{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import uproot\t\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import colormaps\n",
    "from mpl_toolkits import mplot3d\n",
    "import awkward as ak\n",
    "from scipy.optimize import curve_fit\n",
    "from scipy import stats\n",
    "from utils.fit_linear_regression_model import fit_linear_regression_model\n",
    "import sklearn\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import mplhep\n",
    "mplhep.style.use([\"LHCbTex2\"])\n",
    "\n",
    "plt.rcParams[\"savefig.dpi\"] = 600\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def round(n, k):\n",
    "    # function to round number 'n' up/down to nearest 'k'\n",
    "    # use positive k to round up\n",
    "    # use negative k to round down\n",
    "\n",
    "    return n - n % k"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "40402 10099\n",
      "48290\n"
     ]
    }
   ],
   "source": [
    "file = uproot.open(\n",
    "    \"/work/cetin/Projektpraktikum/tracking_losses_ntuple_B_zmag.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n",
    "    # \"/work/cetin/LHCb/lb-stack/data/tracking_losses_ntuple_test_endVelo2endT.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n",
    ")\n",
    "\n",
    "# selektiere nur elektronen von B->K*ee\n",
    "allcolumns = file.arrays()\n",
    "found = allcolumns[(allcolumns.isElectron) & (~allcolumns.lost) &\n",
    "                   (allcolumns.fromB)]  # B: 9056\n",
    "lost = allcolumns[(allcolumns.isElectron) & (allcolumns.lost) &\n",
    "                  (allcolumns.fromB)]  # B: 1466\n",
    "\n",
    "electrons = allcolumns[(allcolumns.isElectron)\n",
    "                       & (allcolumns.fromB)\n",
    "                       & (allcolumns.eta < 5.0)\n",
    "                       & (allcolumns.eta > 2.0)\n",
    "                       # & (np.abs(allcolumns.phi) < 3.142)\n",
    "                       ]\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": [
    {
     "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",
    "phi_found = ak.to_numpy(found[\"phi\"])\n",
    "rad_length_lost = ak.to_numpy(lost[\"rad_length_frac\"])\n",
    "eta_lost = ak.to_numpy(lost[\"eta\"])\n",
    "phi_lost = ak.to_numpy(lost[\"phi\"])\n",
    "\n",
    "eta_a = ak.to_numpy(electrons[\"eta\"])\n",
    "phi_a = ak.to_numpy(electrons[\"phi\"])\n",
    "rad_length_frac_a = ak.to_numpy(electrons[\"rad_length_frac\"])\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": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(\n",
    "    rad_length_lost,\n",
    "    bins=100,\n",
    "    density=True,\n",
    "    alpha=0.5,\n",
    "    color=\"#F05342\",\n",
    "    histtype=\"bar\",\n",
    "    label=\"lost\",\n",
    "    range=[0, 1],\n",
    ")\n",
    "plt.hist(\n",
    "    rad_length_found,\n",
    "    bins=100,\n",
    "    density=True,\n",
    "    alpha=0.5,\n",
    "    color=\"#107E7D\",\n",
    "    histtype=\"bar\",\n",
    "    label=\"found\",\n",
    "    range=[0, 1],\n",
    ")\n",
    "plt.xlim(-0.05, 1)\n",
    "# plt.yscale(\"log\")\n",
    "# plt.title(\"radiation length fraction endVelo2endUT\")\n",
    "plt.xlabel(f\"$x/X_0$\")\n",
    "plt.ylabel(\"Number of Tracks (normalised)\")\n",
    "plt.legend(loc=\"best\")\n",
    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
    "plt.show()\n",
    "# plt.savefig(\n",
    "#     \"/work/cetin/Projektpraktikum/thesis/rad_length_frac_lost_found_endVelo2endUT.pdf\",\n",
    "#     format=\"PDF\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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cHkKHr6qJiMwTZ2traz370jzItulcHl+3zc1Ng9s5NcjjZX9m/2n72M7gJmdnkMfM9PR0W/fRPn6PXPfeHqw8/l1qtb58UnJzc9NJj5zJyzFTKpVSr34nP/JyzLRaR08aFYtFFz4MKXk6DJ5cFgYrr3+P5HlcFHl6D8qB6NalYOgsLS0d/FypVKJYLKaWn56ePvi52WzG+vr6uWybzuXxdcvqA4MzqOOlXq9Ho9GItbW1zLKlUulIP/f3ZzAG+RnTbDZjYWEhs1yxWIxSqXTkOYOTx79LjUYj5ubmYmFhISYnJ3teP93JwzGzvr4ejUYjFhcXu66Ls5eHYyYiYmpq6khdm5ub/gYNKXk6DJ5cFgYrj3+P5HlcJHl5D8qB6AWD20OoWq0e/NzuH+XDJ/Rv3759Ltumc143TmNQx8vt27djdna27S87lUrlyPMvfOELHbVL9wb5GbOxsdF22YcPHx78fOXKlY7bpHt5/Ls0MzMTk5OTj51sJB/ycMzcunUrisViXLt2reu6OHt5OGaq1WrUarWD56urq0faYLjI02Hw5LIwWHn8eyTP4yLJw3tQDkSvGNweMsev5nz3u9/d1n6HP8y6uRJ1UG3TOa8bpzHI4+X69eunSjaOf0mbmJjoqF26c14+Y5rNZjSbzYh4dDLJFduDk8djZnFxMer1eluzbei/PBwz9Xo96vV6NJvNGB0djYmJiZibm/MdKafycMzszxI6XPfs7GxXdZJf8nQYPLksDFYe/x7J87hI8vAelAPRSwa3h8zhq14iou2rXo6X62TJo0G2Tee8bpzGII+XycnJUy1Rsz9QmdQH+uO8fMa88MILB+1KbAcrb8dMvV6P5eVlVxPnWB6OmeNLkTcajahWqzEzMxOFQiFmZmZ8V8qRPBwzMzMzR54/++yzHddF/snTYfDksjBYeft7JM/josnDe1AORC8Z3B4yL7300pHn7X55ftvb3nbk+d27d89V23TO68ZpnKfjpdFoHHl+fGk3+uM8HDPNZjPm5uZicnIyNjY23OdnwPJ2zFy9ejWmp6ddTZxjgz5mGo3GYycKjltfX49yuXzkKnUGJw/HzOGTQsVi8cj97Bg+8nQYvPP0XpDLMozy9h6U53HRDPo9KAei1wxuD5njX4A7vQJna2vrXLVN57xunMZ5Ol4Of9mSrAxO3o+ZRqMR5XI5isVi3LlzxxXbOZCnY2b/quLnn3++67o4O4M+ZkqlUqyursbS0lLMzs6mtl+tVqNcLnfUDr0z6GNmdXX1yPP9QYv19fWYmZmJiYmJKBQKMTo6GuVyOZaXlx+bxcf5Ik+HwTtP7wW5LMMoT+9BeR4X0aDfg3Igeu0rBt0Beuv4h1SnOvngGGTbdM7rxmmcp+Pl8Jem48vF0j95Pmb2v0DvGx0djaWlpVhYWOh5W7QvL8fM+vp6rK+vm81/DuThmDl+4rnZbEa1Wo1bt249Vm+9Xo+pqanY2NjouD26M+hjplqtHnn+1FNPRblcfmyJv2azeXA/98XFxVhbWzO74ZySp8Pgnaf3glyWYZSX96A8j4tq0O9BORC9Zub2kOn0w+X4H/OHDx+eq7bpnNeN0zgvx8vhpW6WlpbMxh2gvB0zzWYzlpeXY2Ji4rF7/UQ8Onl00nb6Jw/HTLPZjJmZmZidnbUM5DmQh2PmpLoXFhZiZ2cn1tbWHmurVqvF8vJyz9rjdAZ5zDQajcfaf+GFF2Jubi52dnai1WpFq9WKra2txy6amJmZifX19VO3yeDJ02Hwzst7QS7LsMrDe1Cex0UmB2LYGNzmRIO8KtsV4eeT143TOOvjZWlpKSIeLZ1jFu5w6NUxU6vVYmtrKyqVSmIyu76+btBpCHRzzFy9evVgqWkujrP62zQ9PR337t2LycnJI9tv3bp1Ju3RP72YRVssFuPevXsxOzt75MTR/mfQ8c+hZ555xvfuC0yeDoMnl4XBkufBYMmByAuD20OmV8updFLPINumc143TuM8HC/1ej2q1WoUi0VLvuZA3o6Z6enpgy/KGxsb0Wq1YnV19bH6FxcXfXEekEEfM8vLy1Gv12Ntba0n/eDsDfqYabfuzc3NIwPczWYzarXambVJskEeM8dP7Bw/oXPc7OzskdkLzWbThRHnkDwdBu88vBfksgyzQb8H5XlcdHIgho3B7SHz1FNPDayeQbZN57xunMZ5OF6eeeaZiIi4c+eOJdxy4DwcM7Ozs7G5ufnYF+vj9wOiPwZ5zOzf02lpaemxWbbk13n4nNn3/PPPH3nuxPVgDPKY2draOvL83e9+d+Y+x++3anWR80eeDoN3Ht4LclmGmTwPBksOxLAxuD1kOr0C5/jstH5eEd6Ltumc143TyPvxMjc3d3AlroQlH/J+zOwrlUpx586dI9teeumlM22Tkw3ymJmZmYnJyUlLQJ4z5+VzJiJicnLyyC0Rjl/BTn8M8pjppI5SqfTY95r9+7FyPsjTYfDy/l6QyzLs5HkwWHIghs1XDLoD9NaVK1eOvMmbzWZbHxYPHz488nxiYuJctU3nvG6cRp6Pl2q1GtVqNVZXV2N6errn9dOZPB8zx01OTsb09HSsr69HhEGnQRnUMbO8vByNRiMqlUrMzMxklj+cnN26dStu37598Pz69es+h/roPH3ORERMTU1ZjnzABnnMdHqcHe9zo9Ew+HGOyNNh8PL8XpDLchHI82Cw5EAMG4PbQ6ZcLh953u4b/vjSEIdnlJyHtumc143TyOvxUqvVYm5uLlZXV4/ck4XBy+sxk+T69esHg9vuuT0YgzpmvvCFL0REdDToWK/XjyRcpVLJSY8+Om+fM4eXGbXM72AM8pg5fgKp3b81x08IHT/JRL7J02Hw8vpekMtyUcjzYLDkQAwby5IPmStXrhx53u6ss8MfKMVisaN7+wyybTrndeM08ni81Ov1mJqaiqWlJScDciiPx0yaw1/sLb85GOftmGHwztsxc7gdnzODcR5zpuPHigsjzpfzeMz5u8qwyeN7QS7LRZLH9yBcJOfx+6gciDQGt4fM5OTkkTd9u/cLvXv37sHPxz9szkPbdM7rxmnk7XhpNBpx9erVWFhYcO+knMrbMXMaPtsGY1DHzNLSUrRarbYfhxO6tbW1I7GlpaVTt0/nztvnzOF2p6am+tYuXzbonOmw4zMh2uXE7vky6GPuPH1GwlnJ23tBLstFI8+DwRr099HD5ED0gsHtIXTt2rWDnw8vnZLmcLnFxcVz2Tad87pxGnk5XhqNRpTL5ZidnW07wWg0GrG8vNyT9mlfXo6Zdhy+etSg0+Ccp2OGfDhPx8zhRN4yv4MzyGPm8Ove7hKZx5fuc6+580eeDoOXl/eCXJaLKi/vQbio5EAMlRZDZ3NzsxURB48sGxsbB2VLpdK5bZvO5fF129raOtKn1dXVM2mH08vD8bKzs9MqlUqt2dnZU+03OTnZ2tzc7EkfaF8ejpl2LS0ttSKiVSwW+9ouR52HY6ZUKh20uba21pc2SXYejpl9+8fOwsJCX9vlqEEeM4friojWzs5O5j6zs7MH5SuVSlftMxjydBi8PLwX5LJcZHl4D2aR5zHM5EAMEzO3h9Dk5OSRK2HW19dTy6+trR38nHX1TbVajcXFxcT7Ipxl25ydQR4zSY5fmUV+DPp4aTabUS6Xo1QqHZTNetRqtSiXywf9p78Gfcycxq1btyIi4vnnn+9JfXTmPB0z5MN5OWbW19ej0WhEsViMZ599tuv66Nwgj5lKpXJkSb39vz1pDs9usCTm+SRPh8Eb9PcFuSwX3aDfg3DRyYEYKoMeXedsHJ71Ojk5mVhuZ2en7atfKpVKW1fXnEXbnL1BHjMnWVtbO7Lv0tJS2/ty9gZ5vExOTh4pd5qHFQAGZ1DHzNLSUmtycrK1sLCQ+Rm0sLBgNmWO5O3v0nGu6M+fQRwzGxsbrWKxeFBX2oyqra2tg7JmXuXDID9njs+a2NraSqzz8CyH0870I1/k6TB4clkYLHkeDJYciGFhcHuIHR4cTBoY3P9iXSwWM//wn+aLda/bpj8Gecwctr9M1+F90/7YMhiDOF66ORkQ4U/eoPX7mDn8RXz/kTRwPT09ndovBiMvf5dO4qRHPvX7mDm8TFpa4r0/CF4qlVITePpvkJ8zq6urB+VKpdKJdR/+Xuz78HCQp8PgyWVhsOR5MFhyIIaBb0dD7vBskunp6dbm5mZrZ2entbGxcfABNTk52VbSul/P/mNjY6NvbdM/gzpmdnZ2WtPT049d6XX8UalUDvrF4PXzeNkffOz04Sq/fOj3Z8zxC2X2v5hPT0+3FhYWWpVK5eC5Aad8GuR3mTROeuRXP4+Z4/cNO/45Mzs7e9BmOytIMBh5yZmKxWJraWmptbm52drc3GwtLS0dxHyPGS55Oebk6VxkclkYLHkeDFZevo/KgeiUwe0LYn9Z1sMfGpVK5VR/pDc2NlqlUqlVLBZPtWRrL9qm/wZ5zHD+OF44rX4dMzs7O62FhYXH2iqVSq3p6enW6uqqk7fnhM8ZTqtfx8zW1lZrdnb2oNzxz5m1tTWfM+fEID9nVldXDy642m97/7YaLr4aXvJ0GDzfMWGwvAdhsORAnFeFVqvVCgAAAAAAAADIsUuD7gAAAAAAAAAAZDG4DQAAAAAAAEDuGdwGAAAAAAAAIPcMbgMAAAAAAACQewa3AQAAAAAAAMg9g9sAAAAAAAAA5J7BbQAAAAAAAAByz+A2AAAAAAAAALlncBsAAAAAAACA3DO4DQAAAAAAAEDuGdwGAAAAAAAAIPcMbgMAAAAAAACQewa3AQAAyJ2pqakoFAoxNzc36K4AAACcOTkQtMfgNgAAALlTq9UiImJmZiaxzPLycoyOjkahUMh8lMvlx/ZvNBoxMTGRut/ExMSZ/Y4AAAD75EDQHoPbAAAA5Mr6+vrBz5VKJbHcwsJC7OzsxNbWVkxOTp5YZmlpKVqtVmxubj4WK5VKsbW1FTs7O4/tXywWY3V1Nba2tjr8LQAAANo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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, 0.6], [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, 0.6], [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 endVelo\")\n",
    "plt.colorbar(a0[3], ax=ax1)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parameterisation for rad_length_frac:\n",
      "intercept= 0.0\n",
      "coef= {'1': 0.19432666451166924, 'x': -0.00010136532791187516, 'y': -0.00022209404990607013, 'tx': 0.058480207541052064, 'ty': 0.18599542917589618, 'qop': -17.657405901936546, 'x^2': 1.2271024867047469e-05, 'x y': 5.376824972059055e-08, 'x tx': -0.025941371835257743, 'x ty': 0.014328015524776564, 'x qop': -0.38410998543244235, 'y^2': -1.8261507968709735e-05, 'y tx': -0.014951077113227147, 'y ty': 0.02154311538810164, 'y qop': -0.008987663050567057, 'tx^2': 9.180854607357592, 'tx ty': 0.1873064867954838, 'tx qop': -0.47120712928737807, 'ty^2': -6.787398610853974, 'ty qop': -0.05031041352613623, 'qop^2': 0.24778641944197533, 'x^3': -5.992321693190818e-09, 'x^2 y': -2.649404482539432e-07, 'x^2 tx': 5.42176741002125e-06, 'x^2 ty': 0.0020253771536145383, 'x^2 qop': 0.003955288970107154, 'x y^2': 2.8906882704270233e-09, 'x y tx': -0.0016493773782229844, 'x y ty': 0.0005067592007986898, 'x y qop': -0.0031813438496783404, 'x tx^2': 0.0022653308811514867, 'x tx ty': -1.5366360302916284, 'x tx qop': -0.47946313010450653, 'x ty^2': -0.16776305178984158, 'x ty qop': 