Projektpraktikum/trackinglosses_energy.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import uproot\t\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits import mplot3d\n",
    "import awkward as ak\n",
    "from scipy.optimize import curve_fit\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "41978 8523\n",
      "50501\n"
     ]
    }
   ],
   "source": [
    "# file = uproot.open(\"tracking_losses_ntuple_Bd2KstEE.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\")\n",
    "file = uproot.open(\n",
    "    \"tracking_losses_ntuple_B_EndVeloP.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n",
    ")\n",
    "\n",
    "# selektiere nur elektronen von B->K*ee\n",
    "allcolumns = file.arrays()\n",
    "found = allcolumns[\n",
    "    (allcolumns.isElectron) & (~allcolumns.lost) & (allcolumns.fromB)\n",
    "]  # B: 9056\n",
    "lost = allcolumns[\n",
    "    (allcolumns.isElectron) & (allcolumns.lost) & (allcolumns.fromB)\n",
    "]  # B: 1466\n",
    "\n",
    "electrons = allcolumns[(allcolumns.isElectron) & (allcolumns.fromB)]\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": [
    {
     "data": {
      "text/html": [
       "<pre>{all_endvtx_types_length: 7,\n",
       " all_endvtx_types: [101, 101, 101, 101, 101, 101, 0],\n",
       " all_endvtx_x_length: 7,\n",
       " all_endvtx_x: [-6.97, -52.9, -52.9, ..., -1.71e+03, -2.14e+03, -3.57e+03],\n",
       " all_endvtx_y_length: 7,\n",
       " all_endvtx_y: [-0.89, -6.75, -6.75, -7.08, -66.1, -72.6, -39.5],\n",
       " all_endvtx_z_length: 7,\n",
       " all_endvtx_z: [112, 859, 859, 895, 8.7e+03, 9.68e+03, 1.26e+04],\n",
       " brem_photons_pe_length: 6,\n",
       " brem_photons_pe: [2.62e+03, 812, 2.54e+03, 1.86e+03, 3.12e+03, 241],\n",
       " brem_photons_px_length: 6,\n",
       " brem_photons_px: [-161, -49.7, -156, -114, -1.18e+03, -101],\n",
       " brem_photons_py_length: 6,\n",
       " brem_photons_py: [-18.9, -6.92, -21.6, -16.8, -20.9, -0.26],\n",
       " brem_photons_pz_length: 6,\n",
       " brem_photons_pz: [2.61e+03, 810, 2.54e+03, 1.86e+03, 2.89e+03, 219],\n",
       " brem_vtx_x_length: 6,\n",
       " brem_vtx_x: [-6.97, -52.9, -52.9, -55.2, -1.71e+03, -2.14e+03],\n",
       " brem_vtx_y_length: 6,\n",
       " ...}\n",
       "---------------------------------------------------------------------------\n",
       "type: {\n",
       "    all_endvtx_types_length: int32,\n",
       "    all_endvtx_types: var * float32,\n",
       "    all_endvtx_x_length: int32,\n",
       "    all_endvtx_x: var * float32,\n",
       "    all_endvtx_y_length: int32,\n",
       "    all_endvtx_y: var * float32,\n",
       "    all_endvtx_z_length: int32,\n",
       "    all_endvtx_z: var * float32,\n",
       "    brem_photons_pe_length: int32,\n",
       "    brem_photons_pe: var * float32,\n",
       "    brem_photons_px_length: int32,\n",
       "    brem_photons_px: var * float32,\n",
       "    brem_photons_py_length: int32,\n",
       "    brem_photons_py: var * float32,\n",
       "    brem_photons_pz_length: int32,\n",
       "    brem_photons_pz: var * float32,\n",
       "    brem_vtx_x_length: int32,\n",
       "    brem_vtx_x: var * float32,\n",
       "    brem_vtx_y_length: int32,\n",
       "    brem_vtx_y: var * float32,\n",
       "    brem_vtx_z_length: int32,\n",
       "    brem_vtx_z: var * float32,\n",
       "    endvtx_type: int32,\n",
       "    endvtx_x: float64,\n",
       "    endvtx_y: float64,\n",
       "    endvtx_z: float64,\n",
       "    energy: float64,\n",
       "    eta: float64,\n",
       "    event_count: int32,\n",
       "    fromB: bool,\n",
       "    fromD: bool,\n",
       "    fromDecay: bool,\n",
       "    fromHadInt: bool,\n",
       "    fromPV: bool,\n",
       "    fromPairProd: bool,\n",
       "    fromSignal: bool,\n",
       "    fromStrange: bool,\n",
       "    ideal_state_770_qop: float64,\n",
       "    ideal_state_770_tx: float64,\n",
       "    ideal_state_770_ty: float64,\n",
       "    ideal_state_770_x: float64,\n",
       "    ideal_state_770_y: float64,\n",
       "    ideal_state_770_z: float64,\n",
       "    ideal_state_9410_qop: float64,\n",
       "    ideal_state_9410_tx: float64,\n",
       "    ideal_state_9410_ty: float64,\n",
       "    ideal_state_9410_x: float64,\n",
       "    ideal_state_9410_y: float64,\n",
       "    ideal_state_9410_z: float64,\n",
       "    isElectron: bool,\n",
       "    isKaon: bool,\n",
       "    isMuon: bool,\n",
       "    isPion: bool,\n",
       "    isProton: bool,\n",
       "    lost: bool,\n",
       "    lost_in_track_fit: bool,\n",
       "    match_fraction: float32,\n",
       "    mc_chi2: float32,\n",
       "    mc_dSlope: float32,\n",
       "    mc_dSlopeY: float32,\n",
       "    mc_distX: float32,\n",
       "    mc_distY: float32,\n",
       "    mc_teta2: float32,\n",
       "    mc_zMag: float32,\n",
       "    mcp_idx: int32,\n",
       "    mother_id: int32,\n",
       "    mother_key: int32,\n",
       "    originvtx_type: int32,\n",
       "    originvtx_x: float64,\n",
       "    originvtx_y: float64,\n",
       "    originvtx_z: float64,\n",
       "    p: float64,\n",
       "    p_end_ut: float64,\n",
       "    p_end_velo: float64,\n",
       "    phi: float64,\n",
       "    pid: int32,\n",
       "    pt: float64,\n",
       "    px: float64,\n",
       "    py: float64,\n",
       "    pz: float64,\n",
       "    quality: int32,\n",
       "    rad_length_frac: float64,\n",
       "    scifi_hit_pos_x_length: int32,\n",
       "    scifi_hit_pos_x: var * float32,\n",
       "    scifi_hit_pos_y_length: int32,\n",
       "    scifi_hit_pos_y: var * float32,\n",
       "    scifi_hit_pos_z_length: int32,\n",
       "    scifi_hit_pos_z: var * float32,\n",
       "    track_p: float64,\n",
       "    track_pt: float64,\n",
       "    tx: float64,\n",
       "    ty: float64,\n",
       "    ut_hit_pos_x_length: int32,\n",
       "    ut_hit_pos_x: var * float32,\n",
