diff --git a/examples/example_dataset_experiment_1.ipynb b/examples/example_dataset_experiment_1.ipynb new file mode 100644 index 0000000..0c72e1e --- /dev/null +++ b/examples/example_dataset_experiment_1.ipynb @@ -0,0 +1,390 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "example_dataset_experiment_1.ipynb", + "provenance": [], + "authorship_tag": "ABX9TyOsvPHK+8Jh4xDDu7XEdFN0", + "include_colab_link": true + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "view-in-github", + "colab_type": "text" + }, + "source": [ + "\"Open" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "ykWyVebmAm7E", + "outputId": "0f83dacc-5f87-44c3-dd94-5ef7a83304b3", + "colab": { + "base_uri": "https://localhost:8080/" + } + }, + "source": [ + "!pip install git+https://github.com/deebuls/deep_evidential_regression_loss_pytorch -q" + ], + "execution_count": 1, + "outputs": [ + { + "output_type": "stream", + "text": [ + " Building wheel for deep-evidential-regression-loss-pytorch (setup.py) ... \u001b[?25l\u001b[?25hdone\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "2PeUi7VQAwgV", + "outputId": "31beb618-33f4-4379-db2d-9f5d8d34ddaf", + "colab": { + "base_uri": "https://localhost:8080/" + } + }, + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "\n", + "import torch\n", + "from torch.autograd import Variable\n", + "import torch.nn.functional as F\n", + "import torch.utils.data as Data\n", + "\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "\n", + "\n", + "torch.manual_seed(1) # reproducible" + ], + "execution_count": 2, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 2 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "t-VcX5G2Bbbd" + }, + "source": [ + "## import loss function" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "VkFuMSx9Bdb0" + }, + "source": [ + "from deep_evidential_regression_loss_pytorch import EvidentialLossSumOfSquares" + ], + "execution_count": 8, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "SqfGKFgHA4Da" + }, + "source": [ + "## Create Dataset \n", + "\n", + "Paper experiment 1" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "SVS4u_zyAzhS", + "outputId": "1d916c23-c701-4a0a-d4e5-08c42054c23a", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 490 + } + }, + "source": [ + "#hide_input\n", + "x_lim=[-10,10]; y_lim=[-1.25, 2.25]\n", + "x = torch.unsqueeze(torch.linspace(-3, 3, 100), dim=1) # x data (tensor), shape=(100, 1)\n", + "test_x = torch.unsqueeze(torch.linspace(-10, 10, 200), dim=1) # x data (tensor), shape=(100, 1)\n", + "y = torch.sin( 3 * x) / (3 * x )+ torch.normal(0, 0.02,size=x.size()) # noisy y data (tensor), shape=(100, 1)\n", + "test_y = (torch.sin( 3 * test_x) / (3 * test_x )) + torch.normal(0, 0.02,size=test_x.size()) # noisy y data (tensor), shape=(100, 1)\n", + "fig, ax = plt.subplots(figsize=(12,7))\n", + "plt.cla()\n", + "ax.set_title('Dataset', fontsize=35)\n", + "ax.set_xlabel('Independent variable', fontsize=24)\n", + "ax.set_ylabel('Dependent variable', fontsize=24)\n", + "ax.plot(x,y, linewidth=3, label='training data')\n", + "ax.plot(test_x, test_y, color='red', alpha=0.5, label='testing data')\n", + "ax.legend( )\n", + "ax.axvspan(x_lim[0], -3.5, alpha=0.1, color='red')\n", + "ax.axvspan(3.5, x_lim[1], alpha=0.1, color='red')\n", + "# torch can only train on Variable, so convert them to Variable\n", + "x, y = Variable(x), Variable(y)\n", + "test_x, test_y = Variable(test_x), Variable(test_y)" + ], + "execution_count": 4, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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a2jj55JPZtGkTmUxm1B7lEx1XLJW1iIiIiEjZ1EUiQ4/vuvtu/nTHHfzlnnt4bO1aVq1cOWIf8GAwOPS4tqZm1Hr1wXG1tbXkSnQq6tlnn81ZZ53F3//+dy6//PJR+5RPdFyxtHIuIiJTk0pBIAA1Wu8RqSajlZ6UUzQapS8WG/X1np4empuaiEQiPP300zzw4IMlj+HQQw7h2l//ms+dcw633nYbXV1dO41Zc9BBfPKcc+jo6KBh3jyuu+469suv1Pf09LDbbrsBcPXVVw+9JxqN0tvbu8O/ZaRxUzUjv5Oa2ZVmttXM/jHK62ZmF5vZOjN73Mz2n+4YRURmhYEB+O534b77Kh2JiFSBuXPncughh7Bi1SrOPe+8nV4/5uijyeVy7PP613Pe+edz8Jo1JY/hS+efz6233caKVau47vrrWbBgAdFodIcxCxcu5MLzz+eQI47g0EMPZZ999hl67cILL+Rd73oXBxxwAC0tLUPXjz/+eG644YahDaGjjZsqc86VbLLpYmaHAzHgx865FSO8fhxwNnAcsAb4jnNuzP/6q1evdmvXri1HuON79lmor6/MvUWqVSwGe+9d6ShkPO3tpL71HX60Ae485DguOXV/WqPB8d8n008/a2aFpzo72WeWf+9Mp9PU1tbi8/n4ywMP8NGzzx7aoLqTgQEIhcoaz1NPPbVD8g9gZo8451aPNH5GlrU45+4xs2VjDDkRL3F3wANm1mRmC51zm6YlQBGR2WLLFh5v66FvfQ8Pz2/npw+8xKffOrsTAxGprJdffpl3v/e9DAwMEAgE+MGll1Y6pKLMyOR8AnYDXil43pa/tkNybmZnAGcALF26dNqCExGZ6X77tw3c91w7n6x5hW19aQL9WeYmeli3dfRaUxGR6bDXXnvx14ceqnQYk7arJucT4pz7PvB98MpaKhyOiMiMsL49zqd/+TcGHCxuf4S6tPftc0FfB+s74hWOTkRkZpuRG0InYAOwpOD54vw1ERGZoj89tYWB/HJG3/oN/C3YQtIfZGFfOy91JJiJe5lERKrFrpqc3wh8IN+15WCgR/XmIiKlceczWwEI5jLUp2JsjjSxKdrCgr52YukcHfFMhSMUEZm5ZmRZi5n9HDgCaDGzNuBLgB/AOXcZcDNep5Z1QAL4YGUiFRHZtcTSOR56sROAlng3AO2RJmqcY3nnRoK5DC91xGmpV8cWEZHJmJEr5865U5xzC51zfufcYufcD51zl+UTc5zn4865PZxz+zrnKtQjUURk13Lfc+1k+72ylZa4d7BHe10zm+vnYjjmxTpZ356oZIgiUkHd3d1877LLJv3+b198MYnE9u8hx51wAt3d3aUIbQenfeQj/Or668ccc9VVV7Fx48aS33s8MzI5FxGRyrjz6a1Dj1sS3aR8QWKBMFuic3FYvu5cm0JFZqvu7m6+d/nlk37/t7/73R2S85tvvJGmpqZShFY0JeciIlLV+gfcUL05eGUt2+qawYy0L0BnpIEFfe2s79DKuchsdd755/P8Cy+w8sADh04I/d9vfIMD3/AGXn/AAXzpoosAiMfj/POJJ7Lf6tWsWLWKX153HRd/97ts3LiRI486iiOPOgqAZXvvTXt7O+vXr2ef17+e0z/6UV63ciVHHXccyWQSgIfXruX1BxwwdM8Vq1btFJdzjrM++UlevWIFbznmGLZu3f697KKLLuLAAw9kxYoVnHHGGTjn+NWvfsXatWt573vfy8qVK0kmkyOOK4cZWXMuIiLTzDn+dt0fSLTHIRhhbtjHCl+KP4UXDw3ZHG1h9842HmhXr3ORqnDLLbBlS2nnnD8fjj561Je/9pWv8I8nnhg6kfPW227juXXreOj++3HOccI73sE9997LtvZ2Fi1axE2//S0APT09NDY28s2LL+bOW2+lpaVlp7mfW7eOn//kJ/zg0kt596mn8usbbuB9p57KB08/nR9ceimHHHww5/2//zdiXDf89rc88+yzPPnYY2zZsoXXrlzJh047DYCzzjqLCy64AID3v//9/P73v+ekk07iu9/9Ll//+tdZvXr1qOOOP/74yX0dx6CVcxERGV9bGxt/8RvevO5BAN67d5Ql9T7a67w/NzeEfGyKthDOpulsK3EyICIz1q1/+hO33n47qw46iP3XrOHpZ57huXXr2Pd1r+O222/nc1/4Avfedx+NjY3jzrV82TJW7rcfAAfsvz/rX3qJ7u5u+mIxDjn4YABOfc97RnzvPffeyyknn0xtbS2LFi3iTUccMfTanXfeyZo1a9h333254447eOKJJ0acY6Ljpkor5yIiMq6uRx7nhfY4y12MZZ0bOGnJfJKNYbbVesn5G/dq4fEeb6Ur0r6F7kSGpkigkiGLyBgr3NPFOcfnzz2Xfzv99J1ee/SBB7j5j3/k/Asv5M1HHskFo6x6DwoGt3eBqq2pIZnLTTm+VCrFxz72MdauXcuSJUu48MILSaVSkx5XClo5FxGRsTnH4396gJcb5tMVbuBfe59maaqbPedHOWjNq9lnYQMfP3JPokt2I1PrZ2HvNtWdi8xS0WiUvtj20raj3/pWrrz6amL5axs2bGDr1q1s3LiRSCTC+049lXM//Wke/etfvffX19PX1zfh+zU1NRGtr+fBhx4C4BfXXjviuMMPO4xfXncd/f39bNq0iTvvvhtgKMFuaWkhFovxq1/9asd/Sz6WscaVmlbORURkbNu28eKzr/DswpX0BSOcUvM0PPAAtfNa+e4H1gwNW9paz8aGVpb0bOHZzX2sXFKZDgsiUjlz587l0EMOYcWqVRx79NH879e+xlNPP80hhx8OQH19PT/90Y9Y9/zznPv5z1NTU4Pf7+fS//s/AM748Ic55vjjWbRoEXfeeuuE7vnDyy/n9I9+lJqaGv7psMNGLJF5+4kncsedd/La/fZj6ZIlHLLG+97V1NTE6aefzooVK1iwYAEHHnjg0HtOO+00zjzzTMLhMH/5y19GHVdqpmOWPatXr3Zr11aoHfqzz0J9fWXuLVKtYjHYe+9KRyHAlt/dys//+yp+cODbGaiP8tie2wi8+DysWAEnnTQ07rK7n+fWH9zA4esfpe1DH+PrH3pjBaOWnehnzazwVGcn+8yy752xWIz6/P/bX/vf/2XTpk1855vfnNibBwYgFCpjdPDUU0+xzz777HDNzB5xzq0eabzKWkREZEwv3v8Im6ItxIMRDt59DoF/PhZ8Pli8eIdxh+/VyitN8wF4ae0/6B/Q4o+IlN9Nf/gDKw88kBWrVnHvffdx/uc/X+mQpkRlLSIiMrqeHrY+8yLPz90TgMP3boWWFvjUpyAS2WHoPgujsGABSX+Q5s1tPN7WzaqlzZWIWkRmkZPf9S5Ofte7Kh1GyWjlXERERpV74knaOhOsm7sEyCfn4JVH1Oz4I8TMOHzvebzSuIAl3Zu555lt0x2uiEDZDseR4k3mv4WScxERGdXLf36UTcEo3eEGdmsKs3tL3Zjj/+nVrbzSOJ9oJsEjf103TVGKyKBQbS0dXV1K0KuAc46Ojg5CRda0q6xFRERGlkyy6fFneH6OV1t++N6tmNmYbzlszxYuaF4AQO+Tz7Ch+0h2awqXPVQR8Syur6etq4tt7e2VDmVmGBgAv79s04dCIRYP258zHiXnIiIyso4ONncl2LTQK2U5bK+dj9MerrkuwB57L6H37/Us7trMx372KNf+28EEfbXljlZEAH9tLcsncNqm5FVhZzCVtYiIyMh6e+lKZIgFvI2f+yxsmNDbPnfsPmxons/inq08/nIn/3nTU+WMUkRkl6LkXERERpRs7ySWztEXDOOvNZY0T6w85aDlczjm+DcQyqVpjXXx84deJpXtL3O0IiK7BiXnIiIyoi1t28jV1JLyBVk6J4KvduI/Mt72jjcSCfhY2rOZbL+jO5EtY6QiIrsOJeciIjKibRu3eSUtZixvKe5kSYtGSTc1s7DX25TWm1JyLiIyEUrORURkRF2b24kFvXrzPVrHbqE4klxjEw3pOAC9SSXnIiIToeRcRERGFNvaSV9+M+jycfqbj2SgqZnGVAyc08q5iMgEKTkXEZGdOUeyvWto5Xz31uLKWgBobibQnyWUS9ObzJU4QBGRXZOScxER2YmLxeiOp4kFvA4tu0+irKWmuRmAxlSMPq2ci4hMiJJzERHZSfvGbWT7B4gFI0RDPubWBYqew9cyB4CGVJzelFbORUQmQsm5iIjspO2lLQD0BuvYvbUeMyt6jkDLXAAa0zFtCBURmSAl5yIispMtbVsBiAUi7DGJzaAAddEICX+IxlRMG0JFRCZIybmIiOzk5Rc30281JP3BSXVqAWgI++kN1nnJuTaEiohMiJJzERHZQTLTz5PPtHmdWsw4dK+WSc3TEPLRE6rXyrmISBGUnIuIyA5ueWIzvniMWCDC7i11rFrSNKl5GsJ+ekL1RNMJ+hKZEkcpIrJrUnIuIiI7+PWjbdSnE/QFI7zzgMWT2gwK0BDykvMaN0B/d0+JoxQR2TUpORcRkSGbe1Lc/9w26jMJ4sEIb1u126TnGixrAbDuzlKFKCKyS1NyLiIiQ+55bhuBbBrfQD/Lli9kt6bwpOdqCPvpzSfnNVo5FxGZECXnIiIypCOWIZpOArD4VfOnNFfQV0M6Us+A1RCJ95LK9pciRBGRXZqScxERGdKdzFCfSQAQnDO5jaCDzIxoJEBfMEJDOq6OLSIiE6DkXEREhnTHs9SnveQ80jJnyvMNbgpVr3MRkYlRci4iIkO6kxmi6TgDVkP93MYpzxdVr3MRkaIoORcRkSHdiSzRTIJ4IExTXXDK8w2eEhrJpujriZcgQhGRXZuScxERGdKTzFKfTtIXiNAY8U95vsGyFoDUto4pzycisqtTci4iIkO6Et6G0FgwQnMkMOX5GsLbe52n25Wci4iMR8m5iIgM6Y5nqE8niAXCNJV45TzXroOIRETGo+RcREQAvD7kqRT+gRypcD1hf+2U52wI+0n5gmRq/fR3KDkXERmPknMREQG2bwYFsMYGzGzKc0ZDPjCjN1TPQKeScxGR8Sg5FxERIF9vnu9x7muaehtF8MpaAGKBMAN9sZLMKSKyK1NyLiIigLdyXp9JAuBrntrpoIMawj4Akv4gLq5WiiIi41FyLiIiAPQkM0TTCRxGsLmhJHMOrpzH/WEsFgPnSjKviMiuSsm5iIgAgyvnCeKBEI11oZLM2RD2kvOEP0Q2k4V0uiTziojsqpSci4gIAF2JbL6NYqQkbRSBoXkSgRC9ySyJzu6SzCsisquakcm5mR1jZs+Y2TozO2+E15ea2Z1m9lcze9zMjqtEnCIiM0l3cvsBRE0lOIAIoLU+yF7z6okHwuQGHPf97aWSzCsisquaccm5mdUClwDHAq8FTjGz1w4bdj5wrXNuFfAe4HvTG6WIyMzTk8gSLfHKuZnxtlW7kfQHAbjr0RdLMq+IyK5qSsm5mc03s9VmdnipApqAg4B1zrkXnHMZ4BfAicPGOGBwN1MjsHEa4xMRmZFiPXEC/Vn6ghGawqVZOQc4Yb9FxP1hAJ5+biPtMdWdi4iMZlLJuZmdbGaP4yW9DwJ3DHu9ycxuM7M/mVlzCeIstBvwSsHztvy1QhcC7zOzNuBm4OyRJjKzM8xsrZmt3bZtW4nDFBGZWdJdXQD5spbSrJwDLJkTYd8953tdYDIpfv+Y1ktEREZTdHJuZv8FXAOsADJ4q9Q7HCPnnOsGtgBHAidPPcyinQJc5ZxbDBwH/MTMdvq3Oue+75xb7Zxb3draOu1BiohUk1xXD0BJy1oGnXjAEhL+EHWZFHc8o8UQEZHRFJWcm9lRwOeAPrxa7npgtO+yV+Ml7UdPJcARbACWFDxfnL9W6MPAtQDOub8AIaClxHGIiOxS+ru95LyvhBtCB61c0kQyECKSTbG5J1nSuUVEdiXFrpyfhbdS/jnn3LXOuf4xxv4lP3a/yQY3ioeBvcxsuZkF8H5JuHHYmJeBNwOY2T54ybmWakRExuB6ewGIB8I0hUu7cj4vGiLuDxHJJNnWp5pzEZHRFJucr8l//ul4A51zMaAXWFBsUOPMm8P7JeEW4Cm8rixPmNlFZnZCfti/A6eb2WPAz4HTnNOxdCIio2Ien5IAACAASURBVEll+wkkYiT8IWr8PiKB2pLOP6cukF85T9OVyJLJDZR0fhGRXYWvyPFNQK9zLj7B8Tb+kOI5527G2+hZeO2CgsdPAoeW494iIrui7sEDiPIlLWal/fZdW2P4GqJE2l8G52iPpVnUFC7pPUREdgXFrpx3Ag1mNu53VDPbDa+d4ebJBCYiItOnO5khmkl6m0FLXNIyKNTcgG+gn2B/VqUtIiKjKDY5fyj/+dgJjP14/vO9Rd5DRESmWWc8Q306kd8MWp7kPNzkHT8RzqbYquRcRGRExSbnV+CVqnzVzBaNNsjMTgc+i7ch9LLJhyciItNhS3sfoVyaWCDM/IZQWe5RN6fJ+5xJaeVcRGQURdWcO+d+Z2bXAKcCj5jZtUAEwMw+ASwFjgH2wUviv5dvZSgiIlWsY1M74B1AtLKxPMl5Q0sjGbyVcyXnIiIjK3ZDKMBpeG0JP8H2kzcd8K38Y8s//wZeT3QREalyPVs6qAX6AhEWNJZno2ZDSzPtQF0myda+VFnuISIy0xWdnOdbGX7azC4B/hU4BFiIVyKzBa+/+Y+dc0+VMlARESmfvq2dNOGtnC8q08p5c2sz2zAi2bRWzkVERjGZlXMAnHPrgC+WMBYREamQRHs+OQ9EWFCm5HxeU5jH/EEi2STbYkrORURGUuyGUBER2QWlO7pJ+YLkan0sLFNZS2t9kEQgrA2hIiJjUHIuIjLLpbL9uN5eYsEItTVGazRYlvu0RoMk/MGhVoo6uFlEZGejlrWY2QWjvVYs59xFpZpLRERKa2tvmvpMgr5AmHnRILU1ZTncmbqgj/5wHU2dW8jkBuhN5Wgs04FHIiIz1Vg15xfidV2ZisHOLUrORUSq1MaeJPXpBFvq57CwTPXmgwKNUcJbXgLn2NaXVnIuIjLMWMn5j5l6ci4iIlVuS0eMSDZFLBApW735oGBzA/6BHIH+HFv7Uuw5r76s9xMRmWlGTc6dc6dNYxwiIlIh7Zs7AK+N4ooyr5xHmr1TQnUQkYjIyLQhVERkluvZ7J0O2heIlL2spX5uIwB12aSScxGRESg5FxGZ5Xq3dgLeynm5y1qiLd7KeUTtFEVERjTpQ4jMbDHwDmB/oDV/eRvwKHC9c65t6uGJiEi5xdu7aALigXDZDiAaFJ3TSA8QyabojGfKei8RkZmo6OTczCLAN4EP4628F/bccsD7gW+Y2RXAvzvnEqUIVEREyiPZ2U22xke61j8tZS0Ooy6ToieZLeu9RERmoqKSczMLALcBB+Ml5W3AvcCG/JBFwOHAYuAMYF8zO9I5p+/AIiJVKJMboL/HO4CopsaYV6YDiAY11AVJ+QOEsym6lZyLiOyk2JXzzwKHAAng48CP3QhHvJnZ+4FL82PPBb46xThFRKQMNnQnqc8kiAfCzG8I4ast71akxrCfuD9MXSbJRiXnIiI7Kfa78HvxSlc+5py7eqTEHMA59xO85N2A900tRBERKZcX22PUZ5LEAmGWza0r+/2aIgESgRB1mSTdCSXnIiLDFZucLwMywDUTGPuz/NhlRd5DRESmyQtbY9RlksQDYZa3lj85bwz76Q3W05COq+ZcRGQExSbn3UDKOZcbb2B+TBLomUxgIiJSfm0bO/AN9BMLRNi9pfzJeV2glr5IPZFsilwqRTrXX/Z7iojMJMUm53cDDWb22vEGmtnrgEbgrknEJSIi02DzBu8AolggzPJpSM7NDBq9XucNKa2ei4gMV2xy/hW8zaA/NLPG0QaZWQNwRX7sf0w+PBERKaeOTV5yHg9OT3IO4JqaAWhMxehVci4isoNRu7WY2dIRLvfitUj8HvC0mV2Kt5pe2Erxn4CPAiHgI0CslAGLiEhpJDI5Eh3d3uNQHUvmRKblvjVzveS8IR3XplARkWHGaqX44jjvbQC+NM6Yn+F1d5n0SaQiIlIe69sT1Ke9c+Lmzp+Lv8xtFAeFGqNka3w0pmIqaxERGWaspNnGeK0YpZpHRERK6MX2OHWZJEl/kFfNb5i2+zZGAvSE6mlMxbRyLiIyzKjJuXNuepZQRESkIgZ7nMcDkWmrNwdoCvvpCqmdoojISJSAi4jMUi+0x6nPJOibpk4tg7xe53U0pGJ0JzLTdl8RkZlAybmIyCz1YnucurS3cj4dPc4HDZa1BPqzJHv6pu2+IiIzgZJzEZFZqm1bH5FsinggzLJpXjnvCdUDkG3vnLb7iojMBJPqomJmYeAk4FC89ol1jL7x0znn3jy58EREpBwGBhzpnj4MR18wQms0OG33bgz76Q15vwzk2jum7b4iIjNB0cm5mb0JuAZoxUvI3eBLBcMKrzlERKSqxDI5IimvjeJAXd20tVEEaIpsXzkf6OqatvuKiMwERSXnZrYn8Fu8lfI/ATcB3wJ6gH8H5gNvAY4E2oEvo0OIRESqTk8iS10mCUBtw/S1UQRv5Txb6yfpD2Ld3dN6bxGRalfsUsm5eIn5T51zRznnvpO/nnTOXemc+698CcsxeCeEfhD4RenCFRGRUuhJZqnPeCvntc1N03rvprDfiyFYj69HybmISKFik/M34ZWpfGWsQc65W4FPAfsD50wuNBERKRcvOU/SbzWEGuun9d4Ng8l5qJ7a3l6cU/WjiMigYpPz3YCMc+7ZgmsDeKvkw10D5IB3TzI2EREpk8GV80QgTGMkMK33DvlrCfpq6A3VU5+KkUjpICIRkUHFJudpdq4h7wMazWyH7+7OuRQQB5ZPPjwRESmH7nzNeSwQpjG/kj2dBjeF1rgBeraqY4uIyKBik/M2vES8cCPp8/nPqwsHmtkCoJHRWyyKiEiF9CQHk/MITdO8cg479jqPb26f9vuLiFSrYpPzJ4FaYL+Ca7fjJeAXmFkIIL+KPrhZ9K9TDVJEREqrJ5klmk4Qr9TKeThAb9DrdZ7YouRcRGRQscn5H/AS8RMLrl2MV+ryVuAVM7sfb4X9JLzNo98oQZwiIlJCsd4Egf4ssWB4aIPmdGoI++kLRnAYaR1EJCIypNhDiH6F10pxaJnDObfBzI4Hfoq3YfSQ/EsJ4PPOud+WIlARESmddP7wn1ggMtTacDo1hv0M1NTSF6wjo+RcRGRIUcm5cy4GXDLC9bvNbDleYr4Y71Ci+51zPSWJUkRESirb5X17rtSG0Dl13j17Q3VktnVO+/1FRKpVsSvno3LO5YB7SzWfiIiUT7a3F8BrpViB5Hx+g9eBty8QId2tdRwRkUHF1pyLiMguINfrdcWN+0MVSc5bo0EAUv4gmZ6+ab+/iEi1UnIuIjIL9ffFGLAa0r4ATZHKrZwn/UFS8STkctMeg4hINRq1rMXMXsg/XOecO2rYtWI459wekwluNGZ2DF6rxlrgCufc10YY827gQryOMY85504tZQwiIjNV/4DDJRIkfUEwIxqqXHKe8IeIpfshkYCGhmmPQ0Sk2oxVc74s/zk1wrViuEm8Z1RmVou3KfWteC0bHzazG51zTxaM2Qv4PHCoc67LzOaVMgYRkZmsL5UlkkmRDISIhnzU1kz/WXHz8mUtSV+QRDqHi8cxJeciImMm50fmPydGuFZJB+Gt5r8AYGa/wOu7/mTBmNOBS5xzXQDOua3THqWISJXqTmQJZ9Mk/MGK1JsD1AV9RIM+Uv4g/c7R29FD48KFFYlFRKSajJqcO+funsi1CtgNeKXgeRuwZtiYvQHyByLVAhc65/44fCIzOwM4A2Dp0qVlCVZEpNr0JLNEsik2h+ZWpN580LyGIF1d3gp657YuGisWiYhI9ShqQ6iZfSL/sahcAZWID9gLOAI4BfiBmTUNH+Sc+75zbrVzbnVra+s0hygiUhmDyXmyQp1aBs1vCHl170BXu9opiohA8d1avgV8nYITQitgA7Ck4Pni/LVCbcCNzrmsc+5F4Fm8ZF1EZNbr7UsS6M+SrGBZC3jJecofwGH0dCg5FxGB4pPzdqDPOZcpRzAT9DCwl5ktN7MA8B7gxmFjfoO3ao6ZteCVuUym04yIyC4n1p0/gKjCK+fzGoI4qyHlDxDrVHIuIgLFJ+ePAo1mVrEakPxJpGcBtwBPAdc6554ws4vM7IT8sFuADjN7ErgTONc511GZiEVEqkuyy0vOvZXzQMXimBfN9zr3BYl36SAiEREYu1vLSC4Gjga+CHyi9OFMjHPuZuDmYdcuKHjsgM/kP0REpECqSlbO5zfk2yn6g6R6eisWh4hINSlq5dw59wfgHOBMM/uJme1XnrBERKRc0t3eKnXlk3Nv5TzlC5LuiVUsDhGRalLUynnBCaE54FTgVDNLAh1A/yhvK/kJoSIiMnnp3l6CQKrSG0LzZS2JQIhM35aKxSEiUk2KLWtZNsK1SP5jNCU9IVRERKYm1xvDZzWka/0V73MOXs15fyzOQP8ANbXFboUSEdm1FJucV8MJoSIiMgW5WJyEPwRmFV05D/lraQz7SfmDMDBAZ1cfLS06ikhEZreikvMqOSFURESmwMXiJANeSUklk3PwNoUm/d4KevvmTiXnIjLr6e+HIiKzjIvnV86Bhgon5/Oi208J7dzWXdFYRESqgZJzEZFZJNc/QG0iQdIfxAyiwWKrG0trXjQ49IuCTgkVESm+5nyImS0F3gAsAuoAG22sc+6iyd5HRERKpzeVI5xNkfQFiQZ91NSM+q17WrRGg17NOdCrU0JFRIpPzs1sEXA5cCxjJOSDw/G6tSg5FxGpAj09cfwDORKBEI0V7NQyqDW6veY81qWDiEREiu1z3gjcDewOtAN/Bk4EksCvgfnAwUA0//pNpQxWRESmJtbpJcDJCh9ANKg1GiRb4yNXU0tCybmISNE1558G9gAeBl7tnHt7/nqPc+4DzrmjgYXA14AWIOuc+2DJohURkSmJd3mlI5U+HXRQazQIZiT9IZL5k0tFRGazYstaTsArUznXOTfitnrnXAL4gpn5gc+Y2d3OuZ9NMU4RESmBxFByXtnTQQfNy58SmvQHoTdW4WhERCqv2JXzPYABvHKWQoERxv53/vPpxQYlIiLlkeyqvrIW8E4JzfYpORcRKTY59wHdzrn+gmtxoMHMdtgc6pxrB7qBfacWooiIlEq6xysdSfqDFe9xDtAQ8hHw1ZD0B6lJJomnc5UOSUSkoopNzjcA9cOutQG1wKsLL5pZGGgCIpOOTkRESirTGyNb4yNb66chVPnk3MyYFw2S8gWJZFNs60tXOiQRkYoqNjl/HgiY2R4F1/6S/3zmsLGfxGul+PwkYxMRkRLL9vaRzB/6Uw1lLeCVtiQCIQL9Wbb1JCodjohIRRWbnN+Ol3AfU3Dt0vzns83sJjP7TzO7EfhPvM2jV089TBERKYVcX4xEvq941STn9UGSPi+mjq0j9hoQEZk1iu3W8nNgDTBv8IJz7mEz+xxe+8Rj8RL3wfrz64FvlCBOEREpgf6+GIlA9a2cv5D/haG7vavC0YiIVFZRyblzbgPwrhGuf93MbgbeCSwGeoDbnHO3lSRKEREpCRePk/I1AdWTnM+Lhkjlk/PeTh1EJCKzW7Er56Nyzj0JPFmq+UREpMScw+JxEs0LgOpJzluj28taett7KhyNiEhlFVVzbmbF1qiLiEi1yGTIZrIkqnFDaD6meLdWzkVkdis22d5oZheb2SFliUZERMpmoC9GOjdAMuCtUkdDJfvj6ZTMiwZJ+b2z7JLdfRWORkSksopNzucBHwfuM7PnzewrZva6MsQlIiIlFuv0SkYS/hD1QR++2ur4Y2hrNIizGlK+IMkeJeciMrsV+535vcBNQBZYDnweeNzMHjOzz5rZ0lIHKCIipVGYnFdLSQtAS723kp/0B8n1xegfcBWOSESkcopKzp1zP3fOnQAsAE4H7sLrZb4v8F/AC2Z2j5mdaWZzSx2siIhMXrzLq+dO+YM0VFFyHvDV0Bzxk/QFCWXSdMR0SqiIzF6T+pumc67bOfdD59yb8VonfgZ4OD/fG4FL8OrTbzKzU0sWrYiITFqiNw5AujZAY7g66s0HLZ0TIekPEs6leW5rrNLhiIhUzJQLDp1zm51z33bOHQzsCXwRr6WiH+9Qop9M9R4iIjJ1yd44DiNT66uqshaA1yxoIOkPEcqmeGqTOraIyOxV0t1AzrkX8E4K/RzwaCnnFhGRqUnF4qR9ATCruuR8n4VR0j4/oVyGpzZpU6iIzF4l+7ummR0GnAKcBBTWm28q1T1ERGTyUn0J0j4vKa++5LyBm3wBfAP9PNvWWelwREQqZkrJuZmtBE4FTsarPQcwoBu4HrgGuHMq9xARkdLIxBPeyjnVl5y/ZmEDqfwpoW0bO8n2D+CvklaPIiLTqejk3Mz2xFshPwV49eBlIAX8Hi8hv9k5lylVkCIiMnXZeIJ0bXUm541hP41zGuB5qEmneGFbnFcviFY6LBGRaVdUcm5mDwEHDD4F+oHb8RLy651z2mIvIlKlEr3xobKWwd7i1WTxojkA+brzXiXnIjIrFfs3w9V4SfmDwCeARc65Y5xzP1ZiLiJS3WI9cTK1XnK+ZE6kwtHsbNlib7tSKJdWxxYRmbWKLWs5H7jGObe+DLGIiEiZOOdI9sVIt8wDYElz9SXnuy9t4UnyK+eb1bFFRGanYk8I/aoScxGRmWdbb5KaTIa0z09DyEdjpLpqzgH2WtoKQDCX4WmtnIvILKWt8CIis0Db5i7AOx20GktaAJYsbGbAagjmMmyLpRkYcJUOSURk2ik5FxGZBTZt7gYg7QuwtEqTc5+vloFgkFAug3MQz+QqHZKIyLRTci4iMgts2jKYnPurduUcgHCYUDYNQF9KybmIzD5KzkVEZoGt23oAb+V8SXO4wtGMzsJhQjnvmIxYWsm5iMw+Ss5FRGaB9vZ8cl7FNecANQXJeV8qW+FoRESmn5JzEZFZoLPDa01Y7WUtNXVhgvnkvFdlLSIyCyk5FxHZxWVyA/R255PzWj+7NVVvWYu/rm57WYuScxGZhYpKzs3sA2b2riLGv8PMPlB8WCIiUiobu5ME8gnvnOYoIX9thSMana8+4q2cO6cNoSIyKxW7cn4V8O0ixn8DuLLIe4iISAm90pUgmMuSqfWzuKWu0uGMyV9Xh+EI5jKqOReRWWkyZS1W5vEiIlJCr3QmCeYyXqeWKq43BwjUe/GFchmtnIvIrFTumvMmIFXme4iIyBg2dCeGkvPFzdWdnAcb6r3PuYxaKYrIrFS25NzM3gE0AuvLMPcxZvaMma0zs/PGGPdOM3NmtrrUMYiIzBSbulME+7Oka/0sagxVOpwxhRq8sptQLkOvylpEZBbyjfWimX0S+OSwy61m9sJYb8NLyhsBB9wwpQh3jqkWuAR4K9AGPGxmNzrnnhw2LooX+4OlvL+IyEyzqSfF7rkMfcE6FlR5ch7Or5yHcmmVtYjIrDRmco5XlrKs4LkDaoddG00W+DnwH5MJbAwHAeuccy8AmNkvgBOBJ4eN+w/gv4FzS3x/EZEZZVNPktcMrpxXcRtFgEjjYHKuDaEiMjuNl5xfBdyVf2zAHUAn8M4x3jMA9ALPOecSU4xvJLsBrxQ8bwPWFA4ws/2BJc65m8xs1OTczM4AzgBYunRpGUIVEaks5xybelIEc1nSPj8Lq3zlvK4gOVfNuYjMRmMm5865l4CXBp+b2cvAFufc3eUObLLMrAb4JnDaeGOdc98Hvg+wevVqV97IRESmX1ciSzrbTzCXoSYcJhryVzqkMdXXhcjW+Ahl02xRWYuIzELjrZzvwDm3rExxFGMDsKTg+eL8tUFRYAVwl5kBLABuNLMTnHNrpy1KEZEqsLE7SaA/h+GI5lelq1k05CflCxDsz6rmXERmpXK3UiyHh4G9zGy5mQWA9wA3Dr7onOtxzrU455blf5l4AFBiLiKz0uaeFMF+73TQhjnRCkczvmjIR9ofJJRNE1NyLiKzUFEr54PypSNvwFuhbgbG/Dupc+6iydxnlLlyZnYWcAve5tQrnXNPmNlFwFrn3I1jzyAiMnts6vEOIAJoaqr+5DzoqyEbCBDKZcj0D5DK9hPy11Y6LBGRaVN0cm5mbwf+D1g4keF4HV5KlpwDOOduBm4edu2CUcYeUcp7i4jMJBvzm0EBmlsaKhzN+MwMC0cIdncB0JfKKTkXkVmlqOTczN4CXIdXDpMBHsKr99YpoCIiVWhzT2po5bx1TvUn5wA1kTCh9s0A9KWytEaDFY5IRGT6FLty/gW8xPxu4FTn3KbShyQiIqXibQj1Vs7nzoCVc4DaSJhQ/hcKtVMUkdmm2A2hB+CVqZymxFxEpPpt7t2+cj5/XmOFo5mY2roIvoF+fP05dWwRkVmn2OTcgN58/3MREaliQwcQ5VfO589vrnBEE+OrrwMgqFNCRWQWKjY5fwqoM7PqPmJOREToiGfI5Aa8A4gCAeojM6N2259PzkO5jFbORWTWKTY5/x5enfr7yxCLiIiU0OYeb69+MJclFK2rcDQTF6yPAErORWR2KvaE0KvN7I3At82szzn3izLFJSIiU7Q9Oc8QikYqHM3EBaN1pIFQLq3kXERmnWJbKV6Zf5gGfmZm/wWsBfrGeJtzzn14kvGJiMgk9SS9eu1gf4ZAXfUfQDQo1FBPGm/FXzXnIjLbFNtK8TS8bi2Wf/6q/MdYHKDkXERkmvXmE9tgLos/MnO2CoUb6unBWzlXK0URmW2KTc6/XJYoRESk5HqTXmIb6M/ir5s5ZS2Rhjoclu/WouRcRGaXYmvOlZyLiMwQ21fOMwTqZ05yHg37SfkDhHKZoX+DiMhsUWy3FhERmSF6k1lwjmAuQ7B+5nRraQj5SPmChLLaECois8+UknPztJjZ0lIFJCIipdGXyuEb6KfWDcyobi2NYT/pWj+hXGZoU6uIyGwxqeTczA4xsxuBXmAL8MKw15vM7IdmdoWZzZyfCCIiu5DeVJZgLgNAOFpf4Wgmbm5dkJQ/SDCXoT2WrnQ4IiLTqujk3Mw+DtwD/AtQh9e5xQrHOOe6gRbgg8A7px6miIgUqzeVJdjvrTyHG2bOOklj2E/GHxw6hCid6690SCIi06ao5NzMDgK+AwwA5wFL8VbOR/IjvKT9uKkEKCIik9ObzA2tnNc1zJyV85oaw18fIZzzVs274iptEZHZo9iV88/gJdwXOuf+xznXNsbYu/Of959UZCIiMiWFZS31jTNnQyhAoCFKMJehZqBfpS0iMqsUm5wflv/8vfEGOue68E4OXVxsUCIiMjXOOXqTWQL5spa6xpmzcg4QaG4AIJJN0xHPVDgaEZHpU2xy3gL0Oud6Jji+fxL3EBGRKYpn+hlw3umgvpqaGXUIEUC4qRGASCZJh1bORWQWKTZx7gGiZhYYb6CZtQCNwLbJBCYiIpPXm29BGM6lCfprIByucETFCc/xkvO6bIpOrZyLyCxSbHL+GF7N+WHjDQROy499sMh7iIjIFA0e3lOXSUI4Ar6iDoSuuOjcJsBbOW+PKTkXkdmj2OT8x3gJ93+Z2agFjGZ2FHAR4IArJx+eiIhMxuCx99F0AheNVjia4jW0eMl5XTalshYRmVWKXUr5KfAB4M3Ag2Z2BRAEMLPjgVcBxwJH4yX+Nzjn/lC6cEVEZCIGy1rqMklY0FLhaIo3pzHCel/QqzlXWYuIzCJFJefOOWdmbwd+ApwIfL3g5d/kPw8eSHQ9XiIvIiLTbHDlvC6TwBoaKhxN8ebWB4kHQtRlUrQpOReRWaToTirOuZhz7u3AW4FrgBeBFJABXgF+CRzrnDvJOZcoZbAiIjIxvckc5gaoy6SobZh5ZS1z6wIk/GEiWXVrEZHZZdI7hJxztwO3lzAWEREpkd5klkgmheHwNTVVOpyiza0PEA+EWNDXQYc2hIrILKIe5CIiu6DeVJb6jPfHS39zY4WjKV590EcmFCGSTZHM9pPI5CodkojItFByLiKyC+pN5qjPJAEINc+8lXMzw98YJdCfxd+f1eq5iMwao5a1mNkFpbqJc+6iUs0lIiLj601lvU4tQGjuzFs5Bwg0eRtZI5kUHfEMS+bMrFNORUQmY6ya8wvx+pQPZ6NcH8ngWCXnIiLTqC+Voy6TZMBqqJuBZS0AoabBU0K1KVREZo+xkvMfM3oS/jagEUgAjwAb8tcXAauBCNAN3DjGHCIiUia9qSzzM0ni/hANdcFKhzMp4Tlech7JpFTWIiKzxqjJuXPutOHXzMyAa4F64HzgO865+LAxEeCTeKvlEefcu0sZsIiIjK83mWX3TJJ4IExDaNKNuSoqOnhKaCZJe1wr5yIyOxS7IfRs4B3Auc65rw5PzP8/e+8dHvd13vl+z/SOMhh0ggTAToCkRIoUVUjJVLVkK7KtYjtZF9mytXF292afZPM4iZM4uZtc772bjZPIlm1ZsRxZtiRHlmzRkqlCUYVi7x291+kFU8/9450fZ9AxwMz8fjM4n+fBg/abwZnBzDnf8573/b4AwDkPcs7/HsCfAPg0Y+wbWRinQCAQCDLAOxGDJRxEQGeE1aCVeziLwlpeggRTwRSdgFNEzgUCwTIhU3H+JQAxAN9fwLXfBxAH8FimgxIIBALB4uGcwxuKwhIJwa83wVqgkXO7RY+gVg9zsiBUIBAIlgOZivPVAPyc84n5Lkxe40/eRiAQCAR5IhSNA9EoDLEwIkYTDFq13ENaFKUmHYI66hLqCUXlHo5AIBDkhUzFeQRAKWNs5XwXMsZWAShN3kYgEAgEecIbisEUTcZQbDZ5B7MEbAYNAloDzJEJeIU4FwgEy4RMxfmHyc/fY4zpZruIMaYF8CTIqeWDRY5NIBAIBIvAHYpc6w7KrFaZR7N4bEYtRc4jIXgnhDgXCATLg0zF+d8BSAC4G8ApxthXGGNrGWOW5MdaxthXAJxMXhMH8LfZHbJAIBAI5mLcH4ElTOLcUF543UElbEYtRc6jE/AGhTgXCATLg4yqhDjnhxljfwDgxwDWA3hqlksZgAkAX+KcH13aEAUCgUCQmUoGPQAAIABJREFUCWP+MCzJ7qCWijKZR7N4SpKRcxVPIOL3yz0cgUAgyAuZRs7BOf85gBYAzwDwgIR4+ocHwNMAWjjnv8jeUAUCgUCwEEZ9YZgjIcRUapSUFW5ai1mnRkhnAAAwfwDReELmEQkEAkHuWZS/Fue8A2SR+BhjrAmAI/mr0eTvBAKBQCATY/4IzJEQ/DoTKqwGuYezaBhjUNloc2GKTsA3EUO5edZyJ4FAICgKlmx+mxTjQpALBAKBQhhPprUEdEass+rlHs6SUCcLWs0RslMU4lwgEBQ7Gae1CAQCgUDZjPnDyci5EfYCF7OakmTkXNgpCgSCZcKiI+eMsXpQ7nkZgDl7Q3POn13s3xEIBAJBZoz5wtgYDqKzrBYVBR45N1lMiKo0MEeFnaJAIFgeZCzOGWM7AfwTgBsyuJkQ5wKBQJAnvG4/tIkY/DoTHJbCFuc2ow5BnSEZOY/JPRyBQCDIORmJc8bYNgBvAzCAnFn6APSDbBMFAoFAIDOcc0w4PQAAv94Iu6Ww01psRg0CWqOInAsEgmVDppHzvwZgBHAW5GF+IusjWgCMsXtA0Xs1gB9xzv9hyu//GMBXAMQAjAL4Mue8O+8DFQgEgjzjnYhBNxEAACTMFph0S677l5USoxaDOgNKQz6Rcy4QCJYFmRaE3gSAA/i8jMJcDeBfAdwLYCOAzzLGNk657CSA7ZzzzQBeAvCd/I5SIBAI5IEaEFF3UH0BdweVsBm0COhE5FwgECwfMhXnBgB+zvm5XAxmgewA0MY57+CcRwD8HMAD6Rdwzt/hnAeT334EoD7PYxQIBAJZGPdHYAnT9GeyF4E4N5I4N0bD8PtCcg9HIBAIck6m4rwNgJ4xJuc5aR2A3rTv+5I/m43HAPx2pl8wxh5njB1jjB0bHR3N4hAFAoFAHsb8YdjCAQS1BpSVmOUezpKxGTVwGchOMT42JvNoBAKBIPdkKs6fAaDDlEi1UmGM/T6A7QD+10y/55z/gHO+nXO+3eFwzHSJQCAQFBRj/jBKJvzwGCywF7hTC0BpLW6jDQDAx8ZlHo1AIBDknkzF+XcB/A7A9xlju3IwnoXQD2BF2vf1yZ9NgjF2B4A/B/BJznk4T2MTCAQCWRnzpcS5o8CdWgBKa3EZKXLOxkXkXCAQFD+Zpqf8BYAjoLzv9xlj7wE4CsA31404599e3PBm5CiANYyxRpAofxTA59IvYIxdB+ApAPdwzkey+LcFAoFA0Yx7Q7CHg7jksBR8AyKAIucxtQY+vRkal0vu4QgEAkHOWYyVIgd5nAPAbgC3znE9S16fNXHOOY8xxr4B4A2QleKPOefnGWPfBnCMc/4qKI3FAuBFxhgA9HDOP5mtMQgEAoFSCYyMw8ET8BisqCiGtBYjLVNOow0Ot1Pm0QgEAkHuyVScPwsS27LCOd8HYN+Un30r7es78j4ogUAgUADhUcrL9hgssJuLIK3FoAUAuIxWrBjvAjgHGJv7RgKBQFDAZCTOOedfzNE4BAKBQFZ8E1H89twQttSXYl21Ve7hLJr4WEqcF0Nai0mnhkbF4DLaoIpEEHZ7oC8rfItIgUAgmI3Cbh0nEAgEWeJvfn0BLx3vg1WvwcE/vR1lBRp15k4nYio1/DpjUaS1MMaSRaHk2BIYGBbiXCAQFDWZurUIBAJBUXLwCvU68IVjONXrlnk0i8M3EYXe74XHYIFOq4bNUBzxF5tBA5eJxHlwYFjm0QgEAkFuWZQ4Z4w1Msa+yxi7yBjzM8ZiU35fyhj7FmPsLxlj2uwMVSAQCHKDbyKKEV/KcbVtxC/jaBbPkGcCpUkbxdoSA1iR5GbbjFr4dCZEVRqEh0XDOIFAUNxkHFZhjD0IKgw1IeXaMqlIlHPuZox9DOTkcgHAL5c4ToFAIMgZHaOBSd+3jxamOB90h2Cb8KPPVonqEoPcw8kaNoMWYAxuoxXRIeGOKxAIipuMIueMsfUAngNgBvADkJXibF0hfggS7/cvZYACgUCQazrGJovxQhXnI8NO6OJRuI1W1JQY5R5O1pDsFF1GG2KjohGRQCAobjKNnP8JAAOAf+Sc/3cAYIzFZ7n2zeTnHYscm0AgEOSOUAjw+YDKSrSPTI2cB2a5kbJx91E+tsdgQU2xRc5B4jzhHAFiMUBTHPn0AoFAMJVMc873glJYvjPfhZzzYQABACsWMS6BQCDILfv3A08/DSQS0yLnzkAEzkBEpoEtHt8g5WMXnTg3przOfaEoIDqFCgSCIiZTcV4NwJcU3gshDKAw/cgEAkHxwjnQ3g6Ew4DTOS1yDhRmaktwhFI+SJwXT1rLmkoLABLnp3rdGO7ok3lES6PzYiee/d4rONwuUnQEAsF0MhXnAQBmxph6vgsZY1YApQBEv2WBQKAsXC7A4wEAxPsH0Dk+gzgvQMeWyMgYfDoT4ip1URWEPrC1DmsqLXAZSxCNJ/DjV46Bc9mbVWdMIp7AK0//Gq888VdwPvcLfO+vfogR74TcwxIIBAojU3F+PnmbbQu49pHktcczHZRAIBDklM7Oa1+Ot3UjEktMu6QQ7RQT4054DRRlri0tnsi5TqPC33+qFRGNFgGtEZ2XunGy0LzoIxG8/u0n0fnM8+ixVOB8VTO2dp3FiedelXtkAoFAYWQqzl8AObD8LWNs1tsyxloB/AMoP/25xQ9PIBAIckBHB2C1AtXVGGvvufbjdFvwQktroQZEHngMFug1KpSZiqvFxPZV5bh7UxVcJhtKQz60DRfW/8f/6mvoOHAYH67cgpc33Y79q3fioqMR/n1vAEeOyD08gUCgIDIV508BOAPgDgBvJT3PNQAJcsbY/YyxfwXwEYByAB8A+EUWxysQCARLg3OgqwtoagJqauDr6qWfAbi+oezaZYXm2DI05oMlEkraKBZPA6J0VpSZ4DJaUR7ywhksoILdaBQn972HM/aVOLKiBaVmPcAYfrf2RhxU2RF45deTTnMEAsHyJiNxzjmPArgHlKqyB8BLIBEOAKcAvALg6wCMIIH+KV6IiYECgaB4GRkBAgGgsRGoroZ7xA1zJAQA+Nj6SqiSmrbHGcRbFwunVfxo7xAAKgYtpnzzdMrMOrgMNhhiYfhcXrmHs2D8p87gbMcILlQ1AQD+5oEW7FhVDs5U+O3am3AxrAVefpnsPQUCwbIn08g5OOdDAG4C8DiADwFEQakuDEACwBEATwDYzTkXpegCgUBZdHTQ58ZGDBtLcXnYB0eArPlubCrH3rUVcPjp+//681O4MuyTa6QZ4e5PepzrLagtIqeWdMpMOvj19NhC4x6ZR7Nwjrz8DkY1JvTZKtFUYcZ9rTW4t7UaABBVa/HnbC1eO3QVg8+9eO0URyAQLF8yFucAwDmPcc5/xDm/FdQttApADQAj53wX5/wpznksmwMVCASCxZJIcHgnouTw0dkJ2O1ASQmevOxHgnNUBlzYtrIM1zeU4f+tdOHrl/Zj43AH/OEYvvkfZ+Ue/oLwDJDHudtYxJFzkxZBHYnzCVdhFIRylws9x8/jQmUTwBi+vqcZahXDPS3V1665rLbiGX0jDvzHAeD0afkGKxAIFMGixHk6nPM453yUcz4sBLlAIFAanHP8t1+cwua//h2+9fIZoLsbaGxE51gAz58agdtghcPvwn+7Yw0Y5yi5fAGf3FqHO9sPY6VrAMd7XPCEonI/jHkJDo8jotZiQqNHTRE5taRTatIhoKWNR8RdGCcaV/d/AHcgjIuVjTDr1Lh/Sw0AoKbEiMd3N10rQj5etwHHWQmcL4r0FoFgubNkcc4Y0zDGHMkP0U9ZIBAoinevjOLV0wMAgP1vnoLL5cNxVQkefPIDROIJjJrLcJ1uAresrqCoutcLx+cfgq6mGvddeh8VPidOdCu/I2XA6UZQawAYQ42tSCPnZi0COhMAIOopgJxzznHljffQW1INr8GC+zbXwKRLLZPf/PgGnPrWXbhtnQOcqfBRQyva+pxAb6+MgxYIBHKzKHHOGCthjH2TMXYCQBDAUPIjyBg7wRj7M8ZYSTYHKhAIBJnCOcc/v9127fsGzxAOXhnFF94ZhTtI0XCXrRwfr9ODRSLAqVOA0Qi0tsL7qYcR1ujwe+cP4MSVIbkewoKZcHsR0JEoL960Fh0iag2iKg3iXuWL83BbB3ra+3E+WQj66evrp11TYtTiwevqAABDFjsujwSFOBcIljkZi3PG2C0ALgL4WwBbQVaKUkGoJvmz/xvARcbYzdkbqkAgEGTGofZxHE+Letd5RnA0pINfrQcAVFr1+OaXb6OGPd3dwMWLQGsroNFg68YVeGPtLpijIQweUX4ecNzrQyiZ8lFp08s8mtxQatICjCGoM4D7/IrvEnr+dx/Cz9Vos69AQ7kJN6wqn/G6vRuqoNOoEFNrcIGbMHIhtaH0BKP46aEunOkrjBx7gUCwdDIS54yxNQBeB1ANwAngfwK4G0BL8uOu5M/Gkte8nryNQCAQ5J3vvdt+7WvGE6jxjWHAWgGAuk6++PVdaNm+gS54+20gFgO2bgVATW/6bJXw6UyInz+HcCye9/EvlFg8AQQDlNYCoNykk3lEuUGvUcOsU8OvM8IQDsEXVnaZk/tKBwZsDsTUGty1sQoq1cze8xa9BretdQAABq12tJ28DCSoa+3fvXYBf/nKeTz81CE4AwXk7S4QCBZNppHzvwFgAvmcr+ec/wXnfD/n/ELy403O+V8A2JC8xgzgr7I7ZIFAIJifcCyOw53Oa98/WKeDLh7FgI1E0Nf3NGOl3QxYLIDZDAwNAQ4HUEMFew6rHo0OC9oqGlA3PoBz7SOyPI6F4PRPwBCNIKQ1oMykhUa95HIixVJq0iGoNcIcCcIdUHChbiSCcP8ghi12AMDqSsucl9+3mV53gzYHTnWMYLyTUltePN4HAJiIJvDOJeW+BgUCQfbIdAbfC4ADeIxzPj7bRZxzJ4DHkt/escixCQQCwaK5OOhDJEbRx5V2E/5wNUWTB2wO1JUa8cSeZrqQMaA6aWu3dSuQ1llz+8oyXKlogCYRR9v7x/M6/kxwjrrBwBHQGVBhKc6UFgkqCjXAHJ2AS8ldQgcH4Q5GMGQlcd5YYZ7z8ntaqtFYYcagtQKRWAL//sL7mIhOPq3RqIuv66tAIJhOpuLcCsDLOT8z34XJa7zJ2wgEAkFeOdmTyjXfuqIUzRMu3L6tCbfvXIOffHkHjDp16uK6OkClAjZvnnQfNzSWY9BaAZ/OhM6Dxyh9RIG4R+iEIKg1wG4pzpQWiTKTDgGdEfpYBG5PQO7hzArv64MrEMFQMnLe6JhbnOs1avz1JzfBqzcjoDXiwtEL11yGJIIR5aZWZQTnVPSq8JoBgUAuMhXn3QAMjDH1fBcmr9ED6FnMwAQCQQ749a+B996TexR54WRPqoDuuhWlQG8vttzUin/67PXTUwxuvhl4/HHAOjmWcNtaB/RaNdoqGqDpbMezBy7nY+gZ4x2jbpkhrQH2Io+cl5p01xoR+caVa3Hpbe/GmMaEkM4Ai14DxwL+L3vWOnDXpmoMWe2o8Y7hn968Oun3ij4pyITOTuCFF4D29vmvFQiWIZmK8xcA6AA8soBrHwGJ859nOiiBQJADQiHg6lXgyJFlYdV2qjclzreVawCXC2homPlivT6V2pJGpc2A/7J3Da5WrIAmEccrLxxAv1t5DWL8ThLnQa0eFeZij5xr4U+K80ByU6IE3r40jIe/fwhPHmhDPMHhvto1KaWFsYWlpDy6YwUGbA6UTvjgHJm8+fAEFZxjnwkDyROBS5fkHYdAoFAyFef/E8ARAE8xxh6d7SLG2CMAngLwEYC/X/zwBAJB1ujvp2NkrRb43e+AaJEs9DMw5g+jxxkEQK4s62JJT+wVKzK+r6/e2gTL6kb4dCY0DHbihwc7sjnUrBBwJcW5zlj8OefJglAACLmUIc4TCY4/feksjnQ58Z3XL+OJHxzEWN/wtZSWpnlSWtJpqSvBoI0chWp8Y5N+5y4WcT6U7BvQ3g5EiuQ0QCDIIpmK8/8B4G0AMQDPMcY6GGPPMMb+LvnxY8ZYO4CfAYgCeAfAnzHGvjX1I7sPQyAQzEtfH6BWA/ffD7jdwKFDco8oZ5xKS2lprSuBbqAP0GiuObFkgk6jwjfv24h2+wqsdA9i/8luJBLKypUNubyIMxXCam3Rp7WUmbTXmi1NOJUhzq+M+DDmD1/7/uqJy3jv6iiGF1gMmk6l1QDU1CDBVKieKs5DRSBkOSdxbreTdWmH8ja7AoHcaOa/ZBJ/DXJrkc7nViU/pJUq/dyuFMCfzXAfLHn9tzP824JcEokAuuI+Dl/29PYCtbVAUxM12jl2DFizZlGCVemc7E2lA1C++QV67Op5y2Vm5JbVFfjf9augGbwM1eAgTva6sG3lzA1l5CDs9pLHOWPFXxBq1iGk1SPBVIh4lCHOD3c4J31f7RsHB8OIpQxAZuIcADY22DFiLkNtoUfOQyHgwgXguuuo4Bqg9LJwGNizB/jgA+DyZWD9+szu1+kk+1N9cW9EBcuXTMX5s0gJcUGx4HQCP/kJ8OijRSnUBKBFcnQU2LWLvt+9myJWv/wlcPvtwMaNZCGYSNDP9fpFpYAohaNdaeK8xgycHEw99kWgUauw9YZ1wNE34Ai4sO/skKLEedTjQygZTS72tJZSkw6cqRDU6mHy+OQeDgDgSOdkcV7lH8e4uRRRtRYA0FQxt8f5VFrrSnHSWoFNw+2wB9wIafWY0OjgCRWYOL9wAThwgPoHSPUeg4P0uaYGWLsWOHOGxPpChXY4DPz0p8C2bcAtt+Rk2AKB3GQkzjnnX8zROARyMjBAomxsTIjzYkXKN6+vp+8NBuDhh4E33gBef50KRauraaH0+egU5atfpesKDH84hhPdKXF+ozECxONL3mzs3d6M93RGOAIuvH5uCH9x34YFF/nlmqjPj4BWEudFHjk3keAN6ozQebwyjwbgnONwZ6rtxz8+vBmX//gltNlTr7dVFaaM7rO13oZfl1Ri6+Bl/MHJ1wAAMZUab97yyewMOl84k5uWq1dT4nxoiOpeysuBdeuAkycp93zjxtTtQiGas0ZHgZaWyS5K3d2UDqOQU5OMGBsDysoWfYInWD4Ubxs5wcIZSx6d+pQRhRLkACnfPH3zVV4OPPIIHS93ddERc1kZcNttlOZ0+vTk+5iYSL1WFMyh9nHEkjnhG2tssDuH6RdLFOc3NdsRLK1ARcCNfncIJ3qUYePHOUfC70coKc6LP+ecNh9+nRHc55d5NED7aABjfsoFLzFq8UCDCVXaxDWnFgCwGrQZ3WdLXQna7fV4qfUO7Ft3Mw40bYc6kYCjt8Dys13J90hbW8rTfGiIAgEqFaWaWa2U2hKL0Zzzb/8GPPkk8MorwIcfAocPT77Ptjb67Jf/f58Rbjfw7LPT51WBYAaEOBekBFehTXZLIZGgqHFfn9wjyQ+9vSTMNVMOy1QqYPt24CtfAb78ZeChh+i4eNUq4MSJlKNLPA689BLw7/9OUS0F897V0Wtf318SBj76CKisBEyZRS+nolWrsHJTE8qDHqgScfz5y+emdXCUg0A4Bl0oiKDWAL1GBbOuuKNypVLkXGsE88sfUEiPmt+wqhyqwQHsWevAcNKpZc9aR8b3WWk1oLLEiL6SKlxxrMKp2nUYtFagfrRPEa+5BeN0UrqK30/pLLEYMDKSsi1ljKLnXV3Aj34EvPkmRdVvvZUCB2vXpoQ7QPOQVEAaUG4Dqhlpb6cNynJZcwRLYlHinDHWyBj7LmPsImPMzxiLTfl9adKV5S8ZY5mFDAT5Zzy5uCynyPngIHDuHPDb3xa1pSAAiniPjs4dObZYKGousXMnEAwC58/T9x99BAwP0+J44UJux7tE3rs6BsYT2NlzFvef3E/i4NOfzsp933vHVugYhz3oxaUhH77zuvxNicbHvVDzBIJaAyosesWk2uQKi14DrZohoDNAOxHCRFje9296vvmNTeVAfz8aa0rxhd+7AR9bX4n/cU+GxY5JWutKJ33fWV6LKv84PMPOWW6hMMJhEtCbN1MQoK2NhHkiMfkET0pnKSsDPvMZ4HOfA3bsoBS81laav6RmRX19dL+lpST4C6nDqLSpGBgorHELZCFjcc4YexDAGQB/CGAdABMmu7SAc+4G8DGQu0uBJcktM0KhVMR8OYnztjZaMLxeEp7FTF8fLQaZpHXU1dGR89GjlPt55AgtojU1lJeu0MWl1xlE51gAd185hFv7zqLmlhuAr30NqKrKyv03bGzC7jUOVATpuP7HH3SibUTe941rlGwjgzpD0eebAwBjDKUmHQI6Ixg4PDI3Ijrbl/r72+ttwLlzYI2N+MYd6/DjL96AjbW2Rd3vl25eBYNWhZoS2nR1ltcBAIIXLmZl3DlHSmmpraW55+rVlL95esMvhwP4wz+kSPnKlRRNl2hooMDBuXP0fXs7nf5t3EhBlXDKvlLRTEzQPGwy0YZlOa21CyEUoudIcI2MxDljbD2A5wCYAfwAwG4AsyWh/hAk2u9fygAFOUYq2CkpWT5pLZyTOG9oADZtIkvB9FzqREKx4nNR9PdPzzefD8aAG26gzcsvf0kL5O23UxTM6aT7VCAHr46ieawX60e74L/xZmg/8+nsWoTa7di8yo49tlRqwcEr8ubhe8dIBAW1hqLPN5coN+kQSDYicg6Nz3N17ghF4ugcp/QKFQPWD3fQPLoEZyCJm1dX4MRf3on3/vR2NFaYMGYqhU9vRuyi/Kc1C0JaW8rKyLLV7SaRbTZPLvAEZn+PqlQ0R3d3k6BtayMBX5o8VSiU1JbublpXduyg76UOqcuZeJw2bL/6FfD979M6I7hGppHzPwFgAPCPnPMnOOfvA5gtAe7N5Ocdix2cIA9IorSxkaIQhRKJWApOJy0Uzc1kKajTAW+9Rakfb74J/Mu/0PfFQDwOdHbOnG8+H83NqUYh99xDzi3r1lGayJkzuRnvEjl0rh+3dxzFqLkMlffdNTkKlw1UKrCqKtyaJs6PdcubZuAbo8h5SGuA3Vz8kXMAaLCbEExaR/b3jcg2jqsjvmv7+MYyIwxHPqJIcWNjVu7fpNNAo1ah1KQDGENHeR14R0cqB1vJOJ0krktLgdWr6b04Opq5I9jGjRQsOXCABPrq1RQsAAonoNTRQfPnli00D0t2ksuZl18GXn2VTlPq6+nz8LDco1IMmYrzvSCf8+/MdyHnfBhAAEDhmiUXEl4v7UIzZWyMxKk0YaZHIjinLpLFdgQnVfs3N9Mx4+7ddOT47LMU2Skro4r63l55x7lUQiGKRoyPkx1ZpjAGfOITwCc/mUqJ0WqBDRuAK1cUWRj6ac9lbLSqcXDdjbh1fXZSWaZRXY3VicC105UjnS5wGU9a/OOUVhHU6lFhXR6R8zWVFgR0FDkf6JPv5OLSUGpuvI2PkSC95ZasbwpLjVS61VlWi0hwggoolY7LBdhsdGpnNtOmBchcnJeXU5rdlSv0vDY10f0BhSHOEwkKkDQ2kjCvri7uyDnnwK9/DVy6NPs1IyN0mrBzJ/D449S1Wq1O1TgJMhbn1QB8SeG9EMIAlkcoR27efZd2oVMFU3c3HRm98gpw6tR0b9ixMYqO2pJ5kelCfHycrKyK7Q3T3k4TpHS02tJCKRy7d1N+8qOPUprP/v2FWyzq8QC/+AWln9x7Lx0NLwa7nSJV6WzerMzC0N5e3O7rwaee+BT2/3+fw+rKzBq/LJiqKjjUcVSryD5vzB9G93gwN39rAYTc5PUd1C2fyPmaqpQ4HxkYnefq3HFpMDlfco6bhi7T+yXTbpcLQHKo6S2tRpCrSKgqHaeThLWENI+k55svFCm4UFdHARUpcl4IaS2Dg7QuNzfT9zU1JE4L4fRjMfT10evzwAGy5J2J06dJjG/bRqcrRiO9Pi5enPy8RKOFsQHLAZmK8wAAM2