Plot_Hypoxic_Volume.ipynb

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   "execution_count": 1,
   "id": "6e093f07",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import os, subprocess, tarfile\n",
    "from glob import glob\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.gridspec as gridspec\n",
    "import cftime\n",
    "import cartopy\n",
    "import cartopy.crs as ccrs\n",
    "import scipy.stats as stats\n",
    "from scipy.io import loadmat\n",
    "\n",
    "import string\n",
    "alphabet=list(string.ascii_lowercase)\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bd069287",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.colors as colors\n",
    "class MidpointNormalize(colors.Normalize):\n",
    "    def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):\n",
    "        self.midpoint = midpoint\n",
    "        super().__init__(vmin, vmax, clip)\n",
    "\n",
    "    def __call__(self, value, clip=None):\n",
    "        # I'm ignoring masked values and all kinds of edge cases to make a\n",
    "        # simple example...\n",
    "        x, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1]\n",
    "        return np.ma.masked_array(np.interp(value, x, y))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c42d72f",
   "metadata": {},
   "source": [
    "# Read in Files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d099ff54",
   "metadata": {},
   "outputs": [],
   "source": [
    "cases=['gzCOBALT-013022','gzCOBALT-tun','gzCOBALT-hp','gzCOBALT-tun_hp']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cbf04ca4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'gzCOBALT-013022': ['data/hypoxicVolume.gzCOBALT-013022.nc',\n",
       "  'data/hypoxicVolume.gzCOBALT-013022_cy2.nc',\n",
       "  'data/hypoxicVolume.gzCOBALT-013022_cy3.nc',\n",
       "  'data/hypoxicVolume.gzCOBALT-013022_cy4.nc',\n",
       "  'data/hypoxicVolume.gzCOBALT-013022_cy5.nc'],\n",
       " 'gzCOBALT-tun': ['data/hypoxicVolume.gzCOBALT-tun_cy1.nc',\n",
       "  'data/hypoxicVolume.gzCOBALT-tun_cy2.nc',\n",
       "  'data/hypoxicVolume.gzCOBALT-tun_cy3.nc',\n",
       "  'data/hypoxicVolume.gzCOBALT-tun_cy4.nc',\n",
       "  'data/hypoxicVolume.gzCOBALT-tun_cy5.nc'],\n",
       " 'gzCOBALT-hp': ['data/hypoxicVolume.gzCOBALT-hp_cy1.nc',\n",
       "  'data/hypoxicVolume.gzCOBALT-hp_cy2.nc',\n",
       "  'data/hypoxicVolume.gzCOBALT-hp_cy3.nc',\n",
       "  'data/hypoxicVolume.gzCOBALT-hp_cy4.nc',\n",
       "  'data/hypoxicVolume.gzCOBALT-hp_cy5.nc'],\n",
       " 'gzCOBALT-tun_hp': ['data/hypoxicVolume.gzCOBALT-tun_hp_cy1.nc',\n",
       "  'data/hypoxicVolume.gzCOBALT-tun_hp_cy2.nc',\n",
       "  'data/hypoxicVolume.gzCOBALT-tun_hp_cy3.nc',\n",
       "  'data/hypoxicVolume.gzCOBALT-tun_hp_cy4.nc',\n",
       "  'data/hypoxicVolume.gzCOBALT-tun_hp_cy5.nc']}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "files={}\n",
    "for case in cases:\n",
    "    prefix=case\n",
    "    if case == 'gzCOBALT-tun':\n",
    "        prefix='gzCOBALT-tun_c'\n",
    "    files[case]=sorted(glob('data/hypoxicVolume.'+prefix+'*.nc'))\n",
    "    \n",
    "files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c53cf21d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# read xarray datasets into a dictionary\n",
    "ds_list={}\n",
    "for case in cases:\n",
    "    filenames=files[case]\n",
    "    ds_list[case]=xr.open_mfdataset(filenames, combine='by_coords')\n",
    "    ds_list[case]=ds_list[case].rename_vars(name_dict={'sub_60mmol':case+'_sub_60mmol',\n",
    "                                                      'sub_5mmol':case+'_sub_5mmol'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c1f0f572",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                     (time: 300)\n",
       "Coordinates:\n",
       "  * time                        (time) int64 1 2 3 4 5 6 ... 296 297 298 299 300\n",
       "Data variables:\n",
       "    gzCOBALT-013022_sub_60mmol  (time) float32 dask.array&lt;chunksize=(60,), meta=np.ndarray&gt;\n",
       "    gzCOBALT-013022_sub_5mmol   (time) float32 dask.array&lt;chunksize=(60,), meta=np.ndarray&gt;\n",