       "    ut_hit_pos_y_length: int32,\n",
       "    ut_hit_pos_y: var * float32,\n",
       "    ut_hit_pos_z_length: int32,\n",
       "    ut_hit_pos_z: var * float32,\n",
       "    velo_hit_pos_x_length: int32,\n",
       "    velo_hit_pos_x: var * float32,\n",
       "    velo_hit_pos_y_length: int32,\n",
       "    velo_hit_pos_y: var * float32,\n",
       "    velo_hit_pos_z_length: int32,\n",
       "    velo_hit_pos_z: var * float32,\n",
       "    velo_track_idx: int32,\n",
       "    velo_track_tx: float64,\n",
       "    velo_track_ty: float64,\n",
       "    velo_track_x: float64,\n",
       "    velo_track_y: float64,\n",
       "    velo_track_z: float64\n",
       "}</pre>"
      ],
      "text/plain": [
       "<Record {all_endvtx_types_length: 7, ...} type='{all_endvtx_types_length: i...'>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "electrons[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>{lost: True,\n",
       " rad_length_frac: 0.129,\n",
       " energy: 1.17e+04,\n",
       " photon_length: 6,\n",
       " brem_photons_pe: [2.62e+03, 812, 2.54e+03, 1.86e+03, 3.12e+03, 241],\n",
       " brem_vtx_x: [-6.97, -52.9, -52.9, -55.2, -1.71e+03, -2.14e+03],\n",
       " brem_vtx_z: [112, 859, 859, 895, 8.7e+03, 9.68e+03]}\n",
       "---------------------------------------------------------------------\n",
       "type: {\n",
       "    lost: bool,\n",
       "    rad_length_frac: float64,\n",
       "    energy: float64,\n",
       "    photon_length: int64,\n",
       "    brem_photons_pe: var * float64,\n",
       "    brem_vtx_x: var * float64,\n",
       "    brem_vtx_z: var * float64\n",
       "}</pre>"
      ],
      "text/plain": [
       "<Record {lost: True, rad_length_frac: ..., ...} type='{lost: bool, rad_leng...'>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lost_e = electrons[\"lost\"]\n",
    "e = electrons[\"energy\"]\n",
    "brem_pe = electrons[\"brem_photons_pe\"]\n",
    "brem_z = electrons[\"brem_vtx_z\"]\n",
    "brem_x = electrons[\"brem_vtx_x\"]\n",
    "length = electrons[\"brem_vtx_z_length\"]\n",
    "rad_length = electrons[\"rad_length_frac\"]\n",
    "\n",
    "brem = ak.ArrayBuilder()\n",
    "\n",
    "for itr in range(ak.num(electrons, axis=0)):\n",
    "    brem.begin_record()\n",
    "    brem.field(\"lost\").boolean(lost_e[itr])\n",
    "    brem.field(\"rad_length_frac\").append(rad_length[itr])\n",
    "    # [:,\"energy\"] energy\n",
    "    brem.field(\"energy\").append(e[itr])\n",
    "    # [:,\"photon_length\"] number of vertices\n",
    "    brem.field(\"photon_length\").integer(length[itr])\n",
    "    # [:,\"brem_photons_pe\",:] photon energy\n",
    "    brem.field(\"brem_photons_pe\").append(brem_pe[itr])\n",
    "    # [:,\"brem_vtx_z\",:] brem vtx z\n",
    "    brem.field(\"brem_vtx_x\").append(brem_x[itr])\n",
    "    brem.field(\"brem_vtx_z\").append(brem_z[itr])\n",
    "    brem.end_record()\n",
    "\n",
    "brem = ak.Array(brem)\n",
    "brem[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "photon_cut = 0\n",
    "photon_cut_ratio = 0.2\n",
    "\n",
    "cut_brem = ak.ArrayBuilder()\n",
    "\n",
    "for itr in range(ak.num(brem, axis=0)):\n",
    "    cut_brem.begin_record()\n",
    "    cut_brem.field(\"event_id\").integer(itr)\n",
    "    cut_brem.field(\"lost\").boolean(brem[itr, \"lost\"])\n",
    "    cut_brem.field(\"rad_length_frac\").real(brem[itr, \"rad_length_frac\"])\n",
    "    cut_brem.field(\"energy\").real(brem[itr, \"energy\"])\n",
    "\n",
    "    ph_length = brem[itr, \"photon_length\"]\n",
    "\n",
    "    tmp_energy = brem[itr, \"energy\"]\n",
    "\n",
    "    cut_brem.field(\"brem_photons_pe\")\n",
    "    cut_brem.begin_list()\n",
    "    for jentry in range(brem[itr, \"photon_length\"]):\n",
    "        if (\n",
    "            brem[itr, \"brem_vtx_z\", jentry] > 2700\n",
    "            or brem[itr, \"brem_photons_pe\", jentry] < photon_cut\n",
    "            or brem[itr, \"brem_photons_pe\", jentry] < photon_cut_ratio * tmp_energy\n",
    "        ):\n",
    "            ph_length -= 1\n",
    "            continue\n",
    "        else:\n",
    "            cut_brem.real(brem[itr, \"brem_photons_pe\", jentry])\n",
    "            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_x\")\n",
    "    cut_brem.begin_list()\n",
    "    for jentry in range(brem[itr, \"photon_length\"]):\n",
    "        if (\n",
    "            brem[itr, \"brem_vtx_z\", jentry] > 2700\n",
    "            or brem[itr, \"brem_photons_pe\", jentry] < photon_cut\n",
    "            or brem[itr, \"brem_photons_pe\", jentry] < photon_cut_ratio * tmp_energy\n",
    "        ):\n",
    "            continue\n",
    "        else:\n",
    "            cut_brem.real(brem[itr, \"brem_vtx_x\", jentry])\n",
    "            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",
    "    cut_brem.begin_list()\n",
    "    for jentry in range(brem[itr, \"photon_length\"]):\n",
    "        if (\n",
    "            brem[itr, \"brem_vtx_z\", jentry] > 2700\n",
    "            or brem[itr, \"brem_photons_pe\", jentry] < photon_cut\n",
    "            or brem[itr, \"brem_photons_pe\", jentry] < photon_cut_ratio * tmp_energy\n",
    "        ):\n",
    "            continue\n",
    "        else:\n",
    "            cut_brem.real(brem[itr, \"brem_vtx_z\", jentry])\n",
    "            tmp_energy -= brem[itr, \"brem_photons_pe\", jentry]\n",
    "    cut_brem.end_list()\n",
    "\n",
    "    cut_brem.field(\"photon_length\").integer(ph_length)\n",
    "\n",
    "    cut_brem.end_record()\n",
    "\n",
    "ntuple = ak.Array(cut_brem)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "24758\n",
      "50501\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre>{event_id: 0,\n",
       " lost: True,\n",
       " rad_length_frac: 0.129,\n",
       " energy: 1.17e+04,\n",
       " brem_photons_pe: [2.62e+03, 2.54e+03, 1.86e+03],\n",
       " brem_vtx_x: [-6.97, -52.9, -55.2],\n",
       " brem_vtx_z: [112, 859, 895],\n",
