JoshuaOsborneDATA_Final.ipynb

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      "name": "Copy of Copy of Final.ipynb",
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      "name": "python3",
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Wd4lY8qe4jFv",
        "colab_type": "text"
      },
      "source": [
        "# Final Exam\n",
        "\n",
        "## Part 1: Coding Problems\n",
        "\n",
        "For the questions in this section, make sure test your implementations and demonstrate they work."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9f_ozYyZ4q6L",
        "colab_type": "text"
      },
      "source": [
        "### 1. *Tensor Dot Product*\n",
        "\n",
        "a. Implement a function `tensor_product(A,B)` that takes two rank-3 tensors (meaning each has three indicies, for example tensor $A$ has elements $a_{ijk}$ and represented as `a[i][j][k]` in python), and multiplies them using the following rule:\n",
        "\n",
        "$c_{ij} = \\sum_{k} a_{ijk} b_{kji}$\n",
        "\n",
        "assume the tensors are lists of lists of lists. Ensure that the dimensions of the incoming tensors are corrent (by using `len()`). "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yaDMjpo-7O7X",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Answer Here\n",
        "def tensor_product(A,B):\n",
        "    tot=0\n",
        "    c=list()\n",
        "    if len(B)==len(A):\n",
        "        for i in range(len(A)):\n",
        "            for j in range (len(A[0])):\n",
        "                for k in range (len(A[0][0])):\n",
        "                    tot+=A[i][j][k]*B[k][j][i]\n",
        "            #print tot\n",
        "            c.append([tot])\n",
        "            tot=0\n",
        "    return c"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1gnU3xYj7pqd",
        "colab_type": "code",
        "outputId": "89dbe3b3-52df-4a90-a405-c0b0fa2f2c3a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "# Test Here\n",
        "A=[[[1,2],[4,5]],[[7,8],[10,11]]]\n",
        "B=[[[12,11],[9,8]],[[6,5],[3,2]]]\n",
        "C=tensor_product(A,B)\n",
        "print (C)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[75], [219]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ETLqa5Xp7qEd",
        "colab_type": "text"
      },
      "source": [
        "b. Modify the example so it can take tensors that have `numpy`-like interface *and* lists of lists of lists. Hint: for simplicity, just recast the list-baesd input as a `numpy` tensor."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PxwjXZIi85l4",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Answer Here\n",
        "def tensor_product2(A,B):\n",
        "    import numpy as np\n",
        "    A=np.array(A)\n",
        "    B=np.array(B)\n",
        "    tot=0\n",
        "    c=list()\n",
        "    if len(B)==len(A):\n",
        "        for i in range(len(A)):\n",
        "            for j in range (len(A[0])):\n",
        "                for k in range (len(A[0][0])):\n",
        "                    tot+=A[i][j][k]*B[k][j][i]\n",
        "            #print tot\n",
        "            c.append([tot])\n",
        "            tot=0\n",
        "    return c"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZziI0spg87gM",
        "colab_type": "code",
        "outputId": "d94a7576-68af-4a19-c80b-9f5a6de37e03",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "# Test Here\n",
        "A=[[[1,2],[4,5]],[[7,8],[10,11]]]\n",
        "B=[[[12,11],[9,8]],[[6,5],[3,2]]]\n",
        "C=tensor_product2(A,B)\n",
        "print (C)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[75], [219]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KoimsIbc89_J",
        "colab_type": "text"
      },
      "source": [
        "c. Now add additional optional argument to `tensor_product(A,B,axes)`, where `axes` is an interger $n$ indicating sum over the last $n$ axes of $A$ and the first $n$ axes of $B$ in order. The sizes of the corresponding axes must match. Note that the implementations above correspond to $n=1$, which should be the default. Note that $n=0$ corresponds to no sum at all."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qR_ctfI0-75S",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Answer Here\n",
        "def tensor_product(A,B,axes):\n",
        "  "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sCFsTTJ5--lI",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Test Here"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HO76b-Gh_Akx",
        "colab_type": "text"
      },
      "source": [
        "d. Now extend your implementation to arbitrary rank tensors. This is meant to be hard, so come back to this question if you cannot figure it out quickly."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6wzBsYzyBxnt",
        "colab_type": "text"
      },
      "source": [
        "### 2. 4-Vectors\n",
        "\n",
        "\n",
        " In relativistic mechanics, the Energy and Momentum of particles are different in every frame, but obey $m^2=E^2-\\vec{p}^2$ or $E^2=\\vec{p}^2$ for massless particles, where we set the speed of light $c=1$. It is therefore convenient to express the Energy and Momentum of a particle as a 4-vector, for example in Euclidean coordiates: $p= (E,p_{x},p_{y},p_{z}) = (E,\\vec{p})$.\n",
        "\n",
        "\n",
        "a. Implement a new `four_vector` class that holds the 4 components of a 4-vector implements interface:\n",
        "\n",
        "* Constructor takes the 0, 3, or 4 components as input. If 0 inputs, then the vector is $(0,0,0,0)$. If 3, then the vector is $(\\sqrt{p_x^2+p_y^2+p_z^2},p_x,p_y,p_z)$. If 4, then the vector is $E,p_x,p_y,p_z)$. Note that $E$ cannot be negative.\n",
        "\n",
        "* Adding two 4-vectors corresponds to adding the individual components.\n",
        "\n",
        "* Negating a 4-vector corresponds to just negating the last 3 components.\n",
        "\n",
        "* Multiplying two 4-vectors returns: $a \\cdot b = E^a E^b -p^a_x p^b_x-p^a_y p^b_y-p^a_z p^b_z$.\n",
        "\n",
        "* A function `mass()` returns the dot product of the vector with itself.\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eZlz0pBzAIf7",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Answer Here\n",
        "class four_vector:\n",
        "    def __init__(self,A):\n",
        "        self.A=A\n",
        "        self.vector=list()\n",
        "        map(float,self.A)\n",
        "        \n",
        "    def Constructor(self):\n",
        "        import copy\n",
        "        if self.A[0]<0:\n",
        "            return \"E cannot be less than 0\"\n",
        "\n",
        "        if self.A[0]==0 and self.A[1]==0:\n",
        "            self.vector=[0,0,0,0]\n",
        "\n",
        "        if A[0]==0 and A[1]!=0:\n",
        "            self.vector=[sqrt(A[1]**2+A[2]**2+A[3]**2),A[1],A[2],A[3]]\n",
        "\n",
        "        if A[0]!=0 and A[1]!=0:\n",
        "            self.vector=copy.deepcopy(self.A)\n",
        "        \n",
        "    def __add__(self,B):\n",
        "        Vect=list()\n",
        "        for i in range(len(self.A)):\n",
        "            Vect.append(float(self.A[i])+float(B[i]))\n",
        "        return Vect\n",
        "    \n",
        "    def Negating(self):\n",
        "        negate_vect=list()\n",
        "        neg_num=0\n",
        "        for i in range(len(self.A)):\n",
        "            if i>0:\n",
        "                negate_vect.append(self.A[i]*-1.0)\n",
        "            else:\n",
        "                negate_vect.append(self.A[i])\n",
        "        return negate_vect\n",
        "        \n",
        "    def __mul__(self,B):\n",
        "        mult_vect=list()\n",
        "        for i in range(len(self.A)):\n",
        "            mult_vect.append(float(self.A[i])*float(B[i]))\n",
        "        mult=mult_vect[0]-mult_vect[1]-mult_vect[2]-mult_vect[3]\n",
        "        return mult\n",
        "    \n",
        "    def mass(self,B):\n",
        "        dot_val=0\n",
        "        for i in range(len(self.A)):\n",
        "            dot_val+=float(self.A[i])*float(B[i])\n",
        "        return dot_val "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "P55eOwxZExb2",
        "colab_type": "code",
        "outputId": "dd5b4502-cc73-4053-d0ff-04d7ac791b0f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 84
        }
      },
      "source": [
        "# Test Here\n",
        "A=[5,10,15,20]\n",
        "B=[20.0,25.0,30.0,35.0]\n",
        "C=four_vector(A)\n",
        "hold=C+B\n",
        "print (hold)\n",
        "C.Constructor()\n",
        "hold=C.Negating()\n",
        "print (hold)\n",
        "hold=C*B\n",
        "print (hold)\n",
        "hold=C.mass(B)\n",
        "print (hold)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[25.0, 35.0, 45.0, 55.0]\n",
            "[5, -10.0, -15.0, -20.0]\n",
            "-1300.0\n",
            "1500.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5QKc29BvIINA",
        "colab_type": "text"
      },
      "source": [
        "b. Another coordinate system that is used defines the following:\n",
        "\n",
        "* $p_T = p \\sin{\\theta}$  where $ p =\\sqrt{p_x^2+p_y^2+p_z^2}$, and $\\sin{\\theta} = \\sqrt{p_x^2+p_y^2}/p_z$\n",
        "\n",
        "* $\\eta= - \\ln{\\tan{\\theta/2}}$\n",
        "\n",
        "* $\\tan{\\phi} = p_x/p_y$\n",
        "\n",
        "Implement a setter function that takes this representation as input to set the 4-vector components."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hMY3JRe5BveT",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def setter(theta,Px,Py,Pz):\n",
        "  import math\n",
        "  Pt=math.sqrt(Px**2+Py**2+Pz**2)*math.sqrt(Px**2+Py**2)/Pz\n",
        "  sin_theta=float(math.sqrt(Px**2+Py**2))/float(Pz)\n",
        "  gamma=-1.0*math.log(float(math.tan(theta))/2.0)\n",
        "  tan_phi=Px/Py\n",
        "  coor_vect=[Pt,sin_theta,gamma,tan_phi]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "G7SGngv1FIJw",
        "colab_type": "text"
      },
      "source": [
        "## Part 2: Data Science\n",
        "\n",
        "We will work here with the other dataset from the paper used in lab 9. You can refer back to that lab for whatever you need. \n",
        "\n",
        "a. Read the description of the dataset (here)[https://archive.ics.uci.edu/ml/datasets/HIGGS] and  download and unzip the dataset (https://archive.ics.uci.edu/ml/machine-learning-databases/00280/HIGGS.csv.gz) using `wget` and `gunzip`. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4aRJO8ZQFYfF",
        "colab_type": "code",
        "outputId": "ee2db5c8-f212-43ae-bff0-5d65b85496ec",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        }
      },
      "source": [
        "!wget https://archive.ics.uci.edu/ml/machine-learning-databases/00280/HIGGS.csv.gz\n",
        "!gunzip HIGGS.csv.gz"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2019-05-08 17:39:08--  https://archive.ics.uci.edu/ml/machine-learning-databases/00280/HIGGS.csv.gz\n",
            "Resolving archive.ics.uci.edu (archive.ics.uci.edu)... 128.195.10.252\n",
            "Connecting to archive.ics.uci.edu (archive.ics.uci.edu)|128.195.10.252|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 2816407858 (2.6G) [application/x-httpd-php]\n",
            "Saving to: ‘HIGGS.csv.gz’\n",
            "\n",
            "HIGGS.csv.gz        100%[===================>]   2.62G  44.0MB/s    in 62s     \n",
            "\n",
            "2019-05-08 17:40:15 (43.2 MB/s) - ‘HIGGS.csv.gz’ saved [2816407858/2816407858]\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YO13-1siiwAL",
        "colab_type": "code",
        "outputId": "3e3f4ab6-9db1-4a3a-e048-69ef41864aac",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 121
        }
      },
      "source": [
        "filename=\"HIGGS.csv\"\n",
        "!head -5  \"HIGGS.csv\""
      ],
      "execution_count": 2,
      "outputs": [
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          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "71XDvU2BGaYV",
        "colab_type": "text"
      },
      "source": [
        "b. Load the dataset into a tensor. Compare distributions of signal and background for each variable."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DvHpEpWkGm1e",
        "colab_type": "code",
        "outputId": "14b195bf-bfa2-4991-960a-c586aad5402b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1918
        }
      },
      "source": [
        "import pandas as pd\n",
        "VarNames=['Signal','lepton_pT', 'lepton_eta', 'lepton_phi', 'missing_energy_magnitude', 'missing_energy_phi', \n",
        "          'jet_1_pt', 'jet_1_eta', 'jet_1_phi', 'jet_1_b-tag', 'jet_2_pt', 'jet_2_eta', 'jet_2_phi', 'jet_2_b-tag', 'jet_3_pt', 'jet_3_eta', 'jet_3_phi', 'jet_3_b-tag', 'jet_4_pt', \n",
        "          'jet_4_eta', 'jet_4_phi', 'jet_4_b-tag', 'm_jj', 'm_jjj', 'm_lv', 'm_jlv', 'm_bb', 'm_wbb', 'm_wwbb']\n",
        "df = pd.read_csv(filename, dtype='float64', names=VarNames,nrows=1000000)\n",
        "df"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Signal</th>\n",
              "      <th>lepton_pT</th>\n",
              "      <th>lepton_eta</th>\n",
              "      <th>lepton_phi</th>\n",
              "      <th>missing_energy_magnitude</th>\n",
              "      <th>missing_energy_phi</th>\n",
              "      <th>jet_1_pt</th>\n",
              "      <th>jet_1_eta</th>\n",
              "      <th>jet_1_phi</th>\n",
              "      <th>jet_1_b-tag</th>\n",
              "      <th>...</th>\n",
              "      <th>jet_4_eta</th>\n",
              "      <th>jet_4_phi</th>\n",
              "      <th>jet_4_b-tag</th>\n",
              "      <th>m_jj</th>\n",
              "      <th>m_jjj</th>\n",
              "      <th>m_lv</th>\n",
              "      <th>m_jlv</th>\n",
              "      <th>m_bb</th>\n",
              "      <th>m_wbb</th>\n",
              "      <th>m_wwbb</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.869293</td>\n",
              "      <td>-0.635082</td>\n",
              "      <td>0.225690</td>\n",
              "      <td>0.327470</td>\n",
              "      <td>-0.689993</td>\n",
              "      <td>0.754202</td>\n",
              "      <td>-0.248573</td>\n",
              "      <td>-1.092064</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.010455</td>\n",
              "      <td>-0.045767</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>1.353760</td>\n",
              "      <td>0.979563</td>\n",
              "      <td>0.978076</td>\n",
              "      <td>0.920005</td>\n",
              "      <td>0.721657</td>\n",
              "      <td>0.988751</td>\n",
              "      <td>0.876678</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.907542</td>\n",
              "      <td>0.329147</td>\n",
              "      <td>0.359412</td>\n",
              "      <td>1.497970</td>\n",
              "      <td>-0.313010</td>\n",
              "      <td>1.095531</td>\n",
              "      <td>-0.557525</td>\n",
              "      <td>-1.588230</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>-1.138930</td>\n",
              "      <td>-0.000819</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.302220</td>\n",
              "      <td>0.833048</td>\n",
              "      <td>0.985700</td>\n",
              "      <td>0.978098</td>\n",
              "      <td>0.779732</td>\n",
              "      <td>0.992356</td>\n",
              "      <td>0.798343</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.798835</td>\n",
              "      <td>1.470639</td>\n",
              "      <td>-1.635975</td>\n",
              "      <td>0.453773</td>\n",
              "      <td>0.425629</td>\n",
              "      <td>1.104875</td>\n",
              "      <td>1.282322</td>\n",
              "      <td>1.381664</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>1.128848</td>\n",
              "      <td>0.900461</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.909753</td>\n",
              "      <td>1.108330</td>\n",
              "      <td>0.985692</td>\n",
              "      <td>0.951331</td>\n",
              "      <td>0.803252</td>\n",
              "      <td>0.865924</td>\n",
              "      <td>0.780118</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1.344385</td>\n",
              "      <td>-0.876626</td>\n",
              "      <td>0.935913</td>\n",
              "      <td>1.992050</td>\n",
              "      <td>0.882454</td>\n",
              "      <td>1.786066</td>\n",
              "      <td>-1.646778</td>\n",
              "      <td>-0.942383</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.678379</td>\n",
              "      <td>-1.360356</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.946652</td>\n",
              "      <td>1.028704</td>\n",
              "      <td>0.998656</td>\n",
              "      <td>0.728281</td>\n",
              "      <td>0.869200</td>\n",
              "      <td>1.026736</td>\n",
              "      <td>0.957904</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1.0</td>\n",
              "      <td>1.105009</td>\n",
              "      <td>0.321356</td>\n",
              "      <td>1.522401</td>\n",
              "      <td>0.882808</td>\n",
              "      <td>-1.205349</td>\n",
              "      <td>0.681466</td>\n",
              "      <td>-1.070464</td>\n",
              "      <td>-0.921871</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.373566</td>\n",
              "      <td>0.113041</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.755856</td>\n",
              "      <td>1.361057</td>\n",
              "      <td>0.986610</td>\n",
              "      <td>0.838085</td>\n",
              "      <td>1.133295</td>\n",
              "      <td>0.872245</td>\n",
              "      <td>0.808487</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1.595839</td>\n",
              "      <td>-0.607811</td>\n",
              "      <td>0.007075</td>\n",
              "      <td>1.818450</td>\n",
              "      <td>-0.111906</td>\n",
              "      <td>0.847550</td>\n",
              "      <td>-0.566437</td>\n",
              "      <td>1.581239</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.654227</td>\n",
              "      <td>-1.274345</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>0.823761</td>\n",
              "      <td>0.938191</td>\n",
