{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Drift detection and characterization\n",
    "\n",
    "This tutorial shows how to implement drift detection, and a limited characterization, on time-stamped data. This data can be from almost any quantum circuit based experiment on one or more qubits, as long as the data is taken using a suitable time-ordering of the experiments, and the data is recorded as a time series. For example, possible experiments include suitably time-ordered GST, RPE, Ramsey or RB experiments.\n",
    "\n",
    "This notebook is an introduction to these tools, and it will be either augmented with further notebooks, or updated to be more comprehensive, at a later date."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "from __future__ import print_function\n",
    "\n",
    "# Importing the drift module is essential\n",
    "from pygsti.extras import drift\n",
    "\n",
    "# Importing all of pyGSTi is optional, but often useful.\n",
    "import pygsti"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## A quick overview\n",
    "We now give a quick overview of the drift detection and characterization methods in the `drift` module. Further details are given later in this tutorial. As we demonstrate below, the analysis can be implemented with only two steps:\n",
    "\n",
    "1. Import some timestamped data, into a `pyGSTi` dataset.\n",
    "2. Pass this data to a single analysis function, `drift.do_basic_drift_characterization()`.\n",
    "\n",
    "Here we demonstrate this with time series GST data, on the $G_i$, $G_x$, $G_y$ gateset, generated from a simulation (the code required to run these simulations is not currently available in `pyGSTi`). In this simulation the $G_i$ gate has low-frequency drift, the $G_x$ has high-frequency drift, and the $G_y$ gate is drift-free (where \"low\" and \"high\" frequency are with respect to the sample rate). More details on the input data format are given later."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading tutorial_files/timeseries_data.txt: 100%\n"
     ]
    }
   ],
   "source": [
    "ds = pygsti.io.load_tddataset(\"tutorial_files/timeseries_data.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# This takes 5 - 10 minutes, but can be sped up a lot with more user input (see below)\n",
    "results_gst = drift.do_basic_drift_characterization(ds)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "** Thats it! **\n",
    "\n",
    "Everything has been calculated, and we can now look at the results. \n",
    "\n",
    "** Is there any detectable drift? **\n",
    "\n",
    "One useful result is printed below: a yes/no outcome for whether or not drift is detected. This is calculated using multiple statistical tests on the data at a specified global confidence level (which defaults to 0.95 when no user-specified value is passed to `drift.do_basic_drift_characterization`). That is, here there is a probability of at most 0.05 that this function will report drift when there is none."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Statistical tests set at a global confidence level of: 0.95\n",
      "Result: The 'no drift' hypothesis *is* rejected.\n"
     ]
    }
   ],
   "source": [
    "results_gst.any_drift_detect()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "** We can plot power spectra **\n",
    "\n",
    "These spectra *should* be flat - up to statistical flucations, due to finite-sampling noise, around the mean noise level - if there is no drift. There are a range of power spectra that we can plot, but the most useful for an overview of the data is the \"global power spectrum\", obtained from averaging power spectra calculated from the individual data for each of the different gate sequences (again, details on exactly what this is are given later). This is plotted below. If there are peaks above the significance threshold, this power spectra provides statistically significant evidence of drift."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
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X0aBBA0JDQxk0aBDz5s3LVW7Dhg106dIFgM6dO/stk59t27bRrVs3oqOjadmy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\n+P9Sp94oZVklxgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c3f99e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results_gst.plot_power_spectrum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "** We can extract the drift frequencies **\n",
    "\n",
    "If we have detected drift, we would probably likely like to know the frequencies of the drift. This information can be extracted from the results object as shown below. All frequencies will be in Hz if the timestamps have been provided in seconds (again, details later). Note that these are the frequencies in the drifting outcome probabilities -- they are *not* directly the frequencies of drift in, say, a Hamiltonian parameter. However, they are closely related to those frequencies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.001 0.003 0.005 0.008 0.011 0.016 0.2  ]\n"
     ]
    }
   ],
   "source": [
    "print(results_gst.global_drift_frequencies)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "** Is there drift for a particular sequence? **\n",
    "\n",
    "There are individual power spectra for all of the sequences. E.g., if we are interested in whether the $G_xG_i^{128}G_y$ sequence shows signs of drift, we can plot the power spectrum:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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pc8ZxhpN+gr2eHgHqdxy2My1Cfl2waJbTH/VPY8xM57lY1jqZgh0i3B+Y5KyOegMwUUo+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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1067bdfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The gatestring we are interested\n",
    "gstr = pygsti.objects.GateString(None,'Gx(Gi)^128Gy') \n",
    "# We hand the gatestring to the plotting function\n",
    "results_gst.plot_power_spectrum(sequence=gstr,loc='upper right')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "** Box-plots for GST data **\n",
    "\n",
    "If the data is from GST experiments, or anything with a GST-like structure of germs and fudicials, we can create a box-plot which shows the maximum power in the spectrum for each sequence. This maximum power is a reasonable proxy for comparing how \"drifty\" the data from the different sequences appears to be. But note that the maximum power should *not* be used to directly compare the level of drift in two different datasets with different parameters, particularly if the number of timestamps is different - because this maximum power will increase with more data, for a fixed level of drift. More on this at a later date.\n",
    "\n",
    "In the plot below we see that the amount of drift appears to be increasing with sequence length, as would be expected with gate drift. Without performing a detailed analysis, by eye it is clear that the $G_i$ gate is the most drifty, that the $G_x$ gate has some drift, and that the data looks consistent with a drift-free $G_y$ gate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# This box constructs some GST objects, needed to create any sort of boxplot with GST data\n",
    "from pygsti.construction import std1Q_XYI # The gateset used with the GST data we imported\n",
    "\n",
    "# This manually specifies the germ and fiducial structure for the imported data.\n",
    "fiducial_strs = ['{}','Gx','Gy','GxGx','GxGxGx','GyGyGy']\n",
    "germ_strs = ['Gi','Gx','Gy','GxGy','GxGyGi','GxGiGy','GxGiGi','GyGiGi','GxGxGiGy','GxGyGyGi','GxGxGyGxGyGy']\n",
    "log2maxL = 9 # log2 of the maximum germ power\n",
    "\n",
    "# Below we use the maxlength, germ and fuducial lists to create the GST structures needed for box plots.\n",
    "fiducials = [pygsti.objects.GateString(None,fs) for fs in fiducial_strs]\n",
    "germs = [pygsti.objects.GateString(None,gs) for gs in germ_strs]\n",
    "max_lengths = [2**i for i in range(0,log2maxL)]\n",
    "gssList = pygsti.construction.make_lsgst_structs(std1Q_XYI.gates, fiducials, fiducials, germs, max_lengths)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
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this.length>t.length?this.clone().ixor(t):t.clone().ixor(this)},a.prototype.uxor=function(t){return this.length>t.length?this.clone().iuxor(t):t.clone().iuxor(this)},a.prototype.inotn=function(t){n(\"number\"==typeof t&&t>=0);var e=0|Math.ceil(t/26),r=t%26;this._expand(e),r>0&&e--;for(var i=0;i<e;i++)this.words[i]=67108863&~this.words[i];return r>0&&(this.words[i]=~this.words[i]&67108863>>26-r),this.strip()},a.prototype.notn=function(t){return this.clone().inotn(t)},a.prototype.setn=function(t,e){n(\"number\"==typeof t&&t>=0);var r=t/26|0,i=t%26;return this._expand(r+1),this.words[r]=e?this.words[r]|1<<i:this.words[r]&~(1<<i),this.strip()},a.prototype.iadd=function(t){var e;if(0!==this.negative&&0===t.negative)return this.negative=0,e=this.isub(t),this.negative^=1,this._normSign();if(0===this.negative&&0!==t.negative)return t.negative=0,e=this.isub(t),t.negative=1,e._normSign();var r,n;this.length>t.length?(r=this,n=t):(r=t,n=this);for(var i=0,a=0;a<n.length;a++)e=(0|r.words[a])+(0|n.words[a])+i,this.words[a]=67108863&e,i=e>>>26;for(;0!==i&&a<r.length;a++)e=(0|r.words[a])+i,this.words[a]=67108863&e,i=e>>>26;if(this.length=r.length,0!==i)this.words[this.length]=i,this.length++;else if(r!==this)for(;a<r.length;a++)this.words[a]=r.words[a];return this},a.prototype.add=function(t){var e;return 0!==t.negative&&0===this.negative?(t.negative=0,e=this.sub(t),t.negative^=1,e):0===t.negative&&0!==this.negative?(this.negative=0,e=t.sub(this),this.negative=1,e):this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},a.prototype.isub=function(t){if(0!==t.negative){t.negative=0;var e=this.iadd(t);return t.negative=1,e._normSign()}if(0!==this.negative)return this.negative=0,this.iadd(t),this.negative=1,this._normSign();var r=this.cmp(t);if(0===r)return this.negative=0,this.length=1,this.words[0]=0,this;var n,i;r>0?(n=this,i=t):(n=t,i=this);for(var a=0,o=0;o<i.length;o++)a=(e=(0|n.words[o])-(0|i.words[o])+a)>>26,this.words[o]=67108863&e;for(;0!==a&&o<n.length;o++)a=(e=(0|n.words[o])+a)>>26,this.words[o]=67108863&e;if(0===a&&o<n.length&&n!==this)for(;o<n.length;o++)this.words[o]=n.words[o];return this.length=Math.max(this.length,o),n!==this&&(this.negative=1),this.strip()},a.prototype.sub=function(t){return this.clone().isub(t)};var k=function(t,e,r){var n,i,a,o=t.words,s=e.words,l=r.words,u=0,c=0|o[0],h=8191&c,f=c>>>13,d=0|o[1],p=8191&d,m=d>>>13,g=0|o[2],v=8191&g,y=g>>>13,b=0|o[3],x=8191&b,_=b>>>13,w=0|o[4],M=8191&w,k=w>>>13,A=0|o[5],T=8191&A,S=A>>>13,E=0|o[6],L=8191&E,C=E>>>13,z=0|o[7],D=8191&z,I=z>>>13,P=0|o[8],O=8191&P,j=P>>>13,R=0|o[9],F=8191&R,N=R>>>13,B=0|s[0],U=8191&B,V=B>>>13,H=0|s[1],q=8191&H,G=H>>>13,Y=0|s[2],W=8191&Y,X=Y>>>13,Z=0|s[3],J=8191&Z,Q=Z>>>13,K=0|s[4],$=8191&K,tt=K>>>13,et=0|s[5],rt=8191&et,nt=et>>>13,it=0|s[6],at=8191&it,ot=it>>>13,st=0|s[7],lt=8191&st,ut=st>>>13,ct=0|s[8],ht=8191&ct,ft=ct>>>13,dt=0|s[9],pt=8191&dt,mt=dt>>>13;r.negative=t.negative^e.negative,r.length=19;var gt=(u+(n=Math.imul(h,U))|0)+((8191&(i=(i=Math.imul(h,V))+Math.imul(f,U)|0))<<13)|0;u=((a=Math.imul(f,V))+(i>>>13)|0)+(gt>>>26)|0,gt&=67108863,n=Math.imul(p,U),i=(i=Math.imul(p,V))+Math.imul(m,U)|0,a=Math.imul(m,V);var vt=(u+(n=n+Math.imul(h,q)|0)|0)+((8191&(i=(i=i+Math.imul(h,G)|0)+Math.imul(f,q)|0))<<13)|0;u=((a=a+Math.imul(f,G)|0)+(i>>>13)|0)+(vt>>>26)|0,vt&=67108863,n=Math.imul(v,U),i=(i=Math.imul(v,V))+Math.imul(y,U)|0,a=Math.imul(y,V),n=n+Math.imul(p,q)|0,i=(i=i+Math.imul(p,G)|0)+Math.imul(m,q)|0,a=a+Math.imul(m,G)|0;var yt=(u+(n=n+Math.imul(h,W)|0)|0)+((8191&(i=(i=i+Math.imul(h,X)|0)+Math.imul(f,W)|0))<<13)|0;u=((a=a+Math.imul(f,X)|0)+(i>>>13)|0)+(yt>>>26)|0,yt&=67108863,n=Math.imul(x,U),i=(i=Math.imul(x,V))+Math.imul(_,U)|0,a=Math.imul(_,V),n=n+Math.imul(v,q)|0,i=(i=i+Math.imul(v,G)|0)+Math.imul(y,q)|0,a=a+Math.imul(y,G)|0,n=n+Math.imul(p,W)|0,i=(i=i+Math.imul(p,X)|0)+Math.imul(m,W)|0,a=a+Math.imul(m,X)|0;var bt=(u+(n=n+Math.imul(h,J)|0)|0)+((8191&(i=(i=i+Math.imul(h,Q)|0)+Math.imul(f,J)|0))<<13)|0;u=((a=a+Math.imul(f,Q)|0)+(i>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(M,U),i=(i=Math.imul(M,V))+Math.imul(k,U)|0,a=Math.imul(k,V),n=n+Math.imul(x,q)|0,i=(i=i+Math.imul(x,G)|0)+Math.imul(_,q)|0,a=a+Math.imul(_,G)|0,n=n+Math.imul(v,W)|0,i=(i=i+Math.imul(v,X)|0)+Math.imul(y,W)|0,a=a+Math.imul(y,X)|0,n=n+Math.imul(p,J)|0,i=(i=i+Math.imul(p,Q)|0)+Math.imul(m,J)|0,a=a+Math.imul(m,Q)|0;var xt=(u+(n=n+Math.imul(h,$)|0)|0)+((8191&(i=(i=i+Math.imul(h,tt)|0)+Math.imul(f,$)|0))<<13)|0;u=((a=a+Math.imul(f,tt)|0)+(i>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(T,U),i=(i=Math.imul(T,V))+Math.imul(S,U)|0,a=Math.imul(S,V),n=n+Math.imul(M,q)|0,i=(i=i+Math.imul(M,G)|0)+Math.imul(k,q)|0,a=a+Math.imul(k,G)|0,n=n+Math.imul(x,W)|0,i=(i=i+Math.imul(x,X)|0)+Math.imul(_,W)|0,a=a+Math.imul(_,X)|0,n=n+Math.imul(v,J)|0,i=(i=i+Math.imul(v,Q)|0)+Math.imul(y,J)|0,a=a+Math.imul(y,Q)|0,n=n+Math.imul(p,$)|0,i=(i=i+Math.imul(p,tt)|0)+Math.imul(m,$)|0,a=a+Math.imul(m,tt)|0;var _t=(u+(n=n+Math.imul(h,rt)|0)|0)+((8191&(i=(i=i+Math.imul(h,nt)|0)+Math.imul(f,rt)|0))<<13)|0;u=((a=a+Math.imul(f,nt)|0)+(i>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(L,U),i=(i=Math.imul(L,V))+Math.imul(C,U)|0,a=Math.imul(C,V),n=n+Math.imul(T,q)|0,i=(i=i+Math.imul(T,G)|0)+Math.imul(S,q)|0,a=a+Math.imul(S,G)|0,n=n+Math.imul(M,W)|0,i=(i=i+Math.imul(M,X)|0)+Math.imul(k,W)|0,a=a+Math.imul(k,X)|0,n=n+Math.imul(x,J)|0,i=(i=i+Math.imul(x,Q)|0)+Math.imul(_,J)|0,a=a+Math.imul(_,Q)|0,n=n+Math.imul(v,$)|0,i=(i=i+Math.imul(v,tt)|0)+Math.imul(y,$)|0,a=a+Math.imul(y,tt)|0,n=n+Math.imul(p,rt)|0,i=(i=i+Math.imul(p,nt)|0)+Math.imul(m,rt)|0,a=a+Math.imul(m,nt)|0;var wt=(u+(n=n+Math.imul(h,at)|0)|0)+((8191&(i=(i=i+Math.imul(h,ot)|0)+Math.imul(f,at)|0))<<13)|0;u=((a=a+Math.imul(f,ot)|0)+(i>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(D,U),i=(i=Math.imul(D,V))+Math.imul(I,U)|0,a=Math.imul(I,V),n=n+Math.imul(L,q)|0,i=(i=i+Math.imul(L,G)|0)+Math.imul(C,q)|0,a=a+Math.imul(C,G)|0,n=n+Math.imul(T,W)|0,i=(i=i+Math.imul(T,X)|0)+Math.imul(S,W)|0,a=a+Math.imul(S,X)|0,n=n+Math.imul(M,J)|0,i=(i=i+Math.imul(M,Q)|0)+Math.imul(k,J)|0,a=a+Math.imul(k,Q)|0,n=n+Math.imul(x,$)|0,i=(i=i+Math.imul(x,tt)|0)+Math.imul(_,$)|0,a=a+Math.imul(_,tt)|0,n=n+Math.imul(v,rt)|0,i=(i=i+Math.imul(v,nt)|0)+Math.imul(y,rt)|0,a=a+Math.imul(y,nt)|0,n=n+Math.imul(p,at)|0,i=(i=i+Math.imul(p,ot)|0)+Math.imul(m,at)|0,a=a+Math.imul(m,ot)|0;var Mt=(u+(n=n+Math.imul(h,lt)|0)|0)+((8191&(i=(i=i+Math.imul(h,ut)|0)+Math.imul(f,lt)|0))<<13)|0;u=((a=a+Math.imul(f,ut)|0)+(i>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(O,U),i=(i=Math.imul(O,V))+Math.imul(j,U)|0,a=Math.imul(j,V),n=n+Math.imul(D,q)|0,i=(i=i+Math.imul(D,G)|0)+Math.imul(I,q)|0,a=a+Math.imul(I,G)|0,n=n+Math.imul(L,W)|0,i=(i=i+Math.imul(L,X)|0)+Math.imul(C,W)|0,a=a+Math.imul(C,X)|0,n=n+Math.imul(T,J)|0,i=(i=i+Math.imul(T,Q)|0)+Math.imul(S,J)|0,a=a+Math.imul(S,Q)|0,n=n+Math.imul(M,$)|0,i=(i=i+Math.imul(M,tt)|0)+Math.imul(k,$)|0,a=a+Math.imul(k,tt)|0,n=n+Math.imul(x,rt)|0,i=(i=i+Math.imul(x,nt)|0)+Math.imul(_,rt)|0,a=a+Math.imul(_,nt)|0,n=n+Math.imul(v,at)|0,i=(i=i+Math.imul(v,ot)|0)+Math.imul(y,at)|0,a=a+Math.imul(y,ot)|0,n=n+Math.imul(p,lt)|0,i=(i=i+Math.imul(p,ut)|0)+Math.imul(m,lt)|0,a=a+Math.imul(m,ut)|0;var kt=(u+(n=n+Math.imul(h,ht)|0)|0)+((8191&(i=(i=i+Math.imul(h,ft)|0)+Math.imul(f,ht)|0))<<13)|0;u=((a=a+Math.imul(f,ft)|0)+(i>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(F,U),i=(i=Math.imul(F,V))+Math.imul(N,U)|0,a=Math.imul(N,V),n=n+Math.imul(O,q)|0,i=(i=i+Math.imul(O,G)|0)+Math.imul(j,q)|0,a=a+Math.imul(j,G)|0,n=n+Math.imul(D,W)|0,i=(i=i+Math.imul(D,X)|0)+Math.imul(I,W)|0,a=a+Math.imul(I,X)|0,n=n+Math.imul(L,J)|0,i=(i=i+Math.imul(L,Q)|0)+Math.imul(C,J)|0,a=a+Math.imul(C,Q)|0,n=n+Math.imul(T,$)|0,i=(i=i+Math.imul(T,tt)|0)+Math.imul(S,$)|0,a=a+Math.imul(S,tt)|0,n=n+Math.imul(M,rt)|0,i=(i=i+Math.imul(M,nt)|0)+Math.imul(k,rt)|0,a=a+Math.imul(k,nt)|0,n=n+Math.imul(x,at)|0,i=(i=i+Math.imul(x,ot)|0)+Math.imul(_,at)|0,a=a+Math.imul(_,ot)|0,n=n+Math.imul(v,lt)|0,i=(i=i+Math.imul(v,ut)|0)+Math.imul(y,lt)|0,a=a+Math.imul(y,ut)|0,n=n+Math.imul(p,ht)|0,i=(i=i+Math.imul(p,ft)|0)+Math.imul(m,ht)|0,a=a+Math.imul(m,ft)|0;var At=(u+(n=n+Math.imul(h,pt)|0)|0)+((8191&(i=(i=i+Math.imul(h,mt)|0)+Math.imul(f,pt)|0))<<13)|0;u=((a=a+Math.imul(f,mt)|0)+(i>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(F,q),i=(i=Math.imul(F,G))+Math.imul(N,q)|0,a=Math.imul(N,G),n=n+Math.imul(O,W)|0,i=(i=i+Math.imul(O,X)|0)+Math.imul(j,W)|0,a=a+Math.imul(j,X)|0,n=n+Math.imul(D,J)|0,i=(i=i+Math.imul(D,Q)|0)+Math.imul(I,J)|0,a=a+Math.imul(I,Q)|0,n=n+Math.imul(L,$)|0,i=(i=i+Math.imul(L,tt)|0)+Math.imul(C,$)|0,a=a+Math.imul(C,tt)|0,n=n+Math.imul(T,rt)|0,i=(i=i+Math.imul(T,nt)|0)+Math.imul(S,rt)|0,a=a+Math.imul(S,nt)|0,n=n+Math.imul(M,at)|0,i=(i=i+Math.imul(M,ot)|0)+Math.imul(k,at)|0,a=a+Math.imul(k,ot)|0,n=n+Math.imul(x,lt)|0,i=(i=i+Math.imul(x,ut)|0)+Math.imul(_,lt)|0,a=a+Math.imul(_,ut)|0,n=n+Math.imul(v,ht)|0,i=(i=i+Math.imul(v,ft)|0)+Math.imul(y,ht)|0,a=a+Math.imul(y,ft)|0;var Tt=(u+(n=n+Math.imul(p,pt)|0)|0)+((8191&(i=(i=i+Math.imul(p,mt)|0)+Math.imul(m,pt)|0))<<13)|0;u=((a=a+Math.imul(m,mt)|0)+(i>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(F,W),i=(i=Math.imul(F,X))+Math.imul(N,W)|0,a=Math.imul(N,X),n=n+Math.imul(O,J)|0,i=(i=i+Math.imul(O,Q)|0)+Math.imul(j,J)|0,a=a+Math.imul(j,Q)|0,n=n+Math.imul(D,$)|0,i=(i=i+Math.imul(D,tt)|0)+Math.imul(I,$)|0,a=a+Math.imul(I,tt)|0,n=n+Math.imul(L,rt)|0,i=(i=i+Math.imul(L,nt)|0)+Math.imul(C,rt)|0,a=a+Math.imul(C,nt)|0,n=n+Math.imul(T,at)|0,i=(i=i+Math.imul(T,ot)|0)+Math.imul(S,at)|0,a=a+Math.imul(S,ot)|0,n=n+Math.imul(M,lt)|0,i=(i=i+Math.imul(M,ut)|0)+Math.imul(k,lt)|0,a=a+Math.imul(k,ut)|0,n=n+Math.imul(x,ht)|0,i=(i=i+Math.imul(x,ft)|0)+Math.imul(_,ht)|0,a=a+Math.imul(_,ft)|0;var St=(u+(n=n+Math.imul(v,pt)|0)|0)+((8191&(i=(i=i+Math.imul(v,mt)|0)+Math.imul(y,pt)|0))<<13)|0;u=((a=a+Math.imul(y,mt)|0)+(i>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(F,J),i=(i=Math.imul(F,Q))+Math.imul(N,J)|0,a=Math.imul(N,Q),n=n+Math.imul(O,$)|0,i=(i=i+Math.imul(O,tt)|0)+Math.imul(j,$)|0,a=a+Math.imul(j,tt)|0,n=n+Math.imul(D,rt)|0,i=(i=i+Math.imul(D,nt)|0)+Math.imul(I,rt)|0,a=a+Math.imul(I,nt)|0,n=n+Math.imul(L,at)|0,i=(i=i+Math.imul(L,ot)|0)+Math.imul(C,at)|0,a=a+Math.imul(C,ot)|0,n=n+Math.imul(T,lt)|0,i=(i=i+Math.imul(T,ut)|0)+Math.imul(S,lt)|0,a=a+Math.imul(S,ut)|0,n=n+Math.imul(M,ht)|0,i=(i=i+Math.imul(M,ft)|0)+Math.imul(k,ht)|0,a=a+Math.imul(k,ft)|0;var Et=(u+(n=n+Math.imul(x,pt)|0)|0)+((8191&(i=(i=i+Math.imul(x,mt)|0)+Math.imul(_,pt)|0))<<13)|0;u=((a=a+Math.imul(_,mt)|0)+(i>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(F,$),i=(i=Math.imul(F,tt))+Math.imul(N,$)|0,a=Math.imul(N,tt),n=n+Math.imul(O,rt)|0,i=(i=i+Math.imul(O,nt)|0)+Math.imul(j,rt)|0,a=a+Math.imul(j,nt)|0,n=n+Math.imul(D,at)|0,i=(i=i+Math.imul(D,ot)|0)+Math.imul(I,at)|0,a=a+Math.imul(I,ot)|0,n=n+Math.imul(L,lt)|0,i=(i=i+Math.imul(L,ut)|0)+Math.imul(C,lt)|0,a=a+Math.imul(C,ut)|0,n=n+Math.imul(T,ht)|0,i=(i=i+Math.imul(T,ft)|0)+Math.imul(S,ht)|0,a=a+Math.imul(S,ft)|0;var Lt=(u+(n=n+Math.imul(M,pt)|0)|0)+((8191&(i=(i=i+Math.imul(M,mt)|0)+Math.imul(k,pt)|0))<<13)|0;u=((a=a+Math.imul(k,mt)|0)+(i>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(F,rt),i=(i=Math.imul(F,nt))+Math.imul(N,rt)|0,a=Math.imul(N,nt),n=n+Math.imul(O,at)|0,i=(i=i+Math.imul(O,ot)|0)+Math.imul(j,at)|0,a=a+Math.imul(j,ot)|0,n=n+Math.imul(D,lt)|0,i=(i=i+Math.imul(D,ut)|0)+Math.imul(I,lt)|0,a=a+Math.imul(I,ut)|0,n=n+Math.imul(L,ht)|0,i=(i=i+Math.imul(L,ft)|0)+Math.imul(C,ht)|0,a=a+Math.imul(C,ft)|0;var Ct=(u+(n=n+Math.imul(T,pt)|0)|0)+((8191&(i=(i=i+Math.imul(T,mt)|0)+Math.imul(S,pt)|0))<<13)|0;u=((a=a+Math.imul(S,mt)|0)+(i>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(F,at),i=(i=Math.imul(F,ot))+Math.imul(N,at)|0,a=Math.imul(N,ot),n=n+Math.imul(O,lt)|0,i=(i=i+Math.imul(O,ut)|0)+Math.imul(j,lt)|0,a=a+Math.imul(j,ut)|0,n=n+Math.imul(D,ht)|0,i=(i=i+Math.imul(D,ft)|0)+Math.imul(I,ht)|0,a=a+Math.imul(I,ft)|0;var zt=(u+(n=n+Math.imul(L,pt)|0)|0)+((8191&(i=(i=i+Math.imul(L,mt)|0)+Math.imul(C,pt)|0))<<13)|0;u=((a=a+Math.imul(C,mt)|0)+(i>>>13)|0)+(zt>>>26)|0,zt&=67108863,n=Math.imul(F,lt),i=(i=Math.imul(F,ut))+Math.imul(N,lt)|0,a=Math.imul(N,ut),n=n+Math.imul(O,ht)|0,i=(i=i+Math.imul(O,ft)|0)+Math.imul(j,ht)|0,a=a+Math.imul(j,ft)|0;var Dt=(u+(n=n+Math.imul(D,pt)|0)|0)+((8191&(i=(i=i+Math.imul(D,mt)|0)+Math.imul(I,pt)|0))<<13)|0;u=((a=a+Math.imul(I,mt)|0)+(i>>>13)|0)+(Dt>>>26)|0,Dt&=67108863,n=Math.imul(F,ht),i=(i=Math.imul(F,ft))+Math.imul(N,ht)|0,a=Math.imul(N,ft);var It=(u+(n=n+Math.imul(O,pt)|0)|0)+((8191&(i=(i=i+Math.imul(O,mt)|0)+Math.imul(j,pt)|0))<<13)|0;u=((a=a+Math.imul(j,mt)|0)+(i>>>13)|0)+(It>>>26)|0,It&=67108863;var Pt=(u+(n=Math.imul(F,pt))|0)+((8191&(i=(i=Math.imul(F,mt))+Math.imul(N,pt)|0))<<13)|0;return u=((a=Math.imul(N,mt))+(i>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,l[0]=gt,l[1]=vt,l[2]=yt,l[3]=bt,l[4]=xt,l[5]=_t,l[6]=wt,l[7]=Mt,l[8]=kt,l[9]=At,l[10]=Tt,l[11]=St,l[12]=Et,l[13]=Lt,l[14]=Ct,l[15]=zt,l[16]=Dt,l[17]=It,l[18]=Pt,0!==u&&(l[19]=u,r.length++),r};Math.imul||(k=u),a.prototype.mulTo=function(t,e){var r=this.length+t.length;return 10===this.length&&10===t.length?k(this,t,e):r<63?u(this,t,e):r<1024?c(this,t,e):h(this,t,e)},f.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},f.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},f.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]]},f.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),u=Math.sin(2*Math.PI/s),c=0;c<i;c+=s)for(var h=l,f=u,d=0;d<o;d++){var p=r[c+d],m=n[c+d],g=r[c+d+o],v=n[c+d+o],y=h*g-f*v;v=h*v+f*g,g=y,r[c+d]=p+g,n[c+d]=m+v,r[c+d+o]=p-g,n[c+d+o]=m-v,d!==s&&(y=l*h-u*f,f=l*f+u*h,h=y)}},f.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},f.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}},f.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},f.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))},f.prototype.stub=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=0;return e},f.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),u=new Array(n),c=new Array(n),h=new Array(n),f=r.words;f.length=n,this.convert13b(t.words,t.length,o,n),this.convert13b(e.words,e.length,u,n),this.transform(o,a,s,l,n,i),this.transform(u,a,c,h,n,i);for(var d=0;d<n;d++){var p=s[d]*c[d]-l[d]*h[d];l[d]=s[d]*h[d]+l[d]*c[d],s[d]=p}return this.conjugate(s,l,n),this.transform(s,l,f,a,n,i),this.conjugate(f,a,n),this.normalize13b(f,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),h(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=l(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){n(\"number\"==typeof t&&t>=0);var i;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 u=0;u<o;u++)l.words[u]=this.words[u];l.length=o}if(0===o);else if(this.length>o)for(this.length-=o,u=0;u<this.length;u++)this.words[u]=this.words[u+o];else this.words[0]=0,this.length=1;var c=0;for(u=this.length-1;u>=0&&(0!==c||u>=i);u--){var h=0|this.words[u];this.words[u]=c<<26-a|h>>>a,c=h&s}return l&&0!==c&&(l.words[l.length++]=c),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=t.length+r;this._expand(a);var o,s=0;for(i=0;i<t.length;i++){o=(0|this.words[i+r])+s;var l=(0|t.words[i])*e;s=((o-=67108863&l)>>26)-(l/67108864|0),this.words[i+r]=67108863&o}for(;i<this.length-r;i++)s=(o=(0|this.words[i+r])+s)>>26,this.words[i+r]=67108863&o;if(0===s)return this.strip();for(n(-1===s),s=0,i=0;i<this.length;i++)s=(o=-(0|this.words[i])+s)>>26,this.words[i]=67108863&o;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 u=0;u<s.length;u++)s.words[u]=0}var c=n.clone()._ishlnsubmul(i,1,l);0===c.negative&&(n=c,s&&(s.words[l]=1));for(var h=l-1;h>=0;h--){var f=67108864*(0|n.words[i.length+h])+(0|n.words[i.length+h-1]);for(f=Math.min(f/o|0,67108863),n._ishlnsubmul(i,f,h);0!==n.negative;)f--,n.negative=0,n._ishlnsubmul(i,1,h),n.isZero()||(n.negative^=1);s&&(s.words[h]=f)}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){if(n(!t.isZero()),this.isZero())return{div:new a(0),mod:new a(0)};var i,o,s;return 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)},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),u=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++u;for(var c=r.clone(),h=e.clone();!e.isZero();){for(var f=0,d=1;0==(e.words[0]&d)&&f<26;++f,d<<=1);if(f>0)for(e.iushrn(f);f-- >0;)(i.isOdd()||o.isOdd())&&(i.iadd(c),o.isub(h)),i.iushrn(1),o.iushrn(1);for(var p=0,m=1;0==(r.words[0]&m)&&p<26;++p,m<<=1);if(p>0)for(r.iushrn(p);p-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(c),l.isub(h)),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(u)}},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=new a(1),o=new a(0),s=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var l=0,u=1;0==(e.words[0]&u)&&l<26;++l,u<<=1);if(l>0)for(e.iushrn(l);l-- >0;)i.isOdd()&&i.iadd(s),i.iushrn(1);for(var c=0,h=1;0==(r.words[0]&h)&&c<26;++c,h<<=1);if(c>0)for(r.iushrn(c);c-- >0;)o.isOdd()&&o.iadd(s),o.iushrn(1);e.cmp(r)>=0?(e.isub(r),i.isub(o)):(r.isub(e),o.isub(i))}var f;return(f=0===e.cmpn(1)?i:o).cmpn(0)<0&&f.iadd(t),f},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=t<0;if(0!==this.negative&&!e)return-1;if(0===this.negative&&e)return 1;this.strip();var r;if(this.length>1)r=1;else{e&&(t=-t),n(t<=67108863,\"Number is too big\");var i=0|this.words[0];r=i===t?0:i<t?-1:1}return 0!==this.negative?0|-r:r},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 y(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 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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},p.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(m,d),i(g,d),i(v,d),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(A[t])return A[t];var e;if(\"k256\"===t)e=new p;else if(\"p224\"===t)e=new m;else if(\"p192\"===t)e=new g;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);e=new v}return A[t]=e,e},y.prototype._verify1=function(t){n(0===t.negative,\"red works only with positives\"),n(t.red,\"red works only with red 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this._verify2(t,e),this.imod(t.imul(e))},y.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},y.prototype.isqr=function(t){return this.imul(t,t.clone())},y.prototype.sqr=function(t){return this.mul(t,t)},y.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 this.pow(t,r)}for(var i=this.m.subn(1),o=0;!i.isZero()&&0===i.andln(1);)o++,i.iushrn(1);n(!i.isZero());var s=new a(1).toRed(this),l=s.redNeg(),u=this.m.subn(1).iushrn(1),c=this.m.bitLength();for(c=new a(2*c*c).toRed(this);0!==this.pow(c,u).cmp(l);)c.redIAdd(l);for(var h=this.pow(c,i),f=this.pow(t,i.addn(1).iushrn(1)),d=this.pow(t,i),p=o;0!==d.cmp(s);){for(var m=d,g=0;0!==m.cmp(s);g++)m=m.redSqr();n(g<p);var v=this.pow(h,new a(1).iushln(p-g-1));f=f.redMul(v),h=v.redSqr(),d=d.redMul(h),p=g}return f},y.prototype.invm=function(t){var e=t._invmp(this.m);return 0!==e.negative?(e.negative=0,this.imod(e).redNeg()):this.imod(e)},y.prototype.pow=function(t,e){if(e.isZero())return new a(1);if(0===e.cmpn(1))return t.clone();var r=new Array(16);r[0]=new a(1).toRed(this),r[1]=t;for(var n=2;n<r.length;n++)r[n]=this.mul(r[n-1],t);var i=r[0],o=0,s=0,l=e.bitLength()%26;for(0===l&&(l=26),n=e.length-1;n>=0;n--){for(var u=e.words[n],c=l-1;c>=0;c--){var h=u>>c&1;i!==r[0]&&(i=this.sqr(i)),0!==h||0!==o?(o<<=1,o|=h,(4===++s||0===n&&0===c)&&(i=this.mul(i,r[o]),s=0,o=0)):s=0}l=26}return i},y.prototype.convertTo=function(t){var e=t.umod(this.m);return e===t?e.clone():e},y.prototype.convertFrom=function(t){var e=t.clone();return e.red=null,e},a.mont=function(t){return new b(t)},i(b,y),b.prototype.convertTo=function(t){return this.imod(t.ushln(this.shift))},b.prototype.convertFrom=function(t){var e=this.imod(t.mul(this.rinv));return e.red=null,e},b.prototype.imul=function(t,e){if(t.isZero()||e.isZero())return t.words[0]=0,t.length=1,t;var r=t.imul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).iushrn(this.shift),a=i;return i.cmp(this.m)>=0?a=i.isub(this.m):i.cmpn(0)<0&&(a=i.iadd(this.m)),a._forceRed(this)},b.prototype.mul=function(t,e){if(t.isZero()||e.isZero())return new a(0)._forceRed(this);var r=t.mul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).iushrn(this.shift),o=i;return i.cmp(this.m)>=0?o=i.isub(this.m):i.cmpn(0)<0&&(o=i.iadd(this.m)),o._forceRed(this)},b.prototype.invm=function(t){return this.imod(t._invmp(this.m).mul(this.r2))._forceRed(this)}}(void 0===e||e,this)},{}],62:[function(t,e,r){\"use strict\";function n(t){var e,r,n,i=t.length,a=0;for(e=0;e<i;++e)a+=t[e].length;var o=new Array(a),s=0;for(e=0;e<i;++e){var l=t[e],u=l.length;for(r=0;r<u;++r){var c=o[s++]=new Array(u-1),h=0;for(n=0;n<u;++n)n!==r&&(c[h++]=l[n]);if(1&r){var f=c[1];c[1]=c[0],c[0]=f}}}return o}e.exports=n},{}],63:[function(t,e,r){\"use strict\";function n(t,e){for(var r=0;r<t;++r)if(!(e[r]<=e[r+t]))return!0;return!1}function i(t,e,r,i){for(var a=0,o=0,s=0,l=t.length;s<l;++s){var u=t[s];if(!n(e,u)){for(var c=0;c<2*e;++c)r[a++]=u[c];i[o++]=s}}return o}function a(t,e,r,n){var a=t.length,o=e.length;if(!(a<=0||o<=0)){var s=t[0].length>>>1;if(!(s<=0)){var l,u=h.mallocDouble(2*s*a),c=h.mallocInt32(a);if((a=i(t,s,u,c))>0){if(1===s&&n)f.init(a),l=f.sweepComplete(s,r,0,a,u,c,0,a,u,c);else{var p=h.mallocDouble(2*s*o),m=h.mallocInt32(o);(o=i(e,s,p,m))>0&&(f.init(a+o),l=1===s?f.sweepBipartite(s,r,0,a,u,c,0,o,p,m):d(s,r,n,a,u,c,o,p,m),h.free(p),h.free(m))}h.free(u),h.free(c)}return l}}}function o(t,e){c.push([t,e])}function s(t){return c=[],a(t,t,o,!0),c}function l(t,e){return c=[],a(t,e,o,!1),c}function u(t,e,r){switch(arguments.length){case 1:return s(t);case 2:return\"function\"==typeof e?a(t,t,e,!0):l(t,e);case 3:return a(t,e,r,!1);default:throw new Error(\"box-intersect: Invalid arguments\")}}e.exports=u;var c,h=t(\"typedarray-pool\"),f=t(\"./lib/sweep\"),d=t(\"./lib/intersect\")},{\"./lib/intersect\":65,\"./lib/sweep\":69,\"typedarray-pool\":521}],64:[function(t,e,r){\"use strict\";function n(t,e,r){var n=\"bruteForce\"+(t?\"Red\":\"Blue\")+(e?\"Flip\":\"\")+(r?\"Full\":\"\"),i=[\"function \",n,\"(\",w.join(),\"){\",\"var \",u,\"=2*\",a,\";\"],l=\"for(var i=\"+c+\",\"+p+\"=\"+u+\"*\"+c+\";i<\"+h+\";++i,\"+p+\"+=\"+u+\"){var x0=\"+f+\"[\"+o+\"+\"+p+\"],x1=\"+f+\"[\"+o+\"+\"+p+\"+\"+a+\"],xi=\"+d+\"[i];\",M=\"for(var j=\"+m+\",\"+b+\"=\"+u+\"*\"+m+\";j<\"+g+\";++j,\"+b+\"+=\"+u+\"){var y0=\"+v+\"[\"+o+\"+\"+b+\"],\"+(r?\"y1=\"+v+\"[\"+o+\"+\"+b+\"+\"+a+\"],\":\"\")+\"yi=\"+y+\"[j];\";return t?i.push(l,_,\":\",M):i.push(M,_,\":\",l),r?i.push(\"if(y1<x0||x1<y0)continue;\"):e?i.push(\"if(y0<=x0||x1<y0)continue;\"):i.push(\"if(y0<x0||x1<y0)continue;\"),i.push(\"for(var k=\"+o+\"+1;k<\"+a+\";++k){var 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m=a(\"labels\");a(\"labelFont\")&&(m=!0),i(\"labelEnable\"),n(\"labelSize\"),n(\"labelPad\"),o(\"labelColor\"),i(\"lineEnable\"),i(\"lineMirror\"),n(\"lineWidth\"),o(\"lineColor\"),i(\"lineTickEnable\"),i(\"lineTickMirror\"),n(\"lineTickLength\"),n(\"lineTickWidth\"),o(\"lineTickColor\"),i(\"gridEnable\"),n(\"gridWidth\"),o(\"gridColor\"),i(\"zeroEnable\"),o(\"zeroLineColor\"),n(\"zeroLineWidth\"),i(\"backgroundEnable\"),o(\"backgroundColor\"),this._text?this._text&&(m||s)&&this._text.update(this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont):this._text=l(this.gl,this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont),this._lines&&s&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=u(this.gl,this.bounds,this.ticks))};var m=[new a,new a,new a],g=[0,0,0],v={model:d,view:d,projection:d};p.isOpaque=function(){return!0},p.isTransparent=function(){return!1},p.drawTransparent=function(t){};var y=[0,0,0],b=[0,0,0],x=[0,0,0];p.draw=function(t){t=t||v;for(var e=this.gl,r=t.model||d,i=t.view||d,a=t.projection||d,s=this.bounds,l=h(r,i,a,s),u=l.cubeEdges,c=l.axis,f=i[12],p=i[13],_=i[14],w=i[15],M=this.pixelRatio*(a[3]*f+a[7]*p+a[11]*_+a[15]*w)/e.drawingBufferHeight,k=0;k<3;++k)this.lastCubeProps.cubeEdges[k]=u[k],this.lastCubeProps.axis[k]=c[k];for(var A=m,k=0;k<3;++k)o(m[k],k,this.bounds,u,c);for(var e=this.gl,T=g,k=0;k<3;++k)this.backgroundEnable[k]?T[k]=c[k]:T[k]=0;this._background.draw(r,i,a,s,T,this.backgroundColor),this._lines.bind(r,i,a,this);for(k=0;k<3;++k){var S=[0,0,0];c[k]>0?S[k]=s[1][k]:S[k]=s[0][k];for(I=0;I<2;++I){var E=(k+1+I)%3,L=(k+1+(1^I))%3;this.gridEnable[E]&&this._lines.drawGrid(E,L,this.bounds,S,this.gridColor[E],this.gridWidth[E]*this.pixelRatio)}for(I=0;I<2;++I){var E=(k+1+I)%3,L=(k+1+(1^I))%3;this.zeroEnable[L]&&s[0][L]<=0&&s[1][L]>=0&&this._lines.drawZero(E,L,this.bounds,S,this.zeroLineColor[L],this.zeroLineWidth[L]*this.pixelRatio)}}for(k=0;k<3;++k){this.lineEnable[k]&&this._lines.drawAxisLine(k,this.bounds,A[k].primalOffset,this.lineColor[k],this.lineWidth[k]*this.pixelRatio),this.lineMirror[k]&&this._lines.drawAxisLine(k,this.bounds,A[k].mirrorOffset,this.lineColor[k],this.lineWidth[k]*this.pixelRatio);for(var C=n(y,A[k].primalMinor),z=n(b,A[k].mirrorMinor),D=this.lineTickLength,I=0;I<3;++I){var P=M/r[5*I];C[I]*=D[I]*P,z[I]*=D[I]*P}this.lineTickEnable[k]&&this._lines.drawAxisTicks(k,A[k].primalOffset,C,this.lineTickColor[k],this.lineTickWidth[k]*this.pixelRatio),this.lineTickMirror[k]&&this._lines.drawAxisTicks(k,A[k].mirrorOffset,z,this.lineTickColor[k],this.lineTickWidth[k]*this.pixelRatio)}this._text.bind(r,i,a,this.pixelRatio);for(k=0;k<3;++k){for(var O=A[k].primalMinor,j=n(x,A[k].primalOffset),I=0;I<3;++I)this.lineTickEnable[k]&&(j[I]+=M*O[I]*Math.max(this.lineTickLength[I],0)/r[5*I]);if(this.tickEnable[k]){for(I=0;I<3;++I)j[I]+=M*O[I]*this.tickPad[I]/r[5*I];this._text.drawTicks(k,this.tickSize[k],this.tickAngle[k],j,this.tickColor[k])}if(this.labelEnable[k]){for(I=0;I<3;++I)j[I]+=M*O[I]*this.labelPad[I]/r[5*I];j[k]+=.5*(s[0][k]+s[1][k]),this._text.drawLabel(k,this.labelSize[k],this.labelAngle[k],j,this.labelColor[k])}}},p.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\":134,\"./lib/cube.js\":135,\"./lib/lines.js\":136,\"./lib/text.js\":138,\"./lib/ticks.js\":139}],134:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}function i(t){for(var e=[],r=[],i=0,l=0;l<3;++l)for(var u=(l+1)%3,c=(l+2)%3,h=[0,0,0],f=[0,0,0],d=-1;d<=1;d+=2){r.push(i,i+2,i+1,i+1,i+2,i+3),h[l]=d,f[l]=d;for(var p=-1;p<=1;p+=2){h[u]=p;for(var m=-1;m<=1;m+=2)h[c]=m,e.push(h[0],h[1],h[2],f[0],f[1],f[2]),i+=1}var g=u;u=c,c=g}var v=a(t,new Float32Array(e)),y=a(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),b=o(t,[{buffer:v,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:v,type:t.FLOAT,size:3,offset:12,stride:24}],y),x=s(t);return x.attributes.position.location=0,x.attributes.normal.location=1,new n(t,v,b,x)}e.exports=i;var a=t(\"gl-buffer\"),o=t(\"gl-vao\"),s=t(\"./shaders\").bg,l=n.prototype;l.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),l.disable(l.POLYGON_OFFSET_FILL)}},l.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders\":137,\"gl-buffer\":141,\"gl-vao\":255}],135:[function(t,e,r){\"use strict\";function n(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 i(t){for(a=0;a<m.length;++a)if((t=l.positive(t,m[a])).length<3)return 0;for(var e=t[0],r=e[0]/e[3],n=e[1]/e[3],i=0,a=1;a+1<t.length;++a){var o=t[a],s=t[a+1],u=o[0]/o[3]-r,c=o[1]/o[3]-n,h=s[0]/s[3]-r,f=s[1]/s[3]-n;i+=Math.abs(u*f-c*h)}return i}function a(t,e,r,a){s(c,e,t),s(c,r,c);for(var l=0,m=0;m<2;++m){d[2]=a[m][2];for(var b=0;b<2;++b){d[1]=a[b][1];for(var x=0;x<2;++x)d[0]=a[x][0],n(h[l],d,c),l+=1}}for(var _=-1,m=0;m<8;++m){for(var w=h[m][3],M=0;M<3;++M)f[m][M]=h[m][M]/w;w<0&&(_<0?_=m:f[m][2]<f[_][2]&&(_=m))}if(_<0){_=0;for(V=0;V<3;++V){for(var k=(V+2)%3,A=(V+1)%3,T=-1,S=-1,E=0;E<2;++E){var L=(z=E<<V)+(E<<k)+(1-E<<A),C=z+(1-E<<k)+(E<<A);u(f[z],f[L],f[C],p)<0||(E?T=1:S=1)}if(T<0||S<0)S>T&&(_|=1<<V);else{for(E=0;E<2;++E){var z=E<<V,L=z+(E<<k)+(1-E<<A),C=z+(1-E<<k)+(E<<A),D=i([h[z],h[L],h[C],h[z+(1<<k)+(1<<A)]]);E?T=D:S=D}S>T&&(_|=1<<V)}}}for(var I=7^_,P=-1,m=0;m<8;++m)m!==_&&m!==I&&(P<0?P=m:f[P][1]>f[m][1]&&(P=m));for(var O=-1,m=0;m<3;++m)(R=P^1<<m)!==_&&R!==I&&(O<0&&(O=R),(A=f[R])[0]<f[O][0]&&(O=R));for(var j=-1,m=0;m<3;++m){var R=P^1<<m;R!==_&&R!==I&&R!==O&&(j<0&&(j=R),(A=f[R])[0]>f[j][0]&&(j=R))}var F=g;F[0]=F[1]=F[2]=0,F[o.log2(O^P)]=P&O,F[o.log2(P^j)]=P&j;var N=7^j;N===_||N===I?(N=7^O,F[o.log2(j^N)]=N&j):F[o.log2(O^N)]=N&O;for(var B=v,U=_,V=0;V<3;++V)B[V]=U&1<<V?-1:1;return y}e.exports=a;var o=t(\"bit-twiddle\"),s=t(\"gl-mat4/multiply\"),l=(t(\"gl-mat4/invert\"),t(\"split-polygon\")),u=t(\"robust-orientation\"),c=new Array(16),h=(new Array(16),new Array(8)),f=new Array(8),d=new Array(3),p=[0,0,0];!function(){for(var t=0;t<8;++t)h[t]=[1,1,1,1],f[t]=[1,1,1]}();var m=[[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]],g=[1,1,1],v=[0,0,0],y={cubeEdges:g,axis:v}},{\"bit-twiddle\":60,\"gl-mat4/invert\":165,\"gl-mat4/multiply\":167,\"robust-orientation\":489,\"split-polygon\":507}],136:[function(t,e,r){\"use strict\";function n(t){return t[0]=t[1]=t[2]=0,t}function i(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function a(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}function o(t,e,r){var n=[],i=[0,0,0],o=[0,0,0],c=[0,0,0],h=[0,0,0];n.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 d=n.length/3|0,p=0;p<r[f].length;++p){g=+r[f][p].x;n.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}v=n.length/3|0;i[f]=d,o[f]=v-d;for(var d=n.length/3|0,m=0;m<r[f].length;++m){var g=+r[f][m].x;n.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}var v=n.length/3|0;c[f]=d,h[f]=v-d}var y=s(t,new Float32Array(n)),b=l(t,[{buffer:y,type:t.FLOAT,size:3,stride:0,offset:0}]),x=u(t);return x.attributes.position.location=0,new a(t,y,b,x,o,i,h,c)}e.exports=o;var s=t(\"gl-buffer\"),l=t(\"gl-vao\"),u=t(\"./shaders\").line,c=[0,0,0],h=[0,0,0],f=[0,0,0],d=[0,0,0],p=[1,1],m=a.prototype;m.bind=function(t,e,r){this.shader.bind(),this.shader.uniforms.model=t,this.shader.uniforms.view=e,this.shader.uniforms.projection=r,p[0]=this.gl.drawingBufferWidth,p[1]=this.gl.drawingBufferHeight,this.shader.uniforms.screenShape=p,this.vao.bind()},m.drawAxisLine=function(t,e,r,a,o){var s=n(h);this.shader.uniforms.majorAxis=h,s[t]=e[1][t]-e[0][t],this.shader.uniforms.minorAxis=s;var l=i(d,r);l[t]+=e[0][t],this.shader.uniforms.offset=l,this.shader.uniforms.lineWidth=o,this.shader.uniforms.color=a;var u=n(f);u[(t+2)%3]=1,this.shader.uniforms.screenAxis=u,this.vao.draw(this.gl.TRIANGLES,6),(u=n(f))[(t+1)%3]=1,this.shader.uniforms.screenAxis=u,this.vao.draw(this.gl.TRIANGLES,6)},m.drawAxisTicks=function(t,e,r,i,a){if(this.tickCount[t]){var o=n(c);o[t]=1,this.shader.uniforms.majorAxis=o,this.shader.uniforms.offset=e,this.shader.uniforms.minorAxis=r,this.shader.uniforms.color=i,this.shader.uniforms.lineWidth=a;var s=n(f);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}},m.drawGrid=function(t,e,r,a,o,s){if(this.gridCount[t]){var l=n(h);l[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=l;var u=i(d,a);u[e]+=r[0][e],this.shader.uniforms.offset=u;var p=n(c);p[t]=1,this.shader.uniforms.majorAxis=p;var m=n(f);m[t]=1,this.shader.uniforms.screenAxis=m,this.shader.uniforms.lineWidth=s,this.shader.uniforms.color=o,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])}},m.drawZero=function(t,e,r,a,o,s){var l=n(h);this.shader.uniforms.majorAxis=l,l[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=l;var u=i(d,a);u[t]+=r[0][t],this.shader.uniforms.offset=u;var c=n(f);c[e]=1,this.shader.uniforms.screenAxis=c,this.shader.uniforms.lineWidth=s,this.shader.uniforms.color=o,this.vao.draw(this.gl.TRIANGLES,6)},m.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},{\"./shaders\":137,\"gl-buffer\":141,\"gl-vao\":255}],137:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\");r.line=function(t){return n(t,\"#define GLSLIFY 1\\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\",\"precision mediump float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\",null,[{name:\"position\",type:\"vec3\"}])};r.text=function(t){return n(t,\"#define GLSLIFY 1\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, axis;\\nuniform float scale, angle, pixelScale;\\nuniform vec2 resolution;\\n\\nvoid main() {  \\n  //Compute plane offset\\n  vec2 planeCoord = position.xy * pixelScale;\\n  mat2 planeXform = scale * mat2(cos(angle), sin(angle),\\n                                -sin(angle), cos(angle));\\n  vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\\n\\n  //Compute world offset\\n  float axisDistance = position.z;\\n  vec3 dataPosition = axisDistance * axis + offset;\\n  vec4 worldPosition = model * vec4(dataPosition, 1);\\n  \\n  //Compute clip position\\n  vec4 viewPosition = view * worldPosition;\\n  vec4 clipPosition = projection * viewPosition;\\n  clipPosition /= clipPosition.w;\\n\\n  //Apply text offset in clip coordinates\\n  clipPosition += vec4(viewOffset, 0, 0);\\n\\n  //Done\\n  gl_Position = clipPosition;\\n}\",\"precision mediump float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\",null,[{name:\"position\",type:\"vec3\"}])};r.bg=function(t){return n(t,\"#define GLSLIFY 1\\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  if(dot(normal, enable) > 0.0) {\\n    vec3 nPosition = mix(bounds[0], bounds[1], 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  colorChannel = abs(normal);\\n}\",\"precision mediump 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}\",null,[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}])}},{\"gl-shader\":239}],138:[function(t,e,r){(function(r){\"use strict\";function n(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}function i(t,e){try{return l(t,e)}catch(t){return console.warn(\"error vectorizing 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c=a.gl,h=a.dataBox,f=a.viewBox,d=a.pixelRatio,p=s[2]-s[0],m=s[3]-s[1],g=h[2]-h[0],v=h[3]-h[1],y=2*p/g,b=2*m/v,x=(s[0]-h[0]-.5*g)/p,_=(s[1]-h[1]-.5*v)/m;t[0]=y,t[1]=b,e[0]=y-t[0],e[1]=b-t[1],r[0]=x,r[1]=_,n[0]=x-r[0],n[1]=_-r[1];var w=f[2]-f[0],M=f[3]-f[1];i[0]=2*d/w,i[1]=2*d/M,o.bind(),o.uniforms.scaleHi=t,o.uniforms.scaleLo=e,o.uniforms.translateHi=r,o.uniforms.translateLo=n,o.uniforms.pixelScale=i,o.uniforms.color=this.color,this.bufferLo.bind(),o.attributes.positionLo.pointer(c.FLOAT,!1,16,0),this.bufferHi.bind(),o.attributes.positionHi.pointer(c.FLOAT,!1,16,0),o.attributes.pixelOffset.pointer(c.FLOAT,!1,16,8),c.drawArrays(c.TRIANGLES,0,l*u.length)}}}(),c.drawPick=function(t){return t},c.pick=function(){return null},c.update=function(t){var e,r,n,i=(t=t||{}).positions||[],a=t.errors||[],o=1;\"lineWidth\"in t&&(o=+t.lineWidth);var l=5;\"capSize\"in t&&(l=+t.capSize),this.color=(t.color||[0,0,0,1]).slice();var c=this.bounds=[1/0,1/0,-1/0,-1/0],h=this.numPoints=i.length>>1;for(e=0;e<h;++e)r=i[2*e],n=i[2*e+1],c[0]=Math.min(r,c[0]),c[1]=Math.min(n,c[1]),c[2]=Math.max(r,c[2]),c[3]=Math.max(n,c[3]);c[2]===c[0]&&(c[2]+=1),c[3]===c[1]&&(c[3]+=1);var f=1/(c[2]-c[0]),d=1/(c[3]-c[1]),p=c[0],m=c[1],g=s.mallocFloat64(h*u.length*4),v=s.mallocFloat32(h*u.length*4),y=s.mallocFloat32(h*u.length*4),b=0;for(e=0;e<h;++e){r=i[2*e],n=i[2*e+1];for(var x=a[4*e],_=a[4*e+1],w=a[4*e+2],M=a[4*e+3],k=0;k<u.length;++k){var A=u[k],T=A[0],S=A[1];T<0?T*=x:T>0&&(T*=_),S<0?S*=w:S>0&&(S*=M),g[b++]=f*(r-p+T),g[b++]=d*(n-m+S),g[b++]=o*A[2]+(l+o)*A[4],g[b++]=o*A[3]+(l+o)*A[5]}}for(e=0;e<g.length;e++)v[e]=g[e],y[e]=g[e]-v[e];this.bufferHi.update(v),this.bufferLo.update(y),s.free(g)},c.dispose=function(){this.plot.removeObject(this),this.shader.dispose(),this.bufferHi.dispose(),this.bufferLo.dispose()}},{\"./lib/shaders\":145,\"gl-buffer\":141,\"gl-shader\":239,\"typedarray-pool\":521}],145:[function(t,e,r){e.exports={vertex:\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 positionHi;\\nattribute vec2 positionLo;\\nattribute vec2 pixelOffset;\\n\\nuniform vec2 scaleHi, scaleLo, translateHi, translateLo, pixelScale;\\n\\nvec2 project(vec2 scHi, vec2 trHi, vec2 scLo, vec2 trLo, vec2 posHi, vec2 posLo) {\\n  return (posHi + trHi) * scHi\\n       + (posLo + trLo) * scHi\\n       + (posHi + trHi) * scLo\\n       + (posLo + trLo) * scLo;\\n}\\n\\nvoid main() {\\n  vec3 scrPosition = vec3(\\n         project(scaleHi, translateHi, scaleLo, translateLo, positionHi, positionLo),\\n         1);\\n  gl_Position = vec4(\\n    scrPosition.xy + scrPosition.z * pixelScale * pixelOffset,\\n    0,\\n    scrPosition.z);\\n}\\n\",fragment:\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = vec4(color.rgb * color.a, color.a);\\n}\\n\"}},{}],146:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.gl=t,this.shader=n,this.buffer=e,this.vao=r,this.pixelRatio=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.lineWidth=[1,1,1],this.capSize=[10,10,10],this.lineCount=[0,0,0],this.lineOffset=[0,0,0],this.opacity=1}function i(t,e){for(var r=0;r<3;++r)t[0][r]=Math.min(t[0][r],e[r]),t[1][r]=Math.max(t[1][r],e[r])}function a(t,e,r,n){for(var i=f[n],a=0;a<i.length;++a){var o=i[a];t.push(e[0],e[1],e[2],r[0],r[1],r[2],r[3],o[0],o[1],o[2])}return i.length}function o(t){var e=t.gl,r=s(e),i=l(e,[{buffer:r,type:e.FLOAT,size:3,offset:0,stride:40},{buffer:r,type:e.FLOAT,size:4,offset:12,stride:40},{buffer:r,type:e.FLOAT,size:3,offset:28,stride:40}]),a=u(e);a.attributes.position.location=0,a.attributes.color.location=1,a.attributes.offset.location=2;var o=new n(e,r,i,a);return o.update(t),o}e.exports=o;var s=t(\"gl-buffer\"),l=t(\"gl-vao\"),u=t(\"./shaders/index\"),c=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],h=n.prototype;h.isOpaque=function(){return this.opacity>=1},h.isTransparent=function(){return this.opacity<1},h.drawTransparent=h.draw=function(t){var e=this.gl,r=this.shader.uniforms;this.shader.bind();var n=r.view=t.view||c,i=r.projection=t.projection||c;r.model=t.model||c,r.clipBounds=this.clipBounds,r.opacity=this.opacity;var a=n[12],o=n[13],s=n[14],l=n[15],u=this.pixelRatio*(i[3]*a+i[7]*o+i[11]*s+i[15]*l)/e.drawingBufferHeight;this.vao.bind();for(var h=0;h<3;++h)e.lineWidth(this.lineWidth[h]),r.capSize=this.capSize[h]*u,e.drawArrays(e.LINES,this.lineOffset[h],this.lineCount[h]);this.vao.unbind()};var f=function(){for(var t=new Array(3),e=0;e<3;++e){for(var r=[],n=1;n<=2;++n)for(var i=-1;i<=1;i+=2){var a=[0,0,0];a[(n+e)%3]=i,r.push(a)}t[e]=r}return t}();h.update=function(t){\"lineWidth\"in(t=t||{})&&(this.lineWidth=t.lineWidth,Array.isArray(this.lineWidth)||(this.lineWidth=[this.lineWidth,this.lineWidth,this.lineWidth])),\"capSize\"in t&&(this.capSize=t.capSize,Array.isArray(this.capSize)||(this.capSize=[this.capSize,this.capSize,this.capSize])),\"opacity\"in t&&(this.opacity=t.opacity);var e=t.color||[[0,0,0],[0,0,0],[0,0,0]],r=t.position,n=t.error;if(Array.isArray(e[0])||(e=[e,e,e]),r&&n){var o=[],s=r.length,l=0;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.lineCount=[0,0,0];for(var u=0;u<3;++u){this.lineOffset[u]=l;t:for(var c=0;c<s;++c){for(var h=r[c],f=0;f<3;++f)if(isNaN(h[f])||!isFinite(h[f]))continue t;var d=n[c],p=e[u];if(Array.isArray(p[0])&&(p=e[c]),3===p.length&&(p=[p[0],p[1],p[2],1]),!isNaN(d[0][u])&&!isNaN(d[1][u])&&(d[0][u]<0&&((m=h.slice())[u]+=d[0][u],o.push(h[0],h[1],h[2],p[0],p[1],p[2],p[3],0,0,0,m[0],m[1],m[2],p[0],p[1],p[2],p[3],0,0,0),i(this.bounds,m),l+=2+a(o,m,p,u)),d[1][u]>0)){var m=h.slice();m[u]+=d[1][u],o.push(h[0],h[1],h[2],p[0],p[1],p[2],p[3],0,0,0,m[0],m[1],m[2],p[0],p[1],p[2],p[3],0,0,0),i(this.bounds,m),l+=2+a(o,m,p,u)}}this.lineCount[u]=l-this.lineOffset[u]}this.buffer.update(o)}},h.dispose=function(){this.shader.dispose(),this.buffer.dispose(),this.vao.dispose()}},{\"./shaders/index\":147,\"gl-buffer\":141,\"gl-vao\":255}],147:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\");e.exports=function(t){return n(t,\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, offset;\\nattribute vec4 color;\\nuniform mat4 model, view, projection;\\nuniform float capSize;\\nvarying vec4 fragColor;\\nvarying vec3 fragPosition;\\n\\nvoid main() {\\n  vec4 worldPosition  = model * vec4(position, 1.0);\\n  worldPosition       = (worldPosition / worldPosition.w) + vec4(capSize * offset, 0.0);\\n  gl_Position         = projection * view * worldPosition;\\n  fragColor           = color;\\n  fragPosition        = position;\\n}\",\"precision mediump float;\\n#define GLSLIFY 1\\nuniform vec3 clipBounds[2];\\nuniform float opacity;\\nvarying vec3 fragPosition;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(fragPosition, clipBounds[0])) || any(greaterThan(fragPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = opacity * fragColor;\\n}\",null,[{name:\"position\",type:\"vec3\"},{name:\"offset\",type:\"vec3\"},{name:\"color\",type:\"vec4\"}])}},{\"gl-shader\":239}],148:[function(t,e,r){\"use strict\";function n(t){return[t.getParameter(t.FRAMEBUFFER_BINDING),t.getParameter(t.RENDERBUFFER_BINDING),t.getParameter(t.TEXTURE_BINDING_2D)]}function i(t,e){t.bindFramebuffer(t.FRAMEBUFFER,e[0]),t.bindRenderbuffer(t.RENDERBUFFER,e[1]),t.bindTexture(t.TEXTURE_2D,e[2])}function a(t,e){var r=t.getParameter(e.MAX_COLOR_ATTACHMENTS_WEBGL);y=new Array(r+1);for(var n=0;n<=r;++n){for(var i=new Array(r),a=0;a<n;++a)i[a]=t.COLOR_ATTACHMENT0+a;for(a=n;a<r;++a)i[a]=t.NONE;y[n]=i}}function o(t){switch(t){case p:throw new Error(\"gl-fbo: Framebuffer unsupported\");case m:throw new Error(\"gl-fbo: Framebuffer incomplete attachment\");case g:throw new Error(\"gl-fbo: Framebuffer incomplete dimensions\");case v:throw new Error(\"gl-fbo: Framebuffer incomplete missing attachment\");default:throw new Error(\"gl-fbo: Framebuffer failed for unspecified reason\")}}function s(t,e,r,n,i,a){if(!n)return null;var o=d(t,e,r,i,n);return o.magFilter=t.NEAREST,o.minFilter=t.NEAREST,o.mipSamples=1,o.bind(),t.framebufferTexture2D(t.FRAMEBUFFER,a,t.TEXTURE_2D,o.handle,0),o}function l(t,e,r,n,i){var a=t.createRenderbuffer();return t.bindRenderbuffer(t.RENDERBUFFER,a),t.renderbufferStorage(t.RENDERBUFFER,n,e,r),t.framebufferRenderbuffer(t.FRAMEBUFFER,i,t.RENDERBUFFER,a),a}function u(t){var e=n(t.gl),r=t.gl,a=t.handle=r.createFramebuffer(),u=t._shape[0],c=t._shape[1],h=t.color.length,f=t._ext,d=t._useStencil,p=t._useDepth,m=t._colorType;r.bindFramebuffer(r.FRAMEBUFFER,a);for(b=0;b<h;++b)t.color[b]=s(r,u,c,m,r.RGBA,r.COLOR_ATTACHMENT0+b);0===h?(t._color_rb=l(r,u,c,r.RGBA4,r.COLOR_ATTACHMENT0),f&&f.drawBuffersWEBGL(y[0])):h>1&&f.drawBuffersWEBGL(y[h]);var g=r.getExtension(\"WEBGL_depth_texture\");g?d?t.depth=s(r,u,c,g.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):p&&(t.depth=s(r,u,c,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):p&&d?t._depth_rb=l(r,u,c,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):p?t._depth_rb=l(r,u,c,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):d&&(t._depth_rb=l(r,u,c,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var v=r.checkFramebufferStatus(r.FRAMEBUFFER);if(v!==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(var b=0;b<t.color.length;++b)t.color[b].dispose(),t.color[b]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),i(r,e),o(v)}i(r,e)}function c(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 l=0;l<i;++l)this.color[l]=null;this._color_rb=null,this.depth=null,this._depth_rb=null,this._colorType=n,this._useDepth=a,this._useStencil=o;var c=this,h=[0|e,0|r];Object.defineProperties(h,{0:{get:function(){return c._shape[0]},set:function(t){return c.width=t}},1:{get:function(){return c._shape[1]},set:function(t){return c.height=t}}}),this._shapeVector=h,u(this)}function h(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 a=t.gl,s=a.getParameter(a.MAX_RENDERBUFFER_SIZE);if(e<0||e>s||r<0||r>s)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var l=n(a),u=0;u<t.color.length;++u)t.color[u].shape=t._shape;t._color_rb&&(a.bindRenderbuffer(a.RENDERBUFFER,t._color_rb),a.renderbufferStorage(a.RENDERBUFFER,a.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(a.bindRenderbuffer(a.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?a.renderbufferStorage(a.RENDERBUFFER,a.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?a.renderbufferStorage(a.RENDERBUFFER,a.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&a.renderbufferStorage(a.RENDERBUFFER,a.STENCIL_INDEX,t._shape[0],t._shape[1])),a.bindFramebuffer(a.FRAMEBUFFER,t.handle);var c=a.checkFramebufferStatus(a.FRAMEBUFFER);c!==a.FRAMEBUFFER_COMPLETE&&(t.dispose(),i(a,l),o(c)),i(a,l)}}function f(t,e,r,n){p||(p=t.FRAMEBUFFER_UNSUPPORTED,m=t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT,g=t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS,v=t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT);var i=t.getExtension(\"WEBGL_draw_buffers\");if(!y&&i&&a(t,i),Array.isArray(e)&&(n=r,r=0|e[1],e=0|e[0]),\"number\"!=typeof e)throw new Error(\"gl-fbo: Missing shape parameter\");var o=t.getParameter(t.MAX_RENDERBUFFER_SIZE);if(e<0||e>o||r<0||r>o)throw new Error(\"gl-fbo: Parameters are too large for FBO\");var s=1;if(\"color\"in(n=n||{})){if((s=Math.max(0|n.color,0))<0)throw new Error(\"gl-fbo: Must specify a nonnegative number of colors\");if(s>1){if(!i)throw new Error(\"gl-fbo: Multiple draw buffer extension not supported\");if(s>t.getParameter(i.MAX_COLOR_ATTACHMENTS_WEBGL))throw new Error(\"gl-fbo: Context does not support \"+s+\" draw buffers\")}}var l=t.UNSIGNED_BYTE,u=t.getExtension(\"OES_texture_float\");if(n.float&&s>0){if(!u)throw new Error(\"gl-fbo: Context does not support floating point textures\");l=t.FLOAT}else n.preferFloat&&s>0&&u&&(l=t.FLOAT);var h=!0;\"depth\"in n&&(h=!!n.depth);var f=!1;return\"stencil\"in n&&(f=!!n.stencil),new c(t,e,r,l,s,h,f,i)}var d=t(\"gl-texture2d\");e.exports=f;var p,m,g,v,y=null,b=c.prototype;Object.defineProperties(b,{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 h(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return t|=0,h(this,t,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t|=0,h(this,this._shape[0],t),t},enumerable:!1}}),b.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])}},b.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\":251}],149:[function(t,e,r){function n(t,e,r){\"use strict\";var n=o(e)||\"of unknown name (see npm glsl-shader-name)\",l=\"unknown type\";void 0!==r&&(l=r===a.FRAGMENT_SHADER?\"fragment\":\"vertex\");for(var u=i(\"Error compiling %s shader %s:\\n\",l,n),c=i(\"%s%s\",u,t),h=t.split(\"\\n\"),f={},d=0;d<h.length;d++){var p=h[d];if(\"\"!==p){var m=parseInt(p.split(\":\")[2]);if(isNaN(m))throw new Error(i(\"Could not parse error: %s\",p));f[m]=p}}for(var g=s(e).split(\"\\n\"),d=0;d<g.length;d++)if((f[d+3]||f[d+2]||f[d+1])&&(u+=g[d]+\"\\n\",f[d+1])){var v=f[d+1];v=v.substr(v.split(\":\",3).join(\":\").length+1).trim(),u+=i(\"^^^ %s\\n\\n\",v)}return{long:u.trim(),short:c.trim()}}var i=t(\"sprintf-js\").sprintf,a=t(\"gl-constants/lookup\"),o=t(\"glsl-shader-name\"),s=t(\"add-line-numbers\");e.exports=n},{\"add-line-numbers\":35,\"gl-constants/lookup\":143,\"glsl-shader-name\":263,\"sprintf-js\":508}],150:[function(t,e,r){\"use strict\";function n(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}function i(t,e){var r=t.gl,i=new n(t,l(r,c.vertex,c.fragment),l(r,c.pickVertex,c.pickFragment),u(r),u(r),u(r),u(r));return i.update(e),t.addObject(i),i}e.exports=i;var a=t(\"binary-search-bounds\"),o=t(\"iota-array\"),s=t(\"typedarray-pool\"),l=t(\"gl-shader\"),u=t(\"gl-buffer\"),c=t(\"./lib/shaders\"),h=n.prototype,f=[0,0,1,0,0,1,1,0,1,1,0,1];h.draw=function(){var t=[1,0,0,0,1,0,0,0,1];return function(){var e=this.plot,r=this.shader,n=this.bounds,i=this.numVertices;if(!(i<=0)){var a=e.gl,o=e.dataBox,s=n[2]-n[0],l=n[3]-n[1],u=o[2]-o[0],c=o[3]-o[1];t[0]=2*s/u,t[4]=2*l/c,t[6]=2*(n[0]-o[0])/u-1,t[7]=2*(n[1]-o[1])/c-1,r.bind();var h=r.uniforms;h.viewTransform=t,h.shape=this.shape;var f=r.attributes;this.positionBuffer.bind(),f.position.pointer(),this.weightBuffer.bind(),f.weight.pointer(a.UNSIGNED_BYTE,!1),this.colorBuffer.bind(),f.color.pointer(a.UNSIGNED_BYTE,!0),a.drawArrays(a.TRIANGLES,0,i)}}}(),h.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,u=a[2]-a[0],c=a[3]-a[1],h=l[2]-l[0],f=l[3]-l[1];t[0]=2*u/h,t[4]=2*c/f,t[6]=2*(a[0]-l[0])/h-1,t[7]=2*(a[1]-l[1])/f-1;for(var d=0;d<4;++d)e[d]=r>>8*d&255;this.pickOffset=r,i.bind();var p=i.uniforms;p.viewTransform=t,p.pickOffset=e,p.shape=this.shape;var m=i.attributes;return this.positionBuffer.bind(),m.position.pointer(),this.weightBuffer.bind(),m.weight.pointer(s.UNSIGNED_BYTE,!1),this.idBuffer.bind(),m.pickId.pointer(s.UNSIGNED_BYTE,!1),s.drawArrays(s.TRIANGLES,0,o),r+this.shape[0]*this.shape[1]}}}(),h.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]]}},h.update=function(t){var e=(t=t||{}).shape||[0,0],r=t.x||o(e[0]),n=t.y||o(e[1]),i=t.z||new Float32Array(e[0]*e[1]);this.xData=r,this.yData=n;var l=t.colorLevels||[0],u=t.colorValues||[0,0,0,1],c=l.length,h=this.bounds,d=h[0]=r[0],p=h[1]=n[0],m=1/((h[2]=r[r.length-1])-d),g=1/((h[3]=n[n.length-1])-p),v=e[0],y=e[1];this.shape=[v,y];var b=(v-1)*(y-1)*(f.length>>>1);this.numVertices=b;for(var x=s.mallocUint8(4*b),_=s.mallocFloat32(2*b),w=s.mallocUint8(2*b),M=s.mallocUint32(b),k=0,A=0;A<y-1;++A)for(var T=g*(n[A]-p),S=g*(n[A+1]-p),E=0;E<v-1;++E)for(var L=m*(r[E]-d),C=m*(r[E+1]-d),z=0;z<f.length;z+=2){var D,I,P,O,j=f[z],R=f[z+1],F=i[(A+R)*v+(E+j)],N=a.le(l,F);if(N<0)D=u[0],I=u[1],P=u[2],O=u[3];else if(N===c-1)D=u[4*c-4],I=u[4*c-3],P=u[4*c-2],O=u[4*c-1];else{var B=(F-l[N])/(l[N+1]-l[N]),U=1-B,V=4*N,H=4*(N+1);D=U*u[V]+B*u[H],I=U*u[V+1]+B*u[H+1],P=U*u[V+2]+B*u[H+2],O=U*u[V+3]+B*u[H+3]}x[4*k]=255*D,x[4*k+1]=255*I,x[4*k+2]=255*P,x[4*k+3]=255*O,_[2*k]=.5*L+.5*C,_[2*k+1]=.5*T+.5*S,w[2*k]=j,w[2*k+1]=R,M[k]=A*v+E,k+=1}this.positionBuffer.update(_),this.weightBuffer.update(w),this.colorBuffer.update(x),this.idBuffer.update(M),s.free(_),s.free(x),s.free(w),s.free(M)},h.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\":151,\"binary-search-bounds\":152,\"gl-buffer\":141,\"gl-shader\":239,\"iota-array\":276,\"typedarray-pool\":521}],151:[function(t,e,r){\"use strict\";e.exports={fragment:\"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:\"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:\"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:\"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\"}},{}],152:[function(t,e,r){arguments[4][77][0].apply(r,arguments)},{dup:77}],153:[function(t,e,r){r.lineVertex=\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aHi, aLo, dHi, dLo;\\n\\nuniform vec2 scaleHi, translateHi, scaleLo, translateLo, screenShape;\\nuniform float width;\\n\\nvarying vec2 direction;\\n\\n\\nvec2 project_1_0(vec2 scHi, vec2 trHi, vec2 scLo, vec2 trLo, vec2 posHi, vec2 posLo) {\\n  return (posHi + trHi) * scHi\\n       + (posLo + trLo) * scHi\\n       + (posHi + trHi) * scLo\\n       + (posLo + trLo) * scLo;\\n}\\n\\n\\nvec2 project_2_1(vec2 scHi, vec2 scLo, vec2 posHi, vec2 posLo) {\\n  return scHi * posHi\\n       + scLo * posHi\\n       + scHi * posLo\\n       + scLo * posLo;\\n}\\n\\nvoid main() {\\n  vec2 p = project_1_0(scaleHi, translateHi, scaleLo, translateLo, aHi, aLo);\\n  vec2 dir = project_2_1(scaleHi, scaleLo, dHi, dLo);\\n  vec2 n = 0.5 * width * normalize(screenShape.yx * vec2(dir.y, -dir.x)) / screenShape.xy;\\n  vec2 tangent = normalize(screenShape.xy * dir);\\n  if(dir.x < 0.0 || (dir.x == 0.0 && dir.y < 0.0)) {\\n    direction = -tangent;\\n  } else {\\n    direction = tangent;\\n  }\\n  gl_Position = vec4(p + n, 0.0, 1.0);\\n}\",r.lineFragment=\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nuniform vec2 screenShape;\\nuniform sampler2D dashPattern;\\nuniform float dashLength;\\n\\nvarying vec2 direction;\\n\\nvoid main() {\\n  float t = fract(dot(direction, gl_FragCoord.xy) / dashLength);\\n  vec4 pcolor = color * texture2D(dashPattern, vec2(t, 0.0)).r;\\n  gl_FragColor = vec4(pcolor.rgb * pcolor.a, pcolor.a);\\n}\",r.mitreVertex=\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aHi, aLo;\\n\\nuniform vec2 scaleHi, translateHi, scaleLo, translateLo;\\nuniform float radius;\\n\\n\\nvec2 project_1_0(vec2 scHi, vec2 trHi, vec2 scLo, vec2 trLo, vec2 posHi, vec2 posLo) {\\n  return (posHi + trHi) * scHi\\n       + (posLo + trLo) * scHi\\n       + (posHi + trHi) * scLo\\n       + (posLo + trLo) * scLo;\\n}\\n\\n\\nvoid main() {\\n  vec2 p = project_1_0(scaleHi, translateHi, scaleLo, translateLo, aHi, aLo);\\n  gl_Position = vec4(p, 0.0, 1.0);\\n  gl_PointSize = radius;\\n}\",r.mitreFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  if(length(gl_PointCoord.xy - 0.5) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(color.rgb, color.a);\\n}\",r.pickVertex=\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aHi, aLo, dHi;\\nattribute vec4 pick0, pick1;\\n\\nuniform vec2 scaleHi, translateHi, scaleLo, translateLo, screenShape;\\nuniform float width;\\n\\nvarying vec4 pickA, pickB;\\n\\n\\nvec2 project_1_0(vec2 scHi, vec2 trHi, vec2 scLo, vec2 trLo, vec2 posHi, vec2 posLo) {\\n  return (posHi + trHi) * scHi\\n       + (posLo + trLo) * scHi\\n       + (posHi + trHi) * scLo\\n       + (posLo + trLo) * scLo;\\n}\\n\\n\\nvoid main() {\\n  vec2 p = project_1_0(scaleHi, translateHi, scaleLo, translateLo, aHi, aLo);\\n  vec2 n = width * normalize(screenShape.yx * vec2(dHi.y, -dHi.x)) / screenShape.xy;\\n  gl_Position = vec4(p + n, 0, 1);\\n  pickA = pick0;\\n  pickB = pick1;\\n}\",r.pickFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 pickOffset;\\n\\nvarying vec4 pickA, pickB;\\n\\nvoid main() {\\n  vec4 fragId = vec4(pickA.xyz, 0.0);\\n  if(pickB.w > pickA.w) {\\n    fragId.xyz = pickB.xyz;\\n  }\\n\\n  fragId += pickOffset;\\n\\n  fragId.y += floor(fragId.x / 256.0);\\n  fragId.x -= floor(fragId.x / 256.0) * 256.0;\\n\\n  fragId.z += floor(fragId.y / 256.0);\\n  fragId.y -= floor(fragId.y / 256.0) * 256.0;\\n\\n  fragId.w += floor(fragId.z / 256.0);\\n  fragId.z -= floor(fragId.z / 256.0) * 256.0;\\n\\n  gl_FragColor = fragId / 255.0;\\n}\",r.fillVertex=\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aHi, aLo, dHi;\\n\\nuniform vec2 scaleHi, translateHi, scaleLo, translateLo, projectAxis;\\nuniform float projectValue, depth;\\n\\n\\nvec2 project_1_0(vec2 scHi, vec2 trHi, vec2 scLo, vec2 trLo, vec2 posHi, vec2 posLo) {\\n  return (posHi + trHi) * scHi\\n       + (posLo + trLo) * scHi\\n       + (posHi + trHi) * scLo\\n       + (posLo + trLo) * scLo;\\n}\\n\\n\\nvoid main() {\\n  vec2 p = project_1_0(scaleHi, translateHi, scaleLo, translateLo, aHi, aLo);\\n  if(dHi.y < 0.0 || (dHi.y == 0.0 && dHi.x < 0.0)) {\\n    if(dot(p, projectAxis) < projectValue) {\\n      p = p * (1.0 - abs(projectAxis)) + projectAxis * projectValue;\\n    }\\n  }\\n  gl_Position = vec4(p, depth, 1);\\n}\",r.fillFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = vec4(color.rgb * color.a, color.a);\\n}\"},{}],154:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s,l){this.plot=t,this.dashPattern=e,this.lineBufferHi=r,this.lineBufferLo=n,this.pickBuffer=i,this.lineShader=a,this.mitreShader=o,this.fillShader=s,this.pickShader=l,this.usingDashes=!1,this.bounds=[1/0,1/0,-1/0,-1/0],this.width=1,this.color=[0,0,1,1],this.fill=[!1,!1,!1,!1],this.fillColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.data=null,this.numPoints=0,this.vertCount=0,this.pickOffset=0}function i(t){return t.map(function(t){return t.slice()})}function a(t,e){var r=t.gl,i=s(r),a=s(r),u=s(r),c=new n(t,l(r,[1,1]),i,a,u,o(r,h.lineVertex,h.lineFragment),o(r,h.mitreVertex,h.mitreFragment),o(r,h.fillVertex,h.fillFragment),o(r,h.pickVertex,h.pickFragment));return t.addObject(c),c.update(e),c}e.exports=a;var o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"gl-texture2d\"),u=t(\"ndarray\"),c=t(\"typedarray-pool\"),h=t(\"./lib/shaders\"),f=n.prototype;f.setProjectionModel=function(){var t={scaleHi:new Float32Array([0,0]),scaleLo:new Float32Array([0,0]),translateHi:new Float32Array([0,0]),translateLo:new Float32Array([0,0]),screenShape:[0,0]};return function(){var e=this.bounds,r=this.plot.viewBox,n=this.plot.dataBox,i=e[2]-e[0],a=e[3]-e[1],o=n[2]-n[0],s=n[3]-n[1],l=r[2]-r[0],u=r[3]-r[1],c=2*i/o,h=2*a/s,f=(e[0]-n[0]-.5*o)/i,d=(e[1]-n[1]-.5*s)/a;return t.scaleHi[0]=c,t.scaleHi[1]=h,t.scaleLo[0]=c-t.scaleHi[0],t.scaleLo[1]=h-t.scaleHi[1],t.translateHi[0]=f,t.translateHi[1]=d,t.translateLo[0]=f-t.translateHi[0],t.translateLo[1]=d-t.translateHi[1],t.screenShape[0]=l,t.screenShape[1]=u,t}}(),f.setProjectionUniforms=function(t,e){t.scaleHi=e.scaleHi,t.scaleLo=e.scaleLo,t.translateHi=e.translateHi,t.translateLo=e.translateLo,t.screenShape=e.screenShape},f.draw=function(){var t=[1,0],e=[-1,0],r=[0,1],n=[0,-1];return function(){var i=this.vertCount;if(i){var a=this.setProjectionModel(),o=this.plot,s=this.width,l=o.gl,u=o.pixelRatio,c=this.color,h=this.fillShader.attributes;this.lineBufferLo.bind(),h.aLo.pointer(l.FLOAT,!1,16,0),this.lineBufferHi.bind();var f=this.fill;if(f[0]||f[1]||f[2]||f[3]){var d=this.fillShader;d.bind();var p=d.uniforms;this.setProjectionUniforms(p,a),p.depth=o.nextDepthValue(),h.aHi.pointer(l.FLOAT,!1,16,0),h.dHi.pointer(l.FLOAT,!1,16,8),l.depthMask(!0),l.enable(l.DEPTH_TEST);var m=this.fillColor;f[0]&&(p.color=m[0],p.projectAxis=e,p.projectValue=1,l.drawArrays(l.TRIANGLES,0,i)),f[1]&&(p.color=m[1],p.projectAxis=n,p.projectValue=1,l.drawArrays(l.TRIANGLES,0,i)),f[2]&&(p.color=m[2],p.projectAxis=t,p.projectValue=1,l.drawArrays(l.TRIANGLES,0,i)),f[3]&&(p.color=m[3],p.projectAxis=r,p.projectValue=1,l.drawArrays(l.TRIANGLES,0,i)),l.depthMask(!1),l.disable(l.DEPTH_TEST)}var g=this.lineShader;g.bind(),this.lineBufferLo.bind(),g.attributes.aLo.pointer(l.FLOAT,!1,16,0),g.attributes.dLo.pointer(l.FLOAT,!1,16,8),this.lineBufferHi.bind();var v=g.uniforms;this.setProjectionUniforms(v,a),v.color=c,v.width=s*u,v.dashPattern=this.dashPattern.bind(),v.dashLength=this.dashLength*u;var y=g.attributes;if(y.aHi.pointer(l.FLOAT,!1,16,0),y.dHi.pointer(l.FLOAT,!1,16,8),l.drawArrays(l.TRIANGLES,0,i),s>2&&!this.usingDashes){var b=this.mitreShader;this.lineBufferLo.bind(),b.attributes.aLo.pointer(l.FLOAT,!1,48,0),this.lineBufferHi.bind(),b.bind();var x=b.uniforms;this.setProjectionUniforms(x,a),x.color=c,x.radius=s*u,b.attributes.aHi.pointer(l.FLOAT,!1,48,0),l.drawArrays(l.POINTS,0,i/3|0)}}}}(),f.drawPick=function(){var t=[0,0,0,0];return function(e){var r=this.vertCount,n=this.numPoints;if(this.pickOffset=e,!r)return e+n;var i=this.setProjectionModel(),a=this.plot,o=this.width,s=a.gl,l=a.pickPixelRatio,u=this.pickShader,c=this.pickBuffer;t[0]=255&e,t[1]=e>>>8&255,t[2]=e>>>16&255,t[3]=e>>>24,u.bind();var h=u.uniforms;this.setProjectionUniforms(h,i),h.width=o*l,h.pickOffset=t;var f=u.attributes;return this.lineBufferHi.bind(),f.aHi.pointer(s.FLOAT,!1,16,0),f.dHi.pointer(s.FLOAT,!1,16,8),this.lineBufferLo.bind(),f.aLo.pointer(s.FLOAT,!1,16,0),c.bind(),f.pick0.pointer(s.UNSIGNED_BYTE,!1,8,0),f.pick1.pointer(s.UNSIGNED_BYTE,!1,8,4),s.drawArrays(s.TRIANGLES,0,r),e+n}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.numPoints;if(r<n||r>=n+i)return null;var a=r-n,o=this.data;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}},f.update=function(t){t=t||{};var e,r,n,a,o,s=this.plot.gl;this.color=(t.color||[0,0,1,1]).slice(),this.width=+(t.width||1),this.fill=(t.fill||[!1,!1,!1,!1]).slice(),this.fillColor=i(t.fillColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var h=t.dashes||[1],f=0;for(e=0;e<h.length;++e)f+=h[e];var d=c.mallocUint8(f);n=0;var p=255;for(e=0;e<h.length;++e){for(r=0;r<h[e];++r)d[n++]=p;p^=255}this.dashPattern.dispose(),this.usingDashes=h.length>1,this.dashPattern=l(s,u(d,[f,1,4],[1,0,0])),this.dashPattern.minFilter=s.NEAREST,this.dashPattern.magFilter=s.NEAREST,this.dashLength=f,c.free(d);var m=t.positions;this.data=m;var g=this.bounds;g[0]=g[1]=1/0,g[2]=g[3]=-1/0;var v=this.numPoints=m.length>>>1;if(0!==v){for(e=0;e<v;++e)a=m[2*e],o=m[2*e+1],isNaN(a)||isNaN(o)||(g[0]=Math.min(g[0],a),g[1]=Math.min(g[1],o),g[2]=Math.max(g[2],a),g[3]=Math.max(g[3],o));g[0]===g[2]&&(g[2]+=1),g[3]===g[1]&&(g[3]+=1);var y=c.mallocFloat64(24*(v-1)),b=c.mallocFloat32(24*(v-1)),x=c.mallocFloat32(24*(v-1)),_=c.mallocUint32(12*(v-1)),w=b.length,M=_.length;n=v;for(var k=0;n>1;){var A=--n;a=m[2*n],o=m[2*n+1];var T=A-1,S=m[2*T],E=m[2*T+1];if(!(isNaN(a)||isNaN(o)||isNaN(S)||isNaN(E))){k+=1,a=(a-g[0])/(g[2]-g[0]),o=(o-g[1])/(g[3]-g[1]);var L=(S=(S-g[0])/(g[2]-g[0]))-a,C=(E=(E-g[1])/(g[3]-g[1]))-o,z=A|1<<24,D=A-1,I=A,P=A-1|1<<24;y[--w]=-C,y[--w]=-L,y[--w]=o,y[--w]=a,_[--M]=z,_[--M]=D,y[--w]=C,y[--w]=L,y[--w]=E,y[--w]=S,_[--M]=I,_[--M]=P,y[--w]=-C,y[--w]=-L,y[--w]=E,y[--w]=S,_[--M]=I,_[--M]=P,y[--w]=C,y[--w]=L,y[--w]=E,y[--w]=S,_[--M]=I,_[--M]=P,y[--w]=-C,y[--w]=-L,y[--w]=o,y[--w]=a,_[--M]=z,_[--M]=D,y[--w]=C,y[--w]=L,y[--w]=o,y[--w]=a,_[--M]=z,_[--M]=D}}for(e=0;e<y.length;e++)b[e]=y[e],x[e]=y[e]-b[e];this.vertCount=6*k,this.lineBufferHi.update(b.subarray(w)),this.lineBufferLo.update(x.subarray(w)),this.pickBuffer.update(_.subarray(M)),c.free(y),c.free(b),c.free(x),c.free(_)}},f.dispose=function(){this.plot.removeObject(this),this.lineBufferLo.dispose(),this.lineBufferHi.dispose(),this.pickBuffer.dispose(),this.lineShader.dispose(),this.mitreShader.dispose(),this.fillShader.dispose(),this.pickShader.dispose(),this.dashPattern.dispose()}},{\"./lib/shaders\":153,\"gl-buffer\":141,\"gl-shader\":239,\"gl-texture2d\":251,ndarray:449,\"typedarray-pool\":521}],155:[function(t,e,r){var n=t(\"gl-shader\"),i=\"precision mediump 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\\nvoid main() {\\n  vec4 projected = projection * view * model * vec4(position, 1.0);\\n  vec4 tangentClip = projection * view * model * vec4(nextPosition - position, 0.0);\\n  vec2 tangent = normalize(screenShape * tangentClip.xy);\\n  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(tangent.y, -tangent.x) / screenShape;\\n\\n  gl_Position = vec4(projected.xy + projected.w * offset, projected.zw);\\n\\n  worldPosition = position;\\n  pixelArcLength = arcLength;\\n  fragColor = color;\\n}\\n\",a=[{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 n(t,i,\"precision mediump float;\\n#define GLSLIFY 1\\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(any(lessThan(worldPosition, clipBounds[0])) || any(greaterThan(worldPosition, clipBounds[1]))) {\\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\",null,a)},r.createPickShader=function(t){return n(t,i,\"precision mediump float;\\n#define GLSLIFY 1\\n\\n#define FLOAT_MAX  1.70141184e38\\n#define FLOAT_MIN  1.17549435e-38\\n\\nlowp vec4 encode_float_1_0(highp float v) {\\n  highp 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  highp vec4 c = vec4(0,0,0,0);\\n\\n  //Compute exponent and mantissa\\n  highp float e = floor(log2(av));\\n  highp 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  highp 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\\n\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(worldPosition, clipBounds[0])) || any(greaterThan(worldPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(pickId/255.0, encode_float_1_0(pixelArcLength).xyz);\\n}\",null,a)}},{\"gl-shader\":239}],156:[function(t,e,r){\"use strict\";function n(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 i(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 a(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function o(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.dirty=!0,this.pixelRatio=1}function s(t){var e=t.gl||t.scene&&t.scene.gl,r=m(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 n=g(e);n.attributes.position.location=0,n.attributes.nextPosition.location=1,n.attributes.arcLength.location=2,n.attributes.lineWidth.location=3,n.attributes.color.location=4;for(var i=l(e),a=u(e,[{buffer:i,size:3,offset:0,stride:48},{buffer:i,size:3,offset:12,stride:48},{buffer:i,size:1,offset:24,stride:48},{buffer:i,size:1,offset:28,stride:48},{buffer:i,size:4,offset:32,stride:48}]),s=d(new Array(1024),[256,1,4]),h=0;h<1024;++h)s.data[h]=255;var f=c(e,s);f.wrap=e.REPEAT;var p=new o(e,r,n,i,a,f);return p.update(t),p}e.exports=s;var l=t(\"gl-buffer\"),u=t(\"gl-vao\"),c=t(\"gl-texture2d\"),h=t(\"glsl-read-float\"),f=t(\"binary-search-bounds\"),d=t(\"ndarray\"),p=t(\"./lib/shaders\"),m=p.createShader,g=p.createPickShader,v=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],y=o.prototype;y.isTransparent=function(){return this.opacity<1},y.isOpaque=function(){return this.opacity>=1},y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.drawTransparent=y.draw=function(t){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||v,view:t.view||v,projection:t.projection||v,clipBounds:i(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)},y.drawPick=function(t){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||v,view:t.view||v,projection:t.projection||v,pickId:this.pickId,clipBounds:i(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount)},y.update=function(t){var e,r;this.dirty=!0;var i=!!t.connectGaps;\"dashScale\"in t&&(this.dashScale=t.dashScale),\"opacity\"in t&&(this.opacity=+t.opacity);var a=t.position||t.positions;if(a){var o=t.color||t.colors||[0,0,0,1],s=t.lineWidth||1,l=[],u=[],c=[],h=0,p=0,m=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],g=!1;t:for(e=1;e<a.length;++e){var v=a[e-1],y=a[e];for(u.push(h),c.push(v.slice()),r=0;r<3;++r){if(isNaN(v[r])||isNaN(y[r])||!isFinite(v[r])||!isFinite(y[r])){if(!i&&l.length>0){for(var b=0;b<24;++b)l.push(l[l.length-12]);p+=2,g=!0}continue t}m[0][r]=Math.min(m[0][r],v[r],y[r]),m[1][r]=Math.max(m[1][r],v[r],y[r])}var x,_;Array.isArray(o[0])?(x=o[e-1],_=o[e]):x=_=o,3===x.length&&(x=[x[0],x[1],x[2],1]),3===_.length&&(_=[_[0],_[1],_[2],1]);var w;w=Array.isArray(s)?s[e-1]:s;var M=h;if(h+=n(v,y),g){for(r=0;r<2;++r)l.push(v[0],v[1],v[2],y[0],y[1],y[2],M,w,x[0],x[1],x[2],x[3]);p+=2,g=!1}l.push(v[0],v[1],v[2],y[0],y[1],y[2],M,w,x[0],x[1],x[2],x[3],v[0],v[1],v[2],y[0],y[1],y[2],M,-w,x[0],x[1],x[2],x[3],y[0],y[1],y[2],v[0],v[1],v[2],h,-w,_[0],_[1],_[2],_[3],y[0],y[1],y[2],v[0],v[1],v[2],h,w,_[0],_[1],_[2],_[3]),p+=4}if(this.buffer.update(l),u.push(h),c.push(a[a.length-1].slice()),this.bounds=m,this.vertexCount=p,this.points=c,this.arcLength=u,\"dashes\"in t){var k=t.dashes.slice();for(k.unshift(0),e=1;e<k.length;++e)k[e]=k[e-1]+k[e];var A=d(new Array(1024),[256,1,4]);for(e=0;e<256;++e){for(r=0;r<4;++r)A.set(e,0,r,0);1&f.le(k,k[k.length-1]*e/255)?A.set(e,0,0,0):A.set(e,0,0,255)}this.texture.setPixels(A)}}},y.