{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# ML examples using `sklearn` and `gym`\n",
    "\n",
    "In this exercise you will see how to use library implementations ML algorithms in the following settings:\n",
    "\n",
    "- Classification.\n",
    "\n",
    "- Regression.\n",
    "\n",
    "- Clustering.\n",
    "\n",
    "- Reinforcement Learning\n",
    "\n",
    "You are expected to go through the code while referencing the relevant API documentation in [sklearn](https://scikit-learn.org/stable/). It might be useful to modify the code or parameters so you can better understand how it works."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np \n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "from IPython import display"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Classification with k-Nearest Neighbors algorithm\n",
    "\n",
    "[Nearest neighbors](https://scikit-learn.org/stable/modules/neighbors.html)\n",
    "\n",
    "[KNeighborsClassifier](https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Toy dataset preparation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.datasets import make_moons, make_circles, make_classification\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from matplotlib.colors import ListedColormap\n",
    "\n",
    "\n",
    "name = \"Nearest Neighbors\"\n",
    "\n",
    "classifier = KNeighborsClassifier(5)\n",
    "\n",
    "X, y = make_classification(n_features = 2, n_redundant = 0, n_informative = 2,\n",
    "                           random_state = 1, n_clusters_per_class = 1)\n",
    "rng = np.random.RandomState(2)\n",
    "X += 2 * rng.uniform(size = X.shape)\n",
    "linearly_separable = (X, y)\n",
    "\n",
    "X, y = make_moons(noise = 0.3, random_state = 0)\n",
    "\n",
    "# preprocess dataset, split into training and test part\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size =.4, random_state = 42)\n",
    "normalizer = StandardScaler()\n",
    "normalizer.fit(X_train)\n",
    "\n",
    "X_train = normalizer.transform(X_train)\n",
    "X_test = normalizer.transform(X_test)\n",
    "x_min, x_max = X[:, 0].min() - .5, X[:, 0].max() + .5\n",
    "y_min, y_max = X[:, 1].min() - .5, X[:, 1].max() + .5\n",
    "\n",
    "# Set step size in the mesh.\n",
    "h = .02\n",
    "# Create a mesh [x_min, x_max] x [y_min, y_max] with step size h.\n",
    "xx, yy = np.meshgrid(np.arange(x_min, x_max, h),\n",
    "                     np.arange(y_min, y_max, h))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Train & Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy on test data: 97.5\n"
     ]
    }
   ],
   "source": [
    "# Train classifier and compute accuracy on test data.\n",
    "classifier.fit(X_train, y_train)\n",
    "score = classifier.score(X_test, y_test)\n",
    "print('Accuracy on test data:', 100 * score)\n",
    "\n",
    "# Estimate class probabilities for each point in the mesh.\n",
    "Z = classifier.predict_proba(np.c_[xx.ravel(), yy.ravel()])[:, 1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot decision boundaries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Put the result into a color plot showing decision boundaries.\n",
    "# For that, we will assign a color to each point in the mesh.\n",
    "def plot_boundaries(xx, yy, Z, score, name):\n",
    "    cm = plt.cm.RdBu\n",
    "    cm_bright = ListedColormap(['#FF0000', '#0000FF'])\n",
    "    Z = Z.reshape(xx.shape)\n",
    "    plt.contourf(xx, yy, Z, cmap=cm, alpha=.8)\n",
    "\n",
    "    # Plot the training points.\n",
    "    plt.scatter(X_train[:, 0], X_train[:, 1], c=y_train, cmap=cm_bright,\n",
    "               marker='^', edgecolors='k', alpha=0.3)\n",
    "\n",
    "    # Plot the testing points.\n",
    "    plt.scatter(X_test[:, 0], X_test[:, 1], c=y_test, cmap=cm_bright,\n",
    "               edgecolors='k', alpha=1)\n",
    "\n",
    "    # Finish the plot.\n",
    "    plt.xlim([xx.min(), xx.max()])\n",
    "    plt.ylim([yy.min(), yy.max()])\n",
    "    plt.xticks(())\n",
    "    plt.yticks(())\n",
    "    plt.title(name)\n",
    "    plt.text(xx.max() - .3, yy.min() + .3, ('%.2f' % score).lstrip('0'),\n",
    "            size = 15, horizontalalignment = 'right')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_boundaries(xx, yy, Z, score, name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Classification with Neural Networks\n",
    "\n",
    "[Neural Network Models](https://scikit-learn.org/stable/modules/neural_networks_supervised.html)\n",
    "\n",
    "[MLPClassifier](https://scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPClassifier.html#sklearn.neural_network.MLPClassifier)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy on test data: 95.0%\n"
     ]
    }
   ],
   "source": [
    "from sklearn.neural_network import MLPClassifier\n",
    "\n",
    "name = \"NN classifier\"\n",
    "\n",
    "# Train a NN with one hidden layer of size 100, for 10,000 epochs,\n",
    "# with an adaptive learning rate, and an L2 decay of 0.001.\n",
    "nn = MLPClassifier(hidden_layer_sizes = (100,), activation = 'relu', random_state = 1, \n",
    "                   max_iter = 2000, shuffle = False, tol = 0.0001, alpha = 0.001, \n",
    "                   learning_rate = 'adaptive')\n",
    "nn_clf = nn.fit(X_train, y_train)\n",
    "\n",
    "# Compute accuracy on training examples.\n",
    "score = nn_clf.score(X_test, y_test)\n",
    "print('Accuracy on test data:', str(100 * score) + '%')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Estimate class probabilities for each point in the mesh.\n",
    "Z = nn_clf.predict_proba(np.c_[xx.ravel(), yy.ravel()])[:, 1]\n",
    "\n",
    "plot_boundaries(xx, yy, Z, score, name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Regression with Support Vector Regression (SVR)\n",
