diff --git a/notebook/Virtual spectrometer SCS Grating.ipynb b/notebook/Virtual spectrometer SCS Grating.ipynb
index 87a4fdfaf9f62642b251beca4cdcf9dbefe45763..ba7cae38817f856ab0fb0c4c3076a74a2834252d 100644
--- a/notebook/Virtual spectrometer SCS Grating.ipynb
+++ b/notebook/Virtual spectrometer SCS Grating.ipynb
@@ -76,12 +76,12 @@
"id": "c7609899-5bc0-4211-ae97-010b3edcf676",
"metadata": {},
"source": [
- "## Get data"
+ "# Training:"
]
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": 94,
"id": "95da5231-e454-4f7f-a1ce-eef7e52fe457",
"metadata": {},
"outputs": [],
@@ -108,7 +108,7 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 95,
"id": "fd8dacae-c22e-4c20-9df9-8720a2814320",
"metadata": {},
"outputs": [],
@@ -119,7 +119,7 @@
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": 96,
"id": "25000b87-246d-467b-b770-8cde527faec4",
"metadata": {},
"outputs": [
@@ -154,7 +154,7 @@
},
{
"cell_type": "code",
- "execution_count": 26,
+ "execution_count": 97,
"id": "294b5f3a-1d59-444e-80ab-4834d26d62dc",
"metadata": {},
"outputs": [],
@@ -167,7 +167,7 @@
},
{
"cell_type": "code",
- "execution_count": 27,
+ "execution_count": 98,
"id": "b477bf49-f5ca-4df0-b6ed-a270ee35cd28",
"metadata": {},
"outputs": [],
@@ -177,7 +177,7 @@
},
{
"cell_type": "code",
- "execution_count": 28,
+ "execution_count": 99,
"id": "a843e981-e57e-4163-a4e0-310de7181aec",
"metadata": {},
"outputs": [
@@ -569,86 +569,86 @@
" bunchPatternTable (trainId, pulse_slot) uint32 2146089 0 ... 16777216\n",
" XTD10_SA3 (trainId, sa3_pId) float32 1.217e+03 ... 1.489e+03\n",
"Attributes:\n",
- " runFolder: /gpfs/exfel/exp/SA3/202330/p900331/raw/r0069</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-0b7c564a-c8ac-49f2-8371-a3b66e4e7362' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0b7c564a-c8ac-49f2-8371-a3b66e4e7362' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>trainId</span>: 7165</li><li><span>PESsampleId</span>: 40000</li><li><span>gratingEnergy</span>: 1800</li><li><span>pulse_slot</span>: 2700</li><li><span class='xr-has-index'>sa3_pId</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-99d8ee8f-922b-4296-ac08-f9d4d4c23d22' class='xr-section-summary-in' type='checkbox' checked><label for='section-99d8ee8f-922b-4296-ac08-f9d4d4c23d22' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>trainId</span></div><div class='xr-var-dims'>(trainId)</div><div class='xr-var-dtype'>uint64</div><div class='xr-var-preview xr-preview'>1724088331 ... 1724098301</div><input id='attrs-26337ad6-da4a-4fe7-9857-e8917bc5ca03' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-26337ad6-da4a-4fe7-9857-e8917bc5ca03' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb81e4b4-50f2-44bc-b9a9-515ca00ab730' class='xr-var-data-in' type='checkbox'><label for='data-fb81e4b4-50f2-44bc-b9a9-515ca00ab730' 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([1724088331, 1724088332, 1724088333, ..., 1724098299, 1724098300,\n",
- " 1724098301], dtype=uint64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>sa3_pId</span></div><div class='xr-var-dims'>(sa3_pId)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1326</div><input id='attrs-ba3ebda4-2a27-4332-9d41-6c26a3be0b02' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ba3ebda4-2a27-4332-9d41-6c26a3be0b02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-edc72482-3ff4-47fe-a649-a4ed63f57457' class='xr-var-data-in' type='checkbox'><label for='data-edc72482-3ff4-47fe-a649-a4ed63f57457' 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([1326])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-150a75b4-825e-42e9-a5d2-db83c8848a93' class='xr-section-summary-in' type='checkbox' ><label for='section-150a75b4-825e-42e9-a5d2-db83c8848a93' class='xr-section-summary' >Data variables: <span>(16)</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>PES_S_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-1 0 -2 0 -2 2 -2 ... 2 4 -1 1 1 1</div><input id='attrs-cbcef525-b7a4-4bc2-ab6a-384f7eb0f86f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cbcef525-b7a4-4bc2-ab6a-384f7eb0f86f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fbd0efa6-d334-4547-a256-6b96e26a41f8' class='xr-var-data-in' type='checkbox'><label for='data-fbd0efa6-d334-4547-a256-6b96e26a41f8' 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([[-1, 0, -2, ..., 1, -4, -1],\n",
