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 "cells": [
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    "# Channel  Quality Assessment and Pruning\n",
    "\n",
    "This notebook sketches how to prune bad channels "
   ]
  },
  {
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     "shell.execute_reply": "2025-04-14T12:56:35.693157Z"
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   "source": [
    "import matplotlib.pyplot as p\n",
    "import numpy as np\n",
    "from matplotlib.colors import LinearSegmentedColormap\n",
    "\n",
    "import cedalion\n",
    "import cedalion.datasets as datasets\n",
    "import cedalion.nirs\n",
    "import cedalion.plots as plots\n",
    "import cedalion.sigproc.quality as quality\n",
    "import cedalion.xrutils as xrutils\n",
    "from cedalion import units\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loading raw CW-NIRS data from a SNIRF file and converting it to OD and CONC\n",
    "\n",
    "This notebook uses a finger-tapping dataset in BIDS layout provided by Rob Luke that is automatically fetched. \n",
    "You can also find it [here](https://github.com/rob-luke/BIDS-NIRS-Tapping)."
   ]
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     "iopub.status.idle": "2025-04-14T12:56:36.127995Z",
     "shell.execute_reply": "2025-04-14T12:56:36.127430Z"
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       "  * wavelength  (wavelength) float64 16B 760.0 850.0\n",
       "Attributes:\n",
       "    data_type_group:  unprocessed raw</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 28</li><li><span class='xr-has-index'>wavelength</span>: 2</li><li><span class='xr-has-index'>time</span>: 23239</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-6aa00795-a9db-4d21-8bfe-1e0c144ea745' class='xr-array-in' type='checkbox' checked><label for='section-6aa00795-a9db-4d21-8bfe-1e0c144ea745' 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>[V] 0.09137 0.09099 0.09102 0.09044 ... 1.273 1.273 1.273 1.276</span></div><div class='xr-array-data'><table><tbody><tr><th>Magnitude</th><td style='text-align:left;'><pre>[[[0.0913686 0.0909875 0.0910225 ... 0.0941083 0.0940129 0.0944882]  [0.1856806 0.186377 0.1836514 ... 0.1856486 0.1850836 0.1842172]] [[0.227516 0.2297024 0.2261366 ... 0.2264519 0.2271665 0.226713]  [0.6354927 0.637668 0.6298023 ... 0.6072068 0.6087293 0.6091066]] [[0.1064704 0.1066212 0.1053444 ... 0.121114 0.1205022 0.1205441]  [0.2755033 0.2761615 0.2727006 ... 0.2911952 0.2900544 0.2909847]] ... [[0.2027881 0.1996586 0.2004866 ... 0.2318743 0.2311941 0.2330808]  [0.4666358 0.4554404 0.4561614 ... 0.4809749 0.4812827 0.4862896]] [[0.4885007 0.4802285 0.4818338 ... 0.6109142 0.6108118 0.613845]  [0.8457658 0.825988 0.8259648 ... 0.975894 0.9756599 0.9826459]] [[0.6304559 0.6284427 0.6287045 ... 0.6810626 0.6809573 0.6818709]  [1.2285622 1.2205907 1.2190002 ... 1.2729124 1.2727222 1.2755645]]]</pre></td></tr><tr><th>Units</th><td style='text-align:left;'>volt</td></tr></tbody></table></div></div></li><li class='xr-section-item'><input id='section-6d2d561c-8b16-4930-b669-38c5d3d9508b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6d2d561c-8b16-4930-b669-38c5d3d9508b' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.128 ... 2.974e+03 2.974e+03</div><input id='attrs-f79d141e-7f00-4a3f-8167-13707e8dea4d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f79d141e-7f00-4a3f-8167-13707e8dea4d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85b57a28-4a18-42c0-ae42-08f5142bce4c' class='xr-var-data-in' type='checkbox'><label for='data-85b57a28-4a18-42c0-ae42-08f5142bce4c' 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>second</dd></dl></div><div class='xr-var-data'><pre>array([0.000000e+00, 1.280000e-01, 2.560000e-01, ..., 2.974208e+03,\n",
       "       2.974336e+03, 2.974464e+03])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>samples</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 ... 23235 23236 23237 23238</div><input id='attrs-4fce6c51-8103-4155-92ac-bf3f066bd683' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4fce6c51-8103-4155-92ac-bf3f066bd683' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60f1cf4f-b0d1-4943-80d5-a643642007d7' class='xr-var-data-in' type='checkbox'><label for='data-60f1cf4f-b0d1-4943-80d5-a643642007d7' 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, ..., 23236, 23237, 23238])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;S1D1&#x27; &#x27;S1D2&#x27; ... &#x27;S8D8&#x27; &#x27;S8D16&#x27;</div><input id='attrs-9b370591-9395-40e5-b6b1-8d53b871234c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9b370591-9395-40e5-b6b1-8d53b871234c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3a2ac54-47c8-4f20-aea4-bd588d25e62f' class='xr-var-data-in' type='checkbox'><label for='data-c3a2ac54-47c8-4f20-aea4-bd588d25e62f' 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;S1D1&#x27;, &#x27;S1D2&#x27;, &#x27;S1D3&#x27;, &#x27;S1D9&#x27;, &#x27;S2D1&#x27;, &#x27;S2D3&#x27;, &#x27;S2D4&#x27;, &#x27;S2D10&#x27;, &#x27;S3D2&#x27;,\n",
       "       &#x27;S3D3&#x27;, &#x27;S3D11&#x27;, &#x27;S4D3&#x27;, &#x27;S4D4&#x27;, &#x27;S4D12&#x27;, &#x27;S5D5&#x27;, &#x27;S5D6&#x27;, &#x27;S5D7&#x27;,\n",
       "       &#x27;S5D13&#x27;, &#x27;S6D5&#x27;, &#x27;S6D7&#x27;, &#x27;S6D8&#x27;, &#x27;S6D14&#x27;, &#x27;S7D6&#x27;, &#x27;S7D7&#x27;, &#x27;S7D15&#x27;,\n",
       "       &#x27;S8D7&#x27;, &#x27;S8D8&#x27;, &#x27;S8D16&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;S1&#x27; &#x27;S1&#x27; &#x27;S1&#x27; ... &#x27;S8&#x27; &#x27;S8&#x27; &#x27;S8&#x27;</div><input id='attrs-578a33cb-d48f-4f7c-ad27-0ca5f68c7952' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-578a33cb-d48f-4f7c-ad27-0ca5f68c7952' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b27592e2-ac51-4ad8-9fd0-a57dcc6a1271' class='xr-var-data-in' type='checkbox'><label for='data-b27592e2-ac51-4ad8-9fd0-a57dcc6a1271' 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;S1&#x27;, &#x27;S1&#x27;, &#x27;S1&#x27;, &#x27;S1&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S3&#x27;, &#x27;S3&#x27;, &#x27;S3&#x27;,\n",
       "       &#x27;S4&#x27;, &#x27;S4&#x27;, &#x27;S4&#x27;, &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;,\n",
       "       &#x27;S7&#x27;, &#x27;S7&#x27;, &#x27;S7&#x27;, &#x27;S8&#x27;, &#x27;S8&#x27;, &#x27;S8&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>detector</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;D1&#x27; &#x27;D2&#x27; &#x27;D3&#x27; ... &#x27;D7&#x27; &#x27;D8&#x27; &#x27;D16&#x27;</div><input id='attrs-0a42a389-632b-4d4f-9599-0b92234d63c8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0a42a389-632b-4d4f-9599-0b92234d63c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1eac94d7-bccc-497a-88a8-8b57b01e048f' class='xr-var-data-in' type='checkbox'><label for='data-1eac94d7-bccc-497a-88a8-8b57b01e048f' 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;D1&#x27;, &#x27;D2&#x27;, &#x27;D3&#x27;, &#x27;D9&#x27;, &#x27;D1&#x27;, &#x27;D3&#x27;, &#x27;D4&#x27;, &#x27;D10&#x27;, &#x27;D2&#x27;, &#x27;D3&#x27;, &#x27;D11&#x27;,\n",
       "       &#x27;D3&#x27;, &#x27;D4&#x27;, &#x27;D12&#x27;, &#x27;D5&#x27;, &#x27;D6&#x27;, &#x27;D7&#x27;, &#x27;D13&#x27;, &#x27;D5&#x27;, &#x27;D7&#x27;, &#x27;D8&#x27;,\n",
       "       &#x27;D14&#x27;, &#x27;D6&#x27;, &#x27;D7&#x27;, &#x27;D15&#x27;, &#x27;D7&#x27;, &#x27;D8&#x27;, &#x27;D16&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>wavelength</span></div><div class='xr-var-dims'>(wavelength)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>760.0 850.0</div><input id='attrs-79e42ec3-5a36-41b6-a45d-728ba4eda457' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-79e42ec3-5a36-41b6-a45d-728ba4eda457' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b135639d-6968-44f7-b33d-13798ff6c7c4' class='xr-var-data-in' type='checkbox'><label for='data-b135639d-6968-44f7-b33d-13798ff6c7c4' 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([760., 850.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-08c42000-88b5-4176-9f9d-ad684d86cf7f' class='xr-section-summary-in' type='checkbox'  ><label for='section-08c42000-88b5-4176-9f9d-ad684d86cf7f' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-44049e97-3736-492a-a119-5cb1557280cc' class='xr-index-data-in' type='checkbox'/><label for='index-44049e97-3736-492a-a119-5cb1557280cc' 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([     0.0,    0.128,    0.256,    0.384,    0.512,     0.64,    0.768,\n",
       "          0.896,    1.024,    1.152,\n",
       "       ...\n",
       "       2973.312,  2973.44, 2973.568, 2973.696, 2973.824, 2973.952,  2974.08,\n",
       "       2974.208, 2974.336, 2974.464],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;time&#x27;, length=23239))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>channel</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1129f538-917b-40d7-b929-1dd093507f96' class='xr-index-data-in' type='checkbox'/><label for='index-1129f538-917b-40d7-b929-1dd093507f96' 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([&#x27;S1D1&#x27;, &#x27;S1D2&#x27;, &#x27;S1D3&#x27;, &#x27;S1D9&#x27;, &#x27;S2D1&#x27;, &#x27;S2D3&#x27;, &#x27;S2D4&#x27;, &#x27;S2D10&#x27;, &#x27;S3D2&#x27;,\n",
       "       &#x27;S3D3&#x27;, &#x27;S3D11&#x27;, &#x27;S4D3&#x27;, &#x27;S4D4&#x27;, &#x27;S4D12&#x27;, &#x27;S5D5&#x27;, &#x27;S5D6&#x27;, &#x27;S5D7&#x27;,\n",
       "       &#x27;S5D13&#x27;, &#x27;S6D5&#x27;, &#x27;S6D7&#x27;, &#x27;S6D8&#x27;, &#x27;S6D14&#x27;, &#x27;S7D6&#x27;, &#x27;S7D7&#x27;, &#x27;S7D15&#x27;,\n",
       "       &#x27;S8D7&#x27;, &#x27;S8D8&#x27;, &#x27;S8D16&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>wavelength</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a4edc81b-663a-4caf-a7b1-9067712ac660' class='xr-index-data-in' type='checkbox'/><label for='index-a4edc81b-663a-4caf-a7b1-9067712ac660' 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([760.0, 850.0], dtype=&#x27;float64&#x27;, name=&#x27;wavelength&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ba137a02-2e81-4315-b54c-e30eedae5cd0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ba137a02-2e81-4315-b54c-e30eedae5cd0' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>data_type_group :</span></dt><dd>unprocessed raw</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (channel: 28, wavelength: 2, time: 23239)> Size: 10MB\n",
       "<Quantity([[[0.0913686 0.0909875 0.0910225 ... 0.0941083 0.0940129 0.0944882]\n",
       "  [0.1856806 0.186377  0.1836514 ... 0.1856486 0.1850836 0.1842172]]\n",
       "\n",
       " [[0.227516  0.2297024 0.2261366 ... 0.2264519 0.2271665 0.226713 ]\n",
       "  [0.6354927 0.637668  0.6298023 ... 0.6072068 0.6087293 0.6091066]]\n",
       "\n",
       " [[0.1064704 0.1066212 0.1053444 ... 0.121114  0.1205022 0.1205441]\n",
       "  [0.2755033 0.2761615 0.2727006 ... 0.2911952 0.2900544 0.2909847]]\n",
       "\n",
       " ...\n",
       "\n",
       " [[0.2027881 0.1996586 0.2004866 ... 0.2318743 0.2311941 0.2330808]\n",
       "  [0.4666358 0.4554404 0.4561614 ... 0.4809749 0.4812827 0.4862896]]\n",
       "\n",
       " [[0.4885007 0.4802285 0.4818338 ... 0.6109142 0.6108118 0.613845 ]\n",
       "  [0.8457658 0.825988  0.8259648 ... 0.975894  0.9756599 0.9826459]]\n",
       "\n",
       " [[0.6304559 0.6284427 0.6287045 ... 0.6810626 0.6809573 0.6818709]\n",
       "  [1.2285622 1.2205907 1.2190002 ... 1.2729124 1.2727222 1.2755645]]], 'volt')>\n",
       "Coordinates:\n",
       "  * time        (time) float64 186kB 0.0 0.128 0.256 ... 2.974e+03 2.974e+03\n",
       "    samples     (time) int64 186kB 0 1 2 3 4 5 ... 23234 23235 23236 23237 23238\n",
       "  * channel     (channel) object 224B 'S1D1' 'S1D2' 'S1D3' ... 'S8D8' 'S8D16'\n",
       "    source      (channel) object 224B 'S1' 'S1' 'S1' 'S1' ... 'S8' 'S8' 'S8'\n",
       "    detector    (channel) object 224B 'D1' 'D2' 'D3' 'D9' ... 'D7' 'D8' 'D16'\n",
       "  * wavelength  (wavelength) float64 16B 760.0 850.0\n",
       "Attributes:\n",
       "    data_type_group:  unprocessed raw"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Gv//+G2PGjEGBAgWy0hg8eDBWrVqFpUuX4tdff8W1a9fQrVs3ZOaWIFRElHM41vI1bSqjOaub6Prj2mO1mp+mIjua0XfoYHutEUfGsG+/lf3Bq1TxPa2cTG+h6PZtYPNm23t3rUCmTgWee87cAtehQ8a3qVzZvvDrK8fzeMsW7fVu3tSfpsO9m1uXLjnPU9/nuWuJ4vhdGGkJAMhrzquvOj+AU3dzMKp0adkyR/2/CwD5HG7TP/7Y1uKmTBnn5USUpwT8CmBxaCYkhHCap2XJkiUYO3Ysli1bhrJly/qU5siRI5GcnJw1ncultQ5lypRBuXLlsqa1a9eievXqaNeuHQBg1KhR6Nq1KyZPnowmTZrgjjvuwIMPPpj1+SYnJ+PLL7/ElClT0KFDBzRp0gSLFi3CgQMHsPm/m5rY2FhYLBasXLkS7du3R6FChdCoUSPsUvXrmj9/PooXL461a9eiVq1aKFSoEHr37o3r169jwYIFqFq1KkqUKIHXXnuNDwiI8rKkJPv3f/0lmw+r+8LPnWu/jq+F8GPHZG3rW2/5lo4rrvr0+tO4cfaB0Nw5dAi4/37g999t8/r107/tDz8Yz5+/qWvPFVoPOL7+Wl96H3xgX7M7c6bzOqmpstA1bBjw5ZfA9u360tbjgQe8286x8B0XJ2v3Hf/PHF244PzA7Phx+/eqChU7zz+vL29Ll2o3G3dssv7668AzzwDTprlPz12/fcdWO+4eUAkh/xdu3wZWrQImTwbefBP47DNZ869mRrN9dTcIwLmgfvy48//YH3/4vl/yv02bgO++C3Qucre0NPl/6tjlLjcTAZKWliZCQkLEypUr7ea//vrr4t5773W77dKlS0XBggXF2rVrnZZVrlxZTJ061W7e1KlTRZUqVXTnLTk5WQAQycnJTstu3rwpDh8+LG7evGmbabUKce1aYCarVfdxqaWlpYlSpUqJ8ePHCyGEyMzMFEWKFBHjxo0T0dHRokyZMuLuu+8Wq1atytpmy5YtAoC4fPmyXVoNGzYU7777rhBCiDNnzggAonbt2mLt2rXi2LFjonfv3iIqKkrcvn1bCCHEvHnzRGhoqOjYsaP466+/xPbt20WpUqVEdHS06Nu3rzh06JBYs2aNCAsLE0uXLnV5DJrfBRHlHhMmCCFvpZ0nIYQ4dcp5fo8evu2zRQtbWjdu+HwIQgghkpKEWL5ciMxMIWrWdH08ZnH3mRnZ9uJFIW7e9JyG1SrE1au2dX791bxjMYPj5xAdLefPnav9GWVmCtG/vzz/9KRXvLjndd55x3/Ho3eKibF/X7iw7fXVq9r72rHD/jMTQoj33tN/funN2x9/yPPIXboHDnh/7OrpzTft83jnna7XrVjRWNpmf6cjR8rz0d0+v/hCiHPnvN93XpWWln372rfP9n39/HP27TevGTpUfsatWgU6Jz5xVw51ZPLdgzF33323ePnll+3m1alTR4wYMcLlNosXLxYFChSwK2Cq9e3bV3Tp0sVuXufOncWjjz6qO1+GC/LXrpnz4+LNdO2a7uNSW7ZsmQgJCRHnz58XQggRHx8vAIhChQqJqVOnipiYGDFx4kRhsVjEtm3bhBBCfPPNNyIsLMwprY4dO4oXXnhBCGEryM+dOzdr+aFDhwQAceTIESGELMgDECdPnsxa58UXXxSFChUSqampWfM6deokXnzxRZfHwII8US7y009CHDxoP++DD9zfMLu68faFOq0OHXxLyzHNl192fTyHDnn9YNbl/hyn9HT5UMHItsWLuy+oKPN79rS9njnTnOMwizr/n3wiH05oLVOOb8MG9wUzx23uucd++dmz5hby1FwVdn2dfvrJlr6rY3V1/EY+K1dTZqbr9TMyjKXlaWrQwH6/Zn6Onv6/XHGV3ujR+o/dTcUH/WfPHiEuXLA9vNmwIXv2+8ILtu9p7Njs2WdeVLKkudfbADFSkA9o0/qhQ4di7ty5+Oqrr3DkyBEMGTIEcXFxeOmllwDIJu9PPPFE1vpLlizBE088gSlTpqBly5ZISEhAQkICklXDfrzxxhvYuHEjPvroIxw9ehQfffQRNm/ejMFmBzgJcl9++SW6dOmCChUqAJCBAwGgR48eGDJkCBo3bowRI0agW7du+Pzzz92mJYRz14WGqmAt5cuXBwAkqsY/LVSoEKpXr571PjIyElWrVkWRIkXs5iVyzFSi3G/TJqBTJxmsSt003qHblB1X1yV1P+DXX5fNdb0NSKXuB+0tIWyvXYzIAgCoV8+cMcn37XO9rG5doFQpY32lHZsoZmTI/snp6cDZs7b5339ve60emk2P6dOB8eONbeONSpWA116TEd8VH3/svJ7OOD1ZWra0f68OAme2Eyf8k+6ZM0CfPkC5crb8O34OnoL6hYXZB2M7c0b//pUm5FWryr/vv29blj8/sGSJ/rTUrl8H/runzKKOCu8YTO74cd/+70uVsgUW1Mvd9UmrW4grjz5qbL95zcKFwN13AxUq2LpXdO4shy9NTfU+3d9+kyNIqEbQcjJ7tu31qVOySwuZTz0Ep/q3NxcLaEG+X79+mD59OsaNG4fGjRvjl19+wfr16xEVFQUAiI+Pt4uY/sUXXyAjIwODBg1C+fLls6Y33ngja53WrVtj6dKlmDdvHho2bIj58+dj2bJlaNGihf8OpFAh2R8rEJPj8DM6nD17Fps3b8Zzzz2XNa906dLInz8/6jqM41qnTp2s76BcuXJIT0/HFYexYBMTE50CDIaGhma9Vgr5VtUNunq5so7WPKs/g04R5UVpacCff/o3oJtR6pFG9u+XP8CZmUCtWq63efll18tGjZI38P/7n3xfrZpv+RNC9jH3JlCdu8BkpUvbv3dXCNfj+nWgSRPXy5WbV1/GzZ4zRwbZCg933Xf+ww/1p3f7thyGbPRoGRU/MdH9UGZGqc/z1193Xq71kH/0aGP7mDJF5vnwYXmuuMr/n3/KwpY3/TeFAIYPB9q0Mb6tHi+9JPvvJibKQrMQzue7p+/l9m1bYXLjRuCOO4zn48wZmQfHGBUDBhhPC5Dnqbto+evW2b+vUUNG9vfFjz8aW99dwd9IQT63SU01tzD25JPa8//+276gbVSbNjKoo+NDIYXj/83XX8sHZupCpx5vvikfGuak3+6cbMGCQOcgWwQ82N0rr7yC2NhYpKWlYe/evbj33nuzls2fPx/btm3Ler9t2zYIIZym+fPn26XZu3dvHD16FOnp6Thy5Ah69erl34OwWIDChQMzeTGm6Lx581C2bFk8qArUEhYWhubNm+PYsWN26x4/fjzrwUqzZs0QGhqaFe0ekA9bDh48iNatW3v54RFRturdG2je3HlMZ7P8/TfwxBP6a8G1bkry5ZO1cN4GcZowAXj3Xe+2dTRpkoxQXbcu4M11zl0k63fecZ6XmOjdzWtaGqBq0eSWL2NRv/KK7fXu3d6no1Df5A4cKCOXh4Y6B2C7dk0GZzNKXRjVGus7f37neUZrVFu3lrV69erJc/fFF7XXa94cWLYMKFHCc5qZmTJ42t698n1MjHxgcPGisby5Glveneefl8fhGARuyRLnIHeOfv1V/u3Uyfh+FWXKyNp9M4SEyPSMnKvqFhveMPIgKCEBaNvW9XKjBfncEiB4926gWDHX/0tmO33aP+mOGyevZ1o6dwb27JEBVvX4v/+Tn0uZMublT68LF4CvvjI2CoU7GRn+H8Hl6aeBt9923xIuFwh4QZ6yl9Vqxbx58/Dkk08iv8MNzJtvvolly5Zhzpw5OHnyJD799FOsWbMGr/x34xYREYFnn30Ww4YNw5YtWxATE4PHH38cDRo0QAfHIVOIKGdau1b+nTrVP+k3bixrHHr31re+Y22FOqL0m296nw/H4xMCULphCSEfEqhvSlav1i7gjhxpi0r+55/G8+FuGCytoU4jI2UhyuiwcZ6ieKvt2yeP1WLxbcgsM6ib5Ksju8+dK2s2mzSR+S1aFIiKMlZzdvy4rPlSaBXaHU2YYP9e3QzblZ077VteqEZp8Vr+/LK1wF13ycKZ0YcLCjP/z0+e9Hy+6G2i3KOH++VmD6t2992e13nmGdtrL1o7ZtHbJfDgQeC/rocuKQV5PecuAHzxhb71cjqlu8qcOdmzP62RJ8zw3nuul/3xB9CiBVC7trGHt0Zr8s1QsSLw7LPmPCC/fFk+3AgLM7f1lZbJk+XDZzO6yeVQLMjnMZs3b0ZcXByeUf9g/efhhx/G559/jsmTJ6NBgwaYO3cuVqxYgTaqpnzTpk1Dz5490bdvX9xzzz0oVKgQ1qxZg5C83PyLKFio+6+ePy8Li99+a1766iGflJpEd+LiZNNXtYEDzcuPWu/eskZ282bZv/7uu4Fu3eSyM2c8FywUs2YBvXq5L6CrubtR+S9GiabOnfWlrzBS0FO6HAByGC2Fus+7Py1cKG9ejx2TzdG13LwJdO0qC/Hq7gJKDV1MjK3219VnXKuWfTP25s09523UKPv3cXEynbFjPW9rxMqVsuZWCPm/MmyY6+No08bz+Xn+vExT1WUOgPs4E0ZNnuz8oMNbq1bZXuutkfQ3VUymbGm+vHix53WUeyu9rWgGDfJfTWd8vPzNyK19j81ozaD+H1bF7/JIuZa5kt2f+aVL8vq7fLl9XI7/+z/f0y5VyvY6u35zOnbMnv0Egl/D7gUpw1HrKSD4XVBQiIsTwmHIxoD54w/taMebN5uT/sWL9ularbaI01rMjBZtZKpb1z6ybbFixtOYM0ffZ7Jpk/b2HTp4jkBuxCuvePdZVK0qRGqqHB6vb1/zPmN3lHVatZLDshlN+8QJ2+sZM7S/j0uXnLf7bwhUJ82b6z8ms6Ocr1mj/bl5+3l/9JHzfDPzq2eaPNm388Obz+D77z3vRzlXXE3qYRN9/QxUI/A4WbdOiI0bhahRw3M6ynDK5cvr3/eIEe6vu97Kn1+m/9135qftyOi54s6nnwrRsaPnz+33342lm5HhPKTjyJHax+BpWrLE/b5+/tn5M9m5U95f+EOrVrZ9tWzpnN+hQ71L98wZ+3SmTTMnv19+KcTq1b5fc3KIoIlaT0SUqx04IPuZliwZ6JxIrvrFm9U1ZsYM+/dKX3dfIgL7g7oW+ORJ+5YKeu3cqW89VzX3BQv61lfdkdFI8YrYWBmkqU8fc1tn6LFrl6xFNqpGDdtrJdjt88/br/PXX87buWo55i6oolpGhufI7UY99JC56T38sPM8x1Yv/uYYqC479Oghb9fd9Yf11IzdzP7lRYvKPsWOVqwAHnxQBvjUMwKB0sXA8drqzqRJ8nfHl/7MQsguUuouI0pts7vggTnRq6/KkVE8MfJ5rVwJRETIPthqEyfKv/v3608LABxifTlx7MO/caOMzaHEsTh/XrbEiInxLpaII3X3oN9/d14+dao8RzzZt08G0rxwQbZ8c/yfcPU7unOn/N70/DafOCGb/bsKNpjLsSBPROQvOS12xKlT5qZ34QKwaJFsQli9uuto5ep+zcqPf8+e5uYlIsK77dSFQiPmzdO3nqsbEbOCeSl8+W63bjUvH4C8AXPF8Wb56FFz960YOdJ5nqsHJ1rravn2W+NNrr0ZQlXPDbIrWoVRdcHayIgCeuiN8F67tu21Lw82HfuKX7tm/7DMsWuBmqd+smY38332Wed5RpsmKw+f/gs6bMdddPwLF4C+fY3tS+3rr2VXg/r1gS5dZJBGhdFCqifp6baYHYC5/aaN/C8ZCVL4yCNylJCNG52X7d8PNGqkPy3AeEwUdTDJqVPl0JphYXII06go/w6BqXD3kP7GDfl9Nmki4zZUrChHsfjgA/v1XH3X99wju33p6ZOvdyi/RYuMBwsNAizIExH5i/pH4+pV327QzWB2AKkqVWSf9uLF3Uf9HT5c/r18WQ4F98orwA8/6N9PwYKe14mP15+eWT7/3HMtjjrKu9ojj3hOX0+h8cABWQukFZRNCYqkvgnPDu5aYPTv7999//STfICmJ0aDwmHYVZcee8xYjXyvXt5FmDZaM6zUAgIy0rcj9UMuPeedEe7GzlY8/bT9AxvHWkwjfv7Z/n3hwvYPxdwFhVONiqTJ7Osj4PxdatVuuqMU5LXy5mlYZSWwqTfUQ7Vt2GDuGPWZmfa/hePH214vX+55ZAQjEhL0r/vbb/rW8/RwzmghXg93D46HDXOe9/ff3u/LYYhpl6xW7esNIAvueqxaJQv8yj2CIz0PqPXeVw0cmCv7yrMgT0Q505QpstBn5Ic4p1H/wJQoIW/GHIfVyk5mRyg3WuDo31/WehkdDsZdYblCBfnARE9h32wvv+w6unVGBnDnna7HDFdqMk+eBL78UnudAQNsNVXp6drrNGyoPYwdIM85IWTNXHaedwsWyP1qHbuRBzhGCSGDBG7Z4r99GCmYezssq56o96VKyWary5YBI0bY5msFUHzhBdtrdc24GVzdyKupgysCsvZQj9Klned5KrwC2qNBAPLBijtmdnVR+PoQTfkNcbzOVKmiPZxiTpSSIluzzJ8vr9V16gD3329brm4KPmiQDIapprfGVYs/ghauWGF+mo5OnwbGjLFVBuh9yKC4dQvYtk3+Bhh5qAmY0xXQ1e+eK1OmaM/X8zDKyG+KLw84cigW5IkoZ/noIzke8/Dhsv+up36NwUZ9A5Pd9u3zvE5qquyf5o/WA1rNEI1yLBxt3Wq74Tc7srgv+vVzX5ug1LBVr24/7JWauhDwwAPG9u8YBTm74zT07ClvIs1uhuuOLw8rjN7s6vH44/KvkQKXEPb9kl2JjJQ1f3qaTxctagv5BOgbx16P55+XNcZ//OH6RnzDBllrrqZ3nHatB1zq2vfISO3tDh2SzaQdzz1PD/uM/o8p3D2YjInxLk1FbKz8W6eO/fyffpIPHtwNb+bOrVty5A5vo5DrfYh76ZJsEdKvn2yZUa2a7NO8bZt8sPzgg/b9wy9elPcAaq66/mRkAEuWeD80Y5Uq+uNjqJkZS0EtJkZ+px98YOuq5u0oLg88ALRvLwvUd90l5506JWMtmDUWvKPUVP21+VqUri+uHlq74urak1dkQ/C9oKMnav2NGzcCkDNSu3HjBqPW50bZFW00M1OIF18U4rPPnJfdvCnEwoVCJCT4tg+tYylUyLc0zc6PMqWny3UaNpTvZ8zwLT2t79CXKNDK5Bi92dH06ebs59o1Y8dm9LNx/A0ZNcrzNgcPykjFnvaTlub792Vk+vxz18sqV7bPgzcjBOidpkxxvezTT92fy55GEPBmUkar+O03/dtcuiTEBx94Xk/ruqVQovDPnKm9fMwYc45Pz/lltTovW7/e/Xeh/k7+/FOIs2eFmDRJ/hVCRswuV06OkmGUu+NR30u4Wy86WohvvrG9nzvX/XZ69681tWqlva3yuQohz5nHH9fe/pVXhKhZU4irV+3z8eqr2mldvChEixae8+XuvuvIESF69RLi0CH3abjKs9a5/uuv9vkUwv7//fp113lxle6oUc6fqx4VK5rz/2Pk/8zXNM6eFSIkRL5+6y33x+frvn791bdj/eEHY9+J0X3cuqXvew4gI1HrdZ61eYu7DzAjI0McPnxYXLp0KQA5I7VLly6Jw4cPiwx/DLNC5rjjDs8/+mq3bmlfeB1/wM0wbZrrHwr1UF6+cPVDkphov94LLwjx/PO+7cuVTZvkzbC7/ABCpKQ4r+NJdt+MKNPQoa7z+Mkn5uxDceCA53WHD5c39m+9pX1z6C59tcREISIjPW+7datc39XDBlfuvtu878Bxf+4Kwt6eM0an117Tnu9YiHHF6P4++8z9cuW6ZfZDgieecD2UnrI/dzeA588b21++fPrOM3frqOe5etBkhLe/Cep8OA5ZpzzMFEKIgQO1j2fjRrk8I8M2Tz28qNY2yrquPkdlcjXEnGPaPXs6H5enB48ffWS/fq1atmXKtd9V/o38T507Z+65rp5WrbLfl1IwBYRYsEA7Py+95JzO++8LcdddQiQlOR+zHv46PleTGftcssT2Wv1wKCccn+Oxqu/NACFOnZIPYpX7yNu37QvjRvdx5oy+7zmAWJD3kacP8MKFC1mF+Rs3boibN28Gx3TjhriZnBz4fPg43bhxI6sQf+HChWw+O3IZ5cbCjBsrR+of9BYt9G2TlKR94d2yxfz8qdOPiXG9zKx9OE5Fish11MfsTQ2TO+vX678ZWL7ceR1XbtyQN71m3oy0b68/rZs3hRg8WI6t68hoIcVdftWMbJucbDx9xU8/ed42PFyuO3OmsbSPHTPns3G1P1fLe/QQYulSIUJD/bN/d9Mjj7j+PBw9/7z+dJs1E2LWLP3fsRnH4lgY84WSZqdOnvdbsKC+80zvuRFI6nxcumT/PjNTez31pC60W63Ov51a20RH6/t+Z84U4scfXX+GqalC7Nnj+iGGu7R79JC/NcpD5Jo1bct69RJi/nxj5/+iRc77j4/33/+xMt24IR+yfPut/fwRI7Q/kz59PJ+3ZcvalrVrJ8S4cdpp6fmctaZz52RB9OJFIa5ckQ/WjWzvzT49Te3b2x4IDxkiHyArD7Lcnfv+/n49Hat6uVIgN7qPXFaQdxPek1wpV64cACDRm2FlAikxUfaNiYzU30ctBytevHjWd0FeOHHCFgjmm29k/zWjMjLkECH33w80aGC/TB1waPdu+ddqdR8ZeM4c7flnzhjPmxFDhzpHQ/a3a9fkPtWf24IF2hFovdW1q+21p35xffq4Drqm9tVX2sMqeeIu0J4Qct+u+kJaLHIdRYECwLRp2utmd19wLUuWeL9ty5ae11GG29KKoD5hguvtatbUn49582R8is6d9W/jyg8/+DfInTtGIpH37ev6GuRo717nsevdOXtWDhdWvz7Qpo3+7UqUkP1OV67UHiPeW998I4N2LVwIFCnifl2rVQ7TqB733MzrVKCEh9u/d3eurFsn11fHF7BY9A0jqTc2yMCBzt/FzJm210WKAM2b60vL0Q8/yACJgBwuVB0EbuVKORmxcaMcxUEtO+LZTJwoh8b7+mv7+ZMm2Y/eoOjUSUbCd+f5522R87dvl9ObbzrfJ2dmGh/ZICNDxpEYNMg2r2FDY2noiW1j1Natcpo82fZbWqWK69FffvrJFjzVH0EhFerAh1pOnrS9rlbN/r4gr8qGBwtBR++TkIyMjIDXThuaoqLk9Mgjgc+LjxOb05tA3Y9JT39oLU8/7fyU+4svZA2641PQ33+3vXb1/Y0cqf0E9c03ZTP9lSu9y+fly0JUqCDE7Nm2vsnq9CMihKhfX4hnn3Ve5gs9T4cnTbK9joz0bX/u9q/u06l30ooR4O2T9pMntef//bdM999/XW/brZv+7yQz0/s8btkiRN++QsTG+nbc/ft7Xkfv9+ZqmjpViIcfdp6/YoX7tGfNEqJqVVl75qk5fFqaEGFh+o+lZUvvP3s9kzf968uVc/95qO3caSztL75wnrdnjxBt2gixa5dv368yXbwoxLZt/ulepBg+3H0ePvxQXjePH7fNW7rUOZ233nJ9bug99/1NnQ/HVkWu1jOS5+XLvT+/FXFx8n2nTsa+d3f9wdXT9u3m/D8qMjOFuHDBv//7eibl/Dt3zpa3BQs8f5ezZzuvU7Kk/Tppae73fd99Qvzf/9nPK1XK9Xdl5Lj0xE8xa1LnrU4d+T9y7Zp93pXzU88UFeXf/KamGt/m5En9/1MBwqb1PjLyAeZo168Lcfq07b27CxkFP+W7PX/e/XppafLi99BDtm2mTvVtn8o5pTeok3KTq/RnVgJ4de7seVtvHuI4pjF/vuv0HZuP+cLbH1KzqNOdMUOIp56Sr598Uv4dPdp9XuLizDkmQIg33nB/vI6FyuLFba/fecfYZ+RtHs1Ks1w553mNG9teK03jzc4/IMTrr3v+fPTsS5GcLAtxERGe19V6gGfm9OWXxreJitL/WRjtyz5njrFzyNNnbvScNIunh1+//WZb9803hWjdWjtgVHq6c/9Wxc8/Z+8xueKYN1eftS/fg7fntxkWL/YcjE1vU3+9+e3b17//995My5fL/32tB5GOrlzRTmPVKhl4TQghduzw/Jk6Bv1cssT8c8Tf0+3bttfz5rnOv6t4Ro5Tjx7OD+LNnH75xfg2R48a/rfKbkbKoRx+LjcrXBi44w5g9mznZX36AKtXZ3+eyD8OHrS9btbM/brh4XI4onXrbPPMGk5l8GB96x0+LP++/rr8qwwptmGD522//dZwtpw89ZTrZY7HoNV8OScRQt96b79tG+YnI0Nu98EH7rcxcwzeGTPcL7dY5DBOlSvLrhShobZlISHm5SM7JCQ4z1OP9f7pp+6379jR+31nZHi/rZZixeSwXermna+9Jocy6tbNvsuEnjG+PXEcik89PJbWUGtnz7pPLyJC/77dNRlVhgHTu747b78NdO/u3bb+kC+f7TbX1XLF5MlyTGvHZumA/J995BHbe3V3rfbtbded3M5I1wkA2LXLt2G71Pr3l+m5Y8YwoGpm/CabrU8feW3QM5RZ0aLa8x9+GOjRQw7l6Wks+wIFnId11HseGBme0t/Uvx+3b7teT+v/X8vQof4ta9x7r/FtXHUfCFIsyOcFL77oPO+77+QFioLDkiXAc885X1jXrZOFguPHbfO0ChFa1IW0HTt8L8xnZsrxhPWYOtX7/SjHZ2YhU23hQvv36s/WqGrVfMuLJ/36AU2bOp8XR44A0dH289QPJDwVfhSeCt9me+kl2UeualX7grzRfon+sGCBb9tbLLIvZsuWwJNPul936FDv92NG3JBixZznVa0qY2EA8v/3jjuANWvsx+ZWf2fe6tbN/v2DDwIffyz7uTr2H+7WTfbrdDf+91tvGdv/4sXyrzL2siIqSvZxN8OkSYGLGeDJypXyM3//fds8I+dU5cqysN+1K/DJJ/bLcuIDuTvv1J5fv77ttdG4G9u3Ay+8oH/9li3NLcyp49P4S06IRWIWT78vbdvaP4jVUq0a0KuX/bxChfTt36yHOGZQ30vUru17etWqyd++PXt8T8ss7ipyglE2tBAIOrmiab1jUzlXTeco57FaZV83dRNy5ftSj1er7pPWpo2+79Vd36ZatYT46y/ZT93VuZ+QYN/MUr391av6mzY1aOC8veN7rX5rgOyHpkRjf+YZfZ+pL023DhzQtw9HmZnejTfryalTsguCus/59u3261Svrp123bryr7oftbu8VK1q7mfpOD31lOvjVPetGzfO2GfkbX486dNHiI8/9i7t77/3nL5Cb19XrUkrroE7SncL9dSmjbE0FN4Os1aliuxzPXSo82/ViRP2+1A30+zSRc5zl7a3/SHffNP53HDsU62O+6H3HFIz45z0F3Vz49zkf/+Tx9S4sXyvfIdPPGG/nnos9f37je/HU9wBf3/HZl2jXU0tWshrmt7RS1wNDelqUg+XZvbkj8/ryBHndNxJTJRxf379NXu+L73T/v221+rhGPV8Zlr94dXeey/wx6fnu8kB2LSegL//tn/vqrb16FHPaaWmylMfAKZMAVat8i1vOUVGhozEmZwc6JzY++QToE4dWy2I8tkDwMWLttfqZui//qovbXe1QMeOydrdiRNlhGKt5eXKAffcAzz6qHPNv5EWHgcOOM9THyfgOiL0//5ni8b+1Ve2+fv3ywj6ZnUTUBw/bntifuWKjDSvbg2gLMvIsDW/W71a1rCcP298f6+/7vxZqFWvLr97VzVJgGz27Ch/flsNgd5mcUpz4r//lk/V1RGUzeCuBlcdDVpdkzd6tLl5MOLbb4Hhw73b1khttS81IYULG1t/zhzZ2uDCBdu8nj2927e3Tc179pStS6ZMca4dc6zFbdXK9lqr5YAjvee6I63vSz3vqadkVwLHFjxGeGqZoe5WkN2KF5fXUnfXomD06qvy+h0TI9+3aAEkJdm6HSlee832uk4d4/vp18/9cmW0Em/Pz+z28MP258Lu3fL/Vk/UfsC5dYZCPbKKomBBeY/hD940xXZFXbOrjAjyxBP6ti1TRv5O33OPefmZPt33mm91RH0jLWhmztTu+qSm7mpj9r2EozvusL3evNm/+wq0bHiwEHRyRY284ziVN25oP5VaskSIlBTX6ajHNN2zJ2ieZukyaFDOPB719zNunBBnz9rejx1rW08roJan43ngAe+eWHoTGVRP+r4sV6+nrgksWdIW6ff2be9rCbX2Ex4uXw8aJMRdd9mWeVtL62pSxnd15Cooz/r1rs8hremnn/Svq2cdrWjVeiZ3oyUorQcAGdn/44+FGDDAcy2B3vPGccqf33O6vqSv/sz9tQ9A3+fjyv79siWMLxHSvcnzyJGu03Ac81fdEmnPHjnv/vvdn7/e2LBBO5158+R1VPmcHaNZG3H6tPvPhaOzBI46cKs3/w+efndOnZLjoSujdpjN2+uHq2nQIP3ptmun/X/oOO/zz+X8jAz7/6M5c/xzDHPnur4+epNeTIz827KlfVrnzsmWRUYULer78Zn93XtSooT9uufOeU7j6FHZGmHfPvO/X/V0/bpsubh4sdyv4/9jDseo9T7KFQX5oUPtT1pXBTHlZnnNGu101Ot++23Q/BPoklP/qR2/ow8/tL1+/33beu6GYhowQH5fntLWexGPjDT/QuvpJlZvfrUi0K9fL5vEm5lfo5+fL9OQIbbX6qFf3G1jtcrowc884zl9dTPvyZN9P24hhPjsM+PH6W6EhUaNbOtNnqzrX8fj5+SuuWuVKvrTf+cdIUJCnLu0uJs2bDDnGPR8F4HkTZ4dm7+rl6Wm2i9TN71XfqPVI3CY9XkkJ+tP57nn5DobNxrfz++/y+4Djvl+5RXv8k3mUD8w8pbjaBvZ+X9qsXh/DdGaFiyQ6eq91qnft28vt23Y0DZv9mznPL/+uiwUp6Xp35dZ10Zv00tJMeeBm+NoOb4cX3Z8XkLYj1ChOHZMXxoHD3ref4UK3uXbsZuM1ueSw7FpPTlHJXXV3FiJHv7qq57T3LbNpyzlKELYv09MDEw+9FA3JVY3mb550/U2ixd7buZkhKeIrd5QdxPwhVbgkvHjbU0XzfLTT+am5860abbX8+bp2yY2Vjb9Vnc3cEUdtXX4cOC99wxlT9NLL8lmxidO6N+mQAHXy8yKWq9u7u0uEGRcnP40x4+X0dp/+AF4/HGgQgXP27g71ryuTBnXyxwD3OXLJ6+DR47Ymtb7o+lk/vz6150zR/6meDPaQIsWzt1kataU3YQocMqXl9HfDx3yPo1Bg8zLj1Fnz8pm6952hXS8ZzTSNcixe4/yOajTuHzZebsZM+RnrjTXD4ZuB0WLmhPEsUQJ5/vSnO7VV4FFi+yD5ypdDDzx9Jl9+KHx4KnjxwOVKslt8xAW5HMrx76KZvQb9nefFkfnz8t+0o79/c0wZYr9++vXjW1/9qwsYH/0kX2/cyGADh3k5//zz77n05G6P6aRYZUuXwa+/trYvpKSZCFy2TL922hFaXc1BIueHz9v+0P/9pt327nTubPvadSpIx/AfP+9/m3GjpV/3Q0FA+gbZkehLlRaLMCYMdrrGblByZcPGDjQfd99R+76V6p/xPfv15+mo6Qk+feDD8wd6SAsTEZu/vpr4PPPPa9vZt/M3MZIoRmQ/R/VcQT8MaqBOhr/K6+Yn747LVtm7/5IW8uWQN263m+v5wGfv1SuLEe18WZ0or/+cv6fUkaT0BO/Qx3HArD9juzda5un5+GbmdH3lRE3cpP+/bXnr1mjPb9mTTkaheN3O3Cgd/vPnx947DE5cohabKwcLcRdBZCn+5lRo4wV5Nu1kyMLxMVlz6gNOQgL8sHO1RM8x2BinoLauavd9YekJGDcOPsxiB098QQwdy7QuLH5AczefNP+vZEbwYwMORTT+PHAiBEy4Mu1a3LZvHnAli3ytbshkcyQkqJvvcxMoFQp/UFYFNu3yzGdjQSdOXPGed7WrdrruqsFVn741QFLcoMWLWQhukcP+2CF7igFUU9B1q5e1Z+PevXs37sqsGdm2s5nI5SHRtWru1/PXY2L+kfc6NBvysOPsDBbTcfo0fb/597evGi5+27P63gbCA6QARAB44Hscoru3d0HFXW8YWvd2lj6L79s/75UKWPba1F/X67GmfaXnDhMGwUno9edSpWAJk2c5yv/A+7ulRISZHBkx/NXq9KhUiXPefE2sKiW8uXNS8uf1MMWjhzpfl3H+1jFfffZXqsflu/bB7z7rvP99Jw5RnLoWVSUrOQqW9b1Ourx6l3RG0gRkA+tAPfnu2NAy1yCBflgtmuX/EdR17Rev679pHPHDvdpOTYt//pr2WTGlbQ0/fnUUrq0LMi5uzFV18TPnu3b/jzR23wZkNFaHX33nfy7dq2+NNLTtZsg62la9c8/tjQ8SU31vlb7kUe8286Rq9o25cKrRalF2L7dnDzkFOqa8E6djG3rKuqvwkgtXtOm+tft0MH98shI53mPPy67Tmg9QFT/r7mrifVlTPIRI4BZs2Tza7UhQ2yv1TWuvoqMlA8d/WXyZPn/oo4sHwyiouQD2++/dx9h3vHGf9Eief35/Xd9+3EseCitZypW1J1VTaNHy4e2w4b5lo4ebdvaXpsxfjORN86ds71Wn5MKd/cokZHOXWEA+4KlQk+3A72/acpvinqkAUfB0mxdXZAfPNh5uboWXv2gXN1yUv3bWamS/O3Yvt3+N+/tt+XfWbMC04VBTyssPYV9QJZH9Dzk9lSxEKyyoc9+0AmaYHfqqOUKV8EfXn5Zf2CL8eM9r9uxo+f8vfOODL6lFfFVnZYSvXLzZtfrVKvm3WekyMwUYscOGThJGYPcaGAPxdtvO2/74otyWaFC2mlmZtqPza4sdwywtXevvmAeZcvqW++jj8wLfOLtpD5evdPjj8vt7rwz8Pk3c3r9dfvvW+92ZkXeV38njrxNa+FC9/8vX3/tvO/Vq2X0Wne6dLFt07u3+3X1Uo8AMWSIDFinvK9Xz/f016yxP9bnnxdiyhQhdu40npar78vdd9G3r+/H4Ct1fn77zfUyT+ejEY5jTl+9KgMkxsb6nrYvEfyN6NDBlv/Ll7Nnn+R/Wud7RET25uHvv+XIDkuX2udDHUhX63/x+HEhQkOF+OAD2zx3Y4Grac1Xz/vnH8/5vn3btv5TT9leR0fbXr/wguv9qqcBA9zvK18+c35HfZWUZEs/Pd1+fxaL/WgKN24I8fPPMuCvmjog6P/9n779ZtfxKdzd09Sv7zpPyqQOnKjXnDnZc2wmYNR6HwVNQb5wYfcXSvX06queL0pLl8oLvlkXMWW9b75xvUzvD4E3/3gTJwrx1VfytRJRu2VL+5t39fTHH/rSdZd3rXkbN9reK8MluTqun382/mPibnrkEe357drJ71odGdwfU9eu8riMRr3/6y+5ndkFeVffvTJVqeLfz8Pbgvwnn5ibDyPntavp8mUhtm3zXNBJTPS8by3du9u28aYgrEU9ese5c0I0b257/9lnvqd/86b9sR475n1af/whb75jYuzna30XPXvKCMLXr/uSe3Oo8xUfb79MKXA7Plj2lXpEFTPSC4SJE235V6J2U/DT+n+tUSNn5OfUKfv3o0c7r+94fXcXbdzVfrTm/fuvvvxarTIqfHq6vJecMEH+9vz+uxy+1DF/rvL22GPu93P0qDm/o2ZYt842AobWPseNkw+I3Vm0SA4ZqPdBpON+tEYVMJurz1WpGPN0//H55/LBh17qYblzOBbkfRQ0BXlPF0p/T9euyZr5Tz91zpt66J6yZe2XKWNvak3qGz9fLpqHD9tvp7cGWw932zrOW7TIed6XX7rep5GCfL9+ntdp2VJ7/nvvyf2px0LXM82ebf/E2NOktLJISZEtGVav1rfdhQtyuxo1zD1n1U+qtSbHMaHNnn780f77NjJ8mbeTeqxXZTJyXrua9FJ/pi1a6N9O/RBKebBjhuPHba0BWrSw7eOLL3xP27GWwXFYNTNofRfDh5u/H2+p83XxovPy+Hjzx/TNDQX5K1ds+c+uVgDkf+5+FwOdH8f3Z8543v7IEX2/CVrz1fP81epEXWlVr57t9fjxnrdVhpJzN0xpdl9nsmufjvtR7sH8Sb2/du1sr5XWGmZ/9mYMKZlNOPxcXqGOiGq1AleuZO/+ixQBNm2yH7qudWsZbKJhQ9s8x/73f/7pOk0lSJWvHD+L7BheTgjneY8/7jzv2Wed5926Jfu8G+mrpCeavKs+pkoAu2bN9O8PkKMIlCypf30laFXRosCkSbbIt54o/afMjBZdpowM1OMucFVYmIxBoO4naCbHvoJKPIuuXf2zv/799UVU96ewMODhh+VrIyM5qPvQGQl640mNGkCtWvL1M8/Y5hs5r13xJaCdL3yJJ2C2qlVtrwsVcl5erpz5n1NuiPJevLiMKREbG7jziMx311221zdvAseP+z8Qrrf09ElW/3+rOQ75FRXlPh1/neNKPho1sv9d1boXc6QMJTd5sowT5RjjxcwhfXO67A6sqh5dwdfYJq6o7yPMDqAdQCzIB7Nbt2yvQ0LMuRH11a5d8q96XElH7oZ6++ILOZbopk2+5UMdPd3IP6y7caYzMtyPfe7tEEjp6TKydoUK8vgVSrRyf1Au0iNG+J6W1pBzX3whh5pxDCim58e7WzfbuNJGHzS4uskAbN+dVuAdtYoV9UXUBZyPvXt39+s7FkjDw+UDIHeB/3wxb57zeaQVQMffVq6Ux6lVsHNF/f9kZkFe7fnnba979jQ//RIlzE9Ti5HP1d/UD2OzK1+5ZbihWrU8F4AouDRqZHtdoIB8kJgT3HOP8zyt33JHBQrIEXMuXbKf73iNXrdODt337be2ecWL2177q6AYESHvMffutX/AZ2R/Foss+CsPfBX9+tleP/mkb/nM6dwFJzXb3XcDXbrI1+pzxF05whvqc9TIcL05HAvylP1OnXK/fPBgIDraWJonTthHOB861PZ62jT96bga0u3SJVnr5W44DW8tXSofyiQl2Y8T789CgDIcTNWqMqq0UeqLvNaQc82bG4uMrvjoI/sxUPUO+xQZKccs/d//PK+r94GLnmj/Z87YD93y1FP2y0uUsB9xwd2+leHoSpd2v08j4xqHhwMxMfbzXP0/qMc5Nzqutz9kR0HeYrE11vPHMfvj4eq+fXLs3hYtbPM8PUDKTgMHAtOnu2955U+5pVBPucPEicBDD8mRG3ICpUCrdY+ld9jDokWdh3h03LZePeDQIaBPH9s89ZCf/mxFVKiQzM/DDwP168sWiGYMSVm8OLBihRwV4+OPfU8vp/J0j26WPXuAAQPkZ1q7ttxvXJxteZUqssCtN3q9J2Fh8ne+UKFcVZDP+R0FAiBo+sgXL+7//rV6p1u39AdBUfeFMTK5o6xz+LB8X6yYd/t46y3t9J99Nvs/U/Vx+SNttY4dPW9TurRt/Xvvdb+uuz6eRrdTljkGvrvnHjkywvvvy+itQthHdHV13K5GLXD8XGbM0PdZWq2yT93o0c59f5V+Zm++KdPzxGqVAcvc7W/mTBnVX+/3PGiQ++9e8dVXtnX69jV+Dplt4EDnzzEY1KyZPZ/RoUO2/WRm+ndf/vDzz0I0aOAc2d5bymfRqpU56RHlRmfPCjF3rrxnE8K3a7p620uXPK+fkCBE3br6I6nnBHrva7Jj//78TVHvIyf+nqjz9+qrgc6N37GPfF5Rr16gc2CTkqKvefC77/p3bPCRI2358cZPP2nP97Wpf073xBOe15k40fba05N7b/u/udvu00/t3zdrBowfL88ppQm/nlpVdU3EL7+4Xk9vjYHFIp/Of/CBc/5v35Z/J08GXn9dX1qemiMPGCD77/3+u333GkB7/Gm9tdlt2thee4rV4Kl7ghmWLrW99leNvD/8/LNs5eKum44Z6taVzUcPHvS+W08gtW8P7N9vi6PhK6WFgjruARHZq1JFxulRrvFKrCVvWiSp+//raX0UGSlr6YcNM76vQFG6+QGBj13x44/+S1tdnsjpvye9ewc6BzlKDv+2yC0z+jeb5epV9wHlbt0CUlNlYcds//xje/3DD76l9fff2vPVzX3UgqmA4Y5j3IJffnFucq8VpE/x22+2145BbxwZDfRz7pxspuvYFLBAAed19dyMhITIZlXJyUDbts7N4RVKny1fWK3ebXf1qn1Td8Vzz9m6RbRoIW/Gjh6VfRv37gWOHHHeRn18jn3+1GrUkNeUKVOAIUPc5++77zwdge+UhyBAcP2fVawIjBkjb1r9rWnTnPVAN5C2bJExWtxdp4jI3saNMi7N7t3Gt929Wxb6uncPfCHXX/wVeM0bnTv7L+2tW2XX0ZxUrlD75BPb6+rVA5ePHCgHdIQkrzVu7N12zz4LfPONc22eL8aPBxYscL38rrvM6SOWmelcG7xzp3dpLVokaz979fJu+99+kxe+nBK8xpPz52VN6tSpzsu+/tr+fdu2cgoNtbVyUP9Qd+0qL/wA8NZbslZtwwbgjjs8fx4zZsh+a4r27W1paalUSTv4nFakd3Xhz53QUFuN+9SpskDs2CqhalXZt1HdZ98obwNXRUTIfsaOcQY++sh53Vq1gNOnbe+VPL/8snyvrik5dsz9fpVWF1evai/PzJTnQXbftAVTQZ4Co3Dh3BG9nig71avn/W9cvny5Kvq3pgULZB97f1RC5SRlyshWZDn1gYw6xoHeYMR5RMBr5GfOnIlq1aqhQIECaNasGXbs2OFy3fj4eAwYMAC1atVCvnz5MNhF9OXp06ejVq1aKFiwICpXrowhQ4bglpmF1pzC25N57lxgwgRj23TsKP+6CiTkrhAPyOZUvkbLvnRJHrM6YIqWUaP0pXfHHTJStWMN8pYtshb4xx9ljxxXWrcG7rxTe5ljBGw9Q594a88e+f389Zf79SpUkEPfaA0B56op1YgR8oHHvn3289XBBJXPoFMnfQ811DWIoaGyFcWQIa6HynOleXPned4MG1eihByiTauJ7+rV7qPdqqOeK6xWGW1VCN9+FLVqdPU0X1yxAvj1V/nABNAfwEjN1fmQL19gfuhz0vBqRESUNzRsCBw+DDzySGD2/9BD2bevnFqIB7S7DRKAABfkly1bhsGDB2PUqFGIiYlB27Zt0aVLF8S5aMaclpaGMmXKYNSoUWikHtJD5ZtvvsGIESPw3nvv4ciRI/jyyy+xbNkyjFRqFfMaV2NIP/20++0cm2tu2CCH71q/3vu8+DrEVseO8onhokX28x0L23ofUrRoIS9cjgX/Dh1kP7KuXWUN5bhxspBqxGOP2b+fMsXY9gplrHhXDwwAWaDduNF+mBuj1DXHjs23HnvMOe18+WS09j599PWvd6REl09IkBFwp061j8Kth+PQdoD7NJo0MZa+wl1zfa0fPotFnj++UvouGhUaKocWUgq/3tSYZOfQM3rk9D57REREZnNXmZSXNG0qKykCNRpKDhbQu6OpU6fi2WefxXPPPYc6depg+vTpqFy5MmbNmqW5ftWqVTFjxgw88cQTiFD6iTrYtWsX7rnnHgwYMABVq1ZFdHQ0+vfvjz/z6pfvqi+JeqxGLY4F13z5PA+L5W/qWmH1xc1Tc2FX9BQORo0C3nvPdRA8Vxyfono7bF3fvrKGVz2+vNqNG7bXvhR21A929I7d/txzcoxYT4HRtLz6qvwOfRmeS6sQXb68/fuVK22vtWrw9ShSxPUyb449u3lTIw/IgJEnTpibFyIiItJn8mTZ1c6bYYJzm1699N+f5iEBK8inp6dj7969iHYIYBUdHY2d3vZ5BtCmTRvs3bsXe/bsAQCcPn0a69evx4MPPuhTfoPOO+/Ip1dHj9rPV9esfv89MGiQ9vZaTYYBY2NY+9PevcCBA0BsrCxoB5LWuRUa6lzQfPhh/Wmqt7VYtGufAdfzjVIXSIO5GbNjoVX9+Xgby0CrX7oiGAryjg839Cpa1H1LECIiIvKfOnWApCQZQJVIQ8CC3V26dAmZmZmIdOgHGhkZiQQfhu159NFHcfHiRbRp0wZCCGRkZODll1/GCDeRGNPS0pCWlpb1PsXboctyij59ZPA5wLlG7ddfba979JDTZ585p+GqMJdTmrgeP+7cfD1Q5s2TfcbVTf7z5ZPBBLdskUHjAFk7fP266xre8HBAOQ8dh1pzrE3+8kvg/vvNyT9g38LB2xrc7FCkCHDtmuvlWrX0mzcDa9cCr73m3T7dRa31ZsieYBWoPoJERER5VU6+J6OAC3ipzOJw4y2EcJpnxLZt2zB+/HjMnDkTf/31F1auXIm1a9fiAzcRJydOnIiIiIisqbKrgG7BoHZtW5ArwLmvrlYhskcP53kWi3wSCNiiluckegPa6eVuWC4t6gBoZcpoxyIIC5NDmKk/c1eB027dkk9d1WmqOV7In3lGRlU3i/p/LifXyP/8s+wH7yYopp2OHeVwd9OmeV97npHheln//t6l6Y1A9VvftEmOdDFvXvbuV+93TERERJQHmVaQ//PPP/HLL7/oXr906dIICQlxqn1PTEx0qqU3YsyYMRg4cCCee+45NGjQAA8//DAmTJiAiRMnwupiTOeRI0ciOTk5azrnTeTrQHEclunIEfumtOrlL7ygncbSpfJmXS08XDZdP3fOeIR7QN70+7NlQ2ysb9s7FozLlTO2/Vdf2b93F9ncFaUffc2a8vNWp+E4IoE3D7eMPOxQt7TIyZFLmzeX0e3btNG3vhlPsu+7z/WyatV8T18vT6M16PHmm8a36dBBjnRRtKjv+zeiTRsgMdHcYTKJiIiIcgnTCvIDBw5E+/btda8fFhaGZs2aYZNDAXLTpk1orTUMlE43btxAPofm3yEhIRBCQLiI/hgeHo5ixYrZTUEjPd39cosF+L//kxG7XQQRRIEC8mZdrXhxWQjyZoi7Bx4AnnpK3vj7EuXenxwfTugN5DdkCJCcLIPQeWvPHuD994Hly2UhRR2sb/VqGcG9VSvv01e4q0l2VKKE7XXDhr7vOzdxbD5fv77rZf705JPebxsfDyxcGHxj4ZYpExxxCIiIiIiymWl3oVu2bMHt27cNbTN06FAMHDgQd911F1q1aoXZs2cjLi4OL730EgBZU37+/HksXLgwa5t9/0Uuv3btGi5evIh9+/YhLCwMdf8LwvbQQw9h6tSpaNKkCVq0aIGTJ09izJgx6N69O0Jyez8Tx7HLFcOGyckIb2qYFVOn2l536aJvm9Kl5Tjx2cVxyLTBg2VwQE/y5/fcxNlTbXHz5q4jqJs5ZuiLL9oCtbVs6X7d2rVlRNB//zU+1F5eoy5YZmchU/0Awahy5cyp0SciIiKiHMG0gnwFL8Y87tevH5KSkjBu3DjEx8ejfv36WL9+PaL+G9M6Pj7eaUz5JqqxoPfu3YvFixcjKioKsf81tR49ejQsFgtGjx6N8+fPo0yZMnjooYcwXgn+lpupa1W98f338mGA3sK3K6VK2b9ftAh4/HH32zRsKPs/O2rQQDbx95bjA4L8+WVLA8fuG3qHh3PXAuLSJRlMUCvmQHbr0sW+2beepuh6HmSQPJf37pWvszP4o1kjFBARERFR0LMIV+3NXXAsWDuq4hhcLQilpKQgIiICycnJOb+Zvbo/83PPAXPm+JaeEJ77SKuX9+4NfPed/fK4OEAdMFAI2T9/7lz5/vBh+dBB3Ze/Y0fnfvqAHLJt1Spjx6D25JPAggW291euyGBuji0OEhOdC/euGPuXMY/yuR85ImvQtezYAfzvfzK4W8WKwM6dcqz3Dz7I/j7OgaI+P836rpQ0J0wAhg+3jRpQs6Y56buSnCy7YYwc6RwAkYiIiIhyFSPlUMM18lWrVnUbVT4zM9NokmQWx8B33jAa6KxtW+eCvOM5YLHIBwyDB8s+9xERzukUKCBrHG/etJ/v6zjWjzxiX5AvXlx7Pb018oEkhOcHLW3b2oa7A4DWreWUl8TFATNnyngGZqlUCfjnHzm0Y2go8F/3H7+LiLDvqkJEREREBC+C3cXExOCvv/7Kmnbv3o3PP/8cNWvWxPLly/2RR3JH3S8+EMPEOdbyVqjgOkBevXrahXhAFj43bgTuuMO+n/hzzwElS3qfv5wcgd0bue14/KFyZWDiRHMfzhw/Lgvyvj5YIiIiIiIygeGm9a6sW7cOH3/8MbZt22ZGcgEVVE3rf/kFaNdOvs6uJt/qwuS1a7Zx0hMSZKFb7zjk6nT++Uc2BQfkOOF79sjXJ07IqWtX2VzcaC1rUpJ9n313n5GSn5deAs6flw8W0tKc1wtU03oiIiIiIsq1jJRDTYvUVLNmTfzxxx9mJUd63XsvcPAgkJoamP0XLgwsWwZ8/bXsY663EA/IqOoKdbBEpRAPyOHZunSRfwcPdp9e797A9eu2scPLlrWvzV+zxv32ixYBr70GfPaZHAbuwgVZs0tERERERJSDGO4jn5KSYvdeCIH4+HiMHTsWNWrUMC1jZEC9eoHdv7djqqsL/a6ajCu1/XqG+ereHShUCPjrL+DDD4Fx4+T88+dlRHlP46M/9picFCVLAiNGBKbLAhERERERkQuGC/LFixd3CnYnhEDlypWxdOlS0zJGOdiuXUCrVr6nM2IEsHQp8PTTrtepWtX+fePGwL592usqXQwaNpSR2hUVKtjX+PtiyxZz0iEiIiIiIvKS4YL81q1b7d7ny5cPZcqUwZ133on8+U0blp5yspYt5XBtjkO4GVWxIvDvv85jcQ8eDEyfrr1Nr16uC/JGmvUbMWUKMGyYHBXg/vv9sw8iIiIiIiKdDJe82ym1npS3mTWmtWMhHgDGjgW++Qbo1s15mbvCesGC5uTJ0dChciIiIiIiIsoBTAt2Fx8fj7i4OLOSo7wsIkJGwP/qK+dlHTu63s7VGPFERERERES5iGkF+fvvvx/VqlUzKznK67Rq6gGO401ERERERHmeaZ3aFy5ciBs3bpiVHJE2ZWg5xZUrwFtvAa++Gpj8EBERERERZTOLEEIEOhM5TUpKCiIiIpCcnIxixYoFOjukdvOmHGJOwdOXiIiIiIhyASPlUNOa1hNlC8caeSIiIiIiojzGcNP6zMxMTJs2Dd9++y3i4uKQnp5ut/zy5cumZY7ICQvyRERERESUxxmukX///fcxdepU9O3bF8nJyRg6dCh69eqFfPnyYezYsX7IIpEKC/JERERERJTHGS7If/PNN5gzZw6GDx+O/Pnzo3///pg7dy7effdd/P777/7IIxERERERERH9x3BBPiEhAQ0aNAAAFClSBMnJyQCAbt26Yd26debmjoiIiIiIiIjsGC7IV6pUCfHx8QCAO++8Exs3bgQA/PHHHwgPDzc3d0RERERERERkx3BB/uGHH8aWLVsAAG+88QbGjBmDGjVq4IknnsAzzzxjegaJnCxZAlSqBMTEBDonRERERERE2c7nceR3796N3377DXfeeSe6d+9uVr4CiuPIExERERERUXYyUg41PPycoxYtWqBFixa+JkNEREREREREOhhuWk9EREREREREgcOCPBEREREREVEQYUGeiIiIiIiIKIjoLsgfP37cn/kgIiIiIiIiIh10F+SbNGmCOnXq4O2338bOnTv9mSciIiIiIiIickF3QT4pKQmTJ09GUlISevXqhcjISDz77LNYvXo1bt265c88EhEREREREdF/vBpHXgiBXbt2YfXq1Vi9ejXOnj2LDh06oEePHujWrRvKli3rj7xmG44jT0RERERERNnJSDnUq2B3FosFrVu3xqRJk3D48GHs27cP9957L+bPn4/KlSvjs88+8yrjREREREREROSeVzXy7iQlJeHy5cuoUaOGmclmK9bIExERERERUXYyUg7Nb/bOS5UqhVKlSpmdLBERERERERGB48gTERERERERBRUW5ImIiIiIiIiCCAvyREREREREREHEcEH+qaeewi+//OKPvBARERERERGRB4YL8qmpqYiOjkaNGjUwYcIEnD9/3qcMzJw5E9WqVUOBAgXQrFkz7Nixw+W68fHxGDBgAGrVqoV8+fJh8ODBmutdvXoVgwYNQvny5VGgQAHUqVMH69ev9ymfRERERERERDmB4YL8ihUrcP78ebz66qtYvnw5qlatii5duuC7777D7du3DaW1bNkyDB48GKNGjUJMTAzatm2LLl26IC4uTnP9tLQ0lClTBqNGjUKjRo0010lPT0fHjh0RGxuL7777DseOHcOcOXNQsWJFo4dKRERERERElOP4PI58TEwMvvrqK8ydOxdFihTB448/jldeeUXXOPItWrRA06ZNMWvWrKx5derUQc+ePTFx4kS32953331o3Lgxpk+fbjf/888/x8cff4yjR48iNDTUq2PiOPJERERERESUnYyUQ30KdhcfH4+NGzdi48aNCAkJQdeuXXHo0CHUrVsX06ZNc7tteno69u7di+joaLv50dHR2Llzp9d5Wr16NVq1aoVBgwYhMjIS9evXx4QJE5CZmelym7S0NKSkpNhNRERERERERDmR4YL87du3sWLFCnTr1g1RUVFYvnw5hgwZgvj4eCxYsAAbN27E119/jXHjxrlN59KlS8jMzERkZKTd/MjISCQkJBjNVpbTp0/ju+++Q2ZmJtavX4/Ro0djypQpGD9+vMttJk6ciIiIiKypcuXKXu+fiIiIiIiIyJ/yG92gfPnysFqt6N+/P/bs2YPGjRs7rdOpUycUL15cV3oWi8XuvRDCaZ4RVqsVZcuWxezZsxESEoJmzZrhwoUL+Pjjj/Huu+9qbjNy5EgMHTo0631KSgoL80RERERERJQjGS7IT5s2DX369EGBAgVcrlOiRAmcOXPGbTqlS5dGSEiIU+17YmKiUy29EeXLl0doaChCQkKy5tWpUwcJCQlIT09HWFiY0zbh4eEIDw/3ep9ERERERERE2cVw0/qtW7dqRqe/fv06nnnmGd3phIWFoVmzZti0aZPd/E2bNqF169ZGs5XlnnvuwcmTJ2G1WrPmHT9+HOXLl9csxBMREREREREFE8MF+QULFuDmzZtO82/evImFCxcaSmvo0KGYO3cuvvrqKxw5cgRDhgxBXFwcXnrpJQCyyfsTTzxht82+ffuwb98+XLt2DRcvXsS+fftw+PDhrOUvv/wykpKS8MYbb+D48eNYt24dJkyYgEGDBhk9VCIiIiIiIqIcR3fT+pSUFAghIIRAamqqXdN6JbBc2bJlDe28X79+SEpKwrhx4xAfH4/69etj/fr1iIqKAiCj4juOKd+kSZOs13v37sXixYsRFRWF2NhYAEDlypWxceNGDBkyBA0bNkTFihXxxhtv4O233zaUNyIiIiIiIqKcSPc48vny5XMbhM5iseD999/HqFGjTMtcoHAceSIiIiIiIspORsqhumvkt27dCiEE7r//fqxYsQIlS5bMWhYWFoaoqChUqFDB+1wTERERERERkUe6C/Lt2rUDAJw5cwZVqlTxaYg4IiIiIiIiIvKOroL8/v37Ub9+feTLlw/Jyck4cOCAy3UbNmxoWuaIiIiIiIiIyJ6ugnzjxo2RkJCAsmXLonHjxrBYLNDqWm+xWJCZmWl6JomIiIiIiIhI0lWQP3PmDMqUKZP1moiIiIiIiIgCQ1dBXhkOzvE1EREREREREWWvfEY3WLBgAdatW5f1/q233kLx4sXRunVrnD171tTMEREREREREZE9wwX5CRMmoGDBggCAXbt24dNPP8XkyZNRunRpDBkyxPQMEhEREREREZGN7uHnFOfOncOdd94JAPj+++/Ru3dvvPDCC7jnnntw3333mZ0/IiIiIiIiIlIxXCNfpEgRJCUlAQA2btyIDh06AAAKFCiAmzdvmps7IiIiIiIiIrJjuEa+Y8eOeO6559CkSRMcP34cDz74IADg0KFDqFq1qtn5IyIiIiIiIiIVwzXyn332GVq1aoWLFy9ixYoVKFWqFABg79696N+/v+kZJCIiIiIiIiIbixBCBDoTOU1KSgoiIiKQnJyMYsWKBTo7RERERERElMsZKYcabloPAFevXsWePXuQmJgIq9WaNd9isWDgwIHeJElEREREREREOhguyK9ZswaPPfYYrl+/jqJFi8JisWQtY0GeiIiIiIiIyL8M95EfNmwYnnnmGaSmpuLq1au4cuVK1nT58mV/5JGIiIiIiIiI/mO4IH/+/Hm8/vrrKFSokD/yQ0RERERERERuGC7Id+rUCX/++ac/8kJEREREREREHhjuI//ggw/izTffxOHDh9GgQQOEhobaLe/evbtpmSMiIiIiIiIie4aHn8uXz3UlvsViQWZmps+ZCjQOP0dERERERETZya/Dz6mHmyMiIiIiIiKi7GW4j7zarVu3zMoHEREREREREelguCCfmZmJDz74ABUrVkSRIkVw+vRpAMCYMWPw5Zdfmp5BIiIiIiIiIrIxXJAfP3485s+fj8mTJyMsLCxrfoMGDTB37lxTM0dERERERERE9gwX5BcuXIjZs2fjscceQ0hISNb8hg0b4ujRo6ZmjoiIiIiIiIjsGS7Inz9/HnfeeafTfKvVitu3b5uSKSIiIiIiIiLSZrggX69ePezYscNp/vLly9GkSRNTMkVERERERERE2gwPP/fee+9h4MCBOH/+PKxWK1auXIljx45h4cKFWLt2rT/ySERERERERET/MVwj/9BDD2HZsmVYv349LBYL3n33XRw5cgRr1qxBx44d/ZFHIiIiIiIiIvqPRQghAp2JnCYlJQURERFITk5GsWLFAp0dIiIiIiIiyuWMlEMN18jfcccdSEpKcpp/9epV3HHHHUaTIyIiIiIiIiIDDBfkY2NjkZmZ6TQ/LS0N58+fNyVTRERERERERKRNd7C71atXZ73+6aefEBERkfU+MzMTW7ZsQdWqVU3NHBERERERERHZ012Q79mzJwDAYrHgySeftFsWGhqKqlWrYsqUKaZmjoiIiIiIiIjs6W5ab7VaYbVaUaVKFSQmJma9t1qtSEtLw7Fjx9CtWzfDGZg5cyaqVauGAgUKoFmzZppj1Cvi4+MxYMAA1KpVC/ny5cPgwYPdpr106VJYLJashxBEREREREREwc5wH/kzZ86gdOnSpux82bJlGDx4MEaNGoWYmBi0bdsWXbp0QVxcnOb6aWlpKFOmDEaNGoVGjRq5Tfvs2bMYPnw42rZta0peiYiIiIiIiHICr4af27JlC7Zs2ZJVM6/21Vdf6U6nRYsWaNq0KWbNmpU1r06dOujZsycmTpzodtv77rsPjRs3xvTp052WZWZmol27dnj66aexY8cOXL16Fd9//73ufHH4OSIiIiIiIspOfh1+7v3330d0dDS2bNmCS5cu4cqVK3aTXunp6di7dy+io6Pt5kdHR2Pnzp1Gs2Vn3LhxKFOmDJ599lld66elpSElJcVuIiIiIiIiIsqJdAe7U3z++eeYP38+Bg4c6NOOL126hMzMTERGRtrNj4yMREJCgtfp/vbbb/jyyy+xb98+3dtMnDgR77//vtf7JCIiIiIiIsouhmvk09PT0bp1a9MyYLFY7N4LIZzm6ZWamorHH38cc+bMMdSPf+TIkUhOTs6azp0759X+iYiIiIiIiPzNcI38c889h8WLF2PMmDE+7bh06dIICQlxqn1PTEx0qqXX69SpU4iNjcVDDz2UNU/pw58/f34cO3YM1atXd9ouPDwc4eHhXu2TiIiIiIiIKDsZLsjfunULs2fPxubNm9GwYUOEhobaLZ86daqudMLCwtCsWTNs2rQJDz/8cNb8TZs2oUePHkazBQCoXbs2Dhw4YDdv9OjRSE1NxYwZM1C5cmWv0iUiIiIiIiLKKQwX5Pfv34/GjRsDAA4ePGi3zGiT+KFDh2LgwIG466670KpVK8yePRtxcXF46aWXAMgm7+fPn8fChQuztlH6vl+7dg0XL17Evn37EBYWhrp166JAgQKoX7++3T6KFy8OAE7ziYiIiIiIiIKR4YL81q1bTdt5v379kJSUhHHjxiE+Ph7169fH+vXrERUVBQCIj493GlO+SZMmWa/37t2LxYsXIyoqCrGxsabli4iIiIiIiCin8moc+dyO48gTERERERFRdjJSDtVVI9+rVy/Mnz8fxYoVQ69evdyuu3LlSv05JSIiIiIiIiJDdBXkIyIisvq/R0RE+DVDREREREREROQam9ZrYNN6IiIiIiIiyk5GyqH5silPRERERERERGQCFuSJiIiIiIiIgggL8kRERERERERBhAV5IiIiIiIioiDCgjwRERERERFRENE1/Nwnn3yiO8HXX3/d68wQERERERERkXu6hp+rVq2avsQsFpw+fdrnTAUah58jIiIiIiKi7GSkHKqrRv7MmTOmZIyIiIiIiIiIfMM+8kRERERERERBRFeNvKN//vkHq1evRlxcHNLT0+2WTZ061ZSMEREREREREZEzwwX5LVu2oHv37qhWrRqOHTuG+vXrIzY2FkIING3a1B95JCIiIiIiIqL/GG5aP3LkSAwbNgwHDx5EgQIFsGLFCpw7dw7t2rVDnz59/JFHIiIiIiIiIvqP4YL8kSNH8OSTTwIA8ufPj5s3b6JIkSIYN24cPvroI9MzSEREREREREQ2hgvyhQsXRlpaGgCgQoUKOHXqVNayS5cumZczIiIiIiIiInJiuI98y5Yt8dtvv6Fu3bp48MEHMWzYMBw4cAArV65Ey5Yt/ZFHIiIiIiIiIvqP4YL81KlTce3aNQDA2LFjce3aNSxbtgx33nknpk2bZnoGiYiIiIiIiMjGIoQQgc5ETpOSkoKIiAgkJyejWLFigc4OERERERER5XJGyqFejSMPAOnp6UhMTITVarWbX6VKFW+TJCIiIiIiIiIPDBfkjx8/jmeffRY7d+60my+EgMViQWZmpmmZIyIiIiIiIiJ7hgvyTz/9NPLnz4+1a9eifPnysFgs/sgXEREREREREWkwXJDft28f9u7di9q1a/sjP0RERERERETkhuFx5OvWrcvx4omIiIiIiIgCxHBB/qOPPsJbb72Fbdu2ISkpCSkpKXYTEREREREREfmP4eHn8uWTZX/HvvG5Kdgdh58jIiIiIiKi7OTX4ee2bt3qdcaIiIiIiIiIyDeGC/Lt2rXzRz6IiIiIiIiISAfDBfn9+/drzrdYLChQoACqVKmC8PBwnzNGRERERERERM4MF+QbN27sduz40NBQ9OvXD1988QUKFCjgU+aIiIiIiIiIyJ7hqPWrVq1CjRo1MHv2bOzbtw8xMTGYPXs2atWqhcWLF+PLL7/Ezz//jNGjR/sjv0RERERERER5muEa+fHjx2PGjBno1KlT1ryGDRuiUqVKGDNmDPbs2YPChQtj2LBh+L//+z9TM0tERERERESU1xmukT9w4ACioqKc5kdFReHAgQMAZPP7+Ph433NHRERERERERHYMF+Rr166NSZMmIT09PWve7du3MWnSJNSuXRsAcP78eURGRpqXSyIiIiIiIiIC4EVB/rPPPsPatWtRqVIldOjQAR07dkSlSpWwdu1azJo1CwBw+vRpvPLKK7rSmzlzJqpVq4YCBQqgWbNm2LFjh8t14+PjMWDAANSqVQv58uXD4MGDndaZM2cO2rZtixIlSqBEiRLo0KED9uzZY/QwiYiIiIiIiHIkw33kW7dujdjYWCxatAjHjx+HEAK9e/fGgAEDULRoUQDAwIEDdaW1bNkyDB48GDNnzsQ999yDL774Al26dMHhw4dRpUoVp/XT0tJQpkwZjBo1CtOmTdNMc9u2bejfvz9at26NAgUKYPLkyYiOjsahQ4dQsWJFo4dLRERERERElKNYhBAiUDtv0aIFmjZtmlWTDwB16tRBz549MXHiRLfb3nfffWjcuDGmT5/udr3MzEyUKFECn376KZ544gld+UpJSUFERASSk5NRrFgxXdsQERERERERectIOVRXjfzq1avRpUsXhIaGYvXq1W7X7d69u65MpqenY+/evRgxYoTd/OjoaOzcuVNXGnrcuHEDt2/fRsmSJV2uk5aWhrS0tKz3KSkppu2fiIiIiIiIyEy6CvI9e/ZEQkICypYti549e7pcz2KxIDMzU9eOL126hMzMTKegeJGRkUhISNCVhh4jRoxAxYoV0aFDB5frTJw4Ee+//75p+yQiIiIiIiLyF13B7qxWK8qWLZv12tWktxCvZrFY7N4LIZzmeWvy5MlYsmQJVq5ciQIFCrhcb+TIkUhOTs6azp07Z8r+iYiIiIiIiMxmONidWUqXLo2QkBCn2vfExERThq77v//7P0yYMAGbN29Gw4YN3a4bHh6O8PBwn/dJRERERERE5G+6h5/bvXs3fvzxR7t5CxcuRLVq1VC2bFm88MILdv3MPQkLC0OzZs2wadMmu/mbNm1C69atdaej5eOPP8YHH3yADRs24K677vIpLSIiIiIiIqKcRHdBfuzYsdi/f3/W+wMHDuDZZ59Fhw4dMGLECKxZs8ZjpHlHQ4cOxdy5c/HVV1/hyJEjGDJkCOLi4vDSSy8BkE3eHSPN79u3D/v27cO1a9dw8eJF7Nu3D4cPH85aPnnyZIwePRpfffUVqlatioSEBCQkJODatWuG8kZERERERESUE+kefq58+fJYs2ZNVg33qFGjsH37dvz6668AgOXLl+O9996zK1TrMXPmTEyePBnx8fGoX78+pk2bhnvvvRcA8NRTTyE2Nhbbtm2zZVij/3xUVBRiY2MBAFWrVsXZs2ed1nnvvfcwduxYXXni8HNERERERESUnYyUQ3UX5AsUKIATJ06gcuXKAIA2bdqgc+fOGD16NAAgNjYWDRo0QGpqqo/ZDzwW5ImIiIiIiCg7GSmH6m5aHxkZiTNnzgCQY8D/9ddfaNWqVdby1NRUhIaGepllIiIiIiIiItJDd0G+c+fOGDFiBHbs2IGRI0eiUKFCaNu2bdby/fv3o3r16n7JJBERERERERFJuoef+/DDD9GrVy+0a9cORYoUwYIFCxAWFpa1/KuvvkJ0dLRfMklEREREREREku4+8ork5GQUKVIEISEhdvMvX76MIkWK2BXugxX7yBMREREREVF2MlIO1V0jr4iIiNCcX7JkSaNJEREREREREZFBuvvIExEREREREVHgsSBPREREREREFERYkCciIiIiIiIKIizIExEREREREQURFuSJiIiIiIiIgggL8kRERERERERBhAV5IiIiIiIioiDCgjwRERERERFREGFBnoiIiIiIiCiIsCBPREREREREFERYkCciIiIiIiIKIizIExEREREREQURFuSJiIiIiIiIgggL8kRERERERERBhAV5IiIiIiIioiDCgjwRERERERFREGFBnoiIiIiIiCiIsCBPREREREREFERYkCciIiIiIiIKIizIExEREREREQURFuSJiIiIiIiIgggL8kRERERERERBhAV5IiIiIiIioiDCgjwRERERERFREGFBnoiIiIiIiCiIsCBPREREREREFERYkCciIiIiIiIKIizIExEREREREQURFuSJiIiIiIiIgkjAC/IzZ85EtWrVUKBAATRr1gw7duxwuW58fDwGDBiAWrVqIV++fBg8eLDmeitWrEDdunURHh6OunXrYtWqVX7KPRERERHlOLNmARs26Fv3yBFg/Hjg+nX/5smI6dOBNWuAa9cCnRMiyqECWpBftmwZBg8ejFGjRiEmJgZt27ZFly5dEBcXp7l+WloaypQpg1GjRqFRo0aa6+zatQv9+vXDwIED8ffff2PgwIHo27cvdu/e7c9DISIiopxOCCAlJdC5IEfDhwMWC/D99+akt3078MorQJcu+tavWxcYPRp46y1z9u+rr78GhgwBuncHihYFLl4MdI6IKAeyCCFEoHbeokULNG3aFLNmzcqaV6dOHfTs2RMTJ050u+19992Hxo0bY/r06Xbz+/Xrh5SUFPz4449Z8zp37owSJUpgyZIluvKVkpKCiIgIJCcno1ixYvoPiIiIiHKeN94ASpcGTpyQhaSdO4FWrQKdK+/9+y+QLx9Qpkygc+K7w4eBevVs7824LbVYbK8zMoCQENfrnjoF3Hmnufv3lTr/ANC3L7BsWWDyQkTZykg5NGA18unp6di7dy+io6Pt5kdHR2Pnzp1ep7tr1y6nNDt16uQ2zbS0NKSkpNhNRERElAuMGQN88gnw7ruyEA8ArVsHNk/e+PFHYM8eYPduoFw5oGxZ2Rx8+HDt9W/fzt786fH550DXrsDNm/L9L7/YF+IB4O+/zd3n2bPul6sqkwAAv/3mOQ+XLgFWq3ydkeF93gD54KBLF+COO4Bbt7TX+fZb3/ZBRLlSwAryly5dQmZmJiIjI+3mR0ZGIiEhwet0ExISDKc5ceJEREREZE2VK1f2ev9ERGSihASgRQvgjz8CnZO8Qymg5BYffqg9//Dh7M2HXkIAderIWlmLBfj0U1lr3LWr/F9o2dK27ujRwJQpQM+e9mmsXAmEhwOLFmVr1p38+SfQo4c8jp9/Bl5+WT6QqFlT9v1u1855m5kzZf/wadOAtDR9+/n3X9fL+vRxv+2UKfbv27QBGjcGXnwRePRRmfdffrEt//VX2RIiJARYsgQIDQVWrNCXTy0bNsjpzBmgUSPgySe9T4tcO30amDhRdq1ZsYItHPwtEC1b/vgDqFoVWL48+/cdIAEPdmdxaD4khHCa5+80R44cieTk5Kzp3LlzPu2fiIhMUr68rIW8++7sq2G0WvUXILxx6xbw/PPA6tX+24e3Jk2SBZSlS23zNmwAmjYFjh0LXL68cfs2sG+f6+X16smC5ZEjxtK9fFneKDZsKAt5Su2yWbZvB44etb1/7TX7pt9afvjB/v0jj8gb6YED7ecrfdHdBBY2jdUKNG9uO88feMC27J9/ZN9vLbNny/7hQ4fK1hRqK1cCW7fKGvG335aFdItFtlC4/375YCAmxn6bv/6Sf+PigMxM+VpPIWP2bFthr1072Y/eYgHatrWtM2CA/Nu7t/fXjK5dba+PHwcWLtRez+xr0qlTQHy8uWkGyunTsqWKlkGDgJIlgerVgXfeASIi5Pf16KPA5s2+73vdOvm96ZXbHpRq+eMP2fXH8QGjv/XpI1vg9O2bvfsNoIAV5EuXLo2QkBCnmvLExESnGnUjypUrZzjN8PBwFCtWzG4iIqIcRqt2MTnZVnPZr5/9so8/BubONb6fBx6QN37+6mZVsKDMV48eshYuJxk5Uv7t31/+vXFDNvuNiQFq1w5cvrwRFgY0aeJ+nc8/lwU0I4X5UqXkjeKBA/L9vfd6n0fFoUO2B1Xe1iYp/weOAd4GDbKlrdQ+K3levtzW3WDJElmA9rYmTV3QXLzYfb90vT7+WP794Qd5bI88IgvsZcoAkycD331nW3frVllz3rSpczpFiwJRUbIA9/LLspDRqBGQlKQ/L57OkZUr9acFyIcR9evrX79AAVvT+xMngC++kFH2T5yQn80998jjWbwYKFLEdn4qDh0Cdu2SrZwaN5YPhypUkK0mMjKcC5g+tI7NYrV6V3C9dUvmS+tcTEuT84WQD1omTZKF9JYtnf93bt+WLTyuXNHeT8eOzvEIPLlxQ547Fov8Drp1A2rVkvnwZN8++SDho4/kdzd8uDxOvbKzu4wvNerK78cPPzh/LpcvA++/D5w86X36ajdvAv/3f/L/U92Nxp8P43MSEUB33323ePnll+3m1alTR4wYMcLjtu3atRNvvPGG0/y+ffuKLl262M3r3LmzePTRR3XnKzk5WQAQycnJurchIiI/sN2yCTF4sP2yX36xX67+SVuxwjZv6FDb69u3hZg5U4gnnxTCanW/z+XLzTmGv/8WYsQIIZTfFMc8X75szj4qVxbiwAEh4uOFOHnSu3TU+bJahfjtN+3PVwghoqPlvIceEuLWLSEyMlx/pu6kpAhx5YqxbR57TIgGDVwvP3HC+XP2NGVk2La/ckWIzEzndK1W7W213Lwp87lypXzvmF5GhhCpqfbp7NplPN96ppdfFmLDBvt5hw/bXv/zj+21kl8hhLhwQZ5PapmZQly7JkR6uhAffSTE1KlC9O4ttz14UC4zM++bN/vnM/HHVKOG/FxcycwU4tw5+dqb9MuXN7Z+YqLzedaxo+v1MzOF+PlnId56S75/5x0hXnlFXmuPHxfik09kWu7MmyfE00/L86BxYyGaNjV+XVDnSe1///N8zFarEBcvCrFxoxDvv6/vc+re3X1+Ro2SaQkhxAsvuE7n5k3t7S9eFGL0aCEKFtTe7sgR/Z/JunXys9261f6aZaY1a+S+li6V79PShLh0yf02J0/K3+i4OOfji40VYv16eZ1RrhUlSpiT19GjtT/TM2fMST8AjJRD4XENP1q6dKkIDQ0VX375pTh8+LAYPHiwKFy4sIiNjRVCCDFixAgxcOBAu21iYmJETEyMaNasmRgwYICIiYkRhw4dylr+22+/iZCQEDFp0iRx5MgRMWnSJJE/f37x+++/684XC/JERDmE44+zu2WAEMeOCZGQoP9G99QpeYP65Zey0KK+KVixwvt8W622m1clveefF+L6dec83H+/EE89JW9y9HIsFBq9sXR04IB8GODp85o7V36+rgq0SmHAndRUmYZyHMp2t27py2tKim2b+fOdl7vLm6fp66/tHxAJIURSku273LpVeztHkyfbL//1V9vrhx/2Pn/ZMb39tiyM3rxpm3f7tu3Y7r3X/H1Omxb44zZrKlPG9blbrJixtJ55JvDHozWp7dlje/hTvLhtnUKFbK9HjxZi2TJ5jd250/kasXy5EMOHy/Ps9Gn7ff3f/8m/FSv695imTROieXMhRo6UeVLKABcu6E/jww/lNv/+Kx8Gbtrk/DDU1aQulA8ZIr97xerV9us2aSL/Pvyw/M0DhOjTR/597jm5zd13y/cdO8r3N24I8d13Qly9Kq+hitOn5YMGxdmz9vtKT9fOb//+QuzfL39Dvb3munPpku26c+yYzP/Nm/JzsVjkPCE87yMqyv3DtRwoaAryQgjx2WefiaioKBEWFiaaNm0qtm/fnrXsySefFO3atbNbH4DTFBUVZbfO8uXLRa1atURoaKioXbu2WGHwZowFeSIiL3zxhRBvvuldrayWjAznH2Ulba0CsTdTy5auly1eLAvz16/LGwH1cS1YIESnTrabL/Wy27eFaNhQiG7dnGtcu3Rxn589e+TnqKSXnu5cY3/pkqyZGzRIiHffFSI83HV6AwbIQnNcnG17q1WIHTtkwfnaNVl4NfOG2N0DCfVNobpGGJA38oB8qHL7trzhV27Arl2TLSn++UeIV1+13y46Wq4rhBCPP27usTzyiOd1eveWN9qVKsmWANu2mZuHQE133ml7/emn8v/Al4ck7iYhAn+8Zk7ffKN9/gc6X2ZNe/bI2nr1w56qVY2lsWyZfLi5alXgj8dxUvJUrpx8SJFd+921y/4aqVRCGk3H8WHIqVPa66mv/dOnZ/852quX/DtqlP1vaIUKcn6zZkK88YZt/ZAQ++1v39a3ny5d5Ger98F2gAVVQT4nYkGeiEyzaZMssOQU6emy0GFGc25Hyo+mUqjSIznZtp1jnvbu1f5RXrJE1ppk5w0HIESBArJG1rEwfvSoEKVLy9fPPWffPNroza0yrVplXzNy7Ji80TlxQogPPvAuzYgI2Qza35+Tu2aqetN4/nnbaz2FacBzzdfHHwvRtausjdq0KfvPH18n5aYXEOK99wKTh6JFzU/z11/lubF0aeA/YzOnUaPkcWVkCFG/vv7z2HH6+efAHwunwE1Grpu+TocOBe44O3SQD8Cy4/PM4ViQ9xEL8kQB9Mcfsi+VctF16F4TVGbOzFk/HuratHr1hJgxQ9Yc79ljWyctTRZyrl93nU5qqqzh3bRJiJdekuuqmzsDspm2FqXP5nffCdGunfOP7OHDsiY8I0PWAgb6JoqTd5Or389A5UfdIkFhdl9us6dPP3XuA/vPP0IoLRcfekiud/Jk4PPqavrpJ+fvfd062+sTJ7TPD3f9kLUmdRwMbyelaXK+fK7XefFF2X/899/l+wcflF1jXK1/7ZoQCxd6n6cHHgjs/w2nwE+Ozeo5+TZdver63iaHYEHeRyzIEwWIVlNqwLym2tlNfQznzpnfrOv2bWOfzZYtrn/ctPKsuHVLiH79ZLN5vT+WVarY7zsjQ4iaNY394Oa2Grq8No0ZIwtq/8W9cfn/7e+pWjXX/xPHjwf+c3I1GVG9utxGCUCoTDNmOKdrsWT/MTjOu3lT+9p1xx1yHa0Ad0WKyIKz8r52bbmNOh3HOA/Xr8uHShkZMhCdu7xevy670jj2Efb0nbhqOWRkevppIVq1cp5/9Kjcx/ffOy9TP7zwR9yC3D7973/O5yYnc6effgp8HhynBx80dm0NABbkfcSCPFEAWK1C/PWX9oW3SBFZu+2to0dl9FzHJu7+ekBw4oQsPGgdixLkSy0z03OAMEdJSUKULCmjYut1333uf+AcIyIfPy63cxUV1tN07pwQs2fLBw7z5/vvh/nRR2W/6kDfIBiZrlzRF4E5t0yvvRaY/U6a5Dnasp4gf9k9Kf97emVkyNpfIWxpTJwo3yvB++69V75fssTcvD70kAwo5Tj/kUds+VPPdyc1VQbQEsJWQ96okewSokSh3rRJxnjw9Hk4cuzf/9RT9u/Vvwfq+W+9JacvvnC9L28/O6XFgpK/77+X181PP3WOuq3e7q+/tI/v2Wf173vUqMCf595MWucaIIOhedp20SL5W3vqlO1zc3z4pXdau9b4Nm3aBP7zy85JCCEiIwOfD6185WAsyPuIBXkiA27c8H5bJdBK795ClC3r+eLbrJl3+1GnkZgob3iGDfPton77tpyOHrVFfE1N1Rd8RWG12t8Efvqp5/1euSKbCb/9tr78Hzwo+70JYby/dtGicjtffzQjIuSDFH//KAf65sDIlJlpHygqJ029e8vaSWUYoUcftY9loJ6aNg18fvWcG554qq11nCZM0Leeul+73mnzZv351pKYKIePcjU01Zkztn2dOiVjWnj7+aoDGyqxGywW2SRc/dtw5Ii8Bnz3nf7juHFDDiGWlubVx6BJnXerVQ5hCMj+uWrqUQf0fB/KKBV16+r73JSHLkZ8+618eKtndIvUVCHGjZMPhObNE6JUKSF+/NH5f+Ppp+Xr8ePlEJn588s4H4H+v3U1nT4th0NU3mvFevnuO+ftrl6VkeS1eHsdFkL+tqakaMeO0BqJQfmfTE21dV+7csWcz+aJJ+xbrPg6CSGHHgTkuTN5ssxzWprzunfc4TzU39df2z7j2Fj/xmeZPt32unlzfceWg7Eg7yMW5CkopaVlfxN05aLYt69v2xv9cdGjTx95Q5mY6DnNhx6SBfs//pDbxsXJG3BXtT5aw7G4qiXQmg4csB+OSs/xWa1yO61tFi8W4vx55226dbOt420/2pw+LNQvv7g/r1wF76lTx/n7U4br8feUL58tr599Zm7aN2/K8/fyZe/T2LpV+xyMjZW1hTduyJql5s3lDbKvXSDMupHVmoxylc7587KLSWqqrWVPiRLu962Mt52eLsdwv3BBvm/WTC5ft057v9nh119tD/iEEGLfPnn9M/r5uoulkRNpxS3RGprq9m35G/Lii8Z+V61W51EVzDgvzbJtmwz6qOZqXHh1fk+fFuLzz10fT7NmsjDboIHz/7PVaqyf98KFcv/qFmKjRukfnlKhFPi7dvW8rp58zZ1re63cKygSEuy7P7z0km3Z4cNCvPyy+wCzaWnaXSu8udZ17myb5xjUc9UqGVBO/aDq5Ze9O0fVn4fi2jV5z6UerlJhtcrf3fvvtw2fZ+Z1/tYteZ3VM6KN0RaQ2YwFeR+xIE9BRx20ydVyLdev63u6v2WLrVBYvrws3E2a5HwhzcgQokULGdX7+HH5Y6YEFrFa5VP/WbPke2+b2iYkyNqmK1ec83nkiByP1pcapkWL7N+r+6FPnCjE66+77gJgxvTPP/Y3BDdvygKUnm2VIIHugi/ltkmL4/KPPpLn4ldf2eY79sEdPlw7LT0B0SpX9rxO/vy2165qGDMyZCAzdY2TL5+H1ep6HOqKFWUNHCCHTdu9WxbQlbF5veFLnjdvlv9fjg8gZs+2vU5IsK/5mjVLDq/nmJ4y1vuMGcaPIT1d3vx+8YXn88zdGN+vvGJsv506ye1WrTKeZzMp+VcHm3M1dFXTpoHNq7f8MWKHI0/B+oJBZqYc2nLcONs85Zrh6Xhef915mXr9f/+VQVY3bnS9//37ZYHP1VB+Zho3zpY3pbVe2bL2/+O3btlaXrhy/botroE3Ll607U8dFFJrUncnmzvXPp1335XflRC2e6/vv7dfJyHBdiyOaR886Dmv6uFDjXI3RGdYmPuWBbVqyfuku++Wx+gYMFMIIVq3tq2vxA9RT1r3jzkIC/I+YkGegsLt27KP7cGDQvzwg+0C9c038gZXaUamjMHZq5e8WQeEGDvWvr/g8eOum2HqLRQnJdk/5VVPVqvcp/J+yBDP6bkLzKZMZ8/KoXn8Oc5rqVJCtG3r3z7e7qawsMDsNzunnj3d12726OF6mZYdO+SyCRPs5yvnfJkyzv1lHWtYtCQkyP+7c+dk4D51V4i0NPfRqZcv95y+mnrbDh3kX1dxF5Qpf37ttC5fljWRH31kW9do7ZYefft69/27O3Yh5MMspfClFPTHjLGtX6WK8zZaNUJGqMdhjonRXsfxuvPee/LBj6smvO7cuiVbzQTayZOylYt65BAhbJ/niRPyQRO5l5Hh/ncuWGk9xFa6YKllZsqHc0lJtnnqbVJSsi/PeqSlyZZFSgwb9f3Q9evarTb8ZedOmRch7D+z8eNtcQCiouRn/L//yfm+Uu/HyMPc+fPt4zzo5a6lpFLIdrVcq/Who7Nn5UPePXvkwxHH4Tr98ftnIhbkfcSCPAXUr7/KwqNWUDS1Tz6xv4F0dbOg92a6dm3ZrxGwDwrnrtZJPRUp4nqZN/1ohZBNAL0pGHDSN9WqJQNJGd3OrH7R6qf+6kBFngqEQsjaCncFHz0/1FevyvHf1c0gfXHrli2PzZrJliPqPBuxcaPcrls3+V6pOVFq9pWhx6pVkw/QOncOfHNBPU0aHafHH3dO599/ZY22Y7AvV9QP2apWNedYbt+WQZqiolzXwFmtQixYoK/2KthYrfI3RqvrCumnPtd79JDX29OnA50r71mt8n82IkI+tNq7V/9DM+Wa5s31MK9Snz9KSy6r1fxr/Z49tt/27KIcV5cutuEc1eeG+thnzfL93FFaO7Rtm+NHQjJSDrUIIQTITkpKCiIiIpCcnIxixYoFOjuUG125Anz+OTBoEOB4jlksttfqf8/MTCAkxPa+XTvgl1/c7ycuDqhSxbs8pqcDYWHebeur7duBe+8FfvsNaNMmMHnIzRo1AmJibOfakSNA3br6t9+0CQgPB65fBzp3Bg4fBjZuBIYMMZaPjAz7c3r7dpmn1q2B0FDb/GHDgClT5OsPPgBGjza2n+x27hxQqZI8lpgYoEIFIDLSeDqxsXJbx/9DIWTa168DBQsC+fKZkm1TqK9fjqZOBaxW4KmngD//BL7/Xs4rWNC3fd64ARQuLF//+SfQrJlv6SnS0+Vnmz+/OelR3uPq95xIj+w8f6zW7P0tKVAASEsDTp4EqlcH/voLiIoCSpWSy+Pj5e9fp07Ajz8C774L1K8P9Ovn/T6Vz9Dd71QOYKQcyoK8BhbkHaSmAjdvAmXL+p5WRob8R1LfpJvh00+BO++UhQqFY8HXF1YrsHkz0LQpULo0sHu3vPgULQo0bmwrLGdkAOPGAQ88IAvarrgrrKtvGosVAy5elIUmAPj9d6BFC+c0covChYGUFNuPSWKidwUgcm/RIuCxx+znpabaHip17CgL6466dJHn+uefOy8TAjh0SP4gT54MjB3rvM7p0/LHu0IF+aBm+3bXeVSf3wcOAA0ayNfHjgE1a7o9PAog9ff277/yvKpe3f/7tVrlvnPjdZGC148/Al27ynuGu+8OdG4o2KSnA199BTz4IFC5cqBzY66rV4FLl+S9O9kxVA71c+uAoJRrmtYnJ8vgFjdvyvd79siIkZ6adX3yiS24yN69tuYsevrN/PuvrclKaqr98DOZmTLoROXKsv+R0vTVavWtv8quXbY8Ks2NDh4UIiREiA8/dL1dRoYQy5bJ/q6eqJuxL17s3DxUOc7Bg103/8nMlOMZO0YGVlMPoeFueustc5o257RJq2+pmekLYd/8Vxmn2Kzp22/t31eubD9POe9dRazXM9WtKwO93LypHT1fz+QqSnFmpvx/VPcPVqb+/T3/nyisVtu1oH9/uf2ff+rfXgj7ADVxcXLS04+dAkuJyK78vxEREZFu7CPvo6ApyFutslBy7ZqMuPncc/Z9lTp2lDdTr78u36tvytevl/1Lt22TfS137JBDX6ijZP75p3YhYOpU7fwoQxC99pr9WNr798vljmOYAjIYitIvW+tG/+pV2xjdapmZsm9o3bpCvPOOLb3//c/5WIWQwTO++872UOPcOSEGDdJ/w6m3kKh+36mTc8HO1TRypAwiZGah0l/TjRv2Y7CbObly/bptPFMjU5ky2un/8os8V/SM+e5pslplwD3lIYTW/lz1xzp61LbulCme97Vrl3MaV6/Kvodjxsgo3Y55e/dd/Z+zu3Nez+gGrnjTH81ofilnSE8XYuhQ7wIgERER5XEsyPsoaAryWmOVDh0qh2RwDBL2zz/mFri0gpuol9eoYf9ea4ggTwU5de20Yw2iu4jmjuMyX70qxzwGhHj+eee8AvJhQKdOtoK+2o0bMrCLmZ9fME7qIWDULTV++831Np6i0//5p/zMR4yQNa7uHD/uPq1y5ZyHClNHJnfVokS9fkqK/Bsebj8SgKvpqaec09uwQZ5vyrB7nlittgi5ypjMqanOw3ANGaIvvUuXZOFdebCgHJMy6WmBIoR8OPDBBzKd48f1bWMmV9cFIiIiolyKwe58FDR95I30BZw4ERg50rx9T5wIjBjhfX5cycgAVq+W/cuVgBeALfjZ+fNARIQMkPTee/rSbNUK2LXL9l4I13mdNAl4+21g3jzgmWeATz4BXn/d++PJqR5+GBg4UL7u1cvz+jNnAi+/bHufmSmD0FWsCHz3nQyWtn+/DK53+zYwapRc79Yt+T5/frnegAH2cQuMXn7U39uNG8AbbwCFCgE9egDt2zuvI4TMw5UrQPny7tOsVQs4elSuGx4u+3J7irEQGyuDs/iL+liuXbMF9PI2nchIICHB93xlBwaJIiIiojyGwe58lCsL8v4UEwMkJwP33eff/dx9N7Bnj+/pDBkCTJvmevm2bf4/lux27JgMmtKgAbB4MdC/v5zvGFxPS3q68eCEFy/Kv2XKOC+zWoEdO4CWLW1B/PR66CFg7Vr3gYM6dwZ++km+1nN5278fOHhQPmTQ0rChDLamWL4c6NNHf/q+mD8fePpp7QdnRqxbJyO9L1ggjycYsCBPREREeQwL8j4KmoL80KHuC6QUvEaPlgW3IkW8T+PIEaBOHfnaU2Hc8aFQSIgs5D/xhCz8BRMhgH37gNq1fR/WCpDDqnXqZJ/+lSuyZUhOGvYrtzl+XA5DN3Ys8Oqrgc4NERERkd8ZKYfyLjSYdesW6BzkXY89BmzZIpv4+0Pv3rIZddWqntdVCtrffSdr2wFZCKpdW47ReeuW5xr1cuVsr69ftw0TGGyFeEA+lGjSxJxCPCCHYuveXTbNv3JFzitRgoV4f6tZUw5Nw0I8ERERkRPWyGsImhr5CxdkH2V/OHQIqFdPvrZYvG/a2r8/sGSJefkKtHr1ZDNstVWrnPuZT5gAvPOO7b0QslvA1au22t1Ro2Qf6/vvB559Vha8GzSQY9Wrm1HHxQErV8ouAVqEkDXuYWHeH9fy5UDfvrb0iIiIiIgoWxkph3roHEs5WoUK/ku7bl3b6zlzZJ/gnj2BrVs9bzt2rJwAWUP86acyjfbtgUaNZBCxnOD2bRk8T0+tt+LBB53nPfywLPw+84wMkhcfL2u4CxeWxz9mjFxP6dO9a5es2e3SxZbGM8+43meVKs55TE2VtcTKAwRfCvGADBbXuHHw9J8mIiIiIsrDWCOvIWhq5AHtgHfdu8vI74CM7P7++8bSXLNGNts/d07WIvfqZduP1eo5kndGBvDrr0CxYrKJsyMlknihQsby5cnJkzKA2v33A99+C/z2G3DPPa7XV5/6O3bIqPiunDkDrF8vA4+Z1WTbiFu3bPudO1fW4BMRERERUa7BPvJ5yfnzttcnTgBLl8qm3kLIQnf37vbrT50KXL4sh+1SKLXMK1fK7ZS+95UrA488Yv+wwFO/4JQUWdBv1067EA/I9BwLw/Hx2utOn+68rSvVq8to6cuWyeNo3VrWumtRD20HaBf4mzeXaWVmyhrxV14JTCEekK0YkpJkv/ynnw5MHoiIiIiIKEdgQT7YVagg+0cLAdx5J9Cvn62wbbEAlSrZr9+ypQzUNXWqXN6njxzOy2qVTcSNevNN2+vXXweKFtW/rTJEGCCboitDeqk1bixr+IcPB378Edi50375zJny78mT2vvIn9/WJ12dV8f18+WTfdFHj5ZD6Sl92vv2zTlBzUqWlK0Nckp+iIiIiIgoINi0XkNQNa3XY/RoOR71rFlyHG5fqWvFMzNlATw9XTbJN0II4MsvZYC3Fi3kw4QPPpD98Ldvl+scPGgLuqe1fz2nb1qaHAe8aVMWgomIiIiIKEfiOPI+ynUFebO98QbwyScyYv4//5if/vvv24LlaZ2e774rC/x798rCORERERERUZBjH3nyr+nTgX37gFOn/JN+ZKT75ePGyQI+C/FERERERJQHcfg5Ms5ikcPI+cszzwC//w5ER/tvH0REREREREGKBXnKecLCZJ9+IiIiIiIicsKm9URERERERERBhAV5IiIiIiIioiDCgjwRERERERFREGFBnoiIiIiIiCiIsCBPREREREREFERYkCciIiIiIiIKIizIExEREREREQURFuSJiIiIiIiIgggL8kRERERERERBhAV5IiIiIiIioiDCgjwRERERERFREMkf6AzkREIIAEBKSkqAc0JERERERER5gVL+VMqj7rAgryE1NRUAULly5QDnhIiIiIiIiPKS1NRUREREuF3HIvQU9/MYq9WKCxcuoGjRorBYLIHOjlspKSmoXLkyzp07h2LFigU6OxQkeN6QN3jekDd43pA3eN6QN3jekDdy0nkjhEBqaioqVKiAfPnc94JnjbyGfPnyoVKlSoHOhiHFihUL+IlHwYfnDXmD5w15g+cNeYPnDXmD5w15I6ecN55q4hUMdkdEREREREQURFiQJyIiIiIiIgoiLMgHufDwcLz33nsIDw8PdFYoiPC8IW/wvCFv8Lwhb/C8IW/wvCFvBOt5w2B3REREREREREGENfJEREREREREQYQFeSIiIiIiIqIgwoI8ERERERERURBhQZ6IiIiIiIgoiLAgH8RmzpyJatWqoUCBAmjWrBl27NgR6CxRgIwdOxYWi8VuKleuXNZyIQTGjh2LChUqoGDBgrjvvvtw6NAhuzTS0tLw2muvoXTp0ihcuDC6d++Of/75J7sPhfzsl19+wUMPPYQKFSrAYrHg+++/t1tu1rly5coVDBw4EBEREYiIiMDAgQNx9epVPx8d+Yun8+app55yuga1bNnSbh2eN3nLxIkT0bx5cxQtWhRly5ZFz549cezYMbt1eL0hR3rOG15vSMusWbPQsGFDFCtWDMWKFUOrVq3w448/Zi3PjdcbFuSD1LJlyzB48GCMGjUKMTExaNu2Lbp06YK4uLhAZ40CpF69eoiPj8+aDhw4kLVs8uTJmDp1Kj799FP88ccfKFeuHDp27IjU1NSsdQYPHoxVq1Zh6dKl+PXXX3Ht2jV069YNmZmZgTgc8pPr16+jUaNG+PTTTzWXm3WuDBgwAPv27cOGDRuwYcMG7Nu3DwMHDvT78ZF/eDpvAKBz585216D169fbLed5k7ds374dgwYNwu+//45NmzYhIyMD0dHRuH79etY6vN6QIz3nDcDrDTmrVKkSJk2ahD///BN//vkn7r//fvTo0SOrsJ4rrzeCgtLdd98tXnrpJbt5tWvXFiNGjAhQjiiQ3nvvPdGoUSPNZVarVZQrV05MmjQpa96tW7dERESE+Pzzz4UQQly9elWEhoaKpUuXZq1z/vx5kS9fPrFhwwa/5p0CB4BYtWpV1nuzzpXDhw8LAOL333/PWmfXrl0CgDh69Kifj4r8zfG8EUKIJ598UvTo0cPlNjxvKDExUQAQ27dvF0LwekP6OJ43QvB6Q/qVKFFCzJ07N9deb1gjH4TS09Oxd+9eREdH282Pjo7Gzp07A5QrCrQTJ06gQoUKqFatGh599FGcPn0aAHDmzBkkJCTYnS/h4eFo165d1vmyd+9e3L59226dChUqoH79+jyn8hCzzpVdu3YhIiICLVq0yFqnZcuWiIiI4PmUi23btg1ly5ZFzZo18fzzzyMxMTFrGc8bSk5OBgCULFkSAK83pI/jeaPg9YbcyczMxNKlS3H9+nW0atUq115vWJAPQpcuXUJmZiYiIyPt5kdGRiIhISFAuaJAatGiBRYuXIiffvoJc+bMQUJCAlq3bo2kpKSsc8Ld+ZKQkICwsDCUKFHC5TqU+5l1riQkJKBs2bJO6ZctW5bnUy7VpUsXfPPNN/j5558xZcoU/PHHH7j//vuRlpYGgOdNXieEwNChQ9GmTRvUr18fAK835JnWeQPwekOuHThwAEWKFEF4eDheeuklrFq1CnXr1s2115v82b5HMo3FYrF7L4Rwmkd5Q5cuXbJeN2jQAK1atUL16tWxYMGCrAAw3pwvPKfyJjPOFa31eT7lXv369ct6Xb9+fdx1112IiorCunXr0KtXL5fb8bzJG1599VXs378fv/76q9MyXm/IFVfnDa835EqtWrWwb98+XL16FStWrMCTTz6J7du3Zy3Pbdcb1sgHodKlSyMkJMTpyU9iYqLTkybKmwoXLowGDRrgxIkTWdHr3Z0v5cqVQ3p6Oq5cueJyHcr9zDpXypUrh3/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      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# get example finger tapping dataset\n",
    "\n",
    "rec = datasets.get_fingertapping()\n",
    "rec[\"od\"] = cedalion.nirs.int2od(rec[\"amp\"])\n",
    "\n",
    "# Plot some data for visual validation\n",
    "f,ax = p.subplots(1,1, figsize=(12,4))\n",
    "ax.plot( rec[\"amp\"].time, rec[\"amp\"].sel(channel=\"S1D1\", wavelength=\"850\"), \"r-\", label=\"850nm\")\n",
    "ax.plot( rec[\"amp\"].time, rec[\"amp\"].sel(channel=\"S1D1\", wavelength=\"760\"), \"r-\", label=\"760nm\")\n",
    "p.legend()\n",
    "ax.set_xlabel(\"time / s\")\n",
    "ax.set_ylabel(\"Signal intensity / a.u.\")\n",
    "\n",
    "display(rec[\"amp\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculating Signal Quality Metrics and applying Masks\n",
    "\n",
    "To assess channel quality metrics such as SNR, channel distances, average amplitudes, sci, and others, we use small helper functions. \n",
    "As input, the quality functions should also expect thresholds for these metrics, so they can feed back both the calculated quality metrics as well as a mask. The masks can then be combined and applied - e.g. to prune channels with low SNR.\n",
    "The input and output arguments are based on xarray time series, quality parameters / instructions for thresholding. \n",
    "The returned mask is a boolean array in the shape and size of the input time series. It indicates where the threshold for our quality metric was passed (\"True\") and is False otherwise.\n",
    "Masks can be combined with other masks, for instance to apply several metrics to assess or prune channels. At any point in time, the mask can be applied using the \"apply_mask()\" function available from cedalion's the xrutils package. \n",
    "\n",
    "If you are a user who is mainly interested in high-level application, you can skip to the Section \"***Channel Pruning using Quality Metrics and the Pruning Function***\" below. The \"prune_ch()\" function provides a higher abstraction layer to simply prune your data, using the same metrics and functions that are demonstrated below. \n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Channel Quality Metrics: SNR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T12:56:36.130844Z",
     "iopub.status.busy": "2025-04-14T12:56:36.130670Z",
     "iopub.status.idle": "2025-04-14T12:56:36.168235Z",
     "shell.execute_reply": "2025-04-14T12:56:36.167703Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "channels that were masked according to the SNR threshold: ['S4D4' 'S5D7' 'S6D8' 'S8D8']\n"
     ]
    },
    {
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       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (channel: 24, wavelength: 2, time: 23239)&gt; Size: 9MB\n",
       "&lt;Quantity([[[0.0913686 0.0909875 0.0910225 ... 0.0941083 0.0940129 0.0944882]\n",
       "  [0.1856806 0.186377  0.1836514 ... 0.1856486 0.1850836 0.1842172]]\n",
       "\n",
       " [[0.227516  0.2297024 0.2261366 ... 0.2264519 0.2271665 0.226713 ]\n",
       "  [0.6354927 0.637668  0.6298023 ... 0.6072068 0.6087293 0.6091066]]\n",
       "\n",
       " [[0.1064704 0.1066212 0.1053444 ... 0.121114  0.1205022 0.1205441]\n",
       "  [0.2755033 0.2761615 0.2727006 ... 0.2911952 0.2900544 0.2909847]]\n",
       "\n",
       " ...\n",
       "\n",
       " [[0.187484  0.1868235 0.1866562 ... 0.1735965 0.1736705 0.1738339]\n",
       "  [0.2424386 0.241503  0.2408491 ... 0.22303   0.2229887 0.2234081]]\n",
       "\n",
       " [[0.2027881 0.1996586 0.2004866 ... 0.2318743 0.2311941 0.2330808]\n",
       "  [0.4666358 0.4554404 0.4561614 ... 0.4809749 0.4812827 0.4862896]]\n",
       "\n",
       " [[0.6304559 0.6284427 0.6287045 ... 0.6810626 0.6809573 0.6818709]\n",
       "  [1.2285622 1.2205907 1.2190002 ... 1.2729124 1.2727222 1.2755645]]], &#x27;volt&#x27;)&gt;\n",
       "Coordinates:\n",
       "  * time        (time) float64 186kB 0.0 0.128 0.256 ... 2.974e+03 2.974e+03\n",
       "    samples     (time) int64 186kB 0 1 2 3 4 5 ... 23234 23235 23236 23237 23238\n",
       "  * channel     (channel) object 192B &#x27;S1D1&#x27; &#x27;S1D2&#x27; &#x27;S1D3&#x27; ... &#x27;S8D7&#x27; &#x27;S8D16&#x27;\n",
       "    source      (channel) object 192B &#x27;S1&#x27; &#x27;S1&#x27; &#x27;S1&#x27; &#x27;S1&#x27; ... &#x27;S7&#x27; &#x27;S8&#x27; &#x27;S8&#x27;\n",
       "    detector    (channel) object 192B &#x27;D1&#x27; &#x27;D2&#x27; &#x27;D3&#x27; &#x27;D9&#x27; ... &#x27;D15&#x27; &#x27;D7&#x27; &#x27;D16&#x27;\n",
       "  * wavelength  (wavelength) float64 16B 760.0 850.0\n",
       "Attributes:\n",
