Field_Data_Processing.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyO788UysQCbLzku4c7IDCmj",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/braimahm/Derivative-Spectra-for-Land-Cover---Python-Codes/blob/main/Field_Data_Processing.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 123,
      "metadata": {
        "id": "Kvy4aIFt5-5z",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "42a0da3d-a9dd-4e56-d274-21f8785f645f"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/gdrive; to attempt to forcibly remount, call drive.mount(\"/content/gdrive\", force_remount=True).\n"
          ]
        }
      ],
      "source": [
        " ''' The code interpolates the 1nm reflectance to 10nm\n",
        " and computes derivatives'''\n",
        "\n",
        "##we are importing operational packages\n",
        "\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')\n",
        "\n",
        "##we are importing visualization packages\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "\n",
        "\"\"\" We want to load the excel book and call each worksheet.\n",
        "This saves us time from saving each worksheet seperately as a .csv file\n",
        "\"\"\"\n",
        "\n",
        "ZachA_LynnW = pd.ExcelFile('/content/042623_HWHF_10d_1_1.xlsx')\n",
        "ZachA_15_Weeds = pd.read_excel(ZachA_LynnW, 'ZachA_15_Weeds')\n",
        "ZachA_15_Soil = pd.read_excel(ZachA_LynnW, 'ZachA15_Soil')\n",
        "ZachA_14_Weeds = pd.read_excel(ZachA_LynnW, 'ZachA_14_Weeds')\n",
        "ZachA_14_Soil = pd.read_excel(ZachA_LynnW, 'ZachA14_Soil')\n",
        "ZachA_13_Weeds = pd.read_excel(ZachA_LynnW, 'ZachA13_Weeds')\n",
        "ZachA_13_Soil = pd.read_excel(ZachA_LynnW, 'ZachA13_10D_Soil')\n",
        "ZachA_12_Wheat = pd.read_excel(ZachA_LynnW, 'ZachA12_Wheat')\n",
        "ZachA_12_Road = pd.read_excel(ZachA_LynnW, 'ZachA12_Road')\n",
        "ZachA_11_Wheat = pd.read_excel(ZachA_LynnW, 'ZackA_11_Wheat')\n",
        "ZachA_11_Soil = pd.read_excel(ZachA_LynnW, 'ZachA11_Soil')\n",
        "LynnW05_CornRes = pd.read_excel(ZachA_LynnW, '042623_LynnW05_Cornres')\n",
        "LynnW05_Soil = pd.read_excel(ZachA_LynnW, '042623_LynnW05_Bare_Soil')\n",
        "LynnW04_CornRes = pd.read_excel(ZachA_LynnW, '042623_LynnW04_Cornres')\n",
        "LynnW04_Soil = pd.read_excel(ZachA_LynnW, '042623LynnW04_Bare_SOil')\n",
        "LynnW03_CornRes = pd.read_excel(ZachA_LynnW, '042623_LynnW03_Cornres')\n",
        "LynnW03_Soil = pd.read_excel(ZachA_LynnW, '042623LynnW_03_Bare_Soil')\n",
        "LynnW02_CornRes = pd.read_excel(ZachA_LynnW, '042623_LynnW02_Cornres')\n",
        "LynnW02_Soil = pd.read_excel(ZachA_LynnW, '042623_LynnW02_Bare_Soil')\n",
        "LynnW01_CornRes = pd.read_excel(ZachA_LynnW, '042623_LynnW01_Cornres')\n",
        "LynnW01_Soil = pd.read_excel(ZachA_LynnW, '042623_LynnW01_Bare_Soil')\n",
        "\n",
        "SK_farms = pd.ExcelFile('/content/052423_HWHF_10d_1.xlsx')\n",
        "SK_5_Soil = pd.read_excel(SK_farms, '052423_SK_5_Soil')\n",
        "SK_5_Grass = pd.read_excel(SK_farms, '052423_SK_5_Grass')\n",
        "SK_4_Soil = pd.read_excel(SK_farms, '052423_SK_4_Soil')\n",
        "SK_4_Grass = pd.read_excel(SK_farms, '052423_SK_4_Grass')\n",
        "SK_3_Soil = pd.read_excel(SK_farms, '052423_SK_3_Soil')\n",
        "SK_3_Grass = pd.read_excel(SK_farms, '052423_SK_3_Grass')\n",
        "SK_2_Soil = pd.read_excel(SK_farms, '052423_SK_2_Soil')\n",
        "SK_2_Grass = pd.read_excel(SK_farms, '052423_SK_2_Grass')\n",
        "SK_1_Soil = pd.read_excel(SK_farms, '052423_SK_1_Soil')\n",
        "SK_1_Grass = pd.read_excel(SK_farms, '052423_SK_1_Grass')\n",
        "\n",
        "KB_farms = pd.ExcelFile('/content/052223_HWHF_10d_1.xlsx')\n",
        "KB_5_Wheat = pd.read_excel(KB_farms, '52223_KB5_Wheat')\n",
        "KB_5_Soil = pd.read_excel(KB_farms, '052223_KB5_Soil')\n",
        "KB_5_Drying_Wheat = pd.read_excel(KB_farms, '052223_KB5_Drying_Wheat')\n",
        "KB_5_Corn_Res = pd.read_excel(KB_farms, '052223_KB5_Corn_Res')\n",
        "KB_4_Soil = pd.read_excel(KB_farms, '052223_KB4_Soil')\n",
        "KB_4_Dry_Rye = pd.read_excel(KB_farms, '052223_KB4_Dry_Rye')\n",
        "KB_4_Corn_Res = pd.read_excel(KB_farms, '052223_KB4_Corn_Res')\n",
        "KB_3_Soil = pd.read_excel(KB_farms, '052223_KB3_Soil')\n",
        "KB_3_Corn_Res = pd.read_excel(KB_farms, '052223_KB_3_Corn_Res')\n",
        "KB_1_Soil = pd.read_excel(KB_farms, '052223_KB1_Soil')\n",
        "KB_1_Corn_Res = pd.read_excel(KB_farms, '052223_KB1_Corn_Res')\n",
        "JB_5_Soil = pd.read_excel(KB_farms, '052223_JB5_Soil')\n",
        "JB_5_Corn_Res = pd.read_excel(KB_farms, '052223_JB5_Corn_Res')\n",
        "JB_4_Soil = pd.read_excel(KB_farms, '052223_JB4_Soil')\n",
        "JB_4_Corn_Res = pd.read_excel(KB_farms, '052223_JB4_CorenRes')\n",
        "JB_3_Soil = pd.read_excel(KB_farms, '052223_JB3_Soil')\n",
        "JB_3_Corn_Res = pd.read_excel(KB_farms, '052223_JB3_Corn_Residue')\n",
        "JB_2_Soil = pd.read_excel(KB_farms, '052223_JB2_Soil')\n",
        "JB_2_Corn_Res = pd.read_excel(KB_farms, '052223_JB2_Corn_Residue')\n",
        "JB_1_Soil = pd.read_excel(KB_farms, '052223_JB1_Soil')\n",
        "JB_1_Corn_Res = pd.read_excel(KB_farms, '052223_JB1_CornRes')\n",
        "JB_1_Soya_Bean = pd.read_excel(KB_farms, '052223_JB1_Soya_Bean')\n",
        "JB_Grass_Filt = pd.read_excel(KB_farms, '052223_JB_Grass_Filt')\n",
        "JB_0_Road = pd.read_excel(KB_farms, '052223_JB0_Road')\n",
        "\n",
        "JanD_farms = pd.ExcelFile('/content/041923_HWHF_10d_1_1.xlsx')\n",
        "JanD_S10_Weeds = pd.read_excel(JanD_farms, '041923_JanDS10_Weeds')\n",
        "JanD_S9_Weeds = pd.read_excel(JanD_farms, '041923_JanDS09_Weeds')\n",
        "JanD_S9_Corn_Res = pd.read_excel(JanD_farms, '041923_JanDS09_Cornres')\n",
        "JanD_S8_Corn_Res = pd.read_excel(JanD_farms, '041923_JanDS08_Cornres')\n",
        "JanD_S8_Bare_Soil = pd.read_excel(JanD_farms, '041923JanDS08_Baresoil')\n",
        "JanD_S6_Weed = pd.read_excel(JanD_farms, '041923_JanDS06_Weed')\n",
        "JanD_S6_Weed_2 = pd.read_excel(JanD_farms, '041923_JanDS06_Weed2')\n",
        "JanD_S6_Weed_3 = pd.read_excel(JanD_farms, '041923_JanDS06_Weed3')\n",
        "JanD_S6_Bare_Soil = pd.read_excel(JanD_farms, '041923_JanDS06_Baresoil')\n",
        "JanD_S6_Corn_Redw = pd.read_excel(JanD_farms, '041923JanDS06_Corn_Redw')\n"
      ],
      "metadata": {
        "id": "0pvHct8eXwPl"
      },
      "execution_count": 124,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\"This function calculates the mean avaerage reflectance of the sample and multiplies it by 100\"\n",
        "\n",
        "def mean_reflectance (sample):\n",
        "  sample[\"Mean Reflectance\"] = sample.drop('Wavelength', axis=1).mean(axis=1)*100\n",
        "  return sample[\"Mean Reflectance\"]"
      ],
      "metadata": {
        "id": "5ySqBGiwmQJj"
      },
      "execution_count": 125,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "'''We want to  plot the average reflectance\n",
        "for 1nm wavelength. This was plotted after the atmospheric corrections\n",
        "had been done in excel\n",
        "The plot takes on the mean_reflectance function of each sample and plot it against the 1nm wavelength\n",
        "'''\n",
        "wavelength = ZachA_15_Weeds['Wavelength']\n",
        "fig,axs = plt.subplots(3,1, figsize =(10,10))\n",
        "axs[0].plot(wavelength, mean_reflectance (ZachA_15_Weeds))\n",
        "axs[0].plot(wavelength, mean_reflectance(ZachA_14_Weeds))\n",
        "axs[0].plot(wavelength, mean_reflectance(ZachA_13_Weeds))\n",
        "axs[0].plot(wavelength, mean_reflectance(ZachA_12_Wheat))\n",
        "axs[0].plot(wavelength,mean_reflectance( ZachA_11_Wheat))\n",
        "axs[0].plot(wavelength, mean_reflectance(ZachA_12_Road))\n",
        "axs[0].plot(wavelength, mean_reflectance(SK_5_Grass))\n",
        "axs[0].plot(wavelength, mean_reflectance(SK_4_Grass))\n",
        "axs[0].plot(wavelength, mean_reflectance(SK_3_Grass))\n",
        "axs[0].plot(wavelength, mean_reflectance(SK_2_Grass))\n",
        "axs[0].plot(wavelength, mean_reflectance(SK_1_Grass))\n",
        "axs[0].plot(wavelength, mean_reflectance(KB_5_Wheat))\n",
        "axs[0].plot(wavelength, mean_reflectance(KB_5_Drying_Wheat))\n",
        "axs[0].plot(wavelength, mean_reflectance(KB_4_Dry_Rye))\n",
        "axs[0].plot(wavelength, mean_reflectance(JB_1_Soya_Bean))\n",
        "axs[0].plot(wavelength, mean_reflectance(JB_Grass_Filt))\n",
        "axs[0].plot(wavelength, mean_reflectance(JanD_S10_Weeds))\n",
        "axs[0].plot(wavelength, mean_reflectance(JanD_S9_Weeds))\n",
        "axs[0].plot(wavelength, mean_reflectance(JanD_S6_Weed))\n",
        "axs[0].plot(wavelength, mean_reflectance(JanD_S6_Weed_2))\n",
        "axs[0].plot(wavelength, mean_reflectance(JanD_S6_Weed_3))\n",
        "\n",
        "axs[0].set_title(\"Vegetation\")\n",
        "#axs[0].set_xlabel('Wavelength')\n",
        "axs[0].set_ylabel('Reflectance')\n",
        "\n",
        "axs[1].plot(wavelength, mean_reflectance(ZachA_15_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(ZachA_14_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(ZachA_13_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(ZachA_11_Soil))\n",
        "axs[1].plot(wavelength,mean_reflectance(LynnW05_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(LynnW04_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(LynnW03_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(LynnW02_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(LynnW01_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(SK_5_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(SK_4_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(SK_3_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(SK_2_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(SK_1_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(KB_5_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(KB_4_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(KB_3_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(KB_1_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(JB_5_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(JB_4_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(JB_3_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(JB_2_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(JB_1_Soil))\n",
        "axs[1].plot(wavelength, mean_reflectance(JB_0_Road))\n",
        "axs[1].plot(wavelength, mean_reflectance(JanD_S8_Bare_Soil ))\n",
        "axs[1].plot(wavelength, mean_reflectance(JanD_S6_Bare_Soil ))\n",
        "\n",
        "axs[1].set_title(\"Bare Soil\")\n",
        "#axs[1].set_xlabel('Wavelength')\n",
        "axs[1].set_ylabel('Reflectance')\n",
        "\n",
        "\n",
        "axs[2].plot(wavelength, mean_reflectance(LynnW05_CornRes))\n",
        "axs[2].plot(wavelength, mean_reflectance( LynnW04_CornRes))\n",
        "axs[2].plot(wavelength, mean_reflectance(LynnW03_CornRes))\n",
        "axs[2].plot(wavelength, mean_reflectance(LynnW02_CornRes))\n",
        "axs[2].plot(wavelength, mean_reflectance(LynnW01_CornRes))\n",
        "axs[2].plot(wavelength, mean_reflectance(KB_5_Corn_Res))\n",
        "axs[2].plot(wavelength, mean_reflectance(KB_4_Corn_Res))\n",
        "axs[2].plot(wavelength, mean_reflectance(KB_3_Corn_Res))\n",
        "axs[2].plot(wavelength, mean_reflectance(KB_1_Corn_Res))\n",
        "axs[2].plot(wavelength, mean_reflectance(JB_5_Corn_Res))\n",
        "axs[2].plot(wavelength, mean_reflectance(JB_4_Corn_Res))\n",
        "axs[2].plot(wavelength, mean_reflectance(JB_3_Corn_Res))\n",
        "axs[2].plot(wavelength, mean_reflectance(JB_2_Corn_Res))\n",
        "axs[2].plot(wavelength, mean_reflectance(JB_1_Corn_Res))\n",
        "axs[2].plot(wavelength, mean_reflectance(JanD_S9_Corn_Res))\n",
        "axs[2].plot(wavelength, mean_reflectance(JanD_S8_Corn_Res))\n",
        "axs[2].plot(wavelength, mean_reflectance(JanD_S6_Corn_Redw))\n",
        "\n",
        "\n",
        "\n",
        "axs[2].set_title(\"Corn Residue\")\n",
        "axs[2].set_xlabel('Wavelength')\n",
        "axs[2].set_ylabel('Reflectance')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 889
        },
        "id": "prfCr6tsnxhG",
        "outputId": "3a470353-12a6-4e0c-9e14-84f30fc5ddde"
      },
      "execution_count": 126,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Reflectance')"
            ]
          },
          "metadata": {},
          "execution_count": 126
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x1000 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "'''This function performs the interpolation at 10nm and calculates the derivative spectra'''\n",
        "def derivative(sample):\n",
        "\n",
        "  ## we convert the mean reflectance and wavelength at 1nm  to numpy arrays\n",
        "  Wavelength_np = np.array(sample[\"Wavelength\"])\n",
        "\n",
        "  #we apply the mean_reflectance function on the sample and convert it to numpy arrays\n",
        "  Reflectance_np= np.array( mean_reflectance (sample))\n",
        "\n",
        "  ##we tell python to give us values from 350 t0 2500, in intervals of 10\n",
        "  xvals = np.array(range(350, 2501, 10))\n",
        "\n",
        "  ##we are performing the interpolation at 10nm using the intervals, wavelength, and reflecatnace\n",
        "  interp_10nm = np.interp(xvals,Wavelength_np, Reflectance_np)\n",
        "\n",
        "  ## we want to claculate the derivative using the gradient function dydx = np.gradient(y,x)\n",
        "\n",
        "  derivative = np.gradient( interp_10nm , xvals)\n",
        "\n",
        "  return derivative"
      ],
      "metadata": {
        "id": "aGw_I0XkXuum"
      },
      "execution_count": 127,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "''' we want to execute the derivative function on each sample\n",
        "to get the derivative spectra of each sample'''\n",
        "SK_5_Soil_derivative = derivative(SK_5_Soil)\n",
        "SK_5_Grass_derivative = derivative(SK_5_Grass)\n",
        "SK_4_Soil_derivative = derivative(SK_4_Soil)\n",
        "SK_4_Grass_derivative = derivative( SK_4_Grass)\n",
        "SK_3_Soil_derivative = derivative(SK_3_Soil)\n",
        "SK_3_Grass_derivative = derivative(SK_3_Grass)\n",
        "SK_2_Soil_derivative = derivative(SK_2_Soil)\n",
        "SK_2_Grass_derivative = derivative(SK_2_Grass)\n",
        "SK_1_Soil_derivative = derivative (SK_1_Soil)\n",
        "SK_1_Grass_derivative = derivative (SK_1_Grass)\n",
        "\n",
        "KB_5_Soil_derivative = derivative (KB_5_Soil)\n",
        "KB_5_Wheat_derivative = derivative (KB_5_Wheat)\n",
        "KB_5_Drying_Wheat_derivative = derivative(KB_5_Drying_Wheat)\n",
        "KB_5_Corn_Res_derivative = derivative(KB_5_Corn_Res)\n",
        "KB_4_Dry_Rye_derivative = derivative (KB_4_Dry_Rye)\n",
        "KB_4_Soil_derivative = derivative (KB_4_Soil)\n",
        "KB_3_Corn_Res_derivative = derivative (KB_3_Corn_Res)\n",
        "KB_3_Soil_derivative = derivative (KB_3_Soil)\n",
        "KB_1_Corn_Res_derivative = derivative (KB_1_Corn_Res)\n",
        "KB_1_Soil_derivative = derivative (KB_1_Soil)\n",
        "\n",
        "JB_5_Soil_derivative = derivative(JB_5_Soil)\n",
        "JB_5_Corn_Res_derivative = derivative(JB_5_Corn_Res)\n",
        "JB_4_Soil_derivative = derivative (JB_4_Soil)\n",
        "JB_4_Corn_Res_derivative = derivative (JB_4_Corn_Res)\n",
        "JB_3_Soil_derivative = derivative (JB_3_Soil)\n",
        "JB_3_Corn_Res_derivative = derivative (JB_3_Corn_Res)\n",
        "JB_2_Soil_derivative = derivative (JB_2_Soil)\n",
        "JB_2_Corn_Res_derivative = derivative (JB_2_Corn_Res)\n",
        "JB_1_Soil_derivative = derivative (JB_1_Soil)\n",
        "JB_1_Corn_Res_derivative = derivative (JB_1_Corn_Res)\n",
        "JB_1_Soya_Bean_derivative = derivative (JB_1_Soya_Bean)\n",
        "JB_0_Road_derivative = derivative (JB_0_Road)\n",
        "JB_Grass_Filt_derivative = derivative (JB_Grass_Filt)\n",
        "\n",
        "JanD_S10_Weeds_derivative = derivative(JanD_S10_Weeds)\n",
        "JanD_S9_Weeds_derivative = derivative(JanD_S9_Weeds)\n",
        "JanD_S9_Corn_Res_derivative = derivative(JanD_S9_Corn_Res)\n",
        "\n",
        "JanD_S8_Corn_Res_derivative = derivative (JanD_S8_Corn_Res)\n",
        "JanD_S8_Bare_Soil_derivative = derivative (JanD_S8_Bare_Soil)\n",
        "JanD_S6_Weed_derivative = derivative (JanD_S6_Weed)\n",
        "JanD_S6_Weed_2_derivative = derivative (JanD_S6_Weed_2)\n",
        "JanD_S6_Weed_3_derivative = derivative (JanD_S6_Weed_3)\n",
        "JanD_S6_Corn_Rewd_derivative = derivative (JanD_S6_Corn_Redw )\n",
        "\n",
        "ZachA_15_Weeds_derivative = derivative(ZachA_15_Weeds)\n",
        "ZachA_15_Soil_derivative = derivative(ZachA_15_Soil)\n",
        "ZachA_14_Soil_derivative = derivative(ZachA_14_Soil)\n",
        "ZachA_14_Weeds_derivative = derivative(ZachA_14_Weeds)\n",
        "ZachA_13_Weeds_derivative = derivative(ZachA_13_Weeds)\n",
        "ZachA_13_Soil_derivative = derivative (ZachA_13_Soil)\n",
        "ZachA_12_Wheat_derivative = derivative (ZachA_12_Wheat)\n",
        "ZachA_12_Road_derivative = derivative (ZachA_12_Road)\n",
        "ZachA_11_Wheat_derivative = derivative(ZachA_11_Wheat)\n",
        "ZachA_11_Soil_derivative = derivative(ZachA_11_Soil)\n",
        "\n",
        "\n",
        "LynnW_05_CornRes_derivative = derivative(LynnW05_CornRes)\n",
        "LynnW_05_Soil_derivative = derivative (LynnW05_Soil)\n",
        "LynnW_04_CornRes_derivative = derivative (LynnW04_CornRes)\n",
        "LynnW_04_Soil_derivative = derivative(LynnW04_Soil)\n",
        "LynnW_03_CornRes_derivative = derivative(LynnW03_CornRes)\n",
        "LynnW_03_Soil_derivative = derivative (LynnW03_Soil)\n",
        "LynnW_02_CornRes_derivative = derivative (LynnW02_CornRes)\n",
        "LynnW_02_Soil_derivative = derivative(LynnW02_Soil)\n",
        "LynnW_01_CornRes_derivative = derivative(LynnW01_CornRes)\n",
        "LynnW_01_Soil_derivative = derivative (LynnW01_Soil)\n",
        "\n"
      ],
      "metadata": {
        "id": "KJyGlarpdQ1V"
      },
      "execution_count": 128,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "''' we want to make a dataframe of all derivatives of each sample from each site\n",
        "'''\n",
        "xvals_10nm = np.array(range(350, 2501, 10))\n",
        "derivative_spring_2023 = pd.DataFrame({'Wavelength':xvals_10nm,\n",
        "                                       'ZachA_15_Weeds_derivative': ZachA_15_Weeds_derivative,\n",
        "                                       'ZachA_15_Soil_derivative': ZachA_15_Soil_derivative,\n",
        "                                       'ZachA_14_Weeds_derivative': ZachA_14_Weeds_derivative,\n",
        "                                       'ZachA_14_Soil_derivative':ZachA_14_Soil_derivative,\n",
        "                                       'ZachA_13_Weeds_derivative':ZachA_13_Weeds_derivative,\n",
        "                                       'ZachA_13_Soil_derivative': ZachA_13_Soil_derivative,\n",
        "                                       'ZachA_12_Wheat_derivative ':ZachA_12_Wheat_derivative ,\n",
        "                                       'ZachA_12_Road_derivative': ZachA_12_Road_derivative,\n",
        "                                       'ZachA_11_Wheat_derivative':ZachA_11_Wheat_derivative,\n",
        "                                       'ZachA_11_Soil_derivative': ZachA_11_Soil_derivative,\n",
        "                                       'LynnW_05_CornRes_derivative': LynnW_05_CornRes_derivative,\n",
        "                                       'LynnW_05_Soil_derivative': LynnW_05_Soil_derivative,\n",
        "                                       'LynnW_04_CornRes_derivative ': LynnW_04_CornRes_derivative ,\n",
        "                                       'LynnW_04_Soil_derivative ': LynnW_04_Soil_derivative,\n",
        "                                       'LynnW_03_CornRes_derivative ': LynnW_03_CornRes_derivative,\n",
        "                                       'LynnW_03_Soil_derivative':LynnW_03_Soil_derivative,\n",
        "                                       'LynnW_02_CornRes_derivative ': LynnW_02_CornRes_derivative,\n",
        "                                       'LynnW_02_Soil_derivative':LynnW_02_Soil_derivative,\n",
        "                                       'LynnW_01_CornRes_derivative ': LynnW_01_CornRes_derivative,\n",
        "                                       'LynnW_01_Soil_derivative': LynnW_01_Soil_derivative,\n",
        "                                       'SK_5_Soil_derivative': SK_5_Soil_derivative,\n",
        "                                       'SK_5_Grass_derivative': SK_5_Grass_derivative,\n",
        "                                       'SK_4_Soil_derivative ': SK_4_Soil_derivative,\n",
        "                                       'SK_4_Grass_derivative': SK_4_Grass_derivative,\n",
        "                                       'SK_3_Soil_derivative' : SK_3_Soil_derivative,\n",
        "                                       'SK_3_Grass_derivative': SK_3_Grass_derivative,\n",
        "                                       'SK_2_Soil_derivative': SK_2_Soil_derivative,\n",
        "                                       'SK_2_Grass_derivative': SK_2_Grass_derivative,\n",
        "                                       'SK_1_Soil_derivative ':SK_1_Soil_derivative,\n",
        "                                       'SK_1_Grass_derivative': SK_1_Grass_derivative,\n",
        "                                       'KB_5_Soil_derivative':  KB_5_Soil_derivative,\n",
        "                                       'KB_5_Wheat_derivative': KB_5_Wheat_derivative,\n",
        "                                       'KB_5_Drying_Wheat_derivative': KB_5_Drying_Wheat_derivative,\n",
        "                                       'KB_5_Corn_Res_derivative ': KB_5_Corn_Res_derivative,\n",
        "                                       'KB_4_Dry_Rye_derivative': KB_4_Dry_Rye_derivative,\n",
        "                                       'KB_4_Soil_derivative': KB_4_Soil_derivative,\n",
        "                                       'KB_3_Corn_Res_derivative ': KB_3_Corn_Res_derivative,\n",
        "                                       'KB_3_Soil_derivative': KB_3_Soil_derivative,\n",
        "                                       'KB_1_Corn_Res_derivative' : KB_1_Corn_Res_derivative,\n",
        "                                       'KB_1_Soil_derivative': KB_1_Soil_derivative,\n",
        "                                       'JB_5_Soil_derivative': JB_5_Soil_derivative,\n",
        "                                       'JB_5_Corn_Res_derivative': JB_5_Corn_Res_derivative,\n",
        "                                       'JB_4_Soil_derivative': JB_4_Soil_derivative,\n",
        "                                       'JB_4_Corn_Res_derivative': JB_4_Corn_Res_derivative,\n",
        "                                       'JB_3_Soil_derivative': JB_3_Soil_derivative,\n",
        "                                       'JB_3_Corn_Res_derivative': JB_3_Corn_Res_derivative,\n",
        "                                       'JB_2_Soil_derivative': JB_2_Soil_derivative,\n",
        "                                       'JB_2_Corn_Res_derivative': JB_2_Corn_Res_derivative,\n",
        "                                       'JB_1_Soil_derivative': JB_1_Soil_derivative,\n",
        "                                       'JB_1_Corn_Res_derivative': JB_1_Corn_Res_derivative,\n",
        "                                       'JB_1_Soya_Bean_derivative': JB_1_Soya_Bean_derivative,\n",
        "                                       'JB_0_Road_derivative': JB_0_Road_derivative,\n",
        "                                       'JB_Grass_Filt_derivative': JB_Grass_Filt_derivative,\n",
        "                                       'JanD_S10_Weeds_derivative': JanD_S10_Weeds_derivative,\n",
        "                                       'JanD_S9_Weeds_derivative': JanD_S9_Weeds_derivative,\n",
        "                                       'JanD_S9_Corn_Res_derivative': JanD_S9_Corn_Res_derivative,\n",
        "                                       'JanD_S8_Corn_Res_derivative': JanD_S8_Corn_Res_derivative,\n",
        "                                       'JanD_S8_Bare_Soil_derivative': JanD_S8_Bare_Soil_derivative,\n",
        "                                       'JanD_S6_Weed_derivative': JanD_S6_Weed_derivative,\n",
        "                                       'JanD_S6_Weed_2_derivative ': JanD_S6_Weed_2_derivative,\n",
        "                                       'JanD_S6_Weed_3_derivative ': JanD_S6_Weed_3_derivative,\n",
        "                                       'JanD_S6_Corn_Rewd_derivative': JanD_S6_Corn_Rewd_derivative\n",
        "                                       } )"
      ],
      "metadata": {
        "id": "MWEwd___jds0"
      },
      "execution_count": 129,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\"\"\"We want to plot the derivative spectra\n",
        "\"\"\"\n",
        "derivative_spring_2023.plot(x=\"Wavelength\", y=['ZachA_15_Weeds_derivative',\n",
        "                                        'ZachA_15_Weeds_derivative',\n",
        "                                       'ZachA_15_Soil_derivative',\n",
        "                                       'ZachA_14_Weeds_derivative',\n",
        "                                       'ZachA_14_Soil_derivative',\n",
        "                                       'ZachA_13_Weeds_derivative',\n",
        "                                       'ZachA_13_Soil_derivative',\n",
        "                                       'ZachA_12_Wheat_derivative ',\n",
        "                                       'ZachA_12_Road_derivative',\n",
        "                                       'ZachA_11_Wheat_derivative',\n",
        "                                       'ZachA_11_Soil_derivative',\n",
        "                                       'LynnW_05_CornRes_derivative',\n",
        "                                       'LynnW_05_Soil_derivative',\n",
        "                                       'LynnW_04_CornRes_derivative ' ,\n",
        "                                       'LynnW_04_Soil_derivative ',\n",
        "                                       'LynnW_03_CornRes_derivative ',\n",
        "                                       'LynnW_03_Soil_derivative',\n",
        "                                       'LynnW_02_CornRes_derivative ',\n",
        "                                       'LynnW_02_Soil_derivative',\n",
        "                                       'LynnW_01_CornRes_derivative ',\n",
        "                                       'LynnW_01_Soil_derivative',\n",
        "                                       'SK_5_Soil_derivative',\n",
        "                                       'SK_5_Grass_derivative',\n",
        "                                       'SK_4_Soil_derivative ',\n",
        "                                       'SK_4_Grass_derivative',\n",
        "                                       'SK_3_Soil_derivative' ,\n",
        "                                       'SK_3_Grass_derivative',\n",
        "                                       'SK_2_Soil_derivative',\n",
        "                                       'SK_2_Grass_derivative',\n",
        "                                       'SK_1_Soil_derivative ',\n",
        "                                       'SK_1_Grass_derivative',\n",
        "                                       'KB_5_Soil_derivative',\n",
        "                                       'KB_5_Wheat_derivative',\n",
        "                                       'KB_5_Drying_Wheat_derivative',\n",
        "                                       'KB_5_Corn_Res_derivative ',\n",
        "                                       'KB_4_Dry_Rye_derivative',\n",
        "                                       'KB_4_Soil_derivative',\n",
        "                                       'KB_3_Corn_Res_derivative ',\n",
        "                                       'KB_3_Soil_derivative',\n",
        "                                       'KB_1_Corn_Res_derivative',\n",
        "                                       'KB_1_Soil_derivative',\n",
        "                                       'JB_5_Soil_derivative',\n",
        "                                       'JB_5_Corn_Res_derivative',\n",
        "                                       'JB_4_Soil_derivative',\n",
        "                                       'JB_4_Corn_Res_derivative',\n",
        "                                       'JB_3_Soil_derivative',\n",
        "                                       'JB_3_Corn_Res_derivative',\n",
        "                                       'JB_2_Soil_derivative',\n",
        "                                       'JB_2_Corn_Res_derivative',\n",
        "                                       'JB_1_Soil_derivative',\n",
        "                                       'JB_1_Corn_Res_derivative',\n",
        "                                       'JB_1_Soya_Bean_derivative',\n",
        "                                       'JB_0_Road_derivative',\n",
        "                                       'JB_Grass_Filt_derivative',\n",
        "                                       'JanD_S10_Weeds_derivative',\n",
        "                                       'JanD_S9_Weeds_derivative',\n",
        "                                       'JanD_S9_Corn_Res_derivative',\n",
        "                                       'JanD_S8_Corn_Res_derivative',\n",
        "                                       'JanD_S8_Bare_Soil_derivative',\n",
        "                                       'JanD_S6_Weed_derivative',\n",
        "                                       'JanD_S6_Weed_2_derivative ',\n",
        "                                       'JanD_S6_Weed_3_derivative ',\n",
        "                                       'JanD_S6_Corn_Rewd_derivative'\n",
        "\n",
        "\n",
        "\n",
        "])\n",
        "plt.gca().get_legend().remove()\n",
        "plt.title(\"Derivative Spectra for all samples in 4 farms Spring 2023\")\n",
        "plt.ylabel(\"Derivative Relectance\")\n",
        "plt.xlabel(\"Wavelength (nm)\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 489
        },
        "id": "Ph47bkRzYvpw",
        "outputId": "1815207e-787b-4444-b499-f7b41e1313b7"
      },
      "execution_count": 130,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 0, 'Wavelength (nm)')"
            ]
          },
          "metadata": {},
          "execution_count": 130
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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jGY1GraSk5Hdv87777tMyMzPD56e6DD+NHz++xuGn2p5zQr+38+bNq3I89Nrp3r17lZ/DddddpymKoo0YMaLK5fv166e1b98+/HV9n2NVVbUhQ4ZogJaenq5dd9112muvvVblNRYS+h0fOXJkleO33367Bmjr1q0LHwM0g8Ggbdq0qdrtHPkaDN3uTTfdVOVyV1xxhZacnBz++rffftMAbdKkSVUuN2HChGq3WVs7duzQbDabdsMNN1Q5brfbq8WjaZr29ddf1/jzq6ywsFBLS0vTBg0aVOP3b731Vg0IP0ejR4/WioqK6hz775Hhp+MQExMTLt0VFRWxaNEirr76asrLyykoKKCgoIDCwkIuvPBCduzYQU5OTpXr33zzzeFKx9HExcUxYsQIZs2aFa4AAHz88cf07duXdu3ahY9FRUWF/19aWkpBQQFDhgxh9+7dlJaW1vnxKYrCmDFj+Oabb3A4HFXuu3Xr1uFhlu+++46SkhKuu+668OMuKCjAaDRyzjnnsHjx4mPeT7du3Vi7di1/+tOfyMrKYurUqYwaNYr09HTefvvtapdv1apVlYpEaNhgzZo14U8Kn3zyCYMGDSIxMbFKTMOGDSMQCLBs2TIAZs+ejaIoNc6yOton9Zr89a9/rXas8s/D7XZTUFBA3759AarNJqitb775hrPPPjv83IP+OrzlllvIyspi8+bNVS4/fvz4KnEcS+XLFRcXU1payqBBg+od65ESEhL4+eefyc3NrVUMTqeTgoIC+vfvj6ZprFmzptrl//KXv1S5/c6dO2O327n66qvDxzt37kxCQkKNJfFbbrkFs9kc/vq2227DZDLxzTffHDXGTz75hNNOO40uXbpUeW2Fqoyh13tCQgKgN2oeOeRZX7fcckuV1+WgQYMIBAJkZ2cf83rbt29n6tSpvPDCCxGdhFCXc05mZiYXXnhhjbczbty4Kj+Hc845B03TuOmmm6pc7pxzzmHfvn34/X6g/s+xoijMnz+fp59+msTERD788EMmTpxI+/btueaaa2ocFjmy8nTnnXcCVHutDBkyhK5du9Y6liPPHYMGDaKwsDA8VBwavrr99ttrvP+6qqioYMyYMURFRfHPf/6zyvdcLleNr49QU/mRw8AhqqoyduxYSkpK+Pe//13jZSZNmsR3333HjBkzGDFiBIFAAK/XW6/HcCyS1BwHh8NBbGwsoM/g0TSNxx57jNTU1Cp/Qm+Y+fn5Va5/ZCn8aK655hr27dvHihUrAH08+LfffqtWuvvxxx8ZNmwYdrudhIQEUlNTw2PL9UlqQvftcrnCfUEOh4NvvvmGMWPGhE+uO3bsAPReoyMf+4IFC6o97pqceuqpvPfeexQUFLB+/XqeffZZTCYTt9xyS7Wph506daqWcJx66qkA4V6kHTt2MG/evGrxDBs2DDj8s9i1axetWrUiKSmpXs9PSE0/y6KiIu6++27S09OJiooiNTU1fLn6/jyys7OrlO1DTjvttPD3fy+uo/nqq6/o27cvNpuNpKQkUlNTeeONN+od65Gef/55Nm7cSNu2bTn77LN58sknqyUae/fuZcKECSQlJRETE0NqaipDhgwBqj9nof6nyuLj42nTpk2110d8fHyNvTKh2RwhMTExtGzZ8pjrRO3YsYNNmzZVe22FXoOh19Y111zDgAED+Mtf/kJ6ejrXXnsts2bNOq4Ep/KHGIDExESA3+0Duvvuu+nfvz9XXXVVve+7JnU55xzrtXjk44qPjwegbdu21Y6rqhq+7eN5jq1WK4888ghbtmwhNzeXDz/8kL59+4aHjo505GulY8eOGAyGaq+VuvzOwe//TLOzszEYDNVut1OnTnW6H9CHbEMzlD799FNatWpV5ftRUVHVepaAcO/Q0T4g3XnnncybN4933nmHM844o8bLdOnShWHDhjFu3Di++uorHA4Hl112WZUP65EgPTX1tH//fkpLS8MvrNAv0X333XfUTyNHvghr+wn6sssuIzo6mlmzZtG/f39mzZqFwWCo0ueya9cuzj//fLp06cLLL79M27ZtsVgsfPPNN7zyyiv1PpH27duXjIwMZs2axfXXX8/cuXNxuVxVEqrQbb/33ns1jtXXZRqj0WikR48e9OjRg379+nHeeecxc+bMcDJSW6qqMnz4cP7+97/X+P3QG1Ck1PSzvPrqq/npp5+4//77OfPMM4mJiUFVVS666KKIfXKvT1w1Wb58OSNHjmTw4MG8/vrrtGzZErPZzLRp06o12dbX1VdfzaBBg/j8889ZsGABL7zwAlOmTOGzzz4Lf3IbPnw4RUVFPPDAA3Tp0gW73U5OTg4TJkyo9pwdrcp5tOOROnmqqkqPHj14+eWXa/x+6I04KiqKZcuWsXjxYr7++mvmzZvHxx9/zNChQ1mwYMHvVmlrUp/HtmjRIubNm8dnn31W5Q3Y7/fjcrnIysoiKSmJuLi4OsVS13POsV6L9f1ZRuo5btmyJddeey1XXXUV3bp1Y9asWUyfPv2Y566jVXJr+zsX0tCv18puvvlmvvrqK2bOnFlj/2LLli05cOBAteOhY0cmQQCTJ0/m9ddf55///Cc33HBDrWMZPXo0t956K9u3b6/xg1p9SVJTT++99x5AOIEJzVAym811fgP+PXa7nUsvvZRPPvmEl19+mY8//phBgwZVeYHNnTsXj8fDnDlzqmT+NQ391GVYBfQ3o6lTp1JWVsbHH39MRkZGeBgFDjfNpqWlRfSxh2Z2HflLFqqKVX4c27dvBwg35XXs2BGHw/G78XTs2JH58+dTVFR0zGpNXZ+z4uJivv/+eyZPnhxuaoTDVa36at++Pdu2bat2PLRYWE0zyGpj9uzZ2Gw25s+fX6X8PG3atPoFehQtW7bk9ttv5/bbbyc/P59evXrxzDPPMGLECDZs2MD27duZMWNGlebo7777LqIxVLZjxw7OO++88NcOh4MDBw5w8cUXH/U6HTt2ZN26dZx//vm/+7owGAycf/75nH/++bz88ss8++yzPPLIIyxevDji54mj2bt3L0CVGS0hOTk5ZGZm8sorrzBp0qQ63W5dzjkNKZLPsdls5vTTT2fHjh0UFBRU+ZC2Y8eOKtWSnTt3oqrq7zYCH6/27dujqip79uypUi3auXNnnW7n/vvvZ9q0abz66qtcd911NV7mzDPPZPny5aiqWqVZ+OeffyY6Orrah8HXXnuNJ598kkmTJvHAAw/UKZ7QUFakKsEhMvxUD4sWLeKpp54iMzOTsWPHAvob+rnnnsubb75ZY6Zbl2mXNbnmmmvIzc3lnXfeYd26ddWGnkLZfuXsvrS0tMY3JbvdXqepdNdccw0ej4cZM2Ywb968Kv0KoCd2cXFxPPvss/h8vmrX/73Hvnz58hqvFxqrPjKLz83N5fPPPw9/XVZWxrvvvsuZZ54ZPgldffXVrFixgvnz51e73ZKSkvCY/FVXXYWmaTUu8Ff5uazrc1bTzwM47q0OLr74Yn755ZfwUCTovSdvvfUWGRkZdRrLr8xoNKIoSpUp+llZWRFbRTkQCFQ7eaWlpdGqVatwubum50zTNKZOnRqRGGry1ltvVXntvfHGG/j9fkaMGHHU61x99dXk5OTU2O/lcrnCMxmLioqqfT+0vUBNJf6GMnToUD7//PNqf1JTU+nTpw+ff/45l112WZ1vty7nnIZS3+d4x44d4WSvspKSElasWEFiYmK1oc3QcgEhod6RY71WIiH0wfn111+v8f5r44UXXuDFF1/k4Ycf5u677z7q5UaPHs3BgwerLJFRUFDAJ598wmWXXVblA8/HH3/MXXfdxdixY49atYTqbRcAPp+Pd999l6ioqHqfs45GKjW/49tvv2Xr1q34/X4OHjzIokWL+O6772jfvj1z5sypsirna6+9xsCBA+nRowc333wzHTp04ODBg6xYsYL9+/ezbt26esdx8cUXExsby3333YfRaKw2Nn7BBRdgsVi47LLLuPXWW3E4HLz99tukpaVVS7J69+7NG2+8wdNPP02nTp1IS0s75lTqXr160alTJx555BE8Hk+1hCouLo433niDG264gV69enHttdeSmprK3r17+frrrxkwYAD/+c9/jnr7U6ZM4bfffuPKK68Mr9C8evVq3n33XZKSkqp9gjz11FP585//zKpVq0hPT+f//u//OHjwYJWT6f3338+cOXO49NJLmTBhAr1798bpdLJhwwY+/fRTsrKySElJ4bzzzuOGG27gX//6Fzt27AgPDS1fvpzzzjsvPLbeu3dvFi5cyMsvv0yrVq3IzMzknHPOOepjiouLC0819vl8tG7dmgULFrBnz56jXqc2HnzwQT788ENGjBjBXXfdRVJSEjNmzGDPnj3Mnj273qvQXnLJJbz88stcdNFFXH/99eTn5/Paa6/RqVMn1q9ff1wxgz6duE2bNowePZozzjiDmJgYFi5cyKpVq3jppZcAfcy9Y8eO3HfffeTk5BAXF8fs2bNrtW5MfXm9Xs4//3yuvvpqtm3bxuuvv87AgQMZOXLkUa9zww03MGvWLP7617+yePFiBgwYQCAQYOvWrcyaNSu8Fss//vEPli1bxiWXXEL79u3Jz8/n9ddfp02bNlUavRtau3btqvVtgN64mZ6eXu9Vsutyzmko9X2O161bx/XXX8+IESMYNGgQSUlJ5OTkMGPGDHJzc3n11VerDQvt2bOHkSNHctFFF7FixQref/99rr/++qP2kERK7969ueqqq3j11VcpLCwMT+kOVad/r1r4+eef8/e//51TTjmF0047rdraasOHDw8v6zF69Gj69u3LjTfeyObNm8MrCgcCgSof/H755RfGjRtHcnIy559/PjNnzqxym/379w+PXtx6662UlZUxePBgWrduTV5eHjNnzmTr1q289NJLxMTEHPdzVEXE51M1E6EplKE/FotFa9GihTZ8+HBt6tSpWllZWY3X27VrlzZu3DitRYsWmtls1lq3bq1deuml2qefflrttmuaLn7klO7Kxo4dG57WWZM5c+Zop59+umaz2bSMjAxtypQp2v/93/9Vu728vDztkksu0WJjYzUgPF31WFNzH3nkEQ3QOnXqdNTnbPHixdqFF16oxcfHazabTevYsaM2YcIE7ddffz3qdTRN03788Udt4sSJWvfu3bX4+HjNbDZr7dq10yZMmKDt2rWrymVD01Dnz5+vnX766ZrVatW6dOlSZQXMkPLycu2hhx7SOnXqpFksFi0lJUXr37+/9uKLL1aZPur3+7UXXnhB69Kli2axWLTU1FRtxIgR2m+//Ra+zNatW7XBgweHp56HptuGpmXWNKV0//792hVXXKElJCRo8fHx2pgxY7Tc3NxaT8Okhindmqa/xkaPHq0lJCRoNptNO/vss7WvvvqqymVCP8uanpej+d///qedcsop4ed02rRp4cdXWX2mdHs8Hu3+++/XzjjjDC02Nlaz2+3aGWecob3++utVLrd582Zt2LBhWkxMjJaSkqLdfPPN2rp16zRAmzZtWvhyR5tiPGTIEK1bt27Vjh85fTn0e7Z06VLtlltu0RITE7WYmBht7NixWmFhYbXbPHIJBK/Xq02ZMkXr1q2bZrVatcTERK13797a5MmTtdLSUk3T9JXHL7/8cq1Vq1aaxWLRWrVqpV133XXVlhmoydGmdB95zjie1ZwjMaW7tueco93X0V6nR3u8R/6+1fc5PnjwoPbPf/5TGzJkiNayZUvNZDJpiYmJ2tChQ6ucqyvf5+bNm7XRo0drsbGxWmJionbHHXdUWy34aL+zoe/VNKX7yHNHTe8BTqdTmzhxopaUlKTFxMRoo0aN0rZt26YB2j//+c9jPtbQ/Rztz5GvnaKiIu3Pf/6zlpycrEVHR2tDhgyp9nM48v3xyD+Vf1c//PBDbdiwYVp6enr4eR42bFiVZRMiSdG0BuhGEqKBZGRk0L17d7766qvGDkU0YdOnT+fGG29k1apVVVblFuJITz75JJMnT+bQoUM1LirXWNauXUvPnj15//33w20QQnpqhBBCiJNaTevDvPrqqxgMBgYPHtwIEZ28pKdGCCGEOIk9//zz/Pbbb5x33nmYTCa+/fZbvv32W2655ZZqa/n80UlSI4QQQpzE+vfvz3fffcdTTz2Fw+GgXbt2PPnkk+H9+8Rh0lMjhBBCiGZBemqEEEII0SxIUiOEEEKIZuEP1VOjqiq5ubnExsbWedl7IYQQQjQOTdMoLy+nVatWx1xk9A+V1OTm5kqnuBBCCNFE7du3jzZt2hz1+3+opCY2NhbQn5S67kgrhBBCiMZRVlZG27Ztw+/jR/OHSmpCQ05xcXGS1AghhBBNzO+1jkijsBBCCCGaBUlqhBBCCNEsSFIjhBBCiGZBkhohhBBCNAuS1AghhBCiWZCkRgghhBDNgiQ1QgghhGgWJKkRQgghRLMgSY0QQgghmgVJaoQQQgjRLEhSI4QQQohmQZIaIYQQQjQLktQIIRqNR1XZ6/Jw0ONr7FCEEM2AJDVCiEazqdzF2Su3cOnqHY0dihCiGZCkRgjRaALBf41Ko4YhhGgmmkxSEwgEeOyxx8jMzCQqKoqOHTvy1FNPoWlaY4cmhKinQPD314hkNUKI42dq7ABqa8qUKbzxxhvMmDGDbt268euvv3LjjTcSHx/PXXfd1djhCSHqIZTUGCSnEUJEQJNJan766Scuv/xyLrnkEgAyMjL48MMP+eWXXxo5MiFEfanBQqtRkaxGCHH8mszwU//+/fn+++/Zvn07AOvWreOHH35gxIgRjRyZEKK+AgSHnySnEUJEQJOp1Dz44IOUlZXRpUsXjEYjgUCAZ555hrFjxx71Oh6PB4/HE/66rKzsRIQqhKilQKhSIz01QogIaDKVmlmzZjFz5kw++OADVq9ezYwZM3jxxReZMWPGUa/z3HPPER8fH/7Ttm3bExixEOL3HO6pkaRGCHH8FK2JTB9q27YtDz74IBMnTgwfe/rpp3n//ffZunVrjdepqVLTtm1bSktLiYuLa/CYhRDHNu9QKRM27qF3XDRf9z61scMRQpykysrKiI+P/9337yYz/FRRUYHBULWwZDQaUVX1qNexWq1YrdaGDk0IUU+He2qkUiOEOH5NJqm57LLLeOaZZ2jXrh3dunVjzZo1vPzyy9x0002NHZoQop5CPTVNZhxcCHFSazJJzb///W8ee+wxbr/9dvLz82nVqhW33norjz/+eGOHJoSoJ1WTSo0QInKaTFITGxvLq6++yquvvtrYoQghIiS8orDkNEKICJCqrxCi0Rze+0myGiHE8ZOkRgjRaMJTumWdGiFEBEhSI4RoNIe3SWjcOIQQzYMkNUKIRhOQRmEhRARJUiOEaDShnhrZpVsIEQmS1AghGo1UaoQQkSRJjRCi0YTXqWnkOIQQzYMkNUKIRhPepVsqNUKICJCkRgjRaA7v0t3IgQghmgVJaoQQjSa0Ha1UaoQQkSBJjRCi0YQbhWXxPSFEBEhSI4RoNOFduiWnEUJEgCQ1QohGI1O6hRCRJEmNEKLRHO6padQwhBDNhCQ1QohGIz01QohIkqRGCNFoZEq3ECKSJKkRQjQaVRbfE0JEkCQ1QohGE0AahYUQkSNJjRCi0YSndDduGEKIZkLOJUKIRiNTuoUQkSRJjRCi0RzuqWncOIQQzYMkNUKIRiM9NUKISJKkRgjRaMJTuhs5DiFE8yDnEiFEo5Ep3UKISJKkRgjRaA43CjdyIEKIZkGSGiFEowkE/zVIpUYIEQGS1AghGo1M6RZCRJIkNUKIRhPuqWncMIQQzYQkNUKIRiOVGiFEJElSI4RoNOFtEiSnEUJEgCQ1QohG41dV8AbwegO/f2EhhPgdktQIIRpNeZEL2+I8Xn1/fWOHIoRoBiSpEUI0moCq/2uU8SchRARIUiOEaDQBVc9qDHImEkJEgJxKhBCNJjSl2yCVGiFEBEhSI4RoNIFgViPDT0KISJCkRgjRaEJJjWyTIISIBElqhBCNRg0mNSap1AghIkCSGiFEo1GDKwpLT40QIhIkqRFCNBrpqRFCRJIkNUKIRhMafpK9n4QQkSBJjRCi0aiy+J4QIoIkqRFCNBpV07MaSWqEEJEgSY0QotFIpUYIEUmS1AghGk1o9pNJ9kkQQkSAnEmEEI0m3CgsZyIhRATIqUQI0WhCez8ZpVIjhIgAOZMIIRqNGmyqkRWFhRCRIEmNEKLRaOFKjSQ1Qojj16SSmpycHP70pz+RnJxMVFQUPXr04Ndff23ssIQQ9SR7PwkhIsnU2AHUVnFxMQMGDOC8887j22+/JTU1lR07dpCYmNjYoQkh6ilUqZGkRggRCU0mqZkyZQpt27Zl2rRp4WOZmZmNGJEQ4nhpmlRqhBCR02SGn+bMmUOfPn0YM2YMaWlp9OzZk7fffruxwxJCHAdVNrQUQkRQk0lqdu/ezRtvvMEpp5zC/Pnzue2227jrrruYMWPGUa/j8XgoKyur8kcIcfLQZPE9IUQENZnhJ1VV6dOnD88++ywAPXv2ZOPGjfz3v/9l/PjxNV7nueeeY/LkyScyTCFELWmadrinxiiVGiHE8WsyH49atmxJ165dqxw77bTT2Lt371Gv89BDD1FaWhr+s2/fvoYOUwhRSyqANAoLISKoyVRqBgwYwLZt26oc2759O+3btz/qdaxWK1artaFDE0LUQ0DTwtOfzJLUCCEioMlUau655x5WrlzJs88+y86dO/nggw946623mDhxYmOHJoSoh4BGpUpNkzkVCSFOYk3mTHLWWWfx+eef8+GHH9K9e3eeeuopXn31VcaOHdvYoQkh6kHVNBl+EkJEVJMZfgK49NJLufTSSxs7DCFEBAQgPPwkSY0QIhKaTKVGCNG8BCpVasxGORUJIY6fnEmEEI0ioIEijcJCiAiSpEYI0Sgq99TIisJCiEiQpEYI0SgCSKOwECKyJKkRQjQKfUq37P0khIgcSWqEEI0iUGX4SU5FQojjJ2cSIUSjUCstvieTn4QQkSCnEiFEo9B7akLDT3IqEkIcPzmTCCEaRdVtEqSnRghx/CSpEUI0CrXShpYGSWqEEBEgSY0QolEENA1FKjVCiAiSpEYI0Sj0vZ/0/xsUSWqEEMdPkhohRKMIVBp+kkqNECISJKkRQjSKqlO6JakRQhw/SWqEEI0iIHs/CSEiTJIaIUSjqLxNggw/CSEiQZIaIUSjUCttaClTuoUQkSBJjRCiUUilRggRaZLUCCEaReWeGqnUCCEiQZIaIUSjkMX3hBCRJkmNEKJRqFBpQ0tJaoQQx++4khq32x2pOIQQfzAypVsIEWl1TmpUVeWpp56idevWxMTEsHv3bgAee+wx/ve//0U8QCFE8yS7dAshIq3OSc3TTz/N9OnTef7557FYLOHj3bt355133olocEKI5qvyNgmy95MQIhLqnNS8++67vPXWW4wdOxaj0Rg+fsYZZ7B169aIBieEaL70nhr9/yaDtPcJIY5fnc8kOTk5dOrUqdpxVVXx+XwRCUoI0fxVqdRITiOEiIA6n0q6du3K8uXLqx3/9NNP6dmzZ0SCEkI0f5UbhaVSI4SIBFNdr/D4448zfvx4cnJyUFWVzz77jG3btvHuu+/y1VdfNUSMQohmSHbpFkJEWp0/Hl1++eXMnTuXhQsXYrfbefzxx9myZQtz585l+PDhDRGjEKIZ8mkqoVRGkhohRCTUuVIDMGjQIL777rtIxyKE+APxB7Tw/yWpEUJEQp0rNatWreLnn3+udvznn3/m119/jUhQQojmz6dKUiOEiKw6JzUTJ05k37591Y7n5OQwceLEiAQlhGj+ApUqNbL4nhAiEuqc1GzevJlevXpVO96zZ082b94ckaCEEM2fT1XD/5fF94QQkVDnpMZqtXLw4MFqxw8cOIDJVK8WHSHEH1Dl4Sep1AghIqHOSc0FF1zAQw89RGlpafhYSUkJDz/8sMx+EkLUWqBSUmOQpEYIEQF1Lq28+OKLDB48mPbt24cX21u7di3p6em89957EQ9QCNE8+QP68JOMPAkhIqXOSU3r1q1Zv349M2fOZN26dURFRXHjjTdy3XXXYTabGyJGIUQz5A+21ChSpRFCREi9mmDsdju33HJLpGMRQvyB+DQ9q5EmYSFEpNQrqdmxYweLFy8mPz8ftdIMBtC3URBCiN8TmtKtyLZPQogIqXNS8/bbb3PbbbeRkpJCixYtUCp9ylIURZIaIUSt+IONwopUaoQQEVLnpObpp5/mmWee4YEHHmiIeIQQfxChpEaGn4QQkVLnwm9xcTFjxoxpiFiEEH8ggVBPjTQKCyEipM5JzZgxY1iwYEFDxCKE+AMJ99RITiOEiJA6Dz916tSJxx57jJUrV9KjR49q07jvuuuuiAUnhGi+wsNPUqkRQkRInZOat956i5iYGJYuXcrSpUurfE9RFElqhBC1Ij01QohIq3NSs2fPnoaIQwjxB6NqUqkRQkSWrBAhhGgUhys1jRyIEKLZqNfie/v372fOnDns3bsXr9db5Xsvv/xyRAITQjRvoUZhqdQIISKlzknN999/z8iRI+nQoQNbt26le/fuZGVloWkavXr1aogYhRDNUECGn4QQEVbn4aeHHnqI++67jw0bNmCz2Zg9ezb79u1jyJAhJ3T9mn/+858oisKkSZNO2H0KISInII3CQogIq3NSs2XLFsaNGweAyWTC5XIRExPDP/7xD6ZMmRLxAGuyatUq3nzzTU4//fQTcn9CiMgLJTVGqdQIISKkzkmN3W4P99G0bNmSXbt2hb9XUFAQuciOwuFwMHbsWN5++20SExMb/P6EEA0jIOvUCCEirM5JTd++ffnhhx8AuPjii/nb3/7GM888w0033UTfvn0jHuCRJk6cyCWXXMKwYcMa/L5EA9A02LkQtn0LB9aBGmjsiEQjUSWpEUJEWJ0bhV9++WUcDgcAkydPxuFw8PHHH3PKKac0+Mynjz76iNWrV7Nq1apaXd7j8eDxeMJfl5WVNVRoorZ2L4b3rzr89Wkj4Zr3Gi8e0WhCjcJGyWmEEBFS56SmQ4cO4f/b7Xb++9//RjSgo9m3bx9333033333HTabrVbXee6555g8eXIDRybqJH+L/q8pCvwu2F+7BFU0P9JTI4SItDoPP3Xo0IHCwsJqx0tKSqokPJH222+/kZ+fT69evTCZTJhMJpYuXcq//vUvTCYTgUD1YYyHHnqI0tLS8J99+/Y1WHyilspy9X87X6T/6zxE+aLvcW3c1HgxiUYhw09CiEirc6UmKyurxgTC4/GQk5MTkaBqcv7557Nhw4Yqx2688Ua6dOnCAw88gNForHYdq9WK1WptsJhEPYSSmhanw6bPQfWTO+l2lLg0Tlm+DEWm9/5hqKr+r1F+5kKICKl1UjNnzpzw/+fPn098fHz460AgwPfff09GRkZEg6ssNjaW7t27Vzlmt9tJTk6udlycxMoP6P8mZoA1HjylmGwBvAUF+A8exNyiRaOGJ06cgKZnNTL8JISIlFonNaNGjQL0nbjHjx9f5Xtms5mMjAxeeumliAYnmqGyYDUvrhXEpOpJjVXFC3h27JCk5g9Ehp+EEJFW66RGDdaKMzMzWbVqFSkpKQ0WVG0tWbKksUMQdaFpUJ6n/z+uFdhToXAnRpv+2vJs30HMoEGNGKA4kULDTyZJaoQQEVLnnpo9e/Y0RBzij6CiEALBDVBjWuhJDWAKJTU7dzZWZKIRqJrMfhJCRFadZz/ddddd/Otf/6p2/D//+Y/swySOLTT0ZE8DkyWc1BiteuO5Z8eOxopMNAKZ0i2EiLQ6JzWzZ89mwIAB1Y7379+fTz/9NCJBiWaqLNgkHNdS/7eGSo0WGpMQzZ5UaoQQkVbnpKawsLDKzKeQuLi4E7L3k2jCwk3CrfV/Y6omNZrbjW///saITDQCTaZ0CyEirM5JTadOnZg3b161499++22DLr4nmoHQdO5YvVKjWvUNSY22AKbgrCfpq/njCM1+MhnrfBoSQoga1blR+N577+WOO+7g0KFDDB06FIDvv/+el156iVdffTXS8Ynm5Ijhp4DXhAEw2TSi+/Sh7Kuv8GzfQWzwdSWat/Dwk1RqhBARUuek5qabbsLj8fDMM8/w1FNPAZCRkcEbb7zBuHHjIh6gaEaOGH7yO1TMgNGmciDBgh1pFv4jCSU1MqVbCBEpdU5qAG677TZuu+02Dh06RFRUFDExMZGOSzRHRww/eUv8RAFGk8oMx7fcjiQ1fyRaePhJkhohRGTUazDb7/ezcOFCPvvsM7Tgp63c3FwcDkdEgxPNTGjfp1ClpqAUNbiNWEFcBQCePXvQ/P7GiE6cYMGcRmY/CSEips6VmuzsbC666CL27t2Lx+Nh+PDhxMbGMmXKFDweD//9738bIk7R1HnKwVOm/z/YU+M7mE/AbcRgD2CMCgAm8PlQnU6MNcywE81LuFFYkhohRITUuVJz991306dPH4qLi4mKigofv+KKK/j+++8jGpxoRkJNwtY4sMYC4M/Lw+/RX4LxaKhmfad1VSp+fwiarFMjhIiwOldqli9fzk8//YTFYqlyPCMjg5ycnIgFJpqZ8uDQU7CfBqDiwH4SkvSkJjkQwGszYfMFCDicmBsjRnFCBXMazJLUCCEipM6VGlVVCQQC1Y7v37+f2NjYiAQlmqEjVxMGXLn78bv1l2BSIIA7mCerTueJjk40Ai28TYKsUyOEiIw6n00uuOCCKuvRKIqCw+HgiSee4OKLL45kbKI5cR7S/41JB0Dz+zEVl+N360NOyQEVp0V/k1OdMvz0R6DJlG4hRITVefjppZde4sILL6Rr16643W6uv/56duzYQUpKCh9++GFDxCiaA2+w+mLRp//n79+OQQOf9/DwU7lZrwBKpeaPITz8JFO6hRARUuekpk2bNqxbt46PPvqI9evX43A4+POf/8zYsWOrNA4LUYU3WH2x2AHYtf0XEoFSDLREH37aadY3A5JG4T+G8Do1igw/CSEio16L75lMJv70pz9FOhbRnIUrNXpSU5q3l0SgyBCq1KhssOoXCUhS84cQqtTI4ntCiEipVVIzZ86cWt/gyJEj6x2MaMZ8+uJ6oaSmIv8AB+OiKQm+ApMCAVzSKPyHomkaCtJTI4SInFolNaNGjarVjSmKUuPMKCGOrNQ4cvLIymxJrMkN5BKrqriClRrVIUnNH0EoqZGeGiFEpNQqqVFVtaHjEM1dqKfGrCc1vhIHYMWr6i9BC+CVSs0fihY8rUhPjRAiUo7rbOJ2uyMVh2juvFWHnwJOHwAutPBFVIs0Cv9RqJoGMvtJCBFhdU5qAoEATz31FK1btyYmJobdu3cD8Nhjj/G///0v4gGKZqLS8JOmaWg+/R2tJMaJV9Vfhkpo+EkqNc1eQCPcKWyWxfeEEBFS57PJM888w/Tp03n++eerbJXQvXt33nnnnYgGJ5oP1aNXX/Y5FMq8ZaDpw07eBFN4CMqkr8Mns5/+AAKahiKzn4QQEVbnpObdd9/lrbfeYuzYsRiNxvDxM844g61bt0Y0ONF8eFzlAExdnkueMw+/QU9klLR4/OjJcWgYwucoa5wgxQkTqDTsaJHZT0KICKlzUpOTk0OnTp2qHVdVFZ/PF5GgRPNj9Os9NT/neNiaux+vSU9q1BZJOFV9+0pL8L1NKjXNn6qF/pK9n4QQkVPns0nXrl1Zvnx5teOffvopPXv2jEhQoplRVSyq3lReoVlZvCoHTVFQVI0DtjgcAb1SYwsmNZr01DR7gUqNwhYZfhJCREidVxR+/PHHGT9+PDk5Oaiqymeffca2bdt49913+eqrrxoiRtHUhRbeA5zYWJ1dQVvA6vexu9BEhWYDILTJhuZ0nfgYxQlVuVHYYpRKjRAiMup8Nrn88suZO3cuCxcuxG638/jjj7Nlyxbmzp3L8OHDGyJG0dQFZz6pmoIbC3vdCTiNUZhUPwVlZhzoSU10cN0SxedD9XobK1pxAqgcrtSYFKnUCCEio157Pw0aNIjvvvuu2vFff/2VPn36HHdQopkJLrxXgRWTwYBf1dgV3YF050E0fwzlWjQAUYd7R1GdTgyVZteJ5iVQ6WdtkkqNECJC6nw2cTgcuFxVhwfWrl3LZZddxjnnnBOxwEQzEhx+qsDG8K7pAGRFt8dv8qMF7LjRk5oYTcMTTLNlrZrmLaBplRqFGzkYIUSzUevTyb59++jXrx/x8fHEx8dz7733UlFRwbhx4zjnnHOw2+389NNPDRmraKqCw09OzUq/DskAlJli8Zj9pGlx2Ox6kmzXKu//JDOgmrPK69TI7CchRKTUevjp/vvvx+12M3XqVD777DOmTp3K8uXLOeecc9i1axdt2rRpyDhFExZwOzACLmy0TtL7J5wmO06bn1YGD5rVAy6I1gLkWYwkOKVS09xV3k3OKD01QogIqXVSs2zZMj777DP69u3L1VdfTYsWLRg7diyTJk1qwPBEc+BylhEDOLESG60vrOc1WCmMMZAcn4uCD1wQpQSkUvMHUXX4SZIaIURk1Lrue/DgQTIzMwFIS0sjOjqaESNGNFhgovlwOfVExqNEUVKShVnVZzblRSeSHJOD1e4BwKr4cVj0l6RUapq3qo3CktQIISKjToPZhkpj3waDocreT0IcjTuY1PiNUeQdyCLGrycshZY0UqKKsNn1RmKLMYDLqm+9IasKN2+VKzUGGX4SQkRIrYefNE3j1FNPRQmegBwOBz179qyS6AAUFRVFNkLR5HmD+z75TdEU5edgD1goJpFSUzIpUdnYy9sDh7Aa/LgsRsCH6pBKTXNWuafGJMNPQogIqXVSM23atIaMQzRjvmBSo5rsOAoKiPGnAeAwJNM+tSXKoVTgV8yGAG6zDD/9EVTeJkF6aoQQkVLrpGb8+PENGYdoxgLu4FCSJRpffiH2gJ6w+IgniiisJSUAWA0BvKZgUiPDT81aoMqGlpLUCCEiQxaIEA1O9ehJjGKxYyz2YQ/21CS5WnJodRQ2t767u6KAEkxqAlKpadZU7XCnsCQ1QohIkaRGNLzg4nuKNQazQyMmWKkx+GLZt2kURpc/9KEdk94njK+8tDEiFSeIX1UrLb4nSY0QIjIkqRENTvHpSYxmsWD2KeFKjcMAqmZli+NsvMGR0GBLjSQ1zZy/8pRuSWqEEBEiSY1ocIbg3k8+kwmDerhS41A0VDR2eM7Ci748gDU4u84vPTXNmjdweP6TQZIaIUSE1Dup8Xq9bNu2Db/fH8l4RDNkCuhJjduooika0YEKFE1DU8BgOgQY8AXsAEQFrxNwlDdOsOKE8KuHSzVSqRFCREqdk5qKigr+/Oc/Ex0dTbdu3di7dy8Ad955J//85z8jHqBo+swBfcNKp0//16iq2DX9jcyevBoAbyAGgKhgo4VWUXGiwxQnkK9ypUYW3xNCREidk5qHHnqIdevWsWTJEmw2W/j4sGHD+PjjjyManGgeLKqezDhceqJiViFGDW5s2f40ALyaXqmxEdCv5HSd4CjFieSVSk2je3pXLpO27GWb093YoQgRMXVOar744gv+85//MHDgwPDqwgDdunVj165dEQ1ONA82TT9pVpTq/xo1czipsbQ/C7MlgFcLVWpUAoqC4nKjVZr2K5qXgCpTuhvbt4dK+SiviGKftBCI5qPOSc2hQ4dIS0urdtzpdFZJcoQAcPsCRKMnM75SfeNKRYkmNjj8VOo3Y40xhCs1FoMfn9GAwa+ieb2NE7RocP5KO1rKeaNxOINDgHajzBcRzUedX819+vTh66+/Dn8dOiG988479OvXL3KRiWahxOEmStGTE3OJPrSkmRLClZq8Mje2WDM+LRoAiyGAN7hYjawq3HxVBPTXgiJVmkbjCP4MYozGRo5EiMip9TYJIc8++ywjRoxg8+bN+P1+pk6dyubNm/npp59YunRpQ8QomrCy8jJaBP9vLVcosMfy+ZDLSMgyg8tPTpGD1gU5dFD0eU9WQ4Aiq4U4dzCpSU5uvOBFgynxBZMayWkahaZpUqkRzVKdX80DBw5k7dq1+P1+evTowYIFC0hLS2PFihX07t27IWIE4LnnnuOss84iNjaWtLQ0Ro0axbZt2xrs/kRkOMpKAFBRMLlVFg68jJ3tWrKmi16Z2V/owBSVj1cNVmqMARw2/ZNjoFwqNc1VqVffGkPWqGkcFaoa2k8Uu0mSGtF81LlSA9CxY0fefvvtSMdyTEuXLmXixImcddZZ+P1+Hn74YS644AI2b96M3W4/obGI2nM6ywBwYWN72/bszOwKgBqlJy6FFR5atl+Dd7Nez7EY/DitwU0ty8saIeKG4/D4+Wb9Ac7tnEpanO33r9CMlQUrNTKdu3FUBKs0ChBtkKRGNB91TmqGDRvGn/70J6688kri4uIaIqYazZs3r8rX06dPJy0tjd9++43BgwefsDhE3bgcemLiVmx8PXAoAD13FLK9hZ0AUOE3YrCV4tUyAb2nxm0JVWqazwJ8W/PKuP391ewucHLd2W157srTGzukRhVKamTmU+Nw+A8PPUmjtmhO6pyid+vWjYceeogWLVowZswYvvzyS3w+X0PEdkylpfreQElJSSf8vkXteSr0pKZCsVIam0BceTHDV5dx2YFtBCdAUWHy4lMPNwp7zMFG4WaS1GzMKWXUaz+yu0DfHuJQuczqKvNLUtOYnMEmYemnEc1NnV/RU6dOJScnhy+++AK73c64ceNIT0/nlltuOWGNwqqqMmnSJAYMGED37t2PejmPx0NZWVmVP+LE8lToiUmFYgWgU9ZWLFoUHXI3hHevzDHG49X0RmF99pN+PFDWPJKar9YfwO1TsQUfrztYpfgjK/dKUtOYHMHhJ5n5JJqbeqXpBoOBCy64gOnTp3Pw4EHefPNNfvnlF4YOHRrp+Go0ceJENm7cyEcffXTMyz333HPEx8eH/7Rt2/aExCcOC7j1Zt8K9B6SaJcLRbFgrijGZNZPrLu0tnjRkx6r0Y/P0LwqNS6vvrhZuyS9GiVJDTiClRpZTbhxhJIaaRIWzc1xvaLz8vL473//y5QpU1i/fj1nnXVWpOI6qjvuuIOvvvqKxYsX06ZNm2Ne9qGHHqK0tDT8Z9++fQ0en6hK8waTGkVPauwufejFGPATbdIX5cuq6IBq0YcwLYYAarBx0RecOdXUuX36G0hCtL4TuUuSGsolqWlUMvwkmqs6NwqXlZUxe/ZsPvjgA5YsWUKHDh0YO3YsH3/8MR07dmyIGAF9XYU777yTzz//nCVLlpCZmfm717FarVit1gaLSdSCV9/vyWnUh5eiPfpE0vZ9BpGUV0Q5rcjztkK16ltsmA0qoVzbU1p84uNtAKEkJjHaXOXrPzJnMKkxy8ybRuH0y/CTaJ7qnNSkp6eTmJjINddcw3PPPUefPn0aIq5qJk6cyAcffMCXX35JbGwseXl5AMTHxxMVFXVCYhB1p/j05lhHMKmxu1V8BhfxGR1oU7qEbFpRGojBZTy8a7M1+H9fackJj7chuMNJjV6p8fjUY1282VM1DadfxQKYjVKpaQyy8J5oruqc1MyZM4fzzz8fwwn+hPXGG28AcO6551Y5Pm3aNCZMmHBCYxG1ZwgmNeVmvZ8kxgNuWyml5btoZT0AgOrTOBBlxuOOwmpwEa3o1RxfM1mnxu2X4afKyvwBCG5Waj5Bb6rry/WK4emx0Sfk/k52skWCaK7qnNQMHz68IeL4XbJjc9Nk9OtvJg6T/mYS7QE12YnTuZ14SzBp8ajsjYrCXRGrJzVGPwFFQWsuSY236vDTH71RuNQfILScrfkE9NSU+vxcvnonRgW2DOxxQu7zZCeVGtFc1Sqp6dWrF99//z2JiYn07NnzmIs1rV69OmLBiabPHEpqzNGYfV6sAQtavBe/P5s4a3D/H2+A/YlxeA7FAvnYjH68JgOmcmcjRh45bn/V4SeXL4CmaX/YRc8qJzUnYkr3jyUOXKr+Ju5WVcwGqU7I7CfRXNUqqbn88svDDbeXX375H/ZkLOrOogYbhU3RRLucKIoNe6IRk/kQ8Qb95ad4VHKSknHvjgHAZvDhMxoxOysaLe5IcgUrNQnBSo2mgcevYjP/Md9cS32Hh59ORFKzrPjwHmI+qfgClWc//TFfg6L5qlVS88QTT4T//+STTzZULKIZsqouUPThp2iXA5QoomMNREeXoqh65QKfSmFsPG41FoAoox+f0YDR6WkWFY1wpcZuCR/z+P64SU2JPwABPbmwnoBKwbKiw+sd+VRJaqDy7Cep1Ijmpc6v6A4dOlBYWFjteElJCR06dIhIUKJ5CKgaUVpo+MlOtMuBYrBhsWiYzV7s5goMir6pnqoqlBv0pMZm9OE1GVE0DbUZVGtC69TYLabwuizH2yy81+Xh79v2MXlnDjNyCsLbDjQFZf4Aild/TpIqJXoNYZ/by26XJ/y1VGp0DlmnRjRTdW4UzsrKIhCofgL1eDzs378/IkGJ5qHC6ycafYE9pzkae6kTlATMhoMAKKSSZLdS4PCgeAIUm0NJjZ8S0+Gduo0xTXsXdqdbf1Pd93/jMWvj8WM+7qRmek4h7+Ye/nCxu8LD5FNaH9dtnigl/gBKMNEL9Rk1lOVFVVellkqNzinbJIhmqtZJzZw5c8L/nz9/PvHx8eGvA4EA33//fa0WxBN/HE5PAHswqXGYo4l2FaMpyaj+3aTne2iXs58UpZQCbChelYNRCeDRkxqnLbhTd1k55pYtG/FRHD99XRoDp/vWEqNdhYvE454BdSi4iWys0UB5QCXfe+I3la2vUp8fgpWa5Aau1CwrPiKpkUoNEGwUdvnxufz4AyomqdiIZqLWSc2oUaMAUBSF8ePHV/me2WwmIyODl156KaLBiabN6fUTqwSTGlM06RX78JlcDNo5h5TgRpcp3p1Ad/Co5EXHgQeijD5clmClxtG093/yB1QCwVFeNxZsig+04x9+KglePzPKynqHC28TerMurVypacCkRtW0cFJjKHSDokhSE+QMBLCsLuTOZQeZcdPZDDk1tbFDEiIiap3UqMEpkZmZmaxatYqUlJQGC0o0DxWeAOmhSo0xmky3F7upmJSKMvwGUMwxpHr1rRAUb4B8mz7MZDP6cZtDlZqmvVZNaOE9gBxre9yqFXzHv1ZNabCHJtViBlx4m9CwSqk/EK7UNGRPzT63lyJfAGuBG+W3QjSjQsXQptN71JCcfhXFr79m4qPMjRyNEJFT55rjnj17JKERteJwe4kJVmqcxijsbh8JxgIAsttGEzhzDClKKaBP6863xQEE16kJ7tTtcNRwy01HaDo3wKQz/sbBKP1353iTmlClJs2qfy5pakmN4q26dk9DcKn6EIuyPpg4BzScwR3T/+icARVCG61KUiOakTo3CgM4nU6WLl3K3r178Xq9Vb531113RSQw0fR5Kg5XWZzGaOzuAOnWQwCUxFnIPP0GUn58GdArNXnJoaTGhz84xt/kKzWh5MUA+6PTsRj1x+/yHt/+TyV+/c051RxMarSms59U5eGnhqzU+AIqlnVF4TdvANcffN8tAK+q4g2o2AInV6XGG/BS4CqgVUyrxg5FNGF1TmrWrFnDxRdfTEVFBU6nk6SkJAoKCoiOjiYtLU2SGhHmDvbNBDDgMlixu1WSowtQgZKY1hha9cIeZYBywKuSF50IgM0YQA3uLdbUN7X0BIeJNKOCVfWjBjdwjNTwU5pVf0NqSpWaEq//hAw/7S2qwFDq0+vRmv7H1YSmvjcUZ0CFSsOicSdBUrMidwX3L7ufzLhM3rv4vcYORzRhdR5+uueee7jssssoLi4mKiqKlStXkp2dTe/evXnxxRcbIkbRRPmDlRonNhRNI8qrEG0sYn2CDSWqIygKZS26AKB4AuQHkxoAS3Cnbndp0YkPPILCFRmjgY6qEyKwTo0roOJRNdA0Ui3655KmNFW5xO0nuGdpww4/BYe4DGYjhmAy6fJLpcYRUMOVslir6YSs6vx7OiV0otxbztpDa9lbtrexwxFNWJ2TmrVr1/K3v/0Ng8GA0WjE4/HQtm1bnn/+eR5++OGGiFE0UT5XMKlRoohyO1EUK++mH+KGxDRe2LcXt9/N3pZnAGDwBAgoJtyavvGlzaihAZ6Spp3UhFYT1gyQbjJA6M31OHo7Sv0BDPkurEvy+PHXXNA0PE1kVo+maZS79OnnNrOBKEvDrZMSSmAUAyjByp/LJz01Dn8AfPrr5WSo0gCkRqfSr2U/AObuntvI0YimrM5JjdlsxhA8QaSlpbF3r55Vx8fHs2/fvshGJ5q0gFtv8nUYorA7S1nedR2fJ+lvKvv9RTy46EGy4jP0C/s0UDWcHN4qQVUUvOUljRB55IQbhQ0KraKj0IKfissrXPW+zWKfH8MhN4pXZdayLMwbS/A2kQpEhari9zR8kzCAJxBKapRwpcbtbxrJX0OqqFSpOVn6aQAu63gZAHN3zUVrIkm6OPnUOanp2bMnq1atAmDIkCE8/vjjzJw5k0mTJtG9e/eIByiaLs2t99Q4FRsW90/saJmFUdM4syIdRVP4/sD37C/7FjN6oqN4ApQZD68q7DUZCJQ27UbhCk9wUTyjQvu4+HClpuw4tn+o3GgLYMytoGR78XHFeaKU+g7HnhLTsElNaDq9waBgMESml6k5cFSa+XQyJTVD2w0l2hRNjiOHNflrGjsc0UTVOal59tlnaRlc4fWZZ54hMTGR2267jUOHDvHWW29FPEDRdKmeYFJjiAb/NgDGlTu5pp2P3uW9AXDkf0qcMTht2x2gxBRMagw+PCYTannTXnyvNBi/ZlRoFxd3OKlxuet/m5X2TspI09f28ZV7j3WVk4a+Rk1og09rg95XqHplMBrClRpPDVu8/NE4AwGU4HMT2jn+ZBBliuKCjAsAmLNrzu9cWoia1Tmp6dOnD+eddx6gDz/NmzePsrIyfvvtN84444yIByiaMK8TgHKjjYCi7wvWwWnAZmrDnYPuxKSaCFCBxa4PWyruAIUWfVp3lNGPx2xEczgbJ/YIKQuts2NUaBkdjRLskC111T8JKa60zUDbZD2pUQNNo1xfZTp3A7+huipVaoyhpKaJDNM1pJO1UgMwsuNIAL7e/TWr8lY1cjSiKapzUvP000+zZ8+ehohFNDOKV39DzzGbCRgqMKgGEnKi2TjTgdVRRpo7DQA1Nku/vOdwUmMz6pUaxVn/3pOTgTM0zGRQiDObsBj0obZyT/33aqqcGKTH6dWOJpXUeBt+iwQAb6DS8FNw3SNJavQp3Yrv5FqjJqR3em8GtBqAO+DmtoW3sWz/ssYOSTQxdU5qPvnkEzp16kT//v15/fXXKSgoaIi4RDNg9OtVlu0W/Y2klSMBn8FEwBNg8f+9QQdDJwB8Nj1JVtwBCqyHVxV2m42YKjyNEHnkOFzBpMyoEGMyYkVPZiqOo7ej2OsPf9JuEW8DQGsiU7pLfJW2SGjgRuHDw08KpmClpqk0VDckhz8QXqfmZJn9FGJQDEwdOpVz25yLJ+DhvqX3UeopbeywxFH4Ve2ka+quc1Kzbt061q9fz7nnnsuLL75Iq1atuOSSS/jggw+oqKh/8+MfkdPn5N4l9/K3JX9jyb4l+NSms9NybRh8+ushy6IPtXQsiyNxUCHJbdvhcTppW6FvGeAzHwBDBYpbJd+m7/4eGn4y+VRUb9PoF6mJo0LvndEMCrFGA1ZFr9Qcz8q2+RXe8DovLeKi9NsPaKgn2cmlJnvdnsPDTw3cKByq1BgNSngtFqnUnLyzn0KsRisvn/cyGXEZuPwufj7wc2OHJGrgDqj0+3kL167b3dihVFGv/ea7devGs88+y+7du1m8eDEZGRlMmjSJFi1aRDq+ZkvTNB794VG+y/6OBdkLuHPRnVw99+pm9anEHKzU5Jr1f7s6LTitqQy6Tt/l3bh9P7HeWFA0TPZdKG4/RRY9qbEZfbhN+sJyTblZuNx7ePZTjNGILTjTy3Mcw0UFTj3Js5gNJEYFFwVXtVrvQD1py17OWbGZ0kZYs2V1WUV4+KmhKzWhBMZoNGAMDj9JpQYcgcBJndQAmA1mBrQeAMDKAysbORpRk2y3l31uL8uLy0+qak29kprK7HY7UVFRWCwWfL7mVWloSP/b+D8W7l2IyWBi9KmjibfGs7NkJ39b+rdmU7GxBCooNRgoMegVm+5uFX9UJzr0OpuWp3ZBcZSS7koHwBizDZPbR4m50vCTpenv1O0MzvQxKhomg4JFOf6kpsihD8nZo8xEBTf+RNVqtVVCvsfHx3lFZLu9rC0/sf1KmqaxtqwiPHTW4D01wQTGZFQwhZKagCQ1lRuFT6bZT0fq27IvIEnNyaosuLCoSnDrjZNEvZKaPXv28Mwzz9CtWzf69OnDmjVrmDx5Mnl5eZGOr1lam7+Wf63+FwAPn/MwT/R7gv9d8D+iTFH8fOBnnv/l+ZMq860vs1rBWqv+xhVbEUWC2UHcbwYOPPQwZ2Z2xuB108KpNwub7DtQvSrFldapcQc3a1SbcFJTEfzFNyv6v9GK/svvDdR/afrSCj3pjY82Yw+tyKvWbv+neQWlhC6VdxzNyvWxx+WluFKjcEPu+wT6hpagDz81Rk+NX/WT68g96X6XnQEVxX9yNgpX1ie9D0bFyL7yfew7tLOxwxFHKK20j1rpSbSnWp2Tmr59+9KpUyc+/fRTbrzxRrKzs/n+++/585//THx8fEPE2Kz4VT/P/PwMGhqXdriUMaeOAaBzUmeeG/QcAB9t+4jnVz2PWs+dl38+8DO7SnZFLOb6sqkVrLHps3PSi+Mw+MqImbaW0i++QH3hFRQgrciGQTNgMJeimIooJka/rtGHz2hEA3x5BxvvQRwnV3CEx2zQf+ltwaTmeN5by4NJTUK0BVuwUqOoWq126v7m0OHhzYPeE5vUrC5zgqqdkB264XBSYzIZMP9OpWZfUQVvLdt1eAXoCHh65dNcOPtCrvnqGr7Z/c1Jk9zo2ySc3MNPADGWGHqk9ABg7n3X4Nq0qZEjEpWVVUpkyppyUnP++eezYcMG1qxZw3333Ufr1q0bIq5m6+NtH7O1aCtxljjuP+v+Kt87v935PHLOIwC8v+V9Hv7h4Tr12PgCPh7/8Un+suAvjPryCp786UkKXYURjb+2vH6VaNxssOpJTYuSRIwuB2qM/rVR04hxe7G6XCS5kwAw2XdRGtDXXbEZAygKeE1GfDk5jfIYIsEdfA+1BJMZuyGU1NS/UuN065lSst2CxRT8Fa7F8FOJz88PJeWYNhZjWX6QveX1XwCwPlaXVVTJ5hIa+A01PPxkUDAHnyd/Ddmk0+PnundW8uw3W3lh2Vyu/epaZm2bdVxJyN6yvXy+83MAthRt4YHlDzBj04x6314kOX0BlMDJX6kBOCf9LADWtXCz/8478RcXs6+ogvdWZsvq0JVsKdzCVXOu4qecnyJye/5aVH2bTaXmmWeeoWvXrg0RS7NX4CrgP2v+A8Ddve4myZZU7TLXdrmWZwc+i1Ex8vXurxkxewT/XfdfHME1X46m1FPKXxb8hc93zkbTFEBj9o7ZXD33avKcJ35Y0OnxY8PNpuDwU2pZCtFFTgKqB8Vmw5iYSJzLg9HlJNWdCoAxehelvujwbdiMfjwmI579TXdPMU8AULwYjT8w8fuJbNVexxS3tt5JjaZpeIJJTVqMFWsdkpqFhWUEynyYciowVPjZeaDhh/WWFJVx44Y9bHK4qjQJx0eZw30uDcUfONwofKyemslzN7G/yAWKly9yXmFT4SaeWvkUdy2+q96N+//b+D9UTaVvy7786bQ/AfDOxndw+hp/MclS1+EKXazt5E5q+hg7ALCxvYI39wA5997LY19s4LEvNjJ/k7Q7hHyy/RO2F2/ntXWvHfdtvZ9bSKfl61lWdOwJGmW+k7NSY6rNhe69916eeuop7HY799577zEv+/LLL0cksObold9eweFz0C25G1edctVRL3dZx8tIjU5lyi9T2Fmyk9fWvsbMLTOZ0G0Cl3S4hBb2qrPMClwF3PLdLewo3oGRKNrk9KM4kIy3/XLyXXncteguZoyYQZQpqqEfYpjT66fI4sVpiMagmUhyJGAq1bBoNjI+/ghb586sGXEBBpeTVHdrtrAFo303qkej2BRLor8cu8mL22zCtT/7hMUdaV7NgCXpR3yG+SzTF1XGHP8r7vL6rb7tDKhowcQgPdZapVLze7OfvjlUijH7cHKcX9qwlZoVJQ7Gb9iDR9VYX15BvvfwSsgNPfQE4AsmeWajgiXYU+M/okF73sYDzPpV/8FYkn7ARxEJ1gScPidL9i3h6ZVP88KQF+p0vwccB5izU1/mf+KZE+mR0oMfcn4gqyyLD7d+yF96/OU4H9nxcbr1pCbaagxPdT9ZnVpkxerVKLMr7G1no/XKVfzcajQAOSVNe2HOSNpYsBGA9YfWk+vIpVVMq3rf1tKictyqxpKicgYnxR71cqX+AIaDLjSLoeklNWvWrAnPbFq9ejWKUvMvwtGOC/jt4G/M2TUHBYVH+z6K0WA85uX7tuzL7JGzmZ81n9fXvk5WWRavrn6VV1e/yimJp5ARl0FadFp4HYccRw7JthSid1zIHN8/KcHOuTsfJ/a099lStIWHlz/MlMFTsBgb/s0EwOkJkGXVKwo2LRUbRnwOI6BgPfVUAA507ILh0G5SS22QbsRgcmD05LDX1pJERzlxZjcec9MefvKpCgar3hPUI6UHGwo2YLAWoGkKAVWr85tKiT8AwU9I6TGVk5rDu1IfzdKDJRgPHF5Lqrie+0UFNI1Hd+SQajFxb0bNyzhscbgYv2E3HlXDAOQEm5LjVPACiSdg1k1oqMlsPNxT4zti+OndFXrCrCW6sCQvAeDBsx+kdUxrbvj2BuZnzWfimRPJCO0mXwvTNk3Dr/k5p8U5nJl2JgC3nH4LD//wMDM2zeD6LtcTbY4+9o00IGdwl/STsUrj8XiwWg/vCaZl59AtW2P1KQqb+qVT4QBX8P2z0NF016+KJE/Aw46SHeGvv8v+jvHdxtf79gqDSz3keGp4fgt2QnwbMNs4WObGvLYILAZKzz55kppa1X8XL15MQkICAEuWLGHx4sU1/lm0aFFDxtpk+VQfT698GoCrTr2K7im1283coBgYkTmCzy//nKcGPMXpqaejoLCjeAffZX/HzC0z+WzHZ+Q4cmhpb8ndXV+lv2svBkUjSXHwN+07Mvy3YzKYWLh3IRPmTThhQ1FOj4/tNv3lZfWnYEPDW2FCc7nw7tYXa/r5zH4AmJ0VRLv1TVJtgc3ss+lvlPFmNx6TETX34EnTZFlXPs2IwVwEwKhOowAwmEtA8eGpx6ebytsMJNstWEONwkDR6jX4j7LCt0dVcWc7UCq9pzudvnot2LeosIxpOQU8vycPj1o9kdI0jfu27aPMr3JOvJ2vep2CLZi8tVH0eJMaeDNLAF8gVKkxhJO/wBGJX3Gw6dqS/j2K0UvA1ZaLMi7izLQzObftuWho/N/G/6v1fRa4Cpi9fTYAN59+c/j4iMwRtI9rT4mnhI+3fXxcj+t4qJqGw3V49tzJYu/evbz22mt8+MEHVY57s7LouVv/Of6W6mRdSqfw9wodTXu18UjZXrQdv3p4zan5WfOP6/bCSY37iKQmZzX8pzfMuRPQK70KoHhVCl0nzzIkdRrU9vl8mEwmNm7c2FDxNEuf7/icnSU7SbAmcHfPu+t8fZPBxKhOo5h58UyWXLOEV899lb+f9Xdu6n4Td5x5B4/3e5yPL/2YdXtM9DccniHwJ+NCSrYW8/zAV4mzxLGhYAPXfHUNu0safgVId4Uz3E9j86YSpfgoi9dPohWrfkXTNHzJPqy+AMaKcuJdeiJjVrazz6YnOPFmN26zCcXlJlBS0uAxNwS/ZkCx6ElNki0Ji6Jva2CwFNZrpk2Jr+oQTrinBtg79d/kPfV0jdcr8wcw7tf7OfpkJAKguf0U1aPZckbu4ebzAm/1BfxWlTr5rawCq0Hh7W4Z9Iq382qXdiSbTSSU6/fXrVVcne+3rvxqaJ2aw0nNkcNPTo8fgzUPq/IjAJ6Dl1BSoT+m0DDR3F1za/1hYMamGXhVL2eknsHZLc4OHzcZTNzU/SYAPt3+aaMl6YU+P/7g6yelgRc/rAtPSRGHDh0iKzsbp/Nw35F3zx567tKfq80xpaxunRb+XqFTKjUAGwv19+PTkk7DoBjYULCBHEf9q9tFwaRmv/uIRKUwOK2+SH//KKn0/B9ynjwJZp2SGrPZTLt27QgETp5S08lO0zRmbpkJ6CXoBFvCcd1eki2J89ufzw1db+Ce3vdw6xm3MubUMSRYE1i8OZezDNv0C6b3wKhoPGZ8D7P3ND6+9GM6J3amyF3ErQtvbfCKTVl5PtstehIT5UzEZ/Jy658MfH2WQsVvv+Fd+V8+XXcnKYoTY4WDFJfeLKxYdrPbqv8/zuKhPLhirm9/0xyCCmh+DCa9j+WeJffgIbgfkeUQrnokFCWVNrNMtFuwVGq2dZlsuI8y7bXY48cQrNuPPacdoO+1Vddp3XtdHr4vPNxgfKiGpOa/+w4BcFV6ImlW/TUwKj2RjQO6sTdHv27/jsl1ut/6CAQTGItJwWo8SqXG7cWa9jUKGj5HDwKuDLYX6G+qocTEr/n534b//e79lbgPV2FuOf2WasPxF2VcRLQpmr3le1mdv/q4H1995Hp84dfPybTwXnxcHAa3/ryv+nF5+Lg3K4u0UmhvbYmqaOw75xNiLfqQ4aHyhn8j1TSNfeX7KHIXNfh91Veon2Zwm8H0Se8DwIKsBfW6LVXTwknNQa8Pb+VKrN9d5d/Q0hJweJXzk0Gdpx888sgjPPzwwxQVnbw/5JPJygMr2V26m2hTNFd0uqLB7mf7QQeJpZuJVVxotgS4diYqCv2Mm9m8YxdtYtvw9gVvkxGXQZ4zj1u/u5Uyb8PNfskq3URAUUjxB4hxKWyLc+M1wVdnG3CsWIZlwcMAtLCXYQj4aVtqQvXFoxhdrDLonwTizW6cwfH1ptpXo5pKANAwo6gaGvobncFSgLse+z8Vun3hhdOS7RYMBoXgTeI2W/Dl5ta4V9aBSqX6zul6lURxB+q8AN/MA0VUrjEcOiIpynJ5+LZAnzF0a9u0Kt/bke+gwOHFZjZwZruEOt1vfYRmP+nDT8bgsaoVEo9pM6aYHSiY8LguA2DDwcO/F7eefiugzy75vbWf3t/yPi6/iy5JXRjUelC170ebo7kw40IAvtj5Rf0e1HHKdXvD0+pPpuncaRkdaJmYAMCvK1YAoDqd+PPzARjYRn8+VQVOi9ZXGG7oSs1B50HuWnQXF392MUM+HsKQj4fwxro36r1+WEPZXLgZgO4p3Tm/3fkA/JxXv/2yyvwBQr8iGnCg8vnBF0xqfHqDtrPSkFNJU05q/vOf/7Bs2TJatWpF586d6dWrV5U/oqoPtupjxCM7jiTGEtNg9/PznkL6GfQXt5IxEBLbUxbTEQDHLv0kkWhL5K3hb5EWncbu0t1M+WVKldtQNZXtxdvZX76/ylYNPtXHukPrWLZ/GYv3Lq5VlWdP+RYATvWqRHt85MXpb3SFcQobo0rxOxRmtriEhb0uBSDBUYTnwJX6Zfwb+SHKRrzZjS/4ZtRUkxotnNTYGHQoGbtHX4fHYCnA4an73kvh5ESBuGCjpyH4W+w2W0BV8e2rPgU+L1geVkwKbZL0WXCKX2Ofo/YzoNwBlZnBoacoFQioHDpi/6i39x1CA4YmxdLZrg+1hR7nTzv1fp+zMpLCvUANKVypMRrCw3SBSklNibsMc+oXAPRucwXR0fqMkW0Fh4c/zm55NkPbDiWgBXjul+eOOmy0vXh7eB2am3vcfNRJE1econ+wmZ81v1Gmd1eu1JxMO3QXFRVhbaGveeZQNXau+RVvtl6RMSYl0TO5c/iyKUb9XFDk9KI20O70S/Yt4Yovr2DJ/iUYFP21U+Qu4vW1r3P3orspcZc0yP3WVYWvgt2l+ofA7ind6ZSg9xzllP/++fLv2/YxbNU2XJWql4VH/D7vr9xX4w/ONgtWalyuw5ctrTh5empqNfupslGjRjVAGM3T/vL9LN23FIDrTruuQe9rzd4Srgj207yqdGbzpixeaNMHtu4kvnAtXr+KxWSgZUxLXhzyIuO/Hc+cXXM4v935DG03lB3FO5i8YjLrDq0D9Cbl1KhUUqJS2F26G5f/8PTJKFMU/xjwDy7KuKjGWFRNZX2FXl7v6DGQ49HY26KQnqZM1vj38ENXA/38XXnwlHvobtAYtmItitdBQkUryov6Y0n6icdTkvjKfQCzwa+vKtwEkxq/P4Bi0iuaGha6Ft+ApbSYhafOwGAp4FBF3adU5wdL7larSa/SAAoaoOAJzmzzZmdj7dixyvUOBT9JmSxG4mxmTGYDfp/KruIKaF+7+35yVy4FPj9pmgHP8gMEjHCoU9Wpoz+U6ENt41qlUOrycd8n61i45SD/uLw7P+7SE6J+J2DoCSAQLJ1bTIeTGjV4TNM0Jq/4BwZLEao3kVGdb2LngRycOMgqqpps3HfWffyQ8wM/H/iZhXsXMrz98Crfd/qc/G3J33AH3PRv1Z9h7YcdNaYzU88kIy6DrLIsFmQtCCc5J0quxwe+k2/hvTlZeUxJ7sDFuQeJ9bj4bvYnXNdXr85YMjJIKD8Uvqwv2KMWUDVKXb6I7yH2xc4vePKnJwloAXqk9GBy/8m0jmnN/Kz5PL3yaZbsX8KgjwfROqY1IzuO5LYzbmu0mb+bCzejairp0emkRKXgDei/5zmOHAJq4KizbAOaxkcHivBqGludbnrG6bPxjuyxy6mpUuN3o2kaXrc/XBVxnESNwnVOap544omGiKNZ+nT7p2ho9GvZjw7xHRr0vtZn5/OMYTsAX9i7szW/hDHxnRkO9NB2sCm3lJ7t9AbRnmk9mdB9AtM2TuPRHx+l9brW7CzeiV/zYzFY0NDwqT4OVhzkYIU+HTnBmkCrmFY4fU6yy7K5f+n9rDm4hrGnjaVdXLsqsXyz5xv2B3KJUlXOqbAyzwsZ8flcFT2E28r2sPI0heytp+MzmLEl2Elv3ZoDeQdJUFwU5F+EMXEbh0yFzI2xk2Dx4DMamuQCfGUOBwZLMQAdijKgODPcx6BYCjhYVg7UbWf70Nh1dLDXyLtvHwZNJYCRQPsMWAHerOrr+hRUBHf2Du4VFWu3UFziZm9xRbXL1uTzg8VMz9ErLUPKFeYGT2g5R1R6wsNRDh8jp/9AdqF++0/N3Rzef6l/x5TaP+DjULlSYzuiUvPlri9ZuHc+mmbAlXstqfZ4WiYUsg/IK6n6mNrGtmVC9wm8tf4tHlj2AFlnZHFj9xsxGUzkOfN4auVTZJVlkRadxnODngt/sq+Joihc3ulypq6eyhc7vzjhSc0Bjw8lOPyUEHXyNAqnx6dSXOJhW3o7+uzdRqHLzbofl5AGWDIz2H9wTfiyRRYP8VFmSl0+Cp2eiCY1X+3+isd+fAyAyztezpP9n8Rk0H/XrjjlCk5JPIVHf3iUXaW7yHHk8Ma6N3D5Xdzb+95GSWw2FeofZLsldwMgPTodk8GET/VxyHWo2ppmIQc8PrzBqmN5pVmYhUf0yOXUVKnxuXGpGprn8PUqXHWvOjeUei3pWVJSwjvvvMNDDz0U7q1ZvXo1OU3w03RDUTWVb/Z8A8DoU0f/7uXX5q9l/aH19bqvQoeHhOKNRCseCkzxbI3OBOBZX1sAzjDs4rvtB6pc544z76BTQifKveVsLdqKX/MztO1Qvr7ya379068svnoxMy+eySvnvsInl33C0muW8vGlH/PF5V8wodsEQB9au+TzS/jTN39i1rZZFLuLqfBV8MpvrwBwc0kZFqKJcmu0VbzE/riIRK+KI0ph24FfMQQCxJmMdDnvQgwBPy0q8kGz4HPqn9BmxsUSa3bhMZtw79tbr+emMRUVF4enc7cr6QBoxAdXTzaYnOwvqfueVgeDw0+xwU/Z5QsWYAh2uagt9fJ9qGxfJZZgUmO16ifopFj9jSCv7PerRXPzS/jb1t0ogVJuSoFlG3YC+gktp9ICfn5Vo9gXAE3jhc83kV1YQeuEKM7JTMIbUKnwBoi1muh+AmY+weEExmoyhIe71IBGQA0wdfVUALyHhhPwZRBtNJKZbOcUZT9/LnoLbfbNFL99OYH3RsNHY7m51Mm5aWfhU338a82/GPzxYMZ+M5ZLPruEZfuXYVSMvDjkxRpXCT/SyI4jMSgGVuevJqs0q8Eef01y3d7w8NPJVKkZlpFMfH4pu1P1yp/fHs+8cge/ndoZS0YGO4u2hy9bbIbkGP31WxDhtWqmbZwGwHVdruOpAU+FE5qQ7ind+WLUFyy/ZjkPnPUAANM3Teet9W9FNI7a2l6sPy+nJZ8GgNFgpHWMfh7YV370D4LZrsM9dpW3ODjm8FO4UuOizOcPLy0B4HafPElNnSs169evZ9iwYcTHx5OVlcXNN99MUlISn332GXv37uXdd99tiDibnDX5azjgPECMOYbBbQYf9XKegIeXfn2JD7d+CMAF7S/g/rPuP2qGXZMf9xTQO1il+TnhdBS1DLNnJ1tjelKmRBGHi+/X/MSBNjHcn9GCVjYLFqOFN4e/yfL9y0mNTqVdbLsqC4ylRKWQElX9E7XJYOJvff7GWS3O4sOtH/JT7k+sO7SOdYfW8dTKp7AYLHhVL3GBKMaV7WWZNQq7x0/8+gQW5ifRMamQX1s7+DHTyVlb1hPXeiinnDOApe//H6nFu6Fld7T807Hav2SPxUxeips4q5mYAwfQNK1JLfBYUlqCEkxq4tzJgIJZtRLtiafCWsp+RzYwsNa3p2kau0r1ykfLWL2B2rliJYa0iwHwxejJgjcrq3oswfJwlE1/c0+Pt7FrXxmFZUefQeJRVe7aspdvs5cSW/A6dq2CuTlAW4gFNNXCxt12bnZ2ZuxpY+mc2g8NMOVWsCvfQXyUmS/vGIACXDR1OYfKPZzTIanBt0cICfVbWEwGosyG8LG1h9ZS4Cog2hRDeeEgsBmwe0uZsOclnrV8iFHTYAMkVrot29av+BfwVYuOTLErlHrLwx9Ceqf3ZlKvSeGF9n5PWnQaA1oNYHnOcr7c9SV396r7Mg/1pQ8/Bfchc5ejuhMx2Gwn7P6PxrxpNh13F7K67znsT0ihTUkBOZ3PZPoVZ5NWvIfd+XkQXNuozKhwWlSA3UR2Ab7dpbvZXrwdk2Ji4pkTj3muSbAl8Keuf0LVVF749QX+s/Y/2M12/tT1TxGLpzb2l+urYbePOzyG3CamDdll2ewv389ZLc6q8XrZrsPPW+VKTWjmk1lR8GkaOZWndYdmP2kqpV5PlaTG6/GfNOfnOp9d7r33XiZMmMCOHTuwVfpluPjii1m2bFlEg2vKvtmtV2nOb3c+NlPNJ40CVwG3zLqFFb+soFNpJ9o62/L9nu8ZM3cMBa6aF1E70q/FBdz3/Ux6GvQ1BH6L68bF+d/SveJr0DyssXcBoE/ZOj7av59Bv2wNT8lNi07jqlOvYnCbwXVaMRX06YNvDHuDWZfPo1fmLWgW/ZfKq+q/LAOKM7FqUGGwYQ34KMnXP8G22q0vu/1zZ4Vz1i8g3mQkPi2d9MyOpHn0mQ5+TzSdVH2tmh9a+SmNtqK4vQSK9aGcUk8pn+/4nCm/TOGvC//KmLljGP7pcMZ+PZYnf3qSxXsX13mGwk+5PzHllyl8s/sbKnzVh2QqykqZ/rfbWfDWv2t9myWlpRiC4/+xnmRM7l+Ich0iIVitOejaX6cYd7k84TJvRnwUms9HxerV4UqNL0Z/bmuq1JQFkxp7sLm4TYLeLFzmOPpY+Pu5hXyb9T1xh17BoAWfE+3wKUMxeFHVYlYeWMmdi+5kwjejsTh+xrxTf33dcV4nUmKsJMdYee36XvRsl8CfBzbsMGxlAbV6o7CmaizMXgjA6Yn9ARM9DLvImDGU07Z/gFHRmG88i6dNN3Cf+Tbut05k99mPo3UajmIwc1neLhbt2smnOQd4Xk1mxikTmHbuv2ud0ISEFmKcs3MOAfXELJGhalpw+El/XvzT/8fOIedSvmjxCbn/Y9G6XEKCTSGusIyfOvZAAzoU5tG24AAb539AtuVwb4jHYKCjUf/dKYzg+ijz9+iL1vVr1Y94a3ytrjOu2zhuP+N2AKasmsLnOz6PWDy1EUpq2sa2DR9rE9tG/57j6OeXrKNUagqCSc1pwSb/KqsK+w9XZUud5eGKHwBeFVcDNW3XVZ0rNatWreLNN9+sdrx169bk5ckGY6Dvlj0/W/8FubjDxWiaxvbi7bSNbRteHv2g4yBPzniSzEOZZJIZvm5ACZAbncvbK97moaEPHfN+tpWXcOOC2wiUDqSXQV8me21MZybkvsv+6CjU2HX8ltiDIY419CSL5OyXKGk9lnEbVF44tS3Xt0rGp2qY67n/S4HXz/WbisgJDIIWg0B1M6mNmWtaJDH/lX8A4DJYMSj6G2cruxPK7bQ5ZGd/qpP9CRuJLy0F2nBqv0Ec3DOdNLWQfEMyif5uKIYc1sUb6NrGSJcDULZ3F5/s+4QZm2ZQ7qu+2VqeM4/1BeuZvWM27ePaM6j1IGItsaRHp3Nq4qlkxGcQY45BURQCaoBcZy6bCjfxxY4v+DH3x/DtmFUjf+k4jtsG3RP+5LFpyUIK9++lMGcfA68dR3Tc75/0chx5KAYfaAqxniS6bv+UwmQ38e40cuN3ssP7Ge+sT+ayDpeRHJ1crdR9pF9KneFPR6l2K64NG3F73PQv+AmLz0XKIgMHY6NJz8tDdbkwRB3e66s8mAzF2vT76JCoz8JyV/gIaBrGGj5hfZG1nLiCf6MQYHi7CyjdO4bvtxaSHGOkc1srK3buw9TBwG2n5/Pptk/JLc8inv8QaNEau2cQV/Y5PK357MwkPr99QLX70DSNNflr6JbSDasxsqsMa8HhJ5vJQHR4+Ell4V49qekaP4AE4xKeVv8Pc7mfLKUFD3r+wkq16oa9nywDm60zt/Z9iJuTtxOzcy6dt8+jc/YayF4Di16AUy+AblfCKRfwTr6TT/OKef/0DqRYav6Zntv2XBKsCeS78vkp9ycGtak+BTzSCn1+fKqKNdgLYV65nEBFKdYOmb9zzYY3s6CCJa1Ox7q7jLKz09nUKpPuuXsYtmUVrckh94jZcjF5C4Fr2VFUEZEKgaZpzMuaB8BFmTVPgDiav57xV8p95by3+T0mr5hMl6Qu4eGghuT2u8l36R8E28S0CR8P/f9Yw09ZlYaVymqo1PSIjWK9w8V+t/fw8+s7PFnkYOkRy4F4Vcr8AaJPUBX2WOqc1FitVsrKqq9vsn37dlJTUyMSVFP3U+5PlHpKSbYl0yO5B39b+je+y/4Oq9FKv5b9sGgW/Gv8pDvTAcjVovCoUSQrTuIMHto62+Je5uaDgg8Y2Hcgbdu2rfZLm1Ph4Opvb0VzbSPNfQHp1hL8GLC7nTi+MGExGjk4OJnfOneDfdBT2YG39HySTJMpTr2Pe7fBJ3lFrC5zcl9mSya2S8NQhxNDQNO4Y3M2OR4f7W0WesRG8dUh2OaNJzM+E1PADUZwKxaMiotTY0rxt7+ePmXxDMuz8mNgMzM7z6XLd5/i7XUap5zTn+UfTKe1L498azLFvgwu9FUwL8bOvLMdDNsA/9jwBBtV/Re1Y3xH+rfuT4f4DqRHpxNvjSfXkcu6Q+v4cteXZJdlk11WvWJhNVqxGq2Ue8vRKq24YtAU2h+IoiDeS7ndzxt7pnHQVMoDZz1AlCmKdYuCS49rGs9+M5+LLhzBwMSjb/YGkF2h9zHFeOMxakZaJ2ymU5c1rPANYgsQwMnUNVOZukbv70iLyWRM52vpGJPKvKx5bC/ejtPnJDkqmUf7Psqq0kSUYHKSEmOh4udFbG6dQpfSrfodVsCuVimkb9uLd+8+bJ1PDcdSEZxWHeqj6JQU3HvIHaDA6yfdWrW/Yp8jn917XsJAgLNbDcNz4Dq+33IQi8nAv6/tw3fbD/HTlgpcLjt39hzLLT1u4YFf3mTpjg8xRuXgjvqIS76YywuDXzjmG3ZWyR7W/PVPvHN6NK8+/lNE9yYLzXSymgzYzMHtJMx7yXPmYTNY6fX9S9xj1hcum6f24X7vXylToomyeLDhwWe14jTY0RwB3G6YuiSPfxvi6XfaPdw16kH6FMzFuPETKN4Dm7/U/1jjMbS7mp1pV7CoKIWrW9TcY2MxWrikwyXM3DKTL3Z+cUKSmlyPD9wBFA3MqCRXlGAfNAhLRkaD3/fvaWezQLyZDsUqp/9WQmdjBgXsA/zEpf+FO/MO8Z/0D1CD75kJ7g3AtUzbc5DueS24puXv9zIdy86Snewu3Y3ZYOa8tucBeqLz9aFSPs8vpr3NygUpcZwdb692nlQUhfv73M8BxwEW7l3I0z8/zXsj3jtmw3gkhFYNjjXHVqkshSo1x5rWne3yYNxdjqHUS0nLw7MRC71+UDWSXRr4VVwmA0W+AMkWU5VKTWFJ1d3rFZ9KqT9AC2vj92nVOakZOXIk//jHP5g1axag/0D37t3LAw88wFVXHX3n6T8KTdN4b8t7gD5EM27eOHaW6ENDnoCHpfuW0u9gP1q6WuJX/Pzgb8UeX3tsqSrtXPsociXTM2YFbTwJbN+8ne2bt5OYmEj79u1p3bo1KSkpJCcnM3bxA6iuzQRcbemp6E20m2I6Ebv5EAeS9dLhdRvf590z9H06OhoOkFKaQXnyMpIKXqIw7XFWlOpDAc/sPsCKEgdvdcsgppbrh7yadZAlxeVEGRSm98jEGVD56lApP5c68AdUrJr+ScCrGLEHHLSPv5mkiszwK25kcRpDynrzpfFTvtizj6s7tufiO/5G+dKVrHHAAVcCr1UUszLKRnEc3HOLiTJ1H7GWWB4951EuyrwofNI4uGcXC1//D+26n8F9V9/LnT3v5Ns937K3fC/l3nL2le9je/F2itxFeAIePAG99Go2mDk18VQ6GFtjnrWRRG8Ug66fwGvLX+bXLsV8tuMzvtz5Je2j2pBiKaMLsRhQyF/3G+NadWHTgO5EHeOTyQG3PoQY54nn4uQHyWyhn2SuZBHfEA9HnBzzHXt47bfnqt3OIdchJsybgDHpesxuK4o9gMtazpv7P2dvD4jyuMjzn8VZxRtxWs1ogDc7q0pS4wo28iUGl8ZvHRx+UtwB9rq9VZKagBrg7qUPYFDLUNVW/LDsPDy+g5gMCm+M7UX/Tilszy8PX7/A56OlNYZu7W7g6+/aYbGvIjNzE7kVe5m0eBL/Of8/9GvVr8bnaPcH79B/i0bv3S4Mk5yQGMmkJlSpMRIVHH4yRm8AYEBZGUNUvVH73/5RvOQfQzzlnFu6jB6Fm6j8k9mX2o7vT72AUkc0lPn4cVM+P24Cs7kXp6UP5PyOB+lbsYwuRQuJ9xzgph1vc+XuD1mbPYIfT72Klm27YFAU2rVrh8Fw+PVyaYdLmbllJj/k/IAv4MNsbNg3hFy3F0NFcDNUZxFGNBLHXt+g91lbZxer/LLSC8RAcOR9tbEtq8172G4o4cqSAfwUs5ZfY/W1uL5s64N9erPqgsLS405qQlWaAa0HEGuJ5cficibvymV9+eHqxOv78ukbb+ed7pnVKnCKovDQOQ+x4sAK1h9az+c7PueqUxv2/TA09NQmtk2VD721Gn6q8GDaXY4S0NhfaV2mIl8A4+5y3vouF5sCaryFH9oWcXmntCqVmpJyvbBhthrxeQLgU/UtXE4CdU5qXnrpJUaPHk1aWhoul4shQ4aQl5dHv379eOaZZxoixibly11f8vOBn7EaLGSXZbOzZCfRliRyEieiYWHQ9nW0dGn4gfneU8k3pRJ7lsblW1dh9hsoTMzj64pTadPqIzqUdSTT3YHi4mKKi4tZu3Zt+H7OMsWQb+vNxpJB9DTo5fQ1sadx6q8b8BuMGFQDBs1Pas5+tkZl0MWVxZm+Mn4t6YYtKpfkrDfITbuZsvhOYDCwqKic1/bm80CHlr/7GMv9AV7N1t8QpnRuy2kxUXhVlSiDntX/tC+PWEXvwfBpRs6MPpMESyZ+fKyKX025zUufgs4kBdK4PjCO/8x6lAvu/henDTqPc6NTmf5JNoUOO4loPFFQxD3pqZTZweKD1y96je6J3Sjav4+kVm1wlhbzxZTJOIqLyNu1g+wN67h00gM1nlBcfheFrkI8AQ8J1gTirfGYDCZmP/s4WRVmug0bRu9LRjFiza/Er1rBmnM8FGql7K7IZnc32NHWz3mrY+mwbwcer5eVJQ7OSz76TJ4CXyEYoYN2iEzzdvwYcWHjHF8pz26y83NhW0454KT9oTL+N0Jlbed0AphA83NZhwu4IvNcYs2x/G/j//gu+zv8Be9iDw6dv74JOJyzoHpXouR0ouueMrwmY7Vp3Z7gPlNJwSnlreKDSY1P5cpfd3BeahyTO7UmwVDBkz89yY6CX9E0C64916L6jJzWMo6/X9iZ87roqwS3iAte3xPgkNdPS6uFAxUe8ETj9Qxh5u1P8I9fHmLxvsXctegupl00rdpGroGyMhKnfw1A9ui+nJmYSCSF2qqsJgNRwUqN2a4nNRdW6EnZo74beT8wnHOSN9KzZBeehCQcKb2IKi4mde8BtICHBMdOumVvZ3ebDvx0Sj+yjG2hwIfPp7J+v4P1++3ACBQu5BLDz0wyzaYTuZy7/xPY/wlLOIN34q6kc3wiD40fi8mkn3a7JnclyZZEkbuINflrOLvl2dUeQyTlenwowX2tWpXnY27blpjBR5/EcCLtpJwETwCXQWNjIIBWuomf4w9gsRgoNjjYayjgkoLzw0lNlt1AfMwiir2X8nOJ87iHoJbt1/tB+7U+n79s3MNXh/RKhN1oYFyrZA55/XxTUMrKUicX/baNN7pmcFa8vcptpEWnMfHMiTy/6nleWf0Kw9oPq3VvTn2EhpdCSQwAPjett+nvB0XuIpw+J3Zz1ThLfH5KK3zYgsOzlVcDLvT5MZQF++w0MJR4+WhFNpd3SqPMX8EjaSlc5nDiLHcAFuISbBQedKJowYVBExpugdnaqnNSEx8fz3fffccPP/zA+vXrcTgc9OrVi2HDjr7gVHNX7C4moAUo85TxwqoXABhRWsQX6mqMigmH5SbMa+M427WbLoqGpsEyXycORqViP9PAxZt+wewzYAz4SXaYSG8XT76zFcWpv/KbWkx0zK2klReTWl5CvKOUWJ8Lu99ORrmddYF4epr1StAOczvMXar+SNt7XPyY2JMurizOMWzBVTCI9ka94Za8zQTYzJ7EVmxt3Z4F+JjUOgmv14vb7cZms2GwRbHG4eKnojJ2ljnJcXlwBQLg8xFvNuPwB1hUWEafeDt94qNZXuxgyfodjFD0j1teQwsSUs5BReNxfCwrPQ1KwYTKP6Oy6OvK4CbH9dw1fQJv3PwB3U7pBGTjcFvJjUtlWEU+Z++zsCnFx6Qv/RzI+ojl+3fjdbmwJyZhsdlwFBcRn5KKx+3i4O4dzHn5WW7459RqJ7koU1TVEwCQt3M7WetW61WTH1exYOM9BOxWWhfa6fpLey544lGeefkvrOpUQHFcOV8MdnLWlnja5OxmcfuWR01qyr3l7FP0VZW7BfSFw2YELsZktDCe2VwSdYBiXzqHYhMpsicyfsEBNOUgWzOHkRM/lvRW7ejbUp8B99KQl3hk1dt8vukLFK+XuCgzrT0+fAXlVNhMHEhWMFgK2ZBZxK52wxi6cQfe7KzDwWgaanAMPbSJYVyUCYvZgNen4nf5WVBQzC/7vyWp7BPKPYWAEVfR1ajeNB695DT+PDCzyvOZHqf3vygeNbz/U2h6t8mokGyP5sUhL3LX4rv4MedHnl86mReyzsH12xo8O3cS3acPBpuNqHIv+5Mhddz4o/x21Z8WrNREGQ1Em40ophIMlkIMGgyucLEocCazjOczwriZdKcLt/nwQoKu5GQORkfTZd0GrBV+jAEfp+b9xpU/raTCZGHZmb1Z0H0Q++Jb4w8Y9RlFGnzpH8pXzgEM9K7jWhZzkfYL5yrrOLdsHZ+XD2T0dJXbR1zMBa3TMSgGBrYeyJxdc/gh54cTmtS0dBaQeP31KIbG74EA+G7dKmaf3Y4szU+ntUUUpHqg49d0L+5Cl9Iu/GLaSVt/MqaAGb9Rf9O1Jf4EBRdS4POz2+WhY3T9ZnGVecvYVqTvmffCUjOHPFkY06O44YzW3JfZMlyV2e50M37Dbva4vFy2egc9Y6O5JyOdC1IOJy7XdbmOWdtmkVWWxfKc5Vza4dLjfGaOLlSJqXJO2/QZsfMfISEzkxIC7C/fT+ekzlWul+Xyhl8HcHgSAehJjRLsuUpvH8fB7DL25OsLaq5QHSyxR1NmNNDG6QCSiIuxUFLkIuBTyTsBe3HVRp2TmpCBAwcycGDtp6M2Z+O+HUdWWVb461M9XlYGZ4YFDP1wr07iPMNW2hlLAFhhymRXp0xi0nz89dfNpLksnONbTFvbWrb4W9G2qCdP2q8hPvAMinEXhaUrybefj6HCiC3tQ8ymchLLu9Ol5DScmpkeyh4AijxJpFO136lN8SF+7nw6f879nP6GzXzgv5i2hkJcJi821YxRM9KpOJdOxbkAPLf06yrXVwE1eOKLN5kxmW2U2uxY4hIoiInnHx4PbosVRdNICfiI83lZnFPILYr+Rm4x6w1zb+NhSZSGFmMj1lFGhcvCw64k/qNU0DUQw+15N/D4R3cz+br/km4q46A/jp8t3Wjjzee2gy5+WNuWM/bsZYv7B7xpiRgMBpzFRTgBi8lCQk4xaQqsiTZxKGs3Ods206ZLt2P+3PZt3sC81/U1dbTkNixs2RZLwIdR0zC3aEfZgSzmPvAQnZ3RFCSOYlO7rVg8W/i5WzF295t8f7AV/zilNZQdwFeSy9o1P+MvzKLT5ZP4+6pHcBoKifGaGe0owaFFc5pnIL/aytls6ERXZSd/ylxHrjuZ9UVJrFNaMHpZGf9K+p7i3FZ83/Jy7s3QkxpFUbAmXYLzQAYxRaXcoKzEvXcbGlF8Ofp2ipLiiTn0LjbPj1QYlrA32UjrUKXG54Y3B7HOt4d1lo5s+rU9pd3eJt4aT8tEBwcCKzmlxM+h0s0E/HmUAxZrWw5a/4xpiw2TQWF07zbVEsT0uOAbiCfAweAMidCaN3ExFhRFwWK08EDsGK4M/Mgax1aWLdhE92w90XAsWhS+rXcvMPNmqz7H/FnVhaZprC13hRuFrSYD0SYDxmj99+Q0rxe7pvGGaRTXqKspt0VhLqigzYEcVGMc2JPJSdLwREWx7uzeRO3dgcnlAA6/edkdhxi9Yg4m1UhhYks8lhjiHE5MAQd5bVJR42P5wT+YrdFX0837NRe4F3EFPzB032penr2FNqMncVrLluGkZnnOcu7tc2/EnoOaHKiU1LT2lpFw5Yld+O9Yemecysy5q4nxRpOladgzv8SgBNhiNNBJUyg1VFBkdBMViKHcWIxB06iwuzGVbMNLK34uddYrqdE0janLF6ChoXpSKN4NJiogp4Kf97qZc46XC/LWY1i9CvPuXbzXbwD/Ov9SvigsZ015BeM27OGxjq24vW0qiqJgMpg4r+15TNs0jZ8P/NygSU24UlOpSZhDen9dGxVKDHric2RSk+32VElqnME+vW/2LMCc+3+o/iuAGLp0SORgdhn5RS78ARVXcLVil2LA56oAkoi3m7FYjbh8KvmOJpjUqKrK9OnT+eyzz8jKykJRFDIzMxk9ejQ33HDDSTFHvTEoioKCgkExkKCBw6CQZzYBNnxbBjLCuIUUQwUqcKBlNKdYSrgudy8DNycQpfUI3khf8j3ltDMupkvZQoqTonldvQK78SNsxjn4D+3CGJ2NwVyCV02ldVJHzHkVdFWysCo+ikxxJK3fTDuXmZT44fzSqRijA1pt387W5DhUFE4x5GBUK3iCqcxz9+aZdj6MCmSUZ9LCkYFNM2IMts/6FCNmLYABMAQbLk1eD3avhzRnKacU5oYff4XRQkFMPIVx8ZREx1KiGmmh6NUgo9qCbQT4vlUZXeP8bGjTiSJjMorDR8zmfTxUrPCm4qWNN50xOy7iyo+extHubNitMb+iF1exmE6xhSzJz0QFrC4jnfeXkRjw4TJqHEpNIq9FGzaekoSiqiQe2I9WXsC6Bd9US2oCfj/5WbvYv2UT+zdvYPeaX0HTICaRpb0HsSpTn/US7XExaPtaMsuzUZ0OKqLjWd/9Qhy2Udgci4greh+nLR91z/3MSHmAUV/+HYM7n0SjkRXRUTzz2ddkWwxYfAYezbXTQguwRTuddoZuFAR2M89wLqmai1QlhzZRh2jT+hBd4vNZaD6F65a05b+XzaRoZSz728bQulVrFEXhh4OltDmYxUWHFuIOVGAMqBS27MKOlJaYfD4M6y/E3yYXk30PM85LpdenW9ECAZStX+Es3EHAAL3YQc/cnTz22SguGPAoZckvYMVFXnDyg4EYyuJG4Iq7CNNuN1DO4FNTSYiu3ucSo3noWr6FzIossp6fj/fRxykMntSSg2vo+A7m47vncYb1VpnXx8DskckMa3EP1oz2lHzyKSVz5rC0m4bap0d4VmAkfHKwmLu27MWq6duHvrr6eV4Z8neibPqn8bNcbn4KdMVuM9Lhty302LmJ/d2HkZk2kmRbcPE3NcD8wFoOGEtwtTsV+/5CjC4HmloOeNHw4le8+I1gLysnVOD3JbTFbjOBx8W53q50crYETmWbcglY/k1XZQ+Ti95k9f8W85T7bE5LScWQZGBnyU7ynHl1Wp+qrnLdhz+hd+p5Gts3rMHndtN18FBMlsZdXTjXsRLLwHjOcO9mff42MLpxGwdg0oazwBigQ7Kb1R1ORSnbjsVdTJSq4jQaiY5ZToV6Lj+XOLm+UsNrbVR4/Tz6+Ua+zlmMJRn8aid8HWMZaI9m8/ZCDhSU8P632SyilM7lPtpERRHzwzKu/GEZt151NTNOO5N3iyt4alcuuW4vkzu1xmRQOKflOeGkRtM0vJrGNqebHjFREX2PrNxTE+Iv3M3nsXZSvG6wmcOXqSzbdbi3CqAi2G/3/paZWDybCFg74q/ozzWntWTJsr2oAY3fDpThCe4H6FEUAi69vSDRbsFmM+Fy+CiI4PT641HrpEbTNEaOHMk333zDGWecQY8ePdA0jS1btjBhwgQ+++wzvvjiiwYM9eQ1Z9Qc/T/b5zPjqz/zYrLeG2DOu4ALTXv4f/bOOkyyq9riv2vl2l3tbtPj7jORiRtRIgSIYoFggQdBH55AkECChwBxAiEhbhOZ2Lh7z7S7VHe5XXl/3GoZifdIeLO+L1+mq+rWPVV17rnrrL323i4hg81IcrreQG7LYkR9OsNfvUgYSegjbRQDbqLauUS1c7m8oZuifBubgV7LZjrtnfRJUTBKKfdcxNc23M9H9M/yadk89zbHRD7pvhzZa3omZndkM9EKJlAWTLDNWcO02B5qxS7Wi5V0FgzwlW6dO3MK2BjYAIENGLqEGC8nnSpESxeiRSZj1ayIGAgCWFFxCCl8QoocMU6OEMcjJHFoacpDfZSHTHWmNyOBAmHBwZbUTtqdCU4LpiAIE3taea12Om3+fPrnVyP2JPjcthC/VTVK0wXctFPmW/UpGgWBV+JTSNgt+CxJ8q0xerxOSsNBPnzuj7C7dbxiCoeQRlZVuvILKBAjTLfasA35ebInyIt/+BlCxUwmVteR+9ITtL72EpnUvhV083WJDdVTWFcxceSxuNVOd34Hm5e2c3wPRNWTiNqdSLpGxjYJXRCRNA2I8vNV3+HWAiuCXk1GzIx0zHZpOp96ysUpU3eCAM2eMh5Nr2FDsggjM5snjOnMyoQ41bKRk+VHqXYN8rGq9fy7bSofXjGJFxb+iR/98kFmJSrxl1UyrbWbomAHIgauRJq6/iif+fSlAJRuaKFbtyP2noNUeTsdxX1syJGo2LOHwVd+z1d8S/Aky8hP5GER0lQNPsqXX/wyBgaljgmo0Xqauq2okWlMKclnQmkuT/TuJQ2cPT2fHVtXsfOJTViLK5g4Zxrhju2suOePnJxMoMsKetjOA1/5MoE5ZxHGRqHHhqGqdH7lK2jBIJf01fKC2Mk21xA7FxWxqHgOjjlzuOMsmX81PsxVBXPG9Xo8KceDaBgI2eS2lkgDN63+PopjLxlgTjLFnY5zWbJnI55QL53zL2R27kmIgohhGET0QVyig9MzM3kGk9ioZT4uNl5F13UajVx2Gz72GD7sURfuCCjpMJqSJFlgXnez1Cpq9SLaY7vRUCi0VyOkfsXdln9yvvBvZmu7mS7v4d7QyfglGwPeOK92vPqOqo+/V7RHYggJ82Y2+fzTWfHnm4n094EgMP3k0w/Zed8JVrQbtIbyaRXzQVgAMR0xppLSDaIemU5B5MRdr2PY2thsh3zRQxMxBE8DYqKHlUNvT8oMXadl13p6d75OW0sjv+qbS7vmx1FpNoRMFk4lMBihoaMfmxMcVh3JEFE1hUHZj5rrHPH2Czu2Uv7qy3yuuJwnJkzj3nSKPfEUf5hSwaz8WciiTFesi22DTfxPo8qGSJzfT67ggoLx8Y3phj6S/TS2Rs1jkd38IJBLebZdSVuknbs7+6l32Jif9bs0J1IjWZQwWg24K2puVCUliCbAaSV+nF4r8WCSP27v4AQ9AyikBAFSJqnJc1lx2hUGSRA8Sjp1v2NS87e//Y0VK1awfPlyli1bts9zL7zwAueffz533XUXV1xxxbgP8oOCwZd+xK05PgBckYmcHFeQhQx+I8aZ6Xocxtkjr9XZxWZ5E88LHvK0SZxoWCjHyN4TVXSjkBN64ASOBw408/2Db5AhyuWyWTirVzyNKlEhpWWwiPLIjsAwDGbF7byWO4tpsT0sFLexMfFVlmZCNCo2zg/3sTK2js15LSTlJIqjnUo5TbGSQLH3IGamUK7nU2woOAUnkpHHoAV2u2J0iiFao3FCgyBnJLxCEq+QxCea5KZNLsCfCCPro0WachNDXLfln+xWKmjMLcGRTlFoC/KgKlKvuZmklvCHbT7+xxJjTVphhTST09XV1HqHeK22GkXw8vHwa0R1DxmLhCiBiMTUjkESokJQcuLzCuSpKeiOQ/frtKx6g5dzC8nMP42cSAh3IoaiqxiiTLfVypDLQ050CAEXRZ1pdpQplHY1sTB0Ll3ORp6ecwLoBtWrdtHJILHElxGtnficGxD8jaSEBGTj/LIuU53R+eJLKdwWB1YhTa/g4br+82FMTk0PsFcK8C+thhp9Ib9WfstUuZkPV2zj4ZCbJTtPZFXtbsTmDmo29lOSPS6puskXMvz0+q9yZofAQHyQ9YOm7D69IMHO2GwU1zp+cWEua5YvRxpaxoQx/VwG5DQP2a0YaJS5ynjovHuwy3Ye39zJjQ9tYVtbiG1tpklycXQdXX9bzY7iFPl6B+H2DTzetYZeIZ9JlQux6FE0yWQOjcC84C7mWiHeuJN/3fwsVdu24XY4mHHzbVzUcx/377yf+3beN5IJtWZgI4YgMGecSU3AIvPtwWf4l5BLo1EMpFnf8zqiPY1gGLiSAZwSCMV9eOd6ceZupF1cQ1SI02LtIYJGY0oi0DWVizo/yqtCEz1iiAc4n8ulRzlF2MApQAKFV9yFNJTkEVIrSasTAZEyLZcZ6TJW9z9NU8xsEGsR7czMOZkT3ZfxF7mGifJTnCGs4Uqeo10r4QEkXm55adxJTUrX+eimRjZF4kQSGjbNQDQM0oPtRPr7sPn8TD5u2du/0SFGiT+NvDl68CdDGU4R1/F75Vbu8DvZbPcxO9rDpbqHm706k7ruYX739WzrXkeJ4sdIa+gpje6+IF/u7KdaSPJFy2ZyjTeoEDagGfn8Wz2LC4UXKVda+aGtCx2B1zf/AJdmoc/wsdGoZZU+kVe1aTRQDpQjSVBgU6kzuik3uunPy4NMgjO2rUZHoClQxIUdE1gyoZYa/zR2DWzg02ufYK9ipus/0jM4bqSmL95HSkshCdKoumcYbMoMgcVKTzaL9ZXePdyeaKdIz/Bs+w5spSU051TsE37KpDRSWpqBbM0bwRIk4LIiSyJzSr28EkzyUkuQBYYKKCQFASmdwJAEXpAzJMrs0BY+ajp1v2NSc//99/PNb37zAEIDcNJJJ3HjjTdy7733/r8lNeHWN/gEvaiCBV8ijxP7JiEJkG9kOC11GjZsaGRotG7iH0KaF5MTSamjRZ7+TAwnkGMILBB0potvMBnIEwtpts2kJA62LDdYicrvSHGuuJIAIbqVAM49As9F/sUzOSexzSojIeBHoMTQ+EjLGmJecwe5SNzOL/ksZ6qVzFBhBvWcwRJiQ3FkZGy8swJoJ/Z4GfYYqAIMWA2SUgrBgPWqWU25S8pnjvcFLBUxktFcevpL6AsW02qUYstoTO7et59Tm5iizdKP07AyTwuwhmKeSczmdGU15Xlxns2dPvJaBxqqoYGhEsKNgIZbj5OTTXkRdXDEYugixJ1OqgfG9L4SgWyhOzmTwjnYS+lgP2glJFU30zsGccl1ABTHapjYtJHW/mLawuZnltHwqwr5hpPZoXoGrQPE5RS5KR8O1YGOSoOtgzNKzIJ+D2VOAASqfE3klMfZJUxiMO4zGwtmdBrClVwa/g5/VH7JUmkbl/he5SnDQOubh+QSSFRFqWhsJhPXWbfkBFK5M/nt1gw2PQXIZPDwD+de5tX/hn93ns7rGZmko5eBvtVUpiuJWWxsKamm0+PAHvwJqqhRlPJRmZEYGBwgz+7jVE+aqZ9dyM3PNPDS9nYWyns5q3gjl6SXw37toYKGiz8Z53C/90ycVp16LYhdSyNnYuQkYzhJsU2F7eedR5lcTGxjBx+a/yHu33k/r3a8ylByiIyeoTncjIDArIJZ72jOvWOsv5vPbrmJCyw5XJz+LmfkabzQn6ZPhwnpDM/Jp3DS1H/hcg8BMFw/WgKG6x3PcGjgX8/W2o3kDkxG6ZhMe9zKnZyHX7djI0mPYKDvtzkt1vwsy1RRZPs2F5ZvYzBjZV0sn4b+Alb3P05zdDPLck/mJdfprHPM4NrkQ5yf6OMBCnm9bfxTu98Yio50Th++keUFtnPbmpcIzpxMaO5FXCFKvHXFpUOPKdutuAMvUirJ+BQrdiVFtaMRt55ECLq5LvQkCjrhdCGQpEeS+G5/Cy8o+ax2bKK452nSbafwrao0/TaBpeFnCet2jpebqKSbpB7CL3QgCBo1Qhc3W/4CwGt2G7qQT0lGpURXQVDxCnFq6eTD0gpQYDelrFCnsUKfzppYPS9TCmIpilPG5zAotQxRlOimcqCLmv5OdrfsYXNBOVY20De0AZtvAUnFwoq+IVK6jnUczNnDJuEiZxGKqKBFIoTu/xs7s3f0VPYc7UM7WNS0ji/842/0B/tBlun71R0IY8JPZHRaIt0YmGunpAyQnw0hn1yRyyube8iE0yQVNfveAlImhVrroua1J4g4PWy1VxP+oJGazZs387Of/exNnz/zzDP5zW9+My6D+iAhoSY47dmbifc+QtpioSZUw4zgdARBJF8XOT19MlYUYhjc4RB4IjOReEYHDE62beBT8hPka0FSmkyXkcsavZ5X9Wn8S18ECMwyGjg7+XtScj/TaWWFPonvqx9Dw8aV9udAg5VMoM/xGPaCAHNzVnCcoKMIBgIaIikM324Uu4GWEqkSe2iz7aSv8hUMtRg57cYSL8ASL0RO+UGDtJFmSIwzqMSIKRGG7B0MOTrJ2IIIlig+zU5RupDcVAmeeABrPJ/8ZAABUzHYazUrSw86rORM3guAzRnEV9BAfdrBYPdEBgcLCKfsKJodSTRIRVTiNkiiENNTIHdQpttZrs1GlUVK9R4WGCvpNnIpYJByOqkV2rGJGbqMHJ7W5vGqPpUmoYaJYpDF4h6cziRRw0JQFenET9Rw4DF0LNjIGDkoKOgY9EoRwkQRSOCWh/CJZj0Gl+4hKoZZ0tFDTaqQFAIVuWsQExroUrano0BU9rOmcC8Twxq1QwL2jIOCsiAlQi8hw8Gdxhkw08mOglFjvWyoOBJJJENgyOFlIJPLFXu+z83dt3GJ9DLnCK8yRd/DN6TPUmi3o0524dVdXBTJoTqUREZiBxpeBIoRuTxRxtZ4FQPxWUyKDrEldwsbc7YStBRjkWPEpSrSybsx5Ah21cGc7qVYdSt3/PYOc0CGgahrBCSZpUVOfhK8nfz0EABbjCpapBr8RpQ6Yxf5wiA3Cg9wZeRZrh/4PC/Ik5hQ4uaHPeBNxmmUetkrdRMUo7RmOihd44KVhchVxai2Tr742N+ZWWr6H+pz6hHWR1EnWZG941NRuKXyVB6d8DkaBDcWh4st8mmUaffTJySZmcygFiZwuYcQ007cPfPYk/HwSMRDxrAg+aCsrIeZxhoKpD7yLToUbSW3aCuFkQDdfeUMDRUSSTqRBLCrDjyql4DhZoJWhIDKFs+dDLk70SQ7CUGkItXLwvwO+oIeNgwEebGjnfq8ZWwScrjF9UmujD+IR8sQluDeO7/MVZ+8/V1/5ngmzt+2/Y2klsSluDiz8kzKPGW8HDRT109t28uEfz/PnVNOIJF3LysFHYfWh61tB7/c+Hn+d+67q6I73vA3bOXvOYvJ14tY4XuMMs9zzOpowZUcvfn2uPw0JM8FHmS35EWkj5/1hLjLb6PbcTfPu3cxM2PnpO5V1CSzXpKD3OFiGSuN1mK2CVU8oiSADoYSk/mkcDXT9DaOx0aFNkBG3ERA2MsEoZ0Jcjuf4ClURLYZlazTJrAuNoGt0Uo2G3mszZ0KE53kS2Hmtu7iuKYEq/NASWznattvuFP4FBHZw+vdXSwrLjlgTL2pDF5FelPC83DPIA3xJF+pLEQShAPSuQf+8hdC/7qN3dfa9zlONGJM3vFLCoPZHbGqUrZuLW2ZypHXCGmdPeHRQn2KpY+8rMdqUpGZ3SlHUqRzTFU2JQhY5AyF1iDzN72KgUD74quIJfZNHT9SeMekJhgMUlBQ8KbPFxQUMJjtzfP/CTIyztYdVMamkx8vwq2ZhscqzcFxmXkMCALf9abZEUtB3JwU062N/ND2d2akGmBYBRRhIu0skzbxNR5kl1DKXelTeUA7iQ2qqRoI6BjZdl2LvDuYmdpDWpDxzdmN2XS5nSI2HnScdqBpbSG18U4K0gN0Fm/FJq8/4HWCZk5mQ9BA1HACTuDAy3AzEWC4WUEmYyeeCSAIKgWrzfdI2QUce+sQIsejelpJF63FsA/iL1+Pv3y/tzMEpKSfRNrCgJgiromcq8HyzjN5uX8GJ0sbOFN4Y2wEZwRFQpCr5We4mmf2+zAH/SrM8RoSPfgJG056DB//1E7gaX0+evb7dcgG5TaVSUIT3kyIiZZtFOl+dkcFDEFCEy3069Dr3s3e3LX4MOj0CAzIBp9/rpxTpqwB4IfCFbQvrMdwKYh6Al9qJxdZX2OesIq69TfiipURlSO8Wpjh4VI7X6j6Lo81reCnfbdTJXbzW+0WrlH/h678eo6L7iQkbud1YzcDWj4v625Oq32eq/vm4xycjLz2Bsosm8iVc2nSnESlGJ321UyQFHT9WRRNRwY+bqsiz22lJ6URzmhomgKCQJcnlx2WPP4V/AYBIcxeo5hXjU/hShfylG2QjYKBGlf4857fUjOxjyJLkAcsP+Im9XLubD6TS0scfFJ1kNdTRFQrQJAbMeQuXld2MYcMHw3N5++2R1jd/xwrNlyDrXgS51Wdzecf2cLxT1q58muLkVzv37C6O6Pw46JLxjxSxxT1XlCAVDmLprwMukTphi/xUtLDj1PmjcBVlmagohxDlLiXa3AYMRbrL7Mo9TK11kbs7n6q3Af2ZMtoEindJJlWUcMlwSASZO3Drdn/Uiq4Ix2UBztY19ZCydBZJLFym+8aqpN/Z6MzQzT6BOt+m2DWZ/6EKJkhBFVXWdG+grU9a+mL92Fg8NW5X93HVPzAc7/k933/GPn79c7X+dsZf2PFoHmFLnj2SdokH4pvJYagI+JGMlSCciux7Y/DESY15WdPxvP6D3BaolyWCCNmyYxuCERsNvo8Dl7efCLnFxWzCuiRZLZRwRRa+PLgsJT45D7vqWswGHQRCdtJqFaSMYWtciW/mH8FgyErggGOwO+RgMWuIZZV3Y/dFmVA1OmJW4j1+dD6luIflMjXIpRbm/BJQWYIjcyQG7kGs2BfxpDYEylm3ZYJrLDO4qmqEyhUqpDiL4IYo7x5Oz/w/JJvlX6dJ5+6j2Ufvhy8oyvq3zr6+ebudoqsCjdPKOXUMSnihmHw65Yebm4yN4qTnXbOyfeNGIBzHcX8urmH4154iUSRTmZsyxsDEODRRSJR0UelPp8zXnqahZvW8XpF5cjLhIxOyxhDsSbq+Ozmdzqx0CQ1tmTC9NIAGUFAyheobDNLiQgYTI3tYLPx/gogjhfeManRNG2kaNTBIEkSqnroKwr+9re/5ZZbbqG7u5sZM2Zw2223MX/+oa3v8Fbo7ethQdc0BMG8CCUD5qsTKBC8fDnQy6agC4bM15ba+rnB/SDnR15FTIEqCewt9vKyew7bmYY7lWFBaAsnB1dSr7fzY+WvXOJ4ha8Zn2ZXrATDEMEpcrxvO78b/DkATfk+kqoEQRuSHgDDhqobCIaIiIyhaai6gb2ng16bhVpgqthMoqGQWs8ugkIFqstKxtGLIacwpIOYvXQBOeVESdmxZVLomsB2u0bUGscnGQRkA0VJ4FXayGgypYYVBND22CjVv4ggWaAXjD0fIZa3iVDRa6SdXWTsfRhy9nyCgWYPYrHD2PJ/s3Pv4Z6Bj/GfthOYlGmmSBug2VZEo7eUjpw8Ei4Li4Y2sWRgMzWhLioSPYREJ2uVifRKPqxChgJtkKpMJ149ho6AzUijCBql9IPQz2RaWCZtokXI5wVjNhvSNci6hiOR4lltLq5iBx/xPUHKMKhVUvhtKTxYMTSFkK0HiyOJlHWlbk/UUzJ1ABsZXmEam+fW8mnlTu5QL0SV8wjaplMU/i1OT5yWxd8lrQvYRINqAb4CdFBC26QK7qw+gUs2rWJCsoP75R9zafd3eDB/Hr6yJNV6N9Pi2/hUuoOgGiW66x6seT/En1KpL11HVfUGclIit/daSVl62AJgQEDWuSI3TbllDRStYbipiaYrPJy6nFe2VfHwwDcJiGH2isXsrg2gef7EgKiyUIDFgCgYNJwoEBu0MalHpSCc4rvK3RjAXzvO5A9VLuaevJnJ8c0MpXOQe53k9ImsUxqpiOUhGAKyowWkGIn2K/hTh0gIjc5MknMMnfxxuCZt3Z1U93aQEw+jaBoN+Tq9SnaeefIQhDbydlzOy6EKfpKNrZ3vaePDXR729u/g1TyJLXk+2v15PC+dxfOOs3AZYY5PL2e2voYqpQnbmOtEkTQUSWO47JhqwIAqkEFCQMQpZHBJBlYZ8Mt4/TCrKkpD6iHKuqdi769guWMZ8Cwb7DLXdD3Gtu8tgKt+x0vhVTy342mWdkxnUqKGMtFGi62TLw58gT+dbabmN3Xv5O6mf4ILXCkLUWuaTb0baY9H2BY1P9/sXVtZf8bnsOX8Fl21MjVZyGZXA5XJQq48sI3aYUd8y06qrKO9imKam/VDM9g8VERKjWPoYaCXmT7zhi/IcT6W+hqfy3+aiu42qo0mHOE0QlghnLARTDnoTTpJiAopRSKlyKysncPz3hMQhnQEwOvsxbC3YAALS1pwyKNtU2RHGm9FL1SYPpNeHVqDdozOStxBmZykSoEUJlcJoYgak4Q2JoltfExbTlfDndwlnMa9leXAXhzpbi5o3suQms8fApfws1d+gXDOL+kOJfjaKw0sD0bAKtKRo/PxLU1cUZzLTyeYZRR+3NjF7a29I+O6r2uAc/J9I0rN2riL1i27OKVhN1tOE0aITGGskPxkgEZ3M1FLlBfmR/AMlnPaywILdm5GLDufHI+d/mgaMjrt0dFsVoBi1gMn4HUo+N0WiIRJjsnckhWVmradI39XN+1mVf2CcZkL7xfvKvvpqquuwmo9uEScSh36dK5//OMf3HDDDfzhD39gwYIF3HrrrZx++uns2rWL/PzxWA7fPfxeLxOMPBQlgkcR6LGq3C7E2Nrnweh3USF0c5JjExdbljM52T4ibezFyyvBCoZ2udDSacqEdaiSzIu5JTzr+RgLnHs5T13NjMwenuF/2JJTy2bHBGpSbcwb2IaETmvay/Ov1eDvE4hYdaL2/X+bYelWIBDJoaIsCUUwVWjiX41L+bB7PSltF090TmJIW8xJRVsp8O4CAwQDBMOgOXYc4fhkCq3bKbG9jiiYxHW2IXCffRK35iXIyCqVIizt97JXrOanwnMA5DTHWVXeRGQoSCo1RCYTReoQUDaVIgpVGIKEIdjRRBtWu4jbm6LIPYTPYaDLOprcQkhwcIm4FcOfwq/04Ba7qDc2IBgGQhSIwFDQihaXaVegwxdAs4A1vwW/pRcUjYSoslMEVXST1G2kdCtCUsaaMHAnohTEo1QPRqlQe7map7l6jFjwUel5zuv8EbdEruV/59xMocVcYIZn+4jYawg8rZ6OtNbO5/kzcay8PqOCrzlu5oUdF/NJzz+xZgQMX5h/7LyWb8z/FYqooWSNtroBUV1B1wYoMAZwCirtkzLkNinkDqX4g+VXfKjnxwR7PGxwlbIurxZfbpR53rVsyt/Ogs77qLWkqKreAMBENZ/P54TZkFJpywgEdCfX916Eo9dCe/GzJLwtDEp5vCSdwqvRJaQ2Z7gj8zPqpA5Cso2uOQks1k4qDjrrDbQiga2FLqKtEjUtcb6r3E2f4ePxpkWs9i3ElqdxLX9EzYGW8gq0tmLaB9JUx8vY62zl0py1JHrOZpohcRIKMa9Knmt8wk+xlhBLd79EWk6R4+uhujXIs26oTsLMyq3QeDKJjsWkdI3viXZKEJkwVE8qEcaTCDNxbwRdjtDta2VtqYc1BR72BHJ40noBT3IBGAYCBgYCNpL4GMRBHBmVFBY6hBJURQAhO5EMHXu6gbrU00wXtjLXHiNPSjHNrkHVJiqrNpET8vGbMKy32hDFPqawh7X3X8TM6Hc4S/8qQvMrWNN34a3oIOVOEF03m98lPs50p59vDa1DttmAFNMG57AhsIGknOS2F38N9rMp3NLKK5WL2FHciX2gihPVKp4seRzJEDlj7wk8gcRbV3Q69NCnzuDxRycRVRWiqoVIxopJPUyFQkBiKFBOi+FG1iVUUWNINvhh+ON8susvNETsJGUZQxTAgvlf1ihkACsnLWWNMBMhoSFZdC6peoRA4BX+FrSSL+sI4SJ2d1XxkroXJVPBBeFGAtYQyTwBilRkt4Y9kIJACg3oA3pUieRgAUK/jCuo44lp1CghiqQgX+cBQpF8HvPYeFqeygWs4qrOh/lj6cWse20df+xfxfO7+jEMU0AEcHssDMzK4a7OASqTUWRR5Pb+BBgGF9qcPNwzxItE6EimR1rv7E76Of6NdYiGwXNVLhAM7KqdRb2LEBGpC9ezouA1+hzdDBSu4DM3/oDf/fR7TBpspXDyApbv7EXQDDrGhJ8AciIvAl8GoDzPRW+ka0SpAbCnQ1j7gmz0TEcUNKaFtlEr7gZOPTQT5F3gHZOaK698+4qfh9ok/Mtf/pJPfvKTXH311QD84Q9/4IknnuDOO+/kxhtvPKTnfjPovb38VPYTjpppdTIqE4R2rhWf5Hzba0yl2axglzRLorTGfGzqraQp6kRVzFCHNaNSGIriTmaIdvcTdNrptlu4R5nOsoK91Hv6mRbbw7TYnpHzbh4sZHlXDVW9YYJOFzFnMaLoQhBdINoREDCMNIaRASNN0JemvvU1k9SITXzN9kU6EzkU24NcWLYVzdiGJBjoCWiMBujPlDHTt5t6ywrC0g72JhfTFLmKwbQXv7SH43z/4WPJ7ZzYKXFDTiGNVjdbYouxR2tx28w086FolN7WRw74zhIHPAKxKAT7oAVAcCIINgw9vd+rC3BIfjxKErusMpiyE1MtTPT0UJcMIkXASAiEc+y8Ii4gaTgwJBFDEpBFEcWIkIj34RCTlLkSFKWjOHfoaGEXW8vtdC52UyCEKFWjZFIK+ZYYk6Q2vmL5JzdFLufba7/NcRN/i2A0oWoiF4eOZ3LcjSU0mU2WKl4Wu3le/yII8EK8jpmrS7jXfx0vBidyasVLXFb/MA/svICWcDl/f+kHfErvISMm6Y+G6ejfOVrXHxgEkrKGr68RaXYvJfIAd9pu4dLUd0hFQYxGiTbBcvci1LrT6a7fy/XCrTiBzJ7jqG+8lmrgNDS2yDuYrk5BRMAr/xlrupWfVnyCx+TFyHujiINJrpKe4TRlHaohsDJajm/n6SiCBQ0dTc+AEcEldOAW9pCWu+mRJNJhkdBrLnbX2ZngGeBXyu/YkS5nzxaBlxedSNSq8EXxduqcTTCxCV0XiffksVeFzc5t/JGLELIxwqYh6OjcS2lJ7Xu6Dseiofc5Ln21kZc/3ItWWEZHezNgI0cI0LOrnuPaL2FzuBMtHScl59IpOdiVCaPpYQw9jCFEQdWhH/L6OzhflHHaXHQU+WjMc9Pic5GSZfMaw0BHRtIcuJJJCiJhZgX34g8GcSQzWDMqgq6TEQ2iznyinnN5xuXBmxejWm6k3NGEK7eVKs8QnpiDMPBreS5fz6xhvhpmo/fndFgXQvEukrLMoKeKiM1BsClAyWuDbBIkviRdxi9nm7349FQBuckAHa52Gnc0c3fLKiQNtLyJtLWLOPXjeb32HgCWJvKJz1iHsGbCm36XhwvNL29idyQw8rc1o5ITT1BYsBS/fzIeJZdn9G62iRIe1U3QMoRkD2GEc3lg8qV8ZPN92LQ0kqBjtyRJ2yApu4hLpTw39WxauyXEhIbVnub7835Cni3I/f2mBzBnqJLtwcU8W/A0YU8Y2MKmAlAEL5oeRR+yUtCvMzulUy/pFHjA5tcQLQaOvDTkpdEwr9l1up2cbgt5TSLVahKwIVh6WO8oYXa8gy+33MW/xSX07FyJQS26z0K9z4He10tTWKdw0xCReoW+F7Ibw/xFGAMSTyZVrEBqQR73dvTQGGrMfnE+5qx/hbDTRoPLAsSZMDSRKrUMKzp7pR7m9s/i2dJnIb2Hst5XefDcjzG/ay/u4lN5YVcvhgF92fCTXddJiCKp6FZIRcDqpqbARbgpvY9S4430sUfJ45XcJQCIuRIztdV8/ZbVAAQSefzPd39+CGfMm+Mdk5q//vWvh3Icb4t0Os26dev4xje+MfKYKIqccsopvPHGGwc9JpVK7aMgHay7+PuF7vZzq/57Kizd2IUUOUSwCaMucM0Q6Iz56Ov30NnnY7e7hJjTQX6lhzx/GZI9B5cvQH5JPk7XIG889ResO/qY0TqILaOxtyWPXa58ArkxXI4UkbiVUNiGpc9gXqabLYtncsLl38bl9eLwWHF4LNhcCqIo0NAd4ZLfvk4ypXL+9CI2PLGNeQjkCWFkEnS9WIJYJxGoCiLLGk2xOp4bupa0WEXEYWVNn4FH6CWq55OwCOwqkmgogILwSezYOpfjPX8k3y7y+b0nszlxGroaZVeJ2fW4Bz+9nmLs3gC+vAI8gTxcObkko2m2dw/RFo4ihOOgJ5iYJyJnYiTCgySjg2DEMIzhJmsCsm5BMkTSYpq4ZiGe9f0gSAiCzLZwDduECeiWBFg0U6DKtiZANa01WvY/AUhoFnaHLOzGi7VE5aRIM44WkUUlnWTyBApscV5vrmSDs5jzy3fwSeEJXrTMYmV0Ei/t+AJ1VSv5YfudVIemEbDcwpCi8T+ld/KLhjvxSAlak352t+RgsJ0SjwK5Ai+3LWGeNczrbWZ654TeXawPrRmZJyJgk3xUuyZT6KhCTQzR0PQ0u8VqoqtlFi5oZaa0l+f4EbfHv8FmxUWDRYVIBsv6AfaWlXDjxJ9zWccjnLttPVsSfyBgO50iRxUzVbPnklN6gpelbj4/5U9kOjSUpiACMFXYy7flewF4tbuWtq5ctjdtwUDfp5M5gCzUUGKvYEZOOwIJun0K6ZcMmpfpVLoH+b54Dx9Tv46yOcja+cfzq6CNBfyeWneUQkVnaUEPz3TaabP28NyCb+EfPJkVfTmkPI3clHfLuFyTNY0yz398O1OLRYJr/dyfbypAucGJSKElvNjxV6Kq6f/LMOoLezMkgEQCrIMwCfO/dwsrYI1Dbt/oYxlgL3ZEWx2uRW5qfdtZr8FfiyZjbyzhC/IjzEz1sLbgDUKVOhIQyP5XFYA98+ro1upobm/BEAwcosFlS+5jRcjBwxEI+XbyY3kxuXaDll4rU2KDTM1v4Ek5gk8yCIdPYGengT+v96BjPpyoWXA6/d31TN12J/ZUhCG/we/PqGepYeGcuFmA0j6wjd35eeSoHoKWIeoD29kariY6ZOdvE67hnPAA9QkXumDHYo/QWpvgifwyYpvSiGkNhz3O9+bdTEZy8tTgNewOPwlKmNxoGYG2Ls7f6qG1UGZ3WZSuQIoMMRAEvIbI4kSUSak0d/g89KZl5G6DL0ZkTtIKCTsK6HJHiHqb8NjCDBTL9BcY7G6YCHSTFONUZyLsFVxc3v0EZ079HR96+B7K8xuZKOZT0T+A2rySsG6nqaMcS5MNvcyHYQhc3vQiem8YFRUdDbHToOeFKOpcFUtG5PrX7kHzwZ+Pn0FcWYdVs/KlgQ9TqPvRBJUZaiVbtVY6BzvYlLuZ3bmvUhM+D93px7FxBeWqgJrWoasHwQEzkhlWOqx0SgbseAxmXk6pz0aIDClRwJIRyMgGrkSQTtt0CpPdXOpczn+qN7FWHjU5n9t15EJR77lNwuFGf38/mqYdYFYuKChg586dBz3mpptu4vvf//4hHZeORp3QTpk4ulqlNImehJemkJeVhsLmUi9DE3I4qXYB1y66Gp/9zQ1V1cedjmFo9PQ8RXPDizStaCPelKAp7sYymCatSCRzFbbUT+JVaRm5LjvHV+RSXrxv47R4WuXT965jMKMyr9rP9y+byZ2DCxjoaiTfEmaS0cRr9Wdx8tp7CG3JQy/08ErpN9hQE+CVfI3QoIbLK3BOi5vGwBCrvbkIfSmE3WkaPQr5xTVken+DEDcVITXxBlpqPa6qekhDl+7ntoqPcuGsEn556cx9xvbyrjYeengnojXNxXNK+dTFM0aeSycT9OzdSyqeIFBWCjt30fWZ68zvWoKyx5/AXlSMZFEQRYlMOkXiJ1W49Rgr8y5jetdDBFUH4XP+NlKrZ3h/YbE70Ls6SHe3kztvKRmLhaYtr7Dh3nuZvXuA8DYHVaf3kRhQyNmcIpjvZLO7kOn+bm7V/8oS5WcQ02hoXMh10xZx296bSWcsfLb+2xjbEpwqrgNgRVcFBiJOfwH12hrWUsVOvYif7D4PgHIGWMxzJGadgyFK5HryyevJwZFwIRNGEHcRungGly/5D39+bjf6z25gxW6R4yY0U27dw3ekG3hy6H9pSZSwwtfJVj0fuS1G0urmyaKz+KH/r4QDe/hqqAxnNMQpznKWyquwy3/hV5W3o+5MIvebZP/G2L+4xv8YFkFlbySHgQY70coSHFarmeJpZMNjqOiGhhYdoi2u0JqoAUGiX8nDPtXCvIaVlM0aYqmyiRP0Lbwcmoa8N8L6ugVcuqYOd2oPjxQ9zFy7ymRrJ5uSAuv1Ps6ruIeJ0Xomvt6K5ZwBKHv/FXV76x9hTlGa1wdOYg6PkxECeNNOpGg9Stc6+tQUimbQac/HnxnCYmSQRQlnNIYrJ0D+smVIsmJWChcEEARimkFrKs26cIK+jIqRnVtSewIxqWEUOan3emjfE2FQkJkwu5DN6zsQDY3UpBwYSGP0q0wu9jK9wsVT65tJJXTUMhmH9CT5/W6k6BzIW0e5tJbf1H4faa/O56RHmdvayyOdC2nMC+CW0thtUQoKG6gVG6iVGliZK/HGoJUSRUcQoM6RgIidoGWIH035Cf2qhFisUKB5uDkWAlUkmjyF/43dQ43Uxe+lI98uQYtmmLP59yiZFBFnCVvqP8Lc3ZuJZ9bymiOIS/axVc6hT8pQqvrYQyu58SCnTt7Ic3tmkUnCw5YA2Axs3jSG20U8movYmkQwIOAa4JTZr3Ob7X+Ixmv50eYGnqkOI+kShQMe3L17yBx/Hst8ds7JpNi9bRev5CZ5dc4F9Et+zmr9HfNtj7NsoJdfOr085XLyC4/Gtuhubup8g4l6Ef3aRSjSJtyWVxENuLPww8BTtMpWfJleRIvCqj3FfDHnXp4pqaeqdReprr3sBsC8J7jpwz8rQOm0FzAMgcbGORB2E4/0jHxXfYqZop8TtjDNN49kTglP55jq26lGCdG5v2ejoJNKKPRFXEQS+XwmeDbf8jQTVMI0+3ZTJ9YRauzg3MG15pt220nLZVhcSQyPRtJiJ9axk66Sdbyx61fkK43kbyinfshBS0Ecm7MDrx7mG/JdpP17GJBzsOgGvmy/NXFMxvjhxgeG1LwXfOMb3+CGG0b7qYTDYcrKyt7iiHcPuzeHtf1LaUFiq7WXTV6dpuIaSutO4I/Hn8uDD2zhtS1dLBFzuWHZgndUJjuU0HhwWz3PbPOyIxpGz6qyF84u4bMn1lCT52JbZ5gb/72ZrR1hPvKnlfztmvnMLh8t7HTTkztp7ItR6LHxu4/OwSKLXPaJ7xP+8n1QCFOFZl6quIxwmYg1lcAem8sL9RbWSCrS3gQSkAjCfRM8iAMppIYoMipniavpiOTy1JSZVHQ3oWR6UZPrMPQkK2efyBypBdKmUgPw+JYuvvuhyfuU2m9oHkIcSiNLAl85bd++JBabnbIpo92cjbx8Ou0iQkJHXTgDT1X1Pq9XLFY2eRYzN/wciwYeAAvs9k1h1vEnvaPfz19aguflX5NqUiAEq5fXIiQzuI0MVT2DbGguYpK3l0Kpne8MNvFLSxHhuI3BzRKXLfgZVlkj3a1xcuJlbJYM4YyNnqSLgstP5GPnfZnEDyaQm7mDryU+RY81l2q1g69a/snSkl3Ybnz1gPGkknEM4xSK7WbmzCdPncCG3vPQfvYbns5M4ISJTfgsIS7O/Qrd6TqsmYtwWROsVCtR9kTosft5wT+fUwZXUVWT4s8t1Zyt/AK/tI6v5X2JHc4KLLsGcAhJbrP9iZNtKwFojXnZsr2cB06dxD+/8Yc3/b5WP/wb5m/6Dm90VhJ2l/OotZb79EV0F7RTGBxgZm4XPxLv5njtZpTGMFqejf+d4ebzjwY5qWUOu0pSOByVULiSVTGFc30ZKqfs5FE9lyKijEcgJDEwl0TeSubtama533Q9pUMzUGIOfhxYzPmdb3By4xpuPfmzGCLoJwT45zevxxuL8uz/fpY3Zs6l3GahyKqwNhzj5WCEjtSo+uqURKa47ERVjaZVXRgdcc6fW0F+qYd7eragOGT+c83pnDL0Mrt6o6Tzc5ESUSRnis+cMo1L55WzSd7Ik+s7EHPc7P3kF+iKdvHdP/4FjHV0CRGu6VvD3yddg9ao8AX1Ic5XV7KifRp/0S8lX47ga5mOrXQTRY44zVoY0CgcmM5jwQSzND9290YSaHRpAuVWFawqOxIpulUbYOGSlkFqpC6CeEjKVePwrb8/PL7735ytpQnZLKyucpOJPwJZlbAj0Y7V6WT+xy9n88s7cKvmBi4uaNT393Lq3NW83jGLaK8VMaGRHFRgEKSs882Rk6JnRh13K5OZpO7lZ6uDPOIx1f2cVB6LVq5hzuWXEvjMp0bGczrwiWSKj9z3KCurcvhd6adp2jWV43Kf51z/dvJTce5N23na5cQC/LCvi0LRTMXXNIGv195Ah1AOmafok0XajBzK0kHKy4fY/UoMzywFZ9cCJDlBAg+GYANEypeuwFP1CquiEopoMHvCSkK55Xhev4qd4TiyphP3rGDBtiTTustIVrTSV/8ivZpJemaUbkNTDOxAv70U1a4hphLsrNjCCWI/Dw9ZaM3bzFJPEkWbTyyTQzqaADJ4YwksIZHJQRuG6OaOljU8u+VpZjV48UdHN+K1fRYqJZ2flj6ITVT5iMcUGqrCk3jw8w8gitKhmibvCB8YUhMIBJAkiZ6enn0e7+npobDw4Ls7q9X6psbm8YJVlpj+1W/RY/HxvZ0dSAJoBmwVoE+FG8+cyHM7enhtzwDP7+jl1MlvnhYPcMcrjfzqud3E0qNUtzrPyXfOnsyyiaNm6KklXu775EKu+esa1rYM8rE7VnHHlXNZXBPglYY+7l5pNjT8+cUzyMsWUmpTDcJ4KSfCVLGJP9s1Tm6bCoaVAYfOGouC3BbjImkF1whP8VfjTP65+0QA5gvbuU27jQJbiKShsGDwDp6eJTBn8x6SviK2TpzLtgkzuOCNHwHQ7qxkUq6HHV1hHlrfwbVLzYVT1XS2rzfNf4tnFlHofesmdIIk4fjqVwk/8RhTbvndQV9jm38F+nPPMyS42VVxOVMv/PpbvudYuDx+LAUethdZmNw6gGfALMUWtck8tljnnNcH2VmVxzRfDwutT3BF38f5V0CjO+FE3jhEqtyJZccQx4ubAWiO+khY4LRTPgqAdcJCFu38D8uNr9K/3k3xgiH0jECscBoH++RW24E9kGZcdg2vP3EXtRv6eU6tZXZdJzXuIMXW3Vwp/oZM7GdowBoryI0Rbq35OKcMruLy0DMELRZOE9fRYcnjnvoPIa8KUi+08gfbb6gyOtENeKO/graGAA2FUX5x7c1v+X3NOvvTdG/6DYuKm4FmHFqQJ/RFPCFfzoLOdib5eilT2rlGW8NfWIB3azdDS8r4+7J6rlyewdEWpCS3HUuehaSU5umQlbN9KU6aGkQwxid70t/UxMvpD/ET9Ta+5zDrePS5FvCPQD6ZiEDU5SYlZO2ZssjiwT68sSj9Xh8/za9E7w4e8J6SYKbTnpXn5eqSAD7FXDqPbwjR2hGnNRhHdJiPOc36Ckwv8bKnN4rck0CImKRoQoHpXl1S6efJ9R2ogyl60yrF7mIWnnQewVc20uDbzUO5D3Hy3ghPlZzCGt3PoshDyLTw89APuVv9EK+q85neZCcC7Cl8Gez9xC0RvhRsYkKig5VSOa864bVdswkLbiRR4wlbAyghrINTuEE0G9f+vOxqugqOfNaKq2oS/148gD0McjZ831IQ55Ul1/HLk07jxFwPgijQmkzQssVMM05JKablNhJ7YxKl82P0TJBJRK2kwjJaBAyHjJ5rRZbSXB57iRN8d1G0+bM40rmsc24HID+cT0VoG55zPjQylpZEip82dfNo7yDHz5rJ1OYmtvryeWLicXS35DF1eyN2PcFidwuv5GziUZcT3SXy/bYQoHLz5Mu5x38ux+/+N4NWEUPQ+bRxLQ8Lt1JOhImFvQxu3IqmORCscxDsVShqL64lj+Kp2ktYg/uDVgSgtiiJN7eV1KJbmfTILLpDXcxBJ2ci5CzegtWTYUNExhiyUCSLPNV4KVvCUxlMejD2My8qSgxH9U8JimmiRZuYVLoD664T2LQqiKFDwqqQsI4WflQzEidt2DcBxymnuLBsG/k20x7woiWfrVYrGCL2lPeIExr4AJEai8XCnDlzWL58Oeeffz5gNthcvnw5119//REdW35FHQ3ZehBVdis+WWJtOM7T/SGuKglw7dIqfv/SXn7y5A5OmJCHRT54gaU1zUF+9MQOwCx69ImlVSypDbzpjd9jU7jr2vl86q51vLqnn6v/uoaltQHWtph+gSsWVbC0btR8tyOWZCCwgCW0M1VsIh7T6bM7CMQMnpwWpbAhzh8tv2S2aBqSf2r8ibDhYKLaxpfsD430PbEJGa7oe5xbTvgcWyfOHnl/ezTK0tQmEGBbTg2XTyvnO49s5b5VLVyzpBJBEPjnunbioTSGLHD2gnemmlV+9Gr46NVv+vzUpefSU7kOb04BixyuN33dmyFcMJec6jdY7qogEE3gjaeQKlUcUwsRX9tLU2cO03w91NpW4bd9ms9v/g8/mPEhUkNgGTJTe09WzKyj5pifUK2VfKe5GIi1yzB2/AeLW6No3hAAuibgLJn3jscnShLSiQtIb3+WKbuD9Lqc9CadLMprwyUlqEysQeRc1lvjEFNZ76pnr1xCTbKDW8Q/AvA38VzoSyNFUvzJ+ksqjF4iGQtPdExEaRVJOXqInn0D5fm+txyLYrHSMukTFO64yRxbyWwqIw6aB+K8OKGY+uAQC/LauVJ4nLuZSzImIXfE6C2t4o7jfsDxW2yUD9ZTEi2lydvItv7JlLsH2Z6o4lb/wXOt3i22qxO5IPkC260W4qKIqLooUlwEDYMMAtaqWhJbVwFgSAKnNpkBgIFTTufL1UUogkBTIk17Ms1Ul50Tc9zM9zlxSgcu2MU5DlqBrsEEstNcTn3ZTcQViyv594YOpM74cBSPuiypmZNVVYVwhl3RBI29UU6orOGe9s9g7fsJKbmf5cXPowpP0a5obMwxj3vMleHXvY+wILmDrzm/wExpiCGr6RV8rvRTPF1TTmW0jeM6bgKiaPJO8nuWss4Zpt0dwjAEvhHag1XI0GkJsC5nEr/rehk4snVqrv74Rzijz0tnpJBrLHfzfF4jDpdKV34dA5qGkK2/cuK8Kr6x0VwPk1KShOZiTp5G7rODrJ2isKo2BwokbIEMlZEQ5zYIzMt9iHjZi1gHa8jrn8lyeTN9NtMucNV/NhD45vewlJYwmFG5taWHv7b3k87+YC8MxcCXT1m4kzZPMWuqJrOptJYJnS0UhMqZNORku+91HsdO7gyBGXaDB4XzkNNN7LY/hqgJaALstHj5duJqblH+xKKcNnpibhqjgPoKRF7BN2OA4hrT2/To9pPAtxID+P2Wi/jClMexB8KoH32VHFWgwKkiZG8h/fEcnuh3gdxPU/s57B5cjI0UFUIXeUKIqMVBtyWAMxGlQuuhPTiZYGAjd/eWc4NNZVLFY8wv9NC6tYzepgJ0QwRDAyONYUQxU2Ht2HUX5UoLJ1Rux60kiOl2Pl10I2tTm1FYQ0m8iPacD1jvp6MBN9xwA1deeSVz585l/vz53HrrrcRisZFsqCOJ3mx/nXyLQoXdwtpwnFDGVFs+e2IN/1zbTlN/jLveaOYTx1UfcLymG3zv0W0AXDynlJ99ePo7ClU5LDJ3XDmX6+/bwPM7eli+07ww6vJd3HjmxH1euyOa4KGFl3Ld2ocoFoIEtCFeq5SplbfSrp7Cz8W/MVvcg2pYiedNxNO/id8rv0a0mBe4Mf1S9OLZSE9/nSuEZ7mn4VwGKk3laUJfhOsa/kKF2EsXOTxWcTzfnVHETU/uYG9fjJWNQaaUePj5M2anZLXGQ9E4pfACFJTWvOdjbXXHM7fzPuxOCctJ36bnqV+wxLuXnOrPsnrabdTtVempclFgj1Jvf4HX82dzevBFHguchoHICcpOqqRudEOgNeajat6YukmFo60dBBG6JYlCmwZ5Ew8ykjdH/qIPw0sPkV5vw7MrTdmpQTqTLoptUWY5H6UjWE25VkqTZEPoT/FX+3n8KPI7RAxC7XYePO105F0R5gu7qBB6SWkSdzfNprArzoCvn9cv+jR/ufiadzSWGR+6nh17/kNGcjDv6lv4yMoObnpqJy9yOSf13sK8QDvl1r2ck+rm35Tg2tXPUKGDlP9SXpv4I15nC/lxk/T1KHu4TbudGVGFwVACh9v+Nmd/eyTz8lnCNv5uMcMUSXsNH1u/nr/6FgOgFxWTkLNzTxYxNpv9mc68+mOcX1V00Pd8M1TnOFgJDIaS2LIKTX52EzKzzMdxdQFeaTAL9pX47bis5pJbm+dClAR0zeA7z+2keWMfoixww7mT+LXyRWw93yctmzVmdMFBfiQHVeym2QEfKS7krq7d3BX/Hh+3XIcqpjEMCeVlkFy9tFYF+EfZDXgHfsBal84W66oRD1DBYD0XGc+iGRL+RBWPbPw+jYEz3+M3PX5Yvm03vfatWPQkcn6UAXuaevJYD/SN6V02yetgUDTVhJSYwug6Hu+8v5MX/zRnbDc4U7kdrWA3k7d8meJYKX0T72ew7EUMHZIbPkK/EGadcxe6qGNPS+ypnMuPK6aSt2EP26IJQqq5Zh/nd/Gp0jye7A/xn94hTp80jakOhT+29LEDC1sr6tgKSNpcKlsNwtIb/GPQSqtlPgOym9y+n6IZKh6bh3A6jNPTzz+jJzLXsZtLMy9xTtluXt5Rx+60B+/cEIULzTnStGUR9uSocdtnWckfV13HtXP/gtth9mTDMBDb/fT0VrMrKZMu24pgwKfjezjJ/gwzjD1IYw3+GUbu9AMxkdNziklJPUxu7WFuMgWEQG6DOkgKNnbHTmRXYhnoKg66sSkaxZadTHKYnsEhtYivFH6PV7psuKvuBqA6VM36wl3jPi/eCz5QpObSSy+lr6+P7373u3R3dzNz5kyefvrpt6x0fLjQnY25F1oVHNlS1/FsI0e3TeGrp03gxn9v4TfLG7hwdik5zn0rp/5zbRvbOsO4bTJfP3Piu2pRb1Mkfv+x2Ty2qZNYWqPMb2dhdS42Zd+d5c5Ykl5nAZGUC7c1ykxxD89Ix7Gl7nw8K1o5SzJ3r/rl9+KpXQYPXI7Y8AyGICKc/hOEBZ9B0lVCy39OXqaPz7e+wanNZ5FG43nnJi4QngLgq3VfJaK4ERWJ82YWc//qNq6/bz3zq3IYiKWRXArJcice+chLlQBVs09BXAGL3A201FYyK3cLomBQNfNU2oLtFP3wAbYECygoiTLN8Rive26nvP8Zzs9fT0p2crrwOgBdCTdJXeakGaeMvnmgdkTh0utOw9+7HULtkPfu3CPVU+bTUy0Q2S5hjUG8wUbh1AiaATXuIBXhZ6lMX0+TXUfqTfLg1DP5+ut/RYmq/GfoeHrtOVhjvVygvALA7kgA51CS1ycPkTz5s/z1ws+947HYHC4mfWs04/CiOaX8/NldZDQL4QkF7A73MNHbz9XqIzxmu55kRsHWNES8rp5K5tLHWsREBJfsImqJUtXxKpUdLpTpNih9/1VJPXU+VrdMZblDAgZBKWXZc0/x94sXAhJ6boCkNRvmkwRsiQS2adOw1r77dPLJWeUlGVfpbDcVkxL/KDH7/El1I6RmYsFohyVZEskLOOjpidGysQ8BMFSDX/x7O2cvqeSJgu+g6wOUaH4ult3klxawcTBKk/Q7doe28IPcPO7p6uRryq/4Dm70VAEgI0ZVLFsG0XJ8ZCrOQkk+SUoxvSVaqohfDu4EETar1ejRC/FbqtmU03TE69Sk9BDWwIsIuS/zVPaxPI9J/Pszo6TGJUsUSXZaMMNPyVgOzuBEShf8Ed9mJ/d1XsJl4Y+QH3fQNu33JIrMFOPel6ayWK3macsGBqwDAExq1/nzxz9NTyJNQ8JUGSY5bXy3ppgTc9wIgsCpAS+/rC8bWY8vLSlgbTjOG0NRXgpGeH0oyt7KTxHo7CKpNbO8twG/8HUEbZAiZxHzCufx6N5HKRRbiDCfb0Wv4cTc1RRE45w0aRcVngpCVUEIQc7OXE5IPkHK7+aVbF+9qKObxwe+xVPrFiLKU9FsrUxO7KJYHQD28Duf2Y9uaSLBV4Wnh21IZHQRRdSJI+JAJykI9IkWvLrIudEY//S4+bPHR35cxyvE8Apm2N1mJJnueJrpjqcP+ju1Fjh4MH8mz3XkIQuNCGIai2bBqtmx6N3jNBveH95/Z63DjOuvv56WlhZSqRSrVq1iwYIjHw8G6M62es+3yDikLKnRRn0xF88tY1KRh3BS5dbnd+9zbCie4ZasgvGlUyYQeA8KhiKJXDi7lI8vrODE+vwDCA2YpAagr3whACeKm5D6UijbBzlVW4dHSJBQAljqTgZJhov/Cid9G+GKR2HhdSAIICmEp5nK2DLl3zxatZUVeU/xUfVniILBrqLzWFFi9jiKqBpfPa2eKcUeBmJpntpqTnpjohdEAe9RQmq8/gCNsqme6f+4ElEwaBcKCRSWcco5n0OVDELNdqIZC145yFLr08Rc1VwQ/zeeab3U6+bOqinqJ+xUqQnUjb65zQvDoaglX8IazlbuDOxrkH47CKJIS/4S8qcNATC4zU20zUZGN7/Duf4tTEiZ804cShOWnfxm8FLWrarhR1dejziQwkqac0STuG4PFfCb8yLUX3ULt78LQnMwBFxWbrpwOp86vppTP/sDmlvN0Mok+0oWC+bNwtYSAs0gEbiI7zbncumGWqoHzVLxvZZXeWN6ALFyfDYnbsFFbvwmgqKpmHw0KuFMpRmO+qYRYcnxABiygDWdwnvB+e/pXBN9DvRs2CmVbRhZ6R/1Rc2vymF+pUnUJhbt2zaytnj0b6ffilHtxgCeeK2D22uX8swJH+OFMy6gI1rIt5/t4F9rQqxfezaCYWGzTeYOXzWPeU3VYnGin5+FbuXEwRUoehopmCbWcSoxz7nm5zRklnTWMUNsRbe4mfWtZ4l8ZiIPVb/KpR/5FEcaJxcu4kR1AYagExTMzWBeofkb9aX3bZRoKTT7hqWkFCEhQdm6r1O49TrCE0XOzh/EJTTRMvdmEkWr0Q1oeakIS/IKQkKMbnGIAZvpmZrumcgzy+bw+8kV/GFyBf+YUcPz8+pZluvZZ1O5/7/neZ18oaKAf8+q5e/Tqiix2QkWfB5dsCHqQ0jaIA7Zwc+O/xlVXtNLaKEPxS2hGjLX2b9Kf46CiE5duIm5m0LM3RSiOtWILOhslEeJfZui0K2InG28wbLMfzglsoFiNU7UsPGQtpRHHeba4tE09goKb2yfwNfjX0E797cAtEqlzM+fxPyKUs4qL+CMgjK0xmkIBrzutHJ86Q+Yrv6F6uQ9zEz+kev069npLCAjCagSZDSBQY9MZ4GVByumc3L777h9zccRO5MIsmm5sKt2BpyZg3oEjwQ+cKTmaEXvsFJjUXCOkJrRYmqSKPCdc8wKF/euaqWhZ7Q6xs1P72QglqYu38UVi8bHV7A/hjIqXcNjPOFaAE4W1yMkVaSuJBdK5g7euuBKGG6qZnHC8f8DVcft814lJ19HTHRTJXTzua4buTryB1xCkg7PLOo+/hvc2btHRNPIdVn5x6cXcVzW23PSxHziuSZpcx8lpAagr+gEAKr0ZgC6vGbnaI8nl/YCKO6P8UpfJQBzXf/EXlhNelmaXY4p1AgmIW2O+RkMaHit+6bXk5clMLueNAvsWT3gfvepy9bJZ1FcE6Gt2Lxptq3KIRMWMAwodYQoMnZSajElaqk3yd1nnM9dH/8wYacbcSDFSeIGXEKCcMZKZzyP355zB5+cNz5eig/PKeWbZ01iQsk0QoZCd8KFLGpcE34KrCJJzYK3rZ8mRymhoiquqn6K41MygiFg6C1EVY1kd+ztT/QOMMVwYxhpWrONVS93m6qYlJ1vaVVHOS0bcpFEii69BP/FF7+nc5XaraQX5JGe6kPLs6EV2FhUnbvPa35xyQw+eVwV1yzZN8vozFrzhiTLIv+5egE/PmcKWqn52/51+R7KFIXL/vQGD61vRxRgfk0uou4n2W/e7H/jV1ltt2HXdW6It3BJwWp+WvYgX0nfj2ioSL0ptI1LiHdcjdL8MX6om+bgNmsdq//0OfxdvXz5E99FOgrMnbmOEL92xPlu/wBWXadEM8gvM6/J/vS+BvLcEjPUrIkaA2IIHR1Pz3xKNn0Jo/4xOmbfStq/l6QOf+q10jl4DtPlAA1SFwB9NtNzOH/uuRRaFS4o8HN+gZ8TctxI70IhBzg94OXF+RM5p3gCQ4XfI5z7Oa5beDvPXPQMM/NnUuwsBiAux5loNc+7vmMiT9fUsa1iAiGbn5hiI6FIPK3N5bzUD3jNlW2Ml1VdrvBdxovaDFr0fB7WlvCV9GeYr/6Ouy2n02ExVbinXU4eTZ3KjbWf5/s//ha2OvO7m6i38/uT/4xkZNdke5I2pQ9/v9kkpUZ7GMccB6laH4NWL0+lF3PGwK9YbP0Nf507lxXLclk/08fjgZnc2PA1MpoFQxSQLRpzPM0A2DQbffYMyls12zuMOEZqxgnDSk2BVRlRamJjSA3A4poAp04uQNONEUPw2uYg969uBeDHF0xDkQ7NT7Ijq9KUWBUcdcvQRAvFYpB6oY2psSaWiaavQJz5kbd9L9GZg+OzL9I/+SrispeE5GZo2c2UfOkFRIcPV9ZQGVXNz++yytx51Tzu+8QCbrpk1GPieRPD9JHAvCt/ypZlf2Vl7ZdZWfhRSi8YrW+ULlDwJlLsHArQnXBhEROcpr5Cu6OQi5u3oohp+lI+epIu5KKDhE9ys2GNN7Ldl/Pq4V0ungATFp5FylDwTErSlmND1GDL2hI602b6d53tBWqy6qDcE2fI4+exSSeBAfJAggslM4V8RyifiCPNwpLZb3qu9wP7h06iuSerTthfoDLb8VdoSYNh8MvKK4nLdqZr3RQkTHVmcuuDlNa+d1/UWMw9bxl/qW3FEAwM3YOn2TSFysOkRtOJpswbpSELFF18EYKivOn7vRXyLTK5Dgt6iRP7/Dyu+dBE5vj27VZcluPgW2dPJnc/BfbSmSV8blkN91wzn9p8Nx8tyqF2Wh6GAOuaB7nwd6+xqT2E164QWFLMilobRaeVMaPyUgTdVMMMbFxX+GlejJ9JuxGgQA3yGd8z/Fa5DacRR0gZWMIV3K3dRaE4iG4IVETWM3/oSWas+DRDP65j0wsPvqfPPq5IRRB3PcHFkTjP2qfz4Bl3EchmAu5PavwFZWYfPCAuJ8gIGzAwsIeryd/xURIZhc1ddu7d7mdnWiJaGscG7JK6iUtx0lIMUYfZi8anPo9Hlvjj5Ar+NGsJP5tzCddNOB6fzQdAsStLapQ4M6K7EX0K6PDnhqvorgiyepaFlYtcfNj2LT6TuYENvslYDFP5nZtrbqxUbR3Xur7J8elb+bJ4Pc84FnOCspe9SnKkCNf8RJLtzqU8+LUPmyq9twTyJoGhMyfTwHnFS0fGu2ZyjMGsuthn38U5255jjtSNurSATJ0HQ4S+YC4/Wvs/3JL+OjcNfZsfb/0yui6i5ViY52nh6ZYm5mbXHbtmZ8AWxXKU0IkPlKfmaEZvdpEssCgjZCa+H6kB+OZZk3hpVy8v7+7ju//Zyou7zAl86dwy5lcdui6nw6GnSS47KHaEmhOh4Vl+EX4SpzcHUdCheDaMDZ28BYRAHYFLfg36r0AQsI+5SY8oNepo+E2RRBbXBmhJmDsLuyhiEY+OiwBAVixMO+FC4MIDnnMV5iHQiS8W46Weai6r3MxM+/O8uPoGrlHNolfrg8WAgL9i//bjwIzLYM/zEMo27Ks6/j2N0eHystk+kxr3Nu4vmklerA3/QIZ1UQ8l1hj1jo3UJD7OyxYQgylQdXRZoqClk6iuc7xipp3vDOfRVXPovvulF32BjX9/Cq1CoMDayxV9DXzfVU4yaZA3mKYvx8ePij/F59r+QWVkKd2Obtrczai6iiy+/yXJ58lhr38QIiDo5aT2miXlFasCpEmrOvHhG6UkYH8f81AUBP45s4a2ZJrj/W7s72JTokgi/3P6qGFcEAQ+XlPA/5b3I7fE2N0TxaZI6HMDtDrM62uPobEn14bs+jz2yNPMKb+Mq+afwsXNb/Cblgv5hv8ZPpL4J2fKa5jrDtIfVymnG6eQyo7XYI9Uw4B/BhP6nyfAELHi99+a4n2jdC6c/L9QfxY5+eZ3khc2fR59mX1JjduiICADaVJSil7lPzgiCjmWafg6lvGi3obQPMQElrJj6l2cM7SUdjFIRsjQYzeVzGojgNOyL/l8PxAEgbPzfAc8XuIyQ6xxKYGIxul2gSeHoKW7lPWF05ke2MaDuy5gW99EDAFyihJo2WrqDVFz3sbsKaYKfyZfmEhRQsTQ4LnUJFKuVVgBDINzUm7OuvE65LHzr/Zk6NsBe5fzMRH+bRimYVwAw2GqVoZgMKgMMbtlG+d0GmwtKWb57DyiWwYQYho7VpZDSkMwdHSnTGZGDtYX/VgLCuhSzMQWi2YhKnWh6Ede8YNjpGbcMKzUFFqVkX8fjNRUBZxcuaiSO15t4q43zFoyAZflgEyl8caOqFm0YJLTjHyK9WdCw7NUFm/FqUfMHgKzP/7u3/ggNwR3VqmJHOTzh7NE52jx07wTuKsmA51U9sdZ7ypkfaiM2d42Pp++DVnIkNBc7Az5MDAoqz7I71i+EL68FZIhiPZCzoHZb+8UsYI5BBJrEB0yb9Q6WbYtTM46BfUUgYB1iLpIkPzcKnojaexdEbzWCFWrN9HvLcIqZMjoIv0pB2ULD11n+xxPAaESNy1hH9XeQaYJT1PhuYLWoJV4wxAsKOCu6vOp7mylOF5AXiKfk6JDRAa68eeVjssYhtLZ3jhGOanGjcAYUqPpRJLZG6UsvisicjBMdtmZ7Hr/WVsAFxb4+UGNB6MjjqSDMSuHPodIncPKn6ZUsikSZ+VQjJ70bJIFM/nBBNPE+s2zJ3H5n0N8b/BDPCrU80fLr8hL7CUvu9cwgJ3O+SSnf4wZp3yMWkkinUqydc2zTJ14aBS7d43jbtjnz4DFvD31p1UMwxjxtsgCCIKCkSU1z+qz8XY9QV5pHyfIJ/O57o/wWhrCGly5+XtU2u08K5tlKlq8JlGaVX54vJi59lwsooW0niYhJzi5v5sni4qgK8VvN34Cm5wgqZpzR6t1M6fveVZnq3CE0iEEBJJWjbLtA6ya/Dir8nXSXeeTkHJx5LeBAf87EOTcJd+B/edx7cmmOrxnObVaht8bUbZPOZs7+lYTF0c7eu/y7aC0O4+e9E6u2+njaxisx8aX5AR60lyvtXwr59c/irupkGtZYnr8LGZ4VxVFRL0XRdg3+eVI4RipGQdEVW1EnSmwyAdkP+2PL55SR1/U3DlNK/FyzvRi/M5DOyH2UWoA6k4HwJXJFhqbeA7MvmpczuWSh8NPB9bKHk6ZPFoyn94JpNI6+n3PkxuOY2DwSlcZpQ6dfMXsbLs1Og/VUAk7U8zNfYsQis1r/vc+YC+bidACpa4wDelcuvJVCnrjNEZzmOAZYIL1eWpyrqM3kqZyZwvfXuThm64K6gUzxBlK20CQOWvmh97mTO8P7rPOoP+Re6n2DjLBsZrzYqdxm1CBNqQyRxVZJ+v8cNFnKQ330uk+DyHexrcP6DL/3hHKmKRGopxM2+MAKDYrECOj6oSHw0/vU6kZb/gVmTNLcvjPQrNFRdylMN1t5x8zavArMpNcdi4ryj3guNnlfh66bjGfvnsd6wcn8GXvr7in4mnIxCF/MsLkc5lUOG2fYyxWG1OXnnu4Ptq7RiBb4DBjGIRUbaTgYVjVEbBiECMlpegTaxEn5PGKezm2VD4LotOY7zBYzgBlWEiRoVUyM9Bionkjnl299OAnHWeIgkixq5jmcDMxOUY4FeIUp49nSl1IXSahMWSBzDQ/s+PN6JhqrkWyIgkiCdXcjG6pKyZlHcCaEggoVeyY78PX0YwBzP3Qn6Du7ANPXr4YZDtETFVmiSPAkjP/iOXxa/n50AYkw0ATBIZsfRTQRY9QxH+UXZyfmcFsZG7R7XylBLRChev9tzGloYiZLaa/cpW1nS7FDOtacCJgYBkHlXU8cPRczR9g9GSVGZck4pSlMdlPByc1bpvCry+bxa8vm8Unjqt+26q67xeGYbAzZl4cE7NKDd4SGF7kCqbCBX88qOryXuDOfv6odiCp+SAqNY78KpS8FIpuYIhJVEPinvgSMoYF1VBo7DCJYo8/TaWn8pCOpWiiqbAsy9mBy5vD6koFEWgOmmSpwroBX8ZcwDt0L00ZJz2inyrBXMwHM3aGXEmmBCYf0nHOOvsqjCazD5pXiVE5MER1npn5tXVrH8ty3GiSTIu/mIys0GYvYHzqCUNCTRDXTMIpaaWg64guFxabuXHIaDqR1LBSI2ATjw6D4zAuL8rFcMoYLoUJDhv3TzcJzdthSrGXx65fymdPrOGGD58EF/0ZLrsXTvrW6LX+AYJNEkd8d2PTuoMZFdEwr7mEmCIgxnlRnkB3rsTPi//GkB7EKQmcKwVYIHloknoBnZDVQkrMthPIm3HA+Q4VRnw1cpx+Mcw393rwBLaQOs5HepqfzKJcLh7oZG7LLjrs5rxdWLSIr88brYw+6NoCgEedyo45s7GmGzGMDHn2PCrqzj64R0+xQeWS0b+nfRgkhcsWfYMCVUUbM+/P5nkEQycpDfD7iqfpRmeBLvMTwnzN83NOXOFnZstFANwdeJzvV92EKpq/SV0iG96V3psvbbxxjNSMA4Zr1BRYzB/17UjN4UZnKkNY1ZEFqHWM2Q2f+kOYdgl85AGwvvtKvG+G4aymiHrg5x9+zHUUmYTfDjnFdZTnmEpXbjSboaN28pOhn3F319dJRE1f1KBPpcRdckjHkl9cxSBuvEqKmWefQUwxF3e1w5x7uUovufE+JHTSyPx8jUlmZwhmqHMobaenTDjkC1Cur4jOajetAz4Aai3PcJ6SbTzbk+Sl9kEkXWfR9g1cvPYFvtm5C9mVNy7nXvfvP4FgoKtuJN2c15aa6hETfkY1RkiNIkvvqibU4cBSv4vFPheTnDb+MbOaXMs73wH7nRa+dsbEffrAfZARyBq4xxbgG8yoGIL5u/bbzdpAhelOulouJKYbvNb9MOHM0Mjr1yqmUrG1yIshGtgFK6Wu8QlzvhPkZ9OuE1KSuJBGNdJc1BKksvUmZg828+21ESq79wIQymYv1vqqubDuQqbljpJRXbCzs+4qAGYq5vU8t2DuW8/f2jE1s2ZcBoA1fxLXCWPUPgF2O2KUG6aaaxuw81PMTK3jO3I4+4XrKEmbbV/uy32Suxw7sWpWUpIZbfB5ze/XcozU/PdguJpwQbZvhvNNsp+OFIYzn2octn3NuTXLzN2cb3ybfA5//shBlJph9cZ1kJLzRyvySqrwB8wLeEqrGZOnHxpKGvE2Pkco26xTLvajiIf2whZEkXaraeyU1D6OP+cKIk4JR0hjMG1DEKA62Y6IOfeShoSVDNOzC9Zg2kbB1EmHdIzDkE9cSrTVVAZrHDtwdNRTl7sXAbDsDaOJIg1lVeTGwrS2thGPx8flvI45c7CHytCidYhxk4Raq2tG2pOoY7KfLJajbwkUBYF/z6rlhXn1FFmPDp/CkUJeltCNJTXBjIYh+gAYsmaNv3IQKVWA0fRxuhLwabWDEwhzoWOAJCEMICSZ3a3LvZWHlcjm2MwEkIjVvCb7xQinxCdy7u4czli9llPiAiHRnPsJ2dyElLlNr9QZVWbJhZPLT+aW0//DWUV1zPc68aqmR2hOwZy3Pnn9WaA4oHQeFM0cefi8aVdRlxpta/CU04Hf6CGFDbuq4bRt437M+4ZFcGCg88+c57g773GSnZdg1a/EEMycc7tsbuoth3jte6c4+q7oDyDGVhOGo0+p2RndL/R0iOGW903pHothouc8RKnrhwKKxUrI7aOzWsOTyiDqKQxd4BzrU7jTQVRJImlRya2sPCzjifnN0JHRtZlTzr+KliIFe1qlM242+qvMdJAZY5crLEqTLwwBMJi2s3TGqYdlnFM/dAVii0FSk3DJKfzhXs4tWoGAjtCZ4NyIStDhptE5maFCEITouJx3ds1SCsJXk+y6BCFLaizVVShZUpPRdOIpk1xbD1Kk8mjB0aYgHQmMmoVHC/AFMyppi6nqpcU4QYcbGZ16uYuIVsPfai6mzV6GJkBBgfn797u8FPWa2TqVvsrD+hmGSU04S2q6xEFqUiVUe0PMLp5Gv2SqTVE5ip79yUvdpfv8vzvWzVkFRdwxtYqHZ1azO7gVgJn5M9/65P4K+MJG+PjD+4So5KkXcW9vEGfW97nCYacPJ8+mqtENqCTD42I3X1KCXEGEf/q+wD2BJ5jZN59yXaUyYTYEtevSSD2dQ72he6f44NxZjmKMrSYMo6Qmoevow53sjiBGTMKHi9SMZD8dRKnJemo+SOEngKBSiDTNXCDru8xFaHCrjw6XSSR2lUWp8r73rKZ3A7nE9AN4QzsRBIHeWh+OdIaOhDmWKhrM531WyqcF2Du1GpdkysmhtIcZRYcn26WqbBrNFXa6gua4qi3L8fdWc1bVcwC89HobZWv38Gq/kzca5jOojl8IlFzzpicb5qJtranBkr0uNc0gnDCvWZv16CU1xzBqFt4//BRzmGFewVDZUmxed7PlLqqlPvLENG5LivTMHCYE2wHYXFKDO9IEQIXn0BQ4fTMMk5q4Yn6GBtkMVy+KfZlyamkRTcNtt320zcBweGyY1LRH20eeaww1EsvEsMt2an3vIB3fXQDWfatZY/djn/sJarL3rqQosjpfZ8BwslUzC4NOl7tYr0MjBg0OnQW9C6iJlXGipQln0lSu3RKoKZMsWaSjQ1X8YN1ZjlKMrSYMjGQ/gUlsjjR2ZE3Ck8Yp7fTt4DpInZphRLNKzQcp/AQQcxQz3RlnTZ1AyWDUzEwJ2xhwO8AwaCiLUumtPCxjyaudC0B5ei+aqiJOrkfWDbqj5sJVKjWgGCrOMid7ii1UxTsRBYOMLhJTreTZx8e78k6QOW42keEQlHMHkb2L+VDls9T59pLGQs+QC12AlBRD1jNv827vHJrF9I5JRlaRqa4eCT8lUyrBiLkou9zjl3F1DOOPvOyaOpA1Csc1nYRuoCvZlhoCOON7aHG2ICKwwNZOaoGX/hOrWDK0E3cqgSaIdHpyyYhDwJEjNYZihntSpOiRBpEQ0THYI5mkpt3ZjoCBJEgUOk1iMUxuQqkQ4bS5mdrcZ9abmhaY9v6qQS/7FpXC6Pxf72nj0ouruaB9F5qgkivGKTRiyF5Ip2eSn8zHwEAAUqJ5XfkUDbJ9Ni3iMVLzX4Ox1YSBfepeHOkQlG4YNMTMBfywhZ+GKwof5LN/EMNPAJq7jBxdZ+UCDYumUxgaLemvKymiDu2QZz4No7RuBgnDgkNI0dG4FWud2QYgFZZJajKKmGYurbRoOjoCZ4bMfk+DaTuGqB/Wsvg1H7ocqUkgrYl4lQQ5+naibd/i8uonmB7YygxV5eODUWb5nsdvGb9FUdVMhVQ2dASLBaW0FGuW1IRD5vVgyAIu+9GRhnoMB0dgP0/NYJbciHL+6IuS61ift54BawSrpnLhhhVcueoZpnS1YBjwWs1UZu7eTk+B+V6Hm9T4baZpWzBiDNpNNfLbJffz0dpv8G33y2hChrSYHulJVeAoGClC6VAc5NpMU297JKs69ZukZnredN4XrC6qJpxjnkfXSZPk9d5/cnKxgwGHaVyeJnUxId1DWdQsVfG6LUKju5GkZKr/trSdYZeBIh8dG4QP1p3lKMXYasJgGv3s2XS5I01qhlSNdDYEVmQ9PDHP0eyntzAKf4BSugFEv1kpuNib4s+nixQPjvbuai4IIwkSE/zvrvP2e4Uky7QplQD0NazFr3jpyhFwpFU6E6Zas0jYjaGYl/eJkY0ADKVtpOXUYRnjMKZPPIHmAgvdg8MhqOeJ7vLw4TP/xXVVlZwaMvAN3U35th6SqfExCoNpBgaw5Qco+Na3EGR5JPykZwmP4ZRxfMAUw/9vyBtTgA9MPw2Az+Yf8XI0e/egCzpBSzdS9ve0pcybbpfLz/aSauY1b2PAlm04epg2H8MYVmpUNURTwFSYApnJBJUQGWczYIaeMooZUgs4AvscPxKCypKaTb1mS5vpgfdJaoDKqpPNMWY9eIN9j/CXOVF67LvQMSiSIszPJhk0uPcw6HuVDbkb6M2OWx7IJyMNh5+OkZr/GlxenMsVxblU2kd3msOL5XiRmvWhGF/Y0cJtLT2sHopivEOvzvBi4JOlw9aWwP0W2U+x4ZTuD5hS48g3mxHOTaZ4brbIkx/OxZNI4kilWDMhwZTAFFyWcfSEvA0GvWYGU7p9AzlRnYYicKQzI2bhOeJuUAQcRpSykOmnGUzbSdrHL8TzTiCJEqFF9cRazAWvxrmdaNhCvN9ASk5ES5s90FSbC7fvwKJy7xWZLHFxVJTjv/QSAGzKvnPOcMjYpWNm3KMZI56ajDlvgxlzTcm1WJCy65lACpvsZJ5jHtqYNcdjsfDYLLPI3pzzFgPgtXoPbDh7iDESfjI0Wvzm9VkcEdEFJyVRU8XpcQyQcppVjvcPD4/11YTTYfaGTBXlfSs1jBK8QasdwTYFwcjwYPQFdrsztLrMtHENg3WBdWzyb8WfSYMAEcXc1PlDIlr2slKOElJzTHsdB3yuPP+AxxySyEBm/EjNjbvb2ZzNYgL42YRSrigJvMURJoZJTeBd1Lp4v3C9RfbTsFLzQQs/1c45mW2vzEDwTELgDZ4u6OLa3/yNe7f+ncRANwsKD0/Z9WEIRTNh4D+4g1uJ+crYWyhT0a2OmIUny7s4TXqCJazCnjRvCINpOxnv4c9QKD7rfIRHNqHOEsixJPAZL/PY7XZS6Qxa2syiEPMnkUlpKONk3NWy151lDGmx7DfndId8VFUTPoYDMeyp2T/85FdkYpJ1pOJuUcF5XHvutaxYsQKLxUJubi5vuAIYHUGm6hn0Gi+0Hf7QE5gGWpfiIpqJMuCQUUURu5phUuRUXKqEhkak6EIEwzT4B+z7KTWuUaVma//Wkcdy7e9/E1DuKUcURGKZGBfP+hp37lmBkmrAFlvBptxNePQY2/MH6RF6EABFswEaajaTqrAjRDzbGUaRD4+94e1w7Io+RBjPtO4d0QSbowlkAeZ7zSZszw2E39Gxw5U4A++gIul4YbihZVTTDlCUPqhGYZvDxZRvruD0T/+R+UVmVd8XQ6t5PWGmiQ4/driQU2eSqPJUA/pQB205Xuxple6EG80Q8IuDnGC8QYXWjNMYAszCe0LB4d2lAsyfdz7tXoWBAXPuVlmXk4xq6IleDH0QUddZ8vKrZNLvbE6/E6i6Oe/Gdr237Ze+bTjl99336RgOLYbDTzFNJ67pI4bhHEXCLpuJDzoKe5QTsTtdnH322Zx66qnMnDWLu4NmiYCrJlXTGjZDKIc79DSMYbVGIUqb39wET+0z56NBmt2+6UjaEHAQUjMm/DRsEh4PlQZMwlXsNCsen+bLcGHdhURyP0lAt6CKKi8W7KRH6CEnuxk1BPMaHtbDSnvjqFmrheUYqfnvxtv1f3o3+FePGT44JdfDD+vMuOuqUBTtHYSghus7vJuqpO8Xw0Zh1YCkvj+pGS6+98GdeufWmP1y7t1xL73xXhRRYWbezMM6hvKJc0gZCh5i+PvW0OMuwJHOoBoSvUnTV+NvVWjYfhw2zLYJg2k7nprDv1N1KA4655WRajR33ROc7ezJfYiovhqAwlAMBxEc7vGrgjuq1IzOM6t8kPDTMaXmqIZLErFmb5r96cyIpyZHkUeIAvZJBHU7K0OjdY5eCkZoTqTxyCIXFPhoDjcDR0apgVFSU6wk2FFUCYA9HidnaIj6mUtBEHBhkvoDwk9ZpaY53MyLbS8C40dqgJG08L1De7ilvozz831U656R592ig8VxUxFLK+bjw6t6SW+CdHavYJEPT3bt2+HYFX2IMF5KjWYYPNRtkpqLC3OY4rTjkkTCqj7SefutcCSUGockMiz679//afj7cH7AjMJjcUr5KdhlO6GUmcs4M38mtsO8S7FYbbQops9norqDqLUUwTB/68646e2ZZfVydv0cBEEnnLGSzFiomjjzsI5zGIGLLyXWbkXXIc8WZ1LnDoSkKbeXR4aInTJrXM+nZT01ljE+Grt8TKn5oEEQBPKzIajuVIbBrKcmR5FZXGz6ZMqySsbPm7pJZzeRf+0wifylhTk4JYmWsOkPKfeUH9bxD2M4A6pAStCaWwjeAq6prORzP/oRDVPMulEOI0tqHAf31HTFutg+sB27bOeE0hPGbWx1/joA9gztQRIEfj2pnFzZXEPsuswN/QsYDlrHh0Ne2fBTIKyRGfbUHCM1/90YL1Lz6mCU7nQGnyxxSq4HWRSYlw1BrRyTVvxmOBKeGlEQRlsl7OeriX5AjcJj4VAcnFoxWpV