diff --git a/.gitignore b/.gitignore index 6a058df..e9d8fd5 100644 --- a/.gitignore +++ b/.gitignore @@ -8,6 +8,9 @@ benchmarks/results/* src/ect/embed_graph.py src/ect/embed_cw.py +.vscode +docs_local + # Byte-compiled / optimized / DLL files __pycache__/ *.py[cod] diff --git a/Extra_Notebooks/CodingFiguresFern.ipynb b/Extra_Notebooks/CodingFiguresFern.ipynb deleted file mode 100644 index 42c35ca..0000000 --- a/Extra_Notebooks/CodingFiguresFern.ipynb +++ /dev/null @@ -1,1924 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "ec2a3c4f", - "metadata": {}, - "source": [ - "# Figure generation for *Invitation to the ECT*\n", - "\n", - "This notebook was used to generate the figures for the paper \n", - "\n", - "> Elizabeth Munch. An Invitation to the Euler Characteristic Transform. [arXiv:2310.10395](https://arxiv.org/abs/2310.10395), 2023. To appear: MAA Monthly, 2024." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c7dde292", - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "# import teaspoon \n", - "\n", - "plt.rcParams.update({\n", - " \"text.usetex\": True,\n", - " # \"font.family\": \"Helvetica\",\n", - " \"font.family\": \"serif\",\n", - " \"font.size\": 8\n", - "})" - ] - }, - { - "cell_type": "markdown", - "id": "e26c7194", - "metadata": {}, - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4640fcce", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'3.8.4'" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import matplotlib\n", - "matplotlib.__version__" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b4188598", - "metadata": {}, - "outputs": [], - "source": [ - "# Code to set colormaps to deal with the transparency issue \n", - "\n", - "cmap_viridis = matplotlib.cm.viridis\n", - "cmap_viridis.set_bad('white',1.)\n", - "\n", - "\n", - "cmap_binary = matplotlib.cm.tab20b\n", - "cmap_binary.set_bad('white',1.)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5192867b", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "F = plt.imread('figures/leafbw.tif')\n", - "F = F.T\n", - "F = F/255.\n", - "\n", - "F_finite = np.copy(F)\n", - "F_finite[F==0] = 2000\n", - "\n", - "# G = np.ones_like(F)\n", - "# G[F==0] = 1\n", - "# print(G.shape)\n", - "\n", - "F[F==0] = np.nan\n", - "\n", - "\n", - "plt.matshow(F, origin = 'lower',cmap = cmap_binary)\n", - "# plt.matshow(G, origin = 'lower')\n", - "\n", - "fig = plt.gcf()\n", - "# fig.set_rasterized(True)\n", - "fig.set_figwidth(5)\n", - "\n", - "plt.title('Testing')\n", - "\n", - "plt.savefig('figures/test.png', dpi = 300)\n", - "plt.savefig('figures/test.eps', facecolor='white', transparent=False,bbox_inches='tight')\n", - "plt.savefig('figures/test.pdf')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "55c62385", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "66d9a8a5", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[nan, nan, nan, ..., nan, nan, nan],\n", - " [nan, nan, nan, ..., nan, nan, nan],\n", - " [nan, nan, nan, ..., nan, nan, nan],\n", - " ...,\n", - " [nan, nan, nan, ..., nan, nan, nan],\n", - " [nan, nan, nan, ..., nan, nan, nan],\n", - " [nan, nan, nan, ..., nan, nan, nan]])" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "F" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6c5e8ecb", - "metadata": {}, - "outputs": [], - "source": [ - "def makeFernPic(F, theta, plot = True):\n", - " maxRow, maxCol = np.shape(F)\n", - " omega = (np.cos(theta), np.sin(theta))\n", - " \n", - " # center origin \n", - " Col,Row = np.meshgrid(range(maxCol),range(maxRow))\n", - " Col = Col - np.floor(maxCol/2)\n", - " Row = Row-np.floor(maxRow/2)\n", - " \n", - " fMask = omega[0]*Col + omega[1]*Row\n", - " DT = np.multiply(F,fMask)\n", - " \n", - " return DT\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9f80ebea", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "cmap = matplotlib.cm.viridis\n", - "cmap.set_bad('white',1.)\n", - "\n", - "plt.matshow(makeFernPic(F,np.pi/2), origin = 'lower', cmap = cmap_viridis)\n", - "plt.colorbar(fraction=0.035, pad=0.04)\n", - "\n", - "fig = plt.gcf()\n", - "# fig.set_rasterized(True)\n", - "fig.set_figwidth(5)\n", - "\n", - "plt.savefig('figures/test.png', dpi = 300)\n", - "plt.savefig('figures/test.eps', facecolor='white', transparent=False,bbox_inches='tight')\n", - "plt.savefig('figures/test.pdf')" - ] - }, - { - "cell_type": "markdown", - "id": "77423552", - "metadata": {}, - "source": [ - "# Trying Erik's stuff \n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "844cd027", - "metadata": {}, - "outputs": [], - "source": [ - "import demeter.euler as euler\n", - "import demeter.directions as dirs\n", - "import demeter.misc as misc\n", - "import time\n", - "import tifffile as tf" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2e2ec851", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "leaf_file = 'figures/leafbw.tif'\n", - "leaf_img = tf.imread(leaf_file)\n", - "leaf_img[leaf_img > 0] = 1\n", - "\n", - "fig, ax = plt.subplots(1,2,figsize=(20,6))\n", - "ax[0].imshow(leaf_img, cmap='gray');\n", - "ax[0].plot([200,200,250,250,200], [280,310,310,280,280], c='red', lw=4);\n", - "ax[1].imshow(leaf_img[280:310, 200:250], cmap='gray');" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "37c4e19d", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Complexify in 1.0271 seconds.\n", - "\n", - "Cubical complex made of:\n", - "53832\tvertices\n", - "99196\tedges\n", - "45167\tsquares\n", - "----\n", - "Euler Characteristic: -197\n" - ] - } - ], - "source": [ - "tic = time.perf_counter()\n", - "leaf = euler.CubicalComplex(leaf_img).complexify()\n", - "toc = time.perf_counter()\n", - "\n", - "print(\"Complexify in {:.4f} seconds.