+ " runFolder: /gpfs/exfel/exp/SA3/202330/p900331/raw/r0069</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-c0d8f1a0-ed73-44cb-b5f3-bb70d3f7ae4a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c0d8f1a0-ed73-44cb-b5f3-bb70d3f7ae4a' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>trainId</span>: 7165</li><li><span>PESsampleId</span>: 40000</li><li><span>gratingEnergy</span>: 1800</li><li><span>pulse_slot</span>: 2700</li><li><span class='xr-has-index'>sa3_pId</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-5d194e5e-8ecd-478d-9dbe-4d7477264d53' class='xr-section-summary-in' type='checkbox' checked><label for='section-5d194e5e-8ecd-478d-9dbe-4d7477264d53' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>trainId</span></div><div class='xr-var-dims'>(trainId)</div><div class='xr-var-dtype'>uint64</div><div class='xr-var-preview xr-preview'>1724088331 ... 1724098301</div><input id='attrs-e9370e29-22ae-4ca9-b2e8-6a009e19e08e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e9370e29-22ae-4ca9-b2e8-6a009e19e08e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c01674f7-8907-4f18-b023-154637c3da5e' class='xr-var-data-in' type='checkbox'><label for='data-c01674f7-8907-4f18-b023-154637c3da5e' 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([1724088331, 1724088332, 1724088333, ..., 1724098299, 1724098300,\n",
+ " 1724098301], dtype=uint64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>sa3_pId</span></div><div class='xr-var-dims'>(sa3_pId)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1326</div><input id='attrs-d392100b-e682-4fea-ac1f-4f968853c198' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d392100b-e682-4fea-ac1f-4f968853c198' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a587bd2-ad39-498b-84f1-f903196d60c5' class='xr-var-data-in' type='checkbox'><label for='data-0a587bd2-ad39-498b-84f1-f903196d60c5' 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([1326])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-630922cc-893b-4e0e-afd2-59b14956e040' class='xr-section-summary-in' type='checkbox' ><label for='section-630922cc-893b-4e0e-afd2-59b14956e040' class='xr-section-summary' >Data variables: <span>(16)</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>PES_S_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-1 0 -2 0 -2 2 -2 ... 2 4 -1 1 1 1</div><input id='attrs-1b160e67-1142-4928-9646-5cae518e3e86' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1b160e67-1142-4928-9646-5cae518e3e86' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f17bd3c-d3a9-44aa-8ae0-cfac5c3bbfe8' class='xr-var-data-in' type='checkbox'><label for='data-8f17bd3c-d3a9-44aa-8ae0-cfac5c3bbfe8' 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([[-1, 0, -2, ..., 1, -4, -1],\n",
" [ 0, 4, 0, ..., 2, 1, 1],\n",
" [ 1, -1, -1, ..., 3, 1, 3],\n",
" ...,\n",
" [-2, 2, 0, ..., 1, 1, 4],\n",
" [ 0, 4, 0, ..., 3, -1, 3],\n",
- " [-2, 4, 0, ..., 1, 1, 1]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_SSW_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-4 -3 -4 -2 -4 -2 ... -2 -3 -2 0 -4</div><input id='attrs-1ab5e4ea-5a6f-4a54-ae7a-61d3ae476984' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1ab5e4ea-5a6f-4a54-ae7a-61d3ae476984' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a40be4b-8c69-4ccf-a649-60a8a88caa0b' class='xr-var-data-in' type='checkbox'><label for='data-2a40be4b-8c69-4ccf-a649-60a8a88caa0b' 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([[-4, -3, -4, ..., -4, 0, -2],\n",
+ " [-2, 4, 0, ..., 1, 1, 1]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_SSW_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-4 -3 -4 -2 -4 -2 ... -2 -3 -2 0 -4</div><input id='attrs-0eb4353e-c43e-457e-9d98-6aef7229254a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0eb4353e-c43e-457e-9d98-6aef7229254a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81a19f18-f2f7-4458-987b-d47fbc8c74b0' class='xr-var-data-in' type='checkbox'><label for='data-81a19f18-f2f7-4458-987b-d47fbc8c74b0' 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([[-4, -3, -4, ..., -4, 0, -2],\n",
" [-7, -1, -2, ..., 0, -5, 0],\n",
" [-1, -3, -1, ..., -2, -4, -1],\n",
" ...,\n",
" [-5, -2, -4, ..., -2, -5, -3],\n",
" [-1, -3, -4, ..., 2, 0, -1],\n",
- " [-3, -2, -5, ..., -2, 0, -4]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_SW_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-3 -8 -5 -5 -7 ... -6 -7 -5 -8 -5</div><input id='attrs-5ed1ceb9-5974-4df4-b803-c251eea06bd5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5ed1ceb9-5974-4df4-b803-c251eea06bd5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9024bfb6-7b6d-4ae9-9eac-eebc3e5400ad' class='xr-var-data-in' type='checkbox'><label for='data-9024bfb6-7b6d-4ae9-9eac-eebc3e5400ad' 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([[ -3, -8, -5, ..., -10, -5, -10],\n",
+ " [-3, -2, -5, ..., -2, 0, -4]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_SW_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-3 -8 -5 -5 -7 ... -6 -7 -5 -8 -5</div><input id='attrs-bd481fe4-a20c-4339-b27e-ef9a16603761' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bd481fe4-a20c-4339-b27e-ef9a16603761' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f384c63a-715f-4cc1-b7f6-801ba704a4bc' class='xr-var-data-in' type='checkbox'><label for='data-f384c63a-715f-4cc1-b7f6-801ba704a4bc' 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([[ -3, -8, -5, ..., -10, -5, -10],\n",
" [ -6, -4, -7, ..., -5, -8, -5],\n",
" [ -6, -7, -7, ..., -6, -7, -8],\n",
" ...,\n",
" [ -6, -7, -3, ..., -4, -4, -6],\n",
" [ -8, -5, -9, ..., -9, -6, -4],\n",
- " [ -7, -5, -9, ..., -5, -8, -5]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_WSW_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-4 -6 -4 -5 -5 -3 ... -5 -5 -3 -4 0</div><input id='attrs-877ecb9a-ea20-4714-a187-8bc22c57f883' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-877ecb9a-ea20-4714-a187-8bc22c57f883' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e918a451-58c7-41e1-afea-84067173464e' class='xr-var-data-in' type='checkbox'><label for='data-e918a451-58c7-41e1-afea-84067173464e' 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([[-4, -6, -4, ..., -7, -5, -7],\n",
+ " [ -7, -5, -9, ..., -5, -8, -5]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_WSW_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-4 -6 -4 -5 -5 -3 ... -5 -5 -3 -4 0</div><input id='attrs-67312d48-4b5c-406b-83da-1138aacc0290' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-67312d48-4b5c-406b-83da-1138aacc0290' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-622f828e-ab69-4b0a-9d05-07055d45633c' class='xr-var-data-in' type='checkbox'><label for='data-622f828e-ab69-4b0a-9d05-07055d45633c' 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([[-4, -6, -4, ..., -7, -5, -7],\n",
" [-2, -4, -3, ..., -6, -3, -2],\n",
" [-3, -3, -3, ..., -4, -5, -3],\n",
" ...,\n",
" [-8, -5, -5, ..., -4, -5, -4],\n",
" [-5, -4, -3, ..., -3, -5, -3],\n",
- " [-3, -5, -6, ..., -3, -4, 0]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_E_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-6 -3 -5 -8 -7 ... -4 -6 -2 -4 -6</div><input id='attrs-467b5b92-dc47-4d8d-aeaf-a51170fc2092' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-467b5b92-dc47-4d8d-aeaf-a51170fc2092' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f315ebb-6e84-445e-af7a-189d0b36652c' class='xr-var-data-in' type='checkbox'><label for='data-7f315ebb-6e84-445e-af7a-189d0b36652c' 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([[-6, -3, -5, ..., -7, -8, -4],\n",
+ " [-3, -5, -6, ..., -3, -4, 0]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_E_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-6 -3 -5 -8 -7 ... -4 -6 -2 -4 -6</div><input id='attrs-7348678a-415b-4429-adec-308629d6bfbf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7348678a-415b-4429-adec-308629d6bfbf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0eb0ceb8-094e-464e-b8cd-27d21a03c170' class='xr-var-data-in' type='checkbox'><label for='data-0eb0ceb8-094e-464e-b8cd-27d21a03c170' 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([[-6, -3, -5, ..., -7, -8, -4],\n",
" [-8, -5, -8, ..., -7, -4, -5],\n",
" [-6, -4, -5, ..., -6, -7, -3],\n",
" ...,\n",
" [-6, -5, -9, ..., -5, -7, -5],\n",
" [-6, -5, -7, ..., -6, -9, -6],\n",
- " [-5, -3, -7, ..., -2, -4, -6]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_ESE_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-11 -13 -10 -11 ... -11 -10 -10 -12</div><input id='attrs-30b2a9c8-baf5-44b2-9331-210630fc5f32' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-30b2a9c8-baf5-44b2-9331-210630fc5f32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0f93ad5-335d-42cc-937a-58a6fa14571b' class='xr-var-data-in' type='checkbox'><label for='data-f0f93ad5-335d-42cc-937a-58a6fa14571b' 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([[-11, -13, -10, ..., -12, -13, -9],\n",
+ " [-5, -3, -7, ..., -2, -4, -6]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_ESE_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-11 -13 -10 -11 ... -11 -10 -10 -12</div><input id='attrs-0b4e4269-6988-463c-9354-8fc17a601ef3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0b4e4269-6988-463c-9354-8fc17a601ef3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e9db708-bb09-432f-87ca-da1183f644d2' class='xr-var-data-in' type='checkbox'><label for='data-5e9db708-bb09-432f-87ca-da1183f644d2' 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([[-11, -13, -10, ..., -12, -13, -9],\n",
" [ -8, -10, -13, ..., -12, -9, -9],\n",
" [-12, -12, -11, ..., -10, -9, -11],\n",
" ...,\n",
" [-13, -12, -10, ..., -10, -13, -11],\n",
" [-11, -12, -9, ..., -9, -11, -10],\n",