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()},y.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=h(t.value[0],t.value[1],t.value[2],0),r=f.le(this.arcLength,e);if(r<0)return null;if(r===this.arcLength.length-1)return new a(this.arcLength[this.arcLength.length-1],this.points[this.points.length-1].slice(),r);for(var n=this.points[r],i=this.points[Math.min(r+1,this.points.length-1)],o=(e-this.arcLength[r])/(this.arcLength[r+1]-this.arcLength[r]),s=1-o,l=[0,0,0],u=0;u<3;++u)l[u]=s*n[u]+o*i[u];var c=Math.min(o<.5?r:r+1,this.points.length-1);return new a(e,l,c,this.points[c])}},{\"./lib/shaders\":155,\"binary-search-bounds\":59,\"gl-buffer\":141,\"gl-texture2d\":251,\"gl-vao\":255,\"glsl-read-float\":262,ndarray:449}],157:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=r*a-i*n;return o?(o=1/o,t[0]=a*o,t[1]=-n*o,t[2]=-i*o,t[3]=r*o,t):null}e.exports=n},{}],158:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],h=c*o-s*u,f=-c*a+s*l,d=u*a-o*l,p=r*h+n*f+i*d;return p?(p=1/p,t[0]=h*p,t[1]=(-c*n+i*u)*p,t[2]=(s*n-i*o)*p,t[3]=f*p,t[4]=(c*r-i*l)*p,t[5]=(-s*r+i*a)*p,t[6]=d*p,t[7]=(-u*r+n*l)*p,t[8]=(o*r-n*a)*p,t):null}e.exports=n},{}],159:[function(t,e,r){function n(t){var e=new Float32Array(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}e.exports=n},{}],160:[function(t,e,r){function n(){var t=new Float32Array(16);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}e.exports=n},{}],161:[function(t,e,r){function n(t){var e=t[0],r=t[1],n=t[2],i=t[3],a=t[4],o=t[5],s=t[6],l=t[7],u=t[8],c=t[9],h=t[10],f=t[11],d=t[12],p=t[13],m=t[14],g=t[15];return(e*o-r*a)*(h*g-f*m)-(e*s-n*a)*(c*g-f*p)+(e*l-i*a)*(c*m-h*p)+(r*s-n*o)*(u*g-f*d)-(r*l-i*o)*(u*m-h*d)+(n*l-i*s)*(u*p-c*d)}e.exports=n},{}],162:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=r+r,s=n+n,l=i+i,u=r*o,c=n*o,h=n*s,f=i*o,d=i*s,p=i*l,m=a*o,g=a*s,v=a*l;return t[0]=1-h-p,t[1]=c+v,t[2]=f-g,t[3]=0,t[4]=c-v,t[5]=1-u-p,t[6]=d+m,t[7]=0,t[8]=f+g,t[9]=d-m,t[10]=1-u-h,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}e.exports=n},{}],163:[function(t,e,r){function n(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=n+n,l=i+i,u=a+a,c=n*s,h=n*l,f=n*u,d=i*l,p=i*u,m=a*u,g=o*s,v=o*l,y=o*u;return t[0]=1-(d+m),t[1]=h+y,t[2]=f-v,t[3]=0,t[4]=h-y,t[5]=1-(c+m),t[6]=p+g,t[7]=0,t[8]=f+v,t[9]=p-g,t[10]=1-(c+d),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}e.exports=n},{}],164:[function(t,e,r){function n(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}e.exports=n},{}],165:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],h=e[9],f=e[10],d=e[11],p=e[12],m=e[13],g=e[14],v=e[15],y=r*s-n*o,b=r*l-i*o,x=r*u-a*o,_=n*l-i*s,w=n*u-a*s,M=i*u-a*l,k=c*m-h*p,A=c*g-f*p,T=c*v-d*p,S=h*g-f*m,E=h*v-d*m,L=f*v-d*g,C=y*L-b*E+x*S+_*T-w*A+M*k;return C?(C=1/C,t[0]=(s*L-l*E+u*S)*C,t[1]=(i*E-n*L-a*S)*C,t[2]=(m*M-g*w+v*_)*C,t[3]=(f*w-h*M-d*_)*C,t[4]=(l*T-o*L-u*A)*C,t[5]=(r*L-i*T+a*A)*C,t[6]=(g*x-p*M-v*b)*C,t[7]=(c*M-f*x+d*b)*C,t[8]=(o*E-s*T+u*k)*C,t[9]=(n*T-r*E-a*k)*C,t[10]=(p*w-m*x+v*y)*C,t[11]=(h*x-c*w-d*y)*C,t[12]=(s*A-o*S-l*k)*C,t[13]=(r*S-n*A+i*k)*C,t[14]=(m*b-p*_-g*y)*C,t[15]=(c*_-h*b+f*y)*C,t):null}e.exports=n},{}],166:[function(t,e,r){function n(t,e,r,n){var a,o,s,l,u,c,h,f,d,p,m=e[0],g=e[1],v=e[2],y=n[0],b=n[1],x=n[2],_=r[0],w=r[1],M=r[2];return Math.abs(m-_)<1e-6&&Math.abs(g-w)<1e-6&&Math.abs(v-M)<1e-6?i(t):(h=m-_,f=g-w,d=v-M,p=1/Math.sqrt(h*h+f*f+d*d),h*=p,f*=p,d*=p,a=b*d-x*f,o=x*h-y*d,s=y*f-b*h,p=Math.sqrt(a*a+o*o+s*s),p?(a*=p=1/p,o*=p,s*=p):(a=0,o=0,s=0),l=f*s-d*o,u=d*a-h*s,c=h*o-f*a,p=Math.sqrt(l*l+u*u+c*c),p?(l*=p=1/p,u*=p,c*=p):(l=0,u=0,c=0),t[0]=a,t[1]=l,t[2]=h,t[3]=0,t[4]=o,t[5]=u,t[6]=f,t[7]=0,t[8]=s,t[9]=c,t[10]=d,t[11]=0,t[12]=-(a*m+o*g+s*v),t[13]=-(l*m+u*g+c*v),t[14]=-(h*m+f*g+d*v),t[15]=1,t)}var i=t(\"./identity\");e.exports=n},{\"./identity\":164}],167:[function(t,e,r){function n(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],u=e[6],c=e[7],h=e[8],f=e[9],d=e[10],p=e[11],m=e[12],g=e[13],v=e[14],y=e[15],b=r[0],x=r[1],_=r[2],w=r[3];return 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t[0]=d*n+f*o,t[1]=d*i+f*s,t[2]=d*a+f*l,t[3]=d*o-f*n,t[4]=d*s-f*i,t[5]=d*l-f*a,t[6]=u,t[7]=c,t[8]=h,t},i.scale=function(t,e,r){var n=r[0],i=r[1];return t[0]=n*e[0],t[1]=n*e[1],t[2]=n*e[2],t[3]=i*e[3],t[4]=i*e[4],t[5]=i*e[5],t[6]=e[6],t[7]=e[7],t[8]=e[8],t},i.fromTranslation=function(t,e){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=1,t[5]=0,t[6]=e[0],t[7]=e[1],t[8]=1,t},i.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},i.fromScaling=function(t,e){return t[0]=e[0],t[1]=0,t[2]=0,t[3]=0,t[4]=e[1],t[5]=0,t[6]=0,t[7]=0,t[8]=1,t},i.fromMat2d=function(t,e){return t[0]=e[0],t[1]=e[1],t[2]=0,t[3]=e[2],t[4]=e[3],t[5]=0,t[6]=e[4],t[7]=e[5],t[8]=1,t},i.fromQuat=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=r+r,s=n+n,l=i+i,u=r*o,c=n*o,h=n*s,f=i*o,d=i*s,p=i*l,m=a*o,g=a*s,v=a*l;return t[0]=1-h-p,t[3]=c-v,t[6]=f+g,t[1]=c+v,t[4]=1-u-p,t[7]=d-m,t[2]=f-g,t[5]=d+m,t[8]=1-u-h,t},i.normalFromMat4=function(t,e){var 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t[0]=e[0]+r[0],t[1]=e[1]+r[1],t[2]=e[2]+r[2],t[3]=e[3]+r[3],t[4]=e[4]+r[4],t[5]=e[5]+r[5],t[6]=e[6]+r[6],t[7]=e[7]+r[7],t[8]=e[8]+r[8],t},i.subtract=function(t,e,r){return t[0]=e[0]-r[0],t[1]=e[1]-r[1],t[2]=e[2]-r[2],t[3]=e[3]-r[3],t[4]=e[4]-r[4],t[5]=e[5]-r[5],t[6]=e[6]-r[6],t[7]=e[7]-r[7],t[8]=e[8]-r[8],t},i.sub=i.subtract,i.multiplyScalar=function(t,e,r){return t[0]=e[0]*r,t[1]=e[1]*r,t[2]=e[2]*r,t[3]=e[3]*r,t[4]=e[4]*r,t[5]=e[5]*r,t[6]=e[6]*r,t[7]=e[7]*r,t[8]=e[8]*r,t},i.multiplyScalarAndAdd=function(t,e,r,n){return t[0]=e[0]+r[0]*n,t[1]=e[1]+r[1]*n,t[2]=e[2]+r[2]*n,t[3]=e[3]+r[3]*n,t[4]=e[4]+r[4]*n,t[5]=e[5]+r[5]*n,t[6]=e[6]+r[6]*n,t[7]=e[7]+r[7]*n,t[8]=e[8]+r[8]*n,t},i.exactEquals=function(t,e){return t[0]===e[0]&&t[1]===e[1]&&t[2]===e[2]&&t[3]===e[3]&&t[4]===e[4]&&t[5]===e[5]&&t[6]===e[6]&&t[7]===e[7]&&t[8]===e[8]},i.equals=function(t,e){var r=t[0],i=t[1],a=t[2],o=t[3],s=t[4],l=t[5],u=t[6],c=t[7],h=t[8],f=e[0],d=e[1],p=e[2],m=e[3],g=e[4],v=e[5],y=t[6],b=e[7],x=e[8];return 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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},i.copy=function(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],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],t},i.fromValues=function(t,e,r,i,a,o,s,l,u,c,h,f,d,p,m,g){var v=new n.ARRAY_TYPE(16);return v[0]=t,v[1]=e,v[2]=r,v[3]=i,v[4]=a,v[5]=o,v[6]=s,v[7]=l,v[8]=u,v[9]=c,v[10]=h,v[11]=f,v[12]=d,v[13]=p,v[14]=m,v[15]=g,v},i.set=function(t,e,r,n,i,a,o,s,l,u,c,h,f,d,p,m,g){return t[0]=e,t[1]=r,t[2]=n,t[3]=i,t[4]=a,t[5]=o,t[6]=s,t[7]=l,t[8]=u,t[9]=c,t[10]=h,t[11]=f,t[12]=d,t[13]=p,t[14]=m,t[15]=g,t},i.identity=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},i.scalar.transpose=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},i.SIMD.transpose=function(t,e){var r,n,i,a,o,s,l,u,c,h;return r=SIMD.Float32x4.load(e,0),n=SIMD.Float32x4.load(e,4),i=SIMD.Float32x4.load(e,8),a=SIMD.Float32x4.load(e,12),o=SIMD.Float32x4.shuffle(r,n,0,1,4,5),s=SIMD.Float32x4.shuffle(i,a,0,1,4,5),l=SIMD.Float32x4.shuffle(o,s,0,2,4,6),u=SIMD.Float32x4.shuffle(o,s,1,3,5,7),SIMD.Float32x4.store(t,0,l),SIMD.Float32x4.store(t,4,u),o=SIMD.Float32x4.shuffle(r,n,2,3,6,7),s=SIMD.Float32x4.shuffle(i,a,2,3,6,7),c=SIMD.Float32x4.shuffle(o,s,0,2,4,6),h=SIMD.Float32x4.shuffle(o,s,1,3,5,7),SIMD.Float32x4.store(t,8,c),SIMD.Float32x4.store(t,12,h),t},i.transpose=n.USE_SIMD?i.SIMD.transpose:i.scalar.transpose,i.scalar.invert=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],u=e[7],c=e[8],h=e[9],f=e[10],d=e[11],p=e[12],m=e[13],g=e[14],v=e[15],y=r*s-n*o,b=r*l-i*o,x=r*u-a*o,_=n*l-i*s,w=n*u-a*s,M=i*u-a*l,k=c*m-h*p,A=c*g-f*p,T=c*v-d*p,S=h*g-f*m,E=h*v-d*m,L=f*v-d*g,C=y*L-b*E+x*S+_*T-w*A+M*k;return C?(C=1/C,t[0]=(s*L-l*E+u*S)*C,t[1]=(i*E-n*L-a*S)*C,t[2]=(m*M-g*w+v*_)*C,t[3]=(f*w-h*M-d*_)*C,t[4]=(l*T-o*L-u*A)*C,t[5]=(r*L-i*T+a*A)*C,t[6]=(g*x-p*M-v*b)*C,t[7]=(c*M-f*x+d*b)*C,t[8]=(o*E-s*T+u*k)*C,t[9]=(n*T-r*E-a*k)*C,t[10]=(p*w-m*x+v*y)*C,t[11]=(h*x-c*w-d*y)*C,t[12]=(s*A-o*S-l*k)*C,t[13]=(r*S-n*A+i*k)*C,t[14]=(m*b-p*_-g*y)*C,t[15]=(c*_-h*b+f*y)*C,t):null},i.SIMD.invert=function(t,e){var r,n,i,a,o,s,l,u,c,h,f=SIMD.Float32x4.load(e,0),d=SIMD.Float32x4.load(e,4),p=SIMD.Float32x4.load(e,8),m=SIMD.Float32x4.load(e,12);return o=SIMD.Float32x4.shuffle(f,d,0,1,4,5),n=SIMD.Float32x4.shuffle(p,m,0,1,4,5),r=SIMD.Float32x4.shuffle(o,n,0,2,4,6),n=SIMD.Float32x4.shuffle(n,o,1,3,5,7),o=SIMD.Float32x4.shuffle(f,d,2,3,6,7),a=SIMD.Float32x4.shuffle(p,m,2,3,6,7),i=SIMD.Float32x4.shuffle(o,a,0,2,4,6),a=SIMD.Float32x4.shuffle(a,o,1,3,5,7),o=SIMD.Float32x4.mul(i,a),o=SIMD.Float32x4.swizzle(o,1,0,3,2),s=SIMD.Float32x4.mul(n,o),l=SIMD.Float32x4.mul(r,o),o=SIMD.Float32x4.swizzle(o,2,3,0,1),s=SIMD.Float32x4.sub(SIMD.Float32x4.mul(n,o),s),l=SIMD.Float32x4.sub(SIMD.Float32x4.mul(r,o),l),l=SIMD.Float32x4.swizzle(l,2,3,0,1),o=SIMD.Float32x4.mul(n,i),o=SIMD.Float32x4.swizzle(o,1,0,3,2),s=SIMD.Float32x4.add(SIMD.Float32x4.mul(a,o),s),c=SIMD.Float32x4.mul(r,o),o=SIMD.Float32x4.swizzle(o,2,3,0,1),s=SIMD.Float32x4.sub(s,SIMD.Float32x4.mul(a,o)),c=SIMD.Float32x4.sub(SIMD.Float32x4.mul(r,o),c),c=SIMD.Float32x4.swizzle(c,2,3,0,1),o=SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(n,2,3,0,1),a),o=SIMD.Float32x4.swizzle(o,1,0,3,2),i=SIMD.Float32x4.swizzle(i,2,3,0,1),s=SIMD.Float32x4.add(SIMD.Float32x4.mul(i,o),s),u=SIMD.Float32x4.mul(r,o),o=SIMD.Float32x4.swizzle(o,2,3,0,1),s=SIMD.Float32x4.sub(s,SIMD.Float32x4.mul(i,o)),u=SIMD.Float32x4.sub(SIMD.Float32x4.mul(r,o),u),u=SIMD.Float32x4.swizzle(u,2,3,0,1),o=SIMD.Float32x4.mul(r,n),o=SIMD.Float32x4.swizzle(o,1,0,3,2),u=SIMD.Float32x4.add(SIMD.Float32x4.mul(a,o),u),c=SIMD.Float32x4.sub(SIMD.Float32x4.mul(i,o),c),o=SIMD.Float32x4.swizzle(o,2,3,0,1),u=SIMD.Float32x4.sub(SIMD.Float32x4.mul(a,o),u),c=SIMD.Float32x4.sub(c,SIMD.Float32x4.mul(i,o)),o=SIMD.Float32x4.mul(r,a),o=SIMD.Float32x4.swizzle(o,1,0,3,2),l=SIMD.Float32x4.sub(l,SIMD.Float32x4.mul(i,o)),u=SIMD.Float32x4.add(SIMD.Float32x4.mul(n,o),u),o=SIMD.Float32x4.swizzle(o,2,3,0,1),l=SIMD.Float32x4.add(SIMD.Float32x4.mul(i,o),l),u=SIMD.Float32x4.sub(u,SIMD.Float32x4.mul(n,o)),o=SIMD.Float32x4.mul(r,i),o=SIMD.Float32x4.swizzle(o,1,0,3,2),l=SIMD.Float32x4.add(SIMD.Float32x4.mul(a,o),l),c=SIMD.Float32x4.sub(c,SIMD.Float32x4.mul(n,o)),o=SIMD.Float32x4.swizzle(o,2,3,0,1),l=SIMD.Float32x4.sub(l,SIMD.Float32x4.mul(a,o)),c=SIMD.Float32x4.add(SIMD.Float32x4.mul(n,o),c),h=SIMD.Float32x4.mul(r,s),h=SIMD.Float32x4.add(SIMD.Float32x4.swizzle(h,2,3,0,1),h),h=SIMD.Float32x4.add(SIMD.Float32x4.swizzle(h,1,0,3,2),h),o=SIMD.Float32x4.reciprocalApproximation(h),h=SIMD.Float32x4.sub(SIMD.Float32x4.add(o,o),SIMD.Float32x4.mul(h,SIMD.Float32x4.mul(o,o))),(h=SIMD.Float32x4.swizzle(h,0,0,0,0))?(SIMD.Float32x4.store(t,0,SIMD.Float32x4.mul(h,s)),SIMD.Float32x4.store(t,4,SIMD.Float32x4.mul(h,l)),SIMD.Float32x4.store(t,8,SIMD.Float32x4.mul(h,u)),SIMD.Float32x4.store(t,12,SIMD.Float32x4.mul(h,c)),t):null},i.invert=n.USE_SIMD?i.SIMD.invert:i.scalar.invert,i.scalar.adjoint=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],u=e[7],c=e[8],h=e[9],f=e[10],d=e[11],p=e[12],m=e[13],g=e[14],v=e[15];return t[0]=s*(f*v-d*g)-h*(l*v-u*g)+m*(l*d-u*f),t[1]=-(n*(f*v-d*g)-h*(i*v-a*g)+m*(i*d-a*f)),t[2]=n*(l*v-u*g)-s*(i*v-a*g)+m*(i*u-a*l),t[3]=-(n*(l*d-u*f)-s*(i*d-a*f)+h*(i*u-a*l)),t[4]=-(o*(f*v-d*g)-c*(l*v-u*g)+p*(l*d-u*f)),t[5]=r*(f*v-d*g)-c*(i*v-a*g)+p*(i*d-a*f),t[6]=-(r*(l*v-u*g)-o*(i*v-a*g)+p*(i*u-a*l)),t[7]=r*(l*d-u*f)-o*(i*d-a*f)+c*(i*u-a*l),t[8]=o*(h*v-d*m)-c*(s*v-u*m)+p*(s*d-u*h),t[9]=-(r*(h*v-d*m)-c*(n*v-a*m)+p*(n*d-a*h)),t[10]=r*(s*v-u*m)-o*(n*v-a*m)+p*(n*u-a*s),t[11]=-(r*(s*d-u*h)-o*(n*d-a*h)+c*(n*u-a*s)),t[12]=-(o*(h*g-f*m)-c*(s*g-l*m)+p*(s*f-l*h)),t[13]=r*(h*g-f*m)-c*(n*g-i*m)+p*(n*f-i*h),t[14]=-(r*(s*g-l*m)-o*(n*g-i*m)+p*(n*l-i*s)),t[15]=r*(s*f-l*h)-o*(n*f-i*h)+c*(n*l-i*s),t},i.SIMD.adjoint=function(t,e){var r,n,i,a,o,s,l,u,c,h=SIMD.Float32x4.load(e,0),f=SIMD.Float32x4.load(e,4),d=SIMD.Float32x4.load(e,8),p=SIMD.Float32x4.load(e,12);return o=SIMD.Float32x4.shuffle(h,f,0,1,4,5),n=SIMD.Float32x4.shuffle(d,p,0,1,4,5),r=SIMD.Float32x4.shuffle(o,n,0,2,4,6),n=SIMD.Float32x4.shuffle(n,o,1,3,5,7),o=SIMD.Float32x4.shuffle(h,f,2,3,6,7),a=SIMD.Float32x4.shuffle(d,p,2,3,6,7),i=SIMD.Float32x4.shuffle(o,a,0,2,4,6),a=SIMD.Float32x4.shuffle(a,o,1,3,5,7),o=SIMD.Float32x4.mul(i,a),o=SIMD.Float32x4.swizzle(o,1,0,3,2),s=SIMD.Float32x4.mul(n,o),l=SIMD.Float32x4.mul(r,o),o=SIMD.Float32x4.swizzle(o,2,3,0,1),s=SIMD.Float32x4.sub(SIMD.Float32x4.mul(n,o),s),l=SIMD.Float32x4.sub(SIMD.Float32x4.mul(r,o),l),l=SIMD.Float32x4.swizzle(l,2,3,0,1),o=SIMD.Float32x4.mul(n,i),o=SIMD.Float32x4.swizzle(o,1,0,3,2),s=SIMD.Float32x4.add(SIMD.Float32x4.mul(a,o),s),c=SIMD.Float32x4.mul(r,o),o=SIMD.Float32x4.swizzle(o,2,3,0,1),s=SIMD.Float32x4.sub(s,SIMD.Float32x4.mul(a,o)),c=SIMD.Float32x4.sub(SIMD.Float32x4.mul(r,o),c),c=SIMD.Float32x4.swizzle(c,2,3,0,1),o=SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(n,2,3,0,1),a),o=SIMD.Float32x4.swizzle(o,1,0,3,2),i=SIMD.Float32x4.swizzle(i,2,3,0,1),s=SIMD.Float32x4.add(SIMD.Float32x4.mul(i,o),s),u=SIMD.Float32x4.mul(r,o),o=SIMD.Float32x4.swizzle(o,2,3,0,1),s=SIMD.Float32x4.sub(s,SIMD.Float32x4.mul(i,o)),u=SIMD.Float32x4.sub(SIMD.Float32x4.mul(r,o),u),u=SIMD.Float32x4.swizzle(u,2,3,0,1),o=SIMD.Float32x4.mul(r,n),o=SIMD.Float32x4.swizzle(o,1,0,3,2),u=SIMD.Float32x4.add(SIMD.Float32x4.mul(a,o),u),c=SIMD.Float32x4.sub(SIMD.Float32x4.mul(i,o),c),o=SIMD.Float32x4.swizzle(o,2,3,0,1),u=SIMD.Float32x4.sub(SIMD.Float32x4.mul(a,o),u),c=SIMD.Float32x4.sub(c,SIMD.Float32x4.mul(i,o)),o=SIMD.Float32x4.mul(r,a),o=SIMD.Float32x4.swizzle(o,1,0,3,2),l=SIMD.Float32x4.sub(l,SIMD.Float32x4.mul(i,o)),u=SIMD.Float32x4.add(SIMD.Float32x4.mul(n,o),u),o=SIMD.Float32x4.swizzle(o,2,3,0,1),l=SIMD.Float32x4.add(SIMD.Float32x4.mul(i,o),l),u=SIMD.Float32x4.sub(u,SIMD.Float32x4.mul(n,o)),o=SIMD.Float32x4.mul(r,i),o=SIMD.Float32x4.swizzle(o,1,0,3,2),l=SIMD.Float32x4.add(SIMD.Float32x4.mul(a,o),l),c=SIMD.Float32x4.sub(c,SIMD.Float32x4.mul(n,o)),o=SIMD.Float32x4.swizzle(o,2,3,0,1),l=SIMD.Float32x4.sub(l,SIMD.Float32x4.mul(a,o)),c=SIMD.Float32x4.add(SIMD.Float32x4.mul(n,o),c),SIMD.Float32x4.store(t,0,s),SIMD.Float32x4.store(t,4,l),SIMD.Float32x4.store(t,8,u),SIMD.Float32x4.store(t,12,c),t},i.adjoint=n.USE_SIMD?i.SIMD.adjoint:i.scalar.adjoint,i.determinant=function(t){var e=t[0],r=t[1],n=t[2],i=t[3],a=t[4],o=t[5],s=t[6],l=t[7],u=t[8],c=t[9],h=t[10],f=t[11],d=t[12],p=t[13],m=t[14],g=t[15];return(e*o-r*a)*(h*g-f*m)-(e*s-n*a)*(c*g-f*p)+(e*l-i*a)*(c*m-h*p)+(r*s-n*o)*(u*g-f*d)-(r*l-i*o)*(u*m-h*d)+(n*l-i*s)*(u*p-c*d)},i.SIMD.multiply=function(t,e,r){var n=SIMD.Float32x4.load(e,0),i=SIMD.Float32x4.load(e,4),a=SIMD.Float32x4.load(e,8),o=SIMD.Float32x4.load(e,12),s=SIMD.Float32x4.load(r,0),l=SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(s,0,0,0,0),n),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(s,1,1,1,1),i),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(s,2,2,2,2),a),SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(s,3,3,3,3),o))));SIMD.Float32x4.store(t,0,l);var u=SIMD.Float32x4.load(r,4),c=SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(u,0,0,0,0),n),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(u,1,1,1,1),i),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(u,2,2,2,2),a),SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(u,3,3,3,3),o))));SIMD.Float32x4.store(t,4,c);var h=SIMD.Float32x4.load(r,8),f=SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(h,0,0,0,0),n),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(h,1,1,1,1),i),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(h,2,2,2,2),a),SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(h,3,3,3,3),o))));SIMD.Float32x4.store(t,8,f);var d=SIMD.Float32x4.load(r,12),p=SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(d,0,0,0,0),n),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(d,1,1,1,1),i),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(d,2,2,2,2),a),SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(d,3,3,3,3),o))));return SIMD.Float32x4.store(t,12,p),t},i.scalar.multiply=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],u=e[6],c=e[7],h=e[8],f=e[9],d=e[10],p=e[11],m=e[12],g=e[13],v=e[14],y=e[15],b=r[0],x=r[1],_=r[2],w=r[3];return t[0]=b*n+x*s+_*h+w*m,t[1]=b*i+x*l+_*f+w*g,t[2]=b*a+x*u+_*d+w*v,t[3]=b*o+x*c+_*p+w*y,b=r[4],x=r[5],_=r[6],w=r[7],t[4]=b*n+x*s+_*h+w*m,t[5]=b*i+x*l+_*f+w*g,t[6]=b*a+x*u+_*d+w*v,t[7]=b*o+x*c+_*p+w*y,b=r[8],x=r[9],_=r[10],w=r[11],t[8]=b*n+x*s+_*h+w*m,t[9]=b*i+x*l+_*f+w*g,t[10]=b*a+x*u+_*d+w*v,t[11]=b*o+x*c+_*p+w*y,b=r[12],x=r[13],_=r[14],w=r[15],t[12]=b*n+x*s+_*h+w*m,t[13]=b*i+x*l+_*f+w*g,t[14]=b*a+x*u+_*d+w*v,t[15]=b*o+x*c+_*p+w*y,t},i.multiply=n.USE_SIMD?i.SIMD.multiply:i.scalar.multiply,i.mul=i.multiply,i.scalar.translate=function(t,e,r){var n,i,a,o,s,l,u,c,h,f,d,p,m=r[0],g=r[1],v=r[2];return e===t?(t[12]=e[0]*m+e[4]*g+e[8]*v+e[12],t[13]=e[1]*m+e[5]*g+e[9]*v+e[13],t[14]=e[2]*m+e[6]*g+e[10]*v+e[14],t[15]=e[3]*m+e[7]*g+e[11]*v+e[15]):(n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],u=e[6],c=e[7],h=e[8],f=e[9],d=e[10],p=e[11],t[0]=n,t[1]=i,t[2]=a,t[3]=o,t[4]=s,t[5]=l,t[6]=u,t[7]=c,t[8]=h,t[9]=f,t[10]=d,t[11]=p,t[12]=n*m+s*g+h*v+e[12],t[13]=i*m+l*g+f*v+e[13],t[14]=a*m+u*g+d*v+e[14],t[15]=o*m+c*g+p*v+e[15]),t},i.SIMD.translate=function(t,e,r){var n=SIMD.Float32x4.load(e,0),i=SIMD.Float32x4.load(e,4),a=SIMD.Float32x4.load(e,8),o=SIMD.Float32x4.load(e,12),s=SIMD.Float32x4(r[0],r[1],r[2],0);e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11]),n=SIMD.Float32x4.mul(n,SIMD.Float32x4.swizzle(s,0,0,0,0)),i=SIMD.Float32x4.mul(i,SIMD.Float32x4.swizzle(s,1,1,1,1)),a=SIMD.Float32x4.mul(a,SIMD.Float32x4.swizzle(s,2,2,2,2));var l=SIMD.Float32x4.add(n,SIMD.Float32x4.add(i,SIMD.Float32x4.add(a,o)));return SIMD.Float32x4.store(t,12,l),t},i.translate=n.USE_SIMD?i.SIMD.translate:i.scalar.translate,i.scalar.scale=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},i.SIMD.scale=function(t,e,r){var n,i,a,o=SIMD.Float32x4(r[0],r[1],r[2],0);return n=SIMD.Float32x4.load(e,0),SIMD.Float32x4.store(t,0,SIMD.Float32x4.mul(n,SIMD.Float32x4.swizzle(o,0,0,0,0))),i=SIMD.Float32x4.load(e,4),SIMD.Float32x4.store(t,4,SIMD.Float32x4.mul(i,SIMD.Float32x4.swizzle(o,1,1,1,1))),a=SIMD.Float32x4.load(e,8),SIMD.Float32x4.store(t,8,SIMD.Float32x4.mul(a,SIMD.Float32x4.swizzle(o,2,2,2,2))),t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t},i.scale=n.USE_SIMD?i.SIMD.scale:i.scalar.scale,i.rotate=function(t,e,r,i){var a,o,s,l,u,c,h,f,d,p,m,g,v,y,b,x,_,w,M,k,A,T,S,E,L=i[0],C=i[1],z=i[2],D=Math.sqrt(L*L+C*C+z*z);return Math.abs(D)<n.EPSILON?null:(D=1/D,L*=D,C*=D,z*=D,a=Math.sin(r),o=Math.cos(r),s=1-o,l=e[0],u=e[1],c=e[2],h=e[3],f=e[4],d=e[5],p=e[6],m=e[7],g=e[8],v=e[9],y=e[10],b=e[11],x=L*L*s+o,_=C*L*s+z*a,w=z*L*s-C*a,M=L*C*s-z*a,k=C*C*s+o,A=z*C*s+L*a,T=L*z*s+C*a,S=C*z*s-L*a,E=z*z*s+o,t[0]=l*x+f*_+g*w,t[1]=u*x+d*_+v*w,t[2]=c*x+p*_+y*w,t[3]=h*x+m*_+b*w,t[4]=l*M+f*k+g*A,t[5]=u*M+d*k+v*A,t[6]=c*M+p*k+y*A,t[7]=h*M+m*k+b*A,t[8]=l*T+f*S+g*E,t[9]=u*T+d*S+v*E,t[10]=c*T+p*S+y*E,t[11]=h*T+m*S+b*E,e!==t&&(t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t)},i.scalar.rotateX=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],u=e[8],c=e[9],h=e[10],f=e[11];return 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]),t[4]=a*i+u*n,t[5]=o*i+c*n,t[6]=s*i+h*n,t[7]=l*i+f*n,t[8]=u*i-a*n,t[9]=c*i-o*n,t[10]=h*i-s*n,t[11]=f*i-l*n,t},i.SIMD.rotateX=function(t,e,r){var n=SIMD.Float32x4.splat(Math.sin(r)),i=SIMD.Float32x4.splat(Math.cos(r));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]);var a=SIMD.Float32x4.load(e,4),o=SIMD.Float32x4.load(e,8);return SIMD.Float32x4.store(t,4,SIMD.Float32x4.add(SIMD.Float32x4.mul(a,i),SIMD.Float32x4.mul(o,n))),SIMD.Float32x4.store(t,8,SIMD.Float32x4.sub(SIMD.Float32x4.mul(o,i),SIMD.Float32x4.mul(a,n))),t},i.rotateX=n.USE_SIMD?i.SIMD.rotateX:i.scalar.rotateX,i.scalar.rotateY=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],u=e[8],c=e[9],h=e[10],f=e[11];return 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]),t[0]=a*i-u*n,t[1]=o*i-c*n,t[2]=s*i-h*n,t[3]=l*i-f*n,t[8]=a*n+u*i,t[9]=o*n+c*i,t[10]=s*n+h*i,t[11]=l*n+f*i,t},i.SIMD.rotateY=function(t,e,r){var n=SIMD.Float32x4.splat(Math.sin(r)),i=SIMD.Float32x4.splat(Math.cos(r));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]);var a=SIMD.Float32x4.load(e,0),o=SIMD.Float32x4.load(e,8);return SIMD.Float32x4.store(t,0,SIMD.Float32x4.sub(SIMD.Float32x4.mul(a,i),SIMD.Float32x4.mul(o,n))),SIMD.Float32x4.store(t,8,SIMD.Float32x4.add(SIMD.Float32x4.mul(a,n),SIMD.Float32x4.mul(o,i))),t},i.rotateY=n.USE_SIMD?i.SIMD.rotateY:i.scalar.rotateY,i.scalar.rotateZ=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],u=e[4],c=e[5],h=e[6],f=e[7];return 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]),t[0]=a*i+u*n,t[1]=o*i+c*n,t[2]=s*i+h*n,t[3]=l*i+f*n,t[4]=u*i-a*n,t[5]=c*i-o*n,t[6]=h*i-s*n,t[7]=f*i-l*n,t},i.SIMD.rotateZ=function(t,e,r){var n=SIMD.Float32x4.splat(Math.sin(r)),i=SIMD.Float32x4.splat(Math.cos(r));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]);var a=SIMD.Float32x4.load(e,0),o=SIMD.Float32x4.load(e,4);return SIMD.Float32x4.store(t,0,SIMD.Float32x4.add(SIMD.Float32x4.mul(a,i),SIMD.Float32x4.mul(o,n))),SIMD.Float32x4.store(t,4,SIMD.Float32x4.sub(SIMD.Float32x4.mul(o,i),SIMD.Float32x4.mul(a,n))),t},i.rotateZ=n.USE_SIMD?i.SIMD.rotateZ:i.scalar.rotateZ,i.fromTranslation=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},i.fromScaling=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},i.fromRotation=function(t,e,r){var i,a,o,s=r[0],l=r[1],u=r[2],c=Math.sqrt(s*s+l*l+u*u);return Math.abs(c)<n.EPSILON?null:(c=1/c,s*=c,l*=c,u*=c,i=Math.sin(e),a=Math.cos(e),o=1-a,t[0]=s*s*o+a,t[1]=l*s*o+u*i,t[2]=u*s*o-l*i,t[3]=0,t[4]=s*l*o-u*i,t[5]=l*l*o+a,t[6]=u*l*o+s*i,t[7]=0,t[8]=s*u*o+l*i,t[9]=l*u*o-s*i,t[10]=u*u*o+a,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t)},i.fromXRotation=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},i.fromYRotation=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},i.fromZRotation=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},i.fromRotationTranslation=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=n+n,l=i+i,u=a+a,c=n*s,h=n*l,f=n*u,d=i*l,p=i*u,m=a*u,g=o*s,v=o*l,y=o*u;return t[0]=1-(d+m),t[1]=h+y,t[2]=f-v,t[3]=0,t[4]=h-y,t[5]=1-(c+m),t[6]=p+g,t[7]=0,t[8]=f+v,t[9]=p-g,t[10]=1-(c+d),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t},i.getTranslation=function(t,e){return t[0]=e[12],t[1]=e[13],t[2]=e[14],t},i.getRotation=function(t,e){var r=e[0]+e[5]+e[10],n=0;return r>0?(n=2*Math.sqrt(r+1),t[3]=.25*n,t[0]=(e[6]-e[9])/n,t[1]=(e[8]-e[2])/n,t[2]=(e[1]-e[4])/n):e[0]>e[5]&e[0]>e[10]?(n=2*Math.sqrt(1+e[0]-e[5]-e[10]),t[3]=(e[6]-e[9])/n,t[0]=.25*n,t[1]=(e[1]+e[4])/n,t[2]=(e[8]+e[2])/n):e[5]>e[10]?(n=2*Math.sqrt(1+e[5]-e[0]-e[10]),t[3]=(e[8]-e[2])/n,t[0]=(e[1]+e[4])/n,t[1]=.25*n,t[2]=(e[6]+e[9])/n):(n=2*Math.sqrt(1+e[10]-e[0]-e[5]),t[3]=(e[1]-e[4])/n,t[0]=(e[8]+e[2])/n,t[1]=(e[6]+e[9])/n,t[2]=.25*n),t},i.fromRotationTranslationScale=function(t,e,r,n){var i=e[0],a=e[1],o=e[2],s=e[3],l=i+i,u=a+a,c=o+o,h=i*l,f=i*u,d=i*c,p=a*u,m=a*c,g=o*c,v=s*l,y=s*u,b=s*c,x=n[0],_=n[1],w=n[2];return t[0]=(1-(p+g))*x,t[1]=(f+b)*x,t[2]=(d-y)*x,t[3]=0,t[4]=(f-b)*_,t[5]=(1-(h+g))*_,t[6]=(m+v)*_,t[7]=0,t[8]=(d+y)*w,t[9]=(m-v)*w,t[10]=(1-(h+p))*w,t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t},i.fromRotationTranslationScaleOrigin=function(t,e,r,n,i){var a=e[0],o=e[1],s=e[2],l=e[3],u=a+a,c=o+o,h=s+s,f=a*u,d=a*c,p=a*h,m=o*c,g=o*h,v=s*h,y=l*u,b=l*c,x=l*h,_=n[0],w=n[1],M=n[2],k=i[0],A=i[1],T=i[2];return t[0]=(1-(m+v))*_,t[1]=(d+x)*_,t[2]=(p-b)*_,t[3]=0,t[4]=(d-x)*w,t[5]=(1-(f+v))*w,t[6]=(g+y)*w,t[7]=0,t[8]=(p+b)*M,t[9]=(g-y)*M,t[10]=(1-(f+m))*M,t[11]=0,t[12]=r[0]+k-(t[0]*k+t[4]*A+t[8]*T),t[13]=r[1]+A-(t[1]*k+t[5]*A+t[9]*T),t[14]=r[2]+T-(t[2]*k+t[6]*A+t[10]*T),t[15]=1,t},i.fromQuat=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=r+r,s=n+n,l=i+i,u=r*o,c=n*o,h=n*s,f=i*o,d=i*s,p=i*l,m=a*o,g=a*s,v=a*l;return t[0]=1-h-p,t[1]=c+v,t[2]=f-g,t[3]=0,t[4]=c-v,t[5]=1-u-p,t[6]=d+m,t[7]=0,t[8]=f+g,t[9]=d-m,t[10]=1-u-h,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t},i.frustum=function(t,e,r,n,i,a,o){var s=1/(r-e),l=1/(i-n),u=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)*u,t[11]=-1,t[12]=0,t[13]=0,t[14]=o*a*2*u,t[15]=0,t},i.perspective=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},i.perspectiveFromFieldOfView=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),u=2/(i+a);return t[0]=l,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=u,t[6]=0,t[7]=0,t[8]=-(o-s)*l*.5,t[9]=(i-a)*u*.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},i.ortho=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),u=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*u,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*u,t[15]=1,t},i.lookAt=function(t,e,r,a){var o,s,l,u,c,h,f,d,p,m,g=e[0],v=e[1],y=e[2],b=a[0],x=a[1],_=a[2],w=r[0],M=r[1],k=r[2];return Math.abs(g-w)<n.EPSILON&&Math.abs(v-M)<n.EPSILON&&Math.abs(y-k)<n.EPSILON?i.identity(t):(f=g-w,d=v-M,p=y-k,m=1/Math.sqrt(f*f+d*d+p*p),f*=m,d*=m,p*=m,o=x*p-_*d,s=_*f-b*p,l=b*d-x*f,m=Math.sqrt(o*o+s*s+l*l),m?(o*=m=1/m,s*=m,l*=m):(o=0,s=0,l=0),u=d*l-p*s,c=p*o-f*l,h=f*s-d*o,m=Math.sqrt(u*u+c*c+h*h),m?(u*=m=1/m,c*=m,h*=m):(u=0,c=0,h=0),t[0]=o,t[1]=u,t[2]=f,t[3]=0,t[4]=s,t[5]=c,t[6]=d,t[7]=0,t[8]=l,t[9]=h,t[10]=p,t[11]=0,t[12]=-(o*g+s*v+l*y),t[13]=-(u*g+c*v+h*y),t[14]=-(f*g+d*v+p*y),t[15]=1,t)},i.str=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]+\", 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discard;\\n  }\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\";r.meshShader={vertex:\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n           , view\\n           , projection;\\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\\nvoid main() {\\n  vec4 m_position  = model * vec4(position, 1.0);\\n  vec4 t_position  = view * m_position;\\n  gl_Position      = projection * t_position;\\n  f_color          = color;\\n  f_normal         = normal;\\n  f_data           = position;\\n  f_eyeDirection   = eyePosition   - position;\\n  f_lightDirection = lightPosition - position;\\n  f_uv             = uv;\\n}\",fragment:\"precision mediump float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution_2_0(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\\n\\n\\nfloat cookTorranceSpecular_1_1(\\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_2_0(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\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n            , fresnel\\n            , kambient\\n            , kdiffuse\\n            , kspecular\\n            , opacity;\\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(any(lessThan(f_data, clipBounds[0])) || \\n     any(greaterThan(f_data, clipBounds[1]))) {\\n    discard;\\n  }\\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 = cookTorranceSpecular_1_1(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}\",attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.wireShader={vertex:\"precision mediump 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}\",fragment:\"precision mediump float;\\n#define GLSLIFY 1\\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(any(lessThan(f_data, clipBounds[0])) || \\n     any(greaterThan(f_data, clipBounds[1]))) {\\n    discard;\\n  }\\n\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\",attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.pointShader={vertex:\"precision mediump float;\\n#define GLSLIFY 1\\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(any(lessThan(position, clipBounds[0])) || \\n     any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(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}\",fragment:\"precision mediump 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}\",attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},r.pickShader={vertex:\"precision mediump 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}\",fragment:n,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},r.pointPickShader={vertex:\"precision mediump float;\\n#define GLSLIFY 1\\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(any(lessThan(position, clipBounds[0])) || \\n     any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(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}\",fragment:n,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},r.contourShader={vertex:\"precision mediump 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}\",fragment:\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n  gl_FragColor = vec4(contourColor,1);\\n}\\n\",attributes:[{name:\"position\",type:\"vec3\"}]}},{}],189:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s,l,u,c,h,f,d,p,m,g,v,y,b,x,_,w,M,k,A,T){this.gl=t,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=c,this.triangleNormals=f,this.triangleUVs=h,this.triangleIds=u,this.triangleVAO=d,this.triangleCount=0,this.lineWidth=1,this.edgePositions=p,this.edgeColors=g,this.edgeUVs=v,this.edgeIds=m,this.edgeVAO=y,this.edgeCount=0,this.pointPositions=b,this.pointColors=_,this.pointUVs=w,this.pointSizes=M,this.pointIds=x,this.pointVAO=k,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=A,this.contourVAO=T,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!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._model=I,this._view=I,this._projection=I,this._resolution=[1,1]}function i(t){for(var e=w({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 _(r,[256,256,4],[4,0,1])}function a(t,e,r){for(var n=new Array(e),i=0;i<e;++i)n[i]=0;for(var a=t.length,i=0;i<a;++i)for(var o=t[i],s=0;s<o.length;++s)n[o[s]]=r[i];return n}function o(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}function s(t){var e=p(t,S);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}function l(t){var e=p(t,E);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}function u(t){var e=p(t,L);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=p(t,C);return e.attributes.position.location=0,e.attributes.id.location=1,e}function h(t){var e=p(t,z);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function f(t){var e=p(t,D);return e.attributes.position.location=0,e}function d(t){var e=t.gl,r=s(e),i=l(e),a=u(e),o=c(e),d=h(e),p=f(e),y=v(e,_(new Uint8Array([255,255,255,255]),[1,1,4]));y.generateMipmap(),y.minFilter=e.LINEAR_MIPMAP_LINEAR,y.magFilter=e.LINEAR;var b=m(e),x=m(e),w=m(e),M=m(e),k=m(e),A=g(e,[{buffer:b,type:e.FLOAT,size:3},{buffer:k,type:e.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:x,type:e.FLOAT,size:4},{buffer:w,type:e.FLOAT,size:2},{buffer:M,type:e.FLOAT,size:3}]),T=m(e),S=m(e),E=m(e),L=m(e),C=g(e,[{buffer:T,type:e.FLOAT,size:3},{buffer:L,type:e.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:S,type:e.FLOAT,size:4},{buffer:E,type:e.FLOAT,size:2}]),z=m(e),D=m(e),I=m(e),P=m(e),O=m(e),j=g(e,[{buffer:z,type:e.FLOAT,size:3},{buffer:O,type:e.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:D,type:e.FLOAT,size:4},{buffer:I,type:e.FLOAT,size:2},{buffer:P,type:e.FLOAT,size:1}]),R=m(e),F=new n(e,y,r,i,a,o,d,p,b,k,x,w,M,A,T,L,S,E,C,z,O,D,I,P,j,R,g(e,[{buffer:R,type:e.FLOAT,size:3}]));return F.update(t),F}var p=t(\"gl-shader\"),m=t(\"gl-buffer\"),g=t(\"gl-vao\"),v=t(\"gl-texture2d\"),y=t(\"normals\"),b=t(\"gl-mat4/multiply\"),x=t(\"gl-mat4/invert\"),_=t(\"ndarray\"),w=t(\"colormap\"),M=t(\"simplicial-complex-contour\"),k=t(\"typedarray-pool\"),A=t(\"./lib/shaders\"),T=t(\"./lib/closest-point\"),S=A.meshShader,E=A.wireShader,L=A.pointShader,C=A.pickShader,z=A.pointPickShader,D=A.contourShader,I=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],P=n.prototype;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.highlight=function(t){if(t&&this.contourEnable){for(var e=M(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=k.mallocFloat32(6*a),s=0,l=0;l<a;++l)for(var u=r[l],c=0;c<2;++c){var h=u[0];2===u.length&&(h=u[c]);for(var f=n[h][0],d=n[h][1],p=i[h],m=1-p,g=this.positions[f],v=this.positions[d],y=0;y<3;++y)o[s++]=p*g[y]+m*v[y]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),k.free(o)}else this.contourCount=0},P.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),\"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),t.texture?(this.texture.dispose(),this.texture=v(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(i(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var s=[],l=[],u=[],c=[],h=[],f=[],d=[],p=[],m=[],g=[],b=[],x=[],_=[],w=[];this.cells=r,this.positions=n;var M=t.vertexNormals,k=t.cellNormals,A=void 0===t.vertexNormalsEpsilon?1e-6:t.vertexNormalsEpsilon,T=void 0===t.faceNormalsEpsilon?1e-6:t.faceNormalsEpsilon;t.useFacetNormals&&!k&&(k=y.faceNormals(r,n,T)),k||M||(M=y.vertexNormals(r,n,A));var S=t.vertexColors,E=t.cellColors,L=t.meshColor||[1,1,1,1],C=t.vertexUVs,z=t.vertexIntensity,D=t.cellUVs,I=t.cellIntensity,P=1/0,O=-1/0;if(!C&&!D)if(z)for(q=0;q<z.length;++q){j=z[q];P=Math.min(P,j),O=Math.max(O,j)}else if(I)for(q=0;q<I.length;++q){j=I[q];P=Math.min(P,j),O=Math.max(O,j)}else for(q=0;q<n.length;++q){var j=n[q][2];P=Math.min(P,j),O=Math.max(O,j)}this.intensity=z||(I?a(r,n.length,I):o(n));var R=t.pointSizes,F=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(q=0;q<n.length;++q)for(var N=n[q],B=0;B<3;++B)!isNaN(N[B])&&isFinite(N[B])&&(this.bounds[0][B]=Math.min(this.bounds[0][B],N[B]),this.bounds[1][B]=Math.max(this.bounds[1][B],N[B]));var U=0,V=0,H=0;t:for(var q=0;q<r.length;++q){var G=r[q];switch(G.length){case 1:for(var N=n[W=G[0]],B=0;B<3;++B)if(isNaN(N[B])||!isFinite(N[B]))continue t;g.push(N[0],N[1],N[2]);3===(X=S?S[W]:E?E[q]:L).length?b.push(X[0],X[1],X[2],1):b.push(X[0],X[1],X[2],X[3]);Z=C?C[W]:z?[(z[W]-P)/(O-P),0]:D?D[q]:I?[(I[q]-P)/(O-P),0]:[(N[2]-P)/(O-P),0],x.push(Z[0],Z[1]),R?_.push(R[W]):_.push(F),w.push(q),H+=1;break;case 2:for(B=0;B<2;++B)for(var N=n[W=G[B]],Y=0;Y<3;++Y)if(isNaN(N[Y])||!isFinite(N[Y]))continue t;for(B=0;B<2;++B){N=n[W=G[B]];f.push(N[0],N[1],N[2]);3===(X=S?S[W]:E?E[q]:L).length?d.push(X[0],X[1],X[2],1):d.push(X[0],X[1],X[2],X[3]);Z=C?C[W]:z?[(z[W]-P)/(O-P),0]:D?D[q]:I?[(I[q]-P)/(O-P),0]:[(N[2]-P)/(O-P),0],p.push(Z[0],Z[1]),m.push(q)}V+=1;break;case 3:for(B=0;B<3;++B)for(var N=n[W=G[B]],Y=0;Y<3;++Y)if(isNaN(N[Y])||!isFinite(N[Y]))continue t;for(B=0;B<3;++B){var W=G[B],N=n[W];s.push(N[0],N[1],N[2]);var X;3===(X=S?S[W]:E?E[q]:L).length?l.push(X[0],X[1],X[2],1):l.push(X[0],X[1],X[2],X[3]);var Z;Z=C?C[W]:z?[(z[W]-P)/(O-P),0]:D?D[q]:I?[(I[q]-P)/(O-P),0]:[(N[2]-P)/(O-P),0],c.push(Z[0],Z[1]);var J;J=M?M[W]:k[q],u.push(J[0],J[1],J[2]),h.push(q)}U+=1}}this.pointCount=H,this.edgeCount=V,this.triangleCount=U,this.pointPositions.update(g),this.pointColors.update(b),this.pointUVs.update(x),this.pointSizes.update(_),this.pointIds.update(new Uint32Array(w)),this.edgePositions.update(f),this.edgeColors.update(d),this.edgeUVs.update(p),this.edgeIds.update(new Uint32Array(m)),this.trianglePositions.update(s),this.triangleColors.update(l),this.triangleUVs.update(c),this.triangleNormals.update(u),this.triangleIds.update(new Uint32Array(h))}},P.drawTransparent=P.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||I,n=t.view||I,i=t.projection||I,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,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,contourColor:this.contourColor,texture:0};this.texture.bind(0);var l=new Array(16);b(l,s.view,s.model),b(l,s.projection,l),x(l,l);for(o=0;o<3;++o)s.eyePosition[o]=l[12+o]/l[15];for(var u=l[15],o=0;o<3;++o)u+=this.lightPosition[o]*l[4*o+3];for(o=0;o<3;++o){for(var c=l[12+o],h=0;h<3;++h)c+=l[4*h+o]*this.lightPosition[h];s.lightPosition[o]=c/u}if(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),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){var f=this.contourShader;f.bind(),f.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind()}},P.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||I,n=t.view||I,i=t.projection||I,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,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()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0&&((l=this.pointPickShader).bind(),l.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},P.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(i,[t.coord[0],this._resolution[1]-t.coord[1]],this._model,this._view,this._projection,this._resolution);if(!o)return null;for(var s=o[2],l=0,a=0;a<r.length;++a)l+=s[a]*this.intensity[r[a]];return{position:o[1],index:r[o[0]],cell:r,cellId:e,intensity:l,dataCoordinate:this.positions[r[o[0]]]}},P.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=d},{\"./lib/closest-point\":187,\"./lib/shaders\":188,colormap:92,\"gl-buffer\":141,\"gl-mat4/invert\":165,\"gl-mat4/multiply\":167,\"gl-shader\":239,\"gl-texture2d\":251,\"gl-vao\":255,ndarray:449,normals:451,\"simplicial-complex-contour\":498,\"typedarray-pool\":521}],190:[function(t,e,r){\"use strict\";function n(t,e,r){this.plot=t,this.vbo=e,this.shader=r}function i(t){var e=t.gl;return new n(t,a(e,[0,0,0,1,1,0,1,1]),o(e,s.boxVert,s.lineFrag))}e.exports=i;var a=t(\"gl-buffer\"),o=t(\"gl-shader\"),s=t(\"./shaders\"),l=n.prototype;l.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},l.drawBox=function(){var t=[0,0],e=[0,0];return function(r,n,i,a,o){var s=this.plot,l=this.shader,u=s.gl;t[0]=r,t[1]=n,e[0]=i,e[1]=a,l.uniforms.lo=t,l.uniforms.hi=e,l.uniforms.color=o,u.drawArrays(u.TRIANGLE_STRIP,0,4)}}(),l.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":193,\"gl-buffer\":141,\"gl-shader\":196}],191:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.plot=t,this.vbo=e,this.shader=r,this.tickShader=n,this.ticks=[[],[]]}function i(t,e){return t-e}function a(t){var e=t.gl;return new n(t,o(e),s(e,u.gridVert,u.gridFrag),s(e,u.tickVert,u.gridFrag))}e.exports=a;var o=t(\"gl-buffer\"),s=t(\"gl-shader\"),l=t(\"binary-search-bounds\"),u=t(\"./shaders\"),c=n.prototype;c.draw=function(){var t=[0,0],e=[0,0],r=[0,0];return function(){for(var n=this.plot,i=this.vbo,a=this.shader,o=this.ticks,s=n.gl,l=n._tickBounds,u=n.dataBox,c=n.viewBox,h=n.gridLineWidth,f=n.gridLineColor,d=n.gridLineEnable,p=n.pixelRatio,m=0;m<2;++m){var g=l[m],v=l[m+2]-g,y=.5*(u[m+2]+u[m]),b=u[m+2]-u[m];e[m]=2*v/b,t[m]=2*(g-y)/b}a.bind(),i.bind(),a.attributes.dataCoord.pointer(),a.uniforms.dataShift=t,a.uniforms.dataScale=e;for(var x=0,m=0;m<2;++m){r[0]=r[1]=0,r[m]=1,a.uniforms.dataAxis=r,a.uniforms.lineWidth=h[m]/(c[m+2]-c[m])*p,a.uniforms.color=f[m];var _=6*o[m].length;d[m]&&_&&s.drawArrays(s.TRIANGLES,x,_),x+=_}}}(),c.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],a=[0,0],o=[0,0];return function(){for(var s=this.plot,u=this.vbo,c=this.tickShader,h=this.ticks,f=s.gl,d=s._tickBounds,p=s.dataBox,m=s.viewBox,g=s.pixelRatio,v=s.screenBox,y=v[2]-v[0],b=v[3]-v[1],x=m[2]-m[0],_=m[3]-m[1],w=0;w<2;++w){var M=d[w],k=d[w+2]-M,A=.5*(p[w+2]+p[w]),T=p[w+2]-p[w];e[w]=2*k/T,t[w]=2*(M-A)/T}e[0]*=x/y,t[0]*=x/y,e[1]*=_/b,t[1]*=_/b,c.bind(),u.bind(),c.attributes.dataCoord.pointer();var S=c.uniforms;S.dataShift=t,S.dataScale=e;var 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t=[0,0],e=[0,0];return function(r,n,i,a,o,s){var l=this.plot,u=this.shader,c=l.gl;t[0]=r,t[1]=n,e[0]=i,e[1]=a,u.uniforms.start=t,u.uniforms.end=e,u.uniforms.width=o*l.pixelRatio,u.uniforms.color=s,c.drawArrays(c.TRIANGLE_STRIP,0,4)}}(),l.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":193,\"gl-buffer\":141,\"gl-shader\":196}],193:[function(t,e,r){\"use strict\";var 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:\"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 * 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a=t(\"gl-buffer\"),o=t(\"gl-shader\"),s=t(\"text-cache\"),l=t(\"binary-search-bounds\"),u=t(\"./shaders\"),c=n.prototype;c.drawTicks=function(){var t=[0,0],e=[0,0],r=[0,0];return function(n){var i=this.plot,a=this.shader,o=this.tickX[n],s=this.tickOffset[n],u=i.gl,c=i.viewBox,h=i.dataBox,f=i.screenBox,d=i.pixelRatio,p=i.tickEnable,m=i.tickPad,g=i.tickColor,v=i.tickAngle,y=i.labelEnable,b=i.labelPad,x=i.labelColor,_=i.labelAngle,w=this.labelOffset[n],M=this.labelCount[n],k=l.lt(o,h[n]),A=l.le(o,h[n+2]);t[0]=t[1]=0,t[n]=1,e[n]=(c[2+n]+c[n])/(f[2+n]-f[n])-1;var T=2/f[2+(1^n)]-f[1^n];e[1^n]=T*c[1^n]-1,p[n]&&(e[1^n]-=T*d*m[n],k<A&&s[A]>s[k]&&(a.uniforms.dataAxis=t,a.uniforms.screenOffset=e,a.uniforms.color=g[n],a.uniforms.angle=v[n],u.drawArrays(u.TRIANGLES,s[k],s[A]-s[k]))),y[n]&&M&&(e[1^n]-=T*d*b[n],a.uniforms.dataAxis=r,a.uniforms.screenOffset=e,a.uniforms.color=x[n],a.uniforms.angle=_[n],u.drawArrays(u.TRIANGLES,w,M)),e[1^n]=T*c[2+(1^n)]-1,p[n+2]&&(e[1^n]+=T*d*m[n+2],k<A&&s[A]>s[k]&&(a.uniforms.dataAxis=t,a.uniforms.screenOffset=e,a.uniforms.color=g[n+2],a.uniforms.angle=v[n+2],u.drawArrays(u.TRIANGLES,s[k],s[A]-s[k]))),y[n+2]&&M&&(e[1^n]+=T*d*b[n+2],a.uniforms.dataAxis=r,a.uniforms.screenOffset=e,a.uniforms.color=x[n+2],a.uniforms.angle=_[n+2],u.drawArrays(u.TRIANGLES,w,M))}}(),c.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,u=r.pixelRatio;if(this.titleCount){for(var 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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){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),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var u=this.borderColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[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 c=this.backgroundColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT),a.draw();var h=this.zeroLineEnable,f=this.zeroLineColor,d=this.zeroLineWidth;if(h[0]||h[1]){o.bind();for(b=0;b<2;++b)if(h[b]&&n[b]<=0&&n[b+2]>=0){var p=e[b]-n[b]*(e[b+2]-e[b])/(n[b+2]-n[b]);0===b?o.drawLine(p,e[1],p,e[3],d[b],f[b]):o.drawLine(e[0],p,e[2],p,d[b],f[b])}}for(b=0;b<l.length;++b)l[b].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,g=this.borderLineWidth,v=this.borderLineColor;m[1]&&o.drawLine(r[0],r[1]-.5*g[1]*i,r[0],r[3]+.5*g[3]*i,g[1],v[1]),m[0]&&o.drawLine(r[0]-.5*g[0]*i,r[1],r[2]+.5*g[2]*i,r[1],g[0],v[0]),m[3]&&o.drawLine(r[2],r[1]-.5*g[1]*i,r[2],r[3]+.5*g[3]*i,g[3],v[3]),m[2]&&o.drawLine(r[0]-.5*g[0]*i,r[3],r[2]+.5*g[2]*i,r[3],g[2],v[2]),s.bind();for(b=0;b<2;++b)s.drawTicks(b);this.titleEnable&&s.drawTitle();for(var y=this.overlays,b=0;b<y.length;++b)y[b].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}}}(),f.drawPick=function(){return 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()}}}(),f.pick=function(){return 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),u=this.objects,c=0;c<u.length;++c){var h=u[c].pick(a,o,l);if(h)return h}return null}}}(),f.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()},f.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())},f.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()},f.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,o=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/o,10,10/o]),this.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=i(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=i(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=i(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=i(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=i(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=i(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var s=t.ticks||[[],[]],l=this._tickBounds;l[0]=l[1]=1/0,l[2]=l[3]=-1/0;for(var u=0;u<2;++u){var c=s[u].slice(0);0!==c.length&&(c.sort(a),l[u]=Math.min(l[u],c[0].x),l[u+2]=Math.max(l[u+2],c[c.length-1].x))}this.grid.update({bounds:l,ticks:s}),this.text.update({bounds:l,ticks:s,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()},f.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();this.objects.length=0;for(var t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},f.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},f.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}},f.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},f.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\":190,\"./lib/grid\":191,\"./lib/line\":192,\"./lib/text\":194,\"gl-select-static\":238}],204:[function(t,e,r){var n=t(\"gl-shader\");e.exports=function(t){return n(t,\"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}\",\"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}\",null,[{name:\"position\",type:\"vec2\"}])}},{\"gl-shader\":239}],205:[function(t,e,r){\"use strict\";function n(){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 i(t,e){var r=null;try{(r=t.getContext(\"webgl\",e))||(r=t.getContext(\"experimental-webgl\",e))}catch(t){return null}return r}function a(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}if(e>0){var r=Math.round(Math.pow(10,e));return Math.ceil(t/r)*r}return Math.ceil(t)}function o(t){return\"boolean\"!=typeof t||t}function s(t){function e(){if(!w&&q.autoResize){var t=M.parentNode,e=1,r=1;t&&t!==document.body?(e=t.clientWidth,r=t.clientHeight):(e=window.innerWidth,r=window.innerHeight);var n=0|Math.ceil(e*q.pixelRatio),i=0|Math.ceil(r*q.pixelRatio);if(n!==M.width||i!==M.height){M.width=n,M.height=i;var a=M.style;a.position=a.position||\"absolute\",a.left=\"0px\",a.top=\"0px\",a.width=e+\"px\",a.height=r+\"px\",F=!0}}}function r(){for(var t=P.length,e=R.length,r=0;r<e;++r)j[r]=0;t:for(r=0;r<t;++r){var n=P[r],i=n.pickSlots;if(i){for(var a=0;a<e;++a)if(j[a]+i<255){O[r]=a,n.setPickBase(j[a]+1),j[a]+=i;continue t}var o=f(k,H);O[r]=e,R.push(o),j.push(i),n.setPickBase(1),e+=1}else O[r]=-1}for(;e>0&&0===j[e-1];)j.pop(),R.pop().dispose()}function s(){if(q.contextLost)return!0;k.isContextLost()&&(q.contextLost=!0,q.mouseListener.enabled=!1,q.selection.object=null,q.oncontextloss&&q.oncontextloss())}function b(){if(!s()){k.colorMask(!0,!0,!0,!0),k.depthMask(!0),k.disable(k.BLEND),k.enable(k.DEPTH_TEST);for(var t=P.length,e=R.length,r=0;r<e;++r){var n=R[r];n.shape=G,n.begin();for(var i=0;i<t;++i)if(O[i]===r){var a=P[i];a.drawPick&&(a.pixelRatio=1,a.drawPick(V))}n.end()}}}function x(){if(!s()){e();var t=q.camera.tick();V.view=q.camera.matrix,F=F||t,N=N||t,z.pixelRatio=q.pixelRatio,I.pixelRatio=q.pixelRatio;var r=P.length,n=X[0],i=X[1];n[0]=n[1]=n[2]=1/0,i[0]=i[1]=i[2]=-1/0;for(y=0;y<r;++y){(L=P[y]).pixelRatio=q.pixelRatio,L.axes=q.axes,F=F||!!L.dirty,N=N||!!L.dirty;var o=L.bounds;if(o)for(var l=o[0],u=o[1],h=0;h<3;++h)n[h]=Math.min(n[h],l[h]),i[h]=Math.max(i[h],u[h])}var f=q.bounds;if(q.autoBounds)for(h=0;h<3;++h){if(i[h]<n[h])n[h]=-1,i[h]=1;else{n[h]===i[h]&&(n[h]-=1,i[h]+=1);var d=.05*(i[h]-n[h]);n[h]=n[h]-d,i[h]=i[h]+d}f[0][h]=n[h],f[1][h]=i[h]}for(var m=!1,h=0;h<3;++h)m=m||Z[0][h]!==f[0][h]||Z[1][h]!==f[1][h],Z[0][h]=f[0][h],Z[1][h]=f[1][h];if(N=N||m,F=F||m){if(m){for(var v=[0,0,0],y=0;y<3;++y)v[y]=a((f[1][y]-f[0][y])/10);z.autoTicks?z.update({bounds:f,tickSpacing:v}):z.update({bounds:f})}var x=k.drawingBufferWidth,_=k.drawingBufferHeight;H[0]=x,H[1]=_,G[0]=0|Math.max(x/q.pixelRatio,1),G[1]=0|Math.max(_/q.pixelRatio,1),g(B,q.fovy,x/_,q.zNear,q.zFar);for(y=0;y<16;++y)U[y]=0;U[15]=1;for(var w=0,y=0;y<3;++y)w=Math.max(w,f[1][y]-f[0][y]);for(y=0;y<3;++y)q.autoScale?U[5*y]=q.aspect[y]/(f[1][y]-f[0][y]):U[5*y]=1/w,q.autoCenter&&(U[12+y]=.5*-U[5*y]*(f[0][y]+f[1][y]));for(y=0;y<r;++y)(L=P[y]).axesBounds=f,q.clipToBounds&&(L.clipBounds=f);T.object&&(q.snapToData?I.position=T.dataCoordinate:I.position=T.dataPosition,I.bounds=f),N&&(N=!1,b()),q.axesPixels=c(q.axes,V,x,_),q.onrender&&q.onrender(),k.bindFramebuffer(k.FRAMEBUFFER,null),k.viewport(0,0,x,_);var M=q.clearColor;k.clearColor(M[0],M[1],M[2],M[3]),k.clear(k.COLOR_BUFFER_BIT|k.DEPTH_BUFFER_BIT),k.depthMask(!0),k.colorMask(!0,!0,!0,!0),k.enable(k.DEPTH_TEST),k.depthFunc(k.LEQUAL),k.disable(k.BLEND),k.disable(k.CULL_FACE);var A=!1;z.enable&&(A=A||z.isTransparent(),z.draw(V)),I.axes=z,T.object&&I.draw(V),k.disable(k.CULL_FACE);for(y=0;y<r;++y)(L=P[y]).axes=z,L.pixelRatio=q.pixelRatio,L.isOpaque&&L.isOpaque()&&L.draw(V),L.isTransparent&&L.isTransparent()&&(A=!0);if(A){S.shape=H,S.bind(),k.clear(k.DEPTH_BUFFER_BIT),k.colorMask(!1,!1,!1,!1),k.depthMask(!0),k.depthFunc(k.LESS),z.enable&&z.isTransparent()&&z.drawTransparent(V);for(y=0;y<r;++y)(L=P[y]).isOpaque&&L.isOpaque()&&L.draw(V);k.enable(k.BLEND),k.blendEquation(k.FUNC_ADD),k.blendFunc(k.ONE,k.ONE_MINUS_SRC_ALPHA),k.colorMask(!0,!0,!0,!0),k.depthMask(!1),k.clearColor(0,0,0,0),k.clear(k.COLOR_BUFFER_BIT),z.isTransparent()&&z.drawTransparent(V);for(y=0;y<r;++y){var L=P[y];L.isTransparent&&L.isTransparent()&&L.drawTransparent(V)}k.bindFramebuffer(k.FRAMEBUFFER,null),k.blendFunc(k.ONE,k.ONE_MINUS_SRC_ALPHA),k.disable(k.DEPTH_TEST),E.bind(),S.color[0].bind(0),E.uniforms.accumBuffer=0,p(k),k.disable(k.BLEND)}F=!1;for(y=0;y<r;++y)P[y].dirty=!1}}}function _(){w||q.contextLost||(requestAnimationFrame(_),x())}var w=!1,M=((t=t||{}).pixelRatio||parseFloat(window.devicePixelRatio),t.canvas);M||(M=document.createElement(\"canvas\"),t.container?t.container.appendChild(M):document.body.appendChild(M));var k=t.gl;if(k||(k=i(M,t.glOptions||{premultipliedAlpha:!0,antialias:!0})),!k)throw new Error(\"webgl not supported\");var A=t.bounds||[[-10,-10,-10],[10,10,10]],T=new n,S=d(k,[k.drawingBufferWidth,k.drawingBufferHeight],{preferFloat:!y}),E=v(k),L=t.camera||{eye:[2,0,0],center:[0,0,0],up:[0,1,0],zoomMin:.1,zoomMax:100,mode:\"turntable\"},C=t.axes||{},z=u(k,C);z.enable=!C.disable;var D=t.spikes||{},I=h(k,D),P=[],O=[],j=[],R=[],F=!0,N=!0,B=new Array(16),U=new Array(16),V={view:null,projection:B,model:U},N=!0,H=[k.drawingBufferWidth,k.drawingBufferHeight],q={gl:k,contextLost:!1,pixelRatio:t.pixelRatio||parseFloat(window.devicePixelRatio),canvas:M,selection:T,camera:l(M,L),axes:z,axesPixels:null,spikes:I,bounds:A,objects:P,shape:H,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:o(t.autoResize),autoBounds:o(t.autoBounds),autoScale:!!t.autoScale,autoCenter:o(t.autoCenter),clipToBounds:o(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:V,oncontextloss:null,mouseListener:null},G=[k.drawingBufferWidth/q.pixelRatio|0,k.drawingBufferHeight/q.pixelRatio|0];q.autoResize&&e(),window.addEventListener(\"resize\",e),q.update=function(t){w||(t=t||{},F=!0,N=!0)},q.add=function(t){w||(t.axes=z,P.push(t),O.push(-1),F=!0,N=!0,r())},q.remove=function(t){if(!w){var e=P.indexOf(t);e<0||(P.splice(e,1),O.pop(),F=!0,N=!0,r())}},q.dispose=function(){if(!w&&(w=!0,window.removeEventListener(\"resize\",e),M.removeEventListener(\"webglcontextlost\",s),q.mouseListener.enabled=!1,!q.contextLost)){z.dispose(),I.dispose();for(t=0;t<P.length;++t)P[t].dispose();S.dispose();for(var t=0;t<R.length;++t)R[t].dispose();E.dispose(),k=null,z=null,I=null,P=[]}};var Y=!1,W=0;q.mouseListener=m(M,function(t,e,r){if(!w){var n=R.length,i=P.length,a=T.object;T.distance=1/0,T.mouse[0]=e,T.mouse[1]=r,T.object=null,T.screen=null,T.dataCoordinate=T.dataPosition=null;var o=!1;if(t&&W)Y=!0;else{Y&&(N=!0),Y=!1;for(var s=0;s<n;++s){var l=R[s].query(e,G[1]-r-1,q.pickRadius);if(l){if(l.distance>T.distance)continue;for(var u=0;u<i;++u){var c=P[u];if(O[u]===s){var h=c.pick(l);h&&(T.buttons=t,T.screen=l.coord,T.distance=l.distance,T.object=c,T.index=h.distance,T.dataPosition=h.position,T.dataCoordinate=h.dataCoordinate,T.data=h,o=!0)}}}}}a&&a!==T.object&&(a.highlight&&a.highlight(null),F=!0),T.object&&(T.object.highlight&&T.object.highlight(T.data),F=!0),(o=o||T.object!==a)&&q.onselect&&q.onselect(T),1&t&&!(1&W)&&q.onclick&&q.onclick(T),W=t}}),M.addEventListener(\"webglcontextlost\",s);var X=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],Z=[X[0].slice(),X[1].slice()];return _(),q.redraw=function(){w||(F=!0,x())},q}e.exports=s;var l=t(\"3d-view-controls\"),u=t(\"gl-axes3d\"),c=t(\"gl-axes3d/properties\"),h=t(\"gl-spikes3d\"),f=t(\"gl-select-static\"),d=t(\"gl-fbo\"),p=t(\"a-big-triangle\"),m=t(\"mouse-change\"),g=t(\"gl-mat4/perspective\"),v=t(\"./lib/shader\"),y=t(\"is-mobile\")()},{\"./lib/shader\":204,\"3d-view-controls\":32,\"a-big-triangle\":34,\"gl-axes3d\":133,\"gl-axes3d/properties\":140,\"gl-fbo\":148,\"gl-mat4/perspective\":168,\"gl-select-static\":238,\"gl-spikes3d\":248,\"is-mobile\":278,\"mouse-change\":434}],206:[function(t,e,r){r.pointVertex=\"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=\"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=\"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=\"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\"},{}],207:[function(t,e,r){arguments[4][196][0].apply(r,arguments)},{\"./lib/GLError\":208,\"./lib/create-attributes\":209,\"./lib/create-uniforms\":210,\"./lib/reflect\":211,\"./lib/runtime-reflect\":212,\"./lib/shader-cache\":213,dup:196}],208:[function(t,e,r){arguments[4][197][0].apply(r,arguments)},{dup:197}],209:[function(t,e,r){arguments[4][198][0].apply(r,arguments)},{\"./GLError\":208,dup:198}],210:[function(t,e,r){arguments[4][199][0].apply(r,arguments)},{\"./GLError\":208,\"./reflect\":211,dup:199}],211:[function(t,e,r){arguments[4][200][0].apply(r,arguments)},{dup:200}],212:[function(t,e,r){arguments[4][201][0].apply(r,arguments)},{dup:201}],213:[function(t,e,r){arguments[4][202][0].apply(r,arguments)},{\"./GLError\":208,dup:202,\"gl-format-compiler-error\":149,\"weakmap-shim\":542}],214:[function(t,e,r){\"use strict\";function n(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}function i(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}function a(t,e){var r=t.gl,i=new n(t,s(r),s(r),o(r,u.pointVertex,u.pointFragment),o(r,u.pickVertex,u.pickFragment));return i.update(e),t.addObject(i),i}var o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"typedarray-pool\"),u=t(\"./lib/shader\");e.exports=a;var c=n.prototype;c.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},c.update=function(t){function e(e,r){return e in t?t[e]:r}var r;t=t||{},this.sizeMin=e(\"sizeMin\",.5),this.sizeMax=e(\"sizeMax\",20),this.color=e(\"color\",[1,0,0,1]).slice(),this.areaRatio=e(\"areaRatio\",1),this.borderColor=e(\"borderColor\",[0,0,0,1]).slice(),this.blend=e(\"blend\",!1);var n=t.positions.length>>>1,i=t.positions instanceof Float32Array,a=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,o=t.positions,s=i?o:l.mallocFloat32(o.length),u=a?t.idToIndex:l.mallocInt32(n);if(i||s.set(o),!a)for(s.set(o),r=0;r<n;r++)u[r]=r;this.points=o,this.offsetBuffer.update(s),this.pickBuffer.update(u),i||l.free(s),a||l.free(u),this.pointCount=n,this.pickOffset=0},c.unifiedDraw=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=void 0!==r,a=n?this.pickShader:this.shader,o=this.plot.gl,s=this.plot.dataBox;if(0===this.pointCount)return r;var l=s[2]-s[0],u=s[3]-s[1],c=i(this.points,s),h=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(c,.33333)));t[0]=2/l,t[4]=2/u,t[6]=-2*s[0]/l-1,t[7]=-2*s[1]/u-1,this.offsetBuffer.bind(),a.bind(),a.attributes.position.pointer(),a.uniforms.matrix=t,a.uniforms.color=this.color,a.uniforms.borderColor=this.borderColor,a.uniforms.pointCloud=h<5,a.uniforms.pointSize=h,a.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),n&&(e[0]=255&r,e[1]=r>>8&255,e[2]=r>>16&255,e[3]=r>>24&255,this.pickBuffer.bind(),a.attributes.pickId.pointer(o.UNSIGNED_BYTE),a.uniforms.pickOffset=e,this.pickOffset=r);var f=o.getParameter(o.BLEND),d=o.getParameter(o.DITHER);return f&&!this.blend&&o.disable(o.BLEND),d&&o.disable(o.DITHER),o.drawArrays(o.POINTS,0,this.pointCount),f&&!this.blend&&o.enable(o.BLEND),d&&o.enable(o.DITHER),r+this.pointCount}}(),c.draw=c.unifiedDraw,c.drawPick=c.unifiedDraw,c.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\":206,\"gl-buffer\":141,\"gl-shader\":207,\"typedarray-pool\":521}],215:[function(t,e,r){function n(t,e,r,n){var i,a,o,s,l,u=e[0],c=e[1],h=e[2],f=e[3],d=r[0],p=r[1],m=r[2],g=r[3];return(a=u*d+c*p+h*m+f*g)<0&&(a=-a,d=-d,p=-p,m=-m,g=-g),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),t[0]=s*u+l*d,t[1]=s*c+l*p,t[2]=s*h+l*m,t[3]=s*f+l*g,t}e.exports=n},{}],216:[function(t,e,r){\"use strict\";e.exports={vertex:\"precision highp float;\\n#define GLSLIFY 1\\n\\n\\nvec4 computePosition_1_0(vec2 posHi, vec2 posLo, vec2 scHi, vec2 scLo, vec2 trHi, vec2 trLo) {\\n  return vec4((posHi + trHi) * scHi\\n  \\t\\t\\t//FIXME: this thingy does not give noticeable precision gain, need test\\n            + (posLo + trLo) * scHi\\n            + (posHi + trHi) * scLo\\n            + (posLo + trLo) * scLo\\n            , 0, 1);\\n}\\n\\n\\nattribute vec2 positionHi, positionLo;\\nattribute float size, border;\\nattribute vec2 char, color;\\n\\n//this is 64-bit form of scale and translate\\nuniform vec2 scaleHi, scaleLo, translateHi, translateLo;\\nuniform float pixelRatio;\\nuniform vec4 viewBox;\\nuniform sampler2D palette;\\n\\nvarying vec4 charColor, borderColor;\\nvarying vec2 charId;\\nvarying vec2 pointCoord;\\nvarying float pointSize;\\nvarying float borderWidth;\\n\\n\\nvoid main() {\\n  charColor = texture2D(palette, vec2(color.x / 255., 0));\\n  borderColor = texture2D(palette, vec2(color.y / 255., 0));\\n\\n  gl_PointSize = size * pixelRatio;\\n  pointSize = size * pixelRatio;\\n\\n  charId = char;\\n  borderWidth = border;\\n\\n  gl_Position = computePosition_1_0(\\n    positionHi, positionLo,\\n    scaleHi, scaleLo,\\n    translateHi, translateLo);\\n\\n  pointCoord = viewBox.xy + (viewBox.zw - viewBox.xy) * (gl_Position.xy * .5 + .5);\\n}\\n\",fragment:\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D chars;\\nuniform vec2 charsShape;\\nuniform float charsStep, pixelRatio, charOffset;\\n\\nvarying vec4 borderColor;\\nvarying vec4 charColor;\\nvarying vec2 charId;\\nvarying vec2 pointCoord;\\nvarying float pointSize;\\nvarying float borderWidth;\\n\\nvoid main() {\\n\\tvec2 pointUV = (pointCoord - gl_FragCoord.xy + pointSize * .5) / pointSize;\\n\\tpointUV.x = 1. - pointUV.x;\\n\\tpointUV.y += charOffset;\\n\\tvec2 texCoord = ((charId + pointUV) * charsStep) / charsShape;\\n\\tfloat dist = texture2D(chars, texCoord).r;\\n\\n\\t//max-distance alpha\\n\\tif (dist < 1e-2)\\n\\t\\tdiscard;\\n\\n\\tfloat dif = 5. * pixelRatio * borderWidth / pointSize;\\n\\tfloat borderLevel = .748 - dif * .5;\\n\\tfloat charLevel = .748 + dif * .5;\\n\\tfloat gamma = .005 * charsStep / pointSize;\\n\\n\\tfloat borderAmt = smoothstep(borderLevel - gamma, borderLevel + gamma, dist);\\n\\tfloat charAmt = smoothstep(charLevel - gamma, charLevel + gamma, dist);\\n\\n\\tvec4 color = borderColor;\\n\\tcolor.a *= borderAmt;\\n\\n\\tgl_FragColor = mix(color, charColor, charAmt);\\n}\\n\",pickVertex:\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 positionHi, positionLo;\\nattribute vec4 id;\\nattribute float size;\\n\\nuniform vec2 scaleHi, scaleLo, translateHi, translateLo;\\nuniform vec4 pickOffset;\\nuniform float pixelRatio;\\n\\nvarying vec4 fragColor;\\n\\n\\nvec4 computePosition_1_0(vec2 posHi, vec2 posLo, vec2 scHi, vec2 scLo, vec2 trHi, vec2 trLo) {\\n  return vec4((posHi + trHi) * scHi\\n  \\t\\t\\t//FIXME: this thingy does not give noticeable precision gain, need test\\n            + (posLo + trLo) * scHi\\n            + (posHi + trHi) * scLo\\n            + (posLo + trLo) * scLo\\n            , 0, 1);\\n}\\n\\n\\nvoid main() {\\n  vec4 fragId = id + pickOffset;\\n\\n  fragId.y += floor(fragId.x / 256.0);\\n  fragId.x -= floor(fragId.x / 256.0) * 256.0;\\n\\n  fragId.z += floor(fragId.y / 256.0);\\n  fragId.y -= floor(fragId.y / 256.0) * 256.0;\\n\\n  fragId.w += floor(fragId.z / 256.0);\\n  fragId.z -= floor(fragId.z / 256.0) * 256.0;\\n\\n  fragColor = fragId / 255.0;\\n\\n  gl_PointSize = size * .25 * pixelRatio;\\n\\n  gl_Position = computePosition_1_0(\\n    positionHi, positionLo,\\n    scaleHi, scaleLo,\\n    translateHi, translateLo);\\n}\\n\",pickFragment:\"precision lowp float;\\n#define GLSLIFY 1\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = fragColor;\\n}\\n\"}},{}],217:[function(t,e,r){arguments[4][77][0].apply(r,arguments)},{dup:77}],218:[function(t,e,r){arguments[4][196][0].apply(r,arguments)},{\"./lib/GLError\":219,\"./lib/create-attributes\":220,\"./lib/create-uniforms\":221,\"./lib/reflect\":222,\"./lib/runtime-reflect\":223,\"./lib/shader-cache\":224,dup:196}],219:[function(t,e,r){arguments[4][197][0].apply(r,arguments)},{dup:197}],220:[function(t,e,r){arguments[4][198][0].apply(r,arguments)},{\"./GLError\":219,dup:198}],221:[function(t,e,r){arguments[4][199][0].apply(r,arguments)},{\"./GLError\":219,\"./reflect\":222,dup:199}],222:[function(t,e,r){arguments[4][200][0].apply(r,arguments)},{dup:200}],223:[function(t,e,r){arguments[4][201][0].apply(r,arguments)},{dup:201}],224:[function(t,e,r){arguments[4][202][0].apply(r,arguments)},{\"./GLError\":219,dup:202,\"gl-format-compiler-error\":149,\"weakmap-shim\":542}],225:[function(t,e,r){\"use strict\";function n(t,e,r,n,a){a<=4*f?i(0,a-1,t,e,r,n):h(0,a-1,t,e,r,n)}function i(t,e,r,n,i,a){for(var o=t+1;o<=e;++o){for(var s=r[o],l=n[2*o],u=n[2*o+1],c=i[o],h=a[o],f=o;f>t;){var d=r[f-1],p=n[2*(f-1)];if((d-s||l-p)>=0)break;r[f]=d,n[2*f]=p,n[2*f+1]=n[2*f-1],i[f]=i[f-1],a[f]=a[f-1],f-=1}r[f]=s,n[2*f]=l,n[2*f+1]=u,i[f]=c,a[f]=h}}function a(t,e,r,n,i,a){var o=r[t],s=n[2*t],l=n[2*t+1],u=i[t],c=a[t];r[t]=r[e],n[2*t]=n[2*e],n[2*t+1]=n[2*e+1],i[t]=i[e],a[t]=a[e],r[e]=o,n[2*e]=s,n[2*e+1]=l,i[e]=u,a[e]=c}function o(t,e,r,n,i,a){r[t]=r[e],n[2*t]=n[2*e],n[2*t+1]=n[2*e+1],i[t]=i[e],a[t]=a[e]}function s(t,e,r,n,i,a,o){var s=n[t],l=i[2*t],u=i[2*t+1],c=a[t],h=o[t];n[t]=n[e],i[2*t]=i[2*e],i[2*t+1]=i[2*e+1],a[t]=a[e],o[t]=o[e],n[e]=n[r],i[2*e]=i[2*r],i[2*e+1]=i[2*r+1],a[e]=a[r],o[e]=o[r],n[r]=s,i[2*r]=l,i[2*r+1]=u,a[r]=c,o[r]=h}function l(t,e,r,n,i,a,o,s,l,u,c){s[t]=s[e],l[2*t]=l[2*e],l[2*t+1]=l[2*e+1],u[t]=u[e],c[t]=c[e],s[e]=r,l[2*e]=n,l[2*e+1]=i,u[e]=a,c[e]=o}function 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if(!c(it,P,O,j,R,r,n,d))for(;;){if(c(S,P,O,j,R,r,n,d)){c(S,L,C,z,D,r,n,d)?(s(it,T,S,r,n,d,p),++T,--S):(a(it,S,r,n,d,p),--S);break}if(--S<it)break}l(t,T-1,L,C,z,D,I,r,n,d,p),l(e,S+1,P,O,j,R,F,r,n,d,p),T-2-t<=f?i(t,T-2,r,n,d,p):h(t,T-2,r,n,d,p),e-(S+2)<=f?i(S+2,e,r,n,d,p):h(S+2,e,r,n,d,p),S-T<=f?i(T,S,r,n,d,p):h(T,S,r,n,d,p)}e.exports=n;var f=32},{}],226:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s){for(var l=r,u=r;u<n;++u){var c=t[2*u],h=t[2*u+1],f=e[u];i<=c&&c<=o&&a<=h&&h<=s&&(u===l?l+=1:(t[2*u]=t[2*l],t[2*u+1]=t[2*l+1],e[u]=e[l],t[2*l]=c,t[2*l+1]=h,e[l]=f,l+=1))}return l}function i(t,e,r){this.pixelSize=t,this.offset=e,this.count=r}function a(t,e,r,a){function l(i,a,o,s,u,c){var h=.5*o,f=s+1,d=u-s;r[_]=d,x[_++]=c;for(var p=0;p<2;++p)for(var m=0;m<2;++m){var g=i+p*h,v=a+m*h,y=n(t,e,f,u,g,v,g+h,v+h);if(y!==f){if(y-f>=Math.max(.9*d,32)){var b=u+s>>>1;l(g,v,h,f,b,c+1),f=b}l(g,v,h,f,y,c+1),f=y}}}var u=t.length>>>1;if(u<1)return[];for(var c=1/0,h=1/0,f=-1/0,d=-1/0,p=0;p<u;++p){var m=t[2*p],g=t[2*p+1];c=Math.min(c,m),f=Math.max(f,m),h=Math.min(h,g),d=Math.max(d,g),e[p]=p}c===f&&(f+=1+Math.abs(f)),h===d&&(d+=1+Math.abs(f));var v=1/(f-c),y=1/(d-h),b=Math.max(f-c,d-h);(a=a||[0,0,0,0])[0]=c,a[1]=h,a[2]=f,a[3]=d;var x=o.mallocInt32(u),_=0;l(c,h,b,0,u,0),s(x,t,e,r,u);for(var w=[],M=0,k=u,_=u-1;_>=0;--_){t[2*_]=(t[2*_]-c)*v,t[2*_+1]=(t[2*_+1]-h)*y;var A=x[_];A!==M&&(w.push(new i(b*Math.pow(.5,A),_+1,k-(_+1))),k=_+1,M=A)}return w.push(new i(b*Math.pow(.5,A+1),0,k)),o.free(x),w}var o=t(\"typedarray-pool\"),s=t(\"./lib/sort\");e.exports=a},{\"./lib/sort\":225,\"typedarray-pool\":521}],227:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.sizeBuffer=i,this.colorBuffer=a,this.idBuffer=o,this.charBuffer=s,this.pointCount=0,this.pickOffset=0,this.points=null,this.scales=[],this.xCoords=[],this.charCanvas=document.createElement(\"canvas\"),this.charTexture=h(this.plot.gl,this.charCanvas),this.charStep=400,this.charOffset=.032,this.snapThreshold=1e4,this.paletteTexture=h(this.plot.gl,[256,1])}function i(t,e){var r=t.gl,i=new n(t,a(r,l.vertex,l.fragment),a(r,l.pickVertex,l.pickFragment),o(r),o(r),o(r),o(r),o(r));return i.update(e),t.addObject(i),i}e.exports=i;var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"typedarray-pool\"),l=t(\"./lib/shaders\"),u=t(\"snap-points-2d\"),c=t(\"font-atlas-sdf\"),h=t(\"gl-texture2d\"),f=t(\"color-id\"),d=t(\"ndarray\"),p=t(\"clamp\"),m=t(\"binary-search-bounds\"),g=n.prototype;!function(){function t(){var t=this.plot,u=t.viewBox,c=t.dataBox,h=t.pixelRatio,f=c[2]-c[0],d=c[3]-c[1],p=2/f,m=2/d,g=-c[0]-.5*f,v=-c[1]-.5*d;i[0]=p,a[0]=p-i[0],i[1]=m,a[1]=m-i[1],o[0]=g,s[0]=g-o[0],o[1]=v,s[1]=v-o[1];var y=u[2]-u[0],b=u[3]-u[1];e=Math.min(f/y,d/b),l[0]=2*h/y,l[1]=2*h/b,r=c[0],n=c[2]}var e,r,n,i=new Float32Array([0,0]),a=new Float32Array([0,0]),o=new Float32Array([0,0]),s=new Float32Array([0,0]),l=[0,0],u=[0,0,0,0];g.drawPick=function(l){var c=void 0!==l,h=this.plot,f=this.pointCount,d=f>this.snapThreshold;if(!f)return l;t.call(this);var p=h.gl,g=c?this.pickShader:this.shader,v=p.isEnabled(p.BLEND);if(g.bind(),c){this.pickOffset=l;for(var y=0;y<4;++y)u[y]=l>>8*y&255;g.uniforms.pickOffset=u,this.idBuffer.bind(),g.attributes.id.pointer(p.UNSIGNED_BYTE,!1)}else p.blendFuncSeparate(p.SRC_ALPHA,p.ONE_MINUS_SRC_ALPHA,p.ONE,p.ONE_MINUS_SRC_ALPHA),p.blendColor(0,0,0,1),v||p.enable(p.BLEND),this.colorBuffer.bind(),g.attributes.color.pointer(p.UNSIGNED_BYTE,!1),this.charBuffer.bind(),g.attributes.char.pointer(p.UNSIGNED_BYTE,!1),g.uniforms.chars=this.charTexture.bind(0),g.uniforms.charsShape=[this.charCanvas.width,this.charCanvas.height],g.uniforms.charsStep=this.charStep,g.uniforms.palette=this.paletteTexture.bind(1),g.uniforms.charOffset=this.charOffset;this.sizeBuffer.bind(),g.attributes.size.pointer(p.FLOAT,!1,8,0),c||g.attributes.border.pointer(p.FLOAT,!1,8,4),this.positionBuffer.bind(),g.attributes.positionHi.pointer(p.FLOAT,!1,16,0),g.attributes.positionLo.pointer(p.FLOAT,!1,16,8),g.uniforms.pixelRatio=h.pixelRatio,g.uniforms.scaleHi=i,g.uniforms.scaleLo=a,g.uniforms.translateHi=o,g.uniforms.translateLo=s,g.uniforms.viewBox=h.viewBox;var b=this.scales;if(d)for(var x=b.length-1;x>=0;x--){var _=b[x];if(!(_.pixelSize&&_.pixelSize<1.25*e&&x>1)){var w=_.offset,M=_.count+w,k=m.ge(this.xCoords,r,w,M-1),A=m.lt(this.xCoords,n,k,M-1)+1;A>k&&p.drawArrays(p.POINTS,k,A-k)}}else p.drawArrays(p.POINTS,0,f);if(c)return l+f;v?p.blendFunc(p.ONE,p.ONE_MINUS_SRC_ALPHA):p.disable(p.BLEND)}}(),g.draw=g.drawPick,g.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]]}},g.update=function(t){var e=(t=t||{}).positions||[],r=t.colors||[],n=t.glyphs||[],i=t.sizes||[],a=t.borderWidths||[],o=t.borderColors||[],l=this.plot.gl;null!=t.charOffset&&(this.charOffset=t.charOffset),this.points=e;var h=this.points.length/2,m=s.mallocInt32(h),g=s.mallocFloat32(2*h),v=s.mallocFloat64(2*h);v.set(this.points),this.pointCount=h;var y=h>this.snapThreshold;y&&(this.scales=u(v,m,g));for(var b=s.mallocFloat32(4*h),x=s.mallocFloat32(2*h),_=s.mallocUint8(2*h),w=s.mallocUint32(h),M=s.mallocUint8(2*h),k={},A=[],T=[],S=[],E=0,L=h,C=0;E<L;++E){var z=[255*r[4*E],255*r[4*E+1],255*r[4*E+2],255*r[4*E+3]];null==k[X=f(z,!1)]&&(k[X]=C++,T.push(z[0]),T.push(z[1]),T.push(z[2]),T.push(z[3])),A.push(X),o&&o.length&&(null==k[X=f(z=[255*o[4*E],255*o[4*E+1],255*o[4*E+2],255*o[4*E+3]],!1)]&&(k[X]=C++,T.push(z[0]),T.push(z[1]),T.push(z[2]),T.push(z[3])),S.push(X))}for(var D={},E=0,L=h,C=0;E<L;E++)null==D[Q=n[E]]&&(D[Q]=C++);for(var I=0,E=0,L=i.length;E<L;++E)i[E]>I&&(I=i[E]);var P=this.charStep;this.charStep=p(Math.ceil(4*I),128,768);var O=Object.keys(D),j=this.charStep,R=Math.floor(j/2),F=l.getParameter(l.MAX_TEXTURE_SIZE),N=F/j*(F/j),B=Math.min(F,j*O.length),U=Math.min(F,j*Math.ceil(j*O.length/F)),V=Math.floor(B/j);O.length>N&&console.warn(\"gl-scatter2d-fancy: number of characters is more than maximum texture size. Try reducing it.\"),this.chars&&this.chars+\"\"==O+\"\"&&this.charStep==P||(this.charCanvas=c({canvas:this.charCanvas,family:\"sans-serif\",size:R,shape:[B,U],step:[j,j],chars:O}),this.chars=O);for(E=0;E<h;++E){var H=y?m[E]:E,q=e[2*H],G=e[2*H+1],Y=i[H],W=a[H];b[4*E]=q,b[4*E+1]=G,b[4*E+2]=q-b[4*E],b[4*E+3]=G-b[4*E+1],this.xCoords[E]=q,x[2*E]=2*Y,x[2*E+1]=W,w[E]=H;var X=A[H],Z=k[X];_[2*E]=Z;var J=k[S[H]];_[2*E+1]=J;var Q=n[H],K=D[Q];M[2*E+1]=Math.floor(K/V),M[2*E]=K%V}this.positionBuffer.update(b),this.sizeBuffer.update(x),this.colorBuffer.update(_),this.idBuffer.update(w),this.charBuffer.update(M),this.charTexture.shape=[this.charCanvas.width,this.charCanvas.height],this.charCanvas&&this.charCanvas.width&&this.charTexture.setPixels(this.charCanvas),this.paletteTexture.setPixels(d(T.slice(0,1024),[256,1,4])),s.free(b),s.free(x),s.free(_),s.free(w),s.free(M),s.free(v),s.free(m),s.free(g)},g.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.sizeBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.charBuffer.dispose(),this.plot.removeObject(this)}},{\"./lib/shaders\":216,\"binary-search-bounds\":217,clamp:81,\"color-id\":85,\"font-atlas-sdf\":119,\"gl-buffer\":141,\"gl-shader\":218,\"gl-texture2d\":251,ndarray:449,\"snap-points-2d\":226,\"typedarray-pool\":521}],228:[function(t,e,r){r.pointVertex=\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 positionHi, positionLo;\\nattribute float weight;\\n\\nuniform vec2 scaleHi, scaleLo, translateHi, translateLo;\\nuniform float pointSize, useWeight;\\n\\nvarying float fragWeight;\\n\\n\\nvec4 pfx_1_0(vec2 scaleHi, vec2 scaleLo, vec2 translateHi, vec2 translateLo, vec2 positionHi, vec2 positionLo) {\\n  return vec4((positionHi + translateHi) * scaleHi\\n            + (positionLo + translateLo) * scaleHi\\n            + (positionHi + translateHi) * scaleLo\\n            + (positionLo + translateLo) * scaleLo, 0.0, 1.0);\\n}\\n\\nvoid main() {\\n  gl_Position = pfx_1_0(scaleHi, scaleLo, translateHi, translateLo, positionHi, positionLo);\\n  gl_PointSize = pointSize;\\n  fragWeight = mix(1.0, weight, useWeight);\\n}\",r.pointFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\n\\nvarying float fragWeight;\\n\\nfloat smoothStep(float x, float y) {\\n  return 1.0 / (1.0 + exp(50.0*(x - y)));\\n}\\n\\nvoid main() {\\n  float radius = length(2.0*gl_PointCoord.xy-1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  vec4 baseColor = mix(borderColor, color, smoothStep(radius, centerFraction));\\n  float alpha = 1.0 - pow(1.0 - baseColor.a, fragWeight);\\n  gl_FragColor = vec4(baseColor.rgb * alpha, alpha);\\n}\",r.pickVertex=\"precision highp float;\\n#define GLSLIFY 1\\n\\nvec4 pfx_1_0(vec2 scaleHi, vec2 scaleLo, vec2 translateHi, vec2 translateLo, vec2 positionHi, vec2 positionLo) {\\n  return vec4((positionHi + translateHi) * scaleHi\\n            + (positionLo + translateLo) * scaleHi\\n            + (positionHi + translateHi) * scaleLo\\n            + (positionLo + translateLo) * scaleLo, 0.0, 1.0);\\n}\\n\\nattribute vec2 positionHi, positionLo;\\nattribute vec4 pickId;\\n\\nuniform vec2 scaleHi, scaleLo, translateHi, translateLo;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\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  gl_Position = pfx_1_0(scaleHi, scaleLo, translateHi, translateLo, positionHi, positionLo);\\n  gl_PointSize = pointSize;\\n  fragId = id;\\n}\",r.pickFragment=\"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}\"},{}],229:[function(t,e,r){arguments[4][77][0].apply(r,arguments)},{dup:77}],230:[function(t,e,r){arguments[4][225][0].apply(r,arguments)},{dup:225}],231:[function(t,e,r){arguments[4][226][0].apply(r,arguments)},{\"./lib/sort\":230,dup:226,\"typedarray-pool\":521}],232:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o){this.plot=t,this.positionBufferHi=e,this.positionBufferLo=r,this.pickBuffer=n,this.weightBuffer=i,this.shader=a,this.pickShader=o,this.scales=[],this.size=12,this.borderSize=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.bounds=[1/0,1/0,-1/0,-1/0],this.pickOffset=0,this.points=null,this.xCoords=null}function i(t,e){var r=t.gl,i=new n(t,o(r),o(r),o(r),o(r),a(r,c.pointVertex,c.pointFragment),a(r,c.pickVertex,c.pickFragment));return i.update(e),t.addObject(i),i}var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"binary-search-bounds\"),l=t(\"snap-points-2d\"),u=t(\"typedarray-pool\"),c=t(\"./lib/shader\");e.exports=i;var h=n.prototype,f=new Float32Array(2),d=new Float32Array(2),p=new Float32Array(2),m=new Float32Array(2),g=[0,0,0,0];h.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBufferHi.dispose(),this.positionBufferLo.dispose(),this.pickBuffer.dispose(),this.xCoords&&u.free(this.xCoords),this.plot.removeObject(this)},h.update=function(t){function e(e,r){return e in t?t[e]:r}t=t||{},this.size=e(\"size\",12),this.color=e(\"color\",[1,0,0,1]).slice(),this.borderSize=e(\"borderSize\",1),this.borderColor=e(\"borderColor\",[0,0,0,1]).slice(),this.xCoords&&u.free(this.xCoords),this.points=t.positions;var r=this.points.length>>>1,n=u.mallocInt32(r),i=u.mallocFloat32(2*r),a=u.mallocFloat64(2*r);a.set(this.points),this.scales=l(a,n,i,this.bounds);var o=u.mallocFloat64(r),s=u.mallocFloat32(2*r),c=u.mallocFloat32(2*r);s.set(a);for(var h=0,f=0;h<r;h++,f+=2)c[f]=a[f]-s[f],c[f+1]=a[f+1]-s[f+1],o[h]=a[f];this.positionBufferHi.update(s),this.positionBufferLo.update(c),this.pickBuffer.update(n),this.weightBuffer.update(i),u.free(n),u.free(a),u.free(s),u.free(c),u.free(i),this.xCoords=o,this.pointCount=r,this.pickOffset=0},h.draw=function(t){var e=void 0!==t,r=this.plot,n=e?this.pickShader:this.shader,i=this.scales,a=this.positionBufferHi,o=this.positionBufferLo,l=this.pickBuffer,u=this.bounds,c=this.size,h=this.borderSize,v=r.gl,y=e?r.pickPixelRatio:r.pixelRatio,b=r.viewBox,x=r.dataBox;if(0===this.pointCount)return t;var _=u[2]-u[0],w=u[3]-u[1],M=x[2]-x[0],k=x[3]-x[1],A=(b[2]-b[0])*y/r.pixelRatio,T=(b[3]-b[1])*y/r.pixelRatio,S=Math.min(M/A,k/T),E=2*_/M,L=2*w/k;f[0]=E,f[1]=L,d[0]=E-f[0],d[1]=L-f[1];var C=(u[0]-x[0]-.5*M)/_,z=(u[1]-x[1]-.5*k)/w;p[0]=C,p[1]=z,m[0]=C-p[0],m[1]=z-p[1],n.bind(),n.uniforms.scaleHi=f,n.uniforms.scaleLo=d,n.uniforms.translateHi=p,n.uniforms.translateLo=m,n.uniforms.color=this.color,n.uniforms.borderColor=this.borderColor,n.uniforms.pointSize=y*(c+h),n.uniforms.centerFraction=0===this.borderSize?2:c/(c+h+1.25),a.bind(),n.attributes.positionHi.pointer(),o.bind(),n.attributes.positionLo.pointer(),e?