\\n\\nCubical complex made of:\".format(toc-tic))\n", - "\n", - "leaf.summary();" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b86a4b9e", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "53832\tvertices\n", - "99196\tedges\n", - "45167\tsquares\n", - "----\n", - "Euler Characteristic: -197\n" - ] - }, - { - "data": { - "text/plain": [ - "0" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "leaf.summary()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8e32dfd9", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[array([[-271.57746322, 89.89517387],\n", - " [-271.57746322, 90.89517387],\n", - " [-270.57746322, 88.89517387],\n", - " ...,\n", - " [ 259.42253678, -44.10482613],\n", - " [ 259.42253678, -43.10482613],\n", - " [ 260.42253678, -45.10482613]]),\n", - " array([[ 0, 1],\n", - " [ 0, 3],\n", - " [ 1, 4],\n", - " ...,\n", - " [53828, 53829],\n", - " [53828, 53831],\n", - " [53829, 53830]]),\n", - " array([[ 0, 1, 3, 4],\n", - " [ 2, 3, 7, 8],\n", - " [ 3, 4, 8, 9],\n", - " ...,\n", - " [53821, 53822, 53826, 53827],\n", - " [53825, 53826, 53828, 53829],\n", - " [53826, 53827, 53829, 53830]])]" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "leaf.cells" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5a52e965", - "metadata": {}, - "outputs": [], - "source": [ - "theta = np.pi/4\n", - "omega = (np.cos(theta),np.sin(theta))\n", - "heights = np.sum(leaf.cells[0]*omega, axis=1)\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c4f5d741", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([-128.46877882, -127.76167204, -128.46877882, ..., 152.25261331,\n", - " 152.9597201 , 152.25261331])" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "heights" - ] - }, - { - "cell_type": "markdown", - "id": "75ae5f49", - "metadata": {}, - "source": [ - "## Making pictures" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "db2a598d", - "metadata": {}, - "outputs": [], - "source": [ - "theta = 6*np.pi/4\n", - "omega = (np.cos(theta), np.sin(theta))\n", - "heights = np.sum(leaf.cells[0]*omega, axis=1)\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a048e87d", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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ed8V2r6eTTCa5995HqamuZdGi5TQ3tWDa1gmkQLOtFAcfPI677r65i5vIg4ddAru5+8NTKjzsEli2bDVr164jHk+4x5QykdnFlpQU09DQjGVZttIBIAiHI7z77kf069+H39/wi03aTiQSbvwBOG4Qu/2NdsnvvvsxX3y+xJEAaYGmKypvv89HYWEB7777Ma2t7ViWVLU+sFyrCcDAgf0BtcD++le30NERdtsD0HWdki0Elj7/3Gu0NLdhmhY+n+5e0xmOcPMf78pKG81ksfTs0YMrf3YJV15+PbNmzSMSidCjRylLlqzkwAP342dXXUIotH2Uiwfu/xdPP/kSjU1NaEIjlVIcHkoJUmMfCgXZe++xjBzZ/WWZPXjY5rBkNygVnvvDg4dtjkRCpRjiuAk0zVUp6uoayS/IJxQKufEQjtvBSfv26ZvXoYWwd/wiYwFxzPCFBYVdzr3zjodYvWad7fvXsl6C4uIifvLT8+nVu6fK+rADKB1mTykFbW0dPPPMZCKRKB9OnUlVVa1LjuW4SHJyQhx2+IGbyLlixRo+/mgWiUTKjZNw5DVNi0gkZrtxtC59KC4p4sOpM1m0aBnhcCemadHS0s7HH83i449n8/FHs7pxlr4c777zIc3NbRhpy40hyXB2aPj8PgYO7M/Vv/jRdpPJgwcP3QfPUuFhp4aUktdfe4958xZhGKbLCSGEwOfzk5un3AgP/O1xlixZRSqZdhd5h91S13307NWDn1x+wRbukmG5FMIOlkSSl5fH0ccc0iVzIhqJY6Rtxk1NQ1jStXCkUwYzZ3zO8BGDFXMmwlZ+bFeEZZGfn88+e48hPz8Py7KIRROuAgAquDKdNlm2dJV7zzVr1jH1gxm88uo7LFu6yiby0tyxwL6PtLICPYVypfgDfkKhEPff/wSNja32dcoiUFhYyKmnTGDCxCO6e9q2iGg0bo+zhiY0pDPeNs9Hr549+NGPz6dXry/nFPHgYadFd5BXeeRXHjxsG3z++WLuufsx1lWsJ5Wyd+gS1zJwxZUXApBOm6SThvpbtNkrBdKOTZAEA0GCwcAm7c+dM9+m5VZxCOo6DYRE13SikQQN9U307qNiMaTMYsdEw0LFS0gpiceT1NU1EonEMpTc9v2RGj6fzoABfbnp5l+597dLlrkvTQiKi4o49pjD3XP+ettDTJ0yA8MwiccTtktFc5UfXfNRkB8CIUi3h1HJpTrBYJCxY0cxoH8/liz+xM4IcWIXNPr06c0ppx3HK5PfJZ0y8Pk08vJyOfnUY7s126K5qZWPPp7N4YePdwnG1Bjb8Sgoa0V+Xg5jxoziRz8+t9vu7cHDdocXU+HBw86L2ppG6uua7PRNZzFSwZTFRcUMHToIwzAYM3YUOTmfEIvFslwO0nYNmDTUt/LE4y/wi19e5ra9ZvU6nvz3S5SvrVaKAQ7nhFrsIpE4b/3vQ0pKirn1z9fS0dFJIpG2UzXVbl/TfHa8BBQWFrL3PmOYNXMeyYThWkqy630UFRe7lo+6uiYsC7t4mUBoPvx+PwMG9ue8C86gpqae+V8sZe3aSmKxJFJaGfmEQ/sNBYX5jB41nLVrK8FRUDRBMBDk2GMPZ/36GhLxpK38KItAcUkx++w7hmt+8Sc++3Qhuq6RSCQZOnQQ0Vic8y84o9vm8IH7/83kl99mz71Gu3II4dRBUWNdUJDLMccexi23Xuulj3rwsAvDi6nwsNMikUjyz3/8h0gkmpVWKNygSp9f6cTPPfs6/33xLWKxOCDU/zQniFMtwJFIjM5w1yJdpmUxY8bnhMMRl3jKad9ZvHWfzsTjjkBKyc033UubTaOt5MnESgihYqt8Ph+trWEsmxkzQ+SkYVnQUN/Mq6+8h2VZvPzS20QicbctARiGBRKWL1vNL35+M7/4+c2sXVOFZWVKsWeXdtc0nX79+nL+hWe6fRVCw+/T6dGzjBEjh7BgwXJSNgmXrmv07FnGCSccxefzljBn9nzC4QjhcJR4PElTcyuJRLJb57G5pY3m5lbmzllAXV1jFhmYsBUylUL6i19extChA7v13h48bHfIbuCo8NwfHjx0Px5+6GmWr1irFlo7I0Paro+cnBAT7ViASCRKbU09pmUpfgepuQRYGUXBoqGhhY72MEXFTvClwDRM0oapPolM1ocQEAoFmXjckRx55EFM+WAG8+cvIx5PdiGTcoI7pYRkIkU4HLFTWZXzxc0iQWV16LrO2LEjWTB/GfX1LViWldWWZseJ5PLhh7NZvGgl4XDEzkLJyKXOBWdRHjlyKNi/RUJoBINBhg4dyGU/Pofnnn2DqvU17v0LCvK4+NKzWL1qHeVrqzBNw23X7/fRp3cPTjttYvdOpJRIBIlEEtO03PGTQF5eLvuP25P99hvLXnvv0b339eBhR8Bzf3jwsHOioaGFZCwFbqkse1GVqqT5UUcf4hxFRSboKprAyf7AcT5opJIGb74+FcuUPPSPWwHQBOiaXVnUDqzUsBA2UZTf52eP0cNJpdIccMDeWKaFrvlU+mNXqRBCo7i4kNNOO44PP5gNaGhIhHTtJeTl5fH731/FjTfcw8oVa2lra1fxDWSKgem6zgEH7EPNhnpi0XgmMkQ6rgLLrppqXyV0hBC88NwbxKNxdE2jrKyEy350Ds//5w2WL1+DaVhoQqOwIJ/jTzgSy5B8OnchZlplqGhCkpuby6hRQ/n9H36urDqdUQqL8unRo3Sr5qqpsYVUOk3//n1IJlPEYwmKSwrd8dGkci85fXX4NXJzc7nzrj8wZuyIb/u4ePDgYSeAp1R42GmhTOMCzVQLkq1PqABFCVpWJVHNfuHUz3CDNe1sBwmWJdlr79Fu+4OHDGDkiKG0t3WSThvOTRECdCAWS/LQ/U/T0RHh4EP2w0ybSEvFT2SqgkpbqRD0KCulV68ywFYphMomcRQQM22ycOFy+vXvzRefL8E0nLodUhFuSYkudNrbwnz+2WKMtOXeR2q208O2WuhAKCfEiBGDOfW0CfzlloewTIlAp7Mjxm23PkQ8nsQwnNgOSCbTfDhlDslUimQiqTJThCAvP4cTT/4ev7n+cp7612R+fsUf0TSNIUMH8Px/H6CktOhL52lDdR2XXfxbhBDc+pdf8/ZbH1NTU89d9/6enj3LSKdsGaTM6quFJnSlCHqMmR6+S/AsFR487HxIp9MYaQPb7p9lqcjU6HB8AcefcCRP/etlIpG4nVYpu7gynPTL3NwcTjjpSEDFa4RCQf5y+2+46PxfU1fb6FYIVZAYhklnZ5R15VV8OmchVVV19ndZPgiZ+VxRvoEfnn01neEMBbdrXQHShsH6dTVMPP4I3n9nGnGSXWIzcnNDHHzI/hx+5HjefWeaLY8dcJrVHijCrYED+3Lpjybxj78/S0NDEyAI5QTJL8ijoaHZ9stminOlUgapZJhs5OSE+P7px/HXu37LuWf9gmVLVxGJxFQ9E13Y7pkvx123/5NlS1eTl5/H++9N5603P6SxoZn1lRuYeNzhLFy4wnZNZfhDhFAVSEeMHMygwf2+8h4ePOwy6I7aHbsw+ZWnVHjYKfHjS3/P7Jkq3VMZ/dXCKoSgoCCfYycextg9VSnvocMGMnLUMNatq0EKCTJTatxZ1HXdx8hRQ+nduyfl5VXcf9+TjBu3J5dc9gMGDepHXW2TOtvVF9R1ubk5nHzqMfz1tkcwXaZODSGUXAiJ0ASWaZFMpkgmk5msj6wNuBDK1H/8SUfx5OMvE48ns+Ii7DiR3Bxuv/t3xGJx7GLmbh+cgBK3TSloqG/hlpseIJFIYJgmuqZhpE3FBSEd5UspWJZUrpjstjRdMGToAK67/ifcf9+/WTB/mU3E5dy7ax82hxeff5MpH8xW1UUtSUtrB21tYVIpk+XLy1m7pkrxatj31jRBSWkRAwb0pWfPUq773U/Jzc35Zg+JBw87I6SlXt+2jV0UnlLhYafE2jXrbb4HexEHd4fbv39fHnnsNkDRU198/m9YvHglYBMqYbkLvrPT9/l8HHn0weTkhLjz/x7l/Xdn8P47M/js08UI4XMJrJxdvZN6WVhUyIknH81fb/snLucEAqRiqzQl9r8FhYV5aJpOe3una1HJbquoqJATTzqa2279B4ahuCtw29TpDMe58NxrKSouJBZRmSy6rtO7d5ntghBUrK0ikVQWjlBOiM5wDMtyUm11pVRE4spNo+tuJoujkEkpVcyIzVdRV9PChKMuxrIs0mkTTeggoEePUk448SgKCvO3OEf19c388+EXaWtT3BjxWIo3X/+IVFK5OyxTEjeSriLmJJulEha5uXk88PAtrrvIgwcP3w14KaUedk5Im+AJ3S0QpoqEaayvrOP0U65k1coK0obJmtXriXQmskivdISmu9dqQqdHWSmHH3EALz7/Np989CnJZIqO9gjvvjWd6uo6Av6gu8hnyKh0nMJeThlxgf3uBoM69/AxeMggRo0ejuZmoHSVu7mpgyMOPpemxjYyFUnV9z6fn149S+nTtxftbR0q3kL4KC4q4u77/sAnM1/g2AmHo+s++vTuyd57j+bWP/+K7x1zMMFAQMmBliWjttH46ZmXyMjX0dFJR3uESGcc0AgEQwwZPJA//PEq7nvgxi/ljIhFYzTUN2OZINAxDJNYNGl/3uiethxIjVgswdrV64nHuzd11YOHnQJe6XMPHnYuvPjc2zQ2tOD6392F3C5J7tMpLCwgNzeH3NwQo0YPw+/3Z9XvcCiynXgKnc7OBFf++BbuueNfFBTkEwiEEAgS8RSRcJxQKKSUA5SyoLltaDz3zFu0NneQYbHUXFkc+UCwbm0NK5aVu4yVmRokqoy5kTJobmrPCiB1uCZ89OpVykOP/ImLLz2TjvYooKFrOn379ebzz5Yybu8zeft/nzBocH8OOWwcyYRJOBzl9zdeyaDBA9C1LJZNsbF82cezsi+yaqQgVBZKKBjkzEkn8PKL77P36FM5cJ+zOO+sX9PR3rnpRAmRUYyy23Lbd1xFai58Pj/BYAAhNKKRBI//86Xt8jx58LBd4QRqftvXLgrP/eFhp8OC+ctJxFNqUXdiDuw0z2AwyPe/P4H7H77RPf/kU49mwfwVGGn1h6jYGu3MDCGwLEnUJr8KhQL84OwTeO/t6bQmnXTVTOyCSlnNkEylkwZP/esVkokUmibc87v8Z19jmiZG0rSvx7acqHaxs1YGDOhDJBKnpblNOVKERjDgZ999x/L2m58AEIsmFLM3sH5dLU8+8SqRSBS/30dhUQHTP1aEXffc+W8OP2IcP73yh/z55odIJpJbkE+48RSuPEhbPkdW5a5JJdM8+cSrxGJx0mkDXdNobGzl7w88y423/AxQqb733/MUw0cMsoNQRKav2cGrkkxgLRK/38/oPYYR7ujEsiTFG5WU9+DBw64PT6nwsPNBZBZ119qgSXJzgow/aG+uu75rBcsxY0fQs2cp1VX14FJtO4uZYnrA3jUXFhZwwPg9WbxoNR0dEaSUJBJpN/NDvakF0ufzUVpWTG1NIxI3eRSxGfkCQR/DRwyiYm0VlpXOEOLZ8SAIVdL70h+fyeP/nEw2u4aUgs/nLSMnFOCIo8fjZLf4/YqsyufXSSZTpNNpmpva3CFqbwvzwftzaG5uJ78gj2QyjUBuVj6EijORwl7iXfkc9UsdTxsmaZt51LHUpFJp/vP0m/zv9U/QdUEqZRCLxTjhpCOzlBSlIGXYRt3JhKyx+/7px/KzX5z3rR4PDx52anjZHx487GRwCnYJMG1KZw0YMWoo/331/i6nPvXEqzz97zeIRVNoQkdKaVsAcBdtTahaIb6gzqmnT6C2ppm2ljCa8GFJU1UdFXbcBPZGG8jJyeWQQ/fjtVc+zMQE2Iu006YpBbqmM2LkEA45dF/WldfYmSFdoawFOp9M/YJevXvQ3Nhuc2NopFMGHe1Reo4sZcnCNUgpyM3NYf8DxnLvA9dTUJjHlT/+Ewvnr6CzM5qJJwVSyTTz561QWSi2XNiFyTQEiitUfVbKhK1gkfnRkigiMFtzcscP+1oBRMJROtojaJpAWhb+QACldugquNPtZ0Y2cHhFFL9GSWkxo/YY8nWfBg8edi1Ysht4KnZdpcKLqfCw00HLil1weC4FGsLaNL9x6gdzWbu6irbWsBvLkH2lE0OgCx+jRg7h2t9ewtT3ZtPY0IZlWrhBjVJHt2MDdDu2Ip00+GjKZ4SCQfeYcNvW3X9pQqOjLcL7b8/GMiyb2TMrlgENpCCZSDHv0yWYaYtQKOjGNvj9fkaMGEjffr3YUN1AUUEBhx66P0jBZRfcxPW/vo8H/3Ej48fvhe7EMEj10oSiGjdS5kbyqXs7/wmZ7RDJGl+3X5obB+GMn9O3zJFMICwWfDzlM+JO6fYuc6a58Rm60NGFTjAQYNI5JzDhuEN3wBPlwYOH7QXPUuFhp4QmBJZNQe3GBWib6sAjRw9hzsxFJFNpwLZOaJnNvCYUs6Wu+wh3xLn4hzdSXdWo2tR0e5GVdp0Om8vB1l2MtElbWyfjD9qTLz5bTjpt2JwSWta7wLKgvrYFXVcEW4l4GsNwGDozlg+E2oBEowk0TcfvD1BaVkT/Ab3o06cnM2d8gWlY7LvfHqxdvYG6uiZM06S6sp4H732WUXsMZc6sJaTTKbevLvUEG8ul3hUDZ8YV4qa6Spc/vAscigrlwnAqiWb6qoI6LSwLmpvbs5SUTF8d3g1d86FpkvyCHPbcewS/+NUF3fBkePCwk2M3d394lgoPOwVqNjRy9eV/5bTjr+bjqZ8jLZsG200TFXbKZ1dc/asLKCoucs+TzjXSKfqlrASGYVKzoZFli9fSGY6ptqTjEsi8O+c7sQ66phPpjKtCZVnybPyuCY38/Hwu/ckkCosLbaouDelwSNiugj59enLiSUegCR8lJcW8+/Fj7L3PaKZ//AWdHXEMQzL/85XU1jS5xF/JVJrZMxfzy+suZOSowWhCd/sqEGApuZw+OX3QhE5efj4lxUWUlBRRVFxIcXExPt3vyueklmb3x+ln1z4645qxdrjfb9RXKQXSEm6w7SGH7ccLr9xNXn7u9nqcPHjYgbAyBFjf9IWX/eHBw7fCF/OWM+2jz+lo71RWCtNCaBkrhe7TGDio9ybX+Xw6vXqV0Nrcjmlm6KyFk4Vgycy/AWk5ZFRORomGcMiycHb/me17PJZi2eJyTNO063TYWQ12fIIrn65z8KF7c875x/Pif97BzQqx29KERiDg57TTj6axsZ10ysAwLG76zYO0tYfJyQ1hmCq+I5E23JRWtVhLmhpaueLiW0nEkvh8OqmU4cqsaRkGUSfTQyDw+3UuuPhkfvXbi1zLTUNDC1de9hfWrl6PZVluyfdsdk93/MDO4BBZ52XKuTuhppngVfvaLiYQgU/X8fm8nxoPHnYHeJYKDzsFBPYuWDo8EQ7/gXJRFBUUcOXV52xyXVFRPqee/j1yQzloaCrmwCGksvktNDuYUENH11TbSPt7hLvzd+6p2URSzruqJJo5JkRX+TShMXToAK67/hKCAT89e5Xg0332NSqmoKggn733GcVVvzqPz+cuJZ00SMZSLF9awWlnfI93P36Ew48YR0F+HrrdZw3dLYwWCceZN3cZ69fVY6Sk23Z2XzeWT9d8BAIBCgrzKCzMo6AwjxEjB3Hu+ScyZOgAfHrAvj7TP3f8sttyxi9LLs0Zt43GZhNZ0ChfXcOG6obt/1B58LAj4JFfefCw45Gfn0uPnqX2Iu0QN/lcNsh0WvLZnOVdrqmuauC6n9/Lm6/OsP8GRRZJVmZxdZUATccfCKLr9vea853mvoNuWyQUDXdXeXS7VLjDWKnk8+l+jLTkntuf5Y+/fYShQwfSo2cZQuj4A36Kigs54+wJ/Ou5W1m6cC3hcMJtK52y+GTKF9x92zP89sZLOf6kIwgEg4D6PiNXJk1U02yyKs3ppy8jX1afpSX48L15vPna9C7j9pOf/YB7H7qOMWOHUVJahK757XiVbNKsrLa0bPZPm5HTZRLVlDwbsZgqOZXy1lDXym03PZ5Vj8WDh+8wdnOlwrNJetgp8L2J43npuQ+oqmxASokmbA4HFYFIMpZmyrtz+enPz+TBu19k1bJKqqrqqFrfSCwaU1kL9iJnWhINDVNadhooaEInlOtXsRFWEsNQyZZOzqMQdu6jdJwf0k4ZlXb8gGpDWk4ApHq3AMuEmupGajY0oQmd0WMGMXBQH9qawwwa1JeLfnQK5118Im9MnsZnc5aSThiqb5ZFe2sn0z+aT0FhLgMH92H4yIHk5uRipCK2FFlEXlnOGc2Rz+2rLR+ZNFrTlDQ3tfPh+59y2plHuWMthCAWTXHWuccxbGR/fveL+2lpbseyScOklGiaXYRMaGhStWmJjHsF1zvSlWhM2kXPsuVLJgw+m72cqe99ynEnHbJdnicPHnYYvNLnHjzsWCxdtJb//Osd1q7cgJAqpdTCVioAJ62gprqJKy/6PxZ8sYpIOIZpWoDK2NA0gbSN7lJIu7CYOiKEoFfvMhCQiCWwDHUcMtkK0lYmJKqSpmlaqi170XRSLC07bVXaC62STqjYLADdwjQlpXk5FBbmc+AheyIlXPfzv7Fy6Tr23m8EJSUFNDW2q527HZOVEwpRkJ/DhT8+lRkfzWfhF6sx0oYiqxJOdgpucTJXvuy+CpXRkl+YRzptUFpWxOFH7sOvbrhwkzF/6dkPaG/r5AfnHovf53MLsSklTBIMBkjEU+hZc+FGnWRleaj3bNUiI59P8xHwa+TkhBDA3BlLPKXCg4fvODylwsMOx3NPvstbr03HMiWmIfH57UVbU4HQmh0E2NYSZvrHC7FME6EJNF2xTsbjKXvRs+z0SZcuEk3T6Nu/Jz6fTm1NE+mUYS+GTpijvcO2QGgCKSwcFk5hk0QFgwG7VHkmMNGSAmUEsQMW7bTO3JwcevQoIpQTom//nkw44WBuvf6fGIaJYVhUrK0jmTQUvwTCtpIo28Oa1TXc93/Pcvb5x1GxZgNtrZ3KciI0+10gbZKrbPmcxV4gCOUG2WufkZx8xmH06FHMUceOIxgKuGMtpeTpx95i+dJ1WJbkw/c+zaJEV5aIYNBHSXEBzel2xYflKm0qG8ayzCxa7i3IJ6BPvx5MOOFA9jtwDH6/j/EHjdkuz5MHDzsUu3lKqadUeNjhSCXSWXU7HGIp0NCRGAh0LGkhTVAmAcWBMGRYHwL+ACuWr7MXWBVkKO3iWJYQBAIBQCMWSZKMG2i6ZrtXtAyngr0gak7qp3AWbZ1g0E9ZWTHhjqiiwc5i3tTQMC0ToSklqKAwh/GHjuWnV5/Jn3//BIlomiceeh3d52PUmCH07d+DJQvK6WyPZbgk0EEKOtqi/O+laeQV5NKnbxmm6SgrGSYNt6y7I589TsLh8xA6iXiaNcurmFNayAOPX9clKwOgen0Dzz35HrXVzfh0H4/c/yrRSCrTJ+GjuKiAfcaN5uMPPrczXZScwYAfn08nGo3brhbLTTElSz5N08nJCbHHnkO54c8/xu/3fmY87EbYzZUKL1DTww6Hy8goM5kD2eXHs1kdpVTH8gvy+OHFJ9K7b5mdJZHF6igz7I5GWlJf00JrS8R1YjhZDU5mhUs17dQZkU7WiU5xcSF3PvRLTjztcGXx0PUusjmBi5qmU9qjhDse+AX/fXoqDXVtNNS3IRAcdcwB3H7/L7jljivo2asYv99PNpslCCxTYhgW0XCcitU1RDvjNoeE7p7rEk1l9bVrqXYNaQo6OmIs+nwN0z9csMlYr11VTUdrFGmBaVi0t6h/O3wVGhrBUJC83Nwsp4+6VzplkUqY+HRVbTQYCKDrvkzgqhT4dB/9+vfkxNMO4+bbL/cUCg8edjN4f/Eedjjy8nJUBoVhZiwBdqyA5da0UG4Cn+3HLyrMZ9CQPrzZNNNeXJ16H5ob5KnqWWiYaQOfP7skuO0sERkXgiVBRwNh2mmU4NN0ysqK2X/8aMYdNIYXnv6Axx98nfbWTqws+TSh4w/46N+/J53hOMuXrCPamaRPv1IOO3pfikvyee9/cwkEfFx+9ZmsWlZNa0vYtTJoduyHZYdZmqYdICkc94iST8VQKMuIZnXtq64J/H6/cuMgaGnq5OXnPuLoieO6jPUrz39CLJpEQ8eyJKlkWgWhappdbMxRUIRt9VExExoall10LTcnh4OP3IuysgKmvPMZ4fYIPs1PMOSnpKyAi39yCudddgLBoH/7PkgePOwM8AI1PXjYsTj/shOZ8s7ntLdF3EUxU0siOwNBZRuEQgEGDe5L+epamprCSAt0TXMzHyATWNi1JkUmHsEpCobdvpBZVU3tyqLBnCBlPUp457XZaD6dgvxc/D6/y3GhdukaOXk5DB3Rh6MmjOP9/82lvSVCTk6QMXsOY/5na1i6sNyWT3LqWUdQUlpEe2sUy6XBdup0SNuFo0IjEdItme70LrPoK0It4dPw+XxIKRk8pA+tzWHa26JYhkXN+ibisSQ5uUEA4rEkG9Y3YjmmVSkwDStj+SBjNXLcLmSNoSOfkbJorm9nv3Gj0DUdTfORVxDiuFMO5pjjD2DiSQdut2fHg4edDlLCt02f3oXTrz2lwsMOxdqV1VSsrcPn86tURRx66MyCllEn1Ofi4gJuuesnvP3aLKLhGHaxCrK5HFy6acj63FXhcFgi3f93uC7sNpJxgwWfrWLFkkoSyRShYIBIZwyEhj/go0//Hhxw0CjyC3I59sTx3PPn56he30g8nkQDZn68GE1ALJZE96l7V6yqod+AntRtaCESsTLyIVRkKo4M2MyVjlybypebm8uoMQMZOKQ3/oCPSecfw/VX/4P2tihSQnNDO/95/F0uv+YMAP7z+Ls0N3YgTac8uXTvnYm9yGIMzfp39vgZhsnqFdVUrKklkUiBBDMliUeSjBg14Bs9Bx48ePhuwFMqPOwwJOIp/virx1m/rp5wR1QtlzJTaROpoQl7Jy0kQlOLXF5eDn36laJrylogsmpeaNJOLRVCxV9ItfdHqugDxdjp0HI7u3+ZyaGw61YoHglJKm1hGglMw8JMW1gm5Ob5GTSsN9fedB577DmEyjV1rK+sp76mDTNt4Nd8pFIp0mnLdq8o+SwLli+qxDQsLDt9U0iBLmzWTrl18qn4B9CFxv7jR3PkhH3o078Hg4f1USqCXaMjFk0S6Yy74x0Jx4lHUxlrTlZflSKn2+3bioat1DhxH5pQ8klpYSRN0kkDRwGKx1PM/HgpGyqbePK1G8nLz9n2D5AHDzsjdvNATU+p8LDDIKWksa6dzvYY0gRN19CFtMt6gybt1FKhkZOr6KZbWzpprg/zwF9f5sLLT+D1F6YT7UiAJdWijECTUtFHZ7eFhiUt97PakWfYFbTseh7SJoCS9jlSLas6OqHcID16FnPcSQdzyJF7ceW5d7N2xQYMw7SDK1FplVJDt+8jpURYICxIxNTOvlf/EqLhJLFo3E6bzeKD2Eg+4dT1wCakstTYxKMpXnhiCm+8MJMBQ3rx6Eu/RbcDXR0eDZFVhC3amVTjInVnAmCjvmpOIKhFpp2N5sKVRjr8FMpNk+hMsL68gWceeY+f/fbM7fUYefCwc8FTKroP7e3tPPbYYwD87ne/c49PnjwZgNbWVoYNG8bEiRO/9LiH3QfuIoa0d9jSsVO4C6KQAr/ux+/zYaZM4imTGVMWs9/4UQwe0oeayma1MNrnZrflpolK3AwKh85KCmnvyhWBlhC2jcAx+VvqbA2B0HV69Splz/2GULuhhc72GP+48zUqVtYgNMHwUf1Ys3wD0WgCaTncDdh+Ffv+jnxCMHz4ANZXNBCPJF3rghoLdUfHQmFfjWa3pbnygTQhaZiYRoz6Da3UVjVhpjNKEKYgGVdl0tdXNDB/zmrSCct1oDjuDVDkXY6lCClIJgx3/B25seVDai4fiHAlFeTkBhk1ZiAHHTl2mz83Hjx42DnRrUrF1KlTaWlpoayszD1WUVHBlClTePTRRwE47rjjmDhx4haPe9i9IJ3S4dJd6jPKBLYfXwpinSlikZQbb1Fb2czt1z9LTp4qimU5LgMpyThQLPw+H/hU6XPLctwKjmnfdi/YVN3SvtaOjsTm10RDIycvwLW3nMvLT31C5eoGqtc2UVSaT49eJZx10dEcddy+/OvBt/nwrS9UTINl2ou2dOVy3pGCJZ9XkkwmbYWKzHdklKIMG3YWBbZjWdE1QjmK1Mo0TDqao1x59n2EO6I4JeLNlGTejNVUVzZipA1amzptN5Du3sulAXOsImikExZrltYgTYHQRdZcSJf0yo4hdeXTdJ0hw/rx4DO/pqSsYJs/Nx487LSQ3ZD9IXfd7I9u5amYNGkSw4cP73Js6tSpFBcXu5+Li4uZOnXqFo/vaKRTxo4WYbeBqhGhKapqkQnQdBgZhM0/oaFhmRJp4mYqGIZFW0snsUiCQMBvKwki827/v7QUBwQOJ4XI4rTA4YlwLAOaazVwztd0jR69i5l08bEcf/pBNNS2YaRMJDB0ZF8uvfpk3nppDucf/xc62qJc9otTCIUU4ZbLtpn9LlUZ8XgsgWnHXGjuvTW3YmpmFDaWTxAKhRg9dhDn/WgChYV5WCYYpklHWwQzbboqlZSClqYOUsm0SlOV2e1lt5+RL+D30XdAGe2tEaXSyU3nIsPvIVyZiwrzuPaWcz2FwoMHr6DYtkV5eXkXy0VpaSnt7e1bPL4lJJNJksmk+zkcDne7rKuXVfPC4x+yz4HD+f4PDwOwK1aKr7jSwzeB7tPYa/8htLaESSUNVMwAYJvTNTvjw9lRZ94VpAXh9ngmKyKrIIW0lBXEsiSmYaHrdms27XVBcS5CQLgtBq5lQKWaOmb9YMDPgCE9+dn1ZzDh1AN45h/v09wYRtM19txvCIcdsxcP/mUyzY2dmIbBZ9NWMmrsQEI5QeKxJF0yS7LlAzuWwX63l/ZgToDBw3tjWpIN65qwLBVlkUqlEFIQCPnoO7CM0XsN4te3nMOrz06nrSWCYSiWUdWmkzQrAYm0f5yeeuBdIp0J1wjj1BAJhvwk4mmktBASjLRF5ZoGDMOws082mguRsaiEQn4GDO5JbkGIIyfuy8FHeW4PDx5UPZ9vG1PRLZLsEOyQQM3W1tavdRzg9ttv59Zbb91WIgHw8F9fY96MVUx94wsevu01NE3j0GP25Na/X7ZN77s7YtbUpfzj9tepqmhAmnY8AXZwJZnKmEjLrY3huEMc14VAIG0rhJYVw+A6EYRESN0liFIkT4JA0M85lxxDUWk+706eS+2GZsJtcYRTFcxWTALBIJf98hSOPeUArjn/7yz+ohxNaPQdWMb61U08vvRtOsMxsO/n8/no278MTWYov12hHH+Bc8QJJFW5KWrZNjX22m84v/rTJG6//jnSaYP6Da2sXFyFaVrkhEL85s/nceRx+zD7o2W8/dJcjGSmsJhiBs0Ee2poxCMGzzz0Pv0H98Cn+zAw1b01QV5BiOPPGM87L39GIp5QnhlTkoyncHkwNp4LO7ZC1zVGjBnI31+4xrNOePCwg7AzxjFuc6Vi+PDhXSwQTmeALR7fHG644QauvfZa93M4HGbgwIHdKuuGimZSCQPLsohFkggBa5bXdOs9PCjUVTdTubaeeDRpByA6aY12cKVzzA5OtJyCVTZZlbSVDae6qNpRZ/n6Be6uHdvNIYSgoDCXg44ewyVXn0BhcR4XX3U8PzntLhZ+Wo5lZfFVCEHvPiWM3XcILz72IQvnriUY8rHvYSOoqWyirTmcofoWwi6gVcaxpxzAq8/MpLMjrlw22fKJLFuLcIIzM/KZKZMZ7y3m4KPGcvujlwPwzzv/R/nyWqRpuC4HNX4thFvsNFy3r8rKopQMO+PFsFi3up5Lf3ESrzw1g1Q8rZQ0CRgwZFhfCvJzSMVTOLQYKrY0K9DVmQvUXPiCOsP36M9Vvztjt1UoIuE411/2KJVr6kkk0gwe3ptf3HIm+x8ykuULKnnjudkcecLeHHHc3jtaVA/bG9sx+2NnjGPc5krFxIkTuf76693PFRUVbgc3d3xLCAaDBIPBbSbn/56fTXN9B06pJuWTltRXt/LeK59x4lkHbbN7754QXf5zqK0Adw5cb77uo7g0h1gkoYp6OdkZZBM2SZvimwxhU1YrGgKpCYbv0Y/r/nwOv//x41SuqUdKScxOBQ0G/RSXFZCXH0LXNc67cgL/+OsbLJy7BoHgR786hXkzVlBX3aoUIOFGFRAI+NjvwBHkFYQ4fMJerF5cTdJMZ/UVJU+WfLJLL9XncHuMe/7wIovnlfPb23/Y5ftUPM0rT07j8Il7uffOxG1kMjGyxw9wlS83ykMqRUTTdfILcl0uDU1AUVk+eXkhotEEHS0RnMwODQGaRn5BDuOPGM2N911ISY/dS6H4+O0FPHHPW7Q0daLrOi2NHRiGSSAYIDc/QF6B4uao29DK4nnlDBrey1MqdkNIK+N2/DZtbA0mTZpEa2trlw36luIVKyoqNnu8uxWLbs/+mDJlCu3t7QwbNoxJkyYxbNgwzj33XCZPnkxrays33HADwBaP7whUrqnn+X9MVbvm7J9pCfFIihUL13tKxTaAkE6qIlljnglodCpgCgmYZDFtZuISMimN2PwONmSW2iJVmfSiknzKehTxi0kPsGF9M6lUGsd2oGkag4f14c4nr2DwiN4s+rSch297jaVfVIKAvccPZdJlR/HSEx+7wZBdlnQLpr+ziFlTlhKLJDDSZlf5HC6IrL4jsxZ5+9/SlHS0xlgybx3trRFmTVmKmVYxE0ZaWR2kzLhSBMLtq4aKqXDbdZQK20SSHTgKICyVFaMCU1VrhQV53PqPS6lcW89TD7yHZUnSKQOfXxVcO/6M8Vz1h9O7/VnYGTH1jS+YPXUp9dVt1FQ1E4smCLdHME3AtpiV9Cjg0O/tyZ8evgRNy2QteVFYHroDG8cObs3murviGL8pulWpmDhx4ma1nkmTJm32/C0d396orWqhqS6sfPtCszkLFImS5v1EbBM4GQRu7IFia1JLnpNmaRNVSVMFVKo50dz0z0zchKNWkJ0NCijSJiEEZaVF/OzG7/PiYx9TVd5kL/KZtnShs/8hoxg8ojfplMGjt7/F6sUbyMsLUVCUS11lGxcefTutdWGEZT8jVuZZMZImTXUdasG33QuaHd7o2CEyfbff7T6qXAyHsEpdW72mmUsn3kVTfTuW4fB5kJVu61yrZRQMNz3VkU89t/VVbcyfudZm7cyMdzKe5p0X5hINJ+zj0LChjd9e/BiFRbmMHjuImx++2E1d3R1Qs76Ze65/icrVDSTiCSKRJJZhkU6l7WdFKW/+gEZpryJ+8puTOf2iw7u0oZ4/zVWYPexm6MbaHxu7+G+55Rb+9Kc/fe3mvkkc4zfFbs+oKaXkvRc/I50wXb+7Jh0SIsfw61WI73YIJzhTc3fJDlz/vR186bgGNIRbydNhcRDuH2/WD7gEoanrNV3HSBsYSYt/3f0ezY1hLNNu2+FoEKgCYPsOYsm8dfzztjdZPn89PfqW8MeHLmTFwiqefuADWptaSCdNNM1WhTZ5VrICSLOIq7rIly2urXg4TJpOm5YliUeTxCIJO+U0Q+AVbolz+69fYN70VZgpm9PDdalkFBTstpDKFJuIpdxnWQiB7tcoKMhhQ0Uz6bjlPuNGyqKtsZP25gh1VW38+pxHuOIPp7LfoV1Txb8LsCyLR//vLQYM68nKhdVUlzcidMGC2WtIJtIITc2FJjIptHpAuYCG7tGX39x+NiP27L9pwxKiHUlmvreUH1x25G6llHmgW2MqqqurKSwsdA9vTQhAd8UxflPs9krFJ28tYvbU5Zhp0+ULkFj2j4gFJiyeXU5rUyelPXcvH/K2RP9BZZSUFpCMtoGzJNsKQtZ+m4xh37L/ZWciCInu07EsS/FQbJRyqgmd3LwgCOhMGUQ6EoTbomiahp5lO1BKhaB331IsQ3LrFU/T1hohNy/EDy49kn0PHs6+Bw9nrwOG8uAfX2XlwipMQ91PKQRWF/mkLZ8UymXh8+v4AjrpZNq9LhM9kokf2VxfN1KfkEAyluKzD1fS3NCBZVnudbJLW5mATQQMGNyLw4/fi+ce+hCn/kleToiefYqpXF2vWrB5QrLnwkimWf55JY//9W3ufenKXX5xTKcM7vntS3S0RPn5raezdF4lrz81G59PEI+lME2Vx2emJQ6LycZzkZ+Xwx1P/ZT9Dxuxxfv06ldCKOSntrKFWCSxy4+bhx2HwsLCLkrF1qC74hi/KXZ7pWLOB8tIRtN2IarMT7pT1glLUrGqjqu//xAj9+rHNf/3A0p7fb1J9rApDpkwljH7DqKppsNmugShqSJeGwdqOnOhIdwMBb/fx+BRfWhr6aSlLuzqE06uhQZoIhP46SzZXYIZVZoDAM117Tx+x9vEOpOM3Ks/Z/3kSD763wLef2kefr/OmP0H88hbv+K8Q/5C3frWTeWzSawsx4Vj/79P18nPzyGcNpHCIjc/RCphKB4IyCK/2lJfu8acIKGzI5YVX5KVuCoydjXX6SIljTXtrJi/3lUeNCHw+X1sKG/CMmzFxPUeZbcKlmGxYv56fnf+Y1xx46nsOX5INz8J2xbLvqhk1vtLmfSTo5j21iKmvjYfy7SoWFlHPJYk2hFDIhVvh65hmZbiptnoWUET+AN+hozsQ2Fx7pfec88DhrD/ISNYNr8ym1bFw+6C7Zz9sbPFMe7WSkVjTTsrFlQhLcv1lwKKREg48fqQihtUrWmgobqV2nWt/PTGkznomD12nODfEQwc2QufTyeZVEoFlu2OBJu+m03mQkqBJiCUG+Dnt3yfWVOW88Hkz0kn08SjKTc2Q1qQjBsIzQ7+tAMjcRZQe8H2+XQM0yQeSZJKGAwf25/SnoX8+673aKhpI5000HSN5rowV9x0Ko5Ws8mzIu2vbK3C8cqkEmlaE4Zy32iCA44aTWtjJysXVJJOK16MLvLJjHxOXx1GbWmpviViaVfBQAib0Vf9kLnuXEdOCyLtcRbMXquWSUsgdEhEU6STBtJyskOce2aySCyprCqJRJrFc9bxyK1vcu9LVxDciXfei+dW8Pm01Zx71ff48NX5PPfQR0Q7E9RUtLD8i0oSsTRISc26Znu9l67yJS252WdFaIKcgiDjjxrNnx+/VAWtfgUsKelojjHtrcWc+aMjtm2nPexc2I5Kxc4Yx7hbBwssnVdJc21YlX+2bLOxJewAQeUv16Tufk7FDVYv2sA9107m2fs/3NHi7/K45FfHUVJagC50lFPC5pNw5kJuOhcqhkFDFz6EpvHL287kxU9v4tTzD6WoWKVDqjkTGCnTJYdyKapNZ++po0kdn+bDr6ny6T7dR1tjhM8+WklNRYsqviXtZ8JSq3uvvqXowrflZ8XpA7odE+KUNdfQpEbA7+PiXx1H3wE90IWOsDaivpbZ8jnF1nT3mBMA6BzXpIYunHPscczqq4ZGTm6Qnr2L3RgWaQnMtEVOboi8vByXtlyTGhqbzoWQage/euEGbrzoSVYtrN7Rj85m8dq/ZvHXq1/gw9cWMPv9ZTx17wfUrW8l3Bpl5jtLaa4PK6XPfa40RY7m/qdv8qxoQiO/MJeLfnkctz52yVYpFKCsY5H2ODPeWbqNe+3Bw86F3VqpyC8MUdKjAF2o+gX2zzSayCwNAmVGd1P+LGjc0MYLD3zEHVe/SGtj547uxi4LXdfp2acYv66TyQXJzIUmNzMX2CmiNk+DrmsUleZx9V/O4Klpv+XkCw4hFArYWTyZa9134XwW+H06RlKlfmqajpEwaK3rJJ003XtotgujrFcRmqZx1k+OJD8/Rz0rYlP5dPtZcd41kbmnQLDy82pefXQmZspC13T3O13Tyc0NUVCUR0Fhjq1oZdrS7LZ0oWX1RXTtm3tcz5JPIxjwM2rv/ggEPk0j4PMxas8B3PSPC9hz/BAlh6O2iOy2MnMhpCARS7NkbiUfv75oRz86AITbovzn3qlUlzcB8NZ/5lK/vpXO1hiff7yazpYYmBIsSCcMjJSFJlzVAV3Y6pM7pl3H0afrFBTksP+hI7nwmon4A1tv2HWDYrdV5z3svPBqf+y+OOjYPThkwhimtMaJdSYwbH++rmsIAaZTUyGbAEECliQWTjDzrSVomsbvHjxnh/VhV4BpWjz51/dYu7QWAfTsX8xPbz6ZguJcTr/0UJ7724fUVrYokzu2pmv7/jNEVrhzIaWTvZGBz6/Ta0AJP/3Dycx+axnN9R2AE1eRUUICOX6kaSEtVXvE55P0GVxGS10H0XAcpER35LBdD737FnPKRQeRWxAilONH0+wlI4tjI1u+jSFtN4WwBC11YRpr2pVcprS5DQTBoJ8TfjieH/z4cCrXNPC3a1+hoy1qu4GyqpJIm2EU0FHuCk0TNi23sImslFQOE2k8nGLulBW2IuVjzPhB3PCP89CFRlP12wjkJmMthKrDotrUCAYDaLqguCyPkh753fVofCss/bSS6W8uZuncdfzoxhNpr+9EWJBOmCyaVa4K0GVmB8jMBZaibJdZfc5+VnRdp2f/Io45fV8u/PXEr13/xyl137CujbrKFvoOKfvKazx8N+C40r5tG7sqdmulAuCKm09h4LCevPPsPGoqGtF9PorL8jAti/qq1iz/Ntm1lMCCRCzFrHeWcp9P40c3nkhx2c7xY7uzoWFDG1Nenk9rfQfSgtyiEBXL6hi57wAu/f3xLJtXRUt9GCNlgbRst4Gd7SGcDA1wggfdbInN/N0FQ3569CmkvSlC2jTUeUJZAkI5fsYePISmDe1sKG8iFAowdGwfxn9vJC8+9Amas5C66Z6ABpYhWTi9nAXT1tLWHMVKWUpJEXY2isjOJHFDHVSsg0pUUeuYtOMiTInQhWttwLZAFJfmM2RMX1IpE11Xu2WJcGgvMmmoApBKEVB03Ep50ISqyqppGghFY64DQkoa1rdjpEwCfh8yLfnnTW9St76V9saIcjdpXZ9xR7nOKwxhWZK9DxnK+ddOQNc0Ru67mTTK7YxVC6uZ/M8Z1Fe2EG6J8ca/ZhMNqxTcVCxFk10kTXPGz/67defCeaTsvrqMo0IjmOOn/9AeXHr9CRxywhh8vq1zeWRDKY2KX2XKy/O5+LfHdfcQeNhZsR1jKnZG7PZKRTAnwBk/OZyR+wwgGo4jJZT2LuDdZz9j5rtLaW+MYFoWQmR+lRy+BCklkfYYM95cQtXqJi7/0ymMHT9oR3dpp4MmBPlFIVrqOzClRbwzwcr5VdSsa2H9ykYuuPYYVs2vonptI1Yy68deqB25U9kzu8qnCi7ctJSfP+Dj6NP3pXZdC5GwJK8wRCqepkffIvY9bBh5hbmsW1ZHYUkuB03Yg8v+cCL3XvMyiWha7WqFRGgCYdq1Rixob44w652l+Pw6qZSRlR3g7F4zTCYOSwUI0DLPirIgOFTiwl29s/vqtiZUJoyzO85qUd1BEwgz67jLT+5YG3DlU4Y1werFNSRjaUCyakE1QsNNcXXH05ZTCkEoL0iv/sVceO2x5JfkMWqf/pTs4JTqN5+ay4a1TfzgyiN46PrXWb1oA5YlCeYEWLe8DstSoySlVOnJQnT5u3VsPpm5sDNsRNZsChg8she/eeAcRuz9LZQnoZJzLctCmrtwyUkPHr4mdnulAtQP6l4HD+lybOCInvQf1oM3/j2H+soWRVAkMuZm7J2NaUkiHQlWfl7NfddM5geXH8HJl3iU3tnoM6iUMeOGUF/Z7pYEt0xJtD3O8s8r+edNbzN0dF9MU1JX2QpSYpmKBllYFsImqnIgBBSV5OHz+1g5v5oPnv8cw7AQmqCkRz6tTZ1omk7/IT04++dHkVcYorM9zsJp5XzxSTmJzhS9Bpbwy7vOJCcviJE27QUlEwfhkG2Z0sIywTLU7hYzw+mgaRqWtBOQ7UpmjlVBWSa6PisZdk27sijYRclU1kH50nq33LkiYsuwZ2q2QiKFI58aF2FTZwmp4iekLtF1HctUJF0SiZW2SKUtHJ+OZWLfE3RdAzeNV/Ul4NfY68DBXHrDiYw5YOdQkld8XsV/7p6KT9eJhhM014Qxkha6TyMeSdGwvgMzZdlWmk3nwvm7tbYwF8InyM0PIaVk4Ije306hwFbqhIY0BeVL65Si8zVdKB52UXiWCg+bQ05ekLOuPJKKpfWkoinamqOun0xRKiszvUSVgzYNg/rKVv5z9xTqq1o55xdHk1+cs4N7sfOgZ99CND0TCCftxdBMWtSuaybaEeOkiw+htTHM9NcWEe6Io2sa0lRmfcuylQwBoVw/PfsV8/nUVXz+8Ro2rG1GaGCkTXr0LSKdMtAkHDRhD0679FCMtMkfz3uK1Ys2kJMXoLAknxF79SOUG+Cdpz+laUPYXeRxF3wLh0ZKty0BKmhXc9k4ldlc2G4T6Vb/dKwPOmTaEooqy3HHaNgKAmrhN1MmaxfVMPOtpfQZXEImE0RBuEtgRiFxmDOVfOq+eXkh8gpzaK5pt5UitXhaTgl5e7FFKpq3rvKBT1exKVf93+kMHt17Oz4hW0Y8kuSxP75NuDlKbmGIxup2ErGkGwSbihmYKcddphRWYftzskNcNp0Lm0RNE+QX53LWVUeRX5jDAceM/FbyppIGNeUtaICVtuhojtFY3U7vQSXfbiA87BrwlAoPW4IQgqv+7zRe/nshH768gJa6MKaZ+fFyMkLUoicwUgZtDRGm/ncBlcsb+PEtJzJ4j53jh3lHIxj0k5sTINmZdMfMWfTMtElHU4x5U1fSb2gZAkFeboic/ACt9WEyNESAhGAwQEdjhDf/9SlSWhjJtE2cpYguLMMiNy/EoBG9aKkL8587p1Jb3kJufpAJZ49j3FEjyCsKUbW6kU9eXUy4JaJcEFrGceDI58RvSPuYE8OgFvXMcYeMytmRCk1gOc8KIkOulkU9rpGJixASou0JPn1vBWdccTiakG5dkY3pov0+XSlbrnxqsdQ1jZ59iyntWUBHUyfSBNDw+XWE0EFCOm2oPmbLZ8d0+AIapb0LOPzEsTtUoYiGE3zwwheM3Kcfex06lCdve5/6ylastIU0LMoX15CKGmhk4iGERSbfwlYAnSDMLc+FAKmhSUEoGOCUiw6isDTvW8v/+dRVpBMG0gBfrg9/wOcpFB52G+zWKaVbg/ziHC698QTGjh9MYUmuygzBjrIXGV+4a+60LDqaoyyaWc7frnmFTz9YuaO7sFPglMsOpteAYvx+X1bZ7ky6rmlYVC6rZ+YbS4hH0uQWBOk7pAx/QHdLmmuahj/gJxFNUVvRQiqRxkhbtu9cMR72GVhKn0FllPYp5Niz9+Ph3/+P6f9bTLgtSkFhDkVluUQ7kwzbqy+DRvXi2HP2o6RHQSZOQoiMfHb8g3tcau5xJ1DTNhK4x3y6prIxwG1L2/hZEcK2ujjjoP7z+TVCuUFiEVWnQ9NEVlwFbs2OYMiPruubyOcP+MnLD9pWC4HQNAIhH30GlrDXYUPp0a+IYCiQadMNNhXk5Qc58NjRnP7Tw7n4huN30FOi8MQt7/D6o7P495/fZ92yej6buoqOtihCCJLxNLHOpB1Uupm5yDqmsriy+rrx361QzKL+oJ+c/K+uqbC1GD9xNKFcPz6/jpU2ad7QzqIZ5d3WvoedHA4D3bd97aLwlIqtgBCCq+78Pkd+f2+KyvJt8zE4oXPOu/v/UpKMp1i3vJ7Hbn6bNx6bTSKW2hGi7zQoKM7lot9NoLA01x01d/xsn7eRMkmnTGVtSFuU9Mx3AxAFGj6fRmFxCJ9fxzBMdak9F0II8opCnPuro0knDcp6F/Dfv33C+hUNxDsVW2b12iaeuX0q/7lzClWrGhFCcOIFB9JrQDFOECTYGQK2YNlecOFmoIgs2R13hvpTCuYG3FoPzlmyy7OS3W7mHQHJeJp5U1cx/bXFXcbHtdPYrgyfT89cn9WsmTapXNFAxfJ6TMPCH9AZMqYP/YaWUb2iibaGCEbKyArmtF+aRjA3wB7jB3H21UeRk7f9GDNrK5pVHI2NpXMqWTSjgpa6DjrbY7z+2Cyaa9pxYnKlZcfb2GMqsufCfnfmwoludfu50d9tbm6QPQ8dwoRz9uesq47sFisFQCDoo/+wHqigUWhtjPDR5IXd0raHnR/S6p7XrgrP/bGVKO6Rz8/vOp3Whk4WzahQ5aKF+7uVsVaATfMLRtKkobKN1x6eSW1FCz+747Qd2YUdjgMn7sHYAwez4JM1xCIpnPBLgUBI2WX8YuEklcsa3KA6C5XaGQ8nSafNjK/cUtfpdvDmF1NX07yhnWh7nCWzKpBScVhIU2IkTKy0pL0x0iWPXFqZOAjNXaiF6+ZQgZIZF0ymdLljTscJl0R3XCjO4mVJ2yKT1Ve3ugdujIOQAsuyCLfEaK7psMucO3fMKDuWKUnE0limRNcz5dI1VKaKaVoEgioLxh/wUVicS926VtpskjbpKBQy08dgnp9QyM+i6WsZOKIHA0b1Ysh2cNslYikev+kdhCb4/RM/JBDy89a/59BU2w4WpOJpqlc32a6ezPg5abzu35r9WRNO7RR1npQO/4bMmgvhzoXu0zjmzH04+ZKDu7VfUko6WuJodgCuz6/vFGm4HjxsD3iWiq8BIQQ/v/N0evQpVGZumSng5DI+SvVZtxcWaZi01IVZ+MlaPpm8kHTK2MG92HEQQjBm3CD8AZ87Ztmv7PGTpkUqlnIXQA0QliSVMJCmZS/0aoHUBeTmh9jrkCHUrmshGUsRaYsRbU+QjqVdVkXNuWYjy2IgoGdcExLbPw8CmZHNliF7frUsGTShlItUJE0ykuoin+PHd/sqN31WnLbMpEnVigaMlGEvnnRpS1gSM2mga1ltu2Mkyc0PMnhUL3r2LqJXnyLWLa2jsarNVXy7yGwrLum4QUdThOVz1vPwda9z7+X/ZfGMCjsTZdvh6b+8z/LP1rPysypee2QWpmFSv64VDBUb01bfyfpldUhTZvVVuJYkd/zssXfGQXT5LLuMn08IdE3Dp2n4/fpGtqjuwWcfrKRubZNNvgVW0mDFp+u7/T4edlLs5oyanlLxNVHWt5ALr59AfkEIkOqHOfuHLstP7u5upaR+XStP/fl9nv7z+6xf0YBpm+93Nxx91j4ccMwo8gpCdqpl1rjJruOnFtGsz9nxK1LYNNyK2Kr3wBIGjuhB7ZpmpGFhpEx39y4N6Sotwk6jzE7vO/L0vQnlBHDYJ3CtJmLz8tlBmY4lwf23naUiLZkln71rtiw7cyRj2erSV7dNSWtt2FZM7Haz+ioQhHIC9O5fQjDoc5dERy5NCMLNUSzDYsDInsQ7EmpRltjKTNf/sCxMwyIZTWEZJpGOBFWrGnn092/y33s/pmplwzZh91s4bS0LPikn1h4nEUsRbony5uNzad6gCNKEVJkTyVhmHLb4rMiuc6E58RbZYytVMGpeYYj9jxrB+ONGc8jxYzj05LHd3rdU3CDSHnfH3DIkrXUenf9ug91cqfDcH98Ah39/L6pWNvLh8/NpqQ/bFIQqXdIxvTqLlrMQWKZFW0MnU579gplvLOWYs/fj7F9/j9yC7gsQ2xXQc0AxV939fX45d71aMOwFwnLGzAkyxE4h1QSa6Ywr7rg6f3JCKCVh4MgefDJ5ES21YWyWB8WaKDLtqpLfOv2HltFvWIY2ef+jRxDKCZCIJhVbpbtYSRAZx4cbxCkyTJ/ODrqLfBK3RDs4Zdg1AnkBcvODtDdEgIyZ3inR7txDkTdllKhMfyWaUJk0+x01grnvLCcVN7r0NRlJ0RxNEcoNULlUxVY4rQjhxGY4oQXSjgex3U9Cc10sNeXNvPbgTGa8toQTLjqQ0392eLc+B6/9fRaNla04Dh5N0+hsiZKIprLklZvMhSZVmfnsZ0Vz5lluZi7IflYEBUW53PSfC/AH/N3an2zsc+QwSnoUqNoj9rO8OfZXDx6+i/AsFd8AmqZxwe8n8qO/nOhGjbuhYpvsRJ2FDbAgHk3S3hDh/afnceePXyDWmdgxndiByC0Icsw5+zH2oMHk5IfUwpEdUAdg7+6zxzXzjVpINKFouYfv049U3KBmVROWZbnBi647g0xMhO7TGXPwYPzBjD4twa3nsZGdJHPHzciHIHMvkVnEhC2bs4gLO9jUSJgkIkl35++0CbgWDJ9Po2e/YoI5/ixlhiwlRl0xbO++lPTMdzNEgiEfgYCOZVpICfFYiuaa9izZsnojcC0obotZHRFCBUQm4inqKlqZ+sJ8qlc3bvX8xiPJL/1eSklzTZtNcJZRzgy7FLy2sXx2Bxw5s+fBnYus8cwOXs1+VpAQbony6kMzt7ov3wRr5m/ASGcCYgFMw/zKcfHw3cDuHqjpKRXfAoedthcnXXIQpX0K7ZREhewfPE0ICopzKCzKsytnAlIS60ywfGYlt5z1FMvn7l7+Vk3TuOim47n15UvJLwy6pr7MmAFI4h0pLHun7Zr/3UBDteAEAqpAVuXSevxBHyP3G0BufjAzBxspeQVFOYw7diSJeIpEPIVpWpT2LmDQqN6Kz4GsRcsJlNxIPuffTvXOLm4KMtYA57OqU6L4MxJ2vMWmC6N6fnRdZ7+jhxPMCWSyUFzTfqbt4l75nPf7CeTmqb76gz78AT85uUFG7NufQaN7q/RdubF7oIuqlFFcttRXS1K7upk7L3mBqc998ZVzO23yIp665T0Wz6jY4jlvPTqH1trOzDxKiLTGmP/hGsy00VU+J2B1C/I5ypvzbIBjsVDjqWkaZX2KCOYG7LRbH8P36