Projektpraktikum/trackinglosses_rad_length.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 30,
   "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": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "40402 10099\n",
      "50501\n"
     ]
    }
   ],
   "source": [
    "file = uproot.open(\n",
    "    \"tracking_losses_ntuple_B_default_radlength_endVelo.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": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "stretch factor:  0.24996287312509283\n"
     ]
    }
   ],
   "source": [
    "rad_length_found = ak.to_numpy(found[\"rad_length_frac\"])\n",
    "eta_found = ak.to_numpy(found[\"eta\"])\n",
    "rad_length_lost = ak.to_numpy(lost[\"rad_length_frac\"])\n",
    "eta_lost = ak.to_numpy(lost[\"eta\"])\n",
    "\n",
    "stretch_factor = ak.num(eta_lost,axis=0)/ak.num(eta_found,axis=0)\n",
    "print(\"stretch factor: \", stretch_factor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "plt.hist(rad_length_lost,bins=100,density=True,alpha=0.5,color=\"darkorange\",histtype=\"bar\",label=\"lost\",range=[0,1])\n",
    "plt.hist(rad_length_found,bins=100,density=True,alpha=0.5,color=\"blue\",histtype=\"bar\",label=\"found\",range=[0,1])\n",
    "plt.xlim(0,1)\n",
    "#plt.yscale(\"log\")\n",
    "plt.title(\"radiation length fraction\")\n",
    "plt.xlabel(f\"$x/X_0$\")\n",
    "plt.ylabel(\"a.u.\")\n",
    "\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 2000x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nbins=100\n",
    "vmax=80\n",
    "\n",
    "fig, ((ax0, ax1)) = plt.subplots(nrows=1, ncols=2, figsize=(20, 8))\n",
    "\n",
    "a0 = ax0.hist2d(\n",
    "    rad_length_found,\n",
    "    eta_found,\n",
    "    density=False,\n",
    "    bins=nbins,\n",
    "    cmap=plt.cm.jet,\n",
    "    cmin=1,\n",
    "    vmax=vmax,\n",
    "    range=[[0,0.5],[2,5]],\n",
    ")\n",
    "ax0.set_xlabel(f\"$x/X_0$\")\n",
    "ax0.set_ylabel(f\"$\\eta$\")\n",
    "ax0.set_title(f\"found $\\eta$ rad_length_frac\")\n",
    "\n",
    "a1 = ax1.hist2d(\n",
    "    rad_length_lost,\n",
    "    eta_lost,\n",
    "    density=False,\n",
    "    bins=nbins,\n",
    "    cmap=plt.cm.jet,\n",
    "    cmin=1,\n",
    "    vmax=vmax * stretch_factor,\n",
    "    range=[[0,0.5],[2,5]],\n",
    ")\n",
    "ax1.set_xlabel(f\"$x/X_0$\")\n",
    "ax1.set_ylabel(f\"$\\eta$\")\n",
    "ax1.set_title(f\"lost $\\eta$ rad_length_frac\")\n",
    "# ax1.set(xlim=(0,4000), ylim=(-1000,1000))\n",
    "\n",
    "plt.suptitle(\"radiation length fraction and eta\")\n",
    "plt.colorbar(a0[3], ax=ax1)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "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",
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