(this.pickOffset=t,g[0]=255&t,g[1]=t>>8&255,g[2]=t>>16&255,g[3]=t>>24&255,n.uniforms.pickOffset=g,l.bind(),n.attributes.pickId.pointer(v.UNSIGNED_BYTE)):(n.uniforms.useWeight=1,this.weightBuffer.bind(),n.attributes.weight.pointer());for(var D=this.xCoords,I=(x[0]-u[0]-S*c*y)/_,P=(x[2]-u[0]+S*c*y)/_,O=!0,j=i.length-1;j>=0;j--){var R=i[j];if(!(R.pixelSize<S&&j>1)){var F=R.offset,N=R.count+F,B=s.ge(D,I,F,N-1),U=s.lt(D,P,B,N-1)+1;U>B&&v.drawArrays(v.POINTS,B,U-B),!e&&O&&(O=!1,n.uniforms.useWeight=0)}}return t+this.pointCount},h.drawPick=h.draw,h.pick=function(t,e,r){var n=r-this.pickOffset;return n<0||n>=this.pointCount?null:{object:this,pointId:n,dataCoord:[this.points[2*n],this.points[2*n+1]]}}},{\"./lib/shader\":228,\"binary-search-bounds\":229,\"gl-buffer\":141,\"gl-shader\":239,\"snap-points-2d\":231,\"typedarray-pool\":521}],233:[function(t,e,r){\"use strict\";function n(t,e){var r=a[e];if(r||(r=a[e]={}),t in r)return r[t];for(var n=i(t,{textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e}),o=i(t,{triangles:!0,textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e}),s=[[1/0,1/0],[-1/0,-1/0]],l=0;l<n.positions.length;++l)for(var u=n.positions[l],c=0;c<2;++c)s[0][c]=Math.min(s[0][c],u[c]),s[1][c]=Math.max(s[1][c],u[c]);return r[t]=[o,n,s]}var i=t(\"vectorize-text\");e.exports=n;var a={}},{\"vectorize-text\":534}],234:[function(t,e,r){function n(t,e){var r=i(t,e),n=r.attributes;return n.position.location=0,n.color.location=1,n.glyph.location=2,n.id.location=3,r}var i=t(\"gl-shader\"),a=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\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(any(lessThan(position, clipBounds[0]))   || \\n     any(greaterThan(position, clipBounds[1])) ) {\\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=\"precision mediump float;\\n#define GLSLIFY 1\\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(any(lessThan(position, clipBounds[0])) || any(greaterThan(position, clipBounds[1]))) {\\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=\"precision mediump float;\\n#define GLSLIFY 1\\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(any(lessThan(position, clipBounds[0]))   ||\\n     any(greaterThan(position, clipBounds[1])) ) {\\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=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(dataCoordinate, fragClipBounds[0]))   ||\\n     any(greaterThan(dataCoordinate, fragClipBounds[1])) ) {\\n    discard;\\n  } else {\\n    gl_FragColor = interpColor * opacity;\\n  }\\n}\\n\",u=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(dataCoordinate, fragClipBounds[0]))   || \\n     any(greaterThan(dataCoordinate, fragClipBounds[1])) ) {\\n    discard;\\n  } else {\\n    gl_FragColor = vec4(pickGroup, pickId.bgr);\\n  }\\n}\",c=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],h={vertex:a,fragment:l,attributes:c},f={vertex:o,fragment:l,attributes:c},d={vertex:s,fragment:l,attributes:c},p={vertex:a,fragment:u,attributes:c},m={vertex:o,fragment:u,attributes:c},g={vertex:s,fragment:u,attributes:c};r.createPerspective=function(t){return n(t,h)},r.createOrtho=function(t){return n(t,f)},r.createProject=function(t){return n(t,d)},r.createPickPerspective=function(t){return n(t,p)},r.createPickOrtho=function(t){return n(t,m)},r.createPickProject=function(t){return n(t,g)}},{\"gl-shader\":239}],235:[function(t,e,r){\"use strict\";function n(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 i(t,e,r,i){return n(i,i,r),n(i,i,e),n(i,i,t)}function a(t,e){this.index=t,this.dataCoordinate=this.position=e}function o(t,e,r,n,i,o,s,l,u,c,h,f){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=o,this.glyphBuffer=s,this.idBuffer=l,this.vao=u,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.pickId=0,this.pickPerspectiveShader=c,this.pickOrthoShader=h,this.pickProjectShader=f,this.points=[],this._selectResult=new a(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}function s(t){return t[0]=t[1]=t[2]=0,t}function l(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function u(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}function c(t){for(var e=L,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}function h(t,e,r,n,a){var o,h=e.axesProject,f=e.gl,d=t.uniforms,p=r.model||x,m=r.view||x,g=r.projection||x,y=e.axesBounds,b=c(e.clipBounds);o=e.axes?e.axes.lastCubeProps.axis:[1,1,1],w[0]=2/f.drawingBufferWidth,w[1]=2/f.drawingBufferHeight,t.bind(),d.view=m,d.projection=g,d.screenSize=w,d.highlightId=e.highlightId,d.highlightScale=e.highlightScale,d.clipBounds=b,d.pickGroup=e.pickId/255,d.pixelRatio=e.pixelRatio;for(var _=0;_<3;++_)if(h[_]&&e.projectOpacity[_]<1===n){d.scale=e.projectScale[_],d.opacity=e.projectOpacity[_];for(var L=S,C=0;C<16;++C)L[C]=0;for(C=0;C<4;++C)L[5*C]=1;L[5*_]=0,o[_]<0?L[12+_]=y[0][_]:L[12+_]=y[1][_],v(L,p,L),d.model=L;var z=(_+1)%3,D=(_+2)%3,I=s(M),P=s(k);I[z]=1,P[D]=1;var O=i(g,m,p,l(A,I)),j=i(g,m,p,l(T,P));if(Math.abs(O[1])>Math.abs(j[1])){var R=O;O=j,j=R,R=I,I=P,P=R;var F=z;z=D,D=F}O[0]<0&&(I[z]=-1),j[1]>0&&(P[D]=-1);for(var N=0,B=0,C=0;C<4;++C)N+=Math.pow(p[4*z+C],2),B+=Math.pow(p[4*D+C],2);I[z]/=Math.sqrt(N),P[D]/=Math.sqrt(B),d.axes[0]=I,d.axes[1]=P,d.fragClipBounds[0]=u(E,b[0],_,-1e8),d.fragClipBounds[1]=u(E,b[1],_,1e8),e.vao.draw(f.TRIANGLES,e.vertexCount),e.lineWidth>0&&(f.lineWidth(e.lineWidth),e.vao.draw(f.LINES,e.lineVertexCount,e.vertexCount))}}function f(t,e,r,n,i,a){var o=r.gl;if(r.vao.bind(),i===r.opacity<1||a){t.bind();var s=t.uniforms;s.model=n.model||x,s.view=n.view||x,s.projection=n.projection||x,w[0]=2/o.drawingBufferWidth,w[1]=2/o.drawingBufferHeight,s.screenSize=w,s.highlightId=r.highlightId,s.highlightScale=r.highlightScale,s.fragClipBounds=C,s.clipBounds=r.axes.bounds,s.opacity=r.opacity,s.pickGroup=r.pickId/255,s.pixelRatio=r.pixelRatio,r.vao.draw(o.TRIANGLES,r.vertexCount),r.lineWidth>0&&(o.lineWidth(r.lineWidth),r.vao.draw(o.LINES,r.lineVertexCount,r.vertexCount))}h(e,r,n,i,a),r.vao.unbind()}function d(t){var e=t.gl,r=y.createPerspective(e),n=y.createOrtho(e),i=y.createProject(e),a=y.createPickPerspective(e),s=y.createPickOrtho(e),l=y.createPickProject(e),u=p(e),c=p(e),h=p(e),f=p(e),d=new o(e,r,n,i,u,c,h,f,m(e,[{buffer:u,size:3,type:e.FLOAT},{buffer:c,size:4,type:e.FLOAT},{buffer:h,size:2,type:e.FLOAT},{buffer:f,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),a,s,l);return d.update(t),d}var p=t(\"gl-buffer\"),m=t(\"gl-vao\"),g=t(\"typedarray-pool\"),v=t(\"gl-mat4/multiply\"),y=t(\"./lib/shaders\"),b=t(\"./lib/glyphs\"),x=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];e.exports=d;var _=o.prototype;_.pickSlots=1,_.setPickBase=function(t){this.pickId=t},_.isTransparent=function(){if(this.opacity<1)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectOpacity[t]<1)return!0;return!1},_.isOpaque=function(){if(this.opacity>=1)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectOpacity[t]>=1)return!0;return!1};var w=[0,0],M=[0,0,0],k=[0,0,0],A=[0,0,0,1],T=[0,0,0,1],S=x.slice(),E=[0,0,0],L=[[0,0,0],[0,0,0]],C=[[-1e8,-1e8,-1e8],[1e8,1e8,1e8]];_.draw=function(t){f(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,!1,!1)},_.drawTransparent=function(t){f(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,!0,!1)},_.drawPick=function(t){f(this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader,this.pickProjectShader,this,t,!1,!0)},_.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},_.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]},_.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{r=+t.projectScale;this.projectScale=[r,r,r]}if(\"projectOpacity\"in t)if(Array.isArray(t.projectOpacity))this.projectOpacity=t.projectOpacity.slice();else{var r=+t.projectOpacity;this.projectOpacity=[r,r,r]}\"opacity\"in t&&(this.opacity=t.opacity),this.dirty=!0;var n=t.position;if(n){var i=t.font||\"normal\",a=t.alignment||[0,0],o=[1/0,1/0,1/0],s=[-1/0,-1/0,-1/0],l=t.glyph,u=t.color,c=t.size,h=t.angle,f=t.lineColor,d=0,p=0,m=0,v=n.length;t:for(j=0;j<v;++j){for(var y=n[j],x=0;x<3;++x)if(isNaN(y[x])||!isFinite(y[x]))continue t;var _=(R=Array.isArray(l)?b(l[j],i):l?b(l,i):b(\"●\",i))[0],w=R[1],M=R[2];p+=3*_.cells.length,m+=2*w.edges.length}var k=p+m,A=g.mallocFloat(3*k),T=g.mallocFloat(4*k),S=g.mallocFloat(2*k),E=g.mallocUint32(k),L=[0,a[1]],C=0,z=p,D=[0,0,0,1],I=[0,0,0,1],P=Array.isArray(u)&&Array.isArray(u[0]),O=Array.isArray(f)&&Array.isArray(f[0]);t:for(var j=0;j<v;++j){for(var y=n[j],x=0;x<3;++x){if(isNaN(y[x])||!isFinite(y[x])){d+=1;continue t}s[x]=Math.max(s[x],y[x]),o[x]=Math.min(o[x],y[x])}var R,_=(R=Array.isArray(l)?b(l[j],i):l?b(l,i):b(\"●\",i))[0],w=R[1],M=R[2];if(Array.isArray(u)){if(3===(F=P?u[j]:u).length){for(x=0;x<3;++x)D[x]=F[x];D[3]=1}else if(4===F.length)for(x=0;x<4;++x)D[x]=F[x]}else D[0]=D[1]=D[2]=0,D[3]=1;if(Array.isArray(f)){var F;if(3===(F=O?f[j]:f).length){for(x=0;x<3;++x)I[x]=F[x];I[x]=1}else if(4===F.length)for(x=0;x<4;++x)I[x]=F[x]}else I[0]=I[1]=I[2]=0,I[3]=1;var N=.5;Array.isArray(c)?N=+c[j]:c?N=+c:this.useOrtho&&(N=12);var B=0;Array.isArray(h)?B=+h[j]:h&&(B=+h);for(var U=Math.cos(B),V=Math.sin(B),y=n[j],x=0;x<3;++x)s[x]=Math.max(s[x],y[x]),o[x]=Math.min(o[x],y[x]);a[0]<0?L[0]=a[0]*(1+M[1][0]):a[0]>0&&(L[0]=-a[0]*(1+M[0][0]));for(var H=_.cells,q=_.positions,x=0;x<H.length;++x)for(var G=H[x],Y=0;Y<3;++Y){for(W=0;W<3;++W)A[3*C+W]=y[W];for(W=0;W<4;++W)T[4*C+W]=D[W];E[C]=d;X=q[G[Y]];S[2*C]=N*(U*X[0]-V*X[1]+L[0]),S[2*C+1]=N*(V*X[0]+U*X[1]+L[1]),C+=1}for(var H=w.edges,q=w.positions,x=0;x<H.length;++x)for(var G=H[x],Y=0;Y<2;++Y){for(W=0;W<3;++W)A[3*z+W]=y[W];for(var W=0;W<4;++W)T[4*z+W]=I[W];E[z]=d;var X=q[G[Y]];S[2*z]=N*(U*X[0]-V*X[1]+L[0]),S[2*z+1]=N*(V*X[0]+U*X[1]+L[1]),z+=1}d+=1}this.vertexCount=p,this.lineVertexCount=m,this.pointBuffer.update(A),this.colorBuffer.update(T),this.glyphBuffer.update(S),this.idBuffer.update(new Uint32Array(E)),g.free(A),g.free(T),g.free(S),g.free(E),this.bounds=[o,s],this.points=n,this.pointCount=n.length}},_.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/glyphs\":233,\"./lib/shaders\":234,\"gl-buffer\":141,\"gl-mat4/multiply\":167,\"gl-vao\":255,\"typedarray-pool\":521}],236:[function(t,e,r){\"use strict\";r.boxVertex=\"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=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = color;\\n}\\n\"},{}],237:[function(t,e,r){\"use strict\";function n(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}function i(t,e){var r=t.gl,i=new n(t,o(r,[0,0,0,1,1,0,1,1]),a(r,s.boxVertex,s.boxFragment));return i.update(e),t.addOverlay(i),i}var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"./lib/shaders\");e.exports=i;var l=n.prototype;l.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,u=t.viewBox,c=t.pixelRatio,h=(e[0]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],f=(e[1]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1],d=(e[2]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],p=(e[3]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1];if(h=Math.max(h,u[0]),f=Math.max(f,u[1]),d=Math.min(d,u[2]),p=Math.min(p,u[3]),!(d<h||p<f)){o.bind();var m=s[2]-s[0],g=s[3]-s[1];if(this.outerFill&&(o.drawBox(0,0,m,f,i),o.drawBox(0,f,h,p,i),o.drawBox(0,p,m,g,i),o.drawBox(d,f,m,p,i)),this.innerFill&&o.drawBox(h,f,d,p,n),r>0){var v=r*c;o.drawBox(h-v,f-v,d+v,f+v,a),o.drawBox(h-v,p-v,d+v,p+v,a),o.drawBox(h-v,f-v,h+v,p+v,a),o.drawBox(d-v,f-v,d+v,p+v,a)}}}},l.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()},l.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},{\"./lib/shaders\":236,\"gl-buffer\":141,\"gl-shader\":239}],238:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function i(t,e,r){this.gl=t,this.fbo=e,this.buffer=r,this._readTimeout=null;var n=this;this._readCallback=function(){n.gl&&(e.bind(),t.readPixels(0,0,e.shape[0],e.shape[1],t.RGBA,t.UNSIGNED_BYTE,n.buffer),n._readTimeout=null)}}function a(t,e){return new i(t,o(t,e),s.mallocUint8(e[0]*e[1]*4))}e.exports=a;var o=t(\"gl-fbo\"),s=t(\"typedarray-pool\"),l=t(\"ndarray\"),u=t(\"bit-twiddle\").nextPow2,c=t(\"cwise/lib/wrapper\")({args:[\"array\",{offset:[0,0,1],array:0},{offset:[0,0,2],array:0},{offset:[0,0,3],array:0},\"scalar\",\"scalar\",\"index\"],pre:{body:\"{this_closestD2=1e8,this_closestX=-1,this_closestY=-1}\",args:[],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[]},body:{body:\"{if(_inline_46_arg0_<255||_inline_46_arg1_<255||_inline_46_arg2_<255||_inline_46_arg3_<255){var _inline_46_l=_inline_46_arg4_-_inline_46_arg6_[0],_inline_46_a=_inline_46_arg5_-_inline_46_arg6_[1],_inline_46_f=_inline_46_l*_inline_46_l+_inline_46_a*_inline_46_a;_inline_46_f<this_closestD2&&(this_closestD2=_inline_46_f,this_closestX=_inline_46_arg6_[0],this_closestY=_inline_46_arg6_[1])}}\",args:[{name:\"_inline_46_arg0_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_46_arg1_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_46_arg2_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_46_arg3_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_46_arg4_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_46_arg5_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_46_arg6_\",lvalue:!1,rvalue:!0,count:4}],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[\"_inline_46_a\",\"_inline_46_f\",\"_inline_46_l\"]},post:{body:\"{return[this_closestX,this_closestY,this_closestD2]}\",args:[],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[]},debug:!1,funcName:\"cwise\",blockSize:64}),h=i.prototype;Object.defineProperty(h,\"shape\",{get:function(){return this.gl?this.fbo.shape.slice():[0,0]},set:function(t){if(this.gl){this.fbo.shape=t;var e=this.fbo.shape[0],r=this.fbo.shape[1];if(r*e*4>this.buffer.length){s.free(this.buffer);for(var n=this.buffer=s.mallocUint8(u(r*e*4)),i=0;i<r*e*4;++i)n[i]=255}return t}}}),h.begin=function(){var t=this.gl;this.shape;t&&(this.fbo.bind(),t.clearColor(1,1,1,1),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT))},h.end=function(){var t=this.gl;t&&(t.bindFramebuffer(t.FRAMEBUFFER,null),this._readTimeout||clearTimeout(this._readTimeout),this._readTimeout=setTimeout(this._readCallback,1))},h.query=function(t,e,r){if(!this.gl)return null;var i=this.fbo.shape.slice();t|=0,e|=0,\"number\"!=typeof r&&(r=1);var a=0|Math.min(Math.max(t-r,0),i[0]),o=0|Math.min(Math.max(t+r,0),i[0]),s=0|Math.min(Math.max(e-r,0),i[1]),u=0|Math.min(Math.max(e+r,0),i[1]);if(o<=a||u<=s)return null;var h=[o-a,u-s],f=l(this.buffer,[h[0],h[1],4],[4,4*i[0],1],4*(a+i[0]*s)),d=c(f.hi(h[0],h[1],1),r,r),p=d[0],m=d[1];return p<0||Math.pow(this.radius,2)<d[2]?null:new n(p+a|0,m+s|0,f.get(p,m,0),[f.get(p,m,1),f.get(p,m,2),f.get(p,m,3)],Math.sqrt(d[2]))},h.dispose=function(){this.gl&&(this.fbo.dispose(),s.free(this.buffer),this.gl=null,this._readTimeout&&clearTimeout(this._readTimeout))}},{\"bit-twiddle\":60,\"cwise/lib/wrapper\":106,\"gl-fbo\":148,ndarray:449,\"typedarray-pool\":521}],239:[function(t,e,r){\"use strict\";function n(t){this.gl=t,this._vref=this._fref=this._relink=this.vertShader=this.fragShader=this.program=this.attributes=this.uniforms=this.types=null}function i(t,e){return t.name<e.name?-1:1}function a(t,e,r,i,a){var o=new n(t);return o.update(e,r,i,a),o}var o=t(\"./lib/create-uniforms\"),s=t(\"./lib/create-attributes\"),l=t(\"./lib/reflect\"),u=t(\"./lib/shader-cache\"),c=t(\"./lib/runtime-reflect\"),h=t(\"./lib/GLError\"),f=n.prototype;f.bind=function(){this.program||this._relink(),this.gl.useProgram(this.program)},f.dispose=function(){this._fref&&this._fref.dispose(),this._vref&&this._vref.dispose(),this.attributes=this.types=this.vertShader=this.fragShader=this.program=this._relink=this._fref=this._vref=null},f.update=function(t,e,r,n){function a(){d.program=u.program(p,d._vref,d._fref,x,_);for(var t=0;t<r.length;++t)E[t]=p.getUniformLocation(d.program,r[t].name)}if(!e||1===arguments.length){var f=t;t=f.vertex,e=f.fragment,r=f.uniforms,n=f.attributes}var d=this,p=d.gl,m=d._vref;d._vref=u.shader(p,p.VERTEX_SHADER,t),m&&m.dispose(),d.vertShader=d._vref.shader;var g=this._fref;if(d._fref=u.shader(p,p.FRAGMENT_SHADER,e),g&&g.dispose(),d.fragShader=d._fref.shader,!r||!n){var v=p.createProgram();if(p.attachShader(v,d.fragShader),p.attachShader(v,d.vertShader),p.linkProgram(v),!p.getProgramParameter(v,p.LINK_STATUS)){var y=p.getProgramInfoLog(v);throw new h(y,\"Error linking program:\"+y)}r=r||c.uniforms(p,v),n=n||c.attributes(p,v),p.deleteProgram(v)}(n=n.slice()).sort(i);for(var b=[],x=[],_=[],w=0;w<n.length;++w){var M=n[w];if(M.type.indexOf(\"mat\")>=0){for(var k=0|M.type.charAt(M.type.length-1),A=new Array(k),T=0;T<k;++T)A[T]=_.length,x.push(M.name+\"[\"+T+\"]\"),\"number\"==typeof M.location?_.push(M.location+T):Array.isArray(M.location)&&M.location.length===k&&\"number\"==typeof M.location[T]?_.push(0|M.location[T]):_.push(-1);b.push({name:M.name,type:M.type,locations:A})}else b.push({name:M.name,type:M.type,locations:[_.length]}),x.push(M.name),\"number\"==typeof M.location?_.push(0|M.location):_.push(-1)}for(var S=0,w=0;w<_.length;++w)if(_[w]<0){for(;_.indexOf(S)>=0;)S+=1;_[w]=S}var E=new Array(r.length);a(),d._relink=a,d.types={uniforms:l(r),attributes:l(n)},d.attributes=s(p,d,b,_),Object.defineProperty(d,\"uniforms\",o(p,d,r,E))},e.exports=a},{\"./lib/GLError\":240,\"./lib/create-attributes\":241,\"./lib/create-uniforms\":242,\"./lib/reflect\":243,\"./lib/runtime-reflect\":244,\"./lib/shader-cache\":245}],240:[function(t,e,r){arguments[4][197][0].apply(r,arguments)},{dup:197}],241:[function(t,e,r){arguments[4][198][0].apply(r,arguments)},{\"./GLError\":240,dup:198}],242:[function(t,e,r){arguments[4][199][0].apply(r,arguments)},{\"./GLError\":240,\"./reflect\":243,dup:199}],243:[function(t,e,r){arguments[4][200][0].apply(r,arguments)},{dup:200}],244:[function(t,e,r){arguments[4][201][0].apply(r,arguments)},{dup:201}],245:[function(t,e,r){arguments[4][202][0].apply(r,arguments)},{\"./GLError\":240,dup:202,\"gl-format-compiler-error\":149,\"weakmap-shim\":542}],246:[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]}function i(t,e){var r=new n(t);return r.update(e),t.addOverlay(r),r}e.exports=i;var a=n.prototype;a.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()},a.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]),u=s[1]+(n[1]-o[1])/(o[3]-o[1])*(s[3]-s[1]);t[0]&&a.drawLine(l,u,s[0],u,e[0],r[0]),t[1]&&a.drawLine(l,u,l,s[1],e[1],r[1]),t[2]&&a.drawLine(l,u,s[2],u,e[2],r[2]),t[3]&&a.drawLine(l,u,l,s[3],e[3],r[3])}},a.dispose=function(){this.plot.removeOverlay(this)}},{}],247:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\");e.exports=function(t){return n(t,\"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\",\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  gl_FragColor = fragColor;\\n}\",null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec3\"},{name:\"weight\",type:\"float\"}])}},{\"gl-shader\":239}],248:[function(t,e,r){\"use strict\";function n(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}function i(t,e){function r(t,e,r,n,a,o){var s=[t,e,r,0,0,0,1];s[n+3]=1,s[n]=a,i.push.apply(i,s),s[6]=-1,i.push.apply(i,s),s[n]=o,i.push.apply(i,s),i.push.apply(i,s),s[6]=1,i.push.apply(i,s),s[n]=a,i.push.apply(i,s)}var i=[];r(0,0,0,0,0,1),r(0,0,0,1,0,1),r(0,0,0,2,0,1),r(1,0,0,1,-1,1),r(1,0,0,2,-1,1),r(0,1,0,0,-1,1),r(0,1,0,2,-1,1),r(0,0,1,0,-1,1),r(0,0,1,1,-1,1);var l=a(t,i),u=o(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}]),c=s(t);c.attributes.position.location=0,c.attributes.color.location=1,c.attributes.weight.location=2;var h=new n(t,l,u,c);return h.update(e),h}var a=t(\"gl-buffer\"),o=t(\"gl-vao\"),s=t(\"./shaders/index\");e.exports=i;var l=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],u=n.prototype,c=[0,0,0],h=[0,0,0],f=[0,0];u.isTransparent=function(){return!1},u.drawTransparent=function(t){},u.draw=function(t){var e=this.gl,r=this.vao,n=this.shader;r.bind(),n.bind();var i,a=t.model||l,o=t.view||l,s=t.projection||l;this.axes&&(i=this.axes.lastCubeProps.axis);for(var u=c,d=h,p=0;p<3;++p)i&&i[p]<0?(u[p]=this.bounds[0][p],d[p]=this.bounds[1][p]):(u[p]=this.bounds[1][p],d[p]=this.bounds[0][p]);f[0]=e.drawingBufferWidth,f[1]=e.drawingBufferHeight,n.uniforms.model=a,n.uniforms.view=o,n.uniforms.projection=s,n.uniforms.coordinates=[this.position,u,d],n.uniforms.colors=this.colors,n.uniforms.screenShape=f;for(p=0;p<3;++p)n.uniforms.lineWidth=this.lineWidth[p]*this.pixelRatio,this.enabled[p]&&(r.draw(e.TRIANGLES,6,6*p),this.drawSides[p]&&r.draw(e.TRIANGLES,12,18+12*p));r.unbind()},u.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))},u.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders/index\":247,\"gl-buffer\":141,\"gl-vao\":255}],249:[function(t,e,r){var n=t(\"gl-shader\"),i=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute vec3 f;\\nattribute vec3 normal;\\n\\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  worldCoordinate = vec3(uv.zw, f.x);\\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\",a=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution_2_0(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\\n\\n\\nfloat beckmannSpecular_1_1(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness) {\\n  return beckmannDistribution_2_0(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\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 (kill > 0.0 ||\\n    any(lessThan(worldCoordinate, clipBounds[0])) || any(greaterThan(worldCoordinate, clipBounds[1]))) {\\n    discard;\\n  }\\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 = beckmannSpecular_1_1(L, V, N, roughness);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  //decide how to interpolate color — in vertex or in fragment\\n  vec4 surfaceColor = step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) + 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\",o=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute float f;\\n\\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  vec4 worldPosition = model * vec4(dataCoordinate, 1.0);\\n\\n  vec4 clipPosition = projection * view * worldPosition;\\n  clipPosition.z = clipPosition.z + zOffset;\\n\\n  gl_Position = clipPosition;\\n  value = f;\\n  kill = -1.0;\\n  worldCoordinate = dataCoordinate;\\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\",s=\"precision mediump float;\\n#define GLSLIFY 1\\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    any(lessThan(worldCoordinate, clipBounds[0])) || any(greaterThan(worldCoordinate, clipBounds[1]))) {\\n    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,i,a,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,i,s,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,o,a,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,o,s,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},{\"gl-shader\":239}],250:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}function i(t){var e=x([y({colormap:t,nshades:j,format:\"rgba\"}).map(function(t){return[t[0],t[1],t[2],255*t[3]]})]);return b.divseq(e,255),e}function a(t,e,r,i,a,o,s,l,u,c,h,f,d,p){this.gl=t,this.shape=e,this.bounds=r,this.intensityBounds=[],this._shader=i,this._pickShader=a,this._coordinateBuffer=o,this._vao=s,this._colorMap=l,this._contourShader=u,this._contourPickShader=c,this._contourBuffer=h,this._contourVAO=f,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new n([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=p,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=[_(v.mallocFloat(1024),[0,0]),_(v.mallocFloat(1024),[0,0]),_(v.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.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}function o(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||F,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=N.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],M(l,t.model,l);var u=N.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)u[i][n]=t.clipBounds[i][n];u[0][r]=-1e8,u[1][r]=1e8}return N.showSurface=o,N.showContour=s,N}function s(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=B;n.model=t.model||I,n.view=t.view||I,n.projection=t.projection||I,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.contourColor=this.contourColor[0],n.inverseModel=k(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],s=0;s<3;++s)a[s]=Math.min(Math.max(this.clipBounds[i][s],-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=V,n.vertexColor=this.vertexColor;var l=U;for(M(l,n.view,n.model),M(l,n.projection,l),k(l,l),i=0;i<3;++i)n.eyePosition[i]=l[12+i]/l[15];var u=l[15];for(i=0;i<3;++i)u+=this.lightPosition[i]*l[4*i+3];for(i=0;i<3;++i){var c=l[12+i];for(s=0;s<3;++s)c+=l[4*s+i]*this.lightPosition[s];n.lightPosition[i]=c/u}var h=o(n,this);if(h.showSurface&&e===this.opacity<1){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=h.projections[i],this._shader.uniforms.clipBounds=h.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(h.showContour&&!e){var f=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,f.bind(),f.uniforms=n;var d=this._contourVAO;for(d.bind(),i=0;i<3;++i)for(f.uniforms.permutation=O[i],r.lineWidth(this.contourWidth[i]),s=0;s<this.contourLevels[i].length;++s)this._contourCounts[i][s]&&(s===this.highlightLevel[i]?(f.uniforms.contourColor=this.highlightColor[i],f.uniforms.contourTint=this.highlightTint[i]):0!==s&&s-1!==this.highlightLevel[i]||(f.uniforms.contourColor=this.contourColor[i],f.uniforms.contourTint=this.contourTint[i]),f.uniforms.height=this.contourLevels[i][s],d.draw(r.LINES,this._contourCounts[i][s],this._contourOffsets[i][s]));for(i=0;i<3;++i)for(f.uniforms.model=h.projections[i],f.uniforms.clipBounds=h.clipBounds[i],s=0;s<3;++s)if(this.contourProject[i][s]){f.uniforms.permutation=O[s],r.lineWidth(this.contourWidth[s]);for(var p=0;p<this.contourLevels[s].length;++p)p===this.highlightLevel[s]?(f.uniforms.contourColor=this.highlightColor[s],f.uniforms.contourTint=this.highlightTint[s]):0!==p&&p-1!==this.highlightLevel[s]||(f.uniforms.contourColor=this.contourColor[s],f.uniforms.contourTint=this.contourTint[s]),f.uniforms.height=this.contourLevels[s][p],d.draw(r.LINES,this._contourCounts[s][p],this._contourOffsets[s][p])}for((d=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=O[i],r.lineWidth(this.dynamicWidth[i]),f.uniforms.contourColor=this.dynamicColor[i],f.uniforms.contourTint=this.dynamicTint[i],f.uniforms.height=this.dynamicLevel[i],d.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]),s=0;s<3;++s)this.contourProject[s][i]&&(f.uniforms.model=h.projections[s],f.uniforms.clipBounds=h.clipBounds[s],d.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]));d.unbind()}}function l(t,e){var r=e.shape.slice(),n=t.shape.slice();b.assign(t.lo(1,1).hi(r[0],r[1]),e),b.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),b.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),b.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),b.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))}function u(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function c(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 h(t){if(Array.isArray(t)){if(Array.isArray(t))return[c(t[0]),c(t[1]),c(t[2])];var e=c(t);return[e.slice(),e.slice(),e.slice()]}}function f(t){var e=t.gl,r=E(e),n=C(e),i=L(e),o=z(e),s=p(e),l=m(e,[{buffer:s,size:4,stride:D,offset:0},{buffer:s,size:3,stride:D,offset:16},{buffer:s,size:3,stride:D,offset:28}]),u=p(e),c=m(e,[{buffer:u,size:4,stride:20,offset:0},{buffer:u,size:1,stride:20,offset:16}]),h=p(e),f=m(e,[{buffer:h,size:2,type:e.FLOAT}]),d=g(e,1,j,e.RGBA,e.UNSIGNED_BYTE);d.minFilter=e.LINEAR,d.magFilter=e.LINEAR;var v=new a(e,[0,0],[[0,0,0],[0,0,0]],r,n,s,l,d,i,o,u,c,h,f),y={levels:[[],[],[]]};for(var b in t)y[b]=t[b];return y.colormap=y.colormap||\"jet\",v.update(y),v}e.exports=f;var d=t(\"bit-twiddle\"),p=t(\"gl-buffer\"),m=t(\"gl-vao\"),g=t(\"gl-texture2d\"),v=t(\"typedarray-pool\"),y=t(\"colormap\"),b=t(\"ndarray-ops\"),x=t(\"ndarray-pack\"),_=t(\"ndarray\"),w=t(\"surface-nets\"),M=t(\"gl-mat4/multiply\"),k=t(\"gl-mat4/invert\"),A=t(\"binary-search-bounds\"),T=t(\"ndarray-gradient\"),S=t(\"./lib/shaders\"),E=S.createShader,L=S.createContourShader,C=S.createPickShader,z=S.createPickContourShader,D=40,I=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],P=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],O=[[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(){for(var t=0;t<3;++t){var e=O[t],r=(t+2)%3;e[(t+1)%3+0]=1,e[r+3]=1,e[t+6]=1}}();var j=256,R=a.prototype;R.isTransparent=function(){return this.opacity<1},R.isOpaque=function(){if(this.opacity>=1)return!0;for(var t=0;t<3;++t)if(this._contourCounts[t].length>0||this._dynamicCounts[t]>0)return!0;return!1},R.pickSlots=1,R.setPickBase=function(t){this.pickId=t};var F=[0,0,0],N={showSurface:!1,showContour:!1,projections:[I.slice(),I.slice(),I.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]},B={model:I,view:I,projection:I,inverseModel:I.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,kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},U=I.slice(),V=[1,0,0,0,1,0,0,0,1];R.draw=function(t){return s.call(this,t,!1)},R.drawTransparent=function(t){return s.call(this,t,!0)};var H={model:I,view:I,projection:I,inverseModel:I,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};R.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=H;r.model=t.model||I,r.view=t.view||I,r.projection=t.projection||I,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.permutation=V;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 s=o(r,this);if(s.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=s.projections[n],this._pickShader.uniforms.clipBounds=s.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(s.showContour){var l=this._contourPickShader;l.bind(),l.uniforms=r;var u=this._contourVAO;for(u.bind(),a=0;a<3;++a)for(e.lineWidth(this.contourWidth[a]),l.uniforms.permutation=O[a],n=0;n<this.contourLevels[a].length;++n)this._contourCounts[a][n]&&(l.uniforms.height=this.contourLevels[a][n],u.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n]));for(n=0;n<3;++n)for(l.uniforms.model=s.projections[n],l.uniforms.clipBounds=s.clipBounds[n],a=0;a<3;++a)if(this.contourProject[n][a]){l.uniforms.permutation=O[a],e.lineWidth(this.contourWidth[a]);for(var c=0;c<this.contourLevels[a].length;++c)this._contourCounts[a][c]&&(l.uniforms.height=this.contourLevels[a][c],u.draw(e.LINES,this._contourCounts[a][c],this._contourOffsets[a][c]))}u.unbind()}},R.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 u=r.position;u[0]=u[1]=u[2]=0;for(var c=0;c<2;++c)for(var h=c?a:1-a,f=0;f<2;++f)for(var d=i+c,p=s+f,m=h*(f?l:1-l),g=0;g<3;++g)u[g]+=this._field[g].get(d,p)*m;for(var v=this._pickResult.level,y=0;y<3;++y)if(v[y]=A.le(this.contourLevels[y],u[y]),v[y]<0)this.contourLevels[y].length>0&&(v[y]=0);else if(v[y]<this.contourLevels[y].length-1){var b=this.contourLevels[y][v[y]],x=this.contourLevels[y][v[y]+1];Math.abs(b-u[y])>Math.abs(x-u[y])&&(v[y]+=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],g=0;g<3;++g)r.dataCoordinate[g]=this._field[g].get(r.index[0],r.index[1]);return r},R.update=function(t){t=t||{},this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=u(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=u(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=u(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=h(t.contourColor)),\"contourProject\"in t&&(this.contourProject=u(t.contourProject,function(t){return u(t,Boolean)})),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=h(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=u(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=u(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\"colorBounds\"in t&&(this.colorBounds=t.colorBounds),\"vertexColor\"in t&&(this.vertexColor=t.vertexColor?1:0);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 n=(e.shape[0]+2)*(e.shape[1]+2);n>this._field[2].data.length&&(v.freeFloat(this._field[2].data),this._field[2].data=v.mallocFloat(d.nextPow2(n))),this._field[2]=_(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),l(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&&(v.freeFloat(this._field[o].data),this._field[o].data=v.mallocFloat(this._field[2].size)),this._field[o]=_(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var s=t.coords;if(!Array.isArray(s)||3!==s.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(o=0;o<2;++o){var c=s[o];for(y=0;y<2;++y)if(c.shape[y]!==a[y])throw new Error(\"gl-surface: coords have incorrect shape\");l(this._field[o],c)}}else if(t.ticks){var f=t.ticks;if(!Array.isArray(f)||2!==f.length)throw new Error(\"gl-surface: invalid ticks\");for(o=0;o<2;++o){var p=f[o];if((Array.isArray(p)||p.length)&&(p=_(p)),p.shape[0]!==a[o])throw new Error(\"gl-surface: invalid tick length\");var m=_(p.data,a);m.stride[o]=p.stride[0],m.stride[1^o]=0,l(this._field[o],m)}}else{for(o=0;o<2;++o){var g=[0,0];g[o]=1,this._field[o]=_(this._field[o].data,[a[0]+2,a[1]+2],g,0)}this._field[0].set(0,0,0);for(var y=0;y<a[0];++y)this._field[0].set(y+1,0,y);for(this._field[0].set(a[0]+1,0,a[0]-1),this._field[1].set(0,0,0),y=0;y<a[1];++y)this._field[1].set(0,y+1,y);this._field[1].set(0,a[1]+1,a[1]-1)}var b=this._field,x=_(v.mallocFloat(3*b[2].size*2),[3,a[0]+2,a[1]+2,2]);for(o=0;o<3;++o)T(x.pick(o),b[o],\"mirror\");var M=_(v.mallocFloat(3*b[2].size),[a[0]+2,a[1]+2,3]);for(o=0;o<a[0]+2;++o)for(y=0;y<a[1]+2;++y){var k=x.get(0,o,y,0),A=x.get(0,o,y,1),S=x.get(1,o,y,0),E=x.get(1,o,y,1),L=x.get(2,o,y,0),C=x.get(2,o,y,1),z=S*C-E*L,D=L*A-C*k,I=k*E-A*S,O=Math.sqrt(z*z+D*D+I*I);O<1e-8?(O=Math.max(Math.abs(z),Math.abs(D),Math.abs(I)))<1e-8?(I=1,D=z=0,O=1):O=1/O:O=1/Math.sqrt(O),M.set(o,y,0,z*O),M.set(o,y,1,D*O),M.set(o,y,2,I*O)}v.free(x.data);var j=[1/0,1/0,1/0],R=[-1/0,-1/0,-1/0],F=1/0,N=-1/0,B=(a[0]-1)*(a[1]-1)*6,U=v.mallocFloat(d.nextPow2(10*B)),V=0,H=0;for(o=0;o<a[0]-1;++o)t:for(y=0;y<a[1]-1;++y){for(var q=0;q<2;++q)for(var G=0;G<2;++G)for(var Y=0;Y<3;++Y){var W=this._field[Y].get(1+o+q,1+y+G);if(isNaN(W)||!isFinite(W))continue t}for(Y=0;Y<6;++Y){var X=o+P[Y][0],Z=y+P[Y][1],J=this._field[0].get(X+1,Z+1),Q=this._field[1].get(X+1,Z+1),K=W=this._field[2].get(X+1,Z+1);z=M.get(X+1,Z+1,0),D=M.get(X+1,Z+1,1),I=M.get(X+1,Z+1,2),t.intensity&&(K=t.intensity.get(X,Z)),U[V++]=X,U[V++]=Z,U[V++]=J,U[V++]=Q,U[V++]=W,U[V++]=0,U[V++]=K,U[V++]=z,U[V++]=D,U[V++]=I,j[0]=Math.min(j[0],J),j[1]=Math.min(j[1],Q),j[2]=Math.min(j[2],W),F=Math.min(F,K),R[0]=Math.max(R[0],J),R[1]=Math.max(R[1],Q),R[2]=Math.max(R[2],W),N=Math.max(N,K),H+=1}}for(t.intensityBounds&&(F=+t.intensityBounds[0],N=+t.intensityBounds[1]),o=6;o<V;o+=10)U[o]=(U[o]-F)/(N-F);this._vertexCount=H,this._coordinateBuffer.update(U.subarray(0,V)),v.freeFloat(U),v.free(M.data),this.bounds=[j,R],this.intensity=t.intensity||this._field[2],this.intensityBounds[0]===F&&this.intensityBounds[1]===N||(r=!0),this.intensityBounds=[F,N]}if(\"levels\"in t){var $=t.levels;for($=Array.isArray($[0])?$.slice():[[],[],$],o=0;o<3;++o)$[o]=$[o].slice(),$.sort(function(t,e){return t-e});t:for(o=0;o<3;++o){if($[o].length!==this.contourLevels[o].length){r=!0;break}for(y=0;y<$[o].length;++y)if($[o][y]!==this.contourLevels[o][y]){r=!0;break t}}this.contourLevels=$}if(r){b=this._field,a=this.shape;for(var tt=[],et=0;et<3;++et){$=this.contourLevels[et];var rt=[],nt=[],it=[0,0,0];for(o=0;o<$.length;++o){var at=w(this._field[et],$[o]);rt.push(tt.length/5|0),H=0;t:for(y=0;y<at.cells.length;++y){var ot=at.cells[y];for(Y=0;Y<2;++Y){var st=at.positions[ot[Y]],lt=st[0],ut=0|Math.floor(lt),ct=lt-ut,ht=st[1],ft=0|Math.floor(ht),dt=ht-ft,pt=!1;e:for(var mt=0;mt<3;++mt){it[mt]=0;var gt=(et+mt+1)%3;for(q=0;q<2;++q){var vt=q?ct:1-ct;for(X=0|Math.min(Math.max(ut+q,0),a[0]),G=0;G<2;++G){var yt=G?dt:1-dt;if(Z=0|Math.min(Math.max(ft+G,0),a[1]),W=mt<2?this._field[gt].get(X,Z):(this.intensity.get(X,Z)-this.intensityBounds[0])/(this.intensityBounds[1]-this.intensityBounds[0]),!isFinite(W)||isNaN(W)){pt=!0;break e}var bt=vt*yt;it[mt]+=bt*W}}}if(pt){if(Y>0){for(var xt=0;xt<5;++xt)tt.pop();H-=1}continue t}tt.push(it[0],it[1],st[0],st[1],it[2]),H+=1}}nt.push(H)}this._contourOffsets[et]=rt,this._contourCounts[et]=nt}var _t=v.mallocFloat(tt.length);for(o=0;o<tt.length;++o)_t[o]=tt[o];this._contourBuffer.update(_t),v.freeFloat(_t)}t.colormap&&this._colorMap.setPixels(i(t.colormap))},R.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)v.freeFloat(this._field[t].data)},R.highlight=function(t){if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(var e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;var r;if(r=this.snapToData?t.dataCoordinate:t.position,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=v.mallocFloat(12*i[0]*i[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var s=(o+1)%3,l=(o+2)%3,u=this._field[o],c=this._field[s],h=this._field[l],f=(this.intensity,w(u,r[o])),d=f.cells,p=f.positions;for(this._dynamicOffsets[o]=n,e=0;e<d.length;++e)for(var m=d[e],g=0;g<2;++g){var y=p[m[g]],b=+y[0],x=0|b,_=0|Math.min(x+1,i[0]),M=b-x,k=1-M,A=+y[1],T=0|A,S=0|Math.min(T+1,i[1]),E=A-T,L=1-E,C=k*L,z=k*E,D=M*L,I=M*E,P=C*c.get(x,T)+z*c.get(x,S)+D*c.get(_,T)+I*c.get(_,S),O=C*h.get(x,T)+z*h.get(x,S)+D*h.get(_,T)+I*h.get(_,S);if(isNaN(P)||isNaN(O)){g&&(n-=1);break}a[2*n+0]=P,a[2*n+1]=O,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)),v.freeFloat(a)}}},{\"./lib/shaders\":249,\"binary-search-bounds\":59,\"bit-twiddle\":60,colormap:92,\"gl-buffer\":141,\"gl-mat4/invert\":165,\"gl-mat4/multiply\":167,\"gl-texture2d\":251,\"gl-vao\":255,ndarray:449,\"ndarray-gradient\":440,\"ndarray-ops\":443,\"ndarray-pack\":444,\"surface-nets\":511,\"typedarray-pool\":521}],251:[function(t,e,r){\"use strict\";function n(t){v=[t.LINEAR,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_NEAREST],y=[t.NEAREST,t.LINEAR,t.NEAREST_MIPMAP_NEAREST,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_LINEAR],b=[t.REPEAT,t.CLAMP_TO_EDGE,t.MIRRORED_REPEAT]}function i(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}function a(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 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h=0,f=0,d=s(c,l.stride.slice());\"float32\"===u?h=t.FLOAT:\"float64\"===u?(h=t.FLOAT,d=!1,u=\"float32\"):\"uint8\"===u?h=t.UNSIGNED_BYTE:(h=t.UNSIGNED_BYTE,d=!1,u=\"uint8\");if(2===c.length)f=t.LUMINANCE,c=[c[0],c[1],1],l=p(l.data,c,[l.stride[0],l.stride[1],1],l.offset);else{if(3!==c.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===c[2])f=t.ALPHA;else if(2===c[2])f=t.LUMINANCE_ALPHA;else if(3===c[2])f=t.RGB;else{if(4!==c[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");f=t.RGBA}c[2]}if(f!==t.LUMINANCE&&f!==t.ALPHA||i!==t.LUMINANCE&&i!==t.ALPHA||(f=i),f!==i)throw new Error(\"gl-texture2d: Incompatible texture format for setPixels\");var 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n=t(\"./builtins\");n=n.slice().filter(function(t){return!/^(gl\\_|texture)/.test(t)}),e.exports=n.concat([\"gl_VertexID\",\"gl_InstanceID\",\"gl_Position\",\"gl_PointSize\",\"gl_FragCoord\",\"gl_FrontFacing\",\"gl_FragDepth\",\"gl_PointCoord\",\"gl_MaxVertexAttribs\",\"gl_MaxVertexUniformVectors\",\"gl_MaxVertexOutputVectors\",\"gl_MaxFragmentInputVectors\",\"gl_MaxVertexTextureImageUnits\",\"gl_MaxCombinedTextureImageUnits\",\"gl_MaxTextureImageUnits\",\"gl_MaxFragmentUniformVectors\",\"gl_MaxDrawBuffers\",\"gl_MinProgramTexelOffset\",\"gl_MaxProgramTexelOffset\",\"gl_DepthRangeParameters\",\"gl_DepthRange\",\"trunc\",\"round\",\"roundEven\",\"isnan\",\"isinf\",\"floatBitsToInt\",\"floatBitsToUint\",\"intBitsToFloat\",\"uintBitsToFloat\",\"packSnorm2x16\",\"unpackSnorm2x16\",\"packUnorm2x16\",\"unpackUnorm2x16\",\"packHalf2x16\",\"unpackHalf2x16\",\"outerProduct\",\"transpose\",\"determinant\",\"inverse\",\"texture\",\"textureSize\",\"textureProj\",\"textureLod\",\"textureOffset\",\"texelFetch\",\"texelFetchOffset\",\"textureProjOffset\",\"textureLodOffset\",\"textureProjLod\",\"textureProjLodOffset\",\"textureGrad\",\"textureGradOffset\",\"textureProjGrad\",\"textureProjGradOffset\"])},{\"./builtins\":266}],266:[function(t,e,r){e.exports=[\"abs\",\"acos\",\"all\",\"any\",\"asin\",\"atan\",\"ceil\",\"clamp\",\"cos\",\"cross\",\"dFdx\",\"dFdy\",\"degrees\",\"distance\",\"dot\",\"equal\",\"exp\",\"exp2\",\"faceforward\",\"floor\",\"fract\",\"gl_BackColor\",\"gl_BackLightModelProduct\",\"gl_BackLightProduct\",\"gl_BackMaterial\",\"gl_BackSecondaryColor\",\"gl_ClipPlane\",\"gl_ClipVertex\",\"gl_Color\",\"gl_DepthRange\",\"gl_DepthRangeParameters\",\"gl_EyePlaneQ\",\"gl_EyePlaneR\",\"gl_EyePlaneS\",\"gl_EyePlaneT\",\"gl_Fog\",\"gl_FogCoord\",\"gl_FogFragCoord\",\"gl_FogParameters\",\"gl_FragColor\",\"gl_FragCoord\",\"gl_FragData\",\"gl_FragDepth\",\"gl_FragDepthEXT\",\"gl_FrontColor\",\"gl_FrontFacing\",\"gl_FrontLightModelProduct\",\"gl_FrontLightProduct\",\"gl_FrontMaterial\",\"gl_FrontSecondaryColor\",\"gl_LightModel\",\"gl_LightModelParameters\",\"gl_LightModelProducts\",\"gl_LightProducts\",\"gl_LightSource\",\"gl_LightSourceParameters\",\"gl_MaterialParameters\",\"gl_MaxClipPlanes\",\"gl_MaxCombinedTextureImageUnits\",\"gl_MaxDrawBuffers\",\"gl_MaxFragmentUniformComponents\",\"gl_MaxLights\",\"gl_MaxTextureCoords\",\"gl_MaxTextureImageUnits\",\"gl_MaxTextureUnits\",\"gl_MaxVaryingFloats\",\"gl_MaxVertexAttribs\",\"gl_MaxVertexTextureImageUnits\",\"gl_MaxVertexUniformComponents\",\"gl_ModelViewMatrix\",\"gl_ModelViewMatrixInverse\",\"gl_ModelViewMatrixInverseTranspose\",\"gl_ModelViewMatrixTranspose\",\"gl_ModelViewProjectionMatrix\",\"gl_ModelViewProjectionMatrixInverse\",\"gl_ModelViewProjectionMatrixInverseTranspose\",\"gl_ModelViewProjectionMatrixTranspose\",\"gl_MultiTexCoord0\",\"gl_MultiTexCoord1\",\"gl_MultiTexCoord2\",\"gl_MultiTexCoord3\",\"gl_MultiTexCoord4\",\"gl_MultiTexCoord5\",\"gl_MultiTexCoord6\",\"gl_MultiTexCoord7\",\"gl_Normal\",\"gl_NormalMatrix\",\"gl_NormalScale\",\"gl_ObjectPlaneQ\",\"gl_ObjectPlaneR\",\"gl_ObjectPlaneS\",\"gl_ObjectPlaneT\",\"gl_Point\",\"gl_PointCoord\",\"gl_PointParameters\",\"gl_PointSize\",\"gl_Position\",\"gl_ProjectionMatrix\",\"gl_ProjectionMatrixInverse\",\"gl_ProjectionMatrixInverseTranspose\",\"gl_ProjectionMatrixTranspose\",\"gl_SecondaryColor\",\"gl_TexCoord\",\"gl_TextureEnvColor\",\"gl_TextureMatrix\",\"gl_TextureMatrixInverse\",\"gl_TextureMatrixInverseTranspose\",\"gl_TextureMatrixTranspose\",\"gl_Vertex\",\"greaterThan\",\"greaterThanEqual\",\"inversesqrt\",\"length\",\"lessThan\",\"lessThanEqual\",\"log\",\"log2\",\"matrixCompMult\",\"max\",\"min\",\"mix\",\"mod\",\"normalize\",\"not\",\"notEqual\",\"pow\",\"radians\",\"reflect\",\"refract\",\"sign\",\"sin\",\"smoothstep\",\"sqrt\",\"step\",\"tan\",\"texture2D\",\"texture2DLod\",\"texture2DProj\",\"texture2DProjLod\",\"textureCube\",\"textureCubeLod\",\"texture2DLodEXT\",\"texture2DProjLodEXT\",\"textureCubeLodEXT\",\"texture2DGradEXT\",\"texture2DProjGradEXT\",\"textureCubeGradEXT\"]},{}],267:[function(t,e,r){var n=t(\"./literals\");e.exports=n.slice().concat([\"layout\",\"centroid\",\"smooth\",\"case\",\"mat2x2\",\"mat2x3\",\"mat2x4\",\"mat3x2\",\"mat3x3\",\"mat3x4\",\"mat4x2\",\"mat4x3\",\"mat4x4\",\"uint\",\"uvec2\",\"uvec3\",\"uvec4\",\"samplerCubeShadow\",\"sampler2DArray\",\"sampler2DArrayShadow\",\"isampler2D\",\"isampler3D\",\"isamplerCube\",\"isampler2DArray\",\"usampler2D\",\"usampler3D\",\"usamplerCube\",\"usampler2DArray\",\"coherent\",\"restrict\",\"readonly\",\"writeonly\",\"resource\",\"atomic_uint\",\"noperspective\",\"patch\",\"sample\",\"subroutine\",\"common\",\"partition\",\"active\",\"filter\",\"image1D\",\"image2D\",\"image3D\",\"imageCube\",\"iimage1D\",\"iimage2D\",\"iimage3D\",\"iimageCube\",\"uimage1D\",\"uimage2D\",\"uimage3D\",\"uimageCube\",\"image1DArray\",\"image2DArray\",\"iimage1DArray\",\"iimage2DArray\",\"uimage1DArray\",\"uimage2DArray\",\"image1DShadow\",\"image2DShadow\",\"image1DArrayShadow\",\"image2DArrayShadow\",\"imageBuffer\",\"iimageBuffer\",\"uimageBuffer\",\"sampler1DArray\",\"sampler1DArrayShadow\",\"isampler1D\",\"isampler1DArray\",\"usampler1D\",\"usampler1DArray\",\"isampler2DRect\",\"usampler2DRect\",\"samplerBuffer\",\"isamplerBuffer\",\"usamplerBuffer\",\"sampler2DMS\",\"isampler2DMS\",\"usampler2DMS\",\"sampler2DMSArray\",\"isampler2DMSArray\",\"usampler2DMSArray\"])},{\"./literals\":268}],268:[function(t,e,r){e.exports=[\"precision\",\"highp\",\"mediump\",\"lowp\",\"attribute\",\"const\",\"uniform\",\"varying\",\"break\",\"continue\",\"do\",\"for\",\"while\",\"if\",\"else\",\"in\",\"out\",\"inout\",\"float\",\"int\",\"void\",\"bool\",\"true\",\"false\",\"discard\",\"return\",\"mat2\",\"mat3\",\"mat4\",\"vec2\",\"vec3\",\"vec4\",\"ivec2\",\"ivec3\",\"ivec4\",\"bvec2\",\"bvec3\",\"bvec4\",\"sampler1D\",\"sampler2D\",\"sampler3D\",\"samplerCube\",\"sampler1DShadow\",\"sampler2DShadow\",\"struct\",\"asm\",\"class\",\"union\",\"enum\",\"typedef\",\"template\",\"this\",\"packed\",\"goto\",\"switch\",\"default\",\"inline\",\"noinline\",\"volatile\",\"public\",\"static\",\"extern\",\"external\",\"interface\",\"long\",\"short\",\"double\",\"half\",\"fixed\",\"unsigned\",\"input\",\"output\",\"hvec2\",\"hvec3\",\"hvec4\",\"dvec2\",\"dvec3\",\"dvec4\",\"fvec2\",\"fvec3\",\"fvec4\",\"sampler2DRect\",\"sampler3DRect\",\"sampler2DRectShadow\",\"sizeof\",\"cast\",\"namespace\",\"using\"]},{}],269:[function(t,e,r){e.exports=[\"<<=\",\">>=\",\"++\",\"--\",\"<<\",\">>\",\"<=\",\">=\",\"==\",\"!=\",\"&&\",\"||\",\"+=\",\"-=\",\"*=\",\"/=\",\"%=\",\"&=\",\"^^\",\"^=\",\"|=\",\"(\",\")\",\"[\",\"]\",\".\",\"!\",\"~\",\"*\",\"/\",\"%\",\"+\",\"-\",\"<\",\">\",\"&\",\"^\",\"|\",\"?\",\":\",\"=\",\",\",\";\",\"{\",\"}\"]},{}],270:[function(t,e,r){function n(t,e){var r=i(e),n=[];return n=n.concat(r(t)),n=n.concat(r(null))}var i=t(\"./index\");e.exports=n},{\"./index\":264}],271:[function(t,e,r){\"use strict\";function n(t,e,r){var n=this.cells=[];if(t instanceof ArrayBuffer){this.arrayBuffer=t;var a=new Int32Array(this.arrayBuffer);t=a[0],e=a[1],r=a[2],this.d=e+2*r;for(var o=0;o<this.d*this.d;o++){var s=a[i+o],l=a[i+o+1];n.push(s===l?null:a.subarray(s,l))}var u=a[i+n.length],c=a[i+n.length+1];this.keys=a.subarray(u,c),this.bboxes=a.subarray(c),this.insert=this._insertReadonly}else{this.d=e+2*r;for(var h=0;h<this.d*this.d;h++)n.push([]);this.keys=[],this.bboxes=[]}this.n=e,this.extent=t,this.padding=r,this.scale=e/t,this.uid=0;var f=r/e*t;this.min=-f,this.max=t+f}e.exports=n;var i=3;n.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)},n.prototype._insertReadonly=function(){throw\"Cannot insert into a GridIndex created from an ArrayBuffer.\"},n.prototype._insertCell=function(t,e,r,n,i,a){this.cells[i].push(a)},n.prototype.query=function(t,e,r,n){var i=this.min,a=this.max;if(t<=i&&e<=i&&a<=r&&a<=n)return Array.prototype.slice.call(this.keys);var o=[],s={};return this._forEachCell(t,e,r,n,this._queryCell,o,s),o},n.prototype._queryCell=function(t,e,r,n,i,a,o){var s=this.cells[i];if(null!==s)for(var l=this.keys,u=this.bboxes,c=0;c<s.length;c++){var h=s[c];if(void 0===o[h]){var f=4*h;t<=u[f+2]&&e<=u[f+3]&&r>=u[f+0]&&n>=u[f+1]?(o[h]=!0,a.push(l[h])):o[h]=!1}}},n.prototype._forEachCell=function(t,e,r,n,i,a,o){for(var s=this._convertToCellCoord(t),l=this._convertToCellCoord(e),u=this._convertToCellCoord(r),c=this._convertToCellCoord(n),h=s;h<=u;h++)for(var f=l;f<=c;f++){var d=this.d*f+h;if(i.call(this,t,e,r,n,d,a,o))return}},n.prototype._convertToCellCoord=function(t){return Math.max(0,Math.min(this.d-1,Math.floor(t*this.scale)+this.padding))},n.prototype.toArrayBuffer=function(){if(this.arrayBuffer)return this.arrayBuffer;for(var t=this.cells,e=i+this.cells.length+1+1,r=0,n=0;n<this.cells.length;n++)r+=this.cells[n].length;var a=new Int32Array(e+r+this.keys.length+this.bboxes.length);a[0]=this.extent,a[1]=this.n,a[2]=this.padding;for(var o=e,s=0;s<t.length;s++){var l=t[s];a[i+s]=o,a.set(l,o),o+=l.length}return a[i+t.length]=o,a.set(this.keys,o),o+=this.keys.length,a[i+t.length+1]=o,a.set(this.bboxes,o),o+=this.bboxes.length,a.buffer}},{}],272:[function(t,e,r){r.read=function(t,e,r,n,i){var a,o,s=8*i-n-1,l=(1<<s)-1,u=l>>1,c=-7,h=r?i-1:0,f=r?-1:1,d=t[e+h];for(h+=f,a=d&(1<<-c)-1,d>>=-c,c+=s;c>0;a=256*a+t[e+h],h+=f,c-=8);for(o=a&(1<<-c)-1,a>>=-c,c+=n;c>0;o=256*o+t[e+h],h+=f,c-=8);if(0===a)a=1-u;else{if(a===l)return o?NaN:1/0*(d?-1:1);o+=Math.pow(2,n),a-=u}return(d?-1:1)*o*Math.pow(2,a-n)},r.write=function(t,e,r,n,i,a){var o,s,l,u=8*a-i-1,c=(1<<u)-1,h=c>>1,f=23===i?Math.pow(2,-24)-Math.pow(2,-77):0,d=n?0:a-1,p=n?1:-1,m=e<0||0===e&&1/e<0?1:0;for(e=Math.abs(e),isNaN(e)||e===1/0?(s=isNaN(e)?1:0,o=c):(o=Math.floor(Math.log(e)/Math.LN2),e*(l=Math.pow(2,-o))<1&&(o--,l*=2),(e+=o+h>=1?f/l:f*Math.pow(2,1-h))*l>=2&&(o++,l/=2),o+h>=c?(s=0,o=c):o+h>=1?(s=(e*l-1)*Math.pow(2,i),o+=h):(s=e*Math.pow(2,h-1)*Math.pow(2,i),o=0));i>=8;t[r+d]=255&s,d+=p,s/=256,i-=8);for(o=o<<i|s,u+=i;u>0;t[r+d]=255&o,d+=p,o/=256,u-=8);t[r+d-p]|=128*m}},{}],273:[function(t,e,r){\"use strict\";function n(t,e,r){this.vertices=t,this.adjacent=e,this.boundary=r,this.lastVisited=-1}function i(t,e,r){this.vertices=t,this.cell=e,this.index=r}function a(t,e){return c(t.vertices,e.vertices)}function o(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 n=new Function(\"test\",e.join(\"\")),i=u[t+1];return i||(i=u),n(i)}function s(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 n=0;n<=t;++n)this.tuple[n]=this.vertices[n];var i=h[t];i||(i=h[t]=o(t)),this.orient=i}function l(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 a=t.slice(0,i+1),o=u.apply(void 0,a);if(0===o)throw new Error(\"Input not in general position\");for(var l=new Array(i+1),c=0;c<=i;++c)l[c]=c;o<0&&(l[0]=1,l[1]=0);for(var h=new n(l,new Array(i+1),!1),f=h.adjacent,d=new Array(i+2),c=0;c<=i;++c){for(var p=l.slice(),m=0;m<=i;++m)m===c&&(p[m]=-1);var g=p[0];p[0]=p[1],p[1]=g;var v=new n(p,new Array(i+1),!0);f[c]=v,d[c]=v}d[i+1]=h;for(c=0;c<=i;++c)for(var p=f[c].vertices,y=f[c].adjacent,m=0;m<=i;++m){var b=p[m];if(b<0)y[m]=h;else for(var x=0;x<=i;++x)f[x].vertices.indexOf(b)<0&&(y[m]=f[x])}for(var _=new s(i,a,d),w=!!e,c=i+1;c<r;++c)_.insert(t[c],w);return _.boundary()}e.exports=l;var u=t(\"robust-orientation\"),c=t(\"simplicial-complex\").compareCells;n.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 h=[],f=s.prototype;f.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 u=s[l];if(u.boundary&&!(u.lastVisited<=-n)){for(var c=u.vertices,h=0;h<=r;++h){var f=c[h];i[h]=f<0?e:a[f]}var d=this.orient();if(d>0)return u;u.lastVisited=-n,0===d&&o.push(u)}}}return null},f.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,u=s.adjacent,c=0;c<=n;++c)a[c]=i[l[c]];s.lastVisited=r;for(c=0;c<=n;++c){var h=u[c];if(!(h.lastVisited>=r)){var f=a[c];a[c]=t;var d=this.orient();if(a[c]=f,d<0){s=h;continue t}h.boundary?h.lastVisited=-r:h.lastVisited=r}}return}return s},f.addPeaks=function(t,e){var r=this.vertices.length-1,o=this.dimension,s=this.vertices,l=this.tuple,u=this.interior,c=this.simplices,h=[e];e.lastVisited=r,e.vertices[e.vertices.indexOf(-1)]=r,e.boundary=!1,u.push(e);for(var f=[];h.length>0;){var d=(e=h.pop()).vertices,p=e.adjacent,m=d.indexOf(r);if(!(m<0))for(C=0;C<=o;++C)if(C!==m){var g=p[C];if(g.boundary&&!(g.lastVisited>=r)){var v=g.vertices;if(g.lastVisited!==-r){for(var y=0,b=0;b<=o;++b)v[b]<0?(y=b,l[b]=t):l[b]=s[v[b]];if(this.orient()>0){v[y]=r,g.boundary=!1,u.push(g),h.push(g),g.lastVisited=r;continue}g.lastVisited=-r}var x=g.adjacent,_=d.slice(),w=p.slice(),M=new n(_,w,!0);c.push(M);var k=x.indexOf(e);if(!(k<0)){x[k]=M,w[m]=g,_[C]=-1,w[C]=e,p[C]=M,M.flip();for(b=0;b<=o;++b){var A=_[b];if(!(A<0||A===r)){for(var T=new Array(o-1),S=0,E=0;E<=o;++E){var L=_[E];L<0||E===b||(T[S++]=L)}f.push(new i(T,M,b))}}}}}}f.sort(a);for(var C=0;C+1<f.length;C+=2){var z=f[C],D=f[C+1],I=z.index,P=D.index;I<0||P<0||(z.cell.adjacent[z.index]=D.cell,D.cell.adjacent[D.index]=z.cell)}},f.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)}},f.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,u=0,c=0;c<=t;++c)s[c]>=0?o[l++]=s[c]:u=1&c;if(u===(1&t)){var h=o[0];o[0]=o[1],o[1]=h}e.push(o)}}return e}},{\"robust-orientation\":489,\"simplicial-complex\":500}],274:[function(t,e,r){\"use strict\";function 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vec2 u_extrude_scale;\\nuniform float u_devicepixelratio;\\n\\nattribute vec2 a_pos;\\n\\n#pragma mapbox: define lowp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n\\nvarying vec2 v_extrude;\\nvarying lowp float v_antialiasblur;\\n\\nvoid main(void) {\\n    #pragma mapbox: initialize lowp vec4 color\\n    #pragma mapbox: initialize mediump float radius\\n    #pragma mapbox: initialize lowp float blur\\n    #pragma mapbox: initialize lowp float opacity\\n\\n    // unencode the extrusion vector that we snuck into the a_pos vector\\n    v_extrude = vec2(mod(a_pos, 2.0) * 2.0 - 1.0);\\n\\n    vec2 extrude = v_extrude * radius * u_extrude_scale;\\n    // multiply a_pos by 0.5, since we had it * 2 in order to sneak\\n    // in extrusion data\\n    gl_Position = u_matrix * vec4(floor(a_pos * 0.5), 0, 1);\\n\\n    if (u_scale_with_map) {\\n        gl_Position.xy += extrude;\\n    } else {\\n        gl_Position.xy += extrude * gl_Position.w;\\n    }\\n\\n    // This is a minimum blur distance that serves as a faux-antialiasing for\\n    // the circle. since blur is a ratio of the circle's size and the intent is\\n    // to keep the blur at roughly 1px, the two are inversely related.\\n    v_antialiasblur = 1.0 / u_devicepixelratio / radius;\\n}\\n\"},line:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform lowp vec4 u_color;\\nuniform lowp float u_opacity;\\nuniform float u_blur;\\n\\nvarying vec2 v_linewidth;\\nvarying vec2 v_normal;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    // Calculate the distance of the pixel from the line in pixels.\\n    float dist = length(v_normal) * v_linewidth.s;\\n\\n    // Calculate the antialiasing fade factor. This is either when fading in\\n    // the line in case of an offset line (v_linewidth.t) or when fading out\\n    // (v_linewidth.s)\\n    float blur = u_blur * v_gamma_scale;\\n    float alpha = clamp(min(dist - (v_linewidth.t - blur), v_linewidth.s - dist) / blur, 0.0, 1.0);\\n\\n    gl_FragColor = u_color * (alpha * u_opacity);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\n// floor(127 / 2) == 63.0\\n// the maximum allowed miter limit is 2.0 at the moment. the extrude normal is\\n// stored in a byte (-128..127). we scale regular normals up to length 63, but\\n// there are also \\\"special\\\" normals that have a bigger length (of up to 126 in\\n// this case).\\n// #define scale 63.0\\n#define scale 0.015873016\\n\\nattribute vec2 a_pos;\\nattribute vec4 a_data;\\n\\nuniform mat4 u_matrix;\\nuniform mediump float u_ratio;\\nuniform mediump float u_linewidth;\\nuniform mediump float u_gapwidth;\\nuniform mediump float u_antialiasing;\\nuniform mediump float u_extra;\\nuniform mat2 u_antialiasingmatrix;\\nuniform mediump float u_offset;\\nuniform mediump float u_blur;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_linewidth;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    vec2 a_extrude = a_data.xy - 128.0;\\n    float a_direction = mod(a_data.z, 4.0) - 1.0;\\n\\n    // We store the texture normals in the most insignificant bit\\n    // transform y so that 0 => -1 and 1 => 1\\n    // In the texture normal, x is 0 if the normal points straight up/down and 1 if it's a round cap\\n    // y is 1 if the normal points up, and -1 if it points down\\n    mediump vec2 normal = mod(a_pos, 2.0);\\n    normal.y = sign(normal.y - 0.5);\\n    v_normal = normal;\\n\\n    float inset = u_gapwidth + (u_gapwidth > 0.0 ? u_antialiasing : 0.0);\\n    float outset = u_gapwidth + u_linewidth * (u_gapwidth > 0.0 ? 2.0 : 1.0) + u_antialiasing;\\n\\n    // Scale the extrusion vector down to a normal and then up by the line width\\n    // of this vertex.\\n    mediump vec2 dist = outset * a_extrude * scale;\\n\\n    // Calculate the offset when drawing a line that is to the side of the actual line.\\n    // We do this by creating a vector that points towards the extrude, but rotate\\n    // it when we're drawing round end points (a_direction = -1 or 1) since their\\n    // extrude vector points in another direction.\\n    mediump float u = 0.5 * a_direction;\\n    mediump float t = 1.0 - abs(u);\\n    mediump vec2 offset = u_offset * a_extrude * scale * normal.y * mat2(t, -u, u, t);\\n\\n    // Remove the texture normal bit of the position before scaling it with the\\n    // model/view matrix.\\n    gl_Position = u_matrix * vec4(floor(a_pos * 0.5) + (offset + dist) / u_ratio, 0.0, 1.0);\\n\\n    // position of y on the screen\\n    float y = gl_Position.y / gl_Position.w;\\n\\n    // how much features are squished in the y direction by the tilt\\n    float squish_scale = length(a_extrude) / length(u_antialiasingmatrix * a_extrude);\\n\\n    // how much features are squished in all directions by the perspectiveness\\n    float perspective_scale = 1.0 / (1.0 - min(y * u_extra, 0.9));\\n\\n    v_linewidth = vec2(outset, inset);\\n    v_gamma_scale = perspective_scale * squish_scale;\\n}\\n\"},linepattern:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform float u_blur;\\n\\nuniform vec2 u_pattern_size_a;\\nuniform vec2 u_pattern_size_b;\\nuniform vec2 u_pattern_tl_a;\\nuniform vec2 u_pattern_br_a;\\nuniform vec2 u_pattern_tl_b;\\nuniform vec2 u_pattern_br_b;\\nuniform float u_fade;\\nuniform float u_opacity;\\n\\nuniform sampler2D u_image;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_linewidth;\\nvarying float v_linesofar;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    // Calculate the distance of the pixel from the line in pixels.\\n    float dist = length(v_normal) * v_linewidth.s;\\n\\n    // Calculate the antialiasing fade factor. This is either when fading in\\n    // the line in case of an offset line (v_linewidth.t) or when fading out\\n    // (v_linewidth.s)\\n    float blur = u_blur * v_gamma_scale;\\n    float alpha = clamp(min(dist - (v_linewidth.t - blur), v_linewidth.s - dist) / blur, 0.0, 1.0);\\n\\n    float x_a = mod(v_linesofar / u_pattern_size_a.x, 1.0);\\n    float x_b = mod(v_linesofar / u_pattern_size_b.x, 1.0);\\n    float y_a = 0.5 + (v_normal.y * v_linewidth.s / u_pattern_size_a.y);\\n    float y_b = 0.5 + (v_normal.y * v_linewidth.s / u_pattern_size_b.y);\\n    vec2 pos_a = mix(u_pattern_tl_a, u_pattern_br_a, vec2(x_a, y_a));\\n    vec2 pos_b = mix(u_pattern_tl_b, u_pattern_br_b, vec2(x_b, y_b));\\n\\n    vec4 color = mix(texture2D(u_image, pos_a), texture2D(u_image, pos_b), u_fade);\\n\\n    alpha *= u_opacity;\\n\\n    gl_FragColor = color * alpha;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\n// floor(127 / 2) == 63.0\\n// the maximum allowed miter limit is 2.0 at the moment. the extrude normal is\\n// stored in a byte (-128..127). we scale regular normals up to length 63, but\\n// there are also \\\"special\\\" normals that have a bigger length (of up to 126 in\\n// this case).\\n// #define scale 63.0\\n#define scale 0.015873016\\n\\n// We scale the distance before adding it to the buffers so that we can store\\n// long distances for long segments. Use this value to unscale the distance.\\n#define LINE_DISTANCE_SCALE 2.0\\n\\nattribute vec2 a_pos;\\nattribute vec4 a_data;\\n\\nuniform mat4 u_matrix;\\nuniform mediump float u_ratio;\\nuniform mediump float u_linewidth;\\nuniform mediump float u_gapwidth;\\nuniform mediump float u_antialiasing;\\nuniform mediump float u_extra;\\nuniform mat2 u_antialiasingmatrix;\\nuniform mediump float u_offset;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_linewidth;\\nvarying float v_linesofar;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    vec2 a_extrude = a_data.xy - 128.0;\\n    float a_direction = mod(a_data.z, 4.0) - 1.0;\\n    float a_linesofar = (floor(a_data.z / 4.0) + a_data.w * 64.0) * LINE_DISTANCE_SCALE;\\n\\n    // We store the texture normals in the most insignificant bit\\n    // transform y so that 0 => -1 and 1 => 1\\n    // In the texture normal, x is 0 if the normal points straight up/down and 1 if it's a round cap\\n    // y is 1 if the normal points up, and -1 if it points down\\n    mediump vec2 normal = mod(a_pos, 2.0);\\n    normal.y = sign(normal.y - 0.5);\\n    v_normal = normal;\\n\\n    float inset = u_gapwidth + (u_gapwidth > 0.0 ? u_antialiasing : 0.0);\\n    float outset = u_gapwidth + u_linewidth * (u_gapwidth > 0.0 ? 2.0 : 1.0) + u_antialiasing;\\n\\n    // Scale the extrusion vector down to a normal and then up by the line width\\n    // of this vertex.\\n    mediump vec2 dist = outset * a_extrude * scale;\\n\\n    // Calculate the offset when drawing a line that is to the side of the actual line.\\n    // We do this by creating a vector that points towards the extrude, but rotate\\n    // it when we're drawing round end points (a_direction = -1 or 1) since their\\n    // extrude vector points in another direction.\\n    mediump float u = 0.5 * a_direction;\\n    mediump float t = 1.0 - abs(u);\\n    mediump vec2 offset = u_offset * a_extrude * scale * normal.y * mat2(t, -u, u, t);\\n\\n    // Remove the texture normal bit of the position before scaling it with the\\n    // model/view matrix.\\n    gl_Position = u_matrix * vec4(floor(a_pos * 0.5) + (offset + dist) / u_ratio, 0.0, 1.0);\\n    v_linesofar = a_linesofar;\\n\\n    // position of y on the screen\\n    float y = gl_Position.y / gl_Position.w;\\n\\n    // how much features are squished in the y direction by the tilt\\n    float squish_scale = length(a_extrude) / length(u_antialiasingmatrix * a_extrude);\\n\\n    // how much features are squished in all directions by the perspectiveness\\n    float perspective_scale = 1.0 / (1.0 - min(y * u_extra, 0.9));\\n\\n    v_linewidth = vec2(outset, inset);\\n    v_gamma_scale = perspective_scale * squish_scale;\\n}\\n\"},linesdfpattern:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform lowp vec4 u_color;\\nuniform lowp float u_opacity;\\n\\nuniform float u_blur;\\nuniform sampler2D u_image;\\nuniform float u_sdfgamma;\\nuniform float u_mix;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_linewidth;\\nvarying vec2 v_tex_a;\\nvarying vec2 v_tex_b;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    // Calculate the distance of the pixel from the line in pixels.\\n    float dist = length(v_normal) * v_linewidth.s;\\n\\n    // Calculate the antialiasing fade factor. This is either when fading in\\n    // the line in case of an offset line (v_linewidth.t) or when fading out\\n    // (v_linewidth.s)\\n    float blur = u_blur * v_gamma_scale;\\n    float alpha = clamp(min(dist - (v_linewidth.t - blur), v_linewidth.s - dist) / blur, 0.0, 1.0);\\n\\n    float sdfdist_a = texture2D(u_image, v_tex_a).a;\\n    float sdfdist_b = texture2D(u_image, v_tex_b).a;\\n    float sdfdist = mix(sdfdist_a, sdfdist_b, u_mix);\\n    alpha *= smoothstep(0.5 - u_sdfgamma, 0.5 + u_sdfgamma, sdfdist);\\n\\n    gl_FragColor = u_color * (alpha * u_opacity);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\n// floor(127 / 2) == 63.0\\n// the maximum allowed miter limit is 2.0 at the moment. the extrude normal is\\n// stored in a byte (-128..127). we scale regular normals up to length 63, but\\n// there are also \\\"special\\\" normals that have a bigger length (of up to 126 in\\n// this case).\\n// #define scale 63.0\\n#define scale 0.015873016\\n\\n// We scale the distance before adding it to the buffers so that we can store\\n// long distances for long segments. Use this value to unscale the distance.\\n#define LINE_DISTANCE_SCALE 2.0\\n\\nattribute vec2 a_pos;\\nattribute vec4 a_data;\\n\\nuniform mat4 u_matrix;\\nuniform mediump float u_ratio;\\nuniform mediump float u_linewidth;\\nuniform mediump float u_gapwidth;\\nuniform mediump float u_antialiasing;\\nuniform vec2 u_patternscale_a;\\nuniform float u_tex_y_a;\\nuniform vec2 u_patternscale_b;\\nuniform float u_tex_y_b;\\nuniform float u_extra;\\nuniform mat2 u_antialiasingmatrix;\\nuniform mediump float u_offset;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_linewidth;\\nvarying vec2 v_tex_a;\\nvarying vec2 v_tex_b;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    vec2 a_extrude = a_data.xy - 128.0;\\n    float a_direction = mod(a_data.z, 4.0) - 1.0;\\n    float a_linesofar = (floor(a_data.z / 4.0) + a_data.w * 64.0) * LINE_DISTANCE_SCALE;\\n\\n    // We store the texture normals in the most insignificant bit\\n    // transform y so that 0 => -1 and 1 => 1\\n    // In the texture normal, x is 0 if the normal points straight up/down and 1 if it's a round cap\\n    // y is 1 if the normal points up, and -1 if it points down\\n    mediump vec2 normal = mod(a_pos, 2.0);\\n    normal.y = sign(normal.y - 0.5);\\n    v_normal = normal;\\n\\n    float inset = u_gapwidth + (u_gapwidth > 0.0 ? u_antialiasing : 0.0);\\n    float outset = u_gapwidth + u_linewidth * (u_gapwidth > 0.0 ? 2.0 : 1.0) + u_antialiasing;\\n\\n    // Scale the extrusion vector down to a normal and then up by the line width\\n    // of this vertex.\\n    mediump vec2 dist = outset * a_extrude * scale;\\n\\n    // Calculate the offset when drawing a line that is to the side of the actual line.\\n    // We do this by creating a vector that points towards the extrude, but rotate\\n    // it when we're drawing round end points (a_direction = -1 or 1) since their\\n    // extrude vector points in another direction.\\n    mediump float u = 0.5 * a_direction;\\n    mediump float t = 1.0 - abs(u);\\n    mediump vec2 offset = u_offset * a_extrude * scale * normal.y * mat2(t, -u, u, t);\\n\\n    // Remove the texture normal bit of the position before scaling it with the\\n    // model/view matrix.\\n    gl_Position = u_matrix * vec4(floor(a_pos * 0.5) + (offset + dist) / u_ratio, 0.0, 1.0);\\n\\n    v_tex_a = vec2(a_linesofar * u_patternscale_a.x, normal.y * u_patternscale_a.y + u_tex_y_a);\\n    v_tex_b = vec2(a_linesofar * u_patternscale_b.x, normal.y * u_patternscale_b.y + u_tex_y_b);\\n\\n    // position of y on the screen\\n    float y = gl_Position.y / gl_Position.w;\\n\\n    // how much features are squished in the y direction by the tilt\\n    float squish_scale = length(a_extrude) / length(u_antialiasingmatrix * a_extrude);\\n\\n    // how much features are squished in all directions by the perspectiveness\\n    float perspective_scale = 1.0 / (1.0 - min(y * u_extra, 0.9));\\n\\n    v_linewidth = vec2(outset, inset);\\n    v_gamma_scale = perspective_scale * squish_scale;\\n}\\n\"},outline:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\n#pragma mapbox: define lowp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\n\\nvarying vec2 v_pos;\\n\\nvoid main() {\\n    #pragma mapbox: initialize lowp vec4 outline_color\\n    #pragma mapbox: initialize lowp float opacity\\n\\n    float dist = length(v_pos - gl_FragCoord.xy);\\n    float alpha = smoothstep(1.0, 0.0, dist);\\n    gl_FragColor = outline_color * (alpha * opacity);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nattribute vec2 a_pos;\\n\\nuniform mat4 u_matrix;\\nuniform vec2 u_world;\\n\\nvarying vec2 v_pos;\\n\\n#pragma mapbox: define lowp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\n\\nvoid main() {\\n    #pragma mapbox: initialize lowp vec4 outline_color\\n    #pragma mapbox: initialize lowp float opacity\\n\\n    gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n    v_pos = (gl_Position.xy / gl_Position.w + 1.0) / 2.0 * u_world;\\n}\\n\"},outlinepattern:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform float u_opacity;\\nuniform vec2 u_pattern_tl_a;\\nuniform vec2 u_pattern_br_a;\\nuniform vec2 u_pattern_tl_b;\\nuniform vec2 u_pattern_br_b;\\nuniform float u_mix;\\n\\nuniform sampler2D u_image;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\nvarying vec2 v_pos;\\n\\nvoid main() {\\n    vec2 imagecoord = mod(v_pos_a, 1.0);\\n    vec2 pos = mix(u_pattern_tl_a, u_pattern_br_a, imagecoord);\\n    vec4 color1 = texture2D(u_image, pos);\\n\\n    vec2 imagecoord_b = mod(v_pos_b, 1.0);\\n    vec2 pos2 = mix(u_pattern_tl_b, u_pattern_br_b, imagecoord_b);\\n    vec4 color2 = texture2D(u_image, pos2);\\n\\n    // find distance to outline for alpha interpolation\\n\\n    float dist = length(v_pos - gl_FragCoord.xy);\\n    float alpha = smoothstep(1.0, 0.0, dist);\\n    \\n\\n    gl_FragColor = mix(color1, color2, u_mix) * alpha * u_opacity;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform vec2 u_pattern_size_a;\\nuniform vec2 u_pattern_size_b;\\nuniform vec2 u_pixel_coord_upper;\\nuniform vec2 u_pixel_coord_lower;\\nuniform float u_scale_a;\\nuniform float u_scale_b;\\nuniform float u_tile_units_to_pixels;\\n\\nattribute vec2 a_pos;\\n\\nuniform mat4 u_matrix;\\nuniform vec2 u_world;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\nvarying vec2 v_pos;\\n\\nvoid main() {\\n    gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n    vec2 scaled_size_a = u_scale_a * u_pattern_size_a;\\n    vec2 scaled_size_b = u_scale_b * u_pattern_size_b;\\n\\n    // the correct offset needs to be calculated.\\n    //\\n    // The offset depends on how many pixels are between the world origin and\\n    // the edge of the tile:\\n    // vec2 offset = mod(pixel_coord, size)\\n    //\\n    // At high zoom levels there are a ton of pixels between the world origin\\n    // and the edge of the tile. The glsl spec only guarantees 16 bits of\\n    // precision for highp floats. We need more than that.\\n    //\\n    // The pixel_coord is passed in as two 16 bit values:\\n    // pixel_coord_upper = floor(pixel_coord / 2^16)\\n    // pixel_coord_lower = mod(pixel_coord, 2^16)\\n    //\\n    // The offset is calculated in a series of steps that should preserve this precision:\\n    vec2 offset_a = mod(mod(mod(u_pixel_coord_upper, scaled_size_a) * 256.0, scaled_size_a) * 256.0 + u_pixel_coord_lower, scaled_size_a);\\n    vec2 offset_b = mod(mod(mod(u_pixel_coord_upper, scaled_size_b) * 256.0, scaled_size_b) * 256.0 + u_pixel_coord_lower, scaled_size_b);\\n\\n    v_pos_a = (u_tile_units_to_pixels * a_pos + offset_a) / scaled_size_a;\\n    v_pos_b = (u_tile_units_to_pixels * a_pos + offset_b) / scaled_size_b;\\n\\n    v_pos = (gl_Position.xy / gl_Position.w + 1.0) / 2.0 * u_world;\\n}\\n\"},pattern:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform float u_opacity;\\nuniform vec2 u_pattern_tl_a;\\nuniform vec2 u_pattern_br_a;\\nuniform vec2 u_pattern_tl_b;\\nuniform vec2 u_pattern_br_b;\\nuniform float u_mix;\\n\\nuniform sampler2D u_image;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\n\\nvoid main() {\\n\\n    vec2 imagecoord = mod(v_pos_a, 1.0);\\n    vec2 pos = mix(u_pattern_tl_a, u_pattern_br_a, imagecoord);\\n    vec4 color1 = texture2D(u_image, pos);\\n\\n    vec2 imagecoord_b = mod(v_pos_b, 1.0);\\n    vec2 pos2 = mix(u_pattern_tl_b, u_pattern_br_b, imagecoord_b);\\n    vec4 color2 = texture2D(u_image, pos2);\\n\\n    gl_FragColor = mix(color1, color2, u_mix) * u_opacity;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform mat4 u_matrix;\\nuniform vec2 u_pattern_size_a;\\nuniform vec2 u_pattern_size_b;\\nuniform vec2 u_pixel_coord_upper;\\nuniform vec2 u_pixel_coord_lower;\\nuniform float u_scale_a;\\nuniform float u_scale_b;\\nuniform float u_tile_units_to_pixels;\\n\\nattribute vec2 a_pos;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\n\\nvoid main() {\\n    gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n    vec2 scaled_size_a = u_scale_a * u_pattern_size_a;\\n    vec2 scaled_size_b = u_scale_b * u_pattern_size_b;\\n\\n    // the correct offset needs to be calculated.\\n    //\\n    // The offset depends on how many pixels are between the world origin and\\n    // the edge of the tile:\\n    // vec2 offset = mod(pixel_coord, size)\\n    //\\n    // At high zoom levels there are a ton of pixels between the world origin\\n    // and the edge of the tile. The glsl spec only guarantees 16 bits of\\n    // precision for highp floats. We need more than that.\\n    //\\n    // The pixel_coord is passed in as two 16 bit values:\\n    // pixel_coord_upper = floor(pixel_coord / 2^16)\\n    // pixel_coord_lower = mod(pixel_coord, 2^16)\\n    //\\n    // The offset is calculated in a series of steps that should preserve this precision:\\n    vec2 offset_a = mod(mod(mod(u_pixel_coord_upper, scaled_size_a) * 256.0, scaled_size_a) * 256.0 + u_pixel_coord_lower, scaled_size_a);\\n    vec2 offset_b = mod(mod(mod(u_pixel_coord_upper, scaled_size_b) * 256.0, scaled_size_b) * 256.0 + u_pixel_coord_lower, scaled_size_b);\\n\\n    v_pos_a = (u_tile_units_to_pixels * a_pos + offset_a) / scaled_size_a;\\n    v_pos_b = (u_tile_units_to_pixels * a_pos + offset_b) / scaled_size_b;\\n}\\n\"},raster:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform float u_opacity0;\\nuniform float u_opacity1;\\nuniform sampler2D u_image0;\\nuniform sampler2D u_image1;\\nvarying vec2 v_pos0;\\nvarying vec2 v_pos1;\\n\\nuniform float u_brightness_low;\\nuniform float u_brightness_high;\\n\\nuniform float u_saturation_factor;\\nuniform float u_contrast_factor;\\nuniform vec3 u_spin_weights;\\n\\nvoid main() {\\n\\n    // read and cross-fade colors from the main and parent tiles\\n    vec4 color0 = texture2D(u_image0, v_pos0);\\n    vec4 color1 = texture2D(u_image1, v_pos1);\\n    vec4 color = color0 * u_opacity0 + color1 * u_opacity1;\\n    vec3 rgb = color.rgb;\\n\\n    // spin\\n    rgb = vec3(\\n        dot(rgb, u_spin_weights.xyz),\\n        dot(rgb, u_spin_weights.zxy),\\n        dot(rgb, u_spin_weights.yzx));\\n\\n    // saturation\\n    float average = (color.r + color.g + color.b) / 3.0;\\n    rgb += (average - rgb) * u_saturation_factor;\\n\\n    // contrast\\n    rgb = (rgb - 0.5) * u_contrast_factor + 0.5;\\n\\n    // brightness\\n    vec3 u_high_vec = vec3(u_brightness_low, u_brightness_low, u_brightness_low);\\n    vec3 u_low_vec = vec3(u_brightness_high, u_brightness_high, u_brightness_high);\\n\\n    gl_FragColor = vec4(mix(u_high_vec, u_low_vec, rgb), color.a);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform mat4 u_matrix;\\nuniform vec2 u_tl_parent;\\nuniform float u_scale_parent;\\nuniform float u_buffer_scale;\\n\\nattribute vec2 a_pos;\\nattribute vec2 a_texture_pos;\\n\\nvarying vec2 v_pos0;\\nvarying vec2 v_pos1;\\n\\nvoid main() {\\n    gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n    v_pos0 = (((a_texture_pos / 32767.0) - 0.5) / u_buffer_scale ) + 0.5;\\n    v_pos1 = (v_pos0 * u_scale_parent) + u_tl_parent;\\n}\\n\"},icon:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform sampler2D u_texture;\\nuniform sampler2D u_fadetexture;\\nuniform lowp float u_opacity;\\n\\nvarying vec2 v_tex;\\nvarying vec2 v_fade_tex;\\n\\nvoid main() {\\n    lowp float alpha = texture2D(u_fadetexture, v_fade_tex).a * u_opacity;\\n    gl_FragColor = texture2D(u_texture, v_tex) * alpha;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nattribute vec2 a_pos;\\nattribute vec2 a_offset;\\nattribute vec2 a_texture_pos;\\nattribute vec4 a_data;\\n\\n\\n// matrix is for the vertex position.