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1139 lines
147 KiB
1139 lines
147 KiB
{
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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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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"41978 8523\n",
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"50501\n"
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]
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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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"file = uproot.open(\n",
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" \"tracking_losses_ntuple_B_EndVeloP.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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"found = allcolumns[(allcolumns.isElectron) & (~allcolumns.lost) &\n",
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" (allcolumns.fromB)] # B: 9056\n",
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"lost = allcolumns[(allcolumns.isElectron) & (allcolumns.lost) &\n",
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" (allcolumns.fromB)] # B: 1466\n",
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"\n",
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"electrons = allcolumns[(allcolumns.isElectron) & (allcolumns.fromB)]\n",
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"\n",
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"print(ak.num(found, axis=0), ak.num(lost, axis=0))\n",
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"print(ak.num(electrons, 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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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<pre>{all_endvtx_types_length: 7,\n",
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" all_endvtx_types: [101, 101, 101, 101, 101, 101, 0],\n",
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" all_endvtx_x_length: 7,\n",
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" all_endvtx_x: [-6.97, -52.9, -52.9, ..., -1.71e+03, -2.14e+03, -3.57e+03],\n",
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" all_endvtx_y_length: 7,\n",
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" all_endvtx_y: [-0.89, -6.75, -6.75, -7.08, -66.1, -72.6, -39.5],\n",
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" all_endvtx_z_length: 7,\n",
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" all_endvtx_z: [112, 859, 859, 895, 8.7e+03, 9.68e+03, 1.26e+04],\n",
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" brem_photons_pe_length: 6,\n",
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" brem_photons_pe: [2.62e+03, 812, 2.54e+03, 1.86e+03, 3.12e+03, 241],\n",
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" brem_photons_px_length: 6,\n",
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" brem_photons_px: [-161, -49.7, -156, -114, -1.18e+03, -101],\n",
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" brem_photons_py_length: 6,\n",
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" brem_photons_py: [-18.9, -6.92, -21.6, -16.8, -20.9, -0.26],\n",
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" brem_photons_pz_length: 6,\n",
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" brem_photons_pz: [2.61e+03, 810, 2.54e+03, 1.86e+03, 2.89e+03, 219],\n",
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" brem_vtx_x_length: 6,\n",
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" brem_vtx_x: [-6.97, -52.9, -52.9, -55.2, -1.71e+03, -2.14e+03],\n",
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" brem_vtx_y_length: 6,\n",
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" ...}\n",
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"---------------------------------------------------------------------------\n",
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"type: {\n",
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" all_endvtx_types_length: int32,\n",
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" all_endvtx_types: var * float32,\n",
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" all_endvtx_x_length: int32,\n",
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" all_endvtx_x: var * float32,\n",
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" all_endvtx_y_length: int32,\n",
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" all_endvtx_y: var * float32,\n",
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" all_endvtx_z_length: int32,\n",
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" all_endvtx_z: var * float32,\n",
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" brem_photons_pe_length: int32,\n",
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" brem_photons_pe: var * float32,\n",
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" brem_photons_px_length: int32,\n",
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" brem_photons_px: var * float32,\n",
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" brem_photons_py_length: int32,\n",
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" brem_photons_py: var * float32,\n",
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" brem_photons_pz_length: int32,\n",
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" brem_photons_pz: var * float32,\n",
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" brem_vtx_x_length: int32,\n",
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" brem_vtx_x: var * float32,\n",
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" brem_vtx_y_length: int32,\n",
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" brem_vtx_y: var * float32,\n",
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" brem_vtx_z_length: int32,\n",
