2023-10-05 10:49:35 +02:00
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{
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"cells": [
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{
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"cell_type": "code",
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2023-10-05 11:50:01 +02:00
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"execution_count": 38,
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2023-10-05 10:49:35 +02:00
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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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2023-10-05 11:50:01 +02:00
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"import matplotlib.ticker as tck\n",
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2023-10-05 10:49:35 +02:00
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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 mpl_toolkits.axes_grid1 import ImageGrid\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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2023-10-05 11:50:01 +02:00
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"execution_count": 39,
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2023-10-05 10:49:35 +02:00
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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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"10522"
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]
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},
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2023-10-05 11:50:01 +02:00
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"execution_count": 39,
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2023-10-05 10:49:35 +02:00
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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(\"tracking_losses_ntuple_Bd2KstEE.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\")\n",
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"\n",
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"#selektiere nur elektronen von B->K*ee und nur solche mit einem momentum von ueber 5 GeV \n",
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"allcolumns = file.arrays()\n",
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"found = allcolumns[(allcolumns.isElectron) & (~allcolumns.lost) & (allcolumns.fromSignal) & (allcolumns.p > 5e3)] #B: 9056\n",
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"lost = allcolumns[(allcolumns.isElectron) & (allcolumns.lost) & (allcolumns.fromSignal) & (allcolumns.p > 5e3)] #B: 1466\n",
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"\n",
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"ak.num(found, axis=0) + ak.num(lost, 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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2023-10-05 11:50:01 +02:00
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"execution_count": 49,
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2023-10-05 10:49:35 +02:00
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"metadata": {},
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"outputs": [],
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"source": [
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"#plot minimal energy of photon abhängigkeit von eta und phi\n",
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"#materialpeak (beampipe)\n",
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"\n",
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2023-10-05 11:50:01 +02:00
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"#looked at minimal photon energy ak.min(...) and sum of photon energies ak.sum(...)\n",
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2023-10-05 10:49:35 +02:00
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"energy_found = ak.to_numpy(ak.min(found[\"brem_photons_pe\"],axis=-1))\n",
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"energy_lost = ak.to_numpy(ak.min(lost[\"brem_photons_pe\"],axis=-1))\n",
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"\n",
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"eta_found = ak.to_numpy(found[\"eta\"])\n",
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"eta_lost = ak.to_numpy(lost[\"eta\"])\n",
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"\n",
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"phi_found = ak.to_numpy(found[\"phi\"])\n",
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"phi_lost = ak.to_numpy(lost[\"phi\"])\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": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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2023-10-05 11:50:01 +02:00
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"execution_count": 50,
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2023-10-05 10:49:35 +02:00
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"metadata": {},
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"outputs": [
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{
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"data": {
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2023-10-05 11:50:01 +02:00
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"image/png": "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2023-10-05 10:49:35 +02:00
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"text/plain": [
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"<Figure size 1800x600 with 3 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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"fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(18,6))\n",
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"\n",
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2023-10-05 11:50:01 +02:00
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"a0=ax[0].hist2d(energy_found, eta_found, bins=200, cmap=plt.cm.jet, cmin=1, range=[[0,3e3],[1,6]], vmax=20)\n",
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"ax[0].set_xlabel(\"minimal or sum of photon energy [MeV]\")\n",
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"ax[0].set_ylabel(r\"$\\eta$\")\n",
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2023-10-05 10:49:35 +02:00
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"ax[0].set_title(\"found eta wrt photon energy\")\n",
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"\n",
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2023-10-05 11:50:01 +02:00
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"a1=ax[1].hist2d(energy_lost, eta_lost, bins=200, cmap=plt.cm.jet, cmin=1, range=[[0,3e3],[1,6]], vmax=20)\n",
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"ax[1].set_xlabel(\"minimal or sum of photon energy [MeV]\")\n",
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"ax[1].set_ylabel(r\"$\\eta$\")\n",
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2023-10-05 10:49:35 +02:00
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"ax[1].set_title(\"lost eta wrt photon energy\")\n",
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"\n",
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"\"\"\"\n",
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2023-10-05 11:50:01 +02:00
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"lost: perhaps slightly more hits at larger eta but not really significant\n",
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2023-10-05 10:49:35 +02:00
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"\"\"\"\n",
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"\n",
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2023-10-05 10:49:35 +02:00
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"fig.colorbar(a0[3],ax=ax[1])\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "code",
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2023-10-05 11:50:01 +02:00
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"execution_count": 51,
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2023-10-05 10:49:35 +02:00
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"metadata": {},
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2023-10-05 11:50:01 +02:00
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<Figure size 1800x600 with 3 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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"fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(18,6))\n",
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"\n",
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"a0=ax[0].hist2d(energy_found, phi_found/np.pi, bins=200, cmap=plt.cm.jet, cmin=1, range=[[0,2e3],[-1.1,1.1]],vmax=10)\n",
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"#ax[0].set_yticks(np.arange(-1,1.1,0.25), minor=True)\n",
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"ax[0].yaxis.set_major_formatter(tck.FormatStrFormatter('%g $\\pi$'))\n",
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"ax[0].set_xlabel(\"minimal or sum of photon energy [MeV]\")\n",
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"ax[0].set_ylabel(r\"$\\phi$\")\n",
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"ax[0].set_title(r\"found phi $\\angle(x,y)$ wrt photon energy\")\n",
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"\n",
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"a1=ax[1].hist2d(energy_lost, phi_lost/np.pi, bins=200, cmap=plt.cm.jet, cmin=1, range=[[0,2e3],[-1.1,1.1]], vmax=10)\n",
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"#ax[1].set_yticks(np.arange(-1,1.1,0.5), minor=True)\n",
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"ax[1].yaxis.set_major_formatter(tck.FormatStrFormatter('%g $\\pi$'))\n",
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"ax[1].set_xlabel(\"minimal or sum of photon energy [MeV]\")\n",
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"ax[1].set_ylabel(r\"$\\phi$\")\n",
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"ax[1].set_title(\"lost phi wrt photon energy\")\n",
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"\n",
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"\"\"\"\n",
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"Cannot really make out any patterns that might explain lost and found differences.\n",
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"See no materialpeak\n",
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"\"\"\"\n",
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"\n",
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"fig.colorbar(a0[3],ax=ax[1])\n",
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"#plt.style.use(\"ggplot\")\n",
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"plt.show()"
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]
|
2023-10-05 10:49:35 +02:00
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "env1",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
|
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"version": "3.11.5"
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}
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},
|
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"nbformat": 4,
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"nbformat_minor": 2
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}
|