\\nuniform mat4 u_matrix;\\n\\nuniform mediump float u_zoom;\\nuniform bool u_rotate_with_map;\\nuniform vec2 u_extrude_scale;\\n\\nuniform vec2 u_texsize;\\n\\nvarying vec2 v_tex;\\nvarying vec2 v_fade_tex;\\n\\nvoid main() {\\n    vec2 a_tex = a_texture_pos.xy;\\n    mediump float a_labelminzoom = a_data[0];\\n    mediump vec2 a_zoom = a_data.pq;\\n    mediump float a_minzoom = a_zoom[0];\\n    mediump float a_maxzoom = a_zoom[1];\\n\\n    // u_zoom is the current zoom level adjusted for the change in font size\\n    mediump float z = 2.0 - step(a_minzoom, u_zoom) - (1.0 - step(a_maxzoom, u_zoom));\\n\\n    vec2 extrude = u_extrude_scale * (a_offset / 64.0);\\n    if (u_rotate_with_map) {\\n        gl_Position = u_matrix * vec4(a_pos + extrude, 0, 1);\\n        gl_Position.z += z * gl_Position.w;\\n    } else {\\n        gl_Position = u_matrix * vec4(a_pos, 0, 1) + vec4(extrude, 0, 0);\\n    }\\n\\n    v_tex = a_tex / u_texsize;\\n    v_fade_tex = vec2(a_labelminzoom / 255.0, 0.0);\\n}\\n\"},sdf:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform sampler2D u_texture;\\nuniform sampler2D u_fadetexture;\\nuniform lowp vec4 u_color;\\nuniform lowp float u_opacity;\\nuniform lowp float u_buffer;\\nuniform lowp float u_gamma;\\n\\nvarying vec2 v_tex;\\nvarying vec2 v_fade_tex;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    lowp float dist = texture2D(u_texture, v_tex).a;\\n    lowp float fade_alpha = texture2D(u_fadetexture, v_fade_tex).a;\\n    lowp float gamma = u_gamma * v_gamma_scale;\\n    lowp float alpha = smoothstep(u_buffer - gamma, u_buffer + gamma, dist) * fade_alpha;\\n\\n    gl_FragColor = u_color * (alpha * u_opacity);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nconst float PI = 3.141592653589793;\\n\\nattribute vec2 a_pos;\\nattribute vec2 a_offset;\\nattribute vec2 a_texture_pos;\\nattribute vec4 a_data;\\n\\n\\n// matrix is for the vertex position.\\nuniform mat4 u_matrix;\\n\\nuniform mediump float u_zoom;\\nuniform bool u_rotate_with_map;\\nuniform bool u_pitch_with_map;\\nuniform mediump float u_pitch;\\nuniform mediump float u_bearing;\\nuniform mediump float u_aspect_ratio;\\nuniform vec2 u_extrude_scale;\\n\\nuniform vec2 u_texsize;\\n\\nvarying vec2 v_tex;\\nvarying vec2 v_fade_tex;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    vec2 a_tex = a_texture_pos.xy;\\n    mediump float a_labelminzoom = a_data[0];\\n    mediump vec2 a_zoom = a_data.pq;\\n    mediump float a_minzoom = a_zoom[0];\\n    mediump float a_maxzoom = a_zoom[1];\\n\\n    // u_zoom is the current zoom level adjusted for the change in font size\\n    mediump float z = 2.0 - step(a_minzoom, u_zoom) - (1.0 - step(a_maxzoom, u_zoom));\\n\\n    // pitch-alignment: map\\n    // rotation-alignment: map | viewport\\n    if (u_pitch_with_map) {\\n        lowp float angle = u_rotate_with_map ? (a_data[1] / 256.0 * 2.0 * PI) : u_bearing;\\n        lowp float asin = sin(angle);\\n        lowp float acos = cos(angle);\\n        mat2 RotationMatrix = mat2(acos, asin, -1.0 * asin, acos);\\n        vec2 offset = RotationMatrix * a_offset;\\n        vec2 extrude = u_extrude_scale * (offset / 64.0);\\n        gl_Position = u_matrix * vec4(a_pos + extrude, 0, 1);\\n        gl_Position.z += z * gl_Position.w;\\n    // pitch-alignment: viewport\\n    // rotation-alignment: map\\n    } else if (u_rotate_with_map) {\\n        // foreshortening factor to apply on pitched maps\\n        // as a label goes from horizontal <=> vertical in angle\\n        // it goes from 0% foreshortening to up to around 70% foreshortening\\n        lowp float pitchfactor = 1.0 - cos(u_pitch * sin(u_pitch * 0.75));\\n\\n        lowp float lineangle = a_data[1] / 256.0 * 2.0 * PI;\\n\\n        // use the lineangle to position points a,b along the line\\n        // project the points and calculate the label angle in projected space\\n        // this calculation allows labels to be rendered unskewed on pitched maps\\n        vec4 a = u_matrix * vec4(a_pos, 0, 1);\\n        vec4 b = u_matrix * vec4(a_pos + vec2(cos(lineangle),sin(lineangle)), 0, 1);\\n        lowp float angle = atan((b[1]/b[3] - a[1]/a[3])/u_aspect_ratio, b[0]/b[3] - a[0]/a[3]);\\n        lowp float asin = sin(angle);\\n        lowp float acos = cos(angle);\\n        mat2 RotationMatrix = mat2(acos, -1.0 * asin, asin, acos);\\n\\n        vec2 offset = RotationMatrix * (vec2((1.0-pitchfactor)+(pitchfactor*cos(angle*2.0)), 1.0) * a_offset);\\n        vec2 extrude = u_extrude_scale * (offset / 64.0);\\n        gl_Position = u_matrix * vec4(a_pos, 0, 1) + vec4(extrude, 0, 0);\\n        gl_Position.z += z * gl_Position.w;\\n    // pitch-alignment: viewport\\n    // rotation-alignment: viewport\\n    } else {\\n        vec2 extrude = u_extrude_scale * (a_offset / 64.0);\\n        gl_Position = u_matrix * vec4(a_pos, 0, 1) + vec4(extrude, 0, 0);\\n    }\\n\\n    v_gamma_scale = (gl_Position.w - 0.5);\\n\\n    v_tex = a_tex / u_texsize;\\n    v_fade_tex = vec2(a_labelminzoom / 255.0, 0.0);\\n}\\n\"},collisionbox:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform float u_zoom;\\nuniform float u_maxzoom;\\n\\nvarying float v_max_zoom;\\nvarying float v_placement_zoom;\\n\\nvoid main() {\\n\\n    float alpha = 0.5;\\n\\n    gl_FragColor = vec4(0.0, 1.0, 0.0, 1.0) * alpha;\\n\\n    if (v_placement_zoom > u_zoom) {\\n        gl_FragColor = vec4(1.0, 0.0, 0.0, 1.0) * alpha;\\n    }\\n\\n    if (u_zoom >= v_max_zoom) {\\n        gl_FragColor = vec4(0.0, 0.0, 0.0, 1.0) * alpha * 0.25;\\n    }\\n\\n    if (v_placement_zoom >= u_maxzoom) {\\n        gl_FragColor = vec4(0.0, 0.0, 1.0, 1.0) * alpha * 0.2;\\n    }\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nattribute vec2 a_pos;\\nattribute vec2 a_extrude;\\nattribute vec2 a_data;\\n\\nuniform mat4 u_matrix;\\nuniform float u_scale;\\n\\nvarying float v_max_zoom;\\nvarying float v_placement_zoom;\\n\\nvoid main() {\\n    gl_Position = u_matrix * vec4(a_pos + a_extrude / u_scale, 0.0, 1.0);\\n\\n    v_max_zoom = a_data.x;\\n    v_placement_zoom = a_data.y;\\n}\\n\"}},e.exports.util=\"float evaluate_zoom_function_1(const vec4 values, const float t) {\\n    if (t < 1.0) {\\n        return mix(values[0], values[1], t);\\n    } else if (t < 2.0) {\\n        return mix(values[1], values[2], t - 1.0);\\n    } else {\\n        return mix(values[2], values[3], t - 2.0);\\n    }\\n}\\nvec4 evaluate_zoom_function_4(const vec4 value0, const vec4 value1, const vec4 value2, const vec4 value3, const float t) {\\n    if (t < 1.0) {\\n        return mix(value0, value1, t);\\n    } else if (t < 2.0) {\\n        return mix(value1, value2, t - 1.0);\\n    } else {\\n        return 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\"+b+\")\",\"/\",u.multiplier.toFixed(1)].join(\" \")+\";\\n\";else{for(var T=[],S=0;S<4;S++)T.push(m+S),p.attributes.push(c.extend({},u,{getValue:a(u,[M[S]]),isFunction:!0,name:m+S})),p.vertexPragmas.define[v]+=[\"attribute\",\"{precision}\",\"{type}\",m+S].join(\" \")+\";\\n\";p.vertexPragmas.initialize[v]=[v,\" = \",\"evaluate_zoom_function_4(\"+T.join(\", \")+\", \"+b+\")\",\"/\",u.multiplier.toFixed(1)].join(\" \")+\";\\n\"}}}}}return e}function a(t,e){return function(r,n,i){if(1===e.length)return t.getValue(r,c.extend({},n,{zoom:e[0]}),i);for(var a=[],o=0;o<e.length;o++){var s=e[o];a.push(t.getValue(r,c.extend({},n,{zoom:s}),i)[0])}return a}}function o(t,e){return function(r,n){var i=r.getPaintInterpolationT(t.paintProperty,n.zoom);return[Math.max(0,Math.min(4,i-e))]}}var s=t(\"feature-filter\"),l=t(\"./array_group\"),u=t(\"./buffer_group\"),c=t(\"../util/util\"),h=t(\"../util/struct_array\"),f=t(\"assert\");e.exports=n,n.create=function(e){return new({fill:t(\"./bucket/fill_bucket\"),line:t(\"./bucket/line_bucket\"),circle:t(\"./bucket/circle_bucket\"),symbol:t(\"./bucket/symbol_bucket\")}[e.layer.type])(e)},n.EXTENT=8192,n.prototype.populateArrays=function(){this.createArrays(),this.recalculateStyleLayers();for(var t=0;t<this.features.length;t++)this.addFeature(this.features[t]);this.trimArrays()},n.prototype.prepareArrayGroup=function(t,e){var r=this.arrayGroups[t],n=r.length&&r[r.length-1];return n&&n.hasCapacityFor(e)||((n=new l({layoutVertexArrayType:this.programInterfaces[t].layoutVertexArrayType,elementArrayType:this.programInterfaces[t].elementArrayType,elementArrayType2:this.programInterfaces[t].elementArrayType2,paintVertexArrayTypes:this.paintVertexArrayTypes[t]})).index=r.length,r.push(n)),n},n.prototype.createArrays=function(){this.arrayGroups={},this.paintVertexArrayTypes={};for(var t in this.programInterfaces){this.arrayGroups[t]=[];var e=this.paintVertexArrayTypes[t]={},r=this.paintAttributes[t];for(var i in r)e[i]=new n.VertexArrayType(r[i].attributes)}},n.prototype.destroy=function(t){for(var e in this.bufferGroups)for(var r=this.bufferGroups[e],n=0;n<r.length;n++)r[n].destroy(t)},n.prototype.trimArrays=function(){for(var t in this.arrayGroups)for(var e=this.arrayGroups[t],r=0;r<e.length;r++)e[r].trim()},n.prototype.isEmpty=function(){for(var t in this.arrayGroups)for(var e=this.arrayGroups[t],r=0;r<e.length;r++)if(!e[r].isEmpty())return!1;return!0},n.prototype.getTransferables=function(t){for(var e in this.arrayGroups)for(var r=this.arrayGroups[e],n=0;n<r.length;n++)r[n].getTransferables(t)},n.prototype.setUniforms=function(t,e,r,n,i){for(var a=this.paintAttributes[e][n.id].uniforms,o=0;o<a.length;o++){var s=a[o],l=r[s.name];t[\"uniform\"+s.components+\"fv\"](l,s.getValue(n,i))}},n.prototype.serialize=function(){return{layerId:this.layer.id,zoom:this.zoom,arrays:c.mapObject(this.arrayGroups,function(t){return t.map(function(t){return t.serialize()})}),paintVertexArrayTypes:c.mapObject(this.paintVertexArrayTypes,function(t){return c.mapObject(t,function(t){return t.serialize()})}),childLayerIds:this.childLayers.map(function(t){return t.id})}},n.prototype.createFilter=function(){this.filter||(this.filter=s(this.layer.filter))};var d={lastIntegerZoom:1/0,lastIntegerZoomTime:0,lastZoom:0};n.prototype.recalculateStyleLayers=function(){for(var t=0;t<this.childLayers.length;t++)this.childLayers[t].recalculate(this.zoom,d)},n.prototype.populatePaintArrays=function(t,e,r,n,i){for(var a=0;a<this.childLayers.length;a++)for(var o=this.childLayers[a],s=this.arrayGroups[t],l=n.index;l<s.length;l++){var u=s[l],c=u.layoutVertexArray.length,h=u.paintVertexArrays[o.id];h.resize(c);for(var f=this.paintAttributes[t][o.id].attributes,d=0;d<f.length;d++)for(var p=f[d],m=p.getValue(o,e,r),g=p.multiplier||1,v=p.components||1,y=l===n.index?i:0;y<c;y++)for(var b=h.get(y),x=0;x<v;x++)b[v>1?p.name+x:p.name]=m[x]*g}},n.VertexArrayType=function(t){return new h({members:t,alignment:4})},n.ElementArrayType=function(t){return new h({members:[{type:\"Uint16\",name:\"vertices\",components:t||3}]})}},{\"../util/struct_array\":422,\"../util/util\":424,\"./array_group\":310,\"./bucket/circle_bucket\":312,\"./bucket/fill_bucket\":313,\"./bucket/line_bucket\":314,\"./bucket/symbol_bucket\":315,\"./buffer_group\":317,assert:40,\"feature-filter\":117}],312:[function(t,e,r){\"use strict\";function n(){i.apply(this,arguments)}var i=t(\"../bucket\"),a=t(\"../../util/util\"),o=t(\"../load_geometry\"),s=i.EXTENT;e.exports=n,n.prototype=a.inherit(i,{}),n.prototype.addCircleVertex=function(t,e,r,n,i){return t.emplaceBack(2*e+(n+1)/2,2*r+(i+1)/2)},n.prototype.programInterfaces={circle:{layoutVertexArrayType:new i.VertexArrayType([{name:\"a_pos\",components:2,type:\"Int16\"}]),elementArrayType:new i.ElementArrayType,paintAttributes:[{name:\"a_color\",components:4,type:\"Uint8\",getValue:function(t,e,r){return t.getPaintValue(\"circle-color\",e,r)},multiplier:255,paintProperty:\"circle-color\"},{name:\"a_radius\",components:1,type:\"Uint16\",isLayerConstant:!1,getValue:function(t,e,r){return[t.getPaintValue(\"circle-radius\",e,r)]},multiplier:10,paintProperty:\"circle-radius\"},{name:\"a_blur\",components:1,type:\"Uint16\",isLayerConstant:!1,getValue:function(t,e,r){return[t.getPaintValue(\"circle-blur\",e,r)]},multiplier:10,paintProperty:\"circle-blur\"},{name:\"a_opacity\",components:1,type:\"Uint16\",isLayerConstant:!1,getValue:function(t,e,r){return[t.getPaintValue(\"circle-opacity\",e,r)]},multiplier:255,paintProperty:\"circle-opacity\"}]}},n.prototype.addFeature=function(t){for(var e={zoom:this.zoom},r=o(t),n=this.prepareArrayGroup(\"circle\",0),i=n.layoutVertexArray.length,a=0;a<r.length;a++)for(var l=0;l<r[a].length;l++){var u=r[a][l].x,c=r[a][l].y;if(!(u<0||u>=s||c<0||c>=s)){var h=this.prepareArrayGroup(\"circle\",4),f=h.layoutVertexArray,d=this.addCircleVertex(f,u,c,-1,-1);this.addCircleVertex(f,u,c,1,-1),this.addCircleVertex(f,u,c,1,1),this.addCircleVertex(f,u,c,-1,1),h.elementArray.emplaceBack(d,d+1,d+2),h.elementArray.emplaceBack(d,d+3,d+2)}}this.populatePaintArrays(\"circle\",e,t.properties,n,i)}},{\"../../util/util\":424,\"../bucket\":311,\"../load_geometry\":319}],313:[function(t,e,r){\"use strict\";function n(){i.apply(this,arguments)}var i=t(\"../bucket\"),a=t(\"../../util/util\"),o=t(\"../load_geometry\"),s=t(\"earcut\"),l=t(\"../../util/classify_rings\");e.exports=n,n.prototype=a.inherit(i,{}),n.prototype.programInterfaces={fill:{layoutVertexArrayType:new i.VertexArrayType([{name:\"a_pos\",components:2,type:\"Int16\"}]),elementArrayType:new i.ElementArrayType(1),elementArrayType2:new i.ElementArrayType(2),paintAttributes:[{name:\"a_color\",components:4,type:\"Uint8\",getValue:function(t,e,r){return t.getPaintValue(\"fill-color\",e,r)},multiplier:255,paintProperty:\"fill-color\"},{name:\"a_outline_color\",components:4,type:\"Uint8\",getValue:function(t,e,r){return t.getPaintValue(\"fill-outline-color\",e,r)},multiplier:255,paintProperty:\"fill-outline-color\"},{name:\"a_opacity\",components:1,type:\"Uint8\",getValue:function(t,e,r){return[t.getPaintValue(\"fill-opacity\",e,r)]},multiplier:255,paintProperty:\"fill-opacity\"}]}},n.prototype.addFeature=function(t){for(var e=o(t),r=l(e,500),n=this.prepareArrayGroup(\"fill\",0),i=n.layoutVertexArray.length,a=0;a<r.length;a++)this.addPolygon(r[a]);this.populatePaintArrays(\"fill\",{zoom:this.zoom},t.properties,n,i)},n.prototype.addPolygon=function(t){for(var e=0,r=0;r<t.length;r++)e+=t[r].length;for(var n=this.prepareArrayGroup(\"fill\",e),i=[],a=[],o=n.layoutVertexArray.length,l=0;l<t.length;l++){var u=t[l];l>0&&a.push(i.length/2);for(var c=0;c<u.length;c++){var h=u[c],f=n.layoutVertexArray.emplaceBack(h.x,h.y);c>=1&&n.elementArray2.emplaceBack(f-1,f),i.push(h.x),i.push(h.y)}}for(var d=s(i,a),p=0;p<d.length;p++)n.elementArray.emplaceBack(d[p]+o)}},{\"../../util/classify_rings\":412,\"../../util/util\":424,\"../bucket\":311,\"../load_geometry\":319,earcut:111}],314:[function(t,e,r){\"use strict\";function n(){i.apply(this,arguments)}var i=t(\"../bucket\"),a=t(\"../../util/util\"),o=t(\"../load_geometry\"),s=i.EXTENT,l=Math.cos(Math.PI/180*37.5),u=Math.pow(2,14)/.5;e.exports=n,n.prototype=a.inherit(i,{}),n.prototype.addLineVertex=function(t,e,r,n,i,a,o){return t.emplaceBack(e.x<<1|n,e.y<<1|i,Math.round(63*r.x)+128,Math.round(63*r.y)+128,1+(0===a?0:a<0?-1:1)|(.5*o&63)<<2,.5*o>>6)},n.prototype.programInterfaces={line:{layoutVertexArrayType:new i.VertexArrayType([{name:\"a_pos\",components:2,type:\"Int16\"},{name:\"a_data\",components:4,type:\"Uint8\"}]),elementArrayType:new i.ElementArrayType}},n.prototype.addFeature=function(t){for(var e=o(t,15),r=0;r<e.length;r++)this.addLine(e[r],this.layer.layout[\"line-join\"],this.layer.layout[\"line-cap\"],this.layer.layout[\"line-miter-limit\"],this.layer.layout[\"line-round-limit\"])},n.prototype.addLine=function(t,e,r,n,i){for(var a=t.length;a>2&&t[a-1].equals(t[a-2]);)a--;if(!(t.length<2)){\"bevel\"===e&&(n=1.05);var o=s/(512*this.overscaling)*15,u=t[0],c=t[a-1],h=u.equals(c);if(this.prepareArrayGroup(\"line\",10*a),2!==a||!h){this.distance=0;var f,d,p,m,g,v,y,b=r,x=h?\"butt\":r,_=!0;this.e1=this.e2=this.e3=-1,h&&(f=t[a-2],g=u.sub(f)._unit()._perp());for(var w=0;w<a;w++)if(!(p=h&&w===a-1?t[1]:t[w+1])||!t[w].equals(p)){g&&(m=g),f&&(d=f),f=t[w],g=p?p.sub(f)._unit()._perp():m;var M=(m=m||g).add(g)._unit(),k=M.x*g.x+M.y*g.y,A=1/k,T=k<l&&d&&p;if(T&&w>0){var S=f.dist(d);if(S>2*o){var E=f.sub(f.sub(d)._mult(o/S)._round());this.distance+=E.dist(d),this.addCurrentVertex(E,this.distance,m.mult(1),0,0,!1),d=E}}var L=d&&p,C=L?e:p?b:x;if(L&&\"round\"===C&&(A<i?C=\"miter\":A<=2&&(C=\"fakeround\")),\"miter\"===C&&A>n&&(C=\"bevel\"),\"bevel\"===C&&(A>2&&(C=\"flipbevel\"),A<n&&(C=\"miter\")),d&&(this.distance+=f.dist(d)),\"miter\"===C)M._mult(A),this.addCurrentVertex(f,this.distance,M,0,0,!1);else if(\"flipbevel\"===C){if(A>100)M=g.clone();else{var z=m.x*g.y-m.y*g.x>0?-1:1,D=A*m.add(g).mag()/m.sub(g).mag();M._perp()._mult(D*z)}this.addCurrentVertex(f,this.distance,M,0,0,!1),this.addCurrentVertex(f,this.distance,M.mult(-1),0,0,!1)}else if(\"bevel\"===C||\"fakeround\"===C){var I=m.x*g.y-m.y*g.x>0,P=-Math.sqrt(A*A-1);if(I?(y=0,v=P):(v=0,y=P),_||this.addCurrentVertex(f,this.distance,m,v,y,!1),\"fakeround\"===C){for(var O,j=Math.floor(8*(.5-(k-.5))),R=0;R<j;R++)O=g.mult((R+1)/(j+1))._add(m)._unit(),this.addPieSliceVertex(f,this.distance,O,I);this.addPieSliceVertex(f,this.distance,M,I);for(var F=j-1;F>=0;F--)O=m.mult((F+1)/(j+1))._add(g)._unit(),this.addPieSliceVertex(f,this.distance,O,I)}p&&this.addCurrentVertex(f,this.distance,g,-v,-y,!1)}else\"butt\"===C?(_||this.addCurrentVertex(f,this.distance,m,0,0,!1),p&&this.addCurrentVertex(f,this.distance,g,0,0,!1)):\"square\"===C?(_||(this.addCurrentVertex(f,this.distance,m,1,1,!1),this.e1=this.e2=-1),p&&this.addCurrentVertex(f,this.distance,g,-1,-1,!1)):\"round\"===C&&(_||(this.addCurrentVertex(f,this.distance,m,0,0,!1),this.addCurrentVertex(f,this.distance,m,1,1,!0),this.e1=this.e2=-1),p&&(this.addCurrentVertex(f,this.distance,g,-1,-1,!0),this.addCurrentVertex(f,this.distance,g,0,0,!1)));if(T&&w<a-1){var N=f.dist(p);if(N>2*o){var B=f.add(p.sub(f)._mult(o/N)._round());this.distance+=B.dist(f),this.addCurrentVertex(B,this.distance,g.mult(1),0,0,!1),f=B}}_=!1}}}},n.prototype.addCurrentVertex=function(t,e,r,n,i,a){var o,s=a?1:0,l=this.arrayGroups.line[this.arrayGroups.line.length-1],c=l.layoutVertexArray,h=l.elementArray;o=r.clone(),n&&o._sub(r.perp()._mult(n)),this.e3=this.addLineVertex(c,t,o,s,0,n,e),this.e1>=0&&this.e2>=0&&h.emplaceBack(this.e1,this.e2,this.e3),this.e1=this.e2,this.e2=this.e3,o=r.mult(-1),i&&o._sub(r.perp()._mult(i)),this.e3=this.addLineVertex(c,t,o,s,1,-i,e),this.e1>=0&&this.e2>=0&&h.emplaceBack(this.e1,this.e2,this.e3),this.e1=this.e2,this.e2=this.e3,e>u/2&&(this.distance=0,this.addCurrentVertex(t,this.distance,r,n,i,a))},n.prototype.addPieSliceVertex=function(t,e,r,n){var i=n?1:0;r=r.mult(n?-1:1);var a=this.arrayGroups.line[this.arrayGroups.line.length-1],o=a.layoutVertexArray,s=a.elementArray;this.e3=this.addLineVertex(o,t,r,0,i,0,e),this.e1>=0&&this.e2>=0&&s.emplaceBack(this.e1,this.e2,this.e3),n?this.e2=this.e3:this.e1=this.e3}},{\"../../util/util\":424,\"../bucket\":311,\"../load_geometry\":319}],315:[function(t,e,r){\"use strict\";function n(t){o.apply(this,arguments),this.showCollisionBoxes=t.showCollisionBoxes,this.overscaling=t.overscaling,this.collisionBoxArray=t.collisionBoxArray,this.symbolQuadsArray=t.symbolQuadsArray,this.symbolInstancesArray=t.symbolInstancesArray,this.sdfIcons=t.sdfIcons,this.iconsNeedLinear=t.iconsNeedLinear,this.adjustedTextSize=t.adjustedTextSize,this.adjustedIconSize=t.adjustedIconSize,this.fontstack=t.fontstack}function i(t,e,r,n,i,a,o,s,l,u,c){return t.emplaceBack(e,r,Math.round(64*n),Math.round(64*i),a/4,o/4,10*(u||0),c,10*(s||0),10*Math.min(l||25,25))}var a=t(\"point-geometry\"),o=t(\"../bucket\"),s=t(\"../../symbol/anchor\"),l=t(\"../../symbol/get_anchors\"),u=t(\"../../util/token\"),c=t(\"../../symbol/quads\"),h=t(\"../../symbol/shaping\"),f=t(\"../../symbol/resolve_text\"),d=t(\"../../symbol/mergelines\"),p=t(\"../../symbol/clip_line\"),m=t(\"../../util/util\"),g=t(\"../load_geometry\"),v=t(\"../../symbol/collision_feature\"),y=h.shapeText,b=h.shapeIcon,x=c.getGlyphQuads,_=c.getIconQuads,w=o.EXTENT;e.exports=n,n.MAX_QUADS=65535,n.prototype=m.inherit(o,{}),n.prototype.serialize=function(){var t=o.prototype.serialize.apply(this);return t.sdfIcons=this.sdfIcons,t.iconsNeedLinear=this.iconsNeedLinear,t.adjustedTextSize=this.adjustedTextSize,t.adjustedIconSize=this.adjustedIconSize,t.fontstack=this.fontstack,t};var M=new o.VertexArrayType([{name:\"a_pos\",components:2,type:\"Int16\"},{name:\"a_offset\",components:2,type:\"Int16\"},{name:\"a_texture_pos\",components:2,type:\"Uint16\"},{name:\"a_data\",components:4,type:\"Uint8\"}]),k=new o.ElementArrayType;n.prototype.addCollisionBoxVertex=function(t,e,r,n,i){return t.emplaceBack(e.x,e.y,Math.round(r.x),Math.round(r.y),10*n,10*i)},n.prototype.programInterfaces={glyph:{layoutVertexArrayType:M,elementArrayType:k},icon:{layoutVertexArrayType:M,elementArrayType:k},collisionBox:{layoutVertexArrayType:new o.VertexArrayType([{name:\"a_pos\",components:2,type:\"Int16\"},{name:\"a_extrude\",components:2,type:\"Int16\"},{name:\"a_data\",components:2,type:\"Uint8\"}])}},n.prototype.populateArrays=function(t,e,r){var n={lastIntegerZoom:1/0,lastIntegerZoomTime:0,lastZoom:0};this.adjustedTextMaxSize=this.layer.getLayoutValue(\"text-size\",{zoom:18,zoomHistory:n}),this.adjustedTextSize=this.layer.getLayoutValue(\"text-size\",{zoom:this.zoom+1,zoomHistory:n}),this.adjustedIconMaxSize=this.layer.getLayoutValue(\"icon-size\",{zoom:18,zoomHistory:n}),this.adjustedIconSize=this.layer.getLayoutValue(\"icon-size\",{zoom:this.zoom+1,zoomHistory:n});var i=512*this.overscaling;this.tilePixelRatio=w/i,this.compareText={},this.iconsNeedLinear=!1,this.symbolInstancesStartIndex=this.symbolInstancesArray.length;var a=this.layer.layout,o=this.features,s=this.textFeatures,l=.5,c=.5;switch(a[\"text-anchor\"]){case\"right\":case\"top-right\":case\"bottom-right\":l=1;break;case\"left\":case\"top-left\":case\"bottom-left\":l=0}switch(a[\"text-anchor\"]){case\"bottom\":case\"bottom-right\":case\"bottom-left\":c=1;break;case\"top\":case\"top-right\":case\"top-left\":c=0}for(var h=\"right\"===a[\"text-justify\"]?1:\"left\"===a[\"text-justify\"]?0:.5,f=24*a[\"text-line-height\"],p=\"line\"!==a[\"symbol-placement\"]?24*a[\"text-max-width\"]:0,v=24*a[\"text-letter-spacing\"],x=[24*a[\"text-offset\"][0],24*a[\"text-offset\"][1]],_=this.fontstack=a[\"text-font\"].join(\",\"),M=[],k=0;k<o.length;k++)M.push(g(o[k]));if(\"line\"===a[\"symbol-placement\"]){var A=d(o,s,M);M=A.geometries,o=A.features,s=A.textFeatures}for(var T,S,E=0;E<o.length;E++)if(M[E]){if(T=s[E]?y(s[E],e[_],p,f,l,c,h,v,x):null,a[\"icon-image\"]){var L=r[u(o[E].properties,a[\"icon-image\"])];S=b(L,a),L&&(void 0===this.sdfIcons?this.sdfIcons=L.sdf:this.sdfIcons!==L.sdf&&m.warnOnce(\"Style sheet warning: Cannot mix SDF and non-SDF icons in one buffer\"),1!==L.pixelRatio?this.iconsNeedLinear=!0:0===a[\"icon-rotate\"]&&this.layer.isLayoutValueFeatureConstant(\"icon-rotate\")||(this.iconsNeedLinear=!0))}else S=null;(T||S)&&this.addFeature(M[E],T,S,o[E])}this.symbolInstancesEndIndex=this.symbolInstancesArray.length,this.placeFeatures(t,this.showCollisionBoxes),this.trimArrays()},n.prototype.addFeature=function(t,e,r,n){var i=this.layer.layout,a=this.adjustedTextSize/24,o=void 0!==this.adjustedTextMaxSize?this.adjustedTextMaxSize:this.adjustedTextSize,u=this.tilePixelRatio*a,c=this.tilePixelRatio*o/24,h=this.tilePixelRatio*this.adjustedIconSize,f=this.tilePixelRatio*i[\"symbol-spacing\"],d=i[\"symbol-avoid-edges\"],m=i[\"text-padding\"]*this.tilePixelRatio,g=i[\"icon-padding\"]*this.tilePixelRatio,v=i[\"text-max-angle\"]/180*Math.PI,y=\"map\"===i[\"text-rotation-alignment\"]&&\"line\"===i[\"symbol-placement\"],b=\"map\"===i[\"icon-rotation-alignment\"]&&\"line\"===i[\"symbol-placement\"],x=i[\"text-allow-overlap\"]||i[\"icon-allow-overlap\"]||i[\"text-ignore-placement\"]||i[\"icon-ignore-placement\"],_=\"line\"===i[\"symbol-placement\"],M=f/2;_&&(t=p(t,0,0,w,w));for(var k=0;k<t.length;k++)for(var A,T=t[k],S=0,E=(A=_?l(T,f,v,e,r,24,c,this.overscaling,w):[new s(T[0].x,T[0].y,0)]).length;S<E;S++){var L=A[S];if(!(e&&_&&this.anchorIsTooClose(e.text,M,L))){var C=!(L.x<0||L.x>w||L.y<0||L.y>w);if(!d||C){var z=C||x;this.addSymbolInstance(L,T,e,r,this.layer,z,this.symbolInstancesArray.length,this.collisionBoxArray,n.index,this.sourceLayerIndex,this.index,u,m,y,h,g,b,{zoom:this.zoom},n.properties)}}}},n.prototype.anchorIsTooClose=function(t,e,r){var n=this.compareText;if(t in n){for(var i=n[t],a=i.length-1;a>=0;a--)if(r.dist(i[a])<e)return!0}else n[t]=[];return n[t].push(r),!1},n.prototype.placeFeatures=function(t,e){this.recalculateStyleLayers(),this.createArrays();var r=this.layer.layout,n=t.maxScale,i=\"map\"===r[\"text-rotation-alignment\"]&&\"line\"===r[\"symbol-placement\"],a=\"map\"===r[\"icon-rotation-alignment\"]&&\"line\"===r[\"symbol-placement\"];if(r[\"text-allow-overlap\"]||r[\"icon-allow-overlap\"]||r[\"text-ignore-placement\"]||r[\"icon-ignore-placement\"]){var o=this.symbolInstancesArray.toArray(this.symbolInstancesStartIndex,this.symbolInstancesEndIndex),s=t.angle,l=Math.sin(s),u=Math.cos(s);this.sortedSymbolInstances=o.sort(function(t,e){return(l*t.anchorPointX+u*t.anchorPointY|0)-(l*e.anchorPointX+u*e.anchorPointY|0)||e.index-t.index})}for(var c=this.symbolInstancesStartIndex;c<this.symbolInstancesEndIndex;c++){var h=this.sortedSymbolInstances?this.sortedSymbolInstances[c-this.symbolInstancesStartIndex]:this.symbolInstancesArray.get(c),f={boxStartIndex:h.textBoxStartIndex,boxEndIndex:h.textBoxEndIndex},d={boxStartIndex:h.iconBoxStartIndex,boxEndIndex:h.iconBoxEndIndex},p=!(h.textBoxStartIndex===h.textBoxEndIndex),m=!(h.iconBoxStartIndex===h.iconBoxEndIndex),g=r[\"text-optional\"]||!p,v=r[\"icon-optional\"]||!m,y=p?t.placeCollisionFeature(f,r[\"text-allow-overlap\"],r[\"symbol-avoid-edges\"]):t.minScale,b=m?t.placeCollisionFeature(d,r[\"icon-allow-overlap\"],r[\"symbol-avoid-edges\"]):t.minScale;g||v?!v&&y?y=Math.max(b,y):!g&&b&&(b=Math.max(b,y)):b=y=Math.max(b,y),p&&(t.insertCollisionFeature(f,y,r[\"text-ignore-placement\"]),y<=n&&this.addSymbols(\"glyph\",h.glyphQuadStartIndex,h.glyphQuadEndIndex,y,r[\"text-keep-upright\"],i,t.angle)),m&&(t.insertCollisionFeature(d,b,r[\"icon-ignore-placement\"]),b<=n&&this.addSymbols(\"icon\",h.iconQuadStartIndex,h.iconQuadEndIndex,b,r[\"icon-keep-upright\"],a,t.angle))}e&&this.addToDebugBuffers(t)},n.prototype.addSymbols=function(t,e,r,n,a,o,s){for(var l=this.prepareArrayGroup(t,4*(r-e)),u=l.elementArray,c=l.layoutVertexArray,h=this.zoom,f=Math.max(Math.log(n)/Math.LN2+h,0),d=e;d<r;d++){var p=this.symbolQuadsArray.get(d).SymbolQuad,m=(p.anchorAngle+s+Math.PI)%(2*Math.PI);if(!(a&&o&&(m<=Math.PI/2||m>3*Math.PI/2))){var g=p.tl,v=p.tr,y=p.bl,b=p.br,x=p.tex,_=p.anchorPoint,w=Math.max(h+Math.log(p.minScale)/Math.LN2,f),M=Math.min(h+Math.log(p.maxScale)/Math.LN2,25);if(!(M<=w)){w===f&&(w=0);var k=Math.round(p.glyphAngle/(2*Math.PI)*256),A=i(c,_.x,_.y,g.x,g.y,x.x,x.y,w,M,f,k);i(c,_.x,_.y,v.x,v.y,x.x+x.w,x.y,w,M,f,k),i(c,_.x,_.y,y.x,y.y,x.x,x.y+x.h,w,M,f,k),i(c,_.x,_.y,b.x,b.y,x.x+x.w,x.y+x.h,w,M,f,k),u.emplaceBack(A,A+1,A+2),u.emplaceBack(A+1,A+2,A+3)}}}},n.prototype.updateIcons=function(t){this.recalculateStyleLayers();var e=this.layer.layout[\"icon-image\"];if(e)for(var r=0;r<this.features.length;r++){var n=u(this.features[r].properties,e);n&&(t[n]=!0)}},n.prototype.updateFont=function(t){this.recalculateStyleLayers();var e=this.layer.layout[\"text-font\"],r=t[e]=t[e]||{};this.textFeatures=f(this.features,this.layer.layout,r)},n.prototype.addToDebugBuffers=function(t){for(var e=this.prepareArrayGroup(\"collisionBox\",0).layoutVertexArray,r=-t.angle,n=t.yStretch,i=this.symbolInstancesStartIndex;i<this.symbolInstancesEndIndex;i++){var o=this.symbolInstancesArray.get(i);o.textCollisionFeature={boxStartIndex:o.textBoxStartIndex,boxEndIndex:o.textBoxEndIndex},o.iconCollisionFeature={boxStartIndex:o.iconBoxStartIndex,boxEndIndex:o.iconBoxEndIndex};for(var s=0;s<2;s++){var l=o[0===s?\"textCollisionFeature\":\"iconCollisionFeature\"];if(l)for(var u=l.boxStartIndex;u<l.boxEndIndex;u++){var c=this.collisionBoxArray.get(u),h=c.anchorPoint,f=new a(c.x1,c.y1*n)._rotate(r),d=new a(c.x2,c.y1*n)._rotate(r),p=new a(c.x1,c.y2*n)._rotate(r),m=new a(c.x2,c.y2*n)._rotate(r),g=Math.max(0,Math.min(25,this.zoom+Math.log(c.maxScale)/Math.LN2)),v=Math.max(0,Math.min(25,this.zoom+Math.log(c.placementScale)/Math.LN2));this.addCollisionBoxVertex(e,h,f,g,v),this.addCollisionBoxVertex(e,h,d,g,v),this.addCollisionBoxVertex(e,h,d,g,v),this.addCollisionBoxVertex(e,h,m,g,v),this.addCollisionBoxVertex(e,h,m,g,v),this.addCollisionBoxVertex(e,h,p,g,v),this.addCollisionBoxVertex(e,h,p,g,v),this.addCollisionBoxVertex(e,h,f,g,v)}}}},n.prototype.addSymbolInstance=function(t,e,r,i,a,o,s,l,u,c,h,f,d,p,g,y,b,w,M){var k,A,T,S,E,L,C,z;if(r&&(C=o?x(t,r,f,e,a,p):[],E=new v(l,e,t,u,c,h,r,f,d,p,!1)),k=this.symbolQuadsArray.length,C&&C.length)for(var D=0;D<C.length;D++)this.addSymbolQuad(C[D]);A=this.symbolQuadsArray.length;var I=E?E.boxStartIndex:this.collisionBoxArray.length,P=E?E.boxEndIndex:this.collisionBoxArray.length;i&&(z=o?_(t,i,g,e,a,b,r,w,M):[],L=new v(l,e,t,u,c,h,i,g,y,b,!0)),T=this.symbolQuadsArray.length,z&&1===z.length&&this.addSymbolQuad(z[0]),S=this.symbolQuadsArray.length;var O=L?L.boxStartIndex:this.collisionBoxArray.length,j=L?L.boxEndIndex:this.collisionBoxArray.length;return S>n.MAX_QUADS&&m.warnOnce(\"Too many symbols being rendered in a tile. See https://github.com/mapbox/mapbox-gl-js/issues/2907\"),A>n.MAX_QUADS&&m.warnOnce(\"Too many glyphs being rendered in a tile. See https://github.com/mapbox/mapbox-gl-js/issues/2907\"),this.symbolInstancesArray.emplaceBack(I,P,O,j,k,A,T,S,t.x,t.y,s)},n.prototype.addSymbolQuad=function(t){return this.symbolQuadsArray.emplaceBack(t.anchorPoint.x,t.anchorPoint.y,t.tl.x,t.tl.y,t.tr.x,t.tr.y,t.bl.x,t.bl.y,t.br.x,t.br.y,t.tex.h,t.tex.w,t.tex.x,t.tex.y,t.anchorAngle,t.glyphAngle,t.maxScale,t.minScale)}},{\"../../symbol/anchor\":373,\"../../symbol/clip_line\":375,\"../../symbol/collision_feature\":377,\"../../symbol/get_anchors\":379,\"../../symbol/mergelines\":382,\"../../symbol/quads\":383,\"../../symbol/resolve_text\":384,\"../../symbol/shaping\":385,\"../../util/token\":423,\"../../util/util\":424,\"../bucket\":311,\"../load_geometry\":319,\"point-geometry\":465}],316:[function(t,e,r){\"use strict\";function n(t,e,r){this.arrayBuffer=t.arrayBuffer,this.length=t.length,this.attributes=e.members,this.itemSize=e.bytesPerElement,this.type=r,this.arrayType=e}e.exports=n,n.prototype.bind=function(t){var e=t[this.type];this.buffer?t.bindBuffer(e,this.buffer):(this.buffer=t.createBuffer(),t.bindBuffer(e,this.buffer),t.bufferData(e,this.arrayBuffer,t.STATIC_DRAW),this.arrayBuffer=null)};var i={Int8:\"BYTE\",Uint8:\"UNSIGNED_BYTE\",Int16:\"SHORT\",Uint16:\"UNSIGNED_SHORT\"};n.prototype.setVertexAttribPointers=function(t,e){for(var r=0;r<this.attributes.length;r++){var n=this.attributes[r],a=e[n.name];void 0!==a&&t.vertexAttribPointer(a,n.components,t[i[n.type]],!1,this.arrayType.bytesPerElement,n.offset)}},n.prototype.destroy=function(t){this.buffer&&t.deleteBuffer(this.buffer)},n.BufferType={VERTEX:\"ARRAY_BUFFER\",ELEMENT:\"ELEMENT_ARRAY_BUFFER\"}},{}],317:[function(t,e,r){\"use strict\";function n(t,e){this.layoutVertexBuffer=new a(t.layoutVertexArray,e.layoutVertexArrayType,a.BufferType.VERTEX),t.elementArray&&(this.elementBuffer=new a(t.elementArray,e.elementArrayType,a.BufferType.ELEMENT));var r,n=this.vaos={};t.elementArray2&&(this.elementBuffer2=new a(t.elementArray2,e.elementArrayType2,a.BufferType.ELEMENT),r=this.secondVaos={}),this.paintVertexBuffers=i.mapObject(t.paintVertexArrays,function(i,s){return n[s]=new o,t.elementArray2&&(r[s]=new o),new a(i,e.paintVertexArrayTypes[s],a.BufferType.VERTEX)})}var i=t(\"../util/util\"),a=t(\"./buffer\"),o=t(\"../render/vertex_array_object\");e.exports=n,n.prototype.destroy=function(t){this.layoutVertexBuffer.destroy(t),this.elementBuffer&&this.elementBuffer.destroy(t),this.elementBuffer2&&this.elementBuffer2.destroy(t);for(var e in this.paintVertexBuffers)this.paintVertexBuffers[e].destroy(t);for(var r in this.vaos)this.vaos[r].destroy(t);for(var n in this.secondVaos)this.secondVaos[n].destroy(t)}},{\"../render/vertex_array_object\":339,\"../util/util\":424,\"./buffer\":316}],318:[function(t,e,r){\"use strict\";function n(t,e,r){if(t.grid){var n=t,i=e;t=n.coord,e=n.overscaling,this.grid=new p(n.grid),this.featureIndexArray=new k(n.featureIndexArray),this.rawTileData=i,this.bucketLayerIDs=n.bucketLayerIDs}else this.grid=new p(h,16,0),this.featureIndexArray=new k;this.coord=t,this.overscaling=e,this.x=t.x,this.y=t.y,this.z=t.z-Math.log(e)/Math.LN2,this.setCollisionTile(r)}function i(t){return Math.sqrt(t[0]*t[0]+t[1]*t[1])}function a(t,e){return e-t}function o(t){return t[\"line-gap-width\"]>0?t[\"line-gap-width\"]+2*t[\"line-width\"]:t[\"line-width\"]}function s(t,e,r,n,i){if(!e[0]&&!e[1])return t;e=u.convert(e),\"viewport\"===r&&e._rotate(-n);for(var a=[],o=0;o<t.length;o++){for(var s=t[o],l=[],c=0;c<s.length;c++)l.push(s[c].sub(e._mult(i)));a.push(l)}return a}function l(t,e){for(var r=[],n=new u(0,0),i=0;i<t.length;i++){for(var a=t[i],o=[],s=0;s<a.length;s++){var l=a[s-1],c=a[s],h=a[s+1],f=0===s?n:c.sub(l)._unit()._perp(),d=s===a.length-1?n:h.sub(c)._unit()._perp(),p=f._add(d)._unit(),m=p.x*d.x+p.y*d.y;p._mult(1/m),o.push(p._mult(e)._add(c))}r.push(o)}return r}var u=t(\"point-geometry\"),c=t(\"./load_geometry\"),h=t(\"./bucket\").EXTENT,f=t(\"feature-filter\"),d=t(\"../util/struct_array\"),p=t(\"grid-index\"),m=t(\"../util/dictionary_coder\"),g=t(\"vector-tile\"),v=t(\"pbf\"),y=t(\"../util/vectortile_to_geojson\"),b=t(\"../util/util\").arraysIntersect,x=t(\"../util/intersection_tests\"),_=x.multiPolygonIntersectsBufferedMultiPoint,w=x.multiPolygonIntersectsMultiPolygon,M=x.multiPolygonIntersectsBufferedMultiLine,k=new d({members:[{type:\"Uint32\",name:\"featureIndex\"},{type:\"Uint16\",name:\"sourceLayerIndex\"},{type:\"Uint16\",name:\"bucketIndex\"}]});e.exports=n,n.prototype.insert=function(t,e,r,n){var i=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(e,r,n);for(var a=c(t),o=0;o<a.length;o++){for(var s=a[o],l=[1/0,1/0,-1/0,-1/0],u=0;u<s.length;u++){var h=s[u];l[0]=Math.min(l[0],h.x),l[1]=Math.min(l[1],h.y),l[2]=Math.max(l[2],h.x),l[3]=Math.max(l[3],h.y)}this.grid.insert(i,l[0],l[1],l[2],l[3])}},n.prototype.setCollisionTile=function(t){this.collisionTile=t},n.prototype.serialize=function(){var t={coord:this.coord,overscaling:this.overscaling,grid:this.grid.toArrayBuffer(),featureIndexArray:this.featureIndexArray.serialize(),bucketLayerIDs:this.bucketLayerIDs};return{data:t,transferables:[t.grid,t.featureIndexArray.arrayBuffer]}},n.prototype.query=function(t,e){this.vtLayers||(this.vtLayers=new g.VectorTile(new v(new Uint8Array(this.rawTileData))).layers,this.sourceLayerCoder=new m(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"]));var r={},n=t.params||{},s=h/t.tileSize/t.scale,l=f(n.filter),c=0;for(var d in e){var p=e[d],y=p.paint,b=0;\"line\"===p.type?b=o(y)/2+Math.abs(y[\"line-offset\"])+i(y[\"line-translate\"]):\"fill\"===p.type?b=i(y[\"fill-translate\"]):\"circle\"===p.type&&(b=y[\"circle-radius\"]+i(y[\"circle-translate\"])),c=Math.max(c,b*s)}for(var x=t.queryGeometry.map(function(t){return t.map(function(t){return new u(t.x,t.y)})}),_=1/0,w=1/0,M=-1/0,k=-1/0,A=0;A<x.length;A++)for(var T=x[A],S=0;S<T.length;S++){var E=T[S];_=Math.min(_,E.x),w=Math.min(w,E.y),M=Math.max(M,E.x),k=Math.max(k,E.y)}var L=this.grid.query(_-c,w-c,M+c,k+c);L.sort(a),this.filterMatching(r,L,this.featureIndexArray,x,l,n.layers,e,t.bearing,s);var C=this.collisionTile.queryRenderedSymbols(_,w,M,k,t.scale);return C.sort(),this.filterMatching(r,C,this.collisionTile.collisionBoxArray,x,l,n.layers,e,t.bearing,s),r},n.prototype.filterMatching=function(t,e,r,n,i,a,u,h,f){for(var d,p=0;p<e.length;p++){var m=e[p];if(m!==d){d=m;var g=r.get(m),v=this.bucketLayerIDs[g.bucketIndex];if(!a||b(a,v)){var x=this.sourceLayerCoder.decode(g.sourceLayerIndex),k=this.vtLayers[x].feature(g.featureIndex);if(i(k))for(var A=null,T=0;T<v.length;T++){var S=v[T];if(!(a&&a.indexOf(S)<0)){var E=u[S];if(E){var L;if(\"symbol\"!==E.type){A||(A=c(k));var C=E.paint;if(\"line\"===E.type){L=s(n,C[\"line-translate\"],C[\"line-translate-anchor\"],h,f);var z=o(C)/2*f;if(C[\"line-offset\"]&&(A=l(A,C[\"line-offset\"]*f)),!M(L,A,z))continue}else if(\"fill\"===E.type){if(L=s(n,C[\"fill-translate\"],C[\"fill-translate-anchor\"],h,f),!w(L,A))continue}else if(\"circle\"===E.type){L=s(n,C[\"circle-translate\"],C[\"circle-translate-anchor\"],h,f);var D=C[\"circle-radius\"]*f;if(!_(L,A,D))continue}}var I=new y(k,this.z,this.x,this.y);I.layer=E.serialize({includeRefProperties:!0});var P=t[S];void 0===P&&(P=t[S]=[]),P.push(I)}}}}}}}},{\"../util/dictionary_coder\":414,\"../util/intersection_tests\":419,\"../util/struct_array\":422,\"../util/util\":424,\"../util/vectortile_to_geojson\":425,\"./bucket\":311,\"./load_geometry\":319,\"feature-filter\":117,\"grid-index\":271,pbf:459,\"point-geometry\":465,\"vector-tile\":530}],319:[function(t,e,r){\"use strict\";function n(t){return{min:-1*Math.pow(2,t-1),max:Math.pow(2,t-1)-1}}var i=t(\"../util/util\"),a=t(\"./bucket\").EXTENT,o=t(\"assert\"),s={15:n(15),16:n(16)};e.exports=function(t,e){var r=s[e||16];o(r);for(var n=a/t.extent,l=t.loadGeometry(),u=0;u<l.length;u++)for(var c=l[u],h=0;h<c.length;h++){var f=c[h];f.x=Math.round(f.x*n),f.y=Math.round(f.y*n),(f.x<r.min||f.x>r.max||f.y<r.min||f.y>r.max)&&i.warnOnce(\"Geometry exceeds allowed extent, reduce your vector tile buffer size\")}return l}},{\"../util/util\":424,\"./bucket\":311,assert:40}],320:[function(t,e,r){\"use strict\";function n(t,e,r){this.column=t,this.row=e,this.zoom=r}e.exports=n,n.prototype={clone:function(){return new n(this.column,this.row,this.zoom)},zoomTo:function(t){return this.clone()._zoomTo(t)},sub:function(t){return this.clone()._sub(t)},_zoomTo:function(t){var e=Math.pow(2,t-this.zoom);return this.column*=e,this.row*=e,this.zoom=t,this},_sub:function(t){return t=t.zoomTo(this.zoom),this.column-=t.column,this.row-=t.row,this}}},{}],321:[function(t,e,r){\"use strict\";function n(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\")}e.exports=n;var i=t(\"../util/util\").wrap;n.prototype.wrap=function(){return new n(i(this.lng,-180,180),this.lat)},n.prototype.toArray=function(){return[this.lng,this.lat]},n.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},n.convert=function(t){return t instanceof n?t:Array.isArray(t)?new n(t[0],t[1]):t}},{\"../util/util\":424}],322:[function(t,e,r){\"use strict\";function n(t,e){t&&(e?this.extend(t).extend(e):4===t.length?this.extend([t[0],t[1]]).extend([t[2],t[3]]):this.extend(t[0]).extend(t[1]))}e.exports=n;var i=t(\"./lng_lat\");n.prototype={extend:function(t){var e,r,a=this._sw,o=this._ne;if(t instanceof i)e=t,r=t;else{if(!(t instanceof n))return t?this.extend(i.convert(t)||n.convert(t)):this;if(e=t._sw,r=t._ne,!e||!r)return this}return a||o?(a.lng=Math.min(e.lng,a.lng),a.lat=Math.min(e.lat,a.lat),o.lng=Math.max(r.lng,o.lng),o.lat=Math.max(r.lat,o.lat)):(this._sw=new i(e.lng,e.lat),this._ne=new i(r.lng,r.lat)),this},getCenter:function(){return new i((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},getSouthWest:function(){return this._sw},getNorthEast:function(){return this._ne},getNorthWest:function(){return new i(this.getWest(),this.getNorth())},getSouthEast:function(){return new i(this.getEast(),this.getSouth())},getWest:function(){return this._sw.lng},getSouth:function(){return this._sw.lat},getEast:function(){return this._ne.lng},getNorth:function(){return this._ne.lat},toArray:function(){return[this._sw.toArray(),this._ne.toArray()]},toString:function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"}},n.convert=function(t){return!t||t instanceof n?t:new n(t)}},{\"./lng_lat\":321}],323:[function(t,e,r){\"use strict\";function n(t,e){this.tileSize=512,this._minZoom=t||0,this._maxZoom=e||22,this.latRange=[-85.05113,85.05113],this.width=0,this.height=0,this._center=new i(0,0),this.zoom=0,this.angle=0,this._altitude=1.5,this._pitch=0,this._unmodified=!0}var i=t(\"./lng_lat\"),a=t(\"point-geometry\"),o=t(\"./coordinate\"),s=t(\"../util/util\").wrap,l=t(\"../util/interpolate\"),u=t(\"../source/tile_coord\"),c=t(\"../data/bucket\").EXTENT,h=t(\"gl-matrix\"),f=h.vec4,d=h.mat4,p=h.mat2;e.exports=n,n.prototype={get minZoom(){return this._minZoom},set minZoom(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},get maxZoom(){return this._maxZoom},set maxZoom(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},get worldSize(){return this.tileSize*this.scale},get centerPoint(){return this.size._div(2)},get size(){return new a(this.width,this.height)},get bearing(){return-this.angle/Math.PI*180},set bearing(t){var e=-s(t,-180,180)*Math.PI/180;this.angle!==e&&(this._unmodified=!1,this.angle=e,this._calcMatrices(),this.rotationMatrix=p.create(),p.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},get pitch(){return this._pitch/Math.PI*180},set pitch(t){var e=Math.min(60,t)/180*Math.PI;this._pitch!==e&&(this._unmodified=!1,this._pitch=e,this._calcMatrices())},get altitude(){return this._altitude},set altitude(t){var e=Math.max(.75,t);this._altitude!==e&&(this._unmodified=!1,this._altitude=e,this._calcMatrices())},get zoom(){return this._zoom},set zoom(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._calcMatrices(),this._constrain())},get center(){return this._center},set center(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._calcMatrices(),this._constrain())},coveringZoomLevel:function(t){return(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize))},coveringTiles:function(t){var e=this.coveringZoomLevel(t),r=e;if(e<t.minzoom)return[];e>t.maxzoom&&(e=t.maxzoom);var n=this,i=n.locationCoordinate(n.center)._zoomTo(e),o=new a(i.column-.5,i.row-.5);return u.cover(e,[n.pointCoordinate(new a(0,0))._zoomTo(e),n.pointCoordinate(new a(n.width,0))._zoomTo(e),n.pointCoordinate(new a(n.width,n.height))._zoomTo(e),n.pointCoordinate(new a(0,n.height))._zoomTo(e)],t.reparseOverscaled?r:e).sort(function(t,e){return o.dist(t)-o.dist(e)})},resize:function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._calcMatrices(),this._constrain()},get unmodified(){return this._unmodified},zoomScale:function(t){return Math.pow(2,t)},scaleZoom:function(t){return Math.log(t)/Math.LN2},project:function(t,e){return new a(this.lngX(t.lng,e),this.latY(t.lat,e))},unproject:function(t,e){return new i(this.xLng(t.x,e),this.yLat(t.y,e))},get x(){return this.lngX(this.center.lng)},get y(){return this.latY(this.center.lat)},get point(){return new a(this.x,this.y)},lngX:function(t,e){return(180+t)*(e||this.worldSize)/360},latY:function(t,e){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))*(e||this.worldSize)/360},xLng:function(t,e){return 360*t/(e||this.worldSize)-180},yLat:function(t,e){var r=180-360*t/(e||this.worldSize);return 360/Math.PI*Math.atan(Math.exp(r*Math.PI/180))-90},panBy:function(t){var e=this.centerPoint._add(t);this.center=this.pointLocation(e)},setLocationAtPoint:function(t,e){var r=this.locationCoordinate(t),n=this.pointCoordinate(e),i=this.pointCoordinate(this.centerPoint),a=n._sub(r);this._unmodified=!1,this.center=this.coordinateLocation(i._sub(a))},locationPoint:function(t){return this.coordinatePoint(this.locationCoordinate(t))},pointLocation:function(t){return this.coordinateLocation(this.pointCoordinate(t))},locationCoordinate:function(t){var e=this.zoomScale(this.tileZoom)/this.worldSize,r=i.convert(t);return new o(this.lngX(r.lng)*e,this.latY(r.lat)*e,this.tileZoom)},coordinateLocation:function(t){var e=this.zoomScale(t.zoom);return new i(this.xLng(t.column,e),this.yLat(t.row,e))},pointCoordinate:function(t){var e=[t.x,t.y,0,1],r=[t.x,t.y,1,1];f.transformMat4(e,e,this.pixelMatrixInverse),f.transformMat4(r,r,this.pixelMatrixInverse);var n=e[3],i=r[3],a=e[0]/n,s=r[0]/i,u=e[1]/n,c=r[1]/i,h=e[2]/n,d=r[2]/i,p=h===d?0:(0-h)/(d-h),m=this.worldSize/this.zoomScale(this.tileZoom);return new o(l(a,s,p)/m,l(u,c,p)/m,this.tileZoom)},coordinatePoint:function(t){var e=this.worldSize/this.zoomScale(t.zoom),r=[t.column*e,t.row*e,0,1];return f.transformMat4(r,r,this.pixelMatrix),new a(r[0]/r[3],r[1]/r[3])},calculatePosMatrix:function(t,e){void 0===e&&(e=1/0),t instanceof u&&(t=t.toCoordinate(e));var r=Math.min(t.zoom,e),n=this.worldSize/Math.pow(2,r),i=new Float64Array(16);return d.identity(i),d.translate(i,i,[t.column*n,t.row*n,0]),d.scale(i,i,[n/c,n/c,1]),d.multiply(i,this.projMatrix,i),new Float32Array(i)},_constrain:function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var t,e,r,n,i,o,s,l,u=this.size,c=this._unmodified;this.latRange&&(t=this.latY(this.latRange[1]),i=(e=this.latY(this.latRange[0]))-t<u.y?u.y/(e-t):0),this.lngRange&&(r=this.lngX(this.lngRange[0]),o=(n=this.lngX(this.lngRange[1]))-r<u.x?u.x/(n-r):0);var h=Math.max(o||0,i||0);if(h)return this.center=this.unproject(new a(o?(n+r)/2:this.x,i?(e+t)/2:this.y)),this.zoom+=this.scaleZoom(h),this._unmodified=c,void(this._constraining=!1);if(this.latRange){var f=this.y,d=u.y/2;f-d<t&&(l=t+d),f+d>e&&(l=e-d)}if(this.lngRange){var p=this.x,m=u.x/2;p-m<r&&(s=r+m),p+m>n&&(s=n-m)}void 0===s&&void 0===l||(this.center=this.unproject(new a(void 0!==s?s:this.x,void 0!==l?l:this.y))),this._unmodified=c,this._constraining=!1}},_calcMatrices:function(){if(this.height){var t=Math.atan(.5/this.altitude),e=Math.sin(t)*this.altitude/Math.sin(Math.PI/2-this._pitch-t),r=Math.cos(Math.PI/2-this._pitch)*e+this.altitude,n=new Float64Array(16);if(d.perspective(n,2*Math.atan(this.height/2/this.altitude),this.width/this.height,.1,r),d.translate(n,n,[0,0,-this.altitude]),d.scale(n,n,[1,-1,1/this.height]),d.rotateX(n,n,this._pitch),d.rotateZ(n,n,this.angle),d.translate(n,n,[-this.x,-this.y,0]),this.projMatrix=n,n=d.create(),d.scale(n,n,[this.width/2,-this.height/2,1]),d.translate(n,n,[1,-1,0]),this.pixelMatrix=d.multiply(new Float64Array(16),n,this.projMatrix),!(n=d.invert(new Float64Array(16),this.pixelMatrix)))throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=n}}}},{\"../data/bucket\":311,\"../source/tile_coord\":351,\"../util/interpolate\":418,\"../util/util\":424,\"./coordinate\":320,\"./lng_lat\":321,\"gl-matrix\":177,\"point-geometry\":465}],324:[function(t,e,r){\"use strict\";var n={\" 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a,o,s,l,u,c,h,f,d=[];for(a=0,o=t.length;a<o;a++)if(u=n[t[a]]){for(f=null,s=0,l=u[1].length;s<l;s+=2)-1===u[1][s]&&-1===u[1][s+1]?f=null:(c=e+u[1][s]*i,h=r-u[1][s+1]*i,f&&d.push(f.x,f.y,c,h),f={x:c,y:h});e+=u[0]*i}return d}},{}],325:[function(t,e,r){\"use strict\";var n=e.exports={};n.version=t(\"../package.json\").version,n.Map=t(\"./ui/map\"),n.Control=t(\"./ui/control/control\"),n.Navigation=t(\"./ui/control/navigation\"),n.Geolocate=t(\"./ui/control/geolocate\"),n.Attribution=t(\"./ui/control/attribution\"),n.Popup=t(\"./ui/popup\"),n.Marker=t(\"./ui/marker\"),n.Style=t(\"./style/style\"),n.LngLat=t(\"./geo/lng_lat\"),n.LngLatBounds=t(\"./geo/lng_lat_bounds\"),n.Point=t(\"point-geometry\"),n.Evented=t(\"./util/evented\"),n.util=t(\"./util/util\"),n.supported=t(\"./util/browser\").supported;var i=t(\"./util/ajax\");n.util.getJSON=i.getJSON,n.util.getArrayBuffer=i.getArrayBuffer;var a=t(\"./util/config\");n.config=a,Object.defineProperty(n,\"accessToken\",{get:function(){return a.ACCESS_TOKEN},set:function(t){a.ACCESS_TOKEN=t}})},{\"../package.json\":426,\"./geo/lng_lat\":321,\"./geo/lng_lat_bounds\":322,\"./style/style\":360,\"./ui/control/attribution\":391,\"./ui/control/control\":392,\"./ui/control/geolocate\":393,\"./ui/control/navigation\":394,\"./ui/map\":403,\"./ui/marker\":404,\"./ui/popup\":405,\"./util/ajax\":407,\"./util/browser\":408,\"./util/config\":413,\"./util/evented\":416,\"./util/util\":424,\"point-geometry\":465}],326:[function(t,e,r){\"use strict\";var n=t(\"assert\");e.exports=function(t){for(var e={define:{},initialize:{}},r=0;r<t.length;r++){var i=t[r];n(\"u_\"===i.name.slice(0,2));var a=\"{precision} \"+(1===i.components?\"float\":\"vec\"+i.components);e.define[i.name.slice(2)]=\"uniform \"+a+\" \"+i.name+\";\\n\",e.initialize[i.name.slice(2)]=a+\" \"+i.name.slice(2)+\" = \"+i.name+\";\\n\"}return e}},{assert:40}],327:[function(t,e,r){\"use strict\";function n(t,e,r){var n,s=t.gl,l=t.transform,u=r.paint[\"background-color\"],c=r.paint[\"background-pattern\"],h=r.paint[\"background-opacity\"],f=c?t.spriteAtlas.getPosition(c.from,!0):null,d=c?t.spriteAtlas.getPosition(c.to,!0):null;if(t.setDepthSublayer(0),f&&d){if(t.isOpaquePass)return;n=t.useProgram(\"pattern\"),s.uniform1i(n.u_image,0),s.uniform2fv(n.u_pattern_tl_a,f.tl),s.uniform2fv(n.u_pattern_br_a,f.br),s.uniform2fv(n.u_pattern_tl_b,d.tl),s.uniform2fv(n.u_pattern_br_b,d.br),s.uniform1f(n.u_opacity,h),s.uniform1f(n.u_mix,c.t),s.uniform2fv(n.u_pattern_size_a,f.size),s.uniform2fv(n.u_pattern_size_b,d.size),s.uniform1f(n.u_scale_a,c.fromScale),s.uniform1f(n.u_scale_b,c.toScale),s.activeTexture(s.TEXTURE0),t.spriteAtlas.bind(s,!0),t.tileExtentPatternVAO.bind(s,n,t.tileExtentBuffer)}else{if(t.isOpaquePass!==(1===u[3]))return;var p=a([{name:\"u_color\",components:4},{name:\"u_opacity\",components:1}]);n=t.useProgram(\"fill\",[],p,p),s.uniform4fv(n.u_color,u),s.uniform1f(n.u_opacity,h),t.tileExtentVAO.bind(s,n,t.tileExtentBuffer)}s.disable(s.STENCIL_TEST);for(var m=l.coveringTiles({tileSize:o}),g=0;g<m.length;g++){var v=m[g];if(f&&d){var y={coord:v,tileSize:o};s.uniform1f(n.u_tile_units_to_pixels,1/i(y,1,t.transform.tileZoom));var b=y.tileSize*Math.pow(2,t.transform.tileZoom-y.coord.z),x=b*(y.coord.x+v.w*Math.pow(2,y.coord.z)),_=b*y.coord.y;s.uniform2f(n.u_pixel_coord_upper,x>>16,_>>16),s.uniform2f(n.u_pixel_coord_lower,65535&x,65535&_)}s.uniformMatrix4fv(n.u_matrix,!1,t.transform.calculatePosMatrix(v)),s.drawArrays(s.TRIANGLE_STRIP,0,t.tileExtentBuffer.length)}s.stencilMask(0),s.stencilFunc(s.EQUAL,128,128)}var i=t(\"../source/pixels_to_tile_units\"),a=t(\"./create_uniform_pragmas\"),o=512;e.exports=n},{\"../source/pixels_to_tile_units\":345,\"./create_uniform_pragmas\":326}],328:[function(t,e,r){\"use strict\";function n(t,e,r,n){if(!t.isOpaquePass){var a=t.gl;t.setDepthSublayer(0),t.depthMask(!1),a.disable(a.STENCIL_TEST);for(var o=0;o<n.length;o++){var s=n[o],l=e.getTile(s),u=l.getBucket(r);if(u){var c=u.bufferGroups.circle;if(c){var h=u.paintAttributes.circle[r.id],f=t.useProgram(\"circle\",h.defines,h.vertexPragmas,h.fragmentPragmas);\"map\"===r.paint[\"circle-pitch-scale\"]?(a.uniform1i(f.u_scale_with_map,!0),a.uniform2f(f.u_extrude_scale,t.transform.pixelsToGLUnits[0]*t.transform.altitude,t.transform.pixelsToGLUnits[1]*t.transform.altitude)):(a.uniform1i(f.u_scale_with_map,!1),a.uniform2fv(f.u_extrude_scale,t.transform.pixelsToGLUnits)),a.uniform1f(f.u_devicepixelratio,i.devicePixelRatio),a.uniformMatrix4fv(f.u_matrix,!1,t.translatePosMatrix(s.posMatrix,l,r.paint[\"circle-translate\"],r.paint[\"circle-translate-anchor\"])),u.setUniforms(a,\"circle\",f,r,{zoom:t.transform.zoom});for(var d=0;d<c.length;d++){var p=c[d];p.vaos[r.id].bind(a,f,p.layoutVertexBuffer,p.elementBuffer,p.paintVertexBuffers[r.id]),a.drawElements(a.TRIANGLES,3*p.elementBuffer.length,a.UNSIGNED_SHORT,0)}}}}}}var i=t(\"../util/browser\");e.exports=n},{\"../util/browser\":408}],329:[function(t,e,r){\"use strict\";function n(t,e,r,n){var i=t.gl;i.enable(i.STENCIL_TEST);for(var a=t.useProgram(\"collisionbox\"),o=0;o<n.length;o++){var s=n[o],l=e.getTile(s),u=l.getBucket(r);if(u){var c=u.bufferGroups.collisionBox;if(c&&c.length){var h=c[0];0!==h.layoutVertexBuffer.length&&(i.uniformMatrix4fv(a.u_matrix,!1,s.posMatrix),t.enableTileClippingMask(s),t.lineWidth(1),i.uniform1f(a.u_scale,Math.pow(2,t.transform.zoom-l.coord.z)),i.uniform1f(a.u_zoom,10*t.transform.zoom),i.uniform1f(a.u_maxzoom,10*(l.coord.z+1)),h.vaos[r.id].bind(i,a,h.layoutVertexBuffer),i.drawArrays(i.LINES,0,h.layoutVertexBuffer.length))}}}}e.exports=n},{}],330:[function(t,e,r){\"use strict\";function n(t,e,r){if(!t.isOpaquePass&&t.options.debug)for(var n=0;n<r.length;n++)i(t,e,r[n])}function i(t,e,r){var n=t.gl;n.disable(n.STENCIL_TEST),t.lineWidth(1*o.devicePixelRatio);var i=r.posMatrix,h=t.useProgram(\"debug\");n.uniformMatrix4fv(h.u_matrix,!1,i),n.uniform4f(h.u_color,1,0,0,1),t.debugVAO.bind(n,h,t.debugBuffer),n.drawArrays(n.LINE_STRIP,0,t.debugBuffer.length);for(var f=a(r.toString(),50,200,5),d=new t.PosArray,p=0;p<f.length;p+=2)d.emplaceBack(f[p],f[p+1]);var m=new u(d.serialize(),t.PosArray.serialize(),u.BufferType.VERTEX);(new c).bind(n,h,m),n.uniform4f(h.u_color,1,1,1,1);for(var g=e.getTile(r).tileSize,v=l/(Math.pow(2,t.transform.zoom-r.z)*g),y=[[-1,-1],[-1,1],[1,-1],[1,1]],b=0;b<y.length;b++){var x=y[b];n.uniformMatrix4fv(h.u_matrix,!1,s.translate([],i,[v*x[0],v*x[1],0])),n.drawArrays(n.LINES,0,m.length)}n.uniform4f(h.u_color,0,0,0,1),n.uniformMatrix4fv(h.u_matrix,!1,i),n.drawArrays(n.LINES,0,m.length)}var a=t(\"../lib/debugtext\"),o=t(\"../util/browser\"),s=t(\"gl-matrix\").mat4,l=t(\"../data/bucket\").EXTENT,u=t(\"../data/buffer\"),c=t(\"./vertex_array_object\");e.exports=n},{\"../data/bucket\":311,\"../data/buffer\":316,\"../lib/debugtext\":324,\"../util/browser\":408,\"./vertex_array_object\":339,\"gl-matrix\":177}],331:[function(t,e,r){\"use strict\";function n(t,e,r,n){var o=t.gl;o.enable(o.STENCIL_TEST);var s;if(s=!r.paint[\"fill-pattern\"]&&(r.isPaintValueFeatureConstant(\"fill-color\")&&r.isPaintValueFeatureConstant(\"fill-opacity\")&&1===r.paint[\"fill-color\"][3]&&1===r.paint[\"fill-opacity\"]),t.isOpaquePass===s){t.setDepthSublayer(1);for(var l=0;l<n.length;l++)i(t,e,r,n[l])}if(!t.isOpaquePass&&r.paint[\"fill-antialias\"]){t.lineWidth(2),t.depthMask(!1);var u=r.getPaintProperty(\"fill-outline-color\");(u||!r.paint[\"fill-pattern\"])&&u?t.setDepthSublayer(2):t.setDepthSublayer(0);for(var c=0;c<n.length;c++)a(t,e,r,n[c])}}function i(t,e,r,n){var i=e.getTile(n),a=i.getBucket(r);if(a){var s=a.bufferGroups.fill;if(s){var l,u=t.gl,c=r.paint[\"fill-pattern\"];if(c)l=t.useProgram(\"pattern\"),o(c,r.paint[\"fill-opacity\"],i,n,t,l),u.activeTexture(u.TEXTURE0),t.spriteAtlas.bind(u,!0);else{var h=a.paintAttributes.fill[r.id];l=t.useProgram(\"fill\",h.defines,h.vertexPragmas,h.fragmentPragmas),a.setUniforms(u,\"fill\",l,r,{zoom:t.transform.zoom})}u.uniformMatrix4fv(l.u_matrix,!1,t.translatePosMatrix(n.posMatrix,i,r.paint[\"fill-translate\"],r.paint[\"fill-translate-anchor\"])),t.enableTileClippingMask(n);for(var f=0;f<s.length;f++){var d=s[f];d.vaos[r.id].bind(u,l,d.layoutVertexBuffer,d.elementBuffer,d.paintVertexBuffers[r.id]),u.drawElements(u.TRIANGLES,d.elementBuffer.length,u.UNSIGNED_SHORT,0)}}}}function a(t,e,r,n){var i=e.getTile(n),a=i.getBucket(r);if(a){var s,l=t.gl,u=a.bufferGroups.fill,c=r.paint[\"fill-pattern\"],h=r.paint[\"fill-opacity\"],f=r.getPaintProperty(\"fill-outline-color\");if(c&&!f)s=t.useProgram(\"outlinepattern\"),l.uniform2f(s.u_world,l.drawingBufferWidth,l.drawingBufferHeight);else{var d=a.paintAttributes.fill[r.id];s=t.useProgram(\"outline\",d.defines,d.vertexPragmas,d.fragmentPragmas),l.uniform2f(s.u_world,l.drawingBufferWidth,l.drawingBufferHeight),l.uniform1f(s.u_opacity,h),a.setUniforms(l,\"fill\",s,r,{zoom:t.transform.zoom})}l.uniformMatrix4fv(s.u_matrix,!1,t.translatePosMatrix(n.posMatrix,i,r.paint[\"fill-translate\"],r.paint[\"fill-translate-anchor\"])),c&&o(c,h,i,n,t,s),t.enableTileClippingMask(n);for(var p=0;p<u.length;p++){var m=u[p];m.secondVaos[r.id].bind(l,s,m.layoutVertexBuffer,m.elementBuffer2,m.paintVertexBuffers[r.id]),l.drawElements(l.LINES,2*m.elementBuffer2.length,l.UNSIGNED_SHORT,0)}}}function o(t,e,r,n,i,a){var o=i.gl,l=i.spriteAtlas.getPosition(t.from,!0),u=i.spriteAtlas.getPosition(t.to,!0);if(l&&u){o.uniform1i(a.u_image,0),o.uniform2fv(a.u_pattern_tl_a,l.tl),o.uniform2fv(a.u_pattern_br_a,l.br),o.uniform2fv(a.u_pattern_tl_b,u.tl),o.uniform2fv(a.u_pattern_br_b,u.br),o.uniform1f(a.u_opacity,e),o.uniform1f(a.u_mix,t.t),o.uniform1f(a.u_tile_units_to_pixels,1/s(r,1,i.transform.tileZoom)),o.uniform2fv(a.u_pattern_size_a,l.size),o.uniform2fv(a.u_pattern_size_b,u.size),o.uniform1f(a.u_scale_a,t.fromScale),o.uniform1f(a.u_scale_b,t.toScale);var c=r.tileSize*Math.pow(2,i.transform.tileZoom-r.coord.z),h=c*(r.coord.x+n.w*Math.pow(2,r.coord.z)),f=c*r.coord.y;o.uniform2f(a.u_pixel_coord_upper,h>>16,f>>16),o.uniform2f(a.u_pixel_coord_lower,65535&h,65535&f),o.activeTexture(o.TEXTURE0),i.spriteAtlas.bind(o,!0)}}var s=t(\"../source/pixels_to_tile_units\");e.exports=n},{\"../source/pixels_to_tile_units\":345}],332:[function(t,e,r){\"use strict\";var n=t(\"../util/browser\"),i=t(\"gl-matrix\").mat2,a=t(\"../source/pixels_to_tile_units\");e.exports=function(t,e,r,o){if(!t.isOpaquePass){t.setDepthSublayer(0),t.depthMask(!1);var s=t.gl;if(s.enable(s.STENCIL_TEST),!(r.paint[\"line-width\"]<=0)){var l=1/n.devicePixelRatio,u=r.paint[\"line-blur\"]+l,c=r.paint[\"line-color\"],h=t.transform,f=i.create();i.scale(f,f,[1,Math.cos(h._pitch)]),i.rotate(f,f,t.transform.angle);var d,p,m,g,v,y=Math.sqrt(h.height*h.height/4*(1+h.altitude*h.altitude)),b=(y+h.height/2*Math.tan(h._pitch))/y-1,x=r.paint[\"line-dasharray\"],_=r.paint[\"line-pattern\"];if(x)d=t.useProgram(\"linesdfpattern\"),s.uniform1f(d.u_linewidth,r.paint[\"line-width\"]/2),s.uniform1f(d.u_gapwidth,r.paint[\"line-gap-width\"]/2),s.uniform1f(d.u_antialiasing,l/2),s.uniform1f(d.u_blur,u),s.uniform4fv(d.u_color,c),s.uniform1f(d.u_opacity,r.paint[\"line-opacity\"]),p=t.lineAtlas.getDash(x.from,\"round\"===r.layout[\"line-cap\"]),m=t.lineAtlas.getDash(x.to,\"round\"===r.layout[\"line-cap\"]),s.uniform1i(d.u_image,0),s.activeTexture(s.TEXTURE0),t.lineAtlas.bind(s),s.uniform1f(d.u_tex_y_a,p.y),s.uniform1f(d.u_tex_y_b,m.y),s.uniform1f(d.u_mix,x.t),s.uniform1f(d.u_extra,b),s.uniform1f(d.u_offset,-r.paint[\"line-offset\"]),s.uniformMatrix2fv(d.u_antialiasingmatrix,!1,f);else if(_){if(g=t.spriteAtlas.getPosition(_.from,!0),v=t.spriteAtlas.getPosition(_.to,!0),!g||!v)return;d=t.useProgram(\"linepattern\"),s.uniform1i(d.u_image,0),s.activeTexture(s.TEXTURE0),t.spriteAtlas.bind(s,!0),s.uniform1f(d.u_linewidth,r.paint[\"line-width\"]/2),s.uniform1f(d.u_gapwidth,r.paint[\"line-gap-width\"]/2),s.uniform1f(d.u_antialiasing,l/2),s.uniform1f(d.u_blur,u),s.uniform2fv(d.u_pattern_tl_a,g.tl),s.uniform2fv(d.u_pattern_br_a,g.br),s.uniform2fv(d.u_pattern_tl_b,v.tl),s.uniform2fv(d.u_pattern_br_b,v.br),s.uniform1f(d.u_fade,_.t),s.uniform1f(d.u_opacity,r.paint[\"line-opacity\"]),s.uniform1f(d.u_extra,b),s.uniform1f(d.u_offset,-r.paint[\"line-offset\"]),s.uniformMatrix2fv(d.u_antialiasingmatrix,!1,f)}else d=t.useProgram(\"line\"),s.uniform1f(d.u_linewidth,r.paint[\"line-width\"]/2),s.uniform1f(d.u_gapwidth,r.paint[\"line-gap-width\"]/2),s.uniform1f(d.u_antialiasing,l/2),s.uniform1f(d.u_blur,u),s.uniform1f(d.u_extra,b),s.uniform1f(d.u_offset,-r.paint[\"line-offset\"]),s.uniformMatrix2fv(d.u_antialiasingmatrix,!1,f),s.uniform4fv(d.u_color,c),s.uniform1f(d.u_opacity,r.paint[\"line-opacity\"]);for(var w=0;w<o.length;w++){var M=o[w],k=e.getTile(M),A=k.getBucket(r);if(A){var T=A.bufferGroups.line;if(T){t.enableTileClippingMask(M);var S=t.translatePosMatrix(M.posMatrix,k,r.paint[\"line-translate\"],r.paint[\"line-translate-anchor\"]);s.uniformMatrix4fv(d.u_matrix,!1,S);var E=1/a(k,1,t.transform.zoom);if(x){var L=p.width*x.fromScale,C=m.width*x.toScale,z=[1/a(k,L,t.transform.tileZoom),-p.height/2],D=[1/a(k,C,t.transform.tileZoom),-m.height/2],I=t.lineAtlas.width/(256*Math.min(L,C)*n.devicePixelRatio)/2;s.uniform1f(d.u_ratio,E),s.uniform2fv(d.u_patternscale_a,z),s.uniform2fv(d.u_patternscale_b,D),s.uniform1f(d.u_sdfgamma,I)}else _?(s.uniform1f(d.u_ratio,E),s.uniform2fv(d.u_pattern_size_a,[a(k,g.size[0]*_.fromScale,t.transform.tileZoom),v.size[1]]),s.uniform2fv(d.u_pattern_size_b,[a(k,v.size[0]*_.toScale,t.transform.tileZoom),v.size[1]])):s.uniform1f(d.u_ratio,E);for(var P=0;P<T.length;P++){var O=T[P];O.vaos[r.id].bind(s,d,O.layoutVertexBuffer,O.elementBuffer),s.drawElements(s.TRIANGLES,3*O.elementBuffer.length,s.UNSIGNED_SHORT,0)}}}}}}}},{\"../source/pixels_to_tile_units\":345,\"../util/browser\":408,\"gl-matrix\":177}],333:[function(t,e,r){\"use strict\";function n(t,e,r,n){if(!t.isOpaquePass){var a=t.gl;a.enable(a.DEPTH_TEST),t.depthMask(!0),a.depthFunc(a.LESS);for(var o=n.length&&n[0].z,s=0;s<n.length;s++){var l=n[s];t.setDepthSublayer(l.z-o),i(t,e,r,l)}a.depthFunc(a.LEQUAL)}}function i(t,e,r,n){var i=t.gl;i.disable(i.STENCIL_TEST);var u=e.getTile(n),c=t.transform.calculatePosMatrix(n,e.maxzoom),h=t.useProgram(\"raster\");i.uniformMatrix4fv(h.u_matrix,!1,c),i.uniform1f(h.u_brightness_low,r.paint[\"raster-brightness-min\"]),i.uniform1f(h.u_brightness_high,r.paint[\"raster-brightness-max\"]),i.uniform1f(h.u_saturation_factor,s(r.paint[\"raster-saturation\"])),i.uniform1f(h.u_contrast_factor,o(r.paint[\"raster-contrast\"])),i.uniform3fv(h.u_spin_weights,a(r.paint[\"raster-hue-rotate\"]));var f,d,p=u.source&&u.source.findLoadedParent(n,0,{}),m=l(u,p,r,t.transform);i.activeTexture(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,u.texture),i.activeTexture(i.TEXTURE1),p?(i.bindTexture(i.TEXTURE_2D,p.texture),f=Math.pow(2,p.coord.z-u.coord.z),d=[u.coord.x*f%1,u.coord.y*f%1]):(i.bindTexture(i.TEXTURE_2D,u.texture),m[1]=0),i.uniform2fv(h.u_tl_parent,d||[0,0]),i.uniform1f(h.u_scale_parent,f||1),i.uniform1f(h.u_buffer_scale,1),i.uniform1f(h.u_opacity0,m[0]),i.uniform1f(h.u_opacity1,m[1]),i.uniform1i(h.u_image0,0),i.uniform1i(h.u_image1,1);var g=u.boundsBuffer||t.rasterBoundsBuffer;(u.boundsVAO||t.rasterBoundsVAO).bind(i,h,g),i.drawArrays(i.TRIANGLE_STRIP,0,g.length)}function a(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]}function o(t){return t>0?1/(1-t):1+t}function s(t){return t>0?1-1/(1.001-t):-t}function l(t,e,r,n){var i=[1,0],a=r.paint[\"raster-fade-duration\"];if(t.source&&a>0){var o=(new Date).getTime(),s=(o-t.timeAdded)/a,l=e?(o-e.timeAdded)/a:-1,c=n.coveringZoomLevel(t.source),h=!!e&&Math.abs(e.coord.z-c)>Math.abs(t.coord.z-c);!e||h?(i[0]=u.clamp(s,0,1),i[1]=1-i[0]):(i[0]=u.clamp(1-l,0,1),i[1]=1-i[0])}var f=r.paint[\"raster-opacity\"];return i[0]*=f,i[1]*=f,i}var u=t(\"../util/util\"),c=t(\"../util/struct_array\");e.exports=n,n.RasterBoundsArray=new c({members:[{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]})},{\"../util/struct_array\":422,\"../util/util\":424}],334:[function(t,e,r){\"use strict\";function n(t,e,r,n){if(!t.isOpaquePass){var a=!(r.layout[\"text-allow-overlap\"]||r.layout[\"icon-allow-overlap\"]||r.layout[\"text-ignore-placement\"]||r.layout[\"icon-ignore-placement\"]),o=t.gl;a?o.disable(o.STENCIL_TEST):o.enable(o.STENCIL_TEST),t.setDepthSublayer(0),t.depthMask(!1),o.disable(o.DEPTH_TEST),i(t,e,r,n,!1,r.paint[\"icon-translate\"],r.paint[\"icon-translate-anchor\"],r.layout[\"icon-rotation-alignment\"],r.layout[\"icon-rotation-alignment\"],r.layout[\"icon-size\"],r.paint[\"icon-halo-width\"],r.paint[\"icon-halo-color\"],r.paint[\"icon-halo-blur\"],r.paint[\"icon-opacity\"],r.paint[\"icon-color\"]),i(t,e,r,n,!0,r.paint[\"text-translate\"],r.paint[\"text-translate-anchor\"],r.layout[\"text-rotation-alignment\"],r.layout[\"text-pitch-alignment\"],r.layout[\"text-size\"],r.paint[\"text-halo-width\"],r.paint[\"text-halo-color\"],r.paint[\"text-halo-blur\"],r.paint[\"text-opacity\"],r.paint[\"text-color\"]),o.enable(o.DEPTH_TEST),e.map.showCollisionBoxes&&s(t,e,r,n)}}function i(t,e,r,n,i,o,s,l,u,c,h,f,d,p,m){for(var g=0;g<n.length;g++){var v=e.getTile(n[g]),y=v.getBucket(r);if(y){var b=y.bufferGroups,x=i?b.glyph:b.icon;x.length&&(t.enableTileClippingMask(n[g]),a(t,r,n[g].posMatrix,v,y,x,i,i||y.sdfIcons,!i&&y.iconsNeedLinear,i?y.adjustedTextSize:y.adjustedIconSize,y.fontstack,o,s,l,u,c,h,f,d,p,m))}}}function a(t,e,r,n,i,a,s,u,c,h,f,d,p,m,g,v,y,b,x,_,w){var M,k,A,T=t.gl,S=t.transform,E=\"map\"===m,L=\"map\"===g,C=s?24:1,z=v/C;if(L?(k=l(n,1,t.transform.zoom)*z,A=1/Math.cos(S._pitch),M=[k,k]):(k=t.transform.altitude*z,A=1,M=[S.pixelsToGLUnits[0]*k,S.pixelsToGLUnits[1]*k]),s||t.style.sprite.loaded()){var D=t.useProgram(u?\"sdf\":\"icon\");if(T.uniformMatrix4fv(D.u_matrix,!1,t.translatePosMatrix(r,n,d,p)),T.uniform1i(D.u_rotate_with_map,E),T.uniform1i(D.u_pitch_with_map,L),T.uniform2fv(D.u_extrude_scale,M),T.activeTexture(T.TEXTURE0),T.uniform1i(D.u_texture,0),s){var I=f&&t.glyphSource.getGlyphAtlas(f);if(!I)return;I.updateTexture(T),T.uniform2f(D.u_texsize,I.width/4,I.height/4)}else{var P=t.options.rotating||t.options.zooming,O=1!==z||o.devicePixelRatio!==t.spriteAtlas.pixelRatio||c,j=L||t.transform.pitch;t.spriteAtlas.bind(T,u||P||O||j),T.uniform2f(D.u_texsize,t.spriteAtlas.width/4,t.spriteAtlas.height/4)}var R=Math.log(v/h)/Math.LN2||0;T.uniform1f(D.u_zoom,10*(t.transform.zoom-R)),T.activeTexture(T.TEXTURE1),t.frameHistory.bind(T),T.uniform1i(D.u_fadetexture,1);var F;if(u){var N=.105*C/v/o.devicePixelRatio;if(y){T.uniform1f(D.u_gamma,(1.19*x/z/8+N)*A),T.uniform4fv(D.u_color,b),T.uniform1f(D.u_opacity,_),T.uniform1f(D.u_buffer,(6-y/z)/8);for(var B=0;B<a.length;B++)(F=a[B]).vaos[e.id].bind(T,D,F.layoutVertexBuffer,F.elementBuffer),T.drawElements(T.TRIANGLES,3*F.elementBuffer.length,T.UNSIGNED_SHORT,0)}T.uniform1f(D.u_gamma,N*A),T.uniform4fv(D.u_color,w),T.uniform1f(D.u_opacity,_),T.uniform1f(D.u_buffer,.75),T.uniform1f(D.u_pitch,S.pitch/360*2*Math.PI),T.uniform1f(D.u_bearing,S.bearing/360*2*Math.PI),T.uniform1f(D.u_aspect_ratio,S.width/S.height);for(var U=0;U<a.length;U++)(F=a[U]).vaos[e.id].bind(T,D,F.layoutVertexBuffer,F.elementBuffer),T.drawElements(T.TRIANGLES,3*F.elementBuffer.length,T.UNSIGNED_SHORT,0)}else{T.uniform1f(D.u_opacity,_);for(var V=0;V<a.length;V++)(F=a[V]).vaos[e.id].bind(T,D,F.layoutVertexBuffer,F.elementBuffer),T.drawElements(T.TRIANGLES,3*F.elementBuffer.length,T.UNSIGNED_SHORT,0)}}}var o=t(\"../util/browser\"),s=t(\"./draw_collision_debug\"),l=t(\"../source/pixels_to_tile_units\");e.exports=n},{\"../source/pixels_to_tile_units\":345,\"../util/browser\":408,\"./draw_collision_debug\":329}],335:[function(t,e,r){\"use strict\";function n(){this.changeTimes=new Float64Array(256),this.changeOpacities=new Uint8Array(256),this.opacities=new Uint8ClampedArray(256),this.array=new Uint8Array(this.opacities.buffer),this.fadeDuration=300,this.previousZoom=0,this.firstFrame=!0}e.exports=n,n.prototype.record=function(t){var e=Date.now();this.firstFrame&&(e=0,this.firstFrame=!1);var r;if((t=Math.floor(10*t))<this.previousZoom)for(r=t+1;r<=this.previousZoom;r++)this.changeTimes[r]=e,this.changeOpacities[r]=this.opacities[r];else for(r=t;r>this.previousZoom;r--)this.changeTimes[r]=e,this.changeOpacities[r]=this.opacities[r];for(r=0;r<256;r++){var n=(e-this.changeTimes[r])/this.fadeDuration*255;this.opacities[r]=r<=t?this.changeOpacities[r]+n:this.changeOpacities[r]-n}this.changed=!0,this.previousZoom=t},n.prototype.bind=function(t){this.texture?(t.bindTexture(t.TEXTURE_2D,this.texture),this.changed&&(t.texSubImage2D(t.TEXTURE_2D,0,0,0,256,1,t.ALPHA,t.UNSIGNED_BYTE,this.array),this.changed=!1)):(this.texture=t.createTexture(),t.bindTexture(t.TEXTURE_2D,this.texture),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),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texImage2D(t.TEXTURE_2D,0,t.ALPHA,256,1,0,t.ALPHA,t.UNSIGNED_BYTE,this.array))}},{}],336:[function(t,e,r){\"use strict\";function n(t,e){this.width=t,this.height=e,this.nextRow=0,this.bytes=4,this.data=new Uint8Array(this.width*this.height*this.bytes),this.positions={}}var i=t(\"../util/util\");e.exports=n,n.prototype.setSprite=function(t){this.sprite=t},n.prototype.getDash=function(t,e){var r=t.join(\",\")+e;return this.positions[r]||(this.positions[r]=this.addDash(t,e)),this.positions[r]},n.prototype.addDash=function(t,e){var r=e?7:0,n=2*r+1;if(this.nextRow+n>this.height)return i.warnOnce(\"LineAtlas out of space\"),null;for(var a=0,o=0;o<t.length;o++)a+=t[o];for(var s=this.width/a,l=s/2,u=t.length%2==1,c=-r;c<=r;c++)for(var h=this.nextRow+r+c,f=this.width*h,d=u?-t[t.length-1]:0,p=t[0],m=1,g=0;g<this.width;g++){for(;p<g/s;)d=p,p+=t[m],u&&m===t.length-1&&(p+=t[0]),m++;var v,y=Math.abs(g-d*s),b=Math.abs(g-p*s),x=Math.min(y,b),_=m%2==1;if(e){var w=r?c/r*(l+1):0;if(_){var M=l-Math.abs(w);v=Math.sqrt(x*x+M*M)}else v=l-Math.sqrt(x*x+w*w)}else v=(_?1:-1)*x;this.data[3+4*(f+g)]=Math.max(0,Math.min(255,v+128))}var k={y:(this.nextRow+r+.5)/this.height,height:2*r/this.height,width:a};return this.nextRow+=n,this.dirty=!0,k},n.prototype.bind=function(t){this.texture?(t.bindTexture(t.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,t.texSubImage2D(t.TEXTURE_2D,0,0,0,this.width,this.height,t.RGBA,t.UNSIGNED_BYTE,this.data))):(this.texture=t.createTexture(),t.bindTexture(t.TEXTURE_2D,this.texture),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.REPEAT),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.REPEAT),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.LINEAR),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.LINEAR),t.texImage2D(t.TEXTURE_2D,0,t.RGBA,this.width,this.height,0,t.RGBA,t.UNSIGNED_BYTE,this.data))}},{\"../util/util\":424}],337:[function(t,e,r){\"use strict\";function n(t,e){this.gl=t,this.transform=e,this.reusableTextures={},this.preFbos={},this.frameHistory=new o,this.setup(),this.numSublayers=s.maxUnderzooming+s.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.lineWidthRange=t.getParameter(t.ALIASED_LINE_WIDTH_RANGE)}var i=t(\"../util/browser\"),a=t(\"gl-matrix\").mat4,o=t(\"./frame_history\"),s=t(\"../source/source_cache\"),l=t(\"../data/bucket\").EXTENT,u=t(\"../source/pixels_to_tile_units\"),c=t(\"../util/util\"),h=t(\"../util/struct_array\"),f=t(\"../data/buffer\"),d=t(\"./vertex_array_object\"),p=t(\"./draw_raster\").RasterBoundsArray,m=t(\"./create_uniform_pragmas\");e.exports=n,c.extend(n.prototype,t(\"./painter/use_program\")),n.prototype.resize=function(t,e){var r=this.gl;this.width=t*i.devicePixelRatio,this.height=e*i.devicePixelRatio,r.viewport(0,0,this.width,this.height)},n.prototype.setup=function(){var t=this.gl;t.verbose=!0,t.enable(t.BLEND),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),t.enable(t.STENCIL_TEST),t.enable(t.DEPTH_TEST),t.depthFunc(t.LEQUAL),this._depthMask=!1,t.depthMask(!1);var e=this.PosArray=new h({members:[{name:\"a_pos\",type:\"Int16\",components:2}]}),r=new e;r.emplaceBack(0,0),r.emplaceBack(l,0),r.emplaceBack(0,l),r.emplaceBack(l,l),this.tileExtentBuffer=new f(r.serialize(),e.serialize(),f.BufferType.VERTEX),this.tileExtentVAO=new d,this.tileExtentPatternVAO=new d;var n=new e;n.emplaceBack(0,0),n.emplaceBack(l,0),n.emplaceBack(l,l),n.emplaceBack(0,l),n.emplaceBack(0,0),this.debugBuffer=new f(n.serialize(),e.serialize(),f.BufferType.VERTEX),this.debugVAO=new d;var i=new p;i.emplaceBack(0,0,0,0),i.emplaceBack(l,0,32767,0),i.emplaceBack(0,l,0,32767),i.emplaceBack(l,l,32767,32767),this.rasterBoundsBuffer=new f(i.serialize(),p.serialize(),f.BufferType.VERTEX),this.rasterBoundsVAO=new d},n.prototype.clearColor=function(){var t=this.gl;t.clearColor(0,0,0,0),t.clear(t.COLOR_BUFFER_BIT)},n.prototype.clearStencil=function(){var t=this.gl;t.clearStencil(0),t.stencilMask(255),t.clear(t.STENCIL_BUFFER_BIT)},n.prototype.clearDepth=function(){var t=this.gl;t.clearDepth(1),this.depthMask(!0),t.clear(t.DEPTH_BUFFER_BIT)},n.prototype._renderTileClippingMasks=function(t){var e=this.gl;e.colorMask(!1,!1,!1,!1),this.depthMask(!1),e.disable(e.DEPTH_TEST),e.enable(e.STENCIL_TEST),e.stencilMask(248),e.stencilOp(e.KEEP,e.KEEP,e.REPLACE);var r=1;this._tileClippingMaskIDs={};for(var n=0;n<t.length;n++){var i=t[n],a=this._tileClippingMaskIDs[i.id]=r++<<3;e.stencilFunc(e.ALWAYS,a,248);var o=m([{name:\"u_color\",components:4},{name:\"u_opacity\",components:1}]),s=this.useProgram(\"fill\",[],o,o);e.uniformMatrix4fv(s.u_matrix,!1,i.posMatrix),this.tileExtentVAO.bind(e,s,this.tileExtentBuffer),e.drawArrays(e.TRIANGLE_STRIP,0,this.tileExtentBuffer.length)}e.stencilMask(0),e.colorMask(!0,!0,!0,!0),this.depthMask(!0),e.enable(e.DEPTH_TEST)},n.prototype.enableTileClippingMask=function(t){var e=this.gl;e.stencilFunc(e.EQUAL,this._tileClippingMaskIDs[t.id],248)},n.prototype.prepareBuffers=function(){},n.prototype.bindDefaultFramebuffer=function(){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,null)};var g={symbol:t(\"./draw_symbol\"),circle:t(\"./draw_circle\"),line:t(\"./draw_line\"),fill:t(\"./draw_fill\"),raster:t(\"./draw_raster\"),background:t(\"./draw_background\"),debug:t(\"./draw_debug\")};n.prototype.render=function(t,e){this.style=t,this.options=e,this.lineAtlas=t.lineAtlas,this.spriteAtlas=t.spriteAtlas,this.spriteAtlas.setSprite(t.sprite),this.glyphSource=t.glyphSource,this.frameHistory.record(this.transform.zoom),this.prepareBuffers(),this.clearColor(),this.clearDepth(),this.showOverdrawInspector(e.showOverdrawInspector),this.depthRange=(t._order.length+2)*this.numSublayers*this.depthEpsilon,this.renderPass({isOpaquePass:!0}),this.renderPass({isOpaquePass:!1})},n.prototype.renderPass=function(t){var e=this.style._groups,r=t.isOpaquePass;this.currentLayer=r?this.style._order.length:-1;for(var n=0;n<e.length;n++){var i,a=e[r?e.length-1-n:n],o=this.style.sources[a.source],s=[];if(o){for(s=o.getVisibleCoordinates(),i=0;i<s.length;i++)s[i].posMatrix=this.transform.calculatePosMatrix(s[i],o.maxzoom);this.clearStencil(),o.prepare&&o.prepare(),o.isTileClipped&&this._renderTileClippingMasks(s)}for(r?