       "    data_type_group:  unprocessed raw</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 24</li><li><span class='xr-has-index'>wavelength</span>: 2</li><li><span class='xr-has-index'>time</span>: 23239</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-1ff3b437-1023-4812-ac5d-2cd154ea2575' class='xr-array-in' type='checkbox' checked><label for='section-1ff3b437-1023-4812-ac5d-2cd154ea2575' 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>[V] 0.09137 0.09099 0.09102 0.09044 ... 1.273 1.273 1.273 1.276</span></div><div class='xr-array-data'><table><tbody><tr><th>Magnitude</th><td style='text-align:left;'><pre>[[[0.0913686 0.0909875 0.0910225 ... 0.0941083 0.0940129 0.0944882]  [0.1856806 0.186377 0.1836514 ... 0.1856486 0.1850836 0.1842172]] [[0.227516 0.2297024 0.2261366 ... 0.2264519 0.2271665 0.226713]  [0.6354927 0.637668 0.6298023 ... 0.6072068 0.6087293 0.6091066]] [[0.1064704 0.1066212 0.1053444 ... 0.121114 0.1205022 0.1205441]  [0.2755033 0.2761615 0.2727006 ... 0.2911952 0.2900544 0.2909847]] ... [[0.187484 0.1868235 0.1866562 ... 0.1735965 0.1736705 0.1738339]  [0.2424386 0.241503 0.2408491 ... 0.22303 0.2229887 0.2234081]] [[0.2027881 0.1996586 0.2004866 ... 0.2318743 0.2311941 0.2330808]  [0.4666358 0.4554404 0.4561614 ... 0.4809749 0.4812827 0.4862896]] [[0.6304559 0.6284427 0.6287045 ... 0.6810626 0.6809573 0.6818709]  [1.2285622 1.2205907 1.2190002 ... 1.2729124 1.2727222 1.2755645]]]</pre></td></tr><tr><th>Units</th><td style='text-align:left;'>volt</td></tr></tbody></table></div></div></li><li class='xr-section-item'><input id='section-cb70543b-b421-44a6-aa8b-47f01ddf39e3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cb70543b-b421-44a6-aa8b-47f01ddf39e3' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.128 ... 2.974e+03 2.974e+03</div><input id='attrs-3091fd82-fd41-4eb2-9c8e-750827e095e0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3091fd82-fd41-4eb2-9c8e-750827e095e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3bd185fa-2fac-4178-97c8-bb4c3a7ca2af' class='xr-var-data-in' type='checkbox'><label for='data-3bd185fa-2fac-4178-97c8-bb4c3a7ca2af' 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>second</dd></dl></div><div class='xr-var-data'><pre>array([0.000000e+00, 1.280000e-01, 2.560000e-01, ..., 2.974208e+03,\n",
       "       2.974336e+03, 2.974464e+03])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>samples</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 ... 23235 23236 23237 23238</div><input id='attrs-49c6e751-723e-41df-bdc4-86c417c20f7e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-49c6e751-723e-41df-bdc4-86c417c20f7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5244a085-e9e0-4697-b261-17cad333833b' class='xr-var-data-in' type='checkbox'><label for='data-5244a085-e9e0-4697-b261-17cad333833b' 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, ..., 23236, 23237, 23238])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;S1D1&#x27; &#x27;S1D2&#x27; ... &#x27;S8D7&#x27; &#x27;S8D16&#x27;</div><input id='attrs-44bcf60e-7cf8-49d4-9824-4f26ce3e9263' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-44bcf60e-7cf8-49d4-9824-4f26ce3e9263' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9066ddc-2ae3-4eea-9b62-ed23cb54acc3' class='xr-var-data-in' type='checkbox'><label for='data-b9066ddc-2ae3-4eea-9b62-ed23cb54acc3' 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;S1D1&#x27;, &#x27;S1D2&#x27;, &#x27;S1D3&#x27;, &#x27;S1D9&#x27;, &#x27;S2D1&#x27;, &#x27;S2D3&#x27;, &#x27;S2D4&#x27;, &#x27;S2D10&#x27;, &#x27;S3D2&#x27;,\n",
       "       &#x27;S3D3&#x27;, &#x27;S3D11&#x27;, &#x27;S4D3&#x27;, &#x27;S4D12&#x27;, &#x27;S5D5&#x27;, &#x27;S5D6&#x27;, &#x27;S5D13&#x27;, &#x27;S6D5&#x27;,\n",
       "       &#x27;S6D7&#x27;, &#x27;S6D14&#x27;, &#x27;S7D6&#x27;, &#x27;S7D7&#x27;, &#x27;S7D15&#x27;, &#x27;S8D7&#x27;, &#x27;S8D16&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;S1&#x27; &#x27;S1&#x27; &#x27;S1&#x27; ... &#x27;S7&#x27; &#x27;S8&#x27; &#x27;S8&#x27;</div><input id='attrs-6bca32de-3c9a-4bcd-bf5f-d0b099f83632' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6bca32de-3c9a-4bcd-bf5f-d0b099f83632' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47d24829-d54b-46e5-b6d2-794ff15b408d' class='xr-var-data-in' type='checkbox'><label for='data-47d24829-d54b-46e5-b6d2-794ff15b408d' 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;S1&#x27;, &#x27;S1&#x27;, &#x27;S1&#x27;, &#x27;S1&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S3&#x27;, &#x27;S3&#x27;, &#x27;S3&#x27;,\n",
       "       &#x27;S4&#x27;, &#x27;S4&#x27;, &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;, &#x27;S7&#x27;, &#x27;S7&#x27;, &#x27;S7&#x27;,\n",
       "       &#x27;S8&#x27;, &#x27;S8&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>detector</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;D1&#x27; &#x27;D2&#x27; &#x27;D3&#x27; ... &#x27;D15&#x27; &#x27;D7&#x27; &#x27;D16&#x27;</div><input id='attrs-56fc7752-83d9-431e-876d-a2e5f89f2a5a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-56fc7752-83d9-431e-876d-a2e5f89f2a5a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac852209-eb24-4202-a2ef-40ae6a492e8c' class='xr-var-data-in' type='checkbox'><label for='data-ac852209-eb24-4202-a2ef-40ae6a492e8c' 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;D1&#x27;, &#x27;D2&#x27;, &#x27;D3&#x27;, &#x27;D9&#x27;, &#x27;D1&#x27;, &#x27;D3&#x27;, &#x27;D4&#x27;, &#x27;D10&#x27;, &#x27;D2&#x27;, &#x27;D3&#x27;, &#x27;D11&#x27;,\n",
       "       &#x27;D3&#x27;, &#x27;D12&#x27;, &#x27;D5&#x27;, &#x27;D6&#x27;, &#x27;D13&#x27;, &#x27;D5&#x27;, &#x27;D7&#x27;, &#x27;D14&#x27;, &#x27;D6&#x27;, &#x27;D7&#x27;,\n",
       "       &#x27;D15&#x27;, &#x27;D7&#x27;, &#x27;D16&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>wavelength</span></div><div class='xr-var-dims'>(wavelength)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>760.0 850.0</div><input id='attrs-871159b7-4ca4-45a0-a25e-68051ac23bc3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-871159b7-4ca4-45a0-a25e-68051ac23bc3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-621c0d72-940f-487d-a2f0-c5ffc531c260' class='xr-var-data-in' type='checkbox'><label for='data-621c0d72-940f-487d-a2f0-c5ffc531c260' 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([760., 850.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b47c6858-26ab-43df-abaf-e8c24ef68f0c' class='xr-section-summary-in' type='checkbox'  ><label for='section-b47c6858-26ab-43df-abaf-e8c24ef68f0c' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-648107fb-b4a1-4e86-aead-9ec44bb248a8' class='xr-index-data-in' type='checkbox'/><label for='index-648107fb-b4a1-4e86-aead-9ec44bb248a8' 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([     0.0,    0.128,    0.256,    0.384,    0.512,     0.64,    0.768,\n",
       "          0.896,    1.024,    1.152,\n",
       "       ...\n",
       "       2973.312,  2973.44, 2973.568, 2973.696, 2973.824, 2973.952,  2974.08,\n",
       "       2974.208, 2974.336, 2974.464],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;time&#x27;, length=23239))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>channel</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6cf1f8e9-3ccd-49f4-b040-65154bf00116' class='xr-index-data-in' type='checkbox'/><label for='index-6cf1f8e9-3ccd-49f4-b040-65154bf00116' 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([&#x27;S1D1&#x27;, &#x27;S1D2&#x27;, &#x27;S1D3&#x27;, &#x27;S1D9&#x27;, &#x27;S2D1&#x27;, &#x27;S2D3&#x27;, &#x27;S2D4&#x27;, &#x27;S2D10&#x27;, &#x27;S3D2&#x27;,\n",
       "       &#x27;S3D3&#x27;, &#x27;S3D11&#x27;, &#x27;S4D3&#x27;, &#x27;S4D12&#x27;, &#x27;S5D5&#x27;, &#x27;S5D6&#x27;, &#x27;S5D13&#x27;, &#x27;S6D5&#x27;,\n",
       "       &#x27;S6D7&#x27;, &#x27;S6D14&#x27;, &#x27;S7D6&#x27;, &#x27;S7D7&#x27;, &#x27;S7D15&#x27;, &#x27;S8D7&#x27;, &#x27;S8D16&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>wavelength</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-405f6a69-32d5-4896-8c3f-2e6e4d8bf6ff' class='xr-index-data-in' type='checkbox'/><label for='index-405f6a69-32d5-4896-8c3f-2e6e4d8bf6ff' 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([760.0, 850.0], dtype=&#x27;float64&#x27;, name=&#x27;wavelength&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-57617702-6457-436e-8ab8-100b77ec1796' class='xr-section-summary-in' type='checkbox'  checked><label for='section-57617702-6457-436e-8ab8-100b77ec1796' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>data_type_group :</span></dt><dd>unprocessed raw</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (channel: 24, wavelength: 2, time: 23239)> Size: 9MB\n",
       "<Quantity([[[0.0913686 0.0909875 0.0910225 ... 0.0941083 0.0940129 0.0944882]\n",
       "  [0.1856806 0.186377  0.1836514 ... 0.1856486 0.1850836 0.1842172]]\n",
       "\n",
       " [[0.227516  0.2297024 0.2261366 ... 0.2264519 0.2271665 0.226713 ]\n",
       "  [0.6354927 0.637668  0.6298023 ... 0.6072068 0.6087293 0.6091066]]\n",
       "\n",
       " [[0.1064704 0.1066212 0.1053444 ... 0.121114  0.1205022 0.1205441]\n",
       "  [0.2755033 0.2761615 0.2727006 ... 0.2911952 0.2900544 0.2909847]]\n",
       "\n",
       " ...\n",
       "\n",
       " [[0.187484  0.1868235 0.1866562 ... 0.1735965 0.1736705 0.1738339]\n",
       "  [0.2424386 0.241503  0.2408491 ... 0.22303   0.2229887 0.2234081]]\n",
       "\n",
       " [[0.2027881 0.1996586 0.2004866 ... 0.2318743 0.2311941 0.2330808]\n",
       "  [0.4666358 0.4554404 0.4561614 ... 0.4809749 0.4812827 0.4862896]]\n",
       "\n",
       " [[0.6304559 0.6284427 0.6287045 ... 0.6810626 0.6809573 0.6818709]\n",
       "  [1.2285622 1.2205907 1.2190002 ... 1.2729124 1.2727222 1.2755645]]], 'volt')>\n",
       "Coordinates:\n",
       "  * time        (time) float64 186kB 0.0 0.128 0.256 ... 2.974e+03 2.974e+03\n",
       "    samples     (time) int64 186kB 0 1 2 3 4 5 ... 23234 23235 23236 23237 23238\n",
       "  * channel     (channel) object 192B 'S1D1' 'S1D2' 'S1D3' ... 'S8D7' 'S8D16'\n",
       "    source      (channel) object 192B 'S1' 'S1' 'S1' 'S1' ... 'S7' 'S8' 'S8'\n",
       "    detector    (channel) object 192B 'D1' 'D2' 'D3' 'D9' ... 'D15' 'D7' 'D16'\n",
       "  * wavelength  (wavelength) float64 16B 760.0 850.0\n",
       "Attributes:\n",
       "    data_type_group:  unprocessed raw"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Here we assess channel quality by SNR\n",
    "snr_thresh = 16 # the SNR (std/mean) of a channel. Set high here for demonstration purposes\n",
    "\n",
    "# SNR thresholding using the \"snr\" function of the quality subpackage\n",
    "snr, snr_mask = quality.snr(rec[\"amp\"], snr_thresh)\n",
    "\n",
    "# apply mask function. In this example, we want all signals with an SNR below the threshold to be replaced with \"nan\". \n",
    "# We do not want to collapse / combine any dimension of the mask (last argument: \"none\")\n",
    "data_masked_snr_1, masked_elements_1 = xrutils.apply_mask(rec[\"amp\"], snr_mask, \"nan\", \"none\")\n",
    "\n",
    "# alternatively, we can \"drop\" all channels with an SNR below the threshold. Since the SNR of both wavelength might differ\n",
    "# (pass the threshold for one wavelength, but not for the other), we collapse to the \"channel\" dimension.\n",
    "data_masked_snr_2, masked_elements_2 = xrutils.apply_mask(rec[\"amp\"], snr_mask, \"drop\", \"channel\")\n",
    "\n",
    "# show some results\n",
    "print(f\"channels that were masked according to the SNR threshold: {masked_elements_2}\")\n",
    "\n",
    "# dropped:\n",
    "data_masked_snr_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T12:56:36.170415Z",
     "iopub.status.busy": "2025-04-14T12:56:36.170065Z",
     "iopub.status.idle": "2025-04-14T12:56:36.529881Z",
     "shell.execute_reply": "2025-04-14T12:56:36.529287Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# we can plot the values per channel in a 2D montage\n",
    "wl_idx = 0\n",
    "# plots._simple_scalp_plot(rec['amp'], rec.geo3d, snr.isel(wavelength=wl_idx), ax, cmap=p.cm.jet, vmin=0, vmax=25, title='SNR ' + str(rec.wavelengths[wl_idx]))\n",
    "# plots.scalp_plot(rec, snr.isel(wavelength=wl_idx).values, ax, colormap=p.cm.jet, vmin=0, vmax=25, title='SNR ' + str(rec.wavelengths[wl_idx]))\n",
    "\n",
    "f, ax = p.subplots(1, 2, figsize=(10, 4))\n",
    "for i, wl in enumerate(rec[\"amp\"].wavelength.values):\n",
    "    plots.scalp_plot(\n",
    "        rec[\"amp\"],\n",
    "        rec.geo3d,\n",
    "        snr.sel(wavelength=wl),\n",
    "        ax[i],\n",
    "        cmap=\"RdYlGn\",\n",
    "        vmin=0,\n",
    "        vmax=50,\n",
    "        title=f\"{wl} nm\",\n",
    "        cb_label=\"SNR\",\n",
    "        channel_lw=2\n",
    "    )\n",
    "f.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Channel Quality Metrics: Scalp Coupling Index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T12:56:36.531863Z",
     "iopub.status.busy": "2025-04-14T12:56:36.531699Z",
     "iopub.status.idle": "2025-04-14T12:56:36.609062Z",
     "shell.execute_reply": "2025-04-14T12:56:36.608611Z"
    }
   },
   "outputs": [],
   "source": [
    "# Here we can assess the scalp coupling index (SCI) of the channels\n",
    "sci_threshold = 0.75\n",
    "window_length = 5*units.s\n",
    "sci, sci_mask = quality.sci(rec[\"amp\"], window_length, sci_threshold)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T12:56:36.611276Z",
     "iopub.status.busy": "2025-04-14T12:56:36.611100Z",
     "iopub.status.idle": "2025-04-14T12:56:37.197353Z",
     "shell.execute_reply": "2025-04-14T12:56:37.196797Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/runner/miniconda3/envs/cedalion/lib/python3.11/site-packages/xarray/core/variable.py:338: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n",
      "  data = np.asarray(data)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1700x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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      "text/plain": [
       "<Figure size 1700x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# we can plot a heat map to visualize the SCI across all time windows and channels\n",
    "colors = [\"black\", \"#DC3220\", \"#5D3A9B\", \"#0C7BDC\"]\n",
    "nodes = [0.0, 0.75, 0.751, 1.0]\n",
    "sci_cmap = LinearSegmentedColormap.from_list(\"sci_cmap\", list(zip(nodes,colors)))\n",
    "sci_binary_cmap = LinearSegmentedColormap.from_list(\"sci_binary_cmap\", list(zip([0,0.5,0.5,1],[\"#DC3220\",\"#DC3220\",\"#0C7BDC\",\"#0C7BDC\"])))\n",
    "\n",
    "# plot the heatmap\n",
    "f,ax = p.subplots(1,1,figsize=(17,8))\n",
    "\n",
    "m = ax.pcolormesh(sci.time, np.arange(len(sci.channel)), sci, shading=\"nearest\", cmap=sci_cmap)\n",
    "cb = p.colorbar(m, ax=ax)\n",
    "cb.set_label(\"SCI\")\n",
    "ax.set_xlabel(\"time / s\")\n",
    "p.tight_layout()\n",
    "ax.yaxis.set_ticks(np.arange(len(sci.channel)))\n",
    "ax.yaxis.set_ticklabels(sci.channel.values);\n",
    "\n",
    "# plot the binary heatmap\n",
    "f,ax = p.subplots(1,1,figsize=(17,8))\n",
    "\n",
    "m = ax.pcolormesh(sci.time, np.arange(len(sci.channel)), sci>0.75, shading=\"nearest\", cmap=sci_binary_cmap)\n",
    "cb = p.colorbar(m, ax=ax)\n",
    "p.tight_layout()\n",
    "ax.yaxis.set_ticks(np.arange(len(sci.channel)))\n",
    "ax.yaxis.set_ticklabels(sci.channel.values);\n",
    "cb.set_label(\"SCI > 0.75\")\n",
    "ax.set_xlabel(\"time / s\");\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T12:56:37.199283Z",
     "iopub.status.busy": "2025-04-14T12:56:37.199099Z",
     "iopub.status.idle": "2025-04-14T12:56:37.725881Z",
     "shell.execute_reply": "2025-04-14T12:56:37.725292Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1700x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ch = \"S3D3\"\n",
    "t1,t2 = 100, 1200\n",
    "f,ax = p.subplots(2,1, figsize=(17,5), sharex=True)\n",