3fuHhDT0NY9A3deTfVjWXXr+BNTPqqylKNVMRMzMlGiK5yLpAjX/iERnrsgWXsqnSSrTPJH9THAMomohHTzJvSRuLJoRAHb/MLC2rEFr2CT+N+bddBlk8ptR8AFCWbUTalkyPUWokJuealbXdWgcuSWRlKMZXd7Xxt45+ns+G56/K+g6HSc2RDj95BHPN7jrtTPI++1kkl4sV2UxK403CT/mO/JEaMFbJyu0n3T5CdMYDw6SmYdDcZFhFkTlecwwFhoPX7VNJZknMoKto5DiPLiHrjIafFMe4jen94NgVfYjgHCdS889us3bBefk+rNkFeLHPZNFvDL19WflRUnN4DaIjad1jlJq0ro+kl3+QSQ2MhqAAFhQdXpPwMISSUXXDrvnozhHMdgkJ0zejDO2CnU8A0BAOIBoZ8p0HmtoPB+yyndh5JxBtNknNnLxO3DJcENiGxaXh6dsImbdXHt8pDhZ+GqvUONzmTeKYUnP0ozxLalrHkBq/IlPvrwegLbyHP0wuRwQe7B7kxt3tGMBZAS81DhuhVIih1JD5Xu4jo9QMkxo75pq9I2qmnPemMmbFd0MnljYV+f3DT6IgMq9wHnbZzq+X/Xrc/Xt1vlGlZtgDGbCZIWyVDK+WlpLKkpqkdTREXCDbERSFTJbUyMoxpea/GuOl1AwTlw/l+0YeWziG1LxdaveRCD/BKGkZW6tmbDE+5wfMKLw/5hXOY2HRQmblz2JqYOrbH3AIkDdhlEzZDJkOv4g9nSGmWghlfGaPpUyEmOagM+HBEBIH7AIPJ0648AvsCjmJdVuwCxmuqXyNQEEcDREu/jvYfeN2Lj2r1FjHKjVjPDW2Y6TmA4PybKmMlkR6n/BThbcCRVSIZWJMtEb5yYRSBEwS9KO6Em6fbPpnhlWafEc+jiOkJgyTGlEzFaTGRJKUrvNqdn2fbE+jGzoCwkioaixuP/l2ll+8nCUlS8Z9bBXeCmRRJpaJ0RnrBMBtMTdGGSONLGgjpMYQbGT7WFKiOKl84D7SWa+BRXGO+9jeC45d0YcIw6QmdpBaLe8UfekMHakMAjDTPXoxznDbsYsCwYzG7vhbS/ZHIvwEB29qOdz3ySYKyOIHuz6IKIj8+bQ/c9eZdx2xRm5lE2aRMLK1kQTo8DpwZH/vzmTByOsaoxUYCGQU9bB7f8aiNqeOTcvK6XjDTyYuIivm3NhccRYUzxzXcx3MU+McQ+xlV7b69wd8Hv5/wMGVGglFVKjxmZVudw/u5qqSAJuXTOGNhZP4RGneyBo8TGqOlEkYRklNIj2ERxZRDdgbT7EiaIaeZtjTI68briY8FrIo47a4D3h8PKCICtXZvnXDISi3dZjUqNj01Ej4CcECWcdkEQq22koywnD46Rip+a/GeGQ/bY6YcnyNw7pPBV6LKDLHk/XVvE0Iqj9btCrvcJOagzS1HG2R8MFWaY4WyIqFFouZuSAKAh1uH/Zstltnwjfyut1Rs49M0nrkm6vO/PTX+c0pFl7am0s6KrEx6CQu14z7eYyDKDUWSRjJ2pBc5vVwTKk5+jFKalIjpCY3S1CHq3jvHtwNmHVtpP26mx/pzCcYNQoPpgaZ6DTDNDuiCV7J+mlqLGY17f1NwocL+/tq3DYfADEJyga6SGXJf1HPwMgxeciQSYyQGuUYqfnvxniEnzZHzIk+w32gZDrfZ06gjZE3Ly2f0nXCWaXksIefDtLUcrRGzbFpN14Y8k0BQBAlOhwlI0pNc8yOYQgkdA9tUXMRTbiO/Pd+YvkyrvvGP1j7tWs5Z1ItmypFbL1bxv08w+GnseZgiyjCcDE+x7BSc+S/k2N4a5TbzUq1HckMiezvmvMmpOZgONI1amBUqQkmgyM9+G5q6qIjlcEiCAQk00B8pMLDw76aUVJjjjclCpy65oURpWbxq+sxsluDPANQE6Php2O9n/67MT6kxlRqprsPNGANZwR0p9687P1A9gYnC+A9zCnUw0pNbMznj430fTo27cYLvgUfoZccZE8+Ib0aMMORQ0mNxwa/zn8G/hdNNxfMVM7RsehMCUzhGwu+wS9qb+TKcISC6I5xP8eop2Z03suCgDrBg63Wgzas1BwjNUc98i0yVnFUZZOF0Y3RsMLwVqRmJJ37CJmEgZHqv4PJQY73m5vU9myl7/leJ+GUqYAcMVIzrNQMmaTGZc8ZeW5646YRT01MtAxHn8jRDMgkR8NP0tHRpftYm4RDhPHo/bQpq8JMP4hSU5jNZup5C1IzahJWEITD6x1wH0ypGUnnPhZ+Gi9MnHsyzG2i8OltaC0R+nw6tnSGpEWhOVaMILoAHUE3EIp9R3q4+6BsymJ4EUqNLkLBPrw54yO9a7oxUh3MLo9VagS0chcWizxybXiVY3PxaIcoCJTZLOzJ+gdzFHlkPRtWalrDrcQz8QOMwIZhjIafvEcu/DTcb8rAYLFHYOXCSWyKxGlNpDknz8d9m/uAAzOfDheGlZrmUDMZLYNicePSdaKiSNxmjJCaAc+of1DU01mlJht+OkLewv1xbJtyiPB+U7r70hk6sybhaa4DlZrCbMft7vRbkJojZBKGUeISGfP5P6h9nz4IsCkSqD66cgS82cXf0HrQ1Q4AfIkknvKyIznEA+ALFNIhmIbm1q2vjtv7ZsbMubFVhGVhuDKtSjCjIQkwwXF0lHY/hrfGsDINo6EnMJWNXFsuBgZ7h/YecFxfoo+EmkAURMpcR27+K6IyQmyCiSCVdivn5fv5fEUBVQ4r/QmzWOCRUmoKnYW4FTeqodIYagSLA3fWDxq3M1qnZoxtJqWmTaUmK90o0jFS81+N0eyn90ZqhkNPtfuZhIdRkCU1wYxG6k3MyEcqnRvG1Kk5iKfmmFF4/HFyWQ4g0JUj402YpCZkdJHSzIXeG09SWDL5CI7w4Oh2mWOKNa4Zt/dMjcm4s4012GcX5uFnJzhs2I4R7A8EyseQGv9+6tpb+WqGQ08lrpIjftMd9tUMpgYPeK4vkVVqjpBRWBCEkRDUsy3PguLAk12vY1ZhRKmJOtWRY5J6ah+lZrhA4JHGsSv6EOH9Zj+9VegJwC9LI4t0b1o96GuOrFIz2tRyGLHh8NMxT82444wJ+bz41RNJFHlGSE1a60VPtwOQkZNU5dQdySEeFJmCmQBYezeO33u+iVKj7Je+PfUgXrVjODpRYR/1g+Xst0kbJjXbB7YfcNyRbo8wFv5s4bqB5MABzw0rNUcq/ARwSf0lANyx5Q5WD+0eUWpiToFU9n6WcCRHXp/SM1lPjfn3kSaNwzh2dzlEeL9G4c0jpObgC68gCCNqzZv5avqOQDPLYYwqNQeGn45lPx0aVAWcZKqL8WTDT/5MCMVIgWHQ509S5j66wk8AnhqzgGBJfPzMwsOkxhDANsYIrOznKztYWPcYjk6Uv0n4CWB2gdk7aWXXygOOO9LtEcZi2CwcTAT3edwwjBFSM/yaI4Gzq8/m/Nrz0Q2dr6/+MdYsqYnmjSpjqi088u+kZio1mWNKzf8PvF9Ss2Uk8+nNK2AWZMnKm2VAHcnw00hF4YPUqTlmFD50yKmeRMpimoWH4Umkac0/ctL2W6F8ykLWek6hccK1aOrBFcd3i4yadQnvV+Rxf6VmyjFS84HBcFVhOJDUzC+cjyRItEZaaYu07fPc0VB4bxhj07rHIpKJkNLMjciRVGoAvrngm9T6aulPDtAnm99zyDN6DxMto2NPp2No6TjaUZb9dIzUHCK8H1ITUzU6skSl3vnmRsaCtzELH8nw00ErCh8zCh9yTM6dwp4iYSQEBZATS9BZIOOxeI7gyA4Ol8fP3BseYuHl30aSx2eepoeJtLCvOrO/UjP1GKn5wGBfpWbfTZHL4mJG3gwA3uh8Y5/njiZSM0xYeuI9+zzeHzdVGrfiPqIVv8Hs0fbRSR8FYCi7+RzIVv4WdRDE9EhmYdLIkI71jhx7LPvpvxzDpCah6+hv059pf+zN3pByFfmAXclYvF1a93CdmiNqFD6YUnOYa+b8f0KJu4Q9xaMZUAA5sSSZ6pLDntZ/pJAeq9S8Cakpt1nwHoHr4hjeG3yKjCfrj/If5HdbVLwI2JfUaLpGa8QsvHc0kJpCp1nZuzvWvc/jwybhgOPI9WUbi3mF8wAYyN7DdmQ3z5Jh/i1gbgZSgkBmsHnkuGOemv9yOMaoEYl3aRYersdQ53jrYmlvl9Y9En46zB26YYxR+CB1ao4pNYcOdf469hSbIadh6EKCipIpR3BUhxcjRmFR2CfkNPbf046ZhD9wqMum3xdbD1zPFhcvBmBV1ypUPdv/LNaJqqtYRAuFjsLDN9A3wZuRmo6oWXah2Fl82Md0MJS7y8m354+ElfZYTJVsWEmt8GbbrggC6dBouE8Wjo5NwrG7yyHC2Eql7zYE1RAzHeZ1bxF6gtHwU2/qQC+CYRhHRfgpoRuo2equx4zChx75jnx6KjzkxBI4k2kKh6J0BYwRM+X/B4wYhUX2UWokQRhZ8I6Fnj54uKW+jJsnlLLY5zrguSm5U/BYPEQyEbb2bwXghdYXAKjPqUcSj7w6XOQsAszwkzFGvR/2AZW6S4/IuPaHIAjMLZwLgDxmnGnM+8mknIlAVqkJm2O3IB41SvCxu8shgigII8TmXZOauElqat9OqbG8uVIT0XTS2QmZewSNwjBKZqLHjMKHBRWlU+n3GJywq43ZLT0058PE7EL0/wHpYR+XIIyUPRjGsFpzjNR88DDZZeeqkgDiQW6ekiixsGghAK91voZu6Dyw8wEALqq76LCO881Q4DQLTSbUBKFUaOTx9ohZduFoyk4cDkE5xkQZdEPHY/GM1LMxSU0nABbh6KESR89I/gvxXs3Cw+Gn2repdvpWKd3D3WztorhPKOxwwSKK2LI3kOGqwsOhKOexOjWHFHML59JQPLrwt+QL1Ppqj+CIDi9mlfsxjisgMyt3n+wnML00dlFktufo6Ch8DOOH40uPB+Du7XfzwM4HaI+247a4Oav6rCM8MhNWyTqSAdUdHw1BDZOao0WpgVFSE9uvN9qpFaeOtKJICQLpbNaWIhw9G9Vjd5dDiPdCalTdoHGE1LydUmMqMEOqRmK/cwyTmv0zBQ4nhhWZYTITP6bUHBZMDUxlzxhSEyzx4La4j+CIDi/sFomMQ8ZwygdkPD08q46X5tcfkdpNx3BocXb12czOn00sE+Om1TcBcH7t+djlo0eVK3CYas1YX01bNBt+ch09pKbcXU4+8oivZhhnVZ2FVTLvSylBGOnQfYzU/D/Be+n/1JZMkzYMbKKwT7+Tg8EjS9jF4arC+6o1gxmTSBwsU+BwYf+mlqPhp2PT7lBicu7kEaUmqYCr+v+PSgOgG8ZIKwR5v0U5YJH3qU57DP89kP+vvfuPirrK/wf+fA/DDCC/RIYB5Ef8UDJF8sdmaIKoBdaWWsdM+exqx9xsy21L3XKtqNzK3fX4x3bK3DoHOh11T+1XrdORShNSi1jlAEYpiaKYQviLX/Ib7veP4f1m3vwWmZk3w/NxDucw7/ed99y315l5ce/r3qvT4+8Jf1ctXfBYzGMOrFF3cl5N+Y1yAEBNc40yFKWl4SdJkjDdRb0EhKvOFdPM05SgplEnWS28p50/EvjtYkNKT81NzH6S82miPIw9jh1bkyQJAXJeTVPXoMbSU9N1nxR7st7Usqm9HS0dOT6c/WRbo91G43rkGOxO0GH7/TrEBsQ5ukp21WKV3OiqjdxFspPAUYHYPGszXCQX3Bt+rya2R7DWdQaUPPQ0xm1Mtx3GHe1R91AEt7RC6ng/hXmFwUXnoqylY+mp6djMUiMznwAGNTblMYhE4dMDzKeR9TatWws9NZ5WPTXWi/BxQ0vbm2Keir2zdMi5Q4eJ/iNnOjcAZbYdgG45NeT85obNxcElB/H32X93dFW66S2o0VI+jWyaRwi+/OUS1kuWPatiTbEA0NlTI+mUHbq11FOjnZo4ocHs1F0ywJlPst6Sha93LDk/2oEL3XnJOTVt7coMKPcuS9eTbUw2TcbBsoMAgHG+2tvI0pase2q0NCuD7MffXRsL2XXVNaiRp3NraehJMcqyD9WjATOhC4/F3LC5AAA3F8sf3M0SlM0sDRpZeA9gUGNTnYnCbf2U7FRyQ154b4A9Ncrwk3qtGi301HRuatmmBHbspbGPSf6TAFjyDMJ9HL+aqj1ZBzV6xs+kIXJOjdJTU6fdnhpMXwW4esAtdgn+zzNAOSwnXtfrdJ3DTxrZzBJgUGNTg5n9NNiemu6JwlrIqelYVbitzWqLBP7lbA9TAqbgoaiHEOUbpZk9WeylpWP4SS9BMwuCEQGdPTWV9ZVoa2/Tdk+Nhx8Q/3S3w95GSwJxjc5FSRTWyhYJAIMamxqlfKkPLKipb2vH9Y6ZQmEDnKHR207dWuqpqWttV6Z1czq3feh1erxxzxuOroZDyD01XadzEzmav7s/dJIOraIVVxuvdubUaGg6d3/k2WU3dBIalNlP2plRyD+bbai3mUm9udzR2+Kmk+A1wBlCZoPcU9Nl+ElDOTW1bW1KYMeZT2RrrULuqWFQQ9qi1+mV3bov1F5QhqE02VPTC+s1r652fMa76rUz/MRvGBuSN167NOCgxhKImAyuA+42Nxn1Hc/VXk9N5+ynzkRhBjVka0pPDRPSSYPkvJr8yny0iTa4ubhpNrG5J3qdHqNcLStyX+kIagwuA8sBtQd+w9hQcMfieZeamvspaSHnxQTcxGqncm/Q9dY2NFmth6OFnBpl+EmVU8PhJ7Kt1nb21JB2yXk1X577EoAlSXi4a7WtnAAAGixJREFU5X7JQ1BXO/5INegZ1IwIck9NeVOLalfW3shDSHKgMhC+ehcld0Delbu5vV0Z7nFoTo1L5zo1vzRaArvAm7g3osFoZk4NaZgc1Jy6dgqAZRfx4UYOaq50/JHq6sKcmpty7tw5rFq1ChEREXB3d0dUVBTS0tLQ3DywHhBHCTK6QgLQ1C5wpaW13/JyT43pJnpqdJKklJeDoqqOoScJgI8jc2r0nSsKn2uwTFW/zV07Y6/knOSeGg4/kRbNDJ4JAAj3Dsfz057HSzNecnCNbp48A0rJqXHVzv5aw2L206lTp9De3o4dO3YgOjoaRUVFWL16NW7cuIGtW7c6unq9Muh0MBn0qGxuxaWmFpj66aW4PIieGrn8paYWJa9GnkHlq3eBiwP/Wh1ltaFlaYMlAI3gvjtkY5z9RFoWHxyP4/93HAadYdgNO8mUnho5qNFQTs2wCGpSUlKQkpKiPI6MjERxcTG2b9+u6aAGAIKNBktQ09iMOK++9/YYTE6Ndflf5aCmo1fI14H5NEDnhpbVrW242lGniAGuv0M0WGHuRmyKDHJoLyVRX4waGq4ZDB+jDwDghk57OTXDIqjpSXV1Nfz8/Pos09TUhKamJuVxTU2NravVzVg3VxTUDmwGVGXT4HtqrJ/fmSTs2Oa13iYBsCyGFmLk8BPZVqibAWvDzY6uBpHTst4JHQAMLtr5XB8WOTVdlZSU4O2338aTTz7ZZ7m33noLPj4+yk9oqP3XAgi6iWndg+2p6cypkXtqOqZz6x0b1HRdPTjUzcB9n4iIhrmuQY2WVi13aFDz4osvQpKkPn9OnTqles7FixeRkpKCJUuWYPXq1X1ef+PGjaiurlZ+Lly4YMvb6VFwR8/Epca+k5qFEJ3r1Bhvsqemo7z8fDmnxpHTuQHLLuXW/8FuYz4NEdGwp+WeGof+Kb9u3TqsXLmyzzKRkZHK75cuXUJSUhJmzpyJf//73/1e32g0wmh07BfpQBfgq25tU6aimm5y2MjcrafG8WvUAJZ9d7z0LqjuCLKYJExENPzJs59kWuqpcWhQYzKZYDKZBlT24sWLSEpKwrRp05Ceng6dbniMnI3tWIDvYj8L8MnTsX30LnC7yVV3A7pslaCVnBrAsqklgxoiIufRbfiJG1renIsXL2LOnDkIDw/H1q1bcfnyZeVcYGCgA2vWP7mnpqKpBW1C9DrFerD5NEBnTs3lZssif1rYIkHmpXcBOnqpuEYNEdHw1234Saedz3bHf+sNwIEDB1BSUoKSkhKEhKh3Mx3ISr2OZDa4QgegVVhyXgJ7yZex3vfpZsnPaWgXqG1rx7UWx29mKfOy2pU7ktO5iYiGva7DT1rKqRkWYzgrV66EEKLHH63T6yQlkOkrWfhWemo8XHTKlgSVzS2o6hju8dNAT408A0oHy+wnIiIa3jj7aYSTh6Au9pEsPJh9n6yZjZ1r1Whl8T2gc6uEEDcDDMMkD4qIiHrnZfBSPWZPzQgzkN26B7PvkzXrtWq0lFPj2dGDxCRhIiLnoNfp4enqqTxmT80Io0zrbuy9p+byIFcTlsnPO9fQpEwN99NATo13Rx2YJExE5Dysh6AY1Iww4zws+2IcuFqD9l7ygG4lp8b6eT/XW7aFMEgSPG5yargtLA30Q4q/N1aM9Xd0VYiIaIhYJwtz+GmEWRjgC2+9DmcbmvDVlZ73n1Jyam5yNWGZ3FOTebmq4zp6TewAO8HTHRmxkbjDUztb0xMR0a1hT80I5ql3wYpgS0/F9guV3c63tgtlF+vB99R0TuvWS8BLkcGDrC0REVHfrIMa9tSMQKtCTHCVJORW30Be9Q3VucrmFghYdrEe7DTs6I41YHz1LvhPXBQWmUffapWJiIh6pBp+0tDiewxq7CTQ6IqHOwKN9ItXVOcudKxfM9Zo6HXF4f5M9fbAx3FRyLorBveM9ur/CURERIOkGn7S0DYJDGrsaLHZFwBQUFuvOl7WEdTcyuJ0kiQhwc8LQUbtRMxEROScmFNDiBllmQVV2tCE5vZ25bjcUxPKac9ERDQM+Bh9lN+ZUzNCBRpc4emiQ5sAzjY0KccvDEFPDRERkb2wp4YgSRLGd/TWnL5hFdQ0MKghIqLhg7OfCEDnQnyn6xuVY+ypISKi4USe/aSX9NBJ2gkltFOTEWJcx9Trn29Ygpo2IXCxY0+oMAY1REQ0DIxxGwMA8HD1cHBN1By/4+EIoww/dfTUlDe1oFUArpKk7LRNRESkZUGeQVg/fT3MHmZHV0WFQY2dyUFNSX0T2oToXKPGzXXQa9QQERHZ24qJKxxdhW44/GRnoW4GuOkkNLVbAhrm0xAREQ0NBjV25iJJiLLKq+HMJyIioqHBoMYB5BlQP99oHJLVhImIiIg5NQ4h59X8XN+IXxpbADCoISIiulUMahxA7qk5er0OLUIAYFBDRER0qxjUOECinxfGGl1xsalFORbGfZ+IiIhuCXNqHMBb74I9U6IxtmNdGldJgtnANWqIiIhuBYMaBwl3N+L/TYnGZE93LAvyg45r1BAREd0SDj850G3uRnz1mxhHV4OIiMgpsKeGiIiInAKDGiIiInIKDGqIiIjIKTCoISIiIqfAoIaIiIicAoMaIiIicgoMaoiIiMgpMKghIiIip8CghoiIiJwCgxoiIiJyCgxqiIiIyCkwqCEiIiKnwKCGiIiInAKDGiIiInIKekdXwJ6EEACAmpoaB9eEiIiIBkr+3pa/x3szooKa2tpaAEBoaKiDa0JEREQ3q7a2Fj4+Pr2el0R/YY8TaW9vx6VLl+Dl5QVJkhxdnSFTU1OD0NBQXLhwAd7e3o6uDvWAbaRtbB/tYxtpny3bSAiB2tpaBAcHQ6frPXNmRPXU6HQ6hISEOLoaNuPt7c03u8axjbSN7aN9bCPts1Ub9dVDI2OiMBERETkFBjVERETkFBjUOAGj0Yi0tDQYjUZHV4V6wTbSNraP9rGNtE8LbTSiEoWJiIjIebGnhoiIiJwCgxoiIiJyCgxqiIiIyCkwqCEiIiKnwKBGo1599VVIkqT6uf3225XzjY2NePrppzFmzBh4enrikUcewa+//qq6RllZGR544AF4eHggICAAGzZsQGtrq71vxWkcPnwYDz74IIKDgyFJEvbt26c6L4TAK6+8gqCgILi7u2P+/Pk4ffq0qsy1a9eQmpoKb29v+Pr6YtWqVairq1OVOXHiBGbPng03NzeEhobiH//4h61vzSn01z4rV67s9p5KSUlRlWH72NZbb72F3/zmN/Dy8kJAQAAWLVqE4uJiVZmh+mzLzs7G1KlTYTQaER0djYyMDFvfnlMYSBvNmTOn23tpzZo1qjIOayNBmpSWliYmTpwoysvLlZ/Lly8r59esWSNCQ0PF119/LY4fPy7uvvtuMXPmTOV8a2urmDRpkpg/f77Iz88X+/fvF/7+/mLjxo2OuB2nsH//frFp0yaxZ88eAUDs3btXdX7Lli3Cx8dH7Nu3TxQWFoqHHnpIREREiIaGBqVMSkqKiIuLE99//704cuSIiI6OFsuWLVPOV1dXC7PZLFJTU0VRUZHYvXu3cHd3Fzt27LDXbQ5b/bXPihUrREpKiuo9de3aNVUZto9tJScni/T0dFFUVCQKCgrE/fffL8LCwkRdXZ1SZig+286ePSs8PDzE888/L3766Sfx9ttvCxcXF/HFF1/Y9X6Ho4G0UWJioli9erXqvVRdXa2cd2QbMajRqLS0NBEXF9fjuaqqKuHq6io++eQT5djJkycFAJGTkyOEsHzA63Q6UVFRoZTZvn278Pb2Fk1NTTat+0jQ9Uuzvb1dBAYGin/+85/KsaqqKmE0GsXu3buFEEL89NNPAoA4duyYUiYzM1NIkiQuXrwohBDi3XffFaNHj1a10QsvvCBiYmJsfEfOpbegZuHChb0+h+1jf5WVlQKA+Oabb4QQQ/fZ9pe//EVMnDhR9VpLly4VycnJtr4lp9O1jYSwBDXPPvtsr89xZBtx+EnDTp8+jeDgYERGRiI1NRVlZWUAgLy8PLS0tGD+/PlK2dtvvx1hYWHIyckBAOTk5CA2NhZms1kpk5ycjJqaGvz444/2vZERoLS0FBUVFao28fHxwYwZM1Rt4uvri+nTpytl5s+fD51Oh9zcXKVMQkICDAaDUiY5ORnFxcW4fv26ne7GeWVnZyMgIAAxMTF46qmncPXqVeUc28f+qqurAQB+fn4Ahu6zLScnR3UNuYx8DRq4rm0k27lzJ/z9/TFp0iRs3LgR9fX1yjlHttGI2tByOJkxYwYyMjIQExOD8vJyvPbaa5g9ezaKiopQUVEBg8EAX19f1XPMZjMqKioAABUVFar/UPJ5+RwNLfnftKd/c+s2CQgIUJ3X6/Xw8/NTlYmIiOh2Dfnc6NGjbVL/kSAlJQUPP/wwIiIicObMGfz1r3/FggULkJOTAxcXF7aPnbW3t+PPf/4zZs2ahUmTJgHAkH229VampqYGDQ0NcHd3t8UtOZ2e2ggAli9fjvDwcAQHB+PEiRN44YUXUFxcjD179gBwbBsxqNGoBQsWKL9PnjwZM2bMQHh4OD7++GO+IYkG4bHHHlN+j42NxeTJkxEVFYXs7GzMmzfPgTUbmZ5++mkUFRXh6NGjjq4K9aK3NvrDH/6g/B4bG4ugoCDMmzcPZ86cQVRUlL2rqcLhp2HC19cX48ePR0lJCQIDA9Hc3IyqqipVmV9//RWBgYEAgMDAwG4zBuTHchkaOvK/aU//5tZtUllZqTrf2tqKa9eusd0cIDIyEv7+/igpKQHA9rGnZ555Bp9//jmysrIQEhKiHB+qz7beynh7e/OPwgHqrY16MmPGDABQvZcc1UYMaoaJuro6nDlzBkFBQZg2bRpcXV3x9ddfK+eLi4tRVlaG+Ph4AEB8fDx++OEH1Yf0gQMH4O3tjTvuuMPu9Xd2ERERCAwMVLVJTU0NcnNzVW1SVVWFvLw8pcyhQ4fQ3t6ufCjEx8fj8OHDaGlpUcocOHAAMTExHNoYYr/88guuXr2KoKAgAGwfexBC4JlnnsHevXtx6NChbkN5Q/XZFh8fr7qGXEa+BvWuvzbqSUFBAQCo3ksOa6NbSjMmm1m3bp3Izs4WpaWl4ttvvxXz588X/v7+orKyUghhmfYYFhYmDh06JI4fPy7i4+NFfHy88nx5St19990nCgoKxBdffCFMJhOndN+C2tpakZ+fL/Lz8wUAsW3bNpGfny/Onz8vhLBM6fb19RWffvqpOHHihFi4cGGPU7qnTJkicnNzxdGjR8W4ceNUU4arqqqE2WwWv/vd70RRUZH4z3/+Izw8PDhleAD6ap/a2lqxfv16kZOTI0pLS8XBgwfF1KlTxbhx40RjY6NyDbaPbT311FPCx8dHZGdnq6YD19fXK2WG4rNNni68YcMGcfLkSfHOO+9wSvcA9ddGJSUl4vXXXxfHjx8XpaWl4tNPPxWRkZEiISFBuYYj24hBjUYtXbpUBAUFCYPBIMaOHSuWLl0qSkpKlPMNDQ3ij3/8oxg9erTw8PAQixcvFuXl5aprnDt3TixYsEC4u7sLf39/sW7dOtHS0mLvW3EaWVlZAkC3nxUrVgghLNO6X375ZWE2m4XRaBTz5s0TxcXFqmtcvXpVLFu2THh6egpvb2/x+OOPi9raWlWZwsJCcc899wij0SjGjh0rtmzZYq9bHNb6ap/6+npx3333CZPJJFxdXUV4eLhYvXq1asqpEGwfW+upfQCI9PR0pcxQfbZlZWWJO++8UxgMBhEZGal6Depdf21UVlYmEhIShJ+fnzAajSI6Olps2LBBtU6NEI5rI6njJoiIiIiGNebUEBERkVNgUENEREROgUENEREROQUGNUREROQUGNQQERGRU2BQQ0RERE6BQQ0RERE5BQY1ROQQr776Ku68805HV0MhSRL27dt3088rLi5GYGAgamtrh75SVq5cuYKAgAD88ssvNn0douGMQQ2RE3vvvffg5eWF1tZW5VhdXR1cXV0xZ84cVdns7GxIkoQzZ87YuZb2NdTB1MaNG7F27Vp4eXkN2TV74u/vj9///vdIS0uz6esQDWcMaoicWFJSEurq6nD8+HHl2JEjRxAYGIjc3Fw0NjYqx7OyshAWFoaoqChHVHVYKisrw+eff46VK1fa5fUef/xx7Ny5E9euXbPL6xENNwxqiJxYTEwMgoKCkJ2drRzLzs7GwoULERERge+//151PCkpCQDw0UcfYfr06fDy8kJgYCCWL1+u7Ljb3t6OkJAQbN++XfVa+fn50Ol0OH/+PACgqqoKTzzxBEwmE7y9vTF37lwUFhb2Wd8PPvgAEyZMgJubG26//Xa8++67yrlz585BkiTs2bMHSUlJ8PDwQFxcHHJyclTXeP/99xEaGgoPDw8sXrwY27Ztg6+vLwAgIyMDr732GgoLCyFJEiRJQkZGhvLcK1euYPHixfDw8MC4cePw2Wef9Vnfjz/+GHFxcRg7dqxyLCMjA76+vvjyyy8xYcIEeHp6IiUlBeXl5UqZlStXYtGiRXjzzTdhNpvh6+uL119/Ha2trdiwYQP8/PwQEhKC9PR01etNnDgRwcHB2Lt3b5/1IhqpGNQQObmkpCRkZWUpj7OysjBnzhwkJiYqxxsaGpCbm6sENS0tLdi8eTMKCwuxb98+nDt3TumN0Ol0WLZsGXbt2qV6nZ07d2LWrFkIDw8HACxZsgSVlZXIzMxEXl4epk6dinnz5vXay7Bz50688soreOONN3Dy5Em8+eabePnll/Hhhx+qym3atAnr169HQUEBxo8fj2XLlinDa99++y3WrFmDZ599FgUFBbj33nvxxhtvKM9dunQp1q1bh4kTJ6K8vBzl5eVYunSpcv61117Do48+ihMnTuD+++9Hampqn70iR44cwfTp07sdr6+vx9atW/HRRx/h8OHDKCsrw/r161VlDh06hEuXLuHw4cPYtm0b0tLS8Nvf/hajR49Gbm4u1qxZgyeffLJbDs1dd92FI0eO9FonohHtlrfEJCJNe//998WoUaNES0uLqKmpEXq9XlRWVopdu3aJhIQEIYQQX3/9tQAgzp8/3+M1jh07JgAoO1bn5+cLSZKU8m1tbWLs2LFi+/btQgghjhw5Iry9vUVjY6PqOlFRUWLHjh1CCCHS0tJEXFyc6tyuXbtU5Tdv3izi4+OFEEKUlpYKAOKDDz5Qzv/4448CgDh58qQQwrK7/QMPPKC6RmpqqvDx8VEed31dGQDx0ksvKY/r6uoEAJGZmdnjv4kQQsTFxYnXX39ddSw9PV0AECUlJcqxd955R5jNZuXxihUrRHh4uGhra1OOxcTEiNmzZyuPW1tbxahRo8Tu3btV13/uuefEnDlzeq0T0UjGnhoiJzdnzhzcuHEDx44dw5EjRzB+/HiYTCYkJiYqeTXZ2dmIjIxEWFgYACAvLw8PPvggwsLC4OXlhcTERACWHBIAuPPOOzFhwgSlt+abb75BZWUllixZAgAoLCxEXV0dxowZA09PT+WntLS0x0TkGzdu4MyZM1i1apWq/N/+9rdu5SdPnqz8HhQUBADK0FhxcTHuuusuVfmuj/tife1Ro0bB29tbuXZPGhoa4Obm1u24h4eHKjcpKCio23UmTpwIna7zI9hsNiM2NlZ57OLigjFjxnR7nru7O+rr6wd8T0Qjid7RFSAi24qOjkZISAiysrJw/fp1JUAJDg5GaGgovvvuO2RlZWHu3LkALAFGcnIykpOTsXPnTphMJpSVlSE5ORnNzc3KdVNTU7Fr1y68+OKL2LVrF1JSUjBmzBgAlhlWXXN5ZHJ+i7W6ujoAlnyYGTNmqM65uLioHru6uiq/S5IEwJLnMxSsry1fv69r+/v74/r16wO6jhCi3zIDef1r167BZDL1fhNEIxiDGqIRICkpCdnZ2bh+/To2bNigHE9ISEBmZib+97//4amnngIAnDp1ClevXsWWLVsQGhoKAKrZU7Lly5fjpZdeQl5eHv773//ivffeU85NnToVFRUV0Ov1uO222/qtn9lsRnBwMM6ePYvU1NRB32dMTAyOHTumOtb1scFgQFtb26Bfw9qUKVPw008/Dcm1BqqoqKjbdHwisuDwE9EIkJSUhKNHj6KgoEDpqQGAxMRE7NixA83NzUqScFhYGAwGA95++22cPXsWn332GTZv3tztmrfddhtmzpyJVatWoa2tDQ899JBybv78+YiPj8eiRYvw1Vdf4dy5c/juu++wadOmHgMkwJKk+9Zbb+Ff//oXfv75Z/zwww9IT0/Htm3bBnyfa9euxf79+7Ft2zacPn0aO3bsQGZmptKjI9e7tLQUBQUFuHLlCpqamgZ8/a6Sk5ORk5MzZEFSf+rr65GXl4f77rvPLq9HNNwwqCEaAZKSktDQ0IDo6GiYzWbleGJiImpra5Wp3wBgMpmQkZGBTz75BHfccQe2bNmCrVu39njd1NRUFBYWYvHixXB3d1eOS5KE/fv3IyEhAY8//jjGjx+Pxx57DOfPn1e9vrUnnngCH3zwAdLT0xEbG4vExERkZGQgIiJiwPc5a9YsvPfee9i2bRvi4uLwxRdf4LnnnlPlvTzyyCNISUlBUlISTCYTdu/ePeDrd7VgwQLo9XocPHhw0Ne4GZ9++inCwsIwe/Zsu7we0XAjia4DvURETmT16tU4deqUzaZBv/POO/jss8/w5Zdf2uT61u6++2786U9/wvLly23+WkTDEXNqiMipbN26Fffeey9GjRqFzMxMfPjhh6pF/Ibak08+iaqqKtTW1tp0q4QrV67g4YcfxrJly2z2GkTDHXtqiMipPProo8jOzkZtbS0iIyOxdu1arFmzxtHVIiI7YFBDREREToGJwkREROQUGNQQERGRU2BQQ0RERE6BQQ0RERE5BQY1RERE5BQY1BAREZFTYFBDREREToFBDRERETkFBjVERETkFP4/eBDLrQ675PAAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "''' we want to show the first 10 rows of the derivative spectra\n",
        "'''\n",
        "derivative_spring_2023.head(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 456
        },
        "id": "SFSV9BfuwuoB",
        "outputId": "db1f93c6-c00a-4542-f6c8-815d77386480"
      },
      "execution_count": 131,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Wavelength  ZachA_15_Weeds_derivative  ZachA_15_Soil_derivative  \\\n",
              "0         350                  -0.005281                  0.060978   \n",
              "1         360                   0.005605                  0.081897   \n",
              "2         370                   0.036323                  0.146291   \n",
              "3         380                   0.076360                  0.228821   \n",
              "4         390                   0.115458                  0.267241   \n",
              "5         400                   0.164383                  0.250059   \n",
              "6         410                   0.244600                  0.260643   \n",
              "7         420                   0.300163                  0.314684   \n",
              "8         430                   0.264296                  0.349809   \n",
              "9         440                   0.181860                  0.305738   \n",
              "\n",
              "   ZachA_14_Weeds_derivative  ZachA_14_Soil_derivative  \\\n",
              "0                  -0.000832                  0.040839   \n",
              "1                  -0.003619                  0.049214   \n",
              "2                   0.013253                  0.105019   \n",
              "3                   0.049443                  0.187289   \n",
              "4                   0.071207                  0.212487   \n",
              "5                   0.102408                  0.197066   \n",
              "6                   0.166635                  0.213888   \n",
              "7                   0.197567                  0.265226   \n",
              "8                   0.159233                  0.305424   \n",
              "9                   0.099917                  0.273616   \n",
              "\n",
              "   ZachA_13_Weeds_derivative  ZachA_13_Soil_derivative  \\\n",
              "0                  -0.011647                  0.005545   \n",
              "1                   0.006625                  0.027518   \n",
              "2                   0.039676                  0.080672   \n",
              "3                   0.076208                  0.138341   \n",
              "4                   0.111778                  0.165985   \n",
              "5                   0.137207                  0.153614   \n",
              "6                   0.183130                  0.160402   \n",
              "7                   0.219217                  0.203492   \n",
              "8                   0.199436                  0.231249   \n",
              "9                   0.149080                  0.200303   \n",
              "\n",
              "   ZachA_12_Wheat_derivative   ZachA_12_Road_derivative  \\\n",
              "0                   -0.011322                 -0.008601   \n",
              "1                   -0.013001                 -0.009691   \n",
              "2                   -0.004930                 -0.001066   \n",
              "3                    0.010323                  0.020064   \n",
              "4                    0.018530                  0.037863   \n",
              "5                    0.034832                  0.074473   \n",
              "6                    0.065421                  0.147777   \n",
              "7                    0.085760                  0.169737   \n",
              "8                    0.075800                  0.109184   \n",
              "9                    0.052444                  0.044486   \n",
              "\n",
              "   ZachA_11_Wheat_derivative  ...  JB_Grass_Filt_derivative  \\\n",
              "0                  -0.655343  ...                  0.004218   \n",
              "1                   0.042381  ...                  0.003247   \n",
              "2                  -0.123756  ...                  0.006300   \n",
              "3                  -1.725799  ...                  0.014875   \n",
              "4                  -2.344396  ...                  0.032060   \n",
              "5                  -2.498441  ...                  0.067092   \n",
              "6                  -2.930245  ...                  0.100975   \n",
              "7                  -3.000377  ...                  0.104461   \n",
              "8                  -2.444193  ...                  0.074961   \n",
              "9                  -1.699056  ...                  0.046087   \n",
              "\n",
              "   JanD_S10_Weeds_derivative  JanD_S9_Weeds_derivative  \\\n",
              "0                   0.000599                 -0.009809   \n",
              "1                  -0.000565                 -0.009532   \n",
              "2                   0.012066                  0.002503   \n",
              "3                   0.038554                  0.026391   \n",
              "4                   0.058406                  0.045591   \n",
              "5                   0.078698                  0.063795   \n",
              "6                   0.103666                  0.086019   \n",
              "7                   0.119760                  0.098693   \n",
              "8                   0.115592                  0.089792   \n",
              "9                   0.100481                  0.072596   \n",
              "\n",
              "   JanD_S9_Corn_Res_derivative  JanD_S8_Corn_Res_derivative  \\\n",
              "0                     0.077457                     0.108654   \n",
              "1                     0.078543                     0.127122   \n",
              "2                     0.107185                     0.178711   \n",
              "3                     0.167358                     0.246973   \n",
              "4                     0.218499                     0.308960   \n",
              "5                     0.247852                     0.368264   \n",
              "6                     0.280453                     0.448514   \n",
              "7                     0.305317                     0.504783   \n",
              "8                     0.295919                     0.508072   \n",
              "9                     0.268566                     0.484901   \n",
              "\n",
              "   JanD_S8_Bare_Soil_derivative  JanD_S6_Weed_derivative  \\\n",
              "0                      0.029559                 0.010741   \n",
              "1                      0.037857                 0.021101   \n",
              "2                      0.058177                 0.047206   \n",
              "3                      0.083475                 0.086076   \n",
              "4                      0.099326                 0.123375   \n",
              "5                      0.104427                 0.145688   \n",
              "6                      0.116544                 0.161866   \n",
              "7                      0.130170                 0.160079   \n",
              "8                      0.136547                 0.133238   \n",
              "9                      0.133514                 0.118788   \n",
              "\n",
              "   JanD_S6_Weed_2_derivative   JanD_S6_Weed_3_derivative   \\\n",
              "0                    0.025963                   -0.012493   \n",
              "1                    0.029599                   -0.009615   \n",
              "2                    0.052788                    0.004685   \n",
              "3                    0.090710                    0.029517   \n",
              "4                    0.123217                    0.049883   \n",
              "5                    0.154441                    0.076187   \n",
              "6                    0.194516                    0.120418   \n",
              "7                    0.212879                    0.155434   \n",
              "8                    0.191972                    0.153241   \n",
              "9                    0.178585                    0.136635   \n",
              "\n",
              "   JanD_S6_Corn_Rewd_derivative  \n",
              "0                      0.329258  \n",
              "1                      0.329629  \n",
              "2                      0.438000  \n",
              "3                      0.636000  \n",
              "4                      0.800002  \n",
              "5                      0.917083  \n",
              "6                      1.031726  \n",
              "7                      1.119915  \n",
              "8                      1.094072  \n",
              "9                      1.009411  \n",
              "\n",
              "[10 rows x 63 columns]"
            ],
            "text/html": [
              "\n",
              "\n",
              "  <div id=\"df-e19d4ada-ec54-437e-b0a4-11d8c74995fb\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Wavelength</th>\n",
              "      <th>ZachA_15_Weeds_derivative</th>\n",
              "      <th>ZachA_15_Soil_derivative</th>\n",
              "      <th>ZachA_14_Weeds_derivative</th>\n",
              "      <th>ZachA_14_Soil_derivative</th>\n",
              "      <th>ZachA_13_Weeds_derivative</th>\n",
              "      <th>ZachA_13_Soil_derivative</th>\n",
              "      <th>ZachA_12_Wheat_derivative</th>\n",
              "      <th>ZachA_12_Road_derivative</th>\n",
              "      <th>ZachA_11_Wheat_derivative</th>\n",
              "      <th>...</th>\n",
              "      <th>JB_Grass_Filt_derivative</th>\n",
              "      <th>JanD_S10_Weeds_derivative</th>\n",
              "      <th>JanD_S9_Weeds_derivative</th>\n",
              "      <th>JanD_S9_Corn_Res_derivative</th>\n",
              "      <th>JanD_S8_Corn_Res_derivative</th>\n",
              "      <th>JanD_S8_Bare_Soil_derivative</th>\n",
              "      <th>JanD_S6_Weed_derivative</th>\n",
              "      <th>JanD_S6_Weed_2_derivative</th>\n",
              "      <th>JanD_S6_Weed_3_derivative</th>\n",
              "      <th>JanD_S6_Corn_Rewd_derivative</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>350</td>\n",
              "      <td>-0.005281</td>\n",
              "      <td>0.060978</td>\n",
              "      <td>-0.000832</td>\n",
              "      <td>0.040839</td>\n",
              "      <td>-0.011647</td>\n",
              "      <td>0.005545</td>\n",
              "      <td>-0.011322</td>\n",
              "      <td>-0.008601</td>\n",