2.1889500302073115, 'x qop^2': 0.008745243979922932, 'y^3': 1.4363120470761714e-08, 'y^2 tx': -0.0005062978553841023, 'y^2 ty': 1.4165440283044409e-05, 'y^2 qop': -0.005787147937546765, 'y tx^2': 1.404047645962725, 'y tx ty': 0.1643910546131908, 'y tx qop': 2.0452379823825813, 'y ty^2': -0.02140660574730952, 'y ty qop': 4.596387657867597, 'y qop^2': -0.00994088354226498, 'tx^3': -0.1303976515212055, 'tx^2 ty': -0.01339610187978276, 'tx^2 qop': -0.0009383144690666937, 'tx ty^2': 0.010330807276347866, 'tx ty qop': 0.00564141621903312, 'tx qop^2': 1.1663926820802422e-05, 'ty^3': 0.00629773549670367, 'ty^2 qop': 0.012052455601588194, 'ty qop^2': -1.60166284721317e-05, 'qop^3': -1.5639205966369518e-06, 'x^4': 1.4244960766518489e-09, 'x^3 y': -3.1096076824610464e-09, 'x^3 tx': -3.587531603760352e-06, 'x^3 ty': 2.4713133050052738e-05, 'x^3 qop': 2.5845963699160437e-05, 'x^2 y^2': -2.0323240867980985e-09, 'x^2 y tx': 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3.0725068466100624e-07, 'y qop^4': -4.09432863754477e-09, 'tx^5': -0.052446331725343374, 'tx^4 ty': -0.0031642363210890884, 'tx^4 qop': 5.831594421042545e-05, 'tx^3 ty^2': -0.005193740457310502, 'tx^3 ty qop': 1.5211405438268112e-05, 'tx^3 qop^2': 7.987434860389955e-09, 'tx^2 ty^3': -0.0017266713029734364, 'tx^2 ty^2 qop': -3.2665518364513855e-06, 'tx^2 ty qop^2': -1.2886641260179494e-07, 'tx^2 qop^3': -7.431322766916425e-10, 'tx ty^4': -0.0009711418007784676, 'tx ty^3 qop': -1.1566774851255521e-05, 'tx ty^2 qop^2': 3.07405227672554e-08, 'tx ty qop^3': 1.5258831556369568e-09, 'tx qop^4': 6.567772758657935e-12, 'ty^5': 0.00011456709116180268, 'ty^4 qop': 6.736678103390532e-06, 'ty^3 qop^2': -6.391677860197088e-08, 'ty^2 qop^3': 8.915568061124554e-10, 'ty qop^4': -6.626331897050053e-12, 'qop^5': -2.2660425734485018e-13}\n",
      "r2 score= 0.04993524171391073\n",
      "RMSE = 0.12351226258714283\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x900 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rad_length_frac = found[\"rad_length_frac\"]\n",
    "# @ z = 9400.mm or 770.mm\n",
    "state = 1\n",
    "\n",
    "if state == 1:\n",
    "    slopex = found[\"ideal_state_770_tx\"]\n",
    "    slopey = found[\"ideal_state_770_ty\"]\n",
    "    x = found[\"ideal_state_770_x\"]\n",
    "    y = found[\"ideal_state_770_y\"]\n",
    "    qop = found[\"ideal_state_770_qop\"]\n",
    "elif state == 2:\n",
    "    slopex = found[\"ideal_state_9410_tx\"]\n",
    "    slopey = found[\"ideal_state_9410_ty\"]\n",
    "    x = found[\"ideal_state_9410_x\"]\n",
    "    y = found[\"ideal_state_9410_y\"]\n",
    "    qop = found[\"ideal_state_9410_qop\"]\n",
    "\n",
    "data = ak.zip({\n",
    "    \"rad_length_frac\": rad_length_frac,\n",
    "    \"x\": x,\n",
    "    \"y\": y,\n",
    "    \"tx\": slopex,\n",
    "    \"ty\": slopey,\n",
    "    \"qop\": qop,\n",
    "})\n",
    "lin_reg, features, xx0_test, xx0_predicted = fit_linear_regression_model(\n",
    "    data,\n",
    "    \"rad_length_frac\",\n",
    "    [\"x\", \"y\", \"tx\", \"ty\", \"qop\"],\n",
    "    5,\n",
    "    include_bias=True,\n",
    ")\n",
    "\n",
    "nbins = 100\n",
    "vmax = 100\n",
    "\n",
    "a0 = plt.hist2d(\n",
    "    xx0_test,\n",
    "    xx0_predicted,\n",
    "    density=False,\n",
    "    bins=nbins,\n",
    "    cmap=plt.cm.jet,\n",
    "    cmin=1,\n",
    "    vmax=vmax,\n",
    "    range=[[0, 0.5], [0, 0.5]],\n",
    ")\n",
    "plt.plot([0, 0.5], [0, 0.5], marker=\"\", alpha=0.8)\n",
    "plt.xlabel(f\"True $x/X_0$\")\n",
    "plt.ylabel(f\"Predicted $x/X_0$\")\n",
    "plt.title(f\"found rad_length_frac\")\n",
    "\n",
    "plt.colorbar(a0[3])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x600 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=(15, 6))\n",
    "\n",
    "# ax0.set_aspect(\"equal\")\n",
    "\n",
    "a0 = ax0.hist2d(\n",
    "    xx0_test,\n",
    "    xx0_predicted,\n",
    "    density=False,\n",
    "    bins=nbins,\n",
    "    cmap=plt.cm.jet,\n",
    "    cmin=1,\n",
    "    vmax=vmax,\n",
    "    range=[[0, 0.5], [0, 0.5]],\n",
    ")\n",
    "ax0.plot([0, 0.5], [0, 0.5], marker=\"\", alpha=0.8)\n",
    "ax0.set_box_aspect(1)\n",
    "ax0.set_xlabel(f\"True $x/X_0$\")\n",
    "ax0.set_ylabel(f\"Predicted $x/X_0$\")\n",
    "ax0.set_title(f\"found rad_length_frac\")\n",
    "plt.colorbar(a0[3], ax=ax0)\n",
    "\n",
    "ax1.hist(\n",
    "    xx0_test,\n",
    "    bins=100,\n",
    "    density=True,\n",
    "    alpha=0.5,\n",
    "    color=\"darkorange\",\n",
    "    histtype=\"bar\",\n",
    "    label=\"test\",\n",
    "    range=[0, 0.5],\n",
    ")\n",
    "ax1.hist(\n",
    "    xx0_predicted,\n",
    "    bins=100,\n",
    "    density=True,\n",
    "    alpha=0.5,\n",
    "    color=\"blue\",\n",
    "    histtype=\"bar\",\n",
    "    label=\"predicted\",\n",
    "    range=[0, 0.5],\n",
    ")\n",
    "ax1.set_xlim(0, 0.5)\n",
    "ax1.set_title(\"radiation length fraction endVelo\")\n",
    "ax1.set_xlabel(f\"$x/X_0$\")\n",
    "ax1.set_ylabel(\"a.u.\")\n",
