WLSAnalysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from legend_plot_style import LEGENDPlotStyle as lps\n",
    "lps.use(\"legend_talks\")\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from scipy.optimize import curve_fit\n",
    "import math\n",
    "import matplotlib.ticker as ticker\n",
    "\n",
    "file_path = '/home/eric/sim/WWLegend/Archive/WLS/'\n",
    "file_path_2 = '/home/eric/sim/WLSfoil/build/'\n",
    "\n",
    "LambdaIn, LambdaOut = np.loadtxt(file_path_2 + \"output0_nt_Hits.csv\", dtype=float, delimiter=',', skiprows=6, unpack=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now reproduce the 3 Plots. First Plot: Reflectivity!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def Get_Percentage_Absorbed(LambdaIn, LambdaOut, wavelengths):\n",
    "    \"\"\" Takes the Incident wavelengths LambdaIn and the outgoing wavelength LambdaOut\n",
    "        and array wavelengths. Returns an array stating the percantage of absorbed\n",
    "        photons per wavelength in wavelengths.\"\"\"\n",
    "    results_array = np.array([])\n",
    "    for i in wavelengths:\n",
    "        First = LambdaIn[LambdaIn == i]\n",
    "        Second = LambdaOut[LambdaIn == i]\n",
    "        if First.shape != Second.shape:\n",
    "            raise ValueError(\"Arrays must have the same length! rip\")\n",
    "        reflected_elements = np.sum(First == Second)\n",
    "        percentage_reflected = (reflected_elements / First.size) * 100\n",
    "        percentage_absorbed = 100 - percentage_reflected\n",
    "        results_array = np.append(results_array, percentage_absorbed)\n",
    "    return results_array\n",
    "\n",
    "def Get_Percentage_Reflected(wavelengths):\n",
    "    \"\"\" DOES NOT RETURN ACTUAL REFLECTANCE!\n",
    "        Takes an array wavelengths and returns an array consisting of 100 matching the shape.\n",
    "        Reason is to reproduce VM2000 plot.\"\"\"\n",
    "    results_array = np.array([])\n",
    "    for i in wavelengths:\n",
    "        results_array = np.append(results_array, 100)\n",
    "    return results_array\n",
    "\n",
    "def Get_Percentage_Absorbed_for_WLS(LambdaIn, LambdaOut, wavelengths):\n",
    "    \"\"\" Takes the Incident wavelengths LambdaIn and the outgoing wavelength LambdaOut\n",
    "        and array wavelengths. Returns an array stating the percantage of absorbed\n",
    "        photons used in WLS per wavelength in wavelengths.\"\"\"\n",
    "    results_array = np.array([])\n",
    "    for i in wavelengths:\n",
    "        First = LambdaIn[LambdaIn == i]\n",
    "        Second = LambdaOut[LambdaIn == i]\n",
    "        if First.shape != Second.shape:\n",
    "            raise ValueError(\"Arrays must have the same length! rip\")\n",
    "        reflected_elements = np.sum((First == Second) | (Second == 0))\n",
    "        percentage_reflected = (reflected_elements / First.size) * 100\n",
    "        percentage_absorbed = 100 - percentage_reflected\n",
    "        results_array = np.append(results_array, percentage_absorbed)\n",
    "    return results_array"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_5740/4256103025.py:12: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  percentage_reflected = (reflected_elements / First.size) * 100\n",
      "/tmp/ipykernel_5740/4256103025.py:37: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  percentage_reflected = (reflected_elements / First.size) * 100\n"
     ]
    },
    {
     "data": {
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777+f6NevX6JOnTqbHTsrKyvRqVOnxKBBgxKLFy8u8TzrFX4/7Lrrrht8ffHixYkbb7wxsdtuu222n4YNGybOOeecMr+fNubFF19M9O7dO1G1atXN9tCiRYvE7373u8SMGTPKdf68vLzEfffdl9hnn302O3+VKlUShx12WGLYsGGJgoKCcu0hHbp27Zp8bPvvv/9Gz2nTpk3ynD59+pTLvFv6jPr+++8Tl1566RY/czp16lTiz94tWbFiRWLw4MGJ/fbbb7Of/RGRqFWrVuKEE05IvP322+U2/3pffPFF4vzzz080bNhwsz1kZ2cnunfvnrjvvvsSK1euLNOchcf95JNPUr62evXqxN13351o167dRvt4/vnnNzrmr3/96+Q5H3/88QZfHzVqVKJfv36b/XzPzs5O9OjRI/Hcc8+V6PEUnru0t80p799vvvnmm8QVV1yRaN68+Rb76ty5c+LWW29NLFq0qExztmrVKjnmX//61w2+PmbMmMQZZ5yRqFWr1mb72XPPPRN33nlnYvXq1WXqZ2tYt25dokGDBsne69Spk1i7dm2Jx7n77rtTnoNnnnkm+bWvv/465Wt/+ctfStVr69atk2PUrFmz2J91Rd/76fDwww+n9FARn5OJRCLx7LPPJvbff//kbd68eRUyDwAAZApBMAAAACrc1gqC/f3vf0+Z58svvyz1WB999FGiY8eOJf6D8e6775544403ijVHWf84vTWCYKtWrUr8/ve/T1SuXLlEvVWqVClxwQUXJJYtW1aqedf74YcfEkcffXSJn5vs7OzEr371q8TSpUu3OEdFvg5FTZs2LXHooYeWap66desm/vOf/5TqedxcEOzxxx9P1K9fv0S9VKlSJXHTTTeVqpeixo8fn9hvv/1K/HxUqVIlceWVV5ZL6ODll19O7LLLLiXuYZ999kmMGjWqHJ6F9CgaVLjnnns2et6AAQNSnveFCxeWee5NfUatW7cucdNNN20xEFj01r59+8SYMWPK3Ncbb7xRqvdCRCQOPPDAxJQpU8rcw5w5cxInn3xyqXpo1qxZYtiwYaWeu/BYL730UvL42LFjE+3bt9/s3MUJgj3++OPJ40uWLEmcffbZJX6Mhx9+eGLOnDnFejyZEgRbsmRJ4qKLLkpUqlSpxP3Vq1cvceeddybWrVtXqrk3FQRbtmxZ4rzzzktkZWWVqJ82bdpkxOfiCSeckNL3Z599VuIxCv9+Urly5cSSJUtSvl44xNW1a9cSj//DDz+k9HjEEUcU+9ptIQj29ttvp/Twxz/+MS19AADAjsbWkAAAAGw35syZk1IX3SqyuO688874/e9/n7JdWkREkyZNYs8994ymTZvGunXrYv78+TFu3LhYuHBh8pwpU6bEscceGw888ECce+65pZp/WzFjxoz4xS9+EWPHjk05np2dHXvttVe0aNEi6tWrF4sWLYoZM2bEuHHjktsArVu3Lh588MEYM2ZMvPbaa9GoUaMSz//BBx9Enz59Ijc3N+V45cqVY88994xmzZpFo0aNYunSpTF9+vQYN25cFBQURMRP28k9+uij8dFHH8Xzzz8fnTp1KuWzUH5ef/31OOWUU2L58uUpx6tXrx5dunSJZs2aRe3atWP58uUxb968+PLLL2PZsmXJ85YsWRJnn312/O9//4shQ4aUeYvGRCIRf/jDH+L2229POb777rvHHnvsEfXr14/8/PyYP39+fPHFF7F48eLkOWvWrIk///nPMXPmzLj33ntL3cNzzz0XZ5xxRuTl5aUcr1GjRnTo0CGaNWsW9evXj0WLFsXUqVNj4sSJKT3ccccd8f7778ezzz4bu+yyS4nnLygoiGuuuSb+8Y9/bPC1XXbZJdq1axc77bRTrF69OubNmxdjxoxJeU1Gjx4