NsXq8uxpgVQCmAAiktL2CCwVQ0eOqO/MoVKrQYGaFUjWeeSbmzAPR1RUVqspsqzgG6bbEgWXpJEyVA0Zjdu0mgG40UHb7zTor8FGKxKOfACy/QY/3MZyY398gGDocyC0P376dN5sc+BoNWnTvXkupqqBjDbSWJaz862iXfNBdyexHS6sGZqui7g0qsqbQirlJjQqPHuIzuJZeHaWO0wjOMlWEPcPPNqTb1WaQ06e0eV6kxaK+leV1J772pcE7zZ7o437wZ2Ls31QgtE9asoWi5NJfpdCmLRqXT3k6viZUr6fvaWoqmSykc0Sid2p44Id8YMyE+j5XnuXMkvAMBCghOJRwmEb5+Pa23Ei0tk5154nHgxRdJs7jd2Rt/gZDpLHI+eZttC7j2keS1xzMdlCBDzp+nNztj08V5fz+lJHzlK8B/+k80aUr5wsEg7ejt9pnFuVTQMypfZCrrSG/8qdHgqaxcmSoWnenxX7o097GdnLhclOa0Z8+SG+/MilQYqpTUn3CYIjZbtmS3AHQmks4vO4ypUxU5xXnE7UMw2YCofJlEzpsdFjAGBHQG+Mc9CMfk8f6WIudbBy7DXlVO74scUGJMORL3VNSRWFFy0MTrJXGVbs+q0wFbty5u86LXA1//OlkrSlgshSHOOzpoQyJ1W5bSeqS1WlpjDh9WfjQ9EKCarMuzFCVPTNDGcdMmSj86cmS6C8ulS7QhmfpekZx5pJP699+nQFoiAbz22vybgiIj03fJCyAHlr9ljM16W8ZYK4B/AOWnP7f44QnmhXPg7Fk67quqmizOQyGKftfXk3B3OEiUXrhAk4BUDFpRQblwJtPM4tztLp5C0fZ2KlCy2+e/ds8emlB/85vJ6UKdncC+feSRrsQCFmlMizk+XihS1OPkydz9jUzo7aVJXIpO5RKDASgtRasm9Z441iVft9CYz3etO+hyiZwbdWrUlRoR1BphnAiiayz/aUWjvjDGAxGAc6wMOlHSuiHzousFIqW1AEB7WR3N50pON5QKHmj1AAAgAElEQVTWjvTIebYxm5Uvzvv7aQ1uakr9zGymtMmBARr/kSO0HgWDyksVnMroKGmHQ4dmPrmRGka1tNApUjhMmw8JzimlRTp9TUdy5unqomuOHaPN3L33UrHoBx/k9KEpjUzF+VMgj/M7ALyV9DzXACTIGWP3M8b+FcBHAMoBfADgF1kcr2AqfX0UKW1tpeOywcHUDlOyu6urS12ffnSULs6B6ZGI8fHUYjNX2/Y336SUAqVEciYmgN/9LmWRyDm9ud99l3Lwm5sXVrBlNFJBpNtNOfvRKD3Xr71Gk6nRSAJdadGO4WE6VlzIBmSxaDT0WurooCiZ3HR30+Seq5OCqVRXY1XMC52aptCOsQCcgVnyK3NM3OdH4Jo4Xx6Rc4CKQv06I8zREK7K4DV/OVkMao6EUKdLQFVXm7O/VWZK/V+HEhoSe0pKK7tyBfj5z1M1OvkQ53JHzkMhqsmarS4pHKb1wWabXpBfU0Nr9fvvU1DhgQeoi/Hx46n/KeeUVrkYo4dcIXnXj4+nmiqlc+4crTvV1fR41q2jdB2pNmBwkAT+li0zr8GbNtHjfvNNuv2ePdQldvNm6rlRCIXQWSIjcc45jwK4B5SqsgfASyARDgCnALwC4OsAjCCB/ikup43BcuDMGTryW7uWxHk8nhLJ/f0kWNIjqCtXUiHk2bMkXI3GVFtzqzUVOZdyBqUd/2zC2+ulXe6ZM8BPfwo8/7z8NlFnz9LHu+8CP/kJ8M//DDz3HE0Sq1ZREcpCqa8HPv5xei737aOiW8ZoMr3rrlTRrJIYHqZTlBzkvk5iy5bJaVJy0t1Nr/9cp7RIVFVB63Zhnd1w7UedY/kvTosnOHggcC1yvlzSWgBgTZUVQZ0BpsgErg7lX5xfGqJNaWXABYdFn7kLSQakp7W4g1F677ndQE9Pzv5mRly8SHOk1CzI5aJ1KT2nONuYzST65JIYFy5QBHm2uqR336X18d576blIp7aWxn7+PHD99ZT+s307bWqk1MsPP6Ro8euvU1R9NoaGaP7LBy4X1WRZrZMj4gCJ7qEhChRKwvumm0iTPPMM8LOfUdBMp5u9aLqsjAIsOh05uEjBwdtuI9H/+uvLpllRxqs353wIwE0AHgfwIYAoKNWFAUgAOALgCQC7OefyducodkIh2lVv2EBvGClCLkXM+/un+1urVLSL7+mhD7s99UZKj0R4vRQRXrmSJtjZ8s6lSeGRR2iX6/HI6xGenubz1a8Cd99NE8Fdd1HO4oMPTm+AMR/r1tFja2sjMX7ffZQa09REE9GxY8qxxpIKjbLUEXNOSkroOTh7Vt7Tg2iUXuv5SGmRqK4GOEeLKrVo9jjzL85d3iD0sQiCOgPKTFpo1DnekCmI1ZUWBLRGaBMxdPXnP+f/RA9FER0BF+xWfU7fc+lpLZ5QlOY0nU4ZG2POU2vOkSMkxiSnllwVZQO0XiUS8lm6SvU2x45NNlkAaK04e5ZMBmYqgJU2ckYj2QkCFGCzWil6fvYsif7mZppbZwsAxWIUMPrtb7PzmObD5SIBvW0bndqnr3vnzpG+SDcgKC8nK95160ijRKN026mblXQ+8Qmqj0uvV9BqaZMTDCovGJYjFjWTc85jnPMfcc5vBXULrQJQA8DIOd/FOX+Kc66ws/4i5OJFmgilwgqLhY7QBgbIwmh4eHJKi4Rkq+fxpFJaAJoYJiboDSRNNuXllB82W+S8s5P+bl0d7fxvuIH+7lxpMLmkp4cmkM2bU8eJd91FInopUZzt22n3fs89FH2X2LOHHv877yx15NnB5aL/Xz7EOUA5gcGgvNZu/f30PsinOE+2GW+ZSL3O5bBTdI0sv+6gEmsqLfDr6T092Jvf2o+JaBwHLlPAotLvRG1T3dyCY4mUpqW1uINREuYbNlDkVe60uvFxEsjr1lFw5/z56TaKuUDORkSJBInz1atJOL71ViqCPzxMEeLKSoocz4TDQRt8qa4JSFkL9vVRmuiqVSRUN28msT51AwCQG4rPR1H4uaLr2cLtJtHc2krjPnqU1ptTp0icNzdPX2ebm8n97KGHKGA223MiYTRS4GcqVVX0XJw6pcxaryyz5DAL5zzOOR/lnA/nS5Azxu5hjF1mjLUxxv5sht/rGWO/SP7+MGNsVT7GlXeuXiVx7XCkflZbS+JcqnKeSZyXlFBlNDA5LzndsUXKGbTb6f7Hxuj+0kkkSAyvWpWKkGzYQLtnuQpbTp+mSWPt2uzf97Zt020J9XoSqENDyihOGhqiz/kS5ytX0iI8k2VWvujuptdfvvLNAUoFq6tDsyeVwtUjgzh3j5LFWHAZdQeVWF1pgU9PzWicg6OIxRPz3CJ7HLwyimCEans2IIDKNbndGJp1amhUNMeGonFMRJNBGckdQ076+ujzzTfTvPPRRyQW0yOfuUBOcT48TAGwdeuAW28loX7xIonVn/2M1sD77iPBPRNqNfD5z0/vP9HSQuLU4Ug15tm1izYABw9OvjYcppMKqSFTrmu+4nEK6JWV0eZwyxZKwfnhD2lzYrdTA65ccvPN9Py8/bZy6i1yxKLFOWNMzRhzJD/m9T3PFsm/9a8A7gWwEcBnGWNTjZwfA+DinK8G8I8A/p98jS9vhEIkwtP9ugES44EATRSMpbqyTUWKtqeLOKkRkd9P4txoTE0U8XiqGERicJAmiPRIsslEndAuXJgu5nNNIECTRUtLzlwTZkRq1d3Zmb+/ORvDw/TYcx21kmCMJunBQflSe7q76XWcy/zWmVi7FrV+J0wROlbvduZfnHvGUpHz5eLUImE1aKEtKwUAGIMBck7JE6+fo02wPhrGVivAZptnswRjbHpqS2MjnXbKndrS10dCubQUuPHGVN1SviLncjQiklJaVqygKHJ1NeVDHzxIa/IXvrC4x6/XU0rHo4+mTmJMJkp96eiYXBB57BjpgHvuoe9zbXns8ZAgljZd119P/4OaGkpr/exnc/8/NxppMzQwoGy3oiyQkThnjN3HGHuOMdYDIAJgKPkRYYx1M8b+nTF2by4GmsYOAG2c8w7OeQTAzwE8MOWaBwD8JPn1SwD2spx1JJGJ7m4Sv5IwlJAWiYsXKapuMEy/LUBNHb74xclFTOmR8/QGEpWV9Hnqzryri8SZFIWX2LSJJsx8FalInDtHz0m6F24+qKigRXKm6vV8k69i0HQ2baKFRI4mGvE4LZT5TGmRWLMGJSYtVrkoei5HWovfmdYddBk5tUiYHeWIMxVs4QCGvfkpFIvEEth/kY7VHQEXdaLNYTGoxBO3rcZf3LcB/+szm2HWa+g93tpKJ6j5SGmYCc5JnEt2vc3NqZPcXAs1KWLsy38x8LV6LbOZ/g933EHf3303paIsJVBgsVCkPJ3rrqMT75dfJieToSHKTV+7loJjVmvuI+fSaXopbYhhMgGPP051XNL/Px9s2kRByAMHaM0v0gj6glZwxlgtY+xDAK8CeBRAPVJFoNLHCgCfBfAbxth7jLFcmSzXAUjvfNKX/NmM1yRTbTwApvnKMcYeZ4wdY4wdGy20RjsdHTQBTF0UKiroyCmRmLsTG2PTrfbSjwnHx1OTa3k5TUBTn6OuLooYTJ2IGhtpU5DPnW0iQRGkhob8RY0lGKPH3N0tb6OERIIm6HyltEjo9SmRkG9bxcFBynmUQ5xXV8NSUYZmN50YjPnDCITzm/8bdFJaS0irh928vCLnAFBVYoBfb4Jtwo9hb356MRzqGIdvgv7PG1kQlVZ9bnsKJHnslkZ85dYmPLR9BSz65Mng5s0058jVEM3tpkCMtNYwRrU5TU0pEZcr1GoSiPlOa4nFqM4lPShVVUXR8paW3IhUjQZ4+GESpmfPkvtYPE5pHgAF0HKtYaST81ynK80HY3RaUFEBvPEGWXgqxcY5i8wrzhljdgCHAewEifBRAM8D+CbIleWJ5NfPJ3/HQG4uhxhjeVZJmcE5/wHnfDvnfLsjPW9b6SQSJIwbG6dHSFWqlGCfKd98LrRaEtojI3RcJolctZreCOlvgFCIorTpKS0SGg3l4rW15cf2KBSiI0Wvl1Is5KCxkUSilH8pB+PjtHDkW5wDFNkB8t+USDqdkUOcMwb12jVoDY9BlaBNWU+eU1tCbi+iKg2iau2yjJxXWQ3w6i2whoN5i5yf6/dc+/r2kjhYSUkqiptvqqrkPbWTXFrSA0ENDRRNnS3fOptIdor5ZHCQ5tmpJ8a5xmYjc4PHHqP6p927U2u0w0GR7dk817OBy5VKdZWb0lJKpbn7btogPv+8fKdHOWIhkfMnQZHoMIBvAFjBOf885/wfkq4sTyW//jwoev5HACYANAD4lxyMuT/5dyTqkz+b8RrGmAZACYAZSp0LlMFBEqRTU1okpCOmuSLns2GxpLxz0yPQ0s5cOkLq7qavZxLnAO3w43GKnufy2Kmjg7zML1+mwpk1a3L3t+aioYEWIznzzvPRGXQ2bDZ67s+cyW832e5u2jjKJY7WroVDC9T4aHrJtzgPu3wI6pZfAyKJKpsePr0JtrAfI3kS5+P+VG77irBbnvebhHRq19kpz/F+Xx+JtXyfVkrI0Yiop2fx62s2sNnodCK9X0dlJf3/c+mSJtkoKgXG6KTiwQdps6SEtNIsMqc4T7qcfAZAHMDvcc6fTDYimhHOeZRz/q8APgWAA3iYMZbt7eVRAGsYY42MMR0ozebVKde8CuALya8/A+DtomqG1NFBEfLZhPG2bcDnPrc4wSLZKQKTJ1yHg3amUpSiq4tSV2ZbmKqr6TYHDgBPPUWR7aNHKS/59OnsHEO1tVEOnsFAj/emm/KX9zYVnY6Kg+QU50NDdPoh1wS6bRs5GEiNSHJNKETvhfTW2PmmqQk2sx6NTooP5NuxJe5xw6+jJmLLzUoRACptBngNZpgjExhx5ee5dwZo86mJx1AW9OUl33xOmppoXpbjaL+vj05o5Zp3LZb8R857e+nEYrZ6LjmQ6sJymdoi2Sgqjaoq0jrLSZyDcsgZgBc5579b6J1yzt8A8GLytp9b/PBmvO8YKIL/BoCLAF7gnJ9njH2bMfbJ5GVPA7AzxtoA/DGAaXaLBU1nJxV+zjY5aLWLj+ZIeedq9WSvUenN/9FHlOd19SpFi2crPGSMfE3vvpsm7/Z2qmR/5x0qaHn55aVFejin7mnl5cDv/748qRxTaWyko8Wprjb5Qso3l2uhrKmh//WJE/lx6pGaH0kpNXKg10OzaiVWuSjvvDvPjYi4xwufPinOl5mVIgBU2Qzw6c1g4PCN5Ke3gjNI8amKgBsmLVOGOAfyL058PnLwkCuCDJAoCwZTtT4+X25TKSMROrnOp23rQrDZqPYnV/7fkQidUChRnDNG74GuLnlrvrLMfH5zO0AR8H9bxH0/A+ARUK56VuGc7wOwb8rPvpX29QSAh7L9d/NOIkHR4RMn6EW3c2cqvWT37tz8Tal75tTubhUVJNhPn6ZjzNpaaswzF0YjHTu1tJCYDofp85UrJNAHBjLPi5dob6cjvHvvza9t4lw0NtLmo7Mz/5NYPE7iXE6hClDO/759tIAt9n+7EDgnt4LaWtnFkWHjelQcPAlrOJBfxxbOwbxe+Krp8S/HyHmVTQ9P0us8MJqfLqFS5NwRcMFYrpE3rQUgYVZRQeJ81678/V2pvkZOcW610lwQDFKg6Cc/oefikUdyE6To6aF1Od/55vPBGJ1U5ypy7qbCc0WKcyDVqbq3d/aMggJjPlXTkvz80SLuW7pNy5xXCSbDOb3Buroof9fjoQg2Y8Arr6RSVXJ1lC9FzqfmEBoMVI2u0dA1mU58jKUi/evWUROBtrbFCTjOgUOHqChk/frMb58rysroeWtvJw/YfNLXRwI9l4J4IUgTY09PbsfS309Rok98Ind/Y4GUX0dT3CrnAHqc+SssD7m8iMdi8OuM0KoZbAaFbFLziBQ5B4DIWJ7EeTLnvDLghGGVeeZuhvmmqYkagcXj+SnEBGjO0ekmN8HLN+l2isePUwCov59EWrYFdCRCp79Wq/zz7ExUVpJmSCSyb6UrnQbn2oFnsaxcSa/7jo7UGhQMkmDfsmVylkE0SqmXdXWpjAAFMt9sXgZggnOesT8a59zLGAsl70MwH04nTS7t7akcutpaipCvXk2C9MIFEqUVFbkrwEmPnE8lW7tmg4HeQFeu0OObSeifPk1NFnbtoq6j6dd0dFCU+O678+vnvRDWrwc+/JD+V1O7iS4Ezufe+Eg2XitWTH7snZ30vdwRHaORJryentxG8Y4fJ2HQIv/ev251PTwGCxpd/XjNtRbReAJade5fl64hSuPw602wm/UotlYOC8Fu1iFgMIGDIeF2IxJLQKfJ7XPvDCbFud8Fw4rr5EsjS6exkbpF9vXlz7mov58EjpxzsBRMOnuW1pOdO0l4ffTR7HNhNErzaKauI++9RyL1oYem+5ArAYeDHpfbnX19oHRxrtXS676jA7j9dvrZ/v0UAGxrAz71Kfp/h8PAr36VOvWprCQbYKWlKWF+cW7D0lxOfAAUbacoK5yTiPnNb2iiU6tJiK9aRR/SxCPR2kouKIlE7hYEu50m21xHBtasoTfS8PD0Y+FIhPLJw2Hgt7+liXf3btqUaDQ08ZaUkGhXGjt20P90/34abyY7895e4D/+A/jSl1LdWiUmJuh5OH6cNm9Tq/U7O2mC0Skg77ihgVKxIpHcjCccpgW4tTXVRU9GTHotPPWrsKLjEhCLoccZRLPDMv8Nl4h3mKZmn84ExzJ0agEAjVqFcpsJAZ0BtokARv1h1JXmzuotGIlhIpqAJh5DdcgN/SqFpDesWkVrQmdnfsR5MEjWrYsJQGQTaY08d47Wrl27KPjz7rupzcNUpJTKL35x4acM3d10MnH99fIHQGYjvVlgLsS5xaKM9WU2mppIUzidlH3Q1kZNmtragJdeAu6/n/TE8DBZUkoR9LfeIr/4fDcvnIf5trwaUM75YuEA8nTGVoBwTmJscJAmlccfpxdQS8t0YS6hUuU2x9piAb7xjdxP8M3N9FiuXJn+u9OnyYnj4YeBO++k3PKf/Qz47neBf/kXciXZuTN/x7eZoFbT/9BgAF59lR7HQunspMjH0NDkn/v9wI9/TEeqdjt9nD2bKqh1uWhCktO1JJ2GBtpA9k91OM0SZ8/SxJq+OZGb1WugTcRQ7xlG52h+ikJ9IyTO/XoTKpZhvrlElS1/XufOQCqlxaxhYEqJuEl1QPkqCpXe23Knd5hMtI4wRoJLrabGTEYjBXFmYmSEossLbZI3MUFuY+XlwC23ZG/s2UYKrOXCtUdpNoozIa1/585R2mx1NXDffcADD9BG8plnUqmQra200fqDPyBDibVr5R37DCgsJ2CZoVKRBeAXv0g2gCaT3CMi8nFkZzRSpPfq1cmuLdEoRYcbGmji37wZ+PKXKYXlllsoUnP99fJHbObCbKYJwOcjZ5uFMkht4Kd51fb0kMh/8EE6Ur3uOppsJBEv2TfO5nufb6Sj7t7e+a9dDMeP08RbW5ub+18ElvXNiKo0aHQOoGMsP77LgTEX4kyFoNawLBsQSeTT61wS59W+cRi1avnFaTpNTXRcHw7TfNHbu/imNIHA3P7hfX0khOUuhpX8xnfsSM0HOh2ZFXR1TQ90cJ4qbjx8eGHuHh98QCcF99yjzHQWCbWaBHouikKVaqOYjtVKpwfHjtF7QEp7bWoigW63A7/3e5SdIMEYOZwp8ERgISHYcsbY24u8f5HSMh9VVVT0uRxZu5bSP8bGUkVFZ87QwnD//anrJNeXQqK2FrjxRso/l4p65yKRSC0kU8X52BhNMtJpxrp15B9/7hw5lUjuMEqZPHU6evxS985sMjBAm5iPf1wZub5JVlaX4XRpFRpd/egczb04n4jGcaVtAH69CWBsWUfOK20GdBssWD3ei2FPbsX5eJo456Wls59wykFTE+VFf/e7qbqlvXuBW2/N7H6kE914nEwAZnqf9fXRe1wJp5cPzWDMtmUL9dU4fpyipxJ+P51ONjdTfdf58xQAmo2xMTrJ3bJFdleoBVFbS2vogQMU8MuG6AyF6EMp68tcNDXRycGNN1JaqURjo3KCVwtkIeJcB+C2JfyN4mn+I8guq1dT/t+VKyTOo1GaUOvr5bXnyhZScWhb2/wpGGNjtGio1RQVT2dkhHb90kJoMNDG5tIlypXr7QW2bs3NY1gsDQ1UvBwKZbfd84kTFL2aa0GVgSaHGa+U1aLJ2Y/ergEAW3L2t1yBCB566hC2XukHSzYgymWetdKpshpwTm+CmifgGhoHkLtF2JUU5zW+MURWKewofMUKmnPUahKSx44tLrVsYCCVGtHXN71YbmKCorM33rj0MecKvZ7GPdX3WypsvO46ioYfPkx1XDNtMjgna1y9noRuISBtxI4fp1Ppu+6aO0U1GqWo+GyOO05n6vRXCb1E5mPrVloflJTyuEjmE+c/ycsoBMsTk4mOhQ8fpt2+Wk0Rn49/XO6RZYeyMhLVCxHnUkrLmjW0WYnFUrUFY2PTvVtbWsgR5q23KMKltKhAQwNtTHp7s5fPF4nQ62TTJmV15wPQVGFGVxkdqyeuXAVwb87+1juXR9A24set4QAGrRXY1WTHg9crKL0iz1TZ9PAm7RR9w0vxL5gfZyACSzgIaziAhJJSWgCaLx59NPX98DClxGXK6dMUcWWMiiCnivOBARKuSg+gVFTQ3BuNptJR0l1Hdu2iE4LZouft7fT83X57dgMMuUSvB+64gzZp+/dTs7+vfW36+MNh+j8fP06blEcfnZyixTlt7j74gJ67e+5R/v8boJTSHTvkHkVWmFOcc86/lK+BCJYpe/cCFy9SNCYUopQNpRRZZYM1a2jzEQzOXVMwOEi/b26miLjTSflzgQB9pB/RATRRlpaSkNdqlTdxVlfTuLq7FyfOo1GyvLr7bjpSBiiNJxJRZFSkvsyEkNmKcVMJSvu74JuIwmrITX7quD8CcA5LOIjWHSvwxFd2QqVSTopPvkn3Og+O5rZLqDMQQZWPNgAqpc9TNTVUPB0IpPzA5yMYBC5fpvecJM6n3r6vj9LslJ7mUVFBItPpTEV93W4KAtls9FFTM3P0PBYjxxe7PTX/FBL19ZQa+uyztPlIbxjY10c9UyYmKOgzOkoi/OGHU9ecOkUGBKtXk9hf6OtHkDVEQahAXioq6CjuzjuBT34S2LNHUbnES0byqJ/PRWFwkBYKSYRLeedScc9US0bGUnn4UgMGJaFW0yZrMZE7gARCby853kj3cfw4PQ9K24gAUKsYVtrN6CyrQ51nBF39uWuI4w5FYIyGoeYJVNQ6lrUwB4BKmx5eA4mHUI67hDoDEdT4xhBnKujrlVOQPCOSeJ5aFDkX585R/cuWLfSRSNDP0unvT22+lczUuRSgyHlpKc2fjJHrl9dLAZF0Tp4kIb9nj/Lm1oXicKRy0CXTBc7JyUSnIzOKT38auOEGmmuleTYQILHe0EBrshDmsiDEuUCQSyorKUJz9ers14RCFN2pqaFUGJVqujifKSdw0yaaZJXUJTWdhgZa4N59lxbAhcI5LY5lZVRI+8IL9Pz195NTj0I3b00VZnSV10LNExg5ezlnf8cTisISCQIA9OUKbQqSRxxWPaJqLUJaPbjkxJEjJHE+YilHeYlC3LVmQxLnUsqcxJkzlJoylUSCUh1WrKCIcXk5fS11nQToRGtoSFkuNbNRWkpzaXoNz1TXkaYmEvFHj6YEbDBINoxNTcpLF8yUzZtpQyI5Z7W10Zpy002p18fmzSTADx2i5+Ddd+n/vHevYufa5YAQ5wJBLmGMouddXZTnNxNSZKumhqI0ZWWpBWV0lBwhZsp5tFiA//yfKRVIibS00NhOnACefhp47TU6Sp0PqSBtyxbKhYxEgOefp5xaBR8xNzrMGLaQQdVYe45sJAG4g1FYwyTOjRUF4KCQY8pM5Ejh05uh8noQT+TOg8Dlm0Cl34khawXKzMqzX5uEwUBzSbo4D4WoCP/w4enXd3bSJjq9uHzLFvpZVxd9PzhIQl2Bp1fTUKlogyEFOhKJ6X7dUvR8fJyEKwC8/z6ltezZk/8xZ5u1a+l1cPo0Ce8PPqDnJL2Bn1ZLz0FfH/3+4kWKpueqC7lgQQhxLhDkmjVraGHo6iKhefAg8POfp+zOhoZSfqsARXKkBWVkZPZKekDZR656PeU9fvnLFPG+coW64UpRuNk4dYpuu24dnTw8+CDdZuNGRRdmNVdYEFVr4dOb4esbnP8GiyQ9cm6sEAuoVq2C1aCBV2+GZSIAb2iR3t4LgA8PQ5uIYdBqh13p4hygDX+6OO/uJpEmFXWmc+YMRVCbm1M/W72afrZ/P/Dii5QSwZiiegzMSUVFKtDh89E8MrUF/dq19LPDh2m+PXeO3FyKQZxqtXTC2tZGQZLxcSqEVU2Rfq2tFOw5fJhOenfulGe8gmsIcS4Q5JraWir2PHqUupQdPUoL5m9+Q04rg4O0EEit6CsqKFoVClGkZy5xXgiUlFAU6o47SBwcODD7tX4/ifiWlpRH74YNwGOPTfYrViBNDsrNHDeVwNc7Q9pAlvCEKHIeZypY7fP45y8T7GYdfHozrOEgxv2znFBlAf0w/V+HrBUoLxRx7nSmTqyk2peJCfq5RCyWKt5O3/Cr1fTeLSuja1QqEnIKc0uaFWkuDYdTTi1T/bpVKooUDw9TEbrBoGybyEzZvJk2JVKB60wnrRoNpbowRu40Sq8nWAbksA+8QCAAQJN/czM5JzgcFE32eoF9+0ioDg5SdF1CKmS6coUm1anFoIVKaytFbo4fn90FQSpemvo7pTtjANhUWwKdRgWX0Ya6oTb0u4KoK8t+XrI7GEVNOIiAzoQSUwEIxDxQZtbBqzdDF4/C4/QAVdas/41QJA7L6BACWiN8BjNKC+G5Ty8Kra+nor+GBspB7u+n9yFAkfR4fGZP7A0bJgR/0gkAACAASURBVKdBFBLS4xsfT3UGnRo5B+hU7sMPKbp+xx2Fs/lYCOXl9D/v6UkJ8JlobaU8e1EAqgiEOBcI8sEtt1BxUXMzifW6OorUHD9Ov0+3JZMWlIsX6XOhR87T2b2bInZvv02OD+mNLeJxEuerVlF0a6724QrEqFNjZ2M5xvtKoE3EcOhEOz6ztzXrf8cTisIaCcKnNxaGQMwD5SYdupJ2it7hcWBD9nKiY/EEvvrsMbxzeRRf8I1j2GpHqUkHdSG45KQXhcZiVOi3bRuJ1YGBlL93dzfNS4WQS54JUqBjfJwi5xrNzF1dNRqam9raSKQWG7fcQkX16UGgmRDCXDGItBaBIB+YTDQxpuf67d6digini/PSUlos+vvp80yRnkJFpaImU1rt9KK0CxcoD//66+UZWxbYs9YBl9EGADhzqj3r959IcHgnorCEg/DrTLAZRHwFAMrNumt2isHh7Hqd7zs3hHcuj8IUCaEs5EWfrfJaEariMZsph3hwkOxJNRqKjtfWTu4e2tNDc5CUWlcslJTQYx4bo8i5ZKM4Exs3knXg1HzsYqCmhtYb4b5SMBThq1AgKBBUKloMPvGJyU2GGEtFzysqim+xMBjIEaKtLZX3mkiQWK+unrvdtMLZs9YBZ1Kcd5zvRDQ+T/FrhvgmYuAJDkskiLjFBo26yF4bi6TcrINPTylEobHseZ1zzvG9A7TJqvWSremAzQGzvoA2RTU1FCW/fJneWxoNiXO3mzbDoRCd4jU0yD3S7CPNpWNj051aBAIFI2Z2gUBODIaZO2hKYr2YUlrSuf562nQcO0bfX7oEeDzkElDA0Z3VlRaUOkoR0uqh97pwqje7vtvuUASGWBiaRBwosWX1vguZMrMOExo9ImotIlkU5wevjuHiIHn013tGEFVpMGIpw+b6AirErakhcer1pny7JbeVgQGy0OO8oDfFcyK5X3k8xXUKKShqhDgXCJSIFDkvVnFuMpEjy/nzVIR15Agtouk2bgUIY+xa9Lw86MHBK6NZvX/yOA8BAFRCnF+j3KwDGINPb0LMmb0N0Q8OplKTPlURx427t+D3b27Cf9k7T+6ukpBS5hhLCfCqKnJi6e+nfHOtlk6tihG7nRoLJRLFYY8oWBYIcS4QKJHa2sLyE14M27fT51/9igq2CjxqLrGr2Q6nqQTlIe+1qGu2IBtF8sfXlBVQ9DbHlCdzwL16MxJuV1buMxJL4MN28sjWxyPYU5LArXdux7cfaEGVrYDcPCRxvmIFbYoBSm2prqbIeXc3/U7JPROWQnrKoEhrERQIQpwLBEqkrg742tcmu5kUG6WllNIzMkKL5kzpPQXIKrsZLqMNxmgYo0PZS7EAAHdaAyJtmTiil5C6dfr0ZkpfyAIjvolrfXpaYx6UGDSFmZdttQLr1wM7dkz+eW0tWSy63cWb0gKkTiEBkdYiKBiEOBcIlMpysLXasYNyz2+8sWgKX+vLjBg3UVQ7ODAMPrUT4xLwhMipJcFUMJaKyLmE1K3TazAj4Q9SJ94lMuSZuPb1xqiLIsuFaDXIGPDoo5RGlk5dXapLaDGLc6uVGprpdKmTA4FA4RRQyblAICg6HA7giSeKqulHuVmHkI2Oz/UeFzyhaNb8yD3BCKyRpI2iuchs75ZAeuQ8FI1T9HyJ9RpD3pQ4bw45gdpVxdU5UUqZM5uLOxebMWrkFosVRdqcYHkgxLlAIJCXIhLmABWFllRXIKrSwB70oM8Vyp44D0VREXDDZbRinamIhOISsRk00KgYvHozovEEwqPj0C9VnCcj55p4DCtCTmDlnmwMVTkYjRQ9r6wsftF6552pUwKBoAAojnNkgUAgUBD15Sa4TDZqWuMKZe1+vd4g7EEPhqx2lBqFOJdgjKHMrKOccwC+kaU3IpLEebVvDFadujhTPx55BLj9drlHkXvKyyfnngsECkeIc4FAIMgy9WUmOI22ZOQ8mL07HhqCiicwbLGjRIjzSZSbdPDrjIgzFfxD40u+Pymtpd47ArNBm+rmW0wwVvxRc4GgABHiXCAQCLJMfZkRTlMJrOEABkeyZ6eoGRoAAAxZ7SgRaS2TkLzO/XpTVrqESpHzOs8o9HU1RZd+JRAIlIsQ5wKBQJBlpMg5ALh7B7N2v4bhIfj0ZgR1RhE5n0K55Niit2BiNDuR85KQD3XeEZjWFVDTIYFAUPAIcS4QCARZRoqcA0C4ty9r92seG8aQhXJns1VkWiyUmWmz4tObEHUurRFRIsEx7J3Azd2nEVOpUXJHkRWDCgQCRSPEuUAgEGSZ+jIjXEYrxsxlWHn2KHgoC0WhgQB0XjeGrCTOReR8MuVJa0mvwYyYxwfE44u+L2cwArtrFGvHunGpcRNM5aJ5jUAgyB9CnAsEAkGWKTfrYNBpsX/1DmiCAQT3vbHk+wx39yKW4Bi22qFRMZh1RdpufZGUm6TIuRkTkSjgXXyu/5A7hFu7TiKgNWJ407ZsDVEgEAgWhBDnAoFAkGUYY6gvM2LYWoGTtevw66dfxfMvvLekbqHBzh5wMAxbylFi1IIJl41JSI2IPHozQpEEtaVfJN7T51HnHcFHDa2w263ZGqJAIBAsCCHOBQKBIAfUlxkBAIdWbsaVsAaXfvgcfnGoc1H39cb5ITzz4gcYN5UgqtYKp5YZqLKRm4pPb4YzEKEuoYuBc2jeeRtOow3nqptRYxMuLQKBIL8IcS4QCAQ5oL7MBACIqrV4c/UOlIW82P+jl+EORjK6n15nEN947jjC3T0YslYAAGpLjFkfb6Gzub4EGhWDT2/CWCAC7+Do4u6orQ2xoWEcbmgFZypUlQhxLhAI8osQ5wKBQJADdjWnOhL2ltego7weazvO4v/8+nRG9/PkgTaYAj4Yo2EMWe1YXWnB/3WnsPabikmnweb6EiRUagR0BrRd6V3cHR0+jHGVHlft1HSoWkTOBQJBntHIPQCBQCAoRu5tqcbTX9gOzoFYIoG//L4Lnz+1D2d+tR8Dd7egtnT+6HevM4gXj/Wh2U++3d/86l7cdHNLrodesNzYZMeJHje8egu6O4dwfaZ3MDaGkRPn8LZ1JRIqKritEZFzgUCQZ0TkXCAQCHIAYwx7N1Thjo1VuHtTNRpbmnGlYiW2DFzG+6e7F3QfTx5oQyzBUe0bR5Xdil071+d41IXNjU10WuHTmzDUPZTx7fc9/Qp+erQPr+vrrv2splSIc4FAkF+EOBcIBIIcwxjDXZuq8FFDK7TxGIZ/+9a8t4knOH5zmrqL1npHccOujWAacdg5F9tWlkGjYvAaLAiOOeHyhxd8231HO3Bu30FccaxESEeC/KZmO9ZVCbcWgUCQX4Q4FwgEgjywe60DTlMJLjlWAUeOIu6Z24e7fdQPXzgGSziIxogHzTddl5+BFjBmPeWd+/QmqHkCx871TLvm+SM9+PT3PsTr51KR9bYRH/7tyVegi0dxsmYdtq0sw8++uhP//thOYVkpEAjyjhDnAoFAkAfWVFpQZdPjo4ZWRKMxdLz29pzXn+ohn+5GZz+qSwxgGzbkY5gFz41Ndnj1ZgDAL988i7YRH/761fP45fE+eEJRfOuVczje7cIfPX8CoQh1EX3pWB829l7CgNUBS2MDfvyFG3BTcwVUKiHMBQJB/hHiXCAQCPIAYwy3rnHAY7Ri0FqB3sNn5rz+ZC+J8yZnH8rqq4CKinwMs+B5YGsdxmz0XI1dasPd/+c9/NuHXfjvL57Gf5zoQzROjaCicY79F4cBACM9Qyid8OFiZSP+aO9q4SMvEAhkRYhzgUAgyBO3riHR2FVWg7G2bsDvn/XaU71u6GJRNLiHYL++FRDpFQtiXbUVX72nFU6jDbXeUcQTqa6sT78/uQnUr072AwBC3WS7OGwpR0O5OX+DFQgEghkQ4lwgEAjyxC2rJXFei0HvBKKXr854XTASw5VhHxrcg1DzBBpEvnlG/OHtzf9/e3ceLldV5nv8+8twMpyE5BwSMpCQEDpimGQICIgYLgiItjgD2hD0emm1oaUVvHDxatR+tGmf1u5+WptG8UFEJmlRGkdm7SugDGGSQMKchMwTYcj43j/WKk6dyq5z6iQnVXVyfp/n2U9V7bX23m+ts2qfd+9aexct++zNnuuWo9j6xvyFq1/rVO/up5azcv0GNi9axBYNYGXraPZqH17vcM3MOnFybmZWJ7uPGMIeI4ewvLWNVwYNYe2jTxTWe2zROrZsDfZZtZARo0cyYvo+dY60bxs0cADn/NVxzBjdwuHDNlWtt2Vr8OP7XmDEqhWsbB1Ny5AWxoxoqWOkZmbbcnJuZlZHE0YNBYnn2ybw+rynYOvWberMfXE1iq1MXb2YwW/eFwZ4V91Texy4L+89eCLXnDiBoYOrt98P/vsZxq1fxbLWdia3D/PdWcys4frUHl9Su6RbJc3Pj20FdQ6WdI+kxyU9Ium0RsRqZlZkXP45+OdHT+CVNS/DSy91FC5ZAosX8/ALa5i4bgXDNm1g98MObFCkfdyoUTB6NIMWvshBe47uVDRySMf94reuXsPQzRtYOqKdyW0e0mJmjdenknPgIuD2iJgO3J5fV3oVOCsi9gdOBv5Z0uiCemZmdTd+VEdyvn7jFnj66VSwbBlccQVcfjkH/PSHvP3ZB9miAUw+/KAGRtvHTZkCzz/PIZNHdZo96817MDH/HcauXw3AshFtTPZ4czNrAn0tOT8V+GF+/kPgfZUVIuKpiJifny8GlgFj6xahmVkXSsn5ay1DWTJ8NCxYAJs2wY03QksLvPvdvBBDGLd+Fc+3TWTP8T63sN2mTIFXXuGI3ToPHdp/4m68ZXJq13HrV7JVA1jR6uTczJpDX/st6HERUfoOeAkwrqvKko4AWoCnq5SfA5wDsNdee/VimGZmxcbnYS0AC0aNhxdfhJtvTmfOzzyTdXvuxbX7LmPItA0MahnMv7T6AsXtNmUKAAdvTb/GqtjKtFWLOGBsuvvNrx5bwh6vrGbV8FFsGTDQd2oxs6bQdMm5pNuA8QVFl5S/iIiQFAX1SuuZAPwImB0R215xldZxOXA5wMyZM6uuy8yst5TOnAM8MXwP2LQEHn0UjjkG9tmHxUtSIrlh8BD23L3VFyjuiPZ2aG1l95VL2Kd9NNPvuY39Vz7Pwc9MYcCMwyGCPdav4tn2PQGcnJtZU2i65DwiTqhWJmmppAkR8VJOvpdVqbcb8Avgkoi4dyeFambWY+Vnzh8fsBsMH56SyOOOA2BR2b2492wbVvf4dinSG+POvzdyHfMGrGTqkfsy4pGHOPDoo9lt46sM3/Q6y1rTvQUmub3NrAn0tTHnNwOz8/PZwM8rK0hqAW4CroqIG+sYm5lZt8rPnL/08ka+PuFtfPT16cxb/goAi9d0JOcTRzlZ3GFTpsDatUxb+hynfH42+13wKdi0iZFzH2Bmy+sALBvRzpgRLbQOabrzVWbWD/W15PwfgHdKmg+ckF8jaaak7+c6HwGOBc6WNDdPBzcmXDOzzoa3DGK3oSkJ3Lw1uPzxNfxh4XrOu+YhNm/ZysI1PnPeq6ZPT99OnHwyHH007LEH7Lcf3HcfRw98mUAsb21jkm+jaGZNok+dJoiIlcDxBfPvBz6Zn18NXF3n0MzMajZ+1FDWvb6+07z5y9Zzw/0LOw9rGe3kfIe1t8OFF6YhLiXHHguPP87hyxfwk+Gj2DxwEHuPaW1cjGZmZframXMzsz5vfJXhKt+69SnmL+1I2ic6Oe8dlRfVjhsHM2YwY9xIWqdOYsKooXz8bVMbEpqZWaU+debczGxXMH63IYXzV6zfwIr1G9547QsUd6Jjj6Vl3jwuPudELjrsMN8Vx8yahpNzM7M6K79jSzUSjKuhnm2nCRPgb/4G2tqcmJtZU/GwFjOzOqsc1jL7qCm0DOq8Ox43cug286yXjRkDAwc2Ogozs0685zczq7PxozoPa3nnfuN5x5vGdprnO7WYmfVPTs7NzOps7IjOw1UOm9LGew6a0GmeLwY1M+ufnJybmdXZvuNHvnGbxPcfsifDWgZy/Ixxneps3LylEaGZmVmD+YJQM7M6axk0gFvOO4aHF67hyGm7AzBiyCCmjWnlmRXpl0KPmT62q1WYmdkuymfOzcwaoK21hVn77sHQwR0XJF525mFM2X04b5k8mlMPntjA6MzMrFF85tzMrEm8adxI7r7wuEaHYWZmDeQz52ZmZmZmTcLJuZmZmZlZk3BybmZmZmbWJJycm5mZmZk1CSfnZmZmZmZNwsm5mZmZmVmTcHJuZmZmZtYknJybmZmZmTUJJ+dmZmZmZk3CybmZmZmZWZNwcm5mZmZm1iScnJuZmZmZNQkn52ZmZmZmTcLJuZmZmZlZk3BybmZmZmbWJBQRjY6hKUhaDjzfoM2PAVY0aNt9kdurZ9xePeP26hm3V8+4vXrG7dVzbrOeaVR7TYmIsUUFTs6bgKT7I2Jmo+PoK9xePeP26hm3V8+4vXrG7dUzbq+ec5v1TDO2l4e1mJmZmZk1CSfnZmZmZmZNwsl5c7i80QH0MW6vnnF79Yzbq2fcXj3j9uoZt1fPuc16punay2POzczMzMyahM+cm5mZmZk1CSfnZmZmZmZNwsl5nUj6sKTHJW2VNLOi7GJJCyQ9KemkKsvvLem+XO96SS31ibzx8vudm6fnJM2tUu85SY/mevfXO85mIWmOpEVlbXZKlXon5z63QNJF9Y6zWUj6pqR5kh6RdJOk0VXq9ev+1V1/kTQkf1YX5H3V1PpH2RwkTZZ0p6Q/5/3+ZwvqzJK0tuxz+qVGxNosuvt8KfnX3L8ekXRoI+JsBpL2Les3cyWtk3R+RZ1+378k/UDSMkmPlc1rl3SrpPn5sa3KsrNznfmSZtcv6iwiPNVhAmYA+wJ3ATPL5u8HPAwMAfYGngYGFix/A3B6fn4Z8OlGv6cGteM/AV+qUvYcMKbRMTZ6AuYAF3RTZ2Dua9OAltwH92t07A1qrxOBQfn5pcClVer12/5VS38BPgNclp+fDlzf6Lgb2F4TgEPz85HAUwXtNQu4pdGxNsvU3ecLOAX4FSDgSOC+RsfcDFP+bC4h/aBN+fx+37+AY4FDgcfK5v0jcFF+flHR/h5oB57Jj235eVs9Y/eZ8zqJiCci4smColOB6yJiQ0Q8CywAjiivIEnA/wBuzLN+CLxvZ8bbjHI7fAS4ttGx7AKOABZExDMRsRG4jtQX+52I+G1EbM4v7wUmNTKeJlVLfzmVtG+CtK86Pn9m+52IeCkiHszPXwaeAPZsbFR93qnAVZHcC4yWNKHRQTWB44GnI6JRv3DetCLid8Cqitnl+6lqudRJwK0RsSoiVgO3AifvtEALODlvvD2BF8teL2TbnfjuwJqyBKKoTn/wdmBpRMyvUh7AbyU9IOmcOsbVjM7NX/3+oMrXdrX0u/7oE6Szc0X6c/+qpb+8USfvq9aS9l39Wh7ecwhwX0HxUZIelvQrSfvXNbDm093ny/usYqdT/YSV+9e2xkXES/n5EmBcQZ2G97VB9dzYrk7SbcD4gqJLIuLn9Y6nL6mx7c6g67Pmx0TEIkl7ALdKmpePnHc5XbUX8O/A10j/7L5GGgr0ifpF13xq6V+SLgE2Az+uspp+07+sd0gaAfwncH5ErKsofpA0FGF9vi7kZ8D0esfYRPz56qF87dl7gYsLit2/uhERIakp7yfu5LwXRcQJ27HYImBy2etJeV65laSv8AblM1JFdfq07tpO0iDgA8BhXaxjUX5cJukm0lfxu+TOvda+Jul7wC0FRbX0u11GDf3rbOA9wPGRBx0WrKPf9K8CtfSXUp2F+fM6irTv6pckDSYl5j+OiJ9Wlpcn6xHxS0nflTQmIlbUM85mUcPnq1/ts2r0LuDBiFhaWeD+VdVSSRMi4qU8LGpZQZ1FpDH7JZNI1wvWjYe1NN7NwOn5Tgd7k45s/1heIScLdwIfyrNmA/3tTPwJwLyIWFhUKKlV0sjSc9JFfo8V1d3VVYzDfD/F7fAnYLrSXYBaSF+N3lyP+JqNpJOBLwDvjYhXq9Tp7/2rlv5yM2nfBGlfdUe1A51dXR5rfwXwRER8q0qd8aUx+ZKOIP0/7pcHMzV+vm4Gzsp3bTkSWFs2PKG/qvptsvtXVeX7qWq51G+AEyW15WGhJ+Z59VPPq0/780RKkhYCG4ClwG/Kyi4h3QnhSeBdZfN/CUzMz6eRkvYFwE+AIY1+T3VuvyuBT1XMmwj8sqx9Hs7T46ThCg2Pu0Ft9SPgUeAR0o5oQmV75denkO4i8XQ/b68FpPGFc/NUuuOI+1fndtqmvwBfJR3UAAzN+6YFeV81rdExN7CtjiENK3ukrF+dAnyqtB8Dzs196WHShchHNzruBrZX4eeror0EfCf3v0cpu+tZf5yAVlKyPapsnvtX5za6FngJ2JTzr/9Jug7mdmA+cBvQnuvOBL5ftuwn8r5sAfDxeseuHISZmZmZmTWYh7WYmZmZmTUJJ+dmZmZmZk3CybmZmZmZWZNwcm5mZmZm1iScnJuZmZmZNQkn52bW50m6S1LkHxOyLki6MrfVnEbH0h9ImpXb+7leXm/kaep2LOs+YNbEnJybWa8o+4d/V6Njsb5D0lRJcySd3+hYzMyagZNzMzNrpKnAl4FdNTl/lfQDc083OhAz6xsGNToAMzOzXVVE/BF4c6PjMLO+w2fOzczMzMyahJNzM9vpyi/YlDQsjzF+UtJrkpZJuk7S9G7WcbKkOyStlbRO0r2Szqxx+y2SzpX0e0mrJG2Q9LykH0iaUWWZNy6akzRU0lckzSuL+VpJb9rJ2x0o6XxJD0t6Na/jFkkzu9nuWyX9V66/XtJcSZ+V1O0+X9IASWdKulXSckkbJS2WdL2kt1ZZZk6O+cr8erak+yS9nP9Wd0p6Z8FyzwF35pdTyi5yLE1n1xDvJbnu/d3UOyPXWyZpUNn8SZIukPRrSfNzO6+T9FD+m4+usr5OF3pKepekX+X1by2Noe/qglBJI/Nn4gZJj0lak/vXAkmXd/eZKFvPAfkztETS67mf/l9JQ2pZvso6/1LSz/M6N+b39V+STtredZpZjSLCkydPnnZ4Aq4EAriroOyuXPa3wIP5+euk8biRp5XAPlXWfWFZva3AamBLfv1PZes/u2DZCcDcsuW3AOvKXr8GfKCL9/MN4J78fAOwtmzZV4Bjq8S8o9v9e+DX+flG4OWKZY+qst3Tgc1ldVcDm/LzG8vWP6dg2ZHArRVtXf5+twDnFiw3J5dfCXw/P99csOwHK5b7E7CqrHxJxXRaDf1u77JtvKmLejfnOt+pmH9j2fIbcj/cUjZvATCpYH2zcvlzwOfL2mt1fu/nV9YrWMe5ZdvZnLe9oWzeeuCEKu+nVOejuV7k9i5f/h5gRBd9rKgPDAauLltHab3lry9t9P7Gk6ddeWp4AJ48edo1JmpLzlcDzwInAQNJ3969HXgxl99QsOwxOekJ4EfA+Dx/NHBpnr+GguQ8Jxp/zGW3AUcBg3PZBODbdCTZ+1R5P2ty+Zllyx4MPJDLlwBtO2G7q3Oy9hGgJZcdBDyay/9Y0Fb7kBL3AH4DTMvzhwOfywlgqa3mFCx/Uy57ADgRGJrntwGXkA4StgBvq1huTlnMrwGfAobnsr2Bu3P5YmBQxbKzqJK89qDvlQ6evlylvI2OpLUy9q8B5wHTgQFlf793lP0Nf1GwzlLcr+V2/Q4wLpcNJSf0Xb0/0oHU3wOHl/2NRRqjXkqQlwGtBcuWEuU1Oc4D8/wW4Gw6Dnwv7+KzWtQHSn1zPvDh0rZJB26fpuMA84xG73M8edpVp4YH4MmTp11jorbk/FXgLwrKP0jH2fSWirLbc9kdgAqWLZ2pLUrOP5nn/46cHBcsf1mu829V3k8AHytYbgywIpd/cSdt95iC5Q4rK9+rouyKPH8eObGuKP9i2bJzKspOKFt2VJWYL8p1bqmYP6ebtppIR3J8bEXZLHY8OT+vFHuV8tLf49miPtTFettJyfFWYGqVuAO4pot1bNf7IyXppW8xZheUl7a9FGgvKD+bjm8kKvtJqY9V9oHp+b0uAyZXiev0vOxj2/v38uTJU9eTx5ybWT3dGBELCuaXhhwMAf6iNFNSO3BcfnlpRETBsl/vYnuz8+O/RMSmKnV+nB+3GROdPQ9cUzkzIlYA/5FffmgnbPf3EfHfBdt9AFiYXx5Qmi9JwAfyy29HxOsF6/xn0gFSkVLM34uItd3EfJykgQXlL1DcVotJZ3c7xdyLricloftKOrSg/Iz8eF2VPlQoIlYBfyAlykd3UfWbta6zB9sO4Bf55du6qHpZjrPSVaR+MoCOftGds0jv9fqIeLFKnRtJB1r7S5pQ43rNrAd8K0Uzq6c/Fc2MiE2SlgHjSEMQSg4hJQtbgW0S1bzsM5JeBCaXz88X/R2RX/6HpO9UiamUZE6uUn53Fwnd3cD/AQ6Q1BIRG3txu4VtlS0CJtG5raaRhvqU4tpGRKyX9ABpKFGlUvL5RUkXdrFtSMNkdiedYS13fxdttSg/tlUp324RsUzS7aShOB8lXdcAQE4gZ+WX2xw45DpHkIbiHE1q19aCahOrbP414OHtCjxtexLpzP8JpGFJI9n2Zg3Vtg3pW6ltRMRWSb8nHZgUHbAUKfWB2ZI+3EW9wflxMvBSjes2sxo5OTezenq5i7LSmd7BZfPG5se1EfFKF8suYtskt500/hZSItmdYV2su6vtQkq028hDDHppu9vbVpDGdldT7f2UzoIW3p2kwPCCeT2NuTddQ0rOT5N0YdlBwmmkZPexiHi0ciFJFwD/SDoIhHQGfjVpfD3AKNIY8qKEHWBlRGzdnoAlvQO4BRhRNnstHW01DNiti21Dbf1zbBd1ypX6wMg8daeoD5jZDvKwFjPbVZXv3w6JCHU39fHt7qhS3O+vJeaIeK6RwRb4KSmpnQQcWza/NKRlm7PmkvYnXVQs4N+Avsjd9QAABSFJREFU/YEhEdEeEeMjYjxpGAd0JO+VtmxPsJJKd0UZQbpo+FhgWESMLtv257rZdm8r9YG/q7EP3FWnuMz6FSfnZtbMlufHUZK6OktX9LV/6ZZ4AHvtQAxdDSkolZXOtvbmdntqednzWmKutDQ/1jPmXhMRL5POQkNOyCXtQxpiFMC1BYt9kPR/8DcRcV5E/DkiKpPtcTsp5KNIBxKrgFMj4vcF1wnUsu1a/tbLu6hTrk/3AbNdhZNzM2tmD5ESqwGkWypuQ9LeFCQT+ULM0g/TvGsHYnhHDWWPRcTGXt5uTz1Duq0edD5z/AZJrUC1HzC6Jz/WM2ZI1xNA75wdLp0d/1A+M316fn1PlTP9k/LjQ0Ury+11ZC/EVaS07aciotpFuifUsJ7C/pkvEC71gweL6hQo9YGTa6xvZjuBk3Mza1r5LhR35JdfyAlHpYu6WMWV+fFsSW/paluSql2oOFXSGZUz851kzskvf7ITttsjeYz1f+aX51f5dci/pfo44Svz40mSukzOeivmbF1+HNUL6/ol6QBld9L486pDWrLSXWkOrFJ+CbWNvd4epW1PlzS0slDSiXTcqagrn67yK6Z/RToA2Eoa8lOLq0gHwzMk/XVXFXu5D5hZGSfnZtbs5pAShuOBKyWNA5A0StLXSQlytVv/XQHcS7qg7w5J/0vSbqVCSeMlfUzS3cBnq6xjLfC9XG9QXu4g0o/8jCXdseS7O2G72+MbpHHXM4Cf5W8VkDQs/5z816jSVhHxa1ISJ+AmSRdKeuNCQkntkt4n6WbgW70Y83zSL5iOkvTBHVlRRGygIxH9KmkM+WbghiqL3Jof3y3p4tLQKUljJX0TuJg0TGln+H+k21ruDlxVui1h/lt9gnSgVcu2hwK/lnRAXn6wpNmk++gDXBERL9QSUET8mfQjRADflfSNfDcZ8rpHSjpR0tVse0BqZr3EybmZNbV8r+//nV+eBbwkaRUpcbmYlCjOrbLsJuBUUiLUDlwOrJa0UtJ60m3griZ9/V/tFoD/DjyW662XtJZ067yZpOTqwxGxunyBXtpuj0XE08DHSWPeTwaekbSadHb628DPgJ93sYqzcp2hpDuYLJW0WtI6UnvfBPxlb8WbY36FjvHgN0paI+m5PFXeP74WpbPkpdsH3hYRhWOuI+K3dCTzXyf9fVeRxl5fQDrIuqVo2R0VEWtI/RfSL3EulrSG9Le6AlgAfKWGVX2GdOb/0bz8etK3IMNJB4ifq75ooS+Q+vwA0rdSL0pam9e9lnRQ+jE6bgVqZr3MybmZNb2I+CZpLPSdpORjEGlc91kR8flull1GGpf7MdKwh+V0DFWYR/oq/yPAP1RZxQbSfbK/SvpBopa8juuAQyPidztpu9slIq4j/WjNL0hDPFqAPwPn5+1VPRiIiFci4v3Ae0hJ62JSkjeYlCzeQEr+z+vNmEn3GP8GqV2GAFPyNKKrhaq4k8733q42pKXkNFIS+gTpDL5IB1WzI+KT27H9mkXEv5J+IKh0Fn0QqQ2+TLrneFe3piz5A/BW0t+m9CusTwJfAmZFxPoexrQlIj5DusbjalKfH0I6YHuB9INh57LtD2+ZWS9RD34szcys35B0JelXM78SEXMaG42ZmfUXPnNuZmZmZtYknJybmZmZmTUJJ+dmZmZmZk3CybmZmZmZWZPwBaFmZmZmZk3CZ87NzMzMzJqEk3MzMzMzsybh5NzMzMzMrEk4OTczMzMzaxJOzs3MzMzMmsT/B29AIuRYmCxfAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8YdhdvVGBBIk" + }, + "source": [ + "## Plotting prediction with the uncertainty" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "k8sDN5oZA24T" + }, + "source": [ + "#hide\n", + "def plot_prediction(x, y, prediction, sigma=0.01, e=0.01):\n", + " x_lim=[-10,10]; y_lim=[-1.25, 2.25]\n", + " p = prediction.view(-1).data.numpy()\n", + " x = x.view(-1).data.numpy()\n", + " y = y.view(-1).data.numpy()\n", + " if not type(sigma) == float:\n", + " sigma = sigma.view(-1).data.numpy()\n", + "\n", + " if not type(e) == float:\n", + " e = e.view(-1).data.numpy()\n", + " \n", + "\n", + " # plot and show learning process\n", + " fig, ax = plt.subplots(figsize=(12,7))\n", + " plt.cla()\n", + " ax.set_title('Regression Analysis', fontsize=35)\n", + " ax.set_xlabel('Independent variable', fontsize=24)\n", + " ax.set_ylabel('Dependent variable', fontsize=24)\n", + " ax.set_xlim(x_lim[0], x_lim[1])\n", + " ax.set_ylim(y_lim[0], y_lim[1])\n", + " ax.axvspan(x_lim[0], -3.5, alpha=0.1, color='blue')\n", + " ax.axvspan(3.5, x_lim[1], alpha=0.1, color='blue')\n", + " ax.scatter(x, y, color = \"orange\")\n", + " ax.plot(x, p, 'g-', lw=3, alpha=0.8)\n", + " \n", + " ax.fill_between(x, p + 2*sigma,p - 2*sigma, color='gray', alpha=0.3)\n", + " if not type(e) == float:\n", + " ax.fill_between(x, p +e, p-e, color='gray', alpha=0.3)\n", + " #ax.plot(x.data.numpy(), (prediction - 2*sigma).data.numpy(), 'gray', alpha=0.5)\n", + " #ax.plot(x.data.numpy(), (prediction + 2*sigma).data.numpy(), 'gray', alpha=0.5)\n", + " #ax.axvline(-3.5, alpha=0.5)\n", + " \n", + " #ax.axvline(3.5, alpha=0.5)\n", + " ax.text(1.0, 0.5, 'Step = %d' % t, fontdict={'size': 24, 'color': 'red'})\n", + " ax.text(1.0, 0, 'Loss = %.4f' % loss.data.numpy(),\n", + " fontdict={'size': 24, 'color': 'red'})" + ], + "execution_count": 6, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "REh53NwoBKNh" + }, + "source": [ + "## Define Deep Nerual Network architecture" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "07YD-PgLBECj" + }, + "source": [ + "# this is one way to define a network\n", + "class Net(torch.nn.Module):\n", + " def __init__(self, n_feature, n_hidden, n_output):\n", + " super(Net, self).__init__()\n", + " \n", + " self.hidden = torch.nn.Linear(n_feature, n_hidden) # hidden layer\n", + " self.hidden_2 = torch.nn.Linear(n_hidden, n_hidden)\n", + " self.hidden_3 = torch.nn.Linear(n_hidden, n_hidden)\n", + " #self.predict = torch.nn.Linear(n_hidden, n_output) # output layer\n", + " self.predict = torch.nn.Linear(n_hidden, 1) # output layer\n", + " self.predict_probability = torch.nn.Linear(n_hidden, 3)\n", + "\n", + " def forward(self, x):\n", + " x = self.hidden(x)\n", + " x = F.relu(self.hidden_2(x)) # activation function for hidden layer\n", + " x = F.relu(self.hidden_3(x)) # activation function for hidden layer\n", + " #out = self.predict(x)\n", + " out_value = self.predict(x) # linear output\n", + " out_probability = torch.abs(self.predict_probability(x))\n", + " out = torch.cat((out_value, out_probability), dim=1)\n", + "\n", + " return out" + ], + "execution_count": 7, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "GBCtpnyyBVmf" + }, + "source": [ + "## Train the network" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "f32S7SXLB2Ef", + "outputId": "80026716-0c27-43a3-daa2-b4b174e5f6ed", + "colab": { + "base_uri": "https://localhost:8080/" + } + }, + "source": [ + "\n", + "evnet = Net(n_feature=1, n_hidden=7, n_output=4) # define the network\n", + "print(evnet) # net architecture\n", + "optimizer = torch.optim.Adam(evnet.parameters(), lr=0.0001)\n", + "loss_func = EvidentialLossSumOfSquares() \n", + "\n" + ], + "execution_count": 27, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Net(\n", + " (hidden): Linear(in_features=1, out_features=7, bias=True)\n", + " (hidden_2): Linear(in_features=7, out_features=7, bias=True)\n", + " (hidden_3): Linear(in_features=7, out_features=7, bias=True)\n", + " (predict): Linear(in_features=7, out_features=1, bias=True)\n", + " (predict_probability): Linear(in_features=7, out_features=3, bias=True)\n", + ")\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "QQITtH5aBP8q", + "outputId": "303bc874-b050-499f-e9ae-514853d9eb41", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 626 + } + }, + "source": [ + "\n", + "# train the network\n", + "for t in range(8000):\n", + " \n", + " prediction = evnet(x) # input x and predict based on x\n", + "\n", + " loss = loss_func(prediction, y) # must be (1. nn output, 2. target)\n", + "\n", + " optimizer.zero_grad() # clear gradients for next train\n", + " loss.backward() # backpropagation, compute gradients\n", + " optimizer.step() # apply gradients\n", + "\n", + " if t%1000 == 0: print(loss)\n", + "\n", + "\n", + "\n", + "prediction = evnet(test_x)\n", + "mu = prediction[:,0].view(-1) #first column is mu,delta, predicted value\n", + "a = prediction[:,1].view(-1) + 1.0 #alpha\n", + "b = prediction[:,2].view(-1) + 0.1 #beta\n", + "l = prediction[:,3].view(-1) + 1.0 #lamda\n", + "\n", + "#a = torch.exp(a); b = torch.exp(b); l = torch.exp(l)\n", + "var = b / ((a -1)*l) #epistemic/ model/prediciton uncertaitnty\n", + "e = b / (a - 1) # aleatoric uncertainty/ data uncertainty\n", + "plot_prediction(test_x, test_y, mu, var, e)" + ], + "execution_count": 28, + "outputs": [ + { + "output_type": "stream", + "text": [ + "tensor(1.9857, grad_fn=)\n", + "tensor(0.9587, grad_fn=)\n", + "tensor(0.5419, grad_fn=)\n", + "tensor(0.2418, grad_fn=)\n", + "tensor(0.0526, grad_fn=)\n", + "tensor(-0.0255, grad_fn=)\n", + "tensor(-0.0795, grad_fn=)\n", + "tensor(-0.1198, grad_fn=)\n" + ], + "name": "stdout" + }, + { + "output_type": "display_data", + "data": { + "image/png": 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\n", 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