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Explore model capacity as a function of the number of training examples
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{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"import numpy as np\n", | |
"import matplotlib as mpl\n", | |
"import matplotlib.pyplot as plt\n", | |
"\n", | |
"%matplotlib inline" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"mpl.rcParams['axes.titlesize'] = 16\n", | |
"mpl.rcParams['axes.labelsize'] = 14\n", | |
"mpl.rcParams['xtick.labelsize'] = 14\n", | |
"mpl.rcParams['ytick.labelsize'] = 14\n", | |
"mpl.rcParams['legend.fontsize'] = 14\n", | |
"mpl.rcParams['figure.figsize'] = (8, 6)" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Construct a polynomial" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"from numpy.polynomial.polynomial import polyval" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 4, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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LQkJEENbsKmbx1yCHU+LNLYV4c8sJlJisSIgIxv/kDMJNkzKRERfW5fddPiIZ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\nkiQ15jdVaafFJd9zQgAAAABJRU5ErkJggg==\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x10a5d5450>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"# 5-degree polynomial (arbitralily chosen coefficients)\n", | |
"# figure 5.4 caption does not specify\n", | |
"coef = -1, -6, 5, 5, -5, 1\n", | |
"\n", | |
"x = np.linspace(-4, 4, 100)\n", | |
"y = polyval(x, coef)\n", | |
"\n", | |
"label = r'$y = {:+d} {:+d}x {:+d}x^2 {:+d}x^3 {:+d}x^4 {:+d}x^5$'.format(*coef)\n", | |
"\n", | |
"plt.plot(x, y, label=label)\n", | |
"\n", | |
"plt.xlim(-2, 4)\n", | |
"plt.ylim(-6, 6)\n", | |
"plt.xlabel(r'$x$')\n", | |
"plt.ylabel(r'$y$')\n", | |
"\n", | |
"plt.axhline(y=0, color='gray', lw=1)\n", | |
"plt.axvline(x=0, color='gray', lw=1)\n", | |
"plt.legend()\n", | |
"plt.grid()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Generate random samples from polynomial" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 5, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"# limit domain to interesting part\n", | |
"xmin, xmax = -1, 3" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 6, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"def uniform(a, b, n):\n", | |
" width = b - a\n", | |
" center = 0.5*(a + b)\n", | |
" return width * (np.random.rand(n) - 0.5) + center" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 7, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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Pb6H7ZX8icF3ffl/gOODX+jabgf3p5g7MzRtYDzwMr4QoSdIeGfUWxm/Y2w9K8g7gRcDP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\nSJLUOMOAJEmNMwxIktS4/w8Cs5uTUC94tAAAAABJRU5ErkJggg==\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x10a5d5210>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"# sanity check uniform function\n", | |
"plt.hist(uniform(xmin, xmax, 10000), bins=25)\n", | |
"plt.xlabel(r'$x$')\n", | |
"plt.ylabel('Counts per bin');" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 8, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"# gaussian random noise \n", | |
"def noise(sigma, n):\n", | |
" return sigma*np.random.randn(n)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 9, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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NbUTjJfeQ+sXvfkcT2S9lafn/BLQGfiiy/BJgWdgSiYinfXtwzu8UCS3lomNJ\n2fISzBnN2LzzuKr3OBZUqOR3LJH9Vpbi/xzwkpk1BT7Hu7b/POBG4J4IZBMR8c+2DTCmC/zwEVzw\nAD2nNuEqFX6JE2W5zn+Qmf0C/BO4qmDxQqCjc+6DSIQTEfHFhtXw5jWwZgG06w/NutAjT7fglfgR\nUvE3swp43fufOufGRTaSiAAwaJDfCRLTL995hX/zr97NeRpcAmgkv8SXUO/qlwuMBQ6ObBwR2aVb\nN78TJJTUjBxY+pl3DX/eNrhl0q7CLxJvyjLa/xvghEgFEZEidHOYqFoybRiMuBKq1oR/ZOxxDb9I\nPClL8e8DPG9mV5jZ0WZ2ROFHhPKJiESWczD9BV6s9DLUPRP+MQUO19XLEt/KMto/veDnWLyR/jsZ\nuqufiMSg/lMWUGP6v7m2QhYf5J3DA993ZXvfz3VHPol7ZSn+LUvfRETCpm1bvxPEty2/02PVv6DC\ndLjwX/SYcipL++mYS2IIdbR/RaAN8IpzThP6iETDhAl+J4hfvy2GNzt6d+W7chCcdi1MSS99P5E4\nEepo/x1Ad7wu/v1iZt3NbImZbTWzbDM7P8T9zjOzXDObv78ZRGJCu3Z+J4hPy76Awa28S/lu+sAr\n/OiOfJJYyjLgbwpw0f68mZl1AvoDTwGn480U+KGZ1Stlv8OB4UDm/ry/SEyZONHvBHElNSMH5o2B\n4e3hwCPgto/gmHN2rdc5fkkkZTnnnwk8ZWanAtnApsIrnXNjQ3iNnsBQ59zgguf3mNmlwJ3AQ3vZ\n73VgGF7Pw9VlyCwi4o3oz+oHFd+DpPOh43DvC4BIgipL8d95K997i1lX6mh/M6sENMO7R0BhU4Fz\n9txj137dgZrANcCjoYYVEQFgx1YYfw8pFd+D0zp70/Vqjn5JcOaidNcwM6sNrAAudM59Wmj5Y8D1\nzrkTi9nnFOAj4Gzn3BIz6wNc7Zw7uYT36AZ0A6hRo0azUaNGhf8XiTEbN26katWqfseIezrO0VHW\n45z53RquWvkMp5f7gWd2dGRA3uWAcfnxFbmyvr4AlESf5+iIxHFu2bJltnOueWnblaXlHy5Fv21Y\nMcsws8rAKOB+59ySkF7YuTQgDaB58+YuOTl5/5LGgaysLHQcIi8ixzktTVP8FlGm47zya5LndIfK\nv8NVIxkwrBxL+7WJaL54of83osPP41zqgD8z+9zMDiv0/OnCM/qZWTUz+ymE91oH5OF14RdWHVhT\nzPa1gEZXQ2n5AAAc/UlEQVTAkIJR/rnAY0DjgueadFvi2+23+50gdi0YB29cChjcOgUa6soJkcJC\nGe1/NlC4f+wu4LBCz8sDdUp7EefcdryBgq2LrGqNN+q/qBXAKUCTQo+BwA8F/y5uHxFJZPn5MO1p\nGNMFap0K3aZ5P9GlfCKF7Uu3//5c6/8CMMLMZgEzgDuA2nhFHTMbDuCcu6lgboHdruk3s1+Abc45\nXesvIrvbvgnevxO+/QCaXA9tU6FC5V2rdSmfyF+ies7fOfeOmR0JPILXrT8fuKzQrIF7vd5fJKGM\nH+93gtjx53J4+zpY/T+45D/Q4m7dFVFkL0Ip/o49B+Tt8yUCzrkBwIAS1iWXsm8fvLsLisS/Zs38\nThAbfpoJo2+E7Zuh82hooOFAIqUJpfgbMNLMthU8rwIMNrPNBc8rF7+biOyXOnW8yWmkZNlDIf1+\nOLQuw+q/yM0q/CIhCWXA3zBgJfBrwWMk8HOh5yvxpt4VEYmO3O0w4T6Y0AOOuxC6TaP3F3l+pxKJ\nGaW2/J1zt0QjiIhISDasgdE3wc9fwrn3QavHoNxeJxgVkSLKcmMfEYmmrl39ThAYqRk5ABy8PgfS\nkmH1PLj6DVK5nqR/Tyapl3c73qRe6ST1St+1vYgUz48Z/kQkFGlpficIjP6Zi0ipNovT5/4bDq0F\n/5gKNU8h5eS/LuFL6pWuGfxEQqSWv0hQabS/J28HvSsMgw/u4s9DG0K3T6DmKX6nEolpKv4iQTVn\njt8JfJWakcMZvd5kZt/zuKXCFNJy29B89QOkzlhX7PaawU8kdOr2F5FASmnwKynf9IVtG7h30128\n+NRTNMjKIjm5+Jn6NIOfSOjU8hcJqlq1/E7gD+fgiwEwrC1Uqgq3ZTI+/1y/U4nEFRV/kaBaudLv\nBFGza3T+to3w7q0w5SGo/zfvxjw1GqlLXyTMVPxFgqpPH78TRE3/zEWwNgdeawXfvg+tekOnkVDl\nUEBd+iLhpuIvElR9+/qdIGouLTcLBreETWvhxnFwfk8op/+eRCJFA/5ExBepGTm8krmQByq8w8BK\n6czdegLdt/eg44+1STnO73Qi8U3FX0R8kXLmgaT89Ar8PJMRuRdzY5+3+KKC7hMmEg3qVxMJqtmz\n/U4QOYsyYOD5sGYBdHidR3NvBRV+kahRy19EoicvF6Y9CZ+9ANUbQ8dhUK0+PVppLn6RaFLxFwmq\n5s29a97jxfpV8N4/YNkMaHoT/P0ZqHgAoNH8ItGm4i8iEffemBF0WNIHdmyGKwfBadf6HUkkoan4\ni0jk5OfBJ89w5fz/QvUT4ZphUP0kv1OJJDwVf5Gg6t3b7wT7588VMLYrLJvBuPzz6dD1Hah0kN+p\nRAQVf5HgiuUZ/r6bxJZ37yB/x1Ye3XEHY/Mv4J+PZQHe3fd0jl/EXyr+IkFVu3bsze+/YytkPAaz\nBnFAzVPh6iG8UO0ExvZKZ2m/Nn6nE5ECus5fJKhWrfI7QUh23ZRn3SJ47WKYNQjO7g63fQTVTvA3\nnIgUSy1/Edkv/TNzSKk2CyY94F26d907cOKlu22ju/KJBIuKv0hQNW3qd4LSbf2T/hVfgQ8+h6Tz\n4arBcEitPTbTOX6RYFG3v0hQZWf7naBEqRk5XP3Q8yx/uiltyn3Jczuu4bjvbid15ga/o4lICNTy\nFwmqbt0gLc3vFHvK20FKuXdIqfICHFaPq1bfzdinU7jf71wiEjK1/EWCavBgvxMAhQb0Aaz7AV6/\nBKY/B6d1hjs+Y45Tl75IrFHxF5G96p+5yLvHwOwhMOh8+G2xN1PfFa9A5YM1mE8kBqnbX0T26gjW\nw6jr4ft0OPZCuHIgHFJ713oN5hOJPSr+IkG1YoVvb52akUP/zEUkl/uayZXT2PbdRp7JvYGqte4h\npVDhF5HYpOIvElTZ2d4sfz5IuaAWKVtehjnD+D6/LtW7p/NozZN9ySIi4afiLxJU7dt759qjbeln\n8P6d8MfPcG4P2meezvcq/CJxRcVfRDw7tkDmE/DlADg8CW6dDPXO5g5ySt1VRGKLir9IgkvNyCGl\n0QYYdwesy4EzboPWj++6/a4G9InEHxV/kaAaNCjy75G7nfKfPAmfT4CDa8KN4+D4iyL/viLiKxV/\nkaDq1i2yr79qHnzQnXsr/A9O7QyXPg0HHBbZ9xSRQNAkPyJBZRaZ183dxpevpbBjYDJrV/1Et+0p\nJM1sS1LfGbvP5icicUstf5FEsjwbPriLs9cuhCbXcdTfnmLq41+wtF8bv5OJSBSp5S8S51IzcryR\n/FMfhdcvhq1/Qucx3kx9Bx7hdzwR8YFa/iJB1bZtWF7ms48nkvLdm/DrD9D0ZrjkCahy6K71mptf\nJPGo+IsE1YQJ+7f/to3w8ROMqTQI8o6GG9+H41vusZku5RNJPOr2Fwmqdu32eddx7wxh+VOnwcyB\nDM9rTaPVfUgavFkD+kQEUMtfJLgmTiz7PhvWwOReXLlwLFQ/Cdq9SZ8Bv2pAn4jsRsVfJB7k58Pc\nEZDxqDe4r+UjcG4PqFAJSPc7nYgEjIq/SAxLzcghpQkw8T5YNgOOORfa9Ydqfw3i04A+ESlKxV8k\nqEq7o1/uNvKz/gtfjoeKB0D7l6DJDVBu96E8GtAnIkVpwJ9IUKWllbxucRa8ei7/rPguNGwHd8+G\npjftUfhFRIqj/ylEgur22/dctn4V3718DQy/nKVr19Nl+4Mkze5A0n++0kh+EQlZ1Lv9zaw78ABQ\nC1gA3Oecm17CtlcBdwCnA1WAb4EnnXPjoxRXJBjycuGrwfDxk5yUtx0u7EXSeSlkPZqpkfwiUmZR\nbfmbWSegP/AUXkH/HPjQzOqVsMuFwMdAm4LtJwHjzOz8KMQV8V1qRg78PAvSkmFyLzj6TOj+BbR8\nCCpW8TueiMSoaLf8ewJDnXODC57fY2aXAncCDxXd2DnXo8iivmbWBrgCKLa3QCRujB5JzU8ehBnT\n4ODa0HE4NGy/293+NJJfRPZF1Iq/mVUCmgHPFVk1FTinDC91MPB7uHKJBE5eLmQPgbl9uLriFjjn\nXrjwX1C56h6baiS/iOwT51xUHkBtwAEXFFn+GPB9iK9xF7ABOKaE9d2A2cDs+gcd5Jx3sZRz4L4a\nONB9NXDgbsuW3HyzmzZtmtt65JG7lq2vX99NmzbNrWjTZrdtZ4wZ4+Y9+eRuy77r2dNNmzZtt2Vr\nW7Rw06ZNc2tbtNht+bRp09x3PXvutmzek0+6GWPG7LZsRZs2btq0aW59/fq7lm098kg3bdo0t+Tm\nm/U7xfnvNHfsi25j88N32/aM7sPcrR0ejdnfKR7/Tvqd9DsF9XcCZodUT30o/ucXWd4b+C6E/TsA\nm4H2obxfs2bNnDjvAy0Rt6/H+YWp33v/+H2Zc+/c5FzvQ5x74WTnFrzvHLhj/jUxfCHjgD7P0aHj\nHB2ROM6hFv9onvNfB+QBNYssrw6s2duOZtYBGAHc5DTSX+LIwMwFpFQcC5+lAgbJ/4Zz7/Um7RER\niZCoFX/n3HYzywZaA2MKrWoNvFfSfmbWERgG3OycezeyKUWixDn49gMyK98PWeug8ZXQ+gk47Oi/\ntunaVQP6RCQioj3a/wVghJnNAmbgXcNfGxgIYGbDAZxzNxU8vxavxX8/8KmZ7ew12O6c+y3K2UXC\n4q2x4zjh66c5s9z3bHD16LT9UWZmN6THYVtIaV1ow7Q0UnxLKSLxLKrF3zn3jpkdCTyCN8nPfOAy\n59yygk2KXu9/B17G/yt47PQJkBzZtCJh9sfPkPk4nf83Gg4+Clr+H23fPZIf+7UvfvtmzSA7O7oZ\nRSQhRH2GP+fcAGBACeuS9/ZcJJakZuR4l+JtXe+d0/+y4GN//j/hvBSofDB57+7ldrtz5kQnqIgk\nHN3VTyRCXs78jpTDP4NpT8GmtXBqJ7jo0d3O6+ucvoj4QcVfJNycg5wpTKr0EExcDvXOgc6joU7T\nPTbd6yQ9tWpFMKSIJDLd1U8kjEa9N4ZZvc+CtztRiR3cvj2FpJy7SP12z9n5SrVyZfgDioiglr/I\nPtt1Th84cNNP8PZ1XPv9JDikBlz4Aq3fq8YP/S7f9zfo08d7iIiEmVr+Ivuof+YibwT/+90546se\nsPQz75z+vXPhjH+Qu7/frfv2DU9QEZEi1PIX2Rebf+PhCiPhpUwAltdtz9GdU+HAI3ZtosF8IhJU\nKv4iZTDgw2xyZ7zIreUnc2v5bYzedgH/l9uBM1wt+hcq/KA77olIcKn4i4Ri63qYOZDuX78MFf6E\nRpdz8dxz+ejp2+kIZGVlhf89Z88O/2uKiKBz/iIlSs3Ige2bvAl6+p8K056EpPPgjs+g43B+cHX9\njigisk/U8hcpzo4tbMzqD19P8SboOaE1tPz3btfqR/ycfvPm3pwBIiJhpuIvUtj2TTB7CHz+Io9W\nXAPVL4SWD0O9s/bYVOf0RSRWqfiLgHdO/6vBbP7kRQ7M/YMZeY15MbcbMxc2hIXr6NEqR8VeROKG\nir8krNSMHFLOOwq+HAgzX4Wtf3LgCa3hggc4t95ZXN8rnaX92vgXsHdv/95bROKair8kpk3rqPzJ\nE/DVNNi+AU5q691tr5j5932j2f1EJEJU/CWx/L4MvngF5o7gjvJboP4VcP79UPPkPTb1fZKe2rU1\nv7+IRISKvySGVfNgRn/y548j18H4/HN5NbcdP2bXgexl9GhVaY9z+r6f41+1yt/3F5G4peIvcSk1\nI4eUi+vDkk9gRn/48WOoVJVyLe6k0tndufrQOtzv9zl9ERGfqPhL/MnL5YdpI2Dxp7DqazioOrR6\nDJr/Aw44zO90oWsaoPEHIhJXVPwlfmz9E+YMh5lpvFLpJ9h2PLTrD6deCxWr7LG57+f0S5Od7XcC\nEYlTmt5XYlJqRs5fT379ESY9yPZnToKpjzDz9wO5fft9HLeyL0ljjiI166diX8P3c/ql6dbN7wQi\nEqfU8peY1D8zh5TjV8GXr0LOZChXgUond4Cz7+Cs2qfTKR7O5w8eDGlpfqcQkTik4i+xZftmmP8u\nH1Z6Fob/BAceCRc8AGf8Aw6u6Xc6EZGYoOIvsWHdIua89zzHr/yAQ20zcDQP7OjG+N/O4Y68xqQU\nKfyBP58vIuIjFX8JpNSMHFIuOg6+nwRfvQZLPqFpuYpwSns44zb+/upvLO3XlmdL2D/w5/NDsWKF\n3wlEJE6p+EvwrF+Fy/ovzPscNqyEQ+rCRY/A6TfBwTUKNkr3NWJUZGd7s/yJiISZir8EQ14u/JAB\nc0ZAzmR6VsyD6q2gzXNQ/29QfvePakJ067dvD875nUJE4pCKv0Rdakah2+P+thjmjoS5b8LG1ax1\nh/Be3t95O+8ili2oCQugR6vFwZt6V0Qkhqn4S9QNzFxASo1vYM4wWDodrByc0BqaPs9RDf7GHeUr\n0i8eLtUTEQkoFX+JDufg51kwbxQzK78DYzfB4Uneufwm18MhOre9h0GD/E4gInFKxV/Cbo9u/W/e\n4Y+ZIzls63K2uEpk5TfnnbyWfLmqIfc2OpGUYgp/QpzTL41m+BORCFHxl7AbmjmXlMOmw7x34OeZ\ngHHYsRfAaQ9zQMN23Nf701K79HVOHzDTgD8RiQgVfwmPbRu9aXbnj2VW5SmQngtHNYSL+8ApHeHQ\nOn4nFBGRAir+Uma7uvV3bIGcKbBgLDu+m0zF/G2sdoeTnteasXnns+DnY+jRoAEpRQq/uvRFRPyl\n4i9lk7uNBdNGwfqf4PsPYftGOOgoKja7ERpfRc16LXji3x/utVtfXfohatvW7wQiEqdU/KV02zbA\nogz4biLkTOW1Shvgh8Ph5A5w8lVwzHl7TMIjYTBhgt8JRCRO6X9s2UNqRg4p5xzhzau/cCIszoK8\nbaxzh/BRXjMm55/JZ1tPJvfzCvQ4oDYpxyXg7HvR0K6dvgCISESo+Mtffv0RciZzzvTh8HkOuHw4\nrB6ccRuc1IZq9c7m2nLl6VXKBDzq1g+TiRP9TiAicUrFP8Hsdg1+7jZYNgNypsKiqfDbjwAcwtFw\nwQNwUluoeYp3yZmIiMQNFf8E807ml6QcPsM7h784C3ZsggpVWHJwU97YcT7T8puw3FWHKcCUn+nR\nqsoeLXl164uIxDYV/zizW8seKJ+7Gb6f7BX6xVl8WWUhTAQOrQdNroP6l0DS+Rxb6UCeKNgnSd36\nwaAJfkQkQlT848wrmQtJOfF3WDwNFmdx7s+zwOWx1VVkVv5JfJZ/HdPyT2fRmjr0OLkBKQ1UyAMr\nLU1T/IpIRKj4x5iiLXvydsCqb7xz90tnMLfyp/DGFsCgdhN+PvoKjkm+iSpHn80FFatwUwh3y1O3\nfkDcfruKv4hEhIp/jBmYuYCU+r/Ass+9gv/zLNixGYAf82sxM78F0/NP4Yv8Rtx8bFNOr7iSY45L\nLtN7qFtfRCS+qfgHyB6teoD1K2H5VwWP2cyr/BUMzQUMajSG02+AY86Beudw/ME1aFWkZZ+VtXK3\nl1OrXkREVPyjqNjiXsjAzAWknPjbbsWe9SsA2OYq8K1LYlb+35iVfxKz80+kywmnl7mVrlZ9DBk/\n3u8EIhKnVPyjqH/mor+K77YNsHo+rJ7nnbNfNY/5lb+FN/K89YcdA/VaQN0zoO4ZVK55MqdXqMyV\npZyzV8s+jjRr5ncCEYlTKv5hVGzL3jmv637tQrqVnwDvvger5sGvPwDepVxr3SEsyD+W+a4tX+ef\nwNf5J3B94+b71EpXyz6O1Kmjy/1EJCJU/Mtgr932zvFW5lekHL8SflnoPdZ+x9aVC6iStxGAf1eE\n5f+rxoL8JA4+thvnnHsR1DqNow6uSbIZXTQSX0REokDFvwz6Zy4i5bzq3jS4vy4u+Pnjrp9fVfkD\nhhdsfMDhUL0RVU7vBNUbQvWGNBm4nK/7XUvd/ciglr2IiOyvqBd/M+sOPADUAhYA9znnpu9l+wuB\nF4DGwErgGefcwGhk3eX3pTC2G7MrL4T/ri+cjvWVazBv85Esdc340dXme3c0i/Lr0vmc5qRccuJu\nL/MH6Xt9G7XqZTddu/qdQETiVFSLv5l1AvoD3YHPCn5+aGaNnHM/FbP9scAk4A3gBuA8YICZrXXO\nvReNzKkZOQzJnEtapfUsyW/GEleTpa4m5511FjddlswhFQ/gvIJgpU2LW1pxV6tedpOW5ncCEYlT\n0W759wSGOucGFzy/x8wuBe4EHipm+zuAlc65ewqeLzSzs4D7gagU/5TWDQqKcieuDeGcfGmvJRKy\nZs0gO9vvFCISh8pF643MrBLQDJhaZNVU4JwSdmtRzPZTgOZmVjG8Cfefuu0lrObM8TuBiMSpaLb8\nqwHlgTVFlq8BLi5hn5rAR8VsX6Hg9VYVXmFm3YBuADVq1CArK2v/Ehdx+fEV9/qap1fcc0Y9v23c\nuDHsx0H2FInjnAz62xWhz3N06DhHh5/H2Y/R/kUvXLZilpW2fXHLcc6lAWkAzZs3d8nJyfsYsXhh\nfrmoyMrKItzHQfYUkeNcq5b+dkXo8xwdOs7R4edxjlq3P7AOyMNrzRdWnT17A3ZaXcL2ucCvYU0n\nEjQrg9WLJCLxI2rF3zm3HcgGWhdZ1Rr4vITdvmDPUwKtgdnOuR3hTSgSMH36+J1AROJUNFv+4F2v\n38XMbjOzhmbWH6gNDAQws+FmNrzQ9gOBumb2fwXb3wZ0AZ6Lcm6R6Ovb1+8EIhKnonrO3zn3jpkd\nCTyCN8nPfOAy59yygk3qFdl+iZldBqTiXQ64Erg3Wtf4i4iIxKOoD/hzzg0ABpSwLrmYZZ8ATSMc\nS0REJGFEu9tfREI1e7bfCUQkTqn4i4iIJBgVf5Ggat7c7wQiEqdU/EVERBKMir+IiEiCMef2NrNu\n7DKztcCyUjeMf9XwZleUyNJxjg4d5+jQcY6OSBznY5xzR5W2UdwWf/GY2WznnE4eR5iOc3ToOEeH\njnN0+Hmc1e0vIiKSYFT8RUREEoyKf/xL8ztAgtBxjg4d5+jQcY4O346zzvmLiIgkGLX8RUREEoyK\nv4iISIJR8Y9xZtbdzJaY2VYzyzaz8/ey7VVmNtXM1prZBjObaWbto5k3VpXlOBfZ7zwzyzWz+ZHO\nGA/KepzNrJKZPV6wzzYz+8nM7o1W3li1D8e5s5l9bWabzWy1mY00s5rRyhuLzOwCMxtvZivMzJlZ\nlxD2OcXMPjGzLQX7PWZmFol8Kv4xzMw6Af2Bp4DTgc+BD82sXgm7XAh8DLQp2H4SMC7UQpao9uE4\n79zvcGA4kBnxkHFgH4/z28ClQDfgROAaYF6Eo8a0sh5nMzsXGAEMAxoDVwCNgDejEjh2VQXmAz2A\nLaVtbGaHABnAGuAM4F7gAaBnJMJpwF8MM7OZwDznXNdCyxYB7zrnHgrxNWYB051z/4xQzJi3r8fZ\nzMYC3wAGXO2cOzniYWNYWY+zmV0CjAGOd85pNroQ7cNxvh+4xzl3TKFltwAvOeeqRiNzrDOzjcDd\nzrmhe9nmTuC/QA3n3JaCZY8AdwJ1XZiLtVr+McrMKgHNgKlFVk0FzinDSx0M/B6uXPFmX4+zmXUH\nagL/iVy6+LGPx/kK4Cugp5ktN7NFZvaimakglWAfj/MMoJaZtTNPNeBavJ5DCZ8WeA2xwr0EU4Da\nQFK430zFP3ZVA8rjdREVtgav6JTKzO4C6uJ16UnxynyczewUoDdwvXMuL7Lx4sa+fJ6PA84DTgM6\nAHfjnQIYGpmIcaHMx9k59wVwHV43/3ZgLV5v1s2Ri5mQalL832XnurBS8Y99RbuCrJhlezCzDsCz\neAVKN0AqXUjH2cwqA6OA+51zS6IRLM6U5fNcrmBdZ+fcTOfcFLwvAB3MrEYEM8aDkI+zmTUCXgSe\nwOs1uBSvGA2KZMAEVdzfpbjl+61CuF9QomYdkMee3wirs+e3x90UFP4RwE3OufGRiRc3ynqca+EN\nhhpiZkMKlpUDzMxygcucc0W7XGXfPs+rgBXOuT8LLVtY8LPeXvZLZPtynB8CZjnnni14Ps/MNgHT\nzexh59zPkYmacFZT/N8FIvBZVss/RjnntgPZQOsiq1rjjd4tlpl1BEYCXZxz70YuYXzYh+O8AjgF\naFLoMRD4oeDfJf5tEtk+fp5nALWLnONvUPBTvVnF2MfjfCDeF4bCdj6PyGVoCeoL4Hwzq1JoWWtg\nJbA07O/mnNMjRh9AJ7xzcLcBDfEu39mIdz9n8C4zG15o+2uBHXiXntQs9DjC798lyI+yHudi9u8D\nzPf79wj6Yx8+z1WBn/FG/DcGzsW7tGqM379LkB/7cJy7FPy/cSfeOItz8QZaZvv9uwT5UfD53NkA\n2Aw8VvDvegXrnwYyC21/KF7rfxRwMnAVsB74Z0Ty+X2A9NjPPyB0x/tWuA3vG/0FhdZlAVlFnrti\nHlnRzh1rj7Ic52L2VfGP0HHGu7Z/asF/riuAV4CD/f49gv7Yh+N8D7Cg4DivAt7Cu/zM998lqA8g\nuYT/b4cWrB8KLC2yzynAp8DWguPcm4JL8sP90HX+IiIiCUbn/EVERBKMir+IiEiCUfEXERFJMCr+\nIiIiCUbFX0REJMGo+IuIiCQYFX8REZEEo+IvIiKSYFT8RUREEoyKv4iEhZmdaWYZZrbWzFyRx/F+\n5xORv6j4i8h+M7OT8eaEX4g3p/lFeDcpmQXcACz2K5uI7Elz+4vIfjOzTOAP51yHQsueBq52ztX3\nL5mIFKeC3wFEJLaZWTXgQuBvRVZtwruLmYgEjLr9RWR/NQPKA98UWd4c777vIhIwavmLyP4qX/Dz\ngJ0LzOwEvJ6AK31JJCJ7pZa/iOyvmcBm4Bkza2hmfwPSgVHOucn+RhOR4mjAn4jsNzO7DHgBOA5Y\nAbwO9HPO5foaTESKpeIvIiKSYNTtLyIikmBU/EVERBKMir+IiEiCUfEXERFJMCr+IiIiCUbFX0RE\nJMGo+IuIiCQYFX8REZEEo+IvIiKSYP4fC1CA/LagEXYAAAAASUVORK5CYII=\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x10dcc2710>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"# we want to pick a sigma that yields rougly a ~0.2 MSE\n", | |
"n = 10000\n", | |
"sigmas = np.linspace(0.1, 1, 50)\n", | |
"mses = [np.mean(noise(sigma, n)**2) for sigma in sigmas]\n", | |
"\n", | |
"plt.plot(sigmas, mses, marker='+', lw=0)\n", | |
"plt.plot(sigmas, sigmas**2)\n", | |
"\n", | |
"plt.axhline(0.2, color='red', ls='--', lw=1)\n", | |
"plt.axvline(np.sqrt(0.2), color='red', ls='--', lw=1)\n", | |
"\n", | |
"plt.ylabel('Error (MSE)')\n", | |
"plt.xlabel(r'$\\sigma$')\n", | |
"plt.grid()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 10, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"test_sigma = np.sqrt(0.2)\n", | |
"test_n = 100\n", | |
"\n", | |
"test_x = uniform(xmin, xmax, test_n)\n", | |
"test_y = polyval(test_x, coef) + noise(test_sigma, test_n)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 11, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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jLnQu9uojqTEMGANjP4Om7WH6JZD152r3h1C9CBcUbIOERpCqgl0NpeQvAYew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\ndG5RAAAAAElFTkSuQmCC\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x10dc60c50>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"fig, ax = plt.subplots(figsize=(8, 6))\n", | |
"\n", | |
"plt.plot(test_x, test_y, marker='+', lw=0, label='test set')\n", | |
"plt.plot(x, y, label='truth')\n", | |
"\n", | |
"plt.xlim(-2, 4)\n", | |
"plt.ylim(-6, 6)\n", | |
"plt.xlabel(r'$x$')\n", | |
"plt.ylabel(r'$y$')\n", | |
"\n", | |
"plt.axhline(y=0, color='gray', lw=1)\n", | |
"plt.axvline(x=0, color='gray', lw=1)\n", | |
"plt.legend()\n", | |
"plt.grid()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 12, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"0.19419998259009286" | |
] | |
}, | |
"execution_count": 12, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"# check MSE\n", | |
"np.mean((test_y - polyval(test_x, coef))**2)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 13, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"# \"closed form fit\"\n", | |
"def poly_least_squares_fit(x, y, degree):\n", | |
" # polynomial features\n", | |
" X = np.empty((len(x), degree + 1))\n", | |
" for i in range(degree + 1):\n", | |
" X[:, i] = np.power(x, i)\n", | |
" # least squares fit\n", | |
" result = np.linalg.lstsq(X, y)\n", | |
" fitted_coef = result[0]\n", | |
" return fitted_coef" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 14, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"array([-1.07976384, -6.11490336, 5.07159267, 4.9828746 , -4.9694386 ,\n", | |
" 0.99102186])" | |
] | |
}, | |
"execution_count": 14, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"# check fit results using correct\n", | |
"poly_least_squares_fit(test_x, test_y, 5)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 15, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"array([-0.3171954 , -1.82207557, 0.40317794])" | |
] | |
}, | |
"execution_count": 15, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"# can fit polynomials of other degrees\n", | |
"poly_least_squares_fit(test_x, test_y, 2)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 16, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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I6SzOLkYo+2cjveprS4dCrMwbb7xRIhKJ+JiYmHBvb+/o3NzcNlf4xsbGqj/4\n4IO877//3m3AgAFhBw4cUC5atKj42jZPPfVU9YgRI2offPDBYG9v7+i1a9faVPmYW6E5g1aotrwJ\n21ZeQO8YNwyd3rfdwtSc+M85hryBR8PJIigGe4EJ2871D3z9OZIP7Ud9ZQW4XiGdGjshhHS3LFcX\nLFdMx8O1uzDG0sEQqxIVFaW5cOFC2rX3vfzyy232hLz++usVr7/+esW197399tstc7ekUim/Z8+e\ny9cfx/N8wvX3FRYWJnY86u5HPYNWqK5cjcYaDS4eKMCZnbm3dWz1L5mo/fUyqn/JxPWTYZvFTZgC\nALh0YA+0DeYVve6o9oaEqfwMIeROVfGmL8xKwV29iQQhHUbJoBXyC3PG6DnhYAw4syMH5/flm32s\n4l4vMBGHpnNlqNuX12YbN/9ABN9zHww6HYoTTnRW2G1qb0iYhoYJIXfCYDDgCm+aC+1AY12EdAgl\ng1aqb5w7Rj0ZCgA4vjkLSYevmHWc2NcezrNDAQbUHyxAw+niNtsNeXQ2GONQkZqIqiLzzn07yrU6\nLLtcjP/klWJzSRX+qK6HUSaA1oaW2hNCrF9jYyNy4QoAcBLRRxohHUF/OVas371eGDHT1HN2eH0G\n0k62ndhdT9rPGY5T+gIAarZmtbmPsYuPHyJGjQZ4Hsc2fNd5QQPQGXk8fSERK/NK8f7lYryQmo9p\nF7KhHeaJLekbO/VahJC7m1qthkZoWhPgKLKZGr+EWBVKBq1cxAhfDJlqSuwaazRmH6cY7AX7kX6A\nEaj6MRXaooYb2tw7fSaYUIjMU8dRlnvDnNgOez8zGwmNHJz4Soznt+Me/hiC+VS48aVA5eaWdjoz\nVksTQsitqBrqoRaatvJ0ErW/pSch5EY0w8IG9B/jD68gB3j2crit45RjAmCo1cBQr4XQ2e6Gx+2d\nXeF7z3D0H3wP3AJ6dVa4uEehw0bU4un6byDMUsJOWgypnQESOz0gcMP69eshHHAPPqpowsbo3giU\nSTvt2oSQu4u6vhJNnOk9xFPu205rQkhbKBm0EdcmgnUVKtRXquET4nSLI0y7lDhNDQKYqR5hW9wj\nYxE0aEinxjrOJxRD7JU4uskfZ+pFqL9uwTKPdJx09kSe2AmPJpzFb4PvhaOYXoqEkNunqq/GtFMJ\nCPR3RsSI5ywdDiE2iT6BbUxjrQZblp+DukGHiS9Gt58QXlNrkNcb0XCiGIohXm0mhzUlxVC6u4Pj\n2t8b+XoT1y4QAAAgAElEQVRaoxEJVcW419UHAKD8/Z+YkP8Dxts5Qyt2gEaghEaogIqzR3GNCs9m\nrsfU8A+Rr/fHE+eO45dBwyDiekwxd0JIN1HX10Kq1yJACAjpPYSQDqE5gzZGZi+GX5gz9Dojdnx6\nCUVZNWYfW/VTOmp3XkbNtuwbahCe2LQe6155DqlHD3UoriUZWZiaWIq/7f8Ytad/BM7/AAz7f+AW\n58Du1QtwWHgE7i/sQsBfNuKeBZ/CzyjDF5eXQsnX4IxKiYUX/7hpXURCCLkZVVM9ROIm2MmF9B5C\nSAdRMmhjGMcwcnY/hNzjCb3GgB3/uYiSy7VmHau4zwcQcmg8XYKGI63LyTi4e4A3GvHHxh+g12pv\nK6btpZX4urgJHG+AW8NZrN99HLz3ACB+cdsHOPgCT+9ESIMYcwv/BxGvwS81CqzIOHtb1yWEEK8A\nJxwbGIL19vloaEy3dDikByouLhYyxuJ27Nhhb+lYugolgzaIcQyjngxF0EAP6DQG/PrJBZTl1bV7\nnMRfCecZpu3nanfnoimxvOWxfveNgJt/IOory3Fh7w6zY8lVabAoNQcA8Kh+PXTJvhgvOAk2/UtA\ncIsyD0pvsJnrochVYEaVaYXxh0UCnCs3vZk371BCCCG3UqnT4rwwDhnoB5Hw9hbZkbvDsmXL3Hx8\nfCIlEklseHh46J49exSWjsnaUDJooziO4YGnQ9En1g1atQHbV11AU137PXqySFc4jDetHK7amAFJ\nTfP5BBg262kAwKktP0HdeGMpmrasykpEEy/EAP4U/JJVGKk7jYCHFgPO7a9OlrkH4ol5L8E3hcfj\ndT/iH/zrEJd9aTrvgUyzrk8IubtVa9QAAAUaIBLdeg41ufusXbvW6e9//7vfq6++WnzixImUAQMG\nNEydOjUoMzNTbOnYrqdWqy026ZWSQRvGCTiMnhuO3jFuiBsXCJnSvNe2YrgP5IM9Ab0RXuc46KtN\nb6aBMXHwC4uEurEBp7b81O55jDyP3ypNtQ8Hl1xAQG01BkeGAFGPmP07KD174ck5z8EnyQhtuhcK\nUsPNPpYQQv4oMX0JVrAmCAQ3ltAid7f//Oc/HtOnT6987bXXKmJjY9XffvttgZubm27lypVuNzvm\n8OHDsvDw8FCJRBIbGhoadvjwYfn1bRISEuzi4+P7yuXy/s7OztGTJk3qlZ+f37IoV6fTYe7cuX5K\npTJGqVTGzJ0712/27Nn+gwYNCmluM2jQoJDZs2f7z58/39fJySl6wIAB/QCgsrJSMHPmzABnZ+do\nuVzef+DAgSFHjhyRXXv9ffv2yQcOHBgilUr7u7u7R82ePdu/qqqqwzkdJYM2TiDgMG5+BPqP8W+5\nr71J1IwxOD7UB5IgR6gdAU4marl/+ONzAADndm1HdXHhLc+TUFODSl4OF74c7gVGTHLMAJv40W3/\nDs6+fTHjsWdRWtoHpxMvI+TfO8AzIHDxTgQu3klDxoSQm7qiN32MKZjOwpEQa6NWq1lKSop8zJgx\nreZRDR8+vO706dNtDhXX1dVxDz/8cJC/v7/m2LFjKf/4xz+uvPnmm60KWObl5YkeeOCBkNDQUNXR\no0dTd+/endHY2CiYMGFCkMFgAAAsWbLE8+eff3b55JNPco8ePZpqNBqxfft25+uvt3XrVhee53Hw\n4MH07777LsdoNGLMmDF9i4uLRZs3b848depUypAhQ+offPDBkLy8PBEAnD59Wjp58uTgBx98sOb0\n6dMpGzZsyE5OTpbNmjUrsKPPFZWW6QHYNeUUasqasHdtEu5/KgyuvjefFsEEHFweD0Py8aPoJ/mz\nlIxnnyCEj3gAOrUKAtGtexqdBDpMNCaAqYrwgPoUxLO/AiQdm1/r3ScUMf5KrJL0Rq23Lzyys3Hx\n2WkdOhch5O7RKDC9fzkIaN/z7hb5bWTczR57Le61vKcjnq4AgG+SvnFdnrA84GZtE59KTGi+PXnr\n5NDLtZdl7bUzR0lJidBgMMDLy6vVNwUPDw/d0aNHlW0ds2bNGmedTsc2bNiQ6+DgYBw4cKC6tLS0\n+IUXXmiZ+7RixQq3fv36qT777LOWHpONGzfmuLu7xxw5ckQ2cuTIprVr17q/+OKLJU8//XQNAHz1\n1VcFhw4duuGaPj4+mrVr17as6Ny+fbt9amqqrKys7IJCoeABYNWqVUV79+51XLt2rfM//vGP0n/9\n618eEydOrFq6dGnp1cM0n376ad7QoUPDCgsLhT4+PvrbeZ4ASgZ7nPN781BR0IBtK89j8qL+t0wI\nOYkAuJpH8jojmi6VQxbrjjHPvQRO0H6twb5Kd3zZOwjab/8K4ag3AN+bvi+YZdTUubiy6338A72g\n7uWMJr0WMuGfCemKfRl4ZXTwHV2DENJzGI1GNF390uoopBqDpG2MtX5t8DwPxhg/a9Ys/61bt7o0\n39/U1HQ+NTVVGhISonJwcGj5djFixIjGa4+/cOGC7MyZMwqZTNb/+mtlZGTYRUVFaSoqKkT33HNP\ny3EcxyE6OrqpqKioVS9LVFRU07U/nzlzRqZWqzl3d/eYa+/XarXc5cuX7QAgMTFRnp+fL5HJZC09\njc0jgqmpqRJKBgmGPxaCxlot8pIqsW3FeUx+5dYJIWB6EVV8nQTN5VoY1XrYD/X58zGjETz4mxei\nTt4CsUgC3PvCHcf+1Zky/JHkjkCPHORyvTDup/8h/5IbFt4fhFdGB2PVgUxKBgkhLVQqFexrNQgS\n5yKuT7ylw7nrmNtT93TE0xXNvYTt2TZlW+qdRfUnT09PvUAgQFFRUavSFmVlZSJXV1f9hx9+WPTm\nm2+WXvuYObUqjUYji4+Pr125cuWV6x/z8fHRGY1GBtyYhLZFJpO16tI2Go3MxcVF9/vvv99QJ8nJ\nyclwtQ1mzJhR8be//a30+jaBgYG3VxvuKkoGexiBiMP45yKx+4tEsxNCxhjkgzyhuVyL2h2XIXSR\nQtrPGSVZGTiw7jOEDR+F/uMmtTrmh9yLyCrOxDOXjyEgaDQguvP9hV8ZHYxXRr+OjTtfw0JZL5R6\n9cal6QOhFNPexYSQGzU2NiK8IB/Dy3Mx4aEplg6HWBk7Ozs+LCyscd++fco5c+ZUN99/9OhR5YQJ\nE6p9fHz01/eihYWFqTZt2uRSV1fHKZVKIwAcOXKk1QKS6Ojopu3btzsFBQVpJRJJm9mjq6ur7uTJ\nk/JJkybVA6YE7uLFizI3N7db9toNGDCg6V//+peI4zg+LCyszcQuIiKiKT09XRoREaEx75loHy0g\n6YGaE8KACBeoG3XYtuI8Kq7U3/IYWYw7lA/4AzxQ9b80aIsaUF9diZLsTBz/6Ueo6lvXMfw8rxyf\nq/tijft94EMntXnOji78GOD3CAINl1ELJRYe2daykASgRSWEkD811po+3+US6tcgbXvppZdKN23a\n5PLxxx+7njt3zu6ZZ57xKysrEy1cuLC8rfbz5s2rEggE/MyZMwPPnj1rt2XLFuVHH33kdW2b1157\nray+vl4wadKk3gcPHpSnpKSIt27daj9z5syA6upq7up5ylavXu353XffOV68eFEyf/5834qKChFj\n7JZdj5MnT67r379/w5QpU/r+9NNPyrS0NPH+/fvlr7zyindzfcS33nqrJDExUTZr1iz/P/74Q5qU\nlCRZv369w6xZs246L7M9Vp0MMsbeYIydYYzVMcbKGWO/MsYiLB2XLWhJCCNNCWFJdvu7lNjf7w9p\njBt4rQGV36agV0gs/COioG5swPGf/9fSrkClQpbRFRJejUGFWWDBY9s83+3WCmxO8ALDB2L4lUsA\ngCOcLxL+byhyl00AAOQum4DcZRNouJgQArGxCV5emXDsk4uaukRLh0Os0Lx586rfe++9guXLl3vd\nc889YadPn1Zs3rw5Mzg4uM1eNwcHB+PmzZuzcnJyJEOGDAlbvHix73vvvddqODgwMFB3+PDhNI7j\n+ClTpgTFxsZGLFq0KEAsFhulUikPAEuXLi2ZOnVq5QsvvBA4bNiwUAAYM2ZMzc16EptxHIf9+/dn\nDh06tP6ll14KjIyMjHj88cf7ZGZm2vn5+ekAYPDgwaq9e/emFxQUSMaOHdtv4MCBYUuWLPFxd3fv\n8JJ6a/86FQ/gUwBnYFrq8C6A/YyxMJ7nqywZmC0QiDiMnx+J3KQK9Onv3m57xhicpwWjvEoNbX49\nKr9PxYjZz+KHNxfh4r5diB49Hq5+AdhSkAJAgAhDIqIdXTq8gvh6zXMCBQIBnombgoTiRPQWZiI3\n5zRcQl/tlGsQQnoOH3vgX31fhJqT4nBdJhyVkZYOiVihxYsXly9evLjNnsC2jBo1qjElJaXV3MVZ\ns2a1mh8ZGRmp2bNnz+WbnUMkEmHdunUF69atK2i+LywsLHTgwIEtOzqcPn26zf0TnZycjF9//XUB\ngIK2HgeA4cOHNx09erTTdmew6p5BnufH8jz/Nc/zSTzPJwJ4AoAbgKEWDs1mCERcq0SwuqQRxVk1\nN23PRBxcngyDwEkCoZMEbn4BiBo9HrzRiEPffQme5/FriWkecGhNFvxjR7c6fsW+jE4Z1u0XEY3R\niccxtvoAKi+WAQAW3h90W+cghPRsjfUVUHNSiHgNnMRtVgohxCIyMjLEH330kevFixclZ8+etXvm\nmWf80tPTZXPnzq20dGxtsfaewevZw5TAVrfXkNyooVqDbSvOQ6PSY+IL0fAJaXvrJoFCDPe/xIBT\niMA4hiGPzMLFQweRd+k8zp4+iSS9GwTQY0hRCriJi1sda1oEYhrCDVy8s2V492ZW7MtoNZzcnEQC\ngAuLx6R6D3C8Aelbj+KVKcNajqFhYkLI5YoKAG5wQC3E4hvq+RJiMRzH8evXr3dZunSpr9FoZH36\n9FH9/PPPmcOHD29q/+juZ2vJ4CoAFwCcaOtBxth8APMBwM3NDYcOHeq+yGwAb+QhdOLRWAts++Q8\n/IcxQNHY7vPE9ECRw0j41u7HT/kp4F3j0M+QhGA9j0OnLt7y2PbO3V8EfDPOtFDr6T2NLbdNPwOe\nznLss/NAMadCv98PQcSAVQca0V9UZNbv3NnoNdW+hoYGep7MQM+T+W72XB1IKQJCQ+GAGpw/XwHG\nzNtTnZCu1rdvX11CQkKbw8DWyGaSQcbYxwDuA3Afz/OGttrwPL8GwBoACFcq+eiSUjg9NqMbo7R+\nfDyPQz+mIeWPYlw5xuAzRI74ifE3bW/UGFC+5hJ85RFw/ctkvFdwHpH6JETUpSJ8+FSwgTc/dqEu\nA/Hxt9GDt2cn4uPjW/08bebT+PLseVyxc0eBZzHmhI6/sV03OXz4sEWua2sOHTpEz5MZ6Hky382e\nq61ZaQAAB9Rg6NCpEItduzkyQnoGq54z2IwxtgLATACjeJ6/6YTNVsdodWg6c6blZ16vB6/tUC3G\nHoVxDPGz+yFihA8MeiPyj/LISihrs+2KfRnovWQPNhZWQcIY8r/PwrFDHN7LO4f3Er8Bu0lJmWa3\nO5R7/ZzAhfcHwc3NDU86FwMA1l2pR+DiHQCoxAwhBKjiTLWEHVELkYiGiQnpKKtPBhljqwDMgikR\nTDP3OIObK5yffrrl54ZDh5A5Ih4l7/8TquRks6qM91SMYxj+WDBiRpvqCv72VTJqSm+cxvDK6GDk\nLpuAl94fhVPQwwkcPuBlEGclY295LHiZSxtn77hrk8dr5wU+FT0dUr4JWcJgbFzoDYBKzBBCgNqr\n21W6CBkYs/qPM0KsllX/9TDGVgN4BqZewWrGmOfVf7feXw2AUSaDNPLPkoSNJ0/BUF2N6u+/R+60\n6ciZPAWV676Gvtzs1eY9CmMMQ6b2gVuE6b+OHm3uCw4AWHkwE++gCV8EX8HlgCJo1Y8ir4LDitU/\ndFl81y4qcbCTY6TR9D3gs9Tb2qecENJDaTQaBF0pxORLR7Ew7kVLh0OITbPqZBDAAphWEB8AUHzN\nv/93uyfyeOtNBG7aBKfHH4fA0RGajAyU/fvfyIwfiZJ/vN+5UdsIxhjcIxhiHvBvuU/VcONQ+iuj\ng/HM/X3xY2AA3ggNQ0bfSsQ4j4Lk/C401bVfzLozcDmm/x5CBGR2jS3DxDO+aHMtESGkh2tsbIRC\nq0a/xjL0ldtZOhxCbJpVLyDheb79XZ7NxBiDNCIc0ohwePz1ddQfPozaLVvRcOQIhO5/1uHTlZVB\nX1oKu4gIszaZ7klqSpvwy/JzCBvqhcEP9W71+4eFcWjKkMGXz0dkcR/ARQdNZiOO/LAO4xa80inX\nv1mZmYX3B+HTpx5H6qHtyBb1xT398rDhsdc75ZqEENvU2NAAwAi5WGDpUAixeVadDHYVJhZDOXo0\nlKNHQ19ZCSb882mo+flnVPznvxD37QPHKVOgnPQQRB7t797RE1RcaYC6QYeE3XnQqg0Y9kgQGGdK\nCHfmJQMIRERjCsKHOqEhZgK4v25E8uEDCB9xP/zCo+74+u3VKJzOV6OR/xhRikvg+f931yXrhJA/\nuSklKI8RokhpxH25XyMs8BlLh0R6MJlM1n/ZsmX5L7/8slUWjb5T1j5M3OWELi4QODi0/MzZ2UHg\n7AxtVjbKPlqOrJEjkT9vPup27YJRo7FgpF2vb5w7xs2LACdkSPz9CvZ/mwKDwQgASFebFtyE1uZC\nfO9YOHv7YvCURyFkYvzx5Xcw6Du8JaLZnh40DR7ZKqRcuh/1pbldfj1CiPWS6Grxq3IstrMpEHBi\nS4dDrNTu3bsVo0aN6uvu7h7FGIv75JNPOnflYw9x1yeD13OZOxdBhw/B99PVsB89GhAI0Hj0KApf\nfQ0l77xj6fC6XO/+bpj4QjSEEgEyTpViz+eJ0GsNyIfp7ydWUw04BZpuj3wIY/2fQZzkATSUdO6X\npba2nnNycobSbjzUWnsc3/3jLY+nkjOE9GwNDRXQMgkkvBpOdlRfkLStrq5OEBYWpvrggw8K7Ozs\njJaO51bUarXFhrsoGWwDE4lgP2oUfP/zCYKOHIbHW2/BLjwcygcfbGnTePo0Kr5YA11JiQUj7Rp+\noc6YvCgGErkQuYmV+OHz06hjSsj4Rgz0/3M4WGRvB6WXJ6SQQ/NrKXh95/2d3axkzKBho3A4KBrP\n+4xGcV3pTY+/du4hIaTnOZKWC8BUcFosoWSQtG3GjBm1//3vfwufeeaZanOnFiUlJUkGDRoUIpFI\nYgMDAyPWr1/vcH2bnJwc0cSJE3srlcoYpVIZEx8f3zcxMVFybZs33njD08XFJVomk/V/+OGHA197\n7TUvHx+fyObHp02bFjhy5Mi+b731lqeHh0eUt7d3FGBKCv/yl7/4eHh4REml0v4RERGhmzdvbrX5\ndkJCgl18fHxfuVze39nZOXrSpEm98vPzOzz1j5LBdgidnOD8xOPotXkT5MOHt9xf/eP/UL5iBbJG\njkL+nLmo/fVXGFUqC0bauTx7OeDh12Ihd5RAHKKBu7EEvsYCOEZMbGnDiQXwmBsFgYMY2rw6VG3K\ngNHQ5uYwnSYwIAD2XjKoRRJ8dn59l16LEGK9LpXXAzAlgxLx3TGvm3Q9g8GAqVOn9jEajTh48GDq\nmjVrct5//31vrVbbkknW19dzI0eODJFIJMZ9+/alHz58OM3Dw0M3duzY4Pr6eg4A1qxZ4/Txxx97\nv/XWW4UnT55M6devn3rNmjUe11/v9OnT9omJidIdO3Zk7NmzJwMAHn300cDjx4/bf/PNN5cTEhKS\nZ82aVfHYY4/1PXHihBQA8vLyRA888EBIaGio6ujRo6m7d+/OaGxsFEyYMCHI0MHP4LtyAUlHXfut\nwnH6dIAxNBw4gMbjx9F4/Dg4uRz248fBacZjrWoc2ioXbwVmLhkMiVSIR/a8jfKEDeBHJOPa71YC\npQQuT4Wj7LMLUF0oR2n5ZYS99OBNz3mnGGOYH+SF01lGbDGE4u/aeojF9gBuvRqZilMT0rOU603v\nRA6ooW3oLCS1X2jczR5zf/31PJe5cyoAoPKrda5lH34YcLO2oWl/FpDNnjAxVJud3Wbh22vbdZVt\n27Yps7OzpWlpaYlBQUFaAFi+fHnBuHHjQprbfPXVV048z+Pnn3/O5ThTn9qPP/6Y5+rqGrNx40aH\nZ599tvrTTz/1mDZtWsWrr75aAQBRUVElR44csc/NzW1VB0ksFhs3btyYK5VKeQBITk6W7Nixwzk9\nPb3l+mFhYeUHDx5Url692u3ee+/NX7FihVu/fv1Un332WWHzeTZu3Jjj7u4ec+TIEdnIkSNv3EWi\nHZQMdpBi2H1QDLsPhpoa1O3ejZotW6G+dAm1mzZD7OPTkgzyPG/Tq14lUtNLRFR6EXaKKGxcdh6j\n54TDxefPut9ibwUMQ+zADjVCWWiP0gPJ8Lg/vMtietA3Ep5ZB1DCPLDhzDd4cuhLANpfjUwI6Tmq\nrn4IO7JGCARSC0dDbNHixYs9P/nkE6/mny9evJicnJxs5+7urm1OxAAgPj6+sTnpA4CEhAR5YWGh\nRKFQ9L/2fGq1msvOzpYAwOXLl+2efvrpVrtaDBgwoPH6ZDA4OFjVnAgCwKlTp2Q8zyM6OrrVh6hW\nq2X33HNPPQBcuHBBdubMGYVMJmt1fQDIyMiwo2TQAgSOjnCaORNOM2dCk52N2q3b4PDQQy2PV679\nEo1//AGHh6dAOWYMONnNd/qwVtWaJjiVXEKC5v9QWdSIXz46hwkLouAd5NjSJmD8AJxN2gDPSh9c\n3ncKbvH9wAm6pv4Xxxgm2DXgK7Ur1jcp8GSXXIUQYs14rQEe6jKEelKvv6WY21PnMndORXMvYXv6\n7NyRemdRme+VV14pf/zxx6ubfw4MDNSas1Wt0WhEv379mjZs2HD5+sfc3Nz0zbfN6QiSyWStJtsb\nDAYwxnDs2LFUsVjcKhi5XG68en0WHx9fu3LlyivXn8/Hx6dDpT0oGexEkj594P7aq63uq9u1C5q0\nNDSdOoWSd9+DcuxYOEyZAtnAAWCc9U/ZVOl1iPgjBQ4DvsQxYQb0aW64fL4c21ddwJhnw9E7xq2l\nbcSCSdi5+H3kll0C96s9Bk95pMvierL3QHydXIJLgkhk5hxBUK/hrR5vazUyIaRn0Ov16FVUjN5F\nRXjjnSWWDofYKA8PD4OHh0erSXYRERHqsrIycVZWlqhv3746ADh8+LDMaPwzZ4uNjW3avn27s6en\np97V1bXNSXq9e/dWnz59Wg6gpdRGQkKCvL2YBg8e3MTzPAoLC0WTJk2qb6tNdHR00/bt252CgoK0\nEomk/ezVDNafjdi4gO++hee7SyHt3x98UxNqt2xB/lNPIXv0GNTt3m3p8Np1oiAZBiaEGFo49RqA\nsfMiED7cBwa9EXu+SETSkZYpC7CTyxH37HTTcT//iIqsHBhV+pud+o6EePggXJ8NAxPi59R9NzxO\ncwQJ6bmamkyjYDKBAZwNfKkmllNbW8sdP35cevz4cSnP88jPzxcfP35cmpmZ2WZxysmTJ9f16tVL\nPXv27F7Hjx+X7t+/X/7aa6/5CwSClqRr/vz5VS4uLvrx48f33blzpyItLU28e/duxbx583ybVxQv\nWLCgdPPmza4rV650SUxMlPz973/3uHjxYrvJYFRUlOahhx6qeu655wK//vprp5SUFPGRI0dk77zz\njse3337rCACvvfZaWX19vWDSpEm9Dx48KE9JSRFv3brVfubMmQHV1dUd+oOgv6IuJlAq4fToowhc\n/z/03r0LLs8/B6GXF3SFhWDiP1+LupISGBoaLRhp206XZAMA/HSFYJ4R4DiGETODMWhSL/A8cPh/\n6Ti7K6elfWB0LCJHjYEUClR9mYaKH1LAG7qmtNPzzhJ8yL+MKN0u8F28ipnYNqo72bPo9Xp4O+ai\nl38WGhrSLR0OsWJHjx6VDx06NGzo0KFharWaW758uffQoUPDFi9e7N1We4FAgF9++SXr6lBs6Ny5\nc3stXry46NohW3t7e+PRo0fTAgICNE888USfqKioiGeffbZXTU2NsLmncP78+dWLFi0qevfdd30H\nDx4clpycLH3iiSfKJRJJux+IP/30U+5jjz1W+fbbb/tGR0dHTJ06NejYsWP2vXv31gJAYGCg7vDh\nw2kcx/FTpkwJio2NjVi0aFGAWCw2Xjv/8HbQMHE3kvTqBfdFi+D28stoOnUKsrg/F2KV/ftD1P/+\nO5RjRpuGkQcPtoph5LSmJoADeqlLALFpviNjDAMn9ILUXowjGzIgd2y9SfyIJ+aiLCkbYqEdtNm1\nqN6SBadpQZ2+kOah6Afx5Rd7kF3hhv6eO+AzeHKnnp/0HKsOZFJvcQ/irFRgdfgsVAqcsLn0OAYr\nQto/iNyVJk6cWM/z/G2tQo6KitKcOXOm1beM2bNnn7/2Zz8/P/2mTZtyb3WeZcuWlSxbtqylGPHo\n0aP7BAYGtmxltnnz5jaPl0gk/Mcff1z08ccfF93s3JGRkZo9e/bcMGexoygZtADGcZDfe2/LzzzP\nw1BbC16lQu227ajdth1Cby84PPQQHKdMgTgw0GKx5vKmVXph/I29lhHDfeAb4gRHj9aLYiQyOWZ8\n9AH4Mh3K11xC09lSCF2kUI7069TYRCIRevWZiNKKMzh85iRmUTJIyF2Bb6xAlcAReiaCm51j+wcQ\n0s3q6+u5jz76yG3SpEm1IpGIX79+vdOBAwccv/nmm2xLx9YWSgatAGMM/l99CW1BAWq3bkPt1q3Q\nFRai8vMvUPn5F/BcuhROMx7t9riMRiOucKYamfc6OLXZ5tpEsOJKPY79nIUxc8MhU9oBfnZwnhGC\nyh9SUbc3F0JnCWTRnVscNjA6Fq/p5NBKRJhanQu7q1vlEUJ1J3uuyupS6JgYdnwTHKRu7R9ASDdj\njPH79u1zWLVqlZdGo2H+/v6a1atX5zz55JM1lo6tLZQMWhGxnx/cXnoRri8sQNOZs6jdsgX1v/0G\n+ZA/exHrf/8dTCiCfMi9YF1UuqVZcnE2Gpg95HwD0iq8EX2LtjzP48iGDBRn1WLzv89i4ovRcPKU\no0wdnT0AACAASURBVFJYiuSmEwiX3YuqnzMgcJBAEnjDzj4dFuLlCU6ejnpOjm2XfsCMEX/vtHMT\n20Z1J3uuHWeTAJdIOKAWEnFvS4dDyA0UCgV//Phxm5msbPlJaeQGjOMgHzwI3sv+haATxyH2Mw2v\n8jyPsuXLUTBvHrJGjkLZ8uXQZHddj7OH3BHv1P2KZ4v/h/fPSW7ZljGGcfMj4R5gj7oKNTZ/mIDi\nrBrYyRVIqzqJrLpzgJ6HJru2U2NkjEFRZlrRvEnrDJhRI4oQYttKNKYqBY6ohlhMPYOE3ClKBq0c\nJ7kmCdPr4TBhAkT+/tCXlaFy7Ze4PGEich6dger162Go7dxEy93RDQs0WXij/Bjq0O6KeMiUYkx5\nNRaBkS7QNOqxbeUF1JRJMfyJOThXuR8na3YA0Z2/U0B5pgKMN+KkYACyLtB+xeRGVHeyZ6kwmJJB\nJeogEtGcQULuFCWDNoSJRHD9y1/QZ+8eBPz4AxwfmQ5OLof60iWULH0XjadOder1VuzLQE7SCeyq\nNM0bDFy8E4GLd96yTIdIIsD45yNbahHuXZsEHpHoFTsAedXJ2L16OYxGAwz1WvC6jpeDWbEvoyUe\nfZMQAZpc6JgYn+d0W/F6YkNojmDPUsWZKhM4c2owRh9jhNwpmjNogxhjkMXFQRYXB48330T9/gOo\n/20vFPHxLW1Kl30AcBwcpkyGXfDtfxDyPI+LglMojJyON1wdgL0we84VJ+AwYmYwHFylOLElC0pX\nKcY+vxDfvv4irqQk4fyGbfDO94XYzx7OM/uBcbdfcub6+WCzPBzwz1rghEMk9PWlENp73PY5CSG2\nwbOkEiPrE/DUpOmWDoWQHoG+Utk4TiqFw6SJ8P3Pf8BdLWJtaGhE9caNqFq3DjkPTUbO1Gmo+v4H\n6Kur2znbn4oqirEXYfifyzRIPMNuOy7GGPqP8ces/7sHfePcIXNwxPgFrwAALuzdBUOTDqrECtRe\nU7D6TsyJHAE7XoUi5oPjh1d0yjkJIdbHaDTCrqEJIaUFGO7paelwCOkRKBnsgTi5DAFfr4PjYzPA\n2dtDnZKC0vf/P3vnHRbVlTbw353KwNC7oHRERYq9RAVL1ESsiTGxRNeS1Wyixt2NxlQ32bhfEo1m\n1axpphglsZeosYuxoKiIKL0I2EB6H2bu9wdCUFFQUUTu73l4nLnn3HPeM9658973vOUj4nv3If21\n1ylLSKhzjMMXzyAKchwMl9E6d7lvn6uaqWc05l6YOQTTbfIUbCa0A7lA4eEMCg5n3GWEupnZzwut\nUsF82UGWiVPIzTp9UyCJVH1CQuLJobS0FAMCapkehULa3JKQaAgkZfAJRBAENAEBOL7/Pl6Hw3Ba\n9BkmvXuBXk/B7t0INW6gwo0an7cSlXsVABddBpjaN4jP1bHNiZSXBXJ8q44cQcDyucox87YnUXIu\n677HrZJtlN+LnD0xhDMpXSiMO1TdXjPXnISERNNGoVAgti8iv1sRF9LWN7Y4Es0EY2PjwKVLl1o3\nthwPC0kZfMKRqdWYPfMMrVauxHP/fhwXfnxTRRPLzxaRNGIk2d9/T8X169XHkyoqgzu8K+5fSbuV\nwa+0p1VbK0oKdGxafIozCdEUuBSDCNfXxlKWmv9A41tZueDS0o8ymYoDh3c3kNQSEhKPEyqlkg3m\nT/OdcgIFD6nuucSTwbx58xx8fX3baLXaQEtLS/++fft6njhxwqjuM5sfkjLYjFDa22ExfHj1e921\na8hzcii7cIGrHy8kvk8QaTNeJW/XLtJklYmhA1UNN79Ko+DZV/1oH+SMvjyPY+sW89uB/6J3V0CF\ngfIHVAYBCtt14Ifug1hl5kqbueurq07UJxJaQkLi8UcsKyBHVplOxlHTcAnsJZ48wsLCTKdOnXpt\n//79F3bt2hUnl8vFwYMHt7569erDrdhwn5SWlt57NGUDISmDzRilnR2Z/1mI05IllZHIokjhvn3E\nvjWPDHkLAHrYezTonDK5jN5jvAka1xmFphsgsunQ5xiPcsa0t/MDj9/HwwWdQslJ63b88dzV6gjo\nlIXPkrLwWSnFiIREE+dcXDQVghKNWISZUcOWt5R4sjh8+HD8zJkzr3fu3Lm0S5cuJevWrUvOyclR\n7N27V3u3886dO6fu0qVLa7Va3cHV1dV3zZo1tz11JCcnK4cMGeJuZmYWYGZmFhAUFOQZFRV1U3WG\nefPmOVhbW/sbGxsHjhgxwnXOnDmOTk5O7avaR40a5RocHOw5f/58B3t7e78WLVr4QaVSOH36dCd7\ne3s/jUYT6Ovr22b9+vVmNceOiIgwCgoK8jQxMQm0srLyDwkJcbt48eJ9O9FKymBzR6nEbODTtPxy\nBV4HD2D35puU+LemdVksbvpEWrbqCkBhWBgVmZkNNq1vbydG/nMaCrUbFboidmz6ggqdDoCK3FIM\npRX3Na63qRYfRSalgoZfL59vMHklJCQeD04lpwFgQa5UfUTinsjNzZUbDAasra3vmORWr9czcuRI\nD4PBwL59+y6sXLky+aOPPmpRXl5ebbUrKCiQBQcHt1ar1Ybdu3fHHjx4MMbe3l43cOBA74KCAhnA\nypUrLRctWtRi/vz5GceOHTvv4+NTunLlyttynoWHh5tGRUVptm3bFrdz5844gNGjR7seOXLEdNWq\nVUkRERHRL730UtaYMWM8jx49qgFITU1V9u/fv3WbNm1KwsLCLuzYsSOuqKhI/uyzz3rp9feXv1cK\nxZKoRmFjg/WkifSe+DI9Vk+nKH4zQr9LGIqKSJ85C7GsDO1TT2E+Yjja4OCbq6PcBy3b2jDxsw8I\nfX8OVxLiOPjj13Tp8yIFobEobTTY/MUXQXHvzysj7bT8+xJsMurAX67F3xYJvXh3nGQhlJBoolwt\nLQUzMCMPlcqmscVp1iz7676Od2rrMcozNXBAqyyA07sv2hxZn+Byp76vftk3our1zx8ca5Nzudi4\nrn73w/Tp01v6+PiU9OvXr/BOfTZv3myWmJioiYmJifLy8ioH+Oyzz9IGDRrUuqrPN998YymKIr/+\n+muKTFb5G7V69epUGxubgNDQUPMpU6bkLF++3H7UqFFZb7zxRhaAn5/flUOHDpmmpKTc5LOoUqkM\noaGhKRqNRgSIjo5Wb9u2zSo2NrZ6/rZt22bu27fPbNmyZbbdu3e/uHjxYlsfH5+SFStWVKfiCA0N\nTbazsws4dOiQcXBwcO2RoXdBsgxK3IYgCChL4jhvcAVBQJ+Xh0mP7iAIFB48SMas2cT37sPlDz6g\n5OxZxAeoB2xua8XQ2fOQKxSc2bWdX//vFyrK9JQl5ZEdGotouPexX3QJRC5WECn3548/vrpN8ZOi\niyUkmi5Z+jIALChALn+wB1KJ5sOUKVOcT548qV2/fn1CVUqiuXPnOhgbGwdW/cXHx6uio6ON7Ozs\nyqsUMYCgoKCiKqUPICIiwiQjI0Ot1WqrzzUzMwvMz8+XJyYmqgGSkpKMunTpUlRThk6dOt30HsDb\n27ukShEEOH78uLEoivj7+7erKduBAwfMU1JS1ABnzpwxPnHihLZmu4uLix9AXFzcfQXISJZBiZtY\n9Hss684eJbQshWixKy/dCMCYOex1XluwgPxt28jdtImy8xfIXbOW3DVrcd/xG2o3t/ue08HTm+CJ\nr3Dgx1UUVag5mFlKbwsVJVFZ5GoTsRjqgSDU7ldbm5XP1sgIfyGDU7iwSVATZDCATHrukZB4EijW\niRjri3DQPLFZPpoM9bXUBQ5olVVlJayLl97r1uA1RSdPntxyy5Ytlr///ntc27Ztq5W82bNnZ44b\nN666GoOrq2t5fYwbBoMBHx+f4rVr1ybd2mZra1vt43Sn362aGBsb3xQSr9frEQSBw4cPX1CpVDcJ\nY2JiYrgxvxAUFJT3+eefp986npOTk67OSWtBUgYlbmJKN0e+l9vTWbaBYREbSfn7zSXorCZMwGrC\nBEpjY8nbuInylJSbFMErH36EJjAA0379kBnV/wHFf8BgvLr24OL5Yg78FMvRfB09tAqKjl5GbqrC\nrG+rWs9bsje+1i3fF5ycOJUBF7W2FJzfxdeXPW6yCFZFGc/s5yVtGUtINCE8L6UzIfkSf/vb3xpb\nFIkmwKRJk1pu2bLFavfu3bGBgYGlNdvs7e319vb2NznZ+fr6ll67dk2VkJCg9PT01AEcPHjQ2GD4\nU2fr0KFD8ZYtW6wcHBwqbGxsanXSc3d3Lw0PDzcBqnO2RUREmNQlb9euXYtFUSQjI0MZEhJSUFsf\nf3//4i1btlh6eXmVq9Xq+9+aq4GkDErcRNzFaK4J9sjFCuKzW9yxn1Hr1hjNffOmY6WxceT89BM5\nP/2EzNQUs8GDMR8xHE1AQP2ekMzM8elmjpWjCZsXb+VkoR2dtUbk/56KXKvCpEv9S0897x5IRcpz\ntDDEcu5EN2ZP+vamWsb1rbMsISHxeFF0w+6h1d41IFRCgvHjx7fauHGj9c8//5xgY2NTURVta25u\nbjA3N681SeWwYcPy3dzcSseOHeu2ePHitOLiYtmcOXNayeXyaqVr2rRp2V988YXD4MGDPd9///0M\nDw+P8uTkZNWGDRssXn/99cz27duXzZgx4+rrr7/u1rlz56J+/foVhoaGWkRGRpqYmZndNcLDz8+v\nbOjQodmvvPKKa1ZWVnrXrl2LsrKyFHv27DH18PAoe/nll3PnzJlzbfXq1TYhISHuc+fOveLg4KCL\ni4tTh4aGWi1fvjzN0tLynhNwSntnEjdxKjMOUZDRwnCJoUG97+lcpaMD9u+8jZGvL4aCAnJ/+YXU\nF18iadBgsr78En3hHX12b+Ja0nHyr6zlqm4nZ4srLe4VNaKLF++Oq84bCLXnEDRWyOlk/zfCjz/H\n2VQjKMm9p7VISEg8fuh0OsxNsrC1uogoXq/7BIlmzU8//WRbVFQkGzZsmLeLi4t/1d8HH3xwR8uC\nXC5nw4YNCTe2YttMnjzZbe7cuZdqbtmampoawsLCYlxcXMrGjx/v4efn5ztlyhS33NxcRZWlcNq0\naTmzZs26tGDBAueuXbu2jY6O1owfPz5TrVbXqaj98ssvKWPGjLn+zjvvOPv7+/uOHDnS6/Dhw6bu\n7u7lAK6urrqDBw/GyGQycfjw4V4dOnTwnTVrlotKpTLU9D+8FyTLoMRNxJcVghrcdJeZNXjoPZ0r\nNzPDauxYrMaOpSw+ntyNm8jbuoXy1FSuf/U1Vi+/XN1X1OsR5LXn/XTyaYuRsQnFubHkeLbA8MwY\nzHs6VbfPHuBdLytf27a9+W37Uc7L3blybC0OwX8FuO86yxISEo2LUqlkc/s+XFFY0C5jH0Ge4xtb\nJInHGFEU7yv62M/Pr+zEiROxNY+NHTv2dM33LVu2rFi3bl3K3cZZuHDhlYULF16pej9gwAAPV1fX\nsqr369evr/V8tVotLlq06NKiRYsu3Wns9u3bl+3cufM2n8X7RbIMStxEBpUKmgf1s+LdCbWXF/b/\n/Ade+/fTcuX/sPvnP5FpNAAYSkpI6NefS2+/TfHJk7dFI1s6OhHyxjxkcjlXE/ZTUBFT3ZawL43c\n6PpZBJRKJQc69SW0S38Op0VWH5d8BCUkmi4ZclsyBXss1JaNLYqExB0pKCiQvffee/YnT540ioyM\nVM+dO9dh7969FhMnTmy4Gq8NiKQMStxEtlCpsHncUNweFEGhQNu7N5YvjK4+VnziBBVXrpC3bj2p\n48aTOHAQmcuWUZ5enTKJVr7+9J1Uacn7/X9fkH7hHOknryLsTCbnh/OkH7sM1G3l6+BQqdxut2sF\nmbF37SshcS9IpQ0fPYYKHblCZTEIB42kDEo8vgiCIO7evdu8f//+Pt26dWu7ceNGq2XLliVPmDDh\nsfRZkpRBiWoW7TxPjryy4o23zR3zgz4w2t69cf/tN6ynTUNhb4/u4kWyvvgvif37kzrhZfSFlamY\n/AcMJnBwCAZ9BZs++Rdo8ijWKFAKULohnrNbEpnV/+7K4FiXynJ6h1RPkXf6q4e2JonHHH0FlOZB\nwRXIToKr0ZB+Eoqz73tIKV/lo+fQiWMYBDkmYgFaI6n6iMTji1arFY8cORKXm5t7pqSk5HRsbOz5\n6dOn3/8N5yEj+QxKVPPfA4l83zuGpEtrOFPyOr19H95canc37N6Yje3M1yk6eoy8TZso2L0bfWEB\ncu2f0fddA7pSkJXJpbgYVCYK2s7rQvKiCIzyy9GHZbA3vZDek9qh0tR+Kfua2+AujyRJb813OXnM\n0leAXLrsmwV56XDqBzj1IxTc7HpTgYwijNEIelTewdD+eWg9GJQNYxGXeDik5WaDkSnm5KFWt6/7\nBAkJiXoh/SpKVGNARi8hl17X/sA1YQKvP/PwS7cJcjnap3qifaon+oICKq5U+9pSlpjIxTEv4tOi\nBX6DnsZCpkBupMB9TkfSl5zGJLsUp+Q8Nn4UzoAZ/li1qD2F0xALOUuvwy6rbrwS/Rsav3sLjJFo\nQhj0kLAXTn4L8btAFCn26U2Zw0AuZBtIzCmhTF+BTq9DJtOTn+uAQ0IxXrFL6ap8HaHd0ErF0K03\nyG4PcFq8O07KV9mIXC0pBCMwJxeFwryxxZGQeGKQlMFmzsb4cibu3F79fveRcJwFS6AyL+Cdkjo/\nDOSmpshNTavf665cQdHCkYpLlyj9dhWJ365C07EjeV074PniS+SFpmOaVYKfTo9Ceec8hhO9uvBF\nVgxRcj/+OP0l/SVl8MnDoIdjK+D4l5CXRr7GhWNOM3HoZM2m7JNkGRSUWRhRZmFHKWrK0FCGCrvk\nUorSsim28qKDayzK6K1wZjVX7YJwGLsMzJ1vmqa+kewSD4dMfQkAFhTXK3ephIRE/ZCUwWbOCC8V\nS6Y+Xfl6+RKWuo6lzfUEiP7T6vGwrYN3QtuzJ5579lAcHk7exk3k//47sclxnKvIJXLPLl749hdy\nfojHsq01ZraVdc1Fg4i+woBC9adVp4XGmPayy8QZrDhhJNC/8Bpo7R75eiQeEnkZsGEaYuphLrr1\nIKpFf07FWmFIN+Bmb8sK7UzEO7hHLx7gQNucqygUCrYUJpBn1Y9OOj07jtvS+YvX6fP8dBStBzzi\nBUncCcvrRXQtjOIZvzaNLYqExBOFpAxKVKO1LmO3pg9G1jfnxFyyN54le+MbZStMkMkw6dYNk27d\nsH/nHTTrfiF+xwYyNUr2rvmKQX+bBaKezKVLMRsSwrk4gbjwqwya5oulw5/bxp9425ERM4F80ZGs\noz9jM2DWI12HxEMi5jfYPINrShl/dAkk3MiNSEM7OhvSaNfWl54dejKjREREhlYhw1gmw+TGv0qZ\njL5WpmhbOVBRUcBHh/3YJ/bAUrxOv067MYkzJX7NRkZ2Pond4Ddvq28t5at89GjzcggsyWHooP6N\nLYqExBOFpAxKVKPTqABwV4mcAFIWPvtYbYXJtSa4TJzEc72e4pcF87hw+ABqExM6ObiQtXwFWT9t\ng57/IK9Ezi8fnaD3i63x6e6AIAj4OXYi5cQ/iYlJxUYTQf/+IkjbTE0XXSnsfgcxfCVR3m3YYN+G\nH4QpFAsmIIfpE/oS4l4ZSa6th2VboTClk8sIYjIuc0lnzTr5GLx8YnjeeiNfR5jRN/mvdJn0MTIT\n6+pzJB/BR09RuQGQYVLDnURCQuLBkVLLSAAgiiKFqkpLmpuJ8WNt9XDw8GLYnLeRKxSc2bWd8Jiz\nmA4fgXGnSdirjeilLMKgM7Dvhwvs/M8Bykp0CIJAQEBfKmQy9gpeGC6eaOxlSNwvmXHwdX/KznxF\n2FOdec9hHF/KZlIsmNDRRMmKti4McHGr7l7fFDBvuDkS0TOQNX7u2Cl0xAs+LLZ9naKOBezMcuTH\nRW+TF3f0Ya1Koh6o2hSi7pTOpfywxhZFohlhbGwcuHTpUuu6ezZdmoQyKAjCDEEQkgVBKBUEIUIQ\nhF6NLdOTwsb4clznbqftvM3k3ojO23yyoLr9cVUKXfwCGPr3+cgVCs4eP8zFju1wnDcQQWnA3MSC\nvlxDoS8jKUXk149PknmxAJ2NPT/2eIbNfr3IP7WqsZcgcT+knYCv+1GRf5mfeo7mr7K5HBWewkgw\n8IlXC7Z1bssIe0uM5Pd3axMEgWBrMw50C+RpCxklggmrjCdTbm5Bht6K7PVzICelYdckUW/WWfRh\nicnfuFhS0tiiSDQBPv74Y1tvb++2Wq02UKvVBgYEBPisXbtWCkOvhTrvmIIg+DwKQe4y/wvAEuDf\nQCBwBNghCEKrxpTrSWGEl4qUhc+yc3og2TIrAP770rDqLbDHeSvMPbAzIW+8hZmtHa179EbV0gq7\nv3VCplViYuHEYEcBK62evGslHNmQgHPmFcz0eWSrLdmfnwLlRY29BIl7If0k/DSSHHVLvjadRbzi\nObIFGwK1SvZ3acd4Z7vqCNPFu+Nwnbu9Ogiq6nV9q4ZYKRV8H9Ce/3g58K6HM29NncrkMcNwVKcj\n/jy6MoG1xCMnu7r6iEUjSyLRFGjZsqXuww8/TD927Nj5I0eOnO/Vq1fBuHHjPI4fP/7YJRQtLS1t\nVL+l+jw+nxYEYYkgCI1V++cNYJUoil+JonhBFMXXgMvA9EaS54kkMzuFHCwRRAMtLR0bW5x649Gx\nC5MW/w9rp5YAKO1NsJ3aHplWiazchH5edgQEO9F3QhsKtm6j74UDAIRa9Cd96ngK9u9HrKhoxBVI\n1Iv0kxh+GkGcjSMry0O4cu06zpEJfOrtzJaObXEzVt/UffYAb1IWPlvt71r1+l4ebgRB4GVnB15p\nZYdWq0Vpr2d1YAA7LI1I+eFvlJcUN+gSJe7O9ZwccoXKCkkOJlaNLI1EU2DcuHG5o0ePzvf19S3z\n8/Mr++KLLzJMTEwMhw4dqj0pLXDu3Dl1ly5dWqvV6g6urq6+a9asuc2SmJycrBwyZIi7mZlZgJmZ\nWUBQUJBnVFTUTTehefPmOVhbW/sbGxsHjhgxwnXOnDmOTk5O1ZnSR40a5RocHOw5f/58B3t7e78W\nLVr4QaVSOH36dCd7e3s/jUYT6Ovr22b9+vVmNceOiIgwCgoK8jQxMQm0srLyDwkJcbt48eIDxYDU\nRxnsArQD4gVBeE0QhNszsT4kBEFQAR2B329p+h3o8ajkaA6UoSdAdxa/ivOoZE3Ce6AahVJZ/frU\njq0c2/srNlPbIzNVUp6cT4f2NphaGWE9dQoTPLsAcMy0O5EluaRPn0F8UDCZS5c2lvgSdXFDEdzh\n48IMjxmI1hfx9PRk8qRJjHOyQSl7+A/Ui3fHca6wggW8xSyHBayRa/n1y3+j1+sf+twSlUQlxCMK\nMrRiPlq1lBpK4t6oqKhg5cqVlsXFxbI+ffrUui2k1+sZOXKkh8FgYN++fRdWrlyZ/NFHH7UoLy+v\nvskUFBTIgoODW6vVasPu3btjDx48GGNvb68bOHCgd0FBgQxg5cqVlosWLWoxf/78jGPHjp338fEp\nXblypf2t84WHh5tGRUVptm3bFrdz5844gNGjR7seOXLEdNWqVUkRERHRL730UtaYMWM8jx49qgFI\nTU1V9u/fv3WbNm1KwsLCLuzYsSOuqKhI/uyzz3o9yP2oTk1SFMUooL8gCMOBT4DpgiDMEUVxx33P\nWn9sADlw9ZbjVwEpt0AD0jOwLzuW+INTR2BcY4tzX+RevcLBH7/GoNdjMBjoPvUFdGmFaNpW+v3K\njIzQ2nbGNfskKUbO7BnZkxl5J6hITaU8Lb16HLG8HH1REQrLxjKGS1STHoH+pxH81saNt0znkynY\nI3d2YPuA/igU9XsQbgi/1yV744nrN5iAS0c5XmzBGrehjDm/gy3ffsrwKf+UEiA/AtLzroPcEQty\nUameaF/+JsNnLwzpeKe23uP+kto5ZGQWwImtG2wO/fTtHQvezwndFlH1etUb09tcz0gzrqtffQkP\nD9cEBQX5lJeXyzQajf7HH39M7NKlS61Op5s3bzZLTEzUxMTERHl5eZUDfPbZZ2mDBg1qXdXnm2++\nsRRFkV9//TVFdsNwsnr16lQbG5uA0NBQ8ylTpuQsX77cftSoUVlvvPFGFoCfn9+VQ4cOmaakpBjV\nnE+lUhlCQ0NTNBqNCBAdHa3etm2bVWxsbPX8bdu2zdy3b5/ZsmXLbLt3735x8eLFtj4+PiUrVqzI\nqBonNDQ02c7OLuDQoUPGwcHB97VlUW+zoiiKmwRB+A2YDawVBOEP4A1RFGPuZ+J7RLzlvVDLMQRB\nmAZMA3B0dOSDDz54BKI1fQ4ePHjj1UjIBaKb8OfWugMABxLTOLDi08pj227uMhiACEDBzz26Q4/u\nlQ31uF6ka6p+/HlNNQRT4Aw8x7HqIx+FH7+nET448mASTNLAx/86SQegw41jOqw5SylnFyy473Eb\n9nN68qnyDfpX2OlGlUOi6eDn51caHh5+Pjs7Wx4aGmo5ffp0Vw8Pj9j169dbLF26tNonKjIyMjo6\nOtrIzs6uvEoRAwgKCiqS1dgti4iIMMnIyFBrtdrAmvOUlpbKEhMT1QBJSUlGEydOzKzZ3qlTp6Jb\nlUFvb++SKkUQ4Pjx48aiKOLv79+uZr/y8nKhW7duBQBnzpwxPnHihNbY2Pim+QHi4uKMHroyeANj\nKn9FvwdeBc4KgvAl8I4oig/DozoL0AMOtxy343ZrIaIorgRWArRu3Vp87733HoJITxYHDhwgKCiI\nmMSjGK8bj3O/t5F1mtjYYj0QyadPsmXRx1SUl+HZuTvPvv4PxGwdmV+dRW6lQTnOG7+IaJxJ46Xj\nkaguBdNjpCft+zghyAQyly8n67/LwFCZfFtuZYXZkGf5n06HdE3VTdU19UBcT0T/TV+2tnFnrsm7\n5AqWuJZms613N2xMajUaNDi31iGuYko/Dzaor3FJb0Y7fRTBJ6Po36kn3foPu6fxG+RzaiYcOHCA\n3VmpfGPtz1PiBdb1fbGxRXosef/99x/pfPW11HUOGZlVZSWsi4mLVlx4MKluxsjISPT19S0D61Tt\nrwAAIABJREFU6N27d/Hp06dNPvnkE/svvvgifdy4cTlV/VxdXctF8TYb020YDAZ8fHyK165dm3Rr\nm62tbbUDen12C4yNjW+q8KDX6xEEgcOHD19QqVQ3CWNiYmK4Mb8QFBSU9/nnn6dzC05OTro6J70D\ndSqDgiDMAjrf+PMAyoEzVEb4ngHGAucFQRgpiuK9Pa7XgSiK5YIgRAADgF9rNA0A1jfkXM0ZnU7H\nvLjTHO2yjvmGOF5rbIEeELfATjw3/19s/L8PSDhxlA0L32fI5H8gqBXo0goQv73Ai5ar6ef4Oymm\nnajQ9SYsNA6VRo5PN0dsZ8zA4rnnyN+6lbxNmyiLTyDnhx/hxTGkz5yF85LPG3uJTzalebBmDFu9\n3fmnyfvkC+Z0NDLwfeeuj0wRhLvXIX6pyJlnTkQSLW+P4K3EcDgClzYdcLwRyCTR8LS5doUp0amM\nGNKvsUWRaMIYDAbKyspk9vb2ent7+5uc7Hx9fUuvXbumSkhIUHp6euoADh48aGww/KmzdejQoXjL\nli1WDg4OFTY2NrU66bm7u5eGh4ebANerjkVERNwxaKWKrl27FouiSEZGhjIkJKSgtj7+/v7FW7Zs\nsfTy8ipXq9V1a6/1pD6RAnMAJbACeAowF0WxuyiKb4ii+IMoigOBpcC3DSXULSwCJgqCMEUQhDaC\nICwBWgBfPqT5mh15eXnkKSuDlVzNbzXCNk2cfNrywnsLMbGwJOdyBhVqHXav+KGwM6biajEj4gcS\nHzOFK1nutPfaj0t7a7w7/+nfq7Szw3ryZNy2bMH111+xHDsWAE173+o+usuXyd/1O4by8tvml7hP\nDHpYN5ny6xc5YzGTfMGcXuZy1nUJwEZb5730keFuouVnf2+sFCJBIhhRStGJNbX2rW86G4m7U1hS\nhkI04GDTdLIdSDQuM2bMcNq5c6c2NjZWFR4ernn11VedwsPDTceOHXu9tv7Dhg3Ld3NzKx07dqzb\nkSNHNHv27DGZM2dOK7lcXq10TZs2Ldva2rpi8ODBntu3b9fGxMSoduzYoZ06dapzVUTxjBkzrq5f\nv97m888/t46KilK//fbb9pGRkXXewPz8/MqGDh2a/corr7h+9913lufPn1cdOnTI+N1337X//vvv\nLQDmzJlzraCgQB4SEuK+b98+k/Pnz6s2bdpk+uKLL7rk5OTcd/RnfQJI6vOo+x2VeQAbHFEUQwVB\nsAbeBhyBc8AzoiimPoz5miPZ2dnVOQbd7R7fvIL3iq2LG2MWfIJeV46ZjR2Ld8ex6tpVPsMYH72W\ntGs2JJoZOKdL5tW/OsGNRMVFeWUc35JEjxGeGGmVaNr7ViqBH3yA5UsvVY+fu249WcuWITc3x2zI\nEMyHD8fIt50UTPAg7HkPMWE3mx3nw4EzzHvWjVf82913EumGorYglA6WtpzoYYVS3w5d6W9oor+H\n3s+BlftN/ZbsjX+s83U2FSrIw8REh5FWWXdnCQng6tWryr/85S9uWVlZSq1Wq/fx8Sn59ddf40eN\nGpVfW3+5XM6GDRsSJk+e7BoUFNTG0dGx/N///nfa1KlTq7/UpqamhrCwsJjZs2c7jx8/3qOwsFBu\na2ur69GjR0GVpXDatGk5SUlJ6gULFji/9dZbsoEDB+aMHz8+c+fOnXUmyPzll19S5s2b5/jOO+84\nX716VWlubq738/MrGjBgQAGAq6ur7uDBgzH/+Mc/nIYPH+5VXl4uc3BwKO/Tp09eTf/De0Wozx55\nnYNU/vr1FkXxsfGGbt26tRgbG9vYYjz2HDhwALVax+gSM3SCmoRe7dEqHln2oEdO+OZ1OHu2I+LH\nK0S6KPmvj5answ7xQwsRes4EYNfX50g4eQ1jMxXB431wbW8DVAaP1PQZzN20iezvVlFW4zpTe3li\nPnwEZiFDUNo1z/QX9+0Ld+ZnMg7/nVN2TxNx3hWVSsXUqVOxtbVtcBkbElEUuZL8HfvjfqBftgU2\nL6xHLv/zO3Sn+t6Sz2D9OXDgAN/rYkiSmzHfWeRp77GNLdJjiSAIEaIodnoYY0dGRqb4+/vXy+9P\n4nYGDBjgodfrhX379iU0lgyRkZE2/v7+rrW1PVCSwirESo3ysVEEJe6NtIKL6JQdMRELn2hFMPlM\nBGE/rwK5gn1WwfTP9gW0/GEdSPTBafxeNJDZT/vQbZgHRbllXE7IY/uys/h0c6Dn87dbhiyGD8di\n+HBKL1wgd+NG8rduoyw+gWuffEJp9DmcFi165GtssqSdIH/fbGb6v0Ws4MMw+/2MCR7z2CuCUOko\nvia7gM9Un9DL8g/6/ff/KPAZwdL9idV9qiqhzOznJVkJ75MLghMpQktUqsuNLYqExF0pKCiQffrp\np7YhISF5SqVSXLNmjeXevXstVq1alVj32Y1DgyiDEk2bjNIcUIKtIafuzk2YVr7++PUfxNk9O+mb\nuZuuvW2w1enIVDpw3L0dM1tkAD6Y22oY/kYHzu5L49jmJGKOXeHihezKWPpaMGrTBoc2bbD/+98p\nDAsjb9MmzEeOqm4vDDtMwd49WIwYgZGfn7SNfCt5GZSte5F320/ksKwPKkMZ7q0H4+PTqJUw74mn\nPUez6HQ6B4yCaGG1jqGy5Gpr4J0sgxL3RlUpOkdjqRSdxOONIAji7t27zZcsWeJYVlYmtGrVqmzZ\nsmXJEyZMyG1s2e5E0yo1IfFQuKovA8BBKGxkSR4ucoWC/lNeJfjlqQiCjKPr1+CZHA3AWpsQItfk\nUnC4Mo+nTCYQ0L8VL8zvjIO7OcV5lUEiudfunMJJUKkw7dcP5y++QPtUz+rjub+Ekrs2lJQXxpD0\nzLNkrfwK3dXbMiM1TyrK0Ie+yDLvbqxVvIggGhife4mJQb2aVOCFr4Ujr9pVFjX4zakvB06HceXK\nlUaW6skh7dpV8mVmKEQdLYxtGlscCYm7otVqxSNHjsTl5uaeKSkpOR0bG3t++vTp2Y0t192QlEEJ\nXnIJ5OOEj3nDuNYKPU8UgiDQ4ZlhDH/zHVQaDR2OHkMh6oiStSfc4Tx525LI3ZaEaKj0pbV0MGHE\n3zvQ8zlPACzs7j21ic3fXsNq0iTkNjaUJyeTuWgRCUHBXJw8hcJDhxp0fU0Ncfe7bLRSsFhTmdCo\n/9VY3n5mEDKZrNYcf48z/2jTmzaKK+QKVkT4ubLplx/R6/UNUgGluXO1pPJB1YZMNEZPRsYDCYnH\nCUkZlMBPq2BSxk56/1lD+4nHPbAzLy74BAetKf75UYiCjCOuKsqEMgoPZ5C9NgaxojK3VJWVsCYp\nUVnsXHmOoryyOucyau2N/Zv/xGv/PpxXLMd04EAEhYKiP/6g9Pyf+VUN5eU0REBXkyF2B6cvbWW+\n1TvoBDWjLPQs6t8fjUbT2JLdFwqZjOXt/VBRxgl1Fy5YFhF2cL/kI9gAZFH5PbPhOgqFaSNLIyHx\n5CEpgxKQeyNLj+UdS0c+kdi0cmXsR4v4q7cfKrEMpXEJGeY/IKhllJzNIvObcxhKKm47TzSIHFmf\nQOKpa6z54Djn/7hULyVOUCoxDQ7GecnneIUdwv7ddzAf/mfViuxvvyVp0GCyvvwS3aVLDbrWx478\nS7BpBsfMQsgTLOliXMrn/h346UwOrnO3VwdcVL1uKlvGbSxaMNOuMlfsLptgDoYdJi/vYRRnal5c\nV1Z+v+yfcFcWCYnGQgogaebk5eXyl5Ji1AH/YIHSgsc/drNhMTa3YIhZR1TXJ1KUFccZQzsKK7bR\nQhyITXIemSvPYvdaIILsz6APQSYw5DV/Dv4cy8XobPb/GENc+FWCx7XG3LZ+28hyCwusauQsBCg6\n/Aflqalkfr6EzCVLMe7WFYvhwzEdMACZ8aOrvPHQMehh/VRKdCK6NFtmW+cx0a8bSplw16ofTYVZ\nbfqSr0rHYddmtKRRkX8NzM0bW6wmjcn1cvyFGPr5+tbdWUJC4p6RLIPNnPz8SxxQd2Sj+RCQPblp\nZe7E4t1xuM37jdd+G074mWfILnfmXEYSv1/6CSzlaHs736QIVmFmrWHI3/zpP6ktRiZKMmJzWLsg\nnFO7UtHrDbXMVDetVn1Hy69WYvbMMwhKJcVHj3HpzbnEP9WLnDW1V7dokhz6lOycY2yzf42c/EIs\nE2KxUT05z6VymYwPvFox5bkXGM8GLKO/bmyRmjQGgwGr6zl0j41hXOuujS2OhMQTiaQMNnMK9dcp\nFrSoxDJslE/OD3J9mT3Am5SFzxL38QhiDHYk2DpR7OSEvPwKa0/9H+P+t5JFu2JqPVcQBFp3deCl\n97vi3cWeCp2BqAPp6HX3pwwKCgXaXr1wWvQZXofDcPjgAzQBARiKi1E4/Ok0X5aUTHla2n3N0eik\nHuF0/I8MCfgf8WYXUCqVjBo1qjpJc83t4KYeeCFa2XKuazu+qojDkJvR2OI0WYqKijAgQyOUo1Kp\nGlscCYknEkkZbObkKCods23F3Gaf/+60dxv2tO1MXoAWpYUKgQqeyjmG+Ntyss+lAJCzOQFRf7N/\noMZUxYC/tCPkdX+Cx/ugMqpUqnVlekoLdfcli9zMDMsXRuO6dg3uv/2G9qmnqtsyv1hK4oCnSR03\nntz1G9AXNpEo8OJs8rZNZabH2yQJnuzSDOSZZ57B2tq6ukvNCOKmHnghkxnxpnoq75m8x7s7vuHi\nxYuNLVKTRBAE1L5XsfJPobAopbHFkWimGBsbBy5dutS67p5NE0kZbObkS47Z1TzvoAZgp3Ufnnc+\nwYg5czE2t4ArScTuqiywU3T0MlnfncNQfLuS16qtNa3a/nmvCN+axOr3j3HhyOUHihJWu7shKCvr\nsYqiiMzEBMHIiOKTJ7k8fz7xvXpx6c03KTp2DNFwf1bJh44oot/yKvM8RhEn+GCuz+XlchkBAQGN\nLdlDQ6EwoZ9tZUnCrXad2bVrG6IoNplgmMcF0UjDEutXWGA2E4HH9PqWaBLMnTvXQRCEjhMmTGhV\nd+/mhaQMNmMqKirIU1ZuuzgrpJvsJ/274CzLIUewZo9HR9xVabz86TKiTNsS+EplRRGZVklZQi5X\n/3uG8ow7K9AGg8j1S0WUFurY98MFNn52iqz0ggeWURAEWnz4IV6Hw3D88F9oOnVELCkhb/MWLk6c\nRPZ33z3wHA+FUz/wg7yEDeqRyEQ9IcmxvPjsMwiCwOLdcU06gvhuvOrTD0eucVXmyFHTQuLj45tc\n/sTG5mJOZYJ2WzLRaJwaWRqJpsrevXtNfvzxR1tvb++SxpblTpSWljba9pykDDZj8vLyyFebANDK\nuGnmdmtIBEFgjF3lFu+PtiPYveFr2v77MAds+uDzYaVlcIuvCYVCHvrsUq6tOEPRidqrTMhkAiGv\nVQaYaEyVXE7I45ePTnBobRylRfe3dVwTuVaLxXPP4frTT3j8vgubGTNQOjtjOnBgdZ+8bdvJ+fVX\n9AUProQ+ENnJnItYzEfWcwAISI/itacHVecTrPLbrIocrnrd1LeJAdQKFX93rvSHDLPrym97tiEg\nWQfvhYjkMwDYCTnIZOpGlkaiKXL9+nX5xIkT3VasWJFibm6ur6v/uXPn1F26dGmtVqs7uLq6+q5Z\ns+a2dADJycnKIUOGuJuZmQWYmZkFBAUFeUZFRd10gc6bN8/B2tra39jYOHDEiBGuc+bMcXRy+jOh\n76hRo1yDg4M958+f72Bvb+/XokULP6hUCqdPn+5kb2/vp9FoAn19fdusX7/erObYERERRkFBQZ4m\nJiaBVlZW/iEhIW4XL168b8d/SRlsxuh0Osx1JbjpE/GxcmxscR4LXnbvVFmRRN6eNFt7Uma2BKhW\nVHqYZrAj+SsS889AhUjOlgT0+bUnnq4KMBn7QTf8+jqDIBB1IJ3V7x2rV7Lq+qJq1Qrb11/DY/fv\nqJydgcrt5Kzly7nyzrvEP9WLjL//g8LDfyDq67wPNiwGPYaNr/CG6xsUCqbYFWYQfd6WPivOPTHW\nvztRZfGc/00xrSqSKBDMOe6gwF12nSV745m4s+iJXn9DcTwjHQBbJFcWiftjwoQJLkOGDMkZOnRo\nnU/Ger2ekSNHehgMBvbt23dh5cqVyR999FGL8vLyaqtdQUGBLDg4uLVarTbs3r079uDBgzH29va6\ngQMHehcUFMgAVq5cablo0aIW8+fPzzh27Nh5Hx+f0pUrV9rfOl94eLhpVFSUZtu2bXE7d+6MAxg9\nerTrkSNHTFetWpUUERER/dJLL2WNGTPG8+jRoxqA1NRUZf/+/Vu3adOmJCws7MKOHTviioqK5M8+\n+6yX/j7v8c0vfFSiGgcHB+Zfi8Yp5mvon9rY4jwW2Ko19DK6xv4yJ/a7BjLm8ApgSHV7+74DEWQy\nDq1eRVZmBqJgwHFnKl2HP4/iDpGOamMlvUZ706ZHC8JC41AbKzAxb3gLx00BQAYD1lOmkLdpE8Xh\n4eRv20b+tm0o7O0xHzoUixdGVyuOD5U/liBLO87IlpPJV5aw5en+dPljzx3zBzb1COKa1MyZ2Gv5\nN9AGDpt3Y4TJAZILrPh2kClBQU3f+vmwyRQqbRZOymZUnaeJkD43rOOd2syfcUs17e2cBVBwKN0m\n77fkO1Y1cF7YK6Lq9ZVFEW0qrhXXmli1Zr/68tlnn9mkpKSo169fn1yf/ps3bzZLTEzUxMTERHl5\neZXfGCNt0KBBrav6fPPNN5aiKPLrr7+myGSV1+fq1atTbWxsAkJDQ82nTJmSs3z5cvtRo0ZlvfHG\nG1kAfn5+Vw4dOmSakpJiVHM+lUplCA0NTdFoNCJAdHS0etu2bVaxsbHV87dt2zZz3759ZsuWLbPt\n3r37xcWLF9v6+PiUrFixojpNQWhoaLKdnV3AoUOHjIODg4vv9XN6YpXBi+UXaf/9zeXV3u3+Ls97\nPw/Ar3G/suDogjueH/VyVPXr0VtHcyH7Qq39RnmN4v0e7wMQfT2aMdvG3HHMtUPW0s66HQDvH3mf\n9fHra+3XxqoNv4T8Uv3+1nXU5IHXpAYczaDGHE1+TbVwL2v6Z8//EncxDTfjWBbFp2PaZi7tv5/L\nczyH3w9+AKi7yuiXXIRdop7U9eeJ+eMAqXZyrpgXctQ08o5rGv5GIL9Er6P992MBsC1sRfvLvTne\naitF6ryGX1M/sO0o54vy51D/fgRdWhrXv/qKude/4UTrGxsDogg3FMkG+3/6/s+XLey60f3IBaZ7\nlGPbsxvGrl/Q/vu5d1wT1LGmGzSlay/tYmc6ehWiTT2Pib6IVm6f8Vrq9Zs+p6a2pkdyjxDB1rby\nWknOOVm9zia9pjvwMNbU3ImMjFR/+OGHTvv27Ys1MjK67Wli7ty5DkuXLnWs0T86OjrayM7OrrxK\nEQMICgoqqlL6ACIiIkwyMjLUWq02sOZ4paWlssTERDVAUlKS0cSJEzNrtnfq1KnoVmXQ29u7pEoR\nBDh+/LixKIr4+/u3q9mvvLxc6NatWwHAmTNnjE+cOKE1Nja+aX6AuLg4I0kZlLgnNAYlFUot5foc\nmndSmZsJtLBm6dVvSUrK5GKZB4gZ3PoBlakMJHdX89r4d9nz9XLKrhQwSTMJZYGS7RZhfGW/jjLZ\n7b6BgiAgq2FA7JYaglO+N27Z/pxpsZfIFnsbfD2ZFgIMeR6Pv79HSUQEe779gFOefz4kT//NgFoH\nB9oL6MwbzvpiIZcTaOaAWXpl1Qgfb28EQcDOTM31u7hNLt4d90T4C9ZkZj8vZg/w5vC6jcwWDlGq\nKG1skZoESoOSHJkNAPllmXX0lnjU1NdSZ9rbOavKSlgXDm90bDDN9uDBg9rc3FxF586dqxUrvV7P\nyZMntT///LNtcnJy5Lhx43Kq2lxdXcvrk/nBYDDg4+NTvHbt2qRb22xtbatrmNYnXZuxsfFN0Zt6\nvR5BEDh8+PAFlUp1kzAmJiaGG/MLQUFBeZ9//nn6reM5OTndl1O68CApLx5nWrduLcbGxja2GI81\nn699l4X2I3EQszjTt39ji/NYYTAY+OKLL8jJyWG0Yg9t/76dD/7zOe+9995tffUVOmKPHKal4EXe\nzhTQixi0YDHaEzPvu/ti5mWWcHRjAomnKn/otJZqug33wLuzfa2VTxoaQ0kJcT16IpZUBtgpbG0x\nHzYU8+HDUXt63teYBw4coE/5bqbqNexQD2RUzmY6Fnoxfvx4aj5d34mmWoauPojF2VxfFchRtSOm\nHgsJCgp6otf7oFy+fJnlK1ei0Ii8OeddjOSSm/vdEAQhQhTFTg9j7MjIyBR/f/96KXSPC1lZWfLk\n5GRlzWOTJk1yc3NzK3333Xcvd+zYsfTWe9KGDRvMnn/+ea/Y2Niznp6eOoDff//dZODAgT5LlixJ\nef31169/9tlnNu+//75zcnJylI2NTa1OegEBAT7t2rUrXr16dXWC0aeeesorOTnZKCMjIwoqA0iy\ns7MV+/fvT6jqc/bsWbW/v7/vli1b4kJCQmr1cXzttdectmzZYhkXFxetVqvrrcRFRkba+Pv7u9bW\nJn2zmjFZYmUQg41wzxblJx6ZTMY1Gy+Ourdjk7onRKy6Y1+5Qknb3sGY9nLG7m+ByKxUyAoh95tY\nopdtp7zkzpkMzG01DJrWnhFzArFpqaUwp4w9351n3X9Okn354SeTlmk0eGzfhu2smahcXKjIzOT6\n19+QNCSE5OdHUxJ5+5Z3XZjnnmNtZiTbjIYAAqorVgwbNqxeiuCTTpm8nIWtRzDH7T8sOR2F29xt\nwJOVTqchycvLQy6KtNTnS4qgxD1jY2Oj79y5c2nNP2NjY4OlpaW+c+fOtymCAMOGDct3c3MrHTt2\nrNuRI0c0e/bsMZkzZ04ruVxerXRNmzYt29raumLw4MGe27dv18bExKh27NihnTp1qnNVRPGMGTOu\nrl+/3ubzzz+3joqKUr/99tv2kZGRJnXJ7OfnVzZ06NDsV155xfW7776zPH/+vOrQoUPG7777rv33\n339vATBnzpxrBQUF8pCQEPd9+/aZnD9/XrVp0ybTF1980SUnJ+e+vijSt6uZUlJSQr6q8oHJWSnl\nGKyNH3UmRLb04ryfCxz7sl7nqBxN0LzkzFVVGjJBjnmaGcff+p6ze3air7iz9b6FlyXPz+tM3wk+\nGJupyLlSjJGJ8o79GxJlixbY/PWvuO/cgcvPP2MxejQyrZbSqCjklpbV/crT0xF1dexAlOYjT/2G\n9x0r08j0vnKcM5esCVj4x10VnSc512BNjNQOlBl3JF8wp8jbnG3j3YAnK51OQ5KbfQWt9jrGRo84\nCl6i2SKXy9mwYUPCja3YNpMnT3abO3fupZpbtqampoawsLAYFxeXsvHjx3v4+fn5TpkyxS03N1dR\nZSmcNm1azqxZsy4tWLDAuWvXrm2jo6M148ePz1Sr1XX+4P7yyy8pY8aMuf7OO+84+/v7+44cOdLr\n8OHDpu7u7uUArq6uuoMHD8bIZDJx+PDhXh06dPCdNWuWi0qlMtT0P7wXpG3iZsqlS5d46/T37DQe\nzBSzK3zYcVBji/TY4fWvzRT2bIkMA/vOjWVtzkuY9Xix3j/YqTtPUr4/i/0ZP1Ogy0ZrbUPXYc8T\nMPDuW4K6Mj2ZF/Np4VWpiOn1BsK3JuMX5IyJxaPJs2YoLaX4ZATap3oClalqkocOoyI7G/OQEMxH\nDMeodevbztNvms5wk0BOKLrgUZaI9x9pfLtg5j2VOnzSt00Tc+LofToPA3JmpR1jxYVWpCwcUveJ\nzZDf4g6yMP0SnfWRfDZgYWOL89gjbRM/3gwYMMBDr9cL+/btS6i7d8Nzt21iKYCkmZKTk0O+0hQA\nF7PbUh81WxbvjqtRIUJBq6JEUrVeLPEYi/1JkSV7Ky1V9VEIXQZ1wtBPjz5cw7ENoVxPv4jueC4V\nnUpQWN85ybdSLa9WBAEuHL7EqZ2pnN2bhl+/lgQOaPXQrYYyI6NqRRBAn5uLqNejv36d7FWryF61\nCnXbNlgMH47ZkCEorKwgZjufV5RxQtEFE4p509SaN3XyZl/z+lY8LL0ZoFjFTn0AYZZqXu10Wz7b\nZk/V99DX9yJxTt2x1mXhOnd7dSCOhMTjTkFBgezTTz+1DQkJyVMqleKaNWss9+7da7Fq1arExpat\nNqRt4mZKdnY2ufLKHyFXc4dGlubx4dZqGIWxlV+RHZp+APSRnb2ncmIypRyfnn14+ZP/MuL5uTgW\nt+Lq56coCMsg/VwUR9etoSg3565jOPtY4R5oS4XOwKmdqfz0zlFO7kihvLTiruc1JApLS9y3b2Nm\nn9exeHEMMjMzys5f4Oq/Pya+dx+KD++jZOscvrGcAMACVzVDewYxrV/be57rSco1eCdmt/ZHEPWc\n1vpjUlGv9GfNiqrvoUerygdWD1WFtI0u0aQQBEHcvXu3ef/+/X26devWduPGjVbLli1LnjBhQm5j\ny1YbkmWwmVJQcIXrRpUpG1yMLRpZmseLmtbBoiwjnMtSSVdX5kudJN/JQYP/PVspBJkMl0FdyK1I\nouRMJnnbkygQcohO28XxjaG07tGbDoOHYu9+ewSvhb0xg19pz5WkPI5tTiQjNpfjm5M4uy+NnqM8\nad3t0VSPEQSBOMtWOL43Hfu5cyncv5+8jZsoiYrCKOUrKMnm7aLrHC9MZZR9Z0RRvK8f7+bwg+9v\nH0jXqG84Ju/IbnUJz127hp2dXWOL9dgRUywHNVhLdguJJoZWqxWPHDnSZJyepW9YMyUwsCv/TF3N\nm1k/0Uoj1fusSZVVospC9XZbtz8bVUraCZWWnCV74+8pwEGuVWE9xgfrCW2RmakwFS0Z6PwX/MyD\niD/8Bz/Nm8Wad/5BzJFD6Ctut/o5uJszfHYHhs4KwM7VjJICHQbDw/f5rS24w/29PXwjd6fl/77E\nc/ErCAm/ccxzDnGnonA5GUnSyFEkDxvO9e9WUZEluRnVxlBZZc3iFMGdP44caWRpHj/Ky8vJlFeW\nY7WVSbXT70b2pSIO/Cz5yEvcP5JlsJniaOvA2NRtpLiMllI23IHZA7xZsjeeoS3bszmkGsWXAAAg\nAElEQVR5JQCp9mZMTdvO8H/tuO9xNW2tUbubk7crhaJjl/E264iVZysOR4VyKe4Cl+IuEDzxFToM\nDqn1/JY+Vji/acnF6GxatvnTt/DU76moNQp8ujsiVzTc/2nNsmq3BXfkpnHo3Pf83mMS1tGXAEt8\n9HoUFhaUxcVx7T//4dqnn6J96inMR4xA2zcY2R3K9jU33GWurDWc5syZSJx79mpscR47cnNzyZZb\nAWAn1JmRo9lydn8aYb/Ew5MZCyrxiJC0gOZKXhogUmokBY/cjZn9vJAJAp+1ryxDl3qlHS6yHMhJ\neaBxZUYKLId5Yvd6B4wD7fB/bTjTVqyi3+QZOLq0xqfHn8rB2T07ObVjKyUF+dXHBEHAxdca2Q1F\nvji/nBNbkzmwOpbV7x4jOiwDfcVDThlkMJC/9W/Mdp3Dt8qJxDrbERgYiPGIEXgdOojTF0vR9u0L\ngkDhwYNkzJqFLj2j7nGbEUE9n+N11Xo65G1FFKX0KTVJy8mlVNBgJBajxbLuE5oRev2f322n1pbI\nFTJ8ezs1okQSTR1JGWymLD+2jskBb7FPiiS+K1UWMSur7gAYDAr+kHVGPPgJQK3bxPeydaxyNMHq\nhdYIShkqIw1+Tw0gyPQ5Sn67QkVWCQaDnqMb1rJ/1f/48pUJbPy/BUQf3EtpUeFN4xhplfSd0AZL\nB2MKskurlcJzhzKo0DWcknFTcEf4SuZYduGyrAVO+nS8MowZOHAgAIJKhdmAAbRcvgyvgwewnzcX\n85EjUbv/ueWePns217/+Gt3Vaw0mX5NDbcqVTj3ZoI1lS8wW4N6unyeZnLw8Aq5coHtBAjLBuLHF\neSzISi9g19fn2Lz4NFVp4axbaJm4sCd9Xro91ZOERH2RtombIWVlZZzS69huPgQqpALn98LOgKdQ\nGMoZf2Ya5j1eY8nexNsCHpbsjb/vIIiy1HwMpXpKIjMpicrEuKM9QaP+wrnwvaRGniYpIpykiHBk\ncgWt2vvTbeQYnFq3QSYT8Opsj0dHOxIjrnFiezI5V4o5+HMsJ7YnM+adLmi0D749W72uq+dZH7uD\nra0+QCHqCD5/ilFDx2FkZHTbOQpra6xefvmmY6UxMRTs2EnBjp1cW7QYk549MR8+DNN+/ZDVMsaT\nzHmnp3n9qj8Wl/OxyQ9nyd7MZhFEcyeqArh6KBLppsgGfTETddbM1D15Navry+XEPCJ2ppAadR0A\nmVwg92oxlg6V2+ePKkG9xJOLZBlshhQWFlKorHzStpRJzwO3cjfLzCVzSxIsW5DQoiXs+1eDz61p\nY43D3zth3MkeRCg+cRWT/XL6+b3M1EXf0G/yDFr5+iEaDKSciUBfoyLIlcR4MlOT8Oxkx5h3u/L0\nlHbYtNRi5WhykyJYXvKAKWl0JVze+hpvtZwFQL/rYfT17IS7u3t1l7qsW2oPD5yXL8N0wACQyykK\nC+PSnL8T36s3l999j4rs7AeTsQkR1PpFWpJOjmDJquQTCDTvikBVAVyjfCrvUcO6tWXVIJNmpwiK\nokja+Ww2fnaKDZ9EkBp1HYVShn/floz/sHu1Iigh0RBImkAzpLCwkGJ55Y3WTJCc+W/lbpa9Z7SX\n2VTozL9ajmfT8Xl0EDrhOvf2flWRt/eTJFdhaYTVc96Y9nYmf3cqJVFZFIZloL5sQcCUZwh4+hmK\n/5+9846Pok4b+He29/ReSUgIIYUqHRKKoICA3CkWrFjv1APPAqf3qucp750CouC9tuPu5AQLIKKC\ndFCkCgECJIGQkIT0urvZvvP+sSQkEKpAgOz381nYnfnNb56dncw889SGeo7u3k5k127N2239/FOO\n7d2N1teP2PSexKb3ZMyTqcgU+uYxFYUNLJu9h+SBYaQPi8IQePFZmu41f+axqDupF/yIcRzltX6/\nISykda3K81lHBbkc/bBh6IcNw1lbS8O331G/bBnW7Gwavv+ekJkzmse6TCakOt1Fy3m9IJOpGWnL\n42NVDNsCE4iSlP+q8+dGwRJ4giBVNkJQMHTA9ukOm4tVH+zHbnWhUMtIy4wkLTMStd57zb7aaDSa\nHrNmzTr+9NNPV7e3LFcKrzLYATGZTJiknpurj+AtK3MxTE/swze/FLFd2ZePg2/h+bLF9Ht1G7To\nsnG52qnJgzUE3NMVe7GR+h8K0bcIEFc4FHRNG4xEKm1e5hsaji6gEFN1Fdmb1pG9aR0AfmER9B47\nkbQRozl+sAanzcW+9cXs31BMfM9guo+MJiTWcGFC5a6m/pf/UtbjfTRyM9bdDoau3w/sv2TFRebn\nh/+99+B/7z1Yc3Ox5x9rdhW7Gxs5kjkMdWoqPhMnoB8xAon6xisz8tLwqaz4cQeV0mC6ReWw+Ykp\n7S1Su/OlsgvblLfxluYIkR1AGbRbnRzaWkryoHDkCikKlYzet3bC7XaTMjQSpdp7u75Ypk+fHj5n\nzpxWhVgDAgKcVVVVWe0l07WK9+zqgDQ01GMUPNYiAx0rPutstG5Dd3bLXqJPCOP1u1hqjGBx51t4\np2Iu5K6GLleut7MiUk/QQymtltX/UIhlXyXq1ED0QyJRROoZ9uBjZD7wKNXFxynYu5uCfXsoyTlI\nbWkJLpfHNdz7lliU6jK2L/2aRqMvOdtCyNt5nPDEEHqNjiUmJeDsghjLYPkTqP0682BJGTED4niy\nvq5Z8W2qR9jEpVi3VImJqBJPjbVmZyNarZi3bsW8dSsSrRb9LaPxnTgRdc+eN0yrO7XCl4mS/Xwg\nDudEbAiVlZUEBQW1t1jtSqmoBwFifUNxVl29bjtXG1OtjX0bisjecgK7xdkqM7jHzdHtLN31T2xs\nrHXTpk3NRRhlsmtT7bFarYJKpWq3AkHX5lHxckUxm8tokHhKNfhwY9xMfy3nrKXXgjlrclm71YFy\nsJX98nT+Gzmcuxf9kR8GxfCHm7sCv66d2pw15w+SF0URiVIKEgHLvios+6pQxBrQ9g1DkxJIYFQM\ngVEx9B53Oy6nk4qCoxgCT3W3qC05RH35/lZzFuz2paG0EymZPek9duKZO3W7sS5/EqfUwmrfByjP\nK0S6dSsQ3jyk6Rhu3LiRB1aZL4t1VNOnDwlbNtPw/ffULV+ONWsf9V9+Rf2XXyGPjqbTl18gNVyg\nVfMa57GUkfxrXyO5qkS+2f0LD40e1d4itRtWq5UyPDUGOxvCOczxdpbo8iKKImVH69m3oZijeyoR\nTxaPD0/wxTf4xrN8tycymYzo6OgLfpo4cOCA8qGHHorNysrShoWF2d98882i08ccO3ZM/tRTT0Vt\n3rzZANCzZ0/Tu+++W5SammprGjNjxozQDz74IMRisUhGjRpVGxcXZ1u8eHFgSUnJfoBJkybF1tTU\nyAYMGGD66KOPgh0Oh1BTU5NltVqFadOmhS9dujSgoaFBGh8fb3311VdLJk2a1FxbbPfu3apnn302\ncufOnXqlUukeOHBgw/z584su5nuecZwudUMv1zESBwHuGuSCG4NEev7xXpppUnj+tOc7/l0bgC3C\nib1Yyx+C9wJdm8dcKheSiSwIAn63J6AfHo3ppxLM28uwFzRgL2ig/puj+N3RBXWS50YqlckI69y6\n5ETq8FH4R0RRnp9H+dEjVBTk43LWUV28h+yNNfQeO5GcbaWU5tdz4uBC/CNC8XcU8l50P6oibmFY\n3s/I5THcfvvtmPdc+UQPqa8vfnfdhd9dd2HLz6d+2TLqv16B1GBopQga169H27cvEu31GVgfEZjG\nOPu/yarz5fCJfOzDMlF00ALdB4uPYxNUaEQzwbrkG04ZXP/vQxz+uQwAQSLQuVcw3UdEE9Lpxniw\nuZYoLi5WBAcHp8nlcrFHjx7mv/3tb8XJycn2tsa6XC5uv/32eIPB4Fq/fv0hs9ksmT59erTdbm+2\nmhiNRklmZmaXXr16mdasWZOjUCjEWbNmhYwaNSoxJycnW6/Xuz/44AO/2bNnh7/55pvHR4wYYfzs\ns8/83nvvvVCDwdCqzteOHTv0er3etXLlylxRFAWAO+64I7awsFC5cOHC/JiYGPvy5ct9Jk+e3Hnz\n5s2H+vfvbyksLJSPGDGiy+TJk6tmz55d7HA4hBkzZkSMGTMmYe/evYek0ku7p3uVwQ7IiCETGfF6\nEGTMZCN921uca44Lsey90C2D+LVj8bFa2aLqR8r6N5B1mwjyM93uF2LtuxRkPkp8b43DMDyaxqxK\nzNvLcJwwIQ8+VZPNXmJC5qdEojlVesIvNBy/0HBSMkYAMHv1IaZ0UVJ2NA+pTIYoiuxZc5yqonJs\n9QcozTtAYc/O/OBzM3LRTrqrgKDKEuoL85k28iYAqooKMVZVog8IxGW3/Srr6LlQxsUR/OyzBP3h\nDzgrK5uX2/LyKH7ydwgaDYZRo/CZMAFNn94IkuurYMK73Xuy7h/PE9drBHJ5xy0XklNzHAgkUKxE\nIrn+FeKGKguCREDv77k+RHbxo2BfNd0Gh5MyNAKd3/UZrvPKK6/0Otu6kSNHFg4cOLAK4Keffgpc\ns2ZNzDnm2d30fv78+V0rKyvbLCzZctyF0K9fP1NycrIlNTXVWlpaKnvjjTfChwwZ0vXAgQMHQkND\nzyjA+vXXXxuOHj2qPnz48P6EhAQ7wNtvv100evTo5ifqjz/+2E8URb744osCycnry6JFiwoDAwO7\nL1myxGfq1Km1CxYsCJk0aVLV9OnTqwDS0tLKNm/erC8oKGj1QysUCveSJUsK1Gq1CJCdna1cuXKl\nf05OTvP+k5OTK9evX2+YP39+UP/+/Y/PmTMnKCkpyfL+++83V/BfsmTJseDg4O6bN2/WZGZmXlKE\nrVcZ7IiYT95EdcFgOvfQjsiFKG4GhYbNJX+kt+0o1dZqfrH6cdOuj6H/784Yez5r34XGK54NiVKG\n7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bhqrbhNDkxbT2DaegJBKUWV6Ic6NRB1csA1rRjm1XvKpwVTddUtmw6bi8ID1RzZXY7O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\nMj09/VSClpycXDJr1qzYitry+XzSsGHD0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FAngyISDfwLmGyMOWp1PHXNmjVrmNZmDLdF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\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x10d977790>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"fig, ax = plt.subplots(figsize=(8, 6))\n", | |
"\n", | |
"plt.plot(test_x, test_y, marker='+', lw=0, label='obs')\n", | |
"plt.plot(x, y, label='truth')\n", | |
"\n", | |
"for degree in range(8):\n", | |
" plt.plot(x, polyval(x, poly_least_squares_fit(test_x, test_y, degree)), \n", | |
" label='{:d}-degree'.format(degree), ls='--', lw=2)\n", | |
"\n", | |
"plt.xlim(-2, 4)\n", | |
"plt.ylim(-6, 6)\n", | |
"plt.xlabel(r'$x$')\n", | |
"plt.ylabel(r'$y$')\n", | |
"\n", | |
"plt.axhline(y=0, color='gray', lw=1)\n", | |
"plt.axvline(x=0, color='gray', lw=1)\n", | |
"plt.legend(loc=(1.05, 0.2))\n", | |
"plt.grid()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Explore model capacity" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 17, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"array([ 1, 2, 3, 4, 7, 10, 15, 22,\n", | |
" 33, 48, 71, 104, 153, 224, 329, 481,\n", | |
" 705, 1032, 1511, 2212, 3238, 4740, 6940, 10160,\n", | |
" 14873, 21773, 31874, 46662, 68309, 100000])" | |
] | |
}, | |
"execution_count": 17, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"# explore effect of number of training examples from 1 to 10^5\n", | |
"training_example_nums = np.logspace(0.2, 5, 30).astype(int)\n", | |
"training_example_nums" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 18, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"# will fit polynomials of degree [0-20]\n", | |
"poly_degrees = np.arange(0, 21)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 19, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"# repeat each \"experiment\" 40 times\n", | |
"num_training_sets = 40" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 20, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"CPU times: user 8min 53s, sys: 30.8 s, total: 9min 24s\n", | |
"Wall time: 2min 25s\n" | |
] | |
} | |
], | |
"source": [ | |
"%%time\n", | |
"\n", | |
"np.random.seed(12345)\n", | |
"\n", | |
"test_mses = np.zeros((len(poly_degrees), len(training_example_nums), num_training_sets))\n", | |
"train_mses = np.zeros_like(test_mses)\n", | |
"\n", | |
"sigma = np.sqrt(0.2)\n", | |
"\n", | |
"# single test set, the caption does not specify number of examples\n", | |
"num_test_examples = 1000\n", | |
"test_x = uniform(xmin, xmax, num_test_examples)\n", | |
"test_y = polyval(test_x, coef) + noise(sigma, num_test_examples)\n", | |
"\n", | |
"for j, num_training_examples in enumerate(training_example_nums):\n", | |
"\n", | |
" for i in range(num_training_sets):\n", | |
"\n", | |
" # generate random training set\n", | |
" train_x = uniform(xmin, xmax, num_training_examples)\n", | |
" train_y = polyval(train_x, coef) + noise(sigma, num_training_examples)\n", | |
" \n", | |
" for k, degree in enumerate(poly_degrees):\n", | |
"\n", | |
" # polynomial least squares\n", | |
" fitted_coef = poly_least_squares_fit(train_x, train_y, degree)\n", | |
"\n", | |
" # compute residuals for train and test\n", | |
" train_residuals = train_y - polyval(train_x, fitted_coef)\n", | |
" test_residuals = test_y - polyval(test_x, fitted_coef)\n", | |
"\n", | |
" # save MSE\n", | |
" train_mses[k, j, i] = np.mean(train_residuals**2)\n", | |
" test_mses[k, j, i] = np.mean(test_residuals**2)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 21, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"def plot_train_test_error(degree):\n", | |
" plt.errorbar(training_example_nums, np.mean(test_mses[degree], axis=1), \n", | |
" yerr=np.std(test_mses[degree], axis=1), label='test ({:d}-degree)'.format(degree))\n", | |
" plt.errorbar(training_example_nums, np.mean(train_mses[degree], axis=1), \n", | |
" yerr=np.std(train_mses[degree], axis=1), label='train ({:d}-degree)'.format(degree))\n", | |
" plt.axhline(0.2, color='red', ls='--', lw=1)\n", | |
"\n", | |
" plt.xscale('log')\n", | |
" plt.ylim(0, 3.5)\n", | |
" plt.ylabel('Error (MSE)')\n", | |
" plt.xlabel('Number of training examples')\n", | |
" plt.grid()\n", | |
" plt.legend()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 22, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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WEepwRETCmpK/tArGGB667AyyjxXzxuffhDocEZGwFrTkb4x52BjzH2PMcWPM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\nWcm4+JuZmZWMi7+ZmVnJ/D9Y75QQEXoxewAAAABJRU5ErkJggg==\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x10dc0ff90>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"plot_train_test_error(2)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 23, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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EJMVkRFrQzLKBYUAPoCnwJbDI3VfGJjQRERGJhRqTv5kdA/wC+CGQCXwDFANt\ngSZmtgp4GHjI3bfHMFYRERGJggOe9jez54C/A58CJwEt3P0gd+/i7s2AXsAdwA+Aj8zsxFgHLCIi\nIvVT05H/v4Bz3H1PVSvdfRWwCnjEzPoDnaIcn4iIiETZAZO/uz8QaUXuvhxYXu+IREREJKZq7O1v\nZieZWUa5+RaV1meb2dhYBCciIiLRF8mtfi8RdO7bZ52ZHVxuvhXw56hGJSIiIjETSfK3GuZFREQk\niWiQHxERkRSj5C8iIpJiIk3+A8xssJkNJjjt37/c/MBIKjCzG83sHTPbZmZfmtnzZnZ4BNsdYWZz\nzKzYzNaZ2a1mpksPIiIidRTp8L6zqHit/7lK6yN56FoB8CfgnXBdvwFmm1k/d/+6qg3MrCXwCjAX\n+A7QB5gO7AD+EGHsIiIiUk4kyb9nNHbk7ieXnzeziwiGCj4GeL6azS4EmgGj3b0YWGZmhwHXmtkk\nd9eTXlOAzvOIiERXjcnf3T+N0b5bEFx22HKAMsOA18OJf59ZwH8RPGBodYxiExERabQiebBPDtDE\n3b8qt+ww4HogB3jW3Z+ow74nA+8C8w5QpgPweaVlG8utq5D8zWwcMA4gLy+PwsLCOoRVta1biykt\nLY1qnZXrB2pdf222q+s+olVXXdtwz549hELRibsxKCoqUlvUk9qw/tSG0ZGodozktP+DBKfnrwQw\ns3bA60AIWA/8zczM3R+PdKdmNgk4FjjW3UtrKF751L5Vsxx3f5jgCYPk5+d7QUFBpCHV6MEP57F1\n61aiWWfl+gEKCobFbLu67iNaddW1DbPeeIXdob0xa/tkU1hYqLaoJ7Vh/akNoyNR7RhJb/9hwD/K\nzV8E7AF6uftA4F7CPwwiYWb3AecD3w8/GOhANhAc4ZeXG37diIiIiNRaJMm/I/BJufnjgafd/Zvw\n/CMEj/atkZlNBi4gSPwrIthkHjDczLLLLTsR+AJYE8k+RUREpKJIkv9OoHm5+aHAf8rN7yLokX9A\nZvYAcAnBUf8WM+sQnnLKlbnbzF4tt9nj4f1PN7PDzews4FeAevqLiIjUUSTJfwlB0sbMCoD2wL/L\nrT+E4Ei8Jj8n6OH/KkFfgX3T+HJlOobrAyB8duFEoBOwAHiA4P7+SRHsT0RERKoQSYe//wJeMrNz\nCRL/dHdfX279mcAbNVXi7jXere3uY6pYthT4XgRxSiOm0zwiItETyX3+c8xsCHASQQe8/6tU5F1g\nfgxiExHewZujAAAgAElEQVQRkRiIaHhfd/8A+KCadQ9HNSIRERGJqUgG+RkcSUXuvqj+4YiIiEis\nRXLkv4BvL7lWd93egfSoRCQiIiIxFUny30NwrX8a8HeCW+9E4ks9/kREoiaSW/06AL8HziC4v/8m\nIM/dPy0/xTJIERERiZ4ak7+7b3X3B9x9MFBAcCbgJTNbbmbXmFkkPyBERESkgahV4nb3xe5+JdCP\nYGz9e4HWsQhMREREYqNWyd/Mjjezx4CVQCbw/4AtsQhMREREYiOSW/26EAzvOwbIBh4DBrv7R7EN\nTURERGIhkt7+q4F1wHTgRWAvkFP5/n/d5y+xUuO40CIiUiuRJP90oBtwK3BLeFnlv8e6z19ERCRJ\nRJL8e8Y8ChEREYmbSB7so3v4RUREGpED9vY3s4iP+i3Qtf4hiYiISCzVdKvfPDP7q5kNq66AmbUx\ns8uB9wlGARQREZEGrKbT/n0JhvN9wcxKgYXAemAX0IZgsJ/DgPnAL919VgxjFRERkSg44JF/eGjf\n64HOwOXACoIR/XoS3PL3CDDI3Y9R4hcREUkOkfT2x92LgRnhSSTuXI/1ExGJGj2UR5KAhvkREYkm\nJX8REZEUo+QvIiKSYpT8RUREUkxEyd/MMs3sd2bWPdYBiYiISGxFlPzdvQT4Oep5JSIikvRqc9p/\nFvD9WAUiIiIi8RHRff5hrwJ3mdkAgpH+dpRf6e7PRDMwERERiY3aJP//Cb9eXcU6B9LrH46IiIjE\nWsTJ3911Z4CIiEgjoIQuDZ+6mYqIRFWtkr+ZjTCzuWa22cy+NLM5ZnZarIITERGR6Is4+ZvZpcCz\nwEpgAvArYDXwrJmNjU14IiIiEm216fA3AbjW3f+n3LK/mtlCgh8CU6MamYiIiMREbU77dwNermL5\nS4BG/pOY0SV/EZHoqk3yXwucWMXyk4BPoxOOiIiIxFptTvvfC/y3mQ0G3iK4t/9Y4CLgqhjEJiIi\nIjEQ8ZG/u08BzgMOI/gh8AegL3Cuuz8cSR1m9j0z+6eZrTMzN7MxNZTvES5XeTol0rhFRESkooiO\n/M0sg+D0/lx3f7Ye+8sBlgGPhqdInQIsKTf/dT1iEBERSWkRJX9332tmzxAc6X9V1525+4vAiwBm\nNr0Wm37l7hvqul8RERH5Vm2u+S8BDgXWxCaUA3rGzLKBj4H73H1GVYXMbBwwDiAvL4/CwsKoBbB1\nazGlpaVRrbNy/UCt66/NdnXdR7Tqqmsb7t69m1AoOnE3BkVFRWqLelIb1p/aMDoS1Y61Sf4TgT+Y\n2W1U/VS/WJyKLwLGA28Ce4GRwFNmNtrd/1a5cLjvwcMA+fn5XlBQELVAHvxwHlu3biWadVauH6Cg\nYFjMtqvrPqJVV13bsMmbs9lZuidmbZ9sCgsL1Rb1pDasP7VhdCSqHWuT/F8Ivz5D0NN/HyNGT/Vz\n980EHQv3WWBm7YAbgP2Sv4iIiNSsNsn/+JhFUTtvA5ckOgiJL/eay4iISGQi7e2fCYwAHnD3RA/o\ncySwPsExiIiIJK1Ie/uXmNnPgT/VZ2dmlkPQaRCCMQa6mdmRwNfuvtbM7gaGuvsPwuVHAyXAYiAE\n/BC4guA5AyIiIlIHtRnedxbw/XruL58gkS8GmgK3h9//Jry+I3BIpW1uBhYA7wCjgLHufl894xAR\nEUlZtbnm/ypwl5kNoOre/s/UVIG7F3KA57S4+5hK848Aj9QiRhEREalBbZL/vkf5Xl3Fupj09hcR\nEZHoizj5u3ttLhGIiIhIA6WELiIikmJqTP5m9paZtS43f7eZtS03387M1sYqQBEREYmuSI78vwtk\nlZu/Amhdbj4d6BzNoERERCR26nLav9re+iIiItLw6Zq/iIhIiokk+TsVH+RDFfMiIiKSJCK51c+A\nv5nZ7vB8NvBnM9sZnm8Sk8hEREQkJiJJ/pVH2KvqUbqPRiEWERERiYMak7+76/G5klDqYSoiEl3q\n8CciIpJilPxFRERSjJK/iIhIilHyFxERSTFK/tLwqcefiEhUKfmLiIikGCV/ERGRFKPkL0lB40mL\niESPkr+IiEiKUfIXERFJMUr+IiIiKUbJX0REJMUo+YuIiKQYJX8REZEUo+QvIiKSYpT8RUREUoyS\nv4iISIpR8hcREUkxSv7S4OmhfiIi0aXkLyIikmKU/EVERFKMkr+IiEiKUfKX5KBn+oqIRI2Sv4iI\nSIqJa/I3s++Z2T/NbJ2ZuZmNiWCbI8xsjpkVh7e71czUAVxERKSO4n3knwMsA34BFNdU2MxaAq8A\nG4HvAFcD1wPXxjBGERGRRi0jnjtz9xeBFwHMbHoEm1wINANGu3sxsMzMDgOuNbNJ7q4rwSnCddFf\nRCRqGvo1/2HA6+HEv88soBPQIyERSdxlZaQTcti4bVeiQxERaRTieuRfBx2Azyst21hu3eryK8xs\nHDAOIC8vj8LCwqgFsnVrMaWlpVGts3L9QK3rr812dd1HtOqqcxuWBPt69MU3+E6Hhv6Vjb2ioqKY\nfQ9Thdqw/tSG0ZGodkyGv6SVz/daNctx94eBhwHy8/O9oKAgakE8+OE8tm7dSjTrrFw/QEHBsJht\nV9d9RKuuurZh3oq3+KxoC8XNO1FQ0K9W2zZGhYWFMfsepgq1Yf2pDaMjUe3Y0E/7byA4wi8vN/y6\nEUkJaWbkNMlg4dotiQ5FRKRRaOjJfx4w3Myyyy07EfgCWJOQiCQhcppksHzdNxTvKU10KCIiSS/e\n9/nnmNmRZnZkeN/dwvPdwuvvNrNXy23yOLATmG5mh5vZWcCvAPX0TzEtsjPYG3Le+3xrokMREUl6\n8T7yzwcWh6emwO3h978Jr+8IHLKvsLt/Q3Ck3wlYADwA/AGYFL+QpSHIaRJ0T1nwqU79i4jUV7zv\n8y/kAI9nd/cxVSxbCnwvdlFJMshMT+OQ9s1ZpOQvIlJvDf2av0iZ/O5tWbh2C6GQrviIiNSHkr8k\njSHd27B1ZwmrNhclOhQRkaSm5C9JY0iPNgAs1Kl/EZF6UfKXpHFwu+a0aZbJgjVK/iIi9aHkL0nD\nzBjSvY0G+xERqSclf0kqg7u3YdWXO/h6x55EhyIikrSU/CWp5HdvC6Bb/kRE6kHJX5LKgC6tyEw3\nDfYjIlIPSv6SVLIz0+nfqRULP/060aGIiCQtJX9JOvnd27Dk82/YszeU6FBERJKSkr8knSHd27Bn\nb4hlX3yT6FBERJKSkr8knSHdg8F+1OlPRKRulPwl6eS2zKZr26Ya7EdEpI6U/CUp7XvIj7se8iMi\nUltK/pKUhnRvw5fbd/PZ18WJDkVEJOko+UtS2nfdf4Fu+RMRqTUlf0lKvfNa0KJJhp7wJyJSB0r+\nkpTS04wju7VW8hcRqQMlf0la+d3b8uHG7WzbVZLoUEREkoqSvyStId3b4A6L125NdCgiIklFyV+S\n1pHdWpNm6NS/iEgtKflL0sppksFhHVvqIT8iIrWk5C9JbUj3Nixeu5W9pXrIj4hIpJT8JakN6d6G\nnXtKWbFhe6JDERFJGkr+ktT2Dfaj6/4iIpFT8pek1rl1Uzq0zFbyFxGpBSV/SWpmxpDubapM/udN\nmcd5U+YlICoRkYZNyV+S3pDubVi3tZj13+ghPyIikVDyl6SX30PX/UVEakPJX5LeYR1b0jQznQVr\nlPxFRCKh5C9JLzM9jYFdW7ForZK/iEgklPylURjSvQ3Lv9jGzj17Ex2KiEiDp+QvjUJ+97aUhpwl\nn32T6FBERBo8JX9pFAZ1aw2gcf5FRCKg5C+NQutmWfTKzVGPfxGRCCj5S6OR3yMY7CcU8kSHIiLS\noMU9+ZvZz81stZntMrOFZjb8AGULzMyrmPrGM2ZJDoO7tWHbrr188mVRokMREWnQ4pr8zew8YDJw\nFzAIeAt4ycy61bBpf6BjuenjWMYpySm/R1tAg/2IiNQk3kf+1wLT3f3P7v6Bu18FrAcur2G7Te6+\nodxUGvtQJdn0OKgZBzXP0mA/IiI1iFvyN7MsYAjwr0qr/gUcXcPmC8xsvZm9ambHxyRASXpmxuDu\nbTTYj4hIDTLiuK92QDqwsdLyjcAJ1Wyz76zAO0AWcBHwqpkVuPvcyoXNbBwwDiAvL4/CwsLoRA5s\n3VpMaWlpVOusXD9Q6/prs11d9xGtuurahrXZV5u9e1i9uYR/znqNrVt31TrGZFBUVNToPlO8qQ3r\nT20YHYlqx3gm/30qd8W2KpYFBd0/BD4st2iemfUAxgP7JX93fxh4GCA/P98LCgrqH23Ygx/OY+vW\nrUSzzsr1AxQUDIvZdnXdR7Tqqmsb1mZfOT2+5u8fzaNJl8NovWZ1rWNMBoWFhTH7HqYKtWH9qQ2j\nI1HtGM9r/puBUqBDpeW57H824EDeBnpFKyhpXA7v3Iqs9DQWqdOfiEi14pb83X0PsBA4sdKqEwl6\n/UfqSILLASL7yc5M5/DOLVmg5C8iUq149/afBIwxs0vN7DAzmwx0Ah4CMLNHzezRfYXN7Jdm9iMz\n62Vm/c3sbuBHwP/EOW5JIvk92rL0828IuQb7ERGpSlyv+bv7U2Z2EHAzwf36y4DT3P3TcJHK9/tn\nAfcCnYFiYDkwwt1fjFPIkoQGd2vDw3NXsWP3XlpkZyY6HBGRBifuHf7c/U/An6pZV1Bp/nfA7+IQ\nljQiQ7q3AaBIyV9EpEoa218anfYtmtD9oGZs37U30aGIiDRISv7SKA3p3obtu/bidbjuf96UeZw3\nZV4MohIRaRiU/KVRyu/elr0hZ/feUKJDERFpcJT8pVHad91/wze72FWiR0GIiJSn5C+NUq/cHNrl\nZLFx+25OvG8O/1q+oU6XAEREGiMlf2mU0tKMQ9rn0LdDC7Iz0hn32EJGT3uHTzYVJTo0EZGEU/KX\nRq1V00xe/MVwbj29H4vXbuGU++dy5wvvs31XSaJDExFJGCV/afQy09MYe2xPXhtfwI8Hd+Evb6zm\n+HvnMGPh54RCuhQgIqlHyV9SRrucJtxz9gD+8fNj6NKmKeP/bwlnPfgWSz7bmujQRETiSslfUs7A\nrq155vKjufecgXy+pZgf/elNJsx4j81FuxMdmohIXMR9eF+RhiAtzTh7SBdO6p/Hf7/6MdPeXMOL\ny9ZzzQm9CbmTZpboEEVEYkZH/pLSWmZnctOIfrz8y+9xZNfW/Gbm+yxbt42vd+xhjwYIEpFGSslf\nBDg0N4dHxw7l4YuGEHLn401FDL1rNjc9u5R31nytjoEi0qjotL9ImJlxUv8ODOjSim3FJfTp0JKn\nF33O/769li5tmnLGkZ04c1BnDs1tkehQRUTqRclfpJI0M1o3y+KP5w+iaPde/rV8A/949wseLFzJ\nA6+tpH+nlpw5qDM/HNiJvJbZiQ5XRKTWlPxFDiCnSQZnDe7CWYO7sGn7LmYuWc9z767jjhc+4M4X\nP+DoQw7iR0d25sl3PiMjzXjqZ8MSHbKISI2U/EUilNsim7HH9mTssT1Z9WUR/3j3C557dx3Xz3gP\ns6Dz4I3PLCWvZRNyW2RXeD0opwnpabqDQEQaBiV/kTo4uH0O157Ym2tO6MXiz7Zy+d8Wsn1XcIng\nqx179iufZsEgQ7ktm5DXIpvc8A+D3JZNaN00i+zMNLIz08nOTKNJRnrZ++A1neyMNDLS1T9XRKJD\nyV+kHsyMwd3a0OOg5gA89bNh7NkbYnPRbjZu28Wm7bvZFH7dN//FN7tY8vlWNhft/yPhQNLTjOyM\nNHaVlJL+ykt0aduU7IxKPxIy08jOSKdJ+R8P+8osfJgmVkrWcb8kMz2NrIw0ssKvmWWvRpOMNLLS\n08nMMLLS08jMSCPdjDQz0tKCPhHBFHx+EUk+Sv4ildz61fXhd2/UafusjDQ6tW5Kp9ZND1iupDTE\nl389n22hLHaN+G92lZSyq6SU3XtDwWtJiF17S8PLQ2Wv696ewV7LIrvDScGyvcHybbtKKpTbHV5X\nUrrvNsXvBS9/X1Knz1UVM/b7YZBuhpUUkQakNW1Z9iMhzcr9cCj3I8LKlhOeNwzKylTYFifT9tKE\nErIIXjMpwcwotQxCpBNKywjel5uwNMxg30+Vr77axZOfLQyWhReaQ5qVkuklZHgJmewNv5aQESoh\ngxIyfS8GhCwNxwhZOm5pOGl4+H2INNj3mhasC2FBe3gphpNmIcwdI0S4pqCUhzAIv+4rF7wHJy28\njeGYhwAve2/hegAsPIeFXzHc0oJX9n3ob9c7BmnpwefAwp8vLfzZ7NvPSFrZZ/9iw0YWbf73t7F6\nKBzbt5/NypYFMaYRgvCjtb+Nh3B85WIti7nysspfwIqzVZUx83A8wUTZ+3Bbefl287L4yr7gVdT7\n7Xx4vdWwft98WX3ffoC2WYn5Aa3kLxIFT2XdEX73QsTbZJrTyTbTyfZCxlrIcNj3e6H8H6B9fyrC\ny7av+ActWuTA0cdAyU7YsyP8ujN4rbQstGcnoT078M8X4u54m564h/BQCPdSCIWCeXfwUNnkHoLi\nbwDHsnKCONzD8QR/UPe9x/f9GQ/eY8FQySHLDhIy6YQ8DfcgeYRCQXIMWXo47aUR2r2DEEZGVjYZ\n4QSc4XvCyXgPGV5CFnV7GuNe0tlLOqVksNfS2RsyQlvTyEwLkel7gwTPXtLQeA618lWiA0h+/+w6\nATg9/jt290Y5DenY0cN/qoJpwYJgKr/sttvc3d3Llx08OFj2059WKPuz3z7nt1x8W8Xtp0wJypZf\ndvrpwbLTT6+43D0oX37ZP//pvm5dxWU//WlQdvDgb5d17Bgsu+22/T7ThBunRvyZXjl2ZMWy69YF\nMdTxM5370Fu1+kwru/WJ6DNV/nf6+4ixwb4i+Heq72dyd193xiF1+3dq1WT/z5SGe+Ez7i/8j/vQ\nLPdTmrif39T9tu7utx/kflvL2Ew3tnAfn+P+ixz3/xnqfkd/94ubuV/YzP2Cpu6Tvuf+1zPcz2vq\nfm5T93Oaut/Qz/3vo90v7eR+ZlP3H2W7n9Pc/XeHut/2XfeR2cH0w2z3v45y/+v57qdnu48IT7cd\n6z7zWvez27qfmh1Mo7u4P3eV+/UD3c/Idj8z2/2spu6PnOt+3w+C/Y9qGsR0fa773d2C9jmnaVDu\nil7uz//S/bLD3E9o4l7QxP3YLPc3/+g+6WL3QZnuA8LT1OvcX5nk/p1M9+9muR+d5X7NMe7/vsv9\ngu7uJzZxP7mJ+9ltfdcd3d2vzHU/LTtYdkIT979d4f74L4Lthma5D8l0v+1s9yVPuR/d3r13hvsh\n6e4n93H/6F/uV45w75Ph3jfD/bAM97l/dp/+K/cjMt0HZrofmek+aaz7O391z890H5wZxDs6333x\n/7pf/B33IzLcD89w75/hvuwZ9/uvDOrsHZ4e+437f54M9ntwunvPdPcrRrqvft39hMPcu6a7d0l3\nH5jr/tkC99t+5t4pLZg6p7u/8qj7v6YH5bqmu3dLd7/t/7mvmus+JDeor2e6+8l93T96JfhMvTO+\n/VyvT3Of/usgvsMzgna+76fuix4LPsug8Oe8ON/93SfcLxoalO0XbpPlz7nff1VQZ68M90Mz3B+7\nI/hMh4aX9cpwv/I09w9ecD+1d7DfvhlBmy971v2284M6903P/T6Yyi+7bZT7e//nfmz7IM7DM9xP\n7+W+5O/uV51cMabXp7k/ckvwGfe19eRfuH/4chDTIenBdMHRwb/zBUdXjHXFS0H5ff9GvTPcH73N\n/c1Hv62zT4b7Vae6v/9P99N6f/sdKf+Z+oVjamH1zk/l/+4BCyLJkebeOH/p5ufn+4IFC6JW33lT\n5rF161ZmTTg1anVWrh+o9a1itdmurvuIVl11bcPldx0LQP9f1+40fK23C4Xgm7WsfWAk6V5K5x/e\nDJYWnoLTot/O75vCy165FbwUjrwAvl4NX68KXrd9HhxJ75OVA217QtuDoU1P+GAmpGfA928J1lc4\nfVjuvX17GrHouevJaZ4Dp90Dmc0hqxlkhqesZpDRNDhnXtm0EcHrJZGfnajTNkmgsLCQgoKCRIeR\n1NSG0RHtdjSzhe6eX1M5nfaX1FS8BTa+DxuXw6bl4dcPYE8R3faV+cdlta/3lVuhadsgwXc7Ctqe\nHyT5tgcHU/N2FRP85+EfqIdFftpvb+Z/QbPW0PN7tYutLgm8kSV9EQko+UujZh6CDcvKJflwwt/+\nxbeFsltDXv/gqD23HyyYCmlZcPafwyfVwtfBQ6UVrolXmGZeF5wBGP0PaNom8gDrkFzfHXSnjrhE\npF6U/KVx2LsbvloJX66ALz+EL1dwSMlHNPHd8NAxQZm0TGjfB3oOD5J8Xv9gatGx4tH40hnBa9uD\nI99/dsvgtTaJX0QkQZT8Jbns2QlffVyW4Mtev14dXHMHwKBND0rIYntaS9qf+dsgyR90KKRnJjR8\nEZGGQMlf4ubWr65n7969QIQd/vbugXULaV+6kaahYrh/AGxdS9mtb5YOBx0CuYdB/zOhXZ/gyL5d\nL8hsytpwh7/2R5xdu0B1bVxEGjklf2k4SvfChiWwem4wrf0PlOykPbDbmkDnIcF1+fZ9oH1faHsI\nZGQlOmoRkaSj5C+JEwoFnfBWz4XVr8Onb8LubcG69n1h0E+gx3A+fPYuSi2D/udMq1X1/Tu2ikHQ\nIiLJT8lf4sc96IA3/89Bwl/zBhR/HaxrewgcflZw+1qP4ZCTW7ZZ6T9+l6CARUQaJyV/ib1NH8B7\nT9Gr5MNgeNYXx0OrrtDn1G+TfavO0d+vrsOLiFRJyV/qpMaH32xbD8tmwHtPwYalYOnstmZs5CC6\nXvUytOlRaTQ7ERGJFyV/iZ5d22DFzCDhr5oDOHTOh1N/B/3PYu0fz2Tv3r10bdsz0ZGKiKQ0JX+p\nn9IS+OTVIOF/+BLsLQ6Gsz1uAgw4N7gVr55+c9DvAXiq3jWJiAgkIPmb2c+B64GOwHLgl+7++gHK\nHwdMAvoDXwC/c/eH4hGrVKF4K3y9klalW2jmO+EPfWDnV8F49oN+AgPOgy75OqUvItKAxTX5m9l5\nwGTg5wQXi38OvGRm/dx9bRXlewIvAlOBnwDHAn8ysy/d/en4RZ5iSoqDEfO++iQ8rQxev14JO74E\noAsQwqDnmUHCP/QHNY6e95uDfh881S8OH0FERKoX7yP/a4Hp7v7n8PxVZnYKcDlwYxXlLwO+cPer\nwvMfmNlRwHhAyb8+SvfCN2u/Texl0yr45jPKRtEDyOkQnL7vc2owRO5Bh/Lx07dRQhb9annvvYiI\nJF7ckr+ZZQFDgHsrrfoXcHQ1mw0Lry9vFjDazDLdvSS6UVYjFOKibQ+zu2Q3zKrdM+UjddG28FPm\nZs2M2XZjvllL+9KN8D9bgiP7ULnma9IqSPDdvgsH/SR4f9ChwWuTFvvVtcfurlWcIiLScMTzyL8d\nkA5srLR8I3BCNdt0AGZXUT4jXN/68ivMbBwwLjxbZGYfht+3Ar6pVE8kyyrPtwM2VxNrNFQVU7S3\nq6bsNuCzVlBYXT1Vt9dNVus2tF/VrQ3/fllExerahrXZtqZy1a1Plu9hdXFFc7totmFVy2tqV7Vh\nZMsP1K6p3IbVrWsI/5+7R1TK3eMyAZ0IziUPr7T8NmBFNdt8BNxSadlx4Xo61GLfD9dlWRXzC2Lc\nRvvFFO3tDlS2tusaUxvWZtuaylW3PlnasD7tmIg2jKTNKi9TG0a2/EDtmsptGGl71dSG8WrHqqa0\nyj8GYmgzUEpwNF9eLvufDdhnQzXl9wJf1WLfz9dxWVVlYqmu+6vNdgcqW9t1jakNa7NtTeWqW58s\nbViffSaiDataHmlbx1Kyt2FVy9SGB17XENuwShb+5RGfnZm9DSxx93Hlln0EPO3u+3X4M7N7gB+5\ne59yyx4GjnD3YfGIuVI8C9w9P977bUzUhvWnNqw/tWH9qQ2jI1HtGM8jfwju1x9jZpea2WFmNpng\ncsBDAGb2qJk9Wq78Q0AXM7s/XP5SYAz7dxqMl4cTtN/GRG1Yf2rD+lMb1p/aMDoS0o5xPfKHskF+\nbiAY5GcZcI27zw2vKwRw94Jy5Y8D7uPbQX7ucQ3yIyIiUmdxT/4iIiKSWPE+7S8iIiIJpuQvIiKS\nYpT8o8DMTjezD83s43CnRKklM3vWzLaY2YxEx5KMzKyrmRWa2ftm9p6ZnZPomJKRmbU2swVm9q6Z\nLTOznyY6pmRlZs3M7FMzS1QH7aRmZmvC/5ffNbPXol6/rvnXj5llAO8DxxOM2rQQGObuXyc0sCRj\nZscDOcBodz870fEkGzPrCOS5+7tm1oHge9jb3XckOLSkYmbpQBN332lmzQk6Jee7e23GFRHAzO4E\negFr3X18ouNJNma2Bjjc3YtiUb+O/OtvKLDc3deF/5FeAk5OcExJx91fA7YnOo5k5e7r3f3d8PsN\nBINqtU1sVMnH3UvdfWd4tglg4Ulqwcx6AX0JnsoqDVDKJ38z+56Z/dPM1pmZm9mYKsr83MxWm9ku\nM1toZsPLre4ErCs3vw7oHOOwG5QotGHKi2YbmtkQIN3dP4t13A1NNNoxfOp/CfA58Ht3j/X49Q1K\nlL6L91L1k1pTQpTa0IE5ZvaOmV0Y7RhTPvkTnGpeBvwCKK680szOAyYDdwGDgLeAl8ys274iVdSZ\natdS6tuGEqU2NLO2wKN8+4CrVFPvdnT3re4+EOgJXGBmefEIvAGpVxua2RnAR+7+Udwibnii8f/5\nGHcfAowEfm1mR0Q1wkQ8UKChTkARMKbSsreBP1da9jFwd/j90cCz5dbdD1yQ6M+STG1YblkBMCPR\nnyHRU13bkOA09VzgokR/hoYw1ee7WG7dg8DZif4sydSGwN3AZ8AagstP3wC3JvqzJFMbVlHH7yvX\nUd9JR/4HYGZZwBDgX5VW/Ysg6QPMBw43s85mlgOcCsyKX5QNW4RtKAcQSRuamQHTgX+7+2NxDTBJ\nRNiOHcysRfh9K2A48CECRNaG7n6ju3d19x7AeIIk95u4BtqARfg9bF7ue5gDfB9YHs04lPwPrB2Q\nzmQNWPcAAAncSURBVP5PHdxI+GmD7r4XuA54DXgX+IOrZ3B5NbYhgJnNBv4POM3MPjezuD+4qQGL\npA2PAc4DfhS+NejdqJ8mTH6RtGM34PXwNf/Xgf9296XxC7HBi+j/sxxQJG2YB7wR/h7+B3jU3d+J\nZhAZ0aysEat8Dd/KL3P3fwL/jGtEyaemNjwhvuEkpWrb0N3fQD/mI/X/2zv3YKvqKo5/vsgj0iST\n8BmgoICGMgopJUjOkKiZM8o0WtSA46gVpTxiJgYc02nwwfhAxihNL5HpjONUBlaiSGoDQlo8Qh5q\n+IB0oAwUEQVXf6zfsc3mnHvu4Rw43HvWZ+Y39+zfXr/fXr+1993r91h77+bsuAQYsN81an00+//8\nsZBZ037RpnXS3HX4CnDqvjx43CyaZzOwiz17tN3Ys9cWFCdsWD1hw9oQdqyesGH1HBA2DOffDGb2\nAf6ylOG5XcPx6MygDGHD6gkb1oawY/WEDavnQLFhw0/7p2CK3mmzHdBd0gDgP2b2GnAbMEfSEuAv\nwNX4s/3xWeFE2LB6woa1IexYPWHD6mkVNqz3YxD1TvjjZVYkNWVkvos/trID77ENrbfeB1IKG4YN\nD5QUdgwbHgipNdgw3u0fBEEQBA1GrPkHQRAEQYMRzj8IgiAIGoxw/kEQBEHQYITzD4IgCIIGI5x/\nEARBEDQY4fyDIAiCoMEI5x8EQRAEDUY4/yCoEklNkubWW48ski6StE7STklN++mY6yVNrLCMSRq5\nr3RqK0haKGlmvfUI2g7h/INWTXK8JmlKLn9Yyu9aL93qzL3AI0AP4JpiAnvjrMswCLi7wjJHAb+v\noQ5BELSAcP5BW+B9YJKkz9ZbkVoiqcNelvs0/s3wP5nZBjPbUoUO7SQd1BJZM9tkZu9VUr+ZvWlm\nO/ZOuyAI9pZw/kFb4Cn8HdlTSwkUmwmQ1DPlDczJnCfpeUnbJT0j6VhJZ0taJuldSXMlHV7kGFMk\nvZVk7pfUObNPkiZJejnVu0LSqCK6XCZpgaTtwFUl2nKYpNmS3k51PSHp5EIbgLeT6IJU57AidSzE\nZwVuTTKW8kcn/c+XtBL4AOgnaZCkxyVtlrRV0rOSBufq3G0mIdV7paSHJW2T9Eq2zRmZkTkbXCJp\nvqT3JK2SNDxX5gJJayS9L+lpSZemcj2L2SuV6SjpZklvJF2WSjo3s3+qpDcldcvkPSjpBUkd0/Z4\nSctT+Q2S7k0drYJ8wXbnSVqd9H9UUhdJI+XLMFskzcldGwslzZJ0Zzqnb0u6VVLJ+3ML2tNB0gxJ\nGyXtkPS6pJtK1Rc0IPX+AEKkSNUkoAmYC5yPO6peKX8Y/iGNrsW2U17PlDcwJ7MEGAKcAqzEv7r1\nJHAGMBD4J3BXTod3gIeBzwPnAhuAGRmZnwBrgBHAccA3gG3ABTld1gMjk8yxJdr8O2A1MBToDzwK\nvA50BjoCJ6W6Lsa/Gd6xSB2fSWV+nGSOTPmjgZ34p0W/BJwIfAo4B/gW0A/oC8zEOxlZe64HJma2\nDXgDGIV/4WxaOkc9cjIjczZYDVwInADMBv4NHJJkuuMfQrkN6JNs9Voq17OZ6+QBYHGy2fHA2KTL\nqWn/QcAzwNy0/W3gPaBvpo5rkx16AmcDy4E5mf2jgQ+BJ4DTgcHARmA+vrRxCvDlZLcJmXIL8evn\nrmTbrwNbgPE5mZkVtGdCOr9Dk82+CIyp9/9rpAMn1V2BSJGqSSTnn34/BTyUfg9j753/uRmZsSnv\ntEze9cDKnA7/LTiolDcqOamDU9oODMnpfgfwWE6XCWXae0KSG5rJ65KcxRVpu2uSGVamrvVknHXK\nG53Knl6mrIB/AaNK1ZfqmZbZbo871FE5mbzzvyqz/5iUd1banga8CP5RspQ3mWacP9AL+Ajonsv/\nLXB3ZrtHOo+3AFuB75SxwYh0jtvlbNcnIzMd2JW77ppI12zaXgiszbVpCvBGTmZmS9sDzMA7rGqu\nDZEaN7UnCNoOk4DFkqZXWc/yzO+30t8Vubxu7M5yM3s3s70IH4X3AjoBnwD+WJheT3TAHWaWv5bR\nrR9+419UyDCzLZJW4CP+WrAT+Hs2I02H34iPXI/AR8qd8VFlc3xsSzPbKWkTe9quZBl85EymTF9g\nqZll7fhcmfpOwzsrqyRl8zsBCzL6vSrpGtw5zzOzn2aFJZ0D/Ag/B11wG3TEZ04Keu4wszWZYm8B\nb5rZ5lxe/lwtzrVpEXCjpEPNbOtetKcJn3FYK+lx4DHgD2b2EUEA4fyDtoOZLZX0CHAz7qiyFG56\n2btlqYC6D7PVprrzeZXEyxRkL8SnqEsdC3wpoDnUzL5afZ97h5ntyuXNxp3+OP7/DfIncefXHPn2\ntcR2H5cxM0sOrlBGVN7OdqnMoCL6bM9tD8VH6t0ldbIUjCipBzAPuAe4Dl+KOA14kN1tsDNXnxU5\nZqXXT56y7TGzF1IMxAh8qWI2sEzS8OgABBDOP2h7TAZW4Te9LJvS36MyvwfU8Lj9JR1sZgXnfSa+\nBvsyfrPega91LyhVQQtZleobDDwNIOlQfO3//grr+gAfvbaEs4AfmNm8dMwjcFvub14ELsrlfaFM\nmb/hnYYjzeypUkKSLga+iTvLX+JLDOPT7oG4kx9X6BhJ+mrF2pfmDEnKjP7PBDYWGfVDC9tjZoU4\nlIfl73pYjMderK2h3kErJaL9gzaFmb0E/Jw9n21/CQ+Aul7SiZK+gq+r1or2wH2STk7R6TcB95jZ\ntnQTng5Ml3S5pN6SBki6WtKVlRzEzNbhAX8/kzREUn/gV/ga9a8r1Hk9METSMSr/PoS1wChJJ0ka\nBDyEdx72N7OAXpKmS+qTHHbhqYiiMwJmthYPkGtKUffHSxooaWIqj6Sj8VH9ZDN7Go/Z+H7mSYN1\n+P3yWknHSboMDwCsFUcDd6Q2jQR+CNxeRXvGy58c6SepNx5guhUPwAyCcP5Bm+QGctOvadr+Ujwy\nehke5T65hsf8M/APPOjwN/ja66TM/ql4oODEJDcfuAR/cqBSxuBPJDya/n4SGGFm+SnsclwHfA6f\nndhURvZy4BDgedzx38ee8Qr7HDN7Fbfb1/DzOA4/l+DveyjFGHxm5Bb8aYK5+BT/q/J1hdn4iPr2\ndJxn8Q5ck6TDzWw53qEcj8++XIGfy1rxAD4L8xzeCfkFJZx/ufak/e/gHYglwAv4LNd5VuF7GIK2\ni3aPMQmCIGhdpCC9G4DDWuN6tvydCyvNbGy9dQkah1jzD4KgVSHpe8BSfLbiTHxWpak1Ov4gqBfh\n/IMgaG30xpdsDsfXsGfhI/8gCFpITPsHQRAEQYMRAX9BEARB0GCE8w+CIAiCBiOcfxAEQRA0GOH8\ngyAIgqDBCOcfBEEQBA1GOP8gCIIgaDD+B2LxHTdqwHtRAAAAAElFTkSuQmCC\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x1108da090>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"plot_train_test_error(5)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 24, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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Ff5EEi7T81e0vIplLwV8kwUJ+HzsrwpRXhtNdFBGROin4iyRY0B97uI9a/yKS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\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x10df92350>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"plot_train_test_error(10)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 25, | |
"metadata": { | |
"scrolled": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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9ELIIZk0UERGRJiBsgvBb4E9m1j6WwYiIiEj9EPYRw9vAZCDLzDYABSV3unv/aAcmIiIi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\nSUVORK5CYII=\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x10db25d10>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"optimal_degree = np.argmin(test_mses, axis=0)\n", | |
"\n", | |
"plt.errorbar(training_example_nums, np.mean(optimal_degree, axis=1), \n", | |
" yerr=np.std(optimal_degree, axis=1))\n", | |
"\n", | |
"plt.xscale('log')\n", | |
"plt.ylim(0, 20)\n", | |
"plt.ylabel('Optimal Capacity (polynomial degree)')\n", | |
"plt.xlabel('Number of training examples')\n", | |
"plt.grid()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 2", | |
"language": "python", | |
"name": "python2" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 2 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython2", | |
"version": "2.7.13" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 2 | |
} |
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