dPXr0iKeffjp69+5d4vnT7bHHHkvez8nJiX79+m30vDPOOCMGDhwYET8970899VRcdNFF5d5PXl5e9OvXL1588cXksUqVKkXHjh2jTZs2Ua9evVi8eHHMnDkzvv7661i9enXyvEmTJsUBBxwQzz//fMr2bCVx8803x5///OcNjjdq1Cg6d+4cjRo1iurVq8fixYvjhx9+iHHjxqX8nPjoo4+iS5cuMXz48Dj22GNL1cPIkSPjpJNOigULFmzwtXbt2kWLFi2iWbNmsXTp0pg9e3ZMnjw55T05Z86cOOOMM+KNN96Ihx56KKpWrVqqPiIi5s6dGxER7733Xhx77LEpn13t27eP3XffPRo0aBA5OT/9J+bibNM5bdq0iIj44Ycf4phjjokJEyYkv1azZs3o0qVLNG3aNGrUqBE//vhj/PDDDzF58uSUMd5+++3Yd99945133tkqW8VWtPHjx8fxxx+ffG4Ka9u2bbRs2TKaN28eeXl5MXv27JgyZUrK7x2LFy+Oyy+/PF599dV46qmnymWb0NmzZ8dRRx0V48ePTx6rVq1a8mdVnTp1YsmSJTFjxoz48ssvU74Ppk2bFr169YoXX3wxDj300DL3UlF69eoVL7zwQrIeOXJk7LvvvsW+ftWqVTFixIhkfcghh2ywHeExxxwT//rXvyIiYsyYMfHjjz+WaPvUTN4WMiLioIMOilq1aiU/Ox599NEYMGBA1KpVK82dAQDAdi7dSTQAAAC2f1trRbAuXbok52jdunWpxrj22ms3WN2ib9++iY8//nijq22sW7cu8cEHH2x01apHHnlks3PNmDFjg9sVV1yRMsbHH3+80fNmzJiRyM3N3eTYZV0R7Pvvv99gVZymTZsm7r333sT8+fM3es3cuXMTd9xxR8p2SxE/bRdV0u3KPvnkk0SNGjVSxtljjz0SgwcP3uTjzs3NTdx1112JFi1apFy30047Jb777rtNzrWx5/app55KGeOOO+4o1euw3quvvpqoUqVKypiHHnpo4uWXX07k5+dv9Jp169YlRo4cmejbt+8G760LLrigeE/k/29jK4Jdc801yWPNmzdP3HbbbZvcTmnt2rWJt99+O3HggQdu0Mu///3vEvWy3vPPP7/Btnv77rtv4oknnkgsX758o9fMmTMnccMNN2zwHmvfvn2JV6kqKCjYYMWUSpUqJc4///xNria4Zs2axBtvvJHo3r17ynU5OTkVtuVVRSkoKEj5Hj/22GM3e/7ee++dPPeggw4q8/xFP6OmTp2aOPHEE1Pep/fff/8GK+ysl5ubm7jvvvsSO++8c8o41apVK9VqRIMGDdrgvf2rX/0q8fnnn2/ymuXLlyceeuihxB577JFyXdWqVRNvvfVWiXt47bXXNvicaNy4ceLWW29NfP/99xu9Ji8vL/H8888njjrqqA36P+KIIxJ5eXkl6qHw9X/7298SkydPTm5hW7NmzcS1116bmDVrVonGLPx9dt555yUWLFiQ8pwddthhiVdffXWTW/NNnDgxcdVVVyVycnJS+mvVqtUmfx6tl5ubu9HP7cI/J7p3777Jz/ctbUFb1t9vRo8enahbt27KGLVq1Upce+21m9xiee3atYk333wz0a9fvw1e87322qtYP5MKK7oi2KJFi1K2/zzssMMSL7300ia3JFy0aFFi0KBBG2zj2qhRo8TcuXNL1MvWNG7cuJR+jzvuuBJd/8orr2zwe8KWznn44YdLNMf555+/we+ExbUtrAiWSCQSp59+ekofF110Udp6AQCAHYUgGAAAABVuawTBvvnmm5Q5LrvsshKP8cgjj6SMUb9+/RKFO4YMGZLyh+patWolpk6dWqIeymtLx7KMs3Llyg22xTz99NOLvc3jggULEgcccEDK9RdffHGx58/NzU00bdo05frf/e53xQ6TLV26NHHaaaelXN+uXbvEqlWrit3Du+++m3J9abdkTCQSidmzZ6cElypXrlziPwa/8MILGwTjXnvttWJfXzQI9uyzzybr0047LbF48eJijVNQUJASIIv4acvKH3/8sUSP59tvv015PNnZ2Ymbb755k0GQon788cfE4YcfntJHjx49StTD9ddfn3J9y5YtS7S14E033ZRy/c4771ziAEY6vfPOOyn9P/HEE5s9/7bbbkuem5WVtdlwZXEU/Yy6+OKLk/cvueSSYn+/z58/f4MgbuvWrUv0/T5hwoSUrSirVauWePnll4t9/apVqxIXXXRRSg9NmzZNLFq0qEQ9VK9ePWWMfv36bTHoVNjQoUM32Oa1f//+xb4+kUgNgv3mN79JdOvWLRERiU6dOpV628vCgZTDDjss8Ytf/CIR8VNgbkuB6cI+/vjjRMuWLVN6POGEE0rVU+HwU0k/Owory+83c+fOTTRp0iTl+sMPP3yTob+NeeONNzYIPx966KGJgoKCYo9RNAh2/PHHJ78PhgwZUuxxZs2alRLIj4jEqaeeWuzrt7aCgoJEo0aNkr3Wq1evRNtrXnLJJSmPdfLkyRucs3LlykS1atWS5/Tt27dEPRYOTNaqVWuTwfGN2VaCYFOmTEl5DiIi8ec//zlt/QAAwI5AEAwAAIAKtzWCYIVXTcrOzk58/fXXJbp+ypQpiVq1aiXHaNKkySZX49icYcOGpTzWI488skTXbwtBsAsvvDDl2ssuu6xEf1ROJH5aKafoH4Q//PDDYl1b9I+XV155ZYnmXu+CCy5IGeemm24q9rXlGQTr379/ylhPP/10qcZ57bXXEllZWclx9txzz2JfW/j90LRp00SzZs2SgZuSvraJxIYrfJTkuS0oKEj06tUr5fq77767xD3k5+cnevfunTLO448/XqxrP/jgg0SlSpWS17Vr1y4xe/bsEvcwcODAlPlLulJbOp199tnJvmvXrr3F4NXMmTNTVnC78cYbyzR/0c+o9bf/+7//K/FYq1ev3mCVtpL0d8YZZ5TqfVTUpZdemjLOVVddVez+C6+4FhGJCy+8sFQ9fPbZZ4natWuX+jOn8HXrV6raY489NrlaYHEU/kxf/31XtWrVUv0uMHHixOQKZetvpVmNb1sIgh177LEp1x533HGbXHVrc6ZOnZpo3rx5yli33XZbsa8v/Fysfx9Wq1YtMWLEiBL3MmfOnJTgc3Z29hZXVUunoitufvHFF8W+tk2bNsnrdtttt02ed8wxxyTPq1OnTrHDXHPmzEnp7eijjy52b4nEthMESyQSiVtvvXWDz/pjjz02MX369LT2BQAA26vsAAAAgAw3ePDgePbZZ5P1eeedFx07dizRGGeeeWYsX748IiIqVaoUTz75ZHTo0KHEvZx++ulx5plnJus333wzxo8fX+Jx0uX111+PBx54IFkffvjhMWjQoMjKyirRODVr1oxhw4ZF1apVk8fuuOOOLV43YsSIGDJkSLI+7LDD4rbbbivR3Ovdd999se+++ybrm2++OVasWFGqsUpr2bJl8dRTTyXrE088MU466aRSjXXMMcdEv379kvXXX39dqvfWjz/+GHPmzIlDDz007r777hK/thER99xzT1SvXj1ZP/zww8W+dsiQIfHuu+8m67PPPjsuvfTSEveQk5MTTz31VOyyyy7JY9dee+0Wr1u1alWceeaZsW7duoj46b363HPPRbNmzUrcwx//+Mf4+c9/nqwfffTRWLBgQYnH2dry8vJSPjP79u2b8npuzM477xw9evRI1sOGDSv3vvr16xc33HBDia+rUqVKPPvss1G/fv3ksVtuuSVmzZq1xWtXr14dL7zwQrLu3r17nHbaaSXuISLiH//4R8rPjWHDhkVBQcEWr7vhhhtizJgxybpPnz5x3333laqHfffdN1588cXIzv5//9n3wgsvjHnz5pV4rCVLlkTlypXjySefjMaNG5eqn6LWf9899NBD0bNnzxJf3759+3jkkUdSjl1xxRWRSCTKobut56GHHopXX301We+3337x9NNPR+XKlUs8Vtu2bePtt9+OmjVrJo8NGDAgvv766xKPtf59eN9996V8vxdX06ZN429/+1uyLigo2OD12pb06tUrpR4xYkSxrps0aVJMmzYtWR933HGbPLd3797J+0uXLo0PPvigWHO89957KXXRXjPJ1VdfHX/6059Sjr366qvRrl27uPLKK2PmzJlp6gwAALZPgmAAAABktAceeCAuuuiiZN2uXbu49dZbSzTG66+/Hp9++mmy/u1vf1umP7jdeOONKX+E/+c//1nqsba2wiGM6tWrx5AhQ1IeS0l07NgxTj/99GT9wgsvbPGPfbfffnvyfnZ2dgwaNKjU81eqVCn+/ve/J+tly5bF22+/XaqxSmvMmDGxcuXKZP2rX/2qTOOdf/75KfUbb7xRqnGqVKkSDzzwQFSqVKlU1zdo0CBOPPHEZP3tt9/G1KlTi3Vt4de4Vq1acfPNN5eqh4ifQlw33nhjsp46dWqMHTt2s9c88sgj8f333yfrv/3tbyUOjq6XnZ0df/3rX5N1Xl5eDB48uFRjbU0vvvhiLF26NFkXDq9uzhlnnJG8P3ny5Bg1alS59dS4ceO49957S3198+bN46qrrkrWK1euLFZAcfr06SkB0V/84hel7qFKlSpxySWXJOsff/wxxo0bt9lrFi9eHHfffXeyrlu3btx///2l/tyL+CkwcvHFFyfr3NzcuOeee0o11vnnnx977713qXvZmOOPPz7OOuusUl9/4oknxiGHHJKsv/rqqxg5cmR5tLZVrFu3LgYOHJisc3JyYvDgwVGtWrVSj9mhQ4e4/vrrk/WaNWvilltuKdVYhx56aJx99tml7uWMM85ICZb+97//LfVYFa3o73rFfR+99tprKfWxxx67yXMLB8E2du2mFO0lk4NgERE33XRT3HfffSmBxby8vBg0aFC0adMmfvnLX8bLL78c+fn5aewSAAC2D4JgAAAAZKQPPvggevfuHRdddFFyhZEWLVrEK6+8EvXq1SvRWP/4xz+S92vVqhUDBgwoU29t2rSJo48+Olm/+eabZRpva3n//fdTAnGXXXZZNG/evExjFg4jrFu3Lt55551Nnjt9+vSUP5Ceeuqp8bOf/axM8/fo0SPlMZQ2OFVaK1asiD333DN569SpU5nGO/jgg1MCIt98802pxunfv3/stttuZeqlaGCm8IpGm/L++++nrGJ26aWXxk477VSmPvr27RtVqlRJ1pt7jQsKCmLQoEHJumXLlinv0dL4+c9/nhIky4Tv98ceeyx5f+eddy52wKBv374pq/wNHTq03Hq6+uqro0GDBmUa43e/+13KqmDFWbVs4cKFKXWjRo3K1MP++++fUm8p/PrAAw8kV6OMiLj++uujadOmZeoh4qfQReFVvP71r3/FqlWrSjRGVlZWXHPNNWXupaibbrqpzGMUDoBGVMwKdRXlmWeeienTpyfr3/zmN2X+WRcRcfnll8eee+6ZrIcPH16sVfGKKryiV2nUqVMnZaXEsWPHbrMrtnXs2DGaNGmSrN9///1i9Vr4d5XatWunPN6i2rZtG+3bt9/otZtTeEWwOnXqRNeuXYt13bbs4osvjrFjx8YRRxyRcnzt2rXx/PPPx/HHHx9NmjSJX/3qV/H000+nBJYBAIDiEwQDAABgq5s/f37MnDmzWLfvvvsuxowZEyNHjoyHHnooLr744mjfvn0ccsgh8frrryfHPPDAA+Ozzz4rcbhlypQpKeGkk046qVy2wDr00EOT96dNmxZz5swp85gV7f7770+pC6+0Vlr77LNP1K1bN1l/+OGHmzx36NChKduolXX1rIifggyF/0D73XfflXnMkjjmmGNi/PjxyVtZw1eVK1dOCaqUZru3iIhzzjmnTH1ERHTu3Dml/vLLL7d4zaOPPppSl8drXLt27ZQ/kG/uNf7f//4XU6ZMSdbnnHNOSrCptAp/v3/22Wexdu3aMo9ZUebNm5eyQs9pp51W7NWn6tWrl7LyzZNPPpkM4pbVL3/5yzKPUatWrejTp0+ynjx5cowePXqz1zRs2DClLrxaXGnstddeMWbMmOTtoIMO2uz5hT93a9WqFeeee26Z5l+vTp06KWMtXLgwZZva4jj44IOjZcuW5dJPYYXDSqXVs2fPlN6eeeaZjFlJ6F//+lfyflZWVlx22WXlMm5OTk7KNrv5+fklXqGwffv2ccABB5S5l8I/H5YtW1bsFSPTofAWpbm5ufHVV19t9vzly5fH+++/n6yPOOKIlDDyxhReFezrr79OCQJuzMKFC1O29jzkkENKvYLntmbXXXeNN998M0aMGJGyst96ixcvjsceeyxOOeWUaNKkSfTp0yeGDRsmFAYAACUgCAYAAMBWd8opp8Quu+xSrNuuu+4aXbt2jZ49e8YFF1wQ999/f0yePDk5VqtWreLBBx+MDz74IJo1a1biXoquUHXSSSeV+fFFxAZbaX3xxRflMm5FKvxcdOvWLVq3bl3mMbOzs1P+ILy55+GDDz5I3m/YsGEcfvjhZZ4/IlJW15k7d265jJlOhbfcWrJkSanGKOsqXBERe+yxR2RlZSXrH3/8cYvXFH6N99prr5RVUsqiuK/x1vh+X7FiRcpn1LbmySefTAmqFXdbyPUKb/c6b968clsBrSxbIRZWNFC2ufBpxE8/Q2rVqpWsn3rqqTIFiqpUqRJdunRJ3gqvUFbUd999lxI8O+2006J27dqlnruoCy+8MOV7dHMrMm5M27Zty62XitC3b9/k/cWLF6cEZ7ZVeXl58fHHHyfrww8/vFyf5zPOOCPlPVTS17w8fjZExAaf7cX5+ZAuRVdEHDFixGbPf/vtt2PNmjXJenPbQm7qnC2tCvbee++lrEyW6dtCbkyPHj3ivffeiy+++CIuvPDCjX72rV69Ol566aU488wzo1mzZnHBBRdscftnAABAEAwAAIAM1rZt27j33nujf//+KX/sLomRI0em1AceeGB5tLbB9mILFiwol3EryjfffJPyh9ryeh4iUp+LTT0PiUQiZVvKfffdN3Jycspl/muvvTamTJkSU6ZMiRdffLFcxtxWpHO7rZycnKhRo0ay3tJqHYsWLUoJSJXHqjPrPfDAA8nX+L777tvkeYW/3+vWrVsuKxNFZNb3e+FtIX/2s5/FXnvtVaLrjzvuuJRV/gqPty3o1atXys+DLa1UV7Vq1ZRVxKZOnRp/+MMfKqq9FIVXFYqIOOqoo8p1/NatW6cEcorOl+kKr8QXERkREPn0009TQkTl/ZrXqlUrDj744GT92Wefpcy3tdSpUyel3pZXcyoasir6e2FRhUNcWVlZKat9bcohhxySEnQqThBscz1uT/bee++4//7748cff4xnn302zjrrrI1uE7xy5cp46KGHokuXLnH44YfH559/noZuAQAgMwiCAQAAkLG+++67OO6446JNmzZx7733lmqLsk8++SR5v3nz5ptdvaUkiv4RdNGiReUybkUp/DxERHTq1Kncxi78XGzqefjuu+9SvlZ0RbWyaNCgQey2226x2267RatWrcptXFJf2y2tTvbFF1+kBNfK8zVu0qRJ8jVu3rz5Rs9Zt25dyh+OyysEFpE53++TJk1KeQ5KuhpYxE/BqcIrMb344ouxfPnycumvPNSqVStly8AxY8Zs8ZobbrghZaW9u+66K04++eSYPXt2hfS4XuGVoSLKNxy5sTGnTZu2Ta/MVFJFf04VZ3vadNvar3leXl5aViQt+plY2tUrt4Z27dqlrChbdDWuogpvS77PPvukrEi5KZUrV05Z5fSdd96J1atXb/L8wmG0evXqRZcuXbY4R6arUaNG/PKXv4xHH3005s6dG2+++Wacf/75GwStI37a5nm//faL0047rdRbZAMAwPZMEAwAAICt7t13341EIlHs27p16yI3NzemTJkSzzzzTFxxxRXRpEmT5HizZs2K3/72t3H44YfH/PnzS9RL4W3kZs+eHVlZWeVya9OmTco82/JqGBEbbqd3wQUXlNtzMWTIkOS4m3oeir5uu+22W/k/yG1cfn5+LFiwIGbOnLnZW2kCjxWlSpUqyfub+6N2RPpf49zc3JQt/z766KNye48XXa1lW/1+L7x6V3Z2dso2jyVxxhlnJO+vXLkynnvuuTL3Vp4KB4SmTZu2xfN33XXXGDJkSFSuXDl57JlnnonWrVvHmWeeGa+//nqFrKpUOGjWqFGjTYYYy6Loim9z5swp9znSpei2nsV5rdOtaLiwpCvyFce28JoX/tkQseWfD+nWs2fP5P0FCxbEhAkTNnreuHHjYubMmcm6ONtCbuzclStXbnILyiVLlqSsbvfzn/+83LbOzRQ5OTlxxBFHxIMPPhhz5syJ559/Po466qiU1R4TiUQ8+eST8bOf/SxeffXVNHYLAADbnh3r/0EAAACQkbKzs6N+/fqx2267Rd++feOOO+6IH374If75z39GzZo1k+eNGDEievfuHatWrSrWuHl5ebFy5cqKajtFQUHBVpmntBYuXLhV5tnUKhtFV1AqvPXc9mjGjBlx1113xVlnnRV77rln1KxZM6pUqRKNGzeOXXbZZbO3wn+EziTpfo231ns8Ytv8fk8kEjFs2LBk3aNHj2jRokWpxurZs2dKaGno0KFl7q88FQ4KL1u2rFhbqJ588snx3//+N9q2bZs8lp+fH8OGDYvevXtH48aN47jjjou///3vMWrUqHIJZObm5ibvN2zYsMzjbUzRcQvPmemysrKicePGyXpbDWAWVvj5r1q1asrvMOVle37NK0pxt4csuqVjSYJgxxxzTEq9qfDSBx98kPIzZHveFrI4cnJy4oQTTog33ngjJk2aFP369UsJhM2bNy9+8YtfxMMPP5zGLgEAYNsiCAYAAEBGqlq1avzmN7+J0aNHpwQSPv/88xgwYECxxvDH0f8n3c/F4sWLU+qi20ptL95444049NBDo1WrVnH55ZfH0KFDY8KECVstkJhO6X6N0/0eT7f3338/pk+fnqxLsy3ketnZ2XHaaacl63feeWebWmmqdu3ayfsFBQXF3rqyV69eMX78+Pj73/8eu+yyS8rXli5dGq+++mpcc801sd9++0XDhg2jT58+8eijj5Y6gFQ4nFhe2xIXVTQUtDUDkVtD4dd6W95+cD2v+bap8IpgEbHJ1boKB8F22mmn6NatW7HnaN68ecqWyIW3mCysaAitaG87sj322COeeOKJ+Pzzz1O2d04kEnH++efH8OHD09gdAABsO3LS3QAAAACURbt27eL111+P7t27J1cCu/fee+PKK6/c4mo3Rbf6uuKKK+LKK6+skD639WBT0edixowZW3X+ottGFd6ibXswY8aMuPjii3fo7YvS/RoXfY/fcccdcfLJJ1fIXA0aNKiQccui8LaQ1apVi5NOOqlM451xxhlx++23R0TEunXr4oknnqiwz8+SKhwOivgpxFX02KZUr149/vCHP8QVV1wRr732WjzzzDPx8ssvbxBkXLJkSbz00kvx0ksvRbVq1eLUU0+Na665Jjp06FDsPguvXlm1atViX1cS1apVS6m3t9Bp4Z+tmbAimNd827T77rvHzjvvHLNmzYqIiPfee2+DcxYvXhwff/xxsu7du3fKylTF0bt37xgzZkxERHz77bfxzTffxB577JFyTuG5GzRoEJ07dy7RHDuCrl27xujRo+Pss8+OJ554IiJ+Cv1ecsklcdhhh0WjRo3S3CEAAKSXIBgAAAAZr3PnznHFFVfETTfdFBE/BT6GDh0af/zjHzd7XaVKlVLqatWqlXqrtExX9Llo0qRJVKlSZavNX/QP4vn5+Vtt7or25ZdfRu/evTdYMalatWrRp0+fOOyww2KfffaJnXfeOerVq7fFcEDr1q1TVnbKFOl+jYu+x2vWrLnDfL/n5eXF008/nVKX99acjz322DYTBMvOTt0EoThbQxaVk5MTxx9/fBx//PGxbt26GDNmTLz//vvx3nvvxciRI1O2Os3Ly4shQ4bEo48+Guecc0784x//iHr16m1xjurVq6eMURGKbpVco0aNCplnW1Ca13lr85pvu3r16pXc5nbu3LkxadKkaN++ffLrb775ZqxduzZZl2RbyPV69+4dAwcOTNavvfZaShBsxYoVMXr06GTdo0ePDT7P+EnVqlXjscceixUrVsRLL70UET+t/HnDDTfEPffck+buAAAgvfy/CAAAALYLV155Zcofyza15U5hRf9QX3TFlx1Jup+LovNnwhZfxTFt2rTo2bNnSgisSpUqcfXVV8ecOXPiySefjPPPPz+6du0aO+20U4WtELMtSPdrnO73eDq9/PLLFf58f/nllzFhwoQKnaO4iq4MVdYVGStVqhTdunWLK664Ip5//vlYsGBBfP755/HHP/4xWrdunTwvkUjEv//97+jUqVOMHz9+i+MWXjmucLCsPBUdd1tcra4sCr/W2/rKmxGpz39FfQZt7695RenVq1dKXXSLxsLbQlauXDmOPPLIEs/RvXv3lK07C48ZEfHRRx+lhM2K9kSqSpUqxYMPPpjy8/2pp56KgoKC9DUFAADbAEEwAAAAtgsNGzaM/fffP1l/+eWXW7ymdu3aKdvTVdQf4jNB4T9MRmz956J+/fopdSZs8bUlBQUFccYZZ6QEcJo3bx6ffPJJ3HrrrcVaMWh7ku7XON3v8XQqvC3k9jDPlixbtix5Pzs7u9jbQhZXdnZ27LPPPnHzzTfHt99+G8OGDYtWrVolvz5r1qzo0aNHTJkyZbPjFH5P5ubmlmuP6y1cuHCTc24PCn+OlPcqdxWh8PO/evXqWLFiRbnPsb2/5hWlZ8+eKfWIESOS9xOJRLzxxhvJ+uc//3mpPleys7PjqKOOStYjR45MeQ8UDZ8V7YkN7bTTTnH66acn63nz5sUnn3ySxo4AACD9BMEAAADYbnTo0CF5f+nSpbF8+fItXtOoUaPk/UmTJlVIX5mg8PMQsfWfi8