{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "artificial-publicity",
   "metadata": {},
   "source": [
    "# Codecademy Portfolio Project: \"OKCupid Date-A-Scientist\"\n",
    "Project Author: Alexander Lacson<br>\n",
    "Part 2 of this project, where the Supervised Machine Learning Section is revised and expanded upon is [here](https://nbviewer.jupyter.org/github/max-torch/OKCupid_Codecademy_Portfolio/blob/main/ml_revisited.ipynb)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "absolute-outside",
   "metadata": {},
   "source": [
    "# !Behind the Scenes!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "super-stomach",
   "metadata": {},
   "source": [
    "This article is a behind the scenes look at the inspection, cleaning, processing, analysis, interpretation, and modelling of the data. It is geared more towards a techincal audience. If you want to see a user-friendly summary, there is a slideshow [here](https://nbviewer.jupyter.org/github/max-torch/OKCupid_Codecademy_Portfolio/blob/main/Slides.slides.html#/). View this project's readme for reproducibility information."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "reserved-toner",
   "metadata": {},
   "source": [
    "# Project Description"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "valuable-bargain",
   "metadata": {},
   "source": [
    "In this project, I will work with data from OKCupid, an online dating app. This dataset was provided to me by Codecademy as part of their \"Data Science Career Path\". In this project I seek to accomplish the following:\n",
    "- Visualize and explore OKCupid user data.<br> _\"Who uses OKCupid? What do people usually share on their profiles? How do people describe themselves?\"_\n",
    "- Use Machine Learning to predict gender.<br> _\"If a user's gender was kept hidden, can the other pieces of information be used to correctly predict the gender? If yes, what information was most important for making the prediction?\"_\n",
    "- Use Unsupervised Machine Learning to create a simple dating recommendation algorithm.<br> _\"Can we recommend who you should date?\"_\n",
    "\n",
    "Let's begin with inspection of the data."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "british-overview",
   "metadata": {},
   "source": [
    "# Inspection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "stuck-andrew",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 59946 entries, 0 to 59945\n",
      "Data columns (total 31 columns):\n",
      " #   Column       Non-Null Count  Dtype  \n",
      "---  ------       --------------  -----  \n",
      " 0   age          59946 non-null  int64  \n",
      " 1   body_type    54650 non-null  object \n",
      " 2   diet         35551 non-null  object \n",
      " 3   drinks       56961 non-null  object \n",
      " 4   drugs        45866 non-null  object \n",
      " 5   education    53318 non-null  object \n",
      " 6   essay0       54458 non-null  object \n",
      " 7   essay1       52374 non-null  object \n",
      " 8   essay2       50308 non-null  object \n",
      " 9   essay3       48470 non-null  object \n",
      " 10  essay4       49409 non-null  object \n",
      " 11  essay5       49096 non-null  object \n",
      " 12  essay6       46175 non-null  object \n",
      " 13  essay7       47495 non-null  object \n",
      " 14  essay8       40721 non-null  object \n",
      " 15  essay9       47343 non-null  object \n",
      " 16  ethnicity    54266 non-null  object \n",
      " 17  height       59943 non-null  float64\n",
      " 18  income       59946 non-null  int64  \n",
      " 19  job          51748 non-null  object \n",
      " 20  last_online  59946 non-null  object \n",
      " 21  location     59946 non-null  object \n",
      " 22  offspring    24385 non-null  object \n",
      " 23  orientation  59946 non-null  object \n",
      " 24  pets         40025 non-null  object \n",
      " 25  religion     39720 non-null  object \n",
      " 26  sex          59946 non-null  object \n",
      " 27  sign         48890 non-null  object \n",
      " 28  smokes       54434 non-null  object \n",
      " 29  speaks       59896 non-null  object \n",
      " 30  status       59946 non-null  object \n",
      "dtypes: float64(1), int64(2), object(28)\n",
      "memory usage: 14.2+ MB\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv('profiles.csv')\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "unexpected-repair",
   "metadata": {},
   "source": [
    "- The sample size is 59,946\n",
    "- There are 30 features to describe each user. Only three of the features are Numeric, the rest are categorical or in text form. \n",
    "- Not all users have complete data."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "legendary-distribution",
   "metadata": {},
   "source": [
    "Let's see how these feature values actually look like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "australian-armstrong",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>body_type</th>\n",
       "      <th>diet</th>\n",
       "      <th>drinks</th>\n",
       "      <th>drugs</th>\n",
       "      <th>education</th>\n",
       "      <th>essay0</th>\n",
       "      <th>essay1</th>\n",
       "      <th>essay2</th>\n",
       "      <th>essay3</th>\n",
       "      <th>essay4</th>\n",
       "      <th>essay5</th>\n",
       "      <th>essay6</th>\n",
       "      <th>essay7</th>\n",
       "      <th>essay8</th>\n",
       "      <th>essay9</th>\n",
       "      <th>ethnicity</th>\n",
       "      <th>height</th>\n",
       "      <th>income</th>\n",
       "      <th>job</th>\n",
       "      <th>last_online</th>\n",
       "      <th>location</th>\n",
       "      <th>offspring</th>\n",
       "      <th>orientation</th>\n",
       "      <th>pets</th>\n",
       "      <th>religion</th>\n",
       "      <th>sex</th>\n",
       "      <th>sign</th>\n",
       "      <th>smokes</th>\n",
       "      <th>speaks</th>\n",
       "      <th>status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>22</td>\n",
       "      <td>a little extra</td>\n",
       "      <td>strictly anything</td>\n",
       "      <td>socially</td>\n",
       "      <td>never</td>\n",
       "      <td>working on college/university</td>\n",
       "      <td>about me:&lt;br /&gt;\\n&lt;br /&gt;\\ni would love to think...</td>\n",
       "      <td>currently working as an international agent fo...</td>\n",
       "      <td>making people laugh.&lt;br /&gt;\\nranting about a go...</td>\n",
       "      <td>the way i look. i am a six foot half asian, ha...</td>\n",
       "      <td>books:&lt;br /&gt;\\nabsurdistan, the republic, of mi...</td>\n",
       "      <td>food.&lt;br /&gt;\\nwater.&lt;br /&gt;\\ncell phone.&lt;br /&gt;\\n...</td>\n",
       "      <td>duality and humorous things</td>\n",
       "      <td>trying to find someone to hang out with. i am ...</td>\n",
       "      <td>i am new to california and looking for someone...</td>\n",
       "      <td>you want to be swept off your feet!&lt;br /&gt;\\nyou...</td>\n",
       "      <td>asian, white</td>\n",
       "      <td>75.0</td>\n",
       "      <td>-1</td>\n",
       "      <td>transportation</td>\n",
       "      <td>2012-06-28-20-30</td>\n",
       "      <td>south san francisco, california</td>\n",
       "      <td>doesn&amp;rsquo;t have kids, but might want them</td>\n",
       "      <td>straight</td>\n",
       "      <td>likes dogs and likes cats</td>\n",
       "      <td>agnosticism and very serious about it</td>\n",
       "      <td>m</td>\n",
       "      <td>gemini</td>\n",
       "      <td>sometimes</td>\n",
       "      <td>english</td>\n",
       "      <td>single</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>35</td>\n",
       "      <td>average</td>\n",
       "      <td>mostly other</td>\n",
       "      <td>often</td>\n",
       "      <td>sometimes</td>\n",
       "      <td>working on space camp</td>\n",
       "      <td>i am a chef: this is what that means.&lt;br /&gt;\\n1...</td>\n",
       "      <td>dedicating everyday to being an unbelievable b...</td>\n",
       "      <td>being silly. having ridiculous amonts of fun w...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>i am die hard christopher moore fan. i don't r...</td>\n",
       "      <td>delicious porkness in all of its glories.&lt;br /...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>i am very open and will share just about anyth...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>white</td>\n",
       "      <td>70.0</td>\n",
       "      <td>80000</td>\n",
       "      <td>hospitality / travel</td>\n",
       "      <td>2012-06-29-21-41</td>\n",
       "      <td>oakland, california</td>\n",
       "      <td>doesn&amp;rsquo;t have kids, but might want them</td>\n",
       "      <td>straight</td>\n",
       "      <td>likes dogs and likes cats</td>\n",
       "      <td>agnosticism but not too serious about it</td>\n",
       "      <td>m</td>\n",
       "      <td>cancer</td>\n",
       "      <td>no</td>\n",
       "      <td>english (fluently), spanish (poorly), french (...</td>\n",
       "      <td>single</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>38</td>\n",
       "      <td>thin</td>\n",
       "      <td>anything</td>\n",
       "      <td>socially</td>\n",
       "      <td>NaN</td>\n",
       "      <td>graduated from masters program</td>\n",
       "      <td>i'm not ashamed of much, but writing public te...</td>\n",
       "      <td>i make nerdy software for musicians, artists, ...</td>\n",
       "      <td>improvising in different contexts. alternating...</td>\n",
       "      <td>my large jaw and large glasses are the physica...</td>\n",
       "      <td>okay this is where the cultural matrix gets so...</td>\n",
       "      <td>movement&lt;br /&gt;\\nconversation&lt;br /&gt;\\ncreation&lt;b...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>viewing. listening. dancing. talking. drinking...</td>\n",
       "      <td>when i was five years old, i was known as \"the...</td>\n",
       "      <td>you are bright, open, intense, silly, ironic, ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>68.0</td>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2012-06-27-09-10</td>\n",
       "      <td>san francisco, california</td>\n",
       "      <td>NaN</td>\n",
       "      <td>straight</td>\n",
       "      <td>has cats</td>\n",
       "      <td>NaN</td>\n",
       "      <td>m</td>\n",
       "      <td>pisces but it doesn&amp;rsquo;t matter</td>\n",
       "      <td>no</td>\n",
       "      <td>english, french, c++</td>\n",
       "      <td>available</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23</td>\n",
       "      <td>thin</td>\n",
       "      <td>vegetarian</td>\n",
       "      <td>socially</td>\n",
       "      <td>NaN</td>\n",
       "      <td>working on college/university</td>\n",
       "      <td>i work in a library and go to school. . .</td>\n",
       "      <td>reading things written by old dead people</td>\n",
       "      <td>playing synthesizers and organizing books acco...</td>\n",
       "      <td>socially awkward but i do my best</td>\n",
       "      <td>bataille, celine, beckett. . .&lt;br /&gt;\\nlynch, j...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>cats and german philosophy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>you feel so inclined.</td>\n",
       "      <td>white</td>\n",
       "      <td>71.0</td>\n",
       "      <td>20000</td>\n",
       "      <td>student</td>\n",
       "      <td>2012-06-28-14-22</td>\n",
       "      <td>berkeley, california</td>\n",
       "      <td>doesn&amp;rsquo;t want kids</td>\n",
       "      <td>straight</td>\n",
       "      <td>likes cats</td>\n",
       "      <td>NaN</td>\n",
       "      <td>m</td>\n",
       "      <td>pisces</td>\n",
       "      <td>no</td>\n",
       "      <td>english, german (poorly)</td>\n",
       "      <td>single</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>29</td>\n",
       "      <td>athletic</td>\n",
       "      <td>NaN</td>\n",
       "      <td>socially</td>\n",
       "      <td>never</td>\n",
       "      <td>graduated from college/university</td>\n",
       "      <td>hey how's it going? currently vague on the pro...</td>\n",
       "      <td>work work work work + play</td>\n",
       "      <td>creating imagery to look at:&lt;br /&gt;\\nhttp://bag...</td>\n",
       "      <td>i smile a lot and my inquisitive nature</td>\n",
       "      <td>music: bands, rappers, musicians&lt;br /&gt;\\nat the...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>asian, black, other</td>\n",
       "      <td>66.0</td>\n",
       "      <td>-1</td>\n",
       "      <td>artistic / musical / writer</td>\n",
       "      <td>2012-06-27-21-26</td>\n",
       "      <td>san francisco, california</td>\n",
       "      <td>NaN</td>\n",
       "      <td>straight</td>\n",
       "      <td>likes dogs and likes cats</td>\n",
       "      <td>NaN</td>\n",
       "      <td>m</td>\n",
       "      <td>aquarius</td>\n",
       "      <td>no</td>\n",
       "      <td>english</td>\n",
       "      <td>single</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age       body_type               diet    drinks      drugs  \\\n",
       "0   22  a little extra  strictly anything  socially      never   \n",
       "1   35         average       mostly other     often  sometimes   \n",
       "2   38            thin           anything  socially        NaN   \n",
       "3   23            thin         vegetarian  socially        NaN   \n",
       "4   29        athletic                NaN  socially      never   \n",
       "\n",
       "                           education  \\\n",
       "0      working on college/university   \n",
       "1              working on space camp   \n",
       "2     graduated from masters program   \n",
       "3      working on college/university   \n",
       "4  graduated from college/university   \n",
       "\n",
       "                                              essay0  \\\n",
       "0  about me:<br />\\n<br />\\ni would love to think...   \n",
       "1  i am a chef: this is what that means.<br />\\n1...   \n",
       "2  i'm not ashamed of much, but writing public te...   \n",
       "3          i work in a library and go to school. . .   \n",
       "4  hey how's it going? currently vague on the pro...   \n",
       "\n",
       "                                              essay1  \\\n",
       "0  currently working as an international agent fo...   \n",
       "1  dedicating everyday to being an unbelievable b...   \n",
       "2  i make nerdy software for musicians, artists, ...   \n",
       "3          reading things written by old dead people   \n",
       "4                         work work work work + play   \n",
       "\n",
       "                                              essay2  \\\n",
       "0  making people laugh.<br />\\nranting about a go...   \n",
       "1  being silly. having ridiculous amonts of fun w...   \n",
       "2  improvising in different contexts. alternating...   \n",
       "3  playing synthesizers and organizing books acco...   \n",
       "4  creating imagery to look at:<br />\\nhttp://bag...   \n",
       "\n",
       "                                              essay3  \\\n",
       "0  the way i look. i am a six foot half asian, ha...   \n",
       "1                                                NaN   \n",
       "2  my large jaw and large glasses are the physica...   \n",
       "3                  socially awkward but i do my best   \n",
       "4            i smile a lot and my inquisitive nature   \n",
       "\n",
       "                                              essay4  \\\n",
       "0  books:<br />\\nabsurdistan, the republic, of mi...   \n",
       "1  i am die hard christopher moore fan. i don't r...   \n",
       "2  okay this is where the cultural matrix gets so...   \n",
       "3  bataille, celine, beckett. . .<br />\\nlynch, j...   \n",
       "4  music: bands, rappers, musicians<br />\\nat the...   \n",
       "\n",
       "                                              essay5  \\\n",
       "0  food.<br />\\nwater.<br />\\ncell phone.<br />\\n...   \n",
       "1  delicious porkness in all of its glories.<br /...   \n",
       "2  movement<br />\\nconversation<br />\\ncreation<b...   \n",
       "3                                                NaN   \n",
       "4                                                NaN   \n",
       "\n",
       "                        essay6  \\\n",
       "0  duality and humorous things   \n",
       "1                          NaN   \n",
       "2                          NaN   \n",
       "3   cats and german philosophy   \n",
       "4                          NaN   \n",
       "\n",
       "                                              essay7  \\\n",
       "0  trying to find someone to hang out with. i am ...   \n",
       "1                                                NaN   \n",
       "2  viewing. listening. dancing. talking. drinking...   \n",
       "3                                                NaN   \n",
       "4                                                NaN   \n",
       "\n",
       "                                              essay8  \\\n",
       "0  i am new to california and looking for someone...   \n",
       "1  i am very open and will share just about anyth...   \n",
       "2  when i was five years old, i was known as \"the...   \n",
       "3                                                NaN   \n",
       "4                                                NaN   \n",
       "\n",
       "                                              essay9            ethnicity  \\\n",
       "0  you want to be swept off your feet!<br />\\nyou...         asian, white   \n",
       "1                                                NaN                white   \n",
       "2  you are bright, open, intense, silly, ironic, ...                  NaN   \n",
       "3                              you feel so inclined.                white   \n",
       "4                                                NaN  asian, black, other   \n",
       "\n",
       "   height  income                          job       last_online  \\\n",
       "0    75.0      -1               transportation  2012-06-28-20-30   \n",
       "1    70.0   80000         hospitality / travel  2012-06-29-21-41   \n",
       "2    68.0      -1                          NaN  2012-06-27-09-10   \n",
       "3    71.0   20000                      student  2012-06-28-14-22   \n",
       "4    66.0      -1  artistic / musical / writer  2012-06-27-21-26   \n",
       "\n",
       "                          location  \\\n",
       "0  south san francisco, california   \n",
       "1              oakland, california   \n",
       "2        san francisco, california   \n",
       "3             berkeley, california   \n",
       "4        san francisco, california   \n",
       "\n",
       "                                      offspring orientation  \\\n",
       "0  doesn&rsquo;t have kids, but might want them    straight   \n",
       "1  doesn&rsquo;t have kids, but might want them    straight   \n",
       "2                                           NaN    straight   \n",
       "3                       doesn&rsquo;t want kids    straight   \n",
       "4                                           NaN    straight   \n",
       "\n",
       "                        pets                                  religion sex  \\\n",
       "0  likes dogs and likes cats     agnosticism and very serious about it   m   \n",
       "1  likes dogs and likes cats  agnosticism but not too serious about it   m   \n",
       "2                   has cats                                       NaN   m   \n",
       "3                 likes cats                                       NaN   m   \n",
       "4  likes dogs and likes cats                                       NaN   m   \n",
       "\n",
       "                                 sign     smokes  \\\n",
       "0                              gemini  sometimes   \n",
       "1                              cancer         no   \n",
       "2  pisces but it doesn&rsquo;t matter         no   \n",
       "3                              pisces         no   \n",
       "4                            aquarius         no   \n",
       "\n",
       "                                              speaks     status  \n",
       "0                                            english     single  \n",
       "1  english (fluently), spanish (poorly), french (...     single  \n",
       "2                               english, french, c++  available  \n",
       "3                           english, german (poorly)     single  \n",
       "4                                            english     single  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option(\"display.max_columns\", None)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "precise-landing",
   "metadata": {},
   "source": [
    "- The income column has values of -1 to signify missing values. The other columns make use of NaN.\n",
    "- I cannot properly see the 'essays' in a tabular display.\n",
    "- The \"last_online\" column has values from the year 2012.\n",
    "- Some of the columns can actually be split up. For example, with the field 'religion', instead of a value being 'agnosticism and very serious about it\", we can have {'religion': 'agnosticism'} and {'religion_seriousness': 'very serious about it'}. \n",
    "\n",
    "To get a proper idea regarding these essays and columns containing text, let's print out a single user's data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "aging-billy",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mage:\u001b[0m 22\n",
      "\u001b[1mbody_type:\u001b[0m a little extra\n",
      "\u001b[1mdiet:\u001b[0m strictly anything\n",
      "\u001b[1mdrinks:\u001b[0m socially\n",
      "\u001b[1mdrugs:\u001b[0m never\n",
      "\u001b[1meducation:\u001b[0m working on college/university\n",
      "\u001b[1messay0:\u001b[0m about me:<br />\n",
      "<br />\n",
      "i would love to think that i was some some kind of intellectual:\n",
      "either the dumbest smart guy, or the smartest dumb guy. can't say i\n",
      "can tell the difference. i love to talk about ideas and concepts. i\n",
      "forge odd metaphors instead of reciting cliches. like the\n",
      "simularities between a friend of mine's house and an underwater\n",
      "salt mine. my favorite word is salt by the way (weird choice i\n",
      "know). to me most things in life are better as metaphors. i seek to\n",
      "make myself a little better everyday, in some productively lazy\n",
      "way. got tired of tying my shoes. considered hiring a five year\n",
      "old, but would probably have to tie both of our shoes... decided to\n",
      "only wear leather shoes dress shoes.<br />\n",
      "<br />\n",
      "about you:<br />\n",
      "<br />\n",
      "you love to have really serious, really deep conversations about\n",
      "really silly stuff. you have to be willing to snap me out of a\n",
      "light hearted rant with a kiss. you don't have to be funny, but you\n",
      "have to be able to make me laugh. you should be able to bend spoons\n",
      "with your mind, and telepathically make me smile while i am still\n",
      "at work. you should love life, and be cool with just letting the\n",
      "wind blow. extra points for reading all this and guessing my\n",
      "favorite video game (no hints given yet). and lastly you have a\n",
      "good attention span.\n",
      "\u001b[1messay1:\u001b[0m currently working as an international agent for a freight\n",
      "forwarding company. import, export, domestic you know the\n",
      "works.<br />\n",
      "online classes and trying to better myself in my free time. perhaps\n",
      "a hours worth of a good book or a video game on a lazy sunday.\n",
      "\u001b[1messay2:\u001b[0m making people laugh.<br />\n",
      "ranting about a good salting.<br />\n",
      "finding simplicity in complexity, and complexity in simplicity.\n",
      "\u001b[1messay3:\u001b[0m the way i look. i am a six foot half asian, half caucasian mutt. it\n",
      "makes it tough not to notice me, and for me to blend in.\n",
      "\u001b[1messay4:\u001b[0m books:<br />\n",
      "absurdistan, the republic, of mice and men (only book that made me\n",
      "want to cry), catcher in the rye, the prince.<br />\n",
      "<br />\n",
      "movies:<br />\n",
      "gladiator, operation valkyrie, the producers, down periscope.<br />\n",
      "<br />\n",
      "shows:<br />\n",
      "the borgia, arrested development, game of thrones, monty\n",
      "python<br />\n",
      "<br />\n",
      "music:<br />\n",
      "aesop rock, hail mary mallon, george thorogood and the delaware\n",
      "destroyers, felt<br />\n",
      "<br />\n",
      "food:<br />\n",
      "i'm down for anything.\n",
      "\u001b[1messay5:\u001b[0m food.<br />\n",
      "water.<br />\n",
      "cell phone.<br />\n",
      "shelter.\n",
      "\u001b[1messay6:\u001b[0m duality and humorous things\n",
      "\u001b[1messay7:\u001b[0m trying to find someone to hang out with. i am down for anything\n",
      "except a club.\n",
      "\u001b[1messay8:\u001b[0m i am new to california and looking for someone to wisper my secrets\n",
      "to.\n",
      "\u001b[1messay9:\u001b[0m you want to be swept off your feet!<br />\n",
      "you are tired of the norm.<br />\n",
      "you want to catch a coffee or a bite.<br />\n",
      "or if you want to talk philosophy.\n",
      "\u001b[1methnicity:\u001b[0m asian, white\n",
      "\u001b[1mheight:\u001b[0m 75.0\n",
      "\u001b[1mincome:\u001b[0m -1\n",
      "\u001b[1mjob:\u001b[0m transportation\n",
      "\u001b[1mlast_online:\u001b[0m 2012-06-28-20-30\n",
      "\u001b[1mlocation:\u001b[0m south san francisco, california\n",
      "\u001b[1moffspring:\u001b[0m doesn&rsquo;t have kids, but might want them\n",
      "\u001b[1morientation:\u001b[0m straight\n",
      "\u001b[1mpets:\u001b[0m likes dogs and likes cats\n",
      "\u001b[1mreligion:\u001b[0m agnosticism and very serious about it\n",
      "\u001b[1msex:\u001b[0m m\n",
      "\u001b[1msign:\u001b[0m gemini\n",
      "\u001b[1msmokes:\u001b[0m sometimes\n",
      "\u001b[1mspeaks:\u001b[0m english\n",
      "\u001b[1mstatus:\u001b[0m single\n"
     ]
    }
   ],
   "source": [
    "def show_user_data(df, index):\n",
    "    '''Takes a row index and prints out all the features of that index'''\n",
    "    for each, col in zip(df.iloc[index], df.columns):\n",
    "        print('\\033[1m' + col + ':' + '\\033[0m' + ' ' + str(each))\n",
    "show_user_data(df, 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "external-champion",
   "metadata": {},
   "source": [
    "- The text data is formatted as HTML. This can be converted to normal text using an HTML Parser and Regex.\n",
    "- The unstructured text data of the essay questions should probably be analyzed using Natural Language Processing."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "occasional-onion",
   "metadata": {},
   "source": [
    "To find out how long ago this sample was taken, let's look at the range of values of **last_online**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "bottom-family",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2011-06-27-01-52\n",
      "2012-07-01-08-57\n"
     ]
    }
   ],
   "source": [
    "print(df.last_online.min())\n",
    "print(df.last_online.max())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "indoor-chaos",
   "metadata": {},
   "source": [
    "### \"This data is very old. We can only make inference about OKCupid's users during the year 2012!\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "forbidden-grenada",
   "metadata": {},
   "source": [
    "Finally, before doing anything to the data, let's see which features have missing values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "developed-information",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Missing values per column\n",
      "[(0, 'age'), (0, 'income'), (0, 'last_online'), (0, 'location'), (0, 'orientation'), (0, 'sex'), (0, 'status'), (3, 'height'), (50, 'speaks'), (2985, 'drinks'), (5296, 'body_type'), (5488, 'essay0'), (5512, 'smokes'), (5680, 'ethnicity'), (6628, 'education'), (7572, 'essay1'), (8198, 'job'), (9638, 'essay2'), (10537, 'essay4'), (10850, 'essay5'), (11056, 'sign'), (11476, 'essay3'), (12451, 'essay7'), (12603, 'essay9'), (13771, 'essay6'), (14080, 'drugs'), (19225, 'essay8'), (19921, 'pets'), (20226, 'religion'), (24395, 'diet'), (35561, 'offspring')]\n"
     ]
    },
    {
     "data": {
      "image/png": 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Pdc71ybLseuz63Qorz36K9WDvCZyHNaZ9ArzbyDh9sbsf1nB3MNZh6p/5CIXC/6WHb3jZHBgDvNHIuFKQdyZzznV3zs3vnOtWqEfrntME/DHNE+w3A3thI6gnBA1MpEX0CB2ASC1c4Y3yzrmvAw9hLzC6Ebgzy7KpWZZd5Zw7Evi5c24H38u4m+8F8Vfn3DRsaOlvnXN7ZVk2NNz/SFLiE+tZMSHiK1E3YkNUz/Nfuwx72dsRft0/sBfwjgb6AN/0vW0aEeOqWFJjIazS83fgk5iSOM65RbMs+9D3npre8yIWzrmlgNWB5YD3syy7PXBIM3DOrQTsjM3t/xJwZZZln4SNqsJXfP8GnOmc+78syyaGjqmac24zrHHsFOfcPTFdIzD9GXczliR4E0uCRMXHOAQrX+4GvBI0oA4459bGGjfXBD50zl0HXFs9F3MozrkVsQTWgsAw4B9Zlo0PG1V7viHlt75MNdY59x6WZOuDzYm9ODAi/75P6OTPyy+AG5xzT2Dvx9kcS9a15Asmq3obzg3Mk2XZKJi+37rFcm7GqHjeFM+fLMs+cM5d6n89wTmHb+Qhy7J/Oef2xBK0Cxb/vUaeg4XjvAFWnrgOGOLLPk9hSeBL/Hd+kmXZmEbFUi0/D32S9Q9Y+fREH9PlWKek/s65C7Msu8E59xrWkLoq9jy61v/944FPgbq/V6h4LfjjNAG42sf8NvAb4B/OuW9lWfaY/2tzOefWz7LsMefcGq3ekcrvw7wh5RrsPJzqnLsCe9Z83Kr34maSXyfOud9iIzn2BV7KsmxCnjsJeZwL95tuhVh13knTcDqXJUU+6fVBoeV9K6znxG7Y8OMtsTlBHwZ+DZyKDW/cK8uyl51NG5MV/v4xwOpZlh1T9v9F0uQL9XsCi2VZdrFfdzcwLMuyI5xz82Nzgx4F/Bi4JE8iA4dhFbtRwL0NTLBvDNyBJdf7Actgw3n/CFwRQ2XDObce8F/g91mW/dCviybR7pzbCLga6wGyNJZI+m2WZccHDazAJzZvxCrF82Bx3ppl2T5BAytwzl2NDSf/FBvVcVWWZZPDRlXhnNsUuBe4Ejg1bwSIJcHlnFsTeBD4K/aC7hl644WuoPh9eD9wLbAYsBLWgBhNot1fz7cDT2EJ7K2xxPCuWZY9HTI2mH4t34YltubB9uOz2D37TxHdF48CBmZZdnp+3vmk5UQs0dUGHAI8ObNz0jn3f8BqwEZZlk0pI/aYVCXYLwHWB9bCrvW7siz7rf9MyYcOFPeLc25zKi+Qvwt4I7PRq4OA72HT9V2UJ9r931kmy7KG9rjuIOZjgcuAkcApmU1fmX/WC5ta6RLsXv/zzPewb3BM+TU8N9bA9y2sB/t9fn1frJF8LeD3wAW+saz4b+yE9crfGdgiy7IX6hxj8VrZCFgKm2ZxeJZlI3y9bmOs09SSWFLxfay8sY///metfB0VjnNv7H1Qk7GpLNfHGkv+BJyfZdko3XPS5+99twOXZln2J79uSayTwTzAO8CF1ddyCXHlSf6+WP34faxOELysLVI3WZZp0ZLUAiwP/A74tf/9QKxi9w3/+7xYIfE24CPgZaz3Xxvwy6p/y3Xw78+wTouW6gWb+/EXwBTgbKyH+PtYsiD/zvzYi5m+wip4fUuMb2Esof5bbH7Mvlgh+glsrtyLgLkC78MVfIxfYI1k5xY+6x7BMV7b30MuxSqXqwK/9PeSI0LH52Ncz++7S7FGlHmxZPYU4Guh4yvEeQjwgL93T8Uan+YOHZeP7etYZfM3WC/S4mdBnweA88t5WJJjkcJni/nnYf88TqBboDg3Ab4EfuN/38dfJweGjKsqxiWxUQCXAfP7db183MeGPu7AIH9v/h3WULYw9tLQ4f4eeTbQI/R+rIp5bqxRZRn/ew8sYfM61pP1a4XvLop1gpjLn9P9gfuAu8t8Nsa4YAnN94EzsSlD7sUaJH8fOrYUFmy6kElYw1kb8Bb2Ut0e/vNBWPK1DevwkP+90u+bQG8smdkGXA8sXPV5L+BI//mljYoNezfCwoXfuwE3+PPuA6wRDaC3/7MP1ngxHEtc96mK+XKsfLl6A2LtVvj5r1jHkbFYx4J/AhsW/g+bAP/z++81rMFyvdDnaOgFX6bGpqdcFRvFsVTh879QKUsu4tepPpzwQqUh6ofYiIXDgPHAc1hZ6EPgeyXHlJ+H/X0cD2PTzfUMvb+0aKnnEjwALVpmdwHm8xWSj3yBr80XSPv4z/NCc1/s7fa/xXrztvmHzYqh/w9ammPBhsT/AUsafgqs5NcXKwTFRPvxFJIJjSzA+grUB1Qan1whnuuxofwXEChpgyVnLvAx/gDrLf4ZkSTa/X66DXsh2UKF9Uv7guFN1cc6QIwDsSTV1cCChfUbYMO3VwCWDhVfVaybAuP8n3/BGgGOAvpVfa/U/ekrIR8Dz1St399f2//DXmi8TsgKJ9ZD/PeF33+GTQv0JZbMvDSvpATYh1v55+sF+f0NS6Q+6M/DhcqMZyZxboclZzbwv/fGkr33YSPdvoFNIZMn5srej7tiPcvWqFq/GZYoGgucFfK+WL1fsJ6rE7Dk2tKFY78BluB6Cdgea7B8Fmtoy59FX8Mat9ZuQIy9q36PNlmEjYjLR1XM7ddt6a+pKygkH2L+f5S8z1zh5wWwl+0e75/PS2IjVd7DpjjJr+elsR7ibf451PB92dk9BCv/XOPv398D5q36vDfWo32VBsW1CNY56YCq9d/y+64NOLKwPn+29AH+7T8/uOrv9gQWaPD+vNrfI3f2v9+GNa48iu/ggiXal8ZewHou9j6u4OdsDIs/r/6FzbF/J5Zw71H4/I9Yov0SlGhPaunoXoONYP63vxcOp9KQ29OfC29jI3PLjnVuXx74D7AGHXT40nmnJfUleABatMzOUqicOaxS14ZVkLv59R1WPrH5qPfFEp37hf5/BN6HwXsUNsNSOBd/hyUZJuJHV/j1xYLr/IXK3dElxbeq3963q2PCejvfhCW4Dwu0/+bFGh9+639fEnvJ1mdEkGjHpjD4HDi8g2N+qS+czhWyIIjNZ3wNsF1xX2HJxDHAUH9ePgDsEipWX+mdH6u8r49V1K/BEu0HA0tgiffSR1Zgc+3nI52+59ed74/901hl9AssYfjtAPE5v/8epTJ663QqPZsPxSrNH2MJhxD78IfYNDtzV60/0T9zD8jPgxDnXyGePYFpwNaFdRv4GN/358BH2NRLeVKptGuGSm/c1arW98eSiBP9fWfngPswv8cUk5zHYI0pT1NJtPfw+/Zlv18/BJ7Jz8/CvXT+Osa2ALBN1e/Xhjznuhj3T7GGsryjyEr+er6+sK7le+J2su+2wUYJ3kmhQRkr8//XX9cnUin7LAtsWlJs3Qs/L++fNSsU1vXwz55JdJBob3BsPYGNCz8XG+m/gTWOvQfsWfw7/s++2KiA4v+vjAaLg4An8+OHNaBMxRrDP8LeUbJBZ8dAy/TONy/6/XV7YX2vws/5fPzX1PP+rKWhx7V4LQ7CRrUu7X+fDxvVcwiwuV/n/D3yIeAn+boS4/0O9r6eVamUKb6Odbj6dX4/otwRRkrqa6nrEjwALVpmd8ESWwtiSY9nscpbMblZfNjkyfe8Qncn1jOxZyveUKv2TUN7nLTKgg3n/waWJByPzVWZf1ZMtPfBpmhpSM+kDuJaEOtx/Tdg0epzAEt6vuArJkGm7cBPMVD4fTlfsP+MQqI94LE9gELSsnAf+SkwKnR8PpaVqn7fEEvG3YpV3PfERi28AqwcONb7qEwnsgTWa2oK1sNmKPZ+gxBxrYw18LRhDRLDfSUgn1JkDayn6ROU3Cu7cM6dgSVYdwDuwYb95s+3/th0Mp8RaBqjTp673f1z+t6Q510hrnWxXpAPYu9pOdxfK38CNsJ6d17q9+MvA8T3DX8O/gToX/XZLVhS6V3sfQsh9l+eqOyDjaTYqfDZ0dgUHU8Dg/w6h837+iP/ef7sqXtDkN/W5v46vdSvexNLKEWdKMIay973Py+DjVi4ET/KB9gPa6SPYkRILIt/hryJvdvmf4X1vfyfC2KJ9rexXs09qv5+wxI4VffD3/v74JfYaK4L8aM3/D0yT7QfC8xX8j7sjpUB/4WfHsav3x4rP75G+0R7r+q/38DYelb9fhD2Qnf8vXsC9p4tqEzj9198IlHLDPszL0usgZVz2oCTOzq2/nlzZyOvES11O67Fe82V/pn3GfbOh5M7ev5hjY1XYnWD5cqM0f/+Q2Cc/3lxrDwxyd/Pp2DTzZVWL63ah3lHAJ37WmpaggegRcucLthUCYv5AupI2ic380p+dYHwr1jLbdC5qAPtr+JD5DdYr8e6z53YzMvMKhS+0PJXZky09/EVglLOuarjfKIvSB9HYfg8lWTJhr7it3vJ+7G6sluMuZhoP6+wfi1gR8rpMTVX1e/dqn4/GJseaADtp+EZ2OjYZhUjVqG/kUKvOKwH3WTg+yXGV5xSIi+0nk0hQQis4vfjV9j7DUpt7KF9I9iq/rwbiTVOtJsyBEs6TAO+E2gf7oAl327BRqBsVrVve2LJpKtD7cOq9XlC9aSy91tnsfifD8USDEN9WeB/2Nzn+fHugSWXHqCq/FBSfFdhoyiOp9IT7RB/H18Oe6ngSGCJEPsQa9B5we+3X9M+MXMMlUT70rP6vzYgxsWwofBt/lq5C+vNHkVluYPnSP7sOMLfn3+A9WC/Cd/IgjX83OzPi5aet76TfboP1uu6DdijsD6/Ly6AJZHHAesEiO86rNH2WGz6l1/75919VKat6um/1+bPhYaWcQr3ut7YtA3HYwnrq2jfIWMHKon2PRoZU2Gb3YFlq9YdUvh5INaT/jms4TlviFoO6509BnvHQ+8y4o15mdm9FitPD8FGevygsL54P+9W/FNL3As28ukDbBrGI6g0PP2J9g1op2LlyJHAWiXElT/n+uFHBmN1z3exBtKnsCmKvou9t2UPrF66TaNj87EUy1+/wEZYDwh9PLWkvwQPQIuW2V0KN+y8AJBXQqoT7bv5h05fbLj9IGz4459D/x9C7TP/89+wBMPP8D3Oqr8TKMaoh3VWPYj3xXrn/QLreZYPo12eSo/2S/zvv8eSTMuUEGPxfQR5JfMarLfmgcw4ncOyWKX+kEbH1kGMc1PpceaqvrMc1rP4U6yH7pr+nL220edpJ/FVJ0f2xabrmA/rQbk0lng6M+A+nCGpXfh9SSzp9KNQ8fnfN8V6zsyPJT9ew6bBuNWfoydQXmIzj7FP4fodjCW6lu3ge4OxoemlTK/USXx5ArGNSg8+R+VZeD9wTRnxzeQ8rL6WV8EqUNd09HmJMfYr3BPn9/v1BuD6wnfzRPIdWM/OhicXaH/P7oklsa/2x3gY1iutDfih/943sB5fpc8zjCXlHsOSMytSSdYVn41HY73RnqAqWVZSjMthCdU24KrC+qAvjK3aRwtRmJ7Dr7vPxzyEygiapbAEyXCqRiy12jKz+wZW1n8Dm3Jnx8L6/HpfiJKSxFVxbYslMXejfRl8FyzR/hfaJ7z/TINHmxXuNwP8/vqmv+cchjX0XE37RPv2WKPZWGDLEvbZZn57+/vf/4X1bC2+oHNNrLywS2HdjtgIr6MooWdu7EvhvOqLTS93A9aQcxi+AwY2smuIf878oPB3i6M3lWBPYAF28s/dbQvHfkX/TPktlTLkAGyO9psa+Uyput91w8qpd+Gnb8PKjNthIwdPANYsfH9nrCf7mo2Krxhb4eeb/HbPpZAb0aJlTpfgAWjRUstCx4n2W7EE6JfAaYXvbgWcX/i9FaeLOR/r7bgRvqcHlZe/lZLc6iSu4jD0I/C9NGNZqh7E12JTDjyDzVv4HDaMNd+feWL9S6xnzYc04MVuM4m1OzZkNn8x54JYr4U8iVmsrKyG9Twsda7pQow3dPBZXglcmkqifRI23UlpowE6i89/fhDW86sPNmT9f1glv7QRMh3F2Nk9DasovwBsFTi+lbDGkq2w5PqTft0iwD+waTzKnBey3bXi1/Uv/FysKOzhr/sQ+/DmwrpfYRWn96nMxd/N33feAH5WVnydHefq/YdNr/Qlfg7gspeOjrNffzVW4Sz28loJm0e8lAazQnwPA9cV1n0HOAd750f+8upuWBL7cQL0tMISch8Ur4HCMS4mkY/BeuOX1qGhEMem2Ei9y/11cnnhO6VNF9JRbP7nP/rz61Ms+bW6X78CliT8HEu2Xo01mo0CBpd9rGNaqvbfilj5dTsKHRewF/C+gvVqLybaq6ccqfsxx5LUW3Swfj8KL/alfYPoj/z5+fUS92PeiNjdXx+P4xNtWANfZ4n23bBRmg3vCINN3Xab3zdPY/WV9aq+sxDWC/Y2//sgbOqLv1df4624FO6F/bGk4etY4+i7WAPkf4CF/XfW8feZdyi57KClpmNc3fHnaKyuuaz/fXmsYewGKi/TXsv/OTdV09HVObZ1fTx9qtbfB5zVwfenTyPnr/+HKamTQyGGK7C68Cb4EWNl3O+0NPcSPAAtWmpdaJ9ov5LKW7RPmtXfaaXFF7geppA8wCp212JD439HCS3HHcRVHIb+JPaiwUNiLCxjFeT3qbx46Re+MvAeNoVInmhfDOtRcDQl9GCvirEv1uD0BH5+T39t/NHHei82HcbRvuD9VNmFiUKMj1PptTdDchXY3cf8PwrTOYSOD5vn/AtsyONjFBoAyjpvZxZj4Z7osJ7E/8OSiWUWWmeIz6+/1x/Tpyj02sN6F7d7h0bJMS5QtQ/z881hjVFPYZXTUPuw+GK6n2A9IccAF2OjZp7BGi5KvW925VoGNsYaJP+PAFNezORc/L4/Fy/CknZ7Yi+YfbzM/Uj7e/aCnXynB/a8fgarODfsGsESL3t1sP4ULAncbs7SwjXTp/Ddb1NOUq6zl90vifVIa5do9591uI9LiPUyLJl1Ppa0bMMaF9fxn/fC5uu+DWtw/BUBRizEumCj8d7HOgy0YUmRcwqf54n254BvlhSTw6ZZuZdKWTa/Hg7FRj9t6X/vXvhsHayHdmmjCP1258Z60t+FTbVTnDKtmGi/ikKivfCdMq7pFbFnWxtwemF9fr+ZC5vy4lNs1Oib2GiptUKfoyEX2pdRewC3Y+XT5fL9h42GG+mP/7x+/ZrYiKlbG/lc0VK341zs9LW4//NnwBj/82LM+F6P72D1/6UaHFt3LJfQhjW2F8sET1IZkVfdSDAv1gnsMdq/IL2M0YRLYY2zR1at+yU22mgPNH2MljlYggegRUtHy+w+6AuFr77YnH0rVn/Wagvte5bNhU1tkQ+F+jqVeRgfw1qNJwNnhShk+eP2MtaTa0M66FUf+jhiw/GewffiwxJdU7Beza9gPfy+S6CXiPqY8grcRtgUNQdXfX40Vhn8AkvI/bNQmCkl0d5BjAd19B1gAyojBspMsHclvq2xyvO7/poqO8HelRgXxBqrHqnah2VOgZHHd2Dhs32xJFOH74Mo6zrv4j5cCBtZ8yiWuCmz4D/T+IBdsYazD/0x/isdTN8Reh8WvnsXAV6A2oX9eAGVKXjewBqjStuPXTwP58YaAJ7052GP4t+tZyzYtDpvAD/p4POD/X76Wgfx98Qae3as+juNnIM9n6JobqzX8OHYtE75dbo0Nt1YG5WXoS6NTVPV8F721fcJbOq27Qr7bD8f2134+bn9+h71PrapL8C3sPLWadhIqI2wubfHAn8ofG93LOk6jE7eC9CA2JbDJ5OANQrr5/WxPNzBubAxNnXaTmXEWNjunf6cexffAYQZE+2HYg0Zt+Mbn0uKLa/HbYn1rn7Qx3pQ4Tv5va8/Nq3EJdjc7C3bGEXHL7YciJVNT6natz2wd+OMo325bDmqGom0xLfQviHlRuBc//N6/l54HTYF6HXAPP6zRbHy4W0U3tXUwBgXpjKa+zisft8L64z2varv5uflkVge4hoaXN/r4F68Flb22glrnD8QeyfYG9hImilUlWu0aOnKEjwALVpmttDJnMidfLejnrAtV1io/j9jvac29j+fjSXTR2O9gE4rPNDuAu4MFPMpWCJw2UJBb21smOpBIY5nB/txVV+Y74Ul1sdTmTdyY6yH39NY633PkmKsHv7usJ4E/bB5hR/A5r4uNrj0xno6zA/te+2GjLGD7+yKJQ8bmsCew/h2xCp/jza6QFhDjAdjFembGx1jF+NbsPBZw4aq1nkffgfrUff3SPbhAh18rz/tezbFdh7m9/PFKKESPxv7sbjPtsR6d65PIRkR0T4chD2riw0pjTzOS/s/ewPbVu2nsdiIhOqXE66CNdif2Ki4/HYG0z45NC/WC/ND7J78AdaIl48qW4pKj/YXsXmoX6DBz2jaP3OX8cfweWBdvy4/z/b2sf2bQqJdS7t92dvfg/9JoUchsDg2Z/0Y4IjC+n3wZbMGx1WdrMmngNkhPwewjhcTsKTxSv46H4RNyfIWsFjJ+3IhKu95OJfKXM3F+2FPbJTPkOr/Y0n7sSc2Fd/a/ri3UegwQlXDXfXvrbQAX8M6+axRtX4QVtc7ubBuekcLrBHqKv97MXHbsvsy1sXf/9YqHiOsYfk1YFe/bj6s1/VEvz6vNw3Cyg0fAquUGPNC/t78JfbS53kovGuh8L28Dro4NoJlhunnGhjjIoWf78BGhw7F8iNnY+XEfv4+fXmj49HSfEvwALRo6WzBeik8TYnzHKe80L43Sp7M2AgbUll8mOyC9QRar7BuEayH8wUhClnY8LLn/M8LYMPGPsXmI20Dbik5nmIFOZ+frRuW0OqO9bi/mErvpUWxFu82rOfSPCXG2hfrvVWd9PiBL2SvUX1+VH2vjEpUV2MsFvZ7U0IjwGzGV6yIHksJCa8aYxxMJZnT0Ou6q/GFXOZwH64d2z6kk2R19e+BY+zs/QBlVJ6ivifO4Xm4QFn3w/z4YT1ZR1KYOgYb7daGTTO3kf+/bItNsfN4I4+v39btfvuH+HVXYc/jjbHemH/HEki/pzIX7WJYsvNv2NyrjW4wKz7H/ow1dr6JNQB8za/vWTiee2MV/P9R4vtbUlmwl/W9Rfse6/kxHIT1kOzs/SlldsxYBeusMh7fQx1LLh2D9Vofh43OewF7X8/gBsfT4X0M62Dxho9hPyrPk3aNtYXzs2H3Q9qXtdfG5nMuTum1LjaNSRtwgF/X199/zi77GMe2+PP/nA6O38JYo96jVI3s9stTwF9Dx69llse3Ozai4xlgI7/O+fvKCHyDnl+/FPbyzo+wDkq3YaNohjf6XtNJ7HmifQrWQe0Tf97dh3UmeBgbnfcK8IvC3yujTvpnrGE7fydFH+DH2Cie4jtnBvl9f1zoc0FLekvwALRo6WjxhYDjsSE7eaVklgWpVi1sYQnJf1PViwzYButhvQidVH6xiukfsYR2w942XthedS+UHsBRWCVqCFZhnoj1pFkHq9R/XCwolhUf9uK5P9J+7uj5fOHmksK6dbDheQMp+a3k2Eve2nxB6qcUXqQFPEsEL4OqJcYyrunZia86nrL2bY0xllFobarzsHqfaR8qxhjiK+N+WNjWJtiUA88B3ymsP5PKnMkTsefhfylh6jFgM6ys8yk2WucirENGnhCcB6tAD8cS7XmP9lLu27RPdF3g4zgNKx/kU4zlcyTPVYj7QCwJu2So8zLWBRs9eD+WoBmYH08qyeE/YZ0c+jb6+sDqJrvRvuHpRnyPYWx+6zv9dfHNQvyDsPLk77H5xJdtcJw9CtteHWsQ60Ol53r+8tAPsBFb01+KWvXvlPV+lKux+fbbgIeAwwqfrUulR/tf/M+TaPGRH7Svq/TBkqp7F9Yd7vfZpRTqdtiIirfoYEowLfEt2Du0RuEbk/26Xtiosp38PSm/3gdiU8vd6JcfU8J7wTq7T2C5hz/48/AzrFf9H7Fn9JXYSPtLKLkzJTZ16lfYqLwOp5oClvAxvlvGPtTSfEvwALRo6WzxhcCPgIu7+P1i76FT8HOVtcKCTWXymi84HV1YvxvWy2fujh6CWGX/Tl+4XauEOPMKZW+s0jTI/74MVhG9y8dUnJ/0KOylJAPLis///Dds6NjZFF4Wg/UCuhN7Sd3O2EsR/4wNwS19Ggwf0zZUGiPew4ZVfwO4HuvJks+9GWxe+9hjjD2+FGKMPb4UYow9PsXYnPHRPjlcfA5ugJUrngf2K6zfFEvOnQDsQCVJV0bv8I2xlxCPwZLtq/v1eUK9H/ZM/gAbJTd3Z/9WA/fnYljicI/CuiP9vnwRWN6vKybag5QfUliwF/u1YZ0vij2d+2Ivj/1bScd1fixJNAIbHXEr1pBSHBlaTLSXOue6334+8qq/v5d8giWU3sZG4A3yny+E9awfhr0rpbRRrLRPEF/k4zgG60n6Mjby48TCd9bCknFvYdNSBR8ZF9Pi7zdtWK/g3QrrT/frH8PqWD/FGnKfa9S9WkvdjmnxmfddrKxwD9b43cs/34I3NBWe/d2xUUeLU3ivmj83L8IamTudxquMskPV+gP9ffFaqjrxYVN/3Yo1bqwVeh9rSXMJHoCW1l6w3igdJX/zHlGnY8OVB8/q3yn8fJwvVHyvXnGmsGC9Pf6Ltboe59cdCLzR2f7CGiOuoYSXBlFpae+OVcqn+gJz/nb0fGh3XlGeC5uj7RHghs4elA2K9XRf8diUDlrYseT6m9jQ/g/LehAzi0oQsDzWe+VFX9ge7a+Fhs6Tm1KMsceXQoyxx5dCjLHHpxhbIz4fQ/5s7om9F2XVqs83pJJo/85M/p1G9mCvHlmS92hvA04qrM/Ljv2wZOhXZe5Lv+1LsTLBS1SVC7AXKb/lP5veo93/2ZIjMWexL6s7PkzCeoQvh72k7jBstOYhJca0JtbbegKW+FrZr+9W9Z080b598f/SyONMJcHeE5tm4iFsxMfuWE/nL7HemYP89xbEOpNMBbYJcHyXBH4B7FGIfQ1s+sp3aZ9o741NmzVfmeddjAsdJCSx0RKjsNFHuxXWH4qNApnonzPF9/RoDvaIFzpOtN/r73sfAydj7wg7CGsoOxhrSNmt+u83KL48wd7P31+e8/fjvwJbF763KDYKZQqWo5mno/9jA+Ir3pP7Vm/P77e8R/uKft0KWO/7WymMYteiZXaX4AFo0VK4SS+PT7gWPvsGNoT2MP/7DL26qm6Yx2Nvif5u6P9XoH25HjbP2bv+gbsX1kt9dV+YXcwvi2PzNfejhJd0Fo5xf6x3192+YN+GJbOXKh5f7GVmB2C9cKb3uOjo+Dcg1rmwiskfqguytO99s54v9BxDCVPEFPZBH6w315W+gLVFJ9/fG6uMTsSSIw0fhh57jLHHl0KMsceXQoyxx6cYWyM+v81ir9cHsSTNRKx31yKFz7+GJYefozBVRpkLlmQrzi+8MTa/65cUynxUktYDgJ9QciIJ+Cb2gtU2OughjDWqvIb1gNYw9Fnvz+kvI8bKj1P9vh2F9dI+tfDdRieV8kT5P7BOFiNpP3q0+G6kNYF/+VgbnsAuxDYXNr/5A/jpNgvfudDvv6ML18nCwC0BrpMz/bU7mso0GPk9czV/bb8LnFByXNNH5VD1EuoYlsJx7gP8qeqzQX5/vkH7RPsCWB1wwcLfb9me7LTPG0TXoFIV31yFnw/DRnA95e8rj2LTsIzFRoOM9EvDk8OF+3I/rNH4v9hLpw/H3kvxLLBz4fuLYGWgNmD3kvfnn7GRg/N3sH8PxfJGf6YywmxeCi/Z1qJlTpbgAWhpzQWr+Pyq8PvG/sb7HFYZXabw2fX+4TFD74WqG+X3/I3ysAbFHHWLf6HglCfa38JesPSVL3B9BnyB9b4Zi/XAXqzE+Ob2D+J7sV41iwO/xCqaI/EJBawifY5/YN9CpdBdxsveuvmCwGfAT/26jnqyL9XoWDo697BEyDPYcNr/+OviRdonGHpW/d1v+eti21aOMfb4Uogx9vhSiDH2+BRja8Tnt5OXGfJerw9gHRXOxKZheRBYmUplekOsLDGSQi+1ko6zwxIKDwDrFD7/ut+vY2exTxtSfqPjkZi9gK2xDg5PAqt18J3j/XnR0Lm5m3HBplo6CuuFuGlhfWlTP2GJpH2pdGo5pvBZMdG+GiX2iMQSw0/76/Qp/LQNtJ++4Z/YSMxeHfz9MqeMOQybxmQyPhnn48/vN6tiHXLGAceWtf/8n/2wl0ieAaxS1j6Zjfi6YXNvtwG3VX1nEJZob9ejveo70SWWS9yHHb44Ppal+hqk0Ovb/36kf949B+zqr5n5sfeFzUOJ045hZYebsGlsFvLrrvLxvY2Ve7YvfH8xbAR9Q+vzHezD+7DGxZMpJNr9ddQbe8/Dl9goDz2TtdRlCR6AltZbsJb0J7EezMWhgEdhLwWahFVC/w8bEnoU1ivoW/57HfVm/x6WTK45wY5NZ7IdsGFh3UUU5taMYZlZYRirDP/XF7TuxYZWb4rN0b6j/7nUBwnwbazivinte4rshc1v+R4+6e+P+2YUejCVsQ+pJB2eBP5bWN+z8PO3sGFvC5a8/+bGps65n0rP//uwRpN3aP+iqO60b4B6zV9bje7lFXWMsceXQoyxx5dCjLHHpxibPz4qz7oe2EsRbwfW9uu6YWWgD7EkYjHRvilWqW54Mo5KQmluLJmev/zwBgpTCGJz1OaJ9oMbHVfxmBV+7ov1nM9fLNkNSwZ/6M+BjhLt85YVa4wLnUwXOZPvd5pEn9lndYhzZttdn44T7X2BXfzPjU4oFe8bvYET/bUwGdiqcK3n5+a+WMJpvUbG1VmMVev3xRL+n+Tx+Hthfr9ZE5uGYvkSYiyO6nkZq0N9l6rGiEY+M2YRX7Hh9gJ/zx7u74n/rvruIH/veYXCy1BbfSnsw75Yvf42rIfzRqFjK8bnfz4DKzuMwkaW7VP47AjsnXX3EnBedmAVH8OW/vcb/Tm5NDYyL39PwDc7+Lt1vy9iDXMLFH4/Of8dS6BPxTp5zl/19/6ANUqOoWpGBS1a5nQJHoCWEg92wJeQdRDLSthLLt+l/VDPbliF7lxsOpEPsN5UbcCfO/m3DvCfH1qn2BbCKkVPY8nqf/ob7wyVpID7r/ggPgr4OTYCYB4qBeoNsML/UODwCGI+DuudN8D/nhf4u2M959qwRHuejMgLQ2VMEXNGfnyxobY/xuaVu6DqewtiQ8oeoeRhpNi0NPdRmUvzH/76OADrtTSaQoKhcB7Mh1ViLqDxSa+oY4w9vhRijD2+FGKMPT7F2DLxzYX1pn4CuK/qs2KS+L9Yma16XvSGz8GOJZSeB4ZgFfgHsYry7RTmO8eS8Hdi5YiGv2yS9mWws3x8Q/2fm1F5x0wx0R5Nj9iQC9aJYonC79sB3wgdVxeO847Ye46+i/XgzK/XDbGy9jtYOXxB4AosOdbQ0aJUysnFOPtjPe0nYQ1SS9I+EX8EVqcp5XxkxsaohWnfs34/LKn9NrB+/ncK/7eGT2lZiKWnv4YfAJahfUNfcR+GemF2H6wB9h6s7rexvy9O7eAePsjfD28IEWusiz8HX/H78SlsbvM36aTXf6AYb8E6Il4LXO7vJcOBMwrfOdyvf4KwifZtsdFbh/uYi6OL/o6NfBsObNLgOJYFHscaT+bCpuoaB6xU+M7fqCTa5/PrFvXX0Nepekm6Fi21LMED0NKgA2sFgr2xVry9gaX9+qDDo7CKW15wyufce5PCi6vy7/k/T8B6c7X5AuPWVd/r4Qtode1ljk25ks8VGO3bpf2DeCzWE7zNFw43KuzjvPD/FoFfRoe9mLWN9vNX5on2ZX2M72MV6vnLiNNve1O/D1+k8gKrxQv79p/AlljF5GZsKpnVAxzrr+cFLOA3WIUu7/mzq9+3rwE/Kh4HbL65zymhkSj2GGOPL4UYY48vhRhjj08xtkZ8fntn+TjGMONLOrth78X5wMdZ9jRpPbBk+pNUns3zYmW+Sf6zwYXvb+X3c2lzDWPlhBFYOfWv2KjLCVjZtZ//zjZY8uEVChX+VlyAgVg56hqsMelgf/7tPJv/TsPrMrR/ad7VWCPKO9h8w//GGlPysvYGWK/TL/2x/oTCtEYNii9PAPcFrgPOKnzWGzjWx3OjPwf7YaM+nsSSyGV0YCkm2C/B6iPjgDsoTAHjr+mX/P5dt/rvNjjG6SMqqLx7YovC5ztgybl7qOp4U1Z8hZ+PxXowr1U49+bHRi98BdxR9XcHlrUf/fZKaxCZzbiK5+Ge/ljmL7rcgcr7SL4dQayH+WO8JZX3JiyLTZ00Ajii6nx4mxKezbM6j7De4PcWzsveWE7iDmz0d0PPQ38fPMk/T4b6+/A6/rPiFF43Y+WHm/x1c6Pfr4NCH3stzbUED0BLAw6q9WJ4yd9kPsUSxR8C24WOrRDjvljl7l1/s5sA/LDwefV8mpthlcDTO/i36lqhKjwgXvY36xfxQ6H8+mANFVUPip2wOdk29A/grfyD4hlg88L/Y31/PrxAicOTsR4XJ1GpCAzyD+DnKAwdw5IKe2PDvb+PVU5KnZoH65n0it9Pq/p1SwHn+XM0f8nWw8AaJcQzvXcS7QvYPbAh6c/7wkFvv341rEHgfV9gKP6djWjAy9VijzH2+FKIMfb4Uogx9vgUY2vE5//dDl/2BvwQe8ZdTtXLVrFE+zexhHYje64v0sG6ebCE1wWFdXkybH+sR9oNdJDMpJx3uByONUBsXli3KJZA/gLfMxLrVbcj1lAxqNFxxb4AP/Dn2yNUXsLZ5YRv1bk7sIR4/4olbLby18PlVF46WCxrr+rPiZ8DKzQolvz8L04d8jKW4D+dQk9MrAx+LFbHmorVDR7AknXTpzUq6Zjf5PfhGcBPqbwQ9teF7+yD1Q8+w09d1cB48v2Yz1mf74+1sDrzcVjHoEt8nP8G/oclPxs+Mhirtx3TwfpzfXztptLEEu23+FhvL3w//14Z03v9kZLe1TGH8fXFeoafB/y86rOtgYeIINEOXIzVRfNjmyfal8Y6Jd5P+5ehzlNCTHksvbGG9z2Ar1d95xpgVOH35bGOlIML6xqdaHdYmaoNa3icv/BZcZ/9Gnsej8YaHdcMecy1NOcSPAAtdT6gNmTnIX9jWxcb+raWv+mMxfdoDxzjPljvip9hvVi+jVWkRlDo0V64qeeFod9iFZp5S4rzp1jhfwr2cp6tCp+FHhHwHWwo+Z9oP+xyMDYs61naF/7XpeTKHTYFzFRs6FZ+LHfAktbPY4X/BX3h5hHgUiwh8QXwiwbFVD0He3HfHYq9KKiYaO+L9ZzbwhdwZnj5bgNiLPZOugp730Dfwuer+wLEfv73fP7ca4B1qBSqGzlHadQxxh5fCjHGHl8KMcYen2JsjfiqYuyOlRP7Vn1+mo/xYmZMtBeTmnWvJGNT0UwBvlZY1w1LWL+PT8QV/g8OSyo9SmWO9oHVsTZ6wcpgb1D1fhaszPBfrKNLv0LMfRoYS0ejB6OZIrKD8+h2rB7wJIWRgbM6flX/xo+xOsFCDYx5b6y8upn//WRsrvOfYNMgPIb1OC0jibku1uBVTHg9jHVeWbawvpho74a9KHE8liReh0qdaq5Gx1zYh8OwzlJ5I+O2/tq9Jl/n138Xqw80bA52fw/8Pr5Oh42o+BR739JC2BQXH2J1qVfwSVdgCSwp98MGxuaw58gDwC87+Hw/v9+KU3Lkx30LrB49AbipjGNbiGFJv92D8vOuzO13McZdsfplG/Bjv65YB9wa63k9HP+sDhTnFf6+VpxbPE+0H+TjX5VK/b7R0/IVG/Sewurwn2MjJ67Bj/rAGpLzF+5e6a+dp8uK029jCazX/BXY9LS/qdqPxY6KS/r7ZqlTv2ppnSV4AFrqfECtAPUusDOVFvp9sQrMyf73vEJXeqIY65n0X2y4Tr/C+pX9+o+BHxTWF4d4nYklQOt+Q2QmBWRsOpEp2FxfxUR7b6wXecMKqlgPuP2r1m3vH7KfUOjZXziua/lCwhNYi3NpQwWr4lwAG2L7AT6BXoj/P/7/0OYf1o/7/bm8//5BjTzGFObvp/1LTb+L9RR4gUJPpLKuFWbsnfQ/4NSqGPtjQxvfwSp3O2AVrb935Xxu9hhjjy+FGGOPL4UYY49PMTZ/fPhEOpVnb3/shfJPYj1Jq8sWeaL9IqoS7Y1csOf+gR3tB6w32mgqL0UvVpJv8f+fqcBPGxzjDEkjLLn/FpUESLGMcTxWtlmrhP2Xb7831rnim9jIwdKmzelCjK7qz3uxKRvasN6lnc4PXv13/c/fw8rlxzYizvxnrPf66f73I4CJwHf874f6+O/ApmNp5PsTNvTbOq2wP7bEporYvPC9b2AJphuw5HZvbPrQo7Gk2B+xRHLdY/XbmuG+gXVYegXo739fAau/XItveMLPxe5/HtDgc3FRrGd9G9bJ6zXsfpy/D2pJLCG7PbCsX9cDG330Yn6vanCMS/o/56bw4lJsKtOXsNEIaxTWd/fXxO3YKPFRwMaNjrOw/X5Y3e3MsrbZhZh6VP3ex1+zb2H1vHxO7uKzeivsOX57CfF12BCBdUBro+OX7n4fawBqWMNiJzH1xhLsQ7CcyOpUGsr+5e8pcwGHYA1EzwHXU2jcL2sf+mu1P9YgOg0rzyxY+LwPSqxrKWEJHoCWOh9QS6i34YfIUGn1/on/vT9wNrBwoPgWwBLAF/rfXeEmvBZWKfkQOK3q7y3mH4p1b52nfcXoYKxA+Gv/IMkfwptjvVce8wWvebGW2kdo0Pzhft9c7Lc5V9VnR/nj+haFYZVUEu1rYC32D1HCizyqH6BUhl7Oi1WCh2MjEfLK4FLAmlilZVust43DWsU/oE4jLvzD9EgqyQZHZS7cqwrfK/ZmONV//jQBXnaLFWYewUajLFvYZ8WC4K5YQ0AbNnz18cL3yugtEHWMsceXQoyxx5dCjLHHpxibNz6s48IwfAIOexa+iFWUb8QqwVPxZcPC3zsVS8ZdRcnlRGzk5TPA9wrr1sTKOS/T/mWZa2A92bfEymLvAIs0aF8Wy4ir4CvsWDK7Dd+BpervHIr1dG5Ij1xgRSxZmZf55vH77lMssTAeK8c2fHq7LsRaTFyvRGE0KtYYkQ/tX7Xq7y3cyb/xPf9/PKyBxznfr/Nj9Zb+WFn8dCq9sVfFkpltWJK2IWVtrBz9KPB//vfiXP+TsHnE1wXO8dfuI8B7FKZdwZK1x2KNBDfX+9r21+5w4EfV1yBwPjDC/7wUNqr6xsL/Y29sPudFSzwn18I6dn2Fjfx1+HpIB9/tjU3f8j+/bxuVMFwRWK54DmKNIhNpP3/9D7CGx3uwumkvLPn+P6wRZhl/Th5U1v70cd0PXOd/Lq338ixi6odN4bS4/31uLHk9Gnse53XD4rN63UYd48I2iveagdXnPjY90cf+2pjHr1sEu08+QglTxBSPHzY9zCv+XpOvyzv8fa/q78yFjVLPv9eQxt4O9uGqtH9mzAOcgj0rLvTf6QP8GSvfRPn+AC3NswQPQEudDyisjSVXdwZ29zfAU/1nDhsO9x8KvQZKjq8XVhF9CN8SS/uXof4TG+72Mf4FYX79asAJhd/r8uCmfcH9b37bL2OV4BH+Rpw/nL+ONQJ8gr3cahz+BT0N3F9L4wvuFOaF978fTaVyskphfV45WI0GzQvZSax9gO0Lv+cJhPmwRPtHFKaOqfq7O2KF7o8pzN9Wh5gu8/vop1R6zCyOVZS+on2iPa849cB6tozHKjY963W+dTHmbbDeScWh81sCv/OFg70K58Yu/lrPr59Seq7FHmPs8aUQY+zxpRBj7PEpxuaND+v5+iqW6N3Ix3MXvkyAJTv/iO8dW/V3z8Eq8qUO+ceGet+O9VA+1K+bC+s88ib2Xp5L/fIS8Kj/zsXYM7vulWbaV+R/7/fhsVg5YXGs3PIF7UdgLoQlMh+lAdMbYiMch2FJ9RWwMsqdWA/Cb2LTcpyNfxEiARPttC9j74M19JxOocczlTnar6Pygts9gH9gjVbFF5CWkWD/OZaU6VNYlyeHi1NaboWNphhMITnagH3YE+v0cTWWaJuAjezt7q+DL7BGpveBvfz6fv46Orzw7/TCkuAf0YCENtaLdR7/c7Hn6OFYwv8UrP50I763OtaB6mZs3vu+9Y5pFvE+jCWwp+HrLszYYWgBrJHgceyeOMOolTrFMgDrYPQkvve8X78BVmd+G/h+Yf33qTTafoI1rj3jj/E6WOPPjg3efxdjHaOO9HHe6s/Hho5E6EJcxdFOp1MZAZJPKdbbn6sf0T7RXt1rvFGNKcV74p+x6VUmYo2ieaPYUthon6+w+/p12Gi4zwgwfzj2frXRhX2Yd+jMO3DOh+WXqq+fhtSdaX+//h3WeaAN62l/YuGzAViP9q+we+iD2P0ySA5MS2stwQPQUuMBnLGn7iD/0HgXK2Dl8445rJX8f9gQnoZWnmZ2YwV+hfWgOob2PVrmwZLsJ1F4MWYHf7/usWMvQhkGbIwfRoQV/NqwHknFuc0vwZLFK5e1D6n0XD+m6jvfp4NeQI16sM3sWGDzw7fRfmhjXiCdH+sF9BU2R1qxENQDm5//79S557i/Pm7HEg2nU+k5syiVwtdVVX9nc6wh6iga8PK5mR1n//u3scJMPiQv7530KFYoHEYHjTs0sOdF7DHGHl8KMcYeXwoxxh6fYmyN+Ar//tew5+5IrLf376o+Xw7rQTq9M0b1/5HyE+0rYMnEafgEIZZoX92vfxubB/16LPnYE0tC3UZj5zy/CUtkHoyfusavX9dvuw0rN9yKJUc+pUHJEKxjym5YR5D7sV62d1P10kHgML8fz8MSr8HmScbmEs6Tw1+rPrew5G+bP1//iNURTq/6N07A6jX1TrAX47gFS3pdQWFEJZbsfx1LEK+LNZj9CUvqNCQ57I/rMf78/xM2yne032beSamP33e7Aiv5dT2wuswbwHZV/2Yv6vxuoerzCku83kBlqpVuVJJgD+LrfVij2p+xHvArlXw+9vP7bGcsiTkNn5SuOh8G+fvO+VRGXde9YbRwTY/E7mfLU7kHr+3329u0b8xbG9gTq1MfRKWeej02+mexesdZ2PbK2PPtCX/8pmLPvGlYY8QVWKPKt4FN6ODF1g2KK98H/bDOVWdQaYj4WR4HlUT7aGwkQ78y4quK9WJ/TM/ARnpPxUYn5PfH7lhj6YP++vkrM5lWq8Gx/hD41P+8i9+np/jfHTYq/T5KeO8f7XMj12P5ru9i5a8XsdE9ZxW+0xdrFHiEBuQZtGjpbAkegJYaD6AlfD/Hel7kifZt/M16mL+x9Md6tT/mHyZ5QaFRLwEr3gBXB3bCeld8vbD+n1jL7enY/HeL+JvkCAoVk0bFWBVvf6yicgaVeewXxXqt/JVKD+i8R3nDKyu0b6VdjMowsZkl2q+mxB5LhcLMAv4YruMLCKOAfQvfy/fpt/xnX+BHJVAYTkadez9Q6Zney59v7wC/LFwneaJ9mt+3i2LDzX7nH8S96xnPLPbhXFQad5bCCq0jsALYsHx/+v3chp8TtOTjHGWMsceXQoyxx5dCjLHHpxhbIz6/zeKLBNfGRg7mZYTpIwf958thCfg24Nyqf6eRc0y3m06A9lO2rYAl6qYn2gufLUxlOrrFsDLaZ1RNNVLnWA/Dkl/foIOX1Pp9eASWCHkcGwHZ0GSIP447Ysmjd7CEat7LcK7C987FRl0uXdb510Gs62G9dE+i/QuBFwcGFX4/GpvG6Gng+Kp/Y2N/jh7ZwDjPx3qDf51KubVYnzkCmzZyrN/nY2hcQ8rXsBfD/tz/voi/Hr7Aerx2ODUN1ui0JjYVygM0uCHPb7N67uuz/LG6HFjRr1vMXx9jscTYn3x8o6jj6NWZxDj9fsOMjQJfxxoupifa/fqlmLGRopGNy/k1PYaZJ9q/38nf39Tv27GU8y6IfJ8uhI2cPgUbjXyvvw+O9efraMqdCqgvNrLpQax+/D1/fKcyY6L9YH+uXl1CXNXn3V+BnQq/58nrB2mfLxngr+uGT2/S2fmNTUH0ETZSoY32oypW8TH/kXJHfZ+EzTywsf/9aH+M/4vlxX5Z9f2+nd03tWhpxBI8AC1zeOCslfYY7C3KE6m00hbn6nvRP9wmYXNp3U6Dhrp1EuNBvgD1sb8pTwauLHx+nX8Af4lVTqdQNWy5zvH09w+BhavWD/SFgXxaneX97zdRSbAfCmxX5gPEb/dO/xDpifUcuNbvy2Orvvc9v/4PZTyIC9ud2x+7u/zvm2ENFqNpn2jvhs31+hds2F6xkt/oOVR39Nuc7M/Hn1FJtA8ETvTXz1f+//IR5RRQ88aufljvqb/jK8K+QHMy1kiWD5+eCxv2/yqwTUnHN+oYY48vhRhjjy+FGGOPTzE2f3zYvM0rF36fj0pP8K9jiY9x+GnnaJ88XA4bufcEJZRxaN/b8CKsB/jtwM8K31mGSqK9+KLyPMm9uf8779Hg5zXWy/BJqspWVJWjaWBP107iypNyQ7Hy3/6FGPKy/jf8PtyujJg6iXNff5wWLhz3P2H1kmHAXwrfXYDCS+kKx3sRGjjEH0tkPYP1+q9OGhdHXu4C/MIvjZpvf14sKXhLIbbjsZHID2Ll62LHqnwfzYdNkfg/f76WVt/z27kCPw84Vs5uwzqtLOfX9fLX+z/8/+9MSpjScib3m58XvvM1LOk/1Z+v62H3w1F08OLdBsbalUT7W8xYB1zQ7+v7gNUbGN98/vwcUIzZ/7meP+ar+N/nxhrSGtajvpMYz8amF1u5av2NVBLtAwsx7tToa4T2ddIVsefbM8CGVefojn4fPgBsUvJ+y58dvX0ce2PvLuiJNU6dijU2v4ElrOfHnsNPYg1oje7AWdyH82AjAfIOe8djOaRdsKnwXvT78eeNiEWLlq4swQPQMgcHrdJK+4B/WByHVeI+p/2UGIOwl0Pt5m86+YOwjDlKv4kl0E/FelWsjfW6/xK4vvC9HXz8P6J9D4JGTAmzM9bTuk/V+oX9A/k3WGt8nmDP5wxcHSu4HELjX6BW7IG0p38Ib0ulsLwKlR7t1YWso2jwMCj/oC3GeAI2THm1wrrNsUT7GKzS5/w+fJD280OW0dBzM1YgvQybx/VNf17+gkoFpT/Wc+5nfh82bG7NQlzdCtt+1Z9fh/lru6MXL/XECjsPY5WTMkZ4RB1j7PGlEGPs8aUQY+zxKcbmjw8bCXaQ387Oft272DQmea/vjahMX5P3/Com2hcv/B8b2YM9Txj1w6bfeAYrb/0Lew/KffjkJZb8vwqrPFe/XG05bI7vZRsVa37csSlgnpzJd3bGv7unkfuvk/OsN1aOHo6NVl2D9knhb2Nl2lITNlXHeg8syf4TrHPQq/7306i8r2eGKSIbeR52sK3lsXL1fv73jt4d1KukWHoDz+N712KjAI7CRtH2xsrceaI97wjUDasf3IA1CjW8wYf2Sa9f+uO4SeG4/4JKon3Fss+/qnNwZvebvBFgI+yFk23Y1DwNf3k2HTwXsGfHjlgHtY4S7fdjnet2r/p7CwLzN3BfXoQ9z97395rtqTwzumGjgccBe5Z0bNemgwYFbMTWy4V9VrwfPoR1qvopVVPY0KA6Ke2fs3/FGhbf9+fY1n79XIV9uSP2zHsW2KCkfZnvq/7+3jMWa5CYgk3ptDrWSHYa1vD0of9/vIDlohrWoFd9D8O/zwMrXy2N5W3ex3qy53Ec4I9zG/CLMvahFi3VS/AAtMzmAbOE5bnYkLHiyy57YT2VJlDoqdvB3y+jsuywHkj3UngDti8A5PMu/mwmf7+uMWKF0vxlX3mF8zjaD1M9DevJPBVLYucF1AWwHjcvAEs1aH/1pmo+QmzqnNOwnt/VQ8yKifajSjrvVqLQWwwrsJ6JDTM/Jz/uhc83waZoacNavj/ECrel9PDyMeQvW9qmUHiZGyu0jvPXScPmcO1CfD39NXIv1quh2NumOKR6AawB6GFK7p0Ue4yxx5dCjLHHl0KMscenGJs/PmALrPfWUOx5+x+s928xEbYRlhzpMNHufy+jjNgdS64+SKEnK5UXle9QWLci1uv04Q5irWviq7N/3x/LL4D1qr+HJXpuALZq8D7Ly6TdsbL0klTKs92w3phjsMTgQf7z7am8sLGUsn8n65fEEpujsLL0VVSSw+ti89dv3ej4ZhYzVjb8ALimep/7nw/Bpj9paBkWqz/NjTVItPl9NgTrDNS7EGtnifb+hf9TWT3YN8Km2plhrnzaJ9ob3oGlk/hmdb8pdvBaFmuYOorK/b1RL6ee3hCCjapdhsI0Rf6a7ijRviHWkFLK8fXbvAlryPs5loO41e+7E2g/PdnrwIUlxDMA60B1ctX6bv64voV1NGyXaMdGLudztB9KB9MH1TnO4rRi+bvfTsJG1U/E6sdrFM6DvK66G5boXrqEfdm9sP1/Yknzb2DvhMjfg/EwNp2q8+fp8VhSu1i/bsS7CrbB7rv5ve8h7H5YPOe+jZV51iis+yVW1rmUQA18WrQED0DLHBw06537VOH3/KHcyz/gPsYKNvkc4mX2BnE+jpeAm/26boUH3eJYb6oHKSHB6R8ad2Ct2oP9ug38Q/Yf+MQ51gKfvwDs58BgrIBzI419gVUPrEdFMb4NfRxttC/wFx/Wq2Ct9W0UhlI3KMaFsGG9zxZi3L4Q44WdxDgI641/MfbSlOmVxJLOxfOx3lL5wzmvkPby+/szZtIgVUJ8y/vr9duFdbtgUxA8h40CWYDKfHe/p/zh6FHHGHt8KcQYe3wpxBh7fIqxZeLbFZsWbSJwdGF9cfRZ3qP9Q2CLMo5rB3HOhfWW+xWVBoi9sU4OP/a/9yt8fwka3MueqinsKEwNg80n/RY2JH6lwvrFsWTJ6xR6sjcqNiyBejPWE3wU1oCzFZWy/k5YIqwNG9J/JzaaoYxGnmLDQ/5+m+XwHW2wBp8VaZ/knBvrDPEasE5J515ncw73xTrUjCpeO/6zBbAeqPfiX9pZQpxrYp1BqsvYeXk279HebgrEjo5Hg+P8BZYM/BTYNt/HVddTnmi/hgDvBpjd+01Xzpd6nYf+mr7dX6+jsOfI1lRGpOeNZ/dSSLQ3Or6qbeyHvYNgs0Lcm/pjehHtk8NPY/XmRo8sc1RGIPSmMHUT1slrGvYC8m60vzediL1/7Tb/f+pf0jm4ONYjfJ/CuoP8ve8NfI7B78t8H5dWN/X7cE0sX7JD1We7YbMQ/JFOyjGNON7+2H0T6zz6H+x59h7+xbCF7+3pz8X8hbHzYw25J1Di9LlatFQvwQPQMhsHq5Kozqe9WKbwWZ5oPwmrZL2FvaSn4Q+6TtbfjLXYLu5/L/YIuQib+7qub7ifSYwnY727hlBJEu+NJVn/WYhxeazH0iSswDgUazVt6MtEO4lvD6xXzTsUKh+0T2KvgTUMNPxN2b5g8gaWOFjLr8tbj1+hMGRvZuccjSuwdjSM+idY4bQ4T21+neyH9Uz7mKqeEA3ch9WF43V8wWBfrBfiJf73f1MZBbCP/+58lNA7KfYYY48vhRhjjy+FGGOPTzG2Rnx5jFQSHD/AXvr1Mlam2LvwvWIZbENsOpk7GhXXTOLtjjXAfwkc4Nft7/fdKf733lgngn2q/m6j5nqt7m34HyyB/S0q0wbugg1JH4klY6/w+/pT6twJo/q88+vyaSIfx6aFPBdLHI4HjsUS1t2wDhCvYYnPlQvnYCOnDSkmsfbFEoV5GfpvdJBYxXpDHoNNc3lSWede4efd/PVyEr4M7WN6zh/n32BTEeyOjRz9lHKmY8yv5fOxhGX+HqbTC9/Ly7G9scRTG3BIGfuwg5h39XFOv36r/y+F/8/n+LmwS4hr+r13Nu43e5cRWyHGvliD2cPY6OpjsSTnFKyXcA8qc7SP8tf7EgGO8elYx7n8nQrL+fvLdVRGUeRTeBxPg+vM1cfZXwPDsClN8usnfyfAudjohB5YEvlJrD67if981xJivAjLN7yKHw1V+OxA7H49lEKP9uI5XEJ83bBn3ldYuWDZYhz+5xOx3FLD5vvvJLa5/D24DUu2zzBiDOsIeC+Wu/kHNnLrUxr88nEtWma1BA9ASxcPVPvCSn7D+QlVrbDYEJnLsYL48xSG1NQxlo7mOVsJ6yG+gX+YfQcbktzuRaNYReAarFLa0J7stC/4H+sfYg9SaTHeByv03U7hxSxYD5yNKfTCCRTfXlhPljtoP7VN8VxoaCtt1baOpZJoX6MQ43isN34xxjJHT3TYAw3rsdeG9VoYUPV3vucfyrdQwlCyQqGpG1aw7u9/P8fHOBwraOXz6fbGGtLO7OycabUYY48vhRhjjy+FGGOPTzG2RnxVMXbHnn39/J/rYeW/N2nfc64blZ6wy1NOL8jOeg4/gvXEPdLvz1MLn30dK2ccXEJ8xXLYDVjnhtuxlx5OxXq/zu8/Xw2bJuFVbGqeq2lARZ5KYt9RKW+f749pscfmwliHlnHA5oXz8FvAXRTmS27UfqN9GfE7WJn6bKzX+sX+2D5F+05BO2Hl2neAH3V0LBoQbzHOG/1xHouVX7/E5mh2WLn/Vr++DeuI8SwNGs1aiCnvvTr9JZv+ul4Eq0d1lmifG2sQCHktb4g17I0F9i0ez6r9vmDAGB/BEolHRXS/ORNL+q5YWPddH9/BhXNhLqxT078bcS13IeZrgNf8z0tTeW9Z3tv+MH/NdPh+kkYd48L9bStsCt2n8UlgLPH6U6xH+7vYaKNhwLP+8/zlsus2+hzERiY8Xziu1XOMH4A9Tz6mhE5zVfswP8e2wu7TbVgDT16PzssYX8eS8N8qMz7/8yF+30ykk9FEWO7pMn8O3FrWftSiZWZL8AC0zOIAWSGrF1VDUYELsQrAaVRaHdfEkusH+BtiG/CNBsS0vv8zvzkf6B9ek7DC/v+wQtf1WE/nf2LDpwf7h/EXwJFl7LvCz0sV4nkIWNWvzxPt/6RBc67XGN/ePr5/0b6SUkpBi/aV+PWwF+6MnUmMgwLuwzP8w/VFrHK3ItZTqg0bLZBPDbQYVmj8OeUWCPOh3k9hCZrrsMacvFFnGf8956/l14CDytyPscYYe3wpxBh7fCnEGHt8irE14uskxmcKMa6Mlbmexxrv9/DfXRRL1Hy3+t9pUIx5RX1uLLl1HLCdX3cU1jNtGnBWHgvWYeMRLEnc6Dn2i9PoDMaS/l/D5t6fm0qDyrkUXpKHJXD60IBODtjL3L6gav5qrHz1EDMmaBbBepk+SgcvaaRxvf+re2Su6+PIewcviyWq/4sltJ+m0tt1ZWwKkR0bHWf1v42NPhmGJdkW9XH/zh/nM/x3FsAaofbwx2OhBp+HeTm7H9ZJ6iF/7Z7p92M/bPREdaK9d9W/08hruVjW/gGW+L8X+L4/B1f3Mb/BjA17DX+hctV+7IN1CjrF32f6Y1NWjvH7MNT9Jo8vb7C92t9z8gaTfbH74cn+9/nwCcWq/V9Gg8oPqTw39sWSnL/E5jK/gco0UEtgoy2uopMpdxq0D/v663Z3//smWDL9GQoJVuw5/RtsqpafUHlu/g0btbJwneMrHqcf4nvK+/hex+6Ra3fw9w7H8jcNf2/BLPbha9jo9A1pP2Xajljdf5sS4ivuw+9jvegXxkagfOLvO3nDd/Vow/6U9IJqLVpmtQQPQMtMDo4VrK7BelGMwQpfK/rP+gAX+ALDO1jhZrh/wHTDerJ8jE+E1jGmfJjd4f73bbGK0jlYD/ujsRcbve1//w02NUwbloj9EPhJ4d9rVC+0YiXj79hwvJeoDGucPg0MlUT73ykpSTyb8eVJ7NvKeABXx+gfWq9jhdCH/QOuoxjHYUO1li8rxkKsf/Pn2Z+w3ukvYkPb9qEyH+QLwD1Yz5GxlDjsDSvMvI69iOXnWCPAYz6urQvfmxur7D+CNVaV+WKjqGOMPb4UYow9vhRijD0+xdga8XUS40VYD+w2bGqbjbEyxQgsyfA4Volu5NQh61PoEQrMg5VthmE94T4CLvGf5VNI3IOVWX/l43+eQgN/neMbAOxZte7X2EvchzDj3NZn+v15Ng2cd72wvc2AH/qf8zJYT6zs9b/C94qJ4wv9MV60pPMurwcUG2v2wF4u2QdLUH/i9+nchX34KL58SPsETt3rAVj9aZfC792xxpGXKCSqC59d6M/PTcvYh9X/dx/vUCzx9zcs+TreX6/r+Gs979H+8xAx+p//7s+1x32sk7Hy9irYFJbP+//HXmXGWIivPzbSZDhWJ/kCK/tvjyWDx5R5v+nkvHwWm87kSeBWv35f2k9h0wNrEGr4y3Y7iPF6fwz/z593y/vj3QY8XvjeYsBfsHt7GSOCiw3Lz/v7yXlYzqMHliR+3+/fNehgJA82wvn/sOlb6j3NV3E712Mjya7FnoF5fO/566ajRPuAesZTwz58119Dx2ENortiZYzHS7g+ivvwBqzR7lrsudIf60T6KfYy4Hn893ph9XxND6MlqiV4AFo6OTD2IH4NK/Qfj70gow1LIBbn6P4Wlmy/HhsalRcUbsES7nXtgYH1/Pi7j2V/YDvs5V79q74zxN+kFwOWxObA3hnYoPC9hvfG9g+PMVhlc0G/7qdYIfFBKnMx7uX/T9dRYoFmDuK7oeT4umNDp5/D5qvMe0qd4mMs9mjPYzy/rPj8do/FCnlfo9JzLr9eLve/f8c/qB/CGq7q2vjUhRh/gyU7iqMRzvAxHud/74dVSp+lfa+0spJKUccYe3wpxBh7fCnEGHt8irE14utCjN/zv2+GNX6/io3Ya1iMWCX9OgovZMcSg/dgPYaX9ftrDPBn//lR2HN5PJZI/i0NfFks1nPvUWwKBudj/tDH/GThe8XK/pnYPMmXUOjR3uBj2xtLAG7jfz/Cx3h0B989C0uYlPWeo2I94JDCsd/M//wPvyxc+OwtLPH+DpZ0avT7on7t4zuosG4FLCl8kv99es9/bN7ud7Eeud0pd8rDblQ6VC1dWH8QNg3LK1j5eyBW35p+fZW5YCOnR2GJyuJUIS9jybAlsXL4k/4a/3ZJcRWnLv0/rP65rt9fW2ONn+9h9dUfYnWrUu43HcT3F2x0x2JYD93x/r4yjfYd0NYGHgB+WfIxvspfB5tSmN4Ha0R5yV+/1/j9dg8wGv8usZLim9ufX/f567ln1eebYMntZ6nqSIU1FvwWu1c2bN74zvZhVXzP499vVvbSxX34or/PvIeVG26iUr8uo/zV2XnosNzTaKzcsA/WgaANJdm1RLYED0BLBwfFeq3c5h9geeL1Rqz37UR/Y1y/8P1iL4Ov+ZvTOBo0hyA2NPBvVOYlvbSD76zh453hM/95GQn2vliv65sozG3pPzuJSm/sfA63b1N4SWarx+e3uRBWOT+v+rhhQ+/aaD9H+9aU3+vicr8f+/rfl/Hn3jVUKgL58Mzpc7aXHON/gKsKv+cNEj/yvw/Aetr8CBsVkvc2KLNBJeoYY48vhRhjjy+FGGOPTzG2RnyzEeP8WBJvXsp5CeaiWGeAvCPGGfjh6P7z+f3+GlsV+6Cqf6dRL7Odj8rL+jb3f/bCEnFt2FQY+bz1xfLOb3zMDZ06pLC9dbDE5UQsqTkX9oK/L4BjCnGvjCVsrqHcxPAiWGeeNuCwqv37BvCzwrq1sOTcb4DvlBTfoli9qQ0/ssLvrzeBfxW+V+xR/xxwc1n7sLDdftiUVJf534vTJRyMJWJ/7n9fBfhxmfeZPCas3vdP/3Px2sincchHqOyM1QvKHHnbz2/3fArzwvvPFsZGGj1PpZ6wRNV3yujBvjM29dS+ft1aVN79cF1+PmJTjz2GJePbzZ3d4Bg3wxKbO1Xtu8OwFwXvj70E9WGsAeACYIWSz8O9/TW8ZmHd17GRAT/1P2/qvzMMP52u/14PbE75uk4R04V9uBA21/6h2H19U2wE2ruU+JLY2diHm/gYn8ZyPOsXzsO5Soivs314KNbwuIn/P7yH9Wp/m0ANFlq0zGwJHoCWDg6KvVzp71R6sNyEzWm4CtZz/Uv/+YZVf29prHLzUqNv3FgPgWuw3j03+3XVL7l5GLgz4H7sgQ1v+k9hXXEOzn9gQ8aep+Q3ZqcQn4+hn38Y/7UYd+HnB7AW5Zdp/0KuMhMNdwMP+5/zBPtNVArTh2KV+v5lxdTBcX4WuN7/nidC8mGhPbEGi1MpvNCFknpDphBj7PGlEGPs8aUQY+zxKcbWiG82Yvy5j7F34e+V0cGh2BFjIpUeznnP4XmwZ/IYLBFaPa9qGQmlo318R/jfe2FlrU+w+XHzeZKLZdpSEuyF7W2KJQcnY1MSLY7Nqd/m1z+Mlb2ep9IbN1SiPe/RPgAb5XiD/70fNpL17uL+K+kYF+PLp7j8kf/97KrvLoElPM+mqtNLCXEOwBJF1xbWFcvZ92IJr+rrpMxydk+/fx7oJMbrscRY3tu1T4mxOSojF6YCu/n1xcaKbbH3huUjbIqxN3qu+GJ8X9L+XQTfxOqBn2Ed5P7lj/VTlD8yahfsnrwq1li2GzbKZ7iP/WEKo6ZCLNgc3cOx95gth00TMgUb+d/mz9HFsA5ffy9r383GPnwK6z2+JTaNUen7s4v7cAksmf0BNivC4IjOw8f9PlzYX9elTJOmRcvsLsED0NLBQbFhottgvQWO9QWXTfxn81KZt7vdW8n958uUdcPBeopc72M5toP/w3+wF1HO1ehCTCfxdcOGhn0IbFlYn7fI/t0/VJ6kMERT8bWLsSf2UrXp52Ah9rmx3hYP+/Og1MJMIZZzsQrK/liC/UYqc7Ut7c/BXxPoZSh+X12FVYZ/QeVFrPlxXg+rMJ8QIr4UYow9vhRijD2+FGKMPT7F2BrxzUaM/8PP7x0gvoHYi/2m0f5ljXkyeB5smpM2/AsnS45vUSoJ2GKi/UVmkmgvKbbiqMbNsHJWnmjvgfWKHOLjP6OwT0vt3ey3WUxk5wnM4/1xfxEbkTsJ3/gTOL59/XXzf/73a7CpGnf219InlNwzt3De/QNLIm1aWN/dx/sPAnZYKsTyR7+Ptiqsz8+9i7D6ytyB4lscm4plKnBhYX0+L/cS2PvDQj1T8vi+As6t+mwd4AR/TV+FTWkTYmTUCv5afcw/Oz7D6qgr+HtP9fRLIer1a/oYh2LTKI0BDsFGhm/oY9yy6u+U2fjdlX2Yj2QIda10eR9iifahlNjrvov78IAQ+06LltlZggegpZMDUxnWexM2PK9Y6P4nNq/lnWU+PDqJs1iAPQ1rFV0BG142Bd+7JWB8K2FT59wLbFRYvwCWjN2OQk80xddhjKtiLye7l/YVgBWxCtTahfO19POxEF+bvybyQvXC2Fxt7xDgZaxVMa6JFfDbKEyhhI1OeRQrXIe+lqOOMfb4Uogx9vhSiDH2+BRja8SXQoxYov0mZpxSJE/MzYfNyR6qgb5Yfi0m2l/A5p7+HuEa5ztLtG/s181V9f2Qx7ldItuvOwDrgPF3fC/y6v9XyfHlIyu+jXUeOQv42K/7CBsBvFbAfTgYmwroXvzID79+eawh7TehYivEsjo2MqW6vjI/Vva+LdT14uMYSGWKoKOrPvsa1qHp8BCxdRDfYR18Xj1SIUR9ajNs1Ml5tJ/mazVsipPtQu2/QiwbAldgnRDzqUq7AztgDT0zvFQ0on34BrB9KvsQG4WxJTZaqrRe9ymch1q0zGrJE2MSIedcd6wHw/zALlmWfeKcWwt7cdMPsix7Kv9elmXTAsa5CHApsCdWMXkBmz/rlizLzvPfcVmgk805tw1W+BuOFQTfA76BtdCum2XZuyHiysUeH4BzblussjQWa1kegw3TmgKsl2XZtMDH+BvYPnybygu5NsIK1ltnWfZCiLiKfIz/wHoE/A+r6K2D9fjaKMuyqRFcy1HHGHt8KcQYe3wpxBh7fIqxNeJLIUZfPvwtsDuWyP6TXz9XlmVTC98LEmNVfEdlWfYH51w+d/dXwDpZln1Wdlw+tullKufcZtiovXWBbbMse8g51w0gy7K2EPEV+f14OZbE3j/Lsuudc3NhjQFf+O90CxWrj+932JSb+2RZdrNzblGsnP0eMCzLstEhYss553bEGgPGYg0Un2LJpmlYXeCrgOEB7WIcAdzh/9wM2BxrAHolYHjV1/OlWGNjb2x6qF7Y+8xC15c7uh92B7Isy9pC1qXyWIr7yF8nv8CO8dZZlo0MFVtH/H1mRez6/gKbyzvoPbGZ9qFzzmFTzk0qOaak9qFINSXZI+ecWx8blnwXlkDcDEtsbhayoFDNOTcQm2PzIGxqjl9lWTbRfxasYF2Ib3XgQqwnRnesYHhIlmUvhowrF3t8AM65VbCXoqyDzSv4BvYSq69CJxp8fOsCv8KmTJqCzVf76yzLXg8ZV5FvJPsB1tNwONZ76iy/D3tEUomKOsbY44P4Y4w9Pog/xtjjA8XYCvFB/DFWJZYOy7LsLyHjqdZR4ssn2hfPsuydwLEVE+2bY3OGrw1skWXZkyFjq1bV4ea4LMt+V/gsaOLQx1BsCDg0y7K/hoynI/5a/ik2SmUM8Cr2otsoytkwvaz9a2wU6STgLWwalpeDBub543wJsAfWE/c8bGTrsVmWTQm9H2O/HxY55w4CtsLmjt8ypjopgHNuAawBZTugD/auuq9iyDvkEt6HUdxvIP59KNIRJdkT4JzbFJsLrzs2bHCv0L2TOuKcWwz4E3BvlmUX+XXBC9Y551wf7AHSHxibZdm4wCG1E3t8ML21ey5sPvaxWZZlMVTic865nth1MhUglriKfK+AblUt9LFdy1HHGHt8EH+MsccH8ccYe3ygGOsh9vgg/hirErC7Zln2r8AhtVNIzO2FdXC4OnBI01Ul2jcBLsDm6t4hy7JPggZXxXe4uQq4O8uyi8NGM6Oq47x/lmXXBw5pBr4c2xNoK4wCiKacDdPrK/39rxPyTlWx8OfhucCBwMFZll3j1/fMsuzLoMER//0QwDm3EXAZNiXZsaFHKXTE2Sjr07F5ww+LpWE5p31YuxT2oUhHlGRPhHOuHzbULbrEZpFzrk9eKJTmF1MjioiIiMTJD/c+FnsRaozl10WxEZnnZ1n2auh4iqoS7ecAu2K92T8KG9mMYq8HxHycO6Jy9pzxifbfYiMXDs+y7M+BQ2ongfthN+wda2OzLBsTOp6O+MblJYDhPjcSTcMyaB/WQwr7UKQjSrInKKZhUJ1RoVBEREREqkXcUSSqBEORT4YAXIm9t2fdLMs+DRjSTMVcD4j5OEv9+B7jFwN7AwdlWfZ/YSPqWKz3w5SkkBuJnfahSP30CB2AzL4UboCxFqxFREREJJxYE0oxJ159L8Ne2Dzdl8WcYIe46wExH2epnyzLRjvnfoi9p+mZ0PF0Jtb7YUpSyI3ETvtQpH7Uk11ERERERCRy6m0oMns0ckFERMrULXQAZXPO7eGcu8w597BzbrxzLnPOXRs6LhERERERkc4owS4ye5RgFxGRMrXidDE/BdbC3lI8HFg5bDgiIiIiIiIiIiIikqqW68kOnACsCAwAjg4ci4iIiIiIiIiIiIgkrOV6smdZNiT/2TkXMhQRERERERERERERSVwr9mQXEREREREREREREakLJdlFREREREREREREROZQy00XUy9bbLFFFjqGmbn44osZPHhw6DBEpA6ef/55fvCDH4QOo0MXX3wxgO43LSDm8xD03JN4pHCtANHGGHt8EH+MsccH8ccYe3yQTox6Ntcu5ueKzsP62WKLLUKH0KkUjjPAgw8+2IxzQjck97jVVluRZVGnNWuy4447ctJJJ3X0UUPPESXZm5gexrWJPcZUCgs6D2uTxxg7FQprE3uMqZyHut/UJvYYY48P0rlWRKRrHnzwwdAhzNTzzz8fOoRZ0rO5Nnqu1EcK56FIvY0ZM4ZjjjmGjz/+OHQopbvvvvs6S7I3lJLsEszgwYNVcBURERERkSil0IkgdrHX+VTfq4+YjzHoOEtrevPNN1sywQ6w2mqrBdmukuxNLPYCjdQu5hZ5SKfwLyIiIiIi9RdzfUV1lfpRg5RIfDbeeGOGDBnS4WdPPvkk999/PwBfffUVH330Ec45XnrppTJDbJh55503yHaVZG9isRdoUpjqRES6JoUGvdhjjL2HTSoNtynEGLNUjrNIaLpWRJpDCtdy7GVEEUnPySefHDqEhnr33XeDbFdJdhERqVkKvVdibXSENHrYxNxwC/Ef5xSOcSqUDJEYxHxP1P2mfnS/aX4xX8ug61lEGuOaa67hlVdeAeCFF17g7rvvDhxRfQ0YMCDIdlsuye6c2w3Yzf860P+5kXPuKv/zx1mWnVhyWC1JBRoREZG4xPxsjr0hBVR2EGk2KXQiEBER6chrr73GMcccEzqMIFZZZZUg2225JDswGDioat2yfgF4H1CSXUSikcIwVhHpmtivZfWKFBGRVpJCOVvPZhGZE926dQsdQjCTJk0Kst2WS7JnWXY6cHrgMEREuiyFnqWxUwVKYqFekc1P9xsRkXTEXM4GPZtFZM6ttNJKnb74tGjLLbcsIZpyjRw5Msh2Wy7JLiIirUcVKBEpi+43Is1DDWYiItKMdtxxx2C9vcswYsSIINtVkl0kYeotJyIiIiIiIiIiXdXMCXaAzTbbLMh2lWQXSZh6y4mIiIiISKxi7xSkDkEi0qyyLOPll1/miy++4KOPPuI3v/lN6JBKc9NNN3HUUUeVvl0l2SWY2AtcoEKXiIhIbFR2EBERERGZuXvvvZdzzjkndBhBrLbaakG2qyS7BJNCL+zYGwJUkRcRkVajl8eKSFl0vxERkVRtuummPPfcc4wdO3aGz5588skAEZVniSWWCLJdJdlFZiLmhgAVrEVEREREJGaqT4mIlOfjjz/moosuIsuy6eu6d++Oc67d9zbeeOPpPz/66KOlxVeWTz75JMh2lWSXYGLvJQ7qKS7SLHS/aQ0pHGcREUlH7M8UlR1ql0LZQcdZRLrqmmuuacqk+ewaOXJkkO0qyS7BxNyrAdSzQaSZ6H7TGmI+zjrGIiLp0XQxtYs9iR1z2QHSOc4iEofjjz+er33tawCMGDGC3/3ud4EjCmO++eYLsl0l2UVEREQEiD8ZIiIiaYk5ia0Etog0mx49ekyfCmarrbYKHE04kyZNCrJdJdlFREREBFAyRESkKPZGxxSmEUmh8Tb2+FI4ziISh6uvvpqrrroqdBjBDRw4MMh2lWSXYFIocKlAIyIiIiIiMmdSaLyNNT5QA7OIzJ711ltPSXZg8cUXD7LdbkG2KiIiIiIiIiIiIiJ1sdpqqzFkyBCGDBnC97///dDhBLPwwgsH2a56sjex2HuKx9yrAdRroFXEfp2ARlSISHlSuCfGHh/EH6OeKyIiIiLpeuyxx3jxxRen/55lGQA33XRTqJCi8t577wXZrpLsTSzmJPbFF1+cREVeldDmF/N1AmrskXikcM+G+JObsccX8z0xpWH9KcQoIiJSLymUb0Saxfjx4zn11FNDhxG1L7/8Msh2lWQXSVgKSS8VaESaQ8zJV4g/uRl7fJBOA7iIiEi9pPDcS6E+tcUWW4QOoVNqXJZmM2DAAH7zm9/w+uuvd/j5qFGjAHjggQeYMGFCmaFFo0ePMOluJdklmFQSNjHTPhTpmhQqUBB/L6DY40uhEioiIulQ4lBERGK09tprs/baa8/0OyeccALDhg1r16s7n1bmiCOOaGh8oX3yySdBtqsku4i0tBSSr0oc1i6VBqlYY4w9PlAvbBEREZl9qZQRRUTmxFJLLdXh+osuuoiHH34YgOHDh/Pkk0+WGVbDLb744kG2qyR7E0sh2RB7fEpuNj8VrEWaR8zXs65lkeaSQjlbahf7MU6hrhL7tZLCPkxBzMcYdJxFJkyYwMEHHxysh3fZQk2ToyR7E4s92TB48ODQYYiIiEhB7GUHkVjoWhHpGl0rrUFTK4nEbdKkSS2TYAd4//33g2xXSXYRaSj1XmkNMR/jXOwx6lysXez3mxSksA9jj0/XcmtI4VoRiUEK10rs8aXwXNE+FInbQgstxJAhQzr87Mgjj2To0KElR9RYU6ZMCbJdJdlFEpZCoVW9V2qXwnGW2sV+nFU5qY+Yj7GIdJ3KNyJdE/u1otHV9RF7T/bYy9kiZdt2222ZOnVq6DAaZtCgQUG2qyS7SMJiLrRCGgWaFBKHMR/nVF6ICYqxFqkkbHSt1Cb2GGOPD9K5VkREyhJ7XUBaQwplRJEyrbfeejz22GOhw2iYeeedN8h2lWSXYGJ+0EEaD7sUCq0xH+cUjrHURyrXitQmheMcuxT2Yezx6VpuDSlcK1K72HvnpiD2uoB6sotIK+rZs2foEBrqqaeeCrJdJdklmBQqJ7FXlGMutEI6hX+pXQrXsq6V5hfzcdYxrh8lvSQGut+0hhTKN1KbmK9l0PUsIo3x0EMPhQ6hoRZddNEg21WSXYJRgUZikEJjD8RfyYudjnN9xB4fxB9j7PGlIPZ9qKSXSPNQo17zS6GMqOeKiHTVtGnTZnnPcM5x4YUX4pzDOcePf/zjppuffaWVVgqyXSXZRWYi9kKXCly1S6WxJ9YYY48PNBS4XnSt1Cb2+CCdayX2pFfsZQdQ+UFEJJdK+UZEpCsuvfRSbr/99tBhBPfwww9z+OGHl75dJdlFZiLmQpcq8hKTFM7DWK9liD8Bq/tN64j5WsmvkxTOw1j3IShhIzI7UrjfxC6F8kPs8aVwnEUkDvvttx8jRowgyzKA6X9We+6558oMq3TrrbdekO0qyS6SMFXkJRax9yyV2ul+I7GI/X6TQkJJCRsREaPyTX3ouScSh4UXXpgLLrhglt8bMWIEr776aoef5Yn5hx56iEcffbSu8ZWld+/eQbarJLtIwlSRFxERiYsSNiIiFTHfE9UwKiLN4PTTT2/6F5nOrgceeIAjjjii9O0qyS6SsJgLrZBGwVWFVhERERHpSOwjZ1KQQl0g9vpUCnStiIQzZcqU0CFEZ/nllw+yXSXZRURERERERKrEnByGNDqLxJzETqFDEKRxnEUknHPOOWf6z1mW8dFHHwEwceJEzjvvPMaMGQPAp59+GiS+EDQnu4g0pdgL1iIiIiIi0ppirquA6isiMnuccyyyyCLTf7/yyisBeO+99zjkkENChVW622+/nd1226307SrJLsGo14CIiIg0G5VvREQqUrgnxh6f7tm1S+E8FKm3yy67jFtvvTV0GEH07NkzyHaVZJdg1GtAYpBCgSuFgnXs+xDijzH245zCtQLxH2epXezHWOUbkeaheaabn+7ZrSHm46xjLI2y6aabtmySPZ8yp2xKsotIS4u5wAXpFLpSqITqONcmlWsl1hjz+FJIEMcuhfuNiDQH3bObXwqdCHScRaSrsixj3LhxAAwaNIjbbrttln/nxhtv5Kabbmp0aKUaOHBgkO0qyS7BqEAjIiKtRgni2qnsICJl0T27djE30sfeQA/pHGcRicOVV17ZdAnzOTFgwIAg21WSXURERESANBrAlfQSEZF6SeG5p8ZbEemq7bbbjv/85z9kWdZu/eTJk5kyZUqgqMq33nrrBdmukuwiMxF7oSuFAlfs+xDi7xUJ8ccYe3ygGOsh9vgg/hhjjy8FKezD2GNMofwQuxTKN1K72I9xCteyrhWJgc5DaRXLLLPM9CliRowYwf777x84ojDUk13qTg+S2qUwvDF2KezDWOOD+GOMPT5QjPUQe3wQf4yxxwfxxxh7fGAxDh48OHQYIiLRiL0uoHt2a4j9PBRphJEjR4YOIZihQ4ey7bbblr5dJdmbWOwPEhVoRETSkULDbQo9+rQPa5fCPoy1/AWqzItIuVIoP4iINKP111+fIUOGADBhwgT22WcfJk6cGDiqcnTv3j3IdpVkFxERkVlS4rA+NJ947bQPJQYx3xN1HkpMUrhWYo0PdD2LSH3069ePO+64o8PPpk6dyrBhwwD4y1/+wqOPPlpmaA0xbty4INtVkl1ERERERESkihr1RESk2f3oRz/ipZdeCh1GXTnngmxXSXYRERERERGRKrFPc5LCFF+xTxeTwj4UEWmko446igsvvBCAd955J3A09TF06NAg21WSXYKJeeggpNE7JPZCK8RfcE1hH0L8lbzY4wPFWA+xxwfxxxh7fBB/jLHHF/tzT0SkTDHX+fL3hOm5IiLNaNKkSVx++eV8/PHHADzxxBOBIyrPKqusEmS7SrKLJCzmQiuk0VCRyj6MNcY8vthfZKzjXJvY44P4Y9S1UrvYjzGk8dwTka7TdDEiIpKS999/n1NOOYUsyxg9enTocIL56KOPgmxXSXYREalZ7JVQ9VKSWMR+rYiISIXKDs0v5sZl0LNZRGbPjTfeyKhRo0KHEdznn38eZLtKsouISNNTBUpERERmlxpGaxd7Rwc1VIhIMwn1ws/YTJs2Lch2lWQXERGRphB7RV5ERKTVxNzRIZWGihTEXv5SY4q0iu9973ssvfTS7dZlWdbuT4A//OEPpcZVtrXXXjvIdpVkFxERkaagiryIlEWNeq0h9mOsxKHEQqM+ROIw99xzs/fee3f42aRJk5gyZQoAt9566/QXojajd955J8h2lWQXSVgqFbzYY4w9Pog/xtjjA8VYD7HHB/HHGHt8EH+MscenpJeISEUK9ZXY49NzRURqNWLECPbff//QYZRmwoQJQbarJLsEk0KBK/YCTcy9NqHSayDWGGOPD+KPMfb4QDHWQ+zxQfwxxh4fxB9j7PGBesu1kpjLYDoPJSYpXCuxxge6nkVkzr333nsccsghocMIYskllwyyXSXZRURERERERKTuYu9YFXunKhGROTVu3LjQIQQz//zzB9mukuwiIiIiIiIiVTTPdO1S6MkuItKMevRo3ZTvZ599FmS7rbvHW0DsvQakNcR+HqbQeyX2fSitIZXzMIUYpTYpHOPYY0zh2Re7VO6JUpvYj7Gu5dqlcC2ncJy1D0Xi06tXr9AhBPPf//6XU045pfTtKsnexGLvNTB48ODQYSQvlUJhzOdhCrQPJQYxn4cQ/7yqulbqJ4WepbGeh6BzsV5ivifqGIt0XczXMqRzPafwbBZpNcsvvzxDhgyZ/vv777/Pxx9/PMP3TjzxxDLDKsVXX30VZLtKsoskTIVCka5JoUEK4u8FFHt8EH+Mscennl4iIhVKHDa/FMqIKTybtQ9F4rf00kuz9NJLz7B+wIABjB8/PkBEjbPCCisE2a6S7BKMEsS1U6FQpGtSud/EGmPs8UH8McYeH6Tx3BOJRQplMBGRsqhBSiQOo0eP5txzzyXLMl5//XWmTJkSOqQgBgwYEGS7SrJLMClUTmJPEKeSOBQRERFpJjGXwVT+qh/VVZpfzNcy6HoWkdlz/fXX69mAposRERERkcBSaAAXESmLeuc2vxSee0qYiUhXHX/88Wy55ZZkWQZAlmUz/JxlGSeffHLIMBtOPdlFRKRDKRT+RaQ5xNyjTwklESlb7OUvJV9rF/NzD/TsE5HZ0717dwYPHjzL7x133HHceuutAIwcObLBUZXv008/DbJdJdlFpKWlkMCOufCvgr+IlC2Fe7aIiJjYy9q6Z4tIK/jkk0/YY489QodRmtdeey3IdpVkl2BiThyCkoetQuehiEhaNH2DiJRF95vaxVzWTmUfiogUffHFF+y0006hw4jaGmusEWS7SrJLMLH3agD1bBARERERaVWqq4iISGx69uzJ+uuvz1NPPRU6lGi1tbUF2a6S7E0s9iR2zL0aII2eDbEf41zsMcYeH8QfY+zxgWKsh9jjg/hjjD0+iD/G2OOD+GNUYq52qZTBREJL4VqJPb4U7tnahyLl6dGjB+eff/4svzd8+HAOOOCAEiKKz+TJk4NsV0n2JhZzEjuFBHYKYj7GUDnOscYYe3wQf4yxxweKsR5ijw/ijzH2+CD+GGOPD9KKUWoTcxlMx7h+NF1M7VK4VmKND9I5zrpWROIzevTo0CEEM2nSpCDbVZJdJGEp9AxRr4HWoPNQYpDCPVGaXwrnoe6JIl2ja7l2KdwTY48vheMsIvFZd911GTJkCACjRo1i3333DRxReRZffPEg21WSvYmpQFO72As0MfcMAfUaaCXqvSIxiPmeqPOwdcR8HoLORRGRIt2zRSRFTz/9NC+//DIAWZZNX59lGePGjZv+c74A7LTTTu1+z911110lRV0ezckudRdzgeHiiy9m8ODBocNIXgoNKbE3VIiIiIiIdESdCEREJDbjx4/npJNOCh1G1BZddNEg21WSXYKJuREA0ii4ah+KiIiIiDSGOrPULub6iuoqIpKiAQMGcN555/Hqq68CcPXVVweOKD7//Oc/OfbYY0vfrpLsEox6YUsMdB6KiFSkcE+MPT7ds0VERESkkTbYYAM22GADAO655x4+/PDDwBHFZY899giyXSXZRaShYk/YxNy7BtTDRkSkmqZvEBGReom9rgJqvBWRGb377ru89957ABx22GHT1xfnW588eTKXX345kyZNKju84EaOHBlku0qySzBKbtYulUJhrMc5hWMsIlIm3bNFRKSeYq+vxPzcAz37RGRG48eP57vf/W7oMKK20korBdmukuwiCVOhsDXEXjkBTd9QD7EfZ+3D+og9vhSOs4iIiIhIq+rfvz8nnngiTz311PR1zrnpf+Y/P/DAA0Hii8HYsWODbFdJdgkmhWRI7MkG7cPWEHNjSt6QEmt8kE5jTwrHOXYp7MNY44N0jrOIiKQjhWezNL8U6s0iXeWcY6eddmKnnXaa4bOPPvqIX//612RZxnzzzcenn34aIMLwunXrFmS7SrJLMDEXuCCNQpf2oYiI1FMKldDY41Pjskjz0DsgRJpDzPVmXctST9dddx1PP/106DCCe+KJJzj66KNL366S7BJMChV5VZQlBilcK9L8UjkPU4hRRNKXyj1RahP7MU6hrpLCtRJ7fCkcZxGJw/HHH88mm2wyfcqY3OjRo7ngggsCRVW+wYMHB9mukuwSTMytyZBGi3IKhVYVCmsX87WSwnUi9RHzeQjxT8eSyrUS83GO/RhDOsdZapfCtSISgxSulVjjA13PIjJ7unfvzvrrrz/D+i+//JKnnnpqei/3iRMnlh1aqaZNmxZku0qySzBKENcu5kIrqFAoIpKaFJ7NIjHQtSLSNSlcK7HHF3udVETiN2zYMB566KHQYZRm9OjRQbarJLsEowRx7VIotKpQKCJSEfs9W0S6JuZybAplWGkdKVwrscYHup5FpD769+8fOoRSaboYEZltMRdaQYXCVhJ74lCNPRKLFF6iF+tzJY9P9xsRKUsK92wREZFZGTBgACuvvDKvv/566FBKMXTo0CDbVZK9iaXQyzn2+FRRFhFJh5579ZFCjCIiZYj9fqi6ioiIdMW4ceNaJsEOsO666wbZrpLsTSzmXs6x95YD9Q4RkXLFniBOoSKv515tYo8xjy/U8E8RaT3qyS4iIil54oknOOWUU0KHEdyECROCbFdJdgkm9oQSxJ9U0j6UWKgSWrsUEsQiMdD9RkRE6kX1KRFpJsOHDw8dQhSeeeYZ9t1339K3qyS7BBNzQgnSqChrH4qIiIiINIaSr81P9SkRaSa77747u++++2z9nV/96lcMGTKkQRGFsfLKKwfZrpLsIiIiIiIiIlU0ckZERJrRN7/5TSZOnBg6jIYZN25ckO0qyS4iIiIiIjIbUphiQkRERKQjzZxgB4K95FVJdgkmhcqJhmCKNIcU7jcQ/7D02OODNGKU5pbC/Ublm9rFPMWEejjXj67l5qd7tog0q8cee4xTTz01dBhBLLDAAkG2qyS7BBNz5QRUQRFpJqncb2KNMfb4IP4Y9UxpHancb0Rk1jRdjIiIpCbLMgBefvnlwJGEM2DAgCDbVZJdREREmkIKvdGkdrEfY/U4FBEREZEQ/vSnP3HdddeFDiO4eeaZJ8h2lWSXYFJIhsReUdY+FBGpiLkHsXoc1o96lopIWVTObn4xlx1AzxURmT2bbrop119//fTe7K0qVC9+JdklGBVoapfCPkyhISD2+FKoQGkf1k7XSn3EHmPs8UH8McYeXwr3G6ldCvdskRikcK3EHp+eK7VL4TwUqYeVVlqJBx54AID//ve//OIXvwgcURihOuUoyS7BpPCgU4GmdjE3BMQ+hzOk0dgD6llaD7pWahN7jLHHB/HHGHt8kM79RmqXwj1bJAYpXCuxxge6nuslhfNQpN4222wz7rjjDtra2hgzZgyHHnpo6JBK07t37yDbVZJdRERERERERFqOOn6JSDPr27cvAN26dWOxxRZj5MiRgSMqx8cffxxku0qySzAxtyZDGi3KKhSKiIiIiEisYq+vqE4qIq2gb9++7V6Ieuihh/LOO+8EjKix3nzzzSDbVZJdREREREREpIqmw6tdzEnsVPZhCmJuSAF1/JLW9eqrrzJp0qQZ1q+wwgpNnWQfMGBAkO0qyS6SsJgLraCCq4iIiIikS4lDka5Rg5RIfG6//XYuuuii0GEEseKKKwbZrpLsEkzsQwdBBVcRkZSk8FyJXQr7MPb4VHZoDSlcKyIxSOFaiT0+PVdEZE7ce++9oUMIpqPe+2VQkl1EGir2grUKrRILXSu1i3l0Tyq9qFLYh7HGB+kcZ6ldCteK1E69c2sX+7UyePDg0GGIiDTEueeey8EHHxzsJaAhPfHEExxwwAGlb1dJdgkm5gIXpFNwjV3Mx1nHWGKia0VERESkXDGXv0BlMBGZc3379uWaa65h2rRpjB49msMOOyx0SKVZcsklg2xXSXaRhMXe8xXS6P0qIiIiIiKtR/Wp+tA+FInPAw88wBlnnBE6jCAmTpwYZLtKsjex2AsMetDVTj0vREREREQaI+a6FKRRn0qhTqr6VO00tZJIHLIsY/To0QC88MILgaMJZ+TIkUG2qyR7E4u5wJDPfxdzgQvSKLiKyKzpftMaUjjOsccHacQoIlIGJQ5rF3udVESkmZx22mk89thjocMIbv755w+yXSXZJZiYC1ygQpdIM9H9pjXEfJxTeWmnXgAnIiIiIpKmqVOnhg4hCgsuuGCQ7SrJLsGk0ONQPUtFRKSVpNBQISJSFtVVmp/qpCLSTM477zyGDx8OwF133cWNN94YOKIwxowZE2S7SrKLiEjNVDkRERERkWopJLFFRJpFt27dWGqppQA47LDDmHfeeRk/fjxZlvH5558zefJksizj/vvvDxxpY40YMSLIdpVkl2Bi7i0H6jEn8VDlpHYp7EM1BEgMUrhWRETKojnZaxdznS+VqdxERLpqxIgRnHHGGbS1tc3wmXMOsJejNrsvvvgiyHaVZJdgUqjIx5700j5sDaqc1CalGEVk1vTckxikUAaT2sV+jFO436RwrcQeXwrHWUTi8Pe//5033ngjdBjBTZ48Och2lWSXYGJOHEIaSa8U9mHsBWsVWkVEKmJ+rqjBTGKSwrUiEoPYrxW98FtEmslxxx3HdtttN1t/56ijjmpQNOFsu+22QbarJLsEE3vyFZSArYfYC9YiImWK/bkH8ccYe3wqO7SGFMqxUjtNF9P8Yq6rgI6ziMyeG264gT/96U+hwwhuiSWWCLJdJdklGBVoRESk1aSQsIn12Rx7fKCyQyuJuRyr87B+Ym9IUaOeiIgUrb766qFDiMK4ceOCbFdJdhEREWkK6llauxT2YezxKekl0jxSaBgVERHJrbXWWgwZMmSW39tyyy1LiCacueeeO8h2lWRvYqoo1y72inIKxzj2fSgizUM9S2uXwj6MNT5I5ziLSNeonN38VJ8SkdTdd999M0wR45zr8M/qn5tVz549g2xXSfYmpopybVJ4aWcKYt+HKRRaY9+HoEpoPeg410fsMcYeH8QfY+zxpXC/kdqlcM8WiYGuldaQwjFOIUaROXHOOefQ1tYWOoyoDBs2LMh2lWQXmQk1VNQm9hhT6XGo87A2Os61S+k4xxpj7PFB/DHGHh+kc7+R2qVwzxaJQQrXSqzxQTrXcwpTK8V6nFM5xhKvu+66i7Fjx07/PcuyGf4cNmwYp556apD4QhgxYkSQ7SrJLiIiIiIiIlIlhcShiIi0tp49ezJw4MDQYUSlX79+QbarJLsEk8LQQQ35FpGyxH5P1P1QRERaTczPZUjj2azyjYhIeAsttBBbbbUVTz/9NADjx48PHFFjff7550G2qyR7E4u9QCO1S+EYq+Aq0jUpDKcWkVnTs1mkeagne+1iL9/onl0f2ocicevZsyc/+9nPOvxs2223ZerUqSVH1Fjdu3cPsl0l2ZtY7AUaiHdeNEij4BrzMYY09qGIiFSkkGyIPT49m0VE0qF7tog0k5deeonjjz8+dBjBLbzwwkG2qyS7BJNCRT72Fu8U9iHEnRCJ/RiLiJQp5mRDKg30KTyb9eyrXQrHWWoX+zFO4VpO4VqJPb4UjrOIxOGFF14IHUIU5ptvviDbVZJdgom5Ig9p9BpIZR/GGmMKx1hERNqLPRkiIiIVMddX8oZRqZ2mVhKJw/7778/+++8//fdXXnmFSZMmzfC9k046qcywSjdmzJgg21WSXYJJoVcDxF2ZV6+G2uk8rI/Y4wPFWA+xxwfxxxh7fJBGjDGLOaEESjbUS8zHWcdYpOtivpZB13O9pFLnE6mne+65h3POOSd0GEH069cvyHaVZJdgUinQxBqjClz1ofOwNrHHB4qxHmKPD+KPMfb4IP4YY48P9GwWaTbqnSvSHGKu8+lalkbZdNNNeeaZZ/jkk09m+r1nnnmmpIjK8+GHHwbZrpLsIiJSs9h7hmjUR+1S6AGUwnHWPqyd9qGIlEX3GxERSVXPnj1ZaaWVGDduHADOuXZ/5poxyT527Ngg21WSXYJRwkakeainV/OLuQcQpPPCydivFe3D2uh+IyKSlhSee6qTisicuPvuu7nssstChxHERx99FGS7SrJLMCkkbERikELhP3Yp7MPYK1Ap7ENpDbGfh7FfyyLSdWrUa36qk9aHns0i8dl+++2ZMmUKn3/+OVmWAUz/c8iQIXzwwQchw2uoNddcM8h2lWQXkZamxGF9aB/WTudia9AxFhERkWajBimR+HTv3p1vf/vbAEydOpVLLrmE5557DoCRI0eGDK3hhg4dGmS7SrJLMCkklNTi3fxS6b0Sa4x5fIMHDw4ah4hILFS+aQ0pHGepXezHOIVrOYVrJfb4UjjO2ocicfvoo4/497//HTqM0uywww5BtqskuwSTSnJTRNKXyv0m1hhjjw/ijzGVBqmYr5XYjzGkFaPUJoVrRSQGsV8rsT+XU6Ge7CJxW3zxxbntttuYOHHiDJ/tv//+ASJqLPVkl7qLvdeAWpNrF/sxBh3nVqGCtUjX6FoREUmH7tnNL+ZGANBxFpFZO+GEE5R3qbLQQgsF2a6S7E0s5gKDCgv1EfMxBh1nEREREUmXOrOIiEjsBg4cGDqE6Hz++edBtqskuwSjXtgizSP2axnij1H3G4lBCs/m2KWwD3W/EZGypHBPjD0+3bNFZGZOPvlkTj755BnWP/fcc/zwhz8MEFF4a621VpDtKskuwagXtkjzSGE4te43IrMW87M5lesk5n0I6exHkRikUL6R2uieLSLN6s033wwdQjBLLbVUkO0qyS7BpNCrQb0GRKQsKdwTY48P4o8x9vggjRhFRERERKRzm2++Of/3f//HhAkTQodSumeffTbIi62VZG9isSds1GtARKQi5ntiSqMBYo0x9vgg/hhTeS7HXv4CdSIQ6Spdy7VLoXwjItKMhg0b1pIJdoAVV1wxyHaVZG9iKtBIDGJPNqRQOUlBzMcYdJzrIfZrGXSc6yGF4xy7mMtfoDJYvehaEWkOKVzLKt+IyJxYbLHFQocQzD333MMmm2xS+naVZG9iKRQYYo9PBZraxZxsUKKhfmKfszSF+yHEf0+U2ukYizQHlW9aQ+zlGxERkaOOOoo33ngjdBhRWXzxxYNsV0n2JpZC4T/W+EAFV4lHCgni2OOT1pDCtSK1i/0Yq4FepHnoftP8Yq4zg+qkIjJrq666qpLsVbp16xZku0qySzApJENUcJUYxFz4T6nBTDHOudjjg/hjjD0+iD/G2OMDJUNERKqlUOeLPb4U6qTahyLhHH/88Rx//PEAnHXWWdx3332BIwpvnnnmCbJdJdklmJgTh6CKcr2oYF0fsccYe3ygGOsh9vgg/hhjjw/ijzH2+FSRbw0plG9EYhBznS+fUlBqp6mVROJw2mmncdppp82wfujQoRx55JEBIgrjkUceYa+99ip9u0qySzCpVE5ijzH2+GIvWEMavSJjjTH2+EAx1kPs8UH8McYeH8QfY+zxQTrvgFBDQO1SKN+IxCCFe6I0P52H0ur69+8fOoRSLbzwwkG2qyS7BBNz5QTir8zHHh+okifxSKVgHXuMsccH8ccYe3wQf4yxx5dK+UZEpAwx3xPVk711xH4eijTaoosuypAhQ6b/vuWWWwaMpvEWWmihINtVkl1ERJpezAVriL/RLPb4IP4YY48P4o8x9vhAFWURkWqxd3RIpYwYu5iPMWgEl0i1YsL90Ucf7XCKmZRNmDAhyHaVZBcRERERERGRuos5iZ1KAjsFmpNdJD6jRo3ikEMOYfLkyaFDKZ1zLsh2lWQXERERERERkbpLoSe7iEgzev/991sywQ724tMTTjih9O0qyS4iIiJNIfaKfAq0D0VEpJ5i78mewnNPDQEiMic23HDDdtPCFI0ZM4Z3330XgMcee4x//OMfJUbWePPNN1+Q7SrJLiIiIk0h9op8CrQPRURERESa21577RU6hIZaZpllgmxXSfYmFnurvFrkRURE4hJ72UFERNIS+3Ml5sZlSKeBOeZjDMo9SGv66quvuPnmm/nss89m+GzBBRfk448/Lj+okkycODHIdpVkb2IxFxg0NE9ERCQ+sZcdRETKpJc51k7Pldaga0UkPvfccw9//OMfQ4cRRPfu3YNsV0l2CSbmAhfoYSzxSKFBSkRERKTZxF7+UocgERHpTDP3VJ+VAQMGBNmukuwSTAqJQxVcJQYxN0ipMUpERESalXrn1i72Op/qeyLSTKZMmcI999wDwIsvvhg4mnAWXHDBINtVkl1EREREpE5iTyiBkkoiXaVruXaxdxbRPVtEmslll13Gv//979BhBPf2228H2a6S7CIiIhGIvZKXQgUv9n0I8SdsII0YYxZzQgnS6f0qEgP1ZBfpmtjLDimUY0Xq4fDDD5/+86RJk3jggQcCRhPO//73vyDbVZJdJGEpJJRUoKldCsc59vggjRhjlsJ5KK0h9vNQzz2R5qH7Te1UfhARKc8888zDiSeeCMC9997bskn27bffPsh2lWSXYNTTq3bah60h5uOcH+NY4wPFWA+xxwfxxxh7fFAZNh879SyVGChx2Bp0v2l+MZezIZ3jrGtFJA5ffvkl9913H1mWAbDzzjszefJkPvjgA15//fXA0ZWne/fuQbarJLuIiIiIAHEnG1RJlpjoWhHpGl0rIiLlufTSSzUnO7DiiisG2a6S7CIiIiIiIiIiIiIJO+yww2hra5utv/PFF1/wzDPPTP/dOYdzjvHjx9c7vNJMnDgxyHaVZBcRERERERERERFJ2LzzzsuPf/zj2fo7F1xwARMmTGhQRGHcd9997LvvvqVvV0l2EREREQE0z7SIiNRX7M+VFF4eKyJSb6eddhqPPvpo6DAapk+fPkG2qyS7BBN7gQtU6BIRkdaiuXNFRCpUV6mdnisiIuFNmjSJk046iVdeeSV0KKUYOXJkkO0qyS7BxFzgAhW6RERERERa2RZbbBE6hE6priIiIl01bty4lkmwA3Tr1i3IdpVkFxGRmsXe0wsUYz3EHh/EH2Ps8UH8McYeXwo9S0Wka3S/ERGRZjBw4ECGDBky/fe7776bO+64A4Bp06bx4YcfApaMbwZbb711kO0qyS4iIjVLoadXCiNnYo0x9vgg/hhjjw/ijzH2+EA9S0WaTQrlGxERkY5MmDCBc845h48++mim33vrrbdKiqg8mpNdWo7mZBcREZFmo/KNiIiIiIT2xBNPNPXLTWfms88+C7JdJdlFREREROpE75wREamIveFRjY4i0qy23nprVlhhBaZMmTLDZ0cccUSAiMrz+eefB9mukuwSjCqhtYu90JqLPcbY44P4Y4w9PlCM9RB7fBB/jLHHB/HHGHt8EH+MSiqJdI2u5drFXOe7+OKLk6hPpXCcRSROSy211PSfJ0yYwKRJkwC4+eabO/z+XnvtVUpcjfbxxx8H2a6S7BKMCjS1i7nQCvHPnxt7fBB/jLHHB4qxHmKPD+KPMY9v8ODBQeNoBinMkRzreQhpdCIQkeaRQp1Pahf7MY69Xi9SLzfccAN/+MMfQocR3Pjx44NsV0l2CSaVBHHMUii0qkAjIlKhBPGcS+G5LCLNJYV7duxirvPF/tyDdI6zrhWROKy88sqhQ4jCwIEDg2xXSXaRhMVcaAUVaERmRwqNZrHHB/HHGHt8ahgVEanQPbt2sZdvUtiHIiJdtfbaazNkyJBZfm/LLbcsIZpwFltssSDbVZJdJGGxF1pBBVeRroq50Sylnl6xxhh7fJDO3LQiImVR79zapVC+ERFpNb///e956qmnAJg0aRIvvPACzjlefvnlwJHVR69evYJsV0l2CSaVinwKMYqIiNSDkiG1S6F8owbw2qVwnKV2sR/jFK7lFK6V2ONL4TjHvg8hjRhFyrLSSiux0korAXD00Ufz+uuvB46ovkLdN5Vkl2BirshD/L0OY48P0kmIiIiI1Esq5RupTczHWcdYYpLCtRJrfJDO9ZzCqI9Yj3Mqx1jS8+WXX3LeeecxevRoALIsm/7Zq6++GiqsUujFpyIiIiJNLoVeVCnEKCIiUg8p9LRPoSe7iMRnu+22Cx1CMGussUaQ7SrJLsGoQCMiIq1GPb3mnHp6iUjZUrhni4iIdOSggw7i6quvDh1GEMsuu2yQ7SrJLiIiIiIiIlJFHYJERCRVBx98MAcffPAsv3fhhRdyxx13ND6gEr377rtBtqskuwQT8/x8oN4hIiIiIiIizUx1UhFpBVOmTGH77bcPHUZp2tragmxXSXYREWl6mp6qNaRwnGOPD+KPMfb4IP4Ydb8RkbLE/mzW/VBEWsFzzz0XOoRSFV/yWiYl2SWY2AtcEH+hK4V9CHEnG2I/xiLSdTH3Rot9vnOwGAcPHhw6jOTFfB6CekWKiIiItIphw4YxZcoUFlhgAb7//e8zYsSIdp8757jlllsCRdc4TzzxRJDtKskuIg0Vc7IhlURDKo0pIqHpWmkNehGhiEg6Yq8LpFB2UKcgEZkTN998M1dccUXoMFqKkuwSTMwFLkijoqx92BpiPs6pHOOY9yGksx9jF/NxTuUYax+KiFSoUa/5xfzcAx1nEZlz8847b+gQghkwYECQ7SrJLiIiIiKARgOIiEh9xf5cUS9xEWkmr7zyCscdd1zoMIJbffXVg2xXSXYREalZzJWnXOwxqpInMYi5R59684mIpEfPFRGRxrriiiu4+eabQ4cRlcmTJwfZrpLsEkzsvRpASS+RrkphOHWsFTxQJU9ERCRGqquIiEjsnn766dAhRKd///5Btqsku4iIiIiIiIiIiEhi/vznP9f098855xzuueeeOkUTh169egXZrpLsEkzMQwchjZ6lGg0gIiIiItIYKYzUk9qoPiUiqXvggQemJ9pHjhwZOJo4DB06NMh2lWQXSZgaKkREREREROaM6lMikrozzzyTLMtChxGVbbfdNsh2lWQXERERERERERERScxdd93Fxx9/PMP6trY27rrrLj7//POZ/v077rijUaEF8+CDD7L99tuXvl0l2UWkpaUwRBTif/FW7PGBYqyH2OODNGKMWSr3xJilsA819YBI1+harl0K98TY40vhOMcuhfNQZE716tWLxRdfvMPPjjjiiA7Xf/nll0yaNAmAQw45hA8//BCAH/7wh3z55ZeNCbREbW1tQbarJLuItLRUhojGGmPs8YFirIfY44P4Y0xluHfM90Ttw/pIZT+KxEBzsjc/3bNbQ8zHWcdYQthuu+1Ch9BQ3bp1C7JdJdklmBRak9VrQKRrdC1LDFJ4roiISDpif6akUL5RclNEJD6HHXYYN998M8D0+dyzLGPChAkhw6qbAQMGBNmukuwSTMwFLkij0JVCQimFwr/UTj29JAYxP1d0HoqIpEflG5HmkEK9WaRM++23H/vttx8A5513HnfffXfgiOpr2WWXDbJdJdlFEhZzQglU+BcRERGRdMWelFNnFpGuibnerDqzlGXUqFF89tlnANx444089NBDYQNqoD59+gTZrpLsEkwKrckquIqIiIiIiDQn1UlFpBV88MEHHHjggaHDKM3zzz/PLrvsUvp2lWSXYGJuTQa1KIuIiIiItDJNF9P8VCcVkVaw2GKLseeee/Liiy8C8MYbbwSOqLFGjRoVZLtKsotIQ8XeO0Q9Q1pD7OdhLvYYY48P4o8x9vgg/hhjj0/PFZHmofuNSHNIpS4g0ijdu3fnmGOOmf77lltuGTCaxuvbt2+Q7SrJLiINFXPvkIsvvjiJApcqULWL+TyESi+lWGOMPT6IP8bY44PKPVFERIx6sos0h5jrArqWReov1PNbSXYRaWkxF7hAhS6R2ZFCo5nUTkkvEZF0pPBsjj0+dbgRkTnxyCOP8NOf/jR0GEHcdNNN7LTTTqVvV0l2CSaFApcKNLWL/TjrGNdHzMcY0jjOsV8rEP9xToH2Ye1i34cp3G+kdincs6V2sR9j3W8kFrpWROKz4oorssgiizB69OjQoZRu2rRpQbarJLuIiNQs9p6lKSRDYh5VkcpUJxBvjLHHB5ouRmR2pHDPFolB7NeKnnv1EXtdQKQVLbTQQtx4440ATJgwgYMOOoixY8cGjqocyy+/fJDtKsnexFJIKsUu9n2YQot87AVraQ0xn4eQxrkY+/0Q0rgnxi7mayWVhgppDSncE0VioGulNcR+jFVGlFY3adKklkmwA3z55ZdBtqskexNTRbk2sceoiryIlCnmZwronigi5Yr5nqj7ocQkhWsl1vggnetZPdlF4rbQQgsxZMiQDj+79957Ofvss0uOqLHee++9INtVkl2CSaFXg1q8RUREREREREQkJa+88grHHXdc6DCCWGONNYJsV0l2EWmo2BtT1JAiIiIiIiIiIs3kpZdeCh1CMCuuuGKQ7SrJLiINlcIQUREREZHZEXsnAhEREWlta621VugQghk3blyQ7SrJLsHEnHwFJWBFpFyxJ2w06kNEpCLmcqzKsCIiIq0pyzJGjx4NwD333BM4mnCeeeYZDj300NK3qyS7BBN7QgniTyppH4o0DyVsJAYpPFdERCQdKTxXYo9P9anapXAeitTDFVdcwS233BI6jODmm2++INtVkl2CiTmhBGkklbQPRUSknmJ+ruiZIiJl22KLLUKH0KlU7okpPFdijQ/SOc6xJ7BTOA9F6mHzzTdXkj0gJdlFRKTppdJ7JeYY1YuqPmI+xrkUYhQRkTTEXgZT+aY+1CAlEoc777wzdAhR2HDDDYNsV0l2CSb2Aheo0CXSVbFfy1K7FO7ZoHOxFaRwjGOPUeWb2qVyT5TaxH6MdS2LiEjRcccdx9JLLz3L711xxRUlRBPOzTffzC677FL6dpVkl2BiHrIFavEWmR0p9F5J4X4Ta4yxxwcW4+DBg0OHISXQ/aY2Kt/UR8zlWB3j+knhfhM7XSsiIuWZe+652WuvvWb5veJ33nrrLa688koAnn766YbFVqZvfvObQbarJLuIiIg0hRQq8rHGB/HHqGSIiJRNPdlrF/uojxT2oYhIIx1++OGhQ6i7L774Ish2lWQXkZYWe8E/F3uMsccHirEeYo8P4o8x9vgg/hhjj08JG5HmoZ7stYu9ATyFuoCeKyIis2fUqFFBtqsku0jCVChsDbFXTiDenq+gaUTqJebzENI5zrEnbLQPa5NK0ktEukblbBERaXZzzTUXU6dODR1GXX355ZdBtqsku4iINL0UEsQQb2NFKonDmI+z9mHtUtmHIiKSjpife6Bnn4jUz2OPPcb7778//fcsywBYc801eeaZZ0KF1RBrrrlmkO0qyS6SMBUKa6d9KCIiIiId0cgZERFpBi+99BKnnnpq6DBKM378+CDbVZJdgtFUJyJSFt1vREREZHap7CAiIimZNm0azz///PRe6s45AF5//fWQYZXuzTffDLJdJdklGPUgFpGy6H4jIiIiIiIizezSSy/l9ttvDx1GcIMGDQqyXSXZJRj1LK2d9qGISFp0zxYRSYemi6ld7PUVPfdEpJnst99+jBgxAqjMuV79M8Bzzz1Xalxle++994JsV0l2CUY9S2unfSgikhYlbEREpJXEXF/Rc09Ems3CCy/MBRdcMMP6sWPHsvvuuweIKIwpU6YE2a6S7CIiIiIiIiIiIiJNYtq0afzzn/9k/PjxwV4EGsqYMWOCbFdJdgkm9qGDoOGDIiIiIiIicyr2Op/qeyLSrO6++24uu+yy0GEEMXz48CDbVZJdgol56CBo+GC9xF6whvjnSIb4Y4w9PlCM9RB7fBB/jLHHB/HHGHt8StiINA/db2oXc51P9T0RaTZvvfUWP/jBD8iyjC+++CJ0OMFssskmQbarJLuINFQKBetY44P4Y4w9PlCM9RB7fBB/jLHHBxbj4MGDQ4cxS5rXXkQkHbF3uEmhoUJEpKseeOABJk6cGDqM4AYNGhRku0qyi0hLi73gD2kU/mPfh6AY6yH2+FK4VqR2Og9FpCxq1BMRkZQcfvjh7LfffgBMmjSJSy+9tN385M65dj8753jllVdKj7PR3nnnnSDbVZJdRFpazD3tIZ0KVOyV0BR658Z8LqbUCzv2BGzsdB7WJpV7toh0TezPlBQa9VJ4roiINAvnHH379gXgkUce4eGHHw4cURiTJk0Ksl0l2UVEpOnFXMEDVfLqJebjrGPcOlJo7EkhMScizSGFe2Ls8emeLSJzYtttt2WxxRabnnDOsmz6Zw899BB33303AG1tbUHia6R+/foF2a6S7CIiIjJLKVSSVQmVGMTc2ANq8KmXFO6JIjGI+Z6YymhHEZE5tfrqq3e4/uSTTy45knINHz48yHaVZJdgUqicKGEjImJiriSDEociUq6Y74m6H4p0XczXMuh6FhGZE2PHjg2yXSXZRUREIhB7w6MaHUVEREQkRbGXs0XKNmTIkOk/H3fccU338tOllloqyHaVZJdg1GtApHmkUGhNIUapTQoVqNjjgzRiFBGRNMT+bFYngvqI+RhD3LkH5R0ktGZLsAMsuuiiQbarJLsEE3uBC+IvdKWwDyHuQlfsxzgVW2yxRegQOpUXXGMtWEP8MarwXz+6VuaczkMRkfTEntxMoT6VQn0l9vJNCsdZpNFeeuml6XOVn3/++YGjaaw33ngjyHaVZBeRhoq9YC0iUqYUKnixxxh7fCkkQ0Ska2JPHKZAyc3WEPsxVp1UWt3777/P8ccfHzqM0vTp0yfIdpVkF0lYzIUFUIFBRMoV8z0x9l7iEH+MsccHeu6JiFTTs7k2qTxX1CAlEoebb76ZK664InQYwX311VdBtqskuwQTc4EL9DAWEZHWox6HIiIVsd8PNXJGRESKlllmmdAhRGHw4MFBtqsku4iIiIgAcTeAq/FbRMqm3rkiIpKS9ddfnyFDhgDwzjvvcOihhwaOKIwJEyYE2W63IFsVERERERERERERkbqbOHFi6BCCefbZZ4NsVz3ZJZgUhqRrCKaIiIiISGtSXUVERFK1xhprTO/VPnr0aPbZZ5/AEZVn4MCBQbarJLsEE/OQdNAQTBGR1KTQeCu1i/0YK+kl0jw0XUztYn82654tIqkbP348b7/9NgD//ve/uf/++wNHFN6iiy4aZLtKsouIiEhTiLnxVskQERFpRXo2t4bYyw5qTJFmtuuuu4YOITpLLbVUkO0qyS7BpFCRj/1hnMI+hLgLXbEfYxGRMqWQDIk1PlDCRqTZxFyGhTTKsbHXV1LYhynQqA+RcM477zxuuOEGALIsm77+hRdeCBVScG+99VaQ7SrJ3sRiL9BI7WJOhoAVaAYPHhw6DBERERERCSDm+kpeV4m9zpxCQ4D2oUg4G2ywARtssMEM6z/44AMOPPDAABGFd99993HaaaeVvl0l2ZtY7AUaUG+0VpDCeSgiIiIiIq0n5roKpFNfUU92kfgsueSS0198Wu1HP/oRzz77bMkRNT8l2UVERERERESqKHFYu9h7iquHs4ik7oADDmD48OGhw4jKwgsvHGS7SrKLiEjNYq485WKPUZW82sVekRcREWk1MfcU13Qx9aN9KBLOFltswbXXXhs6jKgsueSSQbarJLuIiNQshZ5esVbwIJ3eaLGLvSIPqoSKiIjEJOayA6RTRkyhLiDSrA499FAOPfTQGdaPHDmS/fbbL0BE4U2YMCHIdpVkFxGRppdCLyWIOwGr5Gt9qBIqIiIiIiKNcPbZZ3PvvfeGDiO4FVZYIch2lWSXYFJIesWeVNI+FGkeMfek0nBqERFpRXruiXSNrhWROCjBbl588cUg21WSvYmlkBCR2sSclAP1ipR46FqpnfahiIiIiHREI/VE4nDMMcfwu9/9LnQYwX311VdBtqskexOLOSGiOZJFREREREQkpBQ6pqkXtoh01Z577smee+45w/pRo0ax7777BogojEGDBgXZrpLsEowKNCIiFSncE2OPD+KPMfb49NwTEZF6ir18E3PHNFDHLxGZc+PHj+eXv/wlH330EZMnTw4dTqnmnXfeINtVkl2CUYGmdrEXWkEJG5GuivmemNLoo1hjjD0+SOO5JyJSJk2BUbsUyjciIs3omWee4dlnnw0dRhBvv/12kO0qyS4iIk1PDVKtIYXjHDvtQxERERGR9K2//vost9xyjBgxYqbfc85N/3nSpEmNDqsU2223XZDtKskuIiI1iz0pF3MvKrCeVLEnN9UIICJSEfs9W+oj9mOcwrM5hWsl9vhSOM4iEoevvvqKJ554AoAHHnggWI/u0IYOHRpku0qyiyQshcShtIbYh1OnUMGLXQr7MOZ7Yir3Q+1Dka7RtSIiIiKxufTSS/nXv/4VOozg+vXrF2S7SrKLiEjTizkZAvHP1x17fKCkkoiISIxiLoPlHTFERJrFgQceyCeffDL992HDhjFlypQZvjdmzJgywyrdsssuG2S7SrKLiIiIiIiIVIl9pJ7ULuZGANBxFpHZs+CCC3LWWWcBcP/993PmmWcGjiiMV199lR122KH07SrJ3sRSGNofe3ya/05EREREpDWpriIiIql68cUXQ4cQzAsvvBBku0qyN7GYW+U19YCIiIiIiIiIiEj9bbzxxtx+++2hwwhi/fXXD7JdJdklmBR62qt3iIiIiIiIiIiIxO6xxx7j1FNPDR1GcAMHDgyyXSXZJZiYe9qDerJLPFJokIo9PjWYiXSN7je10/1GREREREIYNWpU6BCiMG3atCDbVZJdRCRyMTdIaeonkeai+01tdL8REUlLCo3LKTTeah+KxOFb3/oW3/rWtwC48847+fWvfx04ojD69+8fZLtKsjex2AsMetCJiIiIiEistthii9AhdEqNehITXSsi8ZkyZUroEIJ58cUX2WmnnUrfrpLsTSz23mixNwKAGgJaQQrnIcTfOyT2+EAx1kPs8UH8McYeH8QfY+zxqewg0jx0vxERkVTtvPPOTJ48mXHjxgHgnJv+Z/5z9e/XXntt+YE2QL9+/YJsV0l2CSbmRgBQi3erSOU8jDXG2OMDxVgPsccH8ccYe3wQf4yxxwcqO4iIpCaVuoCIyOzq0aMH++67LwCjR49mn332CRxReQYMGBBku0qyi4iIiAiQzugeEZEyaAoMERFpBgMGDGDFFVdk6NChoUMpxeOPP85BBx1U+naVZBdJWArJEA1jrV0Kxzn2+EAx1kPs8UH8McYeXwpS2Iexx6hns0jX6FquncqxtUvhOItI3CZNmtQyCXaAyZMnB9mukuwiCdPwxtYQ83FOafoGxTjnYo8P4o8x9vgg/hhjjw8q75wRkeagnuy1Uzm2NqkcZxGJW48erZX+nTBhQpDtttZeFhGRlpRCLyr1UmoNOg+bX8wJpf9v797j9Krqe49/dxJyAcMlIMSgBAQS0oMwwdMAFTUpBltLaAOoVRHw1RNA0XB6TspFoMXaiqUWUIwi4qV4O8UgIhIRLNMYMBCJCJRgbpALgZA75DK5Tdb545mZTCYJeTJ7z/79fvv5vF8vXmGembC+7P2svdf6rfXskSjYAPuCa3b1MUYsBscQ8O3AAw9Uc3Pzbr83c+ZMXXfddZKkrVu3lhmrxxx77LEm7VJkhxkGNPlxDIH6RCh6ee/P9OVisCuy+rz3ZYn+XIQI5xnwgL4CD3gfAnt21VVXWUco3PHHH2/SLkV2IDAKh/lRaIAXnvszxVcAAABExTgbaCz9+vUzaZciO8x4vtFJMW523gvYku/zHOEcAwAAAFF5nwvwezQAoHpmzZqlCy64oPR2KbIDgXketEoUsQEgmgiLt4AHnsdgjL8AlI3H4QH+tba2KqUkScqyrOP166+/Xp///OetYvWIAQMGmLRLkR0AAOxVhOJrhMc/eT+GEXg/hp6LrxLFBgDojGs2gEbwyiuv6KMf/ah1jNJs2rTJpF2K7DAToWAj+Z/Me88n+c4YoSgHeMAktBgRdnp5Pc/e80lx3ocAUJYIcz7v+Ziv5BfhfQgULaWkRx99VBs2bNCWLVus45SKIjsaTpSCjdeM3vNJ/jNSDAEAAAB6juc5H89kbxze34dAT3jwwQd10003Wccw8d73vtekXYrsMBNhNZldAwAAAOgqwjgW+UX49JF39JXG4P0cM69HIzrzzDO1ePFirVmzRvPmzdMLL7xgHak09913nz784Q+X3i5FdpjxvJosxRi4Rhi0MqABAABV43kcG2EMi8YRoa94zSfF6c8sSAH+9O3bV5deeqkkacmSJbrwwguNE5XnhBNOMGmXIjsQmOdBq8SABgDQeFgABwAAgAebNm3S9u3btXHjRusopVq6dKlJuxTZAQAAgIKwAA4AAAAL8+fP12c+8xlt37694X7ZaWf77befSbsU2QEAAAAAAAAgsEceeUSbNm2yjmGupaXFpF2K7AAAAAAAoHDeH6HF47Mag/f3IVCUCRMm6MILL1SWZVqyZIkmTJhgHcnEIYccYtIuRXYAAAAAAFA4z4/Q4vFZjYP3IRpFlmXq37+/JOm1114zTmOnX79+Ju1SZAcCi7Aiz+6QxuD9fSiRMa8IfTnCNdG7CMfQe74IfQUAAADV9s53vlPNzc27/d6YMWNKTlOuxYsXm7RLkR1mIkzkvU+UPa/IS6zKN5LRo0dbR9ij9vdhhL7iNWOUvuz5msgxzM97P5HinGcA9WGuUn3MSQE0gvXr1+vCCy/UmjVrrKOUYtCgQSbtUmSHGc8TeYmJMgAAANDIImwi8M57EZs5KYBG0NLS0jAFdkkdj8wpG0V2IDDvg1aJnRcAAACIiXF2fp6L2BSwATSK1tZW6wilslpQoMgOMxSIAQAAAAAAgJ5z8MEHa+TIkXrqqaeso5Ti7LPPNmmXIjvMeN7VIMXY2cAxBKrD+8Iji44AsIP3azaKweNi8ovQV7znYwwGIK/+/fvr5ptv7vi66r/4dNq0aTrnnHNKb5ciOwAADnheNIsykUd+EYohgAdcsxuD9+thhOKr977S1NRkHQMAULA3velNJu1SZIeZKBN5zxkjDKwjnGfv+ST/Gb3nk8hYBO/5JP8ZveeLwPsxjHBvRn4RxjeAB/SVxhDhHEfICBTp+eef16c+9SnrGCb69LEpd1NkhxnPuxqkHbuAvGZkl1IxeB/m056PXUAAAKBqeFwMUA2e53z0ZfSUXr16WUcws3DhQpN2KbIDgUXYGcKApjFEmIR6fR9K/jN6zyf5z+g9n+Q/o/d8EveVRsL4BqgGz31ZitOfI8wFgEYzfPhwNTc3S5Lmzp2rSy+91DhRec466yyTdimyw0yUAjGAvfPelyX/Gbne5BfhvuJdhGPoPR99GagOrjdAfegrgD+zZs3SpEmTrGOYeP31103apcgOM+wayI9jCC8i7F6hr+QTofjq+ZoY4RxLMY6h13xSnPMMAECRIswFgEbzu9/9zjqCmUMOOcSkXYrsFea9IMJqMjzw3k/aRciIfKK8Fz2LcAy955P8Z/Sej/FNY4hwvUF+FA7zi7B4CwBVdPLJJ+uHP/yhdQwTv/nNb3T++eeX3i5F9grzPqCJMDlhopyf9/PsuZ9I/nduMjkBqsXzNdH79VBifANUDX0ZqA99BfBnyJAh1hHMDBgwwKRdiuwAelSEgg3gQYS+4jWf5D9je76mpibTHFUQYSLv9X0oce8DUC7vC48UXwFU1Vvf+taOX3y6cOFCfeITnzBOVJ7W1laTdimywwyTUADYgUloY+DRA/l5P4be+7JEfy6C53FslL4cgffrTQTe+wrXbACNYOjQobr66qs1f/58SdKUKVOME/WsU0891aRdiuwAADjgfRIKoD6e+7JEfwb2BcXX6uOaXQwWpAAf1qxZo8mTJyulJElKKXX8067zv1fV9OnTNX78+NLbpcgOoKFF2L0i+Z/kec8nkbEI3vNJ/jN6zyf5z+g9H0UvoDooHAIAIvnWt76l//zP/7SOYW748OEm7VJkh5kIxU3vE2WOYX4Rdq/wDGcA2IGiFzyIMAYDPPDeV7zPVVAM7+9DoCgTJ07UySefrCzLOv5p1/m1G264wS5kCdatW2fSLkV2mIlQ3PSOY9gYPJ9n779sUiJjEbznk/xn9J5P8p+Rewo8iXBvBjygr8AD3odoFH379tXYsWOtY5hbvXq1SbsU2Ssswmqt93zsbAAAAEBXEcbZyM/7OWaukl+Evsx5BtAdra2tuu+++/T66693vNZ5Z3uVrVixwqRdiuwVFmG11ms+iRXlongfuDJoBQAA+yrCOBsAADSuBx98ULfddpt1DBPHHnusSbsU2WHGe/FVogBbBCahAIBGwvgGAOLwPFeR4sxXuO8B/rztbW+zjmBm0aJFJu1SZAcAAAAKQsEGANBo+KXkgD/777+/dQQzy5YtM2mXIjsAAAAAAGg4fPqoGBxDwJ/jjjtOzc3NkqR58+bpkksuMU5UnjFjxpi0S5EdAAAAkmIUG7yLcAwpNgD1YXdu9fHpo2LQVwCfVq5cqa1bt+70y08bwcaNG03apcgOAAAASb6LDVEmyZ6PoRTnOAIesGCWn/eFxwjHEAC64+6779bXv/516xgmXn31VZN2KbLDDJNQAAAAAAAAoFgHHXSQdQQzb3/7203apcgOAAAAAAAK53ljFZuqAFTZ+9//fr3//e+XJC1atEgXX3yxbaAStbS0mLRLkR0IzPvHLyU+ggkAAICYeM40ACCqFStW6DOf+YzZo1MsrV+/3qRdiuwAAAAAAHTBZpbqY9MSgKqaO3duQxbYJWnp0qUm7VJkhxkGNPl5/vilxA4bAAAAoJF5n/MxnwJQVUOGDLGOYGbYsGEm7VJkB95AhEGhdxzD/LwfQ8n/Ti+JjEXwnk/yn9F7Psl/Ru/5ItxXkF+EezOAvYvQlyPcV7wfQylGRqBI69ats45gZuPGjSbtUmSHmSi7BrxmvPXWW8MMCj0fwwgiHEOv+SQyFsF7Psl/Ru/5pB33Fe+8PyM5yr0ZAIBGEWE+BRTtpJNO0m233aaNGzfqxRdf1O23324dqTT9+vUzaZciOxCY58GCFGPAEKEYIvnfeeE9n+Q/I0UveOD5vtJ+T4nQl70eQynGvTkCz+eZc1wc74t6EXjvKxEWlwGgXtu3b9eCBQuUUtLDDz+sKVOmWEcysWTJEpN2KbLDTITipveiF8cQqI/nCZ4UZ/er93xcbxoDRS8AiMP7+CbCGDEC7s2AD1/96ld17733Wscwd+yxx5q0S5EdZhjQ5McxzC/KMfSa0Xs+KU4B2/N7Mcp5BgCgSBHGDt55H99EGSMCQD3OO+88Pfvss5Kk+fPnG6exc9JJJ5m0S5EdAFB5nid4EgVioEoo2ADADhGuiQBQFUceeaS++c1vSpJee+01fe5zn9Py5cu1dOlS42TlWrBggUm7FNlhJsKAi0koAADYFyzqAcAOnq+JfFIPQNU8/vjjuuaaa6xjmLOq5VFkhxnPAy4pxoCGhQoAAAAA6B7mUwCq5OWXX7aO4MIxxxxj0i5FdiAwFioAAAAAoHuYTwGoknPPPVfnnnvuLq/PmTNHl112mUEiG/vtt59JuxTZYYZdAwDKwvUGqE+EvgIAAADgjT3zzDO64oorrGOYWLt2rUm7FNlhhl0DAMrC9Qaoj+e+Qj8BABQtwuIyGzEA1OuXv/ylvvjFL1rHMHfAAQeYtEuRHQgswqBQkuuMDFoBAACwO6NHj7aOsEcsPBbD8+KyxHkGsG/69KHMK0mbN282aZejDwQWZVDoNSODVgBA0SIsgLPAnF+E8wx44L2vcD0EUCVnnnmmzjzzzN1+b/Xq1Vq/fr0k6Wtf+5qeeOKJMqOVauTIkSbtUmQHAAAAChJlARz5eD7PnGN4Ql8BAB8GDRqkQYMGSVKlC+yWKLIDAAAAANCF5x3YEruwAQD1W7t2bcdO9u9973sdr3/84x+3itRjWlpaTNqlyF5hfDQPAAAAALqHZ7JXn/c5s8S8GUB+c+bM0WWXXWYdozRLly41aZcie4V5/2geAxoAAAAAgBXPc2aJxRQAxTjooIOsI5Tq9ddfN2mXIjvMMKABgB28Lzyy6AgvPPcTib4CAJF4H39JMe4rHEPAt8GDB6u5ubnj6zFjxhim6XmnnXaaSbsU2WGGAQ0A7OB54ZFFR3jC4xsAlIW5Sn7e53yex19SnPsK92Yglu9///uaPXu2JOkLX/iCcZriPfbYY/qzP/uz0tulyA4zDGgAlMX7BE+KMVH2LsJ5BgDEQeEwP89zvijHEACKdsABB2jIkCGSpK985SvavHmzUkq68sorjZMV48gjjzRplyI7zEQohlD0AoA4mMgDAIrEXAWoD30FiGX8+PHWEXrU3LlzTdqlyA4znoshUoyCCAsVQH243gAAgH3FTnagPvQVAJ5Y/aJXiuxAYBQOAQAAAHjlfVMQG4IANKLvfve7euaZZ5RS2un1yZMna8uWLUapirNy5UqTdimyAwAAAADQhefisBSjQOx5UxAbggA0qqFDh2ro0KG7vH7LLbcYpCneoEGDTNqlyA4AAABJ/nccAgBQpAj3vQiLKQBiefbZZzVjxgxJ0qOPPqolS5YYJyrWSy+9ZNIuRXYgMAaF+XEMAWAHdhwCABqJ5/uexL0PQM+YOHGidYQedfLJJ5u0S5EdZihu5segMD+OIQAAAHaHX+YIAKii22+/XbNmzVJKSXfeead1nML179/fpF2K7DBDcRMAdvC+8Oh90REAAAAAsHfDhw/X8OHDJUkDBw6szLPY223cuNGkXYrsMOO9oCRRVAJQHs8Ljyw6AsDOIoxjkZ/3cxxhruK9r0Q4hgBQhCeeeEKLFi3q+DrLMmVZpsmTJxum6hkzZ840aZciOwAAAFAQ7wUliaJSEVgYbQw8Lqb6uGYDaAQLFy7U1VdfbR2jNMcdd5xJuxTZYcbz5ERi4AoAAPYd4xsAiINrNoAqWbt2rb7xjW/s8npKSb169dL27dsNUpXv1VdfNWmXIjsAAAAAAF2wwzk/z0XsW2+9lZ3sACpl4sSJWrJkiXUMc4sXLzZplyI7zDCgyS/CMZR8T1C8n2MA1eL5eihxTQQANBbPiwASO9kB7JsxY8borrvuso5h7t3vfrdJuxTZYYYBTX5RjqHXjBHOMYBq4fm+AIBG4n1TEIvLAKpk0KBB1hFcmDt3rkm7FNlhxvuAS2LQBQAAAAAAAP8OO+ww6wguWC02UGSHmSi7sFFtERZ7JP+PmPCeTyJjEbznk/xn9J5P8p/Rez4W6AEgjghzgQj3FY4h4MO73vUuNTc3S5JWrVql888/3ziRjeHDh5u0S5EdZhjQwIMoiz1eM3rPJ5GxCN7zSf4zes8n+c/oPZ/EAj1QNTziKz/PY23uK8WhrwD+PP/889YRzPzqV7/SpZdeWnq7FNkBAJXHol5+HMNieD+Gkv+M3vNJ/jNG6CveRbgmIj/v5zhCX47QV7zni3CeAfhzxhln6KGHHlJKaafXsyzTWWedZZSqHCeeeKJJuxTZAQCV53kXlRRjhw3HsBgRdnp5Pc/e80mxMiIfz9dEzjE88d5XmpqarGMAQC5f+cpXdO+991rHcOWVV14xaZciOwA4xw6gYpAxP+/5JP8ZveeT/Gf0no8dh0B1RFgY9S7COBb5eT/H3JtRZbNnz7aO4M7+++9v0i5FdpjxvKtBijNwRfV57iuRdm2Ssfu855P8Z/SeT/Kf0Xs+ibEDUDUUDvPzPo5lJ3sxWJAC7Nx+++27ff3555/Xpz71qZLT+LB161aTdimyA4BzEXYAec8nkbEI3vNJ/jN6zyf5z+g9X4SiFwCgxvMigESBGED3jRgxQs3NzZKklStX6oMf/KBxovIMHTrUpF2K7ADgnOfBf6SdpWTsPu/5JP8ZveeT/Gf0nk+iGAJUDbtzAQBV0KdPY5V/p02bpkmTJpXebmMdZQCl874Lmx2H8IK+AgAAUC7v4y8pxhiMYwj4duCBB+qSSy7peH77o48+apyoZw0bNsykXYrsMMOApjFE2IUNeEBfAQDAF+Yq+Xmf83kef0lxxmB86gPw4Uc/+pHuuOMO6xjm3vzmN5u0S5EdZhjQAACK5H0iHwHHEADQSCLc9yIspgDw4YQTTrCO4EKWZSbtUmSHGQY0AIAieV68jbJwyzEEABQpwn3Faz6Jex+AfTNy5MiOX3ba2csvv6yPfexjBolsrFmzxqRdiuwAepT3xRQWUgAAAAAAQFUNGTJEDz30kFpbW5VS0qRJkzqez15FI0aMMGmXIjuAHhVh9wry87yQ0s57RhZ8GoP396HkP6P3fPTlxuB9EwGKwXOm8/PeV7hmF8PzOZY4z2gcq1ev1uTJk5VS6nhkSpZlHf+0f13lArsk9e3b16Rdiuww47n4KsUZuKL6vE9OpBiTUK43+UR4H0r+J3n0le7znk+K0ZdRDM/jWN6HxfF+T4lQOKSvNIYI4xugEXz729/WI488Yh3D3Msvv2zSLkV2mIlQsIkwcEU+Ed6HEUQ4hmSEBxHOsfeM3vMxdgAAAICFiRMn6pRTTlFKSb///e/185//3DqSidWrV5u0S5EdQEPzvLtG8r9z03s+qZaxqanJOsZeeX4vRjnPkt+M3vNJcfoKu+UAlIXrDQAgkr59++pP//RPJUnHHXdcwxbZR44cadIuRXaY8VxQkmIMXCPswmZHHwDE4fne3H5f5r4HAHF4n69wzQZQVUOHDlVzc7MkKaWke+65R3PmzNnpZ9qf0747Dz/8cI/m60lr1qwxaZciO8x4H3BJ/gddnoshUoyFCjQG+gpQHd53ljK+AQAAgCfbtm3TCy+8oGeffXan11NKWr58uVGqnrNs2TKTdimywwxFLwAAfIlQIAYAAABQM3nyZE2ZMsU6hiuPP/64SbsU2WEmwkSenV4AgEbieQE8yuK352MoxTmOAAAA2DvqVrs68sgjTdqlyF5hEYrYAPYuQl/2nk8iYxG855P8Z/SeT/Kf0Xs+JjpAdXC9yc/zwiOLjsWhrwB2vvnNb+729e985zu66667Sk7jw5IlS0zapcheYREGNF7zSQy64Ad9OZ8oGZuamqxjvCHP70MpxjGU/D9PXPLbV9rzRTjPAKohwjUb8IC+AvhzwQUXKMsyrV27dpfv3XfffeUHKtG5555r0i5FdgAAHPBcxI4yOeEY5hfhkzPeJ/IRjiE7+oD60Jfzi3BN9J4vwnkG4M9+++2niy++eLffq3qR/bHHHtOECRNKb5cie4UxoMnP+4Amwjn2fgwBADuwUAHUJ8IYDADK4v16yJwUjWjmzJm66qqrrGOYOOmkk0zapcheYd4nynzcOz/P51iiIAIAAAA0Ms/zFeakxfH+KTOgER111FHab7/9tHXrVusopRs4cKBJuxTZYcbzgEviZgwAAPYd45vG4Pk8c46LQ+Gw+jz3ZYnzDKD7Bg8erIceekiSNH36dP393/+9caLyrF692qRdiuwAAACQxCMwgHrRVxqD93PMIzDyi9CXOc8AumPOnDm67LLLrGOYOP74403apcgOBMagEABQJM87+tjNB0/oK0B9IsxXAKAqWlpa9MADDyilpGnTplnHMbN06VKTdimyA4F5nuBJTPKAfeF9EsqCWTE8n+N2ETJ65r0vS/RnAOXxPF/hmewAquarX/2qpk6dah3D3ObNm03apcgOBMZEHqiOCJNQrjf5RXi+r+f3oeR/EcBzX5ZYAAdQrgjjB1Qf70M0issuu0z7779/x9cpJUnSokWL9OSTT1rFKt3GjRtN2qXIDgAAKoEJVGOIsFABoBq43uTneeGRneyNw/v7ECjKwIEDdfnll+/yekpJ999/v+bOnbvL9x544IEyopXKavMVRXaYiVAMibArEgBQwwQKAADsC89jB4nxQ1Ei1B6AnrR+/Xrddttt2rZtm3WUUgwZMsSkXYrsQGAMCgGUhesNAAAAIvI8jmUMizJs2rSpYQrsknTssceatEuRHWY83+gkbnZF8b5rgE8rAACAfeV9fAMAABrb4sWLddFFF1nHMPH666+btEuRHWYiTE68F2CjHEOviykspAAAgO5gfNMYIoyzvYswX/GeL8J5BuDPihUrrCOYWbBggUm7FNlhxvPkRIoxQeEYAgAAAD2DX3yan+f5Svsx9JpPinOeAfjzzne+U83NzZKk1atX67zzzjNOVJ6jjjrKpF2K7AAAAAiDHYcAAADAG3vyySf1d3/3d9YxTBx22GEm7VJkBwBUXoSPKlOYgwcR+go7SwGUxfv1MMLYIcJ9xXu+COfZ+zGUYmQEimRVaPZg4cKFJu1SZIeZCAOuCAMaAHvn+aPKEoW5okS4rwAAAFSN9wXwpqYm6xhA6WbPnm0dwczYsWNN2qXIDgAAKsHzYkqUhRSOIQDs4L1wCKA+jG/QiE4++WTrCGZWrVpl0i5FdpjxfKOTuNkBAAAAjcz7p6MifOrW85yPX3wKoMoee+wx6whmpk2bpgsvvLD0dimyw0yEj/VHGLginwjvQ8n/JM97PomMRfCeT/Kf0Xs+yX9G7/kYOzSGKOMHAG8sQl/mvgKgO1pbW60jmDn88MNN2qXIDjOedzVI7BpoFFHeh14zes8nkbEI3vNJ/jN6zyf5z+g9n8TYoZF4Hj/wPiwOj4upPs99WeI8A+i+7du3W0cws23bNpN2e5m0CgAAAAAAAAAo3MiRI60jmHn++edN2qXIDgAAAAAAAAAVsXr1ausIDYfHxQAAAAAAAABAYD/72c90yy23WMcwN2LECJN2KbIDgfGLegAA8IV7MwAAvkS4NwNFGDRokHUEF1JKJu1SZAcC4xf1AADgC/dmoDq8F+VYMAPq4/nezH0ZRTrjjDPU3Ny8y+uPPfaYrrvuOoNENk455RSTdimyV5j31VoGhQAAoGq8j78kxmAAAACN5NRTT9UhhxyiNWvWWEcpRWtrq0m7FNkrzPtqLZNQAECj4b6XX4Rj6HX8JbFjDgA6Y04KoBH06dNHt956q1asWCFJmjRpknGinrVp0yaTdimywwyTUAAAfIlQbBg9erR1hD1i7ABUC9eb/CLcV1B9vA/R6BYvXqyLLrrIOkZp1q5da9IuRXYgsAiDBXZeAMAOEQo2XhfAoxSUAAA7eN5Y1f7palSf9/ch0BNaWlo0efJkrVy50uwXgVo5/PDDTdqlyA4E5nmwIDFgAAAAABpZhE1BAFBFv/71r/XAAw9YxzDx9NNPm7RLkR0AAAe8T0L5VAoAAAAAxHDWWWfpiCOOUEtLi7Zt26bbbrut45nsVTdgwACTdimyA4F5L8pJFOaAenn+ZAqfSgEAAN0RYXzjNZ/EGAzAvpk5c6auuuoq6xjmRowYYdIuRfYKi1CA9Z7Pe4HY86BVYlAIANFEGDsAQFm8Xw+9z1UiiHDf4zwDqNfixYutI7iwfv16k3YpsleY5wIsuwYAAPAnwtgB8CBCYQ7wwHtf8Xzfk7j3Adg3559/vs4//3xJ0oMPPqh/+Zd/MU5ko3fv3ibtUmSHGe8DLoldA40gwvtQ8r+Tyns+iYxF8J5P8p/Rez7Jf0bv+Rg7AEAcEeYCEe4r3o+hFCMjUCSr55J70NLSYtIuRXYADS3C7pWmpibrGHs1evRo6wh7FOUYehehr0h+PyHlPZ9EXwH2hedrIjtfAWBnXLPRiN773vfqvvvuU0pJL730kj796U9bRyrNoEGDTNqlyA4znm90Ejc7+OG5r0TpJ56PoeS/ABvlPCM/z33Fez+R6CtA1XjfRBAB95V8opxnAD4deOCBkhpvV/trr71m0i5FdgBAbhE+fuk9Y4SPAnsX4SPf3vNJ/jN6z0dfBgA0GhakAN9mzZplHaFUBx10kEm7FNlhJkIxhIlyft7PM+e4GBEG1uxSqj52y+XjPaP3fBJ9Gagaz2NYiXEsAKA+o0aN0rBhwzR37lzrKKVYvHixSbsU2WHGczFEYqJcFM/nmXMMAAAAAACqbOnSpQ1TYJekPn1syt0U2WHG+w5nid0hAIDGEuHeDACIw/t9hfleMTyfY4nzjMb0+OOP65prrrGOYWL9+vUm7VJkhxnPO5wldjkD+8L7wFoiY14RJifeJ/KS73MMANhZhMfhIZ8IY4cIYzD6CuDP0Ucfrf33318bN260jlK6d7zjHSbtUmSHGQY0QH0i9BVUH+9DeOH9fcjYAQDiYOMXgKoaPHiwHnjgAUnSs88+q4kTJxonKs9TTz2lD37wg6W3S5EdZhjQAPXx3Fci/SJCMnaf93yS/4ze80n+M3rPJzF2AICuIoxjAaDqsiyzjlCqfv36mbRLkR1mIuyKZDcaUA1cbwAAANAVY0QAVbJw4UJdeeWVSint9PrKlSuNEtngcTFoOJ53NUjsbACqhOsNUJ8IxQYAKIv36yHFV3hBXwF8mDp1qlasWGEdw9yiRYtM2qXIDgAAAEm+F6RYjAJQNn6ZY/V5vu9Jcc4zfQXw4fjjj7eO4MLq1atN2qXIDgAAgDDYLQegLFxvAACIZ82aNSbtUmSHmQgfSWfgCgBxRLivID92y8EDrjdAfSL0Fe/5IsxJOYaAD2PHjtXYsWP3+nNjxowpIY2dwYMHm7RLkR1m+GhefhEGrQxo8otwnr3nk8hYBO/5IohwDL1n9J6P+15j8DyOjTCGBQAA6CmHHHKISbsU2WEmQuFQ8j2Z9zzBk5jkFcXzeW4/x17zSWQsgvd8kv+M3vNJ/jN6zydx3wOArryPY5uamqxjVAKfMgPgSe/evU3apcgOvAHvg0IAAAAAQPd4nu9JzPkA9Iybb75Z06dP3+X1uXPn6rnnnjNIVCyeyQ4ABiJ8ooJHDwAAAJSP3bkAgCoaOXKkRo4cKUl68cUXdeedd0pSJQrsknTEEUeYtEuRHWbYNQDUJ8JCgPd8kv+MLKYAAAAAAPbFhz/8YS1fvtw6hisDBw40aZciO4CGFmWxx2tG7/mkWBkBAIAfLNDnx2aR/CKcZwB2xo0bp29961vWMVxZtmyZSbsU2YHAIgxaGRQCAICqiTAGQ348LiY/zxta2IgBoAouuOACXXDBBYX8t26++Wbdf//9hfy3LA0fPtykXYrsQGCeB60Sg0L4EaEYwoIUAMTheQzG+AsAAHS2bt06nX/++dqyZYt1lFKsXbvWpF2K7AAAoBIiLKZ4F+EYes/HghkAoNFwbwZ827JlS8MU2CXp6aef1oc+9KHS26XIDgAAKoGdpflFOIZNTU2mOQAAwM54tBLg26GHHqrm5ua9/lxzc7P+8R//sYREPeuII44waZciOxBYhB2H7BqAB54Lh1KMwX+E643kfyeV93xcswEARfI+fuC+B6CqUkpqbm7W+vXrlVJSSqnj9a5/tv/75MmTbcIW7OGHH9bEiRNLb5ciOxAYhUMAZYlyvfGa0Xs+Kc41m91yABCH5/ED12wAVfaLX/xC//qv/2odw8SIESNM2qXIDjPedzVI7GwAAAAAGhVzFQBAVGPHjtWyZcs6fglolmUd38uyrOOfe++91yhhz2nfmV82iuww43lXgxRjZwMLFQAAAEDP4JMz+XmfrzBXAVAlL730kq677ro9fr+9sN75axSHIjvMeB9wSf4HXSxUAPWJcL2RfO+Y8349RDGi9BUAKIP362GEe7Pn+QpzFQBVc++992rRokXWMcwdcMABJu1SZIcZzwMuKcagK0IxJMLgH9UX5XrjNWOE6yGK4bmv8D4EUDZ2sgMAIrn88ss1bty4jq+7Pjal89ft//7JT35SW7duLSdgSXr37m3SLkV2mKFAnJ/nYojE4B8AAABxMVcBAETSq1cvHX300ZKk1tZW3XvvvXr99dd3+4zy9teGDBlSud3vBx98sEm7FNkBAAAgKcYCuHcRjiGFufwinGcAexehL3PNBvBG1q9frxdeeKHj6/bnrE+dOlUPPvigVSxTS5YsMWmXIjvMsAsbAABfPN+bo9yXPR9DKc5x9M7zeeYcA/Xz3Jcl+jPQCLIsGyjp85LGSzpc0lOSrkgp/baev9/58TCo6d+/v0m7FNkB9Cjvu0PYGVIMz+dY4jwD9fJ+zZa43gAoD89kBwCU4E5JJ0m6SNJLki6Q9Kssy/5od4956erGG2/UD3/4Q0m7PnN9wYIF2rRpU09kdu1tb3ubSbsU2WEmwkSeiXJ+nneHMDkpDpNQeBDhvuJdhGu213wS1xugarzfU5irAEBsWZYNkHSepPNSSv/V9vINWZaNk/TJ3f2d1tZWzZw5U/PmzdPxxx+vUaNG6bTTTtvl5x5++GF94Qtf6Knorg0YMMCkXYrsAACgEiIUiAEAgB8RFuhZTAEqrY+k3pK6bjdvkXRG1x9ubW3VlVdeqeeff16bNm1S//79NWLECN10003q3bu3XnrpJV133XWSpA0bNvR4eK/69u1r0i5FdpjxXAyRKIgA+4LJCQAAqBo+qQfUh7kA0D0ppXVZls2QdF2WZf8taZmkj0g6XdL8rj8/c+ZMPf/882ppaZEktbS06He/+53GjRunPn36aN26dWXGd2vVqlUm7VJkBwDkxiQUAABUDYVDoD7MBYBcPi7p26o9j71V0u8k/UjSKV1/cN68ebt9xnp70R01ffrYlLspsgOB8fFGAACA8kUYgyE/CofVx6erAVhLKS2Q9N4syw6QdGBK6ZUsy/5D0ouSRnT+2eOPP179+/ffqajev39/TZo0SX/8x3+sZcuW6dJLLy01v0evvvqqSbsU2YHAGBQCAACUz/MYjPEXAADxpJQ2SNqQZdkhkt4v6UpJH+j8M6NGjdKIESM0e/Zsbd68Wf369dMf/dEfafTo0erdu7f+8i//0iK6OxTZAQC7FWG3nPd8EhmL4D2f5D+j93yS/4ze8/EJLgDYwfs4lms2AGtZlr1fUi9Jf5B0nKR/lTRH0nckfaPzz/bu3Vs33XSTZs6cqfnz5+u4447TqFGj1Lt3b0nSj3/8Y1188cWSGvsXn1o9m54iOxCY90FrO88ZIwysI+yW85pPImMRvOeT/Gf0nk/yn7E9X1NTk2kOAEB1RJhPRZivAMjlIEk3SnqrpNWS7pF0bUpp6+5+uHfv3jr99NN1+umn7/K95cuXN3Rxvd0ZZ5xh0i5FdphhQNMYIhSIAQBxeH9GMuMboDroy9Xnea4ixZmv0FeA7ksp3S3p7iL+WzNnziziPxNe//79TdqlyA4zDGjy4xjmF6EYIvkfuHrPJ5GxCN7zSf4zes8nxcjoGfdmAIgjwlyAAjGAel188cUdj4vp7OWXX9bHPvax8gMZefnll03apcgOMwxo8uMY5helGOI1o/d8EhmL4D2f5D+j93zSjl3YAIAa75+cicDzWDvKvTkC+grg29atu33yTGWtWrXKpF2K7EBgngetEgMaAIjG832FewqAsrGZBQBQBYMHD9Zpp53W8TiZ7du3GyfqWX379jVplyI78AYi7BT3no/Bf2PgfVh9Ea6Hkv/3ovd8UoyMAIAYIowfvOdjHJtfhPchUIQpU6Zo8uTJ1jHMrV692qRdiuzAG4iwo89rPoldh42Ej4jmx+A/P67Z+XjPGKUvAwB24N6cT5R7n/cxbIT3IVCEo446yjqCC8OHDzdplyI7zHi+0Unc7ACUy/M1kUkoAOyMhdHGwCYCoD70FcCHUaNGqbm5ea8/N3fuXM2aNUspJT322GOaPXt2CenKM3fuXJN2KbJXWITBv/d8fDQPANBIIowdAA8iLIwiP+/XQ+YqAIDuGDZsmIYNGyZJ+uhHP9rx+i233KKf/exnVrEKs23bNpN2KbJXmPfBf1NTk3UMAADQifexAwCUid251RdhcZnFFABlWbNmjXWEQhxzzDEm7VJkhxnPE3kpxsCVQSFQnwh9RfK9Yy5CX45ynj2LcAy954vQVwDUh+sNUA0RxjeAByeeeKKmT59uHSMsiuwwE+FG533gykIFUJ8ofcVrxih92fN55hjm572fSHHOM4D6sJO9+jzf9yTOc1E8n2fOMaz94Ac/0J133mkdo1CvvvqqSbsU2YHAWKgAUJYI1xvJ/65D7/m4ZucXoa9wnoH60Jerj2t2Y4hwnoEizJgxQ5/97GetY5jbsGGDSbsU2WHG82qyFGNFmWMIoCxRrjdeM3rPJ3HNBoCu2MlefVHGN8jH83nmHKNIy5Yts47gQktLi0m7FNkBALlF2BniPSO7lBqD9/ehFCOjZ54n8hKTeWBfeL8eRhg7RNhB7D1fhPMMwIfx48dr/PjxkqQnnnhCV199tXEiG6eccopJuxTZYSbCgIsBDVCfCDu9KHrBA/pK99FPACAezwuPt956q5qamqxjAEBh7rvvPsbMkl588UWTdimyA4GxUAEAAAD0jAgLo955n694XgSQ4pxnAD4cdthh1hFcOOKII0zapcgOMwxo8uMYAgAAAPDK83yFuQqAqnnXu96l5ubmbv/9a6+9Vr/5zW8KTGRj3bp1Ju1SZAcAAAAAoAvPO7AlPjEKAMhvw4YNevLJJyWpEgV2STr88MNN2qXIDgAAgDAoegEoC4+LyS/C42IAILIrr7xSv/3tb61juLJkyRKTdimyA+hRDKwBAEWi6AUPvI9vAC94XAwA9KyBAwdaR3Dn0EMPNWmXIjuAHuV9YB1lkuw9o/d8EhmL4D2f5D+j93yS/4ze87F42xi8j29QDK43AADvrr/+el1//fV7/bkXXnhBy5cvV0pJn/3sZ0tIZuekk04yaZciOxBYhAKx98G/50mytGOi7DWj93wSGYvgPZ/kP6P3fJL/jN7zSRQ3AaAr7/MV73MVAChCSkmzZs3SH/7wB+sopfjtb3+rcePGld4uRXYgsCgFYgDxeZ8kt/Oe0Xs+KUZGACgDj6fKz/N8JcoxBIC8Fi9erK997WvWMUpzyCGHmLRLkR1mIhRsvO9s4BgCKIvnSbLkf5ez93yS/4wUQwAAAIB9N3ToUE2ePFmvvPKKUkr653/+Z+tIPWrLli0m7VJkh5koBRvPOIYAAABAz2AzCwCgCjZv3qx///d/18yZM62jlGLVqlUm7VJkr7AIu5y952PgCgAAADQmHhcDAKiC1atXN0yBXart3LdAkb3CPO9y9v6RdImBKwAAANDI2BAEAKiCt7zlLWpubu74+gc/+IH+4z/+QyklrV+/3jBZz3jttddM2qXIDjMRdtozcAWqgetNfhGOoeS/IOI9n+Q/o/d8kv+M3q83AAAA2HfTpk3TDTfcYB3DXN++fU3apcgOM5532ksxdrJHKHp5n8hzDBsD15v8ohxDrxm955P8Z/SeT6plbGpqso4BoCA8LgYAEMm6deusI7iwfPlyk3YpsgOBRSl6ecYxBFAm74t6UoyMnnFfAarD+/UwwkaMCBtavOeLcJ4B+HD22Wfr7LPP3uX1RYsW6eKLLy4/kJEDDjjApF2K7DATYcDFgAYAUCTvuyLZhQ0AKJLnhccon5CKgHk94MOqVav05S9/WSklSer4M8syHXbYYVq5cqVlvNLMmTPHpF2K7DDjecAlxRnQIB8We4rBMYQHEfqz93wAABSJe3N+Ecax3jcRAI3iu9/9rqZPn24dw9ypp55q0i5FdiCwCINW74PCCIs9Ec6z94F1hGMo+Z7kee/LUUToKwCAGu/X7Ag8j7XZyQ6gas4880z9/Oc/t45h7rnnnjNplyI7zEQoenkvKnketEoMCovi+TxHOceej6Hkf5LHec6PY5hflGMIoDqYqwAAIrn//vutI7iwefNmk3YpssOM54m8xGQeAAAAaGTsZAcARDJo0CDrCC706WNT7qbIDjPsZAcAAAAAAAC6Z9q0afrOd74jqfaLTvv167fT91NK2rZtm7Zv324Rz8SJJ55o0i5F9grzXsRmJzsA7OD9mi3xsflGEOF9CABl8X49jHDfi3Bf8Z4vwnkGYOeGG26wjuDOxo0bTdqlyF5hnovYUX4RIQOa/LyfZ84xvIhwzQY88HxPkbivNArv4xsUg8fF5Mf4BgB61tSpU7Vs2bKOr7Ms6/gzpbTLa11ddNFFJaQsV/v/d9koslcYg//qi3COvQ+sAdTHc1+W6M9F8Xyevf+CYIlNBI0kQl9BfvTl6vPclyX6M4C9GzBggI455phu//1f/vKXWrhwoaTaDvC//du/LSiZnYMPPtikXYrsFeZ5wBBlouyd53MsxTiGEUQo2CA/7+eZiTy88NxPJO7NANCZ9/GNFOO+AgBF+trXvqYf//jH1jF6zHPPPWfSLkV2mIkw4GJAk5/38xzhHHsu2FCsKQ7nGagPj2+AB97HNwCAHbhmo1E89NBDuvHGG61jmDvppJNM2qXIDjOeC0oSE+WieD7PnGMAANAdjG+A+kToK17zSfTnokR4HwJF2N0z1xvRk08+adIuRXaYibCaHGGXs3fezzPnGABQJO/3PYl7H1AvPjkDVEOEezNQhLFjx2rs2LG7vP7aa6/pr/7qr8oPZKS1tdWkXYrsFcaNBB6wayA/+nJj8H6eIxTlvB9DNAbP9z0pzr0PQDVEuDd7zxdhDOad53sz92XktWzZMs2YMWOvP3fFFVd0/PuXv/zlnoxkbtSoUSbtUmSvsAg3Eq/5JG528CNCX0Z+nOf8OIb5RSiGAADiiHBv9ppPijN+AGDnIx/5iHUEd9jJDgAAAFMRiiEAAAAAanr16qXt27dbx3Dl8ccf12c+85nS26XIDgQWYcchH28EAAAAAAAo3jnnnKOf/vSn1jFcOeGEE0zapcgOMxSIG4P388w5BqrD+/VG8v/cV8l/Ru/5JP8ZufflF+F6A3gQoa94z8c1G8AbueKKK3Z63no9zj77bG3YsKGHEtk76KCDTNqlyA4E5vlj/ZL/5xzy6AEAZRs9erR1hD2Kcs32mk+qZWxqarKOgRJ4HoMxvikOxdf8IvQVr/kk+jOAYqxdu1bjx4+3jlGaBQsWmLRLkR1mPA+4JAY0ABCN5/sK95TG4fl9KPFeBFAudrLnF2ExhWMIwJMxY8aYtEuRHWYiDLi4GQMAAABA93heeOTTR8WJ8Ek9oJEdfPDBam5u7vh69uzZ+tWvfiVJuvfee61i9Zh58+aZtEuRHWY8D7gkbsYAAABAI6NwWH3MSQE0ossvv9w6Qo86/PDDTdqlyA4z7GSHB7wPGwPnGV54fx9KMTIC1iLcV5Cf93McYewQoa94zxfhPAOAJ9OnT9dFF11UersU2WGGXQPwgPdhY+A8w4sIuyK99hX6CTzxfF+hr8CTCH3Faz6J/gygZ9xzzz1atGjRLq+nlJRSkiQtW7ZMX/rSl8qOVohevXqZtEuRHQAA7FWEnWiS/91o3vNJMTICAGLwPn5glziARrBs2TJ95CMfsY5RmqOOOsqkXYrsAABgrzzvRJP870bznk/yn5HdfAAQj+fxA/cVAFW2detW3XXXXVqzZs1ud61X2WmnnWbSLkV2mPG+q0Hyv7OBYwjUh74CAACArhgjAqiqhx9+WN///vetY5h49NFH9b73va/0dimyw4znXQ1SjJ0NHMP8IgysJf+Pb/CeL4II70Xv+ST/Gb3nk/xn9J6PYggAxMF8CkBV/fmf/7kGDBigDRs2aMWKFbrrrrusI5Xmr//6r03apcgOMxEKSkyUqy/KwNprRu/5pFrGpqYm6xh75fm9GOU8S34zes8n+c/oPZ9EMQQAAAA+ZFmmMWPGSJJefvnlhiqyP/LIIzrhhBNKb5ciO8x4LihJMSbKLFQA9eF6AwAA9tXo0aOtI+wRYwd44n1OKsXICPSUIUOG6M4779Ty5cuVUtK1115rHalHbdmyxaRdiuwwQ4E4vwiFwwjn2Xs+yX9G7/kkMhbBez7Jf0bv+ST/Gb3n8z52AFA/rjfVF2GuEuE8e1+QivCpVqAId999t77+9a9bxzD37LPPmrRLkR1mIhSIkZ/n8xzl0QMMCgEAAACgeyLMSYEiHHvssdYRXBg2bJhJuxTZAcC5CINCr/kkMhbBez7Jf0bv+aQ4i3red8sBqA6uN9XneZwtcZ4B7JvjjjtO55xzzl5/7mc/+1kJaez06tXLpF2K7EBgfLwRAFAkz8UGCg0AAADAnt1xxx2aOnWqdQxzb37zm03apcgOoEdFWAjwnk/yn9F7PomMRfCeT/Kf0Xs+yX9G7/kk/xlZAAfqQ1+uvghzFc4zgHpNnDix41Epv/jFLzRnzhzjRDY2bNhg0i5FdphhQJOf5x2Hkv/HI3jPJ/nP6D2fRMYieM8n+c/oPZ/E42KKEOU8AwBqosynAGBPfvSjH+mOO+6wjuHKjBkzdPnll5feLkV2IDAWKvLjGAL1oa/AC96HABCH9/ED12wA0U2ZMsU6gjvveMc7TNqlyF5h3gc0yI+dF/lxDIH60Fcag+fzzC5xAIgnwn0FACK75557dvv6vHnzdMkll5ScxofTTz/dpF2K7BUWYUDjNZ/EoAsAAI+8byBgVyRQHREeT+VdhI1f3vNxXwFQr/nz52vixIlKKWnTpk3Wcczcfffdes973lN6uxTZK4wBTX4MaAAA8IWiFwDEwcavfLivANgXjzzyiFpaWqxjmBsyZIhJuxTZK8z7gCbCL1cDAAAAAFRThI1pbPwCUK8JEybo4x//eMfXKSVJ0rJly/Q3f/M3VrFKZ7XQQJEdZjwvAkjsGiiK94Erg1YAAACgZ0SYCzAnBVAVWZZpwIABu7z+9re/Xc3NzR1fjxkzpsxYpdu6datJuxTZYcb7gEuiAAsAaCwR7s3e8zF2aAwR+gry836Oud4AAOqxevVqnXfeedYxSnPKKaeYtEuRHWbYNZBfhAme5/Mc4RwDqBau2d3Hs3PhSYS+gvz4HRAAgCro3bu3dYRSrVixwqRdiuxAYJ4neBKDfwDlirDwSMEGqIYI1xvk5/0cR9jJ7nm+0v57wjjPAKruoIMO0he/+EUtWrRIkvT1r3/dOFHPeuqpp0zapcgOAAAqwftEHkB1cL1pDCyMAgCqYOHChbr66qutY5TmrLPOMmmXInuFRViV955P8p/Rez7vOy8i9BPJ/3lGfhHei97zeb/eSBzDRhChL3OegfrQl/OLcE1EfhHOcYSMQE8ZOnSorrnmGs2fP18pJU2ZMsU6Uo965JFH9KEPfaj0dimyV1iEHTZe80n+M7Z/vBH5eO4nUoz3IYrh+b3o/X0oxXkvsiuy+jz3ZYnzDOwLrtn5eb4mMr4pToS+4vU8RznHiG3jxo369re/rVdffdU6SikGDhxo0i5FdpiJsKvB++4Qz4NWiQEDAAAA4mKuUn3MSYvBMQR8+MlPfqLbbrvNOoa5fv36mbRbd5E9y7KFkobu4duvppQGd/n5N0m6StL5ko6RtEnSLEn/llKauoc23i7pWklnSTpC0mpJzZI+l1L6Qx0Zh0l6StL+kn6QUrrgDX723ZL+t6Q/kTSora1nJd26p3wAAMCvCBNl7/kiTEI5hgAA+BJhJztQVdu3b9fWrVslSYceeqhxGh8mTJhg0u6+7mR/TdKtu3l9fecvsiw7WNJ0SSdKek7SNyQdIOkcSQ9kWXZFSukrXf7OKaoV1A+U9Iik/yfpbZLOkzQuy7L3pZQe31OwLMv6SPqepO17+5/Isuw6SZ+XtFLSzyW9IukwSSMljZZEkR0AgE4iFLA9f7qnfYLn/TFfEc4zACAO7/cVz2MHiQIxgL37wAc+oM2bN1vHcGXq1Kn65Cc/udvvZVl2uaRLJR3d9tJzkv4ppfRA2/fPbfv+KarViseklP6rnnb3tci+NqV0Qx0/d4NqBfafSPpwSmlbW9A3S5op6UtZlv0ipTSv09/5lmoF9v+TUrql/cUsy06X9GtJd2VZ9j9SSlv30OZnJTVJ+jtJX95TsCzLPqhagf1Xks5NKa3r8v396vj/QwEY0AAoi/cJXrsIGQFr7JYDUBauN/l5nvNFOYYA8EYuv/xyffWrX93l9S1bthik8WHVqlVv9O2XVHvyyjxJvSRdJOmnWZa9M6X0jGqbxH8j6fuS7tqXdnvqmezntv359+0FdklKKa3IsuzfJN0m6TJJ/1fqeExMk6Tl6lIgTynNyLLsPtV2tP+ZpPu7NpZl2f+UdL2kz0l6Zk+hsizrJelfJG2U9NGuBfa29vZUxAcABOV5gifF+EXGEY5hBN4LNt7fh5L/xSgeF9MYoizeIh/v5zjC9SZCX/GeL8J5BmBn3LhxGjdu3C6vz5o1S5MmTTJIZO+ZZ57RjBkzNGrUKPXu3Xun76WU7uvy49dmWfZJSadLeial9D1JyrLssH1td1+L7P2yLLtA0lGSNqhW0P51Sqm1y8+1P5/9hd38N9pfO3M3P78wpbS7x710/js7FdmzLBug2srC7yV9UdIZb5D/T1R7PvwUSWuyLPsL1Xbcb5I0M6U04w3+bjgMaPJjQJOf9/ch57gxeH8fSr6L2FEK2GgM3hcqAABxeB5/SdxXAHTfEUccYR3BzIoVK/T5z39eI0aM0E033bRLob1dlmW9JX1Q0ptU272ey74W2Qer9tzzzl7MsuwTKaVpnV5bKektqhW0Z3f5+be3/XlCl5+XpKF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      "text/plain": [
       "<Figure size 1800x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import missingno as msno\n",
    "msno.matrix(df)\n",
    "print('Missing values per column')\n",
    "nulls = [(df[feature].isnull().sum(), feature) for feature in df.columns]\n",
    "print(sorted(nulls))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "middle-champagne",
   "metadata": {},
   "source": [
    "- The income column is shown as having no missing values, but in reality it has missing values encoded as \"-1\".\n",
    "- Some columns such as age, height, orientation, have no missing values, whereas most of the other columns do have missing values. This means that when a user signs up for OKCupid there are required and optional fields for the user to fill."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "religious-innocent",
   "metadata": {},
   "source": [
    "## Inspection Recap"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "polished-collapse",
   "metadata": {},
   "source": [
    "In this section we have learned the following:\n",
    "- The sample size is 59,946\n",
    "- There are 30 features to describe each user, 3 of which are numeric, the rest are categorical or text\n",
    "- Users were given Optional and Required fields upon signing up. A lot of users do not supply complete data.\n",
    "- The income column uses -1 as its placeholder for missing data\n",
    "- This data sample was collected from the year 2012\n",
    "- The text data is formatted as HTML\n",
    "- The essay questions are good candidates for analysis using Natural Language Processing\n",
    "- Some of the columns can be split up to give us more features"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "passing-activity",
   "metadata": {},
   "source": [
    "# Cleaning and Tidying"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "approximate-elizabeth",
   "metadata": {},
   "source": [
    "The data has to be cleaned and preprocessed before it can be analyzed. Let's start with replacing the '-1' in the income field with **NaN**, the null value recognized by Pandas and NumPy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "informative-meaning",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "df.income.replace(-1, np.nan, inplace = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "swiss-chemical",
   "metadata": {},
   "source": [
    "We can reinspect the missing values visualization to confirm the replacement of the null values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "operating-conversation",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Missing values per column\n",
      "[(0, 'age'), (0, 'last_online'), (0, 'location'), (0, 'orientation'), (0, 'sex'), (0, 'status'), (3, 'height'), (50, 'speaks'), (2985, 'drinks'), (5296, 'body_type'), (5488, 'essay0'), (5512, 'smokes'), (5680, 'ethnicity'), (6628, 'education'), (7572, 'essay1'), (8198, 'job'), (9638, 'essay2'), (10537, 'essay4'), (10850, 'essay5'), (11056, 'sign'), (11476, 'essay3'), (12451, 'essay7'), (12603, 'essay9'), (13771, 'essay6'), (14080, 'drugs'), (19225, 'essay8'), (19921, 'pets'), (20226, 'religion'), (24395, 'diet'), (35561, 'offspring'), (48442, 'income')]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "msno.matrix(df)\n",
    "print('Missing values per column')\n",
    "nulls = [(df[feature].isnull().sum(), feature) for feature in df.columns]\n",
    "print(sorted(nulls))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "experienced-benchmark",
   "metadata": {},
   "source": [
    "It appears that income is one of the pieces of information that people would least like to share. Later on, we could make a detailed comparison of the percentage of missing values of each column to evaluate \"willingness of users to share information\"."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "documentary-potter",
   "metadata": {},
   "source": [
    "Let's move on to the HTML formatted text data. Not only is it more difficult to read, it is also not suitable for Natural Language Processing. Let's clean up the text using an HTML Parser and Regex. I will demonstrate the process when applied to a single entry first."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "shared-marijuana",
   "metadata": {},
   "outputs": [],
   "source": [
    "from bs4 import BeautifulSoup\n",
    "import re\n",
    "\n",
    "#Create html_parser function\n",
    "def html_parser(raw_html):\n",
    "    raw_html = str(raw_html)\n",
    "    soup = BeautifulSoup(raw_html, 'html.parser')\n",
    "    soup_string = soup.get_text()\n",
    "    soup_string = re.sub('<.*>', ' ', soup_string)\n",
    "    return soup_string"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "connected-holly",
   "metadata": {},
   "source": [
    "**Before:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "hungry-memory",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "you want to be swept off your feet!<br />\n",
      "you are tired of the norm.<br />\n",
      "you want to catch a coffee or a bite.<br />\n",
      "or if you want to talk philosophy.\n"
     ]
    }
   ],
   "source": [
    "print(df.essay9[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aboriginal-contemporary",
   "metadata": {},
   "source": [
    "**After:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "offshore-affiliate",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "you want to be swept off your feet!\n",
      "you are tired of the norm.\n",
      "you want to catch a coffee or a bite.\n",
      "or if you want to talk philosophy.\n"
     ]
    }
   ],
   "source": [
    "print(html_parser(df.essay9[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "standing-addition",
   "metadata": {},
   "source": [
    "Now let's apply this to all of the text in the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "noble-shark",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Takes a few minutes - Parse all the raw HTML in the data\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "object_cols = [series for series in df.columns if df[series].dtype == 'O']\n",
    "for series in object_cols:\n",
    "    df[series] = df[series].apply(lambda row: html_parser(row) if pd.notnull(row) else row)\n",
    "\n",
    "# warnings.resetwarnings()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "another-blond",
   "metadata": {},
   "source": [
    "Lots of warnings given, mostly because users are including YouTube URLs. It's good to be made aware, as the URLs could affect the anlaysis later."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "natural-little",
   "metadata": {},
   "source": [
    "## Cleaning Recap"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "private-constraint",
   "metadata": {},
   "source": [
    "In this section, we accomplished the following:\n",
    "- The -1 values of income have been replaced with NaN, making it consistent with the null placeholders used by the other columns, and recognized by Pandas and NumPy\n",
    "- All HTML formatted text has been converted to normal, readable text. A caveat though is that it still includes '\\n', the carriage return symbol, which is parsed by python when the text is input to the print() function."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "foreign-plain",
   "metadata": {},
   "source": [
    "# Feature Engineering Part 1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "vocal-floating",
   "metadata": {},
   "source": [
    "Machine Learning can work better if there are more columns because we're giving it more points of comparison. The addition of more columns, also called features, is feature engineering.\n",
    "\n",
    "I'm going to back up the dataframe in its current form, so that even after modification and addition of columns, we can easily refer to the original data if necessary."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "secure-basis",
   "metadata": {},
   "outputs": [],
   "source": [
    "original_df_backup = df.copy(deep = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "foster-reflection",
   "metadata": {},
   "source": [
    "## Splitting Columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "environmental-bargain",
   "metadata": {},
   "source": [
    "We can produce new features by splitting the existing ones. Some of our features are actually describing two variables that are potentially independent of each other. Later on, before we develop our model, we will investigate variable codependence by checking Pearson correlations."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cooperative-rwanda",
   "metadata": {},
   "source": [
    "### Splitting various columns into two"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "arbitrary-software",
   "metadata": {},
   "outputs": [],
   "source": [
    "def two_split_columns(delimiter, df, feature, col1_name, col2_name, swap = False, stringify_None = False, strip = False):\n",
    "    '''splits a column into two. Takes a delimiter, DataFrame, and Series name'''\n",
    "    new = df[feature].str.split(delimiter, n = 1, expand = True) \n",
    "    if swap:\n",
    "        new[1] = new.apply(lambda row: row[0] if not(isinstance(row[1], str)) else row[1], axis = 1)\n",
    "        new[0] = new.apply(lambda row: '[No Prefix]' if row[0] == row[1] else row[0], axis = 1)\n",
    "    if stringify_None:\n",
    "        new[1] = new[1].apply(lambda col: 'None' if col is None else col)\n",
    "        new[0] = new[0].apply(lambda col: 'None' if col is None else col)\n",
    "    if strip:\n",
    "        new[1] = new[1].apply(lambda col: col.strip() if isinstance(col, str) else col)\n",
    "        new[0] = new[0].apply(lambda col: col.strip() if isinstance(col, str) else col)      \n",
    "    df[col1_name]= new[0] \n",
    "    df[col2_name]= new[1]\n",
    "    return new\n",
    "\n",
    "two_split_columns(\" \", df, \"diet\", \"diet_adherence\", \"diet_type\", True)\n",
    "two_split_columns(\",\", df, \"location\", \"city\", \"state/country\")\n",
    "two_split_columns(\",\", df, \"offspring\", \"offspring_want\", \"offspring_attitude\", False, False)\n",
    "##Religion\n",
    "df['temp'] = df['religion'].apply(lambda col: col.replace(\"but\", \"and\") if isinstance(col, str) else col)\n",
    "two_split_columns(\"and\", df, \"temp\", \"religion_type\", \"religion_attitude\", stringify_None = True, strip = True)\n",
    "del df['temp']\n",
    "## Sign\n",
    "df['temp'] = df['sign'].apply(lambda col: col.replace(\"but\", \"and\") if isinstance(col, str) else col)\n",
    "two_split_columns(\"and\", df, \"temp\", \"sign_type\", \"sign_attitude\", stringify_None = True, strip = True)\n",
    "del df['temp']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "important-pressing",
   "metadata": {},
   "source": [
    "Columns split in two:\n",
    "\n",
    "| Original Feature        | New Feature 1      | New Feature 2|\n",
    "| :------------- | :---------- | :---------- |\n",
    "| diet | diet_adherence| diet_type|\n",
    "| location | city| state|\n",
    "| offspring | offspring_want| offspring_attitude|\n",
    "| religion | religion_type| religion_attitude|\n",
    "| sign | sign_type| sign_attitude|"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acceptable-ladder",
   "metadata": {},
   "source": [
    "### Splitting 'pets'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aggressive-corrections",
   "metadata": {},
   "source": [
    "There are really two kinds of pets among the values: dogs and cats. Let's proceed by splitting 'pets' into 'dogs' and 'cats'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "deadly-jewel",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "temp = two_split_columns(\"and\", df, \"pets\", \"dogs\", \"cats\", False, False, strip = True)\n",
    "temp[1] = temp.apply(lambda row: row[0] if \"cat\" in str(row[0]) else row[1], axis = 1)\n",
    "temp[0] = temp.apply(lambda row: None if \"cat\" in str(row[0]) else row[0], axis = 1)\n",
    "df[\"dogs\"] = temp[0]\n",
    "df[\"cats\"] = temp[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "defined-thursday",
   "metadata": {},
   "source": [
    "Having a pet can have nothing to do with liking a pet. Let's  further split this into 'dog_preference', 'has_dogs', 'cat_preference', 'has_cats'. Let's also remove 'dogs' and 'cats'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "solar-identifier",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['dog_preference'] = df.apply(lambda row: row['dogs'] if \"like\" in str(row['dogs']) else None, axis = 1)\n",
    "df['cat_preference'] = df.apply(lambda row: row['cats'] if \"like\" in str(row['cats']) else None, axis = 1)\n",
    "df['has_dogs'] =  df.apply(lambda row: 1 if \"has\" in str(row['dogs']) else 0, axis = 1)\n",
    "df['has_dogs'] =  df.apply(lambda row: row['has_dogs'] if isinstance(row['pets'], str) else None, axis = 1)\n",
    "df['has_cats'] =  df.apply(lambda row: 1 if \"has\" in str(row['cats']) else 0, axis = 1)\n",
    "df['has_cats'] =  df.apply(lambda row: row['has_cats'] if isinstance(row['pets'], str) else None, axis = 1)\n",
    "del df['dogs']\n",
    "del df['cats']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "native-steam",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dog_preference</th>\n",
       "      <th>has_dogs</th>\n",
       "      <th>cat_preference</th>\n",
       "      <th>has_cats</th>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>likes cats</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>likes dogs</td>\n",
       "      <td>0.0</td>\n",
       "      <td>likes cats</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  dog_preference  has_dogs cat_preference  has_cats\n",
       "0     likes dogs       0.0     likes cats       0.0\n",
       "1     likes dogs       0.0     likes cats       0.0\n",
       "2           None       0.0           None       1.0\n",
       "3           None       0.0     likes cats       0.0\n",
       "4     likes dogs       0.0     likes cats       0.0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['dog_preference', 'has_dogs', 'cat_preference', 'has_cats']].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "civilian-maine",
   "metadata": {},
   "source": [
    "### Splitting 'speaks'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "interior-stroke",
   "metadata": {},
   "source": [
    "There's quite some unpacking that needs to be done here. There appear to be several different languages and different options for fluency. Before we start making new columns, let's get a better sense for what exactly our values are."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "simplified-afternoon",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 77 different language options:\n",
      "['afrikaans', 'albanian', 'ancient greek', 'arabic', 'armenian', 'basque', 'belarusan', 'bengali', 'breton', 'bulgarian', 'c++', 'catalan', 'cebuano', 'chechen', 'chinese', 'croatian', 'czech', 'danish', 'dutch', 'english', 'esperanto', 'estonian', 'farsi', 'finnish', 'french', 'frisian', 'georgian', 'german', 'greek', 'gujarati', 'hawaiian', 'hebrew', 'hindi', 'hungarian', 'icelandic', 'ilongo', 'indonesian', 'irish', 'italian', 'japanese', 'khmer', 'korean', 'latin', 'latvian', 'lisp', 'lithuanian', 'malay', 'maori', 'mongolian', 'norwegian', 'occitan', 'other', 'persian', 'polish', 'portuguese', 'romanian', 'rotuman', 'russian', 'sanskrit', 'sardinian', 'serbian', 'sign language', 'slovak', 'slovenian', 'spanish', 'swahili', 'swedish', 'tagalog', 'tamil', 'thai', 'tibetan', 'turkish', 'ukrainian', 'urdu', 'vietnamese', 'welsh', 'yiddish']\n",
      "There are 4 different fluency options per language:\n",
      "['afrikaans', 'afrikaans (fluently)', 'afrikaans (okay)', 'afrikaans (poorly)']\n"
     ]
    }
   ],
   "source": [
    "languages = df.speaks.value_counts()\n",
    "languages = languages.index\n",
    "languages = [each.split(',') for each in languages]\n",
    "languages = [item for sublist in languages for item in sublist]\n",
    "languages = set([each.strip() for each in languages])\n",
    "temp = languages\n",
    "languages = [each.split(\" (\") for each in languages]\n",
    "languages = [each[0] for each in languages]\n",
    "languages = sorted(set(languages))\n",
    "print(\"There are {} different language options:\".format(len(languages)))\n",
    "print(languages)\n",
    "print(\"There are 4 different fluency options per language:\")\n",
    "print(sorted(temp)[:4])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "marked-firmware",
   "metadata": {},
   "source": [
    "After isolation of terms it is revealed that among the 'speaks' values there are 77 different languages and four different descriptors of language fluency. The ambiguity of the fluency options presents a dilemma. What is 'afrikaans' supposed to mean compared to 'afrikaans (okay)'? Because of this ambiguity, we will not make use of the fluency descriptors in our visualization. We will create a new column for each language containing a 1 to indicate if the language is spoken, 0 if not. The result is actually called a sparse matrix. 'Sparse' because it contains much more 0s than 1s."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "contemporary-bailey",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Takes a few minutes\n",
    "for language in languages:\n",
    "    df[language] = df.apply(lambda row: 1 if (language in str(row['speaks'])) else 0, axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "suburban-regular",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   afrikaans  albanian  ancient greek  arabic  armenian  basque  belarusan  \\\n",
       "0          0         0              0       0         0       0          0   \n",
       "1          0         0              0       0         0       0          0   \n",
       "2          0         0              0       0         0       0          0   \n",
       "\n",
       "   bengali  breton  bulgarian  c++  catalan  cebuano  chechen  chinese  \\\n",
       "0        0       0          0    0        0        0        0        0   \n",
       "1        0       0          0    0        0        0        0        0   \n",
       "2        0       0          0    1        0        0        0        0   \n",
       "\n",
       "   croatian  czech  danish  dutch  english  esperanto  estonian  farsi  \\\n",
       "0         0      0       0      0        1          0         0      0   \n",
       "1         0      0       0      0        1          0         0      0   \n",
       "2         0      0       0      0        1          0         0      0   \n",
       "\n",
       "   finnish  french  frisian  georgian  german  greek  gujarati  hawaiian  \\\n",
       "0        0       0        0         0       0      0         0         0   \n",
       "1        0       1        0         0       0      0         0         0   \n",
       "2        0       1        0         0       0      0         0         0   \n",
       "\n",
       "   hebrew  hindi  hungarian  icelandic  ilongo  indonesian  irish  italian  \\\n",
       "0       0      0          0          0       0           0      0        0   \n",
       "1       0      0          0          0       0           0      0        0   \n",
       "2       0      0          0          0       0           0      0        0   \n",
       "\n",
       "   japanese  khmer  korean  latin  latvian  lisp  lithuanian  malay  maori  \\\n",
       "0         0      0       0      0        0     0           0      0      0   \n",
       "1         0      0       0      0        0     0           0      0      0   \n",
       "2         0      0       0      0        0     0           0      0      0   \n",
       "\n",
       "   mongolian  norwegian  occitan  other  persian  polish  portuguese  \\\n",
       "0          0          0        0      0        0       0           0   \n",
       "1          0          0        0      0        0       0           0   \n",
       "2          0          0        0      0        0       0           0   \n",
       "\n",
       "   romanian  rotuman  russian  sanskrit  sardinian  serbian  sign language  \\\n",
       "0         0        0        0         0          0        0              0   \n",
       "1         0        0        0         0          0        0              0   \n",
       "2         0        0        0         0          0        0              0   \n",
       "\n",
       "   slovak  slovenian  spanish  swahili  swedish  tagalog  tamil  thai  \\\n",
       "0       0          0        0        0        0        0      0     0   \n",
       "1       0          0        1        0        0        0      0     0   \n",
       "2       0          0        0        0        0        0      0     0   \n",
       "\n",
       "   tibetan  turkish  ukrainian  urdu  vietnamese  welsh  yiddish  \n",
       "0        0        0          0     0           0      0        0  \n",
       "1        0        0          0     0           0      0        0  \n",
       "2        0        0          0     0           0      0        0  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[languages].head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "democratic-railway",
   "metadata": {},
   "source": [
    "Print memory usage function. Let's investigate the memory being used up by the sparse matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "minor-management",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Memory usage is 36.927 MB\n"
     ]
    }
   ],
   "source": [
    "#Credit where credit is due: Function from Dafni Sidiropoulou Velidou's article \"Working with sparse data sets in pandas and sklearn\"\n",
    "BYTES_TO_MB_DIV = 0.000001\n",
    "def print_memory_usage_of_data_frame(df):\n",
    "    mem = round(df.memory_usage().sum() * BYTES_TO_MB_DIV, 3) \n",
    "    print(\"Memory usage is \" + str(mem) + \" MB\")\n",
    "    \n",
    "print_memory_usage_of_data_frame(df[languages])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "capital-memory",
   "metadata": {},
   "source": [
    "Converting our sparse matrix to a Pandas Sparse Array reduces its memory usage and allows AI algorithms to take less time training on it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "hindu-affect",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Memory usage is 0.553 MB\n"
     ]
    }
   ],
   "source": [
    "temp = df[languages].copy()\n",
    "for (columnName, columnData) in temp.iteritems():\n",
    "    df[columnName] = pd.arrays.SparseArray(columnData.values, dtype='uint8')\n",
    "\n",
    "print_memory_usage_of_data_frame(df[languages])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "amateur-island",
   "metadata": {},
   "source": [
    "## Adding columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "facial-office",
   "metadata": {},
   "source": [
    "There are other ways to derive new features in addition to splitting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "studied-carnival",
   "metadata": {},
   "outputs": [],
   "source": [
    "temp = df['ethnicity'].apply(lambda col: col.split(\",\") if isinstance(col, str) else col)\n",
    "df['num_ethnicities'] = temp.apply(lambda col: len(col) if isinstance(col, list) else col)\n",
    "df['optional_%unfilled'] = ((original_df_backup.isnull().sum(axis = 1))/24) * 100\n",
    "df['num_languages'] = df[languages].sum(axis = 1).replace(0, None)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "processed-state",
   "metadata": {},
   "source": [
    "Added Columns:\n",
    "\n",
    "| New Feature        | Description      |\n",
    "| :------------- | :---------- |\n",
    "| num_ethnicities |Contains the number of ethnicities listed in 'ethnicity'|\n",
    "| optional_%unfilled |Percentage of optional fields unfilled|\n",
    "| num_languages|Count of languages spoken|"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "spanish-walter",
   "metadata": {},
   "source": [
    "## Feature Engineering Part 1 Recap"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "smoking-louis",
   "metadata": {},
   "source": [
    "In this section, we accomplished the following:\n",
    "- We split the following columns into two:\n",
    "\n",
    "| Original Feature        | New Feature 1      | New Feature 2|\n",
    "| :------------- | :---------- | :---------- |\n",
    "| diet | diet_adherence| diet_type|\n",
    "| location | city| state|\n",
    "| offspring | offspring_want| offspring_attitude|\n",
    "| religion | religion_type| religion_attitude|\n",
    "| sign | sign_type| sign_attitude|\n",
    "\n",
    "- We split 'pets' into 'dog_preference', 'has_dogs', 'cat_preference', 'has_cats'\n",
    "- We expanded 'speaks' into a boolean matrix where each column is a language and each row value is 1 or 0\n",
    "- We introduced the following additional columns:\n",
    "\n",
    "| New Feature        | Description      |\n",
    "| :------------- | :---------- |\n",
    "| num_ethnicities |Contains the number of ethnicities listed in 'ethnicity'|\n",
    "| optional_%unfilled |Percentage of optional fields unfilled|\n",
    "| num_languages|Count of languages spoken|"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "vietnamese-livestock",
   "metadata": {},
   "source": [
    "# Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "first-creativity",
   "metadata": {},
   "source": [
    "## Numerical Features"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "oriental-finger",
   "metadata": {},
   "source": [
    "The best way to explore data is to visualize it. Let's start by generating histograms and boxplots of our numerical features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "matched-playlist",
   "metadata": {},
   "outputs": [
    {
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xt=(c+(n=n+Math.imul(f,J)|0)|0)+((8191&(i=(i=i+Math.imul(f,K)|0)+Math.imul(h,J)|0))<<13)|0;c=((a=a+Math.imul(h,K)|0)+(i>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(T,U),i=(i=Math.imul(T,V))+Math.imul(k,U)|0,a=Math.imul(k,V),n=n+Math.imul(b,H)|0,i=(i=i+Math.imul(b,G)|0)+Math.imul(_,H)|0,a=a+Math.imul(_,G)|0,n=n+Math.imul(v,W)|0,i=(i=i+Math.imul(v,X)|0)+Math.imul(y,W)|0,a=a+Math.imul(y,X)|0,n=n+Math.imul(d,J)|0,i=(i=i+Math.imul(d,K)|0)+Math.imul(g,J)|0,a=a+Math.imul(g,K)|0;var bt=(c+(n=n+Math.imul(f,$)|0)|0)+((8191&(i=(i=i+Math.imul(f,tt)|0)+Math.imul(h,$)|0))<<13)|0;c=((a=a+Math.imul(h,tt)|0)+(i>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(A,U),i=(i=Math.imul(A,V))+Math.imul(S,U)|0,a=Math.imul(S,V),n=n+Math.imul(T,H)|0,i=(i=i+Math.imul(T,G)|0)+Math.imul(k,H)|0,a=a+Math.imul(k,G)|0,n=n+Math.imul(b,W)|0,i=(i=i+Math.imul(b,X)|0)+Math.imul(_,W)|0,a=a+Math.imul(_,X)|0,n=n+Math.imul(v,J)|0,i=(i=i+Math.imul(v,K)|0)+Math.imul(y,J)|0,a=a+Math.imul(y,K)|0,n=n+Math.imul(d,$)|0,i=(i=i+Math.imul(d,tt)|0)+Math.imul(g,$)|0,a=a+Math.imul(g,tt)|0;var _t=(c+(n=n+Math.imul(f,rt)|0)|0)+((8191&(i=(i=i+Math.imul(f,nt)|0)+Math.imul(h,rt)|0))<<13)|0;c=((a=a+Math.imul(h,nt)|0)+(i>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(C,U),i=(i=Math.imul(C,V))+Math.imul(L,U)|0,a=Math.imul(L,V),n=n+Math.imul(A,H)|0,i=(i=i+Math.imul(A,G)|0)+Math.imul(S,H)|0,a=a+Math.imul(S,G)|0,n=n+Math.imul(T,W)|0,i=(i=i+Math.imul(T,X)|0)+Math.imul(k,W)|0,a=a+Math.imul(k,X)|0,n=n+Math.imul(b,J)|0,i=(i=i+Math.imul(b,K)|0)+Math.imul(_,J)|0,a=a+Math.imul(_,K)|0,n=n+Math.imul(v,$)|0,i=(i=i+Math.imul(v,tt)|0)+Math.imul(y,$)|0,a=a+Math.imul(y,tt)|0,n=n+Math.imul(d,rt)|0,i=(i=i+Math.imul(d,nt)|0)+Math.imul(g,rt)|0,a=a+Math.imul(g,nt)|0;var wt=(c+(n=n+Math.imul(f,at)|0)|0)+((8191&(i=(i=i+Math.imul(f,ot)|0)+Math.imul(h,at)|0))<<13)|0;c=((a=a+Math.imul(h,ot)|0)+(i>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(P,U),i=(i=Math.imul(P,V))+Math.imul(z,U)|0,a=Math.imul(z,V),n=n+Math.imul(C,H)|0,i=(i=i+Math.imul(C,G)|0)+Math.imul(L,H)|0,a=a+Math.imul(L,G)|0,n=n+Math.imul(A,W)|0,i=(i=i+Math.imul(A,X)|0)+Math.imul(S,W)|0,a=a+Math.imul(S,X)|0,n=n+Math.imul(T,J)|0,i=(i=i+Math.imul(T,K)|0)+Math.imul(k,J)|0,a=a+Math.imul(k,K)|0,n=n+Math.imul(b,$)|0,i=(i=i+Math.imul(b,tt)|0)+Math.imul(_,$)|0,a=a+Math.imul(_,tt)|0,n=n+Math.imul(v,rt)|0,i=(i=i+Math.imul(v,nt)|0)+Math.imul(y,rt)|0,a=a+Math.imul(y,nt)|0,n=n+Math.imul(d,at)|0,i=(i=i+Math.imul(d,ot)|0)+Math.imul(g,at)|0,a=a+Math.imul(g,ot)|0;var Tt=(c+(n=n+Math.imul(f,lt)|0)|0)+((8191&(i=(i=i+Math.imul(f,ct)|0)+Math.imul(h,lt)|0))<<13)|0;c=((a=a+Math.imul(h,ct)|0)+(i>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(D,U),i=(i=Math.imul(D,V))+Math.imul(R,U)|0,a=Math.imul(R,V),n=n+Math.imul(P,H)|0,i=(i=i+Math.imul(P,G)|0)+Math.imul(z,H)|0,a=a+Math.imul(z,G)|0,n=n+Math.imul(C,W)|0,i=(i=i+Math.imul(C,X)|0)+Math.imul(L,W)|0,a=a+Math.imul(L,X)|0,n=n+Math.imul(A,J)|0,i=(i=i+Math.imul(A,K)|0)+Math.imul(S,J)|0,a=a+Math.imul(S,K)|0,n=n+Math.imul(T,$)|0,i=(i=i+Math.imul(T,tt)|0)+Math.imul(k,$)|0,a=a+Math.imul(k,tt)|0,n=n+Math.imul(b,rt)|0,i=(i=i+Math.imul(b,nt)|0)+Math.imul(_,rt)|0,a=a+Math.imul(_,nt)|0,n=n+Math.imul(v,at)|0,i=(i=i+Math.imul(v,ot)|0)+Math.imul(y,at)|0,a=a+Math.imul(y,ot)|0,n=n+Math.imul(d,lt)|0,i=(i=i+Math.imul(d,ct)|0)+Math.imul(g,lt)|0,a=a+Math.imul(g,ct)|0;var kt=(c+(n=n+Math.imul(f,ft)|0)|0)+((8191&(i=(i=i+Math.imul(f,ht)|0)+Math.imul(h,ft)|0))<<13)|0;c=((a=a+Math.imul(h,ht)|0)+(i>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(B,U),i=(i=Math.imul(B,V))+Math.imul(N,U)|0,a=Math.imul(N,V),n=n+Math.imul(D,H)|0,i=(i=i+Math.imul(D,G)|0)+Math.imul(R,H)|0,a=a+Math.imul(R,G)|0,n=n+Math.imul(P,W)|0,i=(i=i+Math.imul(P,X)|0)+Math.imul(z,W)|0,a=a+Math.imul(z,X)|0,n=n+Math.imul(C,J)|0,i=(i=i+Math.imul(C,K)|0)+Math.imul(L,J)|0,a=a+Math.imul(L,K)|0,n=n+Math.imul(A,$)|0,i=(i=i+Math.imul(A,tt)|0)+Math.imul(S,$)|0,a=a+Math.imul(S,tt)|0,n=n+Math.imul(T,rt)|0,i=(i=i+Math.imul(T,nt)|0)+Math.imul(k,rt)|0,a=a+Math.imul(k,nt)|0,n=n+Math.imul(b,at)|0,i=(i=i+Math.imul(b,ot)|0)+Math.imul(_,at)|0,a=a+Math.imul(_,ot)|0,n=n+Math.imul(v,lt)|0,i=(i=i+Math.imul(v,ct)|0)+Math.imul(y,lt)|0,a=a+Math.imul(y,ct)|0,n=n+Math.imul(d,ft)|0,i=(i=i+Math.imul(d,ht)|0)+Math.imul(g,ft)|0,a=a+Math.imul(g,ht)|0;var Mt=(c+(n=n+Math.imul(f,dt)|0)|0)+((8191&(i=(i=i+Math.imul(f,gt)|0)+Math.imul(h,dt)|0))<<13)|0;c=((a=a+Math.imul(h,gt)|0)+(i>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,H),i=(i=Math.imul(B,G))+Math.imul(N,H)|0,a=Math.imul(N,G),n=n+Math.imul(D,W)|0,i=(i=i+Math.imul(D,X)|0)+Math.imul(R,W)|0,a=a+Math.imul(R,X)|0,n=n+Math.imul(P,J)|0,i=(i=i+Math.imul(P,K)|0)+Math.imul(z,J)|0,a=a+Math.imul(z,K)|0,n=n+Math.imul(C,$)|0,i=(i=i+Math.imul(C,tt)|0)+Math.imul(L,$)|0,a=a+Math.imul(L,tt)|0,n=n+Math.imul(A,rt)|0,i=(i=i+Math.imul(A,nt)|0)+Math.imul(S,rt)|0,a=a+Math.imul(S,nt)|0,n=n+Math.imul(T,at)|0,i=(i=i+Math.imul(T,ot)|0)+Math.imul(k,at)|0,a=a+Math.imul(k,ot)|0,n=n+Math.imul(b,lt)|0,i=(i=i+Math.imul(b,ct)|0)+Math.imul(_,lt)|0,a=a+Math.imul(_,ct)|0,n=n+Math.imul(v,ft)|0,i=(i=i+Math.imul(v,ht)|0)+Math.imul(y,ft)|0,a=a+Math.imul(y,ht)|0;var At=(c+(n=n+Math.imul(d,dt)|0)|0)+((8191&(i=(i=i+Math.imul(d,gt)|0)+Math.imul(g,dt)|0))<<13)|0;c=((a=a+Math.imul(g,gt)|0)+(i>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,W),i=(i=Math.imul(B,X))+Math.imul(N,W)|0,a=Math.imul(N,X),n=n+Math.imul(D,J)|0,i=(i=i+Math.imul(D,K)|0)+Math.imul(R,J)|0,a=a+Math.imul(R,K)|0,n=n+Math.imul(P,$)|0,i=(i=i+Math.imul(P,tt)|0)+Math.imul(z,$)|0,a=a+Math.imul(z,tt)|0,n=n+Math.imul(C,rt)|0,i=(i=i+Math.imul(C,nt)|0)+Math.imul(L,rt)|0,a=a+Math.imul(L,nt)|0,n=n+Math.imul(A,at)|0,i=(i=i+Math.imul(A,ot)|0)+Math.imul(S,at)|0,a=a+Math.imul(S,ot)|0,n=n+Math.imul(T,lt)|0,i=(i=i+Math.imul(T,ct)|0)+Math.imul(k,lt)|0,a=a+Math.imul(k,ct)|0,n=n+Math.imul(b,ft)|0,i=(i=i+Math.imul(b,ht)|0)+Math.imul(_,ft)|0,a=a+Math.imul(_,ht)|0;var St=(c+(n=n+Math.imul(v,dt)|0)|0)+((8191&(i=(i=i+Math.imul(v,gt)|0)+Math.imul(y,dt)|0))<<13)|0;c=((a=a+Math.imul(y,gt)|0)+(i>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,J),i=(i=Math.imul(B,K))+Math.imul(N,J)|0,a=Math.imul(N,K),n=n+Math.imul(D,$)|0,i=(i=i+Math.imul(D,tt)|0)+Math.imul(R,$)|0,a=a+Math.imul(R,tt)|0,n=n+Math.imul(P,rt)|0,i=(i=i+Math.imul(P,nt)|0)+Math.imul(z,rt)|0,a=a+Math.imul(z,nt)|0,n=n+Math.imul(C,at)|0,i=(i=i+Math.imul(C,ot)|0)+Math.imul(L,at)|0,a=a+Math.imul(L,ot)|0,n=n+Math.imul(A,lt)|0,i=(i=i+Math.imul(A,ct)|0)+Math.imul(S,lt)|0,a=a+Math.imul(S,ct)|0,n=n+Math.imul(T,ft)|0,i=(i=i+Math.imul(T,ht)|0)+Math.imul(k,ft)|0,a=a+Math.imul(k,ht)|0;var Et=(c+(n=n+Math.imul(b,dt)|0)|0)+((8191&(i=(i=i+Math.imul(b,gt)|0)+Math.imul(_,dt)|0))<<13)|0;c=((a=a+Math.imul(_,gt)|0)+(i>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,$),i=(i=Math.imul(B,tt))+Math.imul(N,$)|0,a=Math.imul(N,tt),n=n+Math.imul(D,rt)|0,i=(i=i+Math.imul(D,nt)|0)+Math.imul(R,rt)|0,a=a+Math.imul(R,nt)|0,n=n+Math.imul(P,at)|0,i=(i=i+Math.imul(P,ot)|0)+Math.imul(z,at)|0,a=a+Math.imul(z,ot)|0,n=n+Math.imul(C,lt)|0,i=(i=i+Math.imul(C,ct)|0)+Math.imul(L,lt)|0,a=a+Math.imul(L,ct)|0,n=n+Math.imul(A,ft)|0,i=(i=i+Math.imul(A,ht)|0)+Math.imul(S,ft)|0,a=a+Math.imul(S,ht)|0;var Ct=(c+(n=n+Math.imul(T,dt)|0)|0)+((8191&(i=(i=i+Math.imul(T,gt)|0)+Math.imul(k,dt)|0))<<13)|0;c=((a=a+Math.imul(k,gt)|0)+(i>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,rt),i=(i=Math.imul(B,nt))+Math.imul(N,rt)|0,a=Math.imul(N,nt),n=n+Math.imul(D,at)|0,i=(i=i+Math.imul(D,ot)|0)+Math.imul(R,at)|0,a=a+Math.imul(R,ot)|0,n=n+Math.imul(P,lt)|0,i=(i=i+Math.imul(P,ct)|0)+Math.imul(z,lt)|0,a=a+Math.imul(z,ct)|0,n=n+Math.imul(C,ft)|0,i=(i=i+Math.imul(C,ht)|0)+Math.imul(L,ft)|0,a=a+Math.imul(L,ht)|0;var Lt=(c+(n=n+Math.imul(A,dt)|0)|0)+((8191&(i=(i=i+Math.imul(A,gt)|0)+Math.imul(S,dt)|0))<<13)|0;c=((a=a+Math.imul(S,gt)|0)+(i>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,at),i=(i=Math.imul(B,ot))+Math.imul(N,at)|0,a=Math.imul(N,ot),n=n+Math.imul(D,lt)|0,i=(i=i+Math.imul(D,ct)|0)+Math.imul(R,lt)|0,a=a+Math.imul(R,ct)|0,n=n+Math.imul(P,ft)|0,i=(i=i+Math.imul(P,ht)|0)+Math.imul(z,ft)|0,a=a+Math.imul(z,ht)|0;var It=(c+(n=n+Math.imul(C,dt)|0)|0)+((8191&(i=(i=i+Math.imul(C,gt)|0)+Math.imul(L,dt)|0))<<13)|0;c=((a=a+Math.imul(L,gt)|0)+(i>>>13)|0)+(It>>>26)|0,It&=67108863,n=Math.imul(B,lt),i=(i=Math.imul(B,ct))+Math.imul(N,lt)|0,a=Math.imul(N,ct),n=n+Math.imul(D,ft)|0,i=(i=i+Math.imul(D,ht)|0)+Math.imul(R,ft)|0,a=a+Math.imul(R,ht)|0;var Pt=(c+(n=n+Math.imul(P,dt)|0)|0)+((8191&(i=(i=i+Math.imul(P,gt)|0)+Math.imul(z,dt)|0))<<13)|0;c=((a=a+Math.imul(z,gt)|0)+(i>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,n=Math.imul(B,ft),i=(i=Math.imul(B,ht))+Math.imul(N,ft)|0,a=Math.imul(N,ht);var zt=(c+(n=n+Math.imul(D,dt)|0)|0)+((8191&(i=(i=i+Math.imul(D,gt)|0)+Math.imul(R,dt)|0))<<13)|0;c=((a=a+Math.imul(R,gt)|0)+(i>>>13)|0)+(zt>>>26)|0,zt&=67108863;var Ot=(c+(n=Math.imul(B,dt))|0)+((8191&(i=(i=Math.imul(B,gt))+Math.imul(N,dt)|0))<<13)|0;return c=((a=Math.imul(N,gt))+(i>>>13)|0)+(Ot>>>26)|0,Ot&=67108863,l[0]=mt,l[1]=vt,l[2]=yt,l[3]=xt,l[4]=bt,l[5]=_t,l[6]=wt,l[7]=Tt,l[8]=kt,l[9]=Mt,l[10]=At,l[11]=St,l[12]=Et,l[13]=Ct,l[14]=Lt,l[15]=It,l[16]=Pt,l[17]=zt,l[18]=Ot,0!==c&&(l[19]=c,r.length++),r};function d(t,e,r){return(new g).mulp(t,e,r)}function g(t,e){this.x=t,this.y=e}Math.imul||(p=h),a.prototype.mulTo=function(t,e){var r=this.length+t.length;return 10===this.length&&10===t.length?p(this,t,e):r<63?h(this,t,e):r<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,i=0,a=0;a<r.length-1;a++){var o=i;i=0;for(var s=67108863&n,l=Math.min(a,e.length-1),c=Math.max(0,a-t.length+1);c<=l;c++){var u=a-c,f=(0|t.words[u])*(0|e.words[c]),h=67108863&f;s=67108863&(h=h+s|0),i+=(o=(o=o+(f/67108864|0)|0)+(h>>>26)|0)>>>26,o&=67108863}r.words[a]=s,n=o,o=i}return 0!==n?r.words[a]=n:r.length--,r.strip()}(this,t,e):d(this,t,e)},g.prototype.makeRBT=function(t){for(var e=new Array(t),r=a.prototype._countBits(t)-1,n=0;n<t;n++)e[n]=this.revBin(n,r,t);return e},g.prototype.revBin=function(t,e,r){if(0===t||t===r-1)return t;for(var n=0,i=0;i<e;i++)n|=(1&t)<<e-i-1,t>>=1;return n},g.prototype.permute=function(t,e,r,n,i,a){for(var o=0;o<a;o++)n[o]=e[t[o]],i[o]=r[t[o]]},g.prototype.transform=function(t,e,r,n,i,a){this.permute(a,t,e,r,n,i);for(var o=1;o<i;o<<=1)for(var s=o<<1,l=Math.cos(2*Math.PI/s),c=Math.sin(2*Math.PI/s),u=0;u<i;u+=s)for(var f=l,h=c,p=0;p<o;p++){var d=r[u+p],g=n[u+p],m=r[u+p+o],v=n[u+p+o],y=f*m-h*v;v=f*v+h*m,m=y,r[u+p]=d+m,n[u+p]=g+v,r[u+p+o]=d-m,n[u+p+o]=g-v,p!==s&&(y=l*f-c*h,h=l*h+c*f,f=y)}},g.prototype.guessLen13b=function(t,e){var r=1|Math.max(e,t),n=1&r,i=0;for(r=r/2|0;r;r>>>=1)i++;return 1<<i+1+n},g.prototype.conjugate=function(t,e,r){if(!(r<=1))for(var n=0;n<r/2;n++){var i=t[n];t[n]=t[r-n-1],t[r-n-1]=i,i=e[n],e[n]=-e[r-n-1],e[r-n-1]=-i}},g.prototype.normalize13b=function(t,e){for(var r=0,n=0;n<e/2;n++){var i=8192*Math.round(t[2*n+1]/e)+Math.round(t[2*n]/e)+r;t[n]=67108863&i,r=i<67108864?0:i/67108864|0}return t},g.prototype.convert13b=function(t,e,r,i){for(var a=0,o=0;o<e;o++)a+=0|t[o],r[2*o]=8191&a,a>>>=13,r[2*o+1]=8191&a,a>>>=13;for(o=2*e;o<i;++o)r[o]=0;n(0===a),n(0==(-8192&a))},g.prototype.stub=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=0;return e},g.prototype.mulp=function(t,e,r){var n=2*this.guessLen13b(t.length,e.length),i=this.makeRBT(n),a=this.stub(n),o=new Array(n),s=new Array(n),l=new Array(n),c=new Array(n),u=new Array(n),f=new Array(n),h=r.words;h.length=n,this.convert13b(t.words,t.length,o,n),this.convert13b(e.words,e.length,c,n),this.transform(o,a,s,l,n,i),this.transform(c,a,u,f,n,i);for(var p=0;p<n;p++){var d=s[p]*u[p]-l[p]*f[p];l[p]=s[p]*f[p]+l[p]*u[p],s[p]=d}return this.conjugate(s,l,n),this.transform(s,l,h,a,n,i),this.conjugate(h,a,n),this.normalize13b(h,n),r.negative=t.negative^e.negative,r.length=t.length+e.length,r.strip()},a.prototype.mul=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},a.prototype.mulf=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),d(this,t,e)},a.prototype.imul=function(t){return this.clone().mulTo(t,this)},a.prototype.imuln=function(t){n(\"number\"==typeof t),n(t<67108864);for(var e=0,r=0;r<this.length;r++){var i=(0|this.words[r])*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[r]=67108863&a}return 0!==e&&(this.words[r]=e,this.length++),this},a.prototype.muln=function(t){return this.clone().imuln(t)},a.prototype.sqr=function(){return this.mul(this)},a.prototype.isqr=function(){return this.imul(this.clone())},a.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r<e.length;r++){var n=r/26|0,i=r%26;e[r]=(t.words[n]&1<<i)>>>i}return e}(t);if(0===e.length)return new a(1);for(var r=this,n=0;n<e.length&&0===e[n];n++,r=r.sqr());if(++n<e.length)for(var i=r.sqr();n<e.length;n++,i=i.sqr())0!==e[n]&&(r=r.mul(i));return r},a.prototype.iushln=function(t){n(\"number\"==typeof t&&t>=0);var e,r=t%26,i=(t-r)/26,a=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e<this.length;e++){var s=this.words[e]&a,l=(0|this.words[e])-s<<r;this.words[e]=l|o,o=s>>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==i){for(e=this.length-1;e>=0;e--)this.words[e+i]=this.words[e];for(e=0;e<i;e++)this.words[e]=0;this.length+=i}return this.strip()},a.prototype.ishln=function(t){return n(0===this.negative),this.iushln(t)},a.prototype.iushrn=function(t,e,r){var i;n(\"number\"==typeof t&&t>=0),i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<<a,l=r;if(i-=o,i=Math.max(0,i),l){for(var c=0;c<o;c++)l.words[c]=this.words[c];l.length=o}if(0===o);else if(this.length>o)for(this.length-=o,c=0;c<this.length;c++)this.words[c]=this.words[c+o];else this.words[0]=0,this.length=1;var u=0;for(c=this.length-1;c>=0&&(0!==u||c>=i);c--){var f=0|this.words[c];this.words[c]=u<<26-a|f>>>a,u=f&s}return l&&0!==u&&(l.words[l.length++]=u),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},a.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},a.prototype.shln=function(t){return this.clone().ishln(t)},a.prototype.ushln=function(t){return this.clone().iushln(t)},a.prototype.shrn=function(t){return this.clone().ishrn(t)},a.prototype.ushrn=function(t){return this.clone().iushrn(t)},a.prototype.testn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,i=1<<e;return!(this.length<=r)&&!!(this.words[r]&i)},a.prototype.imaskn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,\"imaskn works only with positive numbers\"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},a.prototype.maskn=function(t){return this.clone().imaskn(t)},a.prototype.iaddn=function(t){return n(\"number\"==typeof t),n(t<67108864),t<0?this.isubn(-t):0!==this.negative?1===this.length&&(0|this.words[0])<t?(this.words[0]=t-(0|this.words[0]),this.negative=0,this):(this.negative=0,this.isubn(t),this.negative=1,this):this._iaddn(t)},a.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},a.prototype.isubn=function(t){if(n(\"number\"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},a.prototype.addn=function(t){return this.clone().iaddn(t)},a.prototype.subn=function(t){return this.clone().isubn(t)},a.prototype.iabs=function(){return this.negative=0,this},a.prototype.abs=function(){return this.clone().iabs()},a.prototype._ishlnsubmul=function(t,e,r){var i,a,o=t.length+r;this._expand(o);var s=0;for(i=0;i<t.length;i++){a=(0|this.words[i+r])+s;var l=(0|t.words[i])*e;s=((a-=67108863&l)>>26)-(l/67108864|0),this.words[i+r]=67108863&a}for(;i<this.length-r;i++)s=(a=(0|this.words[i+r])+s)>>26,this.words[i+r]=67108863&a;if(0===s)return this.strip();for(n(-1===s),s=0,i=0;i<this.length;i++)s=(a=-(0|this.words[i])+s)>>26,this.words[i]=67108863&a;return this.negative=1,this.strip()},a.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),i=t,o=0|i.words[i.length-1];0!==(r=26-this._countBits(o))&&(i=i.ushln(r),n.iushln(r),o=0|i.words[i.length-1]);var s,l=n.length-i.length;if(\"mod\"!==e){(s=new a(null)).length=l+1,s.words=new Array(s.length);for(var c=0;c<s.length;c++)s.words[c]=0}var u=n.clone()._ishlnsubmul(i,1,l);0===u.negative&&(n=u,s&&(s.words[l]=1));for(var f=l-1;f>=0;f--){var h=67108864*(0|n.words[i.length+f])+(0|n.words[i.length+f-1]);for(h=Math.min(h/o|0,67108863),n._ishlnsubmul(i,h,f);0!==n.negative;)h--,n.negative=0,n._ishlnsubmul(i,1,f),n.isZero()||(n.negative^=1);s&&(s.words[f]=h)}return s&&s.strip(),n.strip(),\"div\"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},a.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new a(0),mod:new a(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),\"mod\"!==e&&(i=s.div.neg()),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:i,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),\"mod\"!==e&&(i=s.div.neg()),{div:i,mod:s.mod}):0!=(this.negative&t.negative)?(s=this.neg().divmod(t.neg(),e),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new a(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new a(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new a(this.modn(t.words[0]))}:this._wordDiv(t,e);var i,o,s},a.prototype.div=function(t){return this.divmod(t,\"div\",!1).div},a.prototype.mod=function(t){return this.divmod(t,\"mod\",!1).mod},a.prototype.umod=function(t){return this.divmod(t,\"mod\",!0).mod},a.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},a.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,i=this.length-1;i>=0;i--)r=(e*r+(0|this.words[i]))%t;return r},a.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var i=(0|this.words[r])+67108864*e;this.words[r]=i/t|0,e=i%t}return this.strip()},a.prototype.divn=function(t){return this.clone().idivn(t)},a.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i=new a(1),o=new a(0),s=new a(0),l=new a(1),c=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++c;for(var u=r.clone(),f=e.clone();!e.isZero();){for(var h=0,p=1;0==(e.words[0]&p)&&h<26;++h,p<<=1);if(h>0)for(e.iushrn(h);h-- >0;)(i.isOdd()||o.isOdd())&&(i.iadd(u),o.isub(f)),i.iushrn(1),o.iushrn(1);for(var d=0,g=1;0==(r.words[0]&g)&&d<26;++d,g<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(u),l.isub(f)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),i.isub(s),o.isub(l)):(r.isub(e),s.isub(i),l.isub(o))}return{a:s,b:l,gcd:r.iushln(c)}},a.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i,o=new a(1),s=new a(0),l=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var c=0,u=1;0==(e.words[0]&u)&&c<26;++c,u<<=1);if(c>0)for(e.iushrn(c);c-- >0;)o.isOdd()&&o.iadd(l),o.iushrn(1);for(var f=0,h=1;0==(r.words[0]&h)&&f<26;++f,h<<=1);if(f>0)for(r.iushrn(f);f-- >0;)s.isOdd()&&s.iadd(l),s.iushrn(1);e.cmp(r)>=0?(e.isub(r),o.isub(s)):(r.isub(e),s.isub(o))}return(i=0===e.cmpn(1)?o:s).cmpn(0)<0&&i.iadd(t),i},a.prototype.gcd=function(t){if(this.isZero())return t.abs();if(t.isZero())return this.abs();var e=this.clone(),r=t.clone();e.negative=0,r.negative=0;for(var n=0;e.isEven()&&r.isEven();n++)e.iushrn(1),r.iushrn(1);for(;;){for(;e.isEven();)e.iushrn(1);for(;r.isEven();)r.iushrn(1);var i=e.cmp(r);if(i<0){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.iushln(n)},a.prototype.invm=function(t){return this.egcd(t).a.umod(t)},a.prototype.isEven=function(){return 0==(1&this.words[0])},a.prototype.isOdd=function(){return 1==(1&this.words[0])},a.prototype.andln=function(t){return this.words[0]&t},a.prototype.bincn=function(t){n(\"number\"==typeof t);var e=t%26,r=(t-e)/26,i=1<<e;if(this.length<=r)return this._expand(r+1),this.words[r]|=i,this;for(var a=i,o=r;0!==a&&o<this.length;o++){var s=0|this.words[o];a=(s+=a)>>>26,s&=67108863,this.words[o]=s}return 0!==a&&(this.words[o]=a,this.length++),this},a.prototype.isZero=function(){return 1===this.length&&0===this.words[0]},a.prototype.cmpn=function(t){var e,r=t<0;if(0!==this.negative&&!r)return-1;if(0===this.negative&&r)return 1;if(this.strip(),this.length>1)e=1;else{r&&(t=-t),n(t<=67108863,\"Number is too big\");var i=0|this.words[0];e=i===t?0:i<t?-1:1}return 0!==this.negative?0|-e:e},a.prototype.cmp=function(t){if(0!==this.negative&&0===t.negative)return-1;if(0===this.negative&&0!==t.negative)return 1;var e=this.ucmp(t);return 0!==this.negative?0|-e:e},a.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=0|this.words[r],i=0|t.words[r];if(n!==i){n<i?e=-1:n>i&&(e=1);break}}return e},a.prototype.gtn=function(t){return 1===this.cmpn(t)},a.prototype.gt=function(t){return 1===this.cmp(t)},a.prototype.gten=function(t){return this.cmpn(t)>=0},a.prototype.gte=function(t){return this.cmp(t)>=0},a.prototype.ltn=function(t){return-1===this.cmpn(t)},a.prototype.lt=function(t){return-1===this.cmp(t)},a.prototype.lten=function(t){return this.cmpn(t)<=0},a.prototype.lte=function(t){return this.cmp(t)<=0},a.prototype.eqn=function(t){return 0===this.cmpn(t)},a.prototype.eq=function(t){return 0===this.cmp(t)},a.red=function(t){return new w(t)},a.prototype.toRed=function(t){return n(!this.red,\"Already a number in reduction context\"),n(0===this.negative,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},a.prototype.fromRed=function(){return n(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},a.prototype._forceRed=function(t){return this.red=t,this},a.prototype.forceRed=function(t){return n(!this.red,\"Already a number in reduction context\"),this._forceRed(t)},a.prototype.redAdd=function(t){return n(this.red,\"redAdd works only with red numbers\"),this.red.add(this,t)},a.prototype.redIAdd=function(t){return n(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,t)},a.prototype.redSub=function(t){return n(this.red,\"redSub works only with red numbers\"),this.red.sub(this,t)},a.prototype.redISub=function(t){return n(this.red,\"redISub works only with red numbers\"),this.red.isub(this,t)},a.prototype.redShl=function(t){return n(this.red,\"redShl works only with red numbers\"),this.red.shl(this,t)},a.prototype.redMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.mul(this,t)},a.prototype.redIMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.imul(this,t)},a.prototype.redSqr=function(){return n(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},a.prototype.redISqr=function(){return n(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},a.prototype.redSqrt=function(){return n(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},a.prototype.redInvm=function(){return n(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},a.prototype.redNeg=function(){return n(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},a.prototype.redPow=function(t){return n(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var m={k256:null,p224:null,p192:null,p25519:null};function v(t,e){this.name=t,this.p=new a(e,16),this.n=this.p.bitLength(),this.k=new a(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}function y(){v.call(this,\"k256\",\"ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff fffffffe fffffc2f\")}function x(){v.call(this,\"p224\",\"ffffffff ffffffff ffffffff ffffffff 00000000 00000000 00000001\")}function b(){v.call(this,\"p192\",\"ffffffff ffffffff ffffffff fffffffe ffffffff ffffffff\")}function _(){v.call(this,\"25519\",\"7fffffffffffffff ffffffffffffffff ffffffffffffffff ffffffffffffffed\")}function w(t){if(\"string\"==typeof t){var e=a._prime(t);this.m=e.p,this.prime=e}else n(t.gtn(1),\"modulus must be greater than 1\"),this.m=t,this.prime=null}function T(t){w.call(this,t),this.shift=this.m.bitLength(),this.shift%26!=0&&(this.shift+=26-this.shift%26),this.r=new a(1).iushln(this.shift),this.r2=this.imod(this.r.sqr()),this.rinv=this.r._invmp(this.m),this.minv=this.rinv.mul(this.r).isubn(1).div(this.m),this.minv=this.minv.umod(this.r),this.minv=this.r.sub(this.minv)}v.prototype._tmp=function(){var t=new a(null);return t.words=new Array(Math.ceil(this.n/13)),t},v.prototype.ireduce=function(t){var e,r=t;do{this.split(r,this.tmp),e=(r=(r=this.imulK(r)).iadd(this.tmp)).bitLength()}while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):r.strip(),r},v.prototype.split=function(t,e){t.iushrn(this.n,0,e)},v.prototype.imulK=function(t){return t.imul(this.k)},i(y,v),y.prototype.split=function(t,e){for(var r=Math.min(t.length,9),n=0;n<r;n++)e.words[n]=t.words[n];if(e.length=r,t.length<=9)return t.words[0]=0,void(t.length=1);var i=t.words[9];for(e.words[e.length++]=4194303&i,n=10;n<t.length;n++){var a=0|t.words[n];t.words[n-10]=(4194303&a)<<4|i>>>22,i=a}i>>>=22,t.words[n-10]=i,0===i&&t.length>10?t.length-=10:t.length-=9},y.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e=0,r=0;r<t.length;r++){var n=0|t.words[r];e+=977*n,t.words[r]=67108863&e,e=64*n+(e/67108864|0)}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},i(x,v),i(b,v),i(_,v),_.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*(0|t.words[r])+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},a._prime=function(t){if(m[t])return m[t];var e;if(\"k256\"===t)e=new y;else if(\"p224\"===t)e=new x;else if(\"p192\"===t)e=new b;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);e=new _}return m[t]=e,e},w.prototype._verify1=function(t){n(0===t.negative,\"red works only with positives\"),n(t.red,\"red works only with red numbers\")},w.prototype._verify2=function(t,e){n(0==(t.negative|e.negative),\"red works only with positives\"),n(t.red&&t.red===e.red,\"red works only with red numbers\")},w.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.umod(this.m)._forceRed(this)},w.prototype.neg=function(t){return t.isZero()?t.clone():this.m.sub(t)._forceRed(this)},w.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},w.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},w.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},w.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},w.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.ushln(e))},w.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},w.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},w.prototype.isqr=function(t){return this.imul(t,t.clone())},w.prototype.sqr=function(t){return this.mul(t,t)},w.prototype.sqrt=function(t){if(t.isZero())return t.clone();var e=this.m.andln(3);if(n(e%2==1),3===e){var r=this.m.add(new a(1)).iushrn(2);return 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M=s[c-1];s[c-1]=s[h],s[h]=M,h=n(t,e,l,c-1,o,s,p);for(_=f*(c-1),w=f*h,T=0;T<f;++T,++_,++w){k=o[_];o[_]=o[w],o[w]=k}M=s[c-1];if(s[c-1]=s[h],s[h]=M,u<h){for(c=h-1;l<c&&o[f*(c-1)+e]===p;)c-=1;c+=1}else{if(!(h<u))break;for(l=h+1;l<c&&o[f*l+e]===p;)l+=1}}return n(t,e,r,u,o,s,o[f*u+e])};var n=t(\"./partition\")(\"lo<p0\",[\"p0\"]);function i(t,e,r,n,i,a){for(var o=2*t,s=o*(r+1)+e,l=r+1;l<n;++l,s+=o)for(var c=i[s],u=l,f=o*(l-1);u>r&&i[f+e]>c;--u,f-=o){for(var h=f,p=f+o,d=0;d<o;++d,++h,++p){var g=i[h];i[h]=i[p],i[p]=g}var m=a[u];a[u]=a[u-1],a[u-1]=m}}},{\"./partition\":105}],105:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=\"abcdef\".split(\"\").concat(e),n=[];t.indexOf(\"lo\")>=0&&n.push(\"lo=e[k+n]\");t.indexOf(\"hi\")>=0&&n.push(\"hi=e[k+o]\");return r.push(\"for(var j=2*a,k=j*c,l=k,m=c,n=b,o=a+b,p=c;d>p;++p,k+=j){var _;if($)if(m===p)m+=1,l+=j;else{for(var s=0;j>s;++s){var t=e[k+s];e[k+s]=e[l],e[l++]=t}var u=f[p];f[p]=f[m],f[m++]=u}}return 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       "/*!\n",
       " * The buffer module from node.js, for the browser.\n",
       " *\n",
       " * @author   Feross Aboukhadijeh <https://feross.org>\n",
       " * @license  MIT\n",
       " */\n",
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       " * @license   Licensed under MIT license\n",
       " *            See https://raw.githubusercontent.com/stefanpenner/es6-promise/master/LICENSE\n",
