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zonca/out_plot_cl_E.ipynb

Created February 28, 2025 21:17
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out_plot_cl_E.ipynb
{
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{
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"tags": []
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"source": [
"import healpy as hp\n",
"import numpy as np\n",
"import pickle\n",
"import h5py\n",
"import altair as alt\n",
"\n",
"alt.renderers.enable(\"html\")\n",
"import pandas as pd\n",
"import warnings\n",
"\n",
"warnings.filterwarnings(\"ignore\")\n",
"import pysm3.units as u"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "3d9ca1dc",
"metadata": {
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{
"data": {
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" $('div.input').show();\n",
" }\n",
" code_show = !code_show\n",
"} \n",
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"<IPython.core.display.HTML object>"
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"source": [
"from IPython.display import HTML\n",
"\n",
"HTML(\n",
" \"\"\"<script>\n",
"code_show=true; \n",
"function code_toggle() {\n",
" if (code_show){\n",
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" code_show = !code_show\n",
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"</script>\n",
"<form action=\"javascript:code_toggle()\"><input type=\"submit\" value=\"Click here to toggle on/off the raw code.\"></form>\"\"\"\n",
")"
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{
"cell_type": "code",
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"id": "dc5a2711",
"metadata": {
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"tags": [
"parameters"
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},
"outputs": [],
"source": [
"pol = \"T\""
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "b19fb7c9",
"metadata": {
"execution": {
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"tags": [
"injected-parameters"
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},
"outputs": [],
"source": [
"# Parameters\n",
"pol = \"E\"\n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "0ade89db",
"metadata": {
"execution": {
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"tags": []
},
"outputs": [],
"source": [
"selection = {}\n",
"cl = {}\n",
"i_pol = \"TEB\".index(pol)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "3d8e26f6",
"metadata": {
"execution": {
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"status": "completed"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"/mnt/home/azonca/p/software/map_based_simulations/mbs-s0019-20250221\n"
]
}
],
"source": [
"%cd .."
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "c8ea2254",
"metadata": {
"execution": {
"iopub.execute_input": "2025-02-28T21:12:51.457438Z",
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"tags": []
},
"outputs": [],
"source": [
"import os\n",
"\n",
"if os.path.basename(os.getcwd()) == \"verification\":\n",
" %cd .."
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "28d62030",
"metadata": {
"execution": {
"iopub.execute_input": "2025-02-28T21:12:51.466438Z",
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"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"from astropy.table import QTable"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "a5ddbe09",
"metadata": {
"execution": {
"iopub.execute_input": "2025-02-28T21:12:51.475333Z",
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"tags": []
},
"outputs": [],
"source": [
"chs = QTable.read(\"instrument_model/instrument_model.tbl\", format=\"ascii.ipac\")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "4beb70f6",
"metadata": {
"execution": {
"iopub.execute_input": "2025-02-28T21:12:51.487289Z",
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"tags": []
},
"outputs": [
{
"data": {
"text/html": [
"<div><i>QTable length=5</i>\n",
"<table id=\"table23447019410816\" class=\"table-striped table-bordered table-condensed\">\n",
"<thead><tr><th>telescope</th><th>band</th><th>fwhm</th><th>center_frequency</th><th>nside</th><th>bandpass_file</th><th>beam_file</th></tr></thead>\n",
"<thead><tr><th></th><th></th><th>arcmin</th><th>GHz</th><th></th><th></th><th></th></tr></thead>\n",
"<thead><tr><th>str4</th><th>str2</th><th>float64</th><th>float64</th><th>int64</th><th>str15</th><th>str11</th></tr></thead>\n",
"<tr><td>WMAP</td><td>K</td><td>52.8</td><td>22.451910974502667</td><td>512</td><td>bandpass_K.tbl</td><td>beam_K.tbl</td></tr>\n",
"<tr><td>WMAP</td><td>Ka</td><td>39.6</td><td>32.706607212937314</td><td>512</td><td>bandpass_Ka.tbl</td><td>beam_Ka.tbl</td></tr>\n",
"<tr><td>WMAP</td><td>Q</td><td>30.6</td><td>40.36343387766631</td><td>512</td><td>bandpass_Q.tbl</td><td>beam_Q.tbl</td></tr>\n",
"<tr><td>WMAP</td><td>V</td><td>21.0</td><td>60.07932358223898</td><td>512</td><td>bandpass_V.tbl</td><td>beam_V.tbl</td></tr>\n",
"<tr><td>WMAP</td><td>W</td><td>13.2</td><td>92.82552325276862</td><td>512</td><td>bandpass_W.tbl</td><td>beam_W.tbl</td></tr>\n",
"</table></div>"
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"text/plain": [
"<QTable length=5>\n",
"telescope band fwhm center_frequency nside bandpass_file beam_file \n",
" arcmin GHz \n",
" str4 str2 float64 float64 int64 str15 str11 \n",
"--------- ---- ------- ------------------ ----- --------------- -----------\n",
" WMAP K 52.8 22.451910974502667 512 bandpass_K.tbl beam_K.tbl\n",
" WMAP Ka 39.6 32.706607212937314 512 bandpass_Ka.tbl beam_Ka.tbl\n",
" WMAP Q 30.6 40.36343387766631 512 bandpass_Q.tbl beam_Q.tbl\n",
" WMAP V 21.0 60.07932358223898 512 bandpass_V.tbl beam_V.tbl\n",
" WMAP W 13.2 92.82552325276862 512 bandpass_W.tbl beam_W.tbl"
]
},
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"chs"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "d3e2dae7",
"metadata": {
"execution": {
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"status": "completed"
},
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"DataTransformerRegistry.enable('default')"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"alt.data_transformers.enable(\"default\")"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "477b754a",
"metadata": {
"execution": {
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"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"DataTransformerRegistry.enable('default')"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"alt.data_transformers.disable_max_rows()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "0e881116",
"metadata": {
"execution": {
"iopub.execute_input": "2025-02-28T21:12:51.518146Z",
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"exception": false,
"start_time": "2025-02-28T21:12:51.514281",
"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"import pysm3 as pysm\n",
"from pysm3 import units as u"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "d26ff6e3",
"metadata": {
"execution": {
"iopub.execute_input": "2025-02-28T21:12:51.527401Z",
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},
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"end_time": "2025-02-28T21:12:51.533638",
"exception": false,
"start_time": "2025-02-28T21:12:51.523615",
"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"import mapsims"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "c01af542",
"metadata": {
"execution": {
"iopub.execute_input": "2025-02-28T21:12:51.540382Z",
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"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"pol_label = [\"TT\", \"EE\", \"BB\"][i_pol]"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "5c12aeb5",
"metadata": {
"execution": {
"iopub.execute_input": "2025-02-28T21:12:51.549869Z",
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"start_time": "2025-02-28T21:12:51.546061",
"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"from glob import glob"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "f06429fc",
"metadata": {
"execution": {
"iopub.execute_input": "2025-02-28T21:12:51.559308Z",
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},
"tags": []
},
"outputs": [],
"source": [
"toml_files = glob(\"*.toml\")"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "94391a17",
"metadata": {
"execution": {
"iopub.execute_input": "2025-02-28T21:12:51.569425Z",
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"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"toml_files.remove(\"common.toml\")"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "50e045aa",
"metadata": {
"execution": {
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"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"toml_files.remove(\"co_co1.toml\")\n",
"toml_files.remove(\"co_co3.toml\")"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "7cfbd44d",
"metadata": {
"execution": {
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"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"toml_files.sort()"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "af5f193e",
"metadata": {
"execution": {
"iopub.execute_input": "2025-02-28T21:12:51.597654Z",