aNG6fUWwpQZIL//ve/8fHHHyfrBg0axIcffhh77713GrtKn3S/xkXDEDvK9/uCBQtSAgyXXHJJzJgxo9xuv/jFL5JjP/7449vE9nw//vhj8n6dOnUiKyurwuaqVKlSnH766TF27NiUFYJyc3Pj3HPP3ey1zZo1S95fsGDBBtvHloexY8em1E2bNi33OdKloKAg5s6dm6wzIVxb+DWPiBg3bly5z7E9v+YVqW3bttGyZctkXfjn94QJE1Lea6XZFnJj165ZsyY++uijjc7ZqFGj6NSpU6nnSbd+/frFwQcfHAcffHBcd911FTpX7969U+rvvvuuQucDAIBtnSAYAAAA240mTZqk1MXZCm2vvfZK3v/qq69i5cqV5d5XJij8PETEVl9NoW3btil/xC/Oim7buiFDhqTU99xzT8o2cjuarl27pgRytvZrXLVq1Wjfvn2y/vTTT7fq/Ony5JNPRn5+frI+55xzokWLFuV2O/PMM5Nj//DDD/Hee++l42GmKByu2X333bfKnHXr1o0XXngh9txzz+Sx999/PyXYUVT37t1T6or43C08ZsuWLTcIImWyb775JlatWpWst9ZrXRZb+zWvUqXKDhs+Lo3CWzFOnz49uXJk0Z8Xxx13XKnnOOqoo1K2Mh81alRE/LTq2OjRo5PHe/bsWaEh1oo2adKk+PDDD+PDDz/cYKWz8lY4wBcRFRKqBQCATCIIBgAAwHajatWqKXXh8MOm9OjRI3l/3bp18f7775d7X5lgn332iVq1aiXrwlsibQ1ZWVkpfyAfNWpUrF27tlzGHjt2bAwdOjSGDh0aL7zwQrmMWRyFg05NmzaNU045ZavNvS2qX79+tGvXLlkXXgWlrD788MPka/z2229v8rzC3+9z5syJyZMnl1sP26rC2zXusccesc8++5Tr+Mcdd1zUrFlzo/OlQ25ubsycOTNZd+vWbavNXb169bj11ltTjm3uM+eQQw5Jqf/73/+Waz8zZsyIiRMnbnK+TDdmzJiUurzf2xVh//33T9mSurxf85UrV8YHH3yQrPfdd9+oVq1auc6xPSu6FeP6n+OFg2C77757mUKHRbcyXx8E+/bbb1P+AUOmbwtZOJz1ww8/VOhcBQUFm60BAGBHIwgGAADADq3oH9oefvjh9DSSZjk5OXHQQQcl608++SQlQLA1HHzwwcn7CxcujP/973/lMu4DDzwQZ511Vpx11lnx17/+tVzGLI7CYZS99947cnJyyjzmihUrIjc3t8zjpEvh13jcuHHlFsQaOHBg8jX+17/+tcnzdrTv92+++SY+++yzZH3aaaeV+xw1atRI2R7ymWeeidWrV5f7PMX18ssvp9SbCwctWbIkRowYkbwV3lKytI466qioUqVKsp42bdomz91tt91il112SdZPPPFErFixosw9rDd48OCUQETh1Y62B88//3xKnQlBsBo1aqSEnt96662YPn16uY0/fPjwlDDR9vaaV7Siz9fGgmBl2RZyY2N8/vnnKf+7qV4yTZcuXZL3p02bFhMmTKiwuYp+D+20004VNhcAAGQCQTAAAAB2aPvvv3/KdnEvvPDCDrulTP/+/VPq++67b6vOf+aZZ6Zsl/Too4+Wy7hTpkxJ3m/RokWxrincR8RPWzaVRd26dct0/XqDBw+OZcuWlctY6fDrX/86pd7ar/EvfvGLaNCgQbJ+5JFHUraW294MHTo0pa6IIFhERL9+/ZL3lyxZskEYqzgKv4ZlMXz48OT97OzsOOqoozZ57syZM6NXr17J27Bhw8o8f05OTsp7bEvfrxdeeGHy/tKlSzfYUra0Vq5cGYMHD07W9erVS3md0qk8goLLli2LV155JVnvvvvusdtuuxX7+sKf8WX9fC+pwq95QUFB3HvvveUybkFBQfzzn/9M1pUqVYrzzjuvXMbeUbRq1SratGmTrMeMGRMrVqyI8ePHJ4+VZVvI9Xr37p28P3PmzPjxxx9TtoXcaaedomPHjmWeJ52KfvaW18/7jXnppZdS6qLbnQMAwI5GEAwAAIDtRlZWVqmuueqqq5L1mjVr4oorrijPtjLGySefHK1atUrW999/f3z11Vdbbf5WrVql/HF0+PDh8fXXX5dpzNzc3Bg5cmSyPuCAA4p1XeFtMiOiVKv0NG7cOHl/1qxZJb6+qJkzZ8b1119f5nHS6eCDD45OnTol63vuuSfmzZtXpjHHjx8f3377bbLe3Gtcs2bNuPjii5P1vHnz4oYbbijT/NuqRCKREgTr2rVrytac5emYY45JCTsWDaAVx3XXXVfmQM64ceNStto78sgjNxsMbNmyZUogaNKkSWWaPyJi1apVMX/+/GTdrFmzzZ5/0UUXRY0aNZL1tddem3J9aV1//fUxe/bsZH3BBRekbOGZTnfddVeZx7jzzjtTQpxnn312ia4v/BlfnquwFccpp5wSO++8c7K+6667ymUFzvvvvz+++OKLZN23b9+Un+kUT+GVuL788sv4/PPPY926dRERUbt27XLZYnXvvfeO5s2bJ+tRo0alrAiW6dtCRkQceOCBKT9z7rzzzjL/Trcxs2fPjqeeeipZt2jRImU1MgAA2BEJggEAALDdqFatWkq9cuXKYl131llnpWzPNXz48FKtaFPU8uXLt/ofmMuiUqVKcfXVVyfrtWvXxgUXXBBr1qwp89hz584t1nlXXnll8v66deviiiuuKFM45Prrr4/8/PyI+Cn0V9wVkerXr59Sz5gxo8RzFw48ffrppynbdZXUsmXLom/fvrF48eKU44W3fcsUhYOXy5YtiwEDBpRpvMLX16xZM44//vjNnn/ppZdG7dq1k/Xtt9+eEp4orQULFmxTr8eHH36Ysi1hRa0GFhFRpUqVOPHEE5P166+/XuItTD/++OO44447ytTHVVddlfIabGk1pNq1a0ePHj2S9bPPPlvmFeKefPLJZGgkIqJz586bPb9hw4ZxySWXJOvc3Nz4zW9+U6bPvU8++SQGDRqUrOvUqROXXXZZqccrbzfccEOZtombPXt2/P3vf0/WOTk5G6w2uCWFP+NL8/leFpUrV44//elPyXrNmjVx3nnnleln7dSpU1PGzMnJiT/+8Y9l6nNHVTiENXHixHjvvfeS9RFHHJGy9WtZHHPMMcn7n332WYwZM2ajPWSqrKyslPD66tWr47TTTiuXoOt669ati/79+6esvHjJJZeU6h+GAADA9kQQDAAAgO1G0e33Fi1aVKzrqlatGo8++mjKyjD9+vWLDz/8sNS9TJ06NQ444ICMW23o4osvjsMPPzxZf/LJJ3H66aenBBtK6pZbbokOHToUa8vNXr16pWxR+dZbb6WE00riySefTNly61e/+lWxV0dp1apVyio9pXkvHHnkkcn7a9asiVtuuaXEY0T8tJrYkUceGZ999lnUrVs3JcCQidtE/vrXv05ZcWXw4MGl3ob073//e8qWUL///e9TXreN2WmnnVLeF2vXro1jjjkmJk+eXKoeIiJGjx4dXbt2jfvvv3+L5z7yyCORlZWVvI0YMaLU827OY489lryflZVV4dsCFh5/zZo1KSu0FNc111wTzz77bKnmv/HGG+Ptt99O1gceeGD88pe/3OJ1F110UfL+okWL4ne/+12p5o/4adW+wp9X2dnZccopp2zxur/+9a+x5557Juunn346Lr/88lL18NVXX8Wxxx4ba9euTR675557UlagSreVK1fGcccdV6oA1ooVK+KEE06I5cuXJ49dccUVKasrFUeHDh2S9+fNm5eyquDWcMkll6T8rP3oo4+iX79+pfpZO2vWrDj88MNj6dKlyWPXXntt7L333uXS69YyYsSIlM/GRx55JC19FP75tHbt2pTtNstjW8j1Cq+A+u9//zvl9SvcQybr169fSjj7q6++iv322y/GjRtX5rHz8vKib9++8dZbbyWPtW3bttSfnQAAsD0RBAMAAGC70bJly5S6JFvQ9OzZM2U1jZUrV0bv3r1j2LBhJeph5cqV8Y9//CO6desW48ePj0GDBlXIVjgVJSsrKx599NGUbQ2fffbZOOGEE4oV5Crs888/j6OOOir+9Kc/xaJFi1JW+9qcO+64I2U7tX/84x9x1VVXRV5eXrGuX7t2bQwcODDOOOOM5OpATZs2LdFqQ9nZ2bHvvvsm648++ihl26biOPPMM6NOnTrJ+u9//3s88cQTxb6+oKAgHn300ejSpUt88sknkZWVFQ8//HDK+7wsq4ylS1ZWVgwePDglsHXZZZfF3//+92KHIFasWBGXXXZZXHPNNcljnTp1ij//+c/Fuv6ss86KM844I1nPmzcvDj300JRtBYtj0aJF8Ze//CUOPvjgmDFjRgwYMKDYq99VpNWrV6cEsQ455JDNbpFYHg477LBo1KhRsi4cRNuSFi1axAknnBDr1q2LU089NW699dZivxcKCgri5ptvjuuuuy55LCcnJ+6///5irQpzyimnpIQ2H3rooTjrrLNSQhnF8eWXX8bBBx8cCxYsSB676KKLihVQqlatWjz++ONRtWrV5LG77747fvWrX5VoZbXnn38+Dj/88JRrTjnllPjVr35V7DG2hl122SWmTZsWBxxwQLz//vvFvm7OnDlx/PHHx6hRo5LHWrZsmfLaF1f37t1T6vLYrrIksrKyYsiQIdGwYcPkseeff77EAbn33nsvfv7zn8f333+fPHbAAQeUeaXFHVmLFi1it912S9brty/OyspKWcWrrI444oioXLlyRETK71fNmjWrsG180+HRRx+Nrl27Juvvv/8+unXrFpdeemmpVwd79913Y5999okXX3wxeaxmzZrx9NNPR/Xq1cvcMwAAZDpBMAAAALYbhVdUiYiU7XyK44YbbkhZ1Wbp0qVx5plnxpFHHhkvv/xyrF69eqPXrVu3Lj788MMYMGBAtG3bNv7whz8kt/DLzs6OmTNnluyBpFmzZs3ipZdeStk+75VXXokOHTrEwIEDY+rUqZu89scff4xHHnkkjj322Nh3333jzTffTH5t7ty5xdo6r379+vH888+nBIXuuOOO6NKlSzz88MObXOlt+fLl8fDDD0eXLl3iL3/5S3Kuxo0bx5tvvhkNGjTY4tyFnX766cn7iUQi+vbtW6ItBOvXr58STCooKIjTTz89LrzwwpQt+4qaOXNm3HnnndG5c+f49a9/HQsWLIjs7Ox44IEH4pe//GXUq1cveW4mBsEiflq14/HHH49KlSpFxE/fQ9dcc00ceOCBMXz48E1uqZqbmxt33nlndOzYMe65557k8d122y1ef/31Em3Z9eCDD6ZsCzh79uw4+uijo1+/fvG///1vk0Gk1atXx1tvvRVXXHFFtG7dOgYOHJgMKSYSiRIHJivCK6+8krKNaEVuC7leTk5O9O3bN1l/9NFHm32fF9aqVav497//He3bt49169bFH//4x+jSpUs8+uijm1z1bvXq1fHSSy/FQQcdtEEA8JZbbomf/exnxe59yJAhKcGLoUOHRuvWrePPf/7zFleu+eKLL+Kiiy6Kbt26xfTp05PHO3ToELfeemuxe+jcuXMMHz48cnJykscee+yx6NChQ9x2220pYxeWn58fr7/+evTp0yd++ctfJkMrEREHH3xw/Oc//yl2D1vLM888EzVq1IhZs2ZFjx49ol+/fjFy5MhN/nyYM2dODBo0KPbcc8945513kserVKkSjz32WNSsWbPEPZx44okpgZF777037rjjjq26vWvz5s3j1VdfTflZ+8Ybb0THjh3j//7v/2LixIkbva6goCDee++96N+/f/Ts2TO+++675Nfat28fL7zwQvKzldLZ2NaM++yzTzRt2rTc5qhdu3YccsghxZq7PMycObPCbptTt27dePvtt+Ooo45KHsvPz49//vOf0bJlyzj11FPj5Zdf3mDr66J+/PHHePjhh6NHjx5x6KGHpmwvW69evXj11VdTAmcAALAjy9nyKQAAAJAZWrVqFe3atUtu8fbMM8/EHXfcEU2aNCnW9ZUqVYqhQ4dGkyZN4u67704ef+utt+Ktt96KOnXqRMeOHaNZs2ZRq1atmD9/fsybNy+mTp260UBOixYt4oknnoiDDz64fB7gVtS9e/cYOXJk9OnTJ7k6yZIlS+Ivf/lL/OUvf4k99tgjWrZsGU2bNo1Vq1bFvHnz4scff4xvv/02EonEBuNdeOGFcdddd6Vsv7k5+++/f7z55ptx/PHHJ1e3mTx5cpx77rlx0UUXRadOnaJZs2bRqFGjWL58efzwww/x5ZdfpmyHFhGxxx57xLPPPhudOnUq8XNw1llnxT/+8Y+YMmVKRET88MMPse+++0b37t1jt912i9WrV8cPP/wQvXv3jr/85S8bHePqq6+OUaNGpWx39+CDD8aDDz4Y7dq1iw4dOkTdunVj1apVkZubG19//fUGQaJ69erF0KFD49hjj42ISFnZKTc3N5YsWbLBtqiZoE+fPvHUU0/FmWeeGatWrYqIiM8++yz69esX1atXjz333DOaNWsW9evXj6VLl8bUqVNj/PjxG7y/9t1333juuedKvOJVjRo14rXXXov+/fvH008/nTw+fPjwGD58eDRq1CjatWsXzZo1i2rVqsW8efNi3rx58c0338TKlSs3GK9jx47x9NNPR8eOHUvxbJSvwqtx5eTkxEknnbRV5u3Xr1888MADyXro0KFx7bXXbvG6Vq1aRYMGDeKtt96KY445JsaPHx/jx4+PX//613HuuedGhw4dYtddd406derEihUrYs6cOTF+/PiNrto1YMCAuOqqq0rUd9OmTeOdd96J3r17x9ixYyPip9Xebr755rj55pujYcOG0alTp2jSpEnUrFkzVqxYEfPnz49x48ZtdMWurl27xhtvvBG1atUqUR99+vSJ119/PU455ZRk4HXevHlx9dVXx9VXXx3t27ePFi1aRNOmTWPlypUxZ86cmDRp0kbDsSeeeGIMHTp0i1ulpsN+++0Xr732WpxwwgmxePHi5Pdc3bp1o3PnztGsWbOoXr16zJ8/P2bNmhVfffXVBgGtqlWrxpNPPhk///nPS9VD3bp148orr4yBAwdGxE8hzquuuiruuuuuOOCAA6JKlSoxb968WLBgQYlXgyyJ/fffP957773o06dP/PDDDxHxU6j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      "text/plain": [
       "<Figure size 2400x1350 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wavelengths = np.arange(250, 601)\n",
    "absorbed = Get_Percentage_Absorbed(LambdaIn, LambdaOut, wavelengths)\n",
    "reflected = Get_Percentage_Reflected(wavelengths)\n",
    "absorbedWLS = Get_Percentage_Absorbed_for_WLS(LambdaIn, LambdaOut, wavelengths)\n",
    "\n",
    "fig, ax1 = plt.subplots()\n",
    "ax1.plot(wavelengths, reflected)\n",
    "ax1.fill_between(wavelengths, reflected, label = \"Reflected light\")\n",
    "ax1.plot(wavelengths, absorbed,  color = lps.colors[\"darkred\"])\n",
    "ax1.fill_between(wavelengths, absorbed, color = lps.colors[\"darkred\"], label = \"Absorbed light\")\n",
    "ax1.plot(wavelengths, absorbedWLS,  color = lps.colors[\"legend_orange\"])\n",
    "ax1.fill_between(wavelengths, absorbedWLS, color = lps.colors[\"legend_orange\"], label = \"Absorbed light for WLS\")\n",
    "\n",
    "# Set minor ticks locator\n",
    "minor_locator = ticker.MultipleLocator(0.2)  # Minor ticks every 0.2 units\n",
    "ax1.xaxis.set_minor_locator(minor_locator)\n",
    "ax1.yaxis.set_minor_locator(minor_locator)\n",
    "\n",
    "# Activate the minor ticks\n",
    "ax1.minorticks_on()\n",
    "\n",
    "\n",
    "ax1.set_xlabel('Wavelength in nm')\n",
    "ax1.set_ylabel('Ratio of light amount [%]')\n",
    "ax1.set_title('Reflectance, Absorption, WLS')\n",
    "#ax1.grid()\n",
    "ax1.legend(loc='center right', facecolor='white', framealpha=1)\n",
    "#ax1.set_legend_logo(position=\"lower left\")\n",
    "plt.savefig(\"/home/eric/sim/WWLegend/Plots/WLS/Reflectance_Absorption.png\", dpi=300, bbox_inches=\"tight\", pad_inches=0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now reproduce 2D histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_shifted(LambdaIn, LambdaOut):\n",
    "    ShiftedIn = LambdaIn[~((LambdaIn == LambdaOut) | (LambdaOut == 0))]\n",
    "    ShiftedOut = LambdaOut[~((LambdaIn == LambdaOut) | (LambdaOut == 0))]\n",
    "    return ShiftedIn, ShiftedOut"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/eric/.local/lib/python3.8/site-packages/numpy/lib/histograms.py:1065: RuntimeWarning: invalid value encountered in divide\n",
      "  hist /= s\n"
     ]
    },
    {
     "data": {
      "image/png": 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Jdddff33k5eXFL37xi2rNsWjRojj44IPjk08+iYiIQw45JH784x/HEUccEY0aNVrv6x966KH4zW9+kwT1lixZEieeeGJ8+OGH0aFDhyrPcPPNN68T+tpnn33i8ssvj6OPPnq9c3z++edx7733xh//+Mf45ptv4vLLL4+mTZuuE9DckLXBsfLefPPNtC1hb7311hg8ePB6r6/qNpulpaXRv3//mDx5ckREHHvssXHRRRfFwQcfnLaK3lqzZ8+O2267Le64444kqDh79uw46aST4p133lnvM6kNK1eujMMPPzzeeeed5Fy7du3iqquuijPOOGODv2c+++yzGDp0aNx5553J/O+++24cfvjh8dprr0XLli2rNU8uPMfOnTuv9+frpz/9aQwfPjyp1/eatco/n+HDh6dtCVz+PmsNHjw4br311vX2Wt/vEgAAAABqWQoAAIAa+dvf/paKiOTrkksuqfS1q1atSrVq1Sq5dt99913v6x544IG0e/ztb3+r9D1Gjx6ddu0FF1xQ6WtTqVTqxBNPTLt+0KBBqUWLFlX6+hkzZqT23nvvtB4nnHDCJq9buXJlqn379sk1++yzT5XmXp9FixalmjZtmvT8/ve/X6nrzjzzzLT5d9ttt9SUKVMqde2qVatSF154Ydr1ffr0Sa1YsaJS13fp0iW57qCDDqrUNWv9+9//TuXn5yfXN23aNDVs2LBKX//KK6+kmjdvnlxfUFCQGj16dJXn/tWvfpU65phjkhkefvjhSs8wa9asVJ8+fdKe34knnljp69caO3ZsqqCgIK3PVVddlVq1alWlrv/888+TOQoKClK33HJLWq/K/jykUqnUa6+9lnbtgw8+WOX3k0qlUlOmTEnrc91116UOO+ywVESkiouLU6+88kqle7311lup4uLitH433nhjteaqjmuvvTbt3nvuuWfqyy+/rPT1kyZNSvXo0SOtx/nnn1+pa+vbc6zJ3/lUKpU644wz0u5fU+V7nXHGGTXuBwAAAEDm5FcrLQYAAEDigAMOSFsBpuK2ihvzxhtvxFdffZXUG1pF6Mgjj4y8vLykLr9K2KZUnKd///5VuvbJJ59M6mOOOSaeeuqpaNWqVaV7bLPNNvHyyy+nbXf21FNPpa3ssz4VV+N66623ktV3quvpp59O236xMts8Pvnkk/HQQw8l9X777Revv/56bLfddpW6Z2FhYdx5551x3nnnJecmTJgQt9xyS6Xnro7S0tI47bTTYs2aNRERscUWW8SIESPi5JNPrnSPww8/PP7xj38kP99lZWVx1llnpa0eVhnPPvts/PWvf42mTZvGyy+/HKeffnqlr916663jH//4R7Rt2zY5N3z48LQt/irjf/7nf9K2jrz00kvjN7/5TaVXKdphhx3iP//5T+y3335RVlYWV155ZZXuXxeGDRsWI0aMiE6dOsXo0aPj8MMPr/S1e++9dzz11FNpv2fuvPPOtGdWWxYvXhy///3vk3qrrbaKf/7zn7HllltWukePHj1i5MiRadvI/vnPf05bqbCycvU5AgAAALD5EfwCAACooVatWsXuu++e1O+//34sWLCgUtf+4x//SKu/973vrfd1HTt2jD322GOD123M66+/nlZXJfh13333JcdNmjSJe++9N/Lzq/7/SrZu3Tpuv/32tHPlA2UbctZZZ6XVjzzySJXvXd5f/vKX5Lhjx45xxBFHbPT1c+bMifPPPz+pt9pqq3jmmWeqtX3cbbfdFt26dUvqP/3pT7Fq1aoq96msCy+8MGbNmpXUQ4cOjf3337/KfQ444IC46qqrkvrjjz9OtuCsrLVbod51111x0EEHVXmGjh07xq9//eukXrNmTVoYb1OGDx8e//3vf5N6v/32i5tuuqnKc7Ro0SL+9re/RZcuXWL16tVVvr62ffbZZ9G0adP429/+FjvuuGOVr+/fv3+cdtppST179ux45ZVXMjnier3wwgvxzTffJPV1112XFvSrrA4dOqT9XKRSqbS/85WVq88RAAAAgM2P4BcAAEAGDBgwIDlOpVLrhK02pPzKXdtss03stttuG3ztUUcdlRxPnTo1Jk2atMn+ZWVl8cYbbyR1z549q7SKTvlrjzjiiOjQoUOlr63o8MMPjy5duiT1yy+/vMlrevfuHXvuuWdS/+Uvf6nyalNrTZ8+PW31s9NPP32Tqz394Q9/SFuR7a677qrS8yuvWbNmcfXVVyf1nDlz4plnnqlWr02ZNGlSDB8+PKmPPfbYKq2yVdEVV1yRFna74447qtzj4IMPrtQKaxtyyimnxBZbbJHUVQnSVJz3d7/7XdoqfVXRpk2bKoXO6to111yTFkStqnPPPTetfvXVV2s60iZV/F129NFHV7vX/vvvn/Y745///Ge1+uTicwQAAABg8yP4BQAAkAEVV9GqzHaPM2fOjPfffz+pywe71qfiNpCV2e5xwoQJ8fXXX29wzk1p06ZN9OrVK3r16hUHHHBAla5dnwMPPDA5ruy2jeXDQlOnTq10qK6iYcOGpYXGNhVCWrJkSfz5z39O6r333juOO+64at17rZNOOinatGmT1NUNpWzKLbfckrzX/Pz8uPHGG2vUr6ioKE499dSkHjVqVKxcubJKPcqv2FUdLVu2TPv5ee+99yoVApw+fXr85z//SerDDjss+vXrV6NZ+vfvX6NwUm3p0KFDXHbZZTXqsf/++6dt5bp2tbbaVFpamla3b9++Rv323nvv5LiqW4JG5O5zBAAAAGDzI/gFAACQAQcccEDa6lGVCX5VDG5taJvHtb7zne9EcXFxUldmu72Kc5Rfmawy3n333fjggw/igw8+iEsvvbRK167PVlttlRyvXLkyFi1atMlrTj755GjSpElSP/zww9W696OPPpoc77PPPtG9e/eNvv7xxx9Pm++HP/xhte5bXuPGjWO//fZL6vIrqmXKkiVLYtiwYUl94IEHRq9evWrc9+CDD06Oly9fHu+++26lr+3evXvsu+++NZ6hd+/eyfHixYvj888/3+Q1Tz75ZFpArPwWfDVRfuvV+uLUU09N+7tSXeVXHpw4cWKN+21Ku3bt0uqpU6fWqN+1114b48ePj/Hjx1drpa1cfY4AAAAAbH4EvwAAADKgqKgobXux9957b5OhpvLBr6ZNm8Yhhxyy0dfn5+fHEUcckdRvvPFG2mpe61M++JWXl1flFb8yrfxWfRGRto3ihrRp0yZtpa2nn346vvnmmyrd9913342PPvooqc8666xNXvPvf/87OW7UqFEce+yxVbrnhpTfPu7TTz+NpUuXZqTvWm+88UasWLEiqY8//viM9K247d24ceMqfW11t8esqGJY78svv9zkNf/973+T40aNGm0yYJnLioqKMtJnxx13TI4XLFhQ7e1VK6tiMPEvf/lLjfp17Ngx+vTpE3369Nno9rkbkqvPEQAAAIDNj+AXAABAhpRfTWvNmjVp28tVtHLlyrSVaPr37x/NmjXb5D3Kbwe5atWqGDFixAZfm0ql0kIvu+yyS423UMu0ygYhyge1Fi9eHM8991yV7lN+ta8tttgiTjzxxE1eUz4016NHj2jdunWV7rkhFf8M5s+fn5G+a1Vc5a2m2xquVdtzV0bLli3T6k0FHyO+3e50rT59+qRttcn6lQ8+pVKpWLx4ca3e7+ijj04Lhd58883x5ptv1uo960JdP0cAAAAANj+CXwAAABlScTWtjW33+Prrr8eSJUuSurKrEA0cODAKCgqSuuJ2keW9//77sWDBgg3Ol0sOPfTQ6Ny5c1I/8sgjlb62rKwsnnjiiaQeNGjQOgGiiqZPnx5z5sxJ6l122aUK025cxXsvXLgwY70jIt56663kOD8/P3r06JGRvrU9d3Vm2NSKcQsXLozp06cndSb/HBuy6gTsanq/a6+9NqmXL18ehx12WNxxxx2xatWqWr13barr5wgAAADA5kfwCwAAIEP233//aNSoUVJvLPhVMbD13e9+t1L3aNOmTey7775J/Y9//GODq2a9/vrraXX5FckyLZVKxddffx2zZ8+OmTNnbvCrusGH/Pz8OOOMM5L6X//6V1owa2P++c9/xty5c5O6Mts8ln99RMRjjz0WeXl5GfkaMmRIWu9Mh0HKz75mzZrYYostMjZ7bc5dGY0bN06ry29puT5Tp05NqytuKcj65een/+ui1atX1/o9L7/88hg8eHBSL126NC655JLYfvvt45e//GVMmjSp1mfItGw8RwAAAAA2L4JfAAAAGdK8efP4zne+k9Tjx4/f4NZe5YNfPXv2jO22267S9ym/3eOcOXNi/Pjx631d+eBZXl5eHHTQQZW+x8YsX748nn766fjxj38cBx54YLRr1y4KCwujVatW0alTp+jcufMGv2677bZq33fIkCFJ+KisrCyGDRtWqevKb/O43XbbVWrls9LS0mrNWB1r1qzJaL+6mj3Tc9eGiiuCdejQIUuTsCmFhYXxxBNPxLXXXpsW8Js1a1Zcf/310atXr+jatWucffbZ8cgjj8SMGTOyOC0AAAAA1A+CXwAAABlUPlRUVlYW//nPf9Z5zZQpU+KTTz5J6spu87hWxdXBNrTdY/kVv3r37h1t27at0n0qmjVrVlxwwQXRsWPHGDx4cPzxj3+M//znP7FgwYI6CQHtsMMOceCBByZ1+UDXhixevDief/75pD7zzDPXWblqfcpvkZlrcnn2TKu4KllRUVGWJqEy8vPz44YbboiJEyfG6aefvs4Kb1988UU88MADccYZZ8S2224bO+20U1x00UXxn//8Z4MrHwIAAABAQ1aY7QEAAAAakgEDBsRvfvObpB41alTaCl0RES+++GJaXdltHtfq3bt3bLPNNjFz5syI+Db4dc0116S95uOPP46SkpK0uaprzZo18dvf/jZuvPHGWLZsWbX7ZMJZZ52VrGQ2ceLEmDBhQvTp02eDr3/mmWfim2++iYhvVz0788wzK3WflStXptVPPfVU2habmVRcXJzRfqtWrUqOBw8eHLfeemtG+6/VvHnzWumbSYJfuWnnnXeOhx9+OH73u9/FE088Ec8880y88cYb6wRMP/vss/jss8/irrvuis6dO8f//M//xHnnnRctWrTI0uQAAAAAULcEvwAAADJov/32i8aNGyfBofLbLa5VfoWuNm3aRL9+/ap8nyOPPDLuvffeiIgYM2ZMLFiwIG1Fr4r3rW7w65tvvolTTz01nn322XW+t8cee8Txxx8fffv2je7du0fr1q03Gay5/vrr45e//GW1ZomIOP744+Piiy9OttB8+OGHNxr8Kr8q2MEHHxxdunSp1H0KCgrS6latWsU222xT9YGzID8/PwnIFBYW5szctaHiKlCVWe2N+mPLLbeMH//4x/HjH/84Fi1aFG+88Ub85z//iZEjR8a7774bq1evTl47Y8aMuPTSS+M3v/lN3HrrrXH66adncXIAAAAAqBu2egQAAMigLbbYIvbee++kfvfdd2PJkiVJ/c0338TIkSOTeuDAgVFYWPX/Jqf8KmFr1qyJl19+Oe375bd5zM/PT9sisSpOPPHEdUJfBx54YLz77rvx7rvvxlVXXRWHHXZYdO7cuU5WU2rWrFmceOKJSf3444+nhT/KmzVrVtqzHjJkSKXv07p167R60aJFVRkzq8rPnktz14aWLVum1eX/LpJbWrduHd/97nfjt7/9bbz11luxYMGCeO655+LEE0+MLbbYInldaWlpnHHGGXHCCSess3IfAAAAADQ0gl8AAAAZ1r9//+R49erV8cYbbyT1a6+9lmw9GFH1bR7XOvTQQ6Nx48ZJXXH7yPIrfvXp02edIFNl3H333fG3v/0tqfPy8uKmm26KUaNGxR577FH1oTOkfIBr7ty58corr6z3dcOGDUtWvmrVqlV8//vfr/Q92rVrl1YvXLiwGpNmR/nZc2nu2tCqVau0uuLWj+SuoqKiOO644+KJJ56IqVOnxmWXXZYWoh0+fHgcf/zxWZwQAAAAAGqf4BcAAECGVdxW8c0330yOX3vtteQ4Pz8/jjzyyGrdo3nz5nHQQQcldfmVrWbMmBGzZs3a4DyVUVZWFr/+9a/Tzv3hD3+IK664ourDZli/fv2ie/fuSf3II4+s93Xlt3k86aST0lYF2pT27dun1R9//HEVp8ye8rN/8skn62x3uDmpGHicO3dudgahVnXo0CFuvvnmeP3116NNmzbJ+b/97W9x//33Z3EyAAAAAKhdgl8AAAAZtu+++0aTJk2SesKECcnxmDFjkuN99tlnnZWlquKoo45KjmfPnh2zZ8+OiIh33nkn7XXVCX6NGDEi6RcRcdhhh8WPfvSjak6aeeVX/frrX/8aX331Vdr3J0yYEB988MF6X18ZXbt2jRYtWiT1W2+9Vc1J695uu+2WHC9cuDA+/fTTLE6TXV27do28vLyknjhxYhanobbtu+++8dxzz6X9md98881ZnAgAAAAAapfgFwAAQIY1bdo09tlnn6QeP358RHy7ita7776bnK/uNo9rlQ9+Rfz/wFf5exQUFMQBBxxQ5d7lw2oRET/+8Y+rPmAtOu2006KgoCAiIpYvXx5PPfVU2vfLr/bVs2fP2HvvvavUv6CgIPbbb7+kHj9+/Drhsvqq/EpwEemrwW1uioqKolu3bkn93nvvZXEa6sJBBx0UgwYNSupPPvkkPvrooyxOBAAAAAC1R/ALAACgFpRfZWv69OmxcOHCeP/992PZsmXJ+ZoGv7p16xY77rhjUo8dOzbt/0ZE7LHHHtGyZcsq9545c2Za/Z3vfKeaU6abPn16RvpstdVWadtklt/usaysLB5//PGkrupqX2v1798/OV6xYkU89thj1epT1yoGvx544IEsTVI/lP/ZnThxYsyYMSOL01DRJ598EiNHjky+MuGYY45Jq6dMmZKRvgAAAABQ3wh+AQAA1IKK2yuOHz8+bZvHzp07p23JV13lV/1a34pf1dnmcX1atWpV4x5z585NC2TVVPlA1xtvvJGEO/7973/HnDlzIiKisLAwTjvttGr1P+WUU6KwsDCphw4dGqlUqgYT142tttoqBg4cmNRvv/122s/E5qb835FUKrXO6nDVVZMV4PLz0/91TC78XNWW++67LwYMGJB8lZaW1rhnhw4d0urFixfXuOfmrPzWmZvzzyoAAABAfST4BQAAUAv22Wef2GKLLZJ6woQJ8dZbbyV1xW0aq6v8qmFjx46NqVOnpgUnqhv8Ki4uTqtnzZpVvQHLueiii2L58uU17rPW0UcfHe3bt4+Ib8MIf/vb3yIi4tlnn01ec9RRR8WWW25Zrf6dO3eOE088MaknTpwY99xzTw0mrjuXXXZZWn3JJZdstoGN//N//k+0bt06qf/0pz/FihUratRzzpw5cd9991X7+hYtWqTVS5curdE8uWy77bZLqz/++OMa95w2bVpavdVWW9W45+as/M/r5vyzCgAAAFAfCX4BAADUgsaNG8e+++6b1BMmTEhb8aum2zyuddBBB0Xz5s0jIqK0tDSGDx+efK+wsDD233//avXdZZdd0upXXnml+kNGxE033RTPPPPMOufXrFlT7Z6NGjWKU089NanXzrg2ABZR/W0e17riiiuioKAgqa+66qqMbBU4d+7cGvfYmEMPPTT22muvpH7zzTfjjjvuqHHf1atXx4IFC2rcpy41bdo0Tj755KSeNm1a/OEPf6h2vzVr1sQZZ5wRS5YsqXaPNm3apNWb8/aT3/ve99JWlHr00Udr3HPYsGHJcUFBQfTs2bPGPTdn5X9eN+efVQAAAID6SPALAACglpRfbesf//hHspJN06ZN45BDDsnIPZo0aRIHH3xwUt92223Jcd++fddZWaiyDj744LTA080331yt1brWrFkT119/ffzsZz+LiHVX96npFmxnnXVWcjxy5Mh48803k9XJOnToUOOAXe/eveO6665L6kWLFsWhhx4aJSUl1e75yiuvRI8ePeKll16q0Wyb8vDDD0ezZs2S+ic/+cl6w3eVNW/evDj00EPjggsuyMR4deraa69N2670F7/4RYwaNarKfVKpVFxwwQUxYsSIGs3TpUuXtD+bN954o0b9clmXLl3iiCOOSOr77rsvXn/99Wr3Gzp0aNr1hx12WLIyINXTo0eP5HjixIm2zgQAAACoRwS/AAAAakn54Nf8+fOTrfYGDBiQFvqoqfLhpjlz5qz3/lXVpk2b+MEPfpDUU6ZMiR/84AdV2iLvgw8+iEMPPTR++ctfRkTEcccdFz/+8Y/TXvPVV19Ve8aIiF133TX69u0bERHLli2L//mf/0m+d+qpp0ajRo1q1D8i4uqrr44DDzwwqT/99NM46KCD4p133qlSn1mzZsVFF10URx11VCxcuDAuueSSjG59WVH37t3j9ttvT+qysrI4+eST4w9/+EOVVlpbvXp13HfffbH77rvHqFGjYvjw4TVeAa6udezYMW688cakXrlyZRx33HFVeh+lpaVxzDHHxL333hsREdtuu22158nPz4/vfOc7ST169OgYO3Zstfvluj/96U/J1rhlZWXx3e9+N/7yl79UqUcqlYrbbrstLrroouRcfn5+WnCT6tlnn32S4+XLl8ef//znLE4DAAAAQHmCXwAAALVkr732Wm/AK1PbPK511FFHrfd8//79a9T3+uuvT7aRjIh4/vnnY++9945//OMfSYitom+++SZeeOGFGDx4cOy2227x2muvRcS3q+48/vjj0bp167TX1zT4FZG+nePbb7+93vM1kZ+fH08//XTadnEff/xx7LPPPnHBBRfEW2+9tcHnsWTJkvjrX/8a5557bnTt2jXuuuuuJHS1cuXKmDdvXkZm3JBzzjknLr/88qReuXJl/OQnP4l99tknnnjiiQ1uV5hKpWLcuHFx4403Rrdu3eLcc89NVlLLy8tLjnPJD3/4w/je976X1IsWLYojjjgizjjjjHjrrbc2eN3UqVPjhhtuiB133DH+/ve/R0TEiSeeWOOfr/LbT6ZSqRg0aFCMGzeuRj1zVdeuXePhhx9OVhlcsmRJnHbaabHnnnvGAw88EPPnz9/gtcuXL4+nnnoq9tlnn/jpT3+aFmq8+uqr00JLVE/5n9WIb5/rY489lqVpAAAAACivMNsDAAAANFSNGjWK/fbbb51t4cqHTzKhc+fOseuuu8b777+/zr1romvXrvGXv/wlBg0alIQp3nvvvTjqqKOibdu20bdv3+jQoUNEfBvgmjJlSnz00UdRVlaW1ufCCy+MP/zhD9GoUaPYZptt0r73xRdf1GjGiG9DCZdeemna6ll9+/aNXXbZpca91youLo5Ro0bF8ccfn2wRuGbNmrjnnnvinnvuia233jp23HHH2GqrrSI/Pz9KSkqipKQkPvnkk1i5cuU6/fbbb7948skno1OnThmbcUN+97vfRfv27eOqq65K/hzfeeed+MEPfhBbbLFF9OrVK7beeuto3bp1lJaWRklJSUyZMmW9YZvWrVvHgw8+GMcdd1ytz51p+fn58cQTT8Rxxx0X//rXv5LzjzzySDzyyCPRqVOn2GmnnWKrrbaKgoKCWLBgQUyaNCmmTp2a1uekk06KRx99NH7961/XaJ7TTjstfv/738fkyZMjImL69Onxne98J/bZZ5/YcccdY8WKFTF9+vQ46qij4pprrqnRvXLB4MGDIyLizDPPjGXLlkVExLhx4+Lss8+O/Pz82GGHHWLnnXeO1q1bR0FBQXz99dcxderU+PDDD2PVqlXr9LvmmmvihhtuqNP30FB169YtTjnllBg2bFhERKxYsSJOOeWUuOGGG2LPPfeMvLy8+PLLL6NZs2bx17/+NcvTAgAAAGxeBL8AAABq0YABA9KCX7169YouXbpk/D5HHXVUWvBrr732Slutq7qOO+64eOmll+KUU06J0tLS5PyCBQvin//850av7datW/zpT3+Kww8/PDlXftWsiIiJEyfWeMbWrVvHcccdF0888URy7qyzzqpx34r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      "text/plain": [
       "<Figure size 2400x1350 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ShiftedIn, ShiftedOut = get_shifted(LambdaIn, LambdaOut)\n",
    "\n",
    "fig, ax1 = plt.subplots()\n",
    "ax1.plot(wavelengths, reflected)\n",
    "\n",
    "\n",
    "plt.hist2d(ShiftedIn,ShiftedOut, bins = (70,351), range= ((250,600),(250,600)), cmap='jet', density=True, label='Heatmap')\n",
    "plt.xlabel('Absorption Wavelength [nm]')\n",
    "plt.ylabel('Emission Wavelength [nm]')\n",
    "plt.ylim(ymin=250, ymax=600)\n",
    "plt.title('Wavelength shift')\n",
    "plt.colorbar(label='Gamma (not in %)')\n",
    "plt.savefig(\"/home/eric/sim/WWLegend/Plots/WLS/Wavelength_shift.png\", dpi=300, bbox_inches=\"tight\", pad_inches=0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Third Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/eric/.local/lib/python3.8/site-packages/numpy/lib/histograms.py:883: RuntimeWarning: invalid value encountered in divide\n",
      "  return n/db/n.sum(), bin_edges\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2400x1350 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax1 = plt.subplots()\n",
    "\n",
    "ax1.hist(ShiftedIn, density=True, histtype=\"step\", bins=34)\n",
    "\n",
    "\n",
    "ax1.set_xlabel('Wavelength in nm')\n",
    "ax1.set_ylabel('WLS Ratio [not in %]')\n",
    "ax1.set_title('Percentage of WLS light')\n",
    "#ax1.grid()\n",
    "#ax1.set_legend_logo(position=\"lower left\")\n",
    "plt.savefig(\"/home/eric/sim/WWLegend/Plots/WLS/Percentage_of_WLS_light.png\", dpi=300, bbox_inches=\"tight\", pad_inches=0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compare Knapp 2x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "#yes i am that stupid/lazy\n",
    "Efficiency = np.array([0.    , 0.    , 0.    , 0.    , 0.    , 0.    , 0.    , 0.    ,\n",
    "                       0.    , 0.    , 0.    , 0.    , 0.    , 0.    , 0.    , 0.    ,\n",
    "                       0.    , 0.    , 0.    , 0.    , 0.    , 0.    , 0.    , 0.    ,\n",
    "                       0.    , 0.    , 0.    , 0.    , 0.    , 0.    , 0.    , 0.001 ,\n",
    "                       0.002 , 0.003 , 0.004 , 0.005 , 0.006 , 0.007 , 0.008 , 0.009 ,\n",