       " photon_length: 3}\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: 0, lost: True, ...} type='{event_id: int64, lost: bool, ...'>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(ak.sum(ak.num(ntuple[\"brem_photons_pe\"], axis=1)))\n",
    "print(ak.num(ntuple, axis=0))\n",
    "ntuple[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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": 9,
   "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": 10,
   "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": 10,
     "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": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "Z_found = ak.to_numpy(\n",
    "    ak.sum(ntuple[~ntuple.lost][\"brem_photons_pe\"], axis=-1,\n",
    "           keepdims=False)) / ak.to_numpy(ntuple[~ntuple.lost][\"energy\"])\n",
    "Z_lost = ak.to_numpy(\n",
    "    ak.sum(ntuple[ntuple.lost][\"brem_photons_pe\"], axis=-1,\n",
    "           keepdims=False)) / ak.to_numpy(ntuple[ntuple.lost][\"energy\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "found:  19848 , lost:  4910\n",
      "0.2473800886739218\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre>[-3.61,\n",
       " -33.8,\n",
       " -133,\n",
       " 65.2,\n",
       " -26.6,\n",
       " 31.6,\n",
       " -52.1,\n",
       " -44.7,\n",
       " -103,\n",
       " -10.2,\n",
       " ...,\n",
       " 330,\n",
       " -11.6,\n",
       " -13.1,\n",
       " -25.6,\n",
       " -4.27,\n",
       " -103,\n",
       " 8.82,\n",
       " 12.8,\n",
       " -17.8]\n",
       "---------------------\n",
       "type: 19848 * float64</pre>"
      ],
      "text/plain": [
       "<Array [-3.61, -33.8, -133, ..., 8.82, 12.8, -17.8] type='19848 * float64'>"
      ]
     },
     "execution_count": 13,
     "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": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABkgAAAL5CAYAAAD7Uaj9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAACypElEQVR4nOz9f5Qj533f+X5qhuK4Y3KIafpIEe2YQ7SUazmxLlkY/8g618NIwPF6vc690XQPN7F3NY5FYJnezSa8Vw0zc3ebEx+mg7EvvZtNWwZGicZ74vVygNGe2Md2EkA2xydObGtQpO0kdK7Z0FCyqFBH6oaGvG4NNT11/+gBCDTqeRpVAAq/3q9z+vRMfet56ltPFdDPgwdV5fi+7wsAAAAAAAAAAGCOHBl3AgAAAAAAAAAAAHFjggQAAAAAAAAAAMwdJkgAAAAAAAAAAMDcYYIEAAAAAAAAAADMHSZIAAAAAAAAAADA3GGCBAAAAAAAAAAAzB0mSAAAAAAAAAAAwNxhggQAAAAAAAAAAMwdJkgAAAAAAAAAAMDcYYIEAAAARs1mU5VKRSsrKzpx4oQ8zxt3SpgRtVpNuVxOJ06cUKVSGXc6AAAAAOYQEyQAAAAwKpVKKhaLqlQqajab404HMbh48WJ7QuzEiRPK5XJDP/aVSkXFYlGlUonzakI1m005jqNMJhOqTD6f19LSkhzH6fppnU8HlzuOo1KpNMI9GVylUlEmk1Emk1EqlVImk1GtVhta/Z7nKZPJ9DUBPattDAAAMC5MkAAAAMBobW1NxWJx3GlMtWazORWTAM1mU6lUSl/96ldVLpf1uc99TouLiyqVSkP/cHV5eVnlcnmodfZrWo7HuLWO+crKSt9lEomECoWCqtVq17KdnZ32j+/78n1f9Xpd2WxWknTq1KnhJj9EKysrWllZae9XvV5XLpdTJpNRPp8fqO5Go6GVlRWlUqm+J1xmsY0BAADGiQkSAAAAWC0uLo47ham2srKiRqMx7jQOlc/n5XmecrmcpP0PXbe2tlStVrW2tjbm7IZnWo7HuL3wwguSpLNnz4Yu2zkBdfbsWSUSiZ51XNdVsVhUIpGQ67pR0xypXC7XvtqpM8fl5WVls1ldvHgx8u3hWlfnRTUrbQwAADBuTJAAAAAAI5LP54d6K55Ral0xcHBCLJ1OjyOdkZim4zFOjUZDnucpnU4HfvB+mM42