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| "# Creating ancillaries with ANTS\n", | |
| "\n", | |
| "Convert a sample netCDF dataset to ancil format to be used by the UM\n", | |
| "\n", | |
| "Some features here need to use conda environment analysis3-21.07 or later" | |
| ] | |
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| "import xarray\n", | |
| "import ants\n", | |
| "import xesmf\n", | |
| "import cftime\n", | |
| "import numpy\n", | |
| "import matplotlib.pyplot as plt" | |
| ] | |
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| "## Source CABLE data\n", | |
| "\n", | |
| "Our source dataset is some CABLE inputs at 0.5 degree resolution, that we'd like to use in ACCESS-CM2 at N96e resolution" | |
| ] | |
| }, | |
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| "</style><pre class='xr-text-repr-fallback'><xarray.Dataset>\n", | |
| "Dimensions: (longitude: 720, latitude: 360, time: 12, soil: 6, rad: 3, patch: 1, pools_plant: 3, pools_litter: 3, pools_soil: 3)\n", | |
| "Coordinates:\n", | |
| " * longitude (longitude) float32 -179.8 -179.2 -178.8 ... 179.2 179.8\n", | |
| " * latitude (latitude) float32 89.75 89.25 88.75 ... -88.75 -89.25 -89.75\n", | |
| "Dimensions without coordinates: time, soil, rad, patch, pools_plant, pools_litter, pools_soil\n", | |
| "Data variables: (12/42)\n", | |
| " area (latitude, longitude) float32 ...\n", | |
| " iveg (latitude, longitude) float64 ...\n", | |
| " patchfrac (latitude, longitude) float32 ...\n", | |
| " isoil (latitude, longitude) float64 ...\n", | |
| " SoilMoist (time, soil, latitude, longitude) float32 ...\n", | |
| " SoilTemp (time, soil, latitude, longitude) float32 ...\n", | |
| " ... ...\n", | |
| " Pplant (pools_plant, patch, latitude, longitude) float32 ...\n", | |
| " Plitter (pools_litter, patch, latitude, longitude) float32 ...\n", | |
| " Psoil (pools_soil, patch, latitude, longitude) float32 ...\n", | |
| " Psoillab (patch, latitude, longitude) float32 ...\n", | |
| " Psoilsorb (patch, latitude, longitude) float32 ...\n", | |
| " Psoilocc (patch, latitude, longitude) float32 ...\n", | |
| "Attributes:\n", | |
| " title: CABLE gridinfo file reconciled with CRU forcing\n", | |
| " introduction: reconciled to CRU forcing landmask; based on interpolated ...\n", | |
| " production: Lei.Cheng@csiro.au & Chris.Lu@csiro.au\n", | |
| " history: Created: Sun Jan 5 18:11:21 EST 2014</pre><div class='xr-wrap' hidden><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-25d79219-ecee-4a2c-b9bd-00620fe9e621' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-25d79219-ecee-4a2c-b9bd-00620fe9e621' 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'>longitude</span>: 720</li><li><span class='xr-has-index'>latitude</span>: 360</li><li><span>time</span>: 12</li><li><span>soil</span>: 6</li><li><span>rad</span>: 3</li><li><span>patch</span>: 1</li><li><span>pools_plant</span>: 3</li><li><span>pools_litter</span>: 3</li><li><span>pools_soil</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-851e4e5a-4525-4abc-a7db-0c2bdc53b537' class='xr-section-summary-in' type='checkbox' checked><label for='section-851e4e5a-4525-4abc-a7db-0c2bdc53b537' 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'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-179.8 -179.2 ... 179.2 179.8</div><input id='attrs-ac73ae14-d71d-4d01-aa16-f5bcf51bcc83' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac73ae14-d71d-4d01-aa16-f5bcf51bcc83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e5a08d6-3032-4ef8-9aba-1b46098607d1' class='xr-var-data-in' type='checkbox'><label for='data-0e5a08d6-3032-4ef8-9aba-1b46098607d1' 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 -180 ~ +180</dd><dt><span>max :</span></dt><dd>179.75</dd><dt><span>min :</span></dt><dd>-179.75</dd><dt><span>interval :</span></dt><dd>0.5</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-179.75, -179.25, -178.75, ..., 178.75, 179.25, 179.75],\n", | |
| " dtype=float32)</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'>float32</div><div class='xr-var-preview xr-preview'>89.75 89.25 88.75 ... -89.25 -89.75</div><input id='attrs-c2336519-c0b2-4d02-829c-922684838d89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c2336519-c0b2-4d02-829c-922684838d89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c55591a8-adb6-4b27-9b42-cb3c537067ad' class='xr-var-data-in' type='checkbox'><label for='data-c55591a8-adb6-4b27-9b42-cb3c537067ad' 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 -90 ~ +90</dd><dt><span>max :</span></dt><dd>89.75</dd><dt><span>min :</span></dt><dd>-89.75</dd><dt><span>interval :</span></dt><dd>0.5</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 89.75, 89.25, 88.75, ..., -88.75, -89.25, -89.75], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1bce2d00-f58f-478a-b4f9-8011b1702d75' class='xr-section-summary-in' type='checkbox' ><label for='section-1bce2d00-f58f-478a-b4f9-8011b1702d75' class='xr-section-summary' >Data variables: <span>(42)</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>area</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b6193ff0-4dc3-41bc-b3d8-4128871eccf8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b6193ff0-4dc3-41bc-b3d8-4128871eccf8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5981120-986d-4776-8773-4c0d43fd3045' class='xr-var-data-in' type='checkbox'><label for='data-d5981120-986d-4776-8773-4c0d43fd3045' 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>method :</span></dt><dd>as provided by Chris Lu</dd><dt><span>units :</span></dt><dd>m^2</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iveg</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9ba3f0f4-3bce-4c65-aa2a-e78080590f4d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ba3f0f4-3bce-4c65-aa2a-e78080590f4d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07213f80-6c23-4405-a76b-47b56c6a4ba3' class='xr-var-data-in' type='checkbox'><label for='data-07213f80-6c23-4405-a76b-47b56c6a4ba3' 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>method :</span></dt><dd>0.5x0.5 = 1x1 & if missing = nearest within 2deg</dd><dt><span>long_name :</span></dt><dd>CSIRO classification of veg type</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>patchfrac</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2fa897e7-0956-4737-8df1-315076788753' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2fa897e7-0956-4737-8df1-315076788753' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3111465-0ce5-450f-a4a7-89b387d60651' class='xr-var-data-in' type='checkbox'><label for='data-b3111465-0ce5-450f-a4a7-89b387d60651' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>long_name :</span></dt><dd>Patch fraction; 1.0 for 0.5x0.5 grid</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>isoil</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6323ad46-7f69-43bb-8527-aee27b885773' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6323ad46-7f69-43bb-8527-aee27b885773' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b360e46a-2bbc-463f-a37d-bcfe2dfbfc6b' class='xr-var-data-in' type='checkbox'><label for='data-b360e46a-2bbc-463f-a37d-bcfe2dfbfc6b' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>long_name :</span></dt><dd>Zobler soil type</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SoilMoist</span></div><div class='xr-var-dims'>(time, soil, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ebf94157-7aee-447e-af41-7bff318d2f39' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ebf94157-7aee-447e-af41-7bff318d2f39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d618f38-f3e6-433a-a513-26fb6df4a01c' class='xr-var-data-in' type='checkbox'><label for='data-9d618f38-f3e6-433a-a513-26fb6df4a01c' 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^3/m^3</dd><dt><span>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>long_name :</span></dt><dd>Soil moisture profile from previous GSWP runs</dd></dl></div><div class='xr-var-data'><pre>[18662400 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SoilTemp</span></div><div class='xr-var-dims'>(time, soil, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1584216b-3189-4b5e-ad8f-977886a5de6a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1584216b-3189-4b5e-ad8f-977886a5de6a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b18095b9-a408-4ade-a2aa-05ef33285500' class='xr-var-data-in' type='checkbox'><label for='data-b18095b9-a408-4ade-a2aa-05ef33285500' 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>K</dd><dt><span>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>long_name :</span></dt><dd>Soil temperature profile from previous GSWP runs</dd></dl></div><div class='xr-var-data'><pre>[18662400 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SnowDepth</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4d7ef5e9-b38d-471e-bc38-635d5b562e11' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4d7ef5e9-b38d-471e-bc38-635d5b562e11' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e7de14b-68fe-4af5-a4a7-463766a6990b' class='xr-var-data-in' type='checkbox'><label for='data-6e7de14b-68fe-4af5-a4a7-463766a6990b' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>long_name :</span></dt><dd>snow depth (source?)</dd></dl></div><div class='xr-var-data'><pre>[3110400 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Albedo</span></div><div class='xr-var-dims'>(rad, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b31f3103-84f6-4bd1-81c0-7df643b2725a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b31f3103-84f6-4bd1-81c0-7df643b2725a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4748a29-4e27-486f-ac55-14b80711fa3d' class='xr-var-data-in' type='checkbox'><label for='data-d4748a29-4e27-486f-ac55-14b80711fa3d' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>long_name :</span></dt><dd>ISLSCP2 snow-free bareground albedo</dd></dl></div><div class='xr-var-data'><pre>[777600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LAI</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d9698c62-cee3-4822-9ef6-45b08d79fd93' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d9698c62-cee3-4822-9ef6-45b08d79fd93' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c3ecbe2-e9d7-48bf-9b7a-c758cce19730' class='xr-var-data-in' type='checkbox'><label for='data-8c3ecbe2-e9d7-48bf-9b7a-c758cce19730' 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^2/m^2</dd><dt><span>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>long_name :</span></dt><dd>leaf area index</dd></dl></div><div class='xr-var-data'><pre>[3110400 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SoilOrder</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4e992ec8-32eb-4e7f-844c-716d6840716d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e992ec8-32eb-4e7f-844c-716d6840716d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecb52935-5f46-4683-86b2-550053f10390' class='xr-var-data-in' type='checkbox'><label for='data-ecb52935-5f46-4683-86b2-550053f10390' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>long_name :</span></dt><dd>soil order</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ndep</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-858896cb-7206-460a-9f84-9b3c67516e3b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-858896cb-7206-460a-9f84-9b3c67516e3b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98bb90db-0fd7-4d77-9c1e-32f88591ceca' class='xr-var-data-in' type='checkbox'><label for='data-98bb90db-0fd7-4d77-9c1e-32f88591ceca' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>units :</span></dt><dd>g N/m^2/year</dd><dt><span>long_name :</span></dt><dd>annual Nitrogen deposition rate</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Nfix</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5a9d98f4-f473-4a84-b2c9-0a3337ead0c7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a9d98f4-f473-4a84-b2c9-0a3337ead0c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dbedbe83-d25e-498f-8d29-4b84937de38f' class='xr-var-data-in' type='checkbox'><label for='data-dbedbe83-d25e-498f-8d29-4b84937de38f' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>units :</span></dt><dd>g N/m^2/year</dd><dt><span>long_name :</span></dt><dd>annual Nitrogen fixation rate</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Pwea</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-40fd04bf-e842-4420-b850-ceace1fc2e43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-40fd04bf-e842-4420-b850-ceace1fc2e43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-089a2abe-d331-4c1c-b7f0-f8531a04847b' class='xr-var-data-in' type='checkbox'><label for='data-089a2abe-d331-4c1c-b7f0-f8531a04847b' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>units :</span></dt><dd>g P/m^2/year</dd><dt><span>long_name :</span></dt><dd>annual yield of Phosphorus from weathering</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Pdust</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bcb62dd3-9397-4a10-95d2-790527240ec7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bcb62dd3-9397-4a10-95d2-790527240ec7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-74f9028b-6187-44a2-9c53-4c32f40d5206' class='xr-var-data-in' type='checkbox'><label for='data-74f9028b-6187-44a2-9c53-4c32f40d5206' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>units :</span></dt><dd>g P/m^2/year</dd><dt><span>long_name :</span></dt><dd>annual yield of Phosphorus from dust deposition</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>clay</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-51b93346-9019-4277-b112-3cf8eb68cd2d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-51b93346-9019-4277-b112-3cf8eb68cd2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4ebba3a-0ecc-4421-8b2a-1a3b0afa8bcc' class='xr-var-data-in' type='checkbox'><label for='data-e4ebba3a-0ecc-4421-8b2a-1a3b0afa8bcc' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>units :</span></dt><dd>unknow</dd><dt><span>long_name :</span></dt><dd>UM soil texture - clay fraction</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>silt</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4d1d8098-5eed-4a88-945b-4d2dc1cdc3d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4d1d8098-5eed-4a88-945b-4d2dc1cdc3d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-719f6f39-6ff9-4387-a4b1-b2aadc7eda96' class='xr-var-data-in' type='checkbox'><label for='data-719f6f39-6ff9-4387-a4b1-b2aadc7eda96' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>units :</span></dt><dd>unknow</dd><dt><span>long_name :</span></dt><dd>UM soil texture - silt fraction</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sand</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8530b4a0-f4c2-4006-b964-0348dabbae26' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8530b4a0-f4c2-4006-b964-0348dabbae26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b98df289-2174-4424-a153-1abd076e8c91' class='xr-var-data-in' type='checkbox'><label for='data-b98df289-2174-4424-a153-1abd076e8c91' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>units :</span></dt><dd>unknow</dd><dt><span>long_name :</span></dt><dd>UM soil texture - sand fraction</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swilt</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a5e4c7df-8264-45e8-bd63-41b7a4361b31' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a5e4c7df-8264-45e8-bd63-41b7a4361b31' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3318adc-28ea-4103-8db4-8a8bf0f25294' class='xr-var-data-in' type='checkbox'><label for='data-d3318adc-28ea-4103-8db4-8a8bf0f25294' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>units :</span></dt><dd>unknow</dd><dt><span>long_name :</span></dt><dd>VOL SMC AT WILTING</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sfc</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3d0bdff4-89de-40f4-b738-1c720402dec8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d0bdff4-89de-40f4-b738-1c720402dec8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55728435-6881-4ed8-ac0f-ef9cecbdaa55' class='xr-var-data-in' type='checkbox'><label for='data-55728435-6881-4ed8-ac0f-ef9cecbdaa55' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>units :</span></dt><dd>unknow</dd><dt><span>long_name :</span></dt><dd>VOL SMC AT CRIT PT</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ssat</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6854a412-4c07-40f6-b665-69b0c25fd4c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6854a412-4c07-40f6-b665-69b0c25fd4c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6b240d4-49ac-416c-a0a4-5858c7ee9327' class='xr-var-data-in' type='checkbox'><label for='data-a6b240d4-49ac-416c-a0a4-5858c7ee9327' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>units :</span></dt><dd>unknow</dd><dt><span>long_name :</span></dt><dd>VOL SMC AT SATURATOIN</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>bch</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-25ab0fc4-29f1-466b-9d34-c362ec17eca0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25ab0fc4-29f1-466b-9d34-c362ec17eca0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c02bcf13-a2fb-43a9-9fb9-adad7a0dd2c6' class='xr-var-data-in' type='checkbox'><label for='data-c02bcf13-a2fb-43a9-9fb9-adad7a0dd2c6' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>units :</span></dt><dd>unknow</dd><dt><span>long_name :</span></dt><dd>CLAPP-HORNBERGER B COEFFICIENT</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hyds</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f09bdeb6-7165-42d9-a0da-bd118896bdd0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f09bdeb6-7165-42d9-a0da-bd118896bdd0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f645ce46-94d0-4c45-8ee0-537b49365b22' class='xr-var-data-in' type='checkbox'><label for='data-f645ce46-94d0-4c45-8ee0-537b49365b22' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>units :</span></dt><dd>m/s</dd><dt><span>long_name :</span></dt><dd>SAT SOIL CONDUCTIVITY</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sucs</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5547ba64-94cd-4c81-bb26-1650a78d7064' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5547ba64-94cd-4c81-bb26-1650a78d7064' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a91437ba-31d2-4ae0-8da0-1a1c13b994b1' class='xr-var-data-in' type='checkbox'><label for='data-a91437ba-31d2-4ae0-8da0-1a1c13b994b1' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>SATURATED SOIL WATER SUCTION</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rhosoil</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-35672d48-7fe3-4b05-bd89-897075549bf9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-35672d48-7fe3-4b05-bd89-897075549bf9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cd5af3e-5429-41a3-9962-8409316d10ec' class='xr-var-data-in' type='checkbox'><label for='data-2cd5af3e-5429-41a3-9962-8409316d10ec' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>units :</span></dt><dd>kg/m^3</dd><dt><span>long_name :</span></dt><dd>SOIL BULK DENSITY</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cnsd</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1828c657-ba52-4b28-90e1-2b0adbda2634' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1828c657-ba52-4b28-90e1-2b0adbda2634' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7d925e4-c183-4df7-bb2c-7325286c6ba7' class='xr-var-data-in' type='checkbox'><label for='data-f7d925e4-c183-4df7-bb2c-7325286c6ba7' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>units :</span></dt><dd>W/m/K</dd><dt><span>long_name :</span></dt><dd>THERMAL CONDUCTIVITY</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>css</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3acbb1f9-4791-4a73-aad8-d39622828102' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3acbb1f9-4791-4a73-aad8-d39622828102' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-190634aa-f8da-4f24-9c67-f2b4860e8ef2' class='xr-var-data-in' type='checkbox'><label for='data-190634aa-f8da-4f24-9c67-f2b4860e8ef2' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>units :</span></dt><dd>J/kg/K</dd><dt><span>long_name :</span></dt><dd>Soi specific heat capacity</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>albedo2</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b757205e-a44d-4613-82ac-4c430fd99b39' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b757205e-a44d-4613-82ac-4c430fd99b39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0ff9ce0-c6d2-4e13-8f22-0c94fd613994' class='xr-var-data-in' type='checkbox'><label for='data-b0ff9ce0-c6d2-4e13-8f22-0c94fd613994' 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>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>units :</span></dt><dd>unknown</dd><dt><span>long_name :</span></dt><dd>UM SNOW-FREE ALBEDO OF SOIL</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>land_fraction</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-70ef82ba-6593-4f56-b33d-6a0b6b86c6d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-70ef82ba-6593-4f56-b33d-6a0b6b86c6d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1c27e71-2878-424b-9947-66ef6dc3a7da' class='xr-var-data-in' type='checkbox'><label for='data-f1c27e71-2878-424b-9947-66ef6dc3a7da' 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> fraction</dd><dt><span>method :</span></dt><dd>crude- value 1 for land and 0 for ocean</dd><dt><span>long_name :</span></dt><dd>land area fraction</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Clabile</span></div><div class='xr-var-dims'>(patch, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-aef6c8fa-6a71-4821-8356-ea1943729558' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aef6c8fa-6a71-4821-8356-ea1943729558' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69fb449f-770e-4092-90e7-c0959c6f402a' class='xr-var-data-in' type='checkbox'><label for='data-69fb449f-770e-4092-90e7-c0959c6f402a' 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>g C/m2</dd><dt><span>method :</span></dt><dd>trendy simulation by Lei Cheng</dd><dt><span>long_name :</span></dt><dd>labile carbon pool</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CASA_Cplant</span></div><div class='xr-var-dims'>(pools_plant, patch, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bbe463f8-5c8a-4aa8-aa22-4fefd7f36783' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bbe463f8-5c8a-4aa8-aa22-4fefd7f36783' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3caf9f47-7355-4eab-8e22-35bf1ccf0ead' class='xr-var-data-in' type='checkbox'><label for='data-3caf9f47-7355-4eab-8e22-35bf1ccf0ead' 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>g C/m2</dd><dt><span>method :</span></dt><dd>trendy simulation by Lei Cheng</dd><dt><span>long_name :</span></dt><dd>plant carbon pool</dd></dl></div><div class='xr-var-data'><pre>[777600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Clitter</span></div><div class='xr-var-dims'>(pools_litter, patch, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b05b1f14-4e85-47a2-baf1-d626da220978' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b05b1f14-4e85-47a2-baf1-d626da220978' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ec17105-3933-46ed-9548-d1c32c81cfa5' class='xr-var-data-in' type='checkbox'><label for='data-2ec17105-3933-46ed-9548-d1c32c81cfa5' 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>g C/m2</dd><dt><span>method :</span></dt><dd>trendy simulation by Lei Cheng</dd><dt><span>long_name :</span></dt><dd>litter carbon pool</dd></dl></div><div class='xr-var-data'><pre>[777600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CASA_Csoil</span></div><div class='xr-var-dims'>(pools_soil, patch, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-06ae2a83-a914-44da-a8dc-be2c46812525' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06ae2a83-a914-44da-a8dc-be2c46812525' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3817b831-e111-410d-9b66-31541af30800' class='xr-var-data-in' type='checkbox'><label for='data-3817b831-e111-410d-9b66-31541af30800' 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>g C/m2</dd><dt><span>method :</span></dt><dd>trendy simulation by Lei Cheng</dd><dt><span>long_name :</span></dt><dd>soil carbon pool</dd></dl></div><div class='xr-var-data'><pre>[777600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Nplant</span></div><div class='xr-var-dims'>(pools_plant, patch, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-928317d9-bfdc-4883-871c-0d95e1cc5bba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-928317d9-bfdc-4883-871c-0d95e1cc5bba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b068ec0d-5d31-43dd-820e-4232876542dc' class='xr-var-data-in' type='checkbox'><label for='data-b068ec0d-5d31-43dd-820e-4232876542dc' 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>g N/m2</dd><dt><span>method :</span></dt><dd>trendy simulation by Lei Cheng</dd><dt><span>long_name :</span></dt><dd>plant nitrogen pool</dd></dl></div><div class='xr-var-data'><pre>[777600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Nlitter</span></div><div class='xr-var-dims'>(pools_litter, patch, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b0e10018-3d5c-4b4c-b20a-dd26958c3f72' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0e10018-3d5c-4b4c-b20a-dd26958c3f72' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-815c3632-5f2c-4fbf-b741-befec13fcb84' class='xr-var-data-in' type='checkbox'><label for='data-815c3632-5f2c-4fbf-b741-befec13fcb84' 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>g N/m2</dd><dt><span>method :</span></dt><dd>trendy simulation by Lei Cheng</dd><dt><span>long_name :</span></dt><dd>litter nitrogen pool</dd></dl></div><div class='xr-var-data'><pre>[777600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Nsoil</span></div><div class='xr-var-dims'>(pools_soil, patch, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1f3c239f-726f-4c2a-a79a-16b92e7e7ff3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f3c239f-726f-4c2a-a79a-16b92e7e7ff3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a57c626-00a7-4899-be30-faf3b7cc81f2' class='xr-var-data-in' type='checkbox'><label for='data-1a57c626-00a7-4899-be30-faf3b7cc81f2' 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>g N/m2</dd><dt><span>method :</span></dt><dd>trendy simulation by Lei Cheng</dd><dt><span>long_name :</span></dt><dd>soil nitrogen pool</dd></dl></div><div class='xr-var-data'><pre>[777600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Nsoilmin</span></div><div class='xr-var-dims'>(patch, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-95ced482-0471-4681-a1a1-b25145e43715' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95ced482-0471-4681-a1a1-b25145e43715' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-433f9aa8-2468-4447-b965-454760033452' class='xr-var-data-in' type='checkbox'><label for='data-433f9aa8-2468-4447-b965-454760033452' 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>g N/m2</dd><dt><span>method :</span></dt><dd>trendy simulation by Lei Cheng</dd><dt><span>long_name :</span></dt><dd>soil mineral N pool</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Pplant</span></div><div class='xr-var-dims'>(pools_plant, patch, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2912f208-2461-4f0d-9ef0-d990081d1be2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2912f208-2461-4f0d-9ef0-d990081d1be2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04a6a6cf-17d5-40a8-a9a8-869b3697d657' class='xr-var-data-in' type='checkbox'><label for='data-04a6a6cf-17d5-40a8-a9a8-869b3697d657' 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>g P/m2</dd><dt><span>method :</span></dt><dd>trendy simulation by Lei Cheng</dd><dt><span>long_name :</span></dt><dd>plant phosphorus pool</dd></dl></div><div class='xr-var-data'><pre>[777600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Plitter</span></div><div class='xr-var-dims'>(pools_litter, patch, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-13371bd9-ec2a-49bc-9a98-b07a44b56516' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-13371bd9-ec2a-49bc-9a98-b07a44b56516' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-713e70d4-5885-4cce-9393-ea625e772bc3' class='xr-var-data-in' type='checkbox'><label for='data-713e70d4-5885-4cce-9393-ea625e772bc3' 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>g P/m2</dd><dt><span>method :</span></dt><dd>trendy simulation by Lei Cheng</dd><dt><span>long_name :</span></dt><dd>litter phosphorus pool</dd></dl></div><div class='xr-var-data'><pre>[777600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Psoil</span></div><div class='xr-var-dims'>(pools_soil, patch, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a2d7e9e2-7551-4c51-bd56-63289e25303b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2d7e9e2-7551-4c51-bd56-63289e25303b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e3a0a74-e348-4048-87dd-c6094664fee9' class='xr-var-data-in' type='checkbox'><label for='data-5e3a0a74-e348-4048-87dd-c6094664fee9' 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>g P/m2</dd><dt><span>method :</span></dt><dd>trendy simulation by Lei Cheng</dd><dt><span>long_name :</span></dt><dd>soil phosphorus pool</dd></dl></div><div class='xr-var-data'><pre>[777600 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Psoillab</span></div><div class='xr-var-dims'>(patch, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3cf3f126-1ff9-4480-bf34-dfe1dade863b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3cf3f126-1ff9-4480-bf34-dfe1dade863b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6824c5a-8aa8-4b72-bc26-672b6f50ae58' class='xr-var-data-in' type='checkbox'><label for='data-b6824c5a-8aa8-4b72-bc26-672b6f50ae58' 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>g P/m2</dd><dt><span>method :</span></dt><dd>trendy simulation by Lei Cheng</dd><dt><span>long_name :</span></dt><dd>soil labile P pool</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Psoilsorb</span></div><div class='xr-var-dims'>(patch, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d7a0f92c-067d-473c-9431-f9b73893be04' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7a0f92c-067d-473c-9431-f9b73893be04' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b20db8ba-2ebe-45f8-ae47-d648cbe5b2cd' class='xr-var-data-in' type='checkbox'><label for='data-b20db8ba-2ebe-45f8-ae47-d648cbe5b2cd' 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>g P/m2</dd><dt><span>method :</span></dt><dd>trendy simulation by Lei Cheng</dd><dt><span>long_name :</span></dt><dd>soil sorbed P pool</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Psoilocc</span></div><div class='xr-var-dims'>(patch, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-343ed837-e0e4-4e26-b4b9-20c6d64c478b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-343ed837-e0e4-4e26-b4b9-20c6d64c478b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15fe203c-4a0d-4ae8-a6eb-48384a38e12e' class='xr-var-data-in' type='checkbox'><label for='data-15fe203c-4a0d-4ae8-a6eb-48384a38e12e' 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>g P/m2</dd><dt><span>method :</span></dt><dd>trendy simulation by Lei Cheng</dd><dt><span>long_name :</span></dt><dd>soil occluded P pool</dd></dl></div><div class='xr-var-data'><pre>[259200 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a47802d8-0a5b-44be-8d62-61ad7e131bb3' class='xr-section-summary-in' type='checkbox' checked><label for='section-a47802d8-0a5b-44be-8d62-61ad7e131bb3' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>CABLE gridinfo file reconciled with CRU forcing</dd><dt><span>introduction :</span></dt><dd>reconciled to CRU forcing landmask; based on interpolated gridinfo 0.5x0.5 interpolated from CABLE 1x1 gridinfo</dd><dt><span>production :</span></dt><dd>Lei.Cheng@csiro.au & Chris.Lu@csiro.au</dd><dt><span>history :</span></dt><dd>Created: Sun Jan 5 18:11:21 EST 2014</dd></dl></div></li></ul></div></div>" | |
| ], | |
| "text/plain": [ | |
| "<xarray.Dataset>\n", | |
| "Dimensions: (longitude: 720, latitude: 360, time: 12, soil: 6, rad: 3, patch: 1, pools_plant: 3, pools_litter: 3, pools_soil: 3)\n", | |
| "Coordinates:\n", | |
| " * longitude (longitude) float32 -179.8 -179.2 -178.8 ... 179.2 179.8\n", | |
| " * latitude (latitude) float32 89.75 89.25 88.75 ... -88.75 -89.25 -89.75\n", | |
| "Dimensions without coordinates: time, soil, rad, patch, pools_plant, pools_litter, pools_soil\n", | |
| "Data variables: (12/42)\n", | |
| " area (latitude, longitude) float32 ...\n", | |
| " iveg (latitude, longitude) float64 ...\n", | |
| " patchfrac (latitude, longitude) float32 ...\n", | |
| " isoil (latitude, longitude) float64 ...\n", | |
| " SoilMoist (time, soil, latitude, longitude) float32 ...\n", | |
| " SoilTemp (time, soil, latitude, longitude) float32 ...\n", | |
| " ... ...\n", | |
| " Pplant (pools_plant, patch, latitude, longitude) float32 ...\n", | |
| " Plitter (pools_litter, patch, latitude, longitude) float32 ...\n", | |
| " Psoil (pools_soil, patch, latitude, longitude) float32 ...\n", | |
| " Psoillab (patch, latitude, longitude) float32 ...\n", | |
| " Psoilsorb (patch, latitude, longitude) float32 ...\n", | |
| " Psoilocc (patch, latitude, longitude) float32 ...\n", | |
| "Attributes:\n", | |
| " title: CABLE gridinfo file reconciled with CRU forcing\n", | |
| " introduction: reconciled to CRU forcing landmask; based on interpolated ...\n", | |
| " production: Lei.Cheng@csiro.au & Chris.Lu@csiro.au\n", | |
| " history: Created: Sun Jan 5 18:11:21 EST 2014" | |
| ] | |
| }, | |
| "execution_count": 2, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "gridinfo = xarray.open_dataset('/g/data/p66/yxw599/cable_input/surface_data/gridinfo/gridinfo_0.5x0.5_new.nc')\n", | |
| "gridinfo" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "dc7b73d5-6555-4878-9598-9cd44806032d", | |
| "metadata": {}, | |
| "source": [ | |
| "To create an ancil file you'll first need to know what variables you're using and what their corresponding STASH codes are.\n", | |
| "\n", | |
| "I'll be looking at LAI (STASH 00217) - you can look up stash codes in the STASHmaster_A file - `~access/umdir/vn10.6/ctldata/STASHmaster/STASHmaster_A`, or open an existing file with Iris and look at the fields's metadata (which will look like `m01s00i217`)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 3, | |
| "id": "c4fcd6f6-cc01-457c-ae50-d16978bb898f", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "<matplotlib.collections.QuadMesh at 0x7fc1429c2b50>" | |
| ] | |
| }, | |
| "execution_count": 3, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 2 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| }, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "lai_source = gridinfo.LAI\n", | |
| "lai_source[0,...].plot()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "71ddffb3-7af3-4cbc-8ca7-db00af2c8036", | |
| "metadata": {}, | |
| "source": [ | |
| "## Sample CABLE ancil file\n", | |
| "\n", | |
| "This will define the output resolution and give us something to compare against when we set up attributes for writing out the ancil" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 4, | |
| "id": "a2314e9a-f329-46fa-bb41-33d9ec8adee6", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stderr", | |
| "output_type": "stream", | |
| "text": [ | |
| "/g/data/hh5/public/apps/miniconda3/envs/analysis3-21.07/lib/python3.9/site-packages/mule/stashmaster.py:284: UserWarning: Ancillary files do not define the UM version number in the Fixed Length Header. No STASHmaster file loaded: Fields will not have STASH entries attached.\n", | |
| " warnings.warn(msg)\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "target_ancil = ants.load('/g/data/access/projects/access/data/ancil/access_cm2_n96e/O1/cable_vegfunc_ncarlai.anc')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "9d0aa682-59de-4e67-9772-302ba42ef99c", | |
| "metadata": {}, | |
| "source": [ | |
| "Here's what the LAI looks like for ACCESS-CM2. Note that this version has an LAI for each of the land surface tiles, while the input is a single value. Note the 'STASH' attribute has the field's STASH code" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 5, | |
| "id": "406576e0-b3b6-4324-9abd-82117e5ed3d5", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/html": [ | |
| "\n", | |
| "<style>\n", | |
| " a.iris {\n", | |
| " text-decoration: none !important;\n", | |
| " }\n", | |
| " table.iris {\n", | |
| " white-space: pre;\n", | |
| " border: 1px solid;\n", | |
| " border-color: #9c9c9c;\n", | |
| " font-family: monaco, monospace;\n", | |
| " }\n", | |
| " th.iris {\n", | |
| " background: #303f3f;\n", | |
| " color: #e0e0e0;\n", | |
| " border-left: 1px solid;\n", | |
| " border-color: #9c9c9c;\n", | |
| " font-size: 1.05em;\n", | |
| " min-width: 50px;\n", | |
| " max-width: 125px;\n", | |
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| " tr.iris :first-child {\n", | |
| " border-right: 1px solid #9c9c9c !important;\n", | |
| " }\n", | |
| " td.iris-title {\n", | |
| " background: #d5dcdf;\n", | |
| " border-top: 1px solid #9c9c9c;\n", | |
| " font-weight: bold;\n", | |
| " }\n", | |
| " .iris-word-cell {\n", | |
| " text-align: left !important;\n", | |
| " white-space: pre;\n", | |
| " }\n", | |
| " .iris-subheading-cell {\n", | |
| " padding-left: 2em !important;\n", | |
| " }\n", | |
| " .iris-inclusion-cell {\n", | |
| " padding-right: 1em !important;\n", | |
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| " .iris-panel-body {\n", | |
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| " .iris-panel-title {\n", | |
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| " }\n", | |
| " .iris-panel-title {\n", | |
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| " }\n", | |
| "</style>\n", | |
| "<table class=\"iris\" id=\"140468007493792\">\n", | |
| " <tr class=\"iris\">\n", | |
| "<th class=\"iris iris-word-cell\">Leaf Area Index (1)</th>\n", | |
| "<th class=\"iris iris-word-cell\">--</th>\n", | |
| "<th class=\"iris iris-word-cell\">time</th>\n", | |
| "<th class=\"iris iris-word-cell\">latitude</th>\n", | |
| "<th class=\"iris iris-word-cell\">longitude</th>\n", | |
| "</tr>\n", | |
| " <tr class=\"iris\">\n", | |
| "<td class=\"iris-word-cell iris-subheading-cell\">Shape</td>\n", | |
| "<td class=\"iris iris-inclusion-cell\">13</td>\n", | |
| "<td class=\"iris iris-inclusion-cell\">12</td>\n", | |
| "<td class=\"iris iris-inclusion-cell\">144</td>\n", | |
| "<td class=\"iris iris-inclusion-cell\">192</td>\n", | |
| "</tr>\n", | |
| " <tr class=\"iris\">\n", | |
| " <td class=\"iris-title iris-word-cell\">Dimension coordinates</td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-word-cell iris-subheading-cell\">\ttime</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| " <td class=\"iris-inclusion-cell\">x</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-word-cell iris-subheading-cell\">\tlatitude</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| " <td class=\"iris-inclusion-cell\">x</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-word-cell iris-subheading-cell\">\tlongitude</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| " <td class=\"iris-inclusion-cell\">x</td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-title iris-word-cell\">Auxiliary coordinates</td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-word-cell iris-subheading-cell\">\tpseudo_level</td>\n", | |
| " <td class=\"iris-inclusion-cell\">x</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-title iris-word-cell\">Attributes</td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-word-cell iris-subheading-cell\">\tSTASH</td>\n", | |
| " <td class=\"iris-word-cell\" colspan=\"4\">m01s00i217</td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-word-cell iris-subheading-cell\">\tgrid_staggering</td>\n", | |
| " <td class=\"iris-word-cell\" colspan=\"4\">6</td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-word-cell iris-subheading-cell\">\tsource</td>\n", | |
| " <td class=\"iris-word-cell\" colspan=\"4\">Data from Met Office Unified Model</td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-word-cell iris-subheading-cell\">\tum_version</td>\n", | |
| " <td class=\"iris-word-cell\" colspan=\"4\">7.3</td>\n", | |
| "</tr>\n", | |
| "</table>\n", | |
| " " | |
| ], | |
| "text/plain": [ | |
| "<iris 'Cube' of leaf_area_index / (1) (-- : 13; time: 12; latitude: 144; longitude: 192)>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| }, | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "<matplotlib.collections.QuadMesh at 0x7fc141c2cca0>" | |
| ] | |
| }, | |
| "execution_count": 5, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| }, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "target_lai = target_ancil.extract_cube('leaf_area_index')\n", | |
| "\n", | |
| "display(target_lai)\n", | |
| "plt.pcolormesh(target_lai[0,0,:,:].data)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "41058235-d46a-4b5e-b106-c3983b88a9bb", | |
| "metadata": {}, | |
| "source": [ | |
| "# Converting from Xarray to ANTS\n", | |
| "\n", | |
| "We'll need to\n", | |
| " 1. Regrid to target resolution\n", | |
| " 2. Convert from Xarray to ANTS\n", | |
| " 3. Save to an ancil file" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "217eca0d-d541-4543-9717-8cf3698d1789", | |
| "metadata": {}, | |
| "source": [ | |
| "## Regridding\n", | |
| "\n", | |
| "Xesmf can be used to interpolate a Xarray object to a different grid. It needs a sample Xarray object on the target grid, which we can get by converting the target field." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 6, | |
| "id": "1cd8151c-056f-4211-a83c-4455292751c2", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stderr", | |
| "output_type": "stream", | |
| "text": [ | |
| "/g/data/hh5/public/apps/miniconda3/envs/analysis3-21.07/lib/python3.9/site-packages/xarray/core/dataarray.py:789: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n", | |
| " return key in self.data\n", | |
| "/g/data/hh5/public/apps/miniconda3/envs/analysis3-21.07/lib/python3.9/site-packages/dask/array/core.py:383: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n", | |
| " o = func(*args, **kwargs)\n", | |
| "/g/data/hh5/public/apps/miniconda3/envs/analysis3-21.07/lib/python3.9/site-packages/xesmf/frontend.py:522: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n", | |
| " dr_out = xr.apply_ufunc(\n" | |
| ] | |
| }, | |
| { | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 2 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| }, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "regrid_land = xesmf.Regridder(lai_source, xarray.DataArray.from_iris(target_lai), method='bilinear')\n", | |
| "\n", | |
| "regrid_land(lai_source)[0,...].plot(vmin=0);" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "828860ba-c00d-4e46-95e4-aa153ed6a45d", | |
| "metadata": {}, | |
| "source": [ | |
| "The prime area for problems when regridding is the coastlines - note how Indonesia for example is much more sparse in the regridded data compared to the sample ancil file. This is because we need to mask out the ocean when regridding (the NAN values in the ocean are getting included, so turning the coasts into NAN).\n", | |
| "\n", | |
| "We tell xesmf about the mask by creating a Dataset with a variable called 'mask', that is 1 where we want to use the data and 0 where we want to mask out" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 7, | |
| "id": "c9bab25a-c02e-499b-9b78-a8ca8d178849", | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 2 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| }, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "mask = xarray.where(numpy.isfinite(lai_source[0,:,:]), 1, 0)\n", | |
| "mask = mask.to_dataset(name='mask')\n", | |
| "\n", | |
| "mask.mask.plot();" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "31a3136d-7d3c-4549-b76a-0304ca81f7c6", | |
| "metadata": {}, | |
| "source": [ | |
| "With the mask enabled the ocean values are now set to zero." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 8, | |
| "id": "99dd904f-3788-4c63-bfc4-229982c02ea0", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stderr", | |
| "output_type": "stream", | |
| "text": [ | |
| "/g/data/hh5/public/apps/miniconda3/envs/analysis3-21.07/lib/python3.9/site-packages/dask/array/core.py:383: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n", | |
| " o = func(*args, **kwargs)\n", | |
| "/g/data/hh5/public/apps/miniconda3/envs/analysis3-21.07/lib/python3.9/site-packages/xesmf/frontend.py:522: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n", | |
| " dr_out = xr.apply_ufunc(\n" | |
| ] | |
| }, | |
| { | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 2 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| }, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "regrid_land = xesmf.Regridder(mask, xarray.DataArray.from_iris(target_ancil[2]), method='bilinear')\n", | |
| "lai_out = regrid_land(lai_source, keep_attrs = True)\n", | |
| "\n", | |
| "lai_out[0,...].plot(vmin=0);" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "77ad5613-d1bb-4be8-a199-b0533376c551", | |
| "metadata": {}, | |
| "source": [ | |
| "You can additionally enable extrapolation to ensure that the coasts are covered, in case the source data and target masks don't exactly line up" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 9, | |
| "id": "bdbe69ad-3442-4981-affe-da6da83a53cf", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stderr", | |
| "output_type": "stream", | |
| "text": [ | |
| "/g/data/hh5/public/apps/miniconda3/envs/analysis3-21.07/lib/python3.9/site-packages/dask/array/core.py:383: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n", | |
| " o = func(*args, **kwargs)\n", | |
| "/g/data/hh5/public/apps/miniconda3/envs/analysis3-21.07/lib/python3.9/site-packages/xesmf/frontend.py:522: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n", | |
| " dr_out = xr.apply_ufunc(\n" | |
| ] | |
| }, | |
| { | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 2 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| }, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "regrid_land = xesmf.Regridder(mask, xarray.DataArray.from_iris(target_ancil[2]), method='bilinear', extrap_method='inverse_dist')\n", | |
| "lai_out = regrid_land(lai_source, keep_attrs = True)\n", | |
| "\n", | |
| "lai_out[0,...].plot(vmin=0);" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "7c3ce559-a73c-4eec-9b87-352889c0a288", | |
| "metadata": {}, | |
| "source": [ | |
| "## Things to watch for\n", | |
| "\n", | |
| " - Inspect the output values around coastlines\n", | |
| " - Some CABLE variables output by the ACCESS model need additional masking as the data is only valid where the land fraction of that tile is > 0\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "68954510-8ac1-45b5-9914-1bcfeda082c7", | |
| "metadata": {}, | |
| "source": [ | |
| "## Converting formats\n", | |
| "\n", | |
| "We can swap between Iris/Ants and Xarray formats with `xarray.DataArray.from_iris` and `xarray.DataArray.to_iris`. The basic plan is to make the metadata match in Xarray format, then convert to Iris and write out the file.\n", | |
| "\n", | |
| "So far we have the new data regridded to the target grid:" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 10, | |
| "id": "5650f2b1-6993-479b-92e8-360b3cbe4a77", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/html": [ | |
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| "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n", | |
| " *\n", | |
| " */\n", | |
| "\n", | |
| ":root {\n", | |
| " --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n", | |
| " --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n", | |
| " --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n", | |
| " --xr-border-color: var(--jp-border-color2, #e0e0e0);\n", | |
| " --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n", | |
| " --xr-background-color: var(--jp-layout-color0, white);\n", | |
| " --xr-background-color-row-even: var(--jp-layout-color1, white);\n", | |
| " --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n", | |
| "}\n", | |
| "\n", | |
| "html[theme=dark],\n", | |
| "body.vscode-dark {\n", | |
| " --xr-font-color0: rgba(255, 255, 255, 1);\n", | |
| " --xr-font-color2: rgba(255, 255, 255, 0.54);\n", | |
| " --xr-font-color3: rgba(255, 255, 255, 0.38);\n", | |
| " --xr-border-color: #1F1F1F;\n", | |
| " --xr-disabled-color: #515151;\n", | |
| " --xr-background-color: #111111;\n", | |
| " --xr-background-color-row-even: #111111;\n", | |
| " --xr-background-color-row-odd: #313131;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-wrap {\n", | |
| " display: block;\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", | |
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| " 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", | |
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| ".xr-array-name {\n", | |
| " margin-left: 2px;\n", | |
| " margin-right: 10px;\n", | |
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| " color: var(--xr-font-color2);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-sections {\n", | |
| " padding-left: 0 !important;\n", | |
| " display: grid;\n", | |
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| "\n", | |
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| " display: contents;\n", | |
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| " display: none;\n", | |
| "}\n", | |
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| " color: var(--xr-disabled-color);\n", | |
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| " cursor: pointer;\n", | |
| " color: var(--xr-font-color2);\n", | |
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| "\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", | |
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| " display: inline-block;\n", | |
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| "\n", | |
| ".xr-section-summary-in:disabled + label {\n", | |
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| " display: inline-block;\n", | |
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| " 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", | |
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| "}\n", | |
| "\n", | |
| ".xr-section-summary,\n", | |
| ".xr-section-inline-details {\n", | |
| " padding-top: 4px;\n", | |
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| ".xr-attrs dd {\n", | |
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| " margin: 0;\n", | |
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| " width: auto;\n", | |
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| ".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", | |
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| " 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'><xarray.DataArray 'LAI' (time: 12, latitude: 144, longitude: 192)>\n", | |
| "array([[[2.5513756 , 2.55138088, 2.55138526, ..., 2.55135443,\n", | |
| " 2.55136238, 2.55136943],\n", | |
| " [2.55304255, 2.55305315, 2.55306091, ..., 2.55299362,\n", | |
| " 2.5530128 , 2.55302911],\n", | |
| " [2.55476278, 2.55477103, 2.55477439, ..., 2.55470805,\n", | |
| " 2.55473136, 2.55474958],\n", | |
| " ...,\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ],\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ],\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ]],\n", | |
| "\n", | |
| " [[2.66356206, 2.66356757, 2.66357214, ..., 2.66353995,\n", | |
| " 2.66354825, 2.66355562],\n", | |
| " [2.6653041 , 2.66531516, 2.66532325, ..., 2.665253 ,\n", | |
| " 2.66527303, 2.66529006],\n", | |
| " [2.6671018 , 2.66711039, 2.66711388, ..., 2.66704468,\n", | |
| " 2.66706901, 2.66708803],\n", | |
| "...\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ],\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ],\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ]],\n", | |
| "\n", | |
| " [[2.41992673, 2.41993171, 2.41993586, ..., 2.41990671,\n", | |
| " 2.41991422, 2.41992089],\n", | |
| " [2.42150245, 2.42151247, 2.42151981, ..., 2.42145619,\n", | |
| " 2.42147432, 2.42148974],\n", | |
| " [2.42312855, 2.42313634, 2.42313953, ..., 2.42307681,\n", | |
| " 2.42309884, 2.42311607],\n", | |
| " ...,\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ],\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ],\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ]]])\n", | |
| "Coordinates:\n", | |
| " * longitude (longitude) float32 0.9375 2.812 4.688 ... 355.3 357.2 359.1\n", | |
| " * latitude (latitude) float32 -89.38 -88.12 -86.88 ... 86.88 88.12 89.38\n", | |
| "Dimensions without coordinates: time\n", | |
| "Attributes:\n", | |
| " units: m^2/m^2\n", | |
| " method: 0.5x0.5 = 1x1\n", | |
| " long_name: leaf area index\n", | |
| " regrid_method: bilinear</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'LAI'</div><ul class='xr-dim-list'><li><span>time</span>: 12</li><li><span class='xr-has-index'>latitude</span>: 144</li><li><span class='xr-has-index'>longitude</span>: 192</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-efbb36f5-1085-4dd5-aa39-8b600514580d' class='xr-array-in' type='checkbox' checked><label for='section-efbb36f5-1085-4dd5-aa39-8b600514580d' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2.551 2.551 2.551 2.551 2.551 2.551 2.551 ... 0.0 0.0 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([[[2.5513756 , 2.55138088, 2.55138526, ..., 2.55135443,\n", | |
| " 2.55136238, 2.55136943],\n", | |
| " [2.55304255, 2.55305315, 2.55306091, ..., 2.55299362,\n", | |
| " 2.5530128 , 2.55302911],\n", | |
| " [2.55476278, 2.55477103, 2.55477439, ..., 2.55470805,\n", | |
| " 2.55473136, 2.55474958],\n", | |
| " ...,\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ],\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ],\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ]],\n", | |
| "\n", | |
| " [[2.66356206, 2.66356757, 2.66357214, ..., 2.66353995,\n", | |
| " 2.66354825, 2.66355562],\n", | |
| " [2.6653041 , 2.66531516, 2.66532325, ..., 2.665253 ,\n", | |
| " 2.66527303, 2.66529006],\n", | |