    "                       0.01  , 0.019 , 0.028 , 0.037 , 0.046 , 0.055 , 0.064 , 0.073 ,\n",
    "                       0.082 , 0.091 , 0.1   , 0.104 , 0.108 , 0.112 , 0.116 , 0.12  ,\n",
    "                       0.124 , 0.128 , 0.132 , 0.136 , 0.14  , 0.144 , 0.148 , 0.152 ,\n",
    "                       0.156 , 0.16  , 0.164 , 0.168 , 0.172 , 0.176 , 0.18  , 0.184 ,\n",
    "                       0.188 , 0.192 , 0.196 , 0.2   , 0.204 , 0.208 , 0.212 , 0.216 ,\n",
    "                       0.22  , 0.224 , 0.228 , 0.232 , 0.236 , 0.24  , 0.244 , 0.248 ,\n",
    "                       0.252 , 0.256 , 0.26  , 0.264 , 0.268 , 0.272 , 0.276 , 0.28  ,\n",
    "                       0.284 , 0.288 , 0.292 , 0.296 , 0.3   , 0.3   , 0.3   , 0.3   ,\n",
    "                       0.3   , 0.3   , 0.3   , 0.3   , 0.3   , 0.3   , 0.3   , 0.3   ,\n",
    "                       0.3   , 0.3   , 0.3   , 0.3   , 0.3   , 0.3   , 0.3   , 0.3   ,\n",
    "                       0.3   , 0.299 , 0.298 , 0.297 , 0.296 , 0.295 , 0.294 , 0.293 ,\n",
    "                       0.292 , 0.291 , 0.29  , 0.289 , 0.288 , 0.287 , 0.286 , 0.285 ,\n",
    "                       0.284 , 0.283 , 0.282 , 0.281 , 0.28  , 0.28  , 0.28  , 0.28  ,\n",
    "                       0.28  , 0.28  , 0.28  , 0.28  , 0.28  , 0.28  , 0.28  , 0.2789,\n",
    "                       0.2778, 0.2767, 0.2756, 0.2745, 0.2734, 0.2723, 0.2712, 0.2701,\n",
    "                       0.269 , 0.2679, 0.2668, 0.2657, 0.2646, 0.2635, 0.2624, 0.2613,\n",
    "                       0.2602, 0.2591, 0.258 , 0.2569, 0.2558, 0.2547, 0.2536, 0.2525,\n",
    "                       0.2514, 0.2503, 0.2492, 0.2481, 0.247 , 0.2459, 0.2448, 0.2437,\n",
    "                       0.2426, 0.2415, 0.2404, 0.2393, 0.2382, 0.2371, 0.236 , 0.2349,\n",
    "                       0.2338, 0.2327, 0.2316, 0.2305, 0.2294, 0.2283, 0.2272, 0.2261,\n",
    "                       0.225 , 0.2235, 0.222 , 0.2205, 0.219 , 0.2175, 0.216 , 0.2145,\n",
    "                       0.213 , 0.2115, 0.21  , 0.2085, 0.207 , 0.2055, 0.204 , 0.2025,\n",
    "                       0.201 , 0.1995, 0.198 , 0.1965, 0.195 , 0.1935, 0.192 , 0.1905,\n",
    "                       0.189 , 0.1875, 0.186 , 0.1845, 0.183 , 0.1815, 0.18  , 0.1785,\n",
    "                       0.177 , 0.1755, 0.174 , 0.1725, 0.171 , 0.1695, 0.168 , 0.1665,\n",
    "                       0.165 , 0.1635, 0.162 , 0.1605, 0.159 , 0.1575, 0.156 , 0.1545,\n",
    "                       0.153 , 0.1515, 0.15  , 0.148 , 0.146 , 0.144 , 0.142 , 0.14  ,\n",
    "                       0.138 , 0.136 , 0.134 , 0.132 , 0.13  , 0.128 , 0.126 , 0.124 ,\n",
    "                       0.122 , 0.12  , 0.118 , 0.116 , 0.114 , 0.112 , 0.11  , 0.108 ,\n",
    "                       0.106 , 0.104 , 0.102 , 0.1   , 0.098 , 0.096 , 0.094 , 0.092 ,\n",
    "                       0.09  , 0.088 , 0.086 , 0.084 , 0.082 , 0.08  , 0.078 , 0.076 ,\n",
    "                       0.074 , 0.072 , 0.07  , 0.068 , 0.066 , 0.064 , 0.062 , 0.06  ,\n",
    "                       0.058 , 0.056 , 0.054 , 0.052 , 0.05  , 0.0492, 0.0484, 0.0476,\n",
    "                       0.0468, 0.046 , 0.0452, 0.0444, 0.0436, 0.0428, 0.042 , 0.0412,\n",
    "                       0.0404, 0.0396, 0.0388, 0.038 , 0.0372, 0.0364, 0.0356, 0.0348,\n",
    "                       0.034 , 0.0332, 0.0324, 0.0316, 0.0308, 0.03  , 0.0292, 0.0284,\n",
    "                       0.0276, 0.0268, 0.026 , 0.0252, 0.0244, 0.0236, 0.0228, 0.022 ,\n",
    "                       0.0212, 0.0204, 0.0196, 0.0188, 0.018 , 0.0172, 0.0164, 0.0156,\n",
    "                       0.0148, 0.014 , 0.0132, 0.0124, 0.0116, 0.0108, 0.01  ])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 2400x1350 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wavelengths = np.arange(100, 601)\n",
    "\n",
    "def Cherenkov_yield(wavelength):\n",
    "    return 1e5 / (wavelength*wavelength)\n",
    "\n",
    "fig, ax1 = plt.subplots()\n",
    "ax1.plot(wavelengths, Cherenkov_yield(wavelengths), color = lps.colors[\"darkred\"])\n",
    "condition = (wavelengths>350) & (wavelengths < 475)\n",
    "area1 = np.sum(Cherenkov_yield(wavelengths[condition]))\n",
    "ax1.fill_between(wavelengths[condition], Cherenkov_yield(wavelengths[condition]), color = lps.colors[\"darkred\"], label=f\"Area = {area1}\")\n",
    "condition2 = (wavelengths>200) & (wavelengths < 350)\n",
    "area2 = np.sum(Cherenkov_yield(wavelengths[condition2]))\n",
    "ax1.fill_between(wavelengths[condition2], Cherenkov_yield(wavelengths[condition2]), alpha=0.7, color = lps.colors[\"legend_orange\"], label=f\"Area = {area2}\")\n",
    "condition3 = (wavelengths < 350)\n",
    "area3 = np.sum(Cherenkov_yield(wavelengths[condition3]))\n",
    "ax1.fill_between(wavelengths[condition3], Cherenkov_yield(wavelengths[condition3]), alpha=0.7, color = lps.colors[\"legend_darkblue\"], label=f\"Area = {area3}\")\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "ax1.set_xlabel('Wavelength in nm')\n",
    "ax1.set_ylabel('Cherenkov light in a.u.')\n",
    "ax1.set_title('Cherenkov session')\n",
    "#ax1.grid()\n",
    "ax1.legend(loc='upper right', facecolor='white', framealpha=1)\n",
    "#ax1.set_legend_logo(position=\"lower left\")\n",
    "#plt.savefig(\"/home/eric/sim/WWLegend/Plots/WLS/Reflectance_Absorption.png\", dpi=300, bbox_inches=\"tight\", pad_inches=0.1)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}