PuwKlDBXNrSu3IjjGDYajfZronUVxsFcJEW+iiSbzapQKKhQKEQqP6o2BgAAmDdMkAAAAAAjUKlUdPHixXGn0Zd5uKJimo7HuLWubGhNAoTVefunwybYwtxqrVgsKpPJtG9LFfXqjX60Ji5M+buuq0QioUajMdCETdQr9EbVxgAAAPOGCRIAAACE0rpvfuuBwLZbFtVqNa2srLS/iZ3L5QIf/NxsNpXL5doPHk6lUsYPsyuVilZWVtrf3G494Lj1kOLOco1GQ7lcrv3g4kwmE+r5E57nKZVKdT3s+GBelUqlnXer/kqloieffLK9zoc//OF2e3W2YWe9mUym/c391jZPnDgR6RvqFy9ebD9QemlpSZlMJvA5IqVSSSdOnFAqlWove+SRR9q59juh0HqIdWsb+Xy+q837/QC5s1wqlTr0odX97udhxyNqvdL+uVsqlbrWKZVKXeeyaT+azWb7GRcrKytaWlrS0tLSoRMTnud1PYx7aWmp3cYXL17siXXm3mw226+XpaWlwNdDa+JheXnZmodJK5egD+6bzWZXe4S9QmVtbU07OzvK5XLth5WP4gHkrX2w3ZoqmUxK0lie0zTKNgYAAJgrPgAAAGCxs7PjS/Il+YVCwZfkJ5NJP5FItJdL8qvVartMoVDwk8lkO1YsFv10Ot1VZmtry/d9369Wq77ruu3yW1tbfjqd9iX5ruu266xWq+3lkvxsNuuvra35ruv6a2trfjab7dpeuVz2k8lke71WPp119rv/rbzT6XTgOq39NbVbvV4PLFcsFtvrlMvlnvp2dnZC5Vqv1/1kMukvLy935bG8vNzOP6jOra2tnuPS7/Y6j0krb9d1fdd1u86PQqHQU77zeLmu66fT6a5jJSkw3yj72c/xCFtv69zt3Mfl5WXfdV0/m80euh/JZLKrXXZ2dnq2b1KtVgPPndZ+BL0uD7ZFUDu0yvaTw2F5FYvFnng2mw11jh2m9TpPJBKB51gUB9/zTFrnxcHXftRtmc7Lg+JuYwAAgFnGBAkAAACsOj/ASyaTXR+8dX5Ql0gkrOVaH9QWCgU/m836vv/OB/MHPxjsLLu2ttYV6/xA/uAHw61JkkQi0fMBb9RJgFbOrbJBlpeXez6o7PeDz9YH7K2Jm9aETL8flnZKJBI9x6Gl1W5BkzyDtI3v+13nQGferQ/8TXV3nh8H97c1KXXw+Efdz36OR9T2a+WaSCS6JiQ6J9cOftDemhw72CbVarXvyYlW2wa1USsW9AF/a2InyNramnFipR+t8gf3bWdnxy8UCsb2HVS5XPZd121PlISdXOzUOcEUNAHR0jkpG1WUCZJxtTEAAMAs4hZbAAAA6FuhUGjfVkbav71L6/YyzWaz65ZMiUSifWuXdDrdvhXM2tpau0w+n1cikei5jU3nsoO3z+ms8+AtgFoPK242m7p06VJXLJlMtsseduumgzof0nwwn2azqVqtFvgg5360ng/geZ5KpZJWVlaUzWatt/YJks/n1Ww2jXm0nqlQq9VG9uyGZ555pivvRCLR9awE0wOpC4VCz/62zpeDt28b1X4OUm/rNZHNZrtueZRIJNoPyN7a2uoq0/r/wbrS6XTXa8ymdSuuoFtMtWJBt38qFovG23iVSiUlEolDn2th0rk/rduMdd4u7uzZs5HqPczy8rLq9brK5bKq1Wp7e2Fuqdeyvb3d/rftGSGdt66Ksp2oBmnj1u0MW7d1a93aDwAAYF4xQQIAAIC+BX1wm81m2x8Ufvaznw0s1/mMi06VSkXNZrP97IXOn9YkRrPZ7PrwsfWBZdB99Q974HErHvYDwUQi0f7g/OAHzleuXIn8YbK036Zra2uS9j/UbjQaxokEm9aHpt/93d8dGHddt338XnjhhYjZBmsdi6Bjkkwm25Mf169f77vOVq4Hj9Wo9nNU9Zr2Y2lpSdL+xMzB58z0e/xb52Rrkq5TawKm9VybFtuEXq1WU7PZjDyJ0Ww22/uZzWbl79+xQDs7O6pWq0okEu1JzFFJp9OqVquq1+tqNBo6ceJE+3U1CwZt49Z7cblcVrlcbk+SxDnBAwAAMEmYIAEAAMDAWt+SD3NlRmvddDqtra2tnp/WB3++7w/tIcOD1NP6xr3neV37WSwW9cwzzwyUV+eVOWGvHGnp5wPg1jbCXkEzKNPVIFGMaj/jbr/Oq4QuXrzY9aD1fiUSifZVVJ0Td60Hx7favTNmm9BrXc102EPiTa5cudL+d+eH9K0rUpLJ5ECTiWG4rqtyuaytrS1tb29raWmp78mZzonWzqtJDuqcVIjrQeiDtHE+n++ZgG1NlD355JMjyhgAAGCyMUECAACAgfV7S6BOrQ8ep+Wb3a7rtj/Qbn3g3Gg01Gw2I09qdGp90F2pVEJ/UN7ZhrYPdFvHybbOKDz44INDqWdU+zmu9qvX6+3j3mg0lMlktLKyEurb/K3JjNbVWNL+bbKWl5fbH4R3fqheKBSME3qt22tFPZ87b6cW9CF9XJMjBx12ZdlBne9ntmPROg/imhyRBmvjUqkk13V78k2n013nDwAAwDxhggQAAAADa33gFuaD1ai3uxqng898sD3LIYxGo9H+8LJzO/3q/ED34LMuOrWOU5QJrWFoXWkU1aj2c5zt17rVUavOSqVivCVdkHQ63c6rNRGysbHRfh5MMplUs9lUpVJpX/kS9Dpt3WIs6rN0JLUn9kwf0ke5dVxUjUZDKysrWlpa0vb2tra2ttpXyBwmkUi0j8dXv/pV43qtCYU4J36itrHneWo2m4Gvwdb51jmRBgAAMC+YIAEAAMDAWpMcpuc3BOn8kNn2MO3W7YImQefzVkqlkkql0kAfKLesrKyoUCi0HyzfaDS6Hnjfj1Z
      "text/plain": [
       "<Figure size 2000x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vmax = 150\n",
    "nbins = 100\n",
    "\n",
