{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1bd00345-0314-425b-9b86-ad1196286a4a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Bar Plot from SRO: from plot_fate_byOilAndLocation.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f69bb9dd-5f54-4678-b714-7b5ffc6df372",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import yaml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "b5dcc4a0-a289-488c-8a77-82143367045c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "Bad key xtick.labelcolor in file extraction_from_rachaels.template, line 22 ('xtick.labelcolor:    inherit # color of the tick labels or inherit from xtick.color')\n",
      "You probably need to get an updated matplotlibrc file from\n",
      "https://github.com/matplotlib/matplotlib/blob/v3.3.3/matplotlibrc.template\n",
      "or from the matplotlib source distribution\n",
      "\n",
      "Bad key ytick.labelcolor in file extraction_from_rachaels.template, line 32 ('ytick.labelcolor:    inherit # color of the tick labels or inherit from ytick.color')\n",
      "You probably need to get an updated matplotlibrc file from\n",
      "https://github.com/matplotlib/matplotlib/blob/v3.3.3/matplotlibrc.template\n",
      "or from the matplotlib source distribution\n"
     ]
    }
   ],
   "source": [
    "plt.style.use(r'extraction_from_rachaels.template')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "183313f1-77a2-4377-bd05-b25616f87332",
   "metadata": {},
   "outputs": [],
   "source": [
    "MIDOSScolors={\n",
    "    'ANS': 'darkslategrey',\n",
    "    'Bunker-C':'teal',\n",
    "    'Dilbit':'slategrey',\n",
    "    'Diesel':'darkgoldenrod',\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "c64c510d-bfa1-4755-ad42-f66f9bed0ea2",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('SRO_files_try3_t2.yaml') as file:\n",
    "    sro = yaml.safe_load(file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6a8b9e42-e37f-42fd-a52e-083e58402f7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df={}\n",
    "df['ANS'] = pd.DataFrame(sro['akns'])\n",
    "df['Bunker-C'] = pd.DataFrame(sro['bunker'])\n",
    "df['Diesel'] = pd.DataFrame(sro['diesel'])\n",
    "df['Dilbit'] = pd.DataFrame(sro['dilbit'])\n",
    "\n",
    "oil_types = ['ANS', 'Bunker-C', 'Diesel', 'Dilbit']\n",
    "locations = ['water','sfc','beach','air']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "9fc5246e-bf64-4623-8aa6-e2d81aa3930e",
   "metadata": {},
   "outputs": [],
   "source": [
    "final = {}\n",
    "initial={}\n",
    "for location in locations:\n",
    "    final[location]={}\n",
    "    for oil in oil_types:\n",
    "        final[location][oil]=[]\n",
    "for oil in oil_types:\n",
    "    final['water'][oil] = (df[oil]['MDispersed'] + \n",
    "        df[oil]['MDissolved'] + \n",
    "        df[oil]['MBio'])\n",
    "    final['sfc'][oil] = df[oil]['MassOil']\n",
    "    final['beach'][oil] = df[oil]['MBeached']\n",
    "    final['air'][oil] = df[oil]['MEvaporated']\n",
    "    initial[oil]=df[oil]['MInitial']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "c2551a95-56a4-4ed8-9e3c-5299ee09e5c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "persist = {}\n",
    "\n",
    "# Calculate Quantiles\n",
    "persist['Q1']={}\n",
    "persist['Q2']={}\n",
    "persist['Q3']={}\n",
    "for oil in ['ANS','Bunker-C','Diesel']:\n",
    "    persist['Q1'][oil]={}\n",
    "    persist['Q2'][oil]={}\n",
    "    persist['Q3'][oil]={}\n",
    "    for loc in locations:\n",
    "        #Quantile 0.25 (in percent form)\n",
    "        persist['Q1'][oil][loc]=100*np.quantile(\n",
    "            final[loc][oil]/(initial[oil]), .25)\n",
    "        #Quantile 0.5 (median, in percent form)\n",
    "        persist['Q2'][oil][loc]=100*np.quantile(\n",
    "            final[loc][oil]/(initial[oil]), .50)\n",
    "        #Quantile 0.75 (in percent form)\n",
    "        persist['Q3'][oil][loc]=100*np.quantile(\n",
    "            final[loc][oil]/(initial[oil]), .75)\n",
