depth_analysis_preLL_AConly.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/cosilab/miniconda3/lib/python3.11/site-packages/numpy/core/fromnumeric.py:3464: RuntimeWarning: Mean of empty slice.\n",
      "  return _methods._mean(a, axis=axis, dtype=dtype,\n",
      "/home/cosilab/miniconda3/lib/python3.11/site-packages/numpy/core/_methods.py:192: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  ret = ret.dtype.type(ret / rcount)\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from scipy.optimize import curve_fit\n",
    "from scipy import stats\n",
    "from scipy.integrate import quad\n",
    "from scipy.interpolate import UnivariateSpline\n",
    "import seaborn as sns\n",
    "from scipy.special import factorial\n",
    "import math\n",
    "from iminuit import cost, Minuit \n",
    "import numpy as np\n",
    "import pickle\n",
    "\n",
    "sns.set_context('talk', font_scale=1.0)\n",
    "sns.set_palette('colorblind')\n",
    "\n",
    "from depth_helpers import *\n",
    "\n",
    "Cs_line = source_dict['Cs137']\n",
    "\n",
    "datpath = '/home/cosilab/CalibrationData/CalibratedDATs/'\n",
    "plot_dir = '/home/cosilab/CalibrationData/figures/preLL/'\n",
    "AC_illumination_CTD = '/home/cosilab/CalibrationData/CTDs/Am241_AC_preLL_57to62keV/CTD_parameters.txt'\n",
    "DC_illumination_CTD = '/home/cosilab/CalibrationData/CTDs/Am241_DC_preLL_57to62keV/CTD_parameters.txt'\n",
    "CTD_sims = '/home/cosilab/COSITrapping/ctd_sims/CTD_HP414183.csv'\n",
    "AC_sim_events = '/home/cosilab/COSITrapping/ctd_sims/am241_interactions_HP414183_ac.csv'\n",
    "DC_sim_events = '/home/cosilab/COSITrapping/ctd_sims/am241_interactions_HP414183_dc.csv'\n",
    "sim_dCCE = '/home/cosilab/COSITrapping/cce_sims/HP414183_dCCE_1000cm.csv'\n",
    "\n",
    "calibrator = DepthCalibrator_Am241(AC_illumination_CTD, DC_illumination_CTD, AC_sim_events, DC_sim_events, CTD_sims)\n",
    "sim_depth, sim_ctd = calibrator.get_simdata()\n",
    "\n",
    "# plt.figure()\n",
    "# plt.hist(calibrator.AC_sim_CTD + np.random.normal(loc=0.0, scale=21.9, size=calibrator.AC_sim_CTD.shape), bins=100, label='Extra noise')\n",
    "# plt.hist(calibrator.DC_sim_CTD + np.random.normal(loc=0.0, scale=19.6, size=calibrator.DC_sim_CTD.shape), bins=100, color='C0')\n",
    "# plt.hist(calibrator.AC_sim_CTD + np.random.normal(loc=0.0, scale=12.0, size=calibrator.AC_sim_CTD.shape), bins=100, histtype='step', color='red', label='Original noise')\n",
    "# plt.hist(calibrator.DC_sim_CTD + np.random.normal(loc=0.0, scale=12.0, size=calibrator.DC_sim_CTD.shape), bins=100, histtype='step', color='red')\n",
    "# plt.legend()\n",
    "# plt.xlabel('CTD (ns)')\n",
    "# plt.ylabel('Counts')\n",
    "# plt.tight_layout()\n",
    "# plt.savefig(plot_dir + 'sim_CTD_noise_comparison.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "file_dict = {'Cs137': [['20231003_Cs137_AC_600V_1.dat', '20231003_Cs137_AC_600V_2.dat', '20231011_Cs137_AC_600V.dat', '20231020_Cs137_AC_600V.dat']], \\\n",
    "            'Ba133': [['20231005_Ba133_AC_600V.dat']], \\\n",
    "            'Na22': [['20231024_Na22_AC_600V_1.dat', '20231024_Na22_AC_600V_2.dat', '20231026_Na22_AC_600V.dat']], \\\n",
    "            'Am241': [['20230920_Am241_AC_600V.dat', '20231026_Am241_AC_600V.dat']]}\n",
    "\n",
    "erange_dict = {'Cs137': [630., 667.], 'Ba133': [330., 360.], 'Na22': [1220., 1280.], 'Am241': [50., 64.]}\n",
    "zbin_dict = {'Cs137': np.linspace(calibrator.zmin, calibrator.zmax, 31), \\\n",
    "             'Ba133': np.linspace(calibrator.zmin, calibrator.zmax, 31), \\\n",
    "             'Na22': np.linspace(calibrator.zmin, calibrator.zmax, 31), \\\n",
    "             'Am241': np.linspace(calibrator.zmin, calibrator.zmax, 31)}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Loop and make depth-calibrated dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM = 3.91\n",
      "FWTM = 9.17\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlsAAAHLCAYAAAD/S12vAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAABAxklEQVR4nO3dd3hUVeL/8c8ESKcEQotUIRRdWuhNlKBYEFkEFSwgfoEtKKCuq34XsSCrCFjY/SqgiAsKStPFhiJxhVVAQ3MlShNRaVICpJc5vz/4ZTZjZsIkM3cmM/N+Pc88T7j33HvO5DDMh3PPPddmjDECAACAJSIC3QAAAIBQRtgCAACwEGELAADAQoQtAAAACxG2AAAALETYAgAAsBBhCwAAwELVA92AcNeiRQsdP35c0dHRatmyZaCbAwAAPPD9998rLy9PDRo00MGDB8sta2NR08CKjY1Vbm5uoJsBAAAqISYmRjk5OeWWYWQrwKKjo5Wbm6uYmBi1b98+0M0BAAAeyMjIUG5urqKjoy9YlrAVYC1bttTp06fVvn17paenB7o5AADAA127dtW2bds8mgLEBHkAAAALEbYAAAAsRNgCAACwEGELAADAQoQtAAAACxG2AAAALETYqoCrr75aNptNf/nLXwLdFAAAECQIWx5atmyZdu7cGehmAACAIEPY8kBmZqamTp2quXPnBropAAAgyBC2PPDAAw/o0ksv1ahRowLdFAAAEGSCKmwdPXpUS5cu1eTJk9W3b1/FxsbKZrOpW7duHh2flpamIUOGqH79+oqJiVG7du00bdo0ZWdnuz1m06ZN+sc//qH/+7//89XbAAAAYSSono24fPlyTZ06tVLHzps3T5MnT5YxRk2aNFHTpk21e/duzZgxQ6tWrdKmTZtUt25dp2MKCws1ceJE3X///Wrbtq0v3gIAAAgzQTWyVatWLQ0aNEgPPvigVq5cqZkzZ3p0XHp6uqZMmSJJmj9/vg4dOqRt27bpwIED6tq1qzIyMjR+/Pgyxz399NPKzc3V//7v//rybQAAgDASVCNb48aN07hx4xx/Xrx4sUfHPfHEE7Lb7brjjjs0YcIEx/akpCQtW7ZM7dq10+rVq7Vr1y517NhRknTo0CE9+eSTevnll5Wfn6/8/HzHcfn5+crMzFTNmjVVrVo137w5AAAQkoJqZKsysrKy9OGHH0qSU9AqkZycrIEDB0qSVqxY4dh+4MAB5eXl6bbbblNCQoLjJUmzZ89WQkKCvv76az+8AwAA3Iu4f63jhaopqEa2KmP79u3Kz89XVFSUevTo4bJM//79tX79em3evNmxrXPnzkpLSytT9oorrtBtt92mu+66S61bt7as3QAAIDSEfNjas2ePJKlZs2aqUaOGyzKtWrWSJH333XeObXXq1NHll1/usnzz5s3d7pPOzwtbsGCBR+3LyMjwqBwAABdSenTLPvv6ALYEpYV82Dp16pQklbnTsLSSfadPn/ZJnUeOHNG2bdt8ci4AACrD3WVFQpj/hXzYysvLkyRFRka6LRMVFSVJys3NveD5jDEXLNO4cWOlpKR41L6MjAyP6gUAAMEp5MNWdHS0JKmgoMBtmZI7DWNiYnxS58SJEzVx4kSPynbt2pVRMAAAQljIh62SOwhLLie6UrKvpKyvlbdCvd1ut6ROAABQNYR82GrTpo2k8+tmFRYWupwkv3//fqeyvhYfH2/JeQEAQNUX8utspaSkKDIyUvn5+dq6davLMhs3bpQk9e7d259NAwAAYSDkw1Z8fLwGDx4sSS6XY9i7d682bNggSRoxYoQlbcjKynL76ty5syV1AgCAqiHkLyNK0rRp0/Tuu+9qyZIl6tu3r8aPHy+bzaYjR45o1KhRstvtGjZsmDp16mRJ/XFxcW73RUSEfN4FAPgYq8UHl6D6pv/xxx+VmJjoeN19992SpJ07dzptnzVrltNx3bt319y5cyWdv1OwefPmSklJUcuWLZWenq62bdtq4cKFlrU7Ozvb7YsJ8gAAhLagGtkqLi7WyZMny2wvKipy2p6Tk1OmzJQpU9ShQwfNmTNHW7Zs0fHjx9W8eXONGDFCDz30kKWT2JkgDwBA+AqqsNWiRQuPFhV1JzU1VampqT5sEQAA/uGrS4c80sf/gipsBausrCy3+/r166cdO3b4rzEAAMCvCFt+wAR5AADCF2ELAIAwxSVF/yBs+QGP6wEAIHwRtvyAuxEBAAhfTBgCAACwECNbfsDdiAAAhC/Clh9wNyIAoDJ4LE9o4JseAADAQoQtAAAAC3EZ0Q9Y+gEAgPBF2PIDln4AACB8cRkRAADAQoxs+QFLPwAAEL4IW37A0g8AAIQvwhYAAOCh1BZiWAUAAMBChC0AAAALcRnRD1hnCwCA8EXY8gPW2QIAeIrnIYYeLiMCAABYiJEtP2CdLQAAwhdhyw9YZwsAgPDFNz0AAICFCFsAAAAWImwBAABYiDlbAADACY/u8S3Clh+wqCkAAOGLsOUHLGoKAED4ImwBABBgrBof2ghbfsCipgAAhC/Clh+wqCkAAOGLb3oAAAALEbYAAAAsRNgCAACwEGELAADAQoQtAAAACxG2AAAALETYAgAAsBDrbAEAALd4KLX3CFt+wIOoAQC/xiN6wgdhyw94EDUAAOGLOVsAAAAWYmTLD3gQNQAA4Yuw5Qc8iBoAgPDFNz0AAICFCFsAAAAWImwBAABYiLAFAABgIcIWAACAhQhbAAAAFiJsAQAAWIh1tgAA8AOehRi+GNkCAACwECNbAADAI6VH5+yzrw9gS4ILI1sAAAAWImwBAABYiLAFAABgIeZs+UF2drbbfXa73Y8tAQAA/kbY8oP4+PhANwEAAAQIlxEBAAAsxMiWH2RlZbnd169fP+3YscN/jQEAAH5F2PKDuLg4t/siIhhcBAAglPFNDwAAYCHCFgAAgIUIWwAAABYibAEAAFiICfIAAFik9IObEb4Y2QIAALAQYQsAAMBChC0AAAALEbYAAAAsRNgCAACwEGELAADAQoQtAAAAC7HOFgAAqLDSa4jZZ18fwJZUfYxsAQAAWIiRLQAAfIhV4/FrjGwBAABYiLBVjs8//1xXXXWVkpKSFBUVpUaNGmnIkCHasmVLoJsGAACCBGGrHKdPn1b79u317LPP6qOPPtK8efN06tQp9e/fX19++WWgmwcAAIIAc7bKcd111+m6665z2nb11VcrMTFR//jHP9S9e/cAtQwAAAQLRrYqKC4uTlFRUapRo0agmwIAAIJAUIWto0ePaunSpZo8ebL69u2r2NhY2Ww2devWzaPj09LSNGTIENWvX18xMTFq166dpk2bpuzs7HKPs9vtKiws1KFDhzRp0iTZbDaNHz/eF28JAACEuKC6jLh8+XJNnTq1UsfOmzdPkydPljFGTZo0UdOmTbV7927NmDFDq1at0qZNm1S3bl2Xx1577bVat26dJKlhw4Z6//331b59+0q/DwBAaGG5B5QnqEa2atWqpUGDBunBBx/UypUrNXPmTI+OS09P15QpUyRJ8+fP16FDh7Rt2zYdOHBAXbt2VUZGRrkjVfPmzdPWrVv19ttvq3v37rrmmmv02Wef+eItAQCAEBdUI1vjxo3TuHHjHH9evHixR8c98cQTstvtuuOOOzRhwgTH9qSkJC1btkzt2rXT6tWrtWvXLnXs2LHM8cnJyY6fhw4dqn79+umee+7Rjh07Kv1eAABAeAiqka3KyMrK0ocffihJTkGrRHJysgYOHChJWrFixQXPVzJH7LvvvvNtQwEAQEgK+bC1fft25efnKyoqSj169HBZpn///pKkzZs3X/B8RUVF2rRpk1q3bu3TdgIAgNAUVJcRK2PPnj2SpGbNmrldrqFVq1aSVGa06tZbb1WLFi2UkpKixMRE/fTTT3r55Ze1Y8cOrVy50m2d8+fP14IFCzxqX0ZGhkflAABAcAr5sHXq1ClJcnunYel9p0+fdtreu3dvLV26VC+99JLOnDmjunXrqmfPntqwYYMGDBjg9nxHjhzRtm3bfNB6AAAQ7EI+bOXl5UmSIiMj3ZaJioqSJOXm5jptnzRpkiZNmlThOhs3bqyUlBSPymZkZJSpFwAAhI6QD1vR0dGSpIKCArdl8vPzJUkxMTE+qXPixImaOHGiR2W7du3KKBgAACEs5MNWQkKCpP9eTnSlZF9JWV8rb4V6u91uSZ0AAKBqCPmw1aZNG0nSoUOHVFhY6HKS/P79+53K+lp8fLwl5wUAAFVfyIetlJQURUZGKj8/X1u3blXfvn3LlNm4caOk8xPiAQBAxZR+XJF99vUBbEnVFPJhKz4+XoMHD9batWu1YMGCMmFr79692rBhgyRpxIgRlrQhKyvL7b5+/fqxEj0ABCGehwhPhfyippI0bdo02Ww2LVmyRAsWLJAxRtL5JRpGjRolu92uYcOGqVOnTpbUHxcX5/YVEREWXQAAQNgKqm/6H3/8UYmJiY7X3XffLUnauXOn0/ZZs2Y5Hde9e3fNnTtX0vk7BZs3b66UlBS1bNlS6enpatu2rRYuXGhZu7Ozs92+mCAPAEBoC6rLiMXFxTp58mSZ7UVFRU7bc3JyypSZMmWKOnTooDlz5mjLli06fvy4mjdvrhEjRuihhx6ydBI7E+QBAAhfQRW2WrRo4bgEWBmpqalKTU31YYsAAADKF1RhK1gxQR4AgPBF2PKDuLg4t/uYIA8AQGjjmx4AAMBCjGz5AY/rAYDQwNpaqAzClh9wNyIAAOGLy4gAAAAWYmTLD7gbEQCA8EXY8gPuRgQAIHzxTQ8AAGAhRrb8gLsRASB4cQcivEXY8gPuRgQAIHxxGREAAMBCjGz5AXcjAgAQvghbfsDdiAAAhC+vvukzMzP12Wefafv27WX2HTlyRCNGjFDt2rVVt25d3X777Tp+/Lg31QEAgCou4v61jhfO8ypsvfLKK7riiiu0aNEip+1FRUW66qqrtGbNGp07d06ZmZl64403lJqaqoKCAq8aDACA1QgM8CWvwtZHH30kSRo1apTT9jfffFPffPONoqOj9b//+7+aMWOGatWqpd27d2vBggXeVAkAABBUvJqztW/fPklShw4dnLa/9dZbstlseuyxx3T//fdLklq3bq1bbrlFK1eu1KRJk7ypNuiwzhYAVH2MYsEqXoWtEydOKD4+XjVr1nTa/tlnn0mSbr31Vse2YcOGyWaz6ZtvvvGmyqDEOlsAAIQvry4j5uXllRmZ+e6773TmzBklJyercePGju2RkZFKSEjQ2bNnvakSAAAgqHg1stWgQQMdPnxYR48eVaNGjSRJ69evlyT16dOnTPnc3FzVrl3bmyqDEutsAUDVxKVD+INXI1vdu3eXJM2dO1eSlJOTo5deekk2m02pqalOZX/++Wfl5uY6jXaFi7i4OLcv1tkCACC0efVNP3HiRBljNGfOHLVv315t2rTRN998o/r162v48OFOZdPS0iSVnUwPAAAQyrwKW4MHD9ajjz4qm82m7777TocPH1ZiYqJef/11xcTEOJV94403JElXXHGFN1UCAAAEFa8f1/PII49o7Nix2rJli+rUqaMePXqUmZdVUFCg3r17q2fPnrruuuu8rRIAACBo+OTZiM2aNVOzZs3c7o+MjNS0adN8URUAAEBQ8SpsPf7444qPj9e9997rUfkXXnhBmZmZeuSRR7ypFgCASuMORPibV2Hr0UcfVaNGjTwOW88++6wOHToUdmGLFeQBILAIWAgkn1xGRPlYQR4A/I+AharCr4s8nTp1StHR0f6sEgAAIKD8NrK1YsUKnTt3Tm3btvVXlVUGK8gDABC+KhS2nn/+eT3//PNO23755RddfPHFbo8xxigzM1Nnz56VzWYLy6Uf4uLi3O5jBXkAAEJbhcJWZmamDh486LStuLi4zDZ3UlNTw25yPAAACG8VClvDhg1TixYtJJ0fsRo3bpxq166t5557zu0xERERqlWrln7zm9+oVatW3rQVAAAg6FQobHXq1EmdOnVy/HncuHGKiYnRmDFjfN4wAACAUODVBHnWiAIAACgf62wBAIJC6XWz7LOvD2BLgIrxWdiy2+3au3evTp06pcLCwnLLXnbZZb6qFgAABxYyRVXkddg6cuSIHnroIa1cuVK5ubkXLG+z2VRUVORttQAASCJgoerzKmwdPnxYPXv21OHDh2WM8egYT8sBAMITlwtDB315ntcPov75559Vs2ZNPfnkk7rhhhuUlJSkatWq+ap9IYEHUQOAbzGahWDiVdj64IMPZLPZ9Morr2jEiBG+alPI4UHUAACEL6/C1i+//KLq1atr2LBhPmoOAAD/xQgWQoFXYatBgwY6e/asqldnBYny8CBqACiL+TwIF16lpEGDBum1117T3r17lZyc7Ks2hRweRA0A5zFShXDk1Tf9ww8/rLi4OP35z3/2VXsAAEEu4v61jhcAL0e2WrdurX/+85+68cYbdeWVV+rhhx9Wjx49yh3JAQCEDwIX4GXYKr3Ew4YNG7Rhw4YLHsOipgAAIJx4FbZYoBQAIDGCBZTHq7CVlpbmq3YAAAKgqtwRSFhDKPMqbA0YMMBX7QAAAAhJLJAFAPAYI1BAxbHIEwAAgIW8Gtn67LPPKnXcZZdd5k21AAAAQcOrsHX55ZfLZrNV6BiWfgAAAOHE6zlbFV3+geUiAMA6VeXuQgD/5VXYstvt5e4/e/astmzZopkzZ+rrr7/WmjVr1L9/f2+qBICw5asgxSR3wL8svRuxVq1auvLKKzVo0CANGzZMQ4cO1bZt29SyZUsrqwWAkGfFCBajYoA1/LL0g81m06xZs9S+fXs98cQTWrRokT+qrTKys7Pd7rvQ6CAAXAgjVUDV5rd1ttq2batatWrp448/9leVVUZ8fHygmwAAAALEb2GrsLBQubm5ysvL81eVAOATVl1e8+S8gRq1YrQM8B2/ha23335bhYWFatKkib+qrDKysrLc7uvXr5927Njhv8YA8KtfhxbmQgHhx9KwVVBQoB9//FGrVq3SzJkzZbPZdM0111hZZZUUFxfndl9EBIv4A6GgKk4uZ3QKqBq8ClvVqlXzuKwxRhdddJGmT5/uTZUAEPIISUBo8WpYxRjj0Ss6Olq33XabNm/erKSkJF+1HQAAoMrzamQrLS2t/JNXr66EhAS1adNG1av7bXoYAHiN0SXAt8J5/qJXCWjAgAG+agcAAEBIYrgJQFirKhPbGUkDQpfPw9YPP/yg48ePy2azqX79+mrevLmvqwAAAAgaPglbR44c0V//+lctX75cJ0+edNpXr149jR49Wn/+85/VuHFjX1QHIIz4c+TJH6NLjGAB4cfrsPXvf/9bw4YN06lTp2SMKbP/xIkTmjdvnt544w29/fbb6tOnj7dVAkCV4C44EagAlOZV2Dp+/LiGDh2q06dPq1atWvrd736nK6+80rFK/E8//aT169dr/vz5OnHihIYOHardu3erQYMGPmk8AHiqqszNAhB+vApbc+bM0enTp9WuXTt9/PHHuuiii5z2t23bVqmpqbr77rs1aNAgfffdd5o7d66eeuoprxoNwL98GVR8da5AhSdGrQBUlFeLmr733nuy2WxauHBhmaBVWlJSkhYuXChjjN59911vqgQAAAgqXo1sHTx4UHFxcerbt+8Fy/bt21dxcXH64YcfvKkSQIBV9ctxVb19AMKPV2HLZrO5nBRfnoqWBxB8PF0p2upgxCU/AFWBV2GrefPmysjI0ObNm9WrV69yy37xxRfKzs7WJZdc4k2VAKoQq8JSRUOS1eUBwBteha1rrrlGu3fv1oQJE/TJJ5+ofv36LssdP35cEyZMkM1m07XXXutNlQBcsGLSuS95cl5flQGAqsarsHX//ffrlVde0TfffKP27dvr97//vVJTU3XRRRfJZrPpxx9/1CeffKL58+fr5MmTqlOnju6//35ftR1ABTCXCQACw6uw1bBhQ61Zs0a//e1vderUKc2cOVMzZ84sU84Yozp16ujtt98OqjW2Vq1apTfffFNffvmljh49qiZNmujaa6/VI488onr16gW6eQhDBCYACD5eLf0gSQMGDNCuXbs0ceJEJSQkyBjj9EpISNDvf/97ff3117rssst80Wa/eeaZZ1RUVKTHH39cH374oe677z69+eab6tOnj3JycgLdPAAAEAR88mzEJk2a6MUXX9SLL76o77//XsePH5ckNWjQQC1btvRFFQGxdu1ap3loAwYMUHJysgYNGqRVq1bp9ttvD2DrUBWEwkgT86AAwFoVDltFRUWOUZ1atWqV2d+yZcsyAevs2bOSpLi4OFWrVq0y7QwIVxP+u3fvLun8o4gAf+D5ewAQ3Cp8GfGWW25RQkKCxo4d6/Ex48aNq/Axrhw9elRLly7V5MmT1bdvX8XGxspms6lbt24eHZ+WlqYhQ4aofv36iomJUbt27TRt2jRlZ2d73Ia0tDRJUvv27Sv1HgBPRNy/1vEKFsHYZgDwhwqNbH3zzTdavXq1ateurUWLFnl83MKFC/XJJ59o2bJleuSRR5ScnFzhhkrS8uXLNXXq1EodO2/ePE2ePFnGGDVp0kRNmzbV7t27NWPGDK1atUqbNm1S3bp1yz3H6dOnNXXqVHXo0EHXXx+cl4zgH54u6gkACH0VCluvv/66JOkPf/iD6tSp4/FxCQkJuvvuuzVjxgwtXbpUjz32WIUaWaJWrVoaNGiQunXrpm7dumnPnj16+OGHL3hcenq6pkyZIkmaP3++xo8fL5vNpsOHD2vo0KFKT0/X+PHjtWrVKrfnyMvL0/Dhw3X69Gm9++67QXU5FN6z6kHMpfEwZQAITRW6jLhx40bZbDbdeOONFa5o+PDhkqRPP/20wseWGDdunD7++GP99a9/1Y033qjGjRt7dNwTTzwhu92u22+/3bG4qnT+AdnLli1TRESEVq9erV27drk8vrCwUCNGjNDWrVv17rvvsgo+AADwWIVGtvbs2aOIiAh16dKlwhV17NhRERER+vbbbyt8rDeysrL04YcfSpImTJhQZn9ycrIGDhyo9evXa8WKFerYsaPT/uLiYo0aNUrr16/X2rVrPXroNkKDv0d/rKiPESwACLwKha3MzEzVqVPHMTJUEREREapTp47OnDlT4WO9sX37duXn5ysqKko9evRwWaZ///5av369Nm/e7LTdbrdrzJgxeuedd7Ry5UpdeeWV/mgyqriqHmCqevsAINxUKGzFxsbq3Llzla4sKytLMTExlT6+Mvbs2SNJatasmWrUqOGyTKtWrSRJ3333ndP2u+++W6+//rqmTJmihg0bOoWxJk2aqEmTJi7PN3/+fC1YsMCj9mVkZHhUDt4LhTWxAADBp0Jhq0GDBtq3b5/279/vCCie2r9/vwoKCtS8efMKHeetU6dOSVK5dxqW7Dt9+rTT9vfee0+S9Nxzz+m5555z2jd9+nQ9+uijLs935MgRbdu2rZItDi9VYbJ4aYF8EDMAIDRVKGz16tVL+/bt0+rVq/WnP/2pQhWV3OnXs2fPCh3nrby8PElSZGSk2zJRUVGSpNzcXKftBw8erFSdjRs3VkpKikdlMzIyytQL9zwZnfJVGQAAfKFCYWvIkCFasmSJnnnmGd12220e3w14+PBhzZ49WzabTUOGDKlUQysrOjpaklRQUOC2TH5+viT57BLnxIkTNXHiRI/Kdu3atcqOglkVSBjlAQCEkwqFrRtvvFHJycnat2+fBg8erDVr1lzwcuK+ffs0fPhwnThxQsnJyRo5cqRXDa6ohIQESf+9nOhKyb6Ssr5W3gr1drvdkjrDDQEOAFBVVShsRURE6LXXXtMVV1yhb775Rh07dtRtt92mYcOGqUuXLo65T6dOndL27du1Zs0avfHGG8rJyVFUVJQWL15cqTsZvdGmTRtJ0qFDh1RYWOhykvz+/fudyvpafHy8JecNF94EKU+OJagBgP+F03SOCj+IulevXnrrrbd0++236+zZs3r55Zf18ssvuy1vjFF8fLyWLFmi3r17e9XYykhJSVFkZKTy8/O1detWl+tkbdy4UZIC0r5gF8gPS1ULSVWtPQCAqqHCD6KWpOuvv15fffWVRo4cKZvNJmOMy5fNZtPIkSOVnp6uG264wddt90h8fLwGDx4sSS6XY9i7d682bNggSRoxYoQlbcjKynL76ty5syV1AgCAqqHCI1slWrdurTfffFPHjx9XWlqavvnmG508eVLGGCUmJurSSy/VFVdcoQYNGviyvZUybdo0vfvuu1qyZIn69u3reDbikSNHNGrUKNntdg0bNkydOnWypP64uDi3+yIiKpV3gw6jPgCAcFXpsFWiQYMGuvnmm33Rlgv68ccfnR4VVHIX4c6dO5WYmOjY/sADD+iBBx5w/Ll79+6aO3eu7r33Xk2cOFEzZsxQYmKidu/erfz8fLVt21YLFy60rN2hNkGe4AQAgOe8Dlv+VFxcrJMnT5bZXlRU5LQ9JyenTJkpU6aoQ4cOmjNnjrZs2aLjx4+refPmGjFihB566CFLJ7EH0wR5X05GD/UJjwAAeCKowlaLFi1kjKn08ampqUpNTfVhiwAAAMoXVGErWGVlZbnd169fP+3YscN/jfn//HEXIZcbAQAgbPkFE+QBAAhfhC0wAgUAgIUIW34QyLsRw2mFXgAAqiLClh8E092IAADAtwhbqJK4tAkACBWELT+oincjAgAA/yBs+QF3IwIAEL74pgcAALAQI1t+EArPRmQOFQAAlUPY8gPuRgQAIHxxGREAAMBCjGz5AXcjAgAQvghbfsDdiAAAhC++6QEAACzEyFYY4Y5CAAD8j7AFAAACqvRggH329QFsiTUIW34QCutsAQCAyiFs+QHrbAEAEL6YIA8AAGAhRrb8gHW2AAAIX4QtP2CdLQAAwhff9AAAABYibAEAAFiIsAUAAGAhwhYAAICFCFsAAAAW4m5EP2AFeQAAwhdhyw9YQR4AgPDFZUQAAAALMbLlB6wgDwBA+CJs+QEryAMAEL74pgcAALAQI1sAAKDKiLh/reNn++zrA9gS32FkCwAAwEKELQAAAAsRtgAAACxE2AIAALAQYQsAAMBChC0AAAALsfSDH/AgagAAwhdhyw94EDUAAOGLy4gAAAAWYmTLD3gQNQAA4Yuw5Qc8iBoAgPDFNz0AAICFCFsAAAAWImwBAABYiLAFAABgIcIWAACAhQhbAAAAFiJsAQAAWIiwBQAAYCHCFgAAgIUIWwAAABYibAEAAFiIsAUAAGAhwhYAAICFqge6AeEgOzvb7T673e7HlgAAAH8jbPlBfHx8oJsAAAAChMuIAAAAFmJkyw+ysrLc7uvXr5927Njhv8YAAAC/Imz5QVxcnNt9EREMLgIAEMr4pgcAALAQYQsAAMBChC0AAAALEbYAAAAsxAR5AABQJUXcv9bxs3329QFsiXcY2QIAALAQYQsAAMBChC0AAAALEbYAAAAsxAR5AAAQVIJt4jwjWwAAABYibAEAAFiIsAUAAGAhwhYAAICFCFsAAAAWImwBAABYiLBVjp9++kl33323evfurdjYWNlsNh08eDDQzQIAAEGEsFWOffv26a233lJCQoL69+8f6OYAAIAgRNgqx2WXXaZjx47p/fff18iRIwPdHAAAEIQIW+WIiODXAwAAvBNUaeLo0aNaunSpJk+erL59+zrmUXXr1s2j49PS0jRkyBDVr19fMTExateunaZNm6bs7GyLWw4AAMJVUD0bcfny5Zo6dWqljp03b54mT54sY4yaNGmipk2bavfu3ZoxY4ZWrVqlTZs2qW7duj5uMQAACHdBNbJVq1YtDRo0SA8++KBWrlypmTNnenRcenq6pkyZIkmaP3++Dh06pG3btunAgQPq2rWrMjIyNH78eAtbDgAAwlVQjWyNGzdO48aNc/x58eLFHh33xBNPyG6364477tCECRMc25OSkrRs2TK1a9dOq1ev1q5du9SxY0dfNxsAAHgp4v61gW5CpQXVyFZlZGVl6cMPP5Qkp6BVIjk5WQMHDpQkrVixwq9tAwAAoS/kw9b27duVn5+vqKgo9ejRw2WZkjW0Nm/e7M+mAQCAMBBUlxErY8+ePZKkZs2aqUaNGi7LtGrVSpL03Xffldm3cuVKSefnfUnSBx98oPr166t+/foaMGCAy/PNnz9fCxYs8Kh9GRkZHpUDAADBKeTD1qlTpySp3DsNS/adPn26zL5fL2b6hz/8QZI0YMAAffrppy7Pd+TIEW3btq0yzQUAACEm5MNWXl6eJCkyMtJtmaioKElSbm5umX3GmArX2bhxY6WkpHhUNiMjw2W9AAAgNIR82IqOjpYkFRQUuC2Tn58vSYqJifFJnRMnTtTEiRM9Ktu1a1dGwQAACGEhH7YSEhIk/fdyoisl+0rK+lp5K9Tb7XZL6gQAAFVDyIetNm3aSJIOHTqkwsJCl5Pk9+/f71TW1+Lj4y05LwAAqPpCfumHlJQURUZGKj8/X1u3bnVZZuPGjZKk3r17+7NpAAAgDIR82IqPj9fgwYMlyeVyDHv37tWGDRskSSNGjLCkDVlZWW5fnTt3tqROAABQNYR82JKkadOmyWazacmSJVqwYIHjDsMjR45o1KhRstvtGjZsmDp16mRJ/XFxcW5fERFh0QUAAIStoPqm//HHH5WYmOh43X333ZKknTt3Om2fNWuW03Hdu3fX3LlzJZ2/U7B58+ZKSUlRy5YtlZ6errZt22rhwoWWtTs7O9vtiwnyAACEtqCaIF9cXKyTJ0+W2V5UVOS0PScnp0yZKVOmqEOHDpozZ462bNmi48ePq3nz5hoxYoQeeughSyexM0EeAIDwFVRhq0WLFpVaZLREamqqUlNTfdgiAACA8gVV2ApWWVlZbvf169dPO3bs8F9jAACAXxG2/CAuLs7tPibIAwAQ2vimBwAAsBAjW37A43oAAAhfhC0/4G5EAADCF2ELAAAErYj71zp+ts++PoAtcY+w5QfcjQgAQPgibPkBdyMCABC++KYHAACwECNbfsDdiAAAhC/Clh9wNyIAAOGLsAUAAEJCVb0zkbDlB9yNCABA+CJs+QF3IwIAEL74pgcAALAQYQsAAMBChC0AAAALMWfLD1hnCwCA8EXY8gPW2QIAIHwRtgAAQMipSmtuEbb8gHW2AAAIX4QtP2CdLQAAwhff9AAAABYibAEAAFiIsAUAAGAhwhYAAICFCFsAAAAW4m5EP2AFeQAAwhdhyw9YQR4AgPDFZUQAAAALMbLlB6wgDwBA+CJs+QEryAMAEL74pgcAALAQYQsAAMBChC0AAAAL2YwxJtCNCGd169bV6dOnFRMTo/bt2/v8/Nt+OuPzcwIAEExSmtT2+TkzMjKUm5urhIQEnTp1qtyyhK0Ai42NVW5ubqCbAQAAKiEmJkY5OTnlluFuxABr0KCBjh8/rujoaLVs2dKn5y5J3VaNmqFqoJ/DA/0cHujn4PH9998rLy9PDRo0uGBZwlaAHTx40LJzd+3aVdu2bVP79u2Vnp5uWT0ILPo5PNDP4YF+Dk1MkAcAALAQYQsAAMBChC0AAAALEbYAAAAsRNgCAACwEGELAADAQoQtAAAACxG2AAAALETYAgAAsBBhCwAAwEI8rieETZgwQUeOHFHjxo0D3RRYiH4OD/RzeKCfQ5PNGGMC3QgAAIBQxWVEAAAACxG2AAAALETYAgAAsBBhCwAAwEKErSru/fff1/Dhw5WUlKSoqCg1bNhQffv21V/+8hcVFRU5yuXk5Gj27Nm6+eabdckllygxMVE1atRQYmKiLr/8cr344osqLCwst64DBw5o3LhxatKkiaKiotS0aVPddddd+v77761+m2HP0352Z+TIkbLZbLLZbHr00UfLLUs/B0ZF+rhFixaO/nT3ysvLc1sXfRw4lfks5+TkaNasWerRo4cSEhIUExOjFi1a6MYbb9Q777zjti76OYgYVEmFhYXmtttuM5KMJNOkSRPTvXt3c/HFF5vIyEgjyZw7d85R/vvvv3eUrVWrlmnXrp1JSUkxiYmJju3dunUzp0+fdlnf559/buLj440kk5CQYLp27Wrq1KljJJmaNWuaLVu2+Omdh5eK9rMra9ascRwvyUyfPt1tWfrZ/yrTx82bNzeSzG9+8xvTt29fl6/8/HyX9dHHgVHZz3JGRoZp0aKFkWSqVatmLrnkEpOSkmIaNWpkJJkbb7zRZX30c3AhbFVR//M//2MkmU6dOpmtW7c67cvOzjbvvPOOKSgocGw7efKkef75583u3budytrtdrNmzRoTFxdnJJnf/e53ZerKzs42jRs3NpLMuHHjTG5urjHGmNzcXHPnnXc6/uHIycmx4J2Gt4r2869lZmaapKQk07RpU9O1a9dywxb9HBiV6eOSsJWWllahuujjwKlMP//yyy+O/po0aZI5efKk0/4ffvjBfPrpp2Xqop+DD2GrCtqwYYORZJKSksp8+Crr6aefNpJMgwYNyux79tlnjSTTunXrMv9bzs/PN61atTKSzAsvvOCTtuA8X/RzyT/w77zzjhkwYEC5YYt+9r/K9nFlwxZ9HBiV7ec77rjD7X+Cy0M/Bx/mbFVBc+fOlST96U9/Ut26dX1yzvbt20s6Pzfg11asWCFJGjt2rCIjI532RUZG6s4775QkvfXWWz5pC87ztp/T0tL0yiuvaPjw4Ro6dOgFy9PP/mfFZ7k89HFgVKafjx49qmXLlikyMlKPPfZYheqjn4MPj+upYvLy8rRu3TpJ0g033KAvv/xSr776qvbu3auYmBh169bNMSGyIjZt2iRJ6tatm9P24uJiffXVV5Kk/v37uzy2ZPuXX36p4uJiVatWrUJ1oyxv+zk3N1fjx49XzZo1NW/evAvWRz/7ny8+yy+99JJmz56t3NxcNWrUSP3799ett96qmjVrlilLHwdGZfv5/fffV2FhoS677DLVrVtXixcv1vvvv6+TJ0+qcePGuuqqqzR69GhVr+78NU0/B6lAD63B2ebNm40kExcXZ2bNmmUiIiKcJj9LMjExMeatt9664Lny8/PNvn37zKOPPmqqVatm4uPjy0ya3Ldvn+O8P//8s8vz/PTTT44y+/fv98n7DHfe9vN9991nJJm//