pca.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7304f911-084e-4725-baf7-aabf74c962de",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Table of content # \n",
    "\n",
    "\n",
    "1. [ PCA Description ](#desc)\n",
    "\n",
    "2. [ The Math behind PCA ](#math)\n",
    "\n",
    "3. [ PCA from scratch ](#code)\n",
    "    1. [ Import Library ](#import)    \n",
    "    2. [ Class PCA ](#class)\n",
    "    3. [ Work with Iris data ](#dataset)"
   ]
  },
  {
   "attachments": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "ee0df63c-39da-4a15-90e7-bb77bfeaa223",
   "metadata": {},
   "source": [
    "<a name=\"desc\"></a>\n",
    "## PCA Description\n",
    "\n",
    "PCA is one of many dimension reduction methods (dim-redction). The idea is simple: find a set of `k` orthogonal vector (`k`<`d`) that approximate the `d` original vector (`d` features). In other word, PCA cut off some redundant feature that has less important. But what important means? The final goal is to keep the interesting, systematic variations between data points. It leads to 2 equivalent soluiton: \n",
    "* First answer is that we are looking for some features that strongly differ across data points, thus, PCA looks for features that captures as much variation across data points as possible.\n",
    "\n",
    "* The second answer is that we are looking for the features that would allow us to \"reconstruct\" the original features. Imagine that we come up with a feature that has no relation to the original ones; If we were to use this new feature, there is no way we can relate this to the original ones. So PCA looks for features that minimizes the reconstruction error.\n",
    "\n",
    "![image.png](attachment:117c9344-2655-425f-86a0-2e50b5ecd16e.png)\n",
    "\n",
    "The 2 solution is equivalent that basically infered by Pythagorean theorem.\n",
    "\n",
    "\n",
    "**Application: Face-matching**\n",
    "\n",
    "*\"Each point $x(i) \\in R^{100 \\times 100}$ was a 10000 dimensional vector, with each coordinate corresponding to a pixel intensity value in a 100x100 image of a face. Using PCA, we represent each image $x(i)$ with a much lower-dimensional $y(i)$. In doing so, we hope that the principal components we found retain the interesting, systematic variations between faces that capture what a person really looks like, but not the “noise” in the images introduced by minor lighting variations, slightly different imaging conditions, and so on. We then measure distances between faces i and j by working in the reduced dimension, and computing $||y(i) −y\n",
    "(j)||_2$. This resulted in a surprisingly good face-matching and retrieval algorithm \"*"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d1a388f-61de-4365-86db-2e096cd6078f",
   "metadata": {},
   "source": [
    "<a name=\"math\"></a>\n",
    "## The Math behind PCA\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df8c2e45-5e68-491d-bcf9-2a31abcfa60c",
   "metadata": {},
   "source": [
    "To begin with, there are some annotations in PCA:\n",
    "* x(i) : data point $i^{th}$ in high-dim, standardized to zero mean and variance 1 ($x \\leftarrow \\frac{x - \\mu }{\\sigma}$)\n",
    "* y(i) : data point $i^{th}$ in low-dim, ($y(i) = u^\\top x(i) $)\n",
    "* u: project vector, this is `trainable` parameter\n",
    "* $\\Sigma$: Covariance of data points\n",
    "\n",
    "Let consider PCA's objective function: maximize variance of projected data points y(i)\n",
    "\n",
    "\\begin{align}\n",
    "\\Sigma =\\frac{1}{n}(\\mathbf{Y})^\\top \\mathbf{Y} = \\frac{1}{n}(\\mathbf{Xu})^\\top \\mathbf{Xu} = \\mathbf u^\\top (\\frac{1}{n}\\mathbf X^\\top\\mathbf X) \\mathbf u = \\mathbf u^\\top \\mathbf{Cu}\n",
    "\\end{align}\n",
    "(I used 1/n instead of 1/(n-1) due to the assumption  $d << n$)\n",
    "\n",
    "$C =\\frac{1}{n}\\mathbf (X-\\mu_X) ^\\top\\mathbf (X-\\mu_X) = \\frac{1}{n}\\mathbf (X) ^\\top\\mathbf (X)  $ which is just the empirical covariance matrix of the data (assuming it has zero mean, if not, we standardize X). \n",
    "\n",
    "So far so good, we did transform the covariance of projected points into simple form. However, it is still impossible to find the optimum value because the formula are unchanged whenever we scale `u` by arbitrary number, thus we should constraints `u` into  a unit vector: $u^\\top u= 1$\n",
    "\n",
    "Apply Lagrange multiplier, we try to minimize the loss function:\n",
    "\\begin{align}\n",
    "L &= \\mathbf u^\\top \\mathbf{Cu}-\\lambda(\\mathbf u^\\top \\mathbf u-1)\n",
    "\\end{align}\n",
    "\n",
    "\\begin{align}\n",
    "\\frac{\\partial L}{\\partial \\mathbf w} \n",
    "& = \\mathbf{Cw} - \\lambda \\mathbf w = 0 \\\\\n",
    "& => \\mathbf{Cw} = \\lambda \\mathbf w\n",
    "\\end{align}\n",
    "\n",
    "This lead to a familiar equation of finding eigenvalues and eigenvectors of C."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e64718e-1c45-4c2a-8b7c-173b1b1cd0f6",
   "metadata": {},
   "source": [
    "<a name=\"code\"></a>\n",
    "## PCA from scratch\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11738464-64c5-4532-9b2e-79ba23b20866",
   "metadata": {
    "tags": []
   },
   "source": [
    "<a name=\"import\"></a>\n",
    "### Import library"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ac30f4da-aa1f-4d06-93b9-ef8a46aab902",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 1. magic for inline plot\n",
    "# 2. magic to print version\n",
    "# 3. magic so that the notebook will reload external python modules\n",
    "# 4. magic to enable retina (high resolution) plots\n",
    "# https://gist.github.com/minrk/3301035\n",
    "%matplotlib inline\n",
