{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Evolution of the 1D model implementation : with acidity\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import xarray as xr\n",
    "\n",
    "from seapopym.configuration.acidity import (\n",
    "    AcidityConfiguration,\n",
    "    ForcingParameter,\n",
    "    FunctionalGroupParameter,\n",
    "    FunctionalGroupUnit,\n",
    "    FunctionalTypeParameter,\n",
    ")\n",
    "from seapopym.configuration.no_transport import (\n",
    "    ForcingUnit,\n",
    "    MigratoryTypeParameter,\n",
    ")\n",
    "from seapopym.model import AcidityModel\n",
    "from seapopym.standard import coordinates\n",
    "from seapopym.standard.units import StandardUnitsLabels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generating data for the 1D simulation\n",
    "\n",
    "Let's generate some data for the 1D simulation. In this NoTransport model, only temperature and primary production are required. The temperature is generated as a sine wave with a period of 1 year and the primary production is randomly generated.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 900x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "time_axis = coordinates.new_time(pd.date_range(\"2000-01-01\", \"2001-01-01\", freq=\"D\"))\n",
    "n = int(time_axis.size)\n",
    "t = np.linspace(0, 1, n)\n",
    "temperature = np.ones_like(t) * 15\n",
    "acidity = 15 + 15 * np.cos(2 * np.pi * t)\n",
    "\n",
    "temperature = xr.DataArray(\n",
    "    dims=[\"time\", \"latitude\", \"longitude\", \"layer\"],\n",
    "    coords={\n",
    "        \"time\": coordinates.new_time(pd.date_range(\"2000-01-01\", \"2001-01-01\", freq=\"D\")),\n",
    "        \"latitude\": coordinates.new_latitude([0]),\n",
    "        \"longitude\": coordinates.new_longitude([0]),\n",
    "        \"layer\": coordinates.new_layer([0]),\n",
    "    },\n",
    "    attrs={\"units\": StandardUnitsLabels.temperature},\n",
    "    data=temperature[:, np.newaxis, np.newaxis, np.newaxis],\n",
    ")\n",
    "\n",
    "plt.figure(figsize=(9, 3))\n",
    "temperature[:, 0, 0].cf.plot.line(x=\"T\")\n",
    "plt.title(\"Temperature\")\n",
    "plt.show()\n",
    "\n",
    "acidity = xr.DataArray(\n",
    "    dims=[\"time\", \"latitude\", \"longitude\", \"layer\"],\n",
    "    coords={\n",
    "        \"time\": coordinates.new_time(pd.date_range(\"2000-01-01\", \"2001-01-01\", freq=\"D\")),\n",
    "        \"latitude\": coordinates.new_latitude([0]),\n",
    "        \"longitude\": coordinates.new_longitude([0]),\n",
    "        \"layer\": coordinates.new_layer([0]),\n",
    "    },\n",
    "    attrs={\"units\": StandardUnitsLabels.acidity},\n",
    "    data=acidity[:, np.newaxis, np.newaxis, np.newaxis],\n",
    ")\n",
    "\n",
    "plt.figure(figsize=(9, 3))\n",
    "acidity[:, 0, 0].cf.plot.line(x=\"T\")\n",
    "plt.title(\"Acidity\")\n",
    "plt.show()\n",
    "\n",
    "primary_production = xr.DataArray(\n",
    "    dims=[\"time\", \"latitude\", \"longitude\"],\n",
    "    coords={\n",
    "        \"time\": coordinates.new_time(pd.date_range(\"2000-01-01\", \"2001-01-01\", freq=\"D\")),\n",
    "        \"latitude\": coordinates.new_latitude([0]),\n",
    "        \"longitude\": coordinates.new_longitude([0]),\n",
    "    },\n",
    "    attrs={\"units\": StandardUnitsLabels.production},\n",
    "    data=np.random.rand(367, 1, 1),\n",
    ")\n",
    "\n",
    "plt.figure(figsize=(9, 3))\n",
    "primary_production.plot()\n",
    "plt.title(\"Primary Production\")\n",
    "plt.show()\n",
    "\n",
    "dataset = xr.Dataset({\"temperature\": temperature, \"primary_production\": primary_production, \"acidity\": acidity})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initialize the model\n",
    "\n",
    "First we set up the model parameters. We will define a single functional group with the commonly used parameters for the zooplankton in Seapodym LMTL.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "  --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",
       "html[data-theme=\"dark\"],\n",
       "body[data-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 0 20px 0 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "  height: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 13kB\n",
       "Dimensions:                     (time: 367, latitude: 1, longitude: 1,\n",
       "                                 layer: 1, functional_group: 2, cohort: 11)\n",
       "Coordinates:\n",
       "  * time                        (time) datetime64[ns] 3kB 2000-01-01 ... 2001...\n",
       "  * latitude                    (latitude) int64 8B 0\n",
       "  * longitude                   (longitude) int64 8B 0\n",
       "  * layer                       (layer) int64 8B 0\n",
       "  * cohort                      (cohort) int64 88B 0 1 2 3 4 5 6 7 8 9 10\n",
       "  * functional_group            (functional_group) int64 16B 0 1\n",
       "Data variables: (12/21)\n",
       "    temperature                 (time, latitude, longitude, layer) float64 3kB ...\n",
       "    primary_production          (time, latitude, longitude) float64 3kB 0.716...\n",
       "    acidity                     (time, latitude, longitude, layer) float64 3kB ...\n",
       "    name                        (functional_group) &lt;U8 64B &#x27;D0N0&#x27; &#x27;D0N0_BIS&#x27;\n",
       "    energy_transfert            (functional_group) float64 16B 0.1668 0.0834\n",
       "    lambda_temperature_0        (functional_group) float64 16B 0.006667 0.003333\n",
       "    ...                          ...\n",
       "    max_timestep                (functional_group, cohort) float64 176B 1.0 ....\n",
       "    mean_timestep               (functional_group, cohort) float64 176B 1.0 ....\n",
       "    timestep                    float64 8B 1.0\n",
       "    angle_horizon_sun           float64 8B 0.0\n",
       "    compute_initial_conditions  bool 1B False\n",
       "    compute_preproduction       bool 1B False</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-051e5ef1-c935-4034-be7c-9b381bef67ca' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-051e5ef1-c935-4034-be7c-9b381bef67ca' 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>: 367</li><li><span class='xr-has-index'>latitude</span>: 1</li><li><span class='xr-has-index'>longitude</span>: 1</li><li><span class='xr-has-index'>layer</span>: 1</li><li><span class='xr-has-index'>functional_group</span>: 2</li><li><span class='xr-has-index'>cohort</span>: 11</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-2ad8f4a6-892e-4064-87bd-509287688eb4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2ad8f4a6-892e-4064-87bd-509287688eb4' class='xr-section-summary' >Coordinates: <span>(6)</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'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2000-01-01 ... 2001-01-01</div><input id='attrs-b71564b7-1549-402d-a069-f09f5dbd218b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b71564b7-1549-402d-a069-f09f5dbd218b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e06583e6-b5bf-4825-a4d2-c99968f74d6c' class='xr-var-data-in' type='checkbox'><label for='data-e06583e6-b5bf-4825-a4d2-c99968f74d6c' 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>time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2000-01-01T00:00:00.000000000&#x27;, &#x27;2000-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-01-03T00:00:00.000000000&#x27;, ..., &#x27;2000-12-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-12-31T00:00:00.000000000&#x27;, &#x27;2001-01-01T00:00:00.000000000&#x27;],\n",
       "      shape=(367,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-836cffb1-f9ae-44cb-b233-40745cd16b15' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-836cffb1-f9ae-44cb-b233-40745cd16b15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ac8f695-a02c-42a4-9819-c757a8bb93a2' class='xr-var-data-in' type='checkbox'><label for='data-7ac8f695-a02c-42a4-9819-c757a8bb93a2' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-be1ee130-93af-4261-82c6-bf3e401e7f6f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be1ee130-93af-4261-82c6-bf3e401e7f6f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91a3651d-91b0-49d6-84d3-e2de9d8f59ed' class='xr-var-data-in' type='checkbox'><label for='data-91a3651d-91b0-49d6-84d3-e2de9d8f59ed' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>layer</span></div><div class='xr-var-dims'>(layer)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-08467636-3580-444f-8bfe-e67317978227' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-08467636-3580-444f-8bfe-e67317978227' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b23fda6-0f0e-466a-a637-5932832ca042' class='xr-var-data-in' type='checkbox'><label for='data-3b23fda6-0f0e-466a-a637-5932832ca042' 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>layer</dd><dt><span>standard_name :</span></dt><dd>layer</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>flag_values :</span></dt><dd>[0]</dd><dt><span>flag_meanings :</span></dt><dd>epipelagic upper-mesopelagic lower-mesopelagic</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cohort</span></div><div class='xr-var-dims'>(cohort)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 7 8 9 10</div><input id='attrs-2eebb2fa-bbf8-4169-abb5-f083444baed2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2eebb2fa-bbf8-4169-abb5-f083444baed2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-826ba227-242e-41db-ac4c-7c6e8ae5f306' class='xr-var-data-in' type='checkbox'><label for='data-826ba227-242e-41db-ac4c-7c6e8ae5f306' 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>cohort</dd><dt><span>standard_name :</span></dt><dd>cohort</dd></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>functional_group</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1</div><input id='attrs-4c52c614-fcc6-44b9-86ef-dc31546745ee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c52c614-fcc6-44b9-86ef-dc31546745ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f76c2ee3-600a-4ca8-8baf-415df0e09365' class='xr-var-data-in' type='checkbox'><label for='data-f76c2ee3-600a-4ca8-8baf-415df0e09365' 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>flag_values :</span></dt><dd>range(0, 2)</dd><dt><span>flag_meanings :</span></dt><dd>D0N0 D0N0_BIS</dd><dt><span>standard_name :</span></dt><dd>functional_group</dd><dt><span>long_name :</span></dt><dd>functional group</dd></dl></div><div class='xr-var-data'><pre>array([0, 1])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5c766c71-febc-41f8-acf6-c3bc2b99a851' class='xr-section-summary-in' type='checkbox'  ><label for='section-5c766c71-febc-41f8-acf6-c3bc2b99a851' class='xr-section-summary' >Data variables: <span>(21)</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>temperature</span></div><div class='xr-var-dims'>(time, latitude, longitude, layer)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>15.0 15.0 15.0 ... 15.0 15.0 15.0</div><input id='attrs-4fb00b4d-7f9f-4500-bb47-c73b46339e35' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4fb00b4d-7f9f-4500-bb47-c73b46339e35' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85a8cf5d-538d-45bd-bf89-71ebc4dda1b9' class='xr-var-data-in' type='checkbox'><label for='data-85a8cf5d-538d-45bd-bf89-71ebc4dda1b9' 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>units :</span></dt><dd>degree_Celsius</dd></dl></div><div class='xr-var-data'><pre>array([[[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "...\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>primary_production</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.7161 0.4075 ... 0.4889 0.9776</div><input id='attrs-7387d00c-d715-4618-9a1d-4dc16fa19ff8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7387d00c-d715-4618-9a1d-4dc16fa19ff8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9537f901-5f71-44b2-85b2-1c59cc81435d' class='xr-var-data-in' type='checkbox'><label for='data-9537f901-5f71-44b2-85b2-1c59cc81435d' 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>units :</span></dt><dd>kilogram / day / meter ** 2</dd></dl></div><div class='xr-var-data'><pre>array([[[0.7160657 ]],\n",
       "\n",
       "       [[0.40752087]],\n",
       "\n",
       "       [[0.4376077 ]],\n",
       "\n",
       "       [[0.20433431]],\n",
       "\n",
       "       [[0.97912897]],\n",
       "\n",
       "       [[0.76427116]],\n",
       "\n",
       "       [[0.80520399]],\n",
       "\n",
       "       [[0.21153023]],\n",
       "\n",
       "       [[0.1510713 ]],\n",
       "\n",
       "       [[0.20603357]],\n",
       "\n",
       "...\n",
       "\n",
       "       [[0.31220196]],\n",
       "\n",
       "       [[0.98725181]],\n",
       "\n",
       "       [[0.92216668]],\n",
       "\n",
       "       [[0.9670813 ]],\n",
       "\n",
       "       [[0.26836333]],\n",
       "\n",
       "       [[0.27605521]],\n",
       "\n",
       "       [[0.4165289 ]],\n",
       "\n",
       "       [[0.37762779]],\n",
       "\n",
       "       [[0.48887636]],\n",
       "\n",
       "       [[0.97762773]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>acidity</span></div><div class='xr-var-dims'>(time, latitude, longitude, layer)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>30.0 30.0 29.99 ... 29.99 30.0 30.0</div><input id='attrs-f2172788-be54-44df-8806-379bbd20122f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f2172788-be54-44df-8806-379bbd20122f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b78a45b0-f722-4b6c-bc18-630768147d9b' class='xr-var-data-in' type='checkbox'><label for='data-b78a45b0-f722-4b6c-bc18-630768147d9b' 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>units :</span></dt><dd>dimensionless</dd></dl></div><div class='xr-var-data'><pre>array([[[[3.00000000e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99977897e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99911595e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99801113e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99646485e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99447755e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99204981e+01]]],\n",
       "\n",
       "...\n",
       "\n",
       "       [[[2.99204981e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99447755e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99646485e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99801113e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99911595e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99977897e+01]]],\n",
       "\n",
       "\n",