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a=e(t,r.key);n.push(r),a<0&&(i=n.length),r=a<0?r.left:r.right}return n.length=i,new h(this,n)},l.lt=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a>0&&(i=n.length),r=a<=0?r.left:r.right}return n.length=i,new h(this,n)},l.le=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a>=0&&(i=n.length),r=a<0?r.left:r.right}return n.length=i,new h(this,n)},l.find=function(t){for(var e=this._compare,r=this.root,n=[];r;){var i=e(t,r.key);if(n.push(r),0===i)return new h(this,n);r=i<=0?r.left:r.right}return new h(this,[])},l.remove=function(t){var e=this.find(t);return e?e.remove():this},l.get=function(t){for(var e=this._compare,r=this.root;r;){var n=e(t,r.key);if(0===n)return r.value;r=n<=0?r.left:r.right}};var p=h.prototype;function d(t,e){t.key=e.key,t.value=e.value,t.left=e.left,t.right=e.right,t._color=e._color,t._count=e._count}function g(t,e){return t<e?-1:t>e?1:0}Object.defineProperty(p,\"valid\",{get:function(){return this._stack.length>0}}),Object.defineProperty(p,\"node\",{get:function(){return this._stack.length>0?this._stack[this._stack.length-1]:null},enumerable:!0}),p.clone=function(){return new h(this.tree,this._stack.slice())},p.remove=function(){var t=this._stack;if(0===t.length)return this.tree;var e=new Array(t.length),r=t[t.length-1];e[e.length-1]=new n(r._color,r.key,r.value,r.left,r.right,r._count);for(var l=t.length-2;l>=0;--l){(r=t[l]).left===t[l+1]?e[l]=new n(r._color,r.key,r.value,e[l+1],r.right,r._count):e[l]=new n(r._color,r.key,r.value,r.left,e[l+1],r._count)}if((r=e[e.length-1]).left&&r.right){var c=e.length;for(r=r.left;r.right;)e.push(r),r=r.right;var u=e[c-1];e.push(new n(r._color,u.key,u.value,r.left,r.right,r._count)),e[c-1].key=r.key,e[c-1].value=r.value;for(l=e.length-2;l>=c;--l)r=e[l],e[l]=new n(r._color,r.key,r.value,r.left,e[l+1],r._count);e[c-1].left=e[c]}if(0===(r=e[e.length-1])._color){var f=e[e.length-2];f.left===r?f.left=null:f.right===r&&(f.right=null),e.pop();for(l=0;l<e.length;++l)e[l]._count--;return new s(this.tree._compare,e[0])}if(r.left||r.right){r.left?d(r,r.left):r.right&&d(r,r.right),r._color=1;for(l=0;l<e.length-1;++l)e[l]._count--;return new s(this.tree._compare,e[0])}if(1===e.length)return new s(this.tree._compare,null);for(l=0;l<e.length;++l)e[l]._count--;var h=e[e.length-2];return function(t){for(var e,r,n,s,l=t.length-1;l>=0;--l){if(e=t[l],0===l)return void(e._color=1);if((r=t[l-1]).left===e){if((n=r.right).right&&0===n.right._color){if(s=(n=r.right=i(n)).right=i(n.right),r.right=n.left,n.left=r,n.right=s,n._color=r._color,e._color=1,r._color=1,s._color=1,o(r),o(n),l>1)(c=t[l-2]).left===r?c.left=n:c.right=n;return void(t[l-1]=n)}if(n.left&&0===n.left._color){if(s=(n=r.right=i(n)).left=i(n.left),r.right=s.left,n.left=s.right,s.left=r,s.right=n,s._color=r._color,r._color=1,n._color=1,e._color=1,o(r),o(n),o(s),l>1)(c=t[l-2]).left===r?c.left=s:c.right=s;return void(t[l-1]=s)}if(1===n._color){if(0===r._color)return r._color=1,void(r.right=a(0,n));r.right=a(0,n);continue}n=i(n),r.right=n.left,n.left=r,n._color=r._color,r._color=0,o(r),o(n),l>1&&((c=t[l-2]).left===r?c.left=n:c.right=n),t[l-1]=n,t[l]=r,l+1<t.length?t[l+1]=e:t.push(e),l+=2}else{if((n=r.left).left&&0===n.left._color){if(s=(n=r.left=i(n)).left=i(n.left),r.left=n.right,n.right=r,n.left=s,n._color=r._color,e._color=1,r._color=1,s._color=1,o(r),o(n),l>1)(c=t[l-2]).right===r?c.right=n:c.left=n;return void(t[l-1]=n)}if(n.right&&0===n.right._color){if(s=(n=r.left=i(n)).right=i(n.right),r.left=s.right,n.right=s.left,s.right=r,s.left=n,s._color=r._color,r._color=1,n._color=1,e._color=1,o(r),o(n),o(s),l>1)(c=t[l-2]).right===r?c.right=s:c.left=s;return void(t[l-1]=s)}if(1===n._color){if(0===r._color)return r._color=1,void(r.left=a(0,n));r.left=a(0,n);continue}var c;n=i(n),r.left=n.right,n.right=r,n._color=r._color,r._color=0,o(r),o(n),l>1&&((c=t[l-2]).right===r?c.right=n:c.left=n),t[l-1]=n,t[l]=r,l+1<t.length?t[l+1]=e:t.push(e),l+=2}}}(e),h.left===r?h.left=null:h.right=null,new s(this.tree._compare,e[0])},Object.defineProperty(p,\"key\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].key},enumerable:!0}),Object.defineProperty(p,\"value\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].value},enumerable:!0}),Object.defineProperty(p,\"index\",{get:function(){var t=0,e=this._stack;if(0===e.length){var r=this.tree.root;return r?r._count:0}e[e.length-1].left&&(t=e[e.length-1].left._count);for(var n=e.length-2;n>=0;--n)e[n+1]===e[n].right&&(++t,e[n].left&&(t+=e[n].left._count));return t},enumerable:!0}),p.next=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.right)for(e=e.right;e;)t.push(e),e=e.left;else for(t.pop();t.length>0&&t[t.length-1].right===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(p,\"hasNext\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].right)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].left===t[e])return!0;return!1}}),p.update=function(t){var e=this._stack;if(0===e.length)throw new Error(\"Can't update empty node!\");var r=new Array(e.length),i=e[e.length-1];r[r.length-1]=new n(i._color,i.key,t,i.left,i.right,i._count);for(var a=e.length-2;a>=0;--a)(i=e[a]).left===e[a+1]?r[a]=new n(i._color,i.key,i.value,r[a+1],i.right,i._count):r[a]=new n(i._color,i.key,i.value,i.left,r[a+1],i._count);return new s(this.tree._compare,r[0])},p.prev=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.left)for(e=e.left;e;)t.push(e),e=e.right;else for(t.pop();t.length>0&&t[t.length-1].left===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(p,\"hasPrev\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].left)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].right===t[e])return!0;return!1}})},{}],248:[function(t,e,r){var n=[.9999999999998099,676.5203681218851,-1259.1392167224028,771.3234287776531,-176.6150291621406,12.507343278686905,-.13857109526572012,9984369578019572e-21,1.5056327351493116e-7],i=[.9999999999999971,57.15623566586292,-59.59796035547549,14.136097974741746,-.4919138160976202,3399464998481189e-20,4652362892704858e-20,-9837447530487956e-20,.0001580887032249125,-.00021026444172410488,.00021743961811521265,-.0001643181065367639,8441822398385275e-20,-26190838401581408e-21,36899182659531625e-22];function a(t){if(t<0)return Number(\"0/0\");for(var e=i[0],r=i.length-1;r>0;--r)e+=i[r]/(t+r);var n=t+607/128+.5;return.5*Math.log(2*Math.PI)+(t+.5)*Math.log(n)-n+Math.log(e)-Math.log(t)}e.exports=function t(e){if(e<.5)return Math.PI/(Math.sin(Math.PI*e)*t(1-e));if(e>100)return Math.exp(a(e));e-=1;for(var r=n[0],i=1;i<9;i++)r+=n[i]/(e+i);var o=e+7+.5;return Math.sqrt(2*Math.PI)*Math.pow(o,e+.5)*Math.exp(-o)*r},e.exports.log=a},{}],249:[function(t,e,r){e.exports=function(t,e){if(\"string\"!=typeof t)throw new TypeError(\"must specify type string\");if(e=e||{},\"undefined\"==typeof document&&!e.canvas)return null;var r=e.canvas||document.createElement(\"canvas\");\"number\"==typeof e.width&&(r.width=e.width);\"number\"==typeof e.height&&(r.height=e.height);var n,i=e;try{var a=[t];0===t.indexOf(\"webgl\")&&a.push(\"experimental-\"+t);for(var o=0;o<a.length;o++)if(n=r.getContext(a[o],i))return n}catch(t){n=null}return n||null}},{}],250:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=new u(t);return r.update(e),r};var n=t(\"./lib/text.js\"),i=t(\"./lib/lines.js\"),a=t(\"./lib/background.js\"),o=t(\"./lib/cube.js\"),s=t(\"./lib/ticks.js\"),l=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]);function c(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function u(t){this.gl=t,this.pixelRatio=1,this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.autoTicks=!0,this.tickSpacing=[1,1,1],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickAlign=[\"auto\",\"auto\",\"auto\"],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[10,10,10],this.lastCubeProps={cubeEdges:[0,0,0],axis:[0,0,0]},this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=\"sans-serif\",this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelAlign=[\"auto\",\"auto\",\"auto\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[10,10,10],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[0,0,0],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!1,!1,!1],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._firstInit=!0,this._text=null,this._lines=null,this._background=a(t)}var f=u.prototype;function h(){this.primalOffset=[0,0,0],this.primalMinor=[0,0,0],this.mirrorOffset=[0,0,0],this.mirrorMinor=[0,0,0]}f.update=function(t){function e(e,r,n){if(n in t){var i,a=t[n],o=this[n];(e?Array.isArray(a)&&Array.isArray(a[0]):Array.isArray(a))?this[n]=i=[r(a[0]),r(a[1]),r(a[2])]:this[n]=i=[r(a),r(a),r(a)];for(var s=0;s<3;++s)if(i[s]!==o[s])return!0}return!1}t=t||{};var r,a=e.bind(this,!1,Number),o=e.bind(this,!1,Boolean),l=e.bind(this,!1,String),c=e.bind(this,!0,(function(t){if(Array.isArray(t)){if(3===t.length)return[+t[0],+t[1],+t[2],1];if(4===t.length)return[+t[0],+t[1],+t[2],+t[3]]}return[0,0,0,1]})),u=!1,f=!1;if(\"bounds\"in t)for(var h=t.bounds,p=0;p<2;++p)for(var d=0;d<3;++d)h[p][d]!==this.bounds[p][d]&&(f=!0),this.bounds[p][d]=h[p][d];if(\"ticks\"in t){r=t.ticks,u=!0,this.autoTicks=!1;for(p=0;p<3;++p)this.tickSpacing[p]=0}else a(\"tickSpacing\")&&(this.autoTicks=!0,f=!0);if(this._firstInit&&(\"ticks\"in t||\"tickSpacing\"in t||(this.autoTicks=!0),f=!0,u=!0,this._firstInit=!1),f&&this.autoTicks&&(r=s.create(this.bounds,this.tickSpacing),u=!0),u){for(p=0;p<3;++p)r[p].sort((function(t,e){return t.x-e.x}));s.equal(r,this.ticks)?u=!1:this.ticks=r}o(\"tickEnable\"),l(\"tickFont\")&&(u=!0),a(\"tickSize\"),a(\"tickAngle\"),a(\"tickPad\"),c(\"tickColor\");var g=l(\"labels\");l(\"labelFont\")&&(g=!0),o(\"labelEnable\"),a(\"labelSize\"),a(\"labelPad\"),c(\"labelColor\"),o(\"lineEnable\"),o(\"lineMirror\"),a(\"lineWidth\"),c(\"lineColor\"),o(\"lineTickEnable\"),o(\"lineTickMirror\"),a(\"lineTickLength\"),a(\"lineTickWidth\"),c(\"lineTickColor\"),o(\"gridEnable\"),a(\"gridWidth\"),c(\"gridColor\"),o(\"zeroEnable\"),c(\"zeroLineColor\"),a(\"zeroLineWidth\"),o(\"backgroundEnable\"),c(\"backgroundColor\"),this._text?this._text&&(g||u)&&this._text.update(this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont):this._text=n(this.gl,this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont),this._lines&&u&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=i(this.gl,this.bounds,this.ticks))};var p=[new h,new h,new h];function d(t,e,r,n,i){for(var a=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,c=n[e],u=0;u<3;++u)if(e!==u){var f=a,h=s,p=o,d=l;c&1<<u&&(f=s,h=a,p=l,d=o),f[u]=r[0][u],h[u]=r[1][u],i[u]>0?(p[u]=-1,d[u]=0):(p[u]=0,d[u]=1)}}var g=[0,0,0],m={model:l,view:l,projection:l,_ortho:!1};f.isOpaque=function(){return!0},f.isTransparent=function(){return!1},f.drawTransparent=function(t){};var v=[0,0,0],y=[0,0,0],x=[0,0,0];f.draw=function(t){t=t||m;for(var e=this.gl,r=t.model||l,n=t.view||l,i=t.projection||l,a=this.bounds,s=t._ortho||!1,u=o(r,n,i,a,s),f=u.cubeEdges,h=u.axis,b=n[12],_=n[13],w=n[14],T=n[15],k=(s?2:1)*this.pixelRatio*(i[3]*b+i[7]*_+i[11]*w+i[15]*T)/e.drawingBufferHeight,M=0;M<3;++M)this.lastCubeProps.cubeEdges[M]=f[M],this.lastCubeProps.axis[M]=h[M];var A=p;for(M=0;M<3;++M)d(p[M],M,this.bounds,f,h);e=this.gl;var S,E=g;for(M=0;M<3;++M)this.backgroundEnable[M]?E[M]=h[M]:E[M]=0;this._background.draw(r,n,i,a,E,this.backgroundColor),this._lines.bind(r,n,i,this);for(M=0;M<3;++M){var C=[0,0,0];h[M]>0?C[M]=a[1][M]:C[M]=a[0][M];for(var L=0;L<2;++L){var I=(M+1+L)%3,P=(M+1+(1^L))%3;this.gridEnable[I]&&this._lines.drawGrid(I,P,this.bounds,C,this.gridColor[I],this.gridWidth[I]*this.pixelRatio)}for(L=0;L<2;++L){I=(M+1+L)%3,P=(M+1+(1^L))%3;this.zeroEnable[P]&&Math.min(a[0][P],a[1][P])<=0&&Math.max(a[0][P],a[1][P])>=0&&this._lines.drawZero(I,P,this.bounds,C,this.zeroLineColor[P],this.zeroLineWidth[P]*this.pixelRatio)}}for(M=0;M<3;++M){this.lineEnable[M]&&this._lines.drawAxisLine(M,this.bounds,A[M].primalOffset,this.lineColor[M],this.lineWidth[M]*this.pixelRatio),this.lineMirror[M]&&this._lines.drawAxisLine(M,this.bounds,A[M].mirrorOffset,this.lineColor[M],this.lineWidth[M]*this.pixelRatio);var z=c(v,A[M].primalMinor),O=c(y,A[M].mirrorMinor),D=this.lineTickLength;for(L=0;L<3;++L){var R=k/r[5*L];z[L]*=D[L]*R,O[L]*=D[L]*R}this.lineTickEnable[M]&&this._lines.drawAxisTicks(M,A[M].primalOffset,z,this.lineTickColor[M],this.lineTickWidth[M]*this.pixelRatio),this.lineTickMirror[M]&&this._lines.drawAxisTicks(M,A[M].mirrorOffset,O,this.lineTickColor[M],this.lineTickWidth[M]*this.pixelRatio)}this._lines.unbind(),this._text.bind(r,n,i,this.pixelRatio);var F,B;function N(t){(B=[0,0,0])[t]=1}function j(t,e,r){var n=(t+1)%3,i=(t+2)%3,a=e[n],o=e[i],s=r[n],l=r[i];a>0&&l>0||a>0&&l<0||a<0&&l>0||a<0&&l<0?N(n):(o>0&&s>0||o>0&&s<0||o<0&&s>0||o<0&&s<0)&&N(i)}for(M=0;M<3;++M){var U=A[M].primalMinor,V=A[M].mirrorMinor,q=c(x,A[M].primalOffset);for(L=0;L<3;++L)this.lineTickEnable[M]&&(q[L]+=k*U[L]*Math.max(this.lineTickLength[L],0)/r[5*L]);var H=[0,0,0];if(H[M]=1,this.tickEnable[M]){-3600===this.tickAngle[M]?(this.tickAngle[M]=0,this.tickAlign[M]=\"auto\"):this.tickAlign[M]=-1,F=1,\"auto\"===(S=[this.tickAlign[M],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),B=[0,0,0],j(M,U,V);for(L=0;L<3;++L)q[L]+=k*U[L]*this.tickPad[L]/r[5*L];this._text.drawTicks(M,this.tickSize[M],this.tickAngle[M],q,this.tickColor[M],H,B,S)}if(this.labelEnable[M]){F=0,B=[0,0,0],this.labels[M].length>4&&(N(M),F=1),\"auto\"===(S=[this.labelAlign[M],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]);for(L=0;L<3;++L)q[L]+=k*U[L]*this.labelPad[L]/r[5*L];q[M]+=.5*(a[0][M]+a[1][M]),this._text.drawLabel(M,this.labelSize[M],this.labelAngle[M],q,this.labelColor[M],[0,0,0],B,S)}}this._text.unbind()},f.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},{\"./lib/background.js\":251,\"./lib/cube.js\":252,\"./lib/lines.js\":253,\"./lib/text.js\":255,\"./lib/ticks.js\":256}],251:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=[],r=[],s=0,l=0;l<3;++l)for(var c=(l+1)%3,u=(l+2)%3,f=[0,0,0],h=[0,0,0],p=-1;p<=1;p+=2){r.push(s,s+2,s+1,s+1,s+2,s+3),f[l]=p,h[l]=p;for(var d=-1;d<=1;d+=2){f[c]=d;for(var g=-1;g<=1;g+=2)f[u]=g,e.push(f[0],f[1],f[2],h[0],h[1],h[2]),s+=1}var m=c;c=u,u=m}var v=n(t,new Float32Array(e)),y=n(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),x=i(t,[{buffer:v,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:v,type:t.FLOAT,size:3,offset:12,stride:24}],y),b=a(t);return b.attributes.position.location=0,b.attributes.normal.location=1,new o(t,v,x,b)};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders\").bg;function o(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}var s=o.prototype;s.draw=function(t,e,r,n,i,a){for(var o=!1,s=0;s<3;++s)o=o||i[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:i,colors:a},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),this.vao.unbind(),l.disable(l.POLYGON_OFFSET_FILL)}},s.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders\":254,\"gl-buffer\":259,\"gl-vao\":358}],252:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,a,p){i(s,e,t),i(s,r,s);for(var y=0,x=0;x<2;++x){u[2]=a[x][2];for(var b=0;b<2;++b){u[1]=a[b][1];for(var _=0;_<2;++_)u[0]=a[_][0],h(l[y],u,s),y+=1}}var w=-1;for(x=0;x<8;++x){for(var T=l[x][3],k=0;k<3;++k)c[x][k]=l[x][k]/T;p&&(c[x][2]*=-1),T<0&&(w<0||c[x][2]<c[w][2])&&(w=x)}if(w<0){w=0;for(var M=0;M<3;++M){for(var A=(M+2)%3,S=(M+1)%3,E=-1,C=-1,L=0;L<2;++L){var I=(z=L<<M)+(L<<A)+(1-L<<S),P=z+(1-L<<A)+(L<<S);o(c[z],c[I],c[P],f)<0||(L?E=1:C=1)}if(E<0||C<0)C>E&&(w|=1<<M);else{for(L=0;L<2;++L){I=(z=L<<M)+(L<<A)+(1-L<<S),P=z+(1-L<<A)+(L<<S);var z,O=d([l[z],l[I],l[P],l[z+(1<<A)+(1<<S)]]);L?E=O:C=O}C>E&&(w|=1<<M)}}}var D=7^w,R=-1;for(x=0;x<8;++x)x!==w&&x!==D&&(R<0||c[R][1]>c[x][1])&&(R=x);var F=-1;for(x=0;x<3;++x){if((N=R^1<<x)!==w&&N!==D)F<0&&(F=N),(S=c[N])[0]<c[F][0]&&(F=N)}var B=-1;for(x=0;x<3;++x){var N;if((N=R^1<<x)!==w&&N!==D&&N!==F)B<0&&(B=N),(S=c[N])[0]>c[B][0]&&(B=N)}var j=g;j[0]=j[1]=j[2]=0,j[n.log2(F^R)]=R&F,j[n.log2(R^B)]=R&B;var U=7^B;U===w||U===D?(U=7^F,j[n.log2(B^U)]=U&B):j[n.log2(F^U)]=U&F;var V=m,q=w;for(M=0;M<3;++M)V[M]=q&1<<M?-1:1;return v};var n=t(\"bit-twiddle\"),i=t(\"gl-mat4/multiply\"),a=t(\"split-polygon\"),o=t(\"robust-orientation\"),s=new Array(16),l=new Array(8),c=new Array(8),u=new Array(3),f=[0,0,0];function h(t,e,r){for(var n=0;n<4;++n){t[n]=r[12+n];for(var i=0;i<3;++i)t[n]+=e[i]*r[4*i+n]}}!function(){for(var t=0;t<8;++t)l[t]=[1,1,1,1],c[t]=[1,1,1]}();var p=[[0,0,1,0,0],[0,0,-1,1,0],[0,-1,0,1,0],[0,1,0,1,0],[-1,0,0,1,0],[1,0,0,1,0]];function d(t){for(var e=0;e<p.length;++e)if((t=a.positive(t,p[e])).length<3)return 0;var r=t[0],n=r[0]/r[3],i=r[1]/r[3],o=0;for(e=1;e+1<t.length;++e){var s=t[e],l=t[e+1],c=s[0]/s[3]-n,u=s[1]/s[3]-i,f=l[0]/l[3]-n,h=l[1]/l[3]-i;o+=Math.abs(c*h-u*f)}return o}var g=[1,1,1],m=[0,0,0],v={cubeEdges:g,axis:m}},{\"bit-twiddle\":97,\"gl-mat4/multiply\":295,\"robust-orientation\":548,\"split-polygon\":566}],253:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){var o=[],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[0,0,0];o.push(0,0,1,0,1,1,0,0,-1,0,0,-1,0,1,1,0,1,-1);for(var f=0;f<3;++f){for(var h=o.length/3|0,d=0;d<r[f].length;++d){var g=+r[f][d].x;o.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}var m=o.length/3|0;s[f]=h,l[f]=m-h;h=o.length/3|0;for(var v=0;v<r[f].length;++v){g=+r[f][v].x;o.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}m=o.length/3|0;c[f]=h,u[f]=m-h}var y=n(t,new Float32Array(o)),x=i(t,[{buffer:y,type:t.FLOAT,size:3,stride:0,offset:0}]),b=a(t);return b.attributes.position.location=0,new p(t,y,x,b,l,s,u,c)};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders\").line,o=[0,0,0],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[1,1];function f(t){return t[0]=t[1]=t[2]=0,t}function h(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function p(t,e,r,n,i,a,o,s){this.gl=t,this.vertBuffer=e,this.vao=r,this.shader=n,this.tickCount=i,this.tickOffset=a,this.gridCount=o,this.gridOffset=s}var d=p.prototype;d.bind=function(t,e,r){this.shader.bind(),this.shader.uniforms.model=t,this.shader.uniforms.view=e,this.shader.uniforms.projection=r,u[0]=this.gl.drawingBufferWidth,u[1]=this.gl.drawingBufferHeight,this.shader.uniforms.screenShape=u,this.vao.bind()},d.unbind=function(){this.vao.unbind()},d.drawAxisLine=function(t,e,r,n,i){var a=f(s);this.shader.uniforms.majorAxis=s,a[t]=e[1][t]-e[0][t],this.shader.uniforms.minorAxis=a;var o,u=h(c,r);u[t]+=e[0][t],this.shader.uniforms.offset=u,this.shader.uniforms.lineWidth=i,this.shader.uniforms.color=n,(o=f(l))[(t+2)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6),(o=f(l))[(t+1)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6)},d.drawAxisTicks=function(t,e,r,n,i){if(this.tickCount[t]){var a=f(o);a[t]=1,this.shader.uniforms.majorAxis=a,this.shader.uniforms.offset=e,this.shader.uniforms.minorAxis=r,this.shader.uniforms.color=n,this.shader.uniforms.lineWidth=i;var s=f(l);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}},d.drawGrid=function(t,e,r,n,i,a){if(this.gridCount[t]){var u=f(s);u[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=u;var p=h(c,n);p[e]+=r[0][e],this.shader.uniforms.offset=p;var d=f(o);d[t]=1,this.shader.uniforms.majorAxis=d;var g=f(l);g[t]=1,this.shader.uniforms.screenAxis=g,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])}},d.drawZero=function(t,e,r,n,i,a){var o=f(s);this.shader.uniforms.majorAxis=o,o[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=o;var u=h(c,n);u[t]+=r[0][t],this.shader.uniforms.offset=u;var p=f(l);p[e]=1,this.shader.uniforms.screenAxis=p,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,6)},d.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},{\"./shaders\":254,\"gl-buffer\":259,\"gl-vao\":358}],254:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\\nuniform float lineWidth;\\nuniform vec2 screenShape;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nvoid main() {\\n  vec3 major = position.x * majorAxis;\\n  vec3 minor = position.y * minorAxis;\\n\\n  vec3 vPosition = major + minor + offset;\\n  vec3 pPosition = project(vPosition);\\n  vec3 offset = project(vPosition + screenAxis * position.z);\\n\\n  vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\\n\\n  gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\"]);r.line=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"}])};var s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, axis, alignDir, alignOpt;\\nuniform float scale, angle, pixelScale;\\nuniform vec2 resolution;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nfloat computeViewAngle(vec3 a, vec3 b) {\\n  vec3 A = project(a);\\n  vec3 B = project(b);\\n\\n  return atan(\\n    (B.y - A.y) * resolution.y,\\n    (B.x - A.x) * resolution.x\\n  );\\n}\\n\\nconst float PI = 3.141592;\\nconst float TWO_PI = 2.0 * PI;\\nconst float HALF_PI = 0.5 * PI;\\nconst float ONE_AND_HALF_PI = 1.5 * PI;\\n\\nint option = int(floor(alignOpt.x + 0.001));\\nfloat hv_ratio =       alignOpt.y;\\nbool enableAlign =    (alignOpt.z != 0.0);\\n\\nfloat mod_angle(float a) {\\n  return mod(a, PI);\\n}\\n\\nfloat positive_angle(float a) {\\n  return mod_angle((a < 0.0) ?\\n    a + TWO_PI :\\n    a\\n  );\\n}\\n\\nfloat look_upwards(float a) {\\n  float b = positive_angle(a);\\n  return ((b > HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\\n    b - PI :\\n    b;\\n}\\n\\nfloat look_horizontal_or_vertical(float a, float ratio) {\\n  // ratio controls the ratio between being horizontal to (vertical + horizontal)\\n  // if ratio is set to 0.5 then it is 50%, 50%.\\n  // when using a higher ratio e.g. 0.75 the result would\\n  // likely be more horizontal than vertical.\\n\\n  float b = positive_angle(a);\\n\\n  return\\n    (b < (      ratio) * HALF_PI) ? 0.0 :\\n    (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI :\\n    (b < (2.0 + ratio) * HALF_PI) ? 0.0 :\\n    (b < (4.0 - ratio) * HALF_PI) ? HALF_PI :\\n                                    0.0;\\n}\\n\\nfloat roundTo(float a, float b) {\\n  return float(b * floor((a + 0.5 * b) / b));\\n}\\n\\nfloat look_round_n_directions(float a, int n) {\\n  float b = positive_angle(a);\\n  float div = TWO_PI / float(n);\\n  float c = roundTo(b, div);\\n  return look_upwards(c);\\n}\\n\\nfloat applyAlignOption(float rawAngle, float delta) {\\n  return\\n    (option >  2) ? look_round_n_directions(rawAngle + delta, option) :       // option 3-n: round to n directions\\n    (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical\\n    (option == 1) ? rawAngle + delta :       // use free angle, and flip to align with one direction of the axis\\n    (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards\\n    (option ==-1) ? 0.0 :                    // useful for backward compatibility, all texts remains horizontal\\n                    rawAngle;                // otherwise return back raw input angle\\n}\\n\\nbool isAxisTitle = (axis.x == 0.0) &&\\n                   (axis.y == 0.0) &&\\n                   (axis.z == 0.0);\\n\\nvoid main() {\\n  //Compute world offset\\n  float axisDistance = position.z;\\n  vec3 dataPosition = axisDistance * axis + offset;\\n\\n  float beta = angle; // i.e. user defined attributes for each tick\\n\\n  float axisAngle;\\n  float clipAngle;\\n  float flip;\\n\\n  if (enableAlign) {\\n    axisAngle = (isAxisTitle) ? HALF_PI :\\n                      computeViewAngle(dataPosition, dataPosition + axis);\\n    clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\\n\\n    axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\\n    clipAngle += (sin(clipAngle) < 0.0) ? PI : 0.0;\\n\\n    flip = (dot(vec2(cos(axisAngle), sin(axisAngle)),\\n                vec2(sin(clipAngle),-cos(clipAngle))) > 0.0) ? 1.0 : 0.0;\\n\\n    beta += applyAlignOption(clipAngle, flip * PI);\\n  }\\n\\n  //Compute plane offset\\n  vec2 planeCoord = position.xy * pixelScale;\\n\\n  mat2 planeXform = scale * mat2(\\n     cos(beta), sin(beta),\\n    -sin(beta), cos(beta)\\n  );\\n\\n  vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\\n\\n  //Compute clip position\\n  vec3 clipPosition = project(dataPosition);\\n\\n  //Apply text offset in clip coordinates\\n  clipPosition += vec3(viewOffset, 0.0);\\n\\n  //Done\\n  gl_Position = vec4(clipPosition, 1.0);\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\"]);r.text=function(t){return i(t,s,l,null,[{name:\"position\",type:\"vec3\"}])};var c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 enable;\\nuniform vec3 bounds[2];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n\\n  vec3 signAxis = sign(bounds[1] - bounds[0]);\\n\\n  vec3 realNormal = signAxis * normal;\\n\\n  if(dot(realNormal, enable) > 0.0) {\\n    vec3 minRange = min(bounds[0], bounds[1]);\\n    vec3 maxRange = max(bounds[0], bounds[1]);\\n    vec3 nPosition = mix(minRange, maxRange, 0.5 * (position + 1.0));\\n    gl_Position = projection * view * model * vec4(nPosition, 1.0);\\n  } else {\\n    gl_Position = vec4(0,0,0,0);\\n  }\\n\\n  colorChannel = abs(realNormal);\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 colors[3];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n  gl_FragColor = colorChannel.x * colors[0] +\\n                 colorChannel.y * colors[1] +\\n                 colorChannel.z * colors[2];\\n}\"]);r.bg=function(t){return i(t,c,u,null,[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}])}},{\"gl-shader\":335,glslify:257}],255:[function(t,e,r){(function(r){(function(){\"use strict\";e.exports=function(t,e,r,a,s,l){var u=n(t),f=i(t,[{buffer:u,size:3}]),h=o(t);h.attributes.position.location=0;var p=new c(t,h,u,f);return p.update(e,r,a,s,l),p};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"vectorize-text\"),o=t(\"./shaders\").text,s=window||r.global||{},l=s.__TEXT_CACHE||{};s.__TEXT_CACHE={};function c(t,e,r,n){this.gl=t,this.shader=e,this.buffer=r,this.vao=n,this.tickOffset=this.tickCount=this.labelOffset=this.labelCount=null}var u=c.prototype,f=[0,0];u.bind=function(t,e,r,n){this.vao.bind(),this.shader.bind();var i=this.shader.uniforms;i.model=t,i.view=e,i.projection=r,i.pixelScale=n,f[0]=this.gl.drawingBufferWidth,f[1]=this.gl.drawingBufferHeight,this.shader.uniforms.resolution=f},u.unbind=function(){this.vao.unbind()},u.update=function(t,e,r,n,i){var o=[];function s(t,e,r,n,i,s){var 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n=t(\"extract-frustum-planes\"),i=t(\"split-polygon\"),a=t(\"./lib/cube.js\"),o=t(\"gl-mat4/multiply\"),s=t(\"gl-mat4/transpose\"),l=t(\"gl-vec4/transformMat4\"),c=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),u=new Float32Array(16);function f(t,e,r){this.lo=t,this.hi=e,this.pixelsPerDataUnit=r}var h=[0,0,0,1],p=[0,0,0,1];function d(t,e,r,n,i){for(var a=0;a<3;++a){for(var o=h,s=p,c=0;c<3;++c)s[c]=o[c]=r[c];s[3]=o[3]=1,s[a]+=1,l(s,s,e),s[3]<0&&(t[a]=1/0),o[a]-=1,l(o,o,e),o[3]<0&&(t[a]=1/0);var u=(o[0]/o[3]-s[0]/s[3])*n,f=(o[1]/o[3]-s[1]/s[3])*i;t[a]=.25*Math.sqrt(u*u+f*f)}return t}var g=[new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0)],m=[0,0,0]},{\"./lib/cube.js\":252,\"extract-frustum-planes\":240,\"gl-mat4/multiply\":295,\"gl-mat4/transpose\":306,\"gl-vec4/transformMat4\":429,\"split-polygon\":566}],259:[function(t,e,r){\"use strict\";var n=t(\"typedarray-pool\"),i=t(\"ndarray-ops\"),a=t(\"ndarray\"),o=[\"uint8\",\"uint8_clamped\",\"uint16\",\"uint32\",\"int8\",\"int16\",\"int32\",\"float32\"];function s(t,e,r,n,i){this.gl=t,this.type=e,this.handle=r,this.length=n,this.usage=i}var l=s.prototype;function c(t,e,r,n,i,a){var o=i.length*i.BYTES_PER_ELEMENT;if(a<0)return t.bufferData(e,i,n),o;if(o+a>r)throw new Error(\"gl-buffer: If resizing buffer, must not specify offset\");return t.bufferSubData(e,a,i),r}function u(t,e){for(var r=n.malloc(t.length,e),i=t.length,a=0;a<i;++a)r[a]=t[a];return r}l.bind=function(){this.gl.bindBuffer(this.type,this.handle)},l.unbind=function(){this.gl.bindBuffer(this.type,null)},l.dispose=function(){this.gl.deleteBuffer(this.handle)},l.update=function(t,e){if(\"number\"!=typeof e&&(e=-1),this.bind(),\"object\"==typeof t&&\"undefined\"!=typeof t.shape){var r=t.dtype;if(o.indexOf(r)<0&&(r=\"float32\"),this.type===this.gl.ELEMENT_ARRAY_BUFFER)r=gl.getExtension(\"OES_element_index_uint\")&&\"uint16\"!==r?\"uint32\":\"uint16\";if(r===t.dtype&&function(t,e){for(var r=1,n=e.length-1;n>=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}(t.shape,t.stride))0===t.offset&&t.data.length===t.shape[0]?this.length=c(this.gl,this.type,this.length,this.usage,t.data,e):this.length=c(this.gl,this.type,this.length,this.usage,t.data.subarray(t.offset,t.shape[0]),e);else{var s=n.malloc(t.size,r),l=a(s,t.shape);i.assign(l,t),this.length=c(this.gl,this.type,this.length,this.usage,e<0?s:s.subarray(0,t.size),e),n.free(s)}}else if(Array.isArray(t)){var f;f=this.type===this.gl.ELEMENT_ARRAY_BUFFER?u(t,\"uint16\"):u(t,\"float32\"),this.length=c(this.gl,this.type,this.length,this.usage,e<0?f:f.subarray(0,t.length),e),n.free(f)}else if(\"object\"==typeof t&&\"number\"==typeof t.length)this.length=c(this.gl,this.type,this.length,this.usage,t,e);else{if(\"number\"!=typeof t&&void 0!==t)throw new Error(\"gl-buffer: Invalid data type\");if(e>=0)throw new Error(\"gl-buffer: Cannot specify offset when resizing buffer\");(t|=0)<=0&&(t=1),this.gl.bufferData(this.type,0|t,this.usage),this.length=t}},e.exports=function(t,e,r,n){if(r=r||t.ARRAY_BUFFER,n=n||t.DYNAMIC_DRAW,r!==t.ARRAY_BUFFER&&r!==t.ELEMENT_ARRAY_BUFFER)throw new Error(\"gl-buffer: Invalid type for webgl buffer, must be either gl.ARRAY_BUFFER or gl.ELEMENT_ARRAY_BUFFER\");if(n!==t.DYNAMIC_DRAW&&n!==t.STATIC_DRAW&&n!==t.STREAM_DRAW)throw new Error(\"gl-buffer: Invalid usage for buffer, must be either gl.DYNAMIC_DRAW, gl.STATIC_DRAW or gl.STREAM_DRAW\");var i=t.createBuffer(),a=new s(t,r,i,0,n);return a.update(e),a}},{ndarray:495,\"ndarray-ops\":490,\"typedarray-pool\":595}],260:[function(t,e,r){\"use strict\";var n=t(\"gl-vec3\");e.exports=function(t,e){var r=t.positions,i=t.vectors,a={positions:[],vertexIntensity:[],vertexIntensityBounds:t.vertexIntensityBounds,vectors:[],cells:[],coneOffset:t.coneOffset,colormap:t.colormap};if(0===t.positions.length)return e&&(e[0]=[0,0,0],e[1]=[0,0,0]),a;for(var o=0,s=1/0,l=-1/0,c=1/0,u=-1/0,f=1/0,h=-1/0,p=null,d=null,g=[],m=1/0,v=!1,y=0;y<r.length;y++){var x=r[y];s=Math.min(x[0],s),l=Math.max(x[0],l),c=Math.min(x[1],c),u=Math.max(x[1],u),f=Math.min(x[2],f),h=Math.max(x[2],h);var b=i[y];if(n.length(b)>o&&(o=n.length(b)),y){var _=2*n.distance(p,x)/(n.length(d)+n.length(b));_?(m=Math.min(m,_),v=!1):v=!0}v||(p=x,d=b),g.push(b)}var w=[s,c,f],T=[l,u,h];e&&(e[0]=w,e[1]=T),0===o&&(o=1);var k=1/o;isFinite(m)||(m=1),a.vectorScale=m;var M=t.coneSize||.5;t.absoluteConeSize&&(M=t.absoluteConeSize*k),a.coneScale=M;y=0;for(var A=0;y<r.length;y++)for(var S=(x=r[y])[0],E=x[1],C=x[2],L=g[y],I=n.length(L)*k,P=0;P<8;P++){a.positions.push([S,E,C,A++]),a.positions.push([S,E,C,A++]),a.positions.push([S,E,C,A++]),a.positions.push([S,E,C,A++]),a.positions.push([S,E,C,A++]),a.positions.push([S,E,C,A++]),a.vectors.push(L),a.vectors.push(L),a.vectors.push(L),a.vectors.push(L),a.vectors.push(L),a.vectors.push(L),a.vertexIntensity.push(I,I,I),a.vertexIntensity.push(I,I,I);var z=a.positions.length;a.cells.push([z-6,z-5,z-4],[z-3,z-2,z-1])}return a};var i=t(\"./lib/shaders\");e.exports.createMesh=t(\"./create_mesh\"),e.exports.createConeMesh=function(t,r){return e.exports.createMesh(t,r,{shaders:i,traceType:\"cone\"})}},{\"./create_mesh\":261,\"./lib/shaders\":262,\"gl-vec3\":377}],261:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"gl-mat4/multiply\"),l=t(\"gl-mat4/invert\"),c=t(\"ndarray\"),u=t(\"colormap\"),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e,r,n,i,a,o,s,l,c,u){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.pickShader=n,this.trianglePositions=i,this.triangleVectors=a,this.triangleColors=s,this.triangleUVs=l,this.triangleIds=o,this.triangleVAO=c,this.triangleCount=0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.traceType=u,this.tubeScale=1,this.coneScale=2,this.vectorScale=1,this.coneOffset=.25,this._model=f,this._view=f,this._projection=f,this._resolution=[1,1]}var p=h.prototype;function d(t,e){var r=n(t,e.meshShader.vertex,e.meshShader.fragment,null,e.meshShader.attributes);return r.attributes.position.location=0,r.attributes.color.location=2,r.attributes.uv.location=3,r.attributes.vector.location=4,r}function g(t,e){var r=n(t,e.pickShader.vertex,e.pickShader.fragment,null,e.pickShader.attributes);return r.attributes.position.location=0,r.attributes.id.location=1,r.attributes.vector.location=4,r}p.isOpaque=function(){return this.opacity>=1},p.isTransparent=function(){return this.opacity<1},p.pickSlots=1,p.setPickBase=function(t){this.pickId=t},p.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),void 0!==t.tubeScale&&(this.tubeScale=t.tubeScale),void 0!==t.vectorScale&&(this.vectorScale=t.vectorScale),void 0!==t.coneScale&&(this.coneScale=t.coneScale),void 0!==t.coneOffset&&(this.coneOffset=t.coneOffset),t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=u({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var i=e[n],a=0;a<3;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return c(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,i=t.vectors;if(n&&r&&i){var a=[],o=[],s=[],l=[],f=[];this.cells=r,this.positions=n,this.vectors=i;var h=t.meshColor||[1,1,1,1],p=t.vertexIntensity,d=1/0,g=-1/0;if(p)if(t.vertexIntensityBounds)d=+t.vertexIntensityBounds[0],g=+t.vertexIntensityBounds[1];else for(var m=0;m<p.length;++m){var v=p[m];d=Math.min(d,v),g=Math.max(g,v)}else for(m=0;m<n.length;++m){v=n[m][2];d=Math.min(d,v),g=Math.max(g,v)}this.intensity=p||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n),this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(m=0;m<n.length;++m)for(var y=n[m],x=0;x<3;++x)!isNaN(y[x])&&isFinite(y[x])&&(this.bounds[0][x]=Math.min(this.bounds[0][x],y[x]),this.bounds[1][x]=Math.max(this.bounds[1][x],y[x]));var b=0;t:for(m=0;m<r.length;++m){var _=r[m];switch(_.length){case 3:for(x=0;x<3;++x){y=n[T=_[x]];for(var w=0;w<3;++w)if(isNaN(y[w])||!isFinite(y[w]))continue t}for(x=0;x<3;++x){var T;y=n[T=_[2-x]];a.push(y[0],y[1],y[2],y[3]);var k=i[T];o.push(k[0],k[1],k[2],k[3]||0);var M,A=h;3===A.length?s.push(A[0],A[1],A[2],1):s.push(A[0],A[1],A[2],A[3]),M=p?[(p[T]-d)/(g-d),0]:[(y[2]-d)/(g-d),0],l.push(M[0],M[1]),f.push(m)}b+=1}}this.triangleCount=b,this.trianglePositions.update(a),this.triangleVectors.update(o),this.triangleColors.update(s),this.triangleUVs.update(l),this.triangleIds.update(new Uint32Array(f))}},p.drawTransparent=p.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var c={model:r,view:n,projection:i,inverseModel:f.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,texture:0};c.inverseModel=l(c.inverseModel,c.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);s(u,c.view,c.model),s(u,c.projection,u),l(u,u);for(o=0;o<3;++o)c.eyePosition[o]=u[12+o]/u[15];var h=u[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];c.lightPosition[o]=p/h}if(this.triangleCount>0){var g=this.triShader;g.bind(),g.uniforms=c,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},p.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind())},p.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3),i={position:n,dataCoordinate:n,index:Math.floor(r[1]/48)};return\"cone\"===this.traceType?i.index=Math.floor(r[1]/48):\"streamtube\"===this.traceType&&(i.intensity=this.intensity[r[1]],i.velocity=this.vectors[r[1]].slice(0,3),i.divergence=this.vectors[r[1]][3],i.index=e),i},p.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()},e.exports=function(t,e,r){var n=r.shaders;1===arguments.length&&(t=(e=t).gl);var s=d(t,n),l=g(t,n),u=o(t,c(new Uint8Array([255,255,255,255]),[1,1,4]));u.generateMipmap(),u.minFilter=t.LINEAR_MIPMAP_LINEAR,u.magFilter=t.LINEAR;var f=i(t),p=i(t),m=i(t),v=i(t),y=i(t),x=a(t,[{buffer:f,type:t.FLOAT,size:4},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:m,type:t.FLOAT,size:4},{buffer:v,type:t.FLOAT,size:2},{buffer:p,type:t.FLOAT,size:4}]),b=new h(t,u,s,l,f,p,y,m,v,x,r.traceType||\"cone\");return b.update(e),b}},{colormap:131,\"gl-buffer\":259,\"gl-mat4/invert\":293,\"gl-mat4/multiply\":295,\"gl-shader\":335,\"gl-texture2d\":353,\"gl-vao\":358,ndarray:495}],262:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec3 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, coneScale, coneOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * conePosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  // vec4 m_position  = model * vec4(conePosition, 1.0);\\n  vec4 t_position  = view * conePosition;\\n  gl_Position      = projection * t_position;\\n\\n  f_color          = color;\\n  f_data           = conePosition.xyz;\\n  f_position       = position.xyz;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float vectorScale, coneScale, coneOffset;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector.xyz), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n  gl_Position = projection * view * conePosition;\\n  f_id        = id;\\n  f_position  = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec3\"}]},r.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec3\"}]}},{glslify:263}],263:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],264:[function(t,e,r){e.exports={0:\"NONE\",1:\"ONE\",2:\"LINE_LOOP\",3:\"LINE_STRIP\",4:\"TRIANGLES\",5:\"TRIANGLE_STRIP\",6:\"TRIANGLE_FAN\",256:\"DEPTH_BUFFER_BIT\",512:\"NEVER\",513:\"LESS\",514:\"EQUAL\",515:\"LEQUAL\",516:\"GREATER\",517:\"NOTEQUAL\",518:\"GEQUAL\",519:\"ALWAYS\",768:\"SRC_COLOR\",769:\"ONE_MINUS_SRC_COLOR\",770:\"SRC_ALPHA\",771:\"ONE_MINUS_SRC_ALPHA\",772:\"DST_ALPHA\",773:\"ONE_MINUS_DST_ALPHA\",774:\"DST_COLOR\",775:\"ONE_MINUS_DST_COLOR\",776:\"SRC_ALPHA_SATURATE\",1024:\"STENCIL_BUFFER_BIT\",1028:\"FRONT\",1029:\"BACK\",1032:\"FRONT_AND_BACK\",1280:\"INVALID_ENUM\",1281:\"INVALID_VALUE\",1282:\"INVALID_OPERATION\",1285:\"OUT_OF_MEMORY\",1286:\"INVALID_FRAMEBUFFER_OPERATION\",2304:\"CW\",2305:\"CCW\",2849:\"LINE_WIDTH\",2884:\"CULL_FACE\",2885:\"CULL_FACE_MODE\",2886:\"FRONT_FACE\",2928:\"DEPTH_RANGE\",2929:\"DEPTH_TEST\",2930:\"DEPTH_WRITEMASK\",2931:\"DEPTH_CLEAR_VALUE\",2932:\"DEPTH_FUNC\",2960:\"STENCIL_TEST\",2961:\"STENCIL_CLEAR_VALUE\",2962:\"STENCIL_FUNC\",2963:\"STENCIL_VALUE_MASK\",2964:\"STENCIL_FAIL\",2965:\"STENCIL_PASS_DEPTH_FAIL\",2966:\"STENCIL_PASS_DEPTH_PASS\",2967:\"STENCIL_REF\",2968:\"STENCIL_WRITEMASK\",2978:\"VIEWPORT\",3024:\"DITHER\",3042:\"BLEND\",3088:\"SCISSOR_BOX\",3089:\"SCISSOR_TEST\",3106:\"COLOR_CLEAR_VALUE\",3107:\"COLOR_WRITEMASK\",3317:\"UNPACK_ALIGNMENT\",3333:\"PACK_ALIGNMENT\",3379:\"MAX_TEXTURE_SIZE\",3386:\"MAX_VIEWPORT_DIMS\",3408:\"SUBPIXEL_BITS\",3410:\"RED_BITS\",3411:\"GREEN_BITS\",3412:\"BLUE_BITS\",3413:\"ALPHA_BITS\",3414:\"DEPTH_BITS\",3415:\"STENCIL_BITS\",3553:\"TEXTURE_2D\",4352:\"DONT_CARE\",4353:\"FASTEST\",4354:\"NICEST\",5120:\"BYTE\",5121:\"UNSIGNED_BYTE\",5122:\"SHORT\",5123:\"UNSIGNED_SHORT\",5124:\"INT\",5125:\"UNSIGNED_INT\",5126:\"FLOAT\",5386:\"INVERT\",5890:\"TEXTURE\",6401:\"STENCIL_INDEX\",6402:\"DEPTH_COMPONENT\",6406:\"ALPHA\",6407:\"RGB\",6408:\"RGBA\",6409:\"LUMINANCE\",6410:\"LUMINANCE_ALPHA\",7680:\"KEEP\",7681:\"REPLACE\",7682:\"INCR\",7683:\"DECR\",7936:\"VENDOR\",7937:\"RENDERER\",7938:\"VERSION\",9728:\"NEAREST\",9729:\"LINEAR\",9984:\"NEAREST_MIPMAP_NEAREST\",9985:\"LINEAR_MIPMAP_NEAREST\",9986:\"NEAREST_MIPMAP_LINEAR\",9987:\"LINEAR_MIPMAP_LINEAR\",10240:\"TEXTURE_MAG_FILTER\",10241:\"TEXTURE_MIN_FILTER\",10242:\"TEXTURE_WRAP_S\",10243:\"TEXTURE_WRAP_T\",10497:\"REPEAT\",10752:\"POLYGON_OFFSET_UNITS\",16384:\"COLOR_BUFFER_BIT\",32769:\"CONSTANT_COLOR\",32770:\"ONE_MINUS_CONSTANT_COLOR\",32771:\"CONSTANT_ALPHA\",32772:\"ONE_MINUS_CONSTANT_ALPHA\",32773:\"BLEND_COLOR\",32774:\"FUNC_ADD\",32777:\"BLEND_EQUATION_RGB\",32778:\"FUNC_SUBTRACT\",32779:\"FUNC_REVERSE_SUBTRACT\",32819:\"UNSIGNED_SHORT_4_4_4_4\",32820:\"UNSIGNED_SHORT_5_5_5_1\",32823:\"POLYGON_OFFSET_FILL\",32824:\"POLYGON_OFFSET_FACTOR\",32854:\"RGBA4\",32855:\"RGB5_A1\",32873:\"TEXTURE_BINDING_2D\",32926:\"SAMPLE_ALPHA_TO_COVERAGE\",32928:\"SAMPLE_COVERAGE\",32936:\"SAMPLE_BUFFERS\",32937:\"SAMPLES\",32938:\"SAMPLE_COVERAGE_VALUE\",32939:\"SAMPLE_COVERAGE_INVERT\",32968:\"BLEND_DST_RGB\",32969:\"BLEND_SRC_RGB\",32970:\"BLEND_DST_ALPHA\",32971:\"BLEND_SRC_ALPHA\",33071:\"CLAMP_TO_EDGE\",33170:\"GENERATE_MIPMAP_HINT\",33189:\"DEPTH_COMPONENT16\",33306:\"DEPTH_STENCIL_ATTACHMENT\",33635:\"UNSIGNED_SHORT_5_6_5\",33648:\"MIRRORED_REPEAT\",33901:\"ALIASED_POINT_SIZE_RANGE\",33902:\"ALIASED_LINE_WIDTH_RANGE\",33984:\"TEXTURE0\",33985:\"TEXTURE1\",33986:\"TEXTURE2\",33987:\"TEXTURE3\",33988:\"TEXTURE4\",33989:\"TEXTURE5\",33990:\"TEXTURE6\",33991:\"TEXTURE7\",33992:\"TEXTURE8\",33993:\"TEXTURE9\",33994:\"TEXTURE10\",33995:\"TEXTURE11\",33996:\"TEXTURE12\",33997:\"TEXTURE13\",33998:\"TEXTURE14\",33999:\"TEXTURE15\",34e3:\"TEXTURE16\",34001:\"TEXTURE17\",34002:\"TEXTURE18\",34003:\"TEXTURE19\",34004:\"TEXTURE20\",34005:\"TEXTURE21\",34006:\"TEXTURE22\",34007:\"TEXTURE23\",34008:\"TEXTURE24\",34009:\"TEXTURE25\",34010:\"TEXTURE26\",34011:\"TEXTURE27\",34012:\"TEXTURE28\",34013:\"TEXTURE29\",34014:\"TEXTURE30\",34015:\"TEXTURE31\",34016:\"ACTIVE_TEXTURE\",34024:\"MAX_RENDERBUFFER_SIZE\",34041:\"DEPTH_STENCIL\",34055:\"INCR_WRAP\",34056:\"DECR_WRAP\",34067:\"TEXTURE_CUBE_MAP\",34068:\"TEXTURE_BINDING_CUBE_MAP\",34069:\"TEXTURE_CUBE_MAP_POSITIVE_X\",34070:\"TEXTURE_CUBE_MAP_NEGATIVE_X\",34071:\"TEXTURE_CUBE_MAP_POSITIVE_Y\",34072:\"TEXTURE_CUBE_MAP_NEGATIVE_Y\",34073:\"TEXTURE_CUBE_MAP_POSITIVE_Z\",34074:\"TEXTURE_CUBE_MAP_NEGATIVE_Z\",34076:\"MAX_CUBE_MAP_TEXTURE_SIZE\",34338:\"VERTEX_ATTRIB_ARRAY_ENABLED\",34339:\"VERTEX_ATTRIB_ARRAY_SIZE\",34340:\"VERTEX_ATTRIB_ARRAY_STRIDE\",34341:\"VERTEX_ATTRIB_ARRAY_TYPE\",34342:\"CURRENT_VERTEX_ATTRIB\"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p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float opacity;\\nvarying vec3 fragPosition;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if (\\n    outOfRange(clipBounds[0], clipBounds[1], fragPosition) ||\\n    fragColor.a * opacity == 0.\\n  ) discard;\\n\\n  gl_FragColor = opacity * fragColor;\\n}\"]);e.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"offset\",type:\"vec3\"}])}},{\"gl-shader\":335,glslify:267}],269:[function(t,e,r){\"use strict\";var n=t(\"gl-texture2d\");e.exports=function(t,e,r,n){i||(i=t.FRAMEBUFFER_UNSUPPORTED,a=t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT,o=t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS,s=t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT);var c=t.getExtension(\"WEBGL_draw_buffers\");!l&&c&&function(t,e){var r=t.getParameter(e.MAX_COLOR_ATTACHMENTS_WEBGL);l=new Array(r+1);for(var n=0;n<=r;++n){for(var i=new 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t.bindRenderbuffer(t.RENDERBUFFER,a),t.renderbufferStorage(t.RENDERBUFFER,n,e,r),t.framebufferRenderbuffer(t.FRAMEBUFFER,i,t.RENDERBUFFER,a),a}function d(t,e,r,n,i,a,o,s){this.gl=t,this._shape=[0|e,0|r],this._destroyed=!1,this._ext=s,this.color=new Array(i);for(var d=0;d<i;++d)this.color[d]=null;this._color_rb=null,this.depth=null,this._depth_rb=null,this._colorType=n,this._useDepth=a,this._useStencil=o;var g=this,m=[0|e,0|r];Object.defineProperties(m,{0:{get:function(){return g._shape[0]},set:function(t){return g.width=t}},1:{get:function(){return g._shape[1]},set:function(t){return g.height=t}}}),this._shapeVector=m,function(t){var e=c(t.gl),r=t.gl,n=t.handle=r.createFramebuffer(),i=t._shape[0],a=t._shape[1],o=t.color.length,s=t._ext,d=t._useStencil,g=t._useDepth,m=t._colorType;r.bindFramebuffer(r.FRAMEBUFFER,n);for(var v=0;v<o;++v)t.color[v]=h(r,i,a,m,r.RGBA,r.COLOR_ATTACHMENT0+v);0===o?(t._color_rb=p(r,i,a,r.RGBA4,r.COLOR_ATTACHMENT0),s&&s.drawBuffersWEBGL(l[0])):o>1&&s.drawBuffersWEBGL(l[o]);var y=r.getExtension(\"WEBGL_depth_texture\");y?d?t.depth=h(r,i,a,y.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):g&&(t.depth=h(r,i,a,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):g&&d?t._depth_rb=p(r,i,a,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):g?t._depth_rb=p(r,i,a,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):d&&(t._depth_rb=p(r,i,a,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null);for(v=0;v<t.color.length;++v)t.color[v].dispose(),t.color[v]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),u(r,e),f(x)}u(r,e)}(this)}var g=d.prototype;function m(t,e,r){if(t._destroyed)throw new Error(\"gl-fbo: Can't resize destroyed FBO\");if(t._shape[0]!==e||t._shape[1]!==r){var n=t.gl,i=n.getParameter(n.MAX_RENDERBUFFER_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var a=c(n),o=0;o<t.color.length;++o)t.color[o].shape=t._shape;t._color_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._color_rb),n.renderbufferStorage(n.RENDERBUFFER,n.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&n.renderbufferStorage(n.RENDERBUFFER,n.STENCIL_INDEX,t._shape[0],t._shape[1])),n.bindFramebuffer(n.FRAMEBUFFER,t.handle);var s=n.checkFramebufferStatus(n.FRAMEBUFFER);s!==n.FRAMEBUFFER_COMPLETE&&(t.dispose(),u(n,a),f(s)),u(n,a)}}Object.defineProperties(g,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error(\"gl-fbo: Shape vector must be length 2\");var e=0|t[0],r=0|t[1];return m(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return m(this,t|=0,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t|=0,m(this,this._shape[0],t),t},enumerable:!1}}),g.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},g.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},{\"gl-texture2d\":353}],270:[function(t,e,r){var n=t(\"sprintf-js\").sprintf,i=t(\"gl-constants/lookup\"),a=t(\"glsl-shader-name\"),o=t(\"add-line-numbers\");e.exports=function(t,e,r){\"use strict\";var s=a(e)||\"of unknown name (see npm glsl-shader-name)\",l=\"unknown type\";void 0!==r&&(l=r===i.FRAGMENT_SHADER?\"fragment\":\"vertex\");for(var c=n(\"Error compiling %s shader %s:\\n\",l,s),u=n(\"%s%s\",c,t),f=t.split(\"\\n\"),h={},p=0;p<f.length;p++){var d=f[p];if(\"\"!==d&&\"\\0\"!==d){var g=parseInt(d.split(\":\")[2]);if(isNaN(g))throw new Error(n(\"Could not parse error: %s\",d));h[g]=d}}var m=o(e).split(\"\\n\");for(p=0;p<m.length;p++)if(h[p+3]||h[p+2]||h[p+1]){var v=m[p];if(c+=v+\"\\n\",h[p+1]){var y=h[p+1];y=y.substr(y.split(\":\",3).join(\":\").length+1).trim(),c+=n(\"^^^ %s\\n\\n\",y)}}return{long:c.trim(),short:u.trim()}}},{\"add-line-numbers\":66,\"gl-constants/lookup\":265,\"glsl-shader-name\":431,\"sprintf-js\":567}],271:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=t.gl,n=o(r,l.vertex,l.fragment),i=o(r,l.pickVertex,l.pickFragment),a=s(r),u=s(r),f=s(r),h=s(r),p=new c(t,n,i,a,u,f,h);return p.update(e),t.addObject(p),p};var n=t(\"binary-search-bounds\"),i=t(\"iota-array\"),a=t(\"typedarray-pool\"),o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"./lib/shaders\");function c(t,e,r,n,i,a,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.weightBuffer=i,this.colorBuffer=a,this.idBuffer=o,this.xData=[],this.yData=[],this.shape=[0,0],this.bounds=[1/0,1/0,-1/0,-1/0],this.pickOffset=0}var u,f=c.prototype,h=[0,0,1,0,0,1,1,0,1,1,0,1];f.draw=(u=[1,0,0,0,1,0,0,0,1],function(){var t=this.plot,e=this.shader,r=this.bounds,n=this.numVertices;if(!(n<=0)){var i=t.gl,a=t.dataBox,o=r[2]-r[0],s=r[3]-r[1],l=a[2]-a[0],c=a[3]-a[1];u[0]=2*o/l,u[4]=2*s/c,u[6]=2*(r[0]-a[0])/l-1,u[7]=2*(r[1]-a[1])/c-1,e.bind();var f=e.uniforms;f.viewTransform=u,f.shape=this.shape;var h=e.attributes;this.positionBuffer.bind(),h.position.pointer(),this.weightBuffer.bind(),h.weight.pointer(i.UNSIGNED_BYTE,!1),this.colorBuffer.bind(),h.color.pointer(i.UNSIGNED_BYTE,!0),i.drawArrays(i.TRIANGLES,0,n)}}),f.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,i=this.pickShader,a=this.bounds,o=this.numVertices;if(!(o<=0)){var s=n.gl,l=n.dataBox,c=a[2]-a[0],u=a[3]-a[1],f=l[2]-l[0],h=l[3]-l[1];t[0]=2*c/f,t[4]=2*u/h,t[6]=2*(a[0]-l[0])/f-1,t[7]=2*(a[1]-l[1])/h-1;for(var p=0;p<4;++p)e[p]=r>>8*p&255;this.pickOffset=r,i.bind();var d=i.uniforms;d.viewTransform=t,d.pickOffset=e,d.shape=this.shape;var g=i.attributes;return this.positionBuffer.bind(),g.position.pointer(),this.weightBuffer.bind(),g.weight.pointer(s.UNSIGNED_BYTE,!1),this.idBuffer.bind(),g.pickId.pointer(s.UNSIGNED_BYTE,!1),s.drawArrays(s.TRIANGLES,0,o),r+this.shape[0]*this.shape[1]}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.shape[0]*this.shape[1];if(r<n||r>=n+i)return null;var a=r-n,o=this.xData,s=this.yData;return{object:this,pointId:a,dataCoord:[o[a%this.shape[0]],s[a/this.shape[0]|0]]}},f.update=function(t){var e=(t=t||{}).shape||[0,0],r=t.x||i(e[0]),o=t.y||i(e[1]),s=t.z||new Float32Array(e[0]*e[1]),l=!1!==t.zsmooth;this.xData=r,this.yData=o;var c,u,f,p,d=t.colorLevels||[0],g=t.colorValues||[0,0,0,1],m=d.length,v=this.bounds;l?(c=v[0]=r[0],u=v[1]=o[0],f=v[2]=r[r.length-1],p=v[3]=o[o.length-1]):(c=v[0]=r[0]+(r[1]-r[0])/2,u=v[1]=o[0]+(o[1]-o[0])/2,f=v[2]=r[r.length-1]+(r[r.length-1]-r[r.length-2])/2,p=v[3]=o[o.length-1]+(o[o.length-1]-o[o.length-2])/2);var y=1/(f-c),x=1/(p-u),b=e[0],_=e[1];this.shape=[b,_];var w=(l?(b-1)*(_-1):b*_)*(h.length>>>1);this.numVertices=w;for(var T=a.mallocUint8(4*w),k=a.mallocFloat32(2*w),M=a.mallocUint8(2*w),A=a.mallocUint32(w),S=0,E=l?b-1:b,C=l?_-1:_,L=0;L<C;++L){var I,P;l?(I=x*(o[L]-u),P=x*(o[L+1]-u)):(I=L<_-1?x*(o[L]-(o[L+1]-o[L])/2-u):x*(o[L]-(o[L]-o[L-1])/2-u),P=L<_-1?x*(o[L]+(o[L+1]-o[L])/2-u):x*(o[L]+(o[L]-o[L-1])/2-u));for(var z=0;z<E;++z){var O,D;l?(O=y*(r[z]-c),D=y*(r[z+1]-c)):(O=z<b-1?y*(r[z]-(r[z+1]-r[z])/2-c):y*(r[z]-(r[z]-r[z-1])/2-c),D=z<b-1?y*(r[z]+(r[z+1]-r[z])/2-c):y*(r[z]+(r[z]-r[z-1])/2-c));for(var R=0;R<h.length;R+=2){var F,B,N,j,U=h[R],V=h[R+1],q=s[l?(L+V)*b+(z+U):L*b+z],H=n.le(d,q);if(H<0)F=g[0],B=g[1],N=g[2],j=g[3];else if(H===m-1)F=g[4*m-4],B=g[4*m-3],N=g[4*m-2],j=g[4*m-1];else{var G=(q-d[H])/(d[H+1]-d[H]),Y=1-G,W=4*H,X=4*(H+1);F=Y*g[W]+G*g[X],B=Y*g[W+1]+G*g[X+1],N=Y*g[W+2]+G*g[X+2],j=Y*g[W+3]+G*g[X+3]}T[4*S]=255*F,T[4*S+1]=255*B,T[4*S+2]=255*N,T[4*S+3]=255*j,k[2*S]=.5*O+.5*D,k[2*S+1]=.5*I+.5*P,M[2*S]=U,M[2*S+1]=V,A[S]=L*b+z,S+=1}}}this.positionBuffer.update(k),this.weightBuffer.update(M),this.colorBuffer.update(T),this.idBuffer.update(A),a.free(k),a.free(T),a.free(M),a.free(A)},f.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.weightBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},{\"./lib/shaders\":272,\"binary-search-bounds\":96,\"gl-buffer\":259,\"gl-shader\":335,\"iota-array\":463,\"typedarray-pool\":595}],272:[function(t,e,r){\"use strict\";var n=t(\"glslify\");e.exports={fragment:n([\"precision lowp float;\\n#define GLSLIFY 1\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\"]),vertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 color;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n  fragColor = color;\\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"]),pickFragment:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nuniform vec2 shape;\\nuniform vec4 pickOffset;\\n\\nvoid main() {\\n  vec2 d = step(.5, vWeight);\\n  vec4 id = fragId + pickOffset;\\n  id.x += d.x + d.y*shape.x;\\n\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  gl_FragColor = id/255.;\\n}\\n\"]),pickVertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nvoid main() {\\n  vWeight = weight;\\n\\n  fragId = pickId;\\n\\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"])}},{glslify:273}],273:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],274:[function(t,e,r){var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvec4 project(vec3 p) {\\n  return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n  vec4 startPoint = project(position);\\n  vec4 endPoint   = project(nextPosition);\\n\\n  vec2 A = startPoint.xy / startPoint.w;\\n  vec2 B =   endPoint.xy /   endPoint.w;\\n\\n  float clipAngle = atan(\\n    (B.y - A.y) * screenShape.y,\\n    (B.x - A.x) * screenShape.x\\n  );\\n\\n  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(\\n    sin(clipAngle),\\n    -cos(clipAngle)\\n  ) / screenShape;\\n\\n  gl_Position = vec4(startPoint.xy + startPoint.w * offset, startPoint.zw);\\n\\n  worldPosition = position;\\n  pixelArcLength = arcLength;\\n  fragColor = color;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3      clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float     dashScale;\\nuniform float     opacity;\\n\\nvarying vec3    worldPosition;\\nvarying float   pixelArcLength;\\nvarying vec4    fragColor;\\n\\nvoid main() {\\n  if (\\n    outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\\n    fragColor.a * opacity == 0.\\n  ) discard;\\n\\n  float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n  if(dashWeight < 0.5) {\\n    discard;\\n  }\\n  gl_FragColor = fragColor * opacity;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\n#define FLOAT_MAX  1.70141184e38\\n#define FLOAT_MIN  1.17549435e-38\\n\\n// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl\\nvec4 packFloat(float v) {\\n  float av = abs(v);\\n\\n  //Handle special cases\\n  if(av < FLOAT_MIN) {\\n    return vec4(0.0, 0.0, 0.0, 0.0);\\n  } else if(v > FLOAT_MAX) {\\n    return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n  } else if(v < -FLOAT_MAX) {\\n    return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n  }\\n\\n  vec4 c = vec4(0,0,0,0);\\n\\n  //Compute exponent and mantissa\\n  float e = floor(log2(av));\\n  float m = av * pow(2.0, -e) - 1.0;\\n\\n  //Unpack mantissa\\n  c[1] = floor(128.0 * m);\\n  m -= c[1] / 128.0;\\n  c[2] = floor(32768.0 * m);\\n  m -= c[2] / 32768.0;\\n  c[3] = floor(8388608.0 * m);\\n\\n  //Unpack exponent\\n  float ebias = e + 127.0;\\n  c[0] = floor(ebias / 2.0);\\n  ebias -= c[0] * 2.0;\\n  c[1] += floor(ebias) * 128.0;\\n\\n  //Unpack sign bit\\n  c[0] += 128.0 * step(0.0, -v);\\n\\n  //Scale back to range\\n  return c / 255.0;\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\\n\\n  gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz);\\n}\"]),l=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];r.createShader=function(t){return i(t,a,o,null,l)},r.createPickShader=function(t){return i(t,a,s,null,l)}},{\"gl-shader\":335,glslify:276}],275:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl||t.scene&&t.scene.gl,r=f(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var o=h(e);o.attributes.position.location=0,o.attributes.nextPosition.location=1,o.attributes.arcLength.location=2,o.attributes.lineWidth.location=3,o.attributes.color.location=4;for(var s=n(e),l=i(e,[{buffer:s,size:3,offset:0,stride:48},{buffer:s,size:3,offset:12,stride:48},{buffer:s,size:1,offset:24,stride:48},{buffer:s,size:1,offset:28,stride:48},{buffer:s,size:4,offset:32,stride:48}]),u=c(new Array(1024),[256,1,4]),p=0;p<1024;++p)u.data[p]=255;var d=a(e,u);d.wrap=e.REPEAT;var g=new v(e,r,o,s,l,d);return g.update(t),g};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"gl-texture2d\"),o=new Uint8Array(4),s=new Float32Array(o.buffer);var l=t(\"binary-search-bounds\"),c=t(\"ndarray\"),u=t(\"./lib/shaders\"),f=u.createShader,h=u.createPickShader,p=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function d(t,e){for(var r=0,n=0;n<3;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function g(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function m(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function v(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.hasAlpha=!1,this.dirty=!0,this.pixelRatio=1}var y=v.prototype;y.isTransparent=function(){return this.hasAlpha},y.isOpaque=function(){return!this.hasAlpha},y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.drawTransparent=y.draw=function(t){if(this.vertexCount){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,clipBounds:g(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},y.drawPick=function(t){if(this.vertexCount){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,pickId:this.pickId,clipBounds:g(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},y.update=function(t){var e,r;this.dirty=!0;var n=!!t.connectGaps;\"dashScale\"in t&&(this.dashScale=t.dashScale),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var i=[],a=[],o=[],s=0,u=0,f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],h=t.position||t.positions;if(h){var p=t.color||t.colors||[0,0,0,1],g=t.lineWidth||1,m=!1;t:for(e=1;e<h.length;++e){var v,y,x,b=h[e-1],_=h[e];for(a.push(s),o.push(b.slice()),r=0;r<3;++r){if(isNaN(b[r])||isNaN(_[r])||!isFinite(b[r])||!isFinite(_[r])){if(!n&&i.length>0){for(var w=0;w<24;++w)i.push(i[i.length-12]);u+=2,m=!0}continue t}f[0][r]=Math.min(f[0][r],b[r],_[r]),f[1][r]=Math.max(f[1][r],b[r],_[r])}Array.isArray(p[0])?(v=p.length>e-1?p[e-1]:p.length>0?p[p.length-1]:[0,0,0,1],y=p.length>e?p[e]:p.length>0?p[p.length-1]:[0,0,0,1]):v=y=p,3===v.length&&(v=[v[0],v[1],v[2],1]),3===y.length&&(y=[y[0],y[1],y[2],1]),!this.hasAlpha&&v[3]<1&&(this.hasAlpha=!0),x=Array.isArray(g)?g.length>e-1?g[e-1]:g.length>0?g[g.length-1]:[0,0,0,1]:g;var 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t[0]=1-(p+g),t[1]=f+y,t[2]=h-v,t[3]=0,t[4]=f-y,t[5]=1-(u+g),t[6]=d+m,t[7]=0,t[8]=h+v,t[9]=d-m,t[10]=1-(u+p),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}},{}],285:[function(t,e,r){e.exports=function(t,e){return t[0]=e[0],t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=e[1],t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=e[2],t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],286:[function(t,e,r){e.exports=function(t,e){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=e[0],t[13]=e[1],t[14]=e[2],t[15]=1,t}},{}],287:[function(t,e,r){e.exports=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=n,t[6]=r,t[7]=0,t[8]=0,t[9]=-r,t[10]=n,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],288:[function(t,e,r){e.exports=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=0,t[2]=-r,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=r,t[9]=0,t[10]=n,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],289:[function(t,e,r){e.exports=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=r,t[2]=0,t[3]=0,t[4]=-r,t[5]=n,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],290:[function(t,e,r){e.exports=function(t,e,r,n,i,a,o){var s=1/(r-e),l=1/(i-n),c=1/(a-o);return t[0]=2*a*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=2*a*l,t[6]=0,t[7]=0,t[8]=(r+e)*s,t[9]=(i+n)*l,t[10]=(o+a)*c,t[11]=-1,t[12]=0,t[13]=0,t[14]=o*a*2*c,t[15]=0,t}},{}],291:[function(t,e,r){e.exports=function(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],292:[function(t,e,r){e.exports={create:t(\"./create\"),clone:t(\"./clone\"),copy:t(\"./copy\"),identity:t(\"./identity\"),transpose:t(\"./transpose\"),invert:t(\"./invert\"),adjoint:t(\"./adjoint\"),determinant:t(\"./determinant\"),multiply:t(\"./multiply\"),translate:t(\"./translate\"),scale:t(\"./scale\"),rotate:t(\"./rotate\"),rotateX:t(\"./rotateX\"),rotateY:t(\"./rotateY\"),rotateZ:t(\"./rotateZ\"),fromRotation:t(\"./fromRotation\"),fromRotationTranslation:t(\"./fromRotationTranslation\"),fromScaling:t(\"./fromScaling\"),fromTranslation:t(\"./fromTranslation\"),fromXRotation:t(\"./fromXRotation\"),fromYRotation:t(\"./fromYRotation\"),fromZRotation:t(\"./fromZRotation\"),fromQuat:t(\"./fromQuat\"),frustum:t(\"./frustum\"),perspective:t(\"./perspective\"),perspectiveFromFieldOfView:t(\"./perspectiveFromFieldOfView\"),ortho:t(\"./ortho\"),lookAt:t(\"./lookAt\"),str:t(\"./str\")}},{\"./adjoint\":277,\"./clone\":278,\"./copy\":279,\"./create\":280,\"./determinant\":281,\"./fromQuat\":282,\"./fromRotation\":283,\"./fromRotationTranslation\":284,\"./fromScaling\":285,\"./fromTranslation\":286,\"./fromXRotation\":287,\"./fromYRotation\":288,\"./fromZRotation\":289,\"./frustum\":290,\"./identity\":291,\"./invert\":293,\"./lookAt\":294,\"./multiply\":295,\"./ortho\":296,\"./perspective\":297,\"./perspectiveFromFieldOfView\":298,\"./rotate\":299,\"./rotateX\":300,\"./rotateY\":301,\"./rotateZ\":302,\"./scale\":303,\"./str\":304,\"./translate\":305,\"./transpose\":306}],293:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],c=e[7],u=e[8],f=e[9],h=e[10],p=e[11],d=e[12],g=e[13],m=e[14],v=e[15],y=r*s-n*o,x=r*l-i*o,b=r*c-a*o,_=n*l-i*s,w=n*c-a*s,T=i*c-a*l,k=u*g-f*d,M=u*m-h*d,A=u*v-p*d,S=f*m-h*g,E=f*v-p*g,C=h*v-p*m,L=y*C-x*E+b*S+_*A-w*M+T*k;if(!L)return null;return L=1/L,t[0]=(s*C-l*E+c*S)*L,t[1]=(i*E-n*C-a*S)*L,t[2]=(g*T-m*w+v*_)*L,t[3]=(h*w-f*T-p*_)*L,t[4]=(l*A-o*C-c*M)*L,t[5]=(r*C-i*A+a*M)*L,t[6]=(m*b-d*T-v*x)*L,t[7]=(u*T-h*b+p*x)*L,t[8]=(o*E-s*A+c*k)*L,t[9]=(n*A-r*E-a*k)*L,t[10]=(d*w-g*b+v*y)*L,t[11]=(f*b-u*w-p*y)*L,t[12]=(s*M-o*S-l*k)*L,t[13]=(r*S-n*M+i*k)*L,t[14]=(g*x-d*_-m*y)*L,t[15]=(u*_-f*x+h*y)*L,t}},{}],294:[function(t,e,r){var n=t(\"./identity\");e.exports=function(t,e,r,i){var a,o,s,l,c,u,f,h,p,d,g=e[0],m=e[1],v=e[2],y=i[0],x=i[1],b=i[2],_=r[0],w=r[1],T=r[2];if(Math.abs(g-_)<1e-6&&Math.abs(m-w)<1e-6&&Math.abs(v-T)<1e-6)return n(t);f=g-_,h=m-w,p=v-T,d=1/Math.sqrt(f*f+h*h+p*p),a=x*(p*=d)-b*(h*=d),o=b*(f*=d)-y*p,s=y*h-x*f,(d=Math.sqrt(a*a+o*o+s*s))?(a*=d=1/d,o*=d,s*=d):(a=0,o=0,s=0);l=h*s-p*o,c=p*a-f*s,u=f*o-h*a,(d=Math.sqrt(l*l+c*c+u*u))?(l*=d=1/d,c*=d,u*=d):(l=0,c=0,u=0);return t[0]=a,t[1]=l,t[2]=f,t[3]=0,t[4]=o,t[5]=c,t[6]=h,t[7]=0,t[8]=s,t[9]=u,t[10]=p,t[11]=0,t[12]=-(a*g+o*m+s*v),t[13]=-(l*g+c*m+u*v),t[14]=-(f*g+h*m+p*v),t[15]=1,t}},{\"./identity\":291}],295:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],f=e[8],h=e[9],p=e[10],d=e[11],g=e[12],m=e[13],v=e[14],y=e[15],x=r[0],b=r[1],_=r[2],w=r[3];return t[0]=x*n+b*s+_*f+w*g,t[1]=x*i+b*l+_*h+w*m,t[2]=x*a+b*c+_*p+w*v,t[3]=x*o+b*u+_*d+w*y,x=r[4],b=r[5],_=r[6],w=r[7],t[4]=x*n+b*s+_*f+w*g,t[5]=x*i+b*l+_*h+w*m,t[6]=x*a+b*c+_*p+w*v,t[7]=x*o+b*u+_*d+w*y,x=r[8],b=r[9],_=r[10],w=r[11],t[8]=x*n+b*s+_*f+w*g,t[9]=x*i+b*l+_*h+w*m,t[10]=x*a+b*c+_*p+w*v,t[11]=x*o+b*u+_*d+w*y,x=r[12],b=r[13],_=r[14],w=r[15],t[12]=x*n+b*s+_*f+w*g,t[13]=x*i+b*l+_*h+w*m,t[14]=x*a+b*c+_*p+w*v,t[15]=x*o+b*u+_*d+w*y,t}},{}],296:[function(t,e,r){e.exports=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),c=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*c,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*c,t[15]=1,t}},{}],297:[function(t,e,r){e.exports=function(t,e,r,n,i){var a=1/Math.tan(e/2),o=1/(n-i);return t[0]=a/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=a,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(i+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*i*n*o,t[15]=0,t}},{}],298:[function(t,e,r){e.exports=function(t,e,r,n){var i=Math.tan(e.upDegrees*Math.PI/180),a=Math.tan(e.downDegrees*Math.PI/180),o=Math.tan(e.leftDegrees*Math.PI/180),s=Math.tan(e.rightDegrees*Math.PI/180),l=2/(o+s),c=2/(i+a);return t[0]=l,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=c,t[6]=0,t[7]=0,t[8]=-(o-s)*l*.5,t[9]=(i-a)*c*.5,t[10]=n/(r-n),t[11]=-1,t[12]=0,t[13]=0,t[14]=n*r/(r-n),t[15]=0,t}},{}],299:[function(t,e,r){e.exports=function(t,e,r,n){var i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,w,T,k,M,A,S,E=n[0],C=n[1],L=n[2],I=Math.sqrt(E*E+C*C+L*L);if(Math.abs(I)<1e-6)return null;E*=I=1/I,C*=I,L*=I,i=Math.sin(r),a=Math.cos(r),o=1-a,s=e[0],l=e[1],c=e[2],u=e[3],f=e[4],h=e[5],p=e[6],d=e[7],g=e[8],m=e[9],v=e[10],y=e[11],x=E*E*o+a,b=C*E*o+L*i,_=L*E*o-C*i,w=E*C*o-L*i,T=C*C*o+a,k=L*C*o+E*i,M=E*L*o+C*i,A=C*L*o-E*i,S=L*L*o+a,t[0]=s*x+f*b+g*_,t[1]=l*x+h*b+m*_,t[2]=c*x+p*b+v*_,t[3]=u*x+d*b+y*_,t[4]=s*w+f*T+g*k,t[5]=l*w+h*T+m*k,t[6]=c*w+p*T+v*k,t[7]=u*w+d*T+y*k,t[8]=s*M+f*A+g*S,t[9]=l*M+h*A+m*S,t[10]=c*M+p*A+v*S,t[11]=u*M+d*A+y*S,e!==t&&(t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t}},{}],300:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[4],o=e[5],s=e[6],l=e[7],c=e[8],u=e[9],f=e[10],h=e[11];e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[4]=a*i+c*n,t[5]=o*i+u*n,t[6]=s*i+f*n,t[7]=l*i+h*n,t[8]=c*i-a*n,t[9]=u*i-o*n,t[10]=f*i-s*n,t[11]=h*i-l*n,t}},{}],301:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],c=e[8],u=e[9],f=e[10],h=e[11];e!==t&&(t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[0]=a*i-c*n,t[1]=o*i-u*n,t[2]=s*i-f*n,t[3]=l*i-h*n,t[8]=a*n+c*i,t[9]=o*n+u*i,t[10]=s*n+f*i,t[11]=l*n+h*i,t}},{}],302:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],c=e[4],u=e[5],f=e[6],h=e[7];e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[0]=a*i+c*n,t[1]=o*i+u*n,t[2]=s*i+f*n,t[3]=l*i+h*n,t[4]=c*i-a*n,t[5]=u*i-o*n,t[6]=f*i-s*n,t[7]=h*i-l*n,t}},{}],303:[function(t,e,r){e.exports=function(t,e,r){var n=r[0],i=r[1],a=r[2];return t[0]=e[0]*n,t[1]=e[1]*n,t[2]=e[2]*n,t[3]=e[3]*n,t[4]=e[4]*i,t[5]=e[5]*i,t[6]=e[6]*i,t[7]=e[7]*i,t[8]=e[8]*a,t[9]=e[9]*a,t[10]=e[10]*a,t[11]=e[11]*a,t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t}},{}],304:[function(t,e,r){e.exports=function(t){return\"mat4(\"+t[0]+\", \"+t[1]+\", \"+t[2]+\", \"+t[3]+\", \"+t[4]+\", \"+t[5]+\", \"+t[6]+\", \"+t[7]+\", \"+t[8]+\", \"+t[9]+\", \"+t[10]+\", \"+t[11]+\", \"+t[12]+\", \"+t[13]+\", \"+t[14]+\", \"+t[15]+\")\"}},{}],305:[function(t,e,r){e.exports=function(t,e,r){var n,i,a,o,s,l,c,u,f,h,p,d,g=r[0],m=r[1],v=r[2];e===t?(t[12]=e[0]*g+e[4]*m+e[8]*v+e[12],t[13]=e[1]*g+e[5]*m+e[9]*v+e[13],t[14]=e[2]*g+e[6]*m+e[10]*v+e[14],t[15]=e[3]*g+e[7]*m+e[11]*v+e[15]):(n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],f=e[8],h=e[9],p=e[10],d=e[11],t[0]=n,t[1]=i,t[2]=a,t[3]=o,t[4]=s,t[5]=l,t[6]=c,t[7]=u,t[8]=f,t[9]=h,t[10]=p,t[11]=d,t[12]=n*g+s*m+f*v+e[12],t[13]=i*g+l*m+h*v+e[13],t[14]=a*g+c*m+p*v+e[14],t[15]=o*g+u*m+d*v+e[15]);return t}},{}],306:[function(t,e,r){e.exports=function(t,e){if(t===e){var r=e[1],n=e[2],i=e[3],a=e[6],o=e[7],s=e[11];t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=r,t[6]=e[9],t[7]=e[13],t[8]=n,t[9]=a,t[11]=e[14],t[12]=i,t[13]=o,t[14]=s}else t[0]=e[0],t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=e[1],t[5]=e[5],t[6]=e[9],t[7]=e[13],t[8]=e[2],t[9]=e[6],t[10]=e[10],t[11]=e[14],t[12]=e[3],t[13]=e[7],t[14]=e[11],t[15]=e[15];return t}},{}],307:[function(t,e,r){\"use strict\";var n=t(\"barycentric\"),i=t(\"polytope-closest-point/lib/closest_point_2d.js\");function a(t,e){for(var r=[0,0,0,0],n=0;n<4;++n)for(var i=0;i<4;++i)r[i]+=t[4*n+i]*e[n];return r}function o(t,e,r,n,i){for(var o=a(n,a(r,a(e,[t[0],t[1],t[2],1]))),s=0;s<3;++s)o[s]/=o[3];return[.5*i[0]*(1+o[0]),.5*i[1]*(1-o[1])]}function s(t,e){for(var r=[0,0,0],n=0;n<t.length;++n)for(var i=t[n],a=e[n],o=0;o<3;++o)r[o]+=a*i[o];return r}e.exports=function(t,e,r,a,l,c){if(1===t.length)return[0,t[0].slice()];for(var u=new Array(t.length),f=0;f<t.length;++f)u[f]=o(t[f],r,a,l,c);var h=0,p=1/0;for(f=0;f<u.length;++f){for(var d=0,g=0;g<2;++g)d+=Math.pow(u[f][g]-e[g],2);d<p&&(p=d,h=f)}var m=function(t,e){if(2===t.length){for(var r=0,a=0,o=0;o<2;++o)r+=Math.pow(e[o]-t[0][o],2),a+=Math.pow(e[o]-t[1][o],2);return r=Math.sqrt(r),a=Math.sqrt(a),r+a<1e-6?[1,0]:[a/(r+a),r/(a+r)]}if(3===t.length){var s=[0,0];return i(t[0],t[1],t[2],e,s),n(t,s)}return[]}(u,e),v=0;for(f=0;f<3;++f){if(m[f]<-.001||m[f]>1.0001)return null;v+=m[f]}if(Math.abs(v-1)>.001)return null;return[h,s(t,m),m]}},{barycentric:78,\"polytope-closest-point/lib/closest_point_2d.js\":525}],308:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n           , view\\n           , projection\\n           , inverseModel;\\nuniform vec3 eyePosition\\n           , lightPosition;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvec4 project(vec3 p) {\\n  return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n  gl_Position      = project(position);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * vec4(position , 1.0);\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal  = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  f_color          = color;\\n  f_data           = position;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n            , fresnel\\n            , kambient\\n            , kdiffuse\\n            , kspecular;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (f_color.a == 0.0 ||\\n    outOfRange(clipBounds[0], clipBounds[1], f_data)\\n  ) discard;\\n\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\\n\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * f_color.a;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_color = color;\\n  f_data  = position;\\n  f_uv    = uv;\\n}\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\\n\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\\n  } else {\\n    gl_Position = projection * view * model * vec4(position, 1.0);\\n  }\\n  gl_PointSize = pointSize;\\n  f_color = color;\\n  f_uv = uv;\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\\n  if(dot(pointR, pointR) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_id        = id;\\n  f_position  = position;\\n}\"]),f=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]),h=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3  position;\\nattribute float pointSize;\\nattribute vec4  id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\\n  } else {\\n    gl_Position  = projection * view * model * vec4(position, 1.0);\\n    gl_PointSize = pointSize;\\n  }\\n  f_id         = id;\\n  f_position   = position;\\n}\"]),p=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n}\"]),d=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n  gl_FragColor = vec4(contourColor, 1.0);\\n}\\n\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.wireShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.pointShader={vertex:l,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},r.pickShader={vertex:u,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},r.pointPickShader={vertex:h,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},r.contourShader={vertex:p,fragment:d,attributes:[{name:\"position\",type:\"vec3\"}]}},{glslify:310}],309:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"normals\"),l=t(\"gl-mat4/multiply\"),c=t(\"gl-mat4/invert\"),u=t(\"ndarray\"),f=t(\"colormap\"),h=t(\"simplicial-complex-contour\"),p=t(\"typedarray-pool\"),d=t(\"./lib/shaders\"),g=t(\"./lib/closest-point\"),m=d.meshShader,v=d.wireShader,y=d.pointShader,x=d.pickShader,b=d.pointPickShader,_=d.contourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function T(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,T,k,M,A,S){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=u,this.triangleNormals=h,this.triangleUVs=f,this.triangleIds=c,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=m,this.edgeUVs=v,this.edgeIds=g,this.edgeVAO=y,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=T,this.pointSizes=k,this.pointIds=b,this.pointVAO=M,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=A,this.contourVAO=S,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=w,this._view=w,this._projection=w,this._resolution=[1,1]}var k=T.prototype;function M(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}function A(t){var e=n(t,m.vertex,m.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}function S(t){var e=n(t,v.vertex,v.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}function E(t){var e=n(t,y.vertex,y.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function C(t){var e=n(t,x.vertex,x.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e}function L(t){var e=n(t,b.vertex,b.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function I(t){var e=n(t,_.vertex,_.fragment);return e.attributes.position.location=0,e}k.isOpaque=function(){return!this.hasAlpha},k.isTransparent=function(){return this.hasAlpha},k.pickSlots=1,k.setPickBase=function(t){this.pickId=t},k.highlight=function(t){if(t&&this.contourEnable){for(var e=h(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=p.mallocFloat32(6*a),s=0,l=0;l<a;++l)for(var c=r[l],u=0;u<2;++u){var f=c[0];2===c.length&&(f=c[u]);for(var d=n[f][0],g=n[f][1],m=i[f],v=1-m,y=this.positions[d],x=this.positions[g],b=0;b<3;++b)o[s++]=m*y[b]+v*x[b]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),p.free(o)}else this.contourCount=0},k.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=t.opacity,this.opacity<1&&(this.hasAlpha=!0)),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale,this.hasAlpha=!0),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),t.texture?(this.texture.dispose(),this.texture=o(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t,e){for(var r=f({colormap:t,nshades:256,format:\"rgba\"}),n=new Uint8Array(1024),i=0;i<256;++i){for(var a=r[i],o=0;o<3;++o)n[4*i+o]=a[o];n[4*i+3]=e?255*M(i/255,e):255*a[3]}return u(n,[256,256,4],[4,0,1])}(t.colormap,this.opacityscale)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var i=[],a=[],l=[],c=[],h=[],p=[],d=[],g=[],m=[],v=[],y=[],x=[],b=[],_=[];this.cells=r,this.positions=n;var w=t.vertexNormals,T=t.cellNormals,k=void 0===t.vertexNormalsEpsilon?1e-6:t.vertexNormalsEpsilon,A=void 0===t.faceNormalsEpsilon?1e-6:t.faceNormalsEpsilon;t.useFacetNormals&&!T&&(T=s.faceNormals(r,n,A)),T||w||(w=s.vertexNormals(r,n,k));var S=t.vertexColors,E=t.cellColors,C=t.meshColor||[1,1,1,1],L=t.vertexUVs,I=t.vertexIntensity,P=t.cellUVs,z=t.cellIntensity,O=1/0,D=-1/0;if(!L&&!P)if(I)if(t.vertexIntensityBounds)O=+t.vertexIntensityBounds[0],D=+t.vertexIntensityBounds[1];else for(var R=0;R<I.length;++R){var F=I[R];O=Math.min(O,F),D=Math.max(D,F)}else if(z)if(t.cellIntensityBounds)O=+t.cellIntensityBounds[0],D=+t.cellIntensityBounds[1];else for(R=0;R<z.length;++R){F=z[R];O=Math.min(O,F),D=Math.max(D,F)}else for(R=0;R<n.length;++R){F=n[R][2];O=Math.min(O,F),D=Math.max(D,F)}this.intensity=I||(z||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n)),this.pickVertex=!(z||E);var B=t.pointSizes,N=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(R=0;R<n.length;++R)for(var j=n[R],U=0;U<3;++U)!isNaN(j[U])&&isFinite(j[U])&&(this.bounds[0][U]=Math.min(this.bounds[0][U],j[U]),this.bounds[1][U]=Math.max(this.bounds[1][U],j[U]));var V=0,q=0,H=0;t:for(R=0;R<r.length;++R){var G=r[R];switch(G.length){case 1:for(j=n[W=G[0]],U=0;U<3;++U)if(isNaN(j[U])||!isFinite(j[U]))continue t;v.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:C,this.opacityscale&&I?a.push(X[0],X[1],X[2],this.opacity*M((I[W]-O)/(D-O),this.opacityscale)):3===X.length?y.push(X[0],X[1],X[2],this.opacity):(y.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=L?L[W]:I?[(I[W]-O)/(D-O),0]:P?P[R]:z?[(z[R]-O)/(D-O),0]:[(j[2]-O)/(D-O),0],x.push(Z[0],Z[1]),B?b.push(B[W]):b.push(N),_.push(R),H+=1;break;case 2:for(U=0;U<2;++U){j=n[W=G[U]];for(var Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t}for(U=0;U<2;++U){j=n[W=G[U]];p.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:C,this.opacityscale&&I?a.push(X[0],X[1],X[2],this.opacity*M((I[W]-O)/(D-O),this.opacityscale)):3===X.length?d.push(X[0],X[1],X[2],this.opacity):(d.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=L?L[W]:I?[(I[W]-O)/(D-O),0]:P?P[R]:z?[(z[R]-O)/(D-O),0]:[(j[2]-O)/(D-O),0],g.push(Z[0],Z[1]),m.push(R)}q+=1;break;case 3:for(U=0;U<3;++U)for(j=n[W=G[U]],Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t;for(U=0;U<3;++U){var W,X,Z,J;j=n[W=G[2-U]];i.push(j[0],j[1],j[2]),(X=S?S[W]:E?E[R]:C)?this.opacityscale&&I?a.push(X[0],X[1],X[2],this.opacity*M((I[W]-O)/(D-O),this.opacityscale)):3===X.length?a.push(X[0],X[1],X[2],this.opacity):(a.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)):a.push(.5,.5,.5,1),Z=L?L[W]:I?[(I[W]-O)/(D-O),0]:P?P[R]:z?[(z[R]-O)/(D-O),0]:[(j[2]-O)/(D-O),0],c.push(Z[0],Z[1]),J=w?w[W]:T[R],l.push(J[0],J[1],J[2]),h.push(R)}V+=1}}this.pointCount=H,this.edgeCount=q,this.triangleCount=V,this.pointPositions.update(v),this.pointColors.update(y),this.pointUVs.update(x),this.pointSizes.update(b),this.pointIds.update(new Uint32Array(_)),this.edgePositions.update(p),this.edgeColors.update(d),this.edgeUVs.update(g),this.edgeIds.update(new Uint32Array(m)),this.trianglePositions.update(i),this.triangleColors.update(a),this.triangleUVs.update(c),this.triangleNormals.update(l),this.triangleIds.update(new Uint32Array(h))}},k.drawTransparent=k.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,inverseModel:w.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],contourColor:this.contourColor,texture:0};s.inverseModel=c(s.inverseModel,s.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);l(u,s.view,s.model),l(u,s.projection,u),c(u,u);for(o=0;o<3;++o)s.eyePosition[o]=u[12+o]/u[15];var f,h=u[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];s.lightPosition[o]=p/h}this.triangleCount>0&&((f=this.triShader).bind(),f.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind());this.edgeCount>0&&this.lineWidth>0&&((f=this.lineShader).bind(),f.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind());this.pointCount>0&&((f=this.pointShader).bind(),f.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind());this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0&&((f=this.contourShader).bind(),f.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind())},k.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s,l={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255};((s=this.pickShader).bind(),s.uniforms=l,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0)&&((s=this.pointPickShader).bind(),s.uniforms=l,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},k.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=t.coord[0],s=t.coord[1];if(!this.pickVertex){var l=this.positions[r[0]],c=this.positions[r[1]],u=this.positions[r[2]],f=[(l[0]+c[0]+u[0])/3,(l[1]+c[1]+u[1])/3,(l[2]+c[2]+u[2])/3];return{_cellCenter:!0,position:[o,s],index:e,cell:r,cellId:e,intensity:this.intensity[e],dataCoordinate:f}}var h=g(i,[o*this.pixelRatio,this._resolution[1]-s*this.pixelRatio],this._model,this._view,this._projection,this._resolution);if(!h)return null;var p=h[2],d=0;for(a=0;a<r.length;++a)d+=p[a]*this.intensity[r[a]];return{position:h[1],index:r[h[0]],cell:r,cellId:e,intensity:d,dataCoordinate:this.positions[r[h[0]]]}},k.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},e.exports=function(t,e){1===arguments.length&&(t=(e=t).gl);var r=t.getExtension(\"OES_standard_derivatives\")||t.getExtension(\"MOZ_OES_standard_derivatives\")||t.getExtension(\"WEBKIT_OES_standard_derivatives\");if(!r)throw new Error(\"derivatives not supported\");var n=A(t),s=S(t),l=E(t),c=C(t),f=L(t),h=I(t),p=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));p.generateMipmap(),p.minFilter=t.LINEAR_MIPMAP_LINEAR,p.magFilter=t.LINEAR;var d=i(t),g=i(t),m=i(t),v=i(t),y=i(t),x=a(t,[{buffer:d,type:t.FLOAT,size:3},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:g,type:t.FLOAT,size:4},{buffer:m,type:t.FLOAT,size:2},{buffer:v,type:t.FLOAT,size:3}]),b=i(t),_=i(t),w=i(t),k=i(t),M=a(t,[{buffer:b,type:t.FLOAT,size:3},{buffer:k,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:_,type:t.FLOAT,size:4},{buffer:w,type:t.FLOAT,size:2}]),P=i(t),z=i(t),O=i(t),D=i(t),R=i(t),F=a(t,[{buffer:P,type:t.FLOAT,size:3},{buffer:R,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:z,type:t.FLOAT,size:4},{buffer:O,type:t.FLOAT,size:2},{buffer:D,type:t.FLOAT,size:1}]),B=i(t),N=a(t,[{buffer:B,type:t.FLOAT,size:3}]),j=new T(t,p,n,s,l,c,f,h,d,y,g,m,v,x,b,k,_,w,M,P,R,z,O,D,F,B,N);return j.update(e),j}},{\"./lib/closest-point\":307,\"./lib/shaders\":308,colormap:131,\"gl-buffer\":259,\"gl-mat4/invert\":293,\"gl-mat4/multiply\":295,\"gl-shader\":335,\"gl-texture2d\":353,\"gl-vao\":358,ndarray:495,normals:498,\"simplicial-complex-contour\":556,\"typedarray-pool\":595}],310:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],311:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[0,0,0,1,1,0,1,1]),s=i(e,a.boxVert,a.lineFrag);return new o(t,r,s)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"./shaders\");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawBox=(s=[0,0],l=[0,0],function(t,e,r,n,i){var a=this.plot,o=this.shader,c=a.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,o.uniforms.lo=s,o.uniforms.hi=l,o.uniforms.color=i,c.drawArrays(c.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":314,\"gl-buffer\":259,\"gl-shader\":335}],312:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),a=i(e,o.gridVert,o.gridFrag),l=i(e,o.tickVert,o.gridFrag);return new s(t,r,a,l)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"binary-search-bounds\"),o=t(\"./shaders\");function s(t,e,r,n){this.plot=t,this.vbo=e,this.shader=r,this.tickShader=n,this.ticks=[[],[]]}function l(t,e){return t-e}var c,u,f,h,p,d=s.prototype;d.draw=(c=[0,0],u=[0,0],f=[0,0],function(){for(var t=this.plot,e=this.vbo,r=this.shader,n=this.ticks,i=t.gl,a=t._tickBounds,o=t.dataBox,s=t.viewBox,l=t.gridLineWidth,h=t.gridLineColor,p=t.gridLineEnable,d=t.pixelRatio,g=0;g<2;++g){var m=a[g],v=a[g+2]-m,y=.5*(o[g+2]+o[g]),x=o[g+2]-o[g];u[g]=2*v/x,c[g]=2*(m-y)/x}r.bind(),e.bind(),r.attributes.dataCoord.pointer(),r.uniforms.dataShift=c,r.uniforms.dataScale=u;var b=0;for(g=0;g<2;++g){f[0]=f[1]=0,f[g]=1,r.uniforms.dataAxis=f,r.uniforms.lineWidth=l[g]/(s[g+2]-s[g])*d,r.uniforms.color=h[g];var _=6*n[g].length;p[g]&&_&&i.drawArrays(i.TRIANGLES,b,_),b+=_}}),d.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],i=[0,0],o=[0,0];return function(){for(var s=this.plot,c=this.vbo,u=this.tickShader,f=this.ticks,h=s.gl,p=s._tickBounds,d=s.dataBox,g=s.viewBox,m=s.pixelRatio,v=s.screenBox,y=v[2]-v[0],x=v[3]-v[1],b=g[2]-g[0],_=g[3]-g[1],w=0;w<2;++w){var T=p[w],k=p[w+2]-T,M=.5*(d[w+2]+d[w]),A=d[w+2]-d[w];e[w]=2*k/A,t[w]=2*(T-M)/A}e[0]*=b/y,t[0]*=b/y,e[1]*=_/x,t[1]*=_/x,u.bind(),c.bind(),u.attributes.dataCoord.pointer();var S=u.uniforms;S.dataShift=t,S.dataScale=e;var E=s.tickMarkLength,C=s.tickMarkWidth,L=s.tickMarkColor,I=6*f[0].length,P=Math.min(a.ge(f[0],(d[0]-p[0])/(p[2]-p[0]),l),f[0].length),z=Math.min(a.gt(f[0],(d[2]-p[0])/(p[2]-p[0]),l),f[0].length),O=0+6*P,D=6*Math.max(0,z-P),R=Math.min(a.ge(f[1],(d[1]-p[1])/(p[3]-p[1]),l),f[1].length),F=Math.min(a.gt(f[1],(d[3]-p[1])/(p[3]-p[1]),l),f[1].length),B=I+6*R,N=6*Math.max(0,F-R);i[0]=2*(g[0]-E[1])/y-1,i[1]=(g[3]+g[1])/x-1,o[0]=E[1]*m/y,o[1]=C[1]*m/x,N&&(S.color=L[1],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(g[2]+g[0])/y-1,i[1]=2*(g[1]-E[0])/x-1,o[0]=C[0]*m/y,o[1]=E[0]*m/x,D&&(S.color=L[0],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,O,D)),i[0]=2*(g[2]+E[3])/y-1,i[1]=(g[3]+g[1])/x-1,o[0]=E[3]*m/y,o[1]=C[3]*m/x,N&&(S.color=L[3],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(g[2]+g[0])/y-1,i[1]=2*(g[3]+E[2])/x-1,o[0]=C[2]*m/y,o[1]=E[2]*m/x,D&&(S.color=L[2],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,O,D))}}(),d.update=(h=[1,1,-1,-1,1,-1],p=[1,-1,1,1,-1,-1],function(t){for(var e=t.ticks,r=t.bounds,n=new Float32Array(18*(e[0].length+e[1].length)),i=(this.plot.zeroLineEnable,0),a=[[],[]],o=0;o<2;++o)for(var s=a[o],l=e[o],c=r[o],u=r[o+2],f=0;f<l.length;++f){var d=(l[f].x-c)/(u-c);s.push(d);for(var g=0;g<6;++g)n[i++]=d,n[i++]=h[g],n[i++]=p[g]}this.ticks=a,this.vbo.update(n)}),d.dispose=function(){this.vbo.dispose(),this.shader.dispose(),this.tickShader.dispose()}},{\"./shaders\":314,\"binary-search-bounds\":96,\"gl-buffer\":259,\"gl-shader\":335}],313:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[-1,-1,-1,1,1,-1,1,1]),s=i(e,a.lineVert,a.lineFrag);return new o(t,r,s)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"./shaders\");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawLine=(s=[0,0],l=[0,0],function(t,e,r,n,i,a){var o=this.plot,c=this.shader,u=o.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,c.uniforms.start=s,c.uniforms.end=l,c.uniforms.width=i*o.pixelRatio,c.uniforms.color=a,u.drawArrays(u.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":314,\"gl-buffer\":259,\"gl-shader\":335}],314:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=n([\"precision lowp float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = vec4(color.xyz * color.w, color.w);\\n}\\n\"]);e.exports={lineVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 start, end;\\nuniform float width;\\n\\nvec2 perp(vec2 v) {\\n  return vec2(v.y, -v.x);\\n}\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  vec2 delta = normalize(perp(start - end));\\n  vec2 offset = mix(start, end, 0.5 * (coord.y+1.0));\\n  gl_Position = vec4(screen(offset + 0.5 * width * delta * coord.x), 0, 1);\\n}\\n\"]),lineFrag:i,textVert:n([\"#define GLSLIFY 1\\nattribute vec3 textCoordinate;\\n\\nuniform vec2 dataScale, dataShift, dataAxis, screenOffset, textScale;\\nuniform float angle;\\n\\nvoid main() {\\n  float dataOffset  = textCoordinate.z;\\n  vec2 glyphOffset  = textCoordinate.xy;\\n  mat2 glyphMatrix = mat2(cos(angle), sin(angle), -sin(angle), cos(angle));\\n  vec2 screenCoordinate = dataAxis * (dataScale * dataOffset + dataShift) +\\n    glyphMatrix * glyphOffset * textScale + screenOffset;\\n  gl_Position = vec4(screenCoordinate, 0, 1);\\n}\\n\"]),textFrag:i,gridVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale;\\nuniform float lineWidth;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  pos += 10.0 * dataCoord.y * vec2(dataAxis.y, -dataAxis.x) + dataCoord.z * lineWidth;\\n  gl_Position = vec4(pos, 0, 1);\\n}\\n\"]),gridFrag:i,boxVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 lo, hi;\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  gl_Position = vec4(screen(mix(lo, hi, coord)), 0, 1);\\n}\\n\"]),tickVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale, screenOffset, tickScale;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  gl_Position = vec4(pos + tickScale*dataCoord.yz + screenOffset, 0, 1);\\n}\\n\"])}},{glslify:316}],315:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),a=i(e,s.textVert,s.textFrag);return new l(t,r,a)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"text-cache\"),o=t(\"binary-search-bounds\"),s=t(\"./shaders\");function l(t,e,r){this.plot=t,this.vbo=e,this.shader=r,this.tickOffset=[[],[]],this.tickX=[[],[]],this.labelOffset=[0,0],this.labelCount=[0,0]}var c,u,f,h,p,d,g=l.prototype;g.drawTicks=(c=[0,0],u=[0,0],f=[0,0],function(t){var e=this.plot,r=this.shader,n=this.tickX[t],i=this.tickOffset[t],a=e.gl,s=e.viewBox,l=e.dataBox,h=e.screenBox,p=e.pixelRatio,d=e.tickEnable,g=e.tickPad,m=e.tickColor,v=e.tickAngle,y=e.labelEnable,x=e.labelPad,b=e.labelColor,_=e.labelAngle,w=this.labelOffset[t],T=this.labelCount[t],k=o.lt(n,l[t]),M=o.le(n,l[t+2]);c[0]=c[1]=0,c[t]=1,u[t]=(s[2+t]+s[t])/(h[2+t]-h[t])-1;var A=2/h[2+(1^t)]-h[1^t];u[1^t]=A*s[1^t]-1,d[t]&&(u[1^t]-=A*p*g[t],k<M&&i[M]>i[k]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=m[t],r.uniforms.angle=v[t],a.drawArrays(a.TRIANGLES,i[k],i[M]-i[k]))),y[t]&&T&&(u[1^t]-=A*p*x[t],r.uniforms.dataAxis=f,r.uniforms.screenOffset=u,r.uniforms.color=b[t],r.uniforms.angle=_[t],a.drawArrays(a.TRIANGLES,w,T)),u[1^t]=A*s[2+(1^t)]-1,d[t+2]&&(u[1^t]+=A*p*g[t+2],k<M&&i[M]>i[k]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=m[t+2],r.uniforms.angle=v[t+2],a.drawArrays(a.TRIANGLES,i[k],i[M]-i[k]))),y[t+2]&&T&&(u[1^t]+=A*p*x[t+2],r.uniforms.dataAxis=f,r.uniforms.screenOffset=u,r.uniforms.color=b[t+2],r.uniforms.angle=_[t+2],a.drawArrays(a.TRIANGLES,w,T))}),g.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,c=r.pixelRatio;if(this.titleCount){for(var u=0;u<2;++u)e[u]=2*(o[u]*c-a[u])/(a[2+u]-a[u])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}}(),g.bind=(h=[0,0],p=[0,0],d=[0,0],function(){var t=this.plot,e=this.shader,r=t._tickBounds,n=t.dataBox,i=t.screenBox,a=t.viewBox;e.bind();for(var o=0;o<2;++o){var s=r[o],l=r[o+2]-s,c=.5*(n[o+2]+n[o]),u=n[o+2]-n[o],f=a[o],g=a[o+2]-f,m=i[o],v=i[o+2]-m;p[o]=2*l/u*g/v,h[o]=2*(s-c)/u*g/v}d[1]=2*t.pixelRatio/(i[3]-i[1]),d[0]=d[1]*(i[3]-i[1])/(i[2]-i[0]),e.uniforms.dataScale=p,e.uniforms.dataShift=h,e.uniforms.textScale=d,this.vbo.bind(),e.attributes.textCoordinate.pointer()}),g.update=function(t){var e,r,n,i,o,s=[],l=t.ticks,c=t.bounds;for(o=0;o<2;++o){var u=[Math.floor(s.length/3)],f=[-1/0],h=l[o];for(e=0;e<h.length;++e){var p=h[e],d=p.x,g=p.text,m=p.font||\"sans-serif\";i=p.fontSize||12;for(var v=1/(c[o+2]-c[o]),y=c[o],x=g.split(\"\\n\"),b=0;b<x.length;b++)for(n=a(m,x[b]).data,r=0;r<n.length;r+=2)s.push(n[r]*i,-n[r+1]*i-b*i*1.2,(d-y)*v);u.push(Math.floor(s.length/3)),f.push(d)}this.tickOffset[o]=u,this.tickX[o]=f}for(o=0;o<2;++o){for(this.labelOffset[o]=Math.floor(s.length/3),n=a(t.labelFont[o],t.labels[o],{textAlign:\"center\"}).data,i=t.labelSize[o],e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.labelCount[o]=Math.floor(s.length/3)-this.labelOffset[o]}for(this.titleOffset=Math.floor(s.length/3),n=a(t.titleFont,t.title).data,i=t.titleSize,e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.titleCount=Math.floor(s.length/3)-this.titleOffset,this.vbo.update(s)},g.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":314,\"binary-search-bounds\":96,\"gl-buffer\":259,\"gl-shader\":335,\"text-cache\":575}],316:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],317:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[e.drawingBufferWidth,e.drawingBufferHeight]),c=new l(e,r);return c.grid=i(c),c.text=a(c),c.line=o(c),c.box=s(c),c.update(t),c};var n=t(\"gl-select-static\"),i=t(\"./lib/grid\"),a=t(\"./lib/text\"),o=t(\"./lib/line\"),s=t(\"./lib/box\");function l(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-1/0,-1/0],this.static=!1,this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}var c=l.prototype;function u(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function f(t,e){return t.x-e.x}c.setDirty=function(){this.dirty=this.pickDirty=!0},c.setOverlayDirty=function(){this.dirty=!0},c.nextDepthValue=function(){return this._depthCounter++/65536},c.draw=function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,i=this.pixelRatio,a=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){if(this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),this.borderColor){t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var c=this.borderColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT)}t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var u=this.backgroundColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT),a.draw();var f=this.zeroLineEnable,h=this.zeroLineColor,p=this.zeroLineWidth;if(f[0]||f[1]){o.bind();for(var d=0;d<2;++d)if(f[d]&&n[d]<=0&&n[d+2]>=0){var g=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(g,e[1],g,e[3],p[d],h[d]):o.drawLine(e[0],g,e[2],g,p[d],h[d])}}for(d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var m=this.borderLineEnable,v=this.borderLineWidth,y=this.borderLineColor;for(m[1]&&o.drawLine(r[0],r[1]-.5*v[1]*i,r[0],r[3]+.5*v[3]*i,v[1],y[1]),m[0]&&o.drawLine(r[0]-.5*v[0]*i,r[1],r[2]+.5*v[2]*i,r[1],v[0],y[0]),m[3]&&o.drawLine(r[2],r[1]-.5*v[1]*i,r[2],r[3]+.5*v[3]*i,v[3],y[3]),m[2]&&o.drawLine(r[0]-.5*v[0]*i,r[3],r[2]+.5*v[2]*i,r[3],v[2],y[2]),s.bind(),d=0;d<2;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();var x=this.overlays;for(d=0;d<x.length;++d)x[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}},c.drawPick=function(){if(!this.static){var t=this.pickBuffer;this.gl,this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}},c.pick=function(t,e){if(!this.static){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),c=this.objects,u=0;u<c.length;++u){var f=c[u].pick(a,o,l);if(f)return f}return null}},c.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},c.setDataBox=function(t){var e=this.dataBox;(e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3])&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},c.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},c.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]);this.screenBox;this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,i=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/i,10,10/i]),this.borderColor=!1!==t.borderColor&&(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=u(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=u(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=u(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t)||!!t.titleEnable,this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=u(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=u(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=u(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var a=t.ticks||[[],[]],o=this._tickBounds;o[0]=o[1]=1/0,o[2]=o[3]=-1/0;for(var s=0;s<2;++s){var l=a[s].slice(0);0!==l.length&&(l.sort(f),o[s]=Math.min(o[s],l[0].x),o[s+2]=Math.max(o[s+2],l[l.length-1].x))}this.grid.update({bounds:o,ticks:a}),this.text.update({bounds:o,ticks:a,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\"}),this.static=!!t.static,this.setDirty()},c.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();this.objects.length=0;for(t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},c.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},c.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},c.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},c.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},{\"./lib/box\":311,\"./lib/grid\":312,\"./lib/line\":313,\"./lib/text\":315,\"gl-select-static\":334}],318:[function(t,e,r){\"use strict\";e.exports=function(t,e){t=t||document.body,e=e||{};var r=[.01,1/0];\"distanceLimits\"in e&&(r[0]=e.distanceLimits[0],r[1]=e.distanceLimits[1]);\"zoomMin\"in e&&(r[0]=e.zoomMin);\"zoomMax\"in e&&(r[1]=e.zoomMax);var c=i({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||\"orbit\",distanceLimits:r}),u=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],f=0,h=t.clientWidth,p=t.clientHeight,d={keyBindingMode:\"rotate\",enableWheel:!0,view:c,element:t,delay:e.delay||16,rotateSpeed:e.rotateSpeed||1,zoomSpeed:e.zoomSpeed||1,translateSpeed:e.translateSpeed||1,flipX:!!e.flipX,flipY:!!e.flipY,modes:c.modes,_ortho:e._ortho||e.projection&&\"orthographic\"===e.projection.type||!1,tick:function(){var e=n(),r=this.delay,i=e-2*r;c.idle(e-r),c.recalcMatrix(i),c.flush(e-(100+2*r));for(var a=!0,o=c.computedMatrix,s=0;s<16;++s)a=a&&u[s]===o[s],u[s]=o[s];var l=t.clientWidth===h&&t.clientHeight===p;return h=t.clientWidth,p=t.clientHeight,a?!l:(f=Math.exp(c.computedRadius[0]),!0)},lookAt:function(t,e,r){c.lookAt(c.lastT(),t,e,r)},rotate:function(t,e,r){c.rotate(c.lastT(),t,e,r)},pan:function(t,e,r){c.pan(c.lastT(),t,e,r)},translate:function(t,e,r){c.translate(c.lastT(),t,e,r)}};return Object.defineProperties(d,{matrix:{get:function(){return c.computedMatrix},set:function(t){return c.setMatrix(c.lastT(),t),c.computedMatrix},enumerable:!0},mode:{get:function(){return c.getMode()},set:function(t){var e=c.computedUp.slice(),r=c.computedEye.slice(),i=c.computedCenter.slice();if(c.setMode(t),\"turntable\"===t){var a=n();c._active.lookAt(a,r,i,e),c._active.lookAt(a+500,r,i,[0,0,1]),c._active.flush(a)}return c.getMode()},enumerable:!0},center:{get:function(){return c.computedCenter},set:function(t){return c.lookAt(c.lastT(),null,t),c.computedCenter},enumerable:!0},eye:{get:function(){return c.computedEye},set:function(t){return c.lookAt(c.lastT(),t),c.computedEye},enumerable:!0},up:{get:function(){return c.computedUp},set:function(t){return c.lookAt(c.lastT(),null,null,t),c.computedUp},enumerable:!0},distance:{get:function(){return f},set:function(t){return c.setDistance(c.lastT(),t),t},enumerable:!0},distanceLimits:{get:function(){return c.getDistanceLimits(r)},set:function(t){return c.setDistanceLimits(t),t},enumerable:!0}}),t.addEventListener(\"contextmenu\",(function(t){return t.preventDefault(),!1})),d._lastX=-1,d._lastY=-1,d._lastMods={shift:!1,control:!1,alt:!1,meta:!1},d.enableMouseListeners=function(){function e(e,r,i,a){var o=d.keyBindingMode;if(!1!==o){var s=\"rotate\"===o,l=\"pan\"===o,u=\"zoom\"===o,h=!!a.control,p=!!a.alt,g=!!a.shift,m=!!(1&e),v=!!(2&e),y=!!(4&e),x=1/t.clientHeight,b=x*(r-d._lastX),_=x*(i-d._lastY),w=d.flipX?1:-1,T=d.flipY?1:-1,k=Math.PI*d.rotateSpeed,M=n();if(-1!==d._lastX&&-1!==d._lastY&&((s&&m&&!h&&!p&&!g||m&&!h&&!p&&g)&&c.rotate(M,w*k*b,-T*k*_,0),(l&&m&&!h&&!p&&!g||v||m&&h&&!p&&!g)&&c.pan(M,-d.translateSpeed*b*f,d.translateSpeed*_*f,0),u&&m&&!h&&!p&&!g||y||m&&!h&&p&&!g)){var A=-d.zoomSpeed*_/window.innerHeight*(M-c.lastT())*100;c.pan(M,0,0,f*(Math.exp(A)-1))}return d._lastX=r,d._lastY=i,d._lastMods=a,!0}}d.mouseListener=a(t,e),t.addEventListener(\"touchstart\",(function(r){var n=s(r.changedTouches[0],t);e(0,n[0],n[1],d._lastMods),e(1,n[0],n[1],d._lastMods)}),!!l&&{passive:!0}),t.addEventListener(\"touchmove\",(function(r){var n=s(r.changedTouches[0],t);e(1,n[0],n[1],d._lastMods),r.preventDefault()}),!!l&&{passive:!1}),t.addEventListener(\"touchend\",(function(t){e(0,d._lastX,d._lastY,d._lastMods)}),!!l&&{passive:!0}),d.wheelListener=o(t,(function(t,e){if(!1!==d.keyBindingMode&&d.enableWheel){var r=d.flipX?1:-1,i=d.flipY?1:-1,a=n();if(Math.abs(t)>Math.abs(e))c.rotate(a,0,0,-t*r*Math.PI*d.rotateSpeed/window.innerWidth);else if(!d._ortho){var o=-d.zoomSpeed*i*e/window.innerHeight*(a-c.lastT())/20;c.pan(a,0,0,f*(Math.exp(o)-1))}}}),!0)},d.enableMouseListeners(),d};var n=t(\"right-now\"),i=t(\"3d-view\"),a=t(\"mouse-change\"),o=t(\"mouse-wheel\"),s=t(\"mouse-event-offset\"),l=t(\"has-passive-events\")},{\"3d-view\":54,\"has-passive-events\":441,\"mouse-change\":483,\"mouse-event-offset\":484,\"mouse-wheel\":486,\"right-now\":542}],319:[function(t,e,r){var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision mediump float;\\n#define GLSLIFY 1\\nattribute vec2 position;\\nvarying vec2 uv;\\nvoid main() {\\n  uv = position;\\n  gl_Position = vec4(position, 0, 1);\\n}\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D accumBuffer;\\nvarying vec2 uv;\\n\\nvoid main() {\\n  vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\\n  gl_FragColor = min(vec4(1,1,1,1), accum);\\n}\"]);e.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec2\"}])}},{\"gl-shader\":335,glslify:320}],320:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],321:[function(t,e,r){\"use strict\";var n=t(\"./camera.js\"),i=t(\"gl-axes3d\"),a=t(\"gl-axes3d/properties\"),o=t(\"gl-spikes3d\"),s=t(\"gl-select-static\"),l=t(\"gl-fbo\"),c=t(\"a-big-triangle\"),u=t(\"mouse-change\"),f=t(\"gl-mat4/perspective\"),h=t(\"gl-mat4/ortho\"),p=t(\"./lib/shader\"),d=t(\"is-mobile\")({tablet:!0,featureDetect:!0});function g(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function m(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}if(e>0){r=Math.round(Math.pow(10,e));return Math.ceil(t/r)*r}return Math.ceil(t)}function v(t){return\"boolean\"!=typeof t||t}e.exports={createScene:function(t){(t=t||{}).camera=t.camera||{};var e=t.canvas;if(!e){if(e=document.createElement(\"canvas\"),t.container)t.container.appendChild(e);else document.body.appendChild(e)}var r=t.gl;r||(t.glOptions&&(d=!!t.glOptions.preserveDrawingBuffer),r=function(t,e){var r=null;try{(r=t.getContext(\"webgl\",e))||(r=t.getContext(\"experimental-webgl\",e))}catch(t){return null}return r}(e,t.glOptions||{premultipliedAlpha:!0,antialias:!0,preserveDrawingBuffer:d}));if(!r)throw new Error(\"webgl not supported\");var y=t.bounds||[[-10,-10,-10],[10,10,10]],x=new g,b=l(r,r.drawingBufferWidth,r.drawingBufferHeight,{preferFloat:!d}),_=p(r),w=t.cameraObject&&!0===t.cameraObject._ortho||t.camera.projection&&\"orthographic\"===t.camera.projection.type||!1,T={eye:t.camera.eye||[2,0,0],center:t.camera.center||[0,0,0],up:t.camera.up||[0,1,0],zoomMin:t.camera.zoomMax||.1,zoomMax:t.camera.zoomMin||100,mode:t.camera.mode||\"turntable\",_ortho:w},k=t.axes||{},M=i(r,k);M.enable=!k.disable;var A=t.spikes||{},S=o(r,A),E=[],C=[],L=[],I=[],P=!0,z=!0,O=new Array(16),D=new Array(16),R={view:null,projection:O,model:D,_ortho:!1},F=(z=!0,[r.drawingBufferWidth,r.drawingBufferHeight]),B=t.cameraObject||n(e,T),N={gl:r,contextLost:!1,pixelRatio:t.pixelRatio||1,canvas:e,selection:x,camera:B,axes:M,axesPixels:null,spikes:S,bounds:y,objects:E,shape:F,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:v(t.autoResize),autoBounds:v(t.autoBounds),autoScale:!!t.autoScale,autoCenter:v(t.autoCenter),clipToBounds:v(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:R,oncontextloss:null,mouseListener:null,_stopped:!1,getAspectratio:function(){return{x:this.aspect[0],y:this.aspect[1],z:this.aspect[2]}},setAspectratio:function(t){this.aspect[0]=t.x,this.aspect[1]=t.y,this.aspect[2]=t.z,z=!0},setBounds:function(t,e){this.bounds[0][t]=e.min,this.bounds[1][t]=e.max},setClearColor:function(t){this.clearColor=t},clearRGBA:function(){this.gl.clearColor(this.clearColor[0],this.clearColor[1],this.clearColor[2],this.clearColor[3]),this.gl.clear(this.gl.COLOR_BUFFER_BIT|this.gl.DEPTH_BUFFER_BIT)}},j=[r.drawingBufferWidth/N.pixelRatio|0,r.drawingBufferHeight/N.pixelRatio|0];function U(){if(!N._stopped&&N.autoResize){var t=e.parentNode,r=1,n=1;t&&t!==document.body?(r=t.clientWidth,n=t.clientHeight):(r=window.innerWidth,n=window.innerHeight);var i=0|Math.ceil(r*N.pixelRatio),a=0|Math.ceil(n*N.pixelRatio);if(i!==e.width||a!==e.height){e.width=i,e.height=a;var o=e.style;o.position=o.position||\"absolute\",o.left=\"0px\",o.top=\"0px\",o.width=r+\"px\",o.height=n+\"px\",P=!0}}}N.autoResize&&U();function V(){for(var t=E.length,e=I.length,n=0;n<e;++n)L[n]=0;t:for(n=0;n<t;++n){var i=E[n],a=i.pickSlots;if(a){for(var o=0;o<e;++o)if(L[o]+a<255){C[n]=o,i.setPickBase(L[o]+1),L[o]+=a;continue t}var l=s(r,F);C[n]=e,I.push(l),L.push(a),i.setPickBase(1),e+=1}else C[n]=-1}for(;e>0&&0===L[e-1];)L.pop(),I.pop().dispose()}function q(){if(N.contextLost)return!0;r.isContextLost()&&(N.contextLost=!0,N.mouseListener.enabled=!1,N.selection.object=null,N.oncontextloss&&N.oncontextloss())}window.addEventListener(\"resize\",U),N.update=function(t){N._stopped||(t=t||{},P=!0,z=!0)},N.add=function(t){N._stopped||(t.axes=M,E.push(t),C.push(-1),P=!0,z=!0,V())},N.remove=function(t){if(!N._stopped){var e=E.indexOf(t);e<0||(E.splice(e,1),C.pop(),P=!0,z=!0,V())}},N.dispose=function(){if(!N._stopped&&(N._stopped=!0,window.removeEventListener(\"resize\",U),e.removeEventListener(\"webglcontextlost\",q),N.mouseListener.enabled=!1,!N.contextLost)){M.dispose(),S.dispose();for(var t=0;t<E.length;++t)E[t].dispose();b.dispose();for(t=0;t<I.length;++t)I[t].dispose();_.dispose(),r=null,M=null,S=null,E=[]}},N._mouseRotating=!1,N._prevButtons=0,N.enableMouseListeners=function(){N.mouseListener=u(e,(function(t,e,r){if(!N._stopped){var n=I.length,i=E.length,a=x.object;x.distance=1/0,x.mouse[0]=e,x.mouse[1]=r,x.object=null,x.screen=null,x.dataCoordinate=x.dataPosition=null;var o=!1;if(t&&N._prevButtons)N._mouseRotating=!0;else{N._mouseRotating&&(z=!0),N._mouseRotating=!1;for(var s=0;s<n;++s){var l=I[s].query(e,j[1]-r-1,N.pickRadius);if(l){if(l.distance>x.distance)continue;for(var c=0;c<i;++c){var u=E[c];if(C[c]===s){var f=u.pick(l);f&&(x.buttons=t,x.screen=l.coord,x.distance=l.distance,x.object=u,x.index=f.distance,x.dataPosition=f.position,x.dataCoordinate=f.dataCoordinate,x.data=f,o=!0)}}}}}a&&a!==x.object&&(a.highlight&&a.highlight(null),P=!0),x.object&&(x.object.highlight&&x.object.highlight(x.data),P=!0),(o=o||x.object!==a)&&N.onselect&&N.onselect(x),1&t&&!(1&N._prevButtons)&&N.onclick&&N.onclick(x),N._prevButtons=t}}))},e.addEventListener(\"webglcontextlost\",q);var H=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],G=[H[0].slice(),H[1].slice()];function Y(){if(!q()){U();var t=N.camera.tick();R.view=N.camera.matrix,P=P||t,z=z||t,M.pixelRatio=N.pixelRatio,S.pixelRatio=N.pixelRatio;var e=E.length,n=H[0],i=H[1];n[0]=n[1]=n[2]=1/0,i[0]=i[1]=i[2]=-1/0;for(var o=0;o<e;++o){(L=E[o]).pixelRatio=N.pixelRatio,L.axes=N.axes,P=P||!!L.dirty,z=z||!!L.dirty;var s=L.bounds;if(s)for(var l=s[0],u=s[1],p=0;p<3;++p)n[p]=Math.min(n[p],l[p]),i[p]=Math.max(i[p],u[p])}var d=N.bounds;if(N.autoBounds)for(p=0;p<3;++p){if(i[p]<n[p])n[p]=-1,i[p]=1;else{n[p]===i[p]&&(n[p]-=1,i[p]+=1);var g=.05*(i[p]-n[p]);n[p]=n[p]-g,i[p]=i[p]+g}d[0][p]=n[p],d[1][p]=i[p]}var v=!1;for(p=0;p<3;++p)v=v||G[0][p]!==d[0][p]||G[1][p]!==d[1][p],G[0][p]=d[0][p],G[1][p]=d[1][p];if(z=z||v,P=P||v){if(v){var y=[0,0,0];for(o=0;o<3;++o)y[o]=m((d[1][o]-d[0][o])/10);M.autoTicks?M.update({bounds:d,tickSpacing:y}):M.update({bounds:d})}var T=r.drawingBufferWidth,k=r.drawingBufferHeight;F[0]=T,F[1]=k,j[0]=0|Math.max(T/N.pixelRatio,1),j[1]=0|Math.max(k/N.pixelRatio,1),function(t,e){var r=t.bounds,n=t.cameraParams,i=n.projection,a=n.model,o=t.gl.drawingBufferWidth,s=t.gl.drawingBufferHeight,l=t.zNear,c=t.zFar,u=t.fovy,p=o/s;e?(h(i,-p,p,-1,1,l,c),n._ortho=!0):(f(i,u,p,l,c),n._ortho=!1);for(var d=0;d<16;++d)a[d]=0;a[15]=1;var g=0;for(d=0;d<3;++d)g=Math.max(g,r[1][d]-r[0][d]);for(d=0;d<3;++d)t.autoScale?a[5*d]=t.aspect[d]/(r[1][d]-r[0][d]):a[5*d]=1/g,t.autoCenter&&(a[12+d]=.5*-a[5*d]*(r[0][d]+r[1][d]))}(N,w);for(o=0;o<e;++o){(L=E[o]).axesBounds=d,N.clipToBounds&&(L.clipBounds=d)}x.object&&(N.snapToData?S.position=x.dataCoordinate:S.position=x.dataPosition,S.bounds=d),z&&(z=!1,function(){if(!q()){r.colorMask(!0,!0,!0,!0),r.depthMask(!0),r.disable(r.BLEND),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL);for(var t=E.length,e=I.length,n=0;n<e;++n){var i=I[n];i.shape=j,i.begin();for(var a=0;a<t;++a)if(C[a]===n){var o=E[a];o.drawPick&&(o.pixelRatio=1,o.drawPick(R))}i.end()}}}()),N.axesPixels=a(N.axes,R,T,k),N.onrender&&N.onrender(),r.bindFramebuffer(r.FRAMEBUFFER,null),r.viewport(0,0,T,k),N.clearRGBA(),r.depthMask(!0),r.colorMask(!0,!0,!0,!0),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL),r.disable(r.BLEND),r.disable(r.CULL_FACE);var A=!1;M.enable&&(A=A||M.isTransparent(),M.draw(R)),S.axes=M,x.object&&S.draw(R),r.disable(r.CULL_FACE);for(o=0;o<e;++o){(L=E[o]).axes=M,L.pixelRatio=N.pixelRatio,L.isOpaque&&L.isOpaque()&&L.draw(R),L.isTransparent&&L.isTransparent()&&(A=!0)}if(A){b.shape=F,b.bind(),r.clear(r.DEPTH_BUFFER_BIT),r.colorMask(!1,!1,!1,!1),r.depthMask(!0),r.depthFunc(r.LESS),M.enable&&M.isTransparent()&&M.drawTransparent(R);for(o=0;o<e;++o){(L=E[o]).isOpaque&&L.isOpaque()&&L.draw(R)}r.enable(r.BLEND),r.blendEquation(r.FUNC_ADD),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.colorMask(!0,!0,!0,!0),r.depthMask(!1),r.clearColor(0,0,0,0),r.clear(r.COLOR_BUFFER_BIT),M.isTransparent()&&M.drawTransparent(R);for(o=0;o<e;++o){var L;(L=E[o]).isTransparent&&L.isTransparent()&&L.drawTransparent(R)}r.bindFramebuffer(r.FRAMEBUFFER,null),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.disable(r.DEPTH_TEST),_.bind(),b.color[0].bind(0),_.uniforms.accumBuffer=0,c(r),r.disable(r.BLEND)}P=!1;for(o=0;o<e;++o)E[o].dirty=!1}}}return N.enableMouseListeners(),function t(){if(N._stopped||N.contextLost)return;Y(),requestAnimationFrame(t)}(),N.redraw=function(){N._stopped||(P=!0,Y())},N},createCamera:n}},{\"./camera.js\":318,\"./lib/shader\":319,\"a-big-triangle\":64,\"gl-axes3d\":250,\"gl-axes3d/properties\":258,\"gl-fbo\":269,\"gl-mat4/ortho\":296,\"gl-mat4/perspective\":297,\"gl-select-static\":334,\"gl-spikes3d\":345,\"is-mobile\":467,\"mouse-change\":483}],322:[function(t,e,r){var n=t(\"glslify\");r.pointVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform float pointCloud;\\n\\nhighp float rand(vec2 co) {\\n  highp float a = 12.9898;\\n  highp float b = 78.233;\\n  highp float c = 43758.5453;\\n  highp float d = dot(co.xy, vec2(a, b));\\n  highp float e = mod(d, 3.14);\\n  return fract(sin(e) * c);\\n}\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n    // if we don't jitter the point size a bit, overall point cloud\\n    // saturation 'jumps' on zooming, which is disturbing and confusing\\n  gl_PointSize = pointSize * ((19.5 + rand(position)) / 20.0);\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    // get the same square surface as circle would be\\n    gl_PointSize *= 0.886;\\n  }\\n}\"]),r.pointFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\nuniform float pointCloud;\\n\\nvoid main() {\\n  float radius;\\n  vec4 baseColor;\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    if(centerFraction == 1.0) {\\n      gl_FragColor = color;\\n    } else {\\n      gl_FragColor = mix(borderColor, color, centerFraction);\\n    }\\n  } else {\\n    radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n    if(radius > 1.0) {\\n      discard;\\n    }\\n    baseColor = mix(borderColor, color, step(radius, centerFraction));\\n    gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\\n  }\\n}\\n\"]),r.pickVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n\\n  vec4 id = pickId + pickOffset;\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  fragId = id;\\n}\\n\"]),r.pickFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  gl_FragColor = fragId / 255.0;\\n}\\n\"])},{glslify:323}],323:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],324:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"typedarray-pool\"),o=t(\"./lib/shader\");function s(t,e,r,n,i){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=i,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}e.exports=function(t,e){var r=t.gl,a=i(r),l=i(r),c=n(r,o.pointVertex,o.pointFragment),u=n(r,o.pickVertex,o.pickFragment),f=new s(t,a,l,c,u);return f.update(e),t.addObject(f),f};var l,c,u=s.prototype;u.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},u.update=function(t){var e;function r(e,r){return e in t?t[e]:r}t=t||{},this.sizeMin=r(\"sizeMin\",.5),this.sizeMax=r(\"sizeMax\",20),this.color=r(\"color\",[1,0,0,1]).slice(),this.areaRatio=r(\"areaRatio\",1),this.borderColor=r(\"borderColor\",[0,0,0,1]).slice(),this.blend=r(\"blend\",!1);var n=t.positions.length>>>1,i=t.positions instanceof Float32Array,o=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,s=t.positions,l=i?s:a.mallocFloat32(s.length),c=o?t.idToIndex:a.mallocInt32(n);if(i||l.set(s),!o)for(l.set(s),e=0;e<n;e++)c[e]=e;this.points=s,this.offsetBuffer.update(l),this.pickBuffer.update(c),i||a.free(l),o||a.free(c),this.pointCount=n,this.pickOffset=0},u.unifiedDraw=(l=[1,0,0,0,1,0,0,0,1],c=[0,0,0,0],function(t){var e=void 0!==t,r=e?this.pickShader:this.shader,n=this.plot.gl,i=this.plot.dataBox;if(0===this.pointCount)return t;var a=i[2]-i[0],o=i[3]-i[1],s=function(t,e){var r,n=0,i=t.length>>>1;for(r=0;r<i;r++){var a=t[2*r],o=t[2*r+1];a>=e[0]&&a<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}(this.points,i),u=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(s,.33333)));l[0]=2/a,l[4]=2/o,l[6]=-2*i[0]/a-1,l[7]=-2*i[1]/o-1,this.offsetBuffer.bind(),r.bind(),r.attributes.position.pointer(),r.uniforms.matrix=l,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointCloud=u<5,r.uniforms.pointSize=u,r.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),e&&(c[0]=255&t,c[1]=t>>8&255,c[2]=t>>16&255,c[3]=t>>24&255,this.pickBuffer.bind(),r.attributes.pickId.pointer(n.UNSIGNED_BYTE),r.uniforms.pickOffset=c,this.pickOffset=t);var f=n.getParameter(n.BLEND),h=n.getParameter(n.DITHER);return f&&!this.blend&&n.disable(n.BLEND),h&&n.disable(n.DITHER),n.drawArrays(n.POINTS,0,this.pointCount),f&&!this.blend&&n.enable(n.BLEND),h&&n.enable(n.DITHER),t+this.pointCount}),u.draw=u.unifiedDraw,u.drawPick=u.unifiedDraw,u.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(r<n||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},{\"./lib/shader\":322,\"gl-buffer\":259,\"gl-shader\":335,\"typedarray-pool\":595}],325:[function(t,e,r){e.exports=function(t,e,r,n){var i,a,o,s,l,c=e[0],u=e[1],f=e[2],h=e[3],p=r[0],d=r[1],g=r[2],m=r[3];(a=c*p+u*d+f*g+h*m)<0&&(a=-a,p=-p,d=-d,g=-g,m=-m);1-a>1e-6?(i=Math.acos(a),o=Math.sin(i),s=Math.sin((1-n)*i)/o,l=Math.sin(n*i)/o):(s=1-n,l=n);return t[0]=s*c+l*p,t[1]=s*u+l*d,t[2]=s*f+l*g,t[3]=s*h+l*m,t}},{}],326:[function(t,e,r){\"use strict\";e.exports=function(t){return t||0===t?t.toString():\"\"}},{}],327:[function(t,e,r){\"use strict\";var n=t(\"vectorize-text\");e.exports=function(t,e,r){var a=i[e];a||(a=i[e]={});if(t in a)return a[t];var o={textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e,lineSpacing:1.25,styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},triangles:!0},s=n(t,o);o.triangles=!1;var l,c,u=n(t,o);if(r&&1!==r){for(l=0;l<s.positions.length;++l)for(c=0;c<s.positions[l].length;++c)s.positions[l][c]/=r;for(l=0;l<u.positions.length;++l)for(c=0;c<u.positions[l].length;++c)u.positions[l][c]/=r}var f=[[1/0,1/0],[-1/0,-1/0]],h=u.positions.length;for(l=0;l<h;++l){var p=u.positions[l];for(c=0;c<2;++c)f[0][c]=Math.min(f[0][c],p[c]),f[1][c]=Math.max(f[1][c],p[c])}return a[t]=[s,u,f]};var i={}},{\"vectorize-text\":600}],328:[function(t,e,r){var n=t(\"gl-shader\"),i=t(\"glslify\"),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = 1.0;\\n    if(distance(highlightId, id) < 0.0001) {\\n      scale = highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1);\\n    vec4 viewPosition = view * worldPosition;\\n    viewPosition = viewPosition / viewPosition.w;\\n    vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = pixelRatio;\\n    if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n      scale *= highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1.0);\\n    vec4 viewPosition = view * worldPosition;\\n    vec4 clipPosition = projection * viewPosition;\\n    clipPosition /= clipPosition.w;\\n\\n    gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float lscale = pixelRatio * scale;\\n    if(distance(highlightId, id) < 0.0001) {\\n      lscale *= highlightScale;\\n    }\\n\\n    vec4 clipCenter   = projection * view * model * vec4(position, 1);\\n    vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n    vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = dataPosition;\\n  }\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (\\n    outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) ||\\n    interpColor.a * opacity == 0.\\n  ) discard;\\n  gl_FragColor = interpColor * opacity;\\n}\\n\"]),c=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard;\\n\\n  gl_FragColor = vec4(pickGroup, pickId.bgr);\\n}\"]),u=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:u},h={vertex:o,fragment:l,attributes:u},p={vertex:s,fragment:l,attributes:u},d={vertex:a,fragment:c,attributes:u},g={vertex:o,fragment:c,attributes:u},m={vertex:s,fragment:c,attributes:u};function v(t,e){var r=n(t,e),i=r.attributes;return i.position.location=0,i.color.location=1,i.glyph.location=2,i.id.location=3,r}r.createPerspective=function(t){return v(t,f)},r.createOrtho=function(t){return v(t,h)},r.createProject=function(t){return v(t,p)},r.createPickPerspective=function(t){return v(t,d)},r.createPickOrtho=function(t){return v(t,g)},r.createPickProject=function(t){return v(t,m)}},{\"gl-shader\":335,glslify:329}],329:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],330:[function(t,e,r){\"use strict\";var n=t(\"is-string-blank\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"typedarray-pool\"),s=t(\"gl-mat4/multiply\"),l=t(\"./lib/shaders\"),c=t(\"./lib/glyphs\"),u=t(\"./lib/get-simple-string\"),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function p(t,e,r,n){return h(n,n),h(n,n),h(n,n)}function d(t,e){this.index=t,this.dataCoordinate=this.position=e}function g(t){return!0===t||t>1?1:t}function m(t,e,r,n,i,a,o,s,l,c,u,f){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=a,this.glyphBuffer=o,this.idBuffer=s,this.vao=l,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.hasAlpha=!1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.projectHasAlpha=!1,this.pickId=0,this.pickPerspectiveShader=c,this.pickOrthoShader=u,this.pickProjectShader=f,this.points=[],this._selectResult=new d(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.dirty=!0}e.exports=function(t){var e=t.gl,r=l.createPerspective(e),n=l.createOrtho(e),o=l.createProject(e),s=l.createPickPerspective(e),c=l.createPickOrtho(e),u=l.createPickProject(e),f=i(e),h=i(e),p=i(e),d=i(e),g=a(e,[{buffer:f,size:3,type:e.FLOAT},{buffer:h,size:4,type:e.FLOAT},{buffer:p,size:2,type:e.FLOAT},{buffer:d,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),v=new m(e,r,n,o,f,h,p,d,g,s,c,u);return v.update(t),v};var v=m.prototype;v.pickSlots=1,v.setPickBase=function(t){this.pickId=t},v.isTransparent=function(){if(this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectHasAlpha)return!0;return!1},v.isOpaque=function(){if(!this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&!this.projectHasAlpha)return!0;return!1};var y=[0,0],x=[0,0,0],b=[0,0,0],_=[0,0,0,1],w=[0,0,0,1],T=f.slice(),k=[0,0,0],M=[[0,0,0],[0,0,0]];function A(t){return t[0]=t[1]=t[2]=0,t}function S(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function E(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}function C(t,e,r,n){var i,a=e.axesProject,o=e.gl,l=t.uniforms,c=r.model||f,u=r.view||f,h=r.projection||f,d=e.axesBounds,g=function(t){for(var e=M,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}(e.clipBounds);i=e.axes&&e.axes.lastCubeProps?e.axes.lastCubeProps.axis:[1,1,1],y[0]=2/o.drawingBufferWidth,y[1]=2/o.drawingBufferHeight,t.bind(),l.view=u,l.projection=h,l.screenSize=y,l.highlightId=e.highlightId,l.highlightScale=e.highlightScale,l.clipBounds=g,l.pickGroup=e.pickId/255,l.pixelRatio=n;for(var m=0;m<3;++m)if(a[m]){l.scale=e.projectScale[m],l.opacity=e.projectOpacity[m];for(var v=T,C=0;C<16;++C)v[C]=0;for(C=0;C<4;++C)v[5*C]=1;v[5*m]=0,i[m]<0?v[12+m]=d[0][m]:v[12+m]=d[1][m],s(v,c,v),l.model=v;var L=(m+1)%3,I=(m+2)%3,P=A(x),z=A(b);P[L]=1,z[I]=1;var O=p(0,0,0,S(_,P)),D=p(0,0,0,S(w,z));if(Math.abs(O[1])>Math.abs(D[1])){var R=O;O=D,D=R,R=P,P=z,z=R;var F=L;L=I,I=F}O[0]<0&&(P[L]=-1),D[1]>0&&(z[I]=-1);var B=0,N=0;for(C=0;C<4;++C)B+=Math.pow(c[4*L+C],2),N+=Math.pow(c[4*I+C],2);P[L]/=Math.sqrt(B),z[I]/=Math.sqrt(N),l.axes[0]=P,l.axes[1]=z,l.fragClipBounds[0]=E(k,g[0],m,-1e8),l.fragClipBounds[1]=E(k,g[1],m,1e8),e.vao.bind(),e.vao.draw(o.TRIANGLES,e.vertexCount),e.lineWidth>0&&(o.lineWidth(e.lineWidth*n),e.vao.draw(o.LINES,e.lineVertexCount,e.vertexCount)),e.vao.unbind()}}var L=[[-1e8,-1e8,-1e8],[1e8,1e8,1e8]];function I(t,e,r,n,i,a,o){var s=r.gl;if((a===r.projectHasAlpha||o)&&C(e,r,n,i),a===r.hasAlpha||o){t.bind();var l=t.uniforms;l.model=n.model||f,l.view=n.view||f,l.projection=n.projection||f,y[0]=2/s.drawingBufferWidth,y[1]=2/s.drawingBufferHeight,l.screenSize=y,l.highlightId=r.highlightId,l.highlightScale=r.highlightScale,l.fragClipBounds=L,l.clipBounds=r.axes.bounds,l.opacity=r.opacity,l.pickGroup=r.pickId/255,l.pixelRatio=i,r.vao.bind(),r.vao.draw(s.TRIANGLES,r.vertexCount),r.lineWidth>0&&(s.lineWidth(r.lineWidth*i),r.vao.draw(s.LINES,r.lineVertexCount,r.vertexCount)),r.vao.unbind()}}function P(t,e,r,i){var a;a=Array.isArray(t)?e<t.length?t[e]:void 0:t,a=u(a);var o=!0;n(a)&&(a=\"\\u25bc\",o=!1);var s=c(a,r,i);return{mesh:s[0],lines:s[1],bounds:s[2],visible:o}}v.draw=function(t){I(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!1,!1)},v.drawTransparent=function(t){I(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!0,!1)},v.drawPick=function(t){I(this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader,this.pickProjectShader,this,t,1,!0,!0)},v.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||e<0)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;i<3;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},v.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},v.update=function(t){if(\"perspective\"in(t=t||{})&&(this.useOrtho=!t.perspective),\"orthographic\"in t&&(this.useOrtho=!!t.orthographic),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"project\"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if(\"projectScale\"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(this.projectHasAlpha=!1,\"projectOpacity\"in t){if(Array.isArray(t.projectOpacity))this.projectOpacity=t.projectOpacity.slice();else{r=+t.projectOpacity;this.projectOpacity=[r,r,r]}for(var n=0;n<3;++n)this.projectOpacity[n]=g(this.projectOpacity[n]),this.projectOpacity[n]<1&&(this.projectHasAlpha=!0)}this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=g(t.opacity),this.opacity<1&&(this.hasAlpha=!0)),this.dirty=!0;var i,a,s=t.position,l=t.font||\"normal\",c=t.alignment||[0,0];if(2===c.length)i=c[0],a=c[1];else{i=[],a=[];for(n=0;n<c.length;++n)i[n]=c[n][0],a[n]=c[n][1]}var u=[1/0,1/0,1/0],f=[-1/0,-1/0,-1/0],h=t.glyph,p=t.color,d=t.size,m=t.angle,v=t.lineColor,y=-1,x=0,b=0,_=0;if(s.length){_=s.length;t:for(n=0;n<_;++n){for(var w=s[n],T=0;T<3;++T)if(isNaN(w[T])||!isFinite(w[T]))continue t;var k=(N=P(h,n,l,this.pixelRatio)).mesh,M=N.lines,A=N.bounds;x+=3*k.cells.length,b+=2*M.edges.length}}var S=x+b,E=o.mallocFloat(3*S),C=o.mallocFloat(4*S),L=o.mallocFloat(2*S),I=o.mallocUint32(S);if(S>0){var z=0,O=x,D=[0,0,0,1],R=[0,0,0,1],F=Array.isArray(p)&&Array.isArray(p[0]),B=Array.isArray(v)&&Array.isArray(v[0]);t:for(n=0;n<_;++n){y+=1;for(w=s[n],T=0;T<3;++T){if(isNaN(w[T])||!isFinite(w[T]))continue t;f[T]=Math.max(f[T],w[T]),u[T]=Math.min(u[T],w[T])}k=(N=P(h,n,l,this.pixelRatio)).mesh,M=N.lines,A=N.bounds;var N,j=N.visible;if(j)if(Array.isArray(p)){if(3===(U=F?n<p.length?p[n]:[0,0,0,0]:p).length){for(T=0;T<3;++T)D[T]=U[T];D[3]=1}else if(4===U.length){for(T=0;T<4;++T)D[T]=U[T];!this.hasAlpha&&U[3]<1&&(this.hasAlpha=!0)}}else D[0]=D[1]=D[2]=0,D[3]=1;else D=[1,1,1,0];if(j)if(Array.isArray(v)){var U;if(3===(U=B?n<v.length?v[n]:[0,0,0,0]:v).length){for(T=0;T<3;++T)R[T]=U[T];R[T]=1}else if(4===U.length){for(T=0;T<4;++T)R[T]=U[T];!this.hasAlpha&&U[3]<1&&(this.hasAlpha=!0)}}else R[0]=R[1]=R[2]=0,R[3]=1;else R=[1,1,1,0];var V=.5;j?Array.isArray(d)?V=n<d.length?+d[n]:12:d?V=+d:this.useOrtho&&(V=12):V=0;var q=0;Array.isArray(m)?q=n<m.length?+m[n]:0:m&&(q=+m);var H=Math.cos(q),G=Math.sin(q);for(w=s[n],T=0;T<3;++T)f[T]=Math.max(f[T],w[T]),u[T]=Math.min(u[T],w[T]);var Y=i,W=a;Y=0;Array.isArray(i)?Y=n<i.length?i[n]:0:i&&(Y=i);W=0;Array.isArray(a)?W=n<a.length?a[n]:0:a&&(W=a);var X=[Y*=Y>0?1-A[0][0]:Y<0?1+A[1][0]:1,W*=W>0?1-A[0][1]:W<0?1+A[1][1]:1],Z=k.cells||[],J=k.positions||[];for(T=0;T<Z.length;++T)for(var K=Z[T],Q=0;Q<3;++Q){for(var $=0;$<3;++$)E[3*z+$]=w[$];for($=0;$<4;++$)C[4*z+$]=D[$];I[z]=y;var tt=J[K[Q]];L[2*z]=V*(H*tt[0]-G*tt[1]+X[0]),L[2*z+1]=V*(G*tt[0]+H*tt[1]+X[1]),z+=1}for(Z=M.edges,J=M.positions,T=0;T<Z.length;++T)for(K=Z[T],Q=0;Q<2;++Q){for($=0;$<3;++$)E[3*O+$]=w[$];for($=0;$<4;++$)C[4*O+$]=R[$];I[O]=y;tt=J[K[Q]];L[2*O]=V*(H*tt[0]-G*tt[1]+X[0]),L[2*O+1]=V*(G*tt[0]+H*tt[1]+X[1]),O+=1}}}this.bounds=[u,f],this.points=s,this.pointCount=s.length,this.vertexCount=x,this.lineVertexCount=b,this.pointBuffer.update(E),this.colorBuffer.update(C),this.glyphBuffer.update(L),this.idBuffer.update(I),o.free(E),o.free(C),o.free(L),o.free(I)},v.dispose=function(){this.shader.dispose(),this.orthoShader.dispose(),this.pickPerspectiveShader.dispose(),this.pickOrthoShader.dispose(),this.vao.dispose(),this.pointBuffer.dispose(),this.colorBuffer.dispose(),this.glyphBuffer.dispose(),this.idBuffer.dispose()}},{\"./lib/get-simple-string\":326,\"./lib/glyphs\":327,\"./lib/shaders\":328,\"gl-buffer\":259,\"gl-mat4/multiply\":295,\"gl-vao\":358,\"is-string-blank\":470,\"typedarray-pool\":595}],331:[function(t,e,r){\"use strict\";var n=t(\"glslify\");r.boxVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 vertex;\\n\\nuniform vec2 cornerA, cornerB;\\n\\nvoid main() {\\n  gl_Position = vec4(mix(cornerA, cornerB, vertex), 0, 1);\\n}\\n\"]),r.boxFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = color;\\n}\\n\"])},{glslify:332}],332:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],333:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"./lib/shaders\");function o(t,e,r){this.plot=t,this.boxBuffer=e,this.boxShader=r,this.enabled=!0,this.selectBox=[1/0,1/0,-1/0,-1/0],this.borderColor=[0,0,0,1],this.innerFill=!1,this.innerColor=[0,0,0,.25],this.outerFill=!0,this.outerColor=[0,0,0,.5],this.borderWidth=10}e.exports=function(t,e){var r=t.gl,s=i(r,[0,0,0,1,1,0,1,1]),l=n(r,a.boxVertex,a.boxFragment),c=new o(t,s,l);return c.update(e),t.addOverlay(c),c};var s=o.prototype;s.draw=function(){if(this.enabled){var t=this.plot,e=this.selectBox,r=this.borderWidth,n=(this.innerFill,this.innerColor),i=(this.outerFill,this.outerColor),a=this.borderColor,o=t.box,s=t.screenBox,l=t.dataBox,c=t.viewBox,u=t.pixelRatio,f=(e[0]-l[0])*(c[2]-c[0])/(l[2]-l[0])+c[0],h=(e[1]-l[1])*(c[3]-c[1])/(l[3]-l[1])+c[1],p=(e[2]-l[0])*(c[2]-c[0])/(l[2]-l[0])+c[0],d=(e[3]-l[1])*(c[3]-c[1])/(l[3]-l[1])+c[1];if(f=Math.max(f,c[0]),h=Math.max(h,c[1]),p=Math.min(p,c[2]),d=Math.min(d,c[3]),!(p<f||d<h)){o.bind();var g=s[2]-s[0],m=s[3]-s[1];if(this.outerFill&&(o.drawBox(0,0,g,h,i),o.drawBox(0,h,f,d,i),o.drawBox(0,d,g,m,i),o.drawBox(p,h,g,d,i)),this.innerFill&&o.drawBox(f,h,p,d,n),r>0){var v=r*u;o.drawBox(f-v,h-v,p+v,h+v,a),o.drawBox(f-v,d-v,p+v,d+v,a),o.drawBox(f-v,h-v,f+v,d+v,a),o.drawBox(p-v,h-v,p+v,d+v,a)}}}},s.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},s.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},{\"./lib/shaders\":331,\"gl-buffer\":259,\"gl-shader\":335}],334:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=e[0],a=e[1],o=n(t,r,a,{}),s=i.mallocUint8(r*a*4);return new l(t,o,s)};var n=t(\"gl-fbo\"),i=t(\"typedarray-pool\"),a=t(\"ndarray\"),o=t(\"bit-twiddle\").nextPow2;function s(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function 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a=[t.id,e.id,r.join(\":\"),i.join(\":\")].join(\"@\"),o=this.programs[a];return o&&this.gl.isProgram(o)||(this.programs[a]=o=function(t,e,r,i,a){var o=t.createProgram();t.attachShader(o,e),t.attachShader(o,r);for(var s=0;s<i.length;++s)t.bindAttribLocation(o,a[s],i[s]);if(t.linkProgram(o),!t.getProgramParameter(o,t.LINK_STATUS)){var l=t.getProgramInfoLog(o);throw new n(l,\"Error linking program: \"+l)}return o}(this.gl,t.shader,e.shader,r,i),t.programs.push(a),e.programs.push(a)),o}},{\"./GLError\":336,\"gl-format-compiler-error\":270,\"weakmap-shim\":605}],342:[function(t,e,r){\"use strict\";function n(t){this.plot=t,this.enable=[!0,!0,!1,!1],this.width=[1,1,1,1],this.color=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.center=[1/0,1/0]}e.exports=function(t,e){var r=new n(t);return r.update(e),t.addOverlay(r),r};var i=n.prototype;i.update=function(t){t=t||{},this.enable=(t.enable||[!0,!0,!1,!1]).slice(),this.width=(t.width||[1,1,1,1]).slice(),this.color=(t.color||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]).map((function(t){return t.slice()})),this.center=(t.center||[1/0,1/0]).slice(),this.plot.setOverlayDirty()},i.draw=function(){var t=this.enable,e=this.width,r=this.color,n=this.center,i=this.plot,a=i.line,o=i.dataBox,s=i.viewBox;if(a.bind(),o[0]<=n[0]&&n[0]<=o[2]&&o[1]<=n[1]&&n[1]<=o[3]){var l=s[0]+(n[0]-o[0])/(o[2]-o[0])*(s[2]-s[0]),c=s[1]+(n[1]-o[1])/(o[3]-o[1])*(s[3]-s[1]);t[0]&&a.drawLine(l,c,s[0],c,e[0],r[0]),t[1]&&a.drawLine(l,c,l,s[1],e[1],r[1]),t[2]&&a.drawLine(l,c,s[2],c,e[2],r[2]),t[3]&&a.drawLine(l,c,l,s[3],e[3],r[3])}},i.dispose=function(){this.plot.removeOverlay(this)}},{}],343:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],344:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, color;\\nattribute float weight;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 coordinates[3];\\nuniform vec4 colors[3];\\nuniform vec2 screenShape;\\nuniform float lineWidth;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  vec3 vertexPosition = mix(coordinates[0],\\n    mix(coordinates[2], coordinates[1], 0.5 * (position + 1.0)), abs(position));\\n\\n  vec4 clipPos = projection * view * model * vec4(vertexPosition, 1.0);\\n  vec2 clipOffset = (projection * view * model * vec4(color, 0.0)).xy;\\n  vec2 delta = weight * clipOffset * screenShape;\\n  vec2 lineOffset = normalize(vec2(delta.y, -delta.x)) / screenShape;\\n\\n  gl_Position   = vec4(clipPos.xy + clipPos.w * 0.5 * lineWidth * lineOffset, clipPos.z, clipPos.w);\\n  fragColor     = color.x * colors[0] + color.y * colors[1] + color.z * colors[2];\\n}\\n\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  gl_FragColor = fragColor;\\n}\"]);e.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec3\"},{name:\"weight\",type:\"float\"}])}},{\"gl-shader\":335,glslify:343}],345:[function(t,e,r){\"use strict\";var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders/index\");e.exports=function(t,e){var r=[];function o(t,e,n,i,a,o){var s=[t,e,n,0,0,0,1];s[i+3]=1,s[i]=a,r.push.apply(r,s),s[6]=-1,r.push.apply(r,s),s[i]=o,r.push.apply(r,s),r.push.apply(r,s),s[6]=1,r.push.apply(r,s),s[i]=a,r.push.apply(r,s)}o(0,0,0,0,0,1),o(0,0,0,1,0,1),o(0,0,0,2,0,1),o(1,0,0,1,-1,1),o(1,0,0,2,-1,1),o(0,1,0,0,-1,1),o(0,1,0,2,-1,1),o(0,0,1,0,-1,1),o(0,0,1,1,-1,1);var l=n(t,r),c=i(t,[{type:t.FLOAT,buffer:l,size:3,offset:0,stride:28},{type:t.FLOAT,buffer:l,size:3,offset:12,stride:28},{type:t.FLOAT,buffer:l,size:1,offset:24,stride:28}]),u=a(t);u.attributes.position.location=0,u.attributes.color.location=1,u.attributes.weight.location=2;var f=new s(t,l,c,u);return f.update(e),f};var o=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function s(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n,this.pixelRatio=1,this.bounds=[[-1e3,-1e3,-1e3],[1e3,1e3,1e3]],this.position=[0,0,0],this.lineWidth=[2,2,2],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.enabled=[!0,!0,!0],this.drawSides=[!0,!0,!0],this.axes=null}var l=s.prototype,c=[0,0,0],u=[0,0,0],f=[0,0];l.isTransparent=function(){return!1},l.drawTransparent=function(t){},l.draw=function(t){var e=this.gl,r=this.vao,n=this.shader;r.bind(),n.bind();var i,a=t.model||o,s=t.view||o,l=t.projection||o;this.axes&&(i=this.axes.lastCubeProps.axis);for(var h=c,p=u,d=0;d<3;++d)i&&i[d]<0?(h[d]=this.bounds[0][d],p[d]=this.bounds[1][d]):(h[d]=this.bounds[1][d],p[d]=this.bounds[0][d]);f[0]=e.drawingBufferWidth,f[1]=e.drawingBufferHeight,n.uniforms.model=a,n.uniforms.view=s,n.uniforms.projection=l,n.uniforms.coordinates=[this.position,h,p],n.uniforms.colors=this.colors,n.uniforms.screenShape=f;for(d=0;d<3;++d)n.uniforms.lineWidth=this.lineWidth[d]*this.pixelRatio,this.enabled[d]&&(r.draw(e.TRIANGLES,6,6*d),this.drawSides[d]&&r.draw(e.TRIANGLES,12,18+12*d));r.unbind()},l.update=function(t){t&&(\"bounds\"in t&&(this.bounds=t.bounds),\"position\"in t&&(this.position=t.position),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"colors\"in t&&(this.colors=t.colors),\"enabled\"in t&&(this.enabled=t.enabled),\"drawSides\"in t&&(this.drawSides=t.drawSides))},l.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders/index\":344,\"gl-buffer\":259,\"gl-vao\":358}],346:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n  float segmentCount = 8.0;\\n\\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d);\\n  vec3 y = v * sin(angle) * length(d);\\n  vec3 v3 = x + y;\\n\\n  normal = normalize(v3);\\n\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, tubeScale;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * tubePosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  // vec4 m_position  = model * vec4(tubePosition, 1.0);\\n  vec4 t_position  = view * tubePosition;\\n  gl_Position      = projection * t_position;\\n\\n  f_color          = color;\\n  f_data           = tubePosition.xyz;\\n  f_position       = position.xyz;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n  float segmentCount = 8.0;\\n\\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d);\\n  vec3 y = v * sin(angle) * length(d);\\n  vec3 v3 = x + y;\\n\\n  normal = normalize(v3);\\n\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float tubeScale;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  vec3 normal;\\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  gl_Position = projection * view * tubePosition;\\n  f_id        = id;\\n  f_position  = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec4\"}]},r.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec4\"}]}},{glslify:347}],347:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],348:[function(t,e,r){\"use strict\";var n=t(\"gl-vec3\"),i=t(\"gl-vec4\"),a=[\"xyz\",\"xzy\",\"yxz\",\"yzx\",\"zxy\",\"zyx\"],o=function(t,e,r,a){for(var o=0,s=0;s<t.length;s++)for(var l=t[s].velocities,c=0;c<l.length;c++)o=Math.max(o,n.length(l[c]));var u=t.map((function(t){return function(t,e,r,a){for(var o=t.points,s=t.velocities,l=t.divergences,c=[],u=[],f=[],h=[],p=[],d=[],g=0,m=0,v=i.create(),y=i.create(),x=0;x<o.length;x++){var b=o[x],_=s[x],w=l[x];0===e&&(w=.05*r),m=n.length(_)/a,v=i.create(),n.copy(v,_),v[3]=w;for(var T=0;T<8;T++)p[T]=[b[0],b[1],b[2],T];if(h.length>0)for(T=0;T<8;T++){var k=(T+1)%8;c.push(h[T],p[T],p[k],p[k],h[k],h[T]),f.push(y,v,v,v,y,y),d.push(g,m,m,m,g,g);var M=c.length;u.push([M-6,M-5,M-4],[M-3,M-2,M-1])}var A=h;h=p,p=A;var S=y;y=v,v=S;var E=g;g=m,m=E}return{positions:c,cells:u,vectors:f,vertexIntensity:d}}(t,r,a,o)})),f=[],h=[],p=[],d=[];for(s=0;s<u.length;s++){var g=u[s],m=f.length;f=f.concat(g.positions),p=p.concat(g.vectors),d=d.concat(g.vertexIntensity);for(c=0;c<g.cells.length;c++){var v=g.cells[c],y=[];h.push(y);for(var x=0;x<v.length;x++)y.push(v[x]+m)}}return{positions:f,cells:h,vectors:p,vertexIntensity:d,colormap:e}},s=function(t,e){var r,n=t.length;for(r=0;r<n;r++){var i=t[r];if(i===e)return r;if(i>e)return r-1}return r},l=function(t,e,r){return t<e?e:t>r?r:t},c=function(t){var e=1/0;t.sort((function(t,e){return t-e}));for(var r=t.length,n=1;n<r;n++){var i=Math.abs(t[n]-t[n-1]);i<e&&(e=i)}return e};e.exports=function(t,e){var r=t.startingPositions,i=t.maxLength||1e3,u=t.tubeSize||1,f=t.absoluteTubeSize,h=t.gridFill||\"+x+y+z\",p={};-1!==h.indexOf(\"-x\")&&(p.reversedX=!0),-1!==h.indexOf(\"-y\")&&(p.reversedY=!0),-1!==h.indexOf(\"-z\")&&(p.reversedZ=!0),p.filled=a.indexOf(h.replace(/-/g,\"\").replace(/\\+/g,\"\"));var d=t.getVelocity||function(e){return function(t,e,r){var i=e.vectors,a=e.meshgrid,o=t[0],c=t[1],u=t[2],f=a[0].length,h=a[1].length,p=a[2].length,d=s(a[0],o),g=s(a[1],c),m=s(a[2],u),v=d+1,y=g+1,x=m+1;if(d=l(d,0,f-1),v=l(v,0,f-1),g=l(g,0,h-1),y=l(y,0,h-1),m=l(m,0,p-1),x=l(x,0,p-1),d<0||g<0||m<0||v>f-1||y>h-1||x>p-1)return n.create();var b,_,w,T,k,M,A=a[0][d],S=a[0][v],E=a[1][g],C=a[1][y],L=a[2][m],I=(o-A)/(S-A),P=(c-E)/(C-E),z=(u-L)/(a[2][x]-L);switch(isFinite(I)||(I=.5),isFinite(P)||(P=.5),isFinite(z)||(z=.5),r.reversedX&&(d=f-1-d,v=f-1-v),r.reversedY&&(g=h-1-g,y=h-1-y),r.reversedZ&&(m=p-1-m,x=p-1-x),r.filled){case 5:k=m,M=x,w=g*p,T=y*p,b=d*p*h,_=v*p*h;break;case 4:k=m,M=x,b=d*p,_=v*p,w=g*p*f,T=y*p*f;break;case 3:w=g,T=y,k=m*h,M=x*h,b=d*h*p,_=v*h*p;break;case 2:w=g,T=y,b=d*h,_=v*h,k=m*h*f,M=x*h*f;break;case 1:b=d,_=v,k=m*f,M=x*f,w=g*f*p,T=y*f*p;break;default:b=d,_=v,w=g*f,T=y*f,k=m*f*h,M=x*f*h}var O=i[b+w+k],D=i[b+w+M],R=i[b+T+k],F=i[b+T+M],B=i[_+w+k],N=i[_+w+M],j=i[_+T+k],U=i[_+T+M],V=n.create(),q=n.create(),H=n.create(),G=n.create();n.lerp(V,O,B,I),n.lerp(q,D,N,I),n.lerp(H,R,j,I),n.lerp(G,F,U,I);var Y=n.create(),W=n.create();n.lerp(Y,V,H,P),n.lerp(W,q,G,P);var X=n.create();return n.lerp(X,Y,W,z),X}(e,t,p)},g=t.getDivergence||function(t,e){var r=n.create(),i=1e-4;n.add(r,t,[i,0,0]);var a=d(r);n.subtract(a,a,e),n.scale(a,a,1/i),n.add(r,t,[0,i,0]);var o=d(r);n.subtract(o,o,e),n.scale(o,o,1/i),n.add(r,t,[0,0,i]);var s=d(r);return n.subtract(s,s,e),n.scale(s,s,1/i),n.add(r,a,o),n.add(r,r,s),r},m=[],v=e[0][0],y=e[0][1],x=e[0][2],b=e[1][0],_=e[1][1],w=e[1][2],T=function(t){var e=t[0],r=t[1],n=t[2];return!(e<v||e>b||r<y||r>_||n<x||n>w)},k=10*n.distance(e[0],e[1])/i,M=k*k,A=1,S=0,E=r.length;E>1&&(A=function(t){for(var e=[],r=[],n=[],i={},a={},o={},s=t.length,l=0;l<s;l++){var u=t[l],f=u[0],h=u[1],p=u[2];i[f]||(e.push(f),i[f]=!0),a[h]||(r.push(h),a[h]=!0),o[p]||(n.push(p),o[p]=!0)}var d=c(e),g=c(r),m=c(n),v=Math.min(d,g,m);return isFinite(v)?v:1}(r));for(var C=0;C<E;C++){var L=n.create();n.copy(L,r[C]);var I=[L],P=[],z=d(L),O=L;P.push(z);var D=[],R=g(L,z),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F),m.push({points:I,velocities:P,divergences:D});for(var B=0;B<100*i&&I.length<i&&T(L);){B++;var N=n.clone(z),j=n.squaredLength(N);if(0===j)break;if(j>M&&n.scale(N,N,k/Math.sqrt(j)),n.add(N,N,L),z=d(N),n.squaredDistance(O,N)-M>-1e-4*M){I.push(N),O=N,P.push(z);R=g(N,z),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F)}L=N}}var U=o(m,t.colormap,S,A);return f?U.tubeScale=f:(0===S&&(S=1),U.tubeScale=.5*u*A/S),U};var u=t(\"./lib/shaders\"),f=t(\"gl-cone3d\").createMesh;e.exports.createTubeMesh=function(t,e){return f(t,e,{shaders:u,traceType:\"streamtube\"})}},{\"./lib/shaders\":346,\"gl-cone3d\":260,\"gl-vec3\":377,\"gl-vec4\":413}],349:[function(t,e,r){var n=t(\"gl-shader\"),i=t(\"glslify\"),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute vec3 f;\\nattribute vec3 normal;\\n\\nuniform vec3 objectOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 localCoordinate = vec3(uv.zw, f.x);\\n  worldCoordinate = objectOffset + localCoordinate;\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n  vec4 clipPosition = projection * view * worldPosition;\\n  gl_Position = clipPosition;\\n  kill = f.y;\\n  value = f.z;\\n  planeCoordinate = uv.xy;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * worldPosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  lightDirection = lightPosition - cameraCoordinate.xyz;\\n  eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  surfaceNormal  = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\\n\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat beckmannSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness) {\\n  return beckmannDistribution(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform float vertexColor;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  if (\\n    kill > 0.0 ||\\n    vColor.a == 0.0 ||\\n    outOfRange(clipBounds[0], clipBounds[1], worldCoordinate)\\n  ) discard;\\n\\n  vec3 N = normalize(surfaceNormal);\\n  vec3 V = normalize(eyeDirection);\\n  vec3 L = normalize(lightDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = max(beckmannSpecular(L, V, N, roughness), 0.);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  //decide how to interpolate color \\u2014 in vertex or in fragment\\n  vec4 surfaceColor =\\n    step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) +\\n    step(.5, vertexColor) * vColor;\\n\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\\n}\\n\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute float f;\\n\\nuniform vec3 objectOffset;\\nuniform mat3 permutation;\\nuniform mat4 model, view, projection;\\nuniform float height, zOffset;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 dataCoordinate = permutation * vec3(uv.xy, height);\\n  worldCoordinate = objectOffset + dataCoordinate;\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n\\n  vec4 clipPosition = projection * view * worldPosition;\\n  clipPosition.z += zOffset;\\n\\n  gl_Position = clipPosition;\\n  value = f + objectOffset.z;\\n  kill = -1.0;\\n  planeCoordinate = uv.zw;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Don't do lighting for contours\\n  surfaceNormal   = vec3(1,0,0);\\n  eyeDirection    = vec3(0,1,0);\\n  lightDirection  = vec3(0,0,1);\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n  float vh = 255.0 * v;\\n  float upper = floor(vh);\\n  float lower = fract(vh);\\n  return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n  if ((kill > 0.0) ||\\n      (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\\n\\n  vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n  vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n  gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\\n\"]);r.createShader=function(t){var e=n(t,a,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createPickShader=function(t){var e=n(t,a,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createContourShader=function(t){var e=n(t,s,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},r.createPickContourShader=function(t){var e=n(t,s,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},{\"gl-shader\":335,glslify:350}],350:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],351:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=y(e),n=b(e),s=x(e),l=_(e),c=i(e),u=a(e,[{buffer:c,size:4,stride:40,offset:0},{buffer:c,size:3,stride:40,offset:16},{buffer:c,size:3,stride:40,offset:28}]),f=i(e),h=a(e,[{buffer:f,size:4,stride:20,offset:0},{buffer:f,size:1,stride:20,offset:16}]),p=i(e),d=a(e,[{buffer:p,size:2,type:e.FLOAT}]),g=o(e,1,256,e.RGBA,e.UNSIGNED_BYTE);g.minFilter=e.LINEAR,g.magFilter=e.LINEAR;var m=new A(e,[0,0],[[0,0,0],[0,0,0]],r,n,c,u,g,s,l,f,h,p,d,[0,0,0]),v={levels:[[],[],[]]};for(var w in t)v[w]=t[w];return v.colormap=v.colormap||\"jet\",m.update(v),m};var n=t(\"bit-twiddle\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"typedarray-pool\"),l=t(\"colormap\"),c=t(\"ndarray-ops\"),u=t(\"ndarray-pack\"),f=t(\"ndarray\"),h=t(\"surface-nets\"),p=t(\"gl-mat4/multiply\"),d=t(\"gl-mat4/invert\"),g=t(\"binary-search-bounds\"),m=t(\"ndarray-gradient\"),v=t(\"./lib/shaders\"),y=v.createShader,x=v.createContourShader,b=v.createPickShader,_=v.createPickContourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],T=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],k=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];function M(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}!function(){for(var t=0;t<3;++t){var e=k[t],r=(t+2)%3;e[(t+1)%3+0]=1,e[r+3]=1,e[t+6]=1}}();function A(t,e,r,n,i,a,o,l,c,u,h,p,d,g,m){this.gl=t,this.shape=e,this.bounds=r,this.objectOffset=m,this.intensityBounds=[],this._shader=n,this._pickShader=i,this._coordinateBuffer=a,this._vao=o,this._colorMap=l,this._contourShader=c,this._contourPickShader=u,this._contourBuffer=h,this._contourVAO=p,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new M([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=g,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.snapToData=!1,this.pixelRatio=1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}var S=A.prototype;S.genColormap=function(t,e){var r=!1,n=u([l({colormap:t,nshades:256,format:\"rgba\"}).map((function(t,n){var i=e?function(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}(n/255,e):t[3];return i<1&&(r=!0),[t[0],t[1],t[2],255*i]}))]);return c.divseq(n,255),this.hasAlphaScale=r,n},S.isTransparent=function(){return this.opacity<1||this.hasAlphaScale},S.isOpaque=function(){return!this.isTransparent()},S.pickSlots=1,S.setPickBase=function(t){this.pickId=t};var E=[0,0,0],C={showSurface:!1,showContour:!1,projections:[w.slice(),w.slice(),w.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function L(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||E,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=C.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(a[r]>0)][r],p(l,t.model,l);var c=C.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)c[i][n]=t.clipBounds[i][n];c[0][r]=-1e8,c[1][r]=1e8}return C.showSurface=o,C.showContour=s,C}var I={model:w,view:w,projection:w,inverseModel:w.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},P=w.slice(),z=[1,0,0,0,1,0,0,0,1];function O(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=I;n.model=t.model||w,n.view=t.view||w,n.projection=t.projection||w,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.objectOffset=this.objectOffset,n.contourColor=this.contourColor[0],n.inverseModel=d(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],o=0;o<3;++o)a[o]=Math.min(Math.max(this.clipBounds[i][o],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=z,n.vertexColor=this.vertexColor;var s=P;for(p(s,n.view,n.model),p(s,n.projection,s),d(s,s),i=0;i<3;++i)n.eyePosition[i]=s[12+i]/s[15];var l=s[15];for(i=0;i<3;++i)l+=this.lightPosition[i]*s[4*i+3];for(i=0;i<3;++i){var c=s[12+i];for(o=0;o<3;++o)c+=s[4*o+i]*this.lightPosition[o];n.lightPosition[i]=c/l}var u=L(n,this);if(u.showSurface){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),i=0;i<3;++i)this.surfaceProject[i]&&this.vertexCount&&(this._shader.uniforms.model=u.projections[i],this._shader.uniforms.clipBounds=u.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(u.showContour){var f=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,f.bind(),f.uniforms=n;var h=this._contourVAO;for(h.bind(),i=0;i<3;++i)for(f.uniforms.permutation=k[i],r.lineWidth(this.contourWidth[i]*this.pixelRatio),o=0;o<this.contourLevels[i].length;++o)o===this.highlightLevel[i]?(f.uniforms.contourColor=this.highlightColor[i],f.uniforms.contourTint=this.highlightTint[i]):0!==o&&o-1!==this.highlightLevel[i]||(f.uniforms.contourColor=this.contourColor[i],f.uniforms.contourTint=this.contourTint[i]),this._contourCounts[i][o]&&(f.uniforms.height=this.contourLevels[i][o],h.draw(r.LINES,this._contourCounts[i][o],this._contourOffsets[i][o]));for(i=0;i<3;++i)for(f.uniforms.model=u.projections[i],f.uniforms.clipBounds=u.clipBounds[i],o=0;o<3;++o)if(this.contourProject[i][o]){f.uniforms.permutation=k[o],r.lineWidth(this.contourWidth[o]*this.pixelRatio);for(var g=0;g<this.contourLevels[o].length;++g)g===this.highlightLevel[o]?(f.uniforms.contourColor=this.highlightColor[o],f.uniforms.contourTint=this.highlightTint[o]):0!==g&&g-1!==this.highlightLevel[o]||(f.uniforms.contourColor=this.contourColor[o],f.uniforms.contourTint=this.contourTint[o]),this._contourCounts[o][g]&&(f.uniforms.height=this.contourLevels[o][g],h.draw(r.LINES,this._contourCounts[o][g],this._contourOffsets[o][g]))}for(h.unbind(),(h=this._dynamicVAO).bind(),i=0;i<3;++i)if(0!==this._dynamicCounts[i])for(f.uniforms.model=n.model,f.uniforms.clipBounds=n.clipBounds,f.uniforms.permutation=k[i],r.lineWidth(this.dynamicWidth[i]*this.pixelRatio),f.uniforms.contourColor=this.dynamicColor[i],f.uniforms.contourTint=this.dynamicTint[i],f.uniforms.height=this.dynamicLevel[i],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]),o=0;o<3;++o)this.contourProject[o][i]&&(f.uniforms.model=u.projections[o],f.uniforms.clipBounds=u.clipBounds[o],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]));h.unbind()}}S.draw=function(t){return O.call(this,t,!1)},S.drawTransparent=function(t){return O.call(this,t,!0)};var D={model:w,view:w,projection:w,inverseModel:w,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,objectOffset:[0,0,0],permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};function R(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function F(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function B(t){if(Array.isArray(t)){if(Array.isArray(t))return[F(t[0]),F(t[1]),F(t[2])];var e=F(t);return[e.slice(),e.slice(),e.slice()]}}S.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=D;r.model=t.model||w,r.view=t.view||w,r.projection=t.projection||w,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.objectOffset=this.objectOffset,r.permutation=z;for(var n=0;n<2;++n)for(var i=r.clipBounds[n],a=0;a<3;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var o=L(r,this);if(o.showSurface){for(this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount),n=0;n<3;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=o.projections[n],this._pickShader.uniforms.clipBounds=o.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(o.showContour){var s=this._contourPickShader;s.bind(),s.uniforms=r;var l=this._contourVAO;for(l.bind(),a=0;a<3;++a)for(e.lineWidth(this.contourWidth[a]*this.pixelRatio),s.uniforms.permutation=k[a],n=0;n<this.contourLevels[a].length;++n)this._contourCounts[a][n]&&(s.uniforms.height=this.contourLevels[a][n],l.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n]));for(n=0;n<3;++n)for(s.uniforms.model=o.projections[n],s.uniforms.clipBounds=o.clipBounds[n],a=0;a<3;++a)if(this.contourProject[n][a]){s.uniforms.permutation=k[a],e.lineWidth(this.contourWidth[a]*this.pixelRatio);for(var c=0;c<this.contourLevels[a].length;++c)this._contourCounts[a][c]&&(s.uniforms.height=this.contourLevels[a][c],l.draw(e.LINES,this._contourCounts[a][c],this._contourOffsets[a][c]))}l.unbind()}},S.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var c=r.position;c[0]=c[1]=c[2]=0;for(var u=0;u<2;++u)for(var f=u?a:1-a,h=0;h<2;++h)for(var p=i+u,d=s+h,m=f*(h?l:1-l),v=0;v<3;++v)c[v]+=this._field[v].get(p,d)*m;for(var y=this._pickResult.level,x=0;x<3;++x)if(y[x]=g.le(this.contourLevels[x],c[x]),y[x]<0)this.contourLevels[x].length>0&&(y[x]=0);else if(y[x]<this.contourLevels[x].length-1){var b=this.contourLevels[x][y[x]],_=this.contourLevels[x][y[x]+1];Math.abs(b-c[x])>Math.abs(_-c[x])&&(y[x]+=1)}for(r.index[0]=a<.5?i:i+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],v=0;v<3;++v)r.dataCoordinate[v]=this._field[v].get(r.index[0],r.index[1]);return r},S.padField=function(t,e){var r=e.shape.slice(),n=t.shape.slice();c.assign(t.lo(1,1).hi(r[0],r[1]),e),c.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),c.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),c.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),c.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))},S.update=function(t){t=t||{},this.objectOffset=t.objectOffset||this.objectOffset,this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=R(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=R(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=R(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=B(t.contourColor)),\"contourProject\"in t&&(this.contourProject=R(t.contourProject,(function(t){return R(t,Boolean)}))),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=B(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=R(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=R(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale),\"colorBounds\"in t&&(this.colorBounds=t.colorBounds),\"vertexColor\"in t&&(this.vertexColor=t.vertexColor?1:0),\"colormap\"in t&&this._colorMap.setPixels(this.genColormap(t.colormap,this.opacityscale));var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var i=(e.shape[0]+2)*(e.shape[1]+2);i>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(n.nextPow2(i))),this._field[2]=f(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),this.padField(this._field[2],e),this.shape=e.shape.slice();for(var a=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(s.freeFloat(this._field[o].data),this._field[o].data=s.mallocFloat(this._field[2].size)),this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var l=t.coords;if(!Array.isArray(l)||3!==l.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(o=0;o<2;++o){var c=l[o];for(v=0;v<2;++v)if(c.shape[v]!==a[v])throw new Error(\"gl-surface: coords have incorrect shape\");this.padField(this._field[o],c)}}else if(t.ticks){var u=t.ticks;if(!Array.isArray(u)||2!==u.length)throw new Error(\"gl-surface: invalid ticks\");for(o=0;o<2;++o){var p=u[o];if((Array.isArray(p)||p.length)&&(p=f(p)),p.shape[0]!==a[o])throw new Error(\"gl-surface: invalid tick length\");var d=f(p.data,a);d.stride[o]=p.stride[0],d.stride[1^o]=0,this.padField(this._field[o],d)}}else{for(o=0;o<2;++o){var g=[0,0];g[o]=1,this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2],g,0)}this._field[0].set(0,0,0);for(var v=0;v<a[0];++v)this._field[0].set(v+1,0,v);for(this._field[0].set(a[0]+1,0,a[0]-1),this._field[1].set(0,0,0),v=0;v<a[1];++v)this._field[1].set(0,v+1,v);this._field[1].set(0,a[1]+1,a[1]-1)}var y=this._field,x=f(s.mallocFloat(3*y[2].size*2),[3,a[0]+2,a[1]+2,2]);for(o=0;o<3;++o)m(x.pick(o),y[o],\"mirror\");var b=f(s.mallocFloat(3*y[2].size),[a[0]+2,a[1]+2,3]);for(o=0;o<a[0]+2;++o)for(v=0;v<a[1]+2;++v){var _=x.get(0,o,v,0),w=x.get(0,o,v,1),k=x.get(1,o,v,0),M=x.get(1,o,v,1),A=x.get(2,o,v,0),S=x.get(2,o,v,1),E=k*S-M*A,C=A*w-S*_,L=_*M-w*k,I=Math.sqrt(E*E+C*C+L*L);I<1e-8?(I=Math.max(Math.abs(E),Math.abs(C),Math.abs(L)))<1e-8?(L=1,C=E=0,I=1):I=1/I:I=1/Math.sqrt(I),b.set(o,v,0,E*I),b.set(o,v,1,C*I),b.set(o,v,2,L*I)}s.free(x.data);var P=[1/0,1/0,1/0],z=[-1/0,-1/0,-1/0],O=1/0,D=-1/0,F=(a[0]-1)*(a[1]-1)*6,N=s.mallocFloat(n.nextPow2(10*F)),j=0,U=0;for(o=0;o<a[0]-1;++o)t:for(v=0;v<a[1]-1;++v){for(var V=0;V<2;++V)for(var q=0;q<2;++q)for(var H=0;H<3;++H){var G=this._field[H].get(1+o+V,1+v+q);if(isNaN(G)||!isFinite(G))continue t}for(H=0;H<6;++H){var Y=o+T[H][0],W=v+T[H][1],X=this._field[0].get(Y+1,W+1),Z=this._field[1].get(Y+1,W+1);G=this._field[2].get(Y+1,W+1),E=b.get(Y+1,W+1,0),C=b.get(Y+1,W+1,1),L=b.get(Y+1,W+1,2),t.intensity&&(J=t.intensity.get(Y,W));var J=t.intensity?t.intensity.get(Y,W):G+this.objectOffset[2];N[j++]=Y,N[j++]=W,N[j++]=X,N[j++]=Z,N[j++]=G,N[j++]=0,N[j++]=J,N[j++]=E,N[j++]=C,N[j++]=L,P[0]=Math.min(P[0],X+this.objectOffset[0]),P[1]=Math.min(P[1],Z+this.objectOffset[1]),P[2]=Math.min(P[2],G+this.objectOffset[2]),O=Math.min(O,J),z[0]=Math.max(z[0],X+this.objectOffset[0]),z[1]=Math.max(z[1],Z+this.objectOffset[1]),z[2]=Math.max(z[2],G+this.objectOffset[2]),D=Math.max(D,J),U+=1}}for(t.intensityBounds&&(O=+t.intensityBounds[0],D=+t.intensityBounds[1]),o=6;o<j;o+=10)N[o]=(N[o]-O)/(D-O);this._vertexCount=U,this._coordinateBuffer.update(N.subarray(0,j)),s.freeFloat(N),s.free(b.data),this.bounds=[P,z],this.intensity=t.intensity||this._field[2],this.intensityBounds[0]===O&&this.intensityBounds[1]===D||(r=!0),this.intensityBounds=[O,D]}if(\"levels\"in t){var K=t.levels;for(K=Array.isArray(K[0])?K.slice():[[],[],K],o=0;o<3;++o)K[o]=K[o].slice(),K[o].sort((function(t,e){return t-e}));for(o=0;o<3;++o)for(v=0;v<K[o].length;++v)K[o][v]-=this.objectOffset[o];t:for(o=0;o<3;++o){if(K[o].length!==this.contourLevels[o].length){r=!0;break}for(v=0;v<K[o].length;++v)if(K[o][v]!==this.contourLevels[o][v]){r=!0;break t}}this.contourLevels=K}if(r){y=this._field,a=this.shape;for(var Q=[],$=0;$<3;++$){var tt=this.contourLevels[$],et=[],rt=[],nt=[0,0,0];for(o=0;o<tt.length;++o){var it=h(this._field[$],tt[o]);et.push(Q.length/5|0),U=0;t:for(v=0;v<it.cells.length;++v){var at=it.cells[v];for(H=0;H<2;++H){var ot=it.positions[at[H]],st=ot[0],lt=0|Math.floor(st),ct=st-lt,ut=ot[1],ft=0|Math.floor(ut),ht=ut-ft,pt=!1;e:for(var dt=0;dt<3;++dt){nt[dt]=0;var gt=($+dt+1)%3;for(V=0;V<2;++V){var mt=V?ct:1-ct;for(Y=0|Math.min(Math.max(lt+V,0),a[0]),q=0;q<2;++q){var vt=q?ht:1-ht;if(W=0|Math.min(Math.max(ft+q,0),a[1]),G=dt<2?this._field[gt].get(Y,W):(this.intensity.get(Y,W)-this.intensityBounds[0])/(this.intensityBounds[1]-this.intensityBounds[0]),!isFinite(G)||isNaN(G)){pt=!0;break e}var yt=mt*vt;nt[dt]+=yt*G}}}if(pt){if(H>0){for(var xt=0;xt<5;++xt)Q.pop();U-=1}continue t}Q.push(nt[0],nt[1],ot[0],ot[1],nt[2]),U+=1}}rt.push(U)}this._contourOffsets[$]=et,this._contourCounts[$]=rt}var bt=s.mallocFloat(Q.length);for(o=0;o<Q.length;++o)bt[o]=Q[o];this._contourBuffer.update(bt),s.freeFloat(bt)}},S.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)s.freeFloat(this._field[t].data)},S.highlight=function(t){var e,r;if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;for(r=this.snapToData?t.dataCoordinate:t.position,e=0;e<3;++e)r[e]-=this.objectOffset[e];if(this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=s.mallocFloat(12*i[0]*i[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var l=(o+1)%3,c=(o+2)%3,u=this._field[o],f=this._field[l],p=this._field[c],d=h(u,r[o]),g=d.cells,m=d.positions;for(this._dynamicOffsets[o]=n,e=0;e<g.length;++e)for(var v=g[e],y=0;y<2;++y){var x=m[v[y]],b=+x[0],_=0|b,w=0|Math.min(_+1,i[0]),T=b-_,k=1-T,M=+x[1],A=0|M,S=0|Math.min(A+1,i[1]),E=M-A,C=1-E,L=k*C,I=k*E,P=T*C,z=T*E,O=L*f.get(_,A)+I*f.get(_,S)+P*f.get(w,A)+z*f.get(w,S),D=L*p.get(_,A)+I*p.get(_,S)+P*p.get(w,A)+z*p.get(w,S);if(isNaN(O)||isNaN(D)){y&&(n-=1);break}a[2*n+0]=O,a[2*n+1]=D,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),s.freeFloat(a)}}},{\"./lib/shaders\":349,\"binary-search-bounds\":96,\"bit-twiddle\":97,colormap:131,\"gl-buffer\":259,\"gl-mat4/invert\":293,\"gl-mat4/multiply\":295,\"gl-texture2d\":353,\"gl-vao\":358,ndarray:495,\"ndarray-gradient\":488,\"ndarray-ops\":490,\"ndarray-pack\":491,\"surface-nets\":570,\"typedarray-pool\":595}],352:[function(t,e,r){\"use strict\";var n=t(\"css-font\"),i=t(\"pick-by-alias\"),a=t(\"regl\"),o=t(\"gl-util/context\"),s=t(\"es6-weak-map\"),l=t(\"color-normalize\"),c=t(\"font-atlas\"),u=t(\"typedarray-pool\"),f=t(\"parse-rect\"),h=t(\"is-plain-obj\"),p=t(\"parse-unit\"),d=t(\"to-px\"),g=t(\"detect-kerning\"),m=t(\"object-assign\"),v=t(\"font-measure\"),y=t(\"flatten-vertex-data\"),x=t(\"bit-twiddle\").nextPow2,b=new s,_=!1;if(document.body){var w=document.body.appendChild(document.createElement(\"div\"));w.style.font=\"italic small-caps bold condensed 16px/2 cursive\",getComputedStyle(w).fontStretch&&(_=!0),document.body.removeChild(w)}var T=function(t){!function(t){return\"function\"==typeof t&&t._gl&&t.prop&&t.texture&&t.buffer}(t)?this.gl=o(t):(t={regl:t},this.gl=t.regl._gl),this.shader=b.get(this.gl),this.shader?this.regl=this.shader.regl:this.regl=t.regl||a({gl:this.gl}),this.charBuffer=this.regl.buffer({type:\"uint8\",usage:\"stream\"}),this.sizeBuffer=this.regl.buffer({type:\"float\",usage:\"stream\"}),this.shader||(this.shader=this.createShader(),b.set(this.gl,this.shader)),this.batch=[],this.fontSize=[],this.font=[],this.fontAtlas=[],this.draw=this.shader.draw.bind(this),this.render=function(){this.regl._refresh(),this.draw(this.batch)},this.canvas=this.gl.canvas,this.update(h(t)?t:{})};T.prototype.createShader=function(){var t=this.regl,e=t({blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},stencil:{enable:!1},depth:{enable:!1},count:t.prop(\"count\"),offset:t.prop(\"offset\"),attributes:{charOffset:{offset:4,stride:8,buffer:t.this(\"sizeBuffer\")},width:{offset:0,stride:8,buffer:t.this(\"sizeBuffer\")},char:t.this(\"charBuffer\"),position:t.this(\"position\")},uniforms:{atlasSize:function(t,e){return[e.atlas.width,e.atlas.height]},atlasDim:function(t,e){return[e.atlas.cols,e.atlas.rows]},atlas:function(t,e){return e.atlas.texture},charStep:function(t,e){return e.atlas.step},em:function(t,e){return e.atlas.em},color:t.prop(\"color\"),opacity:t.prop(\"opacity\"),viewport:t.this(\"viewportArray\"),scale:t.this(\"scale\"),align:t.prop(\"align\"),baseline:t.prop(\"baseline\"),translate:t.this(\"translate\"),positionOffset:t.prop(\"positionOffset\")},primitive:\"points\",viewport:t.this(\"viewport\"),vert:\"\\n\\t\\t\\tprecision highp float;\\n\\t\\t\\tattribute float width, charOffset, char;\\n\\t\\t\\tattribute vec2 position;\\n\\t\\t\\tuniform float fontSize, charStep, em, align, baseline;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tuniform vec4 color;\\n\\t\\t\\tuniform vec2 atlasSize, atlasDim, scale, translate, positionOffset;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\t\"+(T.normalViewport?\"\":\"vec2 positionOffset = vec2(positionOffset.x,- positionOffset.y);\")+\"\\n\\n\\t\\t\\t\\tvec2 offset = floor(em * (vec2(align + charOffset, baseline)\\n\\t\\t\\t\\t\\t+ positionOffset))\\n\\t\\t\\t\\t\\t/ (viewport.zw * scale.xy);\\n\\n\\t\\t\\t\\tvec2 position = (position + translate) * scale;\\n\\t\\t\\t\\tposition += offset * scale;\\n\\n\\t\\t\\t\\t\"+(T.normalViewport?\"position.y = 1. - position.y;\":\"\")+\"\\n\\n\\t\\t\\t\\tcharCoord = position * viewport.zw + viewport.xy;\\n\\n\\t\\t\\t\\tgl_Position = vec4(position * 2. - 1., 0, 1);\\n\\n\\t\\t\\t\\tgl_PointSize = charStep;\\n\\n\\t\\t\\t\\tcharId.x = mod(char, atlasDim.x);\\n\\t\\t\\t\\tcharId.y = floor(char / atlasDim.x);\\n\\n\\t\\t\\t\\tcharWidth = width * em;\\n\\n\\t\\t\\t\\tfontColor = color / 255.;\\n\\t\\t\\t}\",frag:\"\\n\\t\\t\\tprecision highp float;\\n\\t\\t\\tuniform sampler2D atlas;\\n\\t\\t\\tuniform float fontSize, charStep, opacity;\\n\\t\\t\\tuniform vec2 atlasSize;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\n\\t\\t\\tfloat lightness(vec4 color) {\\n\\t\\t\\t\\treturn color.r * 0.299 + color.g * 0.587 + color.b * 0.114;\\n\\t\\t\\t}\\n\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\tvec2 uv = gl_FragCoord.xy - charCoord + charStep * .5;\\n\\t\\t\\t\\tfloat halfCharStep = floor(charStep * .5 + .5);\\n\\n\\t\\t\\t\\t// invert y and shift by 1px (FF expecially needs that)\\n\\t\\t\\t\\tuv.y = charStep - uv.y;\\n\\n\\t\\t\\t\\t// ignore points outside of character bounding box\\n\\t\\t\\t\\tfloat halfCharWidth = ceil(charWidth * .5);\\n\\t\\t\\t\\tif (floor(uv.x) > halfCharStep + halfCharWidth ||\\n\\t\\t\\t\\t\\tfloor(uv.x) < halfCharStep - halfCharWidth) return;\\n\\n\\t\\t\\t\\tuv += charId * charStep;\\n\\t\\t\\t\\tuv = uv / atlasSize;\\n\\n\\t\\t\\t\\tvec4 color = fontColor;\\n\\t\\t\\t\\tvec4 mask = texture2D(atlas, uv);\\n\\n\\t\\t\\t\\tfloat maskY = lightness(mask);\\n\\t\\t\\t\\t// float colorY = lightness(color);\\n\\t\\t\\t\\tcolor.a *= maskY;\\n\\t\\t\\t\\tcolor.a *= opacity;\\n\\n\\t\\t\\t\\t// color.a += .1;\\n\\n\\t\\t\\t\\t// antialiasing, see yiq color space y-channel formula\\n\\t\\t\\t\\t// color.rgb += (1. - color.rgb) * (1. - mask.rgb);\\n\\n\\t\\t\\t\\tgl_FragColor = color;\\n\\t\\t\\t}\"});return{regl:t,draw:e,atlas:{}}},T.prototype.update=function(t){var e=this;if(\"string\"==typeof t)t={text:t};else if(!t)return;null!=(t=i(t,{position:\"position positions coord coords coordinates\",font:\"font fontFace fontface typeface cssFont css-font family fontFamily\",fontSize:\"fontSize fontsize size font-size\",text:\"text texts chars characters value values symbols\",align:\"align alignment textAlign textbaseline\",baseline:\"baseline textBaseline textbaseline\",direction:\"dir direction textDirection\",color:\"color colour fill fill-color fillColor textColor textcolor\",kerning:\"kerning kern\",range:\"range dataBox\",viewport:\"vp viewport viewBox viewbox viewPort\",opacity:\"opacity alpha transparency visible visibility opaque\",offset:\"offset positionOffset padding shift indent indentation\"},!0)).opacity&&(Array.isArray(t.opacity)?this.opacity=t.opacity.map((function(t){return parseFloat(t)})):this.opacity=parseFloat(t.opacity)),null!=t.viewport&&(this.viewport=f(t.viewport),T.normalViewport&&(this.viewport.y=this.canvas.height-this.viewport.y-this.viewport.height),this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null==this.viewport&&(this.viewport={x:0,y:0,width:this.gl.drawingBufferWidth,height:this.gl.drawingBufferHeight},this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null!=t.kerning&&(this.kerning=t.kerning),null!=t.offset&&(\"number\"==typeof t.offset&&(t.offset=[t.offset,0]),this.positionOffset=y(t.offset)),t.direction&&(this.direction=t.direction),t.range&&(this.range=t.range,this.scale=[1/(t.range[2]-t.range[0]),1/(t.range[3]-t.range[1])],this.translate=[-t.range[0],-t.range[1]]),t.scale&&(this.scale=t.scale),t.translate&&(this.translate=t.translate),this.scale||(this.scale=[1/this.viewport.width,1/this.viewport.height]),this.translate||(this.translate=[0,0]),this.font.length||t.font||(t.font=T.baseFontSize+\"px sans-serif\");var r,a=!1,o=!1;if(t.font&&(Array.isArray(t.font)?t.font:[t.font]).forEach((function(t,r){if(\"string\"==typeof t)try{t=n.parse(t)}catch(e){t=n.parse(T.baseFontSize+\"px \"+t)}else t=n.parse(n.stringify(t));var i=n.stringify({size:T.baseFontSize,family:t.family,stretch:_?t.stretch:void 0,variant:t.variant,weight:t.weight,style:t.style}),s=p(t.size),l=Math.round(s[0]*d(s[1]));if(l!==e.fontSize[r]&&(o=!0,e.fontSize[r]=l),!(e.font[r]&&i==e.font[r].baseString||(a=!0,e.font[r]=T.fonts[i],e.font[r]))){var c=t.family.join(\", \"),u=[t.style];t.style!=t.variant&&u.push(t.variant),t.variant!=t.weight&&u.push(t.weight),_&&t.weight!=t.stretch&&u.push(t.stretch),e.font[r]={baseString:i,family:c,weight:t.weight,stretch:t.stretch,style:t.style,variant:t.variant,width:{},kerning:{},metrics:v(c,{origin:\"top\",fontSize:T.baseFontSize,fontStyle:u.join(\" \")})},T.fonts[i]=e.font[r]}})),(a||o)&&this.font.forEach((function(r,i){var a=n.stringify({size:e.fontSize[i],family:r.family,stretch:_?r.stretch:void 0,variant:r.variant,weight:r.weight,style:r.style});if(e.fontAtlas[i]=e.shader.atlas[a],!e.fontAtlas[i]){var o=r.metrics;e.shader.atlas[a]=e.fontAtlas[i]={fontString:a,step:2*Math.ceil(e.fontSize[i]*o.bottom*.5),em:e.fontSize[i],cols:0,rows:0,height:0,width:0,chars:[],ids:{},texture:e.regl.texture()}}null==t.text&&(t.text=e.text)})),\"string\"==typeof t.text&&t.position&&t.position.length>2){for(var s=Array(.5*t.position.length),h=0;h<s.length;h++)s[h]=t.text;t.text=s}if(null!=t.text||a){if(this.textOffsets=[0],Array.isArray(t.text)){this.count=t.text[0].length,this.counts=[this.count];for(var b=1;b<t.text.length;b++)this.textOffsets[b]=this.textOffsets[b-1]+t.text[b-1].length,this.count+=t.text[b].length,this.counts.push(t.text[b].length);this.text=t.text.join(\"\")}else this.text=t.text,this.count=this.text.length,this.counts=[this.count];r=[],this.font.forEach((function(t,n){T.atlasContext.font=t.baseString;for(var i=e.fontAtlas[n],a=0;a<e.text.length;a++){var o=e.text.charAt(a);if(null==i.ids[o]&&(i.ids[o]=i.chars.length,i.chars.push(o),r.push(o)),null==t.width[o]&&(t.width[o]=T.atlasContext.measureText(o).width/T.baseFontSize,e.kerning)){var s=[];for(var l in t.width)s.push(l+o,o+l);m(t.kerning,g(t.family,{pairs:s}))}}}))}if(t.position)if(t.position.length>2){for(var w=!t.position[0].length,k=u.mallocFloat(2*this.count),M=0,A=0;M<this.counts.length;M++){var S=this.counts[M];if(w)for(var E=0;E<S;E++)k[A++]=t.position[2*M],k[A++]=t.position[2*M+1];else for(var C=0;C<S;C++)k[A++]=t.position[M][0],k[A++]=t.position[M][1]}this.position.call?this.position({type:\"float\",data:k}):this.position=this.regl.buffer({type:\"float\",data:k}),u.freeFloat(k)}else this.position.destroy&&this.position.destroy(),this.position={constant:t.position};if(t.text||a){var L=u.mallocUint8(this.count),I=u.mallocFloat(2*this.count);this.textWidth=[];for(var P=0,z=0;P<this.counts.length;P++){for(var O=this.counts[P],D=this.font[P]||this.font[0],R=this.fontAtlas[P]||this.fontAtlas[0],F=0;F<O;F++){var B=this.text.charAt(z),N=this.text.charAt(z-1);if(L[z]=R.ids[B],I[2*z]=D.width[B],F){var j=I[2*z-2],U=I[2*z],V=I[2*z-1]+.5*j+.5*U;if(this.kerning){var q=D.kerning[N+B];q&&(V+=.001*q)}I[2*z+1]=V}else I[2*z+1]=.5*I[2*z];z++}this.textWidth.push(I.length?.5*I[2*z-2]+I[2*z-1]:0)}t.align||(t.align=this.align),this.charBuffer({data:L,type:\"uint8\",usage:\"stream\"}),this.sizeBuffer({data:I,type:\"float\",usage:\"stream\"}),u.freeUint8(L),u.freeFloat(I),r.length&&this.font.forEach((function(t,r){var n=e.fontAtlas[r],i=n.step,a=Math.floor(T.maxAtlasSize/i),o=Math.min(a,n.chars.length),s=Math.ceil(n.chars.length/o),l=x(o*i),u=x(s*i);n.width=l,n.height=u,n.rows=s,n.cols=o,n.em&&n.texture({data:c({canvas:T.atlasCanvas,font:n.fontString,chars:n.chars,shape:[l,u],step:[i,i]})})}))}if(t.align&&(this.align=t.align,this.alignOffset=this.textWidth.map((function(t,r){var n=Array.isArray(e.align)?e.align.length>1?e.align[r]:e.align[0]:e.align;if(\"number\"==typeof n)return n;switch(n){case\"right\":case\"end\":return-t;case\"center\":case\"centre\":case\"middle\":return.5*-t}return 0}))),null==this.baseline&&null==t.baseline&&(t.baseline=0),null!=t.baseline&&(this.baseline=t.baseline,Array.isArray(this.baseline)||(this.baseline=[this.baseline]),this.baselineOffset=this.baseline.map((function(t,r){var n=(e.font[r]||e.font[0]).metrics,i=0;return i+=.5*n.bottom,i+=\"number\"==typeof t?t-n.baseline:-n[t],T.normalViewport||(i*=-1),i}))),null!=t.color)if(t.color||(t.color=\"transparent\"),\"string\"!=typeof t.color&&isNaN(t.color)){var H;if(\"number\"==typeof t.color[0]&&t.color.length>this.counts.length){var G=t.color.length;H=u.mallocUint8(G);for(var Y=(t.color.subarray||t.color.slice).bind(t.color),W=0;W<G;W+=4)H.set(l(Y(W,W+4),\"uint8\"),W)}else{var X=t.color.length;H=u.mallocUint8(4*X);for(var Z=0;Z<X;Z++)H.set(l(t.color[Z]||0,\"uint8\"),4*Z)}this.color=H}else this.color=l(t.color,\"uint8\");if(t.position||t.text||t.color||t.baseline||t.align||t.font||t.offset||t.opacity)if(this.color.length>4||this.baselineOffset.length>1||this.align&&this.align.length>1||this.fontAtlas.length>1||this.positionOffset.length>2){var J=Math.max(.5*this.position.length||0,.25*this.color.length||0,this.baselineOffset.length||0,this.alignOffset.length||0,this.font.length||0,this.opacity.length||0,.5*this.positionOffset.length||0);this.batch=Array(J);for(var K=0;K<this.batch.length;K++)this.batch[K]={count:this.counts.length>1?this.counts[K]:this.counts[0],offset:this.textOffsets.length>1?this.textOffsets[K]:this.textOffsets[0],color:this.color?this.color.length<=4?this.color:this.color.subarray(4*K,4*K+4):[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[K]:this.opacity,baseline:null!=this.baselineOffset[K]?this.baselineOffset[K]:this.baselineOffset[0],align:this.align?null!=this.alignOffset[K]?this.alignOffset[K]:this.alignOffset[0]:0,atlas:this.fontAtlas[K]||this.fontAtlas[0],positionOffset:this.positionOffset.length>2?this.positionOffset.subarray(2*K,2*K+2):this.positionOffset}}else this.count?this.batch=[{count:this.count,offset:0,color:this.color||[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[0]:this.opacity,baseline:this.baselineOffset[0],align:this.alignOffset?this.alignOffset[0]:0,atlas:this.fontAtlas[0],positionOffset:this.positionOffset}]:this.batch=[]},T.prototype.destroy=function(){},T.prototype.kerning=!0,T.prototype.position={constant:new Float32Array(2)},T.prototype.translate=null,T.prototype.scale=null,T.prototype.font=null,T.prototype.text=\"\",T.prototype.positionOffset=[0,0],T.prototype.opacity=1,T.prototype.color=new Uint8Array([0,0,0,255]),T.prototype.alignOffset=[0,0],T.normalViewport=!1,T.maxAtlasSize=1024,T.atlasCanvas=document.createElement(\"canvas\"),T.atlasContext=T.atlasCanvas.getContext(\"2d\",{alpha:!1}),T.baseFontSize=64,T.fonts={},e.exports=T},{\"bit-twiddle\":97,\"color-normalize\":125,\"css-font\":144,\"detect-kerning\":172,\"es6-weak-map\":233,\"flatten-vertex-data\":244,\"font-atlas\":245,\"font-measure\":246,\"gl-util/context\":354,\"is-plain-obj\":469,\"object-assign\":499,\"parse-rect\":504,\"parse-unit\":506,\"pick-by-alias\":511,regl:540,\"to-px\":578,\"typedarray-pool\":595}],353:[function(t,e,r){\"use strict\";var n=t(\"ndarray\"),i=t(\"ndarray-ops\"),a=t(\"typedarray-pool\");e.exports=function(t){if(arguments.length<=1)throw new Error(\"gl-texture2d: Missing arguments for texture2d constructor\");o||c(t);if(\"number\"==typeof arguments[1])return v(t,arguments[1],arguments[2],arguments[3]||t.RGBA,arguments[4]||t.UNSIGNED_BYTE);if(Array.isArray(arguments[1]))return v(t,0|arguments[1][0],0|arguments[1][1],arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(\"object\"==typeof arguments[1]){var e=arguments[1],r=u(e)?e:e.raw;if(r)return y(t,r,0|e.width,0|e.height,arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(e.shape&&e.data&&e.stride)return x(t,e)}throw new Error(\"gl-texture2d: Invalid arguments for texture2d constructor\")};var o=null,s=null,l=null;function c(t){o=[t.LINEAR,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_NEAREST],s=[t.NEAREST,t.LINEAR,t.NEAREST_MIPMAP_NEAREST,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_LINEAR],l=[t.REPEAT,t.CLAMP_TO_EDGE,t.MIRRORED_REPEAT]}function u(t){return\"undefined\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\"undefined\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\"undefined\"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement||\"undefined\"!=typeof ImageData&&t instanceof ImageData}var f=function(t,e){i.muls(t,e,255)};function h(t,e,r){var n=t.gl,i=n.getParameter(n.MAX_TEXTURE_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-texture2d: Invalid texture size\");return t._shape=[e,r],t.bind(),n.texImage2D(n.TEXTURE_2D,0,t.format,e,r,0,t.format,t.type,null),t._mipLevels=[0],t}function p(t,e,r,n,i,a){this.gl=t,this.handle=e,this.format=i,this.type=a,this._shape=[r,n],this._mipLevels=[0],this._magFilter=t.NEAREST,this._minFilter=t.NEAREST,this._wrapS=t.CLAMP_TO_EDGE,this._wrapT=t.CLAMP_TO_EDGE,this._anisoSamples=1;var o=this,s=[this._wrapS,this._wrapT];Object.defineProperties(s,[{get:function(){return o._wrapS},set:function(t){return o.wrapS=t}},{get:function(){return o._wrapT},set:function(t){return o.wrapT=t}}]),this._wrapVector=s;var l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}var d=p.prototype;function g(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function m(t){var e=t.createTexture();return t.bindTexture(t.TEXTURE_2D,e),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),e}function v(t,e,r,n,i){var a=t.getParameter(t.MAX_TEXTURE_SIZE);if(e<0||e>a||r<0||r>a)throw new Error(\"gl-texture2d: Invalid texture shape\");if(i===t.FLOAT&&!t.getExtension(\"OES_texture_float\"))throw new Error(\"gl-texture2d: Floating point textures not supported on this platform\");var o=m(t);return t.texImage2D(t.TEXTURE_2D,0,n,e,r,0,n,i,null),new p(t,o,e,r,n,i)}function y(t,e,r,n,i,a){var o=m(t);return t.texImage2D(t.TEXTURE_2D,0,i,i,a,e),new p(t,o,r,n,i,a)}function x(t,e){var r=e.dtype,o=e.shape.slice(),s=t.getParameter(t.MAX_TEXTURE_SIZE);if(o[0]<0||o[0]>s||o[1]<0||o[1]>s)throw new Error(\"gl-texture2d: Invalid texture size\");var l=g(o,e.stride.slice()),c=0;\"float32\"===r?c=t.FLOAT:\"float64\"===r?(c=t.FLOAT,l=!1,r=\"float32\"):\"uint8\"===r?c=t.UNSIGNED_BYTE:(c=t.UNSIGNED_BYTE,l=!1,r=\"uint8\");var u,h,d=0;if(2===o.length)d=t.LUMINANCE,o=[o[0],o[1],1],e=n(e.data,o,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==o.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===o[2])d=t.ALPHA;else if(2===o[2])d=t.LUMINANCE_ALPHA;else if(3===o[2])d=t.RGB;else{if(4!==o[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");d=t.RGBA}}c!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(c=t.UNSIGNED_BYTE,l=!1);var v=e.size;if(l)u=0===e.offset&&e.data.length===v?e.data:e.data.subarray(e.offset,e.offset+v);else{var y=[o[2],o[2]*o[0],1];h=a.malloc(v,r);var 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strict\";e.exports=function(t,e){var r=t.length;if(0===r)throw new Error(\"Must have at least d+1 points\");var i=t[0].length;if(r<=i)throw new Error(\"Must input at least d+1 points\");var o=t.slice(0,i+1),s=n.apply(void 0,o);if(0===s)throw new Error(\"Input not in general position\");for(var l=new Array(i+1),u=0;u<=i;++u)l[u]=u;s<0&&(l[0]=1,l[1]=0);var f=new a(l,new Array(i+1),!1),h=f.adjacent,p=new Array(i+2);for(u=0;u<=i;++u){for(var d=l.slice(),g=0;g<=i;++g)g===u&&(d[g]=-1);var m=d[0];d[0]=d[1],d[1]=m;var v=new a(d,new Array(i+1),!0);h[u]=v,p[u]=v}p[i+1]=f;for(u=0;u<=i;++u){d=h[u].vertices;var y=h[u].adjacent;for(g=0;g<=i;++g){var x=d[g];if(x<0)y[g]=f;else for(var b=0;b<=i;++b)h[b].vertices.indexOf(x)<0&&(y[g]=h[b])}}var _=new c(i,o,p),w=!!e;for(u=i+1;u<r;++u)_.insert(t[u],w);return _.boundary()};var n=t(\"robust-orientation\"),i=t(\"simplicial-complex\").compareCells;function a(t,e,r){this.vertices=t,this.adjacent=e,this.boundary=r,this.lastVisited=-1}function o(t,e,r){this.vertices=t,this.cell=e,this.index=r}function s(t,e){return i(t.vertices,e.vertices)}a.prototype.flip=function(){var t=this.vertices[0];this.vertices[0]=this.vertices[1],this.vertices[1]=t;var e=this.adjacent[0];this.adjacent[0]=this.adjacent[1],this.adjacent[1]=e};var l=[];function c(t,e,r){this.dimension=t,this.vertices=e,this.simplices=r,this.interior=r.filter((function(t){return!t.boundary})),this.tuple=new Array(t+1);for(var i=0;i<=t;++i)this.tuple[i]=this.vertices[i];var a=l[t];a||(a=l[t]=function(t){for(var e=[\"function orient(){var tuple=this.tuple;return test(\"],r=0;r<=t;++r)r>0&&e.push(\",\"),e.push(\"tuple[\",r,\"]\");e.push(\")}return orient\");var i=new Function(\"test\",e.join(\"\")),a=n[t+1];return a||(a=n),i(a)}(t)),this.orient=a}var u=c.prototype;u.handleBoundaryDegeneracy=function(t,e){var r=this.dimension,n=this.vertices.length-1,i=this.tuple,a=this.vertices,o=[t];for(t.lastVisited=-n;o.length>0;){(t=o.pop()).vertices;for(var s=t.adjacent,l=0;l<=r;++l){var c=s[l];if(c.boundary&&!(c.lastVisited<=-n)){for(var u=c.vertices,f=0;f<=r;++f){var h=u[f];i[f]=h<0?e:a[h]}var p=this.orient();if(p>0)return c;c.lastVisited=-n,0===p&&o.push(c)}}}return null},u.walk=function(t,e){var r=this.vertices.length-1,n=this.dimension,i=this.vertices,a=this.tuple,o=e?this.interior.length*Math.random()|0:this.interior.length-1,s=this.interior[o];t:for(;!s.boundary;){for(var l=s.vertices,c=s.adjacent,u=0;u<=n;++u)a[u]=i[l[u]];s.lastVisited=r;for(u=0;u<=n;++u){var f=c[u];if(!(f.lastVisited>=r)){var h=a[u];a[u]=t;var p=this.orient();if(a[u]=h,p<0){s=f;continue t}f.boundary?f.lastVisited=-r:f.lastVisited=r}}return}return s},u.addPeaks=function(t,e){var r=this.vertices.length-1,n=this.dimension,i=this.vertices,l=this.tuple,c=this.interior,u=this.simplices,f=[e];e.lastVisited=r,e.vertices[e.vertices.indexOf(-1)]=r,e.boundary=!1,c.push(e);for(var h=[];f.length>0;){var p=(e=f.pop()).vertices,d=e.adjacent,g=p.indexOf(r);if(!(g<0))for(var m=0;m<=n;++m)if(m!==g){var v=d[m];if(v.boundary&&!(v.lastVisited>=r)){var y=v.vertices;if(v.lastVisited!==-r){for(var x=0,b=0;b<=n;++b)y[b]<0?(x=b,l[b]=t):l[b]=i[y[b]];if(this.orient()>0){y[x]=r,v.boundary=!1,c.push(v),f.push(v),v.lastVisited=r;continue}v.lastVisited=-r}var _=v.adjacent,w=p.slice(),T=d.slice(),k=new a(w,T,!0);u.push(k);var M=_.indexOf(e);if(!(M<0)){_[M]=k,T[g]=v,w[m]=-1,T[m]=e,d[m]=k,k.flip();for(b=0;b<=n;++b){var A=w[b];if(!(A<0||A===r)){for(var S=new Array(n-1),E=0,C=0;C<=n;++C){var L=w[C];L<0||C===b||(S[E++]=L)}h.push(new o(S,k,b))}}}}}}h.sort(s);for(m=0;m+1<h.length;m+=2){var I=h[m],P=h[m+1],z=I.index,O=P.index;z<0||O<0||(I.cell.adjacent[I.index]=P.cell,P.cell.adjacent[P.index]=I.cell)}},u.insert=function(t,e){var r=this.vertices;r.push(t);var n=this.walk(t,e);if(n){for(var i=this.dimension,a=this.tuple,o=0;o<=i;++o){var s=n.vertices[o];a[o]=s<0?t:r[s]}var l=this.orient(a);l<0||(0!==l||(n=this.handleBoundaryDegeneracy(n,t)))&&this.addPeaks(t,n)}},u.boundary=function(){for(var t=this.dimension,e=[],r=this.simplices,n=r.length,i=0;i<n;++i){var a=r[i];if(a.boundary){for(var o=new Array(t),s=a.vertices,l=0,c=0,u=0;u<=t;++u)s[u]>=0?o[l++]=s[u]:c=1&u;if(c===(1&t)){var f=o[0];o[0]=o[1],o[1]=f}e.push(o)}}return e}},{\"robust-orientation\":548,\"simplicial-complex\":558}],460:[function(t,e,r){\"use strict\";var n=t(\"binary-search-bounds\");function i(t,e,r,n,i){this.mid=t,this.left=e,this.right=r,this.leftPoints=n,this.rightPoints=i,this.count=(e?e.count:0)+(r?r.count:0)+n.length}e.exports=function(t){if(!t||0===t.length)return new v(null);return new v(m(t))};var a=i.prototype;function o(t,e){t.mid=e.mid,t.left=e.left,t.right=e.right,t.leftPoints=e.leftPoints,t.rightPoints=e.rightPoints,t.count=e.count}function s(t,e){var r=m(e);t.mid=r.mid,t.left=r.left,t.right=r.right,t.leftPoints=r.leftPoints,t.rightPoints=r.rightPoints,t.count=r.count}function l(t,e){var r=t.intervals([]);r.push(e),s(t,r)}function c(t,e){var r=t.intervals([]),n=r.indexOf(e);return n<0?0:(r.splice(n,1),s(t,r),1)}function u(t,e,r){for(var n=0;n<t.length&&t[n][0]<=e;++n){var i=r(t[n]);if(i)return i}}function f(t,e,r){for(var n=t.length-1;n>=0&&t[n][1]>=e;--n){var i=r(t[n]);if(i)return i}}function h(t,e){for(var r=0;r<t.length;++r){var n=e(t[r]);if(n)return n}}function p(t,e){return t-e}function d(t,e){var r=t[0]-e[0];return r||t[1]-e[1]}function g(t,e){var r=t[1]-e[1];return r||t[0]-e[0]}function m(t){if(0===t.length)return null;for(var e=[],r=0;r<t.length;++r)e.push(t[r][0],t[r][1]);e.sort(p);var n=e[e.length>>1],a=[],o=[],s=[];for(r=0;r<t.length;++r){var l=t[r];l[1]<n?a.push(l):n<l[0]?o.push(l):s.push(l)}var c=s,u=s.slice();return c.sort(d),u.sort(g),new i(n,m(a),m(o),c,u)}function v(t){this.root=t}a.intervals=function(t){return t.push.apply(t,this.leftPoints),this.left&&this.left.intervals(t),this.right&&this.right.intervals(t),t},a.insert=function(t){var e=this.count-this.leftPoints.length;if(this.count+=1,t[1]<this.mid)this.left?4*(this.left.count+1)>3*(e+1)?l(this,t):this.left.insert(t):this.left=m([t]);else if(t[0]>this.mid)this.right?4*(this.right.count+1)>3*(e+1)?l(this,t):this.right.insert(t):this.right=m([t]);else{var r=n.ge(this.leftPoints,t,d),i=n.ge(this.rightPoints,t,g);this.leftPoints.splice(r,0,t),this.rightPoints.splice(i,0,t)}},a.remove=function(t){var e=this.count-this.leftPoints;if(t[1]<this.mid)return this.left?4*(this.right?this.right.count:0)>3*(e-1)?c(this,t):2===(s=this.left.remove(t))?(this.left=null,this.count-=1,1):(1===s&&(this.count-=1),s):0;if(t[0]>this.mid)return this.right?4*(this.left?this.left.count:0)>3*(e-1)?c(this,t):2===(s=this.right.remove(t))?(this.right=null,this.count-=1,1):(1===s&&(this.count-=1),s):0;if(1===this.count)return this.leftPoints[0]===t?2:0;if(1===this.leftPoints.length&&this.leftPoints[0]===t){if(this.left&&this.right){for(var r=this,i=this.left;i.right;)r=i,i=i.right;if(r===this)i.right=this.right;else{var a=this.left,s=this.right;r.count-=i.count,r.right=i.left,i.left=a,i.right=s}o(this,i),this.count=(this.left?this.left.count:0)+(this.right?this.right.count:0)+this.leftPoints.length}else this.left?o(this,this.left):o(this,this.right);return 1}for(a=n.ge(this.leftPoints,t,d);a<this.leftPoints.length&&this.leftPoints[a][0]===t[0];++a)if(this.leftPoints[a]===t){this.count-=1,this.leftPoints.splice(a,1);for(s=n.ge(this.rightPoints,t,g);s<this.rightPoints.length&&this.rightPoints[s][1]===t[1];++s)if(this.rightPoints[s]===t)return this.rightPoints.splice(s,1),1}return 0},a.queryPoint=function(t,e){if(t<this.mid){if(this.left)if(r=this.left.queryPoint(t,e))return r;return u(this.leftPoints,t,e)}if(t>this.mid){var r;if(this.right)if(r=this.right.queryPoint(t,e))return r;return f(this.rightPoints,t,e)}return h(this.leftPoints,e)},a.queryInterval=function(t,e,r){var n;if(t<this.mid&&this.left&&(n=this.left.queryInterval(t,e,r)))return n;if(e>this.mid&&this.right&&(n=this.right.queryInterval(t,e,r)))return n;return e<this.mid?u(this.leftPoints,e,r):t>this.mid?f(this.rightPoints,t,r):h(this.leftPoints,r)};var y=v.prototype;y.insert=function(t){this.root?this.root.insert(t):this.root=new i(t[0],null,null,[t],[t])},y.remove=function(t){if(this.root){var e=this.root.remove(t);return 2===e&&(this.root=null),0!==e}return!1},y.queryPoint=function(t,e){if(this.root)return this.root.queryPoint(t,e)},y.queryInterval=function(t,e,r){if(t<=e&&this.root)return this.root.queryInterval(t,e,r)},Object.defineProperty(y,\"count\",{get:function(){return this.root?this.root.count:0}}),Object.defineProperty(y,\"intervals\",{get:function(){return this.root?this.root.intervals([]):[]}})},{\"binary-search-bounds\":461}],461:[function(t,e,r){arguments[4][243][0].apply(r,arguments)},{dup:243}],462:[function(t,e,r){\"use strict\";e.exports=function(t,e){e=e||new Array(t.length);for(var r=0;r<t.length;++r)e[t[r]]=r;return e}},{}],463:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=new Array(t),r=0;r<t;++r)e[r]=r;return e}},{}],464:[function(t,e,r){e.exports=!0},{}],465:[function(t,e,r){function n(t){return!!t.constructor&&\"function\"==typeof t.constructor.isBuffer&&t.constructor.isBuffer(t)}\n",