(this._showOverdrawInspector||this.gl.disable(this.gl.BLEND),this.isOpaquePass=!0):(this.gl.enable(this.gl.BLEND),this.isOpaquePass=!1,s.reverse()),i=0;i<a.length;i++){var l=a[r?a.length-1-i:i];this.currentLayer+=r?-1:1,this.renderLayer(this,o,l,s)}o&&g.debug(this,o,s)}},n.prototype.depthMask=function(t){t!==this._depthMask&&(this._depthMask=t,this.gl.depthMask(t))},n.prototype.renderLayer=function(t,e,r,n){r.isHidden(this.transform.zoom)||(\"background\"===r.type||n.length)&&(this.id=r.id,g[r.type](t,e,r,n))},n.prototype.setDepthSublayer=function(t){var e=1-((1+this.currentLayer)*this.numSublayers+t)*this.depthEpsilon,r=e-1+this.depthRange;this.gl.depthRange(r,e)},n.prototype.translatePosMatrix=function(t,e,r,n){if(!r[0]&&!r[1])return t;if(\"viewport\"===n){var i=Math.sin(-this.transform.angle),o=Math.cos(-this.transform.angle);r=[r[0]*o-r[1]*i,r[0]*i+r[1]*o]}var s=[u(e,r[0],this.transform.zoom),u(e,r[1],this.transform.zoom),0],l=new Float32Array(16);return a.translate(l,t,s),l},n.prototype.saveTexture=function(t){var e=this.reusableTextures[t.size];e?e.push(t):this.reusableTextures[t.size]=[t]},n.prototype.getTexture=function(t){var e=this.reusableTextures[t];return e&&e.length>0?e.pop():null},n.prototype.lineWidth=function(t){this.gl.lineWidth(c.clamp(t,this.lineWidthRange[0],this.lineWidthRange[1]))},n.prototype.showOverdrawInspector=function(t){if(t||this._showOverdrawInspector){this._showOverdrawInspector=t;var e=this.gl;if(t){e.blendFunc(e.CONSTANT_COLOR,e.ONE);e.blendColor(1/8,1/8,1/8,0),e.clearColor(0,0,0,1),e.clear(e.COLOR_BUFFER_BIT)}else e.blendFunc(e.ONE,e.ONE_MINUS_SRC_ALPHA)}}},{\"../data/bucket\":311,\"../data/buffer\":316,\"../source/pixels_to_tile_units\":345,\"../source/source_cache\":349,\"../util/browser\":408,\"../util/struct_array\":422,\"../util/util\":424,\"./create_uniform_pragmas\":326,\"./draw_background\":327,\"./draw_circle\":328,\"./draw_debug\":330,\"./draw_fill\":331,\"./draw_line\":332,\"./draw_raster\":333,\"./draw_symbol\":334,\"./frame_history\":335,\"./painter/use_program\":338,\"./vertex_array_object\":339,\"gl-matrix\":177}],338:[function(t,e,r){\"use strict\";function n(t,e){return t.replace(/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,function(t,r,n,i,a){return e[r][a].replace(/{type}/g,i).replace(/{precision}/g,n)})}var i=t(\"assert\"),a=t(\"../../util/util\"),o=t(\"mapbox-gl-shaders\"),s=o.util;e.exports._createProgram=function(t,e,r,l){for(var u=this.gl,c=u.createProgram(),h=o[t],f=\"#define MAPBOX_GL_JS;\\n\",d=0;d<e.length;d++)f+=\"#define \"+e[d]+\";\\n\";var p=u.createShader(u.FRAGMENT_SHADER);u.shaderSource(p,n(f+h.fragmentSource,l)),u.compileShader(p),i(u.getShaderParameter(p,u.COMPILE_STATUS),u.getShaderInfoLog(p)),u.attachShader(c,p);var m=u.createShader(u.VERTEX_SHADER);u.shaderSource(m,n(f+s+h.vertexSource,r)),u.compileShader(m),i(u.getShaderParameter(m,u.COMPILE_STATUS),u.getShaderInfoLog(m)),u.attachShader(c,m),u.linkProgram(c),i(u.getProgramParameter(c,u.LINK_STATUS),u.getProgramInfoLog(c));for(var g={},v=u.getProgramParameter(c,u.ACTIVE_ATTRIBUTES),y=0;y<v;y++){var b=u.getActiveAttrib(c,y);g[b.name]=u.getAttribLocation(c,b.name)}for(var x={},_=u.getProgramParameter(c,u.ACTIVE_UNIFORMS),w=0;w<_;w++){var M=u.getActiveUniform(c,w);x[M.name]=u.getUniformLocation(c,M.name)}return a.extend({program:c,definition:h,attributes:g,numAttributes:v},g,x)},e.exports._createProgramCached=function(t,e,r,n){this.cache=this.cache||{};var i=JSON.stringify({name:t,defines:e,vertexPragmas:r,fragmentPragmas:n});return this.cache[i]||(this.cache[i]=this._createProgram(t,e,r,n)),this.cache[i]},e.exports.useProgram=function(t,e,r,n){var i=this.gl;e=e||[],this._showOverdrawInspector&&(e=e.concat(\"OVERDRAW_INSPECTOR\"));var a=this._createProgramCached(t,e,r,n);return this.currentProgram!==a&&(i.useProgram(a.program),this.currentProgram=a),a}},{\"../../util/util\":424,assert:40,\"mapbox-gl-shaders\":285}],339:[function(t,e,r){\"use strict\";function n(){this.boundProgram=null,this.boundVertexBuffer=null,this.boundVertexBuffer2=null,this.boundElementBuffer=null,this.vao=null}var i=t(\"assert\");e.exports=n,n.prototype.bind=function(t,e,r,n,i){void 0===t.extVertexArrayObject&&(t.extVertexArrayObject=t.getExtension(\"OES_vertex_array_object\"));var a=!this.vao||this.boundProgram!==e||this.boundVertexBuffer!==r||this.boundVertexBuffer2!==i||this.boundElementBuffer!==n;!t.extVertexArrayObject||a?this.freshBind(t,e,r,n,i):t.extVertexArrayObject.bindVertexArrayOES(this.vao)},n.prototype.freshBind=function(t,e,r,n,a){var o,s=e.numAttributes;if(t.extVertexArrayObject)this.vao&&this.destroy(t),this.vao=t.extVertexArrayObject.createVertexArrayOES(),t.extVertexArrayObject.bindVertexArrayOES(this.vao),o=0,this.boundProgram=e,this.boundVertexBuffer=r,this.boundVertexBuffer2=a,this.boundElementBuffer=n;else{o=t.currentNumAttributes||0;for(var l=s;l<o;l++)i(0!==l),t.disableVertexAttribArray(l)}for(var u=o;u<s;u++)t.enableVertexAttribArray(u);r.bind(t),r.setVertexAttribPointers(t,e),a&&(a.bind(t),a.setVertexAttribPointers(t,e)),n&&n.bind(t),t.currentNumAttributes=s},n.prototype.unbind=function(t){var e=t.extVertexArrayObject;e&&e.bindVertexArrayOES(null)},n.prototype.destroy=function(t){var e=t.extVertexArrayObject;e&&this.vao&&(e.deleteVertexArrayOES(this.vao),this.vao=null)}},{assert:40}],340:[function(t,e,r){\"use strict\";function n(t,e,r){e=e||{},this.id=t,this.dispatcher=r,this._data=e.data,void 0!==e.maxzoom&&(this.maxzoom=e.maxzoom),e.type&&(this.type=e.type);var n=s/this.tileSize;this.workerOptions=a.extend({source:this.id,cluster:e.cluster||!1,geojsonVtOptions:{buffer:(void 0!==e.buffer?e.buffer:128)*n,tolerance:(void 0!==e.tolerance?e.tolerance:.375)*n,extent:s,maxZoom:this.maxzoom},superclusterOptions:{maxZoom:Math.min(e.clusterMaxZoom,this.maxzoom-1)||this.maxzoom-1,extent:s,radius:(e.clusterRadius||50)*n,log:!1}},e.workerOptions),this._updateWorkerData(function(t){t?this.fire(\"error\",{error:t}):this.fire(\"load\")}.bind(this))}var i=t(\"../util/evented\"),a=t(\"../util/util\"),o=t(\"resolve-url\"),s=t(\"../data/bucket\").EXTENT;e.exports=n,n.prototype=a.inherit(i,{type:\"geojson\",minzoom:0,maxzoom:18,tileSize:512,isTileClipped:!0,reparseOverscaled:!0,onAdd:function(t){this.map=t},setData:function(t){return this._data=t,this._updateWorkerData(function(t){if(t)return this.fire(\"error\",{error:t});this.fire(\"change\")}.bind(this)),this},_updateWorkerData:function(t){var e=a.extend({},this.workerOptions),r=this._data;\"string\"==typeof r?e.url=\"undefined\"!=typeof window?o(window.location.href,r):r:e.data=JSON.stringify(r),this.workerID=this.dispatcher.send(this.type+\".loadData\",e,function(e){this._loaded=!0,t(e)}.bind(this))},loadTile:function(t,e){var r=t.coord.z>this.maxzoom?Math.pow(2,t.coord.z-this.maxzoom):1,n={type:this.type,uid:t.uid,coord:t.coord,zoom:t.coord.z,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,overscaling:r,angle:this.map.transform.angle,pitch:this.map.transform.pitch,showCollisionBoxes:this.map.showCollisionBoxes};t.workerID=this.dispatcher.send(\"load tile\",n,function(r,n){if(t.unloadVectorData(this.map.painter),!t.aborted)return r?e(r):(t.loadVectorData(n,this.map.style),t.redoWhenDone&&(t.redoWhenDone=!1,t.redoPlacement(this)),e(null))}.bind(this),this.workerID)},abortTile:function(t){t.aborted=!0},unloadTile:function(t){t.unloadVectorData(this.map.painter),this.dispatcher.send(\"remove tile\",{uid:t.uid,source:this.id},function(){},t.workerID)},serialize:function(){return{type:this.type,data:this._data}}})},{\"../data/bucket\":311,\"../util/evented\":416,\"../util/util\":424,\"resolve-url\":482}],341:[function(t,e,r){\"use strict\";function n(t,e,r){r&&(this.loadGeoJSON=r),h.call(this,t,e)}var i=t(\"../util/util\"),a=t(\"../util/ajax\"),o=t(\"geojson-rewind\"),s=t(\"./geojson_wrapper\"),l=t(\"vt-pbf\"),u=t(\"supercluster\"),c=t(\"geojson-vt\"),h=t(\"./vector_tile_worker_source\");e.exports=n,n.prototype=i.inherit(h,{_geoJSONIndexes:{},loadVectorData:function(t,e){var r=t.source,n=t.coord;if(!this._geoJSONIndexes[r])return e(null,null);var i=this._geoJSONIndexes[r].getTile(Math.min(n.z,t.maxZoom),n.x,n.y);if(!i)return e(null,null);var a=new s(i.features);a.name=\"_geojsonTileLayer\";var o=l({layers:{_geojsonTileLayer:a}});0===o.byteOffset&&o.byteLength===o.buffer.byteLength||(o=new Uint8Array(o)),e(null,{tile:a,rawTileData:o.buffer})},loadData:function(t,e){var r=function(r,n){return r?e(r):\"object\"!=typeof n?e(new Error(\"Input data is not a valid GeoJSON object.\")):(o(n,!0),void this._indexData(n,t,function(r,n){if(r)return e(r);this._geoJSONIndexes[t.source]=n,e(null)}.bind(this)))}.bind(this);this.loadGeoJSON(t,r)},loadGeoJSON:function(t,e){if(t.url)a.getJSON(t.url,e);else{if(\"string\"!=typeof t.data)return e(new Error(\"Input data is not a valid GeoJSON object.\"));try{return e(null,JSON.parse(t.data))}catch(t){return e(new Error(\"Input data is not a valid GeoJSON object.\"))}}},_indexData:function(t,e,r){try{e.cluster?r(null,u(e.superclusterOptions).load(t.features)):r(null,c(t,e.geojsonVtOptions))}catch(t){return r(t)}}})},{\"../util/ajax\":407,\"../util/util\":424,\"./geojson_wrapper\":342,\"./vector_tile_worker_source\":353,\"geojson-rewind\":123,\"geojson-vt\":127,supercluster:509,\"vt-pbf\":536}],342:[function(t,e,r){\"use strict\";function n(t){this.features=t,this.length=t.length,this.extent=s}function i(t){if(this.type=t.type,1===t.type){this.rawGeometry=[];for(var e=0;e<t.geometry.length;e++)this.rawGeometry.push([t.geometry[e]])}else this.rawGeometry=t.geometry;this.properties=t.tags,this.extent=s}var a=t(\"point-geometry\"),o=t(\"vector-tile\").VectorTileFeature,s=t(\"../data/bucket\").EXTENT;e.exports=n,n.prototype.feature=function(t){return new i(this.features[t])},i.prototype.loadGeometry=function(){var t=this.rawGeometry;this.geometry=[];for(var e=0;e<t.length;e++){for(var r=t[e],n=[],i=0;i<r.length;i++)n.push(new a(r[i][0],r[i][1]));this.geometry.push(n)}return this.geometry},i.prototype.bbox=function(){this.geometry||this.loadGeometry();for(var t=this.geometry,e=1/0,r=-1/0,n=1/0,i=-1/0,a=0;a<t.length;a++)for(var o=t[a],s=0;s<o.length;s++){var l=o[s];e=Math.min(e,l.x),r=Math.max(r,l.x),n=Math.min(n,l.y),i=Math.max(i,l.y)}return[e,n,r,i]},i.prototype.toGeoJSON=o.prototype.toGeoJSON},{\"../data/bucket\":311,\"point-geometry\":465,\"vector-tile\":530}],343:[function(t,e,r){\"use strict\";function n(t,e,r){this.id=t,this.dispatcher=r,this.url=e.url,this.coordinates=e.coordinates,u.getImage(e.url,function(t,r){if(t)return this.fire(\"error\",{error:t});this.image=r,this.image.addEventListener(\"load\",function(){this.map._rerender()}.bind(this)),this._loaded=!0,this.fire(\"load\"),this.map&&this.setCoordinates(e.coordinates)}.bind(this))}var i=t(\"../util/util\"),a=t(\"./tile_coord\"),o=t(\"../geo/lng_lat\"),s=t(\"point-geometry\"),l=t(\"../util/evented\"),u=t(\"../util/ajax\"),c=t(\"../data/bucket\").EXTENT,h=t(\"../render/draw_raster\").RasterBoundsArray,f=t(\"../data/buffer\"),d=t(\"../render/vertex_array_object\");e.exports=n,n.prototype=i.inherit(l,{minzoom:0,maxzoom:22,tileSize:512,onAdd:function(t){this.map=t,this.image&&this.setCoordinates(this.coordinates)},setCoordinates:function(t){this.coordinates=t;var e=this.map,r=t.map(function(t){return e.transform.locationCoordinate(o.convert(t)).zoomTo(0)}),n=this.centerCoord=i.getCoordinatesCenter(r);return n.column=Math.round(n.column),n.row=Math.round(n.row),this.minzoom=this.maxzoom=n.zoom,this._coord=new a(n.zoom,n.column,n.row),this._tileCoords=r.map(function(t){var e=t.zoomTo(n.zoom);return new s(Math.round((e.column-n.column)*c),Math.round((e.row-n.row)*c))}),this.fire(\"change\"),this},_setTile:function(t){this._prepared=!1,this.tile=t;var e=new h;e.emplaceBack(this._tileCoords[0].x,this._tileCoords[0].y,0,0),e.emplaceBack(this._tileCoords[1].x,this._tileCoords[1].y,32767,0),e.emplaceBack(this._tileCoords[3].x,this._tileCoords[3].y,0,32767),e.emplaceBack(this._tileCoords[2].x,this._tileCoords[2].y,32767,32767),this.tile.buckets={},this.tile.boundsBuffer=new f(e.serialize(),h.serialize(),f.BufferType.VERTEX),this.tile.boundsVAO=new d,this.tile.state=\"loaded\"},prepare:function(){if(this._loaded&&this.image&&this.image.complete&&this.tile){var t=this.map.painter.gl;this._prepared?(t.bindTexture(t.TEXTURE_2D,this.tile.texture),t.texSubImage2D(t.TEXTURE_2D,0,0,0,t.RGBA,t.UNSIGNED_BYTE,this.image)):(this.tile.texture=t.createTexture(),t.bindTexture(t.TEXTURE_2D,this.tile.texture),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),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.LINEAR),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.LINEAR),t.texImage2D(t.TEXTURE_2D,0,t.RGBA,t.RGBA,t.UNSIGNED_BYTE,this.image))}},loadTile:function(t,e){this._coord&&this._coord.toString()===t.coord.toString()?(this._setTile(t),e(null)):(t.state=\"errored\",e(null))},serialize:function(){return{type:\"image\",urls:this.url,coordinates:this.coordinates}}})},{\"../data/bucket\":311,\"../data/buffer\":316,\"../geo/lng_lat\":321,\"../render/draw_raster\":333,\"../render/vertex_array_object\":339,\"../util/ajax\":407,\"../util/evented\":416,\"../util/util\":424,\"./tile_coord\":351,\"point-geometry\":465}],344:[function(t,e,r){\"use strict\";var n=t(\"../util/util\"),i=t(\"../util/ajax\"),a=t(\"../util/browser\"),o=t(\"../util/mapbox\").normalizeSourceURL;e.exports=function(t,e){var r=function(t,r){if(t)return e(t);var i=n.pick(r,[\"tiles\",\"minzoom\",\"maxzoom\",\"attribution\"]);r.vector_layers&&(i.vectorLayers=r.vector_layers,i.vectorLayerIds=i.vectorLayers.map(function(t){return t.id})),e(null,i)};t.url?i.getJSON(o(t.url),r):a.frame(r.bind(null,null,t))}},{\"../util/ajax\":407,\"../util/browser\":408,\"../util/mapbox\":421,\"../util/util\":424}],345:[function(t,e,r){\"use strict\";var n=t(\"../data/bucket\");e.exports=function(t,e,r){return e*(n.EXTENT/(t.tileSize*Math.pow(2,r-t.coord.z)))}},{\"../data/bucket\":311}],346:[function(t,e,r){\"use strict\";function n(t,e){var r=t.coord,n=e.coord;return r.z-n.z||r.y-n.y||r.w-n.w||r.x-n.x}function i(t){for(var e=t[0]||{},r=1;r<t.length;r++){var n=t[r];for(var i in n){var a=n[i],o=e[i];if(void 0===o)o=e[i]=a;else for(var s=0;s<a.length;s++)o.push(a[s])}}return e}var a=t(\"./tile_coord\");r.rendered=function(t,e,r,a,o,s){var l=t.tilesIn(r);l.sort(n);for(var u=[],c=0;c<l.length;c++){var h=l[c];h.tile.featureIndex&&u.push(h.tile.featureIndex.query({queryGeometry:h.queryGeometry,scale:h.scale,tileSize:h.tile.tileSize,bearing:s,params:a},e))}return i(u)},r.source=function(t,e){for(var r=t.getRenderableIds().map(function(e){return t.getTileByID(e)}),n=[],i={},o=0;o<r.length;o++){var s=r[o],l=new a(Math.min(s.sourceMaxZoom,s.coord.z),s.coord.x,s.coord.y,0).id;i[l]||(i[l]=!0,s.querySourceFeatures(n,e))}return n}},{\"./tile_coord\":351}],347:[function(t,e,r){\"use strict\";function n(t,e,r){this.id=t,this.dispatcher=r,i.extend(this,i.pick(e,[\"url\",\"scheme\",\"tileSize\"])),s(e,function(t,e){if(t)return this.fire(\"error\",t);i.extend(this,e),this.fire(\"load\")}.bind(this))}var i=t(\"../util/util\"),a=t(\"../util/ajax\"),o=t(\"../util/evented\"),s=t(\"./load_tilejson\"),l=t(\"../util/mapbox\").normalizeTileURL;e.exports=n,n.prototype=i.inherit(o,{minzoom:0,maxzoom:22,roundZoom:!0,scheme:\"xyz\",tileSize:512,_loaded:!1,onAdd:function(t){this.map=t},serialize:function(){return{type:\"raster\",url:this.url,tileSize:this.tileSize}},loadTile:function(t,e){function r(r,n){if(delete t.request,!t.aborted){if(r)return e(r);var i=this.map.painter.gl;t.texture=this.map.painter.getTexture(n.width),t.texture?(i.bindTexture(i.TEXTURE_2D,t.texture),i.texSubImage2D(i.TEXTURE_2D,0,0,0,i.RGBA,i.UNSIGNED_BYTE,n)):(t.texture=i.createTexture(),i.bindTexture(i.TEXTURE_2D,t.texture),i.texParameteri(i.TEXTURE_2D,i.TEXTURE_MIN_FILTER,i.LINEAR_MIPMAP_NEAREST),i.texParameteri(i.TEXTURE_2D,i.TEXTURE_MAG_FILTER,i.LINEAR),i.texParameteri(i.TEXTURE_2D,i.TEXTURE_WRAP_S,i.CLAMP_TO_EDGE),i.texParameteri(i.TEXTURE_2D,i.TEXTURE_WRAP_T,i.CLAMP_TO_EDGE),i.pixelStorei(i.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!0),i.texImage2D(i.TEXTURE_2D,0,i.RGBA,i.RGBA,i.UNSIGNED_BYTE,n),t.texture.size=n.width),i.generateMipmap(i.TEXTURE_2D),this.map.animationLoop.set(this.map.style.rasterFadeDuration),t.state=\"loaded\",e(null)}}var n=l(t.coord.url(this.tiles,null,this.scheme),this.url,this.tileSize);t.request=a.getImage(n,r.bind(this))},abortTile:function(t){t.request&&(t.request.abort(),delete t.request)},unloadTile:function(t){t.texture&&this.map.painter.saveTexture(t.texture)}})},{\"../util/ajax\":407,\"../util/evented\":416,\"../util/mapbox\":421,\"../util/util\":424,\"./load_tilejson\":344}],348:[function(t,e,r){\"use strict\";var n=t(\"../util/util\"),i={vector:t(\"../source/vector_tile_source\"),raster:t(\"../source/raster_tile_source\"),geojson:t(\"../source/geojson_source\"),video:t(\"../source/video_source\"),image:t(\"../source/image_source\")};r.create=function(t,e,r){if((e=new i[e.type](t,e,r)).id!==t)throw new Error(\"Expected Source id to be \"+t+\" instead of \"+e.id);return n.bindAll([\"load\",\"abort\",\"unload\",\"serialize\",\"prepare\"],e),e},r.getType=function(t){return i[t]},r.setType=function(t,e){i[t]=e}},{\"../source/geojson_source\":340,\"../source/image_source\":343,\"../source/raster_tile_source\":347,\"../source/vector_tile_source\":352,\"../source/video_source\":354,\"../util/util\":424}],349:[function(t,e,r){\"use strict\";function n(t,e,r){this.id=t,this.dispatcher=r;var n=this._source=o.create(t,e,r).on(\"load\",function(){this.map&&this._source.onAdd&&this._source.onAdd(this.map),this._sourceLoaded=!0,this.tileSize=n.tileSize,this.minzoom=n.minzoom,this.maxzoom=n.maxzoom,this.roundZoom=n.roundZoom,this.reparseOverscaled=n.reparseOverscaled,this.isTileClipped=n.isTileClipped,this.attribution=n.attribution,this.vectorLayerIds=n.vectorLayerIds,this.fire(\"load\")}.bind(this)).on(\"error\",function(t){this._sourceErrored=!0,this.fire(\"error\",t)}.bind(this)).on(\"change\",function(){this.reload(),this.transform&&this.update(this.transform,this.map&&this.map.style.rasterFadeDuration),this.fire(\"change\")}.bind(this));this._tiles={},this._cache=new c(0,this.unloadTile.bind(this)),this._isIdRenderable=this._isIdRenderable.bind(this)}function i(t,e,r){var n=r.zoomTo(Math.min(t.z,e));return{x:(n.column-(t.x+t.w*Math.pow(2,t.z)))*d,y:(n.row-t.y)*d}}function a(t,e){return t%32-e%32}var o=t(\"./source\"),s=t(\"./tile\"),l=t(\"../util/evented\"),u=t(\"./tile_coord\"),c=t(\"../util/lru_cache\"),h=t(\"../geo/coordinate\"),f=t(\"../util/util\"),d=t(\"../data/bucket\").EXTENT;e.exports=n,n.maxOverzooming=10,n.maxUnderzooming=3,n.prototype=f.inherit(l,{onAdd:function(t){this.map=t,this._source&&this._source.onAdd&&this._source.onAdd(t)},loaded:function(){if(this._sourceErrored)return!0;if(!this._sourceLoaded)return!1;for(var t in this._tiles){var e=this._tiles[t];if(\"loaded\"!==e.state&&\"errored\"!==e.state)return!1}return!0},getSource:function(){return this._source},loadTile:function(t,e){return this._source.loadTile(t,e)},unloadTile:function(t){if(this._source.unloadTile)return this._source.unloadTile(t)},abortTile:function(t){if(this._source.abortTile)return this._source.abortTile(t)},serialize:function(){return this._source.serialize()},prepare:function(){if(this._sourceLoaded&&this._source.prepare)return this._source.prepare()},getIds:function(){return Object.keys(this._tiles).map(Number).sort(a)},getRenderableIds:function(){return this.getIds().filter(this._isIdRenderable)},_isIdRenderable:function(t){return this._tiles[t].isRenderable()&&!this._coveredTiles[t]},reload:function(){this._cache.reset();for(var t in this._tiles){var e=this._tiles[t];\"loading\"!==e.state&&(e.state=\"reloading\"),this.loadTile(this._tiles[t],this._tileLoaded.bind(this,this._tiles[t]))}},_tileLoaded:function(t,e){if(e)return t.state=\"errored\",this.fire(\"tile.error\",{tile:t,error:e}),void this._source.fire(\"tile.error\",{tile:t,error:e});t.source=this,t.timeAdded=(new Date).getTime(),this.fire(\"tile.load\",{tile:t}),this._source.fire(\"tile.load\",{tile:t})},getTile:function(t){return this.getTileByID(t.id)},getTileByID:function(t){return this._tiles[t]},getZoom:function(t){return t.zoom+t.scaleZoom(t.tileSize/this.tileSize)},findLoadedChildren:function(t,e,r){var n=!1;for(var i in this._tiles){var a=this._tiles[i];if(!(r[i]||!a.isRenderable()||a.coord.z<=t.z||a.coord.z>e)){var o=Math.pow(2,Math.min(a.coord.z,this.maxzoom)-Math.min(t.z,this.maxzoom));if(Math.floor(a.coord.x/o)===t.x&&Math.floor(a.coord.y/o)===t.y)for(r[i]=!0,n=!0;a&&a.coord.z-1>t.z;){var s=a.coord.parent(this.maxzoom).id;(a=this._tiles[s])&&a.isRenderable()&&(delete r[i],r[s]=!0)}}}return n},findLoadedParent:function(t,e,r){for(var n=t.z-1;n>=e;n--){t=t.parent(this.maxzoom);var i=this._tiles[t.id];if(i&&i.isRenderable())return r[t.id]=!0,i;if(this._cache.has(t.id))return this.addTile(t),r[t.id]=!0,this._tiles[t.id]}},updateCacheSize:function(t){var e=(Math.ceil(t.width/t.tileSize)+1)*(Math.ceil(t.height/t.tileSize)+1);this._cache.setMaxSize(Math.floor(5*e))},update:function(t,e){if(this._sourceLoaded){var r,i,a;this.updateCacheSize(t);var o=(this.roundZoom?Math.round:Math.floor)(this.getZoom(t)),s=Math.max(o-n.maxOverzooming,this.minzoom),l=Math.max(o+n.maxUnderzooming,this.minzoom),c={},h=(new Date).getTime();this._coveredTiles={};var d=this.used?t.coveringTiles(this._source):[];for(r=0;r<d.length;r++)i=d[r],a=this.addTile(i),c[i.id]=!0,a.isRenderable()||this.findLoadedChildren(i,l,c)||this.findLoadedParent(i,s,c);for(var p={},m=Object.keys(c),g=0;g<m.length;g++){var v=m[g];i=u.fromID(v),(a=this._tiles[v])&&a.timeAdded>h-(e||0)&&(this.findLoadedChildren(i,l,c)&&(c[v]=!0),this.findLoadedParent(i,s,p))}var y;for(y in p)c[y]||(this._coveredTiles[y]=!0);for(y in p)c[y]=!0;var b=f.keysDifference(this._tiles,c);for(r=0;r<b.length;r++)this.removeTile(+b[r]);this.transform=t}},addTile:function(t){var e=this._tiles[t.id];if(e)return e;var r=t.wrapped();if((e=this._tiles[r.id])||(e=this._cache.get(r.id))&&this._redoPlacement&&this._redoPlacement(e),!e){var n=t.z,i=n>this.maxzoom?Math.pow(2,n-this.maxzoom):1;e=new s(r,this.tileSize*i,this.maxzoom),this.loadTile(e,this._tileLoaded.bind(this,e))}return e.uses++,this._tiles[t.id]=e,this.fire(\"tile.add\",{tile:e}),this._source.fire(\"tile.add\",{tile:e}),e},removeTile:function(t){var e=this._tiles[t];e&&(e.uses--,delete this._tiles[t],this.fire(\"tile.remove\",{tile:e}),this._source.fire(\"tile.remove\",{tile:e}),e.uses>0||(e.isRenderable()?this._cache.add(e.coord.wrapped().id,e):(e.aborted=!0,this.abortTile(e),this.unloadTile(e))))},clearTiles:function(){for(var t in this._tiles)this.removeTile(t);this._cache.reset()},tilesIn:function(t){for(var e={},r=this.getIds(),n=1/0,a=1/0,o=-1/0,s=-1/0,l=t[0].zoom,c=0;c<t.length;c++){var f=t[c];n=Math.min(n,f.column),a=Math.min(a,f.row),o=Math.max(o,f.column),s=Math.max(s,f.row)}for(var p=0;p<r.length;p++){var m=this._tiles[r[p]],g=u.fromID(r[p]),v=[i(g,m.sourceMaxZoom,new h(n,a,l)),i(g,m.sourceMaxZoom,new h(o,s,l))];if(v[0].x<d&&v[0].y<d&&v[1].x>=0&&v[1].y>=0){for(var y=[],b=0;b<t.length;b++)y.push(i(g,m.sourceMaxZoom,t[b]));var x=e[m.coord.id];void 0===x&&(x=e[m.coord.id]={tile:m,coord:g,queryGeometry:[],scale:Math.pow(2,this.transform.zoom-m.coord.z)}),x.queryGeometry.push(y)}}var _=[];for(var w in e)_.push(e[w]);return _},redoPlacement:function(){for(var t=this.getIds(),e=0;e<t.length;e++)this.getTileByID(t[e]).redoPlacement(this)},getVisibleCoordinates:function(){return this.getRenderableIds().map(u.fromID)}})},{\"../data/bucket\":311,\"../geo/coordinate\":320,\"../util/evented\":416,\"../util/lru_cache\":420,\"../util/util\":424,\"./source\":348,\"./tile\":350,\"./tile_coord\":351}],350:[function(t,e,r){\"use strict\";function n(t,e,r){this.coord=t,this.uid=a.uniqueId(),this.uses=0,this.tileSize=e,this.sourceMaxZoom=r,this.buckets={},this.state=\"loading\"}function i(t,e){if(e){for(var r={},n=0;n<t.length;n++){var i=e.getLayer(t[n].layerId);if(i){var s=o.create(a.extend({layer:i,childLayers:t[n].childLayerIds.map(e.getLayer.bind(e)).filter(function(t){return t})},t[n]));r[s.id]=s}}return r}}var a=t(\"../util/util\"),o=t(\"../data/bucket\"),s=t(\"../data/feature_index\"),l=t(\"vector-tile\"),u=t(\"pbf\"),c=t(\"../util/vectortile_to_geojson\"),h=t(\"feature-filter\"),f=t(\"../symbol/collision_tile\"),d=t(\"../symbol/collision_box\"),p=t(\"../symbol/symbol_instances\"),m=t(\"../symbol/symbol_quads\");e.exports=n,n.prototype={loadVectorData:function(t,e){this.state=\"loaded\",t&&(this.collisionBoxArray=new d(t.collisionBoxArray),this.collisionTile=new f(t.collisionTile,this.collisionBoxArray),this.symbolInstancesArray=new p(t.symbolInstancesArray),this.symbolQuadsArray=new m(t.symbolQuadsArray),this.featureIndex=new s(t.featureIndex,t.rawTileData,this.collisionTile),this.rawTileData=t.rawTileData,this.buckets=i(t.buckets,e))},reloadSymbolData:function(t,e,r){if(\"unloaded\"!==this.state){this.collisionTile=new f(t.collisionTile,this.collisionBoxArray),this.featureIndex.setCollisionTile(this.collisionTile);for(var n in this.buckets){var o=this.buckets[n];\"symbol\"===o.type&&(o.destroy(e.gl),delete this.buckets[n])}a.extend(this.buckets,i(t.buckets,r))}},unloadVectorData:function(t){for(var e in this.buckets)this.buckets[e].destroy(t.gl);this.collisionBoxArray=null,this.symbolQuadsArray=null,this.symbolInstancesArray=null,this.collisionTile=null,this.featureIndex=null,this.rawTileData=null,this.buckets=null,this.state=\"unloaded\"},redoPlacement:function(t){function e(e,r){this.reloadSymbolData(r,t.map.painter,t.map.style),t.fire(\"tile.load\",{tile:this}),this.state=\"loaded\",this.redoWhenDone&&(this.redoPlacement(t),this.redoWhenDone=!1)}\"loaded\"===this.state&&\"reloading\"!==this.state?(this.state=\"reloading\",t.dispatcher.send(\"redo placement\",{uid:this.uid,source:t.id,angle:t.map.transform.angle,pitch:t.map.transform.pitch,showCollisionBoxes:t.map.showCollisionBoxes},e.bind(this),this.workerID)):this.redoWhenDone=!0},getBucket:function(t){return this.buckets&&this.buckets[t.ref||t.id]},querySourceFeatures:function(t,e){if(this.rawTileData){this.vtLayers||(this.vtLayers=new l.VectorTile(new u(new Uint8Array(this.rawTileData))).layers);var r=this.vtLayers._geojsonTileLayer||this.vtLayers[e.sourceLayer];if(r)for(var n=h(e.filter),i={z:this.coord.z,x:this.coord.x,y:this.coord.y},a=0;a<r.length;a++){var o=r.feature(a);if(n(o)){var s=new c(o,this.coord.z,this.coord.x,this.coord.y);s.tile=i,t.push(s)}}}},isRenderable:function(){return\"loaded\"===this.state||\"reloading\"===this.state}}},{\"../data/bucket\":311,\"../data/feature_index\":318,\"../symbol/collision_box\":376,\"../symbol/collision_tile\":378,\"../symbol/symbol_instances\":387,\"../symbol/symbol_quads\":388,\"../util/util\":424,\"../util/vectortile_to_geojson\":425,\"feature-filter\":117,pbf:459,\"vector-tile\":530}],351:[function(t,e,r){\"use strict\";function n(t,e,r,n){l(!isNaN(t)&&t>=0&&t%1==0),l(!isNaN(e)&&e>=0&&e%1==0),l(!isNaN(r)&&r>=0&&r%1==0),isNaN(n)&&(n=0),this.z=+t,this.x=+e,this.y=+r,this.w=+n,(n*=2)<0&&(n=-1*n-1);var i=1<<this.z;this.id=32*(i*i*n+i*this.y+this.x)+this.z,this.posMatrix=null}function i(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}function a(t,e){if(t.row>e.row){var r=t;t=e,e=r}return{x0:t.column,y0:t.row,x1:e.column,y1:e.row,dx:e.column-t.column,dy:e.row-t.row}}function o(t,e,r,n,i){var a=Math.max(r,Math.floor(e.y0)),o=Math.min(n,Math.ceil(e.y1));if(t.x0===e.x0&&t.y0===e.y0?t.x0+e.dy/t.dy*t.dx<e.x1:t.x1-e.dy/t.dy*t.dx<e.x0){var s=t;t=e,e=s}for(var l=t.dx/t.dy,u=e.dx/e.dy,c=t.dx>0,h=e.dx<0,f=a;f<o;f++){var d=l*Math.max(0,Math.min(t.dy,f+c-t.y0))+t.x0,p=u*Math.max(0,Math.min(e.dy,f+h-e.y0))+e.x0;i(Math.floor(p),Math.ceil(d),f)}}function s(t,e,r,n,i,s){var l,u=a(t,e),c=a(e,r),h=a(r,t);u.dy>c.dy&&(l=u,u=c,c=l),u.dy>h.dy&&(l=u,u=h,h=l),c.dy>h.dy&&(l=c,c=h,h=l),u.dy&&o(h,u,n,i,s),c.dy&&o(h,c,n,i,s)}var l=t(\"assert\"),u=t(\"whoots-js\"),c=t(\"../geo/coordinate\");e.exports=n,n.prototype.toString=function(){return this.z+\"/\"+this.x+\"/\"+this.y},n.prototype.toCoordinate=function(t){var e=Math.min(this.z,t),r=Math.pow(2,e),n=this.y,i=this.x+r*this.w;return new c(i,n,e)},n.fromID=function(t){var e=t%32,r=1<<e,i=(t-e)/32,a=i%r,o=(i-a)/r%r,s=Math.floor(i/(r*r));return s%2!=0&&(s=-1*s-1),s/=2,new n(e,a,o,s)},n.prototype.url=function(t,e,r){var n=u.getTileBBox(this.x,this.y,this.z),a=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}\",Math.min(this.z,e||this.z)).replace(\"{x}\",this.x).replace(\"{y}\",\"tms\"===r?Math.pow(2,this.z)-this.y-1:this.y).replace(\"{quadkey}\",a).replace(\"{bbox-epsg-3857}\",n)},n.prototype.parent=function(t){return 0===this.z?null:this.z>t?new n(this.z-1,this.x,this.y,this.w):new n(this.z-1,Math.floor(this.x/2),Math.floor(this.y/2),this.w)},n.prototype.wrapped=function(){return new n(this.z,this.x,this.y,0)},n.prototype.children=function(t){if(this.z>=t)return[new n(this.z+1,this.x,this.y,this.w)];var e=this.z+1,r=2*this.x,i=2*this.y;return[new n(e,r,i,this.w),new n(e,r+1,i,this.w),new n(e,r,i+1,this.w),new n(e,r+1,i+1,this.w)]},n.cover=function(t,e,r){function i(t,e,i){var s,l;if(i>=0&&i<=a)for(s=t;s<e;s++)l=new n(r,(s%a+a)%a,i,Math.floor(s/a)),o[l.id]=l}var a=1<<t,o={};return s(e[0],e[1],e[2],0,a,i),s(e[2],e[3],e[0],0,a,i),Object.keys(o).map(function(t){return o[t]})}},{\"../geo/coordinate\":320,assert:40,\"whoots-js\":546}],352:[function(t,e,r){\"use strict\";function n(t,e,r){if(this.id=t,this.dispatcher=r,a.extend(this,a.pick(e,[\"url\",\"scheme\",\"tileSize\"])),this._options=a.extend({type:\"vector\"},e),512!==this.tileSize)throw new Error(\"vector tile sources must have a tileSize of 512\");o(e,function(t,e){t?this.fire(\"error\",t):(a.extend(this,e),this.fire(\"load\"))}.bind(this))}var i=t(\"../util/evented\"),a=t(\"../util/util\"),o=t(\"./load_tilejson\"),s=t(\"../util/mapbox\").normalizeTileURL;e.exports=n,n.prototype=a.inherit(i,{minzoom:0,maxzoom:22,scheme:\"xyz\",tileSize:512,reparseOverscaled:!0,isTileClipped:!0,onAdd:function(t){this.map=t},serialize:function(){return a.extend({},this._options)},loadTile:function(t,e){function r(r,n){if(!t.aborted){if(r)return e(r);t.loadVectorData(n,this.map.style),t.redoWhenDone&&(t.redoWhenDone=!1,t.redoPlacement(this)),e(null),t.reloadCallback&&(this.loadTile(t,t.reloadCallback),t.reloadCallback=null)}}var n=t.coord.z>this.maxzoom?Math.pow(2,t.coord.z-this.maxzoom):1,i={url:s(t.coord.url(this.tiles,this.maxzoom,this.scheme),this.url),uid:t.uid,coord:t.coord,zoom:t.coord.z,tileSize:this.tileSize*n,source:this.id,overscaling:n,angle:this.map.transform.angle,pitch:this.map.transform.pitch,showCollisionBoxes:this.map.showCollisionBoxes};t.workerID?\"loading\"===t.state?t.reloadCallback=e:(i.rawTileData=t.rawTileData,this.dispatcher.send(\"reload tile\",i,r.bind(this),t.workerID)):t.workerID=this.dispatcher.send(\"load tile\",i,r.bind(this))},abortTile:function(t){this.dispatcher.send(\"abort tile\",{uid:t.uid,source:this.id},null,t.workerID)},unloadTile:function(t){t.unloadVectorData(this.map.painter),this.dispatcher.send(\"remove tile\",{uid:t.uid,source:this.id},null,t.workerID)}})},{\"../util/evented\":416,\"../util/mapbox\":421,\"../util/util\":424,\"./load_tilejson\":344}],353:[function(t,e,r){\"use strict\";function n(t,e,r){this.actor=t,this.styleLayers=e,r&&(this.loadVectorData=r),this.loading={},this.loaded={}}var i=t(\"../util/ajax\"),a=t(\"vector-tile\"),o=t(\"pbf\"),s=t(\"./worker_tile\");e.exports=n,n.prototype={loadTile:function(t,e){function r(t,r){return delete this.loading[n][i],t?e(t):r?(a.data=r.tile,a.parse(a.data,this.styleLayers.getLayerFamilies(),this.actor,r.rawTileData,e),this.loaded[n]=this.loaded[n]||{},void(this.loaded[n][i]=a)):e(null,null)}var n=t.source,i=t.uid;this.loading[n]||(this.loading[n]={});var a=this.loading[n][i]=new s(t);a.abort=this.loadVectorData(t,r.bind(this))},reloadTile:function(t,e){var r=this.loaded[t.source],n=t.uid;if(r&&r[n]){var i=r[n];i.parse(i.data,this.styleLayers.getLayerFamilies(),this.actor,t.rawTileData,e)}},abortTile:function(t){var e=this.loading[t.source],r=t.uid;e&&e[r]&&e[r].abort&&(e[r].abort(),delete e[r])},removeTile:function(t){var e=this.loaded[t.source],r=t.uid;e&&e[r]&&delete e[r]},loadVectorData:function(t,e){function r(t,r){if(t)return e(t);var n=new a.VectorTile(new o(new Uint8Array(r)));e(t,{tile:n,rawTileData:r})}var n=i.getArrayBuffer(t.url,r.bind(this));return function(){n.abort()}},redoPlacement:function(t,e){var r=this.loaded[t.source],n=this.loading[t.source],i=t.uid;if(r&&r[i]){var a=r[i].redoPlacement(t.angle,t.pitch,t.showCollisionBoxes);a.result&&e(null,a.result,a.transferables)}else n&&n[i]&&(n[i].angle=t.angle)}}},{\"../util/ajax\":407,\"./worker_tile\":356,pbf:459,\"vector-tile\":530}],354:[function(t,e,r){\"use strict\";function n(t,e){this.id=t,this.urls=e.urls,this.coordinates=e.coordinates,u.getVideo(e.urls,function(t,r){if(t)return this.fire(\"error\",{error:t});this.video=r,this.video.loop=!0;var n;this.video.addEventListener(\"playing\",function(){n=this.map.style.animationLoop.set(1/0),this.map._rerender()}.bind(this)),this.video.addEventListener(\"pause\",function(){this.map.style.animationLoop.cancel(n)}.bind(this)),this.map&&(this.video.play(),this.setCoordinates(e.coordinates)),this.fire(\"load\")}.bind(this))}var i=t(\"../util/util\"),a=t(\"./tile_coord\"),o=t(\"../geo/lng_lat\"),s=t(\"point-geometry\"),l=t(\"../util/evented\"),u=t(\"../util/ajax\"),c=t(\"../data/bucket\").EXTENT,h=t(\"../render/draw_raster\").RasterBoundsArray,f=t(\"../data/buffer\"),d=t(\"../render/vertex_array_object\");e.exports=n,n.prototype=i.inherit(l,{minzoom:0,maxzoom:22,tileSize:512,roundZoom:!0,getVideo:function(){return this.video},onAdd:function(t){this.map||(this.map=t,this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},setCoordinates:function(t){this.coordinates=t;var e=this.map,r=t.map(function(t){return e.transform.locationCoordinate(o.convert(t)).zoomTo(0)}),n=this.centerCoord=i.getCoordinatesCenter(r);return n.column=Math.round(n.column),n.row=Math.round(n.row),this.minzoom=this.maxzoom=n.zoom,this._coord=new a(n.zoom,n.column,n.row),this._tileCoords=r.map(function(t){var e=t.zoomTo(n.zoom);return new s(Math.round((e.column-n.column)*c),Math.round((e.row-n.row)*c))}),this.fire(\"change\"),this},_setTile:function(t){this._prepared=!1,this.tile=t;var e=new h;e.emplaceBack(this._tileCoords[0].x,this._tileCoords[0].y,0,0),e.emplaceBack(this._tileCoords[1].x,this._tileCoords[1].y,32767,0),e.emplaceBack(this._tileCoords[3].x,this._tileCoords[3].y,0,32767),e.emplaceBack(this._tileCoords[2].x,this._tileCoords[2].y,32767,32767),this.tile.buckets={},this.tile.boundsBuffer=new f(e.serialize(),h.serialize(),f.BufferType.VERTEX),this.tile.boundsVAO=new d,this.tile.state=\"loaded\"},prepare:function(){if(!(this.video.readyState<2)&&this.tile){var t=this.map.painter.gl;this._prepared?(t.bindTexture(t.TEXTURE_2D,this.tile.texture),t.texSubImage2D(t.TEXTURE_2D,0,0,0,t.RGBA,t.UNSIGNED_BYTE,this.video)):(this._prepared=!0,this.tile.texture=t.createTexture(),t.bindTexture(t.TEXTURE_2D,this.tile.texture),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),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.LINEAR),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.LINEAR),t.texImage2D(t.TEXTURE_2D,0,t.RGBA,t.RGBA,t.UNSIGNED_BYTE,this.video)),this._currentTime=this.video.currentTime}},loadTile:function(t,e){this._coord&&this._coord.toString()===t.coord.toString()?(this._setTile(t),e(null)):(t.state=\"errored\",e(null))},serialize:function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}}})},{\"../data/bucket\":311,\"../data/buffer\":316,\"../geo/lng_lat\":321,\"../render/draw_raster\":333,\"../render/vertex_array_object\":339,\"../util/ajax\":407,\"../util/evented\":416,\"../util/util\":424,\"./tile_coord\":351,\"point-geometry\":465}],355:[function(t,e,r){\"use strict\";function n(t){this.self=t,this.actor=new a(t,this);var e={getLayers:function(){return this.layers}.bind(this),getLayerFamilies:function(){return this.layerFamilies}.bind(this)};this.workerSources={vector:new l(this.actor,e),geojson:new u(this.actor,e)},this.self.registerWorkerSource=function(t,r){if(this.workerSources[t])throw new Error('Worker source with name \"'+t+'\" already registered.');this.workerSources[t]=new r(this.actor,e)}.bind(this)}function i(t){var e={};for(var r in t){var n=t[r],i=n.ref||n.id,a=t[i];a.layout&&\"none\"===a.layout.visibility||(e[i]=e[i]||[],r===i?e[i].unshift(n):e[i].push(n))}return e}var a=t(\"../util/actor\"),o=t(\"../style/style_layer\"),s=t(\"../util/util\"),l=t(\"./vector_tile_worker_source\"),u=t(\"./geojson_worker_source\");e.exports=function(t){return new n(t)},s.extend(n.prototype,{\"set layers\":function(t){function e(t){var e=o.create(t,t.ref&&r.layers[t.ref]);e.updatePaintTransitions({},{transition:!1}),r.layers[e.id]=e}this.layers={};for(var r=this,n=[],a=0;a<t.length;a++){var s=t[a];\"fill\"!==s.type&&\"line\"!==s.type&&\"circle\"!==s.type&&\"symbol\"!==s.type||(s.ref?n.push(a):e(s))}for(var l=0;l<n.length;l++)e(t[n[l]]);this.layerFamilies=i(this.layers)},\"update layers\":function(t){function e(t){var e=a.layers[t.ref];a.layers[t.id]?a.layers[t.id].set(t,e):a.layers[t.id]=o.create(t,e),a.layers[t.id].updatePaintTransitions({},{transition:!1})}var r,n,a=this;for(r in t)(n=t[r]).ref&&e(n);for(r in t)(n=t[r]).ref||e(n);this.layerFamilies=i(this.layers)},\"load tile\":function(t,e){var r=t.type||\"vector\";this.workerSources[r].loadTile(t,e)},\"reload tile\":function(t,e){var r=t.type||\"vector\";this.workerSources[r].reloadTile(t,e)},\"abort tile\":function(t){var e=t.type||\"vector\";this.workerSources[e].abortTile(t)},\"remove tile\":function(t){var e=t.type||\"vector\";this.workerSources[e].removeTile(t)},\"redo placement\":function(t,e){var r=t.type||\"vector\";this.workerSources[r].redoPlacement(t,e)},\"load worker source\":function(t,e){try{this.self.importScripts(t.url),e()}catch(t){e(t)}}})},{\"../style/style_layer\":363,\"../util/actor\":406,\"../util/util\":424,\"./geojson_worker_source\":341,\"./vector_tile_worker_source\":353}],356:[function(t,e,r){\"use strict\";function n(t){this.coord=t.coord,this.uid=t.uid,this.zoom=t.zoom,this.tileSize=t.tileSize,this.source=t.source,this.overscaling=t.overscaling,this.angle=t.angle,this.pitch=t.pitch,this.showCollisionBoxes=t.showCollisionBoxes}function i(t){return!t.isEmpty()}function a(t){return t.serialize()}function o(t){var e=[];for(var r in t)t[r].getTransferables(e);return e}function s(t){return t.id}var l=t(\"../data/feature_index\"),u=t(\"../symbol/collision_tile\"),c=t(\"../data/bucket\"),h=t(\"../symbol/collision_box\"),f=t(\"../util/dictionary_coder\"),d=t(\"../util/util\"),p=t(\"../symbol/symbol_instances\"),m=t(\"../symbol/symbol_quads\");e.exports=n,n.prototype.parse=function(t,e,r,n,g){function v(t,e){for(var r=0;r<t.length;r++){var n=t.feature(r);n.index=r;for(var i in e)e[i].filter(n)&&e[i].features.push(n)}}function y(t){if(t)return g(t);if(2===++N){for(var e=P.length-1;e>=0;e--)b(E,P[e]);x()}}function b(t,e){if(e.populateArrays(A,F,R),\"symbol\"!==e.type)for(var r=0;r<e.features.length;r++){var n=e.features[r];T.insert(n,n.index,e.sourceLayerIndex,e.index)}e.features=null}function x(){E.status=\"done\",E.redoPlacementAfterDone&&(E.redoPlacement(E.angle,E.pitch,null),E.redoPlacementAfterDone=!1);var t=T.serialize(),e=A.serialize(),r=E.collisionBoxArray.serialize(),s=E.symbolInstancesArray.serialize(),l=E.symbolQuadsArray.serialize(),u=[n].concat(t.transferables).concat(e.transferables),c=I.filter(i);g(null,{buckets:c.map(a),featureIndex:t.data,collisionTile:e.data,collisionBoxArray:r,symbolInstancesArray:s,symbolQuadsArray:l,rawTileData:n},o(c).concat(u))}this.status=\"parsing\",this.data=t,this.collisionBoxArray=new h,this.symbolInstancesArray=new p,this.symbolQuadsArray=new m;var _,w,M,k,A=new u(this.angle,this.pitch,this.collisionBoxArray),T=new l(this.coord,this.overscaling,A,t.layers),S=new f(t.layers?Object.keys(t.layers).sort():[\"_geojsonTileLayer\"]),E=this,L={},C={},z=0;for(var D in e)(w=e[D][0]).source===this.source&&(w.ref||w.minzoom&&this.zoom<w.minzoom||w.maxzoom&&this.zoom>=w.maxzoom||w.layout&&\"none\"===w.layout.visibility||t.layers&&!t.layers[w.sourceLayer]||((k=c.create({layer:w,index:z++,childLayers:e[D],zoom:this.zoom,overscaling:this.overscaling,showCollisionBoxes:this.showCollisionBoxes,collisionBoxArray:this.collisionBoxArray,symbolQuadsArray:this.symbolQuadsArray,symbolInstancesArray:this.symbolInstancesArray,sourceLayerIndex:S.encode(w.sourceLayer||\"_geojsonTileLayer\")})).createFilter(),L[w.id]=k,t.layers&&(C[M=w.sourceLayer]=C[M]||{},C[M][w.id]=k)));if(t.layers)for(M in C)1===w.version&&d.warnOnce('Vector tile source \"'+this.source+'\" layer \"'+M+'\" does not use vector tile spec v2 and therefore may have some rendering errors.'),(w=t.layers[M])&&v(w,C[M]);else v(t,L);var I=[],P=this.symbolBuckets=[],O=[];T.bucketLayerIDs={};for(var j in L)0!==(k=L[j]).features.length&&(T.bucketLayerIDs[k.index]=k.childLayers.map(s),I.push(k),\"symbol\"===k.type?P.push(k):O.push(k));var R={},F={},N=0;if(P.length>0){for(_=P.length-1;_>=0;_--)P[_].updateIcons(R),P[_].updateFont(F);for(var B in F)F[B]=Object.keys(F[B]).map(Number);R=Object.keys(R),r.send(\"get glyphs\",{uid:this.uid,stacks:F},function(t,e){F=e,y(t)}),R.length?r.send(\"get icons\",{icons:R},function(t,e){R=e,y(t)}):y()}for(_=O.length-1;_>=0;_--)b(this,O[_]);if(0===P.length)return x()},n.prototype.redoPlacement=function(t,e,r){if(\"done\"!==this.status)return this.redoPlacementAfterDone=!0,this.angle=t,{};for(var n=new u(t,e,this.collisionBoxArray),s=this.symbolBuckets,l=s.length-1;l>=0;l--)s[l].placeFeatures(n,r);var c=n.serialize(),h=s.filter(i);return{result:{buckets:h.map(a),collisionTile:c.data},transferables:o(h).concat(c.transferables)}}},{\"../data/bucket\":311,\"../data/feature_index\":318,\"../symbol/collision_box\":376,\"../symbol/collision_tile\":378,\"../symbol/symbol_instances\":387,\"../symbol/symbol_quads\":388,\"../util/dictionary_coder\":414,\"../util/util\":424}],357:[function(t,e,r){\"use strict\";function n(){this.n=0,this.times=[]}e.exports=n,n.prototype.stopped=function(){return this.times=this.times.filter(function(t){return t.time>=(new Date).getTime()}),!this.times.length},n.prototype.set=function(t){return this.times.push({id:this.n,time:t+(new Date).getTime()}),this.n++},n.prototype.cancel=function(t){this.times=this.times.filter(function(e){return e.id!==t})}},{}],358:[function(t,e,r){\"use strict\";function n(t){this.base=t,this.retina=s.devicePixelRatio>1;var e=this.retina?\"@2x\":\"\";o.getJSON(l(t,e,\".json\"),function(t,e){t?this.fire(\"error\",{error:t}):(this.data=e,this.img&&this.fire(\"load\"))}.bind(this)),o.getImage(l(t,e,\".png\"),function(t,e){if(t)this.fire(\"error\",{error:t});else{for(var r=e.getData(),n=e.data=new Uint8Array(r.length),i=0;i<r.length;i+=4){var a=r[i+3]/255;n[i+0]=r[i+0]*a,n[i+1]=r[i+1]*a,n[i+2]=r[i+2]*a,n[i+3]=r[i+3]}this.img=e,this.data&&this.fire(\"load\")}}.bind(this))}function i(){}var a=t(\"../util/evented\"),o=t(\"../util/ajax\"),s=t(\"../util/browser\"),l=t(\"../util/mapbox\").normalizeSpriteURL;e.exports=n,n.prototype=Object.create(a),n.prototype.toJSON=function(){return this.base},n.prototype.loaded=function(){return!(!this.data||!this.img)},n.prototype.resize=function(){if(s.devicePixelRatio>1!==this.retina){var t=new n(this.base);t.on(\"load\",function(){this.img=t.img,this.data=t.data,this.retina=t.retina}.bind(this))}},i.prototype={x:0,y:0,width:0,height:0,pixelRatio:1,sdf:!1},n.prototype.getSpritePosition=function(t){if(!this.loaded())return new i;var e=this.data&&this.data[t];return e&&this.img?e:new i}},{\"../util/ajax\":407,\"../util/browser\":408,\"../util/evented\":416,\"../util/mapbox\":421}],359:[function(t,e,r){\"use strict\";var n=t(\"csscolorparser\").parseCSSColor,i=t(\"../util/util\"),a=t(\"./style_function\"),o={};e.exports=function t(e){if(a.isFunctionDefinition(e))return i.extend({},e,{stops:e.stops.map(function(e){return[e[0],t(e[1])]})});if(\"string\"==typeof e){if(!o[e]){var r=n(e);if(!r)throw new Error(\"Invalid color \"+e);o[e]=[r[0]/255*r[3],r[1]/255*r[3],r[2]/255*r[3],r[3]]}return o[e]}throw new Error(\"Invalid color \"+e)}},{\"../util/util\":424,\"./style_function\":362,csscolorparser:101}],360:[function(t,e,r){\"use strict\";function n(t,e,r){this.animationLoop=e||new m,this.dispatcher=new p(r||1,this),this.spriteAtlas=new l(1024,1024),this.lineAtlas=new u(256,512),this._layers={},this._order=[],this._groups=[],this.sources={},this.zoomHistory={},c.bindAll([\"_forwardSourceEvent\",\"_forwardTileEvent\",\"_forwardLayerEvent\",\"_redoPlacement\"],this),this._resetUpdates();var n=function(t,e){if(t)this.fire(\"error\",{error:t});else if(!g.emitErrors(this,g(e))){this._loaded=!0,this.stylesheet=e,this.updateClasses();var r=e.sources;for(var n in r)this.addSource(n,r[n]);e.sprite&&(this.sprite=new o(e.sprite),this.sprite.on(\"load\",this.fire.bind(this,\"change\"))),this.glyphSource=new s(e.glyphs),this._resolve(),this.fire(\"load\")}}.bind(this);\"string\"==typeof t?h.getJSON(f(t),n):d.frame(n.bind(this,null,t)),this.on(\"source.load\",function(t){var e=t.source;if(e&&e.vectorLayerIds)for(var r in this._layers){var n=this._layers[r];n.source===e.id&&this._validateLayer(n)}})}var i=t(\"../util/evented\"),a=t(\"./style_layer\"),o=t(\"./image_sprite\"),s=t(\"../symbol/glyph_source\"),l=t(\"../symbol/sprite_atlas\"),u=t(\"../render/line_atlas\"),c=t(\"../util/util\"),h=t(\"../util/ajax\"),f=t(\"../util/mapbox\").normalizeStyleURL,d=t(\"../util/browser\"),p=t(\"../util/dispatcher\"),m=t(\"./animation_loop\"),g=t(\"./validate_style\"),v=t(\"../source/source\"),y=t(\"../source/query_features\"),b=t(\"../source/source_cache\"),x=t(\"./style_spec\"),_=t(\"./style_function\");e.exports=n,n.prototype=c.inherit(i,{_loaded:!1,_validateLayer:function(t){var e=this.sources[t.source];t.sourceLayer&&e&&e.vectorLayerIds&&-1===e.vectorLayerIds.indexOf(t.sourceLayer)&&this.fire(\"error\",{error:new Error('Source layer \"'+t.sourceLayer+'\" does not exist on source \"'+e.id+'\" as specified by style layer \"'+t.id+'\"')})},loaded:function(){if(!this._loaded)return!1;if(Object.keys(this._updates.sources).length)return!1;for(var t in this.sources)if(!this.sources[t].loaded())return!1;return!(this.sprite&&!this.sprite.loaded())},_resolve:function(){var t,e;this._layers={},this._order=this.stylesheet.layers.map(function(t){return t.id});for(var r=0;r<this.stylesheet.layers.length;r++)(e=this.stylesheet.layers[r]).ref||(t=a.create(e),this._layers[t.id]=t,t.on(\"error\",this._forwardLayerEvent));for(var n=0;n<this.stylesheet.layers.length;n++)if((e=this.stylesheet.layers[n]).ref){var i=this.getLayer(e.ref);t=a.create(e,i),this._layers[t.id]=t,t.on(\"error\",this._forwardLayerEvent)}this._groupLayers(),this._updateWorkerLayers()},_groupLayers:function(){var t;this._groups=[];for(var e=0;e<this._order.length;++e){var r=this._layers[this._order[e]];t&&r.source===t.source||((t=[]).source=r.source,this._groups.push(t)),t.push(r)}},_updateWorkerLayers:function(t){this.dispatcher.broadcast(t?\"update layers\":\"set layers\",this._serializeLayers(t))},_serializeLayers:function(t){t=t||this._order;for(var e=[],r={includeRefProperties:!0},n=0;n<t.length;n++)e.push(this._layers[t[n]].serialize(r));return e},_applyClasses:function(t,e){if(this._loaded){t=t||[],e=e||{transition:!0};var r=this.stylesheet.transition||{},n=this._updates.allPaintProps?this._layers:this._updates.paintProps;for(var i in n){var a=this._layers[i],o=this._updates.paintProps[i];if(this._updates.allPaintProps||o.all)a.updatePaintTransitions(t,e,r,this.animationLoop);else for(var s in o)this._layers[i].updatePaintTransition(s,t,e,r,this.animationLoop)}}},_recalculate:function(t){for(var e in this.sources)this.sources[e].used=!1;this._updateZoomHistory(t),this.rasterFadeDuration=300;for(var r in this._layers){var n=this._layers[r];n.recalculate(t,this.zoomHistory),!n.isHidden(t)&&n.source&&(this.sources[n.source].used=!0)}Math.floor(this.z)!==Math.floor(t)&&this.animationLoop.set(300),this.z=t,this.fire(\"zoom\")},_updateZoomHistory:function(t){var e=this.zoomHistory;void 0===e.lastIntegerZoom&&(e.lastIntegerZoom=Math.floor(t),e.lastIntegerZoomTime=0,e.lastZoom=t),Math.floor(e.lastZoom)<Math.floor(t)?(e.lastIntegerZoom=Math.floor(t),e.lastIntegerZoomTime=Date.now()):Math.floor(e.lastZoom)>Math.floor(t)&&(e.lastIntegerZoom=Math.floor(t+1),e.lastIntegerZoomTime=Date.now()),e.lastZoom=t},_checkLoaded:function(){if(!this._loaded)throw new Error(\"Style is not done loading\")},update:function(t,e){if(!this._updates.changed)return this;if(this._updates.allLayers)this._groupLayers(),this._updateWorkerLayers();else{var r=Object.keys(this._updates.layers);r.length&&this._updateWorkerLayers(r)}var n,i=Object.keys(this._updates.sources);for(n=0;n<i.length;n++)this._reloadSource(i[n]);for(n=0;n<this._updates.events.length;n++){var a=this._updates.events[n];this.fire(a[0],a[1])}return this._applyClasses(t,e),this._updates.changed&&this.fire(\"change\"),this._resetUpdates(),this},_resetUpdates:function(){this._updates={events:[],layers:{},sources:{},paintProps:{}}},addSource:function(t,e){if(this._checkLoaded(),void 0!==this.sources[t])throw new Error(\"There is already a source with this ID\");if(!e.type)throw new Error(\"The type property must be defined, but the only the following properties were given: \"+Object.keys(e)+\".\");return[\"vector\",\"raster\",\"geojson\",\"video\",\"image\"].indexOf(e.type)>=0&&this._handleErrors(g.source,\"sources.\"+t,e)?this:(e=new b(t,e,this.dispatcher),this.sources[t]=e,e.style=this,e.on(\"load\",this._forwardSourceEvent).on(\"error\",this._forwardSourceEvent).on(\"change\",this._forwardSourceEvent).on(\"tile.add\",this._forwardTileEvent).on(\"tile.load\",this._forwardTileEvent).on(\"tile.error\",this._forwardTileEvent).on(\"tile.remove\",this._forwardTileEvent).on(\"tile.stats\",this._forwardTileEvent),this._updates.events.push([\"source.add\",{source:e}]),this._updates.changed=!0,this)},removeSource:function(t){if(this._checkLoaded(),void 0===this.sources[t])throw new Error(\"There is no source with this ID\");var e=this.sources[t];return delete this.sources[t],delete this._updates.sources[t],e.off(\"load\",this._forwardSourceEvent).off(\"error\",this._forwardSourceEvent).off(\"change\",this._forwardSourceEvent).off(\"tile.add\",this._forwardTileEvent).off(\"tile.load\",this._forwardTileEvent).off(\"tile.error\",this._forwardTileEvent).off(\"tile.remove\",this._forwardTileEvent).off(\"tile.stats\",this._forwardTileEvent),this._updates.events.push([\"source.remove\",{source:e}]),this._updates.changed=!0,this},getSource:function(t){return this.sources[t]&&this.sources[t].getSource()},addLayer:function(t,e){if(this._checkLoaded(),!(t instanceof a)){if(this._handleErrors(g.layer,\"layers.\"+t.id,t,!1,{arrayIndex:-1}))return this;var r=t.ref&&this.getLayer(t.ref);t=a.create(t,r)}return this._validateLayer(t),t.on(\"error\",this._forwardLayerEvent),this._layers[t.id]=t,this._order.splice(e?this._order.indexOf(e):1/0,0,t.id),this._updates.allLayers=!0,t.source&&(this._updates.sources[t.source]=!0),this._updates.events.push([\"layer.add\",{layer:t}]),this.updateClasses(t.id)},removeLayer:function(t){this._checkLoaded();var e=this._layers[t];if(void 0===e)throw new Error(\"There is no layer with this ID\");for(var r in this._layers)this._layers[r].ref===t&&this.removeLayer(r);return e.off(\"error\",this._forwardLayerEvent),delete this._layers[t],delete this._updates.layers[t],delete this._updates.paintProps[t],this._order.splice(this._order.indexOf(t),1),this._updates.allLayers=!0,this._updates.events.push([\"layer.remove\",{layer:e}]),this._updates.changed=!0,this},getLayer:function(t){return this._layers[t]},getReferentLayer:function(t){var e=this.getLayer(t);return e.ref&&(e=this.getLayer(e.ref)),e},setLayerZoomRange:function(t,e,r){this._checkLoaded();var n=this.getReferentLayer(t);return n.minzoom===e&&n.maxzoom===r?this:(null!=e&&(n.minzoom=e),null!=r&&(n.maxzoom=r),this._updateLayer(n))},setFilter:function(t,e){this._checkLoaded();var r=this.getReferentLayer(t);return null!==e&&this._handleErrors(g.filter,\"layers.\"+r.id+\".filter\",e)?this:c.deepEqual(r.filter,e)?this:(r.filter=c.clone(e),this._updateLayer(r))},getFilter:function(t){return this.getReferentLayer(t).filter},setLayoutProperty:function(t,e,r){this._checkLoaded();var n=this.getReferentLayer(t);return c.deepEqual(n.getLayoutProperty(e),r)?this:(n.setLayoutProperty(e,r),this._updateLayer(n))},getLayoutProperty:function(t,e){return this.getReferentLayer(t).getLayoutProperty(e)},setPaintProperty:function(t,e,r,n){this._checkLoaded();var i=this.getLayer(t);if(c.deepEqual(i.getPaintProperty(e,n),r))return this;var a=i.isPaintValueFeatureConstant(e);return i.setPaintProperty(e,r,n),!(r&&_.isFunctionDefinition(r)&&\"$zoom\"!==r.property&&void 0!==r.property)&&a||(this._updates.layers[t]=!0,i.source&&(this._updates.sources[i.source]=!0)),this.updateClasses(t,e)},getPaintProperty:function(t,e,r){return this.getLayer(t).getPaintProperty(e,r)},updateClasses:function(t,e){if(this._updates.changed=!0,t){var r=this._updates.paintProps;r[t]||(r[t]={}),r[t][e||\"all\"]=!0}else this._updates.allPaintProps=!0;return this},serialize:function(){return c.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,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:c.mapObject(this.sources,function(t){return t.serialize()}),layers:this._order.map(function(t){return this._layers[t].serialize()},this)},function(t){return void 0!==t})},_updateLayer:function(t){return this._updates.layers[t.id]=!0,t.source&&(this._updates.sources[t.source]=!0),this._updates.changed=!0,this},_flattenRenderedFeatures:function(t){for(var e=[],r=this._order.length-1;r>=0;r--)for(var n=this._order[r],i=0;i<t.length;i++){var a=t[i][n];if(a)for(var o=0;o<a.length;o++)e.push(a[o])}return e},queryRenderedFeatures:function(t,e,r,n){e&&e.filter&&this._handleErrors(g.filter,\"queryRenderedFeatures.filter\",e.filter,!0);var i={};if(e&&e.layers)for(var a=0;a<e.layers.length;a++){var o=e.layers[a];i[this._layers[o].source]=!0}var s=[];for(var l in this.sources)if(!e.layers||i[l]){var u=this.sources[l],c=y.rendered(u,this._layers,t,e,r,n);s.push(c)}return this._flattenRenderedFeatures(s)},querySourceFeatures:function(t,e){e&&e.filter&&this._handleErrors(g.filter,\"querySourceFeatures.filter\",e.filter,!0);var r=this.sources[t];return r?y.source(r,e):[]},addSourceType:function(t,e,r){return v.getType(t)?r(new Error('A source type called \"'+t+'\" already exists.')):(v.setType(t,e),e.workerSourceURL?void this.dispatcher.broadcast(\"load worker source\",{name:t,url:e.workerSourceURL},r):r(null,null))},_handleErrors:function(t,e,r,n,i){var a=n?g.throwErrors:g.emitErrors,o=t.call(g,c.extend({key:e,style:this.serialize(),value:r,styleSpec:x},i));return a.call(g,this,o)},_remove:function(){this.dispatcher.remove()},_reloadSource:function(t){this.sources[t].reload()},_updateSources:function(t){for(var e in this.sources)this.sources[e].update(t)},_redoPlacement:function(){for(var t in this.sources)this.sources[t].redoPlacement&&this.sources[t].redoPlacement()},_forwardSourceEvent:function(t){this.fire(\"source.\"+t.type,c.extend({source:t.target.getSource()},t))},_forwardTileEvent:function(t){this.fire(t.type,c.extend({source:t.target},t))},_forwardLayerEvent:function(t){this.fire(\"layer.\"+t.type,c.extend({layer:{id:t.target.id}},t))},\"get sprite json\":function(t,e){var r=this.sprite;r.loaded()?e(null,{sprite:r.data,retina:r.retina}):r.on(\"load\",function(){e(null,{sprite:r.data,retina:r.retina})})},\"get icons\":function(t,e){var r=this.sprite,n=this.spriteAtlas;r.loaded()?(n.setSprite(r),n.addIcons(t.icons,e)):r.on(\"load\",function(){n.setSprite(r),n.addIcons(t.icons,e)})},\"get glyphs\":function(t,e){function r(t,r,n){t&&console.error(t),a[n]=r,0===--i&&e(null,a)}var n=t.stacks,i=Object.keys(n).length,a={};for(var o in n)this.glyphSource.getSimpleGlyphs(o,n[o],t.uid,r)}})},{\"../render/line_atlas\":336,\"../source/query_features\":346,\"../source/source\":348,\"../source/source_cache\":349,\"../symbol/glyph_source\":381,\"../symbol/sprite_atlas\":386,\"../util/ajax\":407,\"../util/browser\":408,\"../util/dispatcher\":415,\"../util/evented\":416,\"../util/mapbox\":421,\"../util/util\":424,\"./animation_loop\":357,\"./image_sprite\":358,\"./style_function\":362,\"./style_layer\":363,\"./style_spec\":370,\"./validate_style\":372}],361:[function(t,e,r){\"use strict\";function n(t,e){this.value=s.clone(e),this.isFunction=a.isFunctionDefinition(e),this.json=JSON.stringify(this.value);var r=\"color\"===t.type&&this.value?o(this.value):e;if(this.calculate=a[t.function||\"piecewise-constant\"](r),this.isFeatureConstant=this.calculate.isFeatureConstant,this.isZoomConstant=this.calculate.isZoomConstant,\"piecewise-constant\"===t.function&&t.transition&&(this.calculate=i(this.calculate)),!this.isFeatureConstant&&!this.isZoomConstant){this.stopZoomLevels=[];for(var n=[],l=this.value.stops,u=0;u<this.value.stops.length;u++){var c=l[u][0].zoom;this.stopZoomLevels.indexOf(c)<0&&(this.stopZoomLevels.push(c),n.push([c,n.length]))}this.calculateInterpolationT=a.interpolated({stops:n,base:e.base})}}function i(t){return function(e,r){var n,i,a,o=e.zoom,s=e.zoomHistory,l=e.duration,u=o%1,c=Math.min((Date.now()-s.lastIntegerZoomTime)/l,1),h=1;return o>s.lastIntegerZoom?(n=u+(1-u)*c,h*=2,i=t({zoom:o-1},r),a=t({zoom:o},r)):(n=1-(1-c)*u,a=t({zoom:o},r),i=t({zoom:o+1},r),h/=2),void 0===i||void 0===a?void 0:{from:i,fromScale:h,to:a,toScale:1,t:n}}}var a=t(\"./style_function\"),o=t(\"./parse_color\"),s=t(\"../util/util\");e.exports=n},{\"../util/util\":424,\"./parse_color\":359,\"./style_function\":362}],362:[function(t,e,r){\"use strict\";var n=t(\"mapbox-gl-function\");r.interpolated=function(t){var e=n.interpolated(t),r=function(t,r){return e(t&&t.zoom,r||{})};return r.isFeatureConstant=e.isFeatureConstant,r.isZoomConstant=e.isZoomConstant,r},r[\"piecewise-constant\"]=function(t){var e=n[\"piecewise-constant\"](t),r=function(t,r){return e(t&&t.zoom,r||{})};return r.isFeatureConstant=e.isFeatureConstant,r.isZoomConstant=e.isZoomConstant,r},r.isFunctionDefinition=n.isFunctionDefinition},{\"mapbox-gl-function\":284}],363:[function(t,e,r){\"use strict\";function n(t,e){this.set(t,e)}function i(t){return t.value}var a=t(\"../util/util\"),o=t(\"./style_transition\"),s=t(\"./style_declaration\"),l=t(\"./style_spec\"),u=t(\"./validate_style\"),c=t(\"./parse_color\"),h=t(\"../util/evented\");e.exports=n;n.create=function(e,r){return new({background:t(\"./style_layer/background_style_layer\"),circle:t(\"./style_layer/circle_style_layer\"),fill:t(\"./style_layer/fill_style_layer\"),line:t(\"./style_layer/line_style_layer\"),raster:t(\"./style_layer/raster_style_layer\"),symbol:t(\"./style_layer/symbol_style_layer\")}[(r||e).type])(e,r)},n.prototype=a.inherit(h,{set:function(t,e){this.id=t.id,this.ref=t.ref,this.metadata=t.metadata,this.type=(e||t).type,this.source=(e||t).source,this.sourceLayer=(e||t)[\"source-layer\"],this.minzoom=(e||t).minzoom,this.maxzoom=(e||t).maxzoom,this.filter=(e||t).filter,this.paint={},this.layout={},this._paintSpecifications=l[\"paint_\"+this.type],this._layoutSpecifications=l[\"layout_\"+this.type],this._paintTransitions={},this._paintTransitionOptions={},this._paintDeclarations={},this._layoutDeclarations={},this._layoutFunctions={};var r,n;for(var i in t){var a=i.match(/^paint(?:\\.(.*))?$/);if(a){var o=a[1]||\"\";for(r in t[i])this.setPaintProperty(r,t[i][r],o)}}if(this.ref)this._layoutDeclarations=e._layoutDeclarations;else for(n in t.layout)this.setLayoutProperty(n,t.layout[n]);for(r in this._paintSpecifications)this.paint[r]=this.getPaintValue(r);for(n in this._layoutSpecifications)this._updateLayoutValue(n)},setLayoutProperty:function(t,e){if(null==e)delete this._layoutDeclarations[t];else{var r=\"layers.\"+this.id+\".layout.\"+t;if(this._handleErrors(u.layoutProperty,r,t,e))return;this._layoutDeclarations[t]=new s(this._layoutSpecifications[t],e)}this._updateLayoutValue(t)},getLayoutProperty:function(t){return this._layoutDeclarations[t]&&this._layoutDeclarations[t].value},getLayoutValue:function(t,e,r){var n=this._layoutSpecifications[t],i=this._layoutDeclarations[t];return i?i.calculate(e,r):n.default},setPaintProperty:function(t,e,r){var n=\"layers.\"+this.id+(r?'[\"paint.'+r+'\"].':\".paint.\")+t;if(a.endsWith(t,\"-transition\"))if(this._paintTransitionOptions[r||\"\"]||(this._paintTransitionOptions[r||\"\"]={}),null===e||void 0===e)delete this._paintTransitionOptions[r||\"\"][t];else{if(this._handleErrors(u.paintProperty,n,t,e))return;this._paintTransitionOptions[r||\"\"][t]=e}else if(this._paintDeclarations[r||\"\"]||(this._paintDeclarations[r||\"\"]={}),null===e||void 0===e)delete this._paintDeclarations[r||\"\"][t];else{if(this._handleErrors(u.paintProperty,n,t,e))return;this._paintDeclarations[r||\"\"][t]=new s(this._paintSpecifications[t],e)}},getPaintProperty:function(t,e){return e=e||\"\",a.endsWith(t,\"-transition\")?this._paintTransitionOptions[e]&&this._paintTransitionOptions[e][t]:this._paintDeclarations[e]&&this._paintDeclarations[e][t]&&this._paintDeclarations[e][t].value},getPaintValue:function(t,e,r){var n=this._paintSpecifications[t],i=this._paintTransitions[t];return i?i.calculate(e,r):\"color\"===n.type&&n.default?c(n.default):n.default},getPaintValueStopZoomLevels:function(t){var e=this._paintTransitions[t];return e?e.declaration.stopZoomLevels:[]},getPaintInterpolationT:function(t,e){return this._paintTransitions[t].declaration.calculateInterpolationT({zoom:e})},isPaintValueFeatureConstant:function(t){var e=this._paintTransitions[t];return!e||e.declaration.isFeatureConstant},isLayoutValueFeatureConstant:function(t){var e=this._layoutDeclarations[t];return!e||e.isFeatureConstant},isPaintValueZoomConstant:function(t){var e=this._paintTransitions[t];return!e||e.declaration.isZoomConstant},isHidden:function(t){return!!(this.minzoom&&t<this.minzoom)||(!!(this.maxzoom&&t>=this.maxzoom)||(\"none\"===this.layout.visibility||0===this.paint[this.type+\"-opacity\"]))},updatePaintTransitions:function(t,e,r,n){for(var i=a.extend({},this._paintDeclarations[\"\"]),o=0;o<t.length;o++)a.extend(i,this._paintDeclarations[t[o]]);var s;for(s in 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this._layoutFunctions[t],this.layout[t]=this.getLayoutValue(t))},_handleErrors:function(t,e,r,n){return u.emitErrors(this,t.call(u,{key:e,layerType:this.type,objectKey:r,value:n,styleSpec:l,style:{glyphs:!0,sprite:!0}}))}})},{\"../util/evented\":416,\"../util/util\":424,\"./parse_color\":359,\"./style_declaration\":361,\"./style_layer/background_style_layer\":364,\"./style_layer/circle_style_layer\":365,\"./style_layer/fill_style_layer\":366,\"./style_layer/line_style_layer\":367,\"./style_layer/raster_style_layer\":368,\"./style_layer/symbol_style_layer\":369,\"./style_spec\":370,\"./style_transition\":371,\"./validate_style\":372}],364:[function(t,e,r){\"use strict\";function n(){a.apply(this,arguments)}var i=t(\"../../util/util\"),a=t(\"../style_layer\");e.exports=n,n.prototype=i.inherit(a,{})},{\"../../util/util\":424,\"../style_layer\":363}],365:[function(t,e,r){\"use strict\";function n(){a.apply(this,arguments)}var i=t(\"../../util/util\"),a=t(\"../style_layer\");e.exports=n,n.prototype=i.inherit(a,{})},{\"../../util/util\":424,\"../style_layer\":363}],366:[function(t,e,r){\"use strict\";function n(){a.apply(this,arguments)}var i=t(\"../../util/util\"),a=t(\"../style_layer\");n.prototype=i.inherit(a,{getPaintValue:function(t,e,r){return\"fill-outline-color\"===t&&void 0===this.getPaintProperty(\"fill-outline-color\")?a.prototype.getPaintValue.call(this,\"fill-color\",e,r):a.prototype.getPaintValue.call(this,t,e,r)},getPaintValueStopZoomLevels:function(t){return\"fill-outline-color\"===t&&void 0===this.getPaintProperty(\"fill-outline-color\")?a.prototype.getPaintValueStopZoomLevels.call(this,\"fill-color\"):a.prototype.getPaintValueStopZoomLevels.call(this,arguments)},getPaintInterpolationT:function(t,e){return\"fill-outline-color\"===t&&void 0===this.getPaintProperty(\"fill-outline-color\")?a.prototype.getPaintInterpolationT.call(this,\"fill-color\",e):a.prototype.getPaintInterpolationT.call(this,t,e)},isPaintValueFeatureConstant:function(t){return\"fill-outline-color\"===t&&void 0===this.getPaintProperty(\"fill-outline-color\")?a.prototype.isPaintValueFeatureConstant.call(this,\"fill-color\"):a.prototype.isPaintValueFeatureConstant.call(this,t)},isPaintValueZoomConstant:function(t){return\"fill-outline-color\"===t&&void 0===this.getPaintProperty(\"fill-outline-color\")?a.prototype.isPaintValueZoomConstant.call(this,\"fill-color\"):a.prototype.isPaintValueZoomConstant.call(this,t)}}),e.exports=n},{\"../../util/util\":424,\"../style_layer\":363}],367:[function(t,e,r){\"use strict\";function n(){a.apply(this,arguments)}var i=t(\"../../util/util\"),a=t(\"../style_layer\");e.exports=n,n.prototype=i.inherit(a,{getPaintValue:function(t,e,r){var n=a.prototype.getPaintValue.apply(this,arguments);if(n&&\"line-dasharray\"===t){var i=Math.floor(e.zoom);this._flooredZoom!==i&&(this._flooredZoom=i,this._flooredLineWidth=this.getPaintValue(\"line-width\",e,r)),n.fromScale*=this._flooredLineWidth,n.toScale*=this._flooredLineWidth}return n}})},{\"../../util/util\":424,\"../style_layer\":363}],368:[function(t,e,r){\"use strict\";function n(){a.apply(this,arguments)}var i=t(\"../../util/util\"),a=t(\"../style_layer\");e.exports=n,n.prototype=i.inherit(a,{})},{\"../../util/util\":424,\"../style_layer\":363}],369:[function(t,e,r){\"use strict\";function n(){a.apply(this,arguments)}var i=t(\"../../util/util\"),a=t(\"../style_layer\");e.exports=n,n.prototype=i.inherit(a,{isHidden:function(){if(a.prototype.isHidden.apply(this,arguments))return!0;var t=0===this.paint[\"text-opacity\"]||!this.layout[\"text-field\"],e=0===this.paint[\"icon-opacity\"]||!this.layout[\"icon-image\"];return!(!t||!e)},getLayoutValue:function(t,e,r){return(\"text-rotation-alignment\"!==t||\"line\"!==this.getLayoutValue(\"symbol-placement\",e,r)||this.getLayoutProperty(\"text-rotation-alignment\"))&&(\"icon-rotation-alignment\"!==t||\"line\"!==this.getLayoutValue(\"symbol-placement\",e,r)||this.getLayoutProperty(\"icon-rotation-alignment\"))?\"text-pitch-alignment\"!==t||this.getLayoutProperty(\"text-pitch-alignment\")?a.prototype.getLayoutValue.apply(this,arguments):this.getLayoutValue(\"text-rotation-alignment\"):\"map\"}})},{\"../../util/util\":424,\"../style_layer\":363}],370:[function(t,e,r){\"use strict\";e.exports=t(\"mapbox-gl-style-spec/reference/latest.min\")},{\"mapbox-gl-style-spec/reference/latest.min\":307}],371:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.declaration=e,this.startTime=this.endTime=(new Date).getTime(),\"piecewise-constant\"===t.function&&t.transition?this.interp=i:this.interp=o[t.type],this.oldTransition=r,this.duration=n.duration||0,this.delay=n.delay||0,this.instant()||(this.endTime=this.startTime+this.duration+this.delay,this.ease=a.easeCubicInOut),r&&r.endTime<=this.startTime&&delete r.oldTransition}function i(t,e,r){return void 0===(t&&t.to)||void 0===(e&&e.to)?void 0:{from:t.to,fromScale:t.toScale,to:e.to,toScale:e.toScale,t:r}}var a=t(\"../util/util\"),o=t(\"../util/interpolate\");e.exports=n,n.prototype.instant=function(){return!this.oldTransition||!this.interp||0===this.duration&&0===this.delay},n.prototype.calculate=function(t,e){var r=this.declaration.calculate(a.extend({},t,{duration:this.duration}),e);if(this.instant())return r;var n=t.time||Date.now();if(n<this.endTime){var i=this.oldTransition.calculate(a.extend({},t,{time:this.startTime}),e),o=this.ease((n-this.startTime-this.delay)/this.duration);r=this.interp(i,r,o)}return r}},{\"../util/interpolate\":418,\"../util/util\":424}],372:[function(t,e,r){\"use strict\";e.exports=t(\"mapbox-gl-style-spec/lib/validate_style.min\"),e.exports.emitErrors=function(t,e){if(e&&e.length){for(var r=0;r<e.length;r++)t.fire(\"error\",{error:new Error(e[r].message)});return!0}return!1},e.exports.throwErrors=function(t,e){if(e)for(var r=0;r<e.length;r++)throw new Error(e[r].message)}},{\"mapbox-gl-style-spec/lib/validate_style.min\":306}],373:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.x=t,this.y=e,this.angle=r,void 0!