       "       [[[3.00000000e+01]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>name</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>&lt;U8</div><div class='xr-var-preview xr-preview'>&#x27;D0N0&#x27; &#x27;D0N0_BIS&#x27;</div><input id='attrs-f9b0ade8-07b5-49d2-b4d7-ea92d96274d8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f9b0ade8-07b5-49d2-b4d7-ea92d96274d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34b9fe02-bb70-43d7-9a99-0d4c43a40c7e' class='xr-var-data-in' type='checkbox'><label for='data-34b9fe02-bb70-43d7-9a99-0d4c43a40c7e' 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([&#x27;D0N0&#x27;, &#x27;D0N0_BIS&#x27;], dtype=&#x27;&lt;U8&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>energy_transfert</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1668 0.0834</div><input id='attrs-672b370b-67d5-4019-b0b4-0897eb0d5cc4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-672b370b-67d5-4019-b0b4-0897eb0d5cc4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a796d57b-0acd-49ba-802e-dc57bb5407c1' class='xr-var-data-in' type='checkbox'><label for='data-a796d57b-0acd-49ba-802e-dc57bb5407c1' 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>units :</span></dt><dd>dimensionless</dd></dl></div><div class='xr-var-data'><pre>array([0.1668, 0.0834])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lambda_temperature_0</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.006667 0.003333</div><input id='attrs-2f93ebf0-700d-4c89-9ce4-1020e6accac2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2f93ebf0-700d-4c89-9ce4-1020e6accac2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-308abcfd-b006-4a62-b776-92bd74065cfe' class='xr-var-data-in' type='checkbox'><label for='data-308abcfd-b006-4a62-b776-92bd74065cfe' 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>units :</span></dt><dd>1 / day</dd></dl></div><div class='xr-var-data'><pre>array([0.00666667, 0.00333333])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gamma_lambda_temperature</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.15 0.075</div><input id='attrs-81ff1cc3-6d0e-4e36-b367-640049fde576' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81ff1cc3-6d0e-4e36-b367-640049fde576' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3dca27c-69d8-49b9-ae83-288d9818e3c4' class='xr-var-data-in' type='checkbox'><label for='data-f3dca27c-69d8-49b9-ae83-288d9818e3c4' 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>units :</span></dt><dd>1 / delta_degree_Celsius</dd></dl></div><div class='xr-var-data'><pre>array([0.15 , 0.075])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tr_0</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>10.38 5.19</div><input id='attrs-4e63fb73-57b9-44f1-a3f0-3782ff8b548c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e63fb73-57b9-44f1-a3f0-3782ff8b548c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2939fc37-ac50-4510-8558-be86ffbfc395' class='xr-var-data-in' type='checkbox'><label for='data-2939fc37-ac50-4510-8558-be86ffbfc395' 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>units :</span></dt><dd>day</dd></dl></div><div class='xr-var-data'><pre>array([10.38,  5.19])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gamma_tr</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.11 -0.055</div><input id='attrs-29e660b4-db29-4d60-84ee-a931b82ddc2a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29e660b4-db29-4d60-84ee-a931b82ddc2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9e83556-ecd2-45ed-a5c0-1e510af9fe39' class='xr-var-data-in' type='checkbox'><label for='data-f9e83556-ecd2-45ed-a5c0-1e510af9fe39' 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>units :</span></dt><dd>1 / delta_degree_Celsius</dd></dl></div><div class='xr-var-data'><pre>array([-0.11 , -0.055])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lambda_acidity_0</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.006667 0.003333</div><input id='attrs-6b8d6fd8-df68-43d6-81e3-54eaad542ae0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6b8d6fd8-df68-43d6-81e3-54eaad542ae0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40a47a6a-3e79-4c83-a25d-30dfc171c788' class='xr-var-data-in' type='checkbox'><label for='data-40a47a6a-3e79-4c83-a25d-30dfc171c788' 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([0.00666667, 0.00333333])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gamma_lambda_acidity</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.15 0.075</div><input id='attrs-e5233357-edfb-4001-a75f-e1a02b3bbc53' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e5233357-edfb-4001-a75f-e1a02b3bbc53' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5ee5f23-b2d2-4d04-bc6d-c5637e339142' class='xr-var-data-in' type='checkbox'><label for='data-b5ee5f23-b2d2-4d04-bc6d-c5637e339142' 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([0.15 , 0.075])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>day_layer</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 0</div><input id='attrs-58f24ae4-aa66-41f3-ac2e-36e81c164d7b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-58f24ae4-aa66-41f3-ac2e-36e81c164d7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-657adb70-6439-44ae-b112-724765fca8ae' class='xr-var-data-in' type='checkbox'><label for='data-657adb70-6439-44ae-b112-724765fca8ae' 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([0, 0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>night_layer</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 0</div><input id='attrs-310f1264-3f29-49b8-975a-a53bd7fba646' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-310f1264-3f29-49b8-975a-a53bd7fba646' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-decef2dc-044b-498e-99ba-167eb0e71fea' class='xr-var-data-in' type='checkbox'><label for='data-decef2dc-044b-498e-99ba-167eb0e71fea' 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([0, 0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>timesteps_number</span></div><div class='xr-var-dims'>(functional_group, cohort)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 1.0 1.0 1.0 ... nan nan nan nan</div><input id='attrs-3ba37288-b573-4f9a-8192-34875f8ea10a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ba37288-b573-4f9a-8192-34875f8ea10a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de70c794-6771-4163-8fcc-6412f8416c4b' class='xr-var-data-in' type='checkbox'><label for='data-de70c794-6771-4163-8fcc-6412f8416c4b' 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>description :</span></dt><dd>The number of timesteps represented in the cohort. If there is no aggregation, all values are equal to 1.</dd><dt><span>units :</span></dt><dd>day</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.],\n",
       "       [ 1.,  1.,  1.,  1.,  1.,  1., nan, nan, nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min_timestep</span></div><div class='xr-var-dims'>(functional_group, cohort)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0 3.0 4.0 ... nan nan nan nan</div><input id='attrs-5286e293-849d-4d77-b1d0-58d6ae7e1bc3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5286e293-849d-4d77-b1d0-58d6ae7e1bc3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e6c849c-e78d-4ada-ad10-0cb8e37732b0' class='xr-var-data-in' type='checkbox'><label for='data-8e6c849c-e78d-4ada-ad10-0cb8e37732b0' 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>description :</span></dt><dd>The minimum timestep index.</dd><dt><span>units :</span></dt><dd>day</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11.],\n",
       "       [ 1.,  2.,  3.,  4.,  5.,  6., nan, nan, nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max_timestep</span></div><div class='xr-var-dims'>(functional_group, cohort)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0 3.0 4.0 ... nan nan nan nan</div><input id='attrs-b5a5ca17-7743-4d0e-aa2a-ca87c73cec19' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b5a5ca17-7743-4d0e-aa2a-ca87c73cec19' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-688dc120-d6ac-46aa-925a-ca8b01ac8e12' class='xr-var-data-in' type='checkbox'><label for='data-688dc120-d6ac-46aa-925a-ca8b01ac8e12' 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>description :</span></dt><dd>The maximum timestep index.</dd><dt><span>units :</span></dt><dd>day</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11.],\n",
       "       [ 1.,  2.,  3.,  4.,  5.,  6., nan, nan, nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean_timestep</span></div><div class='xr-var-dims'>(functional_group, cohort)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0 3.0 4.0 ... nan nan nan nan</div><input id='attrs-cd2812db-a0d4-491d-9143-731ba40b0de0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd2812db-a0d4-491d-9143-731ba40b0de0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a691b7e-2a28-43ae-a560-0b18a653b0fb' class='xr-var-data-in' type='checkbox'><label for='data-2a691b7e-2a28-43ae-a560-0b18a653b0fb' 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>description :</span></dt><dd>The mean timestep index.</dd><dt><span>units :</span></dt><dd>day</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11.],\n",
       "       [ 1.,  2.,  3.,  4.,  5.,  6., nan, nan, nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>timestep</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0</div><input id='attrs-4ee78de2-e5a2-4f00-a3ab-9f38561a4a29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4ee78de2-e5a2-4f00-a3ab-9f38561a4a29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28a147db-e31b-46cb-8d58-eecb38d19e37' class='xr-var-data-in' type='checkbox'><label for='data-28a147db-e31b-46cb-8d58-eecb38d19e37' 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>units :</span></dt><dd>day</dd></dl></div><div class='xr-var-data'><pre>array(1.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_horizon_sun</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-2f32be59-a9c7-47c9-b65a-50dfef968939' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2f32be59-a9c7-47c9-b65a-50dfef968939' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-889fc15b-eba3-4ead-804e-4fe4c918540b' class='xr-var-data-in' type='checkbox'><label for='data-889fc15b-eba3-4ead-804e-4fe4c918540b' 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(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>compute_initial_conditions</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>False</div><input id='attrs-44620eee-e9c6-4c86-9c1f-0ee530cf4d69' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-44620eee-e9c6-4c86-9c1f-0ee530cf4d69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9786950b-a975-4e27-80e9-6940b9a9acab' class='xr-var-data-in' type='checkbox'><label for='data-9786950b-a975-4e27-80e9-6940b9a9acab' 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(False)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>compute_preproduction</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>False</div><input id='attrs-90c15d1e-4001-4d60-969f-fcf1c971b355' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-90c15d1e-4001-4d60-969f-fcf1c971b355' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9442732d-e0fd-45ce-af8c-7b27a429369a' class='xr-var-data-in' type='checkbox'><label for='data-9442732d-e0fd-45ce-af8c-7b27a429369a' 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(False)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cdfc98a1-b776-41fe-9dcf-76d0c2e125e1' class='xr-section-summary-in' type='checkbox'  ><label for='section-cdfc98a1-b776-41fe-9dcf-76d0c2e125e1' class='xr-section-summary' >Indexes: <span>(6)</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><input type='checkbox' disabled/><label></label><input id='index-0851881a-08b1-4b0d-905a-9f8bcb3243d5' class='xr-index-data-in' type='checkbox'/><label for='index-0851881a-08b1-4b0d-905a-9f8bcb3243d5' 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(DatetimeIndex([&#x27;2000-01-01&#x27;, &#x27;2000-01-02&#x27;, &#x27;2000-01-03&#x27;, &#x27;2000-01-04&#x27;,\n",
       "               &#x27;2000-01-05&#x27;, &#x27;2000-01-06&#x27;, &#x27;2000-01-07&#x27;, &#x27;2000-01-08&#x27;,\n",
       "               &#x27;2000-01-09&#x27;, &#x27;2000-01-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2000-12-23&#x27;, &#x27;2000-12-24&#x27;, &#x27;2000-12-25&#x27;, &#x27;2000-12-26&#x27;,\n",
       "               &#x27;2000-12-27&#x27;, &#x27;2000-12-28&#x27;, &#x27;2000-12-29&#x27;, &#x27;2000-12-30&#x27;,\n",
       "               &#x27;2000-12-31&#x27;, &#x27;2001-01-01&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=367, freq=&#x27;D&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-7d361a45-5f7a-4638-a96d-93ddd35aa579' class='xr-index-data-in' type='checkbox'/><label for='index-7d361a45-5f7a-4638-a96d-93ddd35aa579' 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(Index([0], dtype=&#x27;int64&#x27;, name=&#x27;latitude&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-89e32e3c-9bfa-4845-96aa-af3fad8b46f0' class='xr-index-data-in' type='checkbox'/><label for='index-89e32e3c-9bfa-4845-96aa-af3fad8b46f0' 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(Index([0], dtype=&#x27;int64&#x27;, name=&#x27;longitude&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>layer</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-0ec53116-1c36-45a5-9fa1-ee3a6732c902' class='xr-index-data-in' type='checkbox'/><label for='index-0ec53116-1c36-45a5-9fa1-ee3a6732c902' 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(Index([0], dtype=&#x27;int64&#x27;, name=&#x27;layer&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>cohort</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-b9ae4a37-ec9a-45bd-beac-6afa1f9b6b89' class='xr-index-data-in' type='checkbox'/><label for='index-b9ae4a37-ec9a-45bd-beac-6afa1f9b6b89' 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(Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10], dtype=&#x27;int64&#x27;, name=&#x27;cohort&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>functional_group</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-c9cc8527-9af9-4428-856b-e7af09dd8318' class='xr-index-data-in' type='checkbox'/><label for='index-c9cc8527-9af9-4428-856b-e7af09dd8318' 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(Index([0, 1], dtype=&#x27;int64&#x27;, name=&#x27;functional_group&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a1505f50-0c1c-4827-9099-599fe8afc90f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a1505f50-0c1c-4827-9099-599fe8afc90f' 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> Size: 13kB\n",
       "Dimensions:                     (time: 367, latitude: 1, longitude: 1,\n",
       "                                 layer: 1, functional_group: 2, cohort: 11)\n",
       "Coordinates:\n",
       "  * time                        (time) datetime64[ns] 3kB 2000-01-01 ... 2001...\n",
       "  * latitude                    (latitude) int64 8B 0\n",
       "  * longitude                   (longitude) int64 8B 0\n",
       "  * layer                       (layer) int64 8B 0\n",
       "  * cohort                      (cohort) int64 88B 0 1 2 3 4 5 6 7 8 9 10\n",
       "  * functional_group            (functional_group) int64 16B 0 1\n",
       "Data variables: (12/21)\n",
       "    temperature                 (time, latitude, longitude, layer) float64 3kB ...\n",
       "    primary_production          (time, latitude, longitude) float64 3kB 0.716...\n",
       "    acidity                     (time, latitude, longitude, layer) float64 3kB ...\n",
       "    name                        (functional_group) <U8 64B 'D0N0' 'D0N0_BIS'\n",
       "    energy_transfert            (functional_group) float64 16B 0.1668 0.0834\n",
       "    lambda_temperature_0        (functional_group) float64 16B 0.006667 0.003333\n",
       "    ...                          ...\n",
       "    max_timestep                (functional_group, cohort) float64 176B 1.0 ....\n",
       "    mean_timestep               (functional_group, cohort) float64 176B 1.0 ....\n",
       "    timestep                    float64 8B 1.0\n",
       "    angle_horizon_sun           float64 8B 0.0\n",
       "    compute_initial_conditions  bool 1B False\n",
       "    compute_preproduction       bool 1B False"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "day_layer = 0\n",
    "night_layer = 0\n",
    "tr_0 = 10.38\n",
    "gamma_tr = -0.11\n",
    "lambda_temperature_0 = 1 / 150\n",
    "gamma_lambda_temperature = 0.15\n",
    "lambda_acidity_0 = 1 / 150\n",
    "gamma_lambda_acidity = 0.15\n",
    "\n",
    "f_groups = FunctionalGroupParameter(\n",
    "    functional_group=[\n",
    "        FunctionalGroupUnit(\n",
    "            name=f\"D{day_layer}N{night_layer}\",\n",
    "            energy_transfert=0.1668,\n",
    "            migratory_type=MigratoryTypeParameter(day_layer=day_layer, night_layer=night_layer),\n",
    "            functional_type=FunctionalTypeParameter(\n",
    "                lambda_temperature_0=lambda_temperature_0,\n",
    "                gamma_lambda_temperature=gamma_lambda_temperature,\n",
    "                lambda_acidity_0=lambda_acidity_0,\n",
    "                gamma_lambda_acidity=gamma_lambda_acidity,\n",
    "                tr_0=tr_0,\n",
    "                gamma_tr=gamma_tr,\n",
    "            ),\n",
    "        ),\n",
    "        FunctionalGroupUnit(\n",
    "            name=f\"D{day_layer}N{night_layer}_BIS\",\n",
    "            energy_transfert=0.1668 / 2,\n",
    "            migratory_type=MigratoryTypeParameter(day_layer=day_layer, night_layer=night_layer),\n",
    "            functional_type=FunctionalTypeParameter(\n",