    "# %load_ext watermark\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.datasets import load_iris"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55b3f65e-7ab9-43f0-9f12-615ee2589ce9",
   "metadata": {
    "tags": []
   },
   "source": [
    "<a name=\"class\"></a>\n",
    "### class PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "48801e29-4d6a-4d47-afe2-695e6b2bf121",
   "metadata": {},
   "outputs": [],
   "source": [
    "def standardize(X): # X: (nxd), standardize along all examples of each feature (axis = 0)\n",
    "    return (X-np.mean(X, axis = 0))/np.std(X, axis = 0) \n",
    "\n",
    "def covariance(X_std): # this may be different to np.cov when n is not large enough\n",
    "    n = len(X)\n",
    "    return 1/n*(X_std.T @ X_std)\n",
    "\n",
    "class PCA:\n",
    "    \"\"\"\n",
    "    Principal component analysis (PCA)\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    n_components : int\n",
    "        top number of principal components to keep\n",
    "    \"\"\"\n",
    "    def __init__(self, n_components):\n",
    "        self.n_components = n_components\n",
    "        \n",
    "    def fit(self, X):\n",
    "        # standardization\n",
    "        X_std = standardize(X)\n",
    "        \n",
    "        # empircal covariance C\n",
    "        C = covariance(X_std)\n",
    "    \n",
    "        # eigendecomposition\n",
    "        eig_vals, eig_vecs = np.linalg.eig(C) # this function is sorted by descending order.\n",
    "        var_exp = eig_vals / np.sum(eig_vals)\n",
    "        self.explained_variance_ratio = var_exp[:self.n_components]\n",
    "        \n",
    "        # k principle components\n",
    "        self.k_eig_vecs = eig_vecs[:, :self.n_components]\n",
    "        \n",
    "        return self"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b8bdeaf-eb19-46bc-a5ed-6705c642a27c",
   "metadata": {
    "tags": []
   },
   "source": [
    "<a name=\"dataset\"></a>\n",
    "### Work with Iris dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d13ea044-790f-4ef4-b46d-3c5f868d4ed6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 4 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 413,
       "width": 614
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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rep1Lls2AS1hYoG9ZX9FT8ToiHdq0NEdxDwBAVSBAAUAtqMWqZMWuc7n2l2ffduOGkhYWCDeFNbhm0HGI6oh0aPCWQc8FKKpSYkY6POT85yyRSB4/U9p+AYALBCgAqAW1WJUstc5l/YCzdUo3bZLe9D777zdukN49WPLCApF5Ee1au0vbbtqmlnBL1mNam1u17aZtunftvZo/d37R56h6iRnpoQ9J++5wFtZTHwbsu8NuR4gCUGGMZVlB96GmGGOeWLFixYonnngi6K4AqCepi9QjDzjb5yl9xGr57XZQqYW1IYkZafx+Z4UFJPt5GN/jS2GBeCKusckxTUQnNDU9peamZrVH2tW1sKu+1zwdHrLDUEq+n89sI6nrB+y1SwDgo5UrV+rw4cOHLctaWWxbApTPCFAAAhNgeABycjK9tJjjAMAHXgIU70gAUCuoSuYP1uv4y8naO8ITgCrCuxIAACms1ymNfCFqJk54AlBV6nhSNgAAGcbvt9eRSYU32s0cNTnygL2xK+t1ssu18XHmhs+EJwAVjncnAEDtKnY63o3vl65dffHfucq855pylm0vKlyUbSQqHeEJQBXgHQoAUJvcTMfbv106fUi6+rqLt7Nex1+hkLRuR/b71u3gOQRQ8XiXAgDUpszpePlCVGYoeuGZ7CNRrNfxLhVUs9m/vTI3dQaANLzbAwBqU+fG/JXfUnKNKH3g4UvbfzpCePIi23OdrlDQBYAKwDs+AKA2eS2f3dDIeh0/5Xqu74w6C7oAUCF41wcA1C6v5bNZr+OPYoMqIQpABeOdHwBQ23KFKCfT8Viv452TohtORgsBoEIQoAAAtc9N+WzW6/hjfI+zdWO5QtT4nvL0EwAcIkABAOpDMdPxWK/jn84N0vLbk38vsG4sM0Qtv91uDwAVpDHoDgAAUBaFpuOlLuwLTTlbv9O+LXV/6isFJbILNUi3fV5a3GVXRiz0HKWe40Wr7fAUaihPPwHAIQIUAKD2OZmOJ9kjUfu3O1uvk96OEJVfqEFa0VfE8aHijgeAMiJAAQBqW64RpcywND4sRX8onT40+7h863VS7VJfF63mwr9CxBNxHZw8qInohGLTMYWbwmqPtKt7YbcaQ1z+AHCPdxAAQO0qdjre6UPS1ddJLzzjfL1Oqj3rdSpCbDqmoaNDGjkxorOxs5fc3xJuUW9br/qW9SncFA6ghwCqHQEKAFCbiimfLV087oVnpGtXO9vnifU6FSV6IaqtB7ZqIjqR85izsbMaGB/Q6OlRDa4ZVGRepIw9BFALmKgNAKhNXspnnz5E+ewqE5uOFQxP6SaiE9p6YKti07ES9wxArWEECoHavPtxjR5/3lXbniULtHvzKp97BKBmdG6QTo5JRx5wPh3PSkhP3m/fdvqQdFNf/lGo9FGuk2N2tTlGoQIxdHTIcXhKmYhOaPjYsLYs31KiXgGoRYxAIVBuw5PXtgDqQKp89voBZ9XxQiFp0X+4+O/x+/Pv8ZQ5RfDIA3YblF08EdfIiRFXbUdOjCieiPvcIwC1jAAFAKhdqfLZTkuL37TJ2Ua5udZXdW703mcU7eDkwawFI5w4M3VGY5NjPvcIQC0jQAEAkJJtPVRmiHJSnAJlVezUPb/bA6gvvNMDAIKVmJEOD+WeKnfJ8Ynk8TOl6U++EDUTJzxVIK+FIKamp3zqCYB6QBEJAEBwEjPSQx+y1w+dOlQ4iJSraEOujXLTg5NEeKoQXvdzam5q9qknAOoB7/gAgOCM32+HJynLVLmMkalCRRv8HpnKNhKVjvBUMdoj7YG2B1BfeNcHAASnc2OOqXLT9sjUvjvyT51LFW1Ihat9d9jt/AxR63Zkv8/JRrsoi+6F3WoJt7hq29rcqq6FXT73CEAt450fABCcXOuN7nvX7JGpwVW51x2Vspx4IiHt3579vv3bna/bQkk1hhrV29brqm1vW68aQ6xoAOAcAQoAEKxsIer0IWn+9Rf/fe7pi3/PF55S9/tRTjzbY6fLVeIcgehb1lf0VLyOSIc2Lc0xRRMAciBAAQCCly1EpYemlPnXX5w6V8py4tke+8YN0rp7pBvTwlm+EFXqaoGYJdwU1uCaQcchqiPSocFbBj0XoABQf+ouQBljfsMYs9MYM2aM+bkxxjLG5Ph4EQBQNoWKNkh2qNq/vbTlxHOFp0Rc2v8RyahwiCrVmizkFZkX0a61u7Ttpm0510S1Nrdq203bdO/aezV/7vwy9xBALajHSb//r6QbJf1C0qSkG4LtTnA2735co8efd9W2Z8kC7d68yuceAah7qaINuabNSaUtJ55rVOvaX5b2b0uef489RfDGjdKTey72SbpY+jxzTdbiLmlFn7e+wZFwU1hblm9Rf0e/xibHNBGd0NT0lJqbmtUeaVfXwi7WPAHwpB7fQT4qOzj9UNKvShoNtjvBcRuevLYFgJzyFW2Yf332aX1+lhMf35N9VEuSTn87bU+oHCHq2lXS6cdLsyYLRWkMNapnUY96FvUE3RUANabupvBZljVqWdYPLMuygu4LACBNoaIN2cKT5G858c4N0vLbk39PC2ZZqwXumT2d703vs4tflGJaIbLL3Cus4PGsSwPgHe/oCFTPkgWBtAVQYXJNnbszmn9NlORvOfFQg3Tb56X1A5cGn3wh6l07pIbG2eXTCU+llZiZvVdYoZ8B1qUB8Ek9TuHzhTHmiRx31e2aqnSsrwLgWKFqeut2SKe+lXsEKn39kR9hJdSQe71SKkSln3d8j/0nHeGp9Mbvn71XmJT7Oc+2Vxjr0gC4RIBCSbC+CoAjhcJTak1UrpLmqdv9DlH5ZAtR6QhP5dG5UTqVNmUy189AKfcKcyCeiOvg5EFNRCcUm44p3BRWe6Rd3Qu7KWYBVCn+57pkWdbKbLcnR6ZWlLk7AFCdchVtyLXPU3poOve0dO1qe92RVP4QlataoJ9rspBb1tHAjJ+BUu4VVkBsOqaho0MaOTGis7Gzl9zfEm5Rb1uv+pb1sRcVUGV4hwcABCdX0YZcF75bH7+4Bmn57dJv/UPGmqQ8G9v6KV+1QD/XZCG/rOvSkj8DpdwrrIDohaj6H+nXwPhA1vAkSWdjZzUwPqD+R/oVvRAtaX8A+IsABQAITq6iDblGphoa7a/rB+x2jU3ZL6Az1yQVK191t0LVAssV4mDLFaI+HQls5Gnrga2aiE44On4iOqGtB7YqNh0rab8A+IcABQAIVqpoQ/qFba6RKcn+uqLPbpf6d/oF9PLb7fZu5avuli083bhRujHjfISo8soWotKVcV3a0NEhx+EpZSI6oeFjeTaPBlBRCFAAgMqTr5x41uNDs0emUuHKjczqbqkglCs8GUlP3p/lcQhRZZVal5ZNmdalxRNxjZwYcdV25MSI4om4zz0CUAp1V0TCGHObpNuS/2xNfv0Pxpj7kn//qWVZf1DmbgEAMuUrJ571+JA/ZamzVnezJEvSk2lTA1PhKX26YOfG2ceVs7BFvSu0Lq0Mr8HByYM51zwVcmbqjMYmx9SzqMfnXgHwW90FKEmdkn4r47ZfSv6RpB9LIkABQL3KtddTuqzhadPFdsbMDmCLVrPnUAm8WiL8p99X7Pg/Knz2qNrD89QduzD7AqdMQbbYqXvZ2hOggMpXdwHKsqxPSvpkwN0AAJRaYsaejte50dlFcyJhB6LODfboV669nm7ckDs8pc6T3tbrmixcImeJ8KuvlCS1mMvUu/yD6nvmSYWf/Dv7vjKEKK+FIKamp3zqCYBSqrsABQCoA6lCEEcesKfjFbpoTl/fdHLs4jqqbCEqc71TtgIFqVGsRasvBjL4InohWrDK3VnrFQ08+TmNRto1uPx9ihzZa99R4hDldT+n5qZmn3oCoJSYkF3HepYsCKQtAJRcrkIQ2cSnpd3vuHhxfeQBu73krbpbZrVAeOaqRPhl5xW78f0XbyxhcY/2SHug7QGUByNQdWz35lVBdwEASiNrIQhdGnbi09Lgm6UXnklru8lun5Kq7pZt36d3/S+KQ5SR6xLhnXdoi2ko+bq07oXdagm3uCok0drcqq6FXb72B0Bp8K4PAKg9uTZXTR95SCSkL75rdniaf/2lJa/zVXf74nrKlJeJpxLhP/i/ir/rL/3bKyyHxlCjett6XbXtbetVY4jPtYFqQIACANSmfCFqJm5/PX1odptzT9thKT1kZe79lO70IfZ6KhPPJcJ/8k3/9grLo29ZX9FT8ToiHdq0NMc0UQAVh486UBI9SxZo9Pjzrtvms3n3454em6mLQB3JWpJ8+NJANP96OzylH7duhx2msoWnbMez11NJ+VYivMTl5MNNYQ2uGXS8Vqsj0qHBWwY9F6AAUD4EKJREKUOK2/CU3pYQBtSRbCEqXeemS8PS+LB06lsXQ5KT4yVCVAlVU4nwyLyIdq3dpeFjw9p7fG/WkbPW5lb1tvVq09JNFR+eXt1vKzqh2HRM4aaw2iPt6l7YzbRD1CV+6lGX/AhhAKpIvkIQ63ZIDY2Xhqxc4SkVkrKNbEmEqBK5rOEyT+3LXSI83BTWluVb1N/Rr7HJMU1EJzQ1PaXmpma1R9rVtbCr4sNHzv22klrCLept61Xfsr6KD4GAnyr7fy4AAH7IVwhi//bZoSj6w0vXRkmXlizPFaJKUN2tnkUvRPWxgx/T42ce9/Q4QZUIbww1qmdRjz19sIo42m8rdlYD4wMaPT2qwTWDisyLlLGHQHD4iAx1Z/Nub7+EAVSZQoUg0qvzhULSb+7LflxmdT7p0kIVJaruVq9++MIPdeuDt+rbZ74tS5brx6FEeHFc7bd1YKvnaZZAtSBAoe4wBQ+oI9nCU+cm6c5o7up8D//X7I+VXp0vXSpElbi6W72JXojq/Q+/Xy/NvOT5sSgRXhzX+20dy/EhBVBjCFAAgNqUKzyt33lxzVNmiBpc5WykKlMoZE/bIzz55mMHP+ZLeKJEeHE87bd1YkTxRNznHgGVhwAFAKg9+cJT5hqm9BCVXjgi30gV+z65k5iRDg8VfP5eir+kfz37r55PR4nw4nneb2tyzOceAZWH8WzAhcUff7io4yl9DpTZ+J784SklVZ0vs2T5tauptue3xIz00IekIw9Ipw7lff6+8OQXlLDch9Tmxmb1v6m/KkqEVxrf9tsCahjv/EAZsO4KKLPODXZBByl3eJIuVudLD09XXyd94B/yj1QxElW88fvt8CQVfP6eOPuEp1O1zW/TluVbCE8uVNN+W0BQGIFCRfGywS0AvCrUYBd0WNwldW7MPVKUOVK18JelzQ9LDU0Zj5djJOraVdJNm+xwkO886RIJ+7ydG+przVTnRnvkqdBIXiKhC9ETnk51IX7BU/t65jV0lnu/LSAIjEChohCeAPgm1JAs7JDnV13nBulNvRf/fc0bJJMj1KRC1I0bL972zJj0pd+R9t3hbEQqtTZr3x32dLbEjPPvp9o5GclLPj/zpqKeThVuZOTJLa/7ZQW13xZQToxAAQDqV6jBHqX6XrLq2PgeSSb/+iaT9vfvp1UrK7Q2KrOwxZEH7HPX6Ka78URcBycPaiI6odh0TOGmsNoj7ep+11/aFx+ZI1HrdtjTKceHtfLqK/XdeXNdn3tly0rP/a9X3Qu71RJucVVIgv22UC8IUACA+nZTn3T6cUdTy+wAtOfibZ0bJUvSk3scts0obNGZNppVI2LTMQ0dHdLIiZGsF+Et4Rb1vvE31Ge9X+En/86+cXx41nPzOy+8qF1XXSk3K8xCJqQty7e47D0aQ43qbevVwPhA0W3Zbwv1gil8AID6VsTUsksr+w1I7x5w2bb2qvhFL0TV/0i/BsYHco5gnI2d1cCTg+pv+pmiy9+X9Zi5nZv05tZfdtWHVa2rNLfR/egVpL5lfUVPxWO/LdST2nrnBgroWbIg6C4AqET5QtRMPH8A8tK2hsSmY9p6YKvjMtgT0Qltbfq5YsZceue6HfpM92c0t6G4IDSvYZ7u7rq7qDa4VLgprME1g45DFPttod4wzoqacvLudxY8ptg9nADUiVyV9tLDj5Q9AHlpWyOGjg4VvYfQxLmjGr7icm158eez79i/XZH1O/V37/w7vf/h9+ulmZcKPta8hnn6P+/6P4rMixTVB2QXmRfRrrW7NHxsWHuP7806otja3Kretl7220LdIUChJlEOHYAr2YJQunwByEvbKhdPxDVyYqTwgVmMXPEa9b/489kXJMnn7w3rd+qr7/2qPj72cT1+5vGsm+uGTEirWlfp7q67CU8+CzeFtWX5FvV39GtsckwT0QlNTU+pualZ7ZF2dS3sYs0T6hI/9ahJhCcAroVCdkW4bCFo3Y78AchL2yp2cPKgq6ptknSmsVFj7e9Qz3uGX63CJ+nVr5H1O/W/3/6/9VL8Jf31kb/WE2efUCweU7gxrJUtK7Vl+RbWPJVYY6hRPYt61LOoJ+iuABWBAAUAQLpEwr6Qz2b/9vyjSF7aVrFip+5d0v76t6qnoTH7NEhJWr9Tcxvn6iMrPuLpPOlylllf2M2oCoC8eIdAXl6mwvUsWaDdm1f53KP8/FrflG0tFWungDqQrWJeunx7PXlpW+Vi0zFP7afiyfa51pJJvj1vjsqst/Wqb1kf63oAZFVb7+DwnZepcNU8jW7xxx/W4o8/rM27Hw+6KwDKJVe58Tuj+cuUe21bA7wGjeam5ov/yFXVMH3/LZccl1kfH1D/I/2KXoh6PieA2sMIFJBHNYdAAEUotFdTvlERyX3bGhmJKnbPoILtM5+35bdLnRs8ncNVmfUDW7Vr7a5LAiLT/4D6xv9ywKGeJQs8TWcEkEdiRhq/X+rc6CxUJBL2iETnBinU4PHcDja6zRmELMmS9OQeF21VMyGqe2G3WsItrgpJtDa3qmth16V3pJ63Rat9eZ1dlVmPTmj42LC2LN8iiel/AGwEKMChcq/nAupGYkZ66EPSkQekU4cKh4r0wHNyTLrt894ursf3ONvoNmsQyphWlq/tuz4rRX8onT508TEWrZZW9GXvl58hscQaQ43qbevVwPhA0W1723pzj9qEQrmfnyJ4KrN+YkT9Hf168eUXC45gpab/jZ4e1eCawaxl1Rm9Aqof/1NRUbyM8gCoUuP32+FJKjwykzladOQBaXGXt4vszg12EDvyQOG9mjJD1JveJ8mSvjeSv21iRtq31Q5P86+Xzj2df1parpAY5EhdAX3L+jR6erSoUZ6OSIc2Ld1U+ECPPJVZnzqjr//467pv4j5P0/8YvQJqBwEKFcXNKA/V8YAq17nRHnkqNL0t11S7zo3ezh9qsAPK4i5nwSRzapkkXfer+dumh8RzT0vXrpbePZg91OQKiZ0bgh2pKyDcFNbgmkHH64w6Ih0avGWwLGHBa5n1vcf3epr+F70Q9WX0CkBlIECh5KqtFDqAMnOyRsjJOqVizRrNaSg8ipU5mpN+fKG2mSHx9CFp/+8VFxLH9wQ7UudAZF5Eu9bu0vCxYe09vjfrSEtrc6t623q1aemmso20eC2z7jaAjZwY0X9e8p99K14BoDIQoFBy9VoKHUAR8oWodTvsTWj9Dk/lHM3xIyQGPVLnULgprC3Lt6i/o19jk2OaiE5oanpKzU3Nao+0q2thV9nX+ngNIrG4uwB2ZuqM/uTbf+K5eAWAykKAAgBUhlwhI3NjWq/hSQpm3ZXXkBjUSJ1LjaFG9SzqUc+inrKeNxuvZda9eOz0Y67apYpXUFgCqDzVXzsVAFA7sm2ims6vMNC50dkGt36P5uTaJPbTkeIqAWbr+0y8YsJTpUmVWXcj3Oht9GoqPuWq3ZmpMxqbHPN0bgClwccaqHgUiQDqTChkj8hkjjxJ9u1+hIEgR3OynTtdsZUAU19LMVJXI7yUWV8WWabvnP1OCXpV2ER0oiJG8ADMxrsqAKCyJBL2dLZs9m+/dJTIrSBHc1IhMRsnIbFcI3U1pG9ZX9FT+ToiHXrfkveVqEeFTU27G70CUFqMQAEAKke2UZ90hdYrFSuo0ZxCIdHJucoxUleB3G5E67bM+hWXXaGWcIurfaSam5o9haDmpmbXbQGUDgEKAFAZck2ZyyywUI4Qla4U4cmPkOhHCKtQ2ULSG656g06+eFIP/uBB1xvRui2z7nb639sWvk0PP+N+GnqQxS8A5EaAQl49SxZ42sMJABwptN6o0HolV+dM3wfKwWhO5j5Qrs7pU0gs90hdmcSmYxo6OqSREyNFj/g43YjWTZn1vmV9Gj09WlQ58o5Ih/7wl/9Q3zn7HVejV63Nrepa2FV0OwClR4BCXtW+ie3Ju9/peSNfACXmpFiD3yEqcx+oVIDJZv/22QHHzT5Qkn8hMaiRuhKLXogWteFsLk43oi2mzLrb6X+Xz7nc9ehVb1svJcyBCsX/TNS8ag+BQM0b31NcCW9pdkhYtLr4PZky94E69S3p3NM5js24380+UH6FxCBG6sogNh3zJTyllGIjWrfT/9yOXm1amqNACIDAEaAAAMHq3GCP6hx5oPgS3stvt9sXfc6N9shTKmCkh6dsozmZ9xe7D5QfIbFzY/lH6spk6OiQb+EppRQb0bqZ/ud29Crf6BmAYBGgAADBCjXYU+IWd11cj5T3+GRIWLTa/Xqk1JqnzJGn+dfbtzc05r+/2CDiR0gMYqSuDOKJuEZOjPj+uKmNaEuxj1Ix0/8k96NXACoTAQoAELxQg/OL+8ziDwWPz1L8IVXBLnPa3rmnZ695ynV/saM5foTEbCFMlnR46NLHzBXC/CiE4bODkwddFVlwopI2onUzegWgMvE/FTVt8ccvLR/bs2QB66KAapVZ/MFJqe/UtLf04g+Zoznzr78YlrLtA5V5v5vRnGJComR/X+nHZ4YwWfmfi8wQJpP9uQhCWgj2e+peukrciLbY0SsAlacyJ0OjplRaJTu3FfkAVIDM4g/7ttkhKZvMggtHHrDbS3agWH578u+bpK2P21+zybz/Te+TrETu82brx+EhOzR4lQphoZCz5+LVEGZyPxfllgrB++6Q9m1T7JVYyU7FRrQASoERKJRc5mhPtlEhAHAks/jD+LAU/aH0gYftdUspuarV3fj+5JS3DZdOqcu3D1RDoz2ac+0qe/Rm/0ek04+7HwEr1XMhXZzal5rmKGV/LtILYZRzal9G8Au/9CslO1W9bESbbePh9ki7uhd2My0QKAH+VwEAqke2AgmnD0mDq+xRooZGZ/skpcJMaopcak1UNulrnkxI+t7I7PM73ezWTfnzfHJW3EtIM3Hpe3ulH39LMrLDUUpm8YlShrxsMoJf+6knpBb/ZyrUw0a0hTYebgm3qLetV++/4f36ztnvELAAn/C/BgBQXVLBIfpDOzxJ9vqkwVXShw9J//DRwpvMpoeZbIErXXpQyjfq42SzW6flz50Wykg9F5YlPZkMSelT857cM/v4fOFJ8j/k5euzJI0Pqzt2QS3xuM42+ntJUusb0TrZePhs7KwGxgf0V0f+SvFE/JL7UwGrb1kflf+AIrAGCmVXaWuiAFShUMietjf/+ou3nXta+v8WFA5Pqds7N+YOOndGZ6+JSq0xkpJBKst9qfVHTjbNzSdjjZCjtVam8CHq3Jg/PKX6WeweV26kQlTnJjVK6j3/C18fvtY3oi124+Fs4Um6GLD6H+lX9ELUzy4CNa1sH80YY66QdJVlWafKdU5UJj8q4LGOCoAaGu1pe4OrLi03LuUPT6kRkHxBJ9+GtLnuy3c+p2XPM4tDpM6Zd5rgnkvvy2Rla+ehn16lPcd9T+7RaHieJubM8fyw9bARrd8bD09EJ7T1wFbtWrurpp83wC+e3iWNMdcbY75sjHnRGBM1xgwbY67LcfhHJT3j5XwAAMzS0GhP28vmnX/hPjxJs0ZJXlVoJOrTEe+hpHNj/hGulGwh6MYNuR/3yT328TPx4MNTSvI5Dt+4UYNnnlf7yy+7fqjW5lZtu2mb7l17r+bPne9jJytLqTYenohOaPhYjmmsAGZxPQJljHmtpG9Iakm7eYOkdxljNlqWxRABAKC0Egl7zVM2f9wy+9/pIeHwkLMAkWskKrUPVOZ9uc5XjEKjX6FQjhGkjbNHmbLJtsdVUOEpJVkBMTI+rF3PPqfhKy7X3itek3VNVGtzq977xvdq8RWL9cOf/bAuN6It5cbDIydG1N/RXxfPI+CFl/8h/112ePqCpD+SNC3ptyXdJenvjTG3W5b1kOceAgCQTaHiD+kyQ0LnBrvi3JEHCgeIzECz/PbkxrQqXP7cbSjJF6KyThNMhqfMohGFBB2epFkVEMOWpS0v/lz9L/5cY+F5mli0UlPXdav5svoKSfmUcuPhM1NnNDY5xia/QAFe3jHfIelJy7I+ZFnWs5Zl/dSyrM9IepukFyT9H2PMu/zoJAAAs+Raw/OHOT6Zf9dfzg4JoQa7XPf6AWcBIhVo1g/MLvNdqPy50812852z4DTBLOEpWyGMbLyEPD/kCMGNknpiF3THU9/Qx549pTtu/LB6FvXUfXiS7AISpVTKgAbUCi/vmq+X9GjmjZZl/aukbklRSSPGmFs9nAMAgNny7fP08O9nb/O51fban3ShBnsantMAEQolj08LT4XKnzutopfvnJkhKl2u8LR+58XNf/NV1fMa8rwotgJivn4mZuxpmU6/l0QiefyMu74HqNRFHqamp0r6+EAt8BKgLkjK+s5jWdYJST2yR6L+3hhzi4fzAABgc7JJbjapfaIyQ5Tf/ch68X+Hswv7XBf1qWmC2aTv/yTZUwuvzah0mm9d1PiwtPsdUny6cP/8lK8K4KvBz2GIKrbse+rc++6w21VZiGqPtJf08Zubmkv6+EAt8BKgfizpxlx3JkPUGknnJT0k6a0ezgUAgF2u2+k+T//v85fuE3XfO72PuDi6+E+rhje+p3CIyndRn2+a4JNpm+Z2brAD4v6PzK62V2hd1OlD0uCbyxeinJRQz1cBMfN5zCz7ni9EZds4OH3j4TziibgePfWodn53pz7z+Ge087s79eipR3PusVQq3Qu71RJuKXygS6UOaEAt8BKgviGp2xhzZa4DLMs6JukWSS/JDlMAALjXucEu4iAV3uep8TJ7n6j0EHX6kLdpdU4v/q9dPbtdvhCV76LeaaGMGzfa5/ze3uT5hu0Rt1klzjdenM73pl7p6l+6eN8Lz0hffFd5pvNlC8H5KiBmhqjMPa+8lH13sHFwbDqmLzz5Bd364K3aPrpdf33krzV8bFh/feSvtX10u2598FZ94ckvlHxtUkpjqFG9bb0leezW5lZ1LewqyWMDtcRLgHpY0hxJH853kGVZ35Mdon7m4VzALD1LFgTSFkDA0os/ONm0NrXZbnqg8bI2yenF/019dmDJbPvdjCCU76Le6TRBSTK6NEikby7cuUl690DyedsphZqkF340+zG8hsukgiM1mSHYSQXE1PeVXgEx1zHSpa+xy42Doxei6n+kXwPjAzlLh5+NndXA+ID6H+lX9EI052P5qW9ZX0lGinrbeinUAThgLKvQphF5GhszR9KMZVkFx6+NMVdJutKyrB+7PmEVMMY8sWLFihVPPPFE0F0BgNp2eMge1UnJd0Gc7QJ6/YBdFKIYqfU2TsqfJxLSl++YPYXuxg3Suwfz7OXkcKPffGvB7nunHYZS5l9vh8iGxuzt5l8/O2y5eV5kj9QMHR3SyImRrGGjJdyi3rZe9S3rU7hhjj3K1rnRWRGPRMIOoJ0bLhbxyHaM0/VxDsJTbDqm/kf6i6pK1x5p1661u0pe6EGyw93WA1t9q5rXEenQvWvvLUvfgUqwcuVKHT58+LBlWSuLbeupdqllWS87CU/JY39W6+EJAFBGfo9kOFFM+fNQyB71SR+JevL+2euT3ISnbN+PZB+/f7v0W/ukq6+7ePu5p+3bc51z6+Oen5eiR2pe/pm3Coi5jnFU9t3Z3ldDR4eKDicT0QkNH3OwL5kPIvMi2rV2l7bdtC3nmiino0kdkQ4N3jJIeAIc8jQChUsxAlU+m3c/rtHjz7tq27NkgXZvXlX4QACVLTHj/0iG35ysY0q/qPdjZO3G/yzd967ZI1H5zunheTn/8nnd/vDtOn3+tOM2JR2pyfd8OwxP8URctz54a84wmE9rc6u+8p6vlHUqXDwR19jkmCaiE5qanlJzk73x8M0tN+vvjv+d9h7fm/V7aW1uVW9brzYt3UR4QsnFE3EdnDyoieiEYtMxhZvCao+0q3thdyBTR72MQNVlgDLGLJT0R5JulRSR9KzsSoGfsizrBY+PTYAqk8Uff9hT+5N3v9OnngBAAcVc1OeaJpgrLKY/9vLbL270OxO/dDpfrnMW9b3Y/Yi1/ycNPbVHuyd2u9o7aNtN27Rl+Zbiz+/ETNweecp0Z9SeyljAo6ce1fbRHJUPHbin5x71LOpx3d5vuQJW18Iu1jyh5Iqa3lvGIO8lQNXd/xpjzPWS/kXSayV9WdJTklZJ2i7pVmPMWy3LKs8qUABAfUjt5ZQtQK3bMTvIpKYJLu66GJbSQ9WpQ9mn8y1afXEEKVX6PNcIVOY5nUr2I/r9EW09+jlNzPyi+MdIGjkxov6Ofv8v4POVfd+/3VFw9LquaCI6UVEBqjHUqJ5FPRXVJ9QHJ2v1UtN7R0+PanDNoCLzsnz4UWHqLkBJ+pzs8PQRy7J2pm40xvwvSR+V9MeSfjegvlU9ptUBQBbFXtSHGmYXcsjc60i6NESljncyZdBhkLjE+P2KfW+vtr7utZ7CkySdmTqjsckxfy/qC33v2Z67LLyWJHczIgfUmth0rKhCJxPRCW09sLVshVi88FREotokR5/eLumkpMGMuz8haUpSnzGGbbhdchuevLYFgIrl5KK+UPlwL3sduT1njn4MLfkVTcyZU1y7HO6buM+/zWidln138L17vXhrbuIyAqj0Qixe1FWAkpT6mOtrlmXNeue0LOu8pG9KCktandkQAICi+XVR73avIy/nzCKuhEYaXnJ8fCGHnzvsz2a0+UrCNzQWfu4yeN1jqRR7NAHVJJ6Ia+TEiKu2IydG/PlQpYTqbQrfkuTXEznu/4HsEao2SQfyPZAxJleViBvcdQ21jKmNQB0qtHlrqmR56v5C08vytcm215Ef58xwcPKgq8p0hXhaA+Fkk9wiv/fuhd1qCbe4rsLXtbCr6HZALfHyXlGS6b0+cz0CZYy5zBjzuDHmgDGmqcBxB4wxh/IdVyZXJr++mOP+1O1Xlb4rqCdMbQTqTDEX9X6MRGXudeTnOdP4tWlrvsffemBrcSNR43uc7fOU63sf36NMjaFG9bb1Ftl7W29bL5XtUPf8KMRSybxM4dskaaWkv7AsazrXQZZlvSLpz2RXutuY67hqY1nWymx/ZFf1AwDUsxJc1Odtk42f50zyWlzBiaLXQJRoQ+W+ZX1FT8XriHRo09ICrwtQB2q9EIuXAPUeST+yLOsfCx1oWdZXZU+Pc/dxjn9SI0xX5rg/dfvPSt8VAEDNKtFF/aw263bkOX8JzinvxRWcKmoNRKrs+/oBZ1MRU9/7+oGLe2ZlEW4Ka3DNoOMQ1RHp0OAtgxVfPQwoh1ovxOJljPkmSQXDU5qDkv6jh/P54Xjya1uO+9+Y/JprjRRKzOvmuABQEbLt5ZT3+Cx7OeWTryz6taud7fNU7DlVvuIIRa+ByCz7XvD4kKPjI/Mi2rV2l4aPDWvv8b1Z13S0Nreqt61Xm5ZuIjwBSbVeiMVLgLpGUjGrw85KCnpnrNHk17cbY0LplfiMMZdLequkmKQcOw8CAOBQiS7qC5YqP33I+T5PTs+Z5KW4QrEqZTPacFNYW5ZvUX9Hv8YmxzQRndDU9JSam5rVHmlX18Iu1jwBGWq9EIuXKXwXJL2miONfI8m/2qcuWJb1tKSvSVosaWvG3Z+S1CxpyLKsyp54CQCoTz7udeSGl+IKxaq0NRCNoUb1LOrRHTfdoY+t+pjuuOkO9SzqITwBWdR6IRYvAeq0pJuLOP5mSac8nM8vH5b0nKR7jDEPGWP+1BjzqKSPyp6694eB9g4AgGx83uvIrb4bNqq9oZjPT92p9DUQAPKr5UIsXgLUY5L+gzGmYIgyxqyU9BZdnEIXmOQo1M2S7pP0y5J+X9L1knZIWm1ZVjS43gEAkEWpyqK76Ef4Kx/T4I+eUvvLL/vzmDlU+hoIAPnVciEWLwFqQJIlacQYszTXQcaYGySNSJqR9DkP5/ONZVmnLcvabFnW6yzLusyyrNdblvV7lmW9EHTfUB49SxYE3QUAcK6UZdFd9COSSGjXs89p25zFagm3ZD20NdyiZhUuTJG1bRWsgQBQWKoQy7abtuV+r2hu1babtunetfdq/tz5Ze6hO64nGFqWddwY80eSPinpu8aY/yvpUUmTyUP+vaQ1kt4raY6kuyzLOp7tsYByOXn3O4PuAgAUr3ODdHJMOvKA8xLlkh2eHJYoL7Yf4Rs3asv6nepXImdxhXuP/I0Gnhws+jTVsAYCgDO1WIjFU28ty/ojY0xc0ickbZD0/oxDjKRpSX9oWdafejkXAAB1q9Rl0T30o1Eh9SzqyVoxr6/9NzU6+ZgmohOOT1EtayAAFCdViKUSqmt65TnuWZb1J8aYPZL6ZZcBf13yrmclfUPSbsuyfuz1PKgOPUsWaPT480F3w7HNux933d+eJQu0e/Mqn3sEADmUqix6CfuRWgOx9cBWRyGqmtZAAKhfvoyXJQPSJ/x4LFQ3N4EiyM1zvYS9agqKAFC0xIw0fr+zES/JLlQxvueSEa9a3Iw2nojr4ORBTUQnFJuOKdwUVnukXd0Lu6tuKhKA4nn+X26MWSTpzbILSvyrZVmnPfcKKJEgwxoAVI3EjPTQh+w1V6cOFd6UN71K4Mkxe5pfWoiqlTUQsemYho4OaeTESNYg+Np5r9XNrTerJdyi6cQ0wapCEHjhN08/NcaYP5f0e7LXOkmSZYz5S8uy/h+vHQNqiZepjVQMBFB24/fb4Um6WP0vV4jKLLF+5AF7jVSWaX7VvAYieiFacCricxee0z8+84+X3N4SblFvW6