diff --git a/bayesian/bayesian_optimization.ipynb b/bayesian/bayesian_optimization.ipynb new file mode 100644 index 0000000..c7829db --- /dev/null +++ b/bayesian/bayesian_optimization.ipynb @@ -0,0 +1,1017 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 336, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.datasets import fetch_openml\n", + "import pandas as pd\n", + "from sklearn import preprocessing\n", + "from sklearn import metrics\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.model_selection import train_test_split\n", + "import numpy as np\n", + "import GPy\n", + "from scipy import stats\n", + "from scipy import optimize\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.neural_network import MLPClassifier\n", + "from sklearn import metrics\n", + "from tqdm import tqdm\n", + "from functools import partial\n", + "\n", + "# http://krasserm.github.io/2018/03/21/bayesian-optimization/" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Expected Improvement\n", + "\n", + "[derivation](http://ash-aldujaili.github.io/blog/2018/02/01/ei/)\n", + "\n", + "$$\\text{EI}(x) = \\mathbb{E}\\max(f(x^*) - f(x^+), 0)$$\n", + "\n", + "$$\\text{EI}(x) = (\\mu(x^*) - f(x^+)) \\Phi(\\frac{\\mu(x^*) - f(x^+)}{\\sigma(x^*)}) + \\sigma(x^*) \\phi(\\frac{\\mu(x^*) - f(x^+)}{\\sigma(x^*)})$$\n", + "\n", + "* $\\Phi$ = CDF standard normal\n", + "* $\\phi$ = PDF standard normal\n", + "* $x^*$ = proposed points\n", + "* $x^+$ = current best\n", + "\n", + "Numerrically unstable if $\\sigma \\to 0$\n", + "\n", + "$$\\text{EI}(x) = (\\mu(x^*) - f(x^+)) \\Phi(Z) + \\sigma \\phi(Z)$$\n", + "\n", + "$$Z = \\begin{cases}\n", + " \\frac{\\mu(x^*) - f(x^+)}{\\sigma(x^*)},& \\text{if } \\sigma(x^*) > 0 \\\\\n", + " 0, & \\text{otherwise}\n", + "\\end{cases}$$\n", + "\n", + "Let $\\mu(x^*) - f(x^+) := \\delta$.\n", + "\n", + "$$Z = \\begin{cases}\n", + " \\frac{\\delta}{\\sigma(x^*)},& \\text{if } \\sigma(x^*) > 0 \\\\\n", + " 0, & \\text{otherwise}\n", + "\\end{cases}$$\n", + "\n", + "$$\\text{EI}(x) = (\\delta) \\Phi(Z) + \\sigma \\phi(Z)$$\n", + "\n", + "Recommendation value for $\\xi = 0.01$. \n" + ] + }, + { + "cell_type": "code", + "execution_count": 391, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Randomly selected hyper parameters: {'x': 9.545454545454545}\n" + ] + } + ], + "source": [ + "\n", + "def select_hyperparams_random(param_ranges):\n", + " selection = {}\n", + " for k in param_ranges:\n", + " val = np.random.choice(\n", + " np.linspace(*param_ranges[k]['range'], num=100)\n", + " )\n", + " \n", + " dtype = param_ranges[k]['type']\n", + " if dtype is 'int':\n", + " val = int(val)\n", + " selection[k] = val\n", + " return selection\n", + "\n", + "\n", + "def expected_improvement(f, y_current, x_proposed):\n", + " \"\"\"\n", + " Return E(max(f_proposed - f_current), 0)\n", + " \n", + " Parameters\n", + " ----------\n", + "\n", + " f : GP predict function\n", + " y_current : float\n", + " Current best score\n", + " x_proposed : np.array\n", + " Proposal parameters. Shape: (1, 1)\n", + " xi : float\n", + " Exploration parameter\n", + " \n", + " Returns\n", + " -------\n", + " expected_improvement : float\n", + " E(max(f_proposed - f_current), 0)\n", + " \n", + " \"\"\"\n", + " mu, var = f(x_proposed)\n", + " std = var**0.5\n", + " delta = mu - y_current\n", + " \n", + " # x / inf = 0\n", + " std[std == 0] = np.inf\n", + " z = delta / std\n", + " unit_norm = stats.norm()\n", + " return delta * unit_norm.cdf(z) + std * unit_norm.pdf(z)\n", + "\n", + "\n", + "\n", + "hp = select_hyperparams_random(param_ranges)\n", + "print('Randomly selected hyper parameters:', hp)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 401, + "metadata": {}, + "outputs": [], + "source": [ + "class BayesOpt:\n", + " def __init__(self, \n", + " param_ranges, \n", + " f, \n", + " random_trials=5, \n", + " optimization_trials=30,\n", + " ):\n", + " \"\"\"\n", + " Parameters\n", + " ----------\n", + " \n", + " param_ranges : dict\n", + " f : function\n", + " \"\"\"\n", + " self.param_ranges = param_ranges\n", + " self.f = f\n", + " self.random_trials = random_trials\n", + " self.optimization_trials = optimization_trials\n", + " self.n_trials = random_trials + optimization_trials\n", + " self.x = np.zeros((self.n_trials, len(param_ranges)))\n", + " self.y = np.zeros((self.n_trials, 1))\n", + " self.kernel = GPy.kern.RBF(input_dim=self.x.shape[1], \n", + " variance=1,\n", + " lengthscale=1) \n", + " self.gp = None\n", + " self.bounds = np.array([pr['range'] for pr in param_ranges.values()])\n", + " \n", + " @property\n", + " def best_params(self):\n", + " return self._prepare_kwargs(self.x[self.y.argmax()])\n", + " \n", + " def fit(self):\n", + " self._random_search()\n", + " self._bayesian_search()\n", + " \n", + " def _random_search(self):\n", + " print(f'Starting {self.random_trials} random trials...')\n", + " for i in tqdm(range(self.random_trials)):\n", + " hp = select_hyperparams_random(self.param_ranges)\n", + " self.x[i] = np.array(list(hp.values()))\n", + " self.y[i] = evaluate_params(hp)\n", + " \n", + " def _bayesian_search(self):\n", + " print(f'Starting {self.optimization_trials} optimization trials...')