    "                lambda_temperature_0=lambda_temperature_0 / 2,\n",
    "                gamma_lambda_temperature=gamma_lambda_temperature / 2,\n",
    "                lambda_acidity_0=lambda_acidity_0 / 2,\n",
    "                gamma_lambda_acidity=gamma_lambda_acidity / 2,\n",
    "                tr_0=tr_0 / 2,\n",
    "                gamma_tr=gamma_tr / 2,\n",
    "            ),\n",
    "        ),\n",
    "    ]\n",
    ")\n",
    "\n",
    "p_param = ForcingParameter(\n",
    "    temperature=ForcingUnit(forcing=dataset[\"temperature\"]),\n",
    "    primary_production=ForcingUnit(forcing=dataset[\"primary_production\"]),\n",
    "    acidity=ForcingUnit(forcing=dataset[\"acidity\"]),\n",
    ")\n",
    "\n",
    "parameters = AcidityConfiguration(forcing=p_param, functional_group=f_groups)\n",
    "no_transport_model = AcidityModel.from_configuration(configuration=parameters)\n",
    "no_transport_model.state"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'The expected memory usage is 0.06 MB.'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "no_transport_model.expected_memory_usage"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run the model\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  --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",
       "html[data-theme=\"dark\"],\n",
       "body[data-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 0 20px 0 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "  height: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 59kB\n",
       "Dimensions:                       (time: 367, latitude: 1, longitude: 1,\n",
       "                                   functional_group: 2, cohort: 11, layer: 1)\n",
       "Coordinates:\n",
       "  * time                          (time) datetime64[ns] 3kB 2000-01-01 ... 20...\n",
       "  * latitude                      (latitude) int64 8B 0\n",
       "  * longitude                     (longitude) int64 8B 0\n",
       "  * functional_group              (functional_group) int64 16B 0 1\n",
       "  * cohort                        (cohort) int64 88B 0 1 2 3 4 5 6 7 8 9 10\n",
       "  * layer                         (layer) int64 8B 0\n",
       "Data variables: (12/32)\n",
       "    biomass                       (functional_group, time, latitude, longitude) float64 6kB ...\n",
       "    recruited                     (functional_group, time, latitude, longitude) float64 6kB ...\n",
       "    mortality_field               (functional_group, time, latitude, longitude) float64 6kB ...\n",
       "    mask_temperature              (functional_group, time, latitude, longitude, cohort) bool 8kB ...\n",
       "    min_temperature               (functional_group, cohort) float64 176B 21....\n",
       "    primary_production_by_fgroup  (functional_group, time, latitude, longitude) float64 6kB ...\n",
       "    ...                            ...\n",
       "    max_timestep                  (functional_group, cohort) float64 176B 1.0...\n",
       "    mean_timestep                 (functional_group, cohort) float64 176B 1.0...\n",
       "    timestep                      float64 8B 1.0\n",
       "    angle_horizon_sun             float64 8B 0.0\n",
       "    compute_initial_conditions    bool 1B False\n",
       "    compute_preproduction         bool 1B False</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-30faab2f-01af-44ba-a7f2-d795cc62e5b1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-30faab2f-01af-44ba-a7f2-d795cc62e5b1' 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>: 367</li><li><span class='xr-has-index'>latitude</span>: 1</li><li><span class='xr-has-index'>longitude</span>: 1</li><li><span class='xr-has-index'>functional_group</span>: 2</li><li><span class='xr-has-index'>cohort</span>: 11</li><li><span class='xr-has-index'>layer</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-405d1d8e-1f11-4d58-9d33-ff199e2bfda3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-405d1d8e-1f11-4d58-9d33-ff199e2bfda3' class='xr-section-summary' >Coordinates: <span>(6)</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'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2000-01-01 ... 2001-01-01</div><input id='attrs-e9c2ea11-16ab-41b3-b8d6-c1875dbef446' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e9c2ea11-16ab-41b3-b8d6-c1875dbef446' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ecbc3bb-21d7-474a-aa79-b52081242c7c' class='xr-var-data-in' type='checkbox'><label for='data-0ecbc3bb-21d7-474a-aa79-b52081242c7c' 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>time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2000-01-01T00:00:00.000000000&#x27;, &#x27;2000-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-01-03T00:00:00.000000000&#x27;, ..., &#x27;2000-12-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-12-31T00:00:00.000000000&#x27;, &#x27;2001-01-01T00:00:00.000000000&#x27;],\n",
       "      shape=(367,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-05c5cf2c-4b01-4974-bf52-3816ebf0522b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-05c5cf2c-4b01-4974-bf52-3816ebf0522b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-348b6bf0-a537-4023-bbaf-d66b6c14066d' class='xr-var-data-in' type='checkbox'><label for='data-348b6bf0-a537-4023-bbaf-d66b6c14066d' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-da210aee-f66c-4a6c-8560-3fd9b5cd8905' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da210aee-f66c-4a6c-8560-3fd9b5cd8905' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7550a00e-a6fd-4097-bcbd-8ec0d4d35925' class='xr-var-data-in' type='checkbox'><label for='data-7550a00e-a6fd-4097-bcbd-8ec0d4d35925' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>functional_group</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1</div><input id='attrs-79467758-a035-43b8-a819-3b264843b343' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79467758-a035-43b8-a819-3b264843b343' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b46dcdb4-c7dd-4195-8b3b-2b36d38e2cae' class='xr-var-data-in' type='checkbox'><label for='data-b46dcdb4-c7dd-4195-8b3b-2b36d38e2cae' 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>flag_values :</span></dt><dd>range(0, 2)</dd><dt><span>flag_meanings :</span></dt><dd>D0N0 D0N0_BIS</dd><dt><span>standard_name :</span></dt><dd>functional_group</dd><dt><span>long_name :</span></dt><dd>functional group</dd></dl></div><div class='xr-var-data'><pre>array([0, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cohort</span></div><div class='xr-var-dims'>(cohort)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 7 8 9 10</div><input id='attrs-0f256021-7694-4b7c-bed4-6ab207481edb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f256021-7694-4b7c-bed4-6ab207481edb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-776ba353-4b1e-4d3e-a3cf-daaa5fc216c0' class='xr-var-data-in' type='checkbox'><label for='data-776ba353-4b1e-4d3e-a3cf-daaa5fc216c0' 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>cohort</dd><dt><span>standard_name :</span></dt><dd>cohort</dd></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>layer</span></div><div class='xr-var-dims'>(layer)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-15620e8c-a25e-44e8-979c-6e20ec8153a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15620e8c-a25e-44e8-979c-6e20ec8153a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18deb077-614a-4f93-9a2e-64c6e9416802' class='xr-var-data-in' type='checkbox'><label for='data-18deb077-614a-4f93-9a2e-64c6e9416802' 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>layer</dd><dt><span>standard_name :</span></dt><dd>layer</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>flag_values :</span></dt><dd>[0]</dd><dt><span>flag_meanings :</span></dt><dd>epipelagic upper-mesopelagic lower-mesopelagic</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c0889782-1dd6-4739-802f-508e90aad9b7' class='xr-section-summary-in' type='checkbox'  ><label for='section-c0889782-1dd6-4739-802f-508e90aad9b7' class='xr-section-summary' >Data variables: <span>(32)</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>biomass</span></div><div class='xr-var-dims'>(functional_group, time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.1194 0.1295 ... 1.201 1.183</div><input id='attrs-f1703a3d-be9c-44a1-8124-c548b6778ff9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1703a3d-be9c-44a1-8124-c548b6778ff9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6dd79e46-d7b8-48d9-bad1-9eb99ae9143e' class='xr-var-data-in' type='checkbox'><label for='data-6dd79e46-d7b8-48d9-bad1-9eb99ae9143e' 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>biomass</dd><dt><span>units :</span></dt><dd>kilogram / meter ** 2</dd><dt><span>description :</span></dt><dd>The biomass of the recruited individuals.</dd></dl></div><div class='xr-var-data'><pre>array([[[[0.        ]],\n",
       "\n",
       "        [[0.11943976]],\n",
       "\n",
       "        [[0.1295486 ]],\n",
       "\n",
       "        [[0.13984475]],\n",
       "\n",
       "        [[0.10634803]],\n",
       "\n",
       "        [[0.21837202]],\n",
       "\n",
       "        [[0.24077014]],\n",
       "\n",
       "        [[0.25953603]],\n",
       "\n",
       "        [[0.17066654]],\n",
       "\n",
       "        [[0.1145179 ]],\n",
       "\n",
       "...\n",
       "\n",
       "        [[1.19915621]],\n",
       "\n",
       "        [[1.20597981]],\n",
       "\n",
       "        [[1.18283435]],\n",
       "\n",
       "        [[1.21685536]],\n",
       "\n",
       "        [[1.24399174]],\n",
       "\n",
       "        [[1.273708  ]],\n",
       "\n",
       "        [[1.24388966]],\n",
       "\n",
       "        [[1.21590364]],\n",
       "\n",
       "        [[1.20076243]],\n",
       "\n",
       "        [[1.18299197]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>recruited</span></div><div class='xr-var-dims'>(functional_group, time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.1194 ... 0.03474 0.03149</div><input id='attrs-1a89c86f-73d5-47d4-8baa-36ebfec36171' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a89c86f-73d5-47d4-8baa-36ebfec36171' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-845690e4-efc6-48e9-86d4-feff4c5d8564' class='xr-var-data-in' type='checkbox'><label for='data-845690e4-efc6-48e9-86d4-feff4c5d8564' 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>production</dd><dt><span>long_name :</span></dt><dd>production</dd><dt><span>units :</span></dt><dd>kilogram / day / meter ** 2</dd></dl></div><div class='xr-var-data'><pre>array([[[[0.        ]],\n",
       "\n",
       "        [[0.11943976]],\n",
       "\n",
       "        [[0.06797448]],\n",
       "\n",
       "        [[0.07299296]],\n",
       "\n",
       "        [[0.03408296]],\n",
       "\n",
       "        [[0.16331871]],\n",
       "\n",
       "        [[0.12748043]],\n",
       "\n",
       "        [[0.13430803]],\n",
       "\n",
       "        [[0.03528324]],\n",
       "\n",
       "        [[0.02519869]],\n",
       "\n",
       "...\n",
       "\n",
       "        [[0.0319838 ]],\n",
       "\n",
       "        [[0.05563904]],\n",
       "\n",
       "        [[0.02603764]],\n",
       "\n",
       "        [[0.0823368 ]],\n",
       "\n",
       "        [[0.0769087 ]],\n",
       "\n",
       "        [[0.08065458]],\n",
       "\n",
       "        [[0.0223815 ]],\n",
       "\n",
       "        [[0.023023  ]],\n",
       "\n",
       "        [[0.03473851]],\n",
       "\n",
       "        [[0.03149416]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mortality_field</span></div><div class='xr-var-dims'>(functional_group, time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5151 0.5152 ... 0.959 0.959</div><input id='attrs-4d58e75c-f2db-4690-9f66-7039d84723ee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4d58e75c-f2db-4690-9f66-7039d84723ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b5a6bc8-5be4-41e4-992e-fb59659f187f' class='xr-var-data-in' type='checkbox'><label for='data-0b5a6bc8-5be4-41e4-992e-fb59659f187f' 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>mortality</dd><dt><span>long_name :</span></dt><dd>mortality coefficient (T, pH)</dd><dt><span>description :</span></dt><dd>Mortality coefficient according to the temperature and acidity (pH).</dd></dl></div><div class='xr-var-data'><pre>array([[[[0.51511465]],\n",
       "\n",
       "        [[0.51521713]],\n",
       "\n",
       "        [[0.51552447]],\n",
       "\n",
       "        [[0.51603632]],\n",
       "\n",
       "        [[0.51675213]],\n",
       "\n",
       "        [[0.51767111]],\n",
       "\n",
       "        [[0.51879226]],\n",
       "\n",
       "        [[0.52011432]],\n",
       "\n",
       "        [[0.52163585]],\n",
       "\n",
       "        [[0.52335513]],\n",
       "\n",
       "...\n",
       "\n",
       "        [[0.95937602]],\n",
       "\n",
       "        [[0.95929184]],\n",
       "\n",
       "        [[0.95921731]],\n",
       "\n",
       "        [[0.95915253]],\n",
       "\n",
       "        [[0.95909758]],\n",
       "\n",
       "        [[0.95905252]],\n",
       "\n",
       "        [[0.95901742]],\n",
       "\n",
       "        [[0.95899232]],\n",
       "\n",
       "        [[0.95897724]],\n",
       "\n",
       "        [[0.95897222]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mask_temperature</span></div><div class='xr-var-dims'>(functional_group, time, latitude, longitude, cohort)</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>False True True ... False False</div><input id='attrs-8607e779-004a-4d30-98ea-d2d1e19ffc47' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8607e779-004a-4d30-98ea-d2d1e19ffc47' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb4b69ab-a5fd-4783-834f-8086a90d57c3' class='xr-var-data-in' type='checkbox'><label for='data-eb4b69ab-a5fd-4783-834f-8086a90d57c3' 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>mask</dd><dt><span>long_name :</span></dt><dd>cohort recruitment mask by functional group</dd><dt><span>description :</span></dt><dd>Mask to recruit a cohort according to the temperature.</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>flag_meanings :</span></dt><dd>0:not recruited, 1:recruited</dd></dl></div><div class='xr-var-data'><pre>array([[[[[False,  True,  True, ...,  True,  True,  True]]],\n",
       "\n",
       "\n",
       "        [[[False,  True,  True, ...,  True,  True,  True]]],\n",
       "\n",
       "\n",
       "        [[[False,  True,  True, ...,  True,  True,  True]]],\n",
       "\n",
       "\n",
       "        ...,\n",
       "\n",
       "\n",
       "        [[[False,  True,  True, ...,  True,  True,  True]]],\n",
       "\n",
       "\n",
       "        [[[False,  True,  True, ...,  True,  True,  True]]],\n",
       "\n",
       "\n",
       "        [[[False,  True,  True, ...,  True,  True,  True]]]],\n",
       "\n",
       "...\n",
       "       [[[[False, False,  True, ..., False, False, False]]],\n",
       "\n",
       "\n",
       "        [[[False, False,  True, ..., False, False, False]]],\n",
       "\n",
       "\n",
       "        [[[False, False,  True, ..., False, False, False]]],\n",
       "\n",
       "\n",
       "        ...,\n",
       "\n",
       "\n",
       "        [[[False, False,  True, ..., False, False, False]]],\n",
       "\n",
       "\n",
       "        [[[False, False,  True, ..., False, False, False]]],\n",
       "\n",
       "\n",
       "        [[[False, False,  True, ..., False, False, False]]]]],\n",
       "      shape=(2, 367, 1, 1, 11))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min_temperature</span></div><div class='xr-var-dims'>(functional_group, cohort)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>21.27 14.97 11.28 ... nan nan nan</div><input id='attrs-3f7095b2-2b10-4b9e-be05-2f17b0236678' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f7095b2-2b10-4b9e-be05-2f17b0236678' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-70a7bfd5-3489-4e4e-ace3-3d96ead67006' class='xr-var-data-in' type='checkbox'><label for='data-70a7bfd5-3489-4e4e-ace3-3d96ead67006' 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>minimum temperature</dd><dt><span>long_name :</span></dt><dd>minimum temperature by cohort</dd><dt><span>description :</span></dt><dd>Minimum temperature to recruit a cohort according to its age.</dd><dt><span>units :</span></dt><dd>degree_Celsius</dd></dl></div><div class='xr-var-data'><pre>array([[21.27164434, 14.97030634, 11.2842599 ,  8.66896833,  6.64039059,\n",