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" brem_vtx_z: var * float32,\n",
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" endvtx_type: int32,\n",
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" endvtx_x: float64,\n",
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" endvtx_y: float64,\n",
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" endvtx_z: float64,\n",
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" energy: float64,\n",
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" eta: float64,\n",
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" event_count: int32,\n",
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" fromB: bool,\n",
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" fromD: bool,\n",
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" fromDecay: bool,\n",
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" fromHadInt: bool,\n",
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" fromPV: bool,\n",
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" fromPairProd: bool,\n",
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" fromSignal: bool,\n",
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" fromStrange: bool,\n",
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" ideal_state_770_qop: float64,\n",
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" ideal_state_770_tx: float64,\n",
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" ideal_state_770_ty: float64,\n",
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" ideal_state_770_x: float64,\n",
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" ideal_state_770_y: float64,\n",
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" ideal_state_770_z: float64,\n",
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" ideal_state_9410_qop: float64,\n",
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" ideal_state_9410_tx: float64,\n",
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" ideal_state_9410_ty: float64,\n",
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" ideal_state_9410_x: float64,\n",
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" ideal_state_9410_y: float64,\n",
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" ideal_state_9410_z: float64,\n",
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" isElectron: bool,\n",
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" isKaon: bool,\n",
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" isMuon: bool,\n",
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" isPion: bool,\n",
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" isProton: bool,\n",
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" lost: bool,\n",
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" lost_in_track_fit: bool,\n",
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" match_fraction: float32,\n",
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" mc_chi2: float32,\n",
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" mc_dSlope: float32,\n",
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" mc_dSlopeY: float32,\n",
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" mc_distX: float32,\n",
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" mc_distY: float32,\n",
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" mc_teta2: float32,\n",
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" mc_zMag: float32,\n",
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" mcp_idx: int32,\n",
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" mother_id: int32,\n",
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" mother_key: int32,\n",
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" originvtx_type: int32,\n",
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" originvtx_x: float64,\n",
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" originvtx_y: float64,\n",
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" originvtx_z: float64,\n",
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" p: float64,\n",
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" p_end_ut: float64,\n",
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" p_end_velo: float64,\n",
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" phi: float64,\n",
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" pid: int32,\n",
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" pt: float64,\n",
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" px: float64,\n",
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" py: float64,\n",
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" pz: float64,\n",
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" quality: int32,\n",
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" rad_length_frac: float64,\n",
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" scifi_hit_pos_x_length: int32,\n",
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" scifi_hit_pos_x: var * float32,\n",
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" scifi_hit_pos_y_length: int32,\n",
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" scifi_hit_pos_y: var * float32,\n",
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" scifi_hit_pos_z_length: int32,\n",
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" scifi_hit_pos_z: var * float32,\n",
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" track_p: float64,\n",
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" track_pt: float64,\n",
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" tx: float64,\n",
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" ty: float64,\n",
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" ut_hit_pos_x_length: int32,\n",
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" ut_hit_pos_x: var * float32,\n",