- " [-12, -10, -8, ..., -10, -10, -12]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_SE_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-7 -3 -8 -2 -3 -2 ... 1 -6 -4 -4 -5</div><input id='attrs-f05e6f41-5689-4146-afa0-902864cbb700' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f05e6f41-5689-4146-afa0-902864cbb700' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e3d9aa7-6d95-4d95-8920-4fe57c6e1824' class='xr-var-data-in' type='checkbox'><label for='data-7e3d9aa7-6d95-4d95-8920-4fe57c6e1824' 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([[-7, -3, -8, ..., -3, -7, -2],\n",
+ " [-12, -10, -8, ..., -10, -10, -12]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_SE_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-7 -3 -8 -2 -3 -2 ... 1 -6 -4 -4 -5</div><input id='attrs-7955c2ed-1418-42bb-9d21-bc8166fd3acf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7955c2ed-1418-42bb-9d21-bc8166fd3acf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-660b8721-305e-4654-8aa3-83a25bdc8424' class='xr-var-data-in' type='checkbox'><label for='data-660b8721-305e-4654-8aa3-83a25bdc8424' 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([[-7, -3, -8, ..., -3, -7, -2],\n",
" [-6, -4, -9, ..., -6, -5, -2],\n",
" [-7, -5, -6, ..., -1, -8, -5],\n",
" ...,\n",
" [-1, -2, -7, ..., -3, -3, -2],\n",
" [-5, -6, -6, ..., -4, -8, -4],\n",
- " [-6, -2, -4, ..., -4, -4, -5]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_SSE_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-13 -14 -14 -13 ... -13 -15 -14 -11</div><input id='attrs-d3190eb4-d829-4c81-9229-39d5aa6aa3e6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d3190eb4-d829-4c81-9229-39d5aa6aa3e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60c5011e-12b2-4606-996b-f4bb2b3627c0' class='xr-var-data-in' type='checkbox'><label for='data-60c5011e-12b2-4606-996b-f4bb2b3627c0' 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([[-13, -14, -14, ..., -14, -13, -16],\n",
+ " [-6, -2, -4, ..., -4, -4, -5]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_SSE_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-13 -14 -14 -13 ... -13 -15 -14 -11</div><input id='attrs-4c63187f-b47b-4df3-aae7-90431566007f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4c63187f-b47b-4df3-aae7-90431566007f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a54b342-dad3-467a-aad5-d662e7975db4' class='xr-var-data-in' type='checkbox'><label for='data-5a54b342-dad3-467a-aad5-d662e7975db4' 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([[-13, -14, -14, ..., -14, -13, -16],\n",
" [-12, -15, -15, ..., -12, -15, -14],\n",
" [-14, -13, -14, ..., -14, -14, -15],\n",
" ...,\n",
" [-11, -10, -13, ..., -14, -10, -13],\n",
" [-12, -14, -11, ..., -9, -14, -13],\n",
- " [-12, -15, -14, ..., -15, -14, -11]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_N_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-10 -9 -9 -10 -8 ... -11 -9 -9 -9</div><input id='attrs-205f537c-9ba4-46fa-8590-40ba07b48eef' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-205f537c-9ba4-46fa-8590-40ba07b48eef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9312925-7a1b-4e40-a683-b294418fcba4' class='xr-var-data-in' type='checkbox'><label for='data-c9312925-7a1b-4e40-a683-b294418fcba4' 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([[-10, -9, -9, ..., -11, -9, -12],\n",
+ " [-12, -15, -14, ..., -15, -14, -11]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_N_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-10 -9 -9 -10 -8 ... -11 -9 -9 -9</div><input id='attrs-d2c62c73-5eb1-4e55-86a6-161f8656f3a0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d2c62c73-5eb1-4e55-86a6-161f8656f3a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64c6b108-1c71-437e-a79a-9ed38054a411' class='xr-var-data-in' type='checkbox'><label for='data-64c6b108-1c71-437e-a79a-9ed38054a411' 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([[-10, -9, -9, ..., -11, -9, -12],\n",
" [ -9, -12, -10, ..., -10, -11, -10],\n",
" [ -9, -10, -8, ..., -11, -11, -10],\n",
" ...,\n",
" [-12, -11, -11, ..., -12, -12, -10],\n",
" [-10, -14, -10, ..., -8, -10, -11],\n",
- " [-11, -9, -11, ..., -9, -9, -9]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_NNE_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-8 -9 -7 -10 -9 ... -8 -8 -8 -7 -8</div><input id='attrs-4694138d-087e-4913-b2da-3322e6f1f47a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4694138d-087e-4913-b2da-3322e6f1f47a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc5372bf-ad21-46e3-bc8a-11e684104565' class='xr-var-data-in' type='checkbox'><label for='data-bc5372bf-ad21-46e3-bc8a-11e684104565' 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([[ -8, -9, -7, ..., -6, -6, -10],\n",