    "        \n",
    "persist_df = {}\n",
    "for opp in ['Q1','Q2','Q3']:\n",
    "    persist_df[opp] = pd.DataFrame({\n",
    "        \"ANS\":[persist[opp][\"ANS\"][\"water\"], persist[opp][\"ANS\"][\"sfc\"], persist[opp][\"ANS\"][\"beach\"], persist[opp][\"ANS\"][\"air\"]],\n",
    "        \"Bunker-C\":[persist[opp][\"Bunker-C\"][\"water\"], persist[opp][\"Bunker-C\"][\"sfc\"], persist[opp][\"Bunker-C\"][\"beach\"], persist[opp][\"Bunker-C\"][\"air\"]],\n",
    "        \"Diesel\":[persist[opp][\"Diesel\"][\"water\"], persist[opp][\"Diesel\"][\"sfc\"], persist[opp][\"Diesel\"][\"beach\"], persist[opp][\"Diesel\"][\"air\"]]\n",
    "        }, \n",
    "        index=[\"water\", \"surface\", \"beach\", \"air\"]\n",
    "    )\n",
    "    persist_df[opp] = persist_df[opp].rename_axis(opp, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "cd806d05-0762-4dd0-9829-002cec779fb4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Q2             ANS   Bunker-C     Diesel\n",
      "water     0.021132   0.000078   0.049216\n",
      "surface   0.636309   0.341071   0.066490\n",
      "beach    18.150134  11.264523  16.996533\n",
      "air       1.693576   1.163776   8.503893\n",
      "[[2.11317052e-02 7.76002149e-05 4.92162097e-02]\n",
      " [6.36309089e-01 3.41070740e-01 6.64895907e-02]\n",
      " [1.81501341e+01 1.12645232e+01 1.69965332e+01]\n",
      " [1.69357583e+00 1.16377621e+00 8.50389329e+00]]\n"
     ]
    }
   ],
   "source": [
    "error_minxx = persist_df['Q2'] - persist_df['Q1']\n",
    "error_maxxx = persist_df['Q3'] - persist_df['Q2']\n",
    "print (error_minxx)\n",
    "print (error_minxx.to_numpy())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "7ca6d9fe-9585-4fee-9b5c-e8a8195e3858",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[2.11317052e-02 6.36309089e-01 1.81501341e+01 1.69357583e+00]\n",
      " [2.50453882e-01 7.58300837e+00 3.39583924e+00 1.28769846e+00]\n",
      " [7.76002149e-05 3.41070740e-01 1.12645232e+01 1.16377621e+00]\n",
      " [2.38240787e-03 5.61651883e+00 3.37988162e+00 3.26644017e+00]\n",
      " [4.92162097e-02 6.64895907e-02 1.69965332e+01 8.50389329e+00]\n",
      " [1.29953371e+00 5.53670112e-01 9.77984958e+00 1.12220080e+01]]\n"
     ]
    }
   ],
   "source": [
    "yerr_reorg = np.zeros((6, 4))\n",
    "for ii in range(0, 6, 2):\n",
    "    jj = int(ii/2)\n",
    "    yerr_reorg[ii] = error_minxx.to_numpy()[:,jj]\n",
    "    yerr_reorg[ii+1] = error_maxxx.to_numpy()[:,jj]\n",
    "print(yerr_reorg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "7de0ab62-0b97-4810-8c73-f0637801082d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1500x1500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1, figsize=(5, 5))\n",
    "persist_df['Q2'].plot(ax=ax,\n",
    "    kind=\"bar\",\n",
    "    color=[MIDOSScolors[\"ANS\"],MIDOSScolors[\"Bunker-C\"],MIDOSScolors[\"Diesel\"]],\n",
    "    legend=False,          \n",
    "    yerr=yerr_reorg, #np.append(error_max, error_min, axis=0), \n",
    "    error_kw=dict(lw=3, capsize=4, capthick=3),\n",
    "    ecolor='lightsteelblue'\n",
    ")\n",
    "ax.set_ylabel(\"Fate (%)\")\n",
    "ax.legend(bbox_to_anchor=(1.5, 1), loc='upper right')\n",
    "ax.set_ylim(0,100)\n",
    "ax.set_yticks([0, 20, 40, 60, 80, 100])\n",
    "ax.set_xticklabels(\n",
    "    [\"water\\ncolumn\", \"water\\nsurface\", \"coast\", \"air\"],\n",
    "    rotation=45\n",
    ")\n",
    "\n",
    "plt.savefig('Fate_ByOilLocation_1panel_MedianErr.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "75ab7463-85d6-4f69-aa59-c98d83ed277f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# For Jose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e93b9435-7662-4651-a733-8ec65e0a311f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from salishsea_tools import river_201702"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "290fe9da-16e3-4062-b0e3-9bdb211f97bc",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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