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" ut_hit_pos_y_length: int32,\n",
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" ut_hit_pos_y: var * float32,\n",
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" ut_hit_pos_z_length: int32,\n",
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" ut_hit_pos_z: var * float32,\n",
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" velo_hit_pos_x_length: int32,\n",
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" velo_hit_pos_x: var * float32,\n",
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" velo_hit_pos_y_length: int32,\n",
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" velo_hit_pos_y: var * float32,\n",
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" velo_hit_pos_z_length: int32,\n",
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" velo_hit_pos_z: var * float32,\n",
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" velo_track_idx: int32,\n",
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" velo_track_tx: float64,\n",
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" velo_track_ty: float64,\n",
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" velo_track_x: float64,\n",
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" velo_track_y: float64,\n",
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" velo_track_z: float64\n",
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"}</pre>"
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],
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"text/plain": [
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"<Record {all_endvtx_types_length: 7, ...} type='{all_endvtx_types_length: i...'>"
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]
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},
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"execution_count": 3,
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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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"electrons[0]"
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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": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<pre>{lost: True,\n",
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" rad_length_frac: 0.129,\n",
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" energy: 1.17e+04,\n",
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" photon_length: 6,\n",
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" brem_photons_pe: [2.62e+03, 812, 2.54e+03, 1.86e+03, 3.12e+03, 241],\n",
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" brem_vtx_x: [-6.97, -52.9, -52.9, -55.2, -1.71e+03, -2.14e+03],\n",
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" brem_vtx_z: [112, 859, 859, 895, 8.7e+03, 9.68e+03]}\n",
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"---------------------------------------------------------------------\n",
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"type: {\n",
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" lost: bool,\n",
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" rad_length_frac: float64,\n",
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" energy: float64,\n",
|
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" photon_length: int64,\n",
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" brem_photons_pe: var * float64,\n",
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" brem_vtx_x: var * float64,\n",
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" brem_vtx_z: var * float64\n",
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"}</pre>"
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],
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"text/plain": [
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"<Record {lost: True, rad_length_frac: ..., ...} type='{lost: bool, rad_leng...'>"
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]
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},
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"execution_count": 4,
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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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"lost_e = electrons[\"lost\"]\n",
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"e = electrons[\"energy\"]\n",
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"brem_pe = electrons[\"brem_photons_pe\"]\n",
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"brem_z = electrons[\"brem_vtx_z\"]\n",
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"brem_x = electrons[\"brem_vtx_x\"]\n",
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"length = electrons[\"brem_vtx_z_length\"]\n",
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"rad_length = electrons[\"rad_length_frac\"]\n",
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"\n",
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"brem = ak.ArrayBuilder()\n",
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"\n",
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"for itr in range(ak.num(electrons, axis=0)):\n",
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" brem.begin_record()\n",
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" brem.field(\"lost\").boolean(lost_e[itr])\n",
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" brem.field(\"rad_length_frac\").append(rad_length[itr])\n",
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" # [:,\"energy\"] energy\n",
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" brem.field(\"energy\").append(e[itr])\n",
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" # [:,\"photon_length\"] number of vertices\n",
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" brem.field(\"photon_length\").integer(length[itr])\n",