       "    gzCOBALT-hp_sub_60mmol      (time) float32 dask.array&lt;chunksize=(60,), meta=np.ndarray&gt;\n",
       "    gzCOBALT-hp_sub_5mmol       (time) float32 dask.array&lt;chunksize=(60,), meta=np.ndarray&gt;\n",
       "    gzCOBALT-tun_hp_sub_60mmol  (time) float32 dask.array&lt;chunksize=(60,), meta=np.ndarray&gt;\n",
       "    gzCOBALT-tun_hp_sub_5mmol   (time) float32 dask.array&lt;chunksize=(60,), meta=np.ndarray&gt;\n",
       "    gzCOBALT-tun_sub_60mmol     (time) float32 dask.array&lt;chunksize=(60,), meta=np.ndarray&gt;\n",
       "    gzCOBALT-tun_sub_5mmol      (time) float32 dask.array&lt;chunksize=(60,), meta=np.ndarray&gt;</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-c32e53cd-25d1-4c8b-b7f7-7099e811105c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c32e53cd-25d1-4c8b-b7f7-7099e811105c' 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'>time</span>: 300</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-467257b8-34f8-4f23-8ed3-f855c74a8bc2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-467257b8-34f8-4f23-8ed3-f855c74a8bc2' class='xr-section-summary' >Coordinates: <span>(1)</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'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 ... 296 297 298 299 300</div><input id='attrs-9c897a04-fd43-4e9b-b379-78e45fbf1551' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9c897a04-fd43-4e9b-b379-78e45fbf1551' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-082049a1-acd3-4bdd-bfcc-3d9fd8e1c0db' class='xr-var-data-in' type='checkbox'><label for='data-082049a1-acd3-4bdd-bfcc-3d9fd8e1c0db' 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'></dl></div><div class='xr-var-data'><pre>array([  1,   2,   3, ..., 298, 299, 300])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8446bcc6-8054-4c22-a798-f54af352272f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8446bcc6-8054-4c22-a798-f54af352272f' class='xr-section-summary' >Data variables: <span>(8)</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>gzCOBALT-013022_sub_60mmol</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(60,), meta=np.ndarray&gt;</div><input id='attrs-db63100d-5747-405b-8f66-ea30634cbc61' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-db63100d-5747-405b-8f66-ea30634cbc61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6dc8bda4-641e-4233-b7db-476efe62e7f4' class='xr-var-data-in' type='checkbox'><label for='data-6dc8bda4-641e-4233-b7db-476efe62e7f4' 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>name :</span></dt><dd>total hypoxic volume (where O2 &lt; 60mmol)</dd><dt><span>units :</span></dt><dd>cubic meters</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> 1.17 kiB </td>\n",
       "                        <td> 240 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (300,) </td>\n",
       "                        <td> (60,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 15 Tasks </td>\n",
       "                        <td> 5 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "                </tbody>\n",
       "            </table>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gzCOBALT-013022_sub_5mmol</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(60,), meta=np.ndarray&gt;</div><input id='attrs-63df176b-991d-4ab3-add4-ad19d661ff44' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63df176b-991d-4ab3-add4-ad19d661ff44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7234e14-21d4-4e4f-9167-ebfe791d4a42' class='xr-var-data-in' type='checkbox'><label for='data-d7234e14-21d4-4e4f-9167-ebfe791d4a42' 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>name :</span></dt><dd>total suboxic volume (where O2 &lt; 5mmol)</dd><dt><span>units :</span></dt><dd>cubic meters</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> 1.17 kiB </td>\n",
       "                        <td> 240 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (300,) </td>\n",
       "                        <td> (60,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 15 Tasks </td>\n",
       "                        <td> 5 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>\n",