\n", + " for i in tqdm(range(self.random_trials, \n", + " self.random_trials + self.optimization_trials)):\n", + " self.x[i], self.y[i] = self._single_iter()\n", + " \n", + " def _single_iter(self):\n", + " self._fit_gp()\n", + " x = self._new_proposal()\n", + " y = evaluate_params(self._prepare_kwargs(x))\n", + " return x, y\n", + " \n", + " \n", + " def _fit_gp(self, noise_var=0):\n", + " mask = self.x.sum(axis=1) != 0\n", + " self.gp = GPy.models.GPRegression(bo.x[mask], \n", + " bo.y[mask], \n", + " normalizer=True, \n", + " kernel=self.kernel,\n", + " noise_var=noise_var)\n", + " self.gp.optimize()\n", + " \n", + " def _new_proposal(self, n=25):\n", + " def f(x):\n", + " return -expected_improvement(\n", + " f=self.gp.predict,\n", + " y_current=self.y.max(),\n", + " x_proposed=x[None, :]\n", + " )\n", + " x0 = np.random.uniform(\n", + " low=self.bounds[:, 0],\n", + " high=self.bounds[:, 1],\n", + " size=(n, self.x.shape[1])\n", + " )\n", + " proposal = None\n", + " best_ei = np.inf\n", + " for x0_ in x0:\n", + " res = optimize.minimize(f, \n", + " x0_, \n", + " bounds=self.bounds)\n", + " if res.success and res.fun < best_ei:\n", + " best_ei = res.fun\n", + " proposal = res.x\n", + " if np.isnan(res.fun):\n", + " raise ValueError('NaN within bounds')\n", + " return proposal\n", + " \n", + " def _prepare_kwargs(self, x):\n", + " # create hyper parameter dict\n", + " hp = dict(zip(self.param_ranges.keys(), x))\n", + " # cast values\n", + " for k in self.param_ranges:\n", + " if self.param_ranges[k]['type'] == 'int':\n", + " hp[k] = int(hp[k])\n", + " elif self.param_ranges[k]['type'] == 'float':\n", + " hp[k] = float(hp[k])\n", + " else:\n", + " raise ValueError('Parameter type not known')\n", + " return hp\n", + "\n", + " \n", + "bo = BayesOpt(param_ranges, evaluate_params)\n", + "# bo.fit()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 1D" + ] + }, + { + "cell_type": "code", + "execution_count": 402, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "x = np.linspace(0, 10)\n", + "\n", + "def func(x):\n", + " return np.sin(2 * x) + (x / 3)**2 - x + 50\n", + "\n", + "plt.figure(figsize=(16, 4))\n", + "plt.plot(x, func(x))\n", + "\n", + "np.random.seed(1)\n", + "bo = BayesOpt(param_ranges, evaluate_params)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 403, + "metadata": {}, + "outputs": [], + "source": [ + "def evaluate_params(hyperparams):\n", + " return func(**hyperparams)\n", + "\n", + "param_ranges = {\n", + " 'x': {\n", + " 'range': [1, 10],\n", + " 'type': 'float'\n", + " }\n", + "}\n" + ] + }, + { + "cell_type": "code", + "execution_count": 438, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 2/2 [00:00<00:00, 5210.32it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Starting 2 random trials...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 438, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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RERERES2j2Q5ZJiIiIiIiIiKiFYoBDxERERERERFRi2PAQ0RERERERETU4hjwEBERERERERG1OAY8REREREREREQtjgEPEREREREREVGLY8BDRERERERERNTiGPAQEREREREREbU4BjxERERERERERC2OAQ8RERERERERUYtjwENERERERERE1OIY8BARERERERERtTgGPERERERERERELY4BDxERERERERFRi2PAQ0RERERERETU4hjwEBERERERERG1OAY8REREREREREQtjgEPEREREREREVGLY8BDRERERERERNTiGPAQEREREREREbU4BjxERERERERERC2OAQ8RERERERERUYtjwENERERERERE1OIY8BARERERERERtTgGPERERERERERELc5ayid7e6KCLz56Gm0pG20pC22eHW170X5XxoFrmUt5SkRERERERERELW9JA57Roo//+3D/JW83BLC+M41NPRls6clgc8PXNR0pmIZYwrMlIiIiIiIiImoNSxrw3HhNG57+k/cgXwkwWQkxWQ4wWQkwWQ4xUQ5wfqKMM8NFDIwU8dzAKIq+TO7rmAY2dqejwKc3g83dmWS7N+tCCIY/RERERERERLQ2LWnAAwCOZaA766I76172OK01hvJVnBku4rXhIgaGizgTfz3+yiACqZNjs66VVPo0Vv9s6smgPWVf6W+JiIiIiIiIiGhZLXnAM1tCCPS1eehr83Dblu6m26TSeHOsjNdGinhtqIDX4uDn+Nkx/I8X34KuZz/oyTrY1FDtE4U/WWzsTsOzOe+HiIiIiIiIiFqf0I1pyBW2f/9+fezYsSv6HJVA4o3RUlL589pQMQqChosYyleT44QArmlPNc35qX2t70zBMrnAGBEREREREREtLyHEc1rr/TMdt2IreObLs01sXZfD1nW5i27LVwIMDJfiyp8iXhuOqn/+24k3ka+EyXGWIbChO40tPZmo+qc3Cn629GSxro3zfoiIiIiIiIhoZVl1Ac/l5DwbN69vx83r25uu11pjtOgnrV61yp+BkSKOnh5GNVTJsSnbvHiVr3joc2fGWepviYiIiIiIiIhobQU8lyKESAY/79/U1XSbUhpvT1YaKn5KeG24gB+9NYF/+dF5SFVvcetI20nosyUe8lzbTzv8oyYiIiIiIiKiK2NJZ/DctGuP/ub/eBSGIWCaBkwB2LYJ1zbhORZsy4RtGS3TAuWHCm+MlTAQV/2cqc38GS7i/GSl6dir2ryLVvna3JvBdZ1pOBbn/RARERERERHRxRZ1Bo8QYgBAHoAEEGqt9wshugA8AmATgAEA/5vWemymx0pnUk37vlIoFUPIfBVaaSilYQhEIZAhYBlixYZAjmXg+t4sru/NXnRbyQ+jeT/DUeXPmXip93956W2MlYLkONMQWN+Zaqr82dyTxebeDK5u82AYy/99EhEREREREdHKNpe+oXu01sMN+78F4FGt9Z8JIX4r3v/Pcz0B0zBgOsZlT6UxBFJKA0pDiCgcMU0DpiHgWgY8x4LrWLBtc9lXwUo7Ft5xTRvecU3bRbeNFX28NlK8qPLn38+MohzI5DjXMpqWeG9c6as746yIkIuIiIiIiIiIlt9CBsP8LIC74+2/BfAE5hHwzMZsQqCyVMjnfUhZgdIaQus4AIorgUyBlGuviCqgzoyDzoyDvRs6m67XWmMwX8WZuM2rtspX/2Aej566gEDW2+lyntU052fHVW3Yu7EDfTlvqb8dIiIiIiIiIlpms5rBI4R4DcAYAA3gL7XWXxZCjGutOxqOGdNad05z348A+AgAXHPt+n3PnHhl0U5+LpTSCEIJqWRSBVRrA6sFQJ5jIe3Zyx4ATSeUCm+Ol5vm/AyMFHFmqIi3Jsqo/TVe15XC3g2dydeOq3Owl7maiYiIiIiIiIjmZ7YzeGYb8FyjtX5LCNEH4DCA3wDwT7MJeBrdtGuP/p+PPT3z2S8DreMASCpIpZoCIMtsrgBybBO2ZS73KScqgcSP3prA8dfHcfzsGI6fHcOFySoAwLMN7FrfEQc+Hdi7sRM9WXeZz5iIiIiIiIiIZmNRhyxrrd+KLweFEN8GcAuAC0KIq7XWbwshrgYwuKAzXmZCCDi2BdjT3y6VxlhtDpBUgEbSAlYbBJ12LHiuBce2lnQ4smeb2LexC/s2Rku8a63x1kQFx1+Pwp7jr4/hr4+eQRgv6b6hK429Gzqwb2Mn3rmhEzuuyi37zCIiIiIiIiIimr8ZK3iEEBkAhtY6H28fBvBHAO4FMNIwZLlLa/1/Xu6xVnIFz0JJpRAEElIpKKlgNAyBtkyBVNz+tVzVP5VA4odvTtRDn7PjGMpHVT5px8Su9e311q6NnejKOEt+jkRERERERETUbDEreNYB+HY8j8YC8Pda638RQjwL4B+EEP8HgLMAfmEhJ9zqTMOA6U5fBaO1xmRFYrTo16t/kuHPBjzbRMqLVgBzLPOKzP7xbBM/sakLP7GpXuVzbqyM42fH8PzZqLXry0fqVT6butPYu6ET79wYtXZtX8cqHyIiIiIiIqKValYzeBbLaq7gWYgwlPBDCa0U9JTZP1H4U5/9cyUHP5d9iRfPjeN4HPg8f3YMwwUfAJBxTOy+Lp7ls7ED77yuE52s8iEiIiIiIiK6ohZ1Bg9dWZZlwrpE21ZZKkxOVKFkGUqp5lW/auGPuziVPynHxK1bunHrlm4AUZXPG6PlZHDz8bNj+IsnfwwZV/ls6cngnXHgs3dDJ7aty8FcwtlDRERERERERBRhBU8LC6VCEEooKZPKHyse+hwt+W7BdaK5P4ul5Id48dxEPLw5qvQZLUZVPlnXwu7r2pM5Pnuv60R7+hJTq4mIiIiIiIhoRqzgWQMs04jn4lwcopQCiYlKBVKWoJWOl3o3YBkCKddCJmXDsa05z9VJOxZu29KN2xqqfF4fKdWrfF4fx//7+KuIi3xwfW+mHvhs6MTWvuySrjBGREREREREtBawgmeN0VojCGVU+aM0DGiYpgHbFLAtAxnXRipe7Wu+LV/FaogXzo1Hw5vjVbvGSgEAIOda2LOhI2rtii/bU6zyISIiIiIiIprObCt4GPBQIlnqXSro2ryfuPIn5ZrIeA5cZ+5VP1prDIyU8FxtifbXx9B/IZ9U+WztyybDm/du6MT1vazyIQIApTSU1lBKQ0NDx/taR/9ftQKk1tBaN+0rpaA1oi8A0Bq1n/S16xp/9tc2px5bvxL16+KDL/XKMdeXlEvlyGLKAaLpyubbRfOhSTgt4utE43HxvmkaMOJjDSP6MoWAiOecGYaAQHwpBIQADFHfJyIiIiJaKgx4aFFFVT8hpGyu+nFsExnPRsqd26yfQjXEC2/UK3yef2Mc43GVT5tnYU9c4bN3Qyf2bOhAm8cqH1qZpFRJCKNUFLRIpRFKBakUlNQIZC1wicITVdtuuE43Xtf4BHG4IGrJBOrbhqiHDyIOMEQcTNSuo4vV/pxVnIKpqX8XSgNCQ6vkHslttb+cJDxK/n5w0d+F0XC7bRowTAHTiFpro4H50XWGiLcZbBMRERHRNBjw0JIIpYIfhFBKAUonFT+OJZD2HGRm2e6ltcaZ4WIc+Izj+bNjeOVCHlpHv0QlVT7xPJ8tPRn+MkQLonUUwtRCmVAqhFIjlDK+VHHFDJoDgIZ9ANDJL/cGNOLQxRBJtYcRbzNsWbu01k0hoNJRNVbt9VdrFf970lHVkKgFdQ0VRnFYZMRhkWkacCwTlmXEFUdxaDTHCksiIiIiWvkY8NCyUiqa9ROGsqndyzYNZFI20q4N17EuG9JMVoK4yidarev5s2OYrIQAgPaUjXfGFT57N3Ri93XtyLHKZ81pDGlCGbUYBlIhkKoe0MTHSdkczmjUKjCMqG2noYrCiKsriFaaqB0vasNTqt6eV7sNWieBomEgaTMz4oovyzJgm/GXbUbVRHFFEUNIIiIiopWJAQ+tSFpr+EEU/Kg4+Kmt8JWOV/fyHHva4EcpjTPDhSTwOX52DKcHC0mVz/Z1uWR4c63Kh7+wtI5aSCOlQiAlgjAKbPw4wFEaTdUPqjGkMYx4RkoU0ES/sDKgIZpKxsFQ1FoYzW2qVRAJoB4GNVShmQbg2CYc02wKheY6j42IiIiI5ocBD7WU2upeYRgNeTYFYFnGjMHPRDmq8qkNcD7xxjjycZVPR9qOK3w64iqfDmRcazm+vTWpFtiEcVhTDUL4gYRUiNuipglravNj4goaVhYQLb9ktlRDKKSSaqEpYZAAzHg+m2tbsC0DlhmFQmyrJSIiIpqf2QY8/G2XVgQhBBzbgmNf/E9yshJitOA3BT+2aSDlWsimHNxxQw8ObOsFEP0i8upQIRnefPzsOB47NQggGni6/aq2JPDZu7ETm7rTDA/mQEqFUCmEoUI1kAgCiWoo64FNQ6WNRvSLH0Q0HyQaLGvBsAQM8IcPUauI2hZN2NbsBulLpVGoKoyXqvGKblGQK4AosI1XKquFQa5twXGiCqFasM+fy0RERERzxwoeakm1ip8gaG71si0DGc9Gxotm/AghMFEK8Pwb9eHNJ86OI1+Nqny6Mg5u3dyFA9t6cefWHqzvTC/zd7b0anNswlDBDyWqQYiqLyGTKhskw2F13AYlDMA0TFbYENGCNA45V1JBawXEbbdGLQiKv1wnqgpyrHqrGBEREdFawBYtWpOSGT9SQkvVtKpX1nOQStmwTBOnB/M4/nrU2vX0j4fx9kQFALClN4MDW3txYFsPbt3c3fItXbXBw9MFN7WKG60RDxk2YMRzNfgJOhGtJEkQ3RAEaQ2YtSDINGAKwLZNuLYJz7FgWdFKY/xZRkRERK2OAQ9RA6U0/CCElBJa6WSws+uYyHgW3pz08W9nRnGkfwj//toIKoGCbQrs39iFO7f14MDWXrzj6rZpZ0horZt+gZi6f6W+n0BKhKFCxQ+TdimpozYqpTSkrq8SxeCGiNYCGbeQShX9rFeqPifINASseEXHlGvDcyzYlgnb4s9FIiIiWtkY8CxA9ElhtAytTIZL6obKh8Z91bRkrdLR/bWO5hBE23GbS7ytG45TuvE++qLHUFonS+Em+/GxS02IeJCmEEn5fHKdEd1ePyY+3pjueCTL+EZLU4s4iGhezre2EpJlxiX6l9mf75vzUCoEYQgZSggAlmlAaY3+4SKOvzGBp8+M4tT5PACgJ1uf93PH1h705TwcOnQIW555BvefPAnxxhvQ112Hr+zciTO33YZDhw7N65xq4Y3vh6j4UeVNKKdU3cR/H9Esi2huBVeNIiKamVJRi69U0fwwKA0h0PC6IuBaBlKuDdeJZg+ZbAcjIiKiZbQihyxLpTE0XkrmfQRxuXUYRpfT7sfb0Ve80tK0+zr+ZV0m22FcyRAmy8LWA5mpQY1SKgl11NJnJ7RA9VkNtQDIgGlOv2+aAlbtMl7ZxTaN5JNc26rPlXl3p4NbO7vwdlniXMHH4R+dx3878RYA4Lp2Dx1vtuGqQQfHggxyXRth5wPc+m8nUDDTGJ0sR4Oj48cUQsSzg6J/p42VN+GUIcXRUNPaUsQWTFtgduNNiYjocgxDwHUsXO4tUFkq5CerUbuv1hAa8WtI9OXEbWCeY8KxLc4DIiIiohVhSSt4Mr1b9Dt+7o+X7PkWIhnsGH+aZxj1MMA0DFjxdY23G0k1SlyxElekNO6LhuqVxsqW2vbUqpemqhkDSQWMEAJLWVCugaQSSev67JZLVxjFg3kbKpOm3l6vWLr4+CSEawrqpt+XS5jIaQChaSKwLfi2hcCyoj4oreEEIewghBMEMJW66O/HNo1oBbB4LoRrm3CTXxDMeFnh2pcF16lf13RbbdDotNebbMMiIrrCaq1goYyqgITW8XuG5gAo5UQ/q1kBRERERAuxIit4TEOgpz2VzAKpLXc97b5lJHNSbNOEZYnkONtquM9lrrPMxgDGSHrvjSSgMZLVl2rbpmkkAQq1hqmBkIyrsS7al/WWu9p+Y2gUxFVlQSCjy7jSpnZ9tDR4CD+Q0VeoYD75GC7kujGY68JIth3FTApFpGCFITxouGEIsxpAxxVpgVQoV6/sn4chEC85b0RBkW3Cc6NfNDw3/qXDteJPn+vbKddqOM5Cymk+lr/Z5y0AAAAgAElEQVSgEBFFTMOA6RhwL/E2ylcKpUKAMKxAadVUAWSZBjzbhOdFP1s5CJqIiIgWC2fwEDVIPpUNJZSOP5U168M5bdtE2rHgOhZs24S5ZTPE2bPJ/d9o68PRze/EkRvvwFM3/ATy1RACwPZ1Wey+pg03XZXDDb0ZGIaBUGpU47CoGkQzd6rxduP10W0yDpeikKnpGD9eJcuPrguluiJ/NrZlJOHPRcHQlDAo7dlIezYyXn077da32c5ARGtZGEY/t3XcIm4KxC250YdOac9h9Q8RERElVmQFD9Fyqw3XDKWEVgrQuKisvj1rw3NSsON2p0vRWuMrO3fi/WfPIhNfd93kIH72hX9FeBXwxb/9bbz45gSO9A/jyOkhfOPEW3hEA1nXxL4NHdi7vh171rdjY0cGwjRgmVHL1UI/yZVSxcuiK/hBNKi54oeoVENU/BDlanRduRpEl7XbqmGy3XTpS1SqQVzR5GOy5C/o/ADAsU2kPQsZ105Cn5RrIePZSDeGQp6NTBwMpWqBUXwfx+ZUIiJqTZZlwrKm/xkmlcZoQ/WPgfoAaMsUSMUhuutw9g8RERE1Y8BDq079k9FoVs/UT0azGRsp14uHKs8/JBBC4Mxtt+GbQNMqWt+MV9GyLRP7NnZh38YufPont2GiFOCpHw/j6OkhHOkfxpOnRwAAm7rTeNf13dh3XQfesS4D2zAQSgUNwLQsuLY17fLsl2KaBlKmgZQLAO68v79GWmv4oWoKf+phUf2y4ocoVaL9UiVAsRKgVAlQivdrX7U2t/H8/PvVLNOIQiLPRjblIJOKLrOphv10vO8177uLEKQREV0JtSHQ0SDoZlprTFYkRos+lIw/pDBF0pbO8IeIiGhtY4sWtZzGKpxkuGX8Btc0BDzbRMqL3hwvxWwDrXXTc0zdv9R9zgwXcaR/CEf6h/DMmVGUAwnLENi7sRN3bevFu7Z0YVNXCsWyDz/UUeuY0jDMaLbOpT79Xem01kkFURQCNYQ/1eb9cjWsh0RTjgvl/H92WaZoCoUyKRu5Kfv1sKh2XbTPyiEiWomiVRqj10Ypm18bLVNEFZKuzbYvIiKiFjTbFi0GPLQiSRUNO5ZKQUkFo1aFYwjYlkDKjVp6VsvytNVQ4rmBMRw5PYwj/UN4+e1JAEBXxsEdN/Tgzq09OLCtF71ZFxU/QL7oo+yH8QBoHQ0OtxanxasV1CqKSpUAxXKAYsVHoRygUA5QLPsolAIUKj6K5QCF2n7ZR7ESHeMHct7P7domcmkHuYyDXNpBW9qN9tMO2uLrcvF1tX1WDBHRctJaww8kpIxeVw1Er6m2KWBbBjJu1Aa7Vl5DiIiIWg0DHlrxQhnNiNFKQSsdL0EftVE58TBjLw5x5tKitBoM5av4watDONo/jCOnhzFciFqZtq/L4cC2Hty5tRe3bO6CZ5vJG/dCOQo0/FAtqMVrLYj+vOIwqDwlHIpDoSQcatoP5jXE2rEMZNMO2jIu2tJOtJ2EQu6U/Sgg8hz+okVEV17ygYpU0cDn+HXYMg2kXBNp14bncjg+ERHRcmLAQytC4zwcrTVMEQ00tgwRLdPNZWJnpJTGqfN5HDkdtXMdGxiDLxVcy8Atm7tw17Ze3Lm1F9vWZZv+DINQolQJkC9V4YcaQaggtYZpGnBsvlmfj1p7Wb5URb7kY7LoI1+qf00Wq/Xt2vXFKvxw7qGQZRpoy8ShUMZBe8ZFe9ZFW8ZNttszLtozDtqzLjzH4v8hIlpUQSgRhGEy76cW/NiWQNZzWPVDRES0RBjw0JJpqsRpDHFMY8nn4awFJT/Ev58ZxZHTQzh6ehivDhYAAOvaXNy5tRcHtvXijht60JVxLrqvlArlaoBCyUfZlwikimY1GAYcx1rQ0Gm6tKofJoFPFApdIiCKr88XfVTn2EbmWEYU/mTdhjBo+mCoLePC5SwhIpqnxqofHVf9mLV2r3jWj+uwepSIiGixMOChRSWVgh9IqPjNnFEr4TYEXNtEOmUzxFkmb46XcbQ/Cnt+8OowJsoBhABuvrYdB7b24s6tPdi7sRP2JSp2tNaoVEPky1WUKyF8GQ10Fmtsrs9KUw0k8sUqJks+JgpVTBSrmChUMVls3PYxUaxivFCd81whz7HiMMhpCoY6si46cl50mfXQmXOR9mz+GyCiGdVahsNQRu1e8fw824ravTKeA8+xOOSZiIhojhjw0Jw1rU4lVdPy4o5tIuPZUTsVf+FfsaTSePHcOI70R8uxP//GOKTSyDgmbr++B3fF83s29WRmfKyqH14810cImKbJuT4rUMUPo/CnFgYV68HQZHJdPSSayypklmmgI+eiM+uhPeuisxYANVx2Zl20Zz2k3IuXdiYiqrV7SRkNeW5e2t1CynPYOkxERHQJDHhoWrVlVIMwWmLcgI4HKkY99WnPQXqNDjZejSbKAf7txyPJ/J5zY2UAwIaudLIy1+3Xd6PNs2f1eH4gUSr7yJf9KPQJFSQELMuAY1swDb45bwVaa5SqYT0AioOf8ULtsoLxfHxZqKJcDWf92J5jomNqEJT10JFrrgzqyLpccp6IEMbvSUKpYEAz+CEiIpoGA541rjYXR8UrVNUGI1qGQMq1kEnZq2aJcZodrTUGRko40j+Eo6eH8PSPR1DyJUxDYO+GjmR+z83XtsOcQ7gXSoVipTZMmMOcV6OqH2I8Dn7G8lEINJavJAHQeL5+OZeB0hnPRmfOQ2fOQ1dbdNnZ5qFrynWuw6ogorVmuuDHNqMFGjIpGynXZqsXERGtGQx41oBL9bpbpoiGG6dspBwbtmWwpYou4ocKx8+OxYHPMH745gQAoCNt49039OBAXOFzdXtqzo897TBnFQ1zdm0LFoc5r0paa5SrYUMFUBQETRSqGCtU6kFQoYqJQmXWbWJpz0ZnzkVXLtUUAHW2NQdBHoMgolUvWp2zudXLtgyk4w+vPMdmBTIREa06DHhWkTCUCGS0WgWUTlaosk2BNFeroEUyUqjiB68OJ/N7BvNVAMANfVkc2NqLA9t6cOvmbqSc+YUzSmlU/AD5oo+yH8IPuYLXWqa1RqHsY3SyirF8GWP5CkYno6+xfP1rdLKCUM6uKijtWtMGP125VNP1nBNEtPoEoYwql6WKW8/rq3plvOh9Ej/sIiKiVsWAp8VccuUJs75KlefYnFlBS0JrjVcu5JPqnn9/bRR+qOBYBm7Z1JXM79lxVW5Bb5gbV/AqVUIEoUIYV/rYlgnH5i/ia10UBAUNwU852Z4aBgWzbA9LxUFQV60lrM1DV1sK3W0pdLdH2505j+2FRC0ueW8lJbRUyQdkjiWQS7tIuXxfRURErYEBzwoVShUNOJbRkONkNo4pkGE1Dq1QZV/iPwZGk/k9/RcKAICr2jzcs6MP9+7ow7tv6Jl3dU8jrTWqfoh8yUepEnDZdpqVWhBUD37KTSHQ6GTUIjY6yyBICKA966K7LVUPgNpT6E7CIA/d7Smk3NkNKCeilUMpjWoQQkoJKA3Lij5QS3G+DxERrVCLHvAIIUwAxwC8qbV+rxBiN4D/CiALYADAh7TWk5d7jLUU8CSlwqp5OdDG2Tj81Iha1dsTZRztH8ZjpwZx9PQQir6EYxl41/XduHdHH+7Z0Yf1nelFfc7asu2FcoAgVAhCBWEIWJbF0IdmTWuNYiVoaAcrJ9sjE2WMTEb744UKZvPymHItdLV5cfVPQxgUB0BdbSm0Z1yG9kQtoHG+jwnEwY+BbNpBxrP5WkNERMvmSgQ8vwlgP4C2OOB5FsBntNZPCiF+FcBmrfXvXe4xVlvAo5SOV3iQTT3flmkg5ZrIphyuVEWrXjWUePa1MTx66gIeOzWI10dKAIDt63I4uDOq7nnnhs45rcw16+cOQhTL0TBnP1QIpYIWApZpct4CLUgoFcbzFYxMVjAahz6NAdDoZBkjE+VZrRpmGgKdOe+SAVCtKoihP9HK09hCr3X0Xs82DaQcM6r24TLuRES0BBY14BFCrAfwtwD+FMBvxgHPJIB2rbUWQlwH4F+11u+43OO0asDTuOR445BjxxJIew7SrsVfJokQvRE+M1zEYycH8eipC3h2YAxSaXSkbdy9rRcHd67DXVt70Z6+cm0tfiBRKvuYLPtJpY8GYFoWXJvtj7R46vOByhiJA6AkDGoIhfIlf1aP15Zx0N2eQk97Cj3t6aglLNmPwiDb4i+SRCtBKBWCIEyWcbfjap9MikOdiYho8S12wPOPAP4LgByiqp33CiGeBvB/aa3/e1zd84da69w09/0IgI8AwDXXrt/3zIlX5vitLJ0glAjCEFJqGNAXDTlmWxXR3EyUAxw9PYTHTg7i8VcGMVYKYBoC+zZ24t4dfbh3Zx+u781e8TfBQShRKgeYKFWT0EdpwLIZ+tCV5wcSo/kKRuMKoKQqaKIS75cxNlmBVDO/Hndk3ST0aQqDOlLJvCBWExAtj+mqfRzLgGdH1T5pz+FsHyIimpdFC3iEEO8F8DNa648LIe5GPeDZAeD/AdAN4J8AfFJr3X25x1oJFTyXXK3Kitqq0q4Nz7X5BplokUmlceKNcTx26gIePTmIU+fzAIANXWkc3NGHgzv6cOuWLrhLtFx6EEqUKgHypSqqgUIYKkgIWJYB17YZ+tCSkkpjolDFyEQJwxNlDE9ELWCNl2OTZcyUAQmBqB0sngnU0xGHQW3Rdnd7Gp0574q0TBLR9KJK8KB5to9loC3lIJWy4XLFSCIimsFiBjz/BcD9AEIAHoA2AN/SWv/vDcdsA/B3WutbLvdYSxnwKKXhB9GgPK2iT1FMU8C2DK5WRbQCvDlexuOnBvHYqUE89eowqqFC2jFx59YeHNzRh3u296GvzVvScwqlQrHiI1+swg81glBBag3LNOE4FkyDwS8tHykVxmoh0HhU+TM8UY624+qgsfzMw6GNeCZQYxVQYytYd3sKHVmPr49EV1BtxUgpJXS8kpdjCqQ8C7mUy/eoRETU5Ioskz6lgqdPaz0ohDAA/A2AJ7TW/9/l7n8lAh6pFKr+9PNxsp6DFFc9IFrxyr7Ev50ZxqMno8Dn7YkKAGDX+nbcsz1q5brpmvZlebMbSoVSxUe+5KMaKIY+tKKFUiUzgEbGyxiOK4Iaq4HGC9UZH8c0BLraUheHQHErWE97Cm1cHYxo0QWhhB+/r60t3OE5JnIc6ExEtKYtRcDzAIBfj2/6FoDf1jM82EICnjCUCEIJKSUEkMzHcWwTGc9GyuV8HKLVQGuNU+fzeOzUIB49eQHPvzEOrYHenIuD26Ml2O/c2oOMu3wl7bIW+pQDVHyJMFQIlYZpGXBstnjSyhaEEqOTlYZWsBJGJir1MGi8jMlZDIa2LSMJfno70lEFUHzZG7eDpZbx/ynRaiGVgu9HA51NaLZ4ERGtQVck4Fmo2QQ8fhAiiOfjGACsOMjxHAtpz4Ln2rCXaEYHES2/kUIVT/YP4dFTgzjyyhDy1RCOaeDWLV24d0cfDu5Yhw3d6eU+TUipUK5GS7aXfYlAKoSSoQ+1Jj+QUQtYQytYrSJoZLKC4fESCuVgxsfJpmz0dqTrIVBHCr3xUOje9lQ0D4j/N4jmrNbiFUoJqHgVL8tA2rWQSztcxYuIaJVZ0QHP1FUGDCGSMtS0ayETfxrBN31E1CiQCscGxqJBzacGcWaoCAC4oS8bhz192Lexc8WEKUpplCr+RaGPYRpwbQsWw2pqYRU/xHAc+gyNlzE8XkpmAtWuC6W67GMYhkBXm4fe9loFUFQFVKsA6u1IIePZ/EWVaJZqH5TW5k86loGUYyGbdpByuYAAEVGrWpEBz82736n/+/98HJYpOOiYiBZsYLiIx+JBzf/+2ggCqdHmWbhrex/u3dGHu7b1ojPjLPdpNlFKo+IHyBd9lP0QfqggpYYwDDiOxQpFWjWU0pgsVjE0UcbIeAlDE1EINBQPhR6aKGE8P/M8IM+x0NtRb/+qtYLVrutu8/j/hugywlCiGoRQUsEyotUiPcdENl66faV8KEJERJe2IgOe/fv362PHji3Z8xHR2pGvBHjq1WhQ8+OvDGK44MMQwN4NnTi4sw/37liHbeuyK7ISQGuNSjVEvlxFqRIiiGf6CMOAbZlwOF+BVqkglFHYM15bESyqAhoaL8XXl1Dx5YyP05FzoyqgjoYAqDYTqCON9oyzIv/vEy2X+lwfmSzd7lgG2jIu0h7HIRARrTQMeIhozVJK48U3J+Lqngt46c1JAMC1HSkc3NGHgzv7cPuWbngreDB7bb5CvuSjVAngS40wVBCGAcsy4ToMfWj101qjWAmmtIBFy8QPxUOhRycrUOry72VqA6F7poZAHfXrPP6fojVOKY1qECIMw2QOpmMZyKadZHwCEREtDwY8RESx8xMVPP5K1Mr1g9PDKAcSnm3gjht6cHDHOhzc0Yer2r3lPs0Z1eaXFco+CuUAQRgt2y4MAcuy4NgmqxRozZFSYSxfSVrAanOAhhoCobkMhO5pCH2SqqCOdDQQmi3ltMbU52aG0A3DnLMpG9mUw9cdIqIlwoCHiGgalUDimTMjePzUIB49NYhzY2UAwDuubsO9O6NBzbvXd7TUbLBqEKJYjlbw8kOFUCpoIWCZJldSIQJQroYYqQ2DnijFg6DjECjentNA6I5Uw+pgUSDU25FCmgOhaY2o+mGyWIpliGgFL89CLuXCc/m6Q0S02BjwEBHNQGuN04OFaG7PqUEce30USgPdGQd3b+/DvTv7cOfWHuQ8e7lPdc78QKJU9jFZ9pNKH6UByzbh2lxJhahR40DophawhtlA44WZB0KnXCtp/6oPhK5XBHW3peCs4NZQooXwgxBBEK/gZdZX8MplHHgOX3eIiBaCAQ8R0RyNl3w82T+ER08O4sn+IUyUA1iGwC2bu3BwRx/u3bkOm3syy32a8xaEEqVqgHyxCj/UCEIFqTUs04RtW1xJhegy/EBidLKcVAFNtzT8bAZCt2fc+hygpplA0X4HW8FoFamt4FVbtt02DaQcE9m0g7TnMPQhIkL0ofNo0ceb42W8OVbGm+NlnBuLvqLrSvjhH/4nBjxERPMVSoXjZ8fx6KkLePzUIPovFAAAm3syUdizow/7N3XBsVo7FJFSoVTxkS8HqPoSgVSQ8Qperm3B4koqRLOitUahHNRXAZvaDjZRmtVAaNMQ6GprDH0uHg6dTbEVjFpXKBX8IIAMm5dtz8XLtpv8sIGIVhmlNIYKVZwbKzWENuWm7XLQ/CFRzrVwbWcK13akcG1nCn/8v97MgIeIaLG8MVrCY/Hcnmd+PAJfKuRcC3duiwY13729Fz1Zd7lPc1EopVHxA+SLPso+l20nWixSaYznK0nwMzRRrgdBcSXQRHHmVjDXNptbweLwp7u9tjJYiivtUUsJpUIQxMu2i2imj2sbyMWVPqwwJaKVLJAK5ycqTYHNm+P1MOft8Qr8KbP+ujJOFN7EAc76zsbtNHKuhaofolQNUKwE2HRt70sq9G+e6VwY8BARzVGxGuKpV4fjZdgHMZivQghgz3UdOLg9Wob9HVe3rapP2JuWba+GTSt4mRzmTLRo/EBiZLLe9pXMAWpYJaxcDWd8nFzaiUOfqQOho2CoK+exUoJWNKkUfD8OfQDYtgnHEshlXGQY+hDREqoEEm+N11un3myqwinh/GQFUwt0+3JuFNp0pptCnPUdKVzTkULGjT6IkVKhGoQolH2UqxKhVAilhlQahmHAskw4tokt1/acDP3yO2Y6VwY8REQLoJTGy29P4tGTg3js1AW8cG4CAHBVm4d74laud9/Qg5SzOludkhW8Goc5Iyq5d2wLpsE34ESLrVgJLpr/U98uY2SihFBe/v2dIYCOnHfRamC17e72NNozDoNbWlGU0qgGAcJQwYSGlVT6uEh7Nmy2FRPRPBSqYXPVzVgZ5xraqIanLLRgGgJXtXlxgBOFNrXKm2s7Uri6w4M75edREEpUqgFKlRAVP0QgNUKpoAAYs6iS33xNNwMeIqKlNpiv4IlXhvDYyUEcPT2Eoi/hWgbedX03Du7owz07+rC+M73cp3lFhVKhWPFRKPmoBgph3OJlmJzrQ7QUlNKYKFabqn6SyzgIGi9UMNNbQMcy0D1NFVB3ezqpDkpzSWxaZlHoE0KGIQQA2zJgWwbaUg7SKYcr1xGtcVprjJeChsHFpYuGGU+Ug6b7OJaRtE81tk5d25HC+q401uXcS1YR+oFE2Q9QLAfwA4lAakgZr2ZrmbAtc17vhRnwEBEts2oo8exrY3j01AU8dmoQr4+UAAA7rsrhru29uGtrL/Zt6rwo4V+NppvrE8jm0lP+kki0dIJQYXTy4vav2uXIRBmFKW94p+M5FrrbvSgIaks1X7an0NPuIZtiJRAtLaV0tGx7GMIAQx+i1UwpjeFCNam4iUKbUlOAU5qyymXGMZsGGK9vbKPqSKEn6152lT+tdRTkVAIUKj78MKrGkVIDhoBhGHCdxa1kZ8BDRLSCaK1xZriIx04O4tFTF/Dc62MIpEbaMXH7lu4o8NnWi43drbsM+1zVXhwLZT/6lCNUCKWCBmDEc33Y4kW0fMrVECO1JeHj0GdovISReHt4ooxqMPPS8I5torvNS0KfxgCott2W5pLZdGXVZsmFUkJoDcs04FgGsmkHmZQNlwsIEK1IoVQ4P1mZMvcm3o6//LB5gHF7yr5oaHFjNU5HenarUSqlmwYdh1IjDOsrzppmNJJgKV6/GPAQEa1ghWqIf/vxCI70D+HJ/iGcHY2qezZ2p3HXtl4c2NqL26/vTgawrSVBKFGqBsgXq9EnIqGC1BpCGHAcizMWiFYIrTVKlQDDExWMTJaT4Kdpe6KM0iyGQlumUQ+BGgOghiCoPevCZAhEi6j2QUMYhtBKw7YY+hAttWoo8fZ4bQWqUhLg1Cpyzk9WIKdMMO7Juk1Di+urUKVxbWcK2Tm+fw6lQtUPUaw0DDoOFaTGiqk2Z8BDRNRCBoaLeLJ/CEf6h/D0j0dQDiRsU2D/xi7ctT0KfHZenVuzbQ61Fq9C2Ue5EsKPP0GBIWCZ5pJ9ekJEc1eqBHE72KWDoNm0g5mGQGeb19wClmxH13dydTBaoOlCH9sykE3ZyMbtXWv1tZhoIUKp8PpoCf3n83jlQh79F/J45XweAyOlpgDHENFiJVNbp2oVONd0pODNs82yNh+nXA5QaZyPAwHTFLCtlftBIgMeIqIWVQ0ljg2MJdU9p87nAUTLLR7Y1osD23px5w096Mw4y3ymy68ahCiX6/3PQVw2y4HORK2l6ocYmawkwc/wxMVB0GTRn/FxDAG0Zz10tcVfuVR9uy2VXGZTsyvPJwIaQx8JrVS0UqQpkPZs5NIOXIfDxolqtNZ4c7wcBziFJMh5daiQtFIJAWzsSmPbuhy2rcthU08mCXCuavdgLyCor7VjlqohSpeYj+PY1iWHJK9UDHiIiFaJ8xMVHDkdVfccPT2MiXIAIYBd6ztw17Zods/u9e0t90J1pVw00JnVPkSrgh9IjOYr07eCxeHQbFYHA6IVUjrbUujKeXFVkIfOthS6a6FQu4eunAfXYYsOXVo0yDkOfQwB2zKQ9izkUi48rjBHa8BwodpUkXPqfB6nLxRQaGjNvbrdw7Z1OWy/Kgpztq/L4Ya+LFLOwj6Ek1KhGoQolgOUqyGCOMSprdxqmdGKVavlPR8DHiKiVUgqjRfPjSftXCfeGIfSQJtn4c6tvTiwrQcHtvXi6vbUcp/qijO12qdxto9tR8EPEbW2UCqM5ysYzVcwOlGOLicrGJ0sx5fR9mzmAgFAxrObqn86c3ErWEMo1Jl12RZGiST0kQqmKeAw9KFVYLIS4PSUipz+C3mMNFRWdqZtbL8qCnC2xZdb1+XQnrIX9NxT26pCGVXkKETzcex46fHV/n+LAQ8R0RowXvLxg1eHk3auC5NVAMC2ddloWPO2XvzEpq559yqvdrXVEQplH6VqtHx7bSUv04pCH67kRbT6lKshxvKNwU8cBk1UMJqvh0GhVDM+lhBAe9ZNZgDVLjvbXHRko1CoI+ehI+uy0nKNCkIJ3w+hVT30STkWchkHnmOvmgoDan2VQOLVwUIS4LxyIY/+83m8NVFJjsk4ZhLgNFbm9GSdeYcsSmn4QdRWVSz7UfX1KmirWkwMeIiI1hitNfovFPBk/yCe7B/Cs6+NwZcKnm3gti3dSTvX5p7Mqv+UY6GCUKJcDVAsB6gGMg5+NIQhYLLNi2hN0FqjUPYxMhFXBDWGQbVqoHwZE4XqrNrCAKAt7aCzzYuDHzcJfzpzHjqz9VAoxUqPVS8MJapBHPoYArZpIOWYyKYdpFybVWF0RQVSYWC4mAQ4UYtVAa+PFFGbd+yYBq7vy2L7umxToHNtR2re74GCUKJSDVCqhKjEbfRSRqtVCSMacsxB5tNjwENEtMaV/BDPnBnBkf5hPNk/hNeGiwCA9Z2ppLrnXdd3I+ctrHR2rdBaww/lRW1ejb3efFNCtPZIqTBWqGJsMpoFNDpZxli+gvF8FWP5CsYKFYzlK5gsVKFm+bbbtc04+KlXAXXW9nP1/bYMl45fTUKp4AcBpFSwhIBlGfAcE7mUjZTnrOnqBZofpTTOjZWbVq3qv5DHj4cKCGT0A8kQwKaezEUVOZu60/P6N3fZahwBmPFsHC6EMTcMeIiIqMnZkRKejIc1P/3qMIq+hGUI7NvYiQNxdc87rm5jZcoc1d7IFCtRxU8gVTzfBzDMqKR4pS65SURLRyqNyWI1Dn8qcfhTxdhkBeNxCFQLhaqBnNVjGgJoy7pR9U/OQ0etKijeb8+66Mi6aM+6yHhcOawVSaXgByHCUMEUgGUKuLaBXNpF2rP5+kIAog+hhvJVvNIQ4rxyoYDTF/Io+fWfJ9d2pOrDjq/KYtu6HK7vzc6rld8PJCp+gPI01TirccjxcmPAQ0REl+SHCsfPjuHJ/iE8+coQXn57EgDQk1YiYXwAACAASURBVHVwYGu8FPvWHnRn3WU+09ZVW92hUPZRrkZtXlIqSCDpJecbcyKaSmuNih/NCBqbrCYVQLVQaLwQVwblK7NaOr7GMgXaMlFFUBL8ZKLwp3nfQ1uG1SIrmVIa1SCEDEMIALZlwLYMtKUcpFMOHM7dW9XGSz76LxSmtFflMV4KkmN6sm4S4NSGHm/ty865arv2XqZcjT7ICqfMxjFNA7a1tmfjLBUGPERENGuD+QqO9g8ny7GPlaKl2P//9u41Nq4zvQ/4/z23uc+QFCmK1F02KUt292I7u147axvNFune0luQbotsm3zoIsmXLdIiQPuhcT+0BQq0TbcFugiSIE22CHpxWhTFGptFW6+zSZ2NZO/NsnUXLYkURUq8zP3c3n5433PmnOFQGlG8Dfn/wcScM3OGHks+PJz/PO/zPDNZiZdzffzYEGxewB9bEIRouT7qLRfNlh+XLodA/IsSgx8i6ocfhFiutRPhTzoUWqm1sVpvY7nWRrPPyWGRUt7pEQJlUSk6qBSzqBQ61UFZjpPfcVKqoQF+EAChjEOfYs5GUYc+rOAaLA3Xx+UeQU40UAMAShkL0/H48U6vnEf5gE5KqSZVtdQSdD+QcTXOfptUtZsx4CEiog0JQokf316JJ3O9e3MZQShRylh46Uk1hv3l6VEcGc7v9EvdU1LBT4+KH9viKHci2ri2F2Cl1sZKvY2Vmgp/lqP9qrpdrrVVKNTov3E0AGQdE+VCRn3lHZQLDkqFDCoFB6W8vk3sF7KcHLUdojfuvh9AhiEsU8Dm2PZdx/VDXFtMTK7So8hvLjXi8zBjGZgaT1fknB4vYaKS7evvMOoj2HJ9NKMBEl1LqkxdXcxzc3diwENERJtipenhT6+o6p7vXFyIR2U+MVbAK9MH8crpMXzyJEexb5WoPLre9NBo+/ADNdErlBIQnDhBRJsvCCWqDXdtEKQDoOVaCyt1V93W2vD8h4+TTzIMgVJOBUHlQgalvINKIYNSQd/mHR0YOXFoxGVHm6d7bDsneG2PIJS4eb+xpiLn2kIdvu7AbhoCp0YLa8aQHxvJ99VQ3fUCtF09pcoL4uVUQagmgQqOGx9YDHiIiGjTSSlxdaGGNy8u4K3Li3j72j24foiMZeCTpw7g5alRvHp6DE+MFRk4bLFUc+fEung/kDAMAUNP9TIN/hJHRFtHSolm28dKvY3Vuotqo42Vuouq3l9t6Nt6W4VGdReNlvfwb9wl61ipwKdUcFDMOSjlHBTzahlSKe+gmHdQytko5h3kM6wU6ldygpcpVKWPYwk2c94AKSXurLbWVORcvltFy+uEocdG8qlmx6cPlXBytIDMQ/6soxCn6fpotnWIE0r4gQpxTF31yylVewsDHiIi2nJNN8CfXY9Gsd/F1QU1in2yksUrp8fw8tQYXnxyFJUcR7Fvl7gMWzdEdBNl2CGE+rSWfX6IaAd5fohqQ4VBUfjTOwxSt6v1Nvzg0d+zGAIo5BzVhyYfhUHpUCgKhKJwqJhzkM/aHD+PqJmzh8APOs2cTQPFvINCzkaGy4ZRb/t4f24VF+ZW8cGdTmVOtdXpeXWwlOlMrko0PC5k1v/z6yfEsXRfHNofGPAQEdG2u7XUwFuXFvHWpQX8yZVFVNs+TEPg2WNDeHlqDK+cHsMzkxV+orpD/CBEO9HnJ126bagmz6z6IaJdJqoSWq23sdroBEC1hodq00Wt4aLW9NR9er/a9DZUKQQAQgCFbLoqqJi1kc/aKOT0rd6ObvOZzv5eXk4W9fXxPB+QEpZlwDZF3Ncn4+zdHi53qy28N7uKC9HX3Cpu3KvHfXLKWQtPHSpj+lAxXl41PV7CcMFZ872SPXFaesy4H0p1TdZLsFmJQ0kMeIiIaEd5QYh3P1yOmzX/6PYKAGCk4ODTU6N4eWoMn54excFSdodfKSUnaDRcv6vqBzANA6Ze8sWld0Q0KIIgRK3pqdCn6aLaSIdAyVCoqvdrDRf1DQZDEdsyVPCTtZHXoc+aUCix3f3YIP6sjfr6hLqZs2UayDomSjkbuawzUD1fwlDixr26CnPmVuNQZ7HWmV51dCSHpycqODtZxtmJMs5Oltc0PA6CEK6nGxvra6uvP1QJ2ROHHhEDHiIi2lUWa21897Kq7nnr8gIWay4A4OnJMl6eHsMr02N49tgwHIu/5OwmUZPnpl7yFfX6CQIJCcC0DFgmx6cS0d4RBCHqLS8VCtVbHhpN1fOsoXuf1fW+2nbRaKkKyY0sJ0uyTIGsYyGftZHLWJ1tx0IuayGXsfS2vi9jIZ+1kHPsNY87lrFjP5uDMITrquEABpKj2zd3iZeUMvXf2L3/IC0vwKX5ahzivDe7gg/uVNFwAwCAZQhMjZfwdCLIOTNRjpeeu14AV18jm66vAhy9nCoEYAi1lMqyDFbH0mNhwENERLtWGEpcmFvFd3R1zzszS/BDiYJj4kU9iv3V6TEcHeEo9t3M8wO4XoBGy0OzrcrLo/AHQo1dZfhDRPuJWnoTqsmHLTcOglT446HecjvBUHdgpEMk9xGnkj2IYQjkMxayOvRJh0Y6FMpYyDgmso6+tdVtxjaRcSxkHX2r9zO2ueFlWJ3R7T5k2FnilXMslAoOss6jNcZ+7bXXcOrtt/Hl99+HuHkT8uhR/P6ZM7j2wgt47bXXUscuN1wd4kSVOSu4ulBHoCdYFTNWHOJElTmnRvMQEmi7flzh6geqAscPO/1wTNPgtY621KYHPEIIE8A5ALellF8QQnwMwNcBZAH4AH5FSvm9B30PBjxERNRLteXhT6/ei5dz3VpqAgBOjhbwiq7u+eSpEeQdNnQcFA8Kf6QQMAwRhz97tV8DEdFGeH6AZttHo60rQ1pRs10fzbanb9Xjrbavfs66erudPu5RR9j3y7GjAKgTCPUKiKL7ugMixzbgWCZs24RjGTCEACBhCiCvK5XyGROVYha5TO++RlJK/P5nP4u/8a1voZC4vwbgt7/4s3jqn38N781Vdc+cFcyutOJjDpWzcYgzfbCAUwfyOJC34fpRM+PoeqWqcNijjnbaVgQ8vwrgeQBlHfD8EYB/I6V8QwjxOQC/JqV89UHfgwEPERE9jJQS1xfrcXXP29fuoeWFcEwDP3FyGJ84cQDPnxjGR48OofiACRS0e6lxvJ03IZ4vdXPJEKEEDMOAoT8NZV8CIqKN84MwFfhEAZAKgzphUdv10XIDtD11G/WOabv6NrHf9oJte/22acRLu2zLRMY24qqinGPB/pPvohUEqGdyWMkVsZQv415hCG1bNTYWAEbzNiZKDiaK+qucRTmjqm1MQ0+WdMw4gLJMo+tLxNuGIVils89I2anYUsFfCD8IE0vW9X4/j/shgjDxuK+2vSCAF237IXw/hBck9oMQ3/j1v9pXwNPXb8ZCiCMAPg/gnwH41ei/FUBZb1cAzG7gz4uIiChFCIFTY0WcGiviF186iZYX4M9v3Mdblxbwx5cX8Rv/+xKkVONvz0yU8dzx4fjr8FCOv3gNAPWLsoN8du1kkTCU8PRkkWbLQ9tzVfijp4tIpJd+sfqHiGh9lmmglFfTwDZLtMwqGQh1AiK97SXu0/uuG6DlqZBIVXmGcH31xtb19H1d216gvtAGQgCBZcI3TfjR7fRPqLFn6oXBCgJYfoCi24DlB7CCALgPzEF9PS4h1J+paejgx9IhkKFvLQOmIWDoStXkdvylgyWj+7jUvqG31aADY53vo24BAQH9T+r3ILHOY0JEf2xCH6PuFInn9XpMCEBK9f+ARPe21BPFJEJdOBZKCUhAQnaO7d5H8n5Ahun7wlAilBJBGCIMO02qA31/mNwP9XGysx92HZ86Lnpc3x/oD5tSAU0YYhu72jy2vip4hBD/DcC/AFAC8A91Bc8ZAN+C+js3ALwopZzp8dyvAPgKABw7duy5mZk1hxAREfVtteXh3Q+XcX5mCedn7uPdD5fjZoiHytk47Hn+xDDOTJRhswJkT+mu/lG/gHV+MRNG9MsxAyAiokEkpcS9uotLd1bx/twqLt6t4vpiA3eqnSlWRcfEkXIGp/78LRy5M4NDq4sYalXhGzbapo3myCju/MIv6SoI9X430BUUflcFRRB2qiX8xBKtaN9P7IfhAL3Tp01jRMGeruQyo6ouo2v/UR43jDggtC0DttnZtixT7ev7bcvAF3/yqc1ZoiWE+AKAz0kpf0UI8So6Ac/XAHxHSvm6EOLnAHxFSvmZB30vLtEiIqLN5gchPrhT1YGP+rq9rHr45GwTHz1aUYHP8RE8e2wYlby9w6+YtlL0yW/LTQdAcUNMAQhDVQBxqgkR0c7x/QAtL8Ct+w1cWajh2mId1+7VcXWxgeVmZ1T9keEcnp4o4+nJCp45UsbZiQrGyxkA6NmDpw7g9Z/+aXz5jTfg+SGabQ/VRhuu3+mtI3Ql6KOOpI8qP/x4+UxiXy+l6a4UCbv3pUSolyQnK06SVSip/XUeC0OJQMpO5YyujAEQV5xEFTLJKpoH3b/2MbWf3DZ0WY8QnQqfzra+TexDQPdYQuK5+pjkfcnvE1cMpSuczLgCykhVM5ldlVFxRZSuhDL7PNY0RGpZXtRA29wFHxb124OnnyVaLwH4Gd1nJwugLIT4BoAvAviqPua/Avitjb5YIiKijbJMA88cruCZwxX83RdPAADmVpqpwOfr37mGILwKAJg6WEwt6zo5WuCyrj3EsdUv7IVc7+UInh8FQCoE8hJLwNQvzqoHkDBE3AOI/38QEfVPSrXMxQtCHWRIQEr4YYgPl5q4dq+Ba4t1XFmo48piHS1PreexTYGpgyX8pbPjODupAp2nJkooZ9f/YObaCy/gdSA1Ret1PUVLCBFfEyrFbOr1tV0/nmTmRpU7AEzTgGNZsKy1TZ0B6CBAVYgS7UaPNCa9q4LnfQC/LKV8UwjxUwD+pZTyuQc9nxU8RES0Exqujx/cXMH5mftx6LPa8gEABwoOno2WdR0fxjOHK8j2mNZB+0PUA0j1lVC9IlS5fucTVCl0CCQYAhHR/hKEKgwJw+hLQgAwzU5VhGkKtLwQN5aauHy3jot3a3h/bhVXF2qIVjiVMhbOTJbxtJ5k9fRkBU8eLMKxHr2qUkqZ+hncvd/3f1ugqn3qTTWVzNNLuGAImLrah1WftFM2s4JnPX8PwL8VQlgAWtB9doiIiHabvGPhU08cwKeeOABAvYm/ulDDuUSVz7cvzAMAHNPAM4ej5s0jeO74MMZKmZ18+bSNDEOoMb6OhXKh9zFBEOoGoNFUGb/TnDFVCSQgdD8gLgcjot0sCm6CIFRTg2QIIZFa1mIaAo5loFRQo85t24RlGJhdaeE9PYr8wtwq3ptdxVxiJPlEJYuzE2V89plDcWXOkeHNG4rQ/X02+n1N00Axn0Exn77mu16ggp+Wh7brxn19DL18x7Et9nujXeORKngeFyt4iIhot7pXa6uw58MlnL+xhB/eXoHrq7Lx4wfynebNx0cwdbDIX+bogcJQwgsC+H4Yjxf2dPPO5EQPCd1jwFRBUNTAkYjocUnZGdOsJgFJRKOKunuS2JaBjG3CsVRgETWUTXL9EFfu1nSIs4ILs6u4MLeKqq6INQTwxFhRhziqV87ZyTJGCps3wWu3iCaJNVseqk03rvYJwo339yF6kH4reBjwEBER9dD2A/z49mpqWddizQUAlLIWnj3WWdb10aNDKGQepyiW9qvuIMh1fbj6TUKyuaaUUI0qDRNITPNgVRDR/hKGEn6glo6GQaga5EbLpOKqQTU62zQEMo6JjG2pyTymCdvqb0lpteXh/bkqLsyuqOqcuVVcnq/BDdQHHznbxFMTpXh51dnJMp46VNr3S5xT/X1aHjxfVfuEUkIINR2JwQ9tBAMeIiKiTSSlxIf3Gzh3o1Plc+luFVJ/EnpmooTnjg3juRNqWdfhodxOv2TaQ5KfxLt+AE8HQp4fpiatyFAiiMIgod7sGaITBrHyjGh3SVXYhDIV2Biis0TK0NOEonHKjmPCMVXVX7+hTS9BKDFzr45L81Vcmle9ci7MrWLmXiM+5kDBwdnJcry86uxEGSdHC7tistCgCEMV/DR0j59omReDH+oXAx4iIqItttL08O6HnT4+37+5jIYbAFA9B5LLus5MlLj0hrZNEITwQ/XG0fNCtH0frhcgCJEes6vH9KqlYmqEvBBgKET0iOJx16GaIKVGT6fDGpEIaqLwxjEN2Lapg5vOMs3NPu/CUOLWUhOX5qu4OF/F5fkqLs7XcHWhFi9HBtSS5GTj47OTZRwsZRg8bJFewU8QSPihhMGlXpTAgIeIiGib+UGID+5Uce7GfZz/cBnnb9zHrG40mbNNfOzokAp9Tgzj2aPDqOTXH/1KtJ2iCiG1/COE5wVwA1UhFOhPmaMwKKoUClUrD0CoN6sQAkKIOBRiOESDRMqoSXoY98lS75N0lYV+y2QYQoegiaBGCBgG4NgmbL0MKrmMcjvPAyklZldauBSFOHdquHy3isvzNTS9ID5uspLF1HgJpw+VMHWwiNOHSnjyYBF5h8uNd4NoqVej7aPWdOEHURWnhGBz532JAQ8REdEuMLvcjCt8zs8s4cLcKgI9J3Z6vBhP6nr++DCOH8jzUzoaKNGb4kBXC/l62YEfBPEbkqhSSErVSyjUt1KHRoCqHjIMA1KqptOpSge9zXODeomWNgU6kAn1MidIQMpQVacl/z8TKqARiYBG6JDS1qGMbRqwrKiSxtCjv3dXBaaUEgvVNi7qpVWXdWXOlfkaqm0/Pu5gKYPp8RKmxos4PV7ClN4uZ/kBwyBKNneutVx4voyrfmAIGEanSTbtLQx4iIiIdqGG6+P7N5dxXvfyeWdmCat6Aslo0ek0bz4xjGcOV5Cx9nfDStr7oqqgIAwRBjos0pVEQagCoyAI45AoGRZJ6G0AiAMk/Y0FoAqLhHpnj+imExgZhlDHGAICgp+Gb5JkmAcpu0I9VRUj41VBMvF3qO7RBWEq7ItuE/cZiccs04ApBCyrc5usIDPE7gtnHtW9WhuX5mu6T46qxrk4X8VK04uPGSk4mB4v6jCnhNPjJUyPFzGU33sTrKg31wvQcj00mh5aXiJkhwrQbcuEbXG516DqN+BhDR4REdE2yjsWXnxiFC8+MQpAvbm9slBTzZtnlnB+5j7+6MI8AMAxDfyFI5W4l89zx4cxWszs5Msn2nSGIWBAqE+cN6moIKrkCGVySZkKGeIgScrUUhw/DBAGABLBEdAJjKL9KFhCFEqg85zUffpY/TDSW4k3WKn3Wuk3XgL9fxArU8+VPTc7d4g1/7boPZ/QOyJxQOq+5LHJ4CU6Rm9bpgEDgGEKCETLldTjpmHEFVrJoC3a369WGh4u3VUhzqU7ujLnbjWe4AgA5ayF6fESPv+RCUwfLGL6UAnT4yVeGwiOrfr1lAvZ1P1BEKLt+ag3PTTbPlxd8ROEarmXYRpwbJNTGfcIVvAQERHtMou1Ns7PqOqeczNL+NGtlXg07YkD+c6yrhPDeHKsyKoDogGTDIuS+0CPPKbr8aReYYjo8XgykKGdV2v7uKyrcZKVOfOr7fiYgmNiSlfhTI+rEOf0oRIbHtOmSS73ariqEb8XVUyCVT+7DZdoERER7REtL8B7syuJKp8l3KurT3TLWQvPHh/WI9qH8bGjQ2ySSUS0CzTdAFfudgKcKNC5vdyMj8naBqYOqr4403pp1dR4EYeHcnxTTTsmVfXj+qkmz9A9qWzThMVl5NuGS7SIiIj2iKxt6qqdEQDqU7eZew2cm+ks63rz4gIAwDQEzk6UOyPaTwxjopLbyZdPRLSntf0AV+/WcVkvr4omV314vxFXaTmmgVNjBTx/Yhh/e/yYrsop4shwHiarMGmXMU0DedNBPru2h5PrBWi7HhotHy3XhR9K+IFa7gohYOqqHzZ63hms4CEiItoDVhoe3rm5pJo3zyzh+zeX45G4k5UsPn58GFMHizg5WsATY+q2kOHnPERE/fKCEDcW6/Hkqkt3qrh0t4qZe414OqJlCJwcLcTLqqbHVZ+c4yN5vuGlPS1a8tVyfTRbnUbPQRAikGrJF/v9bByXaBEREe1jXhDig7kqzs3cx/mZJfzg1jJuLTWRvOyPlzM4NVrEybECTiWCnyPDOb4RIaJ9KwglZu7VU/1xLs1XcX2xDi9QP0QNAZw4UIiXVkVfJ0cLcCz+/CRKSoY/9ZYHNwp/Qlb+9IsBDxEREaW0vAAz9xq4tlDDtcU6ri3UcX1RbS83OuN2bVPg2Egep8aKOKXDn1M6/DlQcNgXgoj2hDCUuLXUVAHO3c7kqisLNbh+PMcdR0dyujdOp+nxE2NFZG32HyF6XFJKuH6AVltV/rS9AH4oEQQSfighDAHTMGDp8Ge//g7CHjxERESUkrVNnD6kJrF0u193cX2xhqsLdVxfrKsQaKGO71xciCd4Aaqp86mxog59Cjg5WtS3Bb7ZIaJdSUqJuZUWLs5X9fQqVZlzeb4WL2UF1HLWqfESfnJqFFMHVZDz5MEil7MSbSEhBDK2hYxtoVLMrnk86vnTdH202j68UDV8DkOppn0JHf5YBpd+gQEPERERARgpOBgpdBo5R4JQ4vZSE9cWVeBzbbGG64t1/L9r9/CH795OHXt4KBeHPcmqn8NDOY5yJ6It5wUh5ldbuLHYSC2tujxfQ7Xtx8eNlTI4PV7Clz5xNK7MmRovopy1d/DVE1Evjm3CsU2UCmsfC4JQjXp3fTTbHjzP7yz9knrpl2GoqV/7ZNw7Ax4iIiJal2kIHDuQx7EDebx6Ov1Yw/V1tU+n6uf6Yh3//Z3bqTdTGcvAiQOq4idZ9XNqtICh/NoJHURE3aSUWGp4mF1uxl9zKy3cTmzPr7YQJrpPjBQcTI8X8deePYwpPYJ8erzInztEe4RpGsiZBnJZG0B6YqiUEp4fwvV8NNt+Z9x7KBHGjZ8FhGHEvX/2QgDEgIeIiIg2JO9YeHqygqcnK6n7pZRYqLVxfaGOa4ud8OfinSq+fWEefuId2EjBwalRXfUzFk35KuDYgTwyFpd8Ee0XTTfA7EoTc8stzC43cXu5ibmVJmaXW5hdUSFOywtTz3EsA5OVLCaHcnjpydF4+9hIHtOHShgtZnbov4aIdpoQIq7+KebX/iyIev+4rgp/Wq4PL6r+SQRAxoD1/2GTZSIiIto2XhDi5v1GXPnTWfpVx0K1HR9nCODIcL6z5CvR9+dQOTsQv2QRkRKEEnerLRXWrFN9c7/upp4jBDBWzGByKIfDQzlM6PBGfaltNn0noq2yNgAKEOgAKF4CBkAYBixz63sAsckyERER7Tq2aejpXEX81Jn0Y6stDzfi4Kez5Ot71++j4XYaoeZsU4c+nV4/URBUYg8Nom0lpcRq009U3DRxe7kVb88ut3BntYUgTH+oXMpYcVjz0aNDOKy3Jyoq0BkvZzlunIh2TLL5c6/+PwDg+QE8P0DLVSPgPc9VE8D0+PdQAoZhQBhi25aBMeAhIiKiXaGctfGRI0P4yJGh1P1SStxZbeH6Qh1XF+t66VcNP7y1gm/+aC7Vc2OslImXeZ0aLcZB0NGRPGyTbxaJHlXLC3BnJVom1dIVNyrEmV1uYm65iXoigAUA2xQ4VMlispLDJ06OxBU3kxVVgTMxlGVDYyIaeLZlwrZM5NcO/wIAhKGE5wdoe2oJWNv1EYQSfqACoCCUkEKHQGJzQiAGPERERLSrCSEwUclhopLDi0+Oph5r+wE+vNdIjXe/vljHt96bx/36zfg4yxA4NrJ2ydfJsQLGihku86B9KQwlFmttzK60Es2L9bYOdBZr7TXPGy06mBzK4YmxAj49NaqXUKkKnMNDOYwWM5ycR0T7nmEIZBwLGcdCeZ0qoCAI4Qdh7xBIdiqBAPT1Q5UBDxEREQ2sjGXqEcelNY8tN1y91KuO61Gvn4U63rq8CNfvNGstZSycHEuPdo+CoLzDX5VocFVbXqpJsaq4aenlVGoZlRekl07lHVNV2VSyODtRjrcP6/43hypZZG02QCci2gymqca4PygECkOJwGvV+/l+bLJMRERE+0oYStxebsYVP51JX3XcXm6mjp2oZHF0JI9KzkYpa6GctVHMWChlLZSytr7t3reRt01WMNCWcv0Q86vpaptUFc5KE9WWn3qOaQgcKmfXNiyudLYrOZsVbUREu4wQ4ryU8vmHHcePpYiIiGhfMQyBoyN5HB3J4+XpsdRjTTfAjXvpqp9bS03cvN9AteWj2vJQa/sIH/L5mBBAMaMCoSgAUsGQ3Tscyqj9YrbznGLGgsW+QfuSH4RYbnpxtc1sYmR41Mz4brWN7s9ph/M2Jio5HB3J44VTI5jQIc5h3bz4YCnD/6eIiPYwBjxEREREWs4xcWaijDMT5XWPkVKi7gYq7Gn5WNXBT7Xlo9bubFdbPlb1MdWWj4VaG9cW6/G+G4Tr/jvi12ObPSqEOoFQKWujqO8rJ45JhklcTvP4wlCi5QdougFafoiWFyS+wtRtU9/f1sep56w9ruV17m+6AdqJY/weCWLGMlSvm6EsXp4aS40Lj/rfcEkhEdH+xqsAERER0SMQQqCYUSEKKhv/Pi0vSFUFRdurLT8OgeKwqN0JjWaXm3GY1OiaXtSLYxpxddB61UJxWJRYflaOn2Oj4Ji7atmOlBJtP+wRnqiApR3t+wGabpgKU9qJECZ+nh+qMbd+5/44qPHCvsK4XoQAspaJrG0ga5vI2SYytt63VHiXc0xkrcT9+rhS1tLVN6oHzkjB2VV/B0REtPsw4CEiIiLaAVnbRNY2MVbKbPh7+EEYh0PJaqFkIJQKinSY9KFecraq9x/WktHQS85KXYFQd7VQHArpECljm4lAJdRVKt2VMD0qYhLVMm2vR+jibyxwAVQlTFaHKTn9d5CxTWQtA8N5R99nxH8/2eS+fm7OMZGx0selnmeZyNgGMtbjjbslQSgoqAAABqNJREFUIiJ6FAx4iIiIiAaUZRoYyjsYyjsb/h5hKNHwglQI1B0OJUOk6L671RauLnSO6Z7G1C/HNJBJhC3JkKSSs5EtZVL3d1fBqMCls53+Xp3jco4JxzTY/JqIiPYsBjxERERE+5hhdJacTWxwyVm0ZKo7IGr7wdoqGF0JE1XBmAxciIiINgUDHiIiIiJ6LEKITVlyRkRERBvHOYlERERERERERAOOAQ8RERERERER0YBjwENERERERERENOAY8BARERERERERDTgGPEREREREREREA67vKVpCCBPAOQC3pZRfEEL8ZwCn9cNDAJallB/bgtdIREREREREREQP8Chj0r8K4H0AZQCQUv7N6AEhxL8CsLK5L42IiIiIiIiIiPrR1xItIcQRAJ8H8Fs9HhMAfg7AH2zuSyMiIiIiIiIion7024PnNwD8GoCwx2OfBjAvpbzc64lCiK8IIc4JIc4tLCxs8GUSEREREREREdF6HhrwCCG+AOCulPL8Oof8LTygekdK+ZtSyuellM+PjY1t8GUSEREREREREdF6+unB8xKAnxFCfA5AFkBZCPENKeXPCyEsAH8dwHNb+SKJiIiIiIiIiGh9D63gkVL+IynlESnlCQBfAvB/pJQ/rx/+DIAPpJS3tvA1EhERERERERHRA/Tbg2c9XwKbKxMRERERERER7ahHGZMOKeWbAN5M7P/C5r4cIiIiIiIiIiJ6VI9bwUNERERERERERDuMAQ8RERERERER0YBjwENERERERERENOAY8BARERERERERDTgGPEREREREREREA44BDxERERERERHRgGPAQ0REREREREQ04BjwEBERERERERENOAY8REREREREREQDjgEPEREREREREdGAY8BDRERERERERDTghJRy+/5lQiwAmNm2f+HeMgpgcadfBNEO4jlAxPOAiOcA7Xc8B4j253lwXEo59rCDtjXgoY0TQpyTUj6/06+DaKfwHCDieUDEc4D2O54DRDwPHoRLtIiIiIiIiIiIBhwDHiIiIiIiIiKiAceAZ3D85k6/AKIdxnOAiOcBEc8B2u94DhDxPFgXe/AQEREREREREQ04VvAQEREREREREQ04BjxERERERERERAOOAc8uIoT4HSHEXSHEj9d5XAghviaEuCKE+KEQ4tntfo1EW6mPc+BVIcSKEOL7+uufbPdrJNpKQoijQoj/K4R4XwjxnhDiqz2O4bWA9rQ+zwNeD2jPEkJkhRDfE0L8QJ8D/7THMbwW0J7V5znA60AP1k6/AEr5XQD/HsDvrfP4ZwFM6a9PAvgP+pZor/hdPPgcAIA/llJ+YXteDtG28wH8AynlO0KIEoDzQohvSykvJI7htYD2un7OA4DXA9q72gD+opSyJoSwAXxXCPGGlPLtxDG8FtBe1s85APA6sAYreHYRKeVbAO4/4JC/AuD3pPI2gCEhxMT2vDqirdfHOUC0p0kp56SU7+jtKoD3ARzuOozXAtrT+jwPiPYs/fO9pndt/dU9GYfXAtqz+jwHqAcGPIPlMICbif1b4C88tP98SpdrviGEeHqnXwzRVhFCnADwcQB/1vUQrwW0bzzgPAB4PaA9TAhhCiG+D+AugG9LKXktoH2lj3MA4HVgDQY8g0X0uI9JJu0n7wA4LqX8KIB/B+B/7PDrIdoSQogigNcB/H0p5Wr3wz2ewmsB7TkPOQ94PaA9TUoZSCk/BuAIgE8IIZ7pOoTXAtrT+jgHeB3ogQHPYLkF4Ghi/wiA2R16LUTbTkq5GpVrSim/CcAWQozu8Msi2lR6rfnrAP6TlPIPexzCawHteQ87D3g9oP1CSrkM4E0Af7nrIV4LaF9Y7xzgdaA3BjyD5X8C+Du6a/4LAFaklHM7/aKItosQ4pAQQujtT0D9DLu3s6+KaPPo/79/G8D7Usp/vc5hvBbQntbPecDrAe1lQogxIcSQ3s4B+AyAD7oO47WA9qx+zgFeB3rjFK1dRAjxBwBeBTAqhLgF4NehGkpBSvl1AN8E8DkAVwA0APzizrxSoq3RxznwswB+WQjhA2gC+JKUkuXItJe8BODLAH6k150DwD8GcAzgtYD2jX7OA14PaC+bAPAfhRAm1JvW/yKl/F9CiF8CeC2gfaGfc4DXgR4E/wyIiIiIiIiIiAYbl2gREREREREREQ04BjxERERERERERAOOAQ8RERERERER0YBjwENERERERERENOAY8BARERERERERDTgGPEREREREREREA44BDxERERERERHRgPv/WRTaSvfjNjMAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "np.random.seed(3)\n", + "bo = BayesOpt(param_ranges, \n", + " evaluate_params, \n", + " random_trials=2)\n", + "\n", + "bo._random_search()\n", + "bo._fit_gp()\n", + "bo.gp.plot(plot_density=0, figsize=(16, 4))\n", + "plt.scatter(bo.x[:bo.random_trials], bo.y[:bo.random_trials], color='r')\n", + "plt.plot(x, func(x))" + ] + }, + { + "cell_type": "code", + "execution_count": 436, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 2/2 [00:00<00:00, 1687.17it/s]\n", + " 0%| | 0/5 [00:00" + ] + }, + "execution_count": 436, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# np.random.seed(3)\n", + "bo = BayesOpt(param_ranges, evaluate_params, random_trials=2, optimization_trials=5)\n", + "bo.fit()\n", + "bo.gp.plot(plot_density=0, figsize=(16, 4))\n", + "plt.plot(x, func(x))\n", + "plt.scatter(bo.x[:bo.random_trials], bo.y[:bo.random_trials], color='r')" + ] + }, + { + "cell_type": "code", + "execution_count": 437, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'x': 10.0}" + ] + }, + "execution_count": 437, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bo.best_params" + ] + }, + { + "cell_type": "code", + "execution_count": 407, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([4.47201616])" + ] + }, + "execution_count": 407, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bo._new_proposal(n=25)" + ] + }, + { + "cell_type": "code", + "execution_count": 398, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'dataplot': [],\n", + " 'gpmean': [[]],\n", + " 'gpconfidence': []}" + ] + }, + "execution_count": 398, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "bo._fit_gp()\n", + "bo.gp.plot(plot_density=0, figsize=(16, 4))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 261, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 10/10 [00:00<00:00, 13648.89it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Starting 10 random trials...