    "ax[0].plot(rec[\"amp\"].time, rec[\"amp\"].sel(channel=ch, wavelength=760), \"r-\")\n",
    "ax[0].set_ylabel(\"HbO\", color=\"r\")\n",
    "ax02 = ax[0].twinx()\n",
    "ax02.plot(rec[\"amp\"].time, rec[\"amp\"].sel(channel=ch, wavelength=850), \"b-\")\n",
    "ax02.set_ylabel(\"HbR\", color=\"b\")\n",
    "ax[1].plot(sci.time, sci.sel(channel=ch), \"m.-\")\n",
    "ax[1].set_ylabel(\"sci\", color=\"m\")\n",
    "ax12 = ax[1].twinx()\n",
    "ax12.plot(sci_mask.time, sci_mask.sel(channel=ch), \"g-\")\n",
    "ax12.set_ylabel(\"sci_mask\", color=\"g\")\n",
    "ax[1].set_xlim(t1, t2)\n",
    "ax[1].axhline(0.75, c=\"k\", ls=\":\")\n",
    "for i in sci.time.values:\n",
    "    if i < t1 or i > t2:\n",
    "        continue\n",
    "    ax[0].axvline(i, c=\"k\", alpha=.2)\n",
    "    ax[1].axvline(i, c=\"k\", alpha=.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Channel Quality Metrics: Peak Spectral Power"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T12:56:37.728136Z",
     "iopub.status.busy": "2025-04-14T12:56:37.727958Z",
     "iopub.status.idle": "2025-04-14T12:56:38.003169Z",
     "shell.execute_reply": "2025-04-14T12:56:38.002677Z"
    }
   },
   "outputs": [],
   "source": [
    "# We can also look at the peak spectral power which takes the peak power of the cross-correlation signal between the cardiac band of the two wavelengths\n",
    "psp_threshold = 0.1\n",
    "psp, psp_mask = quality.psp(rec[\"amp\"], window_length, psp_threshold)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T12:56:38.005608Z",
     "iopub.status.busy": "2025-04-14T12:56:38.005195Z",
     "iopub.status.idle": "2025-04-14T12:56:38.700521Z",
     "shell.execute_reply": "2025-04-14T12:56:38.699938Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1700x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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      "text/plain": [
       "<Figure size 1700x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# We can look at similar heatmaps across time and channels\n",
    "# plot the heatmap\n",
    "colors = [\"black\", \"#DC3220\", \"#5D3A9B\", \"#0C7BDC\"]\n",
    "nodes = [0.0, 0.45, 0.46, 1.0]\n",
    "psp_cmap = LinearSegmentedColormap.from_list(\"psp_cmap\", list(zip(nodes,colors)))\n",
    "psp_binary_cmap = LinearSegmentedColormap.from_list(\"psp_binary_cmap\", list(zip([0,0.5,0.5,1],[\"#DC3220\",\"#DC3220\",\"#0C7BDC\",\"#0C7BDC\"])))\n",
    "\n",
    "f,ax = p.subplots(1,1,figsize=(17,8))\n",
    "\n",
    "m = ax.pcolormesh(psp.time, np.arange(len(psp.channel)), psp, shading=\"nearest\", cmap=psp_cmap)\n",
    "cb = p.colorbar(m, ax=ax)\n",
    "cb.set_label(\"PSP\")\n",
    "ax.set_xlabel(\"time / s\")\n",
    "p.tight_layout()\n",
    "ax.yaxis.set_ticks(np.arange(len(psp.channel)))\n",
    "ax.yaxis.set_ticklabels(psp.channel.values);\n",
    "\n",
    "# plot the binary heatmap\n",
    "f,ax = p.subplots(1,1,figsize=(17,8))\n",
    "\n",
    "m = ax.pcolormesh(psp.time, np.arange(len(psp.channel)), psp>psp_threshold, shading=\"nearest\", cmap=psp_binary_cmap)\n",
    "cb = p.colorbar(m, ax=ax)\n",
    "p.tight_layout()\n",
    "ax.yaxis.set_ticks(np.arange(len(psp.channel)))\n",
    "ax.yaxis.set_ticklabels(psp.channel.values);\n",
    "cb.set_label(\"PSP > 0.1\")\n",
    "ax.set_xlabel(\"time / s\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Combining SCI and PSP\n",
    "We want both SCI and PSP to be above their respective thresholds for a window to be considered clean. We can then look at the percentage of time both metrics are above the thresholds."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T12:56:38.702581Z",
     "iopub.status.busy": "2025-04-14T12:56:38.702399Z",
     "iopub.status.idle": "2025-04-14T12:56:39.167326Z",
     "shell.execute_reply": "2025-04-14T12:56:39.166831Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1700x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sci_x_psp_mask = sci_mask & psp_mask\n",
    "perc_time_clean = sci_x_psp_mask.sum(dim=\"time\") / len(sci.time)\n",
    "\n",
    "# plot the percentage of clean time per channel\n",
    "f,ax = p.subplots(1,1,figsize=(8,8))\n",
    "# plots.scalp_plot(rec, perc_time_clean, ax, colormap=p.cm.jet, vmin=0, vmax=1, title='Percentage of clean time')\n",
    "# plots._simple_scalp_plot(rec['amp'], rec.geo3d, perc_time_clean, ax, cmap=p.cm.jet, vmin=0, vmax=1, title='Percentage of clean time')\n",
    "\n",
    "plots.scalp_plot(\n",
    "    rec[\"amp\"],\n",
    "    rec.geo3d,\n",
    "    perc_time_clean,\n",
    "    ax,\n",
    "    cmap=\"RdYlGn\",\n",
    "    vmin=0,\n",
    "    vmax=1,\n",
    "    title=None,\n",
    "    cb_label=\"Percentage of clean time\",\n",
    "    channel_lw=2\n",
    ")\n",
    "f.tight_layout()\n",
    "\n",
    "# we can also plot this as a binary heatmap\n",
    "f,ax = p.subplots(1,1,figsize=(17,8))\n",
    "\n",
    "m = ax.pcolormesh(sci_x_psp_mask.time, np.arange(len(sci_x_psp_mask.channel)), sci_x_psp_mask, shading=\"nearest\", cmap=sci_binary_cmap)\n",
    "cb = p.colorbar(m, ax=ax)\n",
    "p.tight_layout()\n",
    "ax.yaxis.set_ticks(np.arange(len(sci_x_psp_mask.channel)))\n",
    "ax.yaxis.set_ticklabels(sci_x_psp_mask.channel.values);\n",
    "cb.set_label(\"PSP > 0.1 and SCI > 0.75\")\n",
    "ax.set_xlabel(\"time / s\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Channel Quality Metrics: Channel Distance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T12:56:39.169402Z",
     "iopub.status.busy": "2025-04-14T12:56:39.169226Z",
     "iopub.status.idle": "2025-04-14T12:56:39.198972Z",
     "shell.execute_reply": "2025-04-14T12:56:39.198486Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "channel distances are: <xarray.DataArray (channel: 28)> Size: 224B\n",
      "<Quantity([0.039 0.039 0.041 0.008 0.037 0.038 0.037 0.007 0.04  0.037 0.008 0.041\n",
      " 0.034 0.008 0.039 0.039 0.041 0.008 0.037 0.037 0.037 0.008 0.04  0.037\n",
      " 0.007 0.041 0.033 0.008], 'meter')>\n",
      "Coordinates:\n",
      "  * channel   (channel) object 224B 'S1D1' 'S1D2' 'S1D3' ... 'S8D8' 'S8D16'\n",
      "    source    (channel) object 224B 'S1' 'S1' 'S1' 'S1' ... 'S7' 'S8' 'S8' 'S8'\n",
      "    detector  (channel) object 224B 'D1' 'D2' 'D3' 'D9' ... 'D7' 'D8' 'D16'\n",
      "channels that were masked according to the SD Distance thresholds: ['S1D9' 'S2D10' 'S3D11' 'S4D12' 'S5D13' 'S6D14' 'S7D15' 'S8D16']\n"
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       "  * wavelength  (wavelength) float64 16B 760.0 850.0\n",
       "Attributes:\n",
       "    data_type_group:  unprocessed raw</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 20</li><li><span class='xr-has-index'>wavelength</span>: 2</li><li><span class='xr-has-index'>time</span>: 23239</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-32582d57-e347-4143-b4e9-12af8f26f174' class='xr-array-in' type='checkbox' checked><label for='section-32582d57-e347-4143-b4e9-12af8f26f174' 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>[V] 0.09137 0.09099 0.09102 0.09044 ... 0.9732 0.9759 0.9757 0.9826</span></div><div class='xr-array-data'><table><tbody><tr><th>Magnitude</th><td style='text-align:left;'><pre>[[[0.0913686 0.0909875 0.0910225 ... 0.0941083 0.0940129 0.0944882]  [0.1856806 0.186377 0.1836514 ... 0.1856486 0.1850836 0.1842172]] [[0.227516 0.2297024 0.2261366 ... 0.2264519 0.2271665 0.226713]  [0.6354927 0.637668 0.6298023 ... 0.6072068 0.6087293 0.6091066]] [[0.1064704 0.1066212 0.1053444 ... 0.121114 0.1205022 0.1205441]  [0.2755033 0.2761615 0.2727006 ... 0.2911952 0.2900544 0.2909847]] ... [[0.2225884 0.2187791 0.2195495 ... 0.2564863 0.2551258 0.2560233]  [0.3994258 0.3917637 0.389261 ... 0.4304597 0.430814 0.4331249]] [[0.2027881 0.1996586 0.2004866 ... 0.2318743 0.2311941 0.2330808]  [0.4666358 0.4554404 0.4561614 ... 0.4809749 0.4812827 0.4862896]] [[0.4885007 0.4802285 0.4818338 ... 0.6109142 0.6108118 0.613845]  [0.8457658 0.825988 0.8259648 ... 0.975894 0.9756599 0.9826459]]]</pre></td></tr><tr><th>Units</th><td style='text-align:left;'>volt</td></tr></tbody></table></div></div></li><li class='xr-section-item'><input id='section-e8d9b834-2c87-4eff-8f3c-35d90af4cc9f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e8d9b834-2c87-4eff-8f3c-35d90af4cc9f' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.128 ... 2.974e+03 2.974e+03</div><input id='attrs-bf44fd6b-bbda-4a62-8fb9-e64da23a833f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf44fd6b-bbda-4a62-8fb9-e64da23a833f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fccc29e7-2d87-4d61-8456-467c68746465' class='xr-var-data-in' type='checkbox'><label for='data-fccc29e7-2d87-4d61-8456-467c68746465' 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>second</dd></dl></div><div class='xr-var-data'><pre>array([0.000000e+00, 1.280000e-01, 2.560000e-01, ..., 2.974208e+03,\n",
       "       2.974336e+03, 2.974464e+03])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>samples</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 ... 23235 23236 23237 23238</div><input id='attrs-d4719c09-8ea1-48fe-885d-c1797e9374d3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d4719c09-8ea1-48fe-885d-c1797e9374d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-955df712-9cfd-432f-8bad-6a48a7dc1e3f' class='xr-var-data-in' type='checkbox'><label for='data-955df712-9cfd-432f-8bad-6a48a7dc1e3f' 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, ..., 23236, 23237, 23238])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;S1D1&#x27; &#x27;S1D2&#x27; ... &#x27;S8D7&#x27; &#x27;S8D8&#x27;</div><input id='attrs-2e30670d-ef7c-4f28-9bf0-91ac1555326c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2e30670d-ef7c-4f28-9bf0-91ac1555326c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c94eb96-7b21-42cd-b79c-055c71cee47d' class='xr-var-data-in' type='checkbox'><label for='data-0c94eb96-7b21-42cd-b79c-055c71cee47d' 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;S1D1&#x27;, &#x27;S1D2&#x27;, &#x27;S1D3&#x27;, &#x27;S2D1&#x27;, &#x27;S2D3&#x27;, &#x27;S2D4&#x27;, &#x27;S3D2&#x27;, &#x27;S3D3&#x27;, &#x27;S4D3&#x27;,\n",
       "       &#x27;S4D4&#x27;, &#x27;S5D5&#x27;, &#x27;S5D6&#x27;, &#x27;S5D7&#x27;, &#x27;S6D5&#x27;, &#x27;S6D7&#x27;, &#x27;S6D8&#x27;, &#x27;S7D6&#x27;, &#x27;S7D7&#x27;,\n",
       "       &#x27;S8D7&#x27;, &#x27;S8D8&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;S1&#x27; &#x27;S1&#x27; &#x27;S1&#x27; ... &#x27;S7&#x27; &#x27;S8&#x27; &#x27;S8&#x27;</div><input id='attrs-3499e2b6-ef60-41c1-ba55-4d77b4420578' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3499e2b6-ef60-41c1-ba55-4d77b4420578' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce34d769-e6e9-4e52-9f99-c941cf161d90' class='xr-var-data-in' type='checkbox'><label for='data-ce34d769-e6e9-4e52-9f99-c941cf161d90' 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;S1&#x27;, &#x27;S1&#x27;, &#x27;S1&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S3&#x27;, &#x27;S3&#x27;, &#x27;S4&#x27;, &#x27;S4&#x27;, &#x27;S5&#x27;,\n",
       "       &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;, &#x27;S7&#x27;, &#x27;S7&#x27;, &#x27;S8&#x27;, &#x27;S8&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>detector</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;D1&#x27; &#x27;D2&#x27; &#x27;D3&#x27; ... &#x27;D7&#x27; &#x27;D7&#x27; &#x27;D8&#x27;</div><input id='attrs-f2667c33-9607-4f3d-9371-14dc17bd90be' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f2667c33-9607-4f3d-9371-14dc17bd90be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18b319d3-d05f-48aa-9461-97ca32ccd7d1' class='xr-var-data-in' type='checkbox'><label for='data-18b319d3-d05f-48aa-9461-97ca32ccd7d1' 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;D1&#x27;, &#x27;D2&#x27;, &#x27;D3&#x27;, &#x27;D1&#x27;, &#x27;D3&#x27;, &#x27;D4&#x27;, &#x27;D2&#x27;, &#x27;D3&#x27;, &#x27;D3&#x27;, &#x27;D4&#x27;, &#x27;D5&#x27;,\n",
       "       &#x27;D6&#x27;, &#x27;D7&#x27;, &#x27;D5&#x27;, &#x27;D7&#x27;, &#x27;D8&#x27;, &#x27;D6&#x27;, &#x27;D7&#x27;, &#x27;D7&#x27;, &#x27;D8&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>wavelength</span></div><div class='xr-var-dims'>(wavelength)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>760.0 850.0</div><input id='attrs-639b11cc-2204-4bd0-a38b-582e377a53b3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-639b11cc-2204-4bd0-a38b-582e377a53b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1271297-c3b4-4471-8cf2-136c459ef56a' class='xr-var-data-in' type='checkbox'><label for='data-e1271297-c3b4-4471-8cf2-136c459ef56a' 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([760., 850.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7f6d7b6c-236c-4c97-9f5e-dd73fe0842c5' class='xr-section-summary-in' type='checkbox'  ><label for='section-7f6d7b6c-236c-4c97-9f5e-dd73fe0842c5' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5b5b5076-93ce-4c17-bc4e-6a1d9600c73c' class='xr-index-data-in' type='checkbox'/><label for='index-5b5b5076-93ce-4c17-bc4e-6a1d9600c73c' 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([     0.0,    0.128,    0.256,    0.384,    0.512,     0.64,    0.768,\n",
       "          0.896,    1.024,    1.152,\n",
       "       ...\n",
       "       2973.312,  2973.44, 2973.568, 2973.696, 2973.824, 2973.952,  2974.08,\n",
       "       2974.208, 2974.336, 2974.464],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;time&#x27;, length=23239))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>channel</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d583019d-7c15-46e7-9d86-d24e75d707e6' class='xr-index-data-in' type='checkbox'/><label for='index-d583019d-7c15-46e7-9d86-d24e75d707e6' 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([&#x27;S1D1&#x27;, &#x27;S1D2&#x27;, &#x27;S1D3&#x27;, &#x27;S2D1&#x27;, &#x27;S2D3&#x27;, &#x27;S2D4&#x27;, &#x27;S3D2&#x27;, &#x27;S3D3&#x27;, &#x27;S4D3&#x27;,\n",
       "       &#x27;S4D4&#x27;, &#x27;S5D5&#x27;, &#x27;S5D6&#x27;, &#x27;S5D7&#x27;, &#x27;S6D5&#x27;, &#x27;S6D7&#x27;, &#x27;S6D8&#x27;, &#x27;S7D6&#x27;, &#x27;S7D7&#x27;,\n",
       "       &#x27;S8D7&#x27;, &#x27;S8D8&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>wavelength</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-afa40285-76b8-4b7c-b4ca-3ef46b7d0fc8' class='xr-index-data-in' type='checkbox'/><label for='index-afa40285-76b8-4b7c-b4ca-3ef46b7d0fc8' 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([760.0, 850.0], dtype=&#x27;float64&#x27;, name=&#x27;wavelength&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c1b4c659-3f75-4a79-8462-1d8b99a007b4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c1b4c659-3f75-4a79-8462-1d8b99a007b4' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>data_type_group :</span></dt><dd>unprocessed raw</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (channel: 20, wavelength: 2, time: 23239)> Size: 7MB\n",
       "<Quantity([[[0.0913686 0.0909875 0.0910225 ... 0.0941083 0.0940129 0.0944882]\n",
       "  [0.1856806 0.186377  0.1836514 ... 0.1856486 0.1850836 0.1842172]]\n",
       "\n",
       " [[0.227516  0.2297024 0.2261366 ... 0.2264519 0.2271665 0.226713 ]\n",
       "  [0.6354927 0.637668  0.6298023 ... 0.6072068 0.6087293 0.6091066]]\n",
       "\n",
       " [[0.1064704 0.1066212 0.1053444 ... 0.121114  0.1205022 0.1205441]\n",
       "  [0.2755033 0.2761615 0.2727006 ... 0.2911952 0.2900544 0.2909847]]\n",
       "\n",
       " ...\n",
       "\n",
       " [[0.2225884 0.2187791 0.2195495 ... 0.2564863 0.2551258 0.2560233]\n",