==n&&(this.segment=n)}var i=t(\"point-geometry\");e.exports=n,n.prototype=Object.create(i.prototype),n.prototype.clone=function(){return new n(this.x,this.y,this.angle,this.segment)}},{\"point-geometry\":465}],374:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){if(void 0===e.segment)return!0;for(var a=e,o=e.segment+1,s=0;s>-r/2;){if(--o<0)return!1;s-=t[o].dist(a),a=t[o]}s+=t[o].dist(t[o+1]),o++;for(var l=[],u=0;s<r/2;){var c=t[o-1],h=t[o],f=t[o+1];if(!f)return!1;var d=c.angleTo(h)-h.angleTo(f);for(d=Math.abs((d+3*Math.PI)%(2*Math.PI)-Math.PI),l.push({distance:s,angleDelta:d}),u+=d;s-l[0].distance>n;)u-=l.shift().angleDelta;if(u>i)return!1;o++,s+=h.dist(f)}return!0}e.exports=n},{}],375:[function(t,e,r){\"use strict\";function n(t,e,r,n,a){for(var o=[],s=0;s<t.length;s++)for(var l,u=t[s],c=0;c<u.length-1;c++){var h=u[c],f=u[c+1];h.x<e&&f.x<e||(h.x<e?h=new i(e,h.y+(f.y-h.y)*((e-h.x)/(f.x-h.x)))._round():f.x<e&&(f=new i(e,h.y+(f.y-h.y)*((e-h.x)/(f.x-h.x)))._round()),h.y<r&&f.y<r||(h.y<r?h=new i(h.x+(f.x-h.x)*((r-h.y)/(f.y-h.y)),r)._round():f.y<r&&(f=new i(h.x+(f.x-h.x)*((r-h.y)/(f.y-h.y)),r)._round()),h.x>=n&&f.x>=n||(h.x>=n?h=new i(n,h.y+(f.y-h.y)*((n-h.x)/(f.x-h.x)))._round():f.x>=n&&(f=new i(n,h.y+(f.y-h.y)*((n-h.x)/(f.x-h.x)))._round()),h.y>=a&&f.y>=a||(h.y>=a?h=new i(h.x+(f.x-h.x)*((a-h.y)/(f.y-h.y)),a)._round():f.y>=a&&(f=new i(h.x+(f.x-h.x)*((a-h.y)/(f.y-h.y)),a)._round()),l&&h.equals(l[l.length-1])||(l=[h],o.push(l)),l.push(f)))))}return o}var i=t(\"point-geometry\");e.exports=n},{\"point-geometry\":465}],376:[function(t,e,r){\"use strict\";var n=t(\"../util/struct_array\"),i=t(\"../util/util\"),a=t(\"point-geometry\"),o=e.exports=new n({members:[{type:\"Int16\",name:\"anchorPointX\"},{type:\"Int16\",name:\"anchorPointY\"},{type:\"Int16\",name:\"x1\"},{type:\"Int16\",name:\"y1\"},{type:\"Int16\",name:\"x2\"},{type:\"Int16\",name:\"y2\"},{type:\"Float32\",name:\"maxScale\"},{type:\"Uint32\",name:\"featureIndex\"},{type:\"Uint16\",name:\"sourceLayerIndex\"},{type:\"Uint16\",name:\"bucketIndex\"},{type:\"Int16\",name:\"bbox0\"},{type:\"Int16\",name:\"bbox1\"},{type:\"Int16\",name:\"bbox2\"},{type:\"Int16\",name:\"bbox3\"},{type:\"Float32\",name:\"placementScale\"}]});i.extendAll(o.prototype.StructType.prototype,{get anchorPoint(){return new a(this.anchorPointX,this.anchorPointY)}})},{\"../util/struct_array\":422,\"../util/util\":424,\"point-geometry\":465}],377:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s,l,u,c){var h=o.top*s-l,f=o.bottom*s+l,d=o.left*s-l,p=o.right*s+l;if(this.boxStartIndex=t.length,u){var m=f-h,g=p-d;if(m>0)if(m=Math.max(10*s,m),c){var v=e[r.segment+1].sub(e[r.segment])._unit()._mult(g),y=[r.sub(v),r.add(v)];this._addLineCollisionBoxes(t,y,r,0,g,m,n,i,a)}else this._addLineCollisionBoxes(t,e,r,r.segment,g,m,n,i,a)}else t.emplaceBack(r.x,r.y,d,h,p,f,1/0,n,i,a,0,0,0,0,0);this.boxEndIndex=t.length}e.exports=n,n.prototype._addLineCollisionBoxes=function(t,e,r,n,i,a,o,s,l){var u=a/2,c=Math.floor(i/u),h=-a/2,f=this.boxes,d=r,p=n+1,m=h;do{if(--p<0)return f;m-=e[p].dist(d),d=e[p]}while(m>-i/2);for(var g=e[p].dist(e[p+1]),v=0;v<c;v++){for(var y=-i/2+v*u;m+g<y;){if(m+=g,++p+1>=e.length)return f;g=e[p].dist(e[p+1])}var b=y-m,x=e[p],_=e[p+1].sub(x)._unit()._mult(b)._add(x)._round(),w=i/2/Math.max(Math.abs(y-h)-u/2,0);t.emplaceBack(_.x,_.y,-a/2,-a/2,a/2,a/2,w,o,s,l,0,0,0,0,0)}return f}},{}],378:[function(t,e,r){\"use strict\";function n(t,e,r){if(\"object\"==typeof t){var n=t;r=e,t=n.angle,e=n.pitch,this.grid=new o(n.grid),this.ignoredGrid=new o(n.ignoredGrid)}else this.grid=new o(a,12,6),this.ignoredGrid=new o(a,12,0);this.angle=t,this.pitch=e;var i=Math.sin(t),s=Math.cos(t);if(this.rotationMatrix=[s,-i,i,s],this.reverseRotationMatrix=[s,i,-i,s],this.yStretch=1/Math.cos(e/180*Math.PI),this.yStretch=Math.pow(this.yStretch,1.3),this.collisionBoxArray=r,0===r.length){r.emplaceBack();r.emplaceBack(0,0,0,-32767,0,32767,32767,0,0,0,0,0,0,0,0,0),r.emplaceBack(a,0,0,-32767,0,32767,32767,0,0,0,0,0,0,0,0,0),r.emplaceBack(0,0,-32767,0,32767,0,32767,0,0,0,0,0,0,0,0,0),r.emplaceBack(0,a,-32767,0,32767,0,32767,0,0,0,0,0,0,0,0,0)}this.tempCollisionBox=r.get(0),this.edges=[r.get(1),r.get(2),r.get(3),r.get(4)]}var i=t(\"point-geometry\"),a=t(\"../data/bucket\").EXTENT,o=t(\"grid-index\");e.exports=n,n.prototype.serialize=function(){var t={angle:this.angle,pitch:this.pitch,grid:this.grid.toArrayBuffer(),ignoredGrid:this.ignoredGrid.toArrayBuffer()};return{data:t,transferables:[t.grid,t.ignoredGrid]}},n.prototype.minScale=.25,n.prototype.maxScale=2,n.prototype.placeCollisionFeature=function(t,e,r){for(var n=this.collisionBoxArray,a=this.minScale,o=this.rotationMatrix,s=this.yStretch,l=t.boxStartIndex;l<t.boxEndIndex;l++){var u=n.get(l),c=u.anchorPoint._matMult(o),h=c.x,f=c.y,d=h+u.x1,p=f+u.y1*s,m=h+u.x2,g=f+u.y2*s;if(u.bbox0=d,u.bbox1=p,u.bbox2=m,u.bbox3=g,!e)for(var v=this.grid.query(d,p,m,g),y=0;y<v.length;y++){var b=n.get(v[y]),x=b.anchorPoint._matMult(o);if((a=this.getPlacementScale(a,c,u,x,b))>=this.maxScale)return a}if(r){var _;if(this.angle){var w=this.reverseRotationMatrix,M=new i(u.x1,u.y1).matMult(w),k=new i(u.x2,u.y1).matMult(w),A=new i(u.x1,u.y2).matMult(w),T=new i(u.x2,u.y2).matMult(w);(_=this.tempCollisionBox).anchorPointX=u.anchorPoint.x,_.anchorPointY=u.anchorPoint.y,_.x1=Math.min(M.x,k.x,A.x,T.x),_.y1=Math.min(M.y,k.x,A.x,T.x),_.x2=Math.max(M.x,k.x,A.x,T.x),_.y2=Math.max(M.y,k.x,A.x,T.x),_.maxScale=u.maxScale}else _=u;for(var S=0;S<this.edges.length;S++){var E=this.edges[S];if((a=this.getPlacementScale(a,u.anchorPoint,_,E.anchorPoint,E))>=this.maxScale)return a}}}return a},n.prototype.queryRenderedSymbols=function(t,e,r,n,a){var o={},s=[],l=this.collisionBoxArray,u=this.rotationMatrix,c=new i(t,e)._matMult(u),h=this.tempCollisionBox;h.anchorX=c.x,h.anchorY=c.y,h.x1=0,h.y1=0,h.x2=r-t,h.y2=n-e,h.maxScale=a,a=h.maxScale;for(var f=[c.x+h.x1/a,c.y+h.y1/a*this.yStretch,c.x+h.x2/a,c.y+h.y2/a*this.yStretch],d=this.grid.query(f[0],f[1],f[2],f[3]),p=this.ignoredGrid.query(f[0],f[1],f[2],f[3]),m=0;m<p.length;m++)d.push(p[m]);for(var g=0;g<d.length;g++){var v=l.get(d[g]),y=v.sourceLayerIndex,b=v.featureIndex;if(void 0===o[y]&&(o[y]={}),!o[y][b]){var x=v.anchorPoint.matMult(u);this.getPlacementScale(this.minScale,c,h,x,v)>=a&&(o[y][b]=!0,s.push(d[g]))}}return s},n.prototype.getPlacementScale=function(t,e,r,n,i){var a=e.x-n.x,o=e.y-n.y,s=(i.x1-r.x2)/a,l=(i.x2-r.x1)/a,u=(i.y1-r.y2)*this.yStretch/o,c=(i.y2-r.y1)*this.yStretch/o;(isNaN(s)||isNaN(l))&&(s=l=1),(isNaN(u)||isNaN(c))&&(u=c=1);var h=Math.min(Math.max(s,l),Math.max(u,c)),f=i.maxScale,d=r.maxScale;return h>f&&(h=f),h>d&&(h=d),h>t&&h>=i.placementScale&&(t=h),t},n.prototype.insertCollisionFeature=function(t,e,r){for(var n=r?this.ignoredGrid:this.grid,i=this.collisionBoxArray,a=t.boxStartIndex;a<t.boxEndIndex;a++){var o=i.get(a);o.placementScale=e,e<this.maxScale&&n.insert(a,o.bbox0,o.bbox1,o.bbox2,o.bbox3)}}},{\"../data/bucket\":311,\"grid-index\":271,\"point-geometry\":465}],379:[function(t,e,r){\"use strict\";function n(t,e,r,n,a,o,s,l,u){var c=n?.6*o*s:0,h=Math.max(n?n.right-n.left:0,a?a.right-a.left:0),f=0===t[0].x||t[0].x===u||0===t[0].y||t[0].y===u;e-h*s<e/4&&(e=h*s+e/4);var d=2*o;return i(t,f?e/2*l%e:(h/2+d)*s*l%e,e,c,r,h*s,f,!1,u)}function i(t,e,r,n,l,u,c,h,f){for(var d=u/2,p=0,m=0;m<t.length-1;m++)p+=t[m].dist(t[m+1]);for(var g=0,v=e-r,y=[],b=0;b<t.length-1;b++){for(var x=t[b],_=t[b+1],w=x.dist(_),M=_.angleTo(x);v+r<g+w;){var k=((v+=r)-g)/w,A=a(x.x,_.x,k),T=a(x.y,_.y,k);if(A>=0&&A<f&&T>=0&&T<f&&v-d>=0&&v+d<=p){var S=new o(A,T,M,b)._round();n&&!s(t,S,u,n,l)||y.push(S)}}g+=w}return h||y.length||c||(y=i(t,g/2,r,n,l,u,c,!0,f)),y}var a=t(\"../util/interpolate\"),o=t(\"../symbol/anchor\"),s=t(\"./check_max_angle\");e.exports=n},{\"../symbol/anchor\":373,\"../util/interpolate\":418,\"./check_max_angle\":374}],380:[function(t,e,r){\"use strict\";function n(){this.width=o,this.height=o,this.bin=new i(this.width,this.height),this.index={},this.ids={},this.data=new Uint8Array(this.width*this.height)}var i=t(\"shelf-pack\"),a=t(\"../util/util\"),o=128;e.exports=n,n.prototype.getGlyphs=function(){var t,e,r,n={};for(var i in this.ids)e=(t=i.split(\"#\"))[0],r=t[1],n[e]||(n[e]=[]),n[e].push(r);return n},n.prototype.getRects=function(){var t,e,r,n={};for(var i in this.ids)e=(t=i.split(\"#\"))[0],r=t[1],n[e]||(n[e]={}),n[e][r]=this.index[i];return n},n.prototype.addGlyph=function(t,e,r,n){if(!r)return null;var i=e+\"#\"+r.id;if(this.index[i])return this.ids[i].indexOf(t)<0&&this.ids[i].push(t),this.index[i];if(!r.bitmap)return null;var o=r.width+2*n,s=r.height+2*n,l=o+2,u=s+2;l+=4-l%4,u+=4-u%4;var c=this.bin.packOne(l,u);if(c||(this.resize(),c=this.bin.packOne(l,u)),!c)return a.warnOnce(\"glyph bitmap overflow\"),null;this.index[i]=c,this.ids[i]=[t];for(var h=this.data,f=r.bitmap,d=0;d<s;d++)for(var p=this.width*(c.y+d+1)+c.x+1,m=o*d,g=0;g<o;g++)h[p+g]=f[m+g];return this.dirty=!0,c},n.prototype.resize=function(){var t=this.width,e=this.height;if(!(t>=2048||e>=2048)){this.texture&&(this.gl&&this.gl.deleteTexture(this.texture),this.texture=null),this.width*=4,this.height*=4,this.bin.resize(this.width,this.height);for(var r=new ArrayBuffer(this.width*this.height),n=0;n<e;n++){var i=new Uint8Array(this.data.buffer,e*n,t);new Uint8Array(r,e*n*4,t).set(i)}this.data=new Uint8Array(r)}},n.prototype.bind=function(t){this.gl=t,this.texture?t.bindTexture(t.TEXTURE_2D,this.texture):(this.texture=t.createTexture(),t.bindTexture(t.TEXTURE_2D,this.texture),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.LINEAR),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.LINEAR),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),t.texImage2D(t.TEXTURE_2D,0,t.ALPHA,this.width,this.height,0,t.ALPHA,t.UNSIGNED_BYTE,null))},n.prototype.updateTexture=function(t){this.bind(t),this.dirty&&(t.texSubImage2D(t.TEXTURE_2D,0,0,0,this.width,this.height,t.ALPHA,t.UNSIGNED_BYTE,this.data),this.dirty=!1)}},{\"../util/util\":424,\"shelf-pack\":495}],381:[function(t,e,r){\"use strict\";function n(t){this.url=t&&o(t),this.atlases={},this.stacks={},this.loading={}}function i(t,e,r){this.advance=t.advance,this.left=t.left-r-1,this.top=t.top+r+1,this.rect=e}function a(t,e,r,n){return n=n||\"abc\",r.replace(\"{s}\",n[t.length%n.length]).replace(\"{fontstack}\",t).replace(\"{range}\",e)}var o=t(\"../util/mapbox\").normalizeGlyphsURL,s=t(\"../util/ajax\").getArrayBuffer,l=t(\"../util/glyphs\"),u=t(\"../symbol/glyph_atlas\"),c=t(\"pbf\");e.exports=n,n.prototype.getSimpleGlyphs=function(t,e,r,n){void 0===this.stacks[t]&&(this.stacks[t]={}),void 0===this.atlases[t]&&(this.atlases[t]=new u);for(var a,o={},s=this.stacks[t],l=this.atlases[t],c={},h=0,f=0;f<e.length;f++){var d=e[f];if(a=Math.floor(d/256),s[a]){var p=s[a].glyphs[d],m=l.addGlyph(r,t,p,3);p&&(o[d]=new i(p,m,3))}else void 0===c[a]&&(c[a]=[],h++),c[a].push(d)}h||n(void 0,o,t);var g=function(e,a,s){if(!e)for(var u=this.stacks[t][a]=s.stacks[0],f=0;f<c[a].length;f++){var d=c[a][f],p=u.glyphs[d],m=l.addGlyph(r,t,p,3);p&&(o[d]=new i(p,m,3))}--h||n(void 0,o,t)}.bind(this);for(var v in c)this.loadRange(t,v,g)},n.prototype.loadRange=function(t,e,r){if(256*e>65535)return r(\"glyphs > 65535 not supported\");void 0===this.loading[t]&&(this.loading[t]={});var n=this.loading[t];if(n[e])n[e].push(r);else{n[e]=[r];var i=a(t,256*e+\"-\"+(256*e+255),this.url);s(i,function(t,r){for(var i=!t&&new l(new c(new Uint8Array(r))),a=0;a<n[e].length;a++)n[e][a](t,e,i);delete n[e]})}},n.prototype.getGlyphAtlas=function(t){return this.atlases[t]}},{\"../symbol/glyph_atlas\":380,\"../util/ajax\":407,\"../util/glyphs\":417,\"../util/mapbox\":421,pbf:459}],382:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){function n(n){c.push(t[n]),h.push(r[n]),f.push(e[n]),d++}function i(t,e,r){var n=u[t];return delete u[t],u[e]=n,h[n][0].pop(),h[n][0]=h[n][0].concat(r[0]),n}function a(t,e,r){var n=l[e];return delete l[e],l[t]=n,h[n][0].shift(),h[n][0]=r[0].concat(h[n][0]),n}function o(t,e,r){var n=r?e[0][e[0].length-1]:e[0][0];return t+\":\"+n.x+\":\"+n.y}var s,l={},u={},c=[],h=[],f=[],d=0;for(s=0;s<t.length;s++){var p=r[s],m=e[s];if(m){var g=o(m,p),v=o(m,p,!0);if(g in u&&v in l&&u[g]!==l[v]){var y=a(g,v,p),b=i(g,v,h[y]);delete l[g],delete u[v],u[o(m,h[b],!0)]=b,h[y]=null}else g in u?i(g,v,p):v in l?a(g,v,p):(n(s),l[g]=d-1,u[v]=d-1)}else n(s)}return{features:c,textFeatures:f,geometries:h}}},{}],383:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s,l,u){this.anchorPoint=t,this.tl=e,this.tr=r,this.bl=n,this.br=i,this.tex=a,this.anchorAngle=o,this.glyphAngle=s,this.minScale=l,this.maxScale=u}function i(t,e,r,i,a,o,u,c,h){var f,d,p,m,g=e.image.rect,v=a.layout,y=e.left-1,b=y+g.w/e.image.pixelRatio,x=e.top-1,_=x+g.h/e.image.pixelRatio;if(\"none\"!==v[\"icon-text-fit\"]&&u){var w=b-y,M=_-x,k=v[\"text-size\"]/24,A=u.left*k,T=u.right*k,S=u.top*k,E=T-A,L=u.bottom*k-S,C=v[\"icon-text-fit-padding\"][0],z=v[\"icon-text-fit-padding\"][1],D=v[\"icon-text-fit-padding\"][2],I=v[\"icon-text-fit-padding\"][3],P=\"width\"===v[\"icon-text-fit\"]?.5*(L-M):0,O=\"height\"===v[\"icon-text-fit\"]?.5*(E-w):0,j=\"width\"===v[\"icon-text-fit\"]||\"both\"===v[\"icon-text-fit\"]?E:w,R=\"height\"===v[\"icon-text-fit\"]||\"both\"===v[\"icon-text-fit\"]?L:M;f=new s(A+O-I,S+P-C),d=new s(A+O+z+j,S+P-C),p=new s(A+O+z+j,S+P+D+R),m=new s(A+O-I,S+P+D+R)}else f=new s(y,x),d=new s(b,x),p=new s(b,_),m=new s(y,_);var F=a.getLayoutValue(\"icon-rotate\",c,h)*Math.PI/180;if(o){var N=i[t.segment];if(t.y===N.y&&t.x===N.x&&t.segment+1<i.length){var B=i[t.segment+1];F+=Math.atan2(t.y-B.y,t.x-B.x)+Math.PI}else F+=Math.atan2(t.y-N.y,t.x-N.x)}if(F){var U=Math.sin(F),V=Math.cos(F),H=[V,-U,U,V];f=f.matMult(H),d=d.matMult(H),m=m.matMult(H),p=p.matMult(H)}return[new n(new s(t.x,t.y),f,d,m,p,e.image.rect,0,0,l,1/0)]}function a(t,e,r,i,a,u){for(var c=a.layout[\"text-rotate\"]*Math.PI/180,h=a.layout[\"text-keep-upright\"],f=e.positionedGlyphs,d=[],p=0;p<f.length;p++){var m=f[p],g=m.glyph,v=g.rect;if(v){var y,b=(m.x+g.advance/2)*r,x=l;u?(x=o(y=[],t,b,i,t.segment,!0),h&&(x=Math.min(x,o(y,t,b,i,t.segment,!1)))):y=[{anchorPoint:new s(t.x,t.y),offset:0,angle:0,maxScale:1/0,minScale:l}];for(var _=m.x+g.left,w=m.y-g.top,M=_+v.w,k=w+v.h,A=new s(_,w),T=new s(M,w),S=new s(_,k),E=new s(M,k),L=0;L<y.length;L++){var C=y[L],z=A,D=T,I=S,P=E;if(c){var O=Math.sin(c),j=Math.cos(c),R=[j,-O,O,j];z=z.matMult(R),D=D.matMult(R),I=I.matMult(R),P=P.matMult(R)}var F=Math.max(C.minScale,x),N=(t.angle+C.offset+2*Math.PI)%(2*Math.PI),B=(C.angle+C.offset+2*Math.PI)%(2*Math.PI);d.push(new n(C.anchorPoint,z,D,I,P,v,N,B,F,C.maxScale))}}}return d}function o(t,e,r,n,i,a){var o=!a;r<0&&(a=!a),a&&i++;var u=new s(e.x,e.y),c=n[i],h=1/0;r=Math.abs(r);for(var f=l;;){var d=u.dist(c),p=r/d,m=Math.atan2(c.y-u.y,c.x-u.x);if(a||(m+=Math.PI),t.push({anchorPoint:u,offset:o?Math.PI:0,minScale:p,maxScale:h,angle:(m+2*Math.PI)%(2*Math.PI)}),p<=f)break;for(u=c;u.equals(c);)if(i+=a?1:-1,!(c=n[i]))return p;var g=c.sub(u)._unit();u=u.sub(g._mult(d)),h=p}return f}var s=t(\"point-geometry\");e.exports={getIconQuads:i,getGlyphQuads:a,SymbolQuad:n};var l=.5},{\"point-geometry\":465}],384:[function(t,e,r){\"use strict\";function n(t,e,r){for(var n=[],a=0,o=t.length;a<o;a++){var s=i(t[a].properties,e[\"text-field\"]);if(s){s=s.toString();var l=e[\"text-transform\"];\"uppercase\"===l?s=s.toLocaleUpperCase():\"lowercase\"===l&&(s=s.toLocaleLowerCase());for(var u=0;u<s.length;u++)r[s.charCodeAt(u)]=!0;n[a]=s}else n[a]=null}return n}var i=t(\"../util/token\");e.exports=n},{\"../util/token\":423}],385:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.codePoint=t,this.x=e,this.y=r,this.glyph=n}function i(t,e,r,n,i,a){this.positionedGlyphs=t,this.text=e,this.top=r,this.bottom=n,this.left=i,this.right=a}function a(t,e,r,a,s,l,u,c,h){for(var f=[],d=new i(f,t,h[1],h[1],h[0],h[0]),p=0,m=0;m<t.length;m++){var g=t.charCodeAt(m),v=e[g];v&&(f.push(new n(g,p,-17,v)),p+=v.advance+c)}return!!f.length&&(o(d,e,a,r,s,l,u,h),d)}function o(t,e,r,n,i,a,o,u){var c=null,d=0,p=0,m=0,g=0,v=t.positionedGlyphs;if(n)for(var y=0;y<v.length;y++){var b=v[y];if(b.x-=d,b.y+=r*m,b.x>n&&null!==c){var x=v[c+1].x;g=Math.max(x,g);for(var _=c+1;_<=y;_++)v[_].y+=r,v[_].x-=x;if(o){var w=c;h[v[c].codePoint]&&w--,s(v,e,p,w,o)}p=c+1,c=null,d+=x,m++}f[b.codePoint]&&(c=y)}var M=v[v.length-1],k=M.x+e[M.codePoint].advance;g=Math.max(g,k);var A=(m+1)*r;s(v,e,p,v.length-1,o),l(v,o,i,a,g,r,m,u),t.top+=-a*A,t.bottom=t.top+A,t.left+=-i*g,t.right=t.left+g}function s(t,e,r,n,i){for(var a=e[t[n].codePoint].advance,o=(t[n].x+a)*i,s=r;s<=n;s++)t[s].x-=o}function l(t,e,r,n,i,a,o,s){for(var l=(e-r)*i+s[0],u=(-n*(o+1)+.5)*a+s[1],c=0;c<t.length;c++)t[c].x+=l,t[c].y+=u}function u(t,e){if(!t||!t.rect)return null;var r=e[\"icon-offset\"][0],n=e[\"icon-offset\"][1],i=r-t.width/2,a=i+t.width,o=n-t.height/2;return new c(t,o,o+t.height,i,a)}function c(t,e,r,n,i){this.image=t,this.top=e,this.bottom=r,this.left=n,this.right=i}e.exports={shapeText:a,shapeIcon:u};var h={32:!0,8203:!0},f={32:!0,38:!0,43:!0,45:!0,47:!0,173:!0,183:!0,8203:!0,8208:!0,8211:!0}},{}],386:[function(t,e,r){\"use strict\";function n(t,e){this.width=t,this.height=e,this.bin=new o(t,e),this.images={},this.data=!1,this.texture=0,this.filter=0,this.pixelRatio=1,this.dirty=!0}function i(t,e,r,n,i,a,o,s,l,u,c){var h,f,d=n*e+r,p=s*a+o;if(c)for(p-=a,f=-1;f<=u;f++,d=((f+u)%u+n)*e+r,p+=a)for(h=-1;h<=l;h++)i[p+h]=t[d+(h+l)%l];else for(f=0;f<u;f++,d+=e,p+=a)for(h=0;h<l;h++)i[p+h]=t[d+h]}function a(t,e,r,n,i){this.rect=t,this.width=e,this.height=r,this.sdf=n,this.pixelRatio=i}var o=t(\"shelf-pack\"),s=t(\"../util/browser\"),l=t(\"../util/util\");e.exports=n,n.prototype.allocateImage=function(t,e){var r=(t/=this.pixelRatio)+2+(4-(t+2)%4),n=(e/=this.pixelRatio)+2+(4-(e+2)%4),i=this.bin.packOne(r,n);return i||(l.warnOnce(\"SpriteAtlas out of space.\"),null)},n.prototype.getImage=function(t,e){if(this.images[t])return this.images[t];if(!this.sprite)return null;var r=this.sprite.getSpritePosition(t);if(!r.width||!r.height)return null;var n=this.allocateImage(r.width,r.height);if(!n)return null;var i=new a(n,r.width/r.pixelRatio,r.height/r.pixelRatio,r.sdf,r.pixelRatio/this.pixelRatio);return this.images[t]=i,this.copy(n,r,e),i},n.prototype.getPosition=function(t,e){var r=this.getImage(t,e),n=r&&r.rect;if(!n)return null;var i=r.width*r.pixelRatio,a=r.height*r.pixelRatio;return{size:[r.width,r.height],tl:[(n.x+1)/this.width,(n.y+1)/this.height],br:[(n.x+1+i)/this.width,(n.y+1+a)/this.height]}},n.prototype.allocate=function(){if(!this.data){var t=Math.floor(this.width*this.pixelRatio),e=Math.floor(this.height*this.pixelRatio);this.data=new Uint32Array(t*e);for(var r=0;r<this.data.length;r++)this.data[r]=0}},n.prototype.copy=function(t,e,r){if(this.sprite.img.data){var n=new Uint32Array(this.sprite.img.data.buffer);this.allocate();var a=this.data;i(n,this.sprite.img.width,e.x,e.y,a,this.width*this.pixelRatio,(t.x+1)*this.pixelRatio,(t.y+1)*this.pixelRatio,e.width,e.height,r),this.dirty=!0}},n.prototype.setSprite=function(t){t&&(this.pixelRatio=s.devicePixelRatio>1?2:1,this.canvas&&(this.canvas.width=this.width*this.pixelRatio,this.canvas.height=this.height*this.pixelRatio)),this.sprite=t},n.prototype.addIcons=function(t,e){for(var r=0;r<t.length;r++)this.getImage(t[r]);e(null,this.images)},n.prototype.bind=function(t,e){var r=!1;this.texture?t.bindTexture(t.TEXTURE_2D,this.texture):(this.texture=t.createTexture(),t.bindTexture(t.TEXTURE_2D,this.texture),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),r=!0);var n=e?t.LINEAR:t.NEAREST;n!==this.filter&&(t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,n),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,n),this.filter=n),this.dirty&&(this.allocate(),r?t.texImage2D(t.TEXTURE_2D,0,t.RGBA,this.width*this.pixelRatio,this.height*this.pixelRatio,0,t.RGBA,t.UNSIGNED_BYTE,new Uint8Array(this.data.buffer)):t.texSubImage2D(t.TEXTURE_2D,0,0,0,this.width*this.pixelRatio,this.height*this.pixelRatio,t.RGBA,t.UNSIGNED_BYTE,new Uint8Array(this.data.buffer)),this.dirty=!1)}},{\"../util/browser\":408,\"../util/util\":424,\"shelf-pack\":495}],387:[function(t,e,r){\"use strict\";var n=t(\"../util/struct_array\"),i=t(\"../util/util\"),a=t(\"point-geometry\"),o=e.exports=new n({members:[{type:\"Uint16\",name:\"textBoxStartIndex\"},{type:\"Uint16\",name:\"textBoxEndIndex\"},{type:\"Uint16\",name:\"iconBoxStartIndex\"},{type:\"Uint16\",name:\"iconBoxEndIndex\"},{type:\"Uint16\",name:\"glyphQuadStartIndex\"},{type:\"Uint16\",name:\"glyphQuadEndIndex\"},{type:\"Uint16\",name:\"iconQuadStartIndex\"},{type:\"Uint16\",name:\"iconQuadEndIndex\"},{type:\"Int16\",name:\"anchorPointX\"},{type:\"Int16\",name:\"anchorPointY\"},{type:\"Int8\",name:\"index\"}]});i.extendAll(o.prototype.StructType.prototype,{get anchorPoint(){return new a(this.anchorPointX,this.anchorPointY)}})},{\"../util/struct_array\":422,\"../util/util\":424,\"point-geometry\":465}],388:[function(t,e,r){\"use strict\";var n=t(\"../util/struct_array\"),i=t(\"../util/util\"),a=t(\"point-geometry\"),o=t(\"./quads\").SymbolQuad,s=e.exports=new n({members:[{type:\"Int16\",name:\"anchorPointX\"},{type:\"Int16\",name:\"anchorPointY\"},{type:\"Float32\",name:\"tlX\"},{type:\"Float32\",name:\"tlY\"},{type:\"Float32\",name:\"trX\"},{type:\"Float32\",name:\"trY\"},{type:\"Float32\",name:\"blX\"},{type:\"Float32\",name:\"blY\"},{type:\"Float32\",name:\"brX\"},{type:\"Float32\",name:\"brY\"},{type:\"Int16\",name:\"texH\"},{type:\"Int16\",name:\"texW\"},{type:\"Int16\",name:\"texX\"},{type:\"Int16\",name:\"texY\"},{type:\"Float32\",name:\"anchorAngle\"},{type:\"Float32\",name:\"glyphAngle\"},{type:\"Float32\",name:\"maxScale\"},{type:\"Float32\",name:\"minScale\"}]});i.extendAll(s.prototype.StructType.prototype,{get anchorPoint(){return new a(this.anchorPointX,this.anchorPointY)},get SymbolQuad(){return new o(this.anchorPoint,new a(this.tlX,this.tlY),new a(this.trX,this.trY),new a(this.blX,this.blY),new a(this.brX,this.brY),{x:this.texX,y:this.texY,h:this.texH,w:this.texW,height:this.texH,width:this.texW},this.anchorAngle,this.glyphAngle,this.minScale,this.maxScale)}})},{\"../util/struct_array\":422,\"../util/util\":424,\"./quads\":383,\"point-geometry\":465}],389:[function(t,e,r){\"use strict\";var n=t(\"../util/dom\"),i=t(\"point-geometry\"),a={scrollZoom:t(\"./handler/scroll_zoom\"),boxZoom:t(\"./handler/box_zoom\"),dragRotate:t(\"./handler/drag_rotate\"),dragPan:t(\"./handler/drag_pan\"),keyboard:t(\"./handler/keyboard\"),doubleClickZoom:t(\"./handler/dblclick_zoom\"),touchZoomRotate:t(\"./handler/touch_zoom_rotate\")};e.exports=function(t,e){function r(t){v(\"mouseout\",t)}function o(e){t.stop(),_=n.mousePos(b,e),v(\"mousedown\",e)}function s(e){var r=t.dragRotate&&t.dragRotate.isActive();x&&!r&&v(\"contextmenu\",x),x=null,v(\"mouseup\",e)}function l(e){if(!(t.dragPan&&t.dragPan.isActive()||t.dragRotate&&t.dragRotate.isActive())){for(var r=e.toElement||e.target;r&&r!==b;)r=r.parentNode;r===b&&v(\"mousemove\",e)}}function u(e){t.stop(),y(\"touchstart\",e),!e.touches||e.touches.length>1||(w?(clearTimeout(w),w=null,v(\"dblclick\",e)):w=setTimeout(d,300))}function c(t){y(\"touchmove\",t)}function h(t){y(\"touchend\",t)}function f(t){y(\"touchcancel\",t)}function d(){w=null}function p(t){n.mousePos(b,t).equals(_)&&v(\"click\",t)}function m(t){v(\"dblclick\",t),t.preventDefault()}function g(t){x=t,t.preventDefault()}function v(e,r){var i=n.mousePos(b,r);return t.fire(e,{lngLat:t.unproject(i),point:i,originalEvent:r})}function y(e,r){var a=n.touchPos(b,r),o=a.reduce(function(t,e,r,n){return t.add(e.div(n.length))},new i(0,0));return t.fire(e,{lngLat:t.unproject(o),point:o,lngLats:a.map(function(e){return t.unproject(e)},this),points:a,originalEvent:r})}var b=t.getCanvasContainer(),x=null,_=null,w=null;for(var M in a)t[M]=new a[M](t,e),e.interactive&&e[M]&&t[M].enable();b.addEventListener(\"mouseout\",r,!1),b.addEventListener(\"mousedown\",o,!1),b.addEventListener(\"mouseup\",s,!1),b.addEventListener(\"mousemove\",l,!1),b.addEventListener(\"touchstart\",u,!1),b.addEventListener(\"touchend\",h,!1),b.addEventListener(\"touchmove\",c,!1),b.addEventListener(\"touchcancel\",f,!1),b.addEventListener(\"click\",p,!1),b.addEventListener(\"dblclick\",m,!1),b.addEventListener(\"contextmenu\",g,!1)}},{\"../util/dom\":410,\"./handler/box_zoom\":395,\"./handler/dblclick_zoom\":396,\"./handler/drag_pan\":397,\"./handler/drag_rotate\":398,\"./handler/keyboard\":399,\"./handler/scroll_zoom\":400,\"./handler/touch_zoom_rotate\":401,\"point-geometry\":465}],390:[function(t,e,r){\"use strict\";var n=t(\"../util/util\"),i=t(\"../util/interpolate\"),a=t(\"../util/browser\"),o=t(\"../geo/lng_lat\"),s=t(\"../geo/lng_lat_bounds\"),l=t(\"point-geometry\"),u=e.exports=function(){};n.extend(u.prototype,{getCenter:function(){return this.transform.center},setCenter:function(t,e){return this.jumpTo({center:t},e),this},panBy:function(t,e,r){return this.panTo(this.transform.center,n.extend({offset:l.convert(t).mult(-1)},e),r),this},panTo:function(t,e,r){return this.easeTo(n.extend({center:t},e),r)},getZoom:function(){return this.transform.zoom},setZoom:function(t,e){return this.jumpTo({zoom:t},e),this},zoomTo:function(t,e,r){return this.easeTo(n.extend({zoom:t},e),r)},zoomIn:function(t,e){return this.zoomTo(this.getZoom()+1,t,e),this},zoomOut:function(t,e){return this.zoomTo(this.getZoom()-1,t,e),this},getBearing:function(){return this.transform.bearing},setBearing:function(t,e){return this.jumpTo({bearing:t},e),this},rotateTo:function(t,e,r){return this.easeTo(n.extend({bearing:t},e),r)},resetNorth:function(t,e){return this.rotateTo(0,n.extend({duration:1e3},t),e),this},snapToNorth:function(t,e){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(t,e):this},getPitch:function(){return this.transform.pitch},setPitch:function(t,e){return this.jumpTo({pitch:t},e),this},fitBounds:function(t,e,r){e=n.extend({padding:0,offset:[0,0],maxZoom:1/0},e),t=s.convert(t);var i=l.convert(e.offset),a=this.transform,o=a.project(t.getNorthWest()),u=a.project(t.getSouthEast()),c=u.sub(o),h=(a.width-2*e.padding-2*Math.abs(i.x))/c.x,f=(a.height-2*e.padding-2*Math.abs(i.y))/c.y;return e.center=a.unproject(o.add(u).div(2)),e.zoom=Math.min(a.scaleZoom(a.scale*Math.min(h,f)),e.maxZoom),e.bearing=0,e.linear?this.easeTo(e,r):this.flyTo(e,r)},jumpTo:function(t,e){this.stop();var r=this.transform,n=!1,i=!1,a=!1;return\"zoom\"in t&&r.zoom!==+t.zoom&&(n=!0,r.zoom=+t.zoom),\"center\"in t&&(r.center=o.convert(t.center)),\"bearing\"in t&&r.bearing!==+t.bearing&&(i=!0,r.bearing=+t.bearing),\"pitch\"in t&&r.pitch!==+t.pitch&&(a=!0,r.pitch=+t.pitch),this.fire(\"movestart\",e).fire(\"move\",e),n&&this.fire(\"zoomstart\",e).fire(\"zoom\",e).fire(\"zoomend\",e),i&&this.fire(\"rotate\",e),a&&this.fire(\"pitch\",e),this.fire(\"moveend\",e)},easeTo:function(t,e){this.stop(),t=n.extend({offset:[0,0],duration:500,easing:n.ease},t);var r,a,s=this.transform,u=l.convert(t.offset),c=this.getZoom(),h=this.getBearing(),f=this.getPitch(),d=\"zoom\"in t?+t.zoom:c,p=\"bearing\"in t?this._normalizeBearing(t.bearing,h):h,m=\"pitch\"in t?+t.pitch:f;\"center\"in t?(r=o.convert(t.center),a=s.centerPoint.add(u)):\"around\"in t?(r=o.convert(t.around),a=s.locationPoint(r)):(a=s.centerPoint.add(u),r=s.pointLocation(a));var g=s.locationPoint(r);return!1===t.animate&&(t.duration=0),this.zooming=d!==c,this.rotating=h!==p,this.pitching=m!==f,t.noMoveStart||this.fire(\"movestart\",e),this.zooming&&this.fire(\"zoomstart\",e),clearTimeout(this._onEaseEnd),this._ease(function(t){this.zooming&&(s.zoom=i(c,d,t)),this.rotating&&(s.bearing=i(h,p,t)),this.pitching&&(s.pitch=i(f,m,t)),s.setLocationAtPoint(r,g.add(a.sub(g)._mult(t))),this.fire(\"move\",e),this.zooming&&this.fire(\"zoom\",e),this.rotating&&this.fire(\"rotate\",e),this.pitching&&this.fire(\"pitch\",e)},function(){t.delayEndEvents?this._onEaseEnd=setTimeout(this._easeToEnd.bind(this,e),t.delayEndEvents):this._easeToEnd(e)}.bind(this),t),this},_easeToEnd:function(t){var e=this.zooming;this.zooming=!1,this.rotating=!1,this.pitching=!1,e&&this.fire(\"zoomend\",t),this.fire(\"moveend\",t)},flyTo:function(t,e){function r(t){var e=(A*A-k*k+(t?-1:1)*L*L*T*T)/(2*(t?A:k)*L*T);return Math.log(Math.sqrt(e*e+1)-e)}function a(t){return(Math.exp(t)-Math.exp(-t))/2}function s(t){return(Math.exp(t)+Math.exp(-t))/2}function u(t){return a(t)/s(t)}this.stop(),t=n.extend({offset:[0,0],speed:1.2,curve:1.42,easing:n.ease},t);var c=this.transform,h=l.convert(t.offset),f=this.getZoom(),d=this.getBearing(),p=this.getPitch(),m=\"center\"in t?o.convert(t.center):this.getCenter(),g=\"zoom\"in t?+t.zoom:f,v=\"bearing\"in t?this._normalizeBearing(t.bearing,d):d,y=\"pitch\"in t?+t.pitch:p;Math.abs(c.center.lng)+Math.abs(m.lng)>180&&(c.center.lng>0&&m.lng<0?m.lng+=360:c.center.lng<0&&m.lng>0&&(m.lng-=360));var b=c.zoomScale(g-f),x=c.point,_=\"center\"in t?c.project(m).sub(h.div(b)):x,w=c.worldSize,M=t.curve,k=Math.max(c.width,c.height),A=k/b,T=_.sub(x).mag();if(\"minZoom\"in t){var S=n.clamp(Math.min(t.minZoom,f,g),c.minZoom,c.maxZoom),E=k/c.zoomScale(S-f);M=Math.sqrt(E/T*2)}var L=M*M,C=r(0),z=function(t){return s(C)/s(C+M*t)},D=function(t){return k*((s(C)*u(C+M*t)-a(C))/L)/T},I=(r(1)-C)/M;if(Math.abs(T)<1e-6){if(Math.abs(k-A)<1e-6)return this.easeTo(t);var P=A<k?-1:1;I=Math.abs(Math.log(A/k))/M,D=function(){return 0},z=function(t){return Math.exp(P*M*t)}}if(\"duration\"in t)t.duration=+t.duration;else{var O=\"screenSpeed\"in t?+t.screenSpeed/M:+t.speed;t.duration=1e3*I/O}return this.zooming=!0,d!==v&&(this.rotating=!0),p!==y&&(this.pitching=!0),this.fire(\"movestart\",e),this.fire(\"zoomstart\",e),this._ease(function(t){var r=t*I,n=D(r);c.zoom=f+c.scaleZoom(1/z(r)),c.center=c.unproject(x.add(_.sub(x).mult(n)),w),this.rotating&&(c.bearing=i(d,v,t)),this.pitching&&(c.pitch=i(p,y,t)),this.fire(\"move\",e),this.fire(\"zoom\",e),this.rotating&&this.fire(\"rotate\",e),this.pitching&&this.fire(\"pitch\",e)},function(){this.zooming=!1,this.rotating=!1,this.pitching=!1,this.fire(\"zoomend\",e),this.fire(\"moveend\",e)},t),this},isEasing:function(){return!!this._abortFn},stop:function(){return this._abortFn&&(this._abortFn(),this._finishEase()),this},_ease:function(t,e,r){this._finishFn=e,this._abortFn=a.timed(function(e){t.call(this,r.easing(e)),1===e&&this._finishEase()},!1===r.animate?0:r.duration,this)},_finishEase:function(){delete this._abortFn;var t=this._finishFn;delete this._finishFn,t.call(this)},_normalizeBearing:function(t,e){t=n.wrap(t,-180,180);var r=Math.abs(t-e);return Math.abs(t-360-e)<r&&(t-=360),Math.abs(t+360-e)<r&&(t+=360),t},_updateEasing:function(t,e,r){var i;if(this.ease){var a=this.ease,o=(Date.now()-a.start)/a.duration,s=a.easing(o+.01)-a.easing(o),l=.27/Math.sqrt(s*s+1e-4)*.01,u=Math.sqrt(.0729-l*l);i=n.bezier(l,u,.25,1)}else i=r?n.bezier.apply(n,r):n.ease;return this.ease={start:(new Date).getTime(),to:Math.pow(2,e),duration:t,easing:i},i}})},{\"../geo/lng_lat\":321,\"../geo/lng_lat_bounds\":322,\"../util/browser\":408,\"../util/interpolate\":418,\"../util/util\":424,\"point-geometry\":465}],391:[function(t,e,r){\"use strict\";function n(t){o.setOptions(this,t)}var i=t(\"./control\"),a=t(\"../../util/dom\"),o=t(\"../../util/util\");e.exports=n,n.createAttributionString=function(t){var e=[];for(var r in t){var n=t[r];n.attribution&&e.indexOf(n.attribution)<0&&e.push(n.attribution)}return e.sort(function(t,e){return t.length-e.length}),(e=e.filter(function(t,r){for(var n=r+1;n<e.length;n++)if(e[n].indexOf(t)>=0)return!1;return!0})).join(\" | \")},n.prototype=o.inherit(i,{options:{position:\"bottom-right\"},onAdd:function(t){var e=this._container=a.create(\"div\",\"mapboxgl-ctrl-attrib\",t.getContainer());return this._update(),t.on(\"source.load\",this._update.bind(this)),t.on(\"source.change\",this._update.bind(this)),t.on(\"source.remove\",this._update.bind(this)),t.on(\"moveend\",this._updateEditLink.bind(this)),e},_update:function(){this._map.style&&(this._container.innerHTML=n.createAttributionString(this._map.style.sources)),this._editLink=this._container.getElementsByClassName(\"mapbox-improve-map\")[0],this._updateEditLink()},_updateEditLink:function(){if(this._editLink){var t=this._map.getCenter();this._editLink.href=\"https://www.mapbox.com/map-feedback/#/\"+t.lng+\"/\"+t.lat+\"/\"+Math.round(this._map.getZoom()+1)}}})},{\"../../util/dom\":410,\"../../util/util\":424,\"./control\":392}],392:[function(t,e,r){\"use strict\";function n(){}var i=t(\"../../util/util\"),a=t(\"../../util/evented\");e.exports=n,n.prototype={addTo:function(t){this._map=t;var e=this._container=this.onAdd(t);if(this.options&&this.options.position){var r=this.options.position,n=t._controlCorners[r];e.className+=\" mapboxgl-ctrl\",-1!==r.indexOf(\"bottom\")?n.insertBefore(e,n.firstChild):n.appendChild(e)}return this},remove:function(){return this._container.parentNode.removeChild(this._container),this.onRemove&&this.onRemove(this._map),this._map=null,this}},i.extend(n.prototype,a)},{\"../../util/evented\":416,\"../../util/util\":424}],393:[function(t,e,r){\"use strict\";function n(t){s.setOptions(this,t)}var i=t(\"./control\"),a=t(\"../../util/browser\"),o=t(\"../../util/dom\"),s=t(\"../../util/util\");e.exports=n;var l={enableHighAccuracy:!1,timeout:6e3};n.prototype=s.inherit(i,{options:{position:\"top-right\"},onAdd:function(t){var e=this._container=o.create(\"div\",\"mapboxgl-ctrl-group\",t.getContainer());return a.supportsGeolocation?(this._container.addEventListener(\"contextmenu\",this._onContextMenu.bind(this)),this._geolocateButton=o.create(\"button\",\"mapboxgl-ctrl-icon mapboxgl-ctrl-geolocate\",this._container),this._geolocateButton.type=\"button\",this._geolocateButton.addEventListener(\"click\",this._onClickGeolocate.bind(this)),e):e},_onContextMenu:function(t){t.preventDefault()},_onClickGeolocate:function(){navigator.geolocation.getCurrentPosition(this._success.bind(this),this._error.bind(this),l),this._timeoutId=setTimeout(this._finish.bind(this),1e4)},_success:function(t){this._map.jumpTo({center:[t.coords.longitude,t.coords.latitude],zoom:17,bearing:0,pitch:0}),this.fire(\"geolocate\",t),this._finish()},_error:function(t){this.fire(\"error\",t),this._finish()},_finish:function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0}})},{\"../../util/browser\":408,\"../../util/dom\":410,\"../../util/util\":424,\"./control\":392}],394:[function(t,e,r){\"use strict\";function n(t){s.setOptions(this,t)}function i(t){return new MouseEvent(t.type,{button:2,buttons:2,bubbles:!0,cancelable:!0,detail:t.detail,view:t.view,screenX:t.screenX,screenY:t.screenY,clientX:t.clientX,clientY:t.clientY,movementX:t.movementX,movementY:t.movementY,ctrlKey:t.ctrlKey,shiftKey:t.shiftKey,altKey:t.altKey,metaKey:t.metaKey})}var a=t(\"./control\"),o=t(\"../../util/dom\"),s=t(\"../../util/util\");e.exports=n,n.prototype=s.inherit(a,{options:{position:\"top-right\"},onAdd:function(t){var e=\"mapboxgl-ctrl\",r=this._container=o.create(\"div\",e+\"-group\",t.getContainer());return this._container.addEventListener(\"contextmenu\",this._onContextMenu.bind(this)),this._zoomInButton=this._createButton(e+\"-icon \"+e+\"-zoom-in\",t.zoomIn.bind(t)),this._zoomOutButton=this._createButton(e+\"-icon \"+e+\"-zoom-out\",t.zoomOut.bind(t)),this._compass=this._createButton(e+\"-icon \"+e+\"-compass\",t.resetNorth.bind(t)),this._compassArrow=o.create(\"div\",\"arrow\",this._compass),this._compass.addEventListener(\"mousedown\",this._onCompassDown.bind(this)),this._onCompassMove=this._onCompassMove.bind(this),this._onCompassUp=this._onCompassUp.bind(this),t.on(\"rotate\",this._rotateCompassArrow.bind(this)),this._rotateCompassArrow(),this._el=t.getCanvasContainer(),r},_onContextMenu:function(t){t.preventDefault()},_onCompassDown:function(t){0===t.button&&(o.disableDrag(),document.addEventListener(\"mousemove\",this._onCompassMove),document.addEventListener(\"mouseup\",this._onCompassUp),this._el.dispatchEvent(i(t)),t.stopPropagation())},_onCompassMove:function(t){0===t.button&&(this._el.dispatchEvent(i(t)),t.stopPropagation())},_onCompassUp:function(t){0===t.button&&(document.removeEventListener(\"mousemove\",this._onCompassMove),document.removeEventListener(\"mouseup\",this._onCompassUp),o.enableDrag(),this._el.dispatchEvent(i(t)),t.stopPropagation())},_createButton:function(t,e){var r=o.create(\"button\",t,this._container);return r.type=\"button\",r.addEventListener(\"click\",function(){e()}),r},_rotateCompassArrow:function(){var t=\"rotate(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\";this._compassArrow.style.transform=t}})},{\"../../util/dom\":410,\"../../util/util\":424,\"./control\":392}],395:[function(t,e,r){\"use strict\";function n(t){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),o.bindHandlers(this)}var i=t(\"../../util/dom\"),a=t(\"../../geo/lng_lat_bounds\"),o=t(\"../../util/util\");e.exports=n,n.prototype={_enabled:!1,_active:!1,isEnabled:function(){return this._enabled},isActive:function(){return this._active},enable:function(){this.isEnabled()||(this._el.addEventListener(\"mousedown\",this._onMouseDown,!1),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._el.removeEventListener(\"mousedown\",this._onMouseDown),this._enabled=!1)},_onMouseDown:function(t){t.shiftKey&&0===t.button&&(document.addEventListener(\"mousemove\",this._onMouseMove,!1),document.addEventListener(\"keydown\",this._onKeyDown,!1),document.addEventListener(\"mouseup\",this._onMouseUp,!1),i.disableDrag(),this._startPos=i.mousePos(this._el,t),this._active=!0)},_onMouseMove:function(t){var e=this._startPos,r=i.mousePos(this._el,t);this._box||(this._box=i.create(\"div\",\"mapboxgl-boxzoom\",this._container),this._container.classList.add(\"mapboxgl-crosshair\"),this._fireEvent(\"boxzoomstart\",t));var n=Math.min(e.x,r.x),a=Math.max(e.x,r.x),o=Math.min(e.y,r.y),s=Math.max(e.y,r.y);i.setTransform(this._box,\"translate(\"+n+\"px,\"+o+\"px)\"),this._box.style.width=a-n+\"px\",this._box.style.height=s-o+\"px\"},_onMouseUp:function(t){if(0===t.button){var e=this._startPos,r=i.mousePos(this._el,t),n=new a(this._map.unproject(e),this._map.unproject(r));this._finish(),e.x===r.x&&e.y===r.y?this._fireEvent(\"boxzoomcancel\",t):this._map.fitBounds(n,{linear:!0}).fire(\"boxzoomend\",{originalEvent:t,boxZoomBounds:n})}},_onKeyDown:function(t){27===t.keyCode&&(this._finish(),this._fireEvent(\"boxzoomcancel\",t))},_finish:function(){this._active=!1,document.removeEventListener(\"mousemove\",this._onMouseMove,!1),document.removeEventListener(\"keydown\",this._onKeyDown,!1),document.removeEventListener(\"mouseup\",this._onMouseUp,!1),this._container.classList.remove(\"mapboxgl-crosshair\"),this._box&&(this._box.parentNode.removeChild(this._box),this._box=null),i.enableDrag()},_fireEvent:function(t,e){return this._map.fire(t,{originalEvent:e})}}},{\"../../geo/lng_lat_bounds\":322,\"../../util/dom\":410,\"../../util/util\":424}],396:[function(t,e,r){\"use strict\";function n(t){this._map=t,this._onDblClick=this._onDblClick.bind(this)}e.exports=n,n.prototype={_enabled:!1,isEnabled:function(){return this._enabled},enable:function(){this.isEnabled()||(this._map.on(\"dblclick\",this._onDblClick),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._map.off(\"dblclick\",this._onDblClick),this._enabled=!1)},_onDblClick:function(t){this._map.zoomTo(this._map.getZoom()+(t.originalEvent.shiftKey?-1:1),{around:t.lngLat},t)}}},{}],397:[function(t,e,r){\"use strict\";function n(t){this._map=t,this._el=t.getCanvasContainer(),a.bindHandlers(this)}var i=t(\"../../util/dom\"),a=t(\"../../util/util\");e.exports=n;var o=a.bezier(0,0,.3,1);n.prototype={_enabled:!1,_active:!1,isEnabled:function(){return this._enabled},isActive:function(){return this._active},enable:function(){this.isEnabled()||(this._el.addEventListener(\"mousedown\",this._onDown),this._el.addEventListener(\"touchstart\",this._onDown),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._el.removeEventListener(\"mousedown\",this._onDown),this._el.removeEventListener(\"touchstart\",this._onDown),this._enabled=!1)},_onDown:function(t){this._ignoreEvent(t)||this.isActive()||(t.touches?(document.addEventListener(\"touchmove\",this._onMove),document.addEventListener(\"touchend\",this._onTouchEnd)):(document.addEventListener(\"mousemove\",this._onMove),document.addEventListener(\"mouseup\",this._onMouseUp)),this._active=!1,this._startPos=this._pos=i.mousePos(this._el,t),this._inertia=[[Date.now(),this._pos]])},_onMove:function(t){if(!this._ignoreEvent(t)){this.isActive()||(this._active=!0,this._fireEvent(\"dragstart\",t),this._fireEvent(\"movestart\",t));var e=i.mousePos(this._el,t),r=this._map;r.stop(),this._drainInertiaBuffer(),this._inertia.push([Date.now(),e]),r.transform.setLocationAtPoint(r.transform.pointLocation(this._pos),e),this._fireEvent(\"drag\",t),this._fireEvent(\"move\",t),this._pos=e,t.preventDefault()}},_onUp:function(t){if(this.isActive()){this._active=!1,this._fireEvent(\"dragend\",t),this._drainInertiaBuffer();var e=function(){this._fireEvent(\"moveend\",t)}.bind(this),r=this._inertia;if(r.length<2)e();else{var n=r[r.length-1],i=r[0],a=n[1].sub(i[1]),s=(n[0]-i[0])/1e3;if(0===s||n[1].equals(i[1]))e();else{var l=a.mult(.3/s),u=l.mag();u>1400&&(u=1400,l._unit()._mult(u));var c=u/750,h=l.mult(-c/2);this._map.panBy(h,{duration:1e3*c,easing:o,noMoveStart:!0},{originalEvent:t})}}}},_onMouseUp:function(t){this._ignoreEvent(t)||(this._onUp(t),document.removeEventListener(\"mousemove\",this._onMove),document.removeEventListener(\"mouseup\",this._onMouseUp))},_onTouchEnd:function(t){this._ignoreEvent(t)||(this._onUp(t),document.removeEventListener(\"touchmove\",this._onMove),document.removeEventListener(\"touchend\",this._onTouchEnd))},_fireEvent:function(t,e){return this._map.fire(t,{originalEvent:e})},_ignoreEvent:function(t){var e=this._map;if(e.boxZoom&&e.boxZoom.isActive())return!0;if(e.dragRotate&&e.dragRotate.isActive())return!0;if(t.touches)return t.touches.length>1;if(t.ctrlKey)return!0;return\"mousemove\"===t.type?!1&t.buttons:0!==t.button},_drainInertiaBuffer:function(){for(var t=this._inertia,e=Date.now();t.length>0&&e-t[0][0]>160;)t.shift()}}},{\"../../util/dom\":410,\"../../util/util\":424}],398:[function(t,e,r){\"use strict\";function n(t,e){this._map=t,this._el=t.getCanvasContainer(),this._bearingSnap=e.bearingSnap,o.bindHandlers(this)}var i=t(\"../../util/dom\"),a=t(\"point-geometry\"),o=t(\"../../util/util\");e.exports=n;var s=o.bezier(0,0,.25,1);n.prototype={_enabled:!1,_active:!1,isEnabled:function(){return this._enabled},isActive:function(){return this._active},enable:function(){this.isEnabled()||(this._el.addEventListener(\"mousedown\",this._onDown),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._el.removeEventListener(\"mousedown\",this._onDown),this._enabled=!1)},_onDown:function(t){if(!this._ignoreEvent(t)&&!this.isActive()){document.addEventListener(\"mousemove\",this._onMove),document.addEventListener(\"mouseup\",this._onUp),this._active=!1,this._inertia=[[Date.now(),this._map.getBearing()]],this._startPos=this._pos=i.mousePos(this._el,t),this._center=this._map.transform.centerPoint;var e=this._startPos.sub(this._center);e.mag()<200&&(this._center=this._startPos.add(new a(-200,0)._rotate(e.angle()))),t.preventDefault()}},_onMove:function(t){if(!this._ignoreEvent(t)){this.isActive()||(this._active=!0,this._fireEvent(\"rotatestart\",t),this._fireEvent(\"movestart\",t));var e=this._map;e.stop();var r=this._pos,n=i.mousePos(this._el,t),a=this._center,o=r.sub(a).angleWith(n.sub(a))/Math.PI*180,s=e.getBearing()-o,l=this._inertia,u=l[l.length-1];this._drainInertiaBuffer(),l.push([Date.now(),e._normalizeBearing(s,u[1])]),e.transform.bearing=s,this._fireEvent(\"rotate\",t),this._fireEvent(\"move\",t),this._pos=n}},_onUp:function(t){if(!this._ignoreEvent(t)&&(document.removeEventListener(\"mousemove\",this._onMove),document.removeEventListener(\"mouseup\",this._onUp),this.isActive())){this._active=!1,this._fireEvent(\"rotateend\",t),this._drainInertiaBuffer();var e=this._map,r=e.getBearing(),n=this._inertia,i=function(){Math.abs(r)<this._bearingSnap?e.resetNorth({noMoveStart:!0},{originalEvent:t}):this._fireEvent(\"moveend\",t)}.bind(this);if(n.length<2)i();else{var a=n[0],o=n[n.length-1],l=n[n.length-2],u=e._normalizeBearing(r,l[1]),c=o[1]-a[1],h=c<0?-1:1,f=(o[0]-a[0])/1e3;if(0!==c&&0!==f){var d=Math.abs(c*(.25/f));d>180&&(d=180);var p=d/180;u+=h*d*(p/2),Math.abs(e._normalizeBearing(u,0))<this._bearingSnap&&(u=e._normalizeBearing(0,u)),e.rotateTo(u,{duration:1e3*p,easing:s,noMoveStart:!0},{originalEvent:t})}else i()}}},_fireEvent:function(t,e){return this._map.fire(t,{originalEvent:e})},_ignoreEvent:function(t){var e=this._map;if(e.boxZoom&&e.boxZoom.isActive())return!0;if(e.dragPan&&e.dragPan.isActive())return!0;if(t.touches)return t.touches.length>1;var r=t.ctrlKey?1:2,n=t.ctrlKey?0:2;return\"mousemove\"===t.type?t.buttons&0===r:t.button!==n},_drainInertiaBuffer:function(){for(var t=this._inertia,e=Date.now();t.length>0&&e-t[0][0]>160;)t.shift()}}},{\"../../util/dom\":410,\"../../util/util\":424,\"point-geometry\":465}],399:[function(t,e,r){\"use strict\";function n(t){this._map=t,this._el=t.getCanvasContainer(),this._onKeyDown=this._onKeyDown.bind(this)}e.exports=n;n.prototype={_enabled:!1,isEnabled:function(){return this._enabled},enable:function(){this.isEnabled()||(this._el.addEventListener(\"keydown\",this._onKeyDown,!1),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._el.removeEventListener(\"keydown\",this._onKeyDown),this._enabled=!1)},_onKeyDown:function(t){if(!(t.altKey||t.ctrlKey||t.metaKey)){var e=this._map,r={originalEvent:t};if(!e.isEasing())switch(t.keyCode){case 61:case 107:case 171:case 187:e.zoomTo(Math.round(e.getZoom())+(t.shiftKey?2:1),r);break;case 189:case 109:case 173:e.zoomTo(Math.round(e.getZoom())-(t.shiftKey?2:1),r);break;case 37:t.shiftKey?e.easeTo({bearing:e.getBearing()-2},r):(t.preventDefault(),e.panBy([-80,0],r));break;case 39:t.shiftKey?e.easeTo({bearing:e.getBearing()+2},r):(t.preventDefault(),e.panBy([80,0],r));break;case 38:t.shiftKey?e.easeTo({pitch:e.getPitch()+5},r):(t.preventDefault(),e.panBy([0,-80],r));break;case 40:t.shiftKey?e.easeTo({pitch:Math.max(e.getPitch()-5,0)},r):(t.preventDefault(),e.panBy([0,80],r))}}}}},{}],400:[function(t,e,r){\"use strict\";function n(t){this._map=t,this._el=t.getCanvasContainer(),o.bindHandlers(this)}var i=t(\"../../util/dom\"),a=t(\"../../util/browser\"),o=t(\"../../util/util\");e.exports=n;var s=\"undefined\"!=typeof navigator?navigator.userAgent.toLowerCase():\"\",l=-1!==s.indexOf(\"firefox\"),u=-1!==s.indexOf(\"safari\")&&-1===s.indexOf(\"chrom\");n.prototype={_enabled:!1,isEnabled:function(){return this._enabled},enable:function(){this.isEnabled()||(this._el.addEventListener(\"wheel\",this._onWheel,!1),this._el.addEventListener(\"mousewheel\",this._onWheel,!1),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._el.removeEventListener(\"wheel\",this._onWheel),this._el.removeEventListener(\"mousewheel\",this._onWheel),this._enabled=!1)},_onWheel:function(t){var e;\"wheel\"===t.type?(e=t.deltaY,l&&t.deltaMode===window.WheelEvent.DOM_DELTA_PIXEL&&(e/=a.devicePixelRatio),t.deltaMode===window.WheelEvent.DOM_DELTA_LINE&&(e*=40)):\"mousewheel\"===t.type&&(e=-t.wheelDeltaY,u&&(e/=3));var r=a.now(),n=r-(this._time||0);this._pos=i.mousePos(this._el,t),this._time=r,0!==e&&e%4.000244140625==0?(this._type=\"wheel\",e=Math.floor(e/4)):0!==e&&Math.abs(e)<4?this._type=\"trackpad\":n>400?(this._type=null,this._lastValue=e,this._timeout=setTimeout(this._onTimeout,40)):this._type||(this._type=Math.abs(n*e)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,e+=this._lastValue)),t.shiftKey&&e&&(e/=4),this._type&&this._zoom(-e,t),t.preventDefault()},_onTimeout:function(){this._type=\"wheel\",this._zoom(-this._lastValue)},_zoom:function(t,e){if(0!==t){var r=this._map,n=2/(1+Math.exp(-Math.abs(t/100)));t<0&&0!==n&&(n=1/n);var i=r.ease?r.ease.to:r.transform.scale,a=r.transform.scaleZoom(i*n);r.zoomTo(a,{duration:0,around:r.unproject(this._pos),delayEndEvents:200},{originalEvent:e})}}}},{\"../../util/browser\":408,\"../../util/dom\":410,\"../../util/util\":424}],401:[function(t,e,r){\"use strict\";function n(t){this._map=t,this._el=t.getCanvasContainer(),a.bindHandlers(this)}var i=t(\"../../util/dom\"),a=t(\"../../util/util\");e.exports=n;var o=a.bezier(0,0,.15,1);n.prototype={_enabled:!1,isEnabled:function(){return this._enabled},enable:function(){this.isEnabled()||(this._el.addEventListener(\"touchstart\",this._onStart,!1),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._el.removeEventListener(\"touchstart\",this._onStart),this._enabled=!1)},disableRotation:function(){this._rotationDisabled=!0},enableRotation:function(){this._rotationDisabled=!1},_onStart:function(t){if(2===t.touches.length){var e=i.mousePos(this._el,t.touches[0]),r=i.mousePos(this._el,t.touches[1]);this._startVec=e.sub(r),this._startScale=this._map.transform.scale,this._startBearing=this._map.transform.bearing,this._gestureIntent=void 0,this._inertia=[],document.addEventListener(\"touchmove\",this._onMove,!1),document.addEventListener(\"touchend\",this._onEnd,!1)}},_onMove:function(t){if(2===t.touches.length){var e=i.mousePos(this._el,t.touches[0]),r=i.mousePos(this._el,t.touches[1]),n=e.add(r).div(2),a=e.sub(r),o=a.mag()/this._startVec.mag(),s=this._rotationDisabled?0:180*a.angleWith(this._startVec)/Math.PI,l=this._map;if(this._gestureIntent){var u={duration:0,around:l.unproject(n)};\"rotate\"===this._gestureIntent&&(u.bearing=this._startBearing+s),\"zoom\"!==this._gestureIntent&&\"rotate\"!==this._gestureIntent||(u.zoom=l.transform.scaleZoom(this._startScale*o)),l.stop(),this._drainInertiaBuffer(),this._inertia.push([Date.now(),o,n]),l.easeTo(u,{originalEvent:t})}else{var c=Math.abs(1-o)>.15;Math.abs(s)>4?this._gestureIntent=\"rotate\":c&&(this._gestureIntent=\"zoom\"),this._gestureIntent&&(this._startVec=a,this._startScale=l.transform.scale,this._startBearing=l.transform.bearing)}t.preventDefault()}},_onEnd:function(t){document.removeEventListener(\"touchmove\",this._onMove),document.removeEventListener(\"touchend\",this._onEnd),this._drainInertiaBuffer();var e=this._inertia,r=this._map;if(e.length<2)r.snapToNorth({},{originalEvent:t});else{var n=e[e.length-1],i=e[0],a=r.transform.scaleZoom(this._startScale*n[1]),s=r.transform.scaleZoom(this._startScale*i[1]),l=a-s,u=(n[0]-i[0])/1e3,c=n[2];if(0!==u&&a!==s){var h=.15*l/u;Math.abs(h)>2.5&&(h=h>0?2.5:-2.5);var f=1e3*Math.abs(h/(12*.15)),d=a+h*f/2e3;d<0&&(d=0),r.easeTo({zoom:d,duration:f,easing:o,around:r.unproject(c)},{originalEvent:t})}else r.snapToNorth({},{originalEvent:t})}},_drainInertiaBuffer:function(){for(var t=this._inertia,e=Date.now();t.length>2&&e-t[0][0]>160;)t.shift()}}},{\"../../util/dom\":410,\"../../util/util\":424}],402:[function(t,e,r){\"use strict\";function n(){i.bindAll([\"_onHashChange\",\"_updateHash\"],this)}e.exports=n;var i=t(\"../util/util\");n.prototype={addTo:function(t){return this._map=t,window.addEventListener(\"hashchange\",this._onHashChange,!1),this._map.on(\"moveend\",this._updateHash),this},remove:function(){return window.removeEventListener(\"hashchange\",this._onHashChange,!1),this._map.off(\"moveend\",this._updateHash),delete this._map,this},_onHashChange:function(){var t=location.hash.replace(\"#\",\"\").split(\"/\");return t.length>=3&&(this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:+(t[3]||0)}),!0)},_updateHash:function(){var t=this._map.getCenter(),e=this._map.getZoom(),r=this._map.getBearing(),n=Math.max(0,Math.ceil(Math.log(e)/Math.LN2)),i=\"#\"+Math.round(100*e)/100+\"/\"+t.lat.toFixed(n)+\"/\"+t.lng.toFixed(n)+(r?\"/\"+Math.round(10*r)/10:\"\");window.history.replaceState(\"\",\"\",i)}}},{\"../util/util\":424}],403:[function(t,e,r){\"use strict\";function n(t){t.parentNode&&t.parentNode.removeChild(t)}var i=t(\"../util/canvas\"),a=t(\"../util/util\"),o=t(\"../util/browser\"),s=t(\"../util/browser\").window,l=t(\"../util/evented\"),u=t(\"../util/dom\"),c=t(\"../style/style\"),h=t(\"../style/animation_loop\"),f=t(\"../render/painter\"),d=t(\"../geo/transform\"),p=t(\"./hash\"),m=t(\"./bind_handlers\"),g=t(\"./camera\"),v=t(\"../geo/lng_lat\"),y=t(\"../geo/lng_lat_bounds\"),b=t(\"point-geometry\"),x=t(\"./control/attribution\"),_={center:[0,0],zoom:0,bearing:0,pitch:0,minZoom:0,maxZoom:20,interactive:!0,scrollZoom:!0,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,bearingSnap:7,hash:!1,attributionControl:!0,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,trackResize:!0,workerCount:Math.max(o.hardwareConcurrency-1,1)},w=e.exports=function(t){if((t=a.extend({},_,t)).workerCount<1)throw new Error(\"workerCount must an integer greater than or equal to 1.\");this._interactive=t.interactive,this._failIfMajorPerformanceCaveat=t.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=t.preserveDrawingBuffer,this._trackResize=t.trackResize,this._workerCount=t.workerCount,this._bearingSnap=t.bearingSnap,\"string\"==typeof t.container?this._container=document.getElementById(t.container):this._container=t.container,this.animationLoop=new h,this.transform=new d(t.minZoom,t.maxZoom),t.maxBounds&&this.setMaxBounds(t.maxBounds),a.bindAll([\"_forwardStyleEvent\",\"_forwardSourceEvent\",\"_forwardLayerEvent\",\"_forwardTileEvent\",\"_onStyleLoad\",\"_onStyleChange\",\"_onSourceAdd\",\"_onSourceRemove\",\"_onSourceUpdate\",\"_onWindowOnline\",\"_onWindowResize\",\"_update\",\"_render\"],this),this._setupContainer(),this._setupPainter(),this.on(\"move\",this._update.bind(this,!1)),this.on(\"zoom\",this._update.bind(this,!0)),this.on(\"moveend\",function(){this.animationLoop.set(300),this._rerender()}.bind(this)),void 0!==s&&(s.addEventListener(\"online\",this._onWindowOnline,!1),s.addEventListener(\"resize\",this._onWindowResize,!1)),m(this,t),this._hash=t.hash&&(new p).addTo(this),this._hash&&this._hash._onHashChange()||this.jumpTo({center:t.center,zoom:t.zoom,bearing:t.bearing,pitch:t.pitch}),this.stacks={},this._classes=[],this.resize(),t.classes&&this.setClasses(t.classes),t.style&&this.setStyle(t.style),t.attributionControl&&this.addControl(new x(t.attributionControl));var e=this.fire.bind(this,\"error\");this.on(\"style.error\",e),this.on(\"source.error\",e),this.on(\"tile.error\",e),this.on(\"layer.error\",e)};a.extend(w.prototype,l),a.extend(w.prototype,g.prototype),a.extend(w.prototype,{addControl:function(t){return t.addTo(this),this},addClass:function(t,e){return this._classes.indexOf(t)>=0||\"\"===t?this:(this._classes.push(t),this._classOptions=e,this.style&&this.style.updateClasses(),this._update(!0))},removeClass:function(t,e){var r=this._classes.indexOf(t);return r<0||\"\"===t?this:(this._classes.splice(r,1),this._classOptions=e,this.style&&this.style.updateClasses(),this._update(!0))},setClasses:function(t,e){for(var r={},n=0;n<t.length;n++)\"\"!==t[n]&&(r[t[n]]=!0);return this._classes=Object.keys(r),this._classOptions=e,this.style&&this.style.updateClasses(),this._update(!0)},hasClass:function(t){return this._classes.indexOf(t)>=0},getClasses:function(){return this._classes},resize:function(){var t=0,e=0;return this._container&&(t=this._container.offsetWidth||400,e=this._container.offsetHeight||300),this._canvas.resize(t,e),this.transform.resize(t,e),this.painter.resize(t,e),this.fire(\"movestart\").fire(\"move\").fire(\"resize\").fire(\"moveend\")},getBounds:function(){var t=new y(this.transform.pointLocation(new b(0,0)),this.transform.pointLocation(this.transform.size));return(this.transform.angle||this.transform.pitch)&&(t.extend(this.transform.pointLocation(new b(this.transform.size.x,0))),t.extend(this.transform.pointLocation(new b(0,this.transform.size.y)))),t},setMaxBounds:function(t){if(t){var e=y.convert(t);this.transform.lngRange=[e.getWest(),e.getEast()],this.transform.latRange=[e.getSouth(),e.getNorth()],this.transform._constrain(),this._update()}else null!==t&&void 0!==t||(this.transform.lngRange=[],this.transform.latRange=[],this._update());return this},setMinZoom:function(t){if((t=null===t||void 0===t?0:t)>=0&&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 0 and the current maxZoom, inclusive\")},setMaxZoom:function(t){if((t=null===t||void 0===t?20:t)>=this.transform.minZoom&&t<=20)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error(\"maxZoom must be between the current minZoom and 20, inclusive\")},project:function(t){return this.transform.locationPoint(v.convert(t))},unproject:function(t){return this.transform.pointLocation(b.convert(t))},queryRenderedFeatures:function(){var t,e={};return 2===arguments.length?(t=arguments[0],e=arguments[1]):1===arguments.length&&function(t){return t instanceof b||Array.isArray(t)}(arguments[0])?t=arguments[0]:1===arguments.length&&(e=arguments[0]),this.style.queryRenderedFeatures(this._makeQueryGeometry(t),e,this.transform.zoom,this.transform.angle)},_makeQueryGeometry:function(t){void 0===t&&(t=[b.convert([0,0]),b.convert([this.transform.width,this.transform.height])]);var e;if(t instanceof b||\"number\"==typeof t[0])e=[b.convert(t)];else{var r=[b.convert(t[0]),b.convert(t[1])];e=[r[0],new b(r[1].x,r[0].y),r[1],new b(r[0].x,r[1].y),r[0]]}return e=e.map(function(t){return this.transform.pointCoordinate(t)}.bind(this))},querySourceFeatures:function(t,e){return this.style.querySourceFeatures(t,e)},setStyle:function(t){return this.style&&(this.style.off(\"load\",this._onStyleLoad).off(\"error\",this._forwardStyleEvent).off(\"change\",this._onStyleChange).off(\"source.add\",this._onSourceAdd).off(\"source.remove\",this._onSourceRemove).off(\"source.load\",this._onSourceUpdate).off(\"source.error\",this._forwardSourceEvent).off(\"source.change\",this._onSourceUpdate).off(\"layer.add\",this._forwardLayerEvent).off(\"layer.remove\",this._forwardLayerEvent).off(\"layer.error\",this._forwardLayerEvent).off(\"tile.add\",this._forwardTileEvent).off(\"tile.remove\",this._forwardTileEvent).off(\"tile.load\",this._update).off(\"tile.error\",this._forwardTileEvent).off(\"tile.stats\",this._forwardTileEvent)._remove(),this.off(\"rotate\",this.style._redoPlacement),this.off(\"pitch\",this.style._redoPlacement)),t?(this.style=t instanceof c?t:new c(t,this.animationLoop,this._workerCount),this.style.on(\"load\",this._onStyleLoad).on(\"error\",this._forwardStyleEvent).on(\"change\",this._onStyleChange).on(\"source.add\",this._onSourceAdd).on(\"source.remove\",this._onSourceRemove).on(\"source.load\",this._onSourceUpdate).on(\"source.error\",this._forwardSourceEvent).on(\"source.change\",this._onSourceUpdate).on(\"layer.add\",this._forwardLayerEvent).on(\"layer.remove\",this._forwardLayerEvent).on(\"layer.error\",this._forwardLayerEvent).on(\"tile.add\",this._forwardTileEvent).on(\"tile.remove\",this._forwardTileEvent).on(\"tile.load\",this._update).on(\"tile.error\",this._forwardTileEvent).on(\"tile.stats\",this._forwardTileEvent),this.on(\"rotate\",this.style._redoPlacement),this.on(\"pitch\",this.style._redoPlacement),this):(this.style=null,this)},getStyle:function(){if(this.style)return this.style.serialize()},addSource:function(t,e){return this.style.addSource(t,e),this._update(!0),this},addSourceType:function(t,e,r){return this.style.addSourceType(t,e,r)},removeSource:function(t){return this.style.removeSource(t),this._update(!0),this},getSource:function(t){return this.style.getSource(t)},addLayer:function(t,e){return this.style.addLayer(t,e),this._update(!0),this},removeLayer:function(t){return this.style.removeLayer(t),this._update(!0),this},getLayer:function(t){return this.style.getLayer(t)},setFilter:function(t,e){return this.style.setFilter(t,e),this._update(!0),this},setLayerZoomRange:function(t,e,r){return this.style.setLayerZoomRange(t,e,r),this._update(!0),this},getFilter:function(t){return this.style.getFilter(t)},setPaintProperty:function(t,e,r,n){return this.style.setPaintProperty(t,e,r,n),this._update(!0),this},getPaintProperty:function(t,e,r){return this.style.getPaintProperty(t,e,r)},setLayoutProperty:function(t,e,r){return this.style.setLayoutProperty(t,e,r),this._update(!0),this},getLayoutProperty:function(t,e){return this.style.getLayoutProperty(t,e)},getContainer:function(){return 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this._repaint},set repaint(t){this._repaint=t,this._update()},_vertices:!1,get vertices(){return this._vertices},set vertices(t){this._vertices=t,this._update()}})},{\"../geo/lng_lat\":321,\"../geo/lng_lat_bounds\":322,\"../geo/transform\":323,\"../render/painter\":337,\"../style/animation_loop\":357,\"../style/style\":360,\"../util/browser\":408,\"../util/canvas\":409,\"../util/dom\":410,\"../util/evented\":416,\"../util/util\":424,\"./bind_handlers\":389,\"./camera\":390,\"./control/attribution\":391,\"./hash\":402,\"point-geometry\":465}],404:[function(t,e,r){\"use strict\";function n(t,e){t||(t=i.create(\"div\")),t.classList.add(\"mapboxgl-marker\"),this._el=t,this._offset=o.convert(e&&e.offset||[0,0]),this._update=this._update.bind(this)}e.exports=n;var i=t(\"../util/dom\"),a=t(\"../geo/lng_lat\"),o=t(\"point-geometry\");n.prototype={addTo:function(t){return this.remove(),this._map=t,t.getCanvasContainer().appendChild(this._el),t.on(\"move\",this._update),this._update(),this},remove:function(){this._map&&(this._map.off(\"move\",this._update),this._map=null);var t=this._el.parentNode;return t&&t.removeChild(this._el),this},getLngLat:function(){return this._lngLat},setLngLat:function(t){return this._lngLat=a.convert(t),this._update(),this},getElement:function(){return this._el},_update:function(){if(this._map){var t=this._map.project(this._lngLat)._add(this._offset);i.setTransform(this._el,\"translate(\"+t.x+\"px,\"+t.y+\"px)\")}}}},{\"../geo/lng_lat\":321,\"../util/dom\":410,\"point-geometry\":465}],405:[function(t,e,r){\"use strict\";function n(t){i.setOptions(this,t),i.bindAll([\"_update\",\"_onClickClose\"],this)}e.exports=n;var i=t(\"../util/util\"),a=t(\"../util/evented\"),o=t(\"../util/dom\"),s=t(\"../geo/lng_lat\");n.prototype=i.inherit(a,{options:{closeButton:!0,closeOnClick:!0},addTo:function(t){return 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this._createContent(),this._content.appendChild(t),this._update(),this},_createContent:function(){this._content&&this._content.parentNode&&this._content.parentNode.removeChild(this._content),this._content=o.create(\"div\",\"mapboxgl-popup-content\",this._container),this.options.closeButton&&(this._closeButton=o.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.innerHTML=\"&#215;\",this._closeButton.addEventListener(\"click\",this._onClickClose))},_update:function(){if(this._map&&this._lngLat&&this._content){this._container||(this._container=o.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=o.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content));var t=this._map.project(this._lngLat).round(),e=this.options.anchor;if(!e){var r=this._container.offsetWidth,n=this._container.offsetHeight;e=t.y<n?[\"top\"]:t.y>this._map.transform.height-n?[\"bottom\"]:[],t.x<r/2?e.push(\"left\"):t.x>this._map.transform.width-r/2&&e.push(\"right\"),e=0===e.length?\"bottom\":e.join(\"-\")}var i={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%)\"},a=this._container.classList;for(var s in i)a.remove(\"mapboxgl-popup-anchor-\"+s);a.add(\"mapboxgl-popup-anchor-\"+e),o.setTransform(this._container,i[e]+\" translate(\"+t.x+\"px,\"+t.y+\"px)\")}},_onClickClose:function(){this.remove()}})},{\"../geo/lng_lat\":321,\"../util/dom\":410,\"../util/evented\":416,\"../util/util\":424}],406:[function(t,e,r){\"use strict\";function n(t,e){this.target=t,this.parent=e,this.callbacks={},this.callbackID=0,this.receive=this.receive.bind(this),this.target.addEventListener(\"message\",this.receive,!1)}e.exports=n,n.prototype.receive=function(t){function e(t,e,r){this.postMessage({type:\"<response>\",id:String(i),error:t?String(t):null,data:e},r)}var r,n=t.data,i=n.id;if(\"<response>\"===n.type)r=this.callbacks[n.id],delete this.callbacks[n.id],r&&r(n.error||null,n.data);else if(void 0!==n.id&&this.parent[n.type])this.parent[n.type](n.data,e.bind(this));else if(void 0!==n.id&&this.parent.workerSources){var a=n.type.split(\".\");this.parent.workerSources[a[0]][a[1]](n.data,e.bind(this))}else this.parent[n.type](n.data)},n.prototype.send=function(t,e,r,n){var i=null;r&&(this.callbacks[i=this.callbackID++]=r),this.postMessage({type:t,id:String(i),data:e},n)},n.prototype.postMessage=function(t,e){this.target.postMessage(t,e)}},{}],407:[function(t,e,r){\"use strict\";function n(t){var e=document.createElement(\"a\");return 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n.src=(window.URL||window.webkitURL).createObjectURL(i),n.getData=function(){var t=document.createElement(\"canvas\"),e=t.getContext(\"2d\");return t.width=n.width,t.height=n.height,e.drawImage(n,0,0),e.getImageData(0,0,n.width,n.height).data},n})},r.getVideo=function(t,e){var r=document.createElement(\"video\");r.onloadstart=function(){e(null,r)};for(var i=0;i<t.length;i++){var a=document.createElement(\"source\");n(t[i])||(r.crossOrigin=\"Anonymous\"),a.src=t[i],r.appendChild(a)}return r.getData=function(){return r},r}},{}],408:[function(t,e,r){\"use strict\";r.window=window,e.exports.now=function(){return window.performance&&window.performance.now?window.performance.now.bind(window.performance):Date.now.bind(Date)}();var n=window.requestAnimationFrame||window.mozRequestAnimationFrame||window.webkitRequestAnimationFrame||window.msRequestAnimationFrame;r.frame=function(t){return n(t)};var i=window.cancelAnimationFrame||window.mozCancelAnimationFrame||window.webkitCancelAnimationFrame||window.msCancelAnimationFrame;r.cancelFrame=function(t){i(t)},r.timed=function(t,n,i){function a(l){o||((l=e.exports.now())>=s+n?t.call(i,1):(t.call(i,(l-s)/n),r.frame(a)))}if(!n)return t.call(i,1),null;var o=!1,s=e.exports.now();return r.frame(a),function(){o=!0}},r.supported=t(\"mapbox-gl-supported\"),r.hardwareConcurrency=navigator.hardwareConcurrency||4,Object.defineProperty(r,\"devicePixelRatio\",{get:function(){return window.devicePixelRatio}}),r.supportsWebp=!1;var a=document.createElement(\"img\");a.onload=function(){r.supportsWebp=!0},a.src=\"data:image/webp;base64,UklGRh4AAABXRUJQVlA4TBEAAAAvAQAAAAfQ//73v/+BiOh/AAA=\",r.supportsGeolocation=!!navigator.geolocation},{\"mapbox-gl-supported\":309}],409:[function(t,e,r){\"use strict\";function 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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\"};i.calendars.discworld=n},{\"../main\":561,\"object-assign\":452}],550:[function(t,e,r){function n(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}var i=t(\"../main\"),a=t(\"object-assign\");n.prototype=new i.baseCalendar,a(n.prototype,{name:\"Ethiopian\",jdEpoch:1724220.5,daysPerMonth:[30,30,30,30,30,30,30,30,30,30,30,30,5],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Ethiopian\",epochs:[\"BEE\",\"EE\"],monthNames:[\"Meskerem\",\"Tikemet\",\"Hidar\",\"Tahesas\",\"Tir\",\"Yekatit\",\"Megabit\",\"Miazia\",\"Genbot\",\"Sene\",\"Hamle\",\"Nehase\",\"Pagume\"],monthNamesShort:[\"Mes\",\"Tik\",\"Hid\",\"Tah\",\"Tir\",\"Yek\",\"Meg\",\"Mia\",\"Gen\",\"Sen\",\"Ham\",\"Neh\",\"Pag\"],dayNames:[\"Ehud\",\"Segno\",\"Maksegno\",\"Irob\",\"Hamus\",\"Arb\",\"Kidame\"],dayNamesShort:[\"Ehu\",\"Seg\",\"Mak\",\"Iro\",\"Ham\",\"Arb\",\"Kid\"],dayNamesMin:[\"Eh\",\"Se\",\"Ma\",\"Ir\",\"Ha\",\"Ar\",\"Ki\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,i.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,i.local.invalidYear||i.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,i.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 n=this._validate(t,e,r,i.local.invalidDate);return(t=n.year())<0&&t++,n.day()+30*(n.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)}}),i.calendars.ethiopian=n},{\"../main\":561,\"object-assign\":452}],551:[function(t,e,r){function n(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}function i(t,e){return t-e*Math.floor(t/e)}var a=t(\"../main\"),o=t(\"object-assign\");n.prototype=new a.baseCalendar,o(n.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 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t.year&&(e=t.month(),t=t.year()),this._validate(t,e,this.minDay,a.local.invalidMonth),12===e&&this.leapYear(t)?30:8===e&&5===i(this.daysInYear(t),10)?30:9===e&&3===i(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 n=this._validate(t,e,r,a.local.invalidDate);return{yearType:(this.leapYear(n)?\"embolismic\":\"common\")+\" \"+[\"deficient\",\"regular\",\"complete\"][this.daysInYear(n)%10-3]}},toJD:function(t,e,r){var n=this._validate(t,e,r,a.local.invalidDate);t=n.year(),e=n.month(),r=n.day();var i=t<=0?t+1:t,o=this.jdEpoch+this._delay1(i)+this._delay2(i)+r+1;if(e<7){for(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(var 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 i(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)}}),a.calendars.hebrew=n},{\"../main\":561,\"object-assign\":452}],552:[function(t,e,r){function n(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}var i=t(\"../main\"),a=t(\"object-assign\");n.prototype=new i.baseCalendar,a(n.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 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5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var n=this._validate(t,e,r,i.local.invalidDate);return t=n.year(),e=n.month(),r=n.day(),t=t<=0?t+1:t,r+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)}}),i.calendars.islamic=n},{\"../main\":561,\"object-assign\":452}],553:[function(t,e,r){function n(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}var i=t(\"../main\"),a=t(\"object-assign\");n.prototype=new i.baseCalendar,a(n.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,i.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,i.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 n=this._validate(t,e,r,i.local.invalidDate);return t=n.year(),e=n.month(),r=n.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)}}),i.calendars.julian=n},{\"../main\":561,\"object-assign\":452}],554:[function(t,e,r){function n(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}function i(t,e){return t-e*Math.floor(t/e)}function a(t,e){return i(t-1,e)+1}var o=t(\"../main\"),s=t(\"object-assign\");n.prototype=new o.baseCalendar,s(n.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,o.local.invalidYear),!1},formatYear:function(t){t=this._validate(t,this.minMonth,this.minDay,o.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,o.local.invalidYear),18},weekOfYear:function(t,e,r){return this._validate(t,e,r,o.local.invalidDate),0},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,o.local.invalidYear),360},daysInMonth:function(t,e){return this._validate(t,e,this.minDay,o.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(t,e,r){return this._validate(t,e,r,o.local.invalidDate).day()},weekDay:function(t,e,r){return this._validate(t,e,r,o.local.invalidDate),!0},extraInfo:function(t,e,r){var n=this._validate(t,e,r,o.local.invalidDate).toJD(),i=this._toHaab(n),a=this._toTzolkin(n);return{haabMonthName:this.local.haabMonths[i[0]-1],haabMonth:i[0],haabDay:i[1],tzolkinDayName:this.local.tzolkinMonths[a[0]-1],tzolkinDay:a[0],tzolkinTrecena:a[1]}},_toHaab:function(t){var e=i((t-=this.jdEpoch)+8+340,365);return[Math.floor(e/20)+1,i(e,20)]},_toTzolkin:function(t){return t-=this.jdEpoch,[a(t+20,20),a(t+4,13)]},toJD:function(t,e,r){var n=this._validate(t,e,r,o.local.invalidDate);return n.day()+20*n.month()+360*n.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)}}),o.calendars.mayan=n},{\"../main\":561,\"object-assign\":452}],555:[function(t,e,r){function n(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}var i=t(\"../main\"),a=t(\"object-assign\");n.prototype=new i.baseCalendar;var o=i.instance(\"gregorian\");a(n.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,i.local.invalidYear||i.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,i.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 n=this._validate(t,e,r,i.local.invalidMonth);(t=n.year())<0&&t++;for(var a=n.day(),s=1;s<n.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)}}),i.calendars.nanakshahi=n},{\"../main\":561,\"object-assign\":452}],556:[function(t,e,r){function n(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}var i=t(\"../main\"),a=t(\"object-assign\");n.prototype=new i.baseCalendar,a(n.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 this.daysInYear(t)!==this.daysPerYear},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){if(t=this._validate(t,this.minMonth,this.minDay,i.local.invalidYear).year(),void 0===this.NEPALI_CALENDAR_DATA[t])return this.daysPerYear;for(var e=0,r=this.minMonth;r<=12;r++)e+=this.NEPALI_CALENDAR_DATA[t][r];return e},daysInMonth:function(t,e){return t.year&&(e=t.month(),t=t.year()),this._validate(t,e,this.minDay,i.local.invalidMonth),void 0===this.NEPALI_CALENDAR_DATA[t]?this.daysPerMonth[e-1]:this.NEPALI_CALENDAR_DATA[t][e]},weekDay:function(t,e,r){return 6!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var n=this._validate(t,e,r,i.local.invalidDate);t=n.year(),e=n.month(),r=n.day();var a=i.instance(),o=0,s=e,l=t;this._createMissingCalendarData(t);var u=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(u)):o+=this.NEPALI_CALENDAR_DATA[l][9]-this.NEPALI_CALENDAR_DATA[l][0],a.newDate(u,1,1).add(o,\"d\").toJD()},fromJD:function(t){var e=i.instance().fromJD(t),r=e.year(),n=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;n>l;)++o>12&&(o=1,a++),l+=this.NEPALI_CALENDAR_DATA[a][o];var u=this.NEPALI_CALENDAR_DATA[a][o]-(l-n);return this.newDate(a,o,u)},_createMissingCalendarData:function(t){var e=this.daysPerMonth.slice(0);e.unshift(17);for(var r=t-1;r<t+2;r++)void 0===this.NEPALI_CALENDAR_DATA[r]&&(this.NEPALI_CALENDAR_DATA[r]=e)},NEPALI_CALENDAR_DATA:{1970:[18,31,31,32,31,31,31,30,29,30,29,30,30],1971:[18,31,31,32,31,32,30,30,29,30,29,30,30],1972:[17,31,32,31,32,31,30,30,30,29,29,30,30],1973:[19,30,32,31,32,31,30,30,30,29,30,29,31],1974:[19,31,31,32,30,31,31,30,29,30,29,30,30],1975:[18,31,31,32,32,30,31,30,29,30,29,30,30],1976:[17,31,32,31,32,31,30,30,30,29,29,30,31],1977:[18,31,32,31,32,31,31,29,30,29,30,29,31],1978:[18,31,31,32,31,31,31,30,29,30,29,30,30],1979:[18,31,31,32,32,31,30,30,29,30,29,30,30],1980:[17,31,32,31,32,31,30,30,30,29,29,30,31],1981:[18,31,31,31,32,31,31,29,30,30,29,30,30],1982:[18,31,31,32,31,31,31,30,29,30,29,30,30],1983:[18,31,31,32,32,31,30,30,29,30,29,30,30],1984:[17,31,32,31,32,31,30,30,30,29,29,30,31],1985:[18,31,31,31,32,31,31,29,30,30,29,30,30],1986:[18,31,31,32,31,31,31,30,29,30,29,30,30],1987:[18,31,32,31,32,31,30,30,29,30,29,30,30],1988:[17,31,32,31,32,31,30,30,30,29,29,30,31],1989:[18,31,31,31,32,31,31,30,29,30,29,30,30],1990:[18,31,31,32,31,31,31,30,29,30,29,30,30],1991:[18,31,32,31,32,31,30,30,29,30,29,30,30],1992:[17,31,32,31,32,31,30,30,30,29,30,29,31],1993:[18,31,31,31,32,31,31,30,29,30,29,30,30],1994:[18,31,31,32,31,31,31,30,29,30,29,30,30],1995:[17,31,32,31,32,31,30,30,30,29,29,30,30],1996:[17,31,32,31,32,31,30,30,30,29,30,29,31],1997:[18,31,31,32,31,31,31,30,29,30,29,30,30],1998:[18,31,31,32,31,31,31,30,29,30,29,30,30],1999:[17,31,32,31,32,31,30,30,30,29,29,30,31],2e3:[17,30,32,31,32,31,30,30,30,29,30,29,31],2001:[18,31,31,32,31,31,31,30,29,30,29,30,30],2002:[18,31,31,32,32,31,30,30,29,30,29,30,30],2003:[17,31,32,31,32,31,30,30,30,29,29,30,31],2004:[17,30,32,31,32,31,30,30,30,29,30,29,31],2005:[18,31,31,32,31,31,31,30,29,30,29,30,30],2006:[18,31,31,32,32,31,30,30,29,30,29,30,30],2007:[17,31,32,31,32,31,30,30,30,29,29,30,31],2008:[17,31,31,31,32,31,31,29,30,30,29,29,31],2009:[18,31,31,32,31,31,31,30,29,30,29,30,30],2010:[18,31,31,32,32,31,30,30,29,30,29,30,30],2011:[17,31,32,31,32,31,30,30,30,29,29,30,31],2012:[17,31,31,31,32,31,31,29,30,30,29,30,30],2013:[18,31,31,32,31,31,31,30,29,30,29,30,30],2014:[18,31,31,32,32,31,30,30,29,30,29,30,30],2015:[17,31,32,31,32,31,30,30,30,29,29,30,31],2016:[17,31,31,31,32,31,31,29,30,30,29,30,30],2017:[18,31,31,32,31,31,31,30,29,30,29,30,30],2018:[18,31,32,31,32,31,30,30,29,30,29,30,30],2019:[17,31,32,31,32,31,30,30,30,29,30,29,31],2020:[17,31,31,31,32,31,31,30,29,30,29,30,30],2021:[18,31,31,32,31,31,31,30,29,30,29,30,30],2022:[17,31,32,31,32,31,30,30,30,29,29,30,30],2023:[17,31,32,31,32,31,30,30,30,29,30,29,31],2024:[17,31,31,31,32,31,31,30,29,30,29,30,30],2025:[18,31,31,32,31,31,31,30,29,30,29,30,30],2026:[17,31,32,31,32,31,30,30,30,29,29,30,31],2027:[17,30,32,31,32,31,30,30,30,29,30,29,31],2028:[17,31,31,32,31,31,31,30,29,30,29,30,30],2029:[18,31,31,32,31,32,30,30,29,30,29,30,30],2030:[17,31,32,31,32,31,30,30,30,30,30,30,31],2031:[17,31,32,31,32,31,31,31,31,31,31,31,31],2032:[17,32,32,32,32,32,32,32,32,32,32,32,32],2033:[18,31,31,32,32,31,30,30,29,30,29,30,30],2034:[17,31,32,31,32,31,30,30,30,29,29,30,31],2035:[17,30,32,31,32,31,31,29,30,30,29,29,31],2036:[17,31,31,32,31,31,31,30,29,30,29,30,30],2037:[18,31,31,32,32,31,30,30,29,30,29,30,30],2038:[17,31,32,31,32,31,30,30,30,29,29,30,31],2039:[17,31,31,31,32,31,31,29,30,30,29,30,30],2040:[17,31,31,32,31,31,31,30,29,30,29,30,30],2041:[18,31,31,32,32,31,30,30,29,30,29,30,30],2042:[17,31,32,31,32,31,30,30,30,29,29,30,31],2043:[17,31,31,31,32,31,31,29,30,30,29,30,30],2044:[17,31,31,32,31,31,31,30,29,30,29,30,30],2045:[18,31,32,31,32,31,30,30,29,30,29,30,30],2046:[17,31,32,31,32,31,30,30,30,29,29,30,31],2047:[17,31,31,31,32,31,31,30,29,30,29,30,30],2048:[17,31,31,32,31,31,31,30,29,30,29,30,30],2049:[17,31,32,31,32,31,30,30,30,29,29,30,30],2050:[17,31,32,31,32,31,30,30,30,29,30,29,31],2051:[17,31,31,31,32,31,31,30,29,30,29,30,30],2052:[17,31,31,32,31,31,31,30,29,30,29,30,30],2053:[17,31,32,31,32,31,30,30,30,29,29,30,30],2054:[17,31,32,31,32,31,30,30,30,29,30,29,31],2055:[17,31,31,32,31,31,31,30,29,30,30,29,30],2056:[17,31,31,32,31,32,30,30,29,30,29,30,30],2057:[17,31,32,31,32,31,30,30,30,29,29,30,31],2058:[17,30,32,31,32,31,30,30,30,29,30,29,31],2059:[17,31,31,32,31,31,31,30,29,30,29,30,30],2060:[17,31,31,32,32,31,30,30,29,30,29,30,30],2061:[17,31,32,31,32,31,30,30,30,29,29,30,31],2062:[17,30,32,31,32,31,31,29,30,29,30,29,31],2063:[17,31,31,32,31,31,31,30,29,30,29,30,30],2064:[17,31,31,32,32,31,30,30,29,30,29,30,30],2065:[17,31,32,31,32,31,30,30,30,29,29,30,31],2066:[17,31,31,31,32,31,31,29,30,30,29,29,31],2067:[17,31,31,32,31,31,31,30,29,30,29,30,30],2068:[17,31,31,32,32,31,30,30,29,30,29,30,30],2069:[17,31,32,31,32,31,30,30,30,29,29,30,31],2070:[17,31,31,31,32,31,31,29,30,30,29,30,30],2071:[17,31,31,32,31,31,31,30,29,30,29,30,30],2072:[17,31,32,31,32,31,30,30,29,30,29,30,30],2073:[17,31,32,31,32,31,30,30,30,29,29,30,31],2074:[17,31,31,31,32,31,31,30,29,30,29,30,30],2075:[17,31,31,32,31,31,31,30,29,30,29,30,30],2076:[16,31,32,31,32,31,30,30,30,29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n(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}function i(t,e){return t-e*Math.floor(t/e)}var a=t(\"../main\"),o=t(\"object-assign\");n.prototype=new a.baseCalendar,o(n.prototype,{name:\"Persian\",jdEpoch:1948320.5,daysPerMonth:[31,31,31,31,31,31,30,30,30,30,30,29],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Persian\",epochs:[\"BP\",\"AP\"],monthNames:[\"Farvardin\",\"Ordibehesht\",\"Khordad\",\"Tir\",\"Mordad\",\"Shahrivar\",\"Mehr\",\"Aban\",\"Azar\",\"Day\",\"Bahman\",\"Esfand\"],monthNamesShort:[\"Far\",\"Ord\",\"Kho\",\"Tir\",\"Mor\",\"Sha\",\"Meh\",\"Aba\",\"Aza\",\"Day\",\"Bah\",\"Esf\"],dayNames:[\"Yekshambe\",\"Doshambe\",\"Seshambe\",\"Chæharshambe\",\"Panjshambe\",\"Jom'e\",\"Shambe\"],dayNamesShort:[\"Yek\",\"Do\",\"Se\",\"Chæ\",\"Panj\",\"Jom\",\"Sha\"],dayNamesMin:[\"Ye\",\"Do\",\"Se\",\"Ch\",\"Pa\",\"Jo\",\"Sh\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,a.