              "      <td>0.971758</td>\n",
              "      <td>0.789176</td>\n",
              "      <td>0.430553</td>\n",
              "      <td>0.961357</td>\n",
              "      <td>0.957818</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.409391</td>\n",
              "      <td>-1.884684</td>\n",
              "      <td>-1.027292</td>\n",
              "      <td>1.672452</td>\n",
              "      <td>-1.604598</td>\n",
              "      <td>1.338015</td>\n",
              "      <td>0.055427</td>\n",
              "      <td>0.013466</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>0.069496</td>\n",
              "      <td>1.377130</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>0.869418</td>\n",
              "      <td>1.222083</td>\n",
              "      <td>1.000627</td>\n",
              "      <td>0.545045</td>\n",
              "      <td>0.698653</td>\n",
              "      <td>0.977314</td>\n",
              "      <td>0.828786</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.933895</td>\n",
              "      <td>0.629130</td>\n",
              "      <td>0.527535</td>\n",
              "      <td>0.238033</td>\n",
              "      <td>-0.966569</td>\n",
              "      <td>0.547811</td>\n",
              "      <td>-0.059439</td>\n",
              "      <td>-1.706866</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>1.291248</td>\n",
              "      <td>-1.467454</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.901837</td>\n",
              "      <td>1.083671</td>\n",
              "      <td>0.979696</td>\n",
              "      <td>0.783300</td>\n",
              "      <td>0.849195</td>\n",
              "      <td>0.894356</td>\n",
              "      <td>0.774879</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>1.0</td>\n",
              "      <td>1.405144</td>\n",
              "      <td>0.536603</td>\n",
              "      <td>0.689554</td>\n",
              "      <td>1.179567</td>\n",
              "      <td>-0.110061</td>\n",
              "      <td>3.202405</td>\n",
              "      <td>-1.526960</td>\n",
              "      <td>-1.576033</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.151202</td>\n",
              "      <td>1.163489</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.667071</td>\n",
              "      <td>4.039273</td>\n",
              "      <td>1.175828</td>\n",
              "      <td>1.045352</td>\n",
              "      <td>1.542972</td>\n",
              "      <td>3.534827</td>\n",
              "      <td>2.740754</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>1.0</td>\n",
              "      <td>1.176566</td>\n",
              "      <td>0.104161</td>\n",
              "      <td>1.397002</td>\n",
              "      <td>0.479721</td>\n",
              "      <td>0.265513</td>\n",
              "      <td>1.135563</td>\n",
              "      <td>1.534831</td>\n",
              "      <td>-0.253291</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.268541</td>\n",
              "      <td>0.530334</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.833175</td>\n",
              "      <td>0.773968</td>\n",
              "      <td>0.985750</td>\n",
              "      <td>1.103696</td>\n",
              "      <td>0.849140</td>\n",
              "      <td>0.937104</td>\n",
              "      <td>0.812364</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.945974</td>\n",
              "      <td>1.111244</td>\n",
              "      <td>1.218337</td>\n",
              "      <td>0.907639</td>\n",
              "      <td>0.821537</td>\n",
              "      <td>1.153243</td>\n",
              "      <td>-0.365420</td>\n",
              "      <td>-1.566055</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.451018</td>\n",
              "      <td>0.063653</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>0.829024</td>\n",
              "      <td>0.980648</td>\n",
              "      <td>0.994360</td>\n",
              "      <td>0.908248</td>\n",
              "      <td>0.775879</td>\n",
              "      <td>0.783311</td>\n",
              "      <td>0.725122</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.739357</td>\n",
              "      <td>-0.178290</td>\n",
              "      <td>0.829934</td>\n",
              "      <td>0.504539</td>\n",
              "      <td>-0.130217</td>\n",
              "      <td>0.961051</td>\n",
              "      <td>-0.355518</td>\n",
              "      <td>-1.717399</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>0.774065</td>\n",
              "      <td>0.398820</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>0.944536</td>\n",
              "      <td>1.026261</td>\n",
              "      <td>0.982197</td>\n",
              "      <td>0.542115</td>\n",
              "      <td>1.250979</td>\n",
              "      <td>0.830045</td>\n",
              "      <td>0.761308</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>1.0</td>\n",
              "      <td>1.384098</td>\n",
              "      <td>0.116822</td>\n",
              "      <td>-1.179879</td>\n",
              "      <td>0.762913</td>\n",
              "      <td>-0.079782</td>\n",
              "      <td>1.019863</td>\n",
              "      <td>0.877318</td>\n",
              "      <td>1.276887</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>0.846521</td>\n",
              "      <td>0.504809</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>0.959325</td>\n",
              "      <td>0.807376</td>\n",
              "      <td>1.191814</td>\n",
              "      <td>1.221210</td>\n",
              "      <td>0.861141</td>\n",
              "      <td>0.929341</td>\n",
              "      <td>0.838302</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>1.0</td>\n",
              "      <td>1.383549</td>\n",
              "      <td>0.889179</td>\n",
              "      <td>0.618532</td>\n",
              "      <td>1.081547</td>\n",
              "      <td>0.344606</td>\n",
              "      <td>0.956379</td>\n",
              "      <td>0.854543</td>\n",
              "      <td>-1.129207</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>-1.636126</td>\n",
              "      <td>1.144067</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.522238</td>\n",
              "      <td>0.737639</td>\n",
              "      <td>0.986200</td>\n",
              "      <td>1.349616</td>\n",
              "      <td>0.812788</td>\n",
              "      <td>0.953406</td>\n",
              "      <td>0.779723</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>1.0</td>\n",
              "      <td>1.343653</td>\n",
              "      <td>0.838533</td>\n",
              "      <td>-1.061139</td>\n",
              "      <td>2.472015</td>\n",
              "      <td>-0.572632</td>\n",
              "      <td>1.512710</td>\n",
              "      <td>1.143690</td>\n",
              "      <td>0.855562</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>2.396405</td>\n",
              "      <td>0.757294</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.934020</td>\n",
              "      <td>0.844707</td>\n",
              "      <td>1.077844</td>\n",
              "      <td>1.400184</td>\n",
              "      <td>0.947775</td>\n",
              "      <td>1.007614</td>\n",
              "      <td>0.901017</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.547014</td>\n",
              "      <td>-0.349709</td>\n",
              "      <td>-0.646657</td>\n",
              "      <td>2.040462</td>\n",
              "      <td>0.276457</td>\n",
              "      <td>0.544697</td>\n",
              "      <td>0.838699</td>\n",
              "      <td>1.728703</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.629242</td>\n",
              "      <td>1.570795</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>0.689434</td>\n",
              "      <td>0.867230</td>\n",
              "      <td>1.082488</td>\n",
              "      <td>0.664142</td>\n",
              "      <td>0.354115</td>\n",
              "      <td>0.579945</td>\n",
              "      <td>0.817273</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>1.0</td>\n",
              "      <td>1.484204</td>\n",
              "      <td>1.699521</td>\n",
              "      <td>-1.059474</td>\n",
              "      <td>2.700196</td>\n",
              "      <td>-1.055964</td>\n",
              "      <td>2.409453</td>\n",
              "      <td>0.457461</td>\n",
              "      <td>0.344982</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>2.182369</td>\n",
              "      <td>1.043073</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.653626</td>\n",
              "      <td>0.993576</td>\n",
              "      <td>0.983322</td>\n",
              "      <td>0.741380</td>\n",
              "      <td>0.163382</td>\n",
              "      <td>0.592324</td>\n",
              "      <td>0.745138</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1.057976</td>\n",
              "      <td>-0.160759</td>\n",
              "      <td>-0.194997</td>\n",
              "      <td>2.705023</td>\n",
              "      <td>-0.751477</td>\n",
              "      <td>1.909919</td>\n",
              "      <td>-1.031845</td>\n",
              "      <td>0.864986</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.714190</td>\n",
              "      <td>1.505315</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>0.954494</td>\n",
              "      <td>0.651039</td>\n",
              "      <td>1.124950</td>\n",
              "      <td>0.894001</td>\n",
              "      <td>0.672173</td>\n",
              "      <td>1.182358</td>\n",
              "      <td>1.316304</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.675304</td>\n",
              "      <td>1.120984</td>\n",
              "      <td>-0.280446</td>\n",
              "      <td>1.539555</td>\n",
              "      <td>0.734518</td>\n",
              "      <td>0.614684</td>\n",
              "      <td>-0.507023</td>\n",
              "      <td>0.794581</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>-1.145593</td>\n",
              "      <td>-1.374784</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.906940</td>\n",
              "      <td>0.898339</td>\n",
              "      <td>1.119651</td>\n",
              "      <td>1.269073</td>\n",
              "      <td>1.088766</td>\n",
              "      <td>1.015413</td>\n",
              "      <td>0.914636</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.642728</td>\n",
              "      <td>-1.429840</td>\n",
              "      <td>1.519072</td>\n",
              "      <td>0.940999</td>\n",
              "      <td>0.887227</td>\n",
              "      <td>1.615127</td>\n",
              "      <td>-1.336836</td>\n",
              "      <td>-0.266596</td>\n",
              "      <td>1.086538</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.346915</td>\n",
              "      <td>-1.182785</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>0.921090</td>\n",
              "      <td>1.373362</td>\n",
              "      <td>0.984917</td>\n",
              "      <td>1.422878</td>\n",
              "      <td>1.546551</td>\n",
              "      <td>1.782586</td>\n",
              "      <td>1.438174</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>1.0</td>\n",
              "      <td>1.102447</td>\n",
              "      <td>0.426544</td>\n",
              "      <td>1.717157</td>\n",
              "      <td>0.934302</td>\n",
              "      <td>0.775743</td>\n",
              "      <td>1.279386</td>\n",
              "      <td>-0.249563</td>\n",
              "      <td>-0.926306</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>1.207966</td>\n",
              "      <td>-1.150600</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.708635</td>\n",
              "      <td>0.521908</td>\n",
              "      <td>1.054313</td>\n",
              "      <td>1.272654</td>\n",
              "      <td>0.834634</td>\n",
              "      <td>0.934980</td>\n",
              "      <td>0.865305</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>1.0</td>\n",
              "      <td>1.330110</td>\n",
              "      <td>0.201557</td>\n",
              "      <td>1.173393</td>\n",
              "      <td>0.135309</td>\n",
              "      <td>-1.083159</td>\n",
              "      <td>0.728461</td>\n",
              "      <td>1.109032</td>\n",
              "      <td>-0.539903</td>\n",
              "      <td>1.086538</td>\n",
              "      <td>...</td>\n",
              "      <td>1.007255</td>\n",
              "      <td>0.054775</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>0.782073</td>\n",
              "      <td>0.672103</td>\n",
              "      <td>0.990002</td>\n",
              "      <td>0.734279</td>\n",
              "      <td>0.379074</td>\n",
              "      <td>0.764760</td>\n",
              "      <td>0.642924</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1.289848</td>\n",
              "      <td>-1.423023</td>\n",
              "      <td>-0.687162</td>\n",
              "      <td>0.131103</td>\n",
              "      <td>-1.135935</td>\n",
              "      <td>0.821350</td>\n",
              "      <td>0.296053</td>\n",
              "      <td>0.167582</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>1.105529</td>\n",
              "      <td>0.727328</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.006643</td>\n",
              "      <td>0.867914</td>\n",
              "      <td>0.999090</td>\n",
              "      <td>1.109608</td>\n",
              "      <td>1.125094</td>\n",
              "      <td>0.882899</td>\n",
              "      <td>0.859396</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>1.0</td>\n",
              "      <td>1.047910</td>\n",
              "      <td>-1.119144</td>\n",
              "      <td>-0.956825</td>\n",
              "      <td>0.995669</td>\n",
              "      <td>-1.550324</td>\n",
              "      <td>0.733316</td>\n",
              "      <td>0.283180</td>\n",
              "      <td>0.918761</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.325262</td>\n",
              "      <td>1.217316</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.873131</td>\n",
              "      <td>0.873374</td>\n",
              "      <td>0.976218</td>\n",
              "      <td>1.373094</td>\n",
              "      <td>0.887989</td>\n",
              "      <td>1.206525</td>\n",
              "      <td>0.999058</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.488268</td>\n",
              "      <td>1.697574</td>\n",
              "      <td>0.791094</td>\n",
              "      <td>0.893614</td>\n",
              "      <td>-0.709291</td>\n",
              "      <td>1.562727</td>\n",
              "      <td>-0.076273</td>\n",
              "      <td>1.738682</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.077080</td>\n",
              "      <td>0.284508</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.674505</td>\n",
              "      <td>1.413676</td>\n",
              "      <td>0.987923</td>\n",
              "      <td>1.333243</td>\n",
              "      <td>2.004407</td>\n",
              "      <td>1.550748</td>\n",
              "      <td>1.216709</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1.413196</td>\n",
              "      <td>-0.852277</td>\n",
              "      <td>0.310029</td>\n",
              "      <td>1.128018</td>\n",
              "      <td>-1.509792</td>\n",
              "      <td>0.819518</td>\n",
              "      <td>1.152602</td>\n",
              "      <td>-1.670277</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>0.959784</td>\n",
              "      <td>-0.632312</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.889586</td>\n",
              "      <td>0.938041</td>\n",
              "      <td>1.745206</td>\n",
              "      <td>0.973918</td>\n",
              "      <td>0.677132</td>\n",
              "      <td>1.135700</td>\n",
              "      <td>0.972836</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.769919</td>\n",
              "      <td>-0.449054</td>\n",
              "      <td>-0.985677</td>\n",
              "      <td>0.965722</td>\n",
              "      <td>-1.300960</td>\n",
              "      <td>0.738721</td>\n",
              "      <td>-1.032835</td>\n",
              "      <td>0.874965</td>\n",
              "      <td>1.086538</td>\n",
              "      <td>...</td>\n",
              "      <td>0.610832</td>\n",
              "      <td>0.115815</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.048223</td>\n",
              "      <td>1.105509</td>\n",
              "      <td>0.993322</td>\n",
              "      <td>1.131816</td>\n",
              "      <td>0.891868</td>\n",
              "      <td>0.973950</td>\n",
              "      <td>0.951233</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>0.0</td>\n",
              "      <td>2.468061</td>\n",
              "      <td>0.664192</td>\n",
              "      <td>1.023581</td>\n",
              "      <td>0.317203</td>\n",
              "      <td>1.407240</td>\n",
              "      <td>0.996228</td>\n",
              "      <td>-0.452561</td>\n",
              "      <td>-0.499988</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.471839</td>\n",
              "      <td>1.463697</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>1.005921</td>\n",
              "      <td>0.795294</td>\n",
              "      <td>0.996260</td>\n",
              "      <td>0.945199</td>\n",
              "      <td>0.321730</td>\n",
              "      <td>0.735165</td>\n",
              "      <td>1.470303</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>1.0</td>\n",
              "      <td>1.014419</td>\n",
              "      <td>0.012607</td>\n",
              "      <td>-0.484635</td>\n",
              "      <td>0.695256</td>\n",
              "      <td>1.701171</td>\n",
              "      <td>0.597096</td>\n",
              "      <td>0.076222</td>\n",
              "      <td>0.142635</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>1.294579</td>\n",
              "      <td>0.263977</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.575766</td>\n",