       "  [0.3994258 0.3917637 0.389261  ... 0.4304597 0.430814  0.4331249]]\n",
       "\n",
       " [[0.2027881 0.1996586 0.2004866 ... 0.2318743 0.2311941 0.2330808]\n",
       "  [0.4666358 0.4554404 0.4561614 ... 0.4809749 0.4812827 0.4862896]]\n",
       "\n",
       " [[0.4885007 0.4802285 0.4818338 ... 0.6109142 0.6108118 0.613845 ]\n",
       "  [0.8457658 0.825988  0.8259648 ... 0.975894  0.9756599 0.9826459]]], 'volt')>\n",
       "Coordinates:\n",
       "  * time        (time) float64 186kB 0.0 0.128 0.256 ... 2.974e+03 2.974e+03\n",
       "    samples     (time) int64 186kB 0 1 2 3 4 5 ... 23234 23235 23236 23237 23238\n",
       "  * channel     (channel) object 160B 'S1D1' 'S1D2' 'S1D3' ... 'S8D7' 'S8D8'\n",
       "    source      (channel) object 160B 'S1' 'S1' 'S1' 'S2' ... 'S7' 'S8' 'S8'\n",
       "    detector    (channel) object 160B 'D1' 'D2' 'D3' 'D1' ... 'D7' 'D7' 'D8'\n",
       "  * wavelength  (wavelength) float64 16B 760.0 850.0\n",
       "Attributes:\n",
       "    data_type_group:  unprocessed raw"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Here we assess channel distances. We might want to exclude very short or very long channels\n",
    "sd_threshs = [1, 4.5]*units.cm # defines the lower and upper bounds for the source-detector separation that we would like to keep\n",
    "\n",
    "# Source Detector Separation thresholding\n",
    "ch_dist, sd_mask = quality.sd_dist(rec[\"amp\"], rec.geo3d, sd_threshs)\n",
    "# print the channel distances\n",
    "print(f\"channel distances are: {ch_dist}\")\n",
    "\n",
    "# apply mask function. In this example, we want to \"drop\" all channels that do not fall inside sd_threshs \n",
    "# i.e. drop channels shorter than 1cm and longer than 4.5cm. We want to collapse along the \"channel\" dimension.\n",
    "data_masked_sd, masked_elements = xrutils.apply_mask(rec[\"amp\"], sd_mask, \"drop\", \"channel\")\n",
    "\n",
    "# display the resultings\n",
    "print(f\"channels that were masked according to the SD Distance thresholds: {masked_elements}\")\n",
    "data_masked_sd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Channel Quality Metrics: Mean Amplitudes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T12:56:39.201045Z",
     "iopub.status.busy": "2025-04-14T12:56:39.200772Z",
     "iopub.status.idle": "2025-04-14T12:56:39.228533Z",
     "shell.execute_reply": "2025-04-14T12:56:39.227999Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "channels that were masked according to the amplitude threshold: ['S1D1' 'S1D9' 'S3D2' 'S6D8' 'S7D6']\n"
     ]
    },
    {
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       "  --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[data-theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (channel: 23, wavelength: 2, time: 23239)&gt; Size: 9MB\n",
       "&lt;Quantity([[[0.227516  0.2297024 0.2261366 ... 0.2264519 0.2271665 0.226713 ]\n",
       "  [0.6354927 0.637668  0.6298023 ... 0.6072068 0.6087293 0.6091066]]\n",
       "\n",
       " [[0.1064704 0.1066212 0.1053444 ... 0.121114  0.1205022 0.1205441]\n",
       "  [0.2755033 0.2761615 0.2727006 ... 0.2911952 0.2900544 0.2909847]]\n",
       "\n",
       " [[0.5512474 0.5510672 0.5476283 ... 0.6179242 0.6188702 0.6187721]\n",
       "  [1.125532  1.1238331 1.1119423 ... 1.1817728 1.1819598 1.1832658]]\n",
       "\n",
       " ...\n",
       "\n",
       " [[0.2027881 0.1996586 0.2004866 ... 0.2318743 0.2311941 0.2330808]\n",
       "  [0.4666358 0.4554404 0.4561614 ... 0.4809749 0.4812827 0.4862896]]\n",
       "\n",
       " [[0.4885007 0.4802285 0.4818338 ... 0.6109142 0.6108118 0.613845 ]\n",
       "  [0.8457658 0.825988  0.8259648 ... 0.975894  0.9756599 0.9826459]]\n",
       "\n",
       " [[0.6304559 0.6284427 0.6287045 ... 0.6810626 0.6809573 0.6818709]\n",
       "  [1.2285622 1.2205907 1.2190002 ... 1.2729124 1.2727222 1.2755645]]], &#x27;volt&#x27;)&gt;\n",
       "Coordinates:\n",
       "  * time        (time) float64 186kB 0.0 0.128 0.256 ... 2.974e+03 2.974e+03\n",
       "    samples     (time) int64 186kB 0 1 2 3 4 5 ... 23234 23235 23236 23237 23238\n",
       "  * channel     (channel) object 184B &#x27;S1D2&#x27; &#x27;S1D3&#x27; &#x27;S2D1&#x27; ... &#x27;S8D8&#x27; &#x27;S8D16&#x27;\n",
       "    source      (channel) object 184B &#x27;S1&#x27; &#x27;S1&#x27; &#x27;S2&#x27; &#x27;S2&#x27; ... &#x27;S8&#x27; &#x27;S8&#x27; &#x27;S8&#x27;\n",
       "    detector    (channel) object 184B &#x27;D2&#x27; &#x27;D3&#x27; &#x27;D1&#x27; &#x27;D3&#x27; ... &#x27;D7&#x27; &#x27;D8&#x27; &#x27;D16&#x27;\n",
       "  * wavelength  (wavelength) float64 16B 760.0 850.0\n",
       "Attributes:\n",
       "    data_type_group:  unprocessed raw</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 23</li><li><span class='xr-has-index'>wavelength</span>: 2</li><li><span class='xr-has-index'>time</span>: 23239</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7473be87-ae06-4371-bc23-29f891dfe741' class='xr-array-in' type='checkbox' checked><label for='section-7473be87-ae06-4371-bc23-29f891dfe741' 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>[V] 0.2275 0.2297 0.2261 0.2259 0.2267 ... 1.273 1.273 1.273 1.276</span></div><div class='xr-array-data'><table><tbody><tr><th>Magnitude</th><td style='text-align:left;'><pre>[[[0.227516 0.2297024 0.2261366 ... 0.2264519 0.2271665 0.226713]  [0.6354927 0.637668 0.6298023 ... 0.6072068 0.6087293 0.6091066]] [[0.1064704 0.1066212 0.1053444 ... 0.121114 0.1205022 0.1205441]  [0.2755033 0.2761615 0.2727006 ... 0.2911952 0.2900544 0.2909847]] [[0.5512474 0.5510672 0.5476283 ... 0.6179242 0.6188702 0.6187721]  [1.125532 1.1238331 1.1119423 ... 1.1817728 1.1819598 1.1832658]] ... [[0.2027881 0.1996586 0.2004866 ... 0.2318743 0.2311941 0.2330808]  [0.4666358 0.4554404 0.4561614 ... 0.4809749 0.4812827 0.4862896]] [[0.4885007 0.4802285 0.4818338 ... 0.6109142 0.6108118 0.613845]  [0.8457658 0.825988 0.8259648 ... 0.975894 0.9756599 0.9826459]] [[0.6304559 0.6284427 0.6287045 ... 0.6810626 0.6809573 0.6818709]  [1.2285622 1.2205907 1.2190002 ... 1.2729124 1.2727222 1.2755645]]]</pre></td></tr><tr><th>Units</th><td style='text-align:left;'>volt</td></tr></tbody></table></div></div></li><li class='xr-section-item'><input id='section-69ac7604-a1fd-4d54-9305-94120cf8b236' class='xr-section-summary-in' type='checkbox'  checked><label for='section-69ac7604-a1fd-4d54-9305-94120cf8b236' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.128 ... 2.974e+03 2.974e+03</div><input id='attrs-4549470d-dac3-4834-8e84-71304fba9bb8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4549470d-dac3-4834-8e84-71304fba9bb8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77ef8e51-9d97-454a-82c1-7c0fff30a5d4' class='xr-var-data-in' type='checkbox'><label for='data-77ef8e51-9d97-454a-82c1-7c0fff30a5d4' 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>second</dd></dl></div><div class='xr-var-data'><pre>array([0.000000e+00, 1.280000e-01, 2.560000e-01, ..., 2.974208e+03,\n",
       "       2.974336e+03, 2.974464e+03])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>samples</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 ... 23235 23236 23237 23238</div><input id='attrs-b680eab1-96b2-4182-8a27-7262d9c25bc7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b680eab1-96b2-4182-8a27-7262d9c25bc7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fcdd0b05-4868-4861-8557-10d3dcd2b5e0' class='xr-var-data-in' type='checkbox'><label for='data-fcdd0b05-4868-4861-8557-10d3dcd2b5e0' 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, ..., 23236, 23237, 23238])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;S1D2&#x27; &#x27;S1D3&#x27; ... &#x27;S8D8&#x27; &#x27;S8D16&#x27;</div><input id='attrs-4d698043-db5c-4c32-9a66-874e5f775891' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4d698043-db5c-4c32-9a66-874e5f775891' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-422ed4df-0ff4-4612-8527-5244c6724770' class='xr-var-data-in' type='checkbox'><label for='data-422ed4df-0ff4-4612-8527-5244c6724770' 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;S1D2&#x27;, &#x27;S1D3&#x27;, &#x27;S2D1&#x27;, &#x27;S2D3&#x27;, &#x27;S2D4&#x27;, &#x27;S2D10&#x27;, &#x27;S3D3&#x27;, &#x27;S3D11&#x27;,\n",
       "       &#x27;S4D3&#x27;, &#x27;S4D4&#x27;, &#x27;S4D12&#x27;, &#x27;S5D5&#x27;, &#x27;S5D6&#x27;, &#x27;S5D7&#x27;, &#x27;S5D13&#x27;, &#x27;S6D5&#x27;,\n",
       "       &#x27;S6D7&#x27;, &#x27;S6D14&#x27;, &#x27;S7D7&#x27;, &#x27;S7D15&#x27;, &#x27;S8D7&#x27;, &#x27;S8D8&#x27;, &#x27;S8D16&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;S1&#x27; &#x27;S1&#x27; &#x27;S2&#x27; ... &#x27;S8&#x27; &#x27;S8&#x27; &#x27;S8&#x27;</div><input id='attrs-0c17742b-6ac2-4269-9a04-f957ddd07bfa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0c17742b-6ac2-4269-9a04-f957ddd07bfa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd83ad0e-a759-4618-b45f-c83fc36b8604' class='xr-var-data-in' type='checkbox'><label for='data-fd83ad0e-a759-4618-b45f-c83fc36b8604' 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;S1&#x27;, &#x27;S1&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S3&#x27;, &#x27;S3&#x27;, &#x27;S4&#x27;, &#x27;S4&#x27;, &#x27;S4&#x27;,\n",
       "       &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;, &#x27;S7&#x27;, &#x27;S7&#x27;, &#x27;S8&#x27;, &#x27;S8&#x27;,\n",
       "       &#x27;S8&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>detector</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;D2&#x27; &#x27;D3&#x27; &#x27;D1&#x27; ... &#x27;D7&#x27; &#x27;D8&#x27; &#x27;D16&#x27;</div><input id='attrs-5b6dab9c-46d8-47c0-913a-e287d85e735a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5b6dab9c-46d8-47c0-913a-e287d85e735a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-429c9ec3-e518-45c9-a486-40752e7e9d81' class='xr-var-data-in' type='checkbox'><label for='data-429c9ec3-e518-45c9-a486-40752e7e9d81' 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;D2&#x27;, &#x27;D3&#x27;, &#x27;D1&#x27;, &#x27;D3&#x27;, &#x27;D4&#x27;, &#x27;D10&#x27;, &#x27;D3&#x27;, &#x27;D11&#x27;, &#x27;D3&#x27;, &#x27;D4&#x27;,\n",
       "       &#x27;D12&#x27;, &#x27;D5&#x27;, &#x27;D6&#x27;, &#x27;D7&#x27;, &#x27;D13&#x27;, &#x27;D5&#x27;, &#x27;D7&#x27;, &#x27;D14&#x27;, &#x27;D7&#x27;, &#x27;D15&#x27;,\n",
       "       &#x27;D7&#x27;, &#x27;D8&#x27;, &#x27;D16&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>wavelength</span></div><div class='xr-var-dims'>(wavelength)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>760.0 850.0</div><input id='attrs-b28acd43-beac-422c-bb20-47943cebc70a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b28acd43-beac-422c-bb20-47943cebc70a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b49b0966-e29b-4113-a3f0-2611d1da25e7' class='xr-var-data-in' type='checkbox'><label for='data-b49b0966-e29b-4113-a3f0-2611d1da25e7' 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([760., 850.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6dee2d22-86a8-4fcd-83f0-55d062302bf1' class='xr-section-summary-in' type='checkbox'  ><label for='section-6dee2d22-86a8-4fcd-83f0-55d062302bf1' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e510151c-d96d-4d7a-941a-e713d757fdd9' class='xr-index-data-in' type='checkbox'/><label for='index-e510151c-d96d-4d7a-941a-e713d757fdd9' 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([     0.0,    0.128,    0.256,    0.384,    0.512,     0.64,    0.768,\n",
       "          0.896,    1.024,    1.152,\n",
       "       ...\n",
       "       2973.312,  2973.44, 2973.568, 2973.696, 2973.824, 2973.952,  2974.08,\n",
       "       2974.208, 2974.336, 2974.464],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;time&#x27;, length=23239))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>channel</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0883d144-522d-46ba-a2f0-6c3797682410' class='xr-index-data-in' type='checkbox'/><label for='index-0883d144-522d-46ba-a2f0-6c3797682410' 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([&#x27;S1D2&#x27;, &#x27;S1D3&#x27;, &#x27;S2D1&#x27;, &#x27;S2D3&#x27;, &#x27;S2D4&#x27;, &#x27;S2D10&#x27;, &#x27;S3D3&#x27;, &#x27;S3D11&#x27;,\n",
       "       &#x27;S4D3&#x27;, &#x27;S4D4&#x27;, &#x27;S4D12&#x27;, &#x27;S5D5&#x27;, &#x27;S5D6&#x27;, &#x27;S5D7&#x27;, &#x27;S5D13&#x27;, &#x27;S6D5&#x27;,\n",
       "       &#x27;S6D7&#x27;, &#x27;S6D14&#x27;, &#x27;S7D7&#x27;, &#x27;S7D15&#x27;, &#x27;S8D7&#x27;, &#x27;S8D8&#x27;, &#x27;S8D16&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>wavelength</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-05f55e34-7ccf-4883-93f2-d326cf423946' class='xr-index-data-in' type='checkbox'/><label for='index-05f55e34-7ccf-4883-93f2-d326cf423946' 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([760.0, 850.0], dtype=&#x27;float64&#x27;, name=&#x27;wavelength&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2f890569-737b-44fa-a246-5c74497da94d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2f890569-737b-44fa-a246-5c74497da94d' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>data_type_group :</span></dt><dd>unprocessed raw</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (channel: 23, wavelength: 2, time: 23239)> Size: 9MB\n",
       "<Quantity([[[0.227516  0.2297024 0.2261366 ... 0.2264519 0.2271665 0.226713 ]\n",
       "  [0.6354927 0.637668  0.6298023 ... 0.6072068 0.6087293 0.6091066]]\n",
       "\n",
       " [[0.1064704 0.1066212 0.1053444 ... 0.121114  0.1205022 0.1205441]\n",
       "  [0.2755033 0.2761615 0.2727006 ... 0.2911952 0.2900544 0.2909847]]\n",
       "\n",
       " [[0.5512474 0.5510672 0.5476283 ... 0.6179242 0.6188702 0.6187721]\n",
       "  [1.125532  1.1238331 1.1119423 ... 1.1817728 1.1819598 1.1832658]]\n",
       "\n",
       " ...\n",
       "\n",
       " [[0.2027881 0.1996586 0.2004866 ... 0.2318743 0.2311941 0.2330808]\n",
       "  [0.4666358 0.4554404 0.4561614 ... 0.4809749 0.4812827 0.4862896]]\n",
       "\n",
       " [[0.4885007 0.4802285 0.4818338 ... 0.6109142 0.6108118 0.613845 ]\n",
       "  [0.8457658 0.825988  0.8259648 ... 0.975894  0.9756599 0.9826459]]\n",
       "\n",
       " [[0.6304559 0.6284427 0.6287045 ... 0.6810626 0.6809573 0.6818709]\n",
       "  [1.2285622 1.2205907 1.2190002 ... 1.2729124 1.2727222 1.2755645]]], 'volt')>\n",
       "Coordinates:\n",
       "  * time        (time) float64 186kB 0.0 0.128 0.256 ... 2.974e+03 2.974e+03\n",
       "    samples     (time) int64 186kB 0 1 2 3 4 5 ... 23234 23235 23236 23237 23238\n",
       "  * channel     (channel) object 184B 'S1D2' 'S1D3' 'S2D1' ... 'S8D8' 'S8D16'\n",
       "    source      (channel) object 184B 'S1' 'S1' 'S2' 'S2' ... 'S8' 'S8' 'S8'\n",
       "    detector    (channel) object 184B 'D2' 'D3' 'D1' 'D3' ... 'D7' 'D8' 'D16'\n",
       "  * wavelength  (wavelength) float64 16B 760.0 850.0\n",
       "Attributes:\n",
       "    data_type_group:  unprocessed raw"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Here we assess average channel amplitudes. We might want to exclude very small or large signals\n",
    "amp_threshs = [0.1, 3]*units.volt # define whether a channel's amplitude is within a certain range\n",
    "\n",
    "# Amplitude thresholding\n",
    "mean_amp, amp_mask = quality.mean_amp(rec[\"amp\"], amp_threshs)\n",
    "\n",
    "# apply mask function. In this example, we want drop all channels that do not fall inside the amplitude thresholds. \n",
    "# We collapse to the \"channel\" dimension.\n",
    "data_masked_amp, masked_elements = xrutils.apply_mask(rec[\"amp\"], amp_mask, \"drop\", \"channel\")\n",
    "\n",
    "# display the results\n",
    "print(f\"channels that were masked according to the amplitude threshold: {masked_elements}\")\n",
    "data_masked_amp\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Channel Pruning using Quality Metrics and the Pruning Function\n",
    "\n",
    "To prune channels according to quality criteria, we do not have to manually go through the steps above. Instead, we can create quality masks for the metrics that we are interested in and hand them to a dedicated channel pruning function. The prune function expects a list of quality masks alongside a logical operator that defines how these masks should be combined."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T12:56:39.230523Z",
     "iopub.status.busy": "2025-04-14T12:56:39.230351Z",
     "iopub.status.idle": "2025-04-14T12:56:39.274190Z",
     "shell.execute_reply": "2025-04-14T12:56:39.273657Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "List of pruned channels: ['S1D1' 'S1D9' 'S2D10' 'S3D2' 'S3D11' 'S4D4' 'S4D12' 'S5D7' 'S5D13' 'S6D8'\n",
      " 'S6D14' 'S7D6' 'S7D15' 'S8D8' 'S8D16']\n"
     ]
    },
    {
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       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (channel: 13, wavelength: 2, time: 23239)&gt; Size: 5MB\n",
       "&lt;Quantity([[[0.227516  0.2297024 0.2261366 ... 0.2264519 0.2271665 0.226713 ]\n",
       "  [0.6354927 0.637668  0.6298023 ... 0.6072068 0.6087293 0.6091066]]\n",
       "\n",
       " [[0.1064704 0.1066212 0.1053444 ... 0.121114  0.1205022 0.1205441]\n",
       "  [0.2755033 0.2761615 0.2727006 ... 0.2911952 0.2900544 0.2909847]]\n",
       "\n",
       " [[0.5512474 0.5510672 0.5476283 ... 0.6179242 0.6188702 0.6187721]\n",
       "  [1.125532  1.1238331 1.1119423 ... 1.1817728 1.1819598 1.1832658]]\n",
       "\n",
       " ...\n",
       "\n",
       " [[0.3463254 0.3424951 0.3408207 ... 0.3929267 0.3941368 0.3945422]\n",
       "  [0.6978315 0.6875081 0.6857653 ... 0.7259991 0.7271688 0.7292138]]\n",
       "\n",
       " [[0.2225884 0.2187791 0.2195495 ... 0.2564863 0.2551258 0.2560233]\n",
       "  [0.3994258 0.3917637 0.389261  ... 0.4304597 0.430814  0.4331249]]\n",
       "\n",
       " [[0.2027881 0.1996586 0.2004866 ... 0.2318743 0.2311941 0.2330808]\n",
       "  [0.4666358 0.4554404 0.4561614 ... 0.4809749 0.4812827 0.4862896]]], &#x27;volt&#x27;)&gt;\n",
       "Coordinates:\n",
       "  * time        (time) float64 186kB 0.0 0.128 0.256 ... 2.974e+03 2.974e+03\n",
       "    samples     (time) int64 186kB 0 1 2 3 4 5 ... 23234 23235 23236 23237 23238\n",
       "  * channel     (channel) object 104B &#x27;S1D2&#x27; &#x27;S1D3&#x27; &#x27;S2D1&#x27; ... &#x27;S7D7&#x27; &#x27;S8D7&#x27;\n",
       "    source      (channel) object 104B &#x27;S1&#x27; &#x27;S1&#x27; &#x27;S2&#x27; &#x27;S2&#x27; ... &#x27;S6&#x27; &#x27;S7&#x27; &#x27;S8&#x27;\n",
       "    detector    (channel) object 104B &#x27;D2&#x27; &#x27;D3&#x27; &#x27;D1&#x27; &#x27;D3&#x27; ... &#x27;D7&#x27; &#x27;D7&#x27; &#x27;D7&#x27;\n",
       "  * wavelength  (wavelength) float64 16B 760.0 850.0\n",
       "Attributes:\n",
       "    data_type_group:  unprocessed raw</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 13</li><li><span class='xr-has-index'>wavelength</span>: 2</li><li><span class='xr-has-index'>time</span>: 23239</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-a71932a4-2f04-4450-98cd-ad71fdcae355' class='xr-array-in' type='checkbox' checked><label for='section-a71932a4-2f04-4450-98cd-ad71fdcae355' 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>[V] 0.2275 0.2297 0.2261 0.2259 0.2267 ... 0.4808 0.481 0.4813 0.4863</span></div><div class='xr-array-data'><table><tbody><tr><th>Magnitude</th><td style='text-align:left;'><pre>[[[0.227516 0.2297024 0.2261366 ... 0.2264519 0.2271665 0.226713]  [0.6354927 0.637668 0.6298023 ... 0.6072068 0.6087293 0.6091066]] [[0.1064704 0.1066212 0.1053444 ... 0.121114 0.1205022 0.1205441]  [0.2755033 0.2761615 0.2727006 ... 0.2911952 0.2900544 0.2909847]] [[0.5512474 0.5510672 0.5476283 ... 0.6179242 0.6188702 0.6187721]  [1.125532 1.1238331 1.1119423 ... 1.1817728 1.1819598 1.1832658]] ... [[0.3463254 0.3424951 0.3408207 ... 0.3929267 0.3941368 0.3945422]  [0.6978315 0.6875081 0.6857653 ... 0.7259991 0.7271688 0.7292138]] [[0.2225884 0.2187791 0.2195495 ... 0.2564863 0.2551258 0.2560233]  [0.3994258 0.3917637 0.389261 ... 0.4304597 0.430814 0.4331249]] [[0.2027881 0.1996586 0.2004866 ... 0.2318743 0.2311941 0.2330808]  [0.4666358 0.4554404 0.4561614 ... 0.4809749 0.4812827 0.4862896]]]</pre></td></tr><tr><th>Units</th><td style='text-align:left;'>volt</td></tr></tbody></table></div></div></li><li class='xr-section-item'><input id='section-ce2a3824-299b-45c8-ab1c-4b08b447e0f2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ce2a3824-299b-45c8-ab1c-4b08b447e0f2' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.128 ... 2.974e+03 2.974e+03</div><input id='attrs-8e9ac5fe-5f9d-4ab3-a0d9-eb3a59865369' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e9ac5fe-5f9d-4ab3-a0d9-eb3a59865369' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78e3c02b-4fa5-4943-a7ee-2a0ef67545e5' class='xr-var-data-in' type='checkbox'><label for='data-78e3c02b-4fa5-4943-a7ee-2a0ef67545e5' 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>second</dd></dl></div><div class='xr-var-data'><pre>array([0.000000e+00, 1.280000e-01, 2.560000e-01, ..., 2.974208e+03,\n",
       "       2.974336e+03, 2.974464e+03])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>samples</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 ... 23235 23236 23237 23238</div><input id='attrs-c1fae128-7b3a-483e-bfda-f775cd1eb56a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c1fae128-7b3a-483e-bfda-f775cd1eb56a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40385163-9b1c-4e2f-b50a-cb143a9235b3' class='xr-var-data-in' type='checkbox'><label for='data-40385163-9b1c-4e2f-b50a-cb143a9235b3' 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, ..., 23236, 23237, 23238])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;S1D2&#x27; &#x27;S1D3&#x27; ... &#x27;S7D7&#x27; &#x27;S8D7&#x27;</div><input id='attrs-bac9c483-dd26-40d8-a7d9-fa443d2b61e1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bac9c483-dd26-40d8-a7d9-fa443d2b61e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b084aa64-34d2-4e3f-812a-ea706274691c' class='xr-var-data-in' type='checkbox'><label for='data-b084aa64-34d2-4e3f-812a-ea706274691c' 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;S1D2&#x27;, &#x27;S1D3&#x27;, &#x27;S2D1&#x27;, &#x27;S2D3&#x27;, &#x27;S2D4&#x27;, &#x27;S3D3&#x27;, &#x27;S4D3&#x27;, &#x27;S5D5&#x27;, &#x27;S5D6&#x27;,\n",
       "       &#x27;S6D5&#x27;, &#x27;S6D7&#x27;, &#x27;S7D7&#x27;, &#x27;S8D7&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;S1&#x27; &#x27;S1&#x27; &#x27;S2&#x27; ... &#x27;S6&#x27; &#x27;S7&#x27; &#x27;S8&#x27;</div><input id='attrs-728cf46b-aa7f-4f7b-960b-d285788e621f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-728cf46b-aa7f-4f7b-960b-d285788e621f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d33bc91a-0322-475d-a8b5-7bfa0ae51a63' class='xr-var-data-in' type='checkbox'><label for='data-d33bc91a-0322-475d-a8b5-7bfa0ae51a63' 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;S1&#x27;, &#x27;S1&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S2&#x27;, &#x27;S3&#x27;, &#x27;S4&#x27;, &#x27;S5&#x27;, &#x27;S5&#x27;, &#x27;S6&#x27;, &#x27;S6&#x27;,\n",
       "       &#x27;S7&#x27;, &#x27;S8&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>detector</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;D2&#x27; &#x27;D3&#x27; &#x27;D1&#x27; ... &#x27;D7&#x27; &#x27;D7&#x27; &#x27;D7&#x27;</div><input id='attrs-b17479e6-daf1-4bda-b680-4246dc3af7ab' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b17479e6-daf1-4bda-b680-4246dc3af7ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-443c24fb-c88a-4e8c-91e5-e2a8abdee292' class='xr-var-data-in' type='checkbox'><label for='data-443c24fb-c88a-4e8c-91e5-e2a8abdee292' 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;D2&#x27;, &#x27;D3&#x27;, &#x27;D1&#x27;, &#x27;D3&#x27;, &#x27;D4&#x27;, &#x27;D3&#x27;, &#x27;D3&#x27;, &#x27;D5&#x27;, &#x27;D6&#x27;, &#x27;D5&#x27;, &#x27;D7&#x27;,\n",
       "       &#x27;D7&#x27;, &#x27;D7&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>wavelength</span></div><div class='xr-var-dims'>(wavelength)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>760.0 850.0</div><input id='attrs-5c16555b-b9b9-47cd-a000-868501152d60' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5c16555b-b9b9-47cd-a000-868501152d60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-74d28495-4d6f-4d87-8fd7-ec5283778486' class='xr-var-data-in' type='checkbox'><label for='data-74d28495-4d6f-4d87-8fd7-ec5283778486' 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([760., 850.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-05cbd976-388c-4871-b44f-7e0d4cefe078' class='xr-section-summary-in' type='checkbox'  ><label for='section-05cbd976-388c-4871-b44f-7e0d4cefe078' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cb1189b1-df7f-4bce-8dbf-97c771e1cd0d' class='xr-index-data-in' type='checkbox'/><label for='index-cb1189b1-df7f-4bce-8dbf-97c771e1cd0d' 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([     0.0,    0.128,    0.256,    0.384,    0.512,     0.64,    0.768,\n",
       "          0.896,    1.024,    1.152,\n",
       "       ...\n",
       "       2973.312,  2973.44, 2973.568, 2973.696, 2973.824, 2973.952,  2974.08,\n",
       "       2974.208, 2974.336, 2974.464],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;time&#x27;, length=23239))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>channel</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1f6babf7-1340-4452-9a1e-a00ad92dcc2b' class='xr-index-data-in' type='checkbox'/><label for='index-1f6babf7-1340-4452-9a1e-a00ad92dcc2b' 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([&#x27;S1D2&#x27;, &#x27;S1D3&#x27;, &#x27;S2D1&#x27;, &#x27;S2D3&#x27;, &#x27;S2D4&#x27;, &#x27;S3D3&#x27;, &#x27;S4D3&#x27;, &#x27;S5D5&#x27;, &#x27;S5D6&#x27;,\n",
       "       &#x27;S6D5&#x27;, &#x27;S6D7&#x27;, &#x27;S7D7&#x27;, &#x27;S8D7&#x27;],\n",
       "      dtype=&#x27;object&#x27;, name=&#x27;channel&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>wavelength</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-458affc1-b836-4369-ba83-5e17b8434b4a' class='xr-index-data-in' type='checkbox'/><label for='index-458affc1-b836-4369-ba83-5e17b8434b4a' 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([760.0, 850.0], dtype=&#x27;float64&#x27;, name=&#x27;wavelength&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5009bcfd-824d-4235-a40d-af7735c2bccb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5009bcfd-824d-4235-a40d-af7735c2bccb' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>data_type_group :</span></dt><dd>unprocessed raw</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (channel: 13, wavelength: 2, time: 23239)> Size: 5MB\n",
       "<Quantity([[[0.227516  0.2297024 0.2261366 ... 0.2264519 0.2271665 0.226713 ]\n",
       "  [0.6354927 0.637668  0.6298023 ... 0.6072068 0.6087293 0.6091066]]\n",
       "\n",
       " [[0.1064704 0.1066212 0.1053444 ... 0.121114  0.1205022 0.1205441]\n",
       "  [0.2755033 0.2761615 0.2727006 ... 0.2911952 0.2900544 0.2909847]]\n",
       "\n",
       " [[0.5512474 0.5510672 0.5476283 ... 0.6179242 0.6188702 0.6187721]\n",
       "  [1.125532  1.1238331 1.1119423 ... 1.1817728 1.1819598 1.1832658]]\n",
       "\n",
       " ...\n",
       "\n",
       " [[0.3463254 0.3424951 0.3408207 ... 0.3929267 0.3941368 0.3945422]\n",
       "  [0.6978315 0.6875081 0.6857653 ... 0.7259991 0.7271688 0.7292138]]\n",
       "\n",
       " [[0.2225884 0.2187791 0.2195495 ... 0.2564863 0.2551258 0.2560233]\n",
       "  [0.3994258 0.3917637 0.389261  ... 0.4304597 0.430814  0.4331249]]\n",
       "\n",
       " [[0.2027881 0.1996586 0.2004866 ... 0.2318743 0.2311941 0.2330808]\n",
       "  [0.4666358 0.4554404 0.4561614 ... 0.4809749 0.4812827 0.4862896]]], 'volt')>\n",
       "Coordinates:\n",
       "  * time        (time) float64 186kB 0.0 0.128 0.256 ... 2.974e+03 2.974e+03\n",
       "    samples     (time) int64 186kB 0 1 2 3 4 5 ... 23234 23235 23236 23237 23238\n",
       "  * channel     (channel) object 104B 'S1D2' 'S1D3' 'S2D1' ... 'S7D7' 'S8D7'\n",
       "    source      (channel) object 104B 'S1' 'S1' 'S2' 'S2' ... 'S6' 'S7' 'S8'\n",
       "    detector    (channel) object 104B 'D2' 'D3' 'D1' 'D3' ... 'D7' 'D7' 'D7'\n",
       "  * wavelength  (wavelength) float64 16B 760.0 850.0\n",
       "Attributes:\n",
       "    data_type_group:  unprocessed raw"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# as above we use three metrics and define thresholds accordingly\n",
    "snr_thresh = 16 # the SNR (std/mean) of a channel. \n",
    "sd_threshs = [1, 4.5]*units.cm # defines the lower and upper bounds for the source-detector separation that we would like to keep\n",
    "amp_threshs = [0.1, 3]*units.volt # define whether a channel's amplitude is within a certain range\n",
    "\n",
    "# then we calculate the masks for each metric: SNR, SD distance and mean amplitude\n",
    "_, snr_mask = quality.snr(rec[\"amp\"], snr_thresh)\n",
    "_, sd_mask = quality.sd_dist(rec[\"amp\"], rec.geo3d, sd_threshs)\n",
    "_, amp_mask = quality.mean_amp(rec[\"amp\"], amp_threshs)\n",
    "# you can also include other masks, e.g. the SCI mask\n",
    "\n",
    "# put all masks in a list\n",
    "masks = [snr_mask, sd_mask, amp_mask]\n",
    "\n",
    "# prune channels using the masks and the operator \"all\", which will keep only channels that pass all three metrics\n",
    "amp_pruned, drop_list = quality.prune_ch(rec[\"amp\"], masks, \"all\")\n",
    "\n",
    "# print list of dropped channels\n",
    "print(f\"List of pruned channels: {drop_list}\")\n",
    "# display the new data xarray\n",
    "amp_pruned"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Timeseries Quality Metric: Global Variance of the Temporal Derivative"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T12:56:39.276344Z",
     "iopub.status.busy": "2025-04-14T12:56:39.276025Z",
     "iopub.status.idle": "2025-04-14T12:56:39.563344Z",
     "shell.execute_reply": "2025-04-14T12:56:39.562779Z"
    },
    "tags": [
     "nbsphinx-thumbnail"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# we can plot the timeseries of the GVTD to evaluate motion in the data\n",
    "gvtd, gvtd_mask = quality.gvtd(rec[\"amp\"], stat_type=\"histogram_mode\")\n",
    "\n",
    "f, ax = p.subplots(2,1, figsize=(12,4), sharex=True)\n",
    "ax[0].plot(gvtd.time, gvtd)\n",
    "ax[1].plot(gvtd.time, gvtd_mask)\n",
    "ax[0].set_xlabel(\"time / s\")\n",
    "ax[0].set_ylabel(\"GVTD / $s^{-1}$\")\n",
    "ax[1].set_ylabel(\"GVTD mask\")\n",
    "ax[1].set_yticks([0,1])\n",
    "ax[1].set_yticklabels([\"TAINTED\",\"CLEAN\"])\n",
    "ax[0].set_xlim(0, 250)\n",
    "ax[0].grid()\n",
    "ax[1].grid()\n",
    "f.suptitle(\"Global Variance of Temporal Derivative\")\n",
    "p.tight_layout()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "cedalion_default_3.11",
   "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": "3.11.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}