| " [2.6671018 , 2.66711039, 2.66711388, ..., 2.66704468,\n", | |
| " 2.66706901, 2.66708803],\n", | |
| "...\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ],\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ],\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ]],\n", | |
| "\n", | |
| " [[2.41992673, 2.41993171, 2.41993586, ..., 2.41990671,\n", | |
| " 2.41991422, 2.41992089],\n", | |
| " [2.42150245, 2.42151247, 2.42151981, ..., 2.42145619,\n", | |
| " 2.42147432, 2.42148974],\n", | |
| " [2.42312855, 2.42313634, 2.42313953, ..., 2.42307681,\n", | |
| " 2.42309884, 2.42311607],\n", | |
| " ...,\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ],\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ],\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ]]])</pre></div></div></li><li class='xr-section-item'><input id='section-d6f2df49-4649-4805-98fa-15c3cc92c0da' class='xr-section-summary-in' type='checkbox' checked><label for='section-d6f2df49-4649-4805-98fa-15c3cc92c0da' 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'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.9375 2.812 4.688 ... 357.2 359.1</div><input id='attrs-69038182-2d3e-4d52-b96f-74ad3387e3d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69038182-2d3e-4d52-b96f-74ad3387e3d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72e8dec5-d0c5-438a-8e5b-c52a1afb846b' class='xr-var-data-in' type='checkbox'><label for='data-72e8dec5-d0c5-438a-8e5b-c52a1afb846b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([ 0.9375, 2.8125, 4.6875, 6.5625, 8.4375, 10.3125,\n", | |
| " 12.1875, 14.0625, 15.9375, 17.8125, 19.6875, 21.5625,\n", | |
| " 23.4375, 25.3125, 27.1875, 29.0625, 30.9375, 32.8125,\n", | |
| " 34.6875, 36.5625, 38.4375, 40.3125, 42.1875, 44.0625,\n", | |
| " 45.9375, 47.8125, 49.6875, 51.5625, 53.4375, 55.3125,\n", | |
| " 57.1875, 59.0625, 60.9375, 62.8125, 64.6875, 66.5625,\n", | |
| " 68.4375, 70.3125, 72.1875, 74.0625, 75.9375, 77.8125,\n", | |
| " 79.6875, 81.5625, 83.4375, 85.3125, 87.1875, 89.0625,\n", | |
| " 90.9375, 92.8125, 94.6875, 96.5625, 98.4375, 100.3125,\n", | |
| " 102.1875, 104.0625, 105.9375, 107.8125, 109.6875, 111.5625,\n", | |
| " 113.4375, 115.3125, 117.1875, 119.0625, 120.9375, 122.8125,\n", | |
| " 124.6875, 126.5625, 128.4375, 130.3125, 132.1875, 134.0625,\n", | |
| " 135.9375, 137.8125, 139.6875, 141.5625, 143.4375, 145.3125,\n", | |
| " 147.1875, 149.0625, 150.9375, 152.8125, 154.6875, 156.5625,\n", | |
| " 158.4375, 160.3125, 162.1875, 164.0625, 165.9375, 167.8125,\n", | |
| " 169.6875, 171.5625, 173.4375, 175.3125, 177.1875, 179.0625,\n", | |
| " 180.9375, 182.8125, 184.6875, 186.5625, 188.4375, 190.3125,\n", | |
| " 192.1875, 194.0625, 195.9375, 197.8125, 199.6875, 201.5625,\n", | |
| " 203.4375, 205.3125, 207.1875, 209.0625, 210.9375, 212.8125,\n", | |
| " 214.6875, 216.5625, 218.4375, 220.3125, 222.1875, 224.0625,\n", | |
| " 225.9375, 227.8125, 229.6875, 231.5625, 233.4375, 235.3125,\n", | |
| " 237.1875, 239.0625, 240.9375, 242.8125, 244.6875, 246.5625,\n", | |
| " 248.4375, 250.3125, 252.1875, 254.0625, 255.9375, 257.8125,\n", | |
| " 259.6875, 261.5625, 263.4375, 265.3125, 267.1875, 269.0625,\n", | |
| " 270.9375, 272.8125, 274.6875, 276.5625, 278.4375, 280.3125,\n", | |
| " 282.1875, 284.0625, 285.9375, 287.8125, 289.6875, 291.5625,\n", | |
| " 293.4375, 295.3125, 297.1875, 299.0625, 300.9375, 302.8125,\n", | |
| " 304.6875, 306.5625, 308.4375, 310.3125, 312.1875, 314.0625,\n", | |
| " 315.9375, 317.8125, 319.6875, 321.5625, 323.4375, 325.3125,\n", | |
| " 327.1875, 329.0625, 330.9375, 332.8125, 334.6875, 336.5625,\n", | |
| " 338.4375, 340.3125, 342.1875, 344.0625, 345.9375, 347.8125,\n", | |
| " 349.6875, 351.5625, 353.4375, 355.3125, 357.1875, 359.0625],\n", | |
| " dtype=float32)</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'>float32</div><div class='xr-var-preview xr-preview'>-89.38 -88.12 ... 88.12 89.38</div><input id='attrs-8a795066-cd85-46e2-8b65-0eea819e2cbf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a795066-cd85-46e2-8b65-0eea819e2cbf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9103878-8b03-4cf2-bb4c-153137cddfe7' class='xr-var-data-in' type='checkbox'><label for='data-d9103878-8b03-4cf2-bb4c-153137cddfe7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([-89.375, -88.125, -86.875, -85.625, -84.375, -83.125, -81.875,\n", | |
| " -80.625, -79.375, -78.125, -76.875, -75.625, -74.375, -73.125,\n", | |
| " -71.875, -70.625, -69.375, -68.125, -66.875, -65.625, -64.375,\n", | |
| " -63.125, -61.875, -60.625, -59.375, -58.125, -56.875, -55.625,\n", | |
| " -54.375, -53.125, -51.875, -50.625, -49.375, -48.125, -46.875,\n", | |
| " -45.625, -44.375, -43.125, -41.875, -40.625, -39.375, -38.125,\n", | |
| " -36.875, -35.625, -34.375, -33.125, -31.875, -30.625, -29.375,\n", | |
| " -28.125, -26.875, -25.625, -24.375, -23.125, -21.875, -20.625,\n", | |
| " -19.375, -18.125, -16.875, -15.625, -14.375, -13.125, -11.875,\n", | |
| " -10.625, -9.375, -8.125, -6.875, -5.625, -4.375, -3.125,\n", | |
| " -1.875, -0.625, 0.625, 1.875, 3.125, 4.375, 5.625,\n", | |
| " 6.875, 8.125, 9.375, 10.625, 11.875, 13.125, 14.375,\n", | |
| " 15.625, 16.875, 18.125, 19.375, 20.625, 21.875, 23.125,\n", | |
| " 24.375, 25.625, 26.875, 28.125, 29.375, 30.625, 31.875,\n", | |
| " 33.125, 34.375, 35.625, 36.875, 38.125, 39.375, 40.625,\n", | |
| " 41.875, 43.125, 44.375, 45.625, 46.875, 48.125, 49.375,\n", | |
| " 50.625, 51.875, 53.125, 54.375, 55.625, 56.875, 58.125,\n", | |
| " 59.375, 60.625, 61.875, 63.125, 64.375, 65.625, 66.875,\n", | |
| " 68.125, 69.375, 70.625, 71.875, 73.125, 74.375, 75.625,\n", | |
| " 76.875, 78.125, 79.375, 80.625, 81.875, 83.125, 84.375,\n", | |
| " 85.625, 86.875, 88.125, 89.375], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b2f2f639-4f42-475e-9316-8828fac5e37d' class='xr-section-summary-in' type='checkbox' checked><label for='section-b2f2f639-4f42-475e-9316-8828fac5e37d' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m^2/m^2</dd><dt><span>method :</span></dt><dd>0.5x0.5 = 1x1</dd><dt><span>long_name :</span></dt><dd>leaf area index</dd><dt><span>regrid_method :</span></dt><dd>bilinear</dd></dl></div></li></ul></div></div>" | |
| ], | |
| "text/plain": [ | |
| "<xarray.DataArray 'LAI' (time: 12, latitude: 144, longitude: 192)>\n", | |
| "array([[[2.5513756 , 2.55138088, 2.55138526, ..., 2.55135443,\n", | |
| " 2.55136238, 2.55136943],\n", | |
| " [2.55304255, 2.55305315, 2.55306091, ..., 2.55299362,\n", | |
| " 2.5530128 , 2.55302911],\n", | |
| " [2.55476278, 2.55477103, 2.55477439, ..., 2.55470805,\n", | |
| " 2.55473136, 2.55474958],\n", | |
| " ...,\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ],\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ],\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ]],\n", | |
| "\n", | |
| " [[2.66356206, 2.66356757, 2.66357214, ..., 2.66353995,\n", | |
| " 2.66354825, 2.66355562],\n", | |
| " [2.6653041 , 2.66531516, 2.66532325, ..., 2.665253 ,\n", | |
| " 2.66527303, 2.66529006],\n", | |
| " [2.6671018 , 2.66711039, 2.66711388, ..., 2.66704468,\n", | |
| " 2.66706901, 2.66708803],\n", | |
| "...\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ],\n", | |
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| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ]],\n", | |
| "\n", | |
| " [[2.41992673, 2.41993171, 2.41993586, ..., 2.41990671,\n", | |
| " 2.41991422, 2.41992089],\n", | |
| " [2.42150245, 2.42151247, 2.42151981, ..., 2.42145619,\n", | |
| " 2.42147432, 2.42148974],\n", | |
| " [2.42312855, 2.42313634, 2.42313953, ..., 2.42307681,\n", | |
| " 2.42309884, 2.42311607],\n", | |
| " ...,\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ],\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ],\n", | |
| " [0. , 0. , 0. , ..., 0. ,\n", | |
| " 0. , 0. ]]])\n", | |
| "Coordinates:\n", | |
| " * longitude (longitude) float32 0.9375 2.812 4.688 ... 355.3 357.2 359.1\n", | |
| " * latitude (latitude) float32 -89.38 -88.12 -86.88 ... 86.88 88.12 89.38\n", | |
| "Dimensions without coordinates: time\n", | |
| "Attributes:\n", | |
| " units: m^2/m^2\n", | |
| " method: 0.5x0.5 = 1x1\n", | |
| " long_name: leaf area index\n", | |
| " regrid_method: bilinear" | |
| ] | |
| }, | |
| "execution_count": 10, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "lai_out" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "924f26f9-027a-4900-bbfb-584b787fd950", | |
| "metadata": {}, | |
| "source": [ | |
| "---\n", | |
| "\n", | |
| "and we want this to match our sample ancil file:" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 11, | |
| "id": "a1d5390b-1784-4601-9ee1-ea04f3797deb", | |
| "metadata": {}, | |
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| " 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'><xarray.DataArray 'leaf_area_index' (dim_0: 13, time: 12, latitude: 144, longitude: 192)>\n", | |
| "dask.array<filled, shape=(13, 12, 144, 192), dtype=float64, chunksize=(1, 1, 144, 192), chunktype=numpy.ndarray>\n", | |
| "Coordinates:\n", | |
| " * time (time) object 0000-01-16 00:00:00 ... 0000-12-16 00:00:00\n", | |
| " * latitude (latitude) float32 -89.38 -88.12 -86.88 ... 86.88 88.12 89.38\n", | |
| " * longitude (longitude) float32 0.9375 2.812 4.688 ... 355.3 357.2 359.1\n", | |
| " pseudo_level (dim_0) int64 ...\n", | |
| "Dimensions without coordinates: dim_0\n", | |
| "Attributes:\n", | |
| " standard_name: leaf_area_index\n", | |
| " source: Data from Met Office Unified Model\n", | |
| " um_version: 7.3\n", | |
| " STASH: m01s00i217\n", | |
| " grid_staggering: 6</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'leaf_area_index'</div><ul class='xr-dim-list'><li><span>dim_0</span>: 13</li><li><span class='xr-has-index'>time</span>: 12</li><li><span class='xr-has-index'>latitude</span>: 144</li><li><span class='xr-has-index'>longitude</span>: 192</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-4ac06a90-550b-4a7a-8df1-2f075fb90300' class='xr-array-in' type='checkbox' checked><label for='section-4ac06a90-550b-4a7a-8df1-2f075fb90300' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array<chunksize=(1, 1, 144, 192), meta=np.ndarray></span></div><div class='xr-array-data'><table>\n", | |
| "<tr>\n", | |
| "<td>\n", | |
| "<table>\n", | |
| " <thead>\n", | |
| " <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr><th> Bytes </th><td> 32.91 MiB </td> <td> 216.00 kiB </td></tr>\n", | |
| " <tr><th> Shape </th><td> (13, 12, 144, 192) </td> <td> (1, 1, 144, 192) </td></tr>\n", | |
| " <tr><th> Count </th><td> 780 Tasks </td><td> 156 Chunks </td></tr>\n", | |
| " <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "</td>\n", | |
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| "</table></div></div></li><li class='xr-section-item'><input id='section-75dbfb8b-d2e8-4285-aff1-a549395ac5f1' class='xr-section-summary-in' type='checkbox' checked><label for='section-75dbfb8b-d2e8-4285-aff1-a549395ac5f1' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0000-01-16 00:00:00 ... 0000-12-...</div><input id='attrs-0e0b99ae-396c-47bc-a2f6-f0fe846b7954' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0e0b99ae-396c-47bc-a2f6-f0fe846b7954' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4c69ed7-7f5e-4703-8e3e-e20e173db636' class='xr-var-data-in' type='checkbox'><label for='data-f4c69ed7-7f5e-4703-8e3e-e20e173db636' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.Datetime360Day(0, 1, 16, 0, 0, 0, 0, has_year_zero=False),\n", | |
| " cftime.Datetime360Day(0, 2, 16, 0, 0, 0, 0, has_year_zero=False),\n", | |
| " cftime.Datetime360Day(0, 3, 16, 0, 0, 0, 0, has_year_zero=False),\n", | |
| " cftime.Datetime360Day(0, 4, 16, 0, 0, 0, 0, has_year_zero=False),\n", | |
| " cftime.Datetime360Day(0, 5, 16, 0, 0, 0, 0, has_year_zero=False),\n", | |
| " cftime.Datetime360Day(0, 6, 16, 0, 0, 0, 0, has_year_zero=False),\n", | |
| " cftime.Datetime360Day(0, 7, 16, 0, 0, 0, 0, has_year_zero=False),\n", | |
| " cftime.Datetime360Day(0, 8, 16, 0, 0, 0, 0, has_year_zero=False),\n", | |
| " cftime.Datetime360Day(0, 9, 16, 0, 0, 0, 0, has_year_zero=False),\n", | |
| " cftime.Datetime360Day(0, 10, 16, 0, 0, 0, 0, has_year_zero=False),\n", | |
| " cftime.Datetime360Day(0, 11, 16, 0, 0, 0, 0, has_year_zero=False),\n", | |
| " cftime.Datetime360Day(0, 12, 16, 0, 0, 0, 0, has_year_zero=False)],\n", | |
| " dtype=object)</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'>float32</div><div class='xr-var-preview xr-preview'>-89.38 -88.12 ... 88.12 89.38</div><input id='attrs-2ee911a1-b583-4d1e-83b3-62aa8841a3d3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2ee911a1-b583-4d1e-83b3-62aa8841a3d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bbf6b554-cdf4-4604-8340-e7329b4723d4' class='xr-var-data-in' type='checkbox'><label for='data-bbf6b554-cdf4-4604-8340-e7329b4723d4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([-89.375, -88.125, -86.875, -85.625, -84.375, -83.125, -81.875, -80.625,\n", | |
| " -79.375, -78.125, -76.875, -75.625, -74.375, -73.125, -71.875, -70.625,\n", | |
| " -69.375, -68.125, -66.875, -65.625, -64.375, -63.125, -61.875, -60.625,\n", | |
| " -59.375, -58.125, -56.875, -55.625, -54.375, -53.125, -51.875, -50.625,\n", | |
| " -49.375, -48.125, -46.875, -45.625, -44.375, -43.125, -41.875, -40.625,\n", | |
| " -39.375, -38.125, -36.875, -35.625, -34.375, -33.125, -31.875, -30.625,\n", | |
| " -29.375, -28.125, -26.875, -25.625, -24.375, -23.125, -21.875, -20.625,\n", | |
| " -19.375, -18.125, -16.875, -15.625, -14.375, -13.125, -11.875, -10.625,\n", | |
| " -9.375, -8.125, -6.875, -5.625, -4.375, -3.125, -1.875, -0.625,\n", | |
| " 0.625, 1.875, 3.125, 4.375, 5.625, 6.875, 8.125, 9.375,\n", | |
| " 10.625, 11.875, 13.125, 14.375, 15.625, 16.875, 18.125, 19.375,\n", | |
| " 20.625, 21.875, 23.125, 24.375, 25.625, 26.875, 28.125, 29.375,\n", | |
| " 30.625, 31.875, 33.125, 34.375, 35.625, 36.875, 38.125, 39.375,\n", | |
| " 40.625, 41.875, 43.125, 44.375, 45.625, 46.875, 48.125, 49.375,\n", | |
| " 50.625, 51.875, 53.125, 54.375, 55.625, 56.875, 58.125, 59.375,\n", | |
| " 60.625, 61.875, 63.125, 64.375, 65.625, 66.875, 68.125, 69.375,\n", | |
| " 70.625, 71.875, 73.125, 74.375, 75.625, 76.875, 78.125, 79.375,\n", | |
| " 80.625, 81.875, 83.125, 84.375, 85.625, 86.875, 88.125, 89.375],\n", | |
| " dtype=float32)</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'>float32</div><div class='xr-var-preview xr-preview'>0.9375 2.812 4.688 ... 357.2 359.1</div><input id='attrs-09f36c8e-2cb2-40e9-aaa0-2c21d06e10cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-09f36c8e-2cb2-40e9-aaa0-2c21d06e10cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50c64181-8c82-4734-b867-57f383f9f118' class='xr-var-data-in' type='checkbox'><label for='data-50c64181-8c82-4734-b867-57f383f9f118' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([ 0.9375, 2.8125, 4.6875, 6.5625, 8.4375, 10.3125, 12.1875,\n", | |
| " 14.0625, 15.9375, 17.8125, 19.6875, 21.5625, 23.4375, 25.3125,\n", | |
| " 27.1875, 29.0625, 30.9375, 32.8125, 34.6875, 36.5625, 38.4375,\n", | |
| " 40.3125, 42.1875, 44.0625, 45.9375, 47.8125, 49.6875, 51.5625,\n", | |
| " 53.4375, 55.3125, 57.1875, 59.0625, 60.9375, 62.8125, 64.6875,\n", | |
| " 66.5625, 68.4375, 70.3125, 72.1875, 74.0625, 75.9375, 77.8125,\n", | |
| " 79.6875, 81.5625, 83.4375, 85.3125, 87.1875, 89.0625, 90.9375,\n", | |
| " 92.8125, 94.6875, 96.5625, 98.4375, 100.3125, 102.1875, 104.0625,\n", | |
| " 105.9375, 107.8125, 109.6875, 111.5625, 113.4375, 115.3125, 117.1875,\n", | |
| " 119.0625, 120.9375, 122.8125, 124.6875, 126.5625, 128.4375, 130.3125,\n", | |
| " 132.1875, 134.0625, 135.9375, 137.8125, 139.6875, 141.5625, 143.4375,\n", | |
| " 145.3125, 147.1875, 149.0625, 150.9375, 152.8125, 154.6875, 156.5625,\n", | |
| " 158.4375, 160.3125, 162.1875, 164.0625, 165.9375, 167.8125, 169.6875,\n", | |
| " 171.5625, 173.4375, 175.3125, 177.1875, 179.0625, 180.9375, 182.8125,\n", | |
| " 184.6875, 186.5625, 188.4375, 190.3125, 192.1875, 194.0625, 195.9375,\n", | |
| " 197.8125, 199.6875, 201.5625, 203.4375, 205.3125, 207.1875, 209.0625,\n", | |
| " 210.9375, 212.8125, 214.6875, 216.5625, 218.4375, 220.3125, 222.1875,\n", | |
| " 224.0625, 225.9375, 227.8125, 229.6875, 231.5625, 233.4375, 235.3125,\n", | |
| " 237.1875, 239.0625, 240.9375, 242.8125, 244.6875, 246.5625, 248.4375,\n", | |
| " 250.3125, 252.1875, 254.0625, 255.9375, 257.8125, 259.6875, 261.5625,\n", | |
| " 263.4375, 265.3125, 267.1875, 269.0625, 270.9375, 272.8125, 274.6875,\n", | |
| " 276.5625, 278.4375, 280.3125, 282.1875, 284.0625, 285.9375, 287.8125,\n", | |
| " 289.6875, 291.5625, 293.4375, 295.3125, 297.1875, 299.0625, 300.9375,\n", | |
| " 302.8125, 304.6875, 306.5625, 308.4375, 310.3125, 312.1875, 314.0625,\n", | |
| " 315.9375, 317.8125, 319.6875, 321.5625, 323.4375, 325.3125, 327.1875,\n", | |
| " 329.0625, 330.9375, 332.8125, 334.6875, 336.5625, 338.4375, 340.3125,\n", | |
| " 342.1875, 344.0625, 345.9375, 347.8125, 349.6875, 351.5625, 353.4375,\n", | |
| " 355.3125, 357.1875, 359.0625], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pseudo_level</span></div><div class='xr-var-dims'>(dim_0)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a0f57111-e2e0-4347-a9e0-2fa8d21010ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0f57111-e2e0-4347-a9e0-2fa8d21010ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed9c25a5-4698-4d04-80bc-955ac0b845f8' class='xr-var-data-in' type='checkbox'><label for='data-ed9c25a5-4698-4d04-80bc-955ac0b845f8' 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>pseudo_level</dd></dl></div><div class='xr-var-data'><pre>array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b92d07f0-02e7-4ace-9812-af2bf124297c' class='xr-section-summary-in' type='checkbox' checked><label for='section-b92d07f0-02e7-4ace-9812-af2bf124297c' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>leaf_area_index</dd><dt><span>source :</span></dt><dd>Data from Met Office Unified Model</dd><dt><span>um_version :</span></dt><dd>7.3</dd><dt><span>STASH :</span></dt><dd>m01s00i217</dd><dt><span>grid_staggering :</span></dt><dd>6</dd></dl></div></li></ul></div></div>" | |