              "      <td>1.067265</td>\n",
              "      <td>1.071992</td>\n",
              "      <td>0.805769</td>\n",
              "      <td>1.130206</td>\n",
              "      <td>0.838251</td>\n",
              "      <td>0.752052</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1.250867</td>\n",
              "      <td>-0.750010</td>\n",
              "      <td>1.090164</td>\n",
              "      <td>0.461849</td>\n",
              "      <td>-0.380657</td>\n",
              "      <td>0.677161</td>\n",
              "      <td>0.339623</td>\n",
              "      <td>-0.711208</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.907405</td>\n",
              "      <td>0.278959</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>0.848267</td>\n",
              "      <td>0.842342</td>\n",
              "      <td>1.021281</td>\n",
              "      <td>0.665904</td>\n",
              "      <td>0.410987</td>\n",
              "      <td>0.606533</td>\n",
              "      <td>0.638353</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>999970</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.972144</td>\n",
              "      <td>0.603806</td>\n",
              "      <td>-0.970141</td>\n",
              "      <td>0.347800</td>\n",
              "      <td>0.369888</td>\n",
              "      <td>0.872559</td>\n",
              "      <td>0.394086</td>\n",
              "      <td>-0.448986</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>0.498400</td>\n",
              "      <td>0.687375</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.118305</td>\n",
              "      <td>0.909820</td>\n",
              "      <td>0.992795</td>\n",
              "      <td>0.684203</td>\n",
              "      <td>1.674751</td>\n",
              "      <td>0.933095</td>\n",
              "      <td>0.812892</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999971</th>\n",
              "      <td>1.0</td>\n",
              "      <td>1.025400</td>\n",
              "      <td>-0.935064</td>\n",
              "      <td>-1.325807</td>\n",
              "      <td>0.836362</td>\n",
              "      <td>0.718500</td>\n",
              "      <td>0.974426</td>\n",
              "      <td>0.635702</td>\n",
              "      <td>0.811766</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.138709</td>\n",
              "      <td>-1.378668</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.889428</td>\n",
              "      <td>1.139301</td>\n",
              "      <td>1.235817</td>\n",
              "      <td>1.318207</td>\n",
              "      <td>1.407812</td>\n",
              "      <td>1.143519</td>\n",
              "      <td>0.988023</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999972</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.371874</td>\n",
              "      <td>-0.819162</td>\n",
              "      <td>-0.497397</td>\n",
              "      <td>0.590504</td>\n",
              "      <td>-1.607357</td>\n",
              "      <td>1.134464</td>\n",
              "      <td>0.640653</td>\n",
              "      <td>0.421486</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.496735</td>\n",
              "      <td>1.080807</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.911457</td>\n",
              "      <td>0.692983</td>\n",
              "      <td>0.984037</td>\n",
              "      <td>1.180888</td>\n",
              "      <td>0.660106</td>\n",
              "      <td>0.867804</td>\n",
              "      <td>1.209023</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999973</th>\n",
              "      <td>0.0</td>\n",
              "      <td>2.427799</td>\n",
              "      <td>-0.101347</td>\n",
              "      <td>1.734913</td>\n",
              "      <td>0.593191</td>\n",
              "      <td>0.459086</td>\n",
              "      <td>1.043956</td>\n",
              "      <td>0.234659</td>\n",
              "      <td>-0.337002</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>0.227733</td>\n",
              "      <td>0.449872</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.282662</td>\n",
              "      <td>0.981594</td>\n",
              "      <td>1.516869</td>\n",
              "      <td>1.445414</td>\n",
              "      <td>0.999012</td>\n",
              "      <td>1.058491</td>\n",
              "      <td>0.995545</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999974</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.909555</td>\n",
              "      <td>-2.302516</td>\n",
              "      <td>-0.055172</td>\n",
              "      <td>0.719235</td>\n",
              "      <td>-1.179486</td>\n",
              "      <td>0.676061</td>\n",
              "      <td>1.033775</td>\n",
              "      <td>0.037858</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-1.714411</td>\n",
              "      <td>1.230633</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.936048</td>\n",
              "      <td>1.090561</td>\n",
              "      <td>0.989161</td>\n",
              "      <td>0.996433</td>\n",
              "      <td>0.768051</td>\n",
              "      <td>0.950206</td>\n",
              "      <td>0.813717</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999975</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1.556126</td>\n",
              "      <td>-0.060440</td>\n",
              "      <td>0.969204</td>\n",
              "      <td>2.321195</td>\n",
              "      <td>0.183499</td>\n",
              "      <td>0.847000</td>\n",
              "      <td>0.242581</td>\n",
              "      <td>-1.011125</td>\n",
              "      <td>1.086538</td>\n",
              "      <td>...</td>\n",
              "      <td>0.034518</td>\n",
              "      <td>-1.316518</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.039129</td>\n",
              "      <td>1.048839</td>\n",
              "      <td>1.711062</td>\n",
              "      <td>1.367664</td>\n",
              "      <td>1.106266</td>\n",
              "      <td>1.195386</td>\n",
              "      <td>1.204696</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999976</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.674022</td>\n",
              "      <td>0.230776</td>\n",
              "      <td>0.949784</td>\n",
              "      <td>0.858732</td>\n",
              "      <td>-1.556945</td>\n",
              "      <td>1.360550</td>\n",
              "      <td>-0.348586</td>\n",
              "      <td>-0.294315</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>0.249386</td>\n",
              "      <td>0.689039</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>1.095725</td>\n",
              "      <td>0.638144</td>\n",
              "      <td>0.987005</td>\n",
              "      <td>1.394441</td>\n",
              "      <td>0.638116</td>\n",
              "      <td>1.026588</td>\n",
              "      <td>0.936353</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999977</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1.842719</td>\n",
              "      <td>0.575561</td>\n",
              "      <td>-1.658169</td>\n",
              "      <td>0.557681</td>\n",
              "      <td>0.569032</td>\n",
              "      <td>1.458753</td>\n",
              "      <td>-0.125785</td>\n",
              "      <td>0.072230</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.562528</td>\n",
              "      <td>0.037018</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>2.410676</td>\n",
              "      <td>1.288915</td>\n",
              "      <td>1.272565</td>\n",
              "      <td>0.805529</td>\n",
              "      <td>0.383582</td>\n",
              "      <td>0.830770</td>\n",
              "      <td>0.898366</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999978</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.277808</td>\n",
              "      <td>-1.708395</td>\n",
              "      <td>-1.142703</td>\n",
              "      <td>1.253832</td>\n",
              "      <td>-0.505068</td>\n",
              "      <td>0.811182</td>\n",
              "      <td>0.250503</td>\n",
              "      <td>1.251940</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.954788</td>\n",
              "      <td>-0.662277</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>0.942015</td>\n",
              "      <td>0.918240</td>\n",
              "      <td>0.978276</td>\n",
              "      <td>0.676237</td>\n",
              "      <td>0.789154</td>\n",
              "      <td>0.887203</td>\n",
              "      <td>0.813731</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999979</th>\n",
              "      <td>1.0</td>\n",
              "      <td>1.184984</td>\n",
              "      <td>0.440180</td>\n",
              "      <td>-0.636115</td>\n",
              "      <td>1.401829</td>\n",
              "      <td>-1.101669</td>\n",
              "      <td>0.926699</td>\n",
              "      <td>1.185280</td>\n",
              "      <td>0.563406</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>1.356208</td>\n",
              "      <td>1.629615</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.126785</td>\n",
              "      <td>1.143347</td>\n",
              "      <td>0.996909</td>\n",
              "      <td>0.726498</td>\n",
              "      <td>0.194710</td>\n",
              "      <td>0.829596</td>\n",
              "      <td>0.820687</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999980</th>\n",
              "      <td>1.0</td>\n",
              "      <td>1.037112</td>\n",
              "      <td>-0.177316</td>\n",
              "      <td>-0.931301</td>\n",
              "      <td>0.876163</td>\n",
              "      <td>1.542672</td>\n",
              "      <td>1.027467</td>\n",
              "      <td>0.747598</td>\n",
              "      <td>0.171463</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.316101</td>\n",
              "      <td>-1.600078</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>3.209756</td>\n",
              "      <td>2.091912</td>\n",
              "      <td>1.044219</td>\n",
              "      <td>0.812480</td>\n",
              "      <td>0.805250</td>\n",
              "      <td>1.425254</td>\n",
              "      <td>1.148914</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999981</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.453131</td>\n",
              "      <td>2.126120</td>\n",
              "      <td>0.720627</td>\n",
              "      <td>0.405490</td>\n",
              "      <td>0.166030</td>\n",
              "      <td>0.821259</td>\n",
              "      <td>0.929800</td>\n",
              "      <td>0.257945</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.217828</td>\n",
              "      <td>1.506425</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.969039</td>\n",
              "      <td>0.730988</td>\n",
              "      <td>0.983730</td>\n",
              "      <td>1.405588</td>\n",
              "      <td>1.901048</td>\n",
              "      <td>1.208726</td>\n",
              "      <td>1.014675</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999982</th>\n",
              "      <td>1.0</td>\n",
              "      <td>1.717723</td>\n",
              "      <td>0.320382</td>\n",
              "      <td>-1.293625</td>\n",
              "      <td>1.172017</td>\n",
              "      <td>-0.209732</td>\n",
              "      <td>0.818785</td>\n",
              "      <td>-1.155624</td>\n",
              "      <td>-1.587675</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.838192</td>\n",
              "      <td>1.301662</td>\n",
              "      <td>1.550981</td>\n",
              "      <td>2.066406</td>\n",
              "      <td>1.427082</td>\n",
              "      <td>1.629804</td>\n",
              "      <td>1.009671</td>\n",
              "      <td>1.013850</td>\n",
              "      <td>1.048530</td>\n",
              "      <td>1.066861</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999983</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.626989</td>\n",
              "      <td>-1.107457</td>\n",
              "      <td>-0.635005</td>\n",
              "      <td>0.836632</td>\n",
              "      <td>0.240183</td>\n",
              "      <td>0.668916</td>\n",
              "      <td>0.266346</td>\n",
              "      <td>-0.208387</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.260302</td>\n",
              "      <td>1.530841</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>0.991399</td>\n",
              "      <td>1.209010</td>\n",
              "      <td>0.992457</td>\n",
              "      <td>0.613820</td>\n",
              "      <td>0.699125</td>\n",
              "      <td>0.718217</td>\n",
              "      <td>0.720967</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999984</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1.507263</td>\n",
              "      <td>0.352523</td>\n",
              "      <td>0.968650</td>\n",
              "      <td>0.909163</td>\n",
              "      <td>-1.254628</td>\n",
              "      <td>0.684764</td>\n",
              "      <td>-1.018972</td>\n",
              "      <td>-1.365925</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>1.794273</td>\n",
              "      <td>0.217364</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.841261</td>\n",
              "      <td>1.051393</td>\n",
              "      <td>1.472985</td>\n",
              "      <td>1.207435</td>\n",
              "      <td>0.964927</td>\n",
              "      <td>0.976137</td>\n",
              "      <td>1.051808</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999985</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.697814</td>\n",
              "      <td>-0.825006</td>\n",
              "      <td>0.114718</td>\n",
              "      <td>0.442524</td>\n",
              "      <td>-1.173004</td>\n",
              "      <td>0.907003</td>\n",
              "      <td>0.829787</td>\n",
              "      <td>-0.225572</td>\n",
              "      <td>1.086538</td>\n",
              "      <td>...</td>\n",
              "      <td>0.693281</td>\n",
              "      <td>0.918773</td>\n",
              "      <td>1.550981</td>\n",
              "      <td>0.964603</td>\n",
              "      <td>1.089843</td>\n",
              "      <td>0.983592</td>\n",
              "      <td>1.540274</td>\n",
              "      <td>0.812345</td>\n",
              "      <td>1.111762</td>\n",
              "      <td>1.048665</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999986</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.743383</td>\n",
              "      <td>0.819054</td>\n",
              "      <td>0.223471</td>\n",
              "      <td>1.581001</td>\n",
              "      <td>-0.374280</td>\n",
              "      <td>1.007038</td>\n",
              "      <td>-0.905096</td>\n",
              "      <td>1.319574</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.864843</td>\n",
              "      <td>1.498101</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>1.524122</td>\n",
              "      <td>0.986536</td>\n",
              "      <td>0.990786</td>\n",
              "      <td>1.159479</td>\n",
              "      <td>0.592767</td>\n",
              "      <td>0.769826</td>\n",
              "      <td>1.106610</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999987</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.710258</td>\n",
              "      <td>-1.760990</td>\n",
              "      <td>-0.903003</td>\n",
              "      <td>0.375496</td>\n",
              "      <td>-1.572463</td>\n",
              "      <td>0.900041</td>\n",
              "      <td>-0.620900</td>\n",
              "      <td>1.413264</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.530136</td>\n",
              "      <td>0.709016</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.840141</td>\n",
              "      <td>1.111352</td>\n",
              "      <td>0.988545</td>\n",
              "      <td>1.038713</td>\n",
              "      <td>1.503057</td>\n",
              "      <td>0.933002</td>\n",
              "      <td>0.870590</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999988</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.377731</td>\n",
              "      <td>-1.634374</td>\n",
              "      <td>-0.844188</td>\n",
              "      <td>1.176915</td>\n",
              "      <td>-0.611327</td>\n",
              "      <td>1.464067</td>\n",
              "      <td>0.459441</td>\n",
              "      <td>0.785156</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>1.270428</td>\n",
              "      <td>-1.556240</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.187943</td>\n",
              "      <td>1.057999</td>\n",
              "      <td>0.985908</td>\n",
              "      <td>0.606848</td>\n",
              "      <td>0.932036</td>\n",
              "      <td>0.957529</td>\n",
              "      <td>0.868758</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999989</th>\n",
              "      <td>1.0</td>\n",
              "      <td>1.623474</td>\n",
              "      <td>-0.376980</td>\n",
              "      <td>1.051324</td>\n",
              "      <td>0.514070</td>\n",
              "      <td>-0.039491</td>\n",
              "      <td>0.959494</td>\n",
              "      <td>-0.410971</td>\n",
              "      <td>-1.074324</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.347748</td>\n",
              "      <td>-0.382599</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.948664</td>\n",
              "      <td>1.029377</td>\n",
              "      <td>1.052701</td>\n",
              "      <td>0.773623</td>\n",
              "      <td>0.318335</td>\n",
              "      <td>0.895034</td>\n",
              "      <td>0.838218</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999990</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.540060</td>\n",
              "      <td>-1.258422</td>\n",
              "      <td>0.654043</td>\n",
              "      <td>1.873201</td>\n",
              "      <td>-0.153034</td>\n",
              "      <td>1.487610</td>\n",
              "      <td>-1.688367</td>\n",