feV/fimME2LVx+YQVNVRyYtUELV8gZuPecZGqvbttm9PewkkN3g+vBSSndPaJrGJbecwI/+fDK5eYHMD7fI/ulWi9l+Rw+n14Aie+HCJSJat7SOF+/8ENM0d+nKdN8E/qCPkfsPIBDwoSEI+H30GVTK8H36M2BET1Xkyg2aBKdeg6Zp9OhXTO+BJVimxZRn5xELJxg/cRR/ffMn5BflZC0wXeciFk5w1yUvcMV+9/Kz8ffxtytfxhfQufRPJ1DWu9DmmMhabCGrxLg66lSzdJDZVcsu12a7SNx4ENuc76Q2Os+KZvctvyjE2IMHu33dWAnQNUHP/kWMPmAgB524B7mFQXw+3c5ysBhz0CDuePun3PbqZQwc3RNdF13lk5vKl51NIchYbBz5fD6Nsn6FDPqKjJBIR5z/PTKLee+vVIRiW0CdzTGCPYqWYTHn7WXUlje7wY3Zbo2M/M5nW0YhKCjJZeCIXgSCPnscu86FrgnGHzeaYybtx6j9BnDyjw5m/HGjv/rh/IbQNEHPAUXovsyzIiUqxkej29JWPezEsLrptYvCUyq6AUecsRf7HzMCf0B3TbfuD7WEWEeCmjXNXPTH4xm1/wBFQIRarKQhWfVZNT8b9zf+ev5zmLtR8SFN07jwxuPY/9iRDB7Tm32OHsb1T53H3VOu5Mq7TyOY489kQAg1XsGgj2F79+Vn936fEy89CExJOmHQo18R598wMUM2Ba7ZW8U0qLlIJww622N0tsXoaIryxXur+ONp/yIQ9HHaFYepezruBq2rSd1tk0ybrsIjuhKhZcvgEi5ln7tRW85imYykeOeJz1QlUzKLvcN6mZMf5Ie/O4aeA4qRUpKTE6TXgCIKinIp6VnARX88Hp9fp7Asjwv+MJHh+/QjkOPLInzKKEnZO/1smVRfVRCtz6cxavwA/vDshYw6YMCXzuerf5vGhpWNpBMG4kt+WlzFwI5NkVKSiKTAtLYsn5vt0vV5sNIW+UUh+g/vgU8XXb4TgDQlqz6t4uQfH8xd71/BBX+Y+A2f1q2DEILzb5hAv6Fl+LRMVo/Pp7H3EcMIbUcOEA8edgQ8paIbIITgvN9PZJ8jhxPKDbrWCuc/KSV15c0s+ngtN714MQeeMJqC4lzXLG6kDFrrwiyeXs7N3/8XK3Yjd8iAUT35w7MX8sCMX3DT8xczzDZNOy4PIRQzYnGPAnLzQwzeow83Pnchy2ev442HZ2KkFSX32b8+mr7DysCxFmRH/7uWI+G265RON9ImyXia3MIQJ1x6IIeePNYmOMuKsRBd4y3Ibl9sdC/nfo65PssFkuFS2FQ+xxqRjKdpXN/qXp/J2FALvZmyePLG97hi33v44Ml5jDqgvxuHcNoVhzF834xpf/9jRnLTCxczeI8++HSti/xdxpgsemtbeQnlqKDSPcYP4vwbJhLM+erAxvUrGjDTFum4wZSn5202w6lqZQPLZq1TsS/2+LhuJJlt58mST2aNmT1+WICERCTFusX1tNR0sNEsu2Pa0RChoyn6DZ/Qr4/eg0sZdcBAVdwMZVkrKMllr8OGbjcZPOw4SDsD7Nu+dlV42R/dhAGjenLjCxdxz49eZP7UNVgJS/Et2CZmI23wxQcr2e/YEVz3xLm8+sB0Pn5xAeGWKNH2BBKJkTZYu7CG+376EqdffTinXnHYju7WjoO744SC0lwu/fNJrF1Qw56HD2HtghqmvbSISFscoUEwx8+Kz6roO6yM5XPX09matYCIDE+BzLY62DvzvMIQZ/36aMr6FQJwzSOTeOeJT3nvX58SbosSaY1lAvdFZrcsyYo7EGQRYqmXcy8nWM/hX9q0n9K9xo0B6FtAW1Mk0zbqGZJIjFSa5tp2hBC8cv90AMy0xfB9+zHhgnGbNF/UI4+zr/seL9/7MZH2BEiLlrpO0inDlUsTAl9Ix0ha5JeGKCjJY9QBA8grzuGCGycSCH21QjF/6mqqVzYpeQyTuspWLCnRNzqvraFTZb/IzDw4r0xfM+MnJe7WJzsAU32p3oy0QSxsIS3QfYKikjxy8oMIAaYFA0b2oM/Q0q/sQ3fD6YsFJKMpXv/7DAaN6UVRz/ztLouH7YjucF/swgZrT6noRgghOO+GCdSubWHDmkb7mHpJCdGOJG88OJM9DhrED645ih9ccxQv3/sJrz8wnWQijUBRLbc3dvLa32aw6tMqfvnIpC6ZCrsN7EU4EPJz5A/24ciz1OuFv07lo+fnk4wlKeldQCg/QO9BJQjg+dumsm5pLemkgc+nSoerHbF0lRR3AUOZys20xXN/ep9n/vgu/Ub05LK/nszJPzmYk39yMO88Pofn/m+qMufbNT3SltWlLU0ThPKD5BUE6WiJkk4a9s5fWUwcpQHU85FfkoOmaUQ6Yphpy7Flue35/Br7HD2ClZ+tJ96ZQJpq9XTbcN6lJNIWQwhBr0El/PCGCfiDPh655nVWfLqedMKguFc+k677HuNPGM34E1QcQbQjzm3nPMO6JbXofp1AyI9pWux37AhqVjdz/KUHcsKlB212SpprOvjfw7PY+4ihHHjymC7fVS1vINoexeEgjbXF+fjZ+Rx/Wde2pj7zOalEejNzYY9Xl75mxi87LVQ6ZeDtAcluSxOCHn0L+f3zF1LSu+BrP3bdBUd5lQBSkoimWLekjkh73FMqPHyn4bk/uhkDRvXi+1cdTq9+JQT8ehfGTaSkdk0jd5z3LJ+9vRyAU684lL2OGE7vgSUEAj7FDghE2+MsmLKav57zDCt3I3eIAyEU02RuXpDj7UVuwdTVfPz8fCKtMXoPLOXW1y7joTnXcNN/L+aSW08kmOtHSomOwKdp5BcGKSzOVcGKboCfzcxoWxdS8RQNVW201IZZObeSuy96jpmvqNobx196EPt/byR9BpWyx/iBjD5AxcNkt6ULweBRPbn9/SvY69Ch9OpfQlmfAvILQ3bMgGLN0BDoCPy6wO/T0IWWkUdkPSOmZO0X1Zx42cEUluShaY68zj01t12fJgiF/Jxw6YEUlORwx/n/YfbrS2hc30ZLbQcbVjaydsGGLuOaV5TDpOu+x/D9+nPoaXvxg2uO4ntn78ev/nk2937y8y0qFACv3vsJM15ayGv3TyfcnLEGJSJJ5k9ZhZW23KwLI2Gw6rOqTdqoWtaANKwuc6ELu48aWWOWHXch0IXAJzQKinMoKs13g1M151pn/CxJS00HHU1bDhTdHsg8Z6ofPl2jZ/9i8otzdqhcHrYDZDe9dlHshlvgbY9jztufkeP6c/9PX6JmTZMyjQvHVGtSs6aJ1/42nRHjBlDat5Abnr+AVDzNfZe9yOr51cTDSSQWRspi7YIaHr76VU752aGc+ONDdnTXtiMEwRw/hWW55BYEibTFeOW+aaSiaXr0L+LUKw+j34ge7tn+oI/fPXM+D1z+Ep++uRzLtEjF0uTZi7vjStCyzOyW6OoWMVIGjevb+N9DMxm+f3/6DivjN0/9sItUvzz4fpqrO1QJdA0sC+rKW7jj3P9w4CljuPGliwF4/rYP+Pi5+UTDcSzD2ZFLwi0x1wqj2TtrNOnKhWlRs6qJ2jVNHHLKGKa9uJB02lCU78IZGfX/miYoLMmlqCyXey5+gZbaDtKJNJqmqT4JXO6MbBxw/GgOOP7rZ0CsWbCBZCzFhtVNvPHQDC669UQAYp0JGta1KOZOJ1h1C9uVrlaFri4p160kMu4lN4HUtlgEAj6G7tuP2rVNNFa2KTuPkF3mNRlP89iv/8fZ1x/D/hNHfe1+flvUVbSwdn4N2DTvUqhAzQOOG+VZKXYDdEdMhBdT4WETDBjdi5N+egjP/fkDktEUWLbp1k5Brl3bxKv3TeMnd6siY4EcP79/8SJee2A67z46h2g4gWVYWIZFS007r947nWkvLuLoc/flxJ/sDsqFpKA0hwNO2IPqFQ28dOeH1KxuptegYk6/5kim/Xch7zw6G13XMUwTv19n9EGDM7EOmiqn7iziwkkbsFcel61SOEt0ZvE10iaRtjgAtWub+eSF+bTVdVKztpmwHeuQCa6UxDuT1FW0UFfR4rZx/k3HU1CSx+R7PiJlGjiqgGuyh8xq6moA6nM6ZbBidiVX/3MSn729AqPV3Eg5UAGLOQWqzPkLf51KuCmKU07dCbiUlmTaiwv44v1VDBjVk8tuP5n8ktxvPCNOIKWRMlg+J9t6pvqQkVG9Vy6pp2Z1E/1H9cyWvGtwqwBN18jJDdil7E01rraGkZkX9d7RHGHZzHXkFQYRTvE2uz1nXo2UQWN123YNzgT1rDz/5w+oWtlIR2PEZlXLzMXSmes49aoEuQWh7SqXBw/bE55SsQ0x4aLxLJlWztIZ64iG1SKlAvok6aTBZ28t58CTxrDvsSPca8685ihG7N+fF/86lfVL6112tWh7nEhbjNdrOqhaVs/FfzmJUP53l+J74dQ15BaEKOqZz8t3fkTl4noCeX4GjunF5Ds/pqm2HSttsyJJELpGR2MnwfwAEolP1wnmBpCosZOQsRhlvyNtK4BNpSwkqViKJ294C5+m0dkeJ9IRIxk1ME2l5AldkHW6iv3I9bP30cO456LnGXXgQE664lCWTC/HTHeNuLINFplAQykzQZ6OBUPT6DO8lGCOn5LeBUTaYoq6W1ekTgjIKQhxwk8PYunH5axdUKPqZeioAC9NtWkaFq11YdrrO2mr76Sxuv1rKxWLPlrD2vkbGLZvP9obO5XQlqS9LszyWesYe/jQrI5lIC2JaZi01IZdpWLB1NV0tkRBStfyYjNxE8rxYaZNzJSp5sLl2iZjCrbf04k0HSlDWUZ0RdOeV5yDZVhoPrWI733UML533v5fq6/fFmvnb2DFnEpinUmV+ZH1fJmGRUNFC+31nZ5S8V2HF6jpYVvil4+ezXtPfMpr935CPJJ0azRIKYmHEzz5+7c45vxxnP6ro9xr9j5qOKMOHMg9F71A5ZJau8y6xDQl0fYYn76xjOYNHZx9/bGMHD9wB/Zu22HF7Apa6zr55NkvqF/XgmWa6JqfZTMqiLbFsSzpBsAKQNcgEPTTXt8JUvETmCmD3KIQiQ7VpoUyubvvzlxkBf4JCe31aiGWTs0GkcmSEEJVRTVRm2mnLZ8uWD23imWz1rFm3nrmvbuC2tVNaqEjy0XqKDRZJn6R1ZauCfoOL2XSb46htG8hBxw/msZ1rViWRVHPPCJtCYr75HPJbSezzzEj6Nm3iOqVDcSNlF2/I0s+odwzQgMjnuJf173B4L36csEtJ5C3Fb799sZOXr7jI5o2tBPK8RPviLtrfDycZP4Hq5RSISW64/awv9c0wdB9+7LP94YDKuvj5Ts+IhFJ4Nh4nDnAknQ0RVzLRRf3h5UV8Og0LkBYauJ1AXnFIf705o8o7Vfkyu7zb5x3sh3gKBGwyVz4NEFJzzz8W5FJ42HXRnfQbO/KNN2eUrGNoekaJ11+CKvnVrJs1joSNv+/RJH+tNa08/5jcxhxwAD2PHKYe10wJ8Bv/3M+/3toBh8+rRgjpZBICcl4ijWfVvHYL1/npJ8dxrEXHbCDerdtsHJOJU3VYeIdCdeELYBEOIUlVcZEpvCXWq5DuX4KSnNoawjbhEoWqYSFkTTd9EVV/0G6NOBOvQ25UVsKMstF4bhUQDNxeSHcd9t3DoBlEQunqVxcg5S2nGRt5LOs+W4sgf1vTajsj9LehTx9/dtIwBfQCeX6GTi2N5pPY92iWg45Y0/WfFbF23+fSbg1pqqwiuw+bipfKpmmenkjjevaKCzL44c3HfeV8/DafdOoL28mEUsR6xBIUw2kkle6mtL8D1aTiqe69FUA9auaaanpoG5tMy/d8SGN61qUG1DLmgt7DHRdwzKdz4JQviKJsqRFMprOjF9WPq+wuSqMhMFzN3/AOX+YwMCxX876uS3hZAM5xGnus6JBXnEO37tgHD0HFu8w+Tx42B7wlIrtACEEV/79LN5+eCYfPj1P+evtbbZEEO9M8uTv3mTCxQdy0s8y3BSBHD8/uO57DBrTi7cenkVdeQvphIllmFimRVNVK6/e9SEbVjRwzo0TCOV9N9whc19fSrIziUAqs3hKledGZmimM9tZ9dlMW9SuVmXPHb+9tJxUTdGlkqe0FQbH/J7dlkMo4SoU2ZYKNCxhKSZH4Vg9MoGJBSW55BUECTfHVEKpS8WNS+XvWldsa5XbFnb1TQRrv6jGSCllyBfQyCkMkYwkSSdNRo8fzODRvXnq+ndUMTrbvCLsTAMlV+bd9RzYu+hUIs2MFxaS6Exy9h8mkFe0eYuFlJIVM9eRTqgYB7c6qBLUDX6tXdPEu4/MJh0z3DgVaXulOhojzHtrGTNfXsyGlY1uvx35VByEJJQbRFpKNgu1MOcXh+g7rAeaT7B85nqXVwN3SgRSU+OXiqdZ/el6Pntz2Q5VKpTFRpGMZT8rCEHfoaWcsFvEQnnY3d0fXkrpdkIoL8CZ132PUQcOJCc/iK7ZwX4CLMuipaaDtx+exco5lV2u03SNg07bi6v/eTaX3Xkqg/bshT+kTLtSSiLtCea8