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201 lines
104 KiB
201 lines
104 KiB
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 25,
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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 matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"import mplhep\n",
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"import awkward as ak\n",
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"import pandas as pd\n",
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"import seaborn as sns\n",
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"\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": 26,
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"metadata": {},
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"outputs": [],
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"source": [
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"tree = uproot.open({\n",
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" \"/work/cetin/LHCb/reco_tuner/data_matching/parameterisations/sample4/param_data_B_default_thesis_selected.root\":\n",
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" \"Selected\"\n",
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"})\n",
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"allcols = tree.arrays()\n",
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"allcols = allcols[allcols.isElectron == 1]"
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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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"zMagnetParamsEndT = [\n",
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" 5283.043384741342,\n",
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" 28.45437483916609,\n",
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" 0.016308934185688337,\n",
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" -1668.3602223088105,\n",
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" 301.07580662497,\n",
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"]\n",
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"dSlope_xEndT = allcols.tx_l11 - allcols.tx\n",
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"dSlope_xEndT_abs = abs(dSlope_xEndT)\n",
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"x_EndT_abs = abs(allcols.x_l11 + allcols.tx_l11 * (9410.0 - allcols.z_l11))\n",
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"\n",
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"zMagTerm = zMagnetParamsEndT[0] + zMagnetParamsEndT[3] * allcols.tx * allcols.tx\n",
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"\n",
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"z_mag_xEndT = (\n",
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" zMagTerm + dSlope_xEndT_abs *\n",
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" (zMagnetParamsEndT[1] + zMagnetParamsEndT[4] * dSlope_xEndT_abs) +\n",
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" zMagnetParamsEndT[2] * x_EndT_abs)"
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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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"source": [
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"zmag = (allcols[\"x\"] - allcols[\"x_l11\"] - allcols[\"tx\"] * allcols[\"z\"] +\n",
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" allcols[\"tx_l11\"] * allcols[\"z_l11\"]) / dSlope_xEndT"
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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": 29,
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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": [
|
|
"<Figure size 1200x900 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.hist(\n",
|
|
" zmag,\n",
|
|
" bins=50,\n",
|
|
" alpha=0.5,\n",
|
|
" density=True,\n",
|
|
" color=\"#107E7D\",\n",
|
|
" label=\"True\",\n",
|
|
")\n",
|
|
"plt.hist(\n",
|
|
" z_mag_xEndT,\n",
|
|
" bins=50,\n",
|
|
" alpha=0.5,\n",
|
|
" density=True,\n",
|
|
" color=\"#F05342\",\n",
|
|
" label=\"Predicted\",\n",
|
|
")\n",
|
|
"plt.xlabel(r\"$z_{mag}$\")\n",
|
|
"plt.ylabel(\"Number of tracks (normalised)\")\n",
|
|
"mplhep.lhcb.text(\"Simulation\", loc=0)\n",
|
|
"plt.legend(loc=\"upper right\")\n",
|
|
"# plt.savefig(\n",
|
|
"# \"/work/cetin/LHCb/reco_tuner/thesis/zmag_new_parameterisation.pdf\", format=\"PDF\"\n",
|
|
"# )\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 35,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"True"
|
|
]
|
|
},
|
|
"execution_count": 35,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"weird = zmag < 5200\n",
|
|
"True in weird"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 32,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1200x900 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"array = {\"z_mag\": zmag, \"z_mag_pred\": z_mag_xEndT, \"diff\": zmag - z_mag_xEndT}\n",
|
|
"df = pd.DataFrame(array)\n",
|
|
"sns.regplot(data=df, x=\"z_mag\", y=\"diff\", x_bins=30, fit_reg=False)\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
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