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Projektpraktikum/trackinglosses_rad_length_b...

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import uproot\t\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"from matplotlib import colormaps\n",
"from mpl_toolkits import mplot3d\n",
"import awkward as ak\n",
"from scipy.optimize import curve_fit\n",
"from scipy import stats\n",
"from methods.fit_linear_regression_model import fit_linear_regression_model\n",
"import sklearn\n",
"import seaborn as sns\n",
"import pandas as pd\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"def round(n, k):\n",
" # function to round number 'n' up/down to nearest 'k'\n",
" # use positive k to round up\n",
" # use negative k to round down\n",
"\n",
" return n - n % k"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"41978 8523\n",
"49865\n"
]
}
],
"source": [
"file = uproot.open(\n",
" \"tracking_losses_ntuple_B_rad_length_beginVelo2endVelo.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n",
")\n",
"\n",
"# selektiere nur elektronen von B->K*ee\n",
"allcolumns = file.arrays()\n",
"found = allcolumns[(allcolumns.isElectron) & (~allcolumns.lost) & (allcolumns.fromB)]\n",
"lost = allcolumns[(allcolumns.isElectron) & (allcolumns.lost) & (allcolumns.fromB)]\n",
"\n",
"electrons = allcolumns[\n",
" (allcolumns.isElectron)\n",
" & (allcolumns.fromB)\n",
" & (allcolumns.eta <= 5.0)\n",
" & (allcolumns.eta >= 1.5)\n",
" & (np.abs(allcolumns.phi) < 3.142)\n",
"]\n",
"\n",
"print(ak.num(found, axis=0), ak.num(lost, axis=0))\n",
"print(ak.num(electrons, axis=0))\n",
"# ak.count(found, axis=None)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# variables\n",
"\n",
"eta_a = ak.to_numpy(electrons[\"eta\"])\n",
"phi_a = ak.to_numpy(electrons[\"phi\"])\n",
"rad_length_frac_a = ak.to_numpy(electrons[\"rad_length_frac\"])"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.hist(\n",
" rad_length_frac_a,\n",
" bins=100,\n",
" density=True,\n",
" alpha=0.5,\n",
" color=\"blue\",\n",
" histtype=\"bar\",\n",
" range=[0, 1],\n",
")\n",
"plt.xlim(0, 1)\n",
"# plt.yscale(\"log\")\n",
"plt.title(\"radiation length fraction beginVelo2endVelo\")\n",
"plt.xlabel(f\"$x/X_0$\")\n",
"plt.ylabel(\"a.u.\")\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"df = pd.DataFrame(\n",
" {\n",
" \"phi\": phi_a * 90.0 / np.pi,\n",
" \"eta\": eta_a * 2.0,\n",
" \"rad_length_frac\": rad_length_frac_a,\n",
" }\n",
")\n",
"df = df.round({\"phi\": 0, \"eta\": 1, \"rad_length_frac\": 4})"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"df_pivoted = df.pivot_table(\n",
" index=\"eta\",\n",
" columns=\"phi\",\n",
" values=\"rad_length_frac\",\n",
" margins=False,\n",
" # fill_value=0,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th>phi</th>\n",
" <th>-90.0</th>\n",
" <th>-89.0</th>\n",
" <th>-88.0</th>\n",
" <th>-87.0</th>\n",
" <th>-86.0</th>\n",
" <th>-85.0</th>\n",
" <th>-84.0</th>\n",
" <th>-83.0</th>\n",
" <th>-82.0</th>\n",
" <th>-81.0</th>\n",
" <th>...</th>\n",
" <th>81.0</th>\n",
" <th>82.0</th>\n",
" <th>83.0</th>\n",
" <th>84.0</th>\n",
" <th>85.0</th>\n",
" <th>86.0</th>\n",
" <th>87.0</th>\n",