| ], | |
| "text/plain": [ | |
| "<xarray.DataArray 'leaf_area_index' (dim_0: 13, time: 12, latitude: 144, longitude: 192)>\n", | |
| "dask.array<filled, shape=(13, 12, 144, 192), dtype=float64, chunksize=(1, 1, 144, 192), chunktype=numpy.ndarray>\n", | |
| "Coordinates:\n", | |
| " * time (time) object 0000-01-16 00:00:00 ... 0000-12-16 00:00:00\n", | |
| " * latitude (latitude) float32 -89.38 -88.12 -86.88 ... 86.88 88.12 89.38\n", | |
| " * longitude (longitude) float32 0.9375 2.812 4.688 ... 355.3 357.2 359.1\n", | |
| " pseudo_level (dim_0) int64 ...\n", | |
| "Dimensions without coordinates: dim_0\n", | |
| "Attributes:\n", | |
| " standard_name: leaf_area_index\n", | |
| " source: Data from Met Office Unified Model\n", | |
| " um_version: 7.3\n", | |
| " STASH: m01s00i217\n", | |
| " grid_staggering: 6" | |
| ] | |
| }, | |
| "execution_count": 11, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "xarray.DataArray.from_iris(target_lai)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "42c34f95-2912-4853-9a01-7e9cd0091a38", | |
| "metadata": {}, | |
| "source": [ | |
| "---\n", | |
| "\n", | |
| "There are a few things needed to make them match:\n", | |
| "\n", | |
| " - Add global attributes\n", | |
| " - Add time coordinate\n", | |
| " - Add pseudo-level for tile types\n", | |
| " \n", | |
| "For global attributes, the only one we really need is the STASH code, so that ANTS knows what variable it's working with" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 12, | |
| "id": "490da56b-d649-4522-a610-4b25dfe4a788", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "lai_out.attrs['STASH'] = 'm01s00i217'" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "ff66f3c6-8a1f-48dc-88c0-fbc51710b49e", | |
| "metadata": {}, | |
| "source": [ | |
| "The time axis is a 12-month climatology, so the year should be set to zero. The calendar isn't that important, here it's 360 day as year 0 has issues with a Gregorian calendar" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 13, | |
| "id": "b3f54f26-35a5-45a0-aee1-7c8f34b85744", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "time = [cftime.datetime(0,n+1,16,0,0,0, calendar='360_day') for n in range(12)]\n", | |
| "lai_out.coords['time'] = time" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "be39506e-0545-4fa2-a716-1cf266493c3d", | |
| "metadata": {}, | |
| "source": [ | |
| "Setting metadata for the lat and lon axes:" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 14, | |
| "id": "92e804d5-3981-452a-9f86-9f23ec5e0887", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "lai_out['longitude'].attrs['standard_name'] = 'longitude'\n", | |
| "lai_out['latitude'].attrs['standard_name'] = 'latitude'" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "f0fdfc4c-c457-4aaf-a7fc-22e3ae76cdca", | |
| "metadata": {}, | |
| "source": [ | |
| "Add a pseudo-level by matching the shape of the sample LAI variable (this will cause all of the land tiles to have identical LAI values)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 15, | |
| "id": "debd2a42-e0ed-491e-bc82-615059d18d59", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "lai_out = lai_out.broadcast_like(xarray.DataArray.from_iris(target_lai))\n", | |
| "lai_out.coords['pseudo_level'] = xarray.DataArray.from_iris(target_lai).pseudo_level" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "004a1200-a276-4163-84f0-da53b703786e", | |
| "metadata": {}, | |
| "source": [ | |
| "# Generating the Ancil File\n", | |
| "\n", | |
| "The Iris view of the new data now matches what it was for the old ancil file" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 16, | |
| "id": "8266177d-88de-4be7-a3d4-c761366ae71d", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/html": [ | |
| "\n", | |
| "<style>\n", | |
| " a.iris {\n", | |
| " text-decoration: none !important;\n", | |
| " }\n", | |
| " table.iris {\n", | |
| " white-space: pre;\n", | |
| " border: 1px solid;\n", | |
| " border-color: #9c9c9c;\n", | |
| " font-family: monaco, monospace;\n", | |
| " }\n", | |
| " th.iris {\n", | |
| " background: #303f3f;\n", | |
| " color: #e0e0e0;\n", | |
| " border-left: 1px solid;\n", | |
| " border-color: #9c9c9c;\n", | |
| " font-size: 1.05em;\n", | |
| " min-width: 50px;\n", | |
| " max-width: 125px;\n", | |
| " }\n", | |
| " tr.iris :first-child {\n", | |
| " border-right: 1px solid #9c9c9c !important;\n", | |
| " }\n", | |
| " td.iris-title {\n", | |
| " background: #d5dcdf;\n", | |
| " border-top: 1px solid #9c9c9c;\n", | |
| " font-weight: bold;\n", | |
| " }\n", | |
| " .iris-word-cell {\n", | |
| " text-align: left !important;\n", | |
| " white-space: pre;\n", | |
| " }\n", | |
| " .iris-subheading-cell {\n", | |
| " padding-left: 2em !important;\n", | |
| " }\n", | |
| " .iris-inclusion-cell {\n", | |
| " padding-right: 1em !important;\n", | |
| " }\n", | |
| " .iris-panel-body {\n", | |
| " padding-top: 0px;\n", | |
| " }\n", | |
| " .iris-panel-title {\n", | |
| " padding-left: 3em;\n", | |
| " }\n", | |
| " .iris-panel-title {\n", | |
| " margin-top: 7px;\n", | |
| " }\n", | |
| "</style>\n", | |
| "<table class=\"iris\" id=\"140468008731264\">\n", | |
| " <tr class=\"iris\">\n", | |
| "<th class=\"iris iris-word-cell\">Leaf Area Index (m^2/m^2)</th>\n", | |
| "<th class=\"iris iris-word-cell\">--</th>\n", | |
| "<th class=\"iris iris-word-cell\">time</th>\n", | |
| "<th class=\"iris iris-word-cell\">latitude</th>\n", | |
| "<th class=\"iris iris-word-cell\">longitude</th>\n", | |
| "</tr>\n", | |
| " <tr class=\"iris\">\n", | |
| "<td class=\"iris-word-cell iris-subheading-cell\">Shape</td>\n", | |
| "<td class=\"iris iris-inclusion-cell\">13</td>\n", | |
| "<td class=\"iris iris-inclusion-cell\">12</td>\n", | |
| "<td class=\"iris iris-inclusion-cell\">144</td>\n", | |
| "<td class=\"iris iris-inclusion-cell\">192</td>\n", | |
| "</tr>\n", | |
| " <tr class=\"iris\">\n", | |
| " <td class=\"iris-title iris-word-cell\">Dimension coordinates</td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-word-cell iris-subheading-cell\">\ttime</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| " <td class=\"iris-inclusion-cell\">x</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-word-cell iris-subheading-cell\">\tlatitude</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| " <td class=\"iris-inclusion-cell\">x</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-word-cell iris-subheading-cell\">\tlongitude</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| " <td class=\"iris-inclusion-cell\">x</td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-title iris-word-cell\">Auxiliary coordinates</td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-word-cell iris-subheading-cell\">\tpseudo_level</td>\n", | |
| " <td class=\"iris-inclusion-cell\">x</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| " <td class=\"iris-inclusion-cell\">-</td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-title iris-word-cell\">Attributes</td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| " <td class=\"iris-title\"></td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-word-cell iris-subheading-cell\">\tSTASH</td>\n", | |
| " <td class=\"iris-word-cell\" colspan=\"4\">m01s00i217</td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-word-cell iris-subheading-cell\">\tmethod</td>\n", | |
| " <td class=\"iris-word-cell\" colspan=\"4\">0.5x0.5 = 1x1</td>\n", | |
| "</tr>\n", | |
| "<tr class=\"iris\">\n", | |
| " <td class=\"iris-word-cell iris-subheading-cell\">\tregrid_method</td>\n", | |
| " <td class=\"iris-word-cell\" colspan=\"4\">bilinear</td>\n", | |
| "</tr>\n", | |
| "</table>\n", | |
| " " | |
| ], | |
| "text/plain": [ | |
| "<iris 'Cube' of leaf area index / (m^2/m^2) (-- : 13; time: 12; latitude: 144; longitude: 192)>" | |
| ] | |
| }, | |
| "execution_count": 16, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "lai_out.to_iris()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "aee6cec0-1b3b-4849-bc46-2954fed6a7f9", | |
| "metadata": {}, | |
| "source": [ | |
| "We can save the file with `ants.fileformats.save`, which will create both a UM format and NetCDF ancil file." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 17, | |
| "id": "69e468a1-66e0-4646-a3c3-4671457c5324", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "ants.fileformats.save(lai_out.to_iris(), 'lai.ancil')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 19, | |
| "id": "9d1c08cc-d85c-49fd-a27e-5d06931bf8ac", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "<matplotlib.collections.QuadMesh at 0x7fc141572cd0>" | |
| ] | |
| }, | |
| "execution_count": 19, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
| "image/png": 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5Dg+NPeDOOCyjl84y8vN/D3xZVV8hIhlIuR0uI34kBP68gmsxAqhe2EZRi9QO8DlCudHLk7Yh2MHXirdQK9RIy0K1yWQW96vZhDfftlaD3BZCq/YNceJAtNNKpzS9f/Pz3adUuWwlUZ8Web7dIg+4M1jwL1/fhEBPnSQRkW7g6cDPAahqGSifcsMN0KZ02mijjTaWAFPxymnpbwFsBU4AHxSRO0XkX0Wk4/Ho8xNG4AtGsxJHzP/UH+I01sha1bCi/RxJ/iLUaebiyJy/ebe5LuL5xld6vj42utYG56g/1zwHtn6e5fIgmu+cS1k9LHCelu5BzWGL27/mfK3u6nvmLxqLDc5/NnpEzYvoWZwphYQeZyzCLXOViNyW+ntjqhkPuAL4J1W9HJjG5A9bdjyxKJ2IQliIjkgjLcybodn29IvcIJdJUy482hYuLThq0bmB0tdRP+HVb0v3rdlx9W2kt6e/LyT06+/FYlGXa2hB6us0FEGJEd2HefjxVqmehSaHpdJE4sjy24g8/8yK0LX33vE94wd4ilAVKtqyl85JVb1ynm0HgYOq+kP7/TM8TgL/CaPht9FGG22cThijrdPSX9N2VI8CB0TkXPvT9cADj0efn1gafhrLmRVzMUvumn0X4aO72GV9vdbcMGNi0NzbqNk509vq96v3Pa9UkVTa4YX2XxD1+y9G81wuQ3Ej76pTRf3qp67tOV5btJj+Y55rTj/7mmAqTo/B+HQbbmtos2b37Awz2lq8GfgP66HzGPDzy9VwGk8cge+6OD3dAITjE60fZ18CyWRqfpbODnDtwyyVCScml6Wby4Y5QjQZ4CLzvMxnOlc8H73WKp1k0ShnfI2babJjtNPCfWvRDXXB9ppcSyPBLr4YATUfbVh3vjh1dpMAwHphH92XRhNCI6onEuQLuS6LIzWBhsuNlgV8/XHnbYO7T/38kdF2OaCqdwHzUT7LhieOwG+jjTbaOM0I2qkVVgbF9Rke/L9byRzzyI7A4N3GKpM5MYUcGwZAiyXC2WKsBUkmg3R1mgYyvqloEEFSD9L3cfp60ZSWr2GiPTn5PFoqJb9H7Yjg9HS3tuJIHbMkaJ2htBHq256vHmcr+0X7qNbSOSJz94+W0MuRmTSiRRpp3I5AmPjlL6rNOWje17h6VCFf83swMma08oUg0roFrf6+NVvxRPfD3oua/qZiPtIUT7z6mTfNckpN17D1DLPi1B7bbNe6fD5z2wEnl639fYm1eXf9TC/81qIPmwNFqOjZJULPrt42QyhI0aHaHRLsKPLY+YaiyR4doHdXPwC54Sq5b94bCyjp740Pn7loLVJVMqNFAKpdGbxxE/tQ6TMDLZrMcwcmcI6bSYS+HiP0HOshUqlCWDtonVX9DbusI2O131OTSNRe9Hv6ezOk26hHozai/RttE0uR1SMcHUvtFNEBtf2tgWfut5YrSKbOXa/JpBO1WdOeRh5Dbs2+MVwhlqRBOI9to4G3S4sTrTiOEfKWAgyPn5jLh0dCy/NqjlsMmj3HGjRrthnt56T6FgnltPCU2skiFsSPV+rkdD4fDVOJztxahQKSZ+UK4Yx5X5187cTbCM6GdQAEheWMtD27/F6eOAK/jTbaaOM0QpE2pbNicBTNhWhVyOwqEPSZWTw8b5pjm4xWef67jqEZn+ql2wBwJ8s4M4aKGdvi4Vag1xZeDjIOYb/R7KsFlyArVPPm4U6vHUB0wLRRUrxiouF50wFusWo+D8+gGQ+xWqyMWUpoetZ87yig0zMLXtpitMPFapKL3R+ooamaHV+/TXLZuZprWrN2kt/EcWpWH/FxTeim+vOpKrFWG1Zrt9XkCqpts+FqJ7UaTMMZXBV/Do6diNsGoFxJURUhOIJWTD8k48/tbwurs/RqT8OwdQqw0UrK9rOhQTs67DR52tQbghPadf4ALi2nqnjVG7Yb4IHfNSttb2z5tPLlMtqeLjyBBD5I3rxM1ZLD0A/MAD5xRYHCsOUqR8YYfvlFRJ5UpZ4CvY+ZgRb6UO2AExcbId+9P2BqnX1ZPXBLEFhHHqea0DtOVRAF1wp96XYQNYNQNuZqtvlTHWRGZmuGiES8pKqJx4tewrHx2uub78VWNfaHaLdsFp0tJturtYKuZt+uzlpBULUvt++hk1ONzwfobBGnr3fe7USTmCqEYZ274eJfkHpBuFAbjQSn+F4sbGNEPHwkKOajlyC+Nzo9g1YqtULX3mO3v5dwbDyZBFShZGjByMYTTwBhWDOhSU83OjJqjgtTdhHPA1W0Uplz7YuZMBqOH3u41JXCXBFECQUjG0yjOg91FJ/4XmLD0HBuwF8KxWdexLoNIwDMrF6eKGBVltMt87RgxXvbKC2oiPSLyNdEZJf937fS/WyjjTbaqIUQtvh3puBM0PAbpQV9J/ANVX2viLwdE2b8u80a8b2ANavHcUSprHLJfcPMETv/8MF4n/Efv5CpDRJr6v4UjG0xGle1A6p5EKskTeASPafQh2oOQquMOxUQGzHulkFdqOas8VIx1hwAFSQkpnzKXQ7FAY/ek1Z7z2QIek2OJPe41e4aLa0jw6j1KEpr39LdBV5djha/M/lSTS3JRZLYgmZUgKqJQwjmCejpaJ65Nd6uik5OJZrZIumBWINt5PkTdXUeQ3fj9hKfcsn4c71NmtyTyENLy2Xj3ZW1hvyp6XilENpVWUTTabmM02mer2SzsZYf9bWGphLB6Uo9t6gvvl0txkZTqfEWq72++a+/ofYfncMBrWjimZMy3orvQRC0lO6h0T4x5ZIyxDb1rLFFgpyMXX0ttIqJ03HUxR2EDnt+/wr++qc+aH+4i8fKq82nyY3cM38PWoYC5baXTuuYLy2oiLwUeKbd7UPATSwg8Dv9EtcN7QFg1+Qg5Uft4OruYtebN8f7BYWQ3HEziAbvKnPiMiP9i6tDdn5ggt2v7QFgdkhwIgZAADWCHcwEIJFjQ9F8j/bNnYRSrz1OzQQQZMygdALwZhOhMnnxIO6sGaT5h8Zq700jzjgS/A23pV6MtJeQNw+vWe8GqgrRyxXlzokmh3kEP9B8n6jtqN9unWdNMwqlUV8boCHfnl76p4913ViQLNr9Ndrf8xh96cX03mgjdzSM3R8jgaZT0+YQ10VnrL2mpxvJZmqeR9yD6H77KaohFsbWDTWieEQSrnoRE2jNBBMhbf/wveScAbXC0/OSvtZThDXnaJKPR5yUq6e74AQQT8w1vy3gXSMOXLQdgLd86tMEWhtdNV41ikjeXZ78PkprxU3OJKw0pTNfWtAhVT0CYP+vXslOttFGG200wnLk0jmdWOn1SJQW9M22oPnfs4gscTbF6BsBOtZ0MFbJs2eyn4JXISwYzf3h3+xnx879AOw72U91JkPRXnb+kRPk1xvf3OmNsO+lvWCViOpQGaatv34I6oBbNLO5OysxbaOu+csdMd9zYyHlLvOAA0sROXbfwO4brDZ00+yAS/c+aww8dzPOiTFwrFGvM4dMJsbP6roBqp1GA/SmK4S+9Vu2bXt37jLnuHgb7qQx2srE9MI3sUnAlk4Y6kjyuUT7jxBpquKY4+Ilj9Zq+75X+z29ohBpqjE2NL4u1uhbf75mmn0US5Hx0WIpMainj5ueoe/z9yLW7zucnZ33GjQIYhrLzZagIx/HXtSs0lzH3KP5+ubU9lt6U/ER5cr8BvbUakAyfnzOsJDBGZ4gPGFiSebc00b32J5fg3ojfL2H0/z0Tt2OKQqpbmWgYSrLZgPPrkYrPkd45IbzueEpH45/ciWsoVwKrqHUfnB0c/O+tQgFwrPMaLvSAn++tKDHRGStqh4RkbXA8UYHq+oNwA0A2Y0b9Vs3XcI1T3sQB2XVBx4GYFvo8eWHLwBg09Aws10ZxrtyADz8J/2GkwEG+qYZ7urGGbHL6rKDWzKDt9pj3HKqObtkdz0yo2abNwVhBnr2Gm+MIOfgzZpB4JYh9Ii9gtSFwIHjV3cB4E8r2SOGj5WJaQhCDr3sHAA6joX0PGAF0PgUs2tz8UTizXgxvSShtTs870Jz3P4Z1L7klc2DZPaeSG5YEy+GORCJKYNwbDzhl0WMQHDNhKojY2a/SFj2dtcKp0IBnTETl2SzsXCMPWbSAjmFmpc8CBPq6PGC6yYugJ6HeB7kzTghVIiuIZ8D30+oGsdhPtE2/uor6X7DAQD2fOscNv3FHTjr1wCgJ4aNnQTMPUhTb46bXG+1aoR2RBd15Qnzpp/F1WbS6bjXahtTM6jW3jfptnafjgKaSWihYE0fssrQl3LgWHw9cxDRcfZeaBDE46KhK2cqRXXLCdqkNjpaUxHCrQag9X8jx6/13ERGksmorC6uNcq5hPzbw6ZMbPmRntb6tSDiXPdnDVZ0emqSFvQLwM/a334W+PwKdK+NNtpoY15EGn4rf2cKVlrDh8ZpQR3gUyLyBmA/8MqFGvGnYO3NIbsuGqQcuDj/ZYIsuveWWfUbxnsi4wYcGinw+vNujY/bXzT7BSrcL8px7OwfQt/91oOn4DPxlFnCqnlwYW+FojWiZccd/NGkH24xxJs1ms3AXeOcuLIXt2y+l/qEIAtluyIfvH2mhnbR2VnW3jQGgDNdTPzZq1W6bjlAsMH4dxcHc/hTRkMu9fpUOhzyJ41m4xTLiA0mG39SD4N7iWmipnlN6nIH1WjUQUA4blciuSyEST4V6e2pTfvrpIyK9blOypW4Xcn4aLmS0AdBkKINgjka/7xZERvsGx9T5wljvGsiFy0f7GfN+QTdqdB8ESQIERuEJ5UAOpI8LlINEz/5ciWJmQiruJs38sgvDwHwwmfdTrdnNOfXvO5WPvGl56G7DL0o+Vxi3O3qZOzaDfTebheyroNmjRavnkNQ8HGn7QqyM8vURqNtzwwKbhmm1m00h5WVzITpc+FIEe/IGJq3/fZdm3YC1BVDCVpaUDevwZksIeMp7584fYFjxs90Mk7npqVI5e+JcN52SkMdZL9+Fy0hlea7pv1Gq7udWwA4+adVMq4Z0+Pjwvd3bUUr19t24J1P/W+uyT8GwM/81VtZd5d5n8q9VXa31qumWGQBlDMCKy7wm6QFvX4x7bjlgI4D03T8fpbi6jzqGYEY5BwmZswL8r4LPsZv/v3/YffbBwFYmxvntn+/FIDuA1W6xis47xgD4OiRXoafbQTnuX85y+ofejjT5vsjv9yPP24GYaVggrK8KcM5eodHyD2YCLmhb87GQi3oKXD4GV0Uhu3y3HcgCpISMZGZjx2I7kvi+lcuo9MzODa6tSAS87Gly9fR/4OjCU8+MxO/rKEn5mVNe+00q/Bl88NoxkXGpoxAxkSThidN0EpMQ0R5YuzLqPna9NIAUg0gDAl3GIFUWpXDnbGcdrGKO1VCTpr7TbWaRFv6ngkes981VGQ+97f0BNDMgySTQQb6Ym+XMOvH1Ig5SXpnCH0nWf5GQXGAlCy37Cf0j2PvU+mSzTz6ogyvePb3AVjlT3FR3jzPjd4YT/7PG/idPS8H4ME96+i/2dwzCWFqIyDGN6H7kUnUjpl9L+7CqYA6xsOkcDRRGCpdienE9FNwS+Z+TG7swKl04M+YCyucCMgMW7dQaxOIHEzUcwk7stCVtdcYIHaiVMdB9h5KPIK0QdWu1FgKnmQW65Ob88ysEopPfzIAW/7gVlpCfVpnDUkTEbv+9BKe8xTjVLnNCXBTD+5ubx1HRozCFu4v8PHf+HH+7DVm+85bJqn0mOvzJ+cfJ4vF2RZ4teICv4022mjjbITJh3/6OHwRaZyFsRahqo7Nt/EJI/BVxCxVMy65w9OxUhDmfAY/bJbrd1+0kdAT1ubMEnyimqNwwubccYUtf/UIJ4rGyFUc9Ai/Ye6veiVwJdZ6dnxoAmfELH/Hrl1PJS94++xyXDUx6EVasPX2kEpA/qTSu8ts93YdTGiMmVmj4aaplbqUyxE94fR0x1pW1y37TfuRdpvLxrl6yl0wc+EQhXsPm21pb5mQWu+PIESHrRbvupDJ1GT5nJPx055v9tx1TG7wWf0tc47JS4aodJi+9d43zuzGTiY3mvvQcSQga6kJQqNlO9bjRMYnkUhrtqudWON33TgNsdrzSoPQe031K0KcxbS7E834RpPFUCU1+6nG1JCKAwiaphIi2sh3DdWTjj+w17DnJ3zeeP3XWeePAbDRH2ajZ8aJi+IAV/Qajb/33FluKxgDfeV4nuzaaY72mdXT0ad0oZ3mOpzsLFv+Rdj9U+YeVvNe7JkVZhTU/sd4bDnW0cCpCITgzZjvpV4Pb4NpY+CeabMysBTP7OosueEyEqRiMyI6q1y1gVdNjKeRQfnSHRy83qxEggzIjql4eO39+Pms/g/zDAtfvGP+tuqgQcD0i68A4OK338U2uTPe5qI41ijrOyFXrdpPfrUZX/0XTfNf//Nszn+XeS9nLlqLUzL7Zg6MtHz+5ljWilet4LD9azbLuMA582184gh8V6j0ZHGLAXiO4V3BBEzZJefHfu3HyXgBt//q5QB4x8bp7DPcZPHPJrn54GbO+Zl9AKw+bzXqmW3OoRMEG4cSgek48efebxmOEPtChOlkaK5jhH4kqItl+u8aRw4YrwqtVBMhE71QKYGldXx1XJUrCBIqZVUvcmK0hjePPDWCHEyu8yjstvz05HTSvudx+Cc20f+AeUFyDx1BCuZlDUdGcbJ1ucfrC4zb7ycv8imcUA78pHFv9WZg7deOATB+2SDjWxxcK+Oj5HPmePOvstpMsJnxyWTyCUNDGZXNgU5PV0wv4QhUqjX3RlI5ceqFfhT1q71dhBlvjqCPoHUumxLWbotdFx2j1yUlJoXyOkMjvO15X2TAneKCrHm+XTLXZvKmAUP3fC23jZGS6duuymouWnOUY9aj5thta6lYr50n7dzLsLuJ7f9hrl/danzu4YvyzKyDoN96PgFBwXrVVAWpCGHG0oklKFvz1OyqDpyq8SAzbULvriwdh2068IEMnqXesrvGCMMwHu9OZwdqn4vkshz86Z2su8koUI/8bIHskJngfCdkdjqLzkQngUMvN9cw2H0lvR+7reFzMA3X0jpv+tNPN9wtxOH7EyYRopXl3D6+AYDV+Wkyxydj6q3w0ImYWi1tGmA5SHxjtD2tXjoPqurlzXYQSc2IDfCEEfhttNFGG6cTpgDKaTXaXnuq+zxhBL5TDcmcnCHMZ6h2+DhVc2nT63P4U0ZbyRydpDLYiXfMelXYTIYAmXf3sWG2iu6wqyFXcCIDXV+PWf5G2nj6c6Vi6IdIQ095FWixBMFY4su8qh9ndCLxT3bdWFuKkfZ4qA/EiXzYVWHA5lg5erImJF+npo3nDOBNw+Dt48Y7BkwOFtvvoz97CVMblKo1tp7zoMbnc6znjY6a+1RTCCUKrOkx2mhuVOn/4kOMvfV8c84ZYwQEOHmJQ3YYijZ5ZN/DAaUB62Gy2qtZmK56KOVtI4IU8nHWT52ZTd0L16xmUiuOGurHdeMVHeVK7IkTdNjVUYuu4XGglr3m0DfX5IDxUor2S9Fk52UPs9WbaKn5Zxd2893CDgAOFHoZf/t6Ov7YxEwEWeX89x4CYPCzkxwruPiWbvHGizjD5hxrd4fMXLyeSZv+e+JZ01RL9pXOgoZC1fY7LEtM9xAKCGgUEShw9KlK9oR5NkFeyYxa+qdzPZXChjgfVKXDof+7BwEobV1N6MHuV5rxdu4HxuPPlEA3l1i/+SQAz1/7IEO+GU9Pe/qj8Mfw1hf9gunOgw3UbfseHH7Lk/nuuFlt3nVyfc0uaeesECEIHSZ2maDGPQNldnRVce3yMijMdSpYDpzO9MiqWjzVfZ4wAh8AEaodHv5oiakthg/t3DNNYCNUxy/uJzMZEmwzuey9mSqzQzn7OUB7faRivRr2jhnBDlANcEem4xHmHhpOBH6xNDdSMRICGtqc7Pbr4aO1+9WM2DrvmQZ53+NgpSBADhjOXK27YdyfUgk9YiiV9R8YIZwtNnTG7NldoZrz2fjxPXPP5ziEx04mpz5+IqaMnHPWc/CFq1n/L8ZTYtWeg0g2G9MDs0MwfJW5v6FvvmfHzLbRc31cOxwrnUlAGtiJM7oHEU9vPWpqKn5Vq4buSd2viM/XIDBCP5o0Owpob1fthUeX2argb4SaClsOh55lKLNmwj4aSq7tgCvwZ+u+AsCtA6t465tfxba3mIn1/H/Yy31/YKiJR3cPsBbI7LG59gt5sONAZ2bJTFToOGLazH8qh2dzM01u9Bl/5iyBJfxD17W2CWOvUCe5B+opmg0pbkgmr0qf5ffXOfhjDkHB7JwZE2ZWG6+r6fWKrJuhkDdC9cUf/S7/+MAzAXj+lgd5Ts/9PCmbjKN6/Nv/fACAZ9z8q2x53QMN9ylcfyIW9PXetydOJAFU7gkfdcCfssGSQYYj12VZe7PZHkWmA5R7lkfsmfTIp9Voewkm0HQ98CXgd1V11G67RVWvWqiNs8unqI022mjjDEKo0tLfMuH9wB8CFwOPAP8rItvstpaS/D9hNHxFUMfBKYeMn5ukmZ3c1hFrdW/944/xN7/3WkJLOYj6fOK9fwnAG17/ZqbOyZGZtP7Hx0/ChjW28QrMzIItQkGosWeGU62ipXJsmJ2T+S8IUn7LOtf/vS6HSFJ4um7fdBBT6KCR3i5iCmfEFFPK6Ds7f6BV9ut3sfG+1YQnTT4VZ/XgnH1qcqZEriEnR1nzg46kCIXrgudS7bRpGHLCsDUrnfu+4zz8q6spWQcftyiEdli6JetDHl3+hjWw/0jt+efzDIm0fDCUjpP0pabP+RxhZp4hLlDvez/3BqS8ViIqSwRShl+pBOSunN/rw00vBpCGGtaTsyf57lPezzVveisAzsEca9ebaL6hjknKtyh0m5WKFjLIiL3ezg68w6NkMmZF5ZRDgqwZ25nJENcP4pQFoRei1qAbVuyKqJq6Dj9ELMXjeCGO/Sx9SrDKxfXMfc2fV2Jk2LxfT9q2n0OTPfzW9q8CUAx9vnzVP5nzLyIb6bef8n6wC80X/NXbWPO+xGe/qVZ/PJFxuZMS57UCyIwLEtRq9t60eX/94RZyTLUAky3ztOrMnar6Zfv5r0TkduDLIvLTtLhmfcIIfFyJqRsk8bJ42tt/wHf+0tgx3vmp1+Nvge795t50757m59/wGwAU13r4UyHHrjQjZvPRjXGgFVgeOaIa8rkkYMpWdapxB0xFDZrycbV5uhsV1k5Sy6bylAR17aVdEVOCreWcJXUIjqZSFJXLcTRtTera6BxREJSGeI8eIozsCUHIQ39+Aef/rVm6B/0dODNmiX/iaavxJoVqtxU6WY155Jhnt6cZP7+Hnj0H7XXOFRbNiq3HboGOjQBOTZTqN3khl6J4uWK5qOQZXjl0YM4ucw6bR9hHmFHl6ksfBeDBT5/L2pcbDr8cuAw/bzN9n7kr3je0z8Lp7UHHJ8hYRSRc3Ys3Yj5Pr1tF+VgeCU1nOs+ZILCfZ8byuLkATQXkuX5yPa4bkvHN8y1kKogo3Vkz3nNuFe+TZga/fXorf/+8j7LZM0rDXaWNNddef72tZMX58m//Jc94yq9SPWposlUM1wh571itIps7EU3E9p2P5ugQVt9ZTNyeHTGTNVA8pwfua6EzLeA059IREelR1XEAVf2WiLwc+E+gFR/95gJfRL7QQhsjqvpzrZysjTbaaOOJAkWohsvjpSMie4FJjJpXVdVG2Qf+HDgf+EHcB9V7ROR64PdbOc9CGv75wC826yfwvlZO9HhDbTh8sd9DBZ71O8Za870/uBrv/xhj6TfP/wguwkt//7cBs3/uYbMtM9jL6IVdcSGT8e0d9H/TasDdnSb0P6IYiiXzB0lAUEpTjzR4p7eHYGSsTltuTLM00tKT32qPSecaWap2X1+sIrBpe5vtD0ClSjg1XdO38/9hBOzxzvGTsNFQYSevCkDT2nZI7qjN9DioINC9e3EaUmzATcUTxLD0jkS02HJl2Ex57GjkPWVXGntf1c9P9dw076GRkXahnkyGHnd9zaQl2Pz+2zixz/BiEz83gZcTnCGTdiE8fCS+9+H4pBlrtgKW4zpMX2riIRBY/03o3Gu2TW/qir3V9r3QZ3DtGDNl8ywqVZdsphrTJ9P397P+KrNqGf7sRlRgw089AkCnX+Sa3/06AOdmj7DOG4uvYU3qc6PrbeVphBiK5w+PPBeArz5wQay1e8cyxFFnQP/FJ3Ht6vnKVQd4x9C34m3fK67lbee9im3/bldDVY1Xe26xtQycrWCZI22fparzWrlV9WPz/L4f+KVWTrCQwP+/qvrtZjuIyB+1cqLHG6EvTK336dpXZmpjht8YMAL/G/1PgY8ZAfST+jaOP7XK9j1GWHujSd6Z4mAeb0ZZdY9Np1oMjaAHI9xrUv7mY3c/8jkolRsK4XBq6VzhQoJ8qYJ+qcdrnQdNBHEEJqeTa3UExyZvyw/OUC75eBlzzPZVJzk0ZJbn5Qf6WPu9IP3+1nLmdZg3D36az4daTn8R19cy4qRidtysr/KM/J54cyucPcylN7qcKr27LIfe1cXx19h0xff2se1L+6huNL6tzrHjSFoBECcunajHTtJxv7kXmfV9+HuOo73WffZEiSBvtl17zYM89K8XULVlhdY95wDlf1hH4TcMpTbz/W5m7zCeMZ3VAAmNoAe4pvsx1tlsga6EZAjI2QCzgtS5GC8B0f1yUpFvq4eMO+dlFx7iaT0P46YGjWvvZLR/YGeH63JH+O5z/w7MvMFTv/ybrP+K0cbdyqm9OxFOt5dOBBG5RFXvWcqxTSddVf3UQg20sk8bbbTRxhMRi0iPvEpEbkv9vbGuKQW+KiK3N9gWQ0Seg/HWWRJaMtqKyE7gbcCm9DGq+uylnnjZYW1px67M8r23/A2O7aY/rZS7Eg+Lgdt8Sv1mnqvme8iMGUrGm6lS7XDJTBhtNPvo8VrN0fdwotQGqnFmyZEnD9JxqIfMHcbgprOzSdWfKB3Acl1i5JdeqS6w5/JD0imPSVE81pCczrWz65cMrTD4qZCj1wGjNofK9UfY0WdWrCe/3kmYceJ6v0FGKD/ZUBqZ2x4BxzH5bVpBI3oHmtfiXSxqauOKzYwD6mr6Z/M/ReNEPQhQKgqVeTVCITdsr6Mjz5afM+OpeuW5hCOjlC43GnfHQH9sbJdM5ByQajOqsHX7w6jjxCm1nWJAtWDuz2N/dx79B2ZQUyOIsaMbkD4Iy9m435GCrWI8X57cvReArZnjrHZNha2xME9RPRyrcfe6xfjaTxVP7zEUEhfWVpX63sSO+PN13bsIsFo7Dt+dXc/T8ocatvfB6z/ABS8w9NaBIMNVnzv1Pi6ypu3JeXj5CNep6mERWQ18TUQeUtXvpHcQkdcBvwU8f2k9bt1L59PA/wP+haZJ1VcOQRbGdgodh+HSL72Zt11nvJcG37yH/qyhG+79fxez6pZxDr/LHBPe3MsrX/89AG5623VkRyqIFRLBUC/OrBXYVd8k9qpaT5XOHEGnCdjyp0OCnEN43iYA3KOj6LBZ8lIuL51j971EyFpBFi3dVwKarnIkTlz+L06XHKGzwJb/MvmEhi8u0PsgdBw1xx67bSvTbxoDYPDWRyletR3NJkavmbV2Qr1yJ5lbH156Z0+R7moKm1ZYLHUwsGZiDo0ToajKZCr0vlLnwpdO7fu92e0UHjT2pPDo8Xgi9W59CIKAjlv2mm2jY8lkW1e20Vk9GKd/dlb1Q6WKO2WomLCQIXfABIb5E3m84ak4BxBA/93jhI8YV+OZNYJTidw5hSM/WeZjB0ya4w+c+1GyVsAHFJkOM/gazLme5cJsMH+E7HfHz40/OxLiiHLr9FYAntt9LxdnxuLtXx6/hG9ZA91H7roaeMey9G+5OHxVPWz/HxeRG4GrgO/U7fYB4AJVPVF/fKtoVeBXVfWflnqSNtpoo40nGhSWxUtHRDoAR1Un7efnAe9usOu7gQ+IyAtVdZ6alM2xkFtmtE7/LxH5VeBGIFYzVXVZ8oyKiAvcBhxS1RfZ834S2AzsBV4VhRDP20YVcifgo7/117zv+LP4/rgJQPs/67/BH+1+MQB9D85ACBt+22g9j/4CfOP3nwaAX61S7vHo2GOWfWHBp9prqAgJFG94Kg68qvQX8MbNbQgyeYKsizdrbmWwaRXeUTsBi0N6QVRf4LlZTVBEYKsJYWffYZNzJ1j5xZWGirh1mn0+F3stUQ3iVVLH0YBqTkwhFizz8FlDMUw8p5/seDVOX6FOwkxMr8+QabFeRg2CYE5FLIl99JfRuJZq6orVB+PPLkKAMmm9hOoTa9VrwGVLR0yGWb528gIq55h74x45Fnt6aUURRwitJ46J60h1IOVBFB47jmMznuK5aKmMTNqcS48dQGxwnVPIMHbFYJwfp/+BaYprOuL4BaeqsTFdQlj/6Qzjm9cCUNzp4ovRlHMSUJSQoi1Ok5Ploxr/dpepf1QJXYIgWRmlKRRHau/nzlUn2DVs7uFnjl5J9wMenYfNfez5/gHGnmrep82jAfuWo5PLF0U7BNwo5jl6wMdSAVbJ6VT/VET2A59jibTOQhr+7ZiJLLqqt6XPD2xdykkb4C3Ag0CUpevtwDdU9b0i8nb7/XebNZAZLrHxI7t4w/G3MnqesO5mM/j+5qE+uuwLUVnrINNhXDD6nK8W48jEcpdH111HefjNhn/eeuMs3piZRGc3dDGzdhWddjIIci6ZI1bACXTuncUbtV4qI2OE6QLUDdBQ0NdByxUcWw0qLJdXhLeP4A4NEp4w3LuGaipS2epb0tuD5nyqaw094JSDJDU1xMLe7Cxkpq1XRVUpd7lx7pc0in0upWvPI/v9hxbXUdVaod+qDWCx5wCmzzGC9V1rvxJvKqsyHiavVH1QTnoCKKc+56TCRDnLzDpDk3XTAGmaKrKbDA6YSmS2T5LPxfUCKJeR9WtQq3w4Pd1U15nEYrNDWSoFoWIjb/0J3+QksjQOnht/jsZqz17zTF956xv58tXGZuii5KQaC3yAadvNrlOUg8cP9yZfUkJVqsnn3NHaCXXPsd64mqdeVuVP3vxB3ne5oc3Vdenca+tULNO4UJaH0lHVx4BLW9z3oyJyZOE9G6OpwFfVLQAikqvPwiYiuaWetK6dDcCPA38CvNX+/FLgmfbzh4CbWEDgt9FGG22cbpzmfPgAqOo3lnpsqxz+zcAVLfy2FPwd8DtAOq3hkKoeAVDVI9ZyPQfWfemNADm3CwoFBr65j/67e5JaqUEQ57nxwxDNJkYgd6pC4Y9M1skn9+3j+y/cyo4PG59fp1RhZnMvAPm948jMLNppKJ78XceTAij/WwTXIbQZKp2B/qa1VRdCOhdMcHz+TIOPB9KUk/heQhWMjsX1dQVL59jCIhRLyEwJ32r1ldVdPPqrNvw9DFj9LScOnHGCROPXgpgKS5HBsRLGNEJuLKCad+Da8wDI/O/9iQF7ITweWn09RJjcaPoTpE43YhMFBdaDp5jS9ivU9v9QpS/+fLLajffbXZTfYxnSGxucM1oVBuDYesbxvesz33VisiZVtB4/WXM/IqqtUnDwSlBNqWyhC7OrTf87jlTZ8K5dANz+PxcweE8qBcPdndx6qcnkeVn2EL6EgBnvRfVw7Uqkww1OKTOj2Hw/aS2+YPXayINIVJNCNWpisqKaM9s/VuV9f/9iwB6kinfCZjP1WxV7zaGsjMC3FPiPYyjvtNfk3yx07EIc/hpMKs68iFxOQu10A4Ul9jfd/ouA46p6u4g8c7HHq+oNmHSh9GSGlHIZfA+ZLsZuk8zOxu6RUiwhqaAed2yax0ZM4qn779jCucEenOP2pQtDCkUbSJLLoMOjSJQ/p1AgPHwkbj/tkhjWRaw6+dy83jWNPHjS7o56Gjn7yPsGQPwGgU82opgwhCAg6DUcvjtqhHZovZZOXpzn9uv/GoCPT+zk746+mG4blzR6UUhmxJwjOwr5YeKc7P6k8XZKI+LdWxb2EZbpvgW51OuR6lqlw2XiXHOOSXVjSiNUqaFq0kL+QGWgpu3JIMf3xrYD8MPvn8e5k8fQz5kAQad3lHDMKB7xeEh5SemkcYvE86BaJYy8wiCJLhaBShXpssGDjoM7biiNwrEMxVUe/fcbb6riYI7QE3oeM+N0el2G2756AQClrWVOaoZV95rzr7o34IYDxu71/u2fwEVJOx9HNFZZldwiEqjVo/9Om+AwTOwwAJ2HkrPlDjVIR51iCKVcgQH7bpbLiSI2syR75xyY1AorknD4v4AicC+tpSiKsdBU93zg54ANwF+TCPwJ4J2L6mJjXAe8REReCOSAbhH5KHBMRNZa7X4tcLxpK2200UYbK4DTWcQ8hQ2qeslSDlyIw/+QiHwEeI2q/seSuta8/XdgHWKthv/bqvp6EflL4GeB99r/n2+hMaMFRVRElJEyn4eozmy1WuO3jCoDHzCaasfDxyGbRSesMTKbjYuIj1+5lu6jJ5LKUqVSKiOmolPThsphroYvTTT8mv3qcts83tp9dL5Ig5RCIdYiNQhwOgqxoVg6CmifZdwOH0c8j+Iao/GXd3bS8+B47G3zjXf+dXyO13Q/wvNf95d8fMwYzn6j/y5uGDeVsf7xlmczXnHiJfnmGyXOceIWA8p9GYKcTV9w3flkv2PSG7ak7Uc0RhiaItyA5uZPFx5p8sWBJNvq7EBKc5OU3dD+9weMkf4jI9fy4p47410ruHFh63qtfibMcNeUqaj29QfOJ7PfrEK3//cUzMwy+FHTTumaC/C/d2/jSws1qZEcFTVJZV91ei1VFHlORWPd86j2m7GePT6NN5OlWrAUVNbBS+WXyY0EFI5G159hdmOVk3YVM3B/wKHvGG+XWzacw1W5/clxy+Sl83tHnkf3PltruZEWn4KkObU0nVcNDO1qV0O6dhViU34QLlM8i64MpQN8SUSep6pfXeyBC5JZqhqKyC8Dyy7wm+C9wKdE5A3AfuCVLR9ZqdYu2VLLynBqGqe7tgJSx0OWJ1c1wj6KzgzDeAB13z9iOO2odOH0TPKSBaBT0+i09QDwvZqyhdHSHBZwx6xD/QSw7BAH8cUUWbeIJybXhZ5utCsqeZdhdshw+PnOHN7+48ysjtwhoLiuk6ABDeQiDDouv9Z/BwAV4Bd7TGWjX3zuA/zDyOV8+jGTJGzPKzrofMQIwL5dAd5MQJC3PHnOQbYZQam797dO8ZQrscDHCvxIuAcFl0recu0DjokojWRcJODTlxTpCBHDYjnm/3zoMjZfZsbQen+U4WonacyE5prumjqHQIVv3WcmvN47fDoP2YClgyfBcWIuPnP3Y81DmKLU1OVyjbBHHDM2AQkCtL8XmTQTk3ZkcYqWDqkEqJOa4IBP/r+/5YXvMU54oxeEiSAVyB7xmF1v+jpz0o158n8/+BSu2r7f8vi1gWUVhKV6dRx8w0ayD5tUMep5SZBfNmsmsuj519eLCMMaZY4wQNfYSVckddzy0DArxeFjsmXeKKa0WwUzOlVVGzp4pdGq9eJrIvLbGN/4OCPYcvnh27ZuwnjjoKrDwPXL1XYbbbTRxuOBFRL4f40pVn6v6uK8FFoV+L9g//9a6rfl9MM/daiauqilclz82vxea9MI9x9MZvpQY61dHKdmNaCVCtJtJkyZmCKcnsGJtOFG9zgOlKnW/dws7fHcYKx4FZDxKT77IsAsuTs+f/v8174IxKsLR3C6Oo3GFG3LWI2vr4fixl4CqwFXsw6VDhvL0FGA7ZsJo3wCAjODLn/zB0k+pzCln+bEJdCU51Fq26/338nVHSZnzPend3D7TqPFP3DLFtZ+z9QZBkPxaNYGEG3dCPsOt3Stmnr2Qc6jOOBTtFRNWoOPg75S39Pafc0TFJjeoIS2WLj4AX97j9FN3nFpbazMzRPb42yK951cy/EjvfTfbq5j8I4pUxs56WxyCjcJ0Ypot6giWXg8iarXcsWs1Owz1NkiGqXtXruayz7+MPeOmbiS8JdDihuMn0Xu0ASVngwf+5u/AuBEmOWF734bL3nzTQD8+21PQe0KhrJDuV/JnjDvzPRaGLzLPJe9Fw7AdhpiMvTwncqiDbdP/8GvsOXhVPxFtYpO2RVNlJE1di7wkI6U74jrJu+w6xA75YPR/qN3c75KaovEInPpLCd2AfctVthDiwI/8sc/oxGGyYBYCGl+PProuiZoJdpWKtW0J/l8/Flnm1j5NUySeLXgnjm34pU9n+OQ/4bhcSdeeiml519O9it3NmxjPtTz9IgTL4PFdXnw97fh2gpUO//lRExnhZ05xrfU5jCJXCbdckg1JzXC8bxffoDzMtE9EZyoUDdCoBrnlwnqiIoA5cqs4Wivzt7BzR27Afh+70E+tuFK3N3mZV73nYQi88AUcW+F1ilXmNphOO2ZIbcxbQNgBX4NT5/+Hv1mEeZCqEbRww6B9TT67viOmtS9gQr3nDQC9+SRHtZ/2aXzgOGU3UPDCSURktigMEpDNN50egYNNRb0Tl8v4eiYOU5DJJNJFJzUBBfuOcAXPnEdP/VakyP+f654Br/5R58wt0VdBrwpbi6aCdYl5OO/95f87fFkUZ3pM22WR3NoIJQGTd+yJ1ym1pl77z9Y4HuXb+W6/GMAVJahRPbm1zxoIj2b0Z6RclUuJ5XQclmkGiT31PMg6yKT1n43W0yqthWXicOH2F5zmnEEuElEvkRt5oNTc8uMICI+8CvA0+1PNwH/rKrLmw6yjTbaaOMsga6c0XaP/cvYv5bRKqXzT5iq6NG6/aftb82qYa0Y6vONNDWWRtrCAp409Vp9PVVT03ZKs29mfG3Wx7Tht/vGu5j+sUupPNNEX/s33d20r+4aE6emk1PG/9gucyWTQaKiLna5mztmto1fsoqee4zxceM/7eHEv17KdW+8DYCbPnYlvi13W+40Gk3Z2r5n1ik/P/TdWKv3cWoonRCNt8FcLT/9+1OykYF7F+6FIR/hKgBGjxfoe8jcD1HwWqR1ZKCP2VXmOtWhJl8Pqc8RndPUaJtutyoJ5SJOXHf+27t28Iwdu7jvpMk7c+JoL94JQ+Gsvy2k88AM7hFr9nIkSZcQ1UWOqAbVebXQWLuPzp8aJ2k4vd088xW3sz1nAgKPXZukczhW7eGPbnx17CH1V6/6ENPqcWXXXgC+27eNqs1fkx2YRUOhPGpoo9JgQMnWu+950OXP7n4BX7zGiAVfwhoBuBjD7VM+barQbceMuZYdHCID9nQIuWxC6QQBOj6RFM4RSdKV6/JQOgB6GgW+iLwD+LKq/tFS22hV4D9ZVdO5Hr4pIs2lzmmGUiuE5+POmw2g+babhGFuUyqn2QBtJWlaU68cDen8xgOMvMxw+n2uO6/bZnDdxbiPWGG4cQ08sgdng6EVZrevIv+QScE7/PR19N2fUDOzAw5dHcYb4sE/vxhWwfduMO6UnRNhzNlXOoWRK6qQMS/NW676BpdmpmPaJmwg0Bv91rDvdr+rs2PAbrjQ/P7NVTs5sMEI0YH7fLoB97EkorQeYj2xRp66IRbioUtM1UCd8Je53+ejdEoDigRS83uUGz8MhFsOb2Jq2FBR/gmfodsSIR4LezDCPk3BBkFs/9FiKRZKC3prpd0yU5+1UmGykuPP/+GnAOh7wTDjgelXrzvDX7/iQ0wEiTjeWxmgaCOFn7fpIb6853zbbUEcraF4sNc/fkGAu6/AK3NG73vBOQ9yXt4EJD4ptw+Ain2m/gL+6tt/57aGvzeyd82zo3k/I3dpR8w9bXrWU8Vp5/D3AG8RkUuBu4EvAV9dKLFkGq0K/EBEtqnqbgAR2coZmhe/jTbaaON04XRq+Kr6CeATADbzwQuAz9pUC1/HaP+3NGujVYH/NuBbIvIYRtfZBPz8Uju+klhqrdhWA6GarSIWWp7Wb68x6JZKDHzZeLQMv/pyPvGevwTgTVufVXNMccBn+CeN85SE4F/eT98njYfP8VevQy43hrp73/JPXPEnv5KcO4TikNEAZ1ab/Dd/8jsfAIxh6pqc8ShxEB6t+Nw8YyoPTQa5RVU5clugd8Bo+U/JGv/9qzp2815+DID9q1bhlrL0pFJH12P6CrNN3TqapoFWX/O5juJpdFkSYN120lZc+9+H6fE8vqVxYu0e6L7NVmJK0zjx8SFardYYX5uO07rqYzE0TDTccoXv3Xwxnc+dq/xlpUJZXUpq+nmi6vMPDz+LUsWIg7U9E2R8s9qYmspTnfHI95q+dez26N5nVxGuEHqg9/cC8C2u5cZzrcF+5yRbVg3zpg3fBuDq7PzB8q/49bdS4I75rze+vOYr9PgewGlRR1fQDx9VvRO4E/gzEenGVO/9ReDUBb6qfkNEdgDnYkb6Q6q6cuWXznC0ugxdaADXb4uCuPpvvI9f+9/XAzD6+rWs+v4JGDPeLh2HZlHHCO7Rcx1e9is38cErnwHAS556C+9YbV7A0dBh9NIqvfeZIVApwIHnG0Fy7dUP8JKBu/j1zxhv3N//ic/gYOgIF2G7X2G7DaCyPW3YfwepoXPqv0f54+dDetvbt34JgHcWX8aRF3QCJrK5+7EDNbSO9PZQ6q3l7ePP9ZTOPAK/mYeOBGIFfiS4U3YYB7yjGbJjyf6xoI93qhX0gHE9nC0mdEwT+5CzehCdMZ4nOjU9dwzFHlnC1s8VefQNJrp29epxjpR7AegvTFNRj//vkWcCsOqv8pR/vcpV603UbFUd1naY8RQOOBz+821kR+w9dYtMr0vshOn7pC5077anf7STA/1d/P7TegA4d+AE/9+mz9dc15v3vRSAwn8tLOzjc7RK8TD/fVy2gEY9/UXMrXAfjNgWAFWdEJFdqvqfCx2/GJ+iJwEXYfI2v1pEfmbRvW2jjTbaeIJAMZROK3/LARF5FfAQ8J8icr+IPDm1+d9baaNVt8yPANuAu0gWSwp8uNXOttEY8xlym2kyWq2C1fZ7H+nl5DWDTK8znjmlAaXaE3kJBXzyo8/ihl++AYCPnbyGHscYZr8wvYquRzyiDL5BDrofMfP/Pfsv4CVvuos3/vjXAHhGfg8+ZvlfISREqaQ01YK0luqgVeNtPa7OjvHDUi8AT1m7h5vZwpFnGM2x91udaCqVxujTz6nV6tN1vutonDmBVvVeO2nWxiq1STpeu9HVWKv2Rh38abDsl9Huawyzjb1DtFhqucCNjk8gfebaqZiVQc0YinzNQ8W761EoGuNrNXRiCqeiLn/wnZ+g6yFL6fzWKD+77TambL7kAIfdU8YV5+A/bidTThW0ySQBikGUBdubK9BUhOwoVL/WB8Ad12V54ZhZMb580128ofcOJn9lld17fM7xLd2LZu/IAgGPy4PTbrR9J/Akm1TyKuAjIvJOVf0s8/qU1aJVDv9KTPHcx9fo/QRES7xj3f4Rao5Le2OEGvO97j2PsmpfNzxnU7Qjvi1r13ftMUq3DvGvRw2l8/Et3+Q/JocA+Oe3v4LgAvBtbNmm/x6n2mUmg6NX5/ClykjV0AEHqh2csAWg17tVDgUZ1ruJO2BRA3INhH4k4CO3zEYCf76grHpcHfEkfXcRqvADNgPw4Lu2cu5vm7wrsu0cQtd65IBJr1znedMwmrZewDegdCJBr2KD0OKJQ3BttmK3BP6koTYAxp+8np5bbAnEemGTChQM05HhUbOtVEXbuhHu35U+KBkjGqKlEp2P2tTN64XPfvNqAG66/2p6O4TxC80zfdaaA4xWOhipmOd902PbGfiioQXdqpIZL8fJ8UJPSKX5byjsI1TzYIcQ/kMFxm09iX/d/Sw+v+MSeh/cPe+xi8Xjmneq2XlP72ndVJ2QW0TkWcAXbRGplnrSKqVzH7BmaX1so4022nhi4nRSOsCkiGxLzq1HMJUBX0rsxNwcrWr4q4AHROQWakN5X9JyV3+E0ar2Me9+NlWDOJ7dr44a8H16dhtao+Ooz7EnGw3/5O1DbL5nmh/u2gLAM//sl3jSu43Hzsvf81X++RM/xqq7zeN0xqY5/GOGKnjWy27n48euiZu/O3MOt0+aFcTb13yFUIXdFaMBhjgECBfYyKx6Tb+R4dYcV3utCxlwI1ydHYP+JMXED9jM2MsvM1+0ztum3hBb76VT/7neS6cBRI0qFWVQcEoQZQX2ZmpppFKP09grB9BSqaFmDwsY+ktJEZ/hJ/UweLCbcNLce8llk1gRm0Zjw7/cb75+to+1vknPUB7qwimH9D1sxsm35AIKg9OUSnZl+LV8vErqOmbGh9qcU5UON75vrWj3kat/pUMJs/Ye9JYZm87TO+/RZwdUITi9BVB+hbqRqaqTIvIC4FWtNNCqwP/DxfWrjWVBJOh931Quir5PTxNuiDj7AqEneEXDs4aZZMm96p4QqYbsuMFIpF2/7DL9frOsV4HyBUp2lwnEwpGYirhp/3amRwpcsuMAAP/22FMYe9h4xXxr4Dxed9kPOSdriOoAh1CF83yT8KpCiN9k4bhUHj+NeqH/paebJHdrvuNawR55qjDXmWY+oS5z90lvi7sdUTqW1pYQnCiA0zHfa2wIPYbTkDHL+9gIWl0ijWN3BGDVD4cJtq9H7nrEtFksxUnWqFSMROq0nEqosQ0hyHu4pRL+hOn4lk/7lHq78KdtMFtYRSNhrgoihrsHqvk6miwNNYIeEmEffQ9zCr2GBvSy5jyH3mpsjuv/5tbWrvsMxOmkdFT17nl+r9Bi+vpW3TK/3Wy7iHxfVa9tpa022mijjScKTmfgVQQR+TlV/felHLs81XxZWq0DEdmI8fRZgwlfuUFV/15E+jG59zcDe4FXLSZ8+GxE4/q2UV6AEO3tZPRSo2UXjlUIs2Zb4AuVTgd/2nwf3+TGGmZupMqRp3UxdKvx2976YZj5bRMAE6oQ7h7gwKsNVTN062y8MhAV/JM+JzcY7XC6mMHabJGTPjc+dglP3bDHnK+SJ1SJKzk9recRXtpxoOE11tM79WjVgAuJEfeLovStNT7jU+v7yZ/QGg17jm99A//6Bd/ZVDxTtK+kWbVUOzUZOR0Yv8g8s97/nYJKJc7ZlPbKWYxRHwAvFXdQCZAd5hnqrn0cfZH9bKmldV+ytZdJUjlIoAQ5D8d636gD0+scBu80fSv1+UmhcFsIJS4+78xP5aSNtOqaIulBwcYW9FTws1FdXtNmcNXk4q77DIOyrPx8SxCRPwB20qIbZj2Wi4Ba6sKmCvyWqp4PXAP8mohcALwd+Iaq7gC+Yb+30UYbbZxR0Bb/lgMicgNwPrDkGKjl0vCXBGtljtyMJkXkQWA9xur8TLvbhzDpmH93Bbq4YhBHqDxpJwDlXp+pdS7erBk61Q6XSiHRLEIPKh1m7nYC6N1l3SHLIcVB2PdCY2A956tFOv/UJBY79BsVvMFZSpNGJZs6JxcbIqsPdVNdX+LkuMms6XkBmaNW+86Bv7+Hm/3LAKPJFVdrrPl+Z/pS/v0pxhXxxvM+NSdb5nLhoM1H/7K+2/n6nnMBqKwLmVkHEhGrKnHag8IRaajdR5hP+weTTiF0G+wP8conPqbO+BsVjiEM0VKZMJUFc9GaPYDrEnbYBbUrECihTXrnrurH2taREAbuV4pbTYm/3GPDaMHst+cVDn13ZVh1t3ELLfd4dB4KCT1rmO10yUxa7d9zkGpIkLMJ4nxJVjD2NgemWaqFZHVT7oIwH6I9xk7g5+bGGbju8mWtXBHo8lI6NifObcAhVX1Rg11eC1yluvR0n8sl8E/5qkVkM3A58ENgKOVvekREVs9zzBuBNwLkKDTa5XFDOky7laCPxbbrrB7k6FXmxR68u0y5242Nkav+61EO/rQRcv4MuKWExnBL0LU/ESqbvzhDkE1JKysMfS+gM1fiRK85R+FYQO+njD979ZoLOfDcPNWttlj2gx3kh81xmcmQICuUum3lKBf8KaFsY4HcWRj7zAYArtz0Vt70ki/HdWxbFfz1HjsHq8JdJZMf546pTdwzuo5KSgIPdhuD6KHjeSSQlH1ViYbm7JDiT0hsYK1BIyMtiVDX+ozj2pjSiY6Jj3NSBuRypSaV8ZKEPeAM9MeCGQBPCDPmXji9nWRsDFP3vhBvVmNBrR051Df7bfySMJ16o0IP/BmNUyYEWWLJ7Y/D7Lo8oZ/sG19DSI2hNp27KCiEaE+1oaAHcFKFYg59eicbXr2rZvty+9U3SkW+HNBwWZWZtwAPAvPVpn0Rptb3S9OpFRaDligdEemwBXMRkZ0i8hJbFCXCTy/l5Kn2O4H/BH5DVSdaPU5Vb1DVK1X1Sl+WWjK5jTbaaGNpUG3tbyHY4KkfB/51/nPpTcBPAR9dan9b1fC/AzxNRPownPptwKuB19mO3LfUDtiJ4z+B/7AhwgDHRGSt1e7XAvOn2ova4XFIjtQClqqpLdTW5JUb4iRcs4M+UiXWsk68dCfrv2GSmRXXdlLu8Yy7HHM1z0qnh2MNb1JWpGo+9/2/Tg4/zUc2GPfAI9fmKL/gSQAM3aIM3BdyZIPRCLv3ao2xUiXR9KoFk3ZArObsVBM3xZ5H4T/f/Tw+sOMFAPzJz36YZ+dPLngf9lXhi5OXcduY4SdGi3mK1US/EFFcx1xouerFn+cYZsM4CwAIVDsVx5Z09GZbMNY28cVvun8Dt8WZa7aR/cqdSx4vkjHad+TmGaMa4t7+MACH3nQZrvX2PHqdsumLIf6UeRhhxkPtSiA7XOLA87PwUrPz9O0d9D8Y4pbNhVUKTqy1739Bnuufewd3/MPl5vwuMZUjarV6+2iCbELvaE8FP18ltBqw42hsrIVaOid+funrXeR9apSipL4+RrRtud7ZKJdOi1glIumk/zeo6g2p738H/A7Q1fScqveJyMsX0880WhX4oqozIvIG4P9T1b8QkTsXPGqhRk0EyQeAB+vqMX4B+Fngvfb/5xfV7uO0fJsP6cF0yue7aEf8ceB+410zvj3Pxo8+yuxlRgBmT84ytc1wKKEvuGWNBXCaRgisJ49/0gTjVHpyHL/KvMnVTsPpn7jUrIxmrp0mHLZVjbpd3LIy+G3zJpe7JJ5IZle5lHuIK2AVhxRvWuiwtbUlTDj0zKShmnp3mYPf8xc/w1++3FRg+tJFxm34gJ2Mbp7ZxpdPmgIvu0cGcFLCIeelPFrqpK3vBvFv/eeMMbKvN2Ulq+XtVZKcOBUPvBZLIC8ZKYtdqccldwqCRvp7AQhztfySMzkDPYYBGLy7FNM9petKBPk8B3/W7Nf3tU6y46YzJy53GNh0kuGTRrY4nUo1m3DzEppCN2Aowi8/cCE9PVZwV6kJbCv1JkK+0qWm3i/gZufPT+zUPUPH0STl82IRRJ4/c+/tcipjDaG0oDXEOKmqVzbaICIvAo6r6u0i8swFT6u6cLm3edCywBeRazEa/RsWeWwzXIehg+4Vkbvsb+/ECPpP2QlmP/DKZThXG2200cayYpkCr64DXiIiL8S4uHeLyEdV9fWNdhaRLcCbMW7rsRxuJfNBq0L7N4B3ADeq6v224tW3Wjx2Xqjq/zK/wff6U22/HgvVl12Mdv54rBycjeuZXWU08MLBGYIOo2F37ymixRL5Rw0doqNj5H3j915aZT00rJ1WQij3Ruo+BFlBPUMDOOWQijUHSRUOPzUXa9/ZrhnGrVY9ck2W7AGfOD9aYvtkemsFQqG83uzrnfTIjhLTRpnJ1DLaITbumpPC+E0medtlj74FfMXpMJRDrlDGa9Fro54C8OzyoztbZMRTqKYiba02qSIJvWNRtXZ+t0xSxGQhLPTYJdlFNFntnIozh3R2oB1znRKkEkCpjK7qNedwhNEdZsxsGjiC+2gnPV3m/D/2ltu4bdSMmZ35CVN319It2VFBXY1XhqGXMs4qaMVBoxiNMjiWFpwdEMrdUO1KtHnXRtO6bkgQNDYRRnRO+jnu+rNLTd/e/fD8NyIqAZkuRuRF3GJr2UaXF7IsRltVfQdGvmI1/N+eT9hbfA7DjPwXrY9cYHGRtt8WkQ77/THg1xdzotOGKGOgXSLKIkrftCr0xZG4/SiAJuJYKZeXNBlIxicY6CQzbl6YalcGp2L6Xu3w8c5ZS/jIXrOv7+HtM9RImFtHtcPDK9lgFk2ES5gVqlnBLUcC0ImpGHWNu2F2zJzjnN4RfnjUVsqacin3hxQOJC9sYDndzHGfyppyPAEUjgjZMcWfiojd5JpK3Q5IUvC80gXlvlq+3cssrTRRRAtU6nKZ9K8fZ+RAr7lGTW6GxC6TqQnAdjn0zb2QVOJvTTerdbx9vXN13eOWRr+fosAPCwmVI3ZcyEwJ8rl4m4TK9Hqzz64DQwxdmuEtOz4DwN/vejYjw8bN9trL9zDS1UH2X0xQ2Mj5MLlJ6NltOpwdU7r+667U9YXx+J583oVMrTNjf3adoq7G1+b0lJP7a92VHDeqzav4XmpicMIa2m71LY1vkEjqQWQyqIaInxJbUQCb48xb0P1xxekzF6ZRVNV/WMqBrXrpXCsiD2BchhCRS0Xk/Us5YRtttNHGEwLWD385s2Wq6k3z+OCn8fci8i4rl6+I/lppv1VK5++A52OMqajq3SLy9BaPPX0QB1wHp7cPctaSND6ZhLMH1sDXKG4hnUt8vuatVu/0dMWJqKJMhaeqXTjr1hCIEPpmDpYgJMjZXOa+UO3J4UeJsDrycRbGzJ4ThDuHqBaisn5CkE0GmFdKPGzKXS79DxuNaHS7x7rvTFBcY6iCsV8dIvNyQwcEBXNMbtQ2kqJ0/OmQo+sg95jR+Hoeq+KWlHK3OX/oQbnLXEOkbUYoDQZIRLcoiDsPvdbADab+tyhLYdZNlvIhQme2xEikOYYpo62j5sWLFjtpbx6r0dcEUwk13igx6rvW4HvsKSVmJdF4x9YwH50Tny6bvMKzg36cyoCiy7FrQzb6Jsnd6EgHQ181z+zrn3ka2d88DL9qnN9mHl2NeopYHqfzAFSeYrLt+jffX9ufkDjJngQQZtQUgcG+fp45f7XszqHQ0khr92MnOzn3YZvxs1Awid/mux9OyhvccaDLdmZqxlA9862u0/V+lxMro+FfjLF9PpuE0lH7vSlaNryq6gGpfYKnoUzwIqEh4DB78YY4259UVpHfbUsQnRwxgnm+nrtucwrIpog9+WPb45c6KhB+qgj6OwiyLmF2ruAOMg6z2/IMTJhoGTkxmng1VANyjxwjGOoFYHxHZ9ymOjCzzok9U8pdsPoOcw3FQTh6XTfZUTNiJ87ppbTG0lMVIxgD68aXG1Ocitkv9IWNN7pkh2fi81S6fIp9c4W8CgQ5JVxjDQzjKQ8Th1hQAIvi7x3ROVROGl6POV91NJfM4VIn5EUTYVzrzEPo1bm3NhLqjV70+X7H3AtnoJ9weGTefqcRUSjS1xsHTIGlcyqpMSoSKwbTaxy02yoesy6/+awvc/es8ewKix6upf067j7M/q+cwwUvNlk2uy4o8djJAcozVqHYL5T6TJuReJW88eCa3ODi2UfvTwhBf4BjPXJcP5jjgRO5YqbpHM+1mV0t/z34bR/n5DF7o9QI8kao9+RxnUSIZ3ycXB9kzX0Ljx6vtaiGDpKxV+M40Dgz9RLwOHsCNcbLgK2qumgts9Up74CIPAVQEcmIyG9j6Z022mijjR9ZaIt/y4u7YWnlBFrV8N8E/D0mz81B4KvAry3lhI8bRMDzcAYHyN97kEOv2gIYH+HO1aZYV/9XJildtYPMd5rEicVpEVNLwCjdwTrTztRGiQNc+gBct+WapPOh2pFBPYlD4QNfCP1IwxecKommN1tErCajg32UhzqpdFr6x4NytzlucqsS9pRxczYvisIxz2hqYSYkyDhxrhenAk7eekFkBedkBlvxDqcidBw3Km9mIsCphgR5c77xrRmmNkC1y1JcWYW0D7YKzNg8/iGLUojS/vf1qKdyIjgoG1cZLmrP2JpEpbH0TjoPTDooS6nTziVlxE0j0uLTdE/0OcQssDXZN92e9ndDixo+kTbqezUaPoCkxppmPIqr7FhI31uF4+VuZsLIoAsdh0w8hvZ20ftoyETF0J6Rl5O3zqjuem8nh3/C0Co7v+yYFbGNA5hZB/ljyTXle4qUy+b5OqKUS4lIcepWbZFXjggEgcPkUbMa3XnfVO21Ow5ERX7qtXpHEtrGFnkB8x6MX9DD6E7zgDMT6ygcC2NPs84v3ZN49wTLRE4osafTacYQ8JCI3MoiC1K16qVzEhtVe6aiNJRn3xsvi1/ItJfF1DobXfn07XR+6Z54kNTD6ewgnLbr1QaGlj2vSao8RpV8JJNBVq8iPGhiIZbqrqmemGpCUe1QH8qdSb6aIAMl67KZP9EJBfN5ZksPoStx8rSJrUJ1p31xqw6OKKHlzVUF7bHL7xkHlDgHjlMGnbJCplBFB0vMihEI/owws8pGaY4LmUkYOc/sO/uUaSqzfq1zWOreZbpLlIfnT3uRjr5sxN03givhvIawdBt+X4mKPbcZD4rEIcPM9dhJB2lBQ3pmzm9pGmeB7lf7CrQSXiSZDGLtNZqxk2VE41SCOD2yumIiaG2/S31A2YyD1VtGKLhl7hozeY3yBz1QIxtmN3Yxscnh/57zdQA+cOTpqErsRjm7Gnp+YO7b0TdcRv6Fxxn7vqET3RJkJsyFTm+AYCJHptNI1TAUwoppw83Uul66Thg/G1MpSui/fR7xU62C7zfeFmriipn148mw0p+vmaDLPVDuceJxOb7lsvj5qAv8+Ycbt79IrFCV73ct9cCWBL6I7AT+CZPU7CIRuQR4iaq+Z6knbqONNto467ECAn+hglTN0Cql8y/A24B/tie8R0Q+Bpx5Al/mKudR6PfwBQ6hfwk9XzXBHTpbZOTVlwGWBkmtDNbfuJ/wxHCqXYnpgeJgQP6o0Sz2v/kSNv51OkXG0lDpcAn9xFBbKSSh7tWcSXuc3zdmfvB9Zrb1ATDb79Z45YQ+8Q1wXCWopNxPQnBmbRrlomNK8qV8z71x62nTVaa7Z5YZm+lwqtJBdsS0MXauEAxAp7XgVGZ8KDkNV0Td6yYoln2oNDAVuYpYA+xCSOfOqd8/Tee4UkshbBgYZc/omvj6jOU07ScetU9twFTUQJRqoJ4BqNfqU/SOwLxCoNybIT/vVaaQ8eMVnPpuot1Hp4yNzeZ/cSDqaLLPizbcx6Mzg9y/22j46x8MKfcaemf4PI/pS4vkbAIkT0JcJ6RSNeKg3AMzG8w5V28ZYewHq2vanhkyX/xJCFZr/EyqQVJxRtWs3iJvnPTKq1J1Ke7rpnfUPtPZElTrbnJUAjKXpcbdJ5eNnSfUc+IYhHKPT7lT4jiTiQsq+Cd9PFvitzq/o9Op4TQWQBGRLy7ksrnQPq0K/IKq3lLnpbMSoW3NYZflQc6k6QVqBqo/CTOrHcbfdD4A7gx0HzCDrtQrDNxf5sg1ZgDte+05rLpvHQD5b9xrRnAkT1Lr8rU3FxumSF4sQl8od6Z4+2ySg92tmKX09A4j5KfWeLFrXJihRsCUByt4qZdLRAlL1p101iF/zHrprA6ZXQ/5w9Zm0IkJosHkLnedkMEew60e2eAyPWRfsqqDVCVOrpU5mKHaFdaMe3fIFlTPlpmarKVzNKJwvKWpRg66uBzkeStIZjzjsdPILdN67KQdKIUk2tQNqLnH9Rx+U4+eyAu1hS7HnjmdHTGVM2efSjV2xVTfjWvNps8F0OUWOVnshKLNpzQVML3GHDe7RnnRBffxWNnQNHvGTQBWFAT396/8AL/6XRPoeW7fcW7VwRo7RXHIfHFKguuHsbdNtejVcF6eG8QeOSJQrphxWC57dO0R/GnrFVaqJkI94khSVb1iCsdzY2EPoLkMpQGb/6nHodIllHvNtnxfkUpHFR6Kcjc3vJ2njBZZyOXCU0XkC022C3BBswZaFfgnRWQb9raJyCuwhUvaaKONNn4k8fh44DTDS1vYp6mrZqsC/9eAG4DzROQQsIcz1Yhrfb/dol3uDgXkjxhtYXJnQGbExbF2be00NE+E0Z2Jn3jow8h55vYMFi8kd+eeWJPLH3LjB+19/z7z3E8xt06509A5caEJl9jDQEKQUCn2muso9SbHOYFlKqKas2mFTxQvG1CZNI2Kwsw6q/EKEApTO5Mgl6z1XxegXPHoyJgO9PbMMHKiy7avuKMe1U5Ljbimr04UULW6yKoek4ZSVQjLKR/ytDFdjKbeOMhq7v3p8E1fyoFr2m1C5aSxZb1J47lnt/XYiaOrUisFSz9EeVGimKv4DI20+waUzoKBWgtp+ZFnTiEhfmqMtYD6ta9saSDDlI19qHYoveuSchLj5RzepLn/02scptdaqu+cabJulT3FQcAYVIPQIZMxg2ibN8Jnn2kC6X/5/tfjVEDs+Fr9/IMcHDYrzd7OGTb3jHL3YbMS1oqDk0s0et8L4mdZrrhUA9MX9+EO3CJ4M9G1VWqtn9XEME3RpI+wHTXnyZr7VFxTiIP8qnmh0gmlfjMW8qL09kxTvNyOm7KH7LI5peaP61ok5LR66ZwKdx9hQYFvy279iqo+x+bScVT1zKw+bPn7MBtSHLK/hUL1YiOApOQSTjqxUPUnpeblnNiuBB1mEGZOevG2o9dk8C88l41/fmtyqiYUzlJSJUfCPqZxyglVIGoon6jfEiaCM6bno5iSbBXfT/hQEaVvi3EFHL5/FfRZ3jZbpTKZQWxkZL6rFEevhqEQhILvmHbyfgXHLvc1EJyKEPqRh4vpT2ipk7UDEzHfXg1cKDvxfVQh5tBhrtteGjmvGk8GnZlSDXdfVacp999wWy5IaB1IArEAbJC1JPI/HWhLtQB+lErZCvj42YS1fL7UTw4plLvceTl86eyY45kzL2xHw6zPzOpav59okj5W6ebgsT7W3GY6OrbdiXn5nBtyRcdevj+xHYDZio/rhGR9I9X7XaHfBiBOfX/QUJj2WvbsG+LJ5+4B4OBUD7feuy2mzSSQ2Ouqs3MWkSS4qhq4lE+aq+8ZhvzJAH+4SX7qNKcf8fmdBdRzKK417pzVrFDqsemgu42ti24zvjN+lZxXxbUPIQyFonUdzg4vY8TtynjpLBkLCnxVDUTkSfbz451BvI022mjj7METTeBb3GmNBZ8GYqGfqlB1xiDIG1eJyBsl7K3i2bBuzwsItlapFM1lV0ou4ltVzRa8dq0mW1kfEB43FE/upDFSNtPc09uWQu+EvtXqUwpbjWaM1WDmnLj2a1f3bO33XIn1HWaZf3JtJzprA7Rcu/yOzpGyKkZa2eq8Mdp+/54dYAtbnLP+JENbp3hkZBUA4yMdEDgMrhmb07WZyEOn0e2IHEtaWBE7ooS2f4HWamdpOqeZ1r9tw3F2P7o2CcSq89iRlF8+NdVwmcPVpo22NV46DfZNY0HDbWEe/b8SxMFWmk0FYkWrzJTxeZ191gdm+3AO5eLgueJqJbPajI3nbn6Y/53Ywc1HtgCQcQO6u4vkPaMdH6i6/NL9pmpp6BM7CAA4ky5jZTMQDx/sp3OPi9hl6dS2gMAG2RWzPvlshZlZ8w5Vix45S61KAG5FjbEW4rxU5oShoXPSGr5NfayeQ3lNVxxzUupxKNl032EGKj0huY5yfE1h6oanc/csGyLPr9MMEVmtqsfrfjtXVZvkljZoVeD3A8PUJudR4HET+CLyAkx0rwv8q6q+t5XjwgxIVQj7zeBds2aMnB3Iw9MdOI7GnjAaCmoDVcQBqoJYDtL3qwTrzEBc/RWX0Z0ZqteaikzeLQ/WROul6Z3F5tWP4JZqC0Q7dV5qocfCHHDUB7uf7wR0+GX2T/YC8OQt+/nh3WYZH7puzOMDhGE1bt9xFc8NOT5r8/JkQxxLE+W9Chm3ymWrTaDZRF+OE7MdlCpJ56PIzWgSEXsOdRW13jkCNtfd/LROwU/sT2XL/4YqOKKxoG/FrTOCOunKZCQeO3VzkoRG3KfdNCs2xXNmnDnUTXKClrtSg4jOaUbl1HP3ALND2Tm/Ve2EeGyql/xRYdrQ64TZAN1lnuc3b7uSUj9UVpn3YuvmYziiXNxr/DD2VgYYtimmGQxwyrVc9YERw+FL2dy4qBZD9rhLyegBlKYylKayaMUclznux9y5UwF3dp7nXq3WJkDz3DgRolRDAt9JaJweSSqYdUGYD3HmGU/Nxtmp4DR76UT4roj8vqp+CkBEfgtTmKqphw60Hmn786fWv8XB2g3eBzwXk8rhVhH5gqo+cDr70UYbbbTRFCsj8J8J3CAir8SkWXgQuKqVA1uNtG2UbH8cuE1VP99iJxeDq4BHbaEVROQTGJekBQW+Oor6il8w6sTYdJ7ugtEySmWPQr5M0S4zCSXxaqkKBEJQtJ4EXQFrbjSaxdQGwZtVJjab7/mui41vPjTMy7EUo22k3ac1+5rVYuqz6PzjzHOTtANZv8ps1We2Yiy6e8b7IWs1nZILIWgm0cYjLahScentnWWsaIN/Kg6ZLqPGRctkJ8q/IiHVwI29ZtKa1PR0NukwRsNPp1JYIBs1XqqtKK9OxXr9LEazj7B2wyhH9xuf8xqPHVGzLEr5zKdJnZozRQbbtEdOnVdOq6kW4qI50JTOqTl9xiPMJmkHZlcl27q2jrGj06z079x9JYUcDN5j7lv1EQcJTVszg671/LLjwlvNto3H+IuhOwHY+tVfQErWIyZ9n4Cwr8LsmKF0MmMuQc7URwajuXtT9riZDFJNaiG7pcQ7xptVvJlUGE+lkvjai6AaJIVPctkk1TlQLST5n0I/CaoM8iFeV5l8thI1UwMRRTMaH7dcWAkNX1WPiMiXMVWyQuAdqjq1wGFA65RODjgPw+EDvBy4H3iDiDxLVX9jcV1eEOuBA6nvB4Gr63cSkTcCbwTweswyUzsDVKE8aYNYBIpHDJEpIUwMuIQ2Z4y6mtAN9n2PXPNymQonX21y0nR9pRMJNa4qNbXWo2BfVi1GPp7Lu2RMC/sgZ3jPVigdVSHjJkIiCBOPlkCFNetGAThysM/YOmyiszBwqFh+3/FCjo13URw1L7Yz69BdMJ4SoQqHp7spWJos4wZkvCrFotnXdwIqltMNq04tNeVQk5+1WQCVSBLBGaowWTZvdprOWSw6MqU48EscMRWxACyHH8v/yGsnRc5H22bXQuGg1HrmRH1u8PJLs2Qr1g0z8s6ZF57T0Ngxs9qNBR5AZ7bM7SMbAei5PcPar5+kstpIY28KqnnzXDqOQW5EYK85rvRYhi1vHOFz0/Y9Gffxx60NLGMS4kVBec5wBm/GTu7WXOSPmf/qEt8o9TCiKL45icDPTIW4U6VEWXJqBoUR9pFbZq6WturcPcnYtt6kb3bOVF/JZhN/y6YKwXLS7ivD4X8NEwd1EbAB+DcR+Y6q/vZCx7Yq8LcDz1bVqj3hP2EyZj4XuHdJvW6ORndxzhNU1Rsw8QHk1m08y+zlbbTRxlmN0x94FeF9qvo5+3lMRK4F3tnKga0K/PVAB4bGwX5eZ102S/MftmQcBDamvm8ADrd0ZNmpnS3CxGdaeyt03JU3WQUxKX0jIyKemoIc9mtaMy71Qv/DAfmDZtXknBgnrK9wlU6rHP+0OANuvaE2bieEaj4JrmqEyKjY41di/3VHNDZ2RujKGk39qK9oVXAizc0N0cjP31FK4zlcmy45UIkNqJ4TcnKmI743M1XfGIet//fxyS4GOq0jlwKBJPc4nfLBCXH9IPb9T1NBGTegM5MMq7BOi1oKnRMhCi4rj+YSQ6RYg25E4djM2LFyLsRxBwDVguBHC+g6j505Hjx1cAYMpaSTqRV4IT/XYJumcqphsjJyvTnpFKIguDUdkzzy2R0AbPiEKW6SOZmkY44JpGwWshm0YLTnoDPLo+Or+HT1yabJqsRjTV2bSdVmcZUgCcJyquAWk8L11bzE29SDakdCVaoDOVtsx58KzM2NCo+nNHwtlpBCfo5mDxDmbHGTlKG22m2zv/aVcB2N/e5bzbx6ylgZSudzIvJUYIeqfhCTpf2jrRzbqsD/C+AuEbkJo30/HfhTG4j19cV3eUHcCuwQkS3AIeCngNc2O0A9KPdFS3QgsANUiaNuOZqh0gVde83X7n1V9v24vQW5wCT0shz+9HiO9WsN/TFV7KKac3COjwFQ3jaEl06slkZdqcRGQt8dGkz63W/8yiJhX0/lgHnBnDJNy9VUuhP6w4+4+MAlCCXmwgt+ORaWA4MTDB/rJrT3yfU0Zg2CkguiZPNmiVwS2NJtrnfvZD95v8JkydI9osxWPCpVc9+KMxmO2zS74hp7ikZBWq7GNImq4HpJ8jRViV3nXCfEc8JY0JeCVI71U3zDNg6YZ/ro2NpkjlZL7UVCQmwvo3xFfhg/GFEoDYb4k/YaqePsW+1exl+Yyongp9JmZ31KA5mGu93/1R1s/he74G4gMGOUSiaYySYv83I5dvSNsGdqwGx3EldMUxFUcCO2JEyoGalC5+EQz3rcTK3zYjdQdQ3lI1HkeCqo0B8voRkPcaIbrOiUVRJ8r4a3j4R83K+MR88ec5NPpKq4ZrMVMv78GlGaEQsyyyelV4LDF5F3AVcC5wIfxMzlHwWuW+jYVr10PiAi/4MxpgrwTlWNNO63LaXTC5yvKiL/B/gK5rX7N1W9f4HD2mijjTZOLx4fb8+F8DLgcuAOAFU9LCJdrRzYqpeOANdj6ii+W0TOEZGrVPWWpfZ4Iajq/wD/0/IBNqVCpN3H3gEzDt17zOehbx7lwEvXkB8xG09clsGzikUVD/UUb8IGh6jHWI/xnHB86Nw3TXWj0cwzx6cgCoMvlZpWu3IGV1HZavI8lHt8EJgdMOcIspJo9OlYfoz3QY1tcoFo8LBg4wfcgIqlcYLQwXWUjPVw8VPBKL25WSY7c1RshaKgWl8vNAl2cr2QO4+bNLuOKLMlP9bGewuzNcZXx0sKXTz33Ie4pPMAH91n7O1HDvTH1a+8/iKd+RLllP/+QME8DM8JyblVJqyhthK4+NYQvVz+1NneoqF1AFQMfRMbbU0Rd408mlRifieieSa3m/5075pb0qSZ1het6DhyIi7y0TSVgjf3wUf1gyMPndxx0/ENf3lrIn+idAStYGKK/77rMjZsNKs4dTRZ0QSAS5wi2qmk8jaFphpblIJYnWTMhr75nDULKjqPBHjTphFnsoTmfXTMMMTS34va/jo9XZDLJpq9M/f+FI4Y+jAoeHFaB3cxgVXLZGeV+eIxHn+UVVXFvmiWaWkJrVI678fMZc8G3g1MAv8JPHmRHX38kKZxQlvRCeg8AIO324RSYYhbgbFtZlvhuNJp1yknniT4Iw6bv2i41VJfFvdrRiCcuBTkvt245yQVusefZbjSjsNF3PEZOGTc4XS2iNPbA8DMkzabnevy7kT56+sN/JlJZXZVKnrSDqZqoTl/D9C/3rw8hsaxOe9tHnk/ZRxIe750FkqMWoGfzmsTOgKjGao26thxNE5tqyqUin7s6TSdzdHdNxMLfVWhXDLbjsx289UHnm/y5QPPvuwBLusyzlcf3nM1vblZDhfNvcpnK5yYMh4lQ12ThCoUq6Yd1wmX7JkzH/q7Zjhi3QtFMFG39hpCTyEXJsxcvatl6sFNnBfQ80CkJNQKgDmlEDFVrwD8yQ5DXzRCI/7eTfaNAgcB8idg6P23cqq44E9PcMVndwPw8fuG5roBp1xW0+O20iGEUQUuhzjHU+RBk7PMpzsb4lTMTSiv6SJ7ZIJwxlZms/8B6O8lLGTiaGIVictpVjvdmnNLRfBXJbY0N+XZ1RTLKaRXwEsH+JSI/DPQKyK/BPwCpmbJgmhV4F+tqleIyJ0AqjoqIo2JxDbaaKONHxWsjNH2r0TkucAEhsf/A1X9WivHtirwKzb6NVpCDLJS7FUTxDTOrEOH1dx7d1coDhpqZuqybgLf+ggDU+uFgfttdsxRl9V3VpnaaDSw/PESo+daSqcK4jiEe4x2KuduoesxkzC02p0lWNOFHy07Q6jmraUqRRNEmO2vowDs9nKnSZHspp1/WrzDYQYK1kumGrixluO5Ab4T1AQwpQ2hlaqLn7VFKFLpgjV0cMuCHjMacKW7SjBu7kvQVUUqDrnDVqsNPaZWZfA2RJ45EhuCHzo6BNMuYlMnf+u2Cxm52Kw+X7rxXo6WuxmeSVajWUs9beoc5b7htfHvGa9acw01175EDasjU0qKts94pt82X5C4Cm6YpMwIUx47dYZZUZiyHsFde2VBw22krfq+3xqVI2Jq10YpgYeShEpOeXm0e4Dw0FG+dNBE5oeFkKCcrFrUIZYUqiSlj+y2aMUa+gn1I6Hx0CmcsBk6j0wTdBuKTl0x197As624oQd1IMzaAK4mj3fDN0KGf86+v00MtmCpwCgeJX9mGW1FJAd8B8hi7vRnVPVdzY6xAr4lIZ9GqwL/H4AbgdUi8ifAK4DfW+zJTgfcWYfehxV/xrqATVbi3ByrjkxTGipw4nKzOOk+oIxts8W5R2B0hxdXcpodzMfuZrOrhfEfv4jeu+36tFShPNgTnzNzeLImwCa0Al9CRVN0TtGWI0zz9uXOVOeFGne4VlHu0STXeKpYtCNak0QqnYSsXPUIVXDdJNI2n7OzjUK5yyG7ypCzpYks/rh9qXMOUk4mpiAH/rjQd4uZECa2OHHO/UrBMXREdL0dAXfvNt62znal2y/GVFFfxyzd1mV0vJwn51WYLpvn5KBkLC1VVWfJQr4eQ6sM1XfkQD+SD+IoYNc3dI7GQXkSu2yaSTjhOFSh2m8f2t66EM5mwqARnVMXVdsIswMJp7/+b5dH2Ivr4mzeENc8yA7OUC6bibhw2GF2bYhUIrpUkqhw1wj5yGsnyBErKd6UpXSOm2cqqjhlc33l3izerr2pDjiIDUKbXe3jljSeYZ2A1Gw7F4vi7qPTLaequjxzRwkT5zQlIj7wvyLyJVX9QXonEZlsdkZV7V7oRK166fyHiNyOMdwK8BOq+mArx7bRRhttPCGhyzN5qAn5jgIzfPs3R7CraheAiLwbOAp8BCOPXwecupeOiPSnvh4HPp7epqojc49aGUhotPvO/bDq1hEIbABGGBLuPRjvl31EqF53OWD8gss2CMupwNAPK/hTRl3Z8xN5MmOJEXhmtYNcZPyUe+49iTduVFxn1360XI6fTnDlebEmIza0PNpWzdr8DSkaJ0JUi3Nqhzl/772JtriQwVYl8V5JpySI0t2mDbWRQVe1VnFynJAgSBXDrjiUpjLxd9c6fTgzDuop05uiQjEumQno3mUond77k87Obuxi348Ta4fZPRmKQ+a4zR3DZJ0qYbgJgNWFKYrW374YeFTVwbOrj5AklqAaJBruqaA/O8szBh8FILexwod2XR1ffxiK+Zz22klp+3NSJVuMXVmm/4eZplpfqcdcY/ZYc10ronvqC5gDDP2XcTtbeD0wP8SRmFJxBs24jvJPPeOc3Xx1ytA71bEMoa+45cRrx0kFV2mV+D75U8R++G7ZBEY5M6bNMOdRLZgxXelwyBcKqA1e1FIJ3XFO3LcgAxIZ0A2JHG+LDL8ATlWZfdga/S8+afrXhGOJ8gMtK1rX8FeJyG2p7zfYTAEAUcLI2zFZDd6nqj9s0tbzVTWdauafROSHmHipplhIw7+dhIk+Bxi1n3uB/cCWhU5wupAdCdj28TF48FFraLCCLbWP+B7S30txvRmElW4PtYJk26eLqOvw6GuiVKxK1SZdy4wBAvmTZoBO7+gnO2IHa6W2XpoKyXK0HBDkXIp90RoYyl0JL1nuhfLq1PEppmL83ICOfTZRWBOBH2QhWF0bXZv2yonSCUeI8tzMlDM17pTmc7JfTYK2GTfuW2ZCKPcpjvWCwoGB+yqx22jQkcF9eD8AuYf3sG36Ao5eZXjnwbvKcQDR57ou5anbd7NpwOgM5cBNqBoxlFPkiumglMNFcFxN0J81NNVzBh5gY8ZQdOf5w/zaVQ/wil0/AcC+kb4aIR+GgkYTZWhtHbGbZuqhKYxcW6L/e0nQU1r+VHNCZmoelTAt2D0nFvRp/h5g8DvHCI6fXPyFpxAJe+mIKtH7TO/sZ+ufm0n7qo89xr5NRhM62NNL6XBn/Hzdkg0CBEr9kE+l9Q49yNhaeKEPHYeh2peLr2PkXHNf+h8soeUy4fmbTX/ufZRKj9nPLYY1tGcNeae1HkqhLwzeYXn5ixeOwO7cZy5i8O5SlEbolLEIDv+kql4530ZVDYDLRKQXuFFELlLV++bZPRCR1wGfwLymr6HF+b/plKeqW1R1KyYA6sWqukpVB4AX8Tjmwm+jjTba+FGEqo4BNwEvaLLba4FXAcfs3ytZIBNBhFaNtk9W1TelOvUlEfnjFo89PSiW4MFHk+/W8p9OQathyOjTN5LrNXRZdbQT32qqj/1knm2fmaXrUaNJVurMH9kxNct5oLB7DH3MaLE4UlOwodrh4ZZsENTIDLPn91GxK4VyF5T65tfq0zBBP61ptRvWDddoNxH9EcbLYvO/EriU6wOsGp7c1KiNDJVOpVaLlbLglsxv53xlBv/gKNV1RiP0Hj1EOJ1U3fK+/wAbhzebQz2HoMM8j80f9ii+y4/7ViUxxkY1ayOayk2lWTgV9Gdnec6AybB9RX4fg7aa/aBr+vSZHZ8D4KMTm/ns0cvZHxX6SKXHCENBVZKC5yleLNL2izYgqnCsifpXCcBvfdXiTpp7Guw9sMCejVFTpCebRfI5gs1rAAizHkHGYWqLoYH/+8QlvHTN3QDc1XEOu7pWceA2E3g3eEeFqQ02PqJCTUZMp2rGOJgYl0pBGN9qtPpStzC1xTzPvkeE6WdfwNRac/35TZdS7jKNdB2oUMx4NX7/qUJktViEwbTvzwo4P7h1zr04ZSyPl84gUFHVMRHJA88B/nzeU6ruxaSLXzRaFfgnReT3MPkaFHg9pgLWGQPFLLfrH6amkpxJocD0Gom54YEfKmPbzf5Bxgjutd81a9Jyf5bDTzOCoGMYcqMBxQEz0DO3HUmCqSJhb7/njs8ytdmQ824px8Qmh6kd1v3PJiprpawfEPPkXbvnFwyV7tpgk4i3N10z3Hepah7zTCUTlwiM5FREBYkkE0OavzYNSfy95zGl754x5IQNoezuhOlpnNuPmV0hcbOztJpYYSWOUFxn7k3hoRMc/tvt5H71EFC7HC8HLlKXBvlUBf6O7hNc3rmfK/L7ABh0SrGgr8fru/fymq49vObRnwBg72g/oX1oRvhL7H1lbCGR8DffixeZ6y0cS1woq1mxrooR4Z16pg1y3qe5e3dylvDhPUu67npBDyA93eB5OEVbY6A7S/5YEW/cGGoe+eJ27r7EBBnuWHec83uPsbdgSmeVe13csvVmKhtX4ohydKqKU02CCsMMTA4ldrAoid6RazOEGfAt/VPucWJaqJrLkB3X2EstzdnPvbjk4/D9qxi86MScXcr/baLjI2EPLKkiXUMsk9EWWAt8yPL4DvApVf3ifDvbCeKXgM2kZLiq/sJCJ2pV4L8GeBfGNVMxPqOvafHYNtpoo40nJpZh7lDVezC5cVrF54HvYhJXLsp236pb5gjwlsU0vFKon73TGo6Wy2QmYXS/WXdWLnXiXB9d++HotR141hsl9JIgkjADxT6X7seM5qbV+a2ozoFjTD3F8EFX//Q93HliPRmrVUda6lDn5LzH92bm5kB5YPe5c36LUsRGQSRpQ201lVohrRm7Tsh0KSkMo5r4Mddo0HVFvbPDwpofGvrD/+69ZoxbbZH+7tqqX+lCMNHnaJUlQu7r95jzAd2+x8EvGr/8dS/ZV+NN5Lu1hucI6X1awY5uo/VF2n1E4wy5OcJ5ItsCu/z5+PbPxb+9+tGXAbB/tI9QJD5/vQE3rfGPPneW/q/MU8mqEWywlVSCJB1xsUq4a+nafUxpeh7Sbd3CMhkQoWoDoTIjs8jew0i3Gbcb339vnLK49OQd/Per1pNdY9IfTA91svY7Y+b6Lu7BCRIKy58S7NBj8hyha18qi2tvJU5H7c26yDTMrLMBgpunKJ0wcRwSusZDx77G/kyi5TczkK6+XdGLan8b+cEQm/55eWIVGiH1ipxuFFT1d5dy4EJumX+oqn94qvusJGomgHIFt6js/JARuOPnduFPm5e+4zuPoLNFSs+8GIDJjT7rv22EQ/b+/YRR+lZg9jkXk/9647ov4eQU6z5lbQk/DZt7RuNtS83jPrktmJfW6d48BkDONZNQOXRrvXICN04vXKp6MZVTX20qPTls+7sq3FHrIDCHKivZfPXpAJp5oBPmfktXZ2JbyWYZu2wgLjc39oFzmLF5hIqrYcNVBxu2tRhqZ0f3Ca60ubCvyO3jfN/FFG9bPD65/UYA7qt4/PG+F8eT6sHR3iRCmVoPHoCTl5vPffdJHOE9Hxq5Yi5W2NdQOJlMXDpQujuTSdpO0P4jhk7TahXKFcLjZnLUckILZr5zD5u9SznyFDNZqMCB5/cC0HlYGbh7mpn1ZlJzyyHFPjNOqx1C4XjA2PmRS5qDM2O9ziowsTOIyyFmvIBqj1EKZi8QZkcy9D5otlU6JLYhuWWN6aSG1173fm16z+Mn7GOsjMD/ooi80CaYXBQW0vB/UUQmmmwXTK76P1zsidtoo402zmroimn4bwHeaYtPVTByWJcj0vZfWDiCq6UsbWcK+j99NwRGy+y5n1jjjHz3848Zv3B/vBPv+DgA1W3r8HYfJrRVigp7xmG7CRhi76E5FM+xl2wHIJzehych3ZmoHuzSAj+uvuzRubROZETNF+nySzV+6rHxNZx7vshgrGqyYAa39AKw4S8eP20oDrAZTuL0Hvqr83EnhA3fNNpk7ht30xtpo67L2IsvIv8Lh+L90+khmqE3W+TibnPcVR27ucA3vgVDbq1m34jOCZqE8Ee4yK/yye03cp9N6/zx7mt5ZNIYBg9YbT/R+CGz3q4M72vwGqWNtXUeO7Jrf9zGQpij1YOhcFwXIl97z0uot1IZyuUkrbcdv2nNPoKGSu6bd7OhZFa+x56cZXaduXer7gvxhqfofswkrtJSmbyNS8k+92JUEt/32dUOA/eaq5k8BwZvdSh3Wi+yo7349vaoA9UOZWKr2bdwVFJCKtH0G2HqK0N0Pt84D3S9aH/Te7ZsWAGBH0XcLgVNBb6q/tFSG14IIvKXwIuBMrAb+Hnrg4qIvAN4A8Yg8euq+pVlOacjSVm1eRDut14j+4EB45aHwvALttP36bvM90CRafsid3Wio2Px8c66NUzZ4owz39pEaXvRJOOyyOUTr6FVXdPzUhTrO2oXVsWrp8n90IQxVvMwu920k3WrNfllnFSkbYBJkhZ56aSjVCuPdrH1/6YD/5ojosbmc2lr5PnQzP1t041KZnwG53aboSMSUACOQ+8X7uVE/hLT75eO0F+YmaelBJGw//Fu41I46JTmCPrlwkU2WdefrPkuGO9Gfv/YdTw0MRQ/i0NjPbHwn3n+JIWvNXlPVWMqR44NExQXrhxaf3+lUEjuYTZjuPpoHyvkwQp2kRrbS9jkfBoq/vcMhXnO7tXMnm8S2+WOTMHUNOF6M+FJuQp7DBVXODiNM1WkcMRw8wef1Uk1b8doGSY3Cf7lY6b9/+2NPXYQE2UbvRYz6xTXFk3PnzSRzlWbrC07WTtpdx4J6f1Vc02nEoW8GCxz1u7m5xI5T1UfEpErGm1X1TsWaqNVL53HA18D3mGrW/058A7gd0XkAgxNdCGwDvi6iOy0kWhttNFGG2cOTq+G/1bgjcBfz9OTZy/UwIoJfFX9aurrDzAZOMEEFHxCVUvAHhF5FFNa8funfM46P31n43rCA4fm3b90buR77FHNpbQpz6nlRlIIu/NUu820f+mTHuPOR8/BsdpgWHWYnc7GxqUTTQyQw5NJ2uCBrmmG+iY42WV+kypkO41G5ohSTRVcB+KKV5W6dATVH/Sx6ZNm+R3sf2Tecy8XmnlM5b55d+02102KWQcB0tPN6m+Zvhb3r2LPS3oBcFcV6emapS+faPzbugxtsyE3ys/03op1cGGV07p23wqdsxD+eOh7MAQfn9wCwH3dG2K65+BYL8Xnj5P/D6vl19E56rvIIyZGIFigWtW8hlnXTWrZ+j6k036Uy6jV4rVaNcct4prjwLOjx3G2mQpuMjGDlko4h4yxN5ycSt6LBx8jBBybRjt83sVUjbLP7BrFLQnu13oBGLuiQuaIsd47FUgzn950cq2TmxV/QigY1oZKQWJPOq9kV7X753+flx3KaRX4qvpG+/9ZS21jJTX8NH4B+KT9vB4zAUQ4aH+bAxF5I2bGI0ehpROlhX548EijHWzjDplbHwYgu34NHamBJIdPQJd1cbMvT/wyZbw4Wc7+iV5WD40zMmH65lhqJz6FKMUZw7lmctV5Ez9Fwr9yrnELzTyQZ7PNQRMJ+0a8fajC6PeG2PJhE50ZHHrscVvqRve0WVBLelu0f8w5O06cl8jpKIDroHl7b47PsOm/zT04ek2BkdVZxnrMPX3dRbdyZYfxZLk0c2xBCmc+V8zlxGu6rGdN1x7uGzCv2L3Fjdw3vYG7qg3crVVx9h6ZV9DPoW7qefoIXZ2JkK9UjJCPeHmReEIV122ZzmmE7OFxe2CAFAqGPgKYnJqz7+RnzIRXvUvjBIHqKWFWmYry4sw6VDtsLqiS1NAkkmJg/UkTADizJt4a5/Xp2r8yBtQVMtouGS1ZEUVkp4h8Q0Tus98vsZG3Cx33dRG5r8HfS1P7/F9MSYX/iH5q0FTD26qqN6jqlap6pS+PD1fbRhtttDEvtMW/MwStavj/ArwN+GcwkWEi8jHgPc0OUtXnNNsuIj+LScR2vc0JDUaj35jabQNwuMV+njokmQMjLwaN0itHK4OZGbB1OJ2+XqNxWY3pxKWdrLvQrBwOHu4n21mmr8vsGyKMTRRija1UzMQGXaeuolPYwMPGz5j+lM6fnVPUJK3ZH/meWRBt/eABug7duqxafaP0FdHvS4HY+r/hSBKvQD6HdhWSilCOQ2bMqHJDtwnVvMORl5g+vKzndgZdo8UuhsJJYznonPkQGXcv8vcYjf/vDDP57he+JvbMkROjBOO1RvqWtfpsZo5WD4nHTeQhlR6jERar2YN5zmHBFqaZLZp3Imi8ahr9zHqGR8zKTDcUCWwB+0x3mcpYNk7zIaEQ2oLx6ghSTXI1pWMX6p+SVKFqmc/x7YJTgZ5FX9Gp4WzT8FsV+AVVvUVqk8AskKW9OUTkBcDvAs9Q1bQLxheAj4nI32CMtjuAW07lXPMiHRUqDVwY8za1azSwLZzenoRvzpqoRbEE5dQGmPmu8WLw81DJZzjRZ3lVUUQ0TrUL4PjmJSzOZGrXNgq5QrreYTIJRGUJIUl/vPths87d/okSm2zekDPZyh1zwjbYB3GS+x0Je3uPQ98lzBoh509VkcDl+nMN3WaCqVpLQnY66JyFEE0AY38Tsqnb2B5uu3knOz7Shz60e87+EUdfI+QjOFLD02sqOFArFeP5E00Up0DhzOlT2v4ggp4cjvs69uMmj/7R51Z4zqoHuVuNHeycnjF+asikeP/cySv4oW6i6tm+zTqxNA87AqTioDbnkFMRnPI8nmEp6RX6xEF8pw3KihV6FZE+jGyMtRxV/c5Cxy0medo2Ind1kVcADQjwReEfMTUcv2Ynkh+o6ptU9X4R+RTwAGZS+bW2h04bbbRxpkFozD8/7ucV+UVM8NUG4C7gGoxTy7J56fwacANwnogcAvZgMmYuGaq6vcm2PwH+5FTab3ruBsZDXKdmaeqsGWTkaSYlbGYypPDVe5Lje7uRWaslBYE5zjfqRbU7JOyy/tTTLk5R8I4YTSbMh4RZRX2bXsAPCcfqMjYWzLFevkK5bB5PZdLs4+bnLqoOfG8j2z58lJ17F3TBXTbMR+sstS0A8QXWrgYg7MiirkOYsVqtQLE/Ud+qBYfXrjplp63HlcpZCB+58EOcCIxytvmnvkDx1cqkTRn58bGr+fZR83qcuHs1Wz89hbvHsppzssHWFeBJUziwrJo92PclWumHCq7ARqPFc+wE3s8dBeCX1j5AnzfNFV3G88glZLMNgttaOMkPdDNiV7ehgpQtvVMymVrDDlsApuLERU/iNN32sTmVJOfOikjeVF9OM94CPBmjJD9LRM4DWoqZajV52mPAc0SkA3BUdf7sX2cZYoGjivge2GLKBCH9N5tFzIO/uYaOnZdzzod2mW2plywY7CXMuYxvMxGNUk15u2VDAkdwKpbCUcEbc4goiKAQ2rz3CZxx80jCcY+gkGwTPySsJMt6eZ7xTdvMsRWhbhYKxGoF7uAAwQmbZTtUgj5Di6krVDo9qvmo5KLEQTsqcOwZVa7Nlhs12TJWUthHqFhO4kTgMugGFGzCuNf0/pCX9JgJvLjTZ+wnCwTWv+JYJWGp3/fgM9C7uumwa+2uAxVy+40Hje7eO+d8iwmaawYpRzUOFTIZNOL0PY/ZTxk6c8Pb/pcuZ5Ze17C1e8uDPFY2HjtbsidwHI3ZEHEVzVglyL4r0QSgmRC1r6SWHaSS5NYJ/ZV/hivE4RdVtSgiiEjWBmPNzbDYAAslT3vrPL8DoKp/s+iuttFGG208UbAyAv+gLYX4OQwlPkqLji0LafhRLPi5mCXEF+z3F2Ny4j9hoJUqTncX1W1meTqxJc8r32kyOlwdPMKH772ag8EOADZ8Zn+8rK12ZSj1eUyvjbQnRaIiEA6Ip4SRB04IaU9Yd8aBmeR7UAhJx2LVhG2nCzBXV2r9OhenQu/E2j0gHXkqXUaVKw54lLuS8PpyF1Rt2EO5N+Rnnrx4OudMMNgCVFL9mFZLu4QAswxaDX/IDThml20dMje/TYRfO//bPLxpLXcMG+qxpMLxGUMTOd+7klX3Vch+Z56yqKEmmUtbiKGoQSnx7desx/hO83DCC7uYthEzk0GOXneGo9VeAIrqxwGB/d4UF6w9yr3710WdQYM6o7Rd+aYLj2smRDNG0weQVCW2GnrndEFPb2qF+LSqL7Mf/1BEvoVxTvpyK8e2lEtHRL4KXBFROSLyh8Cnl9rhMxa93XiHjBDqZoB/vOm5APze9Z/n2q17uL/beMI8snYjG75ho2czQrkrqRClQiKQM2qEfopoDLNhyrKfEuIKEghOKRnEp5OqSZfxm5MKuYkgSB/X6Hsr5wWQfJ6DzzQCX10lKAQQLdlztXfiDX0/YKlpjleKyglRgpREOlztpBi5lTjEQh9g0A0YssJ/UgFmGA4N3TXgTjEWmM9D/jgU4NyC4XQenkmEf/nZZQ5c2UHvRhPotfq/HiWcSDGxjlDj3RQq4syVXo2eZZwEzzGF0DM2p83h6zy2XG2SlnW5RYarnXTY+gNdzmxMYU0GeTwnxPHMcUHZRWw1LCU0tE458oIL0cCOkRTNY/4nvwW+1kwApw0rxCqJyFOBHar6QVsBaz3GttoUrRptz8EkOYtQxpTXaqONNtr4kcWKRPeKvAu4EsO8fBDwMeVnr1vo2FYF/keAW0TkRsyc9jLgw0vq7ZmM2SLaYbSnR1+dA6uB+BJwZbdJdQww0j3GvYO2qPO3POqzHkuQeDHUbHPUVP2xv9Vq++BUHMJcVKEk1U4DODtMvhYZmyBMpR0+FcTadqGAZHzo7zX93HcwSaVbh4jSWbThzxEkn0c6beSM78MW40eezVQpFTMNU710dCwuA2aaylkJ7T4kylxae+6Yzkl/D6PPVTbb0mtdAjgBYIyfw2EhNoSOBQWG/PHYkBtp+hHu8DZw9Hrzeez6dfR8y4zt1TcPo7vr0gc30PiBWOuPnq953pZS6e2mOtCJWzL7eDsmefbqh+MmtmWOs8Y16RbuLw8RYKiginq8fPXtPDoyAMBkNU8UdyleSssHKDtIpNHbdiOtnnxg/sCuApaWfvyUsDIa/sswJRHvAFDVwyLSUsrkVr10/kREvgQ8zf7086p651J6utJoRlcEh4+hV5rAka03lvmx990Ub+v3prisy+SkOZbrxttmBuHBm7ZR7p5HMFcF8RKhLyFG6EfktFIzRkO/zmOnUkv5NIL2diO9jeseyJiJ3tQGOU6AOOkWgGSTJFxkM2ghm7jfiTTleZfE47suks2gA0ZYqefg2gk2n63QkfLCCdShaF1Ur1v/2OLOE7dx+t7M+YR8GnvLg3Q5s/H3nFOJJ4EOYG/VTGrr3Fm6RPCjSuHMMG3dViLB79qZYizomCP0R7qTHFM/eNZmAIav7CF35HI2fs0c7z9mPL40RfloTE47c1KKS5Q7x/cZPTdP34Omnd6OWQa9pI29lVUULY3T684wHWZr2nn5ZpNA79/vuSbOI2XFfuK6nKJ3BCATJne14sT2MskH9N3bWgDecmKFvHTKqqpib5r1nmwJLQl8ETkHOIkpYh7/pqqnqcpAG2200cYZhpXLk/MpEflnoFdEfgmTfLKlQlStUjr/TXJpeWAL8DAmZ/0Zj2bap9tjtONgfAJxBPfgSQAefPfaGm0FoMdqVF1uopndefUWuh9qrFlIIKinsSVfnTqrvlA7YOpWpFF+kWipn9b4Z7b3AuCPm2WyNz43qEZX9yOqMGgKuWhdVaXQd2Njc7k3kxTOViBIOuauOp/sw8brKzw5bNJQuGmvoUQDlEwGohxEQTAv3SOZDFoqxwUzKlftpDRu2qyWPVwvwHXNhWczVTI2SOeNg9+m1VQKK4F64+y8+6kwGdYWOM855llOa4ZIZTsc5FnnzpKxq611XshYaOieE4Hxfok0fYBe19Bihyt9nFs4wsMza+NtT9m8x/ZRuG/NGnatNWPfndrMls+XcGdNNXJ3dAYJLY1ycgQNQiIXAnGEvW803mrPe9ktHP2XNYyda1YRpXI5ppfW+mMADAeGaVjjjSXXaT2Pzs+bDLRP3rKfW3ZvireLp2jk6ean6B2opXjs+wVAxWHof0dOqy+WcPq9dMT4xH8SOA+YwPD4f6CqX2vl+FYpnYvrTnoF8MuL6+rphfiNL00yGcTy9IigdUmriraaz/MueiAevKu8SVwJcVOSe3vOLIOfdtlD3L6/ybxXFfCi4C4r9NNOJ3X5cxoizfkDTsmh3GWEXvSfDY157UohOUHa5TNotHtkenDMOSMWYfWt06Z6EiDbNpso41kz6enMrBUI9hxhiGO5//LOdXgTRbh319x+XbqVyc05vBlLf+SEnjtNB2ZX+5SHqrjdhtYJUpW6zvdbF/Yh4WmhclqhcOpRUQ/HiqfxoDa1dz29Ewn9CL1WgemSIpNajCN204If5lI8I9a3ddf0ai4ZPEJ1lRnDDw4PsfeX83DIbO841EX+hLmW3PAqct++L3YZk3ye570sSW1Vfv44o4fNcdcOHo2Vouhdqah5Xieq3fGEFl13JPhf//+3d+5RllT1vf/8qs6j393TMz0zMDMMrxneqIBEBRUNEjUKPkjEZVzmJVlqjObGa3zkGr3GmxhNspJlzA2JxmhQYuIjxqsSMCAiIiIwwAgjAww4zPvRPd19+ryqfvePvatOnXPqvLpP9+mZrs9avfqceu6zq+q3f/Xdv/3b6+4i5ZgT3PXY6ShGywfQco28AxWJJxO57zzBf6Q+F9Gis8QevpVyvq6qF2MmkeqIefVy2Km0njuffRMSEhJOFES1rb+mxxDZJCK3icgjIrJdRN7V4rR3i8i87G+7Gn50xK0DXAQcnM8JFwuRaq9eTo1kWI54haVV/ZQHzPfJM9PYvjFO+eIu/CNHSU0br+OWH14Izzf5c7JDJYadfOi1uOIT9MS+ZNWj/KSZsqUR3UatE+1EbgA/OtIqul/jQ6amhfxY9TInZnxOrBcfnDYms2DVBFxiBjyBkXv89DgAbr6MWyiGuYMk46FBPiHAmVhNaZOJvigPpUg/tJfyC84HIP3wLvKXnGHOlXY4eLGSmrFx1KfOkfmZTU+h0LcnhXfYXM/ieLny6t4Bi+ndz8erj1JSl/ASSLyXDxV5Z49n6mbMKTBm7x8HWOekGBYr8fhFDnpGDBpzc4y5uTBmf9IbhJTpvN9i9aLHZk3uogvW7KW82mHyZHOOHSevY2a/uXn6DqXZ/OMB/Gkjb8pAP2Bko/uPbOTVpz3M8Jnm/FPl/sp8yjWha3nSoTTZ55RCLz/gugmTSXNNZoZvP3EuxZy9v1I0lXfCKsw011bq3vgbj2drn+5p+GXgD1T1Phtt8xMRuUVVf9pg+5cAvyMiT2EuhmCc/wtbnahdDT8a8lPGaPpfaXPfpSGTMUa+5pW/tKo/NKTlfpfcOjOKE6A0DJ4NOChvXos7M4vfZ/bPHna4/SmTwCp1mseW/gPh6ypUXlkB8muVvgNBREtM2YKBWCk1N0h0m8D4+zU71ur7EbJHwasOeKh8X8DYk2jEgXiQtsE9fsYJnnHCmZOCiJ6UqS/HRgqVN6xGreQw8PhRGBpkdoMp3KoDa5ibSIflzWyYge3m1hoZm2XuWUbCKeQz+AezYVrcvr0p8qe1nzuntAjJVSOxIfM28lE8BKzckYZYow8VeSfQ9A96KYKLMSA+PmXSVt/f7DpMOMYwH/QdDnqDocwz5ubCPoMBp0jOz4SGP+CoTfE9ns0xucFsu/2JDaj6lXTWh4/w9fvNYK7+sTzuhB8+F6NujoydospHcKJ1po4x+kDeM/0OtUYf4MrR7XA6fPsJEy1XnM1UBmVF5B2gXttvIOMGOKvH7QeBp5pu2jbdiNJR1b3Y7MOqOi0ij2AGUjUy+K+Y77naNfg/VdWqkbUi8iuciKNtExISEtqkg07bNSJyb+T7Dap6Q93xRE7FxNj/qNGBVPUpu+1aOhxy3q7Bfz/1xj1uWe8QgbQbevTl/oqnn1tnfqYKlIYkcKxQB7KT5nNhPMMA4BSMd+jOQX7GuP+PTK5jyC2AfRsYdXPhK6srPi+97EHu+tqz4ovlE3q8UWnHrIxsGAzKqtq55mDteBO1bxCtto35LGr+3EJQXkXTdlh7yTdevY3iIJ1GMhn89SbCQzyf9LT1xoslvJPGmXvjJACzb0gzvdfuN1Am88gwfXbM2PT9ayisC3K0gLOqGM6Q5GcdnrjqM7Z0aUparvK4A7qZL6fbHn3AlF95+/DCfBxG3vFtl9qUNxB6+yenj5ptogqJPUSflBh2iqHEU6LMkO3t3OzChDPNEXtP7fOGwrh/J+Xj47ApYyp/X2mUI94gq1LGU1+VypGz8wmvPW+aPbOROHzX5aTvmgfoyLnDfDNzHs9db8anXDC0O4y175MSiF/n5YN5Zia9ygCyWk8/8PLBePrFWRswEInegXqJx5lYXVk3WP+2VBWl1iUPv4Nb45CqXtJsAxEZwign71bVY022uxr4C8wEUQeAzcAjtBE12Spb5iuAVwIbRORvIqtGWOCMV5FzvAf4BDChqofssvcDv4W5tX9PVW9udRxNOZTG+0NDHxh5qGjTpSEBAc+Kp1KuaN/FYYfB6EAkBeeo2XDP8Cj3OxthlV2ZqYRoeurwgpGd3EW8wa8iErFjCkZrox9lvnJN3E0Zsyx4PRUlnBw6+K5BhlRX0JSDBOsdQbIZ/D5Td06usmNu6wS7r0xx7ugBAEYyee7+2TkAvOrSbXzDuZDUrE32VYDsfptLR6C0WsLf27eheuBYWirXqaRl5rRakHU6rKjaxqObBr72HI+WjFGaKg8wEFSyU8bTFOkgfEtTONZ13FNaVSUlRiN47IEJsp6kRQkeyyFJMSApbHcV4840eduncdDPkvMzYYPjpH3Wp6dCY32kPIgVPyiry56qqaWUsW8/CkBmZivO94eY+4i5bttnNjCWtvJOao41qWkcqZfXPHVCow+mcaiN4LlydLvZ+HTYdsRkZNv1zESs0Qcj71QZeWvcS6uqQ1/NxvWL5oV2b+CViKQxxv5GVf1qi80/ipn05FZVfY6IvAR4YzvnaeXh7wHuBa4GfhJZPg38fjsnaIaIbAJeBjwdWXYucB2mtToZuFVEtiazXiUkJCw7umDwbWz9Z4BH2kw5X1LVwyLiiIijqreJyMfbOVerbJnbgG0icqOqdsWjr+GvgPcC/xFZdg1wk6oWgCdFZCdwKWYKr4b4aSG3PkO5z3qikVa8NBTJQBlxjsSvaHDFIQfdsDZcl56B/v1mv9lVWX7OKobS1iMbokreARi83AQt5XesqStbJXw/pie2Vt5pFMED7c+f2UCqaYZTpsrzcYtapU/6wRyjKceGRFXSLuC6Fc9ehOJq42lNb0pz5sVPUfSNtzVTyuINmYPOeRk2rT/C03ZSDGcyFZ4ve0QQP0V5wBR++6tvbFjutKRw7XzEM36BEaefo36QcqC5K7cYnjzUvzFEeaJQucdyvrmJBoC0Uw5j1hGPSj4OI/EEmSbHmK2K4JnVDHmbamHCnWXSnnpWyvSJMipm3YCkCIZkjDs+JXLkrA+Vs/fZrD2Hl3HCsl3Uv4uHs1eYeZ0B6cuGnweenOLIReMcKVjPOksYT19Sl5yXYW3GKBODTqFO3gkCH/KaJu9V0kVEJZ4rR7ezyr413E7FyweqPH0n71BaO1Sp6JhLn1ufqV+4AISuefiXAW8GHhKRB+yyD6jqtxpsP2nlnzuAG0XkAG0qLq0knS+r6q8C9wd5G6K0EwbU5NhXA8+o6raaydE3AHdHvu+2y+KOcT1wPUBmcBXlPqkOLQRKg/HGHqxsETG45ZFsdSeMXeccTeMPFTlWNK+8j82sNUYf2C8jnJI9zNvOMNMD/MmO1zX51dTLOtFz1d6kNRE8TjDgpFuvkT6VRiRybqdEfUMRys1CVVYz14W+LGoTahUnBji22VT0kYs8JoA+19yLeS/Fmy/7AQDn9O9hf36Yg2NGV85nMniFYCawxsND5tSMKO6XSpiSYwXuEaefL0yv4dysGRU84RQYdOKP1ans04hmxj2Ox/PG4GedyvOZ8zPgZxi1GnpJ3fC4gbY/bSewz/mZUAoac2erJJ7ZcoZBq7VNuLOUVMhZO5AVZdgJooIc0jiM2oZyPCU4OGGdFLRM1kbbHPXzyOpx2G1HWs/mwgnV5eg0q+8s8PirjJMzvulpZsv2uljLsrc4Zs8xy7gNCw0MfzR0MzD+gcwT1fcvHjAjhE/ZdJj/7HsWTxw1gtPUkaHQ6I89KuROam7QA2ewq3Qh9FdV76QzoekaTC7t3wfehMmH/7/b2bGVpBMMAHhVB4UJEZFbgfUxqz4IfAC4Km63mGWxtWp7uW8AGFyzqTdZLRISElYmuvSpFQBUNQiS9oF/7mTfVpJOMC777ar6h9F1VjP6w/q9qva/Mm65iFyAyccTePcbgftE5FKMRx8ZNcVG2py+K+ycjXj1zdrNulcyqUgu/Yd8M7GJpTiTYbeMmQKtmjRePrBl6AC78ms4tc/k4Fl11mGO7BynISqVl69aT79RhE0w0KbQPQ9F/Mbna/YG4aUd1HURG38f5M0prrX5VMZSTNnp6bec9Qwj6QKrs8aze/7I46FXV1KXh3efDHtsVFlGkXT1G823rg7kzErAeL9kQy8foKAlslIZRfa8vl0csF7iQSBnO3SHHR9PzZzbAH3Sg1S6EQp+5dELvP0pGwc/msqFHaphZ66tt1pvfyI1XZXbKertr3eP0Wc7TQsKhTAFhs+oA2kJroXJuBl96ynbUKBbcqegx2oCRjTQQYsgwui3zPV55Np1nLPapGvwVZjzKtflSLlyDbNOCRe/0mlNdQQPUNWhGzDszvHqiW08PWo6vm/v38LPD5lIiuxU9fibZt58rQqwEHph8BdCu3f9y2KWzTv4X1UfUtW1qnqqqp6KMfIXqeo+zDSK14lIVkROA7YA9zQ5XEJCQkJv0Db/lgmtNPy3AW8HTheRByOrhoEfLEaBVHW7iHwZM8qsDLyjkwid0LuPJgqLSHvR1t3N1+6bCidzGNhfYG7ChnTtE2b7XdR2/u4+OsYp4yY++rGZtaGXD/CyDTv4153Pjy1bmJEhLEQDLb+m/AGZqdjDtk0jzT4gCFF1ajps4whimqXsga8UxsytdPA5DuX1xnPbODjJ1sH9rEsZD9FTJ+xgLPkuflmwM/nhzgnMmUL5WUUFzk7Hp/nulyyFSCjmd+dMWbakJ1nnpjhm4wvyfqri0vhm+wFbAbNa/wO77f3P+vXnCLzefrdS/sDbr/X0wXj7UU3fiaT18HHYVx5l2jdvScNOvsrb3+dV5kmYcGfC+XFdlCnfHAFgwFFcJKwqVyS8D++bPTXspAWqMs9qsYQAa242Gvv+zOk8/lpzQc9fvZeUeOFvK/sVDzwtHsORh8+kWqjW9QNP/2B5OPx9tXVz9th+js6ZZ7TcFxN+SXe9+TiWMh++iHxXVX9RRD5eq7i0SysN/4vAt4E/Bd4XWT6tqt2ZZgmwXn70+8eAj3V0DLe1sQcbY94gj0Zx1KX/UBBSU30lnTmH4mFz42XXzPH0EfMqecr40dDog3mVXXOmmRf30M7VNKVRBy7Eyi2pudgtWxL8XnXqjxndpt2b1x9I405X2uDSumGmTrPywPoir7zgIQBO7z8YDuMPCAYUHSgOs2H9Ufa4Y6Zsh7OhkXHzrZ/SQMa5cXqcS/tMVO+24jo2pY4wYedRPYLPbHBux0wIngsMCkq25gcHGaHjGoNuE5U7AuNfa/jBGDgXnyE7A5YXY/ynbZ6daa8fpzwKmKiYaANw0BsKk1/1SYkJdzY8R9E39ZG29ZFWP2z8RlNzQCY2xbgWi2iphNi8Suu+9jOeGt8KwMMvhjPGDoWzxAEcKlYa8MFUkZ1TdrCeKLM2IMIRJVeMSfQUIV+oX184RRh+Wtsy8FWS70JQutJp2wEniciLgatF5CZqnmab1LIprTT8KWAKG9QfGco7JCJDyQQoCQkJK5klnvHqQxjHeyNmpG3U4Cvw0lYHaDdb5quBv2QeQ3l7Ra1nD9R5t3EXy7euTdVLfbCddR9UJZyS7ekjq0IvH0wn7ktONvnfvzI1hH+wOstZ5I28eQdu9LxC8xG4DXBK5ly1c+7WbgPB6FoNy9gMP+vi5Kyko8reFwwwe67xqt/8nB+Fr+tp8SipG8aXF/w0h0omnnVffhRHFMdOcuKvLuDNBkOgHdLrq3O7NywLDg8UNtjzlTnoDTHrG0lptTtXNWR4VtOhrOEh5Oz1jPP2F4ODNVP8Bcx56ViJB4y37+GEUkatt1/ClB+q5Z5pr59pr58B+0Y14BTI2A7cvKTJazqcGnHYydMnZfKRKkjbm8BTB7wGiqrngeuiJVP28gWnkdtg9ss9sZp9shp3LD7pnXc007m2rYIzXj/RD0Aq3Vy+6ZpXH0FY2k5bVf134N9F5H+p6kfnc4x2c+n8CfMcyrvkSIyxb3atIzddYcQha1OXzK3N0n8wMq/nPmFuvY01P9xHdk1FXwmMPsCO6XWcNWwiFU5ff5CdBzc2L29wl5ZpKu9IsfkNG9x40TE7zQx9uN887Fy5zw1vnOKmcQoXzfI7598FUBV5ERj6QyWTEdNXwbe/N/jf32eMRS6XxR20xthJ8dvn3tXw/AUtUbA6/bTXR97KO674lDTFMTESR17TjDiVxsfFD+eDHYxEfwTG343cDIvRANw5uzWMUx9MVRuuqMQD9TJPWC6nXGX8gcZyD5CzjUwu0tikpcyAUyRtY+0PyzB9UmTQSmEOykGr/9/7+q2o//PGs8Z5Hk+9z6SIya/z6m4obzLagVazb5OurCjOqtaZUosbi/BEpQ4Xw8DXobrUko49rX5URFZhAlr6IsvvaLVvuwZ/3kN5ExISEk5UejGJuYj8NmaM1EbgAYwz/kO6JemwgKG8S4UK+M0H2gGtOyc14skM7DOe09zEQE26AqFwyHiRgacf7cTdMb0OgKF0kfRJOUp7qzP3Ree4rfoBTVydYKKQ2mNEPfq6Y7Yg2nndNDInTm2yydKeeWeJd597O15EBAtTBAAHipVIkYKfYl9+tOo4owOm/nJzGcS6fG5/mfeMV6ari8bdA+S0TN52rJ6V3cuesqn7vJ9m2u8LIz58dfDtMcdspsggQVng6QNVMk9Y1gaXYiGe/51Hz2TANd5qOCKVem8f4jt1Id7jnylXolicmvINuObY0bcXDyHvpaukoHQkyZmLH07vSc5OZWnz4dd6+rmXP5v8WruvQ/XDFdVYokEIbVRhO1591fYZj8PPTjHy2BKPr+hNyOW7MDMO3q2qLxGRs4GPtLNjuwb/GiDPPIby9pwY3d4Nnq9mht+tfyXs32eWza138AfMTR7V86Fa3gE4Z/1+HrQaM0datEglB9LxVjczCTGJBzsy8FE6icqJY3ajacTedu63w1DLWgJjHzVSfgOhdaC/SC5njKBIvZEPmPZL5FRD45wRr5L2F59pvz+chGPa7wszQHrpyTDtAEBRXQat/NRI5gmIGstCG2EgcY1CsF8uojfGGX9oLfcE+nrK8eoagCgDTjFsDGobAqiexCeKg/K5W64AYMuhn8RuA6AXnsUzL3XCgYGaihxPBfG1YvSj/kytbxP53qmhryrPSJkwyVUT2nEM26UXHj6QV9W8iCAiWVV9VETOamfHdicxn4187Wgob0JCQsIJiVKJ5V1adovIGPB14BYROUqb2QhaDbyaJt4PFkBVdSRmXU8JHbB59tmUBytyxNzaiueVmYFiJBlfcKLaDlyolndy5TQnr50E4JniamSmcvyqiJ2AYEKHGk8/VTNIbL5Eo3Kg/cicWvy3mqjuqHwD1RIO1EsQzejrN97dZRuerFpeOzdt1Pv2EFz7Y4JOx/Dcmg4lnT2lVTgoq20Cr7SUq7KPDjrFKpkH4qUeqPb442j0FvCzQxM4jjnpmeOHq7x9aN/jLwXpKTzH/pb4i3fMjx+MBNDv1neuB0yX+3Br0njEddo+8StDSBF00E4a1F/GL5ljaZmqVCW1ITROg+idheBkPArm0QuDL6J007MP6IWHr6qvtR8/LCK3YRSX77Szb6s4/OFm65c1MRcilELbvUg2i2f/IZ+5NRXLnJ4WSlaz9gc8Cof664w+VOSdAZtWeWBVjll/IAxpbEpE3pFid3TJBck4kf1mT05x3ab7q1bXGnqoN/Z75sYaHn50YI6pnDFQ1625u87I55pk5x4QYxCntY9BpxDKONmIRBMY/4Nlc0s7KCVr/Gf9LKvd6bAfYljy9DnlugYgICr9RGnWEBzTDMWyi2Cu/c8OTYTrtq4xjWdtAwCmEahtAAL63RKO+GED0Ay/ZpvaazPrZXjsqCnT5Ew/I7YLxVk9jn/4SDiHsaTTFC85M9zvpB/6HDnHjp5+VhHHyjpq8/0sdRBLfr1pfLJHTT0vhpGvogdROgAicjmwRVX/SUQmMBmFn2yxW9safkJCQkJCDT2K0vlj4BLgLOCfMFm0/wWTV78pK87g1+bPqaXcbwdelStXUqxOl6maac9sV8INvXwgVt4JOnE3jE3xDDCL6fB0cm58xE6AlXfc3MI8/FoZJ1zeRs6c2ONdeyj83I5n3y7rR0zOnUsy1XWY03Kovsza3+BHfktt52Mg7cxGYs+D8QFBmoeotz/gFDnsRV5mXch5fp3HH9DI82/Ge3e+nnKp8mYXvRTb95kM4ulUpVe+ldcP9Z257ZL30uTK1fvuOjrO7KS5h+VYimJQHekU5eefT+ZxM7bEO3mcw+eYevXTyu6rAJvqyvV6m4EUABtM4WfaeIteKL1LjPZazETn9wGo6h4RaUuNWREG341/A48lVn6VFh0CKqE1jZN3Ak0fjK7/+Jw1Og6hph+r51v6D7RX9jgayTjzNfbPXJHmdSc9FmvoId7YN5Nyopw2VJ2eaWaBk6xF5R3PXtjowLDA+Af/Awlo0jM5X4KBSbNk6bPJ11zxTWpfG/ETbQia8fTB6pTZUeMfEA1iCRoBqG4ImrFxbLLp+l2HK2XIHa4JFS4JqWOmTE4JSvbyPvLRdeAL5/yxqb/Hrx3CG4qUxyPsLyvPpMPBc73CyZiyTZ/hMfz44hp9k169Jxa/qKoaTEolIvFZBmNYEQY/ISEhYTGQ3kTpfFlE/h4YE5G3Ar8J/EM7O55QBr8bqVCjEyekIhcz2nFbK+2UcPD7g5FQ2lDeAePtn3GSeV3ffXSMOexr9Ixb5+WHkTTzdJrcmECI+UblHLrASACv+6X4lAfzlXGivGzVw0C8Zz8bea78Bs/YsJOvSqUL9fKOF7lJot4+VDz9wNXORt7sSmJ+X+D1H7PXLfD8u0Gc1w9QarA8na72/J88tJpyubWsoir1qTpUwkgwdWBuo/mdMpti83/67H/FKQB4awtU5rsESfnoMXNviBLmQ+q5pz9WBBpHKXWFHkk6qvpJEXkZcAyj439IVW9pZ98TyuDHEZVzWun3jVCnuYGsjdoJaBa9E9Bv53Qt9qfrEq25c/NLmLYYHUmFi2cbr2ti7BvJOX5NqONJA9NsTbfWrhoZ+1bE6fpR4++KNm4AILYRAMhT0cL7YlrmI2UTy+uXHHQqg7umS/G1NG4IoviRBkAn40NWHA+kLJSGzI/0RjzSh801HX4a5tY4FIIB0rMpGLQNsoB6gowE+beBObOfP5PGGeqt0Z8+02N4Z4x01rU0O73JpQNgDXxbRj5KT3tZROSdIrJDRLaLyJ9Hlr9fRHbadb/UyzImJCQkNEK0vb+unEtkWkSOxfxNi8ix1kfooYdvM25eA1yoqgWbax8RORe4DpN6+WTgVhHZ2smsV9BZR20cfhqCSZWClAbB5Chza5wqWac8ZLx8qETtBDTy8sPzWHcjky1RnAD/kPFAVWBgT3uuSLte/Xw7avdcnuJ1Z1XPMtkNCSfKtWvvZcKNv8Sz2r5nHyfrRInz9KHe24d6ySdK1PsPOnvzfn3UzKcfexFgZBRGSnjFiMd5rHp7iQxGclKtL5QfI9808uKrsB66e8Se38dkmR029Z86miI7aVZ5WfAylRmw+ve4zJ0RuU6Oop6pu1RfmXKQcjrt401Xfl8vvH1ntMjMZnOdh55yFmf2qyX08LsxLqqXks7bgD9TNUlTVDV4n78GuMkuf1JEdgKXYrLB9ZQ4YxkYfvvmbuUdO+jDGv5A04d4XR+M4R8dyXHMqQxckZ+11iDjdPpa5qvbHz3HPCFR3b4TQ99OdM6gHZTmxBRuus3yevNIKBQdldvM+EOlAYjSrDGIMnW0SQDFSLUR1MicB34pIsVMtTd6SEaLyGilXKoCXr2VcybTSE03iTfkk5o01zYzWZlGQAGcSH9SGWTabKfDZTNPg82lU86nSPWV7ec07nAJzzZq/nQaZ3jpjb7JrwMqizACS0/cScwXg63AC0XkRyLyPRF5rl2+Afh5ZLvddllCQkLC8sLX9v6WCYvq4YvIrcD6mFUftOdehcnl/FxMqNHpxGfBia0xEbkeuB4gPVzpCK2Vc+bTWetlJIyOSXnasuM2SiN5B5pLPLP5DK59lS9M18sDjQZQNWO+Ms7Rs4ULLttpytKhfNNu3H1/qsRvbvgBQFsdtu0ybCc9aSbtRInG68dR6/FDvNcfv3MDHcFtvr9GzznSnmesMRKPM1m5j+q8+hF7b6qQmnTJTNntajNZ1kykl562uXxIVbx8Szlv7hUn5Rn5qt8OyorkhvKOLZ23H8Tlz5zhMbQIcfndisMXkc8CrwIOqOr5XTloDItq8FX1ykbrRORtwFdVVYF7RMQH1mA8+k2RTTfSIBOcqt4A3ADQv36TwsK1+9jzuNWpiQcO+OTWVh6uWj0/IJB34ox+QCPj7x6uPKjtyDZxzNfYz2wSLrh8J6cMdD5PfbvGHmAkXQilnFr9fjHlnDhqE681awDMeVsLwk0bhUYNwQKJGvho0FC0uN6wTa88ZQ2gL2Smogn1aJx8UCFtuwdLcYqyNf5+2cFJeaSy5roWZzO41vi6tgEL5J6lMP7OaJHpc2zk0SPzG6EcS/c0/M8BnwI+360DxtFLSefr2BlaRGQrJpH1IeAbwHUikhWR0zDTeN3T6CAJCQkJPUExHd7t/LU6lJmesHMPq0N62Wn7WeCzIvIwUATeYr397SLyZeCnmFm13tFOhI5ovHc/39j7ZpONiG+8fCD09Ft5+YAZnFXj9TXz9ufj2c/XqweYPMt4Z8MXHp6Xd98JW4YO8JyBp1jtztSta9e7b0WriJ1mNOvUbZf/d/jCqo5YcRbuDUY9+HBZEwc58OwDrx4gdcypkmEC7z48Tv2YrFBUjc5dkj7mVGSdWnzBL7rhtHhutkzKDhQrzGRxM17o6VedaxHl7sywTT99SnekHUE7kXTWiMi9ke83WIViSemZwVfVIvBrDdZ9DPhYJ8fzU5Afhz5rp+Zr6KuOaZ8tt1Qv6wRE0ugA8YY/0PSZdikNa53EExA1/p3ekvONxAmYPEs4/4VGs19MKeeMITPKeGvfPhzxOTs9Ha7rlqGP0qmeH0et3APtNQI/ePTMqu9R498pwUCoTiiPNDbyQJVmX9tohBNVxdizcFnQCESjdmrwI2GolfDNEuXZTNiPIY6Pk7Kfm1TRQhsDz/ZxpNY3DpPuGL/tm/aQql7SvRPPjxN+pG1CQkLCohBIOscRJ47B7/Pxz5ll5ukBhn7e3Q4xLy24pYp7EY3YGdzvM7vOaenlB8TF6ceRmWxz0NUCJJzCmDB1nvHKLjpn17xlnE68+zXWox90ClVyzmJ491EWIu/EEef115I60MXOwSZEPfnw3MecWK8eKp59QODddzowKXMMwKE0aifqmW4g71ii3r6TLYeDy8qzGcpWvgyiasSt9/hbJa1tF7+LaZx7lC1z3pwwBl/VvrKdnGeGPkYf6/DuiLluXsbmxrfGPpgJTrxqPT8w+hAv78QZfQCmU5SGzQ7NjH8tCzHyAZNnCd7mOV5z9kPz2r+TaJxAxgHYlDaNSiDnLLah7wW3Tp3X9WM2MurR/1U0kG+iRPuIao19wwAjpU7jT0/ZMM1Rv6m8ExatWC1Y1hr/qA0NGoA4pEVo65LQvbDMLwFXYLT+3cAfq+pnunLwCCeMwU9ISEhYWrqXPE1V39iVA7XgBDL4EnYK6boCR8aNFzH+o/m/VgedtKbztlrWCQjlnUrG2DovP/D0i0PNvX0g9Phr6YZXP7NJKJxtOqyetfmZRZdwoNq7DzpqAc7L7Fty777bsk4jvvPouUB3Y55jvfiABp3BcV59QDPvPkormSdzDOLmwunU0w8+O1mzfTSXUGmmOi2C2A5e9U2Hb89QepYtc76cOAbfr39VBDh8aQkpmIdlfFt3wrFqI3bUgcF95sabXe9UZi6quRcaSTxRggYgexTc/MJupsKYMLNZYa2JVBkby3HVSY/P61idGPmAQLMfd01q5WF3jjPSpgFoNuH3YhJE7cDCIncacbA8gvPMIjYqLSJ92jXy0NiYtxxEHJ2ai0DLh6ieHx6rDcMfJe4ZdvvqG4GA2sZgqenRBCjz5sQx+AkJCQlLTeLh9wZxlfRQg5FK1qM+9lIoT2YZvy/ys9u4XqbzttJb5Za0qgMXKp24g/t8Ztc7VYfuROJZKFNnCuVBe8J1c4yN5njhEnv1AYF3P+waGemM9EEGaxO69JBuxOjX8unHXlTxwtsdaLWA+PxmHj00HrwX5913nLe9RQdu1bGnK89cO95+nKfvF926Ttxm3v+ioyyrxGjtcMIYfNX4/OC1OEMljvyCuUhOtkz/Njsd4WTjfWoHXNWGaVaVIyLvQLXEk18N/Ycq20aNP3TWABTGzJMWSjb2wRsZmePFJ+9s7yANWKihPykzCcCYm2PAKYQyznIy9lG6pe0fLI8wuz0yWfkCDHktrQx7Lc1GabcTftl2iGbUmYno+Y0MP3Qu80SJawiiy5tF9XSf3s14NV9OGIOfkJCQsOQkBr9H+IJf6Ozn+IUUs2ebUSezAK7PwA4zZD47WZ1OtiLr1GQhjEm5UBWjH5F4+o4Yzym/2qyPevtgvH3HHqs4CnNrbZplm44hnDVIjCcPcNbwMbYOzz+18Hy8eaj26IFwQFVaPNanjDvqiL/sZJxGdKMz95NffQ2ZaXPtGtGpp94JC/HquzINn1Y6cDvx9KsOMQ+vP0qjNwBz8EXIUJoY/OMYzyF3pjGquehy16aT3Wsag/4DkJ6x0TTTfqjnQ330DtRLPEG+n+j9l18D/Qdheos5wNjGimU4fYFGPcp8DXxAnKFPi8eYa2psIDIC9ezMfjLH29hzqo0/tG4APrDttQAEaYEW06hD+0n12rVvtcZ+QXbRHiszBaWRyrECww/xxj8sS00j0HEDsCjzGDY6l4K3lBLSwkkMfkJCQsJ8STz8EwOZib4ams/egPFMZk5t7xjqAMNlyNu0CwUH8HHz9V6ICsxtKvPss54G4NTBwx2Vd6Geey21nnxA4NEHBB2z4X7HiYTTCc3kng8++Bqcexc8t3Qd80mN3YlzGyfhdNs5Th+rfC5FBmc1k3lqiZN9AnSox951EqXTQ3ypMdK9R3xgqlLFmcnmUUSpuTSP7jkDgD2XjLB13Bjdotf9y9TIoEeJ6vIBY26OPilVTTp+Ihr5RgTG/623/qb5vmPpH6GFGuau6PUdkj5WMfrB+aPPQ3Gsc+lvWTzviYefkJCQsEJIDH57iMizgf8L9GFmtnq7qt5j170f+C3AA35PVW/uVTkXQiuPvpboK/Dcf0+wjQkA+l96kOete4rBVOuUvJ2yJjIBSbom3CjoiI3z6NP2+/HYKbsQvnjoedzx/QsY3rN4nYOL0e/Yyqtfir7O6P0N1TJPo2dlPp7/kpF02nbEnwMfUdVvi8gr7fcrRORc4DrgPOBk4FYR2drONIe9oFOjXkvtQxDH3H9PcBsTjF61D4CLVu9mc21MZ6Pjx03TZQkMOtQbdSAcMGWOszINPMATxbX86R2vAiC7L0X/saUNBpkvy8HIN6ORxh+l2fO1LBqD48zD7+Uk5goEl3kU2GM/XwPcpKoFVX0S2Alc2oPyJSQkJDRHtb2/ZUIvPfx3AzeLyCcxDc8L7PINwN2R7XbbZXWIyPXA9QDuqlULKsxCPfV2aMebb8bUf60H4DbWk9tobqKLn/sY543s4bRsfSdsnNceJerBw8r24mv54qHncdu9ZiKT7CGXoQVeu6Wgk87YXnv3tTR6Nhp5/jD/Z7Z7bwaaROlEEZFbgfUxqz4I/CLw+6r6FRH5VeAzwJXUpWMCGqQ4s7O+3wDQt2GTLoXRbsRCjXmnDOw21fTI7q08wtawATjtwt1sGTGG/E2rfwjAWjcXf5CEkA88+loO7jJ5cLKHXNLHwpx7y4qFRNgsNyPfDq2eq2YNQiO6ZicUVI8v52hRDb6qXtlonYh8HniX/fpvwD/az7uBTZFNN1KRexISEhKWD4mH3zZ7gBcDtwMvBR6zy78BfFFE/hLTabsFuKfVwcRbei97ORF4/Pt3b2K/bS/v5KLQ8wc441k/52VrHwXg+QOmuleK9/9EcS3/+MRloRcPxpMP6KVHv1hx8cejR98pPX3mkyidjngr8NcikgLyWC1eVbeLyJeBn2LCNd+xXCN0jgeChgBg7+5T+DynAPB5rgKoahAC/NESzLmhuHbWObv5o83fjD3+UjUYB7yBqu+/frcZ+ORNZqoEv6gRh/q8Nt0fE9tbVoJRX9Ysow7ZduiZwVfVO4GLG6z7GPCxpS1RQkJCQmeon2j4CccR0TeAkN3V84Q+8/hm3sY7lqhE7dHfxja9SCEwXxJP/XhkeYVctkNi8BNOWBIjmrCoJMnTEhISElYGCuhx1mnby5G2CQkJCccvqqB+e38tEJGXi8gOEdkpIu9brCInHn5CQkLCPNEuSDoi4gJ/C7wMMw7pxyLyDVX96YIPXkPi4SckJCTMl+54+JcCO1X1CVUtAjdhcop1HdHjrJe5ESIyDezodTlqWAO0l9ZyaVmO5UrK1B5JmdqnWbk2q+rEQg4uIt+x52iHPsx4o4AbbGoYRORa4OWq+tv2+5uBX1DV311I+eI4kSSdHap6Sa8LEUVE7l1uZYLlWa6kTO2RlKl9FrtcqvryLh2q7fxhCyWRdBISEhJ6y5LlD0sMfkJCQkJv+TGwRUROE5EMZgKobyzGiU4kSeeGXhcghuVYJlie5UrK1B5JmdpnuZarClUti8jvAjcDLvBZVd2+GOc6YTptExISEhKak0g6CQkJCSuExOAnJCQkrBBOCIO/VMOS2yjHLhF5SEQeEJF77bJxEblFRB6z/xc2+W7rMnxWRA6IyMORZQ3LICLvt/W2Q0R+aQnL9GERecbW1QMi8solLtMmEblNRB4Rke0i8i67vGd11aRMva6rPhG5R0S22XJ9xC7vZV01KlNP62rZo6rH9R+mk+Nx4HQgA2wDzu1RWXYBa2qW/TnwPvv5fcDHF7kMLwIuAh5uVQbgXFtfWeA0W4/uEpXpw8B7YrZdqjKdBFxkPw8DP7Pn7lldNSlTr+tKgCH7OQ38CHhej+uqUZl6WlfL/e9E8PCXbFjyPLkG+Gf7+Z+B1yzmyVT1DuBIm2W4BrhJVQuq+iSwE1OfS1GmRixVmfaq6n328zTwCLCBHtZVkzI1YqnqSlV1xn5N2z+lt3XVqEyNWJK6Wu6cCAZ/A/DzyPfdNH9IFhMF/ktEfiIi19tl61R1L5gHGljbg3I1KkOv6+53ReRBK/kEcsCSl0lETgWeg/ESl0Vd1ZQJelxXIuKKyAPAAeAWVe15XTUoEyyT+2o5ciIY/CUbltwGl6nqRcArgHeIyIt6VI526WXd/R1wBvBsYC/wF70ok4gMAV8B3q2qzabEXrJyxZSp53Wlqp6qPhszCvRSETm/yeZLUq4GZep5XS1nTgSDv2TDkluhqnvs/wPA1zCvjPtF5CQA+/9AD4rWqAw9qztV3W8fWB/4Byqv10tWJhFJYwzrjar6Vbu4p3UVV6blUFcBqjoJ3A68nGVyX0XLtJzqajlyIhj8JRuW3AwRGRSR4eAzcBXwsC3LW+xmbwH+Y6nL1qQM3wCuE5GsiJwGbAHuWYoCBYbC8lpMXS1ZmUREgM8Aj6jqX0ZW9ayuGpVpGdTVhIiM2c/9wJXAo/S2rmLL1Ou6Wvb0ute4G3/AKzERDY8DH+xRGU7HRAFsA7YH5QBWA98FHrP/xxe5HF/CvMqWMF7NbzUrA/BBW287gFcsYZm+ADwEPIh5GE9a4jJdjnmlfxB4wP69spd11aRMva6rC4H77fkfBj7U6t5egrpqVKae1tVy/0tSKyQkJCSsEE4ESSchISEhoQ0Sg5+QkJCwQkgMfkJCQsIKITH4CQkJCSuExOAnJCQkrBASg5+QkJCwQkgM/gpCRGZab9XxMa8Wm5JaRF4jIufO4xi3i8glHW6/Q0Sujll3qkTSMJ/oiMgHIp/7bUrgoois6WW5EpYnicFPWBCq+g1V/TP79TWYNLRLwZtUdVFHVIuIu5jH7xKhwVfVOTW5ZVZcyoCE9kgM/gpEDJ8QkYfFTNjyBrv8Cus9/7uIPCoiN9rh/ojIK+2yO0Xkb0Tkm3b5r4vIp0TkBcDVwCesl3lG1HMXkTUisst+7heRm2xGw38F+iNlu0pEfigi94nIv9lEYq1+z8ViJsL4IfCOyHLX/s4f23P9jl3uiMinxUyc8U0R+ZaIXGvX7RKRD4nIncCvNCqPPef3xGRGvTmSU+b3ROSn9nw3NSnzoJhsjj8WkftF5Bq7/FQR+b493322XhGRk0TkDlu3D4vIC0Xkz4DAq7+xrYufsLLp9VDf5G/p/oAZ+//1wC2YyWPWAU9jJt+4ApjCJJZygB9ihvv3YVLLnmb3/xLwTfv514FP2c+fA66NnO924BL7eQ2wy37+H8Bn7ecLgTJwid3mDmDQrvtD7JD5mt8RHtd+fxB4sf38CexEK8D1wB/Zz1ngXszkF9cC37K/cT1wNCg3ZhKb90bKXFceTO71u4AJu/wNkd+zB8jaz2NNrsX/AX4t2A6TGmQQGAD67PItwL328x9QSdfhAsPRa1pz7F3UTMST/CV/qkqKhJXI5cCXVNXDZDz8HvBc4Bhwj6ruBhCTa/xUYAZ4Qs3EEWAM/vW1B+2AFwF/A6CqD4rIg3b58zCS0A/si0UG0+g0RERGMYb1e3bRFzDpqcEksLsw8N6BUYwRvRz4NzUZFfeJyG01h/3XFuU5CzgfuMUudzG5gsA0PjeKyNeBrzcp+lXA1SLyHvu9DzgF02B8SkSeDXjAVrv+x8BnxWTT/LqqPtDk2AkJsSQGf2USlxs8oBD57GHukWbbN6NMRTbsq1kXl8RJMBNZvLGDc0iDYwXr3qmqN1ctFPnlFsecbVYeEbkA2K6qz4/Z95cxDdrVwP8SkfNUtdygbK9X1R01x/4wsB94Fqbu8mBmDRMzv8IvA18QkU+o6udb/I6EhCoSDX9lcgfwBqtxT2AMVLNUsY8Cp4uZhQmMhBHHNGYu1oBdwMX287WR5XcAbwIQM2nFhXb53cBlInKmXTcgIltpgppc6FMicrld9KbI6puBt1mvGBHZKiZ19Z3A662Wvw4jZcXRqDw7gAkReb5dnhaR80TEATap6m3AezFSTaM+iJuBd0b6SJ5jl48Ce+3bx5sxbw+IyGbggKr+AyaF8kV2+1Lw+xISWpEY/JXJ1zDSwzbgvzGa9b5GG6vqHPB24Du2M3M/Ruuv5Sbgf9pOyDOAT2IM7l0YPTzg74AhK+W8F9vYqOpBTJ/Al+y6u4Gz2/g9vwH8re20nYss/0fgp8B9YkI1/x7zxvIVTJrmYNmP4n5Po/KomTv5WuDjIrINk8b4BRjj/C8i8hAmde9f2QYpjo9i+gIetGX7qF3+aeAtInI3Rs4J3jauAB4QkfsxfTB/bZffYI+RdNomtCRJj5zQFiIypKoz1iP9W+AxVf2rHpXlduA9qnrvAo4R/J7VmAbnsmaN3vGEjYa6RFUP9bosCcuLxMNPaJe32k7c7RjZ4e97WJYjwOckZuBVB3zT/p7vAx89EYy92IFXmDcHv8fFSViGJB5+QsIiIiK/AbyrZvEPVPUdcdsnJCwmicFPSEhIWCEkkk5CQkLCCiEx+AkJCQkrhMTgJyQkJKwQEoOfkJCQsEL4/xgBUEvDWgvXAAAAAElFTkSuQmCC\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 2 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| }, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "xarray.open_dataarray('lai.ancil.nc')[0,0,...].plot()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "id": "ab5ea180-f617-4caf-b05f-eb037da8d391", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| } | |
| ], | |
| "metadata": { | |
| "kernelspec": { | |
| "display_name": "Python [conda env:analysis3-21.07]", | |
| "language": "python", | |
| "name": "conda-env-analysis3-21.07-py" | |
| }, | |
| "language_info": { | |
| "codemirror_mode": { | |
| "name": "ipython", | |
| "version": 3 | |
| }, | |
| "file_extension": ".py", | |
| "mimetype": "text/x-python", | |
| "name": "python", | |
| "nbconvert_exporter": "python", | |
| "pygments_lexer": "ipython3", | |
| "version": "3.9.6" | |
| } | |
| }, | |
| "nbformat": 4, | |
| "nbformat_minor": 5 | |
| } |
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