    "ax1.set_box_aspect(1)\n",
    "\n",
    "ax1.legend()\n",
    "\n",
    "# plt.gca().set_aspect(\"equal\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(\n",
    "    xx0_test,\n",
    "    bins=100,\n",
    "    density=True,\n",
    "    alpha=0.5,\n",
    "    color=\"darkorange\",\n",
    "    histtype=\"bar\",\n",
    "    label=\"test\",\n",
    "    range=[0, 0.5],\n",
    ")\n",
    "plt.hist(\n",
    "    xx0_predicted,\n",
    "    bins=100,\n",
    "    density=True,\n",
    "    alpha=0.5,\n",
    "    color=\"blue\",\n",
    "    histtype=\"bar\",\n",
    "    label=\"predicted\",\n",
    "    range=[0, 0.5],\n",
    ")\n",
    "plt.xlim(0, 0.5)\n",
    "# plt.yscale(\"log\")\n",
    "plt.title(\"radiation length fraction endVelo\")\n",
    "plt.xlabel(f\"$x/X_0$\")\n",
    "plt.ylabel(\"a.u.\")\n",
    "\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parameterisation for rad_length_frac:\n",
      "intercept= 0.0\n",
      "coef= {'1': 0.24562140630345797, 'x': -0.0006147519300623754, 'y': 0.00013149294035773212, 'tx': 0.40993139584024857, 'ty': -0.17613130993997955, 'qop': -2.431621847221756, 'x^2': -2.537929422256502e-05, 'x y': 1.6503609236837168e-05, 'x tx': 0.014114349319941343, 'x ty': -0.015914217992780068, 'x qop': -0.3138750804691517, 'y^2': 8.004082295422125e-06, 'y tx': -0.0007103518977325451, 'y ty': -0.012102735170731998, 'y qop': -0.01613366131755978, 'tx^2': -1.1805199392607937, 'tx ty': 2.630285174738731, 'tx qop': 0.2259863956524285, 'ty^2': -0.9000770143303645, 'ty qop': 0.035317808178541486, 'qop^2': 0.506257028947111, 'x^3': -1.054613771280784e-06, 'x^2 y': -7.542919321773425e-07, 'x^2 tx': 0.0016046817739745617, 'x^2 ty': 0.0041420285105903745, 'x^2 qop': 0.021289920901612722, 'x y^2': 1.6630958165414549e-06, 'x y tx': -0.0029322410866066016, 'x y ty': 0.00026646565396820643, 'x y qop': 0.008117926325135527, 'x tx^2': -0.6007987905052633, 'x tx ty': -2.98887506065023, 'x tx qop': -13.962516223136573, 'x ty^2': -0.8388571705095013, 'x ty qop': -3.036359977877559, 'x qop^2': 0.055324587199241985, 'y^3': -8.030979246897996e-08, 'y^2 tx': -0.002767856037518542, 'y^2 ty': 0.00010106006074174414, 'y^2 qop': 0.0087584836303898, 'y tx^2': 2.52086358169213, 'y tx ty': 1.771954217213756, 'y tx qop': -3.4960101511969945, 'y ty^2': -0.02778479572722497, 'y ty qop': -8.306825049361231, 'y qop^2': 0.011633837171348742, 'tx^3': -0.1376005395953692, 'tx^2 ty': 0.08788148993360365, 'tx^2 qop': -0.03627295634145932, 'tx ty^2': 0.03876102551307681, 'tx ty qop': -0.008986008881728739, 'tx qop^2': 9.888031370307247e-05, 'ty^3': -0.3359335900376418, 'ty^2 qop': -0.02333508540052829, 'ty qop^2': 9.573184641700597e-06, 'qop^3': -4.597612275351735e-06, 'x^4': -6.108581640518196e-09, 'x^3 y': -6.564809273967853e-08, 'x^3 tx': 1.5150502404637223e-05, 'x^3 ty': 3.104184179880676e-05, 'x^3 qop': 8.671096332828199e-05, 'x^2 y^2': -7.650740829062697e-09, 'x^2 y tx': 0.00011735105575993998, 'x^2 y ty': -3.2175113096499786e-05, 'x^2 y qop': 6.774919445144169e-05, 'x^2 tx^2': -0.011724689654149013, 'x^2 tx ty': -0.043137944250594654, 'x^2 tx qop': -0.0234816944437721, 'x^2 ty^2': -0.015910369617829878, 'x^2 ty qop': 0.47749147066068204, 'x^2 qop^2': 10.59413029512916, 'x y^3': 3.234245482541809e-08, 'x y^2 tx': 5.3043264426122505e-05, 'x y^2 ty': -5.8168920071072217e-05, 'x y^2 qop': -0.00018640913107006996, 'x y tx^2': -0.06797789037420698, 'x y tx ty': 0.044976962291121, 'x y tx qop': -0.5074481714386293, 'x y ty^2': 0.03709689469083238, 'x y ty qop': 0.42061549746065124, 'x y qop^2': 5.878761197856953, 'x tx^3': 2.928172660629093, 'x tx^2 ty': 15.518053547545511, 'x tx^2 qop': -0.4179045108625407, 'x tx ty^2': 2.863496001226073, 'x tx ty qop': 0.03316794782068423, 'x tx qop^2': 0.011365298564370092, 'x ty^3': -8.111988620415804, 'x ty^2 qop': -0.21644263264392571, 'x ty qop^2': 0.00843273298050687, 'x qop^3': -0.00016877332507871679, 'y^4': 6.023639254060242e-09, 'y^3 tx': -1.594750695611824e-05, 'y^3 ty': -1.437326358022517e-05, 'y^3 qop': -2.1442523502287515e-05, 'y^2 tx^2': -0.04753636763140216, 'y^2 tx ty': 0.018902432682699272, 'y^2 tx qop': -0.31014755455483073, 'y^2 ty^2': 0.011363729381750311, 'y^2 ty qop': 0.01681916414935703, 'y^2 qop^2': -5.242995516210874, 'y tx^3': 12.07113658017565, 'y tx^2 ty': 2.5063182953688687, 'y tx^2 qop': 0.05008258889078114, 'y tx ty^2': -5.840846904263012, 'y tx ty qop': -0.2222888950764648, 'y tx qop^2': 0.008403354774191822, 'y ty^3': -2.8576703684113554, 'y ty^2 qop': 0.156828601288708, 'y ty qop^2': -0.010489395507591974, 'y qop^3': 1.6753570524717795e-05, 'tx^4': -0.01910867380555672, 'tx^3 ty': 0.0837123623190646, 'tx^3 qop': -0.0014826028602247271, 'tx^2 ty^2': 0.0015368291104171875, 'tx^2 ty qop': 8.478961198550636e-05, 'tx^2 qop^2': 1.2316906385746789e-05, 'tx ty^3': -0.0271004544137963, 'tx ty^2 qop': -0.0008124467158542836, 'tx ty qop^2': 1.1953538675306295e-05, 'tx qop^3': -1.6561432689863052e-07, 'ty^4': -0.051346978654440316, 'ty^3 qop': 0.0005598437003601672, 'ty^2 