              "      <td>-0.655343</td>\n",
              "      <td>...</td>\n",
              "      <td>0.004218</td>\n",
              "      <td>0.000599</td>\n",
              "      <td>-0.009809</td>\n",
              "      <td>0.077457</td>\n",
              "      <td>0.108654</td>\n",
              "      <td>0.029559</td>\n",
              "      <td>0.010741</td>\n",
              "      <td>0.025963</td>\n",
              "      <td>-0.012493</td>\n",
              "      <td>0.329258</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>360</td>\n",
              "      <td>0.005605</td>\n",
              "      <td>0.081897</td>\n",
              "      <td>-0.003619</td>\n",
              "      <td>0.049214</td>\n",
              "      <td>0.006625</td>\n",
              "      <td>0.027518</td>\n",
              "      <td>-0.013001</td>\n",
              "      <td>-0.009691</td>\n",
              "      <td>0.042381</td>\n",
              "      <td>...</td>\n",
              "      <td>0.003247</td>\n",
              "      <td>-0.000565</td>\n",
              "      <td>-0.009532</td>\n",
              "      <td>0.078543</td>\n",
              "      <td>0.127122</td>\n",
              "      <td>0.037857</td>\n",
              "      <td>0.021101</td>\n",
              "      <td>0.029599</td>\n",
              "      <td>-0.009615</td>\n",
              "      <td>0.329629</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>370</td>\n",
              "      <td>0.036323</td>\n",
              "      <td>0.146291</td>\n",
              "      <td>0.013253</td>\n",
              "      <td>0.105019</td>\n",
              "      <td>0.039676</td>\n",
              "      <td>0.080672</td>\n",
              "      <td>-0.004930</td>\n",
              "      <td>-0.001066</td>\n",
              "      <td>-0.123756</td>\n",
              "      <td>...</td>\n",
              "      <td>0.006300</td>\n",
              "      <td>0.012066</td>\n",
              "      <td>0.002503</td>\n",
              "      <td>0.107185</td>\n",
              "      <td>0.178711</td>\n",
              "      <td>0.058177</td>\n",
              "      <td>0.047206</td>\n",
              "      <td>0.052788</td>\n",
              "      <td>0.004685</td>\n",
              "      <td>0.438000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>380</td>\n",
              "      <td>0.076360</td>\n",
              "      <td>0.228821</td>\n",
              "      <td>0.049443</td>\n",
              "      <td>0.187289</td>\n",
              "      <td>0.076208</td>\n",
              "      <td>0.138341</td>\n",
              "      <td>0.010323</td>\n",
              "      <td>0.020064</td>\n",
              "      <td>-1.725799</td>\n",
              "      <td>...</td>\n",
              "      <td>0.014875</td>\n",
              "      <td>0.038554</td>\n",
              "      <td>0.026391</td>\n",
              "      <td>0.167358</td>\n",
              "      <td>0.246973</td>\n",
              "      <td>0.083475</td>\n",
              "      <td>0.086076</td>\n",
              "      <td>0.090710</td>\n",
              "      <td>0.029517</td>\n",
              "      <td>0.636000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>390</td>\n",
              "      <td>0.115458</td>\n",
              "      <td>0.267241</td>\n",
              "      <td>0.071207</td>\n",
              "      <td>0.212487</td>\n",
              "      <td>0.111778</td>\n",
              "      <td>0.165985</td>\n",
              "      <td>0.018530</td>\n",
              "      <td>0.037863</td>\n",
              "      <td>-2.344396</td>\n",
              "      <td>...</td>\n",
              "      <td>0.032060</td>\n",
              "      <td>0.058406</td>\n",
              "      <td>0.045591</td>\n",
              "      <td>0.218499</td>\n",
              "      <td>0.308960</td>\n",
              "      <td>0.099326</td>\n",
              "      <td>0.123375</td>\n",
              "      <td>0.123217</td>\n",
              "      <td>0.049883</td>\n",
              "      <td>0.800002</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>400</td>\n",
              "      <td>0.164383</td>\n",
              "      <td>0.250059</td>\n",
              "      <td>0.102408</td>\n",
              "      <td>0.197066</td>\n",
              "      <td>0.137207</td>\n",
              "      <td>0.153614</td>\n",
              "      <td>0.034832</td>\n",
              "      <td>0.074473</td>\n",
              "      <td>-2.498441</td>\n",
              "      <td>...</td>\n",
              "      <td>0.067092</td>\n",
              "      <td>0.078698</td>\n",
              "      <td>0.063795</td>\n",
              "      <td>0.247852</td>\n",
              "      <td>0.368264</td>\n",
              "      <td>0.104427</td>\n",
              "      <td>0.145688</td>\n",
              "      <td>0.154441</td>\n",
              "      <td>0.076187</td>\n",
              "      <td>0.917083</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>410</td>\n",
              "      <td>0.244600</td>\n",
              "      <td>0.260643</td>\n",
              "      <td>0.166635</td>\n",
              "      <td>0.213888</td>\n",
              "      <td>0.183130</td>\n",
              "      <td>0.160402</td>\n",
              "      <td>0.065421</td>\n",
              "      <td>0.147777</td>\n",
              "      <td>-2.930245</td>\n",
              "      <td>...</td>\n",
              "      <td>0.100975</td>\n",
              "      <td>0.103666</td>\n",
              "      <td>0.086019</td>\n",
              "      <td>0.280453</td>\n",
              "      <td>0.448514</td>\n",
              "      <td>0.116544</td>\n",
              "      <td>0.161866</td>\n",
              "      <td>0.194516</td>\n",
              "      <td>0.120418</td>\n",
              "      <td>1.031726</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>420</td>\n",
              "      <td>0.300163</td>\n",
              "      <td>0.314684</td>\n",
              "      <td>0.197567</td>\n",
              "      <td>0.265226</td>\n",
              "      <td>0.219217</td>\n",
              "      <td>0.203492</td>\n",
              "      <td>0.085760</td>\n",
              "      <td>0.169737</td>\n",
              "      <td>-3.000377</td>\n",
              "      <td>...</td>\n",
              "      <td>0.104461</td>\n",
              "      <td>0.119760</td>\n",
              "      <td>0.098693</td>\n",
              "      <td>0.305317</td>\n",
              "      <td>0.504783</td>\n",
              "      <td>0.130170</td>\n",
              "      <td>0.160079</td>\n",
              "      <td>0.212879</td>\n",
              "      <td>0.155434</td>\n",
              "      <td>1.119915</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>430</td>\n",
              "      <td>0.264296</td>\n",
              "      <td>0.349809</td>\n",
              "      <td>0.159233</td>\n",
              "      <td>0.305424</td>\n",
              "      <td>0.199436</td>\n",
              "      <td>0.231249</td>\n",
              "      <td>0.075800</td>\n",
              "      <td>0.109184</td>\n",
              "      <td>-2.444193</td>\n",
              "      <td>...</td>\n",
              "      <td>0.074961</td>\n",
              "      <td>0.115592</td>\n",
              "      <td>0.089792</td>\n",
              "      <td>0.295919</td>\n",
              "      <td>0.508072</td>\n",
              "      <td>0.136547</td>\n",
              "      <td>0.133238</td>\n",
              "      <td>0.191972</td>\n",
              "      <td>0.153241</td>\n",
              "      <td>1.094072</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>440</td>\n",
              "      <td>0.181860</td>\n",
              "      <td>0.305738</td>\n",
              "      <td>0.099917</td>\n",
              "      <td>0.273616</td>\n",
              "      <td>0.149080</td>\n",
              "      <td>0.200303</td>\n",
              "      <td>0.052444</td>\n",
              "      <td>0.044486</td>\n",
              "      <td>-1.699056</td>\n",
              "      <td>...</td>\n",
              "      <td>0.046087</td>\n",
              "      <td>0.100481</td>\n",
              "      <td>0.072596</td>\n",
              "      <td>0.268566</td>\n",
              "      <td>0.484901</td>\n",
              "      <td>0.133514</td>\n",
              "      <td>0.118788</td>\n",
              "      <td>0.178585</td>\n",
              "      <td>0.136635</td>\n",
              "      <td>1.009411</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>10 rows × 63 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e19d4ada-ec54-437e-b0a4-11d8c74995fb')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "\n",
              "\n",
              "\n",
              "    <div id=\"df-9f582a99-275c-4ecf-82ab-6548939bf542\">\n",
              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-9f582a99-275c-4ecf-82ab-6548939bf542')\"\n",
              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-9f582a99-275c-4ecf-82ab-6548939bf542 button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e19d4ada-ec54-437e-b0a4-11d8c74995fb button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e19d4ada-ec54-437e-b0a4-11d8c74995fb');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 131
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "''' we want to add drdl to the wavelength to make it a string\n",
        "'''\n",
        "derivative_spring_2023['Wavelength'] = 'drdl' + derivative_spring_2023['Wavelength']. astype (str)\n",
        "derivative_spring_2023.head(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "id": "sJxu9MvA8apt",
        "outputId": "1fc46541-20ed-4769-cf0e-c145bf0c2d7c"
      },
      "execution_count": 132,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  Wavelength  ZachA_15_Weeds_derivative  ZachA_15_Soil_derivative  \\\n",
              "0    drdl350                  -0.005281                  0.060978   \n",
              "1    drdl360                   0.005605                  0.081897   \n",
              "2    drdl370                   0.036323                  0.146291   \n",
              "3    drdl380                   0.076360                  0.228821   \n",
              "4    drdl390                   0.115458                  0.267241   \n",
              "\n",
              "   ZachA_14_Weeds_derivative  ZachA_14_Soil_derivative  \\\n",
              "0                  -0.000832                  0.040839   \n",
              "1                  -0.003619                  0.049214   \n",
              "2                   0.013253                  0.105019   \n",
              "3                   0.049443                  0.187289   \n",
              "4                   0.071207                  0.212487   \n",
              "\n",
              "   ZachA_13_Weeds_derivative  ZachA_13_Soil_derivative  \\\n",
              "0                  -0.011647                  0.005545   \n",
              "1                   0.006625                  0.027518   \n",
              "2                   0.039676                  0.080672   \n",
              "3                   0.076208                  0.138341   \n",
              "4                   0.111778                  0.165985   \n",
              "\n",
              "   ZachA_12_Wheat_derivative   ZachA_12_Road_derivative  \\\n",
              "0                   -0.011322                 -0.008601   \n",
              "1                   -0.013001                 -0.009691   \n",
              "2                   -0.004930                 -0.001066   \n",
              "3                    0.010323                  0.020064   \n",
              "4                    0.018530                  0.037863   \n",
              "\n",
              "   ZachA_11_Wheat_derivative  ...  JB_Grass_Filt_derivative  \\\n",
              "0                  -0.655343  ...                  0.004218   \n",
              "1                   0.042381  ...                  0.003247   \n",
              "2                  -0.123756  ...                  0.006300   \n",
              "3                  -1.725799  ...                  0.014875   \n",
              "4                  -2.344396  ...                  0.032060   \n",
              "\n",
              "   JanD_S10_Weeds_derivative  JanD_S9_Weeds_derivative  \\\n",
              "0                   0.000599                 -0.009809   \n",
              "1                  -0.000565                 -0.009532   \n",
              "2                   0.012066                  0.002503   \n",
              "3                   0.038554                  0.026391   \n",
              "4                   0.058406                  0.045591   \n",
              "\n",
              "   JanD_S9_Corn_Res_derivative  JanD_S8_Corn_Res_derivative  \\\n",
              "0                     0.077457                     0.108654   \n",
              "1                     0.078543                     0.127122   \n",
              "2                     0.107185                     0.178711   \n",
              "3                     0.167358                     0.246973   \n",
              "4                     0.218499                     0.308960   \n",
              "\n",
              "   JanD_S8_Bare_Soil_derivative  JanD_S6_Weed_derivative  \\\n",
              "0                      0.029559                 0.010741   \n",
              "1                      0.037857                 0.021101   \n",
              "2                      0.058177                 0.047206   \n",
              "3                      0.083475                 0.086076   \n",
              "4                      0.099326                 0.123375   \n",
              "\n",
              "   JanD_S6_Weed_2_derivative   JanD_S6_Weed_3_derivative   \\\n",
              "0                    0.025963                   -0.012493   \n",
              "1                    0.029599                   -0.009615   \n",
              "2                    0.052788                    0.004685   \n",
              "3                    0.090710                    0.029517   \n",
              "4                    0.123217                    0.049883   \n",
              "\n",
              "   JanD_S6_Corn_Rewd_derivative  \n",
              "0                      0.329258  \n",
              "1                      0.329629  \n",
              "2                      0.438000  \n",
              "3                      0.636000  \n",
              "4                      0.800002  \n",
              "\n",
              "[5 rows x 63 columns]"
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Wavelength</th>\n",
              "      <th>ZachA_15_Weeds_derivative</th>\n",
              "      <th>ZachA_15_Soil_derivative</th>\n",
              "      <th>ZachA_14_Weeds_derivative</th>\n",
              "      <th>ZachA_14_Soil_derivative</th>\n",
              "      <th>ZachA_13_Weeds_derivative</th>\n",
              "      <th>ZachA_13_Soil_derivative</th>\n",
              "      <th>ZachA_12_Wheat_derivative</th>\n",
              "      <th>ZachA_12_Road_derivative</th>\n",
              "      <th>ZachA_11_Wheat_derivative</th>\n",
              "      <th>...</th>\n",
              "      <th>JB_Grass_Filt_derivative</th>\n",
              "      <th>JanD_S10_Weeds_derivative</th>\n",
              "      <th>JanD_S9_Weeds_derivative</th>\n",
              "      <th>JanD_S9_Corn_Res_derivative</th>\n",
              "      <th>JanD_S8_Corn_Res_derivative</th>\n",
              "      <th>JanD_S8_Bare_Soil_derivative</th>\n",
              "      <th>JanD_S6_Weed_derivative</th>\n",
              "      <th>JanD_S6_Weed_2_derivative</th>\n",
              "      <th>JanD_S6_Weed_3_derivative</th>\n",
              "      <th>JanD_S6_Corn_Rewd_derivative</th>\n",
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              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>drdl350</td>\n",
              "      <td>-0.005281</td>\n",
              "      <td>0.060978</td>\n",
              "      <td>-0.000832</td>\n",
              "      <td>0.040839</td>\n",
              "      <td>-0.011647</td>\n",
              "      <td>0.005545</td>\n",
              "      <td>-0.011322</td>\n",
              "      <td>-0.008601</td>\n",
              "      <td>-0.655343</td>\n",
              "      <td>...</td>\n",
              "      <td>0.004218</td>\n",
              "      <td>0.000599</td>\n",
              "      <td>-0.009809</td>\n",
              "      <td>0.077457</td>\n",
              "      <td>0.108654</td>\n",
              "      <td>0.029559</td>\n",
              "      <td>0.010741</td>\n",
              "      <td>0.025963</td>\n",
              "      <td>-0.012493</td>\n",
              "      <td>0.329258</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>drdl360</td>\n",
              "      <td>0.005605</td>\n",
              "      <td>0.081897</td>\n",
              "      <td>-0.003619</td>\n",
              "      <td>0.049214</td>\n",
              "      <td>0.006625</td>\n",
              "      <td>0.027518</td>\n",
              "      <td>-0.013001</td>\n",
              "      <td>-0.009691</td>\n",
              "      <td>0.042381</td>\n",
              "      <td>...</td>\n",
              "      <td>0.003247</td>\n",
              "      <td>-0.000565</td>\n",
              "      <td>-0.009532</td>\n",
              "      <td>0.078543</td>\n",
              "      <td>0.127122</td>\n",
              "      <td>0.037857</td>\n",
              "      <td>0.021101</td>\n",
              "      <td>0.029599</td>\n",
              "      <td>-0.009615</td>\n",
              "      <td>0.329629</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>drdl370</td>\n",
              "      <td>0.036323</td>\n",
              "      <td>0.146291</td>\n",
              "      <td>0.013253</td>\n",
              "      <td>0.105019</td>\n",
              "      <td>0.039676</td>\n",
              "      <td>0.080672</td>\n",
              "      <td>-0.004930</td>\n",
              "      <td>-0.001066</td>\n",
              "      <td>-0.123756</td>\n",
              "      <td>...</td>\n",
              "      <td>0.006300</td>\n",
              "      <td>0.012066</td>\n",
              "      <td>0.002503</td>\n",
              "      <td>0.107185</td>\n",
              "      <td>0.178711</td>\n",
              "      <td>0.058177</td>\n",
              "      <td>0.047206</td>\n",
              "      <td>0.052788</td>\n",
              "      <td>0.004685</td>\n",
              "      <td>0.438000</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>drdl380</td>\n",
              "      <td>0.076360</td>\n",
              "      <td>0.228821</td>\n",
              "      <td>0.049443</td>\n",
              "      <td>0.187289</td>\n",
              "      <td>0.076208</td>\n",
              "      <td>0.138341</td>\n",
              "      <td>0.010323</td>\n",
              "      <td>0.020064</td>\n",
              "      <td>-1.725799</td>\n",
              "      <td>...</td>\n",
              "      <td>0.014875</td>\n",
              "      <td>0.038554</td>\n",
              "      <td>0.026391</td>\n",
              "      <td>0.167358</td>\n",
              "      <td>0.246973</td>\n",
              "      <td>0.083475</td>\n",
              "      <td>0.086076</td>\n",
              "      <td>0.090710</td>\n",
              "      <td>0.029517</td>\n",
              "      <td>0.636000</td>\n",
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              "      <th>4</th>\n",
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              "      <td>0.267241</td>\n",
              "      <td>0.071207</td>\n",
              "      <td>0.212487</td>\n",
              "      <td>0.111778</td>\n",
              "      <td>0.165985</td>\n",
              "      <td>0.018530</td>\n",
              "      <td>0.037863</td>\n",
              "      <td>-2.344396</td>\n",
              "      <td>...</td>\n",
              "      <td>0.032060</td>\n",
              "      <td>0.058406</td>\n",
              "      <td>0.045591</td>\n",
              "      <td>0.218499</td>\n",
              "      <td>0.308960</td>\n",
              "      <td>0.099326</td>\n",
              "      <td>0.123375</td>\n",
              "      <td>0.123217</td>\n",
              "      <td>0.049883</td>\n",
              "      <td>0.800002</td>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 132
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "''' we want to export our result to excel\n",
        "'''\n",
        "derivative_spring_2023.to_excel(\"Winter_2023_Derivatives.xlsx\")"
      ],
      "metadata": {
        "id": "8ZBipk9IxCy-"
      },
      "execution_count": 133,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\"We want to transpose the derivatives before calculating correlation matrixes\"\n",
        "derivative_transpose = derivative_spring_2023.set_index('Wavelength').T\n",
        "derivative_transpose.head(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "id": "LbojLpnqAD4z",
        "outputId": "ad0532ba-678c-40e3-c276-e4b19fdf9c68"
      },
      "execution_count": 134,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Wavelength                  drdl350   drdl360   drdl370   drdl380   drdl390  \\\n",
              "ZachA_15_Weeds_derivative -0.005281  0.005605  0.036323  0.076360  0.115458   \n",
              "ZachA_15_Soil_derivative   0.060978  0.081897  0.146291  0.228821  0.267241   \n",
              "ZachA_14_Weeds_derivative -0.000832 -0.003619  0.013253  0.049443  0.071207   \n",
              "ZachA_14_Soil_derivative   0.040839  0.049214  0.105019  0.187289  0.212487   \n",
              "ZachA_13_Weeds_derivative -0.011647  0.006625  0.039676  0.076208  0.111778   \n",
              "\n",
              "Wavelength                  drdl400   drdl410   drdl420   drdl430   drdl440  \\\n",
              "ZachA_15_Weeds_derivative  0.164383  0.244600  0.300163  0.264296  0.181860   \n",
              "ZachA_15_Soil_derivative   0.250059  0.260643  0.314684  0.349809  0.305738   \n",
              "ZachA_14_Weeds_derivative  0.102408  0.166635  0.197567  0.159233  0.099917   \n",
              "ZachA_14_Soil_derivative   0.197066  0.213888  0.265226  0.305424  0.273616   \n",
              "ZachA_13_Weeds_derivative  0.137207  0.183130  0.219217  0.199436  0.149080   \n",
              "\n",
              "Wavelength                 ...  drdl2410  drdl2420  drdl2430  drdl2440  \\\n",
              "ZachA_15_Weeds_derivative  ... -0.262395 -0.245642 -0.263843 -0.225620   \n",
              "ZachA_15_Soil_derivative   ... -0.363686 -0.213672 -0.220900 -0.354144   \n",
              "ZachA_14_Weeds_derivative  ... -0.116054 -0.138614 -0.155877 -0.122684   \n",
              "ZachA_14_Soil_derivative   ... -0.197730 -0.217173 -0.230285 -0.224334   \n",
              "ZachA_13_Weeds_derivative  ... -0.332515 -0.308985 -0.208128 -0.117861   \n",
              "\n",
              "Wavelength                 drdl2450  drdl2460  drdl2470  drdl2480  drdl2490  \\\n",
              "ZachA_15_Weeds_derivative -0.312717 -0.322507  0.042025  0.110931       0.0   \n",
              "ZachA_15_Soil_derivative  -0.386019 -0.349776 -0.342596 -0.204413       0.0   \n",
              "ZachA_14_Weeds_derivative -0.118322 -0.131216 -0.135085 -0.066869       0.0   \n",
              "ZachA_14_Soil_derivative  -0.191753 -0.185074 -0.163813 -0.064058       0.0   \n",
              "ZachA_13_Weeds_derivative -0.243404 -0.460958 -0.192163  0.152064       0.0   \n",
              "\n",
              "Wavelength                 drdl2500  \n",
              "ZachA_15_Weeds_derivative       0.0  \n",
              "ZachA_15_Soil_derivative        0.0  \n",
              "ZachA_14_Weeds_derivative       0.0  \n",
              "ZachA_14_Soil_derivative        0.0  \n",
              "ZachA_13_Weeds_derivative       0.0  \n",
              "\n",
              "[5 rows x 216 columns]"
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              "      <th>Wavelength</th>\n",
              "      <th>drdl350</th>\n",
              "      <th>drdl360</th>\n",
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              "      <th>drdl380</th>\n",
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              "      <th>ZachA_15_Weeds_derivative</th>\n",
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              "      <td>0.076360</td>\n",
              "      <td>0.115458</td>\n",
              "      <td>0.164383</td>\n",
              "      <td>0.244600</td>\n",
              "      <td>0.300163</td>\n",
              "      <td>0.264296</td>\n",
              "      <td>0.181860</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.262395</td>\n",
              "      <td>-0.245642</td>\n",
              "      <td>-0.263843</td>\n",
              "      <td>-0.225620</td>\n",
              "      <td>-0.312717</td>\n",
              "      <td>-0.322507</td>\n",
              "      <td>0.042025</td>\n",
              "      <td>0.110931</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ZachA_15_Soil_derivative</th>\n",
              "      <td>0.060978</td>\n",
              "      <td>0.081897</td>\n",
              "      <td>0.146291</td>\n",
              "      <td>0.228821</td>\n",
              "      <td>0.267241</td>\n",
              "      <td>0.250059</td>\n",
              "      <td>0.260643</td>\n",
              "      <td>0.314684</td>\n",
              "      <td>0.349809</td>\n",
              "      <td>0.305738</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.363686</td>\n",
              "      <td>-0.213672</td>\n",
              "      <td>-0.220900</td>\n",
              "      <td>-0.354144</td>\n",
              "      <td>-0.386019</td>\n",
              "      <td>-0.349776</td>\n",
              "      <td>-0.342596</td>\n",
              "      <td>-0.204413</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ZachA_14_Weeds_derivative</th>\n",
              "      <td>-0.000832</td>\n",
              "      <td>-0.003619</td>\n",
              "      <td>0.013253</td>\n",
              "      <td>0.049443</td>\n",