       "        </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gzCOBALT-hp_sub_60mmol</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(60,), meta=np.ndarray&gt;</div><input id='attrs-9bac59de-c6bd-4321-8036-5719f7e2b651' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9bac59de-c6bd-4321-8036-5719f7e2b651' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7959768e-90be-4f19-b407-b3ff014df4ba' class='xr-var-data-in' type='checkbox'><label for='data-7959768e-90be-4f19-b407-b3ff014df4ba' 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>name :</span></dt><dd>total hypoxic volume (where O2 &lt; 60mmol)</dd><dt><span>units :</span></dt><dd>cubic meters</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
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       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.17 kiB </td>\n",
       "                        <td> 240 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (300,) </td>\n",
       "                        <td> (60,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 15 Tasks </td>\n",
       "                        <td> 5 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>\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gzCOBALT-hp_sub_5mmol</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(60,), meta=np.ndarray&gt;</div><input id='attrs-4bf742f0-0186-41c7-8176-50f140972b1d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4bf742f0-0186-41c7-8176-50f140972b1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26c9abf0-0cd1-48f7-bb94-135e9ab8218d' class='xr-var-data-in' type='checkbox'><label for='data-26c9abf0-0cd1-48f7-bb94-135e9ab8218d' 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>name :</span></dt><dd>total suboxic volume (where O2 &lt; 5mmol)</dd><dt><span>units :</span></dt><dd>cubic meters</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> 1.17 kiB </td>\n",
       "                        <td> 240 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (300,) </td>\n",
       "                        <td> (60,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 15 Tasks </td>\n",
       "                        <td> 5 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gzCOBALT-tun_hp_sub_60mmol</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(60,), meta=np.ndarray&gt;</div><input id='attrs-31d03919-51b0-4420-9875-09d08a18ffdb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31d03919-51b0-4420-9875-09d08a18ffdb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54170dd4-e6fa-49f3-afb0-53cacf7b35da' class='xr-var-data-in' type='checkbox'><label for='data-54170dd4-e6fa-49f3-afb0-53cacf7b35da' 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>name :</span></dt><dd>total hypoxic volume (where O2 &lt; 60mmol)</dd><dt><span>units :</span></dt><dd>cubic meters</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> 1.17 kiB </td>\n",
       "                        <td> 240 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (300,) </td>\n",
       "                        <td> (60,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 15 Tasks </td>\n",
       "                        <td> 5 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gzCOBALT-tun_hp_sub_5mmol</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(60,), meta=np.ndarray&gt;</div><input id='attrs-591063d9-8035-4ae7-81f7-9abdc27f66b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-591063d9-8035-4ae7-81f7-9abdc27f66b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9e32d0d-752a-4cd9-a948-79218667e1ce' class='xr-var-data-in' type='checkbox'><label for='data-d9e32d0d-752a-4cd9-a948-79218667e1ce' 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>name :</span></dt><dd>total suboxic volume (where O2 &lt; 5mmol)</dd><dt><span>units :</span></dt><dd>cubic meters</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.17 kiB </td>\n",
       "                        <td> 240 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (300,) </td>\n",
       "                        <td> (60,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 15 Tasks </td>\n",
       "                        <td> 5 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>\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gzCOBALT-tun_sub_60mmol</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(60,), meta=np.ndarray&gt;</div><input id='attrs-3966350e-56d5-4aa6-b840-f84e53696caf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3966350e-56d5-4aa6-b840-f84e53696caf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be8fede4-577a-4e71-85c4-db9d4062d95a' class='xr-var-data-in' type='checkbox'><label for='data-be8fede4-577a-4e71-85c4-db9d4062d95a' 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>name :</span></dt><dd>total hypoxic volume (where O2 &lt; 60mmol)</dd><dt><span>units :</span></dt><dd>cubic meters</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> 1.17 kiB </td>\n",
       "                        <td> 240 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (300,) </td>\n",
       "                        <td> (60,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 15 Tasks </td>\n",
       "                        <td> 5 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gzCOBALT-tun_sub_5mmol</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(60,), meta=np.ndarray&gt;</div><input id='attrs-e6ad275b-c611-4b1c-a955-eac639535f9e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e6ad275b-c611-4b1c-a955-eac639535f9e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64debc33-4184-420c-aa5e-8c3b20486069' class='xr-var-data-in' type='checkbox'><label for='data-64debc33-4184-420c-aa5e-8c3b20486069' 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>name :</span></dt><dd>total suboxic volume (where O2 &lt; 5mmol)</dd><dt><span>units :</span></dt><dd>cubic meters</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> 1.17 kiB </td>\n",
       "                        <td> 240 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (300,) </td>\n",
       "                        <td> (60,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 15 Tasks </td>\n",
       "                        <td> 5 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>\n",
       "        </td>\n",
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       "\n",
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       "\n",
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       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
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       "\n",
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       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >300</text>\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-6b3541ce-966e-4fc5-a822-b5bdbef11c4f' class='xr-section-summary-in' type='checkbox'  ><label for='section-6b3541ce-966e-4fc5-a822-b5bdbef11c4f' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8b38fd31-de89-4154-9d13-758f8b5d0a9c' class='xr-index-data-in' type='checkbox'/><label for='index-8b38fd31-de89-4154-9d13-758f8b5d0a9c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([  1,   2,   3,   4,   5,   6,   7,   8,   9,  10,\n",
       "            ...\n",
       "            291, 292, 293, 294, 295, 296, 297, 298, 299, 300],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;time&#x27;, length=300))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9c2cb377-2b03-4e66-9cfa-0add22e30e07' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9c2cb377-2b03-4e66-9cfa-0add22e30e07' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                     (time: 300)\n",
       "Coordinates:\n",
       "  * time                        (time) int64 1 2 3 4 5 6 ... 296 297 298 299 300\n",
       "Data variables:\n",
       "    gzCOBALT-013022_sub_60mmol  (time) float32 dask.array<chunksize=(60,), meta=np.ndarray>\n",
       "    gzCOBALT-013022_sub_5mmol   (time) float32 dask.array<chunksize=(60,), meta=np.ndarray>\n",
       "    gzCOBALT-hp_sub_60mmol      (time) float32 dask.array<chunksize=(60,), meta=np.ndarray>\n",
       "    gzCOBALT-hp_sub_5mmol       (time) float32 dask.array<chunksize=(60,), meta=np.ndarray>\n",
       "    gzCOBALT-tun_hp_sub_60mmol  (time) float32 dask.array<chunksize=(60,), meta=np.ndarray>\n",
       "    gzCOBALT-tun_hp_sub_5mmol   (time) float32 dask.array<chunksize=(60,), meta=np.ndarray>\n",
       "    gzCOBALT-tun_sub_60mmol     (time) float32 dask.array<chunksize=(60,), meta=np.ndarray>\n",