       "/*!\n",
       " * Determine if an object is a Buffer\n",
       " *\n",
       " * @author   Feross Aboukhadijeh <https://feross.org>\n",
       " * @license  MIT\n",
       " */\n",
       "e.exports=function(t){return null!=t&&(n(t)||function(t){return\"function\"==typeof t.readFloatLE&&\"function\"==typeof t.slice&&n(t.slice(0,0))}(t)||!!t._isBuffer)}},{}],466:[function(t,e,r){\"use strict\";e.exports=\"undefined\"!=typeof navigator&&(/MSIE/.test(navigator.userAgent)||/Trident\\//.test(navigator.appVersion))},{}],467:[function(t,e,r){\"use strict\";e.exports=a,e.exports.isMobile=a,e.exports.default=a;var n=/(android|bb\\d+|meego).+mobile|avantgo|bada\\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\\/|plucker|pocket|psp|series[46]0|symbian|treo|up\\.(browser|link)|vodafone|wap|windows (ce|phone)|xda|xiino/i,i=/(android|bb\\d+|meego).+mobile|avantgo|bada\\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\\/|plucker|pocket|psp|series[46]0|symbian|treo|up\\.(browser|link)|vodafone|wap|windows (ce|phone)|xda|xiino|android|ipad|playbook|silk/i;function a(t){t||(t={});var e=t.ua;if(e||\"undefined\"==typeof navigator||(e=navigator.userAgent),e&&e.headers&&\"string\"==typeof e.headers[\"user-agent\"]&&(e=e.headers[\"user-agent\"]),\"string\"!=typeof e)return!1;var r=t.tablet?i.test(e):n.test(e);return!r&&t.tablet&&t.featureDetect&&navigator&&navigator.maxTouchPoints>1&&-1!==e.indexOf(\"Macintosh\")&&-1!==e.indexOf(\"Safari\")&&(r=!0),r}},{}],468:[function(t,e,r){\"use strict\";e.exports=function(t){var e=typeof t;return null!==t&&(\"object\"===e||\"function\"===e)}},{}],469:[function(t,e,r){\"use strict\";var n=Object.prototype.toString;e.exports=function(t){var e;return\"[object Object]\"===n.call(t)&&(null===(e=Object.getPrototypeOf(t))||e===Object.getPrototypeOf({}))}},{}],470:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e,r=t.length,n=0;n<r;n++)if(((e=t.charCodeAt(n))<9||e>13)&&32!==e&&133!==e&&160!==e&&5760!==e&&6158!==e&&(e<8192||e>8205)&&8232!==e&&8233!==e&&8239!==e&&8287!==e&&8288!==e&&12288!==e&&65279!==e)return!1;return!0}},{}],471:[function(t,e,r){\"use strict\";e.exports=function(t){return\"string\"==typeof t&&(t=t.trim(),!!(/^[mzlhvcsqta]\\s*[-+.0-9][^mlhvzcsqta]+/i.test(t)&&/[\\dz]$/i.test(t)&&t.length>4))}},{}],472:[function(t,e,r){e.exports=function(t,e,r){return t*(1-r)+e*r}},{}],473:[function(t,e,r){!function(t,n){\"object\"==typeof r&&\"undefined\"!=typeof e?e.exports=n():(t=t||self).mapboxgl=n()}(this,(function(){\"use strict\";var t,e,r;function n(n,i){if(t)if(e){var a=\"var sharedChunk = {}; (\"+t+\")(sharedChunk); (\"+e+\")(sharedChunk);\",o={};t(o),(r=i(o)).workerUrl=window.URL.createObjectURL(new Blob([a],{type:\"text/javascript\"}))}else e=i;else t=i}return n(0,(function(t){function e(t,e){return t(e={exports:{}},e.exports),e.exports}var r=n;function n(t,e,r,n){this.cx=3*t,this.bx=3*(r-t)-this.cx,this.ax=1-this.cx-this.bx,this.cy=3*e,this.by=3*(n-e)-this.cy,this.ay=1-this.cy-this.by,this.p1x=t,this.p1y=n,this.p2x=r,this.p2y=n}n.prototype.sampleCurveX=function(t){return((this.ax*t+this.bx)*t+this.cx)*t},n.prototype.sampleCurveY=function(t){return((this.ay*t+this.by)*t+this.cy)*t},n.prototype.sampleCurveDerivativeX=function(t){return(3*this.ax*t+2*this.bx)*t+this.cx},n.prototype.solveCurveX=function(t,e){var r,n,i,a,o;for(void 0===e&&(e=1e-6),i=t,o=0;o<8;o++){if(a=this.sampleCurveX(i)-t,Math.abs(a)<e)return i;var s=this.sampleCurveDerivativeX(i);if(Math.abs(s)<1e-6)break;i-=a/s}if((i=t)<(r=0))return r;if(i>(n=1))return n;for(;r<n;){if(a=this.sampleCurveX(i),Math.abs(a-t)<e)return i;t>a?r=i:n=i,i=.5*(n-r)+r}return i},n.prototype.solve=function(t,e){return this.sampleCurveY(this.solveCurveX(t,e))};var i=a;function a(t,e){this.x=t,this.y=e}function o(t,e,n,i){var a=new r(t,e,n,i);return function(t){return 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r={transparent:[0,0,0,0],aliceblue:[240,248,255,1],antiquewhite:[250,235,215,1],aqua:[0,255,255,1],aquamarine:[127,255,212,1],azure:[240,255,255,1],beige:[245,245,220,1],bisque:[255,228,196,1],black:[0,0,0,1],blanchedalmond:[255,235,205,1],blue:[0,0,255,1],blueviolet:[138,43,226,1],brown:[165,42,42,1],burlywood:[222,184,135,1],cadetblue:[95,158,160,1],chartreuse:[127,255,0,1],chocolate:[210,105,30,1],coral:[255,127,80,1],cornflowerblue:[100,149,237,1],cornsilk:[255,248,220,1],crimson:[220,20,60,1],cyan:[0,255,255,1],darkblue:[0,0,139,1],darkcyan:[0,139,139,1],darkgoldenrod:[184,134,11,1],darkgray:[169,169,169,1],darkgreen:[0,100,0,1],darkgrey:[169,169,169,1],darkkhaki:[189,183,107,1],darkmagenta:[139,0,139,1],darkolivegreen:[85,107,47,1],darkorange:[255,140,0,1],darkorchid:[153,50,204,1],darkred:[139,0,0,1],darksalmon:[233,150,122,1],darkseagreen:[143,188,143,1],darkslateblue:[72,61,139,1],darkslategray:[47,79,79,1],darkslategrey:[47,79,79,1],darkturquoise:[0,206,209,1],darkviolet:[148,0,211,1],deeppink:[255,20,147,1],deepskyblue:[0,191,255,1],dimgray:[105,105,105,1],dimgrey:[105,105,105,1],dodgerblue:[30,144,255,1],firebrick:[178,34,34,1],floralwhite:[255,250,240,1],forestgreen:[34,139,34,1],fuchsia:[255,0,255,1],gainsboro:[220,220,220,1],ghostwhite:[248,248,255,1],gold:[255,215,0,1],goldenrod:[218,165,32,1],gray:[128,128,128,1],green:[0,128,0,1],greenyellow:[173,255,47,1],grey:[128,128,128,1],honeydew:[240,255,240,1],hotpink:[255,105,180,1],indianred:[205,92,92,1],indigo:[75,0,130,1],ivory:[255,255,240,1],khaki:[240,230,140,1],lavender:[230,230,250,1],lavenderblush:[255,240,245,1],lawngreen:[124,252,0,1],lemonchiffon:[255,250,205,1],lightblue:[173,216,230,1],lightcoral:[240,128,128,1],lightcyan:[224,255,255,1],lightgoldenrodyellow:[250,250,210,1],lightgray:[211,211,211,1],lightgreen:[144,238,144,1],lightgrey:[211,211,211,1],lightpink:[255,182,193,1],lightsalmon:[255,160,122,1],lightseagreen:[32,178,170,1],lightskyblue:[135,206,250,1],lightslategray:[119,136,153,1],lightslategrey:[119,136,153,1],lightsteelblue:[176,196,222,1],lightyellow:[255,255,224,1],lime:[0,255,0,1],limegreen:[50,205,50,1],linen:[250,240,230,1],magenta:[255,0,255,1],maroon:[128,0,0,1],mediumaquamarine:[102,205,170,1],mediumblue:[0,0,205,1],mediumorchid:[186,85,211,1],mediumpurple:[147,112,219,1],mediumseagreen:[60,179,113,1],mediumslateblue:[123,104,238,1],mediumspringgreen:[0,250,154,1],mediumturquoise:[72,209,204,1],mediumvioletred:[199,21,133,1],midnightblue:[25,25,112,1],mintcream:[245,255,250,1],mistyrose:[255,228,225,1],moccasin:[255,228,181,1],navajowhite:[255,222,173,1],navy:[0,0,128,1],oldlace:[253,245,230,1],olive:[128,128,0,1],olivedrab:[107,142,35,1],orange:[255,165,0,1],orangered:[255,69,0,1],orchid:[218,112,214,1],palegoldenrod:[238,232,170,1],palegreen:[152,251,152,1],paleturquoise:[175,238,238,1],palevioletred:[219,112,147,1],papayawhip:[255,239,213,1],peachpuff:[255,218,185,1],peru:[205,133,63,1],pink:[255,192,203,1],plum:[221,160,221,1],powderblue:[176,224,230,1],purple:[128,0,128,1],rebeccapurple:[102,51,153,1],red:[255,0,0,1],rosybrown:[188,143,143,1],royalblue:[65,105,225,1],saddlebrown:[139,69,19,1],salmon:[250,128,114,1],sandybrown:[244,164,96,1],seagreen:[46,139,87,1],seashell:[255,245,238,1],sienna:[160,82,45,1],silver:[192,192,192,1],skyblue:[135,206,235,1],slateblue:[106,90,205,1],slategray:[112,128,144,1],slategrey:[112,128,144,1],snow:[255,250,250,1],springgreen:[0,255,127,1],steelblue:[70,130,180,1],tan:[210,180,140,1],teal:[0,128,128,1],thistle:[216,191,216,1],tomato:[255,99,71,1],turquoise:[64,224,208,1],violet:[238,130,238,1],wheat:[245,222,179,1],white:[255,255,255,1],whitesmoke:[245,245,245,1],yellow:[255,255,0,1],yellowgreen:[154,205,50,1]};function n(t){return(t=Math.round(t))<0?0:t>255?255:t}function i(t){return n(\"%\"===t[t.length-1]?parseFloat(t)/100*255:parseInt(t))}function a(t){return(e=\"%\"===t[t.length-1]?parseFloat(t)/100:parseFloat(t))<0?0:e>1?1:e;var e}function o(t,e,r){return r<0?r+=1:r>1&&(r-=1),6*r<1?t+(e-t)*r*6:2*r<1?e:3*r<2?t+(e-t)*(2/3-r)*6:t}try{e.parseCSSColor=function(t){var e,s=t.replace(/ /g,\"\").toLowerCase();if(s in r)return r[s].slice();if(\"#\"===s[0])return 4===s.length?(e=parseInt(s.substr(1),16))>=0&&e<=4095?[(3840&e)>>4|(3840&e)>>8,240&e|(240&e)>>4,15&e|(15&e)<<4,1]:null:7===s.length&&(e=parseInt(s.substr(1),16))>=0&&e<=16777215?[(16711680&e)>>16,(65280&e)>>8,255&e,1]:null;var l=s.indexOf(\"(\"),c=s.indexOf(\")\");if(-1!==l&&c+1===s.length){var u=s.substr(0,l),f=s.substr(l+1,c-(l+1)).split(\",\"),h=1;switch(u){case\"rgba\":if(4!==f.length)return null;h=a(f.pop());case\"rgb\":return 3!==f.length?null:[i(f[0]),i(f[1]),i(f[2]),h];case\"hsla\":if(4!==f.length)return 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Qt=function(t,e,r){this.sensitivity=t?e?\"variant\":\"case\":e?\"accent\":\"base\",this.locale=r,this.collator=new Intl.Collator(this.locale?this.locale:[],{sensitivity:this.sensitivity,usage:\"search\"})};Qt.prototype.compare=function(t,e){return this.collator.compare(t,e)},Qt.prototype.resolvedLocale=function(){return new Intl.Collator(this.locale?this.locale:[]).resolvedOptions().locale};var $t=function(t,e,r,n,i){this.text=t,this.image=e,this.scale=r,this.fontStack=n,this.textColor=i},te=function(t){this.sections=t};te.fromString=function(t){return new te([new $t(t,null,null,null,null)])},te.prototype.isEmpty=function(){return 0===this.sections.length||!this.sections.some((function(t){return 0!==t.text.length||t.image&&0!==t.image.name.length}))},te.factory=function(t){return t instanceof te?t:te.fromString(t)},te.prototype.toString=function(){return 0===this.sections.length?\"\":this.sections.map((function(t){return t.text})).join(\"\")},te.prototype.serialize=function(){for(var t=[\"format\"],e=0,r=this.sections;e<r.length;e+=1){var n=r[e];if(n.image)t.push([\"image\",n.image.name]);else{t.push(n.text);var i={};n.fontStack&&(i[\"text-font\"]=[\"literal\",n.fontStack.split(\",\")]),n.scale&&(i[\"font-scale\"]=n.scale),n.textColor&&(i[\"text-color\"]=[\"rgba\"].concat(n.textColor.toArray())),t.push(i)}}return t};var ee=function(t){this.name=t.name,this.available=t.available};function re(t,e,r,n){return\"number\"==typeof t&&t>=0&&t<=255&&\"number\"==typeof e&&e>=0&&e<=255&&\"number\"==typeof r&&r>=0&&r<=255?void 0===n||\"number\"==typeof n&&n>=0&&n<=1?null:\"Invalid rgba value [\"+[t,e,r,n].join(\", \")+\"]: 'a' must be between 0 and 1.\":\"Invalid rgba value [\"+(\"number\"==typeof n?[t,e,r,n]:[t,e,r]).join(\", \")+\"]: 'r', 'g', and 'b' must be between 0 and 255.\"}function ne(t){if(null===t)return!0;if(\"string\"==typeof t)return!0;if(\"boolean\"==typeof t)return!0;if(\"number\"==typeof t)return!0;if(t instanceof Kt)return!0;if(t instanceof Qt)return!0;if(t instanceof te)return!0;if(t instanceof ee)return!0;if(Array.isArray(t)){for(var e=0,r=t;e<r.length;e+=1)if(!ne(r[e]))return!1;return!0}if(\"object\"==typeof t){for(var n in t)if(!ne(t[n]))return!1;return!0}return!1}function ie(t){if(null===t)return Ot;if(\"string\"==typeof t)return Rt;if(\"boolean\"==typeof t)return Ft;if(\"number\"==typeof t)return Dt;if(t instanceof Kt)return Bt;if(t instanceof Qt)return Ut;if(t instanceof te)return Vt;if(t instanceof ee)return qt;if(Array.isArray(t)){for(var e,r=t.length,n=0,i=t;n<i.length;n+=1){var a=ie(i[n]);if(e){if(e===a)continue;e=jt;break}e=a}return Ht(e||jt,r)}return Nt}function ae(t){var e=typeof t;return null===t?\"\":\"string\"===e||\"number\"===e||\"boolean\"===e?String(t):t instanceof Kt||t instanceof te||t instanceof ee?t.toString():JSON.stringify(t)}ee.prototype.toString=function(){return this.name},ee.fromString=function(t){return t?new ee({name:t,available:!1}):null},ee.prototype.serialize=function(){return[\"image\",this.name]};var oe=function(t,e){this.type=t,this.value=e};oe.parse=function(t,e){if(2!==t.length)return e.error(\"'literal' expression requires exactly one argument, but found \"+(t.length-1)+\" instead.\");if(!ne(t[1]))return e.error(\"invalid value\");var r=t[1],n=ie(r),i=e.expectedType;return\"array\"!==n.kind||0!==n.N||!i||\"array\"!==i.kind||\"number\"==typeof i.N&&0!==i.N||(n=i),new oe(n,r)},oe.prototype.evaluate=function(){return this.value},oe.prototype.eachChild=function(){},oe.prototype.outputDefined=function(){return!0},oe.prototype.serialize=function(){return\"array\"===this.type.kind||\"object\"===this.type.kind?[\"literal\",this.value]:this.value instanceof Kt?[\"rgba\"].concat(this.value.toArray()):this.value instanceof te?this.value.serialize():this.value};var se=function(t){this.name=\"ExpressionEvaluationError\",this.message=t};se.prototype.toJSON=function(){return this.message};var le={string:Rt,number:Dt,boolean:Ft,object:Nt},ce=function(t,e){this.type=t,this.args=e};ce.parse=function(t,e){if(t.length<2)return e.error(\"Expected at least one argument.\");var r,n=1,i=t[0];if(\"array\"===i){var a,o;if(t.length>2){var s=t[1];if(\"string\"!=typeof s||!(s in le)||\"object\"===s)return e.error('The item type argument of \"array\" must be one of string, number, boolean',1);a=le[s],n++}else a=jt;if(t.length>3){if(null!==t[2]&&(\"number\"!=typeof t[2]||t[2]<0||t[2]!==Math.floor(t[2])))return e.error('The length argument to \"array\" must be a positive integer literal',2);o=t[2],n++}r=Ht(a,o)}else r=le[i];for(var l=[];n<t.length;n++){var c=e.parse(t[n],n,jt);if(!c)return null;l.push(c)}return new ce(r,l)},ce.prototype.evaluate=function(t){for(var e=0;e<this.args.length;e++){var r=this.args[e].evaluate(t);if(!Wt(this.type,ie(r)))return r;if(e===this.args.length-1)throw new se(\"Expected value to be of type \"+Gt(this.type)+\", but found \"+Gt(ie(r))+\" instead.\")}return null},ce.prototype.eachChild=function(t){this.args.forEach(t)},ce.prototype.outputDefined=function(){return this.args.every((function(t){return t.outputDefined()}))},ce.prototype.serialize=function(){var t=this.type,e=[t.kind];if(\"array\"===t.kind){var r=t.itemType;if(\"string\"===r.kind||\"number\"===r.kind||\"boolean\"===r.kind){e.push(r.kind);var n=t.N;(\"number\"==typeof n||this.args.length>1)&&e.push(n)}}return e.concat(this.args.map((function(t){return t.serialize()})))};var ue=function(t){this.type=Vt,this.sections=t};ue.parse=function(t,e){if(t.length<2)return e.error(\"Expected at least one argument.\");var r=t[1];if(!Array.isArray(r)&&\"object\"==typeof r)return e.error(\"First argument must be an image or text section.\");for(var n=[],i=!1,a=1;a<=t.length-1;++a){var o=t[a];if(i&&\"object\"==typeof o&&!Array.isArray(o)){i=!1;var s=null;if(o[\"font-scale\"]&&!(s=e.parse(o[\"font-scale\"],1,Dt)))return null;var l=null;if(o[\"text-font\"]&&!(l=e.parse(o[\"text-font\"],1,Ht(Rt))))return null;var c=null;if(o[\"text-color\"]&&!(c=e.parse(o[\"text-color\"],1,Bt)))return null;var u=n[n.length-1];u.scale=s,u.font=l,u.textColor=c}else{var f=e.parse(t[a],1,jt);if(!f)return null;var h=f.type.kind;if(\"string\"!==h&&\"value\"!==h&&\"null\"!==h&&\"resolvedImage\"!==h)return e.error(\"Formatted text type must be 'string', 'value', 'image' or 'null'.\");i=!0,n.push({content:f,scale:null,font:null,textColor:null})}}return new ue(n)},ue.prototype.evaluate=function(t){return new te(this.sections.map((function(e){var r=e.content.evaluate(t);return ie(r)===qt?new $t(\"\",r,null,null,null):new $t(ae(r),null,e.scale?e.scale.evaluate(t):null,e.font?e.font.evaluate(t).join(\",\"):null,e.textColor?e.textColor.evaluate(t):null)})))},ue.prototype.eachChild=function(t){for(var e=0,r=this.sections;e<r.length;e+=1){var n=r[e];t(n.content),n.scale&&t(n.scale),n.font&&t(n.font),n.textColor&&t(n.textColor)}},ue.prototype.outputDefined=function(){return!1},ue.prototype.serialize=function(){for(var t=[\"format\"],e=0,r=this.sections;e<r.length;e+=1){var n=r[e];t.push(n.content.serialize());var i={};n.scale&&(i[\"font-scale\"]=n.scale.serialize()),n.font&&(i[\"text-font\"]=n.font.serialize()),n.textColor&&(i[\"text-color\"]=n.textColor.serialize()),t.push(i)}return t};var fe=function(t){this.type=qt,this.input=t};fe.parse=function(t,e){if(2!==t.length)return e.error(\"Expected two arguments.\");var r=e.parse(t[1],1,Rt);return r?new fe(r):e.error(\"No image name provided.\")},fe.prototype.evaluate=function(t){var e=this.input.evaluate(t),r=ee.fromString(e);return r&&t.availableImages&&(r.available=t.availableImages.indexOf(e)>-1),r},fe.prototype.eachChild=function(t){t(this.input)},fe.prototype.outputDefined=function(){return!1},fe.prototype.serialize=function(){return[\"image\",this.input.serialize()]};var he={\"to-boolean\":Ft,\"to-color\":Bt,\"to-number\":Dt,\"to-string\":Rt},pe=function(t,e){this.type=t,this.args=e};pe.parse=function(t,e){if(t.length<2)return e.error(\"Expected at least one argument.\");var r=t[0];if((\"to-boolean\"===r||\"to-string\"===r)&&2!==t.length)return e.error(\"Expected one argument.\");for(var n=he[r],i=[],a=1;a<t.length;a++){var o=e.parse(t[a],a,jt);if(!o)return null;i.push(o)}return new pe(n,i)},pe.prototype.evaluate=function(t){if(\"boolean\"===this.type.kind)return Boolean(this.args[0].evaluate(t));if(\"color\"===this.type.kind){for(var e,r,n=0,i=this.args;n<i.length;n+=1){if(r=null,(e=i[n].evaluate(t))instanceof Kt)return e;if(\"string\"==typeof e){var a=t.parseColor(e);if(a)return a}else if(Array.isArray(e)&&!(r=e.length<3||e.length>4?\"Invalid rbga value \"+JSON.stringify(e)+\": expected an array containing either three or four numeric values.\":re(e[0],e[1],e[2],e[3])))return new Kt(e[0]/255,e[1]/255,e[2]/255,e[3])}throw new se(r||\"Could not parse color from value '\"+(\"string\"==typeof e?e:String(JSON.stringify(e)))+\"'\")}if(\"number\"===this.type.kind){for(var o=null,s=0,l=this.args;s<l.length;s+=1){if(null===(o=l[s].evaluate(t)))return 0;var c=Number(o);if(!isNaN(c))return c}throw new se(\"Could not convert \"+JSON.stringify(o)+\" to number.\")}return\"formatted\"===this.type.kind?te.fromString(ae(this.args[0].evaluate(t))):\"resolvedImage\"===this.type.kind?ee.fromString(ae(this.args[0].evaluate(t))):ae(this.args[0].evaluate(t))},pe.prototype.eachChild=function(t){this.args.forEach(t)},pe.prototype.outputDefined=function(){return this.args.every((function(t){return t.outputDefined()}))},pe.prototype.serialize=function(){if(\"formatted\"===this.type.kind)return new ue([{content:this.args[0],scale:null,font:null,textColor:null}]).serialize();if(\"resolvedImage\"===this.type.kind)return new fe(this.args[0]).serialize();var t=[\"to-\"+this.type.kind];return this.eachChild((function(e){t.push(e.serialize())})),t};var de=[\"Unknown\",\"Point\",\"LineString\",\"Polygon\"],ge=function(){this.globals=null,this.feature=null,this.featureState=null,this.formattedSection=null,this._parseColorCache={},this.availableImages=null,this.canonical=null};ge.prototype.id=function(){return this.feature&&\"id\"in this.feature?this.feature.id:null},ge.prototype.geometryType=function(){return this.feature?\"number\"==typeof this.feature.type?de[this.feature.type]:this.feature.type:null},ge.prototype.geometry=function(){return this.feature&&\"geometry\"in this.feature?this.feature.geometry:null},ge.prototype.canonicalID=function(){return this.canonical},ge.prototype.properties=function(){return this.feature&&this.feature.properties||{}},ge.prototype.parseColor=function(t){var e=this._parseColorCache[t];return e||(e=this._parseColorCache[t]=Kt.parse(t)),e};var me=function(t,e,r,n){this.name=t,this.type=e,this._evaluate=r,this.args=n};me.prototype.evaluate=function(t){return 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a=Ne(e,n),o=rr.interpolationFactor(this.interpolation,n,e[a],e[a+1]),s=r[a].evaluate(t),l=r[a+1].evaluate(t);return\"interpolate\"===this.operator?Ve[this.type.kind.toLowerCase()](s,l,o):\"interpolate-hcl\"===this.operator?tr.reverse(tr.interpolate(tr.forward(s),tr.forward(l),o)):$e.reverse($e.interpolate($e.forward(s),$e.forward(l),o))},rr.prototype.eachChild=function(t){t(this.input);for(var e=0,r=this.outputs;e<r.length;e+=1)t(r[e])},rr.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))},rr.prototype.serialize=function(){var t;t=\"linear\"===this.interpolation.name?[\"linear\"]:\"exponential\"===this.interpolation.name?1===this.interpolation.base?[\"linear\"]:[\"exponential\",this.interpolation.base]:[\"cubic-bezier\"].concat(this.interpolation.controlPoints);for(var e=[this.operator,t,this.input.serialize()],r=0;r<this.labels.length;r++)e.push(this.labels[r],this.outputs[r].serialize());return e};var ir=function(t,e){this.type=t,this.args=e};ir.parse=function(t,e){if(t.length<2)return e.error(\"Expectected at least one argument.\");var r=null,n=e.expectedType;n&&\"value\"!==n.kind&&(r=n);for(var i=[],a=0,o=t.slice(1);a<o.length;a+=1){var s=e.parse(o[a],1+i.length,r,void 0,{typeAnnotation:\"omit\"});if(!s)return null;r=r||s.type,i.push(s)}var l=n&&i.some((function(t){return Wt(n,t.type)}));return new ir(l?jt:r,i)},ir.prototype.evaluate=function(t){for(var e,r=null,n=0,i=0,a=this.args;i<a.length&&(n++,(r=a[i].evaluate(t))&&r instanceof ee&&!r.available&&(e||(e=r.name),r=null,n===this.args.length&&(r=e)),null===r);i+=1);return r},ir.prototype.eachChild=function(t){this.args.forEach(t)},ir.prototype.outputDefined=function(){return this.args.every((function(t){return t.outputDefined()}))},ir.prototype.serialize=function(){var t=[\"coalesce\"];return this.eachChild((function(e){t.push(e.serialize())})),t};var ar=function(t,e){this.type=e.type,this.bindings=[].concat(t),this.result=e};ar.prototype.evaluate=function(t){return this.result.evaluate(t)},ar.prototype.eachChild=function(t){for(var e=0,r=this.bindings;e<r.length;e+=1)t(r[e][1]);t(this.result)},ar.parse=function(t,e){if(t.length<4)return e.error(\"Expected at least 3 arguments, but found \"+(t.length-1)+\" instead.\");for(var r=[],n=1;n<t.length-1;n+=2){var i=t[n];if(\"string\"!=typeof i)return e.error(\"Expected string, but found \"+typeof i+\" instead.\",n);if(/[^a-zA-Z0-9_]/.test(i))return e.error(\"Variable names must contain only alphanumeric characters or '_'.\",n);var a=e.parse(t[n+1],n+1);if(!a)return null;r.push([i,a])}var o=e.parse(t[t.length-1],t.length-1,e.expectedType,r);return o?new ar(r,o):null},ar.prototype.outputDefined=function(){return this.result.outputDefined()},ar.prototype.serialize=function(){for(var t=[\"let\"],e=0,r=this.bindings;e<r.length;e+=1){var n=r[e];t.push(n[0],n[1].serialize())}return t.push(this.result.serialize()),t};var or=function(t,e,r){this.type=t,this.index=e,this.input=r};or.parse=function(t,e){if(3!==t.length)return e.error(\"Expected 2 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,Dt),n=e.parse(t[2],2,Ht(e.expectedType||jt));return r&&n?new or(n.type.itemType,r,n):null},or.prototype.evaluate=function(t){var e=this.index.evaluate(t),r=this.input.evaluate(t);if(e<0)throw new se(\"Array index out of bounds: \"+e+\" < 0.\");if(e>=r.length)throw new se(\"Array index out of bounds: \"+e+\" > \"+(r.length-1)+\".\");if(e!==Math.floor(e))throw new se(\"Array index must be an integer, but found \"+e+\" instead.\");return r[e]},or.prototype.eachChild=function(t){t(this.index),t(this.input)},or.prototype.outputDefined=function(){return!1},or.prototype.serialize=function(){return[\"at\",this.index.serialize(),this.input.serialize()]};var sr=function(t,e){this.type=Ft,this.needle=t,this.haystack=e};sr.parse=function(t,e){if(3!==t.length)return e.error(\"Expected 2 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,jt),n=e.parse(t[2],2,jt);return r&&n?Xt(r.type,[Ft,Rt,Dt,Ot,jt])?new sr(r,n):e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+Gt(r.type)+\" instead\"):null},sr.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!r)return!1;if(!Zt(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new se(\"Expected first argument to be of type boolean, string, number or null, but found \"+Gt(ie(e))+\" instead.\");if(!Zt(r,[\"string\",\"array\"]))throw new se(\"Expected second argument to be of type array or string, but found \"+Gt(ie(r))+\" instead.\");return r.indexOf(e)>=0},sr.prototype.eachChild=function(t){t(this.needle),t(this.haystack)},sr.prototype.outputDefined=function(){return!0},sr.prototype.serialize=function(){return[\"in\",this.needle.serialize(),this.haystack.serialize()]};var lr=function(t,e,r){this.type=Dt,this.needle=t,this.haystack=e,this.fromIndex=r};lr.parse=function(t,e){if(t.length<=2||t.length>=5)return e.error(\"Expected 3 or 4 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,jt),n=e.parse(t[2],2,jt);if(!r||!n)return null;if(!Xt(r.type,[Ft,Rt,Dt,Ot,jt]))return e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+Gt(r.type)+\" instead\");if(4===t.length){var i=e.parse(t[3],3,Dt);return i?new lr(r,n,i):null}return new lr(r,n)},lr.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!Zt(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new se(\"Expected first argument to be of type boolean, string, number or null, but found \"+Gt(ie(e))+\" instead.\");if(!Zt(r,[\"string\",\"array\"]))throw new se(\"Expected second argument to be of type array or string, but found \"+Gt(ie(r))+\" instead.\");if(this.fromIndex){var n=this.fromIndex.evaluate(t);return r.indexOf(e,n)}return r.indexOf(e)},lr.prototype.eachChild=function(t){t(this.needle),t(this.haystack),this.fromIndex&&t(this.fromIndex)},lr.prototype.outputDefined=function(){return!1},lr.prototype.serialize=function(){if(null!=this.fromIndex&&void 0!==this.fromIndex){var t=this.fromIndex.serialize();return[\"index-of\",this.needle.serialize(),this.haystack.serialize(),t]}return[\"index-of\",this.needle.serialize(),this.haystack.serialize()]};var cr=function(t,e,r,n,i,a){this.inputType=t,this.type=e,this.input=r,this.cases=n,this.outputs=i,this.otherwise=a};cr.parse=function(t,e){if(t.length<5)return e.error(\"Expected at least 4 arguments, but found only \"+(t.length-1)+\".\");if(t.length%2!=1)return e.error(\"Expected an even number of arguments.\");var r,n;e.expectedType&&\"value\"!==e.expectedType.kind&&(n=e.expectedType);for(var i={},a=[],o=2;o<t.length-1;o+=2){var s=t[o],l=t[o+1];Array.isArray(s)||(s=[s]);var 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e=this.input.evaluate(t);return(ie(e)===this.inputType&&this.outputs[this.cases[e]]||this.otherwise).evaluate(t)},cr.prototype.eachChild=function(t){t(this.input),this.outputs.forEach(t),t(this.otherwise)},cr.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))&&this.otherwise.outputDefined()},cr.prototype.serialize=function(){for(var t=this,e=[\"match\",this.input.serialize()],r=[],n={},i=0,a=Object.keys(this.cases).sort();i<a.length;i+=1){var o=a[i];void 0===(f=n[this.cases[o]])?(n[this.cases[o]]=r.length,r.push([this.cases[o],[o]])):r[f][1].push(o)}for(var s=function(e){return\"number\"===t.inputType.kind?Number(e):e},l=0,c=r;l<c.length;l+=1){var u=c[l],f=u[0],h=u[1];e.push(1===h.length?s(h[0]):h.map(s)),e.push(this.outputs[outputIndex$1].serialize())}return e.push(this.otherwise.serialize()),e};var ur=function(t,e,r){this.type=t,this.branches=e,this.otherwise=r};ur.parse=function(t,e){if(t.length<4)return e.error(\"Expected at least 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fr=function(t,e,r,n){this.type=t,this.input=e,this.beginIndex=r,this.endIndex=n};function hr(t,e){return\"==\"===t||\"!=\"===t?\"boolean\"===e.kind||\"string\"===e.kind||\"number\"===e.kind||\"null\"===e.kind||\"value\"===e.kind:\"string\"===e.kind||\"number\"===e.kind||\"value\"===e.kind}function pr(t,e,r,n){return 0===n.compare(e,r)}function dr(t,e,r){var n=\"==\"!==t&&\"!=\"!==t;return function(){function i(t,e,r){this.type=Ft,this.lhs=t,this.rhs=e,this.collator=r,this.hasUntypedArgument=\"value\"===t.type.kind||\"value\"===e.type.kind}return i.parse=function(t,e){if(3!==t.length&&4!==t.length)return e.error(\"Expected two or three arguments.\");var r=t[0],a=e.parse(t[1],1,jt);if(!a)return null;if(!hr(r,a.type))return e.concat(1).error('\"'+r+\"\\\" comparisons are not supported for type '\"+Gt(a.type)+\"'.\");var o=e.parse(t[2],2,jt);if(!o)return null;if(!hr(r,o.type))return e.concat(2).error('\"'+r+\"\\\" comparisons are not supported for type 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0,o={}),e=e.concat(Xr({key:s+\"[0]\",value:a[0],valueSpec:{zoom:{}},style:t.style,styleSpec:t.styleSpec,objectElementValidators:{zoom:Jr,value:h}}))}else e=e.concat(h({key:s+\"[0]\",value:a[0],valueSpec:{},style:t.style,styleSpec:t.styleSpec},a));return Vr(It(a[1]))?e.concat([new St(s+\"[1]\",a[1],\"expressions are not allowed in function stops.\")]):e.concat(bn({key:s+\"[1]\",value:a[1],valueSpec:i,style:t.style,styleSpec:t.styleSpec}))}function h(t,n){var s=zr(t.value),l=Lt(t.value),c=null!==t.value?t.value:n;if(e){if(s!==e)return[new St(t.key,c,s+\" stop domain type must match previous stop domain type \"+e)]}else e=s;if(\"number\"!==s&&\"string\"!==s&&\"boolean\"!==s)return[new St(t.key,c,\"stop domain value must be a number, string, or boolean\")];if(\"number\"!==s&&\"categorical\"!==a){var u=\"number expected, \"+s+\" found\";return Lr(i)&&void 0===a&&(u+='\\nIf you intended to use a categorical function, specify `\"type\": \"categorical\"`.'),[new St(t.key,c,u)]}return\"categorical\"!==a||\"number\"!==s||isFinite(l)&&Math.floor(l)===l?\"categorical\"!==a&&\"number\"===s&&void 0!==r&&l<r?[new St(t.key,c,\"stop domain values must appear in ascending order\")]:(r=l,\"categorical\"===a&&l in o?[new St(t.key,c,\"stop domain values must be unique\")]:(o[l]=!0,[])):[new St(t.key,c,\"integer expected, found \"+l)]}}function Qr(t){var e=(\"property\"===t.expressionContext?Yr:qr)(It(t.value),t.valueSpec);if(\"error\"===e.result)return e.value.map((function(e){return new St(\"\"+t.key+e.key,t.value,e.message)}));var r=e.value.expression||e.value._styleExpression.expression;if(\"property\"===t.expressionContext&&\"text-font\"===t.propertyKey&&!r.outputDefined())return[new St(t.key,t.value,'Invalid data expression for \"'+t.propertyKey+'\". 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en={type:\"boolean\",default:!1,transition:!1,\"property-type\":\"data-driven\",expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]}};function rn(t){if(null==t)return{filter:function(){return!0},needGeometry:!1};tn(t)||(t=an(t));var e=qr(t,en);if(\"error\"===e.result)throw new Error(e.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));return{filter:function(t,r,n){return e.value.evaluate(t,r,{},n)},needGeometry:function t(e){if(!Array.isArray(e))return!1;if(\"within\"===e[0])return!0;for(var r=1;r<e.length;r++)if(t(e[r]))return!0;return!1}(t)}}function nn(t,e){return t<e?-1:t>e?1:0}function an(t){if(!t)return!0;var e,r=t[0];return t.length<=1?\"any\"!==r:\"==\"===r?on(t[1],t[2],\"==\"):\"!=\"===r?cn(on(t[1],t[2],\"==\")):\"<\"===r||\">\"===r||\"<=\"===r||\">=\"===r?on(t[1],t[2],r):\"any\"===r?(e=t.slice(1),[\"any\"].concat(e.map(an))):\"all\"===r?[\"all\"].concat(t.slice(1).map(an)):\"none\"===r?[\"all\"].concat(t.slice(1).map(an).map(cn)):\"in\"===r?sn(t[1],t.slice(2)):\"!in\"===r?cn(sn(t[1],t.slice(2))):\"has\"===r?ln(t[1]):\"!has\"===r?cn(ln(t[1])):\"within\"!==r||t}function on(t,e,r){switch(t){case\"$type\":return[\"filter-type-\"+r,e];case\"$id\":return[\"filter-id-\"+r,e];default:return[\"filter-\"+r,t,e]}}function sn(t,e){if(0===e.length)return!1;switch(t){case\"$type\":return[\"filter-type-in\",[\"literal\",e]];case\"$id\":return[\"filter-id-in\",[\"literal\",e]];default:return e.length>200&&!e.some((function(t){return typeof t!=typeof e[0]}))?[\"filter-in-large\",t,[\"literal\",e.sort(nn)]]:[\"filter-in-small\",t,[\"literal\",e]]}}function ln(t){switch(t){case\"$type\":return!0;case\"$id\":return[\"filter-has-id\"];default:return[\"filter-has\",t]}}function cn(t){return[\"!\",t]}function un(t){return tn(It(t.value))?Qr(Ct({},t,{expressionContext:\"filter\",valueSpec:{value:\"boolean\"}})):function t(e){var r=e.value,n=e.key;if(\"array\"!==zr(r))return[new St(n,r,\"array expected, \"+zr(r)+\" found\")];var i,a=e.styleSpec,o=[];if(r.length<1)return[new St(n,r,\"filter array must have at least 1 element\")];switch(o=o.concat($r({key:n+\"[0]\",value:r[0],valueSpec:a.filter_operator,style:e.style,styleSpec:e.styleSpec})),Lt(r[0])){case\"<\":case\"<=\":case\">\":case\">=\":r.length>=2&&\"$type\"===Lt(r[1])&&o.push(new St(n,r,'\"$type\" cannot be use with operator \"'+r[0]+'\"'));case\"==\":case\"!=\":3!==r.length&&o.push(new St(n,r,'filter array for operator \"'+r[0]+'\" must have 3 elements'));case\"in\":case\"!in\":r.length>=2&&\"string\"!==(i=zr(r[1]))&&o.push(new St(n+\"[1]\",r[1],\"string expected, \"+i+\" found\"));for(var s=2;s<r.length;s++)i=zr(r[s]),\"$type\"===Lt(r[1])?o=o.concat($r({key:n+\"[\"+s+\"]\",value:r[s],valueSpec:a.geometry_type,style:e.style,styleSpec:e.styleSpec})):\"string\"!==i&&\"number\"!==i&&\"boolean\"!==i&&o.push(new St(n+\"[\"+s+\"]\",r[s],\"string, number, or boolean expected, \"+i+\" found\"));break;case\"any\":case\"all\":case\"none\":for(var l=1;l<r.length;l++)o=o.concat(t({key:n+\"[\"+l+\"]\",value:r[l],style:e.style,styleSpec:e.styleSpec}));break;case\"has\":case\"!has\":i=zr(r[1]),2!==r.length?o.push(new St(n,r,'filter array for \"'+r[0]+'\" operator must have 2 elements')):\"string\"!==i&&o.push(new St(n+\"[1]\",r[1],\"string expected, \"+i+\" found\"));break;case\"within\":i=zr(r[1]),2!==r.length?o.push(new St(n,r,'filter array for \"'+r[0]+'\" operator must have 2 elements')):\"object\"!==i&&o.push(new St(n+\"[1]\",r[1],\"object expected, \"+i+\" found\"))}return o}(t)}function fn(t,e){var r=t.key,n=t.style,i=t.styleSpec,a=t.value,o=t.objectKey,s=i[e+\"_\"+t.layerType];if(!s)return[];var l=o.match(/^(.*)-transition$/);if(\"paint\"===e&&l&&s[l[1]]&&s[l[1]].transition)return bn({key:r,value:a,valueSpec:i.transition,style:n,styleSpec:i});var c,u=t.valueSpec||s[o];if(!u)return[new St(r,a,'unknown property \"'+o+'\"')];if(\"string\"===zr(a)&&Lr(u)&&!u.tokens&&(c=/^{([^}]+)}$/.exec(a)))return[new St(r,a,'\"'+o+'\" does not support interpolation syntax\\nUse an identity property function instead: `{ \"type\": \"identity\", \"property\": '+JSON.stringify(c[1])+\" }`.\")];var f=[];return\"symbol\"===t.layerType&&(\"text-field\"===o&&n&&!n.glyphs&&f.push(new St(r,a,'use of \"text-field\" requires a style \"glyphs\" property')),\"text-font\"===o&&Or(It(a))&&\"identity\"===Lt(a.type)&&f.push(new St(r,a,'\"text-font\" does not support identity 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h=i.sources&&i.sources[r.source],p=h&&Lt(h.type);h?\"vector\"===p&&\"raster\"===s?e.push(new St(n,r.source,'layer \"'+r.id+'\" requires a raster source')):\"raster\"===p&&\"raster\"!==s?e.push(new St(n,r.source,'layer \"'+r.id+'\" requires a vector source')):\"vector\"!==p||r[\"source-layer\"]?\"raster-dem\"===p&&\"hillshade\"!==s?e.push(new St(n,r.source,\"raster-dem source can only be used with layer type 'hillshade'.\")):\"line\"!==s||!r.paint||!r.paint[\"line-gradient\"]||\"geojson\"===p&&h.lineMetrics||e.push(new St(n,r,'layer \"'+r.id+'\" specifies a line-gradient, which requires a GeoJSON source with `lineMetrics` enabled.')):e.push(new St(n,r,'layer \"'+r.id+'\" must specify a \"source-layer\"')):e.push(new St(n,r.source,'source \"'+r.source+'\" not found'))}else e.push(new St(n,r,'missing required property \"source\"'));return e=e.concat(Xr({key:n,value:r,valueSpec:a.layer,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{\"*\":function(){return[]},type:function(){return bn({key:n+\".type\",value:r.type,valueSpec:a.layer.type,style:t.style,styleSpec:t.styleSpec,object:r,objectKey:\"type\"})},filter:un,layout:function(t){return Xr({layer:r,key:t.key,value:t.value,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{\"*\":function(t){return pn(Ct({layerType:s},t))}}})},paint:function(t){return Xr({layer:r,key:t.key,value:t.value,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{\"*\":function(t){return hn(Ct({layerType:s},t))}}})}}}))}function gn(t){var e=t.value,r=t.key,n=zr(e);return\"string\"!==n?[new St(r,e,\"string expected, \"+n+\" found\")]:[]}var mn={promoteId:function(t){var e=t.key,r=t.value;if(\"string\"===zr(r))return gn({key:e,value:r});var n=[];for(var i in r)n.push.apply(n,gn({key:e+\".\"+i,value:r[i]}));return n}};function vn(t){var e=t.value,r=t.key,n=t.styleSpec,i=t.style;if(!e.type)return[new St(r,e,'\"type\" is required')];var a,o=Lt(e.type);switch(o){case\"vector\":case\"raster\":case\"raster-dem\":return Xr({key:r,value:e,valueSpec:n[\"source_\"+o.replace(\"-\",\"_\")],style:t.style,styleSpec:n,objectElementValidators:mn});case\"geojson\":if(a=Xr({key:r,value:e,valueSpec:n.source_geojson,style:i,styleSpec:n,objectElementValidators:mn}),e.cluster)for(var s in e.clusterProperties){var l=e.clusterProperties[s],c=l[0],u=\"string\"==typeof c?[c,[\"accumulated\"],[\"get\",s]]:c;a.push.apply(a,Qr({key:r+\".\"+s+\".map\",value:l[1],expressionContext:\"cluster-map\"})),a.push.apply(a,Qr({key:r+\".\"+s+\".reduce\",value:u,expressionContext:\"cluster-reduce\"}))}return a;case\"video\":return Xr({key:r,value:e,valueSpec:n.source_video,style:i,styleSpec:n});case\"image\":return Xr({key:r,value:e,valueSpec:n.source_image,style:i,styleSpec:n});case\"canvas\":return[new St(r,null,\"Please use runtime APIs to add canvas sources, rather than including them in stylesheets.\",\"source.canvas\")];default:return $r({key:r+\".type\",value:e.type,valueSpec:{values:[\"vector\",\"raster\",\"raster-dem\",\"geojson\",\"video\",\"image\"]},style:i,styleSpec:n})}}function yn(t){var e=t.value,r=t.styleSpec,n=r.light,i=t.style,a=[],o=zr(e);if(void 0===e)return a;if(\"object\"!==o)return a.concat([new St(\"light\",e,\"object expected, \"+o+\" found\")]);for(var s in e){var l=s.match(/^(.*)-transition$/);a=a.concat(l&&n[l[1]]&&n[l[1]].transition?bn({key:s,value:e[s],valueSpec:r.transition,style:i,styleSpec:r}):n[s]?bn({key:s,value:e[s],valueSpec:n[s],style:i,styleSpec:r}):[new St(s,e[s],'unknown property \"'+s+'\"')])}return a}var xn={\"*\":function(){return[]},array:Zr,boolean:function(t){var e=t.value,r=t.key,n=zr(e);return\"boolean\"!==n?[new St(r,e,\"boolean expected, \"+n+\" found\")]:[]},number:Jr,color:function(t){var e=t.key,r=t.value,n=zr(r);return\"string\"!==n?[new St(e,r,\"color expected, \"+n+\" 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r=r.concat(bn({key:\"\",value:t,valueSpec:e.$root,styleSpec:e,style:t,objectElementValidators:{glyphs:_n,\"*\":function(){return[]}}})),t.constants&&(r=r.concat(Et({key:\"constants\",value:t.constants,style:t,styleSpec:e}))),Tn(r)}function Tn(t){return[].concat(t).sort((function(t,e){return t.line-e.line}))}function kn(t){return function(){for(var e=[],r=arguments.length;r--;)e[r]=arguments[r];return Tn(t.apply(this,e))}}wn.source=kn(vn),wn.light=kn(yn),wn.layer=kn(dn),wn.filter=kn(un),wn.paintProperty=kn(hn),wn.layoutProperty=kn(pn);var Mn=wn,An=Mn.light,Sn=Mn.paintProperty,En=Mn.layoutProperty;function Cn(t,e){var r=!1;if(e&&e.length)for(var n=0,i=e;n<i.length;n+=1)t.fire(new kt(new Error(i[n].message))),r=!0;return r}var Ln=In;function In(t,e,r){var n=this.cells=[];if(t instanceof ArrayBuffer){this.arrayBuffer=t;var i=new Int32Array(this.arrayBuffer);t=i[0],this.d=(e=i[1])+2*(r=i[2]);for(var a=0;a<this.d*this.d;a++){var o=i[3+a],s=i[3+a+1];n.push(o===s?null:i.subarray(o,s))}var l=i[3+n.length+1];this.keys=i.subarray(i[3+n.length],l),this.bboxes=i.subarray(l),this.insert=this._insertReadonly}else{this.d=e+2*r;for(var c=0;c<this.d*this.d;c++)n.push([]);this.keys=[],this.bboxes=[]}this.n=e,this.extent=t,this.padding=r,this.scale=e/t,this.uid=0;var u=r/e*t;this.min=-u,this.max=t+u}In.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertCell,this.uid++),this.keys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},In.prototype._insertReadonly=function(){throw\"Cannot insert into a GridIndex created from an ArrayBuffer.\"},In.prototype._insertCell=function(t,e,r,n,i,a){this.cells[i].push(a)},In.prototype.query=function(t,e,r,n,i){var a=this.min,o=this.max;if(t<=a&&e<=a&&o<=r&&o<=n&&!i)return Array.prototype.slice.call(this.keys);var s=[];return this._forEachCell(t,e,r,n,this._queryCell,s,{},i),s},In.prototype._queryCell=function(t,e,r,n,i,a,o,s){var l=this.cells[i];if(null!==l)for(var c=this.keys,u=this.bboxes,f=0;f<l.length;f++){var h=l[f];if(void 0===o[h]){var p=4*h;(s?s(u[p+0],u[p+1],u[p+2],u[p+3]):t<=u[p+2]&&e<=u[p+3]&&r>=u[p+0]&&n>=u[p+1])?(o[h]=!0,a.push(c[h])):o[h]=!1}}},In.prototype._forEachCell=function(t,e,r,n,i,a,o,s){for(var l=this._convertToCellCoord(t),c=this._convertToCellCoord(e),u=this._convertToCellCoord(r),f=this._convertToCellCoord(n),h=l;h<=u;h++)for(var p=c;p<=f;p++){var d=this.d*p+h;if((!s||s(this._convertFromCellCoord(h),this._convertFromCellCoord(p),this._convertFromCellCoord(h+1),this._convertFromCellCoord(p+1)))&&i.call(this,t,e,r,n,d,a,o,s))return}},In.prototype._convertFromCellCoord=function(t){return(t-this.padding)/this.scale},In.prototype._convertToCellCoord=function(t){return Math.max(0,Math.min(this.d-1,Math.floor(t*this.scale)+this.padding))},In.prototype.toArrayBuffer=function(){if(this.arrayBuffer)return this.arrayBuffer;for(var t=this.cells,e=3+this.cells.length+1+1,r=0,n=0;n<this.cells.length;n++)r+=this.cells[n].length;var i=new Int32Array(e+r+this.keys.length+this.bboxes.length);i[0]=this.extent,i[1]=this.n,i[2]=this.padding;for(var a=e,o=0;o<t.length;o++){var s=t[o];i[3+o]=a,i.set(s,a),a+=s.length}return i[3+t.length]=a,i.set(this.keys,a),i[3+t.length+1]=a+=this.keys.length,i.set(this.bboxes,a),a+=this.bboxes.length,i.buffer};var Pn=self.ImageData,zn=self.ImageBitmap,On={};function Dn(t,e,r){void 0===r&&(r={}),Object.defineProperty(e,\"_classRegistryKey\",{value:t,writeable:!1}),On[t]={klass:e,omit:r.omit||[],shallow:r.shallow||[]}}for(var Rn in Dn(\"Object\",Object),Ln.serialize=function(t,e){var r=t.toArrayBuffer();return e&&e.push(r),{buffer:r}},Ln.deserialize=function(t){return new Ln(t.buffer)},Dn(\"Grid\",Ln),Dn(\"Color\",Kt),Dn(\"Error\",Error),Dn(\"ResolvedImage\",ee),Dn(\"StylePropertyFunction\",Wr),Dn(\"StyleExpression\",Ur,{omit:[\"_evaluator\"]}),Dn(\"ZoomDependentExpression\",Gr),Dn(\"ZoomConstantExpression\",Hr),Dn(\"CompoundExpression\",me,{omit:[\"_evaluate\"]}),Tr)Tr[Rn]._classRegistryKey||Dn(\"Expression_\"+Rn,Tr[Rn]);function Fn(t){return t&&\"undefined\"!=typeof ArrayBuffer&&(t instanceof ArrayBuffer||t.constructor&&\"ArrayBuffer\"===t.constructor.name)}function Bn(t){return zn&&t instanceof zn}function Nn(t,e){if(null==t||\"boolean\"==typeof t||\"number\"==typeof t||\"string\"==typeof t||t instanceof Boolean||t instanceof Number||t instanceof String||t instanceof Date||t instanceof RegExp)return t;if(Fn(t)||Bn(t))return e&&e.push(t),t;if(ArrayBuffer.isView(t)){var r=t;return e&&e.push(r.buffer),r}if(t instanceof Pn)return e&&e.push(t.data.buffer),t;if(Array.isArray(t)){for(var n=[],i=0,a=t;i<a.length;i+=1)n.push(Nn(a[i],e));return n}if(\"object\"==typeof t){var o=t.constructor,s=o._classRegistryKey;if(!s)throw new Error(\"can't serialize object of unregistered class\");var l=o.serialize?o.serialize(t,e):{};if(!o.serialize){for(var c in t)if(t.hasOwnProperty(c)&&!(On[s].omit.indexOf(c)>=0)){var u=t[c];l[c]=On[s].shallow.indexOf(c)>=0?u:Nn(u,e)}t instanceof Error&&(l.message=t.message)}if(l.$name)throw new Error(\"$name property is reserved for worker serialization logic.\");return\"Object\"!==s&&(l.$name=s),l}throw new Error(\"can't serialize object of type \"+typeof t)}function jn(t){if(null==t||\"boolean\"==typeof t||\"number\"==typeof t||\"string\"==typeof t||t instanceof Boolean||t instanceof Number||t instanceof String||t instanceof Date||t instanceof RegExp||Fn(t)||Bn(t)||ArrayBuffer.isView(t)||t instanceof Pn)return t;if(Array.isArray(t))return t.map(jn);if(\"object\"==typeof t){var e=t.$name||\"Object\",r=On[e].klass;if(!r)throw new Error(\"can't deserialize unregistered class \"+e);if(r.deserialize)return r.deserialize(t);for(var n=Object.create(r.prototype),i=0,a=Object.keys(t);i<a.length;i+=1){var o=a[i];if(\"$name\"!==o){var s=t[o];n[o]=On[e].shallow.indexOf(o)>=0?s:jn(s)}}return n}throw new Error(\"can't deserialize object of type \"+typeof t)}var Un=function(){this.first=!0};Un.prototype.update=function(t,e){var r=Math.floor(t);return this.first?(this.first=!1,this.lastIntegerZoom=r,this.lastIntegerZoomTime=0,this.lastZoom=t,this.lastFloorZoom=r,!0):(this.lastFloorZoom>r?(this.lastIntegerZoom=r+1,this.lastIntegerZoomTime=e):this.lastFloorZoom<r&&(this.lastIntegerZoom=r,this.lastIntegerZoomTime=e),t!==this.lastZoom&&(this.lastZoom=t,this.lastFloorZoom=r,!0))};var Vn={\"Latin-1 Supplement\":function(t){return t>=128&&t<=255},Arabic:function(t){return t>=1536&&t<=1791},\"Arabic Supplement\":function(t){return t>=1872&&t<=1919},\"Arabic Extended-A\":function(t){return t>=2208&&t<=2303},\"Hangul Jamo\":function(t){return t>=4352&&t<=4607},\"Unified Canadian Aboriginal Syllabics\":function(t){return t>=5120&&t<=5759},Khmer:function(t){return t>=6016&&t<=6143},\"Unified Canadian Aboriginal Syllabics Extended\":function(t){return t>=6320&&t<=6399},\"General Punctuation\":function(t){return t>=8192&&t<=8303},\"Letterlike Symbols\":function(t){return t>=8448&&t<=8527},\"Number Forms\":function(t){return t>=8528&&t<=8591},\"Miscellaneous Technical\":function(t){return t>=8960&&t<=9215},\"Control Pictures\":function(t){return t>=9216&&t<=9279},\"Optical Character Recognition\":function(t){return t>=9280&&t<=9311},\"Enclosed Alphanumerics\":function(t){return t>=9312&&t<=9471},\"Geometric Shapes\":function(t){return t>=9632&&t<=9727},\"Miscellaneous Symbols\":function(t){return t>=9728&&t<=9983},\"Miscellaneous Symbols and Arrows\":function(t){return t>=11008&&t<=11263},\"CJK Radicals Supplement\":function(t){return t>=11904&&t<=12031},\"Kangxi Radicals\":function(t){return t>=12032&&t<=12255},\"Ideographic Description Characters\":function(t){return t>=12272&&t<=12287},\"CJK Symbols and Punctuation\":function(t){return t>=12288&&t<=12351},Hiragana:function(t){return t>=12352&&t<=12447},Katakana:function(t){return t>=12448&&t<=12543},Bopomofo:function(t){return t>=12544&&t<=12591},\"Hangul Compatibility Jamo\":function(t){return t>=12592&&t<=12687},Kanbun:function(t){return t>=12688&&t<=12703},\"Bopomofo Extended\":function(t){return t>=12704&&t<=12735},\"CJK Strokes\":function(t){return t>=12736&&t<=12783},\"Katakana Phonetic Extensions\":function(t){return t>=12784&&t<=12799},\"Enclosed CJK Letters and Months\":function(t){return t>=12800&&t<=13055},\"CJK Compatibility\":function(t){return t>=13056&&t<=13311},\"CJK Unified Ideographs Extension A\":function(t){return t>=13312&&t<=19903},\"Yijing Hexagram Symbols\":function(t){return t>=19904&&t<=19967},\"CJK Unified Ideographs\":function(t){return t>=19968&&t<=40959},\"Yi Syllables\":function(t){return t>=40960&&t<=42127},\"Yi Radicals\":function(t){return t>=42128&&t<=42191},\"Hangul Jamo Extended-A\":function(t){return t>=43360&&t<=43391},\"Hangul Syllables\":function(t){return t>=44032&&t<=55215},\"Hangul Jamo Extended-B\":function(t){return t>=55216&&t<=55295},\"Private Use Area\":function(t){return t>=57344&&t<=63743},\"CJK Compatibility Ideographs\":function(t){return t>=63744&&t<=64255},\"Arabic Presentation Forms-A\":function(t){return t>=64336&&t<=65023},\"Vertical Forms\":function(t){return t>=65040&&t<=65055},\"CJK Compatibility Forms\":function(t){return t>=65072&&t<=65103},\"Small Form Variants\":function(t){return t>=65104&&t<=65135},\"Arabic Presentation Forms-B\":function(t){return t>=65136&&t<=65279},\"Halfwidth and Fullwidth Forms\":function(t){return t>=65280&&t<=65519}};function qn(t){for(var e=0,r=t;e<r.length;e+=1)if(Hn(r[e].charCodeAt(0)))return!0;return!1}function Hn(t){return!(746!==t&&747!==t&&(t<4352||!(Vn[\"Bopomofo Extended\"](t)||Vn.Bopomofo(t)||Vn[\"CJK Compatibility 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0===this.fadeDuration?1:Math.min((this.now-this.zoomHistory.lastIntegerZoomTime)/this.fadeDuration,1)},ii.prototype.getCrossfadeParameters=function(){var t=this.zoom,e=t-Math.floor(t),r=this.crossFadingFactor();return t>this.zoomHistory.lastIntegerZoom?{fromScale:2,toScale:1,t:e+(1-e)*r}:{fromScale:.5,toScale:1,t:1-(1-r)*e}};var ai=function(t,e){this.property=t,this.value=e,this.expression=function(t,e){if(Or(t))return new Wr(t,e);if(Vr(t)){var r=Yr(t,e);if(\"error\"===r.result)throw new Error(r.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));return r.value}var n=t;return\"string\"==typeof t&&\"color\"===e.type&&(n=Kt.parse(t)),{kind:\"constant\",evaluate:function(){return n}}}(void 0===e?t.specification.default:e,t.specification)};ai.prototype.isDataDriven=function(){return\"source\"===this.expression.kind||\"composite\"===this.expression.kind},ai.prototype.possiblyEvaluate=function(t,e,r){return this.property.possiblyEvaluate(this,t,e,r)};var oi=function(t){this.property=t,this.value=new ai(t,void 0)};oi.prototype.transitioned=function(t,e){return new li(this.property,this.value,e,u({},t.transition,this.transition),t.now)},oi.prototype.untransitioned=function(){return new li(this.property,this.value,null,{},0)};var si=function(t){this._properties=t,this._values=Object.create(t.defaultTransitionablePropertyValues)};si.prototype.getValue=function(t){return x(this._values[t].value.value)},si.prototype.setValue=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new oi(this._values[t].property)),this._values[t].value=new ai(this._values[t].property,null===e?void 0:x(e))},si.prototype.getTransition=function(t){return x(this._values[t].transition)},si.prototype.setTransition=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new oi(this._values[t].property)),this._values[t].transition=x(e)||void 0},si.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i);var a=this.getTransition(n);void 0!==a&&(t[n+\"-transition\"]=a)}return t},si.prototype.transitioned=function(t,e){for(var r=new ci(this._properties),n=0,i=Object.keys(this._values);n<i.length;n+=1){var a=i[n];r._values[a]=this._values[a].transitioned(t,e._values[a])}return r},si.prototype.untransitioned=function(){for(var t=new ci(this._properties),e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e];t._values[n]=this._values[n].untransitioned()}return t};var li=function(t,e,r,n,i){this.property=t,this.value=e,this.begin=i+n.delay||0,this.end=this.begin+n.duration||0,t.specification.transition&&(n.delay||n.duration)&&(this.prior=r)};li.prototype.possiblyEvaluate=function(t,e,r){var n=t.now||0,i=this.value.possiblyEvaluate(t,e,r),a=this.prior;if(a){if(n>this.end)return this.prior=null,i;if(this.value.isDataDriven())return this.prior=null,i;if(n<this.begin)return a.possiblyEvaluate(t,e,r);var o=(n-this.begin)/(this.end-this.begin);return this.property.interpolate(a.possiblyEvaluate(t,e,r),i,function(t){if(t<=0)return 0;if(t>=1)return 1;var e=t*t,r=e*t;return 4*(t<.5?r:3*(t-e)+r-.75)}(o))}return i};var ci=function(t){this._properties=t,this._values=Object.create(t.defaultTransitioningPropertyValues)};ci.prototype.possiblyEvaluate=function(t,e,r){for(var n=new hi(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n},ci.prototype.hasTransition=function(){for(var t=0,e=Object.keys(this._values);t<e.length;t+=1)if(this._values[e[t]].prior)return!0;return!1};var ui=function(t){this._properties=t,this._values=Object.create(t.defaultPropertyValues)};ui.prototype.getValue=function(t){return x(this._values[t].value)},ui.prototype.setValue=function(t,e){this._values[t]=new ai(this._values[t].property,null===e?void 0:x(e))},ui.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i)}return t},ui.prototype.possiblyEvaluate=function(t,e,r){for(var n=new hi(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n};var fi=function(t,e,r){this.property=t,this.value=e,this.parameters=r};fi.prototype.isConstant=function(){return\"constant\"===this.value.kind},fi.prototype.constantOr=function(t){return\"constant\"===this.value.kind?this.value.value:t},fi.prototype.evaluate=function(t,e,r,n){return this.property.evaluate(this.value,this.parameters,t,e,r,n)};var hi=function(t){this._properties=t,this._values=Object.create(t.defaultPossiblyEvaluatedValues)};hi.prototype.get=function(t){return this._values[t]};var pi=function(t){this.specification=t};pi.prototype.possiblyEvaluate=function(t,e){return t.expression.evaluate(e)},pi.prototype.interpolate=function(t,e,r){var n=Ve[this.specification.type];return n?n(t,e,r):t};var di=function(t,e){this.specification=t,this.overrides=e};di.prototype.possiblyEvaluate=function(t,e,r,n){return new fi(this,\"constant\"===t.expression.kind||\"camera\"===t.expression.kind?{kind:\"constant\",value:t.expression.evaluate(e,null,{},r,n)}:t.expression,e)},di.prototype.interpolate=function(t,e,r){if(\"constant\"!==t.value.kind||\"constant\"!==e.value.kind)return t;if(void 0===t.value.value||void 0===e.value.value)return new fi(this,{kind:\"constant\",value:void 0},t.parameters);var n=Ve[this.specification.type];return n?new fi(this,{kind:\"constant\",value:n(t.value.value,e.value.value,r)},t.parameters):t},di.prototype.evaluate=function(t,e,r,n,i,a){return\"constant\"===t.kind?t.value:t.evaluate(e,r,n,i,a)};var gi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0===t.value)return new fi(this,{kind:\"constant\",value:void 0},e);if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n),a=\"resolvedImage\"===t.property.specification.type&&\"string\"!=typeof i?i.name:i,o=this._calculate(a,a,a,e);return new fi(this,{kind:\"constant\",value:o},e)}if(\"camera\"===t.expression.kind){var s=this._calculate(t.expression.evaluate({zoom:e.zoom-1}),t.expression.evaluate({zoom:e.zoom}),t.expression.evaluate({zoom:e.zoom+1}),e);return new fi(this,{kind:\"constant\",value:s},e)}return new fi(this,t.expression,e)},e.prototype.evaluate=function(t,e,r,n,i,a){if(\"source\"===t.kind){var o=t.evaluate(e,r,n,i,a);return this._calculate(o,o,o,e)}return\"composite\"===t.kind?this._calculate(t.evaluate({zoom:Math.floor(e.zoom)-1},r,n),t.evaluate({zoom:Math.floor(e.zoom)},r,n),t.evaluate({zoom:Math.floor(e.zoom)+1},r,n),e):t.value},e.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},e.prototype.interpolate=function(t){return t},e}(di),mi=function(t){this.specification=t};mi.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0!==t.value){if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n);return this._calculate(i,i,i,e)}return this._calculate(t.expression.evaluate(new ii(Math.floor(e.zoom-1),e)),t.expression.evaluate(new ii(Math.floor(e.zoom),e)),t.expression.evaluate(new ii(Math.floor(e.zoom+1),e)),e)}},mi.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},mi.prototype.interpolate=function(t){return t};var vi=function(t){this.specification=t};vi.prototype.possiblyEvaluate=function(t,e,r,n){return!!t.expression.evaluate(e,null,{},r,n)},vi.prototype.interpolate=function(){return!1};var yi=function(t){for(var e in this.properties=t,this.defaultPropertyValues={},this.defaultTransitionablePropertyValues={},this.defaultTransitioningPropertyValues={},this.defaultPossiblyEvaluatedValues={},this.overridableProperties=[],t){var r=t[e];r.specification.overridable&&this.overridableProperties.push(e);var n=this.defaultPropertyValues[e]=new ai(r,void 0),i=this.defaultTransitionablePropertyValues[e]=new oi(r);this.defaultTransitioningPropertyValues[e]=i.untransitioned(),this.defaultPossiblyEvaluatedValues[e]=n.possiblyEvaluate({})}};Dn(\"DataDrivenProperty\",di),Dn(\"DataConstantProperty\",pi),Dn(\"CrossFadedDataDrivenProperty\",gi),Dn(\"CrossFadedProperty\",mi),Dn(\"ColorRampProperty\",vi);var xi=function(t){function e(e,r){if(t.call(this),this.id=e.id,this.type=e.type,this._featureFilter={filter:function(){return!0},needGeometry:!1},\"custom\"!==e.type&&(this.metadata=(e=e).metadata,this.minzoom=e.minzoom,this.maxzoom=e.maxzoom,\"background\"!==e.type&&(this.source=e.source,this.sourceLayer=e[\"source-layer\"],this.filter=e.filter),r.layout&&(this._unevaluatedLayout=new ui(r.layout)),r.paint)){for(var n in this._transitionablePaint=new si(r.paint),e.paint)this.setPaintProperty(n,e.paint[n],{validate:!1});for(var i in e.layout)this.setLayoutProperty(i,e.layout[i],{validate:!1});this._transitioningPaint=this._transitionablePaint.untransitioned(),this.paint=new hi(r.paint)}}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.getCrossfadeParameters=function(){return this._crossfadeParameters},e.prototype.getLayoutProperty=function(t){return\"visibility\"===t?this.visibility:this._unevaluatedLayout.getValue(t)},e.prototype.setLayoutProperty=function(t,e,r){void 0===r&&(r={}),null!=e&&this._validate(En,\"layers.\"+this.id+\".layout.\"+t,t,e,r)||(\"visibility\"!==t?this._unevaluatedLayout.setValue(t,e):this.visibility=e)},e.prototype.getPaintProperty=function(t){return m(t,\"-transition\")?this._transitionablePaint.getTransition(t.slice(0,-\"-transition\".length)):this._transitionablePaint.getValue(t)},e.prototype.setPaintProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e&&this._validate(Sn,\"layers.\"+this.id+\".paint.\"+t,t,e,r))return!1;if(m(t,\"-transition\"))return this._transitionablePaint.setTransition(t.slice(0,-\"-transition\".length),e||void 0),!1;var n=this._transitionablePaint._values[t],i=\"cross-faded-data-driven\"===n.property.specification[\"property-type\"],a=n.value.isDataDriven(),o=n.value;this._transitionablePaint.setValue(t,e),this._handleSpecialPaintPropertyUpdate(t);var s=this._transitionablePaint._values[t].value;return s.isDataDriven()||a||i||this._handleOverridablePaintPropertyUpdate(t,o,s)},e.prototype._handleSpecialPaintPropertyUpdate=function(t){},e.prototype._handleOverridablePaintPropertyUpdate=function(t,e,r){return!1},e.prototype.isHidden=function(t){return!!(this.minzoom&&t<this.minzoom)||!!(this.maxzoom&&t>=this.maxzoom)||\"none\"===this.visibility},e.prototype.updateTransitions=function(t){this._transitioningPaint=this._transitionablePaint.transitioned(t,this._transitioningPaint)},e.prototype.hasTransition=function(){return this._transitioningPaint.hasTransition()},e.prototype.recalculate=function(t,e){t.getCrossfadeParameters&&(this._crossfadeParameters=t.getCrossfadeParameters()),this._unevaluatedLayout&&(this.layout=this._unevaluatedLayout.possiblyEvaluate(t,void 0,e)),this.paint=this._transitioningPaint.possiblyEvaluate(t,void 0,e)},e.prototype.serialize=function(){var t={id:this.id,type:this.type,source:this.source,\"source-layer\":this.sourceLayer,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom,filter:this.filter,layout:this._unevaluatedLayout&&this._unevaluatedLayout.serialize(),paint:this._transitionablePaint&&this._transitionablePaint.serialize()};return this.visibility&&(t.layout=t.layout||{},t.layout.visibility=this.visibility),y(t,(function(t,e){return!(void 0===t||\"layout\"===e&&!Object.keys(t).length||\"paint\"===e&&!Object.keys(t).length)}))},e.prototype._validate=function(t,e,r,n,i){return void 0===i&&(i={}),(!i||!1!==i.validate)&&Cn(this,t.call(Mn,{key:e,layerType:this.type,objectKey:r,value:n,styleSpec:At,style:{glyphs:!0,sprite:!0}}))},e.prototype.is3D=function(){return!1},e.prototype.isTileClipped=function(){return!1},e.prototype.hasOffscreenPass=function(){return!1},e.prototype.resize=function(){},e.prototype.isStateDependent=function(){for(var t in this.paint._values){var e=this.paint.get(t);if(e instanceof fi&&Lr(e.property.specification)&&(\"source\"===e.value.kind||\"composite\"===e.value.kind)&&e.value.isStateDependent)return!0}return!1},e}(Mt),bi={Int8:Int8Array,Uint8:Uint8Array,Int16:Int16Array,Uint16:Uint16Array,Int32:Int32Array,Uint32:Uint32Array,Float32:Float32Array},_i=function(t,e){this._structArray=t,this._pos1=e*this.size,this._pos2=this._pos1/2,this._pos4=this._pos1/4,this._pos8=this._pos1/8},wi=function(){this.isTransferred=!1,this.capacity=-1,this.resize(0)};function Ti(t,e){void 0===e&&(e=1);var r=0,n=0;return{members:t.map((function(t){var i=bi[t.type].BYTES_PER_ELEMENT,a=r=ki(r,Math.max(e,i)),o=t.components||1;return n=Math.max(n,i),r+=i*o,{name:t.name,type:t.type,components:o,offset:a}})),size:ki(r,Math.max(n,e)),alignment:e}}function ki(t,e){return Math.ceil(t/e)*e}wi.serialize=function(t,e){return t._trim(),e&&(t.isTransferred=!0,e.push(t.arrayBuffer)),{length:t.length,arrayBuffer:t.arrayBuffer}},wi.deserialize=function(t){var e=Object.create(this.prototype);return e.arrayBuffer=t.arrayBuffer,e.length=t.length,e.capacity=t.arrayBuffer.byteLength/e.bytesPerElement,e._refreshViews(),e},wi.prototype._trim=function(){this.length!==this.capacity&&(this.capacity=this.length,this.arrayBuffer=this.arrayBuffer.slice(0,this.length*this.bytesPerElement),this._refreshViews())},wi.prototype.clear=function(){this.length=0},wi.prototype.resize=function(t){this.reserve(t),this.length=t},wi.prototype.reserve=function(t){if(t>this.capacity){this.capacity=Math.max(t,Math.floor(5*this.capacity),128),this.arrayBuffer=new ArrayBuffer(this.capacity*this.bytesPerElement);var e=this.uint8;this._refreshViews(),e&&this.uint8.set(e)}},wi.prototype._refreshViews=function(){throw new Error(\"_refreshViews() must be implemented by each concrete StructArray layout\")};var Mi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.int16[n+0]=e,this.int16[n+1]=r,t},e}(wi);Mi.prototype.bytesPerElement=4,Dn(\"StructArrayLayout2i4\",Mi);var Ai=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=4*t;return this.int16[a+0]=e,this.int16[a+1]=r,this.int16[a+2]=n,this.int16[a+3]=i,t},e}(wi);Ai.prototype.bytesPerElement=8,Dn(\"StructArrayLayout4i8\",Ai);var Si=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(wi);Si.prototype.bytesPerElement=12,Dn(\"StructArrayLayout2i4i12\",Si);var Ei=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=4*t,l=8*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.uint8[l+4]=n,this.uint8[l+5]=i,this.uint8[l+6]=a,this.uint8[l+7]=o,t},e}(wi);Ei.prototype.bytesPerElement=8,Dn(\"StructArrayLayout2i4ub8\",Ei);var Ci=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c){var u=this.length;return this.resize(u+1),this.emplace(u,t,e,r,n,i,a,o,s,l,c)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u){var f=9*t,h=18*t;return this.uint16[f+0]=e,this.uint16[f+1]=r,this.uint16[f+2]=n,this.uint16[f+3]=i,this.uint16[f+4]=a,this.uint16[f+5]=o,this.uint16[f+6]=s,this.uint16[f+7]=l,this.uint8[h+16]=c,this.uint8[h+17]=u,t},e}(wi);Ci.prototype.bytesPerElement=18,Dn(\"StructArrayLayout8ui2ub18\",Ci);var Li=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f){var h=this.length;return this.resize(h+1),this.emplace(h,t,e,r,n,i,a,o,s,l,c,u,f)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h){var p=12*t;return this.int16[p+0]=e,this.int16[p+1]=r,this.int16[p+2]=n,this.int16[p+3]=i,this.uint16[p+4]=a,this.uint16[p+5]=o,this.uint16[p+6]=s,this.uint16[p+7]=l,this.int16[p+8]=c,this.int16[p+9]=u,this.int16[p+10]=f,this.int16[p+11]=h,t},e}(wi);Li.prototype.bytesPerElement=24,Dn(\"StructArrayLayout4i4ui4i24\",Li);var Ii=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.float32[i+0]=e,this.float32[i+1]=r,this.float32[i+2]=n,t},e}(wi);Ii.prototype.bytesPerElement=12,Dn(\"StructArrayLayout3f12\",Ii);var Pi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){return this.uint32[1*t+0]=e,t},e}(wi);Pi.prototype.bytesPerElement=4,Dn(\"StructArrayLayout1ul4\",Pi);var zi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l){var c=this.length;return this.resize(c+1),this.emplace(c,t,e,r,n,i,a,o,s,l)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c){var u=10*t,f=5*t;return this.int16[u+0]=e,this.int16[u+1]=r,this.int16[u+2]=n,this.int16[u+3]=i,this.int16[u+4]=a,this.int16[u+5]=o,this.uint32[f+3]=s,this.uint16[u+8]=l,this.uint16[u+9]=c,t},e}(wi);zi.prototype.bytesPerElement=20,Dn(\"StructArrayLayout6i1ul2ui20\",zi);var Oi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(wi);Oi.prototype.bytesPerElement=12,Dn(\"StructArrayLayout2i2i2i12\",Oi);var Di=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i){var a=this.length;return this.resize(a+1),this.emplace(a,t,e,r,n,i)},e.prototype.emplace=function(t,e,r,n,i,a){var o=4*t,s=8*t;return this.float32[o+0]=e,this.float32[o+1]=r,this.float32[o+2]=n,this.int16[s+6]=i,this.int16[s+7]=a,t},e}(wi);Di.prototype.bytesPerElement=16,Dn(\"StructArrayLayout2f1f2i16\",Di);var Ri=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=12*t,o=3*t;return this.uint8[a+0]=e,this.uint8[a+1]=r,this.float32[o+1]=n,this.float32[o+2]=i,t},e}(wi);Ri.prototype.bytesPerElement=12,Dn(\"StructArrayLayout2ub2f12\",Ri);var Fi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.uint16[i+0]=e,this.uint16[i+1]=r,this.uint16[i+2]=n,t},e}(wi);Fi.prototype.bytesPerElement=6,Dn(\"StructArrayLayout3ui6\",Fi);var Bi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m){var v=this.length;return this.resize(v+1),this.emplace(v,t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v){var y=24*t,x=12*t,b=48*t;return this.int16[y+0]=e,this.int16[y+1]=r,this.uint16[y+2]=n,this.uint16[y+3]=i,this.uint32[x+2]=a,this.uint32[x+3]=o,this.uint32[x+4]=s,this.uint16[y+10]=l,this.uint16[y+11]=c,this.uint16[y+12]=u,this.float32[x+7]=f,this.float32[x+8]=h,this.uint8[b+36]=p,this.uint8[b+37]=d,this.uint8[b+38]=g,this.uint32[x+10]=m,this.int16[y+22]=v,t},e}(wi);Bi.prototype.bytesPerElement=48,Dn(\"StructArrayLayout2i2ui3ul3ui2f3ub1ul1i48\",Bi);var Ni=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,w,T,k,M,A,S){var E=this.length;return this.resize(E+1),this.emplace(E,t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,w,T,k,M,A,S)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,w,T,k,M,A,S,E){var C=34*t,L=17*t;return this.int16[C+0]=e,this.int16[C+1]=r,this.int16[C+2]=n,this.int16[C+3]=i,this.int16[C+4]=a,this.int16[C+5]=o,this.int16[C+6]=s,this.int16[C+7]=l,this.uint16[C+8]=c,this.uint16[C+9]=u,this.uint16[C+10]=f,this.uint16[C+11]=h,this.uint16[C+12]=p,this.uint16[C+13]=d,this.uint16[C+14]=g,this.uint16[C+15]=m,this.uint16[C+16]=v,this.uint16[C+17]=y,this.uint16[C+18]=x,this.uint16[C+19]=b,this.uint16[C+20]=_,this.uint16[C+21]=w,this.uint16[C+22]=T,this.uint32[L+12]=k,this.float32[L+13]=M,this.float32[L+14]=A,this.float32[L+15]=S,this.float32[L+16]=E,t},e}(wi);Ni.prototype.bytesPerElement=68,Dn(\"StructArrayLayout8i15ui1ul4f68\",Ni);var ji=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){return this.float32[1*t+0]=e,t},e}(wi);ji.prototype.bytesPerElement=4,Dn(\"StructArrayLayout1f4\",ji);var Ui=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.int16[i+0]=e,this.int16[i+1]=r,this.int16[i+2]=n,t},e}(wi);Ui.prototype.bytesPerElement=6,Dn(\"StructArrayLayout3i6\",Ui);var 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a=t;a<e;a++)this.paintVertexArray.emplace(a,r);this.maxValue=Math.max(this.maxValue,Math.abs(r))}},Sa.prototype.upload=function(t){this.paintVertexArray&&this.paintVertexArray.arrayBuffer&&(this.paintVertexBuffer&&this.paintVertexBuffer.buffer?this.paintVertexBuffer.updateData(this.paintVertexArray):this.paintVertexBuffer=t.createVertexBuffer(this.paintVertexArray,this.paintVertexAttributes,this.expression.isStateDependent))},Sa.prototype.destroy=function(){this.paintVertexBuffer&&this.paintVertexBuffer.destroy()};var Ea=function(t,e,r,n,i,a){this.expression=t,this.uniformNames=e.map((function(t){return\"u_\"+t+\"_t\"})),this.type=r,this.useIntegerZoom=n,this.zoom=i,this.maxValue=0,this.paintVertexAttributes=e.map((function(t){return{name:\"a_\"+t,type:\"Float32\",components:\"color\"===r?4:2,offset:0}})),this.paintVertexArray=new a};Ea.prototype.populatePaintArray=function(t,e,r,n,i){var a=this.expression.evaluate(new ii(this.zoom),e,{},n,[],i),o=this.expression.evaluate(new ii(this.zoom+1),e,{},n,[],i),s=this.paintVertexArray.length;this.paintVertexArray.resize(t),this._setPaintValue(s,t,a,o)},Ea.prototype.updatePaintArray=function(t,e,r,n){var i=this.expression.evaluate({zoom:this.zoom},r,n),a=this.expression.evaluate({zoom:this.zoom+1},r,n);this._setPaintValue(t,e,i,a)},Ea.prototype._setPaintValue=function(t,e,r,n){if(\"color\"===this.type)for(var i=ka(r),a=ka(n),o=t;o<e;o++)this.paintVertexArray.emplace(o,i[0],i[1],a[0],a[1]);else{for(var s=t;s<e;s++)this.paintVertexArray.emplace(s,r,n);this.maxValue=Math.max(this.maxValue,Math.abs(r),Math.abs(n))}},Ea.prototype.upload=function(t){this.paintVertexArray&&this.paintVertexArray.arrayBuffer&&(this.paintVertexBuffer&&this.paintVertexBuffer.buffer?this.paintVertexBuffer.updateData(this.paintVertexArray):this.paintVertexBuffer=t.createVertexBuffer(this.paintVertexArray,this.paintVertexAttributes,this.expression.isStateDependent))},Ea.prototype.destroy=function(){this.paintVertexBuffer&&this.paintVertexBuffer.destroy()},Ea.prototype.setUniform=function(t,e){var r=this.useIntegerZoom?Math.floor(e.zoom):e.zoom,n=l(this.expression.interpolationFactor(r,this.zoom,this.zoom+1),0,1);t.set(n)},Ea.prototype.getBinding=function(t,e,r){return new va(t,e)};var Ca=function(t,e,r,n,i,a){this.expression=t,this.type=e,this.useIntegerZoom=r,this.zoom=n,this.layerId=a,this.zoomInPaintVertexArray=new i,this.zoomOutPaintVertexArray=new i};Ca.prototype.populatePaintArray=function(t,e,r){var n=this.zoomInPaintVertexArray.length;this.zoomInPaintVertexArray.resize(t),this.zoomOutPaintVertexArray.resize(t),this._setPaintValues(n,t,e.patterns&&e.patterns[this.layerId],r)},Ca.prototype.updatePaintArray=function(t,e,r,n,i){this._setPaintValues(t,e,r.patterns&&r.patterns[this.layerId],i)},Ca.prototype._setPaintValues=function(t,e,r,n){if(n&&r){var i=n[r.min],a=n[r.mid],o=n[r.max];if(i&&a&&o)for(var s=t;s<e;s++)this.zoomInPaintVertexArray.emplace(s,a.tl[0],a.tl[1],a.br[0],a.br[1],i.tl[0],i.tl[1],i.br[0],i.br[1],a.pixelRatio,i.pixelRatio),this.zoomOutPaintVertexArray.emplace(s,a.tl[0],a.tl[1],a.br[0],a.br[1],o.tl[0],o.tl[1],o.br[0],o.br[1],a.pixelRatio,o.pixelRatio)}},Ca.prototype.upload=function(t){this.zoomInPaintVertexArray&&this.zoomInPaintVertexArray.arrayBuffer&&this.zoomOutPaintVertexArray&&this.zoomOutPaintVertexArray.arrayBuffer&&(this.zoomInPaintVertexBuffer=t.createVertexBuffer(this.zoomInPaintVertexArray,oa.members,this.expression.isStateDependent),this.zoomOutPaintVertexBuffer=t.createVertexBuffer(this.zoomOutPaintVertexArray,oa.members,this.expression.isStateDependent))},Ca.prototype.destroy=function(){this.zoomOutPaintVertexBuffer&&this.zoomOutPaintVertexBuffer.destroy(),this.zoomInPaintVertexBuffer&&this.zoomInPaintVertexBuffer.destroy()};var La=function(t,e,r,n){this.binders={},this.layoutAttributes=n,this._buffers=[];var i=[];for(var a in t.paint._values)if(r(a)){var o=t.paint.get(a);if(o instanceof fi&&Lr(o.property.specification)){var s=Pa(a,t.type),l=o.value,c=o.property.specification.type,u=o.property.useIntegerZoom,f=o.property.specification[\"property-type\"],h=\"cross-faded\"===f||\"cross-faded-data-driven\"===f;if(\"constant\"===l.kind)this.binders[a]=h?new Aa(l.value,s):new Ma(l.value,s,c),i.push(\"/u_\"+a);else if(\"source\"===l.kind||h){var p=za(a,c,\"source\");this.binders[a]=h?new Ca(l,c,u,e,p,t.id):new Sa(l,s,c,p),i.push(\"/a_\"+a)}else{var d=za(a,c,\"composite\");this.binders[a]=new Ea(l,s,c,u,e,d),i.push(\"/z_\"+a)}}}this.cacheKey=i.sort().join(\"\")};La.prototype.getMaxValue=function(t){var e=this.binders[t];return e instanceof Sa||e instanceof Ea?e.maxValue:0},La.prototype.populatePaintArrays=function(t,e,r,n,i){for(var a in this.binders){var o=this.binders[a];(o instanceof Sa||o instanceof Ea||o instanceof Ca)&&o.populatePaintArray(t,e,r,n,i)}},La.prototype.setConstantPatternPositions=function(t,e){for(var r in this.binders){var n=this.binders[r];n instanceof Aa&&n.setConstantPatternPositions(t,e)}},La.prototype.updatePaintArrays=function(t,e,r,n,i){var a=!1;for(var o in t)for(var s=0,l=e.getPositions(o);s<l.length;s+=1){var c=l[s],u=r.feature(c.index);for(var f in this.binders){var h=this.binders[f];if((h instanceof Sa||h instanceof Ea||h instanceof Ca)&&!0===h.expression.isStateDependent){var p=n.paint.get(f);h.expression=p.value,h.updatePaintArray(c.start,c.end,u,t[o],i),a=!0}}}return a},La.prototype.defines=function(){var t=[];for(var e in this.binders){var r=this.binders[e];(r instanceof Ma||r instanceof Aa)&&t.push.apply(t,r.uniformNames.map((function(t){return\"#define HAS_UNIFORM_\"+t})))}return t},La.prototype.getPaintVertexBuffers=function(){return this._buffers},La.prototype.getUniforms=function(t,e){var r=[];for(var n in this.binders){var i=this.binders[n];if(i instanceof Ma||i instanceof Aa||i instanceof Ea)for(var a=0,o=i.uniformNames;a<o.length;a+=1){var s=o[a];if(e[s]){var l=i.getBinding(t,e[s],s);r.push({name:s,property:n,binding:l})}}}return r},La.prototype.setUniforms=function(t,e,r,n){for(var i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.name,l=o.property;this.binders[l].setUniform(o.binding,n,r.get(l),s)}},La.prototype.updatePaintBuffers=function(t){for(var e in this._buffers=[],this.binders){var r=this.binders[e];if(t&&r instanceof Ca){var n=2===t.fromScale?r.zoomInPaintVertexBuffer:r.zoomOutPaintVertexBuffer;n&&this._buffers.push(n)}else(r instanceof Sa||r instanceof Ea)&&r.paintVertexBuffer&&this._buffers.push(r.paintVertexBuffer)}},La.prototype.upload=function(t){for(var e in this.binders){var r=this.binders[e];(r instanceof Sa||r instanceof Ea||r instanceof Ca)&&r.upload(t)}this.updatePaintBuffers()},La.prototype.destroy=function(){for(var t in this.binders){var e=this.binders[t];(e instanceof Sa||e instanceof Ea||e instanceof Ca)&&e.destroy()}};var Ia=function(t,e,r,n){void 0===n&&(n=function(){return!0}),this.programConfigurations={};for(var i=0,a=e;i<a.length;i+=1){var o=a[i];this.programConfigurations[o.id]=new La(o,r,n,t)}this.needsUpload=!1,this._featureMap=new fa,this._bufferOffset=0};function Pa(t,e){return{\"text-opacity\":[\"opacity\"],\"icon-opacity\":[\"opacity\"],\"text-color\":[\"fill_color\"],\"icon-color\":[\"fill_color\"],\"text-halo-color\":[\"halo_color\"],\"icon-halo-color\":[\"halo_color\"],\"text-halo-blur\":[\"halo_blur\"],\"icon-halo-blur\":[\"halo_blur\"],\"text-halo-width\":[\"halo_width\"],\"icon-halo-width\":[\"halo_width\"],\"line-gap-width\":[\"gapwidth\"],\"line-pattern\":[\"pattern_to\",\"pattern_from\",\"pixel_ratio_to\",\"pixel_ratio_from\"],\"fill-pattern\":[\"pattern_to\",\"pattern_from\",\"pixel_ratio_to\",\"pixel_ratio_from\"],\"fill-extrusion-pattern\":[\"pattern_to\",\"pattern_from\",\"pixel_ratio_to\",\"pixel_ratio_from\"]}[t]||[t.replace(e+\"-\",\"\").replace(/-/g,\"_\")]}function za(t,e,r){var n={color:{source:Gi,composite:Yi},number:{source:ji,composite:Gi}},i=function(t){return{\"line-pattern\":{source:Ci,composite:Ci},\"fill-pattern\":{source:Ci,composite:Ci},\"fill-extrusion-pattern\":{source:Ci,composite:Ci}}[t]}(t);return i&&i[r]||n[e][r]}Ia.prototype.populatePaintArrays=function(t,e,r,n,i,a){for(var o in this.programConfigurations)this.programConfigurations[o].populatePaintArrays(t,e,n,i,a);void 0!==e.id&&this._featureMap.add(e.id,r,this._bufferOffset,t),this._bufferOffset=t,this.needsUpload=!0},Ia.prototype.updatePaintArrays=function(t,e,r,n){for(var i=0,a=r;i<a.length;i+=1){var o=a[i];this.needsUpload=this.programConfigurations[o.id].updatePaintArrays(t,this._featureMap,e,o,n)||this.needsUpload}},Ia.prototype.get=function(t){return this.programConfigurations[t]},Ia.prototype.upload=function(t){if(this.needsUpload){for(var e in this.programConfigurations)this.programConfigurations[e].upload(t);this.needsUpload=!1}},Ia.prototype.destroy=function(){for(var t in this.programConfigurations)this.programConfigurations[t].destroy()},Dn(\"ConstantBinder\",Ma),Dn(\"CrossFadedConstantBinder\",Aa),Dn(\"SourceExpressionBinder\",Sa),Dn(\"CrossFadedCompositeBinder\",Ca),Dn(\"CompositeExpressionBinder\",Ea),Dn(\"ProgramConfiguration\",La,{omit:[\"_buffers\"]}),Dn(\"ProgramConfigurationSet\",Ia);var Oa={min:-1*Math.pow(2,14),max:Math.pow(2,14)-1};function Da(t){for(var e=8192/t.extent,r=t.loadGeometry(),n=0;n<r.length;n++)for(var i=r[n],a=0;a<i.length;a++){var o=i[a];o.x=Math.round(o.x*e),o.y=Math.round(o.y*e),(o.x<Oa.min||o.x>Oa.max||o.y<Oa.min||o.y>Oa.max)&&(_(\"Geometry exceeds allowed extent, reduce your vector tile buffer size\"),o.x=l(o.x,Oa.min,Oa.max),o.y=l(o.y,Oa.min,Oa.max))}return r}function Ra(t,e,r,n,i){t.emplaceBack(2*e+(n+1)/2,2*r+(i+1)/2)}var Fa=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new Mi,this.indexArray=new Fi,this.segments=new ia,this.programConfigurations=new Ia(na,t.layers,t.zoom),this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};function Ba(t,e){for(var r=0;r<t.length;r++)if(Wa(e,t[r]))return!0;for(var n=0;n<e.length;n++)if(Wa(t,e[n]))return!0;return!!Va(t,e)}function Na(t,e,r){return!!Wa(t,e)||!!Ha(e,t,r)}function ja(t,e){if(1===t.length)return Ya(e,t[0]);for(var r=0;r<e.length;r++)for(var n=e[r],i=0;i<n.length;i++)if(Wa(t,n[i]))return!0;for(var a=0;a<t.length;a++)if(Ya(e,t[a]))return!0;for(var o=0;o<e.length;o++)if(Va(t,e[o]))return!0;return!1}function Ua(t,e,r){if(t.length>1){if(Va(t,e))return!0;for(var n=0;n<e.length;n++)if(Ha(e[n],t,r))return!0}for(var i=0;i<t.length;i++)if(Ha(t[i],e,r))return!0;return!1}function Va(t,e){if(0===t.length||0===e.length)return!1;for(var r=0;r<t.length-1;r++)for(var n=t[r],i=t[r+1],a=0;a<e.length-1;a++)if(qa(n,i,e[a],e[a+1]))return!0;return!1}function qa(t,e,r,n){return w(t,r,n)!==w(e,r,n)&&w(t,e,r)!==w(t,e,n)}function Ha(t,e,r){var n=r*r;if(1===e.length)return t.distSqr(e[0])<n;for(var i=1;i<e.length;i++)if(Ga(t,e[i-1],e[i])<n)return!0;return!1}function Ga(t,e,r){var n=e.distSqr(r);if(0===n)return t.distSqr(e);var i=((t.x-e.x)*(r.x-e.x)+(t.y-e.y)*(r.y-e.y))/n;return t.distSqr(i<0?e:i>1?r:r.sub(e)._mult(i)._add(e))}function Ya(t,e){for(var r,n,i,a=!1,o=0;o<t.length;o++)for(var s=0,l=(r=t[o]).length-1;s<r.length;l=s++)(n=r[s]).y>e.y!=(i=r[l]).y>e.y&&e.x<(i.x-n.x)*(e.y-n.y)/(i.y-n.y)+n.x&&(a=!a);return a}function Wa(t,e){for(var r=!1,n=0,i=t.length-1;n<t.length;i=n++){var a=t[n],o=t[i];a.y>e.y!=o.y>e.y&&e.x<(o.x-a.x)*(e.y-a.y)/(o.y-a.y)+a.x&&(r=!r)}return r}function Xa(t,e,r){var n=r[0],i=r[2];if(t.x<n.x&&e.x<n.x||t.x>i.x&&e.x>i.x||t.y<n.y&&e.y<n.y||t.y>i.y&&e.y>i.y)return!1;var a=w(t,e,r[0]);return a!==w(t,e,r[1])||a!==w(t,e,r[2])||a!==w(t,e,r[3])}function Za(t,e,r){var n=e.paint.get(t).value;return\"constant\"===n.kind?n.value:r.programConfigurations.get(e.id).getMaxValue(t)}function Ja(t){return Math.sqrt(t[0]*t[0]+t[1]*t[1])}function Ka(t,e,r,n,a){if(!e[0]&&!e[1])return t;var o=i.convert(e)._mult(a);\"viewport\"===r&&o._rotate(-n);for(var s=[],l=0;l<t.length;l++)s.push(t[l].sub(o));return s}Fa.prototype.populate=function(t,e,r){var n=this.layers[0],i=[],a=null;\"circle\"===n.type&&(a=n.layout.get(\"circle-sort-key\"));for(var o=0,s=t;o<s.length;o+=1){var l=s[o],c=l.feature,u=l.id,f=l.index,h=l.sourceLayerIndex,p=this.layers[0]._featureFilter.needGeometry,d={type:c.type,id:u,properties:c.properties,geometry:p?Da(c):[]};if(this.layers[0]._featureFilter.filter(new ii(this.zoom),d,r)){p||(d.geometry=Da(c));var g=a?a.evaluate(d,{},r):void 0;i.push({id:u,properties:c.properties,type:c.type,sourceLayerIndex:h,index:f,geometry:d.geometry,patterns:{},sortKey:g})}}a&&i.sort((function(t,e){return t.sortKey-e.sortKey}));for(var m=0,v=i;m<v.length;m+=1){var y=v[m],x=y.geometry,b=y.index,_=y.sourceLayerIndex,w=t[b].feature;this.addFeature(y,x,b,r),e.featureIndex.insert(w,x,b,_,this.index)}},Fa.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},Fa.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},Fa.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},Fa.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,na),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},Fa.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},Fa.prototype.addFeature=function(t,e,r,n){for(var i=0,a=e;i<a.length;i+=1)for(var o=0,s=a[i];o<s.length;o+=1){var l=s[o],c=l.x,u=l.y;if(!(c<0||c>=8192||u<0||u>=8192)){var f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray,t.sortKey),h=f.vertexLength;Ra(this.layoutVertexArray,c,u,-1,-1),Ra(this.layoutVertexArray,c,u,1,-1),Ra(this.layoutVertexArray,c,u,1,1),Ra(this.layoutVertexArray,c,u,-1,1),this.indexArray.emplaceBack(h,h+1,h+2),this.indexArray.emplaceBack(h,h+3,h+2),f.vertexLength+=4,f.primitiveLength+=2}}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,{},n)},Dn(\"CircleBucket\",Fa,{omit:[\"layers\"]});var Qa=new yi({\"circle-sort-key\":new di(At.layout_circle[\"circle-sort-key\"])}),$a={paint:new yi({\"circle-radius\":new di(At.paint_circle[\"circle-radius\"]),\"circle-color\":new di(At.paint_circle[\"circle-color\"]),\"circle-blur\":new di(At.paint_circle[\"circle-blur\"]),\"circle-opacity\":new di(At.paint_circle[\"circle-opacity\"]),\"circle-translate\":new pi(At.paint_circle[\"circle-translate\"]),\"circle-translate-anchor\":new 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2:for(n=0;n<l.length;n++)u(l[n]);break;case 3:for(l=function(t){var e=t.length;if(e<=1)return[t];for(var r,n,i=[],a=0;a<e;a++){var o=us(t[a]);0!==o&&(void 0===n&&(n=o<0),n===o<0?(r&&i.push(r),r=[t[a]]):r.push(t[a]))}return r&&i.push(r),i}(l),n=0;n<l.length;n++)for(i=0;i<l[n].length;i++)u(l[n][i])}1===l.length?l=l[0]:c=\"Multi\"+c;var h={type:\"Feature\",geometry:{type:c,coordinates:l},properties:this.properties};return\"id\"in this&&(h.id=this.id),h};var fs=hs;function hs(t,e){this.version=1,this.name=null,this.extent=4096,this.length=0,this._pbf=t,this._keys=[],this._values=[],this._features=[],t.readFields(ps,this,e),this.length=this._features.length}function ps(t,e,r){15===t?e.version=r.readVarint():1===t?e.name=r.readString():5===t?e.extent=r.readVarint():2===t?e._features.push(r.pos):3===t?e._keys.push(r.readString()):4===t&&e._values.push(function(t){for(var e=null,r=t.readVarint()+t.pos;t.pos<r;){var n=t.readVarint()>>3;e=1===n?t.readString():2===n?t.readFloat():3===n?t.readDouble():4===n?t.readVarint64():5===n?t.readVarint():6===n?t.readSVarint():7===n?t.readBoolean():null}return e}(r))}function ds(t,e,r){if(3===t){var n=new fs(r,r.readVarint()+r.pos);n.length&&(e[n.name]=n)}}hs.prototype.feature=function(t){if(t<0||t>=this._features.length)throw new Error(\"feature index out of bounds\");this._pbf.pos=this._features[t];var e=this._pbf.readVarint()+this._pbf.pos;return new ss(this._pbf,e,this.extent,this._keys,this._values)};var gs={VectorTile:function(t,e){this.layers=t.readFields(ds,{},e)},VectorTileFeature:ss,VectorTileLayer:fs},ms=gs.VectorTileFeature.types,vs=Math.pow(2,13);function ys(t,e,r,n,i,a,o,s){t.emplaceBack(e,r,2*Math.floor(n*vs)+o,i*vs*2,a*vs*2,Math.round(s))}var xs=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new Si,this.indexArray=new Fi,this.programConfigurations=new Ia(os,t.layers,t.zoom),this.segments=new ia,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};function bs(t,e){return t.x===e.x&&(t.x<0||t.x>8192)||t.y===e.y&&(t.y<0||t.y>8192)}xs.prototype.populate=function(t,e,r){this.features=[],this.hasPattern=ts(\"fill-extrusion\",this.layers,e);for(var n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.feature,s=a.id,l=a.index,c=a.sourceLayerIndex,u=this.layers[0]._featureFilter.needGeometry,f={type:o.type,id:s,properties:o.properties,geometry:u?Da(o):[]};if(this.layers[0]._featureFilter.filter(new ii(this.zoom),f,r)){var h={id:s,sourceLayerIndex:c,index:l,geometry:u?f.geometry:Da(o),properties:o.properties,type:o.type,patterns:{}};void 0!==o.id&&(h.id=o.id),this.hasPattern?this.features.push(es(\"fill-extrusion\",this.layers,h,this.zoom,e)):this.addFeature(h,h.geometry,l,r,{}),e.featureIndex.insert(o,h.geometry,l,c,this.index,!0)}}},xs.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.features;n<i.length;n+=1){var a=i[n];this.addFeature(a,a.geometry,a.index,e,r)}},xs.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},xs.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},xs.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},xs.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,os),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},xs.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},xs.prototype.addFeature=function(t,e,r,n,i){for(var a=0,o=Qo(e,500);a<o.length;a+=1){for(var s=o[a],l=0,c=0,u=s;c<u.length;c+=1)l+=u[c].length;for(var f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray),h=0,p=s;h<p.length;h+=1){var d=p[h];if(0!==d.length&&!((P=d).every((function(t){return t.x<0}))||P.every((function(t){return t.x>8192}))||P.every((function(t){return t.y<0}))||P.every((function(t){return t.y>8192}))))for(var g=0,m=0;m<d.length;m++){var v=d[m];if(m>=1){var y=d[m-1];if(!bs(v,y)){f.vertexLength+4>ia.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));var x=v.sub(y)._perp()._unit(),b=y.dist(v);g+b>32768&&(g=0),ys(this.layoutVertexArray,v.x,v.y,x.x,x.y,0,0,g),ys(this.layoutVertexArray,v.x,v.y,x.x,x.y,0,1,g),ys(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,0,g+=b),ys(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,1,g);var _=f.vertexLength;this.indexArray.emplaceBack(_,_+2,_+1),this.indexArray.emplaceBack(_+1,_+2,_+3),f.vertexLength+=4,f.primitiveLength+=2}}}}if(f.vertexLength+l>ia.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(l,this.layoutVertexArray,this.indexArray)),\"Polygon\"===ms[t.type]){for(var w=[],T=[],k=f.vertexLength,M=0,A=s;M<A.length;M+=1){var S=A[M];if(0!==S.length){S!==s[0]&&T.push(w.length/2);for(var E=0;E<S.length;E++){var C=S[E];ys(this.layoutVertexArray,C.x,C.y,0,0,1,1,0),w.push(C.x),w.push(C.y)}}}for(var 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a=e[n],o=t[0],s=r.sub(i),l=a.sub(i),c=o.sub(i),u=Ts(s,s),f=Ts(s,l),h=Ts(l,l),p=Ts(c,s),d=Ts(c,l),g=u*h-f*f,m=(h*p-f*d)/g,v=(u*d-f*p)/g,y=i.z*(1-m-v)+r.z*m+a.z*v;if(isFinite(y))return y}return 1/0}for(var x=1/0,b=0,_=e;b<_.length;b+=1)x=Math.min(x,_[b].z);return x}var Ms=Ti([{name:\"a_pos_normal\",components:2,type:\"Int16\"},{name:\"a_data\",components:4,type:\"Uint8\"}],4).members,As=gs.VectorTileFeature.types,Ss=Math.cos(Math.PI/180*37.5),Es=Math.pow(2,14)/.5,Cs=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.patternFeatures=[],this.layoutVertexArray=new Ei,this.indexArray=new Fi,this.programConfigurations=new Ia(Ms,t.layers,t.zoom),this.segments=new ia,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return 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a=this.layers[0].layout,o=a.get(\"line-join\").evaluate(t,{}),s=a.get(\"line-cap\"),l=a.get(\"line-miter-limit\"),c=a.get(\"line-round-limit\"),u=0,f=e;u<f.length;u+=1)this.addLine(f[u],t,o,s,l,c);this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},Cs.prototype.addLine=function(t,e,r,n,i,a){if(this.distance=0,this.scaledDistance=0,this.totalDistance=0,e.properties&&e.properties.hasOwnProperty(\"mapbox_clip_start\")&&e.properties.hasOwnProperty(\"mapbox_clip_end\")){this.clipStart=+e.properties.mapbox_clip_start,this.clipEnd=+e.properties.mapbox_clip_end;for(var o=0;o<t.length-1;o++)this.totalDistance+=t[o].dist(t[o+1]);this.updateScaledDistance()}for(var s=\"Polygon\"===As[e.type],l=t.length;l>=2&&t[l-1].equals(t[l-2]);)l--;for(var c=0;c<l-1&&t[c].equals(t[c+1]);)c++;if(!(l<(s?3:2))){\"bevel\"===r&&(i=1.05);var u,f=this.overscaling<=16?122880/(512*this.overscaling):0,h=this.segments.prepareSegment(10*l,this.layoutVertexArray,this.indexArray),p=void 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o=e.y*n-e.x,s=-e.y-e.x*n;this.addHalfVertex(t,e.x+e.y*r,e.y-e.x*r,a,!1,r,i),this.addHalfVertex(t,o,s,a,!0,-n,i),this.distance>Es/2&&0===this.totalDistance&&(this.distance=0,this.addCurrentVertex(t,e,r,n,i,a))},Cs.prototype.addHalfVertex=function(t,e,r,n,i,a,o){var s=.5*this.scaledDistance;this.layoutVertexArray.emplaceBack((t.x<<1)+(n?1:0),(t.y<<1)+(i?1:0),Math.round(63*e)+128,Math.round(63*r)+128,1+(0===a?0:a<0?-1:1)|(63&s)<<2,s>>6);var l=o.vertexLength++;this.e1>=0&&this.e2>=0&&(this.indexArray.emplaceBack(this.e1,this.e2,l),o.primitiveLength++),i?this.e2=l:this.e1=l},Cs.prototype.updateScaledDistance=function(){this.scaledDistance=this.totalDistance>0?(this.clipStart+(this.clipEnd-this.clipStart)*this.distance/this.totalDistance)*(Es-1):this.distance},Cs.prototype.updateDistance=function(t,e){this.distance+=t.dist(e),this.updateScaledDistance()},Dn(\"LineBucket\",Cs,{omit:[\"layers\",\"patternFeatures\"]});var Ls=new yi({\"line-cap\":new 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n,i,a=0;a<e.length;a++){if((n=e.charCodeAt(a))>55295&&n<57344){if(!i){n>56319||a+1===e.length?(t[r++]=239,t[r++]=191,t[r++]=189):i=n;continue}if(n<56320){t[r++]=239,t[r++]=191,t[r++]=189,i=n;continue}n=i-55296<<10|n-56320|65536,i=null}else i&&(t[r++]=239,t[r++]=191,t[r++]=189,i=null);n<128?t[r++]=n:(n<2048?t[r++]=n>>6|192:(n<65536?t[r++]=n>>12|224:(t[r++]=n>>18|240,t[r++]=n>>12&63|128),t[r++]=n>>6&63|128),t[r++]=63&n|128)}return r}(this.buf,t,this.pos);var r=this.pos-e;r>=128&&Zs(e,r,this),this.pos=e-1,this.writeVarint(r),this.pos+=r},writeFloat:function(t){this.realloc(4),qs(this.buf,t,this.pos,!0,23,4),this.pos+=4},writeDouble:function(t){this.realloc(8),qs(this.buf,t,this.pos,!0,52,8),this.pos+=8},writeBytes:function(t){var e=t.length;this.writeVarint(e),this.realloc(e);for(var r=0;r<e;r++)this.buf[this.pos++]=t[r]},writeRawMessage:function(t,e){this.pos++;var r=this.pos;t(e,this);var n=this.pos-r;n>=128&&Zs(r,n,this),this.pos=r-1,this.writeVarint(n),this.pos+=n},writeMessage:function(t,e,r){this.writeTag(t,Gs.Bytes),this.writeRawMessage(e,r)},writePackedVarint:function(t,e){e.length&&this.writeMessage(t,Js,e)},writePackedSVarint:function(t,e){e.length&&this.writeMessage(t,Ks,e)},writePackedBoolean:function(t,e){e.length&&this.writeMessage(t,tl,e)},writePackedFloat:function(t,e){e.length&&this.writeMessage(t,Qs,e)},writePackedDouble:function(t,e){e.length&&this.writeMessage(t,$s,e)},writePackedFixed32:function(t,e){e.length&&this.writeMessage(t,el,e)},writePackedSFixed32:function(t,e){e.length&&this.writeMessage(t,rl,e)},writePackedFixed64:function(t,e){e.length&&this.writeMessage(t,nl,e)},writePackedSFixed64:function(t,e){e.length&&this.writeMessage(t,il,e)},writeBytesField:function(t,e){this.writeTag(t,Gs.Bytes),this.writeBytes(e)},writeFixed32Field:function(t,e){this.writeTag(t,Gs.Fixed32),this.writeFixed32(e)},writeSFixed32Field:function(t,e){this.writeTag(t,Gs.Fixed32),this.writeSFixed32(e)},writeFixed64Field:function(t,e){this.writeTag(t,Gs.Fixed64),this.writeFixed64(e)},writeSFixed64Field:function(t,e){this.writeTag(t,Gs.Fixed64),this.writeSFixed64(e)},writeVarintField:function(t,e){this.writeTag(t,Gs.Varint),this.writeVarint(e)},writeSVarintField:function(t,e){this.writeTag(t,Gs.Varint),this.writeSVarint(e)},writeStringField:function(t,e){this.writeTag(t,Gs.Bytes),this.writeString(e)},writeFloatField:function(t,e){this.writeTag(t,Gs.Fixed32),this.writeFloat(e)},writeDoubleField:function(t,e){this.writeTag(t,Gs.Fixed64),this.writeDouble(e)},writeBooleanField:function(t,e){this.writeVarintField(t,Boolean(e))}};var hl=function(t,e){var r=e.pixelRatio,n=e.version,i=e.stretchX,a=e.stretchY,o=e.content;this.paddedRect=t,this.pixelRatio=r,this.stretchX=i,this.stretchY=a,this.content=o,this.version=n},pl={tl:{configurable:!0},br:{configurable:!0},tlbr:{configurable:!0},displaySize:{configurable:!0}};pl.tl.get=function(){return[this.paddedRect.x+1,this.paddedRect.y+1]},pl.br.get=function(){return[this.paddedRect.x+this.paddedRect.w-1,this.paddedRect.y+this.paddedRect.h-1]},pl.tlbr.get=function(){return this.tl.concat(this.br)},pl.displaySize.get=function(){return[(this.paddedRect.w-2)/this.pixelRatio,(this.paddedRect.h-2)/this.pixelRatio]},Object.defineProperties(hl.prototype,pl);var dl=function(t,e){var r={},n={};this.haveRenderCallbacks=[];var i=[];this.addImages(t,r,i),this.addImages(e,n,i);var a=fl(i),o=new po({width:a.w||1,height:a.h||1});for(var s in t){var l=t[s],c=r[s].paddedRect;po.copy(l.data,o,{x:0,y:0},{x:c.x+1,y:c.y+1},l.data)}for(var u in e){var f=e[u],h=n[u].paddedRect,p=h.x+1,d=h.y+1,g=f.data.width,m=f.data.height;po.copy(f.data,o,{x:0,y:0},{x:p,y:d},f.data),po.copy(f.data,o,{x:0,y:m-1},{x:p,y:d-1},{width:g,height:1}),po.copy(f.data,o,{x:0,y:0},{x:p,y:d+m},{width:g,height:1}),po.copy(f.data,o,{x:g-1,y:0},{x:p-1,y:d},{width:1,height:m}),po.copy(f.data,o,{x:0,y:0},{x:p+g,y:d},{width:1,height:m})}this.image=o,this.iconPositions=r,this.patternPositions=n};dl.prototype.addImages=function(t,e,r){for(var n in t){var i=t[n],a={x:0,y:0,w:i.data.width+2,h:i.data.height+2};r.push(a),e[n]=new hl(a,i),i.hasRenderCallback&&this.haveRenderCallbacks.push(n)}},dl.prototype.patchUpdatedImages=function(t,e){for(var r in t.dispatchRenderCallbacks(this.haveRenderCallbacks),t.updatedImages)this.patchUpdatedImage(this.iconPositions[r],t.getImage(r),e),this.patchUpdatedImage(this.patternPositions[r],t.getImage(r),e)},dl.prototype.patchUpdatedImage=function(t,e,r){if(t&&e&&t.version!==e.version){t.version=e.version;var n=t.tl;r.update(e.data,void 0,{x:n[0],y:n[1]})}},Dn(\"ImagePosition\",hl),Dn(\"ImageAtlas\",dl);var gl={horizontal:1,vertical:2,horizontalOnly:3},ml=function(){this.scale=1,this.fontStack=\"\",this.imageName=null};ml.forText=function(t,e){var r=new ml;return r.scale=t||1,r.fontStack=e,r},ml.forImage=function(t){var e=new ml;return e.imageName=t,e};var vl=function(){this.text=\"\",this.sectionIndex=[],this.sections=[],this.imageSectionID=null};function yl(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g){var m,v=vl.fromFeature(t,i);f===gl.vertical&&v.verticalizePunctuation();var y=ni.processBidirectionalText,x=ni.processStyledBidirectionalText;if(y&&1===v.sections.length){m=[];for(var b=0,_=y(v.toString(),Ml(v,c,a,e,n,p,d));b<_.length;b+=1){var w=_[b],T=new vl;T.text=w,T.sections=v.sections;for(var k=0;k<w.length;k++)T.sectionIndex.push(0);m.push(T)}}else if(x){m=[];for(var M=0,A=x(v.text,v.sectionIndex,Ml(v,c,a,e,n,p,d));M<A.length;M+=1){var S=A[M],E=new vl;E.text=S[0],E.sectionIndex=S[1],E.sections=v.sections,m.push(E)}}else m=function(t,e){for(var r=[],n=t.text,i=0,a=0,o=e;a<o.length;a+=1){var s=o[a];r.push(t.substring(i,s)),i=s}return i<n.length&&r.push(t.substring(i,n.length)),r}(v,Ml(v,c,a,e,n,p,d));var C=[],L={positionedLines:C,text:v.toString(),top:u[1],bottom:u[1],left:u[0],right:u[0],writingMode:f,iconsInText:!1,verticalizable:!1};return function(t,e,r,n,i,a,o,s,l,c,u,f){for(var h=0,p=-17,d=0,g=0,m=\"right\"===s?1:\"left\"===s?0:.5,v=0,y=0,x=i;y<x.length;y+=1){var b=x[y];b.trim();var _=b.getMaxScale(),w=24*(_-1),T={positionedGlyphs:[],lineOffset:0};t.positionedLines[v]=T;var k=T.positionedGlyphs,M=0;if(b.length()){for(var A=0;A<b.length();A++){var S=b.getSection(A),E=b.getSectionIndex(A),C=b.getCharCode(A),L=0,I=null,P=null,z=null,O=24,D=!(l===gl.horizontal||!u&&!Hn(C)||u&&(xl[C]||(H=C,Vn.Arabic(H)||Vn[\"Arabic Supplement\"](H)||Vn[\"Arabic Extended-A\"](H)||Vn[\"Arabic Presentation Forms-A\"](H)||Vn[\"Arabic Presentation Forms-B\"](H))));if(S.imageName){var R=n[S.imageName];if(!R)continue;z=S.imageName,t.iconsInText=t.iconsInText||!0,P=R.paddedRect;var F=R.displaySize;S.scale=24*S.scale/f,L=w+(24-F[1]*S.scale),O=(I={width:F[0],height:F[1],left:1,top:-3,advance:D?F[1]:F[0]}).advance;var B=D?F[0]*S.scale-24*_:F[1]*S.scale-24*_;B>0&&B>M&&(M=B)}else{var N=r[S.fontStack],j=N&&N[C];if(j&&j.rect)P=j.rect,I=j.metrics;else{var U=e[S.fontStack],V=U&&U[C];if(!V)continue;I=V.metrics}L=24*(_-S.scale)}D?(t.verticalizable=!0,k.push({glyph:C,imageName:z,x:h,y:p+L,vertical:D,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:I,rect:P}),h+=O*S.scale+c):(k.push({glyph:C,imageName:z,x:h,y:p+L,vertical:D,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:I,rect:P}),h+=I.advance*S.scale+c)}0!==k.length&&(d=Math.max(h-c,d),Sl(k,0,k.length-1,m,M)),h=0;var q=a*_+M;T.lineOffset=Math.max(M,w),p+=q,g=Math.max(q,g),++v}else p+=a,++v}var H,G=p- -17,Y=Al(o),W=Y.horizontalAlign,X=Y.verticalAlign;(function(t,e,r,n,i,a,o,s,l){var c,u=(e-r)*i;c=a!==o?-s*n- -17:(-n*l+.5)*o;for(var f=0,h=t;f<h.length;f+=1)for(var p=0,d=h[f].positionedGlyphs;p<d.length;p+=1){var g=d[p];g.x+=u,g.y+=c}})(t.positionedLines,m,W,X,d,g,a,G,i.length),t.top+=-X*G,t.bottom=t.top+G,t.left+=-W*d,t.right=t.left+d}(L,e,r,n,m,o,s,l,f,c,h,g),!function(t){for(var e=0,r=t;e<r.length;e+=1)if(0!==r[e].positionedGlyphs.length)return!1;return!0}(C)&&L}vl.fromFeature=function(t,e){for(var r=new vl,n=0;n<t.sections.length;n++){var i=t.sections[n];i.image?r.addImageSection(i):r.addTextSection(i,e)}return r},vl.prototype.length=function(){return this.text.length},vl.prototype.getSection=function(t){return this.sections[this.sectionIndex[t]]},vl.prototype.getSectionIndex=function(t){return this.sectionIndex[t]},vl.prototype.getCharCode=function(t){return this.text.charCodeAt(t)},vl.prototype.verticalizePunctuation=function(){this.text=function(t){for(var e=\"\",r=0;r<t.length;r++){var n=t.charCodeAt(r+1)||null,i=t.charCodeAt(r-1)||null;e+=n&&Gn(n)&&!Us[t[r+1]]||i&&Gn(i)&&!Us[t[r-1]]||!Us[t[r]]?t[r]:Us[t[r]]}return e}(this.text)},vl.prototype.trim=function(){for(var t=0,e=0;e<this.text.length&&xl[this.text.charCodeAt(e)];e++)t++;for(var r=this.text.length,n=this.text.length-1;n>=0&&n>=t&&xl[this.text.charCodeAt(n)];n--)r--;this.text=this.text.substring(t,r),this.sectionIndex=this.sectionIndex.slice(t,r)},vl.prototype.substring=function(t,e){var r=new vl;return r.text=this.text.substring(t,e),r.sectionIndex=this.sectionIndex.slice(t,e),r.sections=this.sections,r},vl.prototype.toString=function(){return this.text},vl.prototype.getMaxScale=function(){var t=this;return this.sectionIndex.reduce((function(e,r){return Math.max(e,t.sections[r].scale)}),0)},vl.prototype.addTextSection=function(t,e){this.text+=t.text,this.sections.push(ml.forText(t.scale,t.fontStack||e));for(var r=this.sections.length-1,n=0;n<t.text.length;++n)this.sectionIndex.push(r)},vl.prototype.addImageSection=function(t){var e=t.image?t.image.name:\"\";if(0!==e.length){var r=this.getNextImageSectionCharCode();r?(this.text+=String.fromCharCode(r),this.sections.push(ml.forImage(e)),this.sectionIndex.push(this.sections.length-1)):_(\"Reached maximum number of images 6401\")}else _(\"Can't add FormattedSection with an empty image.\")},vl.prototype.getNextImageSectionCharCode=function(){return this.imageSectionID?this.imageSectionID>=63743?null:++this.imageSectionID:(this.imageSectionID=57344,this.imageSectionID)};var xl={9:!0,10:!0,11:!0,12:!0,13:!0,32:!0},bl={};function _l(t,e,r,n,i,a){if(e.imageName){var o=n[e.imageName];return o?o.displaySize[0]*e.scale*24/a+i:0}var s=r[e.fontStack],l=s&&s[t];return l?l.metrics.advance*e.scale+i:0}function wl(t,e,r,n){var i=Math.pow(t-e,2);return n?t<e?i/2:2*i:i+Math.abs(r)*r}function Tl(t,e,r){var n=0;return 10===t&&(n-=1e4),r&&(n+=150),40!==t&&65288!==t||(n+=50),41!==e&&65289!==e||(n+=50),n}function kl(t,e,r,n,i,a){for(var o=null,s=wl(e,r,i,a),l=0,c=n;l<c.length;l+=1){var u=c[l],f=wl(e-u.x,r,i,a)+u.badness;f<=s&&(o=u,s=f)}return{index:t,x:e,priorBreak:o,badness:s}}function Ml(t,e,r,n,i,a,o){if(\"point\"!==a)return[];if(!t)return[];for(var s,l=[],c=function(t,e,r,n,i,a){for(var o=0,s=0;s<t.length();s++){var l=t.getSection(s);o+=_l(t.getCharCode(s),l,n,i,e,a)}return o/Math.max(1,Math.ceil(o/r))}(t,e,r,n,i,o),u=t.text.indexOf(\"\\u200b\")>=0,f=0,h=0;h<t.length();h++){var p=t.getSection(h),d=t.getCharCode(h);if(xl[d]||(f+=_l(d,p,n,i,e,o)),h<t.length()-1){var g=!((s=d)<11904||!(Vn[\"Bopomofo Extended\"](s)||Vn.Bopomofo(s)||Vn[\"CJK Compatibility Forms\"](s)||Vn[\"CJK Compatibility Ideographs\"](s)||Vn[\"CJK Compatibility\"](s)||Vn[\"CJK Radicals Supplement\"](s)||Vn[\"CJK Strokes\"](s)||Vn[\"CJK Symbols and Punctuation\"](s)||Vn[\"CJK Unified Ideographs Extension A\"](s)||Vn[\"CJK Unified 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o,s=t.image;if(s.content){var l=s.content,c=s.pixelRatio||1;o=[l[0]/c,l[1]/c,s.displaySize[0]-l[2]/c,s.displaySize[1]-l[3]/c]}var u,f,h,p,d=e.left*a,g=e.right*a;\"width\"===r||\"both\"===r?(p=i[0]+d-n[3],f=i[0]+g+n[1]):f=(p=i[0]+(d+g-s.displaySize[0])/2)+s.displaySize[0];var m=e.top*a,v=e.bottom*a;return\"height\"===r||\"both\"===r?(u=i[1]+m-n[0],h=i[1]+v+n[2]):h=(u=i[1]+(m+v-s.displaySize[1])/2)+s.displaySize[1],{image:s,top:u,right:f,bottom:h,left:p,collisionPadding:o}}bl[10]=!0,bl[32]=!0,bl[38]=!0,bl[40]=!0,bl[41]=!0,bl[43]=!0,bl[45]=!0,bl[47]=!0,bl[173]=!0,bl[183]=!0,bl[8203]=!0,bl[8208]=!0,bl[8211]=!0,bl[8231]=!0;var Cl=function(t){function e(e,r,n,i){t.call(this,e,r),this.angle=n,void 0!==i&&(this.segment=i)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.clone=function(){return new e(this.x,this.y,this.angle,this.segment)},e}(i);function Ll(t,e){var r=e.expression;if(\"constant\"===r.kind)return{kind:\"constant\",layoutSize:r.evaluate(new ii(t+1))};if(\"source\"===r.kind)return{kind:\"source\"};for(var n=r.zoomStops,i=r.interpolationType,a=0;a<n.length&&n[a]<=t;)a++;for(var o=a=Math.max(0,a-1);o<n.length&&n[o]<t+1;)o++;o=Math.min(n.length-1,o);var s=n[a],l=n[o];return\"composite\"===r.kind?{kind:\"composite\",minZoom:s,maxZoom:l,interpolationType:i}:{kind:\"camera\",minZoom:s,maxZoom:l,minSize:r.evaluate(new ii(s)),maxSize:r.evaluate(new ii(l)),interpolationType:i}}function Il(t,e,r){var n=e.uSize,i=r.lowerSize;return\"source\"===t.kind?i/128:\"composite\"===t.kind?Ue(i/128,r.upperSize/128,e.uSizeT):n}function Pl(t,e){var r=0,n=0;if(\"constant\"===t.kind)n=t.layoutSize;else if(\"source\"!==t.kind){var i=t.interpolationType,a=i?l(rr.interpolationFactor(i,e,t.minZoom,t.maxZoom),0,1):0;\"camera\"===t.kind?n=Ue(t.minSize,t.maxSize,a):r=a}return{uSizeT:r,uSize:n}}Dn(\"Anchor\",Cl);var 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h=Hl(n.stretch-x,b,u,t.left),p=Gl(n.fixed-T,k,n.stretch,g),d=Hl(a.stretch-_,w,f,t.top),v=Gl(a.fixed-M,A,a.stretch,m),y=Hl(l.stretch-x,b,u,t.left),S=Gl(l.fixed-T,k,l.stretch,g),E=Hl(c.stretch-_,w,f,t.top),C=Gl(c.fixed-M,A,c.stretch,m),L=new i(h,d),I=new i(y,d),P=new i(y,E),z=new i(h,E),O=new i(p/s,v/s),D=new i(S/s,C/s),R=e*Math.PI/180;if(R){var F=Math.sin(R),B=Math.cos(R),N=[B,-F,F,B];L._matMult(N),I._matMult(N),z._matMult(N),P._matMult(N)}var j=n.stretch+n.fixed,U=a.stretch+a.fixed;return{tl:L,tr:I,bl:z,br:P,tex:{x:o.paddedRect.x+1+j,y:o.paddedRect.y+1+U,w:l.stretch+l.fixed-j,h:c.stretch+c.fixed-U},writingMode:void 0,glyphOffset:[0,0],sectionIndex:0,pixelOffsetTL:O,pixelOffsetBR:D,minFontScaleX:k/s/u,minFontScaleY:A/s/f,isSDF:r}};if(n&&(o.stretchX||o.stretchY))for(var C=ql(h,v,g),L=ql(p,y,m),I=0;I<C.length-1;I++)for(var P=C[I],z=C[I+1],O=0;O<L.length-1;O++)a.push(E(P,L[O],z,L[O+1]));else 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k=s[m.imageName];x=k.sdf,y=1/(b=k.pixelRatio)}var M=a?[m.x+T,m.y]:[0,0],A=a?[0,0]:[m.x+T+r[0],m.y+r[1]-_],S=[0,0];w&&(S=A,A=[0,0]);var E=(m.metrics.left-y)*m.scale-T+A[0],C=(-m.metrics.top-y)*m.scale+A[1],L=E+v.w*m.scale/b,I=C+v.h*m.scale/b,P=new i(E,C),z=new i(L,C),O=new i(E,I),D=new i(L,I);if(w){var R=new i(-T,T- -17),F=-Math.PI/2,B=12-T,N=new i(22-B,-(m.imageName?B:0)),j=new(Function.prototype.bind.apply(i,[null].concat(S)));P._rotateAround(F,R)._add(N)._add(j),z._rotateAround(F,R)._add(N)._add(j),O._rotateAround(F,R)._add(N)._add(j),D._rotateAround(F,R)._add(N)._add(j)}if(c){var U=Math.sin(c),V=Math.cos(c),q=[V,-U,U,V];P._matMult(q),z._matMult(q),O._matMult(q),D._matMult(q)}var H=new i(0,0),G=new i(0,0);u.push({tl:P,tr:z,bl:O,br:D,tex:v,writingMode:e.writingMode,glyphOffset:M,sectionIndex:m.sectionIndex,isSDF:x,pixelOffsetTL:H,pixelOffsetBR:G,minFontScaleX:0,minFontScaleY:0})}}return u}(0,r,l,a,o,s,n,t.allowVerticalPlacement),v=t.textSizeData,y=null;\"source\"===v.kind?(y=[128*a.layout.get(\"text-size\").evaluate(s,{})])[0]>32640&&_(t.layerIds[0]+': Value for \"text-size\" is >= 255. 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Fi,this.programConfigurations=t,this.segments=new ia,this.dynamicLayoutVertexArray=new Ii,this.opacityVertexArray=new Pi,this.placedSymbolArray=new Ji};cc.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length&&0===this.indexArray.length&&0===this.dynamicLayoutVertexArray.length&&0===this.opacityVertexArray.length},cc.prototype.upload=function(t,e,r,n){this.isEmpty()||(r&&(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,Ds.members),this.indexBuffer=t.createIndexBuffer(this.indexArray,e),this.dynamicLayoutVertexBuffer=t.createVertexBuffer(this.dynamicLayoutVertexArray,Rs.members,!0),this.opacityVertexBuffer=t.createVertexBuffer(this.opacityVertexArray,ac,!0),this.opacityVertexBuffer.itemSize=1),(r||n)&&this.programConfigurations.upload(t))},cc.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.dynamicLayoutVertexBuffer.destroy(),this.opacityVertexBuffer.destroy())},Dn(\"SymbolBuffers\",cc);var uc=function(t,e,r){this.layoutVertexArray=new t,this.layoutAttributes=e,this.indexArray=new r,this.segments=new ia,this.collisionVertexArray=new Ri};uc.prototype.upload=function(t){this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,this.layoutAttributes),this.indexBuffer=t.createIndexBuffer(this.indexArray),this.collisionVertexBuffer=t.createVertexBuffer(this.collisionVertexArray,Fs.members,!0)},uc.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.collisionVertexBuffer.destroy())},Dn(\"CollisionBuffers\",uc);var fc=function(t){this.collisionBoxArray=t.collisionBoxArray,this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.pixelRatio=t.pixelRatio,this.sourceLayerIndex=t.sourceLayerIndex,this.hasPattern=!1,this.hasRTLText=!1,this.sortKeyRanges=[],this.collisionCircleArray=[],this.placementInvProjMatrix=eo([]),this.placementViewportMatrix=eo([]);var e=this.layers[0]._unevaluatedLayout._values;this.textSizeData=Ll(this.zoom,e[\"text-size\"]),this.iconSizeData=Ll(this.zoom,e[\"icon-size\"]);var r=this.layers[0].layout,n=r.get(\"symbol-sort-key\"),i=r.get(\"symbol-z-order\");this.sortFeaturesByKey=\"viewport-y\"!==i&&void 0!==n.constantOr(1),this.sortFeaturesByY=(\"viewport-y\"===i||\"auto\"===i&&!this.sortFeaturesByKey)&&(r.get(\"text-allow-overlap\")||r.get(\"icon-allow-overlap\")||r.get(\"text-ignore-placement\")||r.get(\"icon-ignore-placement\")),\"point\"===r.get(\"symbol-placement\")&&(this.writingModes=r.get(\"text-writing-mode\").map((function(t){return gl[t]}))),this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id})),this.sourceID=t.sourceID};fc.prototype.createArrays=function(){this.text=new cc(new Ia(Ds.members,this.layers,this.zoom,(function(t){return/^text/.test(t)}))),this.icon=new cc(new Ia(Ds.members,this.layers,this.zoom,(function(t){return/^icon/.test(t)}))),this.glyphOffsetArray=new $i,this.lineVertexArray=new ta,this.symbolInstances=new Qi},fc.prototype.calculateGlyphDependencies=function(t,e,r,n,i){for(var a=0;a<t.length;a++)if(e[t.charCodeAt(a)]=!0,(r||n)&&i){var o=Us[t.charAt(a)];o&&(e[o.charCodeAt(0)]=!0)}},fc.prototype.populate=function(t,e,r){var n=this.layers[0],i=n.layout,a=i.get(\"text-font\"),o=i.get(\"text-field\"),s=i.get(\"icon-image\"),l=(\"constant\"!==o.value.kind||o.value.value instanceof te&&!o.value.value.isEmpty()||o.value.value.toString().length>0)&&(\"constant\"!==a.value.kind||a.value.value.length>0),c=\"constant\"!==s.value.kind||!!s.value.value||Object.keys(s.parameters).length>0,u=i.get(\"symbol-sort-key\");if(this.features=[],l||c){for(var f=e.iconDependencies,h=e.glyphDependencies,p=e.availableImages,d=new ii(this.zoom),g=0,m=t;g<m.length;g+=1){var v=m[g],y=v.feature,x=v.id,b=v.index,_=v.sourceLayerIndex,w=n._featureFilter.needGeometry,T={type:y.type,id:x,properties:y.properties,geometry:w?Da(y):[]};if(n._featureFilter.filter(d,T,r)){w||(T.geometry=Da(y));var k=void 0;if(l){var M=n.getValueAndResolveTokens(\"text-field\",T,r,p),A=te.factory(M);lc(A)&&(this.hasRTLText=!0),(!this.hasRTLText||\"unavailable\"===ei()||this.hasRTLText&&ni.isParsed())&&(k=js(A,n,T))}var S=void 0;if(c){var E=n.getValueAndResolveTokens(\"icon-image\",T,r,p);S=E instanceof ee?E:ee.fromString(E)}if(k||S){var C=this.sortFeaturesByKey?u.evaluate(T,{},r):void 0,L={id:x,text:k,icon:S,index:b,sourceLayerIndex:_,geometry:Da(y),properties:y.properties,type:ic[y.type],sortKey:C};if(this.features.push(L),S&&(f[S.name]=!0),k){var I=a.evaluate(T,{},r).join(\",\"),P=\"map\"===i.get(\"text-rotation-alignment\")&&\"point\"!==i.get(\"symbol-placement\");this.allowVerticalPlacement=this.writingModes&&this.writingModes.indexOf(gl.vertical)>=0;for(var z=0,O=k.sections;z<O.length;z+=1){var D=O[z];if(D.image)f[D.image.name]=!0;else{var R=qn(k.toString()),F=D.fontStack||I,B=h[F]=h[F]||{};this.calculateGlyphDependencies(D.text,B,P,this.allowVerticalPlacement,R)}}}}}}\"line\"===i.get(\"symbol-placement\")&&(this.features=function(t){var e={},r={},n=[],i=0;function a(e){n.push(t[e]),i++}function o(t,e,i){var a=r[t];return delete r[t],r[e]=a,n[a].geometry[0].pop(),n[a].geometry[0]=n[a].geometry[0].concat(i[0]),a}function s(t,r,i){var a=e[r];return delete e[r],e[t]=a,n[a].geometry[0].shift(),n[a].geometry[0]=i[0].concat(n[a].geometry[0]),a}function l(t,e,r){var n=r?e[0][e[0].length-1]:e[0][0];return t+\":\"+n.x+\":\"+n.y}for(var c=0;c<t.length;c++){var u=t[c],f=u.geometry,h=u.text?u.text.toString():null;if(h){var p=l(h,f),d=l(h,f,!0);if(p in r&&d in e&&r[p]!==e[d]){var g=s(p,d,f),m=o(p,d,n[g].geometry);delete e[p],delete r[d],r[l(h,n[m].geometry,!0)]=m,n[g].geometry=null}else p in r?o(p,d,f):d in e?s(p,d,f):(a(c),e[p]=i-1,r[d]=i-1)}else a(c)}return n.filter((function(t){return t.geometry}))}(this.features)),this.sortFeaturesByKey&&this.features.sort((function(t,e){return t.sortKey-e.sortKey}))}},fc.prototype.update=function(t,e,r){this.stateDependentLayers.length&&(this.text.programConfigurations.updatePaintArrays(t,e,this.layers,r),this.icon.programConfigurations.updatePaintArrays(t,e,this.layers,r))},fc.prototype.isEmpty=function(){return 0===this.symbolInstances.length&&!this.hasRTLText},fc.prototype.uploadPending=function(){return!this.uploaded||this.text.programConfigurations.needsUpload||this.icon.programConfigurations.needsUpload},fc.prototype.upload=function(t){!this.uploaded&&this.hasDebugData()&&(this.textCollisionBox.upload(t),this.iconCollisionBox.upload(t)),this.text.upload(t,this.sortFeaturesByY,!this.uploaded,this.text.programConfigurations.needsUpload),this.icon.upload(t,this.sortFeaturesByY,!this.uploaded,this.icon.programConfigurations.needsUpload),this.uploaded=!0},fc.prototype.destroyDebugData=function(){this.textCollisionBox.destroy(),this.iconCollisionBox.destroy()},fc.prototype.destroy=function(){this.text.destroy(),this.icon.destroy(),this.hasDebugData()&&this.destroyDebugData()},fc.prototype.addToLineVertexArray=function(t,e){var r=this.lineVertexArray.length;if(void 0!==t.segment){for(var n=t.dist(e[t.segment+1]),i=t.dist(e[t.segment]),a={},o=t.segment+1;o<e.length;o++)a[o]={x:e[o].x,y:e[o].y,tileUnitDistanceFromAnchor:n},o<e.length-1&&(n+=e[o+1].dist(e[o]));for(var s=t.segment||0;s>=0;s--)a[s]={x:e[s].x,y:e[s].y,tileUnitDistanceFromAnchor:i},s>0&&(i+=e[s-1].dist(e[s]));for(var l=0;l<e.length;l++){var c=a[l];this.lineVertexArray.emplaceBack(c.x,c.y,c.tileUnitDistanceFromAnchor)}}return{lineStartIndex:r,lineLength:this.lineVertexArray.length-r}},fc.prototype.addSymbols=function(t,e,r,n,i,a,o,s,l,c,u,f){for(var h=t.indexArray,p=t.layoutVertexArray,d=t.segments.prepareSegment(4*e.length,p,h,a.sortKey),g=this.glyphOffsetArray.length,m=d.vertexLength,v=this.allowVerticalPlacement&&o===gl.vertical?Math.PI/2:0,y=a.text&&a.text.sections,x=0;x<e.length;x++){var b=e[x],_=b.tl,w=b.tr,T=b.bl,k=b.br,M=b.tex,A=b.pixelOffsetTL,S=b.pixelOffsetBR,E=b.minFontScaleX,C=b.minFontScaleY,L=b.glyphOffset,I=b.isSDF,P=b.sectionIndex,z=d.vertexLength,O=L[1];oc(p,s.x,s.y,_.x,O+_.y,M.x,M.y,r,I,A.x,A.y,E,C),oc(p,s.x,s.y,w.x,O+w.y,M.x+M.w,M.y,r,I,S.x,A.y,E,C),oc(p,s.x,s.y,T.x,O+T.y,M.x,M.y+M.h,r,I,A.x,S.y,E,C),oc(p,s.x,s.y,k.x,O+k.y,M.x+M.w,M.y+M.h,r,I,S.x,S.y,E,C),sc(t.dynamicLayoutVertexArray,s,v),h.emplaceBack(z,z+1,z+2),h.emplaceBack(z+1,z+2,z+3),d.vertexLength+=4,d.primitiveLength+=2,this.glyphOffsetArray.emplaceBack(L[0]),x!==e.length-1&&P===e[x+1].sectionIndex||t.programConfigurations.populatePaintArrays(p.length,a,a.index,{},f,y&&y[P])}t.placedSymbolArray.emplaceBack(s.x,s.y,g,this.glyphOffsetArray.length-g,m,l,c,s.segment,r?r[0]:0,r?r[1]:0,n[0],n[1],o,0,!1,0,u)},fc.prototype._addCollisionDebugVertex=function(t,e,r,n,i,a){return e.emplaceBack(0,0),t.emplaceBack(r.x,r.y,n,i,Math.round(a.x),Math.round(a.y))},fc.prototype.addCollisionDebugVertices=function(t,e,r,n,a,o,s){var l=a.segments.prepareSegment(4,a.layoutVertexArray,a.indexArray),c=l.vertexLength,u=a.layoutVertexArray,f=a.collisionVertexArray,h=s.anchorX,p=s.anchorY;this._addCollisionDebugVertex(u,f,o,h,p,new i(t,e)),this._addCollisionDebugVertex(u,f,o,h,p,new i(r,e)),this._addCollisionDebugVertex(u,f,o,h,p,new i(r,n)),this._addCollisionDebugVertex(u,f,o,h,p,new i(t,n)),l.vertexLength+=4;var d=a.indexArray;d.emplaceBack(c,c+1),d.emplaceBack(c+1,c+2),d.emplaceBack(c+2,c+3),d.emplaceBack(c+3,c),l.primitiveLength+=4},fc.prototype.addDebugCollisionBoxes=function(t,e,r,n){for(var i=t;i<e;i++){var a=this.collisionBoxArray.get(i);this.addCollisionDebugVertices(a.x1,a.y1,a.x2,a.y2,n?this.textCollisionBox:this.iconCollisionBox,a.anchorPoint,r)}},fc.prototype.generateCollisionDebugBuffers=function(){this.hasDebugData()&&this.destroyDebugData(),this.textCollisionBox=new uc(Oi,Bs.members,qi),this.iconCollisionBox=new uc(Oi,Bs.members,qi);for(var t=0;t<this.symbolInstances.length;t++){var e=this.symbolInstances.get(t);this.addDebugCollisionBoxes(e.textBoxStartIndex,e.textBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.verticalTextBoxStartIndex,e.verticalTextBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.iconBoxStartIndex,e.iconBoxEndIndex,e,!1),this.addDebugCollisionBoxes(e.verticalIconBoxStartIndex,e.verticalIconBoxEndIndex,e,!1)}},fc.prototype._deserializeCollisionBoxesForSymbol=function(t,e,r,n,i,a,o,s,l){for(var c={},u=e;u<r;u++){var f=t.get(u);c.textBox={x1:f.x1,y1:f.y1,x2:f.x2,y2:f.y2,anchorPointX:f.anchorPointX,anchorPointY:f.anchorPointY},c.textFeatureIndex=f.featureIndex;break}for(var h=n;h<i;h++){var p=t.get(h);c.verticalTextBox={x1:p.x1,y1:p.y1,x2:p.x2,y2:p.y2,anchorPointX:p.anchorPointX,anchorPointY:p.anchorPointY},c.verticalTextFeatureIndex=p.featureIndex;break}for(var d=a;d<o;d++){var g=t.get(d);c.iconBox={x1:g.x1,y1:g.y1,x2:g.x2,y2:g.y2,anchorPointX:g.anchorPointX,anchorPointY:g.anchorPointY},c.iconFeatureIndex=g.featureIndex;break}for(var m=s;m<l;m++){var v=t.get(m);c.verticalIconBox={x1:v.x1,y1:v.y1,x2:v.x2,y2:v.y2,anchorPointX:v.anchorPointX,anchorPointY:v.anchorPointY},c.verticalIconFeatureIndex=v.featureIndex;break}return c},fc.prototype.deserializeCollisionBoxes=function(t){this.collisionArrays=[];for(var e=0;e<this.symbolInstances.length;e++){var r=this.symbolInstances.get(e);this.collisionArrays.push(this._deserializeCollisionBoxesForSymbol(t,r.textBoxStartIndex,r.textBoxEndIndex,r.verticalTextBoxStartIndex,r.verticalTextBoxEndIndex,r.iconBoxStartIndex,r.iconBoxEndIndex,r.verticalIconBoxStartIndex,r.verticalIconBoxEndIndex))}},fc.prototype.hasTextData=function(){return this.text.segments.get().length>0},fc.prototype.hasIconData=function(){return this.icon.segments.get().length>0},fc.prototype.hasDebugData=function(){return this.textCollisionBox&&this.iconCollisionBox},fc.prototype.hasTextCollisionBoxData=function(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0},fc.prototype.hasIconCollisionBoxData=function(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0},fc.prototype.addIndicesForPlacedSymbol=function(t,e){for(var r=t.placedSymbolArray.get(e),n=r.vertexStartIndex+4*r.numGlyphs,i=r.vertexStartIndex;i<n;i+=4)t.indexArray.emplaceBack(i,i+1,i+2),t.indexArray.emplaceBack(i+1,i+2,i+3)},fc.prototype.getSortedSymbolIndexes=function(t){if(this.sortedAngle===t&&void 0!==this.symbolInstanceIndexes)return this.symbolInstanceIndexes;for(var e=Math.sin(t),r=Math.cos(t),n=[],i=[],a=[],o=0;o<this.symbolInstances.length;++o){a.push(o);var s=this.symbolInstances.get(o);n.push(0|Math.round(e*s.anchorX+r*s.anchorY)),i.push(s.featureIndex)}return a.sort((function(t,e){return n[t]-n[e]||i[e]-i[t]})),a},fc.prototype.addToSortKeyRanges=function(t,e){var r=this.sortKeyRanges[this.sortKeyRanges.length-1];r&&r.sortKey===e?r.symbolInstanceEnd=t+1:this.sortKeyRanges.push({sortKey:e,symbolInstanceStart:t,symbolInstanceEnd:t+1})},fc.prototype.sortFeatures=function(t){var e=this;if(this.sortFeaturesByY&&this.sortedAngle!==t&&!(this.text.segments.get().length>1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(t),this.sortedAngle=t,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var r=0,n=this.symbolInstanceIndexes;r<n.length;r+=1){var i=this.symbolInstances.get(n[r]);this.featureSortOrder.push(i.featureIndex),[i.rightJustifiedTextSymbolIndex,i.centerJustifiedTextSymbolIndex,i.leftJustifiedTextSymbolIndex].forEach((function(t,r,n){t>=0&&n.indexOf(t)===r&&e.addIndicesForPlacedSymbol(e.text,t)})),i.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,i.verticalPlacedTextSymbolIndex),i.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,i.placedIconSymbolIndex),i.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,i.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},Dn(\"SymbolBucket\",fc,{omit:[\"layers\",\"collisionBoxArray\",\"features\",\"compareText\"]}),fc.MAX_GLYPHS=65535,fc.addDynamicAttributes=sc;var hc=new yi({\"symbol-placement\":new pi(At.layout_symbol[\"symbol-placement\"]),\"symbol-spacing\":new pi(At.layout_symbol[\"symbol-spacing\"]),\"symbol-avoid-edges\":new pi(At.layout_symbol[\"symbol-avoid-edges\"]),\"symbol-sort-key\":new di(At.layout_symbol[\"symbol-sort-key\"]),\"symbol-z-order\":new pi(At.layout_symbol[\"symbol-z-order\"]),\"icon-allow-overlap\":new pi(At.layout_symbol[\"icon-allow-overlap\"]),\"icon-ignore-placement\":new pi(At.layout_symbol[\"icon-ignore-placement\"]),\"icon-optional\":new pi(At.layout_symbol[\"icon-optional\"]),\"icon-rotation-alignment\":new pi(At.layout_symbol[\"icon-rotation-alignment\"]),\"icon-size\":new di(At.layout_symbol[\"icon-size\"]),\"icon-text-fit\":new pi(At.layout_symbol[\"icon-text-fit\"]),\"icon-text-fit-padding\":new pi(At.layout_symbol[\"icon-text-fit-padding\"]),\"icon-image\":new di(At.layout_symbol[\"icon-image\"]),\"icon-rotate\":new di(At.layout_symbol[\"icon-rotate\"]),\"icon-padding\":new pi(At.layout_symbol[\"icon-padding\"]),\"icon-keep-upright\":new pi(At.layout_symbol[\"icon-keep-upright\"]),\"icon-offset\":new di(At.layout_symbol[\"icon-offset\"]),\"icon-anchor\":new di(At.layout_symbol[\"icon-anchor\"]),\"icon-pitch-alignment\":new pi(At.layout_symbol[\"icon-pitch-alignment\"]),\"text-pitch-alignment\":new pi(At.layout_symbol[\"text-pitch-alignment\"]),\"text-rotation-alignment\":new pi(At.layout_symbol[\"text-rotation-alignment\"]),\"text-field\":new di(At.layout_symbol[\"text-field\"]),\"text-font\":new di(At.layout_symbol[\"text-font\"]),\"text-size\":new di(At.layout_symbol[\"text-size\"]),\"text-max-width\":new di(At.layout_symbol[\"text-max-width\"]),\"text-line-height\":new pi(At.layout_symbol[\"text-line-height\"]),\"text-letter-spacing\":new di(At.layout_symbol[\"text-letter-spacing\"]),\"text-justify\":new di(At.layout_symbol[\"text-justify\"]),\"text-radial-offset\":new di(At.layout_symbol[\"text-radial-offset\"]),\"text-variable-anchor\":new pi(At.layout_symbol[\"text-variable-anchor\"]),\"text-anchor\":new di(At.layout_symbol[\"text-anchor\"]),\"text-max-angle\":new pi(At.layout_symbol[\"text-max-angle\"]),\"text-writing-mode\":new pi(At.layout_symbol[\"text-writing-mode\"]),\"text-rotate\":new di(At.layout_symbol[\"text-rotate\"]),\"text-padding\":new pi(At.layout_symbol[\"text-padding\"]),\"text-keep-upright\":new pi(At.layout_symbol[\"text-keep-upright\"]),\"text-transform\":new di(At.layout_symbol[\"text-transform\"]),\"text-offset\":new di(At.layout_symbol[\"text-offset\"]),\"text-allow-overlap\":new pi(At.layout_symbol[\"text-allow-overlap\"]),\"text-ignore-placement\":new pi(At.layout_symbol[\"text-ignore-placement\"]),\"text-optional\":new pi(At.layout_symbol[\"text-optional\"])}),pc={paint:new yi({\"icon-opacity\":new di(At.paint_symbol[\"icon-opacity\"]),\"icon-color\":new di(At.paint_symbol[\"icon-color\"]),\"icon-halo-color\":new di(At.paint_symbol[\"icon-halo-color\"]),\"icon-halo-width\":new di(At.paint_symbol[\"icon-halo-width\"]),\"icon-halo-blur\":new di(At.paint_symbol[\"icon-halo-blur\"]),\"icon-translate\":new pi(At.paint_symbol[\"icon-translate\"]),\"icon-translate-anchor\":new pi(At.paint_symbol[\"icon-translate-anchor\"]),\"text-opacity\":new di(At.paint_symbol[\"text-opacity\"]),\"text-color\":new di(At.paint_symbol[\"text-color\"],{runtimeType:Bt,getOverride:function(t){return t.textColor},hasOverride:function(t){return!!t.textColor}}),\"text-halo-color\":new di(At.paint_symbol[\"text-halo-color\"]),\"text-halo-width\":new di(At.paint_symbol[\"text-halo-width\"]),\"text-halo-blur\":new di(At.paint_symbol[\"text-halo-blur\"]),\"text-translate\":new pi(At.paint_symbol[\"text-translate\"]),\"text-translate-anchor\":new pi(At.paint_symbol[\"text-translate-anchor\"])}),layout:hc},dc=function(t){this.type=t.property.overrides?t.property.overrides.runtimeType:Ot,this.defaultValue=t};dc.prototype.evaluate=function(t){if(t.formattedSection){var e=this.defaultValue.property.overrides;if(e&&e.hasOverride(t.formattedSection))return e.getOverride(t.formattedSection)}return t.feature&&t.featureState?this.defaultValue.evaluate(t.feature,t.featureState):this.defaultValue.property.specification.default},dc.prototype.eachChild=function(t){this.defaultValue.isConstant()||t(this.defaultValue.value._styleExpression.expression)},dc.prototype.outputDefined=function(){return!1},dc.prototype.serialize=function(){return null},Dn(\"FormatSectionOverride\",dc,{omit:[\"defaultValue\"]});var gc=function(t){function e(e){t.call(this,e,pc)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.recalculate=function(e,r){if(t.prototype.recalculate.call(this,e,r),\"auto\"===this.layout.get(\"icon-rotation-alignment\")&&(this.layout._values[\"icon-rotation-alignment\"]=\"point\"!==this.layout.get(\"symbol-placement\")?\"map\":\"viewport\"),\"auto\"===this.layout.get(\"text-rotation-alignment\")&&(this.layout._values[\"text-rotation-alignment\"]=\"point\"!==this.layout.get(\"symbol-placement\")?\"map\":\"viewport\"),\"auto\"===this.layout.get(\"text-pitch-alignment\")&&(this.layout._values[\"text-pitch-alignment\"]=this.layout.get(\"text-rotation-alignment\")),\"auto\"===this.layout.get(\"icon-pitch-alignment\")&&(this.layout._values[\"icon-pitch-alignment\"]=this.layout.get(\"icon-rotation-alignment\")),\"point\"===this.layout.get(\"symbol-placement\")){var n=this.layout.get(\"text-writing-mode\");if(n){for(var i=[],a=0,o=n;a<o.length;a+=1){var s=o[a];i.indexOf(s)<0&&i.push(s)}this.layout._values[\"text-writing-mode\"]=i}else this.layout._values[\"text-writing-mode\"]=[\"horizontal\"]}this._setPaintOverrides()},e.prototype.getValueAndResolveTokens=function(t,e,r,n){var i=this.layout.get(t).evaluate(e,{},r,n),a=this._unevaluatedLayout._values[t];return a.isDataDriven()||Vr(a.value)||!i?i:function(t,e){return e.replace(/{([^{}]+)}/g,(function(e,r){return r in t?String(t[r]):\"\"}))}(e.properties,i)},e.prototype.createBucket=function(t){return new fc(t)},e.prototype.queryRadius=function(){return 0},e.prototype.queryIntersectsFeature=function(){return!1},e.prototype._setPaintOverrides=function(){for(var t=0,r=pc.paint.overridableProperties;t<r.length;t+=1){var n=r[t];if(e.hasPaintOverride(this.layout,n)){var i,a=this.paint.get(n),o=new dc(a),s=new Ur(o,a.property.specification);i=\"constant\"===a.value.kind||\"source\"===a.value.kind?new Hr(\"source\",s):new Gr(\"composite\",s,a.value.zoomStops,a.value._interpolationType),this.paint._values[n]=new fi(a.property,i,a.parameters)}}},e.prototype._handleOverridablePaintPropertyUpdate=function(t,r,n){return!(!this.layout||r.isDataDriven()||n.isDataDriven())&&e.hasPaintOverride(this.layout,t)},e.hasPaintOverride=function(t,e){var r=t.get(\"text-field\"),n=pc.paint.properties[e],i=!1,a=function(t){for(var e=0,r=t;e<r.length;e+=1)if(n.overrides&&n.overrides.hasOverride(r[e]))return void(i=!0)};if(\"constant\"===r.value.kind&&r.value.value instanceof te)a(r.value.value.sections);else if(\"source\"===r.value.kind){var o=function(t){i||(t instanceof oe&&ie(t.value)===Vt?a(t.value.sections):t instanceof ue?a(t.sections):t.eachChild(o))},s=r.value;s._styleExpression&&o(s._styleExpression.expression)}return i},e}(xi),mc={paint:new yi({\"background-color\":new pi(At.paint_background[\"background-color\"]),\"background-pattern\":new mi(At.paint_background[\"background-pattern\"]),\"background-opacity\":new pi(At.paint_background[\"background-opacity\"])})},vc=function(t){function e(e){t.call(this,e,mc)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e}(xi),yc={paint:new yi({\"raster-opacity\":new pi(At.paint_raster[\"raster-opacity\"]),\"raster-hue-rotate\":new pi(At.paint_raster[\"raster-hue-rotate\"]),\"raster-brightness-min\":new pi(At.paint_raster[\"raster-brightness-min\"]),\"raster-brightness-max\":new pi(At.paint_raster[\"raster-brightness-max\"]),\"raster-saturation\":new pi(At.paint_raster[\"raster-saturation\"]),\"raster-contrast\":new pi(At.paint_raster[\"raster-contrast\"]),\"raster-resampling\":new pi(At.paint_raster[\"raster-resampling\"]),\"raster-fade-duration\":new pi(At.paint_raster[\"raster-fade-duration\"])})},xc=function(t){function e(e){t.call(this,e,yc)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e}(xi),bc=function(t){function e(e){t.call(this,e,{}),this.implementation=e}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.is3D=function(){return\"3d\"===this.implementation.renderingMode},e.prototype.hasOffscreenPass=function(){return void 0!==this.implementation.prerender},e.prototype.recalculate=function(){},e.prototype.updateTransitions=function(){},e.prototype.hasTransition=function(){},e.prototype.serialize=function(){},e.prototype.onAdd=function(t){this.implementation.onAdd&&this.implementation.onAdd(t,t.painter.context.gl)},e.prototype.onRemove=function(t){this.implementation.onRemove&&this.implementation.onRemove(t,t.painter.context.gl)},e}(xi),_c={circle:oo,heatmap:vo,hillshade:xo,fill:as,\"fill-extrusion\":ws,line:zs,symbol:gc,background:vc,raster:xc},wc=self.HTMLImageElement,Tc=self.HTMLCanvasElement,kc=self.HTMLVideoElement,Mc=self.ImageData,Ac=self.ImageBitmap,Sc=function(t,e,r,n){this.context=t,this.format=r,this.texture=t.gl.createTexture(),this.update(e,n)};Sc.prototype.update=function(t,e,r){var n=t.width,i=t.height,a=!(this.size&&this.size[0]===n&&this.size[1]===i||r),o=this.context,s=o.gl;if(this.useMipmap=Boolean(e&&e.useMipmap),s.bindTexture(s.TEXTURE_2D,this.texture),o.pixelStoreUnpackFlipY.set(!1),o.pixelStoreUnpack.set(1),o.pixelStoreUnpackPremultiplyAlpha.set(this.format===s.RGBA&&(!e||!1!==e.premultiply)),a)this.size=[n,i],t instanceof wc||t instanceof Tc||t instanceof kc||t instanceof Mc||Ac&&t instanceof Ac?s.texImage2D(s.TEXTURE_2D,0,this.format,this.format,s.UNSIGNED_BYTE,t):s.texImage2D(s.TEXTURE_2D,0,this.format,n,i,0,this.format,s.UNSIGNED_BYTE,t.data);else{var l=r||{x:0,y:0},c=l.x,u=l.y;t instanceof wc||t instanceof Tc||t instanceof kc||t instanceof Mc||Ac&&t instanceof Ac?s.texSubImage2D(s.TEXTURE_2D,0,c,u,s.RGBA,s.UNSIGNED_BYTE,t):s.texSubImage2D(s.TEXTURE_2D,0,c,u,n,i,s.RGBA,s.UNSIGNED_BYTE,t.data)}this.useMipmap&&this.isSizePowerOfTwo()&&s.generateMipmap(s.TEXTURE_2D)},Sc.prototype.bind=function(t,e,r){var n=this.context.gl;n.bindTexture(n.TEXTURE_2D,this.texture),r!==n.LINEAR_MIPMAP_NEAREST||this.isSizePowerOfTwo()||(r=n.LINEAR),t!==this.filter&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,t),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,r||t),this.filter=t),e!==this.wrap&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,e),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,e),this.wrap=e)},Sc.prototype.isSizePowerOfTwo=function(){return this.size[0]===this.size[1]&&Math.log(this.size[0])/Math.LN2%1==0},Sc.prototype.destroy=function(){this.context.gl.deleteTexture(this.texture),this.texture=null};var Ec=function(t){var e=this;this._callback=t,this._triggered=!1,\"undefined\"!=typeof MessageChannel&&(this._channel=new MessageChannel,this._channel.port2.onmessage=function(){e._triggered=!1,e._callback()})};Ec.prototype.trigger=function(){var t=this;this._triggered||(this._triggered=!0,this._channel?this._channel.port1.postMessage(!0):setTimeout((function(){t._triggered=!1,t._callback()}),0))},Ec.prototype.remove=function(){delete this._channel,this._callback=function(){}};var Cc=function(t,e,r){this.target=t,this.parent=e,this.mapId=r,this.callbacks={},this.tasks={},this.taskQueue=[],this.cancelCallbacks={},g([\"receive\",\"process\"],this),this.invoker=new Ec(this.process),this.target.addEventListener(\"message\",this.receive,!1),this.globalScope=k()?t:self};function Lc(t,e,r){var n=2*Math.PI*6378137/256/Math.pow(2,r);return[t*n-2*Math.PI*6378137/2,e*n-2*Math.PI*6378137/2]}Cc.prototype.send=function(t,e,r,n,i){var a=this;void 0===i&&(i=!1);var o=Math.round(1e18*Math.random()).toString(36).substring(0,10);r&&(this.callbacks[o]=r);var s=S(this.globalScope)?void 0:[];return this.target.postMessage({id:o,type:t,hasCallback:!!r,targetMapId:n,mustQueue:i,sourceMapId:this.mapId,data:Nn(e,s)},s),{cancel:function(){r&&delete a.callbacks[o],a.target.postMessage({id:o,type:\"<cancel>\",targetMapId:n,sourceMapId:a.mapId})}}},Cc.prototype.receive=function(t){var e=t.data,r=e.id;if(r&&(!e.targetMapId||this.mapId===e.targetMapId))if(\"<cancel>\"===e.type){delete this.tasks[r];var n=this.cancelCallbacks[r];delete this.cancelCallbacks[r],n&&n()}else k()||e.mustQueue?(this.tasks[r]=e,this.taskQueue.push(r),this.invoker.trigger()):this.processTask(r,e)},Cc.prototype.process=function(){if(this.taskQueue.length){var t=this.taskQueue.shift(),e=this.tasks[t];delete this.tasks[t],this.taskQueue.length&&this.invoker.trigger(),e&&this.processTask(t,e)}},Cc.prototype.processTask=function(t,e){var r=this;if(\"<response>\"===e.type){var n=this.callbacks[t];delete this.callbacks[t],n&&(e.error?n(jn(e.error)):n(null,jn(e.data)))}else{var i=!1,a=S(this.globalScope)?void 0:[],o=e.hasCallback?function(e,n){i=!0,delete r.cancelCallbacks[t],r.target.postMessage({id:t,type:\"<response>\",sourceMapId:r.mapId,error:e?Nn(e):null,data:Nn(n,a)},a)}:function(t){i=!0},s=null,l=jn(e.data);if(this.parent[e.type])s=this.parent[e.type](e.sourceMapId,l,o);else if(this.parent.getWorkerSource){var c=e.type.split(\".\");s=this.parent.getWorkerSource(e.sourceMapId,c[0],l.source)[c[1]](l,o)}else o(new Error(\"Could not find function \"+e.type));!i&&s&&s.cancel&&(this.cancelCallbacks[t]=s.cancel)}},Cc.prototype.remove=function(){this.invoker.remove(),this.target.removeEventListener(\"message\",this.receive,!1)};var Ic=function(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1]))};Ic.prototype.setNorthEast=function(t){return this._ne=t instanceof Pc?new Pc(t.lng,t.lat):Pc.convert(t),this},Ic.prototype.setSouthWest=function(t){return this._sw=t instanceof Pc?new Pc(t.lng,t.lat):Pc.convert(t),this},Ic.prototype.extend=function(t){var e,r,n=this._sw,i=this._ne;if(t instanceof Pc)e=t,r=t;else{if(!(t instanceof Ic))return Array.isArray(t)?4===t.length||t.every(Array.isArray)?this.extend(Ic.convert(t)):this.extend(Pc.convert(t)):this;if(r=t._ne,!(e=t._sw)||!r)return this}return n||i?(n.lng=Math.min(e.lng,n.lng),n.lat=Math.min(e.lat,n.lat),i.lng=Math.max(r.lng,i.lng),i.lat=Math.max(r.lat,i.lat)):(this._sw=new Pc(e.lng,e.lat),this._ne=new Pc(r.lng,r.lat)),this},Ic.prototype.getCenter=function(){return new Pc((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Ic.prototype.getSouthWest=function(){return this._sw},Ic.prototype.getNorthEast=function(){return this._ne},Ic.prototype.getNorthWest=function(){return new Pc(this.getWest(),this.getNorth())},Ic.prototype.getSouthEast=function(){return new Pc(this.getEast(),this.getSouth())},Ic.prototype.getWest=function(){return this._sw.lng},Ic.prototype.getSouth=function(){return this._sw.lat},Ic.prototype.getEast=function(){return this._ne.lng},Ic.prototype.getNorth=function(){return this._ne.lat},Ic.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Ic.prototype.toString=function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"},Ic.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Ic.prototype.contains=function(t){var e=Pc.convert(t),r=e.lng,n=e.lat,i=this._sw.lng<=r&&r<=this._ne.lng;return this._sw.lng>this._ne.lng&&(i=this._sw.lng>=r&&r>=this._ne.lng),this._sw.lat<=n&&n<=this._ne.lat&&i},Ic.convert=function(t){return!t||t instanceof Ic?t:new Ic(t)};var Pc=function(t,e){if(isNaN(t)||isNaN(e))throw new Error(\"Invalid LngLat object: (\"+t+\", \"+e+\")\");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")};Pc.prototype.wrap=function(){return new Pc(c(this.lng,-180,180),this.lat)},Pc.prototype.toArray=function(){return[this.lng,this.lat]},Pc.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},Pc.prototype.distanceTo=function(t){var e=Math.PI/180,r=this.lat*e,n=t.lat*e,i=Math.sin(r)*Math.sin(n)+Math.cos(r)*Math.cos(n)*Math.cos((t.lng-this.lng)*e);return 6371008.8*Math.acos(Math.min(i,1))},Pc.prototype.toBounds=function(t){void 0===t&&(t=0);var e=360*t/40075017,r=e/Math.cos(Math.PI/180*this.lat);return new Ic(new Pc(this.lng-r,this.lat-e),new Pc(this.lng+r,this.lat+e))},Pc.convert=function(t){if(t instanceof Pc)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new Pc(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&\"object\"==typeof t&&null!==t)return new Pc(Number(\"lng\"in t?t.lng:t.lon),Number(t.lat));throw new Error(\"`LngLatLike` argument must be specified as a LngLat instance, an object {lng: <lng>, lat: <lat>}, an object {lon: <lng>, lat: <lat>}, or an array of [<lng>, <lat>]\")};var zc=2*Math.PI*6371008.8;function Oc(t){return zc*Math.cos(t*Math.PI/180)}function Dc(t){return(180+t)/360}function Rc(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))/360}function Fc(t,e){return t/Oc(e)}function Bc(t){return 360/Math.PI*Math.atan(Math.exp((180-360*t)*Math.PI/180))-90}var Nc=function(t,e,r){void 0===r&&(r=0),this.x=+t,this.y=+e,this.z=+r};Nc.fromLngLat=function(t,e){void 0===e&&(e=0);var r=Pc.convert(t);return new Nc(Dc(r.lng),Rc(r.lat),Fc(e,r.lat))},Nc.prototype.toLngLat=function(){return new Pc(360*this.x-180,Bc(this.y))},Nc.prototype.toAltitude=function(){return this.z*Oc(Bc(this.y))},Nc.prototype.meterInMercatorCoordinateUnits=function(){return 1/zc*(t=Bc(this.y),1/Math.cos(t*Math.PI/180));var t};var jc=function(t,e,r){this.z=t,this.x=e,this.y=r,this.key=qc(0,t,t,e,r)};jc.prototype.equals=function(t){return this.z===t.z&&this.x===t.x&&this.y===t.y},jc.prototype.url=function(t,e){var r,n,i,a,o,s=(n=this.y,i=this.z,a=Lc(256*(r=this.x),256*(n=Math.pow(2,i)-n-1),i),o=Lc(256*(r+1),256*(n+1),i),a[0]+\",\"+a[1]+\",\"+o[0]+\",\"+o[1]),l=function(t,e,r){for(var n,i=\"\",a=t;a>0;a--)i+=(e&(n=1<<a-1)?1:0)+(r&n?2:0);return i}(this.z,this.x,this.y);return t[(this.x+this.y)%t.length].replace(\"{prefix}\",(this.x%16).toString(16)+(this.y%16).toString(16)).replace(\"{z}\",String(this.z)).replace(\"{x}\",String(this.x)).replace(\"{y}\",String(\"tms\"===e?Math.pow(2,this.z)-this.y-1:this.y)).replace(\"{quadkey}\",l).replace(\"{bbox-epsg-3857}\",s)},jc.prototype.getTilePoint=function(t){var e=Math.pow(2,this.z);return new i(8192*(t.x*e-this.x),8192*(t.y*e-this.y))},jc.prototype.toString=function(){return this.z+\"/\"+this.x+\"/\"+this.y};var Uc=function(t,e){this.wrap=t,this.canonical=e,this.key=qc(t,e.z,e.z,e.x,e.y)},Vc=function(t,e,r,n,i){this.overscaledZ=t,this.wrap=e,this.canonical=new jc(r,+n,+i),this.key=qc(e,t,r,n,i)};function qc(t,e,r,n,i){(t*=2)<0&&(t=-1*t-1);var a=1<<r;return(a*a*t+a*i+n).toString(36)+r.toString(36)+e.toString(36)}Vc.prototype.equals=function(t){return this.overscaledZ===t.overscaledZ&&this.wrap===t.wrap&&this.canonical.equals(t.canonical)},Vc.prototype.scaledTo=function(t){var e=this.canonical.z-t;return t>this.canonical.z?new Vc(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new Vc(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)},Vc.prototype.calculateScaledKey=function(t,e){var r=this.canonical.z-t;return t>this.canonical.z?qc(this.wrap*+e,t,this.canonical.z,this.canonical.x,this.canonical.y):qc(this.wrap*+e,t,t,this.canonical.x>>r,this.canonical.y>>r)},Vc.prototype.isChildOf=function(t){if(t.wrap!==this.wrap)return!1;var e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ<this.overscaledZ&&t.canonical.x===this.canonical.x>>e&&t.canonical.y===this.canonical.y>>e},Vc.prototype.children=function(t){if(this.overscaledZ>=t)return[new Vc(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new Vc(e,this.wrap,e,r,n),new Vc(e,this.wrap,e,r+1,n),new Vc(e,this.wrap,e,r,n+1),new Vc(e,this.wrap,e,r+1,n+1)]},Vc.prototype.isLessThan=function(t){return this.wrap<t.wrap||!(this.wrap>t.wrap)&&(this.overscaledZ<t.overscaledZ||!(this.overscaledZ>t.overscaledZ)&&(this.canonical.x<t.canonical.x||!(this.canonical.x>t.canonical.x)&&this.canonical.y<t.canonical.y))},Vc.prototype.wrapped=function(){return new Vc(this.overscaledZ,0,this.canonical.z,this.canonical.x,this.canonical.y)},Vc.prototype.unwrapTo=function(t){return new Vc(this.overscaledZ,t,this.canonical.z,this.canonical.x,this.canonical.y)},Vc.prototype.overscaleFactor=function(){return Math.pow(2,this.overscaledZ-this.canonical.z)},Vc.prototype.toUnwrapped=function(){return new Uc(this.wrap,this.canonical)},Vc.prototype.toString=function(){return this.overscaledZ+\"/\"+this.canonical.x+\"/\"+this.canonical.y},Vc.prototype.getTilePoint=function(t){return this.canonical.getTilePoint(new Nc(t.x-this.wrap,t.y))},Dn(\"CanonicalTileID\",jc),Dn(\"OverscaledTileID\",Vc,{omit:[\"posMatrix\"]});var Hc=function(t,e,r){if(this.uid=t,e.height!==e.width)throw new RangeError(\"DEM tiles must be square\");if(r&&\"mapbox\"!==r&&\"terrarium\"!==r)return _('\"'+r+'\" is not a valid encoding type. Valid types include \"mapbox\" and \"terrarium\".');this.stride=e.height;var n=this.dim=e.height-2;this.data=new Uint32Array(e.data.buffer),this.encoding=r||\"mapbox\";for(var i=0;i<n;i++)this.data[this._idx(-1,i)]=this.data[this._idx(0,i)],this.data[this._idx(n,i)]=this.data[this._idx(n-1,i)],this.data[this._idx(i,-1)]=this.data[this._idx(i,0)],this.data[this._idx(i,n)]=this.data[this._idx(i,n-1)];this.data[this._idx(-1,-1)]=this.data[this._idx(0,0)],this.data[this._idx(n,-1)]=this.data[this._idx(n-1,0)],this.data[this._idx(-1,n)]=this.data[this._idx(0,n-1)],this.data[this._idx(n,n)]=this.data[this._idx(n-1,n-1)]};Hc.prototype.get=function(t,e){var r=new Uint8Array(this.data.buffer),n=4*this._idx(t,e);return(\"terrarium\"===this.encoding?this._unpackTerrarium:this._unpackMapbox)(r[n],r[n+1],r[n+2])},Hc.prototype.getUnpackVector=function(){return\"terrarium\"===this.encoding?[256,1,1/256,32768]:[6553.6,25.6,.1,1e4]},Hc.prototype._idx=function(t,e){if(t<-1||t>=this.dim+1||e<-1||e>=this.dim+1)throw new RangeError(\"out of range source coordinates for DEM data\");return(e+1)*this.stride+(t+1)},Hc.prototype._unpackMapbox=function(t,e,r){return(256*t*256+256*e+r)/10-1e4},Hc.prototype._unpackTerrarium=function(t,e,r){return 256*t+e+r/256-32768},Hc.prototype.getPixels=function(){return new po({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},Hc.prototype.backfillBorder=function(t,e,r){if(this.dim!==t.dim)throw new Error(\"dem dimension mismatch\");var n=e*this.dim,i=e*this.dim+this.dim,a=r*this.dim,o=r*this.dim+this.dim;switch(e){case-1:n=i-1;break;case 1:i=n+1}switch(r){case-1:a=o-1;break;case 1:o=a+1}for(var s=-e*this.dim,l=-r*this.dim,c=a;c<o;c++)for(var u=n;u<i;u++)this.data[this._idx(u,c)]=t.data[this._idx(u+s,c+l)]},Dn(\"DEMData\",Hc);var Gc=function(t){this._stringToNumber={},this._numberToString=[];for(var e=0;e<t.length;e++){var r=t[e];this._stringToNumber[r]=e,this._numberToString[e]=r}};Gc.prototype.encode=function(t){return this._stringToNumber[t]},Gc.prototype.decode=function(t){return this._numberToString[t]};var Yc=function(t,e,r,n,i){this.type=\"Feature\",this._vectorTileFeature=t,t._z=e,t._x=r,t._y=n,this.properties=t.properties,this.id=i},Wc={geometry:{configurable:!0}};Wc.geometry.get=function(){return void 0===this._geometry&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry},Wc.geometry.set=function(t){this._geometry=t},Yc.prototype.toJSON=function(){var t={geometry:this.geometry};for(var e in this)\"_geometry\"!==e&&\"_vectorTileFeature\"!==e&&(t[e]=this[e]);return t},Object.defineProperties(Yc.prototype,Wc);var Xc=function(){this.state={},this.stateChanges={},this.deletedStates={}};Xc.prototype.updateState=function(t,e,r){var n=String(e);if(this.stateChanges[t]=this.stateChanges[t]||{},this.stateChanges[t][n]=this.stateChanges[t][n]||{},u(this.stateChanges[t][n],r),null===this.deletedStates[t])for(var i in this.deletedStates[t]={},this.state[t])i!==n&&(this.deletedStates[t][i]=null);else if(this.deletedStates[t]&&null===this.deletedStates[t][n])for(var a in this.deletedStates[t][n]={},this.state[t][n])r[a]||(this.deletedStates[t][n][a]=null);else for(var o in r)this.deletedStates[t]&&this.deletedStates[t][n]&&null===this.deletedStates[t][n][o]&&delete this.deletedStates[t][n][o]},Xc.prototype.removeFeatureState=function(t,e,r){if(null!==this.deletedStates[t]){var n=String(e);if(this.deletedStates[t]=this.deletedStates[t]||{},r&&void 0!==e)null!==this.deletedStates[t][n]&&(this.deletedStates[t][n]=this.deletedStates[t][n]||{},this.deletedStates[t][n][r]=null);else if(void 0!==e)if(this.stateChanges[t]&&this.stateChanges[t][n])for(r in this.deletedStates[t][n]={},this.stateChanges[t][n])this.deletedStates[t][n][r]=null;else this.deletedStates[t][n]=null;else this.deletedStates[t]=null}},Xc.prototype.getState=function(t,e){var r=String(e),n=u({},(this.state[t]||{})[r],(this.stateChanges[t]||{})[r]);if(null===this.deletedStates[t])return{};if(this.deletedStates[t]){var i=this.deletedStates[t][e];if(null===i)return{};for(var a in i)delete n[a]}return n},Xc.prototype.initializeTileState=function(t,e){t.setFeatureState(this.state,e)},Xc.prototype.coalesceChanges=function(t,e){var r={};for(var n in this.stateChanges){this.state[n]=this.state[n]||{};var i={};for(var a in this.stateChanges[n])this.state[n][a]||(this.state[n][a]={}),u(this.state[n][a],this.stateChanges[n][a]),i[a]=this.state[n][a];r[n]=i}for(var o in this.deletedStates){this.state[o]=this.state[o]||{};var s={};if(null===this.deletedStates[o])for(var l in this.state[o])s[l]={},this.state[o][l]={};else for(var c in this.deletedStates[o]){if(null===this.deletedStates[o][c])this.state[o][c]={};else for(var f=0,h=Object.keys(this.deletedStates[o][c]);f<h.length;f+=1)delete this.state[o][c][h[f]];s[c]=this.state[o][c]}r[o]=r[o]||{},u(r[o],s)}if(this.stateChanges={},this.deletedStates={},0!==Object.keys(r).length)for(var p in t)t[p].setFeatureState(r,e)};var Zc=function(t,e){this.tileID=t,this.x=t.canonical.x,this.y=t.canonical.y,this.z=t.canonical.z,this.grid=new Ln(8192,16,0),this.grid3D=new Ln(8192,16,0),this.featureIndexArray=new ra,this.promoteId=e};function Jc(t,e,r,n,i){return v(t,(function(t,a){var o=e instanceof hi?e.get(a):null;return o&&o.evaluate?o.evaluate(r,n,i):o}))}function Kc(t){for(var e=1/0,r=1/0,n=-1/0,i=-1/0,a=0,o=t;a<o.length;a+=1){var s=o[a];e=Math.min(e,s.x),r=Math.min(r,s.y),n=Math.max(n,s.x),i=Math.max(i,s.y)}return{minX:e,minY:r,maxX:n,maxY:i}}function Qc(t,e){return e-t}Zc.prototype.insert=function(t,e,r,n,i,a){var o=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(r,n,i);for(var s=a?this.grid3D:this.grid,l=0;l<e.length;l++){for(var c=e[l],u=[1/0,1/0,-1/0,-1/0],f=0;f<c.length;f++){var h=c[f];u[0]=Math.min(u[0],h.x),u[1]=Math.min(u[1],h.y),u[2]=Math.max(u[2],h.x),u[3]=Math.max(u[3],h.y)}u[0]<8192&&u[1]<8192&&u[2]>=0&&u[3]>=0&&s.insert(o,u[0],u[1],u[2],u[3])}},Zc.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new gs.VectorTile(new Hs(this.rawTileData)).layers,this.sourceLayerCoder=new Gc(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"])),this.vtLayers},Zc.prototype.query=function(t,e,r,n){var a=this;this.loadVTLayers();for(var o=t.params||{},s=8192/t.tileSize/t.scale,l=rn(o.filter),c=t.queryGeometry,u=t.queryPadding*s,f=Kc(c),h=this.grid.query(f.minX-u,f.minY-u,f.maxX+u,f.maxY+u),p=Kc(t.cameraQueryGeometry),d=0,g=this.grid3D.query(p.minX-u,p.minY-u,p.maxX+u,p.maxY+u,(function(e,r,n,a){return function(t,e,r,n,a){for(var o=0,s=t;o<s.length;o+=1){var l=s[o];if(e<=l.x&&r<=l.y&&n>=l.x&&a>=l.y)return!0}var c=[new i(e,r),new i(e,a),new i(n,a),new i(n,r)];if(t.length>2)for(var u=0,f=c;u<f.length;u+=1)if(Wa(t,f[u]))return!0;for(var h=0;h<t.length-1;h++)if(Xa(t[h],t[h+1],c))return!0;return!1}(t.cameraQueryGeometry,e-u,r-u,n+u,a+u)}));d<g.length;d+=1)h.push(g[d]);h.sort(Qc);for(var m,v={},y=function(i){var u=h[i];if(u!==m){m=u;var f=a.featureIndexArray.get(u),p=null;a.loadMatchingFeature(v,f.bucketIndex,f.sourceLayerIndex,f.featureIndex,l,o.layers,o.availableImages,e,r,n,(function(e,r,n){return p||(p=Da(e)),r.queryIntersectsFeature(c,e,n,p,a.z,t.transform,s,t.pixelPosMatrix)}))}},x=0;x<h.length;x++)y(x);return v},Zc.prototype.loadMatchingFeature=function(t,e,r,n,i,a,o,s,l,c,u){var f=this.bucketLayerIDs[e];if(!a||function(t,e){for(var r=0;r<t.length;r++)if(e.indexOf(t[r])>=0)return!0;return!1}(a,f)){var h=this.sourceLayerCoder.decode(r),p=this.vtLayers[h].feature(n);if(i.filter(new ii(this.tileID.overscaledZ),p))for(var d=this.getId(p,h),g=0;g<f.length;g++){var m=f[g];if(!(a&&a.indexOf(m)<0)){var v=s[m];if(v){var y={};void 0!==d&&c&&(y=c.getState(v.sourceLayer||\"_geojsonTileLayer\",d));var x=l[m];x.paint=Jc(x.paint,v.paint,p,y,o),x.layout=Jc(x.layout,v.layout,p,y,o);var b=!u||u(p,v,y);if(b){var _=new Yc(p,this.z,this.x,this.y,d);_.layer=x;var w=t[m];void 0===w&&(w=t[m]=[]),w.push({featureIndex:n,feature:_,intersectionZ:b})}}}}}},Zc.prototype.lookupSymbolFeatures=function(t,e,r,n,i,a,o,s){var l={};this.loadVTLayers();for(var c=rn(i),u=0,f=t;u<f.length;u+=1)this.loadMatchingFeature(l,r,n,f[u],c,a,o,s,e);return l},Zc.prototype.hasLayer=function(t){for(var e=0,r=this.bucketLayerIDs;e<r.length;e+=1)for(var n=0,i=r[e];n<i.length;n+=1)if(t===i[n])return!0;return!1},Zc.prototype.getId=function(t,e){var r=t.id;return this.promoteId&&\"boolean\"==typeof(r=t.properties[\"string\"==typeof this.promoteId?this.promoteId:this.promoteId[e]])&&(r=Number(r)),r},Dn(\"FeatureIndex\",Zc,{omit:[\"rawTileData\",\"sourceLayerCoder\"]});var $c=function(t,e){this.tileID=t,this.uid=h(),this.uses=0,this.tileSize=e,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.hasSymbolBuckets=!1,this.hasRTLText=!1,this.dependencies={},this.expiredRequestCount=0,this.state=\"loading\"};$c.prototype.registerFadeDuration=function(t){var e=t+this.timeAdded;e<R.now()||this.fadeEndTime&&e<this.fadeEndTime||(this.fadeEndTime=e)},$c.prototype.wasRequested=function(){return\"errored\"===this.state||\"loaded\"===this.state||\"reloading\"===this.state},$c.prototype.loadVectorData=function(t,e,r){if(this.hasData()&&this.unloadVectorData(),this.state=\"loaded\",t){for(var n in t.featureIndex&&(this.latestFeatureIndex=t.featureIndex,t.rawTileData?(this.latestRawTileData=t.rawTileData,this.latestFeatureIndex.rawTileData=t.rawTileData):this.latestRawTileData&&(this.latestFeatureIndex.rawTileData=this.latestRawTileData)),this.collisionBoxArray=t.collisionBoxArray,this.buckets=function(t,e){var r={};if(!e)return r;for(var n=function(){var t=a[i],n=t.layerIds.map((function(t){return e.getLayer(t)})).filter(Boolean);if(0!==n.length){t.layers=n,t.stateDependentLayerIds&&(t.stateDependentLayers=t.stateDependentLayerIds.map((function(t){return n.filter((function(e){return e.id===t}))[0]})));for(var o=0,s=n;o<s.length;o+=1)r[s[o].id]=t}},i=0,a=t;i<a.length;i+=1)n();return r}(t.buckets,e.style),this.hasSymbolBuckets=!1,this.buckets){var i=this.buckets[n];if(i instanceof fc){if(this.hasSymbolBuckets=!0,!r)break;i.justReloaded=!0}}if(this.hasRTLText=!1,this.hasSymbolBuckets)for(var a in this.buckets){var o=this.buckets[a];if(o instanceof fc&&o.hasRTLText){this.hasRTLText=!0,ni.isLoading()||ni.isLoaded()||\"deferred\"!==ei()||ri();break}}for(var s in this.queryPadding=0,this.buckets){var l=this.buckets[s];this.queryPadding=Math.max(this.queryPadding,e.style.getLayer(s).queryRadius(l))}t.imageAtlas&&(this.imageAtlas=t.imageAtlas),t.glyphAtlasImage&&(this.glyphAtlasImage=t.glyphAtlasImage)}else this.collisionBoxArray=new Xi},$c.prototype.unloadVectorData=function(){for(var t in this.buckets)this.buckets[t].destroy();this.buckets={},this.imageAtlasTexture&&this.imageAtlasTexture.destroy(),this.imageAtlas&&(this.imageAtlas=null),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state=\"unloaded\"},$c.prototype.getBucket=function(t){return this.buckets[t.id]},$c.prototype.upload=function(t){for(var e in this.buckets){var r=this.buckets[e];r.uploadPending()&&r.upload(t)}var n=t.gl;this.imageAtlas&&!this.imageAtlas.uploaded&&(this.imageAtlasTexture=new Sc(t,this.imageAtlas.image,n.RGBA),this.imageAtlas.uploaded=!0),this.glyphAtlasImage&&(this.glyphAtlasTexture=new Sc(t,this.glyphAtlasImage,n.ALPHA),this.glyphAtlasImage=null)},$c.prototype.prepare=function(t){this.imageAtlas&&this.imageAtlas.patchUpdatedImages(t,this.imageAtlasTexture)},$c.prototype.queryRenderedFeatures=function(t,e,r,n,i,a,o,s,l,c){return this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData?this.latestFeatureIndex.query({queryGeometry:n,cameraQueryGeometry:i,scale:a,tileSize:this.tileSize,pixelPosMatrix:c,transform:s,params:o,queryPadding:this.queryPadding*l},t,e,r):{}},$c.prototype.querySourceFeatures=function(t,e){var r=this.latestFeatureIndex;if(r&&r.rawTileData){var n=r.loadVTLayers(),i=e?e.sourceLayer:\"\",a=n._geojsonTileLayer||n[i];if(a)for(var o=rn(e&&e.filter),s=this.tileID.canonical,l=s.z,c=s.x,u=s.y,f={z:l,x:c,y:u},h=0;h<a.length;h++){var p=a.feature(h);if(o.filter(new ii(this.tileID.overscaledZ),p)){var d=r.getId(p,i),g=new Yc(p,l,c,u,d);g.tile=f,t.push(g)}}}},$c.prototype.hasData=function(){return\"loaded\"===this.state||\"reloading\"===this.state||\"expired\"===this.state},$c.prototype.patternsLoaded=function(){return this.imageAtlas&&!!Object.keys(this.imageAtlas.patternPositions).length},$c.prototype.setExpiryData=function(t){var e=this.expirationTime;if(t.cacheControl){var r=M(t.cacheControl);r[\"max-age\"]&&(this.expirationTime=Date.now()+1e3*r[\"max-age\"])}else t.expires&&(this.expirationTime=new Date(t.expires).getTime());if(this.expirationTime){var n=Date.now(),i=!1;if(this.expirationTime>n)i=!1;else if(e)if(this.expirationTime<e)i=!0;else{var a=this.expirationTime-e;a?this.expirationTime=n+Math.max(a,3e4):i=!0}else i=!0;i?(this.expiredRequestCount++,this.state=\"expired\"):this.expiredRequestCount=0}},$c.prototype.getExpiryTimeout=function(){if(this.expirationTime)return this.expiredRequestCount?1e3*(1<<Math.min(this.expiredRequestCount-1,31)):Math.min(this.expirationTime-(new Date).getTime(),Math.pow(2,31)-1)},$c.prototype.setFeatureState=function(t,e){if(this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData&&0!==Object.keys(t).length){var r=this.latestFeatureIndex.loadVTLayers();for(var n in this.buckets)if(e.style.hasLayer(n)){var i=this.buckets[n],a=i.layers[0].sourceLayer||\"_geojsonTileLayer\",o=r[a],s=t[a];if(o&&s&&0!==Object.keys(s).length){i.update(s,o,this.imageAtlas&&this.imageAtlas.patternPositions||{});var l=e&&e.style&&e.style.getLayer(n);l&&(this.queryPadding=Math.max(this.queryPadding,l.queryRadius(i)))}}}},$c.prototype.holdingForFade=function(){return void 0!==this.symbolFadeHoldUntil},$c.prototype.symbolFadeFinished=function(){return!this.symbolFadeHoldUntil||this.symbolFadeHoldUntil<R.now()},$c.prototype.clearFadeHold=function(){this.symbolFadeHoldUntil=void 0},$c.prototype.setHoldDuration=function(t){this.symbolFadeHoldUntil=R.now()+t},$c.prototype.setDependencies=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1)r[i[n]]=!0;this.dependencies[t]=r},$c.prototype.hasDependency=function(t,e){for(var r=0,n=t;r<n.length;r+=1){var i=this.dependencies[n[r]];if(i)for(var a=0,o=e;a<o.length;a+=1)if(i[o[a]])return!0}return!1};var tu=self.performance,eu=function(t){this._marks={start:[t.url,\"start\"].join(\"#\"),end:[t.url,\"end\"].join(\"#\"),measure:t.url.toString()},tu.mark(this._marks.start)};eu.prototype.finish=function(){tu.mark(this._marks.end);var t=tu.getEntriesByName(this._marks.measure);return 0===t.length&&(tu.measure(this._marks.measure,this._marks.start,this._marks.end),t=tu.getEntriesByName(this._marks.measure),tu.clearMarks(this._marks.start),tu.clearMarks(this._marks.end),tu.clearMeasures(this._marks.measure)),t},t.Actor=Cc,t.AlphaImage=ho,t.CanonicalTileID=jc,t.CollisionBoxArray=Xi,t.Color=Kt,t.DEMData=Hc,t.DataConstantProperty=pi,t.DictionaryCoder=Gc,t.EXTENT=8192,t.ErrorEvent=kt,t.EvaluationParameters=ii,t.Event=Tt,t.Evented=Mt,t.FeatureIndex=Zc,t.FillBucket=rs,t.FillExtrusionBucket=xs,t.ImageAtlas=dl,t.ImagePosition=hl,t.LineBucket=Cs,t.LngLat=Pc,t.LngLatBounds=Ic,t.MercatorCoordinate=Nc,t.ONE_EM=24,t.OverscaledTileID=Vc,t.Point=i,t.Point$1=i,t.Properties=yi,t.Protobuf=Hs,t.RGBAImage=po,t.RequestManager=q,t.RequestPerformance=eu,t.ResourceType=ht,t.SegmentVector=ia,t.SourceFeatureState=Xc,t.StructArrayLayout1ui2=Hi,t.StructArrayLayout2f1f2i16=Di,t.StructArrayLayout2i4=Mi,t.StructArrayLayout3ui6=Fi,t.StructArrayLayout4i8=Ai,t.SymbolBucket=fc,t.Texture=Sc,t.Tile=$c,t.Transitionable=si,t.Uniform1f=va,t.Uniform1i=ma,t.Uniform2f=ya,t.Uniform3f=xa,t.Uniform4f=ba,t.UniformColor=_a,t.UniformMatrix4f=Ta,t.UnwrappedTileID=Uc,t.ValidationError=St,t.WritingMode=gl,t.ZoomHistory=Un,t.add=function(t,e,r){return t[0]=e[0]+r[0],t[1]=e[1]+r[1],t[2]=e[2]+r[2],t},t.addDynamicAttributes=sc,t.asyncAll=function(t,e,r){if(!t.length)return r(null,[]);var n=t.length,i=new Array(t.length),a=null;t.forEach((function(t,o){e(t,(function(t,e){t&&(a=t),i[o]=e,0==--n&&r(a,i)}))}))},t.bezier=o,t.bindAll=g,t.browser=R,t.cacheEntryPossiblyAdded=function(t){++ut>ot&&(t.getActor().send(\"enforceCacheSizeLimit\",at),ut=0)},t.clamp=l,t.clearTileCache=function(t){var e=self.caches.delete(\"mapbox-tiles\");t&&e.catch(t).then((function(){return t()}))},t.clipLine=jl,t.clone=function(t){var e=new to(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e},t.clone$1=x,t.clone$2=function(t){var e=new to(3);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e},t.collisionCircleLayout=Ns,t.config=F,t.create=function(){var t=new to(16);return to!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[11]=0,t[12]=0,t[13]=0,t[14]=0),t[0]=1,t[5]=1,t[10]=1,t[15]=1,t},t.create$1=function(){var t=new to(9);return to!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[5]=0,t[6]=0,t[7]=0),t[0]=1,t[4]=1,t[8]=1,t},t.create$2=function(){var t=new to(4);return to!=Float32Array&&(t[1]=0,t[2]=0),t[0]=1,t[3]=1,t},t.createCommonjsModule=e,t.createExpression=qr,t.createLayout=Ti,t.createStyleLayer=function(t){return\"custom\"===t.type?new bc(t):new _c[t.type](t)},t.cross=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=r[0],s=r[1],l=r[2];return t[0]=i*l-a*s,t[1]=a*o-n*l,t[2]=n*s-i*o,t},t.deepEqual=function t(e,r){if(Array.isArray(e)){if(!Array.isArray(r)||e.length!==r.length)return!1;for(var n=0;n<e.length;n++)if(!t(e[n],r[n]))return!1;return!0}if(\"object\"==typeof e&&null!==e&&null!==r){if(\"object\"!=typeof r)return!1;if(Object.keys(e).length!==Object.keys(r).length)return!1;for(var i in e)if(!t(e[i],r[i]))return!1;return!0}return e===r},t.dot=function(t,e){return t[0]*e[0]+t[1]*e[1]+t[2]*e[2]},t.dot$1=function(t,e){return t[0]*e[0]+t[1]*e[1]+t[2]*e[2]+t[3]*e[3]},t.ease=s,t.emitValidationErrors=Cn,t.endsWith=m,t.enforceCacheSizeLimit=function(t){st(),Q&&Q.then((function(e){e.keys().then((function(r){for(var n=0;n<r.length-t;n++)e.delete(r[n])}))}))},t.evaluateSizeForFeature=Il,t.evaluateSizeForZoom=Pl,t.evaluateVariableOffset=$l,t.evented=ti,t.extend=u,t.featureFilter=rn,t.filterObject=y,t.fromRotation=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=r,t[2]=0,t[3]=-r,t[4]=n,t[5]=0,t[6]=0,t[7]=0,t[8]=1,t},t.getAnchorAlignment=Al,t.getAnchorJustification=tc,t.getArrayBuffer=yt,t.getImage=bt,t.getJSON=function(t,e){return vt(u(t,{type:\"json\"}),e)},t.getRTLTextPluginStatus=ei,t.getReferrer=mt,t.getVideo=function(t,e){var r,n,i=self.document.createElement(\"video\");i.muted=!0,i.onloadstart=function(){e(null,i)};for(var a=0;a<t.length;a++){var o=self.document.createElement(\"source\");r=t[a],n=void 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r}function ft(t,e){var r=[];r.size=t.size,void 0!==t.start&&(r.start=t.start,r.end=t.end);for(var n=0;n<t.length;n+=3)r.push(t[n]+e,t[n+1],t[n+2]);return r}function ht(t,e){if(t.transformed)return t;var r,n,i,a=1<<t.z,o=t.x,s=t.y;for(r=0;r<t.features.length;r++){var l=t.features[r],c=l.geometry,u=l.type;if(l.geometry=[],1===u)for(n=0;n<c.length;n+=2)l.geometry.push(pt(c[n],c[n+1],e,a,o,s));else for(n=0;n<c.length;n++){var f=[];for(i=0;i<c[n].length;i+=2)f.push(pt(c[n][i],c[n][i+1],e,a,o,s));l.geometry.push(f)}}return t.transformed=!0,t}function pt(t,e,r,n,i,a){return[Math.round(r*(t*n-i)),Math.round(r*(e*n-a))]}function dt(t,e,r,n,i){for(var a=e===i.maxZoom?0:i.tolerance/((1<<e)*i.extent),o={features:[],numPoints:0,numSimplified:0,numFeatures:0,source:null,x:r,y:n,z:e,transformed:!1,minX:2,minY:1,maxX:-1,maxY:0},s=0;s<t.length;s++){o.numFeatures++,gt(o,t[s],a,i);var l=t[s].minX,c=t[s].minY,u=t[s].maxX,f=t[s].maxY;l<o.minX&&(o.minX=l),c<o.minY&&(o.minY=c),u>o.maxX&&(o.maxX=u),f>o.maxY&&(o.maxY=f)}return o}function gt(t,e,r,n){var i=e.geometry,a=e.type,o=[];if(\"Point\"===a||\"MultiPoint\"===a)for(var s=0;s<i.length;s+=3)o.push(i[s]),o.push(i[s+1]),t.numPoints++,t.numSimplified++;else if(\"LineString\"===a)mt(o,i,t,r,!1,!1);else if(\"MultiLineString\"===a||\"Polygon\"===a)for(s=0;s<i.length;s++)mt(o,i[s],t,r,\"Polygon\"===a,0===s);else if(\"MultiPolygon\"===a)for(var l=0;l<i.length;l++){var c=i[l];for(s=0;s<c.length;s++)mt(o,c[s],t,r,!0,0===s)}if(o.length){var u=e.tags||null;if(\"LineString\"===a&&n.lineMetrics){for(var f in u={},e.tags)u[f]=e.tags[f];u.mapbox_clip_start=i.start/i.size,u.mapbox_clip_end=i.end/i.size}var h={geometry:o,type:\"Polygon\"===a||\"MultiPolygon\"===a?3:\"LineString\"===a||\"MultiLineString\"===a?2:1,tags:u};null!==e.id&&(h.id=e.id),t.features.push(h)}}function mt(t,e,r,n,i,a){var o=n*n;if(n>0&&e.size<(i?o:n))r.numPoints+=e.length/3;else{for(var s=[],l=0;l<e.length;l+=3)(0===n||e[l+2]>o)&&(r.numSimplified++,s.push(e[l]),s.push(e[l+1])),r.numPoints++;i&&function(t,e){for(var r=0,n=0,i=t.length,a=i-2;n<i;a=n,n+=2)r+=(t[n]-t[a])*(t[n+1]+t[a+1]);if(r>0===e)for(n=0,i=t.length;n<i/2;n+=2){var o=t[n],s=t[n+1];t[n]=t[i-2-n],t[n+1]=t[i-1-n],t[i-2-n]=o,t[i-1-n]=s}}(s,a),t.push(s)}}function vt(t,e){var r=(e=this.options=function(t,e){for(var r in e)t[r]=e[r];return t}(Object.create(this.options),e)).debug;if(r&&console.time(\"preprocess data\"),e.maxZoom<0||e.maxZoom>24)throw new Error(\"maxZoom should be in the 0-24 range\");if(e.promoteId&&e.generateId)throw new Error(\"promoteId and generateId cannot be used together.\");var n=function(t,e){var r=[];if(\"FeatureCollection\"===t.type)for(var n=0;n<t.features.length;n++)J(r,t.features[n],e,n);else J(r,\"Feature\"===t.type?t:{geometry:t},e);return r}(t,e);this.tiles={},this.tileCoords=[],r&&(console.timeEnd(\"preprocess data\"),console.log(\"index: maxZoom: %d, maxPoints: %d\",e.indexMaxZoom,e.indexMaxPoints),console.time(\"generate tiles\"),this.stats={},this.total=0),(n=function(t,e){var r=e.buffer/e.extent,n=t,i=rt(t,1,-1-r,r,0,-1,2,e),a=rt(t,1,1-r,2+r,0,-1,2,e);return(i||a)&&(n=rt(t,1,-r,1+r,0,-1,2,e)||[],i&&(n=ut(i,1).concat(n)),a&&(n=n.concat(ut(a,-1)))),n}(n,e)).length&&this.splitTile(n,0,0,0),r&&(n.length&&console.log(\"features: %d, points: %d\",this.tiles[0].numFeatures,this.tiles[0].numPoints),console.timeEnd(\"generate tiles\"),console.log(\"tiles generated:\",this.total,JSON.stringify(this.stats)))}function yt(t,e,r){return 32*((1<<t)*r+e)+t}function xt(t,e){var r=t.tileID.canonical;if(!this._geoJSONIndex)return e(null,null);var n=this._geoJSONIndex.getTile(r.z,r.x,r.y);if(!n)return e(null,null);var i=new g(n.features),a=b(i);0===a.byteOffset&&a.byteLength===a.buffer.byteLength||(a=new Uint8Array(a)),e(null,{vectorTile:i,rawData:a.buffer})}F.prototype.load=function(t){var e=this.options,r=e.log,n=e.minZoom,i=e.maxZoom,a=e.nodeSize;r&&console.time(\"total time\");var o=\"prepare \"+t.length+\" points\";r&&console.time(o),this.points=t;for(var s=[],l=0;l<t.length;l++)t[l].geometry&&s.push(N(t[l],l));this.trees[i+1]=new D(s,G,Y,a,Float32Array),r&&console.timeEnd(o);for(var c=i;c>=n;c--){var u=+Date.now();s=this._cluster(s,c),this.trees[c]=new D(s,G,Y,a,Float32Array),r&&console.log(\"z%d: %d clusters in %dms\",c,s.length,+Date.now()-u)}return r&&console.timeEnd(\"total time\"),this},F.prototype.getClusters=function(t,e){var r=((t[0]+180)%360+360)%360-180,n=Math.max(-90,Math.min(90,t[1])),i=180===t[2]?180:((t[2]+180)%360+360)%360-180,a=Math.max(-90,Math.min(90,t[3]));if(t[2]-t[0]>=360)r=-180,i=180;else if(r>i){var o=this.getClusters([r,n,180,a],e),s=this.getClusters([-180,n,i,a],e);return o.concat(s)}for(var l=this.trees[this._limitZoom(e)],c=[],u=0,f=l.range(V(r),q(a),V(i),q(n));u<f.length;u+=1){var h=l.points[f[u]];c.push(h.numPoints?j(h):this.points[h.index])}return c},F.prototype.getChildren=function(t){var e=this._getOriginId(t),r=this._getOriginZoom(t),n=\"No cluster with the specified id.\",i=this.trees[r];if(!i)throw new Error(n);var a=i.points[e];if(!a)throw new Error(n);for(var o=this.options.radius/(this.options.extent*Math.pow(2,r-1)),s=[],l=0,c=i.within(a.x,a.y,o);l<c.length;l+=1){var u=i.points[c[l]];u.parentId===t&&s.push(u.numPoints?j(u):this.points[u.index])}if(0===s.length)throw new Error(n);return s},F.prototype.getLeaves=function(t,e,r){var n=[];return this._appendLeaves(n,t,e=e||10,r=r||0,0),n},F.prototype.getTile=function(t,e,r){var n=this.trees[this._limitZoom(t)],i=Math.pow(2,t),a=this.options,o=a.radius/a.extent,s=(r-o)/i,l=(r+1+o)/i,c={features:[]};return this._addTileFeatures(n.range((e-o)/i,s,(e+1+o)/i,l),n.points,e,r,i,c),0===e&&this._addTileFeatures(n.range(1-o/i,s,1,l),n.points,i,r,i,c),e===i-1&&this._addTileFeatures(n.range(0,s,o/i,l),n.points,-1,r,i,c),c.features.length?c:null},F.prototype.getClusterExpansionZoom=function(t){for(var e=this._getOriginZoom(t)-1;e<=this.options.maxZoom;){var r=this.getChildren(t);if(e++,1!==r.length)break;t=r[0].properties.cluster_id}return e},F.prototype._appendLeaves=function(t,e,r,n,i){for(var a=0,o=this.getChildren(e);a<o.length;a+=1){var s=o[a],l=s.properties;if(l&&l.cluster?i+l.point_count<=n?i+=l.point_count:i=this._appendLeaves(t,l.cluster_id,r,n,i):i<n?i++:t.push(s),t.length===r)break}return i},F.prototype._addTileFeatures=function(t,e,r,n,i,a){for(var o=0,s=t;o<s.length;o+=1){var l=e[s[o]],c=l.numPoints,u={type:1,geometry:[[Math.round(this.options.extent*(l.x*i-r)),Math.round(this.options.extent*(l.y*i-n))]],tags:c?U(l):this.points[l.index].properties},f=void 0;c?f=l.id:this.options.generateId?f=l.index:this.points[l.index].id&&(f=this.points[l.index].id),void 0!==f&&(u.id=f),a.features.push(u)}},F.prototype._limitZoom=function(t){return Math.max(this.options.minZoom,Math.min(t,this.options.maxZoom+1))},F.prototype._cluster=function(t,e){for(var r=[],n=this.options,i=n.reduce,a=n.radius/(n.extent*Math.pow(2,e)),o=0;o<t.length;o++){var s=t[o];if(!(s.zoom<=e)){s.zoom=e;for(var l=this.trees[e+1],c=l.within(s.x,s.y,a),u=s.numPoints||1,f=s.x*u,h=s.y*u,p=i&&u>1?this._map(s,!0):null,d=(o<<5)+(e+1)+this.points.length,g=0,m=c;g<m.length;g+=1){var v=l.points[m[g]];if(!(v.zoom<=e)){v.zoom=e;var y=v.numPoints||1;f+=v.x*y,h+=v.y*y,u+=y,v.parentId=d,i&&(p||(p=this._map(s,!0)),i(p,this._map(v)))}}1===u?r.push(s):(s.parentId=d,r.push(B(f/u,h/u,d,u,p)))}}return r},F.prototype._getOriginId=function(t){return t-this.points.length>>5},F.prototype._getOriginZoom=function(t){return(t-this.points.length)%32},F.prototype._map=function(t,e){if(t.numPoints)return e?H({},t.properties):t.properties;var r=this.points[t.index].properties,n=this.options.map(r);return e&&n===r?H({},n):n},vt.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},vt.prototype.splitTile=function(t,e,r,n,i,a,o){for(var s=[t,e,r,n],l=this.options,c=l.debug;s.length;){n=s.pop(),r=s.pop(),e=s.pop(),t=s.pop();var u=1<<e,f=yt(e,r,n),h=this.tiles[f];if(!h&&(c>1&&console.time(\"creation\"),h=this.tiles[f]=dt(t,e,r,n,l),this.tileCoords.push({z:e,x:r,y:n}),c)){c>1&&(console.log(\"tile z%d-%d-%d (features: %d, points: %d, simplified: %d)\",e,r,n,h.numFeatures,h.numPoints,h.numSimplified),console.timeEnd(\"creation\"));var p=\"z\"+e;this.stats[p]=(this.stats[p]||0)+1,this.total++}if(h.source=t,i){if(e===l.maxZoom||e===i)continue;var d=1<<i-e;if(r!==Math.floor(a/d)||n!==Math.floor(o/d))continue}else if(e===l.indexMaxZoom||h.numPoints<=l.indexMaxPoints)continue;if(h.source=null,0!==t.length){c>1&&console.time(\"clipping\");var g,m,v,y,x,b,_=.5*l.buffer/l.extent,w=.5-_,T=.5+_,k=1+_;g=m=v=y=null,x=rt(t,u,r-_,r+T,0,h.minX,h.maxX,l),b=rt(t,u,r+w,r+k,0,h.minX,h.maxX,l),t=null,x&&(g=rt(x,u,n-_,n+T,1,h.minY,h.maxY,l),m=rt(x,u,n+w,n+k,1,h.minY,h.maxY,l),x=null),b&&(v=rt(b,u,n-_,n+T,1,h.minY,h.maxY,l),y=rt(b,u,n+w,n+k,1,h.minY,h.maxY,l),b=null),c>1&&console.timeEnd(\"clipping\"),s.push(g||[],e+1,2*r,2*n),s.push(m||[],e+1,2*r,2*n+1),s.push(v||[],e+1,2*r+1,2*n),s.push(y||[],e+1,2*r+1,2*n+1)}}},vt.prototype.getTile=function(t,e,r){var n=this.options,i=n.extent,a=n.debug;if(t<0||t>24)return null;var o=1<<t,s=yt(t,e=(e%o+o)%o,r);if(this.tiles[s])return ht(this.tiles[s],i);a>1&&console.log(\"drilling down to z%d-%d-%d\",t,e,r);for(var l,c=t,u=e,f=r;!l&&c>0;)c--,u=Math.floor(u/2),f=Math.floor(f/2),l=this.tiles[yt(c,u,f)];return l&&l.source?(a>1&&console.log(\"found parent tile z%d-%d-%d\",c,u,f),a>1&&console.time(\"drilling down\"),this.splitTile(l.source,c,u,f,t,e,r),a>1&&console.timeEnd(\"drilling down\"),this.tiles[s]?ht(this.tiles[s],i):null):null};var bt=function(e){function r(t,r,n,i){e.call(this,t,r,n,xt),i&&(this.loadGeoJSON=i)}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.loadData=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),this._pendingCallback=e,this._pendingLoadDataParams=t,this._state&&\"Idle\"!==this._state?this._state=\"NeedsLoadData\":(this._state=\"Coalescing\",this._loadData())},r.prototype._loadData=function(){var e=this;if(this._pendingCallback&&this._pendingLoadDataParams){var r=this._pendingCallback,n=this._pendingLoadDataParams;delete this._pendingCallback,delete this._pendingLoadDataParams;var i=!!(n&&n.request&&n.request.collectResourceTiming)&&new t.RequestPerformance(n.request);this.loadGeoJSON(n,(function(a,o){if(a||!o)return r(a);if(\"object\"!=typeof o)return r(new Error(\"Input data given to '\"+n.source+\"' is not a valid GeoJSON object.\"));!function t(e,r){var n,i=e&&e.type;if(\"FeatureCollection\"===i)for(n=0;n<e.features.length;n++)t(e.features[n],r);else if(\"GeometryCollection\"===i)for(n=0;n<e.geometries.length;n++)t(e.geometries[n],r);else if(\"Feature\"===i)t(e.geometry,r);else if(\"Polygon\"===i)f(e.coordinates,r);else if(\"MultiPolygon\"===i)for(n=0;n<e.coordinates.length;n++)f(e.coordinates[n],r);return e}(o,!0);try{e._geoJSONIndex=n.cluster?new F(function(e){var r=e.superclusterOptions,n=e.clusterProperties;if(!n||!r)return r;for(var i={},a={},o={accumulated:null,zoom:0},s={properties:null},l=Object.keys(n),c=0,u=l;c<u.length;c+=1){var f=u[c],h=n[f],p=h[0],d=t.createExpression(h[1]),g=t.createExpression(\"string\"==typeof p?[p,[\"accumulated\"],[\"get\",f]]:p);i[f]=d.value,a[f]=g.value}return r.map=function(t){s.properties=t;for(var e={},r=0,n=l;r<n.length;r+=1){var a=n[r];e[a]=i[a].evaluate(o,s)}return e},r.reduce=function(t,e){s.properties=e;for(var r=0,n=l;r<n.length;r+=1){var i=n[r];o.accumulated=t[i],t[i]=a[i].evaluate(o,s)}},r}(n)).load(o.features):function(t,e){return new vt(t,e)}(o,n.geojsonVtOptions)}catch(a){return r(a)}e.loaded={};var s={};if(i){var l=i.finish();l&&(s.resourceTiming={},s.resourceTiming[n.source]=JSON.parse(JSON.stringify(l)))}r(null,s)}))}},r.prototype.coalesce=function(){\"Coalescing\"===this._state?this._state=\"Idle\":\"NeedsLoadData\"===this._state&&(this._state=\"Coalescing\",this._loadData())},r.prototype.reloadTile=function(t,r){var n=this.loaded;return n&&n[t.uid]?e.prototype.reloadTile.call(this,t,r):this.loadTile(t,r)},r.prototype.loadGeoJSON=function(e,r){if(e.request)t.getJSON(e.request,r);else{if(\"string\"!=typeof e.data)return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON object.\"));try{return r(null,JSON.parse(e.data))}catch(t){return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON object.\"))}}},r.prototype.removeSource=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),e()},r.prototype.getClusterExpansionZoom=function(t,e){try{e(null,this._geoJSONIndex.getClusterExpansionZoom(t.clusterId))}catch(t){e(t)}},r.prototype.getClusterChildren=function(t,e){try{e(null,this._geoJSONIndex.getChildren(t.clusterId))}catch(t){e(t)}},r.prototype.getClusterLeaves=function(t,e){try{e(null,this._geoJSONIndex.getLeaves(t.clusterId,t.limit,t.offset))}catch(t){e(t)}},r}(l),_t=function(e){var r=this;this.self=e,this.actor=new t.Actor(e,this),this.layerIndexes={},this.availableImages={},this.workerSourceTypes={vector:l,geojson:bt},this.workerSources={},this.demWorkerSources={},this.self.registerWorkerSource=function(t,e){if(r.workerSourceTypes[t])throw new Error('Worker source with name \"'+t+'\" already registered.');r.workerSourceTypes[t]=e},this.self.registerRTLTextPlugin=function(e){if(t.plugin.isParsed())throw new Error(\"RTL text plugin already registered.\");t.plugin.applyArabicShaping=e.applyArabicShaping,t.plugin.processBidirectionalText=e.processBidirectionalText,t.plugin.processStyledBidirectionalText=e.processStyledBidirectionalText}};return _t.prototype.setReferrer=function(t,e){this.referrer=e},_t.prototype.setImages=function(t,e,r){for(var n in this.availableImages[t]=e,this.workerSources[t]){var i=this.workerSources[t][n];for(var a in i)i[a].availableImages=e}r()},_t.prototype.setLayers=function(t,e,r){this.getLayerIndex(t).replace(e),r()},_t.prototype.updateLayers=function(t,e,r){this.getLayerIndex(t).update(e.layers,e.removedIds),r()},_t.prototype.loadTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).loadTile(e,r)},_t.prototype.loadDEMTile=function(t,e,r){this.getDEMWorkerSource(t,e.source).loadTile(e,r)},_t.prototype.reloadTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).reloadTile(e,r)},_t.prototype.abortTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).abortTile(e,r)},_t.prototype.removeTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).removeTile(e,r)},_t.prototype.removeDEMTile=function(t,e){this.getDEMWorkerSource(t,e.source).removeTile(e)},_t.prototype.removeSource=function(t,e,r){if(this.workerSources[t]&&this.workerSources[t][e.type]&&this.workerSources[t][e.type][e.source]){var n=this.workerSources[t][e.type][e.source];delete this.workerSources[t][e.type][e.source],void 0!==n.removeSource?n.removeSource(e,r):r()}},_t.prototype.loadWorkerSource=function(t,e,r){try{this.self.importScripts(e.url),r()}catch(t){r(t.toString())}},_t.prototype.syncRTLPluginState=function(e,r,n){try{t.plugin.setState(r);var i=t.plugin.getPluginURL();if(t.plugin.isLoaded()&&!t.plugin.isParsed()&&null!=i){this.self.importScripts(i);var a=t.plugin.isParsed();n(a?void 0:new Error(\"RTL Text Plugin failed to import scripts from \"+i),a)}}catch(t){n(t.toString())}},_t.prototype.getAvailableImages=function(t){var e=this.availableImages[t];return e||(e=[]),e},_t.prototype.getLayerIndex=function(t){var e=this.layerIndexes[t];return e||(e=this.layerIndexes[t]=new n),e},_t.prototype.getWorkerSource=function(t,e,r){var n=this;return this.workerSources[t]||(this.workerSources[t]={}),this.workerSources[t][e]||(this.workerSources[t][e]={}),this.workerSources[t][e][r]||(this.workerSources[t][e][r]=new this.workerSourceTypes[e]({send:function(e,r,i){n.actor.send(e,r,i,t)}},this.getLayerIndex(t),this.getAvailableImages(t))),this.workerSources[t][e][r]},_t.prototype.getDEMWorkerSource=function(t,e){return this.demWorkerSources[t]||(this.demWorkerSources[t]={}),this.demWorkerSources[t][e]||(this.demWorkerSources[t][e]=new u),this.demWorkerSources[t][e]},_t.prototype.enforceCacheSizeLimit=function(e,r){t.enforceCacheSizeLimit(r)},\"undefined\"!=typeof WorkerGlobalScope&&void 0!==t.window&&t.window instanceof WorkerGlobalScope&&(t.window.worker=new _t(t.window)),_t})),n(0,(function(t){var e=t.createCommonjsModule((function(t){function e(t){return!r(t)}function r(t){return\"undefined\"==typeof window||\"undefined\"==typeof document?\"not a browser\":Array.prototype&&Array.prototype.every&&Array.prototype.filter&&Array.prototype.forEach&&Array.prototype.indexOf&&Array.prototype.lastIndexOf&&Array.prototype.map&&Array.prototype.some&&Array.prototype.reduce&&Array.prototype.reduceRight&&Array.isArray?Function.prototype&&Function.prototype.bind?Object.keys&&Object.create&&Object.getPrototypeOf&&Object.getOwnPropertyNames&&Object.isSealed&&Object.isFrozen&&Object.isExtensible&&Object.getOwnPropertyDescriptor&&Object.defineProperty&&Object.defineProperties&&Object.seal&&Object.freeze&&Object.preventExtensions?\"JSON\"in window&&\"parse\"in JSON&&\"stringify\"in JSON?function(){if(!(\"Worker\"in window&&\"Blob\"in window&&\"URL\"in window))return!1;var t,e,r=new Blob([\"\"],{type:\"text/javascript\"}),n=URL.createObjectURL(r);try{e=new Worker(n),t=!0}catch(e){t=!1}return e&&e.terminate(),URL.revokeObjectURL(n),t}()?\"Uint8ClampedArray\"in window?ArrayBuffer.isView?function(){var t=document.createElement(\"canvas\");t.width=t.height=1;var e=t.getContext(\"2d\");if(!e)return!1;var r=e.getImageData(0,0,1,1);return r&&r.width===t.width}()?(void 0===n[r=t&&t.failIfMajorPerformanceCaveat]&&(n[r]=function(t){var r=function(t){var r=document.createElement(\"canvas\"),n=Object.create(e.webGLContextAttributes);return n.failIfMajorPerformanceCaveat=t,r.probablySupportsContext?r.probablySupportsContext(\"webgl\",n)||r.probablySupportsContext(\"experimental-webgl\",n):r.supportsContext?r.supportsContext(\"webgl\",n)||r.supportsContext(\"experimental-webgl\",n):r.getContext(\"webgl\",n)||r.getContext(\"experimental-webgl\",n)}(t);if(!r)return!1;var n=r.createShader(r.VERTEX_SHADER);return!(!n||r.isContextLost())&&(r.shaderSource(n,\"void main() {}\"),r.compileShader(n),!0===r.getShaderParameter(n,r.COMPILE_STATUS))}(r)),n[r]?void 0:\"insufficient WebGL support\"):\"insufficient Canvas/getImageData support\":\"insufficient ArrayBuffer support\":\"insufficient Uint8ClampedArray support\":\"insufficient worker support\":\"insufficient JSON support\":\"insufficient Object support\":\"insufficient Function support\":\"insufficent Array support\";var r}t.exports?t.exports=e:window&&(window.mapboxgl=window.mapboxgl||{},window.mapboxgl.supported=e,window.mapboxgl.notSupportedReason=r);var n={};e.webGLContextAttributes={antialias:!1,alpha:!0,stencil:!0,depth:!0}})),r={create:function(e,r,n){var i=t.window.document.createElement(e);return void 0!==r&&(i.className=r),n&&n.appendChild(i),i},createNS:function(e,r){return t.window.document.createElementNS(e,r)}},n=t.window.document.documentElement.style;function i(t){if(!n)return t[0];for(var e=0;e<t.length;e++)if(t[e]in n)return t[e];return t[0]}var a,o=i([\"userSelect\",\"MozUserSelect\",\"WebkitUserSelect\",\"msUserSelect\"]);r.disableDrag=function(){n&&o&&(a=n[o],n[o]=\"none\")},r.enableDrag=function(){n&&o&&(n[o]=a)};var s=i([\"transform\",\"WebkitTransform\"]);r.setTransform=function(t,e){t.style[s]=e};var l=!1;try{var c=Object.defineProperty({},\"passive\",{get:function(){l=!0}});t.window.addEventListener(\"test\",c,c),t.window.removeEventListener(\"test\",c,c)}catch(t){l=!1}r.addEventListener=function(t,e,r,n){void 0===n&&(n={}),t.addEventListener(e,r,\"passive\"in n&&l?n:n.capture)},r.removeEventListener=function(t,e,r,n){void 0===n&&(n={}),t.removeEventListener(e,r,\"passive\"in n&&l?n:n.capture)};var u=function(e){e.preventDefault(),e.stopPropagation(),t.window.removeEventListener(\"click\",u,!0)};function f(t){var e=t.userImage;return!!(e&&e.render&&e.render())&&(t.data.replace(new Uint8Array(e.data.buffer)),!0)}r.suppressClick=function(){t.window.addEventListener(\"click\",u,!0),t.window.setTimeout((function(){t.window.removeEventListener(\"click\",u,!0)}),0)},r.mousePos=function(e,r){var n=e.getBoundingClientRect();return new t.Point(r.clientX-n.left-e.clientLeft,r.clientY-n.top-e.clientTop)},r.touchPos=function(e,r){for(var n=e.getBoundingClientRect(),i=[],a=0;a<r.length;a++)i.push(new t.Point(r[a].clientX-n.left-e.clientLeft,r[a].clientY-n.top-e.clientTop));return i},r.mouseButton=function(e){return void 0!==t.window.InstallTrigger&&2===e.button&&e.ctrlKey&&t.window.navigator.platform.toUpperCase().indexOf(\"MAC\")>=0?0:e.button},r.remove=function(t){t.parentNode&&t.parentNode.removeChild(t)};var h=function(e){function r(){e.call(this),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new t.RGBAImage({width:1,height:1}),this.dirty=!0}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.isLoaded=function(){return this.loaded},r.prototype.setLoaded=function(t){if(this.loaded!==t&&(this.loaded=t,t)){for(var e=0,r=this.requestors;e<r.length;e+=1){var n=r[e];this._notify(n.ids,n.callback)}this.requestors=[]}},r.prototype.getImage=function(t){return this.images[t]},r.prototype.addImage=function(t,e){this._validate(t,e)&&(this.images[t]=e)},r.prototype._validate=function(e,r){var n=!0;return this._validateStretch(r.stretchX,r.data&&r.data.width)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchX\" value'))),n=!1),this._validateStretch(r.stretchY,r.data&&r.data.height)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchY\" value'))),n=!1),this._validateContent(r.content,r)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"content\" value'))),n=!1),n},r.prototype._validateStretch=function(t,e){if(!t)return!0;for(var r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];if(a[0]<r||a[1]<a[0]||e<a[1])return!1;r=a[1]}return!0},r.prototype._validateContent=function(t,e){return!(t&&(4!==t.length||t[0]<0||e.data.width<t[0]||t[1]<0||e.data.height<t[1]||t[2]<0||e.data.width<t[2]||t[3]<0||e.data.height<t[3]||t[2]<t[0]||t[3]<t[1]))},r.prototype.updateImage=function(t,e){e.version=this.images[t].version+1,this.images[t]=e,this.updatedImages[t]=!0},r.prototype.removeImage=function(t){var e=this.images[t];delete this.images[t],delete this.patterns[t],e.userImage&&e.userImage.onRemove&&e.userImage.onRemove()},r.prototype.listImages=function(){return Object.keys(this.images)},r.prototype.getImages=function(t,e){var r=!0;if(!this.isLoaded())for(var n=0,i=t;n<i.length;n+=1)this.images[i[n]]||(r=!1);this.isLoaded()||r?this._notify(t,e):this.requestors.push({ids:t,callback:e})},r.prototype._notify=function(e,r){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i];this.images[o]||this.fire(new t.Event(\"styleimagemissing\",{id:o}));var s=this.images[o];s?n[o]={data:s.data.clone(),pixelRatio:s.pixelRatio,sdf:s.sdf,version:s.version,stretchX:s.stretchX,stretchY:s.stretchY,content:s.content,hasRenderCallback:Boolean(s.userImage&&s.userImage.render)}:t.warnOnce('Image \"'+o+'\" could not be loaded. Please make sure you have added the image with map.addImage() or a \"sprite\" property in your style. 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o.resize({width:i||1,height:a||1}),this.patterns){var l=this.patterns[s].bin,c=l.x+1,u=l.y+1,f=this.images[s].data,h=f.width,p=f.height;t.RGBAImage.copy(f,o,{x:0,y:0},{x:c,y:u},{width:h,height:p}),t.RGBAImage.copy(f,o,{x:0,y:p-1},{x:c,y:u-1},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:c,y:u+p},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:h-1,y:0},{x:c-1,y:u},{width:1,height:p}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:c+h,y:u},{width:1,height:p})}this.dirty=!0},r.prototype.beginFrame=function(){this.callbackDispatchedThisFrame={}},r.prototype.dispatchRenderCallbacks=function(t){for(var e=0,r=t;e<r.length;e+=1){var n=r[e];if(!this.callbackDispatchedThisFrame[n]){this.callbackDispatchedThisFrame[n]=!0;var i=this.images[n];f(i)&&this.updateImage(n,i)}}},r}(t.Evented),p=m,d=m,g=1e20;function m(t,e,r,n,i,a){this.fontSize=t||24,this.buffer=void 0===e?3:e,this.cutoff=n||.25,this.fontFamily=i||\"sans-serif\",this.fontWeight=a||\"normal\",this.radius=r||8;var o=this.size=this.fontSize+2*this.buffer;this.canvas=document.createElement(\"canvas\"),this.canvas.width=this.canvas.height=o,this.ctx=this.canvas.getContext(\"2d\"),this.ctx.font=this.fontWeight+\" \"+this.fontSize+\"px \"+this.fontFamily,this.ctx.textBaseline=\"middle\",this.ctx.fillStyle=\"black\",this.gridOuter=new Float64Array(o*o),this.gridInner=new Float64Array(o*o),this.f=new Float64Array(o),this.d=new Float64Array(o),this.z=new Float64Array(o+1),this.v=new Int16Array(o),this.middle=Math.round(o/2*(navigator.userAgent.indexOf(\"Gecko/\")>=0?1.2:1))}function v(t,e,r,n,i,a,o){for(var s=0;s<e;s++){for(var l=0;l<r;l++)n[l]=t[l*e+s];for(y(n,i,a,o,r),l=0;l<r;l++)t[l*e+s]=i[l]}for(l=0;l<r;l++){for(s=0;s<e;s++)n[s]=t[l*e+s];for(y(n,i,a,o,e),s=0;s<e;s++)t[l*e+s]=Math.sqrt(i[s])}}function y(t,e,r,n,i){r[0]=0,n[0]=-g,n[1]=+g;for(var a=1,o=0;a<i;a++){for(var s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);s<=n[o];)o--,s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);r[++o]=a,n[o]=s,n[o+1]=+g}for(a=0,o=0;a<i;a++){for(;n[o+1]<a;)o++;e[a]=(a-r[o])*(a-r[o])+t[r[o]]}}m.prototype.draw=function(t){this.ctx.clearRect(0,0,this.size,this.size),this.ctx.fillText(t,this.buffer,this.middle);for(var e=this.ctx.getImageData(0,0,this.size,this.size),r=new Uint8ClampedArray(this.size*this.size),n=0;n<this.size*this.size;n++){var i=e.data[4*n+3]/255;this.gridOuter[n]=1===i?0:0===i?g:Math.pow(Math.max(0,.5-i),2),this.gridInner[n]=1===i?g:0===i?0:Math.pow(Math.max(0,i-.5),2)}for(v(this.gridOuter,this.size,this.size,this.f,this.d,this.v,this.z),v(this.gridInner,this.size,this.size,this.f,this.d,this.v,this.z),n=0;n<this.size*this.size;n++)r[n]=Math.max(0,Math.min(255,Math.round(255-255*((this.gridOuter[n]-this.gridInner[n])/this.radius+this.cutoff))));return r},p.default=d;var x=function(t,e){this.requestManager=t,this.localIdeographFontFamily=e,this.entries={}};x.prototype.setURL=function(t){this.url=t},x.prototype.getGlyphs=function(e,r){var n=this,i=[];for(var a in e)for(var o=0,s=e[a];o<s.length;o+=1)i.push({stack:a,id:s[o]});t.asyncAll(i,(function(t,e){var r=t.stack,i=t.id,a=n.entries[r];a||(a=n.entries[r]={glyphs:{},requests:{},ranges:{}});var o=a.glyphs[i];if(void 0===o){if(o=n._tinySDF(a,r,i))return a.glyphs[i]=o,void e(null,{stack:r,id:i,glyph:o});var s=Math.floor(i/256);if(256*s>65535)e(new Error(\"glyphs > 65535 not supported\"));else if(a.ranges[s])e(null,{stack:r,id:i,glyph:o});else{var l=a.requests[s];l||(l=a.requests[s]=[],x.loadGlyphRange(r,s,n.url,n.requestManager,(function(t,e){if(e){for(var r in e)n._doesCharSupportLocalGlyph(+r)||(a.glyphs[+r]=e[+r]);a.ranges[s]=!0}for(var i=0,o=l;i<o.length;i+=1)(0,o[i])(t,e);delete a.requests[s]}))),l.push((function(t,n){t?e(t):n&&e(null,{stack:r,id:i,glyph:n[i]||null})}))}}else e(null,{stack:r,id:i,glyph:o})}),(function(t,e){if(t)r(t);else if(e){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.stack,l=o.id,c=o.glyph;(n[s]||(n[s]={}))[l]=c&&{id:c.id,bitmap:c.bitmap.clone(),metrics:c.metrics}}r(null,n)}}))},x.prototype._doesCharSupportLocalGlyph=function(e){return!!this.localIdeographFontFamily&&(t.isChar[\"CJK Unified Ideographs\"](e)||t.isChar[\"Hangul Syllables\"](e)||t.isChar.Hiragana(e)||t.isChar.Katakana(e))},x.prototype._tinySDF=function(e,r,n){var i=this.localIdeographFontFamily;if(i&&this._doesCharSupportLocalGlyph(n)){var a=e.tinySDF;if(!a){var o=\"400\";/bold/i.test(r)?o=\"900\":/medium/i.test(r)?o=\"500\":/light/i.test(r)&&(o=\"200\"),a=e.tinySDF=new x.TinySDF(24,3,8,.25,i,o)}return{id:n,bitmap:new t.AlphaImage({width:30,height:30},a.draw(String.fromCharCode(n))),metrics:{width:24,height:24,left:0,top:-8,advance:24}}}},x.loadGlyphRange=function(e,r,n,i,a){var o=256*r,s=o+255,l=i.transformRequest(i.normalizeGlyphsURL(n).replace(\"{fontstack}\",e).replace(\"{range}\",o+\"-\"+s),t.ResourceType.Glyphs);t.getArrayBuffer(l,(function(e,r){if(e)a(e);else if(r){for(var n={},i=0,o=t.parseGlyphPBF(r);i<o.length;i+=1){var s=o[i];n[s.id]=s}a(null,n)}}))},x.TinySDF=p;var b=function(){this.specification=t.styleSpec.light.position};b.prototype.possiblyEvaluate=function(e,r){return t.sphericalToCartesian(e.expression.evaluate(r))},b.prototype.interpolate=function(e,r,n){return{x:t.number(e.x,r.x,n),y:t.number(e.y,r.y,n),z:t.number(e.z,r.z,n)}};var _=new t.Properties({anchor:new t.DataConstantProperty(t.styleSpec.light.anchor),position:new b,color:new t.DataConstantProperty(t.styleSpec.light.color),intensity:new t.DataConstantProperty(t.styleSpec.light.intensity)}),w=function(e){function r(r){e.call(this),this._transitionable=new t.Transitionable(_),this.setLight(r),this._transitioning=this._transitionable.untransitioned()}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.getLight=function(){return this._transitionable.serialize()},r.prototype.setLight=function(e,r){if(void 0===r&&(r={}),!this._validate(t.validateLight,e,r))for(var n in e){var i=e[n];t.endsWith(n,\"-transition\")?this._transitionable.setTransition(n.slice(0,-\"-transition\".length),i):this._transitionable.setValue(n,i)}},r.prototype.updateTransitions=function(t){this._transitioning=this._transitionable.transitioned(t,this._transitioning)},r.prototype.hasTransition=function(){return this._transitioning.hasTransition()},r.prototype.recalculate=function(t){this.properties=this._transitioning.possiblyEvaluate(t)},r.prototype._validate=function(e,r,n){return(!n||!1!==n.validate)&&t.emitValidationErrors(this,e.call(t.validateStyle,t.extend({value:r,style:{glyphs:!0,sprite:!0},styleSpec:t.styleSpec})))},r}(t.Evented),T=function(t,e){this.width=t,this.height=e,this.nextRow=0,this.data=new Uint8Array(this.width*this.height),this.dashEntry={}};T.prototype.getDash=function(t,e){var r=t.join(\",\")+String(e);return this.dashEntry[r]||(this.dashEntry[r]=this.addDash(t,e)),this.dashEntry[r]},T.prototype.getDashRanges=function(t,e,r){var n=[],i=t.length%2==1?-t[t.length-1]*r:0,a=t[0]*r,o=!0;n.push({left:i,right:a,isDash:o,zeroLength:0===t[0]});for(var s=t[0],l=1;l<t.length;l++){var c=t[l];n.push({left:i=s*r,right:a=(s+=c)*r,isDash:o=!o,zeroLength:0===c})}return n},T.prototype.addRoundDash=function(t,e,r){for(var n=e/2,i=-r;i<=r;i++)for(var a=this.width*(this.nextRow+r+i),o=0,s=t[o],l=0;l<this.width;l++){l/s.right>1&&(s=t[++o]);var c=Math.abs(l-s.left),u=Math.abs(l-s.right),f=Math.min(c,u),h=void 0,p=i/r*(n+1);if(s.isDash){var d=n-Math.abs(p);h=Math.sqrt(f*f+d*d)}else h=n-Math.sqrt(f*f+p*p);this.data[a+l]=Math.max(0,Math.min(255,h+128))}},T.prototype.addRegularDash=function(t){for(var e=t.length-1;e>=0;--e){var r=t[e],n=t[e+1];r.zeroLength?t.splice(e,1):n&&n.isDash===r.isDash&&(n.left=r.left,t.splice(e,1))}var i=t[0],a=t[t.length-1];i.isDash===a.isDash&&(i.left=a.left-this.width,a.right=i.right+this.width);for(var o=this.width*this.nextRow,s=0,l=t[s],c=0;c<this.width;c++){c/l.right>1&&(l=t[++s]);var u=Math.abs(c-l.left),f=Math.abs(c-l.right),h=Math.min(u,f);this.data[o+c]=Math.max(0,Math.min(255,(l.isDash?h:-h)+128))}},T.prototype.addDash=function(e,r){var n=r?7:0,i=2*n+1;if(this.nextRow+i>this.height)return t.warnOnce(\"LineAtlas out of space\"),null;for(var a=0,o=0;o<e.length;o++)a+=e[o];if(0!==a){var s=this.width/a,l=this.getDashRanges(e,this.width,s);r?this.addRoundDash(l,s,n):this.addRegularDash(l)}var c={y:(this.nextRow+n+.5)/this.height,height:2*n/this.height,width:a};return this.nextRow+=i,this.dirty=!0,c},T.prototype.bind=function(t){var e=t.gl;this.texture?(e.bindTexture(e.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,e.texSubImage2D(e.TEXTURE_2D,0,0,0,this.width,this.height,e.ALPHA,e.UNSIGNED_BYTE,this.data))):(this.texture=e.createTexture(),e.bindTexture(e.TEXTURE_2D,this.texture),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_S,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_T,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,e.LINEAR),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,e.LINEAR),e.texImage2D(e.TEXTURE_2D,0,e.ALPHA,this.width,this.height,0,e.ALPHA,e.UNSIGNED_BYTE,this.data))};var k=function e(r,n){this.workerPool=r,this.actors=[],this.currentActor=0,this.id=t.uniqueId();for(var i=this.workerPool.acquire(this.id),a=0;a<i.length;a++){var o=new e.Actor(i[a],n,this.id);o.name=\"Worker \"+a,this.actors.push(o)}};function M(e,r,n){var i=function(i,a){if(i)return n(i);if(a){var o=t.pick(t.extend(a,e),[\"tiles\",\"minzoom\",\"maxzoom\",\"attribution\",\"mapbox_logo\",\"bounds\",\"scheme\",\"tileSize\",\"encoding\"]);a.vector_layers&&(o.vectorLayers=a.vector_layers,o.vectorLayerIds=o.vectorLayers.map((function(t){return t.id}))),o.tiles=r.canonicalizeTileset(o,e.url),n(null,o)}};return e.url?t.getJSON(r.transformRequest(r.normalizeSourceURL(e.url),t.ResourceType.Source),i):t.browser.frame((function(){return i(null,e)}))}k.prototype.broadcast=function(e,r,n){t.asyncAll(this.actors,(function(t,n){t.send(e,r,n)}),n=n||function(){})},k.prototype.getActor=function(){return this.currentActor=(this.currentActor+1)%this.actors.length,this.actors[this.currentActor]},k.prototype.remove=function(){this.actors.forEach((function(t){t.remove()})),this.actors=[],this.workerPool.release(this.id)},k.Actor=t.Actor;var A=function(e,r,n){this.bounds=t.LngLatBounds.convert(this.validateBounds(e)),this.minzoom=r||0,this.maxzoom=n||24};A.prototype.validateBounds=function(t){return Array.isArray(t)&&4===t.length?[Math.max(-180,t[0]),Math.max(-90,t[1]),Math.min(180,t[2]),Math.min(90,t[3])]:[-180,-90,180,90]},A.prototype.contains=function(e){var r=Math.pow(2,e.z),n=Math.floor(t.mercatorXfromLng(this.bounds.getWest())*r),i=Math.floor(t.mercatorYfromLat(this.bounds.getNorth())*r),a=Math.ceil(t.mercatorXfromLng(this.bounds.getEast())*r),o=Math.ceil(t.mercatorYfromLat(this.bounds.getSouth())*r);return e.x>=n&&e.x<a&&e.y>=i&&e.y<o};var S=function(e){function r(r,n,i,a){if(e.call(this),this.id=r,this.dispatcher=i,this.type=\"vector\",this.minzoom=0,this.maxzoom=22,this.scheme=\"xyz\",this.tileSize=512,this.reparseOverscaled=!0,this.isTileClipped=!0,this._loaded=!1,t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\",\"promoteId\"])),this._options=t.extend({type:\"vector\"},n),this._collectResourceTiming=n.collectResourceTiming,512!==this.tileSize)throw new Error(\"vector tile sources must have a tileSize of 512\");this.setEventedParent(a)}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=M(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new A(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles,e.map._requestManager._customAccessToken),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken,e.map._requestManager._customAccessToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme)),i={request:this.map._requestManager.transformRequest(n,t.ResourceType.Tile),uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,tileSize:this.tileSize*e.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};function a(n,i){return delete e.request,e.aborted?r(null):n&&404!==n.status?r(n):(i&&i.resourceTiming&&(e.resourceTiming=i.resourceTiming),this.map._refreshExpiredTiles&&i&&e.setExpiryData(i),e.loadVectorData(i,this.map.painter),t.cacheEntryPossiblyAdded(this.dispatcher),r(null),void(e.reloadCallback&&(this.loadTile(e,e.reloadCallback),e.reloadCallback=null)))}i.request.collectResourceTiming=this._collectResourceTiming,e.actor&&\"expired\"!==e.state?\"loading\"===e.state?e.reloadCallback=r:e.request=e.actor.send(\"reloadTile\",i,a.bind(this)):(e.actor=this.dispatcher.getActor(),e.request=e.actor.send(\"loadTile\",i,a.bind(this)))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.actor&&t.actor.send(\"abortTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.unloadTile=function(t){t.unloadVectorData(),t.actor&&t.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.hasTransition=function(){return!1},r}(t.Evented),E=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.dispatcher=i,this.setEventedParent(a),this.type=\"raster\",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme=\"xyz\",this.tileSize=512,this._loaded=!1,this._options=t.extend({type:\"raster\"},n),t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\"]))}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=M(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new A(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.loadTile=function(e,r){var n=this,i=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);e.request=t.getImage(this.map._requestManager.transformRequest(i,t.ResourceType.Tile),(function(i,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(i)e.state=\"errored\",r(i);else if(a){n.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=n.map.painter.context,s=o.gl;e.texture=n.map.painter.getTileTexture(a.width),e.texture?e.texture.update(a,{useMipmap:!0}):(e.texture=new t.Texture(o,a,s.RGBA,{useMipmap:!0}),e.texture.bind(s.LINEAR,s.CLAMP_TO_EDGE,s.LINEAR_MIPMAP_NEAREST),o.extTextureFilterAnisotropic&&s.texParameterf(s.TEXTURE_2D,o.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,o.extTextureFilterAnisotropicMax)),e.state=\"loaded\",t.cacheEntryPossiblyAdded(n.dispatcher),r(null)}}))},r.prototype.abortTile=function(t,e){t.request&&(t.request.cancel(),delete t.request),e()},r.prototype.unloadTile=function(t,e){t.texture&&this.map.painter.saveTileTexture(t.texture),e()},r.prototype.hasTransition=function(){return!1},r}(t.Evented),C=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),this.type=\"raster-dem\",this.maxzoom=22,this._options=t.extend({type:\"raster-dem\"},n),this.encoding=n.encoding||\"mapbox\"}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.serialize=function(){return{type:\"raster-dem\",url:this.url,tileSize:this.tileSize,tiles:this.tiles,bounds:this.bounds,encoding:this.encoding}},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);function i(t,n){t&&(e.state=\"errored\",r(t)),n&&(e.dem=n,e.needsHillshadePrepare=!0,e.state=\"loaded\",r(null))}e.request=t.getImage(this.map._requestManager.transformRequest(n,t.ResourceType.Tile),function(n,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(n)e.state=\"errored\",r(n);else if(a){this.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=t.window.ImageBitmap&&a instanceof t.window.ImageBitmap&&t.offscreenCanvasSupported()?a:t.browser.getImageData(a,1),s={uid:e.uid,coord:e.tileID,source:this.id,rawImageData:o,encoding:this.encoding};e.actor&&\"expired\"!==e.state||(e.actor=this.dispatcher.getActor(),e.actor.send(\"loadDEMTile\",s,i.bind(this)))}}.bind(this)),e.neighboringTiles=this._getNeighboringTiles(e.tileID)},r.prototype._getNeighboringTiles=function(e){var r=e.canonical,n=Math.pow(2,r.z),i=(r.x-1+n)%n,a=0===r.x?e.wrap-1:e.wrap,o=(r.x+1+n)%n,s=r.x+1===n?e.wrap+1:e.wrap,l={};return l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y).key]={backfilled:!1},r.y>0&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+1<n&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y+1).key]={backfilled:!1}),l},r.prototype.unloadTile=function(t){t.demTexture&&this.map.painter.saveTileTexture(t.demTexture),t.fbo&&(t.fbo.destroy(),delete t.fbo),t.dem&&delete t.dem,delete t.neighboringTiles,t.state=\"unloaded\",t.actor&&t.actor.send(\"removeDEMTile\",{uid:t.uid,source:this.id})},r}(E),L=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.type=\"geojson\",this.minzoom=0,this.maxzoom=18,this.tileSize=512,this.isTileClipped=!0,this.reparseOverscaled=!0,this._removed=!1,this._loaded=!1,this.actor=i.getActor(),this.setEventedParent(a),this._data=n.data,this._options=t.extend({},n),this._collectResourceTiming=n.collectResourceTiming,this._resourceTiming=[],void 0!==n.maxzoom&&(this.maxzoom=n.maxzoom),n.type&&(this.type=n.type),n.attribution&&(this.attribution=n.attribution),this.promoteId=n.promoteId;var o=t.EXTENT/this.tileSize;this.workerOptions=t.extend({source:this.id,cluster:n.cluster||!1,geojsonVtOptions:{buffer:(void 0!==n.buffer?n.buffer:128)*o,tolerance:(void 0!==n.tolerance?n.tolerance:.375)*o,extent:t.EXTENT,maxZoom:this.maxzoom,lineMetrics:n.lineMetrics||!1,generateId:n.generateId||!1},superclusterOptions:{maxZoom:void 0!==n.clusterMaxZoom?Math.min(n.clusterMaxZoom,this.maxzoom-1):this.maxzoom-1,extent:t.EXTENT,radius:(n.clusterRadius||50)*o,log:!1,generateId:n.generateId||!1},clusterProperties:n.clusterProperties},n.workerOptions)}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.load=function(){var e=this;this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(r){if(r)e.fire(new t.ErrorEvent(r));else{var n={dataType:\"source\",sourceDataType:\"metadata\"};e._collectResourceTiming&&e._resourceTiming&&e._resourceTiming.length>0&&(n.resourceTiming=e._resourceTiming,e._resourceTiming=[]),e.fire(new t.Event(\"data\",n))}}))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setData=function(e){var r=this;return this._data=e,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(e){if(e)r.fire(new t.ErrorEvent(e));else{var n={dataType:\"source\",sourceDataType:\"content\"};r._collectResourceTiming&&r._resourceTiming&&r._resourceTiming.length>0&&(n.resourceTiming=r._resourceTiming,r._resourceTiming=[]),r.fire(new t.Event(\"data\",n))}})),this},r.prototype.getClusterExpansionZoom=function(t,e){return this.actor.send(\"geojson.getClusterExpansionZoom\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterChildren=function(t,e){return this.actor.send(\"geojson.getClusterChildren\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterLeaves=function(t,e,r,n){return this.actor.send(\"geojson.getClusterLeaves\",{source:this.id,clusterId:t,limit:e,offset:r},n),this},r.prototype._updateWorkerData=function(e){var r=this;this._loaded=!1;var n=t.extend({},this.workerOptions),i=this._data;\"string\"==typeof i?(n.request=this.map._requestManager.transformRequest(t.browser.resolveURL(i),t.ResourceType.Source),n.request.collectResourceTiming=this._collectResourceTiming):n.data=JSON.stringify(i),this.actor.send(this.type+\".loadData\",n,(function(t,i){r._removed||i&&i.abandoned||(r._loaded=!0,i&&i.resourceTiming&&i.resourceTiming[r.id]&&(r._resourceTiming=i.resourceTiming[r.id].slice(0)),r.actor.send(r.type+\".coalesce\",{source:n.source},null),e(t))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.loadTile=function(e,r){var n=this,i=e.actor?\"reloadTile\":\"loadTile\";e.actor=this.actor,e.request=this.actor.send(i,{type:this.type,uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId},(function(t,a){return delete e.request,e.unloadVectorData(),e.aborted?r(null):t?r(t):(e.loadVectorData(a,n.map.painter,\"reloadTile\"===i),r(null))}))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.aborted=!0},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id})},r.prototype.onRemove=function(){this._removed=!0,this.actor.send(\"removeSource\",{type:this.type,source:this.id})},r.prototype.serialize=function(){return t.extend({},this._options,{type:this.type,data:this._data})},r.prototype.hasTransition=function(){return!1},r}(t.Evented),I=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]),P=function(e){function r(t,r,n,i){e.call(this),this.id=t,this.dispatcher=n,this.coordinates=r.coordinates,this.type=\"image\",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(i),this.options=r}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.load=function(e,r){var n=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this.url=this.options.url,t.getImage(this.map._requestManager.transformRequest(this.url,t.ResourceType.Image),(function(i,a){n._loaded=!0,i?n.fire(new t.ErrorEvent(i)):a&&(n.image=a,e&&(n.coordinates=e),r&&r(),n._finishLoading())}))},r.prototype.loaded=function(){return this._loaded},r.prototype.updateImage=function(t){var e=this;return this.image&&t.url?(this.options.url=t.url,this.load(t.coordinates,(function(){e.texture=null})),this):this},r.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setCoordinates=function(e){var r=this;this.coordinates=e;var n=e.map(t.MercatorCoordinate.fromLngLat);this.tileID=function(e){for(var r=1/0,n=1/0,i=-1/0,a=-1/0,o=0,s=e;o<s.length;o+=1){var l=s[o];r=Math.min(r,l.x),n=Math.min(n,l.y),i=Math.max(i,l.x),a=Math.max(a,l.y)}var c=Math.max(i-r,a-n),u=Math.max(0,Math.floor(-Math.log(c)/Math.LN2)),f=Math.pow(2,u);return new t.CanonicalTileID(u,Math.floor((r+i)/2*f),Math.floor((n+a)/2*f))}(n),this.minzoom=this.maxzoom=this.tileID.z;var i=n.map((function(t){return r.tileID.getTilePoint(t)._round()}));return this._boundsArray=new t.StructArrayLayout4i8,this._boundsArray.emplaceBack(i[0].x,i[0].y,0,0),this._boundsArray.emplaceBack(i[1].x,i[1].y,t.EXTENT,0),this._boundsArray.emplaceBack(i[3].x,i[3].y,0,t.EXTENT),this._boundsArray.emplaceBack(i[2].x,i[2].y,t.EXTENT,t.EXTENT),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})),this},r.prototype.prepare=function(){if(0!==Object.keys(this.tiles).length&&this.image){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,I.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture||(this.texture=new t.Texture(e,this.image,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.loadTile=function(t,e){this.tileID&&this.tileID.equals(t.tileID.canonical)?(this.tiles[String(t.tileID.wrap)]=t,t.buckets={},e(null)):(t.state=\"errored\",e(null))},r.prototype.serialize=function(){return{type:\"image\",url:this.options.url,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return!1},r}(t.Evented),z=function(e){function r(t,r,n,i){e.call(this,t,r,n,i),this.roundZoom=!0,this.type=\"video\",this.options=r}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1;var r=this.options;this.urls=[];for(var n=0,i=r.urls;n<i.length;n+=1)this.urls.push(this.map._requestManager.transformRequest(i[n],t.ResourceType.Source).url);t.getVideo(this.urls,(function(r,n){e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(e.video=n,e.video.loop=!0,e.video.addEventListener(\"playing\",(function(){e.map.triggerRepaint()})),e.map&&e.video.play(),e._finishLoading())}))},r.prototype.pause=function(){this.video&&this.video.pause()},r.prototype.play=function(){this.video&&this.video.play()},r.prototype.seek=function(e){if(this.video){var r=this.video.seekable;e<r.start(0)||e>r.end(0)?this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+this.id,null,\"Playback for this video can be set only between the \"+r.start(0)+\" and \"+r.end(0)+\"-second mark.\"))):this.video.currentTime=e}},r.prototype.getVideo=function(){return this.video},r.prototype.onAdd=function(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},r.prototype.prepare=function(){if(!(0===Object.keys(this.tiles).length||this.video.readyState<2)){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,I.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.video)):(this.texture=new t.Texture(e,this.video,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this.video&&!this.video.paused},r}(P),O=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),n.coordinates?Array.isArray(n.coordinates)&&4===n.coordinates.length&&!n.coordinates.some((function(t){return!Array.isArray(t)||2!==t.length||t.some((function(t){return\"number\"!=typeof t}))}))||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"coordinates\" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"coordinates\"'))),n.animate&&\"boolean\"!=typeof n.animate&&this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'optional \"animate\" property must be a boolean value'))),n.canvas?\"string\"==typeof n.canvas||n.canvas instanceof t.window.HTMLCanvasElement||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"canvas\" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"canvas\"'))),this.options=n,this.animate=void 0===n.animate||n.animate}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.load=function(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof t.window.HTMLCanvasElement?this.options.canvas:t.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.ErrorEvent(new Error(\"Canvas dimensions cannot be less than or equal to zero.\"))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())},r.prototype.getCanvas=function(){return this.canvas},r.prototype.onAdd=function(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()},r.prototype.onRemove=function(){this.pause()},r.prototype.prepare=function(){var e=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,e=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,e=!0),!this._hasInvalidDimensions()&&0!==Object.keys(this.tiles).length){var r=this.map.painter.context,n=r.gl;for(var i in this.boundsBuffer||(this.boundsBuffer=r.createVertexBuffer(this._boundsArray,I.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(e||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new t.Texture(r,this.canvas,n.RGBA,{premultiply:!0}),this.tiles){var a=this.tiles[i];\"loaded\"!==a.state&&(a.state=\"loaded\",a.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"canvas\",coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this._playing},r.prototype._hasInvalidDimensions=function(){for(var t=0,e=[this.canvas.width,this.canvas.height];t<e.length;t+=1){var r=e[t];if(isNaN(r)||r<=0)return!0}return!1},r}(P),D={vector:S,raster:E,\"raster-dem\":C,geojson:L,video:z,image:P,canvas:O};function R(e,r){var n=t.identity([]);return t.translate(n,n,[1,1,0]),t.scale(n,n,[.5*e.width,.5*e.height,1]),t.multiply(n,n,e.calculatePosMatrix(r.toUnwrapped()))}function F(t,e,r,n,i,a){var o=function(t,e,r){if(t)for(var n=0,i=t;n<i.length;n+=1){var a=e[i[n]];if(a&&a.source===r&&\"fill-extrusion\"===a.type)return!0}else for(var o in e){var s=e[o];if(s.source===r&&\"fill-extrusion\"===s.type)return!0}return!1}(i&&i.layers,e,t.id),s=a.maxPitchScaleFactor(),l=t.tilesIn(n,s,o);l.sort(B);for(var c=[],u=0,f=l;u<f.length;u+=1){var h=f[u];c.push({wrappedTileID:h.tileID.wrapped().key,queryResults:h.tile.queryRenderedFeatures(e,r,t._state,h.queryGeometry,h.cameraQueryGeometry,h.scale,i,a,s,R(t.transform,h.tileID))})}var p=function(t){for(var e={},r={},n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.queryResults,s=a.wrappedTileID,l=r[s]=r[s]||{};for(var c in o)for(var u=o[c],f=l[c]=l[c]||{},h=e[c]=e[c]||[],p=0,d=u;p<d.length;p+=1){var g=d[p];f[g.featureIndex]||(f[g.featureIndex]=!0,h.push(g))}}return e}(c);for(var d in p)p[d].forEach((function(e){var r=e.feature,n=t.getFeatureState(r.layer[\"source-layer\"],r.id);r.source=r.layer.source,r.layer[\"source-layer\"]&&(r.sourceLayer=r.layer[\"source-layer\"]),r.state=n}));return p}function B(t,e){var r=t.tileID,n=e.tileID;return r.overscaledZ-n.overscaledZ||r.canonical.y-n.canonical.y||r.wrap-n.wrap||r.canonical.x-n.canonical.x}var N=function(t,e){this.max=t,this.onRemove=e,this.reset()};N.prototype.reset=function(){for(var t in this.data)for(var e=0,r=this.data[t];e<r.length;e+=1){var n=r[e];n.timeout&&clearTimeout(n.timeout),this.onRemove(n.value)}return this.data={},this.order=[],this},N.prototype.add=function(t,e,r){var n=this,i=t.wrapped().key;void 0===this.data[i]&&(this.data[i]=[]);var a={value:e,timeout:void 0};if(void 0!==r&&(a.timeout=setTimeout((function(){n.remove(t,a)}),r)),this.data[i].push(a),this.order.push(i),this.order.length>this.max){var o=this._getAndRemoveByKey(this.order[0]);o&&this.onRemove(o)}return this},N.prototype.has=function(t){return t.wrapped().key in this.data},N.prototype.getAndRemove=function(t){return this.has(t)?this._getAndRemoveByKey(t.wrapped().key):null},N.prototype._getAndRemoveByKey=function(t){var e=this.data[t].shift();return e.timeout&&clearTimeout(e.timeout),0===this.data[t].length&&delete this.data[t],this.order.splice(this.order.indexOf(t),1),e.value},N.prototype.getByKey=function(t){var e=this.data[t];return e?e[0].value:null},N.prototype.get=function(t){return this.has(t)?this.data[t.wrapped().key][0].value:null},N.prototype.remove=function(t,e){if(!this.has(t))return this;var r=t.wrapped().key,n=void 0===e?0:this.data[r].indexOf(e),i=this.data[r][n];return this.data[r].splice(n,1),i.timeout&&clearTimeout(i.timeout),0===this.data[r].length&&delete this.data[r],this.onRemove(i.value),this.order.splice(this.order.indexOf(r),1),this},N.prototype.setMaxSize=function(t){for(this.max=t;this.order.length>this.max;){var e=this._getAndRemoveByKey(this.order[0]);e&&this.onRemove(e)}return this},N.prototype.filter=function(t){var e=[];for(var r in this.data)for(var n=0,i=this.data[r];n<i.length;n+=1){var a=i[n];t(a.value)||e.push(a)}for(var o=0,s=e;o<s.length;o+=1){var l=s[o];this.remove(l.value.tileID,l)}};var j=function(t,e,r){this.context=t;var n=t.gl;this.buffer=n.createBuffer(),this.dynamicDraw=Boolean(r),this.context.unbindVAO(),t.bindElementBuffer.set(this.buffer),n.bufferData(n.ELEMENT_ARRAY_BUFFER,e.arrayBuffer,this.dynamicDraw?n.DYNAMIC_DRAW:n.STATIC_DRAW),this.dynamicDraw||delete e.arrayBuffer};j.prototype.bind=function(){this.context.bindElementBuffer.set(this.buffer)},j.prototype.updateData=function(t){var e=this.context.gl;this.context.unbindVAO(),this.bind(),e.bufferSubData(e.ELEMENT_ARRAY_BUFFER,0,t.arrayBuffer)},j.prototype.destroy=function(){this.buffer&&(this.context.gl.deleteBuffer(this.buffer),delete this.buffer)};var U={Int8:\"BYTE\",Uint8:\"UNSIGNED_BYTE\",Int16:\"SHORT\",Uint16:\"UNSIGNED_SHORT\",Int32:\"INT\",Uint32:\"UNSIGNED_INT\",Float32:\"FLOAT\"},V=function(t,e,r,n){this.length=e.length,this.attributes=r,this.itemSize=e.bytesPerElement,this.dynamicDraw=n,this.context=t;var i=t.gl;this.buffer=i.createBuffer(),t.bindVertexBuffer.set(this.buffer),i.bufferData(i.ARRAY_BUFFER,e.arrayBuffer,this.dynamicDraw?i.DYNAMIC_DRAW:i.STATIC_DRAW),this.dynamicDraw||delete e.arrayBuffer};V.prototype.bind=function(){this.context.bindVertexBuffer.set(this.buffer)},V.prototype.updateData=function(t){var e=this.context.gl;this.bind(),e.bufferSubData(e.ARRAY_BUFFER,0,t.arrayBuffer)},V.prototype.enableAttributes=function(t,e){for(var r=0;r<this.attributes.length;r++){var n=e.attributes[this.attributes[r].name];void 0!==n&&t.enableVertexAttribArray(n)}},V.prototype.setVertexAttribPointers=function(t,e,r){for(var n=0;n<this.attributes.length;n++){var i=this.attributes[n],a=e.attributes[i.name];void 0!==a&&t.vertexAttribPointer(a,i.components,t[U[i.type]],!1,this.itemSize,i.offset+this.itemSize*(r||0))}},V.prototype.destroy=function(){this.buffer&&(this.context.gl.deleteBuffer(this.buffer),delete this.buffer)};var q=function(t){this.gl=t.gl,this.default=this.getDefault(),this.current=this.default,this.dirty=!1};q.prototype.get=function(){return this.current},q.prototype.set=function(t){},q.prototype.getDefault=function(){return this.default},q.prototype.setDefault=function(){this.set(this.default)};var H=function(e){function r(){e.apply(this,arguments)}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.getDefault=function(){return t.Color.transparent},r.prototype.set=function(t){var 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e=this.gl;e.bindFramebuffer(e.FRAMEBUFFER,t),this.current=t,this.dirty=!1}},e}(q),pt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.bindRenderbuffer(e.RENDERBUFFER,t),this.current=t,this.dirty=!1}},e}(q),dt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.bindTexture(e.TEXTURE_2D,t),this.current=t,this.dirty=!1}},e}(q),gt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){if(t!==this.current||this.dirty){var 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e=this.gl;e.pixelStorei(e.UNPACK_ALIGNMENT,t),this.current=t,this.dirty=!1}},e}(q),xt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.getDefault=function(){return!1},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.pixelStorei(e.UNPACK_PREMULTIPLY_ALPHA_WEBGL,t),this.current=t,this.dirty=!1}},e}(q),bt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.getDefault=function(){return!1},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.pixelStorei(e.UNPACK_FLIP_Y_WEBGL,t),this.current=t,this.dirty=!1}},e}(q),_t=function(t){function e(e,r){t.call(this,e),this.context=e,this.parent=r}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.getDefault=function(){return null},e}(q),wt=function(t){function 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t=this.context.gl,e=this.colorAttachment.get();if(e&&t.deleteTexture(e),this.depthAttachment){var r=this.depthAttachment.get();r&&t.deleteRenderbuffer(r)}t.deleteFramebuffer(this.framebuffer)};var Mt=function(t,e,r){this.func=t,this.mask=e,this.range=r};Mt.ReadOnly=!1,Mt.ReadWrite=!0,Mt.disabled=new Mt(519,Mt.ReadOnly,[0,1]);var At=function(t,e,r,n,i,a){this.test=t,this.ref=e,this.mask=r,this.fail=n,this.depthFail=i,this.pass=a};At.disabled=new At({func:519,mask:0},0,0,7680,7680,7680);var St=function(t,e,r){this.blendFunction=t,this.blendColor=e,this.mask=r};St.disabled=new St(St.Replace=[1,0],t.Color.transparent,[!1,!1,!1,!1]),St.unblended=new St(St.Replace,t.Color.transparent,[!0,!0,!0,!0]),St.alphaBlended=new St([1,771],t.Color.transparent,[!0,!0,!0,!0]);var Et=function(t,e,r){this.enable=t,this.mode=e,this.frontFace=r};Et.disabled=new Et(!1,1029,2305),Et.backCCW=new Et(!0,1029,2305);var Ct=function(t){this.gl=t,this.extVertexArrayObject=this.gl.getExtension(\"OES_vertex_array_object\"),this.clearColor=new H(this),this.clearDepth=new G(this),this.clearStencil=new Y(this),this.colorMask=new W(this),this.depthMask=new X(this),this.stencilMask=new Z(this),this.stencilFunc=new J(this),this.stencilOp=new K(this),this.stencilTest=new Q(this),this.depthRange=new $(this),this.depthTest=new tt(this),this.depthFunc=new et(this),this.blend=new rt(this),this.blendFunc=new nt(this),this.blendColor=new it(this),this.blendEquation=new at(this),this.cullFace=new ot(this),this.cullFaceSide=new st(this),this.frontFace=new lt(this),this.program=new ct(this),this.activeTexture=new ut(this),this.viewport=new ft(this),this.bindFramebuffer=new ht(this),this.bindRenderbuffer=new pt(this),this.bindTexture=new dt(this),this.bindVertexBuffer=new gt(this),this.bindElementBuffer=new mt(this),this.bindVertexArrayOES=this.extVertexArrayObject&&new vt(this),this.pixelStoreUnpack=new yt(this),this.pixelStoreUnpackPremultiplyAlpha=new xt(this),this.pixelStoreUnpackFlipY=new bt(this),this.extTextureFilterAnisotropic=t.getExtension(\"EXT_texture_filter_anisotropic\")||t.getExtension(\"MOZ_EXT_texture_filter_anisotropic\")||t.getExtension(\"WEBKIT_EXT_texture_filter_anisotropic\"),this.extTextureFilterAnisotropic&&(this.extTextureFilterAnisotropicMax=t.getParameter(this.extTextureFilterAnisotropic.MAX_TEXTURE_MAX_ANISOTROPY_EXT)),this.extTextureHalfFloat=t.getExtension(\"OES_texture_half_float\"),this.extTextureHalfFloat&&(t.getExtension(\"OES_texture_half_float_linear\"),this.extRenderToTextureHalfFloat=t.getExtension(\"EXT_color_buffer_half_float\")),this.extTimerQuery=t.getExtension(\"EXT_disjoint_timer_query\")};Ct.prototype.setDefault=function(){this.unbindVAO(),this.clearColor.setDefault(),this.clearDepth.setDefault(),this.clearStencil.setDefault(),this.colorMask.setDefault(),this.depthMask.setDefault(),this.stencilMask.setDefault(),this.stencilFunc.setDefault(),this.stencilOp.setDefault(),this.stencilTest.setDefault(),this.depthRange.setDefault(),this.depthTest.setDefault(),this.depthFunc.setDefault(),this.blend.setDefault(),this.blendFunc.setDefault(),this.blendColor.setDefault(),this.blendEquation.setDefault(),this.cullFace.setDefault(),this.cullFaceSide.setDefault(),this.frontFace.setDefault(),this.program.setDefault(),this.activeTexture.setDefault(),this.bindFramebuffer.setDefault(),this.pixelStoreUnpack.setDefault(),this.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.pixelStoreUnpackFlipY.setDefault()},Ct.prototype.setDirty=function(){this.clearColor.dirty=!0,this.clearDepth.dirty=!0,this.clearStencil.dirty=!0,this.colorMask.dirty=!0,this.depthMask.dirty=!0,this.stencilMask.dirty=!0,this.stencilFunc.dirty=!0,this.stencilOp.dirty=!0,this.stencilTest.dirty=!0,this.depthRange.dirty=!0,this.depthTest.dirty=!0,this.depthFunc.dirty=!0,this.blend.dirty=!0,this.blendFunc.dirty=!0,this.blendColor.dirty=!0,this.blendEquation.dirty=!0,this.cullFace.dirty=!0,this.cullFaceSide.dirty=!0,this.frontFace.dirty=!0,this.program.dirty=!0,this.activeTexture.dirty=!0,this.viewport.dirty=!0,this.bindFramebuffer.dirty=!0,this.bindRenderbuffer.dirty=!0,this.bindTexture.dirty=!0,this.bindVertexBuffer.dirty=!0,this.bindElementBuffer.dirty=!0,this.extVertexArrayObject&&(this.bindVertexArrayOES.dirty=!0),this.pixelStoreUnpack.dirty=!0,this.pixelStoreUnpackPremultiplyAlpha.dirty=!0,this.pixelStoreUnpackFlipY.dirty=!0},Ct.prototype.createIndexBuffer=function(t,e){return new j(this,t,e)},Ct.prototype.createVertexBuffer=function(t,e,r){return new V(this,t,e,r)},Ct.prototype.createRenderbuffer=function(t,e,r){var n=this.gl,i=n.createRenderbuffer();return this.bindRenderbuffer.set(i),n.renderbufferStorage(n.RENDERBUFFER,t,e,r),this.bindRenderbuffer.set(null),i},Ct.prototype.createFramebuffer=function(t,e,r){return new kt(this,t,e,r)},Ct.prototype.clear=function(t){var e=t.color,r=t.depth,n=this.gl,i=0;e&&(i|=n.COLOR_BUFFER_BIT,this.clearColor.set(e),this.colorMask.set([!0,!0,!0,!0])),void 0!==r&&(i|=n.DEPTH_BUFFER_BIT,this.depthRange.set([0,1]),this.clearDepth.set(r),this.depthMask.set(!0)),n.clear(i)},Ct.prototype.setCullFace=function(t){!1===t.enable?this.cullFace.set(!1):(this.cullFace.set(!0),this.cullFaceSide.set(t.mode),this.frontFace.set(t.frontFace))},Ct.prototype.setDepthMode=function(t){t.func!==this.gl.ALWAYS||t.mask?(this.depthTest.set(!0),this.depthFunc.set(t.func),this.depthMask.set(t.mask),this.depthRange.set(t.range)):this.depthTest.set(!1)},Ct.prototype.setStencilMode=function(t){t.test.func!==this.gl.ALWAYS||t.mask?(this.stencilTest.set(!0),this.stencilMask.set(t.mask),this.stencilOp.set([t.fail,t.depthFail,t.pass]),this.stencilFunc.set({func:t.test.func,ref:t.ref,mask:t.test.mask})):this.stencilTest.set(!1)},Ct.prototype.setColorMode=function(e){t.deepEqual(e.blendFunction,St.Replace)?this.blend.set(!1):(this.blend.set(!0),this.blendFunc.set(e.blendFunction),this.blendColor.set(e.blendColor)),this.colorMask.set(e.mask)},Ct.prototype.unbindVAO=function(){this.extVertexArrayObject&&this.bindVertexArrayOES.set(null)};var Lt=function(e){function r(r,n,i){var a=this;e.call(this),this.id=r,this.dispatcher=i,this.on(\"data\",(function(t){\"source\"===t.dataType&&\"metadata\"===t.sourceDataType&&(a._sourceLoaded=!0),a._sourceLoaded&&!a._paused&&\"source\"===t.dataType&&\"content\"===t.sourceDataType&&(a.reload(),a.transform&&a.update(a.transform))})),this.on(\"error\",(function(){a._sourceErrored=!0})),this._source=function(e,r,n,i){var a=new D[r.type](e,r,n,i);if(a.id!==e)throw new Error(\"Expected Source id to be \"+e+\" instead of \"+a.id);return t.bindAll([\"load\",\"abort\",\"unload\",\"serialize\",\"prepare\"],a),a}(r,n,i,this),this._tiles={},this._cache=new N(0,this._unloadTile.bind(this)),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._loadedParentTiles={},this._coveredTiles={},this._state=new t.SourceFeatureState}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.onAdd=function(t){this.map=t,this._maxTileCacheSize=t?t._maxTileCacheSize:null,this._source&&this._source.onAdd&&this._source.onAdd(t)},r.prototype.onRemove=function(t){this._source&&this._source.onRemove&&this._source.onRemove(t)},r.prototype.loaded=function(){if(this._sourceErrored)return!0;if(!this._sourceLoaded)return!1;if(!this._source.loaded())return!1;for(var t in this._tiles){var e=this._tiles[t];if(\"loaded\"!==e.state&&\"errored\"!==e.state)return!1}return!0},r.prototype.getSource=function(){return this._source},r.prototype.pause=function(){this._paused=!0},r.prototype.resume=function(){if(this._paused){var t=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,t&&this.reload(),this.transform&&this.update(this.transform)}},r.prototype._loadTile=function(t,e){return this._source.loadTile(t,e)},r.prototype._unloadTile=function(t){if(this._source.unloadTile)return this._source.unloadTile(t,(function(){}))},r.prototype._abortTile=function(t){if(this._source.abortTile)return this._source.abortTile(t,(function(){}))},r.prototype.serialize=function(){return this._source.serialize()},r.prototype.prepare=function(t){for(var e in this._source.prepare&&this._source.prepare(),this._state.coalesceChanges(this._tiles,this.map?this.map.painter:null),this._tiles){var r=this._tiles[e];r.upload(t),r.prepare(this.map.style.imageManager)}},r.prototype.getIds=function(){return t.values(this._tiles).map((function(t){return t.tileID})).sort(It).map((function(t){return t.key}))},r.prototype.getRenderableIds=function(e){var r=this,n=[];for(var i in this._tiles)this._isIdRenderable(i,e)&&n.push(this._tiles[i]);return e?n.sort((function(e,n){var i=e.tileID,a=n.tileID,o=new t.Point(i.canonical.x,i.canonical.y)._rotate(r.transform.angle),s=new t.Point(a.canonical.x,a.canonical.y)._rotate(r.transform.angle);return i.overscaledZ-a.overscaledZ||s.y-o.y||s.x-o.x})).map((function(t){return t.tileID.key})):n.map((function(t){return t.tileID})).sort(It).map((function(t){return t.key}))},r.prototype.hasRenderableParent=function(t){var e=this.findLoadedParent(t,0);return!!e&&this._isIdRenderable(e.tileID.key)},r.prototype._isIdRenderable=function(t,e){return this._tiles[t]&&this._tiles[t].hasData()&&!this._coveredTiles[t]&&(e||!this._tiles[t].holdingForFade())},r.prototype.reload=function(){if(this._paused)this._shouldReloadOnResume=!0;else for(var t in this._cache.reset(),this._tiles)\"errored\"!==this._tiles[t].state&&this._reloadTile(t,\"reloading\")},r.prototype._reloadTile=function(t,e){var r=this._tiles[t];r&&(\"loading\"!==r.state&&(r.state=e),this._loadTile(r,this._tileLoaded.bind(this,r,t,e)))},r.prototype._tileLoaded=function(e,r,n,i){if(i)return e.state=\"errored\",void(404!==i.status?this._source.fire(new t.ErrorEvent(i,{tile:e})):this.update(this.transform));e.timeAdded=t.browser.now(),\"expired\"===n&&(e.refreshedUponExpiration=!0),this._setTileReloadTimer(r,e),\"raster-dem\"===this.getSource().type&&e.dem&&this._backfillDEM(e),this._state.initializeTileState(e,this.map?this.map.painter:null),this._source.fire(new t.Event(\"data\",{dataType:\"source\",tile:e,coord:e.tileID}))},r.prototype._backfillDEM=function(t){for(var e=this.getRenderableIds(),r=0;r<e.length;r++){var n=e[r];if(t.neighboringTiles&&t.neighboringTiles[n]){var i=this.getTileByID(n);a(t,i),a(i,t)}}function a(t,e){t.needsHillshadePrepare=!0;var r=e.tileID.canonical.x-t.tileID.canonical.x,n=e.tileID.canonical.y-t.tileID.canonical.y,i=Math.pow(2,t.tileID.canonical.z),a=e.tileID.key;0===r&&0===n||Math.abs(n)>1||(Math.abs(r)>1&&(1===Math.abs(r+i)?r+=i:1===Math.abs(r-i)&&(r-=i)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[a]&&(t.neighboringTiles[a].backfilled=!0)))}},r.prototype.getTile=function(t){return this.getTileByID(t.key)},r.prototype.getTileByID=function(t){return this._tiles[t]},r.prototype._retainLoadedChildren=function(t,e,r,n){for(var i in this._tiles){var a=this._tiles[i];if(!(n[i]||!a.hasData()||a.tileID.overscaledZ<=e||a.tileID.overscaledZ>r)){for(var o=a.tileID;a&&a.tileID.overscaledZ>e+1;){var s=a.tileID.scaledTo(a.tileID.overscaledZ-1);(a=this._tiles[s.key])&&a.hasData()&&(o=s)}for(var l=o;l.overscaledZ>e;)if(t[(l=l.scaledTo(l.overscaledZ-1)).key]){n[o.key]=o;break}}}},r.prototype.findLoadedParent=function(t,e){if(t.key in this._loadedParentTiles){var r=this._loadedParentTiles[t.key];return r&&r.tileID.overscaledZ>=e?r:null}for(var n=t.overscaledZ-1;n>=e;n--){var i=t.scaledTo(n),a=this._getLoadedTile(i);if(a)return a}},r.prototype._getLoadedTile=function(t){var e=this._tiles[t.key];return e&&e.hasData()?e:this._cache.getByKey(t.wrapped().key)},r.prototype.updateCacheSize=function(t){var e=Math.ceil(t.width/this._source.tileSize)+1,r=Math.ceil(t.height/this._source.tileSize)+1,n=Math.floor(e*r*5),i=\"number\"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,n):n;this._cache.setMaxSize(i)},r.prototype.handleWrapJump=function(t){var e=Math.round((t-(void 0===this._prevLng?t:this._prevLng))/360);if(this._prevLng=t,e){var r={};for(var n in this._tiles){var i=this._tiles[n];i.tileID=i.tileID.unwrapTo(i.tileID.wrap+e),r[i.tileID.key]=i}for(var a in this._tiles=r,this._timers)clearTimeout(this._timers[a]),delete this._timers[a];for(var o in this._tiles)this._setTileReloadTimer(o,this._tiles[o])}},r.prototype.update=function(e){var n=this;if(this.transform=e,this._sourceLoaded&&!this._paused){var i;this.updateCacheSize(e),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used?this._source.tileID?i=e.getVisibleUnwrappedCoordinates(this._source.tileID).map((function(e){return new t.OverscaledTileID(e.canonical.z,e.wrap,e.canonical.z,e.canonical.x,e.canonical.y)})):(i=e.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(i=i.filter((function(t){return n._source.hasTile(t)})))):i=[];var a=e.coveringZoomLevel(this._source),o=Math.max(a-r.maxOverzooming,this._source.minzoom),s=Math.max(a+r.maxUnderzooming,this._source.minzoom),l=this._updateRetainedTiles(i,a);if(Pt(this._source.type)){for(var c={},u={},f=0,h=Object.keys(l);f<h.length;f+=1){var p=h[f],d=l[p],g=this._tiles[p];if(g&&!(g.fadeEndTime&&g.fadeEndTime<=t.browser.now())){var m=this.findLoadedParent(d,o);m&&(this._addTile(m.tileID),c[m.tileID.key]=m.tileID),u[p]=d}}for(var v in this._retainLoadedChildren(u,a,s,l),c)l[v]||(this._coveredTiles[v]=!0,l[v]=c[v])}for(var y in l)this._tiles[y].clearFadeHold();for(var x=0,b=t.keysDifference(this._tiles,l);x<b.length;x+=1){var _=b[x],w=this._tiles[_];w.hasSymbolBuckets&&!w.holdingForFade()?w.setHoldDuration(this.map._fadeDuration):w.hasSymbolBuckets&&!w.symbolFadeFinished()||this._removeTile(_)}this._updateLoadedParentTileCache()}},r.prototype.releaseSymbolFadeTiles=function(){for(var t in this._tiles)this._tiles[t].holdingForFade()&&this._removeTile(t)},r.prototype._updateRetainedTiles=function(t,e){for(var n={},i={},a=Math.max(e-r.maxOverzooming,this._source.minzoom),o=Math.max(e+r.maxUnderzooming,this._source.minzoom),s={},l=0,c=t;l<c.length;l+=1){var u=c[l],f=this._addTile(u);n[u.key]=u,f.hasData()||e<this._source.maxzoom&&(s[u.key]=u)}this._retainLoadedChildren(s,e,o,n);for(var h=0,p=t;h<p.length;h+=1){var d=p[h],g=this._tiles[d.key];if(!g.hasData()){if(e+1>this._source.maxzoom){var m=d.children(this._source.maxzoom)[0],v=this.getTile(m);if(v&&v.hasData()){n[m.key]=m;continue}}else{var y=d.children(this._source.maxzoom);if(n[y[0].key]&&n[y[1].key]&&n[y[2].key]&&n[y[3].key])continue}for(var x=g.wasRequested(),b=d.overscaledZ-1;b>=a;--b){var _=d.scaledTo(b);if(i[_.key])break;if(i[_.key]=!0,!(g=this.getTile(_))&&x&&(g=this._addTile(_)),g&&(n[_.key]=_,x=g.wasRequested(),g.hasData()))break}}}return n},r.prototype._updateLoadedParentTileCache=function(){for(var t in this._loadedParentTiles={},this._tiles){for(var e=[],r=void 0,n=this._tiles[t].tileID;n.overscaledZ>0;){if(n.key in this._loadedParentTiles){r=this._loadedParentTiles[n.key];break}e.push(n.key);var i=n.scaledTo(n.overscaledZ-1);if(r=this._getLoadedTile(i))break;n=i}for(var a=0,o=e;a<o.length;a+=1)this._loadedParentTiles[o[a]]=r}},r.prototype._addTile=function(e){var r=this._tiles[e.key];if(r)return r;(r=this._cache.getAndRemove(e))&&(this._setTileReloadTimer(e.key,r),r.tileID=e,this._state.initializeTileState(r,this.map?this.map.painter:null),this._cacheTimers[e.key]&&(clearTimeout(this._cacheTimers[e.key]),delete this._cacheTimers[e.key],this._setTileReloadTimer(e.key,r)));var n=Boolean(r);return n||(r=new t.Tile(e,this._source.tileSize*e.overscaleFactor()),this._loadTile(r,this._tileLoaded.bind(this,r,e.key,r.state))),r?(r.uses++,this._tiles[e.key]=r,n||this._source.fire(new t.Event(\"dataloading\",{tile:r,coord:r.tileID,dataType:\"source\"})),r):null},r.prototype._setTileReloadTimer=function(t,e){var r=this;t in this._timers&&(clearTimeout(this._timers[t]),delete this._timers[t]);var n=e.getExpiryTimeout();n&&(this._timers[t]=setTimeout((function(){r._reloadTile(t,\"expired\"),delete r._timers[t]}),n))},r.prototype._removeTile=function(t){var e=this._tiles[t];e&&(e.uses--,delete this._tiles[t],this._timers[t]&&(clearTimeout(this._timers[t]),delete this._timers[t]),e.uses>0||(e.hasData()&&\"reloading\"!==e.state?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))},r.prototype.clearTiles=function(){for(var t in this._shouldReloadOnResume=!1,this._paused=!1,this._tiles)this._removeTile(t);this._cache.reset()},r.prototype.tilesIn=function(e,r,n){var i=this,a=[],o=this.transform;if(!o)return a;for(var s=n?o.getCameraQueryGeometry(e):e,l=e.map((function(t){return o.pointCoordinate(t)})),c=s.map((function(t){return o.pointCoordinate(t)})),u=this.getIds(),f=1/0,h=1/0,p=-1/0,d=-1/0,g=0,m=c;g<m.length;g+=1){var v=m[g];f=Math.min(f,v.x),h=Math.min(h,v.y),p=Math.max(p,v.x),d=Math.max(d,v.y)}for(var y=function(e){var n=i._tiles[u[e]];if(!n.holdingForFade()){var s=n.tileID,g=Math.pow(2,o.zoom-n.tileID.overscaledZ),m=r*n.queryPadding*t.EXTENT/n.tileSize/g,v=[s.getTilePoint(new t.MercatorCoordinate(f,h)),s.getTilePoint(new t.MercatorCoordinate(p,d))];if(v[0].x-m<t.EXTENT&&v[0].y-m<t.EXTENT&&v[1].x+m>=0&&v[1].y+m>=0){var y=l.map((function(t){return s.getTilePoint(t)})),x=c.map((function(t){return s.getTilePoint(t)}));a.push({tile:n,tileID:s,queryGeometry:y,cameraQueryGeometry:x,scale:g})}}},x=0;x<u.length;x++)y(x);return a},r.prototype.getVisibleCoordinates=function(t){for(var e=this,r=this.getRenderableIds(t).map((function(t){return e._tiles[t].tileID})),n=0,i=r;n<i.length;n+=1){var a=i[n];a.posMatrix=this.transform.calculatePosMatrix(a.toUnwrapped())}return r},r.prototype.hasTransition=function(){if(this._source.hasTransition())return!0;if(Pt(this._source.type))for(var e in this._tiles){var r=this._tiles[e];if(void 0!==r.fadeEndTime&&r.fadeEndTime>=t.browser.now())return!0}return!1},r.prototype.setFeatureState=function(t,e,r){this._state.updateState(t=t||\"_geojsonTileLayer\",e,r)},r.prototype.removeFeatureState=function(t,e,r){this._state.removeFeatureState(t=t||\"_geojsonTileLayer\",e,r)},r.prototype.getFeatureState=function(t,e){return this._state.getState(t=t||\"_geojsonTileLayer\",e)},r.prototype.setDependencies=function(t,e,r){var n=this._tiles[t];n&&n.setDependencies(e,r)},r.prototype.reloadTilesForDependencies=function(t,e){for(var r in this._tiles)this._tiles[r].hasDependency(t,e)&&this._reloadTile(r,\"reloading\");this._cache.filter((function(r){return!r.hasDependency(t,e)}))},r}(t.Evented);function It(t,e){var r=Math.abs(2*t.wrap)-+(t.wrap<0),n=Math.abs(2*e.wrap)-+(e.wrap<0);return t.overscaledZ-e.overscaledZ||n-r||e.canonical.y-t.canonical.y||e.canonical.x-t.canonical.x}function Pt(t){return\"raster\"===t||\"image\"===t||\"video\"===t}function zt(){return new t.window.Worker(Yi.workerUrl)}Lt.maxOverzooming=10,Lt.maxUnderzooming=3;var Ot=\"mapboxgl_preloaded_worker_pool\",Dt=function(){this.active={}};Dt.prototype.acquire=function(t){if(!this.workers)for(this.workers=[];this.workers.length<Dt.workerCount;)this.workers.push(new zt);return this.active[t]=!0,this.workers.slice()},Dt.prototype.release=function(t){delete this.active[t],0===this.numActive()&&(this.workers.forEach((function(t){t.terminate()})),this.workers=null)},Dt.prototype.isPreloaded=function(){return!!this.active[Ot]},Dt.prototype.numActive=function(){return Object.keys(this.active).length};var Rt,Ft=Math.floor(t.browser.hardwareConcurrency/2);function Bt(){return Rt||(Rt=new Dt),Rt}function Nt(e,r){var n={};for(var i in e)\"ref\"!==i&&(n[i]=e[i]);return t.refProperties.forEach((function(t){t in r&&(n[t]=r[t])})),n}function jt(t){t=t.slice();for(var e=Object.create(null),r=0;r<t.length;r++)e[t[r].id]=t[r];for(var n=0;n<t.length;n++)\"ref\"in t[n]&&(t[n]=Nt(t[n],e[t[n].ref]));return t}Dt.workerCount=Math.max(Math.min(Ft,6),1);var Ut={setStyle:\"setStyle\",addLayer:\"addLayer\",removeLayer:\"removeLayer\",setPaintProperty:\"setPaintProperty\",setLayoutProperty:\"setLayoutProperty\",setFilter:\"setFilter\",addSource:\"addSource\",removeSource:\"removeSource\",setGeoJSONSourceData:\"setGeoJSONSourceData\",setLayerZoomRange:\"setLayerZoomRange\",setLayerProperty:\"setLayerProperty\",setCenter:\"setCenter\",setZoom:\"setZoom\",setBearing:\"setBearing\",setPitch:\"setPitch\",setSprite:\"setSprite\",setGlyphs:\"setGlyphs\",setTransition:\"setTransition\",setLight:\"setLight\"};function Vt(t,e,r){r.push({command:Ut.addSource,args:[t,e[t]]})}function qt(t,e,r){e.push({command:Ut.removeSource,args:[t]}),r[t]=!0}function Ht(t,e,r,n){qt(t,r,n),Vt(t,e,r)}function Gt(e,r,n){var i;for(i in e[n])if(e[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;for(i in r[n])if(r[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;return!0}function Yt(e,r,n,i,a,o){var s;for(s in r=r||{},e=e||{})e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}));for(s in r)r.hasOwnProperty(s)&&!e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}))}function Wt(t){return t.id}function Xt(t,e){return t[e.id]=e,t}var Zt=function(t,e){this.reset(t,e)};Zt.prototype.reset=function(t,e){this.points=t||[],this._distances=[0];for(var r=1;r<this.points.length;r++)this._distances[r]=this._distances[r-1]+this.points[r].dist(this.points[r-1]);this.length=this._distances[this._distances.length-1],this.padding=Math.min(e||0,.5*this.length),this.paddedLength=this.length-2*this.padding},Zt.prototype.lerp=function(e){if(1===this.points.length)return this.points[0];e=t.clamp(e,0,1);for(var r=1,n=this._distances[r],i=e*this.paddedLength+this.padding;n<i&&r<this._distances.length;)n=this._distances[++r];var a=r-1,o=this._distances[a],s=n-o,l=s>0?(i-o)/s:0;return this.points[a].mult(1-l).add(this.points[r].mult(l))};var Jt=function(t,e,r){var n=this.boxCells=[],i=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(var a=0;a<this.xCellCount*this.yCellCount;a++)n.push([]),i.push([]);this.circleKeys=[],this.boxKeys=[],this.bboxes=[],this.circles=[],this.width=t,this.height=e,this.xScale=this.xCellCount/t,this.yScale=this.yCellCount/e,this.boxUid=0,this.circleUid=0};function Kt(e,r,n,i,a){var o=t.create();return r?(t.scale(o,o,[1/a,1/a,1]),n||t.rotateZ(o,o,i.angle)):t.multiply(o,i.labelPlaneMatrix,e),o}function Qt(e,r,n,i,a){if(r){var o=t.clone(e);return t.scale(o,o,[a,a,1]),n||t.rotateZ(o,o,-i.angle),o}return i.glCoordMatrix}function $t(e,r){var n=[e.x,e.y,0,1];ue(n,n,r);var i=n[3];return{point:new t.Point(n[0]/i,n[1]/i),signedDistanceFromCamera:i}}function te(t,e){return.5+t/e*.5}function ee(t,e){var r=t[0]/t[3],n=t[1]/t[3];return r>=-e[0]&&r<=e[0]&&n>=-e[1]&&n<=e[1]}function re(e,r,n,i,a,o,s,l){var c=i?e.textSizeData:e.iconSizeData,u=t.evaluateSizeForZoom(c,n.transform.zoom),f=[256/n.width*2+1,256/n.height*2+1],h=i?e.text.dynamicLayoutVertexArray:e.icon.dynamicLayoutVertexArray;h.clear();for(var p=e.lineVertexArray,d=i?e.text.placedSymbolArray:e.icon.placedSymbolArray,g=n.transform.width/n.transform.height,m=!1,v=0;v<d.length;v++){var y=d.get(v);if(y.hidden||y.writingMode===t.WritingMode.vertical&&!m)ce(y.numGlyphs,h);else{m=!1;var x=[y.anchorX,y.anchorY,0,1];if(t.transformMat4(x,x,r),ee(x,f)){var b=te(n.transform.cameraToCenterDistance,x[3]),_=t.evaluateSizeForFeature(c,u,y),w=s?_/b:_*b,T=new t.Point(y.anchorX,y.anchorY),k=$t(T,a).point,M={},A=ae(y,w,!1,l,r,a,o,e.glyphOffsetArray,p,h,k,T,M,g);m=A.useVertical,(A.notEnoughRoom||m||A.needsFlipping&&ae(y,w,!0,l,r,a,o,e.glyphOffsetArray,p,h,k,T,M,g).notEnoughRoom)&&ce(y.numGlyphs,h)}else ce(y.numGlyphs,h)}}i?e.text.dynamicLayoutVertexBuffer.updateData(h):e.icon.dynamicLayoutVertexBuffer.updateData(h)}function ne(t,e,r,n,i,a,o,s,l,c,u){var f=s.glyphStartIndex+s.numGlyphs,h=s.lineStartIndex,p=s.lineStartIndex+s.lineLength,d=e.getoffsetX(s.glyphStartIndex),g=e.getoffsetX(f-1),m=se(t*d,r,n,i,a,o,s.segment,h,p,l,c,u);if(!m)return null;var v=se(t*g,r,n,i,a,o,s.segment,h,p,l,c,u);return v?{first:m,last:v}:null}function ie(e,r,n,i){return e===t.WritingMode.horizontal&&Math.abs(n.y-r.y)>Math.abs(n.x-r.x)*i?{useVertical:!0}:(e===t.WritingMode.vertical?r.y<n.y:r.x>n.x)?{needsFlipping:!0}:null}function ae(e,r,n,i,a,o,s,l,c,u,f,h,p,d){var g,m=r/24,v=e.lineOffsetX*m,y=e.lineOffsetY*m;if(e.numGlyphs>1){var x=e.glyphStartIndex+e.numGlyphs,b=e.lineStartIndex,_=e.lineStartIndex+e.lineLength,w=ne(m,l,v,y,n,f,h,e,c,o,p);if(!w)return{notEnoughRoom:!0};var T=$t(w.first.point,s).point,k=$t(w.last.point,s).point;if(i&&!n){var M=ie(e.writingMode,T,k,d);if(M)return M}g=[w.first];for(var A=e.glyphStartIndex+1;A<x-1;A++)g.push(se(m*l.getoffsetX(A),v,y,n,f,h,e.segment,b,_,c,o,p));g.push(w.last)}else{if(i&&!n){var S=$t(h,a).point,E=e.lineStartIndex+e.segment+1,C=new t.Point(c.getx(E),c.gety(E)),L=$t(C,a),I=L.signedDistanceFromCamera>0?L.point:oe(h,C,S,1,a),P=ie(e.writingMode,S,I,d);if(P)return P}var z=se(m*l.getoffsetX(e.glyphStartIndex),v,y,n,f,h,e.segment,e.lineStartIndex,e.lineStartIndex+e.lineLength,c,o,p);if(!z)return{notEnoughRoom:!0};g=[z]}for(var O=0,D=g;O<D.length;O+=1){var R=D[O];t.addDynamicAttributes(u,R.point,R.angle)}return{}}function oe(t,e,r,n,i){var a=$t(t.add(t.sub(e)._unit()),i).point,o=r.sub(a);return r.add(o._mult(n/o.mag()))}function se(e,r,n,i,a,o,s,l,c,u,f,h){var p=i?e-r:e+r,d=p>0?1:-1,g=0;i&&(d*=-1,g=Math.PI),d<0&&(g+=Math.PI);for(var m=d>0?l+s:l+s+1,v=a,y=a,x=0,b=0,_=Math.abs(p),w=[];x+b<=_;){if((m+=d)<l||m>=c)return null;if(y=v,w.push(v),void 0===(v=h[m])){var T=new t.Point(u.getx(m),u.gety(m)),k=$t(T,f);if(k.signedDistanceFromCamera>0)v=h[m]=k.point;else{var M=m-d;v=oe(0===x?o:new t.Point(u.getx(M),u.gety(M)),T,y,_-x+1,f)}}x+=b,b=y.dist(v)}var A=(_-x)/b,S=v.sub(y),E=S.mult(A)._add(y);E._add(S._unit()._perp()._mult(n*d));var C=g+Math.atan2(v.y-y.y,v.x-y.x);return w.push(E),{point:E,angle:C,path:w}}Jt.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},Jt.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertBoxCell,this.boxUid++),this.boxKeys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},Jt.prototype.insertCircle=function(t,e,r,n){this._forEachCell(e-n,r-n,e+n,r+n,this._insertCircleCell,this.circleUid++),this.circleKeys.push(t),this.circles.push(e),this.circles.push(r),this.circles.push(n)},Jt.prototype._insertBoxCell=function(t,e,r,n,i,a){this.boxCells[i].push(a)},Jt.prototype._insertCircleCell=function(t,e,r,n,i,a){this.circleCells[i].push(a)},Jt.prototype._query=function(t,e,r,n,i,a){if(r<0||t>this.width||n<0||e>this.height)return!i&&[];var o=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(i)return!0;for(var s=0;s<this.boxKeys.length;s++)o.push({key:this.boxKeys[s],x1:this.bboxes[4*s],y1:this.bboxes[4*s+1],x2:this.bboxes[4*s+2],y2:this.bboxes[4*s+3]});for(var l=0;l<this.circleKeys.length;l++){var c=this.circles[3*l],u=this.circles[3*l+1],f=this.circles[3*l+2];o.push({key:this.circleKeys[l],x1:c-f,y1:u-f,x2:c+f,y2:u+f})}return a?o.filter(a):o}return this._forEachCell(t,e,r,n,this._queryCell,o,{hitTest:i,seenUids:{box:{},circle:{}}},a),i?o.length>0:o},Jt.prototype._queryCircle=function(t,e,r,n,i){var a=t-r,o=t+r,s=e-r,l=e+r;if(o<0||a>this.width||l<0||s>this.height)return!n&&[];var c=[];return this._forEachCell(a,s,o,l,this._queryCellCircle,c,{hitTest:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}},i),n?c.length>0:c},Jt.prototype.query=function(t,e,r,n,i){return this._query(t,e,r,n,!1,i)},Jt.prototype.hitTest=function(t,e,r,n,i){return this._query(t,e,r,n,!0,i)},Jt.prototype.hitTestCircle=function(t,e,r,n){return this._queryCircle(t,e,r,!0,n)},Jt.prototype._queryCell=function(t,e,r,n,i,a,o,s){var l=o.seenUids,c=this.boxCells[i];if(null!==c)for(var u=this.bboxes,f=0,h=c;f<h.length;f+=1){var p=h[f];if(!l.box[p]){l.box[p]=!0;var d=4*p;if(t<=u[d+2]&&e<=u[d+3]&&r>=u[d+0]&&n>=u[d+1]&&(!s||s(this.boxKeys[p]))){if(o.hitTest)return a.push(!0),!0;a.push({key:this.boxKeys[p],x1:u[d],y1:u[d+1],x2:u[d+2],y2:u[d+3]})}}}var g=this.circleCells[i];if(null!==g)for(var m=this.circles,v=0,y=g;v<y.length;v+=1){var x=y[v];if(!l.circle[x]){l.circle[x]=!0;var b=3*x;if(this._circleAndRectCollide(m[b],m[b+1],m[b+2],t,e,r,n)&&(!s||s(this.circleKeys[x]))){if(o.hitTest)return a.push(!0),!0;var _=m[b],w=m[b+1],T=m[b+2];a.push({key:this.circleKeys[x],x1:_-T,y1:w-T,x2:_+T,y2:w+T})}}}},Jt.prototype._queryCellCircle=function(t,e,r,n,i,a,o,s){var l=o.circle,c=o.seenUids,u=this.boxCells[i];if(null!==u)for(var f=this.bboxes,h=0,p=u;h<p.length;h+=1){var d=p[h];if(!c.box[d]){c.box[d]=!0;var g=4*d;if(this._circleAndRectCollide(l.x,l.y,l.radius,f[g+0],f[g+1],f[g+2],f[g+3])&&(!s||s(this.boxKeys[d])))return a.push(!0),!0}}var m=this.circleCells[i];if(null!==m)for(var v=this.circles,y=0,x=m;y<x.length;y+=1){var b=x[y];if(!c.circle[b]){c.circle[b]=!0;var _=3*b;if(this._circlesCollide(v[_],v[_+1],v[_+2],l.x,l.y,l.radius)&&(!s||s(this.circleKeys[b])))return a.push(!0),!0}}},Jt.prototype._forEachCell=function(t,e,r,n,i,a,o,s){for(var l=this._convertToXCellCoord(t),c=this._convertToYCellCoord(e),u=this._convertToXCellCoord(r),f=this._convertToYCellCoord(n),h=l;h<=u;h++)for(var p=c;p<=f;p++)if(i.call(this,t,e,r,n,this.xCellCount*p+h,a,o,s))return},Jt.prototype._convertToXCellCoord=function(t){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(t*this.xScale)))},Jt.prototype._convertToYCellCoord=function(t){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(t*this.yScale)))},Jt.prototype._circlesCollide=function(t,e,r,n,i,a){var o=n-t,s=i-e,l=r+a;return l*l>o*o+s*s},Jt.prototype._circleAndRectCollide=function(t,e,r,n,i,a,o){var s=(a-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;var c=(o-i)/2,u=Math.abs(e-(i+c));if(u>c+r)return!1;if(l<=s||u<=c)return!0;var f=l-s,h=u-c;return f*f+h*h<=r*r};var le=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function ce(t,e){for(var r=0;r<t;r++){var n=e.length;e.resize(n+4),e.float32.set(le,3*n)}}function ue(t,e,r){var n=e[0],i=e[1];return t[0]=r[0]*n+r[4]*i+r[12],t[1]=r[1]*n+r[5]*i+r[13],t[3]=r[3]*n+r[7]*i+r[15],t}var fe=function(t,e,r){void 0===e&&(e=new Jt(t.width+200,t.height+200,25)),void 0===r&&(r=new Jt(t.width+200,t.height+200,25)),this.transform=t,this.grid=e,this.ignoredGrid=r,this.pitchfactor=Math.cos(t._pitch)*t.cameraToCenterDistance,this.screenRightBoundary=t.width+100,this.screenBottomBoundary=t.height+100,this.gridRightBoundary=t.width+200,this.gridBottomBoundary=t.height+200};function he(e,r,n){return r*(t.EXTENT/(e.tileSize*Math.pow(2,n-e.tileID.overscaledZ)))}fe.prototype.placeCollisionBox=function(t,e,r,n,i){var a=this.projectAndGetPerspectiveRatio(n,t.anchorPointX,t.anchorPointY),o=r*a.perspectiveRatio,s=t.x1*o+a.point.x,l=t.y1*o+a.point.y,c=t.x2*o+a.point.x,u=t.y2*o+a.point.y;return!this.isInsideGrid(s,l,c,u)||!e&&this.grid.hitTest(s,l,c,u,i)?{box:[],offscreen:!1}:{box:[s,l,c,u],offscreen:this.isOffscreen(s,l,c,u)}},fe.prototype.placeCollisionCircles=function(e,r,n,i,a,o,s,l,c,u,f,h,p){var d=[],g=new t.Point(r.anchorX,r.anchorY),m=$t(g,o),v=te(this.transform.cameraToCenterDistance,m.signedDistanceFromCamera),y=(u?a/v:a*v)/t.ONE_EM,x=$t(g,s).point,b=ne(y,i,r.lineOffsetX*y,r.lineOffsetY*y,!1,x,g,r,n,s,{}),_=!1,w=!1,T=!0;if(b){for(var k=.5*h*v+p,M=new t.Point(-100,-100),A=new t.Point(this.screenRightBoundary,this.screenBottomBoundary),S=new Zt,E=b.first,C=b.last,L=[],I=E.path.length-1;I>=1;I--)L.push(E.path[I]);for(var P=1;P<C.path.length;P++)L.push(C.path[P]);var z=2.5*k;if(l){var O=L.map((function(t){return $t(t,l)}));L=O.some((function(t){return t.signedDistanceFromCamera<=0}))?[]:O.map((function(t){return t.point}))}var D=[];if(L.length>0){for(var R=L[0].clone(),F=L[0].clone(),B=1;B<L.length;B++)R.x=Math.min(R.x,L[B].x),R.y=Math.min(R.y,L[B].y),F.x=Math.max(F.x,L[B].x),F.y=Math.max(F.y,L[B].y);D=R.x>=M.x&&F.x<=A.x&&R.y>=M.y&&F.y<=A.y?[L]:F.x<M.x||R.x>A.x||F.y<M.y||R.y>A.y?[]:t.clipLine([L],M.x,M.y,A.x,A.y)}for(var N=0,j=D;N<j.length;N+=1){var U;S.reset(j[N],.25*k),U=S.length<=.5*k?1:Math.ceil(S.paddedLength/z)+1;for(var V=0;V<U;V++){var q=V/Math.max(U-1,1),H=S.lerp(q),G=H.x+100,Y=H.y+100;d.push(G,Y,k,0);var W=G-k,X=Y-k,Z=G+k,J=Y+k;if(T=T&&this.isOffscreen(W,X,Z,J),w=w||this.isInsideGrid(W,X,Z,J),!e&&this.grid.hitTestCircle(G,Y,k,f)&&(_=!0,!c))return{circles:[],offscreen:!1,collisionDetected:_}}}}return{circles:!c&&_||!w?[]:d,offscreen:T,collisionDetected:_}},fe.prototype.queryRenderedSymbols=function(e){if(0===e.length||0===this.grid.keysLength()&&0===this.ignoredGrid.keysLength())return{};for(var r=[],n=1/0,i=1/0,a=-1/0,o=-1/0,s=0,l=e;s<l.length;s+=1){var c=l[s],u=new t.Point(c.x+100,c.y+100);n=Math.min(n,u.x),i=Math.min(i,u.y),a=Math.max(a,u.x),o=Math.max(o,u.y),r.push(u)}for(var f={},h={},p=0,d=this.grid.query(n,i,a,o).concat(this.ignoredGrid.query(n,i,a,o));p<d.length;p+=1){var g=d[p],m=g.key;if(void 0===f[m.bucketInstanceId]&&(f[m.bucketInstanceId]={}),!f[m.bucketInstanceId][m.featureIndex]){var v=[new t.Point(g.x1,g.y1),new t.Point(g.x2,g.y1),new t.Point(g.x2,g.y2),new t.Point(g.x1,g.y2)];t.polygonIntersectsPolygon(r,v)&&(f[m.bucketInstanceId][m.featureIndex]=!0,void 0===h[m.bucketInstanceId]&&(h[m.bucketInstanceId]=[]),h[m.bucketInstanceId].push(m.featureIndex))}}return h},fe.prototype.insertCollisionBox=function(t,e,r,n,i){(e?this.ignoredGrid:this.grid).insert({bucketInstanceId:r,featureIndex:n,collisionGroupID:i},t[0],t[1],t[2],t[3])},fe.prototype.insertCollisionCircles=function(t,e,r,n,i){for(var a=e?this.ignoredGrid:this.grid,o={bucketInstanceId:r,featureIndex:n,collisionGroupID:i},s=0;s<t.length;s+=4)a.insertCircle(o,t[s],t[s+1],t[s+2])},fe.prototype.projectAndGetPerspectiveRatio=function(e,r,n){var i=[r,n,0,1];return ue(i,i,e),{point:new t.Point((i[0]/i[3]+1)/2*this.transform.width+100,(-i[1]/i[3]+1)/2*this.transform.height+100),perspectiveRatio:.5+this.transform.cameraToCenterDistance/i[3]*.5}},fe.prototype.isOffscreen=function(t,e,r,n){return r<100||t>=this.screenRightBoundary||n<100||e>this.screenBottomBoundary},fe.prototype.isInsideGrid=function(t,e,r,n){return r>=0&&t<this.gridRightBoundary&&n>=0&&e<this.gridBottomBoundary},fe.prototype.getViewportMatrix=function(){var e=t.identity([]);return t.translate(e,e,[-100,-100,0]),e};var pe=function(t,e,r,n){this.opacity=t?Math.max(0,Math.min(1,t.opacity+(t.placed?e:-e))):n&&r?1:0,this.placed=r};pe.prototype.isHidden=function(){return 0===this.opacity&&!this.placed};var de=function(t,e,r,n,i){this.text=new pe(t?t.text:null,e,r,i),this.icon=new pe(t?t.icon:null,e,n,i)};de.prototype.isHidden=function(){return this.text.isHidden()&&this.icon.isHidden()};var ge=function(t,e,r){this.text=t,this.icon=e,this.skipFade=r},me=function(){this.invProjMatrix=t.create(),this.viewportMatrix=t.create(),this.circles=[]},ve=function(t,e,r,n,i){this.bucketInstanceId=t,this.featureIndex=e,this.sourceLayerIndex=r,this.bucketIndex=n,this.tileID=i},ye=function(t){this.crossSourceCollisions=t,this.maxGroupID=0,this.collisionGroups={}};function xe(e,r,n,i,a){var o=t.getAnchorAlignment(e),s=-(o.horizontalAlign-.5)*r,l=-(o.verticalAlign-.5)*n,c=t.evaluateVariableOffset(e,i);return new t.Point(s+c[0]*a,l+c[1]*a)}function be(e,r,n,i,a,o){var s=e.x1,l=e.x2,c=e.y1,u=e.y2,f=e.anchorPointX,h=e.anchorPointY,p=new t.Point(r,n);return i&&p._rotate(a?o:-o),{x1:s+p.x,y1:c+p.y,x2:l+p.x,y2:u+p.y,anchorPointX:f,anchorPointY:h}}ye.prototype.get=function(t){if(this.crossSourceCollisions)return{ID:0,predicate:null};if(!this.collisionGroups[t]){var e=++this.maxGroupID;this.collisionGroups[t]={ID:e,predicate:function(t){return t.collisionGroupID===e}}}return this.collisionGroups[t]};var _e=function(t,e,r,n){this.transform=t.clone(),this.collisionIndex=new fe(this.transform),this.placements={},this.opacities={},this.variableOffsets={},this.stale=!1,this.commitTime=0,this.fadeDuration=e,this.retainedQueryData={},this.collisionGroups=new ye(r),this.collisionCircleArrays={},this.prevPlacement=n,n&&(n.prevPlacement=void 0),this.placedOrientations={}};function we(t,e,r,n,i){t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0)}_e.prototype.getBucketParts=function(e,r,n,i){var a=n.getBucket(r),o=n.latestFeatureIndex;if(a&&o&&r.id===a.layerIds[0]){var s=n.collisionBoxArray,l=a.layers[0].layout,c=Math.pow(2,this.transform.zoom-n.tileID.overscaledZ),u=n.tileSize/t.EXTENT,f=this.transform.calculatePosMatrix(n.tileID.toUnwrapped()),h=\"map\"===l.get(\"text-pitch-alignment\"),p=\"map\"===l.get(\"text-rotation-alignment\"),d=he(n,1,this.transform.zoom),g=Kt(f,h,p,this.transform,d),m=null;if(h){var v=Qt(f,h,p,this.transform,d);m=t.multiply([],this.transform.labelPlaneMatrix,v)}this.retainedQueryData[a.bucketInstanceId]=new ve(a.bucketInstanceId,o,a.sourceLayerIndex,a.index,n.tileID);var y={bucket:a,layout:l,posMatrix:f,textLabelPlaneMatrix:g,labelToScreenMatrix:m,scale:c,textPixelRatio:u,holdingForFade:n.holdingForFade(),collisionBoxArray:s,partiallyEvaluatedTextSize:t.evaluateSizeForZoom(a.textSizeData,this.transform.zoom),collisionGroup:this.collisionGroups.get(a.sourceID)};if(i)for(var x=0,b=a.sortKeyRanges;x<b.length;x+=1){var _=b[x];e.push({sortKey:_.sortKey,symbolInstanceStart:_.symbolInstanceStart,symbolInstanceEnd:_.symbolInstanceEnd,parameters:y})}else e.push({symbolInstanceStart:0,symbolInstanceEnd:a.symbolInstances.length,parameters:y})}},_e.prototype.attemptAnchorPlacement=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d){var g,m=[f.textOffset0,f.textOffset1],v=xe(t,r,n,m,i),y=this.collisionIndex.placeCollisionBox(be(e,v.x,v.y,a,o,this.transform.angle),u,s,l,c.predicate);if(!d||0!==this.collisionIndex.placeCollisionBox(be(d,v.x,v.y,a,o,this.transform.angle),u,s,l,c.predicate).box.length)return y.box.length>0?(this.prevPlacement&&this.prevPlacement.variableOffsets[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID].text&&(g=this.prevPlacement.variableOffsets[f.crossTileID].anchor),this.variableOffsets[f.crossTileID]={textOffset:m,width:r,height:n,anchor:t,textBoxScale:i,prevAnchor:g},this.markUsedJustification(h,t,f,p),h.allowVerticalPlacement&&(this.markUsedOrientation(h,p,f),this.placedOrientations[f.crossTileID]=p),{shift:v,placedGlyphBoxes:y}):void 0},_e.prototype.placeLayerBucketPart=function(e,r,n){var i=this,a=e.parameters,o=a.bucket,s=a.layout,l=a.posMatrix,c=a.textLabelPlaneMatrix,u=a.labelToScreenMatrix,f=a.textPixelRatio,h=a.holdingForFade,p=a.collisionBoxArray,d=a.partiallyEvaluatedTextSize,g=a.collisionGroup,m=s.get(\"text-optional\"),v=s.get(\"icon-optional\"),y=s.get(\"text-allow-overlap\"),x=s.get(\"icon-allow-overlap\"),b=\"map\"===s.get(\"text-rotation-alignment\"),_=\"map\"===s.get(\"text-pitch-alignment\"),w=\"none\"!==s.get(\"icon-text-fit\"),T=\"viewport-y\"===s.get(\"symbol-z-order\"),k=y&&(x||!o.hasIconData()||v),M=x&&(y||!o.hasTextData()||m);!o.collisionArrays&&p&&o.deserializeCollisionBoxes(p);var A=function(e,a){if(!r[e.crossTileID])if(h)i.placements[e.crossTileID]=new ge(!1,!1,!1);else{var p,T=!1,A=!1,S=!0,E=null,C={box:null,offscreen:null},L={box:null,offscreen:null},I=null,P=null,z=0,O=0,D=0;a.textFeatureIndex?z=a.textFeatureIndex:e.useRuntimeCollisionCircles&&(z=e.featureIndex),a.verticalTextFeatureIndex&&(O=a.verticalTextFeatureIndex);var R=a.textBox;if(R){var F=function(r){var n=t.WritingMode.horizontal;if(o.allowVerticalPlacement&&!r&&i.prevPlacement){var a=i.prevPlacement.placedOrientations[e.crossTileID];a&&(i.placedOrientations[e.crossTileID]=a,i.markUsedOrientation(o,n=a,e))}return n},B=function(r,n){if(o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&a.verticalTextBox)for(var i=0,s=o.writingModes;i<s.length&&(s[i]===t.WritingMode.vertical?(C=n(),L=C):C=r(),!(C&&C.box&&C.box.length));i+=1);else C=r()};if(s.get(\"text-variable-anchor\")){var N=s.get(\"text-variable-anchor\");if(i.prevPlacement&&i.prevPlacement.variableOffsets[e.crossTileID]){var j=i.prevPlacement.variableOffsets[e.crossTileID];N.indexOf(j.anchor)>0&&(N=N.filter((function(t){return t!==j.anchor}))).unshift(j.anchor)}var U=function(t,r,n){for(var a=t.x2-t.x1,s=t.y2-t.y1,c=e.textBoxScale,u=w&&!x?r:null,h={box:[],offscreen:!1},p=y?2*N.length:N.length,d=0;d<p;++d){var m=i.attemptAnchorPlacement(N[d%N.length],t,a,s,c,b,_,f,l,g,d>=N.length,e,o,n,u);if(m&&(h=m.placedGlyphBoxes)&&h.box&&h.box.length){T=!0,E=m.shift;break}}return h};B((function(){return U(R,a.iconBox,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox;return o.allowVerticalPlacement&&!(C&&C.box&&C.box.length)&&e.numVerticalGlyphVertices>0&&r?U(r,a.verticalIconBox,t.WritingMode.vertical):{box:null,offscreen:null}})),C&&(T=C.box,S=C.offscreen);var V=F(C&&C.box);if(!T&&i.prevPlacement){var q=i.prevPlacement.variableOffsets[e.crossTileID];q&&(i.variableOffsets[e.crossTileID]=q,i.markUsedJustification(o,q.anchor,e,V))}}else{var H=function(t,r){var n=i.collisionIndex.placeCollisionBox(t,y,f,l,g.predicate);return n&&n.box&&n.box.length&&(i.markUsedOrientation(o,r,e),i.placedOrientations[e.crossTileID]=r),n};B((function(){return H(R,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox;return o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&r?H(r,t.WritingMode.vertical):{box:null,offscreen:null}})),F(C&&C.box&&C.box.length)}}if(T=(p=C)&&p.box&&p.box.length>0,S=p&&p.offscreen,e.useRuntimeCollisionCircles){var G=o.text.placedSymbolArray.get(e.centerJustifiedTextSymbolIndex),Y=t.evaluateSizeForFeature(o.textSizeData,d,G),W=s.get(\"text-padding\");I=i.collisionIndex.placeCollisionCircles(y,G,o.lineVertexArray,o.glyphOffsetArray,Y,l,c,u,n,_,g.predicate,e.collisionCircleDiameter,W),T=y||I.circles.length>0&&!I.collisionDetected,S=S&&I.offscreen}if(a.iconFeatureIndex&&(D=a.iconFeatureIndex),a.iconBox){var X=function(t){var e=w&&E?be(t,E.x,E.y,b,_,i.transform.angle):t;return i.collisionIndex.placeCollisionBox(e,x,f,l,g.predicate)};A=L&&L.box&&L.box.length&&a.verticalIconBox?(P=X(a.verticalIconBox)).box.length>0:(P=X(a.iconBox)).box.length>0,S=S&&P.offscreen}var Z=m||0===e.numHorizontalGlyphVertices&&0===e.numVerticalGlyphVertices,J=v||0===e.numIconVertices;if(Z||J?J?Z||(A=A&&T):T=A&&T:A=T=A&&T,T&&p&&p.box&&i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,L&&L.box&&O?O:z,g.ID),A&&P&&i.collisionIndex.insertCollisionBox(P.box,s.get(\"icon-ignore-placement\"),o.bucketInstanceId,D,g.ID),I&&(T&&i.collisionIndex.insertCollisionCircles(I.circles,s.get(\"text-ignore-placement\"),o.bucketInstanceId,z,g.ID),n)){var K=o.bucketInstanceId,Q=i.collisionCircleArrays[K];void 0===Q&&(Q=i.collisionCircleArrays[K]=new me);for(var $=0;$<I.circles.length;$+=4)Q.circles.push(I.circles[$+0]),Q.circles.push(I.circles[$+1]),Q.circles.push(I.circles[$+2]),Q.circles.push(I.collisionDetected?1:0)}i.placements[e.crossTileID]=new ge(T||k,A||M,S||o.justReloaded),r[e.crossTileID]=!0}};if(T)for(var S=o.getSortedSymbolIndexes(this.transform.angle),E=S.length-1;E>=0;--E){var C=S[E];A(o.symbolInstances.get(C),o.collisionArrays[C])}else for(var L=e.symbolInstanceStart;L<e.symbolInstanceEnd;L++)A(o.symbolInstances.get(L),o.collisionArrays[L]);if(n&&o.bucketInstanceId in this.collisionCircleArrays){var I=this.collisionCircleArrays[o.bucketInstanceId];t.invert(I.invProjMatrix,l),I.viewportMatrix=this.collisionIndex.getViewportMatrix()}o.justReloaded=!1},_e.prototype.markUsedJustification=function(e,r,n,i){var a;a=i===t.WritingMode.vertical?n.verticalPlacedTextSymbolIndex:{left:n.leftJustifiedTextSymbolIndex,center:n.centerJustifiedTextSymbolIndex,right:n.rightJustifiedTextSymbolIndex}[t.getAnchorJustification(r)];for(var o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex,n.verticalPlacedTextSymbolIndex];o<s.length;o+=1){var l=s[o];l>=0&&(e.text.placedSymbolArray.get(l).crossTileID=a>=0&&l!==a?0:n.crossTileID)}},_e.prototype.markUsedOrientation=function(e,r,n){for(var i=r===t.WritingMode.horizontal||r===t.WritingMode.horizontalOnly?r:0,a=r===t.WritingMode.vertical?r:0,o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex];o<s.length;o+=1)e.text.placedSymbolArray.get(s[o]).placedOrientation=i;n.verticalPlacedTextSymbolIndex&&(e.text.placedSymbolArray.get(n.verticalPlacedTextSymbolIndex).placedOrientation=a)},_e.prototype.commit=function(t){this.commitTime=t,this.zoomAtLastRecencyCheck=this.transform.zoom;var e=this.prevPlacement,r=!1;this.prevZoomAdjustment=e?e.zoomAdjustment(this.transform.zoom):0;var n=e?e.symbolFadeChange(t):1,i=e?e.opacities:{},a=e?e.variableOffsets:{},o=e?e.placedOrientations:{};for(var s in this.placements){var l=this.placements[s],c=i[s];c?(this.opacities[s]=new de(c,n,l.text,l.icon),r=r||l.text!==c.text.placed||l.icon!==c.icon.placed):(this.opacities[s]=new de(null,n,l.text,l.icon,l.skipFade),r=r||l.text||l.icon)}for(var u in i){var f=i[u];if(!this.opacities[u]){var h=new de(f,n,!1,!1);h.isHidden()||(this.opacities[u]=h,r=r||f.text.placed||f.icon.placed)}}for(var p in a)this.variableOffsets[p]||!this.opacities[p]||this.opacities[p].isHidden()||(this.variableOffsets[p]=a[p]);for(var d in o)this.placedOrientations[d]||!this.opacities[d]||this.opacities[d].isHidden()||(this.placedOrientations[d]=o[d]);r?this.lastPlacementChangeTime=t:\"number\"!=typeof this.lastPlacementChangeTime&&(this.lastPlacementChangeTime=e?e.lastPlacementChangeTime:t)},_e.prototype.updateLayerOpacities=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1){var a=i[n],o=a.getBucket(t);o&&a.latestFeatureIndex&&t.id===o.layerIds[0]&&this.updateBucketOpacities(o,r,a.collisionBoxArray)}},_e.prototype.updateBucketOpacities=function(e,r,n){var i=this;e.hasTextData()&&e.text.opacityVertexArray.clear(),e.hasIconData()&&e.icon.opacityVertexArray.clear(),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexArray.clear(),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexArray.clear();var a=e.layers[0].layout,o=new de(null,0,!1,!1,!0),s=a.get(\"text-allow-overlap\"),l=a.get(\"icon-allow-overlap\"),c=a.get(\"text-variable-anchor\"),u=\"map\"===a.get(\"text-rotation-alignment\"),f=\"map\"===a.get(\"text-pitch-alignment\"),h=\"none\"!==a.get(\"icon-text-fit\"),p=new de(null,0,s&&(l||!e.hasIconData()||a.get(\"icon-optional\")),l&&(s||!e.hasTextData()||a.get(\"text-optional\")),!0);!e.collisionArrays&&n&&(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData())&&e.deserializeCollisionBoxes(n);for(var d=function(t,e,r){for(var n=0;n<e/4;n++)t.opacityVertexArray.emplaceBack(r)},g=function(n){var a=e.symbolInstances.get(n),s=a.numHorizontalGlyphVertices,l=a.numVerticalGlyphVertices,g=a.crossTileID,m=i.opacities[g];r[g]?m=o:m||(i.opacities[g]=m=p),r[g]=!0;var v=a.numIconVertices>0,y=i.placedOrientations[a.crossTileID],x=y===t.WritingMode.vertical,b=y===t.WritingMode.horizontal||y===t.WritingMode.horizontalOnly;if(s>0||l>0){var _=Le(m.text);d(e.text,s,x?Ie:_),d(e.text,l,b?Ie:_);var w=m.text.isHidden();[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t){t>=0&&(e.text.placedSymbolArray.get(t).hidden=w||x?1:0)})),a.verticalPlacedTextSymbolIndex>=0&&(e.text.placedSymbolArray.get(a.verticalPlacedTextSymbolIndex).hidden=w||b?1:0);var T=i.variableOffsets[a.crossTileID];T&&i.markUsedJustification(e,T.anchor,a,y);var k=i.placedOrientations[a.crossTileID];k&&(i.markUsedJustification(e,\"left\",a,k),i.markUsedOrientation(e,k,a))}if(v){var M=Le(m.icon),A=!(h&&a.verticalPlacedIconSymbolIndex&&x);a.placedIconSymbolIndex>=0&&(d(e.icon,a.numIconVertices,A?M:Ie),e.icon.placedSymbolArray.get(a.placedIconSymbolIndex).hidden=m.icon.isHidden()),a.verticalPlacedIconSymbolIndex>=0&&(d(e.icon,a.numVerticalIconVertices,A?Ie:M),e.icon.placedSymbolArray.get(a.verticalPlacedIconSymbolIndex).hidden=m.icon.isHidden())}if(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData()){var S=e.collisionArrays[n];if(S){var E=new t.Point(0,0);if(S.textBox||S.verticalTextBox){var C=!0;if(c){var L=i.variableOffsets[g];L?(E=xe(L.anchor,L.width,L.height,L.textOffset,L.textBoxScale),u&&E._rotate(f?i.transform.angle:-i.transform.angle)):C=!1}S.textBox&&we(e.textCollisionBox.collisionVertexArray,m.text.placed,!C||x,E.x,E.y),S.verticalTextBox&&we(e.textCollisionBox.collisionVertexArray,m.text.placed,!C||b,E.x,E.y)}var I=Boolean(!b&&S.verticalIconBox);S.iconBox&&we(e.iconCollisionBox.collisionVertexArray,m.icon.placed,I,h?E.x:0,h?E.y:0),S.verticalIconBox&&we(e.iconCollisionBox.collisionVertexArray,m.icon.placed,!I,h?E.x:0,h?E.y:0)}}},m=0;m<e.symbolInstances.length;m++)g(m);if(e.sortFeatures(this.transform.angle),this.retainedQueryData[e.bucketInstanceId]&&(this.retainedQueryData[e.bucketInstanceId].featureSortOrder=e.featureSortOrder),e.hasTextData()&&e.text.opacityVertexBuffer&&e.text.opacityVertexBuffer.updateData(e.text.opacityVertexArray),e.hasIconData()&&e.icon.opacityVertexBuffer&&e.icon.opacityVertexBuffer.updateData(e.icon.opacityVertexArray),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexBuffer&&e.iconCollisionBox.collisionVertexBuffer.updateData(e.iconCollisionBox.collisionVertexArray),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexBuffer&&e.textCollisionBox.collisionVertexBuffer.updateData(e.textCollisionBox.collisionVertexArray),e.bucketInstanceId in this.collisionCircleArrays){var v=this.collisionCircleArrays[e.bucketInstanceId];e.placementInvProjMatrix=v.invProjMatrix,e.placementViewportMatrix=v.viewportMatrix,e.collisionCircleArray=v.circles,delete this.collisionCircleArrays[e.bucketInstanceId]}},_e.prototype.symbolFadeChange=function(t){return 0===this.fadeDuration?1:(t-this.commitTime)/this.fadeDuration+this.prevZoomAdjustment},_e.prototype.zoomAdjustment=function(t){return Math.max(0,(this.transform.zoom-t)/1.5)},_e.prototype.hasTransitions=function(t){return this.stale||t-this.lastPlacementChangeTime<this.fadeDuration},_e.prototype.stillRecent=function(t,e){var r=this.zoomAtLastRecencyCheck===e?1-this.zoomAdjustment(e):1;return this.zoomAtLastRecencyCheck=e,this.commitTime+this.fadeDuration*r>t},_e.prototype.setStale=function(){this.stale=!0};var Te=Math.pow(2,25),ke=Math.pow(2,24),Me=Math.pow(2,17),Ae=Math.pow(2,16),Se=Math.pow(2,9),Ee=Math.pow(2,8),Ce=Math.pow(2,1);function Le(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;var e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*Te+e*ke+r*Me+e*Ae+r*Se+e*Ee+r*Ce+e}var Ie=0,Pe=function(t){this._sortAcrossTiles=\"viewport-y\"!==t.layout.get(\"symbol-z-order\")&&void 0!==t.layout.get(\"symbol-sort-key\").constantOr(1),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};Pe.prototype.continuePlacement=function(t,e,r,n,i){for(var a=this._bucketParts;this._currentTileIndex<t.length;)if(e.getBucketParts(a,n,t[this._currentTileIndex],this._sortAcrossTiles),this._currentTileIndex++,i())return!0;for(this._sortAcrossTiles&&(this._sortAcrossTiles=!1,a.sort((function(t,e){return t.sortKey-e.sortKey})));this._currentPartIndex<a.length;)if(e.placeLayerBucketPart(a[this._currentPartIndex],this._seenCrossTileIDs,r),this._currentPartIndex++,i())return!0;return!1};var ze=function(t,e,r,n,i,a,o){this.placement=new _e(t,i,a,o),this._currentPlacementIndex=e.length-1,this._forceFullPlacement=r,this._showCollisionBoxes=n,this._done=!1};ze.prototype.isDone=function(){return this._done},ze.prototype.continuePlacement=function(e,r,n){for(var i=this,a=t.browser.now(),o=function(){var e=t.browser.now()-a;return!i._forceFullPlacement&&e>2};this._currentPlacementIndex>=0;){var s=r[e[this._currentPlacementIndex]],l=this.placement.collisionIndex.transform.zoom;if(\"symbol\"===s.type&&(!s.minzoom||s.minzoom<=l)&&(!s.maxzoom||s.maxzoom>l)){if(this._inProgressLayer||(this._inProgressLayer=new Pe(s)),this._inProgressLayer.continuePlacement(n[s.source],this.placement,this._showCollisionBoxes,s,o))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},ze.prototype.commit=function(t){return this.placement.commit(t),this.placement};var Oe=512/t.EXTENT/2,De=function(t,e,r){this.tileID=t,this.indexedSymbolInstances={},this.bucketInstanceId=r;for(var n=0;n<e.length;n++){var i=e.get(n),a=i.key;this.indexedSymbolInstances[a]||(this.indexedSymbolInstances[a]=[]),this.indexedSymbolInstances[a].push({crossTileID:i.crossTileID,coord:this.getScaledCoordinates(i,t)})}};De.prototype.getScaledCoordinates=function(e,r){var n=Oe/Math.pow(2,r.canonical.z-this.tileID.canonical.z);return{x:Math.floor((r.canonical.x*t.EXTENT+e.anchorX)*n),y:Math.floor((r.canonical.y*t.EXTENT+e.anchorY)*n)}},De.prototype.findMatches=function(t,e,r){for(var n=this.tileID.canonical.z<e.canonical.z?1:Math.pow(2,this.tileID.canonical.z-e.canonical.z),i=0;i<t.length;i++){var a=t.get(i);if(!a.crossTileID){var o=this.indexedSymbolInstances[a.key];if(o)for(var s=this.getScaledCoordinates(a,e),l=0,c=o;l<c.length;l+=1){var u=c[l];if(Math.abs(u.coord.x-s.x)<=n&&Math.abs(u.coord.y-s.y)<=n&&!r[u.crossTileID]){r[u.crossTileID]=!0,a.crossTileID=u.crossTileID;break}}}}};var Re=function(){this.maxCrossTileID=0};Re.prototype.generate=function(){return++this.maxCrossTileID};var Fe=function(){this.indexes={},this.usedCrossTileIDs={},this.lng=0};Fe.prototype.handleWrapJump=function(t){var e=Math.round((t-this.lng)/360);if(0!==e)for(var r in this.indexes){var n=this.indexes[r],i={};for(var a in n){var o=n[a];o.tileID=o.tileID.unwrapTo(o.tileID.wrap+e),i[o.tileID.key]=o}this.indexes[r]=i}this.lng=t},Fe.prototype.addBucket=function(t,e,r){if(this.indexes[t.overscaledZ]&&this.indexes[t.overscaledZ][t.key]){if(this.indexes[t.overscaledZ][t.key].bucketInstanceId===e.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(t.overscaledZ,this.indexes[t.overscaledZ][t.key])}for(var n=0;n<e.symbolInstances.length;n++)e.symbolInstances.get(n).crossTileID=0;this.usedCrossTileIDs[t.overscaledZ]||(this.usedCrossTileIDs[t.overscaledZ]={});var i=this.usedCrossTileIDs[t.overscaledZ];for(var a in this.indexes){var o=this.indexes[a];if(Number(a)>t.overscaledZ)for(var s in o){var l=o[s];l.tileID.isChildOf(t)&&l.findMatches(e.symbolInstances,t,i)}else{var c=o[t.scaledTo(Number(a)).key];c&&c.findMatches(e.symbolInstances,t,i)}}for(var u=0;u<e.symbolInstances.length;u++){var f=e.symbolInstances.get(u);f.crossTileID||(f.crossTileID=r.generate(),i[f.crossTileID]=!0)}return void 0===this.indexes[t.overscaledZ]&&(this.indexes[t.overscaledZ]={}),this.indexes[t.overscaledZ][t.key]=new De(t,e.symbolInstances,e.bucketInstanceId),!0},Fe.prototype.removeBucketCrossTileIDs=function(t,e){for(var r in e.indexedSymbolInstances)for(var n=0,i=e.indexedSymbolInstances[r];n<i.length;n+=1)delete this.usedCrossTileIDs[t][i[n].crossTileID]},Fe.prototype.removeStaleBuckets=function(t){var e=!1;for(var r in this.indexes){var n=this.indexes[r];for(var i in n)t[n[i].bucketInstanceId]||(this.removeBucketCrossTileIDs(r,n[i]),delete n[i],e=!0)}return e};var Be=function(){this.layerIndexes={},this.crossTileIDs=new Re,this.maxBucketInstanceId=0,this.bucketsInCurrentPlacement={}};Be.prototype.addLayer=function(t,e,r){var n=this.layerIndexes[t.id];void 0===n&&(n=this.layerIndexes[t.id]=new Fe);var i=!1,a={};n.handleWrapJump(r);for(var o=0,s=e;o<s.length;o+=1){var l=s[o],c=l.getBucket(t);c&&t.id===c.layerIds[0]&&(c.bucketInstanceId||(c.bucketInstanceId=++this.maxBucketInstanceId),n.addBucket(l.tileID,c,this.crossTileIDs)&&(i=!0),a[c.bucketInstanceId]=!0)}return n.removeStaleBuckets(a)&&(i=!0),i},Be.prototype.pruneUnusedLayers=function(t){var e={};for(var r in t.forEach((function(t){e[t]=!0})),this.layerIndexes)e[r]||delete this.layerIndexes[r]};var Ne=function(e,r){return t.emitValidationErrors(e,r&&r.filter((function(t){return\"source.canvas\"!==t.identifier})))},je=t.pick(Ut,[\"addLayer\",\"removeLayer\",\"setPaintProperty\",\"setLayoutProperty\",\"setFilter\",\"addSource\",\"removeSource\",\"setLayerZoomRange\",\"setLight\",\"setTransition\",\"setGeoJSONSourceData\"]),Ue=t.pick(Ut,[\"setCenter\",\"setZoom\",\"setBearing\",\"setPitch\"]),Ve=function(){var e={},r=t.styleSpec.$version;for(var n in t.styleSpec.$root){var i,a=t.styleSpec.$root[n];a.required&&null!=(i=\"version\"===n?r:\"array\"===a.type?[]:{})&&(e[n]=i)}return e}(),qe=function(e){function r(n,i){var a=this;void 0===i&&(i={}),e.call(this),this.map=n,this.dispatcher=new k(Bt(),this),this.imageManager=new h,this.imageManager.setEventedParent(this),this.glyphManager=new x(n._requestManager,i.localIdeographFontFamily),this.lineAtlas=new T(256,512),this.crossTileSymbolIndex=new Be,this._layers={},this._serializedLayers={},this._order=[],this.sourceCaches={},this.zoomHistory=new t.ZoomHistory,this._loaded=!1,this._availableImages=[],this._resetUpdates(),this.dispatcher.broadcast(\"setReferrer\",t.getReferrer());var o=this;this._rtlTextPluginCallback=r.registerForPluginStateChange((function(e){o.dispatcher.broadcast(\"syncRTLPluginState\",{pluginStatus:e.pluginStatus,pluginURL:e.pluginURL},(function(e,r){if(t.triggerPluginCompletionEvent(e),r&&r.every((function(t){return t})))for(var n in o.sourceCaches)o.sourceCaches[n].reload()}))})),this.on(\"data\",(function(t){if(\"source\"===t.dataType&&\"metadata\"===t.sourceDataType){var e=a.sourceCaches[t.sourceId];if(e){var r=e.getSource();if(r&&r.vectorLayerIds)for(var n in a._layers){var i=a._layers[n];i.source===r.id&&a._validateLayer(i)}}}}))}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.loadURL=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"}));var i=\"boolean\"==typeof r.validate?r.validate:!t.isMapboxURL(e);e=this.map._requestManager.normalizeStyleURL(e,r.accessToken);var a=this.map._requestManager.transformRequest(e,t.ResourceType.Style);this._request=t.getJSON(a,(function(e,r){n._request=null,e?n.fire(new t.ErrorEvent(e)):r&&n._load(r,i)}))},r.prototype.loadJSON=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._request=t.browser.frame((function(){n._request=null,n._load(e,!1!==r.validate)}))},r.prototype.loadEmpty=function(){this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._load(Ve,!1)},r.prototype._load=function(e,r){if(!r||!Ne(this,t.validateStyle(e))){for(var n in this._loaded=!0,this.stylesheet=e,e.sources)this.addSource(n,e.sources[n],{validate:!1});e.sprite?this._loadSprite(e.sprite):this.imageManager.setLoaded(!0),this.glyphManager.setURL(e.glyphs);var i=jt(this.stylesheet.layers);this._order=i.map((function(t){return t.id})),this._layers={},this._serializedLayers={};for(var a=0,o=i;a<o.length;a+=1){var s=o[a];(s=t.createStyleLayer(s)).setEventedParent(this,{layer:{id:s.id}}),this._layers[s.id]=s,this._serializedLayers[s.id]=s.serialize()}this.dispatcher.broadcast(\"setLayers\",this._serializeLayers(this._order)),this.light=new w(this.stylesheet.light),this.fire(new t.Event(\"data\",{dataType:\"style\"})),this.fire(new t.Event(\"style.load\"))}},r.prototype._loadSprite=function(e){var r=this;this._spriteRequest=function(e,r,n){var i,a,o,s=t.browser.devicePixelRatio>1?\"@2x\":\"\",l=t.getJSON(r.transformRequest(r.normalizeSpriteURL(e,s,\".json\"),t.ResourceType.SpriteJSON),(function(t,e){l=null,o||(o=t,i=e,u())})),c=t.getImage(r.transformRequest(r.normalizeSpriteURL(e,s,\".png\"),t.ResourceType.SpriteImage),(function(t,e){c=null,o||(o=t,a=e,u())}));function u(){if(o)n(o);else if(i&&a){var e=t.browser.getImageData(a),r={};for(var s in i){var l=i[s],c=l.width,u=l.height,f=l.x,h=l.y,p=l.sdf,d=l.pixelRatio,g=l.stretchX,m=l.stretchY,v=l.content,y=new t.RGBAImage({width:c,height:u});t.RGBAImage.copy(e,y,{x:f,y:h},{x:0,y:0},{width:c,height:u}),r[s]={data:y,pixelRatio:d,sdf:p,stretchX:g,stretchY:m,content:v}}n(null,r)}}return{cancel:function(){l&&(l.cancel(),l=null),c&&(c.cancel(),c=null)}}}(e,this.map._requestManager,(function(e,n){if(r._spriteRequest=null,e)r.fire(new t.ErrorEvent(e));else if(n)for(var i in n)r.imageManager.addImage(i,n[i]);r.imageManager.setLoaded(!0),r._availableImages=r.imageManager.listImages(),r.dispatcher.broadcast(\"setImages\",r._availableImages),r.fire(new t.Event(\"data\",{dataType:\"style\"}))}))},r.prototype._validateLayer=function(e){var r=this.sourceCaches[e.source];if(r){var n=e.sourceLayer;if(n){var i=r.getSource();(\"geojson\"===i.type||i.vectorLayerIds&&-1===i.vectorLayerIds.indexOf(n))&&this.fire(new t.ErrorEvent(new Error('Source layer \"'+n+'\" does not exist on source \"'+i.id+'\" as specified by style layer \"'+e.id+'\"')))}}},r.prototype.loaded=function(){if(!this._loaded)return!1;if(Object.keys(this._updatedSources).length)return!1;for(var t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()},r.prototype._serializeLayers=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=this._layers[n[r]];\"custom\"!==i.type&&e.push(i.serialize())}return e},r.prototype.hasTransitions=function(){if(this.light&&this.light.hasTransition())return!0;for(var t in this.sourceCaches)if(this.sourceCaches[t].hasTransition())return!0;for(var e in this._layers)if(this._layers[e].hasTransition())return!0;return!1},r.prototype._checkLoaded=function(){if(!this._loaded)throw new Error(\"Style is not done loading\")},r.prototype.update=function(e){if(this._loaded){var r=this._changed;if(this._changed){var n=Object.keys(this._updatedLayers),i=Object.keys(this._removedLayers);for(var a in(n.length||i.length)&&this._updateWorkerLayers(n,i),this._updatedSources){var o=this._updatedSources[a];\"reload\"===o?this._reloadSource(a):\"clear\"===o&&this._clearSource(a)}for(var s in this._updateTilesForChangedImages(),this._updatedPaintProps)this._layers[s].updateTransitions(e);this.light.updateTransitions(e),this._resetUpdates()}for(var l in this.sourceCaches)this.sourceCaches[l].used=!1;for(var c=0,u=this._order;c<u.length;c+=1){var f=this._layers[u[c]];f.recalculate(e,this._availableImages),!f.isHidden(e.zoom)&&f.source&&(this.sourceCaches[f.source].used=!0)}this.light.recalculate(e),this.z=e.zoom,r&&this.fire(new t.Event(\"data\",{dataType:\"style\"}))}},r.prototype._updateTilesForChangedImages=function(){var t=Object.keys(this._changedImages);if(t.length){for(var e in this.sourceCaches)this.sourceCaches[e].reloadTilesForDependencies([\"icons\",\"patterns\"],t);this._changedImages={}}},r.prototype._updateWorkerLayers=function(t,e){this.dispatcher.broadcast(\"updateLayers\",{layers:this._serializeLayers(t),removedIds:e})},r.prototype._resetUpdates=function(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={},this._changedImages={}},r.prototype.setState=function(e){var r=this;if(this._checkLoaded(),Ne(this,t.validateStyle(e)))return!1;(e=t.clone$1(e)).layers=jt(e.layers);var n=function(e,r){if(!e)return[{command:Ut.setStyle,args:[r]}];var n=[];try{if(!t.deepEqual(e.version,r.version))return[{command:Ut.setStyle,args:[r]}];t.deepEqual(e.center,r.center)||n.push({command:Ut.setCenter,args:[r.center]}),t.deepEqual(e.zoom,r.zoom)||n.push({command:Ut.setZoom,args:[r.zoom]}),t.deepEqual(e.bearing,r.bearing)||n.push({command:Ut.setBearing,args:[r.bearing]}),t.deepEqual(e.pitch,r.pitch)||n.push({command:Ut.setPitch,args:[r.pitch]}),t.deepEqual(e.sprite,r.sprite)||n.push({command:Ut.setSprite,args:[r.sprite]}),t.deepEqual(e.glyphs,r.glyphs)||n.push({command:Ut.setGlyphs,args:[r.glyphs]}),t.deepEqual(e.transition,r.transition)||n.push({command:Ut.setTransition,args:[r.transition]}),t.deepEqual(e.light,r.light)||n.push({command:Ut.setLight,args:[r.light]});var i={},a=[];!function(e,r,n,i){var a;for(a in r=r||{},e=e||{})e.hasOwnProperty(a)&&(r.hasOwnProperty(a)||qt(a,n,i));for(a in r)r.hasOwnProperty(a)&&(e.hasOwnProperty(a)?t.deepEqual(e[a],r[a])||(\"geojson\"===e[a].type&&\"geojson\"===r[a].type&&Gt(e,r,a)?n.push({command:Ut.setGeoJSONSourceData,args:[a,r[a].data]}):Ht(a,r,n,i)):Vt(a,r,n))}(e.sources,r.sources,a,i);var o=[];e.layers&&e.layers.forEach((function(t){i[t.source]?n.push({command:Ut.removeLayer,args:[t.id]}):o.push(t)})),n=n.concat(a),function(e,r,n){r=r||[];var i,a,o,s,l,c,u,f=(e=e||[]).map(Wt),h=r.map(Wt),p=e.reduce(Xt,{}),d=r.reduce(Xt,{}),g=f.slice(),m=Object.create(null);for(i=0,a=0;i<f.length;i++)d.hasOwnProperty(o=f[i])?a++:(n.push({command:Ut.removeLayer,args:[o]}),g.splice(g.indexOf(o,a),1));for(i=0,a=0;i<h.length;i++)g[g.length-1-i]!==(o=h[h.length-1-i])&&(p.hasOwnProperty(o)?(n.push({command:Ut.removeLayer,args:[o]}),g.splice(g.lastIndexOf(o,g.length-a),1)):a++,n.push({command:Ut.addLayer,args:[d[o],c=g[g.length-i]]}),g.splice(g.length-i,0,o),m[o]=!0);for(i=0;i<h.length;i++)if(s=p[o=h[i]],l=d[o],!m[o]&&!t.deepEqual(s,l))if(t.deepEqual(s.source,l.source)&&t.deepEqual(s[\"source-layer\"],l[\"source-layer\"])&&t.deepEqual(s.type,l.type)){for(u in Yt(s.layout,l.layout,n,o,null,Ut.setLayoutProperty),Yt(s.paint,l.paint,n,o,null,Ut.setPaintProperty),t.deepEqual(s.filter,l.filter)||n.push({command:Ut.setFilter,args:[o,l.filter]}),t.deepEqual(s.minzoom,l.minzoom)&&t.deepEqual(s.maxzoom,l.maxzoom)||n.push({command:Ut.setLayerZoomRange,args:[o,l.minzoom,l.maxzoom]}),s)s.hasOwnProperty(u)&&\"layout\"!==u&&\"paint\"!==u&&\"filter\"!==u&&\"metadata\"!==u&&\"minzoom\"!==u&&\"maxzoom\"!==u&&(0===u.indexOf(\"paint.\")?Yt(s[u],l[u],n,o,u.slice(6),Ut.setPaintProperty):t.deepEqual(s[u],l[u])||n.push({command:Ut.setLayerProperty,args:[o,u,l[u]]}));for(u in l)l.hasOwnProperty(u)&&!s.hasOwnProperty(u)&&\"layout\"!==u&&\"paint\"!==u&&\"filter\"!==u&&\"metadata\"!==u&&\"minzoom\"!==u&&\"maxzoom\"!==u&&(0===u.indexOf(\"paint.\")?Yt(s[u],l[u],n,o,u.slice(6),Ut.setPaintProperty):t.deepEqual(s[u],l[u])||n.push({command:Ut.setLayerProperty,args:[o,u,l[u]]}))}else n.push({command:Ut.removeLayer,args:[o]}),c=g[g.lastIndexOf(o)+1],n.push({command:Ut.addLayer,args:[l,c]})}(o,r.layers,n)}catch(t){console.warn(\"Unable to compute style diff:\",t),n=[{command:Ut.setStyle,args:[r]}]}return n}(this.serialize(),e).filter((function(t){return!(t.command in Ue)}));if(0===n.length)return!1;var i=n.filter((function(t){return!(t.command in je)}));if(i.length>0)throw new Error(\"Unimplemented: \"+i.map((function(t){return t.command})).join(\", \")+\".\");return n.forEach((function(t){\"setTransition\"!==t.command&&r[t.command].apply(r,t.args)})),this.stylesheet=e,!0},r.prototype.addImage=function(e,r){if(this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"An image with this name already exists.\")));this.imageManager.addImage(e,r),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.updateImage=function(t,e){this.imageManager.updateImage(t,e)},r.prototype.getImage=function(t){return this.imageManager.getImage(t)},r.prototype.removeImage=function(e){if(!this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"No image with this name exists.\")));this.imageManager.removeImage(e),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},r.prototype.addSource=function(e,r,n){var i=this;if(void 0===n&&(n={}),this._checkLoaded(),void 0!==this.sourceCaches[e])throw new Error(\"There is already a source with this ID\");if(!r.type)throw new Error(\"The type property must be defined, but the only the following properties were given: \"+Object.keys(r).join(\", \")+\".\");if(!([\"vector\",\"raster\",\"geojson\",\"video\",\"image\"].indexOf(r.type)>=0&&this._validate(t.validateStyle.source,\"sources.\"+e,r,null,n))){this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);var a=this.sourceCaches[e]=new Lt(e,r,this.dispatcher);a.style=this,a.setEventedParent(this,(function(){return{isSourceLoaded:i.loaded(),source:a.serialize(),sourceId:e}})),a.onAdd(this.map),this._changed=!0}},r.prototype.removeSource=function(e){if(this._checkLoaded(),void 0===this.sourceCaches[e])throw new Error(\"There is no source with this ID\");for(var r in this._layers)if(this._layers[r].source===e)return this.fire(new t.ErrorEvent(new Error('Source \"'+e+'\" cannot be removed while layer \"'+r+'\" is using it.')));var n=this.sourceCaches[e];delete this.sourceCaches[e],delete this._updatedSources[e],n.fire(new t.Event(\"data\",{sourceDataType:\"metadata\",dataType:\"source\",sourceId:e})),n.setEventedParent(null),n.clearTiles(),n.onRemove&&n.onRemove(this.map),this._changed=!0},r.prototype.setGeoJSONSourceData=function(t,e){this._checkLoaded(),this.sourceCaches[t].getSource().setData(e),this._changed=!0},r.prototype.getSource=function(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()},r.prototype.addLayer=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=e.id;if(this.getLayer(i))this.fire(new t.ErrorEvent(new Error('Layer with id \"'+i+'\" already exists on this map')));else{var a;if(\"custom\"===e.type){if(Ne(this,t.validateCustomStyleLayer(e)))return;a=t.createStyleLayer(e)}else{if(\"object\"==typeof e.source&&(this.addSource(i,e.source),e=t.clone$1(e),e=t.extend(e,{source:i})),this._validate(t.validateStyle.layer,\"layers.\"+i,e,{arrayIndex:-1},n))return;a=t.createStyleLayer(e),this._validateLayer(a),a.setEventedParent(this,{layer:{id:i}}),this._serializedLayers[a.id]=a.serialize()}var o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.')));else{if(this._order.splice(o,0,i),this._layerOrderChanged=!0,this._layers[i]=a,this._removedLayers[i]&&a.source&&\"custom\"!==a.type){var s=this._removedLayers[i];delete this._removedLayers[i],s.type!==a.type?this._updatedSources[a.source]=\"clear\":(this._updatedSources[a.source]=\"reload\",this.sourceCaches[a.source].pause())}this._updateLayer(a),a.onAdd&&a.onAdd(this.map)}}},r.prototype.moveLayer=function(e,r){if(this._checkLoaded(),this._changed=!0,this._layers[e]){if(e!==r){var n=this._order.indexOf(e);this._order.splice(n,1);var i=r?this._order.indexOf(r):this._order.length;r&&-1===i?this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.'))):(this._order.splice(i,0,e),this._layerOrderChanged=!0)}}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be moved.\")))},r.prototype.removeLayer=function(e){this._checkLoaded();var r=this._layers[e];if(r){r.setEventedParent(null);var n=this._order.indexOf(e);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[e]=r,delete this._layers[e],delete this._serializedLayers[e],delete this._updatedLayers[e],delete this._updatedPaintProps[e],r.onRemove&&r.onRemove(this.map)}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be removed.\")))},r.prototype.getLayer=function(t){return this._layers[t]},r.prototype.hasLayer=function(t){return t in this._layers},r.prototype.setLayerZoomRange=function(e,r,n){this._checkLoaded();var i=this.getLayer(e);i?i.minzoom===r&&i.maxzoom===n||(null!=r&&(i.minzoom=r),null!=n&&(i.maxzoom=n),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot have zoom extent.\")))},r.prototype.setFilter=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=this.getLayer(e);if(i){if(!t.deepEqual(i.filter,r))return null==r?(i.filter=void 0,void this._updateLayer(i)):void(this._validate(t.validateStyle.filter,\"layers.\"+i.id+\".filter\",r,null,n)||(i.filter=t.clone$1(r),this._updateLayer(i)))}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be filtered.\")))},r.prototype.getFilter=function(e){return t.clone$1(this.getLayer(e).filter)},r.prototype.setLayoutProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getLayoutProperty(r),n)||(a.setLayoutProperty(r,n,i),this._updateLayer(a)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getLayoutProperty=function(e,r){var n=this.getLayer(e);if(n)return n.getLayoutProperty(r);this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style.\")))},r.prototype.setPaintProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getPaintProperty(r),n)||(a.setPaintProperty(r,n,i)&&this._updateLayer(a),this._changed=!0,this._updatedPaintProps[e]=!0):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getPaintProperty=function(t,e){return this.getLayer(t).getPaintProperty(e)},r.prototype.setFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=e.sourceLayer,a=this.sourceCaches[n];if(void 0!==a){var o=a.getSource().type;\"geojson\"===o&&i?this.fire(new t.ErrorEvent(new Error(\"GeoJSON sources cannot have a sourceLayer parameter.\"))):\"vector\"!==o||i?(void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),a.setFeatureState(i,e.id,r)):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.removeFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=this.sourceCaches[n];if(void 0!==i){var a=i.getSource().type,o=\"vector\"===a?e.sourceLayer:void 0;\"vector\"!==a||o?r&&\"string\"!=typeof e.id&&\"number\"!=typeof e.id?this.fire(new t.ErrorEvent(new Error(\"A feature id is requred to remove its specific state property.\"))):i.removeFeatureState(o,e.id,r):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.getFeatureState=function(e){this._checkLoaded();var r=e.source,n=e.sourceLayer,i=this.sourceCaches[r];if(void 0!==i){if(\"vector\"!==i.getSource().type||n)return void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),i.getFeatureState(n,e.id);this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+r+\"' does not exist in the map's style.\")))},r.prototype.getTransition=function(){return t.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},r.prototype.serialize=function(){return t.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:t.mapObject(this.sourceCaches,(function(t){return t.serialize()})),layers:this._serializeLayers(this._order)},(function(t){return void 0!==t}))},r.prototype._updateLayer=function(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&\"raster\"!==this.sourceCaches[t.source].getSource().type&&(this._updatedSources[t.source]=\"reload\",this.sourceCaches[t.source].pause()),this._changed=!0},r.prototype._flattenAndSortRenderedFeatures=function(t){for(var e=this,r=function(t){return\"fill-extrusion\"===e._layers[t].type},n={},i=[],a=this._order.length-1;a>=0;a--){var o=this._order[a];if(r(o)){n[o]=a;for(var s=0,l=t;s<l.length;s+=1){var c=l[s][o];if(c)for(var u=0,f=c;u<f.length;u+=1)i.push(f[u])}}}i.sort((function(t,e){return e.intersectionZ-t.intersectionZ}));for(var h=[],p=this._order.length-1;p>=0;p--){var d=this._order[p];if(r(d))for(var g=i.length-1;g>=0;g--){var m=i[g].feature;if(n[m.layer.id]<p)break;h.push(m),i.pop()}else for(var v=0,y=t;v<y.length;v+=1){var x=y[v][d];if(x)for(var b=0,_=x;b<_.length;b+=1)h.push(_[b].feature)}}return h},r.prototype.queryRenderedFeatures=function(e,r,n){r&&r.filter&&this._validate(t.validateStyle.filter,\"queryRenderedFeatures.filter\",r.filter,null,r);var i={};if(r&&r.layers){if(!Array.isArray(r.layers))return this.fire(new t.ErrorEvent(new Error(\"parameters.layers must be an Array.\"))),[];for(var a=0,o=r.layers;a<o.length;a+=1){var s=o[a],l=this._layers[s];if(!l)return this.fire(new t.ErrorEvent(new Error(\"The layer '\"+s+\"' does not exist in the map's style and cannot be queried for features.\"))),[];i[l.source]=!0}}var c=[];for(var u in r.availableImages=this._availableImages,this.sourceCaches)r.layers&&!i[u]||c.push(F(this.sourceCaches[u],this._layers,this._serializedLayers,e,r,n));return this.placement&&c.push(function(t,e,r,n,i,a,o){for(var s={},l=a.queryRenderedSymbols(n),c=[],u=0,f=Object.keys(l).map(Number);u<f.length;u+=1)c.push(o[f[u]]);c.sort(B);for(var h=function(){var r=d[p],n=r.featureIndex.lookupSymbolFeatures(l[r.bucketInstanceId],e,r.bucketIndex,r.sourceLayerIndex,i.filter,i.layers,i.availableImages,t);for(var a in n){var o=s[a]=s[a]||[],c=n[a];c.sort((function(t,e){var n=r.featureSortOrder;if(n){var i=n.indexOf(t.featureIndex);return n.indexOf(e.featureIndex)-i}return e.featureIndex-t.featureIndex}));for(var u=0,f=c;u<f.length;u+=1)o.push(f[u])}},p=0,d=c;p<d.length;p+=1)h();var g=function(e){s[e].forEach((function(n){var i=n.feature,a=r[t[e].source].getFeatureState(i.layer[\"source-layer\"],i.id);i.source=i.layer.source,i.layer[\"source-layer\"]&&(i.sourceLayer=i.layer[\"source-layer\"]),i.state=a}))};for(var m in s)g(m);return s}(this._layers,this._serializedLayers,this.sourceCaches,e,r,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenAndSortRenderedFeatures(c)},r.prototype.querySourceFeatures=function(e,r){r&&r.filter&&this._validate(t.validateStyle.filter,\"querySourceFeatures.filter\",r.filter,null,r);var n=this.sourceCaches[e];return n?function(t,e){for(var r=t.getRenderableIds().map((function(e){return t.getTileByID(e)})),n=[],i={},a=0;a<r.length;a++){var o=r[a],s=o.tileID.canonical.key;i[s]||(i[s]=!0,o.querySourceFeatures(n,e))}return n}(n,r):[]},r.prototype.addSourceType=function(t,e,n){return r.getSourceType(t)?n(new Error('A source type called \"'+t+'\" already exists.')):(r.setSourceType(t,e),e.workerSourceURL?void this.dispatcher.broadcast(\"loadWorkerSource\",{name:t,url:e.workerSourceURL},n):n(null,null))},r.prototype.getLight=function(){return this.light.getLight()},r.prototype.setLight=function(e,r){void 0===r&&(r={}),this._checkLoaded();var n=this.light.getLight(),i=!1;for(var a in e)if(!t.deepEqual(e[a],n[a])){i=!0;break}if(i){var o={now:t.browser.now(),transition:t.extend({duration:300,delay:0},this.stylesheet.transition)};this.light.setLight(e,r),this.light.updateTransitions(o)}},r.prototype._validate=function(e,r,n,i,a){return void 0===a&&(a={}),(!a||!1!==a.validate)&&Ne(this,e.call(t.validateStyle,t.extend({key:r,style:this.serialize(),value:n,styleSpec:t.styleSpec},i)))},r.prototype._remove=function(){for(var e in this._request&&(this._request.cancel(),this._request=null),this._spriteRequest&&(this._spriteRequest.cancel(),this._spriteRequest=null),t.evented.off(\"pluginStateChange\",this._rtlTextPluginCallback),this._layers)this._layers[e].setEventedParent(null);for(var r in this.sourceCaches)this.sourceCaches[r].clearTiles(),this.sourceCaches[r].setEventedParent(null);this.imageManager.setEventedParent(null),this.setEventedParent(null),this.dispatcher.remove()},r.prototype._clearSource=function(t){this.sourceCaches[t].clearTiles()},r.prototype._reloadSource=function(t){this.sourceCaches[t].resume(),this.sourceCaches[t].reload()},r.prototype._updateSources=function(t){for(var e in this.sourceCaches)this.sourceCaches[e].update(t)},r.prototype._generateCollisionBoxes=function(){for(var t in this.sourceCaches)this._reloadSource(t)},r.prototype._updatePlacement=function(e,r,n,i,a){void 0===a&&(a=!1);for(var o=!1,s=!1,l={},c=0,u=this._order;c<u.length;c+=1){var f=this._layers[u[c]];if(\"symbol\"===f.type){if(!l[f.source]){var h=this.sourceCaches[f.source];l[f.source]=h.getRenderableIds(!0).map((function(t){return h.getTileByID(t)})).sort((function(t,e){return e.tileID.overscaledZ-t.tileID.overscaledZ||(t.tileID.isLessThan(e.tileID)?-1:1)}))}var p=this.crossTileSymbolIndex.addLayer(f,l[f.source],e.center.lng);o=o||p}}if(this.crossTileSymbolIndex.pruneUnusedLayers(this._order),((a=a||this._layerOrderChanged||0===n)||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(t.browser.now(),e.zoom))&&(this.pauseablePlacement=new ze(e,this._order,a,r,n,i,this.placement),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,l),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(t.browser.now()),s=!0),o&&this.pauseablePlacement.placement.setStale()),s||o)for(var d=0,g=this._order;d<g.length;d+=1){var m=this._layers[g[d]];\"symbol\"===m.type&&this.placement.updateLayerOpacities(m,l[m.source])}return!this.pauseablePlacement.isDone()||this.placement.hasTransitions(t.browser.now())},r.prototype._releaseSymbolFadeTiles=function(){for(var t in this.sourceCaches)this.sourceCaches[t].releaseSymbolFadeTiles()},r.prototype.getImages=function(t,e,r){this.imageManager.getImages(e.icons,r),this._updateTilesForChangedImages();var n=this.sourceCaches[e.source];n&&n.setDependencies(e.tileID.key,e.type,e.icons)},r.prototype.getGlyphs=function(t,e,r){this.glyphManager.getGlyphs(e.stacks,r)},r.prototype.getResource=function(e,r,n){return t.makeRequest(r,n)},r}(t.Evented);qe.getSourceType=function(t){return D[t]},qe.setSourceType=function(t,e){D[t]=e},qe.registerForPluginStateChange=t.registerForPluginStateChange;var He=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2}]),Ge=vr(\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\",\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\\nvec2 unpack_float(const float packedValue) {int packedIntValue=int(packedValue);int v0=packedIntValue/256;return vec2(v0,packedIntValue-v0*256);}vec2 unpack_opacity(const float packedOpacity) {int intOpacity=int(packedOpacity)/2;return vec2(float(intOpacity)/127.0,mod(packedOpacity,2.0));}vec4 decode_color(const vec2 encodedColor) {return vec4(unpack_float(encodedColor[0])/255.0,unpack_float(encodedColor[1])/255.0\\n);}float unpack_mix_vec2(const vec2 packedValue,const float t) {return mix(packedValue[0],packedValue[1],t);}vec4 unpack_mix_color(const vec4 packedColors,const float t) {vec4 minColor=decode_color(vec2(packedColors[0],packedColors[1]));vec4 maxColor=decode_color(vec2(packedColors[2],packedColors[3]));return mix(minColor,maxColor,t);}vec2 get_pattern_pos(const vec2 pixel_coord_upper,const vec2 pixel_coord_lower,const vec2 pattern_size,const float tile_units_to_pixels,const vec2 pos) {vec2 offset=mod(mod(mod(pixel_coord_upper,pattern_size)*256.0,pattern_size)*256.0+pixel_coord_lower,pattern_size);return (tile_units_to_pixels*pos+offset)/pattern_size;}\"),Ye=vr(\"uniform vec4 u_color;uniform float u_opacity;void main() {gl_FragColor=u_color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),We=vr(\"uniform vec2 u_pattern_tl_a;uniform vec2 u_pattern_br_a;uniform vec2 u_pattern_tl_b;uniform vec2 u_pattern_br_b;uniform vec2 u_texsize;uniform float u_mix;uniform float u_opacity;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(u_pattern_tl_a/u_texsize,u_pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(u_pattern_tl_b/u_texsize,u_pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_mix)*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pattern_size_a;uniform vec2 u_pattern_size_b;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_scale_a;uniform float u_scale_b;uniform float u_tile_units_to_pixels;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_a*u_pattern_size_a,u_tile_units_to_pixels,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_b*u_pattern_size_b,u_tile_units_to_pixels,a_pos);}\"),Xe=vr(\"varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=v_data.xy;float extrude_length=length(extrude);lowp float antialiasblur=v_data.z;float antialiased_blur=-max(blur,antialiasblur);float opacity_t=smoothstep(0.0,antialiased_blur,extrude_length-1.0);float color_t=stroke_width < 0.01 ? 0.0 : smoothstep(antialiased_blur,0.0,extrude_length-radius/(radius+stroke_width));gl_FragColor=opacity_t*mix(color*opacity,stroke_color*stroke_opacity,color_t);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform bool u_scale_with_map;uniform bool u_pitch_with_map;uniform vec2 u_extrude_scale;uniform lowp float u_device_pixel_ratio;uniform highp float u_camera_to_center_distance;attribute vec2 a_pos;varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main(void) {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=vec2(mod(a_pos,2.0)*2.0-1.0);vec2 circle_center=floor(a_pos*0.5);if (u_pitch_with_map) {vec2 corner_position=circle_center;if (u_scale_with_map) {corner_position+=extrude*(radius+stroke_width)*u_extrude_scale;} else {vec4 projected_center=u_matrix*vec4(circle_center,0,1);corner_position+=extrude*(radius+stroke_width)*u_extrude_scale*(projected_center.w/u_camera_to_center_distance);}gl_Position=u_matrix*vec4(corner_position,0,1);} else {gl_Position=u_matrix*vec4(circle_center,0,1);if (u_scale_with_map) {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*u_camera_to_center_distance;} else {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*gl_Position.w;}}lowp float antialiasblur=1.0/u_device_pixel_ratio/(radius+stroke_width);v_data=vec3(extrude.x,extrude.y,antialiasblur);}\"),Ze=vr(\"void main() {gl_FragColor=vec4(1.0);}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),Je=vr(\"uniform highp float u_intensity;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main() {\\n#pragma mapbox: initialize highp float weight\\nfloat d=-0.5*3.0*3.0*dot(v_extrude,v_extrude);float val=weight*u_intensity*GAUSS_COEF*exp(d);gl_FragColor=vec4(val,1.0,1.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform float u_extrude_scale;uniform float u_opacity;uniform float u_intensity;attribute vec2 a_pos;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#pragma mapbox: define mediump float radius\\nconst highp float ZERO=1.0/255.0/16.0;\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main(void) {\\n#pragma mapbox: initialize highp float weight\\n#pragma mapbox: initialize mediump float radius\\nvec2 unscaled_extrude=vec2(mod(a_pos,2.0)*2.0-1.0);float S=sqrt(-2.0*log(ZERO/weight/u_intensity/GAUSS_COEF))/3.0;v_extrude=S*unscaled_extrude;vec2 extrude=v_extrude*radius*u_extrude_scale;vec4 pos=vec4(floor(a_pos*0.5)+extrude,0,1);gl_Position=u_matrix*pos;}\"),Ke=vr(\"uniform sampler2D u_image;uniform sampler2D u_color_ramp;uniform float u_opacity;varying vec2 v_pos;void main() {float t=texture2D(u_image,v_pos).r;vec4 color=texture2D(u_color_ramp,vec2(t,0.5));gl_FragColor=color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(0.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;attribute vec2 a_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos*u_world,0,1);v_pos.x=a_pos.x;v_pos.y=1.0-a_pos.y;}\"),Qe=vr(\"varying float v_placed;varying float v_notUsed;void main() {float alpha=0.5;gl_FragColor=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}\",\"attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;attribute vec2 a_shift;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);gl_Position.xy+=(a_extrude+a_shift)*u_extrude_scale*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;}\"),$e=vr(\"varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}\",\"attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd  =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz  /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}\"),tr=vr(\"uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}\",\"attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,0,1);}\"),er=vr(\"#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_FragColor=color*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);}\"),rr=vr(\"varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),nr=vr(\"uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),ir=vr(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}\"),ar=vr(\"varying vec4 v_color;void main() {gl_FragColor=v_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec4 v_color;\\n#pragma mapbox: define highp float base\\n#pragma mapbox: define highp float height\\n#pragma mapbox: define highp vec4 color\\nvoid main() {\\n#pragma mapbox: initialize highp float base\\n#pragma mapbox: initialize highp float height\\n#pragma mapbox: initialize highp vec4 color\\nvec3 normal=a_normal_ed.xyz;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}\"),or=vr(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\\n? a_pos\\n: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}\"),sr=vr(\"#ifdef GL_ES\\nprecision highp float;\\n#endif\\nuniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform float u_maxzoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggeration=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/ pow(2.0,(u_zoom-u_maxzoom)*exaggeration+19.2562-u_zoom);gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}\"),lr=vr(\"uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\\n#define PI 3.141592653589793\\nvoid main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}\"),cr=vr(\"uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),ur=vr(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,vec2(v_lineprogress,0.5));gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define MAX_LINE_DISTANCE 32767.0\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_lineprogress=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0/MAX_LINE_DISTANCE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),fr=vr(\"uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}\"),hr=vr(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}\"),pr=vr(\"uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}\"),dr=vr(\"uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nlowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}\"),gr=vr(\"#define SDF_PX 8.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}\"),mr=vr(\"#define SDF_PX 8.0\\n#define SDF 1.0\\n#define ICON 0.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\nreturn;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}\");function vr(t,e){var r=/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,n={};return{fragmentSource:t=t.replace(r,(function(t,e,r,i,a){return n[a]=!0,\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"\\n#ifdef HAS_UNIFORM_u_\"+a+\"\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"})),vertexSource:e=e.replace(r,(function(t,e,r,i,a){var o=\"float\"===i?\"vec2\":\"vec4\",s=a.match(/color/)?\"color\":o;return n[a]?\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+a+\" = a_\"+a+\";\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+r+\" \"+i+\" \"+a+\" = a_\"+a+\";\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+r+\" \"+i+\" \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"}))}}var yr=Object.freeze({__proto__:null,prelude:Ge,background:Ye,backgroundPattern:We,circle:Xe,clippingMask:Ze,heatmap:Je,heatmapTexture:Ke,collisionBox:Qe,collisionCircle:$e,debug:tr,fill:er,fillOutline:rr,fillOutlinePattern:nr,fillPattern:ir,fillExtrusion:ar,fillExtrusionPattern:or,hillshadePrepare:sr,hillshade:lr,line:cr,lineGradient:ur,linePattern:fr,lineSDF:hr,raster:pr,symbolIcon:dr,symbolSDF:gr,symbolTextAndIcon:mr}),xr=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};xr.prototype.bind=function(t,e,r,n,i,a,o,s){this.context=t;for(var l=this.boundPaintVertexBuffers.length!==n.length,c=0;!l&&c<n.length;c++)this.boundPaintVertexBuffers[c]!==n[c]&&(l=!0);t.extVertexArrayObject&&this.vao&&this.boundProgram===e&&this.boundLayoutVertexBuffer===r&&!l&&this.boundIndexBuffer===i&&this.boundVertexOffset===a&&this.boundDynamicVertexBuffer===o&&this.boundDynamicVertexBuffer2===s?(t.bindVertexArrayOES.set(this.vao),o&&o.bind(),i&&i.dynamicDraw&&i.bind(),s&&s.bind()):this.freshBind(e,r,n,i,a,o,s)},xr.prototype.freshBind=function(t,e,r,n,i,a,o){var s,l=t.numAttributes,c=this.context,u=c.gl;if(c.extVertexArrayObject)this.vao&&this.destroy(),this.vao=c.extVertexArrayObject.createVertexArrayOES(),c.bindVertexArrayOES.set(this.vao),s=0,this.boundProgram=t,this.boundLayoutVertexBuffer=e,this.boundPaintVertexBuffers=r,this.boundIndexBuffer=n,this.boundVertexOffset=i,this.boundDynamicVertexBuffer=a,this.boundDynamicVertexBuffer2=o;else{s=c.currentNumAttributes||0;for(var f=l;f<s;f++)u.disableVertexAttribArray(f)}e.enableAttributes(u,t);for(var h=0,p=r;h<p.length;h+=1)p[h].enableAttributes(u,t);a&&a.enableAttributes(u,t),o&&o.enableAttributes(u,t),e.bind(),e.setVertexAttribPointers(u,t,i);for(var d=0,g=r;d<g.length;d+=1){var m=g[d];m.bind(),m.setVertexAttribPointers(u,t,i)}a&&(a.bind(),a.setVertexAttribPointers(u,t,i)),n&&n.bind(),o&&(o.bind(),o.setVertexAttribPointers(u,t,i)),c.currentNumAttributes=l},xr.prototype.destroy=function(){this.vao&&(this.context.extVertexArrayObject.deleteVertexArrayOES(this.vao),this.vao=null)};var br=function(t,e,r,n,i){var a=t.gl;this.program=a.createProgram();var o=r?r.defines():[];i&&o.push(\"#define OVERDRAW_INSPECTOR;\");var s=o.concat(Ge.fragmentSource,e.fragmentSource).join(\"\\n\"),l=o.concat(Ge.vertexSource,e.vertexSource).join(\"\\n\"),c=a.createShader(a.FRAGMENT_SHADER);if(a.isContextLost())this.failedToCreate=!0;else{a.shaderSource(c,s),a.compileShader(c),a.attachShader(this.program,c);var u=a.createShader(a.VERTEX_SHADER);if(a.isContextLost())this.failedToCreate=!0;else{a.shaderSource(u,l),a.compileShader(u),a.attachShader(this.program,u);for(var f=r?r.layoutAttributes:[],h=0;h<f.length;h++)a.bindAttribLocation(this.program,h,f[h].name);a.linkProgram(this.program),a.deleteShader(u),a.deleteShader(c),this.numAttributes=a.getProgramParameter(this.program,a.ACTIVE_ATTRIBUTES),this.attributes={};for(var p={},d=0;d<this.numAttributes;d++){var g=a.getActiveAttrib(this.program,d);g&&(this.attributes[g.name]=a.getAttribLocation(this.program,g.name))}for(var m=a.getProgramParameter(this.program,a.ACTIVE_UNIFORMS),v=0;v<m;v++){var y=a.getActiveUniform(this.program,v);y&&(p[y.name]=a.getUniformLocation(this.program,y.name))}this.fixedUniforms=n(t,p),this.binderUniforms=r?r.getUniforms(t,p):[]}}};function _r(t,e,r){var n=1/he(r,1,e.transform.tileZoom),i=Math.pow(2,r.tileID.overscaledZ),a=r.tileSize*Math.pow(2,e.transform.tileZoom)/i,o=a*(r.tileID.canonical.x+r.tileID.wrap*i),s=a*r.tileID.canonical.y;return{u_image:0,u_texsize:r.imageAtlasTexture.size,u_scale:[n,t.fromScale,t.toScale],u_fade:t.t,u_pixel_coord_upper:[o>>16,s>>16],u_pixel_coord_lower:[65535&o,65535&s]}}br.prototype.draw=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g){var m,v=t.gl;if(!this.failedToCreate){for(var y in t.program.set(this.program),t.setDepthMode(r),t.setStencilMode(n),t.setColorMode(i),t.setCullFace(a),this.fixedUniforms)this.fixedUniforms[y].set(o[y]);p&&p.setUniforms(t,this.binderUniforms,f,{zoom:h});for(var x=(m={},m[v.LINES]=2,m[v.TRIANGLES]=3,m[v.LINE_STRIP]=1,m)[e],b=0,_=u.get();b<_.length;b+=1){var w=_[b],T=w.vaos||(w.vaos={});(T[s]||(T[s]=new xr)).bind(t,this,l,p?p.getPaintVertexBuffers():[],c,w.vertexOffset,d,g),v.drawElements(e,w.primitiveLength*x,v.UNSIGNED_SHORT,w.primitiveOffset*x*2)}}};var wr=function(e,r,n,i){var a=r.style.light,o=a.properties.get(\"position\"),s=[o.x,o.y,o.z],l=t.create$1();\"viewport\"===a.properties.get(\"anchor\")&&t.fromRotation(l,-r.transform.angle),t.transformMat3(s,s,l);var c=a.properties.get(\"color\");return{u_matrix:e,u_lightpos:s,u_lightintensity:a.properties.get(\"intensity\"),u_lightcolor:[c.r,c.g,c.b],u_vertical_gradient:+n,u_opacity:i}},Tr=function(e,r,n,i,a,o,s){return t.extend(wr(e,r,n,i),_r(o,r,s),{u_height_factor:-Math.pow(2,a.overscaledZ)/s.tileSize/8})},kr=function(t){return{u_matrix:t}},Mr=function(e,r,n,i){return t.extend(kr(e),_r(n,r,i))},Ar=function(t,e){return{u_matrix:t,u_world:e}},Sr=function(e,r,n,i,a){return t.extend(Mr(e,r,n,i),{u_world:a})},Er=function(e,r,n,i){var a,o,s=e.transform;if(\"map\"===i.paint.get(\"circle-pitch-alignment\")){var l=he(n,1,s.zoom);a=!0,o=[l,l]}else a=!1,o=s.pixelsToGLUnits;return{u_camera_to_center_distance:s.cameraToCenterDistance,u_scale_with_map:+(\"map\"===i.paint.get(\"circle-pitch-scale\")),u_matrix:e.translatePosMatrix(r.posMatrix,n,i.paint.get(\"circle-translate\"),i.paint.get(\"circle-translate-anchor\")),u_pitch_with_map:+a,u_device_pixel_ratio:t.browser.devicePixelRatio,u_extrude_scale:o}},Cr=function(t,e,r){var n=he(r,1,e.zoom),i=Math.pow(2,e.zoom-r.tileID.overscaledZ),a=r.tileID.overscaleFactor();return{u_matrix:t,u_camera_to_center_distance:e.cameraToCenterDistance,u_pixels_to_tile_units:n,u_extrude_scale:[e.pixelsToGLUnits[0]/(n*i),e.pixelsToGLUnits[1]/(n*i)],u_overscale_factor:a}},Lr=function(t,e,r){return{u_matrix:t,u_inv_matrix:e,u_camera_to_center_distance:r.cameraToCenterDistance,u_viewport_size:[r.width,r.height]}},Ir=function(t,e,r){return void 0===r&&(r=1),{u_matrix:t,u_color:e,u_overlay:0,u_overlay_scale:r}},Pr=function(t){return{u_matrix:t}},zr=function(t,e,r,n){return{u_matrix:t,u_extrude_scale:he(e,1,r),u_intensity:n}},Or=function(e,r,n){var i=e.transform;return{u_matrix:Nr(e,r,n),u_ratio:1/he(r,1,i.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_units_to_pixels:[1/i.pixelsToGLUnits[0],1/i.pixelsToGLUnits[1]]}},Dr=function(e,r,n){return t.extend(Or(e,r,n),{u_image:0})},Rr=function(e,r,n,i){var a=e.transform,o=Br(r,a);return{u_matrix:Nr(e,r,n),u_texsize:r.imageAtlasTexture.size,u_ratio:1/he(r,1,a.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_image:0,u_scale:[o,i.fromScale,i.toScale],u_fade:i.t,u_units_to_pixels:[1/a.pixelsToGLUnits[0],1/a.pixelsToGLUnits[1]]}},Fr=function(e,r,n,i,a){var o=e.lineAtlas,s=Br(r,e.transform),l=\"round\"===n.layout.get(\"line-cap\"),c=o.getDash(i.from,l),u=o.getDash(i.to,l),f=c.width*a.fromScale,h=u.width*a.toScale;return t.extend(Or(e,r,n),{u_patternscale_a:[s/f,-c.height/2],u_patternscale_b:[s/h,-u.height/2],u_sdfgamma:o.width/(256*Math.min(f,h)*t.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:c.y,u_tex_y_b:u.y,u_mix:a.t})};function Br(t,e){return 1/he(t,1,e.tileZoom)}function Nr(t,e,r){return t.translatePosMatrix(e.tileID.posMatrix,e,r.paint.get(\"line-translate\"),r.paint.get(\"line-translate-anchor\"))}var jr=function(t,e,r,n,i){return{u_matrix:t,u_tl_parent:e,u_scale_parent:r,u_buffer_scale:1,u_fade_t:n.mix,u_opacity:n.opacity*i.paint.get(\"raster-opacity\"),u_image0:0,u_image1:1,u_brightness_low:i.paint.get(\"raster-brightness-min\"),u_brightness_high:i.paint.get(\"raster-brightness-max\"),u_saturation_factor:(o=i.paint.get(\"raster-saturation\"),o>0?1-1/(1.001-o):-o),u_contrast_factor:(a=i.paint.get(\"raster-contrast\"),a>0?1/(1-a):1+a),u_spin_weights:Ur(i.paint.get(\"raster-hue-rotate\"))};var a,o};function Ur(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}var Vr,qr=function(t,e,r,n,i,a,o,s,l,c){var u=i.transform;return{u_is_size_zoom_constant:+(\"constant\"===t||\"source\"===t),u_is_size_feature_constant:+(\"constant\"===t||\"camera\"===t),u_size_t:e?e.uSizeT:0,u_size:e?e.uSize:0,u_camera_to_center_distance:u.cameraToCenterDistance,u_pitch:u.pitch/360*2*Math.PI,u_rotate_symbol:+r,u_aspect_ratio:u.width/u.height,u_fade_change:i.options.fadeDuration?i.symbolFadeChange:1,u_matrix:a,u_label_plane_matrix:o,u_coord_matrix:s,u_is_text:+l,u_pitch_with_map:+n,u_texsize:c,u_texture:0}},Hr=function(e,r,n,i,a,o,s,l,c,u,f){var h=a.transform;return t.extend(qr(e,r,n,i,a,o,s,l,c,u),{u_gamma_scale:i?Math.cos(h._pitch)*h.cameraToCenterDistance:1,u_device_pixel_ratio:t.browser.devicePixelRatio,u_is_halo:+f})},Gr=function(e,r,n,i,a,o,s,l,c,u){return t.extend(Hr(e,r,n,i,a,o,s,l,!0,c,!0),{u_texsize_icon:u,u_texture_icon:1})},Yr=function(t,e,r){return{u_matrix:t,u_opacity:e,u_color:r}},Wr=function(e,r,n,i,a,o){return t.extend(function(t,e,r,n){var i=r.imageManager.getPattern(t.from.toString()),a=r.imageManager.getPattern(t.to.toString()),o=r.imageManager.getPixelSize(),s=o.width,l=o.height,c=Math.pow(2,n.tileID.overscaledZ),u=n.tileSize*Math.pow(2,r.transform.tileZoom)/c,f=u*(n.tileID.canonical.x+n.tileID.wrap*c),h=u*n.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:i.tl,u_pattern_br_a:i.br,u_pattern_tl_b:a.tl,u_pattern_br_b:a.br,u_texsize:[s,l],u_mix:e.t,u_pattern_size_a:i.displaySize,u_pattern_size_b:a.displaySize,u_scale_a:e.fromScale,u_scale_b:e.toScale,u_tile_units_to_pixels:1/he(n,1,r.transform.tileZoom),u_pixel_coord_upper:[f>>16,h>>16],u_pixel_coord_lower:[65535&f,65535&h]}}(i,o,n,a),{u_matrix:e,u_opacity:r})},Xr={fillExtrusion:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fillExtrusionPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_height_factor:new t.Uniform1f(e,r.u_height_factor),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fill:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},fillPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},fillOutline:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world)}},fillOutlinePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},circle:function(e,r){return{u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_scale_with_map:new t.Uniform1i(e,r.u_scale_with_map),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},collisionBox:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pixels_to_tile_units:new t.Uniform1f(e,r.u_pixels_to_tile_units),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_overscale_factor:new t.Uniform1f(e,r.u_overscale_factor)}},collisionCircle:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_inv_matrix:new t.UniformMatrix4f(e,r.u_inv_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_viewport_size:new t.Uniform2f(e,r.u_viewport_size)}},debug:function(e,r){return{u_color:new t.UniformColor(e,r.u_color),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_overlay:new t.Uniform1i(e,r.u_overlay),u_overlay_scale:new t.Uniform1f(e,r.u_overlay_scale)}},clippingMask:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmap:function(e,r){return{u_extrude_scale:new t.Uniform1f(e,r.u_extrude_scale),u_intensity:new t.Uniform1f(e,r.u_intensity),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmapTexture:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_color_ramp:new t.Uniform1i(e,r.u_color_ramp),u_opacity:new t.Uniform1f(e,r.u_opacity)}},hillshade:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_latrange:new t.Uniform2f(e,r.u_latrange),u_light:new t.Uniform2f(e,r.u_light),u_shadow:new t.UniformColor(e,r.u_shadow),u_highlight:new t.UniformColor(e,r.u_highlight),u_accent:new t.UniformColor(e,r.u_accent)}},hillshadePrepare:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_dimension:new t.Uniform2f(e,r.u_dimension),u_zoom:new t.Uniform1f(e,r.u_zoom),u_maxzoom:new t.Uniform1f(e,r.u_maxzoom),u_unpack:new t.Uniform4f(e,r.u_unpack)}},line:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels)}},lineGradient:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_image:new t.Uniform1i(e,r.u_image)}},linePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_texsize:new t.Uniform2f(e,r.u_texsize),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_image:new t.Uniform1i(e,r.u_image),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},lineSDF:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_patternscale_a:new t.Uniform2f(e,r.u_patternscale_a),u_patternscale_b:new t.Uniform2f(e,r.u_patternscale_b),u_sdfgamma:new t.Uniform1f(e,r.u_sdfgamma),u_image:new t.Uniform1i(e,r.u_image),u_tex_y_a:new t.Uniform1f(e,r.u_tex_y_a),u_tex_y_b:new t.Uniform1f(e,r.u_tex_y_b),u_mix:new t.Uniform1f(e,r.u_mix)}},raster:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_tl_parent:new t.Uniform2f(e,r.u_tl_parent),u_scale_parent:new t.Uniform1f(e,r.u_scale_parent),u_buffer_scale:new t.Uniform1f(e,r.u_buffer_scale),u_fade_t:new t.Uniform1f(e,r.u_fade_t),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image0:new t.Uniform1i(e,r.u_image0),u_image1:new t.Uniform1i(e,r.u_image1),u_brightness_low:new t.Uniform1f(e,r.u_brightness_low),u_brightness_high:new t.Uniform1f(e,r.u_brightness_high),u_saturation_factor:new t.Uniform1f(e,r.u_saturation_factor),u_contrast_factor:new t.Uniform1f(e,r.u_contrast_factor),u_spin_weights:new t.Uniform3f(e,r.u_spin_weights)}},symbolIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture)}},symbolSDF:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},symbolTextAndIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texsize_icon:new t.Uniform2f(e,r.u_texsize_icon),u_texture:new t.Uniform1i(e,r.u_texture),u_texture_icon:new t.Uniform1i(e,r.u_texture_icon),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},background:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_color:new t.UniformColor(e,r.u_color)}},backgroundPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image:new t.Uniform1i(e,r.u_image),u_pattern_tl_a:new t.Uniform2f(e,r.u_pattern_tl_a),u_pattern_br_a:new t.Uniform2f(e,r.u_pattern_br_a),u_pattern_tl_b:new t.Uniform2f(e,r.u_pattern_tl_b),u_pattern_br_b:new t.Uniform2f(e,r.u_pattern_br_b),u_texsize:new t.Uniform2f(e,r.u_texsize),u_mix:new t.Uniform1f(e,r.u_mix),u_pattern_size_a:new t.Uniform2f(e,r.u_pattern_size_a),u_pattern_size_b:new t.Uniform2f(e,r.u_pattern_size_b),u_scale_a:new t.Uniform1f(e,r.u_scale_a),u_scale_b:new t.Uniform1f(e,r.u_scale_b),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_tile_units_to_pixels:new t.Uniform1f(e,r.u_tile_units_to_pixels)}}};function Zr(e,r,n,i,a,o,s){for(var l=e.context,c=l.gl,u=e.useProgram(\"collisionBox\"),f=[],h=0,p=0,d=0;d<i.length;d++){var g=i[d],m=r.getTile(g),v=m.getBucket(n);if(v){var y=g.posMatrix;0===a[0]&&0===a[1]||(y=e.translatePosMatrix(g.posMatrix,m,a,o));var x=s?v.textCollisionBox:v.iconCollisionBox,b=v.collisionCircleArray;if(b.length>0){var _=t.create(),w=y;t.mul(_,v.placementInvProjMatrix,e.transform.glCoordMatrix),t.mul(_,_,v.placementViewportMatrix),f.push({circleArray:b,circleOffset:p,transform:w,invTransform:_}),p=h+=b.length/4}x&&u.draw(l,c.LINES,Mt.disabled,At.disabled,e.colorModeForRenderPass(),Et.disabled,Cr(y,e.transform,m),n.id,x.layoutVertexBuffer,x.indexBuffer,x.segments,null,e.transform.zoom,null,null,x.collisionVertexBuffer)}}if(s&&f.length){var T=e.useProgram(\"collisionCircle\"),k=new t.StructArrayLayout2f1f2i16;k.resize(4*h),k._trim();for(var M=0,A=0,S=f;A<S.length;A+=1)for(var E=S[A],C=0;C<E.circleArray.length/4;C++){var L=4*C,I=E.circleArray[L+0],P=E.circleArray[L+1],z=E.circleArray[L+2],O=E.circleArray[L+3];k.emplace(M++,I,P,z,O,0),k.emplace(M++,I,P,z,O,1),k.emplace(M++,I,P,z,O,2),k.emplace(M++,I,P,z,O,3)}(!Vr||Vr.length<2*h)&&(Vr=function(e){var r=2*e,n=new t.StructArrayLayout3ui6;n.resize(r),n._trim();for(var i=0;i<r;i++){var a=6*i;n.uint16[a+0]=4*i+0,n.uint16[a+1]=4*i+1,n.uint16[a+2]=4*i+2,n.uint16[a+3]=4*i+2,n.uint16[a+4]=4*i+3,n.uint16[a+5]=4*i+0}return n}(h));for(var D=l.createIndexBuffer(Vr,!0),R=l.createVertexBuffer(k,t.collisionCircleLayout.members,!0),F=0,B=f;F<B.length;F+=1){var N=B[F],j=Lr(N.transform,N.invTransform,e.transform);T.draw(l,c.TRIANGLES,Mt.disabled,At.disabled,e.colorModeForRenderPass(),Et.disabled,j,n.id,R,D,t.SegmentVector.simpleSegment(0,2*N.circleOffset,N.circleArray.length,N.circleArray.length/2),null,e.transform.zoom,null,null,null)}R.destroy(),D.destroy()}}var Jr=t.identity(new Float32Array(16));function Kr(e,r,n,i,a,o){var s=t.getAnchorAlignment(e),l=-(s.horizontalAlign-.5)*r,c=-(s.verticalAlign-.5)*n,u=t.evaluateVariableOffset(e,i);return new t.Point((l/a+u[0])*o,(c/a+u[1])*o)}function Qr(e,r,n,i,a,o,s,l,c,u,f){var h=e.text.placedSymbolArray,p=e.text.dynamicLayoutVertexArray,d=e.icon.dynamicLayoutVertexArray,g={};p.clear();for(var m=0;m<h.length;m++){var v=h.get(m),y=v.hidden||!v.crossTileID||e.allowVerticalPlacement&&!v.placedOrientation?null:i[v.crossTileID];if(y){var x=new t.Point(v.anchorX,v.anchorY),b=$t(x,n?l:s),_=te(o.cameraToCenterDistance,b.signedDistanceFromCamera),w=a.evaluateSizeForFeature(e.textSizeData,u,v)*_/t.ONE_EM;n&&(w*=e.tilePixelRatio/c);for(var T=Kr(y.anchor,y.width,y.height,y.textOffset,y.textBoxScale,w),k=n?