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "# np.random.seed(1)\n", + "bo = BayesOpt(param_ranges, evaluate_params, xi=0.05, random_trials=10)\n", + "bo._random_search()" + ] + }, + { + "cell_type": "code", + "execution_count": 364, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 364, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "bo._fit_gp()\n", + "bo.gp.plot(plot_density=0, figsize=(16, 4), plot_limits=[0, 10])\n", + "plt.plot(x, func(x), ls='--')\n", + "plt.scatter(bo.x[:bo.random_trials], bo.y[:bo.random_trials], color='r')" + ] + }, + { + "cell_type": "code", + "execution_count": 356, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1.])" + ] + }, + "execution_count": 356, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bo._new_proposal(n=25)" + ] + }, + { + "cell_type": "code", + "execution_count": 385, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 385, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "ei = expected_improvement(\n", + " f=bo.gp.predict,\n", + " y_current=bo.y.max(),\n", + " x_proposed=x[:, None],\n", + " xi=0\n", + ")\n", + "\n", + "plt.plot(x, ei)\n", + "plt.vlines(bo._new_proposal(), 0, max(ei))\n", + "plt.vlines(bo.x[bo.y.argmax()], 0, max(ei), linestyle='--')" + ] + }, + { + "cell_type": "code", + "execution_count": 151, + "metadata": {}, + "outputs": [], + "source": [ + "def optim_f(x):\n", + " return -expected_improvement(\n", + " f=bo.gp.predict,\n", + " y_current=bo.y.max(),\n", + " x_proposed=x[None, :],\n", + " xi=bo.xi)\n", + "\n", + "\n", + "x0 = np.random.uniform(\n", + " low=bo.bounds[:, 0],\n", + " high=bo.bounds[:, 1],\n", + " size=(25, bo.x.shape[1])\n", + ")\n", + "proposal = None\n", + "best_ei = np.inf\n", + "for x0_ in x0:\n", + " res = optimize.minimize(optim_f, \n", + " x0_, \n", + " bounds=bo.bounds)" + ] + }, + { + "cell_type": "code", + "execution_count": 153, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.05296022])" + ] + }, + "execution_count": 153, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ei_along_axis([8.94396671])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## With real data" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['data', 'target', 'feature_names', 'DESCR', 'details', 'categories', 'url'])" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fetch = fetch_openml('SpeedDating')\n", + "fetch.keys()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " has_null wave gender d_importance_same_race d_importance_same_religion \\\n", + "0 0.0 1.0 0.0 0.0 0.0 \n", + "1 0.0 1.0 0.0 0.0 0.0 \n", + "2 1.0 1.0 0.0 0.0 0.0 \n", + "3 0.0 1.0 0.0 0.0 0.0 \n", + "4 0.0 1.0 0.0 0.0 0.0 \n", + "\n", + " d_pref_o_intelligence d_pref_o_funny d_pref_o_ambitious \\\n", + "0 0.0 0.0 0.0 \n", + "1 1.0 1.0 0.0 \n", + "2 0.0 0.0 0.0 \n", + "3 1.0 1.0 0.0 \n", + "4 0.0 2.0 0.0 \n", + "\n", + " d_pref_o_shared_interests d_sinsere_o ... d_theater d_movies \\\n", + "0 0.0 0.0 ... 0.0 0.0 \n", + "1 0.0 0.0 ... 0.0 0.0 \n", + "2 0.0 1.0 ... 0.0 0.0 \n", + "3 0.0 0.0 ... 0.0 0.0 \n", + "4 1.0 0.0 ... 0.0 0.0 \n", + "\n", + " d_concerts d_music d_shopping d_yoga d_expected_happy_with_sd_people \\\n", + "0 0.0 0.0 0.0 0.0 0.0 \n", + "1 0.0 0.0 0.0 0.0 0.0 \n", + "2 0.0 0.0 0.0 0.0 0.0 \n", + "3 0.0 0.0 0.0 0.0 0.0 \n", + "4 0.0 0.0 0.0 0.0 0.0 \n", + "\n", + " d_expected_num_interested_in_me d_expected_num_matches met \n", + "0 0.0 0.0 0.0 \n", + "1 0.0 0.0 1.0 \n", + "2 0.0 0.0 1.0 \n", + "3 0.0 0.0 0.0 \n", + "4 0.0 0.0 0.0 \n", + "\n", + "[5 rows x 55 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.DataFrame(fetch.data, columns=fetch.feature_names)\n", + "# make it a bit harder\n", + "df = df.drop([\n", + " 'samerace', 'sincere_important', 'age_o', 'shared_interests_important', 'pref_o_attractive', 'exercise', 'd_like', 'hiking', 'art', 'concerts', 'sports', 'pref_o_intelligence', 'pref_o_sincere', 'pref_o_ambitious', 'intellicence_important', 'pref_o_funny', 'funny_partner', 'attractive_important', 'interests_correlate', 'guess_prob_liked', 'funny_o', 'expected_num_matches', 'shared_interests_o', 'attractive_partner', 'attractive_o', 'like',\n", + " 'clubbing', 'expected_happy_with_sd_people', 'importance_same_race', 'attractive', 'ambtition_important', 'd_d_age', 'race', 'reading', 'expected_num_interested_in_me', 'd_ambitous_o', 'd_interests_correlate', 'sincere', 'intelligence', 'movies', 'd_pref_o_sincere', 'importance_same_religion', 'd_funny_partner', 'd_pref_o_attractive', 'sincere_partner', 'tvsports', 'race_o', 'museums', 'funny_important', 'gaming', 'intelligence_o', 'ambitous_o', 'd_shared_interests_o', 'sinsere_o', 'intelligence_partner', 'field', 'ambition_partner', 'd_age', 'age', 'd_guess_prob_liked', 'pref_o_shared_interests', 'd_funny_o', 'd_attractive_partner', 'd_attractive_o', 'shared_interests_partner']\n", + ", axis=1)\n", + "\n", + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "x_train, x_test, y_train, y_test = train_test_split(df, fetch.target)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "imputer = preprocessing.Imputer(strategy='mean')\n", + "x_train = imputer.fit_transform(x_train)\n", + "x_test = imputer.transform(x_test)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# decision tree\n", + "param_ranges = {\n", + " 'min_samples_split': {\n", + " 'range': [2, 10],\n", + " 'type': 'int'\n", + " },\n", + " 'min_samples_leaf': {\n", + " 'range': [1, 10],\n", + " 'type': 'int'\n", + " },\n", + " 'max_depth': {\n", + " 'range': [3, 1000],\n", + " 'type': 'int'\n", + " }\n", + "}\n", + "\n", + "# nn\n", + "param_ranges = {\n", + " 'hidden_layer_sizes': {\n", + " 'range': [1, 10],\n", + " 'type': 'int'\n", + " },\n", + " 'batch_size': {\n", + " 'range': [10, 100],\n", + " 'type': 'int'\n", + " },\n", + " 'learning_rate_init': {\n", + " 'range': [0.00001, 0.01],\n", + " 'type': 'float'\n", + " }\n", + "}\n", + "\n", + "def evaluate_params(hyperparams):\n", + " m = MLPClassifier(**hyperparams)\n", + " m.fit(x_train, y_train)\n", + " return m.score(x_test, y_test)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +}