{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "5712068a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import os\n",
    "import numpy as np\n",
    "import matplotlib as mpl\n",
    "#mpl.use('Agg')\n",
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.cm import get_cmap\n",
    "from matplotlib.gridspec import GridSpec\n",
    "from matplotlib.colors import LightSource\n",
    "from matplotlib.cm import get_cmap\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cf\n",
    "\n",
    "import xarray as xr\n",
    "sys.path.insert(1,'/discover/nobackup/cakelle2/GEOS_CF/Apps/cftools/external/cmcrameri')\n",
    "from cmcrameri import cm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "id": "c04efe55",
   "metadata": {},
   "outputs": [],
   "source": [
    "files = os.listdir('/discover/nobackup/projects/gmao/geos_cf_dev/psturm/graph_benchmark/GCv14.0_GCMv1.17_c90/holding/gcc_cube') \n",
    "path = '/discover/nobackup/projects/gmao/geos_cf_dev/psturm/graph_benchmark/GCv14.0_GCMv1.17_c90/holding/gcc_kpp'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "id": "90a0801e",
   "metadata": {},
   "outputs": [],
   "source": [
    "nc_regrid = xr.open_mfdataset(\n",
    "    path + '/*.nc4',\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "id": "9a19940e",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:             (lon: 360, lat: 181, lev: 72, time: 96)\n",
       "Coordinates:\n",
       "  * lon                 (lon) float64 -180.0 -179.0 -178.0 ... 177.0 178.0 179.0\n",
       "  * lat                 (lat) float64 -90.0 -89.0 -88.0 -87.0 ... 88.0 89.0 90.0\n",
       "  * lev                 (lev) float64 1.0 2.0 3.0 4.0 ... 69.0 70.0 71.0 72.0\n",
       "  * time                (time) datetime64[ns] 2019-07-01T21:15:00 ... 2019-07...\n",
       "Data variables:\n",
       "    KppAccSteps         (time, lev, lat, lon) float32 dask.array&lt;chunksize=(1, 72, 181, 360), meta=np.ndarray&gt;\n",
       "    KppAutoReducerNVAR  (time, lev, lat, lon) float32 dask.array&lt;chunksize=(1, 72, 181, 360), meta=np.ndarray&gt;\n",
       "    KppIntCounts        (time, lev, lat, lon) float32 dask.array&lt;chunksize=(1, 72, 181, 360), meta=np.ndarray&gt;\n",
       "    KppTime             (time, lev, lat, lon) float32 dask.array&lt;chunksize=(1, 72, 181, 360), meta=np.ndarray&gt;\n",
       "    KppTotSteps         (time, lev, lat, lon) float32 dask.array&lt;chunksize=(1, 72, 181, 360), meta=np.ndarray&gt;\n",
       "    Met_SUNCOSmid       (time, lat, lon) float32 dask.array&lt;chunksize=(1, 181, 360), meta=np.ndarray&gt;\n",
       "    SpeciesConc_NO      (time, lev, lat, lon) float32 dask.array&lt;chunksize=(1, 72, 181, 360), meta=np.ndarray&gt;\n",
       "    SpeciesConc_NO2     (time, lev, lat, lon) float32 dask.array&lt;chunksize=(1, 72, 181, 360), meta=np.ndarray&gt;\n",
       "    SpeciesConc_O3      (time, lev, lat, lon) float32 dask.array&lt;chunksize=(1, 72, 181, 360), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    Comment:      NetCDF-4\n",
       "    Contact:      http://gmao.gsfc.nasa.gov\n",
       "    Conventions:  CF\n",
       "    Filename:     gcc_kpp\n",
       "    History:      File written by MAPL_PFIO\n",
       "    Institution:  NASA Global Modeling and Assimilation Office\n",
       "    References:   see MAPL documentation\n",
       "    Source:       GEOSgcm-v10.23.0 experiment_id: GCv14.0_GCMv1.17_c90\n",
       "    Title:        c90_test_run</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-1f031ace-95c5-4bda-ab29-6a15afbd1099' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1f031ace-95c5-4bda-ab29-6a15afbd1099' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 360</li><li><span class='xr-has-index'>lat</span>: 181</li><li><span class='xr-has-index'>lev</span>: 72</li><li><span class='xr-has-index'>time</span>: 96</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-3d749850-8306-450c-ba2d-f89cd168fab2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3d749850-8306-450c-ba2d-f89cd168fab2' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -179.0 ... 178.0 179.0</div><input id='attrs-ac913091-6a0b-4433-9336-71375c6c478a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac913091-6a0b-4433-9336-71375c6c478a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-592938a9-b6e9-4a1a-917a-3faef475b198' class='xr-var-data-in' type='checkbox'><label for='data-592938a9-b6e9-4a1a-917a-3faef475b198' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-180., -179., -178., ...,  177.,  178.,  179.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.0 -88.0 ... 89.0 90.0</div><input id='attrs-dbb7e5c8-b00b-4509-984e-dc94416f982e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dbb7e5c8-b00b-4509-984e-dc94416f982e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-481ced2b-8454-4652-91c9-399fd316501c' class='xr-var-data-in' type='checkbox'><label for='data-481ced2b-8454-4652-91c9-399fd316501c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-90., -89., -88., -87., -86., -85., -84., -83., -82., -81., -80., -79.,\n",
       "       -78., -77., -76., -75., -74., -73., -72., -71., -70., -69., -68., -67.,\n",
       "       -66., -65., -64., -63., -62., -61., -60., -59., -58., -57., -56., -55.,\n",
       "       -54., -53., -52., -51., -50., -49., -48., -47., -46., -45., -44., -43.,\n",
       "       -42., -41., -40., -39., -38., -37., -36., -35., -34., -33., -32., -31.,\n",
       "       -30., -29., -28., -27., -26., -25., -24., -23., -22., -21., -20., -19.,\n",
       "       -18., -17., -16., -15., -14., -13., -12., -11., -10.,  -9.,  -8.,  -7.,\n",
       "        -6.,  -5.,  -4.,  -3.,  -2.,  -1.,   0.,   1.,   2.,   3.,   4.,   5.,\n",
       "         6.,   7.,   8.,   9.,  10.,  11.,  12.,  13.,  14.,  15.,  16.,  17.,\n",
       "        18.,  19.,  20.,  21.,  22.,  23.,  24.,  25.,  26.,  27.,  28.,  29.,\n",
       "        30.,  31.,  32.,  33.,  34.,  35.,  36.,  37.,  38.,  39.,  40.,  41.,\n",
       "        42.,  43.,  44.,  45.,  46.,  47.,  48.,  49.,  50.,  51.,  52.,  53.,\n",
       "        54.,  55.,  56.,  57.,  58.,  59.,  60.,  61.,  62.,  63.,  64.,  65.,\n",
       "        66.,  67.,  68.,  69.,  70.,  71.,  72.,  73.,  74.,  75.,  76.,  77.,\n",
       "        78.,  79.,  80.,  81.,  82.,  83.,  84.,  85.,  86.,  87.,  88.,  89.,\n",
       "        90.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0 3.0 4.0 ... 70.0 71.0 72.0</div><input id='attrs-83f78881-2da6-4407-be1f-b1b40defb65f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-83f78881-2da6-4407-be1f-b1b40defb65f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cfbb52bf-358d-4667-97ba-96f04d9881a1' class='xr-var-data-in' type='checkbox'><label for='data-cfbb52bf-358d-4667-97ba-96f04d9881a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coordinate :</span></dt><dd>eta</dd><dt><span>long_name :</span></dt><dd>vertical level</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>standard_name :</span></dt><dd>model_layers</dd><dt><span>units :</span></dt><dd>layer</dd></dl></div><div class='xr-var-data'><pre>array([ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 13., 14.,\n",
       "       15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28.,\n",
       "       29., 30., 31., 32., 33., 34., 35., 36., 37., 38., 39., 40., 41., 42.,\n",
       "       43., 44., 45., 46., 47., 48., 49., 50., 51., 52., 53., 54., 55., 56.,\n",
       "       57., 58., 59., 60., 61., 62., 63., 64., 65., 66., 67., 68., 69., 70.,\n",
       "       71., 72.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-07-01T21:15:00 ... 2019-07-...</div><input id='attrs-e4c65ff3-138f-4b71-b893-a0548aaefa09' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e4c65ff3-138f-4b71-b893-a0548aaefa09' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8961653b-6357-486f-9aa2-d2ba56d23f9c' class='xr-var-data-in' type='checkbox'><label for='data-8961653b-6357-486f-9aa2-d2ba56d23f9c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>begin_date :</span></dt><dd>20190701</dd><dt><span>begin_time :</span></dt><dd>211500</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>time_increment :</span></dt><dd>1500</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-07-01T21:15:00.000000000&#x27;, &#x27;2019-07-01T21:30:00.000000000&#x27;,\n",
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       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f22f1956-3c0c-4a5e-b954-408f8af8d103' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f22f1956-3c0c-4a5e-b954-408f8af8d103' class='xr-section-summary' >Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>KppAccSteps</span></div><div class='xr-var-dims'>(time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 72, 181, 360), meta=np.ndarray&gt;</div><input id='attrs-3ab98aca-89c8-4a89-986a-daa12264a4e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ab98aca-89c8-4a89-986a-daa12264a4e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf0c220d-20e2-4901-879b-973e5cc04822' class='xr-var-data-in' type='checkbox'><label for='data-bf0c220d-20e2-4901-879b-973e5cc04822' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>fmissing_value :</span></dt><dd>1000000000000000.0</dd><dt><span>long_name :</span></dt><dd>Number of accepted KPP internal timesteps</dd><dt><span>regrid_method :</span></dt><dd>bilinear</dd><dt><span>standard_name :</span></dt><dd>Number of accepted KPP internal timesteps</dd><dt><span>units :</span></dt><dd>count</dd><dt><span>valid_range :</span></dt><dd>[-1.e+15  1.e+15]</dd><dt><span>vmax :</span></dt><dd>1000000000000000.0</dd><dt><span>vmin :</span></dt><dd>-1000000000000000.0</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.68 GiB </td>\n",
       "                        <td> 17.90 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (96, 72, 181, 360) </td>\n",
       "                        <td> (1, 72, 181, 360) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 288 Tasks </td>\n",
       "                        <td> 96 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KppAutoReducerNVAR</span></div><div class='xr-var-dims'>(time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 72, 181, 360), meta=np.ndarray&gt;</div><input id='attrs-6947adc0-8837-4bc6-8441-228b5b06da40' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6947adc0-8837-4bc6-8441-228b5b06da40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d603932d-12db-4801-a9f2-b9013bb8163d' class='xr-var-data-in' type='checkbox'><label for='data-d603932d-12db-4801-a9f2-b9013bb8163d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>fmissing_value :</span></dt><dd>1000000000000000.0</dd><dt><span>long_name :</span></dt><dd>Number of species in auto-reduced mechanism</dd><dt><span>regrid_method :</span></dt><dd>bilinear</dd><dt><span>standard_name :</span></dt><dd>Number of species in auto-reduced mechanism</dd><dt><span>units :</span></dt><dd>count</dd><dt><span>valid_range :</span></dt><dd>[-1.e+15  1.e+15]</dd><dt><span>vmax :</span></dt><dd>1000000000000000.0</dd><dt><span>vmin :</span></dt><dd>-1000000000000000.0</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
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       "                        <td> </td>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.68 GiB </td>\n",
       "                        <td> 17.90 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (96, 72, 181, 360) </td>\n",
       "                        <td> (1, 72, 181, 360) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 288 Tasks </td>\n",
       "                        <td> 96 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KppIntCounts</span></div><div class='xr-var-dims'>(time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 72, 181, 360), meta=np.ndarray&gt;</div><input id='attrs-5a2e5a80-5238-4e44-9cb8-bb569624c99a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a2e5a80-5238-4e44-9cb8-bb569624c99a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c4032622-da8e-45d3-92ff-55af2797f24d' class='xr-var-data-in' type='checkbox'><label for='data-c4032622-da8e-45d3-92ff-55af2797f24d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>fmissing_value :</span></dt><dd>1000000000000000.0</dd><dt><span>long_name :</span></dt><dd>Number of calls to KPP integrator</dd><dt><span>regrid_method :</span></dt><dd>bilinear</dd><dt><span>standard_name :</span></dt><dd>Number of calls to KPP integrator</dd><dt><span>units :</span></dt><dd>count</dd><dt><span>valid_range :</span></dt><dd>[-1.e+15  1.e+15]</dd><dt><span>vmax :</span></dt><dd>1000000000000000.0</dd><dt><span>vmin :</span></dt><dd>-1000000000000000.0</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.68 GiB </td>\n",
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       "                        <td> (96, 72, 181, 360) </td>\n",
       "                        <td> (1, 72, 181, 360) </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 288 Tasks </td>\n",
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       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KppTime</span></div><div class='xr-var-dims'>(time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 72, 181, 360), meta=np.ndarray&gt;</div><input id='attrs-f3c2bd51-d59b-4a52-af45-60f186372648' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f3c2bd51-d59b-4a52-af45-60f186372648' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98d5ca64-031c-4610-a6cd-c10a460004f2' class='xr-var-data-in' type='checkbox'><label for='data-98d5ca64-031c-4610-a6cd-c10a460004f2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>fmissing_value :</span></dt><dd>1000000000000000.0</dd><dt><span>long_name :</span></dt><dd>Time KPP spent in grid box</dd><dt><span>regrid_method :</span></dt><dd>bilinear</dd><dt><span>standard_name :</span></dt><dd>Time KPP spent in grid box</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>valid_range :</span></dt><dd>[-1.e+15  1.e+15]</dd><dt><span>vmax :</span></dt><dd>1000000000000000.0</dd><dt><span>vmin :</span></dt><dd>-1000000000000000.0</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
       "            <table>\n",
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       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.68 GiB </td>\n",
       "                        <td> 17.90 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (96, 72, 181, 360) </td>\n",
       "                        <td> (1, 72, 181, 360) </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 288 Tasks </td>\n",
       "                        <td> 96 Chunks </td>\n",
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       "                        <td> 1.68 GiB </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SpeciesConc_O3</span></div><div class='xr-var-dims'>(time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 72, 181, 360), meta=np.ndarray&gt;</div><input id='attrs-dd884dbf-589c-4ef7-9c5f-cc206f295965' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd884dbf-589c-4ef7-9c5f-cc206f295965' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee61bb2a-9343-4d76-9acc-65747acbdbe9' class='xr-var-data-in' type='checkbox'><label for='data-ee61bb2a-9343-4d76-9acc-65747acbdbe9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>fmissing_value :</span></dt><dd>1000000000000000.0</dd><dt><span>long_name :</span></dt><dd>Dry mixing ratio of species for O3</dd><dt><span>regrid_method :</span></dt><dd>bilinear</dd><dt><span>standard_name :</span></dt><dd>Dry mixing ratio of species for O3</dd><dt><span>units :</span></dt><dd>mol mol-1 dry</dd><dt><span>valid_range :</span></dt><dd>[-1.e+15  1.e+15]</dd><dt><span>vmax :</span></dt><dd>1000000000000000.0</dd><dt><span>vmin :</span></dt><dd>-1000000000000000.0</dd></dl></div><div class='xr-var-data'><table>\n",
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      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:             (lon: 360, lat: 181, lev: 72, time: 96)\n",
       "Coordinates:\n",
       "  * lon                 (lon) float64 -180.0 -179.0 -178.0 ... 177.0 178.0 179.0\n",
       "  * lat                 (lat) float64 -90.0 -89.0 -88.0 -87.0 ... 88.0 89.0 90.0\n",
       "  * lev                 (lev) float64 1.0 2.0 3.0 4.0 ... 69.0 70.0 71.0 72.0\n",
       "  * time                (time) datetime64[ns] 2019-07-01T21:15:00 ... 2019-07...\n",
       "Data variables:\n",
       "    KppAccSteps         (time, lev, lat, lon) float32 dask.array<chunksize=(1, 72, 181, 360), meta=np.ndarray>\n",
       "    KppAutoReducerNVAR  (time, lev, lat, lon) float32 dask.array<chunksize=(1, 72, 181, 360), meta=np.ndarray>\n",
       "    KppIntCounts        (time, lev, lat, lon) float32 dask.array<chunksize=(1, 72, 181, 360), meta=np.ndarray>\n",
       "    KppTime             (time, lev, lat, lon) float32 dask.array<chunksize=(1, 72, 181, 360), meta=np.ndarray>\n",
       "    KppTotSteps         (time, lev, lat, lon) float32 dask.array<chunksize=(1, 72, 181, 360), meta=np.ndarray>\n",
       "    Met_SUNCOSmid       (time, lat, lon) float32 dask.array<chunksize=(1, 181, 360), meta=np.ndarray>\n",
       "    SpeciesConc_NO      (time, lev, lat, lon) float32 dask.array<chunksize=(1, 72, 181, 360), meta=np.ndarray>\n",
       "    SpeciesConc_NO2     (time, lev, lat, lon) float32 dask.array<chunksize=(1, 72, 181, 360), meta=np.ndarray>\n",
       "    SpeciesConc_O3      (time, lev, lat, lon) float32 dask.array<chunksize=(1, 72, 181, 360), meta=np.ndarray>\n",
       "Attributes:\n",
       "    Comment:      NetCDF-4\n",
       "    Contact:      http://gmao.gsfc.nasa.gov\n",
       "    Conventions:  CF\n",
       "    Filename:     gcc_kpp\n",
       "    History:      File written by MAPL_PFIO\n",
       "    Institution:  NASA Global Modeling and Assimilation Office\n",
       "    References:   see MAPL documentation\n",
       "    Source:       GEOSgcm-v10.23.0 experiment_id: GCv14.0_GCMv1.17_c90\n",
       "    Title:        c90_test_run"
      ]
     },
     "execution_count": 191,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nc_regrid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "id": "b3e848f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/gpfsm/dnb32/tdirs/login/discover14.47864.psturm/ipykernel_733/774617048.py:1: DeprecationWarning: Behaviour of argmin/argmax with neither dim nor axis argument will change to return a dict of indices of each dimension. To get a single, flat index, please use np.argmin(da.data) or np.argmax(da.data) instead of da.argmin() or da.argmax().\n",
      "  la_lon = (abs(nc_regrid.variables[\"lon\"][:]- -118.2436 )).argmin()\n",
      "/gpfsm/dnb32/tdirs/login/discover14.47864.psturm/ipykernel_733/774617048.py:2: DeprecationWarning: Behaviour of argmin/argmax with neither dim nor axis argument will change to return a dict of indices of each dimension. To get a single, flat index, please use np.argmin(da.data) or np.argmax(da.data) instead of da.argmin() or da.argmax().\n",
      "  la_lat = (abs(nc_regrid.variables[\"lat\"][:]-34.0522 )).argmin()\n",
      "/gpfsm/dnb32/tdirs/login/discover14.47864.psturm/ipykernel_733/774617048.py:4: DeprecationWarning: Behaviour of argmin/argmax with neither dim nor axis argument will change to return a dict of indices of each dimension. To get a single, flat index, please use np.argmin(da.data) or np.argmax(da.data) instead of da.argmin() or da.argmax().\n",
      "  in_lon = (abs(nc_regrid.variables[\"lon\"][:]- 75)).argmin()\n",
      "/gpfsm/dnb32/tdirs/login/discover14.47864.psturm/ipykernel_733/774617048.py:5: DeprecationWarning: Behaviour of argmin/argmax with neither dim nor axis argument will change to return a dict of indices of each dimension. To get a single, flat index, please use np.argmin(da.data) or np.argmax(da.data) instead of da.argmin() or da.argmax().\n",
      "  in_lat = (abs(nc_regrid.variables[\"lat\"][:]- -5 )).argmin()\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(<xarray.Variable ()>\n",
       " array(34.)\n",
       " Attributes:\n",
       "     long_name:  latitude\n",
       "     units:      degrees_north,\n",
       " <xarray.Variable ()>\n",
       " array(-118.)\n",
       " Attributes:\n",
       "     long_name:  longitude\n",
       "     units:      degrees_east)"
      ]
     },
     "execution_count": 193,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "la_lon = (abs(nc_regrid.variables[\"lon\"][:]- -118.2436 )).argmin()\n",
    "la_lat = (abs(nc_regrid.variables[\"lat\"][:]-34.0522 )).argmin()\n",
    "\n",