+ " [-11, -9, -11, ..., -9, -9, -9]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_NNE_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-8 -9 -7 -10 -9 ... -8 -8 -8 -7 -8</div><input id='attrs-539238b3-75f1-44e7-997a-b4d6d224edba' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-539238b3-75f1-44e7-997a-b4d6d224edba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-858c8bb7-5b60-4b41-ae20-4a69c9acae38' class='xr-var-data-in' type='checkbox'><label for='data-858c8bb7-5b60-4b41-ae20-4a69c9acae38' 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([[ -8, -9, -7, ..., -6, -6, -10],\n",
" [ -6, -6, -8, ..., -9, -6, -6],\n",
" [ -8, -10, -9, ..., -6, -7, -8],\n",
" ...,\n",
" [ -7, -8, -7, ..., -9, -7, -7],\n",
" [ -7, -9, -7, ..., -7, -6, -9],\n",
- " [ -7, -9, -8, ..., -8, -7, -8]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_NE_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-2 -5 -2 -4 -1 -2 ... 2 0 -2 2 -3</div><input id='attrs-8faa1bc5-58ee-445f-8a34-92d85402c33f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8faa1bc5-58ee-445f-8a34-92d85402c33f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-862e54d0-e308-4d1d-b900-e76147988d99' class='xr-var-data-in' type='checkbox'><label for='data-862e54d0-e308-4d1d-b900-e76147988d99' 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([[-2, -5, -2, ..., -3, -1, -5],\n",
+ " [ -7, -9, -8, ..., -8, -7, -8]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_NE_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-2 -5 -2 -4 -1 -2 ... 2 0 -2 2 -3</div><input id='attrs-6879833f-9e04-4138-ac53-3aaa159144e0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6879833f-9e04-4138-ac53-3aaa159144e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02b7f534-e2b8-4088-ae59-a19c5d1d2610' class='xr-var-data-in' type='checkbox'><label for='data-02b7f534-e2b8-4088-ae59-a19c5d1d2610' 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([[-2, -5, -2, ..., -3, -1, -5],\n",
" [-1, -2, -2, ..., -2, -2, -5],\n",
" [ 1, -2, -3, ..., -4, -5, -4],\n",
" ...,\n",
" [-2, -1, -1, ..., -4, -2, -6],\n",
" [ 0, -9, 0, ..., -1, 0, -4],\n",
- " [-3, -3, -4, ..., -2, 2, -3]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_ENE_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-4 -3 -2 -3 -3 ... -3 -5 -2 -3 -5</div><input id='attrs-7a1359d6-bcac-4112-8bb1-9c01bc0b0087' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7a1359d6-bcac-4112-8bb1-9c01bc0b0087' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-324bef15-3a74-405a-a546-543bc665b7ae' class='xr-var-data-in' type='checkbox'><label for='data-324bef15-3a74-405a-a546-543bc665b7ae' 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([[-4, -3, -2, ..., -4, -2, -3],\n",
+ " [-3, -3, -4, ..., -2, 2, -3]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PES_ENE_raw</span></div><div class='xr-var-dims'>(trainId, PESsampleId)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>-4 -3 -2 -3 -3 ... -3 -5 -2 -3 -5</div><input id='attrs-12734d04-56b8-4847-9d81-715753faa654' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-12734d04-56b8-4847-9d81-715753faa654' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c07310a5-26b4-4411-8323-5e3bb3169ef5' class='xr-var-data-in' type='checkbox'><label for='data-c07310a5-26b4-4411-8323-5e3bb3169ef5' 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([[-4, -3, -2, ..., -4, -2, -3],\n",
" [-4, -5, -3, ..., -1, -3, 2],\n",
" [-1, -2, -5, ..., -4, -3, -1],\n",
" ...,\n",
" [-5, -2, -4, ..., -2, 0, -1],\n",
" [-2, -2, -4, ..., -6, -4, -2],\n",
- " [-3, -3, -5, ..., -2, -3, -5]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>navitar</span></div><div class='xr-var-dims'>(trainId, gratingEnergy)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>12.22 11.29 10.78 ... 13.06 12.46</div><input id='attrs-cbce4d74-2386-44f0-b28d-99fb8579c29c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cbce4d74-2386-44f0-b28d-99fb8579c29c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ffec1eb-9200-4e81-a7d6-a5af7a5cdc25' class='xr-var-data-in' type='checkbox'><label for='data-2ffec1eb-9200-4e81-a7d6-a5af7a5cdc25' 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([[12.22 , 11.2875, 10.78 , ..., 12.105 , 11.035 , 11.4475],\n",
+ " [-3, -3, -5, ..., -2, -3, -5]], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>navitar</span></div><div class='xr-var-dims'>(trainId, gratingEnergy)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>12.22 11.29 10.78 ... 13.06 12.46</div><input id='attrs-3189f80e-293c-4f54-99c1-c0fc4516454f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3189f80e-293c-4f54-99c1-c0fc4516454f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6cce61f-2bde-4f3b-8f28-de0ae2926a43' class='xr-var-data-in' type='checkbox'><label for='data-c6cce61f-2bde-4f3b-8f28-de0ae2926a43' 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([[12.22 , 11.2875, 10.78 , ..., 12.105 , 11.035 , 11.4475],\n",