              "      <td>-0.526044</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.097812</td>\n",
              "      <td>-1.377559</td>\n",
              "      <td>1.550981</td>\n",
              "      <td>0.890813</td>\n",
              "      <td>0.719385</td>\n",
              "      <td>0.988270</td>\n",
              "      <td>1.077554</td>\n",
              "      <td>0.755790</td>\n",
              "      <td>0.860523</td>\n",
              "      <td>0.913627</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999991</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.420189</td>\n",
              "      <td>1.009951</td>\n",
              "      <td>-1.327472</td>\n",
              "      <td>0.652160</td>\n",
              "      <td>0.910160</td>\n",
              "      <td>1.208941</td>\n",
              "      <td>1.094179</td>\n",
              "      <td>1.508616</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>0.690783</td>\n",
              "      <td>-0.904774</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.023774</td>\n",
              "      <td>1.040296</td>\n",
              "      <td>0.986017</td>\n",
              "      <td>0.720094</td>\n",
              "      <td>1.482483</td>\n",
              "      <td>0.876079</td>\n",
              "      <td>0.767670</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999992</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.816770</td>\n",
              "      <td>0.387585</td>\n",
              "      <td>0.944236</td>\n",
              "      <td>0.647740</td>\n",
              "      <td>-0.353303</td>\n",
              "      <td>1.317678</td>\n",
              "      <td>1.042687</td>\n",
              "      <td>-0.861444</td>\n",
              "      <td>1.086538</td>\n",
              "      <td>...</td>\n",
              "      <td>0.375975</td>\n",
              "      <td>0.037018</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>0.905958</td>\n",
              "      <td>0.844373</td>\n",
              "      <td>0.985637</td>\n",
              "      <td>1.013631</td>\n",
              "      <td>0.937575</td>\n",
              "      <td>0.974468</td>\n",
              "      <td>0.829529</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999993</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.742651</td>\n",
              "      <td>0.242464</td>\n",
              "      <td>0.022056</td>\n",
              "      <td>2.772573</td>\n",
              "      <td>-0.689066</td>\n",
              "      <td>1.708108</td>\n",
              "      <td>-0.055478</td>\n",
              "      <td>0.570613</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.448520</td>\n",
              "      <td>-1.261027</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>0.607600</td>\n",
              "      <td>0.733236</td>\n",
              "      <td>1.187110</td>\n",
              "      <td>0.943022</td>\n",
              "      <td>0.315795</td>\n",
              "      <td>0.615857</td>\n",
              "      <td>0.772179</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999994</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1.289299</td>\n",
              "      <td>-1.108431</td>\n",
              "      <td>0.970869</td>\n",
              "      <td>0.418467</td>\n",
              "      <td>-0.236384</td>\n",
              "      <td>1.439424</td>\n",
              "      <td>1.415013</td>\n",
              "      <td>0.384343</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.196174</td>\n",
              "      <td>-0.649514</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>3.715858</td>\n",
              "      <td>2.295703</td>\n",
              "      <td>0.990350</td>\n",
              "      <td>0.826123</td>\n",
              "      <td>0.602524</td>\n",
              "      <td>1.549889</td>\n",
              "      <td>1.489945</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999995</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.514256</td>\n",
              "      <td>0.441154</td>\n",
              "      <td>0.641281</td>\n",
              "      <td>0.376795</td>\n",
              "      <td>0.840085</td>\n",
              "      <td>0.812464</td>\n",
              "      <td>-0.038644</td>\n",
              "      <td>-0.329241</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.032852</td>\n",
              "      <td>1.471465</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.813464</td>\n",
              "      <td>0.723074</td>\n",
              "      <td>0.984661</td>\n",
              "      <td>0.734838</td>\n",
              "      <td>0.226974</td>\n",
              "      <td>0.817835</td>\n",
              "      <td>0.750583</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999996</th>\n",
              "      <td>1.0</td>\n",
              "      <td>1.586689</td>\n",
              "      <td>0.798600</td>\n",
              "      <td>-1.038389</td>\n",
              "      <td>0.186234</td>\n",
              "      <td>-1.465364</td>\n",
              "      <td>1.328488</td>\n",
              "      <td>0.356457</td>\n",
              "      <td>0.846692</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>0.155277</td>\n",
              "      <td>-0.170067</td>\n",
              "      <td>3.101961</td>\n",
              "      <td>2.318721</td>\n",
              "      <td>1.348919</td>\n",
              "      <td>0.997061</td>\n",
              "      <td>1.345282</td>\n",
              "      <td>0.984395</td>\n",
              "      <td>1.167846</td>\n",
              "      <td>1.042671</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999997</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1.833751</td>\n",
              "      <td>0.194740</td>\n",
              "      <td>1.489664</td>\n",
              "      <td>0.453500</td>\n",
              "      <td>0.077691</td>\n",
              "      <td>1.112570</td>\n",
              "      <td>1.208055</td>\n",
              "      <td>0.155386</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>0.112803</td>\n",
              "      <td>0.599699</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.033291</td>\n",
              "      <td>0.878243</td>\n",
              "      <td>1.207249</td>\n",
              "      <td>0.980557</td>\n",
              "      <td>1.977671</td>\n",
              "      <td>1.186537</td>\n",
              "      <td>1.025073</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999998</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.617107</td>\n",
              "      <td>-1.137650</td>\n",
              "      <td>-0.610591</td>\n",
              "      <td>0.847996</td>\n",
              "      <td>-1.121593</td>\n",
              "      <td>0.908286</td>\n",
              "      <td>2.751823</td>\n",
              "      <td>1.306269</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.941462</td>\n",
              "      <td>1.292229</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.240858</td>\n",
              "      <td>1.850254</td>\n",
              "      <td>0.984099</td>\n",
              "      <td>1.180130</td>\n",
              "      <td>0.514119</td>\n",
              "      <td>1.742259</td>\n",
              "      <td>2.751391</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999999</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1.680206</td>\n",
              "      <td>0.841455</td>\n",
              "      <td>1.303231</td>\n",
              "      <td>0.469627</td>\n",
              "      <td>0.386419</td>\n",
              "      <td>0.935218</td>\n",
              "      <td>1.242713</td>\n",
              "      <td>-0.854237</td>\n",
              "      <td>2.173076</td>\n",
              "      <td>...</td>\n",
              "      <td>0.647476</td>\n",
              "      <td>-0.071848</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.333295</td>\n",
              "      <td>0.758725</td>\n",
              "      <td>0.988097</td>\n",
              "      <td>0.623328</td>\n",
              "      <td>0.271381</td>\n",
              "      <td>0.723280</td>\n",
              "      <td>0.601052</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1000000 rows × 29 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        Signal  lepton_pT  lepton_eta  lepton_phi  missing_energy_magnitude  \\\n",
              "0          1.0   0.869293   -0.635082    0.225690                  0.327470   \n",
              "1          1.0   0.907542    0.329147    0.359412                  1.497970   \n",
              "2          1.0   0.798835    1.470639   -1.635975                  0.453773   \n",
              "3          0.0   1.344385   -0.876626    0.935913                  1.992050   \n",
              "4          1.0   1.105009    0.321356    1.522401                  0.882808   \n",
              "5          0.0   1.595839   -0.607811    0.007075                  1.818450   \n",
              "6          1.0   0.409391   -1.884684   -1.027292                  1.672452   \n",
              "7          1.0   0.933895    0.629130    0.527535                  0.238033   \n",
              "8          1.0   1.405144    0.536603    0.689554                  1.179567   \n",
              "9          1.0   1.176566    0.104161    1.397002                  0.479721   \n",
              "10         1.0   0.945974    1.111244    1.218337                  0.907639   \n",
              "11         0.0   0.739357   -0.178290    0.829934                  0.504539   \n",
              "12         1.0   1.384098    0.116822   -1.179879                  0.762913   \n",
              "13         1.0   1.383549    0.889179    0.618532                  1.081547   \n",
              "14         1.0   1.343653    0.838533   -1.061139                  2.472015   \n",
              "15         0.0   0.547014   -0.349709   -0.646657                  2.040462   \n",
              "16         1.0   1.484204    1.699521   -1.059474                  2.700196   \n",
              "17         0.0   1.057976   -0.160759   -0.194997                  2.705023   \n",
              "18         0.0   0.675304    1.120984   -0.280446                  1.539555   \n",
              "19         1.0   0.642728   -1.429840    1.519072                  0.940999   \n",
              "20         1.0   1.102447    0.426544    1.717157                  0.934302   \n",
              "21         1.0   1.330110    0.201557    1.173393                  0.135309   \n",
              "22         0.0   1.289848   -1.423023   -0.687162                  0.131103   \n",
              "23         1.0   1.047910   -1.119144   -0.956825                  0.995669   \n",
              "24         0.0   0.488268    1.697574    0.791094                  0.893614   \n",
              "25         0.0   1.413196   -0.852277    0.310029                  1.128018   \n",
              "26         1.0   0.769919   -0.449054   -0.985677                  0.965722   \n",
              "27         0.0   2.468061    0.664192    1.023581                  0.317203   \n",
              "28         1.0   1.014419    0.012607   -0.484635                  0.695256   \n",
              "29         0.0   1.250867   -0.750010    1.090164                  0.461849   \n",
              "...        ...        ...         ...         ...                       ...   \n",
              "999970     1.0   0.972144    0.603806   -0.970141                  0.347800   \n",
              "999971     1.0   1.025400   -0.935064   -1.325807                  0.836362   \n",
              "999972     1.0   0.371874   -0.819162   -0.497397                  0.590504   \n",
              "999973     0.0   2.427799   -0.101347    1.734913                  0.593191   \n",
              "999974     1.0   0.909555   -2.302516   -0.055172                  0.719235   \n",
              "999975     0.0   1.556126   -0.060440    0.969204                  2.321195   \n",
              "999976     1.0   0.674022    0.230776    0.949784                  0.858732   \n",
              "999977     0.0   1.842719    0.575561   -1.658169                  0.557681   \n",
              "999978     1.0   0.277808   -1.708395   -1.142703                  1.253832   \n",
              "999979     1.0   1.184984    0.440180   -0.636115                  1.401829   \n",
              "999980     1.0   1.037112   -0.177316   -0.931301                  0.876163   \n",
              "999981     1.0   0.453131    2.126120    0.720627                  0.405490   \n",
              "999982     1.0   1.717723    0.320382   -1.293625                  1.172017   \n",
              "999983     0.0   0.626989   -1.107457   -0.635005                  0.836632   \n",
              "999984     0.0   1.507263    0.352523    0.968650                  0.909163   \n",
              "999985     1.0   0.697814   -0.825006    0.114718                  0.442524   \n",
              "999986     1.0   0.743383    0.819054    0.223471                  1.581001   \n",
              "999987     1.0   0.710258   -1.760990   -0.903003                  0.375496   \n",
              "999988     1.0   0.377731   -1.634374   -0.844188                  1.176915   \n",
              "999989     1.0   1.623474   -0.376980    1.051324                  0.514070   \n",
              "999990     0.0   0.540060   -1.258422    0.654043                  1.873201   \n",
              "999991     0.0   0.420189    1.009951   -1.327472                  0.652160   \n",
              "999992     1.0   0.816770    0.387585    0.944236                  0.647740   \n",
              "999993     1.0   0.742651    0.242464    0.022056                  2.772573   \n",
              "999994     0.0   1.289299   -1.108431    0.970869                  0.418467   \n",
              "999995     1.0   0.514256    0.441154    0.641281                  0.376795   \n",
              "999996     1.0   1.586689    0.798600   -1.038389                  0.186234   \n",
              "999997     0.0   1.833751    0.194740    1.489664                  0.453500   \n",
              "999998     0.0   0.617107   -1.137650   -0.610591                  0.847996   \n",
              "999999     0.0   1.680206    0.841455    1.303231                  0.469627   \n",
              "\n",
              "        missing_energy_phi  jet_1_pt  jet_1_eta  jet_1_phi  jet_1_b-tag  ...  \\\n",
              "0                -0.689993  0.754202  -0.248573  -1.092064     0.000000  ...   \n",
              "1                -0.313010  1.095531  -0.557525  -1.588230     2.173076  ...   \n",
              "2                 0.425629  1.104875   1.282322   1.381664     0.000000  ...   \n",
              "3                 0.882454  1.786066  -1.646778  -0.942383     0.000000  ...   \n",
              "4                -1.205349  0.681466  -1.070464  -0.921871     0.000000  ...   \n",
              "5                -0.111906  0.847550  -0.566437   1.581239     2.173076  ...   \n",
              "6                -1.604598  1.338015   0.055427   0.013466     2.173076  ...   \n",
              "7                -0.966569  0.547811  -0.059439  -1.706866     2.173076  ...   \n",
              "8                -0.110061  3.202405  -1.526960  -1.576033     0.000000  ...   \n",
              "9                 0.265513  1.135563   1.534831  -0.253291     0.000000  ...   \n",
              "10                0.821537  1.153243  -0.365420  -1.566055     0.000000  ...   \n",
              "11               -0.130217  0.961051  -0.355518  -1.717399     2.173076  ...   \n",
              "12               -0.079782  1.019863   0.877318   1.276887     2.173076  ...   \n",
              "13                0.344606  0.956379   0.854543  -1.129207     2.173076  ...   \n",
              "14               -0.572632  1.512710   1.143690   0.855562     0.000000  ...   \n",
              "15                0.276457  0.544697   0.838699   1.728703     0.000000  ...   \n",
              "16               -1.055964  2.409453   0.457461   0.344982     0.000000  ...   \n",
              "17               -0.751477  1.909919  -1.031845   0.864986     0.000000  ...   \n",
              "18                0.734518  0.614684  -0.507023   0.794581     2.173076  ...   \n",
              "19                0.887227  1.615127  -1.336836  -0.266596     1.086538  ...   \n",
              "20                0.775743  1.279386  -0.249563  -0.926306     2.173076  ...   \n",
              "21               -1.083159  0.728461   1.109032  -0.539903     1.086538  ...   \n",
              "22               -1.135935  0.821350   0.296053   0.167582     2.173076  ...   \n",
              "23               -1.550324  0.733316   0.283180   0.918761     2.173076  ...   \n",
              "24               -0.709291  1.562727  -0.076273   1.738682     2.173076  ...   \n",
              "25               -1.509792  0.819518   1.152602  -1.670277     2.173076  ...   \n",
              "26               -1.300960  0.738721  -1.032835   0.874965     1.086538  ...   \n",
              "27                1.407240  0.996228  -0.452561  -0.499988     0.000000  ...   \n",
              "28                1.701171  0.597096   0.076222   0.142635     2.173076  ...   \n",
              "29               -0.380657  0.677161   0.339623  -0.711208     0.000000  ...   \n",
              "...                    ...       ...        ...        ...          ...  ...   \n",
              "999970            0.369888  0.872559   0.394086  -0.448986     2.173076  ...   \n",
              "999971            0.718500  0.974426   0.635702   0.811766     2.173076  ...   \n",
              "999972           -1.607357  1.134464   0.640653   0.421486     0.000000  ...   \n",
              "999973            0.459086  1.043956   0.234659  -0.337002     2.173076  ...   \n",
              "999974           -1.179486  0.676061   1.033775   0.037858     0.000000  ...   \n",
              "999975            0.183499  0.847000   0.242581  -1.011125     1.086538  ...   \n",
              "999976           -1.556945  1.360550  -0.348586  -0.294315     2.173076  ...   \n",
              "999977            0.569032  1.458753  -0.125785   0.072230     0.000000  ...   \n",
              "999978           -0.505068  0.811182   0.250503   1.251940     0.000000  ...   \n",
              "999979           -1.101669  0.926699   1.185280   0.563406     2.173076  ...   \n",
              "999980            1.542672  1.027467   0.747598   0.171463     0.000000  ...   \n",