    "\n",
    "[SVR class in sklearn](https://scikit-learn.org/0.16/modules/generated/sklearn.svm.SVR.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Toy dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.svm import SVR\n",
    "\n",
    "# Generate 40 samples uniformly at random in [0, 5].\n",
    "X = np.sort(5 * np.random.rand(40, 1), axis = 0)\n",
    "t = np.sin(X).ravel()\n",
    "\n",
    "# #############################################################################\n",
    "# Add noise to every other 5 samples.\n",
    "t[::5] += 3 * (0.5 - np.random.rand(8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Train & Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create SVR regression model.\n",
    "svr = SVR(kernel = 'rbf', C = 1e3, gamma = 0.1)\n",
    "\n",
    "# Fit regression model.\n",
    "svr.fit(X, t)\n",
    "\n",
    "# Predict target values.\n",
    "y = svr.predict(X)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot examples and learned target function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'target')"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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op6IHXLWD6b2Sosk74TKAX4ipXz4CAxsQFvY+Xbu+w7FjK9m793+cPLkBMGI0ZnH8+CqOH1+Fr28wzaq1pfmZcMrnNYOWchlWDoZ+y5UQiYhDKVXJUFJSEidOnDBfnz59mv3791O+fHmqVavG5MmTiY6OZt68eYBp59iMGTOYNGkS48ePZ8eOHXz55ZcsWrTIXt+C2FFU1A5WrRrPpUuHzW3lytWiT5/PqF27e943FTYF1uJ5y97c0umuO7m4mpKulUMwzVfdHkf26FXn6RaNOrm6etCo0RAaNRrCtWtn2bfPtMA6IcGUzCUlxbD993C2AzVdobkbNHQDtztnlDc9f/cjXSIiJVCp2lofERFB586dc7U/8cQTzJ07l9GjR3PmzBkiIiLMz23ZsoUXXnjBXHTx5ZdfVtFFJ5OamsAPP0xm9+5PubVd3pW2bf9Gp06v4+7uk/eNWZnwRY0CRn4M4B0INy4VHsSjm+9uZOimvEan/EJNidA9jNJkZWVy8uQG9u79guPHVpJlzMzxfBkDdPaAFm6mHWxm9/r9iIjYmMNWoLYHJUOl29Gj37J27TMkJkab24KDW9K37xcEBzcv+OaoCFiaO/nOxbsi3IijwGmscaets83e2lv3b5O091MOfP80e9Phyh3fSg1X6OcJ5W5On/VeCA2HW+29RUSsTXWGxOklJp5n3bpnOXIk3Nzm7u5D585v06bNs5Ztl7d0aqvhSNj7Efc6jVUoF1ebjsb4VmzInzygnTuczYJf0+BI9kDRmUz49Dp094RWbmCwdGG3iEgpoGRIHIrRmMWePbP44YeXzXV2AOrU6UmfPp9StmwNy1/M0g/8Ov0hpEMe01gh9zyNVayqdoAyVTEkR1PDFWp4w6kMWJkK8UZIB9amwu9GT/r5hFDO3vGKiFiJpskKoWmy0uPSpd9ZteopoqJ+MreVKVOJnj0/4r77hhb9SArzmqFCdnLdnAKz8TRWsYgMN+0Yu02qETamwp6MW23u7mXo1m0aDzzwFxVvFJESSWuGrEjJUMmXkZHK9u1T2bbt32RlpZvbmzV7krCw9/H2Ln/3L27eTQZ5ToHdS0HFkirPOkNwysWPlRmexF+PM7fVqNGJfv1mU65czeKOUkSkQEqGrEjJUMl29uw2Vq9+iri4o+a28uXr8PDDs6hZ04LFz5aw0U6uEi2fCtSp6dfZuPEl9uz5zNy1yKNEjjCCJiIlnpIhK1IyVDKlpFxj48aX2bt3lrnNxcWNdu1eomPHf+Lu7m3dN9QHeA6nTv3IypVjiY8/a26zaJTIVme4iYjcQcmQFSkZKlmMRiNHjixn3bpnSUq6ddRK1aqt6dv3C4KCmtoxOueSmppYtFGi/ApYOvKUo4jYjZIhK1IyVHLEx0exbt0zHDu20tzm4eFLly7/5oEHnsbFiUdq7Cn/UaIvbx12a0kBS2vVYxIRoWif39oGIiVeVlYmv/46g5kzG+VIhOrV68vTT/+eXTdIH6D2UqtWV/7yl0O0bHmrsvuZMxF8+mlTfv31E4zGrOwpRgvPcBMRKWaqMyQl2oULh1i9+in++OMXc5uvb2V69fovDRsOLvp2ebEJT08/Hn74Uxo1GmIeJUpPT2bdumc4cmQZ/Rr1t6wu0d2e4SYicg80TVYITZPZR0ZGClu3vs1PP00jK+tWgZsWLcbTrds0vL1V8q+kynMtkZsX3VxSeMD9jjPO7qQzz0TESrRmyIqUDBW/M2ciWLXqKa5ciTS3VahQn759Z1G9ekc7RiZFkedaojvPODPTmiERsS6tGZJS6caNK3z33Vi++qqzORFycXGnY8fXmDBhvxKhUibPtUTZZ5z9mga3/gyz8hluIiJFpJGhQmhkyPaMRiOHDy9h/frnSU6+aG4PDW3Hww/PolKl++wYnVhDXqNEtV1hsBd4+zt4AUsRsQtNk1mRkiHbunbtLGvXPk1k5Fpzm6enP127vkurVn/WuVcOJK+1ROX8qjB0+GqCgpsXfLOKXopIESkZsiIlQ7Zh2i7/XzZt+ifp6cnm9gYNBtKr13/x969qx+jElk6d+oHly0dw/folANzdfejffw733fdo3jeoarWI3AUlQ1akZMj6YmP3s2rVeM6f321u8/OrQq9eM2jYcKAdI5PiEh9/jiVLBhETs8fc1q7dS3Tt+u+cNaNUtVpE7pKSIStSMmRdO3f+l++/fwGjMdPc1qrVX+jadSpeXgF2jEyKW3r6DdasmcCBA/PMbbVrhzF48CK8vcurarWI3BPtJpMSad++Oaxf/5w5EapYsRFjxmynT5+ZSoSckLu7N/37z6Vnz48xGEzJzMmTG5g1qxUXLhxU1WoRKTZKhqRYHDu2klWrxpuv27Z9kaee2ku1an+yY1RibwaDgTZtnuXxx3/Ex6ciANeunebLL9ty+MgKy15EVatF5B4pGRKbO3t2K8uWDTWPCLVu/Rzdu7+Hm5unnSOTkqJGjYd46qk9VKnSCoD09Oss2/ExW3LUI8qHb7DtAxQRh6ZkSGwqNvYAixb1JSMjBYAmTUbQs+f/6UwxySUgIJQxY7bRrNloc1tEGnybChl5JkQG8As1bbMXEbkHSobEZq5ePcX8+T1ITU0AoE6dnvTvP0e1gyRfbm5e9Os3m27d3jO3HcyAr2/A9RwJkapWi4j16FNJbCIpKZavv+5OcvIFAEJCHuSRR5bh6uph58ikpDMYDPzpT3/n0UeX4+bmDcC5LPjyOsRlZXfyC9G2ehGxGiVDYnUpKfHMn9+Tq1dPAaZdYyNGrMHDo4xpu3RUBBxZZPqalVnAK4kza9hwEKNHb8HXtzIAV4zwZUYZznT4P9N2eiVCImIlSobEqtLTb7B4cT8uXDgAQEBANR577HtT3ZjIcFPdmKWdYe0I09cvapjaRfJQteoDjBu3k0qVmgCQkpbM/A3/4PiJdXaOTEQciZIhsZqsrAyWLx/O2bNbAfDxCeSxxzbg7x9yq5LwnXVjkqJN7UqIJB8BAdV48smfqFOnFwCZmaksWTKQQ4cW2jkyEXEUSobEKoxGI6tXT+DYse8AcHcvw4gRawkMrG+aCtv0PLmPVOBW2+aJmjKTfHl6+jFs2Hc0bjwcMCXe4eGPsWvXp3aOTEQcgZIhsYqffprGvn1fAuDi4s6wYd9SteoDpidVSViswNXVnYEDv6ZlywnZLUbWrn2a7dvftWtcIlL6KRmSe3bkyAp+/HGy+XrgwK+pVavbrQ6WVghWJWEphIuLK336zORPf/qHue3HHyfzww//QMcsisjdcrN3AFK6xcTsY8WKx8zXnTu/RePGQ3N2srRCsCoJiwUMBgPdupkO9r2ZhP/00zRSUuLp0+cTy+tYZWVmj1rGmP7bq9pBNYtEnJSSIblrSUkXWLSoL+np1wFo0mQkHTq8mrtj1Q7gG2JaLJ3nuqHs08dVSViKoH37f+DlVZY1a54GjOzZ8xmpqfEMGPAVrq7uBd8cGW5ax3b79K1vCHT5SFv2RZyQpsnkrmRlZRIePpLExGjAVFSxX/PHMRxdnLt+kIur6UMGMFcONlMlYbl7rVpNYNCg+eZT73/7bRFLlgwkPf1G/jdpZ6OI3EHJkNyVbdve4fTpHwHw9SrL0NSzuIX3yL9+UN1BporBvlVzvpAqCcs9atJkBEOHrsDV1XTwb2TkGhYs6GU+BiYH7WwUkTwYjFp1WKCEhAQCAgKIj4/H39/f3uGUCKdPb2LevG6AEYPBhce9sqiRa1Ane8TnzkRH6zTERs6ciWDRor6kpSUBUKVKK0aOXIePT+CtTlERpmS9MI9uhtBOtghTRIpJUT6/NTIkRZKUFMvy5SO4+Vd0pzK+eSRCkO9f2S6upg+ZhsNNX5UIiZXUqNGJxx/fZKp2Dpw/v5u5cx8iISH6ViftbBSRPCgZEotlZWWyfPkI8+Grtau2ooMxj6kIM9UPkuJVteoDjB69Fd/snYmXLv3OnDkduHLlpKmDdjaKSB6UDInFtm59izNnNgPg51eFgS3HYrhzPXRe9Fe2FKNKle7jySe3U65cLQCuXTvNnDntuXjxt1s7G3Mt5L/JAH6h2tko4mSUDIlFTp36kS1b3gTAYHBh8OBFlAlsYNnN+itbilm5crUYM2YbFSveB5imd+fM6Uh0zB7tbBSRXJQMSaESE2MID7+1Tqhz57eoXr2j/sqWEs3PrwqjR2+hShXTsTApKVeZN68rp93KaWejiOSgZEgKZKonNILk5IsA1K7dg/bts49CUP0gKeF8fCrw+OM/UqOGaQdZWloSCxb04liWG4w/Y9o11nuh6eu400qERJyUkiEp0JYtUzhzJgIAP7+qDBz49a3jDrIywas8tHgevANz3qi/sqWE8PT0Y+TItdSr1xeAzMxUliwZxMHfFmlno4gAOo5DCnDy5Ea2bn0bAIPBlSFDFlOmTEXTk3kdZ+AVCI0egzr9VT9IShQ3Ny8efXQ53303hkOHFmA0ZrJixShSUxN44IGn7R2eiNhZqRsZmjlzJjVr1sTLy4uWLVuybVv+27YjIiIwGAy5HkePHi3GiEunxMTzhIeP5OY6oS5d3qZatfamJ/M7ziDlMuz9CFKuKBGSEsfV1Z2BA+fRqtVfzG1r1