    "in_lon = (abs(nc_regrid.variables[\"lon\"][:]- 75)).argmin()\n",
    "in_lat = (abs(nc_regrid.variables[\"lat\"][:]- -5 )).argmin()\n",
    "\n",
    "(nc_regrid.variables[\"lat\"][la_lat],nc_regrid.variables[\"lon\"][la_lon])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "id": "fb5cb854",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<xarray.Variable ()>\n",
       " array(34.)\n",
       " Attributes:\n",
       "     long_name:  latitude\n",
       "     units:      degrees_north,\n",
       " <xarray.Variable ()>\n",
       " array(-118.)\n",
       " Attributes:\n",
       "     long_name:  longitude\n",
       "     units:      degrees_east)"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "id": "05d34313",
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "invalid syntax (940563186.py, line 18)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;36m  Input \u001b[0;32mIn [224]\u001b[0;36m\u001b[0m\n\u001b[0;31m    color = \"red\",\u001b[0m\n\u001b[0m    ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
     ]
    }
   ],
   "source": [
    "lowzenith_la = np.argmin(abs(nc_regrid.variables['Met_SUNCOSmid'][:,la_lat,la_lon].values))\n",
    "\n",
    "maxloc_la = np.argmax(nc_regrid.variables['KppIntCounts'][:,10:71-35,la_lat,la_lon].values)\n",
    "maxloc_la = np.unravel_index(maxloc_la, nc_regrid[\"KppIntCounts\"][:,10:71-35,la_lat,la_lon].shape)\n",
    "\n",
    "\n",
    "maxloc_in = np.argmax(nc_regrid.variables['KppIntCounts'][:,10:71-35,in_lat,in_lon].values)\n",
    "maxloc_in = np.unravel_index(maxloc_in, nc_regrid[\"KppIntCounts\"][:,10:71-35,in_lat,in_lon].shape)\n",
    "\n",
    "fig, axs = plt.subplots(nrows=1, ncols=2,figsize = (8,8))\n",
    "axs[0].plot(nc_regrid.variables['KppIntCounts'][maxloc_la[0],:,la_lat,la_lon].values,(list(range(72,0,-1))),\n",
    "            color = \"orange\",\n",
    "            label=\"cos(SZA) = \"+str(nc_regrid.variables['Met_SUNCOSmid'][maxloc_la[0],la_lat,la_lon].values))\n",
    "axs[0].plot(nc_regrid.variables['KppIntCounts'][maxloc_la[0]+8,:,la_lat,la_lon].values,(list(range(72,0,-1))),\n",
    "            color = \"skyblue\",\n",
    "            label=\"cos(SZA) = \"+str(nc_regrid.variables['Met_SUNCOSmid'][maxloc_la[0]+8,la_lat,la_lon].values))\n",
    "axs[1].plot(nc_regrid.variables['KppIntCounts'][maxloc_in[0],:,in_lat,in_lon].values,(list(range(72,0,-1))),\n",
    "            color = \"red\",\n",
    "            label=\"cos(SZA) = \"+str(nc_regrid.variables['Met_SUNCOSmid'][maxloc_la[0]+8,la_lat,la_lon].values))\n",
    "axs[1].plot(nc_regrid.variables['KppIntCounts'][maxloc_in[0]+8,:,in_lat,in_lon].values,(list(range(72,0,-1))),\n",
    "            color = \"darkblue\",\n",
    "            label=\"cos(SZA) = \"+str(nc_regrid.variables['Met_SUNCOSmid'][maxloc_la[0]+8,la_lat,la_lon].values))\n",
    "fig.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "id": "26175041",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([22.       , 20.686087 , 23.770561 , 30.829704 , 37.605427 ,\n",
       "       37.53905  , 33.102688 , 37.458393 , 40.506664 , 40.52395  ,\n",
       "       35.02663  , 38.24238  , 38.224277 , 43.533836 , 44.9819   ,\n",
       "       43.429962 , 52.816765 , 47.256073 , 41.92841  , 40.394573 ,\n",
       "       40.394573 , 37.394573 , 35.842636 , 32.859917 , 31.376472 ,\n",
       "       31.310099 , 29.734026 , 29.734026 , 28.222588 , 28.222588 ,\n",
       "       28.205303 , 26.688751 , 21.128057 , 21.128057 , 19.710167 ,\n",
       "       18.151922 , 11.394301 , 18.262104 , 11.405824 , 11.405824 ,\n",
       "       18.262104 , 16.721962 , 15.692824 ,  4.534654 ,  6.0181017,\n",
       "       21.279388 , 17.400608 , 25.276075 , 13.923137 , 18.710926 ,\n",
       "       19.73979  , 25.416256 , 18.752892 , 19.583408 , 27.       ,\n",
       "       27.       , 26.930862 , 21.690441 , 27.       , 28.481983 ,\n",
       "       28.516552 , 29.964613 , 30.033106 , 30.033106 , 30.033106 ,\n",
       "       32.860737 , 31.481167 , 42.351418 , 41.340385 , 41.353367 ,\n",
       "       40.35755  , 42.015003 ], dtype=float32)"
      ]
     },
     "execution_count": 195,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nc_regrid.variables['KppIntCounts'][61,:,la_lat,la_lon].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "id": "e6998aa6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(61, 6)"
      ]
     },
     "execution_count": 211,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "maxloc_la"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "id": "5f11d602",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "52.816765"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.max(nc_regrid.variables['KppIntCounts'][:,10:71-35,la_lat,la_lon].values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "8475c8ee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([35.02663 , 38.24238 , 38.224277, 43.533836, 44.9819  , 43.429962,\n",
       "       52.816765, 47.256073, 41.92841 , 40.394573, 40.394573, 37.394573,\n",
       "       35.842636, 32.859917, 31.376472, 31.310099, 29.734026, 29.734026,\n",
       "       28.222588, 28.222588, 28.205303, 26.688751, 21.128057, 21.128057,\n",
       "       19.710167, 18.151922], dtype=float32)"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nc_regrid.variables['KppIntCounts'][26+12*4-13,10:71-35,la_lat,la_lon].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "907f3054",
   "metadata": {},
   "outputs": [],
   "source": [
    "nc_regrid.variables['KppIntCounts'].max()\n",
    "\n",
    "maxloc = np.argmax(nc_regrid[\"KppIntCounts\"].values)\n",
    "maxloc= np.unravel_index(maxloc, nc_regrid[\"KppIntCounts\"].shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "b13fead3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(78.36203, dtype=float32)"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nc_regrid.variables['KppIntCounts'][maxloc].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "fa7547a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 67, 170, 334)"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Met_SUNCOSmid(maxloc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "id": "99a8bb1e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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width=\"750\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fe93c0c3d00>"
      ]
     },
     "execution_count": 196,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(nrows=1, ncols=1,figsize = (7.5,7.5))\n",
    "\n",
    "ymax = np.max(nc_regrid[\"KppIntCounts\"].values)\n",
    "ymin = 0\n",
    "\n",
    "subtitles = [\"\"]\n",
    "axs.scatter(np.ndarray.flatten(nc_regrid[\"Met_SUNCOSmid\"].values[0:,:,:]),\n",
    "                   np.ndarray.flatten(np.sum(nc_regrid[\"KppIntCounts\"].values[0:,:,:,:],axis=1)), \n",
    "                   s = 0.04, label = \"No P/L\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "21d57deb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
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       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;KppIntCounts&#x27; ()&gt;\n",
       "array(65.75107, dtype=float32)\n",
       "Coordinates:\n",
       "    time     datetime64[ns] 2019-07-02T16:30:00\n",
       "    lon      float64 20.0\n",
       "    lat      float64 -8.0\n",
       "    lev      float64 72.0\n",
       "Attributes:\n",
       "    standard_name:   Number of calls to KPP integrator\n",
       "    long_name:       Number of calls to KPP integrator\n",
       "    units:           count\n",
       "    fmissing_value:  1000000000000000.0\n",
       "    regrid_method:   bilinear\n",
       "    vmax:            1000000000000000.0\n",