/6lvVVxQhbrSgUeHld4JbrAGWMeb+k/yp75Okp2SFqiaT/aow5bFnW3/nTRaD6sVYKQFXp3GiPPKVCUa4QlWt/qs6N5etrGcSmY47XcWVzNnZWA+MDGj09qsE1g4rMi/jcQ2RyEnh5XeCWl32gPigpLukWy7LaLctaJmmtpISk3/ajcwAAIABONuV1srlvjRg6OuQ6PKWbiE5o64Gtik3HfOhVceKJuB499ah2fnenPvP4Z7Tzuzv16KlHFU/Ey96XUis28Ab5uqA6eZnCt1zSly3LGk3dYFnW140xX5b0Nq8dAwAAAcrcTyr967od0v7tdRGe4om4Rk6M+PZ4E9EJDR8b1pblW3x7zHzqcRqbm8Bb7tcF1c3Lu9zVsqfuZXpK0lUeHhd1hjU+AFChco1EfTpS3eEpMSMdHro4mpbHwcmDWYOHFyMnRsoy8hO9EFX/I/0aGB/I+T2kprH1P9Kv6IVoyftUal4Cb7leF1Q/LyNQIdmb5Gaa1sWiEkBBxawPoooeAJRZtpGodNUYnoqoMDjx0+/73oUzU2c0NjlW0mIabqex7Vq7q6pHorwE3nK8LqgNXt/tLF96AQAAKlcoZE/by2bdjuoJT9KlFQbT13VlSiQUO35pVT0/+LGmKh8v09iqmdfntdSvC2qD13e8TxpjZtL/SLpLkjJvT/5hXBQAgGqTSNhrnrLZv93RVLiK0bkxf3GMlGSRjPDZoyXpxtT0VEkeV6rvaWxeC0GU8nVB7fAaoEyRf6roIyoAAJC12l66QqM4labICoPtr7xSkm40NzWX5HElf6axVSuv0w9L+bqgdrgONJZlhdz88bPzAACghHKVKr8z6mwUp1LlC1Ez8Vnfc3fsglrMZb53oT3S7vtjptTzNDavz2spXxfUDgINAAC1qohqc/bxieTxM/n3eWpoLDyKU+kcVhhs7Nyk3uX/xddTtza3qmthl6+Pma6ep7F1L+xWS7jFVdtSvy6oHV6q8AFl17NkgUaPPx90N17ltipgz5IFRVUfBICiFVltblZgeuagHZLG7794f2a1vXz7RFVLVT6HFQb7Zl7S6ORjvo3M9Lb1qjFUukuwep7G1hhqVG9brwbGB4puW+rXxS/xRFwHJw9qIjqh2HRM4aaw2iPt6l7YXRX9rwU8y6gq+UJHNZU4Hz3+fMH+ErIAeJJZbU7KHWwyR5u+t3f2/blKlecKUYtWSyv6/Pk+SujVC9Fr2xQ7dZXCCUvtr7yi7tgF+wIpWWEwHAprcM1gUWXBc+mIdGjT0k2FD/SgFqexFRMa+pb1afT0aFGvVTleF6/qcVPkSkWAQkXavPvxQEeaTt79zoLHlDqwVdJIG4Aq1LnRHnkqNDqUbarejRukRNwOUoX2ecoMUctvlzo3+P/9+CjrheiVV7x6f0s8rt7zv1DfvjsUfvfnpFBIkXkR7Vq7S8PHhrX3+F5XRRo6Ih0avGWw5Be33Qu71dzU7Goq3muaXlNR09jchIZwU3GBt1yvixfRC9GC309qU+TR06MaXDOoyLxIGXtYXwhQqEiEBwDwyMkUu3zrnGRJ13XbQazQdLzUuRattsNTqMH3b8cvji5EGxs1cPVVGn3+UQ0+9DuK3PYFeySqKawty7eov6NfY5NjmohOaGp6Spc1XKazU2f1nbPfyXqR39rcqt62Xm1auqlsF+lGxlU7q4K2+PQSGpwE3iBeFzfqdVPkSkaAqmJeRmmYHgYAdSBfiFq3w97DKVt4SgWmYqbhhUIVP22v6AvROXO09af/rF1f/vCrI1GSvc6mZ1GPehb1zDo+nojPClbNTc1qj7Sra2FXWdemHJw8qF9M/8JV26npKX39x1/Xrdfd6nOviuNHaMgVeIN6XdzysinyluVbStSr+lb5PzXIycsoDSM8xQl6SiEAuJYrRGUWTSg0Va8GuLoQnTNHwycf1pZ92wo+P7mCVbl5Xae198TewAOUn6GhUl4XN7xuitzf0V8VIbHa1O67JOAjwhOAqpatZHe6OghPni5Er3iN4lVUpt1rGfOJn04onoj71JvieQ0NQfbdb/W8KXIlq913SsClniULgu4CAPgvFLKn7WWTrDZXyzxdiDY2aiw8Lzlyt8fnnvnP67qXWDwW6IU3oeGiet4UuZIxpoe65qTaHgDUhETCXvOUzf7t2UegEjN2OXQnhSRS5xjfU5GFJDxfiF52mXresL7iKwxK/pQhn4hOBDblzY/QUI3T9bKp502RK1ltf9wEFLD44w9r8ccf1ubdjwfdFQAonWzV9tJlm56W2oh33x3Opq6lzrHvDrtdYibj/hnp8JDzKXCJRPL4mcLHOuD5QvQNvybd9vmKC4bZdC/sVrjR2yhUkBfehIaL6nlT5EpGgALEGicANSxXqfI7o7PXRGWGqMyNePOFqMxzHHnAbv/q/T6HMRc8X4j++5urIjxJdtGEZZFlnh4jyAtvQsNFtbgpci0gQAEAUKvy7fPU0HhpYYn0oNS5MX/AKnSOzo1pbX0MYy7V24Xo+5a8z1P7IL/fenut8ule2K2WcIurtq3NrRW1KXItYQ0UAAC1KF94Sq1nKrTZrpeNeNPXTHVulE4dyv04hfqcHsZcSl2IuilOUI0Xor/++l/XgnkL9PyF4mdYlOv7jSfiOjh5UBPRCcWmYwo3hdUeaddb/t1b6uq1yqcx1Kjetl4NjA8U3ba3rZcS5iXCswoAQC0a31M42Ei5Q9Si1fbGuF424i10Dqn4MOZSvV2INoYa9Z43vEdf+N4Xim5b6u83Nh3T0NEhjZwYyRqSWsItWnzFYlcBqhpfq0L6lvVp9PRoUcU1OiId2rQ0x7YF8Ky2fsJQUl42k+1ZskC7N6/yuUcAgJw6N0gnx+wpcIWCSGbAWX77xWpzfm3Emy9EFRPGPKinC9HohagO/tvBotuV+vuNXohq64GteV+Ds7GzOhs7q7kNc/XSzEuOH7taX6tCwk1hDa4ZLPi8pXREOjR4y6DntWTIjQAFx7wUWqBIAwAE4PVvlV7/K9JNm5wFkWtX2X9u2jS7YEK28JPOadjxK4y5VC8XorHpmLYe2Kpj544V1W7Z/GUl/X5T/XIaYF+aeclxiKrW18qpyLyIdq3dpeFjw9p7fG/W0bnW5lb1tvVq09JNNfs8VAoCFFCh2NAXgGupqnep0aebCnwqnz59bvnt2Y9PbcSbLUAVsxGvX2FMcrVPVeTYP2rXr/+Nho/fX7MXokNHh1ztpdS9sFvz587Pel+u9UrdC7sdT5lz06+XZl7S6tet1jMvPlOTr1Uxwk1hbVm+Rf0d/RqbHNNEdEJT01NqbmpWe6RdXQu7am76YqXiWUZF6lmyoKZGrdiwF0BZZVa9k3KHkmxV7xZ32eufMo8rdiPeXPwIY+kh8dShwudP+z7DJ8e05bbP1+SFaDwR18iJEVdtH3r6If3Ojb8z63t3sl6pt61Xfcv68gYYL/06+fOT+of/9A/61k++VVOvlVuNoUb1LOqpmc2Cq1F9/cShaqTWSy3++MMB9wQAqpDfVe+cbMSb7fFz8SOM+RASG1f01dyF6MHJg66KL0jSmakzGpsce/X5cLpeaWB8QKOnRzW4ZlCReZGS9OtbP/lWzb1WqF4EqCrmZZQmiOlhhCEAKBM/q97lOi6z8IPTEOVXGKuA0uiVyM3Uvcz2PYt6il6vNBGd0NYDW7Vr7a6sI1F+9QuoBASoKkZVO3+VKuCxlglAIPyoelcoZBUKaZn8DGMVUBq9EsWmY57aT01PSXK3XmkiOqHhY8PasnxLyfoFVAICFKpCrjVEXkqr+4X1TQAqlpeqd35sxFvKMFbo/GUqjV4MPwoxFOK1kEJzU7On9UojJ0bU39F/yffjR7+ASkGAQlVLH4VjiiAAZOG26p1fG/FK/ocxJ+cvojR6qYONX4UYnGiPtHtu7+c6Kj/7BVQKAhQAALXOTdU7vzbilfwNY07Of8n3kv185Qg2fhZicKJ7YbcWzFug5y8UPzsjZEJ66txTujBzwfX5pezrlboXdqsl3OIqmLU2t6prYZenPgF+qs0JwKhLrDUCgBwKVb1LJC69PdQg3fZ5af1AcZvkrh+w26VvxNu5wQ5VkvMw1pnciyozjOU7/7od2e/LEhKjF6Lqf6RfA+MDOS/qU8Gm/5F+RS9EC/chg9tCDF7WC70y84qMjKu2CSuhzz35OX35h192fX4p+3qlxlCjett6XT1eb1tv3ZUqR2XjpxE1w21RDab+AahpXqrehRryj/xkCoWyH58KY4u7nG16mwpRi1bb4Sk9jOVSRGl0vyvM5eJ3IQan53zuwnOu2qace+mcp/a51iv1LevT6OnRop6TjkiHNi0tsBE0UGaMQAEAUKtyrT26M3pxhEey79+3LftIlF9SYayYzXZX9DkPT4VCYtr35yXYOOW1EEM8ES+6nZdz+inXeqVwU1iDawYdr2fqiHRo8JZBz+vCAL8RoAAAqEX5Cjc0NM6eJieVJ0SVQpEhMR5/pSzBxo9CDMXyck6/FFqvFJkX0a61u7Ttpm1qCbfkfIxtN23TvWvv1fy580vVVcA1pvABAFBrSln1rpK4KI1+cPqnvleYyyaIjWO9ntMPTtYrhZvC2rJ8i/o7+jU2OaaJ6ISmpqfU3NSs9ki7uhZ2seYJFY2fTjjWs2RB4HsuAQAcyKx6d+3q7NX2coYoKxlCHEyfC4rLkDjxb9+Srr7S9WmdBpsgNo71ek6vil2v1BhqVM+inqKDIhA0AhQcc1ukQaJQAwCUVXoJ8quvk04fuqSQwqsyQ8bV19kBLBG/tJpeJXFZGj0WclehLsVpsAli49hSrBWaP3e+o6ISrFdCPSFAAQBQa1JV70KNdtCQClTbS5YAj/7QDluSHb4WdxVXha+cXO5TFT6539NpnQabIDaOLcVms7e94TY1NzVr7/G9Wac+tja3qretV5uWbiI8OVTqjZtRerxKAADUolCDvSeTTOE1TqkS4KnwJNmhpHNj2bpbNJel0dsPRqQff8n1aZ2GlCA2jvVyzlw6F3SqZ1EP65V8UI6Nm1Ee/MQDAFCrnBSKcLKWqFK52Kequ/sutTz4LyUPNqmNYwfGB4o+j9uNY72cM5v075f1St5EL0QL7j2W2rh59PSoBtcMKjIvUsYeohgV/s6IWtGzZEEgbQGg7qVCVLaS5TPx6g1PLqVChhvFBpu+ZX1FT6vzunGsm3Pm4jbIYTa3GzcHXRQEufG/AmXhpQBFqXmpLki4A5BVYkYav9/Z1DLJHgUa32Ov6ylF0YZcI1GZG8/WeHhK6VvWp9HTo0WV/XYTbFIbxzq9ePajEEOx58zXFy9BDhd52bh5y/ItJeoVvDCWZQXdh5pijHlixYoVK5544omguwIACEJiRnroQ86KG0izp9Atv720le+yTddLCSo8BRQ2nUypSkkFG7ebusamYxo+NlzWQgyFzplPoe+XIgjOxRNx3frgra6mjF415yr902/8k+Y2zi1Bz7By5UodPnz4sGVZK4ttS4DyGQEKAOrc4SFp3x0X/50vmGQLNOsHSlv5biYufTrL2oo7o1JDmS9+Aw6b5Q428US8rIUY4om4Rk+N6qsnv6pnp57VjDWjV2Ze0U8v/FQ/e/lnlxxf6PulCELxHj31qLaPbnfd/qo5V2nT0k08pyVAgKogBCgAqHNOizIEUbyh0kagKiRsljvYlFqhoPPaea/Vm1vfrJbmFr0y84qj77eYEbv2SDtFEJJ2fnen/vrIX3t+HJ5T/3kJUNX3rgAAQCWr1Mp3+cJTtj6WQ+dG6dQhZ2XWsz1fPpVZr6UKc06CznMXntPDzzzs+KLcbRGEXWt31f2oiV+FIHhOK0ttrxIFACAIlVb5LlcAuTOavY+JRGn6kSnf85TqQzWXWS+zUlV781IEod75GXZ4TisHI1CoSpt3P+6pcl4lVwUEUCMqpfJdoQBSaLSs1PL1Yd0Oe4NfwpMjpaj2Fk/ENXJixFV/Rk6MqL+jvyqnQfrFr5LyKTynlYF3H1Qlt+HJa1sAKEq2EZZ0QYenXH2slJGoT0cITw55DTrxRDzrfQcnD7qqICdJZ6bOaGxyzFXbWtG9sFst4RbfHo/ntDLwDgQAQCmFQvZISjbrdpQ2DIzvcRZAcgWY8T2l61umoMNmlStV0PGyl5Qf7audl42bc6n357QS8C4EAEApJRL2NLRs9m8v7ShP5wa73LdUOIBkBpjlt9vtyynIsFnlShV0vBZBmJqe8tS+FvQt6/N1Kh/PafB4JwIAoFScVL4r5VS5UIO9V9L6AWejN6kQtX6gtBv65hJk2KxypQo6Xjdxndc4z1P7WhBuCmtwzaBvIaq5qdmXx4F7BCgAAEqhUirfhRrsvZKcjt6EQsnjAwhPQYbNKue12lvOi3K2C/VFZF5Eu9bu0rabtunKy6709Fh+F6ZA8QhQqCqbdz+uxR9/OOhuAEB++Yo3NDQGX7Sh0lRK2KxiXi+qc7Y3nh4WacJNYW1ZvkVf7/26rppzlavHaG1uVdfCLn87hqJRAxFVhQp6ACpeMZXvpODKh1eKCimzHk/EdXDyoCaiE4pNxxRuCqs90q7uhd2BlYwupk+pam9uCkmkLsqzne8HL/zA0/dwIX7BU/taNLdxrjYt3aSB8YGi2/a29VLCvALU1StgjGmS9GFJnZJukrRMUpOk/2JZ1t8E2DUAQK0otvKdNDscLFptT6GrBxUQNmPTMQ0dHdLIiZGs4aMl3KLetl71LevzdVNUv/uUqvbm5qL8tutv073fuzfn+bxgvU52fcv6NHp6tKjiHx2RDm1amqNKJcqqjj7ikiQ1S/qspA9IapV0JsjOAABqULVVvgtSwGXWoxei6n+kXwPjAzmDw9nYWQ2MD6j/kX5FL0Q9na/UfXJT7e2Gq2/QP0/+c97zecF6neyKLSzREenQ4C2DZQvxyM9YVv2sDjTGXCZpjaRxy7KeNcZ8UtIn5OMIlDHmiRUrVqx44okn/Hg4ZCjV+qeeJQu0e/Oqkjw2gDqUmJHG75c6NzobIUkk7DDQuaH8xRuClJiRHvqQdOQBZ/s8pY9YLb/dU6XA2HRM/Y/0FzUC0B5p1661u0p2EetHn6IXotp6YKujx1g2f5lmrBkdf+G46z7n09rcqq+85ytMOcsjNh3T8LFh7T2+N2uAbW1uVW9brzYt3UR48tnKlSt1+PDhw5ZlrSy2bV39RFuW9YqkrwTdD1Qe1lYB8FWq8p3j40P1M20vXarM+uIuZ2EzNRK1aLXnsDl0dKjovZMmohMaPjasLcu3uD5vqfuUqvbm5KL8lZlX9IUjX/Cl79mwXqewVGGJ/o5+jU2OaSI6oanpKTU3Nas90q6uhV08hxWIVwQAAAQngLAZT8Q1cmLEVduREyPq7+gv6qLWSTEIP/vk5KJckm598FZX53OC9TrFaQw1qmdRj3oW9QTdFThAgHLJGJNrjt4NZe0IAAAoysHJg67X+5yZOqOxyTFHF7rFFIM49Owh3/uU76L80VOPlmTNk8R6HdQ+AhQAAKgrxU6Ty9a+UIByshYpVQxi9PSoVrSsKHmfMo/3G+t1UC+qLkAZY05Ken0RTfZYluX7GHKuBWfJkSlv74IAAKBkYtMxT+2npqcKPr7TQg6SHWaenXq2pH3K5PU5yHT1nKu1/7b9mts419fHBSpR1QUoSU9LeqmI439Sqo6gOJt3P06xBgBA4LyOjhTa28hNMYhzL53z0qWi91vye4TohZdf0Ld+8i3W8KAuVF2AsixrTdB9gDuVHp5SJdIpaQ4Atc3r3kT52nspBuFFsd9TKfZnKnYaIVCt6m0jXaCgSg96AABvuhd2qyXc4qpta3Prq1XssvFSoMKtQn3KxstzkEux0wiBakWAAgAAdaUx1Kjetl5XbQvtbVSK4gyFuNlvyctzkEux0wiBalV3AcoY83FjzH3GmPsk3Za8eXPqNmPMB4PrHQAAKIe+ZX1FT2NzsreR1+IM8+fOL+p4L/stuXkO8inFtECgEtVdgJJ0q6TfSv65MXnbW9Ju+5WA+gUAAMok3BTW4JpBxxf9Tvc28lqc4V2/9C7f+5RLsc9BPm6mEQLVquqKSHhlWdbbgu4D/HHy7nfO+neqCAQAAE5E5kW0a+0uDR8b1t7je7OuXSp2byOvYeTmlpu1tXOrr33Kx8lz4ISbaYRAteInHQAA1K1wU1hblm9Rf0e/xibHNBGd0NT0lJqbmtUeaVfXwq6igkGqOIObIJIaxWkMNfrap0LSn4Ov//jr+p//+j/1/AXnBZW8TCMEqhEBCgAA1L3GUKN6FvV4LsOdKs4wMD5QdNvMURy/+uRUY6hRt153q97c+mbHGwF7nUYIVKN6XAOFGtWzZEHQXQAAoGQFKsolNa1v203bcpY6b21u1babtunetfcWXfgCqHaMQKFmpG9+y3ooAEBQUsUZqnkUx++pjUAt4ScfAADAZ6UoUBGEck8jBKoBAQoAAKAEGMUBahP/awEAAEqIURygtlBEAgAAAAAcIkChbPyskkfFPQAAAASBKXwom/QqeaXWs2SBRo873wQwsy0AAACQDQEKNamcYQ0AAAD1gyl8AAAAAOAQAQoAAAAAHCJAAQAAAIBDBCgAAAAAcIgABQAAAAAOUYUP8Gjz7sc9lUynYiAAAED1YAQK8MhtePLaFgAAAOVHgAIAAAAAhwhQAAAAAOAQAQoAAAAAHCJAAQAAAIBDVOFDVfJS+W5+82U6N/WKq7ZUzQMAAKhvjEChKnmpXuc2PHk9LwAAAKofAQoAAAAAHCJAAQAAAIBDBCgAAAAAcIgABQAAAAAOEaAAAAAAwCECFAAAAAA4RIACAAAAAIcIUIBHPUsWBNIWAAAA5dcYdAeAard786qguwAAAIAyYQQKAAAAABwiQAEAAACAQwQoAAAAAHCIAAUAAAAADhGgUJW8VK+b33xZIOcFAABA9aMKH6oSle8AAAAQBEagAAAAAMAhAhQAAAAAOESAAgAAAACHCFAAAAAA4BABCgAAAAAcogpfgBKJhM6dO6fz58/r5ZdflmVZQXep6hhjNGfOHF1++eWaP3++QiE+EwAAAEDpEKACkkgkdPr0acVisaC7UtUsy9JLL72kl156SVNTU7r22msJUQAAACgZAlRAzp07p1gspsbGRrW2tqq5uZkLfxcSiYSmpqZ05swZxWIxnTt3Ttdcc03Q3QIAAECNIkAF5Pz585Kk1tZWXX755YH25ZmfTun8S9Ou2l4+t0nXXdPsc4+cC4VCrz5/k5OTOn/+PAEKAAAAJcOQR0BefvllSVJzc3DhI8VtePLa1k+p5zH1vAIAAAClQIAKSKpgBNP2/GGMkSQKcQAAAKCkuHpHTUgFKAAAAKCUCFAAAAAA4BBFJFC1MotfxF+Z0Q+e+4Xe8cWHC7btWbJAuzevKmX3AAAAUIMYgULV8lLAYvT48z72BAAAAPWCEagasnn3466Dwc2vv1p3rVvmc4+cm5yc1F133aWvfvWrikajet3rXqfbbrtNn/jEJ3T11VcH1i8AAAAgHQGqhngZVfnOj1/wsSfFefrpp/WWt7xFzz33nN797nfrhhtu0OOPP64dO3boq1/9qr75zW8qEokE1j8AAAAghSl8CNyHP/xhPffcc7rnnnv00EMP6e6779ajjz6qj370ozp+/Lj+8A//MOguAgAAAJIIUAjY008/ra997WtavHixtm7dOuu+T33qU2pubtbQ0JCmpqYC6iEAACineCKuR089qp3f3anPPP4Z7fzuTj166lHFE/GguwZIYgofAjY6OipJevvb337JpsKXX3653vrWt+prX/uaDh06pDVr1gTRRQAAUAax6ZiGjg5p5MSIzsbOXnJ/S7hFvW296lvWp3BTOIAeAjZGoBCo48ePS5La2tqy3v/GN75RknTixImy9QkAAJRX9EJU/Y/0a2B8IGt4kqSzsbMaGB9Q/yP9il6IlrmHwEUEKATqxRdflCRdeeWVWe9P3f6zn/2sXF0CAABlFJuOaeuBrZqITjg6fiI6oa0Htio2HStxz4DsCFAAAAAIzNDRIcfhKWUiOqHhY8Ml6hGQHwEKnlw+t8lT+9QIU2okKlPq9quuusrTeQAAQOWJJ+IaOTHiqu3IiREKSyAQFJHAq5YvvKrs51yyZImk3GucfvCDH0jKvUYKAABUr4OTB3OueSrkzNQZjU2OqWdRj8+9AvJjBAqB6umx3/S+9rWvKZFIzLrv/Pnz+uY3v6lwOKzVq1cH0T0AAFBCxU7d87s94EZdBShjzBuNMR8zxjxqjDltjHnFGHPWGPNlYwwfXwTg+uuv19vf/nadPHlSg4ODs+77xCc+oampKfX19am5uTmgHgIAgFLxWghiapp9IlF+9TaF79OSbpd0VNI/SjonaYmk9ZLWG2O2W5Z1T4D9q0uf+9zn9Ja3vEUf+chHdODAAS1dulTf/va3NTo6qra2Nv3xH/9x0F0EAAAl4HU/p+YmPmBF+dXVCJSkr0paYVlWu2VZv2NZ1n+3LOs9ktZImpb0Z8aY1wXbxfpz/fXX6zvf+Y4+8IEP6Nvf/rb+4i/+Qk8//bS2b9+uQ4cOKRKJZG3npYBFz5IFrtsCAAB/tEfaA20PuFFXI1CWZd2X4/Z/NsY8JunXJb1F0oNl7BYkXXvttdq9e3dRba67ZvanTsfOP6vlC6/UybtZLwUAQDXoXtitlnCLq0ISrc2t6lrYVYJeAfnV2whUPtPJr1VbD9PLqAojMgAAoNwaQ43qbet11ba3rVeNoboaC0CF4KdOkjHm9bKn8cUkHXTY5okcd93gV7+KtXvzqqBODQAA4Erfsj6Nnh4tqqJeR6RDm5ZuKmGvgNzqfgTKGDNH0h5JcyR90rKsFwLuEgAAQN0IN4U1uGbQ8XqmjkiHBm8Z9FyAAnCr6kagjDEnJb2+iCZ7LMvK+hGFMaZB0pCkt0p6QNKfO31Qy7JW5njMJyStKKJ/AAAAdS0yL6Jda3dp+Niw9h7fm3VNVGtzq3rberVp6SbCEwJVdQFK0tOSXiri+J9kuzEZnoYl9UraK2mTZVmW9+4BAACgWOGmsLYs36L+jn6NTY5pIjqhqekpNTc1qz3Srq6FXax5QkWoup9Cy7LWeH0MY0yT7Gl7vZLul/SblmXNeH1cAAAAeNMYalTPoh71LOoJuitAVlUXoLwyxlwme8Tp3ZL+VtJmy7ISwfaqdjzz0ymdf2m68IFZXD636ZLS5AAAAEAlqasiEsmCEV+SHZ7uFeHJd27Dk9e2AAAAQDnU2wjUX0n6j5J+KunfJN1ljMk85jHLsh4rc78AAAAAVIF6C1DXJb9eI+muPMc9VvquAAAAAKg2dRWgLMt6W9B9AAAAAFC96moNFAAAAAB4QYACAAAAAIcIUAAAAADgEAGq1iRmpMNDUsJhdfZEInl8cPsI/9PDX9af3vnf9IH3vENXXHGFjDHatGlTYP0BAAAAcqmrIhI1LzEjPfQh6cgD0qlD0vqdUihPRk4kpH3bpPFh6eSYdNvnpVBD+fqb9L/v+XMdP/p9hZtfo0XXLtRTTz1V9j4