/6V7dun2TEqESkJSlUytGTJEiZOnMirr77Kvn376NChA7169eLcuXMF3nfs2DFiYmLMj7p16xZTxKVTVlYGy5eP4Pr1SwDUqdOLP/3ppewndZyBlF4Ggwu9e39C+/aTzW0//vgPdu78rx2jEhF7K1XJ0IcffsjYsWMZN24cDRs2ZPr06YSGhvLpp58WeF+lSpWoXLmy+eHqqlGLgkRETOHs2S3AzXVC826tE4relntEKAcVWpSSzWAw0LXrv+nS5d/mtvXrn2P//rn2C0pE7KrUJENpaWns2bOHsLCwHO1hYWH8/PPPBd7bvHlzgoOD6dq1K5s3by6wb2pqKgkJCTkezuTkyQ1s2/YOcHOd0JKcZzvpOANxEB06TKZDh3+ar1euHMvvvy+3Y0RSImRlms6wO7LI9FWj3E6h1CRDcXFxZGZmEhQUlKM9KCiI2NjYPO8JDg5m1qxZLF++nPDwcOrXr0/Xrl3ZunVrvu8zdepUAgICzI/Q0FCrfh8lWUJCdI51Ql27/ptq1f6Us5OOMxAH0rnzm7Ru/RwARmMWy5cP58SJ7+0cldhNZDh8UcN0mO/aEaavX9QwtYtDKzXJ0E2GO85/MBqNudpuql+/PuPHj6dFixa0bduWmTNn0qdPH/7zn//k+/qTJ08mPj7e/IiKirJq/CVVVlYG4eEjuH49DoC6dXvTrt2LuTuq0KI4EIPBQM+e/0ezZqMByMpKZ8mSgZw9q2lep5PfxpCkaFO7EiKHVmqSocDAQFxdXXONAl28eDHXaFFBHnzwQSIjI/N93tPTE39//xwPh5eVyebvRnP2rGnEzN8/hAEDblsndDsVWhQHYzC40LfvFzRsOBiAjIwbLFr0MOfP77FzZFJstDHE6ZWaZMjDw4OWLVuycePGHO0bN26kXbt2Fr/Ovn37CA7WFI5ZZDgnZlRm+8EFgCmdGeKWik/0lvzvqTtIxxmIQ3FxcWPQoAXUqdMTgNTUBObP78GlS7/bOTIpFtoY4vRKVdHFSZMmMWrUKFq1akXbtm2ZNWsW586dY8KECYBpiis6Opp58+YBMH36dGrUqMF9991HWloa8+fPZ/ny5SxfrkWSAESGk/zdYL69fqupqweEpsWZhoULSmzqDoLa/bN/icSY1gip0KKUYm5unjz66HLmz+/JuXPbuHHjMl9/3Z0xY7ZRrlwte4cntqSNIU6vVCVDQ4cO5fLly7z55pvExMTQuHFj1q5dS/Xq1QGIiYnJUXMoLS2NF198kejoaLy9vbnvvvtYs2YNvXv3tte3UHJkpGHc8GfWpEBy9ihwXVdo5w6mYWGDaVi4dv/8ExwXV9MxBiIOwt3dh+HDVzFvXldiYvaQmHieefO6MWbMNvz9qxb+AlI6aWOI0zMYjca8JkklW0JCAgEBAcTHxzvO+qHIcNjwZw4mxrEi1dTkDTztA753Tpw+ulkJjzid69fjmDv3IfM0WWBgQ8aM2ZqzzIQ4jqxM066xpGjyXjdkMC0DGHdao9+lSFE+v0vNmiGxkuwdE4nX41ibeqv5Ya88EiHQsLA4JR+fQEaN2mieHouLO8L8+T1ISYm3c2RiE9oY4vSUDDmT23ZMfJ8GN3OhJm7QKL8JUw0Li5Py86vCqFE/4OdXBYCYmL0sWvQw6enXC7lTSiVtDHFqmiYrhENNk0VFwNLOnMyA+SmmJm/gmTLgk6tskIaFRQAuXfqduXMfMtfgql27B8OGfYebm6edIxObyMrUxhAHoWkyyVtSDBlGckyPdffMKxHKpmFhESpWbMRjj32Pp6fpl+nJk98THj6SrKwMO0cmNnFzY0jD4aav+h3oFJQMORPfYLanw5XsscBqLtAsr+kx74oaFha5TXBwC0aMWIObmzcAR44sZ+XKcRiNWXaOTESsQcmQE7niHcz2NNO/XYA+npDrJBPvivDUH0qERO5QrVp7hg5dgYuLOwAHDnzF+vUT0UoDkdJPyZCTMBqNrF3/HDeLyT/oDpVyjP4aTI/un4GbR/EHKFIK1KnTg8GDF5mPqvn11/+yefO/7ByViNwrJUNO4vffv+HkyQ0A+PsE8lC5Kjk7aMeEiEUaNRpMv36zzdfbtr3DTz+9b8eIRORelaoK1HJ3UlMTWL9+ovm6V98v8KjXVzsmRO5Ss2ZPkJaWyLp1zwLwww8v4enpT6tWf7ZzZCJyN5QMOYHNm18jKbt4Yr16D1O/fn/TYiFVlha5a61bP0NqagKbNr0KwJo1f8HT048mTUbYOTIRKSolQw4uJmYfv/76XwDc3Lzp2fNjDLlWTYvI3WjffjIpKfH8/PN7gJEVKx7H3b0MDRr0t+wFVNNGpERQMuTAjMYs1qz5i3n7b8eO/6RcuZp2jkrEcRgMBrp1e5fU1AT27PkMozGTZcseZcSItdSq1bXgmyPDTRXhk/641eYbYjoWQmv3RIqVFlA7sD17viA6eicAgYENaNfuRTtHJOJ4DAYDffp8QpMmIwHIzExj8eL+REXtyP+m7DMCcyRCYLpeOdj0vIgUGyVDDio5+SI//jjZfN2790xcXbVlXsQWDAYX+vefY1qPB6SnJ7NwYW9iYw/k7nzbGYH52vCUqZ+IFAslQw5q48aXSEm5CkDTpo9Rs2ZnO0ck4thcXd0ZMmQxNWuapsdSUq4xf34YcXHHcnaM3pZ7ROhOKZdh5zs2ilRE7qRkyAGdPbuVAwe+AsDLqyzdu//HzhGJOAc3Ny+GDfuWkJC2gGmE9uuvu3Ht2tlbnbJ3dhZq78caHRIpJkqGHExmZhpr1vzFfN2ly7/x9Q2yY0QizsXDw5eRI9cSFHQ/AAkJf/D1191ISoo1dfANtuyFUi6bRpFExOaUDDmYHTv+j0uXfgegSpUHaNnyKTtHJOJ8vLzKMmrUBipUqA/AlSsn+Prr7ty4ccW0fd6zvGUvZOkokojcEyVDDuTatbNs3fomYFrQ+fDDn+GimiUidlGmTCVGjdpIQEA1AC5e/I0FC3qRmn4dWj5v2YtYOookIvdEyZADWb/+OdLTrwPwwAN/JTi4hZ0jEnFuAQGhjBr1A2XKmKaqo6N/ZfHifqS3mAReFQq40wB+oaZRJBGxOSVDDuLYsZUcO7YSAF/fynTu/JadIxIRgAoV6jJq1Ea8vMoBcOZMBMvCh5PZbSaQVzX47LbO003VqLMyISoCjiwyfdWiahGrUzLkANLSks0HRgKEhX2Il1eAHSMSkdsFBTXhscfW4+HhC8Dx46v59rcVZD28xFR1+nZ+IdBvmakKdWQ4fFEDlnaGtSNMX7+ooaKMIlam4zhKOgvOLtq69S3i488BULNmVxo3HmaPSEWkAFWrtmb48FUsWNCLjIwUfvttMe7uvvQddxrD+e25/z9+s0r1ncUZk6JN7TcTJhG5Z0qGSjILzi66dOl3duz4AABXVw/69Jmpg1hFSqgaNTrxyCPLWLJkAFlZGezb9z88Pf0JC/tPzv/fFlil2ggYYPNEqN1fB7uKWIGmyUqqY8tMZxTlOrso+6/CyHCMRiNr1jxNVlYGAH/608tUqFDPDsGKiKXq1evDwIHzubk26JdfPmTr1jvW+BVapdoIiVGqQyRiJRoZKomOfwNrhufz5K2/Cg8mJXD27BYAypWrRfv2k/O5R0RKksaNh5KWlsiqVeMBiIh4HW/v8rRu/Yypg6X1hVSHSMQqNDJU0kSGw6pHwVjQjhEjNxKi2LDhBXNL796f4O7ubfv4RMQqWrQYR1jYh+brdeue4/Dhb0wXltYXUh0iEatQMlSSmNcJFO7HVLiecg2ARo2GUKdOTxsGJiK20LbtC7Rv/0r2lZEVKx7jzJkI0yJq3xDy3noPqkMkYl1KhkoSS06zBv7IhD2mZUJ4ePjSo8d028YlIjbTpcvbNGs2BjCdLbh4cX8uXDps2igB5E6I7qhDJCL3TMlQSWLB/H+WEdak3rru1GkK/v5VbRiUiNiSwWCgb99Z1K3bB4DU1AQWLOhFfKVWpu3zvnf8//v2OkQiYhVaQF2SWDD//2s6xGaZ/h0U1JQ2bZ6zcVAiYmsuLm4MGbKEefO6Eh29k8TE88yf35Mnn9yO9/gzhdYaE5F7o5GhkqSQdQKJWbA57dZ1nz6f4uKifFbEEXh4lGHEiNXm8hhxcUdYtKgv6ZlpENoJGg43fVUiJGJ1SoZKEhfXAtYJwPdpcDMXat58HKGh7YotNBGxPR+fQEaOXI+vb2UAoqJ+Zvny4eZaYiJiG0qGSpq6g/JcJ3DSoyKHs38f+vgE0q3bu3YITkRsrVy5mowYsRYPDz8Ajh37jrVrn8FozKsa9R10qKvIXdEcS0lUd5CpzH72OoEMrwqsXf1X4BIA3bq9h49PBfvGKCI2ExzcnKFDw1mwoDdZWens2fM5fn5Veeihf+V/kwXH94hI3jQyVFK5uJrXCWw/u4MrV04AUK1ae5o1e8K+sYmIzdWq1Y0BA+aaryMiXmPfvjl5d755qGuu43v+MB3rc/wb2wUq4gCUDJVwV66cYPv2qYBpx0mfPp9iMOh/NhFn0KTJCLp3f998vWrVeCIj1+XsVOChrtlWDzeddygiedKnagm3bt1zZGaaCgs9+OALVKrU2M4RiUhxatv2b7RubSqhYTRm8s03j3D+/O5bHSwp1mrMhNWPmEaQRCQXJUMl2IkT33PihOmvQH//EB566DU7RyQixc1gMNCjx4c0ajQEgPT0ZBYu7MPVq6dMHYpyWOvmiVpULZIHJUMlVFZWJhs3vmi+7tZtGh4evnaMSETsxcXFlYEDv6ZaNdNZZMnJF5k/vyfJyZeKdlhrYpRpJElEclAyVELt3z+Hixd/A6BKlQdo3HiYnSMSEXtyc/Ni2LDvqFixEQBXrkSaijJWapldrNVCRRlJEnESSoZKoPT060REvG6+Dgv7QIumRQRv73KMHLkOP78qAERH72RZ+EiyOn1o+YsUZSRJxEmUuk/YmTNnUrNmTby8vGjZsiXbthU85LtlyxZatmyJl5cXtWrV4rPPPiumSO/eL79MJzHxPAD16/enevUOdo5IREqKgIBqjBy5Dk9PfwCOH1/FmuM/YHx4CRgKOqrDAH6hpmN/RCSHUpUMLVmyhIkTJ/Lqq6+yb98+OnToQK9evTh37lye/U+fPk3v3r3p0KED+/bt45VXXuG5555j+fLlxRy55a5fj+Onn6YBYDC40LXrVDtHJCIlTVBQU4YOXYGLizsAe/fOYtuF49BncT53ZB/v03m6zjYTyYPBaFGN95KhTZs2tGjRgk8//dTc1rBhQwYMGMDUqbmThpdffpmVK1dy5MgRc9uECRM4cOAAO3bssOg9ExISCAgIID4+Hn9//3v/Jgqxfv1Edu40nU/WosV4+vadZfP3FJHS6dChhYSHjzRf9+8/h2Zl/HNXovYLNSVCqkQtTqQon9+lZmQoLS2NPXv2EBYWlqM9LCyMn3/+Oc97duzYkat/jx492L17N+np6TaL9W5dvXqKXbtmAuDm5k2nTm/YNyARKdGaNBlBt27vma9XrhzHCYMPjD8Dj26G3gtNX8edViIkUoBSczZZXFwcmZmZBAUF5WgPCgoiNjY2z3tiY2Pz7J+RkUFcXBzBwbkXEqamppKammq+TkhIsEL0ltm8+V9kZZmStLZtJ5kXSYqI5KdduxdJSIji11//i9GYydKlQxg9egtVQjvZOzSRUqPUjAzdZDAYclwbjcZcbYX1z6v9pqlTpxIQEGB+hIaG3mPElomJ2cuhQwsB8PauQLt2fy+W9xWR0s1UlPH/aNhwMHCzKGPvW0UZRaRQpSYZCgwMxNXVNdco0MWLF3ON/txUuXLlPPu7ublRoULep75PnjyZ+Ph48yMqKso630AhfvjhZfO/O3b8F15eAcXyviJS+rm4uDJo0HyqVWsP3CrKeP16nJ0jEykdSk0y5OHhQcuWLdm4cWOO9o0bN9KuXbs872nbtm2u/hs2bKBVq1a4u7vneY+npyf+/v45HrZ28uQGTp36AYCyZWvSqtUEm7+niDiWm0UZAwMbArcVZUy/bufIREq+UpMMAUyaNIn//e9/zJ49myNHjvDCCy9w7tw5JkwwJQ+TJ0/m8ccfN/efMGECZ8+eZdKkSRw5coTZs2fz5Zdf8uKLL+b3FsXOaMzKMSrUpcs7uLl52jEiESmtvL3LM3LkOnyzCyv+8ccvLF8+nKysDDtHJlKylapkaOjQoUyfPp0333yTZs2asXXrVtauXUv16tUBiImJyVFzqGbNmqxdu5aIiAiaNWvGW2+9xccff8zgwYPt9S3kcujQQmJj9wMQHNySxo2H2jcgESnVypatzsiRa/Hw8APg2LGVrF37DKWoiopIsStVdYbswZZ1hjIyUpgxowHx8WcBGDXqB2rV6mrV9xAR53Tq1A8sWNDLPCrUufPbdOz4auE3ZmWaDnNNijEd3VG1gwo1SqnkkHWGHNGuXZ+aE6HatXsoERIRq6lVqxv9+88xX2/e/E/2759b8E2R4fBFDVjaGdaOMH39ooapXcSBKRmyk5SUa2zb9nb2lYFu3abZNR4RcTxNmz6W43fLypXjOHFifd6dI8Nh5ZCclasBkqJN7UqIxIEpGbKT7duncePGFQCaNh1J5cr32zkiEXFE7dr9ndatnwUwF2U8f35Pzk5ZmaYjPMhr1UR22+aJpn4iDkjJkB0kJESzc+d0AFxdPejc+S37BiQiDsuioozR23KPCOVghMQoUz8RB6RkyA58fYPo1WsGfn5VeOCBZyhbtoa9QxIpObIyISoCjiwyfdVoxD3LryhjcvIlU4ekGMteyNJ+IqWMdpMVwpa7ydLTr5OVlYmnp59VX1ek1IoMz33ium8IdPlIB41awY0bV5g9uz1xcUcAqFq1NY8/vgmPC7tMi6UL8+hm0JlnUkrYdDfZuXPn8qxXYTQac9T4kcK5u/soERK5SQt4bc7buzyPPbbefAh0dPSvLF8+jKzgtqakk/zOeTSAX6hpm72IAypyMlSzZk0uXbqUq/3KlSvUrFnTKkGJiJPRAt5iExBQjZEj1+HpafpL+fjx1axZ9yzGztOze9yZEGVfd56uekPisIqcDOV3SnxSUhJeXl5WCUpEnIwW8BaroKCmDB26AhcX0xmNe/d+wdaYw9BvGfhWzdnZL8TUrmlKcWBulnacNGkSYNqZ8K9//QsfHx/zc5mZmezcuZNmzZpZPUARcQJawFvsatbswoABXxEePgKAiIjX8ev7P1qMP6MK1OJ0LE6G9u3bB5hGhg4dOoSHh4f5OQ8PD+6///4SdQCqiJQi2QeLWq2fWKRJk+EkJp5n40bT7+7Vq/+Mn18wdev2tnNkIsWryLvJxowZw0cffWT1nVUllS13k4lItqxM07EPSdHkvW7IYJquGXdaoxRWZjQa+f77SebaZ+7uPjzxRARVqz5Q+M06x0xKMJvuJpszZw7+/v6cOHGC77//nhs3bgDoRGQRuXsurqbt84AW8BYvU1HGD7jvvkcBU8mPhQv7cOXKiYJv1Dlm4kCKnAxduXKFrl27Uq9ePXr37k1MjGkOf9y4cfztb3+zeoAi4iTqDtICXjsxGFwYMOArqld/CIDr1y9lF2W8mPcNKoMgDqbIydDEiRNxd3fn3LlzORZRDx06lPXr8zkAUETEEnUHwfgzpuJ+vReavo47rUSoGLi5eTFs2LdUrHgfAFevnmTBgt6kpSXl7KgyCOKAipwMbdiwgWnTphESEpKjvW7dupw9e9ZqgYmIk3JxNVU5bjjc9FVTY8XGy6ssjz22Hn9/0+/3mJg9LF06mMzMtFudVAZBHFCRk6Hk5OQcI0I3xcXF4enpaZWgRETEPvz9Qxg5cj1eXmUBOHlyAytXjsVozDJ1UBkEcUBFToY6duzIvHnzzNcGg4GsrCzef/99One24GwbEREp0SpVuo/hw1fh5mYqpHvw4Hx++OEfpidVBkEckMV1hm56//336dSpE7t37yYtLY2XXnqJw4cPc+XKFX766SdbxCgiIsWsWrX2DB68iKVLB2M0ZvHzz+/j6xtM2zbPmc4xK6wMgs4xk1KkyCNDjRo14uDBg7Ru3Zru3buTnJzMoEGD2LdvH7Vr17ZFjCIiYgcNGgygd+9PzNcbNkzi0OElKoMgDqfIRRedjYouioiz27z5dbZufRMAFxc3RoxYQ+2sJNOustsXU/uFmhIh7f6TEqAon99FniY7ePBgnu0GgwEvLy+qVaumhdQiIg6kU6c3SEqKZe/eWWRlZbBkySCeeGITVXWOmTiIIo8Mubi4mE+tv3nr7afYu7u7M3ToUD7//HOHOMVeI0MiIpCVlcmyZY9y5IipoKKPTyBjxmwnMLC+nSMTyZtNj+NYsWIFdevWZdasWRw4cID9+/cza9Ys6tevz8KFC/nyyy/ZtGkT//znP+/6GxARkZLFxcWVQYMW3FalOo7583uQmHjezpGJ3Lsijwy1bt2at956ix49euRo//777/nXv/7Fr7/+yrfffsvf/vY3Tp48adVg7UEjQyIit6SkxDN37kNcuHAAgEqVGjNmzDZzXSKRksKmI0OHDh2ievXqudqrV6/OoUOHAGjWrJn5zDIREXEcXl4BjBy5jrJlawJw8eJvLFrUl/T064XfnJEGe6bDj8+avmakFXaHSLEocjLUoEED3n33XdLSbv1HnJ6ezrvvvkuDBg0AiI6OJigoyHpRiohIieHnF8yoURvw8akIwLlz2/nmm0fIzEzP/6YtL8HHPhDxAuyfYfr6sY+pXcTOiryb7JNPPqFfv36EhITQtGlTDAYDBw8eJDMzk9WrVwNw6tQpnn76aasHKyIiJUP58nV47LH1zJ3bibS0RCIj1/Ltt08waNB8DIY7/s7e8hLsfj/3ixgzb7U/9J7tgxbJx13VGUpKSmL+/PkcP34co9FIgwYNGDFiBH5+fraI0a60ZkhEJH9nzmxhwYKeZGSkANCq1dP07j3j1i7jjDTTCJCxgFPsDa7w3HVw8yiGiMVZ2KzOUHp6OvXr12f16tVMmDDhnoIUEZHSr0aNhxgyZClLlgzEaMxk9+6ZeHuXp0uXt0wdDswsOBEC0/MHZkLLiTaPVyQvRVoz5O7uTmpqao66QiIi4tzq1+/LgAFzzdfbtr3Njh0fmi6uWbir2NJ+IjZQ5AXUzz77LNOmTSMjI8MW8YiISCnUtOlj9Oz5sfl6w4a/sW/fHChr4ZmVlvYTsYEiL6DeuXMnP/74Ixs2bKBJkyaUKVMmx/Ph4eFWC05EREqPNm2eJSXlKhERrwOwatU4vAYtpqHBtfA1Q/dr043YT5GTobJlyzJ48GBbxCIiIqVcx47/4saNK+zc+RFGYxbLv32MEY0HU+vk0vxvajlJi6fFrnRqfSG0m0xEpGiMxiy+/XY0Bw9+DYC7exkebzKAkMjFOUeIDK6mREjb6sUGbHpqvYiISEEMBhf69fuS1NR4jh1bSXp6MguPrGP0qN1UOh9hWixdtrZpakwjQlIC3NXI0LJly1i6dCnnzp3LUYkaYO/evVYLriTQyJCIyN3JyEhhwYJenDkTAYCfXxWefPInypatYde4xDnY9Gyyjz/+mDFjxlCpUiX27dtH69atqVChAqdOnaJXr153HbSIiDgWNzcvhg37juDglgAkJp7n66+7k5QUa+fIRHIqcjI0c+ZMZs2axYwZM/Dw8OCll15i48aNPPfcc8THx9siRhERKaU8Pf0ZOXIdgYGmsyuvXDnB/Pk9uHHjqp0jE7mlyMnQuXPnaNeuHQDe3t4kJiYCMGrUKBYtWmTd6EREpNQrU6Yijz22gYCAagBcuHCQBQt6kpqaYOfIREyKnAxVrlyZy5cvA1C9enV++eUXAE6fPo02pomISF4CAkIZNWojZcpUAiA6+lcWLOhFWlqSnSMTuYtkqEuXLqxatQqAsWPH8sILL9C9e3eGDh3KwIEDrR6giIg4hgoV6vH44z/i7V0BgKion1m4sA9pacmF35yVCVERcGSR6WtWIeediRRBkXeTnT59mqpVq+LhYdoOuXTpUrZv306dOnXo1asXdevWtUmg9qLdZCIi1hUbu5+vvupCSopp3VDNml0YPnw17u7eed8QGQ6bnoekP261+YZAl4+g7qBiiFhKI5vuJqtTpw7Xrl0zXz/66KN8/PHHjBw5kgYNGhQ5WEtdvXqVUaNGERAQQEBAAKNGjcoRR15Gjx6NwWDI8XjwwQdtFqOIiBSucuVmjBq1EU/PAABOn97EkiUDyMhIyd05MhxWDsmZCAEkRZvaI3UElNy7IidD+Q0kJSUl4eXldc8B5WfEiBHs37+f9evXs379evbv38+oUaMKva9nz57ExMSYH2vXrrVZjCIiYpkqVVry2GPf4+HhB8DJkxtYunQImZm31a7LyjSNCJHX50522+aJmjKTe2ZxBepJkyYBYDAYeO211/Dx8TE/l5mZyc6dO2nWrJnVAwQ4cuQI69ev55dffqFNmzYAfPHFF7Rt25Zjx45Rv379fO/19PSkcuXKNolLRETuXkhIG0aOXMv8+T1JT08mMnINy5YNZciQpbi6ukP0ttwjQjkYITHK1C+0U3GFLQ7I4pGhffv2sW/fPoxGI4cOHTJf79u3j6NHj3L//fczd+5cmwS5Y8cOAgICzIkQwIMPPkhAQAA///xzgfdGRERQqVIl6tWrx/jx47l48WKB/VNTU0lISMjxEBER26hWrT0jRqzGzc20Xujo0W8JDx9JVlYGJMVY9iKW9hPJh8UjQ5s3bwZgzJgxfPTRR8W6mDg2NpZKlSrlaq9UqRKxsflXMu3VqxePPPII1atX5/Tp0/zrX/+iS5cu7NmzB09PzzzvmTp1KlOmTLFa7CIiUrAaNToxfPhKFi58mMzMVH7//RtcXd0Z0PJJy/5i9w22dYji4Iq8ZmjOnDlWS4TeeOONXAuc73zs3r0bME3P3cloNObZftPQoUPp06cPjRs3pm/fvqxbt47jx4+zZs2afO+ZPHky8fHx5kdUVNS9f6MiIlKgWrW6MWzYt7i6mnYqHzq0kJV752EsUxXI7/e8AfxCoWqHYotTHJNdT61/5plnGDZsWIF9atSowcGDB7lw4UKu5y5dukRQUJDF7xccHEz16tWJjIzMt4+np2e+o0YiImI7der05JFHlrF06SCysjI4cHAeLrW70TcpOvsP39sXUmcnSJ2ng4urHaIVR2LXZCgwMJDAwMBC+7Vt25b4+Hh+/fVXWrduDcDOnTuJj483Hw1iicuXLxMVFUVwsIZURURKovr1+zJkyBK++eZRjMZM9p38Ade6Peid8BuG5OhbHf1CTImQ6gyJFRS56KK99OrVi/Pnz/P5558D8NRTT1G9enVzNWyABg0aMHXqVAYOHEhSUhJvvPEGgwcPJjg4mDNnzvDKK69w7tw5jhw5gp+fn0Xvq6KLIlIssjKzd0/FmNbAVO3g1CMev/22hPDwERiNWQC0af0cPe4bgCE5Vj8fsUhRPr/tOjJUFAsWLOC5554jLCwMgH79+jFjxowcfY4dO0Z8fDwArq6uHDp0iHnz5nHt2jWCg4Pp3LkzS5YssTgREhEpFqqwnEvjxkPJykpnxYrHASM7f/0YF1cPund/r8C1oiJ3o9SMDNmLRoZExKZuVljOVVgw+wO/3zKnTYgA9u2bw8qVT5qv27d/hS5d3lZCJIWy6XEcIiJiJaqwXKjmzcfw8MOfm6+3b/83P/zwcr6nIYjcDSVDIiL2UpQKy06sZcun6NXrv+brn39+n5UrnzQVZhSxAiVDIiL2ogrLFmvd+hn69PmUm9OH+/fPZcmSgaSnX7dvYOIQlAyJiNiLpZWTVWEZgFatJvDII0vNhRmPH1/N11+HcePGVTtHJqWdkiEREXup2sG0a0wVli3WqNEQRo5cZz7tPirqJ+bO7UhCQnQhd4rkT8mQiIi9uLiats8DuRMiVVjOT82aXRg9OoIyZUxnVl68+BuzZ/+JuLhjdo5MSislQyIi9lR3kGn7vG/VnO1+IU6/rb4gwcEtePLJnyhbtiYA8fFnmTOnPdHRu+wcmZRGqjNUCNUZEpFioQrUdyUxMYYFC3py4cJBANzdyzB06Apq1+5u58jE3ory+a1kqBBKhkRESraUlGssXtyfs2e3AuDi4s7AgV/TuPFQO0cm9qSiiyIi4jS8vMoycuR6GjQYAEBWVjrLlw/n119nFHyjSDYlQyIiUuq5u3vzyCPf0Lz52OwWI+vWPcvmza8XrVp1ViZERcCRRaavTlz925mUmoNaRURECuLi4kbfvl9QpkwQ27f/G4CtW98kOfkCvXt/gktha7B0YK7T0siQiIg4DIPBQNeu79Cjx3Rz2549n7Ns2VAyMlLyv/Hmgbl3Ho+SFG1qjwy3TcBSIigZEhERh/Pgg88zaNACXFxMEyBHjixnwYLepKYm5O5c6IG5Rtg4ATLSbBmy2JGSIRERcUhNmoxg+PBVuLv7AHDmzGbmzu1EUtKFnB0LPTAXuHEJZoVohMhBKRkSERGHVadOTx5/fBPe3uUBiI3dx+zZf+Lq1VO3Oll6EO6NS5oyc1BKhkRExKGFhLRhzJjt+PuHAnD16klmz/4TsbEHTB2KehDu5onaZeZglAyJiIjDq1ixIU8++ROBgQ0BSEqKZe7cjpw5s8WCA3NvZ4TEKNPUmjgMJUMiIuIUAgJCGTNmGyEhDwKQmprA/Pk9OHp81W0H5lrI0qk1KRWUDImIiNPw8anAqFE/UKdOLwAyM1NZunQwexOvmA7G9Qq07IWKOrUmJZqSIXtRlVMREbvw8CjDsGHf0bTpYwAYjVmsWjWebbHHMD71B3hXLOBuA/iFmqbWxGGoArU9qMqpiIhdubq6M2DAV/j4VOKXXz4EYNOmV0hOvkCPbjMxrHo0u+fttYey1xR1ng6FVbOWUkUjQ8VNVU5FREoEg8GFsLD/0K3bNHPbzp0fseK3FWT2WQS+VXPe4BdimkrTH60ORyNDxanQKqcG05bN2v31V4eISDEwGAz86U8v4eNTkVWrxmM0ZnLo0EKSky8y5LF9eF/5zbRY2jfYNDWm380OSSNDxanQKqfasikiYg/Nm49h6NBw3Ny8ADh16gf+N7stFz0rQsPhENpJiZADUzJUnCzdiqktmyIixa5+/X6MGrURHx/TjrIrV07w5ZcPcvTot/YNTGxOyVBxsnQrprZsiojYRbVq7Rk/fheVKzcDIC0tiSVLBvL9938jIyP17l9YO4hLNIPRaMxrAYtkS0hIICAggPj4ePz9/e/txbIy4YsapsXSea4bMpgW6I07reFYERE7Sk+/znffPcnhw0vMbZUrN2PQoIVUrNiwaC+W1w5iz/LQ8nlo86p+39tIUT6/NTJUnFxcb6tyemfZd23ZFBEpKdzdfRg8eBE9evwfrq4eAMTG7mfWrBbs2vUpFo8j5LeDOPUK/Pw6fBqkXcQlgJKh4lZ3kGlrprZsioiUaAaDgQcfnMi4cTvNZ5plZKSwdu3TLFkygOTkSwW/QIE7iLOlXFZZlRJA02SFsOo02e2yMrN3l2nLpohISZeefp0NG/7O7t0zzW2+vpUZMGAetWt3z/umqAhY2tmyN/AL1RIJK9M0WWng4mraqqktmyIiJZ67uw99+nzCsGErzbvNkpJimT8/LP/F1UXZGayyKnalZEhERMRC9ev3ZcKEg9SuHWZu++WXD/nf/9pw6dLvOTsXdWewyqrYjZIhERGRIvDzC2bkyHU5FldfuHCAWbNa5lxcXbWD6dxJS6msit0oGRIRESkig8Ele3H1r1Ss2AjIY3F1jh3EBb6aac1Q1Q62DVrypWRIRETkLlWufD/jx++mVaunzW3Hjq3ks8+acvLkhuwdxMvBq0I+r6CyKiWBkiEREZF74O7uTZ8+nzB8+Ko7Flf34PvvJ5FRsw/85QK0mwJe5XPefC9lVVTV2mq0tb4QNttaLyIiDicpKZZvvx3NyZPfm9uCgu5n8OCFpuk0a5VVyauqtW+IaVpO9eqAon1+KxkqhJIhEREpCqMxi507P+aHH14mMzMNADc3L8LCPqRVqwkYDHeeQFBEN6ta5yrmmP26fZeAd0Wnr2OnZMiKlAyJiMjduHDhIMuXD8+x5b5evb706fMp/v5VC7izAOYzLv/Iv4/BFYy3TZmVqQr3PwVl6zpVcqRkyIqUDImIyN1KT7/Bxo0vsWvXDHObh4cvnTu/RevWz+Di4la0F4yKsLyqdX5KynSajU9iUDJkRUqGRETkXh0/voaVK58kOfmiuS0oqCldu06lTp1elk+dHVkEa0fcYzTZ72XP8zCLYc2TQx7H8c4779CuXTt8fHwoW7asRfcYjUbeeOMNqlSpgre3N506deLw4cO2DVREROQO9er14a9/PUKLFk+Z2y5cOMjChX343/9ac+zYKiwam7BKYcbs99k80T470G6uebpzqi8p2m6H1paaZCgtLY1HHnmEv/zlLxbf89577/Hhhx8yY8YMdu3aReXKlenevTuJiYk2jFRERCQ3b+/y9O37OWPH7iA4uIW5/fz53Sxe3I8vvmjF0aPfFZwUmata3+MibIz2OQ8tK9M0IpRr8TfYM0krNcnQlClTeOGFF2jSpIlF/Y1GI9OnT+fVV19l0KBBNG7cmK+++orr16+zcOFCG0crIiKSt5CQBxk/fhePPrqcoKD7ze0xMXtZsmQAs2a14MiRFRiNWblvzlHV+l4TIor/PLTobQUv/rZTklZqkqGiOn36NLGxsYSF3TpMz9PTk4ceeoiff/7ZjpGJiIizMxhcaNhwEH/+8z6GDv2WypWbm5+Ljd3P0qWD+Pzz5vz++/LcSVHdQab1Pr537Egz3MXi4+I+D83S5KuYk7QiLmMvPWJjYwEICgrK0R4UFMTZs2fzvS81NZXU1FTzdUJCgm0CFBERp2cwGGjQoD/16/fj+PHVbNkyhZiYPYBpTdE33wyhUqXGdOz4Lxo1GoLBkD2GUXcQ1O6fczfW9ThY/Wj2Kxe2/shgqn5d3OehWZp8FXOSZteRoTfeeAODwVDgY/fu3ff0Hneu0DcajQWu2p86dSoBAQHmR2ho6D29v4iISGEMBgP16/dl/PhdDB++mipVHjA/d/HibyxbNpRPP23Cb78tJuvmehoXVwjtBA2Hm77WH5L3iFHudzN9scd5aIWuebLPobV23VofFxdHXFxcgX1q1KiBl5eX+Xru3LlMnDiRa9euFXjfqVOnqF27Nnv37qV581vDj/3796ds2bJ89dVXed6X18hQaGiottaLiEixMRqNnDz5PVu2TOGPP37J8VxgYEM6dvwn9903FJe8kpnb6/dci4SDX+Rcp+MXakqE7LmtfuWQ7IvbUxDrbvkvytZ6u06TBQYGEhgYaJPXrlmzJpUrV2bjxo3mZCgtLY0tW7Ywbdq0fO/z9PTE09PTJjGJiIhYwmAwUKdOT2rX7sGpUxvZsmUKUVGm9a5xcUcIDx/Jli1v0rHjP2nceFjO4o03R4xuavOqTYsbFtnNNU931hnyC7FbklZqii6eO3eOK1eusHLlSt5//322bTOtNK9Tpw6+vr4ANGjQgKlTpzJw4EAApk2bxtSpU5kzZw5169bl3//+NxERERw7dgw/Pz+L3ldFF0VExN6MRiOnT//Ili1TOHdue47nypWrTbNmY2jadCRly9awT4B3QxWoi2706NF5Tm1t3ryZTp06AaZMes6cOYwePRow/cczZcoUPv/8c65evUqbNm345JNPaNy4scXvq2RIRERKCqPRyJkzEWzZMoWzZ7fker5atQ40bfoYjRo9grd3OTtEWHI4ZDJkL0qGRESkJDpzZgvbtr3NqVM/5HrO1dWD2rXDqFv3YerV64O/f4gdIrQvJUNWpGRIRERKsmvXznLo0EIOHvyauLgjefapXLkZNWp0wcPDF4PBBYPBBRcXV/O/DYbb/53/c9a85/Z2V1dPKlSoa9Wfi5IhK1IyJCIipYHRaCQ2dj8HD87n8OHFJCaet3dIFgsIqM7EiWes+pqlZjeZiIiIWIfBYCA4uDnBwc0JC3ufmJh9HD++msjI1Zw/f281+2zNXEzSTpQMiYiIOBiDwYUqVVpSpUpLOnV6ncTEGC5d+h2jMZOsrEyMxqzsx61/52wv6Lmc/azxet7eFez681IyJCIi4uD8/ILx8yvmc8hKEYc9qFVERETEEkqGRERExKkpGRIRERGnpmRIREREnJqSIREREXFqSoZERETEqSkZEhEREaemZEhEREScmpIhERERcWpKhkRERMSpKRkSERERp6ZkSERERJyakiERERFxakqGRERExKkpGRIRERGnpmRIREREnJqSIREREXFqSoZERETEqSkZEhEREaemZEhEREScmpIhERERcWpKhkRERMSpKRkSERERp6ZkSERERJyam70DEBGREi4rE6K3QVIM+AZD1Q7g4mrvqESsRsmQiIjkLzIcNj0PSX/cavMNgS4fQd1B9otLxIo0TSYiInmLDIeVQ3ImQgBJ0ab2yHD7xCViZUqGREQkt6xM04gQxjyezG7bPNHUT6SUUzIkIiK5RW/LPSKUgxESo0z9REo5JUMiIpJbUox1+4mUYEqGREQkN99g6/YTKcGUDImISG5VO5h2jWHIp4MB/EJN/URKOSVDIiKSm4urafs8kDshyr7uPF31hsQhKBkSEZG81R0E/ZaBb9Wc7X4hpnbVGRIHoaKLIiKSv7qDoHZ/VaAWh6ZkSERECubiCqGd7B2FiM1omkxEREScmpIhERERcWqlJhl65513aNeuHT4+PpQtW9aie0aPHo3BYMjxePDBB20bqIiIiJQqpSYZSktL45FHHuEvf/lLke7r2bMnMTEx5sfatWttFKGIiIiURqVmAfWUKVMAmDt3bpHu8/T0pHLlyjaISERERBxBqRkZulsRERFUqlSJevXqMX78eC5evFhg/9TUVBISEnI8RERExHE5dDLUq1cvFixYwKZNm/jggw/YtWsXXbp0ITU1Nd97pk6dSkBAgPkRGhpajBGLiIhIcbNrMvTGG2/kWuB852P37t13/fpDhw6lT58+NG7cmL59+7Ju3TqOHz/OmjVr8r1n8uTJxMfHmx9RUVF3/f4iIiJS8tl1zdAzzzzDsGHDCuxTo0YNq71fcHAw1atXJzIyMt8+np6eeHp6Wu09RUREpGSzazIUGBhIYGBgsb3f5cuXiYqKIjg4uNjeU0REREq2UrNm6Ny5c+zfv59z586RmZnJ/v372b9/P0lJSeY+DRo0YMWKFQAkJSXx4osvsmPHDs6cOUNERAR9+/YlMDCQgQMH2uvbEBERkRKm1Gytf+211/jqq6/M182bNwdg8+bNdOrUCYBjx44RHx8PgKurK4cOHWLevHlcu3aN4OBgOnfuzJIlS/Dz8yv2+EVERKRkMhiNRqO9gyjJEhISCAgIID4+Hn9/f3uHIyIiIhYoyud3qZkmExEREbEFJUMiIiLi1JQMiYiIiFNTMiQiIiJOTcmQiIiIODUlQyIiIuLUlAyJiIiIU1MyJCIiIk5NyZCIiIg4NSVDIiIi4tSUDImIiIhTUzIkIiIiTk3JkIiIiDg1JUMiIiLi1JQMiYiIiFNTMiQiIiJOTcmQiIiIODUlQyIiIuLUlAyJiIiIU1MyJCIiIk5NyZCIiIg4NSVDIiIi4tSUDImIiIhTUzIkIiIiTk3JkIiIiDg1JUMiIiLi1JQMiYiIiFNTMiQiIiJOzc3eAYiIiDiVrEyI3gZJMeAbDFU7gIurvaNyakqGREREiktkOGx6HpL+uNXmGwJdPoK6g+wXl5PTNJmIiEhxiAyHlUNyJkIASdGm9shw+8QlSoZERERsLivTNCKEMY8ns9s2TzT1k2KnZEhERMTWorflHhHKwQiJUaZ+UuyUDImIiNhaUox1+4lVKRkSERGxNd9g6/YTq1IyJCIiYmtVO5h2jWHIp4MB/EJN/aTYKRkSERGxNRdX0/Z5IHdClH3debrqDdmJkiEREZHiUHcQ9FsGvlVztvuFmNpVZ8huVHRRRESkuNQdBLX7qwJ1CaNkSEREpDi5uEJoJ3tHIbfRNJmIiIg4NSVDIiIi4tRKRTJ05swZxo4dS82aNfH29qZ27dq8/vrrpKWlFXif0WjkjTfeoEqVKnh7e9OpUycOHz5cTFGLiIhIaVAqkqGjR4+SlZXF559/zuHDh/m///s/PvvsM1555ZUC73vvvff48MMPmTFjBrt27aJy5cp0796dxMTEYopcRERESjqD0WjM69S4Eu/999/n008/5dSpU3k+bzQaqVKlChMnTuTll18GIDU1laCgIKZNm8af//xni94nISGBgIAA4uPj8ff3t1r8IiIiYjtF+fwuFSNDeYmPj6d8+fL5Pn/69GliY2MJCwszt3l6evLQQw/x888/F0eIIiIiUgqUyq31J0+e5L///S8ffPBBvn1iY2MBCAoKytEeFBTE2bNn870vNTWV1NRU83VCQsI9RisiIiIlmV1Hht544w0MBkOBj927d+e45/z58/Ts2ZNHHnmEcePGFfoeBkPOsudGozFX2+2mTp1KQECA+REaGnp335yIiIiUCnZdMxQXF0dcXFyBfWrUqIGXlxdgSoQ6d+5MmzZtmDt3Li4u+edyp06donbt2uzdu5fmzZub2/v370/ZsmX56quv8rwvr5Gh0NBQrRkSEREpRYqyZsiu02SBgYEEBgZa1Dc6OprOnTvTsmVL5syZU2AiBFCzZk0qV67Mxo0bzclQWloaW7ZsYdq0afne5+npiaenp/n6Zq6o6TIREZHS4+bntkVjPsZSIDo62linTh1jly5djH/88YcxJibG/Lhd/fr1jeHh4ebrd9991xgQEGAMDw83Hjp0yDh8+HBjcHCwMSEhweL3joqKMgJ66KGHHnrooUcpfERFRRX6WV8qFlBv2LCBEydOcOLECUJCQnI8Z7wt4zt27Bjx8fHm65deeokbN27w9NNPc/XqVdq0acOGDRvw8/Oz+L2rVKlCVFQUfn5+Ba41ys/NabaoqChNsxUT/cyLn37m9qGfe/HTz7z43e3P3Gg0kpiYSJUqVQrtW2rrDJUWqlNU/PQzL376mduHfu7FTz/z4lccP/NSW2dIRERExBqUDImIiIhTUzJkY56enrz++us5dqiJbelnXvz0M7cP/dyLn37mxa84fuZaMyQiIiJOTSNDIiIi4tSUDImIiIhTUzIkIiIiTk3JkIiIiDg1JUM2NHPmTGrWrImXlxctW7Zk27Zt9g7JoW3dupW+fftSpUoVDAYD3377rb1DcnhTp07lgQcewM/Pj0qVKjFgwACOHTtm77Ac2qeffkrTpk3x9/fH39+ftm3bsm7dOnuH5VSmTp2KwWBg4sSJ9g7Fob3xxhsYDIYcj8qVK9vkvZQM2ciSJUuYOHEir776Kvv27aNDhw706tWLc+fO2Ts0h5WcnMz999/PjBkz7B2K09iyZQt//etf+eWXX9i4cSMZGRmEhYWRnJxs79AcVkhICO+++y67d+9m9+7ddOnShf79+3P48GF7h+YUdu3axaxZs2jatKm9Q3EK9913HzExMebHoUOHbPI+2lpvI23atKFFixZ8+umn5raGDRsyYMAApk6dasfInIPBYGDFihUMGDDA3qE4lUuXLlGpUiW2bNlCx44d7R2O0yhfvjzvv/8+Y8eOtXcoDi0pKYkWLVowc+ZM3n77bZo1a8b06dPtHZbDeuONN/j222/Zv3+/zd9LI0M2kJaWxp49ewgLC8vRHhYWxs8//2ynqERs7+ZByeXLl7dzJM4hMzOTxYsXk5ycTNu2be0djsP761//Sp8+fejWrZu9Q3EakZGRVKlShZo1azJs2DBOnTplk/cpFafWlzZxcXFkZmYSFBSUoz0oKIjY2Fg7RSViW0ajkUmTJtG+fXsaN25s73Ac2qFDh2jbti0pKSn4+vqyYsUKGjVqZO+wHNrixYvZu3cvu3btsncoTqNNmzbMmzePevXqceHCBd5++23atWvH4cOHqVChglXfS8mQDRkMhhzXRqMxV5uIo3jmmWc4ePAg27dvt3coDq9+/frs37+fa9eusXz5cp544gm2bNmihMhGoqKieP7559mwYQNeXl72Dsdp9OrVy/zvJk2a0LZtW2rXrs1XX33FpEmTrPpeSoZsIDAwEFdX11yjQBcvXsw1WiTiCJ599llWrlzJ1q1bCQkJsXc4Ds/Dw4M6deoA0KpVK3bt2sVHH33E559/bufIHNOePXu4ePEiLVu2NLdlZmaydetWZsyYQWpqKq6urnaM0DmUKVOGJk2aEBkZafXX1pohG/Dw8KBly5Zs3LgxR/vGjRtp166dnaISsT6j0cgzzzxDeHg4mzZtombNmvYOySkZjUZSU1PtHYbD6tq1K4cOHWL//v3mR6tWrRg5ciT79+9XIlRMUlNTOXLkCMHBwVZ/bY0M2cikSZMYNWoUrVq1om3btsyaNYtz584xYcIEe4fmsJKSkjhx4oT5+vTp0+zfv5/y5ctTrVo1O0bmuP7617+ycOFCvvvuO/z8/MyjoQEBAXh7e9s5Osf0yiuv0KtXL0JDQ0lMTGTx4sVERESwfv16e4fmsPz8/HKtgytTpgwVKlTQ+jgbevHFF+nbty/VqlXj4sWLvP322yQkJPDEE09Y/b2UDNnI0KFDuXz5Mm+++SYxMTE0btyYtWvXUr16dXuH5rB2795N586dzdc355SfeOIJ5s6da6eoHNvN0hGdOnXK0T5nzhxGjx5d/AE5gQsXLjBq1ChiYmIICAigadOmrF+/nu7du9s7NBGr+uOPPxg+fDhxcXFUrFiRBx98kF9++cUmn6OqMyQiIiJOTWuGRERExKkpGRIRERGnpmRIREREnJqSIREREXFqSoZERETEqSkZEhEREaemZEhEREScmpIhEXFYnTp1YuLEifYOQ0RKOCVDIiJAREQEBoOBa9eu2TsUESlmSoZERETEqSkZEhGHkJyczOOPP46vry/BwcF88MEHOZ6fP38+rVq1ws/Pj8qVKzNixAguXrwIwJkzZ8zn2pUrVw6DwWA+W239+vW0b9+esmXLUqFCBR5++GFOnjxZrN+biNiWkiERcQh///vf2bx5MytWrGDDhg1ERESwZ88e8/NpaWm89dZbHDhwgG+//ZbTp0+bE57Q0FCWL18OwLFjx4iJieGjjz4CTEnWpEmT2LVrFz/++CMuLi4MHDiQrKysYv8eRcQ2dFCriJR6SUlJVKhQgXnz5jF06FAArly5QkhICE899RTTp0/Pdc+uXbto3bo1iYmJ+Pr6EhERQefOnbl69Sply5bN970uXbpEpUqVOHToEI0bN7bRdyQixUkjQyJS6p08eZK0tDTatm1rbitfvjz169c3X+/bt4/+/ftTvXp1/Pz86NSpEwDnzp0r9LVHjBhBrVq18Pf3p2bNmhbdJyKlh5IhESn1ChvgTk5OJiwsDF9fX+bPn8+uXbtYsWIFYJo+K0jfvn25fPkyX3zxBTt37mTnzp0W3ScipYeSIREp9erUqYO7uzu//PKLue3q1ascP34cgKNHjxIXF8e7775Lhw4daNCggXnx9E0eHh4AZGZmmtsuX77MkSNH+Oc//0nXrl1p2LAhV69eLYbvSESKk5IhESn1fH19GTt2LH//+9/58ccf+e233xg9ejQuLqZfcdWqVcPDw4P//ve/nDp1ipUrV/LWW2/leI3q1atjMBhYvXo1ly5dIikpiXLlylGhQgVmzZrFiRMn2LRpE5MmTbLHtygiNqRkSEQcwvvvv0/Hjh3p168f3bp1o3379rRs2RKAihUrMnfuXL755hsaNWrEu+++y3/+858c91etWpUpU6bwj3/8g6CgIJ555hlcXFxYvHgxe/bsoXHjxrzwwgu8//779vj2RMSGtJtMREREnJpGhkRERMSpKRkSERERp6ZkSERERJyakiERERFxakqGRERExKkpGRIRERGnpmRIREREnJqSIREREXFqSoZERETEqSkZEhEREaemZEhEREScmpIhERERcWr/Dx1x0iMgLg5GAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot \n",
    "plt.scatter(X, t, color = 'darkorange', label = 'data')\n",
    "plt.plot(X, y, color = \"olive\", lw = 2, label = name)\n",
    "plt.title(\"RBF SVR\")\n",
    "plt.xlabel('data')\n",
    "plt.ylabel('target')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Clustering with k-Means\n",
    "\n",
    "[Clustering in sklearn](https://scikit-learn.org/stable/modules/clustering.html)\n",
    "\n",
    "[Mini Batch K-Means documentation](https://scikit-learn.org/stable/modules/clustering.html#mini-batch-kmeans)\n",
    "\n",
    "[MiniBatchKMeans API](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.MiniBatchKMeans.html#sklearn.cluster.MiniBatchKMeans)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Toy dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import cluster, datasets, mixture\n",
    "from sklearn.neighbors import kneighbors_graph\n",
    "from itertools import cycle, islice\n",
    "\n",
    "np.random.seed(0)\n",
    "\n",
    "# ============\n",
    "# Generate datasets. We choose the size big enough to see the scalability\n",
    "# of the algorithms, but not too big to avoid too long running times\n",
    "# ============\n",
    "n_samples = 1500\n",
    "X, y = datasets.make_moons(n_samples = n_samples, noise = .05)\n",