upiHfvISlUvqdkDPuhfxzgSVi+sQAvLL8hh/0hhyi4JuHKPmUGdn78xRmRtuPQkBmpBdzhNa12uy37u+VGoj4GYwOG4PsVGb7q5dCMyUSUGPXEYcMBCfX8visci05VgmNteW0OxnwbBIJ9JIU/0ySVMSaY1StawBTRPsf8IoXrt3GvFIHJAq1kKIzfQD183i9Ekt+JJoR4z5H6yifH7NFudh7RfVRNvjGTlt+RwXBVJSuaiWWS8vprMtikRmLBXur4pkw8pG2hrCdvVY2WUehABd0wiEfCiflbTbhrb6TlbOXU/tmhZ8fg3N9mZ0GT/7s+7TKOyV962CUL8tVs6u5KNnPlcxN458dl9Bpbm+fPuHGOlNWUY9fLfgVSn1sN2g6Ro/vvd0xp+0B4Gg310opQTLtIiF47z45w+ItMU2ubbXkFIO+8E+/PRvZzDigIHkFYfwB3xgSRLRBKvnVvHY1a/y+C9fY/3SXVO5qFxcy0M//i+ttR34Q35G7N+fYy4ar4LenIUSMotl1rXuV471AWG7PYR7bpfFNutqLau9bDeFcw2QaYvNtQXJWIqPn/6cQ3+wN7mFOZvI56Y82oum2Eg+3HvZSZRCoOka/qAPn8+HP+Rj5EEDWfrJWnuRzpJhK+TLlkNKFYz6wWNzNvusxMIJnr/5fWId8U3kcyw4lilp3tBOe0OnW6dk475ahsWqT9djJI0tyieRpOJpLLvmjeOukZaq6tpW30Eylsq6RhUJyyvOIZjjI7cwRL9RPTnv5uOZ+KMDN+nL9sInz3/B+qX1pJPpTF9lZuwjbXFWzFpHc3X7DpPRw3aC5NsXE9t1M0o998f2RkFZHv1H9WJ1z/W01oaxpKIX1nRlrm+pbucfP32Zs286jqH7bVqieeCY3lz+wJlULavn/X/OZv2yepLxFGbaoHF9Cy0b2qla1sBJVx3GYWftswN6+M2QiKZ47qZ3qVxaR0FZHuNOGMUZvzmG5qp2ND1TUTOTpQHS3glKy+Z7EI47IcNboBZRtdN2/PUyw37gahLOv525sEy7LTZqC2Wel/b3ritFSqKtMd649xMs08xwMGibysfG8pFxVWR7Ykr6FJCOpYmnTfqN7Mkehw7muRvfIx1PuxwXFlJZIayu8rkpzGQCWt2+SkX6tfqzKp676T2ue/4CgrmZQleLP1pDW30n0pToPrGpfFLtxPOKgmi6Gi+xmblIJ9K0VLWD5nBybGYupIWZMrCkhV0qI2sunDouuPPq82n0HFzC9399tCrOJaGkbyFD9u67jZ/QL4dlqO2lECo4s8tcmJBXHGTEuAH0GVa2Q+X04GFbw7NU7ABM/NFBnHzVEfQaVIKuaWSXw453Jimfv4EX/vgesXBis9eX9S9i/+NH8+P7z2CfCSMp7V2oqLylKrHctL6VV27/kDfum0YyltrOvftmeOPeT2iqagML+o/qyQV/OZniXgVYlkSTtg9fZApLOUyFjg9bOCXLXZeEs4ZmWCuFHRjosjba466+63osm0/BrT4qMouh5l6Xac9ImTSvbycZSWXdw55fLdOuJgSaLtB9mhuvkJFP9Sm3MESPfoVIS+IP6OTlBfnffdOJhRPu85LN98BG8gmZCQB172mzcTrfm/az8vjPX6V2TZM7F+sW1GDE024Z8a7jZ7N5+nX8AT+dzYoHxJFby5oLQLk06Dp+mq2ZCEDXFFW43+9TkQhZc7LJXCAIBv3k5QfpN7wH+x83mv2PH73DFQpwnjfhBuxmz4XPr9N/ZC/O3sYVUj3sHHC4iL7ta1eFp1TsAARy/Bxz8XjGHjGU0j5F+DTh7m4EEjNt0lLTxqu3f/il7fQcVMKld53GGdd9j32OHUlJrwLF8pg26GyKMOvFBTzxi1d5/5HZO61yMf/dFbz0lyl88dYy4uEE+cU5nPW7Y/AHfbTVhZnz0kK1C8RxU2TRbdtjlqGyzjpHKMZJTSNL0cgQNDn+f5cSWkMpKCKr3eyXG9WfpbS4bTq9kXbsAK58zry68mqqraKyPApKcgnl+NGceAVbbgC/XyfamlDU17qgekUjnU1RsCx0tla+jJLlEIBlFmz1rEXbY6yYvY6Pn/wMUMRfq2ZXkkqkVFtZsT/Z44cpibRFqVnRgJk0MmOvKXp1Xag+uFTaWmYONM2OpQjq9BxYxMQfHUT/0b0I5frd87c0F+lkmtpVTfzn+rf49PUl2+EJ3Tq4yulGc6FrgtJ+hZx+7dEEtqLS67ZGY2Uriz5YtaPF+E5jd4+p8NwfOxCTbjqO0v5FzHj2C9oaO9EsaWcUSGLtcZZNW0vl4lqG7LOpG8RBTn6QI364PwecMpap/5rLrP8uorO5k1TCINzcydKPI2xY3sC6RTWMPnQIh52z31aVsd4eqF3dxCv/N5Vwc4R0ysQf8FHUI5eyAcWUf17NG/d8zPqldSSjKXdRsZzARE1DWpatZEh024HtpCg6a5+uCfSghq7rJBO2id3KKBWOqd0hYXJ30tnUz1lKgXTeRdd3yJYPhOgqn+vuADS/Rt8RPTjxZ4fz3sOzqFi4AStt2btaDSktkpEU0rQoG1DEQafvBQIWvb+K6hUpsKSiprZlz1aQNpaPrHelWzgBhLZ8EsyUQd3aZuKdSea+uohIS7SLVadrW47rSJKOGwRspUhl2jh9leAT6LpA+jIsHRu3lVeUw0Gn70Ug5OOAE/dgzWdVrF9ca8dyOIrERnOBxEwa1K9t4vW7PqJmZSND9unHuI0KnG1v5BYE8fmU28ztKygrU0GQ8s+r6WyKMv60sRnFbDtjxYwKPnhsDmUDihl58GByizwSLg/dD0+p2IHIyQ9yyi+OpHFdK0s/WkO4JeoGdlmWpKOhk8l//oBTf3U0exwx9MvbKghy6jVH0WNgMVMe/ZT6dYp4yTBM2hrCdEyJULWkjvLPqznjd8fSYwfny6+aU8lb908j3BRBSklhzzzGnbAHQ/cfQEFZHs/89k1qVjUR70ig6S4LhPpBViQf9ufNty/s7/xBnUF79cVIW1Qvq8fMir533ABAVq0MtXA5bTitCZF9LCvg0BZCuPJkzP7Z8mXLn1sU4qw/HMfQffvRd0QP7jzz33S2xPD5NMr6FxHtSGCZkn4je7DPhJEE84MEgj5O+sURvPjH9wk3d25WPpH5lJHNPjHTN7t3WfJZpqS5up2nrn2d+rUtdLZGM4GRWeOZGX8VoJFbEKS4TwGx9jipeKprcKql4kykZSE0zZYvY9MVgGWazH5xAalEmvyyPPY7fjTt9Z1uYKa0NjcXSjFKpwzaasN88vTn9BhYzOB9+1HWv4jtheaqNuLhJAP36gPAMZccyKIpq4i2xbvMhZW2qF/bzAf/mMXAvfoyYGxv+mbVrNkeWDN3PeuX1PLp60vRdI2egzVPodiW2M1TSj2lYifAOTcfT92qJmIdcZUiiNrRmmmTqmX1vHjzu/z4oTMZuOeX+46FEBx61r70G9mTV26bQu2aZjpbImBKDMugrbaDxS1ROpsifP83xzB8B7BxGimTL95axrt/n0l7Qyc5BSH2PGY4Iw8azGFn7+ued8T5+9PR0EkymsQyLYSmqyI7DoWmbV1AZi/0WcyY9r5cExpFvfIZdfBgOho66WjodDUIIaW7zAlEpoiPEF0WMw2HQVPY7NGZ7wQo9sQuy96XySfIL8pxF5ayAcXkFAZJRlL0GdGDvJIcEssbyCsMsOdRw5gzeRHtDZ34/Dp7Hj2c0YcMYtm0cpUhJLrKl1EkshZvmzMC4YyI89k+wVbQOhs7qfjcIJ1W9NeanrEwbKxgaIDPJwjl+CkozVX9gi5FkISdwaHiLWz5ZEbZsaQk3pEEAdK0MOIGn722hNJ+hRT3zCfeaZPESdBRiomORPdpGNJEQ2CaFulEimhbFLmdndDvPzKbpsoWfvKPSeSX5NJneA/yS3KItSfs/tuWIWlhpS38QR85+QF6b8dATTNtMv/t5bz94HQ6W2Lkl+Wxz8RRnHT1EdtNht0RuzujphdTsRMgrziHM39/LPklOXaZbsBmLDQSBs3rW3njro/YsKx+q9obvE8/Lv/n2Rxw6hgKSvNUnr+9IqRiKdYvquG5G95k9ksLqNrO3BbvPDiddx6cTnNlK36/zj4TR3LJ3d/volAA7DtxND9+6AeU9C6goDSXMYcPJb8opMzrEjTbXeEwZDrmcmeRdRZcI5lm8Qer+OiJT+k3qiehHD++gE4g6EPYbglNgK5nxT7IjdoiywqQ5SpR/vOMdUOdL9GkklFNY1f5cgqCDBs3QGUuOG1ayg/fc2ARrRvaEVJS3DufWS8uoGl9K6lYknhHgoaKVvY9YTTFvfLRdeHK18WiYMuXHW8iBGgySz5s10aWfJZlEW2Lkopl2CtdhSm7TXvMpClp2dDOimnlGCnDlcGJm9B1jWDQp+R05BNd2xJYSNNU1hLLJNoao668mVh7nD4jyug3ogf9Rvak95BS+o3owbBxA9j/pLGMOmggwVy/LR84jKnbC2bapHZlA1VL63n1tilIKfGHfPQf3YtAyLfpXOiCwh55nP9/p6hskO0g38qZFUz+y/u89cA0mitbEQhGHDCAs/4wkdxCz0rhYdvBs1TsJNjjiKGccOXhTH/2C1o2tKmDToyFYVE+r5qnr3uDS+47gwFbwRqYX5rLeX85md5Dylg9p5LyedUkIgkME9IJk8byVl69bSol/Qo5+Zqj2Oe40ei+badjWqbFyukVLHpvJa21HeQUBhl36li+/5tjtnhNaf8i/EGddCJNj4FFxNpiqpJlwrC3gSLLMqHgsDQ6CxwWGIZBR1MnPYeW4gvoNi+C6bpSgrkBCsry6GyOKgItzd5VO20JgWb79aW9aHbJCBEC6Q5dtg+gq3xCExQU53DAqWNY+1mVfR9ppyNKKubXkE4YFPcrINIcVRwQTqyCrmIU9jpmJAveWkbjuhYsS7oLtZuy6bo6bKVD2HvmLconbeOPsGNAMooWbl/tNrWsQE1Uyiju2G/UVyCY4ycVT7spoZqu2QqZQLpZHtkySYx4GhA0VbRSNrCIkQcN4ahLxrPo/VUc/sP9ySvOYdrT86hd3ZQVfJuRYntg+rNf0FrTTqIzScXn1cx5eSF9hvegsbwFK210mQtNVwGnPQeVUNKvcJvKVb+2mUhbjEXvr2LJh6tpq+nAsixCBTkccMoYvv/bY7fp/T0odEf2xq6c/eEpFTsJhBBMvPxQ+o3uxVO/fJV4JEn2D6URN2hc28w7933C2X85iZK+W/cDdeyPD+bYHx/MR//6lBUzyqlcUEsiksQ0TJKdCRrWpHj9tilULqjhxKuPIGcb7GISkSRTHpnN/LeX01bfSVm/Io6+5CCOueygL73u7fumEW7oJBlN88XrSwnk+tE1gaUJ102kXPzC9fM7C70y9Qt7vRJYKYvyTysx0tINoHTWokDIz6m/OZoV09YRbYthpA2qFtWRiCSxUNkhMqttxzHgrNNulVE25YPAkUoqy1OkJcK/r3oVf46PdMLAH/QR70wAgnhbjPye+QRDARrWtLhFs5y2ywYU01rTzl4TRtFaE6axooVkNGUrP0oaJztGZltXyCz27ii5nbD5J5Cqr4IufRX2+VklN9w2fXZxrHQi27qR6WsyklRKkaaha5L8khyKeubTWt2uUmM3ks+FlCQjSepXNaMLQd+RZRxz2UH4gz4S0RRzXlpI2u63I5/Yjr/C8XCCRGcSISVttR28e/90cvKD1K9tAmmnPSPw+XSKeuUzYM8+HHrOfttUpg3LG3j2N2/QuqGdVMrEsKu45hSGGHfSHpz311O26f09ZMESdqW8b9nGLortplScffbZ3HDDDQD897//5c477wRg8uTJALS2tjJs2DAmTty9c7nHHDWMCT89lFkvzqetpsNdmEDtaFfOWscTV7zMZQ/9gB6DS7a63YxyMZfpz8yjdUOHKk9tmrTWhZn9wnwayps49y8nkVuc24UM6dsg0hbjpZveZcW0clKJNDmFIS686/uMOGjQl163fmENSz9cTaIzCUKQjKVIxdPK128rFBLwBXwIC1L2DhGyFj/H/AxIyyKVkG7KJmQtkBKKexVyyX2nq+ul5Imfvcyyj9cqq4i9QDvuhuxrnQ/ODtytiS43Wijta5KxNNKUpJP2e8JAWha+oI/SASUM3LMPyz5Zg2WYXUz60pSs+KSc5R+vofewMg4/fxwV86rpaIwAkqrFdSRjapcvtAz3hZMt47gINCEIFYYYuGcfp2VA0FDeTEdjZ6ZGid3XzfXZeVd05BpGIr3Zvhop043xEAiMWBohYdThQ1g9q5JEJKWIyLIUMEcipCqdXrOqkTfv+pjGdW384KbjmPLILBrWNqm4D0cWma1CbXsot4u6n2lYqqot0i1dKwCfX1DSr5gJlx/KHkcNo7Asf5vIkoqnibRGeeeBadStbsI0TFex1XWNHoOKOe23W7YGevDQ3dhuSkVFRQUTJkxg/PjxvPzyy+6xKVOm8OijjwJw3HHH7fZKhRCCE64+ggF79eapX75OMpJ00/AsS+0