" <th>88.0</th>\n",
" <th>89.0</th>\n",
" <th>90.0</th>\n",
" </tr>\n",
" <tr>\n",
" <th>eta</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>3.1</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3.2</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3.3</th>\n",
" <td>NaN</td>\n",
" <td>0.30455</td>\n",
" <td>NaN</td>\n",
" <td>0.526900</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.14755</td>\n",
" <td>NaN</td>\n",
" <td>0.135100</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>0.1247</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3.4</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.459800</td>\n",
" <td>0.1691</td>\n",
" <td>0.1710</td>\n",
" <td>0.26650</td>\n",
" <td>NaN</td>\n",
" <td>0.291200</td>\n",
" <td>0.1778</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.14020</td>\n",
" <td>0.1775</td>\n",
" <td>0.5234</td>\n",
" <td>0.1498</td>\n",
" <td>NaN</td>\n",
" <td>0.14810</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3.5</th>\n",
" <td>NaN</td>\n",
" <td>0.45340</td>\n",
" <td>0.35060</td>\n",
" <td>0.447200</td>\n",
" <td>NaN</td>\n",
" <td>0.1885</td>\n",
" <td>NaN</td>\n",
" <td>0.1711</td>\n",
" <td>0.243100</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>0.2161</td>\n",
" <td>0.1313</td>\n",
" <td>NaN</td>\n",
" <td>0.16210</td>\n",
" <td>NaN</td>\n",
" <td>0.4284</td>\n",
" <td>0.4008</td>\n",
" <td>NaN</td>\n",
" <td>0.24475</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9.6</th>\n",
" <td>NaN</td>\n",
" <td>0.06550</td>\n",
" <td>0.09655</td>\n",
" <td>0.181325</td>\n",
" <td>0.1296</td>\n",
" <td>NaN</td>\n",
" <td>0.25035</td>\n",
" <td>0.0707</td>\n",
" <td>NaN</td>\n",
" <td>0.2469</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0692</td>\n",
" <td>0.2822</td>\n",
" <td>0.26520</td>\n",
" <td>0.1244</td>\n",
" <td>NaN</td>\n",
" <td>0.1084</td>\n",
" <td>0.1665</td>\n",
" <td>0.06750</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9.7</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.070000</td>\n",
" <td>0.0816</td>\n",
" <td>0.0878</td>\n",
" <td>0.07350</td>\n",
" <td>0.0864</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>0.1993</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.14480</td>\n",
" <td>0.0652</td>\n",
" <td>0.0755</td>\n",
" <td>NaN</td>\n",
" <td>0.0796</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9.8</th>\n",
" <td>0.0781</td>\n",
" <td>0.09960</td>\n",
" <td>0.08180</td>\n",
" <td>0.083267</td>\n",
" <td>0.0779</td>\n",
" <td>NaN</td>\n",
" <td>0.08810</td>\n",
" <td>0.1684</td>\n",
" <td>0.140867</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0977</td>\n",
" <td>NaN</td>\n",
" <td>0.13015</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.0821</td>\n",
" <td>0.0646</td>\n",
" <td>0.08440</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9.9</th>\n",
" <td>NaN</td>\n",
" <td>0.09210</td>\n",
" <td>0.08210</td>\n",
" <td>0.071900</td>\n",
" <td>NaN</td>\n",
" <td>0.0936</td>\n",
" <td>0.32600</td>\n",
" <td>0.0748</td>\n",
" <td>0.193300</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>0.0727</td>\n",
" <td>0.1494</td>\n",