    "\n",
    "# normalize dataset for easier parameter selection\n",
    "X = StandardScaler().fit_transform(X)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train & Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 6 µs, sys: 3 µs, total: 9 µs\n",
      "Wall time: 16.9 µs\n"
     ]
    }
   ],
   "source": [
    "# Create cluster objects.\n",
    "kmeans = cluster.MiniBatchKMeans(n_clusters = 2, n_init='auto')\n",
    "\n",
    "%time        \n",
    "kmeans.fit(X)\n",
    "\n",
    "if hasattr(kmeans, 'labels_'):\n",
    "    y_pred = kmeans.labels_.astype(int)\n",
    "else:\n",
    "    y_pred = kmeans.predict(X)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot samples and clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([], [])"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title('MiniBatchKMeans', size=18)\n",
    "\n",
    "colors = np.array(list(islice(cycle(['#377eb8', '#ff7f00', '#4daf4a',\n",
    "                                     '#f781bf', '#a65628', '#984ea3',\n",
    "                                     '#999999', '#e41a1c', '#dede00']),\n",
    "                              int(max(y_pred) + 1))))\n",
    "# add black color for outliers (if any)\n",
    "colors = np.append(colors, [\"#000000\"])\n",
    "plt.scatter(X[:, 0], X[:, 1], s=10, color=colors[y_pred])\n",
    "\n",
    "plt.xlim(-2.5, 2.5)\n",
    "plt.ylim(-2.5, 2.5)\n",
    "plt.xticks(())\n",
    "plt.yticks(())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Clustering with SpectralClustering\n",
    "\n",
    "[Spectral clustering documentation](https://scikit-learn.org/stable/modules/clustering.html#spectral-clustering)\n",
    "\n",
    "[SpectralClustering API](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.SpectralClustering.html#sklearn.cluster.SpectralClustering)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Train & Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 4 µs, sys: 1 µs, total: 5 µs\n",
      "Wall time: 10 µs\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/rbunescu/anaconda3/lib/python3.10/site-packages/sklearn/manifold/_spectral_embedding.py:274: UserWarning: Graph is not fully connected, spectral embedding may not work as expected.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "from sklearn.cluster import SpectralClustering\n",
    "\n",
    "sc = SpectralClustering(n_clusters = 2, assign_labels = 'discretize', \n",
    "                        affinity=\"nearest_neighbors\", random_state = 0)\n",
    "\n",
    "%time\n",
    "\n",
    "sc.fit(X)\n",
    "\n",
    "y_pred = sc.labels_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot samples and clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([], [])"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title('SpectralClustering', size=18)\n",
    "\n",
    "colors = np.array(list(islice(cycle(['#377eb8', '#ff7f00', '#4daf4a',\n",
    "                                     '#f781bf', '#a65628', '#984ea3',\n",
    "                                     '#999999', '#e41a1c', '#dede00']),\n",
    "                              int(max(y_pred) + 1))))\n",
    "# add black color for outliers (if any)\n",
    "colors = np.append(colors, [\"#000000\"])\n",
    "plt.scatter(X[:, 0], X[:, 1], s=10, color=colors[y_pred])\n",
    "\n",
    "plt.xlim(-2.5, 2.5)\n",
    "plt.ylim(-2.5, 2.5)\n",
    "plt.xticks(())\n",
    "plt.yticks(())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reinforcement Learning\n",
    "\n",
    "You need to install OpenAI Gymnasium for this exercise by running `pip install gymnasium` on terminal. \n",
    "Please check [this link](https://github.com/Farama-Foundation/Gymnasium) to directly access to the GitHub repo. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Environment: MountainCar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# https://gymnasium.farama.org/\n",
    "import gymnasium as gym\n",
    "\n",
    "ACTIONS = ['<-', '  ', '->']\n",
    "\n",
    "def show_state(env, step=0, a=0):\n",
    "    plt.figure(3)\n",
    "    plt.clf()\n",
    "    plt.imshow(env.render())\n",
    "    plt.title(\"%s [Step: %d]\" % (ACTIONS[a], step))\n",
    "    plt.axis('off')\n",
    "\n",
    "    display.clear_output(wait=True)\n",
    "    display.display(plt.gcf())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import time \n",
    "\n",
    "env = gym.make('MountainCar-v0', render_mode=\"rgb_array\")\n",
    "\n",
    "# Number of steps you run the agent for \n",
    "num_steps = 100\n",
    "\n",
    "obs = env.reset()\n",
    "\n",
    "for step in range(num_steps):\n",
    "    # take random action, but you can also do something more intelligent\n",
    "    # action = my_intelligent_agent_fn(obs) \n",
    "    action = env.action_space.sample()\n",
    "    \n",
    "    # apply the action\n",
    "    obs, reward, done, trunc, info = env.step(action)\n",
    "    \n",
    "    # Render the env\n",
    "    show_state(env, step, action)\n",
    "\n",
    "    # Wait a bit before the next frame unless you want to see a crazy fast video\n",
    "    time.sleep(0.001)\n",
    "    \n",
    "    # If the epsiode is up, then start another one\n",
    "    if done:\n",
    "        env.reset()\n",
    "\n",
    "# Close the env\n",
    "env.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Box([-1.2  -0.07], [0.6  0.07], (2,), float32)"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "env.observation_space"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "env.action_space.n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "DISCRETE_OBSERVATION_SPACE_SIZE = [\n",
    "    20] * len(env.observation_space.high)  # will give out 20*20 list\n",
    "\n",
    "# see how big is the range for each of the 20 different buckets\n",