              "      <td>0.071207</td>\n",
              "      <td>0.102408</td>\n",
              "      <td>0.166635</td>\n",
              "      <td>0.197567</td>\n",
              "      <td>0.159233</td>\n",
              "      <td>0.099917</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.116054</td>\n",
              "      <td>-0.138614</td>\n",
              "      <td>-0.155877</td>\n",
              "      <td>-0.122684</td>\n",
              "      <td>-0.118322</td>\n",
              "      <td>-0.131216</td>\n",
              "      <td>-0.135085</td>\n",
              "      <td>-0.066869</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ZachA_14_Soil_derivative</th>\n",
              "      <td>0.040839</td>\n",
              "      <td>0.049214</td>\n",
              "      <td>0.105019</td>\n",
              "      <td>0.187289</td>\n",
              "      <td>0.212487</td>\n",
              "      <td>0.197066</td>\n",
              "      <td>0.213888</td>\n",
              "      <td>0.265226</td>\n",
              "      <td>0.305424</td>\n",
              "      <td>0.273616</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.197730</td>\n",
              "      <td>-0.217173</td>\n",
              "      <td>-0.230285</td>\n",
              "      <td>-0.224334</td>\n",
              "      <td>-0.191753</td>\n",
              "      <td>-0.185074</td>\n",
              "      <td>-0.163813</td>\n",
              "      <td>-0.064058</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ZachA_13_Weeds_derivative</th>\n",
              "      <td>-0.011647</td>\n",
              "      <td>0.006625</td>\n",
              "      <td>0.039676</td>\n",
              "      <td>0.076208</td>\n",
              "      <td>0.111778</td>\n",
              "      <td>0.137207</td>\n",
              "      <td>0.183130</td>\n",
              "      <td>0.219217</td>\n",
              "      <td>0.199436</td>\n",
              "      <td>0.149080</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.332515</td>\n",
              "      <td>-0.308985</td>\n",
              "      <td>-0.208128</td>\n",
              "      <td>-0.117861</td>\n",
              "      <td>-0.243404</td>\n",
              "      <td>-0.460958</td>\n",
              "      <td>-0.192163</td>\n",
              "      <td>0.152064</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 216 columns</p>\n",
              "</div>\n",
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              "\n",
              "<style>\n",
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              "\n",
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              "        displayQuickchartButton(document);\n",
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              "      <style>\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-b160b112-9a7d-45ce-bde9-c7af2dcbd6ac');\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 134
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "derivative_transpose.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZrY2GZOgtLGg",
        "outputId": "3dd45198-5add-429b-a546-5dd757783bff"
      },
      "execution_count": 135,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(62, 216)"
            ]
          },
          "metadata": {},
          "execution_count": 135
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "''' we want to calculate the correlation matrix\n",
        "'''\n",
        "corr_matrix = derivative_transpose.corr(method = \"pearson\")\n",
        "corr_matrix\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "r-FxGVTnrWWz",
        "outputId": "9a3d856b-fbf3-4777-d403-dfd8ab922d09"
      },
      "execution_count": 136,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Wavelength   drdl350   drdl360   drdl370   drdl380   drdl390   drdl400  \\\n",
              "Wavelength                                                               \n",
              "drdl350     1.000000  0.482606  0.654041  0.975384  0.972916  0.969459   \n",
              "drdl360     0.482606  1.000000  0.955182  0.414024  0.354204  0.326929   \n",
              "drdl370     0.654041  0.955182  1.000000  0.631822  0.575833  0.546365   \n",
              "drdl380     0.975384  0.414024  0.631822  1.000000  0.996738  0.989312   \n",
              "drdl390     0.972916  0.354204  0.575833  0.996738  1.000000  0.997074   \n",
              "...              ...       ...       ...       ...       ...       ...   \n",
              "drdl2460    0.060116 -0.311966 -0.152462  0.187612  0.202508  0.211029   \n",
              "drdl2470   -0.383437 -0.643568 -0.655634 -0.377445 -0.349424 -0.342573   \n",
              "drdl2480   -0.383017 -0.415383 -0.510721 -0.443477 -0.425396 -0.421786   \n",
              "drdl2490         NaN       NaN       NaN       NaN       NaN       NaN   \n",
              "drdl2500         NaN       NaN       NaN       NaN       NaN       NaN   \n",
              "\n",
              "Wavelength   drdl410   drdl420   drdl430   drdl440  ...  drdl2410  drdl2420  \\\n",
              "Wavelength                                          ...                       \n",
              "drdl350     0.956460  0.960268  0.974061  0.978384  ... -0.240908 -0.588634   \n",
              "drdl360     0.277550  0.295224  0.378946  0.491154  ... -0.801476 -0.476166   \n",
              "drdl370     0.499914  0.515765  0.589710  0.681195  ... -0.701706 -0.452974   \n",
              "drdl380     0.978070  0.980699  0.988619  0.980967  ... -0.154865 -0.455782   \n",
              "drdl390     0.990386  0.991829  0.993280  0.977770  ... -0.109846 -0.453058   \n",
              "...              ...       ...       ...       ...  ...       ...       ...   \n",
              "drdl2460    0.233613  0.217842  0.172240  0.105906  ...  0.489465  0.644646   \n",
              "drdl2470   -0.320386 -0.326580 -0.366184 -0.428253  ...  0.492992  0.070767   \n",
              "drdl2480   -0.413989 -0.412389 -0.423417 -0.442914  ...  0.180146 -0.242412   \n",
              "drdl2490         NaN       NaN       NaN       NaN  ...       NaN       NaN   \n",
              "drdl2500         NaN       NaN       NaN       NaN  ...       NaN       NaN   \n",
              "\n",
              "Wavelength  drdl2430  drdl2440  drdl2450  drdl2460  drdl2470  drdl2480  \\\n",
              "Wavelength                                                               \n",
              "drdl350    -0.868091 -0.603000 -0.550032  0.060116 -0.383437 -0.383017   \n",
              "drdl360    -0.463064 -0.752623 -0.782562 -0.311966 -0.643568 -0.415383   \n",
              "drdl370    -0.556404 -0.777527 -0.786910 -0.152462 -0.655634 -0.510721   \n",
              "drdl380    -0.795784 -0.561055 -0.504360  0.187612 -0.377445 -0.443477   \n",
              "drdl390    -0.805610 -0.538734 -0.477485  0.202508 -0.349424 -0.425396   \n",
              "...              ...       ...       ...       ...       ...       ...   \n",
              "drdl2460    0.163821 -0.091117  0.084804  1.000000 -0.135586 -0.558144   \n",
              "drdl2470    0.424720  0.832894  0.785116 -0.135586  1.000000  0.859750   \n",
              "drdl2480    0.310664  0.742342  0.694688 -0.558144  0.859750  1.000000   \n",
              "drdl2490         NaN       NaN       NaN       NaN       NaN       NaN   \n",
              "drdl2500         NaN       NaN       NaN       NaN       NaN       NaN   \n",
              "\n",
              "Wavelength  drdl2490  drdl2500  \n",
              "Wavelength                      \n",
              "drdl350          NaN       NaN  \n",
              "drdl360          NaN       NaN  \n",
              "drdl370          NaN       NaN  \n",
              "drdl380          NaN       NaN  \n",
              "drdl390          NaN       NaN  \n",
              "...              ...       ...  \n",
              "drdl2460         NaN       NaN  \n",
              "drdl2470         NaN       NaN  \n",
              "drdl2480         NaN       NaN  \n",
              "drdl2490         NaN       NaN  \n",
              "drdl2500         NaN       NaN  \n",
              "\n",
              "[216 rows x 216 columns]"
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              "      <th>drdl350</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.482606</td>\n",
              "      <td>0.654041</td>\n",
              "      <td>0.975384</td>\n",
              "      <td>0.972916</td>\n",
              "      <td>0.969459</td>\n",
              "      <td>0.956460</td>\n",
              "      <td>0.960268</td>\n",
              "      <td>0.974061</td>\n",
              "      <td>0.978384</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.240908</td>\n",
              "      <td>-0.588634</td>\n",
              "      <td>-0.868091</td>\n",
              "      <td>-0.603000</td>\n",
              "      <td>-0.550032</td>\n",
              "      <td>0.060116</td>\n",
              "      <td>-0.383437</td>\n",
              "      <td>-0.383017</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <th>drdl360</th>\n",
              "      <td>0.482606</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.955182</td>\n",
              "      <td>0.414024</td>\n",
              "      <td>0.354204</td>\n",
              "      <td>0.326929</td>\n",
              "      <td>0.277550</td>\n",
              "      <td>0.295224</td>\n",
              "      <td>0.378946</td>\n",
              "      <td>0.491154</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.801476</td>\n",
              "      <td>-0.476166</td>\n",
              "      <td>-0.463064</td>\n",
              "      <td>-0.752623</td>\n",
              "      <td>-0.782562</td>\n",
              "      <td>-0.311966</td>\n",
              "      <td>-0.643568</td>\n",
              "      <td>-0.415383</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drdl370</th>\n",
              "      <td>0.654041</td>\n",
              "      <td>0.955182</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.631822</td>\n",
              "      <td>0.575833</td>\n",
              "      <td>0.546365</td>\n",
              "      <td>0.499914</td>\n",
              "      <td>0.515765</td>\n",
              "      <td>0.589710</td>\n",
              "      <td>0.681195</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.701706</td>\n",
              "      <td>-0.452974</td>\n",
              "      <td>-0.556404</td>\n",
              "      <td>-0.777527</td>\n",
              "      <td>-0.786910</td>\n",
              "      <td>-0.152462</td>\n",
              "      <td>-0.655634</td>\n",
              "      <td>-0.510721</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drdl380</th>\n",
              "      <td>0.975384</td>\n",
              "      <td>0.414024</td>\n",
              "      <td>0.631822</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.996738</td>\n",
              "      <td>0.989312</td>\n",
              "      <td>0.978070</td>\n",
              "      <td>0.980699</td>\n",
              "      <td>0.988619</td>\n",
              "      <td>0.980967</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.154865</td>\n",
              "      <td>-0.455782</td>\n",
              "      <td>-0.795784</td>\n",
              "      <td>-0.561055</td>\n",
              "      <td>-0.504360</td>\n",
              "      <td>0.187612</td>\n",
              "      <td>-0.377445</td>\n",
              "      <td>-0.443477</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drdl390</th>\n",
              "      <td>0.972916</td>\n",
              "      <td>0.354204</td>\n",
              "      <td>0.575833</td>\n",
              "      <td>0.996738</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.997074</td>\n",
              "      <td>0.990386</td>\n",
              "      <td>0.991829</td>\n",
              "      <td>0.993280</td>\n",
              "      <td>0.977770</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.109846</td>\n",
              "      <td>-0.453058</td>\n",
              "      <td>-0.805610</td>\n",
              "      <td>-0.538734</td>\n",
              "      <td>-0.477485</td>\n",
              "      <td>0.202508</td>\n",
              "      <td>-0.349424</td>\n",
              "      <td>-0.425396</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drdl2460</th>\n",
              "      <td>0.060116</td>\n",
              "      <td>-0.311966</td>\n",
              "      <td>-0.152462</td>\n",
              "      <td>0.187612</td>\n",
              "      <td>0.202508</td>\n",
              "      <td>0.211029</td>\n",
              "      <td>0.233613</td>\n",
              "      <td>0.217842</td>\n",
              "      <td>0.172240</td>\n",
              "      <td>0.105906</td>\n",
              "      <td>...</td>\n",
              "      <td>0.489465</td>\n",
              "      <td>0.644646</td>\n",
              "      <td>0.163821</td>\n",
              "      <td>-0.091117</td>\n",
              "      <td>0.084804</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.135586</td>\n",
              "      <td>-0.558144</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drdl2470</th>\n",
              "      <td>-0.383437</td>\n",
              "      <td>-0.643568</td>\n",
              "      <td>-0.655634</td>\n",
              "      <td>-0.377445</td>\n",
              "      <td>-0.349424</td>\n",
              "      <td>-0.342573</td>\n",
              "      <td>-0.320386</td>\n",
              "      <td>-0.326580</td>\n",
              "      <td>-0.366184</td>\n",
              "      <td>-0.428253</td>\n",
              "      <td>...</td>\n",
              "      <td>0.492992</td>\n",
              "      <td>0.070767</td>\n",
              "      <td>0.424720</td>\n",
              "      <td>0.832894</td>\n",
              "      <td>0.785116</td>\n",
              "      <td>-0.135586</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.859750</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drdl2480</th>\n",
              "      <td>-0.383017</td>\n",
              "      <td>-0.415383</td>\n",
              "      <td>-0.510721</td>\n",
              "      <td>-0.443477</td>\n",
              "      <td>-0.425396</td>\n",
              "      <td>-0.421786</td>\n",
              "      <td>-0.413989</td>\n",
              "      <td>-0.412389</td>\n",
              "      <td>-0.423417</td>\n",
              "      <td>-0.442914</td>\n",
              "      <td>...</td>\n",
              "      <td>0.180146</td>\n",
              "      <td>-0.242412</td>\n",
              "      <td>0.310664</td>\n",
              "      <td>0.742342</td>\n",
              "      <td>0.694688</td>\n",
              "      <td>-0.558144</td>\n",
              "      <td>0.859750</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drdl2490</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drdl2500</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>216 rows × 216 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-af1abe37-8116-4098-8909-5d8bc502ae29')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "\n",
              "\n",
              "\n",
              "    <div id=\"df-7053af42-4ad5-4b54-b199-470d3702b834\">\n",
              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-7053af42-4ad5-4b54-b199-470d3702b834')\"\n",
              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-7053af42-4ad5-4b54-b199-470d3702b834 button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-af1abe37-8116-4098-8909-5d8bc502ae29 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-af1abe37-8116-4098-8909-5d8bc502ae29');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 136
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "''' we are checking for missing values in the correlation matrix\n",
        "'''\n",
        "corr_matrix.isna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0-amvtLe7ljz",
        "outputId": "d1d5c65c-6624-43f3-f7e0-362613864f6d"
      },
      "execution_count": 137,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Wavelength\n",
              "drdl350      27\n",
              "drdl360      27\n",
              "drdl370      27\n",
              "drdl380      27\n",
              "drdl390      27\n",
              "           ... \n",
              "drdl2460     27\n",
              "drdl2470     27\n",
              "drdl2480     27\n",
              "drdl2490    216\n",
              "drdl2500    216\n",
              "Length: 216, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 137
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "corr_matrix.shape\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1sc-A46-Blgp",
        "outputId": "b792e6cf-1b8e-4317-8f6c-2e0f96fa7c49"
      },
      "execution_count": 138,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(216, 216)"
            ]
          },
          "metadata": {},
          "execution_count": 138
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\"\"\"We want to drop missing values\"\"\"\n",
        "corr_matrix = corr_matrix.dropna(how = 'all')\n",
        "corr_matrix\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "SDXRyQD1whPz",
        "outputId": "5fb719c1-0835-4a82-a6a7-ae8d4230675b"
      },
      "execution_count": 139,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Wavelength   drdl350   drdl360   drdl370   drdl380   drdl390   drdl400  \\\n",
              "Wavelength                                                               \n",
              "drdl350     1.000000  0.482606  0.654041  0.975384  0.972916  0.969459   \n",
              "drdl360     0.482606  1.000000  0.955182  0.414024  0.354204  0.326929   \n",
              "drdl370     0.654041  0.955182  1.000000  0.631822  0.575833  0.546365   \n",
              "drdl380     0.975384  0.414024  0.631822  1.000000  0.996738  0.989312   \n",
              "drdl390     0.972916  0.354204  0.575833  0.996738  1.000000  0.997074   \n",
              "...              ...       ...       ...       ...       ...       ...   \n",
              "drdl2440   -0.603000 -0.752623 -0.777527 -0.561055 -0.538734 -0.542388   \n",
              "drdl2450   -0.550032 -0.782562 -0.786910 -0.504360 -0.477485 -0.476187   \n",
              "drdl2460    0.060116 -0.311966 -0.152462  0.187612  0.202508  0.211029   \n",
              "drdl2470   -0.383437 -0.643568 -0.655634 -0.377445 -0.349424 -0.342573   \n",
              "drdl2480   -0.383017 -0.415383 -0.510721 -0.443477 -0.425396 -0.421786   \n",
              "\n",
              "Wavelength   drdl410   drdl420   drdl430   drdl440  ...  drdl2410  drdl2420  \\\n",
              "Wavelength                                          ...                       \n",
              "drdl350     0.956460  0.960268  0.974061  0.978384  ... -0.240908 -0.588634   \n",
              "drdl360     0.277550  0.295224  0.378946  0.491154  ... -0.801476 -0.476166   \n",
              "drdl370     0.499914  0.515765  0.589710  0.681195  ... -0.701706 -0.452974   \n",
              "drdl380     0.978070  0.980699  0.988619  0.980967  ... -0.154865 -0.455782   \n",
              "drdl390     0.990386  0.991829  0.993280  0.977770  ... -0.109846 -0.453058   \n",
              "...              ...       ...       ...       ...  ...       ...       ...   \n",
              "drdl2440   -0.520842 -0.529198 -0.573945 -0.643271  ...  0.624582  0.352219   \n",
              "drdl2450   -0.452206 -0.462433 -0.510003 -0.584948  ...  0.656487  0.368156   \n",
              "drdl2460    0.233613  0.217842  0.172240  0.105906  ...  0.489465  0.644646   \n",
              "drdl2470   -0.320386 -0.326580 -0.366184 -0.428253  ...  0.492992  0.070767   \n",
              "drdl2480   -0.413989 -0.412389 -0.423417 -0.442914  ...  0.180146 -0.242412   \n",
              "\n",
              "Wavelength  drdl2430  drdl2440  drdl2450  drdl2460  drdl2470  drdl2480  \\\n",
              "Wavelength                                                               \n",
              "drdl350    -0.868091 -0.603000 -0.550032  0.060116 -0.383437 -0.383017   \n",
              "drdl360    -0.463064 -0.752623 -0.782562 -0.311966 -0.643568 -0.415383   \n",
              "drdl370    -0.556404 -0.777527 -0.786910 -0.152462 -0.655634 -0.510721   \n",
              "drdl380    -0.795784 -0.561055 -0.504360  0.187612 -0.377445 -0.443477   \n",
              "drdl390    -0.805610 -0.538734 -0.477485  0.202508 -0.349424 -0.425396   \n",
              "...              ...       ...       ...       ...       ...       ...   \n",
              "drdl2440    0.679845  1.000000  0.928359 -0.091117  0.832894  0.742342   \n",
              "drdl2450    0.649296  0.928359  1.000000  0.084804  0.785116  0.694688   \n",
              "drdl2460    0.163821 -0.091117  0.084804  1.000000 -0.135586 -0.558144   \n",
              "drdl2470    0.424720  0.832894  0.785116 -0.135586  1.000000  0.859750   \n",
              "drdl2480    0.310664  0.742342  0.694688 -0.558144  0.859750  1.000000   \n",
              "\n",
              "Wavelength  drdl2490  drdl2500  \n",
              "Wavelength                      \n",
              "drdl350          NaN       NaN  \n",
              "drdl360          NaN       NaN  \n",
              "drdl370          NaN       NaN  \n",
              "drdl380          NaN       NaN  \n",
              "drdl390          NaN       NaN  \n",
              "...              ...       ...  \n",
              "drdl2440         NaN       NaN  \n",
              "drdl2450         NaN       NaN  \n",
              "drdl2460         NaN       NaN  \n",
              "drdl2470         NaN       NaN  \n",
              "drdl2480         NaN       NaN  \n",
              "\n",
              "[189 rows x 216 columns]"
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              "      <th>drdl350</th>\n",
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              "      <th>drdl360</th>\n",
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              "      <td>0.414024</td>\n",
              "      <td>0.354204</td>\n",
              "      <td>0.326929</td>\n",
              "      <td>0.277550</td>\n",
              "      <td>0.295224</td>\n",
              "      <td>0.378946</td>\n",
              "      <td>0.491154</td>\n",
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              "      <td>-0.801476</td>\n",
              "      <td>-0.476166</td>\n",
              "      <td>-0.463064</td>\n",
              "      <td>-0.752623</td>\n",
              "      <td>-0.782562</td>\n",
              "      <td>-0.311966</td>\n",
              "      <td>-0.643568</td>\n",
              "      <td>-0.415383</td>\n",
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              "      <td>NaN</td>\n",
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              "      <th>drdl370</th>\n",
              "      <td>0.654041</td>\n",
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              "      <td>0.631822</td>\n",
              "      <td>0.575833</td>\n",
              "      <td>0.546365</td>\n",
              "      <td>0.499914</td>\n",
              "      <td>0.515765</td>\n",
              "      <td>0.589710</td>\n",
              "      <td>0.681195</td>\n",
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              "      <td>-0.701706</td>\n",
              "      <td>-0.452974</td>\n",
              "      <td>-0.556404</td>\n",
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              "      <td>-0.510721</td>\n",
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              "      <td>NaN</td>\n",
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              "      <th>drdl380</th>\n",
              "      <td>0.975384</td>\n",
              "      <td>0.414024</td>\n",
              "      <td>0.631822</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.996738</td>\n",
              "      <td>0.989312</td>\n",
              "      <td>0.978070</td>\n",
              "      <td>0.980699</td>\n",
              "      <td>0.988619</td>\n",
              "      <td>0.980967</td>\n",
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              "      <td>-0.154865</td>\n",
              "      <td>-0.455782</td>\n",
              "      <td>-0.795784</td>\n",
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              "      <th>drdl390</th>\n",
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              "      <td>-0.453058</td>\n",
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              "      <td>-0.529198</td>\n",
              "      <td>-0.573945</td>\n",
              "      <td>-0.643271</td>\n",
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              "      <td>0.352219</td>\n",
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              "      <td>-0.091117</td>\n",
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              "      <td>0.742342</td>\n",
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              "      <th>drdl2450</th>\n",
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              "      <td>-0.504360</td>\n",
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              "      <td>-0.462433</td>\n",
              "      <td>-0.510003</td>\n",
              "      <td>-0.584948</td>\n",
              "      <td>...</td>\n",
              "      <td>0.656487</td>\n",
              "      <td>0.368156</td>\n",
              "      <td>0.649296</td>\n",
              "      <td>0.928359</td>\n",
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              "      <td>0.084804</td>\n",
              "      <td>0.785116</td>\n",
              "      <td>0.694688</td>\n",
              "      <td>NaN</td>\n",
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              "      <th>drdl2460</th>\n",
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              "      <td>0.187612</td>\n",
              "      <td>0.202508</td>\n",
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              "      <td>0.233613</td>\n",
              "      <td>0.217842</td>\n",
              "      <td>0.172240</td>\n",
              "      <td>0.105906</td>\n",
              "      <td>...</td>\n",