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" # [:,\"brem_photons_pe\",:] photon energy\n",
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" brem.field(\"brem_photons_pe\").append(brem_pe[itr])\n",
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" # [:,\"brem_vtx_z\",:] brem vtx z\n",
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" brem.field(\"brem_vtx_x\").append(brem_x[itr])\n",
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" brem.field(\"brem_vtx_z\").append(brem_z[itr])\n",
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" brem.end_record()\n",
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"\n",
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"brem = ak.Array(brem)\n",
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"brem[0]"
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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": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"photon_cut = 0\n",
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"photon_cut_ratio = 0.25\n",
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"\n",
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"cut_brem = ak.ArrayBuilder()\n",
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"\n",
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"for itr in range(ak.num(brem, axis=0)):\n",
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" cut_brem.begin_record()\n",
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" cut_brem.field(\"event_id\").integer(itr)\n",
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" cut_brem.field(\"lost\").boolean(brem[itr, \"lost\"])\n",
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" cut_brem.field(\"rad_length_frac\").real(brem[itr, \"rad_length_frac\"])\n",
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" cut_brem.field(\"energy\").real(brem[itr, \"energy\"])\n",
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"\n",
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" ph_length = brem[itr, \"photon_length\"]\n",
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"\n",
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" tmp_energy = brem[itr, \"energy\"]\n",
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"\n",
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" cut_brem.field(\"brem_photons_pe\")\n",
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" cut_brem.begin_list()\n",
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" for jentry in range(brem[itr, \"photon_length\"]):\n",
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" if (brem[itr, \"brem_vtx_z\", jentry] > 2700\n",
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" or brem[itr, \"brem_photons_pe\", jentry] < photon_cut\n",
|
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" or brem[itr, \"brem_photons_pe\",\n",
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" jentry] < photon_cut_ratio * tmp_energy):\n",
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" ph_length -= 1\n",
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" continue\n",
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" else:\n",
|
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" cut_brem.real(brem[itr, \"brem_photons_pe\", jentry])\n",
|
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" tmp_energy -= brem[itr, \"brem_photons_pe\", jentry]\n",
|
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" cut_brem.end_list()\n",
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"\n",
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" tmp_energy = brem[itr, \"energy\"]\n",
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"\n",
|
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" cut_brem.field(\"brem_vtx_x\")\n",
|
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" cut_brem.begin_list()\n",
|
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" for jentry in range(brem[itr, \"photon_length\"]):\n",
|
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" if (brem[itr, \"brem_vtx_z\", jentry] > 2700\n",
|
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" or brem[itr, \"brem_photons_pe\", jentry] < photon_cut\n",
|
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" or brem[itr, \"brem_photons_pe\",\n",
|
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" jentry] < photon_cut_ratio * tmp_energy):\n",
|
|
" continue\n",
|
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" else:\n",
|
|
" cut_brem.real(brem[itr, \"brem_vtx_x\", jentry])\n",
|
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" tmp_energy -= brem[itr, \"brem_photons_pe\", jentry]\n",
|
|
" cut_brem.end_list()\n",
|
|
"\n",
|
|
" tmp_energy = brem[itr, \"energy\"]\n",
|
|
"\n",
|
|
" cut_brem.field(\"brem_vtx_z\")\n",
|
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" cut_brem.begin_list()\n",
|
|
" for jentry in range(brem[itr, \"photon_length\"]):\n",
|
|
" if (brem[itr, \"brem_vtx_z\", jentry] > 2700\n",
|
|
" or brem[itr, \"brem_photons_pe\", jentry] < photon_cut\n",
|
|
" or brem[itr, \"brem_photons_pe\",\n",
|
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" jentry] < photon_cut_ratio * tmp_energy):\n",
|
|
" continue\n",
|
|
" else:\n",
|
|
" cut_brem.real(brem[itr, \"brem_vtx_z\", jentry])\n",
|
|
" tmp_energy -= brem[itr, \"brem_photons_pe\", jentry]\n",
|
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" cut_brem.end_list()\n",
|
|
"\n",
|
|
" cut_brem.field(\"photon_length\").integer(ph_length)\n",
|
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"\n",
|
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" cut_brem.end_record()\n",
|
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"\n",
|
