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apatlpo/mathis_gather.ipynb

Created January 9, 2024 16:29
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mathis_gather.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 24,
"id": "e6a7dfe2-7d86-4867-a434-927e603bb0f7",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"import xarray as xr\n",
"import numpy as np\n",
"from xhistogram.xarray import histogram\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "7b77539b-756e-43c6-8399-412106d512d9",
"metadata": {
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
"Dimensions: (time: 70, drifter: 20, source: 1, SNR: 3)\n",
"Coordinates:\n",
" * SNR (SNR) int64 -20 -10 0\n",
" * source (source) int64 0\n",
" * drifter (drifter) int64 0 1 2 3 4 5 6 7 8 ... 12 13 14 15 16 17 18 19\n",
" * time (time) datetime64[ns] 2010-09-01T14:00:00 ... 2010-09-04T11...\n",
"Data variables:\n",
" rng_est_coh (time, drifter, source, SNR) float64 ...\n",
" rng_est_ncoh (time, drifter, source, SNR) float64 ...\n",
" rng_err_coh (time, drifter, source, SNR) float64 ...\n",
" rng_err_ncoh (time, drifter, source, SNR) float64 ...\n",
" real_range (source, drifter, time) float64 ...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4bfcad07-51eb-4ebe-a63d-9df3bca4cab1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4bfcad07-51eb-4ebe-a63d-9df3bca4cab1' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 70</li><li><span class='xr-has-index'>drifter</span>: 20</li><li><span class='xr-has-index'>source</span>: 1</li><li><span class='xr-has-index'>SNR</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c479ddef-721d-43cd-8539-e2a89010aa1f' class='xr-section-summary-in' type='checkbox' checked><label for='section-c479ddef-721d-43cd-8539-e2a89010aa1f' 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'>SNR</span></div><div class='xr-var-dims'>(SNR)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-20 -10 0</div><input id='attrs-43a4584f-4947-440a-8b9f-1b5faaa8e76b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-43a4584f-4947-440a-8b9f-1b5faaa8e76b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ba0fae7-13d9-4850-bb49-c9d09cfa41b4' class='xr-var-data-in' type='checkbox'><label for='data-6ba0fae7-13d9-4850-bb49-c9d09cfa41b4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-20, -10, 0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>source</span></div><div class='xr-var-dims'>(source)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-4e3a40b3-d516-4693-a030-df8b36c629c4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4e3a40b3-d516-4693-a030-df8b36c629c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae9bb48f-8749-4b5c-9341-6bce524617da' class='xr-var-data-in' type='checkbox'><label for='data-ae9bb48f-8749-4b5c-9341-6bce524617da' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>drifter</span></div><div class='xr-var-dims'>(drifter)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 14 15 16 17 18 19</div><input id='attrs-df9de117-7a61-4dbd-a430-262be826ca1a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-df9de117-7a61-4dbd-a430-262be826ca1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee077ea4-afff-4f02-b7d9-7e9084e5d42c' class='xr-var-data-in' type='checkbox'><label for='data-ee077ea4-afff-4f02-b7d9-7e9084e5d42c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
" 18, 19])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2010-09-01T14:00:00 ... 2010-09-...</div><input id='attrs-f0724ee0-c61a-48d4-9dfe-b292d1c896c7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f0724ee0-c61a-48d4-9dfe-b292d1c896c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58dbe76b-69fc-4bea-984b-f715d3ba3667' class='xr-var-data-in' type='checkbox'><label for='data-58dbe76b-69fc-4bea-984b-f715d3ba3667' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2010-09-01T14:00:00.000000000&#x27;, &#x27;2010-09-01T15:00:00.000000000&#x27;,\n",
" &#x27;2010-09-01T16:00:00.000000000&#x27;, &#x27;2010-09-01T17:00:00.000000000&#x27;,\n",
" &#x27;2010-09-01T18:00:00.000000000&#x27;, &#x27;2010-09-01T19:00:00.000000000&#x27;,\n",
" &#x27;2010-09-01T20:00:00.000000000&#x27;, &#x27;2010-09-01T21:00:00.000000000&#x27;,\n",
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" &#x27;2010-09-02T00:00:00.000000000&#x27;, &#x27;2010-09-02T01:00:00.000000000&#x27;,\n",
" &#x27;2010-09-02T02:00:00.000000000&#x27;, &#x27;2010-09-02T03:00:00.000000000&#x27;,\n",
" &#x27;2010-09-02T04:00:00.000000000&#x27;, &#x27;2010-09-02T05:00:00.000000000&#x27;,\n",
" &#x27;2010-09-02T06:00:00.000000000&#x27;, &#x27;2010-09-02T07:00:00.000000000&#x27;,\n",
" &#x27;2010-09-02T08:00:00.000000000&#x27;, &#x27;2010-09-02T09:00:00.000000000&#x27;,\n",
" &#x27;2010-09-02T10:00:00.000000000&#x27;, &#x27;2010-09-02T11:00:00.000000000&#x27;,\n",
" &#x27;2010-09-02T12:00:00.000000000&#x27;, &#x27;2010-09-02T13:00:00.000000000&#x27;,\n",
" &#x27;2010-09-02T14:00:00.000000000&#x27;, &#x27;2010-09-02T15:00:00.000000000&#x27;,\n",
" &#x27;2010-09-02T16:00:00.000000000&#x27;, &#x27;2010-09-02T17:00:00.000000000&#x27;,\n",
" &#x27;2010-09-02T18:00:00.000000000&#x27;, &#x27;2010-09-02T19:00:00.000000000&#x27;,\n",
" &#x27;2010-09-02T20:00:00.000000000&#x27;, &#x27;2010-09-02T21:00:00.000000000&#x27;,\n",
" &#x27;2010-09-02T22:00:00.000000000&#x27;, &#x27;2010-09-02T23:00:00.000000000&#x27;,\n",
" &#x27;2010-09-03T00:00:00.000000000&#x27;, &#x27;2010-09-03T01:00:00.000000000&#x27;,\n",
" &#x27;2010-09-03T02:00:00.000000000&#x27;, &#x27;2010-09-03T03:00:00.000000000&#x27;,\n",
" &#x27;2010-09-03T04:00:00.000000000&#x27;, &#x27;2010-09-03T05:00:00.000000000&#x27;,\n",
" &#x27;2010-09-03T06:00:00.000000000&#x27;, &#x27;2010-09-03T07:00:00.000000000&#x27;,\n",
" &#x27;2010-09-03T08:00:00.000000000&#x27;, &#x27;2010-09-03T09:00:00.000000000&#x27;,\n",
" &#x27;2010-09-03T10:00:00.000000000&#x27;, &#x27;2010-09-03T11:00:00.000000000&#x27;,\n",
" &#x27;2010-09-03T12:00:00.000000000&#x27;, &#x27;2010-09-03T13:00:00.000000000&#x27;,\n",
" &#x27;2010-09-03T14:00:00.000000000&#x27;, &#x27;2010-09-03T15:00:00.000000000&#x27;,\n",
" &#x27;2010-09-03T16:00:00.000000000&#x27;, &#x27;2010-09-03T17:00:00.000000000&#x27;,\n",
" &#x27;2010-09-03T18:00:00.000000000&#x27;, &#x27;2010-09-03T19:00:00.000000000&#x27;,\n",
" &#x27;2010-09-03T20:00:00.000000000&#x27;, &#x27;2010-09-03T21:00:00.000000000&#x27;,\n",
" &#x27;2010-09-03T22:00:00.000000000&#x27;, &#x27;2010-09-03T23:00:00.000000000&#x27;,\n",
" &#x27;2010-09-04T00:00:00.000000000&#x27;, &#x27;2010-09-04T01:00:00.000000000&#x27;,\n",
" &#x27;2010-09-04T02:00:00.000000000&#x27;, &#x27;2010-09-04T03:00:00.000000000&#x27;,\n",
" &#x27;2010-09-04T04:00:00.000000000&#x27;, &#x27;2010-09-04T05:00:00.000000000&#x27;,\n",
" &#x27;2010-09-04T06:00:00.000000000&#x27;, &#x27;2010-09-04T07:00:00.000000000&#x27;,\n",
" &#x27;2010-09-04T08:00:00.000000000&#x27;, &#x27;2010-09-04T09:00:00.000000000&#x27;,\n",
" &#x27;2010-09-04T10:00:00.000000000&#x27;, &#x27;2010-09-04T11:00:00.000000000&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-13cc99a1-25f4-438d-807b-e9cf93881ac7' class='xr-section-summary-in' type='checkbox' checked><label for='section-13cc99a1-25f4-438d-807b-e9cf93881ac7' class='xr-section-summary' >Data variables: <span>(5)</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>rng_est_coh</span></div><div class='xr-var-dims'>(time, drifter, source, SNR)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2edc5b42-e082-442b-aa00-abfaae3350d2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2edc5b42-e082-442b-aa00-abfaae3350d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b8b3066-1772-447f-a0e9-52b1f8c3bf9a' class='xr-var-data-in' type='checkbox'><label for='data-4b8b3066-1772-447f-a0e9-52b1f8c3bf9a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[4200 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rng_est_ncoh</span></div><div class='xr-var-dims'>(time, drifter, source, SNR)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-aba00bc2-5d77-46ad-a80b-30115269ec42' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-aba00bc2-5d77-46ad-a80b-30115269ec42' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d947156-6df2-4cdc-aad2-28a5135e401e' class='xr-var-data-in' type='checkbox'><label for='data-9d947156-6df2-4cdc-aad2-28a5135e401e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[4200 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rng_err_coh</span></div><div class='xr-var-dims'>(time, drifter, source, SNR)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f2889b4f-8c68-4adf-a15a-0578813e82bc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f2889b4f-8c68-4adf-a15a-0578813e82bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-caed7e65-4392-4081-a000-693d2725f9c5' class='xr-var-data-in' type='checkbox'><label for='data-caed7e65-4392-4081-a000-693d2725f9c5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[4200 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rng_err_ncoh</span></div><div class='xr-var-dims'>(time, drifter, source, SNR)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-39345982-c2d8-4b67-8634-9120e90c66de' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-39345982-c2d8-4b67-8634-9120e90c66de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85186c70-c272-4b41-b77a-cbfaf63d967c' class='xr-var-data-in' type='checkbox'><label for='data-85186c70-c272-4b41-b77a-cbfaf63d967c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[4200 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>real_range</span></div><div class='xr-var-dims'>(source, drifter, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9ac9d4b7-adf3-4214-ad1f-3dd0ff156ac1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9ac9d4b7-adf3-4214-ad1f-3dd0ff156ac1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8bcfa90b-c4ff-48c5-a59a-811481687fc2' class='xr-var-data-in' type='checkbox'><label for='data-8bcfa90b-c4ff-48c5-a59a-811481687fc2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[1400 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6df8ec5e-6dc5-4d13-a0d4-f13ffb7d9060' class='xr-section-summary-in' type='checkbox' ><label for='section-6df8ec5e-6dc5-4d13-a0d4-f13ffb7d9060' class='xr-section-summary' >Indexes: <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-index-name'><div>SNR</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c41ccfef-46fe-4852-bb98-e7bacaf9102c' class='xr-index-data-in' type='checkbox'/><label for='index-c41ccfef-46fe-4852-bb98-e7bacaf9102c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-20, -10, 0], dtype=&#x27;int64&#x27;, name=&#x27;SNR&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>source</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-498dc10b-148a-425a-b6a7-d386a9602eff' class='xr-index-data-in' type='checkbox'/><label for='index-498dc10b-148a-425a-b6a7-d386a9602eff' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0], dtype=&#x27;int64&#x27;, name=&#x27;source&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>drifter</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-66a2ab0c-3cc0-4ac0-ac03-4a457742cbd3' class='xr-index-data-in' type='checkbox'/><label for='index-66a2ab0c-3cc0-4ac0-ac03-4a457742cbd3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19], dtype=&#x27;int64&#x27;, name=&#x27;drifter&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cd21f088-9772-416c-bad5-eff4e50d49b2' class='xr-index-data-in' type='checkbox'/><label for='index-cd21f088-9772-416c-bad5-eff4e50d49b2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2010-09-01 14:00:00&#x27;, &#x27;2010-09-01 15:00:00&#x27;,\n",
" &#x27;2010-09-01 16:00:00&#x27;, &#x27;2010-09-01 17:00:00&#x27;,\n",
" &#x27;2010-09-01 18:00:00&#x27;, &#x27;2010-09-01 19:00:00&#x27;,\n",
" &#x27;2010-09-01 20:00:00&#x27;, &#x27;2010-09-01 21:00:00&#x27;,\n",
" &#x27;2010-09-01 22:00:00&#x27;, &#x27;2010-09-01 23:00:00&#x27;,\n",
" &#x27;2010-09-02 00:00:00&#x27;, &#x27;2010-09-02 01:00:00&#x27;,\n",
" &#x27;2010-09-02 02:00:00&#x27;, &#x27;2010-09-02 03:00:00&#x27;,\n",
" &#x27;2010-09-02 04:00:00&#x27;, &#x27;2010-09-02 05:00:00&#x27;,\n",
" &#x27;2010-09-02 06:00:00&#x27;, &#x27;2010-09-02 07:00:00&#x27;,\n",
" &#x27;2010-09-02 08:00:00&#x27;, &#x27;2010-09-02 09:00:00&#x27;,\n",
" &#x27;2010-09-02 10:00:00&#x27;, &#x27;2010-09-02 11:00:00&#x27;,\n",
" &#x27;2010-09-02 12:00:00&#x27;, &#x27;2010-09-02 13:00:00&#x27;,\n",
" &#x27;2010-09-02 14:00:00&#x27;, &#x27;2010-09-02 15:00:00&#x27;,\n",
" &#x27;2010-09-02 16:00:00&#x27;, &#x27;2010-09-02 17:00:00&#x27;,\n",
" &#x27;2010-09-02 18:00:00&#x27;, &#x27;2010-09-02 19:00:00&#x27;,\n",
" &#x27;2010-09-02 20:00:00&#x27;, &#x27;2010-09-02 21:00:00&#x27;,\n",
" &#x27;2010-09-02 22:00:00&#x27;, &#x27;2010-09-02 23:00:00&#x27;,\n",
" &#x27;2010-09-03 00:00:00&#x27;, &#x27;2010-09-03 01:00:00&#x27;,\n",
" &#x27;2010-09-03 02:00:00&#x27;, &#x27;2010-09-03 03:00:00&#x27;,\n",
" &#x27;2010-09-03 04:00:00&#x27;, &#x27;2010-09-03 05:00:00&#x27;,\n",
" &#x27;2010-09-03 06:00:00&#x27;, &#x27;2010-09-03 07:00:00&#x27;,\n",
" &#x27;2010-09-03 08:00:00&#x27;, &#x27;2010-09-03 09:00:00&#x27;,\n",
" &#x27;2010-09-03 10:00:00&#x27;, &#x27;2010-09-03 11:00:00&#x27;,\n",
" &#x27;2010-09-03 12:00:00&#x27;, &#x27;2010-09-03 13:00:00&#x27;,\n",
" &#x27;2010-09-03 14:00:00&#x27;, &#x27;2010-09-03 15:00:00&#x27;,\n",
" &#x27;2010-09-03 16:00:00&#x27;, &#x27;2010-09-03 17:00:00&#x27;,\n",
" &#x27;2010-09-03 18:00:00&#x27;, &#x27;2010-09-03 19:00:00&#x27;,\n",
" &#x27;2010-09-03 20:00:00&#x27;, &#x27;2010-09-03 21:00:00&#x27;,\n",
" &#x27;2010-09-03 22:00:00&#x27;, &#x27;2010-09-03 23:00:00&#x27;,\n",
" &#x27;2010-09-04 00:00:00&#x27;, &#x27;2010-09-04 01:00:00&#x27;,\n",
" &#x27;2010-09-04 02:00:00&#x27;, &#x27;2010-09-04 03:00:00&#x27;,\n",
" &#x27;2010-09-04 04:00:00&#x27;, &#x27;2010-09-04 05:00:00&#x27;,\n",
" &#x27;2010-09-04 06:00:00&#x27;, &#x27;2010-09-04 07:00:00&#x27;,\n",
" &#x27;2010-09-04 08:00:00&#x27;, &#x27;2010-09-04 09:00:00&#x27;,\n",
" &#x27;2010-09-04 10:00:00&#x27;, &#x27;2010-09-04 11:00:00&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b6d2e748-dbc2-43e4-af89-17e3c7a74ab4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b6d2e748-dbc2-43e4-af89-17e3c7a74ab4' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (time: 70, drifter: 20, source: 1, SNR: 3)\n",
"Coordinates:\n",
" * SNR (SNR) int64 -20 -10 0\n",
" * source (source) int64 0\n",
" * drifter (drifter) int64 0 1 2 3 4 5 6 7 8 ... 12 13 14 15 16 17 18 19\n",
" * time (time) datetime64[ns] 2010-09-01T14:00:00 ... 2010-09-04T11...\n",
"Data variables:\n",
" rng_est_coh (time, drifter, source, SNR) float64 ...\n",
" rng_est_ncoh (time, drifter, source, SNR) float64 ...\n",
" rng_err_coh (time, drifter, source, SNR) float64 ...\n",
" rng_err_ncoh (time, drifter, source, SNR) float64 ...\n",
" real_range (source, drifter, time) float64 ..."
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ds = xr.open_dataset(\"mathias_gather_res.nc\")\n",
"ds"
]
},
{
"cell_type": "markdown",
"id": "41cea220-4237-4c77-8ee6-4f00aa23eb82",
"metadata": {},
"source": [
"### We start by looking at the distribution of true and estimated ranges"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "2991167e-44eb-4939-9eda-abfb297946b0",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"--- coh\n",
"truth, number of data points = 1400\n",
"SNR=-20, number of data points = 19\n",
"SNR=-10, number of data points = 1400\n",
"SNR=0, number of data points = 1400\n",
"--- ncoh\n",
"truth, number of data points = 1400\n",
"SNR=-20, number of data points = 19\n",
"SNR=-10, number of data points = 1400\n",
"SNR=0, number of data points = 1400\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1000x400 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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thbu7uxg5cqT49ddfm7xdayIT4o43VhIZWUREBM6fP49ffvnF1KEQERERkRXjZW9kVDExMejRowf8/Pzw999/Y926dUhNTUViYqKpQyMiIiIiK8fih4yqvLwc77zzDjQaDWQyGTp37ow1a9bgmWeeMXVoRERERGTleNkbERERERHZBL4tkoiIiIiIbAKLHyIiIiIisgksfoiIiIiIyCZY5AMPKioq8Mcff8DNzQ0ymczU4RBVI4TA9evXoVarpZe3mgJzhcwZ84SofswTovo1Jk8ssvj5448/4OfnZ+owiOqVl5eH1q1bm2z/zBWyBMwTovoxT4jq15A8scjix83NDUBlB93d3U0cDVF1hYWF8PPzk8aqqTBXyJwxT4jqxzwhql9j8sQii5+q063u7u5MQDJrpr40gLlCloB5QlQ/5glR/RqSJ3zgARERERER2QQWP0REREREZBNY/BARERERkU1g8UNERERERDaBxQ8REREREdkEFj9ERERERGQTWPwQEREREZFNYPFDZGQJCQmQyWSIjo6us116ejqCg4Ph5OSEdu3aYdmyZcYJkIiIiMhKsfghMqLDhw9j+fLl6Nq1a53tcnJyMHToUPTt2xdZWVmYMWMGXnnlFaSkpBgpUiIiIiLrw+KHyEiKiorw9NNPY8WKFfDw8Kiz7bJly9CmTRssWrQInTp1wnPPPYd///vfmDdvnpGiJSIiIrI+LH6IjGTKlCkYNmwYBg4cWG/bgwcPIiIiQm/e4MGDceTIEZSWlta6nk6nQ2Fhod5ERERERJXsTR0ANR+ZTNak9YUQzRQJ3Sk5ORlHjx7F4cOHG9Reo9HA19dXb56vry/Kyspw+fJlqFSqGtdLSEjA7NmzmxwvGUZTc7QpmN9kTE0Z6xyrZEk41i0Pz/wQGVheXh5effVVrF27Fk5OTg1e787/UKv+k6zrP9q4uDhotVppysvLu7ugicjmyWSyu56IiMwVz/wQGVhmZiYKCgoQHBwszSsvL8e+ffuwZMkS6HQ62NnZ6a2jVCqh0Wj05hUUFMDe3h5eXl617ksul0MulzdvB4iIiIisBIsfIgMLDw9Hdna23rx//etfeOCBB/DGG29UK3wAIDQ0FFu2bNGbt2vXLoSEhMDBwcGg8RIRERFZK172RmRgbm5uCAwM1JtcXFzg5eWFwMBAAJWXqz377LPSOpMnT8aFCxcQExOD06dP48svv0RiYiJiY2NN1Q2iZrV06VL06dMHANC6dWuEhoZi+/bt0nIhBOLj46FWq+Hs7Ix+/frh5MmTetvQ6XSIioqCt7c3XFxcMGLECFy8eNGo/SAiulu8tNQ0WPwQmYH8/Hzk5uZKnwMCArBt2zakpaWhe/fueO+99/Dpp59i9OjRJoySqPm0bt0a8fHxAIC0tDQMGDAAjz32mFTgzJ07FwsWLMCSJUtw+PBhKJVKDBo0CNevX5e2ER0djU2bNiE5ORkHDhxAUVERhg8fjvLyclN0iYiILIGwQFqtVgAQWq3W1KGYFQBNmqj5mMsYNZc4qFJTc9Ta8vvO8enh4SG++OILUVFRIZRKpfjwww+ltrdu3RIKhUIsW7ZMCCHEtWvXhIODg0hOTpbaXLp0SbRo0ULs2LGjSXFQJY5V8zB//nwBQLi5uQk3NzfRu3dvsW3bNml5RUWFmDVrllCpVMLJyUmEhYWJEydO6G3j1q1bYurUqcLLy0u0bNlSREZGiry8vEbFwTypGfPEPDRmfPLMDxERmVR5eTmSk5Nx48YNhIaGIicnBxqNRu9dV3K5HGFhYcjIyABQ+SCR0tJSvTZqtRqBgYFSm9rwfVhkSVq1agWg8gzpkSNHeJaUqIlY/BARkUlU/fF27733YvLkydi0aRM6d+4sPemwpnddVS3TaDRwdHSEh4dHrW1qk5CQAIVCIU1+fn7N1SWiZjdkyBAAwP33348OHTrggw8+gKurKw4dOgQhBBYtWoSZM2di1KhRCAwMxKpVq3Dz5k2sX78eAKDVapGYmIj58+dj4MCB6NGjB9auXYvs7Gzs3r3blF0jMgkWP0REZBLt27cHAOzevRsvvfQSJkyYgFOnTknLa3rXVX03+jakDd+HRZbKmGdJeYaUrBWLHyIiMglHR0cAwIMPPoiEhAR069YNn3zyCZRKJQDU+K6rqrNBSqUSJSUluHr1aq1taiOXy+Hu7q43EZk7tVoNuVxutLOkPENK1orFDxERmQUhBHQ6HQICAqBUKpGamiotKykpQXp6uvR47ODgYDg4OOi1yc/Px4kTJ6Q2RNZk//79OHTokNHOkvIMKVkrvuSUiIiMbsaMGXjkkUcAVN778/333yMtLQ07duyATCZDdHQ05syZg/bt26N9+/aYM2cOWrZsiXHjxgEAFAoFJk2ahGnTpsHLywuenp6IjY1FUFAQBg4caMquERnEfffdB3d3d4SEhODw4cP45JNP8MYbbwCoPLujUqmktrWdJb397E9BQUGdBwrkcjnkcrmBekNkOjzzY2b4wisisgV//vknXnzxRQDAiBEj8NNPP2HHjh0YNGgQAGD69OmIjo7Gyy+/jJCQEFy6dAm7du2Cm5ubtI2FCxdi5MiRGDNmDB566CG0bNkSW7ZsgZ2dnUn6RGQsPEtKdPd45oeIiIwuMTERhYWFUCgU+O2336rddyOTyRAfHy+9CLUmTk5OWLx4MRYvXmzgaIlMZ/bs2QCACxcuAACSk5N5lpSoCVj8EBEREZmpgoICAEBISAgUCgW6du1a7SxpcXExXn75ZVy9ehW9evWq8Sypvb09xowZg+LiYoSHhyMpKYlnSckmyYQQwtRBNFbV0UKtVmt1T+kx5eVrFjgUzJa5jFFziYMqMb/1mcv4NJc4zI2pxqs5jlVTMpfxaS5xmBvmiXlozPjkPT9ERERERGQTWPwQEREREZFNYPFDREREREQ2gcUPERERERHZBBY/RERERERkE1j8EBERERGRTWDxQ0RERERENoHFDxERERER2QQWP0REREREZBNY/BARERERkU1g8UNERERERDahUcVPQkICevbsCTc3N/j4+GDkyJE4e/asXpuJEydCJpPpTb1799Zro9PpEBUVBW9vb7i4uGDEiBG4ePFi03tDRERERERUi0YVP+np6ZgyZQoOHTqE1NRUlJWVISIiAjdu3NBr9+ijjyI/P1+atm3bprc8OjoamzZtQnJyMg4cOICioiIMHz4c5eXlTe8RERERERFRDewb03jHjh16n1euXAkfHx9kZmbikUcekebL5XIolcoat6HVapGYmIg1a9Zg4MCBAIC1a9fCz88Pu3fvxuDBgxvbByIiIiIiono16Z4frVYLAPD09NSbn5aWBh8fH3To0AHPP/88CgoKpGWZmZkoLS1FRESENE+tViMwMBAZGRk17ken06GwsFBvIiIiIiIiaoy7Ln6EEIiJicHDDz+MwMBAaf6QIUOwbt067NmzB/Pnz8fhw4cxYMAA6HQ6AIBGo4GjoyM8PDz0tufr6wuNRlPjvhISEqBQKKTJz8/vbsMmIiIiIiIbddfFz9SpU3H8+HF89dVXevPHjh2LYcOGITAwEJGRkdi+fTt++eUXbN26tc7tCSEgk8lqXBYXFwetVitNeXl5dxs2kUksXboUXbt2hbu7O9zd3REaGort27fX2j4tLa3ag0NkMhnOnDljxKiJiIiIrEuj7vmpEhUVhe+++w779u1D69at62yrUqng7++Pc+fOAQCUSiVKSkpw9epVvbM/BQUF6NOnT43bkMvlkMvldxMqkVlo3bo1PvzwQ9x///0AgFWrVuGxxx5DVlYWunTpUut6Z8+ehbu7u/T53nvvNXisRERERNaqUWd+hBCYOnUqNm7ciD179iAgIKDeda5cuYK8vDyoVCoAQHBwMBwcHJCamiq1yc/Px4kTJ2otfogsXWRkJIYOHYoOHTqgQ4cO+OCDD+Dq6opDhw7VuZ6Pjw+USqU02dnZGSliIiIiIuvTqOJnypQpWLt2LdavXw83NzdoNBpoNBoUFxcDAIqKihAbG4uDBw/i/PnzSEtLQ2RkJLy9vfH4448DABQKBSZNmoRp06bhhx9+QFZWFp555hkEBQVJT38jsmbl5eVITk7GjRs3EBoaWmfbHj16QKVSITw8HHv37q1323w4CBEREVHtGnXZ29KlSwEA/fr105u/cuVKTJw4EXZ2dsjOzsbq1atx7do1qFQq9O/fHxs2bICbm5vUfuHChbC3t8eYMWNQXFyM8PBwJCUl8ag2WbXs7GyEhobi1q1bcHV1xaZNm9C5c+ca26pUKixfvhzBwcHQ6XRYs2YNwsPDkZaWpvdY+TslJCRg9uzZhuoCERERkUWTCSGEqYNorMLCQigUCmi1Wr37IaxBbQ99MAYLHApmq6YxWlJSgtzcXFy7dg0pKSn44osvkJ6eXmsBdKfIyEjIZDJ89913tbbR6XTSkxWr4vDz87PKXLFEzG995vJ/ubnEYW5MNV7NcayakrmMT3OJw9wwT8xDY8bnXT3wgIgaz9HRUXrgQUhICA4fPoxPPvkE//nPfxq0fu/evbF27do62/DhIERERES1a9JLTono7gkh9M7S1CcrK0t6cAgRERERNR7P/BAZwYwZMzBkyBD4+fnh+vXrSE5ORlpaGnbs2AGg8l1Wly5dwurVqwEAixYtQtu2bdGlSxeUlJRg7dq1SElJQUpKiim7QURERGTRWPwQGcGff/6J8ePHIz8/HwqFAl27dsWOHTswaNAgAJWPe8/NzZXal5SUIDY2FpcuXYKzszO6dOmCrVu3YujQoabqAhEREZHFY/FDZASJiYl1Lk9KStL7PH36dEyfPt2AERERERHZHt7zQ0RERERENoHFDxERERER2QQWP0REREREZBNY/BARERERkU1g8UNERERERDaBxQ8REREREdkEFj9ERERERGQTWPwQEREREZFNYPFDRERGl5CQgH79+gEA7rvvPowcORJnz57VazNx4kTIZDK9qXfv3nptdDodoqKi4O3tDRcXF4wYMQIXL140VjeIiMjCsPghIiKjS09Px/PPPw8A2Lx5M8rKyhAREYEbN27otXv00UeRn58vTdu2bdNbHh0djU2bNiE5ORkHDhxAUVERhg8fjvLycqP1hciQ5s+fDwBo1aoVfHx8eKCAqIlY/BARkdHt2LEDTz/9NAAgKCgIK1euRG5uLjIzM/XayeVyKJVKafL09JSWabVaJCYmYv78+Rg4cCB69OiBtWvXIjs7G7t376513zqdDoWFhXoTkbn68ccfAQC7d+9GamoqDxQQNRGLHyIiMjmtVgsAesUNAKSlpcHHxwcdOnTA888/j4KCAmlZZmYmSktLERERIc1Tq9UIDAxERkZGrftKSEiAQqGQJj8/v2buDVHz2bhxIwCgU6dO6Natm1EPFBBZIxY/RERkUkIIxMTE4OGHH0ZgYKA0f8iQIVi3bh327NmD+fPn4/DhwxgwYAB0Oh0AQKPRwNHRER4eHnrb8/X1hUajqXV/cXFx0Gq10pSXl2eYjhEZgLEOFPAMKVkre1MHQEREti02NhbHjx/HgQMH9OaPHTtW+ndgYCBCQkLg7++PrVu3YtSoUbVuTwgBmUxW63K5XA65XN70wImMrK4DBU8++ST8/f2Rk5ODt99+GwMGDEBmZibkcvldHShISEjA7NmzDdofIlPgmR8iIjKp7du3Y+/evWjdunWd7VQqFfz9/XHu3DkAgFKpRElJCa5evarXrqCgAL6+vgaLl8hUpk6diuPHj+Orr77Smz927FgMGzYMgYGBiIyMxPbt2/HLL79g69atdW6vrgMFPENK1orFDxERGZ0QArGxsQCALVu2ICAgoN51rly5gry8PKhUKgBAcHAwHBwckJqaKrXJz8/HiRMn0KdPH8METmQir7/+Or777jujHSiQy+Vwd3fXm4isAYsfIiIyuilTpuDrr78GALi6ukKj0UCj0aC4uBgAUFRUhNjYWBw8eBDnz59HWloaIiMj4e3tjccffxwAoFAoMGnSJEybNg0//PADsrKy8MwzzyAoKAgDBw40Wd+ImpMQAkDlQYI9e/bwQAFRE/GeHyIiMrqlS5dK/+7QoYP075UrV2LixImws7NDdnY2Vq9ejWvXrkGlUqF///7YsGED3NzcpPYLFy6Evb09xowZg+LiYoSHhyMpKQl2dnZG7Q+RoUybNg0A8MUXX8DNzU26R0ehUMDZ2RlFRUWIj4/H6NGjoVKpcP78ecyYMaPWAwVeXl7w9PREbGwsDxSQTZKJqkMKFqSwsBAKhQJardbqTsPWdZOuoVngUDBb5jJGzSUOqsT81mcu49Nc4jA3phqv5jhWTam230PVgYLi4mKMHDkSWVlZegcK3nvvPb3HuN+6dQuvv/461q9fLx0o+Pzzzxv8qHfmSc2YJ+ahMeOTZ36IiIiIzJRWq63zjzpnZ2fs3Lmz3u04OTlh8eLFWLx4sSHCJLIYvOeHiIiIiIhsAosfIiIiIiKyCSx+iIiIiIjIJvCeH5I05aY93nhHREREROaOZ36IiIiIiMgmsPghIiIiIiKbwOKHyAiWLl2Krl27wt3dHe7u7ggNDcX27dvrXCc9PR3BwcFwcnJCu3btsGzZMiNFS0RERGSdWPwQGUHr1q3x4Ycf4siRIzhy5AgGDBiAxx57DCdPnqyxfU5ODoYOHYq+ffsiKysLM2bMwCuvvIKUlBQjR05ERERkPfjAAyIjiIyM1Pv8wQcfYOnSpTh06BC6dOlSrf2yZcvQpk0bLFq0CADQqVMnHDlyBPPmzcPo0aONETIRERGR1eGZHyIjKy8vR3JyMm7cuIHQ0NAa2xw8eBARERF68wYPHowjR46gtLS01m3rdDoUFhbqTURERERUicUPkZFkZ2fD1dUVcrkckydPxqZNm9C5c+ca22o0Gvj6+urN8/X1RVlZGS5fvlzrPhISEqBQKKTJz8+vWftAREREZMlY/BAZSceOHXHs2DEcOnQIL730EiZMmIBTp07V2v7O9y5VvUuprvcxxcXFQavVSlNeXl7zBE9ERERkBXjPD5GRODo64v777wcAhISE4PDhw/jkk0/wn//8p1pbpVIJjUajN6+goAD29vbw8vKqdR9yuRxyubx5AyciIiKyEjzzQ2QiQgjodLoal4WGhiI1NVVv3q5duxASEgIHBwdjhEdERERkdVj8EBnBjBkzsH//fpw/fx7Z2dmYOXMm0tLS8PTTTwOovFzt2WefldpPnjwZFy5cQExMDE6fPo0vv/wSiYmJiI2NNVUXiIiIiCweL3sjMoI///wT48ePR35+PhQKBbp27YodO3Zg0KBBAID8/Hzk5uZK7QMCArBt2za89tpr+Oyzz6BWq/Hpp5/yMddERERETdCoMz8JCQno2bMn3Nzc4OPjg5EjR+Ls2bN6bYQQiI+Ph1qthrOzM/r161ftRY46nQ5RUVHw9vaGi4sLRowYgYsXLza9N0RmKjExEefPn4dOp0NBQQF2794tFT4AkJSUhLS0NL11wsLCcPToUeh0OuTk5GDy5MlGjpqIiIjIujSq+ElPT8eUKVNw6NAhpKamoqysDBEREbhx44bUZu7cuViwYAGWLFmCw4cPQ6lUYtCgQbh+/brUJjo6Gps2bUJycjIOHDiAoqIiDB8+HOXl5c3XMyIiIiIiots06rK3HTt26H1euXIlfHx8kJmZiUceeQRCCCxatAgzZ87EqFGjAACrVq2Cr68v1q9fjxdffBFarRaJiYlYs2YNBg4cCABYu3Yt/Pz8sHv3bgwePLiZukZERERERPQ/TXrggVarBQB4enoCAHJycqDRaPTeTC+XyxEWFoaMjAwAQGZmJkpLS/XaqNVqBAYGSm3uxLfWExERERFRU9118SOEQExMDB5++GEEBgYCgPRekpreTF+1TKPRwNHRER4eHrW2uRPfWk9ERERERE1118XP1KlTcfz4cXz11VfVltX0Zvq63kpfXxu+tZ6IiIiIiJrqroqfqKgofPfdd9i7dy9at24tzVcqlQBQ45vpq84GKZVKlJSU4OrVq7W2uZNcLoe7u7veRERERERE1BiNKn6EEJg6dSo2btyIPXv2ICAgQG95QEAAlEql3pvpS0pKkJ6ejj59+gAAgoOD4eDgoNcmPz8fJ06ckNoQERERERE1t0Y97W3KlClYv349vv32W7i5uUlneBQKBZydnSGTyRAdHY05c+agffv2aN++PebMmYOWLVti3LhxUttJkyZh2rRp8PLygqenJ2JjYxEUFCQ9/Y2IiIiIiKi5Nar4Wbp0KQCgX79+evNXrlyJiRMnAgCmT5+O4uJivPzyy7h69Sp69eqFXbt2wc3NTWq/cOFC2NvbY8yYMSguLkZ4eDiSkpJgZ2fXtN4QERERERHVQiaEEKYOorEKCwuhUCig1Wqt7v6f+h4MYa4scBgZlLmMUXOJgyqZMr/NMUfNZXyaSxzmxlTj1RzHqimZy/g0lzjMDfPEPDRmfDbpPT9ERERERESWgsUPERERERHZBBY/RERERERkE1j8EBERERGRTWDxQ0RERERENoHFDxERERER2QQWP0REREREZBNY/BARERERkU1g8UNEREaXkJCAfv36AQDuu+8+jBw5EmfPntVrI4RAfHw81Go1nJ2d0a9fP5w8eVKvjU6nQ1RUFLy9veHi4oIRI0bg4sWLxuoGERFZGBY/BiCTye56IiKyBenp6Xj++ecBAJs3b0ZZWRkiIiJw48YNqc3cuXOxYMECLFmyBIcPH4ZSqcSgQYNw/fp1qU10dDQ2bdqE5ORkHDhwAEVFRRg+fDjKy8uN3iciIjJ/LH6IiMjoduzYgaeffhoAEBQUhJUrVyI3NxeZmZkAKs/6LFq0CDNnzsSoUaMQGBiIVatW4ebNm1i/fj0AQKvVIjExEfPnz8fAgQPRo0cPrF27FtnZ2di9e7fJ+kbUnObPnw8AaNWqFXx8fHiWlKiJWPwQEZHJabVaAICnpycAICcnBxqNBhEREVIbuVyOsLAwZGRkAAAyMzNRWlqq10atViMwMFBqUxOdTofCwkK9ichc/fjjjwCA3bt3IzU1lWdJiZqIxQ8REZmUEAIxMTF4+OGHERgYCADQaDQAAF9fX722vr6+0jKNRgNHR0d4eHjU2qYmCQkJUCgU0uTn59ec3SFqVhs3bgQAdOrUCd26dTPaWVIeJCBrxeKHiIhMKjY2FsePH8dXX31Vbdmd90IKIeq9P7K+NnFxcdBqtdKUl5d3d4ETmYCxzpLyIAFZKxY/RERkUtu3b8fevXvRunVraZ5SqQSAamdwCgoKpLNBSqUSJSUluHr1aq1taiKXy+Hu7q43EVkCY54l5UECslYsfoiMICEhAT179oSbm1utN6zeKS0trcYnAp45c8ZIURMZjhACsbGxAIAtW7YgICBAb3lAQACUSiVSU1OleSUlJUhPT0efPn0AAMHBwXBwcNBrk5+fjxMnTkhtiKzJ1KlTjXaWlAcJyFrZmzoAIluQnp6OKVOmoGfPnigrK8PMmTMRERGBU6dOwcXFpc51z549q/elc++99xo6XCKDmzJlCr7++msAgKurq3T0WaFQwNnZGTKZDNHR0ZgzZw7at2+P9u3bY86cOWjZsiXGjRsntZ00aRKmTZsGLy8veHp6IjY2FkFBQRg4cKDJ+kZkCK+//jq2bduGffv21XqWVKVSSfNrO0t6+9mfgoICHiggm8Pih8gIduzYofd55cqV8PHxQWZmJh555JE61/Xx8cE999xjwOiIjG/p0qXSvzt06CD9e+XKlZg4cSIAYPr06SguLsbLL7+Mq1evolevXti1axfc3Nyk9gsXLoS9vT3GjBmD4uJihIeHIykpCXZ2dkbrC5EhCSEAVJ4hTU9Pr/MsaY8ePQD87yzpRx99BED/LOmYMWMA/O8s6dy5c43YGyLTY/FDZAJ33rBalx49euDWrVvo3Lkz3nrrLfTv37/WtjqdDjqdTvrMp/OQuRJCoLCwEAqFAlqttsZLamQyGeLj4xEfH1/rdpycnLB48WIsXrzYgNESmc60adMAAF988QXc3Nx4lpSoiVj8EBlZTTes1kSlUmH58uUIDg6GTqfDmjVrEB4ejrS0tFrPFiUkJGD27NmGCp2IiIwsMTERADBs2DC9+TxLSnR3ZKLqfKoFqe9ooanVd4OhNbLAYWRQdY3RKVOmYOvWrThw4IDeddsNERkZCZlMhu+++67G5TWd+fHz8zPbXLE1pvy/wRxz1Fz+LzeXOMyNqcarOY5VUzKX8WkucZgb5ol5aMz45NPeiIwoKioK3333XbXH+jZU7969ce7cuVqX8+k8RERERLXjZW9ERiCEQFRUFDZt2oS0tLRqN6w2VFZWlt7TfIiIiIio4Vj8EBnBlClTsH79enz77bc13rAKVL5Q7tKlS1i9ejUAYNGiRWjbti26dOmCkpISrF27FikpKUhJSTFZP4iIiIgsGYsfIiOoeqxvv3799ObffsNqfn4+cnNzpWUlJSWIjY3FpUuX4OzsjC5dumDr1q0YOnSoscImIjK6pt5DwXshiKguLH6IjKAhX8ZJSUl6n6dPn47p06cbKCIiIiKyVDxIcPf4wAMiIiIiIrIJLH6IiIiIiMgmsPghIiIiIiKbwHt+iIiIrJAtvnCbiKg+LH6IiIiIyCbxIIHt4WVvRERERERkE1j8EBERERGRTWDxQ0RERERENoHFDxERERER2QQWP0REREREZBNY/BARERERkU1g8UNERERERDaBxQ8REREREdkEFj9ERERERGQTWPwQEREREZFNYPFDREREREQ2odHFz759+xAZGQm1Wg2ZTIbNmzfrLZ84cSJkMpne1Lt3b702Op0OUVFR8Pb2houLC0aMGIGLFy82qSNERERERER1aXTxc+PGDXTr1g1Lliyptc2jjz6K/Px8adq2bZve8ujoaGzatAnJyck4cOAAioqKMHz4cJSXlze+B0RERERERA1g39gVhgwZgiFDhtTZRi6XQ6lU1rhMq9UiMTERa9aswcCBAwEAa9euhZ+fH3bv3o3BgwdXW0en00Gn00mfCwsLGxs2ERERERHZOIPc85OWlgYfHx906NABzz//PAoKCqRlmZmZKC0tRUREhDRPrVYjMDAQGRkZNW4vISEBCoVCmvz8/AwRNhERERERWbFmL36GDBmCdevWYc+ePZg/fz4OHz6MAQMGSGduNBoNHB0d4eHhobeer68vNBpNjduMi4uDVquVpry8vOYOm4iIiIiIrFyjL3urz9ixY6V/BwYGIiQkBP7+/ti6dStGjRpV63pCCMhkshqXyeVyyOXy5g6ViIiIiIhsiMEfda1SqeDv749z584BAJRKJUpKSnD16lW9dgUFBfD19TV0OEREREREZKMMXvxcuXIFeXl5UKlUAIDg4GA4ODggNTVVapOfn48TJ06gT58+hg6HiIiIiIhsVKMveysqKsKvv/4qfc7JycGxY8fg6ekJT09PxMfHY/To0VCpVDh//jxmzJgBb29vPP744wAAhUKBSZMmYdq0afDy8oKnpydiY2MRFBQkPf2NiIiIiIiouTW6+Dly5Aj69+8vfY6JiQEATJgwAUuXLkV2djZWr16Na9euQaVSoX///tiwYQPc3NykdRYuXAh7e3uMGTMGxcXFCA8PR1JSEuzs7JqhS0RERERERNU1+rK3fv36QQhRbUpKSoKzszN27tyJgoIClJSU4MKFC0hKSqr2aGonJycsXrwYV65cwc2bN7FlyxY+vpqsWkJCAnr27Ak3Nzf4+Phg5MiROHv2bL3rpaenIzg4GE5OTmjXrh2WLVtmhGiJiIiIrJPB7/khosoiZsqUKTh06BBSU1NRVlaGiIgI3Lhxo9Z1cnJyMHToUPTt2xdZWVmYMWMGXnnlFaSkpBgxciIiIiLr0eyPuiai6nbs2KH3eeXKlfDx8UFmZiYeeeSRGtdZtmwZ2rRpg0WLFgEAOnXqhCNHjmDevHkYPXq0oUMmIiIisjo880NkAlqtFgDg6elZa5uDBw8iIiJCb97gwYNx5MgRlJaW1riOTqdDYWGh3kRERERElVj8ULOQyWR3PdkaIQRiYmLw8MMPIzAwsNZ2Go2m2ruvfH19UVZWhsuXL9e4TkJCAhQKhTSZ8710phozTdlvUydLZag+//jjjwCAjh07QiaTYfPmzXrLJ06cWG17vXv31muj0+kQFRUFb29vuLi4YMSIEbh48WKz9p+IiKwHix8iI5s6dSqOHz+Or776qt62d/7xKISocX6VuLg4aLVaacrLy2t6wEQGcvPmTQDAxx9/XGubRx99FPn5+dK0bds2veXR0dHYtGkTkpOTceDAARQVFWH48OEoLy83aOxExsKDBETNi8UPkRFFRUXhu+++w969e9G6des62yqVSmg0Gr15BQUFsLe3h5eXV43ryOVyuLu7601E5mrQoEEAgBEjRtTaRi6XQ6lUStPtl4pqtVokJiZi/vz5GDhwIHr06IG1a9ciOzsbu3fvNnj8RMbAgwREzYvFD5ERCCEwdepUbNy4EXv27EFAQEC964SGhiI1NVVv3q5duxASEgIHBwdDhUpkVtLS0uDj44MOHTrg+eefR0FBgbQsMzMTpaWlevfGqdVqBAYGIiMjo9Zt8t44siQ8SEDUvFj8EBnBlClTsHbtWqxfvx5ubm7QaDTQaDQoLi6W2sTFxeHZZ5+VPk+ePBkXLlxATEwMTp8+jS+//BKJiYmIjY01RReIjG7IkCFYt24d9uzZg/nz5+Pw4cMYMGAAdDodgMr74hwdHeHh4aG3nq+vb7WzprezpHvjiBqCBwmIGo7FD5ERLF26FFqtFv369YNKpZKmDRs2SG3y8/ORm5srfQ4ICMC2bduQlpaG7t2747333sOnn37Kx1yTzRg7diyGDRuGwMBAREZGYvv27fjll1+wdevWOtcTQtT5sAXeG0fWhAcJiBqH7/khMoKqBxXUJSkpqdq8sLAwHD161AAREVkelUoFf39/nDt3DkDlfXElJSW4evWq3h92BQUF6NOnT63bkcvlkMvlBo+XyBjGjh0r/TswMBAhISHw9/fH1q1bMWrUqFrXa8hBgpiYGOlzYWEhCyCyCjzzQ0REFuHKlSvIy8uDSqUCAAQHB8PBwUHv3rj8/HycOHGizuKHyJrVdZDgdgUFBdVep3A7PkCHrBWLHyIiMomioiIAwPHjxwEAOTk5OHbsGHJzc1FUVITY2FgcPHgQ58+fR1paGiIjI+Ht7Y3HH38cAKBQKDBp0iRMmzYNP/zwA7KysvDMM88gKCgIAwcONFm/iEyJBwmI6sbL3oiIyCSysrIAAH379gUA6RKbCRMmYOnSpcjOzsbq1atx7do1qFQq9O/fHxs2bICbm5u0jYULF8Le3h5jxoxBcXExwsPDkZSUBDs7O+N3iMgAajtI4OnpCU9PT8THx2P06NFQqVQ4f/48ZsyYUetBAi8vL3h6eiI2NpYHCchmsfghIiKTqCp6tFptjZfU7Ny5s95tODk5YfHixVi8eHGzx0dkDniQgKh5sfghIiIiMlM8SEDUvHjPDxERERER2QQWP0REREREZBNY/BARERERkU1g8UNERERERDaBxQ8REREREdkEFj9ERERERGQTWPwQEREREZFNYPFDREREREQ2gcUPERERERHZBBY/RERERERkE1j8EBERERGRTWDxQ0RERERENoHFDxERERER2QQWP0REREREZBNY/BARERERkU2wN3UAREREVDOZTGbqEIiIrAqLHyIiIiKyWDxIQI3By96IiIiIiMgm8MxPDXgEgYiIiIjI+vDMDxERERER2QQWP0REREREZBNY/BAZwb59+xAZGQm1Wg2ZTIbNmzfX2T4tLQ0ymazadObMGeMETERERGSFeM8PkRHcuHED3bp1w7/+9S+MHj26weudPXsW7u7u0ud7773XEOERERER2QQWP0RGMGTIEAwZMqTR6/n4+OCee+5p/oCIiIiIbBAveyMyYz169IBKpUJ4eDj27t1bb3udTofCwkK9iYiIiIgqsfghMkMqlQrLly9HSkoKNm7ciI4dOyI8PBz79u2rc72EhAQoFApp8vPzM1LEREREROav0cVPfTduCyEQHx8PtVoNZ2dn9OvXDydPntRro9PpEBUVBW9vb7i4uGDEiBG4ePFikzpCZE06duyI559/Hg8++CBCQ0Px+eefY9iwYZg3b16d68XFxUGr1UpTXl6ekSImIiIiMn+NLn6qbtxesmRJjcvnzp2LBQsWYMmSJTh8+DCUSiUGDRqE69evS22io6OxadMmJCcn48CBAygqKsLw4cNRXl5+9z0hsnK9e/fGuXPn6mwjl8vh7u6uNxERERFRpUY/8KCuG7eFEFi0aBFmzpyJUaNGAQBWrVoFX19frF+/Hi+++CK0Wi0SExOxZs0aDBw4EACwdu1a+Pn5Yffu3Rg8eHATukNkvbKysqBSqUwdBhEREZHFatanveXk5ECj0SAiIkKaJ5fLERYWhoyMDLz44ovIzMxEaWmpXhu1Wo3AwEBkZGTUWPzodDrodDrpM2/iJktTVFSEX3/9Vfqck5ODY8eOwdPTE23atEFcXBwuXbqE1atXAwAWLVqEtm3bokuXLigpKcHatWuRkpKClJQUU3WBiIiIyOI1a/Gj0WgAAL6+vnrzfX19ceHCBamNo6MjPDw8qrWpWv9OCQkJmD17dnOGSmRUR44cQf/+/aXPMTExAIAJEyYgKSkJ+fn5yM3NlZaXlJQgNjYWly5dgrOzM7p06YKtW7di6NChRo+diIiIyFoY5D0/MplM77MQotq8O9XVJi4uTvpjEag888OnWJEl6devH4QQtS5PSkrS+zx9+nRMnz7dwFERERER2ZZmfdS1UqkEgGpncAoKCqSzQUqlEiUlJbh69Wqtbe7Em7iJiMhSyWSyu56IbAXzhIylWYufgIAAKJVKpKamSvNKSkqQnp6OPn36AACCg4Ph4OCg1yY/Px8nTpyQ2hARERERETW3Rl/2Vt+N29HR0ZgzZw7at2+P9u3bY86cOWjZsiXGjRsHAFAoFJg0aRKmTZsGLy8veHp6IjY2FkFBQdLT34iIiIiIiJpbo4uf+m7cnj59OoqLi/Hyyy/j6tWr6NWrF3bt2gU3NzdpnYULF8Le3h5jxoxBcXExwsPDkZSUBDs7u2boEhERERERUXWNvuyt6sbtO6eqG7ZlMhni4+ORn5+PW7duIT09HYGBgXrbcHJywuLFi3HlyhXcvHkTW7Zs4QMMiIhszI8//ggA6NixI2QyGTZv3qy3XAiB+Ph4qNVqODs7o1+/fjh58qReG51Oh6ioKHh7e8PFxQUjRozAxYsXjdUFIoNjnhA1r2a954eIiKihbt68CQD4+OOPa1w+d+5cLFiwAEuWLMHhw4ehVCoxaNAgXL9+XWoTHR2NTZs2ITk5GQcOHEBRURGGDx+O8vJyo/SByNCYJ0TNTFggrVYrAAitVmuQ7QPgZMTJGhl6jFpaHDUx1Zgx9Xi3xDwz1H5vH58AxKZNm6RlFRUVQqlUig8//FCad+vWLaFQKMSyZcuEEEJcu3ZNODg4iOTkZKnNpUuXRIsWLcSOHTtq3e+tW7eEVquVpry8PIPmial/97Y2WRtT5UldcRiCqceNrU3WpjHjk2d+iIjI7OTk5ECj0SAiIkKaJ5fLERYWhoyMDABAZmYmSktL9dqo1WoEBgZKbWqSkJAAhUIhTbzsmiyVIfNEp9OhsLBQbyKyBix+iIjI7FS9L+7O97/5+vpKyzQaDRwdHeHh4VFrm5rExcVBq9VKU15eXjNHT2QchswTHiQga8Xih4iIzNadLzAUQtT7UsP62vDF2WRtDJEnPEhA1orFDxERmR2lUgkA1Y5MFxQUSEe5lUolSkpKcPXq1VrbEFkzQ+YJDxKQtWLxQ0REZicgIABKpRKpqanSvJKSEqSnp6NPnz4AgODgYDg4OOi1yc/Px4kTJ6Q2RNaMeULUeI1+ySkREVFzKCoqAgAcP34cQOXN28eOHYOnpyfatGmD6OhozJkzB+3bt0f79u0xZ84ctGzZEuPGjQMAKBQKTJo0CdOmTYOXlxc8PT0RGxuLoKAgDBw40GT9ImpOzBOiZmbgJ88ZBB+3aF2TNTKXR0ybSxw1MdWYMfV4t8Q8M9R+v//++xrXmTBhghCi8jG+s2bNEkqlUsjlcvHII4+I7OxsvW0UFxeLqVOnCk9PT+Hs7CyGDx8ucnNzG9U/fqdY12RtmCecmCf1a8z4lAkhBCxMYWEhFAoFtFqtQa5Bre8mQWpeFjgE62XoMWppcdSkKXnWlDFjq/ltqp9ZXfs1l/HJ7xTrYm3fKcwTMgRbzhPe80NERERERDaBxQ8REREREdkEFj9ERERERGQTWPwQEREREZFN4KOuyeSaepOjtd20R0RERESGwTM/RERERERkE1j8EBERERGRTWDxQ0RERERENoHFDxERERER2QQWP0REREREZBNY/BAZwb59+xAZGQm1Wg2ZTIbNmzfXu056ejqCg4Ph5OSEdu3aYdmyZYYPlIiIiMiKsfghMoIbN26gW7duWLJkSYPa5+TkYOjQoejbty+ysrIwY8YMvPLKK0hJSTFwpERERETWi+/5ITKCIUOGYMiQIQ1uv2zZMrRp0waLFi0CAHTq1AlHjhzBvHnzMHr0aANFSURERGTdeOaHyAwdPHgQERERevMGDx6MI0eOoLS0tNb1dDodCgsL9SYiIiIiqsTih8gMaTQa+Pr66s3z9fVFWVkZLl++XOt6CQkJUCgU0uTn51fnfmQymcmmpjDVfomIiMiysfghi2etfwjfGZ8Qosb5t4uLi4NWq5WmvLw8g8ZIRGRurPU7gYiaB+/5ITJDSqUSGo1Gb15BQQHs7e3h5eVV63pyuRxyudzQ4RERERFZJBY/RGYoNDQUW7Zs0Zu3a9cuhISEwMHBwURRERERkTVoypnOqitRLBUveyMygqKiIhw7dgzHjh0DUPko62PHjiE3NxdA5eVqzz77rNR+8uTJuHDhAmJiYnD69Gl8+eWXSExMRGxsrCnCJyIiIrIKPPNDZARHjhxB//79pc8xMTEAgAkTJiApKQn5+flSIQQAAQEB2LZtG1577TV89tlnUKvV+PTTT/mYayIiIqImYPFDZAT9+vWr8zRxUlJStXlhYWE4evSoAaMiIiIisi287I2IiIiIiGwCix8iIiIiIrIJLH6IiIiIiMgmsPghIiIiIiKbwOKHiIiIiIhsAosfIiIiIiKyCSx+iIiIiIjIJvA9P0REREQAZDLZXa9b17vciKyJpecJz/wQEREREZFNYPFDREREREQ2odmLn/j4eMhkMr1JqVRKy4UQiI+Ph1qthrOzM/r164eTJ082dxhERERERER6DHLmp0uXLsjPz5em7OxsadncuXOxYMECLFmyBIcPH4ZSqcSgQYNw/fp1Q4RCREREREQEwEDFj729PZRKpTTde++9ACrP+ixatAgzZ87EqFGjEBgYiFWrVuHmzZtYv369IUIhIiIiIiICYKDi59y5c1Cr1QgICMA///lP/P777wCAnJwcaDQaRERESG3lcjnCwsKQkZFR6/Z0Oh0KCwv1JiIiIiIiosZo9uKnV69eWL16NXbu3IkVK1ZAo9GgT58+uHLlCjQaDQDA19dXbx1fX19pWU0SEhKgUCikyc/Pr7nDJiIiIiIiK9fsxc+QIUMwevRoBAUFYeDAgdi6dSsAYNWqVVKbO58PLoSo85nhcXFx0Gq10pSXl9fcYRMRkZnhA3SIiKi5GfxR1y4uLggKCsK5c+ekL607z/IUFBRUOxt0O7lcDnd3d72JiIisHx+gQ1Q3HiQgahyDFz86nQ6nT5+GSqVCQEAAlEolUlNTpeUlJSVIT09Hnz59DB0KERFZGD5Ah6h+PEhA1HDNXvzExsYiPT0dOTk5+Omnn/DEE0+gsLAQEyZMgEwmQ3R0NObMmYNNmzbhxIkTmDhxIlq2bIlx48Y1dyhERGThmvsBOgAfokPWxxAHCZgnZK2avfi5ePEinnrqKXTs2BGjRo2Co6MjDh06BH9/fwDA9OnTER0djZdffhkhISG4dOkSdu3aBTc3t+YOhYiILJghHqAD8CE6ZH0McZCAeULWSiaEEKYOorEKCwuhUCig1WoNcv9PXQ9fIOtiqOFv6DHaXHFwrNuOpoz1poyTuvbb2Dy5ceMG7rvvPkyfPh29e/fGQw89hD/++AMqlUpq8/zzzyMvLw87duyodTs6nQ46nU4vDj8/P36nUJOY6vtk+/btuHnzJjp06IA///wT77//Ps6cOYOTJ0/i7NmzeOihh3Dp0iWo1WppnRdeeAEXLlzAzp07a90v84QMwRz+7rI3SARERETN7PYH6IwcORJA5QN0bi9+6nuADlB55FsulxsyVCKjGTJkiPTvoKAghIaG4r777sOqVavQu3dvAI1/yi7APCHrZfAHHhARETUHPkCHqH7N8ZRdImvG4oeIiMwSH6BD1Hg8SEBUN172RkREZqnqATqXL1/Gvffei969e1d7gE5xcTFefvllXL16Fb169eIDdMjmxMbGIjIyEm3atEFBQQHef//9Gg8StG/fHu3bt8ecOXN4kIBsGosfIiIyS8nJyXUul8lkiI+PR3x8vHECIjJDPEhA1Di87I3IiD7//HMEBATAyckJwcHB2L9/f61t09LSqr21WyaT4cyZM0aMmIiIzFlycjL++OMPlJSU4NKlS0hJSUHnzp2l5VUHCfLz83Hr1i2kp6cjMDDQhBETmRaLHyIj2bBhA6KjozFz5kxkZWWhb9++GDJkCHJzc+tc7+zZs3pv7m7fvr2RIiYiIiKyLix+iIxkwYIFmDRpEp577jl06tQJixYtgp+fH5YuXVrnej4+Pnpv7razszNSxERERETWhcUPkRGUlJQgMzNT7y3bABAREVHvW7Z79OgBlUqF8PBw7N27t862Op0OhYWFehMRERERVWLxQ2QEly9fRnl5ebX3Kvj6+lZ7/0IVlUqF5cuXIyUlBRs3bkTHjh0RHh6Offv21bqfhIQEKBQKafLz82vWfhARERFZMj7tjciIGvOW7Y4dO6Jjx47S59DQUOTl5WHevHl45JFHalwnLi4OMTEx0ufCwkIWQERERET/H8/8EBmBt7c37OzsmvyW7d69e+PcuXO1LpfL5XB3d9ebiIiIiKgSix8iI3B0dERwcLDeW7YBIDU1tVFv2c7KyoJKpWru8IiIiIhsAi97IzKSmJgYjB8/HiEhIQgNDcXy5cuRm5uLyZMnA6i8ZO3SpUtYvXo1AGDRokVo27YtunTpgpKSEqxduxYpKSlISUkxZTeIiIiILBaLHyIjGTt2LK5cuYJ3330X+fn5CAwMxLZt26S3cOfn5+u986ekpASxsbG4dOkSnJ2d0aVLF2zduhVDhw41VReIiIiILJpMCCFMHURjFRYWQqFQQKvVGuSehtpuQCe6XV2pY+gx2lD1xcGxbjua8l99U8aJNeRJUzHPbIOh/pxinpA1MYc84T0/RERERERkE1j8EBERERGRTWDxQ0RERERENoHFDxERERER2QQWP0REREREZBNY/BARERERkU1g8UNERERERDbBal9yyufFExFRc+D3CVHDMFfIEvDMDxERERER2QQWP0REREREZBNY/BARERERkU2w2nt+iIiIiIylqfe7CCGaKRIiqguLHyIiIiIiMjhzOEjAy96IiIiIiMgmsPghIiIiIiKbwOKHiIiIiIhsAosfIiIiIiKyCSx+iIiIiIjIJrD4ISIiIiIim8Dih4iIiIiIbAKLHyIiIiIisgksfoiIiIiIyCaw+CEiIiIiIpvA4oeIiIiIiGwCix8iIiIiIrIJLH6IiIiIiMgmmLT4+fzzzxEQEAAnJycEBwdj//79pgyHyOAaO+bT09MRHBwMJycntGvXDsuWLTNSpESWhd8nRPVjnhABECaSnJwsHBwcxIoVK8SpU6fEq6++KlxcXMSFCxfqXVer1QoAQqvV1toGACdOBp0aO0YbO+Z///130bJlS/Hqq6+KU6dOiRUrVggHBwfxzTff1JsjDc0VU/8MOZnHeK2PofbbkP/LG6Ip3ycNicPUvztOtjHd7fhsKEPniRDMFU6Gn5oyPqVx2qARbwD/+Mc/xOTJk/XmPfDAA+LNN9+sd10mICdzmBo7Rhs75qdPny4eeOABvXkvvvii6N27d30pUmcctzP1z5CTeYzX+hhqv831R11Tvk8aEoepf3ecbGO62/HZUIbOEyGYK5wMPzVlfFaxhwmUlJQgMzMTb775pt78iIgIZGRkVGuv0+mg0+mkz1qtFgBQWFho2ECJ6lDX+KtaVvld0PgxDwAHDx5ERESE3rzBgwcjMTERpaWlcHBwqLYOc4VqY6ox0Jg8uRt3k1vMEzJHtY0/5gnR/zRHnpik+Ll8+TLKy8vh6+urN9/X1xcajaZa+4SEBMyePbvafD8/P4PFSFQfhUJRb5vr169DoVA0eswDgEajqbF9WVkZLl++DJVKVW0d5grVpiHj1VT7rcqTu3E3ucU8IXNUXw4wT4iaJ09MUvxUkclkep+FENXmAUBcXBxiYmKkzxUVFfj777/h5eVVrX1hYSH8/PyQl5cHd3d3wwRuZmytz5bQXyEErl+/DrVarTe/oWO+rvY1za/SmFwxNEv4PVWxpFgBy4q3rlhry5O70ZjcamieWNLPuanYV/Nl7nkCWN7P9G7ZSj8By+trY/LEJMWPt7c37Ozsqh1tKCgoqHZUAgDkcjnkcrnevHvuuafOfbi7u1vEL6s52Vqfzb2/tx95aOyYBwClUllje3t7e3h5edW4zt3kiqGZ++/pdpYUK2BZ8dYWa1PPSN1NbjU2Tyzp59xU7Kt5soQ8ASzrZ9oUttJPwLL62tA8Mcmjrh0dHREcHIzU1FS9+ampqejTp48pQiIyqLsZ86GhodXa79q1CyEhITXe70Nki/h9QlQ/5gnR/5jssreYmBiMHz8eISEhCA0NxfLly5Gbm4vJkyebKiQig6pvzMfFxeHSpUtYvXo1AGDy5MlYsmQJYmJi8Pzzz+PgwYNITEzEV199ZcpuEJkdfp8Q1Y95QlTJZMXP2LFjceXKFbz77rvIz89HYGAgtm3bBn9//yZtVy6XY9asWdVO1VozW+uzpfa3vjGfn5+P3NxcqX1AQAC2bduG1157DZ999hnUajU+/fRTjB492lRdaBRL+j1ZUqyAZcVrjFj5fdJ07Kv1M1SeALbzM7WVfgLW3VeZaMqzE4mIiIiIiCyESe75ISIiIiIiMjYWP0REREREZBNY/BARERERkU1g8UNERERERDbB6oqfzz//HAEBAXByckJwcDD2799v6pCq2bdvHyIjI6FWqyGTybB582a95UIIxMfHQ61Ww9nZGf369cPJkyf12uh0OkRFRcHb2xsuLi4YMWIELl68qNfm6tWrGD9+PBQKBRQKBcaPH49r167ptcnNzUVkZCRcXFzg7e2NV155BSUlJc3a34SEBPTs2RNubm7w8fHByJEjcfbsWavuszWIj4+HTCbTm5RKpbTcmL+zmlhSHtUX68SJE6v9rHv37m2SWJmv/2Pu3yeWlANNwTFp3pgnlUw9dpgnjSCsSHJysnBwcBArVqwQp06dEq+++qpwcXERFy5cMHVoerZt2yZmzpwpUlJSBACxadMmveUffvihcHNzEykpKSI7O1uMHTtWqFQqUVhYKLWZPHmyaNWqlUhNTRVHjx4V/fv3F926dRNlZWVSm0cffVQEBgaKjIwMkZGRIQIDA8Xw4cOl5WVlZSIwMFD0799fHD16VKSmpgq1Wi2mTp3arP0dPHiwWLlypThx4oQ4duyYGDZsmGjTpo0oKiqy2j5bg1mzZokuXbqI/Px8aSooKJCWG+t3VhtLyqP6Yp0wYYJ49NFH9X7WV65c0WtjrFiZr5Us4fvEknKgKTgmzRfzxHzGDvOk4ayq+PnHP/4hJk+erDfvgQceEG+++aaJIqrfnYlYUVEhlEql+PDDD6V5t27dEgqFQixbtkwIIcS1a9eEg4ODSE5OltpcunRJtGjRQuzYsUMIIcSpU6cEAHHo0CGpzcGDBwUAcebMGSFE5X8ILVq0EJcuXZLafPXVV0IulwutVmuQ/gohREFBgQAg0tPTbabPlmjWrFmiW7duNS4z5u+sISwpj2orfh577LFa+2fK8W+r+Wpp3yeWlANNZatj0hwxT8x37DBPamc1l72VlJQgMzMTERERevMjIiKQkZFhoqgaLycnBxqNRq8fcrkcYWFhUj8yMzNRWlqq10atViMwMFBqc/DgQSgUCvTq1Utq07t3bygUCr02gYGBUKvVUpvBgwdDp9MhMzPTYH3UarUAAE9PTwC20WdLde7cOajVagQEBOCf//wnfv/9dwDG/Z3dDUscU2lpafDx8UGHDh3w/PPPo6CgQFpmylhtMV+t4fvEmn9PtjgmzRHzxLzHDvOkdlZT/Fy+fBnl5eXw9fXVm+/r6wuNRmOiqBqvKta6+qHRaODo6AgPD4862/j4+FTbvo+Pj16bO/fj4eEBR0dHg/3MhBCIiYnBww8/jMDAQCmOqvhvZy19tlS9evXC6tWrsXPnTqxYsQIajQZ9+vTBlStXjPo7uxuWNqaGDBmCdevWYc+ePZg/fz4OHz6MAQMGQKfTmTRWW81Xa/g+sdbfk62OSXPEPDHfscM8qZu9qQNobjKZTO+zEKLaPEtwN/24s01N7e+mTXOaOnUqjh8/jgMHDlRbZq19tlRDhgyR/h0UFITQ0FDcd999WLVqlXQzvrF+Z3fLUsbU2LFjpX8HBgYiJCQE/v7+2Lp1K0aNGmWyWG09X63h+8Tafk+2PibNEfOk5m3cbZvmwDypm9Wc+fH29oadnV21irKgoKBa9WnOqp6mVVc/lEolSkpKcPXq1Trb/Pnnn9W2/9dff+m1uXM/V69eRWlpqUF+ZlFRUfjuu++wd+9etG7dWppvzX22Ji4uLggKCsK5c+eM+ju7G5Y+plQqFfz9/XHu3DmTxWrL+WoN3yfW+Huy5TFpjpgn5jl2mCcNYJA7iUzkH//4h3jppZf05nXq1Mlsb7wTovab7z766CNpnk6nq/GGtA0bNkht/vjjjxpvSPvpp5+kNocOHarxhrQ//vhDapOcnNzsN6RVVFSIKVOmCLVaLX755Zcal1tbn63RrVu3RKtWrcTs2bON+jtrCEvKoztjrcnly5eFXC4Xq1atMnqszNdKlvZ9Ykk50Fgck+aLeWI+Y4d50nBWVfxUPXIxMTFRnDp1SkRHRwsXFxdx/vx5U4em5/r16yIrK0tkZWUJAGLBggUiKytLejTkhx9+KBQKhdi4caPIzs4WTz31VI2PImzdurXYvXu3OHr0qBgwYECNjyLs2rWrOHjwoDh48KAICgqq8VGE4eHh4ujRo2L37t2idevWzf4owpdeekkoFAqRlpam9yjfmzdvSm2src/WYNq0aSItLU38/vvv4tChQ2L48OHCzc1Nyidj/c5qY0l5VFes169fF9OmTRMZGRkiJydH7N27V4SGhopWrVqZJFbmayVL+D6xpBxoCo5J88U8MZ+xwzxpOKsqfoQQ4rPPPhP+/v7C0dFRPPjgg9Ij/szJ3r17BYBq04QJE4QQldX5rFmzhFKpFHK5XDzyyCMiOztbbxvFxcVi6tSpwtPTUzg7O4vhw4eL3NxcvTZXrlwRTz/9tHBzcxNubm7i6aefFlevXtVrc+HCBTFs2DDh7OwsPD09xdSpU8WtW7eatb819RWAWLlypdTG2vpsDaqe/+/g4CDUarUYNWqUOHnypLTcmL+zmlhSHtUV682bN0VERIS49957hYODg2jTpo2YMGFCtTiMFSvz9X/M/fvEknKgKTgmzRvzpJKpxw7zpOFkQghxF1fLERERERERWRSreeABERERERFRXVj8EBERERGRTWDxQ0RERERENoHFDxERERER2QQWP0REREREZBNY/BARERERkU1g8UNERERERDaBxQ8REREREdkEFj9W5vz585DJZDh27JipQyEiI5k4cSJGjhxp6jCIzBrzhKh+tpAnLH6IiBpBJpNh8+bNpg6DyKwxT4jqxzwxDRY/ZqSkpMSk+xdCoKyszKQxkG0zdQ4QWQLmCVH9mCdUGxY/JtSvXz9MnToVMTEx8Pb2xqBBg3Dq1CkMHToUrq6u8PX1xfjx43H58mVpnR07duDhhx/GPffcAy8vLwwfPhy//fbbXe0/LS0NMpkMO3fuREhICORyOfbv34/ffvsNjz32GHx9feHq6oqePXti9+7deuu2bdsWc+bMwb///W+4ubmhTZs2WL58uV6bjIwMdO/eHU5OTggJCcHmzZurXZJXX3/JutWUAzKZDD/88ANCQkLQsmVL9OnTB2fPntVb7/3334ePjw/c3Nzw3HPP4c0330T37t0bvN+VK1eiU6dOcHJywgMPPIDPP/9cWlZSUoKpU6dCpVLByckJbdu2RUJCAoDKcQ8Ajz/+OGQymfS5LvHx8ejevTvWrFmDtm3bQqFQ4J///CeuX78utamoqMBHH32E+++/H3K5HG3atMEHH3wgLc/OzsaAAQPg7OwMLy8vvPDCCygqKqq2r3nz5kGlUsHLywtTpkxBaWlpg38mZL6YJ5WYJ1QX5kkl5kkDCDKZsLAw4erqKl5//XVx5swZkZGRIby9vUVcXJw4ffq0OHr0qBg0aJDo37+/tM4333wjUlJSxC+//CKysrJEZGSkCAoKEuXl5UIIIXJycgQAkZWVVe/+9+7dKwCIrl27il27dolff/1VXL58WRw7dkwsW7ZMHD9+XPzyyy9i5syZwsnJSVy4cEFa19/fX3h6eorPPvtMnDt3TiQkJIgWLVqI06dPCyGEKCwsFJ6enuKZZ54RJ0+eFNu2bRMdOnTQi+2PP/6ot79k3e7MgaVLlwoAolevXiItLU2cPHlS9O3bV/Tp00daZ+3atcLJyUl8+eWX4uzZs2L27NnC3d1ddOvWrUH7XL58uVCpVCIlJUX8/vvvIiUlRXh6eoqkpCQhhBAff/yx8PPzE/v27RPnz58X+/fvF+vXrxdCCFFQUCAAiJUrV4r8/HxRUFBQ7/5mzZolXF1dxahRo0R2drbYt2+fUCqVYsaMGVKb6dOnCw8PD5GUlCR+/fVXsX//frFixQohhBA3btwQarVaWv+HH34QAQEBYsKECdL6EyZMEO7u7mLy5Mni9OnTYsuWLaJly5Zi+fLlDfqZkHljnlRinlBdmCeVmCf1Y/FjQmFhYaJ79+7S57fffltERETotcnLyxMAxNmzZ2vcRlXyZGdnCyHurvjZvHlzvW07d+4sFi9eLH329/cXzzzzjPS5oqJC+Pj4iKVLlwohhFi6dKnw8vISxcXFUpsVK1boxXY3/SXrcmcOVI3J3bt3S/O2bt0qAEhjqVevXmLKlCl623nooYca/GXl5+cnfflUee+990RoaKgQQoioqCgxYMAAUVFRUeP6AMSmTZsatC8hKr+sWrZsKQoLC6V5r7/+uujVq5cQovJAgVwul76c7rR8+XLh4eEhioqKpHlbt24VLVq0EBqNRghR+WXl7+8vysrKpDZPPvmkGDt2bIPjJPPFPGGeUP2YJ8yThuJlbyYWEhIi/TszMxN79+6Fq6urND3wwAMAIF3a9ttvv2HcuHFo164d3N3dERAQAADIzc1tlhgA4MaNG5g+fTo6d+6Me+65B66urjhz5ky1fXTt2lX6t0wmg1KpREFBAQDg7Nmz6Nq1K5ycnKQ2//jHP/TWb0h/yfrdOf4A/bGlUqkAQG9s3TmW7vxcm7/++gt5eXmYNGmS3rh7//33pTE3ceJEHDt2DB07dsQrr7yCXbt23VW/bte2bVu4ubnp9amqP6dPn4ZOp0N4eHiN654+fRrdunWDi4uLNO+hhx5CRUWF3uUbXbp0gZ2dXY37IMvHPGGeUP2YJ8yThrA3dQC27vYBWFFRgcjISHz00UfV2lUlbGRkJPz8/LBixQqo1WpUVFQgMDCwSTf23R4DALz++uvYuXMn5s2bh/vvvx/Ozs544oknqu3DwcFB77NMJkNFRQWAyocnyGQyveVCCL3PDekvWb87xx+gP7aqxlHV2Lp9XpU7x1ZtqraxYsUK9OrVS29Z1X/0Dz74IHJycrB9+3bs3r0bY8aMwcCBA/HNN980aB81qStXnJ2d61y3ply6fTsN2QdZPuYJ84TqxzxhnjQEz/yYkQcffBAnT55E27Ztcf/99+tNLi4uuHLlCk6fPo233noL4eHh6NSpE65evdrscezfvx8TJ07E448/jqCgICiVSpw/f75R23jggQdw/Phx6HQ6ad6RI0f02tTXX6KadOzYET///LPevDvHVm18fX3RqlUr/P7779XGXNVZVABwd3fH2LFjsWLFCmzYsAEpKSn4+++/AVR+KZSXlzdbf9q3bw9nZ2f88MMPNS7v3Lkzjh07hhs3bkjzfvzxR7Ro0QIdOnRotjjIujBPmCdUP+aJbeYJix8zMmXKFPz999946qmn8PPPP+P333/Hrl278O9//xvl5eXw8PCAl5cXli9fjl9//RV79uxBTExMs8dx//33Y+PGjTh27Bj+7//+D+PGjWt0xV+1zgsvvIDTp09LZ5KA/x1dqK+/RDWJiopCYmIiVq1ahXPnzuH999/H8ePHaz2adaf4+HgkJCTgk08+wS+//ILs7GysXLkSCxYsAAAsXLgQycnJOHPmDH755Rf897//hVKpxD333AOg8pKDH374ARqNplkOPjg5OeGNN97A9OnTsXr1avz22284dOgQEhMTAQBPP/00nJycMGHCBJw4cQJ79+5FVFQUxo8fD19f3ybvn6wT84R5QvVjnthmnrD4MSNqtRo//vgjysvLMXjwYAQGBuLVV1+FQqFAixYt0KJFCyQnJyMzMxOBgYF47bXX8PHHHzd7HAsXLoSHhwf69OmDyMhIDB48GA8++GCjtuHu7o4tW7bg2LFj6N69O2bOnIl33nkHAKT7gOrrL1FNnn76acTFxSE2Nla6pGDixIl695fV5bnnnsMXX3yBpKQkBAUFISwsDElJSdKROldXV3z00UcICQlBz549cf78eWzbtk0ak/Pnz0dqair8/PzQo0ePZunT22+/jWnTpuGdd95Bp06dMHbsWOn66pYtW2Lnzp34+++/0bNnTzzxxBMIDw/HkiVLmmXfZJ2YJ8wTqh/zxDbzRCYaenEjUROtW7cO//rXv6DVauu9LpWoMQYNGgSlUok1a9aYOhQis8U8Iaof88T68YEHZDCrV69Gu3bt0KpVK/zf//0f3njjDYwZM4aFDzXJzZs3sWzZMgwePBh2dnb46quvsHv3bqSmppo6NCKzwTwhqh/zxDbx2iIrNnnyZL3HL94+TZ482eD712g0eOaZZ9CpUye89tprePLJJ7F8+XKD75esm0wmw7Zt29C3b18EBwdjy5YtSElJwcCBAwGg1jHv6uqK/fv3N3s8Xbp0qXV/69ata/b9ETUE84SofswT28TL3qxYQUEBCgsLa1zm7u4OHx8fI0dEZHi//vprrctatWrV7GceL1y4gNLS0hqX+fr66r2PgchcME+I6sc8sU4sfoiIiIiIyCbwsjciIiIiIrIJLH6IiIiIiMgmsPghIiIiIiKbwOKHiIiIiIhsAosfIiIiIiKyCSx+iIiIiIjIJrD4ISIiIiIim/D/AF+qJ64IvUnoAAAAAElFTkSuQmCC",
"text/plain": [
"<Figure size 1000x400 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"for c in [\"coh\", \"ncoh\"]:\n",
" \n",
" print(\"---\", c)\n",
"\n",
" fig, axes = plt.subplots(1,4, figsize=(10,4))\n",
" ax=axes[0]\n",
" out = ds.real_range.plot.hist(ax=ax, color=\"k\")\n",
" ax.set_title(\"true range\")\n",
" print(\"truth, number of data points = \", int(np.sum(out[0])))\n",
" \n",
" for i, snr in enumerate(ds.SNR):\n",
"\n",
" ax=axes[1+i]\n",
" out = ds[\"rng_est_\"+c].sel(SNR=snr).plot.hist(ax=ax, color=\"k\")\n",
" ax.set_title(f\"SNR={int(snr)}\")\n",
" print(f\"SNR={int(snr)}, number of data points = \", int(np.sum(out[0])))\n",
"\n",
"\n",
"#counts, bins = ds.rng_est_coh.sel(SNR=-20).plot.hist(ax=ax, label=\"-20dB\", color=\"darkblue\")"
]
},
{
"cell_type": "markdown",
"id": "ef65e2f9-8326-4215-9f15-64611702e890",
"metadata": {
"tags": []
},
"source": [
"There barely any good points for an SNR of -20 (less that 2%) and we skip its inspection next\n",
"\n",
"Coherent and noncoherent treatments lead to similar results"
]
},
{
"cell_type": "markdown",
"id": "d4699e49-7dd6-4901-9ad5-0f793fced5d6",
"metadata": {
"tags": []
},
"source": [
"### We look at the distribution of errors, focusing on an SNR of -10"
]
},
{
"cell_type": "code",
"execution_count": 78,
"id": "5b485bab-4cf5-4d2e-ada5-fcb476a7b51c",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"ds10 = ds.sel(SNR=-10)"
]
},
{
"cell_type": "code",
"execution_count": 82,
"id": "98647171-2d62-45cf-9947-2eb12a45a5d2",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# raw\n",
"fig, ax = plt.subplots(1,1)\n",
"ds10[\"rng_err_coh\"].plot.hist(ax=ax, color=\"k\")\n",
"fig, ax = plt.subplots(1,1)\n",
"ds10[\"rng_err_ncoh\"].plot.hist(ax=ax, color=\"k\");"
]
},
{
"cell_type": "code",
"execution_count": 83,
"id": "7a0fe507-5f24-4844-ad35-02974e1c5b2b",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"bins = np.arange(0, 10e3, 100)\n",
"fig, ax = plt.subplots(1,1)\n",
"ds10[\"rng_err_coh\"].plot.hist(ax=ax, color=\"k\", bins=bins)\n",
"fig, ax = plt.subplots(1,1)\n",
"ds10[\"rng_err_ncoh\"].plot.hist(ax=ax, color=\"k\", bins=bins);"
]
},
{
"cell_type": "markdown",
"id": "a566aa01-463e-4836-91ca-fc0c5c99daa2",
"metadata": {},
"source": [
"Coherent and incoherent treatments are similar.\n",
"\n",
"There is a larger number of values below 100 separated by a broader bump of errors between 2 and 6 km.\n",
"This looks peculiar and needs to be taken into consideration when computing averaged metrics.\n",
"Average errors are for instance:"
]
},
{
"cell_type": "code",
"execution_count": 84,
"id": "56c731b2-4bd5-4924-bd3c-79897b0958de",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"1739.1910528442452"
]
},
"execution_count": 84,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"float(ds10[\"rng_err_coh\"].std()) # meters"
]
},
{
"cell_type": "code",
"execution_count": 85,
"id": "8c145bfe-0474-419b-a9be-1bacc9201a6a",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"1720.7690009698972"
]
},
"execution_count": 85,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"float(ds10[\"rng_err_ncoh\"].std()) # meters"
]
},
{
"cell_type": "markdown",
"id": "410a9dbc-7b8e-40c1-b8a9-03e6850d567f",
"metadata": {},
"source": [
"which is in between both cluster of errors"
]
},
{
"cell_type": "markdown",
"id": "aca6e978-eb3d-4582-9c90-ec9f87c25fe4",
"metadata": {},
"source": [
"### We investigate whether errors depend on range"
]
},
{
"cell_type": "code",
"execution_count": 86,
"id": "063305c9-eeae-435a-8cd2-3bfdd14ef90f",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/aponte/.miniconda3/envs/pynsitu/lib/python3.10/site-packages/xarray/core/computation.py:761: RuntimeWarning: divide by zero encountered in log10\n",
" result_data = func(*input_data)\n"
]
},
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0x12c211630>"
]
},
"execution_count": 86,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"range_bins = np.arange(0,30e3,1e3)\n",
"error_bins = np.arange(0, 10e3, 100)\n",
"h = histogram(ds10[\"rng_err_coh\"], ds10.real_range, bins=[error_bins, range_bins,])\n",
"np.log10(h).plot()"
]
},
{
"cell_type": "markdown",
"id": "66c33c63-1249-40a0-861b-cdd9b199add8",
"metadata": {
"tags": []
},
"source": [
"Same but focus on small errors"
]
},
{
"cell_type": "code",
"execution_count": 87,
"id": "50c051d3-3222-4664-8922-09f18541056c",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0x12b8da0e0>"
]
},
"execution_count": 87,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"range_bins = np.arange(0,30e3,1e3)\n",
"error_bins = np.arange(0, 20, 1)\n",
"h = histogram(ds10[\"rng_err_coh\"], ds10.real_range, bins=[error_bins, range_bins,])\n",
"np.log10(h).plot()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f6ab2ab9-4c53-4b61-9ed8-25911242a2bb",
"metadata": {},
"outputs": [],
"source": [
"Conclusion: \"when errors are small they are very small (according to oceanographics needs) but very large when large\""
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e54b8a06-90b4-4c64-bb30-5699a5a51332",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.11"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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