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"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"pysm_nside = 512"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "1bf92c2f",
"metadata": {
"execution": {
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" width: 100%;\n",
" display: flex;\n",
" }\n",
"\n",
" #altair-viz-912091db67d24f3686649ffc69003c02.vega-embed details,\n",
" #altair-viz-912091db67d24f3686649ffc69003c02.vega-embed details summary {\n",
" position: relative;\n",
" }\n",
"</style>\n",
"<div id=\"altair-viz-912091db67d24f3686649ffc69003c02\"></div>\n",
"<script type=\"text/javascript\">\n",
" var VEGA_DEBUG = (typeof VEGA_DEBUG == \"undefined\") ? {} : VEGA_DEBUG;\n",
" (function(spec, embedOpt){\n",
" let outputDiv = document.currentScript.previousElementSibling;\n",
" if (outputDiv.id !== \"altair-viz-912091db67d24f3686649ffc69003c02\") {\n",
" outputDiv = document.getElementById(\"altair-viz-912091db67d24f3686649ffc69003c02\");\n",
" }\n",
" const paths = {\n",
" \"vega\": \"https://cdn.jsdelivr.net/npm/vega@5?noext\",\n",
" \"vega-lib\": \"https://cdn.jsdelivr.net/npm/vega-lib?noext\",\n",
" \"vega-lite\": \"https://cdn.jsdelivr.net/npm/[email protected]?noext\",\n",
" \"vega-embed\": \"https://cdn.jsdelivr.net/npm/vega-embed@6?noext\",\n",
" };\n",
"\n",
" function maybeLoadScript(lib, version) {\n",
" var key = `${lib.replace(\"-\", \"\")}_version`;\n",
" return (VEGA_DEBUG[key] == version) ?\n",
" Promise.resolve(paths[lib]) :\n",
" new Promise(function(resolve, reject) {\n",
" var s = document.createElement('script');\n",
" document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
" s.async = true;\n",
" s.onload = () => {\n",
" VEGA_DEBUG[key] = version;\n",
" return resolve(paths[lib]);\n",
" };\n",
" s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
" s.src = paths[lib];\n",
" });\n",
" }\n",
"\n",
" function showError(err) {\n",
" outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
" throw err;\n",
" }\n",
"\n",
" function displayChart(vegaEmbed) {\n",
" vegaEmbed(outputDiv, spec, embedOpt)\n",
" .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
" }\n",
"\n",
" if(typeof define === \"function\" && define.amd) {\n",
" requirejs.config({paths});\n",
" require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
" } else {\n",
" maybeLoadScript(\"vega\", \"5\")\n",
" .then(() => maybeLoadScript(\"vega-lite\", \"5.20.1\"))\n",
" .then(() => maybeLoadScript(\"vega-embed\", \"6\"))\n",
" .catch(showError)\n",
" .then(() => displayChart(vegaEmbed));\n",
" }\n",
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"</script>"
],
"text/plain": [
"alt.Chart(...)"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"for config_file in toml_files:\n",
" mapsim = mapsims.from_config(\n",
" [\"common.toml\", config_file], override={\"channels\": \"all\"}\n",
" )\n",
" component = config_file.split(\".\")[0]\n",
" print(component)\n",
" filename = f\"output/C_ell/C_ell_{component}.pkl\"\n",
" with open(filename, \"rb\") as f:\n",
" cl[component] = pickle.load(f)\n",
" sky = pysm.Sky(\n",
" nside=pysm_nside,\n",
" preset_strings=[mapsim.pysm_components_string],\n",
" output_unit=u.uK_CMB,\n",
" )\n",
" onecl = (\n",
" pd.DataFrame({ch: pd.Series(cl[component][ch][i_pol]) for ch in channels})\n",
" .reset_index()\n",
" .rename(columns={\"index\": \"ell\"})\n",
" )\n",
"\n",
" pysm_emission = sky.get_emission(chs[\"center_frequency\"][0])\n",
" label = \"PySM \" + channels[0]\n",
"\n",
" pysm_low = hp.anafast(\n",
" pysm_emission, lmax=int(1.5 * pysm_nside), use_pixel_weights=True\n",
" )[i_pol]\n",
" pysm_low *= (\n",
" hp.gauss_beam(chs[0][\"fwhm\"].to_value(u.rad), lmax=int(1.5 * pysm_nside)) ** 2\n",
" )\n",
" onecl[label] = 0\n",
" onecl[label][: len(pysm_low)] = pysm_low\n",
"\n",
" pysm_emission = sky.get_emission(\n",
" chs[-1][\"center_frequency\"],\n",
" )\n",
" label = \"PySM \" + channels[-1]\n",
"\n",
" pysm_high = hp.anafast(\n",
" pysm_emission, lmax=int(1.5 * pysm_nside), use_pixel_weights=True\n",
" )[i_pol]\n",
" pysm_high *= (\n",
" hp.gauss_beam(chs[-1][\"fwhm\"].to_value(u.rad), lmax=int(1.5 * pysm_nside)) ** 2\n",
" )\n",
" onecl[label] = 0\n",
" onecl[label][: len(pysm_high)] = pysm_high\n",
"\n",
" onecl = onecl[onecl.ell != 0]\n",
" decim = np.concatenate(\n",
" [[0], np.logspace(0, np.log10(len(onecl)), 100, endpoint=False)]\n",
" )\n",
" onecl = onecl.iloc[decim, :] # decimate in log scale to make plots smaller\n",
"\n",
" onecl_long = onecl.melt(\"ell\", var_name=\"channel\")\n",
" onecl_long[onecl_long.value == 0] = np.nan\n",