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,a.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 n=this._validate(t,e,r,a.local.invalidDate);t=n.year(),e=n.month(),r=n.day();var o=t-(t>=0?474:473),s=474+i(o,2820);return r+(e<=7?31*(e-1):30*(e-1)+6)+Math.floor((682*s-110)/2816)+365*(s-1)+1029983*Math.floor(o/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=i(e,1029983),a=2820;if(1029982!==n){var o=Math.floor(n/366),s=i(n,366);a=Math.floor((2134*o+2816*s+2815)/1028522)+o+1}var l=a+2820*r+474;l=l<=0?l-1:l;var 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n=this._validate(t,this.minMonth,this.minDay,i.local.invalidYear),t=this._t2gYear(n.year());return o.weekOfYear(t,n.month(),n.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,i.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 n=this._validate(t,e,r,i.local.invalidDate),t=this._t2gYear(n.year());return o.toJD(t,n.month(),n.day())},fromJD:function(t){var e=o.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)}}),i.calendars.taiwan=n},{\"../main\":561,\"object-assign\":452}],559:[function(t,e,r){function n(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}var i=t(\"../main\"),a=t(\"object-assign\"),o=i.instance();n.prototype=new i.baseCalendar,a(n.prototype,{name:\"Thai\",jdEpoch:1523098.5,yearsOffset:543,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Thai\",epochs:[\"BBE\",\"BE\"],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:\"dd/mm/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,i.local.invalidYear),t=this._t2gYear(e.year());return o.leapYear(t)},weekOfYear:function(t,e,r){var n=this._validate(t,this.minMonth,this.minDay,i.local.invalidYear),t=this._t2gYear(n.year());return o.weekOfYear(t,n.month(),n.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,i.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 n=this._validate(t,e,r,i.local.invalidDate),t=this._t2gYear(n.year());return o.toJD(t,n.month(),n.day())},fromJD:function(t){var e=o.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)}}),i.calendars.thai=n},{\"../main\":561,\"object-assign\":452}],560:[function(t,e,r){function n(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}var i=t(\"../main\"),a=t(\"object-assign\");n.prototype=new i.baseCalendar,a(n.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-Thalāthā’\",\"Yawm al-Arba‘ā’\",\"Yawm al-Khamīs\",\"Yawm al-Jum‘a\",\"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,i.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,i.local.invalidMonth).toJD()-24e5+.5,n=0,a=0;a<o.length;a++){if(o[a]>r)return o[n]-o[n-1];n++}return 30},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var n=this._validate(t,e,r,i.local.invalidDate),a=12*(n.year()-1)+n.month()-15292;return n.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,u=e-o[r-1]+1;return this.newDate(s,l,u)},isValid:function(t,e,r){var n=i.baseCalendar.prototype.isValid.apply(this,arguments);return n&&(n=(t=null!=t.year?t.year:t)>=1276&&t<=1500),n},_validate:function(t,e,r,n){var a=i.baseCalendar.prototype._validate.apply(this,arguments);if(a.year<1276||a.year>1500)throw n.replace(/\\{0\\}/,this.local.name);return 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n(){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 i(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(u.local.invalidDate||u.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name)}function a(t,e){return t=\"\"+t,\"000000\".substring(0,e-t.length)+t}function o(){this.shortYearCutoff=\"+10\"}function s(t){this.local=this.regionalOptions[t]||this.regionalOptions[\"\"]}var l=t(\"object-assign\");l(n.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]}}}),l(i.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(u.local.invalidDate||u.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(u.local.differentCalendars||u.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?\"-\":\"\")+a(Math.abs(this.year()),4)+\"-\"+a(this.month(),2)+\"-\"+a(this.day(),2)}}),l(o.prototype,{_validateLevel:0,newDate:function(t,e,r){return null==t?this.today():(t.year&&(this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),r=t.day(),e=t.month(),t=t.year()),new i(this,t,e,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(t){return this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear).year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear);return(e.year()<0?\"-\":\"\")+a(Math.abs(e.year()),4)},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear),12},monthOfYear:function(t,e){var r=this._validate(t,e,this.minDay,u.local.invalidMonth||u.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,u.local.invalidMonth||u.regionalOptions[\"\"].invalidMonth),r},daysInYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear);return this.leapYear(e)?366:365},dayOfYear:function(t,e,r){var n=this._validate(t,e,r,u.local.invalidDate||u.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,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(t,e,r){return this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),{}},add:function(t,e,r){return this._validate(t,this.minMonth,this.minDay,u.local.invalidDate||u.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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a=r.dayNamesShort||this.local.dayNamesShort,o=r.dayNames||this.local.dayNames,s=r.parseMonth||this.local.parseMonth,l=r.monthNumbers||this.local.monthNumbers,u=r.monthNamesShort||this.local.monthNamesShort,c=r.monthNames||this.local.monthNames,h=-1,f=-1,d=-1,p=-1,m=-1,g=!1,v=!1,y=function(e,r){for(var n=1;k+n<t.length&&t.charAt(k+n)===e;)n++;return k+=n-1,Math.floor(n/(r||1))>1},b=function(t,r){var n=y(t,r),a=[2,3,n?4:2,n?4:2,10,11,20][\"oyYJ@!\".indexOf(t)+1],o=new RegExp(\"^-?\\\\d{1,\"+a+\"}\"),s=e.substring(M).match(o);if(!s)throw(i.local.missingNumberAt||i.regionalOptions[\"\"].missingNumberAt).replace(/\\{0\\}/,M);return M+=s[0].length,parseInt(s[0],10)},x=this,_=function(t,r,n,a){for(var o=y(t,a)?n:r,s=0;s<o.length;s++)if(e.substr(M,o[s].length).toLowerCase()===o[s].toLowerCase())return 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u.boxEnabled&&(c=u.boxStart[0]!==u.boxEnd[0],h=u.boxStart[1]!==u.boxEnd[1],c||h?(c&&(o(0,u.boxStart[0],u.boxEnd[0]),t.xaxis.autorange=!1),h&&(o(1,u.boxStart[1],u.boxEnd[1]),t.yaxis.autorange=!1),t.relayoutCallback()):t.glplot.setDirty(),u.boxEnabled=!1,u.boxInited=!1);break;case\"pan\":u.boxEnabled=!1,u.boxInited=!1,n?(u.panning||(u.dragStart[0]=i,u.dragStart[1]=a),Math.abs(u.dragStart[0]-i)<g&&(i=u.dragStart[0]),Math.abs(u.dragStart[1]-a)<g&&(a=u.dragStart[1]),c=(p-i)*(f[2]-f[0])/(l.viewBox[2]-l.viewBox[0]),h=(m-a)*(f[3]-f[1])/(l.viewBox[3]-l.viewBox[1]),f[0]+=c,f[2]+=c,f[1]+=h,f[3]+=h,t.setRanges(f),u.panning=!0,u.lastInputTime=Date.now(),e(),t.cameraChanged(),t.handleAnnotations()):u.panning&&(u.panning=!1,t.relayoutCallback())}u.lastPos[0]=i,u.lastPos[1]=a}),u.wheelListener=o(i,function(r,n){var i=t.calcDataBox(),a=l.viewBox,o=u.lastPos[0],s=u.lastPos[1];switch(t.fullLayout.dragmode){case\"zoom\":break;case\"pan\":var c=Math.exp(.1*n/(a[3]-a[1])),h=o/(a[2]-a[0])*(i[2]-i[0])+i[0],f=s/(a[3]-a[1])*(i[3]-i[1])+i[1];i[0]=(i[0]-h)*c+h,i[2]=(i[2]-h)*c+h,i[1]=(i[1]-f)*c+f,i[3]=(i[3]-f)*c+f,t.setRanges(i),u.lastInputTime=Date.now(),e(),t.cameraChanged(),t.handleAnnotations(),t.relayoutCallback()}return!0}),u}var a=t(\"mouse-change\"),o=t(\"mouse-wheel\"),s=t(\"../cartesian/constants\");e.exports=i},{\"../cartesian/constants\":729,\"mouse-change\":434,\"mouse-wheel\":437}],763:[function(t,e,r){\"use strict\";function n(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}function i(t){return new n(t)}var a=t(\"../plots\"),o=t(\"../cartesian/axes\"),s=t(\"../../lib/html2unicode\"),l=t(\"../../lib/str2rgbarray\"),u=n.prototype,c=[\"xaxis\",\"yaxis\"];u.merge=function(t){this.titleEnable=!1,this.backgroundColor=l(t.plot_bgcolor);var e,r,n,i,a,o,u,h,f,d,p;for(d=0;d<2;++d){for(e=c[d],r=t[this.scene[e]._name],n=/Click to enter .+ title/.test(r.title)?\"\":r.title,p=0;p<=2;p+=2)this.labelEnable[d+p]=!1,this.labels[d+p]=s(n),this.labelColor[d+p]=l(r.titlefont.color),this.labelFont[d+p]=r.titlefont.family,this.labelSize[d+p]=r.titlefont.size,this.labelPad[d+p]=this.getLabelPad(e,r),this.tickEnable[d+p]=!1,this.tickColor[d+p]=l((r.tickfont||{}).color),this.tickAngle[d+p]=\"auto\"===r.tickangle?0:Math.PI*-r.tickangle/180,this.tickPad[d+p]=this.getTickPad(r),this.tickMarkLength[d+p]=0,this.tickMarkWidth[d+p]=r.tickwidth||0,this.tickMarkColor[d+p]=l(r.tickcolor),this.borderLineEnable[d+p]=!1,this.borderLineColor[d+p]=l(r.linecolor),this.borderLineWidth[d+p]=r.linewidth||0;u=this.hasSharedAxis(r),a=this.hasAxisInDfltPos(e,r)&&!u,o=this.hasAxisInAltrPos(e,r)&&!u,i=r.mirror||!1,h=u?-1!==String(i).indexOf(\"all\"):!!i,f=u?\"allticks\"===i:-1!==String(i).indexOf(\"ticks\"),a?this.labelEnable[d]=!0:o&&(this.labelEnable[d+2]=!0),a?this.tickEnable[d]=r.showticklabels:o&&(this.tickEnable[d+2]=r.showticklabels),(a||h)&&(this.borderLineEnable[d]=r.showline),(o||h)&&(this.borderLineEnable[d+2]=r.showline),(a||f)&&(this.tickMarkLength[d]=this.getTickMarkLength(r)),(o||f)&&(this.tickMarkLength[d+2]=this.getTickMarkLength(r)),this.gridLineEnable[d]=r.showgrid,this.gridLineColor[d]=l(r.gridcolor),this.gridLineWidth[d]=r.gridwidth,this.zeroLineEnable[d]=r.zeroline,this.zeroLineColor[d]=l(r.zerolinecolor),this.zeroLineWidth[d]=r.zerolinewidth}},u.hasSharedAxis=function(t){var e=this.scene,r=a.getSubplotIds(e.fullLayout,\"gl2d\");return 0!==o.findSubplotsWithAxis(r,t).indexOf(e.id)},u.hasAxisInDfltPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"bottom\"===r:\"yaxis\"===t?\"left\"===r:void 0},u.hasAxisInAltrPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"top\"===r:\"yaxis\"===t?\"right\"===r:void 0},u.getLabelPad=function(t,e){var r=e.titlefont.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},u.getTickPad=function(t){return\"outside\"===t.ticks?10+t.ticklen:15},u.getTickMarkLength=function(t){if(!t.ticks)return 0;var e=t.ticklen;return\"inside\"===t.ticks?-e:e},e.exports=i},{\"../../lib/html2unicode\":683,\"../../lib/str2rgbarray\":703,\"../cartesian/axes\":724,\"../plots\":787}],764:[function(t,e,r){\"use strict\";var n=t(\"./scene2d\"),i=t(\"../plots\"),a=t(\"../../constants/xmlns_namespaces\");r.name=\"gl2d\",r.attr=[\"xaxis\",\"yaxis\"],r.idRoot=[\"x\",\"y\"],r.idRegex={x:/^x([2-9]|[1-9][0-9]+)?$/,y:/^y([2-9]|[1-9][0-9]+)?$/},r.attrRegex={x:/^xaxis([2-9]|[1-9][0-9]+)?$/,y:/^yaxis([2-9]|[1-9][0-9]+)?$/},r.attributes=t(\"../cartesian/attributes\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,a=i.getSubplotIds(e,\"gl2d\"),o=0;o<a.length;o++){var s=a[o],l=e._plots[s],u=i.getSubplotData(r,\"gl2d\",s),c=l._scene2d;void 0===c&&(c=new n({id:s,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),l._scene2d=c),c.plot(u,t.calcdata,e,t.layout)}},r.clean=function(t,e,r,n){for(var a=i.getSubplotIds(n,\"gl2d\"),o=0;o<a.length;o++){var s=a[o],l=n._plots[s];l._scene2d&&(0===i.getSubplotData(t,\"gl2d\",s).length&&(l._scene2d.destroy(),delete n._plots[s]))}},r.toSVG=function(t){for(var e=t._fullLayout,r=i.getSubplotIds(e,\"gl2d\"),n=0;n<r.length;n++){var o=e._plots[r[n]]._scene2d,s=o.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:a.svg,\"xlink:href\":s,x:0,y:0,width:\"100%\",height:\"100%\",preserveAspectRatio:\"none\"}),o.destroy()}}},{\"../../constants/xmlns_namespaces\":668,\"../cartesian/attributes\":723,\"../plots\":787,\"./scene2d\":765}],765:[function(t,e,r){\"use strict\";function n(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.fullData=null,this.updateRefs(e),this.makeFramework(),this.glplotOptions=p(this),this.glplotOptions.merge(e),this.glplot=c(this.glplotOptions),this.camera=m(this),this.traces={},this.spikes=h(this.glplot),this.selectBox=f(this.glplot,{innerFill:!1,outerFill:!0}),this.lastButtonState=0,this.pickResult=null,this.bounds=[1/0,1/0,-1/0,-1/0],this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw()}function i(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}var a,o,s=t(\"../../registry\"),l=t(\"../../plots/cartesian/axes\"),u=t(\"../../plots/cartesian/graph_interact\"),c=t(\"gl-plot2d\"),h=t(\"gl-spikes2d\"),f=t(\"gl-select-box\"),d=t(\"webgl-context\"),p=t(\"./convert\"),m=t(\"./camera\"),g=t(\"../../lib/html2unicode\"),v=t(\"../../lib/show_no_webgl_msg\"),y=t(\"../../plots/cartesian/constraints\"),b=[\"xaxis\",\"yaxis\"];e.exports=n;var x=n.prototype;x.makeFramework=function(){if(this.staticPlot){if(!(o||(a=document.createElement(\"canvas\"),o=d({canvas:a,preserveDrawingBuffer:!1,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"Error creating static canvas/context for image server\");this.canvas=a,this.gl=o}else{var t=document.createElement(\"canvas\"),e=d({canvas:t,premultipliedAlpha:!0});e||v(this),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),r.className+=\"user-select-none\";var n=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");n.style.position=\"absolute\",n.style.top=n.style.left=\"0px\",n.style.width=n.style.height=\"100%\",n.style[\"z-index\"]=20,n.style[\"pointer-events\"]=\"none\";var i=this.mouseContainer=document.createElement(\"div\");i.style.position=\"absolute\";var s=this.container;s.appendChild(r),s.appendChild(n),s.appendChild(i)},x.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(a),this.updateSize(this.canvas),this.glplot.setDirty(),this.glplot.draw();var e=this.glplot.gl,r=e.drawingBufferWidth,n=e.drawingBufferHeight;e.bindFramebuffer(e.FRAMEBUFFER,null);var i=new Uint8Array(r*n*4);e.readPixels(0,0,r,n,e.RGBA,e.UNSIGNED_BYTE,i);for(var o=0,s=n-1;o<s;++o,--s)for(var l=0;l<r;++l)for(var u=0;u<4;++u){var c=i[4*(r*o+l)+u];i[4*(r*o+l)+u]=i[4*(r*s+l)+u],i[4*(r*s+l)+u]=c}var h=document.createElement(\"canvas\");h.width=r,h.height=n;var f=h.getContext(\"2d\"),d=f.createImageData(r,n);d.data.set(i),f.putImageData(d,0,0);var p;switch(t){case\"jpeg\":p=h.toDataURL(\"image/jpeg\");break;case\"webp\":p=h.toDataURL(\"image/webp\");break;default:p=h.toDataURL(\"image/png\")}return this.staticPlot&&this.container.removeChild(a),p},x.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),this.redraw&&this.redraw(),t},x.computeTickMarks=function(){this.xaxis.setScale(),this.yaxis.setScale(),this.xaxis._length=this.glplot.viewBox[2]-this.glplot.viewBox[0],this.yaxis._length=this.glplot.viewBox[3]-this.glplot.viewBox[1];for(var t=[l.calcTicks(this.xaxis),l.calcTicks(this.yaxis)],e=0;e<2;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=g(t[e][r].text+\"\");return t},x.updateRefs=function(t){this.fullLayout=t;var e=l.subplotMatch,r=\"xaxis\"+this.id.match(e)[1],n=\"yaxis\"+this.id.match(e)[2];this.xaxis=this.fullLayout[r],this.yaxis=this.fullLayout[n]},x.relayoutCallback=function(){var t=this.graphDiv,e=this.xaxis,r=this.yaxis,n=t.layout;n.xaxis.autorange=e.autorange,n.xaxis.range=e.range.slice(0),n.yaxis.autorange=r.autorange,n.yaxis.range=r.range.slice(0);var i={lastInputTime:this.camera.lastInputTime};i[e._name]=e.range.slice(0),i[r._name]=r.range.slice(0),t.emit(\"plotly_relayout\",i)},x.cameraChanged=function(){var t=this.camera;this.glplot.setDataBox(this.calcDataBox());var e=this.computeTickMarks();i(e,this.glplotOptions.ticks)&&(this.glplotOptions.ticks=e,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions),this.handleAnnotations())},x.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&&s.getComponentMethod(\"annotations\",\"drawOne\")(t,r)}},x.destroy=function(){var t=this.traces;t&&Object.keys(t).map(function(e){t[e].dispose(),delete t[e]}),this.glplot.dispose(),this.staticPlot||this.container.removeChild(this.canvas),this.container.removeChild(this.svgContainer),this.container.removeChild(this.mouseContainer),this.fullData=null,this.glplot=null,this.stopped=!0},x.plot=function(t,e,r){var n=this.glplot;this.updateRefs(r),this.updateTraces(t,e);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=r._size,u=this.xaxis.domain,c=this.yaxis.domain;o.viewBox=[s.l+u[0]*s.w,s.b+c[0]*s.h,i-s.r-(1-u[1])*s.w,a-s.t-(1-c[1])*s.h],this.mouseContainer.style.width=s.w*(u[1]-u[0])+\"px\",this.mouseContainer.style.height=s.h*(c[1]-c[0])+\"px\",this.mouseContainer.height=s.h*(c[1]-c[0]),this.mouseContainer.style.left=s.l+u[0]*s.w+\"px\",this.mouseContainer.style.top=s.t+(1-c[1])*s.h+\"px\";var h=this.bounds;h[0]=h[1]=1/0,h[2]=h[3]=-1/0;var f,d,p=Object.keys(this.traces);for(d=0;d<p.length;++d)for(var m=this.traces[p[d]],g=0;g<2;++g)h[g]=Math.min(h[g],m.bounds[g]),h[g+2]=Math.max(h[g+2],m.bounds[g+2]);for(d=0;d<2;++d)h[d]>h[d+2]&&(h[d]=-1,h[d+2]=1),(f=this[b[d]])._length=o.viewBox[d+2]-o.viewBox[d],l.doAutoRange(f),f.setScale();var v={_axisConstraintGroups:this.graphDiv._fullLayout._axisConstraintGroups,xaxis:this.xaxis,yaxis:this.yaxis};y({_fullLayout:v}),o.ticks=this.computeTickMarks(),o.dataBox=this.calcDataBox(),o.merge(r),n.update(o),this.glplot.draw()},x.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])]},x.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])]},x.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],u=this.traces[i.uid];u?u.update(i,l):(u=i._module.plot(this,i,l),this.traces[i.uid]=u)}this.glplot.objects.sort(function(t,e){return t._trace.index-e._trace.index})},x.emitPointAction=function(t,e){for(var r,n=t.trace.uid,i=0;i<this.fullData.length;i++)this.fullData[i].uid===n&&(r=this.fullData[i]);this.graphDiv.emit(e,{points:[{x:t.traceCoord[0],y:t.traceCoord[1],curveNumber:r.index,pointNumber:t.pointIndex,data:r._input,fullData:this.fullData,xaxis:this.xaxis,yaxis:this.yaxis}]})},x.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,s=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&\"zoom\"===i.dragmode){this.selectBox.enabled=!0;for(var l=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])],c=0;c<2;c++)e.boxStart[c]===e.boxEnd[c]&&(l[c]=t.dataBox[c],l[c+2]=t.dataBox[c+2]);t.setDirty()}else if(!e.panning){this.selectBox.enabled=!1;var h=i._size,f=this.xaxis.domain,d=this.yaxis.domain,p=(a=t.pick(o/t.pixelRatio+h.l+f[0]*h.w,s/t.pixelRatio-(h.t+(1-d[1])*h.h)))&&a.object._trace.handlePick(a);if(p&&n&&this.emitPointAction(p,\"plotly_click\"),a&&\"skip\"!==a.object._trace.hoverinfo&&i.hovermode&&p&&(!this.lastPickResult||this.lastPickResult.traceUid!==p.trace.uid||this.lastPickResult.dataCoord[0]!==p.dataCoord[0]||this.lastPickResult.dataCoord[1]!==p.dataCoord[1])){var m=p;this.lastPickResult={traceUid:p.trace?p.trace.uid:null,dataCoord:p.dataCoord.slice()},this.spikes.update({center:a.dataCoord}),m.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(p,\"plotly_hover\");var g=m.hoverinfo;if(\"all\"!==g){var v=g.split(\"+\");-1===v.indexOf(\"x\")&&(m.traceCoord[0]=void 0),-1===v.indexOf(\"y\")&&(m.traceCoord[1]=void 0),-1===v.indexOf(\"z\")&&(m.traceCoord[2]=void 0),-1===v.indexOf(\"text\")&&(m.textLabel=void 0),-1===v.indexOf(\"name\")&&(m.name=void 0)}u.loneHover({x:m.screenCoord[0],y:m.screenCoord[1],xLabel:this.hoverFormatter(\"xaxis\",m.traceCoord[0]),yLabel:this.hoverFormatter(\"yaxis\",m.traceCoord[1]),zLabel:m.traceCoord[2],text:m.textLabel,name:m.name,color:m.color},{container:this.svgContainer})}}!a&&this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,this.graphDiv.emit(\"plotly_unhover\"),u.loneUnhover(this.svgContainer)),t.draw()}},x.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return l.tickText(r,r.c2l(e),\"hover\").text}}},{\"../../lib/html2unicode\":683,\"../../lib/show_no_webgl_msg\":701,\"../../plots/cartesian/axes\":724,\"../../plots/cartesian/constraints\":731,\"../../plots/cartesian/graph_interact\":733,\"../../registry\":802,\"./camera\":762,\"./convert\":763,\"gl-plot2d\":203,\"gl-select-box\":237,\"gl-spikes2d\":246,\"webgl-context\":543}],766:[function(t,e,r){\"use strict\";function n(t,e){t=t||document.body;var r=[.01,1/0];\"distanceLimits\"in(e=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 n=a({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||\"orbit\",distanceLimits:r}),l=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],u=0,c=t.clientWidth,h=t.clientHeight,f={keyBindingMode:\"rotate\",view:n,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:n.modes,tick:function(){var e=i(),r=this.delay,a=e-2*r;n.idle(e-r),n.recalcMatrix(a),n.flush(e-(100+2*r));for(var o=!0,s=n.computedMatrix,f=0;f<16;++f)o=o&&l[f]===s[f],l[f]=s[f];var d=t.clientWidth===c&&t.clientHeight===h;return c=t.clientWidth,h=t.clientHeight,o?!d:(u=Math.exp(n.computedRadius[0]),!0)},lookAt:function(t,e,r){n.lookAt(n.lastT(),t,e,r)},rotate:function(t,e,r){n.rotate(n.lastT(),t,e,r)},pan:function(t,e,r){n.pan(n.lastT(),t,e,r)},translate:function(t,e,r){n.translate(n.lastT(),t,e,r)}};Object.defineProperties(f,{matrix:{get:function(){return n.computedMatrix},set:function(t){return 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s=-f.zoomSpeed*a*e/window.innerHeight*(o-n.lastT())/100;n.pan(o,0,0,u*(Math.exp(s)-1))}}},!0),f}e.exports=n;var i=t(\"right-now\"),a=t(\"3d-view\"),o=t(\"mouse-change\"),s=t(\"mouse-wheel\")},{\"3d-view\":33,\"mouse-change\":434,\"mouse-wheel\":437,\"right-now\":483}],767:[function(t,e,r){\"use strict\";var n=t(\"./scene\"),i=t(\"../plots\"),a=t(\"../../lib\"),o=t(\"../../constants/xmlns_namespaces\");r.name=\"gl3d\",r.attr=\"scene\",r.idRoot=\"scene\",r.idRegex=/^scene([2-9]|[1-9][0-9]+)?$/,r.attrRegex=/^scene([2-9]|[1-9][0-9]+)?$/,r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,o=i.getSubplotIds(e,\"gl3d\"),s=0;s<o.length;s++){var l=o[s],u=i.getSubplotData(r,\"gl3d\",l),c=e[l],h=c._scene;h||(h=new n({id:l,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),c._scene=h),h.cameraInitial||(h.cameraInitial=a.extendDeep({},c.camera)),h.plot(u,e,t.layout)}},r.clean=function(t,e,r,n){for(var a=i.getSubplotIds(n,\"gl3d\"),o=0;o<a.length;o++){var s=a[o];!e[s]&&n[s]._scene&&n[s]._scene.destroy()}},r.toSVG=function(t){for(var e=t._fullLayout,r=i.getSubplotIds(e,\"gl3d\"),n=e._size,a=0;a<r.length;a++){var s=e[r[a]],l=s.domain,u=s._scene,c=u.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":c,x:n.l+n.w*l.x[0],y:n.t+n.h*(1-l.y[1]),width:n.w*(l.x[1]-l.x[0]),height:n.h*(l.y[1]-l.y[0]),preserveAspectRatio:\"none\"}),u.destroy()}},r.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),\"scene\"+e}}},{\"../../constants/xmlns_namespaces\":668,\"../../lib\":685,\"../plots\":787,\"./layout/attributes\":768,\"./layout/defaults\":772,\"./layout/layout_attributes\":773,\"./scene\":777}],768:[function(t,e,r){\"use strict\";e.exports={scene:{valType:\"subplotid\",dflt:\"scene\"}}},{}],769:[function(t,e,r){\"use strict\";var n=t(\"../../../components/color\"),i=t(\"../../cartesian/layout_attributes\"),a=t(\"../../../lib/extend\").extendFlat;e.exports={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:i.title,titlefont:i.titlefont,type:i.type,autorange:i.autorange,rangemode:i.rangemode,range:i.range,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,separatethousands:i.separatethousands,tickformat:i.tickformat,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}},{\"../../../components/color\":578,\"../../../lib/extend\":677,\"../../cartesian/layout_attributes\":735}],770:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\").mix,i=t(\"../../../lib\"),a=t(\"./axis_attributes\"),o=t(\"../../cartesian/type_defaults\"),s=t(\"../../cartesian/axis_defaults\"),l=[\"xaxis\",\"yaxis\",\"zaxis\"];e.exports=function(t,e,r){function u(t,e){return i.coerce(c,h,a,t,e)}for(var c,h,f=0;f<l.length;f++){var d=l[f];c=t[d]||{},h=e[d]={_id:d[0]+r.scene,_name:d},o(c,h,u,r.data),s(c,h,u,{font:r.font,letter:d[0],data:r.data,showGrid:!0,bgColor:r.bgColor,calendar:r.calendar}),u(\"gridcolor\",n(h.color,r.bgColor,13600/187).toRgbString()),u(\"title\",d[0]),h.setScale=i.noop,u(\"showspikes\")&&(u(\"spikesides\"),u(\"spikethickness\"),u(\"spikecolor\",h.color)),u(\"showaxeslabels\"),u(\"showbackground\")&&u(\"backgroundcolor\")}}},{\"../../../lib\":685,\"../../cartesian/axis_defaults\":726,\"../../cartesian/type_defaults\":746,\"./axis_attributes\":769,tinycolor2:514}],771:[function(t,e,r){\"use strict\";function n(){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.labelAngle=[0,0,0],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()}function i(t){var e=new n;return e.merge(t),e}var a=t(\"../../../lib/html2unicode\"),o=t(\"../../../lib/str2rgbarray\"),s=[\"xaxis\",\"yaxis\",\"zaxis\"];n.prototype.merge=function(t){for(var e=this,r=0;r<3;++r){var n=t[s[r]];n.visible?(e.labels[r]=a(n.title),\"titlefont\"in n&&(n.titlefont.color&&(e.labelColor[r]=o(n.titlefont.color)),n.titlefont.family&&(e.labelFont[r]=n.titlefont.family),n.titlefont.size&&(e.labelSize[r]=n.titlefont.size)),\"showline\"in n&&(e.lineEnable[r]=n.showline),\"linecolor\"in n&&(e.lineColor[r]=o(n.linecolor)),\"linewidth\"in n&&(e.lineWidth[r]=n.linewidth),\"showgrid\"in n&&(e.gridEnable[r]=n.showgrid),\"gridcolor\"in n&&(e.gridColor[r]=o(n.gridcolor)),\"gridwidth\"in n&&(e.gridWidth[r]=n.gridwidth),\"log\"===n.type?e.zeroEnable[r]=!1:\"zeroline\"in n&&(e.zeroEnable[r]=n.zeroline),\"zerolinecolor\"in n&&(e.zeroLineColor[r]=o(n.zerolinecolor)),\"zerolinewidth\"in n&&(e.zeroLineWidth[r]=n.zerolinewidth),\"ticks\"in n&&n.ticks?e.lineTickEnable[r]=!0:e.lineTickEnable[r]=!1,\"ticklen\"in n&&(e.lineTickLength[r]=e._defaultLineTickLength[r]=n.ticklen),\"tickcolor\"in n&&(e.lineTickColor[r]=o(n.tickcolor)),\"tickwidth\"in n&&(e.lineTickWidth[r]=n.tickwidth),\"tickangle\"in n&&(e.tickAngle[r]=\"auto\"===n.tickangle?0:Math.PI*-n.tickangle/180),\"showticklabels\"in n&&(e.tickEnable[r]=n.showticklabels),\"tickfont\"in n&&(n.tickfont.color&&(e.tickColor[r]=o(n.tickfont.color)),n.tickfont.family&&(e.tickFont[r]=n.tickfont.family),n.tickfont.size&&(e.tickSize[r]=n.tickfont.size)),\"mirror\"in n?-1!==[\"ticks\",\"all\",\"allticks\"].indexOf(n.mirror)?(e.lineTickMirror[r]=!0,e.lineMirror[r]=!0):!0===n.mirror?(e.lineTickMirror[r]=!1,e.lineMirror[r]=!0):(e.lineTickMirror[r]=!1,e.lineMirror[r]=!1):e.lineMirror[r]=!1,\"showbackground\"in n&&!1!==n.showbackground?(e.backgroundEnable[r]=!0,e.backgroundColor[r]=o(n.backgroundcolor)):e.backgroundEnable[r]=!1):(e.tickEnable[r]=!1,e.labelEnable[r]=!1,e.lineEnable[r]=!1,e.lineTickEnable[r]=!1,e.gridEnable[r]=!1,e.zeroEnable[r]=!1,e.backgroundEnable[r]=!1)}},e.exports=i},{\"../../../lib/html2unicode\":683,\"../../../lib/str2rgbarray\":703}],772:[function(t,e,r){\"use strict\";function n(t,e,r,n){for(var i=r(\"bgcolor\"),o=a.combine(i,n.paper_bgcolor),u=Object.keys(s.camera),c=0;c<u.length;c++)r(\"camera.\"+u[c]+\".x\"),r(\"camera.\"+u[c]+\".y\"),r(\"camera.\"+u[c]+\".z\");var h=!!r(\"aspectratio.x\")&&!!r(\"aspectratio.y\")&&!!r(\"aspectratio.z\"),f=r(\"aspectmode\",h?\"manual\":\"auto\");h||(t.aspectratio=e.aspectratio={x:1,y:1,z:1},\"manual\"===f&&(e.aspectmode=\"auto\")),l(t,e,{font:n.font,scene:n.id,data:n.fullData,bgColor:o,calendar:n.calendar}),r(\"dragmode\",n.getDfltFromLayout(\"dragmode\")),r(\"hovermode\",n.getDfltFromLayout(\"hovermode\"))}var i=t(\"../../../lib\"),a=t(\"../../../components/color\"),o=t(\"../../subplot_defaults\"),s=t(\"./layout_attributes\"),l=t(\"./axis_defaults\");e.exports=function(t,e,r){function a(e){if(!l)return i.validate(t[e],s[e])?t[e]:void 0}var l=e._basePlotModules.length>1;o(t,e,r,{type:\"gl3d\",attributes:s,handleDefaults:n,font:e.font,fullData:r,getDfltFromLayout:a,paper_bgcolor:e.paper_bgcolor,calendar:e.calendar})}},{\"../../../components/color\":578,\"../../../lib\":685,\"../../subplot_defaults\":794,\"./axis_defaults\":770,\"./layout_attributes\":773}],773:[function(t,e,r){\"use strict\";function n(t,e,r){return{x:{valType:\"number\",dflt:t},y:{valType:\"number\",dflt:e},z:{valType:\"number\",dflt:r}}}var i=t(\"./axis_attributes\"),a=t(\"../../../lib/extend\").extendFlat;e.exports={bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\"},camera:{up:a(n(0,0,1),{}),center:a(n(0,0,0),{}),eye:a(n(1.25,1.25,1.25),{})},domain:{x:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]},y:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]}},aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\"},aspectratio:{x:{valType:\"number\",min:0},y:{valType:\"number\",min:0},z:{valType:\"number\",min:0}},xaxis:i,yaxis:i,zaxis:i,dragmode:{valType:\"enumerated\",values:[\"orbit\",\"turntable\",\"zoom\",\"pan\",!1],dflt:\"turntable\"},hovermode:{valType:\"enumerated\",values:[\"closest\",!1],dflt:\"closest\"},_deprecated:{cameraposition:{valType:\"info_array\"}}}},{\"../../../lib/extend\":677,\"./axis_attributes\":769}],774:[function(t,e,r){\"use strict\";function n(){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]}function i(t){var e=new n;return e.merge(t),e}var a=t(\"../../../lib/str2rgbarray\"),o=[\"xaxis\",\"yaxis\",\"zaxis\"];n.prototype.merge=function(t){for(var e=0;e<3;++e){var r=t[o[e]];r.visible?(this.enabled[e]=r.showspikes,this.colors[e]=a(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness):(this.enabled[e]=!1,this.drawSides[e]=!1)}},e.exports=i},{\"../../../lib/str2rgbarray\":703}],775:[function(t,e,r){\"use strict\";function n(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}function i(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,i=t.fullSceneLayout,c=[[],[],[]],h=0;h<3;++h){var f=i[l[h]];if(f._length=(r[h].hi-r[h].lo)*r[h].pixelsPerDataUnit/t.dataScale[h],Math.abs(f._length)===1/0)c[h]=[];else{f.range[0]=r[h].lo/t.dataScale[h],f.range[1]=r[h].hi/t.dataScale[h],f._m=1/(t.dataScale[h]*r[h].pixelsPerDataUnit),f.range[0]===f.range[1]&&(f.range[0]-=1,f.range[1]+=1);var d=f.tickmode;if(\"auto\"===f.tickmode){f.tickmode=\"linear\";var p=f.nticks||o.constrain(f._length/40,4,9);a.autoTicks(f,Math.abs(f.range[1]-f.range[0])/p)}for(var m=a.calcTicks(f),g=0;g<m.length;++g)m[g].x=m[g].x*t.dataScale[h],m[g].text=s(m[g].text);c[h]=m,f.tickmode=d}}e.ticks=c;for(h=0;h<3;++h){u[h]=.5*(t.glplot.bounds[0][h]+t.glplot.bounds[1][h]);for(g=0;g<2;++g)e.bounds[g][h]=t.glplot.bounds[g][h]}t.contourLevels=n(c)}e.exports=i;var a=t(\"../../cartesian/axes\"),o=t(\"../../../lib\"),s=t(\"../../../lib/html2unicode\"),l=[\"xaxis\",\"yaxis\",\"zaxis\"],u=[0,0,0]},{\"../../../lib\":685,\"../../../lib/html2unicode\":683,\"../../cartesian/axes\":724}],776:[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}function i(t,e){return n(t.projection,n(t.view,n(t.model,[e[0],e[1],e[2],1])))}e.exports=i},{}],777:[function(t,e,r){\"use strict\";function n(t){function e(e,r){var n=t.fullSceneLayout[e];return m.tickText(n,n.d2l(r),\"hover\").text}var r,n=t.svgContainer,i=t.container.getBoundingClientRect(),a=i.width,o=i.height;n.setAttributeNS(null,\"viewBox\",\"0 0 \"+a+\" \"+o),n.setAttributeNS(null,\"width\",a),n.setAttributeNS(null,\"height\",o),M(t),t.glplot.axes.update(t.axesOptions);for(var s=Object.keys(t.traces),l=null,u=t.glplot.selection,c=0;c<s.length;++c)\"skip\"!==(r=t.traces[s[c]]).data.hoverinfo&&r.handlePick(u)&&(l=r),r.setContourLevels&&r.setContourLevels();var h;if(null!==l){var f=x(t.glplot.cameraParams,u.dataCoordinate),d=(r=l.data).hoverinfo,p=e(\"xaxis\",u.traceCoordinate[0]),v=e(\"yaxis\",u.traceCoordinate[1]),y=e(\"zaxis\",u.traceCoordinate[2]);if(\"all\"!==d){var b=d.split(\"+\");-1===b.indexOf(\"x\")&&(p=void 0),-1===b.indexOf(\"y\")&&(v=void 0),-1===b.indexOf(\"z\")&&(y=void 0),-1===b.indexOf(\"text\")&&(u.textLabel=void 0),-1===b.indexOf(\"name\")&&(l.name=void 0)}t.fullSceneLayout.hovermode&&g.loneHover({x:(.5+.5*f[0]/f[3])*a,y:(.5-.5*f[1]/f[3])*o,xLabel:p,yLabel:v,zLabel:y,text:u.textLabel,name:l.name,color:l.color},{container:n});var _={points:[{x:p,y:v,z:y,data:r._input,fullData:r,curveNumber:r.index,pointNumber:u.data.index}]};u.buttons&&u.distance<5?t.graphDiv.emit(\"plotly_click\",_):t.graphDiv.emit(\"plotly_hover\",_),h=_}else g.loneUnhover(n),t.graphDiv.emit(\"plotly_unhover\",h)}function i(t,e,r,i){var a={canvas:r,gl:i,container:t.container,axes:t.axesOptions,spikes:t.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1};if(t.staticMode){if(!(h||(c=document.createElement(\"canvas\"),h=d({canvas:c,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"error creating static canvas/context for image server\");a.pixelRatio=t.pixelRatio,a.gl=h,a.canvas=c}try{t.glplot=f(a)}catch(e){y(t)}var o=function(t){if(!1!==t.fullSceneLayout.dragmode){var e={};e[t.id]=u(t.camera),t.saveCamera(t.graphDiv.layout),t.graphDiv.emit(\"plotly_relayout\",e)}};if(t.glplot.canvas.addEventListener(\"mouseup\",o.bind(null,t)),t.glplot.canvas.addEventListener(\"wheel\",o.bind(null,t)),t.staticMode||t.glplot.canvas.addEventListener(\"webglcontextlost\",function(t){p.warn(\"Lost WebGL context.\"),t.preventDefault()}),!t.camera){var s=t.fullSceneLayout.camera;t.camera=b(t.container,{center:[s.center.x,s.center.y,s.center.z],eye:[s.eye.x,s.eye.y,s.eye.z],up:[s.up.x,s.up.y,s.up.z],zoomMin:.1,zoomMax:100,mode:\"orbit\"})}return t.glplot.camera=t.camera,t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=n.bind(null,t),t.traces={},!0}function a(t,e){var r=document.createElement(\"div\"),n=t.container;this.graphDiv=t.graphDiv;var a=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\",r.appendChild(a),this.svgContainer=a,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=_(e[this.id]),this.spikeOptions=w(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],i(this,e)}function o(t,e,r,n,i){for(var a,o=0;o<e.length;++o)if(Array.isArray(e[o]))for(var s=0;s<e[o].length;++s)a=t.d2l(e[o][s],0,i),!isNaN(a)&&isFinite(a)&&(n[0][r]=Math.min(n[0][r],a),n[1][r]=Math.max(n[1][r],a));else a=t.d2l(e[o],0,i),!isNaN(a)&&isFinite(a)&&(n[0][r]=Math.min(n[0][r],a),n[1][r]=Math.max(n[1][r],a))}function s(t,e,r){var n=t.fullSceneLayout;o(n.xaxis,e.x,0,r,e.xcalendar),o(n.yaxis,e.y,1,r,e.ycalendar),o(n.zaxis,e.z,2,r,e.zcalendar)}function l(t){return[[t.eye.x,t.eye.y,t.eye.z],[t.center.x,t.center.y,t.center.z],[t.up.x,t.up.y,t.up.z]]}function u(t){return{up:{x:t.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]}}}var c,h,f=t(\"gl-plot3d\"),d=t(\"webgl-context\"),p=t(\"../../lib\"),m=t(\"../../plots/cartesian/axes\"),g=t(\"../../plots/cartesian/graph_interact\"),v=t(\"../../lib/str2rgbarray\"),y=t(\"../../lib/show_no_webgl_msg\"),b=t(\"./camera\"),x=t(\"./project\"),_=t(\"./layout/convert\"),w=t(\"./layout/spikes\"),M=t(\"./layout/tick_marks\"),k=a.prototype;k.recoverContext=function(){function t(){r.isContextLost()?requestAnimationFrame(t):i(e,e.fullLayout,n,r)?e.plot.apply(e,e.plotArgs):p.error(\"Catastrophic and unrecoverable WebGL error. Context lost.\")}var e=this,r=this.glplot.gl,n=this.glplot.canvas;this.glplot.dispose(),requestAnimationFrame(t)};var A=[\"xaxis\",\"yaxis\",\"zaxis\"];k.plot=function(t,e,r){if(this.plotArgs=[t,e,r],!this.glplot.contextLost){var n,i,a,o,l,u,c=e[this.id],h=r[this.id];c.bgcolor?this.glplot.clearColor=v(c.bgcolor):this.glplot.clearColor=[0,0,0,0],this.glplot.snapToData=!0,this.fullLayout=e,this.fullSceneLayout=c,this.glplotLayout=c,this.axesOptions.merge(c),this.spikeOptions.merge(c),this.setCamera(c.camera),this.updateFx(c.dragmode,c.hovermode),this.glplot.update({}),this.setConvert(l),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&&s(this,n,f);var d=[1,1,1];for(o=0;o<3;++o)f[0][o]>f[1][o]?d[o]=1:f[1][o]===f[0][o]?d[o]=1:d[o]=1/(f[1][o]-f[0][o]);for(this.dataScale=d,a=0;a<t.length;++a)!0===(n=t[a]).visible&&((i=this.traces[n.uid])?i.update(n):(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)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 m=[[0,0,0],[0,0,0]],g=[],y={};for(a=0;a<3;++a){if(l=c[A[a]],u=l.type,u in y?(y[u].acc*=d[a],y[u].count+=1):y[u]={acc:d[a],count:1},l.autorange){for(m[0][a]=1/0,m[1][a]=-1/0,o=0;o<this.glplot.objects.length;++o){var b=this.glplot.objects[o].bounds;m[0][a]=Math.min(m[0][a],b[0][a]/d[a]),m[1][a]=Math.max(m[1][a],b[1][a]/d[a])}if(\"rangemode\"in l&&\"tozero\"===l.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 x=m[1][a]-m[0][a];m[0][a]-=x/32,m[1][a]+=x/32}}else{var _=c[A[a]].range;m[0][a]=_[0],m[1][a]=_[1]}m[0][a]===m[1][a]&&(m[0][a]-=1,m[1][a]+=1),g[a]=m[1][a]-m[0][a],this.glplot.bounds[0][a]=m[0][a]*d[a],this.glplot.bounds[1][a]=m[1][a]*d[a]}var w=[1,1,1];for(a=0;a<3;++a){var M=y[u=(l=c[A[a]]).type];w[a]=Math.pow(M.acc,1/M.count)/d[a]}var k;if(\"auto\"===c.aspectmode)k=Math.max.apply(null,w)/Math.min.apply(null,w)<=4?w:[1,1,1];else if(\"cube\"===c.aspectmode)k=[1,1,1];else if(\"data\"===c.aspectmode)k=w;else{if(\"manual\"!==c.aspectmode)throw new Error(\"scene.js aspectRatio was not one of the enumerated types\");var T=c.aspectratio;k=[T.x,T.y,T.z]}c.aspectratio.x=h.aspectratio.x=k[0],c.aspectratio.y=h.aspectratio.y=k[1],c.aspectratio.z=h.aspectratio.z=k[2],this.glplot.aspect=k;var S=c.domain||null,E=e._size||null;if(S&&E){var L=this.container.style;L.position=\"absolute\",L.left=E.l+S.x[0]*E.w+\"px\",L.top=E.t+(1-S.y[1])*E.h+\"px\",L.width=E.w*(S.x[1]-S.x[0])+\"px\",L.height=E.h*(S.y[1]-S.y[0])+\"px\"}this.glplot.redraw()}},k.destroy=function(){this.glplot.dispose(),this.container.parentNode.removeChild(this.container),this.glplot=null},k.getCamera=function(){return this.glplot.camera.view.recalcMatrix(this.camera.view.lastT()),u(this.glplot.camera)},k.setCamera=function(t){this.glplot.camera.lookAt.apply(this,l(t))},k.saveCamera=function(t){var e=this.getCamera(),r=p.nestedProperty(t,this.id+\".camera\"),n=r.get(),i=!1;if(void 0===n)i=!0;else for(var a=0;a<3;a++)for(var o=0;o<3;o++)if(!function(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]]}(e,n,a,o)){i=!0;break}return i&&r.set(e),i},k.updateFx=function(t,e){var r=this.camera;r&&(\"orbit\"===t?(r.mode=\"orbit\",r.keyBindingMode=\"rotate\"):\"turntable\"===t?(r.up=[0,0,1],r.mode=\"turntable\",r.keyBindingMode=\"rotate\"):r.keyBindingMode=t),this.fullSceneLayout.hovermode=e},k.toImage=function(t){t||(t=\"png\"),this.staticMode&&this.container.appendChild(c),this.glplot.redraw();var e=this.glplot.gl,r=e.drawingBufferWidth,n=e.drawingBufferHeight;e.bindFramebuffer(e.FRAMEBUFFER,null);var i=new Uint8Array(r*n*4);e.readPixels(0,0,r,n,e.RGBA,e.UNSIGNED_BYTE,i);for(var a=0,o=n-1;a<o;++a,--o)for(var s=0;s<r;++s)for(var l=0;l<4;++l){var u=i[4*(r*a+s)+l];i[4*(r*a+s)+l]=i[4*(r*o+s)+l],i[4*(r*o+s)+l]=u}var h=document.createElement(\"canvas\");h.width=r,h.height=n;var f=h.getContext(\"2d\"),d=f.createImageData(r,n);d.data.set(i),f.putImageData(d,0,0);var p;switch(t){case\"jpeg\":p=h.toDataURL(\"image/jpeg\");break;case\"webp\":p=h.toDataURL(\"image/webp\");break;default:p=h.toDataURL(\"image/png\")}return this.staticMode&&this.container.removeChild(c),p},k.setConvert=function(){for(var t=0;t<3;++t){var e=this.fullSceneLayout[A[t]];m.setConvert(e,this.fullLayout),e.setScale=p.noop}},e.exports=a},{\"../../lib\":685,\"../../lib/show_no_webgl_msg\":701,\"../../lib/str2rgbarray\":703,\"../../plots/cartesian/axes\":724,\"../../plots/cartesian/graph_interact\":733,\"./camera\":766,\"./layout/convert\":771,\"./layout/spikes\":774,\"./layout/tick_marks\":775,\"./project\":776,\"gl-plot3d\":205,\"webgl-context\":543}],778:[function(t,e,r){\"use strict\";var n=t(\"../lib\").extendFlat,i=t(\"./font_attributes\"),a=t(\"../components/color/attributes\");e.exports={font:{family:n({},i.family,{dflt:'\"Open Sans\", verdana, arial, sans-serif'}),size:n({},i.size,{dflt:12}),color:n({},i.color,{dflt:a.defaultLine})},title:{valType:\"string\",dflt:\"Click to enter Plot title\"},titlefont:n({},i,{}),autosize:{valType:\"boolean\",dflt:!1},width:{valType:\"number\",min:10,dflt:700},height:{valType:\"number\",min:10,dflt:450},margin:{l:{valType:\"number\",min:0,dflt:80},r:{valType:\"number\",min:0,dflt:80},t:{valType:\"number\",min:0,dflt:100},b:{valType:\"number\",min:0,dflt:80},pad:{valType:\"number\",min:0,dflt:0},autoexpand:{valType:\"boolean\",dflt:!0}},paper_bgcolor:{valType:\"color\",dflt:a.background},plot_bgcolor:{valType:\"color\",dflt:a.background},separators:{valType:\"string\",dflt:\".,\"},hidesources:{valType:\"boolean\",dflt:!1},smith:{valType:\"enumerated\",values:[!1],dflt:!1},showlegend:{valType:\"boolean\"},dragmode:{valType:\"enumerated\",values:[\"zoom\",\"pan\",\"select\",\"lasso\",\"orbit\",\"turntable\"],dflt:\"zoom\"},hovermode:{valType:\"enumerated\",values:[\"x\",\"y\",\"closest\",!1]}}},{\"../components/color/attributes\":577,\"../lib\":685,\"./font_attributes\":748}],779:[function(t,e,r){\"use strict\";e.exports={styleUrlPrefix:\"mapbox://styles/mapbox/\",styleUrlSuffix:\"v9\",controlContainerClassName:\"mapboxgl-control-container\",noAccessTokenErrorMsg:[\"Missing Mapbox access token.\",\"Mapbox trace type require a Mapbox access token to be registered.\",\"For example:\",\"  Plotly.plot(gd, data, layout, { mapboxAccessToken: 'my-access-token' });\",\"More info here: https://www.mapbox.com/help/define-access-token/\"].join(\"\\n\"),mapOnErrorMsg:\"Mapbox error.\"}},{}],780:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e){var r=t.split(\" \"),i=r[0],a=r[1],o=Array.isArray(e)?n.mean(e):e,s=.5+o/100,l=1.5+o/100,u=[\"\",\"\"],c=[0,0];switch(i){case\"top\":u[0]=\"top\",c[1]=-l;break;case\"bottom\":u[0]=\"bottom\",c[1]=l}switch(a){case\"left\":u[1]=\"right\",c[0]=-s;break;case\"right\":u[1]=\"left\",c[0]=s}var h;return h=u[0]&&u[1]?u.join(\"-\"):u[0]?u[0]:u[1]?u[1]:\"center\",{anchor:h,offset:c}}},{\"../../lib\":685}],781:[function(t,e,r){\"use strict\";function n(t,e){var r=t._fullLayout,n=t._context;if(\"\"===n.mapboxAccessToken)return\"\";for(var i=n.mapboxAccessToken,a=0;a<e.length;a++){var o=r[e[a]];if(o.accesstoken){i=o.accesstoken;break}}if(!i)throw new Error(l.noAccessTokenErrorMsg);return i}var i=t(\"mapbox-gl\"),a=t(\"../plots\"),o=t(\"../../constants/xmlns_namespaces\"),s=t(\"./mapbox\"),l=t(\"./constants\");r.name=\"mapbox\",r.attr=\"subplot\",r.idRoot=\"mapbox\",r.idRegex=/^mapbox([2-9]|[1-9][0-9]+)?$/,r.attrRegex=/^mapbox([2-9]|[1-9][0-9]+)?$/,r.attributes={subplot:{valType:\"subplotid\",dflt:\"mapbox\"}},r.layoutAttributes=t(\"./layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout_defaults\"),r.plot=function(t){var e=t._fullLayout,r=t.calcdata,o=a.getSubplotIds(e,\"mapbox\"),l=n(t,o);i.accessToken=l;for(var u=0;u<o.length;u++){var c=o[u],h=a.getSubplotCalcData(r,\"mapbox\",c),f=e[c],d=f._subplot;f.accesstoken=l,d||(d=s({gd:t,container:e._glcontainer.node(),id:c,fullLayout:e,staticPlot:t._context.staticPlot}),e[c]._subplot=d),d.plot(h,e,t._promises)}},r.clean=function(t,e,r,n){for(var i=a.getSubplotIds(n,\"mapbox\"),o=0;o<i.length;o++){var s=i[o];!e[s]&&n[s]._subplot&&n[s]._subplot.destroy()}},r.toSVG=function(t){for(var e=t._fullLayout,r=a.getSubplotIds(e,\"mapbox\"),n=e._size,i=0;i<r.length;i++){var s=e[r[i]],l=s.domain,u=s._subplot,c=u.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":c,x:n.l+n.w*l.x[0],y:n.t+n.h*(1-l.y[1]),width:n.w*(l.x[1]-l.x[0]),height:n.h*(l.y[1]-l.y[0]),preserveAspectRatio:\"none\"}),u.destroy()}}},{\"../../constants/xmlns_namespaces\":668,\"../plots\":787,\"./constants\":779,\"./layout_attributes\":783,\"./layout_defaults\":784,\"./mapbox\":785,\"mapbox-gl\":325}],782:[function(t,e,r){\"use strict\";function 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n=t.symbol,i=l(n.textposition,n.iconsize);s.extendFlat(e,{\"icon-image\":n.icon+\"-15\",\"icon-size\":n.iconsize/10,\"text-field\":n.text,\"text-size\":n.textfont.size,\"text-anchor\":i.anchor,\"text-offset\":i.offset}),s.extendFlat(r,{\"icon-color\":t.color,\"text-color\":n.textfont.color,\"text-opacity\":t.opacity})}return{layout:e,paint:r}}function o(t){var e,r=t.sourcetype,n=t.source,i={type:r},a=\"string\"==typeof n;return\"geojson\"===r?e=\"data\":\"vector\"===r&&(e=a?\"url\":\"tiles\"),i[e]=n,i}var s=t(\"../../lib\"),l=t(\"./convert_text_opts\"),u=n.prototype;u.update=function(t){this.visible?this.needsNewSource(t)?(this.updateLayer(t),this.updateSource(t)):this.needsNewLayer(t)&&this.updateLayer(t):(this.updateSource(t),this.updateLayer(t)),this.updateStyle(t),this.visible=i(t)},u.needsNewSource=function(t){return this.sourceType!==t.sourcetype||this.source!==t.source||this.layerType!==t.type},u.needsNewLayer=function(t){return 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n=t(\"../../cartesian/layout_attributes\"),i=t(\"../../../lib/extend\").extendFlat;e.exports={title:n.title,titlefont:n.titlefont,color:n.color,tickmode:n.tickmode,nticks:i({},n.nticks,{dflt:6,min:1}),tick0:n.tick0,dtick:n.dtick,tickvals:n.tickvals,ticktext:n.ticktext,ticks:n.ticks,ticklen:n.ticklen,tickwidth:n.tickwidth,tickcolor:n.tickcolor,showticklabels:n.showticklabels,showtickprefix:n.showtickprefix,tickprefix:n.tickprefix,showticksuffix:n.showticksuffix,ticksuffix:n.ticksuffix,showexponent:n.showexponent,exponentformat:n.exponentformat,separatethousands:n.separatethousands,tickfont:n.tickfont,tickangle:n.tickangle,tickformat:n.tickformat,hoverformat:n.hoverformat,showline:i({},n.showline,{dflt:!0}),linecolor:n.linecolor,linewidth:n.linewidth,showgrid:i({},n.showgrid,{dflt:!0}),gridcolor:n.gridcolor,gridwidth:n.gridwidth,min:{valType:\"number\",dflt:0,min:0}}},{\"../../../lib/extend\":677,\"../../cartesian/layout_attributes\":735}],798:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\").mix,i=t(\"../../../lib\"),a=t(\"./axis_attributes\"),o=t(\"../../cartesian/tick_label_defaults\"),s=t(\"../../cartesian/tick_mark_defaults\"),l=t(\"../../cartesian/tick_value_defaults\");e.exports=function(t,e,r){function u(r,n){return i.coerce(t,e,a,r,n)}e.type=\"linear\";var c=u(\"color\"),h=c===t.color?c:r.font.color,f=e._name.charAt(0).toUpperCase(),d=\"Component 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d=e.aaxis,p=e.baxis,m=e.caxis;d.min+p.min+m.min>=o&&(d.min=0,p.min=0,m.min=0,t.aaxis&&delete t.aaxis.min,t.baxis&&delete t.baxis.min,t.caxis&&delete t.caxis.min)}var i=t(\"../../../components/color\"),a=t(\"../../subplot_defaults\"),o=t(\"./layout_attributes\"),s=t(\"./axis_defaults\"),l=[\"aaxis\",\"baxis\",\"caxis\"];e.exports=function(t,e,r){a(t,e,r,{type:\"ternary\",attributes:o,handleDefaults:n,font:e.font,paper_bgcolor:e.paper_bgcolor})}},{\"../../../components/color\":578,\"../../subplot_defaults\":794,\"./axis_defaults\":798,\"./layout_attributes\":800}],800:[function(t,e,r){\"use strict\";var n=t(\"../../../components/color/attributes\"),i=t(\"./axis_attributes\");e.exports={domain:{x:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]},y:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]}},bgcolor:{valType:\"color\",dflt:n.background},sum:{valType:\"number\",dflt:1,min:0},aaxis:i,baxis:i,caxis:i}},{\"../../../components/color/attributes\":577,\"./axis_attributes\":797}],801:[function(t,e,r){\"use strict\";function n(t,e){this.id=t.id,this.graphDiv=t.graphDiv,this.init(e),this.makeFramework()}function i(t){a.select(t).selectAll(\".zoombox,.js-zoombox-backdrop,.js-zoombox-menu,.zoombox-corners\").remove()}var a=t(\"d3\"),o=t(\"tinycolor2\"),s=t(\"../../plotly\"),l=t(\"../../lib\"),u=t(\"../../components/color\"),c=t(\"../../components/drawing\"),h=t(\"../cartesian/set_convert\"),f=t(\"../../lib/extend\").extendFlat,d=t(\"../plots\"),p=t(\"../cartesian/axes\"),m=t(\"../../components/dragelement\"),g=t(\"../../components/titles\"),v=t(\"../cartesian/select\"),y=t(\"../cartesian/constants\"),b=t(\"../cartesian/graph_interact\");e.exports=n;var x=n.prototype;x.init=function(t){this.container=t._ternarylayer,this.defs=t._defs,this.layoutId=t._uid,this.traceHash={}},x.plot=function(t,e){var r=this,n=e[r.id],i=e._size;r.adjustLayout(n,i),d.generalUpdatePerTraceModule(r,t,n),r.layers.plotbg.select(\"path\").call(u.fill,n.bgcolor)},x.makeFramework=function(){var t=this,e=t.defs.selectAll(\"g.clips\").data([0]);e.enter().append(\"g\").classed(\"clips\",!0);var r=\"clip\"+t.layoutId+t.id;t.clipDef=e.selectAll(\"#\"+r).data([0]),t.clipDef.enter().append(\"clipPath\").attr(\"id\",r).append(\"path\").attr(\"d\",\"M0,0Z\"),t.plotContainer=t.container.selectAll(\"g.\"+t.id).data([0]),t.plotContainer.enter().append(\"g\").classed(t.id,!0),t.layers={};var n=[\"draglayer\",\"plotbg\",\"backplot\",\"grids\",\"frontplot\",\"zoom\",\"aaxis\",\"baxis\",\"caxis\",\"axlines\"];t.plotContainer.selectAll(\"g.toplevel\").data(n).enter().append(\"g\").attr(\"class\",function(t){return\"toplevel \"+t}).each(function(e){var r=a.select(this);t.layers[e]=r,\"frontplot\"===e?r.append(\"g\").classed(\"scatterlayer\",!0):\"backplot\"===e?r.append(\"g\").classed(\"maplayer\",!0):\"plotbg\"===e?r.append(\"path\").attr(\"d\",\"M0,0Z\"):\"axlines\"===e&&r.selectAll(\"path\").data([\"aline\",\"bline\",\"cline\"]).enter().append(\"path\").each(function(t){a.select(this).classed(t,!0)})}),t.plotContainer.select(\".grids\").selectAll(\"g.grid\").data([\"agrid\",\"bgrid\",\"cgrid\"]).enter().append(\"g\").attr(\"class\",function(t){return\"grid \"+t}).each(function(e){t.layers[e]=a.select(this)}),t.plotContainer.selectAll(\".backplot,.frontplot,.grids\").call(c.setClipUrl,r),t.graphDiv._context.staticPlot||t.initInteractions()};var _=Math.sqrt(4/3);x.adjustLayout=function(t,e){var r,n,i,a,o,s,l=this,c=t.domain,d=(c.x[0]+c.x[1])/2,p=(c.y[0]+c.y[1])/2,m=c.x[1]-c.x[0],g=c.y[1]-c.y[0],v=m*e.w,y=g*e.h,b=t.sum,x=t.aaxis.min,w=t.baxis.min,M=t.caxis.min;v>_*y?i=(a=y)*_:a=(i=v)/_,o=m*i/v,s=g*a/y,r=e.l+e.w*d-i/2,n=e.t+e.h*(1-p)-a/2,l.x0=r,l.y0=n,l.w=i,l.h=a,l.sum=b,l.xaxis={type:\"linear\",range:[x+2*M-b,b-x-2*w],domain:[d-o/2,d+o/2],_id:\"x\"},h(l.xaxis,l.graphDiv._fullLayout),l.xaxis.setScale(),l.yaxis={type:\"linear\",range:[x,b-w-M],domain:[p-s/2,p+s/2],_id:\"y\"},h(l.yaxis,l.graphDiv._fullLayout),l.yaxis.setScale();var k=l.yaxis.domain[0],A=l.aaxis=f({},t.aaxis,{visible:!0,range:[x,b-w-M],side:\"left\",_counterangle:30,tickangle:(+t.aaxis.tickangle||0)-30,domain:[k,k+s*_],_axislayer:l.layers.aaxis,_gridlayer:l.layers.agrid,_pos:0,_id:\"y\",_length:i,_gridpath:\"M0,0l\"+a+\",-\"+i/2});h(A,l.graphDiv._fullLayout),A.setScale();var 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C=\"translate(\"+r+\",\"+(n+a)+\")\";l.layers.baxis.attr(\"transform\",C),l.layers.bgrid.attr(\"transform\",C);var z=\"translate(\"+(r+i/2)+\",\"+n+\")rotate(30)\";l.layers.aaxis.attr(\"transform\",z),l.layers.agrid.attr(\"transform\",z);var D=\"translate(\"+(r+i/2)+\",\"+n+\")rotate(-30)\";l.layers.caxis.attr(\"transform\",D),l.layers.cgrid.attr(\"transform\",D),l.drawAxes(!0),l.plotContainer.selectAll(\".crisp\").classed(\"crisp\",!1);var I=l.layers.axlines;I.select(\".aline\").attr(\"d\",A.showline?\"M\"+r+\",\"+(n+a)+\"l\"+i/2+\",-\"+a:\"M0,0\").call(u.stroke,A.linecolor||\"#000\").style(\"stroke-width\",(A.linewidth||0)+\"px\"),I.select(\".bline\").attr(\"d\",T.showline?\"M\"+r+\",\"+(n+a)+\"h\"+i:\"M0,0\").call(u.stroke,T.linecolor||\"#000\").style(\"stroke-width\",(T.linewidth||0)+\"px\"),I.select(\".cline\").attr(\"d\",S.showline?\"M\"+(r+i/2)+\",\"+n+\"l\"+i/2+\",\"+a:\"M0,0\").call(u.stroke,S.linecolor||\"#000\").style(\"stroke-width\",(S.linewidth||0)+\"px\")},x.drawAxes=function(t){var e=this,r=e.graphDiv,n=e.id.substr(7)+\"title\",i=e.aaxis,a=e.baxis,o=e.caxis;if(p.doTicks(r,i,!0),p.doTicks(r,a,!0),p.doTicks(r,o,!0),t){var s=Math.max(i.showticklabels?i.tickfont.size/2:0,(o.showticklabels?.75*o.tickfont.size:0)+(\"outside\"===o.ticks?.87*o.ticklen:0));g.draw(r,\"a\"+n,{propContainer:i,propName:e.id+\".aaxis.title\",dfltName:\"Component 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a=x+t,o=w+i,s=Math.max(0,Math.min(1,e(x,w),e(a,o))),l=Math.max(0,Math.min(1,r(x,w),r(a,o))),u=Math.max(0,Math.min(1,n(x,w),n(a,o))),c=(s/2+u)*j.w,h=(1-s/2-l)*j.w,f=(c+h)/2,d=h-c,p=(1-s)*j.h,m=p-d/_;d<y.MINZOOM?(C=E,P.attr(\"d\",D),O.attr(\"d\",\"M0,0Z\")):(C={a:E.a+s*L,b:E.b+l*L,c:E.c+u*L},P.attr(\"d\",D+\"M\"+c+\",\"+p+\"H\"+h+\"L\"+f+\",\"+m+\"L\"+c+\",\"+p+\"Z\"),O.attr(\"d\",\"M\"+x+\",\"+w+T+\"M\"+c+\",\"+p+M+\"M\"+h+\",\"+p+k+\"M\"+f+\",\"+m+A)),I||(P.transition().style(\"fill\",z>.2?\"rgba(0,0,0,0.4)\":\"rgba(255,255,255,0.3)\").duration(200),O.transition().style(\"opacity\",1).duration(200),I=!0)}function c(t,e){if(C===E)return 2===e&&g(),i(F);i(F);var r={};r[j.id+\".aaxis.min\"]=C.a,r[j.id+\".baxis.min\"]=C.b,r[j.id+\".caxis.min\"]=C.c,s.relayout(F,r),S&&F.data&&F._context.showTips&&(l.notifier(\"Double-click to<br>zoom back out\",\"long\"),S=!1)}function h(){E={a:j.aaxis.range[0],b:j.baxis.range[1],c:j.caxis.range[1]},C=E}function f(t,e){var r=t/j.xaxis._m,n=e/j.yaxis._m,i=[(C={a:E.a-n,b:E.b+(r+n)/2,c:E.c-(r-n)/2}).a,C.b,C.c].sort(),a={a:i.indexOf(C.a),b:i.indexOf(C.b),c:i.indexOf(C.c)};i[0]<0&&(i[1]+i[0]/2<0?(i[2]+=i[0]+i[1],i[0]=i[1]=0):(i[2]+=i[0]/2,i[1]+=i[0]/2,i[0]=0),C={a:i[a.a],b:i[a.b],c:i[a.c]},e=(E.a-C.a)*j.yaxis._m,t=(E.c-C.c-E.b+C.b)*j.xaxis._m);var o=\"translate(\"+(j.x0+t)+\",\"+(j.y0+e)+\")\";j.plotContainer.selectAll(\".scatterlayer,.maplayer\").attr(\"transform\",o),j.aaxis.range=[C.a,j.sum-C.b-C.c],j.baxis.range=[j.sum-C.a-C.c,C.b],j.caxis.range=[j.sum-C.a-C.b,C.c],j.drawAxes(!1),j.plotContainer.selectAll(\".crisp\").classed(\"crisp\",!1)}function d(t,e){if(t){var r={};r[j.id+\".aaxis.min\"]=C.a,r[j.id+\".baxis.min\"]=C.b,r[j.id+\".caxis.min\"]=C.c,s.relayout(F,r)}else 2===e&&g()}function p(){j.plotContainer.selectAll(\".select-outline\").remove()}function g(){var t={};t[j.id+\".aaxis.min\"]=0,t[j.id+\".baxis.min\"]=0,t[j.id+\".caxis.min\"]=0,F.emit(\"plotly_doubleclick\",null),s.relayout(F,t)}var x,w,E,L,C,z,D,I,P,O,j=this,R=j.layers.plotbg.select(\"path\").node(),F=j.graphDiv,N=j.layers.zoom,B={element:R,gd:F,plotinfo:{plot:N},doubleclick:g,subplot:j.id,prepFn:function(e,r,n){B.xaxes=[j.xaxis],B.yaxes=[j.yaxis];var i=F._fullLayout.dragmode;e.shiftKey&&(i=\"pan\"===i?\"zoom\":\"pan\"),B.minDrag=\"lasso\"===i?1:void 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r=t._fullLayout._glimages,i=n.selectAll(\".svg-container\");i.filter(function(t,e){return e===i.size()-1}).selectAll(\".parcoords-lines.context, .parcoords-lines.focus\").each(e),window.setTimeout(function(){n.selectAll(\"#filterBarPattern\").attr(\"id\",\"filterBarPattern\")},60)}},{\"../../constants/xmlns_namespaces\":668,\"../../plots/plots\":787,\"./constants\":954,\"./plot\":959,d3:107}],952:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/has_colorscale\"),i=t(\"../../components/colorscale/calc\"),a=t(\"../../lib\");e.exports=function(t,e){var r=!!e.line.colorscale&&a.isArray(e.line.color),o=r?e.line.color:Array.apply(0,Array(e.dimensions.reduce(function(t,e){return Math.max(t,e.values.length)},0))).map(function(){return.5}),s=r?e.line.colorscale:[[0,e.line.color],[1,e.line.color]];return 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   float show = float(mshow(pA, loA, hiA) &&\\n                       mshow(pB, loB, hiB) &&\\n                       mshow(pC, loC, hiC) &&\\n                       mshow(pD, loD, hiD));\\n\\n    vec2 yy = show * vec2(val(pA, dim2A) + val(pB, dim2B) + val(pC, dim2C) + val(pD, dim2D),\\n                          val(pA, dim1A) + val(pB, dim1B) + val(pC, dim1C) + val(pD, dim1D));\\n\\n    vec2 dimensionToggle = vec2(x, 1.0 - x);\\n\\n    vec2 scatterToggle = vec2(scatter, 1.0 - scatter);\\n\\n    float y = dot(yy, dimensionToggle);\\n    mat2 xy = mat2(viewBoxSize * yy + dimensionToggle, viewBoxSize * vec2(x, y));\\n\\n    vec2 viewBoxXY = viewBoxPosition + xy * scatterToggle;\\n\\n    float depthOrHide = depth + 2.0 * (1.0 - show);\\n\\n    gl_Position = vec4(\\n        xyProjection * (2.0 * viewBoxXY / resolution - 1.0),\\n        depthOrHide,\\n        1.0\\n    );\\n\\n    // visible coloring\\n    float clampedColorIndex = clamp((prominence - colorClamp[0]) / (colorClamp[1] - colorClamp[0]), 0.0, 1.0);\\n    fragColor = texture2D(palette, vec2((clampedColorIndex * 255.0 + 0.5) / 256.0, 0.5));\\n}\\n\",frag:\"precision lowp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n    gl_FragColor = fragColor;\\n}\\n\",primitive:\"lines\",lineWidth:1,attributes:P,uniforms:{resolution:O.prop(\"resolution\"),viewBoxPosition:O.prop(\"viewBoxPosition\"),viewBoxSize:O.prop(\"viewBoxSize\"),dim1A:O.prop(\"dim1A\"),dim2A:O.prop(\"dim2A\"),dim1B:O.prop(\"dim1B\"),dim2B:O.prop(\"dim2B\"),dim1C:O.prop(\"dim1C\"),dim2C:O.prop(\"dim2C\"),dim1D:O.prop(\"dim1D\"),dim2D:O.prop(\"dim2D\"),loA:O.prop(\"loA\"),hiA:O.prop(\"hiA\"),loB:O.prop(\"loB\"),hiB:O.prop(\"hiB\"),loC:O.prop(\"loC\"),hiC:O.prop(\"hiC\"),loD:O.prop(\"loD\"),hiD:O.prop(\"hiD\"),palette:j,colorClamp:O.prop(\"colorClamp\"),scatter:O.prop(\"scatter\")},offset:O.prop(\"offset\"),count:O.prop(\"count\")}),F=[0,1],N=[];return{setColorDomain:y,render:x,readPixel:w,readPixels:M,destroy:O.destroy}}},{\"./constants\":954,regl:480}],958:[function(t,e,r){\"use strict\";function n(t){return t.key}function i(t){return[t]}function a(t){return!(\"visible\"in t)||t.visible}function o(t){var e=t.range?t.range[0]:_.min(t.values),r=t.range?t.range[1]:_.max(t.values);return!isNaN(e)&&isFinite(e)||(e=0),!isNaN(r)&&isFinite(r)||(r=0),e===r&&(void 0===e?(e=0,r=1):0===e?(e-=1,r+=1):(e*=.9,r*=1.1)),[e,r]}function s(t,e){var r,n,i,a,o;for(r=0,i=1/0,a=(n=t.range())[0],o;r<n.length;r++){if((o=Math.abs(n[r]-e))>i)return a;i=o,a=n[r]}return n[n.length-1]}function l(t,e,r){var n=o(r);return r.tickvals?_.scale.ordinal().domain(r.tickvals).range(r.tickvals.map(function(t){return(t-n[0])/(n[1]-n[0])}).map(function(r){return t-e+r*(e-(t-e))})):_.scale.linear().domain(n).range([t-e,e])}function u(t,e){return _.scale.linear().range([t-e,e])}function c(t){return _.scale.linear().domain(o(t))}function h(t){var e=o(t);return t.tickvals&&_.scale.ordinal().domain(t.tickvals).range(t.tickvals.map(function(t){return(t-e[0])/(e[1]-e[0])}))}function f(t){var e=t.map(function(t){return t[0]}),r=t.map(function(t){return t[1]}).map(function(t){return _.rgb(t)}),n=function(t){return function(e){return 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e*r/Math.max(1,t.colCount-1)},s=b.verticalPadding/(r*i),f=1-2*s,d=function(t){return s+f*t},p={key:t.key,xScale:o,model:t},m={};return p.dimensions=n.filter(a).map(function(e,n){var a=c(e),s=m[e.label];return m[e.label]=(s||0)+1,{key:e.label+(s?\"__\"+s:\"\"),label:e.label,tickFormat:e.tickformat,tickvals:e.tickvals,ticktext:e.ticktext,ordinal:!!e.tickvals,scatter:b.scatter||e.scatter,xIndex:n,crossfilterDimensionIndex:n,visibleIndex:e._index,height:r,values:e.values,paddedUnitValues:e.values.map(a).map(d),xScale:o,x:o(n),canvasX:o(n)*i,unitScale:u(r,b.verticalPadding),domainScale:l(r,b.verticalPadding,e),ordinalScale:h(e),domainToUnitScale:a,filter:e.constraintrange?e.constraintrange.map(a):[0,1],parent:p,model:t}}),p}function g(t){return b.layers.map(function(e){return{key:e,context:\"contextLineLayer\"===e,pick:\"pickLineLayer\"===e,viewModel:t,model:t.model}})}function v(t){t.classed(\"axisExtentText\",!0).attr(\"text-anchor\",\"middle\").style(\"font-weight\",100).style(\"font-size\",\"10px\").style(\"cursor\",\"default\").style(\"user-select\",\"none\")}var y=t(\"./lines\"),b=t(\"./constants\"),x=t(\"../../lib\"),_=t(\"d3\");e.exports=function(t,e,r,a,o){function l(t){var e=t.selectAll(\"defs\").data(i,n);e.enter().append(\"defs\");var r=e.selectAll(\"#filterBarPattern\").data(i,n);r.enter().append(\"pattern\").attr(\"id\",\"filterBarPattern\").attr(\"patternUnits\",\"userSpaceOnUse\"),r.attr(\"x\",-b.bar.width).attr(\"width\",b.bar.capturewidth).attr(\"height\",function(t){return t.model.height});var a=r.selectAll(\"rect\").data(i,n);a.enter().append(\"rect\").attr(\"shape-rendering\",\"crispEdges\"),a.attr(\"height\",function(t){return t.model.height}).attr(\"width\",b.bar.width).attr(\"x\",b.bar.width/2).attr(\"fill\",b.bar.fillcolor).attr(\"fill-opacity\",b.bar.fillopacity).attr(\"stroke\",b.bar.strokecolor).attr(\"stroke-opacity\",b.bar.strokeopacity).attr(\"stroke-width\",b.bar.strokewidth)}function u(t){return t.dimensions.some(function(t){return 0!==t.filter[0]||1!==t.filter[1]})}function c(t,e){for(var r=e.panels||(e.panels=[]),n=t.each(function(t){return t})[e.key].map(function(t){return t.__data__}),i=n.length-1,a=0;a<1;a++)for(var o=0;o<i;o++){var s=r[o+a*i]||(r[o+a*i]={}),l=n[o],u=n[o+1];s.dim1=l,s.dim2=u,s.canvasX=l.canvasX,s.panelSizeX=u.canvasX-l.canvasX,s.panelSizeY=e.model.canvasHeight/1,s.y=a*s.panelSizeY,s.canvasY=e.model.canvasHeight-s.y-s.panelSizeY}}function h(t,e){for(var r=e.panels||(e.panels=[]),n=t.each(function(t){return t})[e.key].map(function(t){return t.__data__}),i=n.length-1,a=i,o=0;o<i;o++)for(var s=0;s<i;s++){var l=r[s+o*i]||(r[s+o*i]={}),u=n[s],c=n[s+1];l.dim1=n[o+1],l.dim2=c,l.canvasX=u.canvasX,l.panelSizeX=c.canvasX-u.canvasX,l.panelSizeY=e.model.canvasHeight/a,l.y=o*l.panelSizeY,l.canvasY=e.model.canvasHeight-l.y-l.panelSizeY}}function f(t,e){return(b.scatter?h:c)(t,e)}function x(t){return t.ordinal?function(){return\"\"}:_.format(t.tickFormat)}function w(){Y=!0,A=!0}function M(t){T=!1;var e=t.parent,r=t.brush.extent(),n=e.dimensions,i=n[t.xIndex].filter,a=Y&&r[0]===r[1];a&&(t.brush.clear(),_.select(this).select(\"rect.extent\").attr(\"y\",-100));var o=a?[0,1]:r.slice();if(o[0]!==i[0]||o[1]!==i[1]){n[t.xIndex].filter=o,e.focusLineLayer&&e.focusLineLayer.render(e.panels,!0);var s=u(e);!W&&s?(e.contextLineLayer&&e.contextLineLayer.render(e.panels,!0),W=!0):W&&!s&&(e.contextLineLayer&&e.contextLineLayer.render(e.panels,!0,!0),W=!1)}Y=!1}function k(t){var e=t.parent,r=t.brush.extent(),n=r[0]===r[1],i=e.dimensions[t.xIndex].filter;if(!n&&t.ordinal&&(i[0]=s(t.ordinalScale,i[0]),i[1]=s(t.ordinalScale,i[1]),i[0]===i[1]&&(i[0]=Math.max(0,i[0]-.05),i[1]=Math.min(1,i[1]+.05)),_.select(this).transition().duration(150).call(t.brush.extent(i)),e.focusLineLayer.render(e.panels,!0)),e.pickLineLayer&&e.pickLineLayer.render(e.panels,!0),T=!0,A=\"ending\",o&&o.filterChanged){var a=t.domainToUnitScale.invert,l=i.map(a);o.filterChanged(e.key,t.visibleIndex,l)}}var A=!1,T=!0,S=r.filter(function(t){return d(t).trace.visible}).map(p.bind(0,a)).map(m);t.selectAll(\".parcoords-line-layers\").remove();var E=t.selectAll(\".parcoords-line-layers\").data(S,n);E.enter().insert(\"div\",\".\"+e.attr(\"class\").split(\" \").join(\" .\")).classed(\"parcoords-line-layers\",!0).style(\"box-sizing\",\"content-box\"),E.style(\"transform\",function(t){return\"translate(\"+(t.model.translateX-b.overdrag)+\"px,\"+t.model.translateY+\"px)\"});var L=E.selectAll(\".parcoords-lines\").data(g,n),C={renderers:[],dimensions:[]},z=null;L.enter().append(\"canvas\").attr(\"class\",function(t){return\"parcoords-lines \"+(t.context?\"context\":t.pick?\"pick\":\"focus\")}).style(\"box-sizing\",\"content-box\").style(\"float\",\"left\").style(\"clear\",\"both\").style(\"left\",0).style(\"overflow\",\"visible\").style(\"position\",function(t,e){return\"absolute\"}).filter(function(t){return t.pick}).on(\"mousemove\",function(t){if(T&&t.lineLayer&&o&&o.hover){var e=_.event,r=this.width,n=this.height,i=_.mouse(this),a=i[0],s=i[1];if(a<0||s<0||a>=r||s>=n)return;var l=t.lineLayer.readPixel(a,n-1-s),u=0!==l[3],c=u?l[2]+256*(l[1]+256*l[0]):null,h={x:a,y:s,clientX:e.clientX,clientY:e.clientY,dataIndex:t.model.key,curveNumber:c};c!==z&&(u?o.hover(h):o.unhover&&o.unhover(h),z=c)}}),L.style(\"margin\",function(t){var e=t.model.pad;return e.t+\"px \"+e.r+\"px \"+e.b+\"px \"+e.l+\"px\"}).attr(\"width\",function(t){return t.model.canvasWidth}).attr(\"height\",function(t){return t.model.canvasHeight}).style(\"width\",function(t){return t.model.width+2*b.overdrag+\"px\"}).style(\"height\",function(t){return t.model.height+\"px\"}).style(\"opacity\",function(t){return t.pick?.01:1}),e.style(\"background\",\"rgba(255, 255, 255, 0)\");var D=e.selectAll(\".parcoords\").data(S,n);D.exit().remove(),D.enter().append(\"g\").classed(\"parcoords\",!0).attr(\"overflow\",\"visible\").style(\"box-sizing\",\"content-box\").style(\"position\",\"absolute\").style(\"left\",0).style(\"overflow\",\"visible\").style(\"shape-rendering\",\"crispEdges\").style(\"pointer-events\",\"none\").call(l),D.attr(\"width\",function(t){return t.model.width+t.model.pad.l+t.model.pad.r}).attr(\"height\",function(t){return t.model.height+t.model.pad.t+t.model.pad.b}).attr(\"transform\",function(t){return\"translate(\"+t.model.translateX+\",\"+t.model.translateY+\")\"});var I=D.selectAll(\".parcoordsControlView\").data(i,n);I.enter().append(\"g\").classed(\"parcoordsControlView\",!0).style(\"box-sizing\",\"content-box\"),I.attr(\"transform\",function(t){return\"translate(\"+t.model.pad.l+\",\"+t.model.pad.t+\")\"});var P=I.selectAll(\".yAxis\").data(function(t){return t.dimensions},n);P.enter().append(\"g\").classed(\"yAxis\",!0).each(function(t){C.dimensions.push(t)}),I.each(function(t){f(P,t)}),L.each(function(t){t.lineLayer=y(this,t.model.lines,t.model.canvasWidth,t.model.canvasHeight,t.viewModel.dimensions,t.viewModel.panels,t.model.unitToColor,t.context,t.pick,b.scatter),t.viewModel[t.key]=t.lineLayer,C.renderers.push(function(){t.lineLayer.render(t.viewModel.panels,!0)}),t.lineLayer.render(t.viewModel.panels,!t.context)}),P.attr(\"transform\",function(t){return\"translate(\"+t.xScale(t.xIndex)+\", 0)\"}),P.call(_.behavior.drag().origin(function(t){return t}).on(\"drag\",function(t){var e=t.parent;T=!1,A||(t.x=Math.max(-b.overdrag,Math.min(t.model.width+b.overdrag,_.event.x)),t.canvasX=t.x*t.model.canvasPixelRatio,P.sort(function(t,e){return t.x-e.x}).each(function(e,r){e.xIndex=r,e.x=t===e?e.x:e.xScale(e.xIndex),e.canvasX=e.x*e.model.canvasPixelRatio}),f(P,e),P.filter(function(e){return 0!==Math.abs(t.xIndex-e.xIndex)}).attr(\"transform\",function(t){return\"translate(\"+t.xScale(t.xIndex)+\", 0)\"}),_.select(this).attr(\"transform\",\"translate(\"+t.x+\", 0)\"),P.each(function(r,n,i){i===t.parent.key&&(e.dimensions[n]=r)}),e.contextLineLayer&&e.contextLineLayer.render(e.panels,!1,!u(e)),e.focusLineLayer.render&&e.focusLineLayer.render(e.panels))}).on(\"dragend\",function(t){var e=t.parent;A?\"ending\"===A&&(A=!1):(t.x=t.xScale(t.xIndex),t.canvasX=t.x*t.model.canvasPixelRatio,f(P,e),_.select(this).attr(\"transform\",function(t){return\"translate(\"+t.x+\", 0)\"}),e.contextLineLayer&&e.contextLineLayer.render(e.panels,!1,!u(e)),e.focusLineLayer&&e.focusLineLayer.render(e.panels),e.pickLineLayer&&e.pickLineLayer.render(e.panels,!0),T=!0,o&&o.axesMoved&&o.axesMoved(e.key,e.dimensions.map(function(t){return t.crossfilterDimensionIndex})))})),P.exit().remove();var O=P.selectAll(\".axisOverlays\").data(i,n);O.enter().append(\"g\").classed(\"axisOverlays\",!0),O.selectAll(\".axis\").remove();var j=O.selectAll(\".axis\").data(i,n);j.enter().append(\"g\").classed(\"axis\",!0),j.each(function(t){var e=t.model.height/t.model.tickDistance,r=t.domainScale,n=r.domain(),i=t.ticktext;_.select(this).call(_.svg.axis().orient(\"left\").tickSize(4).outerTickSize(2).ticks(e,t.tickFormat).tickValues(t.ordinal?n.map(function(t,e){return i&&i[e]||t}):null).tickFormat(t.ordinal?function(t){return t}:null).scale(r))}),j.selectAll(\".domain, 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N=O.selectAll(\".axisExtent\").data(i,n);N.enter().append(\"g\").classed(\"axisExtent\",!0);var B=N.selectAll(\".axisExtentTop\").data(i,n);B.enter().append(\"g\").classed(\"axisExtentTop\",!0),B.attr(\"transform\",\"translate(0,\"+-b.axisExtentOffset+\")\");var U=B.selectAll(\".axisExtentTopText\").data(i,n);U.enter().append(\"text\").classed(\"axisExtentTopText\",!0).attr(\"alignment-baseline\",\"after-edge\").call(v),U.text(function(t){return x(t)(t.domainScale.domain().slice(-1)[0])});var V=N.selectAll(\".axisExtentBottom\").data(i,n);V.enter().append(\"g\").classed(\"axisExtentBottom\",!0),V.attr(\"transform\",function(t){return\"translate(0,\"+(t.model.height+b.axisExtentOffset)+\")\"});var H=V.selectAll(\".axisExtentBottomText\").data(i,n);H.enter().append(\"text\").classed(\"axisExtentBottomText\",!0).attr(\"alignment-baseline\",\"before-edge\").call(v),H.text(function(t){return x(t)(t.domainScale.domain()[0])});var q=O.selectAll(\".axisBrush\").data(i,n),G=q.enter().append(\"g\").classed(\"axisBrush\",!0);q.each(function(t){t.brush||(t.brush=_.svg.brush().y(t.unitScale).on(\"brushstart\",w).on(\"brush\",M).on(\"brushend\",k),0===t.filter[0]&&1===t.filter[1]||t.brush.extent(t.filter),_.select(this).call(t.brush))}),G.selectAll(\"rect\").attr(\"x\",-b.bar.capturewidth/2).attr(\"width\",b.bar.capturewidth),G.selectAll(\"rect.extent\").attr(\"fill\",\"url(#filterBarPattern)\").style(\"cursor\",\"ns-resize\").filter(function(t){return 0===t.filter[0]&&1===t.filter[1]}).attr(\"y\",-100),G.selectAll(\".resize rect\").attr(\"height\",b.bar.handleheight).attr(\"opacity\",0).style(\"visibility\",\"visible\"),G.selectAll(\".resize.n rect\").style(\"cursor\",\"n-resize\").attr(\"y\",b.bar.handleoverlap-b.bar.handleheight),G.selectAll(\".resize.s rect\").style(\"cursor\",\"s-resize\").attr(\"y\",b.bar.handleoverlap);var Y=!1,W=!1;return C}},{\"../../lib\":685,\"./constants\":954,\"./lines\":957,d3:107}],959:[function(t,e,r){\"use strict\";var n=t(\"./parcoords\");e.exports=function(t,e){var r=t._fullLayout,i=r._paper,a=r._paperdiv,o={},s={},l=r._size;e.forEach(function(e,r){o[r]=t.data[r].dimensions,s[r]=t.data[r].dimensions.slice()});var u=function(e,r,n){var i=s[e][r],a=i.constraintrange;a&&2===a.length||(a=i.constraintrange=[]),a[0]=n[0],a[1]=n[1],t.emit(\"plotly_restyle\")},c=function(e){t.emit(\"plotly_hover\",e)},h=function(e){t.emit(\"plotly_unhover\",e)},f=function(e,r){function n(t){return!(\"visible\"in t)||t.visible}function i(t,e,r){var n=e.indexOf(r),i=t.indexOf(n);return-1===i&&(i+=e.length),i}var a=function(t){return function(e,n){return i(r,t,e)-i(r,t,n)}}(s[e].filter(n));o[e].sort(a),s[e].filter(function(t){return!n(t)}).sort(function(t){return 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i=r.marker.line.color;Array.isArray(i)&&(i=i[e.i]||n.defaultLine);var a=r.marker.line.width||0;Array.isArray(a)&&(a=a[e.i]||0),t.style({\"stroke-width\":a}).call(n.fill,e.color).call(n.stroke,i)}},{\"../../components/color\":578}],971:[function(t,e,r){\"use strict\";var n=t(\"../scattergl/attributes\");e.exports={x:n.x,y:n.y,xy:{valType:\"data_array\"},indices:{valType:\"data_array\"},xbounds:{valType:\"data_array\"},ybounds:{valType:\"data_array\"},text:n.text,marker:{color:{valType:\"color\",arrayOk:!1},opacity:{valType:\"number\",min:0,max:1,dflt:1,arrayOk:!1},blend:{valType:\"boolean\",dflt:null},sizemin:{valType:\"number\",min:.1,max:2,dflt:.5},sizemax:{valType:\"number\",min:.1,dflt:20},border:{color:{valType:\"color\",arrayOk:!1},arearatio:{valType:\"number\",min:0,max:1,dflt:0}}}}},{\"../scattergl/attributes\":1020}],972:[function(t,e,r){\"use strict\";function n(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=a(t.glplot,this.pointcloudOptions),this.pointcloud._trace=this}function i(t,e){var r=new n(t,e.uid);return r.update(e),r}var a=t(\"gl-pointcloud2d\"),o=t(\"../../lib/str2rgbarray\"),s=t(\"../scatter/get_trace_color\"),l=[\"xaxis\",\"yaxis\"],u=n.prototype;u.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}},u.update=function(t){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=s(t,{})},u.updateFast=function(t){var e,r,n,i,a,s,l=this.xData=this.pickXData=t.x,u=this.yData=this.pickYData=t.y,c=this.pickXYData=t.xy,h=t.xbounds&&t.ybounds,f=t.indices,d=this.bounds;if(c){if(n=c,e=c.