" [10.555 , 12.405 , 11.015 , ..., 11.995 , 11.7325, 10.76 ],\n",
" [11.725 , 10.5325, 11.47 , ..., 13.3975, 11.4575, 12.4975],\n",
" ...,\n",
" [10.5275, 11.8375, 10.88 , ..., 11.4275, 11.635 , 11.5475],\n",
" [11.1775, 11. , 10.9025, ..., 11.6725, 12.195 , 10.955 ],\n",
- " [11.59 , 12.0475, 12.6725, ..., 12.425 , 13.0575, 12.455 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>energy</span></div><div class='xr-var-dims'>(trainId, gratingEnergy)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>981.0 981.0 ... 1.02e+03 1.02e+03</div><input id='attrs-3dc06260-d843-4a8b-b792-e0b35fb50b0b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3dc06260-d843-4a8b-b792-e0b35fb50b0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-882f7217-4fe3-475e-bcfb-23d2210fe8b4' class='xr-var-data-in' type='checkbox'><label for='data-882f7217-4fe3-475e-bcfb-23d2210fe8b4' 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([[ 981.00375578, 981.02558941, 981.04742304, ..., 1020.23878641,\n",
+ " [11.59 , 12.0475, 12.6725, ..., 12.425 , 13.0575, 12.455 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>energy</span></div><div class='xr-var-dims'>(trainId, gratingEnergy)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>981.0 981.0 ... 1.02e+03 1.02e+03</div><input id='attrs-07d0393c-bd68-460c-b460-b8456c977626' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-07d0393c-bd68-460c-b460-b8456c977626' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2d0150f-131a-49ec-8354-3e30b3339670' class='xr-var-data-in' type='checkbox'><label for='data-c2d0150f-131a-49ec-8354-3e30b3339670' 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([[ 981.00375578, 981.02558941, 981.04742304, ..., 1020.23878641,\n",
" 1020.26062003, 1020.28245366],\n",
" [ 980.99653477, 981.01836809, 981.04020142, ..., 1020.23101968,\n",
" 1020.252853 , 1020.27468633],\n",
@@ -660,25 +660,25 @@
" [ 981.00375578, 981.02558941, 981.04742304, ..., 1020.23878641,\n",
" 1020.26062003, 1020.28245366],\n",
" [ 981.02541948, 981.04725402, 981.06908856, ..., 1020.2620873 ,\n",
- " 1020.28392184, 1020.30575638]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>bunchPatternTable</span></div><div class='xr-var-dims'>(trainId, pulse_slot)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>2146089 0 ... 16777216 16777216</div><input id='attrs-4a6d7255-c0ce-4bd0-8b24-53fe81716551' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4a6d7255-c0ce-4bd0-8b24-53fe81716551' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0601032-1a28-4b0e-88e7-0c1ad3e11f54' class='xr-var-data-in' type='checkbox'><label for='data-a0601032-1a28-4b0e-88e7-0c1ad3e11f54' 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([[ 2146089, 0, 2097193, ..., 16777216, 16777216, 16777216],\n",
+ " 1020.28392184, 1020.30575638]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>bunchPatternTable</span></div><div class='xr-var-dims'>(trainId, pulse_slot)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>2146089 0 ... 16777216 16777216</div><input id='attrs-c637aabd-c5e9-4df4-accf-18256bc64834' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c637aabd-c5e9-4df4-accf-18256bc64834' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a57c8f8-59ab-4ff4-9afb-504dcc6b6947' class='xr-var-data-in' type='checkbox'><label for='data-7a57c8f8-59ab-4ff4-9afb-504dcc6b6947' 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([[ 2146089, 0, 2097193, ..., 16777216, 16777216, 16777216],\n",
" [ 2146089, 0, 2097193, ..., 16777216, 16777216, 16777216],\n",
" [ 2146089, 0, 2097193, ..., 16777216, 16777216, 16777216],\n",
" ...,\n",
" [ 2146089, 0, 2097193, ..., 16777216, 16777216, 16777216],\n",
" [ 2211625, 0, 2097193, ..., 16777216, 16777216, 16777216],\n",
" [ 2146089, 0, 2097193, ..., 16777216, 16777216, 16777216]],\n",
- " dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>XTD10_SA3</span></div><div class='xr-var-dims'>(trainId, sa3_pId)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.217e+03 1.376e+03 ... 1.489e+03</div><input id='attrs-fbb06019-2284-4894-bf5b-b27f38890f02' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fbb06019-2284-4894-bf5b-b27f38890f02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e20b3c9-2ffc-4a95-9e66-7df8839d2068' class='xr-var-data-in' type='checkbox'><label for='data-1e20b3c9-2ffc-4a95-9e66-7df8839d2068' 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([[1217.2598],\n",
+ " dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>XTD10_SA3</span></div><div class='xr-var-dims'>(trainId, sa3_pId)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.217e+03 1.376e+03 ... 1.489e+03</div><input id='attrs-6ef63ef4-c23a-4b73-a985-0f27b6e0ac27' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6ef63ef4-c23a-4b73-a985-0f27b6e0ac27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa3c86e7-f41b-42f9-b7b3-8fb7b43bee7f' class='xr-var-data-in' type='checkbox'><label for='data-aa3c86e7-f41b-42f9-b7b3-8fb7b43bee7f' 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([[1217.2598],\n",
" [1375.6898],\n",
" [1362.0608],\n",
" ...,\n",
" [1517.0592],\n",
" [1555.7712],\n",
- " [1489.4523]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bf9b5168-318a-4881-8149-9dfd3a4163ea' class='xr-section-summary-in' type='checkbox' ><label for='section-bf9b5168-318a-4881-8149-9dfd3a4163ea' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>trainId</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5564b725-cc93-4373-8602-5f8a74e6a2bc' class='xr-index-data-in' type='checkbox'/><label for='index-5564b725-cc93-4373-8602-5f8a74e6a2bc' 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([1724088331, 1724088332, 1724088333, 1724088334, 1724088335, 1724088336,\n",
+ " [1489.4523]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a2badd6c-5843-4aca-be35-88f78e281d11' class='xr-section-summary-in' type='checkbox' ><label for='section-a2badd6c-5843-4aca-be35-88f78e281d11' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>trainId</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-287f3d59-eacc-4b1c-bff5-40230fe1709a' class='xr-index-data-in' type='checkbox'/><label for='index-287f3d59-eacc-4b1c-bff5-40230fe1709a' 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([1724088331, 1724088332, 1724088333, 1724088334, 1724088335, 1724088336,\n",
" 1724088337, 1724088338, 1724088339, 1724088340,\n",
" ...\n",
" 1724098292, 1724098293, 1724098294, 1724098295, 1724098296, 1724098297,\n",
" 1724098298, 1724098299, 1724098300, 1724098301],\n",
- " dtype='uint64', name='trainId', length=7165))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>sa3_pId</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2c18ae71-a7b0-41f1-9828-66aadc4c2514' class='xr-index-data-in' type='checkbox'/><label for='index-2c18ae71-a7b0-41f1-9828-66aadc4c2514' 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([1326], dtype='int64', name='sa3_pId'))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fd512070-9dfc-467b-bb39-f5e991eff335' class='xr-section-summary-in' type='checkbox' checked><label for='section-fd512070-9dfc-467b-bb39-f5e991eff335' 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>runFolder :</span></dt><dd>/gpfs/exfel/exp/SA3/202330/p900331/raw/r0069</dd></dl></div></li></ul></div></div>"
+ " dtype='uint64', name='trainId', length=7165))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>sa3_pId</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ad03798d-ddcd-44fd-9f71-882ce0472e4d' class='xr-index-data-in' type='checkbox'/><label for='index-ad03798d-ddcd-44fd-9f71-882ce0472e4d' 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([1326], dtype='int64', name='sa3_pId'))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f47ace9b-ea55-4e20-b971-517bf1a16bf3' class='xr-section-summary-in' type='checkbox' checked><label for='section-f47ace9b-ea55-4e20-b971-517bf1a16bf3' 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>runFolder :</span></dt><dd>/gpfs/exfel/exp/SA3/202330/p900331/raw/r0069</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
@@ -706,7 +706,7 @@
" runFolder: /gpfs/exfel/exp/SA3/202330/p900331/raw/r0069"
]
},
- "execution_count": 28,
+ "execution_count": 99,
"metadata": {},
"output_type": "execute_result"
}
@@ -717,7 +717,7 @@
},
{
"cell_type": "code",
- "execution_count": 29,
+ "execution_count": 100,
"id": "8f154e38-d208-477e-9d9c-ef2a632514c8",
"metadata": {},
"outputs": [],
@@ -727,7 +727,7 @@
},
{
"cell_type": "code",
- "execution_count": 31,
+ "execution_count": 101,
"id": "0c5ff2a0-0737-417d-9f57-158d4fbd8090",
"metadata": {},
"outputs": [],
@@ -788,17 +788,17 @@
},
{
"cell_type": "code",
- "execution_count": 40,
+ "execution_count": 104,
"id": "d0b70fef-5e27-4cb1-90e7-2653989cf48a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "[<matplotlib.lines.Line2D at 0x2afe25a554b0>]"
+ "[<matplotlib.lines.Line2D at 0x2afe279ac9d0>]"
]
},
- "execution_count": 40,
+ "execution_count": 104,
"metadata": {},
"output_type": "execute_result"
},
@@ -1007,7 +1007,7 @@
"id": "4d7f95c2-e16d-43b2-a0c5-28a968490bb0",
"metadata": {},
"source": [
- "## Apply model in data not used in training"
+ "# Validation: Apply model in data not used in training"
]
},
{
@@ -1173,7 +1173,7 @@
"id": "1f0f3f20-060a-488a-9f61-6b4cb3cf1614",
"metadata": {},
"source": [
- "# Apply it in new data without grating"
+ "# Inference: Apply it in new data without grating"
]
},
{
@@ -1186,7 +1186,7 @@
},
{
"cell_type": "code",
- "execution_count": 89,