e1vjm3lXUakn/3Pmz4uuYzo6pWYmGg++uijMsfQx4FR2X7+3e9+ZySZ22+/3fTu3dtlX3fq1Mn89NNPTsfRz8GJsFXFlNxZVr16dSPJ9OvXz6Snp5v8/HyzZ88eM3LkSCPJREZGmh07drg8R2pqapkP7c0331xm8rwxxmzdutVRpmSS5a/l5OQ4ynz11Vc+fb/hypt+/vLLL021atVMz549TXFxsWN7eWGLfvY/b/p41KhRZsGCBSYjI8NkZ2eb06dPm7Vr15ouXboYSSY6Otqkp6c7HUMfB0Zl+/mGG24wkkyNGjWMzWYz06ZNM0eOHDG5ubnm/fffN82aNTOSTK9evYzdbnccRz8HJ8JWFbNkyRKn/8GePXvWaX9xcbHp3LmzkWRGjhzp8hxTpkwxffv2NV26dDEJCQlGkqlbt66ZPn2605ezMcZ89tlnjvp+va90nSVlNm7c6Js3GuYq288FBQWmY8eOpnr16mbnzp1Ox5QXtuhn//PFZ/nXcnJyTEpKipFkBg0a5LSPPg6MyvZz6f8UT5w4scx509PTjc1mM5LMe++959hOPwcnJshXMdHR0Y6fJ0yYUGZuRkREhKZOnSpJWrdunex2e5lzPPvss9q0aZO2bdumU6dO6Z133lFcXJwee+wxTZ482W19BQUFLtuUn5/v+DkmJqbibwplVLafn376ae3atUv33XefOnbsWKn66Gf/8MVn+ddiYmL05JNPSpI2bNigzMxMl/XRx/5T2X4ufdx9991X5rwpKSm6/PLLJUkffPCBy/ro5+BB2KpiEhISHD+X3EH4ayXbz549q1OnTl3wnEOHDnXclfLiiy/q0KFDLutzd67S20uXR+VVpp/37dunGTNm6OKLL9b06dMrXR/97B9WfJYlqU+fPpIku92u/fv3u6yPPvafyvZzyXE1atRQq1atyj2u9Irw9HNwImxVMe3atXP8XPp/MKWV3l5cXOzReXv16qXExEQVFxdr+/btju0tWrRw3Dq8b98+l8eW/IMeFRWl5s2be1QfyleZfv7Pf/6j/Px8HT16VC1btlSjRo2cXp9//rkkafbs2WrUqJG6d+/uOJ5+9j+rPsulb/Uv/fgX+jgwKtvPJcdFRkYqIsL1V3HJcaX/btDPwYmwVcVcdNFFjg9H6f+1llb6g1SvXj2Pz13yD3PpyxXVq1dX165dJUkbN250eVzJ9u7du3MLsY940885OTk6duxYmVfJsy+zs7N17Ngx/fLLL45j6Gf/s+qz/J///MepjhL0cWBUtp/79u0r6b+f1/KOo5+DH2GrCrr55pslSa+99prLeRyLFi2SJA0YMKDMGizufPLJJ475HV26dHHaN2LECEnS4sWLyzysuqCgQK+++qqk8w87hu9UtJ+HDRsmc/6mFpevAQMGSJKmT58uY4wOHjzodD762f+s+CzPmjVLknTJJZeUWbuJPg6MyvRz//791bhxY6f9pR0+fNixfldqaqrTPvo5CAVubj7cOX78uKldu7aRZO655x7H4xjsdrt57rnnjCRjs9mcHuUxe/Zss3Tp0jJ3whQVFZnVq1eb+vXrG0nmt7/9bZn6srKyHA89dfecraSkJJOdnW3dmw5Dlenn8lzocT30s/9Vpo+feeYZ88ILL5gTJ044nevEiRNmwoQJjrvMVqxYUaY++jgwKvtZXrBggZFk4uPjndZO++WXXxx3KyYnJ5d5piL9HHwIW1XUxx9/bGJiYox0/onuPXr0cHy4bDabeeaZZ5zKjxkzxkgyERERpnXr1qZnz56mS5cuplatWo5/nAcMGGAyMzNd1rdp0ybHw6pLniBfsmxEfHy8+eKLL/zxtsNORfu5PBcKW8bQz4FQ0T6ePHmyY1/Lli1Njx49TIcOHRzrOEVERJinn37abX30cWBU9rM8fvx4x7/RrVu3Nl27djVRUVFGkmnUqJH5+uuvXR5HPwcXwlYVtmfPHjN27FjTpEkTU6NGDZOYmGiGDh3q8inw6enp5uGHHzb9+/c3TZo0MVFRUSY6Oto0b97cDB8+3KxYscJpYTxX9u3bZ8aMGWOSkpJMjRo1TFJSkhk7diwrEFusIv1cHk/CljH0cyBUpI+/+OILc88995hevXqZpKQkExUVZWJjY02bNm3M+PHjzfbt2y9YH30cGJX9LL/55pvm8ssvNwkJCSYyMtK0bt3aTJ061Rw9erTc4+jn4GEzxhjfX5wEAACAxAR5AAAASxG2AAAALETYAgAAsBBhCwAAwEKELQAAAAsRtgAAACxE2AIAALAQYQsAAMBChC0AAAALEbYAAAAsRNgCgCDTv39/2Ww2bdmyxWn7p59+KpvNJpvNFqCWVU5WVpbq16+vhIQEnTx5MtDNAXyOsAXAI48++qjji9yTF6yxatUqbdq0Sddee6169uwZsHbk5OSodu3astlsmjRpksfHbdy40fF3ZPXq1ZKk+Ph43XfffcrMzNTjjz9uVZOBgCFsAaiwhg0bXvAF3yssLNSDDz4o6Xz4DaTY2FiNGjVKkvTGG28oPz/fo+MWLVokSapfv76uv/56x/ZJkyYpMTFRL774ovbt2+f7BgMBRNgCUGFHjx694Au+t2rVKu3bt0/dunVT9+7dA90c3XXXXZKk06dP6+23375g+aysLK1YsUKSdMcdd6hGjRqOffHx8br11ltVWFio5557zormAgFD2AKAIPHSSy9Jkm677bYAt+S87t27q0OHDpL+O2JVnrfeekvZ2dmSpHHjxpXZX/K+li5dqpycHB+2FAgswhYAv2jRooVsNpsWL16sgoICPfPMM+rUqZPi4uJUu3ZtDRw4UB9++OEFz7N9+3aNGzdOrVq1UmxsrOLj49WpUyf95S9/0YkTJ1weUzLf7PLLL5d0foToqquuUoMGDRQREVHmktw777yj1NRU1alTx3H+WbNmqbCwsMy5pPMjO7GxsbLZbHrrrbfKbf+0adNks9l08cUXyxhzwfdbYu/evfrXv/4lm82mW265xePjSjt58qR69+4tm82mli1bas+ePU77z5w5oyeffFI9e/ZUQkKCoqKi1LRpU40aNUqbN292ec6S0a3169frxx9/LLf+kkDWq1cvXXLJJWX2d+vWTcnJyTpz5ozefPPNyrxFoGoyAOCB6dOnG0mmsv9sNG/e3Egy8+bNMz179jSSTI0aNUx8fLzjvDabzbzyyituz/HII48Ym83mKB8bG2siIyMdf27cuLHZtm2b27YPGDDA3HvvvY66EhISTLVq1cz06dMdZe+77z7H+SSZOnXqmOrVqxtJ5rLLLjMPP/yw41yljRkzxkgyqampbttfVFRkLrroIiPJPPnkkxX6/b3wwgtGkmnbtq3bMmlpaW776ODBg6Zdu3ZGkunUqZM5fPiw0/7Nmzebhg0bOo6vVq2aqVmzplPfzJw5s8x5T5w44eiDJ554wm3b9uzZ4zjXwoUL3Za76667jCRz0003uS0DBBvCFgCP+CpsJSQkmIsuusi8/fbbpqCgwBhjzLfffmt69eplJJn4+HiTmZlZ5vhnn33WSDI1a9Y0f/3rX82RI0eMMecDzFdffWUGDhxoJJkmTZqYc+fOuWx7SbB74IEHzPHjx40xxuTl5ZmDBw8aY4xZtmyZ4z2OHj3a/PTTT8YYY3Jzc82CBQtMdHS0SUhIcBm2Nm/e7Agl+/fvd/k7+Oc//2kkmerVqzva76kRI0YYSeb22293W8Zd2Nq1a5dJSkoykswVV1xhzpw547T/+++/N3Xq1DGSzIgRI0x6eropLCw0xhhz7NgxM23aNEfgXLNmTZl6b7rpJiPJtGrVytjtdpdte/DBB40kExcXZ86ePev2PSxYsMBIMg0bNnRbBgg2hC0AHikdtho2bFju65577ilzfEnYioqKMhkZGWX2Hz9+3ERHRxtJZunSpU77fvnlFxMbG2tsNptZv369y/YVFhaarl27Gknm2Wefddv2e++91+XxdrvdJCcnG0nmyiuvdBkaXn31Vcd5fh22jDGmS5cuRpJ58MEHXdYxZMgQI8kMHz7c5f7yNG3a1Egys2fPdlvGVdj69NNPTe3atY0kM3LkSJOXl1fmOE+C3Ny5cx2jYr+2bt06R71paWll9hcVFTnC3tixY8t9n19++aXjXAcOHCi3LBAsmLMFoMKOHTtW7uvMmTNujx0xYoTatWtXZnv9+vXVu3dvSdKuXbuc9r3++uvKyclRt27dlJqa6vK81atXdyxFsG7dOpdlIiIi9Oc//9nlvh07dmjv3r2SpIcfftjlWmFjxoxRs2bN3Lwz6Xe/+50k6dVXX1VhYaHTvp9//lkffPCBJGnixIluz+GKMUZHjhyRdP735KlVq1Zp8ODBOnPmjCZNmqTly5crKirKqcypU6cc612VLCvhyh133CFJ2rlzp44dO+a0b9CgQY7fy6uvvlrm2HXr1unw4cOS/jvHy53ExETHzyXHAMGOsAWgwsz5UXG3r8WLF7s9tryFOJOSkiSdDwClbdq0SZL0n//8R40aNXL7KlkQ84cffnB5/tatW6tBgwYu923btk2SVKNGDfXp08dlGZvNpgEDBrht/+jRo1WrVi0dO3ZMa9euddq3aNEiFRcXq2XLlrryyivdnsOVzMxMFRUVSZLq1q3r0TF///vfddNNNyk/P19PPvmk5s2bp4iIsv/kf/HFF7Lb7ZKkgQMHuv3dXnrppY5jfv37jYiI0NixYyVJK1eu1Llz55z2l0yMb9Omjfr161duu0u/v19++cWj9wpUdYQtAH5Vs2ZNt/uqV68uSWVGhUpGOHJzc8sdUTt79qwkuV02wF3Qkv77xV6vXj1FRka6LXfRRRe53VeyVpQkLViwwLHdbrfrlVdekSSNHz++wivs5+XlOX7+9ciUO5MmTZLdbtcf//hHPfzww27LlR49utCIZQlXv98777xTNptNOTk5Wr58uWP7yZMnHcHT1XIPvxYTE+P4ufT7BoIZYQtAlVdcXCzp/GW6C42qGWN08OBBl+epVq2a2zrM/1+G4UJBqKScO7///e8lSR9//LGjHR999JF++OEHVa9eXXfeeWe5x7tSr149x8+nT5/26JiSNasWLlxYZpSttJLfbUxMjEe/W2OM07IXJVq0aOG4xFv6UuLSpUtVUFCg6tWrOy5Flqf0qGbp9w0EM8IWgCqvUaNGkqSvv/7asjpKRr1OnDihgoICt+UuNI+oQ4cO6tOnj9No1sKFCyVJN9xwg+O9VERkZKRq1aolqewlVndee+01jRkzRgUFBbrxxhvdrvBe0p7c3FyvH5NTMh/riy++0Lfffivpv8HrmmuuUePGjS94jtLvryLz04CqjLAFoMrr27evJGnz5s1u52N5KyUlRdL5S5iff/65yzLGGH322WcXPFfJ6NaiRYv0888/O0aWJkyYUOn2lSwCeuDAAY/KR0REaNGiRbrrrrtUWFiom266SatWrSpTrk+fPo7RvNKX/yrjt7/9rWPO1aJFi5Senq6dO3dKuvDE+BLff/+9pPOXlJOTk71qD1BVELYAVHm33367YmJiVFxcrD/+8Y+OS1+u2O12ZWZmVriOzp07q3Xr1pKkp556yuXlwqVLl3oU9kaOHKl69erp8OHDGj16tAoLCys1Mb60yy67TJK0detWj4+JiIjQwoULNWHCBBUWFuqWW24ps8J9gwYNdMMNN0iSnnnmmTKryv9aeSNrUVFRjjlrS5YscYzoNWzYUNddd51Hbd6yZYskqWvXroqLi/PoGKCqI2wBqPIaNWqkp556SpL03nvv6corr9S///1vR+gyxujbb7/V3Llz9Zvf/Ebvvvtuheuw2Wx67LHHJJ1fqmDMmDGOS4Z5eXl65ZVXNHHiRCUkJFzwXFFRUY6780pGwiozMb60knlSX331Vblh89dsNpteeukl/eEPf1BRUZFGjx6tZcuWOZWZM2eO6tWrp7Nnz6pfv35atGiR0/IdJ06c0OrVqzV8+HDH8hrulIxgHT161BG27rjjDsfNDxdSErbKu+sTCDqWr+QFICRUZFHThg0bmn//+99Ox5csavrqq6+6raPkkTdjxoxxuX/WrFmmWrVqjnZERkaaevXqmRo1ajg9YufXi6KWflzPhUyZMsXpETUJCQmO8w8cONA89NBDRpIZPHhwuefZu3ev49FClVkx/tfy8/NN/fr1jSTz0UcfuSxT3uN6jDHmnnvucTyK5x//+IfTvm3btpkWLVqUee+lH6ckyQwaNOiCbS1ZXLbk5WoRW1fOnDnjWNh2x44dHh0DBANGtgBU2IWWCDh27Fi5k8wr609/+pO+/fZbTZ06VR07dlR0dLQyMzMVHx+v7t2764EHHtDnn3+u0aNHV7qOZ599VqtXr9bll1+umjVrKj8/X+3bt9czzzyjdevWKTs7W5JUp06dcs/TunVrde7cWVLlJ8aXFhkZ6biT8fXXX6/UOZ5//nnde++9Ki4u1tixY53WQ+vSpYt2796tv/3tbxo0aJASExN17tw52e12JScna/To0Vq+fLljAdTylJ6f1adPH5eL2LqyatUq5eXlqWfPnurUqVOF3x9QVdmMqcBj5wEgzPXt21eff/65Hn/8cU2bNs1tuaNHj6pp06YqKirSunXrdNVVV3ld94EDB9SmTRvFxsbqyJEjITenaeDAgUpLS9Nrr73m0TIRQLBgZAsAPPSvf/3Lcafi1VdfXW7Zl156SUVFRWrdurVXE+NLu/jii3XXXXfp3Llz+vvf/+6Tc1YVW7duVVpami699FLHJHsgVBC2AKCUP/7xj1q8eLGOHj3quCMxMzNT8+fPd9y1N3DgQHXv3t3tOb766ivNmTNHknTvvfd6NTH+1x5//HHFx8dr9uzZjkuaoWD69OmSpFmzZpW7+CwQjLiMCACldO7c2bE2VFRUlGJjY5WZmekIXpdccok++ugjl4/tadGihfLz83X06FFJ5+dBbdmyRTVq1PBpG99++23t2LFDI0eOdHpmYbDKysrSnDlzVKdOHU2ePDnQzQF8jrAFAKX885//1Jo1a7R161YdO3ZMZ86cUa1atXTppZdq+PDhmjBhgmJjY10eWzKC1ahRI1199dV66qmn1LBhQ382H0AVRNgCAACwEHO2AAAALETYAgAAsBBhCwAAwEKELQAAAAsRtgAAACxE2AIAALAQYQsAAMBChC0AAAAL/T/giIcjMii31AAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM = 2.48\n",
      "FWTM = 5.23\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlsAAAHOCAYAAACvhswcAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAAA/GklEQVR4nO3deXQUVcL+8aeTkJCFQDCELZAgAcGFJYCAgCgBd5FBUGEUFF/AGVHQ8XWUdxD3cRDcmDkKKOKIomJAB3VEGaPCICABdEZQFgFR9iVA9oS+vz/4pU2T7qQ73dVJd38/5/Q50FW36tblQh5u3bplM8YYAQAAwBIRdV0BAACAUEbYAgAAsBBhCwAAwEKELQAAAAsRtgAAACxE2AIAALAQYQsAAMBChC0vXHHFFbLZbPrTn/5U11UBAABBgrDloUWLFumbb76p62oAAIAgQ9jyQF5enu655x4988wzdV0VAAAQZKLqugLB4P7779d5552nUaNGafTo0X49dnp6ug4ePKiGDRuqXbt2fj02AACwxs6dO1VcXKyUlBTt2rWr2n2DKmzt379fK1as0Ndff63169dr48aNKioqUo8ePbR+/foay+fk5GjWrFlau3at8vPzlZaWppEjR+qBBx5QfHy8yzKrVq3S3//+d8tuIR48eFBFRUUqKirSsWPHLDkHAACwxsGDB2vcJ6jC1ltvvaV77rmnVmVnz56tyZMnyxij1NRUtWnTRps3b9bjjz+u7OxsrVq1Sk2bNnUqU1ZWpokTJ+q+++7TOeec449LqKJhw4YqKipSbGysOnfubMk5AACAf23ZskVFRUVq2LBhjfsGVdhKTEzU4MGD1bNnT/Xs2VNbt27V1KlTayyXm5urKVOmSJLmzJmj8ePHy2azae/evRo6dKhyc3M1fvx4ZWdnO5X7y1/+oqKiIv3f//2fFZcjSWrXrp2OHTumzp07Kzc317LzAAAA/+nRo4c2bNjg0RSgoApb48aN07hx4xy/X7BggUflHnvsMdntdo0ZM0YTJkxwfN+qVSstWrRInTp10pIlS/Ttt9+qS5cukqSffvpJTzzxhF5++WWVlJSopKTEUa6kpER5eXlq1KiRIiMj/XNxAAAgJIX804j5+fn6+OOPJckpaFXo0KGDBg0aJElavHix4/sff/xRxcXFuvnmm5WUlOT4SNLMmTOVlJSk//znPwG4AgAAEMyCamSrNjZu3KiSkhLFxMTowgsvdLnPgAEDtGLFCq1Zs8bxXbdu3ZSTk1Nl30svvVQ333yzbr/9dmVkZFhWbwAAEBpCPmxt3bpVktS2bVs1aNDA5T7t27eXJP3www+O75o0aaJLLrnE5f5paWlut0mn54XNnTvXo/pt2bLFo/0AAEBwCvmwdfToUUmq8qRhZRXb/LX0wr59+7Rhwwa/HAsAAAS3kA9bxcXFkqTo6Gi3+8TExEiSioqKajyeMabGfVq2bKnMzEyP6lfx6CgAAAhNIR+2Kta/KC0tdbtPxZOGsbGxfjnnxIkTNXHiRI/2rXh0FAAAhKaQfxqx4gnCituJrlRsq9gXAADAX0J+ZKtjx46STq+bVVZW5nKS/I4dO5z29beCggK32+x2uyXnBAAA9UPIh63MzExFR0erpKRE69atU79+/arss3LlSklS3759LalDQkKCJccFAAD1X8jfRkxISNDll18uSS6XY9i2bZs+++wzSdKIESMCWjcAABD6Qj5sSdK0adNks9n0+uuva+7cuY4nCvft26dRo0bJbrdr2LBh6tq1qyXnz8/Pd/vp1q2bJecEAAD1Q1CFrT179ig5OdnxueuuuyRJ33zzjdP3M2bMcCrXq1cvPfPMM5JOPymYlpamzMxMtWvXTrm5uTrnnHM0b948y+odHx/v9hMREVR/BAAAwEtBNWfr1KlTOnLkSJXvy8vLnb4vLCysss+UKVN0wQUXaNasWVq7dq0OHjyotLQ0jRgxQg8++CDzqgAAgCWCKmylp6d7tKioO1lZWcrKyvJjjQAAqP8i7lvm9Hv7zGvrqCbhKajCVrBi6QcAAMIXYSsAuEUJAED4ImwBABDmKt9m5Baj/xG2AiA/P9/ttv79+2vTpk2BqwwAAAgowlYAxMfHu93G0g8AgNqobtL7mdtQtwhbAACEGcJYYDGsAgAAYCFGtgAACAGMVtVfhK0AYJ0tAADCF2ErAFhnCwCA8MWcLQAAAAsxshUArLMFAED4ImwFAOtsAQAQvvhJDwAAYCFGtgAAgEN1K