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thesis TMVA

master
cetin 8 months ago
parent
commit
ff372c2385
  1. 72
      notebooks/thesis_efficiencies.ipynb
  2. 26
      notebooks/thesis_electrons.ipynb

72
notebooks/thesis_efficiencies.ipynb

@ -50,7 +50,9 @@
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"control eff: 0.8626619913200968\n", "control eff: 0.8626619913200968\n",
"new eff: 0.8626619913200968\n"
"new eff: 0.8626619913200968\n",
"control eff: 0.8629752409817771\n",
"new eff: 0.8629752409817771\n"
] ]
} }
], ],
@ -59,24 +61,8 @@
"P_Velo_recoable = file[\"01_long_EndVelo_P_reconstructible;1\"].to_numpy()\n", "P_Velo_recoable = file[\"01_long_EndVelo_P_reconstructible;1\"].to_numpy()\n",
"\n", "\n",
"print(\"control eff: \", np.sum(P_recoed[0]) / np.sum(P_recoable[0]))\n", "print(\"control eff: \", np.sum(P_recoed[0]) / np.sum(P_recoable[0]))\n",
"print(\"new eff: \", np.sum(P_Velo_recoed[0]) / np.sum(P_Velo_recoable[0]))"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"control eff: 0.8629752409817771\n",
"new eff: 0.8629752409817771\n"
]
}
],
"source": [
"print(\"new eff: \", np.sum(P_Velo_recoed[0]) / np.sum(P_Velo_recoable[0]))\n",
"\n",
"Pt_Velo_recoed = file[\"01_long_EndVelo_Pt_reconstructed;1\"].to_numpy()\n", "Pt_Velo_recoed = file[\"01_long_EndVelo_Pt_reconstructed;1\"].to_numpy()\n",
"Pt_Velo_recoable = file[\"01_long_EndVelo_Pt_reconstructible;1\"].to_numpy()\n", "Pt_Velo_recoable = file[\"01_long_EndVelo_Pt_reconstructible;1\"].to_numpy()\n",
"\n", "\n",
@ -86,32 +72,27 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 27,
"execution_count": 4,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "data": {
"text/plain": [ "text/plain": [
"(array([1.00000e+00, 8.01040e+04, 2.49215e+05, 2.50095e+05, 2.10569e+05,\n",
" 1.75027e+05, 1.46219e+05, 1.23088e+05, 1.05255e+05, 9.01970e+04,\n",
" 7.85600e+04, 6.79570e+04, 5.95880e+04, 5.19260e+04, 4.65560e+04,\n",
" 4.07310e+04, 3.72930e+04, 3.35370e+04, 3.01050e+04, 2.72980e+04,\n",
" 2.47460e+04, 2.24910e+04, 2.05840e+04, 1.88150e+04, 1.72910e+04,\n",
" 1.57940e+04, 1.46220e+04, 1.34730e+04, 1.24900e+04, 1.14550e+04,\n",
" 1.07880e+04, 9.95800e+03, 9.23400e+03, 8.56100e+03, 7.91100e+03,\n",
" 7.36700e+03, 6.80700e+03, 6.42800e+03, 6.11500e+03, 5.63900e+03,\n",
" 5.26200e+03, 4.91100e+03, 4.66800e+03, 4.39400e+03, 4.05300e+03,\n",
" 3.75000e+03, 3.49800e+03, 3.30800e+03, 3.20800e+03, 3.03300e+03,\n",
" 2.88100e+03, 2.72300e+03, 2.41900e+03, 2.42900e+03, 2.21800e+03,\n",
" 2.17500e+03, 1.99500e+03, 1.91400e+03, 1.77100e+03, 1.66700e+03,\n",
" 1.64800e+03, 1.49800e+03, 1.46400e+03, 1.40000e+03, 1.33000e+03,\n",
" 1.23000e+03, 1.19300e+03, 1.11400e+03, 1.08300e+03, 1.02700e+03,\n",
" 9.94000e+02, 9.44000e+02, 8.81000e+02, 8.85000e+02, 7.90000e+02,\n",
" 7.94000e+02, 7.77000e+02, 7.05000e+02, 7.03000e+02, 7.09000e+02,\n",
" 6.45000e+02, 5.87000e+02, 5.93000e+02, 5.35000e+02, 5.48000e+02,\n",
" 4.68000e+02, 4.67000e+02, 4.58000e+02, 4.70000e+02, 4.26000e+02,\n",
" 4.30000e+02, 4.23000e+02, 4.11000e+02, 3.76000e+02, 3.56000e+02,\n",
" 3.49000e+02, 3.05000e+02, 3.24000e+02, 2.83000e+02, 3.18000e+02]),\n",
"(array([ 0., 39546., 175333., 205172., 179814., 156192., 131918.,\n",
" 111561., 96269., 82605., 72104., 62481., 54880., 48023.,\n",
" 43043., 37810., 34533., 31242., 27997., 25422., 23137.,\n",
" 20994., 19297., 17662., 16196., 14804., 13679., 12636.,\n",
" 11687., 10738., 10125., 9329., 8681., 8080., 7424.,\n",
" 6950., 6416., 6048., 5771., 5304., 4963., 4611.,\n",
" 4379., 4095., 3844., 3512., 3303., 3104., 3020.,\n",
" 2839., 2717., 2549., 2297., 2287., 2076., 2030.,\n",
" 1875., 1791., 1684., 1557., 1559., 1418., 1389.,\n",
" 1321., 1245., 1164., 1122., 1055., 1008., 961.,\n",
" 920., 899., 833., 839., 746., 744., 725.,\n",
" 656., 657., 673., 601., 547., 552., 504.,\n",
" 524., 452., 440., 427., 438., 395., 412.,\n",
" 408., 392., 349., 328., 328., 289., 308.,\n",
" 271., 297.]),\n",
" array([ 0., 1000., 2000., 3000., 4000., 5000., 6000.,\n", " array([ 0., 1000., 2000., 3000., 4000., 5000., 6000.,\n",
" 7000., 8000., 9000., 10000., 11000., 12000., 13000.,\n", " 7000., 8000., 9000., 10000., 11000., 12000., 13000.,\n",
" 14000., 15000., 16000., 17000., 18000., 19000., 20000.,\n", " 14000., 15000., 16000., 17000., 18000., 19000., 20000.,\n",
@ -129,13 +110,13 @@
" 98000., 99000., 100000.]))" " 98000., 99000., 100000.]))"
] ]
}, },
"execution_count": 27,
"execution_count": 4,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
], ],
"source": [ "source": [
"P_recoable"
"P_recoed"
] ]
}, },
{ {
@ -152,6 +133,13 @@
"outputs": [], "outputs": [],
"source": [] "source": []
}, },
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": null,

26
notebooks/thesis_electrons.ipynb

@ -2,7 +2,7 @@
"cells": [ "cells": [
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 10,
"execution_count": 1,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
@ -25,7 +25,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 11,
"execution_count": 2,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -34,14 +34,14 @@
"50501" "50501"
] ]
}, },
"execution_count": 11,
"execution_count": 2,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
], ],
"source": [ "source": [
"file = uproot.open(\n", "file = uproot.open(\n",
" \"/work/cetin/Projektpraktikum/tracking_losses_ntuple_B_thesis.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n",
" \"/work/cetin/LHCb/reco_tuner/data/tracking_losses_ntuple_B_thesis.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n",
")\n", ")\n",
"\n", "\n",
"# selektiere nur elektronen von B->K*ee\n", "# selektiere nur elektronen von B->K*ee\n",
@ -54,7 +54,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 12,
"execution_count": 3,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
@ -63,7 +63,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 13,
"execution_count": 3,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
@ -76,14 +76,16 @@
"\n", "\n",
"eloss = (electrons[\"p\"] - electrons[\"p_end_scifi\"]) / electrons[\"p\"]\n", "eloss = (electrons[\"p\"] - electrons[\"p_end_scifi\"]) / electrons[\"p\"]\n",
"eloss_magnet_found = ak.to_numpy(\n", "eloss_magnet_found = ak.to_numpy(\n",
" (found[\"p_end_velo\"] - found[\"p_end_scifi\"]) / found[\"p_end_velo\"])\n",
" (found[\"p_end_velo\"] - found[\"p_end_scifi\"]) / found[\"p_end_velo\"]\n",
")\n",
"eloss_magnet_lost = ak.to_numpy(\n", "eloss_magnet_lost = ak.to_numpy(\n",
" (lost[\"p_end_velo\"] - lost[\"p_end_scifi\"]) / lost[\"p_end_velo\"])"
" (lost[\"p_end_velo\"] - lost[\"p_end_scifi\"]) / lost[\"p_end_velo\"]\n",
")"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 14,
"execution_count": 4,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
@ -93,7 +95,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 15,
"execution_count": 5,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -144,7 +146,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 16,
"execution_count": 7,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -194,7 +196,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 17,
"execution_count": 8,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {

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