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"ntuple = ak.Array(cut_brem)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 6,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"19715\n",
|
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"50501\n"
|
|
]
|
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},
|
|
{
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"data": {
|
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"text/html": [
|
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"<pre>{event_id: 0,\n",
|
|
" lost: True,\n",
|
|
" rad_length_frac: 0.129,\n",
|
|
" energy: 1.17e+04,\n",
|
|
" brem_photons_pe: [],\n",
|
|
" brem_vtx_x: [],\n",
|
|
" brem_vtx_z: [],\n",
|
|
" photon_length: 0}\n",
|
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"-----------------------------------\n",
|
|
"type: {\n",
|
|
" event_id: int64,\n",
|
|
" lost: bool,\n",
|
|
" rad_length_frac: float64,\n",
|
|
" energy: float64,\n",
|
|
" brem_photons_pe: var * float64,\n",
|
|
" brem_vtx_x: var * float64,\n",
|
|
" brem_vtx_z: var * float64,\n",
|
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" photon_length: int64\n",
|
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"}</pre>"
|
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],
|
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"text/plain": [
|
|
"<Record {event_id: 0, lost: True, ...} type='{event_id: int64, lost: bool, ...'>"
|
|
]
|
|
},
|
|
"execution_count": 6,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"print(ak.sum(ak.num(ntuple[\"brem_photons_pe\"], axis=1)))\n",
|
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"print(ak.num(ntuple, axis=0))\n",
|
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"ntuple[0]"
|
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]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"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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{
|
|
"cell_type": "code",
|
|
"execution_count": 7,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# nulltuple = ntuple[:7000]\n",
|
|
"# onetuple = ntuple[7000:14000]\n",
|
|
"# twotuple = ntuple[14000:21000]\n",
|
|
"# threetuple = ntuple[21000:28000]\n",
|
|
"# fourtuple = ntuple[28000:35000]\n",
|
|
"# fivetuple = ntuple[35000:42000]\n",
|
|
"# sixtuple = ntuple[42000:49000]\n",
|
|
"# seventuple = ntuple[49000:]\n",
|
|
"\n",
|
|
"# ntuple.nbytes"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 8,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# cut = \"tenCut\"\n",
|
|
"# tree = \"Tree10\"\n",
|
|
"# with uproot.update(\"trackinglosses_B_photon_cuts.root\") as outFile:\n",
|
|
"# #outFile[\"README\"] = \"The Cuts are placed on the photons. noCut: 0*E, first: 0.05*E, second: 0.1*E, etc.\"\n",
|
|
"# outFile.mktree(tree, {cut + \"_event_id\": ntuple[\"event_id\"].type, cut + \"_lost\": ntuple[\"lost\"].type, cut + \"_rad_length_frac\": ntuple[\"rad_length_frac\"].type, cut + \"_energy\": ntuple[\"energy\"].type, cut + \"_brem_photons_pe\": ntuple[\"brem_photons_pe\"].type, cut + \"_brem_vtx_x\": ntuple[\"brem_vtx_x\"].type, cut + \"_brem_vtx_z\": ntuple[\"brem_vtx_z\"].type, cut + \"_photon_length\": ntuple[\"photon_length\"].type} )\n",
|
|
"# outFile[tree].extend( {cut + \"_event_id\": nulltuple[\"event_id\"], cut + \"_lost\": nulltuple[\"lost\"], cut + \"_rad_length_frac\": nulltuple[\"rad_length_frac\"], cut + \"_energy\": nulltuple[\"energy\"], cut + \"_brem_photons_pe\": nulltuple[\"brem_photons_pe\"], cut + \"_brem_vtx_x\": nulltuple[\"brem_vtx_x\"], cut + \"_brem_vtx_z\": nulltuple[\"brem_vtx_z\"], cut + \"_photon_length\": nulltuple[\"photon_length\"]} )\n",
|
|
"# outFile[tree].extend( {cut + \"_event_id\": onetuple[\"event_id\"], cut + \"_lost\": onetuple[\"lost\"], cut + \"_rad_length_frac\": onetuple[\"rad_length_frac\"], cut + \"_energy\": onetuple[\"energy\"], cut + \"_brem_photons_pe\": onetuple[\"brem_photons_pe\"], cut + \"_brem_vtx_x\": onetuple[\"brem_vtx_x\"], cut + \"_brem_vtx_z\": onetuple[\"brem_vtx_z\"], cut + \"_photon_length\": onetuple[\"photon_length\"]} )\n",
|
|
"# outFile[tree].extend( {cut + \"_event_id\": twotuple[\"event_id\"], cut + \"_lost\": twotuple[\"lost\"], cut + \"_rad_length_frac\": twotuple[\"rad_length_frac\"], cut + \"_energy\": twotuple[\"energy\"], cut + \"_brem_photons_pe\": twotuple[\"brem_photons_pe\"], cut + \"_brem_vtx_x\": twotuple[\"brem_vtx_x\"], cut + \"_brem_vtx_z\": twotuple[\"brem_vtx_z\"], cut + \"_photon_length\": twotuple[\"photon_length\"]} )\n",
|
|
"# outFile[tree].extend( {cut + \"_event_id\": threetuple[\"event_id\"], cut + \"_lost\": threetuple[\"lost\"], cut + \"_rad_length_frac\": threetuple[\"rad_length_frac\"], cut + \"_energy\": threetuple[\"energy\"], cut + \"_brem_photons_pe\": threetuple[\"brem_photons_pe\"], cut + \"_brem_vtx_x\": threetuple[\"brem_vtx_x\"], cut + \"_brem_vtx_z\": threetuple[\"brem_vtx_z\"], cut + \"_photon_length\": threetuple[\"photon_length\"]} )\n",
|
|
"# outFile[tree].extend( {cut + \"_event_id\": fourtuple[\"event_id\"], cut + \"_lost\": fourtuple[\"lost\"], cut + \"_rad_length_frac\": fourtuple[\"rad_length_frac\"], cut + \"_energy\": fourtuple[\"energy\"], cut + \"_brem_photons_pe\": fourtuple[\"brem_photons_pe\"], cut + \"_brem_vtx_x\": fourtuple[\"brem_vtx_x\"], cut + \"_brem_vtx_z\": fourtuple[\"brem_vtx_z\"], cut + \"_photon_length\": fourtuple[\"photon_length\"]} )\n",
|
|
"# outFile[tree].extend( {cut + \"_event_id\": fivetuple[\"event_id\"], cut + \"_lost\": fivetuple[\"lost\"], cut + \"_rad_length_frac\": fivetuple[\"rad_length_frac\"], cut + \"_energy\": fivetuple[\"energy\"], cut + \"_brem_photons_pe\": fivetuple[\"brem_photons_pe\"], cut + \"_brem_vtx_x\": fivetuple[\"brem_vtx_x\"], cut + \"_brem_vtx_z\": fivetuple[\"brem_vtx_z\"], cut + \"_photon_length\": fivetuple[\"photon_length\"]} )\n",
|
|
"# outFile[tree].extend( {cut + \"_event_id\": sixtuple[\"event_id\"], cut + \"_lost\": sixtuple[\"lost\"], cut + \"_rad_length_frac\": sixtuple[\"rad_length_frac\"], cut + \"_energy\": sixtuple[\"energy\"], cut + \"_brem_photons_pe\": sixtuple[\"brem_photons_pe\"], cut + \"_brem_vtx_x\": sixtuple[\"brem_vtx_x\"], cut + \"_brem_vtx_z\": sixtuple[\"brem_vtx_z\"], cut + \"_photon_length\": sixtuple[\"photon_length\"]} )\n",
|
|
"# outFile[tree].extend( {cut + \"_event_id\": seventuple[\"event_id\"], cut + \"_lost\": seventuple[\"lost\"], cut + \"_rad_length_frac\": seventuple[\"rad_length_frac\"], cut + \"_energy\": seventuple[\"energy\"], cut + \"_brem_photons_pe\": seventuple[\"brem_photons_pe\"], cut + \"_brem_vtx_x\": seventuple[\"brem_vtx_x\"], cut + \"_brem_vtx_z\": seventuple[\"brem_vtx_z\"], cut + \"_photon_length\": seventuple[\"photon_length\"]} )"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 9,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"50501\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<pre>{event_id: 1,\n",
|
|
" lost: False,\n",
|
|
" rad_length_frac: 0.148,\n",
|
|
" energy: 1.28e+04,\n",
|
|
" brem_photons_pe: [7.42e+03],\n",
|
|
" brem_vtx_x: [-3.61],\n",
|
|
" brem_vtx_z: [35.6],\n",
|
|
" photon_length: 1}\n",
|
|
"-----------------------------------\n",
|
|
"type: {\n",
|
|
" event_id: int64,\n",
|
|
" lost: bool,\n",
|
|
" rad_length_frac: float64,\n",
|
|
" energy: float64,\n",
|
|
" brem_photons_pe: var * float64,\n",
|
|
" brem_vtx_x: var * float64,\n",
|
|
" brem_vtx_z: var * float64,\n",
|
|
" photon_length: int64\n",
|
|
"}</pre>"
|
|
],
|
|
"text/plain": [
|
|
"<Record {event_id: 1, lost: False, ...} type='{event_id: int64, lost: bool,...'>"
|
|
]
|
|
},
|
|
"execution_count": 9,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# data in cut_brem_found and cut_brem_lost\n",
|
|
"\n",
|
|
"length_found = ak.num(ntuple[~ntuple.lost][\"brem_photons_pe\"], axis=0)\n",
|
|
"length_lost = ak.num(ntuple[ntuple.lost][\"brem_photons_pe\"], axis=0)\n",
|
|
"print(length_found + length_lost)\n",
|
|
"ntuple[1]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 10,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"Z_found = ak.to_numpy(\n",
|
|
" ak.sum(ntuple[~ntuple.lost][\"brem_photons_pe\"], axis=-1, keepdims=False)\n",
|
|
") / ak.to_numpy(ntuple[~ntuple.lost][\"energy\"])\n",
|
|
"Z_lost = ak.to_numpy(\n",
|
|
" ak.sum(ntuple[ntuple.lost][\"brem_photons_pe\"], axis=-1, keepdims=False)\n",
|
|
") / ak.to_numpy(ntuple[ntuple.lost][\"energy\"])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 11,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"xlim = 0\n",
|
|
"\n",
|
|
"plt.hist(\n",
|
|
" Z_lost,\n",
|
|
" bins=100,\n",
|
|
" density=True,\n",
|
|
" alpha=0.5,\n",
|
|
" histtype=\"bar\",\n",
|
|
" color=\"darkorange\",\n",
|
|
" label=\"lost\",\n",
|
|
" range=[xlim, 1],\n",
|
|
")\n",
|
|
"plt.hist(\n",
|
|
" Z_found,\n",
|
|
" bins=100,\n",
|
|
" density=True,\n",
|
|
" alpha=0.5,\n",
|
|
" histtype=\"bar\",\n",
|
|
" color=\"blue\",\n",
|
|
" label=\"found\",\n",
|
|
" range=[xlim, 1],\n",
|
|
")\n",
|
|
"plt.yscale(\"log\")\n",
|
|
"plt.xlabel(r\"$E_\\gamma/E_0$\")\n",
|
|
"plt.ylabel(\"a.u.\")\n",
|
|
"plt.title(r\"$E_{ph}/E_0$\")\n",
|
|
"plt.legend()\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 12,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"found: 15673 , lost: 4042\n",
|
|
"0.2578957442735915\n"
|
|
]
|
|
},
|
|
{
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"data": {
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"text/html": [
|
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"<pre>[-3.61,\n",
|
|
" -33.8,\n",
|
|
" 65.2,\n",
|
|
" -26.6,\n",
|
|
" 31.6,\n",
|
|
" -52.1,\n",
|
|
" -44.7,\n",
|
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" -103,\n",
|
|
" -10.2,\n",
|
|
" -47.1,\n",
|
|
" ...,\n",
|
|
" -25.5,\n",
|
|
" -90.3,\n",
|
|
" 55.2,\n",
|
|
" 152,\n",
|
|
" -144,\n",
|
|
" 330,\n",
|
|
" -13.1,\n",
|
|
" -4.27,\n",
|
|
" -17.8]\n",
|
|
"---------------------\n",
|
|
"type: 15673 * float64</pre>"
|
|
],
|
|
"text/plain": [
|
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"<Array [-3.61, -33.8, 65.2, ..., -13.1, -4.27, -17.8] type='15673 * float64'>"
|
|
]
|
|
},
|
|
"execution_count": 12,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"tuple_found = ntuple[~ntuple.lost]\n",
|
|
"tuple_lost = ntuple[ntuple.lost]\n",
|
|
"\n",
|
|
"brem_x_found = ak.to_numpy(ak.flatten(tuple_found[\"brem_vtx_x\"]))\n",
|
|
"brem_z_found = ak.to_numpy(ak.flatten(tuple_found[\"brem_vtx_z\"]))\n",
|
|
"\n",
|
|
"brem_x_lost = ak.to_numpy(ak.flatten(tuple_lost[\"brem_vtx_x\"]))\n",
|
|
"brem_z_lost = ak.to_numpy(ak.flatten(tuple_lost[\"brem_vtx_z\"]))\n",
|
|
"\n",
|
|
"n_found = len(brem_x_found)\n",
|
|
"n_lost = len(brem_x_lost)\n",
|
|
"print(\"found: \", n_found, \", lost: \", n_lost)\n",
|
|
"stretch_factor = n_lost / n_found\n",
|
|
"print(stretch_factor)\n",
|
|
"ak.flatten(tuple_found[\"brem_vtx_x\"])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 13,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
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"image/png": 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",
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"text/plain": [
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"<Figure size 2000x800 with 3 Axes>"
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]
|
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},
|
|
"metadata": {},
|
|
"output_type": "display_data"
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}
|
|
],
|
|
"source": [
|
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"vmax = 150\n",
|
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"nbins = 100\n",
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"\n",
|
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"fig, ((ax0, ax1)) = plt.subplots(nrows=1, ncols=2, figsize=(20, 8))\n",
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"\n",
|
|
"a0 = ax0.hist2d(\n",
|
|
" brem_z_found,\n",
|
|
" brem_x_found,\n",
|
|
" density=False,\n",
|
|
" bins=nbins,\n",
|
|
" cmap=plt.cm.jet,\n",
|
|
" cmin=1,\n",
|
|
" vmax=vmax,\n",
|
|
" range=[[-200, 3000], [-1000, 1000]],\n",
|
|
")\n",
|
|
"ax0.vlines([770, 990, 2700], -1000, 1000, colors=\"red\")\n",
|
|
"ax0.set_ylim(-1000, 1000)\n",
|
|
"ax0.set_xlim(-200, 3000)\n",
|
|
"ax0.set_xlabel(\"z [mm]\")\n",
|
|
"ax0.set_ylabel(\"x [mm]\")\n",
|
|
"ax0.set_title(r\"$e^\\pm$ found brem vertices\")\n",
|
|
"\n",
|
|
"a1 = ax1.hist2d(\n",
|
|
" brem_z_lost,\n",
|
|
" brem_x_lost,\n",
|
|
" density=False,\n",
|
|
" bins=nbins,\n",
|
|
" cmap=plt.cm.jet,\n",
|
|
" cmin=1,\n",
|
|
" vmax=vmax * stretch_factor,\n",
|
|
" range=[[-200, 3000], [-1000, 1000]],\n",
|
|
")\n",
|
|
"ax1.vlines([770, 990, 2700], -1000, 1000, colors=\"red\")\n",
|
|
"ax1.set_ylim(-1000, 1000)\n",
|
|
"ax1.set_xlim(-200, 3000)\n",
|
|
"ax1.set_xlabel(\"z [mm]\")\n",
|
|
"ax1.set_ylabel(\"x [mm]\")\n",
|
|
"ax1.set_title(r\"$e^\\pm$ lost brem vertices\")\n",
|
|
"# ax1.set(xlim=(0,4000), ylim=(-1000,1000))\n",
|
|
"\n",
|
|
"plt.suptitle(\"brem vtx of photons w/ $E>0.1E_0$\")\n",
|
|
"plt.colorbar(a0[3], ax=ax1)\n",
|
|
"\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 14,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"50501\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"energy_emissions = ak.ArrayBuilder()\n",
|
|
"\n",
|
|
"for jelec in range(ak.num(ntuple, axis=0)):\n",
|
|
" energy_emissions.begin_record()\n",
|
|
" energy_emissions.field(\"lost\").boolean(ntuple[jelec, \"lost\"])\n",
|
|
" energy_emissions.field(\"energy\").real(ntuple[jelec, \"energy\"])\n",
|
|
"\n",
|
|
" tmp_velo = 0\n",
|
|
" tmp_richut = 0\n",
|
|
" tmp_neither = 0\n",
|
|
" tmp_velo_length = 0\n",
|
|
" tmp_richut_length = 0\n",
|
|
" tmp_neither_length = 0\n",
|
|
"\n",
|
|
" for jphoton in range(ak.num(ntuple[jelec][\"brem_photons_pe\"], axis=0)):\n",
|
|
" if ntuple[jelec, \"brem_vtx_z\", jphoton] <= 770:\n",
|
|
" tmp_velo += ntuple[jelec, \"brem_photons_pe\", jphoton]\n",
|
|
" tmp_velo_length += 1\n",
|
|
" elif (ntuple[jelec, \"brem_vtx_z\", jphoton]\n",
|
|
" > 770) and (ntuple[jelec, \"brem_vtx_z\", jphoton] <= 2700):\n",
|
|
" tmp_richut += ntuple[jelec, \"brem_photons_pe\", jphoton]\n",
|
|
" tmp_richut_length += 1\n",
|
|
" else:\n",
|
|
" tmp_neither += ntuple[jelec, \"brem_photons_pe\", jphoton]\n",
|
|
" tmp_neither_length += 1\n",
|
|
"\n",
|
|
" energy_emissions.field(\"velo_length\").integer(tmp_velo_length)\n",
|
|
" energy_emissions.field(\"velo\").real(tmp_velo)\n",
|
|
"\n",
|
|
" energy_emissions.field(\"rich_length\").integer(tmp_richut_length)\n",
|
|
" energy_emissions.field(\"rich\").real(tmp_richut)\n",
|
|
"\n",
|
|
" energy_emissions.field(\"neither_length\").integer(tmp_neither_length)\n",
|
|
" energy_emissions.field(\"downstream\").real(tmp_neither)\n",
|
|
"\n",
|
|
" energy_emissions.field(\"photon_length\").integer(tmp_neither_length +\n",
|
|
" tmp_richut_length +\n",
|
|
" tmp_velo_length)\n",
|
|
"\n",
|
|
" if (tmp_velo == 0) and (tmp_richut == 0):\n",
|
|
" energy_emissions.field(\"quality\").integer(0)\n",
|
|
" else:\n",
|
|
" energy_emissions.field(\"quality\").integer(1)\n",
|
|
"\n",
|
|
" energy_emissions.end_record()\n",
|
|
"\n",
|
|
"energy_emissions = ak.Array(energy_emissions)\n",
|
|
"\n",
|
|
"print(ak.num(energy_emissions, axis=0))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 15,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<pre>{lost: False,\n",
|
|
" energy: 5.09e+04,\n",
|
|
" velo_length: 0,\n",
|
|
" velo: 0,\n",
|
|
" rich_length: 0,\n",
|
|
" rich: 0,\n",
|
|
" neither_length: 0,\n",
|
|
" downstream: 0,\n",
|
|
" photon_length: 0,\n",
|
|
" quality: 0}\n",
|
|
"--------------------------\n",
|
|
"type: {\n",
|
|
" lost: bool,\n",
|
|
" energy: float64,\n",
|
|
" velo_length: int64,\n",
|
|
" velo: float64,\n",
|
|
" rich_length: int64,\n",
|
|
" rich: float64,\n",
|
|
" neither_length: int64,\n",
|
|
" downstream: float64,\n",
|
|
" photon_length: int64,\n",
|
|
" quality: int64\n",
|
|
"}</pre>"
|
|
],
|
|
"text/plain": [
|
|
"<Record {lost: False, energy: 5.09e+04, ...} type='{lost: bool, energy: flo...'>"
|
|
]
|
|
},
|
|
"execution_count": 15,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"energy_emissions[3]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 16,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"found: 41978\n",
|
|
"lost: 8523\n",
|
|
"50501\n",
|
|
"VELO energy emission, eff: 0.15952159363180926\n",
|
|
"RICH1+UT energy emission, eff: 0.10419595651571256\n",
|
|
"Neither, eff: 0.5675135145838697\n",
|
|
"total efficiency: 0.8312310647313915\n",
|
|
"efficiency: 0.8312310647313914\n",
|
|
"\n",
|
|
"found in velo/(found + lost in velo)\n",
|
|
"VELO energy emission, eff: 0.8187823965850188\n",
|
|
"RICH1+UT energy emission, eff: 0.7830357142857143\n",
|
|
"eff von e die nicht strahlen: 0.8443815921277473\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# efficiency berechnen als found in velo oder rich über alle elektronen\n",
|
|
"# dann kann man zusammenrechnen mit velo, rich, und allen anderen elektronen\n",
|
|
"# expected eff = 81.19%\n",
|
|
"\n",
|
|
"electrons_found = energy_emissions[~energy_emissions.lost]\n",
|
|
"electrons_lost = energy_emissions[energy_emissions.lost]\n",
|
|
"\n",
|
|
"anz_found = ak.num(electrons[~electrons.lost], axis=0)\n",
|
|
"anz_lost = ak.num(electrons[electrons.lost], axis=0)\n",
|
|
"print(\"found: \", anz_found)\n",
|
|
"print(\"lost: \", anz_lost)\n",
|
|
"\n",
|
|
"num_velo_found = 0\n",
|
|
"num_rich_found = 0\n",
|
|
"num_no_up_rad_found = 0\n",
|
|
"for itr in range(ak.num(electrons_found, axis=0)):\n",
|
|
" if electrons_found[itr, \"quality\"] == 1:\n",
|
|
" if electrons_found[itr, \"velo\"] >= electrons_found[itr, \"rich\"]:\n",
|
|
" num_velo_found += 1\n",
|
|
" else:\n",
|
|
" num_rich_found += 1\n",
|
|
" else:\n",
|
|
" num_no_up_rad_found += 1\n",
|
|
"\n",
|
|
"num_velo_lost = 0\n",
|
|
"num_rich_lost = 0\n",
|
|
"num_no_up_rad_lost = 0\n",
|
|
"for itr in range(ak.num(electrons_lost, axis=0)):\n",
|
|
" if electrons_lost[itr, \"quality\"] == 1:\n",
|
|
" if electrons_lost[itr, \"velo\"] >= electrons_lost[itr, \"rich\"]:\n",
|
|
" num_velo_lost += 1\n",
|
|
" else:\n",
|
|
" num_rich_lost += 1\n",
|
|
" else:\n",
|
|
" num_no_up_rad_lost += 1\n",
|
|
"\n",
|
|
"denom = ak.num(electrons, axis=0)\n",
|
|
"print(denom)\n",
|
|
"\n",
|
|
"eff_velo = num_velo_found / denom\n",
|
|
"\n",
|
|
"eff_rich = num_rich_found / denom\n",
|
|
"\n",
|
|
"eff_other = ak.num(electrons_found[electrons_found.quality == 0],\n",
|
|
" axis=0) / denom\n",
|
|
"\n",
|
|
"print(\"VELO energy emission, eff: \", eff_velo)\n",
|
|
"\n",
|
|
"print(\"RICH1+UT energy emission, eff: \", eff_rich)\n",
|
|
"\n",
|
|
"print(\"Neither, eff: \", eff_other)\n",
|
|
"\n",
|
|
"print(\"total efficiency: \", eff_velo + eff_rich + eff_other)\n",
|
|
"\n",
|
|
"print(\"efficiency: \", anz_found / (anz_found + anz_lost))\n",
|
|
"\n",
|
|
"print(\"\\nfound in velo/(found + lost in velo)\")\n",
|
|
"\n",
|
|
"eff_velo = num_velo_found / (num_velo_found + num_velo_lost)\n",
|
|
"eff_rich = num_rich_found / (num_rich_found + num_rich_lost)\n",
|
|
"\n",
|
|
"eff_no_rad = num_no_up_rad_found / (num_no_up_rad_found + num_no_up_rad_lost)\n",
|
|
"\n",
|
|
"print(\"VELO energy emission, eff: \", eff_velo)\n",
|
|
"\n",
|
|
"print(\"RICH1+UT energy emission, eff: \", eff_rich)\n",
|
|
"\n",
|
|
"print(\"eff von e die nicht strahlen: \", eff_no_rad)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 17,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"41978\n",
|
|
"8523\n",
|
|
"50501\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"print(ak.num(electrons[~electrons.lost], axis=0))\n",
|
|
"print(ak.num(electrons[electrons.lost], axis=0))\n",
|
|
"print(ak.num(electrons, axis=0))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 18,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
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"text/plain": [
|
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"<Figure size 640x480 with 1 Axes>"
|
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]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
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}
|
|
],
|
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"source": [
|
|
"# energyspektren angucken von velo und rich\n",
|
|
"diff_found = ak.to_numpy(energy_emissions[(~energy_emissions.lost) & (\n",
|
|
" energy_emissions.quality == 1)][\"velo\"]) - ak.to_numpy(energy_emissions[\n",
|
|
" (~energy_emissions.lost) & (energy_emissions.quality == 1)][\"rich\"])\n",
|
|
"diff_lost = ak.to_numpy(energy_emissions[(energy_emissions.lost) & (\n",
|
|
" energy_emissions.quality == 1)][\"velo\"]) - ak.to_numpy(energy_emissions[\n",
|
|
" (energy_emissions.lost) & (energy_emissions.quality == 1)][\"rich\"])\n",
|
|
"\n",
|
|
"xlim = 20000\n",
|
|
"nbins = 80\n",
|
|
"\n",
|
|
"plt.hist(\n",
|
|
" diff_lost,\n",
|
|
" bins=nbins,\n",
|
|
" density=True,\n",
|
|
" alpha=0.5,\n",
|
|
" histtype=\"bar\",\n",
|
|
" color=\"darkorange\",\n",
|
|
" label=\"lost\",\n",
|
|
" range=[-xlim, xlim],\n",
|
|
")\n",
|
|
"plt.hist(\n",
|
|
" diff_found,\n",
|
|
" bins=nbins,\n",
|
|
" density=True,\n",
|
|
" alpha=0.5,\n",
|
|
" histtype=\"bar\",\n",
|
|
" color=\"blue\",\n",
|
|
" label=\"found\",\n",
|
|
" range=[-xlim, xlim],\n",
|
|
")\n",
|
|
"plt.xlim(-20000, 20000)\n",
|
|
"plt.title(\"emitted energy difference\")\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": 19,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"# number of brem vtx with E>x*E_0\n",
|
|
"\n",
|
|
"number_velo = ak.to_numpy(\n",
|
|
" energy_emissions[energy_emissions.quality == 1][\"velo_length\"])\n",
|
|
"number_rich = ak.to_numpy(\n",
|
|
" energy_emissions[energy_emissions.quality == 1][\"rich_length\"])\n",
|
|
"\n",
|
|
"plt.hist(\n",
|
|
" number_velo,\n",
|
|
" bins=10,\n",
|
|
" density=True,\n",
|
|
" alpha=0.5,\n",
|
|
" histtype=\"bar\",\n",
|
|
" color=\"darkorange\",\n",
|
|
" label=\"velo\",\n",
|
|
" range=[0, 10],\n",
|
|
")\n",
|
|
"plt.hist(\n",
|
|
" number_rich,\n",
|
|
" bins=10,\n",
|
|
" density=True,\n",
|
|
" alpha=0.5,\n",
|
|
" histtype=\"bar\",\n",
|
|
" color=\"blue\",\n",
|
|
" label=\"rich\",\n",
|
|
" range=[0, 10],\n",
|
|
")\n",
|
|
"plt.xlim(0, 10)\n",
|
|
"plt.title(\"number of photons emitted\")\n",
|
|
"plt.xlabel(\"number of photons\")\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": 20,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"' \\nphoton cut = x*E_0\\neffs, all photons included: x=0\\nfound in velo/(found + lost in velo)\\nVELO energy emission, eff: 0.8446167611094543\\nRICH1+UT energy emission, eff: 0.7961586121437423\\neff von e die nicht strahlen: 0.7954674220963173\\n'"
|
|
]
|
|
},
|
|
"execution_count": 20,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"\"\"\" \n",
|
|
"photon cut = x*E_0\n",
|
|
"effs, all photons included: x=0\n",
|
|
"found in velo/(found + lost in velo)\n",
|
|
"VELO energy emission, eff: 0.8446167611094543\n",
|
|
"RICH1+UT energy emission, eff: 0.7961586121437423\n",
|
|
"eff von e die nicht strahlen: 0.7954674220963173\n",
|
|
"\"\"\""
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"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
|
|
}
|