9OjdghbAAAEAdbRCl7cRgQAALAQI1sBwKKmAACEL8JWALCoKQAA4YvbiAAAABZiZCsAWNQUAOAtJsSHDsJWALCoKQAgWLEUhO/4SQ8AAGAhwhYAAICFCFsAAAAWImwBAABYiLAFAABgIZ5GDABWkAcAIHwRtgKAFeQBAAhf3EYEAACwECNbAcAK8gCAUMEip94jbAUAK8gDABC++EkPAABgIcIWAACAhQhbAAAAFiJsAQAAWIgJ8gAA1BNnPumH0MDIFgAAgIUIWwAAABYibAEAAFiIOVsBwIuoAQAIX4StAOBF1AAAhC9uIwIAAFiIka0A4EXUAACEL8JWAPAiagAAwhc/6QEAACzEyBYAAKi1yqve22deW4c1qb8IWwAA1BFezxMeuI0IAABgIcIWAACAhQhbAAAAFiJsAQAAWIiwBQAAYCHCFgAAgIVY+gEAgABhqYfwxMgWAACAhRjZCoCCggK32+x2ewBrAgAAAo2wFQAJCQl1XQUAAFBHuI0IAABgIUa2AiA/P9/ttv79+2vTpk2BqwwAAAgowlYAxMfHu90WEcHgIgAAoYywBQAA/OLMpS3sM6+to5rULwyrAAAAWIiwBQAAYCHCFgAAgIUIWwAAABZigjwAABbhXYiQGNkCAACwFGELAADAQoQtAAAACxG2AAAALETYAgAAsBBhCwAAwEKELQAAAAsRtgAAACxE2AIAALAQYQsAAMBChC0AAAAL8W5EAAD8hHchwhVGtgAAACzEyFYAFBQUuN1mt9sDWBMAABBohK0ASEhIqOsqAACAOsJtRAAAAAsxshUA+fn5brf1799fmzZtClxlAAAIkDMfGLDPvLaOalK3CFsBEB8f73ZbRASDiwAAhDJ+0gMAAFiIsAUAAGAhwhYAAICFCFsAAAAWYoI8AAA+4BU9qAkjWwAAABYibAEAAFiIsAUAAGAhwhYAAICFCFsAAAAWImwBAABYiLAFAABgIcIWAACAhQhbAAAAFiJsAQAAWIjX9QAA4AVezwNvMbIFAABgIcIWAACAhQhbAAAAFiJsAQAAWIiwBQAAYCHCFgAAgIVY+gEAgGqw1AN8xcgWAACAhRjZAgAAAXHmKKF95rV1VJPAYmSrGqtXr9Zll12mVq1aKSYmRi1atNA111yjtWvX1nXVAABAkCBsVePYsWPq3Lmznn32WX3yySeaPXu2jh49qgEDBujrr7+u6+oBAIAgwG3Ealx99dW6+uqrnb674oorlJycrL///e/q1atXHdUMAAAEC0a2vBQfH6+YmBg1aNCgrqsCAACCQFCFrf3792vhwoWaPHmy+vXrp7i4ONlsNvXs2dOj8jk5ObrmmmvUrFkzxcbGqlOnTpo2bZoKCgqqLWe321VWVqaffvpJkyZNks1m0/jx4/1xSQAAIMQF1W3Et956S/fcc0+tys6ePVuTJ0+WMUapqalq06aNNm/erMcff1zZ2dlatWqVmjZt6rLsVVddpeXLl0uSmjdvro8++kidO3eu9XUAAIDwEVQjW4mJiRo8eLAeeOABvfvuu3ryySc9Kpebm6spU6ZIkubMmaOffvpJGzZs0I8//qgePXpoy5Yt1Y5UzZ49W+vWrdN7772nXr166corr9SXX37pj0sCAAAhLqhGtsaNG6dx48Y5fr9gwQKPyj322GOy2+0aM2aMJkyY4Pi+VatWWrRokTp16qQlS5bo22+/VZcuXaqU79Chg+PXQ4cOVf/+/XX33Xdr06ZNtb4WAAAQHoJqZKs28vPz9fHHH0uSU9Cq0KFDBw0aNEiStHjx4hqPVzFH7IcffvBvRQEAQEgK+bC1ceNGlZSUKCYmRhdeeKHLfQYMGCBJWrNmTY3HKy8v16pVq5SRkeHXegIAgNAUVLcRa2Pr1q2SpLZt27pdrqF9+/aSVGW06re//a3S09OVmZmp5ORk/fzzz3r55Ze1adMmvfvuu27POWfOHM2dO9ej+m3ZssWj/QAA1uFl07BSyIeto0ePSpLbJw0rbzt27JjT93379tXChQv10ksv6fjx42ratKl69+6tzz77TAMHDnR7vH379mnDhg1+qD0AAAh2IR+2iouLJUnR0dFu94mJiZEkFRUVOX0/adIkTZo0yetztmzZUpmZmR7tu2XLlirnBQAAoSPkw1bDhg0lSaWlpW73KSkpkSTFxsb65ZwTJ07UxIkTPdq3R48ejIIBABDCQn6CfFJSkqRfbye6UrGtYl8AAAB/CfmRrY4dO0qSfvrpJ5WVlbmcJL9jxw6nff2tutcB2e12S84JAADqh5APW5mZmYqOjlZJSYnWrVunfv36Vdln5cqVkk5PiLdCQkKCJccFAAD1X8jfRkxISNDll18uSS6XY9i2bZs+++wzSdKIESMCWjcAABD6Qj5sSdK0adNks9n0+uuva+7cuTLGSDq9RMOoUaNkt9s1bNgwde3a1ZLz5+fnu/1069bNknMCAFDfRdy3zPEJZT6Frby8PH355ZfauHFjlW379u3TiBEj1LhxYzVt2lS33HKLDh486MvptGfPHiUnJzs+d911lyTpm2++cfp+xowZTuV69eqlZ555RtLpJwXT0tKUmZmpdu3aKTc3V+ecc47mzZvnU92qEx8f7/YTEREWeRcAgLDl00/6V155RZdeeqnmz5/v9H15ebkuu+wyLV26VCdPnlReXp7efPNNZWVlVbsEQ01OnTqlI0eOOD75+fmO81X+vrCwsErZKVOm6NNPP9WVV16pgoICbd68WWlpaZo6darWr1+v5OTkWtcLAADAHZ8myH/yySeSpFGjRjl9//bbb+u7775TbGys7r33XsXGxurpp5/W5s2bNXfu3FotFCpJ6enpjluAtZGVlaWsrKxalwcABKczb1PZZ15bRzVBOPIpbG3fvl2SdMEFFzh9/84778hms+mRRx7RfffdJ0nKyMjQTTfdpHfffbfWYStYsfQDANQvoT5HCPWLT2Hr8OHDSkhIUKNGjZy+//LLLyWdfpFzhWHDhslms+m7777z5ZRBiaUfAAAIXz7N2SouLq4yMvPDDz/o+PHj6tChg1q2bOn4Pjo6WklJSTpx4oQvpwQAAAgqPoWtlJQUFRYWav/+/Y7vVqxYIUm66KKLquxfVFSkxo0b+3LKoMTSDwAAhC+fwlavXr0kybGsQmFhoV566SXZbLYqE9F/+eUXFRUVOY12hQuWfgAAIHz59JN+4sSJMsZo1qxZ6ty5szp27KjvvvtOzZo10/Dhw532zcnJkVR1Mj0AAEAo8ylsXX755Xr44Ydls9n0ww8/aO/evUpOTtYbb7yh2NhYp33ffPNNSdKll17qyykBAACCis8von7ooYd06623au3atWrSpIkuvPDCKvOySktL1bdvX/Xu3VtXX321r6cEAAAIGj6HLUlq27at2rZt63Z7dHS0pk2b5o9TBSXW2QIAIHz5FLYeffRRJSQk6N577/Vo/xdeeEF5eXl66KGHfDlt0GGdLQAILBYtRX3i05ythx9+WDNnzvR4/2effVaPPPKIL6cEAAAIKn65jYjqVbww25X+/ftr06ZNgasMAAAIqICGraNHj6phw4aBPGW9EB8f73Yb62wBABDaAvaTfvHixTp58mS1E+kBAABCjVcjW88//7yef/55p+8OHTqks88+220ZY4zy8vJ04sQJ2Ww2ln4AANTKmZPe7TOvraOaAN7xKmzl5eVp165dTt+dOnWqynfuZGVlhd2TiAAAILx5FbaGDRum9PR0SadHrMaNG6fGjRvrueeec1smIiJCiYmJOv/889W+fXtf6goAgFss94D6yquw1bVrV3Xt2tXx+3Hjxik2NlZjx471e8VCCYuaAgAQvnx6GpGg4BkWNQUA/2MkC8GCdQcAAAAs5Ld1tux2u7Zt26ajR4+qrKys2n0vvvhif502KLCoKQAA4cvnsLVv3z49+OCDevfdd1VUVFTj/jabTeXl5b6eNqiwqCkAeKbyrUGWdggvoby0h09ha+/everdu7f27t0rY4xHZTzdDwAAIBT4/CLqX375RQkJCXrhhRe0e/dulZWVyW63V/sBAAAIFz6NbP3zn/+UzWbTK6+8ohEjRvirTgAAACHDp7B16NAhRUVFadiwYX6qDgAAp7G0A0KFT7cRU1JSFBsbq6govz3UCAAAEFJ8CluDBw/WyZMntW3bNn/VJyQVFBS4/TCHDQCA0ObTkNTUqVP17rvv6o9//KOWLFnirzqFHFaQB4DTQvnxfsAdn0a2MjIy9I9//ENffPGFhgwZopycnGrfAwgACH0R9y1zfAD4OLIVGRnp+PVnn32mzz77rMYy4bioKSvIAwAQvnwKWyxQ6hlWkAcA1xj9QjjwKWzl5OT4qx4AAAAhyaewNXDgQH/VAwAAICRxDwsAAMBCrEYKALAMc7IAH8PWl19+WatyF198sS+nBQAACBo+ha1LLrlENpvNqzLhuPQDAAAIXz7fRvR2+QeWiwAAAOHEpwnydru92k9eXp6WL1+ugQMHqmnTpvriiy94FyAAAAgrlk6QT0xM1JAhQzR48GANGzZMQ4cO1YYNG9SuXTsrT1vvVPcKI8IngPqguncW8j5DwDcBeRrRZrNpxowZ6ty5sx577DHNnz8/EKetN3gRNYBQxhOHQPUCtvTDOeeco8TERH366aeBOiUAwAKEK8A7AQtbZWVlKioqUnFxcaBOWW/wImoAAMJXwMLWe++9p7KyMqWmpgbqlPUGL6IGACB8WRq2SktLtWfPHmVnZ+vJJ5+UzWbTlVdeaeUpAQAA6hWfwlZkZKTH+xpj1Lp1a02fPt2XUwIAAAQVn8KWpwuUxsbG6vrrr9ef//xntWrVypdTAgD8gEnuQOD4FLZycnKqP3hUlJKSktSxY0dFRfHOawCwEuthIZSEUn/2KQENHDjQX/UAgJDkzx8YgRyNYuQL8B+GmwAgRBGYgPrB72Fr9+7dOnjwoGw2m5o1a6a0tDR/nwIAQlYo3ToBcJpfFnnat2+f7r77bqWkpOjss89Wnz591Lt3b5199tlKSUnRlClTtG/fPn+cCgAAIKj4HLb+/e9/q0uXLvrb3/6mw4cPyxjj9Dl8+LBmz56trl27avXq1f6oMwAAQNDw6TbiwYMHNXToUB07dkyJiYm64447NGTIEMcq8T///LNWrFihOXPm6PDhwxo6dKg2b96slJQUv1QeAACgvvMpbM2aNUvHjh1Tp06d9Omnn6p169ZO28855xxlZWXprrvu0uDBg/XDDz/omWee0VNPPeVTpQEAAIKFT7cRP/zwQ9lsNs2bN69K0KqsVatWmjdvnowx+uCDD3w5ZVAqKChw+7Hb7XVdPQAAYCGfRrZ27dql+Ph49evXr8Z9+/Xrp/j4eO3evduXUwalhISEuq4CgHqCpw2B8ONT2LLZbB6/sqeCt/sDQH1DYALgDZ/CVlpamrZs2aI1a9aoT58+1e771VdfqaCgQOeee64vpwxK+fn5brf1799fmzZtClxlANQrLDwKhD6f5mxdeeWVMsZowoQJOnTokNv9Dh48qAkTJshms+mqq67y5ZRBKT4+3u0nIsIvS50BAIB6yqeRrfvuu0+vvPKKvvvuO3Xu3Fm/+93vlJWVpdatW8tms2nPnj3617/+pTlz5ujIkSNq0qSJ7rvvPn/VHQBCHiNfQPDzKWw1b95cS5cu1W9+8xsdPXpUTz75pJ588skq+xlj1KRJE7333nussQUg5BGQAFTm87sRBw4cqG+//VZPPPGEFi9erKNHjzptb9q0qW688UZNnTq12uUhACCQmOQOIFD88iLq1NRUvfjii3rxxRe1c+dOHTx4UJKUkpKidu3a+eMUAAAAQcnrsFVeXq7CwkJJUmJiYpXt7dq1qxKwTpw4Ien0RPHIyMja1BMA6i1uGwKojtdh66abbtLSpUt13XXXacmSJR6VGTdunJYuXarRo0fr9ddf97qSABBoBCgA/uLVugPfffedlixZosTERM2fP9/jcvPmzVNiYqIWLVqkbdu2eV1JAACAYOXVyNYbb7whSfr973+vJk2aeFwuKSlJd911lx5//HEtXLhQjzzyiFeVBBC+Ko8w+TKJvaaRKkayAFjFq7C1cuVK2Ww2XX/99V6faPjw4Xr88cf1+eefe10WAGqDAAWgPvAqbG3dulURERHq3r271yfq0qWLIiIi9P3333tdFgA8QbgCUB95NWcrLy9PTZo0kc1m8/5EERFq0qSJjh8/7nVZAACAYOXVyFZcXJxOnjxZ65Pl5+crNja21uUBhD5vRqcYyQIQDLwa2UpJSVFZWZl27Njh9Yl27Nih0tJSXtcDAADCildhq0+fPpLk8fpalWVnZ0uSevfu7XVZAACAYOVV2LrmmmtkjNHTTz+tffv2eVxu7969mjlzpmw2m6655hqvKwkAABCsvApb119/vTp06KAjR47o8ssv9+h24vbt23XFFVfo8OHDysjI0MiRI2tdWQAAgGDj1QT5iIgIvfbaa7r00kv13XffqUuXLrr55ps1bNgwde/eXU2bNpUkHT16VBs3btTSpUv15ptvqrCwUDExMVqwYEGtnmQEAIkJ8QCCk9fvRuzTp4/eeecd3XLLLTpx4oRefvllvfzyy273N8YoISFBr7/+uvr27etTZQEEvzMDky+rwgNAMPDqNmKFa6+9VuvXr9fIkSNls9lkjHH5sdlsGjlypHJzc3Xdddf5u+4AACBMRNy3zOkTTLwe2aqQkZGht99+WwcPHlROTo6+++47HTlyRMYYJScn67zzztOll17KUg+SCgoK3G6z2+0BrAkAAAi0WoetCikpKbrxxhv9UZeQlZCQUNdVAOqtYPsfKgB4y+ewBQBnYl4WAPyKsBUA+fn5brf1799fmzZtClxlAABAQBG2AiA+Pt7ttoiIWj2jAAAAggRhC4DPmHcFAO4RtgB4pHKgYg4WAHiOsAXAJUarAMA/CFsALEdwAxDOCFsAJBGIAMAqhC0ghLC+FQDUP4QtAF5jFAwAPEfYAkIYI10AUPcIW0CYYnQKAAKDsAW4wagQAMAfCFsIW/UlTAWyHoxmAUDg8WI+AAAACzGyBQQYo0sAEF4Y2QIAALAQYQsAAMBC3EZESKkvk94BAKhA2Aoz9TGM1Mc6eauunigMxrYCgHBD2ALqOSbUA0BwI2wBFvBlpMubcEUQA4D6j7AFt7i95/lxAQBwh7AFeIiABQCoDcIW8P9ZGaYIagAQvghbCCuEHgBAoLGoKQAAgIUY2QpzrNkEAIC1CFvVyM7O1ttvv62vv/5a+/fvV2pqqq666io99NBDOuuss+q6eiGrplt9hEIAQDAhbFXj6aefVqtWrfToo4+qbdu22rJlix5++GF9/PHH2rhxo+Li4uq6igEVCktBAAAQaIStaixbtkzNmjVz/H7gwIHq0KGDBg8erOzsbN1yyy11WLu6V1e3ILn1CQAIJkyQr0bloFWhV69ekqSff/450NUBAABBKKjC1v79+7Vw4UJNnjxZ/fr1U1xcnGw2m3r27OlR+ZycHF1zzTVq1qyZYmNj1alTJ02bNk0FBQUe1yEnJ0eS1Llz51pdQ6iKuG+Z0wcAAJwWVLcR33rrLd1zzz21Kjt79mxNnjxZxhilpqaqTZs22rx5sx5//HFlZ2dr1apVatq0abXHOHbsmO655x5dcMEFuvZabl8BAICaBVXYSkxM1ODBg9WzZ0/17NlTW7du1dSpU2ssl5ubqylTpkiS5syZo/Hjx8tms2nv3r0aOnSocnNzNX78eGVnZ7s9RnFxsYYPH65jx47pgw8+UGRkpL8uKyTVNJme0S8AgC+Caf5uUIWtcePGady4cY7fL1iwwKNyjz32mOx2u8aMGaMJEyY4vm/VqpUWLVqkTp06acmSJfr222/VpUuXKuXLyso0YsQIrVu3Tp988onOPfdcn68lUOpLqLGqHvXl+gAAcCeowlZt5Ofn6+OPP5Ykp6BVoUOHDho0aJBWrFihxYsXVwlbp06d0qhRo7RixQotW7ZM/fr1C0i96wLBBQAA/wuqCfK1sXHjRpWUlCgmJkYXXnihy30GDBggSVqzZo3T93a7XWPHjtX777+vt99+W0OGDLG8vgAAILSE/MjW1q1bJUlt27ZVgwYNXO7Tvn17SdIPP/zg9P1dd92lN954Q1OmTFHz5s2dwlhqaqpSU1NdHm/OnDmaO3euR/XbsmWLR/sBAIDgFPJh6+jRo5JU7ZOGFduOHTvm9P2HH34oSXruuef03HPPOW2bPn26Hn74YZfH27dvnzZs2FDLGgMAgFAS8mGruLhYkhQdHe12n5iYGElSUVGR0/e7du2q1TlbtmypzMxMj/bdsmVLlfMCAIDQEfJhq2HDhpKk0tJSt/uUlJRIkmJjY/1yzokTJ2rixIke7dujRw9GwQAACGEhP0E+KSlJ0q+3E12p2FaxLwAAgL+E/MhWx44dJUk//fSTysrKXE6S37Fjh9O+/lbd64Dsdrsl5wQAAPVDyIetzMxMRUdHq6SkROvWrXO5TtbKlSslSX379rWkDgkJCZYcFwAA1H8hfxsxISFBl19+uSS5XI5h27Zt+uyzzyRJI0aMCGjdAABA6Av5sCVJ06ZNk81m0+uvv665c+fKGCPp9BINo0aNkt1u17Bhw9S1a1dLzp+fn+/2061bN0vOCQAA6oegClt79uxRcnKy43PXXXdJkr755hun72fMmOFUrlevXnrmmWcknX5SMC0tTZmZmWrXrp1yc3N1zjnnaN68eZbVOz4+3u0nIiKo/ggAAICXgmrO1qlTp3TkyJEq35eXlzt9X1hYWGWfKVOm6IILLtCsWbO0du1aHTx4UGlpaRoxYoQefPBB5lUBAABLBFXYSk9Pd9wCrI2srCxlZWX5sUYAAADVC6qwFaxY+gEAgPBF2AoAblECABC+mJ0NAABgIUa2AiA/P9/ttv79+2vTpk2BqwwAAAgowlYAxMfHu93G0g8AAIQ2ftIDAABYiLAFAABgIcIWAACAhZizFQCsswUAQPgibAUA62wBABC+uI0IAABgIUa2AoB1tgAACF+ErQBgnS0AAKwTcd8yp9/bZ15bRzVxjZ/0AAAAFiJsAQAAWIiwBQAAYCHCFgAAgIWYIB8ALGoKAED4ImwFAIuaAgAQvriNCAAAYCFGtgKARU0BAAhfhK0AYFFTAADCFz/pAQAALETYAgAAsBBhCwAAwEKELQAAAAsRtgAAACzE04gBwAryAACEL8JWALCCPAAA4YvbiAAAABZiZCsAWEEeAIDwRdgKAFaQBwAgfPGTHgAAwEKELQAAAAsRtgAAACxE2AIAALAQYQsAAMBChC0AAAALEbYAAAAsRNgCAACwEIuaBgAvogYAIHwRtgKAF1EDABC+uI0IAABgIUa2AoAXUQMAEL4IWwHAi6gBAAhf/KQHAACwEGELAADAQoQtAAAACxG2AAAALETYAgAAsBBhCwAAwEKELQAAAAsRtgAAACxE2AIAALAQYQsAAMBChC0AAAAL8W7EACgoKHC7zW63B7AmAAAg0AhbAZCQkFDXVQAAAHWE24gAAAAWYmQrAPLz891u69+/vzZt2hS4ygAAgIAibAVAfHy8220REQwuAgAQyvhJDwAAYCHCFgAAgIUIWwAAABYibAEAAFiIsAUAAGAhwhYAAICFCFsAAAAWImwBAABYiLAFAABgIcIWAACAhXhdDwAACCkR9y1z+r195rV1VJPTGNkCAACwEGELAADAQoQtAAAACxG2AAAALETYAgAAsBBhCwAAwEKELQAAAAsRtgAAACzEoqYBUFBQ4Hab3W4PYE0AAECgEbYCICEhoa6rAAAA6gi3EQEAACzEyFYA5Ofnu93Wv39/bdq0KXCVAQAAAUXYCoD4+Hi32yIiGFwEACCU8ZMeAADAQoQtAAAAC9mMMaauKxHOmjZtqmPHjik2NladO3f2+/E3/Hzc78cEACCYZKY29vsxt2zZoqKiIiUlJeno0aPV7kvYqmNxcXEqKiqq62oAAIBaiI2NVWFhYbX7MEG+jqWkpOjgwYNq2LCh2rVr59djV6Ruq0bNQglt5TnaynO0lXdoL8/RVp6zqq127typ4uJipaSk1LgvYauO7dq1y7Jj9+jRQxs2bFDnzp2Vm5tr2XlCAW3lOdrKc7SVd2gvz9FWnqsPbcUEeQAAAAsRtgAAACxE2AIAALAQYQsAAMBChC0AAAALEbYAAAAsRNgCAACwEGELAADAQoQtAAAACxG2AAAALMTrekLYhAkTtG/fPrVs2bKuq1Lv0Vaeo608R1t5h/byHG3lufrQVjZjjKmzswMAAIQ4biMCAABYiLAFAABgIcIWAACAhQhbAAAAFiJs1UPLli3TnXfeqT59+ig1NVUNGzZUQkKCzj//fE2ZMkW7d++uUqawsFAzZ87UjTfeqHPPPVfJyclq0KCBkpOTdckll+jFF19UWVlZtef98ccfNW7cOKWmpiomJkZt2rTR7bffrp07d1p1qT4LdFt9/vnnstls1X5uuukmqy+7VmrTVu6MHDnScb0PP/xwtfuGS79yx5O2Csd+lZ6eXuM1FxcXuz1vMPYrKfDtFY59q0JhYaFmzJihCy+8UElJSYqNjVV6erquv/56vf/++27LWdK3DOqdgQMHGkmmQYMGpm3btqZnz54mPT3dREREGEkmLi7OLF++3KnMzp07jSQjySQmJppOnTqZzMxMk5yc7Pi+Z8+e5tixYy7PuXr1apOQkGAkmaSkJNOjRw/TpEkTI8k0atTIrF27NgBX7r1At1VOTo6RZGJiYky/fv1cfqZPnx6Yi/dSbdrKlaVLlzraSVK11xtO/coVT9sqHPtVWlqakWTOP/98t9dcUlLi8pzB2q+MCXx7hWPfMsaYLVu2mPT0dCPJREZGmnPPPddkZmaaFi1aGEnm+uuvd1nOqr5F2KqHXnvtNbNixQpTXFzs9P327dvNxRdfbCSZ5ORkk5+f79h25MgR8/zzz5vNmzc7lbHb7Wbp0qUmPj7eSDJ33HFHlfMVFBSYli1bGklm3LhxpqioyBhjTFFRkbntttuMJJOammoKCwstuFrfBLqtKv7hSktLs+R6rFSbtjpTXl6eadWqlWnTpo3p0aNHtQEi3PrVmbxpq3DsVxXhIScnx6vzBXO/Mibw7RWOfevQoUOOPjJp0iRz5MgRp+27d+82n3/+eZXzWdm3CFtBZv/+/Y7/JX/00Ucel/vLX/5iJJmUlJQq25599lkjyWRkZFT5n1FJSYlp3769kWReeOEFn+sfSFa0VTD/w1UdT9vqf/7nf4wk8/777zv+1+kuQIR7v/KmrcKxX9U2PIRqvzLGmvYKx741ZswYt/9hro6VfYs5W0GmefPmatq0qaTT96M91blzZ7dlFi9eLEm69dZbFR0d7bQtOjpat912myTpnXfeqVWd64oVbRWqPGmrnJwcvfLKKxo+fLiGDh1a4zHDuV9521ahqrZ/B6sTqv1Ksqa9QpW7ttq/f78WLVqk6OhoPfLII14d08q+xet6gsyWLVt09OhRRUREqHv37h6XW7VqlSSpZ8+eTt+fOnVK69evlyQNGDDAZdmK77/++mudOnVKkZGRtal6wPm7rSo7ceKEJk6cqB07dig6Olrt27fX0KFDNWTIEJ/rXRdqaquioiKNHz9ejRo10uzZs2s8Xjj3K2/bqrJw61eS9NJLL2nmzJkqKipSixYtNGDAAP32t79Vo0aNquwbyv1K8n97VRYufeujjz5SWVmZLr74YjVt2lQLFizQRx99pCNHjqhly5a67LLLNHr0aEVFOccfy/uW12NhCDi73W4OHDhgsrOzTUZGhpFk7r///hrLlZSUmO3bt5uHH37YREZGmoSEhCqT+7Zv3+4Yiv3ll19cHufnn3927LNjxw6/XJNVrGwrY34dknf3ycrKMocOHbLi0vzOm7b6wx/+YCSZv/71r47vqrs1Fs79ytu2MiY8+1XFbTFXn+TkZPPJJ59UKRNq/coYa9vLmPDrW3fccYeRZG655RbTt29fl9fctWtX8/PPPzuVs7pvEbbqsddff71KJ+nUqZN54403qi2XlZVVpdyNN95YZUK4McasW7fOsU/FZMAzFRYWOvZZv369X67N3wLRVsYYs2bNGjNmzBizfPlys2fPHlNSUmJ27dplZs6c6ZhY37dvX1NeXm7FZfqFt2319ddfm8jISNO7d29z6tQpx/fVBYhw7Ve1aStjwrNfjRo1ysydO9ds2bLFFBQUmGPHjplly5aZ7t27G0mmYcOGJjc316lMqPQrYwLTXsaEX9+67rrrjHT6CUabzWamTZtm9u3bZ4qKisxHH31k2rZtaySZPn36GLvd7ihndd8ibNVjy5cvN/369TN9+/Y1bdq0MRERESYiIsJcddVVZs+ePW7LTZkyxfTr1890797dJCUlGUmmadOmZvr06U4/AIwx5ssvv3R0njO3VTh16pRjn5UrV/r1Gv0lEG1Vk9WrV5vIyEgjySxcuNDXS7KMN21VWlpqunTpYqKiosw333zjtK26ABGO/aq2bVWTUOxX1SksLDSZmZlGkhk8eLDTtlDpV8YEpr1qEop9q/J/oCdOnFjlWLm5ucZmsxlJ5sMPP3R8b3XfImwFkR07dphhw4YZSaZ169YmLy/Po3Lvv/++adOmjZFOPwZbWSj9T7EyK9rKEzfeeKORZIYPH+512bpSXVs99thjRpL54x//WKVcOIxsncmKtvJEqPWrmvzzn/80kkxERITTeneh2q+Msaa9PBFqfevqq692/Plv3brVZflLL720yr/xjGzBSXl5uTnvvPOMJPP44497XO6rr74y0unF3Xbv3u34ftu2bY7OEypzICr4u6088fzzzxvp9MKDwcRVW23bts3ExMSYs88+2+W6MtUFiHDrV760lSdCqV954vjx4y5/qIVyvzLG/+3liVDrWzfffLPjNqK7Earf//73RpK5+uqrHd9Z3bdY+iHIREZG6sorr5Qkx5MTnujTp4+Sk5N16tQpbdy40fF9enq64xHX7du3uyy7Y8cOSVJMTIzS0tJqW/WA83dbeaKiLcvLy70qV9dctdV///tflZSUaP/+/WrXrp1atGjh9Fm9erUkaebMmWrRooV69erlOF649Stf2soTodSvPFH5sfvK1xzK/Uryf3t5UzZU+lanTp0knb6uiAjXEadhw4aSTj+BWMHqvkXYCkIV7+2z2+1elav4y1S5XFRUlHr06CFJWrlypctyFd/36tUrqB6jlvzbVp7473//K0lKTU31qlx94K6tCgsLdeDAgSqfiv0LCgp04MABHTp0yFEmXPtVbdrKE6HYr6pTcb2S1Lp1a8evQ71fSf5tL2/Khkrf6tevn6Rf/665UhGaAtm3CFtBprS0VB988IEkebV21L/+9S/l5eW5LDdixAhJ0oIFC6q8gLm0tFSvvvqqpNMv1A0mVrRVdfbu3auFCxdKki677DLPK1oPuGqrYcOGyZyeauDyM3DgQEnS9OnTZYzRrl27nI4ZTv3K17aqTqj1K0/MmDFDknTuuedWCQGh2q8ka9qrOqHYtwYMGKCWLVtKkubPn1+l3N69e7V8+XJJUlZWltM2S/uWVzcdYbmvv/7a/OlPf3I5se+HH34wl112mZFkEhISnNYJmTlzplm4cKE5ceKEU5ny8nKzZMkS06xZMyPJ/OY3v6ly3Pz8fMfLOd29D6pVq1amoKDAz1frm7poq5EjR5rly5ebsrIyp+/Xrl1rOnfu7Gir48eP++kq/aO2bVWdmuYhhVu/qk5NbRVu/erpp582L7zwgjl8+LBTmcOHD5sJEyY45sUsXry4ynGDtV8ZUzftFW59yxhj5s6d69hWef2xQ4cOOZ5W7NChgyktLXUqZ2XfImzVM5UXoGvWrJnJzMw0vXv3dqwNIp1emuBf//qXU7mxY8c6nkbJyMgwvXv3Nt27dzeJiYmOcgMHDnT7hMuqVasca65UvOm8YimEhIQE89VXXwXi8r1SF23VuHFjI8nExsaa888/3/Tu3dvx9KJ0+iWlGzduDFALeK62bVUdTyZ9h1O/qk5NbRVu/Wry5MlGkrHZbKZdu3bmwgsvNBdccIGJiopy/N38y1/+4va8wdivjKmb9gq3vlVh/Pjxjv0yMjJMjx49TExMjJFkWrRoYf7zn/+4LGdV3yJs1TNHjx41L7zwghk+fLjp0KGDSUxMNFFRUeass84y/fv3N48//rjL1X5zc3PN1KlTzYABA0xqaqqJiYkxDRs2NGlpaWb48OFm8eLFTgu4ubJ9+3YzduxY06pVK9OgQQPTqlUrc+utt9bbJ3rqoq1efPFFM2rUKNO5c2fTtGlTExUVZZo0aWIuuugi89RTT3n92HWg1LatquPpE3bh0q+qU1NbhVu/+uqrr8zdd99t+vTpY1q1amViYmJMXFyc6dixoxk/frxHP/yDrV8ZUzftFW59q7K3337bXHLJJSYpKclER0ebjIwMc88995j9+/dXW86KvmUzxhhPbzkCAADAO0yQBwAAsBBhCwAAwEKELQAAAAsRtgAAACxE2AIAALAQYQsAAMBChC0AAAALEbYAAAAsRNgCAACwEGELAADAQoQtAAgyAwYMkM1m09q1a52+//zzz2Wz2WSz2eqoZrWTn5+vZs2aKSkpSUeOHKnr6gB+R9gC4JGHH37Y8YPckw+skZ2drVWrVumqq65S796966wehYWFaty4sWw2myZNmuRxuZUrVzr6yJIlSyRJCQkJ+sMf/qC8vDw9+uijVlUZqDOELQBea968eY0f+F9ZWZkeeOABSafDb12Ki4vTqFGjJElvvvmmSkpKPCo3f/58SVKzZs107bXXOr6fNGmSkpOT9eKLL2r79u3+rzBQhwhbALy2f//+Gj/wv+zsbG3fvl09e/ZUr1696ro6uv322yVJx44d03vvvVfj/vn5+Vq8eLEkacyYMWrQoIFjW0JCgn7729+qrKxMzz33nBXVBeoMYQsAgsRLL70kSbr55pvruCan9erVSxdccIGkX0esqvPOO++ooKBAkjRu3Lgq2yuua+HChSosLPRjTYG6RdgCEBDp6emy2WxasGCBSktL9fTTT6tr166Kj49X48aNNWjQIH388cc1Hmfjxo0aN26c2rdvr7i4OCUkJKhr167605/+pMOHD7ssUzHf7JJLLpF0eoTosssuU0pKiiIiIqrcknv//feVlZWlJk2aOI4/Y8YMlZWVVTmWdHpkJy4uTjabTe+880619Z82bZpsNpvOPvtsGWNqvN4K27Zt0xdffCGbzaabbrrJ43KVHTlyRH379pXNZlO7du20detWp+3Hjx/XE088od69eyspKUkxMTFq06aNRo0apTVr1rg8ZsXo1ooVK7Rnz55qz18RyPr06aNzzz23yvaePXuqQ4cOOn78uN5+++3aXCJQPxkA8MD06dONJFPbfzbS0tKMJDN79mzTu3dvI8k0aNDAJCQkOI5rs9nMK6+84vYYDz30kLHZbI794+LiTHR0tOP3LVu2NBs2bHBb94EDB5p7773Xca6kpCQTGRlppk+f7tj3D3/4g+N4kkyTJk1MVFSUkWQuvvhiM3XqVMexKhs7dqyRZLKystzWv7y83LRu3dpIMk888YRX7ffCCy8YSeacc85xu09OTo7bP6Ndu3aZTp06GUmma9euZu/evU7b16xZY5o3b+4oHxkZaRo1auT0Z/Pkk09WOe7hw4cdfwaPPfaY27pt3brVcax58+a53e/22283kswNN9zgdh8g2BC2AHjEX2ErKSnJtG7d2rz33numtLTUGGPM999/b/r06WMkmYSEBJOXl1el/LPPPmskmUaNGpk///nPZt++fcaY0wFm/fr1ZtCgQUaSSU1NNSdPnnRZ94pgd//995uDBw8aY4wpLi42u3btMsYYs2jRIsc1jh492vz888/GGGOKiorM3LlzTcOGDU1SUpLLsLVmzRpHKNmxY4fLNvjHP/5hJJmoqChH/T01YsQII8nccsstbvdxF7a+/fZb06pVKyPJXHrppeb48eNO23fu3GmaNGliJJkRI0aY3NxcU1ZWZowx5sCBA2batGmOwLl06dIq573hhhuMJNO+fXtjt9td1u2BBx4wkkx8fLw5ceKE22uYO3eukWSaN2/udh8g2BC2AHikcthq3rx5tZ+77767SvmKsBUTE2O2bNlSZfvBgwdNw4YNjSSzcOFCp22HDh0ycXFxxmazmRUrVrisX1lZmenRo4eRZJ599lm3db/33ntdlrfb7aZDhw5GkhkyZIjL0PDqq686jnNm2DLGmO7duxtJ5oEHHnB5jmuuucZIMsOHD3e5vTpt2rQxkszMmTPd7uMqbH3++eemcePGRpIZOXKkKS4urlLOkyD3zDPPOEbFzrR8+XLHeXNycqpsLy8vd4S9W2+9tdrr/Prrrx3H+vHHH6vdFwgWzNkC4LUDBw5U+zl+/LjbsiNGjFCnTp2qfN+sWTP17dtXkvTtt986bXvjjTdUWFionj17Kisry+Vxo6KiHEsRLF++3OU+ERER+uMf/+hy26ZNm7Rt2zZJ0tSpU12uFTZ27Fi1bdvWzZVJd9xxhyTp1VdfVVlZmdO2X375Rf/85z8lSRMnTnR7DFeMMdq3b5+k0+3kqezsbF1++eU6fvy4Jk2apLfeeksxMTFO+xw9etSx3lXFshKujBkzRpL0zTff6MCBA07bBg8e7GiXV199tUrZ5cuXa+/evZJ+nePlTnJysuPXFWWAYEfYAuA1c3pU3O1nwYIFbstWtxBnq1atJJ0OAJWtWrVKkvTf//5XLVq0cPupWBBz9+7dLo+fkZGhlJQUl9s2bNggSWrQoIEuuugil/vYbDYNHDjQbf1Hjx6txMREHThwQMuWLXPaNn/+fJ06dUrt2rXTkCFD3B7Dlby8PJWXl0uSmjZt6lGZv/3tb7rhhhtUUlKiJ554QrNnz1ZERNV/8r/66ivZ7XZJ0qBBg9y27Xnnnecoc2b7RkRE6NZbb5Ukvfvuuzp58qTT9oqJ8R07dlT//v2rrXfl6zt06JBH1wrUd4QtAAHVqFEjt9uioqIkqcqoUMUIR1FRUbUjaidOnJAkt8sGuAta0q8/2M866yxFR0e73a9169Zut1WsFSVJc+fOdXxvt9v1yiuvSJLGjx/v9Qr7xcXFjl+fOTLlzqRJk2S323XnnXdq6tSpbverPHpU04hlBVfte9ttt8lms6mwsFBvvfWW4/sjR444gqer5R7OFBsb6/h15esGghlhC0C9d+rUKUmnb9PVNKpmjNGuXbtcHicyMtLtOcz/X4ahpiBUsZ87v/vd7yRJn376qaMen3zyiXbv3q2oqCjddttt1ZZ35ayzznL8+tixYx6VqVizat68eVVG2SqraNvY2FiP2tYY47TsRYX09HTHLd7KtxIXLlyo0tJSRUVFOW5FVqfyqGbl6waCGWELQL3XokULSdJ//vMfy85RMep1+PBhlZaWut2vpnlEF1xwgS666CKn0ax58+ZJkq677jrHtXgjOjpaiYmJkqreYnXntdde09ixY1VaWqrrr7/e7QrvFfUpKiry+TU5FfOxvvrqK33//feSfg1eV155pVq2bFnjMSpfnzfz04D6jLAFoN7r16+fJGnNmjVu52P5KjMzU9LpW5irV692uY8xRl9++WWNx6oY3Zo/f75++eUXx8jShAkTal2/ikVAf/zxR4/2j4iI0Pz583X77berrKxMN9xwg7Kzs6vsd9FFFzlG8yrf/quN3/zmN445V/Pnz1dubq6++eYbSTVPjK+wc+dOSadvKXfo0MGn+gD1BWELQL13yy23KDY2VqdOndKdd97puPXlit1uV15entfn6NatmzIyMiRJTz31lMvbhQsXLvQo7I0cOVJnnXWW9u7dq9GjR6usrKxWE+Mru/jiiyVJ69at87hMRESE5s2bpwkTJqisrEw33XRTlRXuU1JSdN1110mSnn766Sqryp+pupG1mJgYx5y1119/3TGi17x5c1199dUe1Xnt2rWSpB49eig+Pt6jMkB9R9gCUO+1aNFCTz31lCTpww8/1JAhQ/Tvf//bEbqMMfr+++/1zDPP6Pzzz9cHH3zg9TlsNpseeeQRSaeXKhg7dqzjlmFxcbFeeeUVTZw4UUlJSTUeKyYmxvF0XsVIWG0mxldWMU9q/fr11YbNM9lsNr300kv6/e9/r/Lyco0ePVqLFi1y2mfWrFk666yzdOLECfXv31/z5893Wr7j8OHDWrJkiYYPH+5YXsOdihGs/fv3O8LWmDFjHA8/1KQibFX31CcQdCxfyQtASPBmUdPmzZubf//7307lKxY1ffXVV92eo+KVN2PHjnW5fcaMGSYyMtJRj+joaHPWWWeZBg0aOL1i58xFUSu/rqcmU6ZMcXpFTVJSkuP4gwYNMg8++KCRZC6//PJqj7Nt2zbHq4Vqs2L8mUpKSkyzZs2MJPPJJ5+43Ke61/UYY8zdd9/teBXP3//+d6dtGzZsMOnp6VWuvfLrlCSZwYMH11jXisVlKz6uFrF15fjx446FbTdt2uRRGSAYMLIFwGs1LRFw4MCBaieZ19b//u//6vvvv9c999yjLl26qGHDhsrLy1NCQoJ69eql+++/X6tXr9bo0aNrfY5nn31WS5Ys0SWXXKJGjRqppKREnTt31tNPP63ly5eroKBAktSkSZNqj5ORkaFu3bpJqv3E+Mqio6MdTzK+8cYbtTrG888/r3vvvVenTp3Srbfe6rQeWvfu3bV582b99a9/1eDBg5WcnKyTJ0/KbrerQ4cOGj16tN566y3HAqjVqTw/66KLLnK5iK0r2dnZKi4uVu/evdW1a1evrw+or2zGePHaeQAIc/369dPq1av16KOPatq0aW73279/v9q0aaPy8nItX75cl112mc/n/vHHH9WxY0fFxcVp3759ITenadCgQcrJydFrr73m0TIRQLBgZAsAPPTFF184nlS84oorqt33pZdeUnl5uTIyMnyaGF/Z2Wefrdtvv10nT57U3/72N78cs75Yt26dcnJydN555zkm2QOhgrAFAJXceeedWrBggfbv3+94IjEvL09z5sxxPLU3aNAg9erVy+0x1q9fr1mzZkmS7r33Xp8mxp/p0UcfVUJCgmbOnOm4pRkKpk+fLkmaMWNGtYvPAsGI24gAUEm3bt0ca0PFxMQoLi5OeXl5juB17rnn6pNPPnH52p709HSVlJRo//79kk7Pg1q7dq0aNGjg1zq+99572rRpk0aOHOn0zsJglZ+fr1mzZqlJkyaaPHlyXVcH8DvCFgBU8o9//ENLly7VunXrdODAAR0/flyJiYk677zzNHz4cE2YMEFxcXEuy1aMYLVo0UJXXHGFnnrqKTVv3jyQ1QdQDxG2AAAALMScLQAAAAsRtgAAACxE2AIAALAQYQsAAMBChC0AAAALEbYAAAAsRNgCAACwEGELAADAQv8P3ziCAoiF58sAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM = 2.94\n",