KW6rb6GyNUjao+Gunpx3740MYOLYP/7vnI2pXNCr+CkuSiCRZNXMdd532L4bs258L/3a6IiUKfvNHpLGihWd+/Tq1qxoxDYvivoUcedH4r1QoQNFedzZH3UBHZ80x7cVW2oukZZjKzmzDsWAAGTu880/7x1YdljZDpGJ1THYmSUSThPKCCCEYfdgwVs6owMD1tChdQai0ymyFxFFgcoty0HQUv4TNrujePFu+rONO33Rd44BTxxBpjZGOpzeST2kpiagKAqxd1cjclxZy+b/PQ9cgpyDElEdms3JGhdu+JR27jZPeogZMaIL9TtyDoy/taiVa9MFK3rzrE1qqW5Wi44iY7dLIngsB6XiaYF4QX0BXBdDs4xk9OKOMSSTJeJq61Y2014dt10n295m+Oqm7an4tYuEEiz9YyeB9+9JY0YKRNrPmAjdGY3tB2Dd1YnqkRZfnTAqVUdNe38mbd3/Em3d9xJ7HjOCi+87oVjmklDz969co/7SqC9W5w5WRUxDkjBsmUlCW16339fDl2N0DNbebUnHDDTcwadKkLsemTp1KcXGx+7m4uJipU6fu9ooFwNijR7DvxJEseHcFMu5U3lS7s2Rnkv/88lWO+cmhHHnJ1693MPLQIVzx+A95/f+msGFZPc1VbSRjKayUSbQ1yupZFdw+4REG7tOXnzx6Drpf/9r3MNMmb9/3CbUr6hG6xuB9+nHKdd9j9OFDt+r6DCOhw/+gdszq99t1biBNlaqYHZxp/xOwr3F979JtQ2VyqDZS0STPXvsGvUf24Ac3H8+Q/Qd0Cb50Cl1lduzCjT1wqpUiVDroAd/fk3cfmJ5Ji6SrUtRFPgFuwS4gXN9JxfwNWKbVRT5nJ++4LizDonZpPXce/w+wBIedP45TfnMMJ3yLqP7qRTVEmzqV0kZmcRT2HLjj586FAAvyi3Mw8wO014WxrIwFKVuRysyFxDIl8Y4ElmVXeyV7XrPmMEtZQ0J7bQcvXv+W0h8thyLdkU9m65XbHG5QKhnlp4siZcuYjqcwkwZSWqyaXs6c/y7g0HP37xYZLNNi+tPzKJ9TSTycspVYJZgmNIr7FXLoOfuzxxHDuuV+HrYeUgrlkv2Wbeyq2G5Kxbx58wDl5gC4/PLLKS8vp6wsk2JVWlpKe3v7Zq9PJpMkk0n3czgc3nbC7gQQQnDydcdQu7KRmpX17gInhNqtt9V2MPO5zxl91FB6Df36ee/5pblceO/pRNtivPrnD1j20SqSnWksS2KkDDpbI6yeWcGD5z7FGX88niH7Ddgqq4iUksZ1Lbzw2/9Ru7KRQE6APY8ZwZk3n0B+6derIun8eGdM8M7OVmZZHHBN+7LLyp3ZBasddtZnuw2nTTMtSRgJGsubibXHsu7tMElmZbJuti3nmOTIiw9k2UdrWDe/GmlYarGUWQuPO4TSbksQDPko6VvIkqmriYcTdnBmps/ZY+F00jBMOptjaJqgfm2TWqQ1NxrTTbHcWktWQ3mLiu2QmR24kltusc++oMbeE0eyYXkjHXXhDHPnRnORScEVdvpt5ll22nYYPrMtJAC+oI/ivoUkoyk6myLZGcW24iEzCsh2wpijhjPnhfm014UVF0dW9snmnhUA3a/Tpxv5KZ655jVWzSgnbsemZD8rugZ7HjWcE395ZLfdz8PWY3e3VGy3lNI777yTSZMmcfnll3PnnXduUXlwlI6Ncfvtt1NUVOS+Bg7c/hwL2xul/Ys48Zqj6DuyF4GgL5OaaH/fsr6Vxy55nk9fWviN75FXkstFfzuDCVccQb8xvcktDrkmZcswqVlaz+OXvsiDZz9F5RfVX9pWw9pm/n7u0zw46Sk2LK1DWpKDz96Xi+4/85spFDaro1Osqgs1N5mF1k3vFDYN9sbnamSoqR2TuZ01kE0BbSYNZjyllN9h4wdS3DvfLlG/mRTNrLkQTiEsoSjYT/vtsYw6ZAjFfQrxZ5dBz5YL1ZbPrzFk/36cev0x9BpSSmGPPDsNU2xyzeb6KoDyOZXcesj9vHvfJ+74vXLzu7x990dbP95sftycDA1tI8uRo2x01IUZe/QwN5Vyc3Ox8fi5bTn9EgJ/0EfPYWX0G9OLvqN70X9MH/qO6sXYo0dw1dMXMOyAAeia6DJfLgW7tn2j5Qft04/ew3ts2rfN9NVxRfQYVMzQA7rnN2vui/NZOX0tiUhykzHXBYTyg4w9dkS33MuDh6+L7WKpmDx5MvPmzXODM4uLi6moqGD48OFdlAsnWHNzuOGGG7j22mvdz+FweLdQLPY5YQ8GjO3Dv698idpV9cr8bZvxzZRJW22Yaf+ey7CDBtFzSOk3vs9xVx3OcVcdztR/zGT2s5/T0aSqVJqGSbwzTvXiGh7/yQuE8oP0HdWLSx85B18g4xb59KWFvP/gNDqbophpg5yCECMOG8pxPzv8G8uUrUxYZO0GbX+AwA6n2Kxvwf6nyHqRCV50zPhuW0IxPDZXqXTefnv0pt+Y3rRWtWFlsU86wY6qemlmLrIzI4aOH8jP/nMhlV9U859fvUpbbUcmK4SuJwspqVveyOu3vk+vYWXsOXEUn/53AdK0Mq4ekRWHsQkk8c4EyaigZrniMfn0pQUsemc5fUf3+soxTsXTPPmzl1i/sKZrvIctp+PiyV64LDso1TJMmipaOOPmE5j2r7luiqk/oJNXmkeoIEBLVYcqB541B13G0Z4LDcWvcuHfztxExjWz11GzrE7J53JyZaUNo56VF69/k9UzK7BME2mnGwdy/Ey86ggOOnu/rxyLrcH/7pjKig9Xu4SHXaYl6/lzxiq3OIfCnnnsNXH0t7733BfnM/WRmSQ6U6SiyQwZmzItoekaBT3yGHfaXpvcz0ybPHnVy0Rb45x07dGMOtxzi2wrSNkNlgovpfTLMWzYsC6xE+3t7YwbN47i4mKuv/5693hFRcUW4ymCwSDBYHBbi7pTonRgMROvOoL37v+Etup20pbl/nAhJc2VLTx+6fOccM1RHHDmtyt3PvGqIxi4d18+eHA6zevbiLZFsUyVeRLvSJAIJ+lsjHDXcf+gz6ieXPTQWUy+8R1WTltLpC2KpusU9irg4HP246Rrj/nGcggyCxA4C5FA9+uE8gLEwwmkZXVdzTfGZsz2TltsfMzWTqLNUT59aQEHn7M/ow4dwqpP1iruimyZHHmy/P5+v86QcQOItsV4/tev0VjRipkySCRSaEIjpzSErmlE22KYdoE0JEjTIt4ZJxlNYqZM9jlpDDkFQWLtcddtki1flwHK/reUrP+imofPfZpoW5R4R5zG8maWfrCKvY7f8oI27Ym5VHy6nnTS6BLD4DYtZRdlwJ0LW36EYObT81SKpQB/0E9xnwJSsTT5xbnk5IeoXlqHmTZxGE83NxdmymDVtLXMf2Mp407fq4uMTetaiLbGNjvNQkpS4QQPT3qKaFuMVNJE2vEFUko0TeOduz6k4rMqfnj397c4DluL6gUbFJmUL4tDNVuJ1YSqPKxrIHSOuuxgjr+6e9wQG5bW014bdrOLshU1pLKI7HfSGL7/h+M2udayJE0VzYDotswuD5vH7h5TsV3cH+PGjaO9vZ3Jkydz/fXXM2XKFEApG+eeey6TJ0/msccec1NOPWyK/U4Zyzl/PZVgnt/2oWYYFc2USfuGdt66Yyov/+Gtb32v0UcO5xcvX8b5957OoL37UVCai+4TrhJjpk3aatpZPbOCe09+lEXvLifWEUMgyC/J5Zz/O+VbKRSQFSQILtGUBuTmBdjn+NGKJVQ6BE+ZRS+bCTPbQuEsaBt/35U5E9LxFO/c/SF3TnwYpCp6lTHVZ2I61P2c2Af1Q91rWBmPXvQc5XPX07qhjc7mCGbKQNcEe35vJCf/5lj8QV9X+TS6tDn6iGHse+Ie+AP6pvJu1Fd3fAAkJCIJqhZsoLW6HWlJkp1JNiyt3eIYr52zjk9fno9lp35qApcJdBP5HEbOrLlwZKlaVIs0TAIBHwP37INlmnQ2dVK1sIamipauMRRbmAtQAchv3v4Br97yjiujkTRY9NYyzJSRcXs597blM9ImHQ1hUon0JuMlLEm0Lcb6BV/uuttq2EETZtJ0x2TjuXDHy5LMn7yQO479Ox88MO1b3baxvJnKz6tAWpufCw1CuQEG77956+28lxcSCPo58uIDGbz/gG8liwcPX4btFqjpZH5snAGy8WcPW0Zhr3z6j+1D1fwNpO1y026MhZREWyIs+X/2zjpMsuM6+7+6t3EYd2dmmZkFK5ZWbFuybFmSGWKKKXH8JXGcxIkdchInjmNmkEG2JFuWZPFKq9UKlpl3h5mb4VJ9f1zo2zOzJG1sy5r3eWZ7p6dv3apT1bdOHXjPo4dZcMlsVt+y/EzNnRGLrpjHoivmceKFFh777030HPYX5JKYmsFo5yiWZZ8IlZDCmluWsvTaha/43pVTyu2x7ulG15zNwtl96mbXUloRJamlUHy8Ci78lggvK8TbxGSR3IR/o7KHRWYkQ3Y0y8avbiaf0oo3DWE/zP1MlgKJnsnz9Ne3kIlnvSqoHtumkAy1DNGyrd3bHMf2TwkoVE+rIFoe4dJ3XsDBJ45iOvTX7qarjBlfkbkdJ6PFNFGk4o3xdOg+1Ed6OA2OTNyb+Mm8PPkpoFjF8kMI9EyekUSOUDRIeV0pIx0jpGO2VcEyTHKJrD0+4RurKz+3LadtpCQ9lGLfw4eYf/FsVr5uKS/9dCedB3rA9GXC+OSgMH4u/G0KRVBSFWXW6mmnF8ZZ4PiWZkbaR3xul0KNmMIClM4cCCxLMtodRyJp3toGf37VOd+z7/gAv/3CU/QdG7TlKieYC1VQWlnC8hsWs+aWZePa6DrQw/M/2oaUkgvvWPPyBj+Js4clkK9h8qvJ2h+vItTNquHDP3kX9XNqCjUnfD9g1/Z45N838uDnHz9vRZYWXDaXj9zzHhZcOptoZRhFcRkX8QIKhZBEy8Nc/t6Lz8s96+fU8uGfvou62dWFUyn2w3zuRTOZMq/G7oe7mUwgD7uPvs9M+Pfin8K9JOmRTKGuRdFYx7dh6ibZWNbO3HDblXaZbqRF77F+4r1xpGlN2L9gUGHZdQsprSmhpDJK1dRyFHV8v8a+nmocQtiEX3bKYW6cfPWcztFNJ5Cmdeq2/PIbcw9FgZKKMHpGIzOSoqwqirQs0sMZO83X3xbFbXlptMrYv9t90zIaJ19s5Rf/7zc88+0tmDljwvGddj6d/6sBweo3LOWt/3XbK16Tbbs6ySYyxVaxU62tCdbKy0H/iUE69nSS6E8gDWvC+wUCChfevpK3/Ot41kxTN3niS5uI98Y9OU7i/xYuTfcr/Tlb3HHHHezevZvdu3cXhRPcf//9nhdg48aN/wcjnRiTNN2vQjQsmkKsN0k2mSnyf4O9kSQGkux+YB+zL5zJqtctPS/3DIYDvP8H7+CZbz7Pi3dvR8/pDpV4Afl0nnv/6jfc+BfXMOeiWeflvnVzahhsHcbSjMKbUjJ1wRTad3djWdY4NsfTQeAT2QQPWDepcVybE9xESM7Aj2BfZFkSYViEIkF0Tccyx06a/aOlNX7+yV8z1DpM/bw68jmdeHccwyiUa0cIAkEFU/O/x4SlkqVhMdw2THIgVUS/3r6niye+9Ayd+7rtuiOngjM2NaBSUhUll8xhajbxlKIq1M2poc8hNksNp525mCDuo0jovj9LX4ytYqePRspCBEIBamZUseWHW0mPZCeUlVBEkdIsGD8XalClvLaMhoVnDlgFOPz0MTr39bDhY1ecFenb2awVoQgipWEaF5+5Xo8Ly7R46J+eINYbx9QMm1jMHdupFvsp3t95/17adnZi6taE630Sr378oRFLTloqXoW4679u4+a/vIZoWcTx39onay9w0JJoGY3HvvAkj/7HU+e1LPSGj1zO377wSa758OVU1JQSKQt57gMzb9C5t5v7/+YhXrx7x3m531UfuIRIadCX829HqF33iSuZOq/WS6sU2KyUiiIchsVCES7hPE89s76fR8DlY3Dkp/j+7v7fjTMQSFRFECkN+XznTDAHcsz7UNVYwcVvX2tXR3XvQ+Gz0jTZ99ABjjx9nN7DfbTtaOfm/3cN01c2EY4ECv0TUDuzmkBInbB/wiq06WHMZtL8Qgsde7owcnrxWP1jFsIbS7QizMd/9T5qZ1bbp39VEK2IMNQyjJBQWh1FDap2TZUzyO90cxEpCfLW/76NTz/7CULRIHpGH9/WGLl5r7K4LVdO7/vBW1n/tnUTri0pJY/950a+cfv3+Opt3+Whzz3OgUcOkY1l2fztF/jGHT/gm3f8gBd/vM294JzWipBQVh3l1s/eyK2fvfFslzx63uDw00c58Xwzrds7kLo1nivEsucoUhqickoZdXPGl1TvOzbAc997CT2noSiCyoZymw10Ev+ncAM1X+nP2eIzn/kMo6OjPPXUU15CxKmIJX8XmLRUvAohhODit62j+cUWjjx9wjHRO9RBjukXKUkOpjj46BGu/+Q1r4hueywUReGqD1/KJe+6kBd+vI0Xf7yNbCