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bcolloran/Simple_GP_regression-periodic-sklearn-Mauna-rev2.ipynb

Created June 10, 2021 00:16
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Simple_GP_regression-periodic-sklearn-Mauna-rev2.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import torch\n",
"import gpytorch\n",
"from gpytorch.kernels import PeriodicKernel, CosineKernel, LinearKernel, RBFKernel, RQKernel, SpectralMixtureKernel, ScaleKernel\n",
"from matplotlib import pyplot as plt\n",
"from sklearn.preprocessing import MinMaxScaler, StandardScaler\n",
"import numpy as np\n",
"import gc\n",
"\n",
"from sklearn.datasets import fetch_openml\n",
"\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"output_type": "display_data",
"data": {
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388l1KW7HiItHkhohhBBCCHHJjZrM/POzucyLDmBtWhjffCGfslb7bV8XOlLZSUFjLw9tTsPjglWT9enhnK7tRmv7mhiAE9Vd7Cho4Utb0okJ9rG7rpRiaWIIufU908Yn2jMvTwpx780B3kYPMqIC3X69uLgkqRFCCCGEEJfcucZehsfN/MPWDP7vgeVYtGbXOdeHX754uoEgHyN3LYu3u5YTF0z/iIn6rmG7axaL5odvFBEb7MNDm9Oc3n9pYghlbf0MjJomx87W9eDn5UFWtCQpc4UkNUIIIYQQ4pKbOCdmRXIoEQHeLE4IYb+LephRk5m3ilrZlhODj6f9QZY5cdYDKgubeu2uvXS2kYLGXr61PQtfL+eHYC5NDEFryJ+yWnO2rpvFCcEYPeSj8lwh/0sJIYQQQohL7lRNN6kR/kQGegOwNTOS3PoeugedH6D5blkH/aMmbl4c6/B6VkwgHgZFYVPftHGtNf+7t4wlCcHcscR+hWeqpYkhAOQ3WhOj4TEzRc19LJ9FPY348ElSI4QQQgghLilrN7EuViSfTxS2ZkVi0XCw3HkntDcLmgn29WRDeoTD6z6eHsyLCrBbqanpHKK+a5h7Vya67F4W4udFbLAPJc3WxOh0bTfjZs3q1DB33564DEhSI4QQQggh3GKxaH6+p5RXcxtnFVfZPkj30DgrpyQ1ixNCCPHz5Ghlp8OYkfGJrWfReBmdf2RdEBdkt1Izcc91bpwxA5AdE0hJi7VpwdGqDowGxaoUSWrmEklqhBBCCCGES1pr/u2Vc/xyXwWPvFRAW/+I27F/fLcKD4Ni/ZQVFw+DYkFs0GQycaF3yzsYGDVxy5Q2zo7kxAXT1j86bT7HqjqJDPQmLcLfrfllxwZR2T7AmMnC0cpOFicE4+9tdCtWXB4kqRFCCCGEEC4dr+7i6RN13LM8gXGzhV+8Xe5W3LGqTp45Wc/nN6aSFO437VpmdCDlrf1YLPYtmd/MbyLEz5P1LlZbFsUHA1DQYN2CprXmaFUn69LCUcq9gzOzYwIZN2sKGnvJb+h1e4VHXD5cJjVKKR+l1AmlVJ5SqlAp9f0p1/5RKVVqG//JlPFHlFIVtmvbLtXkhRBCCCHEB2PXuRa8jQZ+eGcOD6xO4tmT9TMW+YM1wfjRzhISQn352vWZdtczowMZHDPT2DO9JfPk1rMFMXi66EC2KD4YD4OaPGumsn2A9v7RWSUm82OtXdT+fKgak0WzLs1xDY+4fLmzUjMKXKu1XgIsBbYrpdYqpa4B7gAWa61zgP8GUEotAO4HcoDtwG+UUs776AkhhBBCiMua1prdhS1syYzEz8vIncviMVv0jEX+YC26z6vv4Yub0xy2Vc6KCQCgvG36FrQDZe0Mjpm5xUnXs6l8befJTCQ1b+Q3oxRsyYx0891BaoQ/Xh4G3ixoJjHMl5Up0vlsrnGZ1GirAdsfPW1fGvgy8GOt9ajtdRONxu8AntFaj2qtq4EKYPVFn7kQQgghhJiVvpFx7vvdUXYXuj70cqr8hl6ae0fYlhMDWIv8w/y92F86c1Lzp0PVBPt6cs+KBIfXM6Ksh1uWtgxMG38zv5lQP0+3V1uWJoWQW9+D2aJ56Uwj69LCiQvxdSsWwNPDQHpUAErBz+9b6vBMHHF5c6umRinloZTKBdqAt7TWx4FMYJNS6rhS6oBSapXt5fFA/ZTwBtvYhfd8SCl1Sil1qr195v9DCCGEEEKI9++vx2o5UdPFd14qoHdo3O24NwuaMRoU182PAqxF/pvnRXCwrN1hPQxAfdcQuwtbeGBNEn5ejovug309iQ32oaz1/ErNyLiZvcWtbF/oeuvZhKWJIfSPmHj+VD11XUPcs9xxEjWTf7o2gx/fvUi6ns1Rbj0pWmuz1nopkACsVkotBIxAKLAW+CbwnLJWYzmqyLJ72rXWj2mtV2qtV0ZGur88KIQQQghxtTpd280n/nicogtaGLtjZNzMnw/VkB0TSPfQGD9/q9StuFGTmRdON3Dd/ChC/Lwmx6/JjqJzcGzy0MoLPX64BoNSfGpdyoz3nxcdOC2p2V9q23q2aOauZ1Mtsx2g+YM3ivDz8mD7whi3YyfctCiWj65KmnWcuDzMqvuZ1roH2I+1VqYBeMm2Pe0EYAEibOOJU8ISgKaLMVkhhBBCiLnsuZP1fPrxE05XN2ZS2T7A5548yaGKDj7+x2OUtzpuhezM86cb6BgY5Xu35XDTolh2F7a6Fbe7sJWuwTE+viZ52viGDGsx/Ylq+3Nm+kbGefZkHbcujiUm2GfG+8+PCaS8dYChMRMA+0vbCPQxsjbN/RWT9MgA4kN8SQj15Y+fWintmK9C7nQ/i1RKhdi+9wWuB0qAV4BrbeOZgBfQAbwG3K+U8lZKpQLzgBOXYvJCCCGEEHNFfdcQ33utkP2l7Ryu7Jh1/A9eL8KgFH/57GpMZs0f3q1yO9ZktvDYwUqWJYWwNi2MZYkhtPSN0N4/OmOc1pq/HKkhKcyPjRnTO4JFBHgTF+zDuUb7VaMd+c0Mjpn57MZUl3PbnBnJmNnCoXLrv5OjVZ2sSQ3H6ObWMwCDQfHON7ay66ubp52FI64e7jwtscA7Sql84CTWmpo3gD8DaUqpc8AzwKdsqzaFwHNAEbALeFhrbb400xdCCCGEmBu+/3ohSkGQj5FnT9a7Dpiic2CUQxUd3L8qkc2ZkSxNCnGYTDjzZkEz9V3DfHlLOkqpybNdzjnZOjbhqWO1nKrt5qHNaRgM9hUGC+ODHd7jYHk7ccE+kz9nJqtSwgj0NrK3uI3GnmFqO4fe0zkxXkaDwzmKq4PLtTmtdT6wzMH4GPAJJzGPAo++79kJIYQQQlwBugbH2FvSxleuyaB/xMTfj9fRPThGqL+X62Bgx7kWzBbN7UutdSYL44P547tVjJrMeBtdd+r686Fq5kUFcP38aAAWxFnPZTnX2Ms12VEOY+q7hnj0zWK2ZEby8TWOa00WxQezp6iV/pFxAn08ATBbNIfKO9i+MMatwy+9jAY2Z0Wyt6RtspXyujQ5/FLMzqxqaoQQQgghxOztL21Da7hxQQz3LE9gzGxhf1mb60Cb1/OamBcVQFa0tQVyTlwQ42ZNeeuAi0hrcpLX0MtHViRMrmQE+niSFuFPwQwrNbsLWxg1WfjBHTlOk5OFtpWYwimNC/IbeugbMbFpnvuNoK6fH0XHwCi/2ldBqJ8n2TGBbscKAZLUCCGEEEJccntL2ogM9CYnLoj5sYF4Gw1ubx9r7h3mZE0Xty2Jm0wuFsa5t30MYOe5ZgBuXjT9IEtnW8cmHCzvIC3Sn+Rwf6evWehgG9uh8g6UOt9IwB03Lojh+vlRNHQPsTUrSraRiVmT1hBCCCGEEJfQuNnCwbJ2bl4Yi8GgMKDIjg2isMl1QgLWgyi1htuWnG9xnBTmR6C3cdoKidP4ghYWxQeTGOY3bXxhfBCv5TXROTBKeID3tGsj42aOV3XygJNtZxMiA72JCfKZtuLzbnkHC+OCCXNzax2Av7eRP35qFV2DY/h5ycGXYvZkpUYIIYQQwk1/fLeKJw5XzyrmTG03/SOmabUrC2KDKGrqQ2vXrZ1fz2tiUXwwqRHnV0wMBsX8uCDOuUiMjlZ2klffY7dKA1NWWRwkRseruxg1Wdic6XoL2YrkUI5WdqK1ZmDUxJm6bjbOe28dyML8vfDxlKRGzJ4kNUIIIYQQbmjpHeG/dpXwX7tK6RsZdzvuUEUHHgbF+ozzxe85cUH0jZho6B6eMba2c5C8hl5uX2J/EOXCuGCKm/swOznzpr5riC//7TTpkf58fK39ikvODFvYDpa142U0sDbVdcH+lqxI2vpHKW7u51hlJyaLZtN7TGqEeK8kqRFCCCGEcMPjh6sxWTTD42ZePN3gdty75R0sSQgmyNYdDKxJDeByC9qfDlXjYVDcsth+pSUnLoiRcQtV7Y6bBTx2sIqRcTN//vSqaT97QrCvJ8nhfk6TmjWpYfi6sRVsi201Z39ZG++Wt+Pr6cGK5FCXcUJcTJLUCCGEEEK40DM0xt+O13HLoliWJobw1LFat7aO9Q6Pk9/QY3dwZXZMEAbFjDUxdZ1D/P14HfevSiQuxNfu+vntY/ZJicWieauola2ZUS4L/S/sgNbUM0x52wCb3exeFh3kw/zYIN4qauVAWTtr0sLcajMtxMUkSY0QQgghhAs/21PG8LiZr1ybwQNrkqhqH3Sre9mxqk4s2r4TmK+XB+mRATMmNb/YW4bRQ/FP181zeD090h9vo4FCB/MoaOylpW+EGxZEzzi/RfHBNHQP0z04Njl2sKwdwK16mgnXZEVytq6Hms4hbloY43acEBeLdD8TQgghxBVPa82OghZ+8XYZ965M4KHN6W7Hnmvs5W/Ha3lwXQrZMUFEBnijFOwraWNRQvCMsfuK2/Dz8mBZkv12rJy4II5WdTqMq+8a4tXcJj6zPoXoIB+HrzF6GMiOddws4K2iVjwMimudHKw5YaI1dGFT32Rx/8HydmKCfMiMDpgxdqrPbUwlKtCbnPhgVsrWM/EhkJUaIYQQQlzx3i5u4+G/n6Gtf5T/3FHCq7mNbsf+955Sgnw9+ecbMgEID/BmSUII+0pnPjyzd2ic1/KauHVxLF5G+49cOXHBtPaN0jEwanftsYNVGBR8flPajD9jYVwQhRd0UdNas6uwhVUpoYS6aKu8MN5a25PX0ANY208fKu9gc2aE0wM3HQkP8ObTG1JZlRI2qzghLhZJaoQQQghxxTtY1o6/lwdHH7mWVSmhfO+1QsbNFpdxufU97C9t5wub0gj2PV9sf212FHn1PbT32yckE54/Xc/wuJkH16U4vH6+WcD07WO9w+M8d6qee5YnEBPseJVmwsL4YPpHTNR3ne+iVtjUR0XbwLRzbZwJ8fMiKzqQY7YVo2NVnfSNmLhhgWwhE3OLJDVCCCGEuOKdrOlieXIofl5GPr8pjZ6hcY5XdbmM+7995YT4efKp9SnTxie2dR2w1Z9caHDUxBNHaliZHDpZ0H+hBU46oO0raWXUZOGjqxJdzm+R7d65tpUWgFfONuLpobjFwdk0jmzIiOBEdRcj42Z2nWvBz8tDWjKLOUeSGiGEEELMCVprylv7sTg5l8WZ3qFxSlv7WZUSBlhbEPt5ebDjXPOMcbWdg+wtaePBdSkEeE8vQ86JCyLUz5PjDmpitNb864v5NPUM8y83Zjm9f4ifF/EhvnYrNTsLWogN9mFJQojL95YVE4ivpwdnarsBMFs0r+Y1cU1WFCF+M289m7BpXgSjJgsnqrvYXdjK1qxIOQBTzDmS1AghhBBiTvjrsVpu+J+D/Pur59xqpzzhTF03WsPKFGsBu4+nB9dkR7GnsMXpwZUAfz9eh0EpHlhtf3ClUooVyaGctiUTU+0va+eN/Gb+5cYs1qXPfHhlTlwQRVOSmqExEwfK2tmWE4PB4Lo2xdPDwOKEYM7WWeexo6CZ9v5R7l4e7zJ2wurUMIwGxY92ltAxMMq2HNl6JuYeSWqEEEIIcdmrbB/g0R3FRAd587fjdfzuQJXbsSdrujAaFMsSz3fl2p4TQ8fAGPlTtm1NNTJu5rlT9dy4INppXcvKlDCqOgbtCv33Frfi5+XBF1wU+YO1Jqa6Y5De4XEADpS2M2qyzCqxWJEcSmFTH/0j4/xsTynZMYGzqonx9zayPCmU4uY+tmRGSlIj5iRJaoQQQghx2fv1vgo8DQZe+8pGVqeG8cpZ97qX9QyN8cLpBpYnh+LrdX5L1dLEEACKmh2fE7O/tI3uoXEeWGO/SjNhlW3l51TN+dUarTX7S9tZnx7hsOPZhVbY2h9PbB97p7SNIB/j5L3dsSI5FJNF843n86jpHOKb27LwcGOVZ6rv3b6A/3tgGU98ZpVsPRNzkiQ1QgghhLisWSya/WXtXDc/iuggH67JiqK0tZ+2vpEZ40ZNZr7zcgFdg2N899YF064lhPoS6G2kpLnfYezr+c1EBHixLs359rGF8cF4GQ2crj3fcKCqY5CG7mG2Zrl3cOWypBCMBsXJmi601hws62DjvAiMHu5/RJs4A2d3YSvbc2Jcnk3jSE5cMLcujpN2zGLOkqRGCCGEEJe1gsZeugbH2Jpl/bA+0ZnrUEWH05jK9gGu//kBdhS08PUbM+06kCmlyI4NpNjBSs3QmIl9xW1sXxgzY3LhbfRgSUIwJ6es1OwvtXZD25LpXlLj52VkYXwwJ2u6KG8boKVvhM3z3IudEObvxQ0LorlvZQK/emCZJCbiqiRJjRBCCCEua/tL21HqfDKzIDaIMH8vDpU7T2r+cqSG9v5Rnvzsar68Jd3ha7Jjgihp6bdrOvBOSTvD42ZuWeT6nJdlSaEUNfUxZrLY5tpGeqQ/iWF+7r49VqeGkVffy1tFrQBscjMhmuoPD67kJx9ZgucsVniEuJLIky+EEEKIy5bZotlb0sri+GDCA7wBMBgU69PDebeiw2EXNK01e0va2JgRyZbMSKcrF9mxgQyMmmjoHp42/kZ+E5GB3qxODXM5vyUJIYyZLZS29DM8ZuZ4dRdbMme3/WtVShhjZgu/fqeC9Eh/4kN8ZxUvhJCkRgghhBAfkHGzhYq2AbdfP2oy8+W/nia/oZe7lydMu7YmLZz2/lG7hASgrHWAhu5hrps/c3IxP9Z6+GVJy/m6msFRE/tK2rh5YYxbxfZLEs8ffnmsqpMxk8XtepoJa9LCyI4JZF1aOD/5yJJZxQohrIyuXyKEEEII8f79545iHj9cw98/v4b1Ga5PrH89r5k9Ra38v1vm8+C65GnXltm6l52p67bb6rW3xLqNy1XBfFZ0IADFzX3csCAagLeLWxk1Wbh1ieutZwDxIb5EBHiRV99DRWs/Pp4Gt1Z4pgry8WTX1zbPKkYIMZ2s1AghhBDikusaHOPpE3UAfOP5vMlzWWbyTmkbUYHefG5jqt0WsqyYQHw8DeTW99jF7StuY1F8MNFBjs+XmeDvbSQjKmDy4EqAN/ObiQ7yZkWSey2VlVIsSQjhVE0Xe0vaWJcWLi2RhfgQSFIjhBBCiEvuySM1jIxb+OlHFtPUO8Lzp+pnfL3JbOFgWTtbsxzXxHh6GFgUH2yX1HQNjnGmrtvttsarU8M4VdON2aLpHR5nf2k7tyyKwzCLc16WJIZQ0zlEU88wH13l/FwbIcSl4zKpUUr5KKVOKKXylFKFSqnv28b/QynVqJTKtX3dPCXmEaVUhVKqVCm17VK+ASGEEEJc3rTWPHuynmuyIrl3ZSLJ4X4cr+6aMeZ0bTf9I6YZk5OliSEUTuk8BtbuYxaNy3qaCWtSw+gfNVHc3MfOgmbGzBbuWhbv3huzuW1JHNfPj+L5L61n+8KYWcUKIS4Od1ZqRoFrtdZLgKXAdqXUWtu1/9FaL7V97QBQSi0A7gdygO3Ab5RSsg4rhBBCXKUKm/po6Rvh5kWxAKxOCeNkTRcWi33nsgnvlLZjNCg2zFB7szQxlDGTZdpZM3tL2ogM9GZhXLDTuKlWpVjrX07WdPHS2UbSI/1ZGB/kVuyE1Ah//vipVaxIdm/LmhDi4nOZ1GiriVYlnrYv5/8VgjuAZ7TWo1rraqACWP2+ZyqEEEKID9XP9pTy3VfPzTru7eJWlIJrbKsua9LC6Rkap3yGTmj7S9tYlRJGoI+n09dMJBEna6yrPuNmCwdL27kuO8rt7WNxIb4khPry9Ik6TlR3cdeyeDm8Uog5yK2aGqWUh1IqF2gD3tJaH7dd+opSKl8p9Wel1MSvJ+KBqRtlG2xjF97zIaXUKaXUqfb29vf+DoQQQghxyb2a28iv9lXwl6O17LN1F3PX3uI2liWGEGE7Z2aNrTvY8epOh69v6hmmpKXfZV1MTLAP6ZH+vGs7hHNvcRv9oyZuzIme1fzWpYVT1jrAovhg7l8tNTFCzEVuJTVaa7PWeimQAKxWSi0EfgukY92S1gz8zPZyR7/esFvZ0Vo/prVeqbVeGRk5+5NzhRBCCPHBGBoz8W8vn2Nlcijpkf784PWiaXUsM2nqGaagsZfr5p9PNBJCfYkN9uF4leO6mv2l1l92XpPt+vPBxowITlR3MWoy8/SJOmKCfNg8b3afK75z83xeeXgDr31lw2TiJYSYW2bV/Uxr3QPsB7ZrrVttyY4F+APnt5g1AIlTwhKApvc/VSGEEEJ8GHLrehgYNfHwtRl8c1sWNZ1DTldZLvT0iTqUgtsWnz/3RSlrrcy75e2Mm+2To30lbSSE+pIeGeDy/hvnRTI8bub1vGYOlrdz36pEjB6za+4a6u/F0sQQ2XYmxBzmTvezSKVUiO17X+B6oEQpFTvlZXcBE5tsXwPuV0p5K6VSgXnAiYs6ayGEEELMyrjZwndfPcfuwpZZx56q7UYpWJ4UyubMSDw9FIcqOlzGTayeXJsVRVL49AMyr58fRd+IiVM13dPGB0ZNHK7o4JqsKLeSjDVpYXgYFN9+MR+DUnx0VaLLGCHElcfoxmtigSdtHcwMwHNa6zeUUk8ppZZi3VpWA3wRQGtdqJR6DigCTMDDWmvzpZi8EEIIIdzzg9eLeOpYLS+faWTJ10OICZ75YMqpTtZ0kRUdSLCvtWh/eVIoh91Ial4920THwBifWp9id23TvEi8PAzsLW5lXXr45PgrZxsZHjdz93L32ioH+Xhy2+JYGnuG+foNWcSH+Lr3poQQVxR3up/la62Xaa0Xa60Xaq1/YBv/pNZ6kW38dq1185SYR7XW6VrrLK31zkv5BoQQQggxs73FrTx1rJa7l8czbrHwvdfc72BmtmjO1vVMa1e8MSOCwqY+ugbHnMaVtPTxH68XsiQxhI0O2jL7extZlx7O28WtaG0tvdVa89djteTEBbE0McTtOf7i/mU8/6X105IjIcTVZXabToUQQggxp2it+b93KkgI9eUn9yzm0+tT2VPUSt/IuFvxpS39DIyaWJlyPqnZMC8CreFIpePVGq01//j3swR4G/n9J1Y4ba983fwoajqHqO0cAuBMXTclLf18Ym2y1LcIIWZFkhohhBDiMqe1pnd4fHJFYzZOVHdxtq6HhzanYfQwsMmWkJyu7XYdDLxT2gbAyuSwybHF8cH4e3lwotpx97Izdd2Utw3wjW1ZM25zW29bWZloOrCnqBVPD8VtS+KcxgghhCOS1AghhBCXuT8dqmbJ9/ew5Pt7nK6OOPO343WE+nly7wprAf2ypBCMBsVJJwnJVGMmC385WsOGjHASw84X+hs9DCyMDyavoddh3ItnGvHxNHDzoliH1yekRwYQEeA12dr5YFkHK5JDCfB2p+RXCCHOk6RGCCGEuMwdr+4iOsibUH8vvvNSAaMm9/rvWCyaQxUdXJMdha+XBwB+XkYWxgdzssZ1UvN6XhOtfaN8YVOa3bUliSEUN/XZnVczMm7mjbwmtufEuExOlFKsTg3jeHUXbX0jFDf3sTlTzq4TQsyeJDVCCCHEZa6oqY9VKWH88I6F1HQO8adD1W7FlbT00zU4xob06YX6q1PDyKvvZWTceXI0MGrif/eWkxkdwBYHicai+GDGzBbKWvunjR8oa6dvxMRdyxPcmuOa1HAae4Z5+kQ9gMOfJYQQrkhSI4QQQlzGeofHaewZZkFcEJszI1mfHs4Lpxvcip1ou7zhgu5jq1LCGDNbKGh0vH0M4LuvnqOhe4hH71rksGh/SUIIAHkNPdPGdxQ0E+LnOVkv48qaNGutzq/2lRMR4M38mCC34oQQYipJaoQQQojLWHFzHwALYq0f9q+fH01V+yD1XUMuYw9VdJARFWBXrL8kMRiAAic1MXuLW3npTCNfuXYeq1LCHL4mMcyXUD9P8uvP32Nk3Mze4ja2LYjB08O9jxiZUYF8cXMa961K5CcfWeS0U5oQQsxEkhohhBDiAzAybuZIRcesO5hdmNRszbJuz9pf1j5jXP/IOCequ9jgYMUkKtCHyEBvzjXZJzXDY2a+91oh86IC+Mo1GU7vr5RiUUIIZ+rOd1E7VN7BwKiJmxbFuH5jNgaD4pGb5/Ofdy3i2uxot+OEEGIqSWqEEEKID8CPdhTzwB+P88hLBZjMFtcBNkVNfUQEeBEZ6A1AaoQ/iWG+HLC1Wnbm+VMNDI+budtJbUtOXBBFTX124387XktD9zA/vHMhXsaZPyZclx1FedsA+bYtaHuKWgjyMbI+3f6wTSGEuJQkqRFCCCEusar2Af52vI60SH+eOVnPk0dr3YrTWpPf0Mv82KDJuhalFFsyIzlS2WnXeWyC2aJ58mgNy5NCWJIY4vA1C+OCKW8bsGsWsKeolfmxQaxNc10Tc9fyeHw9Pfj78Tq01rxb3sHGeREukyEhhLjY5L86QgghxCX2y73leBsNPPvQOrJjAnmrqMWtuHdK2yht7eeGBdO3Za1Li2BozExJi/1KC8BbRS3Udg7x2Y2pTu+dExeE2aKndS/rGRrjdG0312VHuTW/IB9Pbl8Sx6u5TZyp66G5d4RN86R7mRDigydJjRBCCHEJWSya/WXt3LwolshAb7ZmRXGqppv+kfEZ40xmCz/aUUJKuB/3r0qadm1ZUggAZ+t67OLMFs3P9pSRFuHP9hzntS05cdZmAecazydGB8raMVs01813L6kBeHB9MsPjZv7p6bMAbMyQrWdCiA+eJDVCCCHEJVTZPkDP0DirUq1dxLZmRWKyaA5XdM4Y9+ypesrbBvjX7dl227lig32ICvTm7JQi/Qmv5jZS3jbA12/MxDhDB7LEMF8CfYwUNPZMju0tbiPc32uyXbM7cuKCuW9lAo09w7Z6Hz+3Y4UQ4mKRpEYIIYRwwx8OVvGvL+Rjscyue9nJGmviMdEaeUVyKAHeRg7M0L2sd3icn+0pY3VqGNsX2q+2KKVYlhRCbn2P3bUnj9aSHRPIzQtjZ5yXUor16eG8U9KOxaIxmS3sL23jmuyoWbdV/tb2bEL8PN3etiaEEBeb8cOegBBCCHG5e/5UPY/uKAasScl9qxLdjj1Z00VEgDcp4dYVDE8PA+vTw3m33HlS83/7yukeGuO7ty5wePAlwLKkUHYXttI1OEaYvxcArX0j5NX38M1tWW4lJttyYthd2Ep+Yy+j42b6RkxcP4utZxMiArx551+24uftMetYIYS4GGSlRgghhJhBU88w//bKOTZkhLMqJZRHdxTTPTjmdvzJmi5WpYROS07WpYfT0D1MY8+w3eurOwZ54kgN961IZGF8sNP7LrN1NcutP78F7a2iVgBuXODeeS/XZUdjNCh2nWthb0kbnh6Kje+x0D/U3wtvoyQ1QogPhyQ1QgghrgpjJgvmWW4dA/jVvgq01vzXPYv57q059A6Ps7vQve5lZ+q6aegeZrWtnmbCRLvk41X2dTU/2lGMl4eBf9mWOeO9FyUEoxQUNJwv9N9T1EpKuB8ZUQFuzS/Yz5N16eG8ntfEznPNrE0LJ8BbNnEIIeYeSWqEEEJc8Qqbetn0k3189Zmzs4qr6xzi+VP1PLA6iYRQPxbGBxEf4svbxTMffAkwbrbwnZcKiA324d6V07erZUUHEuLnybELkpqBURNvF7fyiXXJRAX6zHh/Py8jqRH+FDb1AtA/Ms7Ryg5uzIlxumXNkS9sSqN3eJz6rmGpiRFCzFmS1AghhLii1XcN8dHfH6N7aJw38pvZX+o6IZnw9Mk6NPAP12QA1uL66+ZHcaii3e7QSrvYE3WUtPTzwzsW2q1+GAyKVSlhHK/umjaeX9+DRcM6Nw6+BFgQG0RRs3Wl5kBZO+NmbXemjSubMyM5/K/X8ouPLuX+1UmuA4QQ4jIkSY0QQogr2t+O1zE8bmbHP20iLcKfH7xehNaut6GZLZpXzjayJTOS6KDzqybXzY9mZNzCkcqOGeNfON1ATlwQ1ztJMtakhlHbOURL78jk2Olaa33MsqRQd94aOXHBNHQP0zs0zp7CVsL9vVjuZuxUwX6e3LksHh9PqYkRQsxNktQIIYS4Yo2bLbxwuoFrsqLIiArgoc1pVHUMUtk+6DL2WFUnzb0j3L08ftr42rQw/Lw8OFjmPKmpah8gv6GXO5fGO33NxAGaE9vHAE7XdZMZHUCwr6fL+QHkxAUBkNfQwzulbVw3PwqPWbZjFkKIK4EkNUIIIeaEqvYBxkyWWcXsLW6jY2CU+20tmCcL9KtnPvgS4LlT9QT6GLl+/vSVFm+jh3XbV1Ofk0h4JbcJpeD2pXFOX5MVY01Iim3bxywWzZnablYku7/SssCW1Px2fyX9IyZuWGB/po0QQlwNJKkRQghx2TtQ1s61PzvAZ544weCoye24vx6rJSbIh61Z1jbFyeF+RAV6c+KCWpYL1XUO8UZ+M/euSHS4JSs7NpDilj6H29hMZgsvnm5gfXr4tG1rFwrwNpIU5kdxSz8Ale0D9I2Y3N56BtbzYaKDvDla1UlmdACb5kW4HSuEEFcSSWqEEEJc1roGx/jG83nEBvtwtLKTb72Y71ZcaUs/hyo6+OS6ZIwe1r/ulFKsTg3jeFXXjHU1vz1QgYdB8cUtaQ6vZ8cE0T9iomlKPcyEHedaaOwZ5lPrUlzOcX5s4ORKzR7bGTPuNgmYcNeyBLbnxPD8l9ZLTYwQ4qrlMqlRSvkopU4opfKUUoVKqe9fcP0bSimtlIqYMvaIUqpCKVWqlNp2KSYuhBDi6vDom8X0DI3xx0+t5ONrktlb3MqoaebOYwBPHKnG22jggQs6eq1JC6elb4SGbvuDLwE6B0Z54XQD961McLrSMj82EICS5ulb0LTW/OFgFakR/nbb1hzJjgmipmOQ4TEzL51pYHVKGIlhfi7jpvr2Tdn87pMr3K7DEUKIK5E7KzWjwLVa6yXAUmC7UmotgFIqEbgBqJt4sVJqAXA/kANsB36jlJJfHQkhhJi107VdvHimgc9vSiMnLphN8yIYGbdwtq5nxrihMROvnG3izqXxhPp7Tbu2OsV6EKazLWiv5zUxbtZ8Ym2y0/tnRluTmuILkprc+h4KGnv53MZUDG4U7M+PDcKi4YUzDVS2D9o1JRBCCOEel0mNthqw/dHT9jWxZv8/wLem/BngDuAZrfWo1roaqABWX7wpCyGEuFr8ZFcpscE+/OO11nNi1qSFY1BwpGLmdsrvlLQzPG7mzmX2SUJGVAD+Xh4UNPY6iISXzzYyPzaIbFshvyOBPp4khvlO1sNMeOVsI95Gw4wNAqaaWPH5yc4SvIwGbloU61acEEKI6dyqqVFKeSilcoE24C2t9XGl1O1Ao9Y674KXxwP1U/7cYBu78J4PKaVOKaVOtbe3v7fZCyGEuGKNjJs5U9fN7Uvj8POyHl4Z7OvJooQQDlfO3L3szYImIgK8WZ0aZnfNw6DIiQ8mv6HH7lpl+wB5Db3c7SAZulB2TNC0lZpxs4XX85u5fkE0QT7ubQVLDPUjMzqAhDA/fnbvEtlCJoQQ75FbSY3W2qy1XgokAKuVUouBfwO+6+Dljtbb7aoxtdaPaa1Xaq1XRkZGzmLKQggh5ppTNV3c9ZvD/HhnCb1D427FnGvsZdysWXFBN7AN6eHk1vfQP+L4PoOjJvaVtHHzohinZ7Ysjg+msKmPcfP0FtEvn2nEoOAON1ZaFsUHU90xSPfgGADvlrfTNTjGXTOcTXMhg0Gx55+3sPOrm7htiXurO0IIIezNqvuZ1roH2I91i1kqkKeUqsGa7JxRSsVgXZlJnBKWADRdhLkKIYSYg+q7hnjoqdNUdwzy2MFKfvZWqVtxZ+q6AVh+wbkt69LDMVu007qaXedaGBm3cMsMW7kWJQQzarJQ3jowOWaxaF4+28iGjAiiZmjFPGF9ejhanz/z5s38FoJ9PdmcKb+oE0KID5o73c8ilVIhtu99geuBs1rrKK11itY6BWsis1xr3QK8BtyvlPJWSqUC84ATl+oNCCGEuLx9+6V8xs0WXvryejbOi+RYleuDLwFO13aTHO5HRID3tPFlSaF4GBQnaxwX+v/9RB1pEf4Ot55NWJwQAjBtC9rJmi4ae4a5Z3mCW/NbnBCCn5cHRyo7MVs075S2sTUrEi+jnJYghBAfNHf+yxsLvKOUygdOYq2pecPZi7XWhcBzQBGwC3hYa+2696YQQogrTm59D4crOvmna+eRFhnAmtQwyloHJrdsOaO15nRtj93WM7AeWrkgNshhUlPS0sfp2m4eWJOEUs67j6WE+xHoYySv4XyzgFdyG/Hz8uDGHNetmAG8jAZWpYRxpLKT3PpuugbHuM6NNs5CCCEuPne6n+VrrZdprRdrrRdqrX/g4DUpWuuOKX9+VGudrrXO0lrvvNiTFkII8cEaN1uobB+gc2B0VnG/eaeCYF9PPrbGelbMxOqJs1UWsG4D+92BKjoGRlmRYp/UAKxMCeVsXQ9jpuk1MU8fr8PLaOAjK2ZebVFKsTQxhLO2LW4Wi+atojauzY6abErgjg0Z4VS0DfDnQzUYDYotsvVMCCE+FLJGLoQQYkaV7QPc9qtDXPezA6z4/952e/tYa98IbxW38sm1yQR4WxOFxQnBeBkNTs+IAfjDu1X8164SbloYw93LHCcnq1PCGDVZONd0fqVlzGThtbwmblwQTYifl8O4C+9R0tJPz9AYxS19dAyMzjopuW5+ND6eBt4saGZVSph0LxNCiA+JJDVCCCGcGjNZeOAPx2jtG+GHd+Tg42lg17kWt2L3FLagNdy57HxXL2+jB0sTQzg+Q1Lz8tlGViSH8puPL8fXy/HZzSttB2iemrLic6Csne6hcbcPsFyTFg7AyZpuDpZZNxvMNqlJjwzgwDev4ScfWcwP7siZVawQQoiLR5IaIYQQTr1V1Epr3yg/v28pn1yXwvr0CPaVtKG1Xad+O7sKW0iL9CcjKnDa+Lq0cAqbeukZsq+rqWofoKSln1sWxc5YExMZ6E1qhD8nqrsnx14+20C4vxeb5rmXmJxfNerkYFk72TGBbnU9u1B0kA/3rUxkXnSg6xcLIYS4JCSpEUKIq4A7SYgjz5ysIz7Ed7JN8TXZUdR1DVHdMThjXPfgGMequtieE2N3bXNmBBYNhyvst7HttK0CbV9oH3ehlcmhnK7twmLRdA+O8XZRG7cticPTw72/2nw8ratGOwpaOFXbJfUwQggxh0lSI4QQVzizRfOZJ07yxadO2R02OZP6riHeLe/gvpWJk4dYbrV98N9X0jZj7J8PV2O2aLY5SGqWJIQQ6GPkYFm73bVd51pYlhRCXIivy/mtSg2je2icyvYBXjzTwJjZwv2rE13GTbU2LZzGnmHSIwP4xNrkWcUKIYS4fEhSI4QQV7i/HK1hf2k7uwtb+X8vn3M77rU867nJ96w4X6OSGOZHeqQ/hys6nIXxam4jv9pXwd3L41mcEGx33ehhYEN6BO+Wt09bQeoYGKWgsZfrsqPcmt8qW13NiZounj5Rx7KkELJjgtyKnfDQ5jT+9KmVvPGPG0kM85tVrBBCiMuHJDVCCHEF6xwY5ae7S9maFckXN6fx7Kl6Ktr63Yrdea6ZpYkhJIRO/7C/MjmM3Poeh1vatNb8ZFcpSxND+PHdi53WxWzOjKSpd4TK9vPb2CYSpc1ubgNLsR3M+au9FVS2D/Kx1UluxU0V4G3kuvnRGN3csiaEEOLyJP8VF0KIK9ieolaGxsx8a1s2D65PAVxvHQOo6xziXGMftyyKtbu2LCmE7qFxajqH7K6dqeumsWeYB9cl42V0/lfMxHk1E+fEABws6yDUz5OcOPvVHUeUUlybHUnv8DgfXZnI7UviXAcJIYS4IklSI4QQV7DdhS0khfkxPzaQ+BBfsmMC3Upqnj5ZB8BNi+xrYpYlWQ/EnJqQTHgttwlvo4EbHdTSTJUW4Y+/lwcFjdZzZrTWvFvezoaMiMn6HXf86O7F5H7vBv7rI4vx8XTc/lkIIcSVT5IaIYS4QvWPjHOkopNtOdGT28CuzY7iZE03vcPjTuN++EYRv91fyc2LYuy2ngFkRAUQ4G3kzAVJjcls4c2CZq6bHzV52KYzBoMiJz6Y/AZrUlPS0k9b/yib5kXM6j16GBTeRklmhBDiaidJjRBCXOba+kb4l+fy2F3o3qGXE94pbWfMbJnWgeza7CjMFuuqiCPVHYP86VA1969K5Jf3L3P4Gg+DYmliCGfreqaNH6vqomNgjNsWu7cNbHF8MEXNfYybLbyZ34xBwbXZ0e69OSGEEGIKSWqEEOIyVt7az82/fJcXzzTwpb+e5q/Hat2O3V3YQkSAN8tt28UAliaG4Ovpwaka+61jYO1cphR87frMGYvnlyWFUNLSz9CYaXLstbxGAryNXONm97JFCcGMmSyUtfbzen4TGzIiiAz0dvPdCSGEEOdJUiOEEJex3+6vZGTcwutf2cja1HB+ursUs8X1QZoj42b2l7Rxw4JoDFNqVIweBhYlBJNb32MXo7Xm1dwm1qaGExPsM+P9lyWFYLboye1joyYzO8+1cGNOtNu1LYsTQgB44nANtZ1Dbq/wCCGEEBeSpEYIIS6x6o5BvvTUacpb3WulPKFrcIw38pu5e3k8ixKC+diaJHqHxzlnK66fyZHKDgbHzGzLsd/OtSwxhKKmPkZN5mnjBY29VHcMcsdS18nF0sSJZgE9gLVzWf+Iidtm0YEsOcyPUD9Pnj/dgJeHweFBnUIIIYQ7Zq7kFEII8b6Mmy189Zmz5Df0ktfQw0v/sJ7YYF+3Yp87Vc+Y2TJ50v369HAADlV0sCQxZMbY3edaCfQ2sj7dvvB+SWIIY2YLxc39LJ1yn30lbSiFW8lFmL8XqRH+kx3QXstrItTPk40Z7hf6GwyKZx5aR2FTLzHBPgT7ebodK4QQQkwlKzVCCHEJPXawivyGXr5+Qya9w+P89+4yt+LGzRaeOlrLmtQwMqMDAYgI8GZBbJDTIv8JJS19vJrXyA0Loh2eFTORyORe0L3s3fIOFieEEOrv5dYclyWGcKauh8FRE28XtXLzolg8Z3mIZVZMIHcvT3CYfAkhhBDukqRGCCFmoLXm1+9U8Ik/Hmdk3Ow64ILYF043sCEjnH+6bh7XZEdxuKIDrV3XxLyZ30xjzzBf3JI2bXzTvAjO1PZMK9CfanjMzD/87QyBPp58++Zsh6+JDfYhKtB7Wl1N7/A4ufU9bJ5FS+VlSSF0DIzyxJEahsfNcvilEEKID40kNUKIK547SYQz//FaIT/dXcqhig7+frxuVrGlrf1Udwxy86JYwLp9rKVvhOqOQZfz/f3BKuZFBbA1c3onsbXp4YyZLeTVO66r2VPUQlX7ID/5yGKiAh0X+yulWJUaxuHKTiy2pgNHKzsxWzSb5kW6/f5WJIcB8NPdpcQE+bAqJcztWCGEEOJikqRGCHHF++YL+Tzwh2MMjjpe3XCmrX+Evx6v4/5ViaxNC+M3+ysZHnN/tWZnQQtKwY0LrDUqE1usjlR2zhj3dnEbxc19fHFL+rTOZQAL44IBKGxynNTsKGgmOsibLS6SkxsXRNPeP8rZeusWtANl7QR4G1mWFOLyfU2YHxvIrx9YzoPrkvnebQvs5iqEEEJ8UCSpEUJc0QoaennhdANHKjt5+O9nJlcm3PFabhNmi+bzm1L55+sz6RgY5cUzDW7Faq3ZUdDMqpSwybNXUsL9iA324egMSY3Fovn5W2WkhPtxp4MuZJGB3kQHeVPY1Gd3bXDUxP7Sdm5aGOsywbgmOwpPD8XuwlbGzRZ2nWtmS1bkrGpilFLcsjiWH9yxkJtsq1FCCCHEh0GSGiHEFe1/95YR7OvJ12/IZH9pO8eru9yOfelMI0sSgsmICmR1ahjZMYE8f6rerdhXc5sobxvg3hUJk2NKKdanR3C0qtPplrg9RS0UN/fx1evnOT38cmFcsMOVmndK2xg1WbhpoevuZUE+nqxPj2DXuRYOlLbTPTTO3cvi3XpvQgghxOVGkhohxBWrumOQt4vb+OyGVD6/KRVvo4HdhS1uxZ5r7KWouY+7bB/0lVLctzKRvIZeSltmPm9mYNTEf+4oZnFCMHcvT5h2bXVqKF2DY1Q5qav506FqEsN8uX2J8wQjJz6YirYBu61wOwtaiAjwZqWbtS23LI6lrmuIb7+UT6ifJ5sz3a+nEUIIIS4nktQIIa5Yr+c1AXDfqgT8vIxsmhfJW0WtbjUO+O2BSgK9jdw9ZaXlzmXxeHool6s1z56sp61/lO/dloPHBdvAViRbD608XdttF3eusZeTNd18al2KXdxUOXFBWDQUt5zfgjY8ZmZfSRvbF0bPGDvVR5Yn8On1KXQMjHHbkrhZt2MWQgghLhcu/wZTSvkopU4opfKUUoVKqe/bxn+olMpXSuUqpfYopeKmxDyilKpQSpUqpbZdyjcghBCOaK15La+J1Slhk4ddbsuJprFnmHON9vUoU1W1D7CjoJlPrEsmyOf8gZBh/l5syIjgQJnzc2K01jxzoo4liSGTCcxUaREBBPt6csZBUvOXozX4enpw78rEGee3MH6iWcD593GgrI3hcTM3L3S/tsVgUHzvtgU89bnVfGu74/bPQgghxFzgzq/lRoFrtdZLgKXAdqXUWuCnWuvFWuulwBvAdwGUUguA+4EcYDvwG6WUxyWYuxBCOFXS0k9F2wC3TSm2v35+NAaFyy1oTx2rxdPDwGc3pNpdW5EUSnnbAL3D4w5jz9T1UN42wMdWOU5MDAbF8qQQu5WaMZOFnQUt3Lo4lmBfT4exE+KCfYgM9OZ41fmGAzsKWgjz92J16uzaKiul2DQvkgBv46zihBBCiMuJy6RGWw3Y/uhp+9Ja66m/6vQHJvZz3AE8o7Ue1VpXAxXA6os4ZyHEVWZw1DSrrmUAz5yow9NDTSuaD7V96J8pqdFas+tcC1syIye7lk213Lb6MvXgyqmxf3y3Cn8vD26b4SDKFcm2xGjofGJ0vLqT/lET23JcF/krpbgmK5IDZe2Mmy2MjJvZW9zKtpxop80FhBBCiCuZW3/7KaU8lFK5QBvwltb6uG38UaVUPfBxbCs1QDwwdcN5g21MCCFmbV9JK6sefZv/3FHsdkz34BjPnWrgjqXxRARMT0y25cRQ3jZAVfuAw9j8hl6ae0ecJhdLEkMwKBxuH3v5bCM7z7Xw5a3p+M+w8jFxaOWp2vOd2PYUtuLr6cHGeREu3x/AdfOj6R8xcbKmi3fLOxgcM3PTLLaeCSGEEFcSt5IarbXZts0sAVitlFpoG/83rXUi8DfgK7aXO6pQtfsVq1LqIaXUKaXUqfZ25/vThRBXr4KGXj7/5CnGzRb+dryOnqExt+KeOlbL8LiZL2xKs7t2oy1Z2V3Y6jB2d2ELHgbF9fOjHF4P8DaSFRPEmbrpSc3gqInvvVrI6pQwvrw1Y8b5LUsKwdfTg4O22hytNW8Xt7JpXgQ+nu7t1t00LwIvo4G9xW3sLGgm2NeTdenhbsUKIYQQV5pZ7VPQWvcA+7HWykz1d+Ae2/cNwNTN5AlAk4N7Paa1Xqm1XhkZKW1EhRD29pe2YdHwl8+uYXjczN+O17mMGTNZ+MvRWrZkRpIVE2h3PT7El0XxwbxVZL8Fbdxs4Y38ZtamhRHi5+X0ZyxPCiG3rmfalrj9pe30j5r4+o2ZLruP+Xh6sC49fLLhwNn6Hpp7RyYTLnf4eRlZnx7OC6cb2FPUyo0LoqV7mRBCiKuWO93PIpVSIbbvfYHrgRKl1LwpL7sdKLF9/xpwv1LKWymVCswDTlzUWQsh5pTSln5MZsus43Lre8iICmBdejib5kXwl6M1Lu+zo6CZjoFRPrvRvsh/wqZ5EeQ39Nqd8/LE4Rrquob49HrnsQDLk0LpHzVR3nZ+C9vOc81EBHixys0zYrZkRlLTOURNxyAvnm7Ax9PAtpxot2In/L9b5pMY5svAqIlbZ6jhEUIIIa507vxaLxZ4RymVD5zEWlPzBvBjpdQ52/iNwFcBtNaFwHNAEbALeFhrbXZ8ayHEle54VSfbfnGQTz9+clphvCtaa87W97A0MQSAB9el0No3yr6SthnjHj9SQ1qEP5synNemrEgOxWTR5Df0TI419Qzzi7fLuDY7yunWswkTzQImtqCNjJt5p6SNGxbEuH1GzNYs6wr1znMtvJ7XxPacGAJ9Zu56dqGMqEBefXgjO7+6iS1ycKYQQoirmDvdz/K11sts7ZsXaq1/YBu/x/bnxVrr27TWjVNiHtVap2uts7TWOy/lGxBCXN5ePNOAt9HA8epOvvNKgdtx9V3DdA2OTSY112RFEh3kzdMnnG9By63vIa++hwfXJWOYIblYlmQ7ANOWlFgsmm88n4cG/uO2HJSaOTFJCfcjzN9rslnAgbJ2W6G++9vHksP9mR8bxH/tKqFvxMQ9Uw75nA0Pg2J+bNB7ihVCCCGuFHIwgRDCqZ/sKqG4uY+PrkpkW06Myw/7FxoZN7OzoIXblsQR4G3k6RN1DI6aZuwMNuFsvTVhWJYUAoDRw8BHVybyq3cqaOwZJj7E1y7mySM1BHgbXSYIYf5epEX6c6a2B7AeenmkspMf372IpHA/l3NTynbWjC0pevZkPZGB3rMu1H/qc6v5w7tVNPWMsD7dva5nQgghhLAnVaVCCIc6B0Z57GAVhys7+dJfz/D914tmfVbMW0Wt9I+auGtZPDctjGHUZHG5fQzgUHkHTx2txdfTg6zo88X+ty+NQ2s4VG7fMbGtf4Q38pv4yIoEt7ZxrUgK5UxdN4OjJn65r4INGeF81MmBmY4sSwqlqn2QwqZe3ilt4/5VibMu1I8I8OaRm+bzq48tc3vbmhBCCCHsSVIjxBVuZNxM58DorONePtuIyaJ5/Ssb+dzGVJ44UsNfj9e6Hd/aN8IP3ygiLcKftWnhrEwJIzLQm53nmmeMq2gb4JN/Pk5paz+fWp8y7TDJ9MgAQv08OVVjf0bMcyfrGTdrHlyX7Nb8ViSH0jU4xhefOk3X4BhfvyFrVitRy21b2P7p6bMAs0qIhBBCCHFxSVIjxBXMYtF84o/H2f6/79I/Mrsi/WdP1rMsKYSsmED+/dYFzI8N4tVcu+7sDo2Mm/niU6cZGDXx20+swMOg8DAotufEsK+kjVGT894hfzhYhZeHgf3f2Mq3b8qedk0pxYrkUE5fcPCl1poXzzSyJjWMtMgAt+Z425I4tmZFcqiig82ZkaywFf+7a2liCFnRgXQMjPHRlYkkhLretiaEEEKIS0OSGiGuYK/kNnKqtpv2/lF+u7/S7bjTtd2Utw1w38rzqw83L4zhdG03zb3DM8Zqrfnuq+fIre/h5/ctmXZWzPr0cEbGLRQ19TmMbesf4eWzjdy7MoHwAG+Hr1mRHEZVxyAdU1afztT1UN0xOKtie39vI49/ehVPfGYV/33vYrfjJvh6ebD7nzeT970b+fE9s48XQgghxMUjSY0QV6iRcTM/3lnCksQQ7lgax58OVdPYM3NCMuHxwzUE+3pyx9LzZ5/cvDgWgJ0F9odWTvWXo7U8d6qBf7o2g+0LY6ddm+g6llvf4zD29weqMFksfG5jmtP7r0yxdS6bslrz0hnrOS+z6T4G1pWfrVlRRAX6zCpOCCGEEJcXSWqEuEK9kd9MW/8o37wxi29tt27j+umuEhdR1vNadhW2cP+qRPy8zncpS48MIDsmkF2FzpOa41Wd/OCNIq6fH8XXrs+0ux4T7ENMkI/DpKa5d5injtVy9/IEUiP8nf6MRfHBeHkYOFXTBViTt/d6zosQQgghrgyS1AhxBdJa8+SRGjKiAtiQEU58iC+f25jKK7lN5DlZJZnw1LFatNZ80kHB/dasKM7UWjuGOfLT3aXEBvvwPx9d6vScmKWJIZyts5/Db96pRGvNV6+bN+P8fDw9WJEcyoEyawe0fSVt9I2YuHv5ezvnRQghhBBznyQ1Qlzmipr6qO8amlVMXkMvBY29fGpd8mRHry9vTSfQ28izp+qdxo2Mm3n6RB03LohxWPi+ISMck0VzwrZKMlV5az+nart5cF3yjCsmy5JCqOsamtaRbWjMxMtnG7ljaTyJYa4L7q+bH0VZ6wD1XUO8eLqB6CBvNmTIOS9CCCHE1UqSGiEuY6dru7nz14fZ+t/7+dHOYrfj3shrwsto4M5l8ZNjgT6e5MQHOS3SB3jlbCM9Q+N8ekOKw+srk8Pw8jBwpKLD7trTJ+rx9FDc42LFZGliCDC9rmbXuRYGRk3c62ah/3XzowFr7c/+snbuXBYv57wIIYQQVzFJaoS4hEZNZv5vX7nLjmGOdAyM8sWnThMb4sP2nBh+f6CK6o5Bl3Faa/YUtbIhPdxuxWR+bBClLf0OD9HUWvPEkRqyYwJZkxrm8N6+XtatX4cqOqeNj4ybeelsAzcuiHHatWzCooRgPAxqWlLzwukGksL8WJXi+OdeKDXCn7QIf/58uJpAHyOfWOPe2TRCCCGEuDJJUiPEJfTYgSr+e08ZP97pukD/Qs+erKdjYJTffWIF/3bLfAB2FMx8cCVAaWs/dV1D3Jhj3wlsfkwQw+Nmah1sZzta1UlJSz+f3ZA64yGUGzLCKW7um7Z9bHdhCz1D49y/2vUBlH5eRrKiAyeTmubeYY5UdnL38nindTiO3LYkjkBvI09+ZrVbW9aEEEIIceWSpEaIS6S2c5BfvVOBv5cHr+c1Udfpfl2MxWI9/HJdWjjzY4OIC/FlRXIob+S7Tmp2n2tFKWvdyYXmxwYBUNxsvwXticM1hPp5cvuUNs6OrLfVrhytOr9a88yJehLDfNmQ7l5dy9KkEHLrerBYNHsKWwG4dfHMP/dCX71uHif+7XqW2LazCSGEEOLqJUmNEDOo6RjkZ3tK6R4cm3Xsnw9Vo4CnH1qL0WDgD+9WuR17tKqTuq6haSsftyyKpbi5j8r2Aadxr5xt5NfvVLA+Pdzh2SvzogPwMCi7pKapZ5i3i1t5YE0SPp4eM85tcXwwgd5GDtu2oFV3DHK0qpP7VyW5vdKyLDGE/lETVR0D7DzXzLyoADKiAtyKnWAwKHy9Zp6rEEIIIa4OktQI4URefQ93/eYwv9pXwa2/OkRFW7/bsRaLZndhK1syI1mcEMINC6LZU9SC1va1LI785aj18MttU7aQ3bDAWhx/tLLTYUx1xyD//Fwuy5JC+PUDyx2+xsfTg7QIf4qbp7+XnedasGi4d4Xr7WNGDwNr0sI5UmltFvD44Wo8PZTbRf5g7YAGsLe4jRPVXWyf5aGZQgghhBBTSVIjhBPfffUcvp4e/PqB5QyNmfiP14rcjs1t6KGlb2Tyw/qGjAha+0apcqPQv7y1n92FrXxqXfK0VZOEUF9C/Dw519jrMO5vx2rxUIpffWwZIX5eTu8/PzaIgsaeaQnW7sIWsmMCSZnh0MupNmSEU9s5xLnGXp47Vc+dS+OJCrJfGXImLSKAQB8jv3i7HItmWvImhBBCCDFbktQI4UBD9xB5Db08uD6FWxbH8uWt6Ryq6OBMXbdb8bvOteDpoSZbD2/ICAdw2Ar5Qr89UImvpwef3pA6bVwpxaL4YAocJDUj42aeP93AtoUxLpOLrVmRtPaNcqrW+l46B0Y5VdPlsLGAMxNnwnzuyZOMjFv4wuY0t2PBunXsnuUJzIsO4NG7FpITFzSreCGEEEKIqSSpEcKB3bbi9YkVhI+vSSbUz5PfvFPpMra9f5QXTjewISOCYF9rS+WkMD/iQ3w54mTr2IQ9hS28dKaRT6xNIszffrUlJy6YstZ+Rk3maeM7zzXTOzzuVmvjbTkx+Hp68NKZRgDeLm61rZZEu4ydMC8qgHtXJBAf4stDm9PIjA50O3bCf9yew2tf2cjH1yTP2G1NCCGEEMIV44c9ASEuR7vONZMdE0iqbTuWv7eRWxfH8crZRrTWDj+ED4yaOFrZyRNHqhkcNfGdm+dPXlNKsT49nLeKW7FYtMOC+oq2fr72bC5LEkP4lxuzHM5rUXww42ZNWcsAixKCJ8cPlnUQ7u/F2jTX57z4exvZlhPNm/lNfO+2BbxwuoHUCH8WxLq/WqKU4qf3LnH79UIIIYQQl5Ks1IhLqqp9gHGz5UP52Vpr2vtH6RmaXeey6o5BTtV22xWvz4sOoH/URHv/qMO4n+0p5Qt/OcXhik6+d1uO3erF+oxweobGKXLQTtls0Xzj+Xy8jQYe++QKpx3IFsVbE5mpW9C01hyp7GBderjbKx73rEigb8TE914t5GRNNw+sTpLVEiGEEELMWZLUiEumpKWP639+gH99If89xZstmk8/foKPPXaMkhb7RMBV7Ed+d5RVj77N2h/t5S9Ha9zuPPaLt8vwMXrw8Qu2cqVHWlsOVzhoqay1Zve5FjZnRnL0kWt5YE2S3WvW285wmegaNtWTR2rIre/hP27PIXqGmpjEMF+CfIzTkprqjkFa+0Yn7++OjRkR3LAgmmdP1ePlYeCeWXQuE0IIIYS43EhSIy6ZX+61drZ66Wwj+0vbZh3/t+O17C9tJ6+hh3t+c4Te4XG3Y49UdnC6tpvPbkhlTWo43321kBdON7iMK23p57W8Jj69IYXIQO9p1yaSmsp2+w5mhU19NPWOcOviWGKDfR3eOzrIh/RIf7u6Gq01fz1Wy6qUUG5fMvMBlEopliaFcrq2a8p7td5vXXq4y/c39T4/unsRUYHe3L083mH9jhBCCCHEXCFJjbgkSlv62VHQwhe3pJEW6c9/7ymdVXxz7zA/2VXKpnkRPPGZ1QyOmTnsRuewCc+daiDEz5N/vSmLJz6ziqWJIfx0dylDY6YZ4544Uo230cBDm+y7eUUHeePv5UFlm/1KzVtFrRgUXJcdNeP9N2REcKK6izHT+S15xc39VHUMcueyeLe2gK1JDaOsdYAu24GgRyo7iA32ISXcz2XsVBEB3uz/5lYevWvRrOKEEEIIIS43ktQIp0bGzbxT2obpPdTEvHSmAU8PxZe3pHProliKmvpcJhQTtNb8+yuFmCwWHr1zEcuTQgjyMbq92tMzNMbuwhbuXBqPt9EDpRT/fut82vpHefxwjdO4gVETr+Y2cdviOEIdrFwopUiPCqDSwfazPUWtrEgOJTzA2+7aVOvTwxkaM5Pf0DM5tqOgGYNy/6yWNanWZgAnqrvoHRpnb3Eb12ZHvaeaGD8vIx4OmhYIIYQQQswlLpMapZSPUuqEUipPKVWolPq+bfynSqkSpVS+UuplpVTIlJhHlFIVSqlSpdS2Szh/cYl0Dozy8T8e5zOPn+Srz+TOuth/X0kbq1PDCPHzYmlSCBYNBQ2OD4280M5zLbxd3MrXb8gkKdwPo4eBTfMiOVDW7rIuxmS28PXn8jCZLdy/OnFyfEVyGIsTgjlU7ny159XcRobGzA7rYSakRwZQdcH2s4q2foqb+7hpYazL97Y2LRyl4HCFdcuY1po3C5pZlx5OhIuEaMLihBC8jQaOV3fySm4joyYLH1vtfM5CCCGEEFc6d1ZqRoFrtdZLgKXAdqXUWuAtYKHWejFQBjwCoJRaANwP5ADbgd8opRy3chKX1N+P17Htfw4yMOreCslU33ohn3ONvdy7IoE3C5r52Z4yt2Pru4YobxvgmizrVqwlCSEA5Nb3uIztHRrne68VsjA+iM9OOXxyi+3AyOLm/hnj/3dvOftK2vjhnQvJjpneonh+TBAlLX1OE6PnTjWQHRPI0sQQp/dPi/CnsWd42qrTK2ebMCi4dYnrpCbEz4ucuKDJZgFFzX1Udwxyy6KZa2mm8jIaWJ4UysGydv56rJZF8cEsjA92HSiEEEIIcYVymdRoq4n9Np62L6213qO1nvhkdwyYaJ90B/CM1npUa10NVACrL/K8rwrDY2ZGxs2uX+iA1prfH6yktLWf3+6vmFVsYVMve0va+MdrM/jpvUu4aWEMz52qn1YHMpOJbWLX2OpLwgO8SQrzcyup+fGuYroGx/jx3Ysxepx/PLdkRgKOO4dNGBk389SxWm5aGGPXuQwgOzaQ7qFxhy2Z6zqHyKvvcVnXkhFlbRZQ1mr9v4TWmldyG9mQEUFUoPOuZVNtSI/gbF0Pw2NmdhQ042FQszr4EmDjvAgq2wcpbxvgE2tllUYIIYQQVze3amqUUh5KqVygDXhLa338gpd8Fthp+z4eqJ9yrcE2duE9H1JKnVJKnWpvb5/1xK90Fovm/j8cY9svDtI54PhclJkcq+qitnOI+BBf/vBuNQ3dQ27H/nZ/JQHeRj65LgWA+1Yl0jU4xt7iVrfi9xS1khzuR5rt4EqAJYkh5LlIao5XdfL0iXo+tzHVbuUhOsiHhFBfztR1O43fXdhCz9C4w4QGmFy5KW6xX+15o6AJgFsWzbzasiIlFDifXOU19NLQPcydS+0ecafWpYczZrZwsqaLN/ObWZcW7rIW50Kf35TKS/+wnre/vpn7Via6DhBCCCGEuIK5ldRorc1a66VYV2NWK6UWTlxTSv0bYAL+NjHk6BYO7vmY1nql1nplZGTkrCd+pdtd2EJefQ91XUN8/i+nZl2s/8zJOgJ9jPzlc6sZM1l4La/Jrbjm3mF2FDTz8bVJBPt6ArB5XiQxQT48e6reRbS169m75R3cszxh2orH0sQQmnpHaOsbcRg3ajLzyMsFJIT68rXr5zl8zfKkUE7XdjvdPvb0iToSw3xZ76S1cXZMoG2O9mfevJHXzLKkEBLDZu4gFhXow/zYIA6WWRPxY1XW2pgtWe4/w6tTwzAaFL/cW05N5xC3LHa9be1C3kYPlieFkhEVKIdmCiGEEOKqN6vuZ1rrHmA/1loZlFKfAm4FPq7Pf9JsAKb+6jgBcO8TtQCsqzT/83YZ6ZH+/Oddizhb18OJmi7XgTYtvSPsKGjmnuUJpEcGTPsQ7srzpxqwaPjElNUOD4PijqVxHCrvcNnB7PcHKvH19ODBddNXSybqVM46Wa15Pa+ZqvZBfnjHQvy8jA5fszwphNa+UZp67ROjE9VdHKvq4oHVyRicdPMK9fciOsibkgvqcl4600BRcx+3LXavrmXzvAhO13YzOGriRHUXaZH+bhf5g7Xj2IrkUE7VdjMvKoCb3WgwIIQQQgghnHOn+1nkRGczpZQvcD1QopTaDvwrcLvWeurepteA+5VS3kqpVGAecOKiz/wKVtDYS1nrAF/aks7tS+Lw8jCwr9j9wyv/dKgKi4bPbbQW2m/JjORUTbfLhgEWi+bZk/VszIiwW7FYlx6OyaI5U9vjMHbUZObnb5Xxal4T969OJMRvekvknLggPD2U07qaZ07UkRbhz9YZVjxWJFtbGZ+pnb4FzWLR/PCNImKDffj0+pQZ32N2TNC07WfHqzr55gv5bMgI5+Nu1qZszoxk3Kw5UtnJyZquyRbLs/Hzjy7lxS+vZ/fXNhPs5znreCGEEEIIcZ47KzWxwDtKqXzgJNaamjeA/wMCgbeUUrlKqd8BaK0LgeeAImAX8LDW+r1Vu1+lDtkOmbwmOwp/byNr08PZV+JeUtM7NM7fj9dx6+LYycRkc2YEJovm6AUn2V/ondI2GnuG+egq+xqNlSlheBgUx6sd3+N3+6v45d5yblkUy9euz7S77uPpwfzYIHLreuyuVbT1c6q2m4+uSpxxK1V2bCA+nga7upo3CpopaOzlW9uz8PWaudFeTlwQ5a39k80Cnj1VT5CPkd9/ciXeRvea9K1IDsXPy4Of7i6hf8TEqpTZJzXxIb6sSA51uqokhBBCCCHc5073s3yt9TKt9WKt9UKt9Q9s4xla60St9VLb15emxDyqtU7XWmdprXc6v/uVa2DUxJ2/Psy/vVzg9qGTEw6VdzA/NmhyS9N12VFUdQxS5eDQxws9dayGwTEzX9ycPjm2MjkMPy+PGbegjZksPPpmMSnhftzooBNXgLeRhXFBkzUkU53vABbOLz+2bLIW50JLE0PIb+jBbJleE/P8qQaMBsU9KxIcxk3w9DCwOCGEMxckRn86VE1ahD93LHFdrH/vykTMWvPkkRq01hwq72BDRgQB3o63vDni4+nBIzfPn+yAtvo9rNQIIYQQQoiLZ1Y1NcJ9/727lLyGHv5+oo7PPnHS7bjhMTOna7vZNC9icuxaW2vkAy7qYkbGzTx+uIatWZEsiDt/RouX0cC6tHAOljuPf/JIDVUdg3zvthynKxZr0sLJq++1azNd2GQ9a8VVTcrSxBAGx8xUTknOtNbsLmxhQ0aEW3Upy5NCKWw8P4czdd3k1ffw6Q0pbq16pEb4s21BDE8dqyW3voe2/tFp/67d9Yk1SXxybTKLE4JJCJ25uYAQQgghhLi0JKm5BM419vLk0Ro+uTaZr12XybGqLtr6HXf9utCJmi7GzBY2ZJz/oJ0Y5kdkoDeFTfZdu6Z67lQ9nYNjfGlLut21zZmR1HYOUds5aHdt1GTm9wcr2ZwZOXm2jCNrUsMYM1vstn+9nteE0aDYvjBmxvktsTULmLoFrbJ9gJrOIW5Y4N45LcuTQjBZNAWNvQD88d0qAn2M3LN85lWeqb64JY3e4XG+/NczAGycN/vue0opfnjnQl59eMOsY4UQQgghxMUlSY0D/SPjfP/1Qhb9x25OVLvfdWzC7w9WEeBt5BvbsiZXWY5UzFzPAmAyW/jft8sI8jGy+oI6jeyYQIqbnSc1fSPj/O/b5axOCXNYuL7Zdniloy1or+U20TEwxhc3p804v5UpYSgFx6vO/zsZN1t4+WwjWzIj7ZoDXCg13J8wf69pW9j2FFnPvrluvvNkaqrlydZzYs7UWldodhS08Jn1KfjPYvvYsqRQvnrdPFr6RkiL8Cc+xNft2AtJO2UhhBBCiA+fJDUO/PCNIp48UoPJrPnVvvJZxTb1WM95uX9VIkE+niyICyLEz3Oy+H8mvz9YxZm6Hn5450K7gvcFsUGUtw44Pa/m1+9U0DU0xr/fusDhB+2UcD8Sw3zttrBprfnToWqyYwKdnu8yIdjXkwWxQdOaBewubKGtf9StzmEGg2LzvAgOlLVjsdXVvFXUyqL4YGKD3UssIgK8SQ7342RNNz/aWUy4vxcPOViZcuVr18/ji1vS+NLW2ccKIYQQQojLiyQ1FxgcNfFGfjP3rUzkK9dm8G55B0Uutn2BNTn4ya4SvvCXU2it+ZSttbCHQbE+PZwjFR1OD40E65a1/3mrjFsXx3KHg9Pps2MDGTNbqO6w3z5W2znI44dquGd5AosSgh3eXynF5nmRHKnsZMx0PjE6WtlJSUs/n92Q6taqw5rUcM7W9TBqsta0PHmkhqQwP7ZmurfSsjUris7BMc419VLW2s/Zuh5uWjTztrULLU8K5e3iVo5VdfH1GzNnVeQ/QSnFIzfN576V9p3ehBBCCCHE3CJJzQV2FDQzNGbm3pUJfGJNMn5eHvzh3SqXcbn1PfxmfyXD42a+fVP2tOLx9ekRNPWOOExIwFrT8s/P5hIe4MX/d+dCh6/JjrEW/hc52IL2ox0lGD0U39yWNeMcN2REMDRm5lxT7+TYnw5VExHgxe1L3Tt4ck1aGKMmC3n1vRQ393GyppsH1zk/8PJCmzMjUQr2l7bz+OEavI0G7l/l3vkw5+8RgVLw3VsX8PE1ya4DhBBCCCHEFW32v+K+wj1/uoHUCH+WJ4WilOL+VUn85WgN39yWRdwMtRev5zXj5WHglYc3EOQzvaXxRlvR/+GKDtIiA+x/5qkGytsG+NOnVjqtS0mPDMDTQ1HS0s8dU8bP1nWzq7CFb9yYSXSQz4zvbeI8lZPVXSxPCqWqfYC9JW189bp5+Hi6d0bLRK3PsapOuofG8PIwzKpIP8zfi8UJIfz1WC19I+PcuTSeMP+Za3EudOfSeK7JinJZwyOEEEIIIa4OslIzxajJjAI+siJhcivWZzemoIE/H6p2Gme2aN7Ib2JrVqRdQgOQHO5HfIivw7qacbOF3x2oZGliyGRTAUe8jAbSIwPsmgW8eKYBH08Dn96Q6vL9RQZ6kxrhz8kaa6H/f+8pxcfTwCfWur/aEervxeqUMB4/XM3LZxu5ISea0FkmJf+63Zog+nkZ+fwm1/O+kFJKEhohhBBCCDFJkpopvI0ePPvFdfzDlOLxhFA/bl0cy99P1NHa57gt8/HqTtr6R7ltieMtXEopNmZEcLSy0+7gyZfPNNLQPcw/XpvhsqZlUXwwufU9k0X242YLb+Y3c/38aLfrSlalhHKyppt3y9vZUdDCw1sziAx0fT7MVP9590KGxsz0DI2/p5qU9ekRvPLwBs78+w3Miw6cdbwQQgghhBBTSVLjwIXJxT9fn4nJovnhG0UOX/+7A1WE+XvN2JZ4fUY4fSMmzjWer2fpGhzjx7tKWJY08yrNhHXp4fQMjVPcYl2tOVTRQffQuMPGAs6sSgmjd3icLz11mqQwP77goo2zIxlRgTx61yK2ZkVObq0TQgghhBDiwyJJjRtSIvz5h63pvJHfPLl1a8KJ6i4OlrXz5S3p+Hk5Xy1Zn2798D91C9qPdhTTNzzOj+5e5FbnsYl7HK20tlR+LbeJIB8jmzPdTyzWpoVjUJAU7s+Tn13tdi3NhT6yIoEnPrMaDzcbBAghhBBCCHGpSFLjpi9uTsfbaODN/OZp479+p4LIQG+XdSmRgd4sSQzhtdwmtNYMjZl4NbeJj61Omuxs5kpMsA9pkf4cqexkeMzMnsIWbl4Ui7fR/cQkMcyPPf+8hZf/YT2pEf5uxwkhhBBCCHG5kqTGTb5eHqxLD592eGX34BiHKjr4yIoEu8MyHblvZQKlrf3kN/RyvKqLMbOFG3OiZzWP9enhHK/qZHdhC4NjZrdbMU+VERXwnldohBBCCCGEuNxIUjMLWzMjqe4YpLbTet7MW8WtmC2amxa6d3jkbUvi8PE08Nypeg6UtePjaZhss+yua7OjGBwz8+2X8okO8mZNavis34cQQgghhBBXEklqZmFrlrWYf0dBC6MmM7vOtRAf4sui+GC34oN8PLllURwvnG7gjfwm1qaFz3rF5JqsKH5450JMZs3dyxOkpkUIIYQQQlz15PDNWUiJ8Cctwp//2lXCf+0qAeBzG1PdKvKf8J2bs8lv6KG8bYAtmZGznoNSik+uTWbbguhZH1ophBBCCCHElUiSmll67MGVnKrpor1/lL6RcT7jxqGXU4UHePO3z6/hT4eruXtZwnueR1SQz3uOFUIIIYQQ4koiSc0sZUQFkBEV8L7uERXkwyM3zb9IMxJCCCGEEOLqJjU1QgghhBBCiDlNkhohhBBCCCHEnCZJjRBCCCGEEGJOk6RGCCGEEEIIMadJUiOEEEIIIYSY0ySpEUIIIYQQQsxpktQIIYQQQggh5jRJaoQQQgghhBBzmtJaf9hzQCnVDtR+2PO4DEQAHR/2JMRVT55DcTmQ51BcLuRZFJcDeQ7PS9ZaR144eFkkNcJKKXVKa73yw56HuLrJcyguB/IcisuFPIviciDPoWuy/UwIIYQQQggxp0lSI4QQQgghhJjTJKm5vDz2YU9ACOQ5FJcHeQ7F5UKeRXE5kOfQBampEUIIIYQQQsxpslIjhBBCCCGEmNMkqRFCCCGEEELMaZLUXEJKqT8rpdqUUuemjC1RSh1VShUopV5XSgVNubbYdq3Qdt3HNr7C9ucKpdQvlVLqw3g/Ym6azXOolPq4Uip3ypdFKbXUdk2eQ/G+zPJZ9FRKPWkbL1ZKPTIlRp5F8Z7N8jn0Uko9bhvPU0ptnRIjz6F4z5RSiUqpd2z/fStUSn3VNh6mlHpLKVVu+2folJhHbM9bqVJq25RxeRaRpOZSewLYfsHYH4Fva60XAS8D3wRQShmBvwJf0lrnAFuBcVvMb4GHgHm2rwvvKcRMnsDN51Br/Tet9VKt9VLgk0CN1jrXFiPPoXi/nsDNZxG4F/C2ja8AvqiUSrFdk2dRvB9P4P5z+AUA2/gNwM+UUhOfneQ5FO+HCfgXrfV8YC3wsFJqAfBtYK/Weh6w1/ZnbNfuB3KwPmu/UUp52O4lzyKS1FxSWuuDQNcFw1nAQdv3bwH32L6/EcjXWufZYju11malVCwQpLU+qq1dHf4C3HnJJy+uGLN8Dqf6GPA0gDyH4mKY5bOoAX/bL3x8gTGgT55F8X7N8jlcgPWDJVrrNqAHWCnPoXi/tNbNWusztu/7gWIgHrgDeNL2sic5/1zdATyjtR7VWlcDFcBqeRbPk6Tmg3cOuN32/b1Aou37TEArpXYrpc4opb5lG48HGqbEN9jGhHg/nD2HU30UW1KDPIfi0nH2LL4ADALNQB3w31rrLuRZFJeGs+cwD7hDKWVUSqViXTVMRJ5DcRHZVqGXAceBaK11M1gTHyDK9rJ4oH5K2MQzJ8+ijSQ1H7zPYl1iPA0EYv3tI4AR2Ah83PbPu5RS1wGO9kVKH27xfjl7DgFQSq0BhrTWE3vO5TkUl4qzZ3E1YAbigFTgX5RSacizKC4NZ8/hn7F+SDwF/AI4gnXbkDyH4qJQSgUALwJf01r3zfRSB2N6hvGrjvHDnsDVRmtdgnWrGUqpTOAW26UG4IDWusN2bQewHGudTcKUWyQATR/YhMUVaYbncML9nF+lAevzKc+huOhmeBYfAHZprceBNqXUYWAl8C7yLIqLzNlzqLU2Af888Tql1BGgHOhGnkPxPimlPLEmNH/TWr9kG25VSsVqrZttW8vabOMNTN9VMfHMyd/PNrJS8wFTSkXZ/mkA/h/wO9ul3cBipZSfbQ/5FqDItvTYr5Raa+tm8SDw6ocwdXEFmeE5nBi7F3hmYkyeQ3GpzPAs1gHXKit/rIW0JfIsikvB2XNo+zvZ3/b9DYBJay1/N4v3zfbc/Ako1lr/fMql14BP2b7/FOefq9eA+5VS3ratkPOAE/IsnicrNZeQUupprF3MIpRSDcD3gACl1MO2l7wEPA6gte5WSv0cOIl12XCH1vpN2+u+jLVbiy+w0/YlhFtm8xzabAYatNZVF9xKnkPxvszyWfy17ftzWLdXPK61zrddk2dRvGezfA6jgN1KKQvQiLUr5AR5DsX7sQHr81SglMq1jX0H+DHwnFLqc1h/uXMvgNa6UCn1HFCEdQvkw1prsy1OnkVAWRslCCGEEEIIIcTcJNvPhBBCCCGEEHOaJDVCCCGEEEKIOU2SGiGEEEIIIcScJkmNEEIIIYQQYk6TpEYIIYQQQggxp0lSI4QQQgghhJjTJKkRQgghhBBCzGn/P/ilfu13o5GKAAAAAElFTkSuQmCC\n"
},
"metadata": {
"needs_background": "light"
}
}
],
"source": [
"def load_mauna_loa_atmospheric_co2():\n",
" ml_data = fetch_openml(data_id=41187, as_frame=False)\n",
" months = []\n",
" ppmv_sums = []\n",
" counts = []\n",
"\n",
" y = ml_data.data[:, 0]\n",
" m = ml_data.data[:, 1]\n",
" month_float = y + (m - 1) / 12\n",
" ppmvs = ml_data.target\n",
"\n",
" for month, ppmv in zip(month_float, ppmvs):\n",
" if not months or month != months[-1]:\n",
" months.append(month)\n",
" ppmv_sums.append(ppmv)\n",
" counts.append(1)\n",
" else:\n",
" # aggregate monthly sum to produce average\n",
" ppmv_sums[-1] += ppmv\n",
" counts[-1] += 1\n",
" \n",
" months = np.array(months).reshape(-1, 1)\n",
" avg_ppmvs = np.array(ppmv_sums) / counts\n",
" return months, avg_ppmvs\n",
"\n",
"def to_torch_cuda(V):\n",
" return torch.tensor(V).flatten().double().cuda()\n",
"\n",
"X_raw, Y_raw = load_mauna_loa_atmospheric_co2()\n",
"\n",
"X_test = np.linspace(X_raw.min(), X_raw.max() + 30, 1000)[:, np.newaxis]\n",
"\n",
"f, ax = plt.subplots(1, 1, figsize=(14, 4))\n",
"ax.plot(X_raw, Y_raw)\n",
"\n",
"X_torch = to_torch_cuda(X_raw)\n",
"Y_torch = to_torch_cuda(Y_raw)\n",
"X_test_torch = to_torch_cuda(X_test)"
]
},
{
"source": [
"# Scikit learn version\n",
"\n",
"see https://scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_co2.html\n"
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.gaussian_process import GaussianProcessRegressor\n",
"from sklearn.gaussian_process.kernels \\\n",
" import RBF, WhiteKernel, RationalQuadratic, ExpSineSquared, ConstantKernel"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\nLearned kernel: 2.63**2 * RBF(length_scale=51.6) + 0.155**2 * RBF(length_scale=91.6) * ExpSineSquared(length_scale=1.49, periodicity=1) + 0.0315**2 * RationalQuadratic(alpha=2.87, length_scale=0.968) + 0.011**2 * RBF(length_scale=0.122) + WhiteKernel(noise_level=0.000126)\nLog-marginal-likelihood: 1362.655\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.collections.PolyCollection at 0x7f59ac0e69d0>"
]
},
"metadata": {},
"execution_count": 4
},
{
"output_type": "display_data",
"data": {
"text/plain": "<Figure size 1008x504 with 1 Axes>",
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\n"
},
"metadata": {
"needs_background": "light"
}
}
],
"source": [
"# Kernel with optimized parameters\n",
"k1 = 50.0**2 * RBF(length_scale=50.0) # long term smooth rising trend\n",
"k2 = 2.0**2 * RBF(length_scale=100.0) \\\n",
" * ExpSineSquared(length_scale=1.0, periodicity=1.0,\n",
" periodicity_bounds=\"fixed\") # seasonal component\n",
"# medium term irregularities\n",
"k3 = 0.5**2 * RationalQuadratic(length_scale=1.0, alpha=1.0)\n",
"k4 = 0.1**2 * RBF(length_scale=0.1) \\\n",
" + WhiteKernel(noise_level=0.1**2,\n",
" noise_level_bounds=(1e-5, np.inf)) # noise terms\n",
"\n",
"kernel = k1 + k2 + k3 + k4\n",
"\n",
"gp = GaussianProcessRegressor(kernel=kernel, alpha=0,\n",
" normalize_y=True)\n",
"gp.fit(X_raw, Y_raw)\n",
"\n",
"print(\"\\nLearned kernel: %s\" % gp.kernel_)\n",
"print(\"Log-marginal-likelihood: %.3f\"\n",
" % gp.log_marginal_likelihood(gp.kernel_.theta))\n",
"\n",
"y_pred, y_std = gp.predict(X_test, return_std=True)\n",
"\n",
"# Illustration\n",
"f, ax = plt.subplots(1, 1, figsize=(14, 7))\n",
"ax.plot(X_raw, Y_raw, 'k.', markersize=4)\n",
"ax.plot(X_test, y_pred,\"-\", color=\"steelblue\")\n",
"ax.fill_between(X_test[:, 0], y_pred - y_std, y_pred + y_std, alpha=0.3, color='k')"
]
},
{
"source": [
"# Gpytorch version"
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"# to keep things simple, this block basically just takes the code\n",
"# from the `Simple_GP_regression.ipynb` demo notebook and wraps it in a function\n",
"\n",
"class ExactGPModel(gpytorch.models.ExactGP):\n",
" def __init__(self, train_x, train_y, likelihood, kernel):\n",
" super(ExactGPModel, self).__init__(train_x, train_y, likelihood)\n",
" self.mean_module = gpytorch.means.ConstantMean()\n",
" self.covar_module = kernel\n",
" \n",
" def forward(self, x):\n",
" mean_x = self.mean_module(x)\n",
" covar_x = self.covar_module(x)\n",
" return gpytorch.distributions.MultivariateNormal(mean_x, covar_x)\n",
"\n",
"def createAndRunModelWithKernel(\n",
" kernel_gen_fn,\n",
" train_x,\n",
" train_y,\n",
" test_x = None,\n",
" num_restarts = 5,\n",
" likelihood_noise = None,\n",
" training_iter = 50\n",
"):\n",
" gc.collect()\n",
" torch.cuda.empty_cache() \n",
"\n",
" # initialize likelihood and model\n",
" likelihood = gpytorch.likelihoods.GaussianLikelihood()\n",
"\n",
" # see: https://github.com/cornellius-gp/gpytorch/issues/559#issuecomment-471243041\n",
" if likelihood_noise is not None:\n",
" likelihood.initialize(noise=likelihood_noise) \n",
"\n",
" likelihood.cuda()\n",
" model = ExactGPModel(train_x, train_y, likelihood, kernel_gen_fn())\n",
" model.cuda()\n",
"\n",
" # Find optimal model hyperparameters\n",
" model.train()\n",
" likelihood.train()\n",
"\n",
" # Use the adam optimizer\n",
" optimizer = torch.optim.Adam(model.parameters(), lr=0.1) # Includes GaussianLikelihood parameters\n",
"\n",
" # \"Loss\" for GPs - the marginal log likelihood\n",
" mll = gpytorch.mlls.ExactMarginalLogLikelihood(likelihood, model)\n",
"\n",
" for i in range(training_iter):\n",
" # Zero gradients from previous iteration\n",
" optimizer.zero_grad()\n",
" # Output from model\n",
" output = model(train_x)\n",
" # Calc loss and backprop gradients\n",
" loss = -mll(output, train_y)\n",
" loss.backward()\n",
" optimizer.step()\n",
"\n",
" # Get into evaluation (predictive posterior) mode\n",
" model.eval()\n",
" likelihood.eval()\n",
"\n",
" # Make predictions by feeding model through likelihood\n",
" with torch.no_grad(), gpytorch.settings.fast_pred_var():\n",
" if test_x is None:\n",
" test_x = train_x\n",
" observed_pred = likelihood(model(test_x))\n",
" log_likelihood = mll(output, train_y)\n",
" M = len(list(model.named_parameters()))\n",
" N = train_x.shape[0]\n",
" BIC = -2*log_likelihood + M * np.log(N)\n",
"\n",
" # bigger plot of the last model\n",
" f, ax = plt.subplots(1, 1, figsize=(14, 7))\n",
" # Get upper and lower confidence bounds\n",
" lower, upper = observed_pred.confidence_region()\n",
" # Plot training data as black stars\n",
" ax.plot(train_x.cpu().numpy(), train_y.cpu().numpy(), 'k.', markersize=3)\n",
" # Plot predictive means as blue line\n",
" ax.plot(test_x.cpu().numpy(), observed_pred.mean.cpu().numpy(), \"-\", color=\"steelblue\")\n",
" # Shade between the lower and upper confidence bounds\n",
" ax.fill_between(test_x.cpu().numpy(), lower.cpu().numpy(), upper.cpu().numpy(), alpha=0.3)\n",
" ax.set_title(f\"BIC: {BIC:.2f}, mll: {log_likelihood:.2f}\")\n",
"\n",
" return model, likelihood"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"# attempting to translate kernel from sklearn example above\n",
"def full_kernel_fn():\n",
" #### long term\n",
" k_long_term_RBF = RBFKernel()\n",
" k_long_term_RBF.lengthscale = 50.0\n",
"\n",
" k_long_term = ScaleKernel(k_long_term_RBF)\n",
" k_long_term.outputscale = 50.0**2\n",
"\n",
" #### seasonal\n",
" k_seasonal_RBF = RBFKernel()\n",
" k_seasonal_RBF.lengthscale = 90\n",
"\n",
" k_seasonal_periodic = PeriodicKernel()\n",
" k_seasonal_periodic.period_length = 1.0\n",
" # this must be squared, see https://github.com/cornellius-gp/gpytorch/issues/1020\n",
" k_seasonal_periodic.lengthscale = 1.0**2\n",
"\n",
" k_seasonal = ScaleKernel(k_seasonal_RBF * k_seasonal_periodic)\n",
" k_seasonal.outputscale = 2.0**2\n",
"\n",
" ### medium term\n",
" k_medium_RQ = RQKernel()\n",
" k_medium_RQ.alpha = 1.0\n",
" k_medium_RQ.lengthscale = 1.0\n",
"\n",
" k_medium = ScaleKernel(k_medium_RQ)\n",
" k_medium.outputscale = 0.5**2\n",
"\n",
" #### noise term\n",
" k_noise_RBF = RBFKernel()\n",
" k_noise_RBF.lengthscale = 0.1\n",
"\n",
" k_noise = ScaleKernel(k_noise_RBF)\n",
" k_noise.outputscale = 0.1**2\n",
"\n",
" return k_long_term + k_seasonal + k_medium + k_noise"
]
},
{
"source": [
"Without optimizing anything, let plot the model with pre-specified parameters to see how they compare to the sklearn result:\n"
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"output_type": "display_data",
"data": {
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467.607402 149.248827 \nL 468.318294 156.276688 \nL 469.029187 156.992629 \nL 469.74008 152.211387 \nL 470.450973 146.741681 \nL 471.161865 142.425211 \nL 471.872758 139.438919 \nL 472.583651 137.176966 \nL 473.294543 133.751776 \nL 474.005436 129.590413 \nL 474.716329 127.594632 \nL 475.427222 128.704636 \nL 476.138114 132.979091 \nL 476.849007 139.691397 \nL 477.5599 147.082433 \nL 478.270792 151.010536 \nL 478.981685 148.653818 \nL 479.692578 143.39081 \nL 480.403471 138.623493 \nL 481.114363 134.801864 \nL 481.825256 131.822041 \nL 482.536149 129.062319 \nL 483.247041 125.218126 \nL 483.957934 121.605657 \nL 484.668827 120.83162 \nL 485.379719 123.834099 \nL 486.090612 129.843557 \nL 486.801505 137.283689 \nL 487.512398 143.819825 \nL 488.22329 144.999348 \nL 488.934183 140.707866 \nL 489.645076 135.062964 \nL 490.355968 130.329276 \nL 491.066861 127.11533 \nL 491.777754 124.811035 \nL 492.488647 121.544128 \nL 493.199539 117.304285 \nL 493.910432 115.175796 \nL 494.621325 116.619988 \nL 495.332217 121.368841 \nL 496.04311 128.502718 \nL 496.754003 136.616564 \nL 497.464896 141.690495 \nL 498.175788 140.158497 \nL 498.886681 134.996688 \nL 499.597574 129.991083 \nL 500.308466 126.108669 \nL 501.019359 123.434519 \nL 501.730252 120.925913 \nL 502.441145 117.013056 \nL 503.152037 113.423381 \nL 503.86293 112.928203 \nL 504.573823 115.939399 \nL 505.284715 121.874004 \nL 505.995608 129.661398 \nL 506.706501 137.006534 \nL 507.417394 139.017311 \nL 508.128286 135.081615 \nL 508.839179 129.61002 \nL 509.550072 124.969251 \nL 510.260964 121.564981 \nL 510.971857 119.129414 \nL 511.68275 115.982938 \nL 512.393643 111.737189 \nL 513.104535 109.311659 \nL 513.815428 110.389109 \nL 514.526321 114.789619 \nL 515.237213 121.656201 \nL 515.948106 129.688337 \nL 516.658999 135.11112 \nL 517.369891 133.935649 \nL 518.080784 128.712078 \nL 518.791677 123.460904 \nL 519.50257 119.326703 \nL 520.213462 116.468311 \nL 520.924355 113.966245 \nL 521.635248 110.123737 \nL 522.34614 106.322329 \nL 523.057033 105.455257 \nL 523.767926 108.107067 \nL 524.478819 113.761495 \nL 525.189711 121.38806 \nL 525.900604 128.912614 \nL 526.611497 131.452054 \nL 527.322389 127.772997 \nL 528.033282 122.210668 \nL 528.744175 117.413982 \nL 529.455068 113.884132 \nL 530.16596 111.44265 \nL 530.876853 108.476313 \nL 531.587746 104.287085 \nL 532.298638 101.627733 \nL 533.009531 102.410737 \nL 533.720424 106.551255 \nL 534.431317 113.252195 \nL 535.142209 121.296264 \nL 535.853102 127.171486 \nL 536.563995 126.523931 \nL 537.274887 121.412221 \nL 537.98578 116.064881 \nL 538.696673 111.828362 \nL 539.407566 108.926183 \nL 540.118458 106.55533 \nL 540.829351 102.930646 \nL 541.540244 99.07273 \nL 542.251136 97.953495 \nL 542.962029 100.347041 \nL 543.672922 105.806178 \nL 544.383814 113.342075 \nL 545.094707 121.084694 \nL 545.8056 124.225655 \nL 546.516493 120.916496 \nL 547.227385 115.348314 \nL 547.938278 110.460297 \nL 548.649171 106.861761 \nL 549.360063 104.459119 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577.795772 97.785679 \nL 578.506665 95.688405 \nL 579.217557 92.591338 \nL 579.92845 88.780145 \nL 580.639343 87.236766 \nL 581.350235 89.152199 \nL 582.061128 94.22855 \nL 582.772021 101.56978 \nL 583.482914 109.653147 \nL 584.193806 113.992556 \nL 584.904699 111.580184 \nL 585.615592 106.100251 \nL 586.326484 101.06734 \nL 587.037377 97.346093 \nL 587.74827 95.012315 \nL 588.459163 92.74335 \nL 589.170055 89.095538 \nL 589.880948 86.051441 \nL 590.591841 86.118512 \nL 591.302733 89.580758 \nL 592.013626 95.839488 \nL 592.724519 103.859156 \nL 593.435412 110.968773 \nL 594.146304 112.149664 \nL 594.857197 107.699451 \nL 595.56809 102.21719 \nL 596.278982 97.757358 \nL 596.989875 94.764921 \nL 597.700768 92.789994 \nL 598.411661 89.977705 \nL 599.122553 86.25553 \nL 599.833446 84.532157 \nL 600.544339 86.217203 \nL 601.255231 91.095869 \nL 601.966124 98.324858 \nL 602.677017 106.522731 \nL 603.38791 111.43566 \nL 604.098802 109.537381 \nL 604.809695 104.148195 \nL 605.520588 99.055714 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102.25759 \nL 634.667189 97.670262 \nL 635.378081 94.598515 \nL 636.088974 92.829876 \nL 636.799867 90.602307 \nL 637.51076 87.180995 \nL 638.221652 85.172705 \nL 638.932545 86.416385 \nL 639.643438 90.888413 \nL 640.35433 97.865048 \nL 641.065223 106.186514 \nL 641.776116 112.159941 \nL 642.487009 111.401797 \nL 643.197901 106.296925 \nL 643.908794 101.113537 \nL 644.619687 97.208979 \nL 645.330579 94.913147 \nL 646.041472 93.285951 \nL 646.752365 90.45806 \nL 647.463258 87.36812 \nL 648.17415 86.829512 \nL 648.885043 89.627972 \nL 649.595936 95.385892 \nL 650.306828 103.203706 \nL 651.017721 111.174377 \nL 651.728614 114.29805 \nL 652.439507 110.918134 \nL 653.150399 105.464658 \nL 653.861292 100.820979 \nL 654.572185 97.703216 \nL 655.283077 96.016762 \nL 655.99397 94.080207 \nL 656.704863 90.8663 \nL 657.415756 88.758495 \nL 658.126648 89.793356 \nL 658.837541 94.058246 \nL 659.548434 100.895948 \nL 660.259326 109.231235 \nL 660.970219 115.68023 \nL 661.681112 115.538457 \nL 662.392005 110.631503 \nL 663.102897 105.418576 \nL 663.81379 101.454428 \nL 664.524683 99.152241 \nL 665.235575 97.712345 \nL 665.946468 95.196754 \nL 666.657361 92.171854 \nL 667.368253 91.463076 \nL 668.079146 94.046653 \nL 668.790039 99.624722 \nL 669.500932 107.344385 \nL 670.211824 115.511918 \nL 670.922717 119.272652 \nL 671.63361 116.339569 \nL 672.344502 110.93937 \nL 673.055395 106.245062 \nL 673.766288 103.077545 \nL 674.477181 101.458469 \nL 675.188073 99.806505 \nL 675.898966 96.833848 \nL 676.609859 94.658456 \nL 677.320751 95.494035 \nL 678.031644 99.550568 \nL 678.742537 106.241379 \nL 679.45343 114.562094 \nL 680.164322 121.443934 \nL 680.875215 121.941541 \nL 681.586108 117.27224 \nL 682.297 112.041681 \nL 683.007893 108.019755 \nL 683.718786 105.701713 \nL 684.429679 104.432495 \nL 685.140571 102.240289 \nL 685.851464 99.320837 \nL 686.562357 98.461452 \nL 687.273249 100.83499 \nL 687.984142 106.227544 \nL 688.695035 113.836482 \nL 689.405928 122.156605 \nL 690.11682 126.536259 \nL 690.827713 124.092624 \nL 691.538606 118.770944 \nL 692.249498 114.032238 \nL 692.960391 110.81177 \nL 693.671284 109.244828 \nL 694.382176 107.867241 \nL 695.093069 105.165738 \nL 695.803962 102.956726 \nL 696.514855 103.603905 \nL 697.225747 107.451878 \nL 697.93664 113.988099 \nL 698.647533 122.268635 \nL 699.358425 129.537023 \nL 700.069318 130.690161 \nL 700.780211 126.299721 \nL 701.491104 121.064508 \nL 702.201996 116.98723 \nL 702.912889 114.644042 \nL 703.623782 113.527314 \nL 704.334674 111.664388 \nL 705.045567 108.88978 \nL 705.75646 107.901649 \nL 706.467353 110.070958 \nL 707.178245 115.272924 \nL 707.889138 122.759841 \nL 708.600031 131.189867 \nL 709.310923 136.162863 \nL 710.021816 134.248449 \nL 710.732709 129.032699 \nL 711.443602 124.256266 \nL 712.154494 120.980288 \nL 712.865387 119.449957 \nL 713.57628 118.33306 \nL 714.287172 115.928124 \nL 714.998065 113.721022 \nL 715.708958 114.192136 \nL 716.419851 117.832355 \nL 717.130743 124.20648 \nL 717.841636 132.423962 \nL 718.552529 140.030006 \nL 719.263421 141.847355 \nL 719.974314 137.777951 \nL 720.685207 132.552252 \nL 721.3961 128.422594 \nL 722.106992 126.045328 \nL 722.817885 125.061605 \nL 723.528778 123.528726 \nL 724.23967 120.936549 \nL 724.950563 119.843796 \nL 725.661456 121.815643 \nL 726.372348 126.822631 \nL 727.083241 134.177212 \nL 727.794134 142.676619 \nL 728.505027 148.210417 \nL 729.215919 146.861182 \nL 729.926812 141.780956 \nL 730.637705 136.973868 \nL 731.348597 133.64053 \nL 732.05949 132.131171 \nL 732.770383 131.258167 \nL 733.481276 129.170266 \nL 734.192168 127.001611 \nL 734.903061 127.310559 \nL 735.613954 130.744833 \nL 736.324846 136.949535 \nL 737.035739 145.083656 \nL 737.746632 152.976884 \nL 738.457525 155.459203 \nL 739.168417 151.753361 \nL 739.87931 146.552691 \nL 740.590203 142.374079 \nL 741.301095 139.954322 \nL 742.011988 139.083086 \nL 742.722881 137.876052 \nL 743.433774 135.501321 \nL 744.144666 134.330206 \nL 744.855559 136.11234 \nL 745.566452 140.920728 \nL 746.277344 148.133378 \nL 746.988237 156.664265 \nL 747.69913 162.72002 \nL 748.410023 161.967139 \nL 749.120915 157.054169 \nL 749.831808 152.223896 \nL 750.542701 148.832091 \nL 751.253593 147.328139 \nL 751.964486 146.679486 \nL 752.675379 144.923829 \nL 753.386271 142.830536 \nL 754.097164 142.992882 \nL 754.808057 146.224001 \nL 755.51895 152.252169 \nL 756.229842 160.284968 \nL 756.940735 168.414326 \nL 757.651628 171.554205 \nL 758.36252 168.254071 \nL 759.073413 163.095471 \nL 759.784306 158.871683 \nL 760.495199 156.401697 \nL 761.206091 155.621663 \nL 761.916984 154.731555 \nL 762.627877 152.60599 \nL 763.338769 151.384714 \nL 764.049662 152.985906 \nL 764.760555 157.592927 \nL 765.471448 164.654546 \nL 766.18234 173.181951 \nL 766.893233 179.71534 \nL 767.604126 179.584288 \nL 768.315018 174.87231 \nL 769.025911 170.026765 \nL 769.736804 166.576125 \nL 770.447697 165.062281 \nL 771.158589 164.616087 \nL 771.869482 163.202429 \nL 772.580375 161.22111 \nL 773.291267 161.25416 \nL 774.00216 164.285888 \nL 774.713053 170.1307 \nL 775.423946 178.046278 \nL 776.134838 186.361086 \nL 776.845731 190.142906 \nL 777.556624 187.289423 \nL 778.267516 182.191651 \nL 778.978409 177.926713 \nL 778.978409 43.917351 \nL 778.978409 43.917351 \nL 778.267516 48.745623 \nL 777.556624 54.375045 \nL 776.845731 57.760152 \nL 776.134838 54.514689 \nL 775.423946 46.742715 \nL 774.713053 39.375945 \nL 774.00216 34.083197 \nL 773.291267 31.605636 \nL 772.580375 32.1331 \nL 771.869482 34.685651 \nL 771.158589 36.683265 \nL 770.447697 37.73279 \nL 769.736804 39.862476 \nL 769.025911 43.891132 \nL 768.315018 49.263008 \nL 767.604126 54.488353 \nL 766.893233 55.136439 \nL 766.18234 49.125423 \nL 765.471448 41.126823 \nL 764.760555 34.598803 \nL 764.049662 30.527384 \nL 763.338769 29.465295 \nL 762.627877 31.234194 \nL 761.916984 33.918794 \nL 761.206091 35.382386 \nL 760.495199 36.756962 \nL 759.784306 39.814318 \nL 759.073413 44.571744 \nL 758.36252 50.229322 \nL 757.651628 54.027292 \nL 756.940735 51.38961 \nL 756.229842 43.768491 \nL 755.51895 36.249778 \nL 754.808057 30.73901 \nL 754.097164 28.027077 \nL 753.386271 28.389557 \nL 752.675379 31.017646 \nL 751.964486 33.319861 \nL 751.253593 34.532944 \nL 750.542701 36.616547 \nL 749.831808 40.555815 \nL 749.120915 45.880904 \nL 748.410023 51.273221 \nL 747.69913 52.508728 \nL 746.988237 46.940426 \nL 746.277344 38.903146 \nL 745.566452 32.188896 \nL 744.855559 27.880894 \nL 744.144666 26.60211 \nL 743.433774 28.284351 \nL 742.722881 31.180859 \nL 742.011988 32.922719 \nL 741.301095 34.34938 \nL 740.590203 37.322658 \nL 739.87931 42.004186 \nL 739.168417 47.67038 \nL 738.457525 51.839359 \nL 737.746632 49.824221 \nL 737.035739 42.403747 \nL 736.324846 34.748068 \nL 735.613954 29.025182 \nL 734.903061 26.074258 \nL 734.192168 26.253618 \nL 733.481276 28.91981 \nL 732.770383 31.516107 \nL 732.05949 32.913749 \nL 731.348597 34.964961 \nL 730.637705 38.813847 \nL 729.926812 44.083579 \nL 729.215919 49.608403 \nL 728.505027 51.405113 \nL 727.794134 46.323133 \nL 727.083241 38.281392 \nL 726.372348 31.389244 \nL 725.661456 26.846701 \nL 724.950563 25.341773 \nL 724.23967 26.908486 \nL 723.528778 29.984513 \nL 722.817885 32.012964 \nL 722.106992 33.511947 \nL 721.3961 36.407346 \nL 720.685207 41.008395 \nL 719.974314 46.665688 \nL 719.263421 51.162919 \nL 718.552529 49.777181 \nL 717.841636 42.607822 \nL 717.130743 34.832526 \nL 716.419851 28.904015 \nL 715.708958 25.710754 \nL 714.998065 25.690916 \nL 714.287172 28.357785 \nL 713.57628 31.232498 \nL 712.865387 32.833716 \nL 712.154494 34.866863 \nL 711.443602 38.625321 \nL 710.732709 43.831826 \nL 710.021816 49.457003 \nL 709.310923 51.783296 \nL 708.600031 47.226081 \nL 707.889138 39.217344 \nL 707.178245 32.156435 \nL 706.467353 27.38254 \nL 705.75646 25.64334 \nL 705.045567 27.067895 \nL 704.334674 30.288062 \nL 703.623782 32.607031 \nL 702.912889 34.198203 \nL 702.201996 37.02289 \nL 701.491104 41.539437 \nL 700.780211 47.172133 \nL 700.069318 51.954773 \nL 699.358425 51.197413 \nL 698.647533 44.329361 \nL 697.93664 36.45444 \nL 697.225747 30.327309 \nL 696.514855 26.889647 \nL 695.803962 26.656496 \nL 695.093069 29.2873 \nL 694.382176 32.419795 \nL 693.671284 34.241217 \nL 692.960391 36.271063 \nL 692.249498 39.94 \nL 691.538606 45.076044 \nL 690.827713 50.771863 \nL 690.11682 53.59162 \nL 689.405928 49.591609 \nL 688.695035 41.656264 \nL 687.984142 34.436742 \nL 687.273249 29.435735 \nL 686.562357 27.4554 \nL 685.851464 28.713595 \nL 685.140571 32.040239 \nL 684.429679 34.648983 \nL 683.718786 36.351568 \nL 683.007893 39.113529 \nL 682.297 43.542193 \nL 681.586108 49.136217 \nL 680.875215 54.162053 \nL 680.164322 54.024404 \nL 679.45343 47.506554 \nL 678.742537 39.554863 \nL 678.031644 33.236581 \nL 677.320751 29.553735 \nL 676.609859 29.095007 \nL 675.898966 31.654293 \nL 675.188073 35.019268 \nL 674.477181 37.074728 \nL 673.766288 39.116291 \nL 673.055395 42.697527 \nL 672.344502 47.756488 \nL 671.63361 53.495708 \nL 670.922717 56.769268 \nL 670.211824 53.352216 \nL 669.500932 45.533094 \nL 668.790039 38.166362 \nL 668.079146 32.943427 \nL 667.368253 30.716316 \nL 666.657361 31.786481 \nL 665.946468 35.180402 \nL 665.235575 38.073326 \nL 664.524683 39.905611 \nL 663.81379 42.613484 \nL 663.102897 46.951598 \nL 662.392005 52.494304 \nL 661.681112 57.722352 \nL 660.970219 58.188529 \nL 660.259326 52.06745 \nL 659.548434 44.064841 \nL 658.837541 37.563331 \nL 658.126648 33.635787 \nL 657.415756 32.940929 \nL 656.704863 35.395067 \nL 655.99397 38.962969 \nL 655.283077 41.263117 \nL 654.572185 43.331478 \nL 653.861292 46.827665 \nL 653.150399 51.803539 \nL 652.439507 57.561352 \nL 651.728614 61.246456 \nL 651.017721 58.430937 \nL 650.306828 50.772704 \nL 649.595936 43.27169 \nL 648.885043 37.832836 \nL 648.17415 35.354505 \nL 647.463258 36.21751 \nL 646.752365 39.638741 \nL 646.041472 42.805303 \nL 645.330579 44.784332 \nL 644.619687 47.447247 \nL 643.908794 51.692885 \nL 643.197901 57.1729 \nL 642.487009 62.563881 \nL 641.776116 63.611363 \nL 641.065223 57.930292 \nL 640.35433 49.905647 \nL 639.643438 43.229329 \nL 638.932545 39.058809 \nL 638.221652 38.118837 \nL 637.51076 40.436456 \nL 636.799867 44.174002 \nL 636.088974 46.72593 \nL 635.378081 48.836055 \nL 634.667189 52.250563 \nL 633.956296 57.137992 \nL 633.245403 62.891912 \nL 632.534511 66.944633 \nL 631.823618 64.741728 \nL 631.112725 57.290155 \nL 630.401833 49.669574 \nL 629.69094 44.021524 \nL 628.980047 41.288715 \nL 628.269154 41.927915 \nL 627.558262 45.336477 \nL 626.847369 48.761195 \nL 626.136476 50.902451 \nL 625.425584 53.529862 \nL 624.714691 57.681835 \nL 624.003798 63.088926 \nL 623.292905 68.605624 \nL 622.582013 70.205976 \nL 621.87112 65.003864 \nL 621.160227 56.989012 \nL 620.449335 50.14688 \nL 619.738442 45.7363 \nL 619.027549 44.543656 \nL 618.316656 46.695974 \nL 617.605764 50.566768 \nL 616.894871 53.373678 \nL 616.183978 55.540235 \nL 615.473086 58.877003 \nL 614.762193 63.6713 \nL 614.0513 69.401031 \nL 613.340407 73.776626 \nL 612.629515 72.189819 \nL 611.918622 64.99095 \nL 611.207729 57.267562 \nL 610.496837 51.417644 \nL 609.785944 48.42828 \nL 609.075051 48.829387 \nL 608.364158 52.186016 \nL 607.653266 55.848593 \nL 606.942373 58.165658 \nL 606.23148 60.767188 \nL 605.520588 64.824995 \nL 604.809695 70.149969 \nL 604.098802 75.757471 \nL 603.38791 77.877163 \nL 602.677017 73.187825 \nL 601.966124 65.21733 \nL 601.255231 58.219077 \nL 600.544339 53.572471 \nL 599.833446 52.120898 \nL 599.122553 54.081946 \nL 598.411661 58.047165 \nL 597.700768 61.108087 \nL 596.989875 63.345255 \nL 596.278982 66.608635 \nL 595.56809 71.305802 \nL 594.857197 76.993078 \nL 594.146304 81.646767 \nL 593.435412 80.672028 \nL 592.724519 73.771286 \nL 592.013626 65.964107 \nL 591.302733 59.920171 \nL 590.591841 56.673357 \nL 589.880948 56.824273 \nL 589.170055 60.091081 \nL 588.459163 63.966642 \nL 587.74827 66.470853 \nL 587.037377 69.056158 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557.890776 84.950477 \nL 557.179883 89.44412 \nL 556.468991 94.999031 \nL 555.758098 100.077692 \nL 555.047205 100.286527 \nL 554.336312 94.111173 \nL 553.62542 86.203256 \nL 552.914527 79.796706 \nL 552.203634 76.037094 \nL 551.492742 75.659136 \nL 550.781849 78.641047 \nL 550.070956 82.851573 \nL 549.360063 85.753491 \nL 548.649171 88.334998 \nL 547.938278 92.112719 \nL 547.227385 97.145746 \nL 546.516493 102.840902 \nL 545.8056 106.279885 \nL 545.094707 103.270425 \nL 544.383814 95.661955 \nL 543.672922 88.263108 \nL 542.962029 82.942551 \nL 542.251136 80.688318 \nL 541.540244 81.949184 \nL 540.829351 85.952008 \nL 540.118458 89.724843 \nL 539.407566 92.251356 \nL 538.696673 95.322792 \nL 537.98578 99.711421 \nL 537.274887 105.179689 \nL 536.563995 110.40802 \nL 535.853102 111.175324 \nL 535.142209 105.421321 \nL 534.431317 97.501452 \nL 533.720424 90.927208 \nL 533.009531 86.914625 \nL 532.298638 86.26137 \nL 531.587746 89.053568 \nL 530.876853 93.379229 \nL 530.16596 96.485719 \nL 529.455068 99.079565 \nL 528.744175 102.766286 \nL 528.033282 107.689819 \nL 527.322389 113.360567 \nL 526.611497 117.151412 \nL 525.900604 114.726189 \nL 525.189711 107.318869 \nL 524.478819 99.813087 \nL 523.767926 94.281909 \nL 523.057033 91.755009 \nL 522.34614 92.749896 \nL 521.635248 96.683075 \nL 520.924355 100.661662 \nL 520.213462 103.307339 \nL 519.50257 106.325346 \nL 518.791677 110.60816 \nL 518.080784 115.977591 \nL 517.369891 121.315439 \nL 516.658999 122.610826 \nL 515.948106 117.311456 \nL 515.237213 109.408256 \nL 514.526321 102.676131 \nL 513.815428 98.414797 \nL 513.104535 97.48166 \nL 512.393643 100.057934 \nL 511.68275 104.4622 \nL 510.971857 107.775347 \nL 510.260964 110.395332 \nL 509.550072 113.999201 \nL 508.839179 118.813321 \nL 508.128286 124.439681 \nL 507.417394 128.541034 \nL 506.706501 126.706864 \nL 505.995608 119.550242 \nL 505.284715 111.96534 \nL 504.573823 106.247216 \nL 503.86293 103.46651 \nL 503.152037 104.208175 \nL 502.441145 108.063147 \nL 501.730252 112.262954 \nL 501.019359 115.084928 \nL 500.308466 118.117689 \nL 499.597574 122.366223 \nL 498.886681 127.69716 \nL 498.175788 133.186493 \nL 497.464896 135.069981 \nL 496.754003 130.363318 \nL 496.04311 122.633335 \nL 495.332217 115.895349 \nL 494.621325 111.546757 \nL 493.910432 110.498607 \nL 493.199539 113.01249 \nL 492.488647 117.635121 \nL 491.777754 121.326769 \nL 491.066861 124.198946 \nL 490.355968 128.057156 \nL 489.645076 133.060014 \nL 488.934183 138.727004 \nL 488.22329 143.021009 \nL 487.512398 141.844399 \nL 486.801505 135.310436 \nL 486.090612 127.87106 \nL 485.379719 121.860894 \nL 484.668827 118.856896 \nL 483.957934 119.629407 \nL 483.247041 123.241141 \nL 482.536149 127.085677 \nL 481.825256 129.846816 \nL 481.114363 132.828566 \nL 480.403471 136.651905 \nL 479.692578 141.42021 \nL 478.981685 146.682907 \nL 478.270792 149.038047 \nL 477.5599 145.108521 \nL 476.849007 137.71692 \nL 476.138114 131.005177 \nL 475.427222 126.73215 \nL 474.716329 125.623736 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152.619706 \nL 446.28062 148.783383 \nL 445.569728 148.158881 \nL 444.858835 151.568584 \nL 444.147942 156.434974 \nL 443.43705 159.48114 \nL 442.726157 161.846333 \nL 442.015264 165.326789 \nL 441.304371 170.066452 \nL 440.593479 175.327489 \nL 439.882586 178.064815 \nL 439.171693 174.449861 \nL 438.460801 166.600042 \nL 437.749908 159.295031 \nL 437.039015 154.443198 \nL 436.328122 152.789346 \nL 435.61723 154.223521 \nL 434.906337 157.850171 \nL 434.195444 161.409751 \nL 433.484552 164.52593 \nL 432.773659 168.486414 \nL 432.062766 173.239604 \nL 431.351873 178.611198 \nL 430.640981 183.496963 \nL 429.930088 183.873546 \nL 429.219195 178.056632 \nL 428.508303 170.183997 \nL 427.79741 163.685095 \nL 427.086517 159.980895 \nL 426.375624 159.819436 \nL 425.664732 163.320449 \nL 424.953839 168.317731 \nL 424.242946 171.749364 \nL 423.532054 174.519074 \nL 422.821161 178.277281 \nL 422.110268 183.216284 \nL 421.399376 188.91886 \nL 420.688483 192.581919 \nL 419.97759 190.188441 \nL 419.266697 183.202079 \nL 418.555805 176.094898 \nL 417.844912 170.74598 \nL 417.134019 168.26967 \nL 416.423127 169.388284 \nL 415.712234 173.632775 \nL 415.001341 177.886822 \nL 414.290448 180.789029 \nL 413.579556 184.320558 \nL 412.868663 189.111832 \nL 412.15777 194.575012 \nL 411.446878 199.657083 \nL 410.735985 200.791369 \nL 410.025092 195.719283 \nL 409.314199 187.856101 \nL 408.603307 180.56319 \nL 407.892414 175.822326 \nL 407.181521 175.030278 \nL 406.470629 177.971122 \nL 405.759736 182.538289 \nL 405.048843 185.902034 \nL 404.33795 188.635616 \nL 403.627058 192.225453 \nL 402.916165 196.442258 \nL 402.205272 200.949902 \nL 401.49438 204.043873 \nL 400.783487 201.77444 \nL 400.072594 194.429993 \nL 399.361701 186.293286 \nL 398.650809 179.914508 \nL 397.939916 176.938631 \nL 397.229023 177.822187 \nL 396.518131 181.894414 \nL 395.807238 186.399234 \nL 395.096345 189.50027 \nL 394.385452 192.461893 \nL 393.67456 196.22798 \nL 392.963667 201.088372 \nL 392.252774 206.210364 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278.509941 270.538422 \nL 279.220833 266.868752 \nL 279.931726 263.820605 \nL 280.642619 259.851966 \nL 281.353511 255.239155 \nL 282.064404 252.778707 \nL 282.775297 253.565426 \nL 283.48619 257.535074 \nL 285.618868 275.776249 \nL 286.32976 274.880422 \nL 288.462439 262.186381 \nL 291.306009 247.510486 \nL 292.016902 246.970474 \nL 292.727795 249.91716 \nL 293.438688 255.754675 \nL 294.860473 270.026843 \nL 295.571366 272.066699 \nL 296.282258 268.386801 \nL 297.704044 258.742318 \nL 298.414937 255.040348 \nL 299.836722 248.643945 \nL 300.547615 244.522869 \nL 301.258507 242.16779 \nL 301.9694 243.027352 \nL 302.680293 247.087975 \nL 303.391186 253.694682 \nL 304.102078 261.468186 \nL 304.812971 267.071469 \nL 305.523864 266.700921 \nL 307.656542 253.541363 \nL 309.078327 247.091472 \nL 310.500113 237.461093 \nL 311.211005 235.297077 \nL 311.921898 236.890362 \nL 312.632791 241.628482 \nL 314.054576 255.930849 \nL 314.765469 259.320028 \nL 315.476362 256.459803 \nL 316.898147 246.182145 \nL 317.60904 242.721252 \nL 318.319932 240.233209 \nL 319.030825 236.663334 \nL 319.741718 231.289473 \nL 320.452611 227.922177 \nL 321.163503 228.707233 \nL 321.874396 232.713418 \nL 322.585289 238.97835 \nL 323.296181 246.705979 \nL 324.007074 252.806003 \nL 324.717967 252.711312 \nL 326.850645 239.093329 \nL 328.27243 232.235167 \nL 329.694216 223.438907 \nL 330.405109 222.130541 \nL 331.116001 224.399064 \nL 331.826894 229.851416 \nL 333.248679 244.273914 \nL 333.959572 247.58048 \nL 334.670465 245.009625 \nL 336.09225 235.542971 \nL 336.803143 232.412171 \nL 337.514036 230.124341 \nL 338.224928 226.921837 \nL 338.935821 221.700114 \nL 339.646714 217.672351 \nL 340.357606 217.60234 \nL 341.068499 221.276997 \nL 343.201177 240.170651 \nL 343.91207 241.003926 \nL 344.622963 237.058844 \nL 346.044748 227.68568 \nL 346.755641 224.552988 \nL 347.466534 222.056814 \nL 348.177426 218.08278 \nL 348.888319 213.045767 \nL 349.599212 210.468329 \nL 350.310104 211.819881 \nL 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172.729294 \nL 424.953839 169.298218 \nL 425.664732 164.301764 \nL 426.375624 160.801428 \nL 427.086517 160.963123 \nL 427.79741 164.666965 \nL 428.508303 171.165086 \nL 429.219195 179.036952 \nL 429.930088 184.853416 \nL 430.640981 184.476971 \nL 433.484552 165.508897 \nL 434.906337 158.83184 \nL 435.61723 155.204467 \nL 436.328122 153.769955 \nL 437.039015 155.424078 \nL 437.749908 160.276637 \nL 439.171693 175.432789 \nL 439.882586 179.047707 \nL 440.593479 176.309792 \nL 442.015264 166.307882 \nL 442.726157 162.82775 \nL 443.43705 160.463049 \nL 444.147942 157.417669 \nL 444.858835 152.55205 \nL 445.569728 149.142717 \nL 446.28062 149.767032 \nL 446.991513 153.602675 \nL 447.702406 159.547281 \nL 449.124191 173.717946 \nL 449.835084 173.616627 \nL 451.967762 156.279378 \nL 452.678655 152.463684 \nL 453.389548 149.28345 \nL 454.811333 140.279513 \nL 455.522226 138.007683 \nL 456.233118 138.981419 \nL 456.944011 142.947465 \nL 458.365796 156.560289 \nL 459.076689 160.165767 \nL 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114.083373 \nL 495.332217 118.632095 \nL 497.464896 138.380238 \nL 498.175788 136.672495 \nL 499.597574 126.178653 \nL 500.308466 122.113179 \nL 501.730252 116.594434 \nL 503.152037 108.815778 \nL 503.86293 108.197356 \nL 504.573823 111.093308 \nL 505.284715 116.919672 \nL 506.706501 131.856699 \nL 507.417394 133.779173 \nL 508.128286 129.760648 \nL 509.550072 119.484226 \nL 510.260964 115.980157 \nL 510.971857 113.45238 \nL 511.68275 110.222569 \nL 512.393643 105.897562 \nL 513.104535 103.39666 \nL 513.815428 104.401953 \nL 514.526321 108.732875 \nL 515.237213 115.532229 \nL 515.948106 123.499897 \nL 516.658999 128.860973 \nL 517.369891 127.625544 \nL 518.791677 117.034532 \nL 519.50257 112.826025 \nL 520.924355 107.313954 \nL 522.34614 99.536113 \nL 523.057033 98.605133 \nL 523.767926 101.194488 \nL 524.478819 106.787291 \nL 525.900604 121.819402 \nL 526.611497 124.301733 \nL 527.322389 120.566782 \nL 528.744175 110.090134 \nL 529.455068 106.481849 \nL 530.16596 103.964185 \nL 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\n"
},
"metadata": {
"needs_background": "light"
}
}
],
"source": [
"likelihood = gpytorch.likelihoods.GaussianLikelihood()\n",
"likelihood.initialize(noise=0.1**2) \n",
"\n",
"likelihood.cuda()\n",
"model = ExactGPModel(X_torch, Y_torch, likelihood, full_kernel_fn())\n",
"model.cuda()\n",
"\n",
"model.eval()\n",
"likelihood.eval()\n",
"\n",
"with torch.no_grad(), gpytorch.settings.fast_pred_var():\n",
" observed_pred = likelihood(model(X_test_torch))\n",
" # bigger plot of the last model\n",
" f, ax = plt.subplots(1, 1, figsize=(14, 7))\n",
" # Get upper and lower confidence bounds\n",
" lower, upper = observed_pred.confidence_region()\n",
" # Plot training data as black stars\n",
" ax.plot(X_torch.cpu().numpy(), Y_torch.cpu().numpy(), 'k.', markersize=3)\n",
" # Plot predictive means as blue line\n",
" ax.plot(X_test_torch.cpu().numpy(), observed_pred.mean.cpu().numpy(), \"-\", color=\"steelblue\")\n",
" # Shade between the lower and upper confidence bounds\n",
" ax.fill_between(X_test_torch.cpu().numpy(), lower.cpu().numpy(), upper.cpu().numpy(), alpha=0.3)"
]
},
{
"source": [
"Using the kernel specification translated from sklearn certainly gives a pretty reasonable fit, which hopefully indicates that the translation isn't completely unreasonable. Nonetheless, the prediction at the end of the series are pretty different than those given by sklearn, so there is a mismatch somewhere.\n",
"\n",
"Let's run optimization the model to make sure that works:"
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": "<Figure size 1008x504 with 1 Axes>",
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136.772563 \nL 495.332217 141.914596 \nL 496.04311 149.154624 \nL 496.754003 157.655938 \nL 497.464896 162.516702 \nL 498.175788 160.571296 \nL 498.886681 155.499303 \nL 499.597574 150.413396 \nL 500.308466 146.636518 \nL 501.019359 143.93367 \nL 501.730252 141.271431 \nL 502.441145 137.190739 \nL 503.152037 133.571672 \nL 503.86293 133.131848 \nL 504.573823 136.265809 \nL 505.284715 142.270912 \nL 505.995608 150.091301 \nL 506.706501 157.670373 \nL 507.417394 159.033741 \nL 508.128286 154.962423 \nL 508.839179 149.505604 \nL 509.550072 144.856644 \nL 510.260964 141.620701 \nL 510.971857 139.034471 \nL 511.68275 135.809331 \nL 512.393643 131.389364 \nL 513.104535 129.055128 \nL 513.815428 130.274276 \nL 514.526321 134.882732 \nL 515.237213 141.755714 \nL 515.948106 150.17351 \nL 516.658999 155.374254 \nL 517.369891 153.657911 \nL 518.080784 148.507271 \nL 518.791677 143.223252 \nL 519.50257 139.255041 \nL 520.213462 136.455218 \nL 520.924355 133.852763 \nL 521.635248 129.839201 \nL 522.34614 126.011306 \nL 523.057033 125.284505 \nL 523.767926 128.158557 \nL 524.478819 133.979121 \nL 525.189711 141.75385 \nL 525.900604 149.666823 \nL 526.611497 151.543518 \nL 527.322389 147.673377 \nL 528.033282 142.166096 \nL 528.744175 137.409039 \nL 529.455068 134.109177 \nL 530.16596 131.57556 \nL 530.876853 128.534354 \nL 531.587746 124.112339 \nL 532.298638 121.561143 \nL 533.009531 122.547499 \nL 533.720424 126.959153 \nL 534.431317 133.734683 \nL 535.142209 142.277352 \nL 535.853102 148.004363 \nL 536.563995 146.706526 \nL 537.274887 141.637533 \nL 537.98578 136.27981 \nL 538.696673 132.238011 \nL 539.407566 129.443127 \nL 540.118458 126.986219 \nL 540.829351 123.138901 \nL 541.540244 119.190734 \nL 542.251136 118.242212 \nL 542.962029 120.909121 \nL 543.672922 126.584237 \nL 544.383814 134.337321 \nL 545.094707 142.596329 \nL 545.8056 145.031809 \nL 546.516493 141.421734 \nL 547.227385 135.907276 \nL 547.938278 131.071978 \nL 548.649171 127.736187 \nL 549.360063 125.27641 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122.669975 \nL 577.795772 119.904627 \nL 578.506665 117.753114 \nL 579.217557 114.319287 \nL 579.92845 110.219027 \nL 580.639343 108.867836 \nL 581.350235 111.141896 \nL 582.061128 116.523927 \nL 582.772021 124.199996 \nL 583.482914 133.084924 \nL 584.193806 136.676876 \nL 584.904699 133.685451 \nL 585.615592 128.22206 \nL 586.326484 123.256055 \nL 587.037377 119.862308 \nL 587.74827 117.553063 \nL 588.459163 115.17746 \nL 589.170055 110.988482 \nL 589.880948 107.932541 \nL 590.591841 108.302599 \nL 591.302733 112.169057 \nL 592.013626 118.643561 \nL 592.724519 127.458879 \nL 593.435412 134.73705 \nL 594.146304 134.883094 \nL 594.857197 130.24736 \nL 595.56809 124.765494 \nL 596.278982 120.551264 \nL 596.989875 117.801548 \nL 597.700768 115.800239 \nL 598.411661 112.602428 \nL 599.122553 108.465065 \nL 599.833446 106.92775 \nL 600.544339 109.010889 \nL 601.255231 114.240957 \nL 601.966124 121.857875 \nL 602.677017 131.015267 \nL 603.38791 135.194215 \nL 604.098802 132.55574 \nL 604.809695 127.148124 \nL 605.520588 122.126657 \nL 606.23148 118.706452 \nL 606.942373 116.469555 \nL 607.653266 114.325589 \nL 608.364158 110.272457 \nL 609.075051 107.081997 \nL 609.785944 107.259005 \nL 610.496837 110.945562 \nL 611.207729 117.304858 \nL 611.918622 126.165056 \nL 612.629515 133.92935 \nL 613.340407 134.601466 \nL 614.0513 130.163496 \nL 614.762193 124.665712 \nL 615.473086 120.400205 \nL 616.183978 117.665608 \nL 616.894871 115.810892 \nL 617.605764 112.864982 \nL 618.316656 108.716453 \nL 619.027549 107.003143 \nL 619.738442 108.898732 \nL 620.449335 113.973324 \nL 621.160227 121.517644 \nL 621.87112 130.918512 \nL 622.582013 135.68544 \nL 623.292905 133.427103 \nL 624.003798 128.095641 \nL 624.714691 123.025374 \nL 625.425584 119.57964 \nL 626.136476 117.412291 \nL 626.847369 115.500718 \nL 627.558262 111.610063 \nL 628.269154 108.302437 \nL 628.980047 108.292394 \nL 629.69094 111.799946 \nL 630.401833 118.036744 \nL 631.112725 126.918804 \nL 631.823618 135.148388 \nL 632.534511 136.364285 \nL 633.245403 132.150022 \nL 633.956296 126.64959 \nL 634.667189 122.335387 \nL 635.378081 119.615099 \nL 636.088974 117.902489 \nL 636.799867 115.221979 \nL 637.51076 111.088439 \nL 638.221652 109.20966 \nL 638.932545 110.921216 \nL 639.643438 115.83726 \nL 640.35433 123.296157 \nL 641.065223 132.910626 \nL 641.776116 138.263144 \nL 642.487009 136.410755 \nL 643.197901 131.176131 \nL 643.908794 126.064076 \nL 644.619687 122.593439 \nL 645.330579 120.492487 \nL 646.041472 118.812212 \nL 646.752365 115.109335 \nL 647.463258 111.702571 \nL 648.17415 111.51175 \nL 648.885043 114.841509 \nL 649.595936 120.948972 \nL 650.306828 129.830398 \nL 651.017721 138.501806 \nL 651.728614 140.276474 \nL 652.439507 136.311492 \nL 653.150399 130.822226 \nL 653.861292 126.461914 \nL 654.572185 123.754858 \nL 655.283077 122.179109 \nL 655.99397 119.775077 \nL 656.704863 115.682766 \nL 657.415756 113.649465 \nL 658.126648 115.180663 \nL 658.837541 119.935549 \nL 659.548434 127.296858 \nL 660.259326 137.094424 \nL 660.970219 143.026786 \nL 661.681112 141.604612 \nL 662.392005 136.487734 \nL 663.102897 131.341286 \nL 663.81379 127.846083 \nL 664.524683 125.808058 \nL 665.235575 124.356233 \nL 665.946468 120.864893 \nL 666.657361 117.377636 \nL 667.368253 117.012561 \nL 668.079146 120.166008 \nL 668.790039 126.137753 \nL 669.500932 134.996682 \nL 670.211824 144.084001 \nL 670.922717 146.429586 \nL 671.63361 142.738933 \nL 672.344502 137.275143 \nL 673.055395 132.871339 \nL 673.766288 130.176131 \nL 674.477181 128.7313 \nL 675.188073 126.612341 \nL 675.898966 122.587385 \nL 676.609859 120.410904 \nL 677.320751 121.765544 \nL 678.031644 126.35709 \nL 678.742537 133.6093 \nL 679.45343 143.559025 \nL 680.164322 150.062144 \nL 680.875215 149.092711 \nL 681.586108 144.114579 \nL 682.297 138.94152 \nL 683.007893 135.421789 \nL 683.718786 133.442886 \nL 684.429679 132.21499 \nL 685.140571 128.95717 \nL 685.851464 125.408594 \nL 686.562357 124.875993 \nL 687.273249 127.854817 \nL 687.984142 133.684887 \nL 688.695035 142.500152 \nL 689.405928 151.975217 \nL 690.11682 154.900885 \nL 690.827713 151.508902 \nL 691.538606 146.085317 \nL 692.249498 141.640676 \nL 692.960391 138.955586 \nL 693.671284 137.635076 \nL 694.382176 135.807252 \nL 695.093069 131.875443 \nL 695.803962 129.567482 \nL 696.514855 130.749437 \nL 697.225747 135.175836 \nL 697.93664 142.308061 \nL 698.647533 152.378767 \nL 699.358425 159.440235 \nL 700.069318 158.944137 \nL 700.780211 154.125707 \nL 701.491104 148.934186 \nL 702.201996 145.389652 \nL 702.912889 143.46572 \nL 703.623782 142.455637 \nL 704.334674 139.451329 \nL 705.045567 135.861028 \nL 705.75646 135.167787 \nL 706.467353 137.973813 \nL 707.178245 143.656647 \nL 707.889138 152.407832 \nL 708.600031 162.240418 \nL 709.310923 165.752241 \nL 710.021816 162.68238 \nL 710.732709 157.314059 \nL 711.443602 152.831287 \nL 712.154494 150.154197 \nL 712.865387 148.950797 \nL 713.57628 147.417619 \nL 714.287172 143.604193 \nL 714.998065 141.176762 \nL 715.708958 142.189935 \nL 716.419851 146.449705 \nL 717.130743 153.451657 \nL 717.841636 163.612102 \nL 718.552529 171.216247 \nL 719.263421 171.211955 \nL 719.974314 166.573995 \nL 720.685207 161.372507 \nL 721.3961 157.802586 \nL 722.106992 155.929108 \nL 722.817885 155.129224 \nL 723.528778 152.396231 \nL 724.23967 148.78411 \nL 724.950563 147.937234 \nL 725.661456 150.57236 \nL 726.372348 156.102758 \nL 727.083241 164.770244 \nL 727.794134 174.928279 \nL 728.505027 179.029145 \nL 729.215919 176.30379 \nL 729.926812 171.006025 \nL 730.637705 166.4879 \nL 731.348597 163.816278 \nL 732.05949 162.722208 \nL 732.770383 161.484641 \nL 733.481276 157.814056 \nL 734.192168 155.279442 \nL 734.903061 156.127726 \nL 735.613954 160.219657 \nL 736.324846 167.081616 \nL 737.035739 177.300673 \nL 737.746632 185.428639 \nL 738.457525 185.932337 \nL 739.168417 181.495287 \nL 739.87931 176.292647 \nL 740.590203 172.69646 \nL 741.301095 170.868541 \nL 742.011988 170.26985 \nL 742.722881 167.823618 \nL 743.433774 164.209778 \nL 744.144666 163.216354 \nL 744.855559 165.682496 \nL 745.566452 171.055598 \nL 746.277344 179.620595 \nL 746.988237 190.070391 \nL 747.69913 194.759936 \nL 748.410023 192.400234 \nL 749.120915 187.18846 \nL 749.831808 182.637849 \nL 750.542701 179.968736 \nL 751.253593 178.975693 \nL 751.964486 178.032201 \nL 752.675379 174.527918 \nL 753.386271 171.898652 \nL 754.097164 172.5859 \nL 754.808057 176.509007 \nL 755.51895 183.221797 \nL 756.229842 193.468626 \nL 756.940735 202.098486 \nL 757.651628 203.123923 \nL 758.36252 198.907759 \nL 759.073413 193.713075 \nL 759.784306 190.089475 \nL 760.495199 188.301838 \nL 761.206091 187.894057 \nL 761.916984 185.747537 \nL 762.627877 182.152159 \nL 763.338769 181.019332 \nL 764.049662 183.318383 \nL 764.760555 188.529643 \nL 765.471448 196.974226 \nL 766.18234 207.680718 \nL 766.893233 212.955288 \nL 767.604126 210.980988 \nL 768.315018 205.87069 \nL 769.025911 201.290581 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49.545981 \nL 761.206091 52.294309 \nL 760.495199 53.314694 \nL 759.784306 55.755014 \nL 759.073413 59.991811 \nL 758.36252 65.684812 \nL 757.651628 70.393911 \nL 756.940735 69.881451 \nL 756.229842 61.780513 \nL 755.51895 52.075929 \nL 754.808057 45.910354 \nL 754.097164 42.542939 \nL 753.386271 42.41837 \nL 752.675379 45.611313 \nL 751.964486 49.688995 \nL 751.253593 51.222904 \nL 750.542701 52.822345 \nL 749.831808 56.131296 \nL 749.120915 61.212042 \nL 748.410023 66.895358 \nL 747.69913 69.744089 \nL 746.988237 65.560458 \nL 746.277344 55.63165 \nL 745.566452 47.594386 \nL 744.855559 42.754022 \nL 744.144666 40.828878 \nL 743.433774 42.36817 \nL 742.722881 46.530742 \nL 742.011988 49.544976 \nL 741.301095 50.72129 \nL 740.590203 53.164017 \nL 739.87931 57.343691 \nL 739.168417 63.014399 \nL 738.457525 67.911778 \nL 737.746632 67.887914 \nL 737.035739 60.255122 \nL 736.324846 50.544795 \nL 735.613954 44.196479 \nL 734.903061 40.626313 \nL 734.192168 40.306695 \nL 733.481276 43.371158 \nL 732.770383 47.580435 \nL 732.05949 49.373518 \nL 731.348597 51.036078 \nL 730.637705 54.312592 \nL 729.926812 59.331992 \nL 729.215919 65.069461 \nL 728.505027 68.250646 \nL 727.794134 64.621676 \nL 727.083241 54.949915 \nL 726.372348 46.775682 \nL 725.661456 41.743256 \nL 724.950563 39.614489 \nL 724.23967 40.973029 \nL 723.528778 45.099662 \nL 722.817885 48.36562 \nL 722.106992 49.707056 \nL 721.3961 52.155965 \nL 720.685207 56.277989 \nL 719.974314 61.916308 \nL 719.263421 66.981093 \nL 718.552529 67.431165 \nL 717.841636 60.287501 \nL 717.130743 50.601215 \nL 716.419851 44.078266 \nL 715.708958 40.305188 \nL 714.998065 39.785473 \nL 714.287172 42.707765 \nL 713.57628 47.024101 \nL 712.865387 49.076848 \nL 712.154494 50.809982 \nL 711.443602 54.055419 \nL 710.732709 59.009535 \nL 710.021816 64.784937 \nL 709.310923 68.276562 \nL 708.600031 65.201709 \nL 707.889138 55.819689 \nL 707.178245 47.526307 \nL 706.467353 42.305762 \nL 705.75646 39.970537 \nL 705.045567 41.140287 \nL 704.334674 45.209978 \nL 703.623782 48.711214 \nL 702.912889 50.225914 \nL 702.201996 52.684699 \nL 701.491104 56.748496 \nL 700.780211 62.344859 \nL 700.069318 67.55599 \nL 699.358425 68.463168 \nL 698.647533 61.826811 \nL 697.93664 52.194881 \nL 697.225747 45.506189 \nL 696.514855 41.530495 \nL 695.803962 40.805838 \nL 695.093069 43.572752 \nL 694.382176 47.970872 \nL 693.671284 50.281519 \nL 692.960391 52.092442 \nL 692.249498 55.308003 \nL 691.538606 60.193179 \nL 690.827713 65.990663 \nL 690.11682 69.769715 \nL 689.405928 67.245431 \nL 688.695035 58.184491 \nL 687.984142 49.790871 \nL 687.273249 44.386753 \nL 686.562357 41.84251 \nL 685.851464 42.815749 \nL 685.140571 46.807913 \nL 684.429679 50.525841 \nL 683.718786 52.220761 \nL 683.007893 54.693032 \nL 682.297 58.69794 \nL 681.586108 64.243331 \nL 680.875215 69.579685 \nL 680.164322 70.925108 \nL 679.45343 64.811306 \nL 678.742537 55.264393 \nL 678.031644 48.419634 \nL 677.320751 44.242119 \nL 676.609859 43.307894 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647.463258 50.420182 \nL 646.752365 54.19763 \nL 646.041472 58.285364 \nL 645.330579 60.356203 \nL 644.619687 62.865889 \nL 643.908794 66.750551 \nL 643.197901 72.169192 \nL 642.487009 77.69301 \nL 641.776116 79.850984 \nL 641.065223 74.815811 \nL 640.35433 65.531285 \nL 639.643438 58.406602 \nL 638.932545 53.829957 \nL 638.221652 52.463712 \nL 637.51076 54.690399 \nL 636.799867 59.177902 \nL 636.088974 62.228349 \nL 635.378081 64.312457 \nL 634.667189 67.443954 \nL 633.956296 72.102543 \nL 633.245403 77.875985 \nL 632.534511 82.371648 \nL 631.823618 81.448659 \nL 631.112725 73.521932 \nL 630.401833 64.951155 \nL 629.69094 59.029782 \nL 628.980047 55.846403 \nL 628.269154 56.187174 \nL 627.558262 59.828666 \nL 626.847369 64.066029 \nL 626.136476 66.329558 \nL 625.425584 68.862945 \nL 624.714691 72.685945 \nL 624.003798 78.029923 \nL 623.292905 83.616482 \nL 622.582013 86.145492 \nL 621.87112 81.660106 \nL 621.160227 72.552608 \nL 620.449335 65.305652 \nL 619.738442 60.532835 \nL 619.027549 58.944687 \nL 618.316656 60.968404 \nL 617.605764 65.433247 \nL 616.894871 68.711135 \nL 616.183978 70.898 \nL 615.473086 74.002775 \nL 614.762193 78.579718 \nL 614.0513 84.316984 \nL 613.340407 89.001249 \nL 612.629515 88.585979 \nL 611.918622 81.087545 \nL 611.207729 72.501905 \nL 610.496837 66.421359 \nL 609.785944 63.022173 \nL 609.075051 63.13899 \nL 608.364158 66.626379 \nL 607.653266 70.987848 \nL 606.942373 73.445018 \nL 606.23148 76.005258 \nL 605.520588 79.765326 \nL 604.809695 85.027843 \nL 604.098802 90.657011 \nL 603.38791 93.53168 \nL 602.677017 89.598805 \nL 601.966124 80.6983 \nL 601.255231 73.341911 \nL 600.544339 68.375985 \nL 599.833446 66.56242 \nL 599.122553 68.372663 \nL 598.411661 72.788852 \nL 597.700768 76.280708 \nL 596.989875 78.575156 \nL 596.278982 81.65358 \nL 595.56809 86.14592 \nL 594.857197 91.834044 \nL 594.146304 96.681345 \nL 593.435412 96.756461 \nL 592.724519 89.707566 \nL 592.013626 81.130443 \nL 591.302733 74.898402 \nL 590.591841 71.282756 \nL 589.880948 71.169674 \nL 589.170055 74.485567 \nL 588.459163 78.944383 \nL 587.74827 81.594373 \nL 587.037377 84.184464 \nL 586.326484 87.880133 \nL 585.615592 93.054919 \nL 584.904699 98.707117 \nL 584.193806 101.900897 \nL 583.482914 98.520065 \nL 582.772021 89.855805 \nL 582.061128 82.403615 \nL 581.350235 77.248288 \nL 580.639343 75.206155 \nL 579.92845 76.793027 \nL 579.217557 81.134985 \nL 578.506665 84.825087 \nL 577.795772 87.231204 \nL 577.084879 90.2835 \nL 576.373986 94.688277 \nL 575.663094 100.315056 \nL 574.952201 105.299846 \nL 574.241308 105.845688 \nL 573.530416 99.265036 \nL 572.819523 90.720451 \nL 572.10863 84.34525 \nL 571.397738 80.513009 \nL 570.686845 80.164508 \nL 569.975952 83.292337 \nL 569.265059 87.820761 \nL 568.554167 90.660933 \nL 567.843274 93.283749 \nL 567.132381 96.913387 \nL 566.421489 101.994707 \nL 565.710596 107.651044 \nL 564.999703 111.136446 \nL 564.28881 108.304062 \nL 563.577918 99.904418 \nL 562.867025 92.370882 \nL 562.156132 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141.627932 \nL 505.995608 134.185725 \nL 505.284715 126.509529 \nL 504.573823 120.656405 \nL 503.86293 117.688049 \nL 503.152037 118.308297 \nL 502.441145 122.127177 \nL 501.730252 126.431818 \nL 501.019359 129.330402 \nL 500.308466 132.310335 \nL 499.597574 136.368714 \nL 498.886681 141.664464 \nL 498.175788 146.977418 \nL 497.464896 149.207901 \nL 496.754003 144.684433 \nL 496.04311 136.591977 \nL 495.332217 129.83976 \nL 494.621325 125.288234 \nL 493.910432 124.139515 \nL 493.199539 126.621888 \nL 492.488647 131.491699 \nL 491.777754 135.513346 \nL 491.066861 138.900602 \nL 490.355968 142.927076 \nL 489.645076 147.885672 \nL 488.934183 153.400091 \nL 488.22329 157.701995 \nL 487.512398 157.018312 \nL 486.801505 150.171767 \nL 486.090612 142.776615 \nL 485.379719 137.034041 \nL 484.668827 134.095889 \nL 483.957934 134.638052 \nL 483.247041 138.182971 \nL 482.536149 142.264026 \nL 481.825256 144.976674 \nL 481.114363 147.682804 \nL 480.403471 151.322052 \nL 479.692578 156.139345 \nL 478.981685 161.167556 \nL 478.270792 163.690151 \nL 477.5599 159.925042 \nL 476.849007 152.427539 \nL 476.138114 146.114194 \nL 475.427222 141.85006 \nL 474.716329 140.688405 \nL 474.005436 142.717705 \nL 473.294543 146.877328 \nL 472.583651 150.080983 \nL 471.872758 152.36653 \nL 471.161865 155.17541 \nL 470.450973 159.485772 \nL 469.74008 164.898545 \nL 469.029187 169.445058 \nL 468.318294 169.07995 \nL 467.607402 162.146779 \nL 466.896509 154.333035 \nL 466.185616 148.22186 \nL 465.474724 144.73744 \nL 464.763831 144.468964 \nL 464.052938 147.335901 \nL 463.342045 151.312209 \nL 462.631153 154.165158 \nL 461.92026 156.992426 \nL 461.209367 160.810021 \nL 460.498475 165.814099 \nL 459.787582 170.971612 \nL 459.076689 173.722407 \nL 458.365796 170.313546 \nL 457.654904 162.996487 \nL 456.944011 156.873302 \nL 456.233118 152.841602 \nL 455.522226 151.905011 \nL 454.811333 154.194137 \nL 454.10044 158.867937 \nL 453.389548 162.951029 \nL 452.678655 166.171774 \nL 451.967762 169.926759 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186.250077 \nL 423.532054 189.08497 \nL 422.821161 192.68165 \nL 422.110268 197.629681 \nL 421.399376 203.121144 \nL 420.688483 206.834488 \nL 419.97759 204.670619 \nL 419.266697 197.599644 \nL 418.555805 190.679536 \nL 417.844912 185.258015 \nL 417.134019 182.841585 \nL 416.423127 183.917715 \nL 415.712234 187.958617 \nL 415.001341 192.059182 \nL 414.290448 195.216626 \nL 413.579556 198.637974 \nL 412.868663 203.315278 \nL 412.15777 208.859186 \nL 411.446878 213.952042 \nL 410.735985 215.285096 \nL 410.025092 209.949876 \nL 409.314199 202.120347 \nL 408.603307 194.987433 \nL 407.892414 190.33335 \nL 407.181521 189.431129 \nL 406.470629 192.208231 \nL 405.759736 196.816345 \nL 405.048843 200.324306 \nL 404.33795 203.157902 \nL 403.627058 206.486262 \nL 402.916165 210.72891 \nL 402.205272 215.272411 \nL 401.49438 218.356651 \nL 400.783487 215.99418 \nL 400.072594 208.428225 \nL 399.361701 200.602729 \nL 398.650809 194.265745 \nL 397.939916 191.264179 \nL 397.229023 192.102841 \nL 396.518131 196.207379 \nL 395.807238 200.635936 \nL 395.096345 203.837595 \nL 394.385452 206.756448 \nL 393.67456 210.652611 \nL 392.963667 215.583383 \nL 392.252774 220.501604 \nL 391.541882 222.078767 \nL 390.830989 216.910929 \nL 390.120096 208.712813 \nL 389.409204 200.829877 \nL 388.698311 195.174616 \nL 387.987418 193.421944 \nL 387.276525 196.011333 \nL 386.565633 201.373266 \nL 385.85474 205.959685 \nL 385.143847 209.328175 \nL 384.432955 212.666105 \nL 383.722062 217.010935 \nL 383.011169 222.123487 \nL 382.300276 226.166804 \nL 381.589384 224.90271 \nL 380.878491 218.220761 \nL 380.167598 211.172132 \nL 379.456706 205.418133 \nL 378.745813 202.498095 \nL 378.03492 202.824683 \nL 377.324027 206.09523 \nL 376.613135 209.905271 \nL 375.902242 212.861852 \nL 375.191349 215.922058 \nL 374.480457 220.064277 \nL 373.769564 224.971331 \nL 373.058671 229.693481 \nL 372.347778 231.387297 \nL 371.636886 226.713228 \nL 370.925993 219.220836 \nL 370.2151 212.48304 \nL 369.504208 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},
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"needs_background": "light"
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],
"source": [
"# note that we're not normalizing the the data, as recommended here:\n",
"# https://stackoverflow.com/questions/56657552/poor-fits-for-simple-2d-gaussian-processes-in-gpytorch\n",
"# normalizing the data seemed to help in earlier experiments, but skipping that\n",
"# while trying to reproduce the sklearn example, which uses the raw data\n",
"\n",
"# per https://github.com/cornellius-gp/gpytorch/issues/559 --\n",
"# to reproduce the `WhiteKernel(noise_level=0.1**2)` component from sklearn?\n",
"# now that `gpytorch.kernels.WhiteNoiseKernel` is gone, should you set \n",
"# `likelihood.initialize(noise=0.1**2)?\n",
"\n",
"# Note that previous version of this notebook that used torch `float` tensors would\n",
"# crash with \"Matrix not positive definite\" exception when initializing the likelihood\n",
"# noise at 0.1**2. Using double, we can go much lower than that, but we don't need to\n",
"# because the seasonal component at this initial noise level (and indeed, at much higher ones).\n",
"\n",
"model, likelihood = createAndRunModelWithKernel(\n",
" full_kernel_fn,\n",
" X_torch,\n",
" Y_torch,\n",
" test_x=X_test_torch,\n",
" likelihood_noise=0.1**2,\n",
")\n"
]
},
{
"source": [
"In both of the cases above, the fit is about the same whether initializing the likelihood noise at `0.2**2` or `1.65**2`.\n",
"\n",
"# Simplified model to reproduce sklearn\n",
"\n",
"We've seen that we're able to fit the fully specified model and get sensible results, but if we want to duplicate an sklearn result, we need to notice to a couple things:\n",
"1. In the sklearn example, they've set `normalize_y = True`\n",
"2. As soon as you `.fit()` an sklearn GPR, it automatically optimizes the parameters unless you set `{parameter}_bounds = \"fixed\"` for each parameter.\n",
"\n",
"So, to compare a Gpytorch model with an sklearn model, let's correct for those factors. Also, just to simplify things a bit, we'll only attend to the long term and seasonal components.\n",
"\n",
"First with sklearn..."
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\nLearned kernel: 50**2 * RBF(length_scale=50) + 2**2 * RBF(length_scale=100) * ExpSineSquared(length_scale=1, periodicity=1) + WhiteKernel(noise_level=0.01)\nLog-marginal-likelihood: -6639.702\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
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},
"metadata": {},
"execution_count": 9
},
{
"output_type": "display_data",
"data": {
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\n"
},
"metadata": {
"needs_background": "light"
}
}
],
"source": [
"k1 = ConstantKernel(constant_value=50.0**2, constant_value_bounds = \"fixed\") \\\n",
" * RBF(length_scale=50.0,length_scale_bounds=\"fixed\")\n",
"\n",
"k2 = ConstantKernel(constant_value=2.0**2, constant_value_bounds = \"fixed\")\\\n",
" * RBF(length_scale=100.0, length_scale_bounds=\"fixed\") \\\n",
" * ExpSineSquared(length_scale=1.0, periodicity=1.0,\n",
" length_scale_bounds=\"fixed\",\n",
" periodicity_bounds=\"fixed\") # seasonal component\n",
"\n",
"knoise = WhiteKernel(noise_level=0.1**2, noise_level_bounds=\"fixed\") # noise terms\n",
"\n",
"kernel = k1 + k2 + knoise\n",
"\n",
"gp = GaussianProcessRegressor(kernel=kernel, alpha=0, normalize_y=False)\n",
"gp.fit(X_raw, Y_raw)\n",
"\n",
"print(\"\\nLearned kernel: %s\" % gp.kernel_)\n",
"print(\"Log-marginal-likelihood: %.3f\"\n",
" % gp.log_marginal_likelihood(gp.kernel_.theta))\n",
"\n",
"X_test = np.linspace(X_raw.min(), X_raw.max() + 30, 1000)[:, np.newaxis]\n",
"y_pred, y_std = gp.predict(X_test, return_std=True)\n",
"\n",
"# Illustration\n",
"f, ax = plt.subplots(1, 1, figsize=(14, 7))\n",
"ax.plot(X_raw, Y_raw, 'k.', markersize=4)\n",
"ax.plot(X_test, y_pred,\"-\", color=\"steelblue\")\n",
"ax.fill_between(X_test[:, 0], y_pred - y_std, y_pred + y_std, alpha=0.3, color='k')\n"
]
},
{
"source": [
"Next gpytorch..."
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 1
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