    "discrete_os_win_size = (env.observation_space.high -\n",
    "                        env.observation_space.low) / DISCRETE_OBSERVATION_SPACE_SIZE\n",
    "\n",
    "LEARNING_RATE = 0.1\n",
    "DISCOUNT = 0.95  # how important we find the new future actions are ; future reward over current reward\n",
    "EPISODES = 500\n",
    "\n",
    "# even though the solution might have been found, we still wish to look for other solutions\n",
    "epsilon = 0.5  # 0-1 ; higher it is, more likely for it to perform something random action\n",
    "START_EPSILON_DECAYING = 1\n",
    "# python2 style division - gives only int values\n",
    "END_EPSILON_DECAYING = EPISODES // 2\n",
    "epsilon_decay_value = epsilon / (END_EPSILON_DECAYING - START_EPSILON_DECAYING)\n",
    "\n",
    "# Q learning\n",
    "# so we will have now a table such that each row will have 400 (20*20) rows for the possible state the agent can be in\n",
    "# and 3 columns for the 3 possible actions\n",
    "# the agent will see which state it is in and take the action corresponding to the largest Q value\n",
    "\n",
    "# Create a randomised q_table and agent will update it after exploring the environment\n",
    "q_table = np.random.uniform(\n",
    "    low=-2, high=0, size=(DISCRETE_OBSERVATION_SPACE_SIZE + [env.action_space.n]))\n",
    "\n",
    "# how to set low and high limits of rewards ? - if you see the rewards printed in below cell, they are mostly -1 and\n",
    "# might be something +ve only when you reach goal. Needs tweaking and playing around\n",
    "# print(q_table.shape)\n",
    "\n",
    "\n",
    "def get_discrete_state(state):\n",
    "    if isinstance(state, tuple):\n",
    "        state = state[0]\n",
    "    discrete_state = (state - env.observation_space.low) / discrete_os_win_size\n",
    "    return tuple(discrete_state.astype(np.int))  # return as tuple\n",
    "\n",
    "\n",
    "epsilon_log = []\n",
    "reward_log = []\n",
    "\n",
    "for ep in range(EPISODES):\n",
    "    done = False\n",
    "    discrete_state = get_discrete_state(env.reset())  # initial discrete state\n",
    "\n",
    "    sum_reward = 0\n",
    "    while not done:  # goal reached means reward = 0\n",
    "\n",
    "        if np.random.random() > epsilon:\n",
    "            # in this environment, 0 means push the car left, 1 means to do nothing, 2 means to push it right\n",
    "            action = np.argmax(q_table[discrete_state])\n",
    "        else:\n",
    "            action = np.random.randint(0, env.action_space.n)\n",
    "\n",
    "        # Run one timestep of the environment's dynamics;  returns a tuple (observation, reward, done, info).\n",
    "        new_state, reward, done, _, _ = env.step(action)\n",
    "        sum_reward += reward\n",
    "\n",
    "        new_discrete_state = get_discrete_state(new_state)\n",
    "\n",
    "        if not done:\n",
    "            # max q value for the next state calculated above\n",
    "            max_future_q = np.max(q_table[new_discrete_state])\n",
    "\n",
    "            # q value for the current action and state\n",
    "            current_q = q_table[discrete_state + (action, )]\n",
    "\n",
    "            new_q = (1 - LEARNING_RATE) * current_q + \\\n",
    "                LEARNING_RATE * (reward + DISCOUNT * max_future_q)\n",
    "\n",
    "            # based on the new q, we update the current Q value\n",
    "            q_table[discrete_state + (action, )] = new_q\n",
    "\n",
    "        # goal reached; reward = 0 and no more negative\n",
    "        elif new_state[0] >= env.goal_position:\n",
    "            # its like a snowbal effect, once the goal is reached - it will most likely reach again soon enough\n",
    "            q_table[discrete_state + (action, )] = 0\n",
    "\n",
    "        discrete_state = new_discrete_state\n",
    "\n",
    "    if END_EPSILON_DECAYING >= ep >= START_EPSILON_DECAYING:\n",
    "        epsilon -= epsilon_decay_value\n",
    "    epsilon_log.append(epsilon)\n",
    "        \n",
    "    reward_log.append(sum_reward)\n",
    "\n",
    "env.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'epsilon')"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14,6))\n",
    "plt.subplot(1,2,1)\n",
    "plt.plot(reward_log)\n",
    "plt.ylabel(\"Sum of Rewards\")\n",
    "\n",
    "plt.subplot(1,2,2)\n",
    "plt.plot(epsilon_log)\n",
    "plt.ylabel(\"epsilon\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Number of steps you run the agent for \n",
    "num_steps = 1000\n",
    "\n",
    "obs = env.reset()\n",
    "\n",
    "for step in range(num_steps):\n",
    "    # take random action, but you can also do something more intelligent\n",
    "    # action = my_intelligent_agent_fn(obs) \n",
    "    #action = env.action_space.sample()\n",
    "    #>>>>>>>>>\n",
    "    discrete_state = get_discrete_state(obs)\n",
    "    action = np.argmax(q_table[discrete_state])\n",
    "    \n",
    "    # apply the action\n",
    "    obs, reward, done, trunc, info = env.step(action)\n",
    "    \n",
    "    # Render the env\n",
    "    show_state(env, step, action)\n",
    "\n",
    "    # Wait a bit before the next frame unless you want to see a crazy fast video\n",
    "    #time.sleep(0.00001)\n",
    "    \n",
    "    # If the epsiode is up, then start another one\n",
    "    if done:\n",
    "        env.reset()\n",
    "        break\n",
    "\n",
    "# Close the env\n",
    "env.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "celltoolbar": "Create Assignment",
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "375.75px"
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   "toc_window_display": true
  }
 },
 "nbformat": 4,
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}