       "    vmin:            -1000000000000000.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'KppIntCounts'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-687cc7fd-068e-4c85-a363-8fa4aabfa2c4' class='xr-array-in' type='checkbox' checked><label for='section-687cc7fd-068e-4c85-a363-8fa4aabfa2c4' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>65.75</span></div><div class='xr-array-data'><pre>array(65.75107, dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-fad1fda0-2edc-4448-acc7-75655a1a0253' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fad1fda0-2edc-4448-acc7-75655a1a0253' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-07-02T16:30:00</div><input id='attrs-484729bf-c006-4ed1-a08b-faf97b85d74d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-484729bf-c006-4ed1-a08b-faf97b85d74d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-221db28f-e56e-4c9c-8bea-cda68b98c22b' class='xr-var-data-in' type='checkbox'><label for='data-221db28f-e56e-4c9c-8bea-cda68b98c22b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2019-07-02T16:30:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>20.0</div><input id='attrs-3035d8a8-a3c2-48d2-af09-8a1bae608835' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3035d8a8-a3c2-48d2-af09-8a1bae608835' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-238ba825-2c15-4122-ad10-4b1b2f755134' class='xr-var-data-in' type='checkbox'><label for='data-238ba825-2c15-4122-ad10-4b1b2f755134' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array(20.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-8.0</div><input id='attrs-660bcb63-c247-4408-8749-29bae916bb80' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-660bcb63-c247-4408-8749-29bae916bb80' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84486355-e8ef-4e7a-aed8-bbe10006da1d' class='xr-var-data-in' type='checkbox'><label for='data-84486355-e8ef-4e7a-aed8-bbe10006da1d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array(-8.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>72.0</div><input id='attrs-3a9b51e8-6249-45b3-aab2-fd36c753ff6d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a9b51e8-6249-45b3-aab2-fd36c753ff6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16be999e-19ea-4791-ba82-79fa2228589f' class='xr-var-data-in' type='checkbox'><label for='data-16be999e-19ea-4791-ba82-79fa2228589f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>model_layers</dd><dt><span>long_name :</span></dt><dd>vertical level</dd><dt><span>units :</span></dt><dd>layer</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>coordinate :</span></dt><dd>eta</dd></dl></div><div class='xr-var-data'><pre>array(72.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2ff9220b-f42b-4719-9429-ae677c800a0e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2ff9220b-f42b-4719-9429-ae677c800a0e' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>Number of calls to KPP integrator</dd><dt><span>long_name :</span></dt><dd>Number of calls to KPP integrator</dd><dt><span>units :</span></dt><dd>count</dd><dt><span>fmissing_value :</span></dt><dd>1000000000000000.0</dd><dt><span>regrid_method :</span></dt><dd>bilinear</dd><dt><span>vmax :</span></dt><dd>1000000000000000.0</dd><dt><span>vmin :</span></dt><dd>-1000000000000000.0</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'KppIntCounts' ()>\n",
       "array(65.75107, dtype=float32)\n",
       "Coordinates:\n",
       "    time     datetime64[ns] 2019-07-02T16:30:00\n",
       "    lon      float64 20.0\n",
       "    lat      float64 -8.0\n",
       "    lev      float64 72.0\n",
       "Attributes:\n",
       "    standard_name:   Number of calls to KPP integrator\n",
       "    long_name:       Number of calls to KPP integrator\n",
       "    units:           count\n",
       "    fmissing_value:  1000000000000000.0\n",
       "    regrid_method:   bilinear\n",
       "    vmax:            1000000000000000.0\n",
       "    vmin:            -1000000000000000.0"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "maxloc = np.argmax(nc_regrid[\"KppIntCounts\"].values[2:,30:,:,:])\n",
    "maxloc= np.unravel_index(maxloc, nc_regrid[\"KppIntCounts\"].shape)\n",
    "nc_regrid[\"KppIntCounts\"][maxloc]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "5f222a40",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(77, 71, 82, 200)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "maxloc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e4e90e61",
   "metadata": {},
   "outputs": [],
   "source": []
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