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(s=0;s<e;s++)i=n[2*s],a=n[2*s+1],i<d[0]&&(d[0]=i),i>d[2]&&(d[2]=i),a<d[1]&&(d[1]=a),a>d[3]&&(d[3]=a);if(f)r=f;else for(r=new Int32Array(e),s=0;s<e;s++)r[s]=s}else for(e=l.length,n=new Float32Array(2*e),r=new 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r,n,i,a=e||.5,o=0;o<2;o++)(n=(r=this.scene[l[o]])._min)||(n=[]),n.push({val:t[o],pad:a}),(i=r._max)||(i=[]),i.push({val:t[o+2],pad:a})},u.dispose=function(){this.pointcloud.dispose()},e.exports=i},{\"../../lib/str2rgbarray\":703,\"../scatter/get_trace_color\":984,\"gl-pointcloud2d\":214}],973:[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\")}},{\"../../lib\":685,\"./attributes\":971}],974:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.calc=t(\"../scatter3d/calc\"),n.plot=t(\"./convert\"),n.moduleType=\"trace\",n.name=\"pointcloud\",n.basePlotModule=t(\"../../plots/gl2d\"),n.categories=[\"gl2d\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/gl2d\":764,\"../scatter3d/calc\":1e3,\"./attributes\":971,\"./convert\":972,\"./defaults\":973}],975:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e){n.mergeArray(e.text,t,\"tx\"),n.mergeArray(e.hovertext,t,\"htx\"),n.mergeArray(e.customdata,t,\"data\"),n.mergeArray(e.textposition,t,\"tp\"),e.textfont&&(n.mergeArray(e.textfont.size,t,\"ts\"),n.mergeArray(e.textfont.color,t,\"tc\"),n.mergeArray(e.textfont.family,t,\"tf\"));var r=e.marker;if(r){n.mergeArray(r.size,t,\"ms\"),n.mergeArray(r.opacity,t,\"mo\"),n.mergeArray(r.symbol,t,\"mx\"),n.mergeArray(r.color,t,\"mc\");var 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n=t(\"../../components/colorscale/color_attributes\"),i=t(\"../../components/errorbars/attributes\"),a=t(\"../../components/colorbar/attributes\"),o=t(\"../../components/drawing/attributes\").dash,s=t(\"../../components/drawing\"),l=(t(\"./constants\"),t(\"../../lib/extend\").extendFlat);e.exports={x:{valType:\"data_array\"},x0:{valType:\"any\",dflt:0},dx:{valType:\"number\",dflt:1},y:{valType:\"data_array\"},y0:{valType:\"any\",dflt:0},customdata:{valType:\"data_array\"},dy:{valType:\"number\",dflt:1},ids:{valType:\"data_array\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0},mode:{valType:\"flaglist\",flags:[\"lines\",\"markers\",\"text\"],extras:[\"none\"]},hoveron:{valType:\"flaglist\",flags:[\"points\",\"fills\"]},line:{color:{valType:\"color\"},width:{valType:\"number\",min:0,dflt:2},shape:{valType:\"enumerated\",values:[\"linear\",\"spline\",\"hv\",\"vh\",\"hvh\",\"vhv\"],dflt:\"linear\"},smoothing:{valType:\"number\",min:0,max:1.3,dflt:1},dash:o,simplify:{valType:\"boolean\",dflt:!0}},connectgaps:{valType:\"boolean\",dflt:!1},fill:{valType:\"enumerated\",values:[\"none\",\"tozeroy\",\"tozerox\",\"tonexty\",\"tonextx\",\"toself\",\"tonext\"],dflt:\"none\"},fillcolor:{valType:\"color\"},marker:l({},{symbol:{valType:\"enumerated\",values:s.symbolList,dflt:\"circle\",arrayOk:!0},opacity:{valType:\"number\",min:0,max:1,arrayOk:!0},size:{valType:\"number\",min:0,dflt:6,arrayOk:!0},maxdisplayed:{valType:\"number\",min:0,dflt:0},sizeref:{valType:\"number\",dflt:1},sizemin:{valType:\"number\",min:0,dflt:0},sizemode:{valType:\"enumerated\",values:[\"diameter\",\"area\"],dflt:\"diameter\"},showscale:{valType:\"boolean\",dflt:!1},colorbar:a,line:l({},{width:{valType:\"number\",min:0,arrayOk:!0}},n(\"marker.line\"))},n(\"marker\")),textposition:{valType:\"enumerated\",values:[\"top 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r,l,u,c=i.getFromId(t,e.xaxis||\"x\"),h=i.getFromId(t,e.yaxis||\"y\"),f=c.makeCalcdata(e,\"x\"),d=h.makeCalcdata(e,\"y\"),p=Math.min(f.length,d.length);c._minDtick=0,h._minDtick=0,f.length>p&&f.splice(p,f.length-p),d.length>p&&d.splice(p,d.length-p);var m={padded:!0},g={padded:!0};if(a.hasMarkers(e)){if(r=e.marker,l=r.size,Array.isArray(l)){var v={type:\"linear\"};i.setConvert(v),(l=v.makeCalcdata(e.marker,\"size\")).length>p&&l.splice(p,l.length-p)}var y,b=1.6*(e.marker.sizeref||1);y=\"area\"===e.marker.sizemode?function(t){return Math.max(Math.sqrt((t||0)/b),3)}:function(t){return Math.max((t||0)/b,3)},m.ppad=g.ppad=Array.isArray(l)?l.map(y):y(l)}o(e),!(\"tozerox\"===e.fill||\"tonextx\"===e.fill&&t.firstscatter)||f[0]===f[p-1]&&d[0]===d[p-1]?e.error_y.visible||-1===[\"tonexty\",\"tozeroy\"].indexOf(e.fill)&&(a.hasMarkers(e)||a.hasText(e))||(m.padded=!1,m.ppad=0):m.tozero=!0,!(\"tozeroy\"===e.fill||\"tonexty\"===e.fill&&t.firstscatter)||f[0]===f[p-1]&&d[0]===d[p-1]?-1!==[\"tonextx\",\"tozerox\"].indexOf(e.fill)&&(g.padded=!1):g.tozero=!0,i.expand(c,f,m),i.expand(h,d,g);var x=new Array(p);for(u=0;u<p;u++)x[u]=n(f[u])&&n(d[u])?{x:f[u],y:d[u]}:{x:!1,y:!1},e.ids&&(x[u].id=String(e.ids[u]));return s(x,e),t.firstscatter=!1,x}},{\"../../plots/cartesian/axes\":724,\"./arrays_to_calcdata\":975,\"./colorscale_calc\":980,\"./subtypes\":996,\"fast-isnumeric\":116}],978:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=0;e<t.length;e++){var r=t[e];if(\"scatter\"===r.type){var n=r.fill;if(\"none\"!==n&&\"toself\"!==n&&(r.opacity=void 0,\"tonexty\"===n||\"tonextx\"===n))for(var i=e-1;i>=0;i--){var a=t[i];if(\"scatter\"===a.type&&a.xaxis===r.xaxis&&a.yaxis===r.yaxis){a.opacity=void 0;break}}}}}},{}],979:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib\"),a=t(\"../../plots/plots\"),o=t(\"../../components/colorscale\"),s=t(\"../../components/colorbar/draw\");e.exports=function(t,e){var r=e[0].trace,l=r.marker,u=\"cb\"+r.uid;if(t._fullLayout._infolayer.selectAll(\".\"+u).remove(),void 0!==l&&l.showscale){var c=l.color,h=l.cmin,f=l.cmax;n(h)||(h=i.aggNums(Math.min,null,c)),n(f)||(f=i.aggNums(Math.max,null,c));var d=e[0].t.cb=s(t,u),p=o.makeColorScaleFunc(o.extractScale(l.colorscale,h,f),{noNumericCheck:!0});d.fillcolor(p).filllevels({start:h,end:f,size:(f-h)/254}).options(l.colorbar)()}else a.autoMargin(t,u)}},{\"../../components/colorbar/draw\":581,\"../../components/colorscale\":592,\"../../lib\":685,\"../../plots/plots\":787,\"fast-isnumeric\":116}],980:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/has_colorscale\"),i=t(\"../../components/colorscale/calc\"),a=t(\"./subtypes\");e.exports=function(t){a.hasLines(t)&&n(t,\"line\")&&i(t,t.line.color,\"line\",\"c\"),a.hasMarkers(t)&&(n(t,\"marker\")&&i(t,t.marker.color,\"marker\",\"c\"),n(t,\"marker.line\")&&i(t,t.marker.line.color,\"marker.line\",\"c\"))}},{\"../../components/colorscale/calc\":584,\"../../components/colorscale/has_colorscale\":591,\"./subtypes\":996}],981:[function(t,e,r){\"use strict\";e.exports={PTS_LINESONLY:20}},{}],982:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./attributes\"),a=t(\"./constants\"),o=t(\"./subtypes\"),s=t(\"./xy_defaults\"),l=t(\"./marker_defaults\"),u=t(\"./line_defaults\"),c=t(\"./line_shape_defaults\"),h=t(\"./text_defaults\"),f=t(\"./fillcolor_defaults\"),d=t(\"../../components/errorbars/defaults\");e.exports=function(t,e,r,p){function m(r,a){return n.coerce(t,e,i,r,a)}var g=s(t,e,p,m),v=g<a.PTS_LINESONLY?\"lines+markers\":\"lines\";if(g){m(\"customdata\"),m(\"text\"),m(\"hovertext\"),m(\"mode\",v),m(\"ids\"),o.hasLines(e)&&(u(t,e,r,p,m),c(t,e,m),m(\"connectgaps\"),m(\"line.simplify\")),o.hasMarkers(e)&&l(t,e,r,p,m),o.hasText(e)&&h(t,e,p,m);var y=[];(o.hasMarkers(e)||o.hasText(e))&&(m(\"marker.maxdisplayed\"),y.push(\"points\")),m(\"fill\"),\"none\"!==e.fill&&(f(t,e,r,m),o.hasLines(e)||c(t,e,m)),\"tonext\"!==e.fill&&\"toself\"!==e.fill||y.push(\"fills\"),m(\"hoveron\",y.join(\"+\")||\"points\"),d(t,e,r,{axis:\"y\"}),d(t,e,r,{axis:\"x\",inherit:\"y\"})}else e.visible=!1}},{\"../../components/errorbars/defaults\":607,\"../../lib\":685,\"./attributes\":976,\"./constants\":981,\"./fillcolor_defaults\":983,\"./line_defaults\":987,\"./line_shape_defaults\":989,\"./marker_defaults\":992,\"./subtypes\":996,\"./text_defaults\":997,\"./xy_defaults\":998}],983:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\");e.exports=function(t,e,r,i){var a=!1;if(e.marker){var o=e.marker.color,s=(e.marker.line||{}).color;o&&!Array.isArray(o)?a=o:s&&!Array.isArray(s)&&(a=s)}i(\"fillcolor\",n.addOpacity((e.line||{}).color||a||r,.5))}},{\"../../components/color\":578}],984:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),i=t(\"./subtypes\");e.exports=function(t,e){var r,a;if(\"lines\"===t.mode)return r=t.line.color,r&&n.opacity(r)?r:t.fillcolor;if(\"none\"===t.mode)return t.fill?t.fillcolor:\"\";var o=e.mcc||(t.marker||{}).color,s=e.mlcc||((t.marker||{}).line||{}).color;return a=o&&n.opacity(o)?o:s&&n.opacity(s)&&(e.mlw||((t.marker||{}).line||{}).width)?s:\"\",a?n.opacity(a)<.3?n.addOpacity(a,.3):a:(r=(t.line||{}).color,r&&n.opacity(r)&&i.hasLines(t)&&t.line.width?r:t.fillcolor)}},{\"../../components/color\":578,\"./subtypes\":996}],985:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../plots/cartesian/graph_interact\"),a=t(\"../../plots/cartesian/constants\"),o=t(\"../../components/errorbars\"),s=t(\"./get_trace_color\"),l=t(\"../../components/color\");e.exports=function(t,e,r,u){var c=t.cd,h=c[0].trace,f=t.xa,d=t.ya,p=f.c2p(e),m=d.c2p(r),g=[p,m];if(-1!==h.hoveron.indexOf(\"points\")){var v=function(t){var e=Math.max(3,t.mrc||0);return Math.max(Math.abs(f.c2p(t.x)-p)-e,1-3/e)},y=function(t){var e=Math.max(3,t.mrc||0);return Math.max(Math.abs(d.c2p(t.y)-m)-e,1-3/e)},b=function(t){var e=Math.max(3,t.mrc||0),r=f.c2p(t.x)-p,n=d.c2p(t.y)-m;return Math.max(Math.sqrt(r*r+n*n)-e,1-3/e)},x=i.getDistanceFunction(u,v,y,b);if(i.getClosest(c,x,t),!1!==t.index){var _=c[t.index],w=f.c2p(_.x,!0),M=d.c2p(_.y,!0),k=_.mrc||1;return 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v=\"projection.\"+m[g];f(v+\".show\")&&(f(v+\".opacity\"),f(v+\".scale\"))}c(t,e,r,{axis:\"z\"}),c(t,e,r,{axis:\"y\",inherit:\"z\"}),c(t,e,r,{axis:\"x\",inherit:\"z\"})}else e.visible=!1}},{\"../../components/errorbars/defaults\":607,\"../../lib\":685,\"../../registry\":802,\"../scatter/line_defaults\":987,\"../scatter/marker_defaults\":992,\"../scatter/subtypes\":996,\"../scatter/text_defaults\":997,\"./attributes\":999}],1004:[function(t,e,r){\"use strict\";var n={};n.plot=t(\"./convert\"),n.attributes=t(\"./attributes\"),n.markerSymbols=t(\"../../constants/gl_markers\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.moduleType=\"trace\",n.name=\"scatter3d\",n.basePlotModule=t(\"../../plots/gl3d\"),n.categories=[\"gl3d\",\"symbols\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../constants/gl_markers\":664,\"../../plots/gl3d\":767,\"../scatter/colorbar\":979,\"./attributes\":999,\"./calc\":1e3,\"./convert\":1002,\"./defaults\":1003}],1005:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../components/colorscale/color_attributes\"),o=t(\"../../components/colorbar/attributes\"),s=t(\"../../lib/extend\").extendFlat,l=n.marker,u=n.line,c=l.line;e.exports={carpet:{valType:\"string\"},a:{valType:\"data_array\"},b:{valType:\"data_array\"},sum:{valType:\"number\",dflt:0,min:0},mode:s({},n.mode,{dflt:\"markers\"}),text:s({},n.text,{}),line:{color:u.color,width:u.width,dash:u.dash,shape:s({},u.shape,{values:[\"linear\",\"spline\"]}),smoothing:u.smoothing},connectgaps:n.connectgaps,fill:s({},n.fill,{values:[\"none\",\"toself\",\"tonext\"]}),fillcolor:n.fillcolor,marker:s({},{symbol:l.symbol,opacity:l.opacity,maxdisplayed:l.maxdisplayed,size:l.size,sizeref:l.sizeref,sizemin:l.sizemin,sizemode:l.sizemode,line:s({},{width:c.width},a(\"marker\".line))},a(\"marker\"),{showscale:l.showscale,colorbar:o}),textfont:n.textfont,textposition:n.textposition,hoverinfo:s({},i.hoverinfo,{flags:[\"a\",\"b\",\"c\",\"text\",\"name\"]}),hoveron:n.hoveron}},{\"../../components/colorbar/attributes\":579,\"../../components/colorscale/color_attributes\":585,\"../../lib/extend\":677,\"../../plots/attributes\":722,\"../scatter/attributes\":976}],1006:[function(t,e,r){\"use 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v=[];(a.hasMarkers(e)||a.hasText(e))&&(d(\"marker.maxdisplayed\"),v.push(\"points\")),d(\"fill\"),\"none\"!==e.fill&&(c(t,e,r,d),a.hasLines(e)||l(t,e,d)),d(\"hoverinfo\",1===f._dataLength?\"a+b+text\":void 0),\"tonext\"!==e.fill&&\"toself\"!==e.fill||v.push(\"fills\"),d(\"hoveron\",v.join(\"+\")||\"points\")}else e.visible=!1}},{\"../../lib\":685,\"../scatter/constants\":981,\"../scatter/fillcolor_defaults\":983,\"../scatter/line_defaults\":987,\"../scatter/line_shape_defaults\":989,\"../scatter/marker_defaults\":992,\"../scatter/subtypes\":996,\"../scatter/text_defaults\":997,\"./attributes\":1005}],1008:[function(t,e,r){\"use strict\";var n=t(\"../scatter/hover\");e.exports=function(t,e,r,i){function a(t,e){g.push((t.labelprefix&&t.labelprefix.length>0?t.labelprefix:t._hovertitle+\": \")+e.toFixed(3)+t.labelsuffix)}var o=n(t,e,r,i);if(o&&!1!==o[0].index){var s=o[0];if(void 0===s.index){var l=1-s.y0/t.ya._length,u=t.xa._length,c=u*l/2,h=u-c;return s.x0=Math.max(Math.min(s.x0,h),c),s.x1=Math.max(Math.min(s.x1,h),c),o}var f=s.cd[s.index];s.a=f.a,s.b=f.b,s.xLabelVal=void 0,s.yLabelVal=void 0;var d=s.trace,p=d._carpet,m=d.hoverinfo.split(\"+\"),g=[];-1!==m.indexOf(\"all\")&&(m=[\"a\",\"b\"]),-1!==m.indexOf(\"a\")&&a(p.aaxis,f.a),-1!==m.indexOf(\"b\")&&a(p.baxis,f.b);var v=p.ab2ij([f.a,f.b]),y=Math.floor(v[0]),b=v[0]-y,x=Math.floor(v[1]),_=v[1]-x,w=p.evalxy([],y,x,b,_);return g.push(\"y: \"+w[1].toFixed(3)),s.extraText=g.join(\"<br>\"),o}}},{\"../scatter/hover\":985}],1009:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.plot=t(\"./plot\"),n.style=t(\"./style\"),n.hoverPoints=t(\"./hover\"),n.selectPoints=t(\"./select\"),n.moduleType=\"trace\",n.name=\"scattercarpet\",n.basePlotModule=t(\"../../plots/cartesian\"),n.categories=[\"carpet\",\"symbols\",\"markerColorscale\",\"showLegend\",\"carpetDependent\"],n.meta={},e.exports=n},{\"../../plots/cartesian\":734,\"../scatter/colorbar\":979,\"./attributes\":1005,\"./calc\":1006,\"./defaults\":1007,\"./hover\":1008,\"./plot\":1010,\"./select\":1011,\"./style\":1012}],1010:[function(t,e,r){\"use strict\";var n=t(\"../scatter/plot\"),i=t(\"../../plots/cartesian/axes\");e.exports=function(t,e,r){var a,o,s=r[0][0].carpet,l={xaxis:i.getFromId(t,s.xaxis||\"x\"),yaxis:i.getFromId(t,s.yaxis||\"y\"),plot:e.plot};for(n(l.graphDiv,l,r),a=0;a<r.length;a++)o=r[a][0].trace,l.plot.selectAll(\"g.trace\"+o.uid+\" .js-line\").attr(\"clip-path\",\"url(#clip\"+s.uid+\"carpet)\")}},{\"../../plots/cartesian/axes\":724,\"../scatter/plot\":993}],1011:[function(t,e,r){\"use strict\";var n=t(\"../scatter/select\");e.exports=function(t,e){var r=n(t,e);if(r){var i,a,o,s=t.cd;for(o=0;o<r.length;o++)a=s[(i=r[o]).pointNumber],i.a=a.a,i.b=a.b,i.c=a.c,delete i.x,delete i.y;return r}}},{\"../scatter/select\":994}],1012:[function(t,e,r){\"use strict\";var n=t(\"../scatter/style\");e.exports=function(t){for(var e=t._fullLayout._modules,r=0;r<e.length;r++)if(\"scatter\"===e[r].name)return;n(t)}},{\"../scatter/style\":995}],1013:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../components/colorscale/color_attributes\"),o=t(\"../../components/drawing/attributes\").dash,s=t(\"../../lib/extend\").extendFlat,l=n.marker,u=n.line,c=l.line;e.exports={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(\"fast-isnumeric\"),i=t(\"../../constants/numerical\").BADNUM,a=t(\"../scatter/colorscale_calc\"),o=t(\"../scatter/arrays_to_calcdata\");e.exports=function(t,e){for(var r=Array.isArray(e.locations),s=r?e.locations.length:e.lon.length,l=new Array(s),u=0;u<s;u++){var c=l[u]={};if(r){var h=e.locations[u];c.loc=\"string\"==typeof h?h:null}else{var f=e.lon[u],d=e.lat[u];n(f)&&n(d)?c.lonlat=[+f,+d]:c.lonlat=[i,i]}}return o(l,e),a(e),l}},{\"../../constants/numerical\":666,\"../scatter/arrays_to_calcdata\":975,\"../scatter/colorscale_calc\":980,\"fast-isnumeric\":116}],1015:[function(t,e,r){\"use strict\";function n(t,e,r){var n,i,a=0,o=r(\"locations\");return o?(r(\"locationmode\"),a=o.length):(n=r(\"lon\")||[],i=r(\"lat\")||[],(a=Math.min(n.length,i.length))<n.length&&(e.lon=n.slice(0,a)),a<i.length&&(e.lat=i.slice(0,a)),a)}var i=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,h){function f(r,n){return i.coerce(t,e,c,r,n)}n(t,e,f)?(f(\"text\"),f(\"hovertext\"),f(\"mode\"),a.hasLines(e)&&(s(t,e,r,h,f),f(\"connectgaps\")),a.hasMarkers(e)&&o(t,e,r,h,f),a.hasText(e)&&l(t,e,h,f),f(\"fill\"),\"none\"!==e.fill&&u(t,e,r,f),f(\"hoverinfo\",1===h._dataLength?\"lon+lat+location+text\":void 0)):e.visible=!1}},{\"../../lib\":685,\"../scatter/fillcolor_defaults\":983,\"../scatter/line_defaults\":987,\"../scatter/marker_defaults\":992,\"../scatter/subtypes\":996,\"../scatter/text_defaults\":997,\"./attributes\":1013}],1016:[function(t,e,r){\"use strict\";e.exports=function(t,e){return t.lon=e.lon,t.lat=e.lat,t.location=e.lon?e.lon:null,t}},{}],1017:[function(t,e,r){\"use strict\";function n(t,e,r){function n(t){return 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Math.max(Math.sqrt(s*s+l*l)-f,1-3/f)}var a=t.cd,l=a[0].trace,u=t.xa,c=t.ya,h=t.subplot;if(i.getClosest(a,r,t),!1!==t.index){var f=a[t.index],d=f.lonlat,p=e(d),m=f.mrc||1;return t.x0=p[0]-m,t.x1=p[0]+m,t.y0=p[1]-m,t.y1=p[1]+m,t.loc=f.loc,t.lat=d[0],t.lon=d[1],t.color=s(l,f),t.extraText=n(l,f,h.mockAxis),[t]}}},{\"../../constants/numerical\":666,\"../../plots/cartesian/axes\":724,\"../../plots/cartesian/graph_interact\":733,\"../scatter/get_trace_color\":984,\"./attributes\":1013}],1018:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.plot=t(\"./plot\"),n.hoverPoints=t(\"./hover\"),n.eventData=t(\"./event_data\"),n.moduleType=\"trace\",n.name=\"scattergeo\",n.basePlotModule=t(\"../../plots/geo\"),n.categories=[\"geo\",\"symbols\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/geo\":752,\"../scatter/colorbar\":979,\"./attributes\":1013,\"./calc\":1014,\"./defaults\":1015,\"./event_data\":1016,\"./hover\":1017,\"./plot\":1019}],1019:[function(t,e,r){\"use strict\";function n(t,e){var r=t[0].trace;if(Array.isArray(r.locations))for(var n=c(r,e),i=r.locationmode,a=0;a<t.length;a++){var o=t[a],s=h(i,o.loc,n);o.lonlat=s?s.properties.ct:[u,u]}}function i(t){var e=t.framework.selectAll(\"g.trace.scattergeo\");e.style(\"opacity\",function(t){return t[0].trace.opacity}),e.each(function(t){var e=t[0].trace,r=a.select(this);r.selectAll(\"path.point\").call(o.pointStyle,e),r.selectAll(\"text\").call(o.textPointStyle,e)}),e.selectAll(\"path.js-line\").style(\"fill\",\"none\").each(function(t){var e=a.select(this),r=t.trace,n=r.line||{};e.call(s.stroke,n.color).call(o.dashLine,n.dash||\"\",n.width||0),\"none\"!==r.fill&&e.call(s.fill,r.fillcolor)})}var a=t(\"d3\"),o=t(\"../../components/drawing\"),s=t(\"../../components/color\"),l=t(\"../../lib\"),u=t(\"../../constants/numerical\").BADNUM,c=t(\"../../lib/topojson_utils\").getTopojsonFeatures,h=t(\"../../lib/geo_location_utils\").locationToFeature,f=t(\"../../lib/geojson_utils\"),d=t(\"../scatter/subtypes\");e.exports=function(t,e){function r(t){return t[0].trace.uid}function o(t,e){t.lonlat[0]===u&&a.select(e).remove()}for(var s=0;s<e.length;s++)n(e[s],t.topojson);var c=t.framework.select(\".scattergeolayer\").selectAll(\"g.trace.scattergeo\").data(e,r);c.enter().append(\"g\").attr(\"class\",\"trace 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n=t(\"../scatter/attributes\"),i=t(\"../../components/colorscale/color_attributes\"),a=t(\"../../constants/gl2d_dashes\"),o=t(\"../../constants/gl_markers\"),s=t(\"../../lib/extend\").extendFlat,l=t(\"../../lib/extend\").extendDeep,u=n.line,c=n.marker,h=c.line;e.exports={x:n.x,x0:n.x0,dx:n.dx,y:n.y,y0:n.y0,dy:n.dy,text:s({},n.text,{}),mode:{valType:\"flaglist\",flags:[\"lines\",\"markers\"],extras:[\"none\"]},line:{color:u.color,width:u.width,dash:{valType:\"enumerated\",values:Object.keys(a),dflt:\"solid\"}},marker:l({},i(\"marker\"),{symbol:{valType:\"enumerated\",values:Object.keys(o),dflt:\"circle\",arrayOk:!0},size:c.size,sizeref:c.sizeref,sizemin:c.sizemin,sizemode:c.sizemode,opacity:c.opacity,showscale:c.showscale,colorbar:c.colorbar,line:l({},i(\"marker.line\"),{width:h.width})}),connectgaps:n.connectgaps,fill:s({},n.fill,{values:[\"none\",\"tozeroy\",\"tozerox\"]}),fillcolor:n.fillcolor,error_y:n.error_y,error_x:n.error_x}},{\"../../components/colorscale/color_attributes\":585,\"../../constants/gl2d_dashes\":662,\"../../constants/gl_markers\":664,\"../../lib/extend\":677,\"../scatter/attributes\":976}],1021:[function(t,e,r){\"use 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n=t(\"../scatter/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../components/colorscale/color_attributes\"),o=t(\"../../components/colorbar/attributes\"),s=t(\"../../components/drawing/attributes\").dash,l=t(\"../../lib/extend\").extendFlat,u=n.marker,c=n.line,h=u.line;e.exports={a:{valType:\"data_array\"},b:{valType:\"data_array\"},c:{valType:\"data_array\"},sum:{valType:\"number\",dflt:0,min:0},mode:l({},n.mode,{dflt:\"markers\"}),text:l({},n.text,{}),hovertext:l({},n.hovertext,{}),line:{color:c.color,width:c.width,dash:s,shape:l({},c.shape,{values:[\"linear\",\"spline\"]}),smoothing:c.smoothing},connectgaps:n.connectgaps,fill:l({},n.fill,{values:[\"none\",\"toself\",\"tonext\"]}),fillcolor:n.fillcolor,marker:l({},{symbol:u.symbol,opacity:u.opacity,maxdisplayed:u.maxdisplayed,size:u.size,sizeref:u.sizeref,sizemin:u.sizemin,sizemode:u.sizemode,line:l({},{width:h.width},a(\"marker\".line))},a(\"marker\"),{showscale:u.showscale,colorbar:o}),textfont:n.textfont,textposition:n.textposition,hoverinfo:l({},i.hoverinfo,{flags:[\"a\",\"b\",\"c\",\"text\",\"name\"]}),hoveron:n.hoveron}},{\"../../components/colorbar/attributes\":579,\"../../components/colorscale/color_attributes\":585,\"../../components/drawing/attributes\":601,\"../../lib/extend\":677,\"../../plots/attributes\":722,\"../scatter/attributes\":976}],1032:[function(t,e,r){\"use 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       "     }, \"Creating Plot 10ed7b2d-49b7-4777-92e4-e0dee591a83c\" );\n",
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       "switchmap_plot_3857[ [] ] = 'plot_3857_0';\n",
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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<pygsti.report.workspaceplots.ColorBoxPlot at 0x1102b4898>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a boxplot of the maximum power in the power spectra for each sequence.\n",
    "w.ColorBoxPlot('driftpwr', gssList[-1], None, None, driftresults = results_gst)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "** Constructing estimates of the drifting probabilities **\n",
    "\n",
    "The analysis creates estimates of the time-dependent probability, $p(t)$, to obtain a given outcome, for each sequence. Below, we will explain how to access and plot all of these estimates. Here, we demonstrate how to plot the estimated $p(t)$ that the analysis concludes is \"the most drifty\" (the $p(t)$ where the estimated drift has the highest power). Obviously, the more this function oscillates, the more drifty the data for this sequence appears to be."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
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    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
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1PK0Zu5znxhpH49V3r/rZmrGmrbfF6//bcqyJdf+WXi+onJNo/+slP8br89pa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\nVQAVRVEURVEURVHihP8P8vzrmKp8FwAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1102b42e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results_gst.plot_most_drifty_probability(plot_data=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "It can also be informative to display multiple reconstructions on a single plot. Below we plot the reconstructions for the $G_i$ and $G_x$ germs, both with varying germ power and fixed fudicials."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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5c2ejD+bDhg1jwoQJGIZRx4MTCASYOnXqCWn8nUw01P9NcSKcn82bN3PppZcy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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fdf7470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Pick a list of sequence labels (here gatestrings) or indices to plot the estimated p(t) for\n",
    "gstrs = [pygsti.objects.GateString(None,'Gx(Gi)^'+str(2**l)+'Gy') for l in range(4,10)]\n",
    "# Hand this list to the plotting function\n",
    "results_gst.plot_multi_estimated_probabilities(gstrs,loc='upper right')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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WFrJ69WrKysoc73ey+W233UZSUhJ5eXlMmjSpjozzzjuPTZs2sX37doqLi1m/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\neUb03xyfAjwg5MxGfjXDEGbrdcMwz7Ag45TzeJDBX9GFIaQ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OsxQrJ48HnvNMyT5+OTwQ\nZOu5LcxcHYTTY/BnadmsghgPsm9JZMev6MKQjjjtomw9GxwTZevJ4FhKkAXnMZzHA5HTTn8ne+ZX\nNM94PGCcCQ/cEmXr6TPUfLY+msy+TnByCrL1XiSdnGeibD25Bd9sw+OMtco7EyIM550eD8fKY+dC\nXOkYHoiyc+yaKAw2kvNd6Kgy64QHhosuEPLKVJJzQBTIZoNj9jqRbVs5K+cPwgNmbacJNE9MWTIr\nJNCcM8G2wfwuIume2bnsTo9oSzPXhofTI9rN4yUnn52jv885E1wbAqeHc97c5RRl5zjHihezHdnQ\n7PrNyGa3KXB6mH5wNmN+FznUXBaRaaQ9jiqnT9ZmHW6Da4JzMrkgCDl+4ZJlJG/HVcS7XtxKRy+B\ncYokST5JkiLsvx9a3//XwoIve2EIeXYJEJMcemsPT3JY4BQ5TvT2TQHJSWUnOSlmy4boDIonyWEW\nZdGFISyR4ghIUmM+n93BFhF9dlsu7wwz+hREL7yd4czztGALEptlFF0Ywm5F5XXB24wEJTarILIZ\nu83Ua1EWRXLIAEbqB5Ac1oaiCwLYLbccyRGNLQZv2LGVLVMpIjnc2BKQMdbJ5PXJ950F2wSLB2wA\nI0k/Z+cZN36F+vSqg+4re2EIG1gRZev57W3Z2xA6/l544DG2+OCYAA86SNLZC0PIs0tu/SDlEGXr\nRXKydudxy91pB/hsvTA4lmX8irJzrGMlcpy4OrzWGiZbz2GjYPxyY4vDAxa3+EAgaTPR7ZmkTUQ3\nX/Ny8usqqws2cCUKELPbs8jgmOhiNHZrOxu4YoNOogtvKCdTsH2YHZ+i8Uo5w17jQrArpjUlslk2\nfsCfpfXKzrE2dgg0+RnPDIqA6DN44J2do+vjnEwBSc/mfImSK6ycor4b1O8d35LIOr9COThnN7uc\nnNwiRzZLHaI2+DoETrfQ6RHXYYB3nNjAgNixotvzclQ13WtsZR8XouycSJ/Z7S7QZzv0SxbRMZNs\npaMvgpckSbpFkqR9ANIA2gT//iuFXexSDKixlyMkBRkUjjC3g+RwwMmQSq+sAbtIsFtqxGfnMm2Y\nJIddiLKTSPbskujCG24hSrIEsB1OJneRTPY22Jdts1kF0XX+rBxtjM04IiV4bxe/2DFEirMJu9WH\nzTKKnOHMZ0ySk12/SQF5SDAZKZbksLqIKjTJ4bKhIifTk+SwDjUtJ5tVEJEcbusvo1+WrAnnGXuZ\nkgdJT6o6vVeezSoIxi8plyGQm8+0i2yWPTvHB67ovrLZJWHQifiM6MIQPjOhM1tP+OAYhwdsAEih\n9csHx3Ru4Weddq/sHGsT8uyS3Y9sjgDAj3keG/m5So8t7+AYOz55bMweEFJ1A8m0B74K5ioVwFD5\ns+AcHrBZcSGuZQ8McAEMbocFLSd5sY9dB7+NlF1nWZsxczmtckSJC2i2MzvnfJ9pU7TbhNSnbtDb\n6QFxoIUdnx2VM56mMVyYwc7iqKYE53Vj7PhlHH8uOCaYZ/yWRFoGUfYjG/k1BI6CV2aNJeUiZ8Nr\n6ySLpQZbKRhnQrAJz8vpEWcZ3ftmGDyxF9VB/oXP3mU/qyiuk34udHoYxypbPwCAdYtYJ7xdjqrH\nOPghjqqor55tsA4eEwTxroOrguPl2eaI/Xu2c4Vu7yd1Kx3NAF4H4FYAf4OZc7wXwD0AvgdwEMBV\nHazv31ZYAh1Pa5RBOhqhBviFSQTwZBUscIquimbbSKnZ5RSRSraO9mTnyDrYKK1oKxVLpMy+Zj7D\nOVaqxg1eso60biCdzk74zItksjwXbKHjzxFmJz2mI0CCg8E5gByREtmd6K1wa7CHnDzJ4TOVpNnT\nmg6FWGXFC3/2aDEXoRaMLfpmK/COqiBrQFYhJr+MnEoHxy/jvJnfYS4M4cgvS3LovoqcIjUL+RX+\nzgUwPPBAFeEBXSeLBzxe6M57f9zk4vUpIHzZgmMeN18Ctt3dHVWvzHBaM/iAkHCekf3wDgyw+uTn\nHY+vLB4kGEfVCxtZ50y0fZOfA9mDjdxaw8wzRWWzjNkDA85niEpEgRZ2npF1aIbBBRs5fOXwgHWs\nNBgdxHA2m88GnQA+iNee4xvZHCuvy39MOb0DxGQN7MU+ol0zbBspBj/FOzDcx6cBcEcB+HWAXs+E\nwTEPx4klpuyc+SHZOS8nUphlZNvwcHK8MoCcY6V7y+nlhIoSNF5OjldGlfWBhG2I+krarIP6NNAO\nfXo6naJxkb3vQoc7i5xeWUZhm4Iso5cTKcoqkoUdF6Itt2zxHL/MH0SB12ylow7glQB+D+BP1u/v\nGIZxN4DTAOwG0M/ti//pYoNeyG92yW0hcp6ndW4hsolT0PpMTBGfI3LqYLOMVpsBWYIEk+QkuQsZ\naDlYg9mLckZO8c1rpJxuW+jIOsgaYoLnbtlQR06GxPBt8Nu1bPIbtF5+GeOi3IxNVDq+JpLTLUJt\n64IjpkwdrNNuZxVknwTZJ0EzgGRa3AalT2pRTjP90LhbzeIdtBnrnHG6ELyQnpOTcZxEY4tzrNK0\nnLGU+EIRN5tEBc85As2OrbTYOXOT084ySjDnmgHBJTqcPmmHWtQPLzxwc6zIOUKOX8fm1vhXVJ3L\nqPJyZMcDUVApwckpJunk2KHxgB/fbtukKTnJNgRyspFKDg8YfOXaUNk50H45HV2k24GNRBXmFnzA\n75Pgk6yxlhZn1kJOG/Q8E7XBZxk9bCYanx7j121HAL3WZJFTlGVkcMvNCcrMAY+5LNhtwvaFHTvc\n+GXWM3sLviSZdjMA7sw6JycbbOTGnnv2LsMPPMYWE2xkx2ZKkF2Oc9goDjZS666HnGwASDSPvMYv\nl5GyvmCfG3Tb5mc/N79P84PMZ+jv2EXj6sjeBusEieXwklPsXEjWP0PQVzsOQ/aV/IRtH7INdt0V\n1UHJofN99eqHt01YZ60jNnOrg+2H97jgbUbXYRjg1hL6Od8GazOv8cvZzKMNcR1iZ82tDXZ8i94V\nKPqMSAYawzlRXUt7bgElS28A2w3D0CRJSgMosoTSJUl6GsALMDOE/6clnkij9lgUAODXdKQA1Bxu\nxbpkFULWO0hqE+Y7VgLW81hKxcaKGhTlBp16WhNp5zMKgN176hFsSDoHbfc2x6g2jtfHUbGxGuGA\nqcY26+yCTzcgA1ABbNp8CEcKw04bxxroOg5WNWFdWxoBy4AHYinqeVtMwYaKahSGTTnJczB+S86v\ndx6DdjTmtHGgiW7jSF0UGyqqkOM35WywFiJZMyDB3IJUsbEanfMzcjZY70ix69hf2Yh1LQr8PlPO\nPW3086bWJCo2VCMvJwAAUHQzcukD4LOIydbtR9BW3eq0UdPQRtVx6HAr1qeqHZsdtRwr+3lC0bCx\nogYleSGnjhZLX7bNvt9bj5ympDNh9rTEqTrqGxPYUFGNSNDURYywGQBoADZtOYS6osxx1iPHaX1W\n1bRgfUxzbFYVZ2wWT2MjYzN7UbVttvPbY5Dq4k4b+xmbHTseQ0VFNXKssdVsOc8+TYcPJphs2FyD\nboTNjjfRNqm0bWYR7r3RJPW8OZrChopq5Fs20wwzKyMBkC2bbf/6KJK1mZ3dVY30PDt8tA3rK6qR\nY9msLkXbLKnq2FhRjbL8HKeOpjZaX3v3NSDSlHIuuNjVSvejsTmJDRurkWvZzA6qyAAka+X8amst\nGoubnTZq6xk8qG3FukQGDw5ZeGA/jyVVbNxYg6JIBg/a4pm+KAB27T4Of33CFQ/qGuLYUJHBg1Zr\nnkq6Dhnm2Nq4+RBqSTxopMfngaomrI+mHZtVRmldtUYVVGysRkGOKafpWOmUnDu+OYr0kajTxoEm\nxmbHsuNBWjNQUVGNThQe0GNnX2UDcltSDh7sbuXxYENFDfJCZhuKbjofMgg82HYErVUZPDjE4kFt\nC9YnNcdmR5IZfE7BJLobN7B4kMF5BcCe7+sRaszgwffNPB5UVFQjbI2tKIEHEgAdwMavDuEoiQf1\ntN2rq5uwPqq64kFUgAc2Cbdt9s23R2HUZTCcxYOjx2Omzayx1aTweLCexYNm2maVBxqxrjWDB99H\naZs1t6VQUZHBcFU3oOo8HiQOZfCgmsGD2iOt2fEgraNiYzXK8kg8oOfi3n0NCBN4sJtZixqakthQ\nkcGDhI0HBuCzCNHmrYdQX5TrtHGYwYPq2lasT1Q57yiriWfWkRSAaILHgyjDD3btqoP/eNzBg30s\nHtTTGN5i4YFPy+DBho2HUJMFDyoPNmF9WwYP9jMY3hpNoWJjDQosm+lGJkvr4MFOGg8Oshh+LIr1\nBB7UO2uVgRTM13tsqKhGp/wcRMIqotGUE3yULH0nUxp8Fn6YNjGo56qmIxZLE86e+b8EOKw4Fk9D\nI3cJqHQb6bSOaFRx6lB0ug3dMBCLKfATFyVpzGeSSRWSFTwEMmuJI6eqIxbLtKERctq8OhZPIy0T\nW7gZOVOKiphmwL6fJcXIoOmmnOSFTo7zYP2fSKQBIniV0lhdaIgScjoX5xqGI2ssloaSVU4NUULO\nJGMzTTP1bctpgLiixPpMPJ6GTh5JYtpQ0hplszSjC0NkM25sqZC09ttM5ADF4gpUOZPvYseWktYQ\ni2Z0wY4toc1cxpZdOJupmnBskTaLxtIIkjZjbMLZzJLBnsstFqfz+XIy4JeldDQD2AAgz/q5GsBg\n4lkxgDD3jf+DousGNEur5TaY+n0oKgqjqCgHRUU5kHNMcCvOz3EW9nBB0HleUBhyJlFZgbk4+XP8\nKCTqMKzFwm5DlyUUFOY4zwMRE4QjQT/C1rVcwdyA87yoKAe2ae06pICMouLMc19IpmRQARQUhJzn\n4fyQ1T3JcV79YT/VhiHTujBkH4oKM/0IhE1d5IX9CFmfDeaGqDrs2Lxdhy/op/QpBWhdaJKEAuJ5\nKM+ULeT3IS9s6sUfoXWhW+TRsVlARiHx3LZZUV4IsmROkDChi8LCENKMzeQcmZITfroN3SehkLBZ\nMNeULRyUEQmafQowcmoSbzNKTovkkjbLy8/ImVcQggHzNjibrPrDAaoOg5ETsoRCymbW2MoJIMf6\nbCgSpORkx5YvSOvCZ/WvvMCyGUCNX9tmQVlCvm2zsMzYTDTPMs/9ls0KcoMIWJ8N5dNypq2l1K5D\nDtFtIOCz9GmPLaCwgLdZTkBGrqV7P6MLGw/sOlg88FnfK7HwQAOQS+BBfkEIKszFznZe5Rw/iopJ\nPKBtZjBjKxAx24iEvPHAltMXpMdWBg/CztgibRbON20W8EkotMiqzOKBPc9sXTB4YNssLxxA0AMP\nMnIyeBCk5dQlGhuDuTwecPOMGVtSgB6/co7ZRlFeCD4LDyJeeBCi6zACPB4UuOBB2BUPWDn9jM14\nPMgn8CCXwINiAg+oOeBnMVyi1iJ7rcnNCTjR31Auiwf0POPxwE891yAhn8IDs40QhQf02OLxgJ7L\nNoYX5gad23HDBB4UFoYIPDD15QvRayI4m4nxIByUEXHDAw7DxfygxJrrGoC8AhrDNZh4YH/GH86O\nB+zYIvEgx+pTkLUZIydnsxCN4apE40GOjeE+CQUWHgRyGJvJ7FrD4IHNDyIBBBkM9/kkyLLPcYZs\nx1SSAFn2Of9sguonSLdPlpzn9q27PkmCz2pD8klUHWwb9s+y7ENhYQQTxo7EjPGjMG3CmXj60Ydh\nAI589r/mlma89LfnKTmnTpnoPLcFddqQJMiEnJKPkFOi5Wxra8ULLzwv0IUE2e9zbeORB+7Fk08+\nSujC+h7gOEKsLhKJBM6fPR0SDByprcW7y9+CLEvQNBUzZkyBpltBPJ/kBCQkWcJzzz2NYcMG4Yor\nLhPbjJTTx+ubfG7rQpIkxxFi5QRrdxd9yrLPcXpYm3F2Z8YWq0+jAzaTZR8UJYX5Z0+Dpmnwyz4c\nrzuGxVdehjPOOAXjxp2JyZMn4IMP3qPbAOCzvm/rPK2qZnDM+oyqa1iwYB569ToBu3d/Bzsc4pd9\nOHzoEBacMxMjRvwEI0YMxrPPPuXIOWrQKZgyZgRmjB+FyWeNceRsa2vFlZdehLNGDsbEUUOwZdNG\nUxd+fp6RnK6wMAeSJLXrfewddQDXARhu/bwUwF2SJN0rSdLvATwCYGUH6/u3Fdvb7tElH4AZaaD2\ntVueeXlpBDkWGbO/A8DZm5/j96G81HSeFaaOpKgNYgeHXUdRQQgFFhCzW0DtaJBTB7MdwJbzhE55\nkCUJOgByN4tdX27Ij9JiMyqtaPR2LFsOUk72DCAAlBSFkWst7KQudMNwIiDdO2fqIBux5ehOtEGe\nnbPbyI8EUGwt7Oz5EVafCtOGrYuykogToU9oRLRJN60TkCV0Kc+zdEGn4kU2Y887AUBhfgiFlnOt\nMGeT+DpofSesrEGXslwErIWN1KcdoQ4H/SgrsWym09uxUiqvC7IVu46SwhzkWeSPHFuGYXA24cav\nSj9XDQhtlhcOoKQoLNQFO88U5kyELWdZccQhY0mijrRubrHzSUA322a6IRy/Pbtm5ogumIcFuUEU\nFYQouRw5BXXQc9m0WefSCEIWGSP1af+cE5BRXhrJyJFlbCns2LL6XZyfg4LcIPU3R07rd1tON32e\n0DkPPskMXKVV3qYRAg/SrD5tObuKMcd+XlqU42R/WDxIs7jF4gGjb0U3oOu8PvMjQRRbjhGLjSJ9\nklteaDyQLf2QUXLzs0HZh85luVZf6W0z4jb4fhTmh1BoOWcpPTseKC540LU8z9minCR0Yds0EvKj\nrDiDBzQusfqmcc3WRUlhjuOcpRg8sPXhYLQBMR50JuaZwGZ54QBKLGeBnWcibIRg/JYWRxCxnKwk\nMX5Va87IPgldLTxIszYRYTgpg0rggYPhDB5otD45fLXq6FyWm9lOJcCDcFBGuYPh4rFD8QPB8+KC\nHMc543BLuF7xcp7QOQ+SZGYR0gI5c3P8GQx3wwNbFywHcfCA4AfE2k1mgoKBDEEmi/3poMW1DOZD\nzvY4nwTZJ67D/p2sw+5JOBzGmnWb8MkXFfh8w2b86oabuDp0w0BrSwuW/O2v8Pszbaxa/UWmDavj\nThvMFjv7d9PBoLf6tbQ0469/fdb5PVMHLYhdR8CfcXpYOW1dOHIycix9+UXMmH0OwjlBfPnFany9\nY7vZZjCIiRPPwlvL3rTk9FHbBZ9//lm8//7H+Mc/XuJswh5Tsc8E+u1+Mgq1RZItZ8qtDkoXLs/9\nss9x/Mk6yLEV8LuMLbYNg7loxvpfliWnL6Q6X3zxn5gx5xzIsoyA34crF/0UI88cg2+/3YP16zfi\npZdeRm3tIVNOv4/bfhkMBjFh4ll4f/ky+CTJcRJvuuFaDBgwAK+/vgyXXPIz1NbWOHLKfhl3/vE+\nbNmyA2vWfInnnnsG3+36DoDpz7714Sf45IsKrPx8nSPnTTf9BhMnTcXqjdvw5aYtOGnAAG5s2bo4\nsUueuZvPAHc0KFvpqAN4F4C11s/3Afg7gMsA/BrAagBXd7C+f1uxQa3EIlppZkO4fbV0OJDJ9JAH\nsjMAn4nWs0QpxbSh6Ab9ygaiDpv8pgjCp1lESgKcaD27ENlAmxP0IydoL0T0jVxmG5kItZecnJNJ\nLGYZks6nrkN+HyJWxJFbiGxCl+N3zl0ogoUoEvQ72y0VZqJycjJOkd3vcEB25EgJyG84IBM2owmI\nLUcxoQtNQHIiQb/jZLKOle0M23UorDNhyRR2qYMkD47NGHJrE8SMLsTBBdJmJDG1Sb/fJyE/J6Nv\nXWD3SEjOnDHxshlHHgxeTkFwISdAyCkItIQDWXRhfb4wEjSzcwaoSx1Ip8fWN0f4GH2ywYWMPgmb\nqaK5nJGTJXwpgS5EwYVwSEbYGr+knJpuQDXM7Rw2HnDOG4FbduBKaLOQn9Cn7olbIlIZDvoRtvFA\nMEdy/L6MLlyc4fycAIEHYkc1owuxM0zKKQoMmNl6Hl/FNhPrgsQDVYQHIb9w/OoCPHBzrHKCctZg\nI40HdB28zXQaDzSBzQhdkMExdhsuK0duyO+cF0u62Yycq5kqhGuNKNhI7rBIimwWkJ15yK3d1meK\nLDxQDXjajMVwfq0Rt5FD2CThaTO6r2Jd8G2QNiPHhaobTnCsIGwfpRA7b5Gg7GyzFfKYkN/RN49b\nvC50wfilbUbrEzAzQZLEE2wg49TIPim70yNJsPw/1zrsrBjnIDqOk6mzeCyG8887FyNHDsWwYT/B\nsmVv4oG770TVwUpMGDUc9955OwwAncqLAQBVVQcxZvhP8JtrrsKwM07DdVf9HF+sWYXJkyfi9NNP\nxebNm6EDuGLRQkwdPxoTRgzBK//8uyPH7373W1RWVmL6+FG4987bIfskvP3Gq5g5eRxGjRqGX/1q\nMTTNvA/giT//CcMHnYb5M6egct/3QhJ/zeWX4opLF2HOlPEYPHAAPv74I+czb7/xOqbNmo1NG9bh\nD3fchg/fW44zRw3HgQOVmDPnHLz5+mucPm/49bU4cOAA5s2bg8cffwwA8MLTT2D0sJ9gyuhheP7p\nJwHD1MOgQafhmqsux5TRw3H4UI2TWWqLRjFv3lyMHDkUI4cPxntvL4NPMtt5+41XMe2ssRg5MtNX\nwzDwxJ//hGFnmH1dfPkleOzRR1BVdRDDhv3EGWdPPfYIHnngXgDA668uxbhxo616roamafD5JNRU\nV2HSyCH4zXWLMWzoIMyZMwuJRAIGDCx77RWMHTEE08eNxHX/czlgAK+++grGjRuNsWcOx603XAtD\n153xSbKD119/FdNmzgYAfPn5GgSCQVz8iysd/O3Royeu+OVi7Ni6BeNGDkUqlUQ8FsPI4YPx7bc7\nAQBnzz4H77z5OiTrrPhfHrwP+QWFuP+BP2H06DF4+unncPXll6G1tQV+n4TOXbpi4Bnmhsn8/HwM\nGHAyag/XOjKxZztbWlrw5ZdfYuHFl0ICEM4JobCwyNUZjgT9TiA7wXChbKVDZwANw9gDYI/1cwqm\n4/frjtTxHykGMsAZEZMce9GJBGUTfGOKcCGKhGjCJ1ok8sMmyVH1DBkAaOD0a3wmKEWQ41zCsRJF\nTCMWyYmltHYQPhMs7UFkkyJ7e5GZnRPJ6UckaBLMlGBBNRc725nQhQu/SaBltCVVh0hSbZByaiYB\nkSSaSBXlZuQULUQRR44UTaQ0QRsOkaJ1YZMcRdXFdQQzrxVWCF2kNLO2oOxDnuVY8RFqzakjEpTR\nmkhnIVJEHaQ+7exxLkFyCMaXcHThd/aFk+/LEtmMzYKzNkupOk0eSIeFCC7ohgFZkigi5YwtluRQ\nNrPJLz8PSZuxEegUSXKCMhKKRl3MQ/bVdmTt4IKETJZR9mW2rrllFXIsmzXFXEh6iNYnBHIWRIKQ\ns0Tjw0G/MzeFgYEA62SSNsvgViToR1zR6ICQxutb0S1ylAUPyIsjhI6TYPza48bRZ0YVVB05ARnR\nlEpl54SYYp8TlujgWBHlUGcJsLW54AE1B2g8sMdfXk4AQdkHRePf4WnXYTdN6sL+OeT3OduPFSbr\nRdokEvKjLakKgwuRIDkHLOdMoj9jY6OJB+K1RlHt4JggUEgEPDl8JQOBARmKqrsErhjcsoYWmWW0\nxxaXwSZwSxgQcgm06IQyHDwIyQgFZCTTmhi3gjICVjTeHp+S028rOOaGBypts+Z4mn59hcBmPB6Y\nvxRGgtaYdsMDGfYXhbpgnGFRcMGcAzISaQ0pnbd7hLOZaTTKGSbxgLxh2hpHlM0IvLAlfnTVXvwn\nyj0zT6EyQc4ZNDJolUhg4tiRMAwDPp+EX91wIyDJ6NK1K959x9y+V9/UjH6DhuD73d9h3aa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ugGcF7vUhTkZPAg6Pfhqkn9sOa7o9h5qAUn5+fgTAsPVtQ0oSaawsxB3ZAfDuCNiirk+X2Y29vC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/lffZoWdCK3kBNgoJv/AJMOyUwRFYvDuzc/Us4Va2eqEWD449L6tjvJXYaaxOuPwA9PZnlZ7+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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ff21588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Pick a list of sequence labels (here gatestrings) or indices to plot the estimated p(t) for\n",
    "gstrs = [pygsti.objects.GateString(None,'(Gx)^'+str(2**l)) for l in range(4,10)]\n",
    "# Hand this list to the plotting function\n",
    "results_gst.plot_multi_estimated_probabilities(gstrs,loc='upper right')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "** More details please? **\n",
    "\n",
    "Having provided an overview of the tools in the `drift` module, we now give a more detailed introduction to:\n",
    "1. The types of data that can be analyzed, and the format they must be imported in to use the `drift` module.\n",
    "2. The analysis methods that are used inside the `drift.do_basic_drift_characterization()`.\n",
    "3. How to access the various outputs returned by the analysis, and some details on how to interpret them. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Input data types and formats\n",
    "#### What types of data can be analyzed?\n",
    "\n",
    " The methods in this notebook can be used on data from any experiment that satisfies the following criteria: \n",
    "\n",
    "- The experiments consist of $S \\geq 1$ different circuits, or sequences, each with $M \\geq 2$ possible outcomes with $M$ the same for all $S$ circuits.\n",
    "\n",
    "\n",
    "- Sequence $s$ is repeated, and one of the $M$ outcomes is recorded, $N$ times during each of $T$ different time-intervals, with $N$ and $T$ the same for all sequences $s$. Let $\\tau_{s,1},\\tau_{s,2},\\dots,\\tau_{s,T}$ denote times associated with these time-intervals (e.g., the start time or mid-point of each interval).\n",
    "\n",
    "\n",
    "- The time-gap between consecutive sets of $N$ repeats of a sequence is approximately constant, and approximately independent of sequence. That is $t_{s,gap} \\approx \\tau_{s,t+1} - \\tau_{s,t}$ for all $s,t$ and some constant $t_{s,gap}$ (the time gap is constant for each sequence), and $t_{gap} \\equiv t_{s,gap} \\approx t_{s',gap}$ for all $s,s'$ (the time gap is the same for every sequence).\n",
    "\n",
    "#### What type of circuits can the data come from?\n",
    "\n",
    "Many characterization routines, including GST, RPE, restricted sets of GST sequences (e.g., Ramsey sequences) or RB, satisfy the above criteria *if* a suitable time-ordering for the repeats of all of the sequences is chosen.\n",
    "\n",
    "An example is a full set of GST sequences, with sequence 1 repeated $N=5$ times, then sequence 2 repeated $N=5$ times, etc, with this entire procedure looped through $T = 500$ times. As long as each circuit follows on from the following circuit with a roughly constant time gap, then -- even if the different circuits take varying times to implement -- the time-gaps between consecutive sets of $N$ repeats of each circuit are all the same.\n",
    "\n",
    "To obtain best performance, it is preferable to minimize $N$ and maximize $T$ for the same fixed $N \\times T$ (this will provide better detection for high frequency drift).\n",
    "\n",
    "\n",
    "#### What input formats can be used?\n",
    "\n",
    "Two data formats are allowed:\n",
    "\n",
    "1. Data can be provided to the analysis function in a `pyGSTi` dataset, which can be imported using the `pygsti.io.load_tddataset()` function, demostrated above. The automated input for this currently has limited functionality, and the analysis is much slower when using this form of input. However, this method has the advantage of simplicity: minimal user specification is required when the analysis uses such a dataset.\n",
    "\n",
    "2. Data can be provided to the analysis function as an ordinary numpy array. The analysis is faster when using this format. The array can have a range of different dimensions, but the most flexible format is when the array is 4 dimensional. \n",
    "\n",
    "Here we will explain the format when the array is 4 dimensional, below we will demonstrate the method with lower dimensional arrays. When the input array is 4 dimensional, the input data format is a numpy array $A$ of dimension $(S \\times E \\times M_{\\rm marg} \\times T)$, where\n",
    "1. $S$ is the number of sequences,\n",
    "2. $E$ is the number of \"entities\" (often 1; and more on this below),\n",
    "3. $M$ is the number of possible measurement outcomes for each circuit,\n",
    "4. $T$ is the number of timesteps.\n",
    "\n",
    "The matrix element $A[s,e,m,t]$ should record the number of counts (a value in $0,1,\\dots,N-1$) for measurement outcome $m$, on entity $e$, for sequence $s$, with the $t^{\\rm th}$ set of repeats for that sequence.\n",
    "\n",
    "The aspect of this array that is perhaps least inuitive is the \"entities\" concept. This allows the storing of independent data for the same circuits, timestamps, and the same possible measurement outcomes for more than one \"entity\". For example, if multiple single-qubit experiments are implemented in parallel, and any correlations between measurement outcomes are discarded, the data from each qubit can be stored with different entity indexes. This then allows for two things:\n",
    "\n",
    "1. The analysis function independently looks for drift in each entity.\n",
    "2. The analysis function combines the data from all entities, to see if that has evidence for drift which was not evident in the analysis of each entity independently. For example, weak evidence for drift in each entity can combine to convincing evidence for drift in the device as a whole.\n",
    "\n",
    "Later we will discuss further how to use this \"entities\" concept to optimize data analysis, via examples.\n",
    "\n",
    "As shown below, the input data is stored in the results object as an $(S \\times E \\times M \\times T)$ array, \n",
    "which is the same format as can be used for the input. In our GST example there are 3121 sequences ($S = 3121$), a single entity ($E = 1$), two-outcome measurements ($M=2)$, and 500 timesteps ($T=500$)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3121, 1, 2, 500)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "np.shape(results_gst.data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## The analysis methods\n",
    "\n",
    "#### What is the aim of the methods in this tutorial?\n",
    "\n",
    "The analysis presented in this tutorial has two purposes: to detect and characterize drift. To explain this further, we need to define what we mean by drift.\n",
    "\n",
    "There is an underlying probability for circuit $s$ to output the measurement outcome $m$ at time $t$. Denote this by $p_{s,m,t}$, and assume these probabilities satisfy $\\sum_m p_{s,m,t} = 1$ for all $s$ and $t$ (i.e., one of the $M$ measurement outcomes is always observed). By definition, there is no drift if $p_{s,m,t} = p_{s,m,t'}$ for all $s,m,t,t'$. Otherwise there is drift. \n",
    "\n",
    "In the experiments considered herein, we are essentially taking $N$ samples from a multinomial probability distribution with probability vector $(p_{s,0,t},p_{s,1,t},\\dots)$ for each $s$ and $m$, at a set of equally-spaced times. As such, the data allows us to estimate properties of the vectors:\n",
    "\n",
    "$$ \\boldsymbol{p}_{s,m} = (p_{s,m,t_1},p_{s,m,t_2},\\dots,p_{s,m,t_3}).$$\n",
    "\n",
    "The aim of our analysis is:\n",
    "\n",
    "1. **Drift Detection:** Starting from the assumption that there is no drift, decide whether there is statistically significant evidence in the data that $p_{s,m,t}$ is *not* independent of $t$.\n",
    "2. **Drift characterization:** Estimate $p_{s,m,t}$ for all sample times $t$.\n",
    "\n",
    "The drift detection and characterization works via spectral analysis, by implement a type of discrete Fourier transform on the data and looking for peaks in the power spectrum that are larger than would be expected if there was no drift.\n",
    "\n",
    "Specifically, consider a data vector $\\boldsymbol{x}=(x_0,x_1,\\dots,x_{T-1})$, of the number of counts observed for measurement outcome $m$ with sequence $s$ as a function of time $t \\in [0,1,\\dots,T]$. We remove the data mean from this vector, and renormalize it in a particular way, to obtain the $\\boldsymbol{z}$ vector, defined by:\n",
    "\n",
    "$$\n",
    "z_{s,m,t} = \\frac{x_{s,m,t} - \\bar{x}_{s,m}}{\\sqrt{ N\\bar{x}_{s,m}(1- \\bar{x}_{s,m})}},\n",
    "$$\n",
    "\n",
    "We won't fully explain the reasons for this mapping on $\\boldsymbol{x}$ here, except to note that (1) it is not essential, and (2) the motivation is that -- after this mapping -- the statisical behaviour of the random variable from which $\\boldsymbol{z}$ is drawn, when there is no drift, is largely independent of $N$ and the value of the time-independent probabilitiy $p_{s,m}$.\n",
    "\n",
    "We then perform a Fourier transform on the data -- specifically, we implement a Type-II orthogonal discrete cosine transform (DCT) -- to obtain Fourier modes $ \\tilde{\\boldsymbol{z}}_{s,m} = F \\boldsymbol{z}_{s,m}$. The precise definition of this transform is not important for obtaining an intuitive understanding of this method, but for completeness it is defined by:\n",
    "\n",
    "\\begin{align}\n",
    "F_{\\omega,t} =\\sqrt{\\frac{2^{1-\\delta_{\\omega,0}}}{N}} \\cos\\left(\\frac{\\omega \\pi}{N}\\left( t + \\frac{1}{2}\\right)\\right), \n",
    "\\end{align}\n",
    "with $\\omega,t=0,\\dots,N-1$.\n",
    "\n",
    "We then square these Fourier modes, to obtain a power spectrum $\\tilde{\\boldsymbol{z}}_{s,m}^2$ for each measurement outcome and each sequence. It is these power spectra that we analyze to detect and characterize drift. We can look at the individual power spectra for a particular sequence and measurement outcome. Using the central limit theorem and some statistics (which we will not cover here), it can be show that -  when there is no drift - each Fourier mode is approximately a zero-mean unit-variance $\\chi^2_1$ random variable. As such, we can calculate the probability that a spike in a power spectrum is due to random statistical flucations, and if this probability is low enough then we can be confident the peak is due to drift. I.e., the underlying $p(t)$ is not constant.\n",
    "\n",
    "We can also average these power spectra over measurement outcomes, and/or over sequences (and over entities, which haven't been discused above, and on which this entire analysis is independently performed). When averaging over all of these quantities, we obtain the global power spectrum presented above. The advantage of this averaging is that it supresses noise from random flucations, but does not supress any \"signal\" due to nonconstant $p(t)$ - as long as the same frequencies are present in many of the power spectra that are being averaged.\n",
    "\n",
    "Before explaining any more of the analysis methods, we turn to a simple example."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Example 1 : Single sequence data\n",
    "We demonstrate this on single-sequence data, for a single entity, with two-outcome measurements. This is the circumstance under which the analysis function can be given data in a 1D array, and so we will use this method below. We now demonstrate the method with simulated data for a drifting and drift free probability.\n",
    "\n",
    "Below we use a drifting probability of\n",
    "$$ p(t) = 0.5 + 0.2 \\cos(0.1 t).,$$\n",
    "with integer $t$ in the range $0,1,2,\\dots,T$.\n",
    "This is similar in form to the drifting probability that would be obtained with certain sorts of Ramsey experiment with drifting $\\sigma_z$ over-rotation angle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Imports for generating fake data to demonstrate the methods.\n",
    "from numpy.random import binomial\n",
    "from numpy.random import multinomial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Due to input array format, analysis is defaulting to assuming:\n",
      "  - single-sequence data\n",
      "  - single entity data\n",
      "  - two-outcome measurements\n",
      "\n",
      "Due to input array format, analysis is defaulting to assuming:\n",
      "  - single-sequence data\n",
      "  - single entity data\n",
      "  - two-outcome measurements\n",
      "\n"
     ]
    }
   ],
   "source": [
    "N = 5 # Counts per timestep\n",
    "T = 100 # Number of timesteps\n",
    "\n",
    "# The confidence of the statistical tests. Here we set it to 0.999, which means that\n",
    "# if we detect drift we are 0.999 confident that we haven't incorrectly rejected the\n",
    "# initial hypothesis of no drift.\n",
    "confidence = 0.999\n",
    "\n",
    "# A drifting probability to obtain the measurement outcome with index 1 (out of [0,1])\n",
    "def pt_drift(t): return 0.5+0.2*np.cos(0.1*t)\n",
    "\n",
    "# A drift-free probability to obtain the measurement outcome with index 1 (out of [0,1])\n",
    "def pt_nodrift(t): return 0.5\n",
    "\n",
    "# If we want the sequence to have a label, we define a list for this (here, a list of length 1).\n",
    "# The labels can, but need not be, pyGSTi GateString objects.\n",
    "sequences = [pygsti.objects.GateString(None,'Gx(Gi)^64Gx'),]\n",
    "\n",
    "# If we want the outcomes to have labels, we define a list for this.\n",
    "outcomes = ['0','1']\n",
    "\n",
    "# Let's create some fake data by sampling from these p(t) at integer times. Here we have\n",
    "# created a 1D array, but we could have instead created a 1 x 1 x 1 x T array.\n",
    "data_1seq_drift = np.array([binomial(N,pt_drift(t)) for t in range(0,T)])\n",
    "data_1seq_nodrift = np.array([binomial(N,pt_nodrift(t)) for t in range(0,T)])\n",
    "\n",
    "# If we want frequencies in Hertz, we need to specify the timestep in seconds. If this isn't\n",
    "# specified, the frequencies are given in 1/timestep with timestep defaulting to 1.\n",
    "timestep = 1e-5\n",
    "\n",
    "# We hand these 1D arrays to the analysis function, along with the number of counts, and other\n",
    "# optional information\n",
    "results_1seq_drift = drift.do_basic_drift_characterization(data_1seq_drift, counts=N, outcomes=outcomes,\n",
    "                                                           confidence=confidence, timestep=timestep, \n",
    "                                                           indices_to_sequences=sequences)\n",
    "results_1seq_nodrift = drift.do_basic_drift_characterization(data_1seq_nodrift, counts=N, outcomes=outcomes, \n",
    "                                                             confidence=confidence, timestep=timestep, \n",
    "                                                             indices_to_sequences=sequences)                                                    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "We can now compare the global power spectrum obtained when there is drift, and when there is not drift. Except in highly unusual cases (1 in 1000) there will be no drift detected when there is indeed no drift. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
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U119/HYAxY8awffv2TPtjYmKYOnUqACNHjmT37t2Z9sfGxvLMM88AcP3113Pw4MFM+3v1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\nqxcwcoQY9GbF7EuLFrKtdRvZvv+AzH/pBjNz57Ec0Se3x9e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aaC+84F0WL11afjlKSsSR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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fe17320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results_1seq_drift.plot_power_spectrum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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nz2bZsmU0b94cgIMHD1K1alWqVKlC7dq1+frrr6lTpw7r16+nVatWjBkzJsPy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\nG/r2lUEnf+uOo8nEiZL3pKTA64XNPscNN3BQ6yB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psY2J4uSll6xO/9FHx+ZDr6hg7tZN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\notRi/h8oW9aecXZtSgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1102b45c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results_1seq_nodrift.plot_power_spectrum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "We can look to see what the p-value associated with the largest peak in the power spectrum is. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0006544481483725662\n",
      "0.3749917484310896\n"
     ]
    }
   ],
   "source": [
    "print(results_1seq_drift.global_pvalue)\n",
    "print(results_1seq_nodrift.global_pvalue)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "The analysis function performs:\n",
    "1. an analysis on a per-sequence, per-entity, per-outcome basis (properties starting with `pspepo`), an analysis on a per-sequence, per-entity, outcome-averaged basis (properties starting with `pspe`), \n",
    "2. an analysis on a per-sequence, entity-averaged, outcome-averaged basis (properties starting with `ps`), \n",
    "3. an analysis on a sequence-averaged, per-entity, outcome-averaged basis (properties starting with `pe`),\n",
    "4. a global analysis on a sequence-averaged, entity-averaged, outcome-averaged basis (properties starting with `global`)\n",
    "\n",
    "That is, it inspects all the power spectra, after the relevant averaging has been performed, for evidence of drift (e.g., for case 1 there are $S \\times E \\times M \\times T$ spectra).\n",
    "\n",
    "In the example here there is a single sequence, a single entity, and two-outcome measurements. Hence, in this case all of the analyzes are exactly equivalent, as is clear by noting that all of the power spectra are the same:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.04870979e-30 1.76948267e+00 1.04190088e+00 2.03213493e+01]\n",
      "[5.04870979e-30 1.76948267e+00 1.04190088e+00 2.03213493e+01]\n",
      "[5.04870979e-30 1.76948267e+00 1.04190088e+00 2.03213493e+01]\n",
      "[5.04870979e-30 1.76948267e+00 1.04190088e+00 2.03213493e+01]\n",
      "[8.07793567e-30 1.76948267e+00 1.04190088e+00 2.03213493e+01]\n",
      "[2.01948392e-30 1.76948267e+00 1.04190088e+00 2.03213493e+01]\n"
     ]
    }
   ],
   "source": [
    "# The power spectrum obtained after averaging over everthing\n",
    "print(results_1seq_drift.global_power_spectrum[:4])\n",
    "# The power spectrum obtained after averaging over everthing except sequence label\n",
    "print(results_1seq_drift.ps_power_spectrum[0,:4])\n",
    "# The power spectrum obtained after averaging over everthing except entity label\n",
    "print(results_1seq_drift.pe_power_spectrum[0,:4])\n",
    "# The power spectrum obtained after averaging over everthing except sequene and entity label\n",
    "print(results_1seq_drift.pspe_power_spectrum[0,0,:4])\n",
    "# The two power spectra obtained after averaging over nothing\n",
    "print(results_1seq_drift.pspepo_power_spectrum[0,0,0,:4])\n",
    "print(results_1seq_drift.pspepo_power_spectrum[0,0,1,:4])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "As we can see above, the power spectra for the two different measurement outcomes are identical. This is because the Fourier modes for all of the measurement outcomes must sum to zero. Hence, there are only $M-1$ independent power spectra, which here is 1.\n",
    "\n",
    "As already demonstrated above, the analysis function also creates an estimate for the drift probability for each measurement outcome (and for each sequence, and each entity, but here there is only one of each of these). This estimate is created in the following way:\n",
    "\n",
    "1. Inspect the relevant power spectrum (the power spectrum for the sequence, entity, and measurement outcome under consideration).\n",
    "2. Take the modes obtained from the data, and set all modes with power below the \"significance threshold\" to zero. This significance threshold is generally adjusted for the number of sequences and entities considered, which is not relevant in this case but is discussed below.\n",
    "3. Keep all modes with power above the significance threshold and invert the Fourier transform.\n",
    "4. This is the estimate of $p(t)$, up to some final adjustments to guarantee that $p(t)$ is within $[0,1]$.\n",
    "\n",
    "Because we have created our data from a known underlying $p(t)$ we can compare our estimate of $p(t)$ with the true $p(t)$. We do this below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Dz4nIJ8B9wHxjzJYOy2UHMP3dd5v4fXHoUK4ePpy9jsPZ773X5PoV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\nt198XRASVhQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110158208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Lets create an array of the true probability. This needs to be\n",
    "# of dimension S x E x M x T\n",
    "parray_1seq = np.zeros((1,1,2,T),float)\n",
    "parray_1seq[0,0,0,:] = np.array([pt_drift(t) for t in range(0,T)])\n",
    "parray_1seq[0,0,1,:] = 1 - parray_1seq[0,0,0,:]\n",
    "\n",
    "# The measurement outcome index we want to look at (here the esimated p(t) \n",
    "# for one index is just 1 - the p(t) for the other index, because we are\n",
    "# looking at a two-outcome measurement).\n",
    "outcome = 1\n",
    "\n",
    "# If we hand the parray to the plotting function, it will also plot\n",
    "# the true probability alongside our estimate from the data\n",
    "results_1seq_drift.plot_estimated_probability(sequence=0,outcome=outcome,parray=parray_1seq,plot_data=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Example 2 : Single-sequence multi-qubit data\n",
    "Single sequence data with two measurement outcomes is (a) often not will be obtained in experiments, and (b) is not sufficient to demonstrate all of the methods contained within the analysis function, or to understand all of the ouput. Hence, we now consider an example with a single-sequence and 4 measurement outcomes, which could represent a two-qubit single-sequence experiment.\n",
    "\n",
    "Let us consider the case of 4 possible measurement outcomes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# We only explicitly name them for labelling purposes.\n",
    "outcomes = ['00','01','10','11']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "This could correspond to computational basis measurements of two qubits. Now let us assume that the drifting $p(t)$ for obtaining each measurement outcome factorizes into probabilities for outcomes 0 and 1 for each qubit (e.g., because it is parallel single-qubit experiments and there is no crosstalk). Specifically, take the first qubit to have drifting probability for outcome 0 of\n",
    "$$ p_{0}(t) = 0.5+0.05 \\cos(0.08t),$$\n",
    "and the second qubit to have drifting probability for outcome 0 of\n",
    "$$ p_{0}(t) = 0.5+0.05 \\cos(0.2t),$$\n",
    "with $t \\in [0,1,\\dots, T]$.\n",
    "\n",
    "Let's create some data from these drifting probabilities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "N = 10 # Counts per timestep\n",
    "T = 1000 # Number of timesteps\n",
    "\n",
    "# The drifting probabilities for the 4 outcomes\n",
    "def pt00(t): return (0.5+0.07*np.cos(0.08*t))*(0.5+0.08*np.cos(0.2*t))\n",
    "def pt01(t): return (0.5+0.07*np.cos(0.08*t))*(0.5-0.08*np.cos(0.2*t))\n",
    "def pt10(t): return (0.5-0.07*np.cos(0.08*t))*(0.5+0.08*np.cos(0.2*t))\n",
    "def pt11(t): return (0.5-0.07*np.cos(0.08*t))*(0.5-0.08*np.cos(0.2*t))\n",
    "\n",
    "# Because of the type of input (>2 measurement outcomes), we must record the\n",
    "# data in a 4D array (even though some of the dimensions are trivial)\n",
    "data_multiqubit = np.zeros((1,1,4,T),float)\n",
    "\n",
    "# Generate data from these p(t)\n",
    "for t in range(0,T):\n",
    "    data_multiqubit[0,0,:,t] = multinomial(N,[pt00(t),pt01(t),pt10(t),pt11(t)])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "#### Example 2.1 : A simple analysis of the full dataset\n",
    "The simplest way to analyze this data is just to hand it to the drift characterization method, as before (note that now we don't need to specify the counts number, as the input is a 4D array). We do this below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "results_multiqubit_full = drift.do_basic_drift_characterization(data_multiqubit,outcomes=outcomes,confidence=0.99)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "By looking at the global power spectrum, we can clearly see that there is drift."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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6OmvWrAFgx44dXHjhhaSnp5ORkcGzzz5b5nL8pk+fTvv27cnIyGDUqFFAyYzL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\nKYF8hWCVbwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ff78940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results_multiqubit_full.plot_power_spectrum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "As always, we can also return the frequencies, found from inspecting the global power spectrum. As we have not specified a timestep, these are integers between $1$ and $T-1$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[25 26 64]\n"
     ]
    }
   ],
   "source": [
    "print(results_multiqubit_full.global_drift_frequencies)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Because there are multiple measurement outcomes, we can look at the power spectra for each of these, and also we can look at the drift frequencies found from just analyzing this spectrum. One example of such a power spectrum is given below"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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5fvw4GRkZNHInJt6+fTtXX301rVq1omPHjmzatAmA4cOHc+edd9KuXTseeuih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\nT5IkSZIGzNAnSZIkSQNm6JMkSZKkAfsvA9LnozGNiywAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fe23ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "outcome = 0 # the outcome index associated with the '00' outcome\n",
    "results_multiqubit_full.plot_power_spectrum(sequence=0,entity=0,outcome=outcome)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "The drift frequencies found via an independent analysis of each of these spectra. Generally, these need not contain the same frequencies as the global analysis. In this example, because all of the frequencies appear in all of the spectra, the global analysis is more sensitive (reduced noise without reducing signal strength). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[]\n",
      "[]\n",
      "[26 64]\n",
      "[64]\n"
     ]
    }
   ],
   "source": [
    "print(results_multiqubit_full.pspepo_drift_frequencies[0,0,0])\n",
    "print(results_multiqubit_full.pspepo_drift_frequencies[0,0,1])\n",
    "print(results_multiqubit_full.pspepo_drift_frequencies[0,0,2])\n",
    "print(results_multiqubit_full.pspepo_drift_frequencies[0,0,3])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "As always, we can also look at the reconstruction for a given drifting probability. An example is shown below, where again we construct the true underlying probability with which to compare it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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mzJjBL3/5y4zymT59Ovfddx9jx45l9OjRVFRUNH/nteyf/exnnH766cRiMYLB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\nd+GFX44fT20yydVlDMSyTDj+eL579tlMGdD0u0uxQICTzz6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FLVT5ZwUCPG0YfJZKMciD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\nAIAmBCAAAEATAhAAAKAJAQgAANDECcisxX8rN1VfAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b4a96d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Creates an array of the true probability.\n",
    "parray_multiqubit_full = np.zeros((1,1,4,T),float)\n",
    "parray_multiqubit_full[0,0,0,:] = np.array([pt00(t) for t in range(0,T)])\n",
    "parray_multiqubit_full[0,0,1,:] = np.array([pt01(t) for t in range(0,T)])\n",
    "parray_multiqubit_full[0,0,2,:] = np.array([pt10(t) for t in range(0,T)])\n",
    "parray_multiqubit_full[0,0,3,:] = np.array([pt11(t) for t in range(0,T)])\n",
    "\n",
    "results_multiqubit_full.plot_estimated_probability(sequence=0,outcome=1, plot_data=True,\n",
    "                                                   parray=parray_multiqubit_full)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "#### Example 2.2 : Marginalizing over qubits\n",
    "\n",
    "The above analysis looks for drift in the $2^2$ measurements outcomes of a two-qubit circuit. This would be problematic for many qubits, as for $Q$ qubits there is $2^Q$ possible measurement outcomes, and the probability of any one outcome being observed will - for many circuits - converge to zero as $Q$ increases. Then, even for very large $T$, there could be, e.g., at most 2 counts for any one measurement outcome, and the power spectra obtained will be useless.\n",
    "\n",
    "However, it is likely in many circumstances that any drift will show up in the marginalized probabilities for obtaining 0 or 1 of each qubit. E.g., in the example above this is precisely what is drifting. We can implement an analysis like this by specifying that the analysis function marginalizes.\n",
    "\n",
    "To do this in an automated way, we specify ` marginalize = 'std'`. This then assumes that the data is such that the 0th indexed outcomes is the bitstring 0...0000, the 1st indexed outcome is the bitstring 0...0001, etc. It then associates the first qubit with entity 0 (where first qubit has its measurement outcome recorded as the first bit in the string), the second qubit with entity 1 and so on.\n",
    "\n",
    "Note that, when using this method, the input data array grows exponentially in the number of qubits. As such, pre-marginalizing will be preferable for a large number of qubits, in which case the data for different qubits should be stored with different \"entity\" indices.\n",
    "\n",
    "Below we demonstrate this method on the same data as analyzed above"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "results_multiqubit_marg = drift.do_basic_drift_characterization(data_multiqubit, outcomes=outcomes, \n",
    "                                                                marginalize = 'std', confidence=0.99)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "As we can see from the returned data shape, the data has been split into separate sets for 2 different entities, each have two possible measurement outcomes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 2, 2, 1000)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.shape(results_multiqubit_marg.data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "As always, we can plot the global power spectrum (averaged over everything, including entity, i.e., qubit)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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MGzeOzMxMPv74Yy6//HIAFi1aRL169cjKyiIjI4NWrVoB8NVXX3HhhRfStWtX+vTpw+bN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\n0rXzz6e6NpVcufTMLbdo3a4dybwrX11hXHpp6numTNH6r3+t3TeNx7V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veAhCCG0AbKvv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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1195a60f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results_multiqubit_marg.plot_power_spectrum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "However, now we can look at the power spectrum for each individual qubit. This then shows us that each qubit has a different drift frequency. Something that was not obvious from the analysis implemented without marginalization. Moreover, these spectra show higher peaks (they are approximately twice as high), because -- earlier -- when we constructed the global power spectrum we were averaging pure noise with \"signal\" at both drift frequencies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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LWLduHdHR0QCcPHmSBg0aUL9+fZo1a8ZXX31F8+bN2bx5M+3bt2fGjBl+yxtz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\nyrhx44iOjvbeU+pPy5YtSU1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eCWV8FdUuRWnZsiVpaWnepC8zM5PvvvuOnJwcdu3aRadO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\noiiK0oH5/55hyLQPFDCUAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1196a7860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results_multiqubit_marg.plot_power_spectrum(sequence=0,entity=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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9y1WVhQsX0rx581zlJ06cSL169fjmm2/Izs6mRo0a3nXVq1f3vg8ICODs2bN+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\nKIqiKIVIR3D6PsZaa4G0r0Y3xpxrjHnFGPPKxo0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2uUaPHgPvn3wg1BbD9LUw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\nURRFKWD+P/Hze4jc6eSDAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11989c320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results_multiqubit_marg.plot_power_spectrum(sequence=0,entity=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "With this analysis we can isolate the drift frequencies of each qubit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[25 26]\n",
      "[63 64]\n"
     ]
    }
   ],
   "source": [
    "# Drift frequencies for the first qubit\n",
    "print(results_multiqubit_marg.pe_drift_frequencies[0])\n",
    "# Drift frequencies for the second qubit\n",
    "print(results_multiqubit_marg.pe_drift_frequencies[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Finally, we can again plot the estimated drift probabilities. Again, these are more informative that what was obtained without marginalization. In particular, the oscillations are noticably stronger, as they are each the sum of two of the drifting probabilities from the \"raw\" unmarginalized case."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Pn4T3JvpmIjLPOTesunSZCahhGIZhGIZhGEY989NPP9G7d++k14cMGcJhhx1W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\n8V8cSJSSmLzGoAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x119af7518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Creates an array of the true probability.\n",
    "parray_multiqubit_marg = np.zeros((1,2,2,T),float)\n",
    "parray_multiqubit_marg[0,0,0,:] = np.array([pt00(t)+pt01(t) for t in range(0,T)])\n",
    "parray_multiqubit_marg[0,0,1,:] = np.array([pt10(t)+pt11(t) for t in range(0,T)])\n",
    "parray_multiqubit_marg[0,1,0,:] = np.array([pt00(t)+pt10(t) for t in range(0,T)])\n",
    "parray_multiqubit_marg[0,1,1,:] = np.array([pt01(t)+pt11(t) for t in range(0,T)])\n",
    "\n",
    "results_multiqubit_marg.plot_estimated_probability(sequence=0,entity=0,outcome=0,parray=parray_multiqubit_marg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "#### Example 2.3 : Marginalizing over qubits loses information and can miss detectable drift\n",
    "Marginalizing involves throwing away information about correlations between measurement outcomes. As such, it is insensitive to certain types of drift. In particular, if only the correlations between measurement outcomes are drifting. This is perhaps a rather contrived situation, but it is possible. For example, consider the drifting probabilities:\n",
    "$$ p_{00}(t) = 0.25-0.05 \\cos(0.05*t) $$\n",
    "$$ p_{01}(t) = 0.25+0.05 \\cos(0.05*t) $$\n",
    "$$ p_{10}(t) = 0.25+0.05 \\cos(0.05*t) $$\n",
    "$$ p_{11}(t) = 0.25-0.05 \\cos(0.05*t) $$\n",
    "In this case, as demonstrated below, the analysis of the full data clearly demonstrates drift, yet the analysis of the marginalized data does not."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "N = 10 # Counts per timestep\n",
    "T = 1000 # Number of timesteps\n",
    "\n",
    "outcomes = ['00','01','10','11']\n",
    "\n",
    "def pt_correlated00(t): return 0.25-0.05*np.cos(0.05*t)\n",
    "def pt_correlated01(t): return 0.25+0.05*np.cos(0.05*t)\n",
    "def pt_correlated10(t): return 0.25+0.05*np.cos(0.05*t)\n",
    "def pt_correlated11(t): return 0.25-0.05*np.cos(0.05*t)\n",
    "\n",
    "data_1seq_multiqubit = np.zeros((1,1,4,T),float)\n",
    "for t in range(0,T):\n",
    "    pvec = [pt_correlated00(t),pt_correlated01(t),pt_correlated10(t),pt_correlated11(t)]\n",
    "    data_1seq_multiqubit[0,0,:,t] = multinomial(N,pvec)\n",
    "        \n",
    "results_correlatedrift_marg = drift.do_basic_drift_characterization(data_1seq_multiqubit,\n",
    "                                                             outcomes=outcomes, marginalize = 'std')\n",
    "\n",
    "results_correlatedrift_full = drift.do_basic_drift_characterization(data_1seq_multiqubit, \n",
    "                                                             outcomes=outcomes, marginalize = 'none')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
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QQgghhBAiDKJap09rPdLLV32jmQ4hhBBCCCGEOFnEQ50+IYQQQgghhBARIkGfEEIIIYQQ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\nECJZJV3Qp7W+TWu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fDz/8UN944426vLxcl5WV6UGDBulPPvmkyvrXqVNXf/GFee9rGb17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\nCRqmOP9ChrRvftO+v/ZiGWO9oMYITS9bFlY8CO0d8hW6OXOEdy1eLN6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jd95p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\nkyRJkqQBs+iTJEmSpAH7D/kF7PkjOWjFAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x119bfec50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results_correlatedrift_marg.plot_power_spectrum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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MjAzatWvHoEGD2Lp1KwCNGjVi1KhRtGvXjpSUFJYtC64U2rp1KxdffDEpKSmk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\nAmNuDnlv5ZQXWL1/KfYKBehclx97W6Rj74znYGx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4/f0IwjNUQ5NblqA8/rbEZjJ+CPBq\nbxZYtisrgBXuPi/5fA+hEajcKX3tw8Cf3P2v7r4JuI+QT5U7pWkMtEbfU8Do5G1KbYSHbO/v4zLJ\ndia5b38OsMTd/yM16n7glOT/pwA/Tg2fnryJbjLQkbqVSWSrcfcvu/sod9+bkB8fcfdPA48Cn0gm\ny8ZmjNlPJNPrKotsE+7+MvAXM9svGXQksBjlTul7LwCTzWyH5BgfY1O5U5rGgOuc3cw+QnhmpQjc\n6u5f6+MiyXbGzA4DfgUsovTc1CWE5/ruBvYE/gx80t1fSw4g1xNuFVkLnOru83u94LJdMbN/AC5w\n92lmtg/hyt8wYCHwGXffYGaDgP8iPJf6GnCSuz/XV2WW5mdm4wkvGWoDngNOJfwArdwpfcrMLgNO\nJLyheyHwOcKze8qd0hQGXKNPREREREREGjfQbu8UERERERGRLlCjT0REREREpImp0SciIiIiItLE\n1OgTERERERFpYmr0iYiIiIiINDE1+kREpF8zs5lm5jn/ftnXZRMRERkIWvq6ACIiIg3oIPTXlh0m\nIiIidajRJyIiA8Fmd3+ykQnNbLC7r9vWBRIRERkodHuniIgMWGbWktzqeY6ZXWtmfwUWpsYfb2YL\nzGy9ma00syvMrCUzj0+a2bNmts7MHjOzSck8P5NZxozM9y43s5czw/Yys++b2etmttbM5prZ6NT4\nfZN5nWBm3zazDjNbYWZfNTPLzOsDZvZAMs0aM3vSzI5IjR+ezGNVsn6Pm9nBW6ViRUSkqajRJyIi\nA0LS+Er/SzeSLgZGAJ8FzkumPxn4AfAb4BjgcuCs5G+c5yTgTuB3wMeBucD3u1m+EcATwL7AmcCJ\nwFDgITNrz0x+NbAa+ESy/MuS5cd5HZDMaxfg88AJwP3Ansn4QcAjwOHAl4DjgNeBX5rZrt0pv4iI\nNC/d3ikiIgPBcGBTZthRwGPJ/1e4+8lxhJkVgKuAW9397GTwL8xsEzDbzK5099cJjcU/Aie5uwM/\nSxpUM7tRxi8B7cCR7r46KcevgeeBfwZuSk37iLtfmPz/ITObChwP3JcMmwm8Ckxx9/Wx/KnvnwLs\nB4x19+eSZT0CLCM0er/cjfKLiEiT0pU+EREZCDqAgzP/5qXGP5CZfgywO3B3+uog4erYYGBsMt0k\n4P6kwRfdR/d8GPg58GZqeR2Eq4gTM9P+IvN5MTAq9fkI4K5Ugy9vWU8BL6SW1Qn8T86yRERkO6cr\nfSIiMhBsdvf52YGp5/NeyYwakfzNNq6iPZK/7wJWZcZlPzdqBKHB9emccdkXy6zOfN4IDAJIblsd\nBqyss6zDqLz6CbC0kcKKiMj2Q40+ERFpBp75/Fry9zRgUc70zyV/XwGyz8BlP78NbAbaMsPfmbPM\nhcDXc5b3Rs6wXO7uZvYasFuNyV4DngS+mDOu2tVBERHZTqnRJyIizWgx8DKwt7vfVmO6p4BjzOzS\n1C2ex6cnSBphLxJuGQXAzIrAkZl5PQwcCyxy9w09LP/DwElm9tUq83oY+DfgeXf/Ww+XJSIiTU6N\nPhERaTru/raZXQDcZmZDCc/abQL2Ibwl89ikMXUl8GvgTjP7T+BAwktXsn4InGlm/wv8GTgD2CEz\nzTeAk4FHzOx64CVgJPAh4DF3v7sLq/CvwG+B/zazWYSXuhwEvOLutwO3Ed7q+ZiZXU24cjkCmAz8\nxd2v7cKyRESkyelFLiIi0pTc/buEBt7fEbpuuBeYQWhMbUqmeZLQUDsY+BEwDTgpZ3ZfJbzg5euE\nBtd84I7M8lYRGl3LgdmE5wmvBHYm/xbTWmVfAvw94dm/OcmyPw68kIxfR2hMPkq44vcQcA3wnmT9\nREREtrDyF5aJiIhs35Irg68Dn3X37/R1eURERHpKV/pERERERESamBp9IiIiIiIiTUy3d4qIiIiI\niDQxXekTERERERFpYmr0iYiIiIiINDE1+kRERERERJqYGn0iIiIiIiJNTI0+ERERERGRJqZGn4iI\niIiISBP7f3C2JKJP+y9GAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x119c2cb00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results_correlatedrift_full.plot_power_spectrum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "What this demonstrates is that it is important to carefully decide how to analyze data from a given experiment, with physical motivations for the analysis used."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}