qop^2': -1.8064704330828996e-05, 'ty qop^3': 3.8598127279103275e-08, 'qop^4': 3.326704284195817e-08, 'x^5': 6.821222753305989e-11, 'x^4 y': 2.526661102564276e-10, 'x^4 tx': -1.251389993850438e-07, 'x^4 ty': 3.4387986458384034e-08, 'x^4 qop': 8.496537125812775e-06, 'x^3 y^2': 5.454374729652045e-10, 'x^3 y tx': -5.823518507419578e-07, 'x^3 y ty': 1.573480655436832e-06, 'x^3 y qop': 1.1149119954367848e-05, 'x^3 tx^2': 7.080646439604904e-05, 'x^3 tx ty': -0.00019832304528768704, 'x^3 tx qop': -0.013548718492619474, 'x^3 ty^2': -0.0011831441371068785, 'x^3 ty qop': -0.007475115795384159, 'x^3 qop^2': -0.05297421345055594, 'x^2 y^3': -3.0988589472258354e-10, 'x^2 y^2 tx': -2.827730114507432e-06, 'x^2 y^2 ty': 3.25980575599516e-06, 'x^2 y^2 qop': -1.1472914959842484e-05, 'x^2 y tx^2': 0.0005880138985921626, 'x^2 y tx ty': -0.00028281256289024864, 'x^2 y tx qop': -0.011299091385256742, 'x^2 y ty^2': -0.0028883860783337767, 'x^2 y ty qop': 0.015857147862434813, 'x^2 y qop^2': -0.13581771520502617, 'x^2 tx^3': -0.011192107550488224, 'x^2 tx^2 ty': 0.12486137523256921, 'x^2 tx^2 qop': 5.225482032478654, 'x^2 tx ty^2': 0.7550762571921301, 'x^2 tx ty qop': 3.755310333424372, 'x^2 tx qop^2': 0.03529628798503831, 'x^2 ty^3': 0.0680249197813556, 'x^2 ty^2 qop': -2.149779516970109, 'x^2 ty qop^2': -0.10043851798514322, 'x^2 qop^3': -0.008357891977863841, 'x y^4': -3.010369731271112e-10, 'x y^3 tx': -2.5632317350865463e-06, 'x y^3 ty': -1.5046913748317792e-06, 'x y^3 qop': -7.480400594950254e-06, 'x y^2 tx^2': 0.0024216018281754056, 'x y^2 tx ty': 0.0007084178707292381, 'x y^2 tx qop': 0.00044348353393648763, 'x y^2 ty^2': 0.0026684932410411567, 'x y^2 ty qop': 0.004142697700575095, 'x y^2 qop^2': 0.04019255202302588, 'x y tx^3': -0.21609228057090962, 'x y tx^2 ty': -0.39898880238968853, 'x y tx^2 qop': 3.716497181247638, 'x y tx ty^2': 1.7005468399990162, 'x y tx ty qop': -1.6246665305727963, 'x y tx qop^2': -0.10861921254973068, 'x y ty^3': -1.0206195922719212, 'x y ty^2 qop': -2.2538410252773176, 'x y ty qop^2': 0.12471546683983396, 'x y qop^3': 0.0010355202027286007, 'x tx^4': -0.38054051948182677, 'x tx^3 ty': 0.02811376405424165, 'x tx^3 qop': 0.024914607795988558, 'x tx^2 ty^2': -0.2390526017685849, 'x tx^2 ty qop': 0.016195442265039908, 'x tx^2 qop^2': -7.88453042343562e-06, 'x tx ty^3': 0.15152568889899992, 'x tx ty^2 qop': -0.008761905989985623, 'x tx ty qop^2': -0.00028476668103488885, 'x tx qop^3': -1.3992733945114136e-05, 'x ty^4': -0.17984996125743222, 'x ty^3 qop': -0.010938588150706838, 'x ty^2 qop^2': 0.00028736668746421283, 'x ty qop^3': 1.0017755372740274e-06, 'x qop^4': 5.647205119564429e-08, 'y^5': 2.2355894913062002e-11, 'y^4 tx': 2.1532131875279248e-06, 'y^4 ty': -4.644247597607176e-08, 'y^4 qop': -6.709499208279457e-06, 'y^3 tx^2': 0.0016621305979105314, 'y^3 tx ty': -0.003130496631703698, 'y^3 tx qop': 0.0073473064465471, 'y^3 ty^2': 3.1438102391929956e-05, 'y^3 ty qop': 0.009790096490369568, 'y^3 qop^2': 0.007755101347045138, 'y^2 tx^3': -0.5967738984072392, 'y^2 tx^2 ty': -1.6414346613041646, 'y^2 tx^2 qop': -1.9221000353689144, 'y^2 tx ty^2': 1.1296103381428921, 'y^2 tx ty qop': -2.0138360070431838, 'y^2 tx qop^2': 0.10014966880153775, 'y^2 ty^3': -0.006765532531283773, 'y^2 ty^2 qop': -3.489466677603648, 'y^2 ty qop^2': -0.15818840693723135, 'y^2 qop^3': -0.006154290860857408, 'y tx^4': 0.06713941420974948, 'y tx^3 ty': -0.18765968488942172, 'y tx^3 qop': 0.01494671954085084, 'y tx^2 ty^2': 0.02688242692225791, 'y tx^2 ty qop': -0.008806488292543392, 'y tx^2 qop^2': -0.0002890003079734742, 'y tx ty^3': 0.0560088747156591, 'y tx ty^2 qop': -0.0091269069301046, 'y tx ty qop^2': 0.0002557631704771736, 'y tx qop^3': 9.13083085488923e-07, 'y ty^4': -0.11308027221966196, 'y ty^3 qop': -0.015522487055330275, 'y ty^2 qop^2': -0.0004358549211642052, 'y ty qop^3': -9.99916544547057e-06, 'y qop^4': -1.583944618976334e-08, 'tx^5': -0.0039057973828551464, 'tx^4 ty': 0.0011021677966443968, 'tx^4 qop': 8.364509298284483e-05, 'tx^3 ty^2': -0.0019793041595461795, 'tx^3 ty qop': 4.1168080154112314e-05, 'tx^3 qop^2': -2.463097953215033e-07, 'tx^2 ty^3': 0.0007208243773861416, 'tx^2 ty^2 qop': -2.5859488653297416e-05, 'tx^2 ty qop^2': -5.822330221226121e-07, 'tx^2 qop^3': -2.1963163726583706e-08, 'tx ty^4': 0.00020328501105408336, 'tx ty^3 qop': -2.7986469931730596e-05, 'tx ty^2 qop^2': 4.5313369723243955e-07, 'tx ty qop^3': 6.464504187809654e-10, 'tx qop^4': 9.133899373812518e-11, 'ty^5': -0.0025485559385795883, 'ty^4 qop': -5.08771174897897e-05, 'ty^3 qop^2': -9.412302186542877e-07, 'ty^2 qop^3': -1.55479697478695e-08, 'ty qop^4': -1.861631536431087e-11, 'qop^5': -1.2879922620235152e-12}\n",
      "r2 score= 0.013501590753704495\n",
      "RMSE = 0.2590497099709809\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x900 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rad_length_frac = lost[\"rad_length_frac\"]\n",
    "# @ z = 9400.mm or 770.mm\n",
    "state = 1\n",
    "\n",
    "if state == 1:\n",
    "    slopex = lost[\"ideal_state_770_tx\"]\n",