      "FWTM = 6.52\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM = 2.41\n",
      "FWTM = 4.48\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM = 4.61\n",
      "FWTM = 15.14\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM = 2.88\n",
      "FWTM = 5.76\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM = 2.7\n",
      "FWTM = 5.82\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM = 2.21\n",
      "FWTM = 5.25\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# AC_list = ['20231003_Cs137_AC_600V_1.dat', '20231003_Cs137_AC_600V_2.dat', '20231011_Cs137_AC_600V.dat', '20231020_Cs137_AC_600V.dat']\n",
    "# DC_list = ['20230927_Cs137_DC_600V.dat', '20231006_Cs137_DC_600V_1.dat', '20231006_Cs137_DC_600V_2.dat', '20231023_Cs137_DC_600V.dat']\n",
    "# allpaths = np.concatenate([AC_list, DC_list])\n",
    "    \n",
    "# path_lists = [AC_list, DC_list, allpaths]\n",
    "# strings = ['Cs137allAC_preLL', 'Cs137allDC_preLL', 'Cs137allACandDC_preLL']\n",
    "\n",
    "data_dict = {}\n",
    "# for source in file_dict:\n",
    "for source in file_dict:\n",
    "    emin = erange_dict[source][0]\n",
    "    emax = erange_dict[source][1]\n",
    "    \n",
    "    string = source + 'allAC_preLL'\n",
    "    \n",
    "    ## Read in the dat files\n",
    "    fullpaths = []\n",
    "    for p in np.concatenate(file_dict[source]):\n",
    "        fullpaths.append(datpath + 'preLL/' + p)\n",
    "    \n",
    "    df = make_df_from_dat(fullpaths, e_min=emin, e_max=emax)\n",
    "    bins = int((emax-emin) * 4)\n",
    "    plt.figure()\n",
    "    hist,binedges,_  = plt.hist(df['energy_p'], bins=bins, range=(emin, emax))\n",
    "    plt.yscale('log')\n",
    "    plt.xlabel('Energy (keV)')\n",
    "    plt.ylabel('Counts')\n",
    "    plt.show()\n",
    "    \n",
    "    fwhm_spline = UnivariateSpline(binedges[:-1], hist-0.5*np.max(hist))\n",
    "    fwtm_spline = UnivariateSpline(binedges[:-1], hist-0.1*np.max(hist))\n",
    "    fwhm = fwhm_spline.roots()[-1]-fwhm_spline.roots()[0]\n",
    "    fwtm = fwtm_spline.roots()[-1]-fwtm_spline.roots()[0]\n",
    "    print('FWHM = ' + str(round(fwhm, 2)))\n",
    "    print('FWTM = ' + str(round(fwtm, 2)))\n",
    "\n",
    "    plt.figure()\n",
    "    hist,binedges,_  = plt.hist(df['energy_n'], bins=binedges)\n",
    "    plt.yscale('log')\n",
    "    plt.xlabel('Energy (keV)')\n",
    "    plt.ylabel('Counts')\n",
    "    plt.show()\n",
    "    \n",
    "    fwhm_spline = UnivariateSpline(binedges[:-1], hist-0.5*np.max(hist))\n",
    "    fwtm_spline = UnivariateSpline(binedges[:-1], hist-0.1*np.max(hist))\n",
    "    fwhm = fwhm_spline.roots()[-1]-fwhm_spline.roots()[0]\n",
    "    fwtm = fwtm_spline.roots()[-1]-fwtm_spline.roots()[0]\n",
    "    print('FWHM = ' + str(round(fwhm, 2)))\n",
    "    print('FWTM = ' + str(round(fwtm, 2)))\n",
    "\n",
    "    ### Run depth calibration\n",
    "\n",
    "    ctd_obs_map = [[[] for p in range(37)] for n in range(37)]\n",
    "    ctd_stretch_map = [[[] for p in range(37)] for n in range(37)]\n",
    "    ctd_obs_flat = []\n",
    "    ctd_stretch_flat = []\n",
    "\n",
    "    for p in range(37):\n",
    "        for n in range(37):\n",
    "            ctd_obs, ctd_stretch, depth, depth_err, bad = calibrator.depth_from_timing_prob(p+1, n+1, df.loc[df.strip_p.eq(p+1)&df.strip_n.eq(n+1), 'time_p'], \\\n",
    "                                                                                       df.loc[df.strip_p.eq(p+1)&df.strip_n.eq(n+1), 'time_n'], \\\n",
    "                                                                                      df.loc[df.strip_p.eq(p+1)&df.strip_n.eq(n+1), 'energy_p'])\n",
    "            df.loc[df.strip_p.eq(p+1)&df.strip_n.eq(n+1), 'z'] =  depth\n",
    "            df.loc[df.strip_p.eq(p+1)&df.strip_n.eq(n+1), 'z_err'] =  depth_err\n",
    "            df.loc[df.strip_p.eq(p+1)&df.strip_n.eq(n+1), 'bad'] =  bad\n",
    "            ctd_obs_map[p][n] = ctd_obs[~bad]\n",
    "            ctd_stretch_map[p][n] = ctd_stretch[~bad]\n",
    "            ctd_obs_flat.append(ctd_obs[~bad])\n",
    "            ctd_stretch_flat.append(ctd_stretch[~bad])\n",
    "\n",
    "    ctd_obs_flat = np.concatenate(ctd_obs_flat)\n",
    "    ctd_stretch_flat = np.concatenate(ctd_stretch_flat)\n",
    "    data_dict[source] = df\n",
    "    \n",
    "    plt.figure()\n",
    "    plt.hist(df[\"z\"], bins=50, histtype = \"step\", range=(calibrator.zmin,calibrator.zmax))\n",
    "    plt.yscale('log')\n",
    "    plt.xlabel(\"z (cm)\")\n",
    "    plt.ylabel(\"counts\")\n",
    "    plt.tight_layout()\n",
    "    plt.savefig(plot_dir + 'depth_' + string + '_prob.pdf')\n",
    "\n",
    "    plt.figure()\n",
    "    plt.hist(ctd_obs_flat, bins=50, histtype=\"step\", label=\"Observed CTD\")\n",
    "    plt.hist(ctd_stretch_flat, bins=50, histtype=\"step\", color='red', label=\"stretched and shifted\")\n",
    "    plt.axvline(np.max(sim_ctd), lw=0.8, color='red', ls='dashed', zorder=0)\n",
    "    plt.axvline(np.min(sim_ctd), lw=0.8, color='red', ls='dashed', zorder=0)\n",
    "    plt.yscale('log')\n",
    "    plt.xlabel('CTD')\n",
    "    plt.ylabel('counts')\n",
    "    plt.tight_layout()\n",
    "    plt.savefig(plot_dir + \"CTD_\" + string + \".pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM = 3.678+/-0.041\n",
      "FWTM = 8.888+/-0.028\n",
      "FWHM = 3.385+/-0.009\n",
      "FWTM = 7.948+/-0.01\n",
      "FWHM = 2.511+/-0.004\n",
      "FWTM = 5.147+/-0.009\n",
      "FWHM = 2.595+/-0.003\n",
      "FWTM = 5.079+/-0.007\n",
      "FWHM = 2.859+/-0.004\n",
      "FWTM = 6.628+/-0.007\n",
      "FWHM = 2.861+/-0.004\n",
      "FWTM = 6.04+/-0.068\n",
      "FWHM = 2.333+/-0.002\n",
      "FWTM = 4.438+/-0.004\n",
      "FWHM = 2.328+/-0.002\n",
      "FWTM = 4.463+/-0.002\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/cosilab/miniconda3/lib/python3.11/site-packages/scipy/interpolate/_fitpack2.py:313: UserWarning: \n",
      "The maximal number of iterations maxit (set to 20 by the program)\n",
      "allowed for finding a smoothing spline with fp=s has been reached: s\n",
      "too small.\n",
      "There is an approximation returned but the corresponding weighted sum\n",
      "of squared residuals does not satisfy the condition abs(fp-s)/s < tol.\n",
      "  warnings.warn(message)\n",
      "/home/cosilab/COSITrapping/depth_helpers.py:632: UserWarning: Attempting to set identical low and high ylims makes transformation singular; automatically expanding.\n",
      "  ax.set_ylim((np.min(hist) + 10., 2.0*np.max(hist)))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM = 4.576+/-0.338\n",
      "FWTM = 16.173+/-0.388\n",
      "FWHM = 4.142+/-0.174\n",
      "FWTM = 11.881+/-0.205\n",
      "FWHM = 3.027+/-0.115\n",
      "FWTM = 5.874+/-0.222\n",
      "FWHM = 2.889+/-0.137\n",
      "FWTM = 5.791+/-0.298\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/cosilab/COSITrapping/depth_helpers.py:57: IntegrationWarning: The occurrence of roundoff error is detected, which prevents \n",
      "  the requested tolerance from being achieved.  The error may be \n",
      "  underestimated.\n",
      "  quad(gauss_plus_tail, Emin, Emax, args=(BoverA, x0, sigma_gauss, gamma, CoverB, D, sigma_ratio))[0]\n",
      "/home/cosilab/miniconda3/lib/python3.11/site-packages/scipy/interpolate/_fitpack2.py:313: UserWarning: \n",
      "A theoretically impossible result was found during the iteration\n",
      "process for finding a smoothing spline with fp = s: s too small.\n",
      "There is an approximation returned but the corresponding weighted sum\n",
      "of squared residuals does not satisfy the condition abs(fp-s)/s < tol.\n",
      "  warnings.warn(message)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM = 2.695+/-0.0\n",
      "FWTM = 5.968+/-0.0\n",
      "FWHM = 3.01+/-0.0\n",
      "FWTM = 6.537+/-0.0\n",
      "FWHM = 2.171+/-0.0\n",
      "FWTM = 5.167+/-0.0\n",
      "FWHM = 2.474+/-0.0\n",
      "FWTM = 5.948+/-0.0\n"
     ]
    }
   ],
   "source": [
    "depth_plot_dict = {}\n",
    "for source in data_dict:\n",
    "    string = source + 'allAC_preLL'\n",
    "    z_bins, e_trapping, h_trapping = make_depthplot(data_dict[source], string, zbin_dict[source], source=source)\n",
    "    depth_plot_dict[source] = z_bins, e_trapping, h_trapping\n",
    "    depth_correction(data_dict[source], z_bins, e_trapping, h_trapping, plot_dir=plot_dir, plot_suffix = string, source = source)\n",
    "    with open('./depth_plot_'+string+'.txt', 'wb') as file:\n",
    "        pickle.dump([z_bins, e_trapping, h_trapping], file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM = 3.678+/-0.041\n",
      "FWTM = 8.888+/-0.028\n",
      "FWHM = 3.402+/-0.007\n",
      "FWTM = 7.906+/-0.013\n",
      "FWHM = 2.511+/-0.004\n",
      "FWTM = 5.147+/-0.009\n",
      "FWHM = 2.617+/-0.002\n",
      "FWTM = 5.102+/-0.003\n",
      "┌─────────────────────────────────────────────────────────────────────────┐\n",
      "│                                Migrad                                   │\n",
      "├──────────────────────────────────┬──────────────────────────────────────┤\n",
      "│ FCN = 210.2 (chi2/ndof = 3.8)    │              Nfcn = 347              │\n",
      "│ EDM = 0.000133 (Goal: 0.0002)    │                                      │\n",
      "├──────────────────────────────────┼──────────────────────────────────────┤\n",
      "│          Valid Minimum           │        No Parameters at limit        │\n",
      "├──────────────────────────────────┼──────────────────────────────────────┤\n",
      "│ Below EDM threshold (goal x 10)  │           Below call limit           │\n",
      "├───────────────┬──────────────────┼───────────┬─────────────┬────────────┤\n",
      "│  Covariance   │     Hesse ok     │ Accurate  │  Pos. def.  │ Not forced │\n",
      "└───────────────┴──────────────────┴───────────┴─────────────┴────────────┘\n",
      "┌───┬──────┬───────────┬───────────┬────────────┬────────────┬─────────┬─────────┬───────┐\n",
      "│   │ Name │   Value   │ Hesse Err │ Minos Err- │ Minos Err+ │ Limit-  │ Limit+  │ Fixed │\n",
      "├───┼──────┼───────────┼───────────┼────────────┼────────────┼─────────┼─────────┼───────┤\n",
      "│ 0 │ ae   │ 1.001158  │ 0.000012  │ -0.000012  │  0.000012  │         │         │       │\n",
      "│ 1 │ b    │   1.316   │   0.011   │   -0.011   │   0.011    │    0    │         │       │\n",
      "│ 2 │ c    │   0.540   │   0.007   │   -0.007   │   0.007    │    0    │         │       │\n",
      "│ 3 │ ah   │ 1.000685  │ 0.000011  │ -0.000011  │  0.000011  │         │         │       │\n",
      "└───┴──────┴───────────┴───────────┴────────────┴────────────┴─────────┴─────────┴───────┘\n",
      "┌──────────┬───────────────────────┬───────────────────────┬───────────────────────┬───────────────────────┐\n",
      "│          │          ae           │           b           │           c           │          ah           │\n",
      "├──────────┼───────────┬───────────┼───────────┬───────────┼───────────┬───────────┼───────────┬───────────┤\n",
      "│  Error   │ -0.012e-3 │ 0.012e-3  │  -0.011   │   0.011   │  -0.007   │   0.007   │ -0.011e-3 │ 0.011e-3  │\n",
      "│  Valid   │   True    │   True    │   True    │   True    │   True    │   True    │   True    │   True    │\n",
      "│ At Limit │   False   │   False   │   False   │   False   │   False   │   False   │   False   │   False   │\n",
      "│ Max FCN  │   False   │   False   │   False   │   False   │   False   │   False   │   False   │   False   │\n",
      "│ New Min  │   False   │   False   │   False   │   False   │   False   │   False   │   False   │   False   │\n",
      "└──────────┴───────────┴───────────┴───────────┴───────────┴───────────┴───────────┴───────────┴───────────┘\n",
      "┌────┬─────────────────────────────────────┐\n",
      "│    │       ae        b        c       ah │\n",
      "├────┼─────────────────────────────────────┤\n",
      "│ ae │ 1.48e-10  9.4e-08  2.5e-08 4.47e-11 │\n",
      "│  b │  9.4e-08 0.000119 2.31e-05 4.56e-08 │\n",
      "│  c │  2.5e-08 2.31e-05 4.74e-05 6.37e-08 │\n",
      "│ ah │ 4.47e-11 4.56e-08 6.37e-08 1.21e-10 │\n",
      "└────┴─────────────────────────────────────┘\n",
      "FWHM = 2.859+/-0.004\n",
      "FWTM = 6.628+/-0.007\n",
      "FWHM = 2.873+/-0.003\n",
      "FWTM = 6.056+/-0.022\n",
      "FWHM = 2.333+/-0.002\n",
      "FWTM = 4.438+/-0.004\n",
      "FWHM = 2.33+/-0.002\n",
      "FWTM = 4.466+/-0.002\n",
      "┌─────────────────────────────────────────────────────────────────────────┐\n",
      "│                                Migrad                                   │\n",
      "├──────────────────────────────────┬──────────────────────────────────────┤\n",
      "│ FCN = 113 (chi2/ndof = 2.0)      │              Nfcn = 319              │\n",
      "│ EDM = 9.84e-05 (Goal: 0.0002)    │                                      │\n",
      "├──────────────────────────────────┼──────────────────────────────────────┤\n",
      "│          Valid Minimum           │        No Parameters at limit        │\n",
      "├──────────────────────────────────┼──────────────────────────────────────┤\n",
      "│ Below EDM threshold (goal x 10)  │           Below call limit           │\n",
      "├───────────────┬──────────────────┼───────────┬─────────────┬────────────┤\n",
      "│  Covariance   │     Hesse ok     │ Accurate  │  Pos. def.  │ Not forced │\n",
      "└───────────────┴──────────────────┴───────────┴─────────────┴────────────┘\n",
      "┌───┬──────┬───────────┬───────────┬────────────┬────────────┬─────────┬─────────┬───────┐\n",
      "│   │ Name │   Value   │ Hesse Err │ Minos Err- │ Minos Err+ │ Limit-  │ Limit+  │ Fixed │\n",
      "├───┼──────┼───────────┼───────────┼────────────┼────────────┼─────────┼─────────┼───────┤\n",
      "│ 0 │ ae   │ 1.001228  │ 0.000019  │ -0.000019  │  0.000019  │         │         │       │\n",
      "│ 1 │ b    │   1.405   │   0.015   │   -0.015   │   0.015    │    0    │         │       │\n",
      "│ 2 │ c    │   0.596   │   0.011   │   -0.011   │   0.011    │    0    │         │       │\n",
      "│ 3 │ ah   │ 1.000648  │ 0.000019  │ -0.000019  │  0.000019  │         │         │       │\n",
      "└───┴──────┴───────────┴───────────┴────────────┴────────────┴─────────┴─────────┴───────┘\n",
      "┌──────────┬───────────────────────┬───────────────────────┬───────────────────────┬───────────────────────┐\n",
      "│          │          ae           │           b           │           c           │          ah           │\n",
      "├──────────┼───────────┬───────────┼───────────┬───────────┼───────────┬───────────┼───────────┬───────────┤\n",
      "│  Error   │ -0.019e-3 │ 0.019e-3  │  -0.015   │   0.015   │  -0.011   │   0.011   │ -0.019e-3 │ 0.019e-3  │\n",
      "│  Valid   │   True    │   True    │   True    │   True    │   True    │   True    │   True    │   True    │\n",
      "│ At Limit │   False   │   False   │   False   │   False   │   False   │   False   │   False   │   False   │\n",
      "│ Max FCN  │   False   │   False   │   False   │   False   │   False   │   False   │   False   │   False   │\n",
      "│ New Min  │   False   │   False   │   False   │   False   │   False   │   False   │   False   │   False   │\n",
      "└──────────┴───────────┴───────────┴───────────┴───────────┴───────────┴───────────┴───────────┴───────────┘\n",
      "┌────┬─────────────────────────────────────┐\n",
      "│    │       ae        b        c       ah │\n",
      "├────┼─────────────────────────────────────┤\n",
      "│ ae │ 3.54e-10 2.03e-07 5.84e-08 1.06e-10 │\n",
      "│  b │ 2.03e-07 0.000222 4.49e-05 8.96e-08 │\n",
      "│  c │ 5.84e-08 4.49e-05 0.000127 1.82e-07 │\n",
      "│ ah │ 1.06e-10 8.96e-08 1.82e-07 3.62e-10 │\n",
      "└────┴─────────────────────────────────────┘\n",
      "FWHM = 4.576+/-0.338\n",
      "FWTM = 16.173+/-0.388\n",
      "FWHM = 4.034+/-0.26\n",
      "FWTM = 12.821+/-0.317\n",
      "FWHM = 3.027+/-0.115\n",
      "FWTM = 5.874+/-0.222\n",
      "FWHM = 2.899+/-0.084\n",
      "FWTM = 5.776+/-0.247\n",
      "┌─────────────────────────────────────────────────────────────────────────┐\n",
      "│                                Migrad                                   │\n",
      "├──────────────────────────────────┬──────────────────────────────────────┤\n",
      "│ FCN = 73.53 (chi2/ndof = 1.3)    │              Nfcn = 330              │\n",
      "│ EDM = 0.000139 (Goal: 0.0002)    │                                      │\n",
      "├──────────────────────────────────┼──────────────────────────────────────┤\n",
      "│          Valid Minimum           │        No Parameters at limit        │\n",
      "├──────────────────────────────────┼──────────────────────────────────────┤\n",
      "│ Below EDM threshold (goal x 10)  │           Below call limit           │\n",
      "├───────────────┬──────────────────┼───────────┬─────────────┬────────────┤\n",
      "│  Covariance   │     Hesse ok     │ Accurate  │  Pos. def.  │ Not forced │\n",
      "└───────────────┴──────────────────┴───────────┴─────────────┴────────────┘\n",
      "┌───┬──────┬───────────┬───────────┬────────────┬────────────┬─────────┬─────────┬───────┐\n",
      "│   │ Name │   Value   │ Hesse Err │ Minos Err- │ Minos Err+ │ Limit-  │ Limit+  │ Fixed │\n",
      "├───┼──────┼───────────┼───────────┼────────────┼────────────┼─────────┼─────────┼───────┤\n",
      "│ 0 │ ae   │  1.00079  │  0.00005  │  -0.00005  │  0.00005   │         │         │       │\n",
      "│ 1 │ b    │   1.15    │   0.05    │   -0.05    │    0.05    │    0    │         │       │\n",
      "│ 2 │ c    │   0.554   │   0.023   │   -0.023   │   0.023    │    0    │         │       │\n",
      "│ 3 │ ah   │ 1.000675  │ 0.000031  │ -0.000031  │  0.000031  │         │         │       │\n",
      "└───┴──────┴───────────┴───────────┴────────────┴────────────┴─────────┴─────────┴───────┘\n",
      "┌──────────┬───────────────────────┬───────────────────────┬───────────────────────┬───────────────────────┐\n",
      "│          │          ae           │           b           │           c           │          ah           │\n",
      "├──────────┼───────────┬───────────┼───────────┬───────────┼───────────┬───────────┼───────────┬───────────┤\n",