" selection[component] = alt.selection_multi(fields=[\"channel\"], bind=\"legend\")\n",
"\n",
" chart = (\n",
" alt.Chart(onecl_long, title=component + \" \" + pol_label)\n",
" .mark_line()\n",
" .encode(\n",
" x=alt.X(\"ell\", scale=alt.Scale(type=\"log\", base=10, domain=[1, 1e4])),\n",
" y=alt.Y(\"value\", scale=alt.Scale(type=\"log\", base=10)),\n",
" color=alt.Color(\n",
" \"channel\",\n",
" sort=[\"PySM \" + channels[0]]\n",
" + list(channels)\n",
" + [\"PySM \" + channels[-1]],\n",
" ),\n",
" opacity=alt.condition(selection[component], alt.value(1), alt.value(0.2)),\n",
" )\n",
" .add_selection(selection[component])\n",
" .interactive()\n",
" )\n",
" chart.display()\n",
" # chart.save(f\"verification/out_plot_cl/{component}_{input_telescope}_{pol}.json\")"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "43e77420",
"metadata": {
"execution": {
"iopub.execute_input": "2025-02-28T21:17:13.612096Z",
"iopub.status.busy": "2025-02-28T21:17:13.611909Z",
"iopub.status.idle": "2025-02-28T21:17:13.615251Z",
"shell.execute_reply": "2025-02-28T21:17:13.614907Z"
},
"papermill": {
"duration": 0.014509,
"end_time": "2025-02-28T21:17:13.616265",
"exception": false,
"start_time": "2025-02-28T21:17:13.601756",
"status": "completed"
},
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"101"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(onecl)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "13dd5267",
"metadata": {
"papermill": {
"duration": 0.010547,
"end_time": "2025-02-28T21:17:13.635536",
"exception": false,
"start_time": "2025-02-28T21:17:13.624989",
"status": "completed"
},
"tags": []
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 28,
"id": "96de33e0",
"metadata": {
"execution": {
"iopub.execute_input": "2025-02-28T21:17:13.654649Z",
"iopub.status.busy": "2025-02-28T21:17:13.654494Z",
"iopub.status.idle": "2025-02-28T21:17:13.710630Z",
"shell.execute_reply": "2025-02-28T21:17:13.710307Z"
},
"papermill": {
"duration": 0.066897,
"end_time": "2025-02-28T21:17:13.711587",
"exception": false,
"start_time": "2025-02-28T21:17:13.644690",
"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"# Make sure the notebook is saved\n",
"\n",
"from ipylab import JupyterFrontEnd\n",
"\n",
"app = JupyterFrontEnd()\n",
"app.commands.execute(\"docmanager:save\")"
]
}
],
"metadata": {
"jupytext": {
"formats": "ipynb,py"
},
"kernelspec": {
"display_name": "cmb",
"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": "3.12.7"
},
"papermill": {
"default_parameters": {},
"duration": 265.718918,
"end_time": "2025-02-28T21:17:14.540610",
"environment_variables": {},
"exception": null,
"input_path": "plot_cl.ipynb",
"output_path": "out_plot_cl_E.ipynb",
"parameters": {
"pol": "E"
},
"start_time": "2025-02-28T21:12:48.821692",
"version": "2.6.0"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
"state": {
"37ba975df0b44cb0a0ed0e13abf5f67a": {
"model_module": "ipylab",
"model_module_version": "^1.0.0",
"model_name": "ShellModel",
"state": {
"_model_module": "ipylab",
"_model_module_version": "^1.0.0",
"_model_name": "ShellModel",
"_view_count": null,
"_view_module": null,
"_view_module_version": "",
"_view_name": null,
"_widgets": []
}
},
"5731713d5cc94f5a8da22f57ea4995d0": {
"model_module": "ipylab",
"model_module_version": "^1.0.0",
"model_name": "SessionManagerModel",
"state": {
"_model_module": "ipylab",
"_model_module_version": "^1.0.0",
"_model_name": "SessionManagerModel",
"_view_count": null,
"_view_module": null,
"_view_module_version": "",
"_view_name": null,
"current_session": {},
"sessions": []
}
},
"753b9a8657d14430a1ca6c1a22261df0": {
"model_module": "ipylab",
"model_module_version": "^1.0.0",
"model_name": "CommandRegistryModel",
"state": {
"_command_list": [],
"_commands": [],
"_model_module": "ipylab",
"_model_module_version": "^1.0.0",
"_model_name": "CommandRegistryModel",
"_view_count": null,
"_view_module": null,
"_view_module_version": "",
"_view_name": null
}
},
"dee6e2be0188428e829bab76108f50d2": {
"model_module": "ipylab",
"model_module_version": "^1.0.0",
"model_name": "JupyterFrontEndModel",
"state": {
"_model_module": "ipylab",
"_model_module_version": "^1.0.0",
"_model_name": "JupyterFrontEndModel",
"_view_count": null,
"_view_module": null,
"_view_module_version": "",
"_view_name": null,
"commands": "IPY_MODEL_753b9a8657d14430a1ca6c1a22261df0",
"sessions": "IPY_MODEL_5731713d5cc94f5a8da22f57ea4995d0",
"shell": "IPY_MODEL_37ba975df0b44cb0a0ed0e13abf5f67a",
"version": ""
}
}
},
"version_major": 2,
"version_minor": 0
}
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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