+ "execution_count": 108,
"id": "afd8d85c-d6f0-4fff-9e90-79a99363aca8",
"metadata": {},
"outputs": [],
@@ -1194,19 +1194,21 @@
"runTest = 70\n",
"\n",
"# bunch pattern table\n",
- "field_bpt = [\n",
- " 'bunchPatternTable_SA3',\n",
- " #{'bunchPatternTable': {'source': 'SA3_BR_UTC/TSYS/TIMESERVER:outputBunchPattern',\n",
- " # 'key': 'data.bunchPatternTable',\n",
- " # 'dim': ['pulses'],\n",
- " # },\n",
- " # },\n",
+ "fields_inference = [\n",
+ " 'XTD10_SA3', # XGM\n",
+ " *list(pes_map.values()), # PES\n",
+ " 'bunchPatternTable_SA3',\n",
+ " #{'bunchPatternTable': {'source': 'SA3_BR_UTC/TSYS/TIMESERVER:outputBunchPattern',\n",
+ " # 'key': 'data.bunchPatternTable',\n",
+ " # 'dim': ['pulses'],\n",
+ " # },\n",
+ " # },\n",
" ]"
]
},
{
"cell_type": "code",
- "execution_count": 76,
+ "execution_count": 109,
"id": "83fe11bc-aa8b-4037-aa15-4a36e3104bf5",
"metadata": {},
"outputs": [],
@@ -1217,7 +1219,7 @@
},
{
"cell_type": "code",
- "execution_count": 90,
+ "execution_count": 110,
"id": "6115d454-d695-441e-b70f-40ac4a336355",
"metadata": {
"tags": []
@@ -1227,14 +1229,12 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "XTD10_SA3: only 92.4% of trains (5914 out of 6402) contain data.\n",
- "navitar: only 72.0% of trains (4608 out of 6402) contain data.\n",
- "energy: only 72.0% of trains (4608 out of 6402) contain data.\n"
+ "XTD10_SA3: only 92.4% of trains (5914 out of 6402) contain data.\n"
]
}
],
"source": [
- "_, data_inf = tb.load(proposal, runTest, fields + field_bpt)\n",
+ "_, data_inf = tb.load(proposal, runTest, fields_inference)\n",
"\n",
"# transform PES data into the format expected\n",
"pes_data_inf = {k: da.from_array(data_inf[item].to_numpy())\n",
@@ -1247,7 +1247,7 @@
},
{
"cell_type": "code",
- "execution_count": 80,
+ "execution_count": 111,
"id": "61361cb1-4ae6-4651-ad98-05504386ef4f",
"metadata": {},
"outputs": [],
@@ -1262,7 +1262,7 @@
},
{
"cell_type": "code",
- "execution_count": 81,
+ "execution_count": 112,
"id": "432794bf-969e-404f-a087-1961c1b93736",
"metadata": {},
"outputs": [
@@ -1283,7 +1283,7 @@
" 'channel_4_D': array([0])}"
]
},
- "execution_count": 81,
+ "execution_count": 112,
"metadata": {},
"output_type": "execute_result"
}
@@ -1304,7 +1304,7 @@
},
{
"cell_type": "code",
- "execution_count": 82,
+ "execution_count": 113,
"id": "d9f267f7-3e0d-4101-97f0-019c837b5e5e",
"metadata": {},
"outputs": [],
@@ -1314,7 +1314,7 @@
},
{
"cell_type": "code",
- "execution_count": 83,
+ "execution_count": 114,
"id": "2be3b1ac-5e21-4503-b763-ba7723b808c2",
"metadata": {},
"outputs": [],
@@ -1322,6 +1322,48 @@
"vs_inf[\"energy\"] = model.get_energy_values()"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": 121,
+ "id": "bdd8a381-41d8-4a3e-9d16-1d7052aa527a",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(5714, 1, 1800)"
+ ]
+ },
+ "execution_count": 121,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "vs_inf[\"expected\"].shape"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 122,
+ "id": "43c23e2b-cc36-47b4-985a-691b155ef355",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(1800,)"
+ ]
+ },
+ "execution_count": 122,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "vs_inf[\"energy\"].shape"
+ ]
+ },
{
"cell_type": "markdown",
"id": "cdd39379-bb88-4717-bcf5-beb4440daf78",
@@ -1332,7 +1374,7 @@
},
{
"cell_type": "code",
- "execution_count": 86,
+ "execution_count": 115,
"id": "c9ea5c57-cdf3-4268-856f-44b48cd3fb69",
"metadata": {},
"outputs": [],
@@ -1361,13 +1403,13 @@
},
{
"cell_type": "code",
- "execution_count": 88,
+ "execution_count": 118,
"id": "99256b0f-780d-4a20-bc70-6e0b894c584c",
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": 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\n",
"text/plain": [
"<Figure size 864x576 with 1 Axes>"
]
@@ -1379,7 +1421,7 @@
}
],
"source": [
- "plot_new(vs_inf, 0, pulse=0)"
+ "plot_new(vs_inf, 2, pulse=0)"
]
},
{
diff --git a/notebook/Virtual spectrometer SCS Viking.ipynb b/notebook/Virtual spectrometer SCS Viking.ipynb
index 3aee0e27ab787c45dd956a18033f4ee1215c1208..778242ad67e88e48663e66b89d9b9614ffd84abd 100644
--- a/notebook/Virtual spectrometer SCS Viking.ipynb
+++ b/notebook/Virtual spectrometer SCS Viking.ipynb
@@ -77,7 +77,7 @@
"id": "c7609899-5bc0-4211-ae97-010b3edcf676",
"metadata": {},
"source": [
- "## Get data and calibrate Viking"
+ "# Training:"
]
},
{
@@ -1140,7 +1140,7 @@
"id": "4d7f95c2-e16d-43b2-a0c5-28a968490bb0",
"metadata": {},
"source": [
- "## Apply model in data not used in training"
+ "# Validation: Apply model in data not used in training"
]
},
{
@@ -1329,7 +1329,7 @@
"id": "1f0f3f20-060a-488a-9f61-6b4cb3cf1614",
"metadata": {},
"source": [
- "## Apply it in new data without Viking"
+ "# Inference: Apply it in new data without Viking"
]
},
{