$t(x.add(T),s).point:b.point.add(r?T.rotate(-o.angle):T),M=e.allowVerticalPlacement&&v.placedOrientation===t.WritingMode.vertical?Math.PI/2:0,A=0;A<v.numGlyphs;A++)t.addDynamicAttributes(p,k,M);f&&v.associatedIconIndex>=0&&(g[v.associatedIconIndex]={shiftedAnchor:k,angle:M})}else ce(v.numGlyphs,p)}if(f){d.clear();for(var S=e.icon.placedSymbolArray,E=0;E<S.length;E++){var C=S.get(E);if(C.hidden)ce(C.numGlyphs,d);else{var L=g[E];if(L)for(var I=0;I<C.numGlyphs;I++)t.addDynamicAttributes(d,L.shiftedAnchor,L.angle);else ce(C.numGlyphs,d)}}e.icon.dynamicLayoutVertexBuffer.updateData(d)}e.text.dynamicLayoutVertexBuffer.updateData(p)}function $r(t,e,r){return r.iconsInText&&e?\"symbolTextAndIcon\":t?\"symbolSDF\":\"symbolIcon\"}function tn(e,r,n,i,a,o,s,l,c,u,f,h){for(var p=e.context,d=p.gl,g=e.transform,m=\"map\"===l,v=\"map\"===c,y=m&&\"point\"!==n.layout.get(\"symbol-placement\"),x=m&&!v&&!y,b=void 0!==n.layout.get(\"symbol-sort-key\").constantOr(1),_=e.depthModeForSublayer(0,Mt.ReadOnly),w=n.layout.get(\"text-variable-anchor\"),T=[],k=0,M=i;k<M.length;k+=1){var A=M[k],S=r.getTile(A),E=S.getBucket(n);if(E){var C=a?E.text:E.icon;if(C&&C.segments.get().length){var L=C.programConfigurations.get(n.id),I=a||E.sdfIcons,P=a?E.textSizeData:E.iconSizeData,z=v||0!==g.pitch,O=e.useProgram($r(I,a,E),L),D=t.evaluateSizeForZoom(P,g.zoom),R=void 0,F=[0,0],B=void 0,N=void 0,j=null,U=void 0;if(a)B=S.glyphAtlasTexture,N=d.LINEAR,R=S.glyphAtlasTexture.size,E.iconsInText&&(F=S.imageAtlasTexture.size,j=S.imageAtlasTexture,U=z||e.options.rotating||e.options.zooming||\"composite\"===P.kind||\"camera\"===P.kind?d.LINEAR:d.NEAREST);else{var V=1!==n.layout.get(\"icon-size\").constantOr(0)||E.iconsNeedLinear;B=S.imageAtlasTexture,N=I||e.options.rotating||e.options.zooming||V||z?d.LINEAR:d.NEAREST,R=S.imageAtlasTexture.size}var q=he(S,1,e.transform.zoom),H=Kt(A.posMatrix,v,m,e.transform,q),G=Qt(A.posMatrix,v,m,e.transform,q),Y=w&&E.hasTextData(),W=\"none\"!==n.layout.get(\"icon-text-fit\")&&Y&&E.hasIconData();y&&re(E,A.posMatrix,e,a,H,G,v,u);var X=e.translatePosMatrix(A.posMatrix,S,o,s),Z=y||a&&w||W?Jr:H,J=e.translatePosMatrix(G,S,o,s,!0),K=I&&0!==n.paint.get(a?\"text-halo-width\":\"icon-halo-width\").constantOr(1),Q={program:O,buffers:C,uniformValues:I?E.iconsInText?Gr(P.kind,D,x,v,e,X,Z,J,R,F):Hr(P.kind,D,x,v,e,X,Z,J,a,R,!0):qr(P.kind,D,x,v,e,X,Z,J,a,R),atlasTexture:B,atlasTextureIcon:j,atlasInterpolation:N,atlasInterpolationIcon:U,isSDF:I,hasHalo:K};if(b)for(var $=0,tt=C.segments.get();$<tt.length;$+=1){var et=tt[$];T.push({segments:new t.SegmentVector([et]),sortKey:et.sortKey,state:Q})}else T.push({segments:C.segments,sortKey:0,state:Q})}}}b&&T.sort((function(t,e){return t.sortKey-e.sortKey}));for(var rt=0,nt=T;rt<nt.length;rt+=1){var it=nt[rt],at=it.state;if(p.activeTexture.set(d.TEXTURE0),at.atlasTexture.bind(at.atlasInterpolation,d.CLAMP_TO_EDGE),at.atlasTextureIcon&&(p.activeTexture.set(d.TEXTURE1),at.atlasTextureIcon&&at.atlasTextureIcon.bind(at.atlasInterpolationIcon,d.CLAMP_TO_EDGE)),at.isSDF){var ot=at.uniformValues;at.hasHalo&&(ot.u_is_halo=1,en(at.buffers,it.segments,n,e,at.program,_,f,h,ot)),ot.u_is_halo=0}en(at.buffers,it.segments,n,e,at.program,_,f,h,at.uniformValues)}}function en(t,e,r,n,i,a,o,s,l){var c=n.context;i.draw(c,c.gl.TRIANGLES,a,o,s,Et.disabled,l,r.id,t.layoutVertexBuffer,t.indexBuffer,e,r.paint,n.transform.zoom,t.programConfigurations.get(r.id),t.dynamicLayoutVertexBuffer,t.opacityVertexBuffer)}function rn(t,e,r,n,i,a,o){var s,l,c,u,f,h=t.context.gl,p=r.paint.get(\"fill-pattern\"),d=p&&p.constantOr(1),g=r.getCrossfadeParameters();o?(l=d&&!r.getPaintProperty(\"fill-outline-color\")?\"fillOutlinePattern\":\"fillOutline\",s=h.LINES):(l=d?\"fillPattern\":\"fill\",s=h.TRIANGLES);for(var m=0,v=n;m<v.length;m+=1){var y=v[m],x=e.getTile(y);if(!d||x.patternsLoaded()){var b=x.getBucket(r);if(b){var _=b.programConfigurations.get(r.id),w=t.useProgram(l,_);d&&(t.context.activeTexture.set(h.TEXTURE0),x.imageAtlasTexture.bind(h.LINEAR,h.CLAMP_TO_EDGE),_.updatePaintBuffers(g));var T=p.constantOr(null);if(T&&x.imageAtlas){var k=x.imageAtlas,M=k.patternPositions[T.to.toString()],A=k.patternPositions[T.from.toString()];M&&A&&_.setConstantPatternPositions(M,A)}var S=t.translatePosMatrix(y.posMatrix,x,r.paint.get(\"fill-translate\"),r.paint.get(\"fill-translate-anchor\"));if(o){u=b.indexBuffer2,f=b.segments2;var E=[h.drawingBufferWidth,h.drawingBufferHeight];c=\"fillOutlinePattern\"===l&&d?Sr(S,t,g,x,E):Ar(S,E)}else u=b.indexBuffer,f=b.segments,c=d?Mr(S,t,g,x):kr(S);w.draw(t.context,s,i,t.stencilModeForClipping(y),a,Et.disabled,c,r.id,b.layoutVertexBuffer,u,f,r.paint,t.transform.zoom,_)}}}}function nn(t,e,r,n,i,a,o){for(var s=t.context,l=s.gl,c=r.paint.get(\"fill-extrusion-pattern\"),u=c.constantOr(1),f=r.getCrossfadeParameters(),h=r.paint.get(\"fill-extrusion-opacity\"),p=0,d=n;p<d.length;p+=1){var g=d[p],m=e.getTile(g),v=m.getBucket(r);if(v){var y=v.programConfigurations.get(r.id),x=t.useProgram(u?\"fillExtrusionPattern\":\"fillExtrusion\",y);u&&(t.context.activeTexture.set(l.TEXTURE0),m.imageAtlasTexture.bind(l.LINEAR,l.CLAMP_TO_EDGE),y.updatePaintBuffers(f));var b=c.constantOr(null);if(b&&m.imageAtlas){var _=m.imageAtlas,w=_.patternPositions[b.to.toString()],T=_.patternPositions[b.from.toString()];w&&T&&y.setConstantPatternPositions(w,T)}var k=t.translatePosMatrix(g.posMatrix,m,r.paint.get(\"fill-extrusion-translate\"),r.paint.get(\"fill-extrusion-translate-anchor\")),M=r.paint.get(\"fill-extrusion-vertical-gradient\"),A=u?Tr(k,t,M,h,g,f,m):wr(k,t,M,h);x.draw(s,s.gl.TRIANGLES,i,a,o,Et.backCCW,A,r.id,v.layoutVertexBuffer,v.indexBuffer,v.segments,r.paint,t.transform.zoom,y)}}}function an(e,r,n,i,a,o){var s=e.context,l=s.gl,c=r.fbo;if(c){var u=e.useProgram(\"hillshade\");s.activeTexture.set(l.TEXTURE0),l.bindTexture(l.TEXTURE_2D,c.colorAttachment.get());var f=function(e,r,n){var i=n.paint.get(\"hillshade-shadow-color\"),a=n.paint.get(\"hillshade-highlight-color\"),o=n.paint.get(\"hillshade-accent-color\"),s=n.paint.get(\"hillshade-illumination-direction\")*(Math.PI/180);\"viewport\"===n.paint.get(\"hillshade-illumination-anchor\")&&(s-=e.transform.angle);var l,c,u,f=!e.options.moving;return{u_matrix:e.transform.calculatePosMatrix(r.tileID.toUnwrapped(),f),u_image:0,u_latrange:(l=r.tileID,c=Math.pow(2,l.canonical.z),u=l.canonical.y,[new t.MercatorCoordinate(0,u/c).toLngLat().lat,new t.MercatorCoordinate(0,(u+1)/c).toLngLat().lat]),u_light:[n.paint.get(\"hillshade-exaggeration\"),s],u_shadow:i,u_highlight:a,u_accent:o}}(e,r,n);u.draw(s,l.TRIANGLES,i,a,o,Et.disabled,f,n.id,e.rasterBoundsBuffer,e.quadTriangleIndexBuffer,e.rasterBoundsSegments)}}function on(e,r,n,i,a,o,s){var l=e.context,c=l.gl,u=r.dem;if(u&&u.data){var f=u.dim,h=u.stride,p=u.getPixels();if(l.activeTexture.set(c.TEXTURE1),l.pixelStoreUnpackPremultiplyAlpha.set(!1),r.demTexture=r.demTexture||e.getTileTexture(h),r.demTexture){var d=r.demTexture;d.update(p,{premultiply:!1}),d.bind(c.NEAREST,c.CLAMP_TO_EDGE)}else r.demTexture=new t.Texture(l,p,c.RGBA,{premultiply:!1}),r.demTexture.bind(c.NEAREST,c.CLAMP_TO_EDGE);l.activeTexture.set(c.TEXTURE0);var g=r.fbo;if(!g){var m=new t.Texture(l,{width:f,height:f,data:null},c.RGBA);m.bind(c.LINEAR,c.CLAMP_TO_EDGE),(g=r.fbo=l.createFramebuffer(f,f,!0)).colorAttachment.set(m.texture)}l.bindFramebuffer.set(g.framebuffer),l.viewport.set([0,0,f,f]),e.useProgram(\"hillshadePrepare\").draw(l,c.TRIANGLES,a,o,s,Et.disabled,function(e,r,n){var i=r.stride,a=t.create();return t.ortho(a,0,t.EXTENT,-t.EXTENT,0,0,1),t.translate(a,a,[0,-t.EXTENT,0]),{u_matrix:a,u_image:1,u_dimension:[i,i],u_zoom:e.overscaledZ,u_maxzoom:n,u_unpack:r.getUnpackVector()}}(r.tileID,u,i),n.id,e.rasterBoundsBuffer,e.quadTriangleIndexBuffer,e.rasterBoundsSegments),r.needsHillshadePrepare=!1}}function sn(e,r,n,i,a){var o=i.paint.get(\"raster-fade-duration\");if(o>0){var s=t.browser.now(),l=(s-e.timeAdded)/o,c=r?(s-r.timeAdded)/o:-1,u=n.getSource(),f=a.coveringZoomLevel({tileSize:u.tileSize,roundZoom:u.roundZoom}),h=!r||Math.abs(r.tileID.overscaledZ-f)>Math.abs(e.tileID.overscaledZ-f),p=h&&e.refreshedUponExpiration?1:t.clamp(h?l:1-c,0,1);return e.refreshedUponExpiration&&l>=1&&(e.refreshedUponExpiration=!1),r?{opacity:1,mix:1-p}:{opacity:p,mix:0}}return{opacity:1,mix:0}}var ln=new t.Color(1,0,0,1),cn=new t.Color(0,1,0,1),un=new t.Color(0,0,1,1),fn=new t.Color(1,0,1,1),hn=new t.Color(0,1,1,1);function pn(t,e,r,n){gn(t,0,e+r/2,t.transform.width,r,n)}function dn(t,e,r,n){gn(t,e-r/2,0,r,t.transform.height,n)}function gn(e,r,n,i,a,o){var s=e.context,l=s.gl;l.enable(l.SCISSOR_TEST),l.scissor(r*t.browser.devicePixelRatio,n*t.browser.devicePixelRatio,i*t.browser.devicePixelRatio,a*t.browser.devicePixelRatio),s.clear({color:o}),l.disable(l.SCISSOR_TEST)}function mn(e,r,n){var i=e.context,a=i.gl,o=n.posMatrix,s=e.useProgram(\"debug\"),l=Mt.disabled,c=At.disabled,u=e.colorModeForRenderPass();i.activeTexture.set(a.TEXTURE0),e.emptyTexture.bind(a.LINEAR,a.CLAMP_TO_EDGE),s.draw(i,a.LINE_STRIP,l,c,u,Et.disabled,Ir(o,t.Color.red),\"$debug\",e.debugBuffer,e.tileBorderIndexBuffer,e.debugSegments);var f=r.getTileByID(n.key).latestRawTileData,h=Math.floor((f&&f.byteLength||0)/1024),p=r.getTile(n).tileSize,d=512/Math.min(p,512)*(n.overscaledZ/e.transform.zoom)*.5,g=n.canonical.toString();n.overscaledZ!==n.canonical.z&&(g+=\" => \"+n.overscaledZ),function(t,e){t.initDebugOverlayCanvas();var r=t.debugOverlayCanvas,n=t.context.gl,i=t.debugOverlayCanvas.getContext(\"2d\");i.clearRect(0,0,r.width,r.height),i.shadowColor=\"white\",i.shadowBlur=2,i.lineWidth=1.5,i.strokeStyle=\"white\",i.textBaseline=\"top\",i.font=\"bold 36px Open Sans, sans-serif\",i.fillText(e,5,5),i.strokeText(e,5,5),t.debugOverlayTexture.update(r),t.debugOverlayTexture.bind(n.LINEAR,n.CLAMP_TO_EDGE)}(e,g+\" \"+h+\"kb\"),s.draw(i,a.TRIANGLES,l,c,St.alphaBlended,Et.disabled,Ir(o,t.Color.transparent,d),\"$debug\",e.debugBuffer,e.quadTriangleIndexBuffer,e.debugSegments)}var vn={symbol:function(e,r,n,i,a){if(\"translucent\"===e.renderPass){var o=At.disabled,s=e.colorModeForRenderPass();n.layout.get(\"text-variable-anchor\")&&function(e,r,n,i,a,o,s){for(var l=r.transform,c=\"map\"===a,u=\"map\"===o,f=0,h=e;f<h.length;f+=1){var p=h[f],d=i.getTile(p),g=d.getBucket(n);if(g&&g.text&&g.text.segments.get().length){var m=t.evaluateSizeForZoom(g.textSizeData,l.zoom),v=he(d,1,r.transform.zoom),y=Kt(p.posMatrix,u,c,r.transform,v),x=\"none\"!==n.layout.get(\"icon-text-fit\")&&g.hasIconData();if(m){var b=Math.pow(2,l.zoom-d.tileID.overscaledZ);Qr(g,c,u,s,t.symbolSize,l,y,p.posMatrix,b,m,x)}}}}(i,e,n,r,n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),a),0!==n.paint.get(\"icon-opacity\").constantOr(1)&&tn(e,r,n,i,!1,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),n.layout.get(\"icon-rotation-alignment\"),n.layout.get(\"icon-pitch-alignment\"),n.layout.get(\"icon-keep-upright\"),o,s),0!==n.paint.get(\"text-opacity\").constantOr(1)&&tn(e,r,n,i,!0,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),n.layout.get(\"text-keep-upright\"),o,s),r.map.showCollisionBoxes&&(Zr(e,r,n,i,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),!0),Zr(e,r,n,i,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),!1))}},circle:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"circle-opacity\"),o=n.paint.get(\"circle-stroke-width\"),s=n.paint.get(\"circle-stroke-opacity\"),l=void 0!==n.layout.get(\"circle-sort-key\").constantOr(1);if(0!==a.constantOr(1)||0!==o.constantOr(1)&&0!==s.constantOr(1)){for(var c=e.context,u=c.gl,f=e.depthModeForSublayer(0,Mt.ReadOnly),h=At.disabled,p=e.colorModeForRenderPass(),d=[],g=0;g<i.length;g++){var m=i[g],v=r.getTile(m),y=v.getBucket(n);if(y){var x=y.programConfigurations.get(n.id),b={programConfiguration:x,program:e.useProgram(\"circle\",x),layoutVertexBuffer:y.layoutVertexBuffer,indexBuffer:y.indexBuffer,uniformValues:Er(e,m,v,n)};if(l)for(var _=0,w=y.segments.get();_<w.length;_+=1){var T=w[_];d.push({segments:new t.SegmentVector([T]),sortKey:T.sortKey,state:b})}else d.push({segments:y.segments,sortKey:0,state:b})}}l&&d.sort((function(t,e){return t.sortKey-e.sortKey}));for(var k=0,M=d;k<M.length;k+=1){var A=M[k],S=A.state;S.program.draw(c,u.TRIANGLES,f,h,p,Et.disabled,S.uniformValues,n.id,S.layoutVertexBuffer,S.indexBuffer,A.segments,n.paint,e.transform.zoom,S.programConfiguration)}}}},heatmap:function(e,r,n,i){if(0!==n.paint.get(\"heatmap-opacity\"))if(\"offscreen\"===e.renderPass){var a=e.context,o=a.gl,s=At.disabled,l=new St([o.ONE,o.ONE],t.Color.transparent,[!0,!0,!0,!0]);!function(t,e,r){var n=t.gl;t.activeTexture.set(n.TEXTURE1),t.viewport.set([0,0,e.width/4,e.height/4]);var i=r.heatmapFbo;if(i)n.bindTexture(n.TEXTURE_2D,i.colorAttachment.get()),t.bindFramebuffer.set(i.framebuffer);else{var a=n.createTexture();n.bindTexture(n.TEXTURE_2D,a),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,n.LINEAR),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,n.LINEAR),i=r.heatmapFbo=t.createFramebuffer(e.width/4,e.height/4,!1),function(t,e,r,n){var i=t.gl;i.texImage2D(i.TEXTURE_2D,0,i.RGBA,e.width/4,e.height/4,0,i.RGBA,t.extRenderToTextureHalfFloat?t.extTextureHalfFloat.HALF_FLOAT_OES:i.UNSIGNED_BYTE,null),n.colorAttachment.set(r)}(t,e,a,i)}}(a,e,n),a.clear({color:t.Color.transparent});for(var c=0;c<i.length;c++){var u=i[c];if(!r.hasRenderableParent(u)){var f=r.getTile(u),h=f.getBucket(n);if(h){var p=h.programConfigurations.get(n.id);e.useProgram(\"heatmap\",p).draw(a,o.TRIANGLES,Mt.disabled,s,l,Et.disabled,zr(u.posMatrix,f,e.transform.zoom,n.paint.get(\"heatmap-intensity\")),n.id,h.layoutVertexBuffer,h.indexBuffer,h.segments,n.paint,e.transform.zoom,p)}}}a.viewport.set([0,0,e.width,e.height])}else\"translucent\"===e.renderPass&&(e.context.setColorMode(e.colorModeForRenderPass()),function(e,r){var n=e.context,i=n.gl,a=r.heatmapFbo;if(a){n.activeTexture.set(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,a.colorAttachment.get()),n.activeTexture.set(i.TEXTURE1);var o=r.colorRampTexture;o||(o=r.colorRampTexture=new t.Texture(n,r.colorRamp,i.RGBA)),o.bind(i.LINEAR,i.CLAMP_TO_EDGE),e.useProgram(\"heatmapTexture\").draw(n,i.TRIANGLES,Mt.disabled,At.disabled,e.colorModeForRenderPass(),Et.disabled,function(e,r,n,i){var a=t.create();t.ortho(a,0,e.width,e.height,0,0,1);var o=e.context.gl;return{u_matrix:a,u_world:[o.drawingBufferWidth,o.drawingBufferHeight],u_image:0,u_color_ramp:1,u_opacity:r.paint.get(\"heatmap-opacity\")}}(e,r),r.id,e.viewportBuffer,e.quadTriangleIndexBuffer,e.viewportSegments,r.paint,e.transform.zoom)}}(e,n))},line:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"line-opacity\"),o=n.paint.get(\"line-width\");if(0!==a.constantOr(1)&&0!==o.constantOr(1)){var s=e.depthModeForSublayer(0,Mt.ReadOnly),l=e.colorModeForRenderPass(),c=n.paint.get(\"line-dasharray\"),u=n.paint.get(\"line-pattern\"),f=u.constantOr(1),h=n.paint.get(\"line-gradient\"),p=n.getCrossfadeParameters(),d=f?\"linePattern\":c?\"lineSDF\":h?\"lineGradient\":\"line\",g=e.context,m=g.gl,v=!0;if(h){g.activeTexture.set(m.TEXTURE0);var y=n.gradientTexture;if(!n.gradient)return;y||(y=n.gradientTexture=new t.Texture(g,n.gradient,m.RGBA)),y.bind(m.LINEAR,m.CLAMP_TO_EDGE)}for(var x=0,b=i;x<b.length;x+=1){var _=b[x],w=r.getTile(_);if(!f||w.patternsLoaded()){var T=w.getBucket(n);if(T){var k=T.programConfigurations.get(n.id),M=e.context.program.get(),A=e.useProgram(d,k),S=v||A.program!==M,E=u.constantOr(null);if(E&&w.imageAtlas){var C=w.imageAtlas,L=C.patternPositions[E.to.toString()],I=C.patternPositions[E.from.toString()];L&&I&&k.setConstantPatternPositions(L,I)}var P=f?Rr(e,w,n,p):c?Fr(e,w,n,c,p):h?Dr(e,w,n):Or(e,w,n);f?(g.activeTexture.set(m.TEXTURE0),w.imageAtlasTexture.bind(m.LINEAR,m.CLAMP_TO_EDGE),k.updatePaintBuffers(p)):c&&(S||e.lineAtlas.dirty)&&(g.activeTexture.set(m.TEXTURE0),e.lineAtlas.bind(g)),A.draw(g,m.TRIANGLES,s,e.stencilModeForClipping(_),l,Et.disabled,P,n.id,T.layoutVertexBuffer,T.indexBuffer,T.segments,n.paint,e.transform.zoom,k),v=!1}}}}}},fill:function(e,r,n,i){var a=n.paint.get(\"fill-color\"),o=n.paint.get(\"fill-opacity\");if(0!==o.constantOr(1)){var s=e.colorModeForRenderPass(),l=n.paint.get(\"fill-pattern\"),c=e.opaquePassEnabledForLayer()&&!l.constantOr(1)&&1===a.constantOr(t.Color.transparent).a&&1===o.constantOr(0)?\"opaque\":\"translucent\";if(e.renderPass===c){var u=e.depthModeForSublayer(1,\"opaque\"===e.renderPass?Mt.ReadWrite:Mt.ReadOnly);rn(e,r,n,i,u,s,!1)}if(\"translucent\"===e.renderPass&&n.paint.get(\"fill-antialias\")){var f=e.depthModeForSublayer(n.getPaintProperty(\"fill-outline-color\")?2:0,Mt.ReadOnly);rn(e,r,n,i,f,s,!0)}}},\"fill-extrusion\":function(t,e,r,n){var i=r.paint.get(\"fill-extrusion-opacity\");if(0!==i&&\"translucent\"===t.renderPass){var a=new Mt(t.context.gl.LEQUAL,Mt.ReadWrite,t.depthRangeFor3D);if(1!==i||r.paint.get(\"fill-extrusion-pattern\").constantOr(1))nn(t,e,r,n,a,At.disabled,St.disabled),nn(t,e,r,n,a,t.stencilModeFor3D(),t.colorModeForRenderPass());else{var o=t.colorModeForRenderPass();nn(t,e,r,n,a,At.disabled,o)}}},hillshade:function(t,e,r,n){if(\"offscreen\"===t.renderPass||\"translucent\"===t.renderPass){for(var i=t.context,a=e.getSource().maxzoom,o=t.depthModeForSublayer(0,Mt.ReadOnly),s=t.colorModeForRenderPass(),l=\"translucent\"===t.renderPass?t.stencilConfigForOverlap(n):[{},n],c=l[0],u=0,f=l[1];u<f.length;u+=1){var h=f[u],p=e.getTile(h);p.needsHillshadePrepare&&\"offscreen\"===t.renderPass?on(t,p,r,a,o,At.disabled,s):\"translucent\"===t.renderPass&&an(t,p,r,o,c[h.overscaledZ],s)}i.viewport.set([0,0,t.width,t.height])}},raster:function(t,e,r,n){if(\"translucent\"===t.renderPass&&0!==r.paint.get(\"raster-opacity\")&&n.length)for(var i=t.context,a=i.gl,o=e.getSource(),s=t.useProgram(\"raster\"),l=t.colorModeForRenderPass(),c=o instanceof P?[{},n]:t.stencilConfigForOverlap(n),u=c[0],f=c[1],h=f[f.length-1].overscaledZ,p=!t.options.moving,d=0,g=f;d<g.length;d+=1){var m=g[d],v=t.depthModeForSublayer(m.overscaledZ-h,1===r.paint.get(\"raster-opacity\")?Mt.ReadWrite:Mt.ReadOnly,a.LESS),y=e.getTile(m),x=t.transform.calculatePosMatrix(m.toUnwrapped(),p);y.registerFadeDuration(r.paint.get(\"raster-fade-duration\"));var b=e.findLoadedParent(m,0),_=sn(y,b,e,r,t.transform),w=void 0,T=void 0,k=\"nearest\"===r.paint.get(\"raster-resampling\")?a.NEAREST:a.LINEAR;i.activeTexture.set(a.TEXTURE0),y.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),i.activeTexture.set(a.TEXTURE1),b?(b.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),w=Math.pow(2,b.tileID.overscaledZ-y.tileID.overscaledZ),T=[y.tileID.canonical.x*w%1,y.tileID.canonical.y*w%1]):y.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST);var M=jr(x,T||[0,0],w||1,_,r);o instanceof P?s.draw(i,a.TRIANGLES,v,At.disabled,l,Et.disabled,M,r.id,o.boundsBuffer,t.quadTriangleIndexBuffer,o.boundsSegments):s.draw(i,a.TRIANGLES,v,u[m.overscaledZ],l,Et.disabled,M,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}},background:function(t,e,r){var n=r.paint.get(\"background-color\"),i=r.paint.get(\"background-opacity\");if(0!==i){var a=t.context,o=a.gl,s=t.transform,l=s.tileSize,c=r.paint.get(\"background-pattern\");if(!t.isPatternMissing(c)){var u=!c&&1===n.a&&1===i&&t.opaquePassEnabledForLayer()?\"opaque\":\"translucent\";if(t.renderPass===u){var f=At.disabled,h=t.depthModeForSublayer(0,\"opaque\"===u?Mt.ReadWrite:Mt.ReadOnly),p=t.colorModeForRenderPass(),d=t.useProgram(c?\"backgroundPattern\":\"background\"),g=s.coveringTiles({tileSize:l});c&&(a.activeTexture.set(o.TEXTURE0),t.imageManager.bind(t.context));for(var m=r.getCrossfadeParameters(),v=0,y=g;v<y.length;v+=1){var x=y[v],b=t.transform.calculatePosMatrix(x.toUnwrapped()),_=c?Wr(b,i,t,c,{tileID:x,tileSize:l},m):Yr(b,i,n);d.draw(a,o.TRIANGLES,h,f,p,Et.disabled,_,r.id,t.tileExtentBuffer,t.quadTriangleIndexBuffer,t.tileExtentSegments)}}}}},debug:function(t,e,r){for(var n=0;n<r.length;n++)mn(t,e,r[n])},custom:function(t,e,r){var n=t.context,i=r.implementation;if(\"offscreen\"===t.renderPass){var a=i.prerender;a&&(t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),a.call(i,n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState())}else if(\"translucent\"===t.renderPass){t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),n.setStencilMode(At.disabled);var o=\"3d\"===i.renderingMode?new Mt(t.context.gl.LEQUAL,Mt.ReadWrite,t.depthRangeFor3D):t.depthModeForSublayer(0,Mt.ReadOnly);n.setDepthMode(o),i.render(n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState(),n.bindFramebuffer.set(null)}}},yn=function(t,e){this.context=new Ct(t),this.transform=e,this._tileTextures={},this.setup(),this.numSublayers=Lt.maxUnderzooming+Lt.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new Be,this.gpuTimers={}};yn.prototype.resize=function(e,r){if(this.width=e*t.browser.devicePixelRatio,this.height=r*t.browser.devicePixelRatio,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(var n=0,i=this.style._order;n<i.length;n+=1)this.style._layers[i[n]].resize()},yn.prototype.setup=function(){var e=this.context,r=new t.StructArrayLayout2i4;r.emplaceBack(0,0),r.emplaceBack(t.EXTENT,0),r.emplaceBack(0,t.EXTENT),r.emplaceBack(t.EXTENT,t.EXTENT),this.tileExtentBuffer=e.createVertexBuffer(r,He.members),this.tileExtentSegments=t.SegmentVector.simpleSegment(0,0,4,2);var n=new t.StructArrayLayout2i4;n.emplaceBack(0,0),n.emplaceBack(t.EXTENT,0),n.emplaceBack(0,t.EXTENT),n.emplaceBack(t.EXTENT,t.EXTENT),this.debugBuffer=e.createVertexBuffer(n,He.members),this.debugSegments=t.SegmentVector.simpleSegment(0,0,4,5);var i=new t.StructArrayLayout4i8;i.emplaceBack(0,0,0,0),i.emplaceBack(t.EXTENT,0,t.EXTENT,0),i.emplaceBack(0,t.EXTENT,0,t.EXTENT),i.emplaceBack(t.EXTENT,t.EXTENT,t.EXTENT,t.EXTENT),this.rasterBoundsBuffer=e.createVertexBuffer(i,I.members),this.rasterBoundsSegments=t.SegmentVector.simpleSegment(0,0,4,2);var a=new t.StructArrayLayout2i4;a.emplaceBack(0,0),a.emplaceBack(1,0),a.emplaceBack(0,1),a.emplaceBack(1,1),this.viewportBuffer=e.createVertexBuffer(a,He.members),this.viewportSegments=t.SegmentVector.simpleSegment(0,0,4,2);var o=new t.StructArrayLayout1ui2;o.emplaceBack(0),o.emplaceBack(1),o.emplaceBack(3),o.emplaceBack(2),o.emplaceBack(0),this.tileBorderIndexBuffer=e.createIndexBuffer(o);var s=new t.StructArrayLayout3ui6;s.emplaceBack(0,1,2),s.emplaceBack(2,1,3),this.quadTriangleIndexBuffer=e.createIndexBuffer(s),this.emptyTexture=new t.Texture(e,{width:1,height:1,data:new Uint8Array([0,0,0,0])},e.gl.RGBA);var l=this.context.gl;this.stencilClearMode=new At({func:l.ALWAYS,mask:0},0,255,l.ZERO,l.ZERO,l.ZERO)},yn.prototype.clearStencil=function(){var e=this.context,r=e.gl;this.nextStencilID=1,this.currentStencilSource=void 0;var n=t.create();t.ortho(n,0,this.width,this.height,0,0,1),t.scale(n,n,[r.drawingBufferWidth,r.drawingBufferHeight,0]),this.useProgram(\"clippingMask\").draw(e,r.TRIANGLES,Mt.disabled,this.stencilClearMode,St.disabled,Et.disabled,Pr(n),\"$clipping\",this.viewportBuffer,this.quadTriangleIndexBuffer,this.viewportSegments)},yn.prototype._renderTileClippingMasks=function(t,e){if(this.currentStencilSource!==t.source&&t.isTileClipped()&&e&&e.length){this.currentStencilSource=t.source;var r=this.context,n=r.gl;this.nextStencilID+e.length>256&&this.clearStencil(),r.setColorMode(St.disabled),r.setDepthMode(Mt.disabled);var i=this.useProgram(\"clippingMask\");this._tileClippingMaskIDs={};for(var a=0,o=e;a<o.length;a+=1){var s=o[a],l=this._tileClippingMaskIDs[s.key]=this.nextStencilID++;i.draw(r,n.TRIANGLES,Mt.disabled,new At({func:n.ALWAYS,mask:0},l,255,n.KEEP,n.KEEP,n.REPLACE),St.disabled,Et.disabled,Pr(s.posMatrix),\"$clipping\",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}},yn.prototype.stencilModeFor3D=function(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();var t=this.nextStencilID++,e=this.context.gl;return new At({func:e.NOTEQUAL,mask:255},t,255,e.KEEP,e.KEEP,e.REPLACE)},yn.prototype.stencilModeForClipping=function(t){var e=this.context.gl;return new At({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)},yn.prototype.stencilConfigForOverlap=function(t){var e,r=this.context.gl,n=t.sort((function(t,e){return e.overscaledZ-t.overscaledZ})),i=n[n.length-1].overscaledZ,a=n[0].overscaledZ-i+1;if(a>1){this.currentStencilSource=void 0,this.nextStencilID+a>256&&this.clearStencil();for(var o={},s=0;s<a;s++)o[s+i]=new At({func:r.GEQUAL,mask:255},s+this.nextStencilID,255,r.KEEP,r.KEEP,r.REPLACE);return this.nextStencilID+=a,[o,n]}return[(e={},e[i]=At.disabled,e),n]},yn.prototype.colorModeForRenderPass=function(){var e=this.context.gl;return this._showOverdrawInspector?new St([e.CONSTANT_COLOR,e.ONE],new t.Color(1/8,1/8,1/8,0),[!0,!0,!0,!0]):\"opaque\"===this.renderPass?St.unblended:St.alphaBlended},yn.prototype.depthModeForSublayer=function(t,e,r){if(!this.opaquePassEnabledForLayer())return Mt.disabled;var n=1-((1+this.currentLayer)*this.numSublayers+t)*this.depthEpsilon;return new Mt(r||this.context.gl.LEQUAL,e,[n,n])},yn.prototype.opaquePassEnabledForLayer=function(){return this.currentLayer<this.opaquePassCutoff},yn.prototype.render=function(e,r){var n=this;this.style=e,this.options=r,this.lineAtlas=e.lineAtlas,this.imageManager=e.imageManager,this.glyphManager=e.glyphManager,this.symbolFadeChange=e.placement.symbolFadeChange(t.browser.now()),this.imageManager.beginFrame();var i=this.style._order,a=this.style.sourceCaches;for(var o in a){var s=a[o];s.used&&s.prepare(this.context)}var l,c,u={},f={},h={};for(var p in a){var d=a[p];u[p]=d.getVisibleCoordinates(),f[p]=u[p].slice().reverse(),h[p]=d.getVisibleCoordinates(!0).reverse()}this.opaquePassCutoff=1/0;for(var g=0;g<i.length;g++)if(this.style._layers[i[g]].is3D()){this.opaquePassCutoff=g;break}this.renderPass=\"offscreen\";for(var m=0,v=i;m<v.length;m+=1){var y=this.style._layers[v[m]];if(y.hasOffscreenPass()&&!y.isHidden(this.transform.zoom)){var x=f[y.source];(\"custom\"===y.type||x.length)&&this.renderLayer(this,a[y.source],y,x)}}for(this.context.bindFramebuffer.set(null),this.context.clear({color:r.showOverdrawInspector?t.Color.black:t.Color.transparent,depth:1}),this.clearStencil(),this._showOverdrawInspector=r.showOverdrawInspector,this.depthRangeFor3D=[0,1-(e._order.length+2)*this.numSublayers*this.depthEpsilon],this.renderPass=\"opaque\",this.currentLayer=i.length-1;this.currentLayer>=0;this.currentLayer--){var b=this.style._layers[i[this.currentLayer]],_=a[b.source],w=u[b.source];this._renderTileClippingMasks(b,w),this.renderLayer(this,_,b,w)}for(this.renderPass=\"translucent\",this.currentLayer=0;this.currentLayer<i.length;this.currentLayer++){var T=this.style._layers[i[this.currentLayer]],k=a[T.source],M=(\"symbol\"===T.type?h:f)[T.source];this._renderTileClippingMasks(T,u[T.source]),this.renderLayer(this,k,T,M)}this.options.showTileBoundaries&&(t.values(this.style._layers).forEach((function(t){t.source&&!t.isHidden(n.transform.zoom)&&(t.source!==(c&&c.id)&&(c=n.style.sourceCaches[t.source]),(!l||l.getSource().maxzoom<c.getSource().maxzoom)&&(l=c))})),l&&vn.debug(this,l,l.getVisibleCoordinates())),this.options.showPadding&&function(t){var e=t.transform.padding;pn(t,t.transform.height-(e.top||0),3,ln),pn(t,e.bottom||0,3,cn),dn(t,e.left||0,3,un),dn(t,t.transform.width-(e.right||0),3,fn);var r=t.transform.centerPoint;!function(t,e,r,n){gn(t,e-1,r-10,2,20,n),gn(t,e-10,r-1,20,2,n)}(t,r.x,t.transform.height-r.y,hn)}(this),this.context.setDefault()},yn.prototype.renderLayer=function(t,e,r,n){r.isHidden(this.transform.zoom)||(\"background\"===r.type||\"custom\"===r.type||n.length)&&(this.id=r.id,this.gpuTimingStart(r),vn[r.type](t,e,r,n,this.style.placement.variableOffsets),this.gpuTimingEnd())},yn.prototype.gpuTimingStart=function(t){if(this.options.gpuTiming){var e=this.context.extTimerQuery,r=this.gpuTimers[t.id];r||(r=this.gpuTimers[t.id]={calls:0,cpuTime:0,query:e.createQueryEXT()}),r.calls++,e.beginQueryEXT(e.TIME_ELAPSED_EXT,r.query)}},yn.prototype.gpuTimingEnd=function(){if(this.options.gpuTiming){var t=this.context.extTimerQuery;t.endQueryEXT(t.TIME_ELAPSED_EXT)}},yn.prototype.collectGpuTimers=function(){var t=this.gpuTimers;return this.gpuTimers={},t},yn.prototype.queryGpuTimers=function(t){var e={};for(var r in t){var n=t[r],i=this.context.extTimerQuery,a=i.getQueryObjectEXT(n.query,i.QUERY_RESULT_EXT)/1e6;i.deleteQueryEXT(n.query),e[r]=a}return e},yn.prototype.translatePosMatrix=function(e,r,n,i,a){if(!n[0]&&!n[1])return e;var o=a?\"map\"===i?this.transform.angle:0:\"viewport\"===i?-this.transform.angle:0;if(o){var s=Math.sin(o),l=Math.cos(o);n=[n[0]*l-n[1]*s,n[0]*s+n[1]*l]}var c=[a?n[0]:he(r,n[0],this.transform.zoom),a?n[1]:he(r,n[1],this.transform.zoom),0],u=new Float32Array(16);return t.translate(u,e,c),u},yn.prototype.saveTileTexture=function(t){var e=this._tileTextures[t.size[0]];e?e.push(t):this._tileTextures[t.size[0]]=[t]},yn.prototype.getTileTexture=function(t){var e=this._tileTextures[t];return e&&e.length>0?e.pop():null},yn.prototype.isPatternMissing=function(t){if(!t)return!1;if(!t.from||!t.to)return!0;var e=this.imageManager.getPattern(t.from.toString()),r=this.imageManager.getPattern(t.to.toString());return!e||!r},yn.prototype.useProgram=function(t,e){this.cache=this.cache||{};var r=\"\"+t+(e?e.cacheKey:\"\")+(this._showOverdrawInspector?\"/overdraw\":\"\");return this.cache[r]||(this.cache[r]=new br(this.context,yr[t],e,Xr[t],this._showOverdrawInspector)),this.cache[r]},yn.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},yn.prototype.setBaseState=function(){var t=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(t.FUNC_ADD)},yn.prototype.initDebugOverlayCanvas=function(){null==this.debugOverlayCanvas&&(this.debugOverlayCanvas=t.window.document.createElement(\"canvas\"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512,this.debugOverlayTexture=new t.Texture(this.context,this.debugOverlayCanvas,this.context.gl.RGBA))},yn.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var xn=function(t,e){this.points=t,this.planes=e};xn.fromInvProjectionMatrix=function(e,r,n){var i=Math.pow(2,n),a=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map((function(r){return t.transformMat4([],r,e)})).map((function(e){return t.scale$1([],e,1/e[3]/r*i)})),o=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map((function(e){var r=t.sub([],a[e[0]],a[e[1]]),n=t.sub([],a[e[2]],a[e[1]]),i=t.normalize([],t.cross([],r,n)),o=-t.dot(i,a[e[1]]);return i.concat(o)}));return new xn(a,o)};var bn=function(e,r){this.min=e,this.max=r,this.center=t.scale$2([],t.add([],this.min,this.max),.5)};bn.prototype.quadrant=function(e){for(var r=[e%2==0,e<2],n=t.clone$2(this.min),i=t.clone$2(this.max),a=0;a<r.length;a++)n[a]=r[a]?this.min[a]:this.center[a],i[a]=r[a]?this.center[a]:this.max[a];return i[2]=this.max[2],new bn(n,i)},bn.prototype.distanceX=function(t){return Math.max(Math.min(this.max[0],t[0]),this.min[0])-t[0]},bn.prototype.distanceY=function(t){return Math.max(Math.min(this.max[1],t[1]),this.min[1])-t[1]},bn.prototype.intersects=function(e){for(var r=[[this.min[0],this.min[1],0,1],[this.max[0],this.min[1],0,1],[this.max[0],this.max[1],0,1],[this.min[0],this.max[1],0,1]],n=!0,i=0;i<e.planes.length;i++){for(var a=e.planes[i],o=0,s=0;s<r.length;s++)o+=t.dot$1(a,r[s])>=0;if(0===o)return 0;o!==r.length&&(n=!1)}if(n)return 2;for(var l=0;l<3;l++){for(var c=Number.MAX_VALUE,u=-Number.MAX_VALUE,f=0;f<e.points.length;f++){var h=e.points[f][l]-this.min[l];c=Math.min(c,h),u=Math.max(u,h)}if(u<0||c>this.max[l]-this.min[l])return 0}return 1};var _n=function(t,e,r,n){if(void 0===t&&(t=0),void 0===e&&(e=0),void 0===r&&(r=0),void 0===n&&(n=0),isNaN(t)||t<0||isNaN(e)||e<0||isNaN(r)||r<0||isNaN(n)||n<0)throw new Error(\"Invalid value for edge-insets, top, bottom, left and right must all be numbers\");this.top=t,this.bottom=e,this.left=r,this.right=n};_n.prototype.interpolate=function(e,r,n){return null!=r.top&&null!=e.top&&(this.top=t.number(e.top,r.top,n)),null!=r.bottom&&null!=e.bottom&&(this.bottom=t.number(e.bottom,r.bottom,n)),null!=r.left&&null!=e.left&&(this.left=t.number(e.left,r.left,n)),null!=r.right&&null!=e.right&&(this.right=t.number(e.right,r.right,n)),this},_n.prototype.getCenter=function(e,r){var n=t.clamp((this.left+e-this.right)/2,0,e),i=t.clamp((this.top+r-this.bottom)/2,0,r);return new t.Point(n,i)},_n.prototype.equals=function(t){return this.top===t.top&&this.bottom===t.bottom&&this.left===t.left&&this.right===t.right},_n.prototype.clone=function(){return new _n(this.top,this.bottom,this.left,this.right)},_n.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var wn=function(e,r,n,i,a){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=void 0===a||a,this._minZoom=e||0,this._maxZoom=r||22,this._minPitch=null==n?0:n,this._maxPitch=null==i?60:i,this.setMaxBounds(),this.width=0,this.height=0,this._center=new t.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new _n,this._posMatrixCache={},this._alignedPosMatrixCache={}},Tn={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};wn.prototype.clone=function(){var t=new wn(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return t.tileSize=this.tileSize,t.latRange=this.latRange,t.width=this.width,t.height=this.height,t._center=this._center,t.zoom=this.zoom,t.angle=this.angle,t._fov=this._fov,t._pitch=this._pitch,t._unmodified=this._unmodified,t._edgeInsets=this._edgeInsets.clone(),t._calcMatrices(),t},Tn.minZoom.get=function(){return this._minZoom},Tn.minZoom.set=function(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},Tn.maxZoom.get=function(){return this._maxZoom},Tn.maxZoom.set=function(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},Tn.minPitch.get=function(){return this._minPitch},Tn.minPitch.set=function(t){this._minPitch!==t&&(this._minPitch=t,this.pitch=Math.max(this.pitch,t))},Tn.maxPitch.get=function(){return this._maxPitch},Tn.maxPitch.set=function(t){this._maxPitch!==t&&(this._maxPitch=t,this.pitch=Math.min(this.pitch,t))},Tn.renderWorldCopies.get=function(){return this._renderWorldCopies},Tn.renderWorldCopies.set=function(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t},Tn.worldSize.get=function(){return this.tileSize*this.scale},Tn.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},Tn.size.get=function(){return new t.Point(this.width,this.height)},Tn.bearing.get=function(){return-this.angle/Math.PI*180},Tn.bearing.set=function(e){var r=-t.wrap(e,-180,180)*Math.PI/180;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=t.create$2(),t.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},Tn.pitch.get=function(){return this._pitch/Math.PI*180},Tn.pitch.set=function(e){var r=t.clamp(e,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())},Tn.fov.get=function(){return this._fov/Math.PI*180},Tn.fov.set=function(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())},Tn.zoom.get=function(){return this._zoom},Tn.zoom.set=function(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._constrain(),this._calcMatrices())},Tn.center.get=function(){return this._center},Tn.center.set=function(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())},Tn.padding.get=function(){return this._edgeInsets.toJSON()},Tn.padding.set=function(t){this._edgeInsets.equals(t)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,t,1),this._calcMatrices())},Tn.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},wn.prototype.isPaddingEqual=function(t){return this._edgeInsets.equals(t)},wn.prototype.interpolatePadding=function(t,e,r){this._unmodified=!1,this._edgeInsets.interpolate(t,e,r),this._constrain(),this._calcMatrices()},wn.prototype.coveringZoomLevel=function(t){var e=(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize));return Math.max(0,e)},wn.prototype.getVisibleUnwrappedCoordinates=function(e){var r=[new t.UnwrappedTileID(0,e)];if(this._renderWorldCopies)for(var n=this.pointCoordinate(new t.Point(0,0)),i=this.pointCoordinate(new t.Point(this.width,0)),a=this.pointCoordinate(new t.Point(this.width,this.height)),o=this.pointCoordinate(new t.Point(0,this.height)),s=Math.floor(Math.min(n.x,i.x,a.x,o.x)),l=Math.floor(Math.max(n.x,i.x,a.x,o.x)),c=s-1;c<=l+1;c++)0!==c&&r.push(new t.UnwrappedTileID(c,e));return r},wn.prototype.coveringTiles=function(e){var r=this.coveringZoomLevel(e),n=r;if(void 0!==e.minzoom&&r<e.minzoom)return[];void 0!==e.maxzoom&&r>e.maxzoom&&(r=e.maxzoom);var i=t.MercatorCoordinate.fromLngLat(this.center),a=Math.pow(2,r),o=[a*i.x,a*i.y,0],s=xn.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,r),l=e.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(l=r);var c=function(t){return{aabb:new bn([t*a,0,0],[(t+1)*a,a,0]),zoom:0,x:0,y:0,wrap:t,fullyVisible:!1}},u=[],f=[],h=r,p=e.reparseOverscaled?n:r;if(this._renderWorldCopies)for(var d=1;d<=3;d++)u.push(c(-d)),u.push(c(d));for(u.push(c(0));u.length>0;){var g=u.pop(),m=g.x,v=g.y,y=g.fullyVisible;if(!y){var x=g.aabb.intersects(s);if(0===x)continue;y=2===x}var b=g.aabb.distanceX(o),_=g.aabb.distanceY(o),w=Math.max(Math.abs(b),Math.abs(_));if(g.zoom===h||w>3+(1<<h-g.zoom)-2&&g.zoom>=l)f.push({tileID:new t.OverscaledTileID(g.zoom===h?p:g.zoom,g.wrap,g.zoom,m,v),distanceSq:t.sqrLen([o[0]-.5-m,o[1]-.5-v])});else for(var T=0;T<4;T++){var k=(m<<1)+T%2,M=(v<<1)+(T>>1);u.push({aabb:g.aabb.quadrant(T),zoom:g.zoom+1,x:k,y:M,wrap:g.wrap,fullyVisible:y})}}return f.sort((function(t,e){return t.distanceSq-e.distanceSq})).map((function(t){return t.tileID}))},wn.prototype.resize=function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()},Tn.unmodified.get=function(){return this._unmodified},wn.prototype.zoomScale=function(t){return Math.pow(2,t)},wn.prototype.scaleZoom=function(t){return Math.log(t)/Math.LN2},wn.prototype.project=function(e){var r=t.clamp(e.lat,-this.maxValidLatitude,this.maxValidLatitude);return new t.Point(t.mercatorXfromLng(e.lng)*this.worldSize,t.mercatorYfromLat(r)*this.worldSize)},wn.prototype.unproject=function(e){return new t.MercatorCoordinate(e.x/this.worldSize,e.y/this.worldSize).toLngLat()},Tn.point.get=function(){return this.project(this.center)},wn.prototype.setLocationAtPoint=function(e,r){var n=this.pointCoordinate(r),i=this.pointCoordinate(this.centerPoint),a=this.locationCoordinate(e),o=new t.MercatorCoordinate(a.x-(n.x-i.x),a.y-(n.y-i.y));this.center=this.coordinateLocation(o),this._renderWorldCopies&&(this.center=this.center.wrap())},wn.prototype.locationPoint=function(t){return this.coordinatePoint(this.locationCoordinate(t))},wn.prototype.pointLocation=function(t){return this.coordinateLocation(this.pointCoordinate(t))},wn.prototype.locationCoordinate=function(e){return t.MercatorCoordinate.fromLngLat(e)},wn.prototype.coordinateLocation=function(t){return t.toLngLat()},wn.prototype.pointCoordinate=function(e){var r=[e.x,e.y,0,1],n=[e.x,e.y,1,1];t.transformMat4(r,r,this.pixelMatrixInverse),t.transformMat4(n,n,this.pixelMatrixInverse);var i=r[3],a=n[3],o=r[1]/i,s=n[1]/a,l=r[2]/i,c=n[2]/a,u=l===c?0:(0-l)/(c-l);return new t.MercatorCoordinate(t.number(r[0]/i,n[0]/a,u)/this.worldSize,t.number(o,s,u)/this.worldSize)},wn.prototype.coordinatePoint=function(e){var r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix),new t.Point(r[0]/r[3],r[1]/r[3])},wn.prototype.getBounds=function(){return(new t.LngLatBounds).extend(this.pointLocation(new t.Point(0,0))).extend(this.pointLocation(new t.Point(this.width,0))).extend(this.pointLocation(new t.Point(this.width,this.height))).extend(this.pointLocation(new t.Point(0,this.height)))},wn.prototype.getMaxBounds=function(){return this.latRange&&2===this.latRange.length&&this.lngRange&&2===this.lngRange.length?new t.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null},wn.prototype.setMaxBounds=function(t){t?(this.lngRange=[t.getWest(),t.getEast()],this.latRange=[t.getSouth(),t.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},wn.prototype.calculatePosMatrix=function(e,r){void 0===r&&(r=!1);var n=e.key,i=r?this._alignedPosMatrixCache:this._posMatrixCache;if(i[n])return i[n];var a=e.canonical,o=this.worldSize/this.zoomScale(a.z),s=a.x+Math.pow(2,a.z)*e.wrap,l=t.identity(new Float64Array(16));return t.translate(l,l,[s*o,a.y*o,0]),t.scale(l,l,[o/t.EXTENT,o/t.EXTENT,1]),t.multiply(l,r?this.alignedProjMatrix:this.projMatrix,l),i[n]=new Float32Array(l),i[n]},wn.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},wn.prototype._constrain=function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var e,r,n,i,a=-90,o=90,s=-180,l=180,c=this.size,u=this._unmodified;if(this.latRange){var f=this.latRange;a=t.mercatorYfromLat(f[1])*this.worldSize,e=(o=t.mercatorYfromLat(f[0])*this.worldSize)-a<c.y?c.y/(o-a):0}if(this.lngRange){var h=this.lngRange;s=t.mercatorXfromLng(h[0])*this.worldSize,r=(l=t.mercatorXfromLng(h[1])*this.worldSize)-s<c.x?c.x/(l-s):0}var p=this.point,d=Math.max(r||0,e||0);if(d)return this.center=this.unproject(new t.Point(r?(l+s)/2:p.x,e?(o+a)/2:p.y)),this.zoom+=this.scaleZoom(d),this._unmodified=u,void(this._constraining=!1);if(this.latRange){var g=p.y,m=c.y/2;g-m<a&&(i=a+m),g+m>o&&(i=o-m)}if(this.lngRange){var v=p.x,y=c.x/2;v-y<s&&(n=s+y),v+y>l&&(n=l-y)}void 0===n&&void 0===i||(this.center=this.unproject(new t.Point(void 0!==n?n:p.x,void 0!==i?i:p.y))),this._unmodified=u,this._constraining=!1}},wn.prototype._calcMatrices=function(){if(this.height){var e=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(this._fov/2)*this.height;var r=Math.PI/2+this._pitch,n=this._fov*(.5+e.y/this.height),i=Math.sin(n)*this.cameraToCenterDistance/Math.sin(t.clamp(Math.PI-r-n,.01,Math.PI-.01)),a=this.point,o=a.x,s=a.y,l=1.01*(Math.cos(Math.PI/2-this._pitch)*i+this.cameraToCenterDistance),c=this.height/50,u=new Float64Array(16);t.perspective(u,this._fov,this.width/this.height,c,l),u[8]=2*-e.x/this.width,u[9]=2*e.y/this.height,t.scale(u,u,[1,-1,1]),t.translate(u,u,[0,0,-this.cameraToCenterDistance]),t.rotateX(u,u,this._pitch),t.rotateZ(u,u,this.angle),t.translate(u,u,[-o,-s,0]),this.mercatorMatrix=t.scale([],u,[this.worldSize,this.worldSize,this.worldSize]),t.scale(u,u,[1,1,t.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=u,this.invProjMatrix=t.invert([],this.projMatrix);var f=this.width%2/2,h=this.height%2/2,p=Math.cos(this.angle),d=Math.sin(this.angle),g=o-Math.round(o)+p*f+d*h,m=s-Math.round(s)+p*h+d*f,v=new Float64Array(u);if(t.translate(v,v,[g>.5?g-1:g,m>.5?m-1:m,0]),this.alignedProjMatrix=v,u=t.create(),t.scale(u,u,[this.width/2,-this.height/2,1]),t.translate(u,u,[1,-1,0]),this.labelPlaneMatrix=u,u=t.create(),t.scale(u,u,[1,-1,1]),t.translate(u,u,[-1,-1,0]),t.scale(u,u,[2/this.width,2/this.height,1]),this.glCoordMatrix=u,this.pixelMatrix=t.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),!(u=t.invert(new Float64Array(16),this.pixelMatrix)))throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=u,this._posMatrixCache={},this._alignedPosMatrixCache={}}},wn.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var e=this.pointCoordinate(new t.Point(0,0)),r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance},wn.prototype.getCameraPoint=function(){var e=Math.tan(this._pitch)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new t.Point(0,e))},wn.prototype.getCameraQueryGeometry=function(e){var r=this.getCameraPoint();if(1===e.length)return[e[0],r];for(var n=r.x,i=r.y,a=r.x,o=r.y,s=0,l=e;s<l.length;s+=1){var c=l[s];n=Math.min(n,c.x),i=Math.min(i,c.y),a=Math.max(a,c.x),o=Math.max(o,c.y)}return[new t.Point(n,i),new t.Point(a,i),new t.Point(a,o),new t.Point(n,o),new t.Point(n,i)]},Object.defineProperties(wn.prototype,Tn);var kn=function(e){var r,n,i,a;this._hashName=e&&encodeURIComponent(e),t.bindAll([\"_getCurrentHash\",\"_onHashChange\",\"_updateHash\"],this),this._updateHash=(r=this._updateHashUnthrottled.bind(this),n=!1,i=null,a=function(){i=null,n&&(r(),i=setTimeout(a,300),n=!1)},function(){return n=!0,i||a(),i})};kn.prototype.addTo=function(e){return this._map=e,t.window.addEventListener(\"hashchange\",this._onHashChange,!1),this._map.on(\"moveend\",this._updateHash),this},kn.prototype.remove=function(){return t.window.removeEventListener(\"hashchange\",this._onHashChange,!1),this._map.off(\"moveend\",this._updateHash),clearTimeout(this._updateHash()),delete this._map,this},kn.prototype.getHashString=function(e){var r=this._map.getCenter(),n=Math.round(100*this._map.getZoom())/100,i=Math.ceil((n*Math.LN2+Math.log(512/360/.5))/Math.LN10),a=Math.pow(10,i),o=Math.round(r.lng*a)/a,s=Math.round(r.lat*a)/a,l=this._map.getBearing(),c=this._map.getPitch(),u=\"\";if(u+=e?\"/\"+o+\"/\"+s+\"/\"+n:n+\"/\"+s+\"/\"+o,(l||c)&&(u+=\"/\"+Math.round(10*l)/10),c&&(u+=\"/\"+Math.round(c)),this._hashName){var f=this._hashName,h=!1,p=t.window.location.hash.slice(1).split(\"&\").map((function(t){var e=t.split(\"=\")[0];return e===f?(h=!0,e+\"=\"+u):t})).filter((function(t){return t}));return h||p.push(f+\"=\"+u),\"#\"+p.join(\"&\")}return\"#\"+u},kn.prototype._getCurrentHash=function(){var e,r=this,n=t.window.location.hash.replace(\"#\",\"\");return this._hashName?(n.split(\"&\").map((function(t){return t.split(\"=\")})).forEach((function(t){t[0]===r._hashName&&(e=t)})),(e&&e[1]||\"\").split(\"/\")):n.split(\"/\")},kn.prototype._onHashChange=function(){var t=this._getCurrentHash();if(t.length>=3&&!t.some((function(t){return isNaN(t)}))){var e=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(t[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:e,pitch:+(t[4]||0)}),!0}return!1},kn.prototype._updateHashUnthrottled=function(){var e=this.getHashString();try{t.window.history.replaceState(t.window.history.state,\"\",e)}catch(t){}};var Mn={linearity:.3,easing:t.bezier(0,0,.3,1)},An=t.extend({deceleration:2500,maxSpeed:1400},Mn),Sn=t.extend({deceleration:20,maxSpeed:1400},Mn),En=t.extend({deceleration:1e3,maxSpeed:360},Mn),Cn=t.extend({deceleration:1e3,maxSpeed:90},Mn),Ln=function(t){this._map=t,this.clear()};function In(t,e){(!t.duration||t.duration<e.duration)&&(t.duration=e.duration,t.easing=e.easing)}function Pn(e,r,n){var i=n.maxSpeed,a=n.linearity,o=n.deceleration,s=t.clamp(e*a/(r/1e3),-i,i),l=Math.abs(s)/(o*a);return{easing:n.easing,duration:1e3*l,amount:s*(l/2)}}Ln.prototype.clear=function(){this._inertiaBuffer=[]},Ln.prototype.record=function(e){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:t.browser.now(),settings:e})},Ln.prototype._drainInertiaBuffer=function(){for(var e=this._inertiaBuffer,r=t.browser.now();e.length>0&&r-e[0].time>160;)e.shift()},Ln.prototype._onMoveEnd=function(e){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var r={zoom:0,bearing:0,pitch:0,pan:new t.Point(0,0),pinchAround:void 0,around:void 0},n=0,i=this._inertiaBuffer;n<i.length;n+=1){var a=i[n].settings;r.zoom+=a.zoomDelta||0,r.bearing+=a.bearingDelta||0,r.pitch+=a.pitchDelta||0,a.panDelta&&r.pan._add(a.panDelta),a.around&&(r.around=a.around),a.pinchAround&&(r.pinchAround=a.pinchAround)}var o=this._inertiaBuffer[this._inertiaBuffer.length-1].time-this._inertiaBuffer[0].time,s={};if(r.pan.mag()){var l=Pn(r.pan.mag(),o,t.extend({},An,e||{}));s.offset=r.pan.mult(l.amount/r.pan.mag()),s.center=this._map.transform.center,In(s,l)}if(r.zoom){var c=Pn(r.zoom,o,Sn);s.zoom=this._map.transform.zoom+c.amount,In(s,c)}if(r.bearing){var u=Pn(r.bearing,o,En);s.bearing=this._map.transform.bearing+t.clamp(u.amount,-179,179),In(s,u)}if(r.pitch){var f=Pn(r.pitch,o,Cn);s.pitch=this._map.transform.pitch+f.amount,In(s,f)}if(s.zoom||s.bearing){var h=void 0===r.pinchAround?r.around:r.pinchAround;s.around=h?this._map.unproject(h):this._map.getCenter()}return this.clear(),t.extend(s,{noMoveStart:!0})}};var zn=function(e){function n(n,i,a,o){void 0===o&&(o={});var s=r.mousePos(i.getCanvasContainer(),a),l=i.unproject(s);e.call(this,n,t.extend({point:s,lngLat:l,originalEvent:a},o)),this._defaultPrevented=!1,this.target=i}e&&(n.__proto__=e),(n.prototype=Object.create(e&&e.prototype)).constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),On=function(e){function n(n,i,a){var o=\"touchend\"===n?a.changedTouches:a.touches,s=r.touchPos(i.getCanvasContainer(),o),l=s.map((function(t){return i.unproject(t)})),c=s.reduce((function(t,e,r,n){return t.add(e.div(n.length))}),new t.Point(0,0)),u=i.unproject(c);e.call(this,n,{points:s,point:c,lngLats:l,lngLat:u,originalEvent:a}),this._defaultPrevented=!1}e&&(n.__proto__=e),(n.prototype=Object.create(e&&e.prototype)).constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),Dn=function(t){function e(e,r,n){t.call(this,e,{originalEvent:n}),this._defaultPrevented=!1}t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e;var r={defaultPrevented:{configurable:!0}};return e.prototype.preventDefault=function(){this._defaultPrevented=!0},r.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(e.prototype,r),e}(t.Event),Rn=function(t,e){this._map=t,this._clickTolerance=e.clickTolerance};Rn.prototype.reset=function(){delete this._mousedownPos},Rn.prototype.wheel=function(t){return this._firePreventable(new Dn(t.type,this._map,t))},Rn.prototype.mousedown=function(t,e){return this._mousedownPos=e,this._firePreventable(new zn(t.type,this._map,t))},Rn.prototype.mouseup=function(t){this._map.fire(new zn(t.type,this._map,t))},Rn.prototype.click=function(t,e){this._mousedownPos&&this._mousedownPos.dist(e)>=this._clickTolerance||this._map.fire(new zn(t.type,this._map,t))},Rn.prototype.dblclick=function(t){return this._firePreventable(new zn(t.type,this._map,t))},Rn.prototype.mouseover=function(t){this._map.fire(new zn(t.type,this._map,t))},Rn.prototype.mouseout=function(t){this._map.fire(new zn(t.type,this._map,t))},Rn.prototype.touchstart=function(t){return this._firePreventable(new On(t.type,this._map,t))},Rn.prototype.touchmove=function(t){this._map.fire(new On(t.type,this._map,t))},Rn.prototype.touchend=function(t){this._map.fire(new On(t.type,this._map,t))},Rn.prototype.touchcancel=function(t){this._map.fire(new On(t.type,this._map,t))},Rn.prototype._firePreventable=function(t){if(this._map.fire(t),t.defaultPrevented)return{}},Rn.prototype.isEnabled=function(){return!0},Rn.prototype.isActive=function(){return!1},Rn.prototype.enable=function(){},Rn.prototype.disable=function(){};var Fn=function(t){this._map=t};Fn.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},Fn.prototype.mousemove=function(t){this._map.fire(new zn(t.type,this._map,t))},Fn.prototype.mousedown=function(){this._delayContextMenu=!0},Fn.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new zn(\"contextmenu\",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},Fn.prototype.contextmenu=function(t){this._delayContextMenu?this._contextMenuEvent=t:this._map.fire(new zn(t.type,this._map,t)),this._map.listens(\"contextmenu\")&&t.preventDefault()},Fn.prototype.isEnabled=function(){return!0},Fn.prototype.isActive=function(){return!1},Fn.prototype.enable=function(){},Fn.prototype.disable=function(){};var Bn=function(t,e){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),this._clickTolerance=e.clickTolerance||1};function Nn(t,e){for(var r={},n=0;n<t.length;n++)r[t[n].identifier]=e[n];return r}Bn.prototype.isEnabled=function(){return!!this._enabled},Bn.prototype.isActive=function(){return!!this._active},Bn.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},Bn.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},Bn.prototype.mousedown=function(t,e){this.isEnabled()&&t.shiftKey&&0===t.button&&(r.disableDrag(),this._startPos=this._lastPos=e,this._active=!0)},Bn.prototype.mousemoveWindow=function(t,e){if(this._active){var n=e;if(!(this._lastPos.equals(n)||!this._box&&n.dist(this._startPos)<this._clickTolerance)){var i=this._startPos;this._lastPos=n,this._box||(this._box=r.create(\"div\",\"mapboxgl-boxzoom\",this._container),this._container.classList.add(\"mapboxgl-crosshair\"),this._fireEvent(\"boxzoomstart\",t));var a=Math.min(i.x,n.x),o=Math.max(i.x,n.x),s=Math.min(i.y,n.y),l=Math.max(i.y,n.y);r.setTransform(this._box,\"translate(\"+a+\"px,\"+s+\"px)\"),this._box.style.width=o-a+\"px\",this._box.style.height=l-s+\"px\"}}},Bn.prototype.mouseupWindow=function(e,n){var i=this;if(this._active&&0===e.button){var a=this._startPos,o=n;if(this.reset(),r.suppressClick(),a.x!==o.x||a.y!==o.y)return this._map.fire(new t.Event(\"boxzoomend\",{originalEvent:e})),{cameraAnimation:function(t){return t.fitScreenCoordinates(a,o,i._map.getBearing(),{linear:!0})}};this._fireEvent(\"boxzoomcancel\",e)}},Bn.prototype.keydown=function(t){this._active&&27===t.keyCode&&(this.reset(),this._fireEvent(\"boxzoomcancel\",t))},Bn.prototype.reset=function(){this._active=!1,this._container.classList.remove(\"mapboxgl-crosshair\"),this._box&&(r.remove(this._box),this._box=null),r.enableDrag(),delete this._startPos,delete this._lastPos},Bn.prototype._fireEvent=function(e,r){return this._map.fire(new t.Event(e,{originalEvent:r}))};var jn=function(t){this.reset(),this.numTouches=t.numTouches};jn.prototype.reset=function(){delete this.centroid,delete this.startTime,delete this.touches,this.aborted=!1},jn.prototype.touchstart=function(e,r,n){(this.centroid||n.length>this.numTouches)&&(this.aborted=!0),this.aborted||(void 0===this.startTime&&(this.startTime=e.timeStamp),n.length===this.numTouches&&(this.centroid=function(e){for(var r=new t.Point(0,0),n=0,i=e;n<i.length;n+=1)r._add(i[n]);return r.div(e.length)}(r),this.touches=Nn(n,r)))},jn.prototype.touchmove=function(t,e,r){if(!this.aborted&&this.centroid){var n=Nn(r,e);for(var i in this.touches){var a=n[i];(!a||a.dist(this.touches[i])>30)&&(this.aborted=!0)}}},jn.prototype.touchend=function(t,e,r){if((!this.centroid||t.timeStamp-this.startTime>500)&&(this.aborted=!0),0===r.length){var n=!this.aborted&&this.centroid;if(this.reset(),n)return n}};var Un=function(t){this.singleTap=new jn(t),this.numTaps=t.numTaps,this.reset()};Un.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},Un.prototype.touchstart=function(t,e,r){this.singleTap.touchstart(t,e,r)},Un.prototype.touchmove=function(t,e,r){this.singleTap.touchmove(t,e,r)},Un.prototype.touchend=function(t,e,r){var n=this.singleTap.touchend(t,e,r);if(n){var i=t.timeStamp-this.lastTime<500,a=!this.lastTap||this.lastTap.dist(n)<30;if(i&&a||this.reset(),this.count++,this.lastTime=t.timeStamp,this.lastTap=n,this.count===this.numTaps)return this.reset(),n}};var Vn=function(){this._zoomIn=new Un({numTouches:1,numTaps:2}),this._zoomOut=new Un({numTouches:2,numTaps:1}),this.reset()};Vn.prototype.reset=function(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()},Vn.prototype.touchstart=function(t,e,r){this._zoomIn.touchstart(t,e,r),this._zoomOut.touchstart(t,e,r)},Vn.prototype.touchmove=function(t,e,r){this._zoomIn.touchmove(t,e,r),this._zoomOut.touchmove(t,e,r)},Vn.prototype.touchend=function(t,e,r){var n=this,i=this._zoomIn.touchend(t,e,r),a=this._zoomOut.touchend(t,e,r);return i?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()+1,around:e.unproject(i)},{originalEvent:t})}}):a?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()-1,around:e.unproject(a)},{originalEvent:t})}}):void 0},Vn.prototype.touchcancel=function(){this.reset()},Vn.prototype.enable=function(){this._enabled=!0},Vn.prototype.disable=function(){this._enabled=!1,this.reset()},Vn.prototype.isEnabled=function(){return this._enabled},Vn.prototype.isActive=function(){return this._active};var qn=function(t){this.reset(),this._clickTolerance=t.clickTolerance||1};qn.prototype.reset=function(){this._active=!1,this._moved=!1,delete this._lastPoint,delete this._eventButton},qn.prototype._correctButton=function(t,e){return!1},qn.prototype._move=function(t,e){return{}},qn.prototype.mousedown=function(t,e){if(!this._lastPoint){var n=r.mouseButton(t);this._correctButton(t,n)&&(this._lastPoint=e,this._eventButton=n)}},qn.prototype.mousemoveWindow=function(t,e){var r=this._lastPoint;if(r&&(t.preventDefault(),this._moved||!(e.dist(r)<this._clickTolerance)))return this._moved=!0,this._lastPoint=e,this._move(r,e)},qn.prototype.mouseupWindow=function(t){r.mouseButton(t)===this._eventButton&&(this._moved&&r.suppressClick(),this.reset())},qn.prototype.enable=function(){this._enabled=!0},qn.prototype.disable=function(){this._enabled=!1,this.reset()},qn.prototype.isEnabled=function(){return this._enabled},qn.prototype.isActive=function(){return this._active};var Hn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.mousedown=function(e,r){t.prototype.mousedown.call(this,e,r),this._lastPoint&&(this._active=!0)},e.prototype._correctButton=function(t,e){return 0===e&&!t.ctrlKey},e.prototype._move=function(t,e){return{around:e,panDelta:e.sub(t)}},e}(qn),Gn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=.8*(e.x-t.x);if(r)return this._active=!0,{bearingDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(qn),Yn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=-.5*(e.y-t.y);if(r)return this._active=!0,{pitchDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(qn),Wn=function(t){this._minTouches=1,this._clickTolerance=t.clickTolerance||1,this.reset()};Wn.prototype.reset=function(){this._active=!1,this._touches={},this._sum=new t.Point(0,0)},Wn.prototype.touchstart=function(t,e,r){return this._calculateTransform(t,e,r)},Wn.prototype.touchmove=function(t,e,r){if(this._active)return t.preventDefault(),this._calculateTransform(t,e,r)},Wn.prototype.touchend=function(t,e,r){this._calculateTransform(t,e,r),this._active&&r.length<this._minTouches&&this.reset()},Wn.prototype.touchcancel=function(){this.reset()},Wn.prototype._calculateTransform=function(e,r,n){n.length>0&&(this._active=!0);var i=Nn(n,r),a=new t.Point(0,0),o=new t.Point(0,0),s=0;for(var l in i){var c=i[l],u=this._touches[l];u&&(a._add(c),o._add(c.sub(u)),s++,i[l]=c)}if(this._touches=i,!(s<this._minTouches)&&o.mag()){var f=o.div(s);if(this._sum._add(f),!(this._sum.mag()<this._clickTolerance))return{around:a.div(s),panDelta:f}}},Wn.prototype.enable=function(){this._enabled=!0},Wn.prototype.disable=function(){this._enabled=!1,this.reset()},Wn.prototype.isEnabled=function(){return this._enabled},Wn.prototype.isActive=function(){return this._active};var Xn=function(){this.reset()};function Zn(t,e,r){for(var n=0;n<t.length;n++)if(t[n].identifier===r)return e[n]}function Jn(t,e){return Math.log(t/e)/Math.LN2}Xn.prototype.reset=function(){this._active=!1,delete this._firstTwoTouches},Xn.prototype._start=function(t){},Xn.prototype._move=function(t,e,r){return{}},Xn.prototype.touchstart=function(t,e,r){this._firstTwoTouches||r.length<2||(this._firstTwoTouches=[r[0].identifier,r[1].identifier],this._start([e[0],e[1]]))},Xn.prototype.touchmove=function(t,e,r){if(this._firstTwoTouches){t.preventDefault();var n=this._firstTwoTouches,i=n[1],a=Zn(r,e,n[0]),o=Zn(r,e,i);if(a&&o){var s=this._aroundCenter?null:a.add(o).div(2);return this._move([a,o],s,t)}}},Xn.prototype.touchend=function(t,e,n){if(this._firstTwoTouches){var i=this._firstTwoTouches,a=i[1],o=Zn(n,e,i[0]),s=Zn(n,e,a);o&&s||(this._active&&r.suppressClick(),this.reset())}},Xn.prototype.touchcancel=function(){this.reset()},Xn.prototype.enable=function(t){this._enabled=!0,this._aroundCenter=!!t&&\"center\"===t.around},Xn.prototype.disable=function(){this._enabled=!1,this.reset()},Xn.prototype.isEnabled=function(){return this._enabled},Xn.prototype.isActive=function(){return this._active};var Kn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._distance,delete this._startDistance},e.prototype._start=function(t){this._startDistance=this._distance=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._distance;if(this._distance=t[0].dist(t[1]),this._active||!(Math.abs(Jn(this._distance,this._startDistance))<.1))return this._active=!0,{zoomDelta:Jn(this._distance,r),pinchAround:e}},e}(Xn);function Qn(t,e){return 180*t.angleWith(e)/Math.PI}var $n=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._minDiameter,delete this._startVector,delete this._vector},e.prototype._start=function(t){this._startVector=this._vector=t[0].sub(t[1]),this._minDiameter=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._vector;if(this._vector=t[0].sub(t[1]),this._active||!this._isBelowThreshold(this._vector))return this._active=!0,{bearingDelta:Qn(this._vector,r),pinchAround:e}},e.prototype._isBelowThreshold=function(t){this._minDiameter=Math.min(this._minDiameter,t.mag());var e=25/(Math.PI*this._minDiameter)*360,r=Qn(t,this._startVector);return Math.abs(r)<e},e}(Xn);function ti(t){return Math.abs(t.y)>Math.abs(t.x)}var ei=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},e.prototype._start=function(t){this._lastPoints=t,ti(t[0].sub(t[1]))&&(this._valid=!1)},e.prototype._move=function(t,e,r){var n=t[0].sub(this._lastPoints[0]),i=t[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(n,i,r.timeStamp),this._valid)return this._lastPoints=t,this._active=!0,{pitchDelta:(n.y+i.y)/2*-.5}},e.prototype.gestureBeginsVertically=function(t,e,r){if(void 0!==this._valid)return this._valid;var n=t.mag()>=2,i=e.mag()>=2;if(n||i){if(!n||!i)return void 0===this._firstMove&&(this._firstMove=r),r-this._firstMove<100&&void 0;var a=t.y>0==e.y>0;return ti(t)&&ti(e)&&a}},e}(Xn),ri={panStep:100,bearingStep:15,pitchStep:10},ni=function(){var t=ri;this._panStep=t.panStep,this._bearingStep=t.bearingStep,this._pitchStep=t.pitchStep};function ii(t){return t*(2-t)}ni.prototype.reset=function(){this._active=!1},ni.prototype.keydown=function(t){var e=this;if(!(t.altKey||t.ctrlKey||t.metaKey)){var r=0,n=0,i=0,a=0,o=0;switch(t.keyCode){case 61:case 107:case 171:case 187:r=1;break;case 189:case 109:case 173:r=-1;break;case 37:t.shiftKey?n=-1:(t.preventDefault(),a=-1);break;case 39:t.shiftKey?n=1:(t.preventDefault(),a=1);break;case 38:t.shiftKey?i=1:(t.preventDefault(),o=-1);break;case 40:t.shiftKey?i=-1:(t.preventDefault(),o=1);break;default:return}return{cameraAnimation:function(s){var l=s.getZoom();s.easeTo({duration:300,easeId:\"keyboardHandler\",easing:ii,zoom:r?Math.round(l)+r*(t.shiftKey?2:1):l,bearing:s.getBearing()+n*e._bearingStep,pitch:s.getPitch()+i*e._pitchStep,offset:[-a*e._panStep,-o*e._panStep],center:s.getCenter()},{originalEvent:t})}}}},ni.prototype.enable=function(){this._enabled=!0},ni.prototype.disable=function(){this._enabled=!1,this.reset()},ni.prototype.isEnabled=function(){return this._enabled},ni.prototype.isActive=function(){return this._active};var ai=function(e,r){this._map=e,this._el=e.getCanvasContainer(),this._handler=r,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=1/450,t.bindAll([\"_onWheel\",\"_onTimeout\",\"_onScrollFrame\",\"_onScrollFinished\"],this)};ai.prototype.setZoomRate=function(t){this._defaultZoomRate=t},ai.prototype.setWheelZoomRate=function(t){this._wheelZoomRate=t},ai.prototype.isEnabled=function(){return!!this._enabled},ai.prototype.isActive=function(){return!!this._active||void 0!==this._finishTimeout},ai.prototype.isZooming=function(){return!!this._zooming},ai.prototype.enable=function(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=t&&\"center\"===t.around)},ai.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},ai.prototype.wheel=function(e){if(this.isEnabled()){var r=e.deltaMode===t.window.WheelEvent.DOM_DELTA_LINE?40*e.deltaY:e.deltaY,n=t.browser.now(),i=n-(this._lastWheelEventTime||0);this._lastWheelEventTime=n,0!==r&&r%4.000244140625==0?this._type=\"wheel\":0!==r&&Math.abs(r)<4?this._type=\"trackpad\":i>400?(this._type=null,this._lastValue=r,this._timeout=setTimeout(this._onTimeout,40,e)):this._type||(this._type=Math.abs(i*r)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,r+=this._lastValue)),e.shiftKey&&r&&(r/=4),this._type&&(this._lastWheelEvent=e,this._delta-=r,this._active||this._start(e)),e.preventDefault()}},ai.prototype._onTimeout=function(t){this._type=\"wheel\",this._delta-=this._lastValue,this._active||this._start(t)},ai.prototype._start=function(e){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var n=r.mousePos(this._el,e);this._around=t.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(n)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},ai.prototype.renderFrame=function(){return this._onScrollFrame()},ai.prototype._onScrollFrame=function(){var e=this;if(this._frameId&&(this._frameId=null,this.isActive())){var r=this._map.transform;if(0!==this._delta){var n=\"wheel\"===this._type&&Math.abs(this._delta)>4.000244140625?this._wheelZoomRate:this._defaultZoomRate,i=2/(1+Math.exp(-Math.abs(this._delta*n)));this._delta<0&&0!==i&&(i=1/i);var a=\"number\"==typeof this._targetZoom?r.zoomScale(this._targetZoom):r.scale;this._targetZoom=Math.min(r.maxZoom,Math.max(r.minZoom,r.scaleZoom(a*i))),\"wheel\"===this._type&&(this._startZoom=r.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var o,s=\"number\"==typeof this._targetZoom?this._targetZoom:r.zoom,l=this._startZoom,c=this._easing,u=!1;if(\"wheel\"===this._type&&l&&c){var f=Math.min((t.browser.now()-this._lastWheelEventTime)/200,1),h=c(f);o=t.number(l,s,h),f<1?this._frameId||(this._frameId=!0):u=!0}else o=s,u=!0;return this._active=!0,u&&(this._active=!1,this._finishTimeout=setTimeout((function(){e._zooming=!1,e._handler._triggerRenderFrame(),delete e._targetZoom,delete e._finishTimeout}),200)),{noInertia:!0,needsRenderFrame:!u,zoomDelta:o-r.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},ai.prototype._smoothOutEasing=function(e){var r=t.ease;if(this._prevEase){var n=this._prevEase,i=(t.browser.now()-n.start)/n.duration,a=n.easing(i+.01)-n.easing(i),o=.27/Math.sqrt(a*a+1e-4)*.01,s=Math.sqrt(.0729-o*o);r=t.bezier(o,s,.25,1)}return this._prevEase={start:t.browser.now(),duration:e,easing:r},r},ai.prototype.reset=function(){this._active=!1};var oi=function(t,e){this._clickZoom=t,this._tapZoom=e};oi.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},oi.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},oi.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},oi.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var si=function(){this.reset()};si.prototype.reset=function(){this._active=!1},si.prototype.dblclick=function(t,e){return t.preventDefault(),{cameraAnimation:function(r){r.easeTo({duration:300,zoom:r.getZoom()+(t.shiftKey?-1:1),around:r.unproject(e)},{originalEvent:t})}}},si.prototype.enable=function(){this._enabled=!0},si.prototype.disable=function(){this._enabled=!1,this.reset()},si.prototype.isEnabled=function(){return this._enabled},si.prototype.isActive=function(){return this._active};var li=function(){this._tap=new Un({numTouches:1,numTaps:1}),this.reset()};li.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},li.prototype.touchstart=function(t,e,r){this._swipePoint||(this._tapTime&&t.timeStamp-this._tapTime>500&&this.reset(),this._tapTime?r.length>0&&(this._swipePoint=e[0],this._swipeTouch=r[0].identifier):this._tap.touchstart(t,e,r))},li.prototype.touchmove=function(t,e,r){if(this._tapTime){if(this._swipePoint){if(r[0].identifier!==this._swipeTouch)return;var n=e[0],i=n.y-this._swipePoint.y;return this._swipePoint=n,t.preventDefault(),this._active=!0,{zoomDelta:i/128}}}else this._tap.touchmove(t,e,r)},li.prototype.touchend=function(t,e,r){this._tapTime?this._swipePoint&&0===r.length&&this.reset():this._tap.touchend(t,e,r)&&(this._tapTime=t.timeStamp)},li.prototype.touchcancel=function(){this.reset()},li.prototype.enable=function(){this._enabled=!0},li.prototype.disable=function(){this._enabled=!1,this.reset()},li.prototype.isEnabled=function(){return this._enabled},li.prototype.isActive=function(){return this._active};var ci=function(t,e,r){this._el=t,this._mousePan=e,this._touchPan=r};ci.prototype.enable=function(t){this._inertiaOptions=t||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add(\"mapboxgl-touch-drag-pan\")},ci.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove(\"mapboxgl-touch-drag-pan\")},ci.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},ci.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var ui=function(t,e,r){this._pitchWithRotate=t.pitchWithRotate,this._mouseRotate=e,this._mousePitch=r};ui.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},ui.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},ui.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},ui.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var fi=function(t,e,r,n){this._el=t,this._touchZoom=e,this._touchRotate=r,this._tapDragZoom=n,this._rotationDisabled=!1,this._enabled=!0};fi.prototype.enable=function(t){this._touchZoom.enable(t),this._rotationDisabled||this._touchRotate.enable(t),this._tapDragZoom.enable(),this._el.classList.add(\"mapboxgl-touch-zoom-rotate\")},fi.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove(\"mapboxgl-touch-zoom-rotate\")},fi.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},fi.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},fi.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},fi.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var hi=function(t){return t.zoom||t.drag||t.pitch||t.rotate},pi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e}(t.Event);function di(t){return t.panDelta&&t.panDelta.mag()||t.zoomDelta||t.bearingDelta||t.pitchDelta}var gi=function(e,n){this._map=e,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new Ln(e),this._bearingSnap=n.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(n),t.bindAll([\"handleEvent\",\"handleWindowEvent\"],this);var i=this._el;this._listeners=[[i,\"touchstart\",{passive:!1}],[i,\"touchmove\",{passive:!1}],[i,\"touchend\",void 0],[i,\"touchcancel\",void 0],[i,\"mousedown\",void 0],[i,\"mousemove\",void 0],[i,\"mouseup\",void 0],[t.window.document,\"mousemove\",{capture:!0}],[t.window.document,\"mouseup\",void 0],[i,\"mouseover\",void 0],[i,\"mouseout\",void 0],[i,\"dblclick\",void 0],[i,\"click\",void 0],[i,\"keydown\",{capture:!1}],[i,\"keyup\",void 0],[i,\"wheel\",{passive:!1}],[i,\"contextmenu\",void 0],[t.window,\"blur\",void 0]];for(var a=0,o=this._listeners;a<o.length;a+=1){var s=o[a],l=s[0];r.addEventListener(l,s[1],l===t.window.document?this.handleWindowEvent:this.handleEvent,s[2])}};gi.prototype.destroy=function(){for(var e=0,n=this._listeners;e<n.length;e+=1){var i=n[e],a=i[0];r.removeEventListener(a,i[1],a===t.window.document?this.handleWindowEvent:this.handleEvent,i[2])}},gi.prototype._addDefaultHandlers=function(t){var e=this._map,r=e.getCanvasContainer();this._add(\"mapEvent\",new Rn(e,t));var n=e.boxZoom=new Bn(e,t);this._add(\"boxZoom\",n);var i=new Vn,a=new si;e.doubleClickZoom=new oi(a,i),this._add(\"tapZoom\",i),this._add(\"clickZoom\",a);var o=new li;this._add(\"tapDragZoom\",o);var s=e.touchPitch=new ei;this._add(\"touchPitch\",s);var l=new Gn(t),c=new Yn(t);e.dragRotate=new ui(t,l,c),this._add(\"mouseRotate\",l,[\"mousePitch\"]),this._add(\"mousePitch\",c,[\"mouseRotate\"]);var u=new Hn(t),f=new Wn(t);e.dragPan=new ci(r,u,f),this._add(\"mousePan\",u),this._add(\"touchPan\",f,[\"touchZoom\",\"touchRotate\"]);var h=new $n,p=new Kn;e.touchZoomRotate=new fi(r,p,h,o),this._add(\"touchRotate\",h,[\"touchPan\",\"touchZoom\"]),this._add(\"touchZoom\",p,[\"touchPan\",\"touchRotate\"]);var d=e.scrollZoom=new ai(e,this);this._add(\"scrollZoom\",d,[\"mousePan\"]);var g=e.keyboard=new ni;this._add(\"keyboard\",g),this._add(\"blockableMapEvent\",new Fn(e));for(var m=0,v=[\"boxZoom\",\"doubleClickZoom\",\"tapDragZoom\",\"touchPitch\",\"dragRotate\",\"dragPan\",\"touchZoomRotate\",\"scrollZoom\",\"keyboard\"];m<v.length;m+=1){var y=v[m];t.interactive&&t[y]&&e[y].enable(t[y])}},gi.prototype._add=function(t,e,r){this._handlers.push({handlerName:t,handler:e,allowed:r}),this._handlersById[t]=e},gi.prototype.stop=function(){if(!this._updatingCamera){for(var t=0,e=this._handlers;t<e.length;t+=1)e[t].handler.reset();this._inertia.clear(),this._fireEvents({},{}),this._changes=[]}},gi.prototype.isActive=function(){for(var t=0,e=this._handlers;t<e.length;t+=1)if(e[t].handler.isActive())return!0;return!1},gi.prototype.isZooming=function(){return!!this._eventsInProgress.zoom||this._map.scrollZoom.isZooming()},gi.prototype.isRotating=function(){return!!this._eventsInProgress.rotate},gi.prototype.isMoving=function(){return Boolean(hi(this._eventsInProgress))||this.isZooming()},gi.prototype._blockedByActive=function(t,e,r){for(var n in t)if(n!==r&&(!e||e.indexOf(n)<0))return!0;return!1},gi.prototype.handleWindowEvent=function(t){this.handleEvent(t,t.type+\"Window\")},gi.prototype._getMapTouches=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r];this._el.contains(i.target)&&e.push(i)}return e},gi.prototype.handleEvent=function(t,e){if(\"blur\"!==t.type){this._updatingCamera=!0;for(var n=\"renderFrame\"===t.type?void 0:t,i={needsRenderFrame:!1},a={},o={},s=t.touches?this._getMapTouches(t.touches):void 0,l=s?r.touchPos(this._el,s):r.mousePos(this._el,t),c=0,u=this._handlers;c<u.length;c+=1){var f=u[c],h=f.handlerName,p=f.handler,d=f.allowed;if(p.isEnabled()){var g=void 0;this._blockedByActive(o,d,h)?p.reset():p[e||t.type]&&(g=p[e||t.type](t,l,s),this.mergeHandlerResult(i,a,g,h,n),g&&g.needsRenderFrame&&this._triggerRenderFrame()),(g||p.isActive())&&(o[h]=p)}}var m={};for(var v in this._previousActiveHandlers)o[v]||(m[v]=n);this._previousActiveHandlers=o,(Object.keys(m).length||di(i))&&(this._changes.push([i,a,m]),this._triggerRenderFrame()),(Object.keys(o).length||di(i))&&this._map._stop(!0),this._updatingCamera=!1;var y=i.cameraAnimation;y&&(this._inertia.clear(),this._fireEvents({},{}),this._changes=[],y(this._map))}else this.stop()},gi.prototype.mergeHandlerResult=function(e,r,n,i,a){if(n){t.extend(e,n);var o={handlerName:i,originalEvent:n.originalEvent||a};void 0!==n.zoomDelta&&(r.zoom=o),void 0!==n.panDelta&&(r.drag=o),void 0!==n.pitchDelta&&(r.pitch=o),void 0!==n.bearingDelta&&(r.rotate=o)}},gi.prototype._applyChanges=function(){for(var e={},r={},n={},i=0,a=this._changes;i<a.length;i+=1){var o=a[i],s=o[0],l=o[1],c=o[2];s.panDelta&&(e.panDelta=(e.panDelta||new t.Point(0,0))._add(s.panDelta)),s.zoomDelta&&(e.zoomDelta=(e.zoomDelta||0)+s.zoomDelta),s.bearingDelta&&(e.bearingDelta=(e.bearingDelta||0)+s.bearingDelta),s.pitchDelta&&(e.pitchDelta=(e.pitchDelta||0)+s.pitchDelta),void 0!==s.around&&(e.around=s.around),void 0!==s.pinchAround&&(e.pinchAround=s.pinchAround),s.noInertia&&(e.noInertia=s.noInertia),t.extend(r,l),t.extend(n,c)}this._updateMapTransform(e,r,n),this._changes=[]},gi.prototype._updateMapTransform=function(t,e,r){var n=this._map,i=n.transform;if(!di(t))return this._fireEvents(e,r);var a=t.panDelta,o=t.zoomDelta,s=t.bearingDelta,l=t.pitchDelta,c=t.around,u=t.pinchAround;void 0!==u&&(c=u),n._stop(!0),c=c||n.transform.centerPoint;var f=i.pointLocation(a?c.sub(a):c);s&&(i.bearing+=s),l&&(i.pitch+=l),o&&(i.zoom+=o),i.setLocationAtPoint(f,c),this._map._update(),t.noInertia||this._inertia.record(t),this._fireEvents(e,r)},gi.prototype._fireEvents=function(e,r){var n=this,i=hi(this._eventsInProgress),a=hi(e),o={};for(var s in e)this._eventsInProgress[s]||(o[s+\"start\"]=e[s].originalEvent),this._eventsInProgress[s]=e[s];for(var l in!i&&a&&this._fireEvent(\"movestart\",a.originalEvent),o)this._fireEvent(l,o[l]);for(var c in e.rotate&&(this._bearingChanged=!0),a&&this._fireEvent(\"move\",a.originalEvent),e)this._fireEvent(c,e[c].originalEvent);var u,f={};for(var h in this._eventsInProgress){var p=this._eventsInProgress[h],d=p.handlerName,g=p.originalEvent;this._handlersById[d].isActive()||(delete this._eventsInProgress[h],f[h+\"end\"]=u=r[d]||g)}for(var m in f)this._fireEvent(m,f[m]);var v=hi(this._eventsInProgress);if((i||a)&&!v){this._updatingCamera=!0;var y=this._inertia._onMoveEnd(this._map.dragPan._inertiaOptions),x=function(t){return 0!==t&&-n._bearingSnap<t&&t<n._bearingSnap};y?(x(y.bearing||this._map.getBearing())&&(y.bearing=0),this._map.easeTo(y,{originalEvent:u})):(this._map.fire(new t.Event(\"moveend\",{originalEvent:u})),x(this._map.getBearing())&&this._map.resetNorth()),this._bearingChanged=!1,this._updatingCamera=!1}},gi.prototype._fireEvent=function(e,r){this._map.fire(new t.Event(e,r?{originalEvent:r}:{}))},gi.prototype._triggerRenderFrame=function(){var t=this;void 0===this._frameId&&(this._frameId=this._map._requestRenderFrame((function(e){delete t._frameId,t.handleEvent(new pi(\"renderFrame\",{timeStamp:e})),t._applyChanges()})))};var mi=function(e){function r(r,n){e.call(this),this._moving=!1,this._zooming=!1,this.transform=r,this._bearingSnap=n.bearingSnap,t.bindAll([\"_renderFrameCallback\"],this)}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.getCenter=function(){return new t.LngLat(this.transform.center.lng,this.transform.center.lat)},r.prototype.setCenter=function(t,e){return this.jumpTo({center:t},e)},r.prototype.panBy=function(e,r,n){return e=t.Point.convert(e).mult(-1),this.panTo(this.transform.center,t.extend({offset:e},r),n)},r.prototype.panTo=function(e,r,n){return this.easeTo(t.extend({center:e},r),n)},r.prototype.getZoom=function(){return this.transform.zoom},r.prototype.setZoom=function(t,e){return this.jumpTo({zoom:t},e),this},r.prototype.zoomTo=function(e,r,n){return this.easeTo(t.extend({zoom:e},r),n)},r.prototype.zoomIn=function(t,e){return this.zoomTo(this.getZoom()+1,t,e),this},r.prototype.zoomOut=function(t,e){return this.zoomTo(this.getZoom()-1,t,e),this},r.prototype.getBearing=function(){return this.transform.bearing},r.prototype.setBearing=function(t,e){return this.jumpTo({bearing:t},e),this},r.prototype.getPadding=function(){return this.transform.padding},r.prototype.setPadding=function(t,e){return this.jumpTo({padding:t},e),this},r.prototype.rotateTo=function(e,r,n){return this.easeTo(t.extend({bearing:e},r),n)},r.prototype.resetNorth=function(e,r){return this.rotateTo(0,t.extend({duration:1e3},e),r),this},r.prototype.resetNorthPitch=function(e,r){return this.easeTo(t.extend({bearing:0,pitch:0,duration:1e3},e),r),this},r.prototype.snapToNorth=function(t,e){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(t,e):this},r.prototype.getPitch=function(){return this.transform.pitch},r.prototype.setPitch=function(t,e){return this.jumpTo({pitch:t},e),this},r.prototype.cameraForBounds=function(e,r){return e=t.LngLatBounds.convert(e),this._cameraForBoxAndBearing(e.getNorthWest(),e.getSouthEast(),0,r)},r.prototype._cameraForBoxAndBearing=function(e,r,n,i){var a={top:0,bottom:0,right:0,left:0};if(\"number\"==typeof(i=t.extend({padding:a,offset:[0,0],maxZoom:this.transform.maxZoom},i)).padding){var o=i.padding;i.padding={top:o,bottom:o,right:o,left:o}}i.padding=t.extend(a,i.padding);var s=this.transform,l=s.padding,c=s.project(t.LngLat.convert(e)),u=s.project(t.LngLat.convert(r)),f=c.rotate(-n*Math.PI/180),h=u.rotate(-n*Math.PI/180),p=new t.Point(Math.max(f.x,h.x),Math.max(f.y,h.y)),d=new t.Point(Math.min(f.x,h.x),Math.min(f.y,h.y)),g=p.sub(d),m=(s.width-(l.left+l.right+i.padding.left+i.padding.right))/g.x,v=(s.height-(l.top+l.bottom+i.padding.top+i.padding.bottom))/g.y;if(!(v<0||m<0)){var y=Math.min(s.scaleZoom(s.scale*Math.min(m,v)),i.maxZoom),x=t.Point.convert(i.offset),b=new t.Point(x.x+(i.padding.left-i.padding.right)/2,x.y+(i.padding.top-i.padding.bottom)/2).mult(s.scale/s.zoomScale(y));return{center:s.unproject(c.add(u).div(2).sub(b)),zoom:y,bearing:n}}t.warnOnce(\"Map cannot fit within canvas with the given bounds, padding, and/or offset.\")},r.prototype.fitBounds=function(t,e,r){return this._fitInternal(this.cameraForBounds(t,e),e,r)},r.prototype.fitScreenCoordinates=function(e,r,n,i,a){return this._fitInternal(this._cameraForBoxAndBearing(this.transform.pointLocation(t.Point.convert(e)),this.transform.pointLocation(t.Point.convert(r)),n,i),i,a)},r.prototype._fitInternal=function(e,r,n){return e?(delete(r=t.extend(e,r)).padding,r.linear?this.easeTo(r,n):this.flyTo(r,n)):this},r.prototype.jumpTo=function(e,r){this.stop();var n=this.transform,i=!1,a=!1,o=!1;return\"zoom\"in e&&n.zoom!==+e.zoom&&(i=!0,n.zoom=+e.zoom),void 0!==e.center&&(n.center=t.LngLat.convert(e.center)),\"bearing\"in e&&n.bearing!==+e.bearing&&(a=!0,n.bearing=+e.bearing),\"pitch\"in e&&n.pitch!==+e.pitch&&(o=!0,n.pitch=+e.pitch),null==e.padding||n.isPaddingEqual(e.padding)||(n.padding=e.padding),this.fire(new t.Event(\"movestart\",r)).fire(new t.Event(\"move\",r)),i&&this.fire(new t.Event(\"zoomstart\",r)).fire(new t.Event(\"zoom\",r)).fire(new t.Event(\"zoomend\",r)),a&&this.fire(new t.Event(\"rotatestart\",r)).fire(new t.Event(\"rotate\",r)).fire(new t.Event(\"rotateend\",r)),o&&this.fire(new t.Event(\"pitchstart\",r)).fire(new t.Event(\"pitch\",r)).fire(new t.Event(\"pitchend\",r)),this.fire(new t.Event(\"moveend\",r))},r.prototype.easeTo=function(e,r){var n=this;this._stop(!1,e.easeId),(!1===(e=t.extend({offset:[0,0],duration:500,easing:t.ease},e)).animate||!e.essential&&t.browser.prefersReducedMotion)&&(e.duration=0);var i=this.transform,a=this.getZoom(),o=this.getBearing(),s=this.getPitch(),l=this.getPadding(),c=\"zoom\"in e?+e.zoom:a,u=\"bearing\"in e?this._normalizeBearing(e.bearing,o):o,f=\"pitch\"in e?+e.pitch:s,h=\"padding\"in e?e.padding:i.padding,p=t.Point.convert(e.offset),d=i.centerPoint.add(p),g=i.pointLocation(d),m=t.LngLat.convert(e.center||g);this._normalizeCenter(m);var v,y,x=i.project(g),b=i.project(m).sub(x),_=i.zoomScale(c-a);e.around&&(v=t.LngLat.convert(e.around),y=i.locationPoint(v));var w={moving:this._moving,zooming:this._zooming,rotating:this._rotating,pitching:this._pitching};return this._zooming=this._zooming||c!==a,this._rotating=this._rotating||o!==u,this._pitching=this._pitching||f!==s,this._padding=!i.isPaddingEqual(h),this._easeId=e.easeId,this._prepareEase(r,e.noMoveStart,w),clearTimeout(this._easeEndTimeoutID),this._ease((function(e){if(n._zooming&&(i.zoom=t.number(a,c,e)),n._rotating&&(i.bearing=t.number(o,u,e)),n._pitching&&(i.pitch=t.number(s,f,e)),n._padding&&(i.interpolatePadding(l,h,e),d=i.centerPoint.add(p)),v)i.setLocationAtPoint(v,y);else{var g=i.zoomScale(i.zoom-a),m=c>a?Math.min(2,_):Math.max(.5,_),w=Math.pow(m,1-e),T=i.unproject(x.add(b.mult(e*w)).mult(g));i.setLocationAtPoint(i.renderWorldCopies?T.wrap():T,d)}n._fireMoveEvents(r)}),(function(t){n._afterEase(r,t)}),e),this},r.prototype._prepareEase=function(e,r,n){void 0===n&&(n={}),this._moving=!0,r||n.moving||this.fire(new t.Event(\"movestart\",e)),this._zooming&&!n.zooming&&this.fire(new t.Event(\"zoomstart\",e)),this._rotating&&!n.rotating&&this.fire(new t.Event(\"rotatestart\",e)),this._pitching&&!n.pitching&&this.fire(new t.Event(\"pitchstart\",e))},r.prototype._fireMoveEvents=function(e){this.fire(new t.Event(\"move\",e)),this._zooming&&this.fire(new t.Event(\"zoom\",e)),this._rotating&&this.fire(new t.Event(\"rotate\",e)),this._pitching&&this.fire(new t.Event(\"pitch\",e))},r.prototype._afterEase=function(e,r){if(!this._easeId||!r||this._easeId!==r){delete this._easeId;var n=this._zooming,i=this._rotating,a=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,n&&this.fire(new t.Event(\"zoomend\",e)),i&&this.fire(new t.Event(\"rotateend\",e)),a&&this.fire(new t.Event(\"pitchend\",e)),this.fire(new t.Event(\"moveend\",e))}},r.prototype.flyTo=function(e,r){var n=this;if(!e.essential&&t.browser.prefersReducedMotion){var i=t.pick(e,[\"center\",\"zoom\",\"bearing\",\"pitch\",\"around\"]);return this.jumpTo(i,r)}this.stop(),e=t.extend({offset:[0,0],speed:1.2,curve:1.42,easing:t.ease},e);var a=this.transform,o=this.getZoom(),s=this.getBearing(),l=this.getPitch(),c=this.getPadding(),u=\"zoom\"in e?t.clamp(+e.zoom,a.minZoom,a.maxZoom):o,f=\"bearing\"in e?this._normalizeBearing(e.bearing,s):s,h=\"pitch\"in e?+e.pitch:l,p=\"padding\"in e?e.padding:a.padding,d=a.zoomScale(u-o),g=t.Point.convert(e.offset),m=a.centerPoint.add(g),v=a.pointLocation(m),y=t.LngLat.convert(e.center||v);this._normalizeCenter(y);var x=a.project(v),b=a.project(y).sub(x),_=e.curve,w=Math.max(a.width,a.height),T=w/d,k=b.mag();if(\"minZoom\"in e){var M=t.clamp(Math.min(e.minZoom,o,u),a.minZoom,a.maxZoom),A=w/a.zoomScale(M-o);_=Math.sqrt(A/k*2)}var S=_*_;function E(t){var e=(T*T-w*w+(t?-1:1)*S*S*k*k)/(2*(t?T:w)*S*k);return Math.log(Math.sqrt(e*e+1)-e)}function C(t){return(Math.exp(t)-Math.exp(-t))/2}function L(t){return(Math.exp(t)+Math.exp(-t))/2}var I=E(0),P=function(t){return L(I)/L(I+_*t)},z=function(t){return w*((L(I)*(C(e=I+_*t)/L(e))-C(I))/S)/k;var e},O=(E(1)-I)/_;if(Math.abs(k)<1e-6||!isFinite(O)){if(Math.abs(w-T)<1e-6)return this.easeTo(e,r);var D=T<w?-1:1;O=Math.abs(Math.log(T/w))/_,z=function(){return 0},P=function(t){return Math.exp(D*_*t)}}return e.duration=\"duration\"in e?+e.duration:1e3*O/(\"screenSpeed\"in e?+e.screenSpeed/_:+e.speed),e.maxDuration&&e.duration>e.maxDuration&&(e.duration=0),this._zooming=!0,this._rotating=s!==f,this._pitching=h!==l,this._padding=!a.isPaddingEqual(p),this._prepareEase(r,!1),this._ease((function(e){var i=e*O,d=1/P(i);a.zoom=1===e?u:o+a.scaleZoom(d),n._rotating&&(a.bearing=t.number(s,f,e)),n._pitching&&(a.pitch=t.number(l,h,e)),n._padding&&(a.interpolatePadding(c,p,e),m=a.centerPoint.add(g));var v=1===e?y:a.unproject(x.add(b.mult(z(i))).mult(d));a.setLocationAtPoint(a.renderWorldCopies?v.wrap():v,m),n._fireMoveEvents(r)}),(function(){return n._afterEase(r)}),e),this},r.prototype.isEasing=function(){return!!this._easeFrameId},r.prototype.stop=function(){return this._stop()},r.prototype._stop=function(t,e){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var r=this._onEaseEnd;delete this._onEaseEnd,r.call(this,e)}if(!t){var n=this.handlers;n&&n.stop()}return this},r.prototype._ease=function(e,r,n){!1===n.animate||0===n.duration?(e(1),r()):(this._easeStart=t.browser.now(),this._easeOptions=n,this._onEaseFrame=e,this._onEaseEnd=r,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},r.prototype._renderFrameCallback=function(){var e=Math.min((t.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(e)),e<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},r.prototype._normalizeBearing=function(e,r){e=t.wrap(e,-180,180);var n=Math.abs(e-r);return Math.abs(e-360-r)<n&&(e-=360),Math.abs(e+360-r)<n&&(e+=360),e},r.prototype._normalizeCenter=function(t){var e=this.transform;if(e.renderWorldCopies&&!e.lngRange){var r=t.lng-e.center.lng;t.lng+=r>180?-360:r<-180?360:0}},r}(t.Evented),vi=function(e){void 0===e&&(e={}),this.options=e,t.bindAll([\"_updateEditLink\",\"_updateData\",\"_updateCompact\"],this)};vi.prototype.getDefaultPosition=function(){return\"bottom-right\"},vi.prototype.onAdd=function(t){var e=this.options&&this.options.compact;return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-attrib\"),this._innerContainer=r.create(\"div\",\"mapboxgl-ctrl-attrib-inner\",this._container),e&&this._container.classList.add(\"mapboxgl-compact\"),this._updateAttributions(),this._updateEditLink(),this._map.on(\"styledata\",this._updateData),this._map.on(\"sourcedata\",this._updateData),this._map.on(\"moveend\",this._updateEditLink),void 0===e&&(this._map.on(\"resize\",this._updateCompact),this._updateCompact()),this._container},vi.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"styledata\",this._updateData),this._map.off(\"sourcedata\",this._updateData),this._map.off(\"moveend\",this._updateEditLink),this._map.off(\"resize\",this._updateCompact),this._map=void 0,this._attribHTML=void 0},vi.prototype._updateEditLink=function(){var e=this._editLink;e||(e=this._editLink=this._container.querySelector(\".mapbox-improve-map\"));var r=[{key:\"owner\",value:this.styleOwner},{key:\"id\",value:this.styleId},{key:\"access_token\",value:this._map._requestManager._customAccessToken||t.config.ACCESS_TOKEN}];if(e){var n=r.reduce((function(t,e,n){return e.value&&(t+=e.key+\"=\"+e.value+(n<r.length-1?\"&\":\"\")),t}),\"?\");e.href=t.config.FEEDBACK_URL+\"/\"+n+(this._map._hash?this._map._hash.getHashString(!0):\"\"),e.rel=\"noopener nofollow\"}},vi.prototype._updateData=function(t){!t||\"metadata\"!==t.sourceDataType&&\"style\"!==t.dataType||(this._updateAttributions(),this._updateEditLink())},vi.prototype._updateAttributions=function(){if(this._map.style){var t=[];if(this.options.customAttribution&&(Array.isArray(this.options.customAttribution)?t=t.concat(this.options.customAttribution.map((function(t){return\"string\"!=typeof t?\"\":t}))):\"string\"==typeof this.options.customAttribution&&t.push(this.options.customAttribution)),this._map.style.stylesheet){var e=this._map.style.stylesheet;this.styleOwner=e.owner,this.styleId=e.id}var r=this._map.style.sourceCaches;for(var n in r){var i=r[n];if(i.used){var a=i.getSource();a.attribution&&t.indexOf(a.attribution)<0&&t.push(a.attribution)}}t.sort((function(t,e){return t.length-e.length}));var o=(t=t.filter((function(e,r){for(var n=r+1;n<t.length;n++)if(t[n].indexOf(e)>=0)return!1;return!0}))).join(\" | \");o!==this._attribHTML&&(this._attribHTML=o,t.length?(this._innerContainer.innerHTML=o,this._container.classList.remove(\"mapboxgl-attrib-empty\")):this._container.classList.add(\"mapboxgl-attrib-empty\"),this._editLink=null)}},vi.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add(\"mapboxgl-compact\"):this._container.classList.remove(\"mapboxgl-compact\")};var yi=function(){t.bindAll([\"_updateLogo\"],this),t.bindAll([\"_updateCompact\"],this)};yi.prototype.onAdd=function(t){this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl\");var e=r.create(\"a\",\"mapboxgl-ctrl-logo\");return e.target=\"_blank\",e.rel=\"noopener nofollow\",e.href=\"https://www.mapbox.com/\",e.setAttribute(\"aria-label\",this._map._getUIString(\"LogoControl.Title\")),e.setAttribute(\"rel\",\"noopener nofollow\"),this._container.appendChild(e),this._container.style.display=\"none\",this._map.on(\"sourcedata\",this._updateLogo),this._updateLogo(),this._map.on(\"resize\",this._updateCompact),this._updateCompact(),this._container},yi.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"sourcedata\",this._updateLogo),this._map.off(\"resize\",this._updateCompact)},yi.prototype.getDefaultPosition=function(){return\"bottom-left\"},yi.prototype._updateLogo=function(t){t&&\"metadata\"!==t.sourceDataType||(this._container.style.display=this._logoRequired()?\"block\":\"none\")},yi.prototype._logoRequired=function(){if(this._map.style){var t=this._map.style.sourceCaches;for(var e in t)if(t[e].getSource().mapbox_logo)return!0;return!1}},yi.prototype._updateCompact=function(){var t=this._container.children;if(t.length){var e=t[0];this._map.getCanvasContainer().offsetWidth<250?e.classList.add(\"mapboxgl-compact\"):e.classList.remove(\"mapboxgl-compact\")}};var xi=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};xi.prototype.add=function(t){var e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e},xi.prototype.remove=function(t){for(var e=this._currentlyRunning,r=0,n=e?this._queue.concat(e):this._queue;r<n.length;r+=1){var i=n[r];if(i.id===t)return void(i.cancelled=!0)}},xi.prototype.run=function(t){void 0===t&&(t=0);var e=this._currentlyRunning=this._queue;this._queue=[];for(var r=0,n=e;r<n.length;r+=1){var i=n[r];if(!i.cancelled&&(i.callback(t),this._cleared))break}this._cleared=!1,this._currentlyRunning=!1},xi.prototype.clear=function(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]};var bi={\"FullscreenControl.Enter\":\"Enter fullscreen\",\"FullscreenControl.Exit\":\"Exit fullscreen\",\"GeolocateControl.FindMyLocation\":\"Find my location\",\"GeolocateControl.LocationNotAvailable\":\"Location not available\",\"LogoControl.Title\":\"Mapbox logo\",\"NavigationControl.ResetBearing\":\"Reset bearing to north\",\"NavigationControl.ZoomIn\":\"Zoom in\",\"NavigationControl.ZoomOut\":\"Zoom out\",\"ScaleControl.Feet\":\"ft\",\"ScaleControl.Meters\":\"m\",\"ScaleControl.Kilometers\":\"km\",\"ScaleControl.Miles\":\"mi\",\"ScaleControl.NauticalMiles\":\"nm\"},_i=t.window.HTMLImageElement,wi=t.window.HTMLElement,Ti=t.window.ImageBitmap,ki={center:[0,0],zoom:0,bearing:0,pitch:0,minZoom:-2,maxZoom:22,minPitch:0,maxPitch:60,interactive:!0,scrollZoom:!0,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,touchPitch:!0,bearingSnap:7,clickTolerance:3,pitchWithRotate:!0,hash:!1,attributionControl:!0,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,trackResize:!0,renderWorldCopies:!0,refreshExpiredTiles:!0,maxTileCacheSize:null,localIdeographFontFamily:\"sans-serif\",transformRequest:null,accessToken:null,fadeDuration:300,crossSourceCollisions:!0},Mi=function(n){function i(e){var r=this;if(null!=(e=t.extend({},ki,e)).minZoom&&null!=e.maxZoom&&e.minZoom>e.maxZoom)throw new Error(\"maxZoom must be greater than or equal to minZoom\");if(null!=e.minPitch&&null!=e.maxPitch&&e.minPitch>e.maxPitch)throw new Error(\"maxPitch must be greater than or equal to minPitch\");if(null!=e.minPitch&&e.minPitch<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(null!=e.maxPitch&&e.maxPitch>60)throw new Error(\"maxPitch must be less than or equal to 60\");var i=new wn(e.minZoom,e.maxZoom,e.minPitch,e.maxPitch,e.renderWorldCopies);if(n.call(this,i,e),this._interactive=e.interactive,this._maxTileCacheSize=e.maxTileCacheSize,this._failIfMajorPerformanceCaveat=e.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=e.preserveDrawingBuffer,this._antialias=e.antialias,this._trackResize=e.trackResize,this._bearingSnap=e.bearingSnap,this._refreshExpiredTiles=e.refreshExpiredTiles,this._fadeDuration=e.fadeDuration,this._crossSourceCollisions=e.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=e.collectResourceTiming,this._renderTaskQueue=new xi,this._controls=[],this._mapId=t.uniqueId(),this._locale=t.extend({},bi,e.locale),this._requestManager=new t.RequestManager(e.transformRequest,e.accessToken),\"string\"==typeof e.container){if(this._container=t.window.document.getElementById(e.container),!this._container)throw new Error(\"Container '\"+e.container+\"' not found.\")}else{if(!(e.container instanceof wi))throw new Error(\"Invalid type: 'container' must be a String or HTMLElement.\");this._container=e.container}if(e.maxBounds&&this.setMaxBounds(e.maxBounds),t.bindAll([\"_onWindowOnline\",\"_onWindowResize\",\"_contextLost\",\"_contextRestored\"],this),this._setupContainer(),this._setupPainter(),void 0===this.painter)throw new Error(\"Failed to initialize WebGL.\");this.on(\"move\",(function(){return r._update(!1)})),this.on(\"moveend\",(function(){return r._update(!1)})),this.on(\"zoom\",(function(){return r._update(!0)})),void 0!==t.window&&(t.window.addEventListener(\"online\",this._onWindowOnline,!1),t.window.addEventListener(\"resize\",this._onWindowResize,!1)),this.handlers=new gi(this,e),this._hash=e.hash&&new kn(\"string\"==typeof e.hash&&e.hash||void 0).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:e.center,zoom:e.zoom,bearing:e.bearing,pitch:e.pitch}),e.bounds&&(this.resize(),this.fitBounds(e.bounds,t.extend({},e.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=e.localIdeographFontFamily,e.style&&this.setStyle(e.style,{localIdeographFontFamily:e.localIdeographFontFamily}),e.attributionControl&&this.addControl(new vi({customAttribution:e.customAttribution})),this.addControl(new yi,e.logoPosition),this.on(\"style.load\",(function(){r.transform.unmodified&&r.jumpTo(r.style.stylesheet)})),this.on(\"data\",(function(e){r._update(\"style\"===e.dataType),r.fire(new t.Event(e.dataType+\"data\",e))})),this.on(\"dataloading\",(function(e){r.fire(new t.Event(e.dataType+\"dataloading\",e))}))}n&&(i.__proto__=n),(i.prototype=Object.create(n&&n.prototype)).constructor=i;var a={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return i.prototype._getMapId=function(){return this._mapId},i.prototype.addControl=function(e,r){if(void 0===r&&e.getDefaultPosition&&(r=e.getDefaultPosition()),void 0===r&&(r=\"top-right\"),!e||!e.onAdd)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.\")));var n=e.onAdd(this);this._controls.push(e);var i=this._controlPositions[r];return-1!==r.indexOf(\"bottom\")?i.insertBefore(n,i.firstChild):i.appendChild(n),this},i.prototype.removeControl=function(e){if(!e||!e.onRemove)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.\")));var r=this._controls.indexOf(e);return r>-1&&this._controls.splice(r,1),e.onRemove(this),this},i.prototype.resize=function(e){var r=this._containerDimensions(),n=r[0],i=r[1];this._resizeCanvas(n,i),this.transform.resize(n,i),this.painter.resize(n,i);var a=!this._moving;return a&&(this.stop(),this.fire(new t.Event(\"movestart\",e)).fire(new t.Event(\"move\",e))),this.fire(new t.Event(\"resize\",e)),a&&this.fire(new t.Event(\"moveend\",e)),this},i.prototype.getBounds=function(){return this.transform.getBounds()},i.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},i.prototype.setMaxBounds=function(e){return this.transform.setMaxBounds(t.LngLatBounds.convert(e)),this._update()},i.prototype.setMinZoom=function(t){if((t=null==t?-2:t)>=-2&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()<t&&this.setZoom(t),this;throw new Error(\"minZoom must be between -2 and the current maxZoom, inclusive\")},i.prototype.getMinZoom=function(){return this.transform.minZoom},i.prototype.setMaxZoom=function(t){if((t=null==t?22:t)>=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error(\"maxZoom must be greater than the current minZoom\")},i.prototype.getMaxZoom=function(){return this.transform.maxZoom},i.prototype.setMinPitch=function(t){if((t=null==t?0:t)<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(t>=0&&t<=this.transform.maxPitch)return this.transform.minPitch=t,this._update(),this.getPitch()<t&&this.setPitch(t),this;throw new Error(\"minPitch must be between 0 and the current maxPitch, inclusive\")},i.prototype.getMinPitch=function(){return this.transform.minPitch},i.prototype.setMaxPitch=function(t){if((t=null==t?60:t)>60)throw new Error(\"maxPitch must be less than or equal to 60\");if(t>=this.transform.minPitch)return this.transform.maxPitch=t,this._update(),this.getPitch()>t&&this.setPitch(t),this;throw new Error(\"maxPitch must be greater than the current minPitch\")},i.prototype.getMaxPitch=function(){return this.transform.maxPitch},i.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},i.prototype.setRenderWorldCopies=function(t){return this.transform.renderWorldCopies=t,this._update()},i.prototype.project=function(e){return this.transform.locationPoint(t.LngLat.convert(e))},i.prototype.unproject=function(e){return this.transform.pointLocation(t.Point.convert(e))},i.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},i.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},i.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},i.prototype._createDelegatedListener=function(t,e,r){var n,i=this;if(\"mouseenter\"===t||\"mouseover\"===t){var a=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){var o=i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[];o.length?a||(a=!0,r.call(i,new zn(t,i,n.originalEvent,{features:o}))):a=!1},mouseout:function(){a=!1}}}}if(\"mouseleave\"===t||\"mouseout\"===t){var o=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){(i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[]).length?o=!0:o&&(o=!1,r.call(i,new zn(t,i,n.originalEvent)))},mouseout:function(e){o&&(o=!1,r.call(i,new zn(t,i,e.originalEvent)))}}}}return{layer:e,listener:r,delegates:(n={},n[t]=function(t){var n=i.getLayer(e)?i.queryRenderedFeatures(t.point,{layers:[e]}):[];n.length&&(t.features=n,r.call(i,t),delete t.features)},n)}},i.prototype.on=function(t,e,r){if(void 0===r)return n.prototype.on.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(i),i.delegates)this.on(a,i.delegates[a]);return this},i.prototype.once=function(t,e,r){if(void 0===r)return n.prototype.once.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in i.delegates)this.once(a,i.delegates[a]);return this},i.prototype.off=function(t,e,r){var i=this;return void 0===r?n.prototype.off.call(this,t,e):(this._delegatedListeners&&this._delegatedListeners[t]&&function(n){for(var a=n[t],o=0;o<a.length;o++){var s=a[o];if(s.layer===e&&s.listener===r){for(var l in s.delegates)i.off(l,s.delegates[l]);return a.splice(o,1),i}}}(this._delegatedListeners),this)},i.prototype.queryRenderedFeatures=function(e,r){if(!this.style)return[];var n;if(void 0!==r||void 0===e||e instanceof t.Point||Array.isArray(e)||(r=e,e=void 0),r=r||{},(e=e||[[0,0],[this.transform.width,this.transform.height]])instanceof t.Point||\"number\"==typeof e[0])n=[t.Point.convert(e)];else{var i=t.Point.convert(e[0]),a=t.Point.convert(e[1]);n=[i,new t.Point(a.x,i.y),a,new t.Point(i.x,a.y),i]}return this.style.queryRenderedFeatures(n,r,this.transform)},i.prototype.querySourceFeatures=function(t,e){return this.style.querySourceFeatures(t,e)},i.prototype.setStyle=function(e,r){return!1!==(r=t.extend({},{localIdeographFontFamily:this._localIdeographFontFamily},r)).diff&&r.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&e?(this._diffStyle(e,r),this):(this._localIdeographFontFamily=r.localIdeographFontFamily,this._updateStyle(e,r))},i.prototype._getUIString=function(t){var e=this._locale[t];if(null==e)throw new Error(\"Missing UI string '\"+t+\"'\");return e},i.prototype._updateStyle=function(t,e){return this.style&&(this.style.setEventedParent(null),this.style._remove()),t?(this.style=new qe(this,e||{}),this.style.setEventedParent(this,{style:this.style}),\"string\"==typeof t?this.style.loadURL(t):this.style.loadJSON(t),this):(delete this.style,this)},i.prototype._lazyInitEmptyStyle=function(){this.style||(this.style=new qe(this,{}),this.style.setEventedParent(this,{style:this.style}),this.style.loadEmpty())},i.prototype._diffStyle=function(e,r){var n=this;if(\"string\"==typeof e){var i=this._requestManager.normalizeStyleURL(e),a=this._requestManager.transformRequest(i,t.ResourceType.Style);t.getJSON(a,(function(e,i){e?n.fire(new t.ErrorEvent(e)):i&&n._updateDiff(i,r)}))}else\"object\"==typeof e&&this._updateDiff(e,r)},i.prototype._updateDiff=function(e,r){try{this.style.setState(e)&&this._update(!0)}catch(n){t.warnOnce(\"Unable to perform style diff: \"+(n.message||n.error||n)+\".  Rebuilding the style from scratch.\"),this._updateStyle(e,r)}},i.prototype.getStyle=function(){if(this.style)return this.style.serialize()},i.prototype.isStyleLoaded=function(){return this.style?this.style.loaded():t.warnOnce(\"There is no style added to the map.\")},i.prototype.addSource=function(t,e){return this._lazyInitEmptyStyle(),this.style.addSource(t,e),this._update(!0)},i.prototype.isSourceLoaded=function(e){var r=this.style&&this.style.sourceCaches[e];if(void 0!==r)return r.loaded();this.fire(new t.ErrorEvent(new Error(\"There is no source with ID '\"+e+\"'\")))},i.prototype.areTilesLoaded=function(){var t=this.style&&this.style.sourceCaches;for(var e in t){var r=t[e]._tiles;for(var n in r){var i=r[n];if(\"loaded\"!==i.state&&\"errored\"!==i.state)return!1}}return!0},i.prototype.addSourceType=function(t,e,r){return this._lazyInitEmptyStyle(),this.style.addSourceType(t,e,r)},i.prototype.removeSource=function(t){return this.style.removeSource(t),this._update(!0)},i.prototype.getSource=function(t){return this.style.getSource(t)},i.prototype.addImage=function(e,r,n){void 0===n&&(n={});var i=n.pixelRatio;void 0===i&&(i=1);var a=n.sdf;void 0===a&&(a=!1);var o=n.stretchX,s=n.stretchY,l=n.content;if(this._lazyInitEmptyStyle(),r instanceof _i||Ti&&r instanceof Ti){var c=t.browser.getImageData(r);this.style.addImage(e,{data:new t.RGBAImage({width:c.width,height:c.height},c.data),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0})}else{if(void 0===r.width||void 0===r.height)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));var u=r;this.style.addImage(e,{data:new t.RGBAImage({width:r.width,height:r.height},new Uint8Array(r.data)),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0,userImage:u}),u.onAdd&&u.onAdd(this,e)}},i.prototype.updateImage=function(e,r){var n=this.style.getImage(e);if(!n)return this.fire(new t.ErrorEvent(new Error(\"The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.\")));var i=r instanceof _i||Ti&&r instanceof Ti?t.browser.getImageData(r):r,a=i.width,o=i.height,s=i.data;return void 0===a||void 0===o?this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\"))):a!==n.data.width||o!==n.data.height?this.fire(new t.ErrorEvent(new Error(\"The width and height of the updated image must be that same as the previous version of the image\"))):(n.data.replace(s,!(r instanceof _i||Ti&&r instanceof Ti)),void this.style.updateImage(e,n))},i.prototype.hasImage=function(e){return e?!!this.style.getImage(e):(this.fire(new t.ErrorEvent(new Error(\"Missing required image id\"))),!1)},i.prototype.removeImage=function(t){this.style.removeImage(t)},i.prototype.loadImage=function(e,r){t.getImage(this._requestManager.transformRequest(e,t.ResourceType.Image),r)},i.prototype.listImages=function(){return this.style.listImages()},i.prototype.addLayer=function(t,e){return this._lazyInitEmptyStyle(),this.style.addLayer(t,e),this._update(!0)},i.prototype.moveLayer=function(t,e){return this.style.moveLayer(t,e),this._update(!0)},i.prototype.removeLayer=function(t){return this.style.removeLayer(t),this._update(!0)},i.prototype.getLayer=function(t){return this.style.getLayer(t)},i.prototype.setLayerZoomRange=function(t,e,r){return this.style.setLayerZoomRange(t,e,r),this._update(!0)},i.prototype.setFilter=function(t,e,r){return void 0===r&&(r={}),this.style.setFilter(t,e,r),this._update(!0)},i.prototype.getFilter=function(t){return this.style.getFilter(t)},i.prototype.setPaintProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setPaintProperty(t,e,r,n),this._update(!0)},i.prototype.getPaintProperty=function(t,e){return this.style.getPaintProperty(t,e)},i.prototype.setLayoutProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setLayoutProperty(t,e,r,n),this._update(!0)},i.prototype.getLayoutProperty=function(t,e){return this.style.getLayoutProperty(t,e)},i.prototype.setLight=function(t,e){return void 0===e&&(e={}),this._lazyInitEmptyStyle(),this.style.setLight(t,e),this._update(!0)},i.prototype.getLight=function(){return this.style.getLight()},i.prototype.setFeatureState=function(t,e){return this.style.setFeatureState(t,e),this._update()},i.prototype.removeFeatureState=function(t,e){return this.style.removeFeatureState(t,e),this._update()},i.prototype.getFeatureState=function(t){return this.style.getFeatureState(t)},i.prototype.getContainer=function(){return this._container},i.prototype.getCanvasContainer=function(){return this._canvasContainer},i.prototype.getCanvas=function(){return this._canvas},i.prototype._containerDimensions=function(){var t=0,e=0;return this._container&&(t=this._container.clientWidth||400,e=this._container.clientHeight||300),[t,e]},i.prototype._detectMissingCSS=function(){\"rgb(250, 128, 114)\"!==t.window.getComputedStyle(this._missingCSSCanary).getPropertyValue(\"background-color\")&&t.warnOnce(\"This page appears to be missing CSS declarations for Mapbox GL JS, which may cause the map to display incorrectly. Please ensure your page includes mapbox-gl.css, as described in https://www.mapbox.com/mapbox-gl-js/api/.\")},i.prototype._setupContainer=function(){var t=this._container;t.classList.add(\"mapboxgl-map\"),(this._missingCSSCanary=r.create(\"div\",\"mapboxgl-canary\",t)).style.visibility=\"hidden\",this._detectMissingCSS();var e=this._canvasContainer=r.create(\"div\",\"mapboxgl-canvas-container\",t);this._interactive&&e.classList.add(\"mapboxgl-interactive\"),this._canvas=r.create(\"canvas\",\"mapboxgl-canvas\",e),this._canvas.addEventListener(\"webglcontextlost\",this._contextLost,!1),this._canvas.addEventListener(\"webglcontextrestored\",this._contextRestored,!1),this._canvas.setAttribute(\"tabindex\",\"0\"),this._canvas.setAttribute(\"aria-label\",\"Map\");var n=this._containerDimensions();this._resizeCanvas(n[0],n[1]);var i=this._controlContainer=r.create(\"div\",\"mapboxgl-control-container\",t),a=this._controlPositions={};[\"top-left\",\"top-right\",\"bottom-left\",\"bottom-right\"].forEach((function(t){a[t]=r.create(\"div\",\"mapboxgl-ctrl-\"+t,i)}))},i.prototype._resizeCanvas=function(e,r){var n=t.browser.devicePixelRatio||1;this._canvas.width=n*e,this._canvas.height=n*r,this._canvas.style.width=e+\"px\",this._canvas.style.height=r+\"px\"},i.prototype._setupPainter=function(){var r=t.extend({},e.webGLContextAttributes,{failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1}),n=this._canvas.getContext(\"webgl\",r)||this._canvas.getContext(\"experimental-webgl\",r);n?(this.painter=new yn(n,this.transform),t.webpSupported.testSupport(n)):this.fire(new t.ErrorEvent(new Error(\"Failed to initialize WebGL\")))},i.prototype._contextLost=function(e){e.preventDefault(),this._frame&&(this._frame.cancel(),this._frame=null),this.fire(new t.Event(\"webglcontextlost\",{originalEvent:e}))},i.prototype._contextRestored=function(e){this._setupPainter(),this.resize(),this._update(),this.fire(new t.Event(\"webglcontextrestored\",{originalEvent:e}))},i.prototype.loaded=function(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()},i.prototype._update=function(t){return this.style?(this._styleDirty=this._styleDirty||t,this._sourcesDirty=!0,this.triggerRepaint(),this):this},i.prototype._requestRenderFrame=function(t){return this._update(),this._renderTaskQueue.add(t)},i.prototype._cancelRenderFrame=function(t){this._renderTaskQueue.remove(t)},i.prototype._render=function(e){var r,n=this,i=0,a=this.painter.context.extTimerQuery;if(this.listens(\"gpu-timing-frame\")&&(r=a.createQueryEXT(),a.beginQueryEXT(a.TIME_ELAPSED_EXT,r),i=t.browser.now()),this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run(e),!this._removed){var o=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;var s=this.transform.zoom,l=t.browser.now();this.style.zoomHistory.update(s,l);var c=new t.EvaluationParameters(s,{now:l,fadeDuration:this._fadeDuration,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),u=c.crossFadingFactor();1===u&&u===this._crossFadingFactor||(o=!0,this._crossFadingFactor=u),this.style.update(c)}if(this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,this._fadeDuration,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:this._fadeDuration,showPadding:this.showPadding,gpuTiming:!!this.listens(\"gpu-timing-layer\")}),this.fire(new t.Event(\"render\")),this.loaded()&&!this._loaded&&(this._loaded=!0,this.fire(new t.Event(\"load\"))),this.style&&(this.style.hasTransitions()||o)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles(),this.listens(\"gpu-timing-frame\")){var f=t.browser.now()-i;a.endQueryEXT(a.TIME_ELAPSED_EXT,r),setTimeout((function(){var e=a.getQueryObjectEXT(r,a.QUERY_RESULT_EXT)/1e6;a.deleteQueryEXT(r),n.fire(new t.Event(\"gpu-timing-frame\",{cpuTime:f,gpuTime:e}))}),50)}if(this.listens(\"gpu-timing-layer\")){var h=this.painter.collectGpuTimers();setTimeout((function(){var e=n.painter.queryGpuTimers(h);n.fire(new t.Event(\"gpu-timing-layer\",{layerTimes:e}))}),50)}return this._sourcesDirty||this._styleDirty||this._placementDirty||this._repaint?this.triggerRepaint():!this.isMoving()&&this.loaded()&&(this._fullyLoaded||(this._fullyLoaded=!0),this.fire(new t.Event(\"idle\"))),this}},i.prototype.remove=function(){this._hash&&this._hash.remove();for(var e=0,r=this._controls;e<r.length;e+=1)r[e].onRemove(this);this._controls=[],this._frame&&(this._frame.cancel(),this._frame=null),this._renderTaskQueue.clear(),this.painter.destroy(),this.handlers.destroy(),delete this.handlers,this.setStyle(null),void 0!==t.window&&(t.window.removeEventListener(\"resize\",this._onWindowResize,!1),t.window.removeEventListener(\"online\",this._onWindowOnline,!1));var n=this.painter.context.gl.getExtension(\"WEBGL_lose_context\");n&&n.loseContext(),Ai(this._canvasContainer),Ai(this._controlContainer),Ai(this._missingCSSCanary),this._container.classList.remove(\"mapboxgl-map\"),this._removed=!0,this.fire(new t.Event(\"remove\"))},i.prototype.triggerRepaint=function(){var e=this;this.style&&!this._frame&&(this._frame=t.browser.frame((function(t){e._frame=null,e._render(t)})))},i.prototype._onWindowOnline=function(){this._update()},i.prototype._onWindowResize=function(t){this._trackResize&&this.resize({originalEvent:t})._update()},a.showTileBoundaries.get=function(){return!!this._showTileBoundaries},a.showTileBoundaries.set=function(t){this._showTileBoundaries!==t&&(this._showTileBoundaries=t,this._update())},a.showPadding.get=function(){return!!this._showPadding},a.showPadding.set=function(t){this._showPadding!==t&&(this._showPadding=t,this._update())},a.showCollisionBoxes.get=function(){return!!this._showCollisionBoxes},a.showCollisionBoxes.set=function(t){this._showCollisionBoxes!==t&&(this._showCollisionBoxes=t,t?this.style._generateCollisionBoxes():this._update())},a.showOverdrawInspector.get=function(){return!!this._showOverdrawInspector},a.showOverdrawInspector.set=function(t){this._showOverdrawInspector!==t&&(this._showOverdrawInspector=t,this._update())},a.repaint.get=function(){return!!this._repaint},a.repaint.set=function(t){this._repaint!==t&&(this._repaint=t,this.triggerRepaint())},a.vertices.get=function(){return!!this._vertices},a.vertices.set=function(t){this._vertices=t,this._update()},i.prototype._setCacheLimits=function(e,r){t.setCacheLimits(e,r)},a.version.get=function(){return t.version},Object.defineProperties(i.prototype,a),i}(mi);function Ai(t){t.parentNode&&t.parentNode.removeChild(t)}var Si={showCompass:!0,showZoom:!0,visualizePitch:!1},Ei=function(e){var n=this;this.options=t.extend({},Si,e),this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this.options.showZoom&&(t.bindAll([\"_setButtonTitle\",\"_updateZoomButtons\"],this),this._zoomInButton=this._createButton(\"mapboxgl-ctrl-zoom-in\",(function(t){return n._map.zoomIn({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomInButton).setAttribute(\"aria-hidden\",!0),this._zoomOutButton=this._createButton(\"mapboxgl-ctrl-zoom-out\",(function(t){return n._map.zoomOut({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomOutButton).setAttribute(\"aria-hidden\",!0)),this.options.showCompass&&(t.bindAll([\"_rotateCompassArrow\"],this),this._compass=this._createButton(\"mapboxgl-ctrl-compass\",(function(t){n.options.visualizePitch?n._map.resetNorthPitch({},{originalEvent:t}):n._map.resetNorth({},{originalEvent:t})})),this._compassIcon=r.create(\"span\",\"mapboxgl-ctrl-icon\",this._compass),this._compassIcon.setAttribute(\"aria-hidden\",!0))};Ei.prototype._updateZoomButtons=function(){var t=this._map.getZoom();this._zoomInButton.disabled=t===this._map.getMaxZoom(),this._zoomOutButton.disabled=t===this._map.getMinZoom()},Ei.prototype._rotateCompassArrow=function(){var t=this.options.visualizePitch?\"scale(\"+1/Math.pow(Math.cos(this._map.transform.pitch*(Math.PI/180)),.5)+\") rotateX(\"+this._map.transform.pitch+\"deg) rotateZ(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\":\"rotate(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\";this._compassIcon.style.transform=t},Ei.prototype.onAdd=function(t){return this._map=t,this.options.showZoom&&(this._setButtonTitle(this._zoomInButton,\"ZoomIn\"),this._setButtonTitle(this._zoomOutButton,\"ZoomOut\"),this._map.on(\"zoom\",this._updateZoomButtons),this._updateZoomButtons()),this.options.showCompass&&(this._setButtonTitle(this._compass,\"ResetBearing\"),this.options.visualizePitch&&this._map.on(\"pitch\",this._rotateCompassArrow),this._map.on(\"rotate\",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new Ci(this._map,this._compass,this.options.visualizePitch)),this._container},Ei.prototype.onRemove=function(){r.remove(this._container),this.options.showZoom&&this._map.off(\"zoom\",this._updateZoomButtons),this.options.showCompass&&(this.options.visualizePitch&&this._map.off(\"pitch\",this._rotateCompassArrow),this._map.off(\"rotate\",this._rotateCompassArrow),this._handler.off(),delete this._handler),delete this._map},Ei.prototype._createButton=function(t,e){var n=r.create(\"button\",t,this._container);return n.type=\"button\",n.addEventListener(\"click\",e),n},Ei.prototype._setButtonTitle=function(t,e){var r=this._map._getUIString(\"NavigationControl.\"+e);t.title=r,t.setAttribute(\"aria-label\",r)};var Ci=function(e,n,i){void 0===i&&(i=!1),this._clickTolerance=10,this.element=n,this.mouseRotate=new Gn({clickTolerance:e.dragRotate._mouseRotate._clickTolerance}),this.map=e,i&&(this.mousePitch=new Yn({clickTolerance:e.dragRotate._mousePitch._clickTolerance})),t.bindAll([\"mousedown\",\"mousemove\",\"mouseup\",\"touchstart\",\"touchmove\",\"touchend\",\"reset\"],this),r.addEventListener(n,\"mousedown\",this.mousedown),r.addEventListener(n,\"touchstart\",this.touchstart,{passive:!1}),r.addEventListener(n,\"touchmove\",this.touchmove),r.addEventListener(n,\"touchend\",this.touchend),r.addEventListener(n,\"touchcancel\",this.reset)};function Li(e,r,n){if(e=new t.LngLat(e.lng,e.lat),r){var i=new t.LngLat(e.lng-360,e.lat),a=new t.LngLat(e.lng+360,e.lat),o=n.locationPoint(e).distSqr(r);n.locationPoint(i).distSqr(r)<o?e=i:n.locationPoint(a).distSqr(r)<o&&(e=a)}for(;Math.abs(e.lng-n.center.lng)>180;){var s=n.locationPoint(e);if(s.x>=0&&s.y>=0&&s.x<=n.width&&s.y<=n.height)break;e.lng>n.center.lng?e.lng-=360:e.lng+=360}return e}Ci.prototype.down=function(t,e){this.mouseRotate.mousedown(t,e),this.mousePitch&&this.mousePitch.mousedown(t,e),r.disableDrag()},Ci.prototype.move=function(t,e){var r=this.map,n=this.mouseRotate.mousemoveWindow(t,e);if(n&&n.bearingDelta&&r.setBearing(r.getBearing()+n.bearingDelta),this.mousePitch){var i=this.mousePitch.mousemoveWindow(t,e);i&&i.pitchDelta&&r.setPitch(r.getPitch()+i.pitchDelta)}},Ci.prototype.off=function(){var t=this.element;r.removeEventListener(t,\"mousedown\",this.mousedown),r.removeEventListener(t,\"touchstart\",this.touchstart,{passive:!1}),r.removeEventListener(t,\"touchmove\",this.touchmove),r.removeEventListener(t,\"touchend\",this.touchend),r.removeEventListener(t,\"touchcancel\",this.reset),this.offTemp()},Ci.prototype.offTemp=function(){r.enableDrag(),r.removeEventListener(t.window,\"mousemove\",this.mousemove),r.removeEventListener(t.window,\"mouseup\",this.mouseup)},Ci.prototype.mousedown=function(e){this.down(t.extend({},e,{ctrlKey:!0,preventDefault:function(){return e.preventDefault()}}),r.mousePos(this.element,e)),r.addEventListener(t.window,\"mousemove\",this.mousemove),r.addEventListener(t.window,\"mouseup\",this.mouseup)},Ci.prototype.mousemove=function(t){this.move(t,r.mousePos(this.element,t))},Ci.prototype.mouseup=function(t){this.mouseRotate.mouseupWindow(t),this.mousePitch&&this.mousePitch.mouseupWindow(t),this.offTemp()},Ci.prototype.touchstart=function(t){1!==t.targetTouches.length?this.reset():(this._startPos=this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.down({type:\"mousedown\",button:0,ctrlKey:!0,preventDefault:function(){return t.preventDefault()}},this._startPos))},Ci.prototype.touchmove=function(t){1!==t.targetTouches.length?this.reset():(this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.move({preventDefault:function(){return t.preventDefault()}},this._lastPos))},Ci.prototype.touchend=function(t){0===t.targetTouches.length&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos)<this._clickTolerance&&this.element.click(),this.reset()},Ci.prototype.reset=function(){this.mouseRotate.reset(),this.mousePitch&&this.mousePitch.reset(),delete this._startPos,delete this._lastPos,this.offTemp()};var Ii={center:\"translate(-50%,-50%)\",top:\"translate(-50%,0)\",\"top-left\":\"translate(0,0)\",\"top-right\":\"translate(-100%,0)\",bottom:\"translate(-50%,-100%)\",\"bottom-left\":\"translate(0,-100%)\",\"bottom-right\":\"translate(-100%,-100%)\",left:\"translate(0,-50%)\",right:\"translate(-100%,-50%)\"};function Pi(t,e,r){var n=t.classList;for(var i in Ii)n.remove(\"mapboxgl-\"+r+\"-anchor-\"+i);n.add(\"mapboxgl-\"+r+\"-anchor-\"+e)}var zi,Oi=function(e){function n(n,i){var a=this;if(e.call(this),(n instanceof t.window.HTMLElement||i)&&(n=t.extend({element:n},i)),t.bindAll([\"_update\",\"_onMove\",\"_onUp\",\"_addDragHandler\",\"_onMapClick\",\"_onKeyPress\"],this),this._anchor=n&&n.anchor||\"center\",this._color=n&&n.color||\"#3FB1CE\",this._draggable=n&&n.draggable||!1,this._state=\"inactive\",this._rotation=n&&n.rotation||0,this._rotationAlignment=n&&n.rotationAlignment||\"auto\",this._pitchAlignment=n&&n.pitchAlignment&&\"auto\"!==n.pitchAlignment?n.pitchAlignment:this._rotationAlignment,n&&n.element)this._element=n.element,this._offset=t.Point.convert(n&&n.offset||[0,0]);else{this._defaultMarker=!0,this._element=r.create(\"div\"),this._element.setAttribute(\"aria-label\",\"Map marker\");var o=r.createNS(\"http://www.w3.org/2000/svg\",\"svg\");o.setAttributeNS(null,\"display\",\"block\"),o.setAttributeNS(null,\"height\",\"41px\"),o.setAttributeNS(null,\"width\",\"27px\"),o.setAttributeNS(null,\"viewBox\",\"0 0 27 41\");var s=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");s.setAttributeNS(null,\"stroke\",\"none\"),s.setAttributeNS(null,\"stroke-width\",\"1\"),s.setAttributeNS(null,\"fill\",\"none\"),s.setAttributeNS(null,\"fill-rule\",\"evenodd\");var l=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");l.setAttributeNS(null,\"fill-rule\",\"nonzero\");var c=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");c.setAttributeNS(null,\"transform\",\"translate(3.0, 29.0)\"),c.setAttributeNS(null,\"fill\",\"#000000\");for(var u=0,f=[{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"9.5\",ry:\"4.77275007\"},{rx:\"8.5\",ry:\"4.29549936\"},{rx:\"7.5\",ry:\"3.81822308\"},{rx:\"6.5\",ry:\"3.34094679\"},{rx:\"5.5\",ry:\"2.86367051\"},{rx:\"4.5\",ry:\"2.38636864\"}];u<f.length;u+=1){var h=f[u],p=r.createNS(\"http://www.w3.org/2000/svg\",\"ellipse\");p.setAttributeNS(null,\"opacity\",\"0.04\"),p.setAttributeNS(null,\"cx\",\"10.5\"),p.setAttributeNS(null,\"cy\",\"5.80029008\"),p.setAttributeNS(null,\"rx\",h.rx),p.setAttributeNS(null,\"ry\",h.ry),c.appendChild(p)}var d=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");d.setAttributeNS(null,\"fill\",this._color);var g=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");g.setAttributeNS(null,\"d\",\"M27,13.5 C27,19.074644 20.250001,27.000002 14.75,34.500002 C14.016665,35.500004 12.983335,35.500004 12.25,34.500002 C6.7499993,27.000002 0,19.222562 0,13.5 C0,6.0441559 6.0441559,0 13.5,0 C20.955844,0 27,6.0441559 27,13.5 Z\"),d.appendChild(g);var m=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");m.setAttributeNS(null,\"opacity\",\"0.25\"),m.setAttributeNS(null,\"fill\",\"#000000\");var v=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");v.setAttributeNS(null,\"d\",\"M13.5,0 C6.0441559,0 0,6.0441559 0,13.5 C0,19.222562 6.7499993,27 12.25,34.5 C13,35.522727 14.016664,35.500004 14.75,34.5 C20.250001,27 27,19.074644 27,13.5 C27,6.0441559 20.955844,0 13.5,0 Z M13.5,1 C20.415404,1 26,6.584596 26,13.5 C26,15.898657 24.495584,19.181431 22.220703,22.738281 C19.945823,26.295132 16.705119,30.142167 13.943359,33.908203 C13.743445,34.180814 13.612715,34.322738 13.5,34.441406 C13.387285,34.322738 13.256555,34.180814 13.056641,33.908203 C10.284481,30.127985 7.4148684,26.314159 5.015625,22.773438 C2.6163816,19.232715 1,15.953538 1,13.5 C1,6.584596 6.584596,1 13.5,1 Z\"),m.appendChild(v);var y=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");y.setAttributeNS(null,\"transform\",\"translate(6.0, 7.0)\"),y.setAttributeNS(null,\"fill\",\"#FFFFFF\");var x=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");x.setAttributeNS(null,\"transform\",\"translate(8.0, 8.0)\");var b=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");b.setAttributeNS(null,\"fill\",\"#000000\"),b.setAttributeNS(null,\"opacity\",\"0.25\"),b.setAttributeNS(null,\"cx\",\"5.5\"),b.setAttributeNS(null,\"cy\",\"5.5\"),b.setAttributeNS(null,\"r\",\"5.4999962\");var _=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");_.setAttributeNS(null,\"fill\",\"#FFFFFF\"),_.setAttributeNS(null,\"cx\",\"5.5\"),_.setAttributeNS(null,\"cy\",\"5.5\"),_.setAttributeNS(null,\"r\",\"5.4999962\"),x.appendChild(b),x.appendChild(_),l.appendChild(c),l.appendChild(d),l.appendChild(m),l.appendChild(y),l.appendChild(x),o.appendChild(l),this._element.appendChild(o),this._offset=t.Point.convert(n&&n.offset||[0,-14])}this._element.classList.add(\"mapboxgl-marker\"),this._element.addEventListener(\"dragstart\",(function(t){t.preventDefault()})),this._element.addEventListener(\"mousedown\",(function(t){t.preventDefault()})),this._element.addEventListener(\"focus\",(function(){var t=a._map.getContainer();t.scrollTop=0,t.scrollLeft=0})),Pi(this._element,this._anchor,\"marker\"),this._popup=null}return e&&(n.__proto__=e),(n.prototype=Object.create(e&&e.prototype)).constructor=n,n.prototype.addTo=function(t){return this.remove(),this._map=t,t.getCanvasContainer().appendChild(this._element),t.on(\"move\",this._update),t.on(\"moveend\",this._update),this.setDraggable(this._draggable),this._update(),this._map.on(\"click\",this._onMapClick),this},n.prototype.remove=function(){return this._map&&(this._map.off(\"click\",this._onMapClick),this._map.off(\"move\",this._update),this._map.off(\"moveend\",this._update),this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler),this._map.off(\"mouseup\",this._onUp),this._map.off(\"touchend\",this._onUp),this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),delete this._map),r.remove(this._element),this._popup&&this._popup.remove(),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this},n.prototype.getElement=function(){return this._element},n.prototype.setPopup=function(t){if(this._popup&&(this._popup.remove(),this._popup=null,this._element.removeEventListener(\"keypress\",this._onKeyPress),this._originalTabIndex||this._element.removeAttribute(\"tabindex\")),t){if(!(\"offset\"in t.options)){var e=Math.sqrt(Math.pow(13.5,2)/2);t.options.offset=this._defaultMarker?{top:[0,0],\"top-left\":[0,0],\"top-right\":[0,0],bottom:[0,-38.1],\"bottom-left\":[e,-1*(24.6+e)],\"bottom-right\":[-e,-1*(24.6+e)],left:[13.5,-24.6],right:[-13.5,-24.6]}:this._offset}this._popup=t,this._lngLat&&this._popup.setLngLat(this._lngLat),this._originalTabIndex=this._element.getAttribute(\"tabindex\"),this._originalTabIndex||this._element.setAttribute(\"tabindex\",\"0\"),this._element.addEventListener(\"keypress\",this._onKeyPress)}return this},n.prototype._onKeyPress=function(t){var e=t.code,r=t.charCode||t.keyCode;\"Space\"!==e&&\"Enter\"!==e&&32!==r&&13!==r||this.togglePopup()},n.prototype._onMapClick=function(t){var e=t.originalEvent.target,r=this._element;this._popup&&(e===r||r.contains(e))&&this.togglePopup()},n.prototype.getPopup=function(){return this._popup},n.prototype.togglePopup=function(){var t=this._popup;return t?(t.isOpen()?t.remove():t.addTo(this._map),this):this},n.prototype._update=function(t){if(this._map){this._map.transform.renderWorldCopies&&(this._lngLat=Li(this._lngLat,this._pos,this._map.transform)),this._pos=this._map.project(this._lngLat)._add(this._offset);var e=\"\";\"viewport\"===this._rotationAlignment||\"auto\"===this._rotationAlignment?e=\"rotateZ(\"+this._rotation+\"deg)\":\"map\"===this._rotationAlignment&&(e=\"rotateZ(\"+(this._rotation-this._map.getBearing())+\"deg)\");var n=\"\";\"viewport\"===this._pitchAlignment||\"auto\"===this._pitchAlignment?n=\"rotateX(0deg)\":\"map\"===this._pitchAlignment&&(n=\"rotateX(\"+this._map.getPitch()+\"deg)\"),t&&\"moveend\"!==t.type||(this._pos=this._pos.round()),r.setTransform(this._element,Ii[this._anchor]+\" translate(\"+this._pos.x+\"px, \"+this._pos.y+\"px) \"+n+\" \"+e)}},n.prototype.getOffset=function(){return this._offset},n.prototype.setOffset=function(e){return this._offset=t.Point.convert(e),this._update(),this},n.prototype._onMove=function(e){this._pos=e.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents=\"none\",\"pending\"===this._state&&(this._state=\"active\",this.fire(new t.Event(\"dragstart\"))),this.fire(new t.Event(\"drag\"))},n.prototype._onUp=function(){this._element.style.pointerEvents=\"auto\",this._positionDelta=null,this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),\"active\"===this._state&&this.fire(new t.Event(\"dragend\")),this._state=\"inactive\"},n.prototype._addDragHandler=function(t){this._element.contains(t.originalEvent.target)&&(t.preventDefault(),this._positionDelta=t.point.sub(this._pos).add(this._offset),this._state=\"pending\",this._map.on(\"mousemove\",this._onMove),this._map.on(\"touchmove\",this._onMove),this._map.once(\"mouseup\",this._onUp),this._map.once(\"touchend\",this._onUp))},n.prototype.setDraggable=function(t){return this._draggable=!!t,this._map&&(t?(this._map.on(\"mousedown\",this._addDragHandler),this._map.on(\"touchstart\",this._addDragHandler)):(this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler))),this},n.prototype.isDraggable=function(){return this._draggable},n.prototype.setRotation=function(t){return this._rotation=t||0,this._update(),this},n.prototype.getRotation=function(){return this._rotation},n.prototype.setRotationAlignment=function(t){return this._rotationAlignment=t||\"auto\",this._update(),this},n.prototype.getRotationAlignment=function(){return this._rotationAlignment},n.prototype.setPitchAlignment=function(t){return this._pitchAlignment=t&&\"auto\"!==t?t:this._rotationAlignment,this._update(),this},n.prototype.getPitchAlignment=function(){return this._pitchAlignment},n}(t.Evented),Di={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0},Ri=0,Fi=!1,Bi=function(e){function n(r){e.call(this),this.options=t.extend({},Di,r),t.bindAll([\"_onSuccess\",\"_onError\",\"_onZoom\",\"_finish\",\"_setupUI\",\"_updateCamera\",\"_updateMarker\"],this)}return e&&(n.__proto__=e),(n.prototype=Object.create(e&&e.prototype)).constructor=n,n.prototype.onAdd=function(e){var n;return this._map=e,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),n=this._setupUI,void 0!==zi?n(zi):void 0!==t.window.navigator.permissions?t.window.navigator.permissions.query({name:\"geolocation\"}).then((function(t){n(zi=\"denied\"!==t.state)})):n(zi=!!t.window.navigator.geolocation),this._container},n.prototype.onRemove=function(){void 0!==this._geolocationWatchID&&(t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),r.remove(this._container),this._map.off(\"zoom\",this._onZoom),this._map=void 0,Ri=0,Fi=!1},n.prototype._isOutOfMapMaxBounds=function(t){var e=this._map.getMaxBounds(),r=t.coords;return e&&(r.longitude<e.getWest()||r.longitude>e.getEast()||r.latitude<e.getSouth()||r.latitude>e.getNorth())},n.prototype._setErrorState=function(){switch(this._watchState){case\"WAITING_ACTIVE\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"ACTIVE_LOCK\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\");break;case\"BACKGROUND\":this._watchState=\"BACKGROUND_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\")}},n.prototype._onSuccess=function(e){if(this._map){if(this._isOutOfMapMaxBounds(e))return this._setErrorState(),this.fire(new t.Event(\"outofmaxbounds\",e)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=e,this._watchState){case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"BACKGROUND\":case\"BACKGROUND_ERROR\":this._watchState=\"BACKGROUND\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\")}this.options.showUserLocation&&\"OFF\"!==this._watchState&&this._updateMarker(e),this.options.trackUserLocation&&\"ACTIVE_LOCK\"!==this._watchState||this._updateCamera(e),this.options.showUserLocation&&this._dotElement.classList.remove(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"geolocate\",e)),this._finish()}},n.prototype._updateCamera=function(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude),n=e.coords.accuracy,i=this._map.getBearing(),a=t.extend({bearing:i},this.options.fitBoundsOptions);this._map.fitBounds(r.toBounds(n),a,{geolocateSource:!0})},n.prototype._updateMarker=function(e){if(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude);this._accuracyCircleMarker.setLngLat(r).addTo(this._map),this._userLocationDotMarker.setLngLat(r).addTo(this._map),this._accuracy=e.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},n.prototype._updateCircleRadius=function(){var t=this._map._container.clientHeight/2,e=this._map.unproject([0,t]),r=this._map.unproject([1,t]),n=e.distanceTo(r),i=Math.ceil(2*this._accuracy/n);this._circleElement.style.width=i+\"px\",this._circleElement.style.height=i+\"px\"},n.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},n.prototype._onError=function(e){if(this._map){if(this.options.trackUserLocation)if(1===e.code){this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.disabled=!0;var r=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.title=r,this._geolocateButton.setAttribute(\"aria-label\",r),void 0!==this._geolocationWatchID&&this._clearWatch()}else{if(3===e.code&&Fi)return;this._setErrorState()}\"OFF\"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"error\",e)),this._finish()}},n.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},n.prototype._setupUI=function(e){var n=this;if(this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this._geolocateButton=r.create(\"button\",\"mapboxgl-ctrl-geolocate\",this._container),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._geolocateButton).setAttribute(\"aria-hidden\",!0),this._geolocateButton.type=\"button\",!1===e){t.warnOnce(\"Geolocation support is not available so the GeolocateControl will be disabled.\");var i=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.disabled=!0,this._geolocateButton.title=i,this._geolocateButton.setAttribute(\"aria-label\",i)}else{var a=this._map._getUIString(\"GeolocateControl.FindMyLocation\");this._geolocateButton.title=a,this._geolocateButton.setAttribute(\"aria-label\",a)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this._watchState=\"OFF\"),this.options.showUserLocation&&(this._dotElement=r.create(\"div\",\"mapboxgl-user-location-dot\"),this._userLocationDotMarker=new Oi(this._dotElement),this._circleElement=r.create(\"div\",\"mapboxgl-user-location-accuracy-circle\"),this._accuracyCircleMarker=new Oi({element:this._circleElement,pitchAlignment:\"map\"}),this.options.trackUserLocation&&(this._watchState=\"OFF\"),this._map.on(\"zoom\",this._onZoom)),this._geolocateButton.addEventListener(\"click\",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on(\"movestart\",(function(e){e.geolocateSource||\"ACTIVE_LOCK\"!==n._watchState||e.originalEvent&&\"resize\"===e.originalEvent.type||(n._watchState=\"BACKGROUND\",n._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\"),n._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),n.fire(new t.Event(\"trackuserlocationend\")))}))},n.prototype.trigger=function(){if(!this._setup)return t.warnOnce(\"Geolocate control triggered before added to a map\"),!1;if(this.options.trackUserLocation){switch(this._watchState){case\"OFF\":this._watchState=\"WAITING_ACTIVE\",this.fire(new t.Event(\"trackuserlocationstart\"));break;case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":case\"BACKGROUND_ERROR\":Ri--,Fi=!1,this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this.fire(new t.Event(\"trackuserlocationend\"));break;case\"BACKGROUND\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.Event(\"trackuserlocationstart\"))}switch(this._watchState){case\"WAITING_ACTIVE\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_LOCK\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"BACKGROUND\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\");break;case\"BACKGROUND_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\")}if(\"OFF\"===this._watchState&&void 0!==this._geolocationWatchID)this._clearWatch();else if(void 0===this._geolocationWatchID){var e;this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"true\"),++Ri>1?(e={maximumAge:6e5,timeout:0},Fi=!0):(e=this.options.positionOptions,Fi=!1),this._geolocationWatchID=t.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,e)}}else t.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},n.prototype._clearWatch=function(){t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this.options.showUserLocation&&this._updateMarker(null)},n}(t.Evented),Ni={maxWidth:100,unit:\"metric\"},ji=function(e){this.options=t.extend({},Ni,e),t.bindAll([\"_onMove\",\"setUnit\"],this)};function Ui(t,e,r){var n=r&&r.maxWidth||100,i=t._container.clientHeight/2,a=t.unproject([0,i]),o=t.unproject([n,i]),s=a.distanceTo(o);if(r&&\"imperial\"===r.unit){var l=3.2808*s;l>5280?Vi(e,n,l/5280,t._getUIString(\"ScaleControl.Miles\")):Vi(e,n,l,t._getUIString(\"ScaleControl.Feet\"))}else r&&\"nautical\"===r.unit?Vi(e,n,s/1852,t._getUIString(\"ScaleControl.NauticalMiles\")):s>=1e3?Vi(e,n,s/1e3,t._getUIString(\"ScaleControl.Kilometers\")):Vi(e,n,s,t._getUIString(\"ScaleControl.Meters\"))}function Vi(t,e,r,n){var i,a,o,s=(i=r,(a=Math.pow(10,(\"\"+Math.floor(i)).length-1))*(o=(o=i/a)>=10?10:o>=5?5:o>=3?3:o>=2?2:o>=1?1:function(t){var e=Math.pow(10,Math.ceil(-Math.log(t)/Math.LN10));return Math.round(t*e)/e}(o)));t.style.width=e*(s/r)+\"px\",t.innerHTML=s+\"&nbsp;\"+n}ji.prototype.getDefaultPosition=function(){return\"bottom-left\"},ji.prototype._onMove=function(){Ui(this._map,this._container,this.options)},ji.prototype.onAdd=function(t){return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-scale\",t.getContainer()),this._map.on(\"move\",this._onMove),this._onMove(),this._container},ji.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"move\",this._onMove),this._map=void 0},ji.prototype.setUnit=function(t){this.options.unit=t,Ui(this._map,this._container,this.options)};var qi=function(e){this._fullscreen=!1,e&&e.container&&(e.container instanceof t.window.HTMLElement?this._container=e.container:t.warnOnce(\"Full screen control 'container' must be a DOM element.\")),t.bindAll([\"_onClickFullscreen\",\"_changeIcon\"],this),\"onfullscreenchange\"in t.window.document?this._fullscreenchange=\"fullscreenchange\":\"onmozfullscreenchange\"in t.window.document?this._fullscreenchange=\"mozfullscreenchange\":\"onwebkitfullscreenchange\"in t.window.document?this._fullscreenchange=\"webkitfullscreenchange\":\"onmsfullscreenchange\"in t.window.document&&(this._fullscreenchange=\"MSFullscreenChange\")};qi.prototype.onAdd=function(e){return this._map=e,this._container||(this._container=this._map.getContainer()),this._controlContainer=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display=\"none\",t.warnOnce(\"This device does not support fullscreen mode.\")),this._controlContainer},qi.prototype.onRemove=function(){r.remove(this._controlContainer),this._map=null,t.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},qi.prototype._checkFullscreenSupport=function(){return!!(t.window.document.fullscreenEnabled||t.window.document.mozFullScreenEnabled||t.window.document.msFullscreenEnabled||t.window.document.webkitFullscreenEnabled)},qi.prototype._setupUI=function(){var e=this._fullscreenButton=r.create(\"button\",\"mapboxgl-ctrl-fullscreen\",this._controlContainer);r.create(\"span\",\"mapboxgl-ctrl-icon\",e).setAttribute(\"aria-hidden\",!0),e.type=\"button\",this._updateTitle(),this._fullscreenButton.addEventListener(\"click\",this._onClickFullscreen),t.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},qi.prototype._updateTitle=function(){var t=this._getTitle();this._fullscreenButton.setAttribute(\"aria-label\",t),this._fullscreenButton.title=t},qi.prototype._getTitle=function(){return this._map._getUIString(this._isFullscreen()?\"FullscreenControl.Exit\":\"FullscreenControl.Enter\")},qi.prototype._isFullscreen=function(){return this._fullscreen},qi.prototype._changeIcon=function(){(t.window.document.fullscreenElement||t.window.document.mozFullScreenElement||t.window.document.webkitFullscreenElement||t.window.document.msFullscreenElement)===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-shrink\"),this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-fullscreen\"),this._updateTitle())},qi.prototype._onClickFullscreen=function(){this._isFullscreen()?t.window.document.exitFullscreen?t.window.document.exitFullscreen():t.window.document.mozCancelFullScreen?t.window.document.mozCancelFullScreen():t.window.document.msExitFullscreen?t.window.document.msExitFullscreen():t.window.document.webkitCancelFullScreen&&t.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var Hi={closeButton:!0,closeOnClick:!0,className:\"\",maxWidth:\"240px\"},Gi=function(e){function n(r){e.call(this),this.options=t.extend(Object.create(Hi),r),t.bindAll([\"_update\",\"_onClose\",\"remove\",\"_onMouseMove\",\"_onMouseUp\",\"_onDrag\"],this)}return e&&(n.__proto__=e),(n.prototype=Object.create(e&&e.prototype)).constructor=n,n.prototype.addTo=function(e){return this._map&&this.remove(),this._map=e,this.options.closeOnClick&&this._map.on(\"click\",this._onClose),this.options.closeOnMove&&this._map.on(\"move\",this._onClose),this._map.on(\"remove\",this.remove),this._update(),this._trackPointer?(this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"mouseup\",this._onMouseUp),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")):this._map.on(\"move\",this._update),this.fire(new t.Event(\"open\")),this},n.prototype.isOpen=function(){return!!this._map},n.prototype.remove=function(){return this._content&&r.remove(this._content),this._container&&(r.remove(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"move\",this._onClose),this._map.off(\"click\",this._onClose),this._map.off(\"remove\",this.remove),this._map.off(\"mousemove\",this._onMouseMove),this._map.off(\"mouseup\",this._onMouseUp),this._map.off(\"drag\",this._onDrag),delete this._map),this.fire(new t.Event(\"close\")),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on(\"move\",this._update),this._map.off(\"mousemove\",this._onMouseMove),this._container&&this._container.classList.remove(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.remove(\"mapboxgl-track-pointer\")),this},n.prototype.trackPointer=function(){return this._trackPointer=!0,this._pos=null,this._update(),this._map&&(this._map.off(\"move\",this._update),this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"drag\",this._onDrag),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")),this},n.prototype.getElement=function(){return this._container},n.prototype.setText=function(e){return this.setDOMContent(t.window.document.createTextNode(e))},n.prototype.setHTML=function(e){var r,n=t.window.document.createDocumentFragment(),i=t.window.document.createElement(\"body\");for(i.innerHTML=e;r=i.firstChild;)n.appendChild(r);return this.setDOMContent(n)},n.prototype.getMaxWidth=function(){return this._container&&this._container.style.maxWidth},n.prototype.setMaxWidth=function(t){return this.options.maxWidth=t,this._update(),this},n.prototype.setDOMContent=function(t){return this._createContent(),this._content.appendChild(t),this._update(),this},n.prototype.addClassName=function(t){this._container&&this._container.classList.add(t)},n.prototype.removeClassName=function(t){this._container&&this._container.classList.remove(t)},n.prototype.toggleClassName=function(t){if(this._container)return this._container.classList.toggle(t)},n.prototype._createContent=function(){this._content&&r.remove(this._content),this._content=r.create(\"div\",\"mapboxgl-popup-content\",this._container),this.options.closeButton&&(this._closeButton=r.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.setAttribute(\"aria-label\",\"Close popup\"),this._closeButton.innerHTML=\"&#215;\",this._closeButton.addEventListener(\"click\",this._onClose))},n.prototype._onMouseUp=function(t){this._update(t.point)},n.prototype._onMouseMove=function(t){this._update(t.point)},n.prototype._onDrag=function(t){this._update(t.point)},n.prototype._update=function(e){var n=this;if(this._map&&(this._lngLat||this._trackPointer)&&this._content&&(this._container||(this._container=r.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=r.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content),this.options.className&&this.options.className.split(\" \").forEach((function(t){return n._container.classList.add(t)})),this._trackPointer&&this._container.classList.add(\"mapboxgl-popup-track-pointer\")),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=Li(this._lngLat,this._pos,this._map.transform)),!this._trackPointer||e)){var i=this._pos=this._trackPointer&&e?e:this._map.project(this._lngLat),a=this.options.anchor,o=function e(r){if(r){if(\"number\"==typeof r){var n=Math.round(Math.sqrt(.5*Math.pow(r,2)));return{center:new t.Point(0,0),top:new t.Point(0,r),\"top-left\":new t.Point(n,n),\"top-right\":new t.Point(-n,n),bottom:new t.Point(0,-r),\"bottom-left\":new t.Point(n,-n),\"bottom-right\":new t.Point(-n,-n),left:new t.Point(r,0),right:new t.Point(-r,0)}}if(r instanceof t.Point||Array.isArray(r)){var i=t.Point.convert(r);return{center:i,top:i,\"top-left\":i,\"top-right\":i,bottom:i,\"bottom-left\":i,\"bottom-right\":i,left:i,right:i}}return{center:t.Point.convert(r.center||[0,0]),top:t.Point.convert(r.top||[0,0]),\"top-left\":t.Point.convert(r[\"top-left\"]||[0,0]),\"top-right\":t.Point.convert(r[\"top-right\"]||[0,0]),bottom:t.Point.convert(r.bottom||[0,0]),\"bottom-left\":t.Point.convert(r[\"bottom-left\"]||[0,0]),\"bottom-right\":t.Point.convert(r[\"bottom-right\"]||[0,0]),left:t.Point.convert(r.left||[0,0]),right:t.Point.convert(r.right||[0,0])}}return e(new t.Point(0,0))}(this.options.offset);if(!a){var s,l=this._container.offsetWidth,c=this._container.offsetHeight;s=i.y+o.bottom.y<c?[\"top\"]:i.y>this._map.transform.height-c?[\"bottom\"]:[],i.x<l/2?s.push(\"left\"):i.x>this._map.transform.width-l/2&&s.push(\"right\"),a=0===s.length?\"bottom\":s.join(\"-\")}var u=i.add(o[a]).round();r.setTransform(this._container,Ii[a]+\" translate(\"+u.x+\"px,\"+u.y+\"px)\"),Pi(this._container,a,\"popup\")}},n.prototype._onClose=function(){this.remove()},n}(t.Evented),Yi={version:t.version,supported:e,setRTLTextPlugin:t.setRTLTextPlugin,getRTLTextPluginStatus:t.getRTLTextPluginStatus,Map:Mi,NavigationControl:Ei,GeolocateControl:Bi,AttributionControl:vi,ScaleControl:ji,FullscreenControl:qi,Popup:Gi,Marker:Oi,Style:qe,LngLat:t.LngLat,LngLatBounds:t.LngLatBounds,Point:t.Point,MercatorCoordinate:t.MercatorCoordinate,Evented:t.Evented,config:t.config,prewarm:function(){Bt().acquire(Ot)},clearPrewarmedResources:function(){var t=Rt;t&&(t.isPreloaded()&&1===t.numActive()?(t.release(Ot),Rt=null):console.warn(\"Could not clear WebWorkers since there are active Map instances that still reference it. The pre-warmed WebWorker pool can only be cleared when all map instances have been removed with map.remove()\"))},get accessToken(){return t.config.ACCESS_TOKEN},set accessToken(e){t.config.ACCESS_TOKEN=e},get baseApiUrl(){return t.config.API_URL},set baseApiUrl(e){t.config.API_URL=e},get workerCount(){return Dt.workerCount},set workerCount(t){Dt.workerCount=t},get maxParallelImageRequests(){return t.config.MAX_PARALLEL_IMAGE_REQUESTS},set maxParallelImageRequests(e){t.config.MAX_PARALLEL_IMAGE_REQUESTS=e},clearStorage:function(e){t.clearTileCache(e)},workerUrl:\"\"};return Yi})),r}))},{}],474:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=1<<t+1,r=new Array(e),n=0;n<e;++n)r[n]=a(t,n);return r};var n=t(\"convex-hull\");function i(t,e,r){for(var n=new Array(t),i=0;i<t;++i)n[i]=0,i===e&&(n[i]+=.5),i===r&&(n[i]+=.5);return n}function a(t,e){if(0===e||e===(1<<t+1)-1)return[];for(var r=[],a=[],o=0;o<=t;++o)if(e&1<<o){r.push(i(t,o-1,o-1)),a.push(null);for(var s=0;s<=t;++s)~e&1<<s&&(r.push(i(t,o-1,s-1)),a.push([o,s]))}var l=n(r),c=[];t:for(o=0;o<l.length;++o){var u=l[o],f=[];for(s=0;s<u.length;++s){if(!a[u[s]])continue t;f.push(a[u[s]].slice())}c.push(f)}return c}},{\"convex-hull\":135}],475:[function(t,e,r){var n=t(\"./normalize\"),i=t(\"gl-mat4/create\"),a=t(\"gl-mat4/clone\"),o=t(\"gl-mat4/determinant\"),s=t(\"gl-mat4/invert\"),l=t(\"gl-mat4/transpose\"),c={length:t(\"gl-vec3/length\"),normalize:t(\"gl-vec3/normalize\"),dot:t(\"gl-vec3/dot\"),cross:t(\"gl-vec3/cross\")},u=i(),f=i(),h=[0,0,0,0],p=[[0,0,0],[0,0,0],[0,0,0]],d=[0,0,0];function g(t,e,r,n,i){t[0]=e[0]*n+r[0]*i,t[1]=e[1]*n+r[1]*i,t[2]=e[2]*n+r[2]*i}e.exports=function(t,e,r,i,m,v){if(e||(e=[0,0,0]),r||(r=[0,0,0]),i||(i=[0,0,0]),m||(m=[0,0,0,1]),v||(v=[0,0,0,1]),!n(u,t))return!1;if(a(f,u),f[3]=0,f[7]=0,f[11]=0,f[15]=1,Math.abs(o(f)<1e-8))return!1;var y,x,b,_,w,T,k,M=u[3],A=u[7],S=u[11],E=u[12],C=u[13],L=u[14],I=u[15];if(0!==M||0!==A||0!==S){if(h[0]=M,h[1]=A,h[2]=S,h[3]=I,!s(f,f))return!1;l(f,f),y=m,b=f,_=(x=h)[0],w=x[1],T=x[2],k=x[3],y[0]=b[0]*_+b[4]*w+b[8]*T+b[12]*k,y[1]=b[1]*_+b[5]*w+b[9]*T+b[13]*k,y[2]=b[2]*_+b[6]*w+b[10]*T+b[14]*k,y[3]=b[3]*_+b[7]*w+b[11]*T+b[15]*k}else m[0]=m[1]=m[2]=0,m[3]=1;if(e[0]=E,e[1]=C,e[2]=L,function(t,e){t[0][0]=e[0],t[0][1]=e[1],t[0][2]=e[2],t[1][0]=e[4],t[1][1]=e[5],t[1][2]=e[6],t[2][0]=e[8],t[2][1]=e[9],t[2][2]=e[10]}(p,u),r[0]=c.length(p[0]),c.normalize(p[0],p[0]),i[0]=c.dot(p[0],p[1]),g(p[1],p[1],p[0],1,-i[0]),r[1]=c.length(p[1]),c.normalize(p[1],p[1]),i[0]/=r[1],i[1]=c.dot(p[0],p[2]),g(p[2],p[2],p[0],1,-i[1]),i[2]=c.dot(p[1],p[2]),g(p[2],p[2],p[1],1,-i[2]),r[2]=c.length(p[2]),c.normalize(p[2],p[2]),i[1]/=r[2],i[2]/=r[2],c.cross(d,p[1],p[2]),c.dot(p[0],d)<0)for(var P=0;P<3;P++)r[P]*=-1,p[P][0]*=-1,p[P][1]*=-1,p[P][2]*=-1;return v[0]=.5*Math.sqrt(Math.max(1+p[0][0]-p[1][1]-p[2][2],0)),v[1]=.5*Math.sqrt(Math.max(1-p[0][0]+p[1][1]-p[2][2],0)),v[2]=.5*Math.sqrt(Math.max(1-p[0][0]-p[1][1]+p[2][2],0)),v[3]=.5*Math.sqrt(Math.max(1+p[0][0]+p[1][1]+p[2][2],0)),p[2][1]>p[1][2]&&(v[0]=-v[0]),p[0][2]>p[2][0]&&(v[1]=-v[1]),p[1][0]>p[0][1]&&(v[2]=-v[2]),!0}},{\"./normalize\":476,\"gl-mat4/clone\":278,\"gl-mat4/create\":280,\"gl-mat4/determinant\":281,\"gl-mat4/invert\":293,\"gl-mat4/transpose\":306,\"gl-vec3/cross\":365,\"gl-vec3/dot\":370,\"gl-vec3/length\":380,\"gl-vec3/normalize\":387}],476:[function(t,e,r){e.exports=function(t,e){var r=e[15];if(0===r)return!1;for(var n=1/r,i=0;i<16;i++)t[i]=e[i]*n;return!0}},{}],477:[function(t,e,r){var n=t(\"gl-vec3/lerp\"),i=t(\"mat4-recompose\"),a=t(\"mat4-decompose\"),o=t(\"gl-mat4/determinant\"),s=t(\"quat-slerp\"),l=f(),c=f(),u=f();function f(){return{translate:h(),scale:h(1),skew:h(),perspective:[0,0,0,1],quaternion:[0,0,0,1]}}function h(t){return[t||0,t||0,t||0]}e.exports=function(t,e,r,f){if(0===o(e)||0===o(r))return!1;var h=a(e,l.translate,l.scale,l.skew,l.perspective,l.quaternion),p=a(r,c.translate,c.scale,c.skew,c.perspective,c.quaternion);return!(!h||!p)&&(n(u.translate,l.translate,c.translate,f),n(u.skew,l.skew,c.skew,f),n(u.scale,l.scale,c.scale,f),n(u.perspective,l.perspective,c.perspective,f),s(u.quaternion,l.quaternion,c.quaternion,f),i(t,u.translate,u.scale,u.skew,u.perspective,u.quaternion),!0)}},{\"gl-mat4/determinant\":281,\"gl-vec3/lerp\":381,\"mat4-decompose\":475,\"mat4-recompose\":478,\"quat-slerp\":527}],478:[function(t,e,r){var n={identity:t(\"gl-mat4/identity\"),translate:t(\"gl-mat4/translate\"),multiply:t(\"gl-mat4/multiply\"),create:t(\"gl-mat4/create\"),scale:t(\"gl-mat4/scale\"),fromRotationTranslation:t(\"gl-mat4/fromRotationTranslation\")},i=(n.create(),n.create());e.exports=function(t,e,r,a,o,s){return n.identity(t),n.fromRotationTranslation(t,s,e),t[3]=o[0],t[7]=o[1],t[11]=o[2],t[15]=o[3],n.identity(i),0!==a[2]&&(i[9]=a[2],n.multiply(t,t,i)),0!==a[1]&&(i[9]=0,i[8]=a[1],n.multiply(t,t,i)),0!==a[0]&&(i[8]=0,i[4]=a[0],n.multiply(t,t,i)),n.scale(t,t,r),t}},{\"gl-mat4/create\":280,\"gl-mat4/fromRotationTranslation\":284,\"gl-mat4/identity\":291,\"gl-mat4/multiply\":295,\"gl-mat4/scale\":303,\"gl-mat4/translate\":305}],479:[function(t,e,r){\"use strict\";e.exports=Math.log2||function(t){return Math.log(t)*Math.LOG2E}},{}],480:[function(t,e,r){\"use strict\";var n=t(\"binary-search-bounds\"),i=t(\"mat4-interpolate\"),a=t(\"gl-mat4/invert\"),o=t(\"gl-mat4/rotateX\"),s=t(\"gl-mat4/rotateY\"),l=t(\"gl-mat4/rotateZ\"),c=t(\"gl-mat4/lookAt\"),u=t(\"gl-mat4/translate\"),f=(t(\"gl-mat4/scale\"),t(\"gl-vec3/normalize\")),h=[0,0,0];function p(t){this._components=t.slice(),this._time=[0],this.prevMatrix=t.slice(),this.nextMatrix=t.slice(),this.computedMatrix=t.slice(),this.computedInverse=t.slice(),this.computedEye=[0,0,0],this.computedUp=[0,0,0],this.computedCenter=[0,0,0],this.computedRadius=[0],this._limits=[-1/0,1/0]}e.exports=function(t){return new p((t=t||{}).matrix||[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1])};var d=p.prototype;d.recalcMatrix=function(t){var e=this._time,r=n.le(e,t),o=this.computedMatrix;if(!(r<0)){var s=this._components;if(r===e.length-1)for(var l=16*r,c=0;c<16;++c)o[c]=s[l++];else{var u=e[r+1]-e[r],h=(l=16*r,this.prevMatrix),p=!0;for(c=0;c<16;++c)h[c]=s[l++];var d=this.nextMatrix;for(c=0;c<16;++c)d[c]=s[l++],p=p&&h[c]===d[c];if(u<1e-6||p)for(c=0;c<16;++c)o[c]=h[c];else i(o,h,d,(t-e[r])/u)}var g=this.computedUp;g[0]=o[1],g[1]=o[5],g[2]=o[9],f(g,g);var m=this.computedInverse;a(m,o);var v=this.computedEye,y=m[15];v[0]=m[12]/y,v[1]=m[13]/y,v[2]=m[14]/y;var 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\"+r+\"(data,\"+o.map((function(t){return\"shape[\"+t+\"]\"})).join(\",\")+\",\"+o.map((function(t){return\"stride[\"+t+\"]\"})).join(\",\")+\",offset)}\"),new Function(\"CTOR_LIST\",\"ORDER\",a.join(\"\\n\"))(c[t],s)}var c={float32:[],float64:[],int8:[],int16:[],int32:[],uint8:[],uint16:[],uint32:[],array:[],uint8_clamped:[],bigint64:[],biguint64:[],buffer:[],generic:[]};e.exports=function(t,e,r,n){if(void 0===t)return(0,c.array[0])([]);\"number\"==typeof t&&(t=[t]),void 0===e&&(e=[t.length]);var o=e.length;if(void 0===r){r=new Array(o);for(var s=o-1,u=1;s>=0;--s)r[s]=u,u*=e[s]}if(void 0===n){n=0;for(s=0;s<o;++s)r[s]<0&&(n-=(e[s]-1)*r[s])}for(var f=function(t){if(i(t))return\"buffer\";if(a)switch(Object.prototype.toString.call(t)){case\"[object Float64Array]\":return\"float64\";case\"[object Float32Array]\":return\"float32\";case\"[object Int8Array]\":return\"int8\";case\"[object Int16Array]\":return\"int16\";case\"[object Int32Array]\":return\"int32\";case\"[object Uint8Array]\":return\"uint8\";case\"[object Uint16Array]\":return\"uint16\";case\"[object Uint32Array]\":return\"uint32\";case\"[object Uint8ClampedArray]\":return\"uint8_clamped\";case\"[object BigInt64Array]\":return\"bigint64\";case\"[object BigUint64Array]\":return\"biguint64\"}return Array.isArray(t)?\"array\":\"generic\"}(t),h=c[f];h.length<=o+1;)h.push(l(f,h.length-1));return(0,h[o+1])(t,e,r,n)}},{\"iota-array\":463,\"is-buffer\":465}],496:[function(t,e,r){\"use strict\";var n=t(\"double-bits\"),i=Math.pow(2,-1074);e.exports=function(t,e){if(isNaN(t)||isNaN(e))return NaN;if(t===e)return t;if(0===t)return e<0?-i:i;var r=n.hi(t),a=n.lo(t);e>t==t>0?a===-1>>>0?(r+=1,a=0):a+=1:0===a?(a=-1>>>0,r-=1):a-=1;return n.pack(a,r)}},{\"double-bits\":173}],497:[function(t,e,r){var n=Math.PI,i=c(120);function a(t,e,r,n){return[\"C\",t,e,r,n,r,n]}function o(t,e,r,n,i,a){return[\"C\",t/3+2/3*r,e/3+2/3*n,i/3+2/3*r,a/3+2/3*n,i,a]}function 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h=e[l],p=e[c],d=e[u],g=new Array(3),m=0,v=new Array(3),y=0,x=0;x<3;++x)g[x]=h[x]-p[x],m+=g[x]*g[x],v[x]=d[x]-p[x],y+=v[x]*v[x];if(m*y>a){var b=i[c],_=1/Math.sqrt(m*y);for(x=0;x<3;++x){var w=(x+1)%3,T=(x+2)%3;b[x]+=_*(v[w]*g[T]-v[T]*g[w])}}}for(o=0;o<n;++o){b=i[o];var k=0;for(x=0;x<3;++x)k+=b[x]*b[x];if(k>a)for(_=1/Math.sqrt(k),x=0;x<3;++x)b[x]*=_;else for(x=0;x<3;++x)b[x]=0}return i},r.faceNormals=function(t,e,r){for(var n=t.length,i=new Array(n),a=void 0===r?1e-6:r,o=0;o<n;++o){for(var s=t[o],l=new Array(3),c=0;c<3;++c)l[c]=e[s[c]];var u=new Array(3),f=new Array(3);for(c=0;c<3;++c)u[c]=l[1][c]-l[0][c],f[c]=l[2][c]-l[0][c];var h=new Array(3),p=0;for(c=0;c<3;++c){var d=(c+1)%3,g=(c+2)%3;h[c]=u[d]*f[g]-u[g]*f[d],p+=h[c]*h[c]}p=p>a?1/Math.sqrt(p):0;for(c=0;c<3;++c)h[c]*=p;i[o]=h}return i}},{}],499:[function(t,e,r){\n",
       "/*\n",
       "object-assign\n",
       "(c) Sindre Sorhus\n",
       "@license MIT\n",
       "*/\n",
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       "/*\n",
       " * @copyright 2016 Sean Connelly (@voidqk), http://syntheti.cc\n",
       " * @license MIT\n",
       " * @preserve Project Home: https://github.com/voidqk/polybooljs\n",
       " */\n",