              "999981            0.166030  0.821259   0.929800   0.257945     0.000000  ...   \n",
              "999982           -0.209732  0.818785  -1.155624  -1.587675     0.000000  ...   \n",
              "999983            0.240183  0.668916   0.266346  -0.208387     2.173076  ...   \n",
              "999984           -1.254628  0.684764  -1.018972  -1.365925     2.173076  ...   \n",
              "999985           -1.173004  0.907003   0.829787  -0.225572     1.086538  ...   \n",
              "999986           -0.374280  1.007038  -0.905096   1.319574     0.000000  ...   \n",
              "999987           -1.572463  0.900041  -0.620900   1.413264     2.173076  ...   \n",
              "999988           -0.611327  1.464067   0.459441   0.785156     2.173076  ...   \n",
              "999989           -0.039491  0.959494  -0.410971  -1.074324     0.000000  ...   \n",
              "999990           -0.153034  1.487610  -1.688367  -0.526044     0.000000  ...   \n",
              "999991            0.910160  1.208941   1.094179   1.508616     2.173076  ...   \n",
              "999992           -0.353303  1.317678   1.042687  -0.861444     1.086538  ...   \n",
              "999993           -0.689066  1.708108  -0.055478   0.570613     0.000000  ...   \n",
              "999994           -0.236384  1.439424   1.415013   0.384343     0.000000  ...   \n",
              "999995            0.840085  0.812464  -0.038644  -0.329241     0.000000  ...   \n",
              "999996           -1.465364  1.328488   0.356457   0.846692     2.173076  ...   \n",
              "999997            0.077691  1.112570   1.208055   0.155386     2.173076  ...   \n",
              "999998           -1.121593  0.908286   2.751823   1.306269     0.000000  ...   \n",
              "999999            0.386419  0.935218   1.242713  -0.854237     2.173076  ...   \n",
              "\n",
              "        jet_4_eta  jet_4_phi  jet_4_b-tag      m_jj     m_jjj      m_lv  \\\n",
              "0       -0.010455  -0.045767     3.101961  1.353760  0.979563  0.978076   \n",
              "1       -1.138930  -0.000819     0.000000  0.302220  0.833048  0.985700   \n",
              "2        1.128848   0.900461     0.000000  0.909753  1.108330  0.985692   \n",
              "3       -0.678379  -1.360356     0.000000  0.946652  1.028704  0.998656   \n",
              "4       -0.373566   0.113041     0.000000  0.755856  1.361057  0.986610   \n",
              "5       -0.654227  -1.274345     3.101961  0.823761  0.938191  0.971758   \n",
              "6        0.069496   1.377130     3.101961  0.869418  1.222083  1.000627   \n",
              "7        1.291248  -1.467454     0.000000  0.901837  1.083671  0.979696   \n",
              "8       -0.151202   1.163489     0.000000  1.667071  4.039273  1.175828   \n",
              "9        0.268541   0.530334     0.000000  0.833175  0.773968  0.985750   \n",
              "10      -0.451018   0.063653     3.101961  0.829024  0.980648  0.994360   \n",
              "11       0.774065   0.398820     3.101961  0.944536  1.026261  0.982197   \n",
              "12       0.846521   0.504809     3.101961  0.959325  0.807376  1.191814   \n",
              "13      -1.636126   1.144067     0.000000  0.522238  0.737639  0.986200   \n",
              "14       2.396405   0.757294     0.000000  0.934020  0.844707  1.077844   \n",
              "15      -0.629242   1.570795     3.101961  0.689434  0.867230  1.082488   \n",
              "16       2.182369   1.043073     0.000000  1.653626  0.993576  0.983322   \n",
              "17      -0.714190   1.505315     3.101961  0.954494  0.651039  1.124950   \n",
              "18      -1.145593  -1.374784     0.000000  0.906940  0.898339  1.119651   \n",
              "19      -0.346915  -1.182785     3.101961  0.921090  1.373362  0.984917   \n",
              "20       1.207966  -1.150600     0.000000  0.708635  0.521908  1.054313   \n",
              "21       1.007255   0.054775     3.101961  0.782073  0.672103  0.990002   \n",
              "22       1.105529   0.727328     0.000000  1.006643  0.867914  0.999090   \n",
              "23      -0.325262   1.217316     0.000000  0.873131  0.873374  0.976218   \n",
              "24      -0.077080   0.284508     0.000000  1.674505  1.413676  0.987923   \n",
              "25       0.959784  -0.632312     0.000000  0.889586  0.938041  1.745206   \n",
              "26       0.610832   0.115815     0.000000  1.048223  1.105509  0.993322   \n",
              "27      -0.471839   1.463697     3.101961  1.005921  0.795294  0.996260   \n",
              "28       1.294579   0.263977     0.000000  1.575766  1.067265  1.071992   \n",
              "29      -0.907405   0.278959     3.101961  0.848267  0.842342  1.021281   \n",
              "...           ...        ...          ...       ...       ...       ...   \n",
              "999970   0.498400   0.687375     0.000000  1.118305  0.909820  0.992795   \n",
              "999971  -0.138709  -1.378668     0.000000  0.889428  1.139301  1.235817   \n",
              "999972   0.496735   1.080807     0.000000  0.911457  0.692983  0.984037   \n",
              "999973   0.227733   0.449872     0.000000  1.282662  0.981594  1.516869   \n",
              "999974  -1.714411   1.230633     0.000000  0.936048  1.090561  0.989161   \n",
              "999975   0.034518  -1.316518     0.000000  1.039129  1.048839  1.711062   \n",
              "999976   0.249386   0.689039     3.101961  1.095725  0.638144  0.987005   \n",
              "999977   0.562528   0.037018     3.101961  2.410676  1.288915  1.272565   \n",
              "999978   0.954788  -0.662277     3.101961  0.942015  0.918240  0.978276   \n",
              "999979   1.356208   1.629615     0.000000  1.126785  1.143347  0.996909   \n",
              "999980  -0.316101  -1.600078     3.101961  3.209756  2.091912  1.044219   \n",
              "999981  -0.217828   1.506425     0.000000  0.969039  0.730988  0.983730   \n",
              "999982   0.838192   1.301662     1.550981  2.066406  1.427082  1.629804   \n",
              "999983  -0.260302   1.530841     3.101961  0.991399  1.209010  0.992457   \n",
              "999984   1.794273   0.217364     0.000000  0.841261  1.051393  1.472985   \n",
              "999985   0.693281   0.918773     1.550981  0.964603  1.089843  0.983592   \n",
              "999986   0.864843   1.498101     3.101961  1.524122  0.986536  0.990786   \n",
              "999987  -0.530136   0.709016     0.000000  0.840141  1.111352  0.988545   \n",
              "999988   1.270428  -1.556240     0.000000  0.187943  1.057999  0.985908   \n",
              "999989  -0.347748  -0.382599     0.000000  0.948664  1.029377  1.052701   \n",
              "999990   0.097812  -1.377559     1.550981  0.890813  0.719385  0.988270   \n",
              "999991   0.690783  -0.904774     0.000000  1.023774  1.040296  0.986017   \n",
              "999992   0.375975   0.037018     3.101961  0.905958  0.844373  0.985637   \n",
              "999993  -0.448520  -1.261027     3.101961  0.607600  0.733236  1.187110   \n",
              "999994  -0.196174  -0.649514     3.101961  3.715858  2.295703  0.990350   \n",
              "999995   0.032852   1.471465     0.000000  0.813464  0.723074  0.984661   \n",
              "999996   0.155277  -0.170067     3.101961  2.318721  1.348919  0.997061   \n",
              "999997   0.112803   0.599699     0.000000  1.033291  0.878243  1.207249   \n",
              "999998   0.941462   1.292229     0.000000  1.240858  1.850254  0.984099   \n",
              "999999   0.647476  -0.071848     0.000000  0.333295  0.758725  0.988097   \n",
              "\n",
              "           m_jlv      m_bb     m_wbb    m_wwbb  \n",
              "0       0.920005  0.721657  0.988751  0.876678  \n",
              "1       0.978098  0.779732  0.992356  0.798343  \n",
              "2       0.951331  0.803252  0.865924  0.780118  \n",
              "3       0.728281  0.869200  1.026736  0.957904  \n",
              "4       0.838085  1.133295  0.872245  0.808487  \n",
              "5       0.789176  0.430553  0.961357  0.957818  \n",
              "6       0.545045  0.698653  0.977314  0.828786  \n",
              "7       0.783300  0.849195  0.894356  0.774879  \n",
              "8       1.045352  1.542972  3.534827  2.740754  \n",
              "9       1.103696  0.849140  0.937104  0.812364  \n",
              "10      0.908248  0.775879  0.783311  0.725122  \n",
              "11      0.542115  1.250979  0.830045  0.761308  \n",
              "12      1.221210  0.861141  0.929341  0.838302  \n",
              "13      1.349616  0.812788  0.953406  0.779723  \n",
              "14      1.400184  0.947775  1.007614  0.901017  \n",
              "15      0.664142  0.354115  0.579945  0.817273  \n",
              "16      0.741380  0.163382  0.592324  0.745138  \n",
              "17      0.894001  0.672173  1.182358  1.316304  \n",
              "18      1.269073  1.088766  1.015413  0.914636  \n",
              "19      1.422878  1.546551  1.782586  1.438174  \n",
              "20      1.272654  0.834634  0.934980  0.865305  \n",
              "21      0.734279  0.379074  0.764760  0.642924  \n",
              "22      1.109608  1.125094  0.882899  0.859396  \n",
              "23      1.373094  0.887989  1.206525  0.999058  \n",
              "24      1.333243  2.004407  1.550748  1.216709  \n",
              "25      0.973918  0.677132  1.135700  0.972836  \n",
              "26      1.131816  0.891868  0.973950  0.951233  \n",
              "27      0.945199  0.321730  0.735165  1.470303  \n",
              "28      0.805769  1.130206  0.838251  0.752052  \n",
              "29      0.665904  0.410987  0.606533  0.638353  \n",
              "...          ...       ...       ...       ...  \n",
              "999970  0.684203  1.674751  0.933095  0.812892  \n",
              "999971  1.318207  1.407812  1.143519  0.988023  \n",
              "999972  1.180888  0.660106  0.867804  1.209023  \n",
              "999973  1.445414  0.999012  1.058491  0.995545  \n",
              "999974  0.996433  0.768051  0.950206  0.813717  \n",
              "999975  1.367664  1.106266  1.195386  1.204696  \n",
              "999976  1.394441  0.638116  1.026588  0.936353  \n",
              "999977  0.805529  0.383582  0.830770  0.898366  \n",
              "999978  0.676237  0.789154  0.887203  0.813731  \n",
              "999979  0.726498  0.194710  0.829596  0.820687  \n",
              "999980  0.812480  0.805250  1.425254  1.148914  \n",
              "999981  1.405588  1.901048  1.208726  1.014675  \n",
              "999982  1.009671  1.013850  1.048530  1.066861  \n",
              "999983  0.613820  0.699125  0.718217  0.720967  \n",
              "999984  1.207435  0.964927  0.976137  1.051808  \n",
              "999985  1.540274  0.812345  1.111762  1.048665  \n",
              "999986  1.159479  0.592767  0.769826  1.106610  \n",
              "999987  1.038713  1.503057  0.933002  0.870590  \n",
              "999988  0.606848  0.932036  0.957529  0.868758  \n",
              "999989  0.773623  0.318335  0.895034  0.838218  \n",
              "999990  1.077554  0.755790  0.860523  0.913627  \n",
              "999991  0.720094  1.482483  0.876079  0.767670  \n",
              "999992  1.013631  0.937575  0.974468  0.829529  \n",
              "999993  0.943022  0.315795  0.615857  0.772179  \n",
              "999994  0.826123  0.602524  1.549889  1.489945  \n",
              "999995  0.734838  0.226974  0.817835  0.750583  \n",
              "999996  1.345282  0.984395  1.167846  1.042671  \n",
              "999997  0.980557  1.977671  1.186537  1.025073  \n",
              "999998  1.180130  0.514119  1.742259  2.751391  \n",
              "999999  0.623328  0.271381  0.723280  0.601052  \n",
              "\n",
              "[1000000 rows x 29 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QqRe69Jylqa4",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import numpy as np\n",
        "df_sig=df[df.Signal==1]\n",
        "df_back=df[df.Signal==0]\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S3D7KhW2nB4Z",
        "colab_type": "code",
        "outputId": "b7fb5132-1d4e-42a7-81bd-996b82296415",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 17002
        }
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "for var in VarNames[1:]:\n",
        "    plt.figure(figsize=(12,10))\n",
        "    plt.title('signal vs background for '+str(var))\n",
        "    plt.hist(np.array(df_sig[var]),bins=150,histtype=\"step\", color=\"red\",label=\"signal\", stacked=True,normed=True)\n",
        "    plt.hist(np.array(df_back[var]),bins=150,histtype=\"step\", color=\"blue\", label=\"background\", stacked=True,normed=True)\n",
        "    plt.legend(loc='upper right')\n",
        "    plt.ylabel('number of events normalized')\n",
        "    plt.xlabel(var)\n",
        "    plt.show()"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/matplotlib/axes/_axes.py:6521: MatplotlibDeprecationWarning: \n",
            "The 'normed' kwarg was deprecated in Matplotlib 2.1 and will be removed in 3.1. Use 'density' instead.\n",
            "  alternative=\"'density'\", removal=\"3.1\")\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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hedCDHpTvfOc7G53rnHPOyQMf+MB85zvfyVVXXZXHP/7xud/97pcXvOAFmZqaytVXX52Z\nmZkccMABee5zn5tVq1bl8ssvz8knn5yDDz44q1atyite8Yr159tll13WP1+zZk2OPfbYJL2R5xNP\nPDGHH3547nWve60fhW6t5YQTTsgBBxyQI444Ij/+8Y9Hcs0EagAA1rv00kvzohe9KJdcckl22223\n/M3f/E1OOOGEnHPOOfnmN7+Z//qv/8pnPvOZJL2lxV/84hfn61//es4666zsueee689z1lln5fd+\n7/fyqU99Kve+973zxje+MY997GNz0UUX5aijjsr3v//99cd++9vfzote9KJcdNFFWbFiRV7xilfk\ni1/8Yi644IKcc845+eQnP7nVuq+88sqceeaZ+cxnPpNXvvKVSZJPfOITufTSS3PxxRfn/e9/f846\n66x5vlo9AjUAAOvd8573zMMf/vAkyXOe85yceeaZOe200/KQhzwkBx98cL74xS/moosuys9+9rNc\nccUV65ceX7lyZXbeeeckvWW8jz/++Hz605/OvvvumyQ588wz8+xnPztJ8sQnPjF3uctd1n/m1NRU\nHvrQhybpjWo/+tGPzh577JGddtopxxxzTL70pS9tte6nP/3p2WGHHXLQQQflRz/6UZLkS1/6Uo4+\n+ujsuOOO2WuvvfLYxz52nq7SxgRqAADWq6rbbL/oRS/KmjVrcuGFF+a4447LjTfeuMVz7Lnnnlm5\ncmW+9rWvDfWZd7zjHbe5trk13P72t1//fLYlZaEI1AAArPf9738/X/7yl5MkH/zgB/OIRzwiSbL7\n7rvn+uuvX9+fvOuuu2afffZZ345x00035YYbbkiS3PnOd85nP/vZvOpVr8rpp5+eJHn4wx+ej3zk\nI0mSL3zhC7n22ms3+fmHHXZYzjjjjFx99dW55ZZbcvLJJ+dRj3pUkuQe97hHLrnkktx66635xCc+\nsdXv8shHPjIf/vCHc8stt+TKK6/Maaedtp1XZcsEagCARWhqan6nzZuaGu5zDzjggLz97W/PgQce\nmGuvvTYvfOELc9xxx2XVqlX5tV/7tRx66KHrjz3ppJPytre9Lfe///1z+OGH54c//OH61+5xj3vk\nM5/5TF784hfn7LPPzutf//p84QtfyKpVq/LRj340v/Irv5Jdd931Np+/55575s1vfnMe85jH5JBD\nDsmDH/zgPO1pT0uSvPnNb85TnvKUHH744Rv1a2/OM57xjOy///456KCD8tznPjcPe9jDhrsI26gW\neki8q9WrV7dzzz133GUsjKreDB9znwMAS84ll1ySAw88cNxljMxNN92UHXfcMTvttFO+/OUv54Uv\nfGEuuOCCcZe13qauf1Wd11pbvbX37jSyqtg+09Mbpsgb9ldJAIBF7vvf/36e9axn5dZbb83tbne7\nvOtd7xp3SfNGoF4M5oZoI9EAwBKz//77D32T4qQRqBeD2QVcAIBlrbV2m1k2GL2uLdBuSgQAWARW\nrlyZa665ZsGnfFvuWmu55pprsnLlyu0+hxFqAIBFYJ999sm6dety1VVXjbuUZWflypXZZ599tvv9\nAjUAwCKwYsWK7LfffuMug+2g5QMAADoQqCfF7Ozu09PjrgQAgAFaPibFzEzvn+78BQBYVIxQAwBA\nBwI1AAB0IFBPmtleav3UAACLgh7qSTPbS53opwYAWASMUAMAQAcjC9RV9d6q+nFVfXMzr1dVva2q\nLquqb1TVg0ZVCwAAjMooR6j/PskTt/D6k5Ls338cn+QdI6wFAABGYmSBurX2pST/uYVDnpbk/a3n\nK0nuXFV7jqqeRWd6esPNhVNT464GAIDtNM6bEvdOcvnA9rr+vivnHlhVx6c3ip199913QYobubVr\nk9bGXQUAAB1NxE2JrbV3ttZWt9ZW77HHHuMuBwAA1htnoL4iyT0Htvfp7wMAgIkxzkB9SpLn9mf7\neGiS61prt2n3AACAxWxkPdRVdXKSRyfZvarWJXl9khVJ0lr72ySnJvn1JJcluSHJ80ZVCwAAjMrI\nAnVr7eitvN6SvHhUnw8AAAthIm5KBACAxUqgBgCADgRqAADoQKAGAIAOBOpJNjW1Yfny6elxVwMA\nsCyNc+lxupqZ2fC8amxlAAAsZ0aoAQCgA4EaAAA6EKgX0vT0hp7nqalxVwMAwDzQQ72Q1q5NWht3\nFQAAzCMj1AAA0IFADQAAHQjUYzTYUm0qaQCAyaSHeozmtlSbShoAYPIYoV5A0/neRiPSJvoAAJh8\nRqgX0NpMm+QDAGCJMUINAAAdCNQAANCBQA0AAB0I1AAA0IFADQAAHQjUAADQgUANAAAdCNSLyNRU\nh6XIB99sDXMAgAVjYZdFZGZm4+1tWop88M3WMAcAWDBGqAEAoAOBGgAAOhCoAQCgA4EaAAA6EKgB\nAKADgRoAADoQqEdoenrjeaWnMjPukgAAmGfmoR6htWuT1gZ21H5J2uYOBwBgAhmhBgCADgRqAADo\nQKAGAIAOBGoAAOhAoF4Is9N9TE2NuxIAAOaZWT4Wwm2m+wAAYKkwQg0AAB0I1AAA0IFADQAAHQjU\nAADQgUANAAAdCNQAANCBQA0AAB0I1IvY1FRvPZjZx/T0uCsCAGAuC7ssYjMzG29XDfnG2SQ++3zu\niQAAmDcC9VI0GKCHTuEAAGwPLR8AANCBQA0AAB0I1AAA0IFADQAAHQjUAADQgUANAAAdCNQAANCB\nQA0AAB0I1AAA0IFADQAAHQjUAADQgUA9QaamkqoNj+npcVcEAMBO4y6A4c3MbLxdNZYyAAAYYIQa\nAAA6EKiXusE+ET0iAADzTsvHUjfYJ6JHBABg3hmhBgCADgTqeTQ9vfEsHFNT464IAIBR0/Ixj9au\nTVobdxUAACwkI9QAANCBQA0AAB0I1AAA0IFADQAAHQjUAADQgUANAAAdCNQAANCBQA0AAB0I1AAA\n0IFADQAAHQjUAADQgUANAAAdCNQAANCBQD0q09NJVe8xNTXuagAAGJGdxl3AkrV2bdLauKsAAGDE\njFADAEAHAvUEm5ra0FVS1esyAQBgYWn5mGAzMxtvV42lDACAZc0INQAAdCBQLyezPSJ6QwAA5o2W\nj+VktkdEbwgAwLwxQg0AAB2MNFBX1ROr6tKquqyqXrmJ1/etqtOq6mtV9Y2q+vVR1gMAAPNtZIG6\nqnZM8vYkT0pyUJKjq+qgOYe9NslHWmsPTPLsJH8zqnoAAGAURjlCfViSy1pr322t/SLJh5I8bc4x\nLclu/ed3SvKDEdYDAADzbpSBeu8klw9sr+vvG/SGJM+pqnVJTk3ykk2dqKqOr6pzq+rcq666ahS1\nAgDAdhn3TYlHJ/n71to+SX49yUlVdZuaWmvvbK2tbq2t3mOPPRa8SAAA2JxRBuorktxzYHuf/r5B\nv5PkI0nSWvtykpVJdh9hTQAAMK9GGajPSbJ/Ve1XVbdL76bDU+Yc8/0kj0uSqjowvUCtpwMAgIkx\nskDdWrs5yQlJPp/kkvRm87ioqt5UVUf2D/v9JMdV1deTnJzk2NZaG1VNAAAw30a6UmJr7dT0bjYc\n3Pe6gecXJ3n4KGsAAIBRGvdNiQAAMNEEagAA6ECgBgCADgRqAADoQKAGAIAOBGoAAOhAoAYAgA4E\nagAA6ECgXkKmppKqDY/p6XFXBACw9I10pUQW1szMxttVYykDAGBZMUINAAAdCNQAANCBQA0AAB0I\n1AAA0IFADQAAHQjUAADQgUANAAAdCNQAANCBQL0cDS6paDlFAIBOrJS4HA0uqWg5RQCAToxQAwBA\nBwI1AAB0IFADAEAHAjUAAHQgUAMAQAcCNQAAdCBQAwBABwJ1B9PTG9ZHqUqmdlw3sDE17vIAAFgA\nFnbpYO3apLWBHXXPOTsAAFjqjFADAEAHAjUAAHQgUAMAQAcCNQAAdCBQAwBABwL1EjY1tfG0ftPT\n464IAGDpMW3eEjYzs/F21VjKAABY0oxQAwBABwI1AAB0IFADAEAHAjUAAHQgUAMAQAcCNQAAdCBQ\nAwBABwI1AAB0IFADAEAHm10psaoetKU3ttbOn/9yAABgsmxp6fE/6/9zZZLVSb6epJLcP8m5SR42\n2tIAAGDx22zLR2vtMa21xyS5MsmDWmurW2sPTvLAJFcsVIEAALCYDdNDfUBr7cLZjdbaN5McOLqS\nAABgcmyp5WPWN6rq3Un+sb99TJJvjK4kAACYHMME6ucleWGSl/a3v5TkHSOrCAAAJshWA3Vr7caq\n+tskp7bWLl2AmlhIU1NJ1YbnMzNjLQcAYNJstYe6qo5MckGSz/W3H1BVp4y6MBbIzEzSWu+xdu24\nqwEAmDjD3JT4+iSHJflJkrTWLkiy3yiLAgCASTFMoP5la+26OfvaKIoBAIBJM8xNiRdV1W8l2bGq\n9k9yYpKzRlsWAABMhmFGqF+S5H5JbkrywSTXJXnZKIsCAIBJMUygfnCS17XWDu0/XpvkoBHXxQjM\nTugx+5ieHndFAACTb5hA/fkkX6yquw/se/eI6mGEBif0MKkHAMD8GCZQX5rkT5OcUVWH9/fV6EoC\nAIDJMcxNia219pmqujTJh6vqvTHLBwAAJBluhLqSpLX27SSP7D/uP8qiAABgUgyz9PgDB55fn+RZ\nVbXvSKsCAIAJsdlAXVV/2Fr7v1X1ts0ccuKIagIAgImxpRHqS/r/PG8hCgEAgEm02UDdWvt0/5//\nsHDlAADAZNlSy8ens4XZPFprR46kIgAAmCBbavl464JVAQAAE2pLLR9nLGQhAAAwibY6D3VV7V9V\na6rq4qr67uxjIYpjgU1NJVW9x/T0uKsBAJgIw6yU+L4kr0/yF0kek+R5GW5BGCbNzMyG52V1eQCA\nYQwTjO/QWvvXJNVaW9tae0OSJ4+2LAAAmAzDjFDfVFU7JPl2VZ2Q5Ioku4y2LAAAmAzDjFC/NMnO\n6a2M+OAkv53kf4yyKAAAmBRbHaFurZ3Tf3p9ev3TAABA31YDdVWtTvKaJFODx7fW7j/CuibH9HSy\ndm3v+dTUWEsBAGDhDdND/YEkL09yYZJbR1vOBFq7NmmbXVASAIAlbphAfVVr7ZSRVwIAABNomED9\n+qp6d5J/TXLT7M7W2sdHVhUAAEyIYQL185LcN8mKbGj5aEkEagAAlr1hAvWhrbUDRl4JAABMoGHm\noT6rqg4aeSUsuKmp3grjs4/p6XFXBAAweYYZoX5okguq6nvp9VBXkmbavMk3M7PxdtVYygAAmGjD\nBOonjrwKAACYUFsM1FW1Y5LPt9buu0D1AADARNliD3Vr7ZYkl1bVvgtUDwAATJRhWj7ukuSiqvpq\nkp/P7mytHTmyqgAAYEIME6j/aORVAADAhNpqoG6tnVFV90hyaH/XV1trPx5tWQAAMBm2Og91VT0r\nyVeTPDPJs5KcXVVHDXPyqnpiVV1aVZdV1Ss3d/6quriqLqqqD25L8QAAMG7DtHy8Jr3VEn+cJFW1\nR5J/SbJmS2/qzxDy9iSPT7IuyTlVdUpr7eKBY/ZP8qokD2+tXVtVd9++rwEAAOMxzEqJO8xp8bhm\nyPcdluSy1tp3W2u/SPKhJE+bc8xxSd7eWrs2SbSSAAAwaYYZof5cVX0+ycn97d9McuoQ79s7yeUD\n2+uSPGTOMfdJkqr69yQ7JnlDa+1zc09UVccnOT5J9t3XDH4AACweWx1pbq29PMk7k9y//3hna+0V\n8/T5OyXZP8mjkxyd5F1VdedN1PDO1trq1trqPfbYY54+ettNT/eW5559TE2NrRQAABaJYUao01r7\nWJKPbeO5r0hyz4Htffr7Bq1LcnZr7ZdJvldV/5FewD5nGz9rQaxdm7Q2Z2eNpRQAABaJYWb5+O9V\n9e2quq6qflpVP6uqnw5x7nOS7F9V+1XV7ZI8O8kpc475ZHqj06mq3dNrAfnuNn0DRmNqasNQ/PT0\nuKsBAFi0hhmh/r9Jntpau2RbTtxau7mqTkjy+fT6o9/bWruoqt6U5NzW2in9155QVRcnuSXJy1tr\n12zbV2AkZmY2PC/D8AAAm1PtNj0Mcw6o+vfW2sMXqJ6tWr16dTv33HPH8tlVm2r52NTOybTZr7KE\nviMAwLCq6rzW2uqtHTfMCPW5VfXh9Nozbprd2Vr7eIf6AABgSRgmUO+W5IYkTxjY15II1AAALHtb\nDdSttectRCEAADCJhlnxEAAA2AyBGgAAOhCoAQCgg2EWdnlpVe1WPe+pqvOr6glbex8AACwHw4xQ\nP7+19tP0Zvm4S5LfTvLmkVZzU0/hAAAX5UlEQVQFAAATYphAPbtM3q8nOam1dtHAPgAAWNaGCdTn\nVdUX0gvUn6+qXZPcOtqyAABgMgyzsMvvJHlAku+21m6oqrslMTc1AABkuBHqf26tnd9a+0mStNau\nSfIXoy0LAAAmw2ZHqKtqZZKdk+xeVXfJhr7p3ZLsvQC1AQDAorello/fTfKyJHslOS8bAvVPk/z1\niOsCAICJsNlA3Vr7qyR/VVUvaa39vwWsiTGZmkqqNt6emRlbOQAAE2GrNyW21v5fVR2eZHrw+Nba\n+0dYF2MwNzyXyREBALZqq4G6qk5Kcu8kFyS5pb+7JRGoAQBY9oaZNm91koNaa23UxQAAwKQZZtq8\nbyb5lVEXAgAAk2iYEerdk1xcVV9NctPsztbakSOrCgAAJsQwgfoNoy4CAAAm1TCzfJxRVVNJ9m+t\n/UtV7Zxkx9GXBgAAi99We6ir6rgka5L8XX/X3kk+OcqiWGRmJ6iuSqanx10NAMCiMkzLx4uTHJbk\n7CRprX27qu4+0qpYXAYnqDY5NQDARoaZ5eOm1tovZjeqaqf05qEGAIBlb5hAfUZVvTrJHarq8Uk+\nmuTToy0LAAAmwzCB+pVJrkpyYZLfTXJqkteOsigAAJgUw/RQPz3J+1tr7xp1MQAAMGmGGaF+apL/\nqKqTquop/R7q5W16esOsF1NT464GAIAx2mqgbq09L8mvptc7fXSS71TVu0dd2KK2dm3SWu8xOAMG\nAADLzjAj1Gmt/TLJPyX5UJLz0msDYYkbnH7aFNQAAJu21faNqnpSkt9M8ugkpyd5d5JnjbQqFoW5\ng++moAYAuK1h+qGfm+TDSX63tXbTiOsBAICJMkwP9dFJvpbkvyVJVd2hqnYddWEAADAJthqoq+q4\nJGuS/F1/1z5JPjnKogAAYFIMc1Pii5M8PMlPk6S19u0kdx9lUQAAMCmGCdQ3tdZ+MbvRn4e6ja4k\nAACYHMME6jOq6tVJ7lBVj09vPupPj7YsAACYDMME6lcmuSrJhUl+N8mpSV47yqIAAGBSbHXavNba\nrUne1X8AAAADhlopEQAA2DSBGgAAOthsoK6qk/r/fOnClQMAAJNlSyPUD66qvZI8v6ruUlV3HXws\nVIEAALCYbemmxL9N8q9J7pXkvCQ18Frr7wcAgGVtsyPUrbW3tdYOTPLe1tq9Wmv7DTyEaQAAyHDT\n5r2wqg5J8t/6u77UWvvGaMsCAIDJsNVZPqrqxCQfSHL3/uMDVfWSURcGAACTYKsj1ElekOQhrbWf\nJ0lVvSXJl5P8v1EWBgAAk2CYeagryS0D27dk4xsUAQBg2RpmhPp9Sc6uqk/0t5+e5D2jK4lFbWoq\nqer9c2Zm3NUAAIzdMDcl/nlVnZ7kEf1dz2utfW2kVbEoTU0ltXamt7E2iVwNADDUCHVaa+cnOX/E\ntbDIbRScq5LWUpp/AIBlbpgeagAAYDMEagAA6GCLgbqqdqyq0xaqGAAAmDRbDNSttVuS3FpVd1qg\negAAYKIMc1Pi9UkurKp/TvLz2Z2ttRNHVhUAAEyIYQL1x/sPAABgjmHmof6HqrpDkn1ba5cuQE0A\nADAxtjrLR1U9NckFST7X335AVZ0y6sIAAGASDDNt3huSHJbkJ0nSWrsgyb1GWBMAAEyMYQL1L1tr\n183Zd+soigEAgEkzzE2JF1XVbyXZsar2T3JikrNGWxYAAEyGYUaoX5LkfkluSnJykp8medkoiwIA\ngEkxzCwfNyR5TVW9pbfZfjb6sgAAYDIMM8vHoVV1YZJvpLfAy9er6sGjLw0AABa/YVo+3pPkRa21\n6dbadJIXJ3nfSKti8ZuaSqp6z6enx1oKAMA4DROob2mt/dvsRmvtzCQ3j64kJsLMTNJa7/natWMt\nBQBgnDbbQ11VD+o/PaOq/i69GxJbkt9McvroS2MSTE0ltbYltWF7ZmasJQEALKgt3ZT4Z3O2Xz/w\nvI2gFibQzEx6rR/90erZLhAAgOVis4G6tfaYhSwEAAAm0VanzauqOyd5bpLpweNbayeOriwAAJgM\nw6yUeGqSryS5MJYcBwCAjQwTqFe21v7nyCsBAIAJNMy0eSdV1XFVtWdV3XX2MfLKAABgAgwzQv2L\nJH+a5DXZMLtHS3KvURUFAACTYphA/ftJfrW1dvWoiwEAgEkzTMvHZUluGHUhAAAwiYYZof55kguq\n6rQkN83uNG0eAAAMF6g/2X8AAABzbDVQt9b+YSEKAQCASTTMSonfy4bZPdZrrZnlAwCAZW+Ylo/V\nA89XJnlmkuU7D3VVMjU17ioWl6mp3nVJsonfvQAAlrRhWj6umbPrL6vqvCSvG01Ji1wTGG9jZmbD\n89rsUQAAS9IwLR8PGtjcIb0R62FGtgEAYMkbJhj/2cDzm5PMJHnWSKoBAIAJM0zLx2MWohAAAJhE\nw7R83D7JbySZHjy+tfam0ZUFAACTYZiWj08luS7JeRlYKREAABguUO/TWnvi9py8qp6Y5K+S7Jjk\n3a21N2/muN9IsibJoa21c7fnswAAYBx2GOKYs6rq4G09cVXtmOTtSZ6U5KAkR1fVQZs4btckL01y\n9rZ+BovPVGZSlfWP6elxVwQAMFrDBOpHJDmvqi6tqm9U1YVV9Y0h3ndYkstaa99trf0iyYeSPG0T\nx/1xkrckuXHoqlm0ZrJfWsv6x9q1464IAGC0hmn5eNJ2nnvvJJcPbK9L8pDBA/pzXN+ztfbZqnr5\n5k5UVccnOT5J9t133+0sBwAA5t8w0+aNZIyxqnZI8udJjh2ihncmeWeSrF692lKFAAAsGsO0fGyv\nK5Lcc2B7n/6+WbsmWZXk9KqaSfLQJKdU1eoR1gQAAPNqlIH6nCT7V9V+VXW7JM9Ocsrsi62161pr\nu7fWpltr00m+kuRIs3wAADBJRhaoW2s3JzkhyeeTXJLkI621i6rqTVV15Kg+FwAAFtIwNyVut9ba\nqUlOnbPvdZs59tGjrAUAAEZhlC0fAACw5AnUAADQgUANAAAdCNQAANCBQA0AAB0I1AAA0IFADQAA\nHQjUjNTUVFK14TE9Pe6KAADm10gXdoGZmY23q8ZSBgDAyBihZn4NDkkbjgYAlgEj1MyvwSFpw9EA\nwDJghBoAADoQqAEAoAOBGgAAOhCoAQCgA4EaAAA6EKgBAKADgRoAADoQqAEAoAOBGgAAOhCoGR3L\nkAMAy4Clxxkdy5ADAMuAEWoAAOhAoAYAgA4EagAA6ECgZkEN3qfoXkUAYClwUyILavA+xcS9igDA\n5DNCDQAAHQjUAADQgUANAAAdCNQAANCBQA0AAB0I1AAA0IFADQAAHQjULIzZFV2s5AIALDEWdmFh\nzK7oYiUXAGCJMUINAAAdCNQAANCBQA0AAB0I1AAA0IFADQAAHQjUjNXsbHqzD7PqAQCTxrR5jNXs\nbHqzzKoHAEwaI9QAANCBQM3CGuzx0N8BACwBWj5YWIM9Hvo7AIAlwAg1AAB0IFADAEAHAjUAAHQg\nUAMAQAcCNQAAdCBQAwBABwI1AAB0IFCzqAyu+2LtFwBgEljYhUVlcN2XxNovAMDiZ4Sa8bEMOQCw\nBBihZnwsQw4ALAFGqAEAoAOBGgAAOhCoAQCgA4EaAAA6EKhZHMz4AQBMKLN8sDiY8QMAmFBGqAEA\noAOBGgAAOhCoAQCgA4GaRW3wXkX3KwIAi5GbElnUBu9VTNyvCAAsPkaoAQCgA4EaAAA6EKhZfCzy\nAgBMED3ULD4WeQEAJogRagAA6ECgZnHT/gEALHJaPljctH8AAIucEWoAAOhAoAYAgA4EagAA6ECg\nBgCADgRqJsrgpB8m/gAAFgOzfDBRBif9SEz8AQCMnxFqAADoQKAGAIAOBGoAAOhAoGZyzN6R6E5E\nAGARcVMik2P2jkR3IgIAi4gRagAA6MAINZNntvUjSdLGWgoAgBFqJs/MTNJa0lqmMmOhFwBgrEYa\nqKvqiVV1aVVdVlWv3MTr/7OqLq6qb1TVv1bV1CjrYemZyX6z2TqtJWvXjrsiAGC5GVmgrqodk7w9\nyZOSHJTk6Ko6aM5hX0uyurV2/yRrkvzfUdUDAACjMMoR6sOSXNZa+25r7RdJPpTkaYMHtNZOa63d\n0N/8SpJ9RlgPAADMu1EG6r2TXD6wva6/b3N+J8k/beqFqjq+qs6tqnOvuuqqeSwRAAC6WRQ3JVbV\nc5KsTvKnm3q9tfbO1trq1trqPfbYY2GLAwCALRhloL4iyT0Htvfp79tIVR2R5DVJjmyt3TTCeliK\nZqfQM8UHADAmo5yH+pwk+1fVfukF6Wcn+a3BA6rqgUn+LskTW2s/HmEtLFWzqycmVlAEAMZiZCPU\nrbWbk5yQ5PNJLknykdbaRVX1pqo6sn/YnybZJclHq+qCqjplVPUAAMAojHSlxNbaqUlOnbPvdQPP\njxjl57P8bLSIYn97cBAbAGC+WXqcJWVueNYFAgCM2qKY5QPmhRsUAYAxMELN0uEGRQBgDIxQAwBA\nBwI1AAB0IFCzNA1O96GfGgAYIT3ULE2z/dSVZO3acVYCACxxRqhZ0qamkkoz+QcAMDJGqFnSZmbS\nS9KtJTH5BwAw/4xQAwBABwI1AAB0IFADAEAHeqhZ+gan0EsbaykAwNIjULP0bbQk+diqAACWKC0f\nAADQgUANAAAdCNQsP1Z4AQDmkR5qlp/WrPACAMwbI9QAANCBQM2yMjuDXqXp/AAA5oWWD5aV9TPo\nVSWt6fwAADozQg0AAB0I1AAA0IFAzfI0uBy5RmoAoAM91CxPs83UlWTt2nFWAgBMOCPULGtTUxtm\n/DDrBwCwPYxQs6zNzGT9jB+J9V4AgG0nUMNgP3XaWEsBACaPQA3rJ6dOr6caAGAb6KEGAIAOBGoY\nMJWZ9TcoukkRABiGQA0DZqYendab9yNtatqMegDAVumhhkEb9VNrqAYAts4INQAAdCBQAwBABwI1\nAAB0IFADAEAHAjVsztSUafQAgK0yywdszsxMZmafVyWtmfgDALgNI9QAANCBQA0AAB0I1DCMqamk\nKlM7rtNTDQBsRA81DKO/guJMv5d6lp5qAMAINQAAdCBQAwBABwI1bIt+L7UGagBglh5q2Bb9Xuok\nvZsUpzbuo56a2vgQAGDpE6ihg7nh2U2KALD8aPkAAIAOBGrYXvqpAYBo+YDtN6efGgBYnoxQAwBA\nBwI1zKPBLhDdIACwPGj5gPnQT9Izs88H2kF0gwDA0iZQw3zYQj+1uaoBYGkTqGHEzFUNAEubHmqY\nb6bTA4BlxQg1zLetTKenBQQAlhaBGkZpMD33k7MWEABYWgRqGCWLvwDAkqeHGgAAOhCoAQCgA4Ea\nAAA6EKhhoczeoDhnKr25y5WbaQ8AJotADQtlZiZpLVm7dpO7Zx+JgA0Ak8QsH7DQNjGV3iDT6gHA\nZBGoYaGZSg8AlhQtH7DI6bEGgMXNCDUsclpAAGBxM0IN4zQ4/GzoGQAmkhFqGKft6KcevKdxdnvu\nKDYAsHAEapgwWkAAYHHR8gGLxXa2f7hpEQDGS6CGxWJwhZdk6IQ8d2GYOevGAAAjpuUDFqMOc1Xr\nsQaAhSVQwxKjxxoAFpaWD1jsOk6tp8caAEZLoIbFbrBJejsapOf2WCcCNgDMJ4EaJsnscHOHFCxg\nA8D8Eqhhksym4WTeErBZQgCgGzclwiTqMAvI1sydJWRTr5s1BAA2EKhh0g0m4HlIu1t7u1lDAGBj\nWj5g0m3ngjDby6whALAxgRqWkgUI125qBICNCdSwVC3QyPXWAvamHkI3AEuJQA3LwabC9YhS7dyA\nvamHmUQAWEoEalhuRjD13raa24dtRBuASSZQw3K1wDczbu6jh3kMlidgA7DYCNTA5sP1Ihku3tY+\nbYEbgIUkUAMb29rwcTL2Ho2uJQrcAMynkQbqqnpiVV1aVZdV1Ss38frtq+rD/dfPrqrpUdYDzINh\n+jWSLSfZ6emRptv5+J1AjzcAwxpZoK6qHZO8PcmTkhyU5OiqOmjOYb+T5NrW2q8m+YskbxlVPcAC\n2lyiTTYstTjGEe9t7eHe3t8fhHaA5WGUI9SHJbmstfbd1tovknwoydPmHPO0JP/Qf74myeOqZv9v\nCyw5s0l2cH3zLiPeC/3Y1Ah7VWbWVloqbWp6XoP6YrwEfmEAuK2dRnjuvZNcPrC9LslDNndMa+3m\nqrouyd2SXD14UFUdn+T4/ub1VXXpkDXsPvdcXYn7y8q8//ww4dau3fJ/BDZ+3c/PNtjapV2m/AzR\nhZ+f+TE1zEGjDNTzprX2ziTv3Nb3VdW5rbXVIyiJZcDPD134+aErP0N04ednYY2y5eOKJPcc2N6n\nv2+Tx1TVTknulOSaEdYEAADzapSB+pwk+1fVflV1uyTPTnLKnGNOSfI/+s+PSvLF1ma7BQEAYPEb\nWctHvyf6hCSfT7Jjkve21i6qqjclObe1dkqS9yQ5qaouS/Kf6YXu+bTNbSIwwM8PXfj5oSs/Q3Th\n52cBlQFhAADYflZKBACADgRqAADoYEkG6q0teQ5bUlX3rKrTquriqrqoql467pqYPFW1Y1V9rao+\nM+5amCxVdeeqWlNV36qqS6rqYeOuiclRVf9f//9d36yqk6tq5bhrWg6WXKAecslz2JKbk/x+a+2g\nJA9N8mI/Q2yHlya5ZNxFMJH+KsnnWmv3TXJI/BwxpKraO8mJSVa31lalNynEfE/4wCYsuUCd4ZY8\nh81qrV3ZWju///xn6f3PbO/xVsUkqap9kjw5ybvHXQuTparulOSR6c2CldbaL1prPxlvVUyYnZLc\nob++x85JfjDmepaFpRioN7XkuTDEdqmq6SQPTHL2eCthwvxlkj9Mcuu4C2Hi7JfkqiTv67cMvbuq\n7jjuopgMrbUrkrw1yfeTXJnkutbaF8Zb1fKwFAM1zIuq2iXJx5K8rLX203HXw2Soqqck+XFr7bxx\n18JE2inJg5K8o7X2wCQ/T+JeIIZSVXdJ72/l90uyV5I7VtVzxlvV8rAUA/UwS57DFlXVivTC9Ada\nax8fdz1MlIcnObKqZtJrOXtsVf3jeEtigqxLsq61Nvu3YmvSC9gwjCOSfK+1dlVr7ZdJPp7k8DHX\ntCwsxUA9zJLnsFlVVen1L17SWvvzcdfDZGmtvaq1tk9rbTq9//58sbVmhIihtNZ+mOTyqjqgv+tx\nSS4eY0lMlu8neWhV7dz/f9nj4qbWBTGypcfHZXNLno+5LCbLw5P8dpILq+qC/r5Xt9ZOHWNNwPLx\nkiQf6A8KfTfJ88ZcDxOitXZ2Va1Jcn56M1Z9LZYgXxCWHgcAgA6WYssHAAAsGIEaAAA6EKgBAKAD\ngRoAADoQqAEAoAOBGgAAOhCoARaJqrq+w3tfVlU7z2c9m/mcX6uqC/qP66vq0v7z94/6swEWK/NQ\nAywSVXV9a22X7XzvTJLVrbWr57eqLX7m6Un+oLV27kJ9JsBiZIQaYBGqqpdX1TlV9Y2qemN/33RV\nfauqPlBVl1TVmv4Swycm2SvJaVV1Wv/Yo6vqwqr6ZlW9ZeC811fVn1TV16vqK1V1jy3U8PdV9bdV\ndW5V/UdVPWXU3xtgEgnUAItMVT0hyf5JDkvygCQPrqpH9l8+IMnftNYOTPLTJC9qrb0tyQ+SPKa1\n9piq2ivJW5I8tv/+Q6vq6f333zHJV1prhyT5UpLjtlLOdL+OJyf526paOU9fE2DJEKgBFp8n9B9f\nS3J+kvumF7CT5PLW2r/3n/9jkkds4v2HJjm9tXZVa+3mJB9IMhvIf5HkM/3n56UXmLfkI621W1tr\n307y3X4tAAzYadwFAHAbleT/tNb+bqOdVdNJ5t74sq03wvyybbh55pZs/f8DXT8PYMkzQg2w+Hw+\nyfOrapckqaq9q+ru/df2raqH9Z//VpIz+89/lmTX/vOvJnlUVe1eVTsmOTrJGdtZyzP//3bu2KSi\nIIgC6B0LsAiNBNsxswDBBgRjaxAMxFwTQUFMDO1A+KmBFRiYjcF7keFb+Pq/54QLu7ObXYZhq2qn\nqvaT7CVZLTwHYGvpUAP8Md39XFUHSV6rKkk+kxxn6iivkpxW1XWStySX87arJE9V9THPUZ8lecnU\n7X7s7vuF13nPFNB3k5x099fSdwFsK9/mAWyIeeTjobsP11TvZq53t456AJvKyAcAAAzQoQb456rq\nPMnRj+Xb7r74jfsAbBqBGgAABhj5AACAAQI1AAAMEKgBAGCAQA0AAAO+ATtlkOufqKAiAAAAAElF\nTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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J6mdWtCVJkqQSmGhLkiRJJTDRliRJkkpgoi1JkiSVwERbkiRJKoGJtiRJklQC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\nkiRJLTBoS5IkSS0waEuSJEkt+D8+VmTzoaiUSwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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hrIsM2v2ih3Y69Y7p9qGv4x/oBgbaHnml0ahtNHDw6D7WWs/ocbFj+n1Qn271\nbAy6nHyb5fzGw8WUvLQb7nS48fbp2NWrtGk2QlgzBu0+MHcuxPJc77qk5gaWX73eL2Z25LWzsb3p\njfUDFdPtINTtr2amRwlqolnO78oJnRvDWaR9/sIwaPeBje19XRuRwulk1Igfal8vHIDarLFED4Ze\n2EzTXT+eCyT6/oOEQVsqpPhPX28MTWSmE3VBL/bdbWqKjxcl7m6qzwXaGA6xkx4lrR83SocZtKVC\nRvdD7fBJb4ZQ9SrfrDfMZM7FmeLjRUfursvD6/XDIbZZg89kR0lTcwZt9aW2h1DTlCjeyq/e4Jt1\n2zbKc3F6dXi9aaR4g4+aMmirLzmE2vTkQX8M7Ta72Rq8UTI0Sr3JoK3+NAXjMDXNOwYitaLdBGXi\nkqSeYdBWZ0zxDw00NQVDIjV9eAaiaceuK9oQfmaWtKEM2uqMxlA5MOA7k6Ydu65oQ/iZWVPGT3V9\nx6AtoMBr23cmSZLa0+n3zmkW3KdZOVPCoC3AXCxJG7O5M1YQMWe96zBn/AXUG6bZm/s0K2dKGLTV\nHzbGj8lqn/uJNKbhNY2h2pAtdYJBW/1hY/yYrPa5n0iSptAm3S5AkiRJ6kcGbUmSJKkAg7YkSZJU\ngEFbkiRJKsCgLUmSJBXgqCOSpo7D60mSNiIGbUlTx+H1JEkbEbuOSJIkSQUYtCVJkqQCDNqSJElS\nAQZtSZIkqQCDtiRJklSAQVuSJEkqwKAtSZIkFWDQliRJkgowaEuSJEkFGLQlSZKkAgzakiRJUgEG\nbUmSJKkAg7YkSZJUgEFbkiRJKsCgLUmSJBVg0JYkSZIKMGhLkiRJBRi0JUmSpAIM2pIkSVIBBm1J\nkiSpAIO2JEmSVIBBW5IkSSrAoC1JkiQVYNCWJEmSCjBoS5IkSQUYtCVJkqQCDNqSJElSAQZtSZIk\nqQCDtiRJklRA0aAdEYdFxNKIWBYRp49x+19GxO0RcWtE/CAi5tbdtjYibqn+LilZpyRJktRpM0ut\nOCJmAGcDrwRWAIsj4pLMvL1uth8Dg5n5WES8G/gH4M3Vbb/PzH1K1SdJkiSVVLJF+wBgWWbenZlP\nABcCR9TPkJlXZeZj1dUfAXMK1iNJkiRNmZJBeyfg3rrrK6pp43kH8B9112dHxFBE/CgijhxrgYg4\nqZpnaNWqVZOvWJIkSeqQYl1H2hERbwUGgZfVTZ6bmSsjYlfgyoi4LTPvql8uM88BzgEYHBzMKStY\nkiRJaqJki/ZKYOe663OqaeuJiEOBDwOHZ+bqkemZubL6fzdwNbBvwVolSZKkjioZtBcD8yNiXkRs\nChwNrDd6SETsC3yeWsh+oG7yLXySAAAgAElEQVT61hGxWXV5O+AgoP4kSkmSJGlaK9Z1JDPXRMQp\nwBXADOC8zFwSEWcCQ5l5CfCPwBbA1yMC4J7MPBzYA/h8RDxJ7cPAWQ2jlUiSJEnTWmT2R9fmwcHB\nHBoa6sp9R0CfbEZJkqSe0a0MFhE3ZeZgs/n8ZUhJkiSpAIO2JEmSVIBBW5IkSSrAoC1JkiQVYNCW\nJEmSCjBoS5IkSQUYtCVJkqQCDNqSJElSAQZtSZIkqQCDtiRJklSAQVuSJEkqwKAtSZIkFWDQliRJ\nkgowaEuSJEkFGLQlSZKkAgzakiRJUgEGbUmSJKkAg7YkSZJUgEFbkiRJKsCgLUmSJBVg0JYkSZIK\nMGhLkiRJBRi0JUmSpAIM2pIkSVIBBm1JkiSpAIO2JEmSVIBBW5IkSSrAoC1JkiQVYNCWJEmSCjBo\nS5IkSQUYtCVJkqQCDNqSJElSAQZtSZIkqQCDtiRJklSAQVuSJEkqwKAtSZIkFWDQliRJkgowaEuS\nJEkFGLQlSZKkAgzakiRJUgEGbUmSJKkAg7YkSZJUgEFbkiRJKsCgLUmSJBVg0JYkSZIKMGhLkiRJ\nBRi0JUmSpAIM2pIkSVIBBm1JkiSpAIO2JEmSVIBBW5IkSSrAoC1JkiQVYNCWJEmSCjBoS5IkSQUY\ntCVJkqQCDNqSJElSAQZtSZIkqQCDtiRJklSAQVuSJEkqwKAtSZIkFWDQliRJkgowaEuSJEkFGLQl\nSZKkAgzakiRJUgEGbUmSJKkAg7YkSZJUgEFbkiRJKsCgLUmSJBVg0JYkSZIKMGhLkiRJBRi0JUmS\npAIM2pIkSVIBBm1JkiSpAIO2JEmSVIBBW5IkSSrAoC1JkiQVYNCWJEmSCigatCPisIhYGhHLIuL0\nMW7/y4i4PSJujYgfRMTcutveFhF3Vn9vK1mnJEmS1GnFgnZEzADOBl4DLACOiYgFDbP9GBjMzL2A\nRcA/VMtuA5wBvBA4ADgjIrYuVaskSZLUaTPHuyEi9ptowcy8ucm6DwCWZebd1fouBI4Abq9bx1V1\n8/8IeGt1+dXA9zPzV9Wy3wcOAy5ocp+SJEnStDBu0AY+Wf2fDQwCPwEC2AsYAl7cZN07AffWXV9B\nrYV6PO8A/mOCZXdqXCAiTgJOAthll12alCNJkiRNnXG7jmTmyzPz5cD9wH6ZOZiZLwD2BVZ2soiI\neCu1MP+P7SyXmedUdQ1uv/32nSxJkiRJmpRW+mjvnpm3jVzJzJ8Ce7Sw3Epg57rrcxgjoEfEocCH\ngcMzc3U7y0qSJEnTVStB+9aIODciDq7+vgDc2sJyi4H5ETEvIjYFjgYuqZ8hIvYFPk8tZD9Qd9MV\nwKsiYuvqJMhXVdMkSZKknjBRH+0RJwDvBt5bXf8h8LlmC2Xmmog4hVpAngGcl5lLIuJMYCgzL6HW\nVWQL4OsRAXBPZh6emb+KiI9TC+sAZ46cGClJkiT1gsjM5jNFPA3YJTOXli9pwwwODubQ0FBX7jsC\nWtiMkiRJ6qBuZbCIuCkzB5vN17TrSEQcDtwCfLe6vk9EXDLxUpIkSdLGrZU+2mdQGxP71wCZeQsw\nr2RRkiRJUq9rJWj/ITMfaZhmRwlJkiRpAq2cDLkkIt4CzIiI+cCpwHVly5IkSZJ6Wyst2n8BPB9Y\nDXwVeAR4X8miJEmSpF7XSov2C4C/ycwPj0yIiP2Am4tVJUmSJPW4Vlq0rwCujIhn1U07t1A9kiRJ\nUl9oJWgvpfbDMtdExIHVtChXkiRJktT7Wuk6kpl5aUQsBS6KiPNw1BFJkiRpQq20aAdAZt4JvLT6\n26tkUZIkSVKva9qinZn71l1+FHhTROxStCpJkiSpx40btCPirzLzHyLi0+PMcmqhmiRJkqSeN1GL\n9h3V/5umohBJkiSpn4wbtDPzO9X/f5u6ciRJkqT+MFHXke8wwegimXl4kYokSZKkPjBR15FPTFkV\nkiRJUp+ZqOvINVNZiCRJktRPmg7vFxHzgb8DFgCzR6Zn5q4F65IkSZJ6Wis/WPMl4HPAGuDlwJeB\nfy9ZlCRJktTrWgnaT8vMHwCRmcsz86PAa8uWJUmSJPW2pl1HgNURsQlwZ0ScAqwEtihbliRJktTb\nWmnRfi+wObVfgnwB8GfA20oWJUmSJPW6pi3ambm4uvgocELZciRJkqT+0MqoI4PAh4G59fNn5l4F\n65IkSZJ6Wit9tL8CfAC4DXiybDmSJElSf2glaK/KzEuKVyJJkiT1kVaC9hkRcS7wA2D1yMTM/Gax\nqiRJkqQe10rQPgF4HjCLp7qOJGDQliRJksbRStDePzN3L16JJEmS1EdaGUf7uohYULwSSZIkqY+0\n0qL9IuCWiPg5tT7aAaTD+0mSJEnjayVoH1a8CkmSJKnPTBi0I2IGcEVmPm+K6pEkSZL6woR9tDNz\nLbA0InaZonokSZKkvtBK15GtgSURcSPwu5GJmXl4saokSZKkHtdK0P7r4lVIkiRJfaZp0M7MayLi\n2cD+1aQbM/OBsmVJkiRJva3pONoR8SbgRuCNwJuAGyLiqNKFSZIkSb2sla4jH6b265APAETE9sB/\nAotKFiZJkiT1slZ+GXKThq4iD7W4nCRJkrTRaqVF+7sRcQVwQXX9zcDl5UqSJEmSel8rJ0N+ICL+\nFDiomnROZl5ctixJkiSpt7XSok1mfgP4RuFaJEmSpL7RyqgjfxIRd0bEIxHxm4j4bUT8ZiqKkyRJ\nknpVKy3a/wC8PjPvKF2MJEmS1C9aGT3kl4ZsSZIkqT2ttGgPRcRFwLeA1SMTM/ObxaqSJEmSelwr\nQXsr4DHgVXXTEjBoS5IkSeNoZXi/E6aiEEmSJKmf+AuPkiRJUgEGbUmSJKkAg7YkSZJUQCs/WPPe\niNgqar4YETdHxKuaLSdJkiRtzFpp0X57Zv6G2qgjWwN/BpxVtCpJkiSpx7UStKP6/z+A8zNzSd00\nSZIkSWNoJWjfFBHfoxa0r4iILYEny5YlSZIk9bZWfrDmHcA+wN2Z+VhEbAs4trYkSZI0gVZatL+f\nmTdn5q8BMvMh4J/LliVJkiT1tnFbtCNiNrA5sF1EbM1T/bK3AnaagtokSZKknjVR15E/B94H7Ajc\nxFNB+zfAZwrXJUmSJPW0cYN2Zv4L8C8R8ReZ+a9TWJMkSZLU85qeDJmZ/xoRBwID9fNn5pcL1iVJ\nkiT1tKZBOyLOB3YDbgHWVpMTMGhLkiRJ42hleL9BYEFmZuliJEmSpH7RyvB+PwX+qHQhkiRJUj9p\npUV7O+D2iLgRWD0yMTMPL1aVJEmS1ONaCdofLV2EJEmS1G9aGXXkmoiYC8zPzP+MiM2BGeVLkyRJ\nknpX0z7aEXEisAj4fDVpJ+BbJYuSJEmSel0rJ0OeDBxE7Rchycw7gWeVLEqSJEnqda0E7dWZ+cTI\nlYiYSW0cbUmSJEnjaCVoXxMRHwKeFhGvBL4OfKdsWZIkSVJvayVonw6sAm4D/hy4HPhIyaIkSZKk\nXtfK8H5HAl/OzC+ULkaSJEnqF620aL8e+O+IOD8iXlf10ZYkSZI0gaZBOzNPAJ5DrW/2McBdEXFu\n6cIkSZKkXtZKizaZ+QfgP4ALgZuodSdpKiIOi4ilEbEsIk4f4/aXRsTNEbEmIo5quG1tRNxS/V3S\nyv1JkiRJ00XTbiAR8RrgzcDBwNXAucCbWlhuBnA28EpgBbA4Ii7JzNvrZrsHOB54/xir+H1m7tPs\nfiRJkqTpqJX+1scBFwF/npmr21j3AcCyzLwbICIuBI4A1gXtzByubnuyjfVKkiRJ014rfbSPAX4M\n/DFARDwtIrZsYd07AffWXV9RTWvV7IgYiogfRcSYXVUi4qRqnqFVq1a1sWpJkiSprKZBOyJOBBYB\nn68mzQG+VbKoytzMHATeAnwqInZrnCEzz8nMwcwc3H777aegJEmSJKk1rZwMeTJwEPAbgMy8E3hW\nC8utBHauuz6nmtaSzFxZ/b+bWt/wfVtdVpIkSeq2VoL26sx8YuRKNY52trDcYmB+RMyLiE2Bo4GW\nRg+JiK0jYrPq8nbUgv7tEy8lSZIkTR+tBO1rIuJDwNMi4pXUxtP+TrOFMnMNcApwBXAH8LXMXBIR\nZ0bE4QARsX9ErADeCHw+IpZUi+8BDEXET4CrgLMaRiuRJEmSprXInLhxOiI2Ad4BvAoIasH53Gy2\n4BQbHBzMoaGhrtx3BEyvrSFJktT/upXBIuKm6lzCCTUd3i8znwS+UP1JkiRJakFLvwwpSZIkqT0G\nbUmSJKmAcYN2RJxf/X/v1JUjSZIk9YeJWrRfEBE7Am+vhtvbpv5vqgqUJEmSetFEJ0P+H+AHwK7A\nTdRGHBmR1XRJkiRJYxi3RTszP52ZewDnZeaumTmv7s+QLUmSJE2gleH93h0RewN/XE36YWbeWrYs\nSZIkqbc1HXUkIk4FvgI8q/r7SkT8RenCJEmSpF7WtEUbeCfwwsz8HUBE/D1wPfCvJQuTJEmSelkr\n42gHsLbu+lrWPzFSkiRJUoNWWrS/BNwQERdX148EvliuJEmSJKn3tXIy5D9FxNXAS6pJJ2Tmj4tW\nJUmSJPW4Vlq0ycybgZsL1yJJkiT1jVb6aEuSJElqk0FbkiRJKmDCoB0RMyLiqqkqRpIkSeoXEwbt\nzFwLPBkRz5iieiRJkqS+0MrJkI8Ct0XE94HfjUzMzFOLVSVJkiT1uFaC9jerP0mSJEktamUc7X+L\niKcBu2Tm0imoSZIkSep5TUcdiYjXA7cA362u7xMRl5QuTJIkSeplrQzv91HgAODXAJl5C7BrwZok\nSZKkntdK0P5DZj7SMO3JEsVIkiRJ/aKVkyGXRMRbgBkRMR84FbiubFmSJElSb2ulRfsvgOcDq4EL\ngN8A7ytZlCRJktTrWhl15DHgwxHx97Wr+dvyZUmSJEm9rZVRR/aPiNuAW6n9cM1PIuIF5UuTJEmS\nelcrfbS/CLwnM/8LICJeAnwJ2KtkYZIkSVIva6WP9tqRkA2QmdcCa8qVJEmSJPW+cVu0I2K/6uI1\nEfF5aidCJvBm4OrypUmSJEm9a6KuI59suH5G3eUsUIskSZLUN8YN2pn58qksRJIkSeonTU+GjIhn\nAscBA/XzZ+ap5cqSJEmSelsro45cDvwIuA1/el2SJElqSStBe3Zm/mXxSiRJkqQ+0srwfudHxIkR\nsUNEbDPyV7wySZIkqYe10qL9BPCPwId5arSRBHYtVZQkSZLU61oJ2v8TeE5mPli6GEmSJKlftNJ1\nZBnwWOlCJEmSpH7SSov274BbIuIqYPXIRIf3kyRJksbXStD+VvUnSZIkqUVNg3Zm/ttUFCJJkiT1\nk1Z+GfLnPDXayDqZ6agjkiRJ0jha6ToyWHd5NvBGwHG0JUmSpAk0HXUkMx+q+1uZmZ8CXjsFtUmS\nJEk9q5WuI/vVXd2EWgt3Ky3hkiRJ0karlcD8ybrLa4Bh4E1FqpEkSZL6RCujjrx8KgqRJEmS+kkr\nXUc2A/4UGKifPzPPLFeWJEmS1Nta6TrybeAR4CbqfhlSkiRJ0vhaCdpzMvOw4pVIkiRJfaTp8H7A\ndRGxZ/FKJEmSpD7SSov2S4Djq1+IXA0EkJm5V9HKJEmSpB7WStB+TfEqJEmSpD7TyvB+y6eiEEmS\nJKmftNJHW5IkSVKbDNqSJElSAQZtSZIkqQCDtiRJklSAQVuSJEkqwKAtSZIkFWDQliRJkgowaEuS\nJEkFGLQlSZKkAgzakiRJUgEGbUmSJKkAg7YkSZJUgEFbkiRJKsCgLUmSJBVg0JYkSZIKMGhLkiRJ\nBRi0JUmSpAIM2pIkSVIBBm1JkiSpAIO2JEmSVIBBW5IkSSqgaNCOiMMiYmlELIuI08e4/aURcXNE\nrImIoxpue1tE3Fn9va1knZIkSVKnFQvaETEDOBt4DbAAOCYiFjTMdg9wPPDVhmW3Ac4AXggcAJwR\nEVuXqlWSJEnqtJIt2gcAyzLz7sx8ArgQOKJ+hswczsxbgScbln018P3M/FVmPgx8HzisYK2SJElS\nR5UM2jsB99ZdX1FN69iyEXFSRAxFxNCqVas2uFBJkiSp03r6ZMjMPCczBzNzcPvtt+92OZIkSdI6\nJYP2SmDnuutzqmmll5UkSZK6rmTQXgzMj4h5EbEpcDRwSYvLXgG8KiK2rk6CfFU1TZIkSeoJxYJ2\nZq4BTqEWkO8AvpaZSyLizIg4HCAi9o+IFcAbgc9HxJJq2V8BH6cW1hcDZ1bTJEmSpJ4QmdntGjpi\ncHAwh4aGunLfEdAnm1GSJKlndCuDRcRNmTnYbL6ePhlSkiRJmq4M2pIkSVIBBm1JkiSpAIO2JEmS\nVIBBW5IkSSrAoC1JkiQVYNCWJEmSCjBoS5IkSQUYtCVJkqQCDNqSJElSAQZtSZIkqQCDtiRJklSA\nQVuSJEkqwKAtSZIkFWDQliRJkgowaEuSJEkFGLQlSZKkAgzakiRJUgEGbUmSJKkAg7YkSZJUgEFb\nkiRJKsCgLUmSJBVg0JYkSZIKMGhLkiRJBRi0JUmSpAIM2pIkSVIBBm1JkiSpAIO2JEmSVIBBW5Ik\nSSrAoC1JkiQVYNCWJEmSCjBoS5IkSQUYtCVJkqQCDNqSJElSAQZtSZIkqQCDtiRJklSAQVuSJEkq\nwKAtSZIkFWDQliRJkgowaEuSJEkFGLQlSZKkAgzakiRJUgEGbUmSJKkAg7YkSZJUgEFbkiRJKsCg\nLUmSJBVg0JYkSZIKMGhLkiRJBRi0JUmSpAIM2pIkSVIBBm1JkiSpAIO2JEmSVIBBW5IkSSrAoC1J\nkiQVYNCWJEmSCjBoS5IkSQUYtCVJkqQCDNqSJElSAQZtSZIkqQCDtiRJklSAQVuSJEkqwKAtSZIk\nFWDQliRJkgowaEuSJEkFGLQlSZKkAgzakiRJUgEGbUmSJKkAg7YkSZJUgEFbkiRJKsCgLUmSJBVg\n0JYkSZIKMGhLkiRJBRi0JUmSpAIM2pIkSVIBBm1JkiSpAIO2JEmSVEDRoB0Rh0XE0ohYFhGnj3H7\nZhFxUXX7DRExUE0fiIjfR8Qt1d//KVmnJEmS1GkzS604ImYAZwOvBFYAiyPiksy8vW62dwAPZ+Zz\nIuJo4O+BN1e33ZWZ+5SqT5IkSSqpZIv2AcCyzLw7M58ALgSOaJjnCODfqsuLgFdERBSsSZIkSZoS\nJYP2TsC9dddXVNPGnCcz1wCPANtWt82LiB9HxDUR8cdj3UFEnBQRQxExtGrVqs5WL0mSJE3CdD0Z\n8n5gl8zcF/hL4KsRsVXjTJl5TmYOZubg9ttvP+VFSpIkSeMpGbRXAjvXXZ9TTRtznoiYCTwDeCgz\nV2fmQwCZeRNwF/DcgrVKkiRJHVUyaC8G5kfEvIjYFDgauKRhnkuAt1WXjwKuzMyMiO2rkymJiF2B\n+cDdBWuVJEmSOqrYqCOZuSYiTgGuAGYA52Xmkog4ExjKzEuALwLnR8Qy4FfUwjjAS4EzI+IPwJPA\nuzLzV6VqlSRJkjotMrPbNXTE4OBgDg0NdeW+I6BPNqMkSVLP6FYGi4ibMnOw2XzT9WRISZIkqacZ\ntCVJkqQCDNqSJElSAQZtSZIkqQCDtiRJklSAQVuSJEkqwKAtSZIkFWDQliRJkgowaEuSJEkFGLQl\nSZKkAgzakiRJUgEGbUmSJKkAg7YkSZJUgEFbkiRJKsCgLUmSJBVg0JYkSZIKMGhLkiRJBRi0JUmS\npAIM2pIkSVIBBm1JkiSpAIO2JEmSVIBBW5IkSSrAoC1JkiQVYNCWJEmSCjBoS5IkSQUYtCVJkqQC\nDNqSJElSAQZtSZIkqQCDtiRJklSAQVuSJEkqwKAtSZIkFWDQliRJkgowaEuSJEkFGLQlSZKkAgza\nkiRJUgEGbUmSJKkAg7YkSZJUgEFbkiRJKsCgLUmSJBVg0JYkSZIKMGhLkiRJBRi0JUmSpAIM2pIk\nSVIBBm1JkiSpAIO2JEmSVIBBW5IkSSrAoC1JkiQVYNCWJEmSCjBoS5IkSQUYtCVJkqQCDNqSJElS\nAQZtSZIkqQCDtiRJklSAQVuSJEkqwKAtSZIkFWDQliRJkgowaEuSJEkFGLQlSZKkAgzakiRJUgEG\nbUmSJKkAg7YkSZJUgEFbkiRJKsCgLUmSJBVg0JYkSZIKMGhLkiRJBRi0JUmSpAIM2pIkSVIBBm1J\nkiSpAIO2JEmSVIBBW5IkSSrAoC1JkiQVYNCWJEmSCjBoS5IkSQUYtCVJkqQCDNqSJElSAQZtSZIk\nqQCDtiRJklRA0aAdEYdFxNKIWBYRp49x+2YRcVF1+w0RMVB32wer6Usj4tUl65QkSZI6rVjQjogZ\nwNnAa4AFwDERsaBhtncAD2fmc4B/Bv6+WnYBcDTwfOAw4LPV+iRJkqSeULJF+wBgWWbenZlPABcC\nRzTMcwTwb9XlRcArIiKq6Rdm5urM/DmwrFqfJEmS1BNmFlz3TsC9dddXAC8cb57MXBMRjwDbVtN/\n1LDsTo13EBEnASdVVx+NiKWdKb19Ed2657ZsBzzY7SL6mNu3HLdtOW7bsty+5bhty+mpbdulDDa3\nlZlKBu3iMvMc4Jxu19ErImIoMwe7XUe/cvuW47Ytx21bltu3HLdtOW7bzinZdWQlsHPd9TnVtDHn\niYiZwDOAh1pcVpIkSZq2SgbtxcD8iJgXEZtSO7nxkoZ5LgHeVl0+CrgyM7OafnQ1Ksk8YD5wY8Fa\nJUmSpI4q1nWk6nN9CnAFMAM4LzOXRMSZwFBmXgJ8ETg/IpYBv6IWxqnm+xpwO7AGODkz15aqdSNi\nN5uy3L7luG3LcduW5fYtx21bjtu2Q6LWgCxJkiSpk/xlSEmSJKkAg7YkSZJUgEG7j0XEGyNiSUQ8\nGRHjDtMTEcMRcVtE3BIRQ1NZYy9rY/seFhFLI2JZRJw+lTX2qojYJiK+HxF3Vv+3Hme+tdV+e0tE\nNJ5srTrN9sPq5POLqttviIiBqa+yN7WwbY+PiFV1++o7u1FnL4qI8yLigYj46Ti3R0R8utr2t0bE\nflNdY69qYdseHBGP1O23fzPVNfYDg3Z/+ynwJ8APW5j35Zm5j+NmtqXp9o2IGcDZwGuABcAxEbFg\nasrraacDP8jM+cAPqutj+X213+6T/7+9e42Rq6zjOP79QUUCghgXCkWkIA00QoAYGolEBU3RYloM\nd2LkHgEJ4Y2JCS+MJETKGxM1UEwl5S6lCVKhFhQKqKGBgiKXcqmNQguCGig2Crjy88V5Voft7uxs\nO2dmz/T3STb7zLnNf/95ZvY/5zxzHnt+78Jrlg774XnAG7YPAr4PLOxtlM00idf47S19dXFPg2y2\nJcCX2qz/MtWdyWZRTWB3bQ9iGhRLaJ9bgF+39NsrehDTwEmhPcBsr7Xdt9kyB12H+Z0DrLO93va7\nwE+BBfVH13gLgBtK+wbgxD7GMgg66YetOV8GfEFqyJy3/ZXXeI1sP0x1V7LxLABudGU1sIekfXoT\nXbN1kNvoghTaAWDgPkmPl2nto3v2BV5uebyhLIv2ptt+tbT/AkwfZ7udJa2RtFpSivHxddIP/7eN\n7WFgE/DRnkTXbJ2+xk8qQxuWSdpvjPWxdfIeW6+jJT0p6ReSPtnvYJqo0VOwB0j6FbD3GKsut31X\nh4c5xvZGSXsBv5T0XPmku93rUn5jDO1y2/rAtiWNdx/S/UvfPRB4QNJTtv/Y7VgjttHPgdtsvyPp\nG1RXDo7rc0wRE3mC6j12s6R5wM+ohujEJKTQbjjbX+zCMTaW369LupPqUmgKbbqS341A69mrj5Vl\n2712uZX0mqR9bL9aLgO/Ps4xRvruekkPAkcCKbS31Ek/HNlmg6RpwIeBv/cmvEabMLe2W/O4GLi6\nB3FtL/IeWxPbb7W0V0i6RtKQ7b/1M66mydCR7ZykXSXtNtIG5lJ9yS+64zFglqQDJO1ENftp7o4x\nseXAWaV9FrDF1QNJH5H0wdIeAj5DNZtsbKmTftia85OBB5wZzToxYW5HjRmeD6ztYXyDbjnw9XL3\nkU8Dm1qGncU2kLT3yPc0JM2hqhnz4XuSckZ7gEn6KvBDYE/gHkm/t328pBnAYtvzqMa+3lleS9OA\nW22v7FvQDdJJfm0PS7oEuBfYEbje9jN9DLsprgKWSjoP+DNwKkC5jeKFts8HZgPXSXqP6h/AVbZT\naI9hvH4o6Qpgje3lwE+AmySto/qC1On9i7g5OsztpZLmA8NUuT27bwE3jKTbgM8DQ5I2AN8BPgBg\nexGwApgHrAP+CZzTn0ibp4PcngxcJGkY+Bdwej58T16mYI+IiIiIqEGGjkRERERE1CCFdkRERERE\nDVJoR0RERETUIIV2REREREQNUmhHRERERNQghXZERERERA1SaEdETFGSNm/DvpdJ2qWb8bR5rrMl\n/WicdSsk7dGLOCIippoU2hERg+kyoCeFdjtl4qY3+x1HREQ/pNCOiGgASd+S9JikP0j6blk2U9Jz\nkm6RtFbSMkm7SLoUmAGskrSqbHuGpKckPS1pYctxN0u6UtKTklZLmt4mhiWSFklaI+kFSV9pWT1D\n0kpJL0q6umWfP0ka6npCIiIaIIV2RMQUJ2kuMAuYAxwBfErSZ8vqg4FrbM8G3gIutv0D4BXgWNvH\nSpoBLASOK/sfJenEsv+uwGrbhwMPAxdMEM7MEscJwCJJO5flRwCnAYcBp0nabxv/7IiIxkuhHREx\n9c0tP78DngAOoSq8AV62/dvSvhk4Zoz9jwIetP1X28PALcBIof4ucHdpP05VSLez1PZ7tl8E1pdY\nAO63vcn228CzwP6T+PsiIgbStH4HEBERExLwPdvXvW+hNBPwqG1HP57Iv22P7PMfJv6/MN7zvdOy\nrJPjREQMvJzRjoiY+u4FzpX0IQBJ+0raq6z7uKSjS/tM4Del/Q9gt9J+FPicpCFJOwJnAA9tZSyn\nSNpB0ieAA4Hnt/I4EREDL2ccIiKmONv3SZoNPCIJYDPwNaozx88D35R0PdWQjWvLbj8GVkp6pYzT\n/jawiurs+D2279rKcLbFeXEAAAB8SURBVF6iKtx3By60/XaJKSIiRtH/rxhGRESTlKEjd9s+tEfP\nt6Q837JePF9ERNNl6EhERERERA1yRjsiIt5H0uXAKaMW32H7yn7EExHRVCm0IyIiIiJqkKEjERER\nERE1SKEdEREREVGDFNoRERERETVIoR0RERERUYP/AhzMAe9bujhmAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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lDgDA2lBV57TWNi213bhPSgQAgIkmUI/T4KURV/1lEQEA2J6RXSmRIcy/NGKN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\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Pp7tHQmv06xw12MyG9ZuO3T3VGtu90BwHe8ps0e4BY33z74edUludbhnoYEvG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\ngg==\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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IcktV7ZLkW1V1SpKrkuwx3LIAAGA8DNKhflmS3dNbGfERSX49yX8bZlEAADAu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\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Qdy1J462zfCpJqsyiCXVmPrrj69sz8/nAXn1c+3pgj4791e1j8/kYcHQf15VU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\nCVvSHu+KAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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qi4nZYYjRTpckdaex8ZT76Afc6Nr5457SynXzO12SJLWFQVttMTE7jLKg0yV1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\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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F0y0HAAAWvklG51ia5E+S7DRz/e5+1BTrAgCABWuSPtEfTvKaJOcnuW265QAA\nwMI3SYhe3t2fnnolAACwnpgkRL+xqt6X5CtJbl4xs7s/MbWqAABgAZskRL8oySOSLMod3Tk6iRAN\nAMAGaZIQvU937zL1SgAAYD0xyTjRZ1TVblOvBAAA1hOTtEQ/LsmyqvphRn2iK0kb4g4AgA3VJCH6\nmWuz46p6YJIPJdkuoz7Ux3T3/62qrZOckGRJkkuSPK+7r1mbYwAAwHxYY3eOqto4yRe6+9KVpwn2\nfUuSP+zu3TJqzX7luFvI65J8pbt3zmjEj9fdxc8AAABzao0hurtvTXJxVT1o6I67+4ruPm/8+vok\nFyV5QJLnJPngeLUPJjlo6L4BAGA+TdKdY6skF1bVWUl+uWJmdx846UGqakmSRyf5RpLtuvuK8aKf\nZtTdY1XbHJnkyCR50IMGZ3gAAJiaSUL0n96VA1TV5kk+nuTV3X1dVd2+rLu7qnpV23X3MUmOSZKl\nS5euch0AAJgPsw5x192nJvluki3G00XjebOqqkUZBegPz3jC4c+qavvx8u2TXLk2hQMAwHyZNURX\n1fOSnJXkt5M8L8k3quqQCbarJMdmFLr/asaiTyd54fj1C5N8amjRAAAwnybpzvEnGT218Mokqapt\nk3w5yYmzbPeEJL+b5PyqWjae9/okb03y0ap6SZJLMwrmAACw3pgkRG+0IkCPXZ3JuoGcntGDWVbl\naRMcFwAAFqRJQvTnq+oLSY4fv/+dJJ+bXkkAALCwzRqiu/s1VfXcjLpnJKMnD5403bIAAGDhmqQl\nOt398YxG2QAAgA3eJKNz/Leq+l5VXVtV11XV9VV13VwUBwAAC9EkLdH/J8mzu/uiaRcDAADrg1lb\nopP8TIAGAIA7TNISfU5VnZDkk0luXjFzxhMIAQBggzJJiN4yyY1JnjFjXicRogEA2CBNMsTdi+ai\nEAAAWF9M0icaAACYQYgGAICBhGgAABhokoetvKqqtqyRY6vqvKp6xmzbAQDA3dUkLdEv7u7rMhqd\nY6skv5vkrVOtCgAAFrBJQnSNv/5mkuO6+8IZ8wAAYIMzSYg+t6q+mFGI/kJVbZHktumWBQAAC9ck\nD1t5SZK9kvx7d99YVfdNYuxoAAA2WJO0RH+pu8/r7l8kSXdfneSd0y0LAAAWrtW2RFfV4iT3TLJN\nVW2VO/pBb5nkAXNQGwAALEhr6s7xe0lenWSHJOfmjhB9XZK/nXJdAACwYK02RHf3/03yf6vqD7r7\nb+awJgAAWNBmvbGwu/+mqvZLsmTm+t39oSnWBQAAC9asIbqqjkvy0CTLktw6nt1JhGgAADZIkwxx\ntzTJbt3d0y4GAADWB5MMcXflCYDuAAASrklEQVRBkvtPuxAAAFhfTNISvU2S71TVWUluXjGzuw+c\nWlUAALCATRKi3zTtIgAAYH0yyegcp1bVTkl27u4vV9U9k2w8/dIAAGBhmrVPdFW9LMmJSf5hPOsB\nST45zaIAAGAhm+TGwlcmeUJGTypMd38vyf2mWRQAACxkk4Tom7v7P1e8qapNMhonGgAANkiThOhT\nq+r1STarqqcn+ViSz0y3LAAAWLgmCdGvS7I8yflJfi/J55K8YZpFAQDAQjbJEHcHJflQd7932sUA\nAMD6YJKW6Gcn+beqOq6qnjXuEw0AABusWUN0d78oycMy6gt9aJIfVNX7pl0YAAAsVBO1Knf3r6rq\nXzIalWOzjLp4vHSahQEAwEI1ycNWfqOqPpDke0mem+R9Se4/5boAAGDBmqQl+vAkJyT5ve6+ecr1\nAADAgjdJn+hDk3wzya8lSVVtVlVbTLswAABYqCbpzvGyJCcm+YfxrB2TfHKaRQEAwEI2yRB3r0zy\nhCTXJUl3fy/J/aZZFAAALGSThOibu/s/V7wZjxPd0ysJAAAWtklC9KlV9fokm1XV0zMaL/oz0y0L\nAAAWrklC9OuSLE9yfpLfS/K5JG+YZlEAALCQzTrEXXffluS94wkAADZ4k7REAwAAMwjRAAAw0GpD\ndFUdN/76qrkrBwAAFr41tUQ/pqp2SPLiqtqqqraeOc1VgQAAsNCs6cbCv0/ylSQPSXJukpqxrMfz\nAQBgg7Palujufld375rk/d39kO5+8IxJgAYAYIM1yRB3L6+qPZP82njWad397emWBQAAC9eso3NU\n1dFJPpzkfuPpw1X1B9MuDAAAFqpZW6KTvDTJY7v7l0lSVW9LcmaSv5lmYQAAsFBNMk50Jbl1xvtb\nc+ebDAEAYIMySUv0Pyb5RlWdNH5/UJJjp1cSAAAsbJPcWPhXVfW1JE8cz3pRd39zqlUBAMACNklL\ndLr7vCTnTbkWAABYL0zSJxoAAJhBiAYAgIHWGKKrauOqOmWuigEAgPXBGkN0d9+a5Laquvcc1QMA\nAAveJDcW3pDk/Kr6UpJfrpjZ3UdPrSoAAFjAJgnRnxhPAABAJhsn+oNVtVmSB3X3xXNQEwAALGiz\njs5RVc9OsizJ58fv96qqT0+w3fur6sqqumDGvDdV1eVVtWw8/eZdKR4AAObDJEPcvSnJvkl+kSTd\nvSzJQybY7gNJnrmK+e/s7r3G0+cmrBMAABaMSUL0r7r72pXm3TbbRt19WpKfr1VVAACwgE0Soi+s\nqv+eZOOq2rmq/ibJGXfhmEdV1bfH3T22Wt1KVXVkVZ1TVecsX778LhwOAADWrUlC9B8keWSSm5Mc\nn+S6JK9ey+O9J8lDk+yV5Iok71jdit19THcv7e6l22677VoeDgAA1r1JRue4McmfVNXbRm/7+rU9\nWHf/bMXrqnpvkpPXdl8AADBfJhmdY5+qOj/JtzN66Mq3quoxa3Owqtp+xtuDk1ywunUBAGChmuRh\nK8cmeUV3fz1JquqJSf4xyaPWtFFVHZ/kKUm2qarLkrwxyVOqaq8kneSSJL+31pUDAMA8mSRE37oi\nQCdJd59eVbfMtlF3H7qK2ccOKQ4AABai1Yboqtp7/PLUqvqHjG4q7CS/k+Rr0y8NAAAWpjW1RK88\ncsYbZ7zuKdQCAADrhdWG6O5+6lwWAgAA64tZ+0RX1X2SHJ5kycz1u/vo6ZUFAAAL1yQ3Fn4uyb8m\nOT8TPO4bAADu7iYJ0Yu7+/+beiUAALCemOSx38dV1cuqavuq2nrFNPXKAABggZqkJfo/k/xlkj/J\nHaNydJKHTKsoAABYyCYJ0X+Y5GHdfdW0iwEAgPXBJN05vp/kxmkXAgAA64tJWqJ/mWRZVZ2S5OYV\nMw1xBwDAhmqSEP3J8QQAAGSCEN3dH5yLQgAAYH0xyRMLf5g7RuW4XXcbnQMAgA3SJN05ls54vTjJ\nbycxTjQAABusWUfn6O6rZ0yXd/dfJ/mtOagNAAAWpEm6c+w94+1GGbVMT9KCDQAAd0uThOF3zHh9\nS5JLkjxvKtUAAMB6YJLROZ46F4UAAMD6YpLuHJsmeW6SJTPX7+63TK8sAABYuCbpzvGpJNcmOTcz\nnlgIAAAbqklC9I7d/cypVwIAAOuJWYe4S3JGVe0x9UoAAGA9MUlL9BOTHDF+cuHNSSpJd/ejploZ\nAAAsUJOE6N+YehUAALAemWSIu0vnohAAAFhfTNInGgAAmEGIBgCAgYRoAAAYSIgGAICBhGgAABhI\niAYAgIGEaAAAGEiIBgCAgYRoAAAYSIgGAICBhGgAABhIiAYAgIGEaAAAGEiIBgCAgYRoAAAYSIgG\nAICBhGgAABhIiAYAgIGEaAAAGEiIBgCAgYRoAAAYSIgGAICBhGgAABhIiAYAgIGEaAAAGEiIBgCA\ngYRoAAAYSIgGAICBhGgAABhIiAYAgIGEaAAAGEiIBgCAgYRoAAAYSIgGAICBhGgAABhIiAYAgIGE\naAAAGEiIBgCAgYRoAAAYSIgGAICBhGgAABhoaiG6qt5fVVdW1QUz5m1dVV+qqu+Nv241reMDAMC0\nTLMl+gNJnrnSvNcl+Up375zkK+P3AACwXplaiO7u05L8fKXZz0nywfHrDyY5aFrHBwCAaZnrPtHb\ndfcV49c/TbLd6lasqiOr6pyqOmf58uVzUx0AAExg3m4s7O5O0mtYfkx3L+3updtuu+0cVgYAAGs2\n1yH6Z1W1fZKMv145x8cHAIC7bK5D9KeTvHD8+oVJPjXHxwcAgLtsmkPcHZ/kzCS7VNVlVfWSJG9N\n8vSq+l6SA8bvAQBgvbLJtHbc3YeuZtHTpnVMAACYC55YCAAAAwnRAAAwkBANAAADCdEAADCQEA0A\nAAMJ0QAAMJAQDQAAAwnRAAAwkBANAAADCdEAADCQEA0AAAMJ0QAAMJAQDQAAAwnRAAAwkBANAAAD\nCdEAADCQEA0AAAMJ0QAAMJAQDQAAAwnRAAAwkBANAAADCdEAADCQEA0AAAMJ0QAAMJAQDQAAAwnR\nAAAwkBANAAADCdEAADCQEA0AAAMJ0QAAMJAQDQAAAwnRAAAwkBANAAADCdEAADCQEA0AAAMJ0QAA\nMJAQDQAAAwnRAAAwkBANAAADCdEAd1NLliRVd0xLlsx3RQB3H5vMdwEATMellybdd7yvmr9aAO5u\ntEQDAMBAQjQAAAwkRAMAwED6RAPcnd2pI3SvdjUAhhGiAe7O7nRn4fyVAXB3ozsHAAAMJEQDAMBA\nQjQAAAwkRAMAwEBCNAAADCREAwDAQEI0AAAMJEQDAMBAQjQAAAwkRAMAwEBCNAAADCREAwDAQEI0\nAAAMJEQDAMBAQjQAAAwkRAMAwEBCNAAADCREAwDAQEI0AAAMJEQDAMBAm8zHQavqkiTXJ7k1yS3d\nvXQ+6gAAgLUxLyF67KndfdU8Hh8AANaK7hwAADDQfIXoTvLFqjq3qo5c1QpVdWRVnVNV5yxfvnyO\nywMAgNWbrxD9xO7eO8lvJHllVT1p5RW6+5juXtrdS7fddtu5rxAAAFZjXkJ0d18+/nplkpOS7Dsf\ndQAAwNqY8xBdVfeqqi1WvE7yjCQXzHUdAACwtuZjdI7tkpxUVSuO/5Hu/vw81AEAAGtlzkN0d/97\nkj3n+rgAALCuGOIOAAAGEqIBAGAgIRoAAAYSogEAYCAhGgAABhKiAQBgICEaAAAGEqIBAGAgIRoA\nAAYSogEAYCAhGgAABhKiAQBgICEaAAAGEqIBAGAgIRoAAAYSogEAYCAhGgAABhKiAQBgICEaAAAG\nEqIBAGAgIRoAAAYSogEAYCAhGgAABhKiAQBgICEaAAAGEqIBAGAgIRoAAAYSogEAYCAhGgAABhKi\nAQBgICEaAAAGEqIBAGAgIRoAAAYSogEAYCAhGgAABhKiAQBgICEaAAAGEqIBAGAgIRoAAAYSogEA\nYCAhGgAABhKiAQBgICEaAAAGEqIBAGAgIRoAAAYSogEAYCAhGgAABhKiAQBgICEaAAAGEqIBAGAg\nIRoAAAYSogEAYCAhGgAABhKiAQBgICEaAAAGEqIBAGAgIRoAAAYSogEAYCAhGgAABhKiAQBgICEa\nAAAGEqIBAGAgIRoAAAYSogEAYCAhGgAABhKiAQBgICEaAAAGmpcQXVXPrKqLq+r7VfW6+agBAADW\n1pyH6KraOMm7k/xGkt2SHFpVu811HQAAsLbmoyV63yTf7+5/7+7/TPLPSZ4zD3UAAMBa2WQejvmA\nJD+e8f6yJI9deaWqOjLJkeO3N1TVxXNQ28q2qcpVM2dUzUMVrC+2Se58vcAspn7NrPwzy8+w9Zqf\nMQyx3l0vC+jn1U6TrDQfIXoi3X1MkmPms4aqOqe7l85nDaw/XC8M5ZphCNcLQ7hepm8+unNcnuSB\nM97vOJ4HAADrhfkI0Wcn2bmqHlxV90jy/CSfnoc6AABgrcx5d47uvqWqjkryhSQbJ3l/d18413VM\naF67k7Decb0wlGuGIVwvDOF6mbLq7vmuAQAA1iueWAgAAAMJ0QAAMJAQndkfQ15Vm1bVCePl36iq\nJXNfJQvFBNfLEVW1vKqWjaeXzkedLAxV9f6qurKqLljN8qqqd42vp29X1d5zXSMLxwTXy1Oq6toZ\nP1/+bK5rZGGoqgdW1SlV9Z2qurCqXrWKdfx8maINPkRP+BjylyS5prsfluSdSd42t1WyUAx4bP0J\n3b3XeHrfnBbJQvOBJM9cw/LfSLLzeDoyyXvmoCYWrg9kzddLknx9xs+Xt8xBTSxMtyT5w+7eLcnj\nkrxyFf8f+fkyRRt8iM5kjyF/TpIPjl+fmORpVZ77tYHy2HoG6e7Tkvx8Das8J8mHeuRfk9ynqraf\nm+pYaCa4XiBJ0t1XdPd549fXJ7koo6dCz+TnyxQJ0at+DPnKF+Ht63T3LUmuTXLfOamOhWaS6yVJ\nnjv+09mJVfXAVSyHFSa9pmCFx1fVt6rqX6rqkfNdDPNv3M300Um+sdIiP1+mSIiGde8zSZZ096OS\nfCl3/BUD4K46L8lO3b1nkr9J8sl5rod5VlWbJ/l4kld393XzXc+GRIie7DHkt69TVZskuXeSq+ek\nOhaaWa+X7r66u28ev31fksfMUW2snyb5GQRJku6+rrtvGL/+XJJFVbXNPJfFPKmqRRkF6A939ydW\nsYqfL1MkRE/2GPJPJ3nh+PUhSb7anlKzoZr1elmpv9mBGfVTg9X5dJLDx3fRPy7Jtd19xXwXxcJU\nVfdfcU9OVe2b0f/jGnU2QOPr4NgkF3X3X61mNT9fpmjOH/u90KzuMeRV9ZYk53T3pzO6SI+rqu9n\ndMPH8+evYubThNfL0VV1YEZ3Tv88yRHzVjDzrqqOT/KUJNtU1WVJ3phkUZJ0998n+VyS30zy/SQ3\nJnnR/FTKQjDB9XJIkpdX1S1J/iPJ8zXqbLCekOR3k5xfVcvG816f5EGJny9zwWO/AQBgIN05AABg\nICEaAAAGEqIBAGAgIRoAAAYSogEAYCAhGgAABhKiAeZYVZ2xhmX3qapXTLCPz1fVL6rq5AnWvWSS\np9pV1etnWweAESEaYI51935rWHyfJLOG6CR/mdGDFtYlIRpgQkI0wByrqhvGX19TVWdX1ber6s3j\nxW9N8tCqWlZVf7m6fXT3V5JcP+Cw/6Oqzq+qs6rqYauo6a1JNhsf98PjeZ+sqnOr6sKqOnLGui+p\nqn8b7+u9VfW3A+oAuFvY4B/7DTAfquoZSXZOsm+SSvLpqnpSktcl2b2791rHh7y2u/eoqsOT/HWS\nZ81c2N2vq6qjVjrui7v751W1WZKzq+rjSTZN8qdJ9s4oxH81ybfWca0AC54QDTA/njGevjl+v3lG\nofpHUzre8TO+vnPCbY6uqoPHrx+YUX33T3Jqd/88SarqY0kevi4LBVgfCNEA86OS/EV3/8OdZlYt\nmdLxeubrqto4ybnj95/u7j9bqY6nJDkgyeO7+8aq+lqSxVOqDWC9o080wPz4QpIXV9XmSVJVD6iq\n+2XURWKLKRzvd2Z8PbO7b+3uvcbTigD9q6paNH597yTXjAP0I5I8bjz/7CRPrqqtqmqTJM+dQq0A\nC56WaIC51939xaraNcmZVZUkNyR5QXf/oKr+X1VdkORfuvs1q9pBVX09ySOSbF5VlyV5SXd/YQ3H\n3Kqqvp3k5iSHrmadY5J8u6rOS/LiJL9fVRcluTjJv44Lv7yq/neSs5L8PMl3k1w76NMD3A1Ud8++\nFgDrRFXdN8l53b3TfNeytqpq8+6+YdwSfVKS93f3SfNdF8Bc0p0DYI5U1Q5Jzkzy9vmu5S56U1Ut\nS3JBkh8m+eQ81wMw57REAyxQVbVHkuNWmn1zdz92NeuflOTBK81+7SzdPABYC0I0AAAMpDsHAAAM\nJEQDAMBAQjQAAAwkRAMAwED/PzJszShlcmboAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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uyUVV9b30xlBXkmbaPAAAGCxQHzH0KgAAYExtNlBX1fZJPtdae/gi1QMAAGNl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\nQIS6zZfzAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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e7d2Bexq21wIvaD0oIk4H3g1sAxzWcO73W87dfZRzTwVOBdhzzz1nJGhJkiRp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\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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vegxsB7gRDdr9aBDel7V4Du2MLT5srQ/t6PSHq9tYqqcO/+86woYGkX20C/Cg\nlOkbbwHf2P6Jg6A228ADZQZPLd54GnT2My+gzz9YhiEv2aJdwDAOQbSpatECXljPt0Frf5/xaRp8\nU31pGvAuAtLA6vkHy+SGIS/Zoj0AhuEbYR30ecPB1JYtW7e1OnPjdtLTOKq+9ttsWPgrhvpBh3cY\nfnaur9/2ya2vUR1fJ1u0e6WDLUTD8I2wDvq84aB7ptFvcxC2WS0O/C2oNic6GoRW+UF4DpuiwzuM\nWnx2dnkH02/75GUjh8Ly5etOHBmBGoVtg3aveACYNBD67YNpKp3+3F4vrEDfBZaREYjluc7tWvJz\no/91+stQ3XYwnTYAz9+gLUl1solJeQA+t6ZtGJ/zpur0CCBDcwiIX4bUwqAtSaV1spXL1DgQpvt9\nqdtdlDrdrcK3rYaVQVuSSrOVSy2mGzwNqvU37MdzDCtHHZE0XKYxKoqGQ6dHnxiEkRLUea0DO/nl\naTjYol3CFF9b/Va7kabx83vfbuNhHzWgH9i63Pe6fYbAjneTqMEBopK6w6BdwhRfU/0Wu5EGYdg4\nQ960eErm4VSLYdcmMzRH/vW3bu8/+raBRz1l0B4C7vMH1BDs1WsfuHpgCN4W/a9vv+kPl/XGYC48\n/rIv+0YYgh2WQXsIlPjnt6WxD/ThXn0I9pkdNzJjBRGz17kNsydeYAqdfltM+Zr6TX4o1eJ/fap/\nhlo8iQHXh59jnWbQ1kaxpXH6hmGfPgT7zI5btro1VG98yC5hyte0yDf5IfhnqbmB+F8fiCehfmfQ\nlrrEfbpUmSpI+88iaUAYtFULvWjgGohGNUc5mT63WXkG6f43EDvAwWc3zv5n0FYt9OJzeSCygKOc\nTMvICMTyXOe2NJQGYgc4+Lp9wKemz6AtSRWzhaRacafV9wzakvqXP19L7fF/RepLBm1J/cvWGqk9\n/q+oC+wTPn2b9boAdcB4S8b4xZYM4dtCUs240+p7y0YOJYm1l2Ujh/a6pL5ni/YgsCVDG+DwxpJq\nxc+y/udrNG0GbQ0lT2a3cdzHSpLUPoO2hpKBUZIklWbQliQNN/tESSrEoC1JGm7+xCWpEIO2JBVk\nY6kkDS+DtjaO6UFqi42lkjS8DNraOKYH1ZDfDyVJ3WTQljQ0/H4oSeomzwwpSZIkFVA0aEfEkRGx\nJCKWRsQZG7j/nRFxU0TcEBE/iIiRpvvWRMT11WVByTolSZKkTivWdSQiZgDnAEcAK4CFEbEgM29q\nmu2nwFhmPhwRbwX+Hviz6r7fZ+Z+peqTJEmSSirZon0gsDQzb8vMR4ELgaObZ8jMyzPz4ermj4HZ\nBeuRJEmSuqZk0N4VuLPp9opVMpYAAAAgAElEQVRq2kTeCHy76fasiFgUET+OiGM2tEBEnFzNs2jl\nypWbXrEkSZLUIX0x6khEvBYYA17QNHkkM++KiD2AyyLixsy8tXm5zDwXOBdgbGwsu1awJEmSNIWS\nLdp3Abs13Z5dTVtHRBwOvA84KjNXjU/PzLuqv7cBVwDPKlirJEmS1FElg/ZCYG5EzImILYDjgHVG\nD4mIZwGfohGy722avl1EbFld3xE4BGg+iFKSJEnqa8W6jmTm6og4FfguMAP4bGYujoizgEWZuQD4\nMLA18OVonK7tjsw8CtgL+FREPEbjy8DZLaOVSJIkSX0tMgeja/PY2FguWrSoJ48dAQOyGSVJkmqj\nVxksIq7NzLGp5vPMkJIkSVIBBm1JkiSpAIO2JEmSVIBBW5IkSSrAoC1JkiQVYNCWJEmSCjBoS5Ik\nSQUYtCVJkqQCDNqSJElSAQZtSZIkqQCDtiRJklSAQVuSJEkqwKAtSZIkFWDQliRJkgowaEuSJEkF\nGLQlSZKkAgzakiRJUgEGbUmSJKkAg7YkSZJUgEFbkiRJKsCgLUmSJBVg0JYkSZIKMGhLkiRJBRi0\nJUmSpAIM2pIkSVIBBm1JkiSpAIO2JEmSVIBBW5IkSSrAoC1JkiQVYNCWJEmSCjBoS5IkSQUYtCVJ\nkqQCDNqSJElSAQZtSZIkqQCDtiRJklSAQVuSJEkqwKAtSZIkFWDQliRJkgowaEuSJEkFGLQlSZKk\nAgzakiRJUgEGbUmSJKkAg7YkSZJUgEFbkiRJKsCgLUmSJBVg0JYkSZIKMGhLkiRJBRi0JUmSpAIM\n2pIkSVIBBm1JkiSpAIO2JEmSVIBBW5IkSSrAoC1JkiQVYNCWJEmSCth8ojsiYv/JFszM6zpfjiRJ\nkjQYJgzawEerv7OAMeBnQAD7AIuA55YtTZIkSaqvCbuOZOYLM/OFwD3A/pk5lpnPBp4F3NWtAiVJ\nkqQ6aqeP9p6ZeeP4jcz8ObBXuZIkSZKk+pus68i4GyLiM8C/V7dPAG4oV5IkSZJUf+0E7dcDbwXe\nXt3+IfCJYhVJkiRJA2DKoJ2Zj0TEJ4FLM3NJF2qSJEmSam/KPtoRcRRwPfCd6vZ+EbGgdGGSJElS\nnbVzMOQHgAOBXwNk5vXAnJJFSZIkSXXXTtD+Q2Y+2DItSxQjSZIkDYp2DoZcHBF/DsyIiLnAacDV\nZcuSJEmS6q2dFu2/Ap4JrAK+CDwIvKNkUZIkSVLdtdOi/WzgrzPzfeMTImJ/4LpiVUmSJEk1106L\n9neByyLiSU3TPlOoHkmSJGkgtBO0lwAfBq6MiIOraVGuJEmSJKn+2uk6kpn5zYhYAlwUEZ/FUUck\nSZKkSbXToh0AmXkL8Pzqsk/JoiRJkqS6a+cU7M9quv4Q8JqI2L1oVZIkSVLNTdiiHRH/s/r78dYL\n8K52Vh4RR0bEkohYGhFnbOD+d0bETRFxQ0T8ICJGmu57XUTcUl1etxHPTZIkSeqZyVq0b67+Xrsx\nK46IGcA5wBHACmBhRCzIzJuaZvspMJaZD0fEW4G/B/4sIrancer3MRr9wa+tln1gY2qRJEmSum3C\noJ2Z36j+fm4j130gsDQzbwOIiAuBo4G1QTszL2+a/8fAa6vrLwG+n5m/qpb9PnAkcMFG1iJJkiR1\n1YRBOyK+wSSji2TmUVOse1fgzqbbK4CDJpn/jcC3J1l21w3UeDJwMsDuu9ttXJIkSf1jsq4jH+lW\nERHxWhrdRF4wneUy81zgXICxsTGHHJQkSVLfmKzryJWbuO67gN2abs+upq0jIg4H3ge8IDNXNS17\naMuyV2xiPZIkSVLXTDmOdkTMjYiLq9FBbhu/tLHuhcDciJgTEVsAxwELWtb9LOBTwFGZeW/TXd8F\nXhwR20XEdsCLq2mSJElSLbRzwpp/BT4BrAZeCHwe+PepFsrM1cCpNALyzcCXMnNxRJwVEeP9uz8M\nbA18OSKuj4gF1bK/Av6GRlhfCJw1fmCkJEmSVAeROXnX5oi4NjOfHRE3ZubezdO6UmGbxsbGctGi\nRT157AiYYjNKkiSpw3qVwaosPDbVfFOeGRJYFRGbAbdExKk0+k9vvakFSpIkSYOsna4jbwe2Ak4D\nng38BeCZGiVJkqRJTNminZkLq6sPAa8vW44kSZI0GKYM2hExRmP4vZHm+TNzn4J1SZIkSbXWTh/t\nLwCnAzcCj5UtR5IkSRoM7QTtlZm5YOrZJEmSJI1rJ2h/ICI+A/wAGD9zI5n51WJVSZIkSTXXTtB+\nPfAMYCZ/7DqSgEFbkiRJmkA7QfuAzNyzeCWSJEnSAGlnHO2rI2Je8UokSZKkAdJOi/ZzgOsj4nYa\nfbQDSIf3kyRJkibWTtA+sngVkiRJ0oCZNGhHxAzgu5n5jC7VI0mSJA2ESftoZ+YaYElE7N6leiRJ\nkqSB0E7Xke2AxRFxDfC78YmZeVSxqiRJkqSaaydo/6/iVUiSJEkDZsqgnZlXRsSTgQOqSddk5r1l\ny5IkSZLqbcpxtCPiNcA1wKuB1wA/iYhjSxcmSZIk1Vk7XUfeR+PskPcCRMROwH8AF5csTJIkSaqz\nds4MuVlLV5H721xOkiRJGlrttGh/JyK+C1xQ3f4z4NJyJUmSJEn1187BkKdHxKuAQ6pJ52bmJWXL\nkiRJkuqtnRZtMvMrwFcK1yJJkiQNjHZGHfnTiLglIh6MiN9ExG8j4jfdKE6SJEmqq3ZatP8eeEVm\n3ly6GEmSJGlQtDN6yC8N2ZIkSdL0tNOivSgiLgK+Bqwan5iZXy1WlSRJklRz7QTtbYGHgRc3TUvA\noC1JkiRNoJ3h/V7fjUIkSZKkQeIZHiVJkqQCDNqSJElSAQZtSZIkqYB2Tljz9ojYNhrOi4jrIuLF\nUy0nSZIkDbN2WrTfkJm/oTHqyHbAXwBnF61KkiRJqrl2gnZUf/8HcH5mLm6aJkmSJGkD2gna10bE\n92gE7e9GxDbAY2XLkiRJkuqtnRPWvBHYD7gtMx+OiB0Ax9aWJEmSJtFOi/b3M/O6zPw1QGbeD/xj\n2bIkSZKkepuwRTsiZgFbATtGxHb8sV/2tsCuXahNkiRJqq3Juo78JfAOYBfgWv4YtH8D/HPhuiRJ\nkqRamzBoZ+b/Bf5vRPxVZv5TF2uSJEmSam/KgyEz858i4mBgtHn+zPx8wbokSZKkWpsyaEfE+cBT\ngeuBNdXkBAzakiRJ0gTaGd5vDJiXmVm6GEmSJGlQtDO838+Bp5QuRJIkSRok7bRo7wjcFBHXAKvG\nJ2bmUcWqkiRJkmqunaB9ZukiJEmSpEHTzqgjV0bECDA3M/8jIrYCZpQvTZIkSaqvKftoR8SbgYuB\nT1WTdgW+VrIoSZIkqe7aORjyFOAQGmeEJDNvAZ5UsihJkiSp7toJ2qsy89HxGxGxOY1xtCVJkiRN\noJ2gfWVEvBd4XEQcAXwZ+EbZsiRJkqR6aydonwGsBG4E/hK4FHh/yaIkSZKkumtneL9jgM9n5qdL\nFyNJkiQNinZatF8B/HdEnB8RL6/6aEuSJEmaxJRBOzNfDzyNRt/s44FbI+IzpQuTJEmS6qyt1unM\n/ENEfJvGaCOPo9Gd5E0lC5MkSZLqrJ0T1rw0Iv4NuAV4FfAZ4CmF65IkSZJqrZ0W7ROBi4C/zMxV\nheuRJEmSBkI7fbSPB34K/AlARDwuIrYpXZgkSZJUZ+10HXkzcDHwqWrSbOBrJYuSJEmS6q6d4f1O\nAQ4BfgOQmbcATypZlCRJklR37QTtVZn56PiNahztLFeSJEmSVH/tBO0rI+K9wOMi4gga42l/o2xZ\nkiRJUr21E7TPAFYCNwJ/CVwKvL9kUZIkSVLdTTm8X2Y+Bny6ukiSJElqQzst2pIkSZKmyaAtSZIk\nFTBh0I6I86u/b+9eOZIkSdJgmKxF+9kRsQvwhojYLiK2b750q0BJkiSpjiY7GPKTwA+APYBrgWi6\nL6vpkiRJkjZgwhbtzPx4Zu4FfDYz98jMOU2XtkJ2RBwZEUsiYmlEnLGB+58fEddFxOqIOLblvjUR\ncX11WTDtZyZJkiT1UDvD+701IvYF/qSa9MPMvGGq5SJiBnAOcASwAlgYEQsy86am2e4ATgLetYFV\n/D4z95vqcSRJkqR+NOWoIxFxGvAF4EnV5QsR8VdtrPtAYGlm3ladwv1C4OjmGTJzWRXaH5t25ZIk\nSVIfm7JFG3gTcFBm/g4gIj4E/Aj4pymW2xW4s+n2CuCgadQ2KyIWAauBszPza60zRMTJwMkAu+++\n+zRWLUmSJJXVzjjaAaxpur2GdQ+MLGUkM8eAPwc+FhFPbZ0hM8/NzLHMHNtpp526UJIkSZLUnnZa\ntP8V+ElEXFLdPgY4r43l7gJ2a7o9u5rWlsy8q/p7W0RcATwLuLXd5SVJkqRemrJFOzP/AXg98Kvq\n8vrM/Fgb614IzI2IORGxBXAc0NboIdW43VtW13cEDgFumnwpSZIkqX+006JNZl4HXDedFWfm6og4\nFfguMIPGMIGLI+IsYFFmLoiIA4BLgO2AV0TEBzPzmcBewKci4jEaXwbObhmtRJIkSeprkZm9rqEj\nxsbGctGiRT157AgYkM0oSZJUG73KYBFxbXUs4aTaORhSkiRJ0jRNGrQjYkZEXN6tYiRJkqRBMWnQ\nzsw1wGMR8YQu1SNJkiQNhHYOhnwIuDEivg/8bnxiZp5WrCpJkiSp5toJ2l+tLpIkSZLaNGXQzszP\nRcTjgN0zc0kXapIkSZJqb8pRRyLiFcD1wHeq2/tFRFsnnpEkSZKGVTvD+50JHAj8GiAzrwf2KFiT\nJEmSVHvtBO0/ZOaDLdMeK1GMJEmSNCjaORhycUT8OTAjIuYCpwFXly1LkiRJqrd2WrT/CngmsAq4\nAPgN8I6SRUmSJEl1186oIw8D74uIDzVu5m/LlyVJkiTVWzujjhwQETcCN9A4cc3PIuLZ5UuTJEmS\n6qudPtrnAW/LzP8EiIjnAf8K7FOyMEmSJKnO2umjvWY8ZANk5lXA6nIlSZIkSfU3YYt2ROxfXb0y\nIj5F40DIBP4MuKJ8aZIkSVJ9TdZ15KMttz/QdD0L1CJJkiQNjAmDdma+sJuFSJIkSYNkyoMhI+KJ\nwInAaPP8mXlaubIkSZKkemtn1JFLgR8DN+Kp1yVJkqS2tBO0Z2XmO4tXIkmSJA2Qdob3Oz8i3hwR\nO0fE9uOX4pVJkiRJNdZOi/ajwIeB9/HH0UYS2KNUUZIkSVLdtRO0/z/gaZl5X+liJEmSpEHRTteR\npcDDpQuRJEmSBkk7Ldq/A66PiMuBVeMTHd5PkiRJmlg7Qftr1UWSJElSm6YM2pn5uW4UIkmSJA2S\nds4MeTt/HG1krcx01BFJkiRpAu10HRlruj4LeDXgONqSJEnSJKYcdSQz72+63JWZHwNe1oXaJEmS\npNpqp+vI/k03N6PRwt1OS7gkSZI0tNoJzB9tur4aWAa8pkg1kiRJ0oBoZ9SRF3ajEEmSJGmQtNN1\nZEvgVcBo8/yZeVa5siRJkqR6a6fryNeBB4FraTozpCRJkqSJtRO0Z2fmkcUrkSRJkgbIlMP7AVdH\nxN7FK5EkSZIGSDst2s8DTqrOELkKCCAzc5+ilUmSJEk11k7QfmnxKiRJkqQB087wfsu7UYgkSZI0\nSNrpoy1JkiRpmgzakiRJUgEGbUmSJKkAg7YkSZJUgEFbkiRJKsCgLUmSJBVg0JYkSZIKMGhLkiRJ\nBRi0JUmSpAIM2pIkSVIBBm1JkiSpAIO2JEmSVIBBW5IkSSrAoC1JkiQVYNCWJEmSCjBoS5IkSQUY\ntCVJkqQCDNqSJElSAQZtSZIkqQCDtiRJklSAQVuSJEkqwKAtSZIkFWDQliRJkgowaEuSJEkFGLQl\nSZKkAgzakiRJUgEGbUmSJKkAg7YkSZJUgEFbkiRJKsCgLUmSJBVg0JYkSZIKKBq0I+LIiFgSEUsj\n4owN3P/8iLguIlZHxLEt970uIm6pLq8rWackSZLUacWCdkTMAM4BXgrMA46PiHkts90BnAR8sWXZ\n7YEPAAcBBwIfiIjtStUqSZIkdVrJFu0DgaWZeVtmPgpcCBzdPENmLsvMG4DHWpZ9CfD9zPxVZj4A\nfB84smCtkiRJUkeVDNq7Anc23V5RTevYshFxckQsiohFK1eu3OhCJUmSpE6r9cGQmXluZo5l5thO\nO+3U63IkSZKktUoG7buA3Zpuz66mlV5WkiRJ6rmSQXshMDci5kTEFsBxwII2l/0u8OKI2K46CPLF\n1TRJkiSpFooF7cxcDZxKIyDfDHwpMxdHxFkRcRRARBwQESuAVwOfiojF1bK/Av6GRlhfCJxVTZMk\nSZJqITKz1zV0xNjYWC5atKgnjx0BA7IZJUmSaqNXGSwirs3Msanmq/XBkJIkSVK/MmhLkiRJBRi0\nJUmSpAIM2pIkSVIBBm1JkiSpAIO2JEmSVIBBW5IkSSrAoC1JkiQVYNCWJEmSCjBoS5IkSQUYtCVJ\nkqQCDNqSJElSAQZtSZIkqQCDtiRJklSAQVuSJEkqwKAtSZIkFWDQliRJkgowaEuSJEkFGLQlSZKk\nAgzakiRJUgEGbUmSJKkAg7YkSZJUgEFbkiRJKsCgLUmSJBVg0JYkSZIKMGhLkiRJBRi0JUmSpAIM\n2pIkSVIBBm1JkiSpAIO2JEmSVIBBW5IkSSrAoC1JkiQVYNCWJEmSCjBoS5IkSQUYtCVJkqQCDNqS\nJElSAQZtSZIkqQCDtiRJklSAQVuSJEkqwKAtSZIkFWDQliRJkgowaEuSJEkFGLQlSZKkAgzakiRJ\nUgEGbUmSJKkAg7YkSZJUgEFbkiRJKsCgLUmSJBVg0JYkSZIKMGhLkiRJBRi0JUmSpAIM2pIkSVIB\nBm1JkiSpAIO2JEmSVIBBW5IkSSrAoC1JkiQVYNCWJEmSCjBoS5IkSQUYtCVJkqQCDNqSJElSAQZt\nSZIkqQCDtiRJklSAQVuSJEkqwKAtSZIkFWDQliRJkgowaEuSJEkFGLQlSZKkAgzakiRJUgEGbUmS\nJKkAg7YkSZJUgEFbkiRJKqBo0I6IIyNiSUQsjYgzNnD/lhFxUXX/TyJitJo+GhG/j4jrq8snS9Yp\nSZIkddrmpVYcETOAc4AjgBXAwohYkJk3Nc32RuCBzHxaRBwHfAj4s+q+WzNzv1L1SZIkSSWVbNE+\nEFiambdl5qPAhcDRLfMcDXyuun4x8KKIiII1SZIkSV1RMmjvCtzZdHtFNW2D82TmauBBYIfqvjkR\n8dOIuDIi/mRDDxARJ0fEoohYtHLlys5WL0mSJG2Cfj0Y8h5g98x8FvBO4IsRsW3rTJl5bmaOZebY\nTjvt1PUiJUmSpImUDNp3Abs13Z5dTdvgPBGxOfAE4P7MXJWZ9wNk5rXArcDTC9YqSZIkdVTJoL0Q\nmBsRcyJiC+A4YEHLPAuA11XXjwUuy8yMiJ2qgymJiD2AucBtBWuVJEmSOqrYqCOZuToiTgW+C8wA\nPpuZiyPiLGBRZi4AzgPOj4ilwK9ohHGA5wNnRcQfgMeAt2Tmr0rVKkmSJHVaZGava+iIsbGxXLRo\nUU8eOwIGZDNKkiTVRq8yWERcm5ljU83XrwdDSpIkSbVm0JYkSZIKMGhLkiRJBRi0JUmSpAIM2pIk\nSVIBBm1JkiSpAIO2JEmSVIBBW5IkSSrAoC1JkiQVYNCWJEmSCjBoS5IkSQUYtCVJkqQCDNqSJElS\nAQZtSZIkqQCDtiRJklSAQVuSJEkqwKAtSZIkFWDQliRJkgowaEuSJEkFGLQlSZKkAgzakiRJUgEG\nbUmSJKkAg7YkSZJUgEFbkiRJKsCgLUmSJBVg0JYkSZIKMGhLkiRJBRi0JUmSpAIM2pIkSVIBBm1J\nkiSpAIO2JEmSVIBBW5IkSSrAoC1JkiQVYNCWJEmSCjBoS5IkSQUYtCVJkqQCDNqSJElSAQZtSZIk\nqQCDtiRJklSAQVuSJEkqwKAtSZIkFWDQliRJkgowaEuSJEkFGLQlSZKkAgzakiRJUgEGbUmSJKkA\ng7YkSZJUgEFbkiRJKsCgLUmSJBVg0JYkSZIKMGhLkiRJBRi0JUmSpAIM2pIkSVIBBm1JkiSpAIO2\nJEmSVIBBW5IkSSrAoC1JkiQVYNCWJEmSCjBoS5IkSQUYtCVJkqQCDNqSJElSAQZtSZIkqQCDtiRJ\nklSAQVuSJEkqwKAtSZIkFWDQliRJkgowaEuSJEkFGLQlSZKkAgzakiRJUgEGbUmSJKkAg7YkSZJU\ngEFbkiRJKqBo0I6IIyNiSUQsjYgzNnD/lhFxUXX/TyJitOm+91TTl0TES0rWKUmSJHVasaAdETOA\nc4CXAvOA4yNiXstsbwQeyMynAf8IfKhadh5wHPBM4EjgX6r1SZIkSbVQskX7QGBpZt6WmY8CFwJH\nt8xzNPC56vrFwIsiIqrpF2bmqsy8HVharU+SJEmqhc0LrntX4M6m2yuAgyaaJzNXR8SDwA7V9B+3\nLLtr6wNExMnAydXNhyJiSWdKn76IXj3ytOwI3NfrIgaY27cct205btuy3L7luG3LqdW27VEGG2ln\nppJBu7jMPBc4t9d11EVELMrMsV7XMajcvuW4bctx25bl9i3HbVuO27ZzSnYduQvYren27GraBueJ\niM2BJwD3t7msJEmS1LdKBu2FwNyImBMRW9A4uHFByzwLgNdV148FLsvMrKYfV41KMgeYC1xTsFZJ\nkiSpo4p1Han6XJ8KfBeYAXw2MxdHxFnAosxcAJwHnB8RS4Ff0QjjVPN9CbgJWA2ckplrStU6ROxm\nU5bbtxy3bTlu27LcvuW4bctx23ZINBqQJUmSJHWSZ4aUJEmSCjBoS5IkSQUYtAdYRLw6IhZHxGMR\nMeEwPRGxLCJujIjrI2JRN2uss2ls3yMjYklELI2IM7pZY11FxPYR8f2IuKX6u90E862p3rfXR0Tr\nwdZqMtX7sDr4/KLq/p9ExGj3q6ynNrbtSRGxsum9+qZe1FlHEfHZiLg3In4+wf0RER+vtv0NEbF/\nt2usqza27aER8WDT+/avu13jIDBoD7afA38K/LCNeV+Ymfs5bua0TLl9I2IGcA7wUmAecHxEzOtO\nebV2BvCDzJwL/KC6vSG/r963+2XmUd0rr17afB++EXggM58G/CPwoe5WWU/T+B+/qOm9+pmuFllv\n/wYcOcn9L6UxMtlcGiew+0QXahoU/8bk2xbgP5vet2d1oaaBY9AeYJl5c2b27GyZg67N7XsgsDQz\nb8vMR4ELgaPLV1d7RwOfq65/Djimh7UMgnbeh83b/GLgRRE1Oedtb/k/XlBm/pDGqGQTORr4fDb8\nGHhiROzcnerqrY1tqw4waAsgge9FxLXVae3VObsCdzbdXlFN0+SenJn3VNd/ATx5gvlmRcSiiPhx\nRBjGJ9bO+3DtPJm5GngQ2KEr1dVbu//jr6q6NlwcEbtt4H79v/buLVSzMY7j+PcXxoVzxmFQjiMT\nitIgmiSNmqTU5FAy41AOyZ0oF+LGhAulRCFRpqSG7ThIbhg5jHGWmRFlyEQ5TDQ1zd/FWrteM/vw\n7rHf/bb2/n5qt9Zex//7tPba//dZz3qePeM9drDOTfJpkteSnDrsYLqo00OwC5K8BRw5xqq7qurF\nPg9zflVtSXI48GaSb9pvunPeNJWvxjBR2fb+UlWVZLx+SI9tr90TgLeTfF5Vm6c7Vul/eglYXVXb\nk9xI8+TgwiHHJE1mPc09dluSZcALNE10NAUm2h1XVRdNwzG2tNOtSdbQPAo10WZayncL0Ft7dUy7\nbM6bqGyT/JJkQVX93D4G3jrOMUav3e+SvAOcCZho766f63B0mx+T7A0cBPw2M+F12qRlW1W95fg4\ncP8MxDVXeI8dkKr6s2f+1SSPJJlfVb8OM66usenIHJdkvyQHjM4DS2le8tP0+BBYmOT4JPNoRj+1\nd4zJjQAr2vkVwG5PD5IckmTfdn4+cB7NaLLaXT/XYW+ZLwfeLkc068ekZbtLm+FLga9nML7ZbgS4\npu195Bzgj55mZ/ofkhw5+p5GksU0OaNfvqfIGu1ZLMllwMPAYcArSTZU1cVJjgIer6plNG1f17R/\nS3sDz1bV60MLukP6Kd+q2pHkVmAtsBfwZFV9OcSwu2IV8FyS64EfgMsB2m4Ub6qqG4BFwGNJdtL8\nA1hVVSbaYxjvOkxyL/BRVY0ATwDPJNlE84LUlcOLuDv6LNvbklwK7KAp25VDC7hjkqwGLgDmJ/kR\nuBvYB6CqHgVeBZYBm4C/gWuHE2n39FG2y4Gbk+wA/gGu9Mv31DkEuyRJkjQANh2RJEmSBsBEW5Ik\nSRoAE21JkiRpAEy0JUmSpAEw0ZYkSZIGwERbkiRJGgATbUnqkCTvTbDu4CS3TLL/GUnWJfkyyWdJ\nrtjDOJ5KsnyM5UcleX5PjilJs439aEvSLJHkOODlqjptgm1OBqqqNraDK30MLKqq36d4rqfac5lU\nS9I4rNGWpA5Jsq2d3p7kw7ZW+p529SrgxCQbkjww1v5V9W1VbWznfwK20oxuOt75vk9yf5LPk3yQ\n5KSe1UuSvJfku9Ha7STHJfliGj6qJHWeQ7BLUsckWQosBBYDAUaSLAHuBE6rqjP6PM5iYB6weZJN\n/6iq05NcAzwEXNIuXwCcD5wCjADWbktSD2u0Jal7lrY/nwDraRLdhVM5QJIFwDPAtVW1c5LNV/dM\nz+1Z/kJV7ayqr4AjpnJ+SZoLrNGWpO4JcF9VPfafhU0b7cl3Tg4EXgHuqqr3+9ilxpnfvktMkqQe\n1mhLUvesBa5Lsj9AkqOTHA78BRww0Y5J5gFrgKen8CLjFT3TdXsWsiTNPdZoS1K3VFW9kWQRsC4J\nwDbg6qranOTd9mXE16rq9jH2vxxYAhyaZGW7bGVVbZjgnIck+YymBvuqafskkjTL2b2fJHVEkkOB\n9VV17Aye83vgrKr6dabOKUmzhU1HJKkD2j6v1wEPDjsWSVJ/rNGWpFkoyek0vYr02l5VZ4+z/Rrg\n+F0W31FVawcRnyTNBZshsDgAAAAqSURBVCbakiRJ0gDYdESSJEkaABNtSZIkaQBMtCVJkqQBMNGW\nJEmSBuBfN/dtnIFMKeEAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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AMLvm7c6R5Iaq2izJhVV1WJJLk2w13bIAAGB2TdIS/Zokd8roCYWPSPJbSV48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\no2AUjIJRMApIBADbrRfPbmKCqQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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TTkjS6zyfcsopOfLII3P/+99/Qxe6tZaTTz45Bx54YI4++uj84Ac/GMo5E6gBANjg8ssv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\nAAZoqAEAYICGGgAABmioAQBgwBK8Ce99DtO03wAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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JOAlgzz33nJOgJUmSpLnQ9cGQmXlWZu4NnAp8cDPPPTszhzNzePHixdUEKEmS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\nDNqSJElSCwzakiRJUgsM2pIkSVIL/gu17vJqged8iwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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/c/02iNLoCLYFU4gQOkKF+IE11CnQ+Cz1k/tMmfSNb0iz81qHf03l0nEZttnn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\nQmCC\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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XJdlhumUBAMDCNUlP9KuT3CGjOxQ+LMkLkrxomkUBAMBCNmtPdHefMn56bZIX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\nAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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llFNywAEHZOXKlXnVq161/ng777zz+sennXZajjvuuCS9keeTTjophx56aB70oAetH4Vu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\nAABoEKgBAKBBoAYAgIY3ayycfk9sRu8AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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gODOXA6dHxOHAY8D9wBuKa1dFxBeAm4H1wGnOOCL1gGq1tirNmEqlYdWNOY9I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\nGjBoS5IkSQ0YtCVJkqQGDNqSJElSA/8FAPThG9ZxHd8AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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+zkSXD3yDdpzdHAbtATSQX191WSdad/3wUkC/HSk1GHr9Zpzm4xcrd0vv4jNg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\naEuSJElDYKItSZIkDcH/Aaf08ASUdHAsAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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BAICFb5LROVYk+YMku89cvrsfPMW6AABgwZqkT/RHkrwiyXlJbp1uOQAAsPBN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\nAAAGEqIBAGAgIRoAAAYSogEAYKD/B4fUQMp7/R40AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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kv5nkLVOtCgAAZsQkgbrGf38lyUndff68dQAAsFObJFCfU1WfyShQ/31V7Znk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\n+gAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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h/p9JntTdF027GAAAmDeTzNbxTWEaAAA2b5Ie6jVV9Z4kH0hy/YaT3f2+qVUF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\nGECgBgCAAQRqAAAY4P8HiowImELDbyIAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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OLrjggtzsZjfL3/3d3+V5z3teTj/99Jx77rn593//93zoQx9KMrqt93Of+9x8+ctfzuc+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\niAYAgIGEaAAAGEiIBgCAgf4v8ckKqizLRUIAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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MYDGw4doWKEmSJHWyEVtAgPcBG9B4EuRewJ8D7ypZlCRJktTuRhzRzszbqpfP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\nQ2u6AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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78MMPZ6ONNmLOnDn8+te/BuD666/n6KOPZtKkSWy99dYccMABo3SXXmDQliRJUi0R8aLt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\nQmCC\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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rTTtHB2vWrL/uVuQAAMM3SMvH69K7W+L3k6Sqdkvyb0nmDNSttZfM8/zb0ptW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\nRK5CYII=\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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q/eZMd7eg1tq5SWqBfVqSV2zOcQEAYDkZJFA/JsnFVfUf6fVQV3pZeN5p8wAA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\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mmwbCJilGn70",
        "colab_type": "text"
      },
      "source": [
        "c. Use scikit-learn to train and compare ROC curves and AUC values for 3 classifiers."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-9IdUW40tlfb",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "outputId": "b02fec34-f23f-4db1-fc9f-28224d756062"
      },
      "source": [
        "import sklearn.discriminant_analysis as DA\n",
        "Fisher=DA.LinearDiscriminantAnalysis()\n",
        "N_Train=1000000\n",
        "\n",
        "Train_Sample=df[:N_Train]\n",
        "Test_Sample=df[N_Train:]\n",
        "\n",
        "X_Train=Train_Sample[VarNames[1:]]\n",
        "y_Train=Train_Sample[\"Signal\"]\n",
        "\n",
        "X_Test=Test_Sample[VarNames[1:]]\n",
        "y_Test=Test_Sample[\"Signal\"]\n",
        "\n",
        "Test_sig=Test_Sample[Test_Sample.Signal==1]\n",
        "Test_bkg=Test_Sample[Test_Sample.Signal==0]\n",
        "\n",
        "\n",
        "Fisher.fit(X_Train,y_Train)\n",
        "\n",
        "\n",
        "\n",
        "#plt.hist(Fisher.decision_function(Test_sig[VarNames[1:]],bins=100,histtype=\"step\", color=\"blue\", label=\"signal\",stacked=True)\n",
        "#plt.hist(Fisher.decision_function(Test_bkg[VarNames[1:]],bins=100,histtype=\"step\", color=\"red\", label=\"background\",stacked=True)\n",
        "#plt.legend(loc='upper right')\n",
        "#plt.show()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "error",
          "ename": "ValueError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-15-78b162bd61d7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     20\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     21\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 22\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mFisher\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdecision_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mTest_sig\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mVarNames\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mflatten\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mbins\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mhisttype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"step\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"blue\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"signal\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mstacked\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     23\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mFisher\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdecision_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mTest_bkg\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mVarNames\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mflatten\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mbins\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mhisttype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"step\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"red\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"background\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mstacked\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     24\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlegend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'upper right'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/base.py\u001b[0m in \u001b[0;36mdecision_function\u001b[0;34m(self, X)\u001b[0m\n\u001b[1;32m    255\u001b[0m                                  \"yet\" % {'name': type(self).__name__})\n\u001b[1;32m    256\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 257\u001b[0;31m         \u001b[0mX\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maccept_sparse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'csr'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    258\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    259\u001b[0m         \u001b[0mn_features\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcoef_\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36mcheck_array\u001b[0;34m(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)\u001b[0m\n\u001b[1;32m    550\u001b[0m                     \u001b[0;34m\"Reshape your data either using array.reshape(-1, 1) if \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    551\u001b[0m                     \u001b[0;34m\"your data has a single feature or array.reshape(1, -1) \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 552\u001b[0;31m                     \"if it contains a single sample.\".format(array))\n\u001b[0m\u001b[1;32m    553\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    554\u001b[0m         \u001b[0;31m# in the future np.flexible dtypes will be handled like object dtypes\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mValueError\u001b[0m: Expected 2D array, got 1D array instead:\narray=[].\nReshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample."
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3F99mD3jHeiW",
        "colab_type": "code",
        "outputId": "84483400-6491-47bc-fd98-5bb4c4fcafd3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 852
        }
      },
      "source": [
        "from sklearn.metrics import roc_curve, auc\n",
        "def plot(var,name=''):\n",
        "  fpr, tpr,_= roc_curve(df.Signal,var )\n",
        "  roc_auc = auc(fpr, tpr)\n",
        "  plt.plot(fpr,tpr,color='red',label='ROC curve (area = %0.2f)' % roc_auc)\n",
        "  plt.legend()\n",
        "  plt.xlabel('False Positive Rate')\n",
        "  plt.ylabel('True Positive Rate')\n",
        "  plt.title('fps vs. tpr for '+name)\n",
        "  plt.show()\n",
        "  \n",
        "plot(df.jet_1_pt,'jet_1_pt')\n",
        "plot(df.lepton_pT,'lepton_pT')\n",
        "plot(df.m_jlv,'m_jlv')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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A698f7r8fKlZMdVQiCRNPUqjn7tsSHolIOnGHp54KS2TutVeocHr66amOSiTh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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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l1Udm1t7M5phZtpndls/ru5vZq9HrE82sTirjKdDKlTBkSFjPoEmT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\nRHIpKYiISC4lBRERyfX/ATlXJFQANfFGAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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e22zo7jslhthEd3u6MptIenGHCRPg4Ydh0iQ45JCQGP74Ry1xKRkjkS6pf8jn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\nKj4AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Sc37Kp5GHiPs",
        "colab_type": "text"
      },
      "source": [
        "d. Find the optimal (most significant) cut value for each classifier assuming 100 signal and 1000 background events."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cCRFo0N7HgTP",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VjgfJUmAQ9jv",
        "colab_type": "text"
      },
      "source": [
        "e. Use your answer to part 1 question 2b to show that you can compute the same mass features in the dataset from the 4-vectors in the dataset."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9vPsBx4PRQqr",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}