225 lines
112 KiB
Plaintext
225 lines
112 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": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import uproot\t\n",
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"from mpl_toolkits import mplot3d\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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"%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": 2,
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"metadata": {},
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"outputs": [],
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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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"file = uproot.open(\n",
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" \"tracking_losses_ntuple_B_rad_length_beginVelo2endVelo.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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"\n",
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"electrons = allcolumns[(allcolumns.isElectron) & (allcolumns.fromB)]"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"p = ak.to_numpy(electrons[\"p\"])\n",
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"p_velo = ak.to_numpy(electrons[\"p_end_velo\"])\n",
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"p_ut = ak.to_numpy(electrons[\"p_end_ut\"])"
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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": 10,
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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 640x480 with 2 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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"xlim = 20000\n",
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"ax = plt.hist2d(p, p_velo, bins=80, range=[[0, xlim], [0, xlim]], cmin=1, vmax=250)\n",
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"plt.colorbar(ax[3])\n",
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"plt.xlabel(f\"True$P$ [MeV]\")\n",
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"plt.ylabel(f\"EndVELO$P$ [MeV]\")\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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"execution_count": 11,
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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 640x480 with 2 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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"xlim = 20000\n",
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"ax = plt.hist2d(p,\n",
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" p_ut,\n",
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" bins=80,\n",
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" range=[[0, xlim], [0, xlim]],\n",
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" cmin=1,\n",
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" vmax=250)\n",
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"plt.colorbar(ax[3])\n",
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"plt.xlabel(f\"True$P$ [MeV]\")\n",
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"plt.ylabel(f\"EndUT$P$ [MeV]\")\n",
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"plt.show()"
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]
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},
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|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 21,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 640x480 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"dvelo = p - p_velo\n",
|
||
|
|
"dut = p - p_ut - dvelo\n",
|
||
|
|
"xlim = 1\n",
|
||
|
|
"nbins = 80\n",
|
||
|
|
"\n",
|
||
|
|
"plt.hist(\n",
|
||
|
|
" dvelo / p,\n",
|
||
|
|
" bins=nbins,\n",
|
||
|
|
" density=True,\n",
|
||
|
|
" alpha=0.5,\n",
|
||
|
|
" histtype=\"bar\",\n",
|
||
|
|
" color=\"darkorange\",\n",
|
||
|
|
" label=\"VELO\",\n",
|
||
|
|
" range=[-xlim, xlim],\n",
|
||
|
|
")\n",
|
||
|
|
"plt.hist(\n",
|
||
|
|
" dut / p,\n",
|
||
|
|
" bins=nbins,\n",
|
||
|
|
" density=True,\n",
|
||
|
|
" alpha=0.5,\n",
|
||
|
|
" histtype=\"bar\",\n",
|
||
|
|
" color=\"blue\",\n",
|
||
|
|
" label=\"UT\",\n",
|
||
|
|
" range=[-xlim, xlim],\n",
|
||
|
|
")\n",
|
||
|
|
"plt.xlim(0, xlim)\n",
|
||
|
|
"# plt.yscale(\"log\")\n",
|
||
|
|
"plt.title(\"emitted energy difference ratio\")\n",
|
||
|
|
"plt.xlabel(r\"$(E_0 - (E_{VELO} , E_{RICH1+UT}))/E_0$\")\n",
|
||
|
|
"plt.ylabel(\"a.u.\")\n",
|
||
|
|
"plt.legend()\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 19,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 640x480 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.hist(\n",
|
||
|
|
" (dut - dvelo) / p,\n",
|
||
|
|
" bins=nbins,\n",
|
||
|
|
" density=True,\n",
|
||
|
|
" alpha=0.5,\n",
|
||
|
|
" histtype=\"bar\",\n",
|
||
|
|
" color=\"blue\",\n",
|
||
|
|
" label=\"UT\",\n",
|
||
|
|
" range=[-xlim, xlim],\n",
|
||
|
|
")\n",
|
||
|
|
"# plt.xlim(0, xlim)\n",
|
||
|
|
"# plt.yscale(\"log\")\n",
|
||
|
|
"plt.title(\"emitted energy difference ratio\")\n",
|
||
|
|
"plt.xlabel(r\"$(E_{VELO} - E_{RICH1+UT})$ [MeV]\")\n",
|
||
|
|
"plt.ylabel(\"a.u.\")\n",
|
||
|
|
"plt.legend()\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"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
|
||
|
|
}
|