" <td>0.0353</td>\n",
" <td>NaN</td>\n",
" <td>0.3264</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.0844</td>\n",
" <td>0.07660</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10.0</th>\n",
" <td>NaN</td>\n",
" <td>0.05840</td>\n",
" <td>NaN</td>\n",
" <td>0.070600</td>\n",
" <td>NaN</td>\n",
" <td>0.0578</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0785</td>\n",
" <td>0.0915</td>\n",
" <td>0.03070</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.07090</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>70 rows × 181 columns</p>\n",
"</div>"
],
"text/plain": [
"phi -90.0 -89.0 -88.0 -87.0 -86.0 -85.0 -84.0 -83.0 \\\n",
"eta \n",
"3.1 NaN NaN NaN NaN NaN NaN NaN NaN \n",
"3.2 NaN NaN NaN NaN NaN NaN NaN NaN \n",
"3.3 NaN 0.30455 NaN 0.526900 NaN NaN 0.14755 NaN \n",
"3.4 NaN NaN NaN 0.459800 0.1691 0.1710 0.26650 NaN \n",
"3.5 NaN 0.45340 0.35060 0.447200 NaN 0.1885 NaN 0.1711 \n",
"... ... ... ... ... ... ... ... ... \n",
"9.6 NaN 0.06550 0.09655 0.181325 0.1296 NaN 0.25035 0.0707 \n",
"9.7 NaN NaN NaN 0.070000 0.0816 0.0878 0.07350 0.0864 \n",
"9.8 0.0781 0.09960 0.08180 0.083267 0.0779 NaN 0.08810 0.1684 \n",
"9.9 NaN 0.09210 0.08210 0.071900 NaN 0.0936 0.32600 0.0748 \n",
"10.0 NaN 0.05840 NaN 0.070600 NaN 0.0578 NaN NaN \n",
"\n",
"phi -82.0 -81.0 ... 81.0 82.0 83.0 84.0 85.0 86.0 \\\n",
"eta ... \n",
"3.1 NaN NaN ... NaN NaN NaN NaN NaN NaN \n",
"3.2 NaN NaN ... NaN NaN NaN NaN NaN NaN \n",
"3.3 0.135100 NaN ... 0.1247 NaN NaN NaN NaN NaN \n",
"3.4 0.291200 0.1778 ... NaN NaN NaN 0.14020 0.1775 0.5234 \n",
"3.5 0.243100 NaN ... 0.2161 0.1313 NaN 0.16210 NaN 0.4284 \n",
"... ... ... ... ... ... ... ... ... ... \n",
"9.6 NaN 0.2469 ... NaN 0.0692 0.2822 0.26520 0.1244 NaN \n",
"9.7 NaN NaN ... 0.1993 NaN NaN 0.14480 0.0652 0.0755 \n",
"9.8 0.140867 NaN ... NaN 0.0977 NaN 0.13015 NaN NaN \n",
"9.9 0.193300 NaN ... 0.0727 0.1494 0.0353 NaN 0.3264 NaN \n",
"10.0 NaN NaN ... NaN 0.0785 0.0915 0.03070 NaN NaN \n",
"\n",
"phi 87.0 88.0 89.0 90.0 \n",
"eta \n",
"3.1 NaN NaN NaN NaN \n",
"3.2 NaN NaN NaN NaN \n",
"3.3 NaN NaN NaN NaN \n",
"3.4 0.1498 NaN 0.14810 NaN \n",
"3.5 0.4008 NaN 0.24475 NaN \n",
"... ... ... ... ... \n",
"9.6 0.1084 0.1665 0.06750 NaN \n",
"9.7 NaN 0.0796 NaN NaN \n",
"9.8 0.0821 0.0646 0.08440 NaN \n",
"9.9 NaN 0.0844 0.07660 NaN \n",
"10.0 NaN NaN 0.07090 NaN \n",
"\n",
"[70 rows x 181 columns]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_pivoted"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ax = sns.heatmap(\n",
" df_pivoted,\n",
" robust=False,\n",
" square=False,\n",
" cmap=colormaps[\"rainbow\"],\n",
" xticklabels=False,\n",
" yticklabels=False,\n",
" vmax=0.8,\n",
")\n",
"# ax.set_yticks([5, 15, 25, 35], [2, 3, 4, 5])\n",
"ax.set_yticks([10, 30, 50, 70], [2, 3, 4, 5])\n",
"ax.set_xticks([39, 89, 139], [-100, 0, 100])\n",
"# ax.set_xticks([79, 179, 279], [-100, 0, 100])\n",
"ax.set_xlabel(f\"$\\phi$ [deg]\")\n",
"ax.set_ylabel(f\"$\\eta$\")\n",
"\n",
"# ax.set_yticklabels([])\n",
"ax.invert_yaxis()\n",
"ax.set_title(\"LHCb VELO $x/X_0$\")\n",
"plt.show()"
]
},
{
"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
}