247 lines
99 KiB
Plaintext
247 lines
99 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 30,
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"metadata": {},
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"outputs": [],
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"source": [
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"import uproot\n",
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"import numpy as np\n",
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"import sys\n",
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"import os\n",
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"import matplotlib\n",
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"import matplotlib.pyplot as plt\n",
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"import mplhep\n",
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"from mpl_toolkits import mplot3d\n",
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"import itertools\n",
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"import awkward as ak\n",
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"from scipy.optimize import curve_fit\n",
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"from utils.components import unique_name_ext_re\n",
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"mplhep.style.use([\"LHCbTex2\"])\n",
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"plt.rcParams[\"savefig.dpi\"] = 600\n",
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"%matplotlib inline"
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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": 31,
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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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"50501"
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]
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},
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"execution_count": 31,
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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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"file = uproot.open(\n",
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" \"/work/cetin/Projektpraktikum/tracking_losses_ntuple_B_rad_length_endVelo2endUT.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n",
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")\n",
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"\n",
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"# selektiere nur elektronen von B->K*ee\n",
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"allcolumns = file.arrays()\n",
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"electrons = allcolumns[(allcolumns.isElectron) & (allcolumns.fromB)]\n",
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"\n",
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"ak.num(electrons, axis=0)\n",
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"# ak.count(found, axis=None)"
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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": 32,
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"metadata": {},
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"outputs": [],
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"source": [
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"# electrons.type.show()"
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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": 33,
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"metadata": {},
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"outputs": [],
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"source": [
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"found = electrons[~electrons.lost]\n",
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"lost = electrons[electrons.lost]\n",
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"\n",
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"eloss_found = (found[\"p\"] - found[\"p_end_scifi\"]) / found[\"p\"]\n",
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"eloss_lost = (lost[\"p\"] - lost[\"p_end_scifi\"]) / lost[\"p\"]\n",
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"\n",
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"eloss = (electrons[\"p\"] - electrons[\"p_end_scifi\"]) / electrons[\"p\"]"
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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": 34,
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"metadata": {},
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"outputs": [],
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"source": [
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"# eloss_upstream_found = (found[\"p\"] - found[\"p_end_ut\"]) / found[\"p\"]\n",
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"# eloss_upstream_lost = (lost[\"p\"] - lost[\"p_end_ut\"]) / lost[\"p\"]"
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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": 35,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 1200x900 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"nbins = 50\n",
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"plt.hist(\n",
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" ak.to_numpy(eloss_lost),\n",
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" bins=nbins,\n",
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" density=True,\n",
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" alpha=0.5,\n",
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" histtype=\"bar\",\n",
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" color=\"#F05342\",\n",
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" label=\"lost\",\n",
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" range=[0.001, 1],\n",
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")\n",
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"# #2A9D8F another teal color\n",
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"plt.hist(\n",
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" ak.to_numpy(eloss_found),\n",
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" bins=nbins,\n",
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" density=True,\n",
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" alpha=0.5,\n",
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" histtype=\"bar\",\n",
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" color=\"#107E7D\",\n",
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" label=\"found\",\n",
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" range=[0.001, 1],\n",
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")\n",
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"\n",
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"plt.xlabel(r\"$E_\\gamma/E_0$\")\n",
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"plt.ylabel(\"a.u.\")\n",
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"# plt.title(r'$B\\rightarrow K^\\ast ee$, $p>5$GeV, photons w/ brem_vtx_z$<9500$mm')\n",
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"plt.legend(title=\"LHCb Simulation\")\n",
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"\n",
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"plt.savefig(\"/work/cetin/Projektpraktikum/thesis/emitted_energy.pdf\", format=\"PDF\")"
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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": 27,
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"metadata": {},
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"outputs": [],
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"source": [
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"# magnet kick position\n",
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"input_tree = uproot.open(\n",
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" {\n",
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" \"/work/cetin/Projektpraktikum/param_data_B_default.root\": \"PrParameterisationData_2ece6184.PrDebugTrackingTool/Tuple;1\"\n",
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" }\n",
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")\n",
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"array = input_tree.arrays()\n",
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"array = array[array.isElectron & (array.fromB)]\n",
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"array[\"dSlope_fringe\"] = array[\"tx_ref\"] - array[\"tx\"]\n",
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"array[\"z_mag_x_fringe\"] = (\n",
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" array[\"x\"]\n",
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" - array[\"x_ref\"]\n",
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" - array[\"tx\"] * array[\"z\"]\n",
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" + array[\"tx_ref\"] * array[\"z_ref\"]\n",
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") / array[\"dSlope_fringe\"]"
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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": 28,
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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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"(exptext: Custom Text(0.05, 0.95, 'LHCb'),\n",
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" expsuffix: Custom Text(0.05, 0.955, 'Simulation'))"
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]
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},
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"execution_count": 28,
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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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"data": {
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"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1200x900 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"fig = plt.figure()\n",
|
||
|
|
"plt.hist(\n",
|
||
|
|
" array[\"z_mag_x_fringe\"], bins=50, range=[5150, 5300], color=\"#2A9D8F\", density=True\n",
|
||
|
|
")\n",
|
||
|
|
"plt.xlabel(r\"z$_{Mag}$ [mm]\")\n",
|
||
|
|
"plt.ylabel(\"Number of Tracks (normalised)\")\n",
|
||
|
|
"mplhep.lhcb.text(\"Simulation\")"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 29,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"50501"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 29,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ak.num(array, axis=0)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"metadata": {
|
||
|
|
"kernelspec": {
|
||
|
|
"display_name": "tuner",
|
||
|
|
"language": "python",
|
||
|
|
"name": "python3"
|
||
|
|
},
|
||
|
|
"language_info": {
|
||
|
|
"codemirror_mode": {
|
||
|
|
"name": "ipython",
|
||
|
|
"version": 3
|
||
|
|
},
|
||
|
|
"file_extension": ".py",
|
||
|
|
"mimetype": "text/x-python",
|
||
|
|
"name": "python",
|
||
|
|
"nbconvert_exporter": "python",
|
||
|
|
"pygments_lexer": "ipython3",
|
||
|
|
"version": "3.10.12"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 2
|
||
|
|
}
|