       "var n,i=t(\"./lib/build-log\"),a=t(\"./lib/epsilon\"),o=t(\"./lib/intersecter\"),s=t(\"./lib/segment-chainer\"),l=t(\"./lib/segment-selector\"),c=t(\"./lib/geojson\"),u=!1,f=a();function h(t,e,r){var i=n.segments(t),a=n.segments(e),o=r(n.combine(i,a));return n.polygon(o)}n={buildLog:function(t){return!0===t?u=i():!1===t&&(u=!1),!1!==u&&u.list},epsilon:function(t){return f.epsilon(t)},segments:function(t){var e=o(!0,f,u);return 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h=[[1,0,0,1,0,0],[1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,1,0,0],[1,0,0,1,0,0],[1,0,-1,0,0,1],[1,0,-1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,1],[1,0,-1,0,0,1],[-1,0,-1,0,0,1],[-1,0,-1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,1],[-1,0,-1,0,0,1],[0,1,1,0,0,0],[0,1,-1,0,0,0],[0,-1,-1,0,0,0],[0,-1,-1,0,0,0],[0,1,1,0,0,0],[0,-1,1,0,0,0],[0,1,0,-1,1,0],[0,1,0,-1,-1,0],[0,1,0,1,-1,0],[0,1,0,1,1,0],[0,1,0,-1,1,0],[0,1,0,1,-1,0],[0,-1,0,-1,1,0],[0,-1,0,-1,-1,0],[0,-1,0,1,-1,0],[0,-1,0,1,1,0],[0,-1,0,-1,1,0],[0,-1,0,1,-1,0]]},{\"array-bounds\":70,\"color-normalize\":125,\"flatten-vertex-data\":244,\"object-assign\":499,\"pick-by-alias\":511,\"to-float32\":577,\"update-diff\":599}],535:[function(t,e,r){\"use strict\";var n=t(\"color-normalize\"),i=t(\"array-bounds\"),a=t(\"object-assign\"),o=t(\"glslify\"),s=t(\"pick-by-alias\"),l=t(\"flatten-vertex-data\"),c=t(\"earcut\"),u=t(\"array-normalize\"),f=t(\"to-float32\"),h=f.float32,p=f.fract32,d=t(\"es6-weak-map\"),g=t(\"parse-rect\");function m(t,e){if(!(this instanceof m))return new m(t,e);if(\"function\"==typeof t?(e||(e={}),e.regl=t):e=t,e.length&&(e.positions=e),!(t=e.regl).hasExtension(\"ANGLE_instanced_arrays\"))throw Error(\"regl-error2d: `ANGLE_instanced_arrays` extension should be enabled\");this.gl=t._gl,this.regl=t,this.passes=[],this.shaders=m.shaders.has(t)?m.shaders.get(t):m.shaders.set(t,m.createShaders(t)).get(t),this.update(e)}e.exports=m,m.dashMult=2,m.maxPatternLength=256,m.precisionThreshold=3e6,m.maxPoints=1e4,m.maxLines=2048,m.shaders=new d,m.createShaders=function(t){var e,r=t.buffer({usage:\"static\",type:\"float\",data:[0,1,0,0,1,1,1,0]}),n={primitive:\"triangle strip\",instances:t.prop(\"count\"),count:4,offset:0,uniforms:{miterMode:function(t,e){return\"round\"===e.join?2:1},miterLimit:t.prop(\"miterLimit\"),scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),translate:t.prop(\"translate\"),thickness:t.prop(\"thickness\"),dashPattern:t.prop(\"dashTexture\"),opacity:t.prop(\"opacity\"),pixelRatio:t.context(\"pixelRatio\"),id:t.prop(\"id\"),dashSize:t.prop(\"dashLength\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]},depth:t.prop(\"depth\")},blend:{enable:!0,color:[0,0,0,0],equation:{rgb:\"add\",alpha:\"add\"},func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},depth:{enable:function(t,e){return!e.overlay}},stencil:{enable:!1},scissor:{enable:!0,box:t.prop(\"viewport\")},viewport:t.prop(\"viewport\")},i=t(a({vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aCoord, bCoord, aCoordFract, bCoordFract;\\nattribute vec4 color;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvec2 project(vec2 position, vec2 positionFract, vec2 scale, vec2 scaleFract, vec2 translate, vec2 translateFract) {\\n\\t// the order is important\\n\\treturn position * scale + translate\\n       + positionFract * scale + translateFract\\n       + position * scaleFract\\n       + positionFract * scaleFract;\\n}\\n\\nvoid main() {\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineOffset = lineTop * 2. - 1.;\\n\\n\\tvec2 diff = (bCoord + bCoordFract - aCoord - aCoordFract);\\n\\ttangent = normalize(diff * scale * viewport.zw);\\n\\tvec2 normal = vec2(-tangent.y, tangent.x);\\n\\n\\tvec2 position = project(aCoord, aCoordFract, scale, scaleFract, translate, translateFract) * lineStart\\n\\t\\t+ project(bCoord, bCoordFract, scale, scaleFract, translate, translateFract) * lineEnd\\n\\n\\t\\t+ thickness * normal * .5 * lineOffset / viewport.zw;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D dashPattern;\\n\\nuniform float dashSize, pixelRatio, thickness, opacity, id;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvoid main() {\\n\\tfloat alpha = 1.;\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashSize) * .5 + .25;\\n\\tfloat dash = texture2D(dashPattern, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},aCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:8,divisor:1},bCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:16,divisor:1},color:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1}}},n));try{e=t(a({cull:{enable:!0,face:\"back\"},vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aCoord, bCoord, nextCoord, prevCoord;\\nattribute vec4 aColor, bColor;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, translate;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\nuniform float miterLimit, miterMode;\\n\\nvarying vec4 fragColor;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 tangent;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nconst float REVERSE_THRESHOLD = -.875;\\nconst float MIN_DIFF = 1e-6;\\n\\n// TODO: possible optimizations: avoid overcalculating all for vertices and calc just one instead\\n// TODO: precalculate dot products, normalize things beforehead etc.\\n// TODO: refactor to rectangular algorithm\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nbool isNaN( float val ){\\n  return ( val < 0.0 || 0.0 < val || val == 0.0 ) ? false : true;\\n}\\n\\nvoid main() {\\n\\tvec2 aCoord = aCoord, bCoord = bCoord, prevCoord = prevCoord, nextCoord = nextCoord;\\n\\n  vec2 adjustedScale;\\n  adjustedScale.x = (abs(scale.x) < MIN_DIFF) ? MIN_DIFF : scale.x;\\n  adjustedScale.y = (abs(scale.y) < MIN_DIFF) ? MIN_DIFF : scale.y;\\n\\n  vec2 scaleRatio = adjustedScale * viewport.zw;\\n\\tvec2 normalWidth = thickness / scaleRatio;\\n\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineBot = 1. - lineTop;\\n\\n\\tfragColor = (lineStart * aColor + lineEnd * bColor) / 255.;\\n\\n\\tif (isNaN(aCoord.x) || isNaN(aCoord.y) || isNaN(bCoord.x) || isNaN(bCoord.y)) return;\\n\\n\\tif (aCoord == prevCoord) prevCoord = aCoord + normalize(bCoord - aCoord);\\n\\tif (bCoord == nextCoord) nextCoord = bCoord - normalize(bCoord - aCoord);\\n\\n\\tvec2 prevDiff = aCoord - prevCoord;\\n\\tvec2 currDiff = bCoord - aCoord;\\n\\tvec2 nextDiff = nextCoord - bCoord;\\n\\n\\tvec2 prevTangent = normalize(prevDiff * scaleRatio);\\n\\tvec2 currTangent = normalize(currDiff * scaleRatio);\\n\\tvec2 nextTangent = normalize(nextDiff * scaleRatio);\\n\\n\\tvec2 prevNormal = vec2(-prevTangent.y, prevTangent.x);\\n\\tvec2 currNormal = vec2(-currTangent.y, currTangent.x);\\n\\tvec2 nextNormal = vec2(-nextTangent.y, nextTangent.x);\\n\\n\\tvec2 startJoinDirection = normalize(prevTangent - currTangent);\\n\\tvec2 endJoinDirection = normalize(currTangent - nextTangent);\\n\\n\\t// collapsed/unidirectional segment cases\\n\\t// FIXME: there should be more elegant solution\\n\\tvec2 prevTanDiff = abs(prevTangent - currTangent);\\n\\tvec2 nextTanDiff = abs(nextTangent - currTangent);\\n\\tif (max(prevTanDiff.x, prevTanDiff.y) < MIN_DIFF) {\\n\\t\\tstartJoinDirection = currNormal;\\n\\t}\\n\\tif (max(nextTanDiff.x, nextTanDiff.y) < MIN_DIFF) {\\n\\t\\tendJoinDirection = currNormal;\\n\\t}\\n\\tif (aCoord == bCoord) {\\n\\t\\tendJoinDirection = startJoinDirection;\\n\\t\\tcurrNormal = prevNormal;\\n\\t\\tcurrTangent = prevTangent;\\n\\t}\\n\\n\\ttangent = currTangent;\\n\\n\\t//calculate join shifts relative to normals\\n\\tfloat startJoinShift = dot(currNormal, startJoinDirection);\\n\\tfloat endJoinShift = dot(currNormal, endJoinDirection);\\n\\n\\tfloat startMiterRatio = abs(1. / startJoinShift);\\n\\tfloat endMiterRatio = abs(1. / endJoinShift);\\n\\n\\tvec2 startJoin = startJoinDirection * startMiterRatio;\\n\\tvec2 endJoin = endJoinDirection * endMiterRatio;\\n\\n\\tvec2 startTopJoin, startBotJoin, endTopJoin, endBotJoin;\\n\\tstartTopJoin = sign(startJoinShift) * startJoin * .5;\\n\\tstartBotJoin = -startTopJoin;\\n\\n\\tendTopJoin = sign(endJoinShift) * endJoin * .5;\\n\\tendBotJoin = -endTopJoin;\\n\\n\\tvec2 aTopCoord = aCoord + normalWidth * startTopJoin;\\n\\tvec2 bTopCoord = bCoord + normalWidth * endTopJoin;\\n\\tvec2 aBotCoord = aCoord + normalWidth * startBotJoin;\\n\\tvec2 bBotCoord = bCoord + normalWidth * endBotJoin;\\n\\n\\t//miter anti-clipping\\n\\tfloat baClipping = distToLine(bCoord, aCoord, aBotCoord) / dot(normalize(normalWidth * endBotJoin), normalize(normalWidth.yx * vec2(-startBotJoin.y, startBotJoin.x)));\\n\\tfloat abClipping = distToLine(aCoord, bCoord, bTopCoord) / dot(normalize(normalWidth * startBotJoin), normalize(normalWidth.yx * vec2(-endBotJoin.y, endBotJoin.x)));\\n\\n\\t//prevent close to reverse direction switch\\n\\tbool prevReverse = dot(currTangent, prevTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, prevNormal)) * min(length(prevDiff), length(currDiff)) <  length(normalWidth * currNormal);\\n\\tbool nextReverse = dot(currTangent, nextTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, nextNormal)) * min(length(nextDiff), length(currDiff)) <  length(normalWidth * currNormal);\\n\\n\\tif (prevReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * startJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / startMiterRatio, 1.);\\n\\t\\taBotCoord = aCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\taTopCoord = aCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!nextReverse && baClipping > 0. && baClipping < length(normalWidth * endBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\tbTopCoord -= normalWidth * endTopJoin;\\n\\t\\tbTopCoord += normalize(endTopJoin * normalWidth) * baClipping;\\n\\t}\\n\\n\\tif (nextReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * endJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / endMiterRatio, 1.);\\n\\t\\tbBotCoord = bCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\tbTopCoord = bCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!prevReverse && abClipping > 0. && abClipping < length(normalWidth * startBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\taBotCoord -= normalWidth * startBotJoin;\\n\\t\\taBotCoord += normalize(startBotJoin * normalWidth) * abClipping;\\n\\t}\\n\\n\\tvec2 aTopPosition = (aTopCoord) * adjustedScale + translate;\\n\\tvec2 aBotPosition = (aBotCoord) * adjustedScale + translate;\\n\\n\\tvec2 bTopPosition = (bTopCoord) * adjustedScale + translate;\\n\\tvec2 bBotPosition = (bBotCoord) * adjustedScale + translate;\\n\\n\\t//position is normalized 0..1 coord on the screen\\n\\tvec2 position = (aTopPosition * lineTop + aBotPosition * lineBot) * lineStart + (bTopPosition * lineTop + bBotPosition * lineBot) * lineEnd;\\n\\n\\tstartCoord = aCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\tendCoord = bCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\n\\tgl_Position = vec4(position  * 2.0 - 1.0, depth, 1);\\n\\n\\tenableStartMiter = step(dot(currTangent, prevTangent), .5);\\n\\tenableEndMiter = step(dot(currTangent, nextTangent), .5);\\n\\n\\t//bevel miter cutoffs\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n\\n\\t//round miter cutoffs\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * abs(dot(startJoinDirection, currNormal)) * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * abs(dot(endJoinDirection, currNormal)) * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D dashPattern;\\nuniform float dashSize, pixelRatio, thickness, opacity, id, miterMode;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nvoid main() {\\n\\tfloat alpha = 1., distToStart, distToEnd;\\n\\tfloat cutoff = thickness * .5;\\n\\n\\t//bevel miter\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToStart + 1., 0.), 1.);\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToEnd + 1., 0.), 1.);\\n\\t\\t}\\n\\t}\\n\\n\\t// round miter\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - startCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - endCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashSize) * .5 + .25;\\n\\tfloat dash = texture2D(dashPattern, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1},bColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:4,divisor:1},prevCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:0,divisor:1},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},nextCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:24,divisor:1}}},n))}catch(t){e=i}return{fill:t({primitive:\"triangle\",elements:function(t,e){return e.triangles},offset:0,vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position, positionFract;\\n\\nuniform vec4 color;\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float pixelRatio, id;\\nuniform vec4 viewport;\\nuniform float opacity;\\n\\nvarying vec4 fragColor;\\n\\nconst float MAX_LINES = 256.;\\n\\nvoid main() {\\n\\tfloat depth = (MAX_LINES - 4. - id) / (MAX_LINES);\\n\\n\\tvec2 position = position * scale + translate\\n       + positionFract * scale + translateFract\\n       + position * scaleFract\\n       + positionFract * scaleFract;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n\\tfragColor.a *= opacity;\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n\\tgl_FragColor = fragColor;\\n}\\n\"]),uniforms:{scale:t.prop(\"scale\"),color:t.prop(\"fill\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),translate:t.prop(\"translate\"),opacity:t.prop(\"opacity\"),pixelRatio:t.context(\"pixelRatio\"),id:t.prop(\"id\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]}},attributes:{position:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8},positionFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:8}},blend:n.blend,depth:{enable:!1},scissor:n.scissor,stencil:n.stencil,viewport:n.viewport}),rect:i,miter:e}},m.defaults={dashes:null,join:\"miter\",miterLimit:1,thickness:10,cap:\"square\",color:\"black\",opacity:1,overlay:!1,viewport:null,range:null,close:!1,fill:null},m.prototype.render=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];e.length&&(t=this).update.apply(t,e),this.draw()},m.prototype.draw=function(){for(var t=this,e=[],r=arguments.length;r--;)e[r]=arguments[r];return(e.length?e:this.passes).forEach((function(e,r){var n;if(e&&Array.isArray(e))return(n=t).draw.apply(n,e);\"number\"==typeof e&&(e=t.passes[e]),e&&e.count>1&&e.opacity&&(t.regl._refresh(),e.fill&&e.triangles&&e.triangles.length>2&&t.shaders.fill(e),e.thickness&&(e.scale[0]*e.viewport.width>m.precisionThreshold||e.scale[1]*e.viewport.height>m.precisionThreshold||\"rect\"===e.join||!e.join&&(e.thickness<=2||e.count>=m.maxPoints)?t.shaders.rect(e):t.shaders.miter(e)))})),this},m.prototype.update=function(t){var e=this;if(t){null!=t.length?\"number\"==typeof t[0]&&(t=[{positions:t}]):Array.isArray(t)||(t=[t]);var r=this.regl,o=this.gl;if(t.forEach((function(t,f){var d=e.passes[f];if(void 0!==t)if(null!==t){if(\"number\"==typeof t[0]&&(t={positions:t}),t=s(t,{positions:\"positions points data coords\",thickness:\"thickness lineWidth lineWidths line-width linewidth width stroke-width strokewidth strokeWidth\",join:\"lineJoin linejoin 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Uint8Array})},t=a({},m.defaults,t)),null!=t.thickness&&(d.thickness=parseFloat(t.thickness)),null!=t.opacity&&(d.opacity=parseFloat(t.opacity)),null!=t.miterLimit&&(d.miterLimit=parseFloat(t.miterLimit)),null!=t.overlay&&(d.overlay=!!t.overlay,f<m.maxLines&&(d.depth=2*(m.maxLines-1-f%m.maxLines)/m.maxLines-1)),null!=t.join&&(d.join=t.join),null!=t.hole&&(d.hole=t.hole),null!=t.fill&&(d.fill=t.fill?n(t.fill,\"uint8\"):null),null!=t.viewport&&(d.viewport=g(t.viewport)),d.viewport||(d.viewport=g([o.drawingBufferWidth,o.drawingBufferHeight])),null!=t.close&&(d.close=t.close),null===t.positions&&(t.positions=[]),t.positions){var v,y;if(t.positions.x&&t.positions.y){var x=t.positions.x,b=t.positions.y;y=d.count=Math.max(x.length,b.length),v=new Float64Array(2*y);for(var _=0;_<y;_++)v[2*_]=x[_],v[2*_+1]=b[_]}else v=l(t.positions,\"float64\"),y=d.count=Math.floor(v.length/2);var w=d.bounds=i(v,2);if(d.fill){for(var T=[],k={},M=0,A=0,S=0,E=d.count;A<E;A++){var C=v[2*A],L=v[2*A+1];isNaN(C)||isNaN(L)||null==C||null==L?(C=v[2*M],L=v[2*M+1],k[A]=M):M=A,T[S++]=C,T[S++]=L}for(var I=c(T,d.hole||[]),P=0,z=I.length;P<z;P++)null!=k[I[P]]&&(I[P]=k[I[P]]);d.triangles=I}var O=new Float64Array(v);u(O,2,w);var D=new Float64Array(2*y+6);d.close?v[0]===v[2*y-2]&&v[1]===v[2*y-1]?(D[0]=O[2*y-4],D[1]=O[2*y-3]):(D[0]=O[2*y-2],D[1]=O[2*y-1]):(D[0]=O[0],D[1]=O[1]),D.set(O,2),d.close?v[0]===v[2*y-2]&&v[1]===v[2*y-1]?(D[2*y+2]=O[2],D[2*y+3]=O[3],d.count-=1):(D[2*y+2]=O[0],D[2*y+3]=O[1],D[2*y+4]=O[2],D[2*y+5]=O[3]):(D[2*y+2]=O[2*y-2],D[2*y+3]=O[2*y-1],D[2*y+4]=O[2*y-2],D[2*y+5]=O[2*y-1]),d.positionBuffer(h(D)),d.positionFractBuffer(p(D))}if(t.range?d.range=t.range:d.range||(d.range=d.bounds),(t.range||t.positions)&&d.count){var R=d.bounds,F=R[2]-R[0],B=R[3]-R[1],N=d.range[2]-d.range[0],j=d.range[3]-d.range[1];d.scale=[F/N,B/j],d.translate=[-d.range[0]/N+R[0]/N||0,-d.range[1]/j+R[1]/j||0],d.scaleFract=p(d.scale),d.translateFract=p(d.translate)}if(t.dashes){var U,V=0;if(!t.dashes||t.dashes.length<2)V=1,U=new Uint8Array([255,255,255,255,255,255,255,255]);else{V=0;for(var q=0;q<t.dashes.length;++q)V+=t.dashes[q];U=new Uint8Array(V*m.dashMult);for(var H=0,G=255,Y=0;Y<2;Y++)for(var W=0;W<t.dashes.length;++W){for(var X=0,Z=t.dashes[W]*m.dashMult*.5;X<Z;++X)U[H++]=G;G^=255}}d.dashLength=V,d.dashTexture({channels:1,data:U,width:U.length,height:1,mag:\"linear\",min:\"linear\"},0,0)}if(t.color){var J=d.count,K=t.color;K||(K=\"transparent\");var Q=new Uint8Array(4*J+4);if(Array.isArray(K)&&\"number\"!=typeof K[0]){for(var $=0;$<J;$++){var tt=n(K[$],\"uint8\");Q.set(tt,4*$)}Q.set(n(K[0],\"uint8\"),4*J)}else for(var et=n(K,\"uint8\"),rt=0;rt<J+1;rt++)Q.set(et,4*rt);d.colorBuffer({usage:\"dynamic\",type:\"uint8\",data:Q})}}else e.passes[f]=null})),t.length<this.passes.length){for(var f=t.length;f<this.passes.length;f++){var d=this.passes[f];d&&(d.colorBuffer.destroy(),d.positionBuffer.destroy(),d.dashTexture.destroy())}this.passes.length=t.length}for(var v=[],y=0;y<this.passes.length;y++)null!==this.passes[y]&&v.push(this.passes[y]);return this.passes=v,this}},m.prototype.destroy=function(){return this.passes.forEach((function(t){t.colorBuffer.destroy(),t.positionBuffer.destroy(),t.dashTexture.destroy()})),this.passes.length=0,this}},{\"array-bounds\":70,\"array-normalize\":71,\"color-normalize\":125,earcut:177,\"es6-weak-map\":233,\"flatten-vertex-data\":244,glslify:536,\"object-assign\":499,\"parse-rect\":504,\"pick-by-alias\":511,\"to-float32\":577}],536:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],537:[function(t,e,r){\"use strict\";function n(t,e){return function(t){if(Array.isArray(t))return t}(t)||function(t,e){if(\"undefined\"==typeof Symbol||!(Symbol.iterator in Object(t)))return;var r=[],n=!0,i=!1,a=void 0;try{for(var o,s=t[Symbol.iterator]();!(n=(o=s.next()).done)&&(r.push(o.value),!e||r.length!==e);n=!0);}catch(t){i=!0,a=t}finally{try{n||null==s.return||s.return()}finally{if(i)throw a}}return r}(t,e)||a(t,e)||function(){throw new TypeError(\"Invalid attempt to destructure non-iterable instance.\\nIn order to be iterable, non-array objects must have a [Symbol.iterator]() method.\")}()}function i(t){return function(t){if(Array.isArray(t))return o(t)}(t)||function(t){if(\"undefined\"!=typeof Symbol&&Symbol.iterator in Object(t))return Array.from(t)}(t)||a(t)||function(){throw new TypeError(\"Invalid attempt to spread non-iterable instance.\\nIn order to be iterable, non-array objects must have a [Symbol.iterator]() method.\")}()}function a(t,e){if(t){if(\"string\"==typeof t)return o(t,e);var r=Object.prototype.toString.call(t).slice(8,-1);return\"Object\"===r&&t.constructor&&(r=t.constructor.name),\"Map\"===r||\"Set\"===r?Array.from(t):\"Arguments\"===r||/^(?:Ui|I)nt(?:8|16|32)(?:Clamped)?Array$/.test(r)?o(t,e):void 0}}function o(t,e){(null==e||e>t.length)&&(e=t.length);for(var r=0,n=new Array(e);r<e;r++)n[r]=t[r];return n}var s=t(\"color-normalize\"),l=t(\"array-bounds\"),c=t(\"color-id\"),u=t(\"@plotly/point-cluster\"),f=t(\"object-assign\"),h=t(\"glslify\"),p=t(\"pick-by-alias\"),d=t(\"update-diff\"),g=t(\"flatten-vertex-data\"),m=t(\"is-iexplorer\"),v=t(\"to-float32\"),y=t(\"parse-rect\"),x=b;function b(t,e){var r=this;if(!(this instanceof b))return new b(t,e);\"function\"==typeof t?(e||(e={}),e.regl=t):(e=t,t=null),e&&e.length&&(e.positions=e);var n,i=(t=e.regl)._gl,a=[];this.tooManyColors=m,n=t.texture({data:new Uint8Array(1020),width:255,height:1,type:\"uint8\",format:\"rgba\",wrapS:\"clamp\",wrapT:\"clamp\",mag:\"nearest\",min:\"nearest\"}),f(this,{regl:t,gl:i,groups:[],markerCache:[null],markerTextures:[null],palette:a,paletteIds:{},paletteTexture:n,maxColors:255,maxSize:100,canvas:i.canvas}),this.update(e);var o={uniforms:{constPointSize:!!e.constPointSize,pixelRatio:t.context(\"pixelRatio\"),palette:n,paletteSize:function(t,e){return[r.tooManyColors?0:255,n.height]},scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translate:t.prop(\"translate\"),translateFract:t.prop(\"translateFract\"),opacity:t.prop(\"opacity\"),marker:t.prop(\"markerTexture\")},attributes:{x:function(t,e){return e.xAttr||{buffer:e.positionBuffer,stride:8,offset:0}},y:function(t,e){return e.yAttr||{buffer:e.positionBuffer,stride:8,offset:4}},xFract:function(t,e){return e.xAttr?{constant:[0,0]}:{buffer:e.positionFractBuffer,stride:8,offset:0}},yFract:function(t,e){return e.yAttr?{constant:[0,0]}:{buffer:e.positionFractBuffer,stride:8,offset:4}},size:function(t,e){return e.size.length?{buffer:e.sizeBuffer,stride:2,offset:0}:{constant:[Math.round(255*e.size/r.maxSize)]}},borderSize:function(t,e){return e.borderSize.length?{buffer:e.sizeBuffer,stride:2,offset:1}:{constant:[Math.round(255*e.borderSize/r.maxSize)]}},colorId:function(t,e){return e.color.length?{buffer:e.colorBuffer,stride:r.tooManyColors?8:4,offset:0}:{constant:r.tooManyColors?a.slice(4*e.color,4*e.color+4):[e.color]}},borderColorId:function(t,e){return e.borderColor.length?{buffer:e.colorBuffer,stride:r.tooManyColors?8:4,offset:r.tooManyColors?4:2}:{constant:r.tooManyColors?a.slice(4*e.borderColor,4*e.borderColor+4):[e.borderColor]}},isActive:function(t,e){return!0===e.activation?{constant:[1]}:e.activation?e.activation:{constant:[0]}}},blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},scissor:{enable:!0,box:t.prop(\"viewport\")},viewport:t.prop(\"viewport\"),stencil:{enable:!1},depth:{enable:!1},elements:t.prop(\"elements\"),count:t.prop(\"count\"),offset:t.prop(\"offset\"),primitive:\"points\"},s=f({},o);s.frag=h([\"precision 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fragColor, colorAmt);\\n    color.a *= opacity;\\n\\n    gl_FragColor = color;\\n  }\\n\\n}\\n\"]),s.vert=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, borderSize;\\nattribute vec4 colorId, borderColorId;\\nattribute float isActive;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract, paletteSize;\\nuniform float pixelRatio;\\nuniform bool constPointSize;\\nuniform sampler2D palette;\\n\\nconst float maxSize = 100.;\\nconst float borderLevel = .5;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragPointSize, fragBorderRadius, fragWidth, fragBorderColorLevel, fragColorLevel;\\n\\nfloat pointSizeScale = (constPointSize) ? 2. : pixelRatio;\\n\\nbool isDirect = (paletteSize.x < 1.);\\n\\nvec4 getColor(vec4 id) {\\n  return isDirect ? id / 255. : texture2D(palette,\\n    vec2(\\n      (id.x + .5) / paletteSize.x,\\n      (id.y + .5) / paletteSize.y\\n    )\\n  );\\n}\\n\\nvoid main() {\\n  // ignore inactive points\\n  if (isActive == 0.) return;\\n\\n  vec2 position = vec2(x, y);\\n  vec2 positionFract = vec2(xFract, yFract);\\n\\n  vec4 color = getColor(colorId);\\n  vec4 borderColor = getColor(borderColorId);\\n\\n  float size = size * maxSize / 255.;\\n  float borderSize = borderSize * maxSize / 255.;\\n\\n  gl_PointSize = 2. * size * pointSizeScale;\\n  fragPointSize = size * pixelRatio;\\n\\n  vec2 pos = (position + translate) * scale\\n      + (positionFract + translateFract) * scale\\n      + (position + translate) * scaleFract\\n      + (positionFract + translateFract) * scaleFract;\\n\\n  gl_Position = vec4(pos * 2. - 1., 0., 1.);\\n\\n  fragColor = color;\\n  fragBorderColor = borderColor;\\n  fragWidth = 1. / gl_PointSize;\\n\\n  fragBorderColorLevel = clamp(borderLevel - borderLevel * borderSize / size, 0., 1.);\\n  fragColorLevel = clamp(borderLevel + (1. - borderLevel) * borderSize / size, 0., 1.);\\n}\"]),this.drawMarker=t(s);var l=f({},o);l.frag=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor, fragBorderColor;\\n\\nuniform float opacity;\\nvarying float fragBorderRadius, fragWidth;\\n\\nfloat smoothStep(float edge0, float edge1, float x) {\\n\\tfloat t;\\n\\tt = clamp((x - edge0) / (edge1 - edge0), 0.0, 1.0);\\n\\treturn t * t * (3.0 - 2.0 * t);\\n}\\n\\nvoid main() {\\n\\tfloat radius, alpha = 1.0, delta = fragWidth;\\n\\n\\tradius = length(2.0 * gl_PointCoord.xy - 1.0);\\n\\n\\tif (radius > 1.0 + delta) {\\n\\t\\tdiscard;\\n\\t}\\n\\n\\talpha -= smoothstep(1.0 - delta, 1.0 + delta, radius);\\n\\n\\tfloat borderRadius = fragBorderRadius;\\n\\tfloat ratio = smoothstep(borderRadius - delta, borderRadius + delta, radius);\\n\\tvec4 color = mix(fragColor, fragBorderColor, ratio);\\n\\tcolor.a *= alpha * opacity;\\n\\tgl_FragColor = color;\\n}\\n\"]),l.vert=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, borderSize;\\nattribute vec4 colorId, borderColorId;\\nattribute float isActive;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float pixelRatio;\\nuniform bool constPointSize;\\nuniform sampler2D palette;\\nuniform vec2 paletteSize;\\n\\nconst float maxSize = 100.;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragBorderRadius, fragWidth;\\n\\nfloat pointSizeScale = (constPointSize) ? 2. : pixelRatio;\\n\\nbool isDirect = (paletteSize.x < 1.);\\n\\nvec4 getColor(vec4 id) {\\n  return isDirect ? id / 255. : texture2D(palette,\\n    vec2(\\n      (id.x + .5) / paletteSize.x,\\n      (id.y + .5) / paletteSize.y\\n    )\\n  );\\n}\\n\\nvoid main() {\\n  // ignore inactive points\\n  if (isActive == 0.) return;\\n\\n  vec2 position = vec2(x, y);\\n  vec2 positionFract = vec2(xFract, yFract);\\n\\n  vec4 color = getColor(colorId);\\n  vec4 borderColor = getColor(borderColorId);\\n\\n  float size = size * maxSize / 255.;\\n  float borderSize = borderSize * maxSize / 255.;\\n\\n  gl_PointSize = (size + borderSize) * pointSizeScale;\\n\\n  vec2 pos = (position + translate) * scale\\n      + (positionFract + translateFract) * scale\\n      + (position + translate) * scaleFract\\n      + (positionFract + translateFract) * scaleFract;\\n\\n  gl_Position = vec4(pos * 2. - 1., 0., 1.);\\n\\n  fragBorderRadius = 1. - 2. * borderSize / (size + borderSize);\\n  fragColor = color;\\n  fragBorderColor = borderColor.a == 0. || borderSize == 0. ? vec4(color.rgb, 0.) : borderColor;\\n  fragWidth = 1. / gl_PointSize;\\n}\\n\"]),m&&(l.frag=l.frag.replace(\"smoothstep\",\"smoothStep\"),s.frag=s.frag.replace(\"smoothstep\",\"smoothStep\")),this.drawCircle=t(l)}b.defaults={color:\"black\",borderColor:\"transparent\",borderSize:0,size:12,opacity:1,marker:void 0,viewport:null,range:null,pixelSize:null,count:0,offset:0,bounds:null,positions:[],snap:1e4},b.prototype.render=function(){return arguments.length&&this.update.apply(this,arguments),this.draw(),this},b.prototype.draw=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];var i=this.groups;if(1===r.length&&Array.isArray(r[0])&&(null===r[0][0]||Array.isArray(r[0][0]))&&(r=r[0]),this.regl._refresh(),r.length)for(var a=0;a<r.length;a++)this.drawItem(a,r[a]);else i.forEach((function(e,r){t.drawItem(r)}));return this},b.prototype.drawItem=function(t,e){var r=this.groups,n=r[t];if(\"number\"==typeof e&&(t=e,n=r[e],e=null),n&&n.count&&n.opacity){n.activation[0]&&this.drawCircle(this.getMarkerDrawOptions(0,n,e));for(var a=[],o=1;o<n.activation.length;o++)n.activation[o]&&(!0===n.activation[o]||n.activation[o].data.length)&&a.push.apply(a,i(this.getMarkerDrawOptions(o,n,e)));a.length&&this.drawMarker(a)}},b.prototype.getMarkerDrawOptions=function(t,e,r){var i=e.range,a=e.tree,o=e.viewport,s=e.activation,l=e.selectionBuffer,c=e.count;this.regl;if(!a)return r?[f({},e,{markerTexture:this.markerTextures[t],activation:s[t],count:r.length,elements:r,offset:0})]:[f({},e,{markerTexture:this.markerTextures[t],activation:s[t],offset:0})];var u=[],h=a.range(i,{lod:!0,px:[(i[2]-i[0])/o.width,(i[3]-i[1])/o.height]});if(r){for(var p=s[t].data,d=new Uint8Array(c),g=0;g<r.length;g++){var m=r[g];d[m]=p?p[m]:1}l.subdata(d)}for(var v=h.length;v--;){var y=n(h[v],2),x=y[0],b=y[1];u.push(f({},e,{markerTexture:this.markerTextures[t],activation:r?l:s[t],offset:x,count:b-x}))}return u},b.prototype.update=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];if(r.length){1===r.length&&Array.isArray(r[0])&&(r=r[0]);var i=this.groups,a=this.gl,o=this.regl,s=this.maxSize,c=this.maxColors,h=this.palette;this.groups=i=r.map((function(e,r){var n=i[r];if(void 0===e)return n;null===e?e={positions:null}:\"function\"==typeof e?e={ondraw:e}:\"number\"==typeof e[0]&&(e={positions:e}),null===(e=p(e,{positions:\"positions data points\",snap:\"snap cluster lod tree\",size:\"sizes size radius\",borderSize:\"borderSizes borderSize border-size bordersize borderWidth borderWidths border-width borderwidth stroke-width strokeWidth strokewidth outline\",color:\"colors color fill fill-color fillColor\",borderColor:\"borderColors borderColor stroke stroke-color strokeColor\",marker:\"markers marker shape\",range:\"range dataBox databox\",viewport:\"viewport viewPort viewBox viewbox\",opacity:\"opacity alpha transparency\",bounds:\"bound bounds boundaries limits\",tooManyColors:\"tooManyColors palette paletteMode optimizePalette enablePalette\"})).positions&&(e.positions=[]),null!=e.tooManyColors&&(t.tooManyColors=e.tooManyColors),n||(i[r]=n={id:r,scale:null,translate:null,scaleFract:null,translateFract:null,activation:[],selectionBuffer:o.buffer({data:new Uint8Array(0),usage:\"stream\",type:\"uint8\"}),sizeBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"uint8\"}),colorBuffer:o.buffer({data:new 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t.x.length?e.xAttr={buffer:o.buffer(t.x),offset:0,stride:4,count:t.x.length}:e.xAttr={buffer:t.x.buffer,offset:4*t.x.offset||0,stride:4*(t.x.stride||1),count:t.x.count},t.y.length?e.yAttr={buffer:o.buffer(t.y),offset:0,stride:4,count:t.y.length}:e.yAttr={buffer:t.y.buffer,offset:4*t.y.offset||0,stride:4*(t.y.stride||1),count:t.y.count},e.count=Math.max(e.xAttr.count,e.yAttr.count),t;t=g(t,\"float64\");var c=e.count=Math.floor(t.length/2),f=e.bounds=c?l(t,2):null;if(r.range||e.range||(delete e.range,r.range=f),r.marker||e.marker||(delete e.marker,r.marker=null),n&&(!0===n||c>n)?e.tree=u(t,{bounds:f}):n&&n.length&&(e.tree=n),e.tree){var h={primitive:\"points\",usage:\"static\",data:e.tree,type:\"uint32\"};e.elements?e.elements(h):e.elements=o.elements(h)}return i({data:v.float(t),usage:\"dynamic\"}),a({data:v.fract(t),usage:\"dynamic\"}),s({data:new Uint8Array(c),type:\"uint8\",usage:\"stream\"}),t}},{marker:function(e,r,n){var i=r.activation;if(i.forEach((function(t){return t&&t.destroy&&t.destroy()})),i.length=0,e&&\"number\"!=typeof e[0]){for(var a=[],s=0,l=Math.min(e.length,r.count);s<l;s++){var c=t.addMarker(e[s]);a[c]||(a[c]=new Uint8Array(r.count)),a[c][s]=1}for(var u=0;u<a.length;u++)if(a[u]){var f={data:a[u],type:\"uint8\",usage:\"static\"};i[u]?i[u](f):i[u]=o.buffer(f),i[u].data=a[u]}}else{i[t.addMarker(e)]=!0}return e},range:function(t,e,r){var n=e.bounds;if(n)return t||(t=n),e.scale=[1/(t[2]-t[0]),1/(t[3]-t[1])],e.translate=[-t[0],-t[1]],e.scaleFract=v.fract(e.scale),e.translateFract=v.fract(e.translate),t},viewport:function(t){return y(t||[a.drawingBufferWidth,a.drawingBufferHeight])}}]),m){var _=n,w=_.count,T=_.size,k=_.borderSize,M=_.sizeBuffer,A=new Uint8Array(2*w);if(T.length||k.length)for(var S=0;S<w;S++)A[2*S]=Math.round(255*(null==T[S]?T:T[S])/s),A[2*S+1]=Math.round(255*(null==k[S]?k:k[S])/s);M({data:A,usage:\"dynamic\"})}if(x){var E,C=n,L=C.count,I=C.color,P=C.borderColor,z=C.colorBuffer;if(t.tooManyColors){if(I.length||P.length){E=new Uint8Array(8*L);for(var O=0;O<L;O++){var D=I[O];E[8*O]=h[4*D],E[8*O+1]=h[4*D+1],E[8*O+2]=h[4*D+2],E[8*O+3]=h[4*D+3];var R=P[O];E[8*O+4]=h[4*R],E[8*O+5]=h[4*R+1],E[8*O+6]=h[4*R+2],E[8*O+7]=h[4*R+3]}}}else if(I.length||P.length){E=new Uint8Array(4*L+2);for(var F=0;F<L;F++)null!=I[F]&&(E[4*F]=I[F]%c,E[4*F+1]=Math.floor(I[F]/c)),null!=P[F]&&(E[4*F+2]=P[F]%c,E[4*F+3]=Math.floor(P[F]/c))}z({data:E||new Uint8Array(0),type:\"uint8\",usage:\"dynamic\"})}return n}))}},b.prototype.addMarker=function(t){var e,r=this.markerTextures,n=this.regl,i=this.markerCache,a=null==t?0:i.indexOf(t);if(a>=0)return a;if(t instanceof Uint8Array||t instanceof Uint8ClampedArray)e=t;else{e=new Uint8Array(t.length);for(var o=0,s=t.length;o<s;o++)e[o]=255*t[o]}var l=Math.floor(Math.sqrt(e.length));return a=r.length,i.push(t),r.push(n.texture({channels:1,data:e,radius:l,mag:\"linear\",min:\"linear\"})),a},b.prototype.updateColor=function(t){var e=this.paletteIds,r=this.palette,n=this.maxColors;Array.isArray(t)||(t=[t]);var i=[];if(\"number\"==typeof t[0]){var a=[];if(Array.isArray(t))for(var o=0;o<t.length;o+=4)a.push(t.slice(o,o+4));else for(var l=0;l<t.length;l+=4)a.push(t.subarray(l,l+4));t=a}for(var u=0;u<t.length;u++){var f=t[u];f=s(f,\"uint8\");var h=c(f,!1);if(null==e[h]){var p=r.length;e[h]=Math.floor(p/4),r[p]=f[0],r[p+1]=f[1],r[p+2]=f[2],r[p+3]=f[3]}i[u]=e[h]}return!this.tooManyColors&&r.length>4*n&&(this.tooManyColors=!0),this.updatePalette(r),1===i.length?i[0]:i},b.prototype.updatePalette=function(t){if(!this.tooManyColors){var e=this.maxColors,r=this.paletteTexture,n=Math.ceil(.25*t.length/e);if(n>1)for(var i=.25*(t=t.slice()).length%e;i<n*e;i++)t.push(0,0,0,0);r.height<n&&r.resize(e,n),r.subimage({width:Math.min(.25*t.length,e),height:n,data:t},0,0)}},b.prototype.destroy=function(){return this.groups.forEach((function(t){t.sizeBuffer.destroy(),t.positionBuffer.destroy(),t.positionFractBuffer.destroy(),t.colorBuffer.destroy(),t.activation.forEach((function(t){return t&&t.destroy&&t.destroy()})),t.selectionBuffer.destroy(),t.elements&&t.elements.destroy()})),this.groups.length=0,this.paletteTexture.destroy(),this.markerTextures.forEach((function(t){return t&&t.destroy&&t.destroy()})),this};var _=t(\"object-assign\");e.exports=function(t,e){var r=new x(t,e),n=r.render.bind(r);return _(n,{render:n,update:r.update.bind(r),draw:r.draw.bind(r),destroy:r.destroy.bind(r),regl:r.regl,gl:r.gl,canvas:r.gl.canvas,groups:r.groups,markers:r.markerCache,palette:r.palette}),n}},{\"@plotly/point-cluster\":57,\"array-bounds\":70,\"color-id\":123,\"color-normalize\":125,\"flatten-vertex-data\":244,glslify:538,\"is-iexplorer\":466,\"object-assign\":499,\"parse-rect\":504,\"pick-by-alias\":511,\"to-float32\":577,\"update-diff\":599}],538:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],539:[function(t,e,r){\"use strict\";var n=t(\"regl-scatter2d\"),i=t(\"pick-by-alias\"),a=t(\"array-bounds\"),o=t(\"raf\"),s=t(\"array-range\"),l=t(\"parse-rect\"),c=t(\"flatten-vertex-data\");function u(t,e){if(!(this instanceof u))return new u(t,e);this.traces=[],this.passes={},this.regl=t,this.scatter=n(t),this.canvas=this.scatter.canvas}function f(t,e,r){return(null!=t.id?t.id:t)<<16|(255&e)<<8|255&r}function h(t,e,r){var n,i,a,o,s=t[e],l=t[r];return s.length>2?(s[0],s[2],n=s[1],i=s[3]):s.length?(n=s[0],i=s[1]):(s.x,n=s.y,s.x+s.width,i=s.y+s.height),l.length>2?(a=l[0],o=l[2],l[1],l[3]):l.length?(a=l[0],o=l[1]):(a=l.x,l.y,o=l.x+l.width,l.y+l.height),[a,n,o,i]}function p(t){if(\"number\"==typeof t)return[t,t,t,t];if(2===t.length)return[t[0],t[1],t[0],t[1]];var e=l(t);return[e.x,e.y,e.x+e.width,e.y+e.height]}e.exports=u,u.prototype.render=function(){for(var t,e=this,r=[],n=arguments.length;n--;)r[n]=arguments[n];return r.length&&(t=this).update.apply(t,r),this.regl.attributes.preserveDrawingBuffer?this.draw():(this.dirty?null==this.planned&&(this.planned=o((function(){e.draw(),e.dirty=!0,e.planned=null}))):(this.draw(),this.dirty=!0,o((function(){e.dirty=!1}))),this)},u.prototype.update=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=0;n<e.length;n++)this.updateItem(n,e[n]);this.traces=this.traces.filter(Boolean);for(var i=[],a=0,o=0;o<this.traces.length;o++){for(var 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u=0;u<s.columns;u++)s.bounds[u]=a(o.data[u],1)}o.range&&(s.range=o.range,n=s.range&&\"number\"!=typeof s.range[0]),o.domain&&(s.domain=o.domain);var d=!1;null!=o.padding&&(Array.isArray(o.padding)&&o.padding.length===s.columns&&\"number\"==typeof o.padding[o.padding.length-1]?(s.padding=o.padding.map(p),d=!0):s.padding=p(o.padding));var g=s.columns,m=s.count,v=s.viewport.width,y=s.viewport.height,x=s.viewport.x,b=s.viewport.y,_=v/g,w=y/g;s.passes=[];for(var T=0;T<g;T++)for(var k=0;k<g;k++)if((s.diagonal||k!==T)&&(s.upper||!(T>k))&&(s.lower||!(T<k))){var M=f(s.id,T,k),A=this.passes[M]||(this.passes[M]={});if(o.data&&(o.transpose?A.positions={x:{buffer:s.buffer,offset:k,count:m,stride:g},y:{buffer:s.buffer,offset:T,count:m,stride:g}}:A.positions={x:{buffer:s.buffer,offset:k*m,count:m},y:{buffer:s.buffer,offset:T*m,count:m}},A.bounds=h(s.bounds,T,k)),o.domain||o.viewport||o.data){var S=d?h(s.padding,T,k):s.padding;if(s.domain){var E=h(s.domain,T,k),C=E[0],L=E[1],I=E[2],P=E[3];A.viewport=[x+C*v+S[0],b+L*y+S[1],x+I*v-S[2],b+P*y-S[3]]}else A.viewport=[x+k*_+_*S[0],b+T*w+w*S[1],x+(k+1)*_-_*S[2],b+(T+1)*w-w*S[3]]}o.color&&(A.color=s.color),o.size&&(A.size=s.size),o.marker&&(A.marker=s.marker),o.borderSize&&(A.borderSize=s.borderSize),o.borderColor&&(A.borderColor=s.borderColor),o.opacity&&(A.opacity=s.opacity),o.range&&(A.range=n?h(s.range,T,k):s.range||A.bounds),s.passes.push(M)}return this},u.prototype.draw=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=[],i=0;i<e.length;i++)if(\"number\"==typeof e[i]){var a=this.traces[e[i]],o=a.passes,l=a.passOffset;n.push.apply(n,s(l,l+o.length))}else if(e[i].length){var c=e[i],u=this.traces[i],f=u.passes,h=u.passOffset;f=f.map((function(t,e){n[h+e]=c}))}(t=this.scatter).draw.apply(t,n)}else this.scatter.draw();return this},u.prototype.destroy=function(){return this.traces.forEach((function(t){t.buffer&&t.buffer.destroy&&t.buffer.destroy()})),this.traces=null,this.passes=null,this.scatter.destroy(),this}},{\"array-bounds\":70,\"array-range\":72,\"flatten-vertex-data\":244,\"parse-rect\":504,\"pick-by-alias\":511,raf:528,\"regl-scatter2d\":537}],540:[function(t,e,r){!function(t,n){\"object\"==typeof r&&\"undefined\"!=typeof e?e.exports=n():t.createREGL=n()}(this,(function(){function t(t,e){this.id=V++,this.type=t,this.data=e}function e(t){return\"[\"+function t(e){if(0===e.length)return[];var r=e.charAt(0),n=e.charAt(e.length-1);if(1<e.length&&r===n&&('\"'===r||\"'\"===r))return['\"'+e.substr(1,e.length-2).replace(/\\\\/g,\"\\\\\\\\\").replace(/\"/g,'\\\\\"')+'\"'];if(r=/\\[(false|true|null|\\d+|'[^']*'|\"[^\"]*\")\\]/.exec(e))return 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r,n=parseInt(e);if(isNaN(n))\"\\u95f0\"===e[0]&&(r=!0,e=e.substring(1)),\"\\u6708\"===e[e.length-1]&&(e=e.substring(0,e.length-1)),n=1+[\"\\u4e00\",\"\\u4e8c\",\"\\u4e09\",\"\\u56db\",\"\\u4e94\",\"\\u516d\",\"\\u4e03\",\"\\u516b\",\"\\u4e5d\",\"\\u5341\",\"\\u5341\\u4e00\",\"\\u5341\\u4e8c\"].indexOf(e);else{var i=e[e.length-1];r=\"i\"===i||\"I\"===i}return this.toMonthIndex(t,n,r)},dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:1,isRTL:!1}},_validateYear:function(t,e){if(t.year&&(t=t.year()),\"number\"!=typeof t||t<1888||t>2111)throw e.replace(/\\{0\\}/,this.local.name);return t},toMonthIndex:function(t,e,r){var i=this.intercalaryMonth(t);if(r&&e!==i||e<1||e>12)throw n.local.invalidMonth.replace(/\\{0\\}/,this.local.name);return i?!r&&e<=i?e-1:e:e-1},toChineseMonth:function(t,e){t.year&&(e=(t=t.year()).month());var r=this.intercalaryMonth(t);if(e<0||e>(r?12:11))throw n.local.invalidMonth.replace(/\\{0\\}/,this.local.name);return r?e<r?e+1:e:e+1},intercalaryMonth:function(t){return t=this._validateYear(t),f[t-f[0]]>>13},isIntercalaryMonth:function(t,e){t.year&&(e=(t=t.year()).month());var r=this.intercalaryMonth(t);return!!r&&r===e},leapYear:function(t){return 0!==this.intercalaryMonth(t)},weekOfYear:function(t,e,r){var i,o=this._validateYear(t,n.local.invalidyear),s=h[o-h[0]],l=s>>9&4095,c=s>>5&15,u=31&s;(i=a.newDate(l,c,u)).add(4-(i.dayOfWeek()||7),\"d\");var f=this.toJD(t,e,r)-i.toJD();return 1+Math.floor(f/7)},monthsInYear:function(t){return this.leapYear(t)?13:12},daysInMonth:function(t,e){t.year&&(e=t.month(),t=t.year()),t=this._validateYear(t);var r=f[t-f[0]];if(e>(r>>13?12:11))throw n.local.invalidMonth.replace(/\\{0\\}/,this.local.name);return r&1<<12-e?30:29},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,s,r,n.local.invalidDate);t=this._validateYear(i.year()),e=i.month(),r=i.day();var o=this.isIntercalaryMonth(t,e),s=this.toChineseMonth(t,e),l=function(t,e,r,n,i){var a,o,s;if(\"object\"==typeof t)o=t,a=e||{};else{var l;if(!(\"number\"==typeof t&&t>=1888&&t<=2111))throw new Error(\"Lunar year outside range 1888-2111\");if(!(\"number\"==typeof e&&e>=1&&e<=12))throw new Error(\"Lunar month outside range 1 - 12\");if(!(\"number\"==typeof r&&r>=1&&r<=30))throw new Error(\"Lunar day outside range 1 - 30\");\"object\"==typeof n?(l=!1,a=n):(l=!!n,a=i||{}),o={year:t,month:e,day:r,isIntercalary:l}}s=o.day-1;var c,u=f[o.year-f[0]],p=u>>13;c=p&&(o.month>p||o.isIntercalary)?o.month:o.month-1;for(var d=0;d<c;d++){s+=u&1<<12-d?30:29}var g=h[o.year-h[0]],m=new Date(g>>9&4095,(g>>5&15)-1,(31&g)+s);return a.year=m.getFullYear(),a.month=1+m.getMonth(),a.day=m.getDate(),a}(t,s,r,o);return a.toJD(l.year,l.month,l.day)},fromJD:function(t){var e=a.fromJD(t),r=function(t,e,r,n){var i,a;if(\"object\"==typeof t)i=t,a=e||{};else{if(!(\"number\"==typeof t&&t>=1888&&t<=2111))throw new Error(\"Solar year outside range 1888-2111\");if(!(\"number\"==typeof e&&e>=1&&e<=12))throw new Error(\"Solar month outside range 1 - 12\");if(!(\"number\"==typeof r&&r>=1&&r<=31))throw new Error(\"Solar day outside range 1 - 31\");i={year:t,month:e,day:r},a=n||{}}var o=h[i.year-h[0]],s=i.year<<9|i.month<<5|i.day;a.year=s>=o?i.year:i.year-1,o=h[a.year-h[0]];var l,c=new Date(o>>9&4095,(o>>5&15)-1,31&o),u=new Date(i.year,i.month-1,i.day);l=Math.round((u-c)/864e5);var p,d=f[a.year-f[0]];for(p=0;p<13;p++){var g=d&1<<12-p?30:29;if(l<g)break;l-=g}var m=d>>13;!m||p<m?(a.isIntercalary=!1,a.month=1+p):p===m?(a.isIntercalary=!0,a.month=p):(a.isIntercalary=!1,a.month=p);return 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n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Coptic\",jdEpoch:1825029.5,daysPerMonth:[30,30,30,30,30,30,30,30,30,30,30,30,5],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Coptic\",epochs:[\"BAM\",\"AM\"],monthNames:[\"Thout\",\"Paopi\",\"Hathor\",\"Koiak\",\"Tobi\",\"Meshir\",\"Paremhat\",\"Paremoude\",\"Pashons\",\"Paoni\",\"Epip\",\"Mesori\",\"Pi Kogi Enavot\"],monthNamesShort:[\"Tho\",\"Pao\",\"Hath\",\"Koi\",\"Tob\",\"Mesh\",\"Pat\",\"Pad\",\"Pash\",\"Pao\",\"Epi\",\"Meso\",\"PiK\"],dayNames:[\"Tkyriaka\",\"Pesnau\",\"Pshoment\",\"Peftoou\",\"Ptiou\",\"Psoou\",\"Psabbaton\"],dayNamesShort:[\"Tky\",\"Pes\",\"Psh\",\"Pef\",\"Pti\",\"Pso\",\"Psa\"],dayNamesMin:[\"Tk\",\"Pes\",\"Psh\",\"Pef\",\"Pt\",\"Pso\",\"Psa\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()+(e.year()<0?1:0))%4==3||t%4==-1},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear),13},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(13===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return(t=i.year())<0&&t++,i.day()+30*(i.month()-1)+365*(t-1)+Math.floor(t/4)+this.jdEpoch-1},fromJD:function(t){var e=Math.floor(t)+.5-this.jdEpoch,r=Math.floor((e-Math.floor((e+366)/1461))/365)+1;r<=0&&r--,e=Math.floor(t)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(e/30)+1,i=e-30*(n-1)+1;return this.newDate(r,n,i)}}),n.calendars.coptic=a},{\"../main\":621,\"object-assign\":499}],609:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Discworld\",jdEpoch:1721425.5,daysPerMonth:[16,32,32,32,32,32,32,32,32,32,32,32,32],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Discworld\",epochs:[\"BUC\",\"UC\"],monthNames:[\"Ick\",\"Offle\",\"February\",\"March\",\"April\",\"May\",\"June\",\"Grune\",\"August\",\"Spune\",\"Sektober\",\"Ember\",\"December\"],monthNamesShort:[\"Ick\",\"Off\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Gru\",\"Aug\",\"Spu\",\"Sek\",\"Emb\",\"Dec\"],dayNames:[\"Sunday\",\"Octeday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Oct\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Oc\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:2,isRTL:!1}},leapYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),!1},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),13},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),400},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/8)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]},daysInWeek:function(){return 8},dayOfWeek:function(t,e,r){return(this._validate(t,e,r,n.local.invalidDate).day()+1)%8},weekDay:function(t,e,r){var n=this.dayOfWeek(t,e,r);return n>=2&&n<=6},extraInfo:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return{century:o[Math.floor((i.year()-1)/100)+1]||\"\"}},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year()+(i.year()<0?1:0),e=i.month(),(r=i.day())+(e>1?16:0)+(e>2?32*(e-2):0)+400*(t-1)+this.jdEpoch-1},fromJD:function(t){t=Math.floor(t+.5)-Math.floor(this.jdEpoch)-1;var e=Math.floor(t/400)+1;t-=400*(e-1),t+=t>15?16:0;var r=Math.floor(t/32)+1,n=t-32*(r-1)+1;return this.newDate(e<=0?e-1:e,r,n)}});var o={20:\"Fruitbat\",21:\"Anchovy\"};n.calendars.discworld=a},{\"../main\":621,\"object-assign\":499}],610:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new 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this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear),13},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(13===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return(t=i.year())<0&&t++,i.day()+30*(i.month()-1)+365*(t-1)+Math.floor(t/4)+this.jdEpoch-1},fromJD:function(t){var e=Math.floor(t)+.5-this.jdEpoch,r=Math.floor((e-Math.floor((e+366)/1461))/365)+1;r<=0&&r--,e=Math.floor(t)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(e/30)+1,i=e-30*(n-1)+1;return this.newDate(r,n,i)}}),n.calendars.ethiopian=a},{\"../main\":621,\"object-assign\":499}],611:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}function o(t,e){return t-e*Math.floor(t/e)}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Hebrew\",jdEpoch:347995.5,daysPerMonth:[30,29,30,29,30,29,30,29,30,29,30,29,29],hasYearZero:!1,minMonth:1,firstMonth:7,minDay:1,regionalOptions:{\"\":{name:\"Hebrew\",epochs:[\"BAM\",\"AM\"],monthNames:[\"Nisan\",\"Iyar\",\"Sivan\",\"Tammuz\",\"Av\",\"Elul\",\"Tishrei\",\"Cheshvan\",\"Kislev\",\"Tevet\",\"Shevat\",\"Adar\",\"Adar II\"],monthNamesShort:[\"Nis\",\"Iya\",\"Siv\",\"Tam\",\"Av\",\"Elu\",\"Tis\",\"Che\",\"Kis\",\"Tev\",\"She\",\"Ada\",\"Ad2\"],dayNames:[\"Yom Rishon\",\"Yom Sheni\",\"Yom Shlishi\",\"Yom Revi'i\",\"Yom Chamishi\",\"Yom Shishi\",\"Yom Shabbat\"],dayNamesShort:[\"Ris\",\"She\",\"Shl\",\"Rev\",\"Cha\",\"Shi\",\"Sha\"],dayNamesMin:[\"Ri\",\"She\",\"Shl\",\"Re\",\"Ch\",\"Shi\",\"Sha\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return this._leapYear(e.year())},_leapYear:function(t){return o(7*(t=t<0?t+1:t)+1,19)<7},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),this._leapYear(t.year?t.year():t)?13:12},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){return t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year(),this.toJD(-1===t?1:t+1,7,1)-this.toJD(t,7,1)},daysInMonth:function(t,e){return t.year&&(e=t.month(),t=t.year()),this._validate(t,e,this.minDay,n.local.invalidMonth),12===e&&this.leapYear(t)||8===e&&5===o(this.daysInYear(t),10)?30:9===e&&3===o(this.daysInYear(t),10)?29:this.daysPerMonth[e-1]},weekDay:function(t,e,r){return 6!==this.dayOfWeek(t,e,r)},extraInfo:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return{yearType:(this.leapYear(i)?\"embolismic\":\"common\")+\" \"+[\"deficient\",\"regular\",\"complete\"][this.daysInYear(i)%10-3]}},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t<=0?t+1:t,o=this.jdEpoch+this._delay1(a)+this._delay2(a)+r+1;if(e<7){for(var s=7;s<=this.monthsInYear(t);s++)o+=this.daysInMonth(t,s);for(s=1;s<e;s++)o+=this.daysInMonth(t,s)}else for(s=7;s<e;s++)o+=this.daysInMonth(t,s);return o},_delay1:function(t){var e=Math.floor((235*t-234)/19),r=12084+13753*e,n=29*e+Math.floor(r/25920);return o(3*(n+1),7)<3&&n++,n},_delay2:function(t){var e=this._delay1(t-1),r=this._delay1(t);return this._delay1(t+1)-r==356?2:r-e==382?1:0},fromJD:function(t){t=Math.floor(t)+.5;for(var e=Math.floor(98496*(t-this.jdEpoch)/35975351)-1;t>=this.toJD(-1===e?1:e+1,7,1);)e++;for(var r=t<this.toJD(e,1,1)?7:1;t>this.toJD(e,r,this.daysInMonth(e,r));)r++;var n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.hebrew=a},{\"../main\":621,\"object-assign\":499}],612:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Islamic\",jdEpoch:1948439.5,daysPerMonth:[30,29,30,29,30,29,30,29,30,29,30,29],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Islamic\",epochs:[\"BH\",\"AH\"],monthNames:[\"Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' al-thani\",\"Jumada al-awwal\",\"Jumada al-thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-ahad\",\"Yawm al-ithnayn\",\"Yawm ath-thulaathaa'\",\"Yawm al-arbi'aa'\",\"Yawm al-kham\\u012bs\",\"Yawm al-jum'a\",\"Yawm as-sabt\"],dayNamesShort:[\"Aha\",\"Ith\",\"Thu\",\"Arb\",\"Kha\",\"Jum\",\"Sab\"],dayNamesMin:[\"Ah\",\"It\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!1}},leapYear:function(t){return(11*this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year()+14)%30<11},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){return this.leapYear(t)?355:354},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year(),e=i.month(),t=t<=0?t+1:t,(r=i.day())+Math.ceil(29.5*(e-1))+354*(t-1)+Math.floor((3+11*t)/30)+this.jdEpoch-1},fromJD:function(t){t=Math.floor(t)+.5;var e=Math.floor((30*(t-this.jdEpoch)+10646)/10631);e=e<=0?e-1:e;var r=Math.min(12,Math.ceil((t-29-this.toJD(e,1,1))/29.5)+1),n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.islamic=a},{\"../main\":621,\"object-assign\":499}],613:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Julian\",jdEpoch:1721423.5,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Julian\",epochs:[\"BC\",\"AD\"],monthNames:[\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"],monthNamesShort:[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"],dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"mm/dd/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()<0?e.year()+1:e.year())%4==0},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(4-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year(),e=i.month(),r=i.day(),t<0&&t++,e<=2&&(t--,e+=12),Math.floor(365.25*(t+4716))+Math.floor(30.6001*(e+1))+r-1524.5},fromJD:function(t){var e=Math.floor(t+.5)+1524,r=Math.floor((e-122.1)/365.25),n=Math.floor(365.25*r),i=Math.floor((e-n)/30.6001),a=i-Math.floor(i<14?1:13),o=r-Math.floor(a>2?4716:4715),s=e-n-Math.floor(30.6001*i);return o<=0&&o--,this.newDate(o,a,s)}}),n.calendars.julian=a},{\"../main\":621,\"object-assign\":499}],614:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}function o(t,e){return t-e*Math.floor(t/e)}function s(t,e){return o(t-1,e)+1}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Mayan\",jdEpoch:584282.5,hasYearZero:!0,minMonth:0,firstMonth:0,minDay:0,regionalOptions:{\"\":{name:\"Mayan\",epochs:[\"\",\"\"],monthNames:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\"],monthNamesShort:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\"],dayNames:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],dayNamesShort:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],dayNamesMin:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],digits:null,dateFormat:\"YYYY.m.d\",firstDay:0,isRTL:!1,haabMonths:[\"Pop\",\"Uo\",\"Zip\",\"Zotz\",\"Tzec\",\"Xul\",\"Yaxkin\",\"Mol\",\"Chen\",\"Yax\",\"Zac\",\"Ceh\",\"Mac\",\"Kankin\",\"Muan\",\"Pax\",\"Kayab\",\"Cumku\",\"Uayeb\"],tzolkinMonths:[\"Imix\",\"Ik\",\"Akbal\",\"Kan\",\"Chicchan\",\"Cimi\",\"Manik\",\"Lamat\",\"Muluc\",\"Oc\",\"Chuen\",\"Eb\",\"Ben\",\"Ix\",\"Men\",\"Cib\",\"Caban\",\"Etznab\",\"Cauac\",\"Ahau\"]}},leapYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),!1},formatYear:function(t){t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year();var e=Math.floor(t/400);return t%=400,t+=t<0?400:0,e+\".\"+Math.floor(t/20)+\".\"+t%20},forYear:function(t){if((t=t.split(\".\")).length<3)throw\"Invalid Mayan year\";for(var e=0,r=0;r<t.length;r++){var n=parseInt(t[r],10);if(Math.abs(n)>19||r>0&&n<0)throw\"Invalid Mayan year\";e=20*e+n}return e},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),18},weekOfYear:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),0},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),360},daysInMonth:function(t,e){return this._validate(t,e,this.minDay,n.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate).day()},weekDay:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),!0},extraInfo:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate).toJD(),a=this._toHaab(i),o=this._toTzolkin(i);return{haabMonthName:this.local.haabMonths[a[0]-1],haabMonth:a[0],haabDay:a[1],tzolkinDayName:this.local.tzolkinMonths[o[0]-1],tzolkinDay:o[0],tzolkinTrecena:o[1]}},_toHaab:function(t){var e=o((t-=this.jdEpoch)+8+340,365);return[Math.floor(e/20)+1,o(e,20)]},_toTzolkin:function(t){return[s((t-=this.jdEpoch)+20,20),s(t+4,13)]},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return i.day()+20*i.month()+360*i.year()+this.jdEpoch},fromJD:function(t){t=Math.floor(t)+.5-this.jdEpoch;var e=Math.floor(t/360);t%=360,t+=t<0?360:0;var r=Math.floor(t/20),n=t%20;return this.newDate(e,r,n)}}),n.calendars.mayan=a},{\"../main\":621,\"object-assign\":499}],615:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar;var o=n.instance(\"gregorian\");i(a.prototype,{name:\"Nanakshahi\",jdEpoch:2257673.5,daysPerMonth:[31,31,31,31,31,30,30,30,30,30,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Nanakshahi\",epochs:[\"BN\",\"AN\"],monthNames:[\"Chet\",\"Vaisakh\",\"Jeth\",\"Harh\",\"Sawan\",\"Bhadon\",\"Assu\",\"Katak\",\"Maghar\",\"Poh\",\"Magh\",\"Phagun\"],monthNamesShort:[\"Che\",\"Vai\",\"Jet\",\"Har\",\"Saw\",\"Bha\",\"Ass\",\"Kat\",\"Mgr\",\"Poh\",\"Mgh\",\"Pha\"],dayNames:[\"Somvaar\",\"Mangalvar\",\"Budhvaar\",\"Veervaar\",\"Shukarvaar\",\"Sanicharvaar\",\"Etvaar\"],dayNamesShort:[\"Som\",\"Mangal\",\"Budh\",\"Veer\",\"Shukar\",\"Sanichar\",\"Et\"],dayNamesMin:[\"So\",\"Ma\",\"Bu\",\"Ve\",\"Sh\",\"Sa\",\"Et\"],digits:null,dateFormat:\"dd-mm-yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear);return o.leapYear(e.year()+(e.year()<1?1:0)+1469)},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(1-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidMonth);(t=i.year())<0&&t++;for(var a=i.day(),s=1;s<i.month();s++)a+=this.daysPerMonth[s-1];return a+o.toJD(t+1468,3,13)},fromJD:function(t){t=Math.floor(t+.5);for(var e=Math.floor((t-(this.jdEpoch-1))/366);t>=this.toJD(e+1,1,1);)e++;for(var r=t-Math.floor(this.toJD(e,1,1)+.5)+1,n=1;r>this.daysInMonth(e,n);)r-=this.daysInMonth(e,n),n++;return this.newDate(e,n,r)}}),n.calendars.nanakshahi=a},{\"../main\":621,\"object-assign\":499}],616:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Nepali\",jdEpoch:1700709.5,daysPerMonth:[31,31,32,32,31,30,30,29,30,29,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,daysPerYear:365,regionalOptions:{\"\":{name:\"Nepali\",epochs:[\"BBS\",\"ABS\"],monthNames:[\"Baisakh\",\"Jestha\",\"Ashadh\",\"Shrawan\",\"Bhadra\",\"Ashwin\",\"Kartik\",\"Mangsir\",\"Paush\",\"Mangh\",\"Falgun\",\"Chaitra\"],monthNamesShort:[\"Bai\",\"Je\",\"As\",\"Shra\",\"Bha\",\"Ash\",\"Kar\",\"Mang\",\"Pau\",\"Ma\",\"Fal\",\"Chai\"],dayNames:[\"Aaitabaar\",\"Sombaar\",\"Manglbaar\",\"Budhabaar\",\"Bihibaar\",\"Shukrabaar\",\"Shanibaar\"],dayNamesShort:[\"Aaita\",\"Som\",\"Mangl\",\"Budha\",\"Bihi\",\"Shukra\",\"Shani\"],dayNamesMin:[\"Aai\",\"So\",\"Man\",\"Bu\",\"Bi\",\"Shu\",\"Sha\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:1,isRTL:!1}},leapYear:function(t){return 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c=t-(s>9||9===s&&r>=this.NEPALI_CALENDAR_DATA[l][0]?56:57);for(9!==e&&(o=r,s--);9!==s;)s<=0&&(s=12,l--),o+=this.NEPALI_CALENDAR_DATA[l][s],s--;return 9===e?(o+=r-this.NEPALI_CALENDAR_DATA[l][0])<0&&(o+=a.daysInYear(c)):o+=this.NEPALI_CALENDAR_DATA[l][9]-this.NEPALI_CALENDAR_DATA[l][0],a.newDate(c,1,1).add(o,\"d\").toJD()},fromJD:function(t){var e=n.instance().fromJD(t),r=e.year(),i=e.dayOfYear(),a=r+56;this._createMissingCalendarData(a);for(var o=9,s=this.NEPALI_CALENDAR_DATA[a][0],l=this.NEPALI_CALENDAR_DATA[a][o]-s+1;i>l;)++o>12&&(o=1,a++),l+=this.NEPALI_CALENDAR_DATA[a][o];var c=this.NEPALI_CALENDAR_DATA[a][o]-(l-i);return this.newDate(a,o,c)},_createMissingCalendarData:function(t){var e=this.daysPerMonth.slice(0);e.unshift(17);for(var r=t-1;r<t+2;r++)\"undefined\"==typeof 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 682*((e.year()-(e.year()>0?474:473))%2820+474+38)%2816<682},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-(n.dayOfWeek()+1)%7,\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t-(t>=0?474:473),s=474+o(a,2820);return r+(e<=7?31*(e-1):30*(e-1)+6)+Math.floor((682*s-110)/2816)+365*(s-1)+1029983*Math.floor(a/2820)+this.jdEpoch-1},fromJD:function(t){var e=(t=Math.floor(t)+.5)-this.toJD(475,1,1),r=Math.floor(e/1029983),n=o(e,1029983),i=2820;if(1029982!==n){var a=Math.floor(n/366),s=o(n,366);i=Math.floor((2134*a+2816*s+2815)/1028522)+a+1}var l=i+2820*r+474;l=l<=0?l-1:l;var 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i=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(i.year());return a.weekOfYear(t,i.month(),i.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=this._t2gYear(i.year());return a.toJD(t,i.month(),i.day())},fromJD:function(t){var e=a.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)},_g2tYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)}}),n.calendars.taiwan=o},{\"../main\":621,\"object-assign\":499}],619:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\"),a=n.instance();function 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(e.year());return a.leapYear(t)},weekOfYear:function(t,e,r){var i=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(i.year());return a.weekOfYear(t,i.month(),i.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=this._t2gYear(i.year());return a.toJD(t,i.month(),i.day())},fromJD:function(t){var e=a.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)},_g2tYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)}}),n.calendars.thai=o},{\"../main\":621,\"object-assign\":499}],620:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"UmmAlQura\",hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Umm al-Qura\",epochs:[\"BH\",\"AH\"],monthNames:[\"Al-Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' Al-Thani\",\"Jumada Al-Awwal\",\"Jumada Al-Thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-Ahad\",\"Yawm al-Ithnain\",\"Yawm al-Thal\\u0101th\\u0101\\u2019\",\"Yawm al-Arba\\u2018\\u0101\\u2019\",\"Yawm al-Kham\\u012bs\",\"Yawm al-Jum\\u2018a\",\"Yawm al-Sabt\"],dayNamesMin:[\"Ah\",\"Ith\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!0}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 355===this.daysInYear(e.year())},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){for(var e=0,r=1;r<=12;r++)e+=this.daysInMonth(t,r);return e},daysInMonth:function(t,e){for(var r=this._validate(t,e,this.minDay,n.local.invalidMonth).toJD()-24e5+.5,i=0,a=0;a<o.length;a++){if(o[a]>r)return o[i]-o[i-1];i++}return 30},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate),a=12*(i.year()-1)+i.month()-15292;return i.day()+o[a-1]-1+24e5-.5},fromJD:function(t){for(var e=t-24e5+.5,r=0,n=0;n<o.length&&!(o[n]>e);n++)r++;var i=r+15292,a=Math.floor((i-1)/12),s=a+1,l=i-12*a,c=e-o[r-1]+1;return this.newDate(s,l,c)},isValid:function(t,e,r){var i=n.baseCalendar.prototype.isValid.apply(this,arguments);return i&&(i=(t=null!=t.year?t.year:t)>=1276&&t<=1500),i},_validate:function(t,e,r,i){var a=n.baseCalendar.prototype._validate.apply(this,arguments);if(a.year<1276||a.year>1500)throw i.replace(/\\{0\\}/,this.local.name);return a}}),n.calendars.ummalqura=a;var 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n=t(\"object-assign\");function i(){this.regionalOptions=[],this.regionalOptions[\"\"]={invalidCalendar:\"Calendar {0} not found\",invalidDate:\"Invalid {0} date\",invalidMonth:\"Invalid {0} month\",invalidYear:\"Invalid {0} year\",differentCalendars:\"Cannot mix {0} and {1} dates\"},this.local=this.regionalOptions[\"\"],this.calendars={},this._localCals={}}function a(t,e,r,n){if(this._calendar=t,this._year=e,this._month=r,this._day=n,0===this._calendar._validateLevel&&!this._calendar.isValid(this._year,this._month,this._day))throw(c.local.invalidDate||c.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name)}function o(t,e){return\"000000\".substring(0,e-(t=\"\"+t).length)+t}function s(){this.shortYearCutoff=\"+10\"}function l(t){this.local=this.regionalOptions[t]||this.regionalOptions[\"\"]}n(i.prototype,{instance:function(t,e){t=(t||\"gregorian\").toLowerCase(),e=e||\"\";var r=this._localCals[t+\"-\"+e];if(!r&&this.calendars[t]&&(r=new this.calendars[t](e),this._localCals[t+\"-\"+e]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[\"\"].invalidCalendar).replace(/\\{0\\}/,t);return r},newDate:function(t,e,r,n,i){return(n=(null!=t&&t.year?t.calendar():\"string\"==typeof n?this.instance(n,i):n)||this.instance()).newDate(t,e,r)},substituteDigits:function(t){return function(e){return(e+\"\").replace(/[0-9]/g,(function(e){return t[e]}))}},substituteChineseDigits:function(t,e){return function(r){for(var n=\"\",i=0;r>0;){var a=r%10;n=(0===a?\"\":t[a]+e[i])+n,i++,r=Math.floor(r/10)}return 0===n.indexOf(t[1]+e[1])&&(n=n.substr(1)),n||t[0]}}}),n(a.prototype,{newDate:function(t,e,r){return this._calendar.newDate(null==t?this:t,e,r)},year:function(t){return 0===arguments.length?this._year:this.set(t,\"y\")},month:function(t){return 0===arguments.length?this._month:this.set(t,\"m\")},day:function(t){return 0===arguments.length?this._day:this.set(t,\"d\")},date:function(t,e,r){if(!this._calendar.isValid(t,e,r))throw(c.local.invalidDate||c.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name);return this._year=t,this._month=e,this._day=r,this},leapYear:function(){return this._calendar.leapYear(this)},epoch:function(){return this._calendar.epoch(this)},formatYear:function(){return this._calendar.formatYear(this)},monthOfYear:function(){return this._calendar.monthOfYear(this)},weekOfYear:function(){return this._calendar.weekOfYear(this)},daysInYear:function(){return this._calendar.daysInYear(this)},dayOfYear:function(){return this._calendar.dayOfYear(this)},daysInMonth:function(){return this._calendar.daysInMonth(this)},dayOfWeek:function(){return this._calendar.dayOfWeek(this)},weekDay:function(){return this._calendar.weekDay(this)},extraInfo:function(){return this._calendar.extraInfo(this)},add:function(t,e){return this._calendar.add(this,t,e)},set:function(t,e){return this._calendar.set(this,t,e)},compareTo:function(t){if(this._calendar.name!==t._calendar.name)throw(c.local.differentCalendars||c.regionalOptions[\"\"].differentCalendars).replace(/\\{0\\}/,this._calendar.local.name).replace(/\\{1\\}/,t._calendar.local.name);var e=this._year!==t._year?this._year-t._year:this._month!==t._month?this.monthOfYear()-t.monthOfYear():this._day-t._day;return 0===e?0:e<0?-1:1},calendar:function(){return this._calendar},toJD:function(){return this._calendar.toJD(this)},fromJD:function(t){return this._calendar.fromJD(t)},toJSDate:function(){return this._calendar.toJSDate(this)},fromJSDate:function(t){return this._calendar.fromJSDate(t)},toString:function(){return(this.year()<0?\"-\":\"\")+o(Math.abs(this.year()),4)+\"-\"+o(this.month(),2)+\"-\"+o(this.day(),2)}}),n(s.prototype,{_validateLevel:0,newDate:function(t,e,r){return null==t?this.today():(t.year&&(this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),r=t.day(),e=t.month(),t=t.year()),new a(this,t,e,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear).year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return(e.year()<0?\"-\":\"\")+o(Math.abs(e.year()),4)},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear),12},monthOfYear:function(t,e){var r=this._validate(t,e,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth);return(r.month()+this.monthsInYear(r)-this.firstMonth)%this.monthsInYear(r)+this.minMonth},fromMonthOfYear:function(t,e){var r=(e+this.firstMonth-2*this.minMonth)%this.monthsInYear(t)+this.minMonth;return this._validate(t,r,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth),r},daysInYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return this.leapYear(e)?366:365},dayOfYear:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return n.toJD()-this.newDate(n.year(),this.fromMonthOfYear(n.year(),this.minMonth),this.minDay).toJD()+1},daysInWeek:function(){return 7},dayOfWeek:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(t,e,r){return this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),{}},add:function(t,e,r){return this._validate(t,this.minMonth,this.minDay,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),this._correctAdd(t,this._add(t,e,r),e,r)},_add:function(t,e,r){if(this._validateLevel++,\"d\"===r||\"w\"===r){var n=t.toJD()+e*(\"w\"===r?this.daysInWeek():1),i=t.calendar().fromJD(n);return this._validateLevel--,[i.year(),i.month(),i.day()]}try{var a=t.year()+(\"y\"===r?e:0),o=t.monthOfYear()+(\"m\"===r?e:0);i=t.day();\"y\"===r?(t.month()!==this.fromMonthOfYear(a,o)&&(o=this.newDate(a,t.month(),this.minDay).monthOfYear()),o=Math.min(o,this.monthsInYear(a)),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o)))):\"m\"===r&&(!function(t){for(;o<t.minMonth;)a--,o+=t.monthsInYear(a);for(var e=t.monthsInYear(a);o>e-1+t.minMonth;)a++,o-=e,e=t.monthsInYear(a)}(this),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o))));var s=[a,this.fromMonthOfYear(a,o),i];return this._validateLevel--,s}catch(t){throw 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r,s,l=o(t,e),c=l.on,u=l.off.concat(l.explicitOff),f={},h=t._fullLayout.annotations;if(!c.length&&!u.length)return;for(r=0;r<c.length;r++)(s=a(t.layout,\"annotations\",h[c[r]])).modifyItem(\"visible\",!0),n.extendFlat(f,s.getUpdateObj());for(r=0;r<u.length;r++)(s=a(t.layout,\"annotations\",h[u[r]])).modifyItem(\"visible\",!1),n.extendFlat(f,s.getUpdateObj());return i.call(\"update\",t,{},f)}}},{\"../../lib\":778,\"../../plot_api/plot_template\":817,\"../../registry\":911}],629:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../color\");e.exports=function(t,e,r,a){a(\"opacity\");var o=a(\"bgcolor\"),s=a(\"bordercolor\"),l=i.opacity(s);a(\"borderpad\");var c=a(\"borderwidth\"),u=a(\"showarrow\");if(a(\"text\",u?\" \":r._dfltTitle.annotation),a(\"textangle\"),n.coerceFont(a,\"font\",r.font),a(\"width\"),a(\"align\"),a(\"height\")&&a(\"valign\"),u){var f,h,p=a(\"arrowside\");-1!==p.indexOf(\"end\")&&(f=a(\"arrowhead\"),h=a(\"arrowsize\")),-1!==p.indexOf(\"start\")&&(a(\"startarrowhead\",f),a(\"startarrowsize\",h)),a(\"arrowcolor\",l?e.bordercolor:i.defaultLine),a(\"arrowwidth\",2*(l&&c||1)),a(\"standoff\"),a(\"startstandoff\")}var d=a(\"hovertext\"),g=r.hoverlabel||{};if(d){var m=a(\"hoverlabel.bgcolor\",g.bgcolor||(i.opacity(o)?i.rgb(o):i.defaultLine)),v=a(\"hoverlabel.bordercolor\",g.bordercolor||i.contrast(m));n.coerceFont(a,\"hoverlabel.font\",{family:g.font.family,size:g.font.size,color:g.font.color||v})}a(\"captureevents\",!!d)}},{\"../../lib\":778,\"../color\":643}],630:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib/to_log_range\");e.exports=function(t,e,r,a){e=e||{};var o=\"log\"===r&&\"linear\"===e.type,s=\"linear\"===r&&\"log\"===e.type;if(o||s)for(var l,c,u=t._fullLayout.annotations,f=e._id.charAt(0),h=0;h<u.length;h++)l=u[h],c=\"annotations[\"+h+\"].\",l[f+\"ref\"]===e._id&&p(f),l[\"a\"+f+\"ref\"]===e._id&&p(\"a\"+f);function p(t){var r=l[t],s=null;s=o?i(r,e.range):Math.pow(10,r),n(s)||(s=null),a(c+t,s)}}},{\"../../lib/to_log_range\":805,\"fast-isnumeric\":241}],631:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../plots/cartesian/axes\"),a=t(\"../../plots/array_container_defaults\"),o=t(\"./common_defaults\"),s=t(\"./attributes\");function l(t,e,r){function a(r,i){return n.coerce(t,e,s,r,i)}var l=a(\"visible\"),c=a(\"clicktoshow\");if(l||c){o(t,e,r,a);for(var u=e.showarrow,f=[\"x\",\"y\"],h=[-10,-30],p={_fullLayout:r},d=0;d<2;d++){var g=f[d],m=i.coerceRef(t,e,p,g,\"\",\"paper\");if(\"paper\"!==m)i.getFromId(p,m)._annIndices.push(e._index);if(i.coercePosition(e,p,a,m,g,.5),u){var v=\"a\"+g,y=i.coerceRef(t,e,p,v,\"pixel\",[\"pixel\",\"paper\"]);\"pixel\"!==y&&y!==m&&(y=e[v]=\"pixel\");var x=\"pixel\"===y?h[d]:.4;i.coercePosition(e,p,a,y,v,x)}a(g+\"anchor\"),a(g+\"shift\")}if(n.noneOrAll(t,e,[\"x\",\"y\"]),u&&n.noneOrAll(t,e,[\"ax\",\"ay\"]),c){var b=a(\"xclick\"),_=a(\"yclick\");e._xclick=void 0===b?e.x:i.cleanPosition(b,p,e.xref),e._yclick=void 0===_?e.y:i.cleanPosition(_,p,e.yref)}}}e.exports=function(t,e){a(t,e,{name:\"annotations\",handleItemDefaults:l})}},{\"../../lib\":778,\"../../plots/array_container_defaults\":823,\"../../plots/cartesian/axes\":828,\"./attributes\":626,\"./common_defaults\":629}],632:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../registry\"),a=t(\"../../plots/plots\"),o=t(\"../../lib\"),s=o.strTranslate,l=t(\"../../plots/cartesian/axes\"),c=t(\"../color\"),u=t(\"../drawing\"),f=t(\"../fx\"),h=t(\"../../lib/svg_text_utils\"),p=t(\"../../lib/setcursor\"),d=t(\"../dragelement\"),g=t(\"../../plot_api/plot_template\").arrayEditor,m=t(\"./draw_arrow_head\");function v(t,e){var r=t._fullLayout.annotations[e]||{},n=l.getFromId(t,r.xref),i=l.getFromId(t,r.yref);n&&n.setScale(),i&&i.setScale(),x(t,r,e,!1,n,i)}function y(t,e,r,n,i){var a=i[r],o=i[r+\"ref\"],s=-1!==r.indexOf(\"y\"),c=\"domain\"===l.getRefType(o),u=s?n.h:n.w;return t?c?a+(s?-e:e)/t._length:t.p2r(t.r2p(a)+e):a+(s?-e:e)/u}function x(t,e,r,a,v,x){var b,_,w=t._fullLayout,T=t._fullLayout._size,k=t._context.edits;a?(b=\"annotation-\"+a,_=a+\".annotations\"):(b=\"annotation\",_=\"annotations\");var M=g(t.layout,_,e),A=M.modifyBase,S=M.modifyItem,E=M.getUpdateObj;w._infolayer.selectAll(\".\"+b+'[data-index=\"'+r+'\"]').remove();var C=\"clip\"+w._uid+\"_ann\"+r;if(e._input&&!1!==e.visible){var L={x:{},y:{}},I=+e.textangle||0,P=w._infolayer.append(\"g\").classed(b,!0).attr(\"data-index\",String(r)).style(\"opacity\",e.opacity),z=P.append(\"g\").classed(\"annotation-text-g\",!0),O=k[e.showarrow?\"annotationTail\":\"annotationPosition\"],D=e.captureevents||k.annotationText||O,R=z.append(\"g\").style(\"pointer-events\",D?\"all\":null).call(p,\"pointer\").on(\"click\",(function(){t._dragging=!1,t.emit(\"plotly_clickannotation\",Y(n.event))}));e.hovertext&&R.on(\"mouseover\",(function(){var r=e.hoverlabel,n=r.font,i=this.getBoundingClientRect(),a=t.getBoundingClientRect();f.loneHover({x0:i.left-a.left,x1:i.right-a.left,y:(i.top+i.bottom)/2-a.top,text:e.hovertext,color:r.bgcolor,borderColor:r.bordercolor,fontFamily:n.family,fontSize:n.size,fontColor:n.color},{container:w._hoverlayer.node(),outerContainer:w._paper.node(),gd:t})})).on(\"mouseout\",(function(){f.loneUnhover(w._hoverlayer.node())}));var F=e.borderwidth,B=e.borderpad,N=F+B,j=R.append(\"rect\").attr(\"class\",\"bg\").style(\"stroke-width\",F+\"px\").call(c.stroke,e.bordercolor).call(c.fill,e.bgcolor),U=e.width||e.height,V=w._topclips.selectAll(\"#\"+C).data(U?[0]:[]);V.enter().append(\"clipPath\").classed(\"annclip\",!0).attr(\"id\",C).append(\"rect\"),V.exit().remove();var q=e.font,H=w._meta?o.templateString(e.text,w._meta):e.text,G=R.append(\"text\").classed(\"annotation-text\",!0).text(H);k.annotationText?G.call(h.makeEditable,{delegate:R,gd:t}).call(W).on(\"edit\",(function(r){e.text=r,this.call(W),S(\"text\",r),v&&v.autorange&&A(v._name+\".autorange\",!0),x&&x.autorange&&A(x._name+\".autorange\",!0),i.call(\"_guiRelayout\",t,E())})):G.call(W)}else n.selectAll(\"#\"+C).remove();function Y(t){var n={index:r,annotation:e._input,fullAnnotation:e,event:t};return a&&(n.subplotId=a),n}function W(r){return r.call(u.font,q).attr({\"text-anchor\":{left:\"start\",right:\"end\"}[e.align]||\"middle\"}),h.convertToTspans(r,t,X),r}function X(){var r=G.selectAll(\"a\");1===r.size()&&r.text()===G.text()&&R.insert(\"a\",\":first-child\").attr({\"xlink:xlink:href\":r.attr(\"xlink:href\"),\"xlink:xlink:show\":r.attr(\"xlink:show\")}).style({cursor:\"pointer\"}).node().appendChild(j.node());var n=R.select(\".annotation-text-math-group\"),f=!n.empty(),g=u.bBox((f?n:G).node()),b=g.width,_=g.height,M=e.width||b,D=e.height||_,B=Math.round(M+2*N),q=Math.round(D+2*N);function H(t,e){return\"auto\"===e&&(e=t<1/3?\"left\":t>2/3?\"right\":\"center\"),{center:0,middle:0,left:.5,bottom:-.5,right:-.5,top:.5}[e]}for(var W=!1,X=[\"x\",\"y\"],Z=0;Z<X.length;Z++){var J,K,Q,$,tt,et=X[Z],rt=e[et+\"ref\"]||et,nt=e[\"a\"+et+\"ref\"],it={x:v,y:x}[et],at=(I+(\"x\"===et?0:-90))*Math.PI/180,ot=B*Math.cos(at),st=q*Math.sin(at),lt=Math.abs(ot)+Math.abs(st),ct=e[et+\"anchor\"],ut=e[et+\"shift\"]*(\"x\"===et?1:-1),ft=L[et],ht=l.getRefType(rt);if(it&&\"domain\"!==ht){var pt=it.r2fraction(e[et]);(pt<0||pt>1)&&(nt===rt?((pt=it.r2fraction(e[\"a\"+et]))<0||pt>1)&&(W=!0):W=!0),J=it._offset+it.r2p(e[et]),$=.5}else{var dt=\"domain\"===ht;\"x\"===et?(Q=e[et],J=dt?it._offset+it._length*Q:J=T.l+T.w*Q):(Q=1-e[et],J=dt?it._offset+it._length*Q:J=T.t+T.h*Q),$=e.showarrow?.5:Q}if(e.showarrow){ft.head=J;var gt=e[\"a\"+et];if(tt=ot*H(.5,e.xanchor)-st*H(.5,e.yanchor),nt===rt){var mt=l.getRefType(nt);\"domain\"===mt?(\"y\"===et&&(gt=1-gt),ft.tail=it._offset+it._length*gt):\"paper\"===mt?\"y\"===et?(gt=1-gt,ft.tail=T.t+T.h*gt):ft.tail=T.l+T.w*gt:ft.tail=it._offset+it.r2p(gt),K=tt}else ft.tail=J+gt,K=tt+gt;ft.text=ft.tail+tt;var vt=w[\"x\"===et?\"width\":\"height\"];if(\"paper\"===rt&&(ft.head=o.constrain(ft.head,1,vt-1)),\"pixel\"===nt){var yt=-Math.max(ft.tail-3,ft.text),xt=Math.min(ft.tail+3,ft.text)-vt;yt>0?(ft.tail+=yt,ft.text+=yt):xt>0&&(ft.tail-=xt,ft.text-=xt)}ft.tail+=ut,ft.head+=ut}else K=tt=lt*H($,ct),ft.text=J+tt;ft.text+=ut,tt+=ut,K+=ut,e[\"_\"+et+\"padplus\"]=lt/2+K,e[\"_\"+et+\"padminus\"]=lt/2-K,e[\"_\"+et+\"size\"]=lt,e[\"_\"+et+\"shift\"]=tt}if(W)R.remove();else{var bt=0,_t=0;if(\"left\"!==e.align&&(bt=(M-b)*(\"center\"===e.align?.5:1)),\"top\"!==e.valign&&(_t=(D-_)*(\"middle\"===e.valign?.5:1)),f)n.select(\"svg\").attr({x:N+bt-1,y:N+_t}).call(u.setClipUrl,U?C:null,t);else{var wt=N+_t-g.top,Tt=N+bt-g.left;G.call(h.positionText,Tt,wt).call(u.setClipUrl,U?C:null,t)}V.select(\"rect\").call(u.setRect,N,N,M,D),j.call(u.setRect,F/2,F/2,B-F,q-F),R.call(u.setTranslate,Math.round(L.x.text-B/2),Math.round(L.y.text-q/2)),z.attr({transform:\"rotate(\"+I+\",\"+L.x.text+\",\"+L.y.text+\")\"});var kt,Mt=function(r,n){P.selectAll(\".annotation-arrow-g\").remove();var l=L.x.head,f=L.y.head,h=L.x.tail+r,p=L.y.tail+n,g=L.x.text+r,b=L.y.text+n,_=o.rotationXYMatrix(I,g,b),w=o.apply2DTransform(_),M=o.apply2DTransform2(_),C=+j.attr(\"width\"),O=+j.attr(\"height\"),D=g-.5*C,F=D+C,B=b-.5*O,N=B+O,U=[[D,B,D,N],[D,N,F,N],[F,N,F,B],[F,B,D,B]].map(M);if(!U.reduce((function(t,e){return t^!!o.segmentsIntersect(l,f,l+1e6,f+1e6,e[0],e[1],e[2],e[3])}),!1)){U.forEach((function(t){var e=o.segmentsIntersect(h,p,l,f,t[0],t[1],t[2],t[3]);e&&(h=e.x,p=e.y)}));var V=e.arrowwidth,q=e.arrowcolor,H=e.arrowside,G=P.append(\"g\").style({opacity:c.opacity(q)}).classed(\"annotation-arrow-g\",!0),Y=G.append(\"path\").attr(\"d\",\"M\"+h+\",\"+p+\"L\"+l+\",\"+f).style(\"stroke-width\",V+\"px\").call(c.stroke,c.rgb(q));if(m(Y,H,e),k.annotationPosition&&Y.node().parentNode&&!a){var W=l,X=f;if(e.standoff){var Z=Math.sqrt(Math.pow(l-h,2)+Math.pow(f-p,2));W+=e.standoff*(h-l)/Z,X+=e.standoff*(p-f)/Z}var 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n=t(\"../annotations/attributes\"),i=t(\"../../plot_api/edit_types\").overrideAll,a=t(\"../../plot_api/plot_template\").templatedArray;e.exports=i(a(\"annotation\",{visible:n.visible,x:{valType:\"any\"},y:{valType:\"any\"},z:{valType:\"any\"},ax:{valType:\"number\"},ay:{valType:\"number\"},xanchor:n.xanchor,xshift:n.xshift,yanchor:n.yanchor,yshift:n.yshift,text:n.text,textangle:n.textangle,font:n.font,width:n.width,height:n.height,opacity:n.opacity,align:n.align,valign:n.valign,bgcolor:n.bgcolor,bordercolor:n.bordercolor,borderpad:n.borderpad,borderwidth:n.borderwidth,showarrow:n.showarrow,arrowcolor:n.arrowcolor,arrowhead:n.arrowhead,startarrowhead:n.startarrowhead,arrowside:n.arrowside,arrowsize:n.arrowsize,startarrowsize:n.startarrowsize,arrowwidth:n.arrowwidth,standoff:n.standoff,startstandoff:n.startstandoff,hovertext:n.hovertext,hoverlabel:n.hoverlabel,captureevents:n.captureevents}),\"calc\",\"from-root\")},{\"../../plot_api/edit_types\":810,\"../../plot_api/plot_template\":817,\"../annotations/attributes\":626}],636:[function(t,e,r){\"use 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n.coerce(t,e,s,r,i)}function c(t){var n=t+\"axis\",a={_fullLayout:{}};return a._fullLayout[n]=r[n],i.coercePosition(e,a,l,t,t,.5)}l(\"visible\")&&(o(t,e,a.fullLayout,l),c(\"x\"),c(\"y\"),c(\"z\"),n.noneOrAll(t,e,[\"x\",\"y\",\"z\"]),e.xref=\"x\",e.yref=\"y\",e.zref=\"z\",l(\"xanchor\"),l(\"yanchor\"),l(\"xshift\"),l(\"yshift\"),e.showarrow&&(e.axref=\"pixel\",e.ayref=\"pixel\",l(\"ax\",-10),l(\"ay\",-30),n.noneOrAll(t,e,[\"ax\",\"ay\"])))}e.exports=function(t,e,r){a(t,e,{name:\"annotations\",handleItemDefaults:l,fullLayout:r.fullLayout})}},{\"../../lib\":778,\"../../plots/array_container_defaults\":823,\"../../plots/cartesian/axes\":828,\"../annotations/common_defaults\":629,\"./attributes\":635}],638:[function(t,e,r){\"use strict\";var n=t(\"../annotations/draw\").drawRaw,i=t(\"../../plots/gl3d/project\"),a=[\"x\",\"y\",\"z\"];e.exports=function(t){for(var e=t.fullSceneLayout,r=t.dataScale,o=e.annotations,s=0;s<o.length;s++){for(var l=o[s],c=!1,u=0;u<3;u++){var 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If `target` is a string (eg *x*) we use the\",\"corresponding trace attribute (eg `xcalendar`) if it exists,\",\"even if `targetcalendar` is provided.\"].join(\" \"))}}},layoutAttributes:l,handleDefaults:c,handleTraceDefaults:function(t,e,r,n){for(var i=0;i<r.length;i++)c(t,e,r[i]+\"calendar\",n.calendar)},CANONICAL_SUNDAY:{chinese:\"2000-01-02\",coptic:\"2000-01-03\",discworld:\"2000-01-03\",ethiopian:\"2000-01-05\",hebrew:\"5000-01-01\",islamic:\"1000-01-02\",julian:\"2000-01-03\",mayan:\"5000-01-01\",nanakshahi:\"1000-01-05\",nepali:\"2000-01-05\",persian:\"1000-01-01\",jalali:\"1000-01-01\",taiwan:\"1000-01-04\",thai:\"2000-01-04\",ummalqura:\"1400-01-06\"},CANONICAL_TICK:{chinese:\"2000-01-01\",coptic:\"2000-01-01\",discworld:\"2000-01-01\",ethiopian:\"2000-01-01\",hebrew:\"5000-01-01\",islamic:\"1000-01-01\",julian:\"2000-01-01\",mayan:\"5000-01-01\",nanakshahi:\"1000-01-01\",nepali:\"2000-01-01\",persian:\"1000-01-01\",jalali:\"1000-01-01\",taiwan:\"1000-01-01\",thai:\"2000-01-01\",ummalqura:\"1400-01-01\"},DFLTRANGE:{chinese:[\"2000-01-01\",\"2001-01-01\"],coptic:[\"1700-01-01\",\"1701-01-01\"],discworld:[\"1800-01-01\",\"1801-01-01\"],ethiopian:[\"2000-01-01\",\"2001-01-01\"],hebrew:[\"5700-01-01\",\"5701-01-01\"],islamic:[\"1400-01-01\",\"1401-01-01\"],julian:[\"2000-01-01\",\"2001-01-01\"],mayan:[\"5200-01-01\",\"5201-01-01\"],nanakshahi:[\"0500-01-01\",\"0501-01-01\"],nepali:[\"2000-01-01\",\"2001-01-01\"],persian:[\"1400-01-01\",\"1401-01-01\"],jalali:[\"1400-01-01\",\"1401-01-01\"],taiwan:[\"0100-01-01\",\"0101-01-01\"],thai:[\"2500-01-01\",\"2501-01-01\"],ummalqura:[\"1400-01-01\",\"1401-01-01\"]},getCal:h,worldCalFmt:function(t,e,r){for(var 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T={y:e.y,b:u.height*g[w],t:u.height*d[w]};\"fraction\"===e.lenmode?(T.l=0,T.xl=e.x-e.len*d[b],T.r=0,T.xr=e.x+e.len*g[b]):(T.x=e.x,T.l=u.outerLength*d[b],T.r=u.outerLength*g[b]),i.autoMargin(t,m(e),T)}function x(t,e,r){if(e.currentvalue.visible){var n,i,a=e._dims;switch(e.currentvalue.xanchor){case\"right\":n=a.inputAreaLength-f.currentValueInset-a.currentValueMaxWidth,i=\"left\";break;case\"center\":n=.5*a.inputAreaLength,i=\"middle\";break;default:n=f.currentValueInset,i=\"left\"}var l=s.ensureSingle(t,\"text\",f.labelClass,(function(t){t.attr({\"text-anchor\":i,\"data-notex\":1})})),u=e.currentvalue.prefix?e.currentvalue.prefix:\"\";if(\"string\"==typeof r)u+=r;else{var h=e.steps[e.active].label,d=e._gd._fullLayout._meta;d&&(h=s.templateString(h,d)),u+=h}e.currentvalue.suffix&&(u+=e.currentvalue.suffix),l.call(o.font,e.currentvalue.font).text(u).call(c.convertToTspans,e._gd);var g=c.lineCount(l),m=(a.currentValueMaxLines+1-g)*e.currentvalue.font.size*p;return 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r=t[e[n]],s=(r._extremes||{})[o];if(!0===r.visible&&s){for(i=0;i<s.min.length;i++)a=s.min[i],d(u,a.val,a.pad,{extrapad:a.extrapad});for(i=0;i<s.max.length;i++)a=s.max[i],g(f,a.val,a.pad,{extrapad:a.extrapad})}}}if(h(s,e._traceIndices),h(c.annotations||[],e._annIndices||[]),h(c.shapes||[],e._shapeIndices||[]),e._matchGroup&&!r)for(var m in e._matchGroup)if(m!==e._id){var v=l(t,m),y=p(t,v,!0),x=e._length/v._length;for(i=0;i<y.min.length;i++)a=y.min[i],d(u,a.val,a.pad*x,{extrapad:a.extrapad});for(i=0;i<y.max.length;i++)a=y.max[i],g(f,a.val,a.pad*x,{extrapad:a.extrapad})}return{min:u,max:f}}function d(t,e,r,n){m(t,e,r,n,y)}function g(t,e,r,n){m(t,e,r,n,x)}function m(t,e,r,n,i){for(var a=n.tozero,o=n.extrapad,s=!0,l=0;l<t.length&&s;l++){var c=t[l];if(i(c.val,e)&&c.pad>=r&&(c.extrapad||!o)){s=!1;break}i(e,c.val)&&c.pad<=r&&(o||!c.extrapad)&&(t.splice(l,1),l--)}if(s){var u=a&&0===e;t.push({val:e,pad:u?0:r,extrapad:!u&&o})}}function v(t){return n(t)&&Math.abs(t)<a}function y(t,e){return 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n,a=t.nticks;a||(\"category\"===t.type||\"multicategory\"===t.type?(n=t.tickfont?1.2*(t.tickfont.size||12):15,a=t._length/n):(n=\"y\"===t._id.charAt(0)?40:80,a=s.constrain(t._length/n,4,9)+1),\"radialaxis\"===t._name&&(a*=2)),\"array\"===t.tickmode&&(a*=100),t._roughDTick=Math.abs(r[1]-r[0])/a,B.autoTicks(t,t._roughDTick),t._minDtick>0&&t.dtick<2*t._minDtick&&(t.dtick=t._minDtick,t.tick0=t.l2r(t._forceTick0))}\"period\"===t.ticklabelmode&&function(t){var e;function r(){return!(i(t.dtick)||\"M\"!==t.dtick.charAt(0))}var n=r(),a=B.getTickFormat(t);if(a){var 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c=\"category\"===t.type?t.d2l_noadd:t.d2l;\"log\"===t.type&&\"L\"!==String(t.dtick).charAt(0)&&(t.dtick=\"L\"+Math.pow(10,Math.floor(Math.min(t.range[0],t.range[1]))-1));for(var u=0;u<e.length;u++){var f=c(e[u]);f>a&&f<o&&(void 0===r[u]?n[l]=B.tickText(t,f):n[l]=it(t,f,String(r[u])),l++)}l<e.length&&n.splice(l,e.length-l);t.rangebreaks&&(n=n.filter((function(e){return t.maskBreaks(e.x)!==P})));return n}(t);var n=H(r),a=n[0],o=n[1],l=r[1]<r[0],c=Math.min(r[0],r[1]),u=Math.max(r[0],r[1]),f=\"log\"===t.type&&!(i(t.dtick)||\"L\"===t.dtick.charAt(0)),h=\"period\"===t.ticklabelmode;if(t._tmin=B.tickFirst(t,e),t._tmin<a!==l)return[];\"category\"!==t.type&&\"multicategory\"!==t.type||(o=l?Math.max(-.5,o):Math.min(t._categories.length-.5,o));var p=t._tmin;t.rangebreaks&&t._tick0Init!==t.tick0&&(p=wt(p,t),l||(p=B.tickIncrement(p,t.dtick,!l,t.calendar))),h&&(p=B.tickIncrement(p,t.dtick,!l,t.calendar));for(var d,g=Math.max(1e3,t._length||0),C=[],L=null;l?p>=o:p<=o;p=B.tickIncrement(p,t.dtick,l,t.calendar)){if(t.rangebreaks&&!l){if(p<a)continue;if(t.maskBreaks(p)===P&&wt(p,t)>=u)break}if(C.length>g||p===L)break;L=p;var I=!1;f&&p!==(0|p)&&(I=!0),C.push({minor:I,value:p})}if(h&&function(t,e,r){for(var n=0;n<t.length;n++){var i=t[n].value,a=n,o=n+1;n<t.length-1?(a=n,o=n+1):n>0?(a=n-1,o=n):(a=n,o=n);var s,l=t[a].value,c=t[o].value,u=Math.abs(c-l),f=r||u,h=0;f>=y?h=u>=y&&u<=m?u:v:r===b&&f>=_?h=u>=_&&u<=x?u:b:f>=k?h=u>=k&&u<=w?u:T:r===M&&f>=M?h=M:f>=A?h=A:r===S&&f>=S?h=S:r===E&&f>=E&&(h=E),h>=u&&(h=u,s=!0);var p=i+h;if(e.rangebreaks&&h>0){for(var d=0,g=0;g<84;g++){var C=(g+.5)/84;e.maskBreaks(i*(1-C)+C*p)!==P&&d++}(h*=d/84)||(t[n].drop=!0),s&&u>M&&(h=u)}(h>0||0===n)&&(t[n].periodX=i+h/2)}}(C,t,t._definedDelta),t.rangebreaks){var z=\"y\"===t._id.charAt(0),O=1;\"auto\"===t.tickmode&&(O=t.tickfont?t.tickfont.size:12);var 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w=e._anchorAxis;w&&w.autorange&&-1!==(e.ticklabelposition||\"\").indexOf(\"inside\")&&!V(a,e._id)&&(a._insideTickLabelsAutorange||(a._insideTickLabelsAutorange={}),a._insideTickLabelsAutorange[w._name+\".autorange\"]=w.autorange,_.push((function(){v.each((function(t,r){var n=dt(this);e._vals[r].bb=h.bBox(n.node())}))})));var T=s.syncOrAsync(_);return T&&T.then&&t._promises.push(T),T},B.getPxPosition=function(t,e){var r,n=t._fullLayout._size,i=e._id.charAt(0),a=e.side;return\"free\"!==e.anchor?r=e._anchorAxis:\"x\"===i?r={_offset:n.t+(1-(e.position||0))*n.h,_length:0}:\"y\"===i&&(r={_offset:n.l+(e.position||0)*n.w,_length:0}),\"top\"===a||\"left\"===a?r._offset:\"bottom\"===a||\"right\"===a?r._offset+r._length:void 0},B.shouldShowZeroLine=function(t,e,r){var n=s.simpleMap(e.range,e.r2l);return n[0]*n[1]<=0&&e.zeroline&&(\"linear\"===e.type||\"-\"===e.type)&&!(e.rangebreaks&&e.maskBreaks(0)===P)&&(pt(e,0)||!function(t,e,r,n){var i=r._mainAxis;if(!i)return;var 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r=a(t.changedTouches[0],e);f(0,r[0],r[1]),f(1,r[0],r[1]),t.preventDefault()}),!!s&&{passive:!1}),e.addEventListener(\"touchmove\",(function(t){t.preventDefault();var r=a(t.changedTouches[0],e);f(1,r[0],r[1]),t.preventDefault()}),!!s&&{passive:!1}),e.addEventListener(\"touchend\",(function(t){f(0,c.lastPos[0],c.lastPos[1]),t.preventDefault()}),!!s&&{passive:!1}),c.wheelListener=i(e,(function(e,n){if(!t.scrollZoom)return!1;var i=t.calcDataBox(),a=r.viewBox,o=c.lastPos[0],s=c.lastPos[1],l=Math.exp(5*n/(a[3]-a[1])),f=o/(a[2]-a[0])*(i[2]-i[0])+i[0],h=s/(a[3]-a[1])*(i[3]-i[1])+i[1];return i[0]=(i[0]-f)*l+f,i[2]=(i[2]-f)*l+f,i[1]=(i[1]-h)*l+h,i[3]=(i[3]-h)*l+h,t.setRanges(i),c.lastInputTime=Date.now(),u(),t.cameraChanged(),t.handleAnnotations(),t.relayoutCallback(),!0}),!0),c}},{\"../cartesian/constants\":834,\"has-passive-events\":441,\"mouse-change\":483,\"mouse-event-offset\":484,\"mouse-wheel\":486}],867:[function(t,e,r){\"use strict\";var n=t(\"../cartesian/axes\"),i=t(\"../../lib/str2rgbarray\");function a(t){this.scene=t,this.gl=t.gl,this.pixelRatio=t.pixelRatio,this.screenBox=[0,0,1,1],this.viewBox=[0,0,1,1],this.dataBox=[-1,-1,1,1],this.borderLineEnable=[!1,!1,!1,!1],this.borderLineWidth=[1,1,1,1],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.ticks=[[],[]],this.tickEnable=[!0,!0,!1,!1],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labels=[\"x\",\"y\"],this.labelEnable=[!0,!0,!1,!1],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelPad=[15,15,15,15],this.labelSize=[12,12],this.labelFont=[\"sans-serif\",\"sans-serif\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.title=\"\",this.titleEnable=!0,this.titleCenter=[0,0,0,0],this.titleAngle=0,this.titleColor=[0,0,0,1],this.titleFont=\"sans-serif\",this.titleSize=18,this.gridLineEnable=[!0,!0],this.gridLineColor=[[0,0,0,.5],[0,0,0,.5]],this.gridLineWidth=[1,1],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[1,1],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.static=this.scene.staticPlot}var o=a.prototype,s=[\"xaxis\",\"yaxis\"];o.merge=function(t){var e,r,n,a,o,l,c,u,f,h,p;for(this.titleEnable=!1,this.backgroundColor=i(t.plot_bgcolor),h=0;h<2;++h){var d=(e=s[h]).charAt(0);for(n=(r=t[this.scene[e]._name]).title.text===this.scene.fullLayout._dfltTitle[d]?\"\":r.title.text,p=0;p<=2;p+=2)this.labelEnable[h+p]=!1,this.labels[h+p]=n,this.labelColor[h+p]=i(r.title.font.color),this.labelFont[h+p]=r.title.font.family,this.labelSize[h+p]=r.title.font.size,this.labelPad[h+p]=this.getLabelPad(e,r),this.tickEnable[h+p]=!1,this.tickColor[h+p]=i((r.tickfont||{}).color),this.tickAngle[h+p]=\"auto\"===r.tickangle?0:Math.PI*-r.tickangle/180,this.tickPad[h+p]=this.getTickPad(r),this.tickMarkLength[h+p]=0,this.tickMarkWidth[h+p]=r.tickwidth||0,this.tickMarkColor[h+p]=i(r.tickcolor),this.borderLineEnable[h+p]=!1,this.borderLineColor[h+p]=i(r.linecolor),this.borderLineWidth[h+p]=r.linewidth||0;c=this.hasSharedAxis(r),o=this.hasAxisInDfltPos(e,r)&&!c,l=this.hasAxisInAltrPos(e,r)&&!c,a=r.mirror||!1,u=c?-1!==String(a).indexOf(\"all\"):!!a,f=c?\"allticks\"===a:-1!==String(a).indexOf(\"ticks\"),o?this.labelEnable[h]=!0:l&&(this.labelEnable[h+2]=!0),o?this.tickEnable[h]=r.showticklabels:l&&(this.tickEnable[h+2]=r.showticklabels),(o||u)&&(this.borderLineEnable[h]=r.showline),(l||u)&&(this.borderLineEnable[h+2]=r.showline),(o||f)&&(this.tickMarkLength[h]=this.getTickMarkLength(r)),(l||f)&&(this.tickMarkLength[h+2]=this.getTickMarkLength(r)),this.gridLineEnable[h]=r.showgrid,this.gridLineColor[h]=i(r.gridcolor),this.gridLineWidth[h]=r.gridwidth,this.zeroLineEnable[h]=r.zeroline,this.zeroLineColor[h]=i(r.zerolinecolor),this.zeroLineWidth[h]=r.zerolinewidth}},o.hasSharedAxis=function(t){var e=this.scene,r=e.fullLayout._subplots.gl2d;return 0!==n.findSubplotsWithAxis(r,t).indexOf(e.id)},o.hasAxisInDfltPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"bottom\"===r:\"yaxis\"===t?\"left\"===r:void 0},o.hasAxisInAltrPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"top\"===r:\"yaxis\"===t?\"right\"===r:void 0},o.getLabelPad=function(t,e){var r=e.title.font.size,n=e.showticklabels;return\"xaxis\"===t?\"top\"===e.side?r*(1.5+(n?1:0))-10:r*(1.5+(n?.5:0))-10:\"yaxis\"===t?\"right\"===e.side?10+r*(1.5+(n?1:.5)):10+r*(1.5+(n?.5:0)):void 0},o.getTickPad=function(t){return\"outside\"===t.ticks?10+t.ticklen:15},o.getTickMarkLength=function(t){if(!t.ticks)return 0;var e=t.ticklen;return\"inside\"===t.ticks?-e:e},e.exports=function(t){return new a(t)}},{\"../../lib/str2rgbarray\":802,\"../cartesian/axes\":828}],868:[function(t,e,r){\"use strict\";var n=t(\"../../plot_api/edit_types\").overrideAll,i=t(\"./scene2d\"),a=t(\"../layout_attributes\"),o=t(\"../../constants/xmlns_namespaces\"),s=t(\"../cartesian/constants\"),l=t(\"../cartesian\"),c=t(\"../../components/fx/layout_attributes\"),u=t(\"../get_data\").getSubplotData;r.name=\"gl2d\",r.attr=[\"xaxis\",\"yaxis\"],r.idRoot=[\"x\",\"y\"],r.idRegex=s.idRegex,r.attrRegex=s.attrRegex,r.attributes=t(\"../cartesian/attributes\"),r.supplyLayoutDefaults=function(t,e,r){e._has(\"cartesian\")||l.supplyLayoutDefaults(t,e,r)},r.layoutAttrOverrides=n(l.layoutAttributes,\"plot\",\"from-root\"),r.baseLayoutAttrOverrides=n({plot_bgcolor:a.plot_bgcolor,hoverlabel:c.hoverlabel},\"plot\",\"nested\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl2d,a=0;a<n.length;a++){var o=n[a],s=e._plots[o],l=u(r,\"gl2d\",o),c=s._scene2d;void 0===c&&(c=new i({id:o,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),s._scene2d=c),c.plot(l,t.calcdata,e,t.layout)}},r.clean=function(t,e,r,n){for(var i=n._subplots.gl2d||[],a=0;a<i.length;a++){var o=i[a],s=n._plots[o];if(s._scene2d){var c=u(t,\"gl2d\",o);0===c.length&&(s._scene2d.destroy(),delete n._plots[o])}}l.clean.apply(this,arguments)},r.drawFramework=function(t){t._context.staticPlot||l.drawFramework(t)},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){var i=e._plots[r[n]]._scene2d,a=i.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":a,x:0,y:0,width:\"100%\",height:\"100%\",preserveAspectRatio:\"none\"}),i.destroy()}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){e._plots[r[n]]._scene2d.updateFx(e.dragmode)}}},{\"../../components/fx/layout_attributes\":684,\"../../constants/xmlns_namespaces\":754,\"../../plot_api/edit_types\":810,\"../cartesian\":841,\"../cartesian/attributes\":826,\"../cartesian/constants\":834,\"../get_data\":865,\"../layout_attributes\":882,\"./scene2d\":869}],869:[function(t,e,r){\"use strict\";var n,i,a=t(\"../../registry\"),o=t(\"../../plots/cartesian/axes\"),s=t(\"../../components/fx\"),l=t(\"gl-plot2d\"),c=t(\"gl-spikes2d\"),u=t(\"gl-select-box\"),f=t(\"webgl-context\"),h=t(\"./convert\"),p=t(\"./camera\"),d=t(\"../../lib/show_no_webgl_msg\"),g=t(\"../cartesian/constraints\"),m=g.enforce,v=g.clean,y=t(\"../cartesian/autorange\").doAutoRange,x=t(\"../../components/dragelement/helpers\"),b=x.drawMode,_=x.selectMode,w=[\"xaxis\",\"yaxis\"],T=t(\"../cartesian/constants\").SUBPLOT_PATTERN;function k(t,e){this.container=t.container,this.graphDiv=t.graphDiv,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.scrollZoom=this.graphDiv._context._scrollZoom.cartesian,this.fullData=null,this.updateRefs(e),this.makeFramework(),this.stopped||(this.glplotOptions=h(this),this.glplotOptions.merge(e),this.glplot=l(this.glplotOptions),this.camera=p(this),this.traces={},this.spikes=c(this.glplot),this.selectBox=u(this.glplot,{innerFill:!1,outerFill:!0}),this.lastButtonState=0,this.pickResult=null,this.isMouseOver=!0,this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw())}e.exports=k;var M=k.prototype;M.makeFramework=function(){if(this.staticPlot){if(!(i||(n=document.createElement(\"canvas\"),i=f({canvas:n,preserveDrawingBuffer:!1,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"Error creating static canvas/context for image server\");this.canvas=n,this.gl=i}else{var t=this.container.querySelector(\".gl-canvas-focus\"),e=f({canvas:t,preserveDrawingBuffer:!0,premultipliedAlpha:!0});if(!e)return d(this),void(this.stopped=!0);this.canvas=t,this.gl=e}var r=this.canvas;r.style.width=\"100%\",r.style.height=\"100%\",r.style.position=\"absolute\",r.style.top=\"0px\",r.style.left=\"0px\",r.style[\"pointer-events\"]=\"none\",this.updateSize(r);var a=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");a.style.position=\"absolute\",a.style.top=a.style.left=\"0px\",a.style.width=a.style.height=\"100%\",a.style[\"z-index\"]=20,a.style[\"pointer-events\"]=\"none\";var o=this.mouseContainer=document.createElement(\"div\");o.style.position=\"absolute\",o.style[\"pointer-events\"]=\"auto\",this.pickCanvas=this.container.querySelector(\".gl-canvas-pick\");var s=this.container;s.appendChild(a),s.appendChild(o);var l=this;o.addEventListener(\"mouseout\",(function(){l.isMouseOver=!1,l.unhover()})),o.addEventListener(\"mouseover\",(function(){l.isMouseOver=!0}))},M.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(n),this.updateSize(this.canvas);var e=this.glplot.gl,r=e.drawingBufferWidth,i=e.drawingBufferHeight;e.clearColor(1,1,1,0),e.clear(e.COLOR_BUFFER_BIT|e.DEPTH_BUFFER_BIT),this.glplot.setDirty(),this.glplot.draw(),e.bindFramebuffer(e.FRAMEBUFFER,null);var a=new Uint8Array(r*i*4);e.readPixels(0,0,r,i,e.RGBA,e.UNSIGNED_BYTE,a);for(var o=0,s=i-1;o<s;++o,--s)for(var l=0;l<r;++l)for(var c=0;c<4;++c){var u=a[4*(r*o+l)+c];a[4*(r*o+l)+c]=a[4*(r*s+l)+c],a[4*(r*s+l)+c]=u}var f=document.createElement(\"canvas\");f.width=r,f.height=i;var h,p=f.getContext(\"2d\"),d=p.createImageData(r,i);switch(d.data.set(a),p.putImageData(d,0,0),t){case\"jpeg\":h=f.toDataURL(\"image/jpeg\");break;case\"webp\":h=f.toDataURL(\"image/webp\");break;default:h=f.toDataURL(\"image/png\")}return this.staticPlot&&this.container.removeChild(n),h},M.updateSize=function(t){t||(t=this.canvas);var e=this.pixelRatio,r=this.fullLayout,n=r.width,i=r.height,a=0|Math.ceil(e*n),o=0|Math.ceil(e*i);return t.width===a&&t.height===o||(t.width=a,t.height=o),t},M.computeTickMarks=function(){this.xaxis.setScale(),this.yaxis.setScale();for(var t=[o.calcTicks(this.xaxis),o.calcTicks(this.yaxis)],e=0;e<2;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=t[e][r].text+\"\";return t},M.updateRefs=function(t){this.fullLayout=t;var e=this.id.match(T),r=\"xaxis\"+e[1],n=\"yaxis\"+e[2];this.xaxis=this.fullLayout[r],this.yaxis=this.fullLayout[n]},M.relayoutCallback=function(){var t=this.graphDiv,e=this.xaxis,r=this.yaxis,n=t.layout,i={},o=i[e._name+\".range\"]=e.range.slice(),s=i[r._name+\".range\"]=r.range.slice();i[e._name+\".autorange\"]=e.autorange,i[r._name+\".autorange\"]=r.autorange,a.call(\"_storeDirectGUIEdit\",t.layout,t._fullLayout._preGUI,i);var l=n[e._name];l.range=o,l.autorange=e.autorange;var c=n[r._name];c.range=s,c.autorange=r.autorange,i.lastInputTime=this.camera.lastInputTime,t.emit(\"plotly_relayout\",i)},M.cameraChanged=function(){var t=this.camera;this.glplot.setDataBox(this.calcDataBox());var e=this.computeTickMarks();(function(t,e){for(var r=0;r<2;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1})(e,this.glplotOptions.ticks)&&(this.glplotOptions.ticks=e,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions),this.handleAnnotations())},M.handleAnnotations=function(){for(var t=this.graphDiv,e=this.fullLayout.annotations,r=0;r<e.length;r++){var n=e[r];n.xref===this.xaxis._id&&n.yref===this.yaxis._id&&a.getComponentMethod(\"annotations\",\"drawOne\")(t,r)}},M.destroy=function(){if(this.glplot){var t=this.traces;t&&Object.keys(t).map((function(e){t[e].dispose(),delete t[e]})),this.glplot.dispose(),this.container.removeChild(this.svgContainer),this.container.removeChild(this.mouseContainer),this.fullData=null,this.glplot=null,this.stopped=!0,this.camera.mouseListener.enabled=!1,this.mouseContainer.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null}},M.plot=function(t,e,r){var n=this.glplot;this.updateRefs(r),this.xaxis.clearCalc(),this.yaxis.clearCalc(),this.updateTraces(t,e),this.updateFx(r.dragmode);var i=r.width,a=r.height;this.updateSize(this.canvas);var o=this.glplotOptions;o.merge(r),o.screenBox=[0,0,i,a];var s={_fullLayout:{_axisConstraintGroups:this.graphDiv._fullLayout._axisConstraintGroups,xaxis:this.xaxis,yaxis:this.yaxis}};v(s,this.xaxis),v(s,this.yaxis);var l,c,u=r._size,f=this.xaxis.domain,h=this.yaxis.domain;for(o.viewBox=[u.l+f[0]*u.w,u.b+h[0]*u.h,i-u.r-(1-f[1])*u.w,a-u.t-(1-h[1])*u.h],this.mouseContainer.style.width=u.w*(f[1]-f[0])+\"px\",this.mouseContainer.style.height=u.h*(h[1]-h[0])+\"px\",this.mouseContainer.height=u.h*(h[1]-h[0]),this.mouseContainer.style.left=u.l+f[0]*u.w+\"px\",this.mouseContainer.style.top=u.t+(1-h[1])*u.h+\"px\",c=0;c<2;++c)(l=this[w[c]])._length=o.viewBox[c+2]-o.viewBox[c],y(this.graphDiv,l),l.setScale();m(s),o.ticks=this.computeTickMarks(),o.dataBox=this.calcDataBox(),o.merge(r),n.update(o),this.glplot.draw()},M.calcDataBox=function(){var t=this.xaxis,e=this.yaxis,r=t.range,n=e.range,i=t.r2l,a=e.r2l;return[i(r[0]),a(n[0]),i(r[1]),a(n[1])]},M.setRanges=function(t){var e=this.xaxis,r=this.yaxis,n=e.l2r,i=r.l2r;e.range=[n(t[0]),n(t[2])],r.range=[i(t[1]),i(t[3])]},M.updateTraces=function(t,e){var r,n,i,a=Object.keys(this.traces);this.fullData=t;t:for(r=0;r<a.length;r++){var o=a[r],s=this.traces[o];for(n=0;n<t.length;n++)if((i=t[n]).uid===o&&i.type===s.type)continue t;s.dispose(),delete this.traces[o]}for(r=0;r<t.length;r++){i=t[r];var l=e[r],c=this.traces[i.uid];c?c.update(i,l):(c=i._module.plot(this,i,l),this.traces[i.uid]=c)}this.glplot.objects.sort((function(t,e){return t._trace.index-e._trace.index}))},M.updateFx=function(t){_(t)||b(t)?(this.pickCanvas.style[\"pointer-events\"]=\"none\",this.mouseContainer.style[\"pointer-events\"]=\"none\"):(this.pickCanvas.style[\"pointer-events\"]=\"auto\",this.mouseContainer.style[\"pointer-events\"]=\"auto\"),this.mouseContainer.style.cursor=\"pan\"===t?\"move\":\"zoom\"===t?\"crosshair\":null},M.emitPointAction=function(t,e){for(var r,n=t.trace.uid,i=t.pointIndex,a=0;a<this.fullData.length;a++)this.fullData[a].uid===n&&(r=this.fullData[a]);var o={x:t.traceCoord[0],y:t.traceCoord[1],curveNumber:r.index,pointNumber:i,data:r._input,fullData:this.fullData,xaxis:this.xaxis,yaxis:this.yaxis};s.appendArrayPointValue(o,r,i),this.graphDiv.emit(e,{points:[o]})},M.draw=function(){if(!this.stopped){requestAnimationFrame(this.redraw);var t=this.glplot,e=this.camera,r=e.mouseListener,n=1===this.lastButtonState&&0===r.buttons,i=this.fullLayout;this.lastButtonState=r.buttons,this.cameraChanged();var a,o=r.x*t.pixelRatio,l=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&\"zoom\"===i.dragmode){this.selectBox.enabled=!0;for(var c=this.selectBox.selectBox=[Math.min(e.boxStart[0],e.boxEnd[0]),Math.min(e.boxStart[1],e.boxEnd[1]),Math.max(e.boxStart[0],e.boxEnd[0]),Math.max(e.boxStart[1],e.boxEnd[1])],u=0;u<2;u++)e.boxStart[u]===e.boxEnd[u]&&(c[u]=t.dataBox[u],c[u+2]=t.dataBox[u+2]);t.setDirty()}else if(!e.panning&&this.isMouseOver){this.selectBox.enabled=!1;var f=i._size,h=this.xaxis.domain,p=this.yaxis.domain,d=(a=t.pick(o/t.pixelRatio+f.l+h[0]*f.w,l/t.pixelRatio-(f.t+(1-p[1])*f.h)))&&a.object._trace.handlePick(a);if(d&&n&&this.emitPointAction(d,\"plotly_click\"),a&&\"skip\"!==a.object._trace.hoverinfo&&i.hovermode&&d&&(!this.lastPickResult||this.lastPickResult.traceUid!==d.trace.uid||this.lastPickResult.dataCoord[0]!==d.dataCoord[0]||this.lastPickResult.dataCoord[1]!==d.dataCoord[1])){var g=d;this.lastPickResult={traceUid:d.trace?d.trace.uid:null,dataCoord:d.dataCoord.slice()},this.spikes.update({center:a.dataCoord}),g.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(a.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(a.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio],this.emitPointAction(d,\"plotly_hover\");var m=this.fullData[g.trace.index]||{},v=g.pointIndex,y=s.castHoverinfo(m,i,v);if(y&&\"all\"!==y){var x=y.split(\"+\");-1===x.indexOf(\"x\")&&(g.traceCoord[0]=void 0),-1===x.indexOf(\"y\")&&(g.traceCoord[1]=void 0),-1===x.indexOf(\"z\")&&(g.traceCoord[2]=void 0),-1===x.indexOf(\"text\")&&(g.textLabel=void 0),-1===x.indexOf(\"name\")&&(g.name=void 0)}s.loneHover({x:g.screenCoord[0],y:g.screenCoord[1],xLabel:this.hoverFormatter(\"xaxis\",g.traceCoord[0]),yLabel:this.hoverFormatter(\"yaxis\",g.traceCoord[1]),zLabel:g.traceCoord[2],text:g.textLabel,name:g.name,color:s.castHoverOption(m,v,\"bgcolor\")||g.color,borderColor:s.castHoverOption(m,v,\"bordercolor\"),fontFamily:s.castHoverOption(m,v,\"font.family\"),fontSize:s.castHoverOption(m,v,\"font.size\"),fontColor:s.castHoverOption(m,v,\"font.color\"),nameLength:s.castHoverOption(m,v,\"namelength\"),textAlign:s.castHoverOption(m,v,\"align\")},{container:this.svgContainer,gd:this.graphDiv})}}a||this.unhover(),t.draw()}},M.unhover=function(){this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,this.graphDiv.emit(\"plotly_unhover\"),s.loneUnhover(this.svgContainer))},M.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return o.tickText(r,r.c2l(e),\"hover\").text}}},{\"../../components/dragelement/helpers\":661,\"../../components/fx\":683,\"../../lib/show_no_webgl_msg\":800,\"../../plots/cartesian/axes\":828,\"../../registry\":911,\"../cartesian/autorange\":827,\"../cartesian/constants\":834,\"../cartesian/constraints\":835,\"./camera\":866,\"./convert\":867,\"gl-plot2d\":317,\"gl-select-box\":333,\"gl-spikes2d\":342,\"webgl-context\":606}],870:[function(t,e,r){\"use strict\";var n=t(\"../../plot_api/edit_types\").overrideAll,i=t(\"../../components/fx/layout_attributes\"),a=t(\"./scene\"),o=t(\"../get_data\").getSubplotData,s=t(\"../../lib\"),l=t(\"../../constants/xmlns_namespaces\");r.name=\"gl3d\",r.attr=\"scene\",r.idRoot=\"scene\",r.idRegex=r.attrRegex=s.counterRegex(\"scene\"),r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.baseLayoutAttrOverrides=n({hoverlabel:i.hoverlabel},\"plot\",\"nested\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl3d,i=0;i<n.length;i++){var s=n[i],l=o(r,\"gl3d\",s),c=e[s],u=c.camera,f=c._scene;f||(f=new a({id:s,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio,camera:u},e),c._scene=f),f.viewInitial||(f.viewInitial={up:{x:u.up.x,y:u.up.y,z:u.up.z},eye:{x:u.eye.x,y:u.eye.y,z:u.eye.z},center:{x:u.center.x,y:u.center.y,z:u.center.z}}),f.plot(l,e,t.layout)}},r.clean=function(t,e,r,n){for(var i=n._subplots.gl3d||[],a=0;a<i.length;a++){var o=i[a];!e[o]&&n[o]._scene&&(n[o]._scene.destroy(),n._infolayer&&n._infolayer.selectAll(\".annotation-\"+o).remove())}},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=e._size,i=0;i<r.length;i++){var a=e[r[i]],o=a.domain,s=a._scene,c=s.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:l.svg,\"xlink:href\":c,x:n.l+n.w*o.x[0],y:n.t+n.h*(1-o.y[1]),width:n.w*(o.x[1]-o.x[0]),height:n.h*(o.y[1]-o.y[0]),preserveAspectRatio:\"none\"}),s.destroy()}},r.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),\"scene\"+e}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=0;n<r.length;n++){e[r[n]]._scene.updateFx(e.dragmode,e.hovermode)}}},{\"../../components/fx/layout_attributes\":684,\"../../constants/xmlns_namespaces\":754,\"../../lib\":778,\"../../plot_api/edit_types\":810,\"../get_data\":865,\"./layout/attributes\":871,\"./layout/defaults\":875,\"./layout/layout_attributes\":876,\"./scene\":880}],871:[function(t,e,r){\"use strict\";e.exports={scene:{valType:\"subplotid\",dflt:\"scene\",editType:\"calc+clearAxisTypes\"}}},{}],872:[function(t,e,r){\"use strict\";var n=t(\"../../../components/color\"),i=t(\"../../cartesian/layout_attributes\"),a=t(\"../../../lib/extend\").extendFlat,o=t(\"../../../plot_api/edit_types\").overrideAll;e.exports=o({visible:i.visible,showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:n.defaultLine},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},color:i.color,categoryorder:i.categoryorder,categoryarray:i.categoryarray,title:{text:i.title.text,font:i.title.font},type:a({},i.type,{values:[\"-\",\"linear\",\"log\",\"date\",\"category\"]}),autotypenumbers:i.autotypenumbers,autorange:i.autorange,rangemode:i.rangemode,range:a({},i.range,{items:[{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}},{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}}],anim:!1}),tickmode:i.tickmode,nticks:i.nticks,tick0:i.tick0,dtick:i.dtick,tickvals:i.tickvals,ticktext:i.ticktext,ticks:i.ticks,mirror:i.mirror,ticklen:i.ticklen,tickwidth:i.tickwidth,tickcolor:i.tickcolor,showticklabels:i.showticklabels,tickfont:i.tickfont,tickangle:i.tickangle,tickprefix:i.tickprefix,showtickprefix:i.showtickprefix,ticksuffix:i.ticksuffix,showticksuffix:i.showticksuffix,showexponent:i.showexponent,exponentformat:i.exponentformat,minexponent:i.minexponent,separatethousands:i.separatethousands,tickformat:i.tickformat,tickformatstops:i.tickformatstops,hoverformat:i.hoverformat,showline:i.showline,linecolor:i.linecolor,linewidth:i.linewidth,showgrid:i.showgrid,gridcolor:a({},i.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:i.gridwidth,zeroline:i.zeroline,zerolinecolor:i.zerolinecolor,zerolinewidth:i.zerolinewidth,_deprecated:{title:i._deprecated.title,titlefont:i._deprecated.titlefont}},\"plot\",\"from-root\")},{\"../../../components/color\":643,\"../../../lib/extend\":768,\"../../../plot_api/edit_types\":810,\"../../cartesian/layout_attributes\":842}],873:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\").mix,i=t(\"../../../lib\"),a=t(\"../../../plot_api/plot_template\"),o=t(\"./axis_attributes\"),s=t(\"../../cartesian/type_defaults\"),l=t(\"../../cartesian/axis_defaults\"),c=[\"xaxis\",\"yaxis\",\"zaxis\"];e.exports=function(t,e,r){var u,f;function h(t,e){return i.coerce(u,f,o,t,e)}for(var p=0;p<c.length;p++){var d=c[p];u=t[d]||{},(f=a.newContainer(e,d))._id=d[0]+r.scene,f._name=d,s(u,f,h,r),l(u,f,h,{font:r.font,letter:d[0],data:r.data,showGrid:!0,noTickson:!0,noTicklabelmode:!0,noTicklabelposition:!0,bgColor:r.bgColor,calendar:r.calendar},r.fullLayout),h(\"gridcolor\",n(f.color,r.bgColor,13600/187).toRgbString()),h(\"title.text\",d[0]),f.setScale=i.noop,h(\"showspikes\")&&(h(\"spikesides\"),h(\"spikethickness\"),h(\"spikecolor\",f.color)),h(\"showaxeslabels\"),h(\"showbackground\")&&h(\"backgroundcolor\")}}},{\"../../../lib\":778,\"../../../plot_api/plot_template\":817,\"../../cartesian/axis_defaults\":830,\"../../cartesian/type_defaults\":853,\"./axis_attributes\":872,tinycolor2:576}],874:[function(t,e,r){\"use strict\";var n=t(\"../../../lib/str2rgbarray\"),i=t(\"../../../lib\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"];function o(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open Sans\"],this.labelSize=[20,20,20],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=this.tickPad.slice(),this._defaultLabelPad=this.labelPad.slice(),this._defaultLineTickLength=this.lineTickLength.slice()}o.prototype.merge=function(t,e){for(var r=0;r<3;++r){var o=e[a[r]];o.visible?(this.labels[r]=t._meta?i.templateString(o.title.text,t._meta):o.title.text,\"font\"in o.title&&(o.title.font.color&&(this.labelColor[r]=n(o.title.font.color)),o.title.font.family&&(this.labelFont[r]=o.title.font.family),o.title.font.size&&(this.labelSize[r]=o.title.font.size)),\"showline\"in o&&(this.lineEnable[r]=o.showline),\"linecolor\"in o&&(this.lineColor[r]=n(o.linecolor)),\"linewidth\"in o&&(this.lineWidth[r]=o.linewidth),\"showgrid\"in o&&(this.gridEnable[r]=o.showgrid),\"gridcolor\"in o&&(this.gridColor[r]=n(o.gridcolor)),\"gridwidth\"in o&&(this.gridWidth[r]=o.gridwidth),\"log\"===o.type?this.zeroEnable[r]=!1:\"zeroline\"in o&&(this.zeroEnable[r]=o.zeroline),\"zerolinecolor\"in o&&(this.zeroLineColor[r]=n(o.zerolinecolor)),\"zerolinewidth\"in o&&(this.zeroLineWidth[r]=o.zerolinewidth),\"ticks\"in o&&o.ticks?this.lineTickEnable[r]=!0:this.lineTickEnable[r]=!1,\"ticklen\"in o&&(this.lineTickLength[r]=this._defaultLineTickLength[r]=o.ticklen),\"tickcolor\"in o&&(this.lineTickColor[r]=n(o.tickcolor)),\"tickwidth\"in o&&(this.lineTickWidth[r]=o.tickwidth),\"tickangle\"in o&&(this.tickAngle[r]=\"auto\"===o.tickangle?-3600:Math.PI*-o.tickangle/180),\"showticklabels\"in o&&(this.tickEnable[r]=o.showticklabels),\"tickfont\"in o&&(o.tickfont.color&&(this.tickColor[r]=n(o.tickfont.color)),o.tickfont.family&&(this.tickFont[r]=o.tickfont.family),o.tickfont.size&&(this.tickSize[r]=o.tickfont.size)),\"mirror\"in o?-1!==[\"ticks\",\"all\",\"allticks\"].indexOf(o.mirror)?(this.lineTickMirror[r]=!0,this.lineMirror[r]=!0):!0===o.mirror?(this.lineTickMirror[r]=!1,this.lineMirror[r]=!0):(this.lineTickMirror[r]=!1,this.lineMirror[r]=!1):this.lineMirror[r]=!1,\"showbackground\"in o&&!1!==o.showbackground?(this.backgroundEnable[r]=!0,this.backgroundColor[r]=n(o.backgroundcolor)):this.backgroundEnable[r]=!1):(this.tickEnable[r]=!1,this.labelEnable[r]=!1,this.lineEnable[r]=!1,this.lineTickEnable[r]=!1,this.gridEnable[r]=!1,this.zeroEnable[r]=!1,this.backgroundEnable[r]=!1)}},e.exports=function(t,e){var r=new o;return r.merge(t,e),r}},{\"../../../lib\":778,\"../../../lib/str2rgbarray\":802}],875:[function(t,e,r){\"use strict\";var n=t(\"../../../lib\"),i=t(\"../../../components/color\"),a=t(\"../../../registry\"),o=t(\"../../subplot_defaults\"),s=t(\"./axis_defaults\"),l=t(\"./layout_attributes\"),c=t(\"../../get_data\").getSubplotData;function u(t,e,r,n){for(var o=r(\"bgcolor\"),l=i.combine(o,n.paper_bgcolor),u=[\"up\",\"center\",\"eye\"],f=0;f<u.length;f++)r(\"camera.\"+u[f]+\".x\"),r(\"camera.\"+u[f]+\".y\"),r(\"camera.\"+u[f]+\".z\");r(\"camera.projection.type\");var h=!!r(\"aspectratio.x\")&&!!r(\"aspectratio.y\")&&!!r(\"aspectratio.z\"),p=r(\"aspectmode\",h?\"manual\":\"auto\");h||(t.aspectratio=e.aspectratio={x:1,y:1,z:1},\"manual\"===p&&(e.aspectmode=\"auto\"),t.aspectmode=e.aspectmode);var d=c(n.fullData,\"gl3d\",n.id);s(t,e,{font:n.font,scene:n.id,data:d,bgColor:l,calendar:n.calendar,autotypenumbersDflt:n.autotypenumbersDflt,fullLayout:n.fullLayout}),a.getComponentMethod(\"annotations3d\",\"handleDefaults\")(t,e,n);var g=n.getDfltFromLayout(\"dragmode\");if(!1!==g&&!g)if(g=\"orbit\",t.camera&&t.camera.up){var m=t.camera.up.x,v=t.camera.up.y,y=t.camera.up.z;0!==y&&(m&&v&&y?y/Math.sqrt(m*m+v*v+y*y)>.999&&(g=\"turntable\"):g=\"turntable\")}else g=\"turntable\";r(\"dragmode\",g),r(\"hovermode\",n.getDfltFromLayout(\"hovermode\"))}e.exports=function(t,e,r){var i=e._basePlotModules.length>1;o(t,e,r,{type:\"gl3d\",attributes:l,handleDefaults:u,fullLayout:e,font:e.font,fullData:r,getDfltFromLayout:function(e){if(!i)return n.validate(t[e],l[e])?t[e]:void 0},autotypenumbersDflt:e.autotypenumbers,paper_bgcolor:e.paper_bgcolor,calendar:e.calendar})}},{\"../../../components/color\":643,\"../../../lib\":778,\"../../../registry\":911,\"../../get_data\":865,\"../../subplot_defaults\":905,\"./axis_defaults\":873,\"./layout_attributes\":876}],876:[function(t,e,r){\"use strict\";var n=t(\"./axis_attributes\"),i=t(\"../../domain\").attributes,a=t(\"../../../lib/extend\").extendFlat,o=t(\"../../../lib\").counterRegex;function s(t,e,r){return{x:{valType:\"number\",dflt:t,editType:\"camera\"},y:{valType:\"number\",dflt:e,editType:\"camera\"},z:{valType:\"number\",dflt:r,editType:\"camera\"},editType:\"camera\"}}e.exports={_arrayAttrRegexps:[o(\"scene\",\".annotations\",!0)],bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"plot\"},camera:{up:a(s(0,0,1),{}),center:a(s(0,0,0),{}),eye:a(s(1.25,1.25,1.25),{}),projection:{type:{valType:\"enumerated\",values:[\"perspective\",\"orthographic\"],dflt:\"perspective\",editType:\"calc\"},editType:\"calc\"},editType:\"camera\"},domain:i({name:\"scene\",editType:\"plot\"}),aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\",editType:\"plot\",impliedEdits:{\"aspectratio.x\":void 0,\"aspectratio.y\":void 0,\"aspectratio.z\":void 0}},aspectratio:{x:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},y:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},z:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},editType:\"plot\",impliedEdits:{aspectmode:\"manual\"}},xaxis:n,yaxis:n,zaxis:n,dragmode:{valType:\"enumerated\",values:[\"orbit\",\"turntable\",\"zoom\",\"pan\",!1],editType:\"plot\"},hovermode:{valType:\"enumerated\",values:[\"closest\",!1],dflt:\"closest\",editType:\"modebar\"},uirevision:{valType:\"any\",editType:\"none\"},editType:\"plot\",_deprecated:{cameraposition:{valType:\"info_array\",editType:\"camera\"}}}},{\"../../../lib\":778,\"../../../lib/extend\":768,\"../../domain\":855,\"./axis_attributes\":872}],877:[function(t,e,r){\"use strict\";var n=t(\"../../../lib/str2rgbarray\"),i=[\"xaxis\",\"yaxis\",\"zaxis\"];function a(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}a.prototype.merge=function(t){for(var e=0;e<3;++e){var r=t[i[e]];r.visible?(this.enabled[e]=r.showspikes,this.colors[e]=n(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness):(this.enabled[e]=!1,this.drawSides[e]=!1)}},e.exports=function(t){var e=new a;return e.merge(t),e}},{\"../../../lib/str2rgbarray\":802}],878:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,s=t.fullSceneLayout,l=[[],[],[]],c=0;c<3;++c){var u=s[a[c]];if(u._length=(r[c].hi-r[c].lo)*r[c].pixelsPerDataUnit/t.dataScale[c],Math.abs(u._length)===1/0||isNaN(u._length))l[c]=[];else{u._input_range=u.range.slice(),u.range[0]=r[c].lo/t.dataScale[c],u.range[1]=r[c].hi/t.dataScale[c],u._m=1/(t.dataScale[c]*r[c].pixelsPerDataUnit),u.range[0]===u.range[1]&&(u.range[0]-=1,u.range[1]+=1);var f=u.tickmode;if(\"auto\"===u.tickmode){u.tickmode=\"linear\";var h=u.nticks||i.constrain(u._length/40,4,9);n.autoTicks(u,Math.abs(u.range[1]-u.range[0])/h)}for(var p=n.calcTicks(u,{msUTC:!0}),d=0;d<p.length;++d)p[d].x=p[d].x*t.dataScale[c],\"date\"===u.type&&(p[d].text=p[d].text.replace(/\\<br\\>/g,\" \"));l[c]=p,u.tickmode=f}}e.ticks=l;for(c=0;c<3;++c){o[c]=.5*(t.glplot.bounds[0][c]+t.glplot.bounds[1][c]);for(d=0;d<2;++d)e.bounds[d][c]=t.glplot.bounds[d][c]}t.contourLevels=function(t){for(var e=new Array(3),r=0;r<3;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}(l)};var n=t(\"../../cartesian/axes\"),i=t(\"../../../lib\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"],o=[0,0,0]},{\"../../../lib\":778,\"../../cartesian/axes\":828}],879:[function(t,e,r){\"use strict\";function n(t,e){var r,n,i=[0,0,0,0];for(r=0;r<4;++r)for(n=0;n<4;++n)i[n]+=t[4*r+n]*e[r];return i}e.exports=function(t,e){return n(t.projection,n(t.view,n(t.model,[e[0],e[1],e[2],1])))}},{}],880:[function(t,e,r){\"use strict\";var n,i,a=t(\"gl-plot3d\"),o=a.createCamera,s=a.createScene,l=t(\"webgl-context\"),c=t(\"has-passive-events\"),u=t(\"../../registry\"),f=t(\"../../lib\"),h=f.preserveDrawingBuffer(),p=t(\"../../plots/cartesian/axes\"),d=t(\"../../components/fx\"),g=t(\"../../lib/str2rgbarray\"),m=t(\"../../lib/show_no_webgl_msg\"),v=t(\"./project\"),y=t(\"./layout/convert\"),x=t(\"./layout/spikes\"),b=t(\"./layout/tick_marks\");function _(t,e){var r=document.createElement(\"div\"),n=t.container;this.graphDiv=t.graphDiv;var i=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");i.style.position=\"absolute\",i.style.top=i.style.left=\"0px\",i.style.width=i.style.height=\"100%\",i.style[\"z-index\"]=20,i.style[\"pointer-events\"]=\"none\",r.appendChild(i),this.svgContainer=i,r.id=t.id,r.style.position=\"absolute\",r.style.top=r.style.left=\"0px\",r.style.width=r.style.height=\"100%\",n.appendChild(r),this.fullLayout=e,this.id=t.id||\"scene\",this.fullSceneLayout=e[this.id],this.plotArgs=[[],{},{}],this.axesOptions=y(e,e[this.id]),this.spikeOptions=x(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=this.pixelRatio||t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],this.convertAnnotations=u.getComponentMethod(\"annotations3d\",\"convert\"),this.drawAnnotations=u.getComponentMethod(\"annotations3d\",\"draw\"),this.initializeGLPlot()}var w=_.prototype;w.prepareOptions=function(){var t={canvas:this.canvas,gl:this.gl,glOptions:{preserveDrawingBuffer:h,premultipliedAlpha:!0,antialias:!0},container:this.container,axes:this.axesOptions,spikes:this.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1,cameraObject:this.camera,pixelRatio:this.pixelRatio};if(this.staticMode){if(!(i||(n=document.createElement(\"canvas\"),i=l({canvas:n,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"error creating static canvas/context for image server\");t.gl=i,t.canvas=n}return t};var T=!0;w.tryCreatePlot=function(){var t=this.prepareOptions(),e=!0;try{this.glplot=s(t)}catch(r){if(this.staticMode||!T||h)e=!1;else{f.warn([\"webgl setup failed possibly due to\",\"false preserveDrawingBuffer config.\",\"The mobile/tablet device may not be detected by is-mobile module.\",\"Enabling preserveDrawingBuffer in second attempt to create webgl scene...\"].join(\" \"));try{h=t.glOptions.preserveDrawingBuffer=!0,this.glplot=s(t)}catch(r){h=t.glOptions.preserveDrawingBuffer=!1,e=!1}}}return T=!1,e},w.initializeGLCamera=function(){var t=this.fullSceneLayout.camera,e=\"orthographic\"===t.projection.type;this.camera=o(this.container,{center:[t.center.x,t.center.y,t.center.z],eye:[t.eye.x,t.eye.y,t.eye.z],up:[t.up.x,t.up.y,t.up.z],_ortho:e,zoomMin:.01,zoomMax:100,mode:\"orbit\"})},w.initializeGLPlot=function(){var t=this;if(t.initializeGLCamera(),!t.tryCreatePlot())return m(t);t.traces={},t.make4thDimension();var e=t.graphDiv,r=e.layout,n=function(){var e={};return t.isCameraChanged(r)&&(e[t.id+\".camera\"]=t.getCamera()),t.isAspectChanged(r)&&(e[t.id+\".aspectratio\"]=t.glplot.getAspectratio(),\"manual\"!==r[t.id].aspectmode&&(t.fullSceneLayout.aspectmode=r[t.id].aspectmode=e[t.id+\".aspectmode\"]=\"manual\")),e},i=function(t){if(!1!==t.fullSceneLayout.dragmode){var e=n();t.saveLayout(r),t.graphDiv.emit(\"plotly_relayout\",e)}};return t.glplot.canvas&&(t.glplot.canvas.addEventListener(\"mouseup\",(function(){i(t)})),t.glplot.canvas.addEventListener(\"wheel\",(function(r){if(e._context._scrollZoom.gl3d){if(t.camera._ortho){var n=r.deltaX>r.deltaY?1.1:1/1.1,a=t.glplot.getAspectratio();t.glplot.setAspectratio({x:n*a.x,y:n*a.y,z:n*a.z})}i(t)}}),!!c&&{passive:!1}),t.glplot.canvas.addEventListener(\"mousemove\",(function(){if(!1!==t.fullSceneLayout.dragmode&&0!==t.camera.mouseListener.buttons){var e=n();t.graphDiv.emit(\"plotly_relayouting\",e)}})),t.staticMode||t.glplot.canvas.addEventListener(\"webglcontextlost\",(function(r){e&&e.emit&&e.emit(\"plotly_webglcontextlost\",{event:r,layer:t.id})}),!1)),t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=function(){t.render()},!0},w.render=function(){var t,e=this,r=e.graphDiv,n=e.svgContainer,i=e.container.getBoundingClientRect();r._fullLayout._calcInverseTransform(r);var a=r._fullLayout._invScaleX,o=r._fullLayout._invScaleY,s=i.width*a,l=i.height*o;n.setAttributeNS(null,\"viewBox\",\"0 0 \"+s+\" \"+l),n.setAttributeNS(null,\"width\",s),n.setAttributeNS(null,\"height\",l),b(e),e.glplot.axes.update(e.axesOptions);for(var c,u=Object.keys(e.traces),h=null,g=e.glplot.selection,m=0;m<u.length;++m)\"skip\"!==(t=e.traces[u[m]]).data.hoverinfo&&t.handlePick(g)&&(h=t),t.setContourLevels&&t.setContourLevels();function y(t,r){var n=e.fullSceneLayout[t];return p.tickText(n,n.d2l(r),\"hover\").text}if(null!==h){var x=v(e.glplot.cameraParams,g.dataCoordinate);t=h.data;var _,w=r._fullData[t.index],T=g.index,k={xLabel:y(\"xaxis\",g.traceCoordinate[0]),yLabel:y(\"yaxis\",g.traceCoordinate[1]),zLabel:y(\"zaxis\",g.traceCoordinate[2])},M=d.castHoverinfo(w,e.fullLayout,T),A=(M||\"\").split(\"+\"),S=M&&\"all\"===M;w.hovertemplate||S||(-1===A.indexOf(\"x\")&&(k.xLabel=void 0),-1===A.indexOf(\"y\")&&(k.yLabel=void 0),-1===A.indexOf(\"z\")&&(k.zLabel=void 0),-1===A.indexOf(\"text\")&&(g.textLabel=void 0),-1===A.indexOf(\"name\")&&(h.name=void 0));var E=[];\"cone\"===t.type||\"streamtube\"===t.type?(k.uLabel=y(\"xaxis\",g.traceCoordinate[3]),(S||-1!==A.indexOf(\"u\"))&&E.push(\"u: \"+k.uLabel),k.vLabel=y(\"yaxis\",g.traceCoordinate[4]),(S||-1!==A.indexOf(\"v\"))&&E.push(\"v: \"+k.vLabel),k.wLabel=y(\"zaxis\",g.traceCoordinate[5]),(S||-1!==A.indexOf(\"w\"))&&E.push(\"w: \"+k.wLabel),k.normLabel=g.traceCoordinate[6].toPrecision(3),(S||-1!==A.indexOf(\"norm\"))&&E.push(\"norm: \"+k.normLabel),\"streamtube\"===t.type&&(k.divergenceLabel=g.traceCoordinate[7].toPrecision(3),(S||-1!==A.indexOf(\"divergence\"))&&E.push(\"divergence: \"+k.divergenceLabel)),g.textLabel&&E.push(g.textLabel),_=E.join(\"<br>\")):\"isosurface\"===t.type||\"volume\"===t.type?(k.valueLabel=p.tickText(e._mockAxis,e._mockAxis.d2l(g.traceCoordinate[3]),\"hover\").text,E.push(\"value: \"+k.valueLabel),g.textLabel&&E.push(g.textLabel),_=E.join(\"<br>\")):_=g.textLabel;var C={x:g.traceCoordinate[0],y:g.traceCoordinate[1],z:g.traceCoordinate[2],data:w._input,fullData:w,curveNumber:w.index,pointNumber:T};d.appendArrayPointValue(C,w,T),t._module.eventData&&(C=w._module.eventData(C,g,w,{},T));var L={points:[C]};e.fullSceneLayout.hovermode&&d.loneHover({trace:w,x:(.5+.5*x[0]/x[3])*s,y:(.5-.5*x[1]/x[3])*l,xLabel:k.xLabel,yLabel:k.yLabel,zLabel:k.zLabel,text:_,name:h.name,color:d.castHoverOption(w,T,\"bgcolor\")||h.color,borderColor:d.castHoverOption(w,T,\"bordercolor\"),fontFamily:d.castHoverOption(w,T,\"font.family\"),fontSize:d.castHoverOption(w,T,\"font.size\"),fontColor:d.castHoverOption(w,T,\"font.color\"),nameLength:d.castHoverOption(w,T,\"namelength\"),textAlign:d.castHoverOption(w,T,\"align\"),hovertemplate:f.castOption(w,T,\"hovertemplate\"),hovertemplateLabels:f.extendFlat({},C,k),eventData:[C]},{container:n,gd:r}),g.buttons&&g.distance<5?r.emit(\"plotly_click\",L):r.emit(\"plotly_hover\",L),c=L}else d.loneUnhover(n),r.emit(\"plotly_unhover\",c);e.drawAnnotations(e)},w.recoverContext=function(){var t=this;t.glplot.dispose();var e=function(){t.glplot.gl.isContextLost()?requestAnimationFrame(e):t.initializeGLPlot()?t.plot.apply(t,t.plotArgs):f.error(\"Catastrophic and unrecoverable WebGL error. Context lost.\")};requestAnimationFrame(e)};var k=[\"xaxis\",\"yaxis\",\"zaxis\"];function M(t,e,r){for(var n=t.fullSceneLayout,i=0;i<3;i++){var a=k[i],o=a.charAt(0),s=n[a],l=e[o],c=e[o+\"calendar\"],u=e[\"_\"+o+\"length\"];if(f.isArrayOrTypedArray(l))for(var h,p=0;p<(u||l.length);p++)if(f.isArrayOrTypedArray(l[p]))for(var d=0;d<l[p].length;++d)h=s.d2l(l[p][d],0,c),!isNaN(h)&&isFinite(h)&&(r[0][i]=Math.min(r[0][i],h),r[1][i]=Math.max(r[1][i],h));else h=s.d2l(l[p],0,c),!isNaN(h)&&isFinite(h)&&(r[0][i]=Math.min(r[0][i],h),r[1][i]=Math.max(r[1][i],h));else r[0][i]=Math.min(r[0][i],0),r[1][i]=Math.max(r[1][i],u-1)}}w.plot=function(t,e,r){if(this.plotArgs=[t,e,r],!this.glplot.contextLost){var n,i,a,o,s,l,c=e[this.id],u=r[this.id];this.fullLayout=e,this.fullSceneLayout=c,this.axesOptions.merge(e,c),this.spikeOptions.merge(c),this.setViewport(c),this.updateFx(c.dragmode,c.hovermode),this.camera.enableWheel=this.graphDiv._context._scrollZoom.gl3d,this.glplot.setClearColor(g(c.bgcolor)),this.setConvert(s),t?Array.isArray(t)||(t=[t]):t=[];var f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(a=0;a<t.length;++a)!0===(n=t[a]).visible&&0!==n._length&&M(this,n,f);!function(t,e){for(var r=t.fullSceneLayout,n=r.annotations||[],i=0;i<3;i++)for(var a=k[i],o=a.charAt(0),s=r[a],l=0;l<n.length;l++){var c=n[l];if(c.visible){var u=s.r2l(c[o]);!isNaN(u)&&isFinite(u)&&(e[0][i]=Math.min(e[0][i],u),e[1][i]=Math.max(e[1][i],u))}}}(this,f);var h=[1,1,1];for(o=0;o<3;++o)f[1][o]===f[0][o]?h[o]=1:h[o]=1/(f[1][o]-f[0][o]);for(this.dataScale=h,this.convertAnnotations(this),a=0;a<t.length;++a)!0===(n=t[a]).visible&&0!==n._length&&((i=this.traces[n.uid])?i.data.type===n.type?i.update(n):(i.dispose(),i=n._module.plot(this,n),this.traces[n.uid]=i):(i=n._module.plot(this,n),this.traces[n.uid]=i),i.name=n.name);var p=Object.keys(this.traces);t:for(a=0;a<p.length;++a){for(o=0;o<t.length;++o)if(t[o].uid===p[a]&&!0===t[o].visible&&0!==t[o]._length)continue t;(i=this.traces[p[a]]).dispose(),delete this.traces[p[a]]}this.glplot.objects.sort((function(t,e){return t._trace.data.index-e._trace.data.index}));var d,m=[[0,0,0],[0,0,0]],v=[],y={};for(a=0;a<3;++a){if((l=(s=c[k[a]]).type)in y?(y[l].acc*=h[a],y[l].count+=1):y[l]={acc:h[a],count:1},s.autorange){m[0][a]=1/0,m[1][a]=-1/0;var x=this.glplot.objects,b=this.fullSceneLayout.annotations||[],_=s._name.charAt(0);for(o=0;o<x.length;o++){var w=x[o],T=w.bounds,A=w._trace.data._pad||0;\"ErrorBars\"===w.constructor.name&&s._lowerLogErrorBound?m[0][a]=Math.min(m[0][a],s._lowerLogErrorBound):m[0][a]=Math.min(m[0][a],T[0][a]/h[a]-A),m[1][a]=Math.max(m[1][a],T[1][a]/h[a]+A)}for(o=0;o<b.length;o++){var S=b[o];if(S.visible){var E=s.r2l(S[_]);m[0][a]=Math.min(m[0][a],E),m[1][a]=Math.max(m[1][a],E)}}if(\"rangemode\"in s&&\"tozero\"===s.rangemode&&(m[0][a]=Math.min(m[0][a],0),m[1][a]=Math.max(m[1][a],0)),m[0][a]>m[1][a])m[0][a]=-1,m[1][a]=1;else{var C=m[1][a]-m[0][a];m[0][a]-=C/32,m[1][a]+=C/32}if(\"reversed\"===s.autorange){var L=m[0][a];m[0][a]=m[1][a],m[1][a]=L}}else{var I=s.range;m[0][a]=s.r2l(I[0]),m[1][a]=s.r2l(I[1])}m[0][a]===m[1][a]&&(m[0][a]-=1,m[1][a]+=1),v[a]=m[1][a]-m[0][a],this.glplot.setBounds(a,{min:m[0][a]*h[a],max:m[1][a]*h[a]})}var P=c.aspectmode;if(\"cube\"===P)d=[1,1,1];else if(\"manual\"===P){var z=c.aspectratio;d=[z.x,z.y,z.z]}else{if(\"auto\"!==P&&\"data\"!==P)throw new Error(\"scene.js aspectRatio was not one of the enumerated types\");var O=[1,1,1];for(a=0;a<3;++a){var D=y[l=(s=c[k[a]]).type];O[a]=Math.pow(D.acc,1/D.count)/h[a]}d=\"data\"===P||Math.max.apply(null,O)/Math.min.apply(null,O)<=4?O:[1,1,1]}c.aspectratio.x=u.aspectratio.x=d[0],c.aspectratio.y=u.aspectratio.y=d[1],c.aspectratio.z=u.aspectratio.z=d[2],this.glplot.setAspectratio(c.aspectratio),this.viewInitial.aspectratio||(this.viewInitial.aspectratio={x:c.aspectratio.x,y:c.aspectratio.y,z:c.aspectratio.z}),this.viewInitial.aspectmode||(this.viewInitial.aspectmode=c.aspectmode);var R=c.domain||null,F=e._size||null;if(R&&F){var B=this.container.style;B.position=\"absolute\",B.left=F.l+R.x[0]*F.w+\"px\",B.top=F.t+(1-R.y[1])*F.h+\"px\",B.width=F.w*(R.x[1]-R.x[0])+\"px\",B.height=F.h*(R.y[1]-R.y[0])+\"px\"}this.glplot.redraw()}},w.destroy=function(){this.glplot&&(this.camera.mouseListener.enabled=!1,this.container.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null,this.glplot.dispose(),this.container.parentNode.removeChild(this.container),this.glplot=null)},w.getCamera=function(){var t;return this.camera.view.recalcMatrix(this.camera.view.lastT()),{up:{x:(t=this.camera).up[0],y:t.up[1],z:t.up[2]},center:{x:t.center[0],y:t.center[1],z:t.center[2]},eye:{x:t.eye[0],y:t.eye[1],z:t.eye[2]},projection:{type:!0===t._ortho?\"orthographic\":\"perspective\"}}},w.setViewport=function(t){var e,r=t.camera;this.camera.lookAt.apply(this,[[(e=r).eye.x,e.eye.y,e.eye.z],[e.center.x,e.center.y,e.center.z],[e.up.x,e.up.y,e.up.z]]),this.glplot.setAspectratio(t.aspectratio),\"orthographic\"===r.projection.type!==this.camera._ortho&&(this.glplot.redraw(),this.glplot.clearRGBA(),this.glplot.dispose(),this.initializeGLPlot())},w.isCameraChanged=function(t){var e=this.getCamera(),r=f.nestedProperty(t,this.id+\".camera\").get();function n(t,e,r,n){var i=[\"up\",\"center\",\"eye\"],a=[\"x\",\"y\",\"z\"];return e[i[r]]&&t[i[r]][a[n]]===e[i[r]][a[n]]}var i=!1;if(void 0===r)i=!0;else{for(var a=0;a<3;a++)for(var o=0;o<3;o++)if(!n(e,r,a,o)){i=!0;break}(!r.projection||e.projection&&e.projection.type!==r.projection.type)&&(i=!0)}return i},w.isAspectChanged=function(t){var e=this.glplot.getAspectratio(),r=f.nestedProperty(t,this.id+\".aspectratio\").get();return void 0===r||r.x!==e.x||r.y!==e.y||r.z!==e.z},w.saveLayout=function(t){var e,r,n,i,a,o,s=this.fullLayout,l=this.isCameraChanged(t),c=this.isAspectChanged(t),h=l||c;if(h){var p={};if(l&&(e=this.getCamera(),n=(r=f.nestedProperty(t,this.id+\".camera\")).get(),p[this.id+\".camera\"]=n),c&&(i=this.glplot.getAspectratio(),o=(a=f.nestedProperty(t,this.id+\".aspectratio\")).get(),p[this.id+\".aspectratio\"]=o),u.call(\"_storeDirectGUIEdit\",t,s._preGUI,p),l)r.set(e),f.nestedProperty(s,this.id+\".camera\").set(e);if(c)a.set(i),f.nestedProperty(s,this.id+\".aspectratio\").set(i),this.glplot.redraw()}return h},w.updateFx=function(t,e){var r=this.camera;if(r)if(\"orbit\"===t)r.mode=\"orbit\",r.keyBindingMode=\"rotate\";else if(\"turntable\"===t){r.up=[0,0,1],r.mode=\"turntable\",r.keyBindingMode=\"rotate\";var n=this.graphDiv,i=n._fullLayout,a=this.fullSceneLayout.camera,o=a.up.x,s=a.up.y,l=a.up.z;if(l/Math.sqrt(o*o+s*s+l*l)<.999){var c=this.id+\".camera.up\",h={x:0,y:0,z:1},p={};p[c]=h;var 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r=t.visible;return\"undefined\"==typeof r||!0===r})),d=!1,g=p.map((function(t,e){return d=d||\"undefined\"!=typeof t.groupId,t}));if(d){var m=n.nest().key((function(t,e){return\"undefined\"!=typeof t.groupId?t.groupId:\"unstacked\"})).entries(g),v=[],y=m.map((function(t,e){if(\"unstacked\"===t.key)return t.values;var r=t.values[0].r.map((function(t,e){return 0}));return t.values.forEach((function(t,e,n){t.yStack=[r],v.push(r),r=o.util.sumArrays(t.r,r)})),t.values}));p=n.merge(y)}p.forEach((function(t,e){t.t=Array.isArray(t.t[0])?t.t:[t.t],t.r=Array.isArray(t.r[0])?t.r:[t.r]}));var x=Math.min(h.width-h.margin.left-h.margin.right,h.height-h.margin.top-h.margin.bottom)/2;x=Math.max(10,x);var b,_=[h.margin.left+x,h.margin.top+x];d?b=[0,n.max(o.util.sumArrays(o.util.arrayLast(p).r[0],o.util.arrayLast(v)))]:b=n.extent(o.util.flattenArray(p.map((function(t,e){return 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P=n.range.apply(this,C);if(P=P.map((function(t,e){return parseFloat(t.toPrecision(12))})),s=n.scale.linear().domain(C.slice(0,2)).range(\"clockwise\"===h.direction?[0,360]:[360,0]),u.layout.angularAxis.domain=s.domain(),u.layout.angularAxis.endPadding=A?E:0,\"undefined\"==typeof(t=n.select(this).select(\"svg.chart-root\"))||t.empty()){var z=(new DOMParser).parseFromString(\"<svg xmlns='http://www.w3.org/2000/svg' class='chart-root'>' + '<g class='outer-group'>' + '<g class='chart-group'>' + '<circle class='background-circle'></circle>' + '<g class='geometry-group'></g>' + '<g class='radial axis-group'>' + '<circle class='outside-circle'></circle>' + '</g>' + '<g class='angular axis-group'></g>' + '<g class='guides-group'><line></line><circle r='0'></circle></g>' + '</g>' + '<g class='legend-group'></g>' + '<g class='tooltips-group'></g>' + '<g class='title-group'><text></text></g>' + '</g>' + 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o=n.hsl(a.color).l,s=o>=.5?\"#aaa\":\"white\",u=o>=.5?\"black\":\"white\",f=i||\"\";e.style({fill:u,\"font-size\":a.fontSize+\"px\"}).text(f);var h=a.padding,p=e.node().getBBox(),d={fill:a.color,stroke:s,\"stroke-width\":\"2px\"},g=p.width+2*h+l,m=p.height+2*h;return r.attr({d:\"M\"+[[l,-m/2],[l,-m/4],[a.hasTick?0:l,0],[l,m/4],[l,m/2],[g,m/2],[g,-m/2]].join(\"L\")+\"Z\"}).style(d),t.attr({transform:\"translate(\"+[l,-m/2+2*h]+\")\"}),t.style({display:\"block\"}),c},c.move=function(e){if(t)return t.attr({transform:\"translate(\"+[e[0],e[1]]+\")\"}).style({display:\"block\"}),c},c.hide=function(){if(t)return t.style({display:\"none\"}),c},c.show=function(){if(t)return t.style({display:\"block\"}),c},c.config=function(t){return i(a,t),c},c},o.tooltipPanel.uid=1,o.adapter={},o.adapter.plotly=function(){var t={convert:function(t,e){var r={};if(t.data&&(r.data=t.data.map((function(t,r){var 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s=i({},t.layout);if([[s,[\"plot_bgcolor\"],[\"backgroundColor\"]],[s,[\"showlegend\"],[\"showLegend\"]],[s,[\"radialaxis\"],[\"radialAxis\"]],[s,[\"angularaxis\"],[\"angularAxis\"]],[s.angularaxis,[\"showline\"],[\"gridLinesVisible\"]],[s.angularaxis,[\"showticklabels\"],[\"labelsVisible\"]],[s.angularaxis,[\"nticks\"],[\"ticksCount\"]],[s.angularaxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.angularaxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.angularaxis,[\"range\"],[\"domain\"]],[s.angularaxis,[\"endpadding\"],[\"endPadding\"]],[s.radialaxis,[\"showline\"],[\"gridLinesVisible\"]],[s.radialaxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.radialaxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.radialaxis,[\"range\"],[\"domain\"]],[s.angularAxis,[\"showline\"],[\"gridLinesVisible\"]],[s.angularAxis,[\"showticklabels\"],[\"labelsVisible\"]],[s.angularAxis,[\"nticks\"],[\"ticksCount\"]],[s.angularAxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.angularAxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.angularAxis,[\"range\"],[\"domain\"]],[s.angularAxis,[\"endpadding\"],[\"endPadding\"]],[s.radialAxis,[\"showline\"],[\"gridLinesVisible\"]],[s.radialAxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.radialAxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.radialAxis,[\"range\"],[\"domain\"]],[s.font,[\"outlinecolor\"],[\"outlineColor\"]],[s.legend,[\"traceorder\"],[\"reverseOrder\"]],[s,[\"labeloffset\"],[\"labelOffset\"]],[s,[\"defaultcolorrange\"],[\"defaultColorRange\"]]].forEach((function(t,r){o.util.translator.apply(null,t.concat(e))})),e?(\"undefined\"!=typeof 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n=t(\"d3\"),i=t(\"tinycolor2\"),a=t(\"../../registry\"),o=t(\"../../lib\"),s=o.strRotate,l=o.strTranslate,c=t(\"../../components/color\"),u=t(\"../../components/drawing\"),f=t(\"../plots\"),h=t(\"../../plots/cartesian/axes\"),p=t(\"../cartesian/set_convert\"),d=t(\"./set_convert\"),g=t(\"../cartesian/autorange\").doAutoRange,m=t(\"../cartesian/dragbox\"),v=t(\"../../components/dragelement\"),y=t(\"../../components/fx\"),x=t(\"../../components/titles\"),b=t(\"../cartesian/select\").prepSelect,_=t(\"../cartesian/select\").selectOnClick,w=t(\"../cartesian/select\").clearSelect,T=t(\"../../lib/setcursor\"),k=t(\"../../lib/clear_gl_canvases\"),M=t(\"../../plot_api/subroutines\").redrawReglTraces,A=t(\"../../constants/alignment\").MID_SHIFT,S=t(\"./constants\"),E=t(\"./helpers\"),C=o._,L=o.mod,I=o.deg2rad,P=o.rad2deg;function 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e,r,n,i,a=t[0],o=t[1]-a,s=L(a,360),l=s+o,c=Math.cos(I(s)),u=Math.sin(I(s)),f=Math.cos(I(l)),h=Math.sin(I(l));i=s<=90&&l>=90||s>90&&l>=450?1:u<=0&&h<=0?0:Math.max(u,h);e=s<=180&&l>=180||s>180&&l>=540?-1:c>=0&&f>=0?0:Math.min(c,f);r=s<=270&&l>=270||s>270&&l>=630?-1:u>=0&&h>=0?0:Math.min(u,h);n=l>=360?1:c<=0&&f<=0?0:Math.max(c,f);return[e,r,n,i]}(p),b=x[2]-x[0],_=x[3]-x[1],w=h/f,T=Math.abs(_/b);w>T?(d=f,y=(h-(g=f*T))/n.h/2,m=[o[0],o[1]],v=[s[0]+y,s[1]-y]):(g=h,y=(f-(d=h/T))/n.w/2,m=[o[0]+y,o[1]-y],v=[s[0],s[1]]),this.xLength2=d,this.yLength2=g,this.xDomain2=m,this.yDomain2=v;var 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e=m(t),r=Math.cos(e),n=Math.sin(e);return\"M\"+[f+u*r,p-u*n]+\"L\"+[f+a*r,p-a*n]},transFn:o.noop,crisp:!1}),h.drawLabels(n,g,{vals:w,layer:i[\"angular-axis\"],repositionOnUpdate:!0,transFn:function(t){return v(m(t))},labelFns:x})}F(i[\"angular-line\"].select(\"path\"),d.showline,{d:r.pathSubplot(),transform:l(f,p)}).attr(\"stroke-width\",d.linewidth).call(c.stroke,d.linecolor)},O.updateFx=function(t,e){this.gd._context.staticPlot||(this.updateAngularDrag(t),this.updateRadialDrag(t,e,0),this.updateRadialDrag(t,e,1),this.updateMainDrag(t))},O.updateMainDrag=function(t){var e,r,s=this,c=s.gd,u=s.layers,f=t._zoomlayer,h=S.MINZOOM,p=S.OFFEDGE,d=s.radius,g=s.innerRadius,x=s.cx,T=s.cy,k=s.cxx,M=s.cyy,A=s.sectorInRad,C=s.vangles,L=s.radialAxis,I=E.clampTiny,P=E.findXYatLength,z=E.findEnclosingVertexAngles,O=S.cornerHalfWidth,D=S.cornerLen/2,R=m.makeDragger(u,\"path\",\"maindrag\",\"crosshair\");n.select(R).attr(\"d\",s.pathSubplot()).attr(\"transform\",l(x,T));var F,B,N,j,U,V,q,H,G,Y={element:R,gd:c,subplot:s.id,plotinfo:{id:s.id,xaxis:s.xaxis,yaxis:s.yaxis},xaxes:[s.xaxis],yaxes:[s.yaxis]};function W(t,e){return Math.sqrt(t*t+e*e)}function X(t,e){return W(t-k,e-M)}function Z(t,e){return Math.atan2(M-e,t-k)}function J(t,e){return[t*Math.cos(e),t*Math.sin(-e)]}function K(t,e){if(0===t)return s.pathSector(2*O);var r=D/t,n=e-r,i=e+r,a=Math.max(0,Math.min(t,d)),o=a-O,l=a+O;return\"M\"+J(o,n)+\"A\"+[o,o]+\" 0,0,0 \"+J(o,i)+\"L\"+J(l,i)+\"A\"+[l,l]+\" 0,0,1 \"+J(l,n)+\"Z\"}function Q(t,e,r){if(0===t)return s.pathSector(2*O);var n,i,a=J(t,e),o=J(t,r),l=I((a[0]+o[0])/2),c=I((a[1]+o[1])/2);if(l&&c){var u=c/l,f=-1/u,h=P(O,u,l,c);n=P(D,f,h[0][0],h[0][1]),i=P(D,f,h[1][0],h[1][1])}else{var p,d;c?(p=D,d=O):(p=O,d=D),n=[[l-p,c-d],[l+p,c-d]],i=[[l-p,c+d],[l+p,c+d]]}return\"M\"+n.join(\"L\")+\"L\"+i.reverse().join(\"L\")+\"Z\"}function $(t,e){return 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e=L._rl,r=(e[1]-e[0])/(1-g/d)/d,n=[e[0]+(N-g)*r,e[0]+(j-g)*r];t[s.id+\".radialaxis.range\"]=n}function ot(t,e){var r=c._fullLayout.clickmode;if(m.removeZoombox(c),2===t){var n={};for(var i in s.viewInitial)n[s.id+\".\"+i]=s.viewInitial[i];c.emit(\"plotly_doubleclick\",null),a.call(\"_guiRelayout\",c,n)}r.indexOf(\"select\")>-1&&1===t&&_(e,c,[s.xaxis],[s.yaxis],s.id,Y),r.indexOf(\"event\")>-1&&y.click(c,e,s.id)}Y.prepFn=function(t,n,a){var l=c._fullLayout.dragmode,u=R.getBoundingClientRect();c._fullLayout._calcInverseTransform(c);var h=c._fullLayout._invTransform;e=c._fullLayout._invScaleX,r=c._fullLayout._invScaleY;var p=o.apply3DTransform(h)(n-u.left,a-u.top);if(F=p[0],B=p[1],C){var g=E.findPolygonOffset(d,A[0],A[1],C);F+=k+g[0],B+=M+g[1]}switch(l){case\"zoom\":Y.moveFn=C?nt:et,Y.clickFn=ot,Y.doneFn=it,function(){N=null,j=null,U=s.pathSubplot(),V=!1;var t=c._fullLayout[s.id];q=i(t.bgcolor).getLuminance(),(H=m.makeZoombox(f,q,x,T,U)).attr(\"fill-rule\",\"evenodd\"),G=m.makeCorners(f,x,T),w(c)}();break;case\"select\":case\"lasso\":b(t,n,a,Y,l)}},R.onmousemove=function(t){y.hover(c,t,s.id),c._fullLayout._lasthover=R,c._fullLayout._hoversubplot=s.id},R.onmouseout=function(t){c._dragging||v.unhover(c,t)},v.init(Y)},O.updateRadialDrag=function(t,e,r){var i=this,c=i.gd,u=i.layers,f=i.radius,h=i.innerRadius,p=i.cx,d=i.cy,g=i.radialAxis,y=S.radialDragBoxSize,x=y/2;if(g.visible){var b,_,T,A=I(i.radialAxisAngle),E=g._rl,C=E[0],L=E[1],z=E[r],O=.75*(E[1]-E[0])/(1-e.hole)/f;r?(b=p+(f+x)*Math.cos(A),_=d-(f+x)*Math.sin(A),T=\"radialdrag\"):(b=p+(h-x)*Math.cos(A),_=d-(h-x)*Math.sin(A),T=\"radialdrag-inner\");var D,B,N,j=m.makeRectDragger(u,T,\"crosshair\",-x,-x,y,y),U={element:j,gd:c};F(n.select(j),g.visible&&h<f,{transform:l(b,_)}),U.prepFn=function(){D=null,B=null,N=null,U.moveFn=V,U.doneFn=q,w(c)},U.clampFn=function(t,e){return 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v=e.gd._fullLayout,y=v[e.id],x=_(A+c*t._invScaleX,E+m*t._invScaleY),b=P(x-z);if(L=C+b,i.frontplot.attr(\"transform\",l(e.xOffset2,e.yOffset2)+s([-b,d,g])),e.vangles){I=e.radialAxisAngle+b;var w=l(h,p)+s(-b),T=l(h,p)+s(-I);i.bg.attr(\"transform\",w),i[\"radial-grid\"].attr(\"transform\",w),i[\"radial-axis\"].attr(\"transform\",T),i[\"radial-line\"].select(\"line\").attr(\"transform\",T),e.updateRadialAxisTitle(v,y,I)}else e.clipPaths.forTraces.select(\"path\").attr(\"transform\",l(d,g)+s(b));D.each((function(){var t=n.select(this),e=u.getTranslate(t);t.attr(\"transform\",l(e.x,e.y)+s([b]))})),R.each((function(){var t=n.select(this),e=t.select(\"text\"),r=u.getTranslate(t);t.attr(\"transform\",s([b,e.attr(\"x\"),e.attr(\"y\")])+l(r.x,r.y))})),f.rotation=o.modHalf(L,360),e.updateAngularAxis(v,y),e._hasClipOnAxisFalse&&!o.isFullCircle(e.sectorInRad)&&O.call(u.hideOutsideRangePoints,e);var S=!1;for(var F in e.traceHash)if(a.traceIs(F,\"gl\")){var 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x={};x[h]=[v/d,(v+1)/d],a(l,e,m,x),o.id=y,f(s,l,m,o)}}},{\"../lib\":778,\"../plot_api/plot_template\":817,\"./domain\":855}],906:[function(t,e,r){\"use strict\";['Variables are inserted using %{variable}, for example \"y: %{y}\".','Numbers are formatted using d3-format\\'s syntax %{variable:d3-format}, for example \"Price: %{y:$.2f}\".',t(\"../constants/docs\").FORMAT_LINK,\"for details on the formatting syntax.\",'Dates are formatted using d3-time-format\\'s syntax %{variable|d3-time-format}, for example \"Day: %{2019-01-01|%A}\".',t(\"../constants/docs\").DATE_FORMAT_LINK,\"for details on the date formatting syntax.\"].join(\" \");function n(t){var e=t.description?\" \"+t.description:\"\",r=t.keys||[];if(r.length>0){for(var n=[],i=0;i<r.length;i++)n[i]=\"`\"+r[i]+\"`\";e+=\"Finally, the template string has access to \",e=1===r.length?\"variable \"+n[0]:\"variables \"+n.slice(0,-1).join(\", \")+\" and \"+n.slice(-1)+\".\"}return e}r.hovertemplateAttrs=function(t,e){t=t||{};n(e=e||{});var r={valType:\"string\",dflt:\"\",editType:t.editType||\"none\"};return!1!==t.arrayOk&&(r.arrayOk=!0),r},r.texttemplateAttrs=function(t,e){t=t||{};n(e=e||{});var r={valType:\"string\",dflt:\"\",editType:t.editType||\"calc\"};return!1!==t.arrayOk&&(r.arrayOk=!0),r}},{\"../constants/docs\":748}],907:[function(t,e,r){\"use strict\";var n=t(\"./ternary\"),i=t(\"../../plots/get_data\").getSubplotCalcData,a=t(\"../../lib\").counterRegex;r.name=\"ternary\";var o=r.attr=\"subplot\";r.idRoot=\"ternary\",r.idRegex=r.attrRegex=a(\"ternary\"),(r.attributes={})[o]={valType:\"subplotid\",dflt:\"ternary\",editType:\"calc\"},r.layoutAttributes=t(\"./layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout_defaults\"),r.plot=function(t){for(var e=t._fullLayout,r=t.calcdata,a=e._subplots.ternary,o=0;o<a.length;o++){var s=a[o],l=i(r,\"ternary\",s),c=e[s]._subplot;c||(c=new 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n=t(\"../../components/color/attributes\"),i=t(\"../domain\").attributes,a=t(\"../cartesian/layout_attributes\"),o=t(\"../../plot_api/edit_types\").overrideAll,s=t(\"../../lib/extend\").extendFlat,l={title:{text:a.title.text,font:a.title.font},color:a.color,tickmode:a.tickmode,nticks:s({},a.nticks,{dflt:6,min:1}),tick0:a.tick0,dtick:a.dtick,tickvals:a.tickvals,ticktext:a.ticktext,ticks:a.ticks,ticklen:a.ticklen,tickwidth:a.tickwidth,tickcolor:a.tickcolor,showticklabels:a.showticklabels,showtickprefix:a.showtickprefix,tickprefix:a.tickprefix,showticksuffix:a.showticksuffix,ticksuffix:a.ticksuffix,showexponent:a.showexponent,exponentformat:a.exponentformat,minexponent:a.minexponent,separatethousands:a.separatethousands,tickfont:a.tickfont,tickangle:a.tickangle,tickformat:a.tickformat,tickformatstops:a.tickformatstops,hoverformat:a.hoverformat,showline:s({},a.showline,{dflt:!0}),linecolor:a.linecolor,linewidth:a.linewidth,showgrid:s({},a.showgrid,{dflt:!0}),gridcolor:a.gridcolor,gridwidth:a.gridwidth,layer:a.layer,min:{valType:\"number\",dflt:0,min:0},_deprecated:{title:a._deprecated.title,titlefont:a._deprecated.titlefont}},c=e.exports=o({domain:i({name:\"ternary\"}),bgcolor:{valType:\"color\",dflt:n.background},sum:{valType:\"number\",dflt:1,min:0},aaxis:l,baxis:l,caxis:l},\"plot\",\"from-root\");c.uirevision={valType:\"any\",editType:\"none\"},c.aaxis.uirevision=c.baxis.uirevision=c.caxis.uirevision={valType:\"any\",editType:\"none\"}},{\"../../components/color/attributes\":642,\"../../lib/extend\":768,\"../../plot_api/edit_types\":810,\"../cartesian/layout_attributes\":842,\"../domain\":855}],909:[function(t,e,r){\"use 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n=t(\"d3\"),i=t(\"tinycolor2\"),a=t(\"../../registry\"),o=t(\"../../lib\"),s=o.strTranslate,l=o._,c=t(\"../../components/color\"),u=t(\"../../components/drawing\"),f=t(\"../cartesian/set_convert\"),h=t(\"../../lib/extend\").extendFlat,p=t(\"../plots\"),d=t(\"../cartesian/axes\"),g=t(\"../../components/dragelement\"),m=t(\"../../components/fx\"),v=t(\"../../components/dragelement/helpers\"),y=v.freeMode,x=v.rectMode,b=t(\"../../components/titles\"),_=t(\"../cartesian/select\").prepSelect,w=t(\"../cartesian/select\").selectOnClick,T=t(\"../cartesian/select\").clearSelect,k=t(\"../cartesian/select\").clearSelectionsCache,M=t(\"../cartesian/constants\");function A(t,e){this.id=t.id,this.graphDiv=t.graphDiv,this.init(e),this.makeFramework(e),this.aTickLayout=null,this.bTickLayout=null,this.cTickLayout=null}e.exports=A;var S=A.prototype;S.init=function(t){this.container=t._ternarylayer,this.defs=t._defs,this.layoutId=t._uid,this.traceHash={},this.layers={}},S.plot=function(t,e){var r=e[this.id],n=e._size;this._hasClipOnAxisFalse=!1;for(var i=0;i<t.length;i++){if(!1===t[i][0].trace.cliponaxis){this._hasClipOnAxisFalse=!0;break}}this.updateLayers(r),this.adjustLayout(r,n),p.generalUpdatePerTraceModule(this.graphDiv,this,t,r),this.layers.plotbg.select(\"path\").call(c.fill,r.bgcolor)},S.makeFramework=function(t){var e=this.graphDiv,r=t[this.id],n=this.clipId=\"clip\"+this.layoutId+this.id,i=this.clipIdRelative=\"clip-relative\"+this.layoutId+this.id;this.clipDef=o.ensureSingleById(t._clips,\"clipPath\",n,(function(t){t.append(\"path\").attr(\"d\",\"M0,0Z\")})),this.clipDefRelative=o.ensureSingleById(t._clips,\"clipPath\",i,(function(t){t.append(\"path\").attr(\"d\",\"M0,0Z\")})),this.plotContainer=o.ensureSingle(this.container,\"g\",this.id),this.updateLayers(r),u.setClipUrl(this.layers.backplot,n,e),u.setClipUrl(this.layers.grids,n,e)},S.updateLayers=function(t){var e=this.layers,r=[\"draglayer\",\"plotbg\",\"backplot\",\"grids\"];\"below 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E=Math.sqrt(4/3);S.adjustLayout=function(t,e){var r,n,i,a,o,l,p=this,d=t.domain,g=(d.x[0]+d.x[1])/2,m=(d.y[0]+d.y[1])/2,v=d.x[1]-d.x[0],y=d.y[1]-d.y[0],x=v*e.w,b=y*e.h,_=t.sum,w=t.aaxis.min,T=t.baxis.min,k=t.caxis.min;x>E*b?i=(a=b)*E:a=(i=x)/E,o=v*i/x,l=y*a/b,r=e.l+e.w*g-i/2,n=e.t+e.h*(1-m)-a/2,p.x0=r,p.y0=n,p.w=i,p.h=a,p.sum=_,p.xaxis={type:\"linear\",range:[w+2*k-_,_-w-2*T],domain:[g-o/2,g+o/2],_id:\"x\"},f(p.xaxis,p.graphDiv._fullLayout),p.xaxis.setScale(),p.xaxis.isPtWithinRange=function(t){return t.a>=p.aaxis.range[0]&&t.a<=p.aaxis.range[1]&&t.b>=p.baxis.range[1]&&t.b<=p.baxis.range[0]&&t.c>=p.caxis.range[1]&&t.c<=p.caxis.range[0]},p.yaxis={type:\"linear\",range:[w,_-T-k],domain:[m-l/2,m+l/2],_id:\"y\"},f(p.yaxis,p.graphDiv._fullLayout),p.yaxis.setScale(),p.yaxis.isPtWithinRange=function(){return!0};var M=p.yaxis.domain[0],A=p.aaxis=h({},t.aaxis,{range:[w,_-T-k],side:\"left\",tickangle:(+t.aaxis.tickangle||0)-30,domain:[M,M+l*E],anchor:\"free\",position:0,_id:\"y\",_length:i});f(A,p.graphDiv._fullLayout),A.setScale();var S=p.baxis=h({},t.baxis,{range:[_-w-k,T],side:\"bottom\",domain:p.xaxis.domain,anchor:\"free\",position:0,_id:\"x\",_length:i});f(S,p.graphDiv._fullLayout),S.setScale();var C=p.caxis=h({},t.caxis,{range:[_-w-T,k],side:\"right\",tickangle:(+t.caxis.tickangle||0)+30,domain:[M,M+l*E],anchor:\"free\",position:0,_id:\"y\",_length:i});f(C,p.graphDiv._fullLayout),C.setScale();var L=\"M\"+r+\",\"+(n+a)+\"h\"+i+\"l-\"+i/2+\",-\"+a+\"Z\";p.clipDef.select(\"path\").attr(\"d\",L),p.layers.plotbg.select(\"path\").attr(\"d\",L);var I=\"M0,\"+a+\"h\"+i+\"l-\"+i/2+\",-\"+a+\"Z\";p.clipDefRelative.select(\"path\").attr(\"d\",I);var P=s(r,n);p.plotContainer.selectAll(\".scatterlayer,.maplayer\").attr(\"transform\",P),p.clipDefRelative.select(\"path\").attr(\"transform\",null);var z=s(r-S._offset,n+a);p.layers.baxis.attr(\"transform\",z),p.layers.bgrid.attr(\"transform\",z);var O=s(r+i/2,n)+\"rotate(30)\"+s(0,-A._offset);p.layers.aaxis.attr(\"transform\",O),p.layers.agrid.attr(\"transform\",O);var D=s(r+i/2,n)+\"rotate(-30)\"+s(0,-C._offset);p.layers.caxis.attr(\"transform\",D),p.layers.cgrid.attr(\"transform\",D),p.drawAxes(!0),p.layers.aline.select(\"path\").attr(\"d\",A.showline?\"M\"+r+\",\"+(n+a)+\"l\"+i/2+\",-\"+a:\"M0,0\").call(c.stroke,A.linecolor||\"#000\").style(\"stroke-width\",(A.linewidth||0)+\"px\"),p.layers.bline.select(\"path\").attr(\"d\",S.showline?\"M\"+r+\",\"+(n+a)+\"h\"+i:\"M0,0\").call(c.stroke,S.linecolor||\"#000\").style(\"stroke-width\",(S.linewidth||0)+\"px\"),p.layers.cline.select(\"path\").attr(\"d\",C.showline?\"M\"+(r+i/2)+\",\"+n+\"l\"+i/2+\",\"+a:\"M0,0\").call(c.stroke,C.linecolor||\"#000\").style(\"stroke-width\",(C.linewidth||0)+\"px\"),p.graphDiv._context.staticPlot||p.initInteractions(),u.setClipUrl(p.layers.frontplot,p._hasClipOnAxisFalse?null:p.clipId,p.graphDiv)},S.drawAxes=function(t){var 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n=t(\"../pie/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../plots/domain\").attributes,o=t(\"../../plots/template_attributes\").hovertemplateAttrs,s=t(\"../../plots/template_attributes\").texttemplateAttrs,l=t(\"../../lib/extend\").extendFlat;e.exports={labels:n.labels,label0:n.label0,dlabel:n.dlabel,values:n.values,marker:{colors:n.marker.colors,line:{color:l({},n.marker.line.color,{dflt:null}),width:l({},n.marker.line.width,{dflt:1}),editType:\"calc\"},editType:\"calc\"},text:n.text,hovertext:n.hovertext,scalegroup:l({},n.scalegroup,{}),textinfo:l({},n.textinfo,{flags:[\"label\",\"text\",\"value\",\"percent\"]}),texttemplate:s({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"text\",\"percent\"]}),hoverinfo:l({},i.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:o({},{keys:[\"label\",\"color\",\"value\",\"text\",\"percent\"]}),textposition:l({},n.textposition,{values:[\"inside\",\"none\"],dflt:\"inside\"}),textfont:n.textfont,insidetextfont:n.insidetextfont,title:{text:n.title.text,font:n.title.font,position:l({},n.title.position,{values:[\"top 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n=t(\"../../lib\"),i=t(\"./attributes\"),a=t(\"../../plots/domain\").defaults,o=t(\"../bar/defaults\").handleText,s=t(\"../pie/defaults\").handleLabelsAndValues;e.exports=function(t,e,r,l){function c(r,a){return n.coerce(t,e,i,r,a)}var u=c(\"labels\"),f=c(\"values\"),h=s(u,f),p=h.len;if(e._hasLabels=h.hasLabels,e._hasValues=h.hasValues,!e._hasLabels&&e._hasValues&&(c(\"label0\"),c(\"dlabel\")),p){e._length=p,c(\"marker.line.width\")&&c(\"marker.line.color\",l.paper_bgcolor),c(\"marker.colors\"),c(\"scalegroup\");var d,g=c(\"text\"),m=c(\"texttemplate\");if(m||(d=c(\"textinfo\",Array.isArray(g)?\"text+percent\":\"percent\")),c(\"hovertext\"),c(\"hovertemplate\"),m||d&&\"none\"!==d){var v=c(\"textposition\");o(t,e,l,c,v,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1})}a(e,l,c),c(\"title.text\")&&(c(\"title.position\"),n.coerceFont(c,\"title.font\",l.font)),c(\"aspectratio\"),c(\"baseratio\")}else 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n=t(\"../pie/layout_attributes\").hiddenlabels;e.exports={hiddenlabels:n,funnelareacolorway:{valType:\"colorlist\",editType:\"calc\"},extendfunnelareacolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{\"../pie/layout_attributes\":1168}],1062:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"funnelareacolorway\",e.colorway),r(\"extendfunnelareacolors\")}},{\"../../lib\":778,\"./layout_attributes\":1061}],1063:[function(t,e,r){\"use strict\";var 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0===d._deltaLastValue&&(d._deltaLastValue=a(r[0]));var l=C.select(\"text.delta\");function p(){l.text(o(a(r[0]),i)).call(m.fill,s(r[0])).call(f.convertToTspans,t)}return l.call(c.font,d.delta.font).call(m.fill,s({delta:d._deltaLastValue})),b(S)?l.transition().duration(S.duration).ease(S.easing).tween(\"text\",(function(){var t=n.select(this),e=a(r[0]),l=d._deltaLastValue,c=P(d.delta.valueformat,i,l,e),u=n.interpolateNumber(l,e);return d._deltaLastValue=e,function(e){t.text(o(u(e),c)),t.call(m.fill,s({delta:u(e)}))}})).each(\"end\",(function(){p(),E&&E()})).each(\"interrupt\",(function(){p(),E&&E()})):p(),u=k(o(a(r[0]),i),d.delta.font,A,t),l}(),O+=d.delta.position+d.delta.font.size+d.delta.font.family+d.delta.valueformat,O+=d.delta.increasing.symbol+d.delta.decreasing.symbol,p=u);d._hasNumber&&(!function(){var e=w(t,{tickformat:d.number.valueformat},d._range);e.setScale(),h.prepTicks(e);var i=function(t){return h.tickText(e,t).text},a=d.number.suffix,o=d.number.prefix,s=C.select(\"text.number\");function u(){var e=\"number\"==typeof r[0].y?o+i(r[0].y)+a:\"-\";s.text(e).call(c.font,d.number.font).call(f.convertToTspans,t)}b(S)?s.transition().duration(S.duration).ease(S.easing).each(\"end\",(function(){u(),E&&E()})).each(\"interrupt\",(function(){u(),E&&E()})).attrTween(\"text\",(function(){var t=n.select(this),e=n.interpolateNumber(r[0].lastY,r[0].y);d._lastValue=r[0].y;var s=P(d.number.valueformat,i,r[0].lastY,r[0].y);return function(r){t.text(o+s(e(r))+a)}})):u(),l=k(o+i(r[0].y)+a,d.number.font,A,t)}(),O+=d.number.font.size+d.number.font.family+d.number.valueformat+d.number.suffix+d.number.prefix,p=l);if(d._hasDelta&&d._hasNumber){var D,R,F=[(l.left+l.right)/2,(l.top+l.bottom)/2],B=[(u.left+u.right)/2,(u.top+u.bottom)/2],N=.75*d.delta.font.size;\"left\"===d.delta.position&&(D=M(d,\"deltaPos\",0,-1*(l.width*y[d.align]+u.width*(1-y[d.align])+N),O,Math.min),R=F[1]-B[1],p={width:l.width+u.width+N,height:Math.max(l.height,u.height),left:u.left+D,right:l.right,top:Math.min(l.top,u.top+R),bottom:Math.max(l.bottom,u.bottom+R)}),\"right\"===d.delta.position&&(D=M(d,\"deltaPos\",0,l.width*(1-y[d.align])+u.width*y[d.align]+N,O,Math.max),R=F[1]-B[1],p={width:l.width+u.width+N,height:Math.max(l.height,u.height),left:l.left,right:u.right+D,top:Math.min(l.top,u.top+R),bottom:Math.max(l.bottom,u.bottom+R)}),\"bottom\"===d.delta.position&&(D=null,R=u.height,p={width:Math.max(l.width,u.width),height:l.height+u.height,left:Math.min(l.left,u.left),right:Math.max(l.right,u.right),top:l.bottom-l.height,bottom:l.bottom+u.height}),\"top\"===d.delta.position&&(D=null,R=l.top,p={width:Math.max(l.width,u.width),height:l.height+u.height,left:Math.min(l.left,u.left),right:Math.max(l.right,u.right),top:l.bottom-l.height-u.height,bottom:l.bottom}),z.attr({dx:D,dy:R})}(d._hasNumber||d._hasDelta)&&C.attr(\"transform\",(function(){var t=s.numbersScaler(p);O+=t[2];var e,r=M(d,\"numbersScale\",1,t[0],O,Math.min);d._scaleNumbers||(r=1),e=d._isAngular?_-r*p.bottom:_-r*(p.top+p.bottom)/2,d._numbersTop=r*p.top+e;var n=p[T];\"center\"===T&&(n=(p.left+p.right)/2);var i=g-r*n;return i=M(d,\"numbersTranslate\",0,i,O,Math.max),o(i,e)+a(r)}))}(t,I,e,{numbersX:p,numbersY:A,numbersScaler:S,transitionOpts:r,onComplete:d}),P&&(E={range:L.gauge.axis.range,color:L.gauge.bgcolor,line:{color:L.gauge.bordercolor,width:0},thickness:1},C={range:L.gauge.axis.range,color:\"rgba(0, 0, 0, 0)\",line:{color:L.gauge.bordercolor,width:L.gauge.borderwidth},thickness:1});var H=I.selectAll(\"g.angular\").data(z?e:[]);H.exit().remove();var G=I.selectAll(\"g.angularaxis\").data(z?e:[]);G.exit().remove(),z&&function(t,e,r,i){var a,c,u,f,p=r[0].trace,d=i.size,g=i.radius,m=i.innerRadius,v=i.gaugeBg,y=i.gaugeOutline,x=[d.l+d.w/2,d.t+d.h/2+g/2],T=i.gauge,k=i.layer,M=i.transitionOpts,A=i.onComplete,S=Math.PI/2;function E(t){var e=p.gauge.axis.range[0],r=(t-e)/(p.gauge.axis.range[1]-e)*Math.PI-S;return r<-S?-S:r>S?S:r}function C(t){return n.svg.arc().innerRadius((m+g)/2-t/2*(g-m)).outerRadius((m+g)/2+t/2*(g-m)).startAngle(-S)}function L(t){t.attr(\"d\",(function(t){return C(t.thickness).startAngle(E(t.range[0])).endAngle(E(t.range[1]))()}))}T.enter().append(\"g\").classed(\"angular\",!0),T.attr(\"transform\",o(x[0],x[1])),k.enter().append(\"g\").classed(\"angularaxis\",!0).classed(\"crisp\",!0),k.selectAll(\"g.xangularaxistick,path,text\").remove(),(a=w(t,p.gauge.axis)).type=\"linear\",a.range=p.gauge.axis.range,a._id=\"xangularaxis\",a.setScale();var I=function(t){return(a.range[0]-t.x)/(a.range[1]-a.range[0])*Math.PI+Math.PI},P={},z=h.makeLabelFns(a,0).labelStandoff;P.xFn=function(t){var e=I(t);return Math.cos(e)*z},P.yFn=function(t){var e=I(t),r=Math.sin(e)>0?.2:1;return-Math.sin(e)*(z+t.fontSize*r)+Math.abs(Math.cos(e))*(t.fontSize*l)},P.anchorFn=function(t){var e=I(t),r=Math.cos(e);return Math.abs(r)<.1?\"middle\":r>0?\"start\":\"end\"},P.heightFn=function(t,e,r){var n=I(t);return-.5*(1+Math.sin(n))*r};var O=function(t){return o(x[0]+g*Math.cos(t),x[1]-g*Math.sin(t))};u=function(t){return O(I(t))};if(c=h.calcTicks(a),f=h.getTickSigns(a)[2],a.visible){f=\"inside\"===a.ticks?-1:1;var D=(a.linewidth||1)/2;h.drawTicks(t,a,{vals:c,layer:k,path:\"M\"+f*D+\",0h\"+f*a.ticklen,transFn:function(t){var e=I(t);return O(e)+\"rotate(\"+-s(e)+\")\"}}),h.drawLabels(t,a,{vals:c,layer:k,transFn:u,labelFns:P})}var R=[v].concat(p.gauge.steps),F=T.selectAll(\"g.bg-arc\").data(R);F.enter().append(\"g\").classed(\"bg-arc\",!0).append(\"path\"),F.select(\"path\").call(L).call(_),F.exit().remove();var B=C(p.gauge.bar.thickness),N=T.selectAll(\"g.value-arc\").data([p.gauge.bar]);N.enter().append(\"g\").classed(\"value-arc\",!0).append(\"path\");var j=N.select(\"path\");b(M)?(j.transition().duration(M.duration).ease(M.easing).each(\"end\",(function(){A&&A()})).each(\"interrupt\",(function(){A&&A()})).attrTween(\"d\",(U=B,V=E(r[0].lastY),q=E(r[0].y),function(){var t=n.interpolate(V,q);return function(e){return U.endAngle(t(e))()}})),p._lastValue=r[0].y):j.attr(\"d\",\"number\"==typeof r[0].y?B.endAngle(E(r[0].y)):\"M0,0Z\");var U,V,q;j.call(_),N.exit().remove(),R=[];var H=p.gauge.threshold.value;H&&R.push({range:[H,H],color:p.gauge.threshold.color,line:{color:p.gauge.threshold.line.color,width:p.gauge.threshold.line.width},thickness:p.gauge.threshold.thickness});var G=T.selectAll(\"g.threshold-arc\").data(R);G.enter().append(\"g\").classed(\"threshold-arc\",!0).append(\"path\"),G.select(\"path\").call(L).call(_),G.exit().remove();var Y=T.selectAll(\"g.gauge-outline\").data([y]);Y.enter().append(\"g\").classed(\"gauge-outline\",!0).append(\"path\"),Y.select(\"path\").call(L).call(_),Y.exit().remove()}(t,0,e,{radius:N,innerRadius:j,gauge:H,layer:G,size:R,gaugeBg:E,gaugeOutline:C,transitionOpts:r,onComplete:d});var Y=I.selectAll(\"g.bullet\").data(O?e:[]);Y.exit().remove();var W=I.selectAll(\"g.bulletaxis\").data(O?e:[]);W.exit().remove(),O&&function(t,e,r,n){var i,a,s,l,c,f=r[0].trace,p=n.gauge,d=n.layer,g=n.gaugeBg,v=n.gaugeOutline,y=n.size,x=f.domain,T=n.transitionOpts,k=n.onComplete;p.enter().append(\"g\").classed(\"bullet\",!0),p.attr(\"transform\",o(y.l,y.t)),d.enter().append(\"g\").classed(\"bulletaxis\",!0).classed(\"crisp\",!0),d.selectAll(\"g.xbulletaxistick,path,text\").remove();var M=y.h,A=f.gauge.bar.thickness*M,S=x.x[0],E=x.x[0]+(x.x[1]-x.x[0])*(f._hasNumber||f._hasDelta?1-u.bulletNumberDomainSize:1);(i=w(t,f.gauge.axis))._id=\"xbulletaxis\",i.domain=[S,E],i.setScale(),a=h.calcTicks(i),s=h.makeTransTickFn(i),l=h.getTickSigns(i)[2],c=y.t+y.h,i.visible&&(h.drawTicks(t,i,{vals:\"inside\"===i.ticks?h.clipEnds(i,a):a,layer:d,path:h.makeTickPath(i,c,l),transFn:s}),h.drawLabels(t,i,{vals:a,layer:d,transFn:s,labelFns:h.makeLabelFns(i,c)}));function C(t){t.attr(\"width\",(function(t){return Math.max(0,i.c2p(t.range[1])-i.c2p(t.range[0]))})).attr(\"x\",(function(t){return i.c2p(t.range[0])})).attr(\"y\",(function(t){return.5*(1-t.thickness)*M})).attr(\"height\",(function(t){return t.thickness*M}))}var L=[g].concat(f.gauge.steps),I=p.selectAll(\"g.bg-bullet\").data(L);I.enter().append(\"g\").classed(\"bg-bullet\",!0).append(\"rect\"),I.select(\"rect\").call(C).call(_),I.exit().remove();var P=p.selectAll(\"g.value-bullet\").data([f.gauge.bar]);P.enter().append(\"g\").classed(\"value-bullet\",!0).append(\"rect\"),P.select(\"rect\").attr(\"height\",A).attr(\"y\",(M-A)/2).call(_),b(T)?P.select(\"rect\").transition().duration(T.duration).ease(T.easing).each(\"end\",(function(){k&&k()})).each(\"interrupt\",(function(){k&&k()})).attr(\"width\",Math.max(0,i.c2p(Math.min(f.gauge.axis.range[1],r[0].y)))):P.select(\"rect\").attr(\"width\",\"number\"==typeof r[0].y?Math.max(0,i.c2p(Math.min(f.gauge.axis.range[1],r[0].y))):0);P.exit().remove();var z=r.filter((function(){return f.gauge.threshold.value})),O=p.selectAll(\"g.threshold-bullet\").data(z);O.enter().append(\"g\").classed(\"threshold-bullet\",!0).append(\"line\"),O.select(\"line\").attr(\"x1\",i.c2p(f.gauge.threshold.value)).attr(\"x2\",i.c2p(f.gauge.threshold.value)).attr(\"y1\",(1-f.gauge.threshold.thickness)/2*M).attr(\"y2\",(1-(1-f.gauge.threshold.thickness)/2)*M).call(m.stroke,f.gauge.threshold.line.color).style(\"stroke-width\",f.gauge.threshold.line.width),O.exit().remove();var D=p.selectAll(\"g.gauge-outline\").data([v]);D.enter().append(\"g\").classed(\"gauge-outline\",!0).append(\"rect\"),D.select(\"rect\").call(C).call(_),D.exit().remove()}(t,0,e,{gauge:Y,layer:W,size:R,gaugeBg:E,gaugeOutline:C,transitionOpts:r,onComplete:d});var X=I.selectAll(\"text.title\").data(e);X.exit().remove(),X.enter().append(\"text\").classed(\"title\",!0),X.attr(\"text-anchor\",(function(){return O?v.right:v[L.title.align]})).text(L.title.text).call(c.font,L.title.font).call(f.convertToTspans,t),X.attr(\"transform\",(function(){var t,e=R.l+R.w*y[L.title.align],r=u.titlePadding,n=c.bBox(X.node());if(P){if(z)if(L.gauge.axis.visible)t=c.bBox(G.node()).top-r-n.bottom;else t=R.t+R.h/2-N/2-n.bottom-r;O&&(t=A-(n.top+n.bottom)/2,e=R.l-u.bulletPadding*R.w)}else t=L._numbersTop-r-n.bottom;return o(e,t)}))}))}},{\"../../components/color\":643,\"../../components/drawing\":665,\"../../constants/alignment\":745,\"../../lib\":778,\"../../lib/svg_text_utils\":803,\"../../plots/cartesian/axes\":828,\"../../plots/cartesian/axis_defaults\":830,\"../../plots/cartesian/layout_attributes\":842,\"../../plots/cartesian/position_defaults\":845,\"./constants\":1119,d3:169}],1123:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/template_attributes\").hovertemplateAttrs,a=t(\"../mesh3d/attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../lib/extend\").extendFlat,l=t(\"../../plot_api/edit_types\").overrideAll;var c=e.exports=l(s({x:{valType:\"data_array\"},y:{valType:\"data_array\"},z:{valType:\"data_array\"},value:{valType:\"data_array\"},isomin:{valType:\"number\"},isomax:{valType:\"number\"},surface:{show:{valType:\"boolean\",dflt:!0},count:{valType:\"integer\",dflt:2,min:1},fill:{valType:\"number\",min:0,max:1,dflt:1},pattern:{valType:\"flaglist\",flags:[\"A\",\"B\",\"C\",\"D\",\"E\"],extras:[\"all\",\"odd\",\"even\"],dflt:\"all\"}},spaceframe:{show:{valType:\"boolean\",dflt:!1},fill:{valType:\"number\",min:0,max:1,dflt:.15}},slices:{x:{show:{valType:\"boolean\",dflt:!1},locations:{valType:\"data_array\",dflt:[]},fill:{valType:\"number\",min:0,max:1,dflt:1}},y:{show:{valType:\"boolean\",dflt:!1},locations:{valType:\"data_array\",dflt:[]},fill:{valType:\"number\",min:0,max:1,dflt:1}},z:{show:{valType:\"boolean\",dflt:!1},locations:{valType:\"data_array\",dflt:[]},fill:{valType:\"number\",min:0,max:1,dflt:1}}},caps:{x:{show:{valType:\"boolean\",dflt:!0},fill:{valType:\"number\",min:0,max:1,dflt:1}},y:{show:{valType:\"boolean\",dflt:!0},fill:{valType:\"number\",min:0,max:1,dflt:1}},z:{show:{valType:\"boolean\",dflt:!0},fill:{valType:\"number\",min:0,max:1,dflt:1}}},text:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertemplate:i(),showlegend:s({},o.showlegend,{dflt:!1})},n(\"\",{colorAttr:\"`value`\",showScaleDflt:!0,editTypeOverride:\"calc\"}),{opacity:a.opacity,lightposition:a.lightposition,lighting:a.lighting,flatshading:a.flatshading,contour:a.contour,hoverinfo:s({},o.hoverinfo)}),\"calc\",\"nested\");c.flatshading.dflt=!0,c.lighting.facenormalsepsilon.dflt=0,c.x.editType=c.y.editType=c.z.editType=c.value.editType=\"calc+clearAxisTypes\",c.transforms=void 0},{\"../../components/colorscale/attributes\":650,\"../../lib/extend\":768,\"../../plot_api/edit_types\":810,\"../../plots/attributes\":824,\"../../plots/template_attributes\":906,\"../mesh3d/attributes\":1128}],1124:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/calc\"),i=t(\"../streamtube/calc\").processGrid,a=t(\"../streamtube/calc\").filter;e.exports=function(t,e){e._len=Math.min(e.x.length,e.y.length,e.z.length,e.value.length),e._x=a(e.x,e._len),e._y=a(e.y,e._len),e._z=a(e.z,e._len),e._value=a(e.value,e._len);var r=i(e);e._gridFill=r.fill,e._Xs=r.Xs,e._Ys=r.Ys,e._Zs=r.Zs,e._len=r.len;for(var o=1/0,s=-1/0,l=0;l<e._len;l++){var c=e._value[l];o=Math.min(o,c),s=Math.max(s,c)}e._minValues=o,e._maxValues=s,e._vMin=void 0===e.isomin||null===e.isomin?o:e.isomin,e._vMax=void 0===e.isomax||null===e.isomin?s:e.isomax,n(t,e,{vals:[e._vMin,e._vMax],containerStr:\"\",cLetter:\"c\"})}},{\"../../components/colorscale/calc\":651,\"../streamtube/calc\":1295}],1125:[function(t,e,r){\"use strict\";var n=t(\"gl-mesh3d\"),i=t(\"../../lib/gl_format_color\").parseColorScale,a=t(\"../../lib/str2rgbarray\"),o=t(\"../../components/colorscale\").extractOpts,s=t(\"../../plots/gl3d/zip3\"),l=function(t,e){for(var r=e.length-1;r>0;r--){var n=Math.min(e[r],e[r-1]),i=Math.max(e[r],e[r-1]);if(i>n&&n<t&&t<=i)return{id:r,distRatio:(i-t)/(i-n)}}return{id:0,distRatio:0}};function c(t,e,r){this.scene=t,this.uid=r,this.mesh=e,this.name=\"\",this.data=null,this.showContour=!1}var u=c.prototype;u.handlePick=function(t){if(t.object===this.mesh){var e=t.data.index,r=this.data._meshX[e],n=this.data._meshY[e],i=this.data._meshZ[e],a=this.data._Ys.length,o=this.data._Zs.length,s=l(r,this.data._Xs).id,c=l(n,this.data._Ys).id,u=l(i,this.data._Zs).id,f=t.index=u+o*c+o*a*s;t.traceCoordinate=[this.data._meshX[f],this.data._meshY[f],this.data._meshZ[f],this.data._value[f]];var h=this.data.hovertext||this.data.text;return Array.isArray(h)&&void 0!==h[f]?t.textLabel=h[f]:h&&(t.textLabel=h),!0}},u.update=function(t){var e=this.scene,r=e.fullSceneLayout;function n(t,e,r,n){return e.map((function(e){return t.d2l(e,0,n)*r}))}this.data=h(t);var 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0),\"category descending\"===t.categoryorder&&(e=e.reverse())}return function(t,e){e=null==e?[]:e.map((function(t){return t}));var r={},n={},i=[];e.forEach((function(t,e){r[t]=0,n[t]=e}));for(var a=0;a<t.length;a++){var o,s=t[a];void 0===r[s]?(r[s]=1,o=e.push(s)-1,n[s]=o):(r[s]++,o=n[s]),i.push(o)}var l=e.map((function(t){return r[t]}));return{uniqueValues:e,uniqueCounts:l,inds:i}}(t.values,e)}));p=l.isArrayOrTypedArray(e.counts)?e.counts:[e.counts],function(t){var e;if(function(t){for(var e=new Array(t.length),r=0;r<t.length;r++){if(t[r]<0||t[r]>=t.length)return!1;if(void 0!==e[t[r]])return!1;e[t[r]]=!0}return!0}(t.map((function(t){return t.displayindex}))))for(e=0;e<t.length;e++)t[e]._displayindex=t[e].displayindex;else for(e=0;e<t.length;e++)t[e]._displayindex=e}(r),r.forEach((function(t,e){!function(t,e){t._categoryarray=e.uniqueValues,null===t.ticktext||void 0===t.ticktext?t._ticktext=[]:t._ticktext=t.ticktext.slice();for(var r=t._ticktext.length;r<e.uniqueValues.length;r++)t._ticktext.push(e.uniqueValues[r])}(t,m[e])}));var v,y=e.line;y?