AAAAAThCgasn4/XZ4kuxQJOUOUenhSbLbLe6SVvSVp69p/uATf6KW1/07LVr8S3rh6SfV09NT9j4AAAAAThCgaknnRnvkKRWKcoWozPAkSZ2b7PYBWPWWrkDOCwAAABSLNVC1JBSyw1Jn2vqh8WE7LKXWROUKT4Wm+wEAAABgBKrmpEKUdOlI1Lod0v7thCcAAADAJQJULcoVotKDk0R4AgAAAIrElXOtyjadL12JwtPlc5sCaQsAAACUAyNQtSwUsqftZY48SfbtJRh5uu6aZk/tf+xTPwAAAIBSYASqliUS9pqnbPZvd77ZLgAAAABJBKjala3aXrrM6nwAAAAACiJA1aJcpcrvjOYvcQ4AAAAgL9ZA1ZpC+zzlKnEeYDW+hx56SA899JAk6cyZM5Kkb33rW/rABz4gSbrmmmv053/+54H0DQAAAEhHgKolTjbJrcAQNT4+ri9+8YuzbvvRj36kH/3oR5Kk17/+9QQoAAAAVASm8NWS8T3ONsnNVuJ8fNhuH4BPfvKTsiwr55+TJ08G0i8AAAAgEwGqlnRukJbfnvx7gX2eMkPU8tvt9gAAAAByYgpfLQk1SLd9XlrcJXVuLDwdLxWiFq22w1OooTz9BAAAAKoUAarWhBqkFX1FHB8q7ngAAACgjjGFDwAAAAAcIkABAAAAgEMEKAAAAABwiAAFAAAAAA4RoAAAAADAIQIUAAAAADhEgAIAAAAAh9gHCgAAADUpnojr4ORBTUQnFJuOKdwUVnukXd0Lu9UY4jIY7vCTAwAAgJoSm45p6OiQRk6M6Gzs7CX3t4Rb1NvWq75lfQo3hQPoIaoZAQoAAAA1I3ohqq0HtmoiOpHzmLOxsxoYH9Do6VENrhlUZF6kjD1EtWMNFAAAAGpCbDpWMDylm4hOaOuBrYpNx0rcM9QSRqBqXKXP/Y1Go/rSl76khx9+WN/73vf0b//2b7rsssv0pje9SZs3b9bmzZsVCpHzAQBAYUNHhxyHp5SJ6ISGjw1ry/ItJeoVak3wV9AoiWqZ+zsyMqIPfehDet3rXqeenh4tWrRIZ8+e1d///d/rgx/8oL7yla9oZGRExpjA+ggAAIJX6EPheCKukRMjrh575MSI+jv6K+LDZVQ+fkpqUDXN/W1ra9O+ffv0zne+c9ZI05/8yZ9o1apVevDBB/X3f//3eu973xtI/wAAQLCcfii86IpFWe934szUGY1NjqlnUY/X7qIOMDeqxlTb3N9f+7Vf07p16y6Zptfa2qrf/d3flSQ99thjAfQMAAAELXohqv5H+jUwPpAzHKU+FP6zf/0zT+cqduof6hcBqsZ4mftbaZqamiRJjY0MlAIAUG+K/VD4+QvPezrf1PSUp/aoHwSoGuJ17m88Efe5R+7F43H97d/+rSTp1ltvDbg3AACg3Nx8KOxFc1Nz2c6F6sZH+zXk4OTBmpn7+/GPf1zf//739bZb1up17b+sI5M/K9gm/sqMfvDcL/SOLz4sSepZskC7N68qcU8BAIDfvHwo7FZ7pL2s50P1YgSqhnj9lKZS5v7ec889+ou/+AvdcMMN+qP/9XnXjzN63NtQPgAACIaXD4XdaG1uVdfCrrKdD9WNEaga4rUQRCXM/R0YGND27du1bNkyHThwQM/F5wbdJQAAUGbl/lC3t62XEuZwjBGoGuJ1P6eg5/5+9rOf1bZt29TR0aHR0VG1trYG2h8AABCMclYH7oh0aNPSTWU7H6ofAaqGeJ27G+Tc38985jP66Ec/qs7OTo2Ojuq1r31tYH0BAADB8vqh8IJ5Cxwd1xHp0OAtg57Ph/rCWGUN6V7YrZZwi6s5w0HO/f30pz+tu+66SytXrtTXvvY1zZ8/P5B+AACAyuD1Q93/9ub/plPnT2nv8b1Zr4tam1vV29arTUs3EZ5QNAJUDWkMNaq3rVcD4wNFtw1q7u8Xv/hF3XXXXWpoaFBXV5fuueeeWfef/flL+ncLF+nd79tQ9r4BAIBgeP1Q+JbX36LGUKP6O/o1NjmmieiEpqan1NzUrPZIu7oWdrHmCa7xk1Nj+pb1afT0aFGLL4Oc+/vMM89IkmZmZvTZz3426zE3r34rAQoAgDri14fCjaFG9SzqqZhtWlAbWANVY8JNYQ2uGXQ89B303N9PfvKTsiwr558nT7+ge0f+IZC+AQCA4PQt6yt6Kh8FIVAOBKgaFJkX0a61u7Ttpm1qCbdkPaa1uVXbbtqme9feq/lzWXMEAAAqS7V9KIz6wRS+GhVuCmvL8i3M/QUAAFUr9aHw8LFhCkKgYnAFXeOY+wsAAKoZHwqj0vDTBgAAgIrHh8KoFKyBAgAAAACHCFAAAAAA4BABChXt8rlNjo6zLOuS23qWLPC7OwAAAKhzrIEKiDFGlmUpkUgoFCLH5nLdNc2OjkskEjr+izO68dqrdPLu1SXuFQAAAOoVV+4BmTNnjiRpamoq4J7UhtTzmHpeAQAAgFIgQAXk8ssvlySdOXNG58+fVyKRyDoNDbmlRvDOnz+vM2fOSLr4vAIAAAClwBS+gMyfP19TU1OKxWKanJwMujs1IRwOa/78+UF3AwAAADWMABWQUCika6+9VufOndP58+f18ssvMwLlgjFGc+bM0eWXX6758+ezngwAAAAlRYAKUCgU0jXXXKNrrrkm6K4AAAAAcICP6wEAAADAIQIUAAAAADhEgAIAAAAAhwhQAAAAAOAQAQoAAAAAHCJAAQAAAIBDBCgAAAAAcMiweau/jDHRefPmzV+6dGnQXQEAAACQxbFjx3ThwoVzlmVFim1LgPKZMeYZSVdIOpnnsBuSX58qeYdQCrx+1Y3Xr7rx+lUvXrvqxutX3Xj9LrVY0s8ty7qu2IYEqAAYY56QJMuyVgbdFxSP16+68fpVN16/6sVrV914/aobr5+/WAMFAAAAAA4RoAAAAADAIQIUAAAAADhEgAIAAAAAhwhQAAAAAOAQVfgAAAAAwCFGoAAAAADAIQIUAAAAADhEgAIAAAAAhwhQAAAAAOAQAQoAAAAAHCJAAQAAAIBDBCgAAAAAcIgAFTBjzLXGmM8ZY75tjDljjHnZGPMTY8yYMWazMaYp6D4iN2PMG40xHzPGPGqMOW2MecUYc9YY82VjTE/Q/UN+xpgmY8x2Y8xuY8x48vWzjDEfDLpvuMgYs9AYsyv53viyMeakMeazxpirg+4b8jPG/IYxZmfyd9rPk/+/hoPuF5wxxkSMMR80xnzJGPNDY8wFY8yLxphvGGN+2xjDdWSFM8Z8xhhzIHmNcsEYc84Y811jzCeMMZGg+1et2Eg3YMaYt0n6sqRvS/qRpHOSIpLeIelaSaOS3m5ZVjygLiIPY8z/kXS7pKOSviH79Vsiab2kBknbLcu6J7geIh9jzFWSXkj+86ykV2T/v/svlmX9TVD9wkXGmOsl/Yuk18p+r3xK0ipJPZKOS3qrZVnR4HqIfIwx45JulPQLSZOSbpC0x7KsTUH2C84YY35X0uclPSv7euSUpBZJ75F0paQHJfVaXExWLGPMK5IOy75OeU5Ss6TVkm6W9BNJqy3LOh1cD6sTASpgxpjLJMUty0pk3N4k6WuS3ibpdsuy9gbQPRRgjPmApCcty/puxu2/KumfJFmSFluW9WwA3UMByf9/aySNW5b1rDHmk5I+IQJUxTDGPCLp7ZI+YlnWzrTb/5ekj0r6gmVZvxtU/5BfciR+UtIPJf2q7ItwAlSVMMb8muwL7ofTr1OMMa2SHpf9gdNvWJb1YEBdRAHGmLmWZb2U5fY/lvQ/JH3esqwPl79n1Y2h14BZlvVKZnhK3j4t6aHkP99Y1k7BMcuy7ssMT8nb/1nSY5Iuk/SWcvcLziT//32FgFuZkqNPb5d0UtJgxt2fkDQlqc8Y01zmrsEhy7JGLcv6ASMU1cmyrEcty9qfeZ1iWdYZSX+V/Ofbyt4xOJYtPCWlPpjnGtMFAlSFMsY0SPqPyX8eCbIvcG06+ZXpl4A7qXWEX8tyAXde0jclhWVPRwFQXvyOq27rkl+5xnShMegOwGaMuUbSHZKMpAWSfl3SGyTdb1nW/iD7huIZY14ve2pYTNLBgLsDVKslya8nctz/A9kjVG2SDpSlRwBkjGmU9JvJf341yL7AGWPMH0h6jey1azdL+hXZ4enuIPtVrQhQleMa2VNSUixJfy57fiqqiDFmjqQ9kuZI+m+WZb1QoAmA7K5Mfn0xx/2p268qfVcApLlbUoekf7Qs65GgOwNH/kB2AZCUr0r6gGVZzwfUn6rGFD4fJEvqWkX8uaSEq2VZT1mWZWSH2tfLXhy9RdJBY8z8Mn9LdcWP1y/tsRokDUl6q6QHZIdglJCfrx8AID9jzEck/b7siph9AXcHDlmW1Zq8zmyVXUXxlyR91xizItieVSdGoPzxtKRci/Sy+UmuOyzLmpFdJnSHMeaspL+T9Eeyp/ehNHx5/ZLhaVhSr+zFmZtYOF0Wvv3/Q8VJjTBdmeP+1O0/K31XABhj7pC0Q3ZJ7DWWZZ0LuEsokmVZZyV9yRhzWPb06L+VPZqIIhCgfGBZ1poSPfRXkl/fVqLHh/x5/ZJl5/fIDk/3S/rNZBhGiZXw/x+Cdzz5tS3H/anqUbnWSAHwiTHm9yT9paTvyw5PzwXbI3hhWdaPjTFHJXUaY66xLOunQfepmjCFr7L9++RXKtxUsOReQiOyw9PfSuojPAG+GE1+fbsxZtbvK2PM5bKnysYkHSp3x4B6Yoz5mOzwNC6ph/BUM/5d8ivXLEUiQAXMGLMiOfUr8/bXyB4ml6SHy9srOJUsGPElSe+WdK+kzdn29QJQPMuynpa9ofhiSVsz7v6U7A0+hyzLmipz14C6YYy5U3bRiCdkjzwxUlEljDFtxphLpkAbY0LJjXRfK+lfKHZVPMMSjWAZYx6S/Snqv8he+xSTvbP3O2RXlvoXSWsty/pFQF1EHsaY3ZI+IOmnkj4nu3pipscsy3qsjN1CEYwxH5d0Q/KfnZJulP3/7gfJ275hWdbfBNA16NXNdP9F9i/6L0s6JumXZe8RdULSWyzLigbXQ+RjjLlN0m3Jf7ZKWivpR5LGkrf91LKsPyh/z+CEMea3JN0ne4Rip7JXxDxpWdZ9ZewWHEpOu/xTSd+Q9IykqOxKfL8qu4jEGdmh+GhQfaxWrIEK3v+W9AtJq2SvdQpLekH2Jz17Je2yLIspfJXruuTXayTdlee4x0rfFbh0q+xfJunekvyTQoAKiGVZTxtjbpZdTOdW2RuMPyt7hP5TfHJa8Tol/VbGbb+U/CNJP5ZdXhmVKfU7rkHS7+U45p9lhyxUnq/L3lP0VyTdJPuD+SnZHz4NSbqHQiDuMAIFAAAAAA6xBgoAAAAAHCJAAQAAAIBDBCgAAAAAcIgABQAAAAAOEaAAAAAAwCECFAAAAAA4RIACAAAAAIcIUAAAAADgEAEKAAAAABwiQAEAAACAQwQoAAAAAHCIAAUAAAAADhGgAAA1xxhjZfyZMcb81BjzqDFmQ552Nxhjdhpjvm+MedEY84ox5ifGmIeNMb9tjJnj8PxLjTGfMsZ82RhzKq0fjf59lwCAIBjLsoLuAwAAvjLGpH65fSr5tUnSDZLeLalB0l9alvVfM9rcJekTsj9c/Jak70j6haQWSW+T9EuSnrAs62YH5/89SX8paUbSDyQtljRXUpNlWXH33xkAIGgEKABAzUkFKMuyTMbtayT9U/Kfv2RZ1snk7f9D0h9LOi2p17Ksb2d5zHdJ+n3LsnocnH+JpKskHbEs64Ix5qSk14sABQBVjwAFAKg5uQJU8r6jkpZKep9lWSPGmMWSTiTvXmFZ1vfzPO4cy7JedtGfkyJAAUBNYA0UAKDepEJV6hPEzbKn+D2YLzxJkpvwBACoLQQoAEDdMMbcImmJ7PD0r8mbfyX59UAgnQIAVBWqAQEAapYx5pPJvzbJDk63yR6B+kvLsn6cvO91ya+TZe0cAKAqEaAAALXsE8mvlqSfSRqTdK9lWcOB9QgAUNUIUACAmpWtiEQWz8ouKvHvS9wdAEANYA0UAKDefSP5dU2gvQAAVAUCFACg3u2WNC3pvcaYZfkONMbMKU+XAACVigAFAKhryc10PynpMkkPG2NuznacMeZWSV8pX88AAJWINVAAgLpnWdafGGMaZRed+FdjzL9I+o6kX0hqkdQt6Y3J2woyxlwj6c/Tbrom+fXe1Ca/ku62LOspP/oPACgfY1lW4aMAAKgiqZDisIhEerulkj4sqUfSIklzJUUljUv6v5KGnWyma4xZLOmZAof1WJb1WDH9AwAEjwAFAAAAAA6xBgoAAAAAHCJAAQAAAIBDBCgAAAAAcIgABQAAAAAOEaAAAAAAwCECFAAAAAA4RIACAAAAAIcIUAAAAADgEAEKAAAAABwiQAEAAACAQwQoAAAAAHCIAAUAAAAADhGgAAAAAMAhAhQAAAAAOESAAgAAAACHCFAAAAAA4BABCgAAAAAc+v8B7qFS4NkKdqsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 279,
