213 lines
103 KiB
Plaintext
Executable File
213 lines
103 KiB
Plaintext
Executable File
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 60,
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"id": "c8582424-19a9-4582-95fc-f989f8812e25",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'/gfa/.mounts/sf_cristallina/applications/cristallina'"
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]
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},
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"execution_count": 60,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import os\n",
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"os.getcwd()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 37,
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"id": "146be213-ed9b-4610-9a74-301b0a08b160",
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"metadata": {},
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"outputs": [],
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"source": [
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"%matplotlib widget\n",
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"\n",
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"import cristallina as cr\n",
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"import sfdata as sf\n",
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"\n",
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"from matplotlib import pyplot as plt\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "1202d43a-a7ec-4369-a70b-ed41f5750349",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pytest\n",
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"import numpy as np\n",
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"import unittest.mock\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "0b89a114-a70e-4bcf-b35d-0f9be2a75ea4",
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"metadata": {},
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"outputs": [],
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"source": [
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"test_image_calculations()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 61,
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"id": "03014ab1-0db1-4521-ace3-923ab4d95a60",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/sf/cristallina/applications/conda/envs/analysis_edge/lib/python3.11/site-packages/sfdata-0.4.0-py3.11.egg/sfdata/sfdatafile.py:107: UserWarning: Skipping channel \"SARFE10-PBPS053:MOTOR_X2\" since it caused DatasetNotInGroupError: Cannot get dataset \"data\" from: <HDF5 group \"/SARFE10-PBPS053:MOTOR_X2\" (0 members)>\n",
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"/sf/cristallina/applications/conda/envs/analysis_edge/lib/python3.11/site-packages/sfdata-0.4.0-py3.11.egg/sfdata/sfdatafile.py:107: UserWarning: Skipping channel \"SAROP31-OPPI151:MOTOR_X.RBV\" since it caused DatasetNotInGroupError: Cannot get dataset \"data\" from: <HDF5 group \"/SAROP31-OPPI151:MOTOR_X.RBV\" (0 members)>\n",
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"/sf/cristallina/applications/conda/envs/analysis_edge/lib/python3.11/site-packages/sfdata-0.4.0-py3.11.egg/sfdata/sfdatafile.py:107: UserWarning: Skipping channel \"SAROP31-OPPI151:MOTOR_Y.RBV\" since it caused DatasetNotInGroupError: Cannot get dataset \"data\" from: <HDF5 group \"/SAROP31-OPPI151:MOTOR_Y.RBV\" (0 members)>\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"(21, 1614, 1030)\n"
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]
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},
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "ecf8cdc76c114ac28ffb57a7a489d057",
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"version_major": 2,
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"version_minor": 0
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},
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"image/png": 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",
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"\n",
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" <div style=\"display: inline-block;\">\n",
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" Figure\n",
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' width=640.0/>\n",
|
|
" </div>\n",
|
|
" "
|
|
],
|
|
"text/plain": [
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"\n",
|
|
"@unittest.mock.patch(\"jungfrau_utils.file_adapter.locate_gain_file\", lambda path, **kwargs: \"tests/data/gains.h5\")\n",
|
|
"@unittest.mock.patch(\"jungfrau_utils.file_adapter.locate_pedestal_file\", lambda path, **kwargs: \"tests/data/JF16T03V01.res.h5\")\n",
|
|
"def test():\n",
|
|
" with sf.SFDataFiles('tests/data/p20841/raw/run0205/data/acq0001.*.h5') as data:\n",
|
|
" jf = data['JF16T03V01']\n",
|
|
" print(jf.data.shape)\n",
|
|
" fig, ax = plt.subplots()\n",
|
|
" ax.imshow(jf.data[11],vmin=-1, vmax=1000)\n",
|
|
" return jf\n",
|
|
" \n",
|
|
"\n",
|
|
"jf = test()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 55,
|
|
"id": "6dd7c89a-4e51-402e-8c46-9632cba23671",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"No ROI name given, generating: ROI(bottom=600,top=750,left=575,right=750)\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"application/vnd.jupyter.widget-view+json": {
|
|
"model_id": "68101b0676ff45f8ac295327835a3101",
|
|
"version_major": 2,
|
|
"version_minor": 0
|
|
},
|
|
"image/png": 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",
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"\n",
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" <div style=\"display: inline-block;\">\n",
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" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
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" Figure\n",
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" </div>\n",
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' width=640.0/>\n",
|
|
" </div>\n",
|
|
" "
|
|
],
|
|
"text/plain": [
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"@unittest.mock.patch(\"jungfrau_utils.file_adapter.locate_gain_file\", lambda path, **kwargs: \"tests/data/gains.h5\")\n",
|
|
"@unittest.mock.patch(\"jungfrau_utils.file_adapter.locate_pedestal_file\", lambda path, **kwargs: \"tests/data/JF16T03V01.res.h5\")\n",
|
|
"def test_roi():\n",
|
|
" roi = cr.utils.ROI(left=575, right=750, top=750, bottom=600)\n",
|
|
" res = cr.analysis.perform_image_roi_crop(['tests/data/p20841/raw/run0205/data/acq0001.*.h5'], roi=roi)\n",
|
|
" return res\n",
|
|
"\n",
|
|
"cutouts = test_roi()\n",
|
|
"fig, ax = plt.subplots()\n",
|
|
"ax.imshow(cutouts[11])\n",
|
|
"\n",
|
|
"sum_roi, max_roi, min_roi = np.sum(cutouts[11]), np.max(cutouts[11]), np.min(cutouts[11])\n",
|
|
"assert np.allclose([3119071.8, 22381.547, -0.9425874 ], [sum_roi, max_roi, min_roi])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "730c51cc-1848-4e78-b8bf-e48f5288d90d",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python [conda env:conda-analysis_edge]",
|
|
"language": "python",
|
|
"name": "conda-env-conda-analysis_edge-py"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.11.6"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|