(i(e,\"line\")&&a(t,e,{vals:e.line.color,containerStr:\"line\",cLetter:\"c\"}),v=s.tryColorscale(y)):v=l.identity;var x,b,_,w,T,k=r[0].values.length,M={},A=m.map((function(t){return t.inds}));for(g=0,x=0;x<k;x++){var S=[];for(b=0;b<A.length;b++)S.push(A[b][x]);d=p[x%p.length],g+=d;var E=(_=x,w=void 0,T=void 0,l.isArrayOrTypedArray(y.color)?T=w=y.color[_%y.color.length]:w=y.color,{color:v(w),rawColor:T}),C=S+\"-\"+E.rawColor;void 0===M[C]&&(M[C]=f(S,E.color,E.rawColor)),h(M[C],x,d)}var L,I=r.map((function(t,e){return function(t,e,r,n,i){return{dimensionInd:t,containerInd:e,displayInd:r,dimensionLabel:n,count:i,categories:[],dragX:null}}(e,t._index,t._displayindex,t.label,g)}));for(x=0;x<k;x++)for(d=p[x%p.length],b=0;b<I.length;b++){var P=I[b].containerInd,z=m[b].inds[x],O=I[b].categories;if(void 0===O[z]){var D=e.dimensions[P]._categoryarray[z],R=e.dimensions[P]._ticktext[z];O[z]={dimensionInd:b,categoryInd:L=z,categoryValue:D,displayInd:L,categoryLabel:R,valueInds:[],count:0,dragY:null}}u(O[z],x,d)}return n(function(t,e,r){var n=t.map((function(t){return t.categories.length})).reduce((function(t,e){return Math.max(t,e)}));return{dimensions:t,paths:e,trace:void 0,maxCats:n,count:r}}(I,M,g))}},{\"../../components/colorscale/calc\":651,\"../../components/colorscale/helpers\":654,\"../../components/drawing\":665,\"../../lib\":778,\"../../lib/filter_unique.js\":769,\"../../lib/gup\":775,\"fast-isnumeric\":241}],1145:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/colorscale/helpers\").hasColorscale,a=t(\"../../components/colorscale/defaults\"),o=t(\"../../plots/domain\").defaults,s=t(\"../../plots/array_container_defaults\"),l=t(\"./attributes\"),c=t(\"../parcoords/merge_length\");function u(t,e){function r(r,i){return n.coerce(t,e,l.dimensions,r,i)}var i=r(\"values\"),a=r(\"visible\");if(i&&i.length||(a=e.visible=!1),a){r(\"label\"),r(\"displayindex\",e._index);var o,s=t.categoryarray,c=Array.isArray(s)&&s.length>0;c&&(o=\"array\");var u=r(\"categoryorder\",o);\"array\"===u?(r(\"categoryarray\"),r(\"ticktext\")):(delete t.categoryarray,delete t.ticktext),c||\"array\"!==u||(e.categoryorder=\"trace\")}}e.exports=function(t,e,r,f){function h(r,i){return n.coerce(t,e,l,r,i)}var p=s(t,e,{name:\"dimensions\",handleItemDefaults:u}),d=function(t,e,r,o,s){s(\"line.shape\"),s(\"line.hovertemplate\");var l=s(\"line.color\",o.colorway[0]);if(i(t,\"line\")&&n.isArrayOrTypedArray(l)){if(l.length)return s(\"line.colorscale\"),a(t,e,o,s,{prefix:\"line.\",cLetter:\"c\"}),l.length;e.line.color=r}return 1/0}(t,e,r,f,h);o(e,f,h),Array.isArray(p)&&p.length||(e.visible=!1),c(e,p,\"values\",d),h(\"hoveron\"),h(\"hovertemplate\"),h(\"arrangement\"),h(\"bundlecolors\"),h(\"sortpaths\"),h(\"counts\");var g={family:f.font.family,size:Math.round(f.font.size),color:f.font.color};n.coerceFont(h,\"labelfont\",g);var m={family:f.font.family,size:Math.round(f.font.size/1.2),color:f.font.color};n.coerceFont(h,\"tickfont\",m)}},{\"../../components/colorscale/defaults\":653,\"../../components/colorscale/helpers\":654,\"../../lib\":778,\"../../plots/array_container_defaults\":823,\"../../plots/domain\":855,\"../parcoords/merge_length\":1158,\"./attributes\":1142}],1146:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),plot:t(\"./plot\"),colorbar:{container:\"line\",min:\"cmin\",max:\"cmax\"},moduleType:\"trace\",name:\"parcats\",basePlotModule:t(\"./base_plot\"),categories:[\"noOpacity\"],meta:{}}},{\"./attributes\":1142,\"./base_plot\":1143,\"./calc\":1144,\"./defaults\":1145,\"./plot\":1148}],1147:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../plot_api/plot_api\"),a=t(\"../../components/fx\"),o=t(\"../../lib\"),s=o.strTranslate,l=t(\"../../components/drawing\"),c=t(\"tinycolor2\"),u=t(\"../../lib/svg_text_utils\");function f(t,e,r,i){var a=t.map(R.bind(0,e,r)),c=i.selectAll(\"g.parcatslayer\").data([null]);c.enter().append(\"g\").attr(\"class\",\"parcatslayer\").style(\"pointer-events\",\"all\");var f=c.selectAll(\"g.trace.parcats\").data(a,h),v=f.enter().append(\"g\").attr(\"class\",\"trace parcats\");f.attr(\"transform\",(function(t){return s(t.x,t.y)})),v.append(\"g\").attr(\"class\",\"paths\");var y=f.select(\"g.paths\").selectAll(\"path.path\").data((function(t){return t.paths}),h);y.attr(\"fill\",(function(t){return t.model.color}));var _=y.enter().append(\"path\").attr(\"class\",\"path\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.model.color})).attr(\"fill-opacity\",0);b(_),y.attr(\"d\",(function(t){return t.svgD})),_.empty()||y.sort(d),y.exit().remove(),y.on(\"mouseover\",g).on(\"mouseout\",m).on(\"click\",x),v.append(\"g\").attr(\"class\",\"dimensions\");var k=f.select(\"g.dimensions\").selectAll(\"g.dimension\").data((function(t){return t.dimensions}),h);k.enter().append(\"g\").attr(\"class\",\"dimension\"),k.attr(\"transform\",(function(t){return s(t.x,0)})),k.exit().remove();var M=k.selectAll(\"g.category\").data((function(t){return t.categories}),h),A=M.enter().append(\"g\").attr(\"class\",\"category\");M.attr(\"transform\",(function(t){return s(0,t.y)})),A.append(\"rect\").attr(\"class\",\"catrect\").attr(\"pointer-events\",\"none\"),M.select(\"rect.catrect\").attr(\"fill\",\"none\").attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})),w(A);var S=M.selectAll(\"rect.bandrect\").data((function(t){return t.bands}),h);S.each((function(){o.raiseToTop(this)})),S.attr(\"fill\",(function(t){return t.color}));var z=S.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.color})).attr(\"fill-opacity\",0);S.attr(\"fill\",(function(t){return t.color})).attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})).attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"perpendicular\"===t.parcatsViewModel.arrangement?\"ns-resize\":\"move\"})),T(z),S.exit().remove(),A.append(\"text\").attr(\"class\",\"catlabel\").attr(\"pointer-events\",\"none\");var O=e._fullLayout.paper_bgcolor;M.select(\"text.catlabel\").attr(\"text-anchor\",(function(t){return p(t)?\"start\":\"end\"})).attr(\"alignment-baseline\",\"middle\").style(\"text-shadow\",O+\" -1px  1px 2px, \"+O+\" 1px  1px 2px, \"+O+\"  1px -1px 2px, \"+O+\" -1px -1px 2px\").style(\"fill\",\"rgb(0, 0, 0)\").attr(\"x\",(function(t){return p(t)?t.width+5:-5})).attr(\"y\",(function(t){return t.height/2})).text((function(t){return t.model.categoryLabel})).each((function(t){l.font(n.select(this),t.parcatsViewModel.categorylabelfont),u.convertToTspans(n.select(this),e)})),A.append(\"text\").attr(\"class\",\"dimlabel\"),M.select(\"text.dimlabel\").attr(\"text-anchor\",\"middle\").attr(\"alignment-baseline\",\"baseline\").attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"ew-resize\"})).attr(\"x\",(function(t){return t.width/2})).attr(\"y\",-5).text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})).each((function(t){l.font(n.select(this),t.parcatsViewModel.labelfont)})),M.selectAll(\"rect.bandrect\").on(\"mouseover\",E).on(\"mouseout\",C),M.exit().remove(),k.call(n.behavior.drag().origin((function(t){return{x:t.x,y:0}})).on(\"dragstart\",L).on(\"drag\",I).on(\"dragend\",P)),f.each((function(t){t.traceSelection=n.select(this),t.pathSelection=n.select(this).selectAll(\"g.paths\").selectAll(\"path.path\"),t.dimensionSelection=n.select(this).selectAll(\"g.dimensions\").selectAll(\"g.dimension\")})),f.exit().remove()}function h(t){return t.key}function p(t){var e=t.parcatsViewModel.dimensions.length,r=t.parcatsViewModel.dimensions[e-1].model.dimensionInd;return t.model.dimensionInd===r}function d(t,e){return t.model.rawColor>e.model.rawColor?1:t.model.rawColor<e.model.rawColor?-1:0}function g(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){o.raiseToTop(this),_(n.select(this));var e=v(t),r=y(t);if(t.parcatsViewModel.graphDiv.emit(\"plotly_hover\",{points:e,event:n.event,constraints:r}),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\")){var i,s,l,u=n.mouse(this)[0],f=t.parcatsViewModel.graphDiv,h=t.parcatsViewModel.trace,p=f._fullLayout,d=p._paperdiv.node().getBoundingClientRect(),g=t.parcatsViewModel.graphDiv.getBoundingClientRect();for(l=0;l<t.leftXs.length-1;l++)if(t.leftXs[l]+t.dimWidths[l]-2<=u&&u<=t.leftXs[l+1]+2){var m=t.parcatsViewModel.dimensions[l],x=t.parcatsViewModel.dimensions[l+1];i=(m.x+m.width+x.x)/2,s=(t.topYs[l]+t.topYs[l+1]+t.height)/2;break}var b=t.parcatsViewModel.x+i,w=t.parcatsViewModel.y+s,T=c.mostReadable(t.model.color,[\"black\",\"white\"]),k=t.model.count,M=k/t.parcatsViewModel.model.count,A={countLabel:k,probabilityLabel:M.toFixed(3)},S=[];-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&S.push([\"Count:\",A.countLabel].join(\" \")),-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&S.push([\"P:\",A.probabilityLabel].join(\" \"));var E=S.join(\"<br>\"),C=n.mouse(f)[0];a.loneHover({trace:h,x:b-d.left+g.left,y:w-d.top+g.top,text:E,color:t.model.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:10,fontColor:T,idealAlign:C<b?\"right\":\"left\",hovertemplate:(h.line||{}).hovertemplate,hovertemplateLabels:A,eventData:[{data:h._input,fullData:h,count:k,probability:M}]},{container:p._hoverlayer.node(),outerContainer:p._paper.node(),gd:f})}}}function m(t){if(!t.parcatsViewModel.dragDimension&&(b(n.select(this)),a.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()),t.parcatsViewModel.pathSelection.sort(d),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\"))){var e=v(t),r=y(t);t.parcatsViewModel.graphDiv.emit(\"plotly_unhover\",{points:e,event:n.event,constraints:r})}}function v(t){for(var e=[],r=z(t.parcatsViewModel),n=0;n<t.model.valueInds.length;n++){var i=t.model.valueInds[n];e.push({curveNumber:r,pointNumber:i})}return e}function y(t){for(var e={},r=t.parcatsViewModel.model.dimensions,n=0;n<r.length;n++){var i=r[n],a=i.categories[t.model.categoryInds[n]];e[i.containerInd]=a.categoryValue}return void 0!==t.model.rawColor&&(e.color=t.model.rawColor),e}function x(t){if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){var e=v(t),r=y(t);t.parcatsViewModel.graphDiv.emit(\"plotly_click\",{points:e,event:n.event,constraints:r})}}function b(t){t.attr(\"fill\",(function(t){return t.model.color})).attr(\"fill-opacity\",.6).attr(\"stroke\",\"lightgray\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1)}function _(t){t.attr(\"fill-opacity\",.8).attr(\"stroke\",(function(t){return c.mostReadable(t.model.color,[\"black\",\"white\"])})).attr(\"stroke-width\",.3)}function w(t){t.select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",1).attr(\"stroke-opacity\",1)}function T(t){t.attr(\"stroke\",\"black\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1).attr(\"fill-opacity\",1)}function k(t){var e=t.parcatsViewModel.pathSelection,r=t.categoryViewModel.model.dimensionInd,n=t.categoryViewModel.model.categoryInd;return e.filter((function(e){return e.model.categoryInds[r]===n&&e.model.color===t.color}))}function M(t,e,r){var i=n.select(t).datum(),a=i.categoryViewModel.model,o=i.parcatsViewModel.graphDiv,s=n.select(t.parentNode).selectAll(\"rect.bandrect\"),l=[];s.each((function(t){k(t).each((function(t){Array.prototype.push.apply(l,v(t))}))}));var c={};c[a.dimensionInd]=a.categoryValue,o.emit(e,{points:l,event:r,constraints:c})}function A(t,e,r){var i=n.select(t).datum(),a=i.categoryViewModel.model,o=i.parcatsViewModel.graphDiv,s=k(i),l=[];s.each((function(t){Array.prototype.push.apply(l,v(t))}));var c={};c[a.dimensionInd]=a.categoryValue,void 0!==i.rawColor&&(c.color=i.rawColor),o.emit(e,{points:l,event:r,constraints:c})}function S(t,e,r){t._fullLayout._calcInverseTransform(t);var i,a,o=t._fullLayout._invScaleX,s=t._fullLayout._invScaleY,l=n.select(r.parentNode).select(\"rect.catrect\"),c=l.node().getBoundingClientRect(),u=l.datum(),f=u.parcatsViewModel,h=f.model.dimensions[u.model.dimensionInd],p=f.trace,d=c.top+c.height/2;f.dimensions.length>1&&h.displayInd===f.dimensions.length-1?(i=c.left,a=\"left\"):(i=c.left+c.width,a=\"right\");var g=u.model.count,m=u.model.categoryLabel,v=g/u.parcatsViewModel.model.count,y={countLabel:g,categoryLabel:m,probabilityLabel:v.toFixed(3)},x=[];-1!==u.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&x.push([\"Count:\",y.countLabel].join(\" \")),-1!==u.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&x.push([\"P(\"+y.categoryLabel+\"):\",y.probabilityLabel].join(\" \"));var b=x.join(\"<br>\");return{trace:p,x:o*(i-e.left),y:s*(d-e.top),text:b,color:\"lightgray\",borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", 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e=k(t);_(e),e.each((function(){o.raiseToTop(this)}))})),n.select(t.parentNode).select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",2.5)}(this),M(this,\"plotly_hover\",n.event)),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\"))\"category\"===l?e=S(r,s,this):\"color\"===l?e=function(t,e,r){t._fullLayout._calcInverseTransform(t);var i,a,o=t._fullLayout._invScaleX,s=t._fullLayout._invScaleY,l=r.getBoundingClientRect(),u=n.select(r).datum(),f=u.categoryViewModel,h=f.parcatsViewModel,p=h.model.dimensions[f.model.dimensionInd],d=h.trace,g=l.y+l.height/2;h.dimensions.length>1&&p.displayInd===h.dimensions.length-1?(i=l.left,a=\"left\"):(i=l.left+l.width,a=\"right\");var m=f.model.categoryLabel,v=u.parcatsViewModel.model.count,y=0;u.categoryViewModel.bands.forEach((function(t){t.color===u.color&&(y+=t.count)}));var x=f.model.count,b=0;h.pathSelection.each((function(t){t.model.color===u.color&&(b+=t.model.count)}));var _=y/v,w=y/b,T=y/x,k={countLabel:v,categoryLabel:m,probabilityLabel:_.toFixed(3)},M=[];-1!==f.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&M.push([\"Count:\",k.countLabel].join(\" \")),-1!==f.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&(M.push(\"P(color \\u2229 \"+m+\"): \"+k.probabilityLabel),M.push(\"P(\"+m+\" | color): \"+w.toFixed(3)),M.push(\"P(color | \"+m+\"): \"+T.toFixed(3)));var A=M.join(\"<br>\"),S=c.mostReadable(u.color,[\"black\",\"white\"]);return{trace:d,x:o*(i-e.left),y:s*(g-e.top),text:A,color:u.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontColor:S,fontSize:10,idealAlign:a,hovertemplate:d.hovertemplate,hovertemplateLabels:k,eventData:[{data:d._input,fullData:d,category:m,count:v,probability:_,categorycount:x,colorcount:b,bandcolorcount:y}]}}(r,s,this):\"dimension\"===l&&(e=function(t,e,r){var i=[];return n.select(r.parentNode.parentNode).selectAll(\"g.category\").select(\"rect.catrect\").each((function(){i.push(S(t,e,this))})),i}(r,s,this)),e&&a.loneHover(e,{container:i._hoverlayer.node(),outerContainer:i._paper.node(),gd:r})}}function C(t){var e=t.parcatsViewModel;if(!e.dragDimension&&(b(e.pathSelection),w(e.dimensionSelection.selectAll(\"g.category\")),T(e.dimensionSelection.selectAll(\"g.category\").selectAll(\"rect.bandrect\")),a.loneUnhover(e.graphDiv._fullLayout._hoverlayer.node()),e.pathSelection.sort(d),-1===e.hoverinfoItems.indexOf(\"skip\"))){\"color\"===t.parcatsViewModel.hoveron?A(this,\"plotly_unhover\",n.event):M(this,\"plotly_unhover\",n.event)}}function L(t){\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragDimensionDisplayInd=t.model.displayInd,t.initialDragDimensionDisplayInds=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),t.dragHasMoved=!1,t.dragCategoryDisplayInd=null,n.select(this).selectAll(\"g.category\").select(\"rect.catrect\").each((function(e){var r=n.mouse(this)[0],i=n.mouse(this)[1];-2<=r&&r<=e.width+2&&-2<=i&&i<=e.height+2&&(t.dragCategoryDisplayInd=e.model.displayInd,t.initialDragCategoryDisplayInds=t.model.categories.map((function(t){return t.displayInd})),e.model.dragY=e.y,o.raiseToTop(this.parentNode),n.select(this.parentNode).selectAll(\"rect.bandrect\").each((function(e){e.y<i&&i<=e.y+e.height&&(t.potentialClickBand=this)})))})),t.parcatsViewModel.dragDimension=t,a.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()))}function I(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragHasMoved=!0,null!==t.dragDimensionDisplayInd)){var e=t.dragDimensionDisplayInd,r=e-1,i=e+1,a=t.parcatsViewModel.dimensions[e];if(null!==t.dragCategoryDisplayInd){var o=a.categories[t.dragCategoryDisplayInd];o.model.dragY+=n.event.dy;var s=o.model.dragY,l=o.model.displayInd,c=a.categories,u=c[l-1],f=c[l+1];void 0!==u&&s<u.y+u.height/2&&(o.model.displayInd=u.model.displayInd,u.model.displayInd=l),void 0!==f&&s+o.height>f.y+f.height/2&&(o.model.displayInd=f.model.displayInd,f.model.displayInd=l),t.dragCategoryDisplayInd=o.model.displayInd}if(null===t.dragCategoryDisplayInd||\"freeform\"===t.parcatsViewModel.arrangement){a.model.dragX=n.event.x;var h=t.parcatsViewModel.dimensions[r],p=t.parcatsViewModel.dimensions[i];void 0!==h&&a.model.dragX<h.x+h.width&&(a.model.displayInd=h.model.displayInd,h.model.displayInd=e),void 0!==p&&a.model.dragX+a.width>p.x&&(a.model.displayInd=p.model.displayInd,p.model.displayInd=t.dragDimensionDisplayInd),t.dragDimensionDisplayInd=a.model.displayInd}N(t.parcatsViewModel),B(t.parcatsViewModel),D(t.parcatsViewModel),O(t.parcatsViewModel)}}function P(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&null!==t.dragDimensionDisplayInd){n.select(this).selectAll(\"text\").attr(\"font-weight\",\"normal\");var e={},r=z(t.parcatsViewModel),a=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),o=t.initialDragDimensionDisplayInds.some((function(t,e){return t!==a[e]}));o&&a.forEach((function(r,n){var i=t.parcatsViewModel.model.dimensions[n].containerInd;e[\"dimensions[\"+i+\"].displayindex\"]=r}));var s=!1;if(null!==t.dragCategoryDisplayInd){var l=t.model.categories.map((function(t){return t.displayInd}));if(s=t.initialDragCategoryDisplayInds.some((function(t,e){return t!==l[e]}))){var c=t.model.categories.slice().sort((function(t,e){return t.displayInd-e.displayInd})),u=c.map((function(t){return t.categoryValue})),f=c.map((function(t){return t.categoryLabel}));e[\"dimensions[\"+t.model.containerInd+\"].categoryarray\"]=[u],e[\"dimensions[\"+t.model.containerInd+\"].ticktext\"]=[f],e[\"dimensions[\"+t.model.containerInd+\"].categoryorder\"]=\"array\"}}if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")&&!t.dragHasMoved&&t.potentialClickBand&&(\"color\"===t.parcatsViewModel.hoveron?A(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent):M(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent)),t.model.dragX=null,null!==t.dragCategoryDisplayInd)t.parcatsViewModel.dimensions[t.dragDimensionDisplayInd].categories[t.dragCategoryDisplayInd].model.dragY=null,t.dragCategoryDisplayInd=null;t.dragDimensionDisplayInd=null,t.parcatsViewModel.dragDimension=null,t.dragHasMoved=null,t.potentialClickBand=null,N(t.parcatsViewModel),B(t.parcatsViewModel),n.transition().duration(300).ease(\"cubic-in-out\").each((function(){D(t.parcatsViewModel,!0),O(t.parcatsViewModel,!0)})).each(\"end\",(function(){(o||s)&&i.restyle(t.parcatsViewModel.graphDiv,e,[r])}))}}function z(t){for(var e,r=t.graphDiv._fullData,n=0;n<r.length;n++)if(t.key===r[n].uid){e=n;break}return e}function O(t,e){var r;void 0===e&&(e=!1),t.pathSelection.data((function(t){return t.paths}),h),(r=t.pathSelection,e?r.transition():r).attr(\"d\",(function(t){return t.svgD}))}function D(t,e){function r(t){return e?t.transition():t}void 0===e&&(e=!1),t.dimensionSelection.data((function(t){return t.dimensions}),h);var i=t.dimensionSelection.selectAll(\"g.category\").data((function(t){return t.categories}),h);r(t.dimensionSelection).attr(\"transform\",(function(t){return s(t.x,0)})),r(i).attr(\"transform\",(function(t){return s(0,t.y)})),i.select(\".dimlabel\").text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})),i.select(\".catlabel\").attr(\"text-anchor\",(function(t){return p(t)?\"start\":\"end\"})).attr(\"x\",(function(t){return p(t)?t.width+5:-5})).each((function(t){var e,r;p(t)?(e=t.width+5,r=\"start\"):(e=-5,r=\"end\"),n.select(this).selectAll(\"tspan\").attr(\"x\",e).attr(\"text-anchor\",r)}));var a=i.selectAll(\"rect.bandrect\").data((function(t){return t.bands}),h),l=a.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"cursor\",\"move\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.color})).attr(\"fill-opacity\",0);a.attr(\"fill\",(function(t){return t.color})).attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})),T(l),a.each((function(){o.raiseToTop(this)})),a.exit().remove()}function R(t,e,r){var n,i=r[0],a=e.margin||{l:80,r:80,t:100,b:80},o=i.trace,s=o.domain,l=e.width,c=e.height,u=Math.floor(l*(s.x[1]-s.x[0])),f=Math.floor(c*(s.y[1]-s.y[0])),h=s.x[0]*l+a.l,p=e.height-s.y[1]*e.height+a.t,d=o.line.shape;n=\"all\"===o.hoverinfo?[\"count\",\"probability\"]:(o.hoverinfo||\"\").split(\"+\");var g={trace:o,key:o.uid,model:i,x:h,y:p,width:u,height:f,hoveron:o.hoveron,hoverinfoItems:n,arrangement:o.arrangement,bundlecolors:o.bundlecolors,sortpaths:o.sortpaths,labelfont:o.labelfont,categorylabelfont:o.tickfont,pathShape:d,dragDimension:null,margin:a,paths:[],dimensions:[],graphDiv:t,traceSelection:null,pathSelection:null,dimensionSelection:null};return i.dimensions&&(N(g),B(g)),g}function F(t,e,r,i,a){var o,s,l=[],c=[];for(s=0;s<r.length-1;s++)o=n.interpolateNumber(r[s]+t[s],t[s+1]),l.push(o(a)),c.push(o(1-a));var u=\"M \"+t[0]+\",\"+e[0];for(u+=\"l\"+r[0]+\",0 \",s=1;s<r.length;s++)u+=\"C\"+l[s-1]+\",\"+e[s-1]+\" \"+c[s-1]+\",\"+e[s]+\" \"+t[s]+\",\"+e[s],u+=\"l\"+r[s]+\",0 \";for(u+=\"l0,\"+i+\" \",u+=\"l -\"+r[r.length-1]+\",0 \",s=r.length-2;s>=0;s--)u+=\"C\"+c[s]+\",\"+(e[s+1]+i)+\" \"+l[s]+\",\"+(e[s]+i)+\" \"+(t[s]+r[s])+\",\"+(e[s]+i),u+=\"l-\"+r[s]+\",0 \";return u+=\"Z\"}function B(t){var e=t.dimensions,r=t.model,n=e.map((function(t){return t.categories.map((function(t){return t.y}))})),i=t.model.dimensions.map((function(t){return t.categories.map((function(t){return t.displayInd}))})),a=t.model.dimensions.map((function(t){return t.displayInd})),o=t.dimensions.map((function(t){return t.model.dimensionInd})),s=e.map((function(t){return t.x})),l=e.map((function(t){return t.width})),c=[];for(var u in r.paths)r.paths.hasOwnProperty(u)&&c.push(r.paths[u]);function f(t){var e=t.categoryInds.map((function(t,e){return i[e][t]}));return o.map((function(t){return e[t]}))}c.sort((function(e,r){var n=f(e),i=f(r);return\"backward\"===t.sortpaths&&(n.reverse(),i.reverse()),n.push(e.valueInds[0]),i.push(r.valueInds[0]),t.bundlecolors&&(n.unshift(e.rawColor),i.unshift(r.rawColor)),n<i?-1:n>i?1:0}));for(var h=new Array(c.length),p=e[0].model.count,d=e[0].categories.map((function(t){return t.height})).reduce((function(t,e){return t+e})),g=0;g<c.length;g++){var m,v=c[g];m=p>0?d*(v.count/p):0;for(var y,x=new Array(n.length),b=0;b<v.categoryInds.length;b++){var _=v.categoryInds[b],w=i[b][_],T=a[b];x[T]=n[T][w],n[T][w]+=m;var k=t.dimensions[T].categories[w],M=k.bands.length,A=k.bands[M-1];if(void 0===A||v.rawColor!==A.rawColor){var S=void 0===A?0:A.y+A.height;k.bands.push({key:S,color:v.color,rawColor:v.rawColor,height:m,width:k.width,count:v.count,y:S,categoryViewModel:k,parcatsViewModel:t})}else{var E=k.bands[M-1];E.height+=m,E.count+=v.count}}y=\"hspline\"===t.pathShape?F(s,x,l,m,.5):F(s,x,l,m,0),h[g]={key:v.valueInds[0],model:v,height:m,leftXs:s,topYs:x,dimWidths:l,svgD:y,parcatsViewModel:t}}t.paths=h}function N(t){var e=t.model.dimensions.map((function(t){return{displayInd:t.displayInd,dimensionInd:t.dimensionInd}}));e.sort((function(t,e){return t.displayInd-e.displayInd}));var r=[];for(var n in e){var i=e[n].dimensionInd,a=t.model.dimensions[i];r.push(j(t,a))}t.dimensions=r}function j(t,e){var r,n=t.model.dimensions.length,i=e.displayInd;r=40+(n>1?(t.width-80-16)/(n-1):0)*i;var a,o,s,l,c,u=[],f=t.model.maxCats,h=e.categories.length,p=e.count,d=t.height-8*(f-1),g=8*(f-h)/2,m=e.categories.map((function(t){return{displayInd:t.displayInd,categoryInd:t.categoryInd}}));for(m.sort((function(t,e){return t.displayInd-e.displayInd})),c=0;c<h;c++)l=m[c].categoryInd,o=e.categories[l],a=p>0?o.count/p*d:0,s={key:o.valueInds[0],model:o,width:16,height:a,y:null!==o.dragY?o.dragY:g,bands:[],parcatsViewModel:t},g=g+a+8,u.push(s);return{key:e.dimensionInd,x:null!==e.dragX?e.dragX:r,y:0,width:16,model:e,categories:u,parcatsViewModel:t,dragCategoryDisplayInd:null,dragDimensionDisplayInd:null,initialDragDimensionDisplayInds:null,initialDragCategoryDisplayInds:null,dragHasMoved:null,potentialClickBand:null}}e.exports=function(t,e,r,n){f(r,t,n,e)}},{\"../../components/drawing\":665,\"../../components/fx\":683,\"../../lib\":778,\"../../lib/svg_text_utils\":803,\"../../plot_api/plot_api\":814,d3:169,tinycolor2:576}],1148:[function(t,e,r){\"use strict\";var n=t(\"./parcats\");e.exports=function(t,e,r,i){var a=t._fullLayout,o=a._paper,s=a._size;n(t,o,e,{width:s.w,height:s.h,margin:{t:s.t,r:s.r,b:s.b,l:s.l}},r,i)}},{\"./parcats\":1147}],1149:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/cartesian/layout_attributes\"),a=t(\"../../plots/font_attributes\"),o=t(\"../../plots/domain\").attributes,s=t(\"../../lib/extend\").extendFlat,l=t(\"../../plot_api/plot_template\").templatedArray;e.exports={domain:o({name:\"parcoords\",trace:!0,editType:\"plot\"}),labelangle:{valType:\"angle\",dflt:0,editType:\"plot\"},labelside:{valType:\"enumerated\",values:[\"top\",\"bottom\"],dflt:\"top\",editType:\"plot\"},labelfont:a({editType:\"plot\"}),tickfont:a({editType:\"plot\"}),rangefont:a({editType:\"plot\"}),dimensions:l(\"dimension\",{label:{valType:\"string\",editType:\"plot\"},tickvals:s({},i.tickvals,{editType:\"plot\"}),ticktext:s({},i.ticktext,{editType:\"plot\"}),tickformat:s({},i.tickformat,{editType:\"plot\"}),visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},range:{valType:\"info_array\",items:[{valType:\"number\",editType:\"plot\"},{valType:\"number\",editType:\"plot\"}],editType:\"plot\"},constraintrange:{valType:\"info_array\",freeLength:!0,dimensions:\"1-2\",items:[{valType:\"number\",editType:\"plot\"},{valType:\"number\",editType:\"plot\"}],editType:\"plot\"},multiselect:{valType:\"boolean\",dflt:!0,editType:\"plot\"},values:{valType:\"data_array\",editType:\"calc\"},editType:\"calc\"}),line:s({editType:\"calc\"},n(\"line\",{colorscaleDflt:\"Viridis\",autoColorDflt:!1,editTypeOverride:\"calc\"}))}},{\"../../components/colorscale/attributes\":650,\"../../lib/extend\":768,\"../../plot_api/plot_template\":817,\"../../plots/cartesian/layout_attributes\":842,\"../../plots/domain\":855,\"../../plots/font_attributes\":856}],1150:[function(t,e,r){\"use strict\";var n=t(\"./constants\"),i=t(\"d3\"),a=t(\"../../lib/gup\").keyFun,o=t(\"../../lib/gup\").repeat,s=t(\"../../lib\").sorterAsc,l=t(\"../../lib\").strTranslate,c=n.bar.snapRatio;function u(t,e){return t*(1-c)+e*c}var f=n.bar.snapClose;function h(t,e){return t*(1-f)+e*f}function p(t,e,r,n){if(function(t,e){for(var r=0;r<e.length;r++)if(t>=e[r][0]&&t<=e[r][1])return!0;return!1}(r,n))return r;var i=t?-1:1,a=0,o=e.length-1;if(i<0){var s=a;a=o,o=s}for(var l=e[a],c=l,f=a;i*f<i*o;f+=i){var p=f+i,d=e[p];if(i*r<i*h(l,d))return u(l,c);if(i*r<i*d||p===o)return u(d,l);c=l,l=d}}function d(t){t.attr(\"x\",-n.bar.captureWidth/2).attr(\"width\",n.bar.captureWidth)}function g(t){t.attr(\"visibility\",\"visible\").style(\"visibility\",\"visible\").attr(\"fill\",\"yellow\").attr(\"opacity\",0)}function m(t){if(!t.brush.filterSpecified)return\"0,\"+t.height;for(var 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k(t){t.on(\"mousemove\",(function(t){i.event.preventDefault(),t.parent.inBrushDrag||T(this,t)})).on(\"mouseleave\",(function(t){t.parent.inBrushDrag||y()})).call(i.behavior.drag().on(\"dragstart\",(function(t){!function(t,e){i.event.sourceEvent.stopPropagation();var r=e.height-i.mouse(t)[1]-2*n.verticalPadding,a=e.unitToPaddedPx.invert(r),o=e.brush,s=_(e,r),l=s.interval,c=o.svgBrush;if(c.wasDragged=!1,c.grabbingBar=\"ns\"===s.region,c.grabbingBar){var u=l.map(e.unitToPaddedPx);c.grabPoint=r-u[0]-n.verticalPadding,c.barLength=u[1]-u[0]}c.clickableOrdinalRange=s.clickableOrdinalRange,c.stayingIntervals=e.multiselect&&o.filterSpecified?o.filter.getConsolidated():[],l&&(c.stayingIntervals=c.stayingIntervals.filter((function(t){return t[0]!==l[0]&&t[1]!==l[1]}))),c.startExtent=s.region?l[\"s\"===s.region?1:0]:a,e.parent.inBrushDrag=!0,c.brushStartCallback()}(this,t)})).on(\"drag\",(function(t){w(this,t)})).on(\"dragend\",(function(t){!function(t,e){var r=e.brush,n=r.filter,a=r.svgBrush;a._dragging||(T(t,e),w(t,e),e.brush.svgBrush.wasDragged=!1),a._dragging=!1,i.event.sourceEvent.stopPropagation();var o=a.grabbingBar;if(a.grabbingBar=!1,a.grabLocation=void 0,e.parent.inBrushDrag=!1,y(),!a.wasDragged)return a.wasDragged=void 0,a.clickableOrdinalRange?r.filterSpecified&&e.multiselect?a.extent.push(a.clickableOrdinalRange):(a.extent=[a.clickableOrdinalRange],r.filterSpecified=!0):o?(a.extent=a.stayingIntervals,0===a.extent.length&&A(r)):A(r),a.brushCallback(e),b(t.parentNode),void a.brushEndCallback(r.filterSpecified?n.getConsolidated():[]);var s=function(){n.set(n.getConsolidated())};if(e.ordinal){var l=e.unitTickvals;l[l.length-1]<l[0]&&l.reverse(),a.newExtent=[p(0,l,a.newExtent[0],a.stayingIntervals),p(1,l,a.newExtent[1],a.stayingIntervals)];var c=a.newExtent[1]>a.newExtent[0];a.extent=a.stayingIntervals.concat(c?[a.newExtent]:[]),a.extent.length||A(r),a.brushCallback(e),c?b(t.parentNode,s):(s(),b(t.parentNode))}else s();a.brushEndCallback(r.filterSpecified?n.getConsolidated():[])}(this,t)})))}function M(t,e){return t[0]-e[0]}function A(t){t.filterSpecified=!1,t.svgBrush.extent=[[-1/0,1/0]]}function S(t){for(var e,r=t.slice(),n=[],i=r.shift();i;){for(e=i.slice();(i=r.shift())&&i[0]<=e[1];)e[1]=Math.max(e[1],i[1]);n.push(e)}return 1===n.length&&n[0][0]>n[0][1]&&(n=[]),n}e.exports={makeBrush:function(t,e,r,n,i,a){var o,l=function(){var t,e,r=[];return{set:function(n){1===(r=n.map((function(t){return t.slice().sort(s)})).sort(M)).length&&r[0][0]===-1/0&&r[0][1]===1/0&&(r=[[0,-1]]),t=S(r),e=r.reduce((function(t,e){return[Math.min(t[0],e[0]),Math.max(t[1],e[1])]}),[1/0,-1/0])},get:function(){return r.slice()},getConsolidated:function(){return t},getBounds:function(){return e}}}();return l.set(r),{filter:l,filterSpecified:e,svgBrush:{extent:[],brushStartCallback:n,brushCallback:(o=i,function(t){var e=t.brush,r=function(t){return t.svgBrush.extent.map((function(t){return t.slice()}))}(e).slice();e.filter.set(r),o()}),brushEndCallback:a}}},ensureAxisBrush:function(t){var e=t.selectAll(\".\"+n.cn.axisBrush).data(o,a);e.enter().append(\"g\").classed(n.cn.axisBrush,!0),function(t){var e=t.selectAll(\".background\").data(o);e.enter().append(\"rect\").classed(\"background\",!0).call(d).call(g).style(\"pointer-events\",\"auto\").attr(\"transform\",l(0,n.verticalPadding)),e.call(k).attr(\"height\",(function(t){return t.height-n.verticalPadding}));var r=t.selectAll(\".highlight-shadow\").data(o);r.enter().append(\"line\").classed(\"highlight-shadow\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width+n.bar.strokeWidth).attr(\"stroke\",n.bar.strokeColor).attr(\"opacity\",n.bar.strokeOpacity).attr(\"stroke-linecap\",\"butt\"),r.attr(\"y1\",(function(t){return t.height})).call(x);var i=t.selectAll(\".highlight\").data(o);i.enter().append(\"line\").classed(\"highlight\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width-n.bar.strokeWidth).attr(\"stroke\",n.bar.fillColor).attr(\"opacity\",n.bar.fillOpacity).attr(\"stroke-linecap\",\"butt\"),i.attr(\"y1\",(function(t){return t.height})).call(x)}(e)},cleanRanges:function(t,e){if(Array.isArray(t[0])?(t=t.map((function(t){return t.sort(s)})),t=e.multiselect?S(t.sort(M)):[t[0]]):t=[t.sort(s)],e.tickvals){var r=e.tickvals.slice().sort(s);if(!(t=t.map((function(t){var e=[p(0,r,t[0],[]),p(1,r,t[1],[])];if(e[1]>e[0])return e})).filter((function(t){return t}))).length)return}return t.length>1?t:t[0]}}},{\"../../lib\":778,\"../../lib/gup\":775,\"./constants\":1153,d3:169}],1151:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../plots/get_data\").getModuleCalcData,a=t(\"./plot\"),o=t(\"../../constants/xmlns_namespaces\");r.name=\"parcoords\",r.plot=function(t){var e=i(t.calcdata,\"parcoords\")[0];e.length&&a(t,e)},r.clean=function(t,e,r,n){var i=n._has&&n._has(\"parcoords\"),a=e._has&&e._has(\"parcoords\");i&&!a&&(n._paperdiv.selectAll(\".parcoords\").remove(),n._glimages.selectAll(\"*\").remove())},r.toSVG=function(t){var e=t._fullLayout._glimages,r=n.select(t).selectAll(\".svg-container\");r.filter((function(t,e){return e===r.size()-1})).selectAll(\".gl-canvas-context, .gl-canvas-focus\").each((function(){var t=this.toDataURL(\"image/png\");e.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":t,preserveAspectRatio:\"none\",x:0,y:0,width:this.width,height:this.height})})),window.setTimeout((function(){n.selectAll(\"#filterBarPattern\").attr(\"id\",\"filterBarPattern\")}),60)}},{\"../../constants/xmlns_namespaces\":754,\"../../plots/get_data\":865,\"./plot\":1160,d3:169}],1152:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").isArrayOrTypedArray,i=t(\"../../components/colorscale\"),a=t(\"../../lib/gup\").wrap;e.exports=function(t,e){var r,o;return i.hasColorscale(e,\"line\")&&n(e.line.color)?(r=e.line.color,o=i.extractOpts(e.line).colorscale,i.calc(t,e,{vals:r,containerStr:\"line\",cLetter:\"c\"})):(r=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=.5;return e}(e._length),o=[[0,e.line.color],[1,e.line.color]]),a({lineColor:r,cscale:o})}},{\"../../components/colorscale\":655,\"../../lib\":778,\"../../lib/gup\":775}],1153:[function(t,e,r){\"use strict\";e.exports={maxDimensionCount:60,overdrag:45,verticalPadding:2,tickDistance:50,canvasPixelRatio:1,blockLineCount:5e3,layers:[\"contextLineLayer\",\"focusLineLayer\",\"pickLineLayer\"],axisTitleOffset:28,axisExtentOffset:10,deselectedLineColor:\"#777\",bar:{width:4,captureWidth:10,fillColor:\"magenta\",fillOpacity:1,snapDuration:150,snapRatio:.25,snapClose:.01,strokeColor:\"white\",strokeOpacity:1,strokeWidth:1,handleHeight:8,handleOpacity:1,handleOverlap:0},cn:{axisExtentText:\"axis-extent-text\",parcoordsLineLayers:\"parcoords-line-layers\",parcoordsLineLayer:\"parcoords-lines\",parcoords:\"parcoords\",parcoordsControlView:\"parcoords-control-view\",yAxis:\"y-axis\",axisOverlays:\"axis-overlays\",axis:\"axis\",axisHeading:\"axis-heading\",axisTitle:\"axis-title\",axisExtent:\"axis-extent\",axisExtentTop:\"axis-extent-top\",axisExtentTopText:\"axis-extent-top-text\",axisExtentBottom:\"axis-extent-bottom\",axisExtentBottomText:\"axis-extent-bottom-text\",axisBrush:\"axis-brush\"},id:{filterBarPattern:\"filter-bar-pattern\"}}},{}],1154:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/colorscale/helpers\").hasColorscale,a=t(\"../../components/colorscale/defaults\"),o=t(\"../../plots/domain\").defaults,s=t(\"../../plots/array_container_defaults\"),l=t(\"../../plots/cartesian/axes\"),c=t(\"./attributes\"),u=t(\"./axisbrush\"),f=t(\"./constants\").maxDimensionCount,h=t(\"./merge_length\");function p(t,e,r,i){function a(r,i){return n.coerce(t,e,c.dimensions,r,i)}var o=a(\"values\"),s=a(\"visible\");if(o&&o.length||(s=e.visible=!1),s){a(\"label\"),a(\"tickvals\"),a(\"ticktext\"),a(\"tickformat\");var f=a(\"range\");e._ax={_id:\"y\",type:\"linear\",showexponent:\"all\",exponentformat:\"B\",range:f},l.setConvert(e._ax,i.layout),a(\"multiselect\");var h=a(\"constraintrange\");h&&(e.constraintrange=u.cleanRanges(h,e))}}e.exports=function(t,e,r,l){function u(r,i){return n.coerce(t,e,c,r,i)}var d=t.dimensions;Array.isArray(d)&&d.length>f&&(n.log(\"parcoords traces support up to \"+f+\" dimensions at the moment\"),d.splice(f));var g=s(t,e,{name:\"dimensions\",layout:l,handleItemDefaults:p}),m=function(t,e,r,o,s){var l=s(\"line.color\",r);if(i(t,\"line\")&&n.isArrayOrTypedArray(l)){if(l.length)return s(\"line.colorscale\"),a(t,e,o,s,{prefix:\"line.\",cLetter:\"c\"}),l.length;e.line.color=r}return 1/0}(t,e,r,l,u);o(e,l,u),Array.isArray(g)&&g.length||(e.visible=!1),h(e,g,\"values\",m);var v={family:l.font.family,size:Math.round(l.font.size/1.2),color:l.font.color};n.coerceFont(u,\"labelfont\",v),n.coerceFont(u,\"tickfont\",v),n.coerceFont(u,\"rangefont\",v),u(\"labelangle\"),u(\"labelside\")}},{\"../../components/colorscale/defaults\":653,\"../../components/colorscale/helpers\":654,\"../../lib\":778,\"../../plots/array_container_defaults\":823,\"../../plots/cartesian/axes\":828,\"../../plots/domain\":855,\"./attributes\":1149,\"./axisbrush\":1150,\"./constants\":1153,\"./merge_length\":1158}],1155:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").isTypedArray;r.convertTypedArray=function(t){return n(t)?Array.prototype.slice.call(t):t},r.isOrdinal=function(t){return!!t.tickvals},r.isVisible=function(t){return t.visible||!(\"visible\"in t)}},{\"../../lib\":778}],1156:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),plot:t(\"./plot\"),colorbar:{container:\"line\",min:\"cmin\",max:\"cmax\"},moduleType:\"trace\",name:\"parcoords\",basePlotModule:t(\"./base_plot\"),categories:[\"gl\",\"regl\",\"noOpacity\",\"noHover\"],meta:{}}},{\"./attributes\":1149,\"./base_plot\":1151,\"./calc\":1152,\"./defaults\":1154,\"./plot\":1160}],1157:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nattribute vec4 p01_04, p05_08, p09_12, p13_16,\\n               p17_20, p21_24, p25_28, p29_32,\\n               p33_36, p37_40, p41_44, p45_48,\\n               p49_52, p53_56, p57_60, colors;\\n\\nuniform mat4 dim0A, dim1A, dim0B, dim1B, dim0C, dim1C, dim0D, dim1D,\\n             loA, hiA, loB, hiB, loC, hiC, loD, hiD;\\n\\nuniform vec2 resolution, viewBoxPos, viewBoxSize;\\nuniform sampler2D mask, palette;\\nuniform float maskHeight;\\nuniform float drwLayer; // 0: context, 1: focus, 2: pick\\nuniform vec4 contextColor;\\n\\nbool isPick    = (drwLayer > 1.5);\\nbool isContext = (drwLayer < 0.5);\\n\\nconst vec4 ZEROS = vec4(0.0, 0.0, 0.0, 0.0);\\nconst vec4 UNITS = vec4(1.0, 1.0, 1.0, 1.0);\\n\\nfloat val(mat4 p, mat4 v) {\\n    return dot(matrixCompMult(p, v) * UNITS, UNITS);\\n}\\n\\nfloat axisY(float ratio, mat4 A, mat4 B, mat4 C, mat4 D) {\\n    float y1 = val(A, dim0A) + val(B, dim0B) + val(C, dim0C) + val(D, dim0D);\\n    float y2 = val(A, dim1A) + val(B, dim1B) + val(C, dim1C) + val(D, dim1D);\\n    return y1 * (1.0 - ratio) + y2 * ratio;\\n}\\n\\nint iMod(int a, int b) {\\n    return a - b * (a / b);\\n}\\n\\nbool fOutside(float p, float lo, float hi) {\\n    return (lo < hi) && (lo > p || p > hi);\\n}\\n\\nbool vOutside(vec4 p, vec4 lo, vec4 hi) {\\n    return (\\n        fOutside(p[0], lo[0], hi[0]) ||\\n        fOutside(p[1], lo[1], hi[1]) ||\\n        fOutside(p[2], lo[2], hi[2]) ||\\n        fOutside(p[3], lo[3], hi[3])\\n    );\\n}\\n\\nbool mOutside(mat4 p, mat4 lo, mat4 hi) {\\n    return (\\n        vOutside(p[0], lo[0], hi[0]) ||\\n        vOutside(p[1], lo[1], hi[1]) ||\\n        vOutside(p[2], lo[2], hi[2]) ||\\n        vOutside(p[3], lo[3], hi[3])\\n    );\\n}\\n\\nbool outsideBoundingBox(mat4 A, mat4 B, mat4 C, mat4 D) {\\n    return mOutside(A, loA, hiA) ||\\n           mOutside(B, loB, hiB) ||\\n           mOutside(C, loC, hiC) ||\\n           mOutside(D, loD, hiD);\\n}\\n\\nbool outsideRasterMask(mat4 A, mat4 B, mat4 C, mat4 D) {\\n    mat4 pnts[4];\\n    pnts[0] = A;\\n    pnts[1] = B;\\n    pnts[2] = C;\\n    pnts[3] = D;\\n\\n    for(int i = 0; i < 4; ++i) {\\n        for(int j = 0; j < 4; ++j) {\\n            for(int k = 0; k < 4; ++k) {\\n                if(0 == iMod(\\n                    int(255.0 * texture2D(mask,\\n                        vec2(\\n                            (float(i * 2 + j / 2) + 0.5) / 8.0,\\n                            (pnts[i][j][k] * (maskHeight - 1.0) + 1.0) / maskHeight\\n                        ))[3]\\n                    ) / int(pow(2.0, float(iMod(j * 4 + k, 8)))),\\n                    2\\n                )) return true;\\n            }\\n        }\\n    }\\n    return false;\\n}\\n\\nvec4 position(bool isContext, float v, mat4 A, mat4 B, mat4 C, mat4 D) {\\n    float x = 0.5 * sign(v) + 0.5;\\n    float y = axisY(x, A, B, C, D);\\n    float z = 1.0 - abs(v);\\n\\n    z += isContext ? 0.0 : 2.0 * float(\\n        outsideBoundingBox(A, B, C, D) ||\\n        outsideRasterMask(A, B, C, D)\\n    );\\n\\n    return vec4(\\n        2.0 * (vec2(x, y) * viewBoxSize + viewBoxPos) / resolution - 1.0,\\n        z,\\n        1.0\\n    );\\n}\\n\\nvoid main() {\\n    mat4 A = mat4(p01_04, p05_08, p09_12, p13_16);\\n    mat4 B = mat4(p17_20, p21_24, p25_28, p29_32);\\n    mat4 C = mat4(p33_36, p37_40, p41_44, p45_48);\\n    mat4 D = mat4(p49_52, p53_56, p57_60, ZEROS);\\n\\n    float v = colors[3];\\n\\n    gl_Position = position(isContext, v, A, B, C, D);\\n\\n    fragColor =\\n        isContext ? vec4(contextColor) :\\n        isPick ? vec4(colors.rgb, 1.0) : texture2D(palette, vec2(abs(v), 0.5));\\n}\\n\"]),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n    gl_FragColor = fragColor;\\n}\\n\"]),o=t(\"./constants\").maxDimensionCount,s=t(\"../../lib\"),l=new Uint8Array(4),c=new Uint8Array(4),u={shape:[256,1],format:\"rgba\",type:\"uint8\",mag:\"nearest\",min:\"nearest\"};function f(t,e,r,n,i){var a=t._gl;a.enable(a.SCISSOR_TEST),a.scissor(e,r,n,i),t.clear({color:[0,0,0,0],depth:1})}function h(t,e,r,n,i,a){var o=a.key;r.drawCompleted||(!function(t){t.read({x:0,y:0,width:1,height:1,data:l})}(t),r.drawCompleted=!0),function s(l){var c=Math.min(n,i-l*n);0===l&&(window.cancelAnimationFrame(r.currentRafs[o]),delete r.currentRafs[o],f(t,a.scissorX,a.scissorY,a.scissorWidth,a.viewBoxSize[1])),r.clearOnly||(a.count=2*c,a.offset=2*l*n,e(a),l*n+c<i&&(r.currentRafs[o]=window.requestAnimationFrame((function(){s(l+1)}))),r.drawCompleted=!1)}(0)}function p(t,e){for(var r=new Array(256),n=0;n<256;n++)r[n]=t(n/255).concat(e);return r}function d(t,e){return(t>>>8*e)%256/255}function g(t,e,r){for(var n=new Array(8*e),i=0,a=0;a<e;a++)for(var o=0;o<2;o++)for(var s=0;s<4;s++){var l=4*t+s,c=r[64*a+l];63===l&&0===o&&(c*=-1),n[i++]=c}return n}function m(t){var e=\"0\"+t;return e.substr(e.length-2)}function v(t){return t<o?\"p\"+m(t+1)+\"_\"+m(t+4):\"colors\"}function y(t,e,r,n,i,a,o,l,c,u,f,h,p){for(var d=[[],[]],g=0;g<64;g++)d[0][g]=g===i?1:0,d[1][g]=g===a?1:0;var m=t.lines.canvasOverdrag,v=t.domain,y=t.canvasWidth,x=t.canvasHeight,b=t.deselectedLines.color;return s.extendFlat({key:f,resolution:[y,x],viewBoxPos:[o+m,l],viewBoxSize:[c,u],i0:i,i1:a,dim0A:d[0].slice(0,16),dim0B:d[0].slice(16,32),dim0C:d[0].slice(32,48),dim0D:d[0].slice(48,64),dim1A:d[1].slice(0,16),dim1B:d[1].slice(16,32),dim1C:d[1].slice(32,48),dim1D:d[1].slice(48,64),drwLayer:h,contextColor:[b[0]/255,b[1]/255,b[2]/255,b[3]<1?b[3]:Math.max(1/255,Math.pow(1/t.lines.color.length,1/3))],scissorX:(n===e?0:o+m)+(t.pad.l-m)+t.layoutWidth*v.x[0],scissorWidth:(n===r?y-o+m:c+.5)+(n===e?o+m:0),scissorY:l+t.pad.b+t.layoutHeight*v.y[0],scissorHeight:u,viewportX:t.pad.l-m+t.layoutWidth*v.x[0],viewportY:t.pad.b+t.layoutHeight*v.y[0],viewportWidth:y,viewportHeight:x},p)}function x(t){var e=Math.max(0,Math.floor(2047*t[0]),0),r=Math.min(2047,Math.ceil(2047*t[1]),2047);return[Math.min(e,r),Math.max(e,r)]}e.exports=function(t,e){var r,n,l,m,b,_=e.context,w=e.pick,T=e.regl,k={currentRafs:{},drawCompleted:!0,clearOnly:!1},M=function(t){for(var e={},r=0;r<=o;r+=4)e[v(r)]=t.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array(0)});return e}(T),A=T.texture(u),S=[];C(e);var E=T({profile:!1,blend:{enable:_,func:{srcRGB:\"src alpha\",dstRGB:\"one minus src 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r=t._fullLayout;if(i(t)){var s={},l={},c={},u={},f=r._size;e.forEach((function(e,r){var n=e[0].trace;c[r]=n.index;var i=u[r]=n._fullInput.index;s[r]=t.data[i].dimensions,l[r]=t.data[i].dimensions.slice()}));n(t,e,{width:f.w,height:f.h,margin:{t:f.t,r:f.r,b:f.b,l:f.l}},{filterChanged:function(e,n,i){var a=l[e][n],o=i.map((function(t){return t.slice()})),s=\"dimensions[\"+n+\"].constraintrange\",f=r._tracePreGUI[t._fullData[c[e]]._fullInput.uid];if(void 0===f[s]){var h=a.constraintrange;f[s]=h||null}var p=t._fullData[c[e]].dimensions[n];o.length?(1===o.length&&(o=o[0]),a.constraintrange=o,p.constraintrange=o.slice(),o=[o]):(delete a.constraintrange,delete p.constraintrange,o=null);var d={};d[s]=o,t.emit(\"plotly_restyle\",[d,[u[e]]])},hover:function(e){t.emit(\"plotly_hover\",e)},unhover:function(e){t.emit(\"plotly_unhover\",e)},axesMoved:function(e,r){var n=function(t,e){return function(r,n){return 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n=t(\"../../plots/attributes\"),i=t(\"../../plots/domain\").attributes,a=t(\"../../plots/font_attributes\"),o=t(\"../../components/color/attributes\"),s=t(\"../../plots/template_attributes\").hovertemplateAttrs,l=t(\"../../plots/template_attributes\").texttemplateAttrs,c=t(\"../../lib/extend\").extendFlat,u=a({editType:\"plot\",arrayOk:!0,colorEditType:\"plot\"});e.exports={labels:{valType:\"data_array\",editType:\"calc\"},label0:{valType:\"number\",dflt:0,editType:\"calc\"},dlabel:{valType:\"number\",dflt:1,editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc\"},marker:{colors:{valType:\"data_array\",editType:\"calc\"},line:{color:{valType:\"color\",dflt:o.defaultLine,arrayOk:!0,editType:\"style\"},width:{valType:\"number\",min:0,dflt:0,arrayOk:!0,editType:\"style\"},editType:\"calc\"},editType:\"calc\"},text:{valType:\"data_array\",editType:\"plot\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"style\"},scalegroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"value\",\"percent\"],extras:[\"none\"],editType:\"calc\"},hoverinfo:c({},n.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:s({},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),texttemplate:l({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),textposition:{valType:\"enumerated\",values:[\"inside\",\"outside\",\"auto\",\"none\"],dflt:\"auto\",arrayOk:!0,editType:\"plot\"},textfont:c({},u,{}),insidetextorientation:{valType:\"enumerated\",values:[\"horizontal\",\"radial\",\"tangential\",\"auto\"],dflt:\"auto\",editType:\"plot\"},insidetextfont:c({},u,{}),outsidetextfont:c({},u,{}),automargin:{valType:\"boolean\",dflt:!1,editType:\"plot\"},title:{text:{valType:\"string\",dflt:\"\",editType:\"plot\"},font:c({},u,{}),position:{valType:\"enumerated\",values:[\"top left\",\"top center\",\"top right\",\"middle center\",\"bottom left\",\"bottom center\",\"bottom right\"],editType:\"plot\"},editType:\"plot\"},domain:i({name:\"pie\",trace:!0,editType:\"calc\"}),hole:{valType:\"number\",min:0,max:1,dflt:0,editType:\"calc\"},sort:{valType:\"boolean\",dflt:!0,editType:\"calc\"},direction:{valType:\"enumerated\",values:[\"clockwise\",\"counterclockwise\"],dflt:\"counterclockwise\",editType:\"calc\"},rotation:{valType:\"number\",min:-360,max:360,dflt:0,editType:\"calc\"},pull:{valType:\"number\",min:0,max:1,dflt:0,arrayOk:!0,editType:\"calc\"},_deprecated:{title:{valType:\"string\",dflt:\"\",editType:\"calc\"},titlefont:c({},u,{}),titleposition:{valType:\"enumerated\",values:[\"top left\",\"top center\",\"top right\",\"middle center\",\"bottom left\",\"bottom center\",\"bottom right\"],editType:\"calc\"}}}},{\"../../components/color/attributes\":642,\"../../lib/extend\":768,\"../../plots/attributes\":824,\"../../plots/domain\":855,\"../../plots/font_attributes\":856,\"../../plots/template_attributes\":906}],1162:[function(t,e,r){\"use strict\";var n=t(\"../../plots/plots\");r.name=\"pie\",r.plot=function(t,e,i,a){n.plotBasePlot(r.name,t,e,i,a)},r.clean=function(t,e,i,a){n.cleanBasePlot(r.name,t,e,i,a)}},{\"../../plots/plots\":891}],1163:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"tinycolor2\"),a=t(\"../../components/color\"),o={};function s(t){return function(e,r){return!!e&&(!!(e=i(e)).isValid()&&(e=a.addOpacity(e,e.getAlpha()),t[r]||(t[r]=e),e))}}function l(t,e){var r,n=JSON.stringify(t),a=e[n];if(!a){for(a=t.slice(),r=0;r<t.length;r++)a.push(i(t[r]).lighten(20).toHexString());for(r=0;r<t.length;r++)a.push(i(t[r]).darken(20).toHexString());e[n]=a}return a}e.exports={calc:function(t,e){var r,i,a=[],o=t._fullLayout,l=o.hiddenlabels||[],c=e.labels,u=e.marker.colors||[],f=e.values,h=e._length,p=e._hasValues&&h;if(e.dlabel)for(c=new Array(h),r=0;r<h;r++)c[r]=String(e.label0+r*e.dlabel);var d={},g=s(o[\"_\"+e.type+\"colormap\"]),m=0,v=!1;for(r=0;r<h;r++){var y,x,b;if(p){if(y=f[r],!n(y))continue;if((y=+y)<0)continue}else y=1;void 0!==(x=c[r])&&\"\"!==x||(x=r);var _=d[x=String(x)];void 0===_?(d[x]=a.length,(b=-1!==l.indexOf(x))||(m+=y),a.push({v:y,label:x,color:g(u[r],x),i:r,pts:[r],hidden:b})):(v=!0,(i=a[_]).v+=y,i.pts.push(r),i.hidden||(m+=y),!1===i.color&&u[r]&&(i.color=g(u[r],x)))}return(\"funnelarea\"===e.type?v:e.sort)&&a.sort((function(t,e){return e.v-t.v})),a[0]&&(a[0].vTotal=m),a},crossTraceCalc:function(t,e){var r=(e||{}).type;r||(r=\"pie\");var n=t._fullLayout,i=t.calcdata,a=n[r+\"colorway\"],s=n[\"_\"+r+\"colormap\"];n[\"extend\"+r+\"colors\"]&&(a=l(a,o));for(var c=0,u=0;u<i.length;u++){var f=i[u];if(f[0].trace.type===r)for(var h=0;h<f.length;h++){var p=f[h];!1===p.color&&(s[p.label]?p.color=s[p.label]:(s[p.label]=p.color=a[c%a.length],c++))}}},makePullColorFn:s,generateExtendedColors:l}},{\"../../components/color\":643,\"fast-isnumeric\":241,tinycolor2:576}],1164:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib\"),a=t(\"./attributes\"),o=t(\"../../plots/domain\").defaults,s=t(\"../bar/defaults\").handleText;function l(t,e){var r=Array.isArray(t),a=i.isArrayOrTypedArray(e),o=Math.min(r?t.length:1/0,a?e.length:1/0);if(isFinite(o)||(o=0),o&&a){for(var s,l=0;l<o;l++){var c=e[l];if(n(c)&&c>0){s=!0;break}}s||(o=0)}return{hasLabels:r,hasValues:a,len:o}}e.exports={handleLabelsAndValues:l,supplyDefaults:function(t,e,r,n){function c(r,n){return i.coerce(t,e,a,r,n)}var u=l(c(\"labels\"),c(\"values\")),f=u.len;if(e._hasLabels=u.hasLabels,e._hasValues=u.hasValues,!e._hasLabels&&e._hasValues&&(c(\"label0\"),c(\"dlabel\")),f){e._length=f,c(\"marker.line.width\")&&c(\"marker.line.color\"),c(\"marker.colors\"),c(\"scalegroup\");var h,p=c(\"text\"),d=c(\"texttemplate\");if(d||(h=c(\"textinfo\",Array.isArray(p)?\"text+percent\":\"percent\")),c(\"hovertext\"),c(\"hovertemplate\"),d||h&&\"none\"!==h){var g=c(\"textposition\");s(t,e,n,c,g,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),(Array.isArray(g)||\"auto\"===g||\"outside\"===g)&&c(\"automargin\"),(\"inside\"===g||\"auto\"===g||Array.isArray(g))&&c(\"insidetextorientation\")}o(e,n,c);var m=c(\"hole\");if(c(\"title.text\")){var v=c(\"title.position\",m?\"middle center\":\"top center\");m||\"middle center\"!==v||(e.title.position=\"top center\"),i.coerceFont(c,\"title.font\",n.font)}c(\"sort\"),c(\"direction\"),c(\"rotation\"),c(\"pull\")}else e.visible=!1}}},{\"../../lib\":778,\"../../plots/domain\":855,\"../bar/defaults\":925,\"./attributes\":1161,\"fast-isnumeric\":241}],1165:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx/helpers\").appendArrayMultiPointValues;e.exports=function(t,e){var r={curveNumber:e.index,pointNumbers:t.pts,data:e._input,fullData:e,label:t.label,color:t.color,value:t.v,percent:t.percent,text:t.text,v:t.v};return 1===t.pts.length&&(r.pointNumber=r.i=t.pts[0]),n(r,e,t.pts),\"funnelarea\"===e.type&&(delete r.v,delete r.i),r}},{\"../../components/fx/helpers\":679}],1166:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");function i(t){return-1!==t.indexOf(\"e\")?t.replace(/[.]?0+e/,\"e\"):-1!==t.indexOf(\".\")?t.replace(/[.]?0+$/,\"\"):t}r.formatPiePercent=function(t,e){var r=i((100*t).toPrecision(3));return n.numSeparate(r,e)+\"%\"},r.formatPieValue=function(t,e){var r=i(t.toPrecision(10));return n.numSeparate(r,e)},r.getFirstFilled=function(t,e){if(Array.isArray(t))for(var r=0;r<e.length;r++){var n=t[e[r]];if(n||0===n||\"\"===n)return n}},r.castOption=function(t,e){return Array.isArray(t)?r.getFirstFilled(t,e):t||void 0},r.getRotationAngle=function(t){return(\"auto\"===t?0:t)*Math.PI/180}},{\"../../lib\":778}],1167:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,supplyLayoutDefaults:t(\"./layout_defaults\"),layoutAttributes:t(\"./layout_attributes\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"./calc\").crossTraceCalc,plot:t(\"./plot\").plot,style:t(\"./style\"),styleOne:t(\"./style_one\"),moduleType:\"trace\",name:\"pie\",basePlotModule:t(\"./base_plot\"),categories:[\"pie-like\",\"pie\",\"showLegend\"],meta:{}}},{\"./attributes\":1161,\"./base_plot\":1162,\"./calc\":1163,\"./defaults\":1164,\"./layout_attributes\":1168,\"./layout_defaults\":1169,\"./plot\":1170,\"./style\":1171,\"./style_one\":1172}],1168:[function(t,e,r){\"use strict\";e.exports={hiddenlabels:{valType:\"data_array\",editType:\"calc\"},piecolorway:{valType:\"colorlist\",editType:\"calc\"},extendpiecolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{}],1169:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"piecolorway\",e.colorway),r(\"extendpiecolors\")}},{\"../../lib\":778,\"./layout_attributes\":1168}],1170:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../plots/plots\"),a=t(\"../../components/fx\"),o=t(\"../../components/color\"),s=t(\"../../components/drawing\"),l=t(\"../../lib\"),c=l.strScale,u=l.strTranslate,f=t(\"../../lib/svg_text_utils\"),h=t(\"../bar/uniform_text\"),p=h.recordMinTextSize,d=h.clearMinTextSize,g=t(\"../bar/constants\").TEXTPAD,m=t(\"./helpers\"),v=t(\"./event_data\"),y=t(\"../../lib\").isValidTextValue;function x(t,e,r){var i=r[0],o=i.trace,s=i.cx,c=i.cy;\"_hasHoverLabel\"in o||(o._hasHoverLabel=!1),\"_hasHoverEvent\"in o||(o._hasHoverEvent=!1),t.on(\"mouseover\",(function(t){var r=e._fullLayout,u=e._fullData[o.index];if(!e._dragging&&!1!==r.hovermode){var f=u.hoverinfo;if(Array.isArray(f)&&(f=a.castHoverinfo({hoverinfo:[m.castOption(f,t.pts)],_module:o._module},r,0)),\"all\"===f&&(f=\"label+text+value+percent+name\"),u.hovertemplate||\"none\"!==f&&\"skip\"!==f&&f){var h=t.rInscribed||0,p=s+t.pxmid[0]*(1-h),d=c+t.pxmid[1]*(1-h),g=r.separators,y=[];if(f&&-1!==f.indexOf(\"label\")&&y.push(t.label),t.text=m.castOption(u.hovertext||u.text,t.pts),f&&-1!==f.indexOf(\"text\")){var x=t.text;l.isValidTextValue(x)&&y.push(x)}t.value=t.v,t.valueLabel=m.formatPieValue(t.v,g),f&&-1!==f.indexOf(\"value\")&&y.push(t.valueLabel),t.percent=t.v/i.vTotal,t.percentLabel=m.formatPiePercent(t.percent,g),f&&-1!==f.indexOf(\"percent\")&&y.push(t.percentLabel);var b=u.hoverlabel,_=b.font;a.loneHover({trace:o,x0:p-h*i.r,x1:p+h*i.r,y:d,text:y.join(\"<br>\"),name:u.hovertemplate||-1!==f.indexOf(\"name\")?u.name:void 0,idealAlign:t.pxmid[0]<0?\"left\":\"right\",color:m.castOption(b.bgcolor,t.pts)||t.color,borderColor:m.castOption(b.bordercolor,t.pts),fontFamily:m.castOption(_.family,t.pts),fontSize:m.castOption(_.size,t.pts),fontColor:m.castOption(_.color,t.pts),nameLength:m.castOption(b.namelength,t.pts),textAlign:m.castOption(b.align,t.pts),hovertemplate:m.castOption(u.hovertemplate,t.pts),hovertemplateLabels:t,eventData:[v(t,u)]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:e}),o._hasHoverLabel=!0}o._hasHoverEvent=!0,e.emit(\"plotly_hover\",{points:[v(t,u)],event:n.event})}})),t.on(\"mouseout\",(function(t){var r=e._fullLayout,i=e._fullData[o.index],s=n.select(this).datum();o._hasHoverEvent&&(t.originalEvent=n.event,e.emit(\"plotly_unhover\",{points:[v(s,i)],event:n.event}),o._hasHoverEvent=!1),o._hasHoverLabel&&(a.loneUnhover(r._hoverlayer.node()),o._hasHoverLabel=!1)})),t.on(\"click\",(function(t){var r=e._fullLayout,i=e._fullData[o.index];e._dragging||!1===r.hovermode||(e._hoverdata=[v(t,i)],a.click(e,n.event))}))}function b(t,e,r){var n=m.castOption(t.insidetextfont.color,e.pts);!n&&t._input.textfont&&(n=m.castOption(t._input.textfont.color,e.pts));var i=m.castOption(t.insidetextfont.family,e.pts)||m.castOption(t.textfont.family,e.pts)||r.family,a=m.castOption(t.insidetextfont.size,e.pts)||m.castOption(t.textfont.size,e.pts)||r.size;return{color:n||o.contrast(e.color),family:i,size:a}}function _(t,e){for(var r,n,i=0;i<t.length;i++)if((n=(r=t[i][0]).trace).title.text){var a=n.title.text;n._meta&&(a=l.templateString(a,n._meta));var o=s.tester.append(\"text\").attr(\"data-notex\",1).text(a).call(s.font,n.title.font).call(f.convertToTspans,e),c=s.bBox(o.node(),!0);r.titleBox={width:c.width,height:c.height},o.remove()}}function w(t,e,r){var n=r.r||e.rpx1,i=e.rInscribed;if(e.startangle===e.stopangle)return{rCenter:1-i,scale:0,rotate:0,textPosAngle:0};var a,o=e.ring,s=1===o&&Math.abs(e.startangle-e.stopangle)===2*Math.PI,l=e.halfangle,c=e.midangle,u=r.trace.insidetextorientation,f=\"horizontal\"===u,h=\"tangential\"===u,p=\"radial\"===u,d=\"auto\"===u,g=[];if(!d){var m,v=function(r,i){if(function(t,e){var r=t.startangle,n=t.stopangle;return r>e&&e>n||r<e&&e<n}(e,r)){var s=Math.abs(r-e.startangle),l=Math.abs(r-e.stopangle),c=s<l?s:l;(a=\"tan\"===i?k(t,n,o,c,0):T(t,n,o,c,Math.PI/2)).textPosAngle=r,g.push(a)}};if(f||h){for(m=4;m>=-4;m-=2)v(Math.PI*m,\"tan\");for(m=4;m>=-4;m-=2)v(Math.PI*(m+1),\"tan\")}if(f||p){for(m=4;m>=-4;m-=2)v(Math.PI*(m+1.5),\"rad\");for(m=4;m>=-4;m-=2)v(Math.PI*(m+.5),\"rad\")}}if(s||d||f){var y=Math.sqrt(t.width*t.width+t.height*t.height);if((a={scale:i*n*2/y,rCenter:1-i,rotate:0}).textPosAngle=(e.startangle+e.stopangle)/2,a.scale>=1)return a;g.push(a)}(d||p)&&((a=T(t,n,o,l,c)).textPosAngle=(e.startangle+e.stopangle)/2,g.push(a)),(d||h)&&((a=k(t,n,o,l,c)).textPosAngle=(e.startangle+e.stopangle)/2,g.push(a));for(var x=0,b=0,_=0;_<g.length;_++){var w=g[_].scale;if(b<w&&(b=w,x=_),!d&&b>=1)break}return g[x]}function T(t,e,r,n,i){e=Math.max(0,e-2*g);var a=t.width/t.height,o=S(a,n,e,r);return{scale:2*o/t.height,rCenter:M(a,o/e),rotate:A(i)}}function k(t,e,r,n,i){e=Math.max(0,e-2*g);var a=t.height/t.width,o=S(a,n,e,r);return{scale:2*o/t.width,rCenter:M(a,o/e),rotate:A(i+Math.PI/2)}}function M(t,e){return Math.cos(e)-t*e}function A(t){return(180/Math.PI*t+720)%180-90}function S(t,e,r,n){var i=t+1/(2*Math.tan(e));return r*Math.min(1/(Math.sqrt(i*i+.5)+i),n/(Math.sqrt(t*t+n/2)+t))}function E(t,e){return t.v!==e.vTotal||e.trace.hole?Math.min(1/(1+1/Math.sin(t.halfangle)),t.ring/2):1}function C(t,e){var r=e.pxmid[0],n=e.pxmid[1],i=t.width/2,a=t.height/2;return r<0&&(i*=-1),n<0&&(a*=-1),{scale:1,rCenter:1,rotate:0,x:i+Math.abs(a)*(i>0?1:-1)/2,y:a/(1+r*r/(n*n)),outside:!0}}function L(t,e){var r,n,i,a=t.trace,o={x:t.cx,y:t.cy},s={tx:0,ty:0};s.ty+=a.title.font.size,i=P(a),-1!==a.title.position.indexOf(\"top\")?(o.y-=(1+i)*t.r,s.ty-=t.titleBox.height):-1!==a.title.position.indexOf(\"bottom\")&&(o.y+=(1+i)*t.r);var l,c,u=(l=t.r,c=t.trace.aspectratio,l/(void 0===c?1:c)),f=e.w*(a.domain.x[1]-a.domain.x[0])/2;return-1!==a.title.position.indexOf(\"left\")?(f+=u,o.x-=(1+i)*u,s.tx+=t.titleBox.width/2):-1!==a.title.position.indexOf(\"center\")?f*=2:-1!==a.title.position.indexOf(\"right\")&&(f+=u,o.x+=(1+i)*u,s.tx-=t.titleBox.width/2),r=f/t.titleBox.width,n=I(t,e)/t.titleBox.height,{x:o.x,y:o.y,scale:Math.min(r,n),tx:s.tx,ty:s.ty}}function I(t,e){var r=t.trace,n=e.h*(r.domain.y[1]-r.domain.y[0]);return Math.min(t.titleBox.height,n/2)}function P(t){var e,r=t.pull;if(!r)return 0;if(Array.isArray(r))for(r=0,e=0;e<t.pull.length;e++)t.pull[e]>r&&(r=t.pull[e]);return r}function z(t,e){for(var r=[],n=0;n<t.length;n++){var i=t[n][0],a=i.trace,o=a.domain,s=e.w*(o.x[1]-o.x[0]),l=e.h*(o.y[1]-o.y[0]);a.title.text&&\"middle center\"!==a.title.position&&(l-=I(i,e));var c=s/2,u=l/2;\"funnelarea\"!==a.type||a.scalegroup||(u/=a.aspectratio),i.r=Math.min(c,u)/(1+P(a)),i.cx=e.l+e.w*(a.domain.x[1]+a.domain.x[0])/2,i.cy=e.t+e.h*(1-a.domain.y[0])-l/2,a.title.text&&-1!==a.title.position.indexOf(\"bottom\")&&(i.cy-=I(i,e)),a.scalegroup&&-1===r.indexOf(a.scalegroup)&&r.push(a.scalegroup)}!function(t,e){for(var r,n,i,a=0;a<e.length;a++){var o=1/0,s=e[a];for(n=0;n<t.length;n++)if(r=t[n][0],(i=r.trace).scalegroup===s){var l;if(\"pie\"===i.type)l=r.r*r.r;else if(\"funnelarea\"===i.type){var c,u;i.aspectratio>1?(c=r.r,u=c/i.aspectratio):(u=r.r,c=u*i.aspectratio),c*=(1+i.baseratio)/2,l=c*u}o=Math.min(o,l/r.vTotal)}for(n=0;n<t.length;n++)if(r=t[n][0],(i=r.trace).scalegroup===s){var f=o*r.vTotal;\"funnelarea\"===i.type&&(f/=(1+i.baseratio)/2,f/=i.aspectratio),r.r=Math.sqrt(f)}}}(t,r)}function O(t,e){return[t*Math.sin(e),-t*Math.cos(e)]}function D(t,e,r){var n=t._fullLayout,i=r.trace,a=i.texttemplate,o=i.textinfo;if(!a&&o&&\"none\"!==o){var s,c=o.split(\"+\"),u=function(t){return-1!==c.indexOf(t)},f=u(\"label\"),h=u(\"text\"),p=u(\"value\"),d=u(\"percent\"),g=n.separators;if(s=f?[e.label]:[],h){var v=m.getFirstFilled(i.text,e.pts);y(v)&&s.push(v)}p&&s.push(m.formatPieValue(e.v,g)),d&&s.push(m.formatPiePercent(e.v/r.vTotal,g)),e.text=s.join(\"<br>\")}if(a){var x=l.castOption(i,e.i,\"texttemplate\");if(x){var b=function(t){return{label:t.label,value:t.v,valueLabel:m.formatPieValue(t.v,n.separators),percent:t.v/r.vTotal,percentLabel:m.formatPiePercent(t.v/r.vTotal,n.separators),color:t.color,text:t.text,customdata:l.castOption(i,t.i,\"customdata\")}}(e),_=m.getFirstFilled(i.text,e.pts);(y(_)||\"\"===_)&&(b.text=_),e.text=l.texttemplateString(x,b,t._fullLayout._d3locale,b,i._meta||{})}else e.text=\"\"}}function R(t,e){var r=t.rotate*Math.PI/180,n=Math.cos(r),i=Math.sin(r),a=(e.left+e.right)/2,o=(e.top+e.bottom)/2;t.textX=a*n-o*i,t.textY=a*i+o*n,t.noCenter=!0}e.exports={plot:function(t,e){var r=t._fullLayout,a=r._size;d(\"pie\",r),_(e,t),z(e,a);var h=l.makeTraceGroups(r._pielayer,e,\"trace\").each((function(e){var h=n.select(this),d=e[0],g=d.trace;!function(t){var e,r,n,i=t[0],a=i.r,o=i.trace,s=m.getRotationAngle(o.rotation),l=2*Math.PI/i.vTotal,c=\"px0\",u=\"px1\";if(\"counterclockwise\"===o.direction){for(e=0;e<t.length&&t[e].hidden;e++);if(e===t.length)return;s+=l*t[e].v,l*=-1,c=\"px1\",u=\"px0\"}for(n=O(a,s),e=0;e<t.length;e++)(r=t[e]).hidden||(r[c]=n,r.startangle=s,s+=l*r.v/2,r.pxmid=O(a,s),r.midangle=s,s+=l*r.v/2,n=O(a,s),r.stopangle=s,r[u]=n,r.largeArc=r.v>i.vTotal/2?1:0,r.halfangle=Math.PI*Math.min(r.v/i.vTotal,.5),r.ring=1-o.hole,r.rInscribed=E(r,i))}(e),h.attr(\"stroke-linejoin\",\"round\"),h.each((function(){var v=n.select(this).selectAll(\"g.slice\").data(e);v.enter().append(\"g\").classed(\"slice\",!0),v.exit().remove();var y=[[[],[]],[[],[]]],_=!1;v.each((function(i,a){if(i.hidden)n.select(this).selectAll(\"path,g\").remove();else{i.pointNumber=i.i,i.curveNumber=g.index,y[i.pxmid[1]<0?0:1][i.pxmid[0]<0?0:1].push(i);var o=d.cx,c=d.cy,u=n.select(this),h=u.selectAll(\"path.surface\").data([i]);if(h.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":\"all\"}),u.call(x,t,e),g.pull){var v=+m.castOption(g.pull,i.pts)||0;v>0&&(o+=v*i.pxmid[0],c+=v*i.pxmid[1])}i.cxFinal=o,i.cyFinal=c;var T=g.hole;if(i.v===d.vTotal){var k=\"M\"+(o+i.px0[0])+\",\"+(c+i.px0[1])+L(i.px0,i.pxmid,!0,1)+L(i.pxmid,i.px0,!0,1)+\"Z\";T?h.attr(\"d\",\"M\"+(o+T*i.px0[0])+\",\"+(c+T*i.px0[1])+L(i.px0,i.pxmid,!1,T)+L(i.pxmid,i.px0,!1,T)+\"Z\"+k):h.attr(\"d\",k)}else{var M=L(i.px0,i.px1,!0,1);if(T){var A=1-T;h.attr(\"d\",\"M\"+(o+T*i.px1[0])+\",\"+(c+T*i.px1[1])+L(i.px1,i.px0,!1,T)+\"l\"+A*i.px0[0]+\",\"+A*i.px0[1]+M+\"Z\")}else h.attr(\"d\",\"M\"+o+\",\"+c+\"l\"+i.px0[0]+\",\"+i.px0[1]+M+\"Z\")}D(t,i,d);var S=m.castOption(g.textposition,i.pts),E=u.selectAll(\"g.slicetext\").data(i.text&&\"none\"!==S?[0]:[]);E.enter().append(\"g\").classed(\"slicetext\",!0),E.exit().remove(),E.each((function(){var u=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),h=l.ensureUniformFontSize(t,\"outside\"===S?function(t,e,r){var n=m.castOption(t.outsidetextfont.color,e.pts)||m.castOption(t.textfont.color,e.pts)||r.color,i=m.castOption(t.outsidetextfont.family,e.pts)||m.castOption(t.textfont.family,e.pts)||r.family,a=m.castOption(t.outsidetextfont.size,e.pts)||m.castOption(t.textfont.size,e.pts)||r.size;return{color:n,family:i,size:a}}(g,i,r.font):b(g,i,r.font));u.text(i.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,h).call(f.convertToTspans,t);var v,y=s.bBox(u.node());if(\"outside\"===S)v=C(y,i);else if(v=w(y,i,d),\"auto\"===S&&v.scale<1){var x=l.ensureUniformFontSize(t,g.outsidetextfont);u.call(s.font,x),v=C(y=s.bBox(u.node()),i)}var T=v.textPosAngle,k=void 0===T?i.pxmid:O(d.r,T);if(v.targetX=o+k[0]*v.rCenter+(v.x||0),v.targetY=c+k[1]*v.rCenter+(v.y||0),R(v,y),v.outside){var M=v.targetY;i.yLabelMin=M-y.height/2,i.yLabelMid=M,i.yLabelMax=M+y.height/2,i.labelExtraX=0,i.labelExtraY=0,_=!0}v.fontSize=h.size,p(g.type,v,r),e[a].transform=v,u.attr(\"transform\",l.getTextTransform(v))}))}function L(t,e,r,n){var a=n*(e[0]-t[0]),o=n*(e[1]-t[1]);return\"a\"+n*d.r+\",\"+n*d.r+\" 0 \"+i.largeArc+(r?\" 1 \":\" 0 \")+a+\",\"+o}}));var T=n.select(this).selectAll(\"g.titletext\").data(g.title.text?[0]:[]);if(T.enter().append(\"g\").classed(\"titletext\",!0),T.exit().remove(),T.each((function(){var e,r=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),i=g.title.text;g._meta&&(i=l.templateString(i,g._meta)),r.text(i).attr({class:\"titletext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,g.title.font).call(f.convertToTspans,t),e=\"middle center\"===g.title.position?function(t){var e=Math.sqrt(t.titleBox.width*t.titleBox.width+t.titleBox.height*t.titleBox.height);return{x:t.cx,y:t.cy,scale:t.trace.hole*t.r*2/e,tx:0,ty:-t.titleBox.height/2+t.trace.title.font.size}}(d):L(d,a),r.attr(\"transform\",u(e.x,e.y)+c(Math.min(1,e.scale))+u(e.tx,e.ty))})),_&&function(t,e){var r,n,i,a,o,s,l,c,u,f,h,p,d;function g(t,e){return t.pxmid[1]-e.pxmid[1]}function v(t,e){return e.pxmid[1]-t.pxmid[1]}function y(t,r){r||(r={});var i,c,u,h,p=r.labelExtraY+(n?r.yLabelMax:r.yLabelMin),d=n?t.yLabelMin:t.yLabelMax,g=n?t.yLabelMax:t.yLabelMin,v=t.cyFinal+o(t.px0[1],t.px1[1]),y=p-d;if(y*l>0&&(t.labelExtraY=y),Array.isArray(e.pull))for(c=0;c<f.length;c++)(u=f[c])===t||(m.castOption(e.pull,t.pts)||0)>=(m.castOption(e.pull,u.pts)||0)||((t.pxmid[1]-u.pxmid[1])*l>0?(y=u.cyFinal+o(u.px0[1],u.px1[1])-d-t.labelExtraY)*l>0&&(t.labelExtraY+=y):(g+t.labelExtraY-v)*l>0&&(i=3*s*Math.abs(c-f.indexOf(t)),(h=u.cxFinal+a(u.px0[0],u.px1[0])+i-(t.cxFinal+t.pxmid[0])-t.labelExtraX)*s>0&&(t.labelExtraX+=h)))}for(n=0;n<2;n++)for(i=n?g:v,o=n?Math.max:Math.min,l=n?1:-1,r=0;r<2;r++){for(a=r?Math.max:Math.min,s=r?1:-1,(c=t[n][r]).sort(i),u=t[1-n][r],f=u.concat(c),p=[],h=0;h<c.length;h++)void 0!==c[h].yLabelMid&&p.push(c[h]);for(d=!1,h=0;n&&h<u.length;h++)if(void 0!==u[h].yLabelMid){d=u[h];break}for(h=0;h<p.length;h++){var x=h&&p[h-1];d&&!h&&(x=d),y(p[h],x)}}}(y,g),function(t,e){t.each((function(t){var r=n.select(this);if(t.labelExtraX||t.labelExtraY){var i=r.select(\"g.slicetext text\");t.transform.targetX+=t.labelExtraX,t.transform.targetY+=t.labelExtraY,i.attr(\"transform\",l.getTextTransform(t.transform));var a=t.cxFinal+t.pxmid[0],s=\"M\"+a+\",\"+(t.cyFinal+t.pxmid[1]),c=(t.yLabelMax-t.yLabelMin)*(t.pxmid[0]<0?-1:1)/4;if(t.labelExtraX){var u=t.labelExtraX*t.pxmid[1]/t.pxmid[0],f=t.yLabelMid+t.labelExtraY-(t.cyFinal+t.pxmid[1]);Math.abs(u)>Math.abs(f)?s+=\"l\"+f*t.pxmid[0]/t.pxmid[1]+\",\"+f+\"H\"+(a+t.labelExtraX+c):s+=\"l\"+t.labelExtraX+\",\"+u+\"v\"+(f-u)+\"h\"+c}else s+=\"V\"+(t.yLabelMid+t.labelExtraY)+\"h\"+c;l.ensureSingle(r,\"path\",\"textline\").call(o.stroke,e.outsidetextfont.color).attr({\"stroke-width\":Math.min(2,e.outsidetextfont.size/8),d:s,fill:\"none\"})}else r.select(\"path.textline\").remove()}))}(v,g),_&&g.automargin){var k=s.bBox(h.node()),M=g.domain,A=a.w*(M.x[1]-M.x[0]),S=a.h*(M.y[1]-M.y[0]),E=(.5*A-d.r)/a.w,I=(.5*S-d.r)/a.h;i.autoMargin(t,\"pie.\"+g.uid+\".automargin\",{xl:M.x[0]-E,xr:M.x[1]+E,yb:M.y[0]-I,yt:M.y[1]+I,l:Math.max(d.cx-d.r-k.left,0),r:Math.max(k.right-(d.cx+d.r),0),b:Math.max(k.bottom-(d.cy+d.r),0),t:Math.max(d.cy-d.r-k.top,0),pad:5})}}))}));setTimeout((function(){h.selectAll(\"tspan\").each((function(){var t=n.select(this);t.attr(\"dy\")&&t.attr(\"dy\",t.attr(\"dy\"))}))}),0)},formatSliceLabel:D,transformInsideText:w,determineInsideTextFont:b,positionTitleOutside:L,prerenderTitles:_,layoutAreas:z,attachFxHandlers:x,computeTransform:R}},{\"../../components/color\":643,\"../../components/drawing\":665,\"../../components/fx\":683,\"../../lib\":778,\"../../lib/svg_text_utils\":803,\"../../plots/plots\":891,\"../bar/constants\":923,\"../bar/uniform_text\":937,\"./event_data\":1165,\"./helpers\":1166,d3:169}],1171:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"./style_one\"),a=t(\"../bar/uniform_text\").resizeText;e.exports=function(t){var e=t._fullLayout._pielayer.selectAll(\".trace\");a(t,e,\"pie\"),e.each((function(t){var e=t[0].trace,r=n.select(this);r.style({opacity:e.opacity}),r.selectAll(\"path.surface\").each((function(t){n.select(this).call(i,t,e)}))}))}},{\"../bar/uniform_text\":937,\"./style_one\":1172,d3:169}],1172:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),i=t(\"./helpers\").castOption;e.exports=function(t,e,r){var a=r.marker.line,o=i(a.color,e.pts)||n.defaultLine,s=i(a.width,e.pts)||0;t.style(\"stroke-width\",s).call(n.fill,e.color).call(n.stroke,o)}},{\"../../components/color\":643,\"./helpers\":1166}],1173:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\");e.exports={x:n.x,y:n.y,xy:{valType:\"data_array\",editType:\"calc\"},indices:{valType:\"data_array\",editType:\"calc\"},xbounds:{valType:\"data_array\",editType:\"calc\"},ybounds:{valType:\"data_array\",editType:\"calc\"},text:n.text,marker:{color:{valType:\"color\",arrayOk:!1,editType:\"calc\"},opacity:{valType:\"number\",min:0,max:1,dflt:1,arrayOk:!1,editType:\"calc\"},blend:{valType:\"boolean\",dflt:null,editType:\"calc\"},sizemin:{valType:\"number\",min:.1,max:2,dflt:.5,editType:\"calc\"},sizemax:{valType:\"number\",min:.1,dflt:20,editType:\"calc\"},border:{color:{valType:\"color\",arrayOk:!1,editType:\"calc\"},arearatio:{valType:\"number\",min:0,max:1,dflt:0,editType:\"calc\"},editType:\"calc\"},editType:\"calc\"},transforms:void 0}},{\"../scatter/attributes\":1187}],1174:[function(t,e,r){\"use strict\";var n=t(\"gl-pointcloud2d\"),i=t(\"../../lib/str2rgbarray\"),a=t(\"../../plots/cartesian/autorange\").findExtremes,o=t(\"../scatter/get_trace_color\");function s(t,e){this.scene=t,this.uid=e,this.type=\"pointcloud\",this.pickXData=[],this.pickYData=[],this.xData=[],this.yData=[],this.textLabels=[],this.color=\"rgb(0, 0, 0)\",this.name=\"\",this.hoverinfo=\"all\",this.idToIndex=new Int32Array(0),this.bounds=[0,0,0,0],this.pointcloudOptions={positions:new Float32Array(0),idToIndex:this.idToIndex,sizemin:.5,sizemax:12,color:[0,0,0,1],areaRatio:1,borderColor:[0,0,0,1]},this.pointcloud=n(t.glplot,this.pointcloudOptions),this.pointcloud._trace=this}var l=s.prototype;l.handlePick=function(t){var e=this.idToIndex[t.pointId];return{trace:this,dataCoord:t.dataCoord,traceCoord:this.pickXYData?[this.pickXYData[2*e],this.pickXYData[2*e+1]]:[this.pickXData[e],this.pickYData[e]],textLabel:Array.isArray(this.textLabels)?this.textLabels[e]:this.textLabels,color:this.color,name:this.name,pointIndex:e,hoverinfo:this.hoverinfo}},l.update=function(t){this.index=t.index,this.textLabels=t.text,this.name=t.name,this.hoverinfo=t.hoverinfo,this.bounds=[1/0,1/0,-1/0,-1/0],this.updateFast(t),this.color=o(t,{})},l.updateFast=function(t){var e,r,n,o,s,l,c=this.xData=this.pickXData=t.x,u=this.yData=this.pickYData=t.y,f=this.pickXYData=t.xy,h=t.xbounds&&t.ybounds,p=t.indices,d=this.bounds;if(f){if(n=f,e=f.length>>>1,h)d[0]=t.xbounds[0],d[2]=t.xbounds[1],d[1]=t.ybounds[0],d[3]=t.ybounds[1];else for(l=0;l<e;l++)o=n[2*l],s=n[2*l+1],o<d[0]&&(d[0]=o),o>d[2]&&(d[2]=o),s<d[1]&&(d[1]=s),s>d[3]&&(d[3]=s);if(p)r=p;else for(r=new Int32Array(e),l=0;l<e;l++)r[l]=l}else for(e=c.length,n=new Float32Array(2*e),r=new Int32Array(e),l=0;l<e;l++)o=c[l],s=u[l],r[l]=l,n[2*l]=o,n[2*l+1]=s,o<d[0]&&(d[0]=o),o>d[2]&&(d[2]=o),s<d[1]&&(d[1]=s),s>d[3]&&(d[3]=s);this.idToIndex=r,this.pointcloudOptions.idToIndex=r,this.pointcloudOptions.positions=n;var g=i(t.marker.color),m=i(t.marker.border.color),v=t.opacity*t.marker.opacity;g[3]*=v,this.pointcloudOptions.color=g;var y=t.marker.blend;if(null===y){y=c.length<100||u.length<100}this.pointcloudOptions.blend=y,m[3]*=v,this.pointcloudOptions.borderColor=m;var x=t.marker.sizemin,b=Math.max(t.marker.sizemax,t.marker.sizemin);this.pointcloudOptions.sizeMin=x,this.pointcloudOptions.sizeMax=b,this.pointcloudOptions.areaRatio=t.marker.border.arearatio,this.pointcloud.update(this.pointcloudOptions);var _=this.scene.xaxis,w=this.scene.yaxis,T=b/2||.5;t._extremes[_._id]=a(_,[d[0],d[2]],{ppad:T}),t._extremes[w._id]=a(w,[d[1],d[3]],{ppad:T})},l.dispose=function(){this.pointcloud.dispose()},e.exports=function(t,e){var r=new s(t,e.uid);return r.update(e),r}},{\"../../lib/str2rgbarray\":802,\"../../plots/cartesian/autorange\":827,\"../scatter/get_trace_color\":1197,\"gl-pointcloud2d\":324}],1175:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./attributes\");e.exports=function(t,e,r){function a(r,a){return n.coerce(t,e,i,r,a)}a(\"x\"),a(\"y\"),a(\"xbounds\"),a(\"ybounds\"),t.xy&&t.xy instanceof Float32Array&&(e.xy=t.xy),t.indices&&t.indices instanceof Int32Array&&(e.indices=t.indices),a(\"text\"),a(\"marker.color\",r),a(\"marker.opacity\"),a(\"marker.blend\"),a(\"marker.sizemin\"),a(\"marker.sizemax\"),a(\"marker.border.color\",r),a(\"marker.border.arearatio\"),e._length=null}},{\"../../lib\":778,\"./attributes\":1173}],1176:[function(t,e,r){\"use 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n=t(\"../../plots/font_attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../components/color/attributes\"),o=t(\"../../components/fx/attributes\"),s=t(\"../../plots/domain\").attributes,l=t(\"../../plots/template_attributes\").hovertemplateAttrs,c=t(\"../../components/colorscale/attributes\"),u=t(\"../../plot_api/plot_template\").templatedArray,f=t(\"../../lib/extend\").extendFlat,h=t(\"../../plot_api/edit_types\").overrideAll;t(\"../../constants/docs\").FORMAT_LINK;(e.exports=h({hoverinfo:f({},i.hoverinfo,{flags:[],arrayOk:!1}),hoverlabel:o.hoverlabel,domain:s({name:\"sankey\",trace:!0}),orientation:{valType:\"enumerated\",values:[\"v\",\"h\"],dflt:\"h\"},valueformat:{valType:\"string\",dflt:\".3s\"},valuesuffix:{valType:\"string\",dflt:\"\"},arrangement:{valType:\"enumerated\",values:[\"snap\",\"perpendicular\",\"freeform\",\"fixed\"],dflt:\"snap\"},textfont:n({}),customdata:void 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o=n[t=i[w]],s=0,l={};for(T=0;T<o.length;T++)l[(e=o[T]).label]||(l[e.label]=0),l[e.label]+=e.value,s+=e.value;for(T=0;T<o.length;T++)(e=o[T]).flow={value:s,labelConcentration:l[e.label]/s,concentration:e.value/s,links:o},e.concentrationscale&&(e.color=a(e.concentrationscale(e.flow.labelConcentration)))}var c=0;for(w=0;w<r.sourceLinks.length;w++)c+=r.sourceLinks[w].value;for(w=0;w<r.sourceLinks.length;w++)(e=r.sourceLinks[w]).concentrationOut=e.value/c;var u=0;for(w=0;w<r.targetLinks.length;w++)u+=r.targetLinks[w].value;for(w=0;w<r.targetLinks.length;w++)(e=r.targetLinks[w]).concenrationIn=e.value/u}}(),s.node.x.length&&s.node.y.length){for(_=0;_<Math.min(s.node.x.length,s.node.y.length,k.nodes.length);_++)if(s.node.x[_]&&s.node.y[_]){var C=[s.node.x[_]*g,s.node.y[_]*v];k.nodes[_].x0=C[0]-d/2,k.nodes[_].x1=C[0]+d/2;var L=k.nodes[_].y1-k.nodes[_].y0;k.nodes[_].y0=C[1]-L/2,k.nodes[_].y1=C[1]+L/2}if(\"snap\"===s.arrangement)!function(t){t.forEach((function(t){var e,r,n,i=0,a=t.length;for(t.sort((function(t,e){return t.y0-e.y0})),n=0;n<a;++n)(e=t[n]).y0>=i||(r=i-e.y0)>1e-6&&(e.y0+=r,e.y1+=r),i=e.y1+p}))}(function(t){var e,r,n=t.map((function(t,e){return{x0:t.x0,index:e}})).sort((function(t,e){return t.x0-e.x0})),i=[],a=-1,o=-1/0;for(_=0;_<n.length;_++){var s=t[n[_].index];s.x0>o+d&&(a+=1,e=s.x0),o=s.x0,i[a]||(i[a]=[]),i[a].push(s),r=e-s.x0,s.x0+=r,s.x1+=r}return i}(y=k.nodes));i.update(k)}return{circular:b,key:r,trace:s,guid:f.randstr(),horizontal:h,width:g,height:v,nodePad:s.node.pad,nodeLineColor:s.node.line.color,nodeLineWidth:s.node.line.width,linkLineColor:s.link.line.color,linkLineWidth:s.link.line.width,valueFormat:s.valueformat,valueSuffix:s.valuesuffix,textFont:s.textfont,translateX:u.x[0]*t.width+t.margin.l,translateY:t.height-u.y[1]*t.height+t.margin.t,dragParallel:h?v:g,dragPerpendicular:h?g:v,arrangement:s.arrangement,sankey:i,graph:k,forceLayouts:{},interactionState:{dragInProgress:!1,hovered:!1}}}function b(t,e,r){var n=a(e.color),i=e.source.label+\"|\"+e.target.label+\"__\"+r;return e.trace=t.trace,e.curveNumber=t.trace.index,{circular:t.circular,key:i,traceId:t.key,pointNumber:e.pointNumber,link:e,tinyColorHue:o.tinyRGB(n),tinyColorAlpha:n.getAlpha(),linkPath:_,linkLineColor:t.linkLineColor,linkLineWidth:t.linkLineWidth,valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,parent:t,interactionState:t.interactionState,flow:e.flow}}function _(){return function(t){if(t.link.circular)return e=t.link,r=e.width/2,n=e.circularPathData,\"top\"===e.circularLinkType?\"M \"+n.targetX+\" \"+(n.targetY+r)+\" L\"+n.rightInnerExtent+\" \"+(n.targetY+r)+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightSmallArcRadius+r)+\" 0 0 1 \"+(n.rightFullExtent-r)+\" \"+(n.targetY-n.rightSmallArcRadius)+\"L\"+(n.rightFullExtent-r)+\" \"+n.verticalRightInnerExtent+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightLargeArcRadius+r)+\" 0 0 1 \"+n.rightInnerExtent+\" \"+(n.verticalFullExtent-r)+\"L\"+n.leftInnerExtent+\" \"+(n.verticalFullExtent-r)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftLargeArcRadius+r)+\" 0 0 1 \"+(n.leftFullExtent+r)+\" \"+n.verticalLeftInnerExtent+\"L\"+(n.leftFullExtent+r)+\" \"+(n.sourceY-n.leftSmallArcRadius)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftSmallArcRadius+r)+\" 0 0 1 \"+n.leftInnerExtent+\" \"+(n.sourceY+r)+\"L\"+n.sourceX+\" \"+(n.sourceY+r)+\"L\"+n.sourceX+\" \"+(n.sourceY-r)+\"L\"+n.leftInnerExtent+\" \"+(n.sourceY-r)+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftSmallArcRadius-r)+\" 0 0 0 \"+(n.leftFullExtent-r)+\" \"+(n.sourceY-n.leftSmallArcRadius)+\"L\"+(n.leftFullExtent-r)+\" \"+n.verticalLeftInnerExtent+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftLargeArcRadius-r)+\" 0 0 0 \"+n.leftInnerExtent+\" \"+(n.verticalFullExtent+r)+\"L\"+n.rightInnerExtent+\" \"+(n.verticalFullExtent+r)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightLargeArcRadius-r)+\" 0 0 0 \"+(n.rightFullExtent+r)+\" \"+n.verticalRightInnerExtent+\"L\"+(n.rightFullExtent+r)+\" \"+(n.targetY-n.rightSmallArcRadius)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightSmallArcRadius-r)+\" 0 0 0 \"+n.rightInnerExtent+\" \"+(n.targetY-r)+\"L\"+n.targetX+\" \"+(n.targetY-r)+\"Z\":\"M \"+n.targetX+\" \"+(n.targetY-r)+\" L\"+n.rightInnerExtent+\" \"+(n.targetY-r)+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightSmallArcRadius+r)+\" 0 0 0 \"+(n.rightFullExtent-r)+\" \"+(n.targetY+n.rightSmallArcRadius)+\"L\"+(n.rightFullExtent-r)+\" \"+n.verticalRightInnerExtent+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightLargeArcRadius+r)+\" 0 0 0 \"+n.rightInnerExtent+\" \"+(n.verticalFullExtent+r)+\"L\"+n.leftInnerExtent+\" \"+(n.verticalFullExtent+r)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftLargeArcRadius+r)+\" 0 0 0 \"+(n.leftFullExtent+r)+\" \"+n.verticalLeftInnerExtent+\"L\"+(n.leftFullExtent+r)+\" \"+(n.sourceY+n.leftSmallArcRadius)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftSmallArcRadius+r)+\" 0 0 0 \"+n.leftInnerExtent+\" \"+(n.sourceY-r)+\"L\"+n.sourceX+\" \"+(n.sourceY-r)+\"L\"+n.sourceX+\" \"+(n.sourceY+r)+\"L\"+n.leftInnerExtent+\" \"+(n.sourceY+r)+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftSmallArcRadius-r)+\" 0 0 1 \"+(n.leftFullExtent-r)+\" \"+(n.sourceY+n.leftSmallArcRadius)+\"L\"+(n.leftFullExtent-r)+\" \"+n.verticalLeftInnerExtent+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftLargeArcRadius-r)+\" 0 0 1 \"+n.leftInnerExtent+\" \"+(n.verticalFullExtent-r)+\"L\"+n.rightInnerExtent+\" \"+(n.verticalFullExtent-r)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightLargeArcRadius-r)+\" 0 0 1 \"+(n.rightFullExtent+r)+\" \"+n.verticalRightInnerExtent+\"L\"+(n.rightFullExtent+r)+\" \"+(n.targetY+n.rightSmallArcRadius)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightSmallArcRadius-r)+\" 0 0 1 \"+n.rightInnerExtent+\" \"+(n.targetY+r)+\"L\"+n.targetX+\" \"+(n.targetY+r)+\"Z\";var e,r,n,i=t.link.source.x1,a=t.link.target.x0,o=v(i,a),s=o(.5),l=o(.5),c=t.link.y0-t.link.width/2,u=t.link.y0+t.link.width/2,f=t.link.y1-t.link.width/2,h=t.link.y1+t.link.width/2;return\"M\"+i+\",\"+c+\"C\"+s+\",\"+c+\" \"+l+\",\"+f+\" \"+a+\",\"+f+\"L\"+a+\",\"+h+\"C\"+l+\",\"+h+\" \"+s+\",\"+u+\" \"+i+\",\"+u+\"Z\"}}function w(t,e){var r=a(e.color),i=n.nodePadAcross,s=t.nodePad/2;e.dx=e.x1-e.x0,e.dy=e.y1-e.y0;var l=e.dx,c=Math.max(.5,e.dy),u=\"node_\"+e.pointNumber;return e.group&&(u=f.randstr()),e.trace=t.trace,e.curveNumber=t.trace.index,{index:e.pointNumber,key:u,partOfGroup:e.partOfGroup||!1,group:e.group,traceId:t.key,trace:t.trace,node:e,nodePad:t.nodePad,nodeLineColor:t.nodeLineColor,nodeLineWidth:t.nodeLineWidth,textFont:t.textFont,size:t.horizontal?t.height:t.width,visibleWidth:Math.ceil(l),visibleHeight:c,zoneX:-i,zoneY:-s,zoneWidth:l+2*i,zoneHeight:c+2*s,labelY:t.horizontal?e.dy/2+1:e.dx/2+1,left:1===e.originalLayer,sizeAcross:t.width,forceLayouts:t.forceLayouts,horizontal:t.horizontal,darkBackground:r.getBrightness()<=128,tinyColorHue:o.tinyRGB(r),tinyColorAlpha:r.getAlpha(),valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,graph:t.graph,arrangement:t.arrangement,uniqueNodeLabelPathId:[t.guid,t.key,u].join(\"_\"),interactionState:t.interactionState,figure:t}}function T(t){t.attr(\"transform\",(function(t){return h(t.node.x0.toFixed(3),t.node.y0.toFixed(3))}))}function k(t){t.call(T)}function M(t,e){t.call(k),e.attr(\"d\",_())}function A(t){t.attr(\"width\",(function(t){return t.node.x1-t.node.x0})).attr(\"height\",(function(t){return t.visibleHeight}))}function S(t){return t.link.width>1||t.linkLineWidth>0}function E(t){return h(t.translateX,t.translateY)+(t.horizontal?\"matrix(1 0 0 1 0 0)\":\"matrix(0 1 1 0 0 0)\")}function C(t){return h(t.horizontal?0:t.labelY,t.horizontal?t.labelY:0)}function L(t){return i.svg.line()([[t.horizontal?t.left?-t.sizeAcross:t.visibleWidth+n.nodeTextOffsetHorizontal:n.nodeTextOffsetHorizontal,0],[t.horizontal?t.left?-n.nodeTextOffsetHorizontal:t.sizeAcross:t.visibleHeight-n.nodeTextOffsetHorizontal,0]])}function I(t){return t.horizontal?\"matrix(1 0 0 1 0 0)\":\"matrix(0 1 1 0 0 0)\"}function P(t){return t.horizontal?\"scale(1 1)\":\"scale(-1 1)\"}function z(t){return t.darkBackground&&!t.horizontal?\"rgb(255,255,255)\":\"rgb(0,0,0)\"}function O(t){return t.horizontal&&t.left?\"100%\":\"0%\"}function D(t,e,r){t.on(\".basic\",null).on(\"mouseover.basic\",(function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.hover(this,t,e),t.interactionState.hovered=[this,t])})).on(\"mousemove.basic\",(function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.follow(this,t),t.interactionState.hovered=[this,t])})).on(\"mouseout.basic\",(function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.unhover(this,t,e),t.interactionState.hovered=!1)})).on(\"click.basic\",(function(t){t.interactionState.hovered&&(r.unhover(this,t,e),t.interactionState.hovered=!1),t.interactionState.dragInProgress||t.partOfGroup||r.select(this,t,e)}))}function R(t,e,r,a){var o=i.behavior.drag().origin((function(t){return{x:t.node.x0+t.visibleWidth/2,y:t.node.y0+t.visibleHeight/2}})).on(\"dragstart\",(function(i){if(\"fixed\"!==i.arrangement&&(f.ensureSingle(a._fullLayout._infolayer,\"g\",\"dragcover\",(function(t){a._fullLayout._dragCover=t})),f.raiseToTop(this),i.interactionState.dragInProgress=i.node,B(i.node),i.interactionState.hovered&&(r.nodeEvents.unhover.apply(0,i.interactionState.hovered),i.interactionState.hovered=!1),\"snap\"===i.arrangement)){var o=i.traceId+\"|\"+i.key;i.forceLayouts[o]?i.forceLayouts[o].alpha(1):function(t,e,r,i){!function(t){for(var e=0;e<t.length;e++)t[e].y=(t[e].y0+t[e].y1)/2,t[e].x=(t[e].x0+t[e].x1)/2}(r.graph.nodes);var a=r.graph.nodes.filter((function(t){return t.originalX===r.node.originalX})).filter((function(t){return!t.partOfGroup}));r.forceLayouts[e]=u.forceSimulation(a).alphaDecay(0).force(\"collide\",u.forceCollide().radius((function(t){return t.dy/2+r.nodePad/2})).strength(1).iterations(n.forceIterations)).force(\"constrain\",function(t,e,r,i){return function(){for(var t=0,a=0;a<r.length;a++){var o=r[a];o===i.interactionState.dragInProgress?(o.x=o.lastDraggedX,o.y=o.lastDraggedY):(o.vx=(o.originalX-o.x)/n.forceTicksPerFrame,o.y=Math.min(i.size-o.dy/2,Math.max(o.dy/2,o.y))),t=Math.max(t,Math.abs(o.vx),Math.abs(o.vy))}!i.interactionState.dragInProgress&&t<.1&&i.forceLayouts[e].alpha()>0&&i.forceLayouts[e].alpha(0)}}(0,e,a,r)).stop()}(0,o,i),function(t,e,r,i,a){window.requestAnimationFrame((function o(){var s;for(s=0;s<n.forceTicksPerFrame;s++)r.forceLayouts[i].tick();if(function(t){for(var e=0;e<t.length;e++)t[e].y0=t[e].y-t[e].dy/2,t[e].y1=t[e].y0+t[e].dy,t[e].x0=t[e].x-t[e].dx/2,t[e].x1=t[e].x0+t[e].dx}(r.graph.nodes),r.sankey.update(r.graph),M(t.filter(N(r)),e),r.forceLayouts[i].alpha()>0)window.requestAnimationFrame(o);else{var l=r.node.originalX;r.node.x0=l-r.visibleWidth/2,r.node.x1=l+r.visibleWidth/2,F(r,a)}}))}(t,e,i,o,a)}})).on(\"drag\",(function(r){if(\"fixed\"!==r.arrangement){var n=i.event.x,a=i.event.y;\"snap\"===r.arrangement?(r.node.x0=n-r.visibleWidth/2,r.node.x1=n+r.visibleWidth/2,r.node.y0=a-r.visibleHeight/2,r.node.y1=a+r.visibleHeight/2):(\"freeform\"===r.arrangement&&(r.node.x0=n-r.visibleWidth/2,r.node.x1=n+r.visibleWidth/2),a=Math.max(0,Math.min(r.size-r.visibleHeight/2,a)),r.node.y0=a-r.visibleHeight/2,r.node.y1=a+r.visibleHeight/2),B(r.node),\"snap\"!==r.arrangement&&(r.sankey.update(r.graph),M(t.filter(N(r)),e))}})).on(\"dragend\",(function(t){if(\"fixed\"!==t.arrangement){t.interactionState.dragInProgress=!1;for(var e=0;e<t.node.childrenNodes.length;e++)t.node.childrenNodes[e].x=t.node.x,t.node.childrenNodes[e].y=t.node.y;\"snap\"!==t.arrangement&&F(t,a)}}));t.on(\".drag\",null).call(o)}function F(t,e){for(var r=[],n=[],i=0;i<t.graph.nodes.length;i++){var a=(t.graph.nodes[i].x0+t.graph.nodes[i].x1)/2,o=(t.graph.nodes[i].y0+t.graph.nodes[i].y1)/2;r.push(a/t.figure.width),n.push(o/t.figure.height)}y.call(\"_guiRestyle\",e,{\"node.x\":[r],\"node.y\":[n]},t.trace.index).then((function(){e._fullLayout._dragCover&&e._fullLayout._dragCover.remove()}))}function B(t){t.lastDraggedX=t.x0+t.dx/2,t.lastDraggedY=t.y0+t.dy/2}function N(t){return function(e){return e.node.originalX===t.node.originalX}}e.exports=function(t,e,r,l,c){var u=!1;f.ensureSingle(t._fullLayout._infolayer,\"g\",\"first-render\",(function(){u=!0}));var h=t._fullLayout._dragCover,p=r.filter((function(t){return m(t).trace.visible})).map(x.bind(null,l)),v=e.selectAll(\".\"+n.cn.sankey).data(p,d);v.exit().remove(),v.enter().append(\"g\").classed(n.cn.sankey,!0).style(\"box-sizing\",\"content-box\").style(\"position\",\"absolute\").style(\"left\",0).style(\"shape-rendering\",\"geometricPrecision\").style(\"pointer-events\",\"auto\").attr(\"transform\",E),v.each((function(e,r){t._fullData[r]._sankey=e;var n=\"bgsankey-\"+e.trace.uid+\"-\"+r;f.ensureSingle(t._fullLayout._draggers,\"rect\",n),t._fullData[r]._bgRect=i.select(\".\"+n),t._fullData[r]._bgRect.style(\"pointer-events\",\"all\").attr(\"width\",e.width).attr(\"height\",e.height).attr(\"x\",e.translateX).attr(\"y\",e.translateY).classed(\"bgsankey\",!0).style({fill:\"transparent\",\"stroke-width\":0})})),v.transition().ease(n.ease).duration(n.duration).attr(\"transform\",E);var y=v.selectAll(\".\"+n.cn.sankeyLinks).data(g,d);y.enter().append(\"g\").classed(n.cn.sankeyLinks,!0).style(\"fill\",\"none\");var k=y.selectAll(\".\"+n.cn.sankeyLink).data((function(t){return t.graph.links.filter((function(t){return t.value})).map(b.bind(null,t))}),d);k.enter().append(\"path\").classed(n.cn.sankeyLink,!0).call(D,v,c.linkEvents),k.style(\"stroke\",(function(t){return S(t)?o.tinyRGB(a(t.linkLineColor)):t.tinyColorHue})).style(\"stroke-opacity\",(function(t){return S(t)?o.opacity(t.linkLineColor):t.tinyColorAlpha})).style(\"fill\",(function(t){return t.tinyColorHue})).style(\"fill-opacity\",(function(t){return t.tinyColorAlpha})).style(\"stroke-width\",(function(t){return S(t)?t.linkLineWidth:1})).attr(\"d\",_()),k.style(\"opacity\",(function(){return t._context.staticPlot||u||h?1:0})).transition().ease(n.ease).duration(n.duration).style(\"opacity\",1),k.exit().transition().ease(n.ease).duration(n.duration).style(\"opacity\",0).remove();var M=v.selectAll(\".\"+n.cn.sankeyNodeSet).data(g,d);M.enter().append(\"g\").classed(n.cn.sankeyNodeSet,!0),M.style(\"cursor\",(function(t){switch(t.arrangement){case\"fixed\":return\"default\";case\"perpendicular\":return\"ns-resize\";default:return\"move\"}}));var F=M.selectAll(\".\"+n.cn.sankeyNode).data((function(t){var e=t.graph.nodes;return function(t){var e,r=[];for(e=0;e<t.length;e++)t[e].originalX=(t[e].x0+t[e].x1)/2,t[e].originalY=(t[e].y0+t[e].y1)/2,-1===r.indexOf(t[e].originalX)&&r.push(t[e].originalX);for(r.sort((function(t,e){return t-e})),e=0;e<t.length;e++)t[e].originalLayerIndex=r.indexOf(t[e].originalX),t[e].originalLayer=t[e].originalLayerIndex/(r.length-1)}(e),e.map(w.bind(null,t))}),d);F.enter().append(\"g\").classed(n.cn.sankeyNode,!0).call(T).style(\"opacity\",(function(e){return!t._context.staticPlot&&!u||e.partOfGroup?0:1})),F.call(D,v,c.nodeEvents).call(R,k,c,t),F.transition().ease(n.ease).duration(n.duration).call(T).style(\"opacity\",(function(t){return t.partOfGroup?0:1})),F.exit().transition().ease(n.ease).duration(n.duration).style(\"opacity\",0).remove();var B=F.selectAll(\".\"+n.cn.nodeRect).data(g);B.enter().append(\"rect\").classed(n.cn.nodeRect,!0).call(A),B.style(\"stroke-width\",(function(t){return t.nodeLineWidth})).style(\"stroke\",(function(t){return o.tinyRGB(a(t.nodeLineColor))})).style(\"stroke-opacity\",(function(t){return o.opacity(t.nodeLineColor)})).style(\"fill\",(function(t){return t.tinyColorHue})).style(\"fill-opacity\",(function(t){return t.tinyColorAlpha})),B.transition().ease(n.ease).duration(n.duration).call(A);var N=F.selectAll(\".\"+n.cn.nodeCapture).data(g);N.enter().append(\"rect\").classed(n.cn.nodeCapture,!0).style(\"fill-opacity\",0),N.attr(\"x\",(function(t){return t.zoneX})).attr(\"y\",(function(t){return t.zoneY})).attr(\"width\",(function(t){return t.zoneWidth})).attr(\"height\",(function(t){return t.zoneHeight}));var 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n=t(\"../../lib\"),i=t(\"../scatter/constants\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/line_shape_defaults\"),c=t(\"../scatter/text_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),f=t(\"./attributes\");e.exports=function(t,e,r,h){function p(r,i){return n.coerce(t,e,f,r,i)}p(\"carpet\"),e.xaxis=\"x\",e.yaxis=\"y\";var d=p(\"a\"),g=p(\"b\"),m=Math.min(d.length,g.length);if(m){e._length=m,p(\"text\"),p(\"texttemplate\"),p(\"hovertext\"),p(\"mode\",m<i.PTS_LINESONLY?\"lines+markers\":\"lines\"),a.hasLines(e)&&(s(t,e,r,h,p),l(t,e,p),p(\"connectgaps\")),a.hasMarkers(e)&&o(t,e,r,h,p,{gradient:!0}),a.hasText(e)&&c(t,e,h,p);var v=[];(a.hasMarkers(e)||a.hasText(e))&&(p(\"marker.maxdisplayed\"),v.push(\"points\")),p(\"fill\"),\"none\"!==e.fill&&(u(t,e,r,p),a.hasLines(e)||l(t,e,p)),\"tonext\"!==e.fill&&\"toself\"!==e.fill||v.push(\"fills\"),\"fills\"!==p(\"hoveron\",v.join(\"+\")||\"points\")&&p(\"hovertemplate\"),n.coerceSelectionMarkerOpacity(e,p)}else e.visible=!1}},{\"../../lib\":778,\"../scatter/constants\":1191,\"../scatter/fillcolor_defaults\":1195,\"../scatter/line_defaults\":1200,\"../scatter/line_shape_defaults\":1202,\"../scatter/marker_defaults\":1206,\"../scatter/subtypes\":1212,\"../scatter/text_defaults\":1213,\"./attributes\":1221}],1224:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,i){var a=n[i];return t.a=a.a,t.b=a.b,t.y=a.y,t}},{}],1225:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r={},n=e._carpet,i=n.ab2ij([t.a,t.b]),a=Math.floor(i[0]),o=i[0]-a,s=Math.floor(i[1]),l=i[1]-s,c=n.evalxy([],a,s,o,l);return r.yLabel=c[1].toFixed(3),r}},{}],1226:[function(t,e,r){\"use 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n=t(\"../scatter/plot\"),i=t(\"../../plots/cartesian/axes\"),a=t(\"../../components/drawing\");e.exports=function(t,e,r,o){var s,l,c,u=r[0][0].carpet,f={xaxis:i.getFromId(t,u.xaxis||\"x\"),yaxis:i.getFromId(t,u.yaxis||\"y\"),plot:e.plot};for(n(t,f,r,o),s=0;s<r.length;s++)l=r[s][0].trace,c=o.selectAll(\"g.trace\"+l.uid+\" .js-line\"),a.setClipUrl(c,r[s][0].carpet._clipPathId,t)}},{\"../../components/drawing\":665,\"../../plots/cartesian/axes\":828,\"../scatter/plot\":1208}],1229:[function(t,e,r){\"use strict\";var n=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../plots/template_attributes\").texttemplateAttrs,a=t(\"../scatter/attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../components/colorscale/attributes\"),l=t(\"../../components/drawing/attributes\").dash,c=t(\"../../lib/extend\").extendFlat,u=t(\"../../plot_api/edit_types\").overrideAll,f=a.marker,h=a.line,p=f.line;e.exports=u({lon:{valType:\"data_array\"},lat:{valType:\"data_array\"},locations:{valType:\"data_array\"},locationmode:{valType:\"enumerated\",values:[\"ISO-3\",\"USA-states\",\"country 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n=t(\"../../lib\"),i=t(\"../scatter/subtypes\"),a=t(\"../scatter/marker_defaults\"),o=t(\"../scatter/line_defaults\"),s=t(\"../scatter/text_defaults\"),l=t(\"../scatter/fillcolor_defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,u){function f(r,i){return n.coerce(t,e,c,r,i)}var h,p=f(\"locations\");if(p&&p.length){var d,g=f(\"geojson\");(\"string\"==typeof g&&\"\"!==g||n.isPlainObject(g))&&(d=\"geojson-id\"),\"geojson-id\"===f(\"locationmode\",d)&&f(\"featureidkey\"),h=p.length}else{var m=f(\"lon\")||[],v=f(\"lat\")||[];h=Math.min(m.length,v.length)}h?(e._length=h,f(\"text\"),f(\"hovertext\"),f(\"hovertemplate\"),f(\"mode\"),i.hasLines(e)&&(o(t,e,r,u,f),f(\"connectgaps\")),i.hasMarkers(e)&&a(t,e,r,u,f,{gradient:!0}),i.hasText(e)&&(f(\"texttemplate\"),s(t,e,u,f)),f(\"fill\"),\"none\"!==e.fill&&l(t,e,r,f),n.coerceSelectionMarkerOpacity(e,f)):e.visible=!1}},{\"../../lib\":778,\"../scatter/fillcolor_defaults\":1195,\"../scatter/line_defaults\":1200,\"../scatter/marker_defaults\":1206,\"../scatter/subtypes\":1212,\"../scatter/text_defaults\":1213,\"./attributes\":1229}],1232:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,i){t.lon=e.lon,t.lat=e.lat,t.location=e.loc?e.loc:null;var a=n[i];return a.fIn&&a.fIn.properties&&(t.properties=a.fIn.properties),t}},{}],1233:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\");e.exports=function(t,e,r){var i={},a=r[e.geo]._subplot.mockAxis,o=t.lonlat;return i.lonLabel=n.tickText(a,a.c2l(o[0]),!0).text,i.latLabel=n.tickText(a,a.c2l(o[1]),!0).text,i}},{\"../../plots/cartesian/axes\":828}],1234:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx\"),i=t(\"../../constants/numerical\").BADNUM,a=t(\"../scatter/get_trace_color\"),o=t(\"../../lib\").fillText,s=t(\"./attributes\");e.exports=function(t,e,r){var l=t.cd,c=l[0].trace,u=t.xa,f=t.ya,h=t.subplot,p=h.projection.isLonLatOverEdges,d=h.project;if(n.getClosest(l,(function(t){var n=t.lonlat;if(n[0]===i)return 1/0;if(p(n))return 1/0;var a=d(n),o=d([e,r]),s=Math.abs(a[0]-o[0]),l=Math.abs(a[1]-o[1]),c=Math.max(3,t.mrc||0);return Math.max(Math.sqrt(s*s+l*l)-c,1-3/c)}),t),!1!==t.index){var g=l[t.index],m=g.lonlat,v=[u.c2p(m),f.c2p(m)],y=g.mrc||1;t.x0=v[0]-y,t.x1=v[0]+y,t.y0=v[1]-y,t.y1=v[1]+y,t.loc=g.loc,t.lon=m[0],t.lat=m[1];var x={};x[c.geo]={_subplot:h};var b=c._module.formatLabels(g,c,x);return 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T=y-_,k=y+w;p[v+u[0]]=x-i.c2l(T),p[v+u[1]]=i.c2l(k)-x,p[v+u[2]]=0,p[v+u[3]]=0,d=Math.min(d,y-_),g=Math.max(g,y+w)}}}h[a]={positions:r,errors:p,_bnds:[d,g]}}}return p(i,l),p(a,u),h},textPosition:function(t,e,r,n){var i,a=e._length,o={};if(f.hasMarkers(e)){var s=r.font,l=r.align,c=r.baseline;for(o.offset=new Array(a),i=0;i<a;i++){var u=n.sizes?n.sizes[i]:n.size,h=Array.isArray(s)?s[i].size:s.size,p=Array.isArray(l)?l.length>1?l[i]:l[0]:l,d=Array.isArray(c)?c.length>1?c[i]:c[0]:c,g=m[p],v=m[d],y=u?u/.8+1:0,x=-v*y-.5*v;o.offset[i]=[g*y/h,x/h]}}return o}}},{\"../../components/drawing\":665,\"../../components/fx/helpers\":679,\"../../constants/interactions\":752,\"../../lib\":778,\"../../lib/gl_format_color\":774,\"../../plots/cartesian/axis_ids\":831,\"../../registry\":911,\"../scatter/make_bubble_size_func\":1204,\"../scatter/subtypes\":1212,\"./constants\":1241,\"./helpers\":1246,\"color-normalize\":125,\"fast-isnumeric\":241,\"svg-path-sdf\":574}],1243:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../registry\"),a=t(\"./helpers\"),o=t(\"./attributes\"),s=t(\"../scatter/constants\"),l=t(\"../scatter/subtypes\"),c=t(\"../scatter/xy_defaults\"),u=t(\"../scatter/period_defaults\"),f=t(\"../scatter/marker_defaults\"),h=t(\"../scatter/line_defaults\"),p=t(\"../scatter/fillcolor_defaults\"),d=t(\"../scatter/text_defaults\");e.exports=function(t,e,r,g){function m(r,i){return n.coerce(t,e,o,r,i)}var v=!!t.marker&&a.isOpenSymbol(t.marker.symbol),y=l.isBubble(t),x=c(t,e,g,m);if(x){u(t,e,g,m);var b=x<s.PTS_LINESONLY?\"lines+markers\":\"lines\";m(\"text\"),m(\"hovertext\"),m(\"hovertemplate\"),m(\"mode\",b),l.hasLines(e)&&(m(\"connectgaps\"),h(t,e,r,g,m),m(\"line.shape\")),l.hasMarkers(e)&&(f(t,e,r,g,m),m(\"marker.line.width\",v||y?1:0)),l.hasText(e)&&(m(\"texttemplate\"),d(t,e,g,m));var _=(e.line||{}).color,w=(e.marker||{}).color;m(\"fill\"),\"none\"!==e.fill&&p(t,e,r,m);var T=i.getComponentMethod(\"errorbars\",\"supplyDefaults\");T(t,e,_||w||r,{axis:\"y\"}),T(t,e,_||w||r,{axis:\"x\",inherit:\"y\"}),n.coerceSelectionMarkerOpacity(e,m)}else e.visible=!1}},{\"../../lib\":778,\"../../registry\":911,\"../scatter/constants\":1191,\"../scatter/fillcolor_defaults\":1195,\"../scatter/line_defaults\":1200,\"../scatter/marker_defaults\":1206,\"../scatter/period_defaults\":1207,\"../scatter/subtypes\":1212,\"../scatter/text_defaults\":1213,\"../scatter/xy_defaults\":1214,\"./attributes\":1239,\"./helpers\":1246}],1244:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/color\"),a=t(\"../../constants/interactions\").DESELECTDIM;e.exports={styleTextSelection:function(t){var e,r,o=t[0],s=o.trace,l=o.t,c=l._scene,u=l.index,f=c.selectBatch[u],h=c.unselectBatch[u],p=c.textOptions[u],d=c.textSelectedOptions[u]||{},g=c.textUnselectedOptions[u]||{},m=n.extendFlat({},p);if(f.length||h.length){var v=d.color,y=g.color,x=p.color,b=Array.isArray(x);for(m.color=new Array(s._length),e=0;e<f.length;e++)r=f[e],m.color[r]=v||(b?x[r]:x);for(e=0;e<h.length;e++){r=h[e];var _=b?x[r]:x;m.color[r]=y||(v?_:i.addOpacity(_,a))}}c.glText[u].update(m)}}},{\"../../components/color\":643,\"../../constants/interactions\":752,\"../../lib\":778}],1245:[function(t,e,r){\"use strict\";var n=t(\"../scatter/format_labels\");e.exports=function(t,e,r){var i=t.i;return\"x\"in t||(t.x=e._x[i]),\"y\"in t||(t.y=e._y[i]),n(t,e,r)}},{\"../scatter/format_labels\":1196}],1246:[function(t,e,r){\"use strict\";var n=t(\"./constants\");r.isOpenSymbol=function(t){return\"string\"==typeof t?n.OPEN_RE.test(t):t%200>100},r.isDotSymbol=function(t){return\"string\"==typeof t?n.DOT_RE.test(t):t>200}},{\"./constants\":1241}],1247:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"../scatter/get_trace_color\");function o(t,e,r,o){var s=t.xa,l=t.ya,c=t.distance,u=t.dxy,f=t.index,h={pointNumber:f,x:e[f],y:r[f]};h.tx=Array.isArray(o.text)?o.text[f]:o.text,h.htx=Array.isArray(o.hovertext)?o.hovertext[f]:o.hovertext,h.data=Array.isArray(o.customdata)?o.customdata[f]:o.customdata,h.tp=Array.isArray(o.textposition)?o.textposition[f]:o.textposition;var p=o.textfont;p&&(h.ts=i.isArrayOrTypedArray(p.size)?p.size[f]:p.size,h.tc=Array.isArray(p.color)?p.color[f]:p.color,h.tf=Array.isArray(p.family)?p.family[f]:p.family);var d=o.marker;d&&(h.ms=i.isArrayOrTypedArray(d.size)?d.size[f]:d.size,h.mo=i.isArrayOrTypedArray(d.opacity)?d.opacity[f]:d.opacity,h.mx=i.isArrayOrTypedArray(d.symbol)?d.symbol[f]:d.symbol,h.mc=i.isArrayOrTypedArray(d.color)?d.color[f]:d.color);var g=d&&d.line;g&&(h.mlc=Array.isArray(g.color)?g.color[f]:g.color,h.mlw=i.isArrayOrTypedArray(g.width)?g.width[f]:g.width);var m=d&&d.gradient;m&&\"none\"!==m.type&&(h.mgt=Array.isArray(m.type)?m.type[f]:m.type,h.mgc=Array.isArray(m.color)?m.color[f]:m.color);var v=s.c2p(h.x,!0),y=l.c2p(h.y,!0),x=h.mrc||1,b=o.hoverlabel;b&&(h.hbg=Array.isArray(b.bgcolor)?b.bgcolor[f]:b.bgcolor,h.hbc=Array.isArray(b.bordercolor)?b.bordercolor[f]:b.bordercolor,h.hts=i.isArrayOrTypedArray(b.font.size)?b.font.size[f]:b.font.size,h.htc=Array.isArray(b.font.color)?b.font.color[f]:b.font.color,h.htf=Array.isArray(b.font.family)?b.font.family[f]:b.font.family,h.hnl=i.isArrayOrTypedArray(b.namelength)?b.namelength[f]:b.namelength);var _=o.hoverinfo;_&&(h.hi=Array.isArray(_)?_[f]:_);var w=o.hovertemplate;w&&(h.ht=Array.isArray(w)?w[f]:w);var T={};T[t.index]=h;var k=o._origX,M=o._origY,A=i.extendFlat({},t,{color:a(o,h),x0:v-x,x1:v+x,xLabelVal:k?k[f]:h.x,y0:y-x,y1:y+x,yLabelVal:M?M[f]:h.y,cd:T,distance:c,spikeDistance:u,hovertemplate:h.ht});return h.htx?A.text=h.htx:h.tx?A.text=h.tx:o.text&&(A.text=o.text),i.fillText(h,o,A),n.getComponentMethod(\"errorbars\",\"hoverInfo\")(h,o,A),A}e.exports={hoverPoints:function(t,e,r,n){var i,a,s,l,c,u,f,h,p,d=t.cd,g=d[0].t,m=d[0].trace,v=t.xa,y=t.ya,x=g.x,b=g.y,_=v.c2p(e),w=y.c2p(r),T=t.distance;if(g.tree){var k=v.p2c(_-T),M=v.p2c(_+T),A=y.p2c(w-T),S=y.p2c(w+T);i=\"x\"===n?g.tree.range(Math.min(k,M),Math.min(y._rl[0],y._rl[1]),Math.max(k,M),Math.max(y._rl[0],y._rl[1])):g.tree.range(Math.min(k,M),Math.min(A,S),Math.max(k,M),Math.max(A,S))}else i=g.ids;var E=T;if(\"x\"===n)for(c=0;c<i.length;c++)s=x[i[c]],(u=Math.abs(v.c2p(s)-_))<E&&(E=u,f=y.c2p(b[i[c]])-w,p=Math.sqrt(u*u+f*f),a=i[c]);else for(c=i.length-1;c>-1;c--)s=x[i[c]],l=b[i[c]],u=v.c2p(s)-_,f=y.c2p(l)-w,(h=Math.sqrt(u*u+f*f))<E&&(E=p=h,a=i[c]);return t.index=a,t.distance=E,t.dxy=p,void 0===a?[t]:[o(t,x,b,m)]},calcHover:o}},{\"../../lib\":778,\"../../registry\":911,\"../scatter/get_trace_color\":1197}],1248:[function(t,e,r){\"use strict\";var n=t(\"./hover\");e.exports={moduleType:\"trace\",name:\"scattergl\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"gl\",\"regl\",\"cartesian\",\"symbols\",\"errorBarsOK\",\"showLegend\",\"scatter-like\"],attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),crossTraceDefaults:t(\"../scatter/cross_trace_defaults\"),colorbar:t(\"../scatter/marker_colorbar\"),formatLabels:t(\"./format_labels\"),calc:t(\"./calc\"),plot:t(\"./plot\"),hoverPoints:n.hoverPoints,selectPoints:t(\"./select\"),meta:{}}},{\"../../plots/cartesian\":841,\"../scatter/cross_trace_defaults\":1193,\"../scatter/marker_colorbar\":1205,\"./attributes\":1239,\"./calc\":1240,\"./defaults\":1243,\"./format_labels\":1245,\"./hover\":1247,\"./plot\":1249,\"./select\":1251}],1249:[function(t,e,r){\"use strict\";var n=t(\"regl-scatter2d\"),i=t(\"regl-line2d\"),a=t(\"regl-error2d\"),o=t(\"gl-text\"),s=t(\"../../lib\"),l=t(\"../../components/dragelement/helpers\").selectMode,c=t(\"../../lib/prepare_regl\"),u=t(\"../scatter/subtypes\"),f=t(\"../scatter/link_traces\"),h=t(\"./edit_style\").styleTextSelection;function p(t,e,r){var n=t._size,i=t.width,a=t.height;return[n.l+e.domain[0]*n.w,n.b+r.domain[0]*n.h,i-n.r-(1-e.domain[1])*n.w,a-n.t-(1-r.domain[1])*n.h]}e.exports=function(t,e,r){if(r.length){var d,g,m=t._fullLayout,v=e._scene,y=e.xaxis,x=e.yaxis;if(v)if(c(t,[\"ANGLE_instanced_arrays\",\"OES_element_index_uint\"])){var b=v.count,_=m._glcanvas.data()[0].regl;if(f(t,e,r),v.dirty){if(!0===v.error2d&&(v.error2d=a(_)),!0===v.line2d&&(v.line2d=i(_)),!0===v.scatter2d&&(v.scatter2d=n(_,{constPointSize:!0})),!0===v.fill2d&&(v.fill2d=i(_)),!0===v.glText)for(v.glText=new Array(b),d=0;d<b;d++)v.glText[d]=new o(_);if(v.glText){if(b>v.glText.length){var w=b-v.glText.length;for(d=0;d<w;d++)v.glText.push(new o(_))}else if(b<v.glText.length){var T=v.glText.length-b;v.glText.splice(b,T).forEach((function(t){t.destroy()}))}for(d=0;d<b;d++)v.glText[d].update(v.textOptions[d])}if(v.line2d&&(v.line2d.update(v.lineOptions),v.lineOptions=v.lineOptions.map((function(t){if(t&&t.positions){for(var e=t.positions,r=0;r<e.length&&(isNaN(e[r])||isNaN(e[r+1]));)r+=2;for(var n=e.length-2;n>r&&(isNaN(e[n])||isNaN(e[n+1]));)n-=2;t.positions=e.slice(r,n+2)}return t})),v.line2d.update(v.lineOptions)),v.error2d){var k=(v.errorXOptions||[]).concat(v.errorYOptions||[]);v.error2d.update(k)}v.scatter2d&&v.scatter2d.update(v.markerOptions),v.fillOrder=s.repeat(null,b),v.fill2d&&(v.fillOptions=v.fillOptions.map((function(t,e){var n=r[e];if(t&&n&&n[0]&&n[0].trace){var i,a,o=n[0],s=o.trace,l=o.t,c=v.lineOptions[e],u=[];s._ownfill&&u.push(e),s._nexttrace&&u.push(e+1),u.length&&(v.fillOrder[e]=u);var f,h,p=[],d=c&&c.positions||l.positions;if(\"tozeroy\"===s.fill){for(f=0;f<d.length&&isNaN(d[f+1]);)f+=2;for(h=d.length-2;h>f&&isNaN(d[h+1]);)h-=2;0!==d[f+1]&&(p=[d[f],0]),p=p.concat(d.slice(f,h+2)),0!==d[h+1]&&(p=p.concat([d[h],0]))}else if(\"tozerox\"===s.fill){for(f=0;f<d.length&&isNaN(d[f]);)f+=2;for(h=d.length-2;h>f&&isNaN(d[h]);)h-=2;0!==d[f]&&(p=[0,d[f+1]]),p=p.concat(d.slice(f,h+2)),0!==d[h]&&(p=p.concat([0,d[h+1]]))}else if(\"toself\"===s.fill||\"tonext\"===s.fill){for(p=[],i=0,a=0;a<d.length;a+=2)(isNaN(d[a])||isNaN(d[a+1]))&&((p=p.concat(d.slice(i,a))).push(d[i],d[i+1]),i=a+2);p=p.concat(d.slice(i)),i&&p.push(d[i],d[i+1])}else{var g=s._nexttrace;if(g){var m=v.lineOptions[e+1];if(m){var y=m.positions;if(\"tonexty\"===s.fill){for(p=d.slice(),e=Math.floor(y.length/2);e--;){var x=y[2*e],b=y[2*e+1];isNaN(x)||isNaN(b)||p.push(x,b)}t.fill=g.fillcolor}}}}if(s._prevtrace&&\"tonext\"===s._prevtrace.fill){var _=v.lineOptions[e-1].positions,w=p.length/2,T=[i=w];for(a=0;a<_.length;a+=2)(isNaN(_[a])||isNaN(_[a+1]))&&(T.push(a/2+w+1),i=a+2);p=p.concat(_),t.hole=T}return t.fillmode=s.fill,t.opacity=s.opacity,t.positions=p,t}})),v.fill2d.update(v.fillOptions))}var M=m.dragmode,A=l(M),S=m.clickmode.indexOf(\"select\")>-1;for(d=0;d<b;d++){var E=r[d][0],C=E.trace,L=E.t,I=L.index,P=C._length,z=L.x,O=L.y;if(C.selectedpoints||A||S){if(A||(A=!0),C.selectedpoints){var D=v.selectBatch[I]=s.selIndices2selPoints(C),R={};for(g=0;g<D.length;g++)R[D[g]]=1;var F=[];for(g=0;g<P;g++)R[g]||F.push(g);v.unselectBatch[I]=F}var B=L.xpx=new Array(P),N=L.ypx=new Array(P);for(g=0;g<P;g++)B[g]=y.c2p(z[g]),N[g]=x.c2p(O[g])}else L.xpx=L.ypx=null}if(A){if(v.select2d||(v.select2d=n(m._glcanvas.data()[1].regl)),v.scatter2d){var j=new Array(b);for(d=0;d<b;d++)j[d]=v.selectBatch[d].length||v.unselectBatch[d].length?v.markerUnselectedOptions[d]:{};v.scatter2d.update(j)}v.select2d&&(v.select2d.update(v.markerOptions),v.select2d.update(v.markerSelectedOptions)),v.glText&&r.forEach((function(t){var e=((t||[])[0]||{}).trace||{};u.hasText(e)&&h(t)}))}else v.scatter2d&&v.scatter2d.update(v.markerOptions);var U={viewport:p(m,y,x),range:[(y._rl||y.range)[0],(x._rl||x.range)[0],(y._rl||y.range)[1],(x._rl||x.range)[1]]},V=s.repeat(U,v.count);v.fill2d&&v.fill2d.update(V),v.line2d&&v.line2d.update(V),v.error2d&&v.error2d.update(V.concat(V)),v.scatter2d&&v.scatter2d.update(V),v.select2d&&v.select2d.update(V),v.glText&&v.glText.forEach((function(t){t.update(U)}))}else v.init()}}},{\"../../components/dragelement/helpers\":661,\"../../lib\":778,\"../../lib/prepare_regl\":791,\"../scatter/link_traces\":1203,\"../scatter/subtypes\":1212,\"./edit_style\":1244,\"gl-text\":352,\"regl-error2d\":534,\"regl-line2d\":535,\"regl-scatter2d\":537}],1250:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e){var r=e._scene,i={count:0,dirty:!0,lineOptions:[],fillOptions:[],markerOptions:[],markerSelectedOptions:[],markerUnselectedOptions:[],errorXOptions:[],errorYOptions:[],textOptions:[],textSelectedOptions:[],textUnselectedOptions:[],selectBatch:[],unselectBatch:[]},a={fill2d:!1,scatter2d:!1,error2d:!1,line2d:!1,glText:!1,select2d:!1};return e._scene||((r=e._scene={}).init=function(){n.extendFlat(r,a,i)},r.init(),r.update=function(t){var e=n.repeat(t,r.count);if(r.fill2d&&r.fill2d.update(e),r.scatter2d&&r.scatter2d.update(e),r.line2d&&r.line2d.update(e),r.error2d&&r.error2d.update(e.concat(e)),r.select2d&&r.select2d.update(e),r.glText)for(var i=0;i<r.count;i++)r.glText[i].update(t)},r.draw=function(){for(var t=r.count,e=r.fill2d,i=r.error2d,a=r.line2d,o=r.scatter2d,s=r.glText,l=r.select2d,c=r.selectBatch,u=r.unselectBatch,f=0;f<t;f++){if(e&&r.fillOrder[f]&&e.draw(r.fillOrder[f]),a&&r.lineOptions[f]&&a.draw(f),i&&(r.errorXOptions[f]&&i.draw(f),r.errorYOptions[f]&&i.draw(f+t)),o&&r.markerOptions[f])if(u[f].length){var h=n.repeat([],r.count);h[f]=u[f],o.draw(h)}else 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n=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../plots/template_attributes\").texttemplateAttrs,a=t(\"../scattergeo/attributes\"),o=t(\"../scatter/attributes\"),s=t(\"../../plots/mapbox/layout_attributes\"),l=t(\"../../plots/attributes\"),c=t(\"../../components/colorscale/attributes\"),u=t(\"../../lib/extend\").extendFlat,f=t(\"../../plot_api/edit_types\").overrideAll,h=a.line,p=a.marker;e.exports=f({lon:a.lon,lat:a.lat,mode:u({},o.mode,{dflt:\"markers\"}),text:u({},o.text,{}),texttemplate:i({editType:\"plot\"},{keys:[\"lat\",\"lon\",\"text\"]}),hovertext:u({},o.hovertext,{}),line:{color:h.color,width:h.width},connectgaps:o.connectgaps,marker:u({symbol:{valType:\"string\",dflt:\"circle\",arrayOk:!0},angle:{valType:\"number\",dflt:\"auto\",arrayOk:!0},allowoverlap:{valType:\"boolean\",dflt:!1},opacity:p.opacity,size:p.size,sizeref:p.sizeref,sizemin:p.sizemin,sizemode:p.sizemode},c(\"marker\")),fill:a.fill,fillcolor:o.fillcolor,textfont:s.layers.symbol.textfont,textposition:s.layers.symbol.textposition,below:{valType:\"string\"},selected:{marker:o.selected.marker},unselected:{marker:o.unselected.marker},hoverinfo:u({},l.hoverinfo,{flags:[\"lon\",\"lat\",\"text\",\"name\"]}),hovertemplate:n()},\"calc\",\"nested\")},{\"../../components/colorscale/attributes\":650,\"../../lib/extend\":768,\"../../plot_api/edit_types\":810,\"../../plots/attributes\":824,\"../../plots/mapbox/layout_attributes\":887,\"../../plots/template_attributes\":906,\"../scatter/attributes\":1187,\"../scattergeo/attributes\":1229}],1253:[function(t,e,r){\"use 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e,r,i,a,s,l,c,u,f,h,p,d,g=t._x,m=t._y,v=t._z,y=t._len,x=-1/0,b=1/0,_=-1/0,w=1/0,T=-1/0,k=1/0,M=\"\";for(y&&(c=g[0],f=m[0],p=v[0]),y>1&&(u=g[y-1],h=m[y-1],d=v[y-1]),e=0;e<y;e++)x=Math.max(x,g[e]),b=Math.min(b,g[e]),_=Math.max(_,m[e]),w=Math.min(w,m[e]),T=Math.max(T,v[e]),k=Math.min(k,v[e]),a||g[e]===c||(a=!0,M+=\"x\"),s||m[e]===f||(s=!0,M+=\"y\"),l||v[e]===p||(l=!0,M+=\"z\");a||(M+=\"x\"),s||(M+=\"y\"),l||(M+=\"z\");var A=o(t._x),S=o(t._y),E=o(t._z);M=(M=(M=M.replace(\"x\",(c>u?\"-\":\"+\")+\"x\")).replace(\"y\",(f>h?\"-\":\"+\")+\"y\")).replace(\"z\",(p>d?\"-\":\"+\")+\"z\");var C=function(){y=0,A=[],S=[],E=[]};(!y||y<A.length*S.length*E.length)&&C();var L=function(t){return\"x\"===t?g:\"y\"===t?m:v},I=function(t){return\"x\"===t?A:\"y\"===t?S:E},P=function(t){return t[y-1]<t[0]?-1:1},z=L(M[1]),O=L(M[3]),D=L(M[5]),R=I(M[1]).length,F=I(M[3]).length,B=I(M[5]).length,N=!1,j=function(t,e,r){return 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M={};u.label&&(M.label=u.label),u.hasOwnProperty(\"v\")&&(M.value=u.v,M.valueLabel=x.formatValue(u.v,l)),M.currentPath=x.getPath(t.data),h||(M.percentParent=d/x.getValue(p),M.percentParentLabel=x.formatPercent(M.percentParent,l),M.parent=x.getPtLabel(p)),M.percentEntry=d/x.getValue(e),M.percentEntryLabel=x.formatPercent(M.percentEntry,l),M.entry=x.getPtLabel(e),M.percentRoot=d/x.getValue(f),M.percentRootLabel=x.formatPercent(M.percentRoot,l),M.root=x.getPtLabel(f),u.hasOwnProperty(\"color\")&&(M.color=u.color);var A=o.castOption(r,u.i,\"text\");return(o.isValidTextValue(A)||\"\"===A)&&(M.text=A),M.customdata=o.castOption(r,u.i,\"customdata\"),o.texttemplateString(k,M,i._d3locale,M,r._meta||{})}},{\"../../components/drawing\":665,\"../../lib\":778,\"../../lib/svg_text_utils\":803,\"../bar/style\":935,\"../bar/uniform_text\":937,\"../pie/helpers\":1166,\"../pie/plot\":1170,\"./constants\":1302,\"./fx\":1304,\"./helpers\":1305,\"./style\":1310,d3:169,\"d3-hierarchy\":161}],1310:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../components/color\"),a=t(\"../../lib\"),o=t(\"../bar/uniform_text\").resizeText;function s(t,e,r){var n=e.data.data,o=!e.children,s=n.i,l=a.castOption(r,s,\"marker.line.color\")||i.defaultLine,c=a.castOption(r,s,\"marker.line.width\")||0;t.style(\"stroke-width\",c).call(i.fill,n.color).call(i.stroke,l).style(\"opacity\",o?r.leaf.opacity:null)}e.exports={style:function(t){var e=t._fullLayout._sunburstlayer.selectAll(\".trace\");o(t,e,\"sunburst\"),e.each((function(t){var e=n.select(this),r=t[0].trace;e.style(\"opacity\",r.opacity),e.selectAll(\"path.surface\").each((function(t){n.select(this).call(s,t,r)}))}))},styleOne:s}},{\"../../components/color\":643,\"../../lib\":778,\"../bar/uniform_text\":937,d3:169}],1311:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),i=t(\"../../components/colorscale/attributes\"),a=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../../plots/attributes\"),s=t(\"../../lib/extend\").extendFlat,l=t(\"../../plot_api/edit_types\").overrideAll;function c(t){return{show:{valType:\"boolean\",dflt:!1},start:{valType:\"number\",dflt:null,editType:\"plot\"},end:{valType:\"number\",dflt:null,editType:\"plot\"},size:{valType:\"number\",dflt:null,min:0,editType:\"plot\"},project:{x:{valType:\"boolean\",dflt:!1},y:{valType:\"boolean\",dflt:!1},z:{valType:\"boolean\",dflt:!1}},color:{valType:\"color\",dflt:n.defaultLine},usecolormap:{valType:\"boolean\",dflt:!1},width:{valType:\"number\",min:1,max:16,dflt:2},highlight:{valType:\"boolean\",dflt:!0},highlightcolor:{valType:\"color\",dflt:n.defaultLine},highlightwidth:{valType:\"number\",min:1,max:16,dflt:2}}}var u=e.exports=l(s({z:{valType:\"data_array\"},x:{valType:\"data_array\"},y:{valType:\"data_array\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertemplate:a(),connectgaps:{valType:\"boolean\",dflt:!1,editType:\"calc\"},surfacecolor:{valType:\"data_array\"}},i(\"\",{colorAttr:\"z or surfacecolor\",showScaleDflt:!0,autoColorDflt:!1,editTypeOverride:\"calc\"}),{contours:{x:c(),y:c(),z:c()},hidesurface:{valType:\"boolean\",dflt:!1},lightposition:{x:{valType:\"number\",min:-1e5,max:1e5,dflt:10},y:{valType:\"number\",min:-1e5,max:1e5,dflt:1e4},z:{valType:\"number\",min:-1e5,max:1e5,dflt:0}},lighting:{ambient:{valType:\"number\",min:0,max:1,dflt:.8},diffuse:{valType:\"number\",min:0,max:1,dflt:.8},specular:{valType:\"number\",min:0,max:2,dflt:.05},roughness:{valType:\"number\",min:0,max:1,dflt:.5},fresnel:{valType:\"number\",min:0,max:5,dflt:.2}},opacity:{valType:\"number\",min:0,max:1,dflt:1},opacityscale:{valType:\"any\",editType:\"calc\"},_deprecated:{zauto:s({},i.zauto,{}),zmin:s({},i.zmin,{}),zmax:s({},i.zmax,{})},hoverinfo:s({},o.hoverinfo),showlegend:s({},o.showlegend,{dflt:!1})}),\"calc\",\"nested\");u.x.editType=u.y.editType=u.z.editType=\"calc+clearAxisTypes\",u.transforms=void 0},{\"../../components/color\":643,\"../../components/colorscale/attributes\":650,\"../../lib/extend\":768,\"../../plot_api/edit_types\":810,\"../../plots/attributes\":824,\"../../plots/template_attributes\":906}],1312:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/calc\");e.exports=function(t,e){e.surfacecolor?n(t,e,{vals:e.surfacecolor,containerStr:\"\",cLetter:\"c\"}):n(t,e,{vals:e.z,containerStr:\"\",cLetter:\"c\"})}},{\"../../components/colorscale/calc\":651}],1313:[function(t,e,r){\"use strict\";var n=t(\"gl-surface3d\"),i=t(\"ndarray\"),a=t(\"ndarray-linear-interpolate\").d2,o=t(\"../heatmap/interp2d\"),s=t(\"../heatmap/find_empties\"),l=t(\"../../lib\").isArrayOrTypedArray,c=t(\"../../lib/gl_format_color\").parseColorScale,u=t(\"../../lib/str2rgbarray\"),f=t(\"../../components/colorscale\").extractOpts;function h(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var p=h.prototype;p.getXat=function(t,e,r,n){var i=l(this.data.x)?l(this.data.x[0])?this.data.x[e][t]:this.data.x[t]:t;return void 0===r?i:n.d2l(i,0,r)},p.getYat=function(t,e,r,n){var i=l(this.data.y)?l(this.data.y[0])?this.data.y[e][t]:this.data.y[e]:e;return void 0===r?i:n.d2l(i,0,r)},p.getZat=function(t,e,r,n){var i=this.data.z[e][t];return null===i&&this.data.connectgaps&&this.data._interpolatedZ&&(i=this.data._interpolatedZ[e][t]),void 0===r?i:n.d2l(i,0,r)},p.handlePick=function(t){if(t.object===this.surface){var e=(t.data.index[0]-1)/this.dataScaleX-1,r=(t.data.index[1]-1)/this.dataScaleY-1,n=Math.max(Math.min(Math.round(e),this.data.z[0].length-1),0),i=Math.max(Math.min(Math.round(r),this.data._ylength-1),0);t.index=[n,i],t.traceCoordinate=[this.getXat(n,i),this.getYat(n,i),this.getZat(n,i)],t.dataCoordinate=[this.getXat(n,i,this.data.xcalendar,this.scene.fullSceneLayout.xaxis),this.getYat(n,i,this.data.ycalendar,this.scene.fullSceneLayout.yaxis),this.getZat(n,i,this.data.zcalendar,this.scene.fullSceneLayout.zaxis)];for(var a=0;a<3;a++){var o=t.dataCoordinate[a];null!=o&&(t.dataCoordinate[a]*=this.scene.dataScale[a])}var s=this.data.hovertext||this.data.text;return Array.isArray(s)&&s[i]&&void 0!==s[i][n]?t.textLabel=s[i][n]:t.textLabel=s||\"\",t.data.dataCoordinate=t.dataCoordinate.slice(),this.surface.highlight(t.data),this.scene.glplot.spikes.position=t.dataCoordinate,!0}};var d=[2,3,5,7,11,13,17,19,23,29,31,37,41,43,47,53,59,61,67,71,73,79,83,89,97,101,103,107,109,113,127,131,137,139,149,151,157,163,167,173,179,181,191,193,197,199,211,223,227,229,233,239,241,251,257,263,269,271,277,281,283,293,307,311,313,317,331,337,347,349,353,359,367,373,379,383,389,397,401,409,419,421,431,433,439,443,449,457,461,463,467,479,487,491,499,503,509,521,523,541,547,557,563,569,571,577,587,593,599,601,607,613,617,619,631,641,643,647,653,659,661,673,677,683,691,701,709,719,727,733,739,743,751,757,761,769,773,787,797,809,811,821,823,827,829,839,853,857,859,863,877,881,883,887,907,911,919,929,937,941,947,953,967,971,977,983,991,997,1009,1013,1019,1021,1031,1033,1039,1049,1051,1061,1063,1069,1087,1091,1093,1097,1103,1109,1117,1123,1129,1151,1153,1163,1171,1181,1187,1193,1201,1213,1217,1223,1229,1231,1237,1249,1259,1277,1279,1283,1289,1291,1297,1301,1303,1307,1319,1321,1327,1361,1367,1373,1381,1399,1409,1423,1427,1429,1433,1439,1447,1451,1453,1459,1471,1481,1483,1487,1489,1493,1499,1511,1523,1531,1543,1549,1553,1559,1567,1571,1579,1583,1597,1601,1607,1609,1613,1619,1621,1627,1637,1657,1663,1667,1669,1693,1697,1699,1709,1721,1723,1733,1741,1747,1753,1759,1777,1783,1787,1789,1801,1811,1823,1831,1847,1861,1867,1871,1873,1877,1879,1889,1901,1907,1913,1931,1933,1949,1951,1973,1979,1987,1993,1997,1999,2003,2011,2017,2027,2029,2039,2053,2063,2069,2081,2083,2087,2089,2099,2111,2113,2129,2131,2137,2141,2143,2153,2161,2179,2203,2207,2213,2221,2237,2239,2243,2251,2267,2269,2273,2281,2287,2293,2297,2309,2311,2333,2339,2341,2347,2351,2357,2371,2377,2381,2383,2389,2393,2399,2411,2417,2423,2437,2441,2447,2459,2467,2473,2477,2503,2521,2531,2539,2543,2549,2551,2557,2579,2591,2593,2609,2617,2621,2633,2647,2657,2659,2663,2671,2677,2683,2687,2689,2693,2699,2707,2711,2713,2719,2729,2731,2741,2749,2753,2767,2777,2789,2791,2797,2801,2803,2819,2833,2837,2843,2851,2857,2861,2879,2887,2897,2903,2909,2917,2927,2939,2953,2957,2963,2969,2971,2999];function g(t,e){if(t<e)return 0;for(var r=0;0===Math.floor(t%e);)t/=e,r++;return r}function m(t){for(var e=[],r=0;r<d.length;r++){var n=d[r];e.push(g(t,n))}return e}function v(t){for(var e=m(t),r=t,n=0;n<d.length;n++)if(e[n]>0){r=d[n];break}return r}function y(t,e){if(!(t<1||e<1)){for(var r=m(t),n=m(e),i=1,a=0;a<d.length;a++)i*=Math.pow(d[a],Math.max(r[a],n[a]));return i}}p.calcXnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getXat(e-1,0),i=this.getXat(e,0);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r},p.calcYnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getYat(0,e-1),i=this.getYat(0,e);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r};var x=[1,2,4,6,12,24,36,48,60,120,180,240,360,720,840,1260],b=x[9],_=x[13];function w(t,e,r){var n=r[8]+r[2]*e[0]+r[5]*e[1];return t[0]=(r[6]+r[0]*e[0]+r[3]*e[1])/n,t[1]=(r[7]+r[1]*e[0]+r[4]*e[1])/n,t}function T(t,e,r){return function(t,e,r,n){for(var i=[0,0],o=t.shape[0],s=t.shape[1],l=0;l<o;l++)for(var c=0;c<s;c++)r(i,[l,c],n),t.set(l,c,a(e,i[0],i[1]))}(t,e,w,r),t}function k(t,e){for(var r=!1,n=0;n<t.length;n++)if(e===t[n]){r=!0;break}!1===r&&t.push(e)}p.estimateScale=function(t,e){for(var r=1+function(t){if(0!==t.length){for(var e=1,r=0;r<t.length;r++)e=y(e,t[r]);return e}}(0===e?this.calcXnums(t):this.calcYnums(t));r<b;)r*=2;for(;r>_;)r--,r/=v(r),++r<b&&(r=_);var n=Math.round(r/t);return n>1?n:1},p.refineCoords=function(t){for(var e=this.dataScaleX,r=this.dataScaleY,n=t[0].shape[0],a=t[0].shape[1],o=0|Math.floor(t[0].shape[0]*e+1),s=0|Math.floor(t[0].shape[1]*r+1),l=1+n+1,c=1+a+1,u=i(new Float32Array(l*c),[l,c]),f=[1/e,0,0,0,1/r,0,0,0,1],h=0;h<t.length;++h){this.surface.padField(u,t[h]);var p=i(new Float32Array(o*s),[o,s]);T(p,u,f),t[h]=p}},p.setContourLevels=function(){var t,e,r,n=[[],[],[]],i=[!1,!1,!1],a=!1;for(t=0;t<3;++t)if(this.showContour[t]&&(a=!0,this.contourSize[t]>0&&null!==this.contourStart[t]&&null!==this.contourEnd[t]&&this.contourEnd[t]>this.contourStart[t]))for(i[t]=!0,e=this.contourStart[t];e<this.contourEnd[t];e+=this.contourSize[t])r=e*this.scene.dataScale[t],k(n[t],r);if(a){var o=[[],[],[]];for(t=0;t<3;++t)this.showContour[t]&&(o[t]=i[t]?n[t]:this.scene.contourLevels[t]);this.surface.update({levels:o})}},p.update=function(t){var e,r,n,a,l=this.scene,h=l.fullSceneLayout,p=this.surface,d=c(t),g=l.dataScale,m=t.z[0].length,v=t._ylength,y=l.contourLevels;this.data=t;var x=[];for(e=0;e<3;e++)for(x[e]=[],r=0;r<m;r++)x[e][r]=[];for(r=0;r<m;r++)for(n=0;n<v;n++)x[0][r][n]=this.getXat(r,n,t.xcalendar,h.xaxis),x[1][r][n]=this.getYat(r,n,t.ycalendar,h.yaxis),x[2][r][n]=this.getZat(r,n,t.zcalendar,h.zaxis);if(t.connectgaps)for(t._emptypoints=s(x[2]),o(x[2],t._emptypoints),t._interpolatedZ=[],r=0;r<m;r++)for(t._interpolatedZ[r]=[],n=0;n<v;n++)t._interpolatedZ[r][n]=x[2][r][n];for(e=0;e<3;e++)for(r=0;r<m;r++)for(n=0;n<v;n++)null==(a=x[e][r][n])?x[e][r][n]=NaN:a=x[e][r][n]*=g[e];for(e=0;e<3;e++)for(r=0;r<m;r++)for(n=0;n<v;n++)null!=(a=x[e][r][n])&&(this.minValues[e]>a&&(this.minValues[e]=a),this.maxValues[e]<a&&(this.maxValues[e]=a));for(e=0;e<3;e++)this.objectOffset[e]=.5*(this.minValues[e]+this.maxValues[e]);for(e=0;e<3;e++)for(r=0;r<m;r++)for(n=0;n<v;n++)null!=(a=x[e][r][n])&&(x[e][r][n]-=this.objectOffset[e]);var b=[i(new Float32Array(m*v),[m,v]),i(new Float32Array(m*v),[m,v]),i(new Float32Array(m*v),[m,v])];for(e=0;e<3;e++)for(r=0;r<m;r++)for(n=0;n<v;n++)b[e].set(r,n,x[e][r][n]);x=[];var w={colormap:d,levels:[[],[],[]],showContour:[!0,!0,!0],showSurface:!t.hidesurface,contourProject:[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],contourWidth:[1,1,1],contourColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],contourTint:[1,1,1],dynamicColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],dynamicWidth:[1,1,1],dynamicTint:[1,1,1],opacityscale:t.opacityscale,opacity:t.opacity},T=f(t);if(w.intensityBounds=[T.min,T.max],t.surfacecolor){var k=i(new Float32Array(m*v),[m,v]);for(r=0;r<m;r++)for(n=0;n<v;n++)k.set(r,n,t.surfacecolor[n][r]);b.push(k)}else w.intensityBounds[0]*=g[2],w.intensityBounds[1]*=g[2];(_<b[0].shape[0]||_<b[0].shape[1])&&(this.refineData=!1),!0===this.refineData&&(this.dataScaleX=this.estimateScale(b[0].shape[0],0),this.dataScaleY=this.estimateScale(b[0].shape[1],1),1===this.dataScaleX&&1===this.dataScaleY||this.refineCoords(b)),t.surfacecolor&&(w.intensity=b.pop());var M=[!0,!0,!0],A=[\"x\",\"y\",\"z\"];for(e=0;e<3;++e){var S=t.contours[A[e]];M[e]=S.highlight,w.showContour[e]=S.show||S.highlight,w.showContour[e]&&(w.contourProject[e]=[S.project.x,S.project.y,S.project.z],S.show?(this.showContour[e]=!0,w.levels[e]=y[e],p.highlightColor[e]=w.contourColor[e]=u(S.color),S.usecolormap?p.highlightTint[e]=w.contourTint[e]=0:p.highlightTint[e]=w.contourTint[e]=1,w.contourWidth[e]=S.width,this.contourStart[e]=S.start,this.contourEnd[e]=S.end,this.contourSize[e]=S.size):(this.showContour[e]=!1,this.contourStart[e]=null,this.contourEnd[e]=null,this.contourSize[e]=0),S.highlight&&(w.dynamicColor[e]=u(S.highlightcolor),w.dynamicWidth[e]=S.highlightwidth))}(function(t){var e=t[0].rgb,r=t[t.length-1].rgb;return e[0]===r[0]&&e[1]===r[1]&&e[2]===r[2]&&e[3]===r[3]})(d)&&(w.vertexColor=!0),w.objectOffset=this.objectOffset,w.coords=b,p.update(w),p.visible=t.visible,p.enableDynamic=M,p.enableHighlight=M,p.snapToData=!0,\"lighting\"in t&&(p.ambientLight=t.lighting.ambient,p.diffuseLight=t.lighting.diffuse,p.specularLight=t.lighting.specular,p.roughness=t.lighting.roughness,p.fresnel=t.lighting.fresnel),\"lightposition\"in t&&(p.lightPosition=[t.lightposition.x,t.lightposition.y,t.lightposition.z])},p.dispose=function(){this.scene.glplot.remove(this.surface),this.surface.dispose()},e.exports=function(t,e){var r=t.glplot.gl,i=n({gl:r}),a=new h(t,i,e.uid);return i._trace=a,a.update(e),t.glplot.add(i),a}},{\"../../components/colorscale\":655,\"../../lib\":778,\"../../lib/gl_format_color\":774,\"../../lib/str2rgbarray\":802,\"../heatmap/find_empties\":1071,\"../heatmap/interp2d\":1074,\"gl-surface3d\":351,ndarray:495,\"ndarray-linear-interpolate\":489}],1314:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"../../components/colorscale/defaults\"),o=t(\"./attributes\");function s(t,e,r,n){var 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d=i.ensureSingle(h,\"g\",\"slicetext\"),T=i.ensureSingle(d,\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),E=i.ensureUniformFontSize(t,u.determineTextFont(C,s,S.font,{onPathbar:!0}));T.text(s._text||\" \").classed(\"slicetext\",!0).attr(\"text-anchor\",\"start\").call(a.font,E).call(o.convertToTspans,t),s.textBB=a.bBox(T.node()),s.transform=b(s,{fontSize:E.size,onPathbar:!0}),s.transform.fontSize=E.size,w?T.transition().attrTween(\"transform\",(function(t){var e=M(t,!0,A,[g,m]);return function(t){return _(e(t))}})):T.attr(\"transform\",_(s))}))}},{\"../../components/drawing\":665,\"../../lib\":778,\"../../lib/svg_text_utils\":803,\"../sunburst/fx\":1304,\"../sunburst/helpers\":1305,\"./constants\":1328,\"./partition\":1335,\"./style\":1337,d3:169}],1331:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../lib\"),a=t(\"../../components/drawing\"),o=t(\"../../lib/svg_text_utils\"),s=t(\"./partition\"),l=t(\"./style\").styleOne,c=t(\"./constants\"),u=t(\"../sunburst/helpers\"),f=t(\"../sunburst/fx\"),h=t(\"../sunburst/plot\").formatSliceLabel;e.exports=function(t,e,r,p,d){var 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strict\";e.exports={attributes:t(\"./attributes\"),layoutAttributes:t(\"./layout_attributes\"),supplyDefaults:t(\"./defaults\"),crossTraceDefaults:t(\"../box/defaults\").crossTraceDefaults,supplyLayoutDefaults:t(\"./layout_defaults\"),calc:t(\"./calc\"),crossTraceCalc:t(\"./cross_trace_calc\"),plot:t(\"./plot\"),style:t(\"./style\"),styleOnSelect:t(\"../scatter/style\").styleOnSelect,hoverPoints:t(\"./hover\"),selectPoints:t(\"../box/select\"),moduleType:\"trace\",name:\"violin\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"cartesian\",\"svg\",\"symbols\",\"oriented\",\"box-violin\",\"showLegend\",\"violinLayout\",\"zoomScale\"],meta:{}}},{\"../../plots/cartesian\":841,\"../box/defaults\":949,\"../box/select\":956,\"../scatter/style\":1211,\"./attributes\":1338,\"./calc\":1339,\"./cross_trace_calc\":1340,\"./defaults\":1341,\"./hover\":1343,\"./layout_attributes\":1345,\"./layout_defaults\":1346,\"./plot\":1347,\"./style\":1348}],1345:[function(t,e,r){\"use strict\";var 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f={\"stroke-width\":u+\"px\",\"stroke-dasharray\":2*u+\"px,\"+u+\"px\"};o.selectAll(\"path.mean\").style(f).call(i.stroke,c.color),o.selectAll(\"path.meanline\").style(f).call(i.stroke,c.color),a(o,r,t)}))}},{\"../../components/color\":643,\"../scatter/style\":1211,d3:169}],1349:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/attributes\"),i=t(\"../isosurface/attributes\"),a=t(\"../surface/attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../lib/extend\").extendFlat,l=t(\"../../plot_api/edit_types\").overrideAll,c=e.exports=l(s({x:i.x,y:i.y,z:i.z,value:i.value,isomin:i.isomin,isomax:i.isomax,surface:i.surface,spaceframe:{show:{valType:\"boolean\",dflt:!1},fill:{valType:\"number\",min:0,max:1,dflt:1}},slices:i.slices,caps:i.caps,text:i.text,hovertext:i.hovertext,hovertemplate:i.hovertemplate},n(\"\",{colorAttr:\"`value`\",showScaleDflt:!0,editTypeOverride:\"calc\"}),{colorbar:i.colorbar,opacity:i.opacity,opacityscale:a.opacityscale,lightposition:i.lightposition,lighting:i.lighting,flatshading:i.flatshading,contour:i.contour,hoverinfo:s({},o.hoverinfo),showlegend:s({},o.showlegend,{dflt:!1})}),\"calc\",\"nested\");c.x.editType=c.y.editType=c.z.editType=c.value.editType=\"calc+clearAxisTypes\",c.transforms=void 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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import plotly.express as px\n",
    "\n",
    "selection = ['age', 'height', 'income', 'optional_%unfilled']\n",
    "fig = px.histogram(df, x = selection, marginal = 'box', histnorm = 'percent').update_traces(visible = False, showlegend=False)\n",
    "fig.data[0].visible = True\n",
    "fig.data[1].visible = True\n",
    "\n",
    "def create_button(column):\n",
    "    temp = []\n",
    "    for each in selection:\n",
    "        temp.append(each == column)\n",
    "        temp.append(each == column)\n",
    "    return dict(\n",
    "                args=[{\"visible\": temp}],\n",
    "                label=column,\n",
    "                method=\"update\"\n",
    "                )\n",
    "\n",
    "fig.update_layout(\n",
    "    title = \"2012 OKCupid Profiles\",\n",
    "    updatemenus=[\n",
    "        #Add a dropdown selector\n",
    "        dict(\n",
    "            buttons = [create_button(column) for column in selection],\n",
    "            direction=\"down\",\n",
    "            pad={\"r\": 10, \"t\": 10},\n",
    "            showactive=True,\n",
    "        )\n",
    "\n",
    "    ]\n",
    ")\n",
    "fig.show()"
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  },
  {
   "cell_type": "markdown",
   "id": "authorized-cylinder",
   "metadata": {},
   "source": [
    "Use the dropdown selector to switch between features. Datapoints show more information on mouseover. The graph can be panned and zoomed.\n",
    "\n",
    "| Feature        | Comment      |\n",
    "| :------------- | :---------- |\n",
    "| Age | The median age is 30. The distribution is right-skewed. Most users are young and working adults.|\n",
    "|  Height        | Most heights range between 59 and 78 in (4.9 - 6.5 ft) with a median of 68in(5.67ft). The distribution appears normal. |\n",
    "|  Income        | The median income is \\\\$50k. A quarter of all incomes are $25k. Most income distributions are log-normal (if the ultra-wealthy are not included), and this is no different. |\n",
    "|All Features Above| From the box plot, we can see that all of the distributions have outliers - There is a 4.5% group of \\\\$1M earners. There are two people over 100 years old. There is a height of 1in. Below, we will inspect these data points (user profiles) to see what's really going on.|\n",
    "|optional_%unfilled| The y-axis shows the percentage of users and the x-axis shows the percentage of optional user information fields left unfilled. Interquartile Range is 12% - 30%, meaning half of all users don't bother to fill 12% - 30% of optional fields. A quarter of users are below that range and a quarter of users are above that range. This is a feature that was engineered from the given raw data.|"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "unlike-pantyhose",
   "metadata": {},
   "source": [
    "### Outlier Inspection"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "increasing-eagle",
   "metadata": {},
   "source": [
    "#### Age"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "precise-truck",
   "metadata": {},
   "source": [
    "Let's look a look at the profiles of our centennial users."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "conservative-helmet",
   "metadata": {},
   "outputs": [
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       "           last_online               location offspring orientation pets  \\\n",
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       "     religion sex sign smokes   speaks  status diet_adherence diet_type  \\\n",
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       "\n",
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       "2512  daly city    california            NaN                NaN           NaN   \n",
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       "     religion_attitude sign_type sign_attitude dog_preference cat_preference  \\\n",
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       "      has_dogs  has_cats  afrikaans  albanian  ancient greek  arabic  \\\n",
       "2512       NaN       NaN          0         0              0       0   \n",
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       "      armenian  basque  belarusan  bengali  breton  bulgarian  c++  catalan  \\\n",
       "2512         0       0          0        0       0          0    0        0   \n",
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       "      esperanto  estonian  farsi  finnish  french  frisian  georgian  german  \\\n",
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       "2512      0         0         0       0      0          0          0       0   \n",
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       "2512           0      0        0         0      0       0      0        0   \n",
       "\n",
       "      lisp  lithuanian  malay  maori  mongolian  norwegian  occitan  other  \\\n",
       "2512     0           0      0      0          0          0        0      0   \n",
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       "      persian  polish  portuguese  romanian  rotuman  russian  sanskrit  \\\n",
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       "      sardinian  serbian  sign language  slovak  slovenian  spanish  swahili  \\\n",
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       "2512        0        0      0     0        0        0          0     0   \n",
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       "      vietnamese  welsh  yiddish  num_ethnicities  optional_%unfilled  \\\n",
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       "\n",
       "      num_languages  \n",
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       "       age body_type          diet drinks  drugs                   education  \\\n",
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       "\n",
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       "\n",
       "                                  religion sex  \\\n",
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       "               religion_attitude sign_type      sign_attitude dog_preference  \\\n",
       "25324  somewhat serious about it  aquarius  it doesn’t matter           None   \n",
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       "       english  esperanto  estonian  farsi  finnish  french  frisian  \\\n",
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       "\n",
       "       icelandic  ilongo  indonesian  irish  italian  japanese  khmer  korean  \\\n",
       "25324          0       0           0      0        0         0      0       0   \n",
       "\n",
       "       latin  latvian  lisp  lithuanian  malay  maori  mongolian  norwegian  \\\n",
       "25324      0        0     0           0      0      0          0          0   \n",
       "\n",
       "       occitan  other  persian  polish  portuguese  romanian  rotuman  \\\n",
       "25324        0      0        0       0           0         0        0   \n",
       "\n",
       "       russian  sanskrit  sardinian  serbian  sign language  slovak  \\\n",
       "25324        0         0          0        0              0       0   \n",
       "\n",
       "       slovenian  spanish  swahili  swedish  tagalog  tamil  thai  tibetan  \\\n",
       "25324          0        0        0        0        0      0     0        0   \n",
       "\n",
       "       turkish  ukrainian  urdu  vietnamese  welsh  yiddish  num_ethnicities  \\\n",
       "25324        0          0     0           0      0        0              NaN   \n",
       "\n",
       "       optional_%unfilled  num_languages  \n",
       "25324           54.166667              1  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(df.iloc[2512:2513])\n",
    "display(df.iloc[25324:25325])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "honey-polyester",
   "metadata": {},
   "source": [
    "The first one has 95% unfilled optional fields. The second has 54% unfilled optional fields and a height of 95inches(8ft tall). Do you think these profiles are reliable?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "popular-eligibility",
   "metadata": {},
   "source": [
    "#### Height"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "printable-atlanta",
   "metadata": {},
   "source": [
    "Below is an example of the kind of user profile which 'has a height of 1 inch'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "spectacular-ministry",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mage:\u001b[0m 36\n",
      "\u001b[1mbody_type:\u001b[0m nan\n",
      "\u001b[1mdiet:\u001b[0m nan\n",
      "\u001b[1mdrinks:\u001b[0m very often\n",
      "\u001b[1mdrugs:\u001b[0m never\n",
      "\u001b[1meducation:\u001b[0m graduated from college/university\n",
      "\u001b[1messay0:\u001b[0m i'm a transplant from southern california with roots in lovely\n",
      "oakland. i find myself bored quite a bit. hence why i'm here. i\n",
      "like whiskey and\n",
      "find the term hipsters laughable yet amusing. the two\n",
      "seem to go hand in hand around oaklands many dive bars. people\n",
      "often describe me as \"intense\" or \"stoic\". i find either of those words\n",
      "loaded and annoying. i have a gift for writing and although i take myself\n",
      "pretty seriously, i don't take this online stuff too seriously. i'm\n",
      "looking to find someone a little more burly than me who enjoys a\n",
      "good day holding hands on the beach, whale watching and a fantastic\n",
      "trip to the olive garden.\n",
      "\n",
      "i am nerdcore, nice smelling, and a unique snowflake\n",
      "\u001b[1messay1:\u001b[0m living each day as if it'd be my last, and managing to hold down a\n",
      "day-job in the process.\n",
      "\n",
      "of course i'm going to make a crack at\n",
      "wanting a quaint craftsman home in rockridge; complete with a white\n",
      "picket fence, a loving wife (preferably not mail order), 2.5 kids,\n",
      "and a green prius parked in the driveway.\n",
      "\n",
      "with a pony...\n",
      "\n",
      "just kidding.\n",
      "\u001b[1messay2:\u001b[0m writing, rambling, fixing anything thats breakable, photography.\n",
      "drinking you under the table. traveling the road less traveled.\n",
      "\u001b[1messay3:\u001b[0m my otherwise perfect hair, my half-sleeve tattoo(s), my perfect\n",
      "teeth i suppose. oh and my rather dry and snarky sense of humor.\n",
      "\u001b[1messay4:\u001b[0m i enjoy reading louis sachar, james burke, alan kaufman,hunter s.\n",
      "thompson, chuck palahniuk for starters.\n",
      "\n",
      "as far as music goes: i tend to listen to old and new punk with\n",
      "bouts involving the classics:\n",
      "frank sinatra\n",
      "tom waits\n",
      "frankie avalon\n",
      "the misfits\n",
      "crass\n",
      "love and rockets\n",
      "ugly ducklings\n",
      "beastie boys\n",
      "the vandals\n",
      "propaghandi\n",
      "minor threat\n",
      "sonic youth\n",
      "anything like old crusty-punk on stereophonic vinyl\n",
      "you get the idea.\n",
      "\n",
      "i noticed that its a very \"hipster\" thing to say that you don't own\n",
      "or even like tv's when i actually own 2 *and* tivo. hows that for\n",
      "going against the grain?\n",
      "\n",
      "netflix, hulu and rapidshare are my best friend.\n",
      "\u001b[1messay5:\u001b[0m irish whiskey\n",
      "broadband internet\n",
      "my iphone\n",
      "a decent pair of good fitting jeans\n",
      "cheese\n",
      "my needy and probably neurotic cat \"peanut\"\n",
      "\u001b[1messay6:\u001b[0m zombies, and ways not to get eaten by them.\n",
      "\n",
      "my next big adventure\n",
      "\u001b[1messay7:\u001b[0m peering through the bottom of a whiskey glass.\n",
      "\n",
      "perpetually rearranging my itunes playlist.\n",
      "\n",
      "riding my iconic vintage peugeot fixed-gear conversion bicycle\n",
      "uphill on a pbr run.\n",
      "\n",
      "writing poetry in spiral patterns on napkins in various coffee\n",
      "shops and giving them to complete strangers.\n",
      "\u001b[1messay8:\u001b[0m i can't stand online dating, or the stigma attached to it.\n",
      "\u001b[1messay9:\u001b[0m if you're a ninja (with skills) or a pirate. you're well mannered.\n",
      "you're not a raging sociopath or a creeper. you like whiskey, you\n",
      "know your whiskeys. you dont type like dis. and if you picked up on\n",
      "the dry sarcasm , you should **definitely** message me.\n",
      "\u001b[1methnicity:\u001b[0m nan\n",
      "\u001b[1mheight:\u001b[0m 1.0\n",
      "\u001b[1mincome:\u001b[0m 80000.0\n",
      "\u001b[1mjob:\u001b[0m science / tech / engineering\n",
      "\u001b[1mlast_online:\u001b[0m 2012-06-28-14-18\n",
      "\u001b[1mlocation:\u001b[0m oakland, california\n",
      "\u001b[1moffspring:\u001b[0m nan\n",
      "\u001b[1morientation:\u001b[0m straight\n",
      "\u001b[1mpets:\u001b[0m likes dogs and has cats\n",
      "\u001b[1mreligion:\u001b[0m judaism and laughing about it\n",
      "\u001b[1msex:\u001b[0m m\n",
      "\u001b[1msign:\u001b[0m leo and it’s fun to think about\n",
      "\u001b[1msmokes:\u001b[0m when drinking\n",
      "\u001b[1mspeaks:\u001b[0m english (fluently), c++ (fluently), hebrew (poorly), other (poorly)\n",
      "\u001b[1mstatus:\u001b[0m single\n",
      "\u001b[1mdiet_adherence:\u001b[0m nan\n",
      "\u001b[1mdiet_type:\u001b[0m nan\n",
      "\u001b[1mcity:\u001b[0m oakland\n",
      "\u001b[1mstate/country:\u001b[0m  california\n",
      "\u001b[1moffspring_want:\u001b[0m nan\n",
      "\u001b[1moffspring_attitude:\u001b[0m nan\n",
      "\u001b[1mreligion_type:\u001b[0m judaism\n",
      "\u001b[1mreligion_attitude:\u001b[0m laughing about it\n",
      "\u001b[1msign_type:\u001b[0m leo\n",
      "\u001b[1msign_attitude:\u001b[0m it’s fun to think about\n",
      "\u001b[1mdog_preference:\u001b[0m likes dogs\n",
      "\u001b[1mcat_preference:\u001b[0m None\n",
      "\u001b[1mhas_dogs:\u001b[0m 0.0\n",
      "\u001b[1mhas_cats:\u001b[0m 1.0\n",
      "\u001b[1mafrikaans:\u001b[0m 0\n",
      "\u001b[1malbanian:\u001b[0m 0\n",
      "\u001b[1mancient greek:\u001b[0m 0\n",
      "\u001b[1marabic:\u001b[0m 0\n",
      "\u001b[1marmenian:\u001b[0m 0\n",
      "\u001b[1mbasque:\u001b[0m 0\n",
      "\u001b[1mbelarusan:\u001b[0m 0\n",
      "\u001b[1mbengali:\u001b[0m 0\n",
      "\u001b[1mbreton:\u001b[0m 0\n",
      "\u001b[1mbulgarian:\u001b[0m 0\n",
      "\u001b[1mc++:\u001b[0m 1\n",
      "\u001b[1mcatalan:\u001b[0m 0\n",
      "\u001b[1mcebuano:\u001b[0m 0\n",
      "\u001b[1mchechen:\u001b[0m 0\n",
      "\u001b[1mchinese:\u001b[0m 0\n",
      "\u001b[1mcroatian:\u001b[0m 0\n",
      "\u001b[1mczech:\u001b[0m 0\n",
      "\u001b[1mdanish:\u001b[0m 0\n",
      "\u001b[1mdutch:\u001b[0m 0\n",
      "\u001b[1menglish:\u001b[0m 1\n",
      "\u001b[1mesperanto:\u001b[0m 0\n",
      "\u001b[1mestonian:\u001b[0m 0\n",
      "\u001b[1mfarsi:\u001b[0m 0\n",
      "\u001b[1mfinnish:\u001b[0m 0\n",
      "\u001b[1mfrench:\u001b[0m 0\n",
      "\u001b[1mfrisian:\u001b[0m 0\n",
      "\u001b[1mgeorgian:\u001b[0m 0\n",
      "\u001b[1mgerman:\u001b[0m 0\n",
      "\u001b[1mgreek:\u001b[0m 0\n",
      "\u001b[1mgujarati:\u001b[0m 0\n",
      "\u001b[1mhawaiian:\u001b[0m 0\n",
      "\u001b[1mhebrew:\u001b[0m 1\n",
      "\u001b[1mhindi:\u001b[0m 0\n",
      "\u001b[1mhungarian:\u001b[0m 0\n",
      "\u001b[1micelandic:\u001b[0m 0\n",
      "\u001b[1milongo:\u001b[0m 0\n",
      "\u001b[1mindonesian:\u001b[0m 0\n",
      "\u001b[1mirish:\u001b[0m 0\n",
      "\u001b[1mitalian:\u001b[0m 0\n",
      "\u001b[1mjapanese:\u001b[0m 0\n",
      "\u001b[1mkhmer:\u001b[0m 0\n",
      "\u001b[1mkorean:\u001b[0m 0\n",
      "\u001b[1mlatin:\u001b[0m 0\n",
      "\u001b[1mlatvian:\u001b[0m 0\n",
      "\u001b[1mlisp:\u001b[0m 0\n",
      "\u001b[1mlithuanian:\u001b[0m 0\n",
      "\u001b[1mmalay:\u001b[0m 0\n",
      "\u001b[1mmaori:\u001b[0m 0\n",
      "\u001b[1mmongolian:\u001b[0m 0\n",
      "\u001b[1mnorwegian:\u001b[0m 0\n",
      "\u001b[1moccitan:\u001b[0m 0\n",
      "\u001b[1mother:\u001b[0m 1\n",
      "\u001b[1mpersian:\u001b[0m 0\n",
      "\u001b[1mpolish:\u001b[0m 0\n",
      "\u001b[1mportuguese:\u001b[0m 0\n",
      "\u001b[1mromanian:\u001b[0m 0\n",
      "\u001b[1mrotuman:\u001b[0m 0\n",
      "\u001b[1mrussian:\u001b[0m 0\n",
      "\u001b[1msanskrit:\u001b[0m 0\n",
      "\u001b[1msardinian:\u001b[0m 0\n",
      "\u001b[1mserbian:\u001b[0m 0\n",
      "\u001b[1msign language:\u001b[0m 0\n",
      "\u001b[1mslovak:\u001b[0m 0\n",
      "\u001b[1mslovenian:\u001b[0m 0\n",
      "\u001b[1mspanish:\u001b[0m 0\n",
      "\u001b[1mswahili:\u001b[0m 0\n",
      "\u001b[1mswedish:\u001b[0m 0\n",
      "\u001b[1mtagalog:\u001b[0m 0\n",
      "\u001b[1mtamil:\u001b[0m 0\n",
      "\u001b[1mthai:\u001b[0m 0\n",
      "\u001b[1mtibetan:\u001b[0m 0\n",
      "\u001b[1mturkish:\u001b[0m 0\n",
      "\u001b[1mukrainian:\u001b[0m 0\n",
      "\u001b[1murdu:\u001b[0m 0\n",
      "\u001b[1mvietnamese:\u001b[0m 0\n",
      "\u001b[1mwelsh:\u001b[0m 0\n",
      "\u001b[1myiddish:\u001b[0m 0\n",
      "\u001b[1mnum_ethnicities:\u001b[0m nan\n",
      "\u001b[1moptional_%unfilled:\u001b[0m 16.666666666666664\n",
      "\u001b[1mnum_languages:\u001b[0m 4\n"
     ]
    }
   ],
   "source": [
    "show_user_data(df, 45959)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "behavioral-pizza",
   "metadata": {},
   "source": [
    "#### Income"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "textile-richmond",
   "metadata": {},
   "source": [
    "Below is the profile of someone who has an income of \\$1M."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "southwest-mechanics",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mage:\u001b[0m 32\n",
      "\u001b[1mbody_type:\u001b[0m fit\n",
      "\u001b[1mdiet:\u001b[0m anything\n",
      "\u001b[1mdrinks:\u001b[0m socially\n",
      "\u001b[1mdrugs:\u001b[0m never\n",
      "\u001b[1meducation:\u001b[0m graduated from space camp\n",
      "\u001b[1messay0:\u001b[0m update: okstupid removed my macbook \"fun house mirror\" effect\n",
      "self-portrait, so you will no longer be able to see how hideously\n",
      "disfigured i was in that photo. apparently, pictures of the back of\n",
      "your head are o.k., but pictures taken with a slightly distorting\n",
      "lens are not. is that how it works? i don't quite get it.\n",
      "\n",
      "mi hermana hablas espanol sehr gut. aber yo hablo espanol solamente\n",
      "en restorants.\n",
      "\n",
      "por ehemplo:\n",
      "\n",
      "\"por favor, ocho tacos en dos platos para llevar. si, quatro y\n",
      "quatro. quatro de asada y quatro de carnitas. con todo. si, para\n",
      "llevar. yo already hablandoed that.\"\n",
      "\n",
      "update: i am no longer eating cheap-ass tacos.\n",
      "\n",
      "zdes' net russkoi klaviatury, tak chto, pridetsa popol'zovatsa\n",
      "transliteracijej.\n",
      "\n",
      "schas, posmotrim, chto napisal po-anglijskij, i perevozhu.\n",
      "\n",
      "mm, da. ja javno byl nemnogo nedovolen etim saitom kogda pridumal\n",
      "svoj username.\n",
      "\n",
      "mne nravyatsa sobaki. mne nravitsa snowboarding. ya tol'ko nedavno\n",
      "nachal chasto ezdit' snowboarding. v pozoproshlom sezone gde-to\n",
      "10-12 dnei posnowboardal. a v proshlom sezone kak-to ne poluchilas'\n",
      "- vsego 4-5 dnei snowboardal.\n",
      "\u001b[1messay1:\u001b[0m what's the point of winter? i mean in the mountains. i want to go\n",
      "snowboarding\n",
      "right now.\n",
      "\u001b[1messay2:\u001b[0m nothing. i suck at everything.\n",
      "\n",
      "april 11th addendum: apparently my above opinion means i'm actually\n",
      "good at everything, which is what people have been telling me. but\n",
      "they're all incompetent (sp?).\n",
      "\n",
      "http://www.zenspider.com/rwd/thoughts/inept.html\n",
      "\n",
      "i enjoy long walks on the moon with my pet lap giraffe.\n",
      "\u001b[1messay3:\u001b[0m is that i'm there.\n",
      "\u001b[1messay4:\u001b[0m ich liebe gern nur rammstein.\n",
      "\n",
      "du hast.\n",
      "\n",
      "du hasst mich.\n",
      "\n",
      "du hasst mich!\n",
      "\n",
      "du hast mich gefragt. du hast mich gefragt. du hast mich\n",
      "gefragt,\n",
      "und ich hab nichts gesagt.\n",
      "\n",
      "that song is so deep.\n",
      "\n",
      "movies: universal soldier, big momma's house, norbit (or\n",
      "anything\n",
      "else with eddy murphy since about 1995), anything starring\n",
      "kurt\n",
      "russell (except captain ron and big trouble in little china).\n",
      "species viii. jurassic park iv (straight to video). the 6th\n",
      "element\n",
      "(sequel to the 5th element, also straight to video, and\n",
      "starring\n",
      "milla jovovich's little sister, milla jovovich). 7th sense\n",
      "(sequel\n",
      "to 6th sense). ocean's 2.35 x 10^3(starring 800 cgi clones each\n",
      "of\n",
      "brad pittt, georgi cluni, and milla jovovich's little sister,\n",
      "milla\n",
      "jovovich). best movie ever: jordi laforge, the movie. i don't\n",
      "think\n",
      "i can list all my favorites. the list is just going too long.\n",
      "anything with bill pullman, except spaceballs and independence\n",
      "day\n",
      "(wait... was there anything else?). etc.,etc.,et.,ce.t,c.,t\n",
      "\n",
      "music: i can't tell you because if i list anything first it\n",
      "will\n",
      "seem like that's what i probably like most and will seem to\n",
      "define\n",
      "me as a particular character in your pop-culture dictionary.\n",
      "i\n",
      "don't watch t.v. and don't care if you do. i don't feel\n",
      "self-important about it. but it also means i am much less\n",
      "affected\n",
      "by the minute-to-minute cultural updates in terminology and\n",
      "opinions and events that inform the masses. i might not have\n",
      "any\n",
      "idea who your are talking about a lot of the time. i just listen\n",
      "to\n",
      "music that i like.\n",
      "\n",
      "but i like [portishead], [led zeppelin],[bach],\n",
      "blues, blues rock, some jazz, electronic music... whatever is\n",
      "danceable and singable (i.e. more complex than a monotonous\n",
      "repetitive beat).\n",
      "\n",
      "books: haven't read much fiction lately. most fiction these\n",
      "days\n",
      "seems to be a sham. how many books were published last year?\n",
      "compare that to the number of books worth reading that were\n",
      "published in the 20th century. so, generally, if you avoid reading\n",
      "new books you are probably avoiding bad books. there are many\n",
      "proven masterpieces out there.\n",
      "\n",
      "i liked the trial (kafka)a lot.\n",
      "i like russian authors a lot (dead souls is one of the funniest\n",
      "books i've ever read). i love funny books. [catch-22], some kurt\n",
      "vonnegut. but\n",
      "lately i have been reading more nonfiction.\n",
      "\n",
      "and i much enjoyed the 10-15 [shakespeare] plays i've seen,\n",
      "though\n",
      "i've only read few.\n",
      "\n",
      "i read [illiad] and [odyssey] last year. they are now two of\n",
      "my favorite books. i tried to read the aeneid, but, i'm sorry,\n",
      "it\n",
      "just sucks. i think i managed to get through about 1/3 of it. the\n",
      "epithets are less prevalent. the repeated phrases, like,\n",
      "\"dawn with her rose-red fingers...\" that began many verses in\n",
      "homer\n",
      "and helped tie together his story are sorely lacking in\n",
      "virgil's\n",
      "[aeneid]. i thought that because it was translated by the\n",
      "same\n",
      "brilliant man, robert fagles, whose translations of homer i\n",
      "read,\n",
      "it would be just as good. apparently, a book's quality depends\n",
      "on\n",
      "more than just its translator.\n",
      "\n",
      "this is funny to me:\n",
      "\n",
      " .  ,  \n",
      "\n",
      "     . \n",
      "\n",
      "  : , , - \n",
      ",\n",
      "   ,       \n",
      "!\n",
      ",  !       \n",
      "\n",
      "\n",
      ", , ,  ,    \n",
      ".\n",
      "   ,   - ,   \n",
      "\n",
      ". , !   .  - , \n",
      ",\n",
      " ,       ! \n",
      ",\n",
      "        , \n",
      "\n",
      "  ,      \n",
      " ,     ,  \n",
      "\n",
      "    .   !  \n",
      ".\n",
      " ,  !    ,\n",
      ",\n",
      ",   ,  ! 1 , , \n",
      "\n",
      "      ,    \n",
      "\n",
      "   ,     .\n",
      ",\n",
      ",  ,       ,\n",
      "\n",
      " ,       ,  \n",
      "\n",
      "     .    \n",
      ",\n",
      "     .\n",
      "\u001b[1messay5:\u001b[0m 1.) the layer of apprehension that intercedes between reality and\n",
      "the perceiver.\n",
      "2.) if perveiver isn't a word, then insert whatever word you\n",
      "like.\n",
      "c.) alphabet.\n",
      "\u001b[1messay6:\u001b[0m thinking about thinking.\n",
      "\u001b[1messay7:\u001b[0m may it never be typical.\n",
      "\u001b[1messay8:\u001b[0m is the stuff i wrote in the other sections. isn't that obvious?\n",
      "\u001b[1messay9:\u001b[0m you can't find any good reason not to.\n",
      "\n",
      "or ...\n",
      "\n",
      "if you want to help me finish off this johnnie walker, green label.\n",
      "i'm not a big hard alcohol fan (i.e. not an alcoholic), but this\n",
      "stuff is so good. and most times when it comes up, people think i'm\n",
      "making it (green label) up, which i can understand. i used to be\n",
      "really gullible when i was a kid. one kid in my class told me that\n",
      "there was a super mario bros. 34 in japan and described all kinds\n",
      "of awesome things you could do in it. japan is really futuristic,\n",
      "and video games come out there decades before they do here. the wii\n",
      "came out in the 1920's. so, i can understand why people might think\n",
      "i'm pulling their leg(s). but now they can just check the internet\n",
      "and see that i'm right. just don't check wikipedia, because i've\n",
      "modified a few articles where i thought fact was less instructive\n",
      "than fiction.\n",
      "\n",
      "never mind, you're too late. i already finished it.\n",
      "\u001b[1methnicity:\u001b[0m asian, middle eastern, black, native american, indian, pacific islander, hispanic / latin, white, other\n",
      "\u001b[1mheight:\u001b[0m 70.0\n",
      "\u001b[1mincome:\u001b[0m 1000000.0\n",
      "\u001b[1mjob:\u001b[0m science / tech / engineering\n",
      "\u001b[1mlast_online:\u001b[0m 2012-06-28-20-59\n",
      "\u001b[1mlocation:\u001b[0m san francisco, california\n",
      "\u001b[1moffspring:\u001b[0m nan\n",
      "\u001b[1morientation:\u001b[0m straight\n",
      "\u001b[1mpets:\u001b[0m likes dogs\n",
      "\u001b[1mreligion:\u001b[0m nan\n",
      "\u001b[1msex:\u001b[0m m\n",
      "\u001b[1msign:\u001b[0m nan\n",
      "\u001b[1msmokes:\u001b[0m no\n",
      "\u001b[1mspeaks:\u001b[0m english (fluently), russian (fluently), german (okay), french (okay), spanish (okay)\n",
      "\u001b[1mstatus:\u001b[0m single\n",
      "\u001b[1mdiet_adherence:\u001b[0m [No Prefix]\n",
      "\u001b[1mdiet_type:\u001b[0m anything\n",
      "\u001b[1mcity:\u001b[0m san francisco\n",
      "\u001b[1mstate/country:\u001b[0m  california\n",
      "\u001b[1moffspring_want:\u001b[0m nan\n",
      "\u001b[1moffspring_attitude:\u001b[0m nan\n",
      "\u001b[1mreligion_type:\u001b[0m nan\n",
      "\u001b[1mreligion_attitude:\u001b[0m nan\n",
      "\u001b[1msign_type:\u001b[0m nan\n",
      "\u001b[1msign_attitude:\u001b[0m nan\n",
      "\u001b[1mdog_preference:\u001b[0m likes dogs\n",
      "\u001b[1mcat_preference:\u001b[0m None\n",
      "\u001b[1mhas_dogs:\u001b[0m 0.0\n",
      "\u001b[1mhas_cats:\u001b[0m 0.0\n",
      "\u001b[1mafrikaans:\u001b[0m 0\n",
      "\u001b[1malbanian:\u001b[0m 0\n",
      "\u001b[1mancient greek:\u001b[0m 0\n",
      "\u001b[1marabic:\u001b[0m 0\n",
      "\u001b[1marmenian:\u001b[0m 0\n",
      "\u001b[1mbasque:\u001b[0m 0\n",
      "\u001b[1mbelarusan:\u001b[0m 0\n",
      "\u001b[1mbengali:\u001b[0m 0\n",
      "\u001b[1mbreton:\u001b[0m 0\n",
      "\u001b[1mbulgarian:\u001b[0m 0\n",
      "\u001b[1mc++:\u001b[0m 0\n",
      "\u001b[1mcatalan:\u001b[0m 0\n",
      "\u001b[1mcebuano:\u001b[0m 0\n",
      "\u001b[1mchechen:\u001b[0m 0\n",
      "\u001b[1mchinese:\u001b[0m 0\n",
      "\u001b[1mcroatian:\u001b[0m 0\n",
      "\u001b[1mczech:\u001b[0m 0\n",
      "\u001b[1mdanish:\u001b[0m 0\n",
      "\u001b[1mdutch:\u001b[0m 0\n",
      "\u001b[1menglish:\u001b[0m 1\n",
      "\u001b[1mesperanto:\u001b[0m 0\n",
      "\u001b[1mestonian:\u001b[0m 0\n",
      "\u001b[1mfarsi:\u001b[0m 0\n",
      "\u001b[1mfinnish:\u001b[0m 0\n",
      "\u001b[1mfrench:\u001b[0m 1\n",
      "\u001b[1mfrisian:\u001b[0m 0\n",
      "\u001b[1mgeorgian:\u001b[0m 0\n",
      "\u001b[1mgerman:\u001b[0m 1\n",
      "\u001b[1mgreek:\u001b[0m 0\n",
      "\u001b[1mgujarati:\u001b[0m 0\n",
      "\u001b[1mhawaiian:\u001b[0m 0\n",
      "\u001b[1mhebrew:\u001b[0m 0\n",
      "\u001b[1mhindi:\u001b[0m 0\n",
      "\u001b[1mhungarian:\u001b[0m 0\n",
      "\u001b[1micelandic:\u001b[0m 0\n",
      "\u001b[1milongo:\u001b[0m 0\n",
      "\u001b[1mindonesian:\u001b[0m 0\n",
      "\u001b[1mirish:\u001b[0m 0\n",
      "\u001b[1mitalian:\u001b[0m 0\n",
      "\u001b[1mjapanese:\u001b[0m 0\n",
      "\u001b[1mkhmer:\u001b[0m 0\n",
      "\u001b[1mkorean:\u001b[0m 0\n",
      "\u001b[1mlatin:\u001b[0m 0\n",
      "\u001b[1mlatvian:\u001b[0m 0\n",
      "\u001b[1mlisp:\u001b[0m 0\n",
      "\u001b[1mlithuanian:\u001b[0m 0\n",
      "\u001b[1mmalay:\u001b[0m 0\n",
      "\u001b[1mmaori:\u001b[0m 0\n",
      "\u001b[1mmongolian:\u001b[0m 0\n",
      "\u001b[1mnorwegian:\u001b[0m 0\n",
      "\u001b[1moccitan:\u001b[0m 0\n",
      "\u001b[1mother:\u001b[0m 0\n",
      "\u001b[1mpersian:\u001b[0m 0\n",
      "\u001b[1mpolish:\u001b[0m 0\n",
      "\u001b[1mportuguese:\u001b[0m 0\n",
      "\u001b[1mromanian:\u001b[0m 0\n",
      "\u001b[1mrotuman:\u001b[0m 0\n",
      "\u001b[1mrussian:\u001b[0m 1\n",
      "\u001b[1msanskrit:\u001b[0m 0\n",
      "\u001b[1msardinian:\u001b[0m 0\n",
      "\u001b[1mserbian:\u001b[0m 0\n",
      "\u001b[1msign language:\u001b[0m 0\n",
      "\u001b[1mslovak:\u001b[0m 0\n",
      "\u001b[1mslovenian:\u001b[0m 0\n",
      "\u001b[1mspanish:\u001b[0m 1\n",
      "\u001b[1mswahili:\u001b[0m 0\n",
      "\u001b[1mswedish:\u001b[0m 0\n",
      "\u001b[1mtagalog:\u001b[0m 0\n",
      "\u001b[1mtamil:\u001b[0m 0\n",
      "\u001b[1mthai:\u001b[0m 0\n",
      "\u001b[1mtibetan:\u001b[0m 0\n",
      "\u001b[1mturkish:\u001b[0m 0\n",
      "\u001b[1mukrainian:\u001b[0m 0\n",
      "\u001b[1murdu:\u001b[0m 0\n",
      "\u001b[1mvietnamese:\u001b[0m 0\n",
      "\u001b[1mwelsh:\u001b[0m 0\n",
      "\u001b[1myiddish:\u001b[0m 0\n",
      "\u001b[1mnum_ethnicities:\u001b[0m 9.0\n",
      "\u001b[1moptional_%unfilled:\u001b[0m 12.5\n",
      "\u001b[1mnum_languages:\u001b[0m 5\n"
     ]
    }
   ],
   "source": [
    "show_user_data(df, 27590)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "collaborative-green",
   "metadata": {},
   "source": [
    "Graduated from space camp, complains about OKCupid picture takedown in essay0, nine ethnicities, five languages, 5' 10\" in height. Do you think this income is reliable?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "assisted-fellowship",
   "metadata": {},
   "source": [
    "### Decision on Outliers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "innovative-writer",
   "metadata": {},
   "source": [
    "We will remove outliers for _age_ and _height_. Outliers have the potential to greatly increase memory usage, variance, and training time. The current objective is to make a predictive model that works. If that objective is accomplished, we have the option of reiterating on this project to incorporate outliers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "representative-effect",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[(df['height'] >= 57) & (df['height'] <= 80) & (df['age'] <= 69)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "exotic-drink",
   "metadata": {},
   "source": [
    "## Categorical Features"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "positive-development",
   "metadata": {},
   "source": [
    "### Interactive Treemap (only interactive if opened with Jupyter Notebooks and required packages are installed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "hungarian-thumbnail",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2fe50ec353074b3599d6cdac110f2007",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='feature', options=('body_type', 'diet', 'drinks', 'drugs', 'educat…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function __main__.make_treemap(df, feature, dropna)>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from ipywidgets import interact, fixed\n",
    "\n",
    "def make_treemap(df, feature, dropna):\n",
    "    counts_table = df[feature].value_counts(normalize = True, dropna = dropna).reset_index()\n",
    "    counts_table.rename(columns={feature: 'Percent'}, inplace = True)\n",
    "    counts_table['Percent'] = counts_table['Percent'] * 100\n",
    "    if dropna:\n",
    "        names = 'index'\n",
    "    else:\n",
    "        names = counts_table['index'].apply(str)\n",
    "    fig = px.treemap(\n",
    "        counts_table,\n",
    "        parents = [feature] * len(counts_table), #Need to define a tree root\n",
    "        names = names,\n",
    "        values = 'Percent',\n",
    "        title = '2012 OKCupid Profiles',\n",
    "        color = 'Percent',\n",
    "        color_continuous_scale='Blues'\n",
    "    )\n",
    "    fig.update_traces(marker_showscale=False, texttemplate='%{label}<br>%{value:.2f%}%')\n",
    "    fig.show()\n",
    "    \n",
    "essay_feats = ['essay0','essay1','essay2','essay3','essay4','essay5','essay6','essay7','essay8','essay9',]\n",
    "numerical_feats = ['age', 'height', 'income']\n",
    "drop_list = essay_feats + numerical_feats + ['last_online']\n",
    "interact(make_treemap, df = fixed(df), feature = [each for each in df.columns if each not in drop_list], dropna = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "small-amplifier",
   "metadata": {},
   "source": [
    "An interactive tool for visualizing the categorical features as a treemap. The dropdown selector allows us to choose the feature to display, and the tickbox allows us to choose whether to include NaN values in the treemap."