       "         4.9829219 ,  3.58155208,  2.36763033,  1.29687546,  0.33905259,\n",
       "        -0.52740359],\n",
       "       [29.94061268, 17.33793667,  9.96584379,  4.73526066,  0.67810518,\n",
       "        -2.63683222,         nan,         nan,         nan,         nan,\n",
       "                nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>primary_production_by_fgroup</span></div><div class='xr-var-dims'>(functional_group, time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1194 0.06797 ... 0.04077 0.08153</div><input id='attrs-44e624c6-17f8-4fd3-9613-e8693f216964' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-44e624c6-17f8-4fd3-9613-e8693f216964' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-654efef8-708d-493f-b382-89fafaa2ccee' class='xr-var-data-in' type='checkbox'><label for='data-654efef8-708d-493f-b382-89fafaa2ccee' 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>primary production</dd><dt><span>long_name :</span></dt><dd>primary production by functional group</dd><dt><span>description :</span></dt><dd>Primary production by functional group according to their energy transfert coefficient.</dd><dt><span>units :</span></dt><dd>kilogram / day / meter ** 2</dd></dl></div><div class='xr-var-data'><pre>array([[[[0.11943976]],\n",
       "\n",
       "        [[0.06797448]],\n",
       "\n",
       "        [[0.07299296]],\n",
       "\n",
       "        [[0.03408296]],\n",
       "\n",
       "        [[0.16331871]],\n",
       "\n",
       "        [[0.12748043]],\n",
       "\n",
       "        [[0.13430803]],\n",
       "\n",
       "        [[0.03528324]],\n",
       "\n",
       "        [[0.02519869]],\n",
       "\n",
       "        [[0.0343664 ]],\n",
       "\n",
       "...\n",
       "\n",
       "        [[0.02603764]],\n",
       "\n",
       "        [[0.0823368 ]],\n",
       "\n",
       "        [[0.0769087 ]],\n",
       "\n",
       "        [[0.08065458]],\n",
       "\n",
       "        [[0.0223815 ]],\n",
       "\n",
       "        [[0.023023  ]],\n",
       "\n",
       "        [[0.03473851]],\n",
       "\n",
       "        [[0.03149416]],\n",
       "\n",
       "        [[0.04077229]],\n",
       "\n",
       "        [[0.08153415]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_acidity</span></div><div class='xr-var-dims'>(functional_group, time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>30.0 30.0 29.99 ... 29.99 30.0 30.0</div><input id='attrs-55b5538f-dfa6-4da5-8214-f5a23dc27316' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-55b5538f-dfa6-4da5-8214-f5a23dc27316' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08792281-f953-4a56-b64f-ed9edf77ea32' class='xr-var-data-in' type='checkbox'><label for='data-08792281-f953-4a56-b64f-ed9edf77ea32' 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>average acidity (pH) by fonctional group</dd><dt><span>standard_name :</span></dt><dd>sea water acidity (pH)</dd><dt><span>description :</span></dt><dd>Average acidity (pH) by functional group according to their layer position during day and night.</dd><dt><span>units :</span></dt><dd>dimensionless</dd></dl></div><div class='xr-var-data'><pre>array([[[[3.00000000e+01]],\n",
       "\n",
       "        [[2.99977897e+01]],\n",
       "\n",
       "        [[2.99911595e+01]],\n",
       "\n",
       "        [[2.99801113e+01]],\n",
       "\n",
       "        [[2.99646485e+01]],\n",
       "\n",
       "        [[2.99447755e+01]],\n",
       "\n",
       "        [[2.99204981e+01]],\n",
       "\n",
       "        [[2.98918237e+01]],\n",
       "\n",
       "        [[2.98587605e+01]],\n",
       "\n",
       "        [[2.98213184e+01]],\n",
       "\n",
       "...\n",
       "\n",
       "        [[2.98213184e+01]],\n",
       "\n",
       "        [[2.98587605e+01]],\n",
       "\n",
       "        [[2.98918237e+01]],\n",
       "\n",
       "        [[2.99204981e+01]],\n",
       "\n",
       "        [[2.99447755e+01]],\n",
       "\n",
       "        [[2.99646485e+01]],\n",
       "\n",
       "        [[2.99801113e+01]],\n",
       "\n",
       "        [[2.99911595e+01]],\n",
       "\n",
       "        [[2.99977897e+01]],\n",
       "\n",
       "        [[3.00000000e+01]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_temperature</span></div><div class='xr-var-dims'>(functional_group, time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>15.0 15.0 15.0 ... 15.0 15.0 15.0</div><input id='attrs-9ebc079f-29fb-4aaa-8043-0485fb577fa9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ebc079f-29fb-4aaa-8043-0485fb577fa9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4900968-fc4a-4f05-b1e4-21b92c023575' class='xr-var-data-in' type='checkbox'><label for='data-f4900968-fc4a-4f05-b1e4-21b92c023575' 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>average sea temperature by fonctional group</dd><dt><span>standard_name :</span></dt><dd>sea water temperature</dd><dt><span>description :</span></dt><dd>Average temperature by functional group according to their layer position during day and night.</dd><dt><span>units :</span></dt><dd>degree_Celsius</dd></dl></div><div class='xr-var-data'><pre>array([[[[15.]],\n",
       "\n",
       "        [[15.]],\n",
       "\n",
       "        [[15.]],\n",
       "\n",
       "        [[15.]],\n",
       "\n",
       "        [[15.]],\n",
       "\n",
       "        [[15.]],\n",
       "\n",
       "        [[15.]],\n",
       "\n",
       "        [[15.]],\n",
       "\n",
       "        [[15.]],\n",
       "\n",
       "        [[15.]],\n",
       "\n",
       "...\n",
       "\n",
       "        [[15.]],\n",
       "\n",
       "        [[15.]],\n",
       "\n",
       "        [[15.]],\n",
       "\n",
       "        [[15.]],\n",
       "\n",
       "        [[15.]],\n",
       "\n",
       "        [[15.]],\n",
       "\n",
       "        [[15.]],\n",
       "\n",
       "        [[15.]],\n",
       "\n",
       "        [[15.]],\n",
       "\n",
       "        [[15.]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>day_length</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5 0.5 0.5 0.5 ... 0.5 0.5 0.5 0.5</div><input id='attrs-0d6225c3-21b7-46d9-8c2f-a267521f6881' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d6225c3-21b7-46d9-8c2f-a267521f6881' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e0d029e-70dd-4137-bfe3-90bf7886d5a0' class='xr-var-data-in' type='checkbox'><label for='data-0e0d029e-70dd-4137-bfe3-90bf7886d5a0' 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>Day length</dd><dt><span>standard_name :</span></dt><dd>day_length</dd><dt><span>description :</span></dt><dd>Day length at the surface using Forsythe&#x27;s method.</dd><dt><span>units :</span></dt><dd>day</dd></dl></div><div class='xr-var-data'><pre>array([[[0.5]],\n",
       "\n",
       "       [[0.5]],\n",
       "\n",
       "       [[0.5]],\n",
       "\n",
       "       [[0.5]],\n",
       "\n",
       "       [[0.5]],\n",
       "\n",
       "       [[0.5]],\n",
       "\n",
       "       [[0.5]],\n",
       "\n",
       "       [[0.5]],\n",
       "\n",
       "       [[0.5]],\n",
       "\n",
       "       [[0.5]],\n",
       "\n",
       "...\n",
       "\n",
       "       [[0.5]],\n",
       "\n",
       "       [[0.5]],\n",
       "\n",
       "       [[0.5]],\n",
       "\n",
       "       [[0.5]],\n",
       "\n",
       "       [[0.5]],\n",
       "\n",
       "       [[0.5]],\n",
       "\n",
       "       [[0.5]],\n",
       "\n",
       "       [[0.5]],\n",
       "\n",
       "       [[0.5]],\n",
       "\n",
       "       [[0.5]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mask_fgroup</span></div><div class='xr-var-dims'>(functional_group, latitude, longitude)</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>True True</div><input id='attrs-22ef56bf-6a2d-40f1-b82c-b991f81206c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22ef56bf-6a2d-40f1-b82c-b991f81206c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34d6e3ee-c04f-4cc9-b155-c10ecefdd889' class='xr-var-data-in' type='checkbox'><label for='data-34d6e3ee-c04f-4cc9-b155-c10ecefdd889' 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>mask</dd><dt><span>long_name :</span></dt><dd>mask</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>flag_meanings :</span></dt><dd>0:land, 1:ocean</dd></dl></div><div class='xr-var-data'><pre>array([[[ True]],\n",
       "\n",
       "       [[ True]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mask</span></div><div class='xr-var-dims'>(latitude, longitude, layer)</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>True</div><input id='attrs-80a51ae6-5e6a-4701-9c5f-2292a3e7d544' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-80a51ae6-5e6a-4701-9c5f-2292a3e7d544' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-143620a5-199d-4a92-9ee1-8c2adfc297f2' class='xr-var-data-in' type='checkbox'><label for='data-143620a5-199d-4a92-9ee1-8c2adfc297f2' 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>mask</dd><dt><span>long_name :</span></dt><dd>mask</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>flag_meanings :</span></dt><dd>0:land, 1:ocean</dd></dl></div><div class='xr-var-data'><pre>array([[[ True]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>(time, latitude, longitude, layer)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>15.0 15.0 15.0 ... 15.0 15.0 15.0</div><input id='attrs-a29522b3-2987-4b67-9011-bfd4fc62c93d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a29522b3-2987-4b67-9011-bfd4fc62c93d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5740ee36-f9de-46da-88e6-cd4763d460f1' class='xr-var-data-in' type='checkbox'><label for='data-5740ee36-f9de-46da-88e6-cd4763d460f1' 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>units :</span></dt><dd>degree_Celsius</dd></dl></div><div class='xr-var-data'><pre>array([[[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "...\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]],\n",
       "\n",
       "\n",
       "       [[[15.]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>primary_production</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.7161 0.4075 ... 0.4889 0.9776</div><input id='attrs-d06bb609-1d35-4d80-ad59-22c2a62ddc5e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d06bb609-1d35-4d80-ad59-22c2a62ddc5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4122f42c-44fa-47bf-a4fa-6dd416b0dcd1' class='xr-var-data-in' type='checkbox'><label for='data-4122f42c-44fa-47bf-a4fa-6dd416b0dcd1' 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>units :</span></dt><dd>kilogram / day / meter ** 2</dd></dl></div><div class='xr-var-data'><pre>array([[[0.7160657 ]],\n",
       "\n",
       "       [[0.40752087]],\n",
       "\n",
       "       [[0.4376077 ]],\n",
       "\n",
       "       [[0.20433431]],\n",
       "\n",
       "       [[0.97912897]],\n",
       "\n",
       "       [[0.76427116]],\n",
       "\n",
       "       [[0.80520399]],\n",
       "\n",
       "       [[0.21153023]],\n",
       "\n",
       "       [[0.1510713 ]],\n",
       "\n",
       "       [[0.20603357]],\n",
       "\n",
       "...\n",
       "\n",
       "       [[0.31220196]],\n",
       "\n",
       "       [[0.98725181]],\n",
       "\n",
       "       [[0.92216668]],\n",
       "\n",
       "       [[0.9670813 ]],\n",
       "\n",
       "       [[0.26836333]],\n",
       "\n",
       "       [[0.27605521]],\n",
       "\n",
       "       [[0.4165289 ]],\n",
       "\n",
       "       [[0.37762779]],\n",
       "\n",
       "       [[0.48887636]],\n",
       "\n",
       "       [[0.97762773]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>acidity</span></div><div class='xr-var-dims'>(time, latitude, longitude, layer)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>30.0 30.0 29.99 ... 29.99 30.0 30.0</div><input id='attrs-d3f989d0-7f97-4dae-a7e4-9ed317f4afe1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3f989d0-7f97-4dae-a7e4-9ed317f4afe1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-502119d9-23c8-4d53-b8c8-3b690c0123a5' class='xr-var-data-in' type='checkbox'><label for='data-502119d9-23c8-4d53-b8c8-3b690c0123a5' 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>units :</span></dt><dd>dimensionless</dd></dl></div><div class='xr-var-data'><pre>array([[[[3.00000000e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99977897e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99911595e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99801113e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99646485e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99447755e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99204981e+01]]],\n",
       "\n",
       "...\n",
       "\n",
       "       [[[2.99204981e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99447755e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99646485e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99801113e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99911595e+01]]],\n",
       "\n",
       "\n",
       "       [[[2.99977897e+01]]],\n",
       "\n",
       "\n",
       "       [[[3.00000000e+01]]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>name</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>&lt;U8</div><div class='xr-var-preview xr-preview'>&#x27;D0N0&#x27; &#x27;D0N0_BIS&#x27;</div><input id='attrs-11ec0030-5ae8-4409-b034-a2096715f525' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-11ec0030-5ae8-4409-b034-a2096715f525' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e054b1aa-6da3-4303-8c08-f4189bea5f8e' class='xr-var-data-in' type='checkbox'><label for='data-e054b1aa-6da3-4303-8c08-f4189bea5f8e' 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([&#x27;D0N0&#x27;, &#x27;D0N0_BIS&#x27;], dtype=&#x27;&lt;U8&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>energy_transfert</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1668 0.0834</div><input id='attrs-f55b9e59-853f-4901-abce-7e2d1a734a4c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f55b9e59-853f-4901-abce-7e2d1a734a4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2bc821be-e158-4b3b-944f-2d3207a73484' class='xr-var-data-in' type='checkbox'><label for='data-2bc821be-e158-4b3b-944f-2d3207a73484' 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>units :</span></dt><dd>dimensionless</dd></dl></div><div class='xr-var-data'><pre>array([0.1668, 0.0834])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lambda_temperature_0</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.006667 0.003333</div><input id='attrs-a236acce-5ffa-42ff-913f-fa38f09a0fd2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a236acce-5ffa-42ff-913f-fa38f09a0fd2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4884803-79e5-4636-8f74-d524ee881ff5' class='xr-var-data-in' type='checkbox'><label for='data-b4884803-79e5-4636-8f74-d524ee881ff5' 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>units :</span></dt><dd>1 / day</dd></dl></div><div class='xr-var-data'><pre>array([0.00666667, 0.00333333])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gamma_lambda_temperature</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.15 0.075</div><input id='attrs-a534e8b4-309e-4578-9d6a-e300303468f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a534e8b4-309e-4578-9d6a-e300303468f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96475ce3-0b10-4842-b791-c9abadc31572' class='xr-var-data-in' type='checkbox'><label for='data-96475ce3-0b10-4842-b791-c9abadc31572' 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>units :</span></dt><dd>1 / delta_degree_Celsius</dd></dl></div><div class='xr-var-data'><pre>array([0.15 , 0.075])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tr_0</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>10.38 5.19</div><input id='attrs-c2d4b843-c357-4ce7-8044-a53aa62338b7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c2d4b843-c357-4ce7-8044-a53aa62338b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4877b482-e6f7-4596-a2a7-04193d5e8f88' class='xr-var-data-in' type='checkbox'><label for='data-4877b482-e6f7-4596-a2a7-04193d5e8f88' 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>units :</span></dt><dd>day</dd></dl></div><div class='xr-var-data'><pre>array([10.38,  5.19])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gamma_tr</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.11 -0.055</div><input id='attrs-9f7431de-056a-4406-add8-818268f58296' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f7431de-056a-4406-add8-818268f58296' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d02f9af-5d62-4a95-a6d5-d29feaf42963' class='xr-var-data-in' type='checkbox'><label for='data-7d02f9af-5d62-4a95-a6d5-d29feaf42963' 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>units :</span></dt><dd>1 / delta_degree_Celsius</dd></dl></div><div class='xr-var-data'><pre>array([-0.11 , -0.055])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lambda_acidity_0</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.006667 0.003333</div><input id='attrs-391a2578-8667-43ee-9540-e87416177d6b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-391a2578-8667-43ee-9540-e87416177d6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-788ddbd0-aedf-470d-8cb8-f4852878c610' class='xr-var-data-in' type='checkbox'><label for='data-788ddbd0-aedf-470d-8cb8-f4852878c610' 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([0.00666667, 0.00333333])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gamma_lambda_acidity</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.15 0.075</div><input id='attrs-f2efd3f2-2e01-43ef-98a8-b668871473d4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f2efd3f2-2e01-43ef-98a8-b668871473d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b9335d2-d118-40c6-8e97-dfb9becb83db' class='xr-var-data-in' type='checkbox'><label for='data-6b9335d2-d118-40c6-8e97-dfb9becb83db' 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([0.15 , 0.075])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>day_layer</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 0</div><input id='attrs-29a2cb14-2f77-41f7-abe1-ff294ef7000c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-29a2cb14-2f77-41f7-abe1-ff294ef7000c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41743c38-186e-4f05-904a-f984845339e3' class='xr-var-data-in' type='checkbox'><label for='data-41743c38-186e-4f05-904a-f984845339e3' 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([0, 0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>night_layer</span></div><div class='xr-var-dims'>(functional_group)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 0</div><input id='attrs-c5534052-56f5-43a6-a855-9995bbf201c8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c5534052-56f5-43a6-a855-9995bbf201c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fcbefbe5-0149-461c-97ad-ee2510f8b3c1' class='xr-var-data-in' type='checkbox'><label for='data-fcbefbe5-0149-461c-97ad-ee2510f8b3c1' 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([0, 0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>timesteps_number</span></div><div class='xr-var-dims'>(functional_group, cohort)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 1.0 1.0 1.0 ... nan nan nan nan</div><input id='attrs-0ecccc07-e810-49ed-a300-c145dcb1b2a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ecccc07-e810-49ed-a300-c145dcb1b2a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7095e1c7-73ae-49eb-a59f-0fd6aec83250' class='xr-var-data-in' type='checkbox'><label for='data-7095e1c7-73ae-49eb-a59f-0fd6aec83250' 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>description :</span></dt><dd>The number of timesteps represented in the cohort. If there is no aggregation, all values are equal to 1.</dd><dt><span>units :</span></dt><dd>day</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.],\n",
       "       [ 1.,  1.,  1.,  1.,  1.,  1., nan, nan, nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min_timestep</span></div><div class='xr-var-dims'>(functional_group, cohort)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0 3.0 4.0 ... nan nan nan nan</div><input id='attrs-8e468e2e-1e24-4956-817d-c1e3e919ecde' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e468e2e-1e24-4956-817d-c1e3e919ecde' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82b25361-1f40-4a4f-ad33-dc6d4e8207f8' class='xr-var-data-in' type='checkbox'><label for='data-82b25361-1f40-4a4f-ad33-dc6d4e8207f8' 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>description :</span></dt><dd>The minimum timestep index.</dd><dt><span>units :</span></dt><dd>day</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11.],\n",
       "       [ 1.,  2.,  3.,  4.,  5.,  6., nan, nan, nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max_timestep</span></div><div class='xr-var-dims'>(functional_group, cohort)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0 3.0 4.0 ... nan nan nan nan</div><input id='attrs-b2b7a233-bc3d-43be-b86b-1fbe46341c40' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2b7a233-bc3d-43be-b86b-1fbe46341c40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-984e763d-61d9-48a9-b56e-f688a2631135' class='xr-var-data-in' type='checkbox'><label for='data-984e763d-61d9-48a9-b56e-f688a2631135' 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>description :</span></dt><dd>The maximum timestep index.</dd><dt><span>units :</span></dt><dd>day</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11.],\n",
       "       [ 1.,  2.,  3.,  4.,  5.,  6., nan, nan, nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean_timestep</span></div><div class='xr-var-dims'>(functional_group, cohort)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0 3.0 4.0 ... nan nan nan nan</div><input id='attrs-1a93b922-fb20-42da-abf8-ff0202cc9164' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a93b922-fb20-42da-abf8-ff0202cc9164' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-042dbc26-8c7d-4010-9dfa-d6c02cbb0f39' class='xr-var-data-in' type='checkbox'><label for='data-042dbc26-8c7d-4010-9dfa-d6c02cbb0f39' 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>description :</span></dt><dd>The mean timestep index.</dd><dt><span>units :</span></dt><dd>day</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11.],\n",
       "       [ 1.,  2.,  3.,  4.,  5.,  6., nan, nan, nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>timestep</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0</div><input id='attrs-bfe0ec02-3feb-46d2-9bd9-d6c6ce1909d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfe0ec02-3feb-46d2-9bd9-d6c6ce1909d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-666855c7-c710-4530-9232-45aa01c6cf2f' class='xr-var-data-in' type='checkbox'><label for='data-666855c7-c710-4530-9232-45aa01c6cf2f' 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>units :</span></dt><dd>day</dd></dl></div><div class='xr-var-data'><pre>array(1.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_horizon_sun</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-0ab32ec5-d9f2-4a57-baef-29a98d5f4322' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0ab32ec5-d9f2-4a57-baef-29a98d5f4322' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c624bb9c-5092-488c-b1c2-a88ecc7be0f0' class='xr-var-data-in' type='checkbox'><label for='data-c624bb9c-5092-488c-b1c2-a88ecc7be0f0' 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(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>compute_initial_conditions</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>False</div><input id='attrs-0cc63810-6fc4-4638-9a29-1ae08290f9ed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0cc63810-6fc4-4638-9a29-1ae08290f9ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f360cad-9482-481d-b5dd-31bbb0d38b8a' class='xr-var-data-in' type='checkbox'><label for='data-7f360cad-9482-481d-b5dd-31bbb0d38b8a' 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(False)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>compute_preproduction</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>False</div><input id='attrs-cd900819-b6ff-4325-8abb-c6072f70aae5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cd900819-b6ff-4325-8abb-c6072f70aae5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-badf623b-1289-4ee3-8b3b-8bf74ff8a1c7' class='xr-var-data-in' type='checkbox'><label for='data-badf623b-1289-4ee3-8b3b-8bf74ff8a1c7' 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(False)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-475dced4-012b-4735-bbfe-418efae866ca' class='xr-section-summary-in' type='checkbox'  ><label for='section-475dced4-012b-4735-bbfe-418efae866ca' class='xr-section-summary' >Indexes: <span>(6)</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><input type='checkbox' disabled/><label></label><input id='index-74bf0ace-a268-4ccb-8817-b9b0e2736bfa' class='xr-index-data-in' type='checkbox'/><label for='index-74bf0ace-a268-4ccb-8817-b9b0e2736bfa' 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(DatetimeIndex([&#x27;2000-01-01&#x27;, &#x27;2000-01-02&#x27;, &#x27;2000-01-03&#x27;, &#x27;2000-01-04&#x27;,\n",
       "               &#x27;2000-01-05&#x27;, &#x27;2000-01-06&#x27;, &#x27;2000-01-07&#x27;, &#x27;2000-01-08&#x27;,\n",
       "               &#x27;2000-01-09&#x27;, &#x27;2000-01-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2000-12-23&#x27;, &#x27;2000-12-24&#x27;, &#x27;2000-12-25&#x27;, &#x27;2000-12-26&#x27;,\n",
       "               &#x27;2000-12-27&#x27;, &#x27;2000-12-28&#x27;, &#x27;2000-12-29&#x27;, &#x27;2000-12-30&#x27;,\n",
       "               &#x27;2000-12-31&#x27;, &#x27;2001-01-01&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=367, freq=&#x27;D&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-4a3582bc-711c-4db8-aa3e-537b6cba90e8' class='xr-index-data-in' type='checkbox'/><label for='index-4a3582bc-711c-4db8-aa3e-537b6cba90e8' 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(Index([0], dtype=&#x27;int64&#x27;, name=&#x27;latitude&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-7b2af5a2-cd7e-4ed5-a886-1841a1d345bb' class='xr-index-data-in' type='checkbox'/><label for='index-7b2af5a2-cd7e-4ed5-a886-1841a1d345bb' 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(Index([0], dtype=&#x27;int64&#x27;, name=&#x27;longitude&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>functional_group</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-dcf3ce86-6676-4454-b7c1-ec3d41ef75e1' class='xr-index-data-in' type='checkbox'/><label for='index-dcf3ce86-6676-4454-b7c1-ec3d41ef75e1' 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(Index([0, 1], dtype=&#x27;int64&#x27;, name=&#x27;functional_group&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>cohort</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e9f38737-1bdc-44f0-bfd8-277c42c660b2' class='xr-index-data-in' type='checkbox'/><label for='index-e9f38737-1bdc-44f0-bfd8-277c42c660b2' 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(Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10], dtype=&#x27;int64&#x27;, name=&#x27;cohort&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>layer</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-75e65002-ef3d-4ec3-ab9b-782904355f87' class='xr-index-data-in' type='checkbox'/><label for='index-75e65002-ef3d-4ec3-ab9b-782904355f87' 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(Index([0], dtype=&#x27;int64&#x27;, name=&#x27;layer&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cac57862-f589-40d1-a0b3-82cdf09e3327' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cac57862-f589-40d1-a0b3-82cdf09e3327' 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> Size: 59kB\n",
       "Dimensions:                       (time: 367, latitude: 1, longitude: 1,\n",
       "                                   functional_group: 2, cohort: 11, layer: 1)\n",
       "Coordinates:\n",
       "  * time                          (time) datetime64[ns] 3kB 2000-01-01 ... 20...\n",
       "  * latitude                      (latitude) int64 8B 0\n",
       "  * longitude                     (longitude) int64 8B 0\n",
       "  * functional_group              (functional_group) int64 16B 0 1\n",
       "  * cohort                        (cohort) int64 88B 0 1 2 3 4 5 6 7 8 9 10\n",
       "  * layer                         (layer) int64 8B 0\n",
       "Data variables: (12/32)\n",
       "    biomass                       (functional_group, time, latitude, longitude) float64 6kB ...\n",
       "    recruited                     (functional_group, time, latitude, longitude) float64 6kB ...\n",
       "    mortality_field               (functional_group, time, latitude, longitude) float64 6kB ...\n",
       "    mask_temperature              (functional_group, time, latitude, longitude, cohort) bool 8kB ...\n",
       "    min_temperature               (functional_group, cohort) float64 176B 21....\n",
       "    primary_production_by_fgroup  (functional_group, time, latitude, longitude) float64 6kB ...\n",
       "    ...                            ...\n",
       "    max_timestep                  (functional_group, cohort) float64 176B 1.0...\n",
       "    mean_timestep                 (functional_group, cohort) float64 176B 1.0...\n",
       "    timestep                      float64 8B 1.0\n",
       "    angle_horizon_sun             float64 8B 0.0\n",
       "    compute_initial_conditions    bool 1B False\n",
       "    compute_preproduction         bool 1B False"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "no_transport_model.run()\n",
    "no_transport_model.state"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting the results\n",
    "\n",
    "### The biomass evolution over time\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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TgUINgHpfJMzzCIlKXGdkBSExP2OSAAiCIAiCEfCvG6qvp0kLXN0JLO4LdP6HXXXiflx/H2BZP8ApM1DnM337/Drg3BrA+7Te58Y+IGdp4Oou4PJ2oMEIoHiLiMcJCQZCgwA7JyA4EDi7EshXA8iY6zVOWhCE1IgkAIIgCILA2fiVHwGBT4B81YEGXwJz3wTOrQaOzAYq9tb7HZoJBPgBVd4DQgJ1wJ7WBnAtDLgWAkKCgBMLgJuHgOePAY9uwJ4JwJUd+vHH50V8XjtnIFc54PpeYH43DkRvn98FyF0esE8PpLUFgp8Dd47rxKTLPODYPOD4v0CG3MDb64DM+V/v3K9sB3KUBtJljftxBEFINkgCIAiCIAinlwOXtwI2DkDbKUCWgkDDL4ENI4B1w4ECdYDHt4BVH+v9D/0F+D8EAh6HH6PVr8C1vYDnf+HbTi3R/zOQz1NBJwIOLkDhhkDRZkCRxjoJmFYPuHcGsHUESr2pk4jbR6MeKxOT0GB93e82MKcN8M4GIH32uJ07JU+se2AC8O5WwDbuziKCICQPJAEQBEEQUjec0V8/XF+vNVgH/6TaAODcOuDaLj07b2Ont3MW/uFVfT1TfsA+nZbyrBocdr8NUK2fnrU/PFsH6+3/BIo1B/y8AOcs4ccyoMxoz0TAozuQtzJQ+xN9TD6W0h8+Z/YSOiFhoqLGOgQ4uRh4eEVLjLotir1U6cImYMv3+rrXSWDXL0C9MBmUkCrYtm0b6tevH+399erVw9atYZ+5BIBuNv/73//UOHx8fJA1a1ZUrFgRP/30E4oXL55gz5vakQRAEARBSL3cOgIsfR/wvaWD+VphM/yEhXbt/gCmNwzX6nMm/73twOmlQLYSQLEWOuheNwzYP1Xv02Yy4NElPEgPfApkK6pvZ8gR9TgoH2o9Ifx21iL6EpnO/wIbvwIy5NRJQtlOwB91gIub9KpE5b4xP/cn3sAS7m8CclcAbh8BdowDirfS9QisVbCxBxzSx/yYQrKjRo0aqndBZFasWIEPPvgA/fv3T7DnDgoKQuPGjVGsWDEsWbJEedvfvHkTa9euxaNHjxLseQVAStUFQRCElMn1/cCu8XrWPTI3DgCzWwPT6wP3zwPpcwLt/9IFtpa4uAFd52uZDqn5MZC1sC7mLdFKJwlMAJqNBtpMAbosCA/+1ePzhAf/8QEdiVqOA+p8qp83e3Gg0df6vvUjgLue4fte2grMbacThNlvALsnAH53w+9nwfOzh0DOsrqOoFhLXWS8+B3g3FrglxLA7zV1LUNMCA3V9QRCBN92/8DgRL/weWMK+xXkzJkzwuXhw4f49NNPMXz4cHTs2NG87/bt21GlShU4ODioYH3o0KGq67FBQEAABg0ahOzZsyt7ylq1auHgwYPRPvepU6dw6dIlTJkyBdWqVUP+/PlRs2ZNfPfdd+q2wY0bN/DWW28hU6ZMyJIlC9q0aYOrV8NW4QD1HEwkuHrg4uKCunXr4siRIxGeiz0Zpk6diubNmysrzYIFC2LRokUR9vH09ESDBg3U/a6urnjvvffw5MkT8/29e/dG27ZtMWrUKGTLlg0ZM2ZUSRLtOMmcOXPU4/g6WMLH9OjRQ13/+uuv4eHhgRkzZiBfvnxInz69SrLYOXrMmDHq9efr9/33YStzCYSsAAiCIAgpg6DnwKUtQM4yQHCA1soHPQW2jQZqfgTUG6aDZs5s/90eCPBlWACU6QA0H6OlOVHBYtwey7R+v+agqPfhccuziNcKVP0AuLBBS4PmdQXe3QI8vQfM6wIEPwvfj4W+TAI6zgYe39TyIUqL3vgNsHXQKxC3DgP3zgLzOuvHUOq0cSTQevzLxxDwBJjzhk4WmEjl9kjYc04mPAsKQcmv1if6857+pimc7eMW4nHmnQE2pT/ffvutefutW7fQokULFQQz0D179izeffddFegzqCWff/45Fi9ejNmzZ6tgngFt06ZNcfHiRRW4R4ZBNC0tGYh//PHHqolaVKsEPEb16tWxc+dO2NraqgShWbNmOHHihEpg/Pz80KtXL/z2228q+fn555/VWC9cuIAMGcJ7eXz55Zf48ccfMWHCBMydOxedO3dWQX+JEiXw9OlT8/MwofD29kbfvn0xcOBAzJo1y3yMzZs3q3OmZIlJSJ8+fVTQz4CdyRITIK6eGIkTj7N69Wps2LDBfAwmPVzlWLdunbreoUMHXL58GUWLFlVJ1p49e/D222+jUaNGqFq1KhKCNKbYpIkpAF9fX5UdPn78WGVugiAIQjKG0hfPxUBIgLbP9L8P2KXTBbHUxttnAAL9wmfvG4/SEhoGwtlLAV0XAJnyItnDpObPhoDPZSCjm05IHt8ACtQFqg/QgTzrEbxPRXxc9YFAU4uZRr6GLCqmLIiJlLGi0Hs14F4r+udfPhA4Oldft3UC2k8HSrRGauL58+dKz16gQAFzcybOxienBICNzFq1aqUC2/3790cInqnTZ3B/5swZc4djztx/8cUXKqZ69uwZMmfOrILlrl27moN3d3d3Fdx/9tlnUT7n5MmTVeLA4L9SpUqqHqFbt25qhp78/fffKuC3fF7OuHM1YNmyZWjSpEmU58H7//33X3U+hI/lbD1XAQy4ylChQgV1HtOnT1fnwtWGdOnSqfvXrFmD1q1b4/bt28iRI4dKflauXKn2MZq9/f777+rc+BowmeFsPl8/Ppb88ssv6hyZBHEMTJbGjh2Lu3fvml9fJjPnzp1TyYDh8c/6Bz4fV1li8lmLbZwrKwCCIAhC8oM++Azit34XcTulOpz1Z/BP3/1+e7ScZfUQYPd4rfU/s0rv2/CrlBH8E65edJkPzGoF+N7U22gR2mFGuLVn+R7Asg+04xFfm9IdgPr/i3icgnWBDn/p2giumGz4H3B4FrBiENBvd7hE6vYxnWCwAPrq7rDgPw3gVhm4eQBY9DbQcwWQvzpSM052NioYt8bzxgVKfvbu3YsDBw5ECP4JA3DOjhtBOKFchxIZ6va5csCAn9sM2LGWkiE+NjoGDBiAnj17qhn1ffv2YeHChfjhhx/ULDplPcePH1fBc+TxMAhmwEy8vLwwYsQIdQzOuFNO4+/vj+vXr0d4DMcf+faxY8fM51euXDlz8G+cH5MJBudMAAj3sez0zGPwNWBSwFUPropUrlxZrZjkyZNHJUQM5C1fNyZFlufDYzMBsmzwxW08l4RCEgBBEAQh+RD0DFj5MXBmBRDkr7fRaz9HKSCzO1C4MXBgmrbibDQKyJgbqPyO9vfnzL/nQv0YBqpFEz8wS1CyFQM+Oq6bjLE/QaU+EX39WT9A+Q9XCVjwbBNNCFC6vb4QvoZ0QvK5BGz/Sdcb7J8GrI1iNpfyqIYjgYW9dIfj+WFypCwFkFph0BdXKU5iM3/+fIwbN07JVYoUiaIAPQFhMMyZdl44208pDv9nAsDgmq5A//zzT5QSIkL5z4MHD5S0h0E4axQYmBva/MSkfPnyKkmgTIqrE6xz4GtqCROjyJ+TqLYx+UgoksenUhAEQRDIgenAifn6erpsumFXxV4R96kxUF8sYQ1A3mraKYcNtaj5f53uvkkVBvml2+lLVPCc6TgUU5wyAS1/BhZ0A3ZPBB5c0sE9oYSKRcNZiwKF6gMVeuumaG9OAx41B+4cA5Z+APRZo7cLSRbOgr/zzjtKH8/gOyqok6cEiMpxYzZ79+7dKnh3c3NTOnjq8bmNQTjhigD19JQAxRQem/IX6uAJJToLFixQhbHRSVr4nJTxUPdPOBt///79F/bjCgNXGyxvM2A3zo+z9awFMFYBeFzOytOlyIArEpQ7sVDYOAYLefPmDV9NZO3A+PHj1SoAdfyW9yUVxAVIEARBSB4E+muvfNJ8LPDJ+ReD/5eRryrQbhowYL9uyiXEDLodlekImEL0ygvrA2g3SknQwIO6hwFvGysKTEI6/a3rL27sA/b8BnidAo7M0U3VWGcgJBkYKNOlhkW/3bt3V9p0y8u9e/fUftS2M7D+8MMPVQHw8uXLMXLkSAwZMkQFyQya+/Xrp/TwLG49ffq0ksNQisPkIrrEgwXHLALm/pT6/PXXX8ohh9sJ6wHo7sPbLAKm9p1SHxbbUnpEuGLBol7KeFi7wMcYAbollBfx2OfPn1djp9SJRb7G81BPz9WEkydPqt4HPFe69xjyH8JVBZ4Px0udP4/DY1jKd1gDwbGxroDFvEkRWQEQBEEQkgY+V7Q1JXX6lKpEnqk+PFO721C+QnmLxQ+ukMBwVr9cZ+D6Pl1nwRWVl62gsLaiyTe6OdqmkfpisG+Krr+oMSh6GZKQaFCecu3aNXWhtWdkOJvPolbq2RnwMsCnxIWuPgyEqb034AoCZSsMmunMw6Le9evXq+LgqODKAfXwtNXkc3D237g9eLBurEe9/Y4dO1SBbrt27dRxOZaGDRuaVwSYNNCyk6sFnG1nDQFtTCPD41Lq1L9/f3Wu8+bNQ8mSJc3Pw7F+9NFHSsPP2+3bt1dFvJbweZlw1KlTR9l9dunSxeyCZMAiXD6Wry2Tq6SIuAAJgiAI1uf8emBh73Bdv0te7XV/7xxQqAHg7KptPZ8/AlpPjN3Mv2AdGF782wm4sB5wcNF1GpQUndPuKHDKopMK1hnY2iO58zJnFsH6MLlYunTpawXkvXv3VsXOdB96FUwUSpUqhYkTw1Yt4xFxARIEQRBSTmEvg//8tYAnd4EHF4GVH4XPGKe103pzFu+Ws2i0JSRduELQZZ7ut+CYKXzF4NAMYPO3wDMf/d7Skaju5/q+p/d112X32imzRkNI8Tx8+FBJlHhhXUJSRRIAQRAEwbrs/x3wu61n/bsvBvwfAP/1BEKDdYHpqSU6+GdywK68KWC2ONXA4l8G+JZUehso31NLutZ8CmwfA+Stqjsyb/lWNxNr/K12FXriDThkeLFDsyAkUcqXL6+SgJ9++ilC8XBSQyRAgiAIgnUbWE3wAAIeA2/+oSUhkaEM6MZ+XYgqgWDKgeEHOw7TtjQyLCBu/qNeGaJsqPE3QJEmWjaURGs/RAIkJBYiARIEQRCSNzt/1sF/jtI6wI/O354XIWVBiU/LX3RTMa76ZC0CVOgJHJ+nrVqXD9D7sfB7WT99nQlA6/FASe0QIwhC3JAEQBAEQUi8GV+/u7p7LGUdj67rpl2EhaDiFZ/6cMkDDDmtPxuGI1DOssAs7eeOIk2B/DWAfVN1bQjrBigPqzdc1w1InYAgxAlJAARBEITEgX7wG78Mn8mls09IIFCgDlC4obVHJ1iLyImfe02gwQidIDb7SfcVqPUxEBwAbBwJ7J8KbPsBCAnQjeAkCRCEWGNVId3o0aOV1yq7yLHDG62Zzp0799LHsEsbrZwsL6K1EwRBSERuHgZ+q6iLN2NaRvb4FrBtdPhtzuQ+uBA++y9BnGBJnc+AN37Twb+BrYOuC2AXZ0M+ZjSGEwQh+awAbN++HQMGDFBJQHBwMIYPH44mTZqo7mpGG+aoYFGDZaJgtKQWBEEQEpjQEG3PSZvOrd/r27UGA3avmIjZ+JW2+cxXXTv9UON9YQPgWli68gqxo+r7euVowwhg6w+6diRjbmuPShCSFVZNANgqOvLsPlcCDh8+rDqsRQcD/pw5cybCCAVBEAQFg60rO4Fc5QAvT8DGQUswtv+oL/lqAJ3/AZyzRHwcE4Qd44CTi/jtDTSnpCOd1nXzIghxofpA4Oxq4PpevRJVuh3w8Brg0S3JugQJQlIiSf2V0LKIsL30y3jy5IlqTc12z23atMGpU6ei3ZdtmmmJZHkRBEFIFWz7Cfi3M3ByCRASFP1+lPF4nQKCA6O+//ZRrd+/cww4Mltva/Q10PQH3eGVXN+jXVssJUGhocC8LlqvTajjZgIhCK8LV/4bjtTX2U9gdmtgxUB9XRCE5JMAhIaG4uOPP0bNmjVRunTpaPdjU4UZM2Zg+fLl+Pvvv9XjatSogZs3b0ZbZ0A/VOPCpEEQBCHFc+OADrzPrwUW9QGm1QMe3dD3+VzRAf2hmboL7+K+wNQawLgiwNJ+2nHlxkEdwBuJBMleErB1AnJ5AJX7AtUHAEOvAX03Azb2wLk1wPrhuniTnF4KXFivH/PmNJ00CEJ8kb+67g1gCetMAvysNaJkCTvWRq6ttLzUr18/QZ+ffvZdu3ZF7ty5VU2nm5ubmtw9e/Zsgj5vaifJNALr168f1q5di127dqk3P6YEBQWhRIkS6NKlC7799tsoVwB4MeAKAJMAaQQmCEKKxPeOdteZ+yZwbZcO1hmQs+jWOSvg6AL4XArfn7fZeTUqMrppff6ZFUCatMCAg0AmTqKkebEb74HpuqurQeV3gUubAZ/LQP3/actGQYhvntwDjs7RdqH/9dCftzqfAw3+l+hDSa6NwAIDA+Hj4/PC9hUrVuCDDz7AggUL0LFjND06XhMjhuPk7pdffolcuXKpCV3Gg61atUK1atUS5HmTO/HRCCxJrAAMHDgQq1atwtatW2MV/BM7OzvVdvnixYtR3u/g4KBeAMuLIAhCiuT0CuCX4sDYwjr4p06/09/A+zv07L3/fR38M5h3r60TAgb/aW2Bt+YAPVcAtT8FirXUnVh9b+rgn5R5C8haWDuxRA7+CVcE2v6uj0sOTtfBWLrsQLX+ifs6CKmH9NmA2p8AOUuHrzDtnaQT4aQA51gDnyb+JRZzu/b29qqu0vLy8OFDfPrpp8qcxTL4p3lLlSpVVGzFYH3o0KHKxMWAE66DBg1S9ZwMTGvVqoWDBw9G+9yUcF+6dAlTpkxRwT7l3VSCfPfddxGC/xs3buCtt95CpkyZlEycKwRXr14138/naNy4MbJmzaqC37p16+LIkSMRnourGVOnTkXz5s3h5OSEggULYtEi1iaF4+npiQYNGqj7XV1d8d577ynZuUHv3r2VY+WoUaOQLVs2FVMySWISRebMmaMeZznxTPiYHj16qOtff/01PDw8lJolX758SJ8+Pfr374+QkBCMGTNGvf58/b7//nuk2CJgLj58+OGHWLp0qVqCYiYTW/iC8Q1r0SKsaYggCEJqhB7pG8JmPdlZ1wjK1Yw9gHc2AOfWAk6ZgTwVdbGuv49uxEVnnoJ19X7G/0HPgas7Aa+TuktrzY9frcn26KIv59YBS94FAnz1zL9D+gQ7bUEwU+INIG9V4MZ+7VDVZpK1R6Sdr36wgkPR8Nu62D4OPHr0SAXY9erVi6CsuHXrloq1GAQz0KVE591331WBPoNa8vnnn2Px4sWYPXu2CuYZ0DZt2lRN0kZV38kgOm3atCoQpwzcxsYmylUCHqN69erYuXMnbG1tVYLQrFkznDhxQiUwfn5+6NWrF3777TcVW/78889qrBcuXFBW8wZcZfjxxx8xYcIEzJ07F507d1YxJFchnj59an4eJhTe3t7o27evmqSmSY3B5s2b1TkzbmUS0qdPHxX0M2BnssQEiKsnRuLE46xevRobNmwwH4NJD1c5aIbD6x06dMDly5dRtGhRlWTt2bMHb7/9Nho1aoSqVasiQTBZkX79+plcXFxM27ZtM925c8d88ff3N+/To0cP09ChQ823R40aZVq/fr3p0qVLpsOHD5s6d+5scnR0NJ06dSpGz/n48WOmxep/QRCEFMPeKSbTyIwm09iiJtPZtSbTnkkmU2D4d2mi8+iGyXRuvckUGmq9MQipj+v79d/B15lMprsn9bYLm0ymXeNNpusHTKaQ4AR76mfPnplOnz6t/jcT8ESPJ7EvfN44EBISYmrevLmpRIkSJl9f3wj3DR8+3FSsWDFTqMXf9OTJk03p06dXj3vy5InJzs7O9M8//5jvDwwMNOXOnds0ZsyYaJ9z0qRJJmdnZ1OGDBlM9evXN33zzTcqxjOYO3fuC88bEBBgcnJyUvFgdOfB461cudK8jbHfBx98EGG/qlWrqliUTJs2zZQ5c2Z1HgarV682pU2b1nT37l11u1evXqYsWbKYnj59at5n6tSp5teA8Hh8DQ1+/vlnU8GCBc3jHzlypDpfy9e3adOmJnd3d/MxCM959OjRMf+sxTLOteoKAJdiCLNMS2bOnKkyTHL9+nWVHRpwWYoZ5927d5E5c2ZUrFhRZUolS5ZM5NELgiAkIR00rRBJ/WFAsWbWHhHg4qYvgpCY5K0ClGwLnF6m62DyVQNOLw+/v2B9oPuSxLMKtXPWs/GJDZ83DlDys3fvXhw4cCDCzDk5c+aMmh237L1EuQ4lMtTtc+WAs/XcZh6GnZ2SDPGx0cF+UD179lQz6vv27cPChQvxww8/qFl0ynqOHz+uVhAij4c6eM6eEy8vL4wYMUIdgzPuVIf4+/urGNISjj/y7WPHjpnPr1y5chH6UPFcaDbD3lM5cuRQ27iPs7NzhGPwNaBMiasejFHZ34orJnny5FGrB4xpLV83d3f3COfDY3P1wzLe5TaeS4qVAL0KvpmW/Prrr+oiCIIghPnsL35bF/lS5+/R3dojEgTr0uQ74K6nrndRwX8aLW27vg+4vBU4tQQo0yFxxsKgL45SnMRm/vz5GDdunJKrFClSJFGfm8Fw69at1YXyHkpx+D8TAAbXnOz9559/opQQEcp/Hjx4oKQ9DMJZo8DA3NDmJybly5dXSQJlUmxuyzoHvqaWMDGyhMlBVNuYfCQUSaIIWBAEQYgj238CruwA7NIBHWcBNlad1xEE68O6l/57dSJQoI7uPN1zOVAnzKVq8ze6ZkYww1nwd955R+njGXxHBXXyXB2wnLzdvXu3Ct5p4FKoUCGlx+c2A64IUE8fG5UGA9/ixYsrTT6pUKGC0vKzMLZw4cIRLiz4NcZB7T11/6VKlVIJwP379184NlcYIt8uUaKE+fy42mA8r3FczsrTpciA+zx79izCMVjIa2kzz9oBzvxT0UIdf1K0oJcEQBAEIbny+CawK2xF9I2JQLbwHylBSNXQrarGh0CvlUDhhnob3ajS5wQeXdNOQYTB7Mua5KUCGCjTpYZy7O7duyuJteXl3r17aj861VDmQvMWFgCzH9PIkSMxZMgQFSRTOkNL988++0wVt54+fVrJYSjFYXIRXeLBgmMWAXN/Sn3++usv5ZDD7aRbt27K3Ye3WQRM+0uqQxjwGz2guGLBol7KePbv368eQyefyFBexGOfP39ejZ1SJxb5Gs/D4l6uJpw8eVI5U/Jc6d5jyH8IVxV4PhzvmjVr1HF4DEv5DvsacGzTp09XxbxJEZkqEgRBSK4w+A8J1NabiSVpEITkCqU47A+w4kO9CkAL3FPLdALAVYIcqbOWkPKUa9euqQutPSNDSQ3dbqhnZ8DLAJ8SF7r6MBCm9t6AKwiUrTBopjNPpUqVsH79elWzGRVcOaAenraafA7O/hu3Bw8erPah3n7Hjh344osv0K5dO3VcjqVhw4Zma3cmDbTs5GoBZ9tZQ0Ab08jwuJQ69e/fX53rvHnzzKsTfB6O9aOPPlIaft5u3749fvnllwjH4PMy4ahTp46y+2QfKsMFyYArE3wsX1smV0mRJNMILLGIaYMEQRCEJD/7P7G8TgB6rQIKhPnvC4IQPQx51n4BHPgj4vZ02YDeq19rFS25NgJLLTC5oO386wTkvXv3VsXOy5Yte+W+TBQoR5o4cSLimxTTCEwQBEGIBT5XgPndwmf/JfgXhJgX5Tb7Eaj0jnbKqfkRkLMs8PQeMLeddtQShNeAbpVGfys6HCVVRAIkCIKQnLhzApjVSjf7csykCx0FQYg51Gq3+gVoMU5fr+kD/NUYeHARWNQHaDhSy4VSqSRIeH0XICYBP/30U4Ti4aSGJACCIAjJhee+wMJeOvhnN9+Os8M7/QqCEDuMok12xe70D/BnQ939+q9GenvF3kDzMbqgWEj2xIfifZZFR+DoYC1DckAkQIIgCMkB/nitHAT4XAYyugHdFknwLwjxRfbiQLvpQPocgAv/rtIAh2cBU6oB64YDD69Ze4SCEK9IAiAIgpAcoGvJqaVAWlug40w9aykIQvxRvAXw6Xlg8EmdYFNix4R732RgVksgwC9Gh0ll3iqCFYiPz5gkAIIgCEmdQzOAXWFWdK1+BfJWsfaIBCFlU6QR8NExoMNMwCUf8PgGsGmUTgKePoi4b9Bz4P4FcydX+t4LQkJifMYidw+ODVIDIAiCkJR59gjYOFJfr/8/oEJPa49IEFIHTpmB0u30/3PbAgenAwf/BGzsgZ7LgBylgC3fAScWqJ4CNvVHIFO+1vC+chrwzwHnrHmV9aQgxOfMP4N/b29vZMqUCTY2NnE+liQAgiAIiU2gPxDkD6TLGv0+3meBDDmAA9OBAF8ge0mg9ouNbQRBSGAK1deJ95E5DMGAkABg0TtAxtzArUPh+239DjkzzABy1of38+bAo2eArb01Ry6kUDJlyoScOXO+1jGkEZggCEJs4dfmo2taGmDR/j1GXN+vnXzoO175XaDu5xH1/OxKyhl/6o6pQTaF6gSg/V/S7VcQrEVIMHBjP5AhJ/BvJ+DBBb2dqwMsHr6wMUJzsRAbJwSVfku7CAlCPELZz8tm/mMa50oCIAiCEBuu7gY2fqVn/vLXBNpMArIUjH7/+xd1shAaApxfq2cRQ4PD72eQX28YUKmPkhFgYR/g2q6Ix3AtAgzYD6SN+3KvIAjxxF1P4K+mgI0d0GsFkKucTtyXfgDcOwfUHwbM76qdhD48DLgWsvaIhVSEryQAUSMJgCAIcebsmrAfdouvTXYTfWsOUKTxi/t7nwH+qKM79lpSqh1QthOweRTgfVpvc8qiA4onXoB9ep1YPLoBnFwENP4WKFg3gU9OEIQY88QbsHUEHKOJI7hKcH4d4NEdaDs5sUcnpGJ8JQGIGkkABEGIE/QB/6O2nqVnAF99gF4JuLYbSGsHtJkMlH0LMIr+QkOBmc2BG/uA9DkBp0y6eVeZjkDBeno/ygqOzgG2jwX8buvHZS2qmxJlK2rV0xUE4TW4cVA3FEuTFui3V/cZEIREQBKAaJAEQBCEWMNAfUZTLfthEN9nnS7uU8v+7wMnF+v9clcAWowF3CoBh2frxl126YCBBwAXt+iPT3nQxc3A/XO6+6hDhkQ7NUEQEoj53YCzq4BiLYAu88L/1ikNim3tkCDEc5wrn0BBEISoeHAJWD4AuLAJ2PubDv4dXICOs8KdPSjZYQEg3XlsnYDbR4C57YDTK4B1w/Q+9Ye/PPgn1PYXbQLU+FCCf0FIKTT6GkhjA5xbo928TvwHjCkALH3P2iMTBFkBEARBeIHHt/SMP5v/EHbfZeFumylA+W5RP+bJPWBBN+0UYlCgDtB9KWAjjsuCkCpZN1w7ekXm7Q1AvqrWGJGQwvGVFQBBEIQ44HdXN/1h8E+HHsLgv3BjwIMFwNGQPpsuBs6QS9+mM1DH2RL8C0Jqpun3uoifKwHEtbD+f+c4qw5LEGQFQBAEweDRdWBOG8DnMpAxD/D2OuDGAeDyVqDBV7ox16ug8w/1/1XfB7IUSIxRC4KQ1KE9aOATPakwqZLu71G6A2CfDmjyLeDoYu0RCikEKQKOBkkABEGIkmcPgWn1gIdXgUz5gZ7LJYAXBCH+WfIecGJB+O2SbfRqoeEgJgiJEOfK2rQgCAItO/mjbAT/nPnPmNvaoxIEISXSdDSQ2V13FN/1C3B6OXBoBlD5HWuPTEhFSAIgCIKwdxJwYYNu7NPpbwn+BUFIONK5ancwwkZiG0YA64cDRZsBLnmsPTohlSBFwIIgpG4C/YHd4/X1Zj8Cucpae0SCIKQWqg0A8lUHgp8D20ZrE4KDfwKnlgG+Yc0BBSEBkBUAQRBSN8f+AfwfAJnyAeV7WHs0giCkJtgQrPE3wF+N9XfRubWA/319H5sI9l4F5Klg7VEKKRCrrgCMHj0alStXRoYMGZA9e3a0bdsW586de+XjFi5ciOLFi8PR0RFlypTBmjVrEmW8giCkkGJf77PhXTn3hnl0Vx8olp2CICQ+easAxVtpZyAG/7QKzVIICHoKrBuqawUEISUlANu3b8eAAQOwb98+bNy4EUFBQWjSpAmePn0a7WP27NmDLl264J133sHRo0dV0sDLyZMnE3XsgiAkw0LfQzOBCeWAKVWBlR+HFf5eAZwyA+W7W3uEgiCkVrgKkKM0UKEX8P5OPfNv56wbC24fo62FKQ8ShHgiSdmA3rt3T60EMDGoU6dOlPt06tRJJQirVq0yb6tWrRo8PDzw+++/v/I5xAZUEFIhQc+BJe8CZ1a8eF+atEDrCUCFntYYmSAIQtRsHwts/S78du7yQN8tWjYkCCmpEzAHS7JkyRLtPnv37kWjRo0ibGvatKnaHhUBAQHqxbC8CIKQSnjuC5xaqpt7Mfi3sdcWfN0WAy55gWwlgHc2SvAvCELSo8ZA3YGc31OsB7h9FDj+r7VHJaQQkozgNTQ0FB9//DFq1qyJ0qVLR7vf3bt3kSNHxG6cvM3t0dUZjBo1Kt7HKwhCEoN6fs7mG810Hl4DZjQF/O7o2w4Zgc7/AAXCVhc/OqH3leY7giAkReycgO6L9PXdE4GNXwKbRgFZiwLZS+gJDVsHa49SSKYkmQSAtQDU8e/atStejzts2DAMGTLEfJsrAHnz5o3X5xAEwYo8e6R9/Pf9DuQsDbT/C3BID/z7lg7+M+YBSrYFKvUBshYJf5wsowuCkFyo+gFweBbgc0k7Bhnk8gAajAAKN5LJDCH5JQADBw5Umv4dO3bAzc3tpfvmzJkTXl5eEbbxNrdHhYODg7oIgpBCYNkSi+HSZQO8TwH/dgb8wvyyr+8FplbXqwGBT4D0ObXER5rrCIKQnLG1Bzr/C2z5Vn/P0bqY3DkG/NMBqNYfaDba2qMUkhFWTQBYf/zhhx9i6dKl2LZtGwoUKPDKx1SvXh2bN29WciEDOghxuyAIKRgG9Vt/AI79qwN++wxAaDAQ/AzIUhCoNQTY/zvgFeYIliE30GWeBP+CIKQMshfXMkZOggT56xonrn6qFdApWhrElU5BSOoJAGU///77L5YvX656ARg6flYvOzk5qes9e/ZEnjx5lJaffPTRR6hbty5+/vlntGzZEvPnz8ehQ4cwbdo0a56KIAgJDYt4d44Lvx3op/8v1BDoOBNwdAHKdACu7gIy5ASylxKZjyAIKQ9KfezT6UvT7wGnTMCW74A1n+pO5nkqWnuEQjLAqjagaaLRq82cORO9e/dW1+vVqwd3d3fMmjUrQiOwESNG4OrVqyhSpAjGjBmDFi1axOg5xQZUEJIh/Jr6syFw67DWwjb8Crh/AXh8EyjaTBp4CYKQur8fF/YCTi8H8lTSskdOfgQHaDME1j5JfUCqwTeGcW6S6gOQGEgCIAjJkGt7gZkM9B2AwSeB9NmtPSJBEISkA+uiJlbQ3YMph2Sx8MXNuhaq/gig7mfWHqGQSCTLPgCCIAgvwDmKXb/q6+U6S/AvCIIQGcoea4c5Hu76Ra8GMPgne37T9QKCYIEkAIIgJG2OzwMurAfS2ADVB1p7NIIgCEkTfj/mKA3Ypwcqvwu8uwXIWgwIeAwcmmHt0QlJDBHOCoKQdKHOf/Un+nr9YUC2otYekSAIQtLEzhF4bzuXTQEbO72t1sfAsn7A3slA2beAjLkjPsb3DvDUG8hVzipDFqyHrAAIgpB02TBC292519a6VkEQBCF6aIhgBP+kTEcgo5sO8seXBdYNB0JD9X1nVgGTKgHT6gE3DlhtyIJ1kBUAQRCSJvcvAufX0asAaDUeSGtj7REJgiAkL5gMdPkXWDsUuL4H2DcZcMqse6hs/zF8v31TgbxVrDlSIZGRFQBBEBKPg38BfzXV0p5XwcY2hDafWQsn+NAEQRBSJJT3vL1WT6SQrd+FB/+l3gzvs0InISHVIAmAIAgJAz36vU6F337+GNj4FXBjH/BvJ+CuJ7DtJ+Danhcf63tbF/+S6v0Tb8yCIAgpFXYJrqh7LClL5TZTgI6zgLzV9IrA4fB+S0LKRyRAgiDEP6eWAcv6a0/qgvWARl/rDr2GLR09qn+vpa/vsNOdfEu01rf5I7ThK639z1lG6/8FQRCE16f5WN0pmJccpfS2Ku/qiZntYwDv07pvgKXhwu1jQIZcQIYc2pb52UPAOYvVTkGIH6QRmCAI8cvBP8Odewxs7HXbev5wVO0HHJmtA/xM+YBH17XFZ5tJQEggsPIj/ZhcHkC76eL8IwiCkJCEBAELewNnV+nbTlmAXiuA9DmB9cMBz//0tk5zgS3fATcPAm2nalchIckhnYCjQRIAQUhAntwDJnromX4G+pxZopPPuTX6/nTZgI9PAn53gODngGsRYPkA4MR8fX+atIApFKg1GGjwpRT+CoIgJBaUbC4fCNw+AqS1A0KDot+XEqKWPwMPrwDOrkChBkD2Eok5WiEapBOwIAiJDwvLGPznrgA0/QFwLQR0+geo/Qlg5ww0GKG9qrMU0D8WtKzjTFKdz/XjGfzTtq7hSAn+BUEQEhNKgnouA/JUCg/+WUDcfYn+TieUAhWoC4QEACsGAjt/1qsEU6rpXgNCskFWAARBiB3X9gLn1wL3zgMuebRGv2Qb7ezDHwFTCNBrFVAgknY/NOTlQf35DcDdE7qbJZMEQRAEIfEJeq5XAbIVD9f6P/cFTi0BijQBHDIAf3cAHl7VNV5c0b2yHbB1BPrvBbIU1LUCDy4CLnnl+zwlSYBmz56NrFmzomXLlur2559/jmnTpqFkyZKYN28e8ufPj6SKJACC8BqwccyCbi9ub/wtcHoZcOuwtu3susAaoxMEQRASG4aRc9roJCB/TaBIY8BzMeDlKb8HKU0C9MMPP8DJyUld37t3LyZPnowxY8aopGDw4MFxH7UgCEn7S37HGH2des/mYwCP7vr2xi918O/oonWhgiAIQuogTRqg5S/a7OHabmDT1zr4J2zmeGkr8PS+XjUWkrcN6I0bN1C4sG7Ms2zZMrRv3x7vvfceatasiXr16sX3GAVBSApwdufOccDWCWj3J5DOVScF1IqeCJvhafUr4OJm7ZEKgiAIiQmbNb7xG3DiPy0bYu3A/fPAkTnAqo8Bfx9dH9ZtEVC4obVHK8Q1AUifPj0ePHiAfPnyYcOGDRgyZIja7ujoiGfPnsX3GAVBsBb0fz63FvC5rPX5pHx3HfwbMz/sLmmfXhf2lm5v1eEKgiAIVqJcZ30x4Kz/yaW6VsBgxSCg/x4g6BmQLjuQVrxoklUC0LhxY/Tt2xfly5fH+fPn0aJFC7X91KlTcHd3j+8xCoJgDQ5MB9Z8GnEbbTqrD4i4zd4ZaPVLog5NEARBSOKkywo0+UY3dqz8jq4TYzIwrqi2ga7cVySjyS0BoOZ/xIgRSgq0ePFiuLrq2cDDhw+jS5cu8T1GQRASmwA/YOv3+nrhxoB7TeD5Y20Px5l+QRAEQXgVld4GKvbRq8VFmwKzWurg32gaWbYzkLeytUeZKhEbUEEQXoTezpu/AVwLA/33a79+QRAEQXgdWEcW6A8cnqUbQLJW4N2t0vclubgArVu3Drt27YqwIuDh4YGuXbvi4cOHcRuxIAjWh/MBV3YAe37Tt9mgS4J/QRAEIT5gwJ+/OtDkW8DBRScEW3+w9qhSJXFKAD777DOVYRBPT0988sknqg7gypUr5oJgQRCSGcGBwOzW+vLsIZC1qBT1CoIgCPFP+uxAs9H6+s5xwO4JQEiwtUeVqohTAsBAn02/CGsAWrVqpXoDcCVg7dq18T1GQRASgx1jgas7ATtnrdlk+3eZ/RcEQRASgvLdgPoj9PWNXwG/lACOS9OwJJ0A2Nvbw9/fX13ftGkTmjRpoq5nyZLFvDIgCEIys/uk7p+0nQq0Hg9kymvtUQmCIAgpmTqfAg2/ApyyAE+9gZWDgGePrD2qVEGcEoBatWopqc+3336LAwcOoGXLlmo7LUHd3KQJkCAkK0JDgZUfAaYQoGRboFRba49IEARBSA3QHaj2J8An54DsJbVDkOdCa48qVRCnBGDSpEmwtbXFokWLMHXqVOTJk0dtp/ynWbNm8T1GQRDiU+fPYP+fjsCTe3obu/jeOQbYZwBajLX2CAVBEITUhq09UKGXvn54tjakEBIUsQEVhNQU/C/sDZxbrW/nKK27+P7XE/C7DTT6Gqg12NqjFARBEFIj/j7Az8WBkADg3S1AnorWHlGyJEFtQC15/vy5ejLLS0zZsWMHWrdujdy5cyNNmjRYtmzZS/fftm2b2i/y5e7du697GoKQ8mGRFYN/GwfAOSvgdRL4q5EO/jPlA6r2s/YIBUEQhNSKcxagZBt9fd9Ua48mxROnBODp06cYOHAgsmfPjnTp0iFz5swRLrE5Trly5ZR7UGw4d+4c7ty5Y75wHIIgvAS/u8Chv/T1DjOA3qv0CgATgdwVgDcmAXaO1h6lIAiCkJqpPkD/zzqA20eB/dOAfb+LJCgBiJPH3+eff46tW7cq/X+PHj1UAH/r1i388ccf+PHHH2N8nObNm6tLbGHAnylTplg/ThBSLfumACGBgFsVoHhLXXjVb7e1RyUIgiAI4eT2AMp01AnAzJZA0FO9PV1WoEwHa48uRRGnFYCVK1diypQpaN++vSoGrl27NkaMGKF6Afzzzz9IaNh1OFeuXGjcuDF27355EBMQEBBniZIgJHv8vIDTy4GDM/Tt2kN08C8IgiAISZEGIwAb+/Dgn6z9HHj6wJqjSnHEKQHw8fFBwYIF1XUWGPC2YQ9KXX9CwaD/999/V83HeMmbNy/q1auHI0eORPuY0aNHq2II48LHCEKKIzgA2PkLsGs8cGGjtvZ8cAmYVFkX+Qb6aYu1Ik2tPVJBEARBiJ7M7kCzH3URcM8VQPZSgP8DYMm7wHOZxLWqBIjBP7sB58uXD8WLF8d///2HKlWqqJWBhJTmFCtWTF0MatSogUuXLuHXX3/F3Llzo3zMsGHDVM8CA64ASBIgpDi2/gDsHh9+u3x3bfMZ8BhwyQfkqwpUHwikfe26f0EQBEFIWCq/oy+kzSRgRjPg0mbgz0ZA90XauEJ4LeIUDfTp0wfHjx9X14cOHapqABwdHTF48GB89tlnSEyYeFy8eDHa+x0cHNQqheVFEFIUd08Ce37T14s2A9KkBY7+DVxYD6S1BXosAdr/qbWVgiAIgpCcyFMB6LMGyJALuH8OWCV21VZbAWCgb9CoUSOcPXsWhw8fRuHChVG2bFkkJseOHVPSIEFIdYQEAxc3AZtH6S6+JVoDnf7WjgnrvtD7VP0AyFrE2iMVBEEQhLjjVgnotQqYUlX/7l3aCrjX0p2D7dNLbVtiJQCRyZ8/v7rElidPnkSYvaesiAF9lixZlLyI8h26C82ZM0fdP378eBQoUAClSpVS/Qf+/PNPbNmyBRs2bIiP0xCE5MPjW8B/PYBbh/VtRxeg+Rh9ver7wPPHwN0TQN2wREAQhFdy9PpDLD92G580KYoMjnbWHo4gCJZkLQxUegc48Aew9AMgyB8I8AXS2ADZigG5PLTMNZM7UPsTkbwmVAJw8OBBZQXq7e2NUBYcWvDLL7/E6BiHDh1C/fr1zbcNrX6vXr0wa9Ys5fF//fp18/2BgYH45JNPVFLg7OysVhs2bdoU4RiCkGK5vB3YMEJ/6bFj4jMfwMEFqNADqNwXyJhb78eZkHoS+AtCbAgJNeGj+cdw3ccfWdLZY1BDWTkThCQHJ7WOzwOeWDSA5Qq492l9MXAtBJRuZ5UhJhfSmEyx765Au0/afrIgN0eOHKobr/mAadKoWfnk3iJZEJIMIUHA1u+1ww8s/lzZyKvzP9oxQRAsOH3bF4uP3MSHDQojk7O9tYeTLFh94g4G/Ksd5YrmSI8Ng+tae0iCIEQF5T8sCC7aXNe2cULszjHA+6z+/+wq3eDy3S2pUhrkG8M4N04rABMmTMCMGTPQu3fv1xmjIAiv4uE1YFGfcKlPhZ5AmbeAoGda/2jvbO0RCkmEx/5BsLVJg3QOtvjfMk8cvf4I/oHBGN0uceuykiOcB5u245L59nmvJzjv5YeiOTJYdVyCIERBofr6YmCfDsiUV9fBPb2vawRuHwGu7da/k0KUxEkglTZtWtSsWTMuDxUEITbe/v920sE/Nf4dZwNv/AYUqA0UbSLBv2Dmnl8A6o7bitaTduHsXV8V/JOFh27iho+/tYeX5Nl/xQfHbz6Gg21aVHbPrLatOn7b2sMSBCG2sGOwR1d93XDHE+IvAaALEK0/BUFIQHaMA+6dAdJlAz7YBZRqa+0RCUmUZUdv4ZF/EC7fe4r35x4OzyFDTZi8NXqbZEGz4OAN9X+7Cm7oXk0bWqw