       "width": 424
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PCA Explained variance ratio:  [0.72962445 0.22850762]\n"
     ]
    }
   ],
   "source": [
    "iris = load_iris()\n",
    "X = iris['data']\n",
    "y = iris['target']\n",
    "\n",
    "label_dict = {\n",
    "    0: 'Iris-Setosa',\n",
    "    1: 'Iris-Versicolor',\n",
    "    2: 'Iris-Virgnica'}\n",
    "\n",
    "feature_dict = {\n",
    "    0: 'sepal length [cm]',\n",
    "    1: 'sepal width [cm]',\n",
    "    2: 'petal length [cm]',\n",
    "    3: 'petal width [cm]'}\n",
    "\n",
    "fig = plt.figure(figsize = (10, 6))\n",
    "for feature in range(len(feature_dict)):\n",
    "    plt.subplot(2, 2, feature + 1)\n",
    "    for index, label in label_dict.items():\n",
    "        plt.hist(X[y == index, feature], label = label,\n",
    "                 bins = 10, alpha = 0.3)\n",
    "        plt.xlabel(feature_dict[feature])\n",
    "        \n",
    "plt.legend(loc = 'upper right', fancybox = True, fontsize = 12)\n",
    "# plt.tight_layout()\n",
    "fig.suptitle(' Distribution of Iris data with 4 features ', fontsize=30)\n",
    "\n",
    "plt.show()\n",
    "\n",
    "def plot_iris_pca(X_pca, y):\n",
    "    \"\"\"a scatter plot of the 2-dimensional iris data\"\"\"\n",
    "    markers = 's', 'x', 'o'\n",
    "    colors = list(plt.rcParams['axes.prop_cycle'])\n",
    "    target = np.unique(y)\n",
    "    for idx, (t, m) in enumerate(zip(target, markers)):\n",
    "        subset = X_pca[y == t]\n",
    "        plt.scatter(subset[:, 0], subset[:, 1], s = 50,\n",
    "                    c = colors[idx]['color'], label = t, marker = m)\n",
    "\n",
    "    plt.xlabel('PC 1')\n",
    "    plt.ylabel('PC 2')\n",
    "    plt.legend(loc = 'lower left')\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "\n",
    "pca = PCA(n_components= 2)\n",
    "X_std = standardize(X)\n",
    "model = pca.fit(X)\n",
    "\n",
    "z = X_std @ model.k_eig_vecs\n",
    "plot_iris_pca(z, y)\n",
    "print(\"PCA Explained variance ratio: \", model.explained_variance_ratio)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8782928a-2938-4763-9cd4-b3fdfc083f8b",
   "metadata": {},
   "source": [
    "## Image compression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ea0b0510-cc47-491c-bf8b-fd5c6abf4a8c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-10-28 00:53:34,019 Downloading LFW metadata: https://ndownloader.figshare.com/files/5976012\n",
      "2021-10-28 00:53:38,995 Downloading LFW metadata: https://ndownloader.figshare.com/files/5976009\n",
      "2021-10-28 00:53:45,746 Downloading LFW metadata: https://ndownloader.figshare.com/files/5976006\n",
      "2021-10-28 00:53:55,726 Downloading LFW data (~200MB): https://ndownloader.figshare.com/files/5976015\n"
     ]
    }
   ],
   "source": [
    "from time import time\n",
    "import logging\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.datasets import fetch_lfw_people\n",
    "from sklearn.metrics import classification_report\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.svm import SVC\n",
    "\n",
    "\n",
    "# Display progress logs on stdout\n",
    "logging.basicConfig(level=logging.INFO, format=\"%(asctime)s %(message)s\")\n",
    "\n",
    "\n",
    "# #############################################################################\n",
    "# Download the data, if not already on disk and load it as numpy arrays\n",
    "\n",
    "lfw_people = fetch_lfw_people(min_faces_per_person=70, resize=0.4)\n",
    "\n",
    "# introspect the images arrays to find the shapes (for plotting)\n",
    "n_samples, h, w = lfw_people.images.shape\n",
    "\n",
    "# for machine learning we use the 2 data directly (as relative pixel\n",
    "# positions info is ignored by this model)\n",
    "X = lfw_people.data\n",
    "n_features = X.shape[1]\n",
    "\n",
    "# the label to predict is the id of the person\n",
    "y = lfw_people.target\n",
    "target_names = lfw_people.target_names\n",
    "n_classes = target_names.shape[0]\n",
    "\n",
    "print(\"Total dataset size:\")\n",
    "print(\"n_samples: %d\" % n_samples)\n",
    "print(\"n_features: %d\" % n_features)\n",
    "print(\"n_classes: %d\" % n_classes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "45b72787-ae0b-463f-ac68-1b94a8e8447a",
   "metadata": {},
   "outputs": [],
   "source": [
    "X, y"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc416570-24af-48e8-b3e3-1811f9afeddd",
   "metadata": {},
   "source": [
    "## Refs\n",
    "\n",
    "\n",
    "http://cs229.stanford.edu/syllabus-summer2019.html\n",
    "\n",
    "https://github.com/ethen8181/machine-learning/blob/master/dim_reduct/PCA.ipynb\n",
    "\n",
    "https://scikit-learn.org/stable/auto_examples/applications/plot_face_recognition.html#sphx-glr-auto-examples-applications-plot-face-recognition-py"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
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