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "tender-bikini",
   "metadata": {},
   "source": [
    "### Static Image Preview\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "naval-spouse",
   "metadata": {},
   "source": [
    "### Dashboard style donut plot grid of variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "described-knitting",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "**Nan represents unfilled/unshared optional information, signifiying that a user has not shared the\n",
      " respective information with OKCupid and it's missing from their profile\n",
      "\u001b[1m*Extrapolated or split from raw data variables\u001b[0m\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1152x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Ey1SWFeOzD94IzZ87qypaG15QVrzlNmZe2dF5CSE6Hyn6hSWIiKA4ptr9udcr/ryhgYlHFXiG7G4nReaK7E6YGfGtKxH8dkZxsmzjFjVS9S9Oxd9h5lRH5yaEEOL3iMhmIxwwIJOu7+23jbh8D2fhMSPtdqeSXqt+U278NB7fOv4frqNOvdjSuKLl1q9egZnPP1iyduWyzdWVZdPjsdp3mVnt6LyEEJ2DFP3CFCJy2Tz+82yujKu8I/bO9084Msvulxl8ewI1GkR4yZxQeMUnlZyMzVJDFfcy87aOzksIIXo6IvIWZNClARddfMLO9pxLJjqzdjQhnxkLN6fwl0VD4jc+8bGrzU4iWiRUU4k5s54Pfv7hmxWx2shLVRUlDzBzZUfnJYToWFL0i7QQUZ7iy73W5vKe7J9wVL5vzBQP2Z0dnZboAMwaYhuXaTUL3yhO1RT/oNaUXsPMqzo6LyGE6GmIKLePn67PdNOJ1+7lLDhtjMPlsLhVvzH6uP5U8p531su4/k5CVVUsWjA39dZLj5RUlZcsLive8k9mXtrReQkhOoYU/aJViGiEEiiYrvhy9sza6+Qi9+AJClHbtR6IriVRthHV818sSZauX5WqKfkbMy/q6JyEEKK7I6IB/TPp9qIMOuDm/V1Fhw21K/p8fe1n4tPR5BXPLnf4Alntel6xY1s2rMabz95ftmrFol/LS7Zdpaqpbzs6JyFE+5KiX7QIEY2xZxY+4igYNCJr79MKnQWDOzqlNsOsQasNQo1UQYtHwIkYtGQMnIiqWqI2ocVrE5yoTWmJqAoGYLMRkY1gU0A2G0F/TWSz22xun0vxZrpsrgyyuTNgc/tgc/lgc2egO/eMSNWUonrBy+XxzSs2quHK61hNfsLyy0YIISxFRGMGZtE9w3JsY287wNVrj74dN4/OPz6Jx8t2+6fr8JMuaJP4zIzacBA11RUIVlUgWF2BSLhGTcRjqUQ89r+v8VhUjcejWiIe04hs5HS6bE6XmxxOl+J0uRWny60Yr+0+f5Y9kJWDQFYuAlk58AWyYbN134aM8tJteO3Ju8tX/Pj1+srS7X9LJhPzOzonIUT7kKJfNIuIRiqZBQ+7CoeOzTrgvAJHVlFHp2QKM0OLVCNZtRXJyq3JVNW2YKqmNKGGyjUtGU9ATcZZTUYBKgV4E6upMlaTVZyIVnEqEQQQBhAx/tQCetkPQDH+2Op9dQAIgGw5No+/iOyuXmRT8gHkApwDUAY5XB6yO932QL5iz+njdmT3DtgzCxQlUAC7Pw9dfSJENVKNmm9nVEVXf7NdjQZv4kTtLCn+hRDCHLuNdu+fSQ/u1kcZ/H/7uwpG5FkzC78ZCzalcNWPw+PXPzYnrXH94WA1irduQPGWDbx5/aqaTetWRstLt6VSyWQilUwkUqlkHEAVgGI1ldpaGwltrA0HywDEAMSNP/VfxwEQACcAVyNfXd4Mf4HXF+hvtzv6AChi5lzFbnfb7Q6n3eF05uQV2vsOGu7uP3hkZlGfgUphnwHIyslHe/eisFpVRSneeObeih+/+WxTVUXptclEXB7MC9HNSdEvGkVEQ5RAwUPO/AETsg84v9CR27ejU2oVZoYaLEOidB0SJWtrEsVrIqlQRYKTsTAYW1hNLlVDFYsA3ghgO4CSjlrjlogUAIUABoBsAxRfzihSHCMBHkIOV6aSkeN29R7hdfYaluXIGwB7ZgG62pAKLV6Lmm9n1tT+/PmmVKjiL6wmv+zonIQQoqshop0HZtFj+/S373znQa683v7Ocy2IpxijntzxuP7qyjKsW7Ucq1f8ULNqxfeRmqqKeDwWrdU0tURT1Z9rqioWJ+LR1QDWQr82d8iNKumVfS6AwYrdPjQ7t3C83e4YBUIfl8uTkeHPdA8ZuYt7+OgJ2QOH7mwr6jsIitLxD19ao6aqHDOee7Dy+/kfba2pKrsmFq39qKNzEkK0DSn6xe8QUX8lUPCAI6fPpOwDzy9y5g/s6JRaRK2tQWL7asQ2r6iMb/k5qtbWhMDaKi0a+lSLR34E8Aszl3d0nukgomwAo2xu/242d8ZkgIaT0x1w5g1wuwdPyHX3HWVXAl2j5UGtrUH1F89XRDcuWanWlF7MzCs6OichhOjsiGjAgEx6ZJdCZbf7DnEXDsnpPMV+fROeiib/9uIvDo/XB2ZGWfEW/PrLEm3l0u+q1vz8YywUrAqrampjrDbyRU1V+VcAljJzdUfnnQ4i8gLY2eP1TcjMztsXwGhPhi9rwJCdXaN2nZQzYvRER58BQ7vEtTlUU4U3nvl35Xfz5/xaVrzlAmZe3tE5CSGsJUW/AAAQUUDx591vzyo6LPvAC3q5ioZ2dEpNYmakqosRW/9DrHbNN5VqqCLCanKTlojO02prvgCwhJmjHZ1nWzJaIIaQw7O/kpF5JGzKSLs/3+cetGumu/+YDGfBoE49NCBZXYyqT54qSZSu+04Nll3KzJs7OichhOhsiCirX4DuGZRtO/yhQ929dinqvC3JzIwL34vHf84+1BaNhMpKtm2KqGpqZbC6ck40EvoWwE/MHOvoPNsS6d3whtodzt1y84uOtCn2cXmFvf0TJx+cNXbivt5+g0d06jkDSrdvxjP331iyfvWKr8tLtv6ZmYs7OichhDWk6O/hiMhm82ZdpHj8/8ie8qdenkG7dspKUY1UI7ZxSap29cLyRNnGMLTUslSw/DVoqU+ZuaKj8+sMjB4BeyqBgiPJZttbycjO8Q7fK8szZLcMe06fTtnakChZi8p5T2xP1ZR+oIbKr+6qLT5CCGElInIU+ehveR669L5D3L0OHmLvlNX+xmoNH61NxWevTFWurdJCCZV/2hikd1jT3mfmso7OrzMgohxFse+TW9j7OMWm7JadXxSYMGlK5u77HurrM6BzNrCs+flHfuref2yvKi95taJs+03MXNvROQkhzJGivwcju2NPuy/3ad/4af0DE4/2d6aWYWZGYvtqRH76rDy2aXmYU/F1WjT0phaPfMjMGzs6v66AiPywKQfY/XlnwGaf4Oo9PCNjp/0K3APGUmdbOSC6YYlaNe+JbWptzW1aNPi0TCgkhOipMt10ZL6X7v/7ZFfv88Y7PIqt8zywZWYsLdHwyvJk9QdrUsFoipdvD/Er0RQ+YeaSjs6vKyCiAJFt7/xefc91OFwTRo3f07/P1OPyRo7ZDYq9c92HffvFB4mXHrtjezhYfWewuuJJZtY6Oi8hRHqk6O+BiKiXEsh/ytVnp91zDrooX/FmdnRKAADWVMS3/oLw8k/K4lt+CrKa+kQNlj4NYJEUgeYYwwFGKBnZJ5PDdaw9szDfN+7QAs+Q3e02R1oTLVuO1RRqvp0RDC+d+6saLD2TmX/u6JyEEKK9EFFR/0x6Ydow+4R7Dnbn+Jydo9hXNcbCLSpeWJos+3KjGo6rvGBDNT8F4GtmVjs6v67MuDbvklvQ+wyHw3l4n4FDM/c79ISCXSdNUbwZ/o5ODwCQTCbw/htPh+fM/O/60u2bT5fx/kJ0TVL09yBE5FB8Of9UfLnn5xxyaS9X0dAOv6NgTUVs0zIOL/u4NFG8Jsip1IdqqOxpACuk0G87RFRg82aeaXN6znbk9svzjTus0DNovI2UZiddbhepYCkqPny4OFmx+R01VP5XZo50dE5CCNFWiMhWmEGXF/no6meP9vTetZfS4ddmVWN8vE7Vnv0xUfZjsVYTT/GczUH+L/SJ9+Ta3EaIqLc/M/sEry9wdq++g3oddsJ5heP3PMBmt3f8tbmyrBiPTL+qZPP6VW9VlG77a3efO0mI7kaK/h6CbMquSiD/5ay9Th6QMeZgT0eP705WFyO0+P2q6K/fVnEyPlMNVzzNzKs7NKkeioj6KRnZ55HDfbKzaEiOf9y0Alf/0dTRywLW/vpdsurTp7eptTXXcDwyQ240hRDdDRHtNCCTXr10N+fgv05y+ju6K//6Kg2PfJ+oemdVqjKS4De2h/kZZl7boUn1UETUOzu34EKX23vqTrvskX3o8efkD91pXIfPz/PtFx8mnn/41q3VVWWXRCNhWeJPiC5Civ5ujog8ij/vQWfBoKNzD7uiQMnI6rBctGQctasWxEOL3y/TamuWp4Jl/wJrC6SY6zyIaJjiz/szOVzH+kYfmOPb5VB/Rw7/0JJx1Cx4qSqycsFyNVh2CjNv77BkhBDCIkTk7hugu4bn2E7+7zGewv6ZHfeQNZZizPw5lXz4u0RJaUT7aVMN36Ey5su1ufMgorH5RX2vcLrcUyYdeGTWYcefm5mdW9Bh+UQjYfz3oZsrlnz7+bflJVvPkUkbhej8pOjvxsju2Mvuz3sh+4Dz+3mHT+qwmdsSpetQ8+3M0sS2VWVavPZxLRp8gZmDHZWP2DEispPDdaSSkX2dI69//8AeJxS5+uzUYS0MibINKH/33i1quPIfam3NSx2ShBBCWMDnpClFPnrijinuvifubHd11O/VpcUqHvgmUfblplR5KI6nymr5WWau6ZBkRIsQkeJwOKfm5Bf9s++gEYNOOOfKouGjdu2wa/Ovvyzh/0y/amt1VfntNZVlT8qDIiE6Lyn6uyG9dT/3YWev4UflHnZFvuL2tXsOzBqi635Qa75+vVgNVy5Ug6W3MPNP7Z6IMI2IBiuB/L/bHJ5DfeMOyfWNOTjD5vK2ex6sJlH1xfNVtau++kYNlp3OzFXtnoQQQqSJiNz9AvTkvgPsh/1nmjsv093+hZrGjNkrU6npX8aLK6K8YGMN38XMS9o9EWEaEQ3OK+xzQ4Y/8+AjTvpT/j5Tj3U7Xe52z0NNpfD6s/+u+fyDNxaXl2w9iZnL2z0JIcQOSdHfzZBNGW8P5L+RfeD5/b3D92r31n1OJRBePi8aXPROOSejr6uhirvkAtA9EJGTXBknK27f9d4Rk4sCexyf1RFd/+Nbf9HKP3hwixquvESLRz5o9wSEEKKViGingVk06/5D3IOPGelo92tzPMV4fmkyev83ibJgnF/cFuJ7pFW/eyAirz8z5zxvhv+yiXtPzTvurMtyOqLr/9qVy/jBWy/dUl1RdnkoWDW73RMQQjRLiv5ugohI8eVcZ8/pc0X+0dcVtncxptbWIPjdW9W1qxaUafHI/Vo09Cwzx9s1CdEuiIigOKbafTn/cg/YpV/m5FPz7IH8ds1BS8RQ+fFj5bGNS+epofILZIZ/IURnRERU5KMrBmXZ/v7miZ6iPoH2HbsfjDMe+jYRem5JojQYx4NltfykXJu7JyIim822b15h33tG77rXoFMuvDYvr6B3u+YQj0VxyQl7pIKx1NtapPJMmeFfiM5Div5ugIhyFH/+TP/4w3YN7HlCoD1nXVejIdR8/VpV7ZpvNqnhyn9ATc6RMV09B9mUPeyB/HudhUOGZ+17ZoEjt1+7nj+6fnGycu6jm1I1pSewpi5p15MLIUQziCinX4DePH+8c+KN+zoD7Tkz//aQhjsXJCrfXZ3cXhHlW4NxzGRmrd0SEB1KUex75BX1uW/k6InDTrv4H/kFvdrn2jz3rRcSr816nR27HG6rmvfE+lRNyfHMvKJdTi6EaJYU/V2czeHaW/HnvZR3xN/6uXqPaLdqX4vXombhG9W1K+dvVSPVf+NUfK4U+z0XEe2sZBbc68wbsGv2QRcVOrKK2u3cam0Nyt66ozhZtW26Gq58pN1OLIQQTfA56YA+Adt/XzjG02+Pvkq7XZvLazXc+Gm8Yu7a1LqtIb4moeJLuTb3XEQ0vqBX/weG7rTLyNMvvr6gV79BbXau4i0bcONlJ6YyTn/QbrM7oYarUPb2ncWpqm33q5Gqe+TfoRAdS4r+LoqIbIovd7qzYND5eUdenW9rp8n6tEQMwe/fCkaWz9umRoP/4ET0bflFLuoQ0U72zMInXP3H7JS93zl57bVEJGsqqr98oTry8xefq6Hy06RLoRCiIxCRvW+A7tutt3LKc8d48gOu9mndDycY/5ofr3llRXLz1iBfllD583Y5segSiGh0Qa9+D44YM3HMuVf8X35WjrVD8tRUClefe0gqutsZdk//Mf/bzqyhZuEbwfCSOV+rofLjmbnW0hMLIVpMiv4uiIjyFX/+u4E9jh/t3/XwjPZYqoU1FaEf3g2HFr+3XY2G/snxyJvSVVA0heyOyXZf7qPenfbtnznppCyb09Mu542uXZSsmPvoWjVYegQzr22XkwohBAAiyusfoDm3HODa+dxx7fNLL6Ux/vNdIvLQd4lt5bV8XTCOt+RBvGiKoth3zyvs/eS+hxw/8PizL890ua1Ziee/D90Sn79qI2UefGmjk1RGN/yYrPjw4bVqsHQaM6+35KRCiFaRor+LIcU+1p5Z+Hb+0dcNcBYObpcmhOiGJWrVvCe3qdHg3Vpt9WPMrLbHeVuKiDYACAFQAaSYeWK9964GcA+A/MZWESCiqwBcAIABLAdwLjPHiOguAIcBWMLMZxn7ngkgh5kfbOOP1C0QEZHTe6ziDdzpn3Bkb//4wzNIsbf5eVM1pSiddft2NVR+pVpb80abn1AI0eMR0Zgh2fTOmyd5B4wvUtr82szMeHd1Kvn3efHtlVG+tzTCj3a2a3NXQUTPAjgCQCkzjza23QbgaAAagFIA5zDztgbHjQDwer1NgwHcxMwPdOZ7CCIinz/rZF9m1vTjz76i9wHTTnbbbOmPQFm57Dv1nluvUH2nP+hsLk6qpgSlM2/bmgqWXqDFInPSPqEQIi1S9HchijfzJHtW0YMFx99U1B7dplM1JaiY80hJsnLLR2qw7Apmrm7zk6bBKPonNizqiagfgKcBjAQwoZH3+wBYAGBnZo4S0RsAPgDwFoD3mHkfInoZwJ0AfgXwHoBDmTnZ1p+pOyEiu82bebHiybw255A/93b3G6209Tk5lUTF3P9UxDYsmaWGyi+Rm2EhRFvJz7CdOCiLHnrvNG9RQUbbD99fUariwndj2zYHtRlbgnwDM4fb/KTdGBHtCyAM4IV6RX+AmYPG68uh3ydc3EwMBcBWAHsAqEYXuIcgImd2XuE1gcyci8+78rbeYybu3ep/vNFIGH89++CUcsQN9pbM5aMlYyh/556yRPGvj6rhilulV4oQ7ad9144RaSEisvvz7nYPHPdo0el3tXnBryVjqPrs2eriV/7xXWzDjwekakrP7qwF/w7cD+Ba6K34TbED8BCRHYAXwDboT/adpI+b8ABIArgGwEOd5WLdlTBzSo1UP5Ks2DSu/L1/zyp7644ytbZtl4cmuwN5067MzZx82umKP+9zIvK36QmFED0OEVHfgO1fUwYpj84/N6PNC/5oknHVR7Gqw1+p/XLhFnXPzTXaFVLwm8fMXwKobLAtWO/bDDR/HwEAUwCsZeaN6CL3EMycqCwrnr5x7S9jH77t8pf/dc3ZpdWVZa2K8eD/XZZIjphia+nkvTaHG/nH3Zjv3/XwqxR/3vtEZM34AiHEDrV9X1thChF5FH/eLP+EIycHdj/O39bj92tXfZ2o+vy/W7Vo8FotHpnZRZ7CMoC5RMQAnmDmJ4noKABbmXlpUz8zZt5KRPcC2AQgCmAuM88FACKaCeBHAJ8AqAGwGzP/Xzt8lm6LmSsBnEQ2Zfd4ydrnArsd29+/67SMtlxi0r/LVK8jp8+k8vfv+46IDjVuyIQQwhQi8vQN0My/7O6cfO1ezkBbX5vnrUupl34Q21oe0a6tiPLrOz5CmEVE0wGcBf0e4IAd7H4KgFcBgJlDXekegpmrAJyl2O0Trrtg2ovHnnnZgKnHnOnd0b/p+XPfSq7etJkzT760VRdxIkLmpJMCzqKhB1XMeWQREU1j5g0mPoIQogWke38nRkR9lEDBnNxDLh3hGTzB0ZbnUsNVKP/ggdJk+cZZaqj8KmaOteX5rEREvZl5GxEVAPgYwGXQx/FPZeaaZrr/ZwOYCeBk6N3x3gQwg5lfarDf0wD+A2ACgKkAljHz7W37qbo3IlIUX87VNm/W5bmHXd7LVTS0Te+Yk9XFKJtx65ZkdfEJnEp825bnEkJ0b0TUp38mzXn8cM+Iw4bZ2/TaXF6r4aL3YmXfb1U/3hzkSxq0QAuLENFA6F3yRzfy3j8AuJn55iaOdULvJTiKmUsaeb/L3EMQkT0nr+iG3MLeF17+z4d69xkwtNH9yku34boLj05lnPZvu82ZfmN9vWvzsZxKLEo7kBBih6R7fydFin2sPafP14Un/d/otiz4mRnhZXNrt7/4t59jG348JBUsu6QrFfwAUDe5DjOXQh+Pvx+AQQCWGgV/XwCLiahh/7ODAKxn5jKjy90sAHvV34GIxhsvVwM4i5lPAjCaiIa11efpCZhZTYUq7kqWrptQ9tb0eVWfPlPFatv1enRkFaHojHv6uoqGzla8mSe02YmEEN2a2067jci1LZx7hnd0Wxb8zIxnf0xEd38qsur91amjNtVop0vB32FeAXB8M+8fBmBxEwV/l7qHYOZURdn2W9f8tHivW684+auXHptenUzEf7ePpmm45/oLksre55oq+AH92lx4xj19nfkD31U8/mmmggkhmiVFfydkc3r2deT1n1N0+t39Hbl92+w8qVAFSl+7oaR6/ksPqcHSXVhTl7TZydoIEWXUjdcmogzoT9G/Z+YCZh7IzAMBbAGwKzMXNzh8E4A9ichrjL2bAuCXBvvcBuAmAA4AdRPQadDH/wuTmLk4VVM6Nbzi0yu3P3/V1kTZhjY7l83tQ+GpdxS5+41+zO7P+3ubnUgI0S3leGjaLkXKOwvPz+g3Iq/t5iPdVKNhn//WFt/0Wfy+9dU8Jpbib9rsZKJRDYryowCsbGb3U2F07W9El7yHYOaN5SVb95k7+8W//O2cgzevW7X8f92CZzz3QLyMApp36O6WnEtx+1B42p1FzqKhzym+nHMtCSqE+APp3t/JKB7/MY7c/o8XnHhLoc3VNtcEZkbkp0+j1fNfXq8GS09m5hVtcqJ2QESDobfuA/ocFa8w8/QG+2yA0b2fiHoDeJqZpxnv3Qq9e38K+vi7C5g5brx3DIBdmPlW4/t7ARwCvWve6W392XoaIuqtBPLf9O9y6OjAnicEyNY2N9XMjOrPnq2KrJz/phoqv7iLzFshhOhART7bWaMLbPe+e6o33+Nou9FIr69Ixq6bF1u7oYaPZeY1bXYi8T9E9CqA/QHkASgBcDOAaQBGQC/QNwK42JgHqOE9hBfAZgCDmbmmQdxj0A3uIYgoP6+wz5sHHn7KuIn7TA386x8XpnxnPuwws8xfY1hTUf7efRXxzSseSIXKO+XwByG6Min6OxHFl/MnZ8Gg6QXH/TOf2qjXoBavRfn795clile/ooYqrulMM8kKQURky8i+wh7IvzbvqGt7tXRG4HTUfDMjGPrh3ffVcMUZzKy12YmEEF1an4Dtmr36KX9/9XhPrt3WNgV/JMH407vR8gWb1Nmbg3wpMyfa5ERCpIGIKDMn/8+apv3bfdBlLu+QiW1yHuOhfHVk5fzXjeV2pUgRwiJS9HcSdn/eDa5+o6/KO+KvuW3VwpkoWcdl79y9WQ2Vn6clop+0yUmEsAARDVECBTOyJp863Df24DbrBhla/F645psZ89RQ+QnMrLbVeYQQXVOfXP/jGfbU2SsvdrhtbTRD/4/FKp82M7ple0i7qDrGH7bJSYSwgHFtnp2931lDM3be391W5wl+PzsU/H72p2qo/ERpnBLCGlL0dzAiIsWf+6B3xOQzsg/8U3ZbLPvDzAgtejsc/P7tZWqo7Bhmbt1CrEJ0ACJSFH/ug+5+Y07JPezyXLI72+Q84eXzaqvnvzRfDZUfKTcXQghAvzb3zfP/54yDRp1aE455SjeswozjHS4rz8HMuOfrROiR7xLLNgf5OGMyWiE6NSJyKP68h119Rh6fe9gVeTanp03OE/nly1jVZ89+r4bKp3a1CaaF6Iyk6O9AesGf96x//LTjMiedFGiLc6ixMMrfubs0WbbxCTVccYt0YxZdjeLxH6P48/+Tf9wNvduqu39k5fxY1afPfKuGyg+VmwshejYior75/ucuOWL8MdeftleAmXH6v95JZAQ34KkjHJY8fSyNaDh5RrRkdYX2yLYQT5duzKKrsbm8B9sD+c/mH3djX0d27zY5R3TtokTFR498p4bKD6qbb0kIkR4p+juIUfA/4R9/+MmZk05sk4I/XrxGK3/n7k2pYNmpnErK7L+iyyKigUqg4L2cgy4a6h22h6WtbXVqf/0uUTn30cVqqHwKM9e2xTmEEJ0bEdn65vtf+9sJux925XG7+eq2q6qGo26akdjZsQ33HOQ0Vfgv2qZqp8yo3bCxho9PqrzEdNJCdBAi6qcE8j/MnXrpcM+QiW0yGVXtmm/jlR8/9o3R4i9zXQiRJlmyr4Mo/rwHfWOnntRWBX/k58+jZbOmL0pVbZ8gBb/o6ph5gxosnVj58WNvV37yZBVr1g+/9w7d3Zk77coJij/vS2NGZiFED2J06X/x+lMnTatf8AOAotgw+9bjnd+H8uiOBclUuud4ZXkyetzrtYvWVvFuVhX8RHQVEf1ERCuI6FUicjd4fyQRLSSiOBFdXW97PhEtMI47pt72t41Z6oVoFjNvVoNlu1V89MhH1QteqWmLhkTvsD1cOVMu3FPx531IRG0zy7UQPYAU/R3AHsi7N2PUAWdm7X1aptWxmTVUfvp0ddXnz81UQ+WTmbnS6nMI0RGYOZYKlp0c+eXL60pe+UeJGgtbfg7PwHGO3GlXjlX8eR8TUdtMIiCE6JT65PkfufToXY+45MhdMxp732FX8OEdJzve3pLJjy9KtOrJo8aMq+fGqq+bF5u1Och7W3VtJqI+AC6HviztaOhrwZ/SYLdKY597G2w/FcDzACYBuMaIdySAxcy8zYr8RPfHzFE1VH5UeOmce8tm3FqmJaKWn8M7Yi9X9gHn7aX4894jIrvlJxCiB5Civ53Z/XnTvSP3OT9r37OyrI6tJaIofePmstqfv/y/VLDsTGZOuzVCiM5KDVc9GS9ec2Txi1dvTlZutTy+Z+A4R85BF04wbi7aZikNIUSn0jfPf/tpB+582nWnTGq2953H5cC8u091PP6zn19fkWhRs2Y4wZj2cm3ZqyuSt22q0c5ogwlD7QA8RjHkBfC7gp2ZS5n5ewANz5sE4AHgAqAZx18J4B6L8xPdHDNzKlRxe2zLT6cVv/i3Lcmq7ZafI2Onfd3Z+5+zj+LPe1uuzUK0nozpb0d2f95N3uF7Xpl90MWWz9KfqilB6Yz/25oKlp2lxSOfWhpciE6IiPoqgYK5edOuHOYeMNbyJ//h5Z/UVs9/cY6xnJ/8ohSim+qT5//rtN2H3PDkVYfmtPTaXBGMYp8rX0zdv2/UfsjQpnscb6jWcNSrtVs31mhn1cS4Ta7NRHQFgOkAogDmMvPpTex3C4AwM99rfJ8J4BUAhQD+DmAUgBpmfr4t8hQ9AxENUAL5H+ZNu6qNrs3zaqvnvzRPDZUfJ0vtCtFy0tLfTuz+3L96Bk+4oi0K/vjWlWrxq/9YnSzfuI8U/KKnYOYtarB09/L37/s6vHye5RPv+cZM8QZ2P3aq4s99htpiLU0hRIcryvGdN3lU3388cWXLC34AyA14MO/uU+2XfeZMLdzceKe6+RtT6gHPR1YvL9X2acOCPxvA0QAGAegNIIOIzmjJscxcw8yHM/NEAIsBHAFgJhE9RUQziGhSW+Qsujdm3qgGy3Yrf/++7yIr51u+Go5vzEHezMmnTVH8ea/KtVmIlpOivx0o3sBxzqJh/8g59C+tuqloiejaRYmyt+/8Ua0p3Z2Z11saXIhOjpnDaqh8SvX8F9+pnv+S5ZMIBSYe7fONnXqc4s+T7q5CdDN5md7jxg8puPOV64/Ks9laf23unefHnDtPtZ/xgZJaUfr7wv/Nn5Kx02dFv9lQzRPb+Np8EID1zFxmDBuYBWCvNOLcBL23wKkAfgBwHoA7LMtS9CjMHFFD5ftXffrMvOAP74Ssju/fZWqGf/y0QxRf7l1Wxxaiu5Kiv42R3bmbPbvPf/KPvi6PyNofd3jFp9GKjx75Wg2V78PMNZYGF6KLYOaUGqo4Lbzs44cr3r+vglmzNH7m5NMyvcP2PM/uz7vB0sBCiA6TmeGasnP/3Edn33p8vl1J/9o8uFcW3rntJPtRM22pjdX6755Hv0+E/zY39snmIB/AzJYXPA1sArAnEXmNVs8pAH5pTQAiGgagNzN/AX1OAA0AA3A3e6AQzWDmpBoqPzr47czXqz7/b7XlD+X3PDHgHjT+PMWXc4GlgYXopmRMfxsiokGO3P5fFJ5xdz/F7dvxAa0Q/H52KPj9W/PUUMVJMmGfEDq7L+dSZ5+Rt+QffV0e2ayb54eZUf7O3RWxjUv/rNbWvGFZYCFEu3PYlV12GVzw4Rf/Pq1XhseaRTq+W7lNO+W2mdpxQxK1r/+Umr0lyOey1U8gm0BEtwI4GUAKwI8ALgBwLgAw8+NEVARgEYAA9II+DGBnZg4ax78B4AZmXkNEBQBmA8gEcBMzz2yPzyC6N7s/72Z3/zGX5R5+Va6l12ZNRekbN5fGt686TYvXfmJZYCG6ISn62wgR5dgzi74tPPWOofbMAsviMjOqv3i+JvLz52+oofKLZIIxIX5Pycg6x1k49O6C42/MJ8W6JX1ZTaL45euKE8VrprGm/mhZYCFEuyGigmF9sr/9+sEzB+Zlei2Ly8w4+uaZkYVL180qr9XOlmuzEL+n+HIucBYMuqPguBvzyW7dirhaIobil6/dlixddxAzt6qXixA9iXTvbwNE5FYC+fPyjrluiLUFv4aKDx+qjPz8+cOpYNmFclMhxB+pkernEsVrLi1546ZSLRm3LC4pDhSccFORPatoNhH1siywEKJdEJGrf0Fgzoybjh1gZcGvaYzz//1B5eI1xXeVRdSz5NosxB+p4cqnE9tWnVf86vUlWsK6+f1sTjcKT7y1tz2r1wdGrxYhRCOk6LcYEdkUf97bOVP/PMpVNNSyWfuYGRXvP1ARW/fD7alg2T+tiitEd6TW1ryZLF1/XunrN5ZoiahlcRVvJgqO+2d/JZA/l4isqxqEEG2KiKhvnv/V+y+ZsvPYwQWWXZtVVcOpd7xd8dGi9dO3lIVusyquEN2RGgu/l6zYfGbpGzeVWPlQXvFlI//4fw5UAvnziCjDssBCdCNS9FtM8efeE9jj+MneIbtZ1neJmVE55+HK2MYld6fCFfdbFVeI7kyNht5PlK4/teTVfxRr8YhlcR15/ZB76GUjFH/e22T17JxCiDbRJ89343mHjj3wuL1HuKyKqWmME2+bXf7Fss3Xby0P3WdVXCG6My0W/jhZsenc0jdvLuVUwrK4zrz+yJ125QjFn/c+EVk3cYAQ3YTcsFpI8QSOcvXZ+Sz/rkdY9pSRmVH58WNV0XU/PJAKVdxtVVwhegItEf0sWb75+JLXbizWktZ1J/QM2tUR2P24PRV/7gOWBRVCtIlsv/uIicN7XX7LWXtnWhWTmXHuve9XfPPL1luKK8NPWhVXiJ5AjYY+TJZtvKDkzZtLOZW0LK5nwC72zEknT1T8ef+2LKgQ3YQU/RYhosFKIO+xvMOvytNXzTGPmVH16dNV0V+/fTQVKpdug0KkQUvGvk5WbTur9M1bLL25CEw8yucZNOF0JSPrHMuCCiEsRUQjBhZmPvnq9UdZdm0GgKse+6Tqkx83PrCtIvwfy4IK0YOo0eC7ybINl5TOvLWMVeuuzf7xh2W4+ow8XXH7jrQsqBDdgBT9FiAir5JZ8H7Bcf/sbeWMpNVfPF9du2rBM6lg+Y2WBRWiB9Ji4Y+T5ZsuLX3r9jLWVMvi5hxyaY49s/AOIhppWVAhhCWIKHtwr6z337v9xF4el3Uredz64oKaGfNXPbelLHi7ZUGF6IHU2uCsROn6v5TOur2MVetWn86ddlWeEsh7jIgGWBZUiC5Oin6TiIgUf97ruYf8xdKZ+qu/fq0m8vNnL6WC5ddYFlSIHkytrZmRKF57ffm791ZYtXw22RTkH3t9LyWzcLZM7Jc+IppIRA914PnnEFGfBtvOIaLeacbbn4jea+G+k4joqXTO08L47fKzJaL/I6KD2vo8LUVEtn75gfdeuf6oQX3y/JbFfXj2ovDTHyydvbU89DfLggrRg6mR6jcSxWuvKpv9rzKrrs02hwv5x97YRwnkv0dEls3jIURXJkW/SYov5+++sQfv4xm0q2XNCOEVn0bDSz6co4YqLrcqphACUCNVT8e3/HR35UePVlq1qpbdn4fcqZcMVvx5L1oSsAdi5kXM3CG/74jIAyCHmbc2eOscAGkV/a10KIA5bRW8PX62RKQw803MPK8tz9MavXN9N1153MSxe4zsbdl9zgsfr6i9+/Vv520pD50ny/IJYR01UvVyonjN7VXznqiyKqYjuxdypvxpuOLPe96qmEJ0ZVL0m2BzuPZ25A+4KnPyaZZNDhTbtCxV/eULi9RQxRlyUyGE9VKhiruj675/ovrLF6utiukZPNHhHbn3gYov+0KrYnZ1RJRBRO8T0VIiWkFEJxvbdyOir43t3xGRv37LuHHcs0T0PRH9SERHG9vPIaJZRqv8GiK6u965DiWixUbMT5qL04j9AXzeIPcTAEwE8DIRLSEiDxFNIKIviOgHIvqIiHoZ+w4lonnGuRcT0RAjjI+IZhDRSiJ6mZoeUD4FwB+KZSK6xsh9GRHdamwbSES/ENFTRPQTEc01HlrU/VyXEdFCIrqHiFYY2+v/bG8xfiafE9E6Irq83vnOMP4+lhDRE3WzXxPRVCPmYiJ6k4h8xvYNRHQTES0AcCIRPWf83Oreu9U4Znnd8Bciyieij43tTxDRRiLKa+Lnkja7YpuwU//ci686fjefVTHf/np14oZnv/h6S3noRLaqOVII8T+pUMVDtWu+fSW46J2wVTG9w/dyeoftOVXJyLrAqphCdFVS9KeJiLIUf95L+UdfV9D0vVzrJMo3ofz9B1aqofLDmNm6wU1CiN9JBcuvj/z06fvhFZ9GrYqZvf+5WfbMwluJaGerYnZxhwLYxsy7MPNoAHOIyAngdQBXMPMuAA4C0PDv4AYAnzLzbgAOAHAP/bbu8jgAJwMYA+BkIupHRPkAngJwvBHzxBbEqe8wNGhpZ+YZABYBOJ2ZxwFIAXgYwAnMPAHAswCmG7u/DOA/xrn3ArDd2D4ewJUAdgYwGMDkhic2Ct4kM9c02D4VwDAAuxufeQIR7Wu8Pcw43ygA1QCON7b/F8DFzDwJQHMTV4wEcIgR+2YichDRTtB/rpONz6sCON3I70YABzHzrsbP5K/1YsWYeW9mfq2R85QbxzwG4Gpj283Q/052BfAWgP7N5JkWIvINKMx8/bUbji606tr87cpt2mWPfLxkS3noCLk2C9F21FD5ZcHvZn1Zu+bbuFUxs6f8KdueVXQbEY22KqYQXZEU/WlSAvmv5E67sq/NZc3qfKlwJcpm3bZeDZYezMzWLSouhGiUGio/p/rLF5bEt/5iycx++vj+G4rsmYVvNVFc9jTLARxERHcR0T5GYTsCwHZm/h4AmDnYSBE1FcB1RLQEegu8G78Vh58wcw0zxwD8DGAAgD0BfMnM642YlS2IU99kAAt28FlGABgN4GMj3o0A+hKRH0AfZn7LOHeMmWuNY75j5i1Gq/ASAAMbiTsVwNwmtk8F8COAxdAL9WHGe+uZeYnx+gcAA4koC4Cfmb82tr/SzGd5n5njzFwOoBRAIfTeBhMAfG98vinQH1TsCf2hxVfG9rOh/8zrvN7MeWbVz9F4vTeA1wCAmecAsKwrb51++f6Xn7zy0AF5mdZMsbG1PITTpr+zfnNZ6FBmtqwQEUL8ETOzGio/rnLe4yvixWss6VFDNgUFx95YZNfn3pFrs+ixpOhPg5KRdY53xORJ7r47K1bE0xJRlL5x87ZU1fZpzFxsRUwhRPOYOaWGyg8rf/fedamaUkti2n05yDn0L4OUQP5LlgTswph5NfRCcjmAfxHRTQAIwI6GLRH0Vvtxxp/+zPyL8V79oksFYG8mZnNx9B2IBgPYzMyJFuT0U71YY5h5qrG9KY3l2tAfehnUO9+/6p1vKDM/00zc1jRpN3X88/XON4KZbzG2f1xv+87MfH6945t7QF13nvqf3bo18xqRn+U957i9R+wzZdeBjf2sWy0aT+KIG9/cvq64+nBmtvwBhRDij5g5rgbLDi6ffedaq67Nii8bOQdf0l/x5z1hSUAhuiAp+luJiPopvpzp2fudk2VFPGYNZbNuL01Vbz+dmVdaEVMI0TLMXJOqKTm0dMYtW7V47Y4PaAHPwPEOz+CJ+yoe/7GWBOyiSJ/5vpaZXwJwL4BdAawE0JuIdjP28RNRwwLtIwCX1Y2BJ6LxOzjVQgD7EdEgY/+cVsRpqugGgBCAumnfVwHIJ6JJRiwHEY1i5iCALUR0jLHdRS1cxcHIayz0XgANfQTgvHrj5/sQUZPLwxgFaYiI9jQ2ndKSHOr5BMAJdecgohzSl7r6BsBkIhpqbPcS0fBWxq5vAYCTjFhTAWSbiPU7RDSoX35g+j0XHmBJTGbGKdPfKdtYEvwTM6+yIqYQomWYuSpVU3JI6Zu3bNZi1gzx9wyZ6HD3G3WIzeU92JKAQnQxUvS3AhHZlED+rPyj/t6bFEsaElD9xQvVyfJNd2iJ6OeWBBRCtAozr0vVlJ5eNuv2UtYs6emP7AMvyLF5sx6sV4D2RGMAfGd0C78BwO1Gi/rJAB4moqUAPobe7b6+2wA4ACwzJqO7rbmTMHMZgAsBzDJi1nU5b0mc5mbOfw7A40b+CoATANxlnGMJ9PH7AHAmgMuJaBmArwEUNZdvPRMA/NjYhK3MPBd6F/2FRLQcwAz89gCiKecDeJKIFkJvUa/Zwf71z/cz9CELc43P8TGAXsbP9hwArxrbv4E+1CBdtwKYSkSLoT9w2Q794YopROQYUBCYPeOmY3s77JZ0wMMtLyyoWbR6+0OVoej7lgQUQrQKM69PVm8/sXTW7SVWzZ2ZM/XSPCUj+ykiClgSUIguhGSC+Jaz+/NuCex5wtWBCUdaMiao9tdvE5VzH3svFSw7fsd7CyHakpKRfZF3+KQ7cg+51JJCPb51pVb2zl0fpWpKp1kRT1iL9LWbv2LmiR10/hsB/NrEJHjpxPMxc9h4fR30ov0KK2JbxfiZq8ycMnpNPGZMHGhKv4LAw3ecu9/5Zx482mM6SQCzFqyKX/HovPe3lIVOkFV0hOhYii/nSt+Yg27O3u/sLCvixTYtV8vfu+/dVLC0R/fGEz2PtPS3ECn2sfacPhf7dz3CkoI/WbUdlR8/sUYNlZ9uRTwhhDlqpOqJ6Nrv34usXBCzIp6rz0ibd9ieeyoe/8lWxBPWMiaz65CC3zj/7VYV/IbDjeX2VgDYB8DtFsa2Sn/okwUuBfAQgD+ZDehQbLvuMrjgJKsK/mXrSvmqxz75eUtZ6FQp+IXoeFqk6sHIT599GV33Q9KKeO7+YxTP4F33VTz+Y6yIJ0RXIS39LUBEDiWzYFmvM/49UvGZHy6oJWMofuFvW5PlGycz80YLUhRCWICInEqgYFHhKdPHOLJ7mY7HqSS2P3f55mTF5l2N2dKFEBYhIsegosxl3zx01siCbPPP46vDMexx2QsbV2+p3J2ZrZlBTAhhGhF5lUDB4qLT7xxhDzQ5vUmLack4tj93xeZU5ZbxzFxhQYpCdHrS0t8Cii/35sxJJw+wouBnZpS/e29ZKlR2gRT8QnQuzJxQg6VHlb11xzZO7WhC9x0juwO5h/+1rxLIf9WC9IQQ9fTJ9d164+mTB1hR8DMzzrzrvbLNZcEzpeAXonNh5lo1WHpk2azp21k13+Bvc7iQd/iVfZRA/ssWpCdElyBF/w4Q0RB7ZsH5vrFTLek6GFr0djixfc3TWizS1ORRQogOxMwb1FD5FRUf/ceSp/+uXsMoY8TeExRv5hlWxBNCAEQ0Ykjv7HPPPWSMJdfmpz9cWrtkbckLtbHkfCviCSGsxcxrUsHSv1p2be490uYdvtfuijfQ2tVOhOiSpOhvBhGREsh/Nffwq4qMVZ9MSZRtRHDR2yvUcMWNFqQnhGgjajQ4I7Zx6duRnz+3ZHx/1n5nZds8gekyY7AQ5hERDSgIvPL8tYdbcm1evaUSt7/89cotZaG/W5CeEKKNqLXB12IbfpwdXvFp1Ip42fudnW1z++8kIkvm69oRIsoioj/X+35/InqvPc4thBT9zbB5Auf4xhw03JHd23QsTiVR/u7dW9Vg2fFs1dojQog2o4bKL6764vnVycqtpmOR4kDOlD/1Vvx5D5jPTIierSDLe8EF03YZOrAoy3SseCKFE2+bvW1TafAYZrZmzU4hRJtRQxUXV89/cU2qpsR0LLI7kX3A+b0Vf949FqTWElkA/ryjnVqKiKxZP1z0CFL0N4GIsmzewK2Zk07KtCJe1WfPVKrhyquZeZsV8YQQbYuZk2qw7Mjyd+7expr5WsAzeILdkdtvGhHtbEF6QvRIRJSTl+n9599P3tOSXjNXPDavcntF+Gpm3mxFPCFE22LmlBosO6HsnbuLrWhD8w7bw2HP7nUsEQ2zIL3fIaK/EtEK48+VAO4EMMRYaaXuQYOPiGYQ0UoiepmM7ktENIGIviCiH4joIyLqZWz/nIjuIKIvAHSqZVlF5yZFfxMUf96juQdf0psUh+lYsU3L1do13yxQa4NWLs8khGhjzLwpFa6YXrPwjaAV8XIPu6xQCRS8UHdRF0K0Tv+CwJOPX3FIb4ddMR3rg+/WJj/4du0npdURmWhTiC6EmdeowbIHQ9+/HbIiXu6hlxcpgXxLr81ENAHAuQD2ALAn9CVK7wKwlpnHMfM1xq7jAVwJYGcAgwFMJiIHgIcBnMDMEwA8C2B6vfBZzLwfM//bqnxF9ydFfyOIaLyzaOgU94BdTN9VaLEwKj58aJMaKj/TityEEO1Li1Q/Fl42d0WizPxiG/ZAAXyjDxhq8/jl94EQrWRXbLvvuVPvffcZ08/0tbmkKoK/PDx3w+ay0DkWpCaEaGdquPLu4A/vrLJiCJ4juxcyRuw9wubKON6C1OrsDeAtZo4wcxjALAD7NLLfd8y8xRj6uwTAQAAjAIwG8DERLQFwI4C+9Y553cI8RQ8hRX8DRERKZsFTOQdfbH4hUADlHzxQpoYrzmZmS1oKhRDti5lZDZadVP7evVtZTZmOlznplEybO3AbEfksSE+IHoGIqF9+4MmHLj0434p4597zfunmsuDJzFxrRTwhRPtiZk0Nlp1g1RC8zH1Oz7Z5A3cTkSUrggBoaa+BeL3XKgC7cexPRo+Accw8hpmn1tsvYlGOogeRor8BcnqOzBg+ebDdn2c6Vu2qrxOJ4l9nacm4LAEkRBfGzFvVcOWtNV+9Wm02FtkdyJ5yQS/Fn3efBakJ0SMEvK5jT95/pwGF2eYn2Z41f1Vi+YayWcmU9qMFqQkhOggzb0yFKu6wYgiezeFG1r5n91H8ef+yIjcAXwI4hoi8xuoAxwL4CoC/BceuApBPRJMAgIgcRDTKorxEDyVFfz1EZFe8mfdmTj4122wsLR5B1efPblFD5VdZkZsQomNptTVPh3/6dGmidJ3pWN4huzkcOX2OJKIhFqQmRLdGRPa8TM+dN56+V5bZWNXhGK556rPNW8pCcm0WohvQaqsfDS+buyxRtsF0LO+IyU57ZsFJRDTYbCxmXgzgOQDfAfgWwNPM/AOAr4yJ/ZpcMYCZEwBOAHAXES2F3u1/L7M5iZ6NmLmjc+g0lIysyzInnfyvwMSjTDcllL93X3nt6q9O0RKxT6zITQjR8YioyJE/cFGvcx7sQzZzw4oT5ZtQ+uYtH6VqSg61KD0huqXC7IzLbzx98h2XHTPB9LX5tDveLp/91ZoTauPJL6zITQjR8Yiol6Ng0Pe9zn7Aqmvz3FRNySEWpSdEpyAt/QYi8tnc/qv946eZvqmIbflZi21a/pUU/EJ0L8xcrEaq7w398G7YbCxnXn84C4eMJ6IxVuQmRHdERBk5fvffLj5inOlr8/zlm9Wvftr6hRT8QnQvzLxdi1Q/FF4yx/QcHc68/nD1GjaOiMZZkJoQnYYU/QbFn3db9n5n9yLFbioOayoqP3pkmxoqO9+i1IQQnYhWW/1w8Id3NqmRatOxcqZcUGDPLHzUfFZCdE998nw3Tz9vvyKzS/QlUyoufvCjbZtKgxdalJoQohNRI1X3Bb97a5MaNb+KX/aB5xcomQWPWZCWEJ2GFP3Qu+wqvpyTPMP2dJiNFfzurZBaG7yTmSusyE0I0bkws6oGy8+tnPd4qdlY9sxCuPqPGUk2ZZIVuQnRnRBRQVG277RjJw93mo1152vfBEurI7cxc6UVuQkhOhdmTqmRygurPnmq3Gwse6AAnoHjh5Hi2M+K3IToDKToB6AE8u/POeiiXkQtXV2jcalQOUI/frBeq62Wp4NCdGOsqd/Ft61aEN+6UjMbK3vfs/OUQP5/yOwvICG6mf4FgQcfvPQg09fmTaU1eObDpb+W10Sftig1IUQnpCXj82Obl38bL/7V9IRlWfuelav4cx+Ua7PoLnp80U9ERXZ//r6u3iNM/6eu+uSpUjVYeg4zmy4EhBCdmxosu6jio0dMrw+s+LLhHbbHQLK7pu54byF6BiIaMrxvzv6TR/U1fZ9y2SPzSjaWBs9hmblYiG5PDZZdUDnn4e1mb8UVbya8Q3fvD8VxkEWpCdGhenzRrwTy78ja7+xeZuMkStchvn3NImaWdX+F6AGYuVyNVD8Q+vGDiNlYmZNPy1Yysu6TFgUhdAMKA3fd86cDiszG+fHXYixZW/IdMy+3Ii8hROemT7hb9Xh42cdRs7EyJ5+abffl/FuuzaI76NFFPxHlKhnZU939Rpn+z1z58ePb1WDpJVbkJYToGrTa6gdC38/eosXN1f2K24eMUfv3IYfrKItSE6LLIqKivnn+SeOGFpqO9ZdHPt6+qTT45xae9yoi+slYQ/tVInI3eH8kES0kojgRXV1vez4RLTCOO6be9reJqLfpDyGEaBU1XHlncOEb5q/NngA8wyf1I7tLlu8TXV6PLvoVf97NWfucYbqVP7pusZqqKX2XmTdZkZcQomtgZlWtrbm65qvXqszGCux2bKbizb7NiryE6Mr65ftv/r9z9jXdyv/R9+tSm0uD7zDzlh3tS0R9AFwOYCIzjwagADilwW6Vxj73Nth+KoDnAUwCcI0R70gAi5l5m7lPIYRoLWZOqrU1V1Z/9arpa3PmpJOzlIzsu63IS4iO1GOLfiLKtHn8x7oHjjf1M2BNRdVnz2xXQ+XXWpWbEKLr4GTs/drVX29UI+buLWxuH9yDJ/Qhm7KPRakJ0eUQUSDH7znigF36m7o2axrj6ic/Ld5cFvp7Kw6zA/AQkR2AF8DvCnZmLmXm7wEkGxyXBOAB4AKgGcdfCeCedPMXQpjDydiH0dULN5i9NiseP9yDxvcmIlllR3RpPbboV/y512ftfXqR2WE64eXzomo0+B9mrrEoNSFEF8LMnApVXF795Yuml+nMnHRSjj2QLy0KosfqleO7+sbT9yo0e21+4ePlsYpg7PGWXpuZeSv0FvxNALYDqGHmuS083SsADgEwB8AtAP4M4AVmrm114kIISzAzp4Jll1Z9/pzpJfwy9zwx155ZON2KvIToKD2y6CeiDJsr41TP0D3sZuJwKoHgNzO2a5Gq+6zKTQjR9bCanB/dsGR1qqbUVBy7PxfOXsMHE9Eoi1ITossgIlcgw3n2sZOHO8zEiSVSmP7qwu3bK8MtbmknomwARwMYBKA3gAwiOqMlxzJzDTMfzswTASwGcASAmUT0FBHNkBZCIToGa+rC2OblvySri03FsWcWwJ7TZyciGmhNZkK0vx5Z9Nu8WZcE9jzRdEtCaMmHES0WuoOZExalJoTootRg6Z+rPnvGXNUPIGvyaQVKZsG/rMhJiK4kL+C54MrjdstXFHO3Jve++W2wKhS7tZXX5oMArGfmMmZOApgFYK80Tn8TgOnQx/n/AOA8AHekEUcIYQG1pvQv1V88Z/7avPfpRUog/xYLUhKiQ/S4op+IyOZ0X5Qxcm+nmTisJhFa/H6pFgs/b1VuQoiui5mXxIvXLE2WbzYVx5HXD/ZAwQQiMj2RmRBdBRHZMjNcV507dYzHTJzaWBLPzllWUhGMvtjKQzcB2JOIvMbyXFMA/NKaAEQ0DEBvZv4C+pwAGgAG4G72QCFEm2HmZfHtq39OVm03FcfVewQUT2AKEQUsSk2IdtXjin7Y7Ad4h03KJcVU70GEl38S1WLhB5g5ZVFmQoguTq0pvbTqs2fM9SMEkDn51CLFn3ejFTkJ0RUEvM7jz546Jt/lNDXqDk9+sCRSE4nfycxaa45j5m8BzIDePX859PujJ4noYiK6GNCXEiSiLQD+CuBGItrSoACYDqDu/+2rAM4B8A3+ONu/EKIdqTWll1V//l/Trf2BPU8oUDKyL7ciJyHaW48r+u3+3Jv9E4/ONhODNRXB798q1aLBJ6zKSwjR9THzmmTFZtMtCu7+Y202p/dIIjLVI0mIriIv0/uPy46ZYKoFLaVqePSdxWWVodgL6RzPzDcz80hmHs3MZzJznJkfZ+bHjfeLmbkvMweYOct4Hax3/EnMvMZ4XcrMezHzKGaeaeZzCSHMYeYV8ZJfV5i9NnuH7+Ukp+d8Y4UOIbqUHlX0E1Ffe3avYfZAnqk4kZ+/iGvx2seZOW5RakKIbiJVU/K3mgUvl5mJQUTwjT04l5ye46zKS4jOioiGjB2U3zvLZ64X/Guf/xIP1SaekB54QoiG1JrSa2u+fs3UTP5kU+AbOzWPnJ4TrMpLiPbSo4p+xZ93beaeJxaaicGsIfjNm6VapOpBq/ISQnQfzLwkvvWX9WrY3NrAGWMPzlA8mVdblJYQnVb/gsDf/nbi7iavzYy7XltYWlwVediqvIQQ5hDRs0RUSkQr6m27hYi2EtES48+0Ro7rR0SfEdEvRPQTEV1R7727iGgZEb1Qb9uZ9fdpDDP/EN+8YqsaC5v6TP7x03yKN/MfpoII0QF6TNFPRE6b03O0q/9YU5+5dvXCpBaPPMfMUatyE0J0L6lQxT9qvptpqupX3D448vv3IaJBVuUlRGdDRHavyzFt8qi+puLM+X6dWhWOz2DmiEWpCSHMew7AoY1sv5+Zxxl/Pmjk/RSAvzHzTgD2BHApEe1MRJkA9mLmsQAUIhpDRB7o82c8uqNk1Nqa20I/vBfc0X7Nsbm8cBYMLiSioWbiCNHeek7R78o4xTfu0Fyzy/QFv5lRooYr/21RWkKI7khLfRZd802JloiZChPY/bhCxZ8vrf2i23I77YefedCoHLPX5ltfXFC8tTw03aK0hBAWYOYvAVSmcdx2Zl5svA5BX0mjD/QVMZzGChseAEkA1wB4yFhqs/m4ydjsyE+flLNqbgSQf+JRhYo/v9meBUJ0Nj2m6Fc8/it9Yw7OMBMjUbYBajT4HTPXWJWXEKL7YWbWYpF7wsvn1pqJ4+o7isjhOlwmDRLdVe9c398vOGwXv5kY363chuLKyOfMXGFVXkKINvUXo4v+s0TU7OTaRDQQwHgA3xoPAGYC+BHAegA1AHZj5rdbclJmVrV49InIyvkJM8m7+o4COZxHEFGPqaNE19cj/rESUR97Tp8im8trKk7NN2+WqjUlN1uUlhCiG9NioRdDiz8oY+a0YxARfKMPzCG76ygLUxOiUyCi3oN7ZQ0syDb1PB43v7Bg+8bS4A0WpSWEaFuPARgCYByA7QCa7D1LRD7oRf6VdStlMPPdxrCAvwG4DcBNRHQBEb1BRDtc6larrX40+O3MUrPXZu/wvbJAtv3TDiJEO+sRRb+Skf0n//jDTU0SpMUjSGxbtZ2ZV+x4byFET8fMSU7G3o5vXp7+nQUA3y6H+JWMrGusykuIzqJPnv+yvx6/m6lrc1l1LVZvqdzIzButyksI0XaYuYSZVWbWADwFYPfG9iMiB/SC/2VmntXI++ONl6sBnMXMJwEYTUTDdnD+sBaPfBjf8rOpa7N/3KFZ9kD+tWZiCNGeekTRTw73KZ5Bu5r6rOGlc8NqbfAeq3ISQnR/aqj8vuB3bxWbiaF4M2HP6tWfiEwVR0J0JkRk87jsJ0+dMMjUtfmZOUvDxZURuTYL0UUQUa963x4L4A+NacaY/WcA/MLM9zUR6jYANwFwAFCMbRqAHXbrVYNl/1fz9WvbW5N3Q/bMQtg8gVFEZGp4khDtpdsX/UQ0ytVnZDYp6Q+JZWaEln5UwYnaNyxMTQjRzTHzxmTF5i1q1NRkwfDtckiBzZN5mkVpCdHhbDba99jJw7MVJf3bEGbGCx+vqKiNJ9+1MDUhhEWI6FUACwGMIKItRHQ+gLuJaDkRLQNwAICrjH17E1HdTP6TAZwJ4MDGlvYjomMAfM/M25i5GsBCIloOfUqdpTvKi5m3pKq3b1RrzU3R5R8/Ld/m9p1uKogQ7aTbF/1KIP8y//hpBWZixDYu1TgZm92SmUGFEKI+NVJ9b3jZx6YWBvYM2c1uc3nPsionITragILAZecfOjbLTIxvftmGSCz5kVybheicmPlUZu7FzA5m7svMzzDzmcw8hpnHMvNRzLzd2HcbM08zXi9gZjL2+cPSfsw8m5lvrff91UbMFhfgaqT6gciKT00t8ekdubfL5vZdbCaGEO2lWxf9RGQju/MQZ++RpuIEv3+rRA2V32tRWkKIHoSTsbciy+dVmJk0yOZ0w55VVCBd/EV3QESK1+WYOKJfrqk4/57xXcmm0qBcm4UQrcbJ2Ozwik9Mrfhhc3rgyB9YaKwwIESn1q2LfgCTvUN3zzSz/q8Wr0WqcmsxM2+xMC8hRA/BzEktGfsovnWlqTh6F/+AdCMU3cE+R04aGjATIBiJ48dfS4qZeY1VSQkheg5mTmiJ6MJE2QZTcXxjDiqweTNPtSYrIdpOty767ZmFl/vGTm12/c8dqV39dVyLhZ+yKichRM+jBsvuDn43y9SEfp4hE+02V4Z08Rdd3qCizEvPOmh0lpkYL3/6U7QyFH3IopSEED2QWlNyT2jxe+VmYrgHjrPZnJ6TrMpJiLbSbYt+IiLYHRMcuf1MxQkvnVOmxcKvWJSWEKIHYua1ybIN5ZxKpB3D5nDDnt2rgIiKLExNiHZFRLbiePTQK5/5NLFgxea04zzx/pLy6nD8VQtTE0L0PItjG5ZWsqamHcDmcEPx5xUQkalGRiHaWrct+gGMcfcd5TMTQA1XQY1Ur2Nmc9N7CiF6PC0ZfTW6frFmJoZvl0Pybd5M6eIvurLd3eMyUit3T9mPeP6duO+MB1J7XftS/J2Fa6BpLfvvsXpLJYKR+A/MHG3jXIUQ3RgzMydjr0TX/ZB+1Q8gY9QBueT0HG1VXkK0hW5b9Cv+3NMzdtov30yM8E+fhtVw5QMWpSSE6MG0SPUL4aUflZiJ4Rk80W5zes+wKich2psj13Fu9j7ZWYHxAVu/Kwe4Bt4xxL59qt11zgfzYv6zH0yNueLZ2PNzlzf7AOClT36q2VgS/E87pi2E6KbUSNUToR/eMXVt9g7dw6V4M8+1Kich2kL6i9d3cqQ4D3f13dlUjMhPn1dyKvG+RSkJIXowZt7iyO5VwalEL7I704phc7ig+LLzicjPzCGLUxSizZGdDvAM9Pz2vULw7eSDbyefmzVG7Yao/a/zF8b//NInSlGGN3XZQePcFx+5K9zO325X3lqwqkZj/rwD0hdCdDPMXOzI7l2qJeO9bQ5XWjGUjCzYXBmDiMjFzHGLUxTCEt2ypZ+ICuxZRdmkpP9MI1m1DZyoXcLM6Q/CFUKIerRk7FWz3Qi9wydlw6YcYFVOQrQXIhrqGegJkK3xFXXIRvAO9qL32b1dg+4YYredm+OevmlZPPfCR1J9Lng0/s/nv9QWr9mOSCy5hJlT7Zy+EKKb0pLRN2Mbl5gafucZPikLRPtbk5EQ1uueRb8r4+iMnfc31bW/dvXCcCpU/qRVOQkhhBapfj689KNSMzE8g3fz2gP5Mq5fdDlKQDkxa1JWi67NRAR3HzeKTipyDZ4+1O77S5HrqeivqUk3vJLaUFLzXBunKoToQbRI9auRFZ+aujZnjNjbbw8UXmBVTkJYrVsW/YrHf6ZnyESHmRi1q76qhqZ+alVOQgjBzFuTlVsqzMzib8/pA9iUCRamJUS7UFzKUd4R3rTuO5z5TuQfWeC0BZRtzJBhd0IIyzDz+kTp+iBz+o39jty+ILtjIhE13pVJiA7W7Yp+InLYXBkDFG9m2jG0eARaNLhVZgYWQlhNS8Rej25IvxshEcGZPyiDiAZZmZcQbYmIFJvb1lvxKGnHSNWkoNaqa2XYnRDCaqwm5yW2rTYVw1k0zAtgmDUZCWGtblf0A5jgHrCLqaX6ousWp7R45BWrEhJCiDpabfXM2tVfl5uJ4R25d77N7T/KqpyEaAdjvcO9XjMBgouDcTWoPmtVQkIIUUcNlj0X+eWLCjMxPEN2y7W5fFOtykkIK3W7ol/JyJnmHrRrjpkYkZ8/K9eioZlW5SSEEPWsTGxbFTETwD1wnGJzZ5xoVUJCtDV7pv1w/zh/npkY1d9Ul2tx7T2rchJCiHp+iG1YYmpVHHf/0YrN4zvGonyEsFS3K/rJ4TzE1XtE2sezpiJZsbmGmbdamJYQQgAAmJk5lfw5VZP+nEGK2wdyefsRUbdddlV0Lzan7QjvsPQb+lllpKpSVcxcbV1WQgihY2aNU8kfk5Xp3/4rGdkgxSFD70Sn1K2KfiKykdNTaHN6drxzExLbV4NTqY8tTEsIIX5HjVS+FF23KGYmhrvvKC+AsRalJESbISLF5rH1Utzpj+ePboiCVf7SwrSEEOJ3UqGy56Nrv681E8ORN8BLRAMtSkkIy3Sroh/AKFfvEabGDNb++l21Gip7w6qEhBCiIU4l5tau+qrSTAz3gF1ybR7//halJERbGpcxIiPDTIDwinAwWZGUYXdCiLajqV9G1y6qNhPCM3T3XHJ6pliUkRCW6VZFv80TOMQzaEKumRixjcvCAL6zKCUhhPgDZq5M1ZTWsKamHcPVewTZXBmHWZiWEG3CnmU/0reLz9S1ObQsFASw0KKUhBDiD5i5KhUsDTNz2jHc/cc4FG/mcRamJYQlulfR7/Ie4eo3Ku3PxJoKLRqsYua4lXkJIURDrKU+SWxPf3kgY+zgQOsyEqJt2Jy2aRnD0m/o5xRDDalVsoyuEKLNsbYkVbUt7cPtgXzAZh9uYUZCWKLbFP1ERGR39lc8gbRjJErWgjV1gYVpCSFEo9Rg2ezYxqVBMzGUQL6XiEy1oArRloiIbC5bgc2V/u2GMZ7/c+uyEkKIxqVCFTNjG5eaavxz5PTJIKJeVuUkhBW6TdEPoJ8jt3/6M/gBiG1cGlaDpW9blZAQQjTj++jGpWEzATwDx2cB2MOadIRoE32dRU6XmQCh5aGaZEVyllUJCSFEk9TkF9FfvzM1545n8IQcgPa0KiUhrNB9in6ica5+o7LMhIiu+6EGwNfWJCSEEE1j5qAaroyYGTvo6ruzVwkUTLMwLSGsNi5jeEammQDh5eEQgG8sykcIIZrEzCXJ6mJTD+SdhUNcSiB/f4tSEsIS3aboV/x5+zkLh7rTPZ5ZgxquDDFzyMq8hBCiSZq6Sg2Vp324s3AwyGbby8KMhLCUI9exv2egJ+1eeKz+bzy/qSUuhRCixbTUL6makrQPd+QNANlsu1mYkRCmdZuin2zKHs78AWkfn6rYCmjaYgtTEkKIZqnR0AfxbSu1dI8nxQFyenKIiKzMSwjL2LCnq2/6vfvjxXEweKmFGQkhRLPUSPVbsU0rkukeb3O6QXZnvpU5CWFW9yn6FWeBzeVN+/h4ya+qGqmaa2FKQgjRLI5HvoxtWFJhJoYjq5cTgEwYJDolm8NWoHiUtI+PbYypqZrUJxamJIQQzeJk7Lv41l+qzMSwebM8ROSzKichzOoWRT8R+WwZmelX/ADiW36u5FRcWvqFEO3pl0Txr6aWIXP2GuYHsJNF+QhhGSIK2DPtpq7NtWtqKznBP1iVkxBCtMDqROm6hJkArt4jvADGWJSPEKZ1i6IfwBjjP1faEiXr4gBWWpSPEELsEDNrWjxSxZqadgxn/iCfzZs50cK0hLDKWO8wr6lrc3RjVK7NQoh2xcwpLR4xNceXq/eILJvbJ+P6RafRLYp+m9u3u6v3yCwzMbR4OMzMaY/fEUKINP2Sqi5O+2BHXn/YnF5ZGkh0OopfmeQd4s1K93hmhhpR5doshGh/mrpJjaTfw99ZMIhsbv9+FmYkhCndpejfz1kwKO2JrNRIFaBpm6zMSQghWkKLhhYmKzanfbwSyAOAIZYlJIRFbG7bfu7+aS+qg1R1CmCstzAlIYRoES0Rm58oTf/XjxIoAAjDLUxJCFO6RdEP0BAlUJD20YnS9eBkbIGFCQkhRIto8ciPiZK1NekeT2QDOd1+K3MSwgpENMCeZU/7+NimGNSo+rl1GQkhRMtotdULE8Vr0u7iT0SwOb1+WV1HdBbdougnh8tr5v9UYvuakBqp+srClIQQoqV+TmxfEzETwO7PcxKRLA8kOhVyksfMtbl2bW21GlIXWpiSEEK01LL4ll9MjetXfDkOALkW5SOEKV2+6Ccil83l9ZiJEd+2KgxguUUpCSFEizFzRSpUYWqWYGfRsAzIDP6iEyEih+JW0u/bDyC6LloLuTYLIToAM5enQuUxMzHsOX1cAAZYlJIQpnT5oh/AQEdOX4eZAGq4IgGg3KJ8hBCiVTgZCzFraR/vyOufSQ73SAtTEsKsvs4Cp2ImQCqYSjJztUX5CCFEq5i+Nuf09UOKftFJdIeif7Ajr7/PTAAtGa9lZrYqISGEaKVf1WBZ2gfb/XmweQJS9IvOZKCzl9PUcn1aUqu1KhkhhGg92qZF0p5yB/asIqctI1t64YlOocsX/Ta3b7g9u1faNxZavBbQUhVW5iSEEK2hJaI/JCu3pn284s8D2RSZwV90GuSkoa4iV9oTTGoJDZzi9O+2hRDCJGZ1dSpYmvbx9kA+bA7XzhamJETaun7R78oYZQ+kP39VKlgKMFZbmJIQQrSKVlu9MhUsS3stcsWXDYD7WJiSEKbYA/axzjxn2rP4JSuTIKK1VuYkhBCtodXWLE8FS9PuCWzUJ4Oty0iI9HX5oh9kG2o3sVxfqqYUWjyywsKMhBCitbakqovD6R5MNgVQ7BlWJiSEGWSjEY689KfbSZQnoMW1nyxMSQghWoWT8XWpym3pL9tndwI2e8DKnIRIVzco+pFPrvTvdVPVxVEtFpKWfiFER9qSqt5uapZgUpymZkoXwmJFii/9efwSpYl4qiYlRb8QoiNtTFZuMTW3CNnNzW0ihFW6fNFPisNhZh3gZOWWMICN1mUkhBCtVpIKlqtmAthcXicRmVq+dEeIaBwRTbMo1hNENLnBtueI6AQr4hvxbiGiq62Kl8b5fyAip4nj84noWyL6kYj2IaI/W5lfWyInecxcm+Pb4iHItVkI0bG2pKqLzV2b3RlOIpKeeKLDdfmiHzZ72jdUAJCqKUkCSH8GLSGEMImZU5yKx83EsGcWKAB6W5RSU8YBaFXRT0T2Jt7aA8A3ZhOqdx4ioja9pjXzWRrbdyCArcycMHHKKQBWMvN4AJsBWF70E5GpZfWaYrPbXGaOTxQnEpCiXwjRgZg5oSWiJq/NRe1xbRZih7p00U9ERIpiqujXoiEGIDMECyE6FKcSzXbvD6/4BNue/Qu2PfsXlL/3bwD6nCQlr12Pbc/+BbHNK/IA7Ar8r8X8MSL6jIjWEdF+RPQsEf1CRM/VxSSiMBH9m4gWE9EnRJRvbP+ciCYar/OIaIPRYv1/AE4moiVEdDIRZRhxvzdao482jjmHiN4koncBzG34WYhoJwCrmbmxFpR9iehrI+8TjP19Rn6LiWh5vfMMND7TowAWA+hHRDcQ0SoimgdghLFfARH9YLzehYiYiPob368lIi8RHVmvVX0eERUa799CRE8S0VwALxit7zONz/x9w94K9RwGYE4jn/1OIvqZiJYR0b3GtgHG51tmfO1PROMA3A1gGhEtAXAXgCHGz/4eInqUiI4yjn+LiJ41Xp9PRLcbr2cbvQ1+IqILG/y9/x8RfQtgEhGdQUTfGbGfMPsggIi8NrfNVIxUKJVk5mozMYQQwixOJaJmjle8AQeALGuyESJ9XbroB5Bpc/vT7z8IgNVUgpk1qxISQoi0aGpQSzbeoJAo24iahW+g8JTp6H3eI8ieotdvlR8/hoxRU9D7vEfg6juKAdTvyp4N4EAAVwF4F8D9AEYBGGMUlACQAWAxM+8K4AsANzeVntFifROA15l5HDO/DuAGAJ8y824ADgBwT71ujJMAnM3MBzYSrtGC2NALwN4AjgBwp7EtBuBYI88DAPybfus7PgLAC0ZreB6AUwCMB3AcgN2M3EsBuIkoAGAfAIsA7ENEAwCUMnMtgAUA9jTivAbg2no5TQBwNDOfBuBBAPcbn/l4AE838TkObfgZiSgHwLEARjHzWAC3G289YnyGsQBeBvAQMy9BvZ83gL8DWGv87K8B8KXxWQCgD4C6ZaH2BjDfeH0eM08AMBHA5USUa2zPALCCmfcAUAHgZACTjfOoAE5v4jO1VI49YDd5beYdrmZBRCOMBxV1f4JEdGWDfbKNhyLLjAcbo43t+US0gIhWENEx9fZ/m4ikVU4IodPUKGvp9/C3eQJOAJnWJSREerp60Z+jZGSZ+wxaKu1lsoQQwjpUrEUb73QU27QM3hGToXj1+wbFoy9/Ht+2Chk77wcA8AyaYMdvhR8AvMvMDGA5gBJmXm484PwJwEBjHw3A68brl6AXjK0xFcB1Rkv05wDcAPob733MzJVNHHcImi76ZzOzxsw/Ayg0thGAO4hoGYB50Ivcuvc2MnPdMIF9ALzFzLXMHATwTr24XwOYDGBfAHcYX/fBbwVyXwAfEdFyANdAf0BS5x1mrmvtOQjAI8ZnfgdAgIh+tx690SuiLzOva/DZgtAfYDxNRMcBqJsgahKAV4zXL6Jlfw/zoT+42BnAzwBKiKiXEetrY5/LiWgp9GEU/QAMM7arAGYar6dAf6jxvfGZpsD8ElO5SkBJf+p+AKzueFgEM68yHoKMg/4ZagG81WC36wEsMR6onAX9oQ0AnArgeeg/r2sAgIiOhP4QbJuZ3IUQ3QjZarR4+nP5KZ6AG9LSLzqBFo9P7KRyFW+Wqe79rKpmxlsKIYRFuFqLN9GLkBl63ds0m8uLBjvVdRvQ6r2u+76p3/116xGn8NtD4eZWBSAAxzPzqt9tJNoDQKTRA4i8ALKaKazq51r3eU4HkA9gAjMniWhDvbwanqepNZXnQy/yBwB4G3rLOQN4z3j/YQD3MfM7RLQ/gFvqHVv/HDYAk+o9BGjMPtB7Dvw+MeYUEe0OvbA+BcBfoPfG+MOuzcSui7WViLKh9yj4EkAOgJMAhJk5ZHyGg4xca4noc/z2M4vVG1pBAJ5n5n/s6JytkGPPtKc9pp+Zwakdt/Q3MAV6T4iG8wDsDOBfRtyVxpCQQgBJAB4ALgAa6fM1XAngyHTzFkJ0S1VaPPK/h+2tZXNn2MnpybM4JyFarau39Ocqvuy0l6liTQW0lKkJOoQQwgqsaZWcaLw1wT1gF9SunA81GgQAqFF92WBXn5GI/PIlACC+dSVgs7e2hdIGoG62/NPwW6G6AXrLKeq9DwAhAPXvfD4CcFldV3siGt+Ccx4A4LNW5pkJvRt+kogOgF64N+ZLAMcSkcdofT+ywXtnAFhj9HiohD4p4Vf1zlE3qevZzeQyF3qxDkBf0aCRfQ4F8GHDjUTkA5DJzB9ALzDrjv0a+kMAQH/A8YcHBvjjzx4AFhpxvoT+UONq/NZzIRNAlVHwjwSwZxOf5xMAJxBRgZFjjjHswYxMuy/9ol+LaYDeK6I1TgHwaiPbl0If6gHjgcsA6L06XsFvPU5ugT5J4gvGUA8hhNCxVs7xRp9ht4jN5YPN6S2yMCMh0tK1i36y5Sne7LSXqNJiYYBsFVamJDov0icj29DG5zjHmCTsHBMx2jxP0flwKlHWVBdCZ/4AZE46GSWvXIdtz/4FVZ/qw8hzDroI4eXz9In8Ni6BkpH5QytPGwEwypjk7kDoE/UBwL0ALiGir6GPk6/zGYCdjfHTJwO4DYADwDIiWmF8vyPNjedvyssAJhLRIuhF8crGdmLmxdCHKyyB3n19fr33NhgvvzS+LgBQzcxVxve3AHiTiOYDKG8ml8uNXJYR0c8ALm5kn/2hz5HQkB/Ae8YwhS+gz7dQF/NcY/uZAK5o5LNVAPjKGIN+j7F5PgA7M/8KfSLDnHqfeQ4AuxHzNjSxUoIxjOJGAHONfT+GPq9C+hQEFG/6k+xqUQ1E1NTQkD8whlMcBeDNRt6+E0C2MXThMgA/Akgxcw0zH87ME6H/7I4AMJOIniKiGUQ0Kd38hfWMHhpM9SYiTSOG6euz6HlYTZVpJop+cnlBij3fwpSESEuX7t5vc/sKbe6MtCcL0vRWsxLrMhIdyei+uh8zm5pAqjMyblL+C+BcZn6uY7MRbUGLR8q0ZiYJ9o2ZAt+YKb/bZs8sRNGpdwAAUsFSlLx2gwsAmPmcun2MYnd0ve/PqR+Dmf8J4J8Ntq0EMLbephuN7ZUwJser56KGuRr/Rp9r4qPshd+K3YbHNczNZ3wthz72ujGj63/DzNMBTG8ifv96r++APra/7vu3oXf7b3jMLQ2+L4c+8V2jiKgvgPLGuv8z83YAuzeyfQMa6ebf8OdoTCRY//1nADxjvE5Cn6Cv7r049Acsf1D3c633/ev4bW4H0xSPUmBzp9+moEZVtHLm/sOgj8X/w/XcmNvhXEBf8QfAeuNPfTdB/zdzKoAfoPcCeBt6rxQhRA+mJaLFWsxMS38GQLbcHe8pRNvq0kU/2RQPTMwVpCWiYNaqdrynEC32FvQWte0mYkzZ8S6i21GTVVosnITect5q5PQC3PlnCDZm4O+2mHkLmii2ewqb05Zr86Rf9GsxDWC0uKUferHeWNd+EFEWgFpj9YkLAHxpPAioe38YgN7M/IUxVCMKfU6FtIcOijaxFcBOkCWWRTvjRG2ZFo+oANJahtTmzgAAKfpFh+vSRT9siotMLAXMqgqwJmP6hWWYuQYmb0qYea1F6YiuJaTFwnGkWfTbnB6AtUBrjmnY4iuEJRTkmGnp12IaONnkyg+/Y0wMeTDq9TghoosBgJkfh14ovkBEKvRVDs5vEGI69KUnAf3BwWzowytuSvsDCMsZPVkaHdYjRBurUaPBGOr1pGoNm9MLgDv9A3nR/XXxMf3kgs3EcwstBehdIEUnRkR7GGMsi4koQUSbieiJurWU68b6AdjP+J7r/fm8kXheIrqHiDYRUZyIfiWiv9dNRlZvv/+NITRev0ZE5UQUI6JFRHREI7GbHDNIRH2J6CEiWmPEqCR93eh/Ntjvd2P6jc/wX+Pb/zb4fAOJ6E7j9VlN/PwmGO+/2+wPWnS0oBYLpb2aCNkUgGymVjMRwgpE5CAl/VFWWlyDltCqW7KvsTxjrvHAtW7b40bBD2ZeyMzDmHkkMx9Xbw6Hun1PYuY1xutSZt6LmUcx80yITqOpMf1E1IuI/mNcNxNEVEZEs4hoQhOh6o47nIi+JqIIEVUZ9xjDmjtG9FhBLWri2qzYAUCuzaLDde2WfrK5SDHR0q+pgKZK0d+JEdG5AJ6CvozXOwA2Q19r+gIARxLRngCqAdwK4BzoMzPfWi/EhgYhHdBn3+4NfXbtFIBjoE/25G5wbJ0BAL4DsA76Gto50Mf0vk1EBzHzDmciJ6KJ0Gc6z4E+kdgsAF7oy0ndguYnQHvO+IxHQx9nuqTee9UAHoe+zvRFAF5o5Pi6FrAndpSn6FAxTiU0UxEaPLgSossimPu/ILo9IhoEfULO3gA+hd5Tox+AEwEcTkTHM/N7jRx6HPQhOG8B+Bz6KhrHAziAiPZquASp6PGS0NQdLqPaPLk0i47XpYt+ArnITEu/mgKzFrMuI2ElIhoOvVDdAH2Cvq313jsQ+izTDzLzsQBuIX1d6gENJ95qoDf0JZwOrptoi4huBbAawFVEdIfRjbC+/QHcwsz/eyBARK9Anx37Guxg+TFjZuk3oRf8pzPzKw3e79fc8cz8nFHLHQ1gdiMT+VUT0YfQb3LGMPPyerF90Me7bkYjS4iJTkWDpsmNhRBCtMzj0K/pNxoTeAIAiOhR6A/XnyeiAcwcbnDckQCOrP9AgIiuAPAAgEch8+qI39NY00w+kJeLs+h4Xbx7P5wwM6ZfU8FqUor+zusS6C3zV9Qv+AGAmT+F3vJ/JOnrcbfG5fVn1mbmUugt6JkARjSy/0YAtzc4/0cANqGRmbgbcSSAgQDeaVjwG7E2tzjzpj1mfL2wwfbTAfgAPM3MqgXnEW1HZTZZ9MuNhRCiBzBWyZgK/Tp8d/33mPlr6K3+OdBb9Rv6tJEeAI8AWAvgQCIaYH3GogtTwWY7HsmlWXS8Lt3SD5DLGCuTFtZSgJqSor/zqluiaz8iarhMGAAUQJ9NdTj0ZZZaosZY07qhusI7u5H3ljRRMG9G08uI1ben8bUtW9o/hL4M1ZlE9Hdmrlvw/UIAKoCn2/Dc3QIRPQt9re5SZh7dyPsjoc+tsCuAG5j5XmN7PvRuolnQW5xmG9vfBnAJM29raQrRLUv8xbP/L+3fSZoaz0r3WCGE6ELGG1/nN9I7D9C7+59h7Ndw2NsXDXdmZpWIFgAYYhyz0cJcRdemaBsXZITeWpf2tVnRQjKRn+hwXbzoN9fSDzUFTklLfydWt8TJNTvYrzUzkFc3sT1lfG3sH1Rzx7Skt0yW8XVrczuZwcwaET0BfW6Ck6FP+DcBeoE6uxWFZ0/2HPTWnsbmRQCASgCXQ58Dor5TATwP4DXoQz5mE9GR0NcNb83PXVUGD055Tz23tT1X/id4zy0yR4kQoieoK6KaWh63bntWI++VNHFMcYPYohNowQP50wH83fg2DP1h+1ILH8gnxwyLqSedVJH2ajf33B1t7MGUEO2qqxf95rrC2hRAUdJaHku0i7rZmDPrr6vcBVUbX/u08XmehT4R4UXQW6RlAr9WYOYviWhgM++XAiglosMbvJUE4AHgAqARkR3AldCHdbQGKQVFUecuE9Iu+qHYozveyTwiCje23J+xVFotM79grGAx1+oHTsbcHQmjCy+M2bzfY+YZVp5HCNGp1d0fFDXxfq8G+9VX2MQxdbFMLbsrLPccmn8gvx76vE9VRHQYgCcB7AHrHshTUaE9NnasJ+2i32ZDu1ybhWhO1x7TD0Q4lfYqGiC7EzaHO/0bbNHWvjG+7tPC/VUAICIT3T/aRN3nOMxEjLrhBU1+NmYuAzADwB5ENBn6BW8D9NUKRNt5BcAh0G8qbgHwZwAv1Bti0VIKbCZ/JbPJeQBNMpZKq7sxOwf6JFtW2x/AXlYEIl1Xvw4K0RP9aHzd23jQ2tABxtfFjby3X8MNxn3D3g1ii06Amb+E3tOuqfe/rrcU5zcA+hqvm3ogf08rU7B11asEEX1urB4FIvqAiLKMP3+ut09vIkrrobmxpPUJTbw3iYieSi/zrouIxhHRtI7OozFd9J+xgTXTRT8pjoCFGQlrPQL9l/b9xkz+v0NETiKq/0Cgwvjavz2Sa4V3oRffRxHRqQ3fJKKW9ABo6Werm9DvdejDHp5kNj0DjWgGM9cw8+HMPBH6DeYRAGYS0VPG2s8tmfcBAFzkcpt7YGXB3zURXUtElxuv7yeiT43XU4jopXr7TSeipUT0DREVGttuIaKrjZuAiQBeJqIlROQhoglE9AUR/UBEHxFRr8bOXy9+DhHNJqJlxjnGGj0xLoa+0saSev//9zXW3F5X/waEiK4hou+NGLca2wYS0S/GDN+LoS/xJYToQph5C/QVfAZCL+T+h4j2AHAagCro3bsbOpCIjmiw7S/Qx/N/xswynr/rOh+/zZ9k1QN5l9tl7ok8c8cvQcrM05i5Gvpwhz/X276NmRst3E06FPrPvsN0UCPgOABS9FuNNS3EqfSHsJLdCdiUtLvriLbFzCsBnAf9ov4TEb1LRP8mooeIaDb0MXv1nyJ+YnydZRQkNxLRme2adCOYOQF93eAqAK8YT17vJKIHiOgjtGzCoIUAagFcSUQPG5/tRiL63dhDZv4K+pKEfaA/MHnW0g8jduQmANOh97L4Afq/3ztaeKybXC5zv5M11YoVGr7Eb71rJgLwEZEDeivYfGN7BoBvmHkXY/8/1Q9gdLVfBH2JynHQ5794GMAJzDwB+r/L6WjerQB+ZOaxAK6HfrO2AfoyXfcz8zhmrsunl5HfEdDntQARTQUwDPoKG+MATCCifY39RxjxxssNvvXYbI8TAox/c0I052Lo4/DvIaK5RHQHEb0IfaI+DcC5zBxq5Lh3AbxFRG8Yx7wPfbm+StQrhkTXQkQHQC/6/w5Y+kDe7XKnXzwyMzQNpq/NxgPrlUT0vPEgewYReY33phDRj0S0nIieJSJXI8dvIKI86NfIIcaD83uMuCuMfRQiuteIs4yILjO232Q8QF9BRE8SUUuWI5gCYF6DHGxE9CgR/URE7xm9D05o6jMQ0WFE9Ea94/cnoneN11OJaCERLSaiN0lforruc95E+sScJxrf32rst5z0SZnrGimeN353bCCi44jobmOfOXXXoKYaLIx7+buI6DsiWk1E+5C+RPf/ATjZ+Pme3Iq/4jbXpYt+aKkQJ0229EvR36kx80sAJgB4GcBY6E/jzwAwFHpX9voX6KcB/Av6JDzXArgN+gWgwzHzIuiFx2MABgD4K4AzoT9xvbkFx1cBOB7AzwDOhf7ZbkPjqw381/j6NjM3NWGRsBgRDQPQm5m/AOCFftPJANwtDOEmjzfteVZYTcGiZRl/gF4g+wHEoT9wmgj9QUBdkZ0A8F69/QfuIOYIAKMBfExESwDciN+6YDZlbwAvAv9bojO34UOuemYzs8bMP+O38bpTjT8/Qr/hGwn9IQAAbGTmb/4YRliCEeFk+oW/4lVALiqwMCPRDTHzOui/mx6H/jvmaujD6OYAmMzMbzdx6CwAx0Lv5XMFgMnGtklGY4PoYohoLPR7wKOZuaKRXcw8kPe4XY0OIWmRRIJBBKsm2R0BvQfnWABBAH8mIjf0eQ9OZuYx0Odru6SZGNcBWGs8OG84UfaFAAYBGG+c42Vj+yPMvJsxkaIH+gOUJhkPF5LM3HB+jOOg3y+MAXABjBWwmvkMHwPYk4gyjONPBvC6Ef9GAAcx867QGxn+Wu88MWbem5lfM74vN/Z7DPrviTpDABwO4GgAL0Hv6TMGQBTA4Ubh31yDhZ2Zd4fe2+hmo5HvJgCvGz/f15v7ObW3Lj2RH6vJMKvmin4YT4ZE58XMy6GPD97Rfir0FsHrm3h/YDPH3gK9+1f9bRvQzOKqzLx/I9ueg/6Lq7H9N6EFrQhN5cnMc9CyrlJ1Sxk93oJ9hYGIXoU+XjyPiLZAfxjjAPSx6kRUBP3CEoA+PvBKADvXm2RyOoAbjNevApgN/Ybypham4CVvhjPd/DkWA9lskXSP/18c5iQRbYD+cOlrAMugj48dAuAXY7ck/9acq2LH1xIC8BMzt7Rlpe6YP6TXxL71b6io3td/MfPvJrIkfYiA6Z+TaBonuVStTf/5k+JVQArlW5iS6PrqHp7+rnhi5q1ovsCpv+9z+P31+b3G9xRdCRH1h/7Q5kxmXt3I+/97IE9E46AXdK15IJ/hzbClfW2OxRhEll1zNhs9OgG9SL0cemG8vt5nfx7ApdB7r7TWQQAeZ+YUADBz3VwKBxDRtdAbNHIA/AS9x0xTpqLx+aT2BvCmMey0mIg+M7aPaOwzMPMDRDQHwJGkzztwOPRGvf0A7AzgK6PTgRN6A0WdhsX2LOPrD9AfPNT50LjnWQ59zqy6e+zl0B9O1G+wgLFP/RVD6scd2OhPohPp0kW/lowFzbb0A/97eiREl0dE/QCcAr04+7SD0+lSmPkP8y00eL8YzbROM/NJ9V6XorWTzRH5yONNv+iPxwCQVTcWX0J/Gn4e9IvffQB+qFfot0QIQN1EqasA5BPRJGZeaDw9H87MPxHRXwCAmR9pJIfTAdxG+oz95cwcJKIQ9AcvO/KRcezLzBwmfe4MWTapHahRtViNpF/027y2upYiIerUzeuzpUOzEO1uRw/koT9YzwXwqFGYpYwu/XVMPZC32eDzeGxpDzeKxRjQr4dWaHgNZjTTOJUGangOoxX+UQATmXkzEd2CHT8wOQz6fUNj8Zs6b1Neh/4QoxLA98wcMoYXfNzMfVvDe6G6h4UNGyniwP+Wva7fmKEZ++2owaKpuJ1S1+7er6YinIqnfWdhs7sA/amVEF0aEZ1m/CL+GPpMtf9sZYEmOhj5A4U2fyDtizfXRgC9u58V5kMfJ7/QGCISw29d+1vqOQCPG935FQAnALiLiJYCWILfHoqMxG8TVdZ3C4CJRLQM+hjEs43t7wI4ln4/kd8fMPNc6BM5LTSe4s/Abw8hRBviBJerETXtByyKVwEaH7okehjSJ/C8C3rRoaHxiflEN8bMpzJzL2Z2MHNfZn6G9ZViHjfev4CZs43u1OMaFPxg5pOYeY3xupSZ92LmUcw8syXn9/ttBRne9MulWEwDrCv6+9NvcxGcCmABgJUABhLRUGP7mdDntWhK/QfyDc0FcDEZK2IQUQ5+K/DLjXHzzU76ZxTkY6Ff5xtaAOB4Y2x/IfSHOdjBZ/gcwK7Q5w6qa8H/BsDkuv2JyEuNTPhtgf81WBjncRDRqB0c09zPt0N1+qcSOxDVkrEkmlnGrDk2dwbAnGtxTkJ0hAsB7AtgM4CrWnoxE78homehj1MrNcatNbXfbtAvOCcz8wwiyod+I5oF4EZmnm3s9zaAS7iF6wHbFYypfeP5ROLb+Rpl55ItJ89uy8xWbP4AyB9A3VfyeEGNzKHDkTBYU8tb+bEbxcyfwGhJMb4f3uB9X73XM6AX1HXDZOq2zwRQ/9/hEuj/RhsaiN+Pxas7vhL6OLuG21dDv6GoM7/B+/VzexDAg42cs8m/X2GJajWsxlDv31Br2Fw2MHNT8zeInmVXAJdBLwouZuYVHZyP6GHcHltvnz/9oj8S0aCqjT7YTscvAM4moicArAHwGDPHiOhcAG8axfr3aGZ4JzNXENFXpE/e9yGA/9R7+2novWqWEVESwFPM/AjpS+8th74S1fc7yHEC9El4G2t4mgl9gr8VAFYD+BZATXOfgZlVInoP+jDfs41tZUR0DoBX6bdJC280YlqGmROkTzT4kDGnkB36sImfmjnsMwDXGQ0e/+pM4/qpKzcGEtFemXud8n7WPmdkpRtj65MXrUhWbhljYVpCiC6I9Jndw9BndW+0KCR9+ZePobd8P2sU/ZdDHyP4GoA5zDyZiI4EsCsz39rS8/fqbX/+vPNyz7IrQGlZClVVKsqroJYH7amaiI0jMRticbIlUyAodrBNASsOQLGDfH6NVZXUDWv/k6qu/kMBLUR7IqLxuYfkzu11aq+0u+ivvm71ivj2uFybhejhdvRAnoiOhj6xsQZ9pZgrmXmBVQ/kCws9H/XqRfv37u3QcnIVys212bOz7UogYEMgoKDuq8PReEe9776txV13lV5TXa3e2+oP//vPORDAe801SnQGRHQjgF/rTaLX8H2fMeQuF8B30CfdLG7XJHuort7SX5oKlpmaEZMU+x+WtRBC9DzM/KVxUW3OZdCfVO9Wb1sS+my2LugT/Nmhz+R6ZGvObyPKHz/Ojeyc3/1aVtBsTyYNqVQMFRW1+OijIF79uebn1pxTiDZSrYbVlJkAZJMl+4QQAPShYo8AeKGJ9z8B8A4zszGL/xvQh42dCn1CuNegT9A223ggv7ilBT8A2O05yiWX3OQMhUIoLi5GWVkZfl1TolZXlyZDoSpEo2HE4zEboJHNxlDsDEUBMjJsnJVl08IhTQkGtbCJz9+lMPPtO9jlPSLKgj753m1S8Lefrl70l6jhClNLVJHikKJfCLFDxkRwxwI4EL8v+l8x/pwFfX3gP0PvLVDbmvgaI88faP1IJbvdhsJCGwJ+JZZM/m5WWSE6SnUqlNLMBCBFin4hxI4fyDNz/YI6A79NRGfJA3kAOWPGjIHN9rsu/s0+kNc0DeXl5di2bRtmzpwZZ563uZXn/ANjRalO3crfEo2tfCXaR9eeyA8Ia7GwuaLf6bYTkceqhIQQ/8/eeYdJUWxt/H0nbM55lwWWKEmCIBIVBBXFgKIgRgyfOed7zVmM9xq5RlBRVFBRUFGRKIJIjkqOm3OcnXC+P7pWxmXz9MKG+j3PPvRUV5863btM9ak6ocXyHwD3q9KQfyMi+SIyViUPWgPDDXE2yXdIzvJKulMjNhuDbLaGJ+HNyXGXouqEeBrN0abAXeL2KXaQVtpZVfIKjUajqQTJ80luAzAPRtUZwFiMPwPGLv9jaOCCvM1mC6hk8NeKxWJBXFwc+vbti5iYmEJAL8hrjj3N2ugXERG3yyf3fltojAVAnEkqaTSalssAADNVDfsLYZQHGlepzyMwygNNglG39WoAz9RFuJ+dda0ZXCVZWa5yAJm+yNBozEBE3OIUn9z7bVE2K4BYk1TSaDQtGBH5SkS6ARgHI77ftAV5f39/nzyCMzMzndBzs6YJ0KyNfgAQt9Mno98aGu0HIN4kdTQaTQtFRDqISIqIpMDIVn9TRWIgACDZBUCSiCyGUQrUA8PNsFZjnqTFz48+vVikpbvcAOocp2gGJJ8gOfpojqnGrTI+kuQNJK9Qx5NJJh1dzTQViEt8mpv9E/wDYFR20Gg0mjohIksAdCJZOYlogxbkSdoDAgJ8mpuzs7M90Ea/pgnQ7I1+uN1l4mm4h78tLC4YQIJ5Cmk0muYIyU8B/AbgOJIHSF6jjMgb6ijiaRglYwDgUxjlZVYAqEvG3oTYWFuDSo9WUFLiKReRUl9k1BcReUREfj6aY9aEqt1ckexpMgBt9B8jxCkl4mm4h79/on8YLOhgokoajaYFQrJzRSgQyRNgJIjL9jrf4AV5AEnx8fE+2UolJSXlIlLmi4yqIPkYyXvqec25JB9o4Hh7qlhMqTj3L5KXNlDuIpID6tF/AMlX69BveS3n/13XMStddwfJIK/P36nEhE2e5p7IDyDTPSUFsIZENuhyW2SivyU48ngA35irmEajaU6IyKR69J1cRdsEr+MMAEPqMXy75GS7T+795Q7fdlYrIPk1gLYwXoj+KyJvq1KF78EIcRAY5QpfITkNRgmhWSQfgZEgKRDAcgDXq2zKi2DU4h0Jo3TSNSKytIbx7wNQJiKvknwFQB8ROZXkKABXichlqt/TMNw1SwGcJyLpJB+DUXZxj9J1BslSAIMB9ADwMoAQAFkAJouIjrNsPA648l197ZENy8fnF+tns4XbjgfQZGocazSao49akB8BIIbkAQCPArADxkIvgPEArlB15UsBTKxUI/5pAA+q408BfA3gdhi7/7XRrn379kG1d6seh8NhusHfEEjaROQbNI69czqACbX2MgER+QPAH3XoV9s72L9RhbeHWkCiiFSXjPYOAB8DKFHjnFWbLk2F5r/TL5597uKcBl9ui0yCxR7Qz0SNNBqNpl6QaJecbA9t6PVut8DprF9yohq4WkT6wzCab1O1dPsCaCMivUTkeAAfVHHd6yJyoqohHAjDIK/AJiIDYUyWj9Yy/hIAw9XxAAAhJO0AhgGoWCwIBrBCRPqo/v/nLUBEZsF4KbhURPrCqN38GoAL1b29D+NFUNNIiEu2lmeVN/h6e4wdFrulh4kqaTSaZoiITBKRRBGxi0iyiLynvLqmqvNTRKSniPQVkcEisqzS9RNEZLs6zhCRIar/7NrG9vPz69SuXbsGz80ulwtOp9PnuZnkFSQ3kFxP8qMqznci+QPJ1SSXkuym2qeRfJnkQgBTVNjb6+pcPMmvlMz1JIeo9q+VnM0kr6uDbmEA/EQks1L7QJLLSa5V/x6n2gNJzlT38xmM94WKa4pITlHj/6xkLCK5i+S5qs8IknPV8WMk3/fqc5u3LPVvIsklJNeR3ERyOMnnAASqthkkU0huJfkmjPwPbUm+RfIP9RweV7Jug+FBuFA90789IJTeN3mN/xjJu9XxvSRXqXt+vLZn2lg0e6PfXZK/xpmb2mAfQltYLADpaKJKGo1GUy9iYqwnJCbZGux5lZPjBgmfSwIpbiO5HkZoQlsAXQDsAtCR5GskxwAoqOK6kSRXktwIo6xhT69zX6p/V6P2OO3VAPqTDAXggBFyMQDGQkCF0V8OYG49ZB4Ho9TRTyTXwQjDSK7lGo0POPOd652ZzgbH3tkj7YCgvZk6aTQaTX2Iioo6PjExscG2UkZGBiwWyx5fdCDZE4anwqlqofv2Krq9DeBWtah9D4A3vc51BTBaRO6udM2rABYrmScA2Kzaq1r4r4nRABZU0b4NwMki0g+GV0XFrvqNAEpEpDeMxff+XtcEA1ikxi8E8BSA02CUS36imvG7wajSMBDAo2qTwJtLAMxXGwB9AKwTkQcAlKqFooqwhONgVHfoJyJ7ATyokkD2BnAKyd4i8iqM3EkjRWRkpXFmApjo9XkCgC9Ing7jPWogjA2U/iRPruZeGpVm794vzrJtzqx9BQDCG3I9LVbQ5t/gVTyNRqPxFbudfZKTG16WPD3dBZcLf/qqB8kRMCbwwSJSolzzA0Qkl2QfGBPrzTAms6u9rguA8ZIxQET2Kzd773CFitADN2qZd0TESaNCwlUwwgQ2wAgN6ARgq+rm9HLfrFUmAALYLCJ1ytasMQE3djtSHYUwQjrqDa0E7Qw2VymNRqOpO1ar9fjk5IavD6empsLhcGytvWeNnApglohkAYCI/MO9mWQIjHDCL3i4yql38sEvKpca9pJ7hZLpBpCv2m8jeb46rlj4r6kc8BhU7f0XDmA6jZwKAhWSAeBkGAsOEJENJDd4XVMOo8QiAGwE4FDvBBtR/eL+PBFxAHCQzICRnP2A1/lVAN5XiwFfi8i6auTsFZEVXp8nKE8HG4BEGCGCG6q80riXtSTjaCQQjgWQKyL7lHfA6QDWqq4hMJ7pkupkNRbNfqcfwPbyjN0+uc5Y/IMCSfqZpZBGo2k+KNewDJKbqjkfTvJb5f62meRVqj2W5DLlLjbOq/8c1jNrvMuF40qKPXA3sLR5aqrTnZvrqnYyqgfhMCaqEuUeOAgAaCTvsSh3yIdh7Ap4U2HgZ6kXkAtrG4hkG5JV7Q4AxmR4j/p3KYAbYKzO1+cBFQKoWND9E0AsVYkmkna1e6JpPPY60hw+JZaknUH0eovVaDSthzrMzfcq9+wKt203ySgz52aLxZIUERHR4Hs4dOiQKysry9e5mTCM5uqwAMhTu9YVP929zhfXeaB/Lvz3gWGo1pZvaCCA36tofxLAQhXyd04lOdXdj/eCvgdqw0DF11e3uO+dz+iITQBV0eFkAAcBfERV4acK/n5OJDvAeAcZpTwS5qFuiR9nwXj/mQhj5x8wfn/Pev1uOovIe3WQZTotwehPdxdkOH0RYItKtkGXBtJoWivTYKxUV8fNALaoCXAEgJfUIuEkANNhJIm7FwBIngNgjYjUq3Sew+EX/thjJWWTr0x1Xn31Qedttx4qf/nlzLJ58wrcmzeXIT+/Zi/pXTvL85xO33f6Yayw29TK+5MwXPwBoA2ARco1fhqAf3lfJCJ5AN6BsTL/NYyV9dpIhBFrXxVL1fnfRCQdQBkOu/bXlWkApiqdrTAm4ikqdGEd6pdoUVN/Up1ZDXfvBwB7tN0GXV1Ho2mtTEMNc7OIvFBhSMGYkxarXXBT5maSdDqdbTZv3ozCwsIG3cDOnTvzRWRngy4+zAIYu87RSq8o75MiUgBgN8mLKvRWnnl1kXujusZKIza/yoX/6lCL59uq8SQIh2FoA0Y1nQqWALhUXd8Lhvt8o0GyPYAMEXkHRkLiik0LZxWhABWEwVgEyCcZD+BMr3PeGwqVmQngYhjvG7NU23wAV6sNkYoNj7iG3o8vNH/3fhGxR7f1aaffLy4lrNhwtfjLJLU0Gk0zQUSWkEypqQuAULXjGAIgB4ax6oSRgMYfgIekDUaiunPqMz7J2C5dupRdcsklf0/kJSUl2LNnD5b/us8zb+6BsuLiLAIui78/EBdn83TtakfnLv7+bdvakZhox65d5Q4A2+szbpU3arjInVnN6cq7+/+oYiAiD+FwyULvPiO8jrNweIF1EIA3qtFjAQ67AkJEulY6H+J1PAtqchWRx7zaZwPwTtS0DsZqv+YoICKegOQAn3b6gzoFhRauKewFQFdZ0GhaGXWYm72ZBCMzP2DS3Awgoby83PbCCy+UlZSU0GKxWAICAtC2bVt3jx49rF26dLGnpKQgJiYG1Tkk7dixwwEfbQsR2UyjWs1ikm4Yu++TK3W7FMBbJB+CMXfOBLC+FtG3A3ib5DUwdshvhLHwf4Na+P8Thxf+q+NMHHbHr8zzMNz77wLwi1f7WwA+UGOsQ9VeAmYyAsC9NKo7FEGFNMDIg7CB5Bocru4AABCR9STXwshzsAvAr16n3wbwPcnUynH96ncVCuCgqOpAIvIjye4AflN/J0UALgOQYe5t1g7r5y3ZNLFHJi5LvOq1oRa/wNo7V0HpnnXInvvSY66inGOWUVGj0Rw71IvFXOWGVvlcKIwSN91grO5OFJF5JMMBfAIjfux+GInr8kVkej3HPnnEiBHfnHLKKbXmJfF4PEhPT8eePXuQlrbPWVCQ4S4vL7E6HO6yrKzysPqMq9E0Nv5x/uu6TOnSh5aGeegXbSrCgXcOPOrMc1aXwEmj0bRgapqbvfoEwYjh7iwiOSbOzaNHjRr15bBhw/7e1XW73di/fz/27NmDjIwMR3FxMTwej8Xf3x+xsbGe7t27o3v37v4pKSlITEzE5MmTd+3YsaNTA269WUDyJwBXiC5/2yxo9jv9ii2uvNShfnENS8LvF98RtPufYrJOGo2mZXAGjNXoU2Ekk/uJ5FIRyQcwFgBIRsJ4ubiA5DsAIgG8JCK/1SY8ICCgX0JCQp0SkVosFiQmJiIxMRHAYDsAu4jg9ddf39aQG9NoGhXir/LM8j7+8f61960C/2R/WPwtOgxDo9HUxDkAfq1IcGfW3BwcHHxiQkLCP9y4rVYrUlJSkJKSAngly/N4PMjKysKuXbuwevVqZ2Fhobu8vNzqcrlaQhh1tYjIacdaB03daRFGv7skf7Uz59C1fnEdG7SdYA0MA6w2Xb5Jo9FUxVUAnlPJZXaQ3A1j19/bJe0RGKVnJsEoIfcJgDkwss7XSGBg4ClxcQ0P78rPzweAHQ0WoNE0Eq4i11LHAceF/vH+9Zqb3WVuFG4oRMnmErfVbe3bSOppNJqWwcU47NpfmQbPzX5+foPrOjdbLBbExcVB9bcDsOfk5ODjjz9ubNd1jabOtAijX8pLN5Sn7cgL7jYssqEyrMGRQSRDRKTITN00Gk2zZx+AUQCWqoQux8GI8QIAqHI0SSKymGRfAKUw8gDUJdMrSHbzJTtwZmYmysrKVjZYgEbTSHhKPH+U7CrJC+sfVu3cXJ5ZjoK1BSjf7ihHDsTipiUoLBApvZLdXc7v6Dc/baGFpF1EfErYq9FoWh7Klf8UGDHSlc/5NDdbLJYuoaENr+idkZEhpaWlv9beU6M5OrQIox/AesfBrSUw3HYaRECbHsGOfRv7AlhmmlYajabJQ/JTGIleYkgeAPAoVBI5EZkKI4v9NBp1Ygng/op6uYqncTgJzKcwstffDmOHobax/dq0aRPqS1WytLS0wpKSkj8aLECjaTw2le4qLQUQ6fF4ULqjFIXrC8Wz3+NAvsdit9sZHhsm/fr3kM43d/BP7pGE8Ni/X7LtALB7zV4e+jOtJ4wQG41G00qow9wMAOcD+FFEqipL58vcHJCcnBziy9ycmpqaX1ZWtqbBAjQak2kRRr+IlNij29a5DmVV+LfpHmEJCh8ObfRrNK0KEZlUy/lDAE6v4fwEr+MM1K8UXK82bdrUadehOvbv318Io1SeRtOkEJHC0PiQgNRHDzr9A/wQ3zHOM/Ck3taUa9oGJB2XAP8gv1pldB7YIWrlV2sGQRv9Gk2rora5WfWZBqO0X1XnfJmb+7Rt2zaoHv2P4ODBgyUwsr9rNE2CFmH0AwA8rr3u4tyu1uCGbfb7JXSGxS9oJIBnzVVMo9FoqiYgIGB4SkpKVO09qycvL69MvdBoNE2OAH//HQ9+c/vAwLCGVddpf3yyJTgyeDSAqbV21mg0GhMICgo6uX379g32HgaAgoKCUhHJNUsnjcZXWkxWSU956cLytJ0Nvt4aHAFYrO3N00ij0WhqJjAw8Ky2bds2+Hu4vLwcLpcr3UydNBozcbvcSw7+mdbg62PaRsFiZbXlujQajcZs/P39xyQnJzfYt7+srAwul+uQmTppNL7Scoz+kvylZQe35PkiwxYaHaLKe2g0Gk2jY7VaO4SEhDT4+tTUVLjd7qW+6kFyeT37jyA5Vx2fS/IBX3XQtExyU/MX7F63r8HhdyQRlRQRqudmjUZztLDZbO2Dg4MbfH1qaipcLtci8zTSaHynxRj9ANY5DmzxKa4/sPPASFisp5ilkEaj0VQHyejw8PCGv1UA2L9/f1FBQcECX3URkQbXQheRb0TkOV910LRY1vy1YleBLwJ6j+oRabFaTjZLIY1Go6kOkgmRkZE+xfPv27evoLCwcKFZOjUGJP9toqwIkjd5fU4iOctE+ZNIPlh7z3rJjCW5kuRaksO99W8KkJxG8sIq2hv8bFuM0S8iRe7ivBJfZASk9Au0hcZOqL2nRqPR+IbFYhnWuXPnCF9k7Nq1qwCAz3WASRapf0eQXERyFsltJGdQpS8mOUa1LQNwgde1k0m+ro7P8ZpEf1YlDkHyMZLvK9m7SN7mq86a5oGIZGTtzyn1RUa3oZ0Do9pEXGSWThqNRlMdVqt1eOfOnX3yLNqzZ08hgNUmqdRYVGn006C+9mEEgL+NZhE5JCJHGKw+MAbAD/W9iKS1htOjAGwTkX4A9sNL/6aML8+2xRj9AACPa5+7OK/Bl9uj2wIWS3/zFNJoNJqqCQ8Pv7hTp04+7SYUFBQUi0ieSSpV0A/AHQB6AOgIYCjJAADvADgHwHAACdVcuwzAIDWJzgRwn9e5bgDOADAQwKMk7SbrrWmiOB3O3QVZRQ2+PrFLPCx6btZoNEeBsLCwizt27NjgqjoigsLCwiIR8cnDCQBIXkFyA8n1JD9Sbe1JLlDtC0i2U+3TSL5KcrlaXL9QtSeSXEJyHclNalf7OQCBqm0GyRSSW0m+CWANgLYVmwFKxoUkp6njeJJfKZ3WkxwC4DkAnZS8F5S8Tap/AMkPSG5UGwIjVftkkl+S/IHkdpLPV/MMCKCv0su73UryRSV3A8lbVfseko+oDYqLSP4fyVVK19kkg0j2BfA8gLNIrgMwpZL+RzwzJbuI5BSSq9XGxkCvzYxzVZ8UkktJrlE/Q1R7TZsqz5Hcou7jRa/bPLmK36f3s51Mco56hn+SfLSmv6cWZfR7yormlO3f5G7o9SRhC48PIRljpl4ajaZpQLItyYVqcttM8vYq+lyqvng3qC/bPqo9luQyNQGM8+o/h2RSfXWxWCz9Y2Ia/lVTUFAAj8ezvcECqud3ETkgIh4YZdJSYBjsu0Vku4gIgI+ruTYZwHySGwHcC6Cn17l5IuIQkSwAGQDiG0F3TROkJL/0q79W7PRpbo5MiggjGWGiWhqNpolQx7n5PDUvryP5B8lhqt3subl3VFTDi+rk5eXB4/FsbbAABcmeAB4EcKqI9AFQ8UxeB/ChiPQGMAPAq16XJQIYBuBsGIY4AFwCYL6I9AXQB8A6EXkAQKmI9BWRS1W/45TcfiKytwbVXgWwWOl0AoyyhA8A2Knk3Vup/80AICLHA5gEYDqNjQTAMOYnAjgewESSbasYrx+A9erdw5vrAHQA0M/rWVRQJiLDRGQmgC9F5ESl71YA14jIOgCPAPhMPZf7K+l/xDNTcoMBLBKR/gAKATwF4DQA5wN4QvXJAHCaiJyg7s3791PVpkqUur6nuo+nvPpX9fuszEAAl8J4lheRHFBNvxZn9P9Qun1Fli8ygroMioLVPtIsnTQaTZPCBeBuEekOYBCAm0n2qNRnN4BT1JfvkwDeVu2TAEwHMBiGQQuS5wBYIyL1ytJLI2YwVC3yNoj9+/d7SkpK5jVYQPU4vI7dOFzatfKEWxWvAXhdTe7XA/DeLalOrqaFU5Jf+uPGBVt9mpt7n9o9Qsf1azQtlrrMzQsA9FGG2NUA3lXtZs7NyTExMb7Oza7i4uK5DRZwmFMBzFIL5RCRHNU+GMAn6vgjGEZhBV+LiEdEtuDwwvoqAFeRfAzA8SJSWM14e0VkRR31ekvp5BaR/Fr6D1N6QkS2AdgLoKs6t0BE8kWkDMAWAFVVURsD4Psq2kcDmCoiLiU7x+vcZ17HvdTO+0YYxrH3ZkR1VPfMynE4zGAjjMUPpzpOUe12AO+o8b6AYeBXUNWmSgGAMgDvkrwAgHeoelW/z8r8JCLZIlIK4Ev88+/hH7Qoox/AjvKMXT7G9fcNsIVG67h+jaYFIiKpIrJGHRfCWPVtU6nPcq/auitg7F4DgBNAIAB/AB6SNhgrti/UV49Am/+FuVk5MW//723nzz/97Dhw4AA8Hk+9ZPz1119ZDofD5yR+dWQbgA4kO6nPk6rpFw7goDq+stG10jQXduzbfNCnubnbsC5BUUkR481SSKPRNB3qODcXee32BuPwQrRpc3NwQNCE7Mys6Hffece5cOFCR2pqKo7cYK6Z7du3Z5eXly+q79hVQNRtsd27j/fiOgFARJYAOBnG3PwRySuqkVM5Gbq33AaHO1ToUQ112Qw4HcCP1cit7vl438s0ALeozYjHUYd7qeGZOb3+Bj0V+isjvkL3OwGkw/AQGADAz0v0EferFi0GApgNYBz+mbvgiN9nVerW8vlvWpTRLyIirvKd7qLc2jtXgy0yCbBY+5iolkajaYKQTIHharWyhm7X4PAK8ycwYtJ/APAYjKQvH4pIvY2ZuJDocT9d9r5t0aTp9jOCBviv+WlF2dQ33nJOnza9/PeVvztzc2v/DktNTS0G8Fd9x24IahX+OgDzVJxcda5/jwH4guRSAD7t7GpaDiIiTodrT2G2L3H9cbBYLYNMVEuj0TRBapqbSZ5PchuAeTB2+wEz5+aIqPPWvvGlbfV/v7CP6TLAf9XiX8umvvmW8+OPPipfvXq1q6Cg9jD9tLS0YgC76jt2FSwAMIFkNAAoN3AAWA7gYnV8KYxcOtVCsj2ADBF5B8B7MFzyAcDJmnPrpJPsTiOp3/mV9LpRybaSDIPh6h5ajZwlSk+Q7AqgHYA/a9LZS/dwGIZxdhWnfwRwg1rk8X4+lQkFkKru9dJq+vxD/xqeWV0IB5CqFgIuB1BTMkGQDAEQLiLfwVis6luPsQDgNJJRJANhLBr8Wl3HFude6SktnF22b8PI4B6n1PiQq4Mk/GJTQkl2FBEz/tNqNJomhvqSnQ3gjuqS7dBINnMNlKuUcmEbq85FwogBu4DkOwAiAbwkIr/VYWxrt9iOnWODjfnpqv7jcVX/8QEAsDfvEKav+dIz97OvywpdJba4+Hh3j5497B07drQEBBxenC4sLITL5dou9d2CqAYRCVH/LgKwyKv9Fq/jH2DE9le+dhqMlXSIyBwAc6ro81ilz71MUFvTjCjJL/lq+8pdp5xwVu8GbTZYLBYk90gM13OzRtNyqW1uFpGvAHxF8mQY4XejTZybbb07HpcSE24k7r9z/GTcOX5yAABs3bcTU+fOdH/1+SxHSbnDmpiU6O7Ro4dfSkoK/fwOb+Tm5+fD7XZvM2NuFpHNJJ8GsJikG8BaAJMB3AbgfZL3AsgEcFUtokYAuJekE0ARgIpd67cBbCC5BkbugMo8AGAujMz2mwCEqPbbAbxN8hoYu9U3ishvJH9VCea+B/CGl5w3AUxV7u4uAJNFxFHHEIrTAPxczbl3YYQJbFD39g6MfAeVeRjGAtJeGG74RyxOiEh2Jf03oepnVhfeBDCb5EUAFuJID4rKhAKYo/IcEIanQH1YBiN8ojOAT0Tkj+o60qR3xiYDyZSgbsN/iz3v/uqyS9dKyfaVnuz5rz3sLsp9xkzdNBrNsUet9s6FkaTl5Wr69AbwFYAzReSI3XSSrwD4GsaEY4Wx0zBHRGrNB0Jy4LUDLvr+0VG31pgpyOPx4Nd9a/DR+jnOdZnbBDYypUMHT/ce3f0zMzOd8+fPv9HhcLxX23gaTVOAZNdB4/svmfzixAYncNz4y1bPRw/Meiw/o+BJM3XTaDTHnrrMzZX67wZwYkXMu2rzZW4edvdFV3/z1FV31Fiuz+Px4PtVS/De/Nnla3dtg8VqZafOnTzdunXzT01NLZ8/f/615eXlH9U2nqZ2SL4L4N065hpodZCcDGCA9wZNTbS4nX4R2eMX087HuP4+Fos94CIA2ujXaFoQNJaW3wOwtQaDvx2MZCiXV2PwdwGQJCKLaZR9KYURQ1WnmLek0LhJZx03otbUwBaLBcNTBmB4ygA7AJS5HJi18QfMXvCj46/sPdby8vKf6jKeRtNE2L5vo49x/UM7W/wC/S6CscOn0WhaCHWcmzvDyLAuJE+AESud7XXep7m5XVzipecNGVWjwQ8Yc/PYk0Zg7Ekj/ACgoKQI0+d/hZlLvi/bcWiv1el06rnZJETk2mOtQ0uiRcX0VyBu51+ugvqHk3o8HhRvWYLy2fc7Il2ZPZSbkEajaTkMhRFjdaoq+7OO5FkkbyB5g+rzCIBoAG9WlAaqJONpAA+p409huNutAPAi6oCf1X5mv6Tu9VY8wOaPy/qdh9kTX/OPtofvEpF99Rai0RwjRETKS8v3FGQ1PK7f7m9HTNvIaOqyuhpNS6Muc/N4AJto1FV/A8DESm70Ps3Ndqvt1BM6Vy4YUDthQSG49fzLseTFjwJiQyN3iUhavYVoNA1ARKbVdZcfaIE7/QDgLs77pHT36pGhfc7wr62vx1WOorXfIXDbt45AR7b1tHYW19Wn2gK2ZtnK7/vJfSGMGBGNRtMCEJFlqDmTbMXKcrWryyIywes4A8CQuo5Pssu53UdF2CwN/+rdkrEDLo+r2kQtGk1TpSin+MMNP28ZMuzigbXOzdUx6IL+sfs2HrwAh0tpajSaZk4d5+YpAKbUcN6Xubn7pJFjI6zWBqUDAwCs2bEFTpdzYYMFaDSNTMvc6XeWzS3esqiqTI8AAFdJPvIXve9xvX+pI+TDCa7/c3zkmH9ekf/2mwNt750bEDC0nQ3ju/v5RQXymqOpt0ajadkkhsZeO6n32DhfZMz/a2n+/vw0HS+oaXaUFTvmrPx6jU9VHY4/tbs9KCJwskkqaTQaDdrExF931ZjxPs3Nc5YvyN2XkTrDLJ00GrNpkTv9IpJrj0zMFFd5Em1GVs3y7AMo+/0zV/DBlZ54/3JO6mmViZfa/duGBwFVPIfIQCIhxJJMMlxlBtVoNBqf8LP6jRvUrm+dUtZWx4KdvxWghpIsGk1TRURyY9tHZzhKytv4B/nVfkEVBEcEISQyuC3JoPqU5CJ5HIDPvJo6AnhERP5TRd8TYbgFTxSRWSRjYST2jADwkIh8rfrNgZG5+lCDbkaj0TQJAvz8xw7p0c8nGT+t/rUQxveGRtMkaZFGPwB4nGWz8ld91duWtskZnLWFnUM9cnVfq+XcMXa/qMCgOsm4so89elOG+3yoclQajUbTUEged063U8N9ce3PLytEflnhAREpN1E1jeaoUVbk+HTL0r969zujV4P9aE88t2/Uoe3p58GI260TIvInVP1jklYAB2EY8v9AnZsCYL5X8yQA0wHMhFEL/GuS5wBYow1+jaZ5Q7LnZaPP88m1Pys/F4UlxXtExGWiahqNqbRI934A8BTnzQpYM8P5/gnbbNtu8LMvmRzoN7mvny0qsO6bbON72ANigvh/jaimRqNpJSSGxt50xQnjGlyuDADmb19anldW+IFZOmk0R5uinOKZv836I9MXGSedf0JQWHTI7T6IGAUjC/jeKs7dCqNOeIZXmxNAIAB/AB6SNgB3AHjBBx00Gk0ToG1s4k1XnXFBrC8yvv1toSO7IG+6WTppNI1BizX6RWRbqB92n9XFZgm0N8ybNspw8W+ns/hrNBpfIMkAm//ZA5N7+yTn8w3fZxY4ir4wSS2N5qgjIvtTt6fnuV3uBssIiQxGbPvodiQTGyjiYlThJUCyDYDzAUytdOoTAGfA2OV/DMBNAD6sT3iBRqNpepC0BPj5nzW4R1+f5Hz409dZBSVFs83RSqNpHFqs0Q8ApU75ZvFet9Tes3puO8kvPj6YN5qlk0ajaZUMGtlxULiFDf/KzS8rRGpR5kERyTNPLY3m6ON0uObt/GOPTzJGTh4WHx4XWu+5maQfgHMBVLV49h8A94vIP1YkRCRfRMaKyAAAawCcDWA2yXdIziI5uP53oNFojjUWi2X42YNGRJANT7WTXZCH9NysvTr/l6ap06KN/oOF8t77a8szau9ZPed3s9lD/XA1fflG0Gg0rZq24Yl3Xtr33GhfZMzfvrQ8r7TgXbN00miOFXlp+R+u/GqNTy7+PU/pavEL9JvUgLn5TBix+OlVnBsAYCbJPQAuBPAmyXGV+jwCox74JACrAVwN4Jl66qDRaJoA7WIT77nmzAsjfJHx9a8/lWXl5+oSopomT4s2+kXkz98PegrcnoZv9tutxPnd7dF2C0aaqJpGo2klkAwI9gs6qWtMik9ytGu/pgWxcfvvuws9Hk+DBVhtVnQf1iUChqFeHyahmgSAItJBRFJEJAXALAA3VWTqBwCSXQAkichiAEEAPAAEQEC9b0Cj0RxTSAaGh4T26ZTUzic5H/00J6uwtPhLk9TSaBqNFm30A4DDJXN/3d/w2EEAuO0kv4jkMD5ikkoajaYVER4Qetnl/c7zKUlQTkkeUosy92vXfk1LQETE6XDO3fH7bp/C70ZcMSQmOjnyvrr2JxkE4DQAX3q13UDyhjqKeBrAQ+r4UwCTYZToerGuOmg0rRWSbUkuJLmV5GaSRyTjJHkeyQ0k15H8g+Qw1R5LchnJTd7eNyTnkExqiD6RIWGXXnXG+JgG3xCAzPwcZOTl7BGRQl/kaDRHgxZv9O8vkHffW+v0ycU/OcyCDpGWLj4kDdJoNK2U8IDQ2y/seUagLzLmbF1Qkl2S+5ovMkimkNxUzbknSI72RX499HiXZI96XrNaxWJ7ty0iWeMuL8k7lKFX8fk7khH1UrjuOk4m+Xo1574jGaF+bmqM8Zsbuan5/13wwbKqXOzrTFLXBASGBpxEsk477SJSIiLR3rG3IjJVRCon7oOITBaRWZXaJojIdnWcISJDRKSniOgEXhpN7bgA3C0i3QEMAnBzFXPBAgB9RKQvjNCZipC2irKZgwHcCwC+ls2MCAm787LR5/g0N3+yYG5xWm7Wq77IqGluNgOSSSRnqeO+JM+qwzUjSM5Vx+eSfEAdj6vv/K2uG0zynUptKSQvqa+shkCy6GiM09Rp8Ua/iGxZts+VW+byaUMB9w3xT2gTyrtNUkuj0bQCSPYdmNw7PsjPp/cKfLbxu+zi8tIjaoqbhYg8IiI/N5b8SmNdKyJb6tqfZAqAgyJS3oDh7oDhhl0x9lnHwlvCa9wIGJnfWz0isuvgttT0smKHT3KGXXxSdGBYwFF5cdRoNA1HRFJFZI06LgSwFUCbSn2KRKTihT0YRvgMYHLZTJInjugzMC44IKj2zjUwY8E3OaWOsm98EtLIiMghEblQfewLoFajv9L134jIc+rjOAD1NvoBjIFR/cSbFABVfner36/GZFq80Q8ABQ689dlmp09vFqd1slqC/Xih/kPUaJomJANI/k5yvXIdfLyKPkfNdRAAkkLjXryi3zifXPv35h1CQVnRRhEp9UWOwqoyjm8m+SPJQAAgOY3kher4OZJb1HN60ev8VJJLSf5F8mzVnqLa1qifIap9hNqJn0VyG8kZFQnXvHfoSY5R160nuaAanc/EkS8L/4DkW+r3+ffvneRtAJIALCS5ULXtIRmj9N5a1bOoYYyNaqeeJLNJXqHaP/Lykkgi+QPJ7SSf97p2D8kYAM8B6KT+/l5Q5+4luUo97yP+ZlsypQVlb62eu96nuXnwhQOCgiOC7q74+9JoNE0ftZjbD8DKKs6dT3IbgHkwdvsBk8tmto9v89hdF17lk2v/n/t3o6Ck6A8R8W3l0qC6ubkvyRVqfviKqoQ4ydu85umZqu0xNR/9ouag/1PtKerdxg/AEwAmqjloIsmBJJeTXKv+Pa6yYlRebGp+PxfAC+r6TiTXePXrQnJ1Nfc3CkDljYXnAAxXsu5U43xB8lsAP5IMIblAvSNsJHmeGmcKvTzm1H3frY5b7XxaF1qF0Z9VIu+9urLcp0zBFhKT+9ijguw41yy9NBqNqTgAnCoifWCsZo8hOahSn6PmOkgyyuEp6X/Lt485b//2SceunP0NEYPPNszLO1iQ/lKDLj6SLgDeEJGeAPIAjPc+STIKRp3yniLSG8BTXqdTAJwCYCyAqTRcqjMAnCYiJwCYCMDbzbEfjJ2YHgA6AhhaaaxYAO8AGK9+ZxdVo3NVOwSVeVCVU+sN4BSSvUXkVQCHAIwUkaoSsdb4LKrgV3UPPQHsAjBctQ+CEdcNGH93EwEcD+PFqm0lGQ8A2CkifUXkXpKnKz0Gqmv7kzy5Fj1aDMV5JTOWfLLCp7nZP8gPPU7uGg/j96DRaJo4JEMAzAZwh4gUVD4vIl+JSDcYu8pPqjbTymaSTA709x/aMbHy13P9ePe7L3L2ph9q7Ln5QxhlRHsD2AjgUdX+AIB+qt07J0lvGHP0YACP0GvTQnnLPQLgMzUHfQZgG4CTRaSfOldtJRIRWQ7gGwD3qut3Asgn2Vd1uQrAtMrXqQVvZxUlDR8AsFTJekW1DQZwpYicCqAMwPnq/WIkgJfU4u5MGPNsBRMAfNHa59O60CqMfhEpyi6R5evTfEvod11/e2hCMP9lkloajcZExKAibsuufqRSn6PiOggAYQH+d57T97iQ207vbw8IzfSfPPtux7kfXe/8acevHo/ULWu5RzyY9+eiPI94FjdUj0rsFpF16ng1DEPemwIYE+27JC8A4L2L8rmIeFRM8y4A3WA843dIboRR99zb7e93ETkgIh4A66oYaxCAJSKyGwBEJKeysmpnIllEdtVyXxPUjsNaGEZ5XdwPa3sWlVkK4GT18xaA40m2AZDj9Xe3QL2clgHYAqB9LTJPVz9rYbzIdoPx0tIqEJGi4tySjZn7sn2Sc8b1I6Oj20Y9aZJaGo2mkSBph2HwzxCRGjPei8gSGJ5RlXfkfSqbGR8cfVugBAT2ve481yuzPigvLCmu1z0AgMfjwQ+rluQBWF7vi6vmiPmIZDiACFUtBDA2JiqM2A0AZpC8DEauhArmiEipiGQBWAjDAK6JcBgG8yYAr8CYP+vDuwCuImmFYYh/UkWf0wH8WEd5P3m9CxDAMyQ3wPASaAMgXkTWAoijkaugD4BcEdmHVj6f1oVWYfQDwN58eWLKrw6fEvpFB1nQO96aTLKzWXppNBrzIGkluQ7GDvRPInJMXAdJ2vxstst6JMbbAOCE9m1w8+j+/qf1jrO//NvrzlPeucT16vIPy/PLak74u2T3Kk9JeennIuLbiuVhvN0Q3QD+Ea4kIi4YLwmzYeyyeO+wV06MIgDuBJAOoA+M0mneyfZqHAvGhF5bspXhAJbV1IFkBwD3ABildj3moW4l1GrTrzJLlD7DASwCkAmjlvtSH2QSwLNqp6OviHQWkffqoHuLIftg7pQlM1bk+iIjOjkSce2je5D0rfaWRqNpNNQu7XsAtorIy9X06VwRqkPyBBhzSrbXeZ/KZpL0Dw0Imfj1pDf95k58x7Zjw37LoFsmOK97+WHH7tQDdb6Xn9Ys95Q4ymZ7bSL4Sn3njrEA3gDQH8BqHg49rmqeroknASwUkV4AzkH9y4/OhhGCdzaA1SJS1QpurSF6XnivwFwKIBZAf+Wdme6l3ywY8+9EGDv/gJ5Pa6XVGP0isnnlQXdagcO3/5/3D/NLaBfOf5uklkajMRERcavJIRnAQJK9qujTqK6DABBgt108qGPbaIvln2HGcWEhmDysr/91I4+3/ZGxyHLW9GucN3z9iGNbZtUb2W+u/CQtrSjrlSpPNgLK7TJcRL6D4enQ1+v0RSQtJDvBcNf/E8YuQarazb8cgLUew/0GwxW/gxo7qoo+YwB8X4ucMBgvCvkk42G8YFRQCCC0HjqB5C0kb6ncLiL7AcQA6KI8D5bBWGxYWrlvDVTWZz6Aq9VzB8k2JOPqo29zRzyydP2Pm/M8nrp5v1THOXednhiVFKF3+zWapstQGPPEqSqOex3Js/jPspnjAWxSi/dvAJhYybD2qWxmZGD4VVf1Hx9roQVBfgF4fNRttsVXzrD39evhP/7hWx2j772qfOHaFZ7abPmXvng/7VB2hlmu/VWi3OFzSVaEkl0OYDFJC4C2IrIQwH0wEsSGqD7n0chvFA1gBIBVlcRWnoPCARxUx5ProNY/rldebfNheL99ULmzWsDpDcPbr0ZZVRAOIENEnCRH4p+eczMBXAzD8K+ostLq59PaaFVJ6bJL5KUP1pW/dftJ/g1O13lSGyuiAnkayUgR8Wl3QqPRNA4ikkdyEQyjscpSOCKyRCWiiVGucBVUdh38BMAcGDFltULSEhUc+PDgzu2rncz8bDaM7XOcDQA2HkjD9XP+5Qi2hVpuGnSpZUzX4VabxYaDBek4kJ+2TUTS6jKuSYQCmKPi9QljJ7+CPwEsBhAP4AYRKSP5JozFkYtguBLW2U9SRDJJXgfgS/USkwGjhro3I2D8PmqSs57kWgCbYYQd/Op1+m0A35NMrSauvyq6VZLhzUocXthYCuBZ1OKJUEnXbJK/KlfK71Vcf3cAv6nNrSIAl8F4Fq0CEfFEJkZ8ue3XHXf2GN61wRsRHfu1R0hU8CiSEXIMKjRoNJqaEZFlMOaVmvpMATClhvMTvI4zAAyp6/gk2T4i6c6Lep15RNLWCcefiQnHn+m/Of0vPPnem467yp+zXn/ORM+Vp5/vF+j/z83vPWkHsD8jdbOI+FRytI5cCSOHThCM+e0qGHPQx8r9nwBeUe88APA7DG+3dgCeFJFDNJImVrAQwANqUeVZAM8DmE7yLgC/1EGfmTBC+m4DcKGK658B4AJU7cLfH8DaajwiNgBwkVwPIxdAZZtqBoBvSf4BY9FgW8UJEdlMMhRGZZ9U1fZja59Pa4PmeaY0fUj694i1/LXpxuB29CHR7w87XO7rvi2dui/fc8RukEajOTaoxHBONfkFwpiApojIXK8+nWEkUhPlOvgtjJhxUee7AHhKRCaSvB1AKYzdhB9FpE67/QF2+4WnHNfhvdN7dg2rj/45RSWYt2F7eW6R23Je99HujKJsxxebfjjX7XGbFc/fYEhOAzBXKtUtb+QxkwG8IyJn1trZ3HHnArhAGlYiUNMASCZ0Oanj6rtn3tDgShkAsG7+Jtenj379fF5a/oNm6abRaFoG/ja/MVf3v/DTB0feGFFb3/yyQjy9+C3nyrT1HN1/iPueCdf4t41NAADc+eYz2VPnzjxXJbZrMpB8DECRiNTJ68HEce+B4SH4cBXnHgKwQ0RmHnml5mjTatz7AUBEHIUO+W7ZfrdPKx1ndLJa44M5ThkZGo2maZAIozzbBhgubT+JyNyj6TpIksH+9idO7tqxXgY/AESFBOHyIX38bhrd17Y1d4V9wa7lTo94ltRXTktBJQE8qga/GvdsbfAfXUQkLedQ3saMPVm1d66B3qf1sAWFBVxe4d6p0Wg0gDE3x4fEPH/ToEsi6tI/PCAUz59xn33h5R/Zkh0Jfuc8cH352H9fV75o3UqZ/8eyLBjhaa0ekl8BuALAf6s6LyJPaYO/6dCqdvoBo17l2C625XMvCUr0Rc6iPS7PlV+XTtub57nGLN00Gk3zxt9mO2dYl5QPz+rdLcIXOb/v3l82b/22B4ocjionUo2mpUFywJCLBnx/xfMTfKqdveb7jc7Pn/jmpdzUPF1pR6PRAACC7AFjLu837pOHT705sqEy/jiwCfcveL48syj32ZzCvMdMVE+jOSq0qp1+ABCRPVsy3Xszin1LGjQixWZJDrOMoVcNTI1G03ohyZAAv2dGdusU4YscEcHSv3ZnFpeXv2OSahpNk0dE/vhrxa7U0oJSn+T0G9PLHhwReBnJCHM002g0zRmSjAmOeuHWIVc02OAHgP5tekKckp5blP+cWbppNEeTVmf0A0BakTz91ipnga9yXjrdP7FdOKssO6LRaFoXNovltF5tEtoE+tl9krM7K1dKnc7vGlouUKNprhTlFj+96KPlNdexrAWSGHffmQmRieGPm6WXRqNpvgTZA84+p9upyREB9SrkcgSLd//uKSov+UJlrNdomh2t0ugvdeH7GRud2W6Pb6ENg5Jt7BhpOZlk+9p7azSalgpJhgX6vzCqe2efdhIAYP7mv9LySsqeMkMvjaY5UVbkmLX8iz+yXOUun+T0GtHNFhodMl6VrdJoNK0UkpbooMgpNw++NMJXWf9ZPj0ttTBT7/Jrmi2t0ugXEXdhubz3yUanw1dZr5wRkNg+nDruVqNpxQTYbBf0bZfULtjfzyc5h/IKkFNUskJEDpikWrOF5B2qTFHF5+9qctmub/8qrreTXN1QfesDySdIjm7AdSmq3F91538g2cZH3c4l+YA6Hkeyhy/y6oOIuMuKHW+s+madT3MzSVzwr7GJUUkRz5qlm0ajaX5EBIRecnHvsW3C/H3L7bk1cyfSi7JWiEimSappNEedVmn0A0Bakbz01NLydJePu/19E6zoHms5SZX60mg0rQyStiB/v+dGde8c4ausueu3puaWlN5jglrNGpJWAHcA+NuIF5Gzaqm/Xt/+lRkG4KiUYBKRR0TkZzNlqjKVUSJy0AcZNhH5RkQqdrPGAaiX0U/S1tDxAaAwq+itH99enOFrkuFuQzpbwuPDxpJM8EmQRqNplpC0RwSEPf5/J06sdzWdyry87IP0A/lpuhSoplnTao1+ESnLK5P/vr/W6VvWIAAvnx6Q0D6cr5uhl0ajaV6E+PvdfErXDon+Np9sHaTlFyKzsHiNiOwySbUmCcmvSa4muZnkdV7tRWoHfCWABwEkwSjBuFCd30MyhmQwyXkk15PcRHIiyduq66+OryC5QV3zUTWqjQHwfRX6FpGconT+meRAkotI7iJ5ruozmTw8B5CcS3IESSvJaUrPjSTvVOenkbxQHZ9IcrnS7XeSoWpHfynJNepnSB0e7QgAiyrpHlfhvUCyD0kh2U593kkySOnysnpuUyruRY15LoAXSK4j2Un9/KCexVKS3bzu528ZddC1WkSkpLSwbOb6Hzc7fZEDABc+dE5iVFLEK77K0Wg0zY+YoMjbrj/p4sRAu79PcnbnHsCm9L+2isg2k1TTaI4JrdboB4CMYnn9heXlaQ6XbzsK3WOt6Jtg7UuyV32vJfk+yQxvl02SF6kXYg/JATVcO4bknyR3VLhjqvYp6gX3Q6+2y0neXl/9NBpN9ZAMC/Lzu3tQp3bBvsqat2Fbem5J6V1m6NXEuVpE+gMYAOA2r7jrYACbROQkEXkCwCEAI0VkZKXrxwA4JCJ9RKQXgB9E5NXq+pPsCWMR4VQR6QOguu/BkahkNHvptUjpXAjgKQCnATgfwBO13GtfAG1EpJeIHA/gg0q6+QH4DMDtSrfRAEoBZAA4TUROADARwKu1jAMAZwL4wbtBRDIABJAMAzAcwB8AhtPIQ5PhlSyyK4DRInK317XLAXwD4F4R6SsiOwG8DeBW9SzuAfCm13BHyGgoeWn5T855aX66x+NblZ1OJ7Rnm+6Jp5Ls7atOGo2m+UAyJCIw7PaLe48N9FXWs4umZhzIT7vVDL00mmNJqzb6RaQ8r0ymvPVHebGvsl46PSCuXTjfJsl6XjoNxkusN5sAXABgSXUXKffXN2C86PUAMIlkD5LhAIaISG8AVpLHK7fPyfjnC5pGo/GRiMCA58/p2z3RavHtqzSzsAhp+YUbROQvk1RrytxGcj2AFQDaAqgIjXIDmF2H6zcCGK0WN4eLSH4t/U8FMEtEsgBARHIqd6BRejWnmooJ5ThsTG8EsFhEnOo4pZaxdwHoSPI1kmMAVK4acxyAVBFZpXQrEBEXADuAd0huBPAF6uZiPxTAsiral6tzJwN4Rv07HMBSrz5fiIi7JuEkQwAMAfAFyXUA/gcgsT4y6oqIFJbkl773x9z1PufdueTJ8+Oi2kROa8DcrNFomimJobFT/j3ihgSbxTcPvF05+7Ep/a+NIlJtLhWNprnQqo1+AMgqkfde/708rcTp225/pygLJva0d48K5KT6XCciSwDkVGrbKiJ/1nLpQAA7RGSXiJQDmAngPAAeAH7qBScQgBPAvQBeVS+qGo3GBEimRAYHnds9Mc63twoA3234MyO3pPROM/RqypAcAWM3e7Da2V4LIECdLquL0agWRvrDMLqfJflIbcMCqO0L/kwA86s555TDAeYeAA6lhwdAxe/ehX/OpwGqTy6APjA8CG4G8G4ddbsTQLq6dgCAGjNEkuwIYL+aCyqzFIaR3x7AHCVzGP65qFyXhW8LgDy161/x072eMupMfkbB8/Ne/Tnd7fJtHSEyMQJDLhrQKTgi6AqTVNNoWj0kA1Q40nrlmXpEiUyS4SS/9epzlWqPJblMhT2N8+o/Ry3A+qpb146RbS84rfNQ3+rnAnhq4Zvp+/PTbvFVjkbTFGj1Rr+IuHJK5fH/rCj3qTYwADwx0j8iNojPsR4Zo32gDYD9Xp8PwHAjLYSxW7YWwG4A+QBOFJE5R0EnjaZVQJIRQQEfXjigV2LtvWsmu6gEB/Pyt4jIZjN0a+KEA8gVkRIVDz6ohr6FAI4orKxeCktE5GMALwI4oab+ABYAmFARRkAyqoo+Vcbz14M9APqStJBsC2NRFjRyClhEZDaAh710rWAbgCSSJ6r+oTQS4YXD8ADwALgcgLWW8Y9w7fdiCYDLAGxX8nIAnAXg1zrc19/PVEQKAOwmeZHSlST71EFGgxCRktL80jdWfrXG55rYZ9wwMiwkMugJ5a2g0Wh8x4HDIVN9AYwhWfn7/GYAW1SfEQBeUiFNkwBMBzAYxqYUSJ4DYI2IHPJFKZJMDkv46Pkz7/M5geeO7L3YmrlznY7l17QUWr3RDwC5ZZjx3pryQ4UO33b7A2zE1LMDktqG8R2TVKuJqlwVBQBE5Hm1C3M3gCcBPELyWpKfk3zoKOim0bRoAv3sE/okJ/aKD6vKxqwf36zbkp5TXHqbCWo1B34AYCO5AcZ304oa+r4N4HuVHM6b4wH8rlzMH4QRY19tf7WY8jSAxSqs4GXv8ypUqouPL3a/wlhk3QhjIWKNam8DYJHSdRqAf1XSrRxGzP5rSrefYHgJvAngSpIrYMTK17aLPgbVGP0iskcdVuzsL4OxY59bh/uaCeBekmtJdgJwKYBrlK6bYXiXNRoFWUX//eGthWlup2+7/XZ/Gy58+JzEyMTwF01STaNp1YhBkfpoVz+VX6IFQKjyPA2BseDoguGBGgjAH4BHLXTeAeAFX/UKDwi9+Lweo7u2i/DZYQCP/vxqmo7l17Qk6GtZnJZCqD/H33GS37tPnhoQ4ausi2eVZH7zp+vCEqdUG5PvDckUAHNVUirv9kUA7hGRP6q4ZjCAx0TkDPX5XwAgIs969ekHY6X1dgDfi8jJJGcCeFhEtjfo5jSaVg7JsNjQ4I13nTa8nd1W2wZszRzMzce0X1d/k1Nc0qjGk6Z6SA4DcJmI3HCsdWkIJP0B/Coi1SZ9bc6ERofccvYdp00ZcfmQoNp718wrl76d9ufyHae0ktwZGk2johZMVwPoDOANEbm/0vlQGMlAu8HwGJooIvNU7qlPAMQDuB9ATwD5IjLdR31CYoMjD3112Vuh7X00+tcc2iI3zXl01oH8tAk+CdJomhB6p19RVI4vP97oPJRb6vsiyJtjA2MTQviucmNqLFYB6EKygxrnYhhfrt48CeARGCuwFdaJB161rDUaTf2ICAp48/wTerXx1eAHgK/WbE7NLSm92QS1NA1ERJY1V4MfAETE0VINfgAoyin+34L3lqY5Hb6npLnsmfEJUW0ipuukfhqN74iIW0T6AkgGMJBHVrA6A8A6GOVU+wJ4nWSYiOSLyFj1vbUGwNkAZpN8h+QstalVb+IiI944bdgJgZM+v8P51spPyt2ehnkIiQge/fm/qQcL0luLB56mlaCNfoWISHqR3PPkEkddXB5rJCqQeHJkQNvkMD5dW1+SnwL4DcBxJA+QvIbk+SQPwIh3mkdyvuqbRPI7pa8LwC0wkk9tBfC5d0ywSo6ySkQOiUgegN9UJmgRkfW+3qNG0xqxWiwnJkeGn941PsZni//PtEx3XknptyJywAzdNJqWiIg4S/JLn/r53SWVKx/Um9j20Rh0Qf/uoTEh15mhm0ajAdQ75iIcWYnqKgBfqlCAHTBCoLpV6vMIjPCrSTC8Bq6GUWWkXlit1gFd27cbc9NF59s+evYB++qSNXLGtKtd6w5trfdO3sJdK1zpRVlfikhafa/1hmRR7b3qLXMSyQcrtY0gObcRxlrEGsqGmzzWufQqPa5pHLR7vxckmRLBtb9fG9wnNti39RARwYjpJWlL9rq1K6FG0wIgaYsMDtx4+6ih3UIC/H2S5fZ48PKPS/enFxQdX4eScxpNq4akJTo5cu19s2/uHR4X5pMst8uNZ8977dCBLYcGishBk1TUaFoVJGNhVDbJo1EW+kcAU0RkrleftwCki8hjJONh7Or3qSifSrILgKdEZCLJ2wGUAvgUwI8iUufdfpK2hOioje88eG+3SK88O7sPpuLxNz8s7x3TXZ487Q7/MP/a83h6xIPT37/qwJ9Zu3uq5KUNhmSRiJiaPJTkdBjVuFZ7tY2AEQp8tsljLUI1IcYNlGdTG5aaY4Te6fdCRORQodx+/8+ObF9lkcS08wIT2ofzU+1KqNE0f8IC/B8Z1a1ze18NfgBYsXNfcbGj/BVt8Gs0tSMintzU/Ks+feTrDF9lWW1WXP2fSUmRSRFf6LlZo2kwiQAWqqSsqwD8JCJzSd5AsiJc6kkAQ5SX6QIA91cY/IqnAVQkl/4UwGQYyV3rlXAzNjLimclnj2kXWSmxboc2iZj29P1+iT2C7WdOv8b15eYfnbVtdM5Y901JbmnBm74a/N6QDCG5gOQakhtJnqfa7yN5mzp+heQv6ngUyY+rkEMYYRJrKp/z6hNM8n2Sq1QC1oqxglQy7w0kPyO5smIXn+RbJP9gNaUXqxjjOZJblKwXVVssydlq3FUkh6r2x0i+TfJHAB+qcXt6yVpEsj/JySRfV23xJL+iUepxPckhqv0yGmUi15H8H0mr+plGo/zjRpItvvSxL2ijvxIOlyxesMu18veDbp9dIDpEWnBdf78u8cG80QzdNJqWivriXluVixrJe9WX/Dr1xe4mGcVGrvVbSYdesaHB153UsW2gr7JKy51Y/Nfug0WO8tfM0E2jaQ24Xe41ezceWLJz9R6Pr7KSusRj2MUDe4bGhOh8GhpNAxCRDSLST0R6i0gvEXlCtU8Vkanq+JCInC4ix6s+H1eSMaEiqbSIZIjIEBHpqUqc1gmr1TqgY5vEK8cOG1xtrqpJZ4yyvP34XbYZ27/0nD/jJuee3KodfHJL8/HWyk/3ZxRn+1xFoBJlAM4XkRMAjIRRupAwKqoMV30GAAghaQcwDMDSKuT0A7Beal65eBDALyJyohrrBZLBAG6CUS63N4zFmP7e16j8Cr0BnEKyd3XCaZS8PR9ATyWronrOfwG8osYdD+Bdr8v6AzhPRC6BURFmgpKVCCDJ22tB8SqAxarU4wkANpPsDqPSzVCVR8INo5pMXxjlynuJyPEAPqjh2bR6tNFfBfsKZPI135QedPpu9+O+oX6hccH8F8k4E1TTaFoqt8PITXEEIvKCKkHZF0bJs8UikoNGrPXrDUm/qODAzy8d1C/ejI3BeRu25RQ7HLf56uZGMoXkpiraGxSH573SrtE0RXIP5d3wyYNfHvK4fbb7ceZNp4ZFJoT/i2Q7E1TTaDRHGZLBCVGRMx++5sq42ubmkKBAvHzvTf6XTzzVfumsu5zPLprqcLjK/9Hn0Z9fzUoryry2EVzQCeAZ5RXxM4xSrvEwchj0p1HlwAEjv9cAGAsBVRn9YwB8X8tYpwN4gEaZ2EUwSsC2g7GQMBMARGQTgA1e10wguQbAWhiVFHrUIL8AxiLGuyQvAFCi2kfDSNS4DkZS8TB1XwDwjYiUquPPAVxUMS6AL6oY41QAbyld3cojchSMxYNVaoxRADoC2AWgI8nXSI5R+mmqQRv9VSAimRnF8syUX8t9/uOxWYhp4wLbtAundiXUaKqAZDKAsfjnynB1TILhBgg0Yq1fb0IDAmac3LVDp7DAAJ9lHcjNl21pGX+UOV3zTVBNo2lViEh2YU7xfxd//Fuxr7IsVot289domjFxkRHv3XXpxHYRoXUPmx/Q4zh8/Ny/7JlBqZbTP7jKtWzPag8ArEvdKr8f2PBbucu5rBFUvRRALID+avMiHUCAiDgB7IGR8HA5DEN/JIBOqHoT5HQYuRNqggDGV2yUiEg7Edmq2o/sTHYAcA+AUWrnfh6MhYIqUQsiAwHMBjAOwA/qlAXAYK9x24hIoTpX7HX9QQDZyptgItRCRB0ggOle8o8TkcdEJBdAHxgLHDejbu+RrRZt9FdDRrFMfXdN+V+7c33fUTgh0cqbT/TrlxT6z4ybGo0GAPAfAPfBKCdZLSSDYKx0V7j+fQKjJNAPAB6D4b72oYiUVCmgAfjbA0+NDutw2pK/9lnW7j3oU80wj0fw+ar1h/JKyq4wSz8ANpLTVWzdLPWM/qa6WD2SJ5JcruLlfvdaka84P5bkbyRjTNRVo/GZgszCV35+d8n+olyf7X4kdIrDiMsHdw+LDb3bBNU0Gs1RIiw4eNyJPbuPHnR8D3t9r7VYLLj90vH2Kfdda3ti2X+dV89+oPy+759PO1iQfm1j6AogHECGiDhJjgTQ3uvcEhhG9xIYRv8NANZVduEnGQ7AJiK15RybD+DWioVMkv1U+zIcdqvvAeB41R4GwyjPp5Fs8cyahJMMARAuIt/B2GTpq079CKOiWEW/vpWv9WImjHe+cBHZWMX5BQBuVHKsJMNU24UVXtMqxLO9ekexqJCQh2GEA2iqQRv91SAisjdfLrni69I0Myoc3DvEL7R7jOUWm4X9a++t0bQOSJ4NYzKsHNNVFecA+FW59kMaqdavl25REcExH9wy9vnwf0/41LZ8d5Hng2Wry8ucDbP9l2zfXVhQ6nhBRNJ90asSxwF4W63QF8BY+PDmiFg9kn4APgNwu4qZGw0jazIAgOT5AB4AcFalpEsazTFHRNx56QXXffHEt6b8bZ72f6eExraLupvk8bX31mg0xxqScdHhYa/edclF0b7ISYyJxjuP3+OPKIcntShzpoj4nCi0GmYAGEDyDxi7/tu8zi2FkRTxN/VuUIaqXftPgxEaUBtPArAD2KDC/55U7W8CiFUhBvfDcO/PF6OE91oAmwG8D+DXWuSHApir5CwGUJE47zZ1jxtIboGxeFEdswBcDMPVvypuBzCSRgLI1TDyB2yBkfTxRzX2TzCeWxsAi5TL/zQYIaCaatAl+2qhTZhlynOj/G+9vI+fzwm8sks8OOnd4l07c6WfmZlBNZrmCslnAVwOwAXDpSwMRl3fy6ro+xWAL0TkkyrOvQLgawBdAVhheAHMEZGRDdSLkcGxC645/dFTUuK6/704unDjLPeiDR/JhAG92Cku2lpXeXklpXjjl9/W55aUniAivrsPGTqmAFgiIu3U51NhTLwRUGV2aGRRvg6ADcYEeSuMyX2qiAytJG8yjNwIhQBO199RmqZMVJvIede9cdmYDn3b+bx5UZBZiOfHv7E9a39OPxHx3YVAo9E0CiQZHxW56NmbrxvetX1bn8NyMnPzcONzL29My87pJyJuM3RsDEi+C+BdEVnRwOutAOwiUkayE4yd864iUl7LpZoWhN7pr4VDhfLwo4sc+3NKfV8ciQ6y4P3zAtu3DeNnOoZQowFE5F8ikiwiKTBWfn+pxuAPB3AKgDlVnOsCIwPsYgBBMMIEBDXEpdVGWFDUbYO7nXmCt8EPACOPv9B6+7lv275at8v91ZrNDlcdE4p9vmpDem5J6aVmGfxeVP5i+vtzDbF6rOK6CnbBWMnvarKeGo2p5B7Ku2L6vZ8fdDp8iroBAITFhuLSZ8Z3iEwMP2JBUaPRNB1iIsLvP+fkoX3NMPgB4NlpM9LTsnMubcoGPwCIyLUNNfgVQQCWkVwP4CsAN2qDv/Whjf5aEJHyg4Vy9Y3zSjPNkHdye5v1ij72wQkhvMsMeRpNS4T/rPULGCVifqxmF86UWr8V2G1+J8aGtfnXmP6Xh1d1Pio0Hg9N/NTP5n+85T8//+rKKCiqUd7GA6nl6QVFs0Rkc0P0qYV2XmEMk2DE7VVQXazeNgBJJE8EAJKhKgkiAOwFcAGMero9odE0UUQkuzCr6O7Zz8zLMUOey+my2bJLxsbYbLrOs0bTBAnw9xvWsU3inVeOPSPMDHlL1qwv33Mo9atq4spbFCJSKCIDRKSPGGUWa6sCoGmBaPf+OtIu3DJz+rjAC0d2sNXZpbc6PCIY/WFJxvL97vPKXD6t3Gk0GhMhmRgXnrzinvNfbxfkH1pr/z0Z2/DBT/92DumU5Dm5awf/yg48peVO/OenZbuyi0t6eZWsMUvXFADfwUgANATAdhihEt/hsHv/NAAnwdjBd8AonTNNGfyvwah+UAojrv9CAANE5BaV/GcGgHNEZKeZems0ZhKVFDnv2tcuGdOpf0qDNzE+//dsZ+rX6/laYhvb/amH0teVlp7pEllrpp4ajabhkIxvFx/3+9sP3tsuJMjnaFvkFxXh/556YeehrOzjzZ6bNZqmijb66wjJ8G4xlg1rrw9uF2Dz3asot1Rw0rvF+7bneE5sxOQhGo2mjpD0jwyJ+/3ms57rnRDZvvYLFC6PC+/9+KCjqHiX5fLB/ezepf2mL1+duS0146Jyl3txY+is0bR2SEbFd4xd9+Dc29v6BfrV69qSwjK8Pva/jv6FbjwUF+9vJ5HrcmHSvr279zmd/VU5KI1GcwwhaY+Pivzt+dtu6N8puY3P8kQE9/z3rYw12/46u9zpXGWCihpNs0C799cREcnPLJYHHlnoyDNDXmQg8cWEwLZtwzjXy7VWo9EcA0gyIjj28wlDbzuuPgY/ANgsNlw/Zor/qf1utb/+y0rXhv2pLgBYvz/VsS8772tt8Gs0jYeI5BRkFt76xZPf1svN/6+Vu/DioGdct7n9rY/HJ/jblZdOpM2G5xOT2ifYbN+q5FcajeYYEhcZ8d71F5zbwwyDHwDmLv2tZNeBg9O1wa9pbWijvx5kl8rMzzY7161OdZviHtEn3sonRvr3Sg7lW2bI02g0DSM8KObhId3PGnF8ymD/hsro1/FkPHDhDNviHbnuab+uLp+7fuu+/NKyW83UU6PRHElJQemcTYv/XLr99111SsY159l5rm8nT3NNi0+ynR4adsSie+/AQMutMbH9Emy2D8zXFiB5HMl1Xj8FJO+o1Oc8Vf5qHck/SA5T7bEkl5HcRHKcV/85JJMaQ1+N5lgRExF+8ykn9D379EEn+u7TD+BgZhamz/the2Ze/r/NkKfRNCe00V8PRET25ctFl84u3V/oMCcsYnJfv8CzutouSAy13GKKQI1GUy+C/EPPbh/X9dYzT7jc5+RAQQEhuPv8t/0zi6wleSWl/yciDjN01Gg0NZN7KG/yRw/MOuAoqT4hdXlJOV4+/WWHdeZa9+dt29mS/aoPBzg/PDxobFjYOfF2u+l1n0XkTxHpKyJ9AfQHUAIjo7Y3CwD0UX2uBvCuap8EYDqAwTBKbILkOQDWiMghs3XVaI4VAf5+Q9olxD9yy8QLIs2Q53K78ej/3k9Ny865QERcZsjUaJoT2uivJyKSdaDAc9XlX5VmmpUP4a2xAVEDkqyPxARZxpsiUKPR1AmSXaND4/83edRDMWZV0fxl/ReFZU7Hix6jhKBGozkKiEheQVbRTTP+PTu7qvN7NuzHcwOfck0upOX5xCR/f0vtrz93xcRGHB8QcFekzXa+6QofZhSAnSKy17tRRIrk8EtGMA6X2XTCSMDpD8CjwgPvAPBCI+qoacaQDCD5O8n1JDeTfLyKPuEkv/Xqc5VqPyaeJSQ7J8XEfPbMzf8XZ63D/9W68MG33+dl5OQ+JSK7TBGo0TQztNHfAIrK5Zc/Drk/fm+ts8QMeRYSsy4KjO0WY3kj1J/DzZCp0WhqhmR4dGjivOvHPJ3kZ2uwV/8/OJC1QxZv/npDfknWM6YI1Gg0daa0oPS7v1bu+nLl12v+kY17/hsLXJ9NfNv1dmyibVx4uL2u8kjipcSkmLZ2+5s2sq/pChtcDKPUaFXjn09yG4B5MHb7AeATAGcA+AHAYwBuAvChiJjyPqJpkTgAnCoifQD0BTCG5KBKfW4GsEX1GQHgJZJ+OAaeJSTj2sTGzH/pjpuSQ4OCTJG5dfdezw/LV67JKSjU4bSaVos2+hvIwUK598kljq1bM+sUQlgr/jbiu0uD4jtFWmbq+tgaTeNC0i8iOPaHyaP+3SEyJNYUmeXOMkxb8PSB3KKMC0SXRdFojgl5afk3z3nxh7/Sd2fCVe7Ca+e95sj/33LPF23b2zr6139xz89iwdQ2yQlt7X5zSJqTSUyhjKpzAXxR1XkR+UpEugEYB+BJ1ZYvImNFZACANQDOBjCb5DskZ5EcbKaOmuaPGBSpj3b1U3mOEgChNFzeQgDkAHDhKHuWkAxJiI5a8Owt13eMizLFqx+lDgeeeu/DA+k5uRP03KxpzeiSfT5AMqlnrGXlqv8LTg60m+ManF7kwcnTSvb9le0ZJiL7TRGq0Wj+hqQ1Ijhm3oVDbhnRt+Nwc7b4AUxb8Ez2pr2/XVlaXjzPLJkajab+kGyX0DlupSWjKPrqgFCZFBHh52v4zp7ycly7f9/WQy7XQC8Dylc9zwNws4icXoe+uwGcKCJZXm2vAPgaQFcAVhheAHNEZKQZ+mlaDqoSxWoAnQG8ISL3VzofCuAbAN0AhAKYKCLzSIbD+LuKB3A/gJ4A8kVkeiPoaI+Lilz8yLVXDuzbtbMplTNEBA+++W7Wmm1/XVZYUjLfDJkaTXNF7/T7gIgcOljouXHynNIssxZP4kMs+P7SoHYdIriAZLQpQjUaDYCK0nwxM87sf8UwMw3+ZVu+Ld6Ruv5zbfBrNMceEdmXuz/n8a5ull4SGemzwQ8AKX5+eC4xqWuizfYLSVMyicNwna7Otb+z2nUFyRMA+AHI9jrfBUCSGLlDggB4YOzWBpikm6YFISJulRQyGcBAkr0qdTkDwDoASTBCAF4nGXa0PEtIMjYy4stbJ1zQzyyDHwC++HlR0dbde97TBr9Go41+n8ktlbnL97unv7nKacrKPwB0jLRg9sSgzu3CuYBksFlyNZrWTkRwzGsn9xx35tDuY037f7UzdaP7hzUz1uYVZ+nyfBpNE6GszDl1m8Px0ey8PNNi3QcEBVkfT0jom2Cz/UzSp0VDkkEATgPwpVfbDSRvUB/HA9hEch2AN2DsvHrvLjwN4CF1/CmAyQBWAHjRF700LRsRyQOwCMCYSqeuAvClCgXYAWA3jF1/bx6B8Xc3CYbXwNUATMlfExsZ8dbFp586YuSAfqYtWm3auds988cFq3V5Po3GQBv9JnCgQO6b8qtj7coDbo9ZMvslWPn+eYE92obxB5J1Tjyk0WiqJjIk9okTOo245PR+k3wuzVdBTmE6Plz43K684syxImJOgg+NRmMKaS7X7W9mZ23cVlZmWhzjsOAQ+4Nx8QMSbLbvfZmbRaRERKJFJN+rbaqITFXHU0SkpyrtN1hEllW6foKIbFfHGSIyRPWf3VCdNC0TlYE/Qh0HAhgNYFulbvtgVJIAyXgAxwHY5SWj0TxL4iIjHx05oN+EiaedGuKrrApyCwrxxLvT92bk5o0TEdPezTWa5ow2+k1ARDz7C+Tcy74q2ZNZbN53y6gONvsLpwUMSA7jLJrhn6jRtFIigmMf7NVu0M3nD7rBnMxAMBL3Tf3hoUPZhWlniUiBWXI1Go05iIg71eU6565Dh/blu81bkxsVGup3T2zc4ASbbY6KldZomjKJABaS3ABgFYCfRGRuJc+SJwEMIbkRwAIA93vnj0AjeZbERUU+NKRPr9tvnXCBaXOz0+XCfa9NTTuUmTVOeTZoNBroRH6mYreyz8Ak6w+LrwpKsFnMs9H/s8JR9OLy8tkHC+UqnXlUo6kfEcExd3dvO+Dfl55yb5RZa2cigv/98FDmzrSNV5Q4in4wRahGo2kU/C2WAT38A76d1q5dgp+J6+df5eeXvJaVOT/N5bpQ7yZqNPUjNjLigcHH97z3vismmTY3A8BT732YvWLjlttyCws/MU2oRtMCaNY7/SQjSN7k9XkEybnHSh+nW9bvyvM8cst3Zblmyr1jkH/IPUP8xieHcbYql6LRaOpAeFD0LV2S+v7rklPuMfWlYt4f0/P3Z+34rzb4NZqmj8Pj+WOvs/y2+1MPmZZ0FwDODw8PujYq+rQEm+0j7Y2n0dSdEH+/KREhIY+YbfDP/mVx8eptf32sDX6N5kiatdEPIALATbV1qitmGNSphZ535m13ffjMUoep7r53DPIPeWaU/5jkMP5IUmfn1WhqISI45u7OSb0fveLUB6ItNO+rbv3uZeUr/vzhl/ySLFMSGGk0msYnx+X6Yl1p6euvZ2fl19677lwSGRkyOTLqnASb7Qvt6q/R1E5EUOCjPdvEX+t2lls++u5Hh1lyV2/90zXj+59WZebm3WWWTI2mJdGsjH6Sd5HcpH7uAPAcgE4k15F8QXULUWVEtpGc4VXypj/JxSRXk5xPMlG1LyL5DMnFAG43Q88DBXLnm6vKf5i2rty0rMEAcHlvv8C3xgYMbRvGJaqmqkajqQRJRoTEvtI7ZeiDk0c9GGOmwZ+aswezlr+xJa84c5IOtdFomhfpLtcTX+bnfz+3IL/UTLlXREWF3hYTe2aCzfaDr1n9NZqWTERQ4LO92sTfftGA3lE3Dh/g/9Ovv+Hj7303/LfvPyDPfPDxlozcvLN1qI1GUzXNxugn2R9GSZGTAAwC8H8ApgDYqbLb3qu69gNwB4AeADoCGKoy7L4G4EIR6Q/gfRhJSSqIEJFTROQlM3QVETlYKJc8vNCx4rvtznIzZFZwdle734wLAk9oF87lJGPMlK3RNHdIWiOCYz4d3uPcqycOvz3STIO/qCwf7/z46N7coowxImLa7oRGozk6iIiku1yXv5yZuW5taYmp1TbGhYcHPRQfPzzBZltM0rQs5BpNS4AkI4ICX+vbLun6cf16RpKExWLBjSef6D9/6XLO+OGnBs+padk5ePCNd3al5+SOFpFiM/WuCyTHkezRgOtGkBxSh37nknygYdr5RuUw6mr6/I/k0EbU4e/Q7WP5LFoCzcboBzAMwFciUiwiRTBq2w6vot/vInJArfStA5ACo/RILwA/qZq3DwFI9rrmM7OVFRH3gQIZe+Pcso0rDrhMfbkY3t5mnXNxUM8OEVxOMrn2KzSalg/JgIjg2PljB1x1zpgTLjWtLB9gZOp/67t/p2UVHLpARNLNlK3RaI4eIuJKc7nG3JeaumN/ualr8jg1JNR/SmLSgCSb7VeSUaYK12iaKST9wgMDvj65a4crz+nTPdI7hl8Z/n7fL/mVn/7wc70N//yiItz9nzf3H8rKPk1EMk1VvO6Mg7HRWGdUOPEIALUa/SLyjYg81yDNfCcCtYdRnwSjkkOjc4yfRbOnORn9dc304f2l4QZgU9duVh4BfUXkeBE53atfo6wMikjZvgIZNWlW6fZtWeaW8O6bYOWPlwd36RJlWUayq6nCNZpmBsnwyODYpRcPv2P44G5jgsyU7Xa7MPWHBzMy8vdPdnvca8yUrdFojj4iUnDQ6Tz9xoMH9ueZWMoPAE4MCrK+2ib5+DZ2+28k25gqXKNpZpAMiwgMWHJe3x6nn3JcxyrDUi0WC246+US/uYuXcuaPv9TZ8HeUl+Pu/7yZeiA94zwR2W2izpeR/F2FDv+vIlcHySKST5NcT3IFyXi1U38ugBdU/07q5wcVTryUZDd1/TSSL5NcCGOz8QYAd6rrhpM8h+RKkmtJ/kwyXl03meTrXjJeJbmc5C6SF6r2ESqE+XOSf5F8juSl6j42kuyk+sWSnE1ylfoZqtofI/m+CnneRfI29TiqCqP2flbdAfwlIu5K7dNIvkVyoZJ3ipK/leQ0r36nk/yN5BqSX1R4SZEco8K0lwG4wKu/97Oo8nlpqqc5Gf1LAIwjGUQyGMD5AH4FUJfY9j8BxJIcDAAk7SR7Np6qhxGR/D35cuo5n5bsPlhgbphR5ygLFl4Z1L5nrGWB3cp+pgrXaJoJJBOiQuJ/u/q0R/r1aj/Iz0zZHvHgvZ8fzzqUs/uOEkfRfDNlazSaY4eI7DvgdJ5/7f59qUUmG/49AgL4TnLbru3sdr0or6kVklZluBxRfYoGr5LcQXIDyRNUeyzJZTRyXI3z6j+HZNJRVL9aSLaJDApcedngEwb0bptYYwJqi8WCm08Z6PftwsX8/KeFtRr+LrcbD7z+dsb+9IxrXG73WhN17g5gIoChItIXxubhpep0MIAVItIHhk3yfyKyHMA3AO5Vm4o7AbwN4FYVTnwPgDe9hugKYLSIjAcwFcAr6rqlAJYBGCQi/QDMBHBfNWomwvB+PhuGUV5BHxi5yY4HcDmAriIyEMC7AG5Vff6rxjwRwHh1roJuAM4AMBDAozRCox/AkWHU3pwJoLoqRpEATgVwJ4BvAbwCoCeA40n2pRGi/JB6HicA+APAXTSSlb8D4BwYHt0J1civ6/PSKJqN0S8iawBMA/A7gJUA3hWR1QB+VV96R6xAeV1bDuBCAFNIrofh9l+rS41ZiEjqjhw544yPSw7klpqb+6tNmAVLrgpO7h1vmRfix5GmCtdomjgkO8eEJS2/6axnu3eI72Fq5mwRwSeLX8zZm/HnE4WleZ+aKVuj0Rx7HB7P6l3l5Rdde2B/WonH3EX5FD8/TG/bLuU4f/+FIVbraaYK17Q0bgewtZpzZwLoon6uA/CWap8EYDqAwQDuBYydTwBrRORQo2pbB0j2ig0J/vW6UwZ2S4mJrNPcbLFYcOMpA/2+/mURZy1YVK3hLyJ45oOPs3ccOPhgUUnp9+ZpDQAYBaA/gFU0woFHwcgPBgDlACoWZlbDCB/+B2qnegiAL9T1/4NhpFfwReVdcS+SAcwnuRHG77S6zcmvRcQjIlsAeO9urxKRVJVzaCeAH1X7Ri9dRwN4Xen2DYAwHk4MPk9EHCKSBSCjkuzqOAPVG/3fqoTHGwGki8hGFXq9WekzCEZYxK9KnysBtIex+LBbRLar6z+uRn5dn5dG0WyMfgAQkZdFpJf6+Y9qu0R9vldEFonI2V79bxGRaep4nYicLCJ9RKSniLyj2keIyB9HQfftO3I8F4yZUZxW6jTX8I8KJBZPDk48Kdk6s02o5Q5S1wvWtHz87AFDEyLbL7z9nJc6JES2N13+Vyum5m07sPqNvOKs10wXrtFomgSlHs+vO8vLL7v+wP50h8mGf7zdjhnt2if1CwycEWez32GqcE2LgEZeprH4546rN+cB+FAMVgCIoFF9ygkgEIA/AA+NGPE7AFS7AXa0CLDbR7eJCJt/06mD28eG1i+npc1iwU2nDPT78ueFnP3LkioN/6mzv8lfu+2vt3LyC6p7Zr5AANO9woGPE5HH1DmnV9WeivDhylgA5Hld31dEunudrymc+DUAr4vI8QCuB1Cdd4T3c2E17R6vzx4vXS0ABnvp1kZECqu4vrr7OzwwGQQjEXp1i0ze41fWrSL0+icvXXqIyDWqT10Mpbo+L42iWRn9zZ0yl6z6M8tz9XkzSzJcHnMN/xA/4qfLg+Ku6Gt/tG0YvyIZaOoAmmYByduV58tmGmUtq+t3Ikm3VzxYk3cV9CY8OObOjvE9vrz7vFeTI0PiTJf/7e/v56/ZuXh6blHmI6YL12g0TYoit3vBdofj2hsPHsgoN7kSZ5DFgqltkmPPDAt9JNFun66MM42mgv/AcEuubsWpDYD9Xp8PqLZPcHiX9TEYydY+FBFTS0XXl/DAgDvbR0fMuOnUwUmhAQ2rXllh+M/6cQG/XLjkH9k23/l6bt6PK1d9mJGb97ApCh/JAgAXkowDAJJRJGvbVSiECjUWkQIAu0lepK4nyT61XacIB3BQHV/ZQP1r40cAt1R8INm3lv6VdfRmJICFPuiyAkaFtc5KlyAVDrUNQIeKPAQwvFqq4mg8rxaFNvqPMnll8v3GDM8Dl39Vmm12mW8LiWdHBURMPTvgrJQIribZsfarNC0Fkr1glLIcCCO262ySXaroZ4VR7tI7Rr1JuwpWQNI/MiTu84FdRj9y89jn4wL9za+M9cPqj/NX/jX/07zizDtNF67RaJok+W733D8djltuPXgg09UIc/MDcfGRt8fEXpRgsy0nGW3qAJpmCcmzAWSoUNVqu1XRJiKSLyJjRWQAgDUw4rtnk3yH5KyKHFZHC5L+EUGBs/qnJD9y7ckD4/xtvq1t2SwW3DxioN8X83/G14uWlgPA+998l//drys+yczNu90UpatAucw/BOBHkhsA/IR/uudXxUwA96q8DJ1g5AC4RoUTb4bhrVEV3wI4XyXJGw5j8eYLkksBZPl+N1VyG4ABKj/EFhjJBKtFRLJRfRh1TfH8taKqLUwG8Kl61isAdBORMhihLPNUIr+91Yh4DI3/vFoUNNvw1NSNNmGWu4a1tf5rxvjAGJvFfG/8PXkejJtZcmhfvufmnFL52vQBNE0OtbJ8hohcqz4/DMAhIs9X6ncHDNfAEwHMFZFZJG8EYIexe/AVjBXc+QDOOdY7BxWQ7BwZEvf1+ME3de7bcXjDthBq4ed1nxUs2vTl7LzirGtEfzlqNK2OGJvtyr6BgS/+J6lNjLURIuU2l5XJ3YcO7jnodI5ziWwwfQBNs4HkszASrrlguCaHAfhSRC7z6vM/AItE5FP1+U8AI0Qk1avPKwC+hpEkzgpjHp8jIkclzxPJNhFBgd+P69fjuF5tEkxNpuvyePDGopXlbRIS3DsPHvowMzfvRj03Nw1IrgFwkog4j7Uumrqhd/qPEQcLPC8v2uu+d+wnJRllLvO/v1IiLFhxbXDSmM62d9qGW15Vu7uals0mACeTjFaxVmcBaOvdgUYJqfNhZI31pkm6ClYQYrWe1t5uX+xntR/Xve2ARjH4F238smjRpq++1Qa/RtN6yXK5pm8oLX303tRD2e5G+BroGRDAGe3ad+gdEPhjrM12u87B03oRkX+JSLKIpAC4GMAv3ga/4hsAVyg38UEA8isZ/F0AJInIYgBBMMIEBEcpvjnQzz4mPixkxXUnDzzebIMfMHb8u8ZGlm7cvn2eNvibFiJygjb4mxfa6D+GpBd5pv1xyPN/oz8sSSt0mP89FmAjPhkfFPPQyf5Xtw3jsubgUkijjmcGyU1ebVEkfyK5Xf0bWcV1bWnUA92q4tlv9zo3RbkyfejVdrl3n5aAiGyF4bb/EwzjfT2MHQRv/gPg/srZY5uaq2AFJC0JdvsLg4OCPpmd0iHpKn833/vxsXIz530Rwbw/puX/vP6zL/OKM6/QLxUaTesmw+V6c1VJyb9vPnggs9zk5H4AEG2z4cN27eIvjIh4PMFmm08y3PRBGgmSEWpO2Kbm28GVznejUXfbQfIer/ZmlTfmWELyBpIVbtffAdgFYAeMMmY3Ver+NAx3dAD4FIa79AoALzayjpaIoMAXu8THfHj76GHJcWHmh9qJCOZt2Jr3x56D04sdzgl6btZofEO79zcBQv15cucoy8yfLg9KjAlqnHWY1alumTSrdO++fM+EMpesapRBTIDkyQCKYOwy91JtzwPIEZHnSD4AIFJE7q90XSKARBFZQ6P8yGoA42Ak+ZgrIsNJzoBR03QHjLIrY1ryKiXJZwAcEJE3vdp243CMYAyAEgDXiRwOATnWroJeesQk2GzfXBsVffykiIiQig2xG9OyHKFdzsaY/pf7vOPvEQ9mLnklZ8v+3/+XV5z1oH6p0Gg0FURabeM7+fu9MTW5bXywpXHm5jUlJe5/p6XuT3W5JpV7PCsaZRATITkdwFIReZekH4AgEcnzOh8Ho+zWOAC5IvKiar8NQCmM+OcfRGSoyhtzgog8fpRvQ+MDJBMjggK+PLVb5+MHd2oX3BjOKiKCOeu25G48kPZuXkmprr+u0ZiA3ulvAhQ6ZMmmDM+ZJ39QcuBAgfm7CgDQP9HKFdcGpwxua/02MdRyZ1N1KRSRJQByKjWfByPJHNS/46q4LlVE1qjjQhg1b9vAcHXzU/cbCCOW/V4Ar7ZEg5+HM862A3ABjJX/vxGRDiKSotwJZwG4qZLBf0xdBSsIt1rP7+Dnt+b1NsmDLomMDPH+c30jLsp/3dZv+NfBddXVuq0TTnc53pn/SOamvSsezS3K/LcZBj/JFG8vlUrnniA52tcx6qjHuyR71POa1eol3rttEckBtVx3hwonqfj8HcmIeims0TRBct2u2X86HJdM3rcvNc/t09dNtZwQFGT9rH1KykmBQXPi7fanSDbZ9zKSYQBOBvAeAIhIubfBr9oyRGQVjLnWmyZbYk5Td0L8/S5LCA9ddc3wgYOGdG7fKAa/xyP4fNWGnI0H0l7XBr9GYx5NdnJpbTjdsn5rlmfkyOnFu//KbpyXi6hAYsEVQfE3DvB7rF04l6r47uZAfEUMm/q3xhptJFMA9AOwUi0AzAawFsBuAPkAThSROY2q8bFjtsrI+i2Am0Ukt5KrYG0cE1fBCkhGJtnt344JDXt3dvuUtj0CAo54o7BYLPg4Icrv00VTJK84s0HjlJWX4LW596bvTNt8U35J9us+K14HROQREfn5KI11rcpCXCfU/5mDIlJeW98quAPGAlHF2GdVNgQ0muZKodv9yzZH2dlX7Nt7IMPVOOvE4VYr/pecHHdNVNTtiTbbryQTGmUg3+kIIBPABzQylb9LMriO1x7zvDEk95DcSCNb+h9VnI8k+ZUKB/ydRkUcHZoA49lEBgd+1z8l+dU7Rg9rkxheXRU33yh3ufHu0t8zt6Vl/juvpFSXzNVoTES79zcxSLZJieAvsyYEdemfaG203fjNGW5c9mXpodQieTK9WP7XlNyalQEy18u9P09EIrzO54rIEXH96lwIgMUAnhaRL6s4/y6ANwD0B3A6gA0i8pTpN6GpN2FW63nRNturT8UntDkhKKjWxJOLCwvxjCPAdff5b9hsVnudxykszcXr8+5PzSo4NKmsvGSxT0pXQv3tfg9gGYAhMMJLzhORUpLTcLhawnMAzoWRc+FHEblHnS8D0BNAPIC7RGSukvkRgIqX61tEZDnJETBenrMA9IIR0nKZiAjJRQDuEZE/SI4B8AyMUI0sERlVhd43wpgP3qzU7i3nLRgVHwIBzBKRR5XL7osA/lSyR5LcA2AAgJDqnkVDnq1Gcywh2bW93f7j/5Lbtm/nZ3q+sr/5s6wM96WmHsxyux7Ldbvfa2Jz8wCo2toispLkfwEUiMgRNdNJPgagqMK9v9K5SACfwfBGewVAJICXROS3RtZ/D4ABIlJleS8aJcmKRORxkt0AvCEio1p7aEKgn/3M0AD/qRNP7NMmJSay0ZJCF5U58O7SValZRcVXlZY759d+hUajqQ96p7+JISIH9+TJ4AtmlmxcvMdVOQmbafSMs2LVdcFJ1w+wP9cMdv3TVcx+Rex+RlWdSNph7OrPqMbg76cO/wJwhYhMANCLVdSy1xw9SEYk2e1zzgwNe392+5R2dTH4AeCU0FCcikLPp4tfqvPudFZBKl6Zc+e+g9k7Tzfb4PeiC4yXxZ4A8gCM9z5JMgpGBYWeItIbgPeiUwqAUwCMBTCVZACMv/fTROQEABMBvOrVvx+MnfYeMHbhhlYaKxZG8qfxItIHwEXV6DwGtdfbfVAleuwN4BSSvUXkVQCHAIysJudDjc9Co2kuiMhfe53O4dce2L99W1lZoxnixwUEYFZKSpuLIyJeTLTZlqlQrabCARh5Ylaqz7MAnNAAOY/A8CqbBGOx8moYC5PHmh4AFgCAiGwDkEIyHq00NIFkUGRQ4Cc9k+I/vOO0Ye0a0+DPKirGGwt/23cor2CMNvg1msZBG/1NEBHJ2VcgQy//qvSPb/50OhprHJuFeHxEQPi8S4KGBoVbt9vCbLc10XjCbwBcqY6vBHCEa76K2X8PwFYRebkaOU/CeNmww9j1BIyY9aBq+msamTCr9dwOfn7rX0hMGvtYQkJUYD2TZd0fE+VXlLpGftv2fa2G/4GsnfLa3Ht2ZOTvP1lEqoy7N4ndIrJOHa+GYch7UwBjR/9dkhfASKZYweci4hGR7TAyNneD8ff6DsmNAL6A8WJawe8ickBEPADWVTHWIABLRGQ3YHy3VFZWxfEni8iuWu5rAo26vGtheCPUJWdAbc9Co2k2iMj+A07nkJsPHli/sKiwIaEwdcJO4taY2PB3ktsO6RUQ8FuszXZfU5ibRSQNwH6Sx6mmUQDqHEYEHPO8MQLgR5W/5Loqzq+H4X0AkgNhJCRMRhMITTja+Ntso6KCgzaMH3D8hZNO6hvjb7M12lj7snPd/1u88s/MwuKhbo9nQ6MNpNG0co75JKKpGhEp2l8gI27+rmzp67+XFzemh99nW5wu/16h1pgzY56yR9tXk+zeaIPVAslPAfwG4DiSB0heAyPj/mkktwM4TX0GySSS36lLhwK4HMCpKl5vHcmzvOSOA7BKRA6peOPflBElIrL+aN2fxoBkRKLdPmdMaNj7s+qxu18VHyVG+/+06gMeyNpZ7X+Svw6udf1v/kObsgvTBovI3oaOVUe8F+rcAP7xtiQiLgADYXiljMM/d9gr34MAuBNAOoA+MNzmvX2LaxwLRqWG2r48hsNwwa8Wkh0A3ANglPJOmIe6vaTXpp9G06wQkaxUl2vwk+npP72bnV3QmHNzR39/zGzXPunaqOiHk2z2NV7G9rHkVgAzSG4A0BfAM955Y0gmkDwA4C4AD6l5PMzr+mOZN2ao8pg6E8DNNKoFefMcgEiS62Dc51oALmmiJW0bA5KxkcGBc3u3TZx552nDOnVPjKt77FwD2HQgzfHh8jVrcotLB4nIgcYcS6Np7egXsCaMiDhInjHlV8cLS/a6rpg+LjAm0G5umP+hAg9e2iro8GSSn8Xf4hd+Unjfg+8e/MUeZf/Cleu6T0TKTB2wFkRkUjWnjohDFpFDAM5Sx8twuBRdVXK/hlGGruLzPTCMGM1RhKQ10mq9qaOf372Pxyck9ffB2K8gwGLBO7Gh9ut+esx19wVv2YL8D9cLFhEs2vRl0YL1X/yRV5x5jogU+Tqer6i8E0Ei8h3JFTBKSFZwEY2SWB1guOv/CSAchkuth+SVOOylUhd+A/AGyQ4isptkVBW7/WNgxN7XRBiAYgD5yt31TACL1LlCAKEwcgtoNC0eESkjec6MvNwp28sdVz+VkBhtb6SCOBYSV0RFhYwKDe3zr9RDi+Lt9o8zXK5HjlVuDOW5U7mix1Sv82kwdseru36C13EGjHwfRwX1zgARySD5FYzF1yVe5wsAXAX87T24W/14Uzk04RMY3odHtaSt2ZC0Bvv7PZkYHnrFhBN7J7WNimjUCk8igqXb9xQt/nPXkvzSsvMbmERWo9HUA73T38QREc/+fM/dP+1yXX3Su8UHd+WaW9Lv5C/KHHGXJ9Hib/wp+EX7IeW+lITESxKv94vz22QNsl6gJj+NxieCLJbRyXb75uujop/5KqVDWzMM/gq6BATgxkAP353/iNMjxv8Rp6scHyx4KmvB+s//l1ecOaopGPyKUABz1U7ZYhg7+RX8qdq+B3CDWnR7E8CVaoGgKwzju06ISCaA6wB8SXI9jORZlRmhxqxJznoYu16bAbwP4Fev028D+J7kwrrqpdE0d0RE0pzO+5YVF992+b69admNl4IHANDGbsf0tu0S7o+Nu6293b410mq7Us/NdYdkMMnQimMYiXw3VeoTwcNlS6+FERpV4HW+SZS0NRs/u9/gxLg2Gzq0P+7Onm0SYhrb4He63fh4xdqsxX/umppfWnaONvg1mqODzt7fjCCZ0j6cc189M6DLucfZfU4f/Poqh/uhdD9X21vb+1d13l3mRua3mXn5K/P3ufJcN3ucnhpdgDWaqiDZNclmf29YcHCPO2Njo8KtjZYLCHemZzkk5TSc3Os8/6k/PHQopzD9luKygq8abUAT8c7ufxTHTAbwjoicebTG1GhaGjaydxu7/euXk9qkVFVm1GwcHg/ey8kp+Kogf2+a03mtS+T3xh6zuUOyI4CKucAG4BMReboiLEFEpio3/Q9hhCJtAXCNiOR6yfgcRkLT7STjYHgPhgN4RERmH727MQeSCfExie/07t7vpNuv/VdseGgELrhqmPO6Yf3tkcGBjTJmXkkpPlj2x6GcktKbShzlLbV0skbTJNFGfzODZEDbMH40oad99JTR/hFWS8PeL/LKPGjzvsPV/rHONmtwzUaYq8CFtC/Ssou3Fm91Zjmvl3rU/9a0XkhGJdhs/+no53faw/EJCe0bscxVBR6PB2ccynKW0JaeW5QxWkT+bPRBTeJYGP0ajcYcSEYn2mzf3R4Te/y54eGNYzFVIsvlwnMZ6ZlrS0tXp7pc/6djojV1gWREXEzCU9ERMefffcPDid079/r7RXLJyl/w/vuPl19/ykmmT9g7M7Ldn61avzOnuPRslaxWo9EcRbTR30xJCrXc3DnK8vCXEwPjY4LqH6XR98NSR/aYeEvESRF1TtJSnlGO1E9S08v2l610ZjtvEZH99R5Y0+IhaY+1Wu+JtNpu+ld8XNJJQcFHJYzII4L/ZWcXfJ6XuzLd7Z7ovUOj0Wg0jQ1JW4LN9mb/wKDzn0hIiKlvNZKGsq2sDI+np6WmuVyfpxvx/gW1X6VpbZAMjo2KezAsLOLym6+8O2Fg36G2qiJErr5znGNom3Bbj6R4U9zyPCL4ecv2gt937f8tr7TswiYUaqfRtCq00d+MsVt5QkoEZ824IKj9wDbWOr9dfL65HNdusZa3v69Dg1ZyS/eWIvXj1FRntnOeM8d5f1VlwDStD5K2cIvlijCr9d/XRkUnXRAeHmg9SiGn+W437jp0MGOHo/yVTLdriugvNo1Gc4wIt1rPjrXZ3nw5qU3bLv5VRs+ZjohgUXGR67+ZWWn5HvfH6S7X09q40gAASf+oiJg7Q0PCbvq/S26NHzH4NL+a0kFk52bi2tvPcd152lCb3cdwvBJHOT78bU1GRkHRSwVljhf03KzRHDu00d/MIRnVNozf3D/Uv89NJ9pDasvrU+byIOZ/Za7khzrZ7HXf5K+Sos1F7rSZaWmuQtc0V57rmZZcs1ZTPSQDo63Wm0MslpsmRUTGTYiICA44SjtcALCprNRz76FD+1JdrosdHs/KozawRqPRVAPJhESbbc7VUdE9L4mICD5aOfdEBD8XFTlfzcxIzyHn55aX36V3/lsnJG0RYZH/FxIcdt8VF16bMGbEeQHWOhrx/3n7aWfWrpWesb27NXjVam92rufTlev25ZWUTXS63TrvhEZzjNFGfwuApCU5jM8PTrZeWVtZv5EzSx1/nRTDqFOjTYnXEo8g//d8R+a3mRnuEvccV67rGRFJNUO2pmlDMjzOZnsg1GK55Jqo6PixYWH+jVW2qipcIng7O7tgdn7e+lSXa5z2ONFoNE0JkpY4m+2p4/z9r30hMSk2rBGTmFbmzoz08o7H9+LyXbvSs4uLvz6Qm/e4iOiymq0AkoERYVHXBweF3Hrh2Evizx8zMdhez9zPHo8H468e7rxmSD97dEhQva51uT34buO2vA0HUlfklZRdokPtNJqmgTb6WxCRgTw7McTyxvvnBSQPSrYdsdX6804nxv0GZ8pDHe1m7zqICIq3FXsy52SmlWeVb3RmOf8tImtMHUTTJCAZn2izPR5htY69KTomYWRIiM1ylCtH7XQ4cF/qoUMZLtcz2W73m9plUKPRNFUCLZah8Tbbx88kJrbtF2heqdLqKHC5cEVBnmvL44/ZLCQWbPvT8/A336Yeys9fuC8n5986H0/LhGRUbFTcA8HBoRMnnTc57oxTzg6or7Hvzco1v+L1t/7lvGnkoDq7habmF2LGirUHC8sc/yoqc3zU4ME1Go3pS1sO2gAANE9JREFUaKO/hUEyql04Pz63q23QC6cHRAbYDGPM5fEg+q0yZ8J9He1+cY2bRd2R5kDm3MzM4m3Fqe5C99Meh2e2iLgbdVBNo0OyQ5LN9lyC3T7stpjYhBMDAy1Hu0y0W+3uz8rP25zqck3UL6+aY4mZFRdIrgYwuDFrVpMsEpGQOvYdAaBcRJarzzcAKBGRD03SZRKAjiLytFfbZAADROSWKvovF5EhDRinWplHE5IRiTbbF2eGhQ24LTomwq8RQ6Duzkgvv/Dss3j10KH/MNZW7N4tD379TequrKzVe7KznwCwWi+YNn9I9kiIS3oiKiJm0FUTbkgY3P9kq1lz8/X3XOToHxdoPT45wVZTP49HsPDPnYW/7dy7Ma+k7CIROWSKAhqNxjS00d9CiQ6yTIgP5osfnBfY5qRkq2X816WOXztHIvacuKOTVQiAu9iNnIU5hblLc7M8ZZ4PXPmu/+rYwuYFSVsAeW6MzXZvRz+/9rfFxCb2CAg4Jrrscjhwr7G7/2y22/2GflnVHGvMMvpJpgB4VUTONUOvKuQTAAEU1MPofwxAkYi82Eg6TYdxz6u92ibDZAO9qRj9ShdGWK2XRVutzzyVkJjUJzDQdMu/yOXCpfl5ri2PP2qzVRNOsDU1Ff/9ZWHWz9v+zCl2OGakFRRMFZEMs3XRNB4krf5+/mdFRcY+0r1Tz3ZXTrg+rnPKcaaPk1eQi8k3n+m687ShNj9b1X9POcUl+Pi3tam5JaUvFpY5XtFzs0bTNNFGfwuGZHS7cM4Y1s466Os8a3CHxzvbaDm6O7MAIG5BwZoCZ+a8zHR3oXuxM9s5RUQ2HnVFNHWGZEqCzXZPoMVyznlh4ZEXhoeHRtlqXOhvNNwieCcnu+CLvLwtqS7XBL27r2ksSAYD+BxAMgArgCdF5DOSjwA4B0AggOUArhcR8Tb6SfYH8DKAEABZACaLSCrJ2wDcAMAFYIuIXFzFuDfCmI/frNS+B8AnAEYCsAO4DsCzADoDeEFEppIMATAHQKTq85CIzFELCd8DWAhgMIBxADaLSAjJGADfAngKwO8ApgJop4a9A8BBACsAuAFkArgVwCioRQCSiwCsVHpFALhGRJaSDAIwDUA3AFsBpAC4WUT+qHRfBLAOQF9vA0EZ6OcD8AfQAcAnIvK4OlekdH8CQMXiSCyAH0XkqkryrwLwLwCpAP4C4BCRW0jGVnGvvwHYpXTJU9fvADBURNLRCJCMTrTZpg8NDh78QFx8VJCJu/73ZqSXn3vWmbxu+LBaXbKdbjfmbdzoenXhooy92Tm7D+Xnv1jmdM4TEadpCmlMhWSP+NjEOwP8Ak4bPfysyAvOmhQWERbZqGO+Oe1F177Ni9zn9evxj00jEcHKXftLft66Y0deSel4EdnRqIpoNBqf0EZ/KyDYnze7Iv0eTLoyKS6kR8jRyyRUBaW7S5G9IDuj5K+SfI/T87Ur1/W2niiaBiRDwiyWSWFW642d/PwSr46Kjh8QGMij7cLvze5yB+49dOhQhss1Jcvtfk3vIGgaE5LjAYwRkf9Tn8NFJJ9kVEWiSJIfAfhcRL6tMPphGN2LAZwnIpkkJwI4Q0SuJnkIQAcRcZCMqDAsK407B8CdIrKrUvseAFNE5C2Sr8AwvIcCCIBhwMeRtAEIEpECZcyvANAFQHsYxuwQEVmh5BUB6ATgGxiLAz+R/ATAmyKyjGQ7APNFpHvlnX7vz8roXy0id5M8C8BdIjKa5D0AuojI9SR7wTDsB1Vh9J8A4A4RuaJS+2QYixq9AJQAWAVj8eSPyqEJJMMBLAVwVSVvgUQYCxL9AeTDWPRYq4z+6u71vwDWicgHJE8C8LSIjK78ezKbUKv17Gir9fWH4xPaDAkO9nlVtcjlwiVql7++pdYyCgrx/vLlhR+t/D2n2OFYuDcn50UR2eyrThrfIRkVER51VVBA0DU9j+sTfdHZl8X16HI8jtbc7PF4cNE1pzivHNTbHhsaDADILCzGZ6vWp+UUl35QUFr2sNkhnGrRcq6I9DJB1mRU4e1zNEKWVPunAHoC+ADG4uwSEfnZjDFr0edcAD1E5Lka+kxG9SFVdgArRKS/yXotAnBP5XmhnjJGwCv8zNd+rYVjs3WnOaoUO+QNkh8ffPfg1MCOgaOSJifF2kKOza8+sEMgkq9NjhOPxBVvK74nZ2HO5f7x/rkeh2emK9/1vogcOCaKtVJI2izAKUl2+729AgJ6XhQeEXNmaGhAyFHMMl0VLhG8n5Nd8Fle3la1u7/vmCqkaS1sBPAiySkwXjiXqvaRJO8DEAQgCsBmGDvlFRwHw1D9Sb2IW2HsMgPABgAzSH4N4OvKA5L0A5Bc2eD34hsv3UJEpBBAIckykhEAigE8Q/JkAB4AbQDEq2v2Vhj8CjuABTB23xerttEAengZEGEkQ6vRxZsv1b+rYezoA8AwAP8FABHZRHJDNdeOgeGFUBU/iUg2AJD8UsmsylNgBoBXvA1+xUkAFolIpur7GYCu6lx19/oZgEdgvJRfrD43OoVu91ySix9KS/1f38DA0Y/GJ8SG+/Dd+1ROTvmdZ5yGhtRWjwsLxQNjzgi9/4zTQ//Yu3fyf35ZeFan2NisgtLSd7KKi6dVtVilaTxI2uw2+5mx0fH39O5+QqfxZ02KG37SKLu/31GL0Pwbi8WCB+96yf7Sf+92Xn/KQPtPm7fnr913aGtuSemlNXxvNXlEZKrJIscAeNW7gWQCjIXX9iaPVSsi8g0Ozx8NYRgMz7ZqIWk9Rjm7RgAoQi361aNfq0Ab/a0EEckHMMlitwze+djOaXHnxrWNGB4ReKx2cWkhQnqEMKRHSILH5Uko2lj0aO6i3Bv84vwyPaWeae4i98cVL20acyEZHkiOjbbZrj7O37/LiOCQ8PHh4eHJfo2b4LGuLCsuck3JyEjNd7tfyHK7X9e7+5qjhYj8pdz0zwLwLMkfATwP4E0YuyH71Y535cQWhLHzPrgKsWMBnAzDJf1hkj1FxOV1fjiAZTWo5VD/eryOKz7bAFwKw829v4g4lXdAhX7FlWS5YBjpZ8DwTAAAC4wEgqX/uKHa54YKXdw4/C5R1wnldADjqzlX+f97Vf//HwNwQEQ+qKOMCqq7198AdFbu/+NghD0cFdQiziWBFsvwTWV73r8xOjr5vLDwgPpWRCn2eLDFSsus4cN8eq8jiRNTUjDj6qviypzOuC/Xrnv+9UWL7ukYG7PtYG7eW+Vu949KZ43JkAy02+xnxEbHX9epfdeepw49I/Ls0eNDY6Jij7VqOOH4gfALjvJM+X5RjtPlvr243DnjKMzNNpX7ox+MMJ0rRKSkhnCrRagi7MhbIMmxAB5S198Cc0OW+gKoXLXqRwBxJNfBCJO6BodDwvYAmK50sQO4SES2kRwI4D/q/kpheDP9qXblz4Wx+NwJwFcicp8afwyAZ2AsOGeJyCjvXXyS56j79gOQDeDSOoQvVbk4qzzGXoYxj9ytvDJuU7JXArhJRNwk3wJworqPWSLyaE2D1TVEDsAD6rOb5GXquUZUvj81buV+21ApxEtEfq3lObQYtNHfyvA4Pb+R7JX+VfqjOYtzrk66IikxsH3gMdXJYrMgrF+YJaxfWKLH4UksXFc4JWdRzt1+cX6pnlLPx+4i97fNeTW5KUCyU7TVenGQxXLhgMDA2LPCwqJPDQkJiLPVuRJPo7PT4cAT6f/f3n2HWVVeix//rtOnMzPAUIWAKChiCWKLir0mamK5N5pEY4qamHt/iYkmN0bTY8lNscTEXFs0lthiiw17BRsoKKCCIDCN6eXUvX5/vO/ocTIDg84ww7A+zzMPc87Ze5/3nGHm7LXftdZbvW51JnNvdTb7fbWmj2YzE5FxQIOq3uhPbE7lwwC63tfPHw90b9y3FBglInup6vM+LXI73EniRFV9XESeAb6IO6Fpytt3Q7PefVEG1PqA/wBcWn9vFPgq8A8ROc+nfT6MO/m9BEBEdlHV14BWoHQTx/IMcCLwuIjsAOzUfQOflh/pms3vwSEiUoE72T3Wjzd//6OBQ3AzOD15EfiDiFQCLcAJwEL/WI+v1QcMd+FOON/cwNgGTGcQPC0iM/9QX//DGxobv/aTqqqxuxYU9rnY/5f1den/OvTjzfL3JhGN8sU5u0e/OGf38asbGsbf8epre93+yiuNU0eNqmtPp+6saWm9DVhmF2Y/PhEZVxArPqakpPTb06fuWHrQvkeUH7j3YUVjRo8b7KF9oLp2LRddeUFNU1vrA00dyXO6Sp02g+1xwfezInINcBZwKXC5qv4MPii3OpoPM68iqjrHlx1dgMvuwW97HPBd4EhVbezhwmZP+54FNKrqrLySpZ7sCizs4Xfhc7ggfxc/htO7PV6vqruJyFnAOcDXcIHpfqqaFZGDccF810XSXfxzpYClInIZkASu9vus8H8/u3sGV2qlIvI14AfA93p5LV0OAH7aw/1FwBuq+hMRmQGci+uBkhGRK3EB9w3A/6hqg4iEgXkiMktVe8z+8p+Zl/HRErlf4v7+n0e3EjkRuYqPlp+Vd399vvys+3Z/x2WIfVDiBczYyPswbFjQvxVS16TnxyJy1ao/rro8MSGx59iTx1YN9FJ+fRGKhyjboyxatkfZ+FxHbnzbkrZdWxa0nBcfG2/XnC7MNmZv0qzO85kLphfi6nz3HB+JnhoR9j+ipKTk6NKyUXsWFoYKBnCpqI+jMZvlkrq6+vkd7QvXZrNfV9UVgz0ms9XaCbhERAIgA5zpTzCuxqXXr8TVmX+EqqZF5Hjgj11BLW6mZhlwo79PcCcbTd12n4tLLf+4bgLuFZGXcCekb21oYz8D8x9+nxbcDM0VPhU/AjyFmx25F7hdRI7BzZD0xZXA9f5Yr+JKG7r/rT4E2FA96zPA33DNCv/eQ93n94BxwHx/0n6Pqn7w/vmZoQtxDfrW4WbeuiLh3l4ruJT+BbgLPYNCVVPAhSJyxTlr114+LR7f//yqMVXjoxu+ONsRBLweCoVu/YSz/BsysaKC/z7owML/PujAws50evxjS5fNuuWll741f+XK9imjRr60uqHxlmwQPKGqjQM1huHAfzbvVVEy5pRwKLz/zEl7lc6eesCop5belTv3Wz+Nbzdl6MQfqVSSa279U9OjzzywvLp27VdU9c3NPITVebOwN+J+fy9lw+VWPZUdgQtgZwOHbmBCYaBKljYk/zk/778vw/0dnYa7UJv/B+CD818RWYK7yNvVJ2CFH2dPF2UmALeK63kSAzZ4npV3Abyjh4dzwB3++4Nw/VMW+L/HBUDXSiAnisg3cH9rxwI74D4TevKxS+Q28fX1WOK1tWQvWdC/FfP188eKyA7JNcmriqYXzRhz4piRkdKh8d8iXBimbHZZuGx22RhVJV2bntq2qO3wlpdbGuNj4i0a6ILM+sydBDy9Ga88D0kiMkpgz3GR6NEhYc8d44kRexYVlhxeUlq+Qzy+2Rr+bIq0Ktc3NLTe1ty0qjaTOTPdLQ3PmM1NVR/CXfnvfv+PcamD3e8/Ne/713Bp/N19prfnE5EJuJmezp4eV9XJed9fh0sz/bfHcN35e/KRJljqG+GpahqXmtnlpB6eexkwK++up/Mem5v3fT0fniAngVNUNSkiU3H9A97rdujDgb/2NNjur7GXsR/Q0+Pdtr0WV5/f/f56enit/rGX6Ht5woDypW0niciOX1m16pqDS4qnnT1yZHlRqOdZ/F/X12fOPvhAYptphZWCWIyjdpoZOmqnmVWqytKamikPL3nzs/9cuKhhWtXo1lwuePG9hobbAtWnt5aT6d6IyGhg94riqsNCodCe4yunVu0wcU7JLlP2LZ84chohcRfh21MtkYeevC+53ZQZg7Mmbp5sLst9j97Z+fe7rqluaWv+UWtby62DlM3xb6U+IpJgw+VWPZUdgWtqOgWXgdVbA7mBKlnakJ6e8+fA46p6nE+df6KH7fP3EXovaepyGfC/qnqPuOZ2F25k+yPo4bPQS+qHdfwCXK+qP8zfQEQ+hctc2N1nVVzHv5fFfWQXNqFErodt+vr6eizx2loMjejODCpVXQLsF4qGPtP+VvvlZXuUTRp19KgR4YLBbeaWT0SIV8WJHxIvrDykslADHZ9am5rR/mb7CS2vtTTGx8ZbCViSa889lWvPLcD98Wga7HEPBD9TMGtEKDy3OBw6MiYyad+iosJ9iopGzC4oLJwWjxMdgkF+F1Xl0ba29O/q6tY1BbmfN+Vy16pqMNjjMmZz8xdejxjscfSjQlxqfxR3Enemv8DwAVX92qCMbAukqotFZM87mps/+3hb229Pr6gc/4WysoJw3t/3ZBDwakjkpv32HZTzORFh+pgxTB8zpuA7Bx4wPggC3li7dvpDS948/t5FrzdNGz26ReGdls7OZ+va2ubj0oJrN3rgLZC4xpqzRxSNPCgSiu4XjcTHzNxmz4Ltxu9aNqVqx8LxlVOJRnrOqNxr+lFc9vDZkbNP+/5mHXO+IAiY98y/UtfccmVNa3vLHxqbGy7v/vu7mW3TVTIF/CcuC6gv5VY9eQ8XhN4lIido31em6I+SpU1Vhls2FfqWefQ8LoPpU13p/T1MhOUf8yt9OObhwPl92G4e8E8R+Z2q1vrSghJcaVg70CwiVbjPuSc2cJxNLZHrXn7W2+vrvl1v5WxbBQv6zQeCTPCMiOza8FjDsc3zmy+qPLhyXMVBFUWhyNBKBwfXCDAxIUFiQqKg8pDKAlUlU5fZPrkmeVznu51NHe92dCQmJpKa0iZFF2Wbs09qWhfi6jWTgz3+vhCROO7K9LRR4fCuiVBoV2DKjvHEiF0KCgr2Kiqs2DlREKrcTLM7/WFxMsnPa6rX1mSzt9Rks+f3kjpmjNkC+Vnd2YM9juHEz7DeIyL/uqK+7pwbGhvO/FblyKrDSkpiIRF+vb4+c9YBczW+kRKAzSUUCjFrwgRmTZhQ9P1DDylS1fFrmppmvLF27dEvr1rd+uKKFW27TJyQakulW1Bdur69/Zmmzs6X2cIu1PsAf6eSgvL949HEQZFQbPz08Z8umjZu55IpY2aWTBw5jUSssM/Hi0ViBFnN1dZXR0aPHDNg4+6JqvLsgieyf77x99Utrc3X1DfW/WaIzIS+CXxFRP4MLAf+pK6R3wbLrXqjrhneybieJp/t4279UbK0qS72z/ld4LGNbexr4L8B3CkiIVx6/SHdNrsQ97rX4JZ1/VRvx/M1+NNUdYOlYv65l4jIj4GH/XNncI0OXxCRV3GlF+8CG2yWt6klciLSvfyst9fXfbsNlXgNezI4GTtmqBORcLg0/M1wYfgHo48ZPaZsj7K4hIbu7HFvgmxAujpNcnUy1/luZ2Pnys5Urj3XoRmtRXg7SAcrs63Zt8lRDdQA1cD6zTHz7P9AjgBGA1Mqw+FdCkOh3RSmJkSKS8LhgqmxWHT7eKJ0SiyWmBSLMSYSYVO7Og82VWVBZ0fwh/r66ppM5pm12ex3VXXNxvc0xhiTT0SKRkci55aGQqeeUVk55spUShb/9IJIYogE/X2VCwJW1Nfz+tq1+tJ7q5rnr1jZUd3SkuxIp5uBRbWtrc+3pVLv4z6Xa3DNKlMbPmr/8EHPaGAMML44MWLHRKxgpirbRsKRsmg4XlhcUBadNGp64dSxO43YZtR2FCfKPvHz3vn8n3I7zZkWnHj0KZvth/nK6/ODy669eF1jc8NtdetrLtxAvftWyf9fiHYrWdouPwNCRP4K/FU/ujzqFktEPoMr09pqguGthQX9ZoNEpCAyInJeuDj81arPV40p2aUksiUG/93lkjky6zNkW7Jkm7Kaacy0Z9ZnOjMNmUy2ORtoVtOa0VSQDZIiUo9bHiqJkgMyKFmUrKJZAnIoGVXNEvjHQCQmIyUio3xX0fIgCEZUtDC6hFAyKhKLisRGhMOh0ZFIZFosXjIlHiuYFI0xNholsoUF9j0JVHm8rS175fr66qZc7v512ewFuvElYowxxmyEiBSXh8O/Ki4p+dIlx3++8ITddouFhliT1o8jnc2yvLaWt6preL+psXN1Q2PH6sbGzJqm5lxHOp1JZ7Op6tZMERKpEQm14Dqrr88F2bp0NlmbyabaI+FoIhyKxEVC8ZD/EgnFXfacxEWIgsRwDb9ioHFVKiPhaCISjsZjkXi8rLBSyourYiNLxxSPLB2XqCwZS0VJFbFIfMBee1N7PTfP/1X6Lxf/fcC7Kr+xdKFefu3F62rqqx+sra8+1/e7MN2ISAnwOK6ZngDnquonWW3FmEFjQb/pExEpj4yIfC+UCJ1SMbdiZPn+5UVDqeZ/oGig5NpzZFuyaFYhcPd98K92ux24mW2AUCJEuDBMqCBEuCCM5pSiH61K3zhx0uAvkzCAMqrc19KSuqZhfW1rENxYm81eZKstGGNM/xOR4nFlZeeUFRSc9oNDDxl98h5zEv25bN9Qs76tjb1++7f02Uf/NpbMdNCZbieZbqfTf2VzGcKhCOFQmFAo7L/3XxIilH/bbxMJRymMl3zQVG8w/fru0zLX/f72aGFBUb8fOwgCnnvpyey1t11V09S8/rHqunXnqerafn8iY8yQZEG/2SQiEg0Vhk4KF4XPK55ZPGbUkaMqY6OGdQzbb1SV3FlvZ+7c5lNbVh5mH3UGAbc1NXXc3NRY2x4EV6zP5a4YInWBxhgzrIlIQVVJybdKEokzvjhn95HfOWBuWWVx8WAPq98tWLmSb972fPL0Qy4c9C73A+G6x36ROebYz4YP3OewfrsCkc6kefDxe5K33HN9bUdH2811DbUX2dKKxmx9LOg3H5uI7BkdGf1lrCo2Y/Qxo8cUTiuUobg03FDSeebyzL3DLOhvzuW4obGh+d6WltrWXO6i5iC4XlWzgz0uY4zZ2ohIqCAaPXJMWemFu0+aPPEnRx0xesdx4wZ7WP3mtpdf5orn6pInfua/hmXQv7LmTZ5b/Y/UJedf+YnrCNY31nHLPTc0PfHcI3UdnW2XNbU0Xr2lNDI2xvS/LafttxlyfNOSg0Rk4vvV758fLgwfXnl45eiyPcriQ7Hj/1CQ3ehSqlsGVeW1ZCfXNDTULE2l1jZkc7/o0OBuW3rPGGMGj/8bfB9wn4jsOH/lil+MKS3b/UdHHDbmyJkzw+EtvO5/dUMjpYWVw3Z2YXLVDG5+YUU4l8sR/hhlGqrKW2+/wXW3/bn63VXL362tr74gm8vOU5vhM2arZ0G/+cRUdTXwDREpqr6l+oy6f9adWbZn2ciKAyvKoiOG1aT2J7alT38353Lc2dzcfmdz0/qOIHhoXTZ7saq+PdjjMsYY81F+LfLjRKTyzL/f8r2CaPSkz+08q/ys/fcrnzpq1GAP72NZ29REaeGUYX1iURKvzC1etjAya8Zufd5nfWMd98+7u/XhJ+9t7Ex2Pl5dt/YX9tlsjMln6f2m34lISGJyRKQsck6kJLJt+b7lI0t3L01Eiu0aU/1ZSzMPTZgSjW5BZRBZVZ5vbw9ubGqsWZlOr2nI5X7bHgR35i9ZY4wxZmgTEQmL7LtNRcW5lcXFs87cb99RJ83+dLwoPnAd6fvbSVdfmykf+bnoTpP3HuyhDJj5yx6hOfpO6gdnXbjBH0wqneKZ+Y9l7njg5tq69TXvrm+suzSVTv1LVTOba6zGmC2HRWGm3/n0wvuB+0WkOLU29YX6B+rPiFREJlbsXzG6ZLeSaDgxfLsLb4jEQkFLLkdlZOj/6i1Ppbi5qXH9c+3tjUnV22qz2T+p6vuDPS5jjDGbzqd4PwU8JSLF37+j7pRfPfjgmbtMmFj17bn7V+07bVuGevp/TWtnbsKEsmE90z9724O49IFbezxJUlXeXP46/7j/ptrFSxfWd3S2X9fY3HCNqq7f3OM0xmxZhn7kYbZoqtoGXA9cLyIVqfdT/1F7V+3XYlWxqvK55VUls0rCodjQPsnoT5oIaUuQo3II/uoFqixJJXmwpbXxqfa21s5AX1iTzVwKvGT1gMYYM3z4z+argKtEZNv5K1eeFY9Ejpo9aZuy0/bee/QB228nQ3Hpv6bOJEWJ0sEexoAKhUKENZZbvfa9yMRxk1BV3nlvGY8+/UDTUy8+1pxKJedV1639X1++YYwxfTL0Ig8zbKlqA3AlcKWIjEmuSn6lJlFzSnxCfGTFARWji2cUhySy5aS9fxxaHKI5PXR63XUGAS90tAf3trTUvZlMtmZUn1ybzV4HPK+qucEenzHGmIHla7+/C3xXRKY9/fY7pxVEo8fOHD+u/PR99h59yPTpoXh0aEyut6bSUhQf3kE/wIyxe0RvuP0vmWg01vzqG/NbM5nMc+tq11wNPGur4xhjPg4L+s2gUNVq4CLgIhGZ3Plu59dCsdBx0croiNLdSytKdipJxEbFBnuY/S5XFg43Vw9uLF2bzTCvtS35QGvL+tpstq4jCG5fn8vdoqrvDOrAjDHGDCpVXQ78CPiRiEx+4d0VXy6Ox4+fWFFeecJuu1UctdPMxDYVFYM2vmQmGyqIFw/a8w+k1s5Glqyan3npncfr65rWNGdJLmxqbfgNsNCy7Ywxn5Q18jNDiohUSEQOjpRHTglFQjsmJieKymaXjSrcvjA0HBoBrrtpHd97PRocWzZis9U0JIOAxckkT7a3NT3V3t7SEQTL12ez13Sq3q+qzZtrHMYYY7ZMIlJeEI0eNras7EuJaGTG7pMmFx23684j5263XaisoGCzjWP8D3+V+dGJ1w+NtINPKBfkWF23jNdWPN305vsLWlKZzhVtnc1/S2Y67lPVmsEenzFmeNnyoygzrPgSgNuA20REUutS27a93nZMuDD8WYnKNgWTCwpLdi6pLNq+KBwp2/L++0bKItRlc1lgQNIYVJW12Qyvdnbmnm1vr38rlUp2BEFdVvXJddnsPcBzlhpojDFmU6hqI3ALcIuIyJJ11ds/8MYbR5cmEp8vSsTH7TZxYuLgGTNG7jNlSnhSZQUyQCvUiAy9PgN9EWhAXfMaVtUtzS1b89r61euXp5LpjsYgyD3X0FZzI/CifTYbYwbSlhc1ma2GT2dbDlwKXCoiklqTmtbyasshkaLIsRKVKdGR0UTh1MLigskFpfEJcaIV0QE72egP0Yoodbn2fivq7/Sz+As6Olpe6Ghvrcvm2nLoW4253H1tQfA0sMzSAo0xxvQX/5nylv+6VERk0ftrtrvz1df2G1VSfFQkFJ4+tqy0+MDtty+Zu912pTtPGE9pP2UDhGToN/5VVRrbanmvbmmwfO3ChpW1byY7U23Nii5u7Wx8OJXpfA5Y6lc62mqJyFwgrarP+dtnAB2qekM/HHsscL2qHvpJjzUciMhkYG9V/ftgj8UMHgv6zRbDn2gs819XAIjIyLZFbTPDpeE54UR4H4SpoUSoJF4VjxVsW1BWsE1BQXxCnKFSGhCpiLA+t+kX89tyOd7LZFiZTgfLUsnmpalUZ3Umm+nUoDaj+kR1NvsgsEBVW/t/1MYYY0zP/GfzUv91NYCIlDyxbPmcieXlh8ci4T3jkcjoEQWFhbtMnBCfM3ly+azx4yPTx1RREOt70ls2myUUGhqf5V1UldbORlbVLePtdYsa36l+o6M92dwWaLCsPdnycGe67VngDVXNDPZYh6C5QBvwHICqXtWPxz4ceKgfj7elmwx8EbCgfytmNf1m2BE31T8R2ClSHtk7FA3tRZix4YJwcWJiIhYfGy+KlEcKI6URiZZFiZRFCBWGNkuGQLo+TfkF76eunbBNvPtjHUHAqnSa9zJpXZZKNS9NpTrWZTLZzkDbc2h9oLyxPpddkFR9C5cBsd5m8Y0xxmwJRCQObBePRGaNG1G2nyC7FESjFUXxWGKbiorw9lVVBdtXVZV+amRlaFJFBeNGjCAc+nBmf0VdPUf9+e7Ut4665N8+PwdKoAEdyVYa22tpaK2hpml1W3XTqrb65jW5ZKYjlc6mOoA1yXT7Y23J5qdwTfc6N9f4+ouInAJ8B1d6+CJwFrAb8H/AHCAMzAdOAlYAlwE74SYPL1TVf4qrvbgIOAxQ4GpVvUxEVgKzVbVeRGbjsjdPBV4AckAdcDZwEO4iwP24Wfo5fmyTgXtUdZaIfBr4X6AYqAdOVdV1PbyeW4GfquqSvPsmAw8CzwB7AguBa4GfAqOBk1V1vojMAX4PFACdwGmqulRETgU+BxQCU4G7VPUH/th/Anb3+9yuqhf4+4/0460HXgGmqOrRIlLUy3t4KnCsf79nAr/1P5MvASngSFVtEJGpuMmvUUAH8HVVfUtErgNagNnAGOAHqnq7iLwAzPA/u+tV9Xfd3zMz/FnQb7YaIhIFtgUmSlTGhYvDU0PR0CRgAlAhEYlLROISk1h0RDQUrYhGo5XRwmh5tFBigoQEQrh/hQ9vS8/3a0bJdeYIOgNynblcri2XyrZmU8GDjSU7JwpqG7JZTatmMqqpjGo65/5Qv9mQzS7oUH0TF9jXWGBvjDFmuPLB4hhgcjQcnjy2rHRWLByZHqhOTEQjhdFwJBaPhGMhCcWX13eU7DplbltRojReFC9NFMSLIwWxIgpiRSRiRagquSBLoDlyQY5ckHW3P/g+l39bs0Eml8tlc5lcOtfcXt/Z0FaTbmqvDzLZdDqby6SyQToJUqcarGhPtixMZjqW4QKn1aqaHtx3rn+IyAzgYuDzqpoRkSuBF1T1BhH5BZDABbPvq+qvReRXwBJVvVFERuAuBuwKfBk4GDhJVbMiUuED1JV0C/pVda6IXAi0qeqlfhwf3BaR1/x43hWRc4Eo7oLCk8AxqlonIicBh6nqV7u9njDwsqru0u3+ycDbfqyLgQW4wP90XDB/mqoeKyKluDKDrIgcDJypql/wAflP/P4pXGbLZ1R1dd5rDQPzcBdQluHO4/ZT1RUicjNQ4oP+3t7DE4Af++8TfrznqupVIvI74D1V/b2IzAPOUNXlIrIH8GtVPdAH/UW4izPTcRdLtvWlFOeo6tF9+C9hhqmhlSdlzADy6XVv+q9eiUikk85RuJOQKonJ+FA0VEKIiIQkCoQJEUGIikgE93sUQQgjRHBXaCMoHZrTuiAZ1AWdQR0uqG8BOh5va1uLm6kf3PX7jDHGmEHkPwfX+K9ngZu6byMiIaAcqHp04a3FQClQFovEKxOxoqpIODoqJOEKX2yQBk0pmlbVdKBBSoMgmdNcKgiyyVyQTWdymaRqkAYy/iuNm41dB9RuZen4BwGfBhb4jMcCoNY/9jNccJzEBbIAhwKfE5Fz/O0EsA0u4L+qqyGhb8z8cd0GnAj8BhfAngRsj5v9fsSPM4z7eXW3By5boScrVPV1ABFZDMxTVRWR13Ep8ABlwPUiMg2XsZC/WsS8rlWPRGQJMAlYDZwoIt/AnQ+OBXYAQsC7qrrC73sz8A3/fW/vIcDjvlSzVUSagXv9/a8Ds0SkGNgb+Edehmp+9svdvl/EEhGp6uV9MFshC/qN6cZ/YK2j5w8TY4wxxmxGPohZ779M/xJcyvcPe3isApdKH8UFpu1++y+o6tKPHMRFoD1lJmZxATD+GH1xKy6ovRN3JWe5iOwELFbVvTay7xG4NP6epPK+D/JuB3wYE/0cF3gf57MDnuhl/xwQEZFPAecAu6tqo59tT+Dep9709h7u0YcxhoCm7pkMvYxx6Ha2Npvd0G+DaozZIojIZBF5U0SuFpHFIvKwiBSIyNdFZIGILBSRO0Sk0G9/nYj8UUSeE5F3ReT4wX4NxhhjzFZmHnC8iIwGEJEKEZnkH/sLcD4u++Iif99DwNk+yEdEdvX3Pwyc4TMgEZEKf/9KXCYBwBfynrcVKOlpQKr6Di6oPh93AQBcOv0oEdnLHz8qIjv2sPtB/jV9XGW4rBNwvQc2phR3MaTZz6wf4e9/C5jiLxyAy1bo0tt7uFGq2gKsEJET/L4iIjtvZLde32uz9bCg3xjTn6YBV6jqjkAT7gP+TlXdXVV3xpVWnJ63/VjgM8DRuDQ+Y4wxxmwmvtndj4GHRWQR8AgwVkS+DGT9Mm+/AXYXkQNxM+FRYJGIvOFvA/wVWOXvX4jrFg+uUd4fRORpXCDf5V7gOBF5TUT27WFotwKn4FL98T0Ujgcu8sd/DZfm/gERGQUkfWD8cV0M/FpEnsWVEGyQqi4EXsX1CbgGV6KCb+h4FvCgiDwD1ADNfrfe3sO+Ohk43b8Pi4FjNrL9IiDrJ1/+3yY+lxkmrJGfMaZf+KvZj6jqNH+7q/nO08AvgBG4NMGHVPUMnwL3iKre5LdvVVW7Em2MMcaYTSZuFYIJqjokJhFEpFhV2/yM/hXAcuucbwaLzfQbY/rTv9W7AdcB31bVnXBX/BO9bG+1Z8aYIUFEnvCdxhGRB3yH7d62PcPPivbXc/9ZRPbpdt91/VUCJSIrRWSkiIwQkbPy7p8rIvf1x3MYMxhU9cahEvB7X/crESzGlQ38eXCHY7ZmFvSbASEiP/NLnRhTAqwTt2TiyYM9GGOM2RSqeqSqNm3g8atU9YZ+fMo9cGuYD7QRuPRjY8wAUNXfqeouqrqDqp6sqh2DPSaz9bKg3wwIVf2Jqj462OMwQ8L5uOVzHsE1tjHGmH7lG4m+JSJ/FZE3ROQmETlYRJ4VkeUiMsdvVyQi1/jmoq+KyDH+/gIRuUVEFonIrbhly7qOvVJERvrvv+y3WSgif/P3Xdi19JbPELhIROaLyLKuWmURCYvIJf55F4nIN3t5HTOAZb0s57pfT41PReT7ecf9ad79d4vIy+Iaq36jh+P9Bpjqa6ov8fcVi8jt/r28qavRmDHGmC2bLdlnNomI3A1MxKVo/wH4P/81G7dUyzWq+jtfr32fqt4uIj8BPos7iXoO+KZfF/UJXDB4AG7G4XRVfXqzviDTb1R1JW4N3a7bl+Y9/Kcetj+12+3igRqbMWarsC1wAm4t7AW4RmKfAT4H/Ag4Fvgf4DFV/apP2Z8vIo8C3wQ6VHWWiMwCXul+cN8p/H+AfVS1Pq87eXcRVZ0jIkcCF+DWLz8daFbV3UUkDjwrIg/nreHdZUPLjXU1Pp0O3APcLiKH4hqozsGVSN0jIvup6lPAV1W1QUQKcGuw36Gq+UvenQfM7Fr6S0TmArsCOwJrcQ3J9gGe6WU8xhhjthAW9JtN9ZGTCOBlYLyqzgTope7xclX9mX/8b7hO7ff6x3o6OTLGGGM21QpVfR1ARBYD8/wF5teByX6bQ4HPdc3M4y5gbwPsB/wRQFUX+S7m3R0I3K6q9X67hl7Gcaf/9+Vuzzsrb4a+DBesdw/6DwNO6+W4d/v16peIWxqs67iH4rqHg2uWOg14CviOiBzn75/o79/YOvfzVfV9AF+LPBkL+o0xZotnQb/ZVN1PImK4dUgvA+7HrdPa3QEi8gOgEKjANTTpCvp7OjkyxhhjNlV+Y9Ag73bAh+c7AnxBVZfm7+iz2De2nJH0YZv8cXQ1M+3a92xVfajXg4sUAiNUde1Gjtt1vK5/f62qH2kQ5mftDwb2UtUOn1mX30R1Y2PvPn5jjDFbMKvpN33W7SRiZ9zMQhzYGXgC+BZundb8fRLAlcDxvnv71fTcvd1OLowxxgy0h4Czu2rVRWRXf/9T+EajIjITmNXDvvOAE0Wk0m/XW3p/b897pm9oiohsJyJF3bY5AHh8E47ZddyvikixP+54ERmNyyRo9AH/dGDPHvZtxTVaNf1MRE4Vkcv7+ZjHisgOebf7tWGy7/8Q66/jbeB5PuiB0Q/H2uDKGsaYD1mQZTZFTycRI4GQqt4hIu/glmfL1xXg1/uTkuOB2zfXgI0xxpg8Pwd+Dyzygf9KXMnZn4BrfVr/a8D87juq6mIR+SXwpIjkcBe+T+3j8/4Vl832in/eOlyPgXxHsImfj6r6sG/+97y/jtEGnILrC3CGfz1L6WE1AFVdL67R4RvAv3DZemboOha4D1gCrmFyfx1YRCYDa1Q13V/H3BxU9cjBHoMxWwpR7UummjHgmw/dDYzHnUSMAu4CvsKHWSM/VNV/dWvk9wvgP3AnV6uB91T1Qp9ueI6qvuQ7I7+kqpM33ysyxhhjhgYReQXYQ1Uzgz0W0zsROQX4Dq688UXgLFXNichpwA+BdcAyIKWq384/H/L7t3U1rvWlj1/ClaD8S1XPE5Gv45pRxoC3/eO74AL+Zv/1BdzKOF3nWQcBl+Im8xYAZ6pqSkRWAtfjmilHgRNU9d9W0RGRM3ExwZXd7u+tEfO2wFW488AcroFmDfBPoNw/149V9Z/+OP8DfBl3DlgHvKyql4rIVOAKf5wO4Ouq+pZ/zzpxTSsn4fpcfAXYC3ixqxGwf32zfWPNu8lrNK2qf9nAj9GYrY4F/cYYY4wxxmyEz6q4GPi8qmZE5EpcFsUjuAsAn8YF5Y8Dr24o6BeRI3CB+8E+g7LCN0qu7FplwU+a1KjqZT0c5zrchYD7gOXAQaq6TERuAF5R1d/7oPi3fv+zgN1U9Ws9vK5/Av9PVd/tdn9FV8NK34j5NlW9V0ReBH6jqnf5Ms4QkAYKVbXFT+S8gGseuRsuC3QP3EWJV4CrfNA/DzhDVZeLyB64/hQH+teWAP4Tt/rG33ArSSzGXdQ4XVVf6xb0d71/XY2m9++2WoUxWzVL7zfGGGOMMWbjDsIF9gt8OUUBUIsLaJ9Q1ToAEbkV2G4jxzoYuFZVO+Ajq0HM9MH+CNxqDL02f/S2x61csczfvh7XY+n3/nZ+w+TPd9/Z1/FP6B7we//WiNlnaY5X1bv8uJP+OFHgVyKyHy5zYTxQBewL3NX1OkXkHv9vMbA38A//XoLrE9Xl3rzVN2q6rcwxGVeGk+/jrFZhzFbDgn5jjDHGGGM2ToDrVfWHH7lT5Fh6X9khiy+B9P0cuprl9bYaxHXAsaq6UEROBeb2YUwbsrGGyfvSw7KMeY2YZ6vqahG5EDf73tvznYxL0/+0z4JYyYd9nXp6nSGgSVV32ci481fi6Lr9kdfxCVarMGarYd37jTHGGGOM2bh5wPF+hQREpEJEJuFS++eKSKWf8T4hb5+VuOwAgGNw9e7gljj+ql+qMX81iBJgnT/OyXnH6W21hbeAyb7OHlwPgCc34TUdjmvk2F1PjZhR1RbgfX+hAxGJ+9dQBtT6gP8AXC0+uJUxjhORAhEpwfUI6DrOChE5wR9HRGTnTRh3vr6sVmHMVs2CfmOMMcYYYzZCVZcAPwYe9isjPAKMVdV1wIXA88CjuLr1LlcD+4vIfFwZQLs/1oPAPcBLIvIa0LWM3fm4iwiP4AL6LrcA3xeRV30DvK4xJXGN7v7hU+EDXJO9vppLDxcJVLXJj/11XBPnBXkPfwmXTr8I1+BvDHATMFtEXsJdrHjLH+cV4FZcOv4dwNN5xzkZOF1EFuLq9Y/ZhHHnexCI+PH8nB5WqzBma2eN/IwxxhhjjNnKiMgE4GpVPWKwx2KMGVgW9BtjjDHGGGOMMcOUpfcbY4wxxhhjjDHDlAX9xhhjjDHGGGPMMGVBvzHGGGOMMcYYM0xZ0G+MMcYYY4wxxgxTFvQbY4wxxhhjjDHDlAX9xhhjjDHGGGPMMGVBvzHGGGOMMcYYM0xZ0G+MMcYYY4wxxgxTFvQbY4wxxhhjjDHDlAX9xhhjjDHGGGPMMGVBvzHGGGOMMcYYM0xZ0G+MMcYYY4wxxgxTFvQbY4wxxhhjjDHDlAX9xhhjjDHGGGPMMGVBvzHGGGOMMcYYM0xZ0G+MMcYYY4wxxgxTFvQbY4wxxhhjjDHDlAX9xhhjjDHGGGPMMGVBvzHGGGOMMcYYM0xZ0G+MMcYYY4wxxgxTFvQbY4wxxhhjjDHDlAX9xhhjjDHGGGPMMGVBvzHGGGOMMcYYM0xZ0G+MMcYYY4wxxgxTFvQbY4wxxhhjjDHDlAX9xhhjjDHGGGPMMGVBvzHGGGOMMcYYM0z9f+qR6uXEtRYkAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1152x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print('**Nan represents unfilled/unshared optional information, \\\n",
    "signifiying that a user has not shared the\\n respective information with OKCupid and it\\'s missing from their profile')\n",
    "print('\\033[1m'+'*Extrapolated or split from raw data variables'+'\\033[0m')\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "drop = ['diet', 'diet_adherence', 'location', 'offspring_want', 'offspring_attitude', 'pets', 'religion', 'sign', 'speaks',\n",
    "        'religion_attitude', 'sign_attitude', 'optional_%unfilled',\n",
    "        'last_online'] + languages + ['age', 'height', 'income'] + essay_feats\n",
    "for_plotting = df.drop(columns = drop).columns.to_list()\n",
    "extrapolated_vars = ['diet_type', 'city', 'state/country', 'religion_type', 'sign_type',\n",
    "                     'dog_preference', 'has_dogs', 'cat_preference', 'has_cats', 'num_ethnicities', 'num_languages']\n",
    "\n",
    "def collapse_category(feat, threshold):\n",
    "    '''Needed to ensure that only a mask would be used to mark categories to collapse,\n",
    "    and to preserve the original data frame'''\n",
    "    sum = df[feat].value_counts(dropna = False).reset_index()[feat].sum()\n",
    "    temp = df[feat].copy()\n",
    "    mask1 = temp.value_counts()/sum < threshold\n",
    "    mask2 = temp.isin(mask1[mask1 == True].index)\n",
    "    temp[mask2] = 'other'\n",
    "    return temp.value_counts(dropna = False).reset_index()\n",
    "\n",
    "\n",
    "for i in range(1, 12):\n",
    "    plt.figure(figsize = (16, 9))\n",
    "    j = 2*i\n",
    "    k = j-2\n",
    "    for num, feat in zip(range(1,3), for_plotting[k:j]):\n",
    "        plt.subplot(1, 2, num)\n",
    "        temp = collapse_category(feat, 0.01)\n",
    "        labels = temp['index']\n",
    "        theme = plt.get_cmap(\"tab20\" if len(labels) > 10 else \"tab10\")\n",
    "        plt.pie(x=temp[feat], autopct=\"%.1f%%\", labels=labels, pctdistance=0.77,\n",
    "                #radius = 1,\n",
    "                colors = theme(np.arange(len(labels))),\n",
    "                wedgeprops=dict(width=0.10,\n",
    "                                edgecolor=\"k\",\n",
    "                                linewidth=0.7))\n",
    "        text = feat + '*' if feat in extrapolated_vars else feat\n",
    "        plt.text(0, 0, text, \n",
    "                 horizontalalignment = 'center',\n",
    "                 verticalalignment = 'center',\n",
    "                 fontsize = 20)\n",
    "    plt.show()\n",
    "    plt.clf()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "lonely-opera",
   "metadata": {},
   "source": [
    "**Bias:**\n",
    "\n",
    "The biggest indicator that this sample does not meet the statistical criteria for independent random sampling is the 'state/country' variable. OKCupid was founded in 2004. It's simply not possible that by 2012 all of their users would only be from the state of California. When you get a dataset, regardless of what you've been told about the quality of the sampling, always check for signs of bias. The process of checking for bias in a study or in a sample is sometimes called a \"Risk of Bias Assessment\".\n",
    "\n",
    "Even though the sample looks like it's heavily biased, we will still draw inference about what is represented in the sample.\n",
    "\n",
    "**The charts tell us that the typical profile on OKCupid back in 2012 was:**\n",
    "- not fat or skinny\n",
    "- has drinks socially\n",
    "- doesn't do drugs\n",
    "- finished college\n",
    "- white ethnicity\n",
    "- varied in terms of possible job background\n",
    "- doesn't have kids\n",
    "- straight\n",
    "- male\n",
    "- doesn't smoke\n",
    "- single\n",
    "- lives in San Francisco, California\n",
    "- eats anything\n",
    "- agnostic or atheist\n",
    "- likes dogs and/or cats but doesn't have them\n",
    "- not multiracial\n",
    "- speaks only one language\n",
    "\n",
    "It's possible that people misrepresent themselves on their profile, paint themselves more positively, and carefully omit negative information."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "liable-function",
   "metadata": {},
   "source": [
    "### Top Spoken Languages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "structured-skating",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "\n",
    "lang_percent = []\n",
    "for language in languages:\n",
    "    lang_percent.append((language, df[language].value_counts(normalize = True).loc[1]))\n",
    "    \n",
    "def sort_func(pair):\n",
    "    return pair[1]    \n",
    "sorted_lang_percent = sorted(lang_percent, key = sort_func, reverse = True)\n",
    "\n",
    "#Make barplot\n",
    "plt.figure(figsize = (16, 9))\n",
    "rects = sns.barplot(x = [each[1] for each in sorted_lang_percent[:10]],\n",
    "            y = [each[0].title() for each in sorted_lang_percent[:10]], \n",
    "            orient = 'h',\n",
    "            palette = \"tab20\")\n",
    "\n",
    "#Add Data Labels outside of bar\n",
    "rect_labels = []\n",
    "for rect in rects.patches:\n",
    "    yloc = rect.get_y() + rect.get_height() / 2\n",
    "    label = plt.annotate(format(rect.get_width(), '.1%'), xy=(rect.get_width(), yloc), xytext=(4, 0),\n",
    "                         textcoords=\"offset points\", horizontalalignment='left', verticalalignment='center',\n",
    "                         color='black', clip_on=True)\n",
    "    rect_labels.append(label)\n",
    "\n",
    "plt.title(\"Top 10 Languages\")\n",
    "plt.ylabel(\"Language\")\n",
    "plt.xlabel('% of users who speak it'.title())\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "signal-senegal",
   "metadata": {},
   "source": [
    "Everyone speaks English. Hilariously some people speak C++... _why not Python?_"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "awful-therapy",
   "metadata": {},
   "source": [
    "##  Unfilled Optional Fields Sorted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "modular-procurement",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sorted_nulls = sorted(nulls, reverse = True)\n",
    "sample_size = 59946\n",
    "\n",
    "#Make barplot\n",
    "plt.figure(figsize = (16, 9))\n",
    "rects = sns.barplot(x = [each[0]/sample_size for each in sorted_nulls[:23]],\n",
    "            y = [each[1].title() for each in sorted_nulls[:23]], \n",
    "            orient = 'h',\n",
    "            palette = \"tab20\")\n",
    "\n",
    "#Add Data Labels outside of bar\n",
    "rect_labels = []\n",
    "for rect in rects.patches:\n",
    "    yloc = rect.get_y() + rect.get_height() / 2\n",
    "    label = plt.annotate(format(rect.get_width(), '.2%'), xy=(rect.get_width(), yloc), xytext=(4, 0),\n",
    "                         textcoords=\"offset points\", horizontalalignment='left', verticalalignment='center',\n",
    "                         color='black', clip_on=True)\n",
    "    rect_labels.append(label)\n",
    "\n",
    "plt.title(\"Unfilled Optional Fields\")\n",
    "plt.ylabel(\"Fields\")\n",
    "plt.xlabel('% of users who did not give information'.title())\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "virtual-baseline",
   "metadata": {},
   "source": [
    "**Disclaimer**: My comments below are pure speculation and hypothesis\n",
    "\n",
    "| Feature        | Hypothesis For Not Sharing Information     |\n",
    "| :------------- | :---------- |\n",
    "| Income |If you're rich you don't want the IRS to know. If you're poor, you don't want potential matches to see that either|\n",
    "| Children |Finding out someone has kids can be a turn off and perceived as extra baggage|\n",
    "| Diet|People are afraid of being criticized for choosing to shun some foods|\n",
    "|Religion|Some people are xenophobic. As a result, some people hide their religion so as not to immediately turn away those xenophobes|\n",
    "|Pets| No idea why a third of users don't share this information|\n",
    "|Essays| There's a pattern where the higher up the chart you go, the higher the essay number. This is because the questions are presented to the user in a fixed order. Not all users have the patience to answer questions all the way to the last one. The reason why essay 8 stands out significantly more than the rest is because the question being asked is \"Share something private\", which of course is rather controversial considering you can't take back what you share online. See below [section](#Interpretation-of-tf-idf-Results) for the essay questions.|\n",
    "|Drugs|Drugs are illegal in some states|"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "applicable-cleanup",
   "metadata": {},
   "source": [
    "## Essay Questions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "searching-force",
   "metadata": {},
   "source": [
    "The essay questions are a perfect candidate for Natural Language Processing (NLP) Topic Modelling. More specifically, we'll be using term frequency - inverse document frequency (tf-idf), a model which initially counts the occurences of each word, then applies a word weighting scheme which deprioritizes common words such as \"the\". The expected result is to condense the essay answers into specific keywords, which may be visualized."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "naval-resident",
   "metadata": {},
   "source": [
    "Let's create a copy of all of the essay answers ,just in case we need to start over in the preprocessing for NLP."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "silver-martin",
   "metadata": {},
   "outputs": [],
   "source": [
    "nlp_essay_df = df[essay_feats].copy(deep = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "scientific-letter",
   "metadata": {},
   "source": [
    "### Text Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "suited-cache",
   "metadata": {},
   "source": [
    "Before we can apply tf-idf to our essay questions, we need to convert them to a suitable format. The process is called text preprocessing. The words of our essay questions will be converted to their root words(also called lemma)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "technological-desktop",
   "metadata": {},
   "outputs": [],
   "source": [
    "import nltk\n",
    "from nltk.stem import WordNetLemmatizer\n",
    "from nltk.corpus import wordnet as wn\n",
    "\n",
    "from collections import Counter\n",
    "import unicodedata\n",
    "import string\n",
    "\n",
    "# Lemmatizer class object - converts tokens to root words\n",
    "lemmatizer = WordNetLemmatizer()\n",
    "# Fetch nltk stopwords\n",
    "stopwords = nltk.corpus.stopwords.words('english')\n",
    "\n",
    "def preprocess_corpus(DataFrame, Series):\n",
    "    # Remove accents function\n",
    "    def remove_accents(data):\n",
    "        return ''.join(x for x in unicodedata.normalize('NFKD', data) if x in string.ascii_letters or x == \" \")\n",
    "\n",
    "    # Look at synonyms of the word if it's likely to be a noun, verb, adjective, or adverb\n",
    "    def get_part_of_speech(word):\n",
    "        # Fetch synonyms of word from wordnet database\n",
    "        probable_part_of_speech = wn.synsets(word)\n",
    "        # Count the number of nouns, verbs, adjectives, and adverbs among the synonyms\n",
    "        pos_counts = Counter()\n",
    "        pos_counts[\"n\"] = len(  [ item for item in probable_part_of_speech if item.pos()==\"n\"]  )\n",
    "        pos_counts[\"v\"] = len(  [ item for item in probable_part_of_speech if item.pos()==\"v\"]  )\n",
    "        pos_counts[\"a\"] = len(  [ item for item in probable_part_of_speech if item.pos()==\"a\"]  )\n",
    "        pos_counts[\"r\"] = len(  [ item for item in probable_part_of_speech if item.pos()==\"r\"]  )\n",
    "        # Get the speech type with the highest count and return it\n",
    "        most_likely_part_of_speech = pos_counts.most_common(1)[0][0]\n",
    "        return most_likely_part_of_speech\n",
    "\n",
    "    # Convert each word into its lemma(root word)\n",
    "    def preprocess_text(text, min_word_length):\n",
    "        # Tokenize\n",
    "        tokens = nltk.word_tokenize(text)\n",
    "        # Convert to lowercase\n",
    "        tokens = [token.lower() for token in tokens]\n",
    "        # Remove accents\n",
    "        tokens = [remove_accents(token) for token in tokens]\n",
    "        # Remove punctuations\n",
    "        tokens = [str(token).translate(string.punctuation) for token in tokens]\n",
    "        tokens = [token for token in tokens if token != '']\n",
    "        # Remove stopwords\n",
    "        tokens = [token for token in tokens if token not in stopwords]\n",
    "        # Remove short words\n",
    "        tokens = [token for token in tokens if len(token) >= min_word_length]\n",
    "        # Lemmatize\n",
    "        lemmas = \" \".join([lemmatizer.lemmatize(token, get_part_of_speech(token)) for token in tokens])\n",
    "        return lemmas\n",
    "    \n",
    "    # Convert Data Series to a List \n",
    "#   list_corpus = DataFrame[Series].dropna().to_list()\n",
    "    list_corpus = DataFrame[Series].to_list()\n",
    "    # Remove linebreaks\n",
    "    list_corpus = [\" \".join(text.splitlines(False)) if isinstance(text, str) else ' ' for text in list_corpus ]\n",
    "    # Remove '/' characters\n",
    "    list_corpus = [text.replace('/', ' ') if isinstance(text, str) else ' ' for text in list_corpus]\n",
    "    #Normalize\n",
    "    processed_corpus = [preprocess_text(text, 3) if isinstance(text, str) else ' ' for text in list_corpus]\n",
    "    return processed_corpus"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "exciting-cornwall",
   "metadata": {},
   "source": [
    "### Term Frequency-Inverse Document Frequency"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "closed-flour",
   "metadata": {},
   "source": [
    "Now that we have our root words, let's apply tf-idf. It will assign a score to each root word. For each user's answer we will get the highest scoring word (keyword). This keyword represents what our model believes is the most significant word of a user's response."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "under-atlas",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "\n",
    "# Tfidf class object - Scores each word\n",
    "vectorizer = vectorizer = TfidfVectorizer()\n",
    "\n",
    "def tfidf_for_keywords(processed_corpus):\n",
    "    '''Generates one keyword for each document in the corpus. Returns all keywords as a list.'''\n",
    "    tfidf_scores = vectorizer.fit_transform(processed_corpus)\n",
    "    feature_names = vectorizer.get_feature_names()\n",
    "    keywords = [feature_names[row.argmax()] for row in tfidf_scores]\n",
    "    return keywords, tfidf_scores, feature_names"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "unexpected-integrity",
   "metadata": {},
   "source": [
    "### Iterate over all essay columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "peaceful-kingston",
   "metadata": {},
   "source": [
    "Let's iterate the whole process over all of our essay features, and let's collect only the most common keywords."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "rising-bradley",
   "metadata": {},
   "outputs": [],
   "source": [
    "essay_vectors = []\n",
    "essay_feature_names = []\n",
    "def series_to_keywords(DataFrame, Series, n_top, export_vectors = False):\n",
    "    processed_corpus = preprocess_corpus(DataFrame, Series)\n",
    "    keywords, tfidf_scores, feature_names = tfidf_for_keywords(processed_corpus)\n",
    "    essay_vectors.append(tfidf_scores)\n",
    "    essay_feature_names.append(feature_names)\n",
    "#   temp = DataFrame[Series].dropna().reset_index()\n",
    "    temp = DataFrame[Series].reset_index()\n",
    "    temp[str(Series) + '_keywords'] = keywords \n",
    "    if export_vectors:\n",
    "        temp[str(Series) + '_keywords'].value_counts().iloc[:n_top].to_csv(str(Series) + '_top_keys.csv')\n",
    "\n",
    "# Training NLP Model commented out due to long training time\n",
    "# for feature in essay_feats:\n",
    "#     series_to_keywords(nlp_essay_df, feature, 40)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "western-illinois",
   "metadata": {},
   "source": [
    "### Top Keywords in User Responses to Essay Questions Visualized as Wordclouds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "operating-blast",
   "metadata": {},
   "source": [
    "Let's generate wordclouds for each of the essay questions. <br>\n",
    "_Developer Note: The code is embedded as an image because it was run in a separate Python 3.7 environment._"
   ]
  },
  {
   "attachments": {
    "image-3.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "attached-slide",
   "metadata": {},
   "source": [
    "![image-3.png](attachment:image-3.png)"
   ]
  },
  {
   "attachments": {
    "essay_wordclouds.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "altered-stuff",
   "metadata": {},
   "source": [
    "![essay_wordclouds.png](attachment:essay_wordclouds.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adverse-tunisia",
   "metadata": {},
   "source": [
    "The level of insight gained from each wordcloud, using the existing model algorithm, is not the same. Some give sufficiently interesting and useful results. Some tell us more about what essay question is being asked rather than what the answers to those questions are. The results merit further filtering, tweaking, and refinement of the algorithm to give us better keywords. Further NLP modelling and analysis deserves to be discussed in its own lengthy separate article/notebook. We will not explore it further here.\n",
    "\n",
    "In addition to the wordclouds, manual reading of several user responses was done to better interpret the tf-idf results."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ceramic-seeker",
   "metadata": {},
   "source": [
    "### Interpretation of tf-idf Results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "geographic-wiring",
   "metadata": {},
   "source": [
    "|Essay Number| Personal best guess of the question asked| Comment on tf-idf Result|\n",
    "| :------------- | :---------- | :---------- |\n",
    "|essay 0| Describe yourself| Users use this essay question to talk about what they like, love, and the qualities of who(someone) they're looking for|\n",
    "|essay 1| What are you currently doing?| A lot of the smaller words are clear answers to the question while the biggest words are a little bit more difficult to interpret or could be weighted to have a lower score| \n",
    "|essay 2| What are you good at?| Users say they're good at listening and that they have a great smile and laugh|\n",
    "|essay 3| Describe yourself physically| Users talk about their eyes, hair, smile, and height|\n",
    "|essay 4|What are your favorite books, movies, tv shows, music, food, etc | Not a very meaningful result. More useful for guessing the essay question.|\n",
    "|essay 5| You can't live without...|Users cannot live without their cellphone, money, gym, job, god, sports, fun. Not sure though what it means that 'good' is top keyword|\n",
    "|essay 6| What do you think about?| Users think about life and the future|\n",
    "|essay 7| What is a typical friday night for you?| Users are with their friends on friday nights|\n",
    "|essay 8| Share something private| Users say 'message/ask me about private things and ill share it with you, but I won't share it here on my public profile'. From the previous section, we can also see that this is the least answered essay question.|\n",
    "|essay 9| You would like me if...| Doesn't seem like a very meaningful result|"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fifth-mumbai",
   "metadata": {},
   "source": [
    "### Further NLP Practice"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "verbal-account",
   "metadata": {},
   "source": [
    "There is still additional NLP analysis that we will not explore here but can definitely be applied. For example, we can see in essay0 the top keywords are 'love' and 'like'. _What do users really mean when they use the word 'love'? Is it 'making love' or 'looking for love'? Are they using 'love' and 'like' interchangeably?_\n",
    "\n",
    "Additional NLP:\n",
    "- Filter keywords by Part of Speech (noun, adjective, verb, adverb)\n",
    "- Contextualize keywords by investigating the words which follow and precede them\n",
    "- Make use of n-grams instead of one-word terms. The terms in our tf-idf model are one word long, but we can also use pairs of words, or groups of three words, and even more. You could also try skip-grams.\n",
    "- Make use of other Word Embedding Models, an AI model that maps words into vectors. Tf-idf was only one example of a simple word embedding model. Each element of the vector could be different properties of the word, such as its part of speech, number of syllables, number of vowels, number of consonants, what word follows it, what word precedes it, location of the word in the paragraph, and much more. \n",
    "- Input the tf-idf results to a Latent Dirichlet Allocation (LDA) Model. Manually assign labels to your LDA topics. Plot the most common topics in the corpus, as well as the most common words per topic,  from your LDA result."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "latin-bacteria",
   "metadata": {},
   "source": [
    "## Visualization Recap"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "settled-momentum",
   "metadata": {},
   "source": [
    "**In this section, we visualized the following:**\n",
    "- We visualized our numerical features using box plots and histograms\n",
    "- We made an interactive treemap of our categorical features\n",
    "- We visualized our categorical features using donut plots\n",
    "- Using bar plots we visualized the top spoken languages and top unfilled optional fields among user profiles\n",
    "- We visualized the essay question responses using Natural Language Processing and wordclouds\n",
    "\n",
    "**From our Numerical Features we learned:**\n",
    "\n",
    "| Feature        | Comment      |\n",
    "| :------------- | :---------- |\n",
    "| Age | The median age is 30. The distribution is right-skewed. Most users are young and working adults.|\n",
    "|  Height        | Most heights range between 59 and 78 in (4.9 - 6.5 ft) with a median of 68in(5.67ft). The distribution appears normal. |\n",
    "|  Income        | The median income is \\\\$50k. A quarter of all incomes are $25k. Most income distributions are log-normal (if the ultra-wealthy are not included), and this is no different. |\n",
    "|optional_%unfilled| Half of all users don't bother to fill 12% - 30% of optional fields. A quarter of users are below that range and a quarter of users are above that range.|\n",
    "\n",
    "**From our Categorical Features we learned the stereotypical profile is:**\n",
    "- not fat or skinny\n",
    "- has drinks socially\n",
    "- doesn't do drugs\n",
    "- finished college\n",
    "- white ethnicity\n",
    "- varied in terms of possible job background\n",
    "- doesn't have kids\n",
    "- straight\n",
    "- male\n",
    "- doesn't smoke\n",
    "- single\n",
    "- lives in San Francisco, California\n",
    "- eats anything\n",
    "- agnostic or atheist\n",
    "- likes dogs and/or cats but doesn't have them\n",
    "- not multiracial\n",
    "- speaks only one language\n",
    "\n",
    "We also discovered that our sample has a high risk of bias. In our sample data which is dated from 2012, although OKCupid was founded in 2004, practically everyone lives in California and half of that in the City of San Francisco.\n",
    "\n",
    "**With the use of bar plots we learned:**\n",
    "- Everyone speaks English\n",
    "- Among the information users don't want to share, 'income' is the highest, with an 80% overwhelming majority, followed by 'offspring'(whether they have children) at 60%.\n",
    "\n",
    "**From our Essay Features we learned:**\n",
    "\n",
    "|Essay Number| Personal best guess of the question asked| Comment on tf-idf Result|\n",
    "| :------------- | :---------- | :---------- |\n",
    "|essay 0| Describe yourself| Users use this essay question to talk about what they like, love, and the qualities of who(someone) they're looking for|\n",
    "|essay 1| What are you currently doing?| A lot of the smaller words are clear answers to the question while the biggest words are a little bit more difficult to interpret or could be weighted to have a lower score| \n",
    "|essay 2| What are you good at?| Users say they're good at listening and that they have a great smile and laugh|\n",
    "|essay 3| Describe yourself physically| Users talk about their eyes, hair, smile, and height|\n",
    "|essay 4|What are your favorite books, movies, tv shows, music, food, etc | Not a very meaningful result. More useful for guessing the essay question.|\n",
    "|essay 5| You can't live without...|Users cannot live without their cellphone, money, gym, job, god, sports, fun. Not sure though what it means that 'good' is the top keyword|\n",
    "|essay 6| What do you think about?| Users think about life and the future|\n",
    "|essay 7| What is a typical friday night for you?| Users are with their friends on friday nights|\n",
    "|essay 8| Share something private| Users say 'message/ask me about private things and ill share it with you, but I won't share it here on my public profile'. From the previous section, we can also see that this is the least answered essay question.|\n",
    "|essay 9| You would like me if...| Doesn't seem like a very meaningful result|\n",
    "\n",
    "**In this section, we made the decision to strip outliers of _age_ and _height_:**<br><br>\n",
    "Outliers have the potential to increase memory usage, variance, and training time. The current objective is to make a predictive model that works. If that objective is accomplished, we have the option of reiterating on this project to incorporate outliers."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "possible-organizer",
   "metadata": {},
   "source": [
    "# Feature Engineering Part 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "gorgeous-steering",
   "metadata": {},
   "source": [
    "We need to do even more feature engineering before we go into Machine Learning. All our features have to be properly formatted and expanded/encoded. Any value that is not a number will not be understood by our ML training algorithm."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fuzzy-assessment",
   "metadata": {},
   "source": [
    "We will make a backup copy of our data at this point, so that we can reset back to this checkpoint if we want to undo any modifications. Let's also drop our languages sparse matrix. Previously we didn't include the fluency descriptors in our sparse matrix for our visualization. Later, when one-hot encoding, we will make a new sparse matrix for languages which contains the fluency descriptors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "personal-bowling",
   "metadata": {},
   "outputs": [],
   "source": [
    "expanded_df_backup = df.drop(columns = languages).copy(deep = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "bulgarian-locator",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = expanded_df_backup.copy(deep=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "amazing-penalty",
   "metadata": {},
   "source": [
    "Let's convert *last_online* from a string to a datetime format and split it up."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "threaded-harvest",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['last_online'] = pd.to_datetime(df.last_online, format = \"%Y-%m-%d-%H-%M\")\n",
    "df['last_online_year'] = df.last_online.dt.year\n",
    "df['last_online_month'] = df.last_online.dt.month\n",
    "df['last_online_day'] = df.last_online.dt.day\n",
    "df['last_online_hour'] = df.last_online.dt.hour"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "decimal-zimbabwe",
   "metadata": {},
   "source": [
    "Let's drop columns that we have created splits from. If we need to use them as target variables for prediction we can recover any of them from our backup dataframe. Let's drop _income_ because 80% of it's values are missing. Let's also drop _num_ethnicities_ and _optional__%unfilled_."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "norman-spring",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop(columns = ['diet', 'location', 'offspring', 'religion', 'sign', 'pets', 'income', 'last_online',\n",
    "                        'num_ethnicities', 'optional_%unfilled'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "younger-killer",
   "metadata": {},
   "source": [
    "Let's apply one-hot encoding to our categorical variables. We will also encode a category to represent the null values of each feature, so that our ML model will include the user's decisions to share particular information when making predictions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "directed-breakdown",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before one-hot encoding:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 59811 entries, 0 to 59945\n",
      "Data columns (total 42 columns):\n",
      " #   Column              Non-Null Count  Dtype  \n",
      "---  ------              --------------  -----  \n",
      " 0   age                 59811 non-null  int64  \n",
      " 1   body_type           54538 non-null  object \n",
      " 2   drinks              56846 non-null  object \n",
      " 3   drugs               45755 non-null  object \n",
      " 4   education           53211 non-null  object \n",
      " 5   essay0              54351 non-null  object \n",
      " 6   essay1              52275 non-null  object \n",
      " 7   essay2              50210 non-null  object \n",
      " 8   essay3              48375 non-null  object \n",
      " 9   essay4              49318 non-null  object \n",
      " 10  essay5              49010 non-null  object \n",
      " 11  essay6              46085 non-null  object \n",
      " 12  essay7              47404 non-null  object \n",
      " 13  essay8              40636 non-null  object \n",
      " 14  essay9              47245 non-null  object \n",
      " 15  ethnicity           54159 non-null  object \n",
      " 16  height              59811 non-null  float64\n",
      " 17  job                 51641 non-null  object \n",
      " 18  orientation         59811 non-null  object \n",
      " 19  sex                 59811 non-null  object \n",
      " 20  smokes              54320 non-null  object \n",
      " 21  speaks              59761 non-null  object \n",
      " 22  status              59811 non-null  object \n",
      " 23  diet_adherence      35481 non-null  object \n",
      " 24  diet_type           35481 non-null  object \n",
      " 25  city                59811 non-null  object \n",
      " 26  state/country       59811 non-null  object \n",
      " 27  offspring_want      24334 non-null  object \n",
      " 28  offspring_attitude  9711 non-null   object \n",
      " 29  religion_type       39631 non-null  object \n",
      " 30  religion_attitude   39631 non-null  object \n",
      " 31  sign_type           48787 non-null  object \n",
      " 32  sign_attitude       48787 non-null  object \n",
      " 33  dog_preference      28880 non-null  object \n",
      " 34  cat_preference      21293 non-null  object \n",
      " 35  has_dogs            39931 non-null  float64\n",
      " 36  has_cats            39931 non-null  float64\n",
      " 37  num_languages       59811 non-null  int64  \n",
      " 38  last_online_year    59811 non-null  int64  \n",
      " 39  last_online_month   59811 non-null  int64  \n",
      " 40  last_online_day     59811 non-null  int64  \n",
      " 41  last_online_hour    59811 non-null  int64  \n",
      "dtypes: float64(3), int64(6), object(33)\n",
      "memory usage: 19.6+ MB\n"
     ]
    }
   ],
   "source": [
    "print('Before one-hot encoding:')\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "objective-meeting",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.get_dummies(df, columns = ['body_type', 'drinks', 'drugs', 'education', 'job', 'orientation', 'sex',\n",
    "                                           'smokes', 'status', 'diet_adherence', 'diet_type', 'city', 'state/country',\n",
    "                                           'offspring_want', 'offspring_attitude', 'religion_type', 'religion_attitude', \n",
    "                                           'sign_type', 'sign_attitude', 'dog_preference', 'cat_preference', 'has_dogs',\n",
    "                                           'has_cats',], \n",
    "                    sparse=True,\n",
    "                    dummy_na=True)\n",
    "\n",
    "df.rename(columns = {'sex_m':'sex'}, inplace = True)\n",
    "df = df.drop(columns = ['sex_f'])\n",
    "\n",
    "def string_dummies(df, series, sep):\n",
    "    if df[series].isna().any():\n",
    "        df[series + '_nan'] = df[series].isna().astype('int64')\n",
    "    temp_df = df[series].str.get_dummies(sep).add_prefix(str(series) + '_')\n",
    "    df = pd.concat([df, temp_df], axis = 1)\n",
    "    return df.drop(columns = [str(series)])\n",
    "\n",
    "selection = ['ethnicity', 'speaks']\n",
    "sep_list = [', ', ', ']\n",
    "for series, sep in zip (selection, sep_list):    \n",
    "    df = string_dummies(df, series, sep)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "worst-holder",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "After one-hot encoding:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 59811 entries, 0 to 59945\n",
      "Columns: 737 entries, age to speaks_yiddish (poorly)\n",
      "dtypes: Sparse[uint8, 0](407), float64(1), int64(319), object(10)\n",
      "memory usage: 157.5+ MB\n"
     ]
    }
   ],
   "source": [
    "print('After one-hot encoding:')\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "nasty-notice",
   "metadata": {},
   "source": [
    "Let's make our dataframe have uniform datatypes. Just ignore the datatype of the essays for now (the ten object coumns)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "metric-salem",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 59811 entries, 0 to 59945\n",
      "Columns: 737 entries, age to speaks_yiddish (poorly)\n",
      "dtypes: Sparse[uint8, 0](727), object(10)\n",
      "memory usage: 14.3+ MB\n"
     ]
    }
   ],
   "source": [
    "df['height'] = df.height.astype('int64')\n",
    "for each in df.select_dtypes(include=['int64']).columns.to_list():\n",
    "    df[each] = pd.arrays.SparseArray(df[each].values, dtype='uint8')\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "restricted-viewer",
   "metadata": {},
   "source": [
    "We are now ready to move on to Machine Learning."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "earlier-corrections",
   "metadata": {},
   "source": [
    "## Feature Engineering Part 2 Recap"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "complete-destiny",
   "metadata": {},
   "source": [
    "In this Section we accomplished the following:\n",
    "* Converted _last_online_ into datetime format and split it up by hour, day, year, month\n",
    "* Dropped columns that, for various reasons, we will not include in the Machine Learning Section\n",
    "* Applied one-hot encoding to our categorical features\n",
    "* Converted the datatypes of our dataframe to become uniform, specifically they are now Sparse[uint8, 0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "varying-logistics",
   "metadata": {},
   "source": [
    "# Machine Learning to Predict Gender"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "offshore-clinic",
   "metadata": {},
   "source": [
    "We will evaluate and compare two different Machine Learning Models to predict gender."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "absent-regression",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Now is a good time to backup the dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "fifteen-region",
   "metadata": {},
   "outputs": [],
   "source": [
    "sparse_essay_df = df.copy(deep = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "multiple-wedding",
   "metadata": {},
   "outputs": [],
   "source": [
    "sparse_essay_df.to_csv('ml_ready_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "quick-buffer",
   "metadata": {},
   "outputs": [],
   "source": [
    "def feature_selection_to_list(df, cat_selection, numeric_selection):\n",
    "    categorical_feats = []\n",
    "    for each in cat_selection:\n",
    "        categorical_feats = categorical_feats + df.loc[:, df.columns.str.startswith(each)].columns.to_list()\n",
    "    return categorical_feats + numeric_selection"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "absent-delhi",
   "metadata": {},
   "source": [
    "## Gender Classification with a Logistic Regression Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "framed-catalyst",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train score: 0.893976759739174\n",
      "Test score: 0.8878207807406169\n"
     ]
    },
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          "text": "Linear coefficient"
         }
        }
       }
      },
      "text/html": [
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   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "from scipy.sparse import coo_matrix\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "import plotly.graph_objects as go\n",
    "\n",
    "def model_with_logistic_regression(feature_selection, target_selection, predictor_legend, use_csr_feats = False,\n",
    "                                  swap_legend_colors = False):\n",
    "    #Select predictors and target\n",
    "    predictors = sparse_essay_df[feature_selection].sparse.to_dense()\n",
    "    if use_csr_feats:\n",
    "        predictors = predictors.sparse.to_coo()\n",
    "        predictors = predictors.tocsr()\n",
    "    target = sparse_essay_df[target_selection]\n",
    "\n",
    "    X_train, X_test, y_train, y_test = train_test_split(predictors, target, test_size = 0.2)\n",
    "\n",
    "    # Scale the feature data so it has mean = 0 and standard deviation = 1\n",
    "    scaler = StandardScaler()\n",
    "    X_train = scaler.fit_transform(X_train)\n",
    "    X_test = scaler.transform(X_test)\n",
    "    # Create and train the model\n",
    "    model = LogisticRegression()\n",
    "    model.fit(X_train, y_train)\n",
    "\n",
    "    print('Train score: ' + str(model.score(X_train, y_train)))\n",
    "    print('Test score: ' + str(model.score(X_test, y_test)))\n",
    "\n",
    "    # Analyze the predictor coefficients\n",
    "    if swap_legend_colors:\n",
    "        colors = [predictor_legend[1] if c > 0 else predictor_legend[0] for c in model.coef_[0]]\n",
    "    else:\n",
    "        colors = [predictor_legend[0] if c > 0 else predictor_legend[1] for c in model.coef_[0]]\n",
    "\n",
    "    fig = px.bar(\n",
    "        y=predictors.columns,\n",
    "        x=abs(model.coef_[0]), \n",
    "        color=colors,\n",
    "        color_discrete_sequence=['red', 'blue'],\n",
    "        labels=dict(x='Predictor', y='Linear coefficient'),\n",
    "        title='Top 20 predictors',\n",
    "    )\n",
    "    fig.update_yaxes(categoryorder = \"total ascending\", range=(len(predictors.columns) - 20.6, len(predictors.columns)))\n",
    "    fig.show()\n",
    "\n",
    "cat_selection = ['body_type', 'drinks', 'drugs', 'education', 'job', 'orientation',\n",
    "                'smokes', 'status', 'diet_adherence', 'diet_type', 'last_online',\n",
    "                'offspring_want', 'offspring_attitude', 'religion_type', 'religion_attitude', \n",
    "                'sign_type', 'sign_attitude', 'dog_preference', 'cat_preference', 'has_dogs',\n",
    "                'has_cats', 'ethnicity', 'speaks']\n",
    "numeric_selection = ['age', 'height']\n",
    "feature_selection = feature_selection_to_list(sparse_essay_df, cat_selection, numeric_selection)\n",
    "predictor_legend = ['Male Predictor', 'Female Predictor']\n",
    "model_with_logistic_regression(feature_selection, target_selection = 'sex', use_csr_feats = False, predictor_legend = predictor_legend)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "executive-myanmar",
   "metadata": {},
   "source": [
    "*Height* and *body_type_curvy* are our top predictors. Probably because men are taller than women on average, and because men are not likely to describe themselves as curvy whereas women are.\n",
    "\n",
    "**AI Ethics:** A model like this highlights the ethical consideration we must take when developing AI. For example, one of the predictors is *job_computer / hardware / software*. This could be misused to discriminate by gender, proclaiming that one gender is not fit for working in a technical computer job. **Never be hasty to deploy a model that will be used on people.**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "integrated-summit",
   "metadata": {},
   "source": [
    "## Gender Classification with a Decision Tree Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "accessory-lender",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The best result is attained when the Decision Tree Model is stopped at a tree depth of 6, providing a test accuracy of 86.38%\n"
     ]
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "dec_tree_df = sparse_essay_df.copy()\n",
    "\n",
    "cat_selection = ['body_type', 'drinks', 'drugs', 'education', 'orientation',\n",
    "                'smokes', 'status', 'diet_adherence', 'diet_type', 'job', 'last_online',\n",
    "                'offspring_want', 'offspring_attitude', 'religion_attitude', 'religion_type', \n",
    "                'sign_type', 'sign_attitude', 'dog_preference', 'cat_preference', 'has_dogs',\n",
    "                'has_cats', 'ethnicity', 'speaks']\n",
    "numeric_selection = ['age', 'height']\n",
    "feature_selection = feature_selection_to_list(dec_tree_df, cat_selection, numeric_selection)\n",
    "\n",
    "target = dec_tree_df['sex']\n",
    "predictors = dec_tree_df[feature_selection]\n",
    "\n",
    "train_data, test_data, train_labels, test_labels = train_test_split(predictors, target)\n",
    "\n",
    "scores = []\n",
    "for i in range(1, 18):\n",
    "  tree = DecisionTreeClassifier(max_depth = i)\n",
    "  tree.fit(train_data, train_labels)\n",
    "  score = tree.score(test_data, test_labels)\n",
    "  scores.append(score)\n",
    "\n",
    "plt.plot(range(1, 18), scores, marker='o')\n",
    "plt.xlabel('Tree Depth')\n",
    "plt.ylabel('Test Accuracy')\n",
    "plt.show()\n",
    "print(\"The best result is attained when the Decision Tree Model is stopped at a tree depth of {}, providing a test accuracy of {:.2f}%\".format(scores.index(max(scores)), max(scores)*100))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "worthy-launch",
   "metadata": {},
   "source": [
    "## Machine Learning to predict Gender Recap"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "civic-damage",
   "metadata": {},
   "source": [
    "In this section we accomplished the following:\n",
    "* Trained a Logistic Regression model to predict gender with an accuracy of about 89%\n",
    "    * *height* and *body_type_curvy* were the top predictors of gender\n",
    "* Trained a Decision Tree model to predict gender with an accuracy of about 86%"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "amateur-spelling",
   "metadata": {},
   "source": [
    "# Date Recommendation using K-Means Clustering"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "martial-young",
   "metadata": {},
   "source": [
    "Clustering, is a technique which groups similar data points together. Let's use this to group similar people together and recommend who you should date. People in the same cluster as you are the people who we will recommend."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "future-chase",
   "metadata": {},
   "source": [
    "## Feature Selection"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "differential-tracy",
   "metadata": {},
   "source": [
    "We start by reviewing the features we have on hand. Which, among the features, would you want your date to have in common with you?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "internal-spectrum",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 59811 entries, 0 to 59945\n",
      "Data columns (total 48 columns):\n",
      " #   Column              Non-Null Count  Dtype  \n",
      "---  ------              --------------  -----  \n",
      " 0   age                 59811 non-null  int64  \n",
      " 1   body_type           54538 non-null  object \n",
      " 2   diet                35481 non-null  object \n",
      " 3   drinks              56846 non-null  object \n",
      " 4   drugs               45755 non-null  object \n",
      " 5   education           53211 non-null  object \n",
      " 6   essay0              54351 non-null  object \n",
      " 7   essay1              52275 non-null  object \n",
      " 8   essay2              50210 non-null  object \n",
      " 9   essay3              48375 non-null  object \n",
      " 10  essay4              49318 non-null  object \n",
      " 11  essay5              49010 non-null  object \n",
      " 12  essay6              46085 non-null  object \n",
      " 13  essay7              47404 non-null  object \n",
      " 14  essay8              40636 non-null  object \n",
      " 15  essay9              47245 non-null  object \n",
      " 16  ethnicity           54159 non-null  object \n",
      " 17  height              59811 non-null  float64\n",
      " 18  income              11456 non-null  float64\n",
      " 19  job                 51641 non-null  object \n",
      " 20  last_online         59811 non-null  object \n",
      " 21  location            59811 non-null  object \n",
      " 22  offspring           24334 non-null  object \n",
      " 23  orientation         59811 non-null  object \n",
      " 24  pets                39931 non-null  object \n",
      " 25  religion            39631 non-null  object \n",
      " 26  sex                 59811 non-null  object \n",
      " 27  sign                48787 non-null  object \n",
      " 28  smokes              54320 non-null  object \n",
      " 29  speaks              59761 non-null  object \n",
      " 30  status              59811 non-null  object \n",
      " 31  diet_adherence      35481 non-null  object \n",
      " 32  diet_type           35481 non-null  object \n",
      " 33  city                59811 non-null  object \n",
      " 34  state/country       59811 non-null  object \n",
      " 35  offspring_want      24334 non-null  object \n",
      " 36  offspring_attitude  9711 non-null   object \n",
      " 37  religion_type       39631 non-null  object \n",
      " 38  religion_attitude   39631 non-null  object \n",
      " 39  sign_type           48787 non-null  object \n",
      " 40  sign_attitude       48787 non-null  object \n",
      " 41  dog_preference      28880 non-null  object \n",
      " 42  cat_preference      21293 non-null  object \n",
      " 43  has_dogs            39931 non-null  float64\n",
      " 44  has_cats            39931 non-null  float64\n",
      " 45  num_ethnicities     54159 non-null  float64\n",
      " 46  optional_%unfilled  59811 non-null  float64\n",
      " 47  num_languages       59811 non-null  int64  \n",
      "dtypes: float64(6), int64(2), object(40)\n",
      "memory usage: 22.4+ MB\n"
     ]
    }
   ],
   "source": [
    "expanded_df_backup.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "forward-commercial",
   "metadata": {},
   "source": [
    "After asking someone which features they would want to have in common with them, the chosen features are:\n",
    "* Drugs\n",
    "* Diet\n",
    "* Pets\n",
    "* Orientation\n",
    "* Religion (attitude only)\n",
    "\n",
    "Let's isolate that subset of features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "economic-suite",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(59811, 37)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clustering_df = sparse_essay_df.copy()\n",
    "cat_selection = ['drugs', 'orientation',\n",
    "                'diet_adherence', 'diet_type','religion_attitude', 'dog_preference', 'cat_preference', 'has_dogs',\n",
    "                'has_cats']\n",
    "numeric_selection = []\n",
    "feature_selection = feature_selection_to_list(clustering_df, cat_selection, numeric_selection)\n",
    "clustering_df = clustering_df[feature_selection]\n",
    "\n",
    "#Conversion to Scipy csr_matrix\n",
    "clustering_coo = clustering_df.sparse.to_coo()\n",
    "clustering_csr = clustering_coo.tocsr()\n",
    "clustering_csr.get_shape()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "talented-person",
   "metadata": {},
   "source": [
    "## Choosing a value of k"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "usual-copper",
   "metadata": {},
   "source": [
    "Now that we have our subset let's search for the best number of k clusters to use in our model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "tropical-pressing",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Recommended setting for training Kmeans on Windows\n",
    "import os\n",
    "os.environ[\"OMP_NUM_THREADS\"] = \"1\"\n",
    "\n",
    "from sklearn.cluster import KMeans\n",
    "\n",
    "execute = False\n",
    "if execute:\n",
    "    num_clusters = list(range(1,200))\n",
    "    inertias= []\n",
    "    for i in num_clusters:\n",
    "      model = KMeans(n_clusters = i)\n",
    "      model.fit(clustering_csr)\n",
    "      inertias.append(model.inertia_)\n",
    "\n",
    "    plt.plot(num_clusters, inertias, '-o')\n",
    "    plt.xlabel('Number of Clusters (k)')\n",
    "    plt.ylabel('Inertia')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "golden-collapse",
   "metadata": {},
   "source": [
    "The Inertia vs k graph we now have below took 5 hours to produce (hence the default setting above to skip execution of the code snippet). Inertia, is a metric which represents how spaced out the points of a cluster are relative to its centroid. A line has been drawn over the tail end of the graph so that we can clearly mark where the graph becomes linear. The specific point where the graph becomes linear is known as the elbow point, and is the number of clusters that we should use."
   ]
  },
  {
   "attachments": {
    "K_Clusters_evaluation_annotated-2.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "scientific-bernard",
   "metadata": {},
   "source": [
    "![K_Clusters_evaluation_annotated-2.png](attachment:K_Clusters_evaluation_annotated-2.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "light-motorcycle",
   "metadata": {},
   "source": [
    "k = 100 is where the linearity begins. Let's create the model we will use for clustering with k = 100."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "dangerous-awareness",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = KMeans(n_clusters = 100)\n",
    "model.fit(clustering_csr)\n",
    "labels = model.predict(clustering_csr)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "brutal-dinner",
   "metadata": {},
   "source": [
    "Let's investigate the uniformity of our cluster distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "viral-sentence",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ser_labels  = pd.Series(labels)\n",
    "ser_labels_props = ser_labels.value_counts()\n",
    "plt.figure(figsize = (16,9))\n",
    "plt.pie(x=ser_labels_props.values, labels = ser_labels_props.index,\n",
    "                wedgeprops=dict(width=0.10,\n",
    "                                edgecolor=\"k\",\n",
    "                                linewidth=0.7))\n",
    "plt.text(0, 0, 'Cluster Distribution', \n",
    "                 horizontalalignment = 'center',\n",
    "                 verticalalignment = 'center',\n",
    "                 fontsize = 20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "french-ethnic",
   "metadata": {},
   "source": [
    "The clusters are somewhat distributed across users. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "relevant-thriller",
   "metadata": {},
   "source": [
    "## Date Match Recommendations (only interactive if opened with Jupyter Notebooks and required packages are installed)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "desirable-surgery",
   "metadata": {},
   "source": [
    "Let's discover who you can date! Select from the dropdown lists to enter your information. Click the 'Run Interact' button to predict your cluster number and display the profile of a potential date. Your cluster contains users that are similar to you - someone you might want to date! Click Run to see another random profile from your cluster.\n",
    "\n",
    "* Note that as an experiment, null values have been included as their own category. The model groups people who similarly leave a lot of fields blank. The values of 'nan' or 'None' or 'No Prefix' means that you are not sharing information for that particular field. Go ahead and try out 'nan' and see how that affects your matches."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "useful-length",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "20395e597cff45c187cab60183e27528",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='sex', options=('Male', 'Female'), value='Male'), Dropdown(descript…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function __main__.make_profile(sex, drugs, orientation, diet_adherence, diet_type, religion_attitude, dog_preference, cat_preference, has_dogs, has_cats, show_same_gender)>"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from ipywidgets import interact_manual\n",
    "import random\n",
    "\n",
    "def make_profile(sex, drugs, orientation, diet_adherence, diet_type, religion_attitude,\n",
    "                 dog_preference, cat_preference, has_dogs, has_cats, show_same_gender):\n",
    "    \n",
    "    user_info = [drugs, orientation, diet_adherence, diet_type, religion_attitude,\n",
    "                 dog_preference, cat_preference, has_dogs, has_cats]\n",
    "    user_dict = {}\n",
    "    for each in clustering_df.columns.to_list():\n",
    "         user_dict[each] = [0]\n",
    "    for each in user_info:\n",
    "        user_dict[each] = [1]\n",
    "    user_df = pd.DataFrame(data=user_dict, index = ['You'])\n",
    "    sparse_user_df = user_df.copy()\n",
    "    for each in sparse_user_df.columns.to_list():\n",
    "        sparse_user_df[each] = pd.arrays.SparseArray(sparse_user_df[each].values, dtype='uint8')\n",
    "        \n",
    "    sparse_user_df = sparse_user_df.sparse.to_coo()\n",
    "    sparse_user_df = sparse_user_df.tocsr()\n",
    "    \n",
    "    user_cluster_label = model.predict(sparse_user_df)\n",
    "    user_cluster = np.where(labels == user_cluster_label)[0]\n",
    "    print(\"Your cluster is {}.\\nThere are {} users in your cluster.\".format(user_cluster_label, len(user_cluster)))\n",
    "    \n",
    "    if show_same_gender == False:\n",
    "        user_sex_dict = {'Male':'m', \"Female\":'f'}\n",
    "        user_sex = user_sex_dict[sex]\n",
    "        #Look for an opposite gender\n",
    "        while user_sex == user_sex_dict[sex]:\n",
    "            rand_index = random.randint(0, len(user_cluster))\n",
    "            rand_user = user_cluster[rand_index]\n",
    "            user_sex = expanded_df_backup.iloc[rand_user]['sex']\n",
    "    else:\n",
    "        rand_index = random.randint(0, len(user_cluster))\n",
    "        rand_user = user_cluster[rand_index]       \n",
    "\n",
    "    print(\"Is this person dateable? Press Run again to see a new recommendation.\\n\")\n",
    "    show_user_data(expanded_df_backup.iloc[:,0:31], rand_user)\n",
    "\n",
    "interact_manual(\n",
    "    make_profile,\n",
    "    sex = ['Male', 'Female'],\n",
    "    drugs = feature_selection_to_list(clustering_df, ['drugs'], []),\n",
    "    orientation = feature_selection_to_list(clustering_df, ['orientation'], []),\n",
    "    diet_adherence = feature_selection_to_list(clustering_df, ['diet_adherence'], []),\n",
    "    diet_type = feature_selection_to_list(clustering_df, ['diet_type'], []),\n",
    "    religion_attitude = feature_selection_to_list(clustering_df, ['religion_attitude'], []),\n",
    "    dog_preference = feature_selection_to_list(clustering_df, ['dog_preference'], []),\n",
    "    cat_preference = feature_selection_to_list(clustering_df, ['cat_preference'], []),\n",
    "    has_dogs = feature_selection_to_list(clustering_df, ['has_dogs'], []),\n",
    "    has_cats = feature_selection_to_list(clustering_df, ['has_cats'], []),\n",
    "    show_same_gender = True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "racial-footage",
   "metadata": {},
   "source": [
    "### Static Image Preview"
   ]
  },
  {
   "attachments": {
    "datrecommender2.jpg": {
     "image/jpeg": 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    }
   },
   "cell_type": "markdown",
   "id": "bright-fraud",
   "metadata": {},
   "source": [
    "![datrecommender2.jpg](attachment:datrecommender2.jpg)"
   ]
  },
  {
   "attachments": {
    "Date%20Recommender%203.jpg": {
     "image/jpeg": 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    }
   },
   "cell_type": "markdown",
   "id": "continued-likelihood",
   "metadata": {},
   "source": [
    "![Date%20Recommender%203.jpg](attachment:Date%20Recommender%203.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "higher-oklahoma",
   "metadata": {},
   "source": [
    "## Date Recommendation using K-Means Clustering Recap"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "center-lying",
   "metadata": {},
   "source": [
    "In this section, we accomplished the following:\n",
    "* Selected features for our model, on the basis of wanting a potential date to be similar for those particular features\n",
    "* Used the 'elbow method' for selecting a value of k for our k-means clustering model\n",
    "* Created an interactive interface for presenting profiles of suggested users to date based on input user data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "regulation-performance",
   "metadata": {},
   "source": [
    "# You've reached the end of this article. Thanks for reading it! Part 2 is [here](https://nbviewer.jupyter.org/github/max-torch/OKCupid_Codecademy_Portfolio/blob/main/ml_revisited.ipynb)."
   ]
  }
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