       "    gzCOBALT-tun_sub_5mmol      (time) float32 dask.array<chunksize=(60,), meta=np.ndarray>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pull into one\n",
    "ds = xr.combine_by_coords([ds_list['gzCOBALT-013022'],\n",
    "                           ds_list['gzCOBALT-tun'],\n",
    "                           ds_list['gzCOBALT-hp'],\n",
    "                           ds_list['gzCOBALT-tun_hp']])\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f69e70b",
   "metadata": {},
   "source": [
    "# Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7ccf06cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "colors=['#000000', '#05A8AA', '#D7B49E', '#BC412B']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c42b3a58",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x396 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(2,1, figsize=(12,5.5))\n",
    "fig.subplots_adjust(hspace=0.5)\n",
    "\n",
    "# hypoxic\n",
    "field1a = ds['gzCOBALT-013022_sub_60mmol'] / 1e9\n",
    "field1b = ds['gzCOBALT-tun_sub_60mmol'] / 1e9\n",
    "#field1c = ds['gzCOBALT-hp_sub_60mmol'] / 1e9\n",
    "#field1d = ds['gzCOBALT-tun_hp_sub_60mmol'] / 1e9\n",
    "\n",
    "ax1.plot(field1a.values, c=colors[0])\n",
    "#ax1.plot(field1b.values, c=colors[1])\n",
    "#ax1.plot(field1c.values, c=colors[2])\n",
    "#ax1.plot(field1d.values, c=colors[3])\n",
    "\n",
    "ax1.legend(['GZ-COBALT Ctrl','Tunicate fast POC','Fish fast POC', 'Tunicate & Fish fast POC'])\n",
    "ax1.set_title('Total Hypoxic Volume (km$^{3}$)')\n",
    "ax1.set_ylabel('O2 $\\leq$ 60 mmol m$^{-3}$')\n",
    "\n",
    "# suboxic\n",
    "field2a = ds['gzCOBALT-013022_sub_5mmol'] / 1e9\n",
    "#field2b = ds['gzCOBALT-tun_sub_5mmol'] / 1e9\n",
    "#field2c = ds['gzCOBALT-hp_sub_5mmol'] / 1e9\n",
    "#field2d = ds['gzCOBALT-tun_hp_sub_5mmol'] / 1e9\n",
    "\n",
    "ax2.plot(field2a.values, c=colors[0])\n",
    "#ax2.plot(field2b.values, c=colors[1])\n",
    "#ax2.plot(field2c.values, c=colors[2])\n",
    "#ax2.plot(field2d.values, c=colors[3])\n",
    "\n",
    "ax2.set_ylabel('O2 $\\leq$ 5 mmol m$^{-3}$')\n",
    "ax2.set_xlabel('Simulation Year')\n",
    "ax2.set_title('Total Suboxic Volume (km$^{3}$)')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig('plots/Hypoxic_Suboxic_Volume_ts_01.png', dpi=300, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7fd93c18",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x396 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(2,1, figsize=(12,5.5))\n",
    "fig.subplots_adjust(hspace=0.5)\n",
    "\n",
    "# hypoxic\n",
    "field1a = ds['gzCOBALT-013022_sub_60mmol'] / 1e9\n",
    "field1b = ds['gzCOBALT-tun_sub_60mmol'] / 1e9\n",
    "#field1c = ds['gzCOBALT-hp_sub_60mmol'] / 1e9\n",
    "#field1d = ds['gzCOBALT-tun_hp_sub_60mmol'] / 1e9\n",
    "\n",
    "ax1.plot(field1a.values, c=colors[0])\n",
    "ax1.plot(field1b.values, c=colors[1])\n",
    "#ax1.plot(field1c.values, c=colors[2])\n",
    "#ax1.plot(field1d.values, c=colors[3])\n",
    "\n",
    "ax1.legend(['GZ-COBALT Ctrl','Tunicate fast POC','Fish fast POC', 'Tunicate & Fish fast POC'])\n",
    "ax1.set_title('Total Hypoxic Volume (km$^{3}$)')\n",
    "ax1.set_ylabel('O2 $\\leq$ 60 mmol m$^{-3}$')\n",
    "\n",
    "# suboxic\n",
    "field2a = ds['gzCOBALT-013022_sub_5mmol'] / 1e9\n",
    "field2b = ds['gzCOBALT-tun_sub_5mmol'] / 1e9\n",
    "#field2c = ds['gzCOBALT-hp_sub_5mmol'] / 1e9\n",
    "#field2d = ds['gzCOBALT-tun_hp_sub_5mmol'] / 1e9\n",
    "\n",
    "ax2.plot(field2a.values, c=colors[0])\n",
    "ax2.plot(field2b.values, c=colors[1])\n",
    "#ax2.plot(field2c.values, c=colors[2])\n",
    "#ax2.plot(field2d.values, c=colors[3])\n",
    "\n",
    "ax2.set_ylabel('O2 $\\leq$ 5 mmol m$^{-3}$')\n",
    "ax2.set_xlabel('Simulation Year')\n",
    "ax2.set_title('Total Suboxic Volume (km$^{3}$)')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig('plots/Hypoxic_Suboxic_Volume_ts_02.png', dpi=300, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ca38b3b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x396 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(2,1, figsize=(12,5.5))\n",
    "fig.subplots_adjust(hspace=0.5)\n",