    "    slopey = lost[\"ideal_state_770_ty\"]\n",
    "    x = lost[\"ideal_state_770_x\"]\n",
    "    y = lost[\"ideal_state_770_y\"]\n",
    "    qop = lost[\"ideal_state_770_qop\"]\n",
    "elif state == 2:\n",
    "    slopex = lost[\"ideal_state_9410_tx\"]\n",
    "    slopey = lost[\"ideal_state_9410_ty\"]\n",
    "    x = lost[\"ideal_state_9410_x\"]\n",
    "    y = lost[\"ideal_state_9410_y\"]\n",
    "    qop = lost[\"ideal_state_9410_qop\"]\n",
    "\n",
    "data = ak.zip({\n",
    "    \"rad_length_frac\": rad_length_frac,\n",
    "    \"x\": x,\n",
    "    \"y\": y,\n",
    "    \"tx\": slopex,\n",
    "    \"ty\": slopey,\n",
    "    \"qop\": qop,\n",
    "})\n",
    "lin_reg, features, xx0_test, xx0_predicted = fit_linear_regression_model(\n",
    "    data,\n",
    "    \"rad_length_frac\",\n",
    "    [\"x\", \"y\", \"tx\", \"ty\", \"qop\"],\n",
    "    5,\n",
    "    include_bias=True,\n",
    ")\n",
    "\n",
    "nbins = 100\n",
    "vmax = 50\n",
    "\n",
    "a0 = plt.hist2d(\n",
    "    xx0_test,\n",
    "    xx0_predicted,\n",
    "    density=False,\n",
    "    bins=nbins,\n",
    "    cmap=plt.cm.jet,\n",
    "    cmin=1,\n",
    "    vmax=vmax * stretch_factor,\n",
    "    range=[[-0.1, 1.0], [-0.1, 1.0]],\n",
    ")\n",
    "plt.plot([-0.1, 1.0], [-0.1, 1.0], marker=\"\", alpha=0.8)\n",
    "plt.xlabel(f\"True $x/X_0$\")\n",
    "plt.ylabel(f\"Predicted $x/X_0$\")\n",
    "plt.title(f\"lost rad_length_frac\")\n",
    "# ax1.set(xlim=(0,4000), ylim=(-1000,1000))\n",
    "\n",
    "plt.colorbar(a0[3])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame({\n",
    "    \"phi\": phi_a * 90.0 / np.pi,\n",
    "    \"eta\": eta_a * 2.0,\n",
    "    \"rad_length_frac\": rad_length_frac_a,\n",
    "})\n",
    "df = df.round({\"phi\": 0, \"eta\": 1, \"rad_length_frac\": 4})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_pivoted = df.pivot_table(\n",
    "    index=\"eta\",\n",
    "    columns=\"phi\",\n",
    "    values=\"rad_length_frac\",\n",
    "    margins=False,\n",
    "    # fill_value=0,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>phi</th>\n",
       "      <th>-90.0</th>\n",
       "      <th>-89.0</th>\n",
       "      <th>-88.0</th>\n",
       "      <th>-87.0</th>\n",
       "      <th>-86.0</th>\n",
       "      <th>-85.0</th>\n",
       "      <th>-84.0</th>\n",
       "      <th>-83.0</th>\n",
       "      <th>-82.0</th>\n",
       "      <th>-81.0</th>\n",
       "      <th>...</th>\n",
       "      <th>81.0</th>\n",
       "      <th>82.0</th>\n",
       "      <th>83.0</th>\n",
       "      <th>84.0</th>\n",
       "      <th>85.0</th>\n",
       "      <th>86.0</th>\n",
       "      <th>87.0</th>\n",
       "      <th>88.0</th>\n",
       "      <th>89.0</th>\n",
       "      <th>90.0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>eta</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.137133</td>\n",
       "      <td>0.140800</td>\n",
       "      <td>0.137350</td>\n",
       "      <td>0.155200</td>\n",
       "      <td>0.160000</td>\n",
       "      <td>0.146800</td>\n",
       "      <td>0.146500</td>\n",
       "      <td>0.164300</td>\n",
       "      <td>0.177060</td>\n",
       "      <td>...</td>\n",
       "      <td>0.18345</td>\n",
       "      <td>0.176550</td>\n",
       "      <td>0.149900</td>\n",
       "      <td>0.152733</td>\n",
       "      <td>0.161000</td>\n",
       "      <td>0.160900</td>\n",
       "      <td>0.13870</td>\n",
       "      <td>0.137400</td>\n",
       "      <td>0.137200</td>\n",
       "      <td>0.13425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.1</th>\n",
       "      <td>0.1510</td>\n",
       "      <td>0.137575</td>\n",
       "      <td>0.141467</td>\n",
       "      <td>0.137575</td>\n",
       "      <td>0.152850</td>\n",
       "      <td>0.160033</td>\n",
       "      <td>0.176100</td>\n",
       "      <td>0.149350</td>\n",
       "      <td>0.173250</td>\n",
       "      <td>0.173386</td>\n",
       "      <td>...</td>\n",
       "      <td>0.16720</td>\n",
       "      <td>0.169650</td>\n",
       "      <td>0.163200</td>\n",
       "      <td>0.153900</td>\n",
       "      <td>0.157467</td>\n",
       "      <td>0.151300</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.136850</td>\n",
       "      <td>0.138880</td>\n",
       "      <td>0.13610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.2</th>\n",
       "      <td>0.1322</td>\n",
       "      <td>0.137800</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.135900</td>\n",
       "      <td>0.141100</td>\n",
       "      <td>0.165500</td>\n",
       "      <td>0.149975</td>\n",
       "      <td>0.149429</td>\n",
       "      <td>0.152883</td>\n",
       "      <td>0.174633</td>\n",
       "      <td>...</td>\n",
       "      <td>0.16582</td>\n",
       "      <td>0.155200</td>\n",
       "      <td>0.153533</td>\n",
       "      <td>0.147900</td>\n",
       "      <td>0.164650</td>\n",
       "      <td>0.140775</td>\n",
       "      <td>0.14170</td>\n",