8cUetDAiCkMyoNoCCdOD8OuDeOWuPJskSJwnQp59+ipYtW6JQoUIoWbIk7OwiuiUsWbIkvsYnCKlP77/+f9rr+Oouva3FWGl6IkQLg9RFh2+ab197oGf8e1XPj9l7r6n7Pm5UFDldHJGSmH/gOsZvuoD2FfNgcKOisLWJm+PH04BgrDupCwo7VnJDsRwZ1ErAlftPlRSoWE6RAQlCsnMLKt5S1wJwFYCNxIQXiNM35qBBg5QDUNGiReHq6qqKDSwvgiDEEc9F2uLs8jYgNBgo8QZQUmb+heg5ecsX57z8YG+bFvmyaFlYegdbDG1eQslZuAqw/NgtJHVO3nqMmbuv4HlQSLT7cDWj98wDGLzgGIYu8cRd3+eYvPUSmk3YiYY/b8MHcw8rN5+Vx2+jzNfrsdbzziufl8H/s6AQFMiaDuXzZlI1FNUKuqr7dpy/F6/nKAhCIlFjkP7/xALg/kVdKCy8/grA7NmzsXjxYrUKIAhCPEG5wb7J4cW+dDgoWC9VuhgIMWfRYS1faVoqJ9qUy4335h5Clyp54WRvgzfLu+Hg1YdYevQW3q9bCEkRBvyfLzqBFWGa+wdPAvFp02Iv7Hf/SQDGro+4nN/GIzc2nfbCRe8n6vale09V8M/9/J4HY8Syk6hRKCtcnKP39F9yVK+evFk+j9nRrm7RbNh+/p66vFunYLyeryAIiUC+qoBbFeDmAWBSRSBNWqDDzIhSWj8vLbFNpf0C4nTWbNRF+Y8gCPEIJT93PQFbJ6DRKKB4Cyn0FV7KncfPsDBM/tOhohsalcyBI182VrP/pGWZXLC3SYuzd/2UNWhSZN6B6+bgnyw/fitK7b0xG583ixM6VnTDmA5lMaFzeawfXAc/dyyHLlW0TG74Uk/cevRMXX/wNBC/bjof7XMzWdhz6YE5ATCoWyyb+v/AFR/lpCQIQjKk/jDdJIyYQoEVg4BHYb2ldv4C/FwUmNkcuBf9d0RKJk4JwNdff42RI0fC31/cJQQh3tg3Rf/v0QVwzmLt0QjJgG9XnYZ/YAgq5c+M2oWzqm30/bdJq2eyOfPdoHh2df2/QzeSZFGrob//uFERONvb4IbPMxy9oV2MLNl2TicAb5TLjbEdy+GtSnnVbbfMzmhf0Q1fNCuGdPY26vUg9cOC+Dl7r+LSPb1CQAKDQ5Xn/5D/juHDeUfVwhuD/7xh8ilSMGs65MnkhMCQUOy/rKUD3n7Psefi/QR9LQRBiEcKNQCG3QSG3wbyVAICHgMLewNH5gCbv9H73NgH/FEbuH0MqY04JQATJ07E2rVrVROwMmXKoEKFChEugiDEkltHgHNrtHNBtf7WHo2QDNh54R7WeN5Vwf63bUsjbVjQH5k3K+iZ7Vl7rqLt5N0Yu/4s1p1MGg43D54E4OBVHWC3r+CGJiVzqOsrjkW04KSuf8cFnQDUK6YTmsgw8eleXTv4MJEY36k86hXLhlATIhRJj157RjX8WnJE10W8W7sAxnUsF+FYlAIZqwCUAZFB846i65/7sfCQllwJgpAM4Co6+wS0/xOwz6BttVd8qJtqlm4P5KsBBD8HtnwXu+OGhgKBT5HqagDatpWiREGIV4zZiLKdgKxFrD0aIRkwa/dV9X+PavlRIlf03R4bl8iBd2oVwNx915TXPS9kbIey6Bg2ix4bngWGKMmsg23Y0vprsPmMtwrQS+bKqGbg3/DIjWXHbitJUCZnO6XFL58vM47deKRsTjM62qpC3ejoV7cQrt33R8MS2dXqR8eKedXKwfKjt/BZk2KqnMZYcWDCQQch1ghEBZ/73/3XsfmsFwbUL6x6BZBxG86hZdlcym0pdyYnuDhFX18gCEISIUsB4J0NwLbRwJmVQK5yQJvJgN8d4LdKwMWNwI2DQN7Krz5WgB8wuzXgcwXosRTIUyH1JACU/wiCEE9c3Axc3gqktdOaRUGIgXXlzjA5SucqLw/iuTLwZauS6FevENZ43sH2c/ew+aw3pm67hOI5M6LXzAMq2P3lrXLmItjo8HkaiCa/7kCezE5Y1r/GK/d/FetP3TUXMJPaRbIhSzp79Ty0+Jy+4zK2fVYfW8966/uLZnup3SdXAX7vUdF8m4lABkdb3H78HPuuPIBrOgfcefxc2Xx+/2ZpONpFn8TUKZJNSYooSfpl43klFSJevgFoOn6H2k63pR7V8yv5UnQJ0ZAFx3Dmrh/mvF0F2TI4mLc/fBqIEctPIig4FFO6VYizjakgCDEkR0mg01zg6QPAIT1g6wBkKQiU6wIc+1snBz1eYWPPL4LlA4DbR/XtBd2B97YB6aNemUzKvNY3zuHDh/H333+ry9GjYS+GIAgxg18ku34F5nXWtyv1ATK7W3tUQjKR/1DLzoJY+tbHhKzpHdCzujsmdCmvZq0v33+KLtP3qWCbLkGWMhlLKBV6/CxIXV/teUe58Ry/8QhHrj+MtySmaWkt/bGzSYvpPSvh/ToFUTBbOjwNDMGwJZ7KHtRYzYgNDPBblc2lrlPys+2cTiRo8/my4J/QRalp6ZzmQmVSOo9eaWHwT54EBKtE6pcN5xEaasIPa86gx1/7lVXp1nPeOHzNB0uO3sKZO77qPPhaBoWEKucidm1mLcKG016q2FgQhEQinasO/g3qfAqktQUubQbOUor7EvibfXq5nrBjfx7fW8CCHkBwIFLFCoC3tzc6d+6Mbdu2IVMmvRz76NEj1K9fH/Pnz0e2bFo7KQjCS2Ah0qav9fWizYAGI6w9IiGZwKCRNCmZM9az8Jy17lXDHRM3X1ABLF2CWOz6zcrTqF7IVRXVWvLnziv4fs0Z5bSzysKtZ9nR26iYP+7F6tTWM4nJ7+ocIYmpmD+zurB4udO0fdh0Rp9rlQJZ0Lpc7lg/D61Q5x24gVUnbqvCXsLagJg9No+5VoB837YMlh+7rRKigQ0KY9fF+/hy2UmVILBh2LQdl837Hr76MEITMZ5Htz/34/QdXyVnivx+1iicFQHBIfEirRIEIZbyoOoDgd3jgdWfAO41AccoelqdWgZsHqWvNxsNFKwPTG+gC4nXfg60Ho8UvwLw4Ycfws/PD6dOnYKPj4+6nDx5Er6+vqpJmCAIMSgg2hvWnbDOZ0CX+VF/4QhJAs7cUspR/psNKP7lWny94pTVxhIcEootYZKYxmFFs7GlTw13ZHCwhW3aNPi7b1WUz5cJfgHB6DXjALx9n0fY11gZ+Hb1aRwIK9glDKg5mx0T6KDTfMJODFtywmyraSn/iSqJqVrQ1Xx+1P7/2snD7G4UG9gMrXaRrHgeFKr6BLyskDgyrA8wZDv8v0weF3zVuiR+fqucahzWtUo+tQrj+zxYNSYzags88urX89C1h6ruoHNlLdOi5SiDf67GvF2zgKrDIBtPe+G/gzdQ/Mt15tUOQRASkXpDgcwFAL/bWuLDAl/O6j/XNVPKJWjp+/p6lfeBKu/qjsMsLqZ5x+GZwKZRyWolIE4JwLp16zBlyhSUKKG9pknJkiUxefJk5Q4kCMIruLQFuH9euxKwY6E0+0rSsCiVUo6H/kEqkJy99ypu+CS+DTJlJhO3XFRBZGZnO2X/GRcyp7PH8oE1sWpQLTWzPrFzeeR2cVQBsiELIrcfPVNdhgmfk6q1cm4uKoDlaxHTTrmLD2sZDGfi35i0Gxe9/cxJTNNS0Scxo94opQpup3avaJ69jy1MLn7rUt7cJdnd1VkF7zGBCUe7sP4ATEYiOy3x/u5VtfMQVzNYb8AEYUJnD1U/oB5XIge+f7MMPmlcFB81LIKFH1TH/uEN1X48N9YjsG8B6wH4+o5eexZX7idvdxFBSHbYOQFv/Kb7BrBIeFJlYEwBYGwR4ORiYMl72i2oSFM9+29QtAnQKKwudtcvwB91gLsnkWITgNDQUNjZveh8wG28TxCEaHhyT3+57Birb1foAThG7+AiJD60nPxz52Vz4Sm16qPXnFXX+9crhJqFXVWgRn/5xA7+3//7sJLukD41C7xW4WjBbOlVETChA8/896qbkwBaXvJ1MCwwLZ1u3vDIg9bltK7++9VnInjsR8fak3fU/3Y2aVTX3jcn71GdeplIlM8bfRJDl53JXSugZliPg7jC4uA/e1VSCdOghrFz2RrcuChGtyuDL5oVj/J+9iNgEE/61iqoXqv8rukwvnN5VCuYBV80L64ShQ8bFlHHquyexbyS4Wxvq1YnjATC+J8rJXxd+R4Qv+dBOHHzkVqJ4ufg143n8fe+a4ivepJ9l3UzNEFI1RSoDfRaAaTPqbX9gU+AkABg0dvA/XNAuuxA26lA2kgyvZofAx1mAM5ZgXtngD8bAkf/RlInjSkOZtBt2rRRmv958+Yhd26tybx16xa6deuGzJkzY+nSpUiqUKbk4uKCx48fI2NGCbyERCQkGJhaQ3+RKNIAg45q/aGQZGAhJ7XcTnY2OPC/hur6b1suKqnHxsF1sfvifbwz+5CSpewb3lAFcYnBWs876PfPERVs0vffaIQVn5y766d6BTwLCsH7dQvi6v2nWH/KC4MbFcV5bz9V/LtsQE08DwpBx9/3KkcdSomWDqiBwtmjLkbmSkntMVvBmHf1oNp4f+5hXA9bPWH3XgbXyR3ahR648gDfvVlG1VjEhgUHr+OLxZ7q9ZnUtYJqUMZVJsLPIGskLt97quo0hrcojmJ0bppxQC0abvmkXoxXM6KC72+Dn7epRPLA8IYqURKEVM/TB3qV3rUgsG8q4LlQb++yACjW7CWPu69lQhc36dtdF+oVgiQa58Zp+mjSpEnqCdzd3VGoUCF1KVCggNr222+/vc64BSH58vgWsPQDYEoNYHI1wPtMxPuP/6uDf8p+CjcCWo6T4D+JwW65RiEng+D5B26Y/faHNy+hnGOoH6echLpvFsImBpz1nRA280+HnIQI/gmLVn8K06X/sf2yudi4fvFsaiZ+1xcN1Kw9C4VXDKyFsm4uSuv+9z7tkvOy2X8677Bfwey3qyirT2I49CR3ulbNp2b8Yxv8k1Zlc6NFmZz4+o1SaFEmFyZ1qaBkVo52adVn8OxdPxX8k2k7rmBWWI0Ap+5m73m9VSgWL3ORgasORqdlQUj1pHMFynYE8lQE3vwDaPId0GbKy4N/9bisOuinoUfxVvp3PqWtABA+bNOmTTh7Vi+Nsx6gUaOkfbJEVgCEBIF/RjObA9f3hm/LmAd4ZyPgkgcIDgB+qwg8vgE0+R6oMdCaoxWiYOnRm/jkv+MqICqaIz3Oez1RRbLBoSYUypZOzf4bGnD609MZh8WzS/vXTPCxsXPvB38fUbPtO7+on+AztZRAfbdaJ7BZ09vjwPBGUXYaZvHqu3MOKenQ7qENXijm5e8EVxTYfIyrFmxaZqwKXPD2Q4PicStiTg1Q/nP1wVNc8n6iJFpvzzqoVlwsYcfjvcMaxqkZGR2Hqv2wWdVyENYjMMkTBCEeoByeHROtQIKuABB+0Tdu3Fg5AvGSHIJ/QYhXgp4Dh2YCeybpZUIG/3bOwFtzgKxFtYbwnw7As0fAnt908J8hF1D5HWuPXIgEG2QNCQv+O1XKq5xxjOCfvFenYIQAuE353EqycfT6I1yOgQb+daDTzrgN59X1PjXdE0Wm0bd2QUztVgGu6ezRo5p7lME/oX6dQSgbbZ285fvC/VO3X1LBP19Ly2JfBrQS/L8c1gkUypYeTUrlVCsnvWu4R3A2YpLqHxiiJERxgR2RGfxzpYGwQRyTAkEQ4gErBf+xIcbrlRMnTsR7770HR0dHdf1liBWokOKhxm/FR4BvpOZJdT8HSrYBcpcH/moCeJ/W/9Pxh9Qbpt0GhCQDPd3p5c5FHGrSv29bWgW87CJL/TslL208tBOMQfYMjqhTNJuSTSw7egtDmhRLsPHRFpKFs5TNvFOrIBKL5mVyoVnpl/cZoCSKXYTXnryrbD3LuLlEsAkds07Xu/yvZQn1mglxp0vVfKoWhb0bulXNr4L/4Us9lU3re3UKxfp4lLeR9+sUwr8HruOeXwD2X/ZRn2tBEFI+MU4Afv31V1XkywSA16ODPxaSAAgpmmt7gXldtTsAZT7OrsDdE0D2kkC1AXofdgjstkjLgoyi3yrvARV6WnXowov8tvkCHjwNVDKfb9qUMs92D6xfROmvP25UJMquse0quKkEgPagHzcq+sIsOd2D6HST0yU88J2775pKGL5rW1rN6r6Ku4+fY8Imrf0f2rw4XJxjL/V4HWLSZIw+/kYC8GnT8ETIcCt6p1YB5VgkvB4ZHe3wW9fyOHnzsWqIxkSA/SgoVWPxtmXTsVfxyD/Q3NOhQ0U31aeBFq2UdEkCIAipgxgnAFeuXInyulFCENtulIKQrHhwSct5nvsCQc908F+0OdBxJmDrCHidBFzcAFsLeUbO0kDnf4DFfXWn32Y/id9/EoN+67PCCim/al0Kdha2mpzN3v5Z/Wgf26RkDlX0efPhM2y/cA/1IzWXomZ7/xUfJd2ghGjx4Zv4eaNeCRq2xBNL+9d45ffmzD1X8DQwBBXyZUKHCm5IitQvnl3Ze17wfqJqI96tU1D1D2BgypxoUIPY2W4K0cPPmPE5o+6/brFsKmhfefw2iuWM+SoUE1fWGBTPmUHJsdjjgAkAE7mRrUvik4XHcejqQ+X4ZDRCexlM9mhLOqN3ZZTOIw0NBSE5EGeR0l9//YXSpUurFQFeeP3PP9kRTRBSGH5ewN/tAJ/LgP99IOgp4FZF+/5SzsMgLmcZwCkKP/MCdYBPzgFvTEwWmsDUxopjt5XOn1p2SlliA1cFDDeeb1edjqCfPn3bVwX/hAlGjR+3mIN/6uGP3XiElSe0O87L2HH+vvq/V43odfjWhoEoG1wRFkazgNhoEMaOuIm9apGa4EoAWXnitnkyztLic/6B65i89eILTes2ndHuTpS5kdpFsimJ2f0nAfhjx2UsP3ZbNSdbfuzWK8fAz/30nZfh7ReAkStOvTAOQRCSJnGKSL766it89NFHaN26NRYuXKguvD548GB1nyAkWyL/ePH2gu7Aw6tAZnegz1rtBdxzGWCvO4u+Epn1T7LQ0580Lx03O8qPGhVRNQL0af9r15UIjkKkdJ6MyiGHsXsuF0d81aqkuRHVT2vPKj/96GAwxu655HUbYSU0AxsUUb0CyE/rzmLBIa0vFzlJwtKoRHbVK+DaA3943nocoWdEvXHbMHSJJ8auP4f647YpuRDtZGn5aTR4a1hCF2Jz5euNsGRi3IZzEYrjY5KkUupGDl97iFUxSGwFQbA+cepgM3XqVEyfPh1dunQxb3vjjTdQtmxZ5Qj0zTffxOcYBSHxfPz/bg84pNfev66FgEubgZsHtLtP9yV6m5AioEb/yPWH6nqtOAbYnP1mcyY6CE3achE9q7vD0TYtlh3T/QE+alhUBWmUWxhde58FhqjGUZxhnbLtEoY01oEzoa6794wD6n8ei7BWgElGUofJ0MGrPth18b5yRyKxXVURYgeb0DUqmUNJgCjhKeuWSW1nUa/x2XFxssW+yz5qJapIjvRwd00X1oXZHh5h+5N2FfKofSznQI5cf4Q7j58hl0v0xgV8bsLPKJPWH9eeVXUh9mHdkQVBSJrE6S80KCgIlSpVemF7xYoVERysZwJiwo4dO9TKAbsJUwu7bNmyVz5m27ZtqFChAhwcHFC4cGHMmjUr1uMXUiBPvIHVnwC3jrzYfXf7WGBcUWD9/4DAp1E/ntr+f9/SbbxvHgT+qAucXgHsGq/vr9BLgn8rwiBjxDJPHLjiEyeJQXBIKBYeuoEP5x1Vun/CY1H+ww6/+VxjuJoTBW+Wz6O6sdKVZetZbxUA01Els7OdCoD53WYE/8TJ3gZftiqprv++/ZJ5PEwSBs07ikPXHqriY8qKCOVJyYUvmhU3X8/kbGcOSIWEw+itsOTITTx8GogHTwKw59IDte337hUw/73q+F+LEur2j2vO4vNFJ9T1BsWzR5CVlcnjogrhDekWrUbJWs+70T43k1lDTvRbl/KqXoCJrdH8TRCEFJYA9OjRQ60CRGbatGnKKSimPH36FOXKlcPkyZNjtD+Lj1u2bIn69evj2LFj+Pjjj9G3b1+sX78+VuMXUiArPwYO/qln8B9e09uePQRmtQS2fgc88QL2TgKm1tRynsgsH6ALedNlB/JWAwL9gP96AFd3Amltgeph7j5CokON8ReLT6hus2/9sRfvzD6kgmVCD352791yVgchUXH9gT+ajt+BzxadUIkEpRCEgfrrzP4bMMBvXjqnWTIxd+81sz47ullQdn5lYE85xvAlnipBGb3mDLac9VY1AoRdYONjfIkJC6cNXTp15fSyFxIWBuqUmgUEh6qZfxby8u+DAX1+Vx3Qv12rgArq2bWZAbq7q7NZihbBwa9hEdX74fOmxVRX4pfJgPjZHb/5vEp83TI7oVrBLOhWNZ+6b07Y34AgCClAAjRkyJAIXxQs+N2wYQOqVaumtu3fvx/Xr19Hz54xtzls3ry5usSU33//HQUKFMDPP/9s7j68a9cuZUvatGnTGB9HSGGcXw+cW62vP/MB5ncFOv8LrBwE3NgHOGQEqg8EjswBHl4B/u2kO/Q6htkw3j4GnFkBpEkLdJ0P5CwLbP4G2BPW76JMRyCTLvYUEp8j1x6pIINa5xCTSQXJdB25eO8JVlvojVcPqoVSubUDCbXOPv6B6nqvmQfULDtn5On5T/0zi3R3Xbgfb/p6BkuU83A2NCjEpDT/lo2bIsPv0G/alEbzCTuw9/IDdJq2T+mnyfjOHlhw8AZ2XrgPe5u0qOyeBcmJb9uUUjPJtJcUEh5+lt6uWUDJ0CjhYQBPWpUNr2thIjamQ1n0/OsAiufKgF/f8kDmsP0sYb8Lo+dFgWzpMGrlabUiRTtaw86WCTQtX/k3yb8n0r1afjWOrlXyKSkcP8snbz0WRyBBSAkrAEePHjVfPD09ldwnW7ZsuHTpkrpkzZpVSXNOndKzawnB3r17X+g4zMCf26MjICBAtUW2vAgprBvv2s/19XJd9Aw+Z/InlAUub9Pa/d6rgXpfAH036k68984C/3QELm7W7bp3jtOPL90ByFMRsLEDmnyri30r9gYajbLqKaZ2dl3UBYvsJMsmXWTC5gsq+OdsObXMxJh5J4PmH0Wl7zapC4P/PJmcsP7jOuZZzX7/HMY5Lz9Vn12j0OsnAKVyZ1RSIgb/hAWVBbOlf+ljKBtiIEaM4J89B1qVzY2RrUupQK59xTxKMpScYKdi9kVwyxx3WZUQO/iZ4Wec0jPKx0hLiwSAFM2RAXuHNcCsPlWiDP4jQ91/xfxhMqAwSQ8b0jHJuPP4uQr++bf3a6dyeL+OblCXPaOjaiAX+e9REIRkvAKwdetWWJu7d+8iR46I7eN5m0H9s2fP4OT0YqHS6NGjMWqUBHAplsOztKSHgX2LsVr+s/YL4NoufX+76UCusvp6xtxAl3nAjOZ6ZYDWni55gcfasQS1w1e5FMWa6YtgVTgTbkhKWKi4+Yw31p26iwwOtpjWs5Ka3aQ0aNmxWxjWvARO3HoUwYmEM/+z366sgpMP6hZS99E1hfSvV0jZH74uWgaUC9N2XFZJxcAGhWP0OAZL1M3TOadd+TxmO83C2dPj4P8aJVnrTyFpQanZwg+qKztOWtvSfSmqBCy2/XqYMDM5pQyIzdxYR0MoX+PntlC29C8kqKxJoNSOnaBHtSkVZRM9QRCSqQtQcmLYsGER5EtMFvLmFTlHiiDQH9ip5WCo+zngkEE33+qzGrh1WFt4ukUqVs9dHnh/B3BwOnBiQXjwX7wVkF0XyglJBxY1GvaGtYpkVQHMuLfKofLBLKhXLJsKQFgUzIZGnPmcsu0itp7zVvtTgsMutOyganjRU5JAaQplRGx4ZMgd4oNOlfNi3oHrKpAvnD3mXVn71SuEtyq5wTWS048E/0JsyJ3JSa0c8RJfsFaFxeiUAd186I/FR26ag/zo5D2sSeBqBGsNmKwbKxHsS2Bnm1bdJwiC9UlWCUDOnDnh5RWx2I+3M2bMGOXsP6FbEC9CMoMFvGdX6w666aKRaDCIf+oNZMoHeHSPeB+lPNGRraheLWj8DXBmpXb9qTU4fscvxAu7L91XeVzRHOmRI6PWILP7LgN7AyYFtMwcvtRTNTEyZv3pSx9VE6qxHcomSPdyJiMnRjaJ02MjB/+CkBSgDIhdqGkHOuDfo7j/JFA5/bD7c3Tw7+oNj9yYuu0SVhy/hWalc6q6gAmbzyvbUtbqGMXJgiBYj2SVAFSvXh1r1qyJsG3jxo1qu5CCoCXn7DeAuycAZ1egWj/g0XXg9lHg3nmgyrvalcc8+z8UsI2DjINdfMu+pS9CkmTjaZ3w1yr8cj95SoOO3XioOuwySOHsfnQdaOM78E+sYwuCteoLmAAcv6F7O7Sv4KYah70M1sAwAdh69h66TN+nLHcJ+1uwWPm/96uLQ5QgpOYE4MmTJ7h48WIEm0/ae2bJkgX58uVT8p1bt25hzpw56v4PPvgAkyZNwueff463334bW7ZswX///YfVq8McYITkT0iQtt9k8E/8HwBbvou4D+08z64Cnj/Wkp6ynawyVCFhueHjb9byt/HQ1pLRQZ3xmA7lEmlkgpB66FYtH1jafv3BU/V/v7qv7odCSR5X7c57PVHBPx28BjcugombtUNQv78Po0f1/KquRxCEVJgAHDp0SHn6Gxha/V69eqkGX3fu3FHWoga0AGWwP3jwYEyYMAFubm7KjlQsQFMQR+dq9x779ECPZbqY98ZBIHtxIJcHcOeYnvln4a+NPdD2d8AmWS1kpQqeB4W8dvEfCxrpZ04f/HJ5paGUIFgDB1ubCJK72FiTDl3iqf5+R7crg7xZnJV8aPCC49hw2ktdxnUsZ7aL9fZ9jl82nle1NOXzafchQRASjjSmuLTVTMawCNjFxQWPHz9WtQNCEiI0BJhUCfC5DDT7UUt/XtgnFFjYU2v3m3wH1PjQGiMVooF+4Z8sPIaDVx9ies9KqhOusfQ/e89VdKzkhuwZtJb/Zdx/EoCaP27RzY36VkWNZNQMSxAEzSP/QLg42UWQxh25/hDTd1xWDcvKublg+cBaanvf2Qex6Yy3sh5d3K+GchK68dAf79UuGKGTtiAI8RPnytSpkHSgrIfBv2MmoHyPqPdJmxboOBu4f15cexIRzsQP+e8YngaE4LOmxVAs54suN5fuPUGHqXvw0F83B/pu1WnU+riO0vr+vu0SJm29qJx6futS/pXPt9bzjgr+y7q5oHoh1wQ5J0EQEr4nRGQq5MuM79qWVisAx28+Vt8bV+49VcG/kSBc9PZT3zfsq8GGYj+2L4tngSHInsFB6mwEIZ6QtFqwDizmvX9RW3WSAD9gR1hDLhb5OrykiVJaGwn+ExkW2C4/dlt1um0xcSdm7b7ywj4zd19RwT/1v5mc7XDB+wmWHr2l7tt1UXv5bz3rjYDgkFc+3/6wosFGJXLID74gpDDoemWsDnI1YOSK8Aai/En45L/j5qZ6azzvouzXG1D1h834cd1Zq41ZEFIakgAIic/VXcCUqsCkisC4osB/vYDpDXThr106oMp71h6hEIlt53Q33oyOtmo14JtVp7E7LKgnwSGhWOt5V10f1qKEuVDw143nI3j5Uwq077IO7qODqkTDNaRKgSwJdk6CIFiPtuV1D475B2+ongHsD/BubV1rwJUB0rpcbmRwDBcq/LH9srnPhyAIr4ckAELiEhwIrBoCmEL1bfr4n16mJT0ZcgM9lwHpo/eYFhIeLrUPXXxCFeQ9DpPzGAnAV61LqaZVoSZg0Lyj8PJ9bp6xf/A0UPnv1yjkil413NVyPX/Y2UiISYPBhlM6UYiO6z7+8PYLgJ1NGnhI8a8gpEgal8iBdGFdhLlqOP+9anijXHhjPv79f/NGKdUR+8TXTdCren61/dP/jqsaIUEQXg+pARASF1p43j8HpMsGfLAbeHARuLYHCH4GVO0HpBdbOGuz5OhNNStnyHq+bFXSPIPPZftWZXPB85YvztzxxczdVzG0eXGsOnFb3c+mP/QIpwFQt6r58eum81gSJgPKm8UJN3yeKe0v04Gs6ewxuHHRFyQ+hvynrFum13YSEgQhaeJkb4NfOnnA8+Zj1Q07nYMt3DKbkCOjA7x8A5T8L3M6XUPA7wGuLPK7gXVEP609i7EdxfZXEF4HWQEQEo8n98J1/k2+BzLkANxrAnU/Axp+JcF/EmHdST1Dn8HBFn7Pg/H5It2ToXSejMrGjz/GH9QtqLZtOeuFoJBQ82PYNMigS5W8sLVo9vNh/SKqi+89vwD8u/86Jm65qAr+InNQ5D+CkCpoWionPm1aTAX/hJMBXD10sE2LvmFyIAN+73z/Zhl1feHhm6rpnyAIcUcSACHx2PUrEPQUyFNRuu8mUR4/C8LeSw/U9SX9a6B2kXD7TaNoj9Qrml25+7DRz587dfFv1vT2qGoRtGfP6KhWBAxqF82K7tXyqx93t8xOats/+8L7fBgcuBqWALhLAiAIqY3+9Qrj7LfNUDH/i3//tAhl12/y9YpTql5IEIS4IQmAkDj43gYO/qmvNxjBqR5rj0iIAs7oB4eaVBfPIjkyYHK3CiiWIwM4kd+8dC7zfi7OdqiUXzfr+XnDOfV/16r5X/Dr7lOzgHqrS+TKiFwuTkoudO675pjctYK6f5XnHVUkTPhjPnHzBVx74K+er0LY8QVBSF28zPlraLPiahKBKwCUAwmCEDckARASh+0/ASEBQP6aQMHw7s9C0oBe26PXnFGaftKslJ65z+hoh+UDa2LLJ/VQOo9LhMc0LKGLtZkwsGCve7V8Uc7YLe1fEzN6V4qwnf7+lBQFBodi8ZGbahuLjnkhgxsVVQ2EBEEQLOHKorEyufmMlzIYOHzNJ4LRgCAIr0YSACHhuX0MODxbX2/wpcz+JzH4wznw3yP4Y8dlnAiz32tqId2h9tY9a7oXHtewRA7zddr1Rdfhl04+nP2PPMPHImHCpOOGjz9+335J3R7ZuiQ+bFgkns5OEISURoPi+rtn81lv/LDmDNpP3YtpOy5be1iCkKyQBEBIWEJDgTWfUuABlOkI5K9u7REJkdh42gtXH/grv+0WZXJiUMMiKJkr+vbhBgWzplOz+Jz9f6dWxIK9mNDWIw+yptdWob1mHlCNfyq7Z1ayIUEQhOgwVh8pA5qzV69aLgtzGxMEIWZIAiAkLAf+AG4eBOzTA42/tfZoUjVHrz/EqJWnVKGvJdN26Jn3XtXdMaVbRQyJwpozKrjPnLerYsPguiiVO6I8KKY2gP3r6YZhl+89Vf+/V0ffFgRBiI4cGR1RJo+L6hpsdAw+5+WHq/f194ggCK9GEgAh4bi0FVj/P32dNp8Zw4tIhcSFdpvd/tyv5DZ/7bpi3k7t7JHrj2BvkxY9a2hJTmzIks4eBaKQB8WUrlXzqYZhpFC2dGhYXJrACYIQ81UAo8cIWf+KJoOCIIQjCYAQ/xyaAUysAPzdDjCFAOW6AFXes/aoUi3XH/ij94wD8A8MUbfXnbxjvu+/g7oAt41H9Br+hIT1BWw0RvnRF82KI61F3wBBEIToeLN8HtWrhJ3J362t+5JIAiAIMUc6AQvxi9cpYNUQrfknhRoCrcZL4a8VWXDoOnyfB6NU7ow47+WnvPsv3XuCfFmcsf60/sF8M8xb2xqwgJgXQRCEmJLfNR2Oj2yiflrYOfir5afUaqa373PlFGRYC7O+6fK9J8jkbBdlbwFBSK3ICoDwejx9ADyz6Mi4aZQO/ou1AD45B3RfDNgl/sxyauLQVR+l74+OHefvq//frlkANQpp+zx27t1z6QEemRt4uSbaeAVBEOIDrhiyFimni6NyGyOrToSvcP625SLqj9uGd2YfQoff9+LMHV8rjlYQkhaSAAhxx98HmFQJ+K2invm/sAm4sB5Iaws0+Q7IkFNm/hNB3tN52j50/H0vjt+wSMTCuP8kAJ63Hps78TYPs/dcfeIOVh2/ra6zwRe7+gqCICRX2nroVcRlx7Qb0POgEMzcreud0tnbqILhVSf0d54gCJIACK/D8fnAMx/A/z4woznwb0e9vWJvwFXcXGILm2I9CQhW158F6h+vP3deVpfvV5/G3/uuvfCYGbuvqEZcvHw0/6j58Qa7LujZf9p6UuPfpFROFeyfvuOLhYe1/r9FGSnOFgQheUMZIb/b2MvkovcTVQ/w0D8IOTM64tu2pdU+az3vKlmQIAhSAyDEFX6JstiXOLgAAXqWGaXbA40oAxJiA3+UOk3biyv3n6rOuX/tuoy/912P0nXHCNhp57nw0A11Pb2DrdK6jll3Ft+0Ka2Oc8HLD5vOeKn76xTNZn78ly1LYMz6c6oomD+OVQqILlYQhOSNa3oH1C2aDVvOequeAAeu+qjtnSrnReOSOZTT2eX7T1UNVLGcGbDkyE3M3nsNP7YrgxIx6HsSE4JCQhFqMsHB1iZejicICYkkAELcuLYbeHBB+/v326WTgbzVgGLNrD2yZMkF7yc4el1LePr9fVgV6xI25rJNm1YF+9vP38OXy07iyLWHWON5RznoPA0MQdEc6TGsRQn0mXlQ/fCNaFkSPWfsxw2fZ+bj1ymqtf+kd80CaFfRDVvOeKsfPpH/CIKQUpyBmABM3X5JdTjnV1vnKnmRwdFOfQduOuOtvjvzuzrju9Vn4PM0EB/8fRgrP6yFjI52cXpOz5uPUTBbOjjb26DXjAM4e9cPGwfXUQmJICRlJAEQ4sbBv/T/7O6bKR/Q6GtrjyhZs8HCvo4/IEbwz8ZcJCA4BK1/26Vmr/608PEn7MJbp0g2ZHa2U0vef2y/FCH4z+hoi0qR3C/4Y9e2vPWcfwRBEOIbzvSzn8ilsMaCzcvkQi4XJ3OtExOApUdvqRVTBv/k2gN/fL7wBKZ2rxCjBoiWTN12CT+tO4smJXNgYIPCyliB7Lp4H2085PtVSNpIAiDEHp/LwOnl+nqlt609mhTBxtNaqlMubyZVzGtvmxbDmpcw388l5XEdy6Hr9P2qcdaQJkXh+ywYgcEh6FAxr5rFb1A8BxYfuamcLwxNLH8Q82dxVscTBEFIyXBVlJ3J7/o+x32/ACX1MWhSKgeyrnXAdR9/fL/mjNrWoaIblh+7hXWn7mLtybuqu/DsPVfxhkdulHXTrkLRseP8PYxdf1Zd33DaC08Dw+uvDl71kQRASPJIAiDEnl3jdYOvwo2BXGWtPZpkj5fvcxy/+VgZJv3RvaL6QSqcPT3yZnGOsB9/kA6NaAQH27RRzlQ1LpldJQCBIaHqdrsKeVC/mHTWFQQh9cDJkDyZnNTFEsqApvWsiC7T9iEgOFQ1H/z6jVLInckJEzdfwHerTsPONq1aEZiz9xp6Vs+P895PkCeTI354s0yE71yaLdB0IdQEJf1hPdXui3r2nxy8Er0tsyAkFWRaUIgdj28Cx/7V1+t8Zu3RpKjZf/pY08/6/bqF0LBEjmhnuKJbpq5dJJsqdCNselOrcLjuXxAEIbVTIV9m/NrJQ9mCDmpQREmB+tUtpJKF24+fq+CfEyycRKHUkrP88w7cUJIe1hQcvvYQoaEmbD7jpeSWrCWY1aeK+fg0WSDnvPzwyF9LjAQhqSIJgBA79k0FQoMA99pAvqrWHk2KYO1J3biGcp3XIZ2DLWoU1g29mpXKCbuwZEAQBEHQ0EXt5KimeLdOQXXbyd4GX7YqYZ44WT2oNr5sVVI5p1UrqGunZu2+is8XnUD7qXswYfMFc7OxNuVyKxe1qmFOal2q5FUFwYTJgiAkZUQCJMSc4IDw2f/qA609mhTB3cfPzYVjrcvqRjavwxfNiiOzsz0GNSwSD6MTBEFIeUReRW1WOhfmvlMFeTM7wz1rOiXBpLkC7ZTZSXjzWW/zvtN3XkZwiO4l0DLsO5urCsuP3UbvGu548CQQl+89VTak0a3kCkJSIElMEU6ePBnu7u5wdHRE1apVceDAgWj3nTVrlvrjtbzwcUI8E/BEe/1bcnaVbvyVITdQuJG1RpaiWHn8tnqZK7tnfkHzHxdo68kfI+paBUEQhJhBCSWDf0sKZE2H+sV0DxVCeRD1/pQI0W2IFsyE37f96hVSqwmV3fVqwMErug+BICRVrJ4ALFiwAEOGDMHIkSNx5MgRlCtXDk2bNoW3d3jGHZmMGTPizp075su1ay92SBVeg9MrgNF5gFmtAO8zQEiQ3n5kjv6/fDfARhaP4gNa0hFxjBAEQUh6vFenkDJoKOfmgindKpi3c/Y/qnqsaoW0DPPYjUd48CTAvJ23d1/UndkFISlg9Sjul19+wbvvvos+ffqo27///jtWr16NGTNmYOjQoVE+hn90OXPmTOSRpiL2Ttb/X9sFTKmmr6e1BUJpc5YGKN/DqsNLCdx/EqCadp2+4ws7mzRoGdbdVxAEQUg6VC/kio2D6yJ3Jkc42dmgUYns2HvpAdpXiHrShgXFtBP1vPUY6095oWvVfKqRY9fp2n1o26f14mW1VxCS9QpAYGAgDh8+jEaNwuUkadOmVbf37t0b7eOePHmC/PnzI2/evGjTpg1OnToV7b4BAQHw9fWNcBFegs8V4MY+HegXahC+XQX/1Ji0BjLnt9rwUgL8MWgwbpvqRGnoTzOHuUcIgiAISQvWBDjb26rJx9+7V8ThLxsjv2tEuZAlzcvkjGDwsPrEHSUdopPQtnPRqxsEIdWsANy/fx8hISHIkSNioQxvnz2rG2xEplixYmp1oGzZsnj8+DHGjRuHGjVqqCTAzc3thf1Hjx6NUaNGJdg5pDg8F+n/C9YFeizVhb9B/kDQM32dXX+F12Lf5QfwfR6sLOM+qFsQPaq5W3tIgiAIQgywtUkLW5uX79OidC6MWXdOGTyw4zD7sxhsO3cPParLd75gfaxeAxBbqlevjp49e8LDwwN169bFkiVLkC1bNvzxxx9R7j9s2DCVKBiXGzduJPqYkw2sRj2xQF8v20n/b+sAOGUGMuYGshQA0r7im094Jfsv6+KwZqVzKn0pC8cEQRCElAGLiUvmyqhm/H/ecC6CJSiTgmsPnuL71adxw8ffquMUUjdWXQHImjUrbGxs4OWlGyEZ8HZMNf52dnYoX748Ll68GOX9Dg4O6iLEgBv7gQcXAFsnoHgra48mxbL/irb9NLyjBUEQhJTFGx65VY3XP/uvq9v1imXDqdu+uOcXgDen7FErA+wAv+C9ai8UEzNxYEdjQUixKwD29vaoWLEiNm/ebN4WGhqqbnOmPyZQQuTp6YlcuaSI8rXZ+Yv+v0x7wDGjtUeTYvX//FEg1QpqtwhBEAQhZcE+Av3rFUJGRz3P2quGO+oW1ZaiDP7JgSs+ShJkcOaOL3rOOIAi/1uD9afuWmnkQmrB6i5AtADt1asXKlWqhCpVqmD8+PF4+vSp2RWIcp88efIoLT/55ptvUK1aNRQuXBiPHj3C2LFjlQ1o3759rXwmyZw7J4AL64E0aYFaQ6w9mhTLoas+Smnl7uqMHBmlf4UgCEJKhJ3YP29WHAMbFMZ9v0Dkc3XG04BgLDp8E5zcr1k4K3ZeuI+f1p1VicHZu35oM3kXgsKajP2x/RKalhK3QyEFJwCdOnXCvXv38NVXX+Hu3btK279u3TpzYfD169eVM5DBw4cPlW0o982cObNaQdizZw9KlixpxbNIAez8Wf9f6k3AtZC1R5Os4HLtnzsvI3tGB7xRLk+US7erTtzG8CWecHG2U7erFpDZf0EQhJQO3YPyuepQiwF9r+r5USF/ZhX01x6zVQX+G057KXMIBv/sN0AL0SPXH+HcXT9M3HwBuVwcMaKVxDhC/JLGZIrc7jVlQxtQFxcXVRDMhmICgNvHgGl19fUPdgM5S1t7RMmum++H846aO/H+0b2imu2xpOPve3Dwangh2C9vlUO7Ci+6VgmCIAipg9Frz+CP7ZfRoHh2Jf+58/g5pveshDl7r6rVgRwZHeDlq5uJbRpSB4WzZ1DXd164h7N3/FCjsKsqNo6qIdmr2HLWCz+sOat+i8q6ZYr3cxOSfpyb7FyAhNckNCTibeZ/G0bo62XekuD/FTBf3nrWWzk4fLbwuNJyLj9223w/v8R/Wh/RwvZJQDCOXn+krlcrmAXl82VCwxIRrW8FQRCE1EXHinnV/1vOeqvgP529DWoXyYp2YU3GjOCfLDykrUSXH7uFXjMO4Ps1Z9By4i68O+cQQkMjzuM+fBqID+Yexr9hBciR4f7frDyNi95PMP+gOCOmVqwuARISCX8fYNHbwOVtgHMWIHcFoOxbwINLwNWdgI0D0PBLa48ySbL/8gNc8/FHhwpumLz1In7eeN58n+/zIGw/rxu7jOtYDp8uPI4tZ7zhHxisln6NxweHmpAvizPmvxez4nZBEAQh5TcYq5Avk5L7kAYlcsDRzkZJhZztT6rmYcVzZlAyocVHbqFIjgz4YvEJMN7navMl7yfYdMYbi47cxFuVdDJBRq44hXWn7mLv5QfoVDnvC7LUree8cfWBtiA9cVM/96u4/egZxq4/p4qbS+dxidfXQbAOsgKQ0nn2EDi7BvirCXB5K+ewAf8HwMWNwJJ3ge0/6v2qvp8sm3w98g/EG5N2YdiSEwly/PNefuj+1358vuiE+uL9bYu2m21eWhdnsdU7dZv8kmZr+LxZnPAsKARbz4Y7O+y6eF/9X6tI1gQZoyAIgpA86WgRuLcI+13h5NE3bUrjrUpumP9eNWRNb4/7TwLUBBNrzjpUdMPqD2vh06ZF1f6j15xRs/5kw6m7WHH8ttl17uStxy8854zdV8zXKSV6HhQS5Wo3V7nf+n0v/J4HYdz6c1h69Ba+XnEqAV4FwRpIApASoaxn90Tg99rATwWA+V20v39GN6DvZuC9bUDtT4EcpYHCjYDG3wANEmf2n19eUX3ZxJVpOy7jxM3HahmTs/HxPdbPFp0wuzIsPHwTgSGhqFM0G6Z0q4C2HrkjeD5Th9myjN62xlO3gCe7LugEoHZhSQAEQRCEcFqVzaUC/GwZHFC3mLYJJQzyx3Qoh0zO9hHqxd6vUxA/tS+LtGnToE/NAiiaIz0e+gepyamA4BB8ufyk2s/eNm2ECSgDFhbvvvhArQpkcLBVq9OGNbUl+y77qN+8A1d98POG81h1Qv+mHbr2EJfvPVFJgWFnKiRPRAKU3AL7p/cBFvwEPwfunQMcXYA8FfU2g60/ADvGhN92LQIUrKuD/oxh/RJyl090yc/Bqz4YvOAYAoJDsfmTusjoqB1x4gpnRGbuvmp+adhtsX6x7HE6FpMHzqDkd01n3jZ371Ucv/FIfUm29sit9JQOtmnxbZtSKtinxRtXAIJDQ9G6bG7zl/nv2y9h81kvJQPyfRaMC95P1NtTo5AkAIIgCEI4GRztsPajOuo3wpCNRqZv7QKqezC7x79Z3i2C1ejwFiXQe+ZBLDx0A0VypFd1Aywe7luroKoT4ATUgPqFzY/hLD5pWDy7Cv5Zf3DixiNUyJc5wnPSfchg1p6rL9zHjsb8Da5dJBuGtSiO4jnDi00fPAlQCQaTFyHpIglAciDoObDsA63fp6QnMtlLAfmrA7aOgO9t4NQSvb3hV4BHNyBD/HsJ/3fohnIpGNuhrNIsvnL/gzcwdInWLpLNZ7wifJEZTVHmHbiOvZceoHOVvPi4kV7ejI6p2y4puY2lx35cEgDO9Hedvk8thS4bUNOsb1wdNov/ceOi6FPDXWkuC7imMycJuTM5YemAGngWGIK8WbTrT6ncGZHf1RnXHvhjreddVQBM6LJgWIAKgiAIggFn/19G9gyO+KNHpSjvq1MkGwpkTYcr959i1Eotz+lSJR8alMiuEgBOjHEyigG5vU1a8+p063K5ceneE50A3Hz8wmQd6wfsbNIgTyYnc71AoxLZVc3BMgvji+3n76nkZOun9dTE2A0ff7T6bZcqaN72WX3zSoSQ9JB3Jjng+R9wamlY8B8205/GRs/s2zkD3qeAg38CeyeFB/91PgNqf5IgwT+z+y+XnVT2l5vP6ALYl8HW59+sOq2Cf36ZkPUnvSLsQ61ij7/2q9mJu77PMX3HZbWcGR2BwaFYEOZe0KKMPseDV15Mjig3CgoJfen4lhy5iZO3fNVsyF+7rpiPzzbtpH6xbGq5tUe1/C/o+DnrUd5i5oRfgEYxFq3c/t53TV1nfYAgCIIgxCf8bepWVdfvPQ8KVYE+E4CCWdMht4ujkq3W+mkrKnyzUc3kX/fxh6NdWmU9Wi7M/vPYzUeqyJe/w9T+j1mnnew6VMyLoc1LqOuZnO3wSycPZEmnZ/XZm+C/96vDyc5GJQj8DeVjhy3xVMe5/fg5jl5/qJzxhvx3DHceP0NKwO95EDae9nplXJEckBWApA61LQem6et1PgfqfArY2AOmUCCtjU4KTi3TM/9B/oBTZq3tL9o0Tk9HTZ+zvc1LZ/Vn772mZDyEf9wty4bJiqLhl43n1Ex4WTcXfN+2DFpP2oVt573VzLmTvY3Z15jHdMvspIJvb78AtcQY3Yw+Vwt4zKzpHfBJk2JY43lXfYkxaXCwtVFfRAzm2WWRS5R/9aoUpVcyE4RfLVx9Vp+4o5ZUbz16psaR2dlOza7EBrouTNh0wZxA8PV8s7wkAIIgCELC2ImO23BOJQBNS+Uwd5lnt2Hq+A2t/qiVp9X//F1N52CrfpPJ5XtPUePHLer3lIXH7FnD360PGxRWgf6Ezh5wd02nZLufNS2mJt9GtyujVsXrF8+mfn/XnLyD03ceR6g52HHhHo5ce6RWE2zTplE1DckZ/8BgdJ2+XzVq+7ZtaTUpmJyRFYCkzo0DwF1PLe+p1g+wddB6fwb/hAF/pT5Ag/8BTb/XCUKxZhFrAmLI9Qf+qP3TFrw393C0+zBopzbegAnAy+D9xkz9l61KonSejGoVgF9U/HIwoHUmaVkml7n9+YZTEVcJLKHGnjQonk3NdLCIigG7Z1jQ/cl/x/Hd6jOqgJdLnPwCigqOjTMVOTM6okweFzVbMv/AdbVsSqiLjG2TFX6JWiZFbTzyKJ2nIAiCIMQ3lJfSnpOz8R/ULWTePqhhEWVWwWCVv5MGLcro3yfX9A4olC18OzX9U7ZdUtc/alhEyVz5+8ffsHJ59WoBVxcolWXwb3msxYdvmhMM9roh7JGz74r+7WWSQPXAO7MO4ttVer/kRGioCUMWHFfBP9kTqbg6OSIJQBLHZMz+l+mg/fsTEDYYeRoYgl0X7qlMNzrtPx0HDF3fyxIAzsJ/t1pLfxjYV3bPor5MjAB//cm7Zg3+tvM6GahfPDsal9RNsrjMFrnBiXFcQ3rEhlo8ZqX8+rWhYwGXHZccvaVmHIwvrUlh9p2RoX6R8MuTFzJ33zXsDvvjZsv2uNCzevjMQPdqyc9eVRAEQUg+fNa0OM582yxCV1/Wpo3vXF7NVE/qWkFJfyjlofzHgLUFv3Yqhy2f1IVH2O9lkezp8XbY7+Gr4GoCzTG4as++BdULuiqXPHLz4TMlYiBcse/x1wFsPuutVuc54ZicmLP3quqtYEA3JMYiyRlJAJIwt25cRfDJZeq6v8fbCf58a8MCcsbc1PNFhvIaFt6SjxsVUf9z9pxe/IR+w5x5v/lQ/2EzSKfdGAuPhjYvbj5O8zDNPpcMWR9w7MYjtUSZ0dEWFfNnRrWCrsp5h7MR+6/4vDAOFi5Rx8jj1gqz1qxeyFX9/8++6+Zgn7MW/CJiIkA5kTGrb8A/Xj43qVwgi5rJoASJX2RcNSCRnRFiCr9Iec4jWpZAqdzSNEUQBEGwHiVzZ8SGj+ti1Ye1lPzHshkZDTkKZkuPv/tWxfdvlsbcd6oqh6GYwGMZUl0WM0/o4oFcLk6qN46BsfpgaTe68kR4IXFS5/6TAHMD0P+1KKGKoxm7MMFJzkgCkERh99jlM36AHYJxOLQIdvglrIac2bjlH2dU3QHp5MMCXcplOFvOYJmcueOn/v9q+UksPnJTNc2iVOiHNWfUds4kGC45pFL+zGpmnjKgP7ZfUjP9pG6x7OpLh6sLXAkgLAzu/49uae7t+1xtM2b/qxVyNX+RdazkpsZD7T5nGAzrNMqNjLbqls1PCP94mXjwj7lErgzqeUe0LGm+n8VU5fLGLXjnqgSXYvvWLhinxwuCIAhCfJLP1RlumcN/iyOT3sEW3armR04XXUMQUz5qVEQ5BE3vWUk5FhH2yyFcHZjQubx5X6OIeNnRW/E6g87ffjocBb+iOJdFvGxu9uNaXegcE1gU7fc8WEmYGc8Yk3qHrr04QZmckAQgCbLtnDfenrEH7UI3qNtzghubJSkJxdqT4Y2riFHAajn7P3mrnv0fUL+QKrQ1NICUAfFitDPnbDu7816+/1Rp87l/5OB4SGNt8Tl771VM26GPyy8QA86eVy2QRTnzUDs4fKmnshZj5b2RAFjuT//kH94sY77NlQFjfL1quKv/N57yMq9WEGP2v2SujOp8CAuoaoc5/XB7dL7MgiAIgiBA/db+2auyWUJE2nrkUav0rBko4+ai6uKyZ3DA3HeqqMk29scxJg/Pe/kpY4/Ywln4dSfvKvvT+uO2of8/R5RJycvg6j6lwr9vv2Ru0vkyvHyfq0JqMuqN0mpikJOYJLKqILkhCUASgzKad+ccQp3Qg8iZ5iECHFyxNrQqdl+6nyjyHwbAUa0AbD93T83+s8HIW5W1zaVlAsAZemMGgfCPm3/kU7tXjLIAtk6RrEruwyJdSo7oPNAqrJkWYfHRgverq+VKFjJRHkRpDsdpZN2RHYI449Cren41o8/HGDBbZzDPAl8WJUVOAIw6ASM5oVMRk4DIiYsgCIIgCDGTHHmOaoKvWulV9cldK2D/8Ibq97hB2G/3+E3nseL4bbSauAtdpu9TPQQMJm+9iBqjN6vkICp2nL+HumO34oO/D6uGoDQBsazriw5LWfFXK06+1G7c2J8LFZz9Z8xCjP8PXZUEQIhHmM0yKH4v415121ShF4LT2CmbroTy0WUDEQbDadMAnzYppraxkZXlbPnRsGBZF/zo2fKSuTKY/0CM7oITu3go20wea2JnD1X4GxUq0H6ztAraf+5YTtmDMbOODJtycbWATUvId2H9BIrlyBBBVmTw9Rul4Pl1U1QpEPF5mWAYRcwG7PJLLGctjGVSaiCblX65vakgCIIgCFHDWIF9CgwMRz3DJGPDaS8MmndUTc7RDMTSGZCTiqwxHLf+3AvH3XDqLt6ZfVAVHbO+oF35PKrejhy+6vNSj35jpSFtGm1/OvcVKwYHwlyMqrjrOkPLBOCclx98nwchuSIJQBLj+M1HSIdnKBtwVN12LN8JZcKq+llQmxDQvovQL79Ijgxwd9WBtWV3wGPXXwyWS+bSOjgW5LLCn4+rVzQ7lvSrgS2f1HtlAM0mWnPeroL2FSN2BI4Kw2qMqwCkoYX8xxJ+wUTVw6BN2HLkqdu+aoWFjkcnbz9+YQVAEARBEISEo0bhrPinb1XVY4BQGkT2hMU43n7PlabfSBIs3QbpDPjV8lNqopSyonUf11ENyt6uWUA5HNHJkEqK6Ip5L3o/Udc/bqRlyEZn5FclDJaTitkzOqrEgysDbIiaXJEEIAnBghgG3bXTesLGFARkLgBkK4aaYQ43CeE7y6ybhbukQ1ggbtiIHQ0L+rmPIQnyCPP3NWbKOTvfqEQOvFEuN8Z2LKey/czp7OEey+ZZr4L1AGzKZRBdAhAdHJNha8ai44/mH1NFyBkcbVHANX7HKgiCIAhC9LBJ2YbBdbC4X3VMDrMN3XPpvgrwjQlHA7oL9p2tJ+6oRqAcmXJjqgcMS3LGHobiICr3QHIwbDsditqHxTtUP7BzsSVPA4JVYM/uyOe9dMJQ2T2iI2D3sCZgf+28EqVdeXJAEoAkBGU3/CA2sw1rxFW8pWroZVhd0iv/VXq12LL30gPcefxcaewN/33acBoFunTJYcbMrJqdAYtkD7f2ItTa/9mrEiZ2KR+t3Cc+sLVJa+4fQBcBj7yxt+f8olkxrBlUW2n784etcjB5sVyiFARBEAQh4WF9YMX8WZSyIJ29jeoxdOaur7k+z2goRofCTWe8MGyJp7nekL0MIq/2c6LQcFE0YBBvBOj7LWbz82RyUk3QeFfkydXRa8/gw3lH0WHqHrNVKpumWcJaSMZNNDsxnAcNKJ+OSYGxtZEEIAnwPChEfWAo/7FBCBraHNN3FGth9qhn8S2D8bWe4Y0o4oMlYbP/b3jkNv8xcSWAGTKfjx37jt3QhS7slBuVTj+xoD0Zs/2uVfLFaRyUB7EwiQ1Ttn1aD7uHNsCP7cOdgwRBEARBSFxo/21IbCgDMhKAjhXzYmyHskrew+Zk1PwbioXmpfWEoCXG5CWLc2kHytX+Gj9uUcE8bxtuilUL6P0Mq9IdFsE6bUKXHNE1jaxBIJFrCglXILpW1asAny48jm5/7lPOQvMOXEfDn7fj/bmHcDfs8UkV8Ti0ImyYNWfvNfWBYdFKZTcn9LdZjgwmP8ApC5C3qvmPo2uV/Ph103nVpbZt+fjpCUBpz9ZzOnO1dOBhkP1j+7J4c8puVdxrLpa1kP9YA1qJnf2mWbzM2DMZ4AyAIAiCIAjWlwRtPXdP2XR6hmn4uQJguA1uOu2FvnMOqetOdjaoF8kFkHBfynrp2U9b8gUHtenHas87SslAd0L2JahWUAf0TADoIERHIUqwGRcsO3ZbJRqc3fd9Hqz2qxKNuqFPTXf8u/+aUm6wRtOyTpMJy0P/wFj3VEhMJAGwAiyYHbr4hCo+MaRjrniMb299BHc73RQLHl0Bm/C3p0uVvPhtywXlO3vq9uNYdZc9dNVHLZv1r18IhS0kPNT1c8mNfzBGVbsBl+T61yukvP+5xEXKJ4FiWZHrCIIgCELKggH992vOYG+YfIeS46I5MkSo+6MV58lbvqhXLBuc7F80+6AygFLhRYdvYtaeKxFchejYw/BhQmcPs5ynWgFXZQ7CgmMmBwza/9l3zVwkHGoyYd/lB2Z5dGRyZHRUSgLWCZy+/RgrT9zBrYfPlMsRaw5j2k3ZWiTt0aVgq89VJ3TwT33/lK4e+M15OtzTeuGuKTO8640BGo2K8BhWnTcLW/Jip102p4iKXzeeR8Oft+HPnZdVN96zd33Re+ZBLDl6C31mHYxg7clsm9Qpki3KDyotQd+vG97Jtny+2OvuBUEQBEEQXgZ19l+3LmW+HVlyzNn5H9uVVcG/ZZ+fyLxVSfcpYgNR9gagWw9n6lljMK5juQjuhE72NqhZ2NUs45m+8zLO3vVTqwTtK7ihb+2CqsFZurD+RtHXMWRGj+ru+O/96ioheL9uoSQf/BNZAbAChkVV7xruyrceeycDoUfw3GSHwXZf4Z86fbRJbSQ+blREddmllWXbybux8IPqEdp6s9hl0taLStrz3eozGLPunJLzcMWB3PB5prRws/pUUX9Y7DhM6hbTOrjI8A9uaLPiynOfdlfMdgVBEARBEOKbXjXcVdD+07qzaFU2V5R9gRi/vAy69dCS/OoDf7OF+KdNi2F4ixJRBuXftCmNNybtUg6MhvV539oF4GLhOphSSfopSgpOAMrldQFuHwM2jlS379f6Gj980ClamQvlO8v611SV63Tu+XLZSaVbM5i5+4oK/plJ583ipJprMPhnBjz/vWpKN7fzwn2M23BOtdA2Puz1wgphoksC2lVwi5FXvyAIgiAIQlx5t05BnPqmqZpRjwuMWTqGrQKQ5mW0ciK6Gfm8WZwxtXtF2IbFXV80K25uiJrSkRWARIYBOi2tSJmsNsCit4HQIKB4K7g1GqBsP18Gvff/6FEJzSfsUBKe9afuqiUtdqObd0AXvPyvRQm1TMYZf+reKuTLpDRvP3Uoq7ruTd12CetPajchauooLxIEQRAEQUgKHYRfh44V3fDXrivK7rtkWBHxy6hW0BXLB9ZU8ZnRByk1IAlAInPl/lNVYe5olxYFT08BfC4BGd2AN357ZfBvwBn+D+oWwm9bLmLQvGPI53oeXo+fq9l+FrHULZpNZcFMFngxYLMurj5M23FZFfZSE8dGXoIgCIIgCCkBTmru+Lw+7GzSqFgoJpSKhbFKSiFJSIAmT54Md3d3ODo6omrVqjhw4MBL91+4cCGKFy+u9i9TpgzWrFmD5AIdfEjZnE5Ie2yu3thiDOAcuyZaA+oXVk49lPnQ3sovIFhJfD5rWuylTjmfNy2mCmi4H4tVGhSPurpdEARBEAQhOUKf/tddSUjpWH0FYMGCBRgyZAh+//13FfyPHz8eTZs2xblz55A9+4s+r3v27EGXLl0wevRotGrVCv/++y/atm2LI0eOoHTp0kgu+v8O6Y4B9x4CGfMARZvF+jhs2rW4Xw1c9/FX/QSypndQKwOvqjxnR12Z9RcEQRAEQUi9pDFZVpFaAQb9lStXxqRJk9Tt0NBQ5M2bFx9++CGGDh36wv6dOnXC06dPsWrVKvO2atWqwcPDQyURr8LX1xcuLi54/PgxMmZ8tTYsvukybZ/yud3nNhE57+8D6n4B1B+e6OMQBEEQBEEQUhYxjXOtKgEKDAzE4cOH0ahRo/ABpU2rbu/duzfKx3C75f6EKwbR7R8QEKBeDMuLtTA998Wo2+9irf0XOvhHGsCjm9XGIwiCIAiCIKQ+rJoA3L9/HyEhIciRI6IOnbfv3tUuNZHh9tjsT6kQMyHjwtUFa3HTxx9FcR0l0mq3HhRrDmTOb7XxCIIgCIIgCKkPq9cAJDTDhg1TNQYGXAGwVhKQM1sWXG3xD+75BaJywaxAnopWGYcgCIIgCIKQerFqApA1a1bY2NjAy8srwnbezplTN2+IDLfHZn8HBwd1SQrY2dnDvUorxK29hSAIgiAIgiAkcwmQvb09KlasiM2bN5u3sQiYt6tXrx7lY7jdcn+ycePGaPcXBEEQBEEQBCEJSYAoz+nVqxcqVaqEKlWqKBtQuvz06dNH3d+zZ0/kyZNHafnJRx99hLp16+Lnn39Gy5YtMX/+fBw6dAjTpk2z8pkIgiAIgiAIQtLH6gkAbT3v3buHr776ShXy0s5z3bp15kLf69evK2cggxo1aijv/xEjRmD48OEoUqQIli1blix6AAiCIAiCIAgCUnsfgMTG2n0ABEEQBEEQBCHV9gEQBEEQBEEQBCFxkQRAEARBEARBEFIRkgAIgiAIgiAIQirC6kXAiY1R8kCNlCAIgiAIgiCkFIz49lUlvqkuAfDz81P/W6sbsCAIgiAIgiAkdLzLYuDoSHUuQGw0dvv2bWTIkAFp0qSxSmbG5OPGjRviQpQEkfcneSDvU9JH3qPkhbxfSR95j5IHvlZ+nxjWM/jPnTt3BBt9pPYVAL4Ybm5u1h6G+lDIH3DSRd6f5IG8T0kfeY+SF/J+JX3kPUoeZLTi+/SymX8DKQIWBEEQBEEQhFSEJACCIAiCIAiCkIqQBCCRcXBwwMiRI9X/QtJD3p/kgbxPSR95j5IX8n4lfeQ9Sh44JJP3KdUVAQuCIAiCIAhCakZWAARBEARBEAQhFSEJgCAIgiAIgiCkIiQBEARBEARBEIRUhCQAgiAIQqLBBozLli2z9jAEQRBSNZIAxJLRo0ejcuXKqpNw9uzZ0bZtW5w7dy7CPs+fP8eAAQPg6uqK9OnTo3379vDy8oqwz/Xr19GyZUs4Ozur43z22WcIDg6OsM+2bdtQoUIFVUleuHBhzJo1K1HOMaXRu3dvFXR88MEHL9zH94n3cR/Besh7lHzh+8LvQSFpcu/ePfTr1w/58uVTvyU5c+ZE06ZNsXv3bmsPTbD47vvxxx8jbGeSzO1Cyo717ty5g65du6Jo0aKqUe3HH3+caOcoCUAs2b59u3rD9+3bh40bNyIoKAhNmjTB06dPzfsMHjwYK1euxMKFC9X+t2/fRrt27cz3h4SEqA9EYGAg9uzZg9mzZ6vg/quvvjLvc+XKFbVP/fr1cezYMfWh6Nu3L9avX5/o55wSYFvu+fPn49mzZxH+eP/991/1w/g68DMgJO33SBBSKwxKjh49qn5nzp8/jxUrVqBevXp48OCBtYcmhOHo6IiffvoJDx8+tPZQhESO9QICApAtWzaMGDEC5cqVQ6JCG1Ah7nh7e9NG1bR9+3Z1+9GjRyY7OzvTwoULzfucOXNG7bN37151e82aNaa0adOa7t69a95n6tSppowZM5oCAgLU7c8//9xUqlSpCM/VqVMnU9OmTRPpzFIOvXr1MrVp08ZUunRp099//23e/s8//5jKli2r7uM+ZO3ataaaNWuaXFxcTFmyZDG1bNnSdPHiRfNjrly5ot7L+fPnm+rUqWNycHAwzZw50yrnlZKIz/eofv36pgEDBrzwd8q/y02bNiXiWaWu947kz5/f9Ouvv0a4v1y5cqaRI0eab/PvZ+nSpYk+ztTIw4cP1eu9bdu2l+7zzjvvmLJmzWrKkCGD+vs5duyY+X6+d3wPf//9d5Obm5vJycnJ1LFjR/VbJ8TP30+rVq1MxYsXN3322Wfm7fwbsQzRFi1aZCpZsqTJ3t5e/Z2NGzfOfN+wYcNMVapUeeHY/O4cNWpUIpxFysc7gWI9S+rWrWv66KOPTImFrAC8Jo8fP1b/Z8mSRf1/+PBhlSk2atTIvE/x4sXVDObevXvVbf5fpkwZ5MiRw7wPl2R9fX1x6tQp8z6WxzD2MY4hxJ63334bM2fONN+eMWMG+vTpE2EfZvdDhgzBoUOHsHnzZrUk9+abbyI0NDTCfkOHDsVHH32EM2fOqPdFSDrvEVfKuGrAmRWDv//+G3ny5EGDBg0S8WwEwbpQlsAL5SSWfw+WdOzYEd7e3li7dq36/aLstGHDhvDx8THvc/HiRfz3339qtnPdunVqRaF///6JeCYpGxsbG/zwww/47bffcPPmzRfu5/vy1ltvoXPnzvD09MTXX3+NL7/80iwL7tatGw4cOIBLly6ZH8NY4sSJE0peIiTdWM+aSALwGjDgoDSnZs2aKF26tNp29+5d2NvbI1OmTBH25QeA9xn7WH4gjPuN+162Dz84lhIJIeZ0794du3btwrVr19SFGlhui7xcziU81lx4eHioAJRfuKdPn46wH9937legQAHkypUrkc8k5RIf75GxBLt8+XLzY/hDaWhtBSG1YGtrqz77lB7wN4m/VcOHD1eBIeHfGgNHShgqVaqEIkWKYNy4cWrfRYsWRZDizZkzR/291alTRwWqlOsZv1fC68NJDL6+7CAbmV9++UUlZQz6qRXnd9nAgQMxduxYdX+pUqWUfIQTHwb//PMPqlatqr4nhaQb61kTSQBeA+rDTp48qb4IhaQPdXbU4/EHkbPMvJ41a9YI+1y4cAFdunRBwYIFkTFjRri7u5sLeSzhj6WQNN8j6ml79OihEgNy5MgR9XcqRcRCaoQJM7XJ1P43a9bMbC7Bv7Hjx4/jyZMn5iJG48IaNMvZZM5qcgXNoHr16iooilwUKbwerANgssaVZUt4m8GnJbzN70LqzI1VACMBoNJu3rx5apvw+gxIobGerbUHkFxh9r1q1Srs2LEDbm5u5u10WGDBx6NHjyJkhqwM533GPpx1scSoHLfcJ3I1OW8z4HFyckrQc0vpEhO+d2Ty5Mkv3N+6dWvkz58f06dPR+7cudWPHDN+vqeWpEuXLtHGnNqIj/eIMiDOpnE5nYkEpT98jJCwUI6lZf7hSJG89WFS3LhxY3XhLDL/PjjTTBkPVzCZFEQm8symkPBwdYUSkWHDhsV6woKTIl988YWa8KBK4MaNG+jUqVOCjTW1MDCBYz1rIisAsYQ/bvxALF26FFu2bFESEEsqVqwIOzs7pU024CwJZyc5a0L4PyUL1F0asMqcwX3JkiXN+1gew9jHOIYQNzgDxj9aBiWRtft0xeB7xWp8LreWKFFCXBmS6XtE3SVXaZgkcFaMSYWQOCs4tLUzoGSRs8lC0oK/M6yl4UoApQiUClEqYnmxXHnj7xdXEQzojMJkr1ixYlY6g5QL7UBZa2FZ78fvuci2rbxNORDrBwiD07p16yrpDy9M9mg7KSTtWM+ayApAHJaCGFBQX0x/WEPH5eLiombm+f8777yjihRZLMI3+sMPP1QfhGrVqql9aSXFN58yhTFjxqhjMKDhsenTTOiHPmnSJHz++ecqeOEHkEVYq1evtur5J3f4ZWksrxpfnAaZM2dWS+HTpk1Ts2L8Q2axr5A83yPOcvILnKs11NcKCQ9XWigt4SoNZ8Vodxf5PRQSDybMLPLlb0jZsmXVbxaL5/m706ZNG1XAyN8mepxzGwNKBvr8neHfjCF15ApCr169VH0Ak7pBgwapotSkMIuZ0uDkBaU7EydONG/75JNPlCf9t99+q2b1mRwwPpgyZUqEx/JxXNnhBMqvv/5qhdGnHAYkUqxHaPVOKMdj3w7eZn1BgicJieY3lELgSxbVxdIK8tmzZ6b+/fubMmfObHJ2dja9+eabpjt37kQ4ztWrV03NmzdXlmq0X/vkk09MQUFBEfbZunWrycPDQ9l+FSxYUOwm48GmMCosLSY3btxoKlGihLL3pIUa7fMsbQsNG9CjR48m2vhTA/H5Hhn4+fmpvz/+LQoJR48ePUzt27dX1x8/fqzsimlzlzdvXtOsWbPEBtSKPH/+3DR06FBThQoVlG0u/x6KFStmGjFihMnf31/t4+vra/rwww9NuXPnVraGfN+6detmun79egQb0ClTpqh9HB0dTR06dDD5+PhY+exS7ncff2f4ux+VDSjfo3z58pnGjh0bpaUrvxf5PvP7T0gesR6ieB5avSY0acKeXBAEIUVx9epVFCpUCAcPHlRSByHhJFuUjHBGUkh50HKSNqLGLKUgCCkDqQEQBCFFwdoBY6mVS7ES/CcMrL1gcRwLSCP3LBEEQRCSNlIDIAhCioLFcfXr11d6ZksvcyF+oa6cqyvUJ1NPLgiCICQfRAIkCIIgCIIgCKkIkQAJgiAIgiAIQipCEgBBEARBEARBSEVIAiAIgiAIgiAIqQhJAARBEARBEAQhFSEJgCAIgiAIgiCkIiQBEARBEOIEewCkSZMGjx49svZQBEEQhFggNqCCIAhCjKhXrx48PDwwfvx4dTswMBA+Pj7IkSOHSgQEQRCE5IE0AhMEQRDihL29PXLmzGntYQiCIAixRCRAgiAIwivp3bs3tm/fjgkTJqjZfl5mzZoVQQLE25kyZcKqVatQrFgxODs7o0OHDvD398fs2bPh7u6OzJkzY9CgQQgJCTEfOyAgAJ9++iny5MmDdOnSoWrVqkpeJAiCICQMsgIgCIIgvBIG/ufPn0fp0qXxzTffqG2nTp16YT8G+xMnTsT8+fPh5+eHdu3a4c0331SJwZo1a3D58mW0b98eNWvWRKdOndRjBg4ciNOnT6vH5M6dG0uXLkWzZs3g6emJIkWKJPq5CoIgpHQkARAEQRBeiYuLi5L8cFbfkP2cPXv2hf2CgoIwdepUFCpUSN3mCsDcuXPh5eWF9OnTo2TJkqhfvz62bt2qEoDr169j5syZ6n8G/4SrAevWrVPbf/jhh0Q+U0EQhJSPJACCIAhCvMEEwQj+CQuEKf1h8G+5zdvbW13nLD/lQEWLFo1wHMqCXF1dE3HkgiAIqQdJAARBEIR4w87OLsJt1ghEtS00NFRdf/LkCWxsbHD48GH1vyWWSYMgCIIQf0gCIAiCIMQISoAsi3fjg/Lly6tjckWgdu3a8XpsQRAEIWrEBUgQBEGIEZTy7N+/H1evXsX9+/fNs/ivA6U/3bp1Q8+ePbFkyRJcuXIFBw4cwOjRo7F69ep4GbcgCIIQEUkABEEQhBjB4lzKdFjImy1bNlW4Gx+w2JcJwCeffKLsQ9u2bYuDBw8iX7588XJ8QRAEISLSCVgQBEEQBEEQUhGyAiAIgiAIgiAIqQhJAARBEARBEAQhFSEJgCAIgiAIgiCkIiQBEARBEARBEIRUhCQAgiAIgiAIgpCKkARAEARBEARBEFIRkgAIgiAIgiAIQipCEgBBEARBEARBSEVIAiAIgiAIgiAIqQhJAARBEARBEAQhFSEJgCAIgiAIgiAg9fB/bj9JgPXfa5YAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 900x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9, 3))\n",
    "no_transport_model.state[\"biomass\"].mean([\"latitude\", \"longitude\"]).plot(\n",
    "    label=\"Zoo Seapopym\", x=\"time\", hue=\"functional_group\"\n",
    ")\n",
    "plt.legend()\n",
    "plt.title(\"Evolution of the biomass\")\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "seapopym-py3.13",
   "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": "3.13.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}