{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f031be76-56ab-48f7-9892-afdaccbde66a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import salem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5908d766-1b62-4da1-8835-7bb8c7103977",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = xr.open_dataset('geology-optimizedC1DF.nc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "efffe4bc-8ad9-430f-8a75-93d41b8b1461",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/users/fmaussion/.miniconda3/envs/oggm_env/lib/python3.10/site-packages/salem/graphics.py:745: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead.\n",
      "  geomtype = shape.iloc[0].geometry.type\n",
      "/home/users/fmaussion/.miniconda3/envs/oggm_env/lib/python3.10/site-packages/salem/graphics.py:749: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead.\n",
      "  if 'Multi' in g.type:\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds.attrs['pyproj_srs'] = 'EPSG:32632'\n",
    "ds['thk'].attrs['pyproj_srs'] = 'EPSG:32632'\n",
    "\n",
    "ds['thk'].salem.quick_map(interp='linear');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "75344953-0f73-4418-9f5c-c4643bb55e01",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       ".xr-text-repr-fallback {\n",
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       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
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       "  margin-bottom: 0;\n",
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       ".xr-section-item input {\n",
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       "\n",
       ".xr-section-summary-in + label:before {\n",
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       "  content: '►';\n",
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       "\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-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",
       "  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",
       "  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-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-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",
       "  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;\n",
       "Dimensions:      (y: 994, x: 423)\n",
       "Coordinates:\n",
       "  * y            (y) float32 4.963e+06 4.963e+06 ... 5.062e+06 5.062e+06\n",
       "  * x            (x) float32 2.643e+05 2.644e+05 ... 3.064e+05 3.065e+05\n",
       "Data variables: (12/15)\n",
       "    thkobs       (y, x) float32 ...\n",
       "    thkinit      (y, x) float32 ...\n",
       "    lon          (y, x) float32 ...\n",
       "    lat          (y, x) float32 ...\n",
       "    usurfobs     (y, x) float32 ...\n",
       "    uvelsurfobs  (y, x) float32 ...\n",
       "    ...           ...\n",
       "    arrhenius    (y, x) float32 ...\n",
       "    slidingco    (y, x) float32 ...\n",
       "    thk          (y, x) float32 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
       "    usurf        (y, x) float32 ...\n",
       "    icemask      (y, x) float32 ...\n",
       "    divflux      (y, x) float32 ...\n",
       "Attributes:\n",
       "    pyproj_srs:  EPSG:32632</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-a0308d16-2c3f-4c30-8579-bd5eab380817' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a0308d16-2c3f-4c30-8579-bd5eab380817' 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'>y</span>: 994</li><li><span class='xr-has-index'>x</span>: 423</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-67f325d7-778b-4a68-bd2c-b453697e1766' class='xr-section-summary-in' type='checkbox'  checked><label for='section-67f325d7-778b-4a68-bd2c-b453697e1766' class='xr-section-summary' >Coordinates: <span>(2)</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'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>4.963e+06 4.963e+06 ... 5.062e+06</div><input id='attrs-430a1b7e-134a-40e7-a37a-46ffaaf42b80' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-430a1b7e-134a-40e7-a37a-46ffaaf42b80' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d305f91-0d18-4e07-8510-2466b8fdfa42' class='xr-var-data-in' type='checkbox'><label for='data-5d305f91-0d18-4e07-8510-2466b8fdfa42' 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>m</dd><dt><span>long_name :</span></dt><dd>y</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([4963125., 4963225., 4963325., ..., 5062225., 5062325., 5062425.],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>2.643e+05 2.644e+05 ... 