              "      <td>0.489465</td>\n",
              "      <td>0.644646</td>\n",
              "      <td>0.163821</td>\n",
              "      <td>-0.091117</td>\n",
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              "      <td>-0.135586</td>\n",
              "      <td>-0.558144</td>\n",
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              "      <td>NaN</td>\n",
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              "      <th>drdl2470</th>\n",
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              "      <td>-0.643568</td>\n",
              "      <td>-0.655634</td>\n",
              "      <td>-0.377445</td>\n",
              "      <td>-0.349424</td>\n",
              "      <td>-0.342573</td>\n",
              "      <td>-0.320386</td>\n",
              "      <td>-0.326580</td>\n",
              "      <td>-0.366184</td>\n",
              "      <td>-0.428253</td>\n",
              "      <td>...</td>\n",
              "      <td>0.492992</td>\n",
              "      <td>0.070767</td>\n",
              "      <td>0.424720</td>\n",
              "      <td>0.832894</td>\n",
              "      <td>0.785116</td>\n",
              "      <td>-0.135586</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.859750</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drdl2480</th>\n",
              "      <td>-0.383017</td>\n",
              "      <td>-0.415383</td>\n",
              "      <td>-0.510721</td>\n",
              "      <td>-0.443477</td>\n",
              "      <td>-0.425396</td>\n",
              "      <td>-0.421786</td>\n",
              "      <td>-0.413989</td>\n",
              "      <td>-0.412389</td>\n",
              "      <td>-0.423417</td>\n",
              "      <td>-0.442914</td>\n",
              "      <td>...</td>\n",
              "      <td>0.180146</td>\n",
              "      <td>-0.242412</td>\n",
              "      <td>0.310664</td>\n",
              "      <td>0.742342</td>\n",
              "      <td>0.694688</td>\n",
              "      <td>-0.558144</td>\n",
              "      <td>0.859750</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "<p>189 rows × 216 columns</p>\n",
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              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-00b3649f-a7f1-43fc-afb4-d18e8b0c6bae button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-00b3649f-a7f1-43fc-afb4-d18e8b0c6bae');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 139
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "corr_matrix.isna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8ioXHTw0_koy",
        "outputId": "510eecd4-f13a-463f-d593-c83616b81f8f"
      },
      "execution_count": 140,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Wavelength\n",
              "drdl350       0\n",
              "drdl360       0\n",
              "drdl370       0\n",
              "drdl380       0\n",
              "drdl390       0\n",
              "           ... \n",
              "drdl2460      0\n",
              "drdl2470      0\n",
              "drdl2480      0\n",
              "drdl2490    189\n",
              "drdl2500    189\n",
              "Length: 216, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 140
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\"There are still missing values so we drop columns with missing values\"\n",
        "corr_matrix = corr_matrix.dropna(axis = 1)\n",
        "corr_matrix"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "Dyp0heOaAwX4",
        "outputId": "8b2bbf71-4d7a-4b56-bd48-ae5e6c519e5d"
      },
      "execution_count": 141,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Wavelength   drdl350   drdl360   drdl370   drdl380   drdl390   drdl400  \\\n",
              "Wavelength                                                               \n",
              "drdl350     1.000000  0.482606  0.654041  0.975384  0.972916  0.969459   \n",
              "drdl360     0.482606  1.000000  0.955182  0.414024  0.354204  0.326929   \n",
              "drdl370     0.654041  0.955182  1.000000  0.631822  0.575833  0.546365   \n",
              "drdl380     0.975384  0.414024  0.631822  1.000000  0.996738  0.989312   \n",
              "drdl390     0.972916  0.354204  0.575833  0.996738  1.000000  0.997074   \n",
              "...              ...       ...       ...       ...       ...       ...   \n",
              "drdl2440   -0.603000 -0.752623 -0.777527 -0.561055 -0.538734 -0.542388   \n",
              "drdl2450   -0.550032 -0.782562 -0.786910 -0.504360 -0.477485 -0.476187   \n",
              "drdl2460    0.060116 -0.311966 -0.152462  0.187612  0.202508  0.211029   \n",
              "drdl2470   -0.383437 -0.643568 -0.655634 -0.377445 -0.349424 -0.342573   \n",
              "drdl2480   -0.383017 -0.415383 -0.510721 -0.443477 -0.425396 -0.421786   \n",
              "\n",
              "Wavelength   drdl410   drdl420   drdl430   drdl440  ...  drdl2390  drdl2400  \\\n",
              "Wavelength                                          ...                       \n",
              "drdl350     0.956460  0.960268  0.974061  0.978384  ... -0.364777 -0.683945   \n",
              "drdl360     0.277550  0.295224  0.378946  0.491154  ... -0.201472 -0.259803   \n",
              "drdl370     0.499914  0.515765  0.589710  0.681195  ... -0.339643 -0.433926   \n",
              "drdl380     0.978070  0.980699  0.988619  0.980967  ... -0.445843 -0.730055   \n",
              "drdl390     0.990386  0.991829  0.993280  0.977770  ... -0.434789 -0.739145   \n",
              "...              ...       ...       ...       ...  ...       ...       ...   \n",
              "drdl2440   -0.520842 -0.529198 -0.573945 -0.643271  ...  0.414212  0.697594   \n",
              "drdl2450   -0.452206 -0.462433 -0.510003 -0.584948  ...  0.348934  0.622189   \n",
              "drdl2460    0.233613  0.217842  0.172240  0.105906  ... -0.438591 -0.447097   \n",
              "drdl2470   -0.320386 -0.326580 -0.366184 -0.428253  ...  0.386213  0.578827   \n",
              "drdl2480   -0.413989 -0.412389 -0.423417 -0.442914  ...  0.555721  0.724434   \n",
              "\n",
              "Wavelength  drdl2410  drdl2420  drdl2430  drdl2440  drdl2450  drdl2460  \\\n",
              "Wavelength                                                               \n",
              "drdl350    -0.240908 -0.588634 -0.868091 -0.603000 -0.550032  0.060116   \n",
              "drdl360    -0.801476 -0.476166 -0.463064 -0.752623 -0.782562 -0.311966   \n",
              "drdl370    -0.701706 -0.452974 -0.556404 -0.777527 -0.786910 -0.152462   \n",
              "drdl380    -0.154865 -0.455782 -0.795784 -0.561055 -0.504360  0.187612   \n",
              "drdl390    -0.109846 -0.453058 -0.805610 -0.538734 -0.477485  0.202508   \n",
              "...              ...       ...       ...       ...       ...       ...   \n",
              "drdl2440    0.624582  0.352219  0.679845  1.000000  0.928359 -0.091117   \n",
              "drdl2450    0.656487  0.368156  0.649296  0.928359  1.000000  0.084804   \n",
              "drdl2460    0.489465  0.644646  0.163821 -0.091117  0.084804  1.000000   \n",
              "drdl2470    0.492992  0.070767  0.424720  0.832894  0.785116 -0.135586   \n",
              "drdl2480    0.180146 -0.242412  0.310664  0.742342  0.694688 -0.558144   \n",
              "\n",
              "Wavelength  drdl2470  drdl2480  \n",
              "Wavelength                      \n",
              "drdl350    -0.383437 -0.383017  \n",
              "drdl360    -0.643568 -0.415383  \n",
              "drdl370    -0.655634 -0.510721  \n",
              "drdl380    -0.377445 -0.443477  \n",
              "drdl390    -0.349424 -0.425396  \n",
              "...              ...       ...  \n",
              "drdl2440    0.832894  0.742342  \n",
              "drdl2450    0.785116  0.694688  \n",
              "drdl2460   -0.135586 -0.558144  \n",
              "drdl2470    1.000000  0.859750  \n",
              "drdl2480    0.859750  1.000000  \n",
              "\n",
              "[189 rows x 189 columns]"
            ],
            "text/html": [
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              "  <div id=\"df-385ac331-a0b2-4390-a5b7-75eacac273ce\">\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>Wavelength</th>\n",
              "      <th>drdl350</th>\n",
              "      <th>drdl360</th>\n",
              "      <th>drdl370</th>\n",
              "      <th>drdl380</th>\n",
              "      <th>drdl390</th>\n",
              "      <th>drdl400</th>\n",
              "      <th>drdl410</th>\n",
              "      <th>drdl420</th>\n",
              "      <th>drdl430</th>\n",
              "      <th>drdl440</th>\n",
              "      <th>...</th>\n",
              "      <th>drdl2390</th>\n",
              "      <th>drdl2400</th>\n",
              "      <th>drdl2410</th>\n",
              "      <th>drdl2420</th>\n",
              "      <th>drdl2430</th>\n",
              "      <th>drdl2440</th>\n",
              "      <th>drdl2450</th>\n",
              "      <th>drdl2460</th>\n",
              "      <th>drdl2470</th>\n",
              "      <th>drdl2480</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Wavelength</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>drdl350</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.482606</td>\n",
              "      <td>0.654041</td>\n",
              "      <td>0.975384</td>\n",
              "      <td>0.972916</td>\n",
              "      <td>0.969459</td>\n",
              "      <td>0.956460</td>\n",
              "      <td>0.960268</td>\n",
              "      <td>0.974061</td>\n",
              "      <td>0.978384</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.364777</td>\n",
              "      <td>-0.683945</td>\n",
              "      <td>-0.240908</td>\n",
              "      <td>-0.588634</td>\n",
              "      <td>-0.868091</td>\n",
              "      <td>-0.603000</td>\n",
              "      <td>-0.550032</td>\n",
              "      <td>0.060116</td>\n",
              "      <td>-0.383437</td>\n",
              "      <td>-0.383017</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drdl360</th>\n",
              "      <td>0.482606</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.955182</td>\n",
              "      <td>0.414024</td>\n",
              "      <td>0.354204</td>\n",
              "      <td>0.326929</td>\n",
              "      <td>0.277550</td>\n",
              "      <td>0.295224</td>\n",
              "      <td>0.378946</td>\n",
              "      <td>0.491154</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.201472</td>\n",
              "      <td>-0.259803</td>\n",
              "      <td>-0.801476</td>\n",
              "      <td>-0.476166</td>\n",
              "      <td>-0.463064</td>\n",
              "      <td>-0.752623</td>\n",
              "      <td>-0.782562</td>\n",
              "      <td>-0.311966</td>\n",
              "      <td>-0.643568</td>\n",
              "      <td>-0.415383</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drdl370</th>\n",
              "      <td>0.654041</td>\n",
              "      <td>0.955182</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.631822</td>\n",
              "      <td>0.575833</td>\n",
              "      <td>0.546365</td>\n",
              "      <td>0.499914</td>\n",
              "      <td>0.515765</td>\n",
              "      <td>0.589710</td>\n",
              "      <td>0.681195</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.339643</td>\n",
              "      <td>-0.433926</td>\n",
              "      <td>-0.701706</td>\n",
              "      <td>-0.452974</td>\n",
              "      <td>-0.556404</td>\n",
              "      <td>-0.777527</td>\n",
              "      <td>-0.786910</td>\n",
              "      <td>-0.152462</td>\n",
              "      <td>-0.655634</td>\n",
              "      <td>-0.510721</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drdl380</th>\n",
              "      <td>0.975384</td>\n",
              "      <td>0.414024</td>\n",
              "      <td>0.631822</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.996738</td>\n",
              "      <td>0.989312</td>\n",
              "      <td>0.978070</td>\n",
              "      <td>0.980699</td>\n",
              "      <td>0.988619</td>\n",
              "      <td>0.980967</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.445843</td>\n",
              "      <td>-0.730055</td>\n",
              "      <td>-0.154865</td>\n",
              "      <td>-0.455782</td>\n",
              "      <td>-0.795784</td>\n",
              "      <td>-0.561055</td>\n",
              "      <td>-0.504360</td>\n",
              "      <td>0.187612</td>\n",
              "      <td>-0.377445</td>\n",
              "      <td>-0.443477</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drdl390</th>\n",
              "      <td>0.972916</td>\n",
              "      <td>0.354204</td>\n",
              "      <td>0.575833</td>\n",
              "      <td>0.996738</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.997074</td>\n",
              "      <td>0.990386</td>\n",
              "      <td>0.991829</td>\n",
              "      <td>0.993280</td>\n",
              "      <td>0.977770</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.434789</td>\n",
              "      <td>-0.739145</td>\n",
              "      <td>-0.109846</td>\n",
              "      <td>-0.453058</td>\n",
              "      <td>-0.805610</td>\n",
              "      <td>-0.538734</td>\n",
              "      <td>-0.477485</td>\n",
              "      <td>0.202508</td>\n",
              "      <td>-0.349424</td>\n",
              "      <td>-0.425396</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drdl2440</th>\n",
              "      <td>-0.603000</td>\n",
              "      <td>-0.752623</td>\n",
              "      <td>-0.777527</td>\n",
              "      <td>-0.561055</td>\n",
              "      <td>-0.538734</td>\n",
              "      <td>-0.542388</td>\n",
              "      <td>-0.520842</td>\n",
              "      <td>-0.529198</td>\n",
              "      <td>-0.573945</td>\n",
              "      <td>-0.643271</td>\n",
              "      <td>...</td>\n",
              "      <td>0.414212</td>\n",
              "      <td>0.697594</td>\n",
              "      <td>0.624582</td>\n",
              "      <td>0.352219</td>\n",
              "      <td>0.679845</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.928359</td>\n",
              "      <td>-0.091117</td>\n",
              "      <td>0.832894</td>\n",
              "      <td>0.742342</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drdl2450</th>\n",
              "      <td>-0.550032</td>\n",
              "      <td>-0.782562</td>\n",
              "      <td>-0.786910</td>\n",
              "      <td>-0.504360</td>\n",
              "      <td>-0.477485</td>\n",
              "      <td>-0.476187</td>\n",
              "      <td>-0.452206</td>\n",
              "      <td>-0.462433</td>\n",
              "      <td>-0.510003</td>\n",
              "      <td>-0.584948</td>\n",
              "      <td>...</td>\n",
              "      <td>0.348934</td>\n",
              "      <td>0.622189</td>\n",
              "      <td>0.656487</td>\n",
              "      <td>0.368156</td>\n",
              "      <td>0.649296</td>\n",
              "      <td>0.928359</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.084804</td>\n",
              "      <td>0.785116</td>\n",
              "      <td>0.694688</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drdl2460</th>\n",
              "      <td>0.060116</td>\n",
              "      <td>-0.311966</td>\n",
              "      <td>-0.152462</td>\n",
              "      <td>0.187612</td>\n",
              "      <td>0.202508</td>\n",
              "      <td>0.211029</td>\n",
              "      <td>0.233613</td>\n",
              "      <td>0.217842</td>\n",
              "      <td>0.172240</td>\n",
              "      <td>0.105906</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.438591</td>\n",
              "      <td>-0.447097</td>\n",
              "      <td>0.489465</td>\n",
              "      <td>0.644646</td>\n",
              "      <td>0.163821</td>\n",
              "      <td>-0.091117</td>\n",
              "      <td>0.084804</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.135586</td>\n",
              "      <td>-0.558144</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drdl2470</th>\n",
              "      <td>-0.383437</td>\n",
              "      <td>-0.643568</td>\n",
              "      <td>-0.655634</td>\n",
              "      <td>-0.377445</td>\n",
              "      <td>-0.349424</td>\n",
              "      <td>-0.342573</td>\n",
              "      <td>-0.320386</td>\n",
              "      <td>-0.326580</td>\n",
              "      <td>-0.366184</td>\n",
              "      <td>-0.428253</td>\n",
              "      <td>...</td>\n",
              "      <td>0.386213</td>\n",
              "      <td>0.578827</td>\n",
              "      <td>0.492992</td>\n",
              "      <td>0.070767</td>\n",
              "      <td>0.424720</td>\n",
              "      <td>0.832894</td>\n",
              "      <td>0.785116</td>\n",
              "      <td>-0.135586</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.859750</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drdl2480</th>\n",
              "      <td>-0.383017</td>\n",
              "      <td>-0.415383</td>\n",
              "      <td>-0.510721</td>\n",
              "      <td>-0.443477</td>\n",
              "      <td>-0.425396</td>\n",
              "      <td>-0.421786</td>\n",
              "      <td>-0.413989</td>\n",
              "      <td>-0.412389</td>\n",
              "      <td>-0.423417</td>\n",
              "      <td>-0.442914</td>\n",
              "      <td>...</td>\n",
              "      <td>0.555721</td>\n",
              "      <td>0.724434</td>\n",
              "      <td>0.180146</td>\n",
              "      <td>-0.242412</td>\n",
              "      <td>0.310664</td>\n",
              "      <td>0.742342</td>\n",
              "      <td>0.694688</td>\n",
              "      <td>-0.558144</td>\n",
              "      <td>0.859750</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>189 rows × 189 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-385ac331-a0b2-4390-a5b7-75eacac273ce')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "\n",
              "\n",
              "\n",
              "    <div id=\"df-68f98355-8f17-44f0-b23e-123a91d4708b\">\n",
              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-68f98355-8f17-44f0-b23e-123a91d4708b')\"\n",
              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-68f98355-8f17-44f0-b23e-123a91d4708b button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-385ac331-a0b2-4390-a5b7-75eacac273ce button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-385ac331-a0b2-4390-a5b7-75eacac273ce');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 141
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\"\"\"Now our matrix is clean\"\"\"\n",
        "corr_matrix.isna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "O1YPt1yPBG0d",
        "outputId": "601949c6-1221-4a5c-9205-02822eb712fe"
      },
      "execution_count": 142,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Wavelength\n",
              "drdl350     0\n",
              "drdl360     0\n",
              "drdl370     0\n",
              "drdl380     0\n",
              "drdl390     0\n",
              "           ..\n",
              "drdl2440    0\n",
              "drdl2450    0\n",
              "drdl2460    0\n",
              "drdl2470    0\n",
              "drdl2480    0\n",
              "Length: 189, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 142
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "YZXrkydrBTvt"
      },
      "execution_count": 142,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "'''We can now plot the correlation matrix'''\n",
        "plt.figure(figsize=(6,4))\n",
        "sns.heatmap(corr_matrix, annot=True, cmap='Reds')\n",
        "plt.title('Correlation matrix',\n",
        "          fontsize=18)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 464
        },
        "id": "Kyvw0b9I8iCL",
        "outputId": "3ca7a205-3e63-43ed-ca1a-28a50a1c1fb4"
      },
      "execution_count": 143,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x400 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "'''We want to calculate the PCA of the correlation matrix'''\n",
        "from sklearn.decomposition import PCA\n",
        "\n",
        "\n",
        "pca = PCA(n_components=corr_matrix.shape[1])\n",
        "pca.fit(corr_matrix)\n",
        "# Reformat and view results\n",
        "loadings = pd.DataFrame(pca.components_.T,\n",
        "columns=['PC%s' % _ for _ in range(len(corr_matrix.columns))],\n",
        "index=corr_matrix.columns)\n",
        "print(loadings)\n",
        "\n",
        "plt.plot(pca.explained_variance_ratio_)\n",
        "plt.ylabel('Explained Variance')\n",
        "plt.xlabel('Components')\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "0hcbkZXfv2FG",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "a4516fef-8f63-485f-8fba-ae710ca63524"
      },
      "execution_count": 144,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                 PC0       PC1       PC2       PC3       PC4       PC5  \\\n",
            "Wavelength                                                               \n",
            "drdl350    -0.078250 -0.003056 -0.097227  0.097339 -0.063386  0.084885   \n",
            "drdl360    -0.083793  0.059683 -0.035474 -0.019160  0.006345  0.012118   \n",
            "drdl370    -0.080346  0.056241 -0.072281  0.023834 -0.024361  0.033536   \n",
            "drdl380    -0.063822 -0.000596 -0.114216  0.117247 -0.078054  0.087897   \n",
            "drdl390    -0.062676 -0.008405 -0.112505  0.118873 -0.076930  0.092488   \n",
            "...              ...       ...       ...       ...       ...       ...   \n",
            "drdl2440    0.091632 -0.016966  0.067127 -0.011088  0.024985 -0.017268   \n",
            "drdl2450    0.096030 -0.021703  0.043385 -0.001743  0.035819 -0.026184   \n",
            "drdl2460    0.054156 -0.015914 -0.096899  0.083129 -0.103638  0.005357   \n",
            "drdl2470    0.064960 -0.037320  0.059585 -0.002409  0.004804 -0.012168   \n",
            "drdl2480    0.032471 -0.021627  0.093578 -0.048255  0.075104 -0.023875   \n",
            "\n",
            "                 PC6       PC7       PC8       PC9  ...     PC179     PC180  \\\n",
            "Wavelength                                          ...                       \n",
            "drdl350    -0.033529  0.056476  0.052302 -0.017834  ...  0.000000 -0.000000   \n",
            "drdl360     0.181579  0.013853  0.004528  0.121383  ... -0.019809  0.016500   \n",
            "drdl370     0.162794  0.012402  0.017595  0.101551  ... -0.016209  0.004619   \n",
            "drdl380    -0.024359  0.034283  0.049377 -0.024158  ... -0.002021  0.008331   \n",
            "drdl390    -0.039789  0.030190  0.049609 -0.037798  ... -0.026130  0.009659   \n",
            "...              ...       ...       ...       ...  ...       ...       ...   \n",
            "drdl2440   -0.176050  0.128321  0.086922  0.015594  ...  0.065083 -0.026598   \n",
            "drdl2450   -0.140637  0.135241  0.121123 -0.122092  ...  0.087570 -0.040576   \n",
            "drdl2460    0.097407 -0.172593 -0.056628 -0.201061  ... -0.035015  0.042005   \n",
            "drdl2470   -0.192267  0.214546  0.086571  0.015701  ...  0.059858 -0.062523   \n",
            "drdl2480   -0.191183  0.261326  0.131582  0.031519  ... -0.161269  0.054732   \n",
            "\n",
            "               PC181     PC182     PC183     PC184     PC185     PC186  \\\n",
            "Wavelength                                                               \n",
            "drdl350    -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000   \n",
            "drdl360     0.018736 -0.015144 -0.017244  0.002631  0.004127  0.041521   \n",
            "drdl370    -0.011908 -0.002459 -0.009979  0.025236  0.020346  0.013975   \n",
            "drdl380    -0.027652 -0.012237  0.019505 -0.011759 -0.047523 -0.022884   \n",
            "drdl390     0.018759 -0.004226 -0.051517 -0.008572  0.009915 -0.002228   \n",
            "...              ...       ...       ...       ...       ...       ...   \n",
            "drdl2440    0.037609 -0.120535  0.037471 -0.158012  0.035473 -0.156084   \n",
            "drdl2450    0.052827  0.033880  0.168198  0.025147  0.068301  0.082514   \n",
            "drdl2460   -0.069411 -0.070025 -0.023174 -0.028037 -0.012215 -0.124804   \n",
            "drdl2470   -0.015717  0.056450  0.037447 -0.041753  0.054150  0.119042   \n",
            "drdl2480   -0.022879 -0.004289 -0.048754  0.071882 -0.101317 -0.154295   \n",
            "\n",
            "               PC187     PC188  \n",
            "Wavelength                      \n",
            "drdl350     0.000000  0.000000  \n",
            "drdl360     0.030615 -0.156536  \n",
            "drdl370     0.059511 -0.191382  \n",
            "drdl380     0.038699 -0.160254  \n",
            "drdl390    -0.186985 -0.339948  \n",
            "...              ...       ...  \n",
            "drdl2440   -0.005677  0.023348  \n",
            "drdl2450   -0.067687 -0.063049  \n",
            "drdl2460   -0.006844  0.021434  \n",
            "drdl2470   -0.035819 -0.014804  \n",
            "drdl2480    0.031410  0.014489  \n",
            "\n",
            "[189 rows x 189 columns]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\"\"\"\n",
        "CODE ENDS HERE\n",
        "\"\"\""
      ],
      "metadata": {
        "id": "tFBc2G7lao_g",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "2743a8d0-d2f5-4420-faa1-0460afbf798b"
      },
      "execution_count": 145,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'\\nCODE ENDS HERE\\n'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 145
        }
      ]
    }
  ]
}