    "fig, ((ax0, ax1)) = plt.subplots(nrows=1, ncols=2, figsize=(20, 8))\n",
    "\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": 15,
   "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": 16,
   "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": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "energy_emissions[3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "found:  41978\n",
      "lost:  8523\n",
      "50501\n",
      "VELO energy emission, eff:  0.19057048375279698\n",
      "RICH1+UT energy emission, eff:  0.1271657986970555\n",
      "Neither, eff:  0.513494782281539\n",
      "total efficiency:  0.8312310647313914\n",
      "efficiency:  0.8312310647313914\n",
      "\n",
      "found in velo/(found + lost in velo)\n",
      "VELO energy emission, eff:  0.8275150472914875\n",
      "RICH1+UT energy emission, eff:  0.7901082677165354\n",
      "eff von e die nicht strahlen:  0.8435090915005041\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], 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": 18,
   "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": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "energy_emissions = energy_emissions[energy_emissions.energy >= 5e3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# energyspektren angucken von velo und rich\n",
    "diff_found = (\n",
    "    ak.to_numpy(\n",
    "        energy_emissions[(~energy_emissions.lost) & (energy_emissions.quality == 1)][\n",
    "            \"velo\"\n",
    "        ]\n",
    "    )\n",
    "    - ak.to_numpy(\n",
    "        energy_emissions[(~energy_emissions.lost) & (energy_emissions.quality == 1)][\n",
    "            \"rich\"\n",
    "        ]\n",
    "    )\n",
    ") / ak.to_numpy(\n",
    "    energy_emissions[(~energy_emissions.lost) & (energy_emissions.quality == 1)][\n",
    "        \"energy\"\n",
    "    ]\n",
    ")\n",
    "diff_lost = (\n",
    "    ak.to_numpy(\n",
    "        energy_emissions[(energy_emissions.lost) & (energy_emissions.quality == 1)][\n",
    "            \"velo\"\n",
    "        ]\n",
    "    )\n",
    "    - ak.to_numpy(\n",
    "        energy_emissions[(energy_emissions.lost) & (energy_emissions.quality == 1)][\n",
    "            \"rich\"\n",
    "        ]\n",
    "    )\n",
    ") / ak.to_numpy(\n",
    "    energy_emissions[(energy_emissions.lost) & (energy_emissions.quality == 1)][\n",
    "        \"energy\"\n",
    "    ]\n",
    ")\n",
    "\n",
    "xlim = 1\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.yscale(\"log\")\n",
    "plt.title(\"emitted energy difference ratio\")\n",
    "plt.xlabel(r\"$(E_{VELO} - E_{RICH1+UT})/E_0$\")\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": [
    "# 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",
    ")\n",
    "number_rich = ak.to_numpy(\n",
    "    energy_emissions[energy_emissions.quality == 1][\"rich_length\"]\n",
    ")\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",
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