       "      <td>0.137314</td>\n",
       "      <td>0.137133</td>\n",
       "      <td>0.13620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.135900</td>\n",
       "      <td>0.136300</td>\n",
       "      <td>0.135900</td>\n",
       "      <td>0.137788</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.153367</td>\n",
       "      <td>0.145900</td>\n",
       "      <td>0.146350</td>\n",
       "      <td>0.158700</td>\n",
       "      <td>...</td>\n",
       "      <td>0.16390</td>\n",
       "      <td>0.148220</td>\n",
       "      <td>0.146367</td>\n",
       "      <td>0.147600</td>\n",
       "      <td>0.156067</td>\n",
       "      <td>0.141640</td>\n",
       "      <td>0.14135</td>\n",
       "      <td>0.136250</td>\n",
       "      <td>0.135740</td>\n",
       "      <td>0.13870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.4</th>\n",
       "      <td>0.1356</td>\n",
       "      <td>0.136075</td>\n",
       "      <td>0.139525</td>\n",
       "      <td>0.137800</td>\n",
       "      <td>0.138975</td>\n",
       "      <td>0.163250</td>\n",
       "      <td>0.153900</td>\n",
       "      <td>0.149725</td>\n",
       "      <td>0.147800</td>\n",
       "      <td>0.156467</td>\n",
       "      <td>...</td>\n",
       "      <td>0.15555</td>\n",
       "      <td>0.149933</td>\n",
       "      <td>0.150256</td>\n",
       "      <td>0.158500</td>\n",
       "      <td>0.157440</td>\n",
       "      <td>0.137333</td>\n",
       "      <td>0.13620</td>\n",
       "      <td>0.136820</td>\n",
       "      <td>0.136467</td>\n",
       "      <td>0.14150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9.6</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.092700</td>\n",
       "      <td>0.097750</td>\n",
       "      <td>0.099525</td>\n",
       "      <td>0.098250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.092600</td>\n",
       "      <td>0.097100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.093400</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.090000</td>\n",
       "      <td>0.100500</td>\n",
       "      <td>0.095100</td>\n",
       "      <td>0.100500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.09600</td>\n",
       "      <td>0.091850</td>\n",
       "      <td>0.094067</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9.7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.098700</td>\n",
       "      <td>0.093400</td>\n",
       "      <td>0.090750</td>\n",
       "      <td>0.090000</td>\n",
       "      <td>0.088100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.09120</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.093500</td>\n",
       "      <td>0.096200</td>\n",
       "      <td>0.097100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.095400</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9.8</th>\n",
       "      <td>0.0922</td>\n",
       "      <td>0.092300</td>\n",
       "      <td>0.096600</td>\n",
       "      <td>0.089067</td>\n",
       "      <td>0.092600</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.080200</td>\n",
       "      <td>0.091950</td>\n",
       "      <td>0.090867</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.076700</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.087750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.09200</td>\n",
       "      <td>0.080300</td>\n",
       "      <td>0.100300</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9.9</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.090800</td>\n",
       "      <td>0.084900</td>\n",
       "      <td>0.076200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.085500</td>\n",
       "      <td>0.090000</td>\n",
       "      <td>0.098400</td>\n",
       "      <td>0.090000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.30180</td>\n",
       "      <td>0.089000</td>\n",
       "      <td>0.088900</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.090000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.081600</td>\n",
       "      <td>0.088767</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.191400</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.119100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.178500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.104250</td>\n",
       "      <td>0.110900</td>\n",
       "      <td>0.085500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.081500</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>61 rows × 181 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "phi    -90.0     -89.0     -88.0     -87.0     -86.0     -85.0     -84.0  \\\n",
       "eta                                                                        \n",
       "4.0      NaN  0.137133  0.140800  0.137350  0.155200  0.160000  0.146800   \n",
       "4.1   0.1510  0.137575  0.141467  0.137575  0.152850  0.160033  0.176100   \n",
       "4.2   0.1322  0.137800       NaN  0.135900  0.141100  0.165500  0.149975   \n",
       "4.3      NaN  0.135900  0.136300  0.135900  0.137788       NaN  0.153367   \n",
       "4.4   0.1356  0.136075  0.139525  0.137800  0.138975  0.163250  0.153900   \n",
       "...      ...       ...       ...       ...       ...       ...       ...   \n",
       "9.6      NaN  0.092700  0.097750  0.099525  0.098250       NaN  0.092600   \n",
       "9.7      NaN       NaN       NaN  0.098700  0.093400  0.090750  0.090000   \n",
       "9.8   0.0922  0.092300  0.096600  0.089067  0.092600       NaN  0.080200   \n",
       "9.9      NaN  0.090800  0.084900  0.076200       NaN  0.085500  0.090000   \n",
       "10.0     NaN  0.191400       NaN  0.119100       NaN  0.178500       NaN   \n",
       "\n",
       "phi      -83.0     -82.0     -81.0  ...     81.0      82.0      83.0  \\\n",
       "eta                                 ...                                \n",
       "4.0   0.146500  0.164300  0.177060  ...  0.18345  0.176550  0.149900   \n",
       "4.1   0.149350  0.173250  0.173386  ...  0.16720  0.169650  0.163200   \n",
       "4.2   0.149429  0.152883  0.174633  ...  0.16582  0.155200  0.153533   \n",
       "4.3   0.145900  0.146350  0.158700  ...  0.16390  0.148220  0.146367   \n",
       "4.4   0.149725  0.147800  0.156467  ...  0.15555  0.149933  0.150256   \n",
       "...        ...       ...       ...  ...      ...       ...       ...   \n",
       "9.6   0.097100       NaN  0.093400  ...      NaN  0.090000  0.100500   \n",
       "9.7   0.088100       NaN       NaN  ...  0.09120       NaN       NaN   \n",
       "9.8   0.091950  0.090867       NaN  ...      NaN  0.076700       NaN   \n",
       "9.9   0.098400  0.090000       NaN  ...  0.30180  0.089000  0.088900   \n",
       "10.0       NaN       NaN       NaN  ...      NaN  0.104250  0.110900   \n",
       "\n",
       "phi       84.0      85.0      86.0     87.0      88.0      89.0     90.0  \n",
       "eta                                                                       \n",
       "4.0   0.152733  0.161000  0.160900  0.13870  0.137400  0.137200  0.13425  \n",
       "4.1   0.153900  0.157467  0.151300      NaN  0.136850  0.138880  0.13610  \n",
       "4.2   0.147900  0.164650  0.140775  0.14170  0.137314  0.137133  0.13620  \n",
       "4.3   0.147600  0.156067  0.141640  0.14135  0.136250  0.135740  0.13870  \n",
       "4.4   0.158500  0.157440  0.137333  0.13620  0.136820  0.136467  0.14150  \n",
       "...        ...       ...       ...      ...       ...       ...      ...  \n",
       "9.6   0.095100  0.100500       NaN  0.09600  0.091850  0.094067      NaN  \n",
       "9.7   0.093500  0.096200  0.097100      NaN  0.095400       NaN      NaN  \n",
       "9.8   0.087750       NaN       NaN  0.09200  0.080300  0.100300      NaN  \n",
       "9.9        NaN  0.090000       NaN      NaN  0.081600  0.088767      NaN  \n",
       "10.0  0.085500       NaN       NaN      NaN       NaN  0.081500      NaN  \n",
       "\n",
       "[61 rows x 181 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_pivoted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(15, 7))\n",
    "ax = sns.heatmap(df_pivoted,\n",
    "                 robust=True,\n",
    "                 square=False,\n",
    "                 cmap=colormaps[\"rainbow\"],\n",
    "                 xticklabels=False,\n",
    "                 yticklabels=False,\n",
    "                 vmax=0.7,\n",
    "                 cbar_kws={\n",
    "                     'label': r'$x/X_0$',\n",
    "                     'pad': 0.005,\n",
    "                     'shrink': 1,\n",
    "                     'ticks': [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7],\n",
    "                     'aspect': 15\n",
    "                 })\n",
    "# ax.set_yticks([5, 15, 25, 35], [2, 3, 4, 5])\n",
    "ax.set_yticks([0, 20, 40, 60], [2, 3, 4, 5])\n",
    "ax.set_xticks([39, 89, 139],\n",
    "              [-100, 0, 100])  # ([79, 179, 279], [-100, 0, 100])\n",
    "ax.set_xlabel(f\"$\\phi$ [deg]\")\n",
    "ax.set_ylabel(f\"$\\eta$\")\n",
    "ax.patch.set_edgecolor('black')\n",
    "\n",
    "ax.patch.set_linewidth(2)\n",
    "# ax.set_yticklabels([])\n",
    "ax.invert_yaxis()\n",
    "# ax.set_title(\"EndVELO to EndUT $x/X_0$\", size=35)\n",
    "mplhep.lhcb.text(\n",
    "    \"Simulation    \\qquad \\qquad \\qquad    EndVELO to EndUT $x/X_0$\", loc=0)\n",
    "# plt.show()\n",
    "plt.savefig(\n",
    "    \"/work/cetin/Projektpraktikum/thesis/rad_length_frac_eta_phi_2.pdf\",\n",
    "    format=\"PDF\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # make these smaller to increase the resolution\n",
    "# dy, dx = 0.1, 1.0\n",
    "\n",
    "# # generate 2 2d grids for the x & y bounds\n",
    "# y, x = np.mgrid[slice(1.5, 5 + dy, dy), slice(-180, 180 + dx, dx)]\n",
    "\n",
    "# plt.pcolormesh(x, y, df_pivoted, cmap=colormaps[\"jet\"], vmax=0.7)\n",
    "\n",
    "# plt.colorbar()\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "tuner",
   "language": "python",
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