    "\n",
    "# hypoxic\n",
    "field1a = ds['gzCOBALT-013022_sub_60mmol'] / 1e9\n",
    "field1b = ds['gzCOBALT-tun_sub_60mmol'] / 1e9\n",
    "field1c = ds['gzCOBALT-hp_sub_60mmol'] / 1e9\n",
    "#field1d = ds['gzCOBALT-tun_hp_sub_60mmol'] / 1e9\n",
    "\n",
    "ax1.plot(field1a.values, c=colors[0])\n",
    "ax1.plot(field1b.values, c=colors[1])\n",
    "ax1.plot(field1c.values, c=colors[2])\n",
    "#ax1.plot(field1d.values, c=colors[3])\n",
    "\n",
    "ax1.legend(['GZ-COBALT Ctrl','Tunicate fast POC','Fish fast POC', 'Tunicate & Fish fast POC'])\n",
    "ax1.set_title('Total Hypoxic Volume (km$^{3}$)')\n",
    "ax1.set_ylabel('O2 $\\leq$ 60 mmol m$^{-3}$')\n",
    "\n",
    "# suboxic\n",
    "field2a = ds['gzCOBALT-013022_sub_5mmol'] / 1e9\n",
    "field2b = ds['gzCOBALT-tun_sub_5mmol'] / 1e9\n",
    "field2c = ds['gzCOBALT-hp_sub_5mmol'] / 1e9\n",
    "#field2d = ds['gzCOBALT-tun_hp_sub_5mmol'] / 1e9\n",
    "\n",
    "ax2.plot(field2a.values, c=colors[0])\n",
    "ax2.plot(field2b.values, c=colors[1])\n",
    "ax2.plot(field2c.values, c=colors[2])\n",
    "#ax2.plot(field2d.values, c=colors[3])\n",
    "\n",
    "ax2.set_ylabel('O2 $\\leq$ 5 mmol m$^{-3}$')\n",
    "ax2.set_xlabel('Simulation Year')\n",
    "ax2.set_title('Total Suboxic Volume (km$^{3}$)')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig('plots/Hypoxic_Suboxic_Volume_ts_03.png', dpi=300, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "18447ba5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x396 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(2,1, figsize=(12,5.5))\n",
    "fig.subplots_adjust(hspace=0.5)\n",
    "\n",
    "# hypoxic\n",
    "field1a = ds['gzCOBALT-013022_sub_60mmol'] / 1e9\n",
    "field1b = ds['gzCOBALT-tun_sub_60mmol'] / 1e9\n",
    "field1c = ds['gzCOBALT-hp_sub_60mmol'] / 1e9\n",
    "field1d = ds['gzCOBALT-tun_hp_sub_60mmol'] / 1e9\n",
    "\n",
    "ax1.plot(field1a.values, c=colors[0])\n",
    "ax1.plot(field1b.values, c=colors[1])\n",
    "ax1.plot(field1c.values, c=colors[2])\n",
    "ax1.plot(field1d.values, c=colors[3])\n",
    "\n",
    "ax1.text(-0.05, 1.08, 'D', transform=ax1.transAxes, fontsize=15, fontweight='bold', va='top')\n",
    "\n",
    "ax1.legend(['GZ-COBALT Ctrl','Tunicate fast POC','Fish fast POC', 'Tunicate & Fish fast POC'])\n",
    "ax1.set_title('Total Hypoxic Volume (km$^{3}$)')\n",
    "ax1.set_ylabel('O2 $\\leq$ 60 mmol m$^{-3}$')\n",
    "\n",
    "# suboxic\n",
    "field2a = ds['gzCOBALT-013022_sub_5mmol'] / 1e9\n",
    "field2b = ds['gzCOBALT-tun_sub_5mmol'] / 1e9\n",
    "field2c = ds['gzCOBALT-hp_sub_5mmol'] / 1e9\n",
    "field2d = ds['gzCOBALT-tun_hp_sub_5mmol'] / 1e9\n",
    "\n",
    "ax2.plot(field2a.values, c=colors[0])\n",
    "ax2.plot(field2b.values, c=colors[1])\n",
    "ax2.plot(field2c.values, c=colors[2])\n",
    "ax2.plot(field2d.values, c=colors[3])\n",
    "\n",
    "ax2.text(-0.05, 1.08, 'E', transform=ax2.transAxes, fontsize=15, fontweight='bold', va='top')\n",
    "\n",
    "ax2.set_ylabel('O2 $\\leq$ 5 mmol m$^{-3}$')\n",
    "ax2.set_xlabel('Simulation Year')\n",
    "ax2.set_title('Total Suboxic Volume (km$^{3}$)')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig('plots/Hypoxic_Suboxic_Volume_ts_all.png', dpi=350, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "cb09624a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax2 = plt.subplots(1,1, figsize=(12,3))\n",
    "fig.subplots_adjust(hspace=0.5)\n",
    "\n",
    "# suboxic\n",
    "field2a = ds['gzCOBALT-013022_sub_5mmol'] / 1e9\n",
    "field2d = ds['gzCOBALT-tun_hp_sub_5mmol'] / 1e9\n",
    "\n",
    "ax2.plot(field2a.values,c=colors[0])\n",
    "ax2.plot(field2d.values,c=colors[3])\n",
    "\n",
    "ax2.legend(['GZ-COBALT Control', 'Fast-sinking Tunicate + Fish POC'],fontsize=14)\n",
    "ax2.set_ylabel('O$_2$ $\\leq$ 5 mmol m$^{-3}$')\n",
    "ax2.set_xlabel('Simulation Year')\n",
    "ax2.set_title('Total Suboxic (O$_2$ $\\leq$ 5 mmol m$^{-3}$) Volume (km$^{3}$)', fontsize=16)\n",
    "\n",
    "plt.savefig('plots/Suboxic_Volume_ts_extremes.png', dpi=300, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "770d15a0",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}