      "│  Error   │ -0.05e-3  │  0.05e-3  │   -0.05   │   0.05    │  -0.023   │   0.023   │ -0.031e-3 │ 0.031e-3  │\n",
      "│  Valid   │   True    │   True    │   True    │   True    │   True    │   True    │   True    │   True    │\n",
      "│ At Limit │   False   │   False   │   False   │   False   │   False   │   False   │   False   │   False   │\n",
      "│ Max FCN  │   False   │   False   │   False   │   False   │   False   │   False   │   False   │   False   │\n",
      "│ New Min  │   False   │   False   │   False   │   False   │   False   │   False   │   False   │   False   │\n",
      "└──────────┴───────────┴───────────┴───────────┴───────────┴───────────┴───────────┴───────────┴───────────┘\n",
      "┌────┬─────────────────────────────────────┐\n",
      "│    │       ae        b        c       ah │\n",
      "├────┼─────────────────────────────────────┤\n",
      "│ ae │ 2.88e-09 2.14e-06 4.84e-07 8.23e-10 │\n",
      "│  b │ 2.14e-06  0.00233 0.000475 8.44e-07 │\n",
      "│  c │ 4.84e-07 0.000475 0.000529 6.04e-07 │\n",
      "│ ah │ 8.23e-10 8.44e-07 6.04e-07 9.46e-10 │\n",
      "└────┴─────────────────────────────────────┘\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/cosilab/miniconda3/lib/python3.11/site-packages/scipy/interpolate/_fitpack2.py:313: UserWarning: \n",
      "A theoretically impossible result was found during the iteration\n",
      "process for finding a smoothing spline with fp = s: s too small.\n",
      "There is an approximation returned but the corresponding weighted sum\n",
      "of squared residuals does not satisfy the condition abs(fp-s)/s < tol.\n",
      "  warnings.warn(message)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM = 2.695+/-0.0\n",
      "FWTM = 5.968+/-0.0\n",
      "FWHM = 2.877+/-0.0\n",
      "FWTM = 6.301+/-0.0\n",
      "FWHM = 2.171+/-0.0\n",
      "FWTM = 5.167+/-0.0\n",
      "FWHM = 2.324+/-0.0\n",
      "FWTM = 5.856+/-0.0\n",
      "┌─────────────────────────────────────────────────────────────────────────┐\n",
      "│                                Migrad                                   │\n",
      "├──────────────────────────────────┬──────────────────────────────────────┤\n",
      "│ FCN = 1.797e+06 (chi2/ndof = 32097.1)│              Nfcn = 291              │\n",
      "│ EDM = 7e-05 (Goal: 0.0002)       │                                      │\n",
      "├──────────────────────────────────┼──────────────────────────────────────┤\n",
      "│          Valid Minimum           │       SOME Parameters at limit       │\n",
      "├──────────────────────────────────┼──────────────────────────────────────┤\n",
      "│ Below EDM threshold (goal x 10)  │           Below call limit           │\n",
      "├───────────────┬──────────────────┼───────────┬─────────────┬────────────┤\n",
      "│  Covariance   │     Hesse ok     │ Accurate  │  Pos. def.  │ Not forced │\n",
      "└───────────────┴──────────────────┴───────────┴─────────────┴────────────┘\n",
      "┌───┬──────┬───────────┬───────────┬────────────┬────────────┬─────────┬─────────┬───────┐\n",
      "│   │ Name │   Value   │ Hesse Err │ Minos Err- │ Minos Err+ │ Limit-  │ Limit+  │ Fixed │\n",
      "├───┼──────┼───────────┼───────────┼────────────┼────────────┼─────────┼─────────┼───────┤\n",
      "│ 0 │ ae   │ 1.002973  │ 0.000012  │ -0.000012  │  0.000012  │         │         │       │\n",
      "│ 1 │ b    │  27.024   │   0.031   │   -0.031   │   0.032    │    0    │         │       │\n",
      "│ 2 │ c    │  0.5e-12  │10711768.3e-12│  -0.5e-12  │10712175.0e-12│    0    │         │       │\n",
      "│ 3 │ ah   │994.020e-3 │ 0.009e-3  │ -0.009e-3  │  0.009e-3  │         │         │       │\n",
      "└───┴──────┴───────────┴───────────┴────────────┴────────────┴─────────┴─────────┴───────┘\n",
      "┌──────────┬───────────────────────┬───────────────────────┬───────────────────────┬───────────────────────┐\n",
      "│          │          ae           │           b           │           c           │          ah           │\n",
      "├──────────┼───────────┬───────────┼───────────┬───────────┼───────────┬───────────┼───────────┬───────────┤\n",
      "│  Error   │ -0.012e-3 │ 0.012e-3  │  -0.031   │   0.032   │ -0.5e-12  │10712175.0e-12│   -9e-6   │   9e-6    │\n",
      "│  Valid   │   True    │   True    │   True    │   True    │   True    │   True    │   True    │   True    │\n",
      "│ At Limit │   False   │   False   │   False   │   False   │   True    │   False   │   False   │   False   │\n",
      "│ Max FCN  │   False   │   False   │   False   │   False   │   False   │   False   │   False   │   False   │\n",
      "│ New Min  │   False   │   False   │   False   │   False   │   False   │   False   │   False   │   False   │\n",
      "└──────────┴───────────┴───────────┴───────────┴───────────┴───────────┴───────────┴───────────┴───────────┘\n",
      "┌────┬─────────────────────────────────────┐\n",
      "│    │       ae        b        c       ah │\n",
      "├────┼─────────────────────────────────────┤\n",
      "│ ae │ 1.48e-10 1.83e-07 1.31e-17 3.54e-12 │\n",
      "│  b │ 1.83e-07  0.00099  2.3e-14 1.91e-08 │\n",
      "│  c │ 1.31e-17  2.3e-14 2.25e-17 8.23e-17 │\n",
      "│ ah │ 3.54e-12 1.91e-08 8.23e-17 8.27e-11 │\n",
      "└────┴─────────────────────────────────────┘\n"
     ]
    }
   ],
   "source": [
    "param_dict = {}\n",
    "for source in data_dict:\n",
    "    string = source + 'allAC_preLL'\n",
    "    m = fit_CCE(*depth_plot_dict[source], sim_dCCE, plot_dir=plot_dir, plot_suffix = string, trim_index = 1, source=source)\n",
    "    depth_correction_CCE(data_dict[source], *m.values['ae','ah','b','c'], sim_dCCE, plot_dir=plot_dir, plot_suffix = string, source=source)\n",
    "    param_dict[source] = m\n",
    "    print(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM = 3.678+/-0.041\n",
      "FWTM = 8.888+/-0.028\n",
      "FWHM = 3.402+/-0.007\n",
      "FWTM = 7.906+/-0.013\n",
      "FWHM = 2.511+/-0.004\n",
      "FWTM = 5.147+/-0.009\n",
      "FWHM = 2.617+/-0.002\n",
      "FWTM = 5.102+/-0.003\n",
      "FWHM = 2.859+/-0.004\n",
      "FWTM = 6.628+/-0.007\n",
      "FWHM = 2.864+/-0.003\n",
      "FWTM = 6.032+/-0.026\n",
      "FWHM = 2.333+/-0.002\n",
      "FWTM = 4.438+/-0.004\n",
      "FWHM = 2.345+/-0.002\n",
      "FWTM = 4.461+/-0.003\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/cosilab/miniconda3/lib/python3.11/site-packages/scipy/interpolate/_fitpack2.py:313: UserWarning: \n",
      "A theoretically impossible result was found during the iteration\n",
      "process for finding a smoothing spline with fp = s: s too small.\n",
      "There is an approximation returned but the corresponding weighted sum\n",
      "of squared residuals does not satisfy the condition abs(fp-s)/s < tol.\n",
      "  warnings.warn(message)\n",
      "/home/cosilab/miniconda3/lib/python3.11/site-packages/scipy/interpolate/_fitpack2.py:313: UserWarning: \n",
      "The maximal number of iterations maxit (set to 20 by the program)\n",
      "allowed for finding a smoothing spline with fp=s has been reached: s\n",
      "too small.\n",
      "There is an approximation returned but the corresponding weighted sum\n",
      "of squared residuals does not satisfy the condition abs(fp-s)/s < tol.\n",
      "  warnings.warn(message)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM = 4.576+/-0.338\n",
      "FWTM = 16.173+/-0.388\n",
      "FWHM = 4.224+/-0.488\n",
      "FWTM = 12.809+/-0.643\n",
      "FWHM = 3.027+/-0.115\n",
      "FWTM = 5.874+/-0.222\n",
      "FWHM = 2.904+/-0.075\n",
      "FWTM = 5.662+/-0.205\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/cosilab/miniconda3/lib/python3.11/site-packages/scipy/interpolate/_fitpack2.py:313: UserWarning: \n",
      "A theoretically impossible result was found during the iteration\n",
      "process for finding a smoothing spline with fp = s: s too small.\n",
      "There is an approximation returned but the corresponding weighted sum\n",
      "of squared residuals does not satisfy the condition abs(fp-s)/s < tol.\n",
      "  warnings.warn(message)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM = 2.695+/-0.0\n",
      "FWTM = 5.968+/-0.0\n",
      "FWHM = 2.509+/-0.0\n",
      "FWTM = 5.806+/-0.0\n",
      "FWHM = 2.171+/-0.0\n",
      "FWTM = 5.167+/-0.0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/cosilab/miniconda3/lib/python3.11/site-packages/scipy/interpolate/_fitpack2.py:313: UserWarning: \n",
      "The maximal number of iterations maxit (set to 20 by the program)\n",
      "allowed for finding a smoothing spline with fp=s has been reached: s\n",
      "too small.\n",
      "There is an approximation returned but the corresponding weighted sum\n",
      "of squared residuals does not satisfy the condition abs(fp-s)/s < tol.\n",
      "  warnings.warn(message)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM = 2.391+/-0.0\n",
      "FWTM = 5.606+/-0.0\n"
     ]
    }
   ],
   "source": [
    "for source in data_dict:\n",
    "    string = source + 'allAC_preLL_Cs137params'\n",
    "    depth_correction_CCE(data_dict[source], *param_dict[source].values['ae','ah'], *param_dict['Cs137'].values['b','c'], sim_dCCE, plot_dir = plot_dir, plot_suffix = string, source=source)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.4"
  },
  "toc-autonumbering": true
 },
 "nbformat": 4,
 "nbformat_minor": 4
}