3.065e+05</div><input id='attrs-e99ae761-1c8c-4d35-b684-259bd77ae717' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e99ae761-1c8c-4d35-b684-259bd77ae717' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c51d7afe-f383-4dd3-8a33-ef931be870b4' class='xr-var-data-in' type='checkbox'><label for='data-c51d7afe-f383-4dd3-8a33-ef931be870b4' 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>m</dd><dt><span>long_name :</span></dt><dd>x</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([264325., 264425., 264525., ..., 306325., 306425., 306525.],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-80fefcdc-2586-48e2-a474-f653761d603b' class='xr-section-summary-in' type='checkbox'  ><label for='section-80fefcdc-2586-48e2-a474-f653761d603b' class='xr-section-summary' >Data variables: <span>(15)</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>thkobs</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ff7ead24-316e-4cc5-9bac-cd193adc273f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ff7ead24-316e-4cc5-9bac-cd193adc273f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e81d29cb-d6c1-4411-9282-61a0fbc21adc' class='xr-var-data-in' type='checkbox'><label for='data-e81d29cb-d6c1-4411-9282-61a0fbc21adc' 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>[420462 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thkinit</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-08aa44fe-4b62-458a-aeef-0f800f119c79' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-08aa44fe-4b62-458a-aeef-0f800f119c79' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af9e2ea2-d60e-4bfa-88ae-f4be4429c401' class='xr-var-data-in' type='checkbox'><label for='data-af9e2ea2-d60e-4bfa-88ae-f4be4429c401' 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>[420462 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-22923582-20f6-4db5-a71b-1599b3fe1327' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-22923582-20f6-4db5-a71b-1599b3fe1327' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07b89d36-bff3-47c7-bd06-5a009aa60778' class='xr-var-data-in' type='checkbox'><label for='data-07b89d36-bff3-47c7-bd06-5a009aa60778' 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>[420462 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d00f23f3-d13f-484e-a519-822102865462' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d00f23f3-d13f-484e-a519-822102865462' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5067ce0a-2a19-4b5f-b8c5-d3620fee4c0d' class='xr-var-data-in' type='checkbox'><label for='data-5067ce0a-2a19-4b5f-b8c5-d3620fee4c0d' 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>[420462 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>usurfobs</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e41f4a0d-c188-4c81-a8f9-b398e33bd7cd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e41f4a0d-c188-4c81-a8f9-b398e33bd7cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d781033e-c5b8-48c2-9b28-7f119e8c1a96' class='xr-var-data-in' type='checkbox'><label for='data-d781033e-c5b8-48c2-9b28-7f119e8c1a96' 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>[420462 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>uvelsurfobs</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4c4447c5-f4b8-4feb-903a-305e31304a7f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4c4447c5-f4b8-4feb-903a-305e31304a7f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ccacebdd-ac18-4108-bfa6-916c9f54aff2' class='xr-var-data-in' type='checkbox'><label for='data-ccacebdd-ac18-4108-bfa6-916c9f54aff2' 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>[420462 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vvelsurfobs</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fce42770-7935-4315-b572-0ea49e293fbb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fce42770-7935-4315-b572-0ea49e293fbb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee9ad2f6-1ffc-4d78-90c7-df4545198429' class='xr-var-data-in' type='checkbox'><label for='data-ee9ad2f6-1ffc-4d78-90c7-df4545198429' 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>[420462 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>icemaskobs</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-36e92c1f-1745-4d70-9781-02d92eac86dc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-36e92c1f-1745-4d70-9781-02d92eac86dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-349db678-6e60-459e-9b25-8c7968a94990' class='xr-var-data-in' type='checkbox'><label for='data-349db678-6e60-459e-9b25-8c7968a94990' 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>[420462 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>strflowctrl</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1a8d949f-47c2-40f3-b90c-e47af261dc78' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a8d949f-47c2-40f3-b90c-e47af261dc78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05690823-2148-4e7d-a161-894b21ca612e' class='xr-var-data-in' type='checkbox'><label for='data-05690823-2148-4e7d-a161-894b21ca612e' 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>[420462 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>arrhenius</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4dbd72a0-bd95-4a04-81c6-da7b3cc9f80c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4dbd72a0-bd95-4a04-81c6-da7b3cc9f80c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e844da04-a7ff-4b0a-9ec3-bbeb3eef76ec' class='xr-var-data-in' type='checkbox'><label for='data-e844da04-a7ff-4b0a-9ec3-bbeb3eef76ec' 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>[420462 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>slidingco</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c7eb6ee6-9dfa-4438-ac19-5e1d1fd6291d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c7eb6ee6-9dfa-4438-ac19-5e1d1fd6291d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14c6775e-84a3-4a3c-a80e-e0f9c2247627' class='xr-var-data-in' type='checkbox'><label for='data-14c6775e-84a3-4a3c-a80e-e0f9c2247627' 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>[420462 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thk</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-1331dd7b-61af-4b03-964e-a508dd1fb8c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1331dd7b-61af-4b03-964e-a508dd1fb8c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9428ea3-2387-43e0-a4dc-7f03f3f2bfb6' class='xr-var-data-in' type='checkbox'><label for='data-b9428ea3-2387-43e0-a4dc-7f03f3f2bfb6' 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>pyproj_srs :</span></dt><dd>EPSG:32632</dd></dl></div><div class='xr-var-data'><pre>array([[0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>usurf</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-da9fca11-dc1f-47eb-b610-3e2cb5dfd793' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-da9fca11-dc1f-47eb-b610-3e2cb5dfd793' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3cb017c-7342-4724-aed2-0becd069a52a' class='xr-var-data-in' type='checkbox'><label for='data-f3cb017c-7342-4724-aed2-0becd069a52a' 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>[420462 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>icemask</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8edfb862-1cb0-481d-82ad-ffb3dca9b345' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8edfb862-1cb0-481d-82ad-ffb3dca9b345' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59164971-af77-466a-bd52-4bd9c104b9bb' class='xr-var-data-in' type='checkbox'><label for='data-59164971-af77-466a-bd52-4bd9c104b9bb' 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>[420462 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>divflux</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4d2ac9d9-d913-457a-afce-be195c5b7064' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4d2ac9d9-d913-457a-afce-be195c5b7064' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d411392-a50b-49a7-beb6-c6f2c8e1eb36' class='xr-var-data-in' type='checkbox'><label for='data-8d411392-a50b-49a7-beb6-c6f2c8e1eb36' 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>[420462 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7f8aae42-c6a9-496a-9b7b-b1abb66470bb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7f8aae42-c6a9-496a-9b7b-b1abb66470bb' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>pyproj_srs :</span></dt><dd>EPSG:32632</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:      (y: 994, x: 423)\n",
       "Coordinates:\n",
       "  * y            (y) float32 4.963e+06 4.963e+06 ... 5.062e+06 5.062e+06\n",
       "  * x            (x) float32 2.643e+05 2.644e+05 ... 3.064e+05 3.065e+05\n",
       "Data variables: (12/15)\n",
       "    thkobs       (y, x) float32 ...\n",
       "    thkinit      (y, x) float32 ...\n",
       "    lon          (y, x) float32 ...\n",
       "    lat          (y, x) float32 ...\n",
       "    usurfobs     (y, x) float32 ...\n",
       "    uvelsurfobs  (y, x) float32 ...\n",
       "    ...           ...\n",
       "    arrhenius    (y, x) float32 ...\n",
       "    slidingco    (y, x) float32 ...\n",
       "    thk          (y, x) float32 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
       "    usurf        (y, x) float32 ...\n",
       "    icemask      (y, x) float32 ...\n",
       "    divflux      (y, x) float32 ...\n",
       "Attributes:\n",
       "    pyproj_srs:  EPSG:32632"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5377503c-8f4d-43d0-8681-a5e7fb8804af",
   "metadata": {},
   "outputs": [],
   "source": [
    "vars=['thk', 'usurf', 'divflux']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9b25f1af-3957-4da5-8fc4-7a37db184870",
   "metadata": {},
   "outputs": [
    {
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       "  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",
       "  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;\n",
       "Dimensions:  (y: 994, x: 423)\n",
       "Coordinates:\n",
       "  * y        (y) float32 4.963e+06 4.963e+06 4.963e+06 ... 5.062e+06 5.062e+06\n",
       "  * x        (x) float32 2.643e+05 2.644e+05 2.645e+05 ... 3.064e+05 3.065e+05\n",
       "Data variables:\n",
       "    thk      (y, x) float32 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0\n",
       "    usurf    (y, x) float32 ...\n",
       "    divflux  (y, x) float32 ...\n",
       "Attributes:\n",
       "    pyproj_srs:  EPSG:32632</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-4c43e2cb-38ac-4c2f-a3d0-0239b7b38c9c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4c43e2cb-38ac-4c2f-a3d0-0239b7b38c9c' 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'>y</span>: 994</li><li><span class='xr-has-index'>x</span>: 423</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d9ed1726-77b4-4053-9ce3-45d967ad1eca' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d9ed1726-77b4-4053-9ce3-45d967ad1eca' class='xr-section-summary' >Coordinates: <span>(2)</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'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>4.963e+06 4.963e+06 ... 5.062e+06</div><input id='attrs-a037954c-6557-4ff9-9f54-cf2d1f458d44' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a037954c-6557-4ff9-9f54-cf2d1f458d44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53f4a647-27ef-45c2-bf57-3f7cd7846cb7' class='xr-var-data-in' type='checkbox'><label for='data-53f4a647-27ef-45c2-bf57-3f7cd7846cb7' 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>m</dd><dt><span>long_name :</span></dt><dd>y</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([4963125., 4963225., 4963325., ..., 5062225., 5062325., 5062425.],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>2.643e+05 2.644e+05 ... 3.065e+05</div><input id='attrs-05c8775c-7da5-416b-9890-414dc9fcd228' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-05c8775c-7da5-416b-9890-414dc9fcd228' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b36c915b-183c-4770-b138-64b4905dbdcc' class='xr-var-data-in' type='checkbox'><label for='data-b36c915b-183c-4770-b138-64b4905dbdcc' 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>m</dd><dt><span>long_name :</span></dt><dd>x</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([264325., 264425., 264525., ..., 306325., 306425., 306525.],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-938c127f-53e4-4e03-abbd-cfb56e6c05dd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-938c127f-53e4-4e03-abbd-cfb56e6c05dd' class='xr-section-summary' >Data variables: <span>(3)</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>thk</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-459317fc-3b3f-4a1d-98e0-e74684eeec0f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-459317fc-3b3f-4a1d-98e0-e74684eeec0f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a4b9357-1a3a-47da-bc9e-31856ae019ee' class='xr-var-data-in' type='checkbox'><label for='data-7a4b9357-1a3a-47da-bc9e-31856ae019ee' 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>pyproj_srs :</span></dt><dd>EPSG:32632</dd></dl></div><div class='xr-var-data'><pre>array([[0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>usurf</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-45877a40-ebde-43c7-bc46-d53372271bb0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-45877a40-ebde-43c7-bc46-d53372271bb0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67d83cd7-28c8-4767-b923-fd2c2a350ad6' class='xr-var-data-in' type='checkbox'><label for='data-67d83cd7-28c8-4767-b923-fd2c2a350ad6' 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>[420462 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>divflux</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-77cecad4-3b5d-4085-9599-f23959fe9397' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-77cecad4-3b5d-4085-9599-f23959fe9397' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e5d1061a-8678-4ca9-bb08-f3f709a74170' class='xr-var-data-in' type='checkbox'><label for='data-e5d1061a-8678-4ca9-bb08-f3f709a74170' 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>[420462 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8de90878-853b-4d7f-9ffa-c8c9a80d0395' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8de90878-853b-4d7f-9ffa-c8c9a80d0395' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>pyproj_srs :</span></dt><dd>EPSG:32632</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (y: 994, x: 423)\n",
       "Coordinates:\n",
       "  * y        (y) float32 4.963e+06 4.963e+06 4.963e+06 ... 5.062e+06 5.062e+06\n",
       "  * x        (x) float32 2.643e+05 2.644e+05 2.645e+05 ... 3.064e+05 3.065e+05\n",
       "Data variables:\n",
       "    thk      (y, x) float32 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0\n",
       "    usurf    (y, x) float32 ...\n",
       "    divflux  (y, x) float32 ...\n",
       "Attributes:\n",
       "    pyproj_srs:  EPSG:32632"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds[vars]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e95fd3c5-b6a0-4806-9aa6-33b2627617d6",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/users/fmaussion/.miniconda3/envs/oggm_env/lib/python3.10/site-packages/salem/graphics.py:745: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead.\n",
      "  geomtype = shape.iloc[0].geometry.type\n",
      "/home/users/fmaussion/.miniconda3/envs/oggm_env/lib/python3.10/site-packages/salem/graphics.py:749: ShapelyDeprecationWarning: The 'type' attribute is deprecated, and will be removed in the future. You can use the 'geom_type' attribute instead.\n",
      "  if 'Multi' in g.type:\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "ds['divflux'].attrs['pyproj_srs'] = 'EPSG:32632'\n",
    "ds['divflux'].salem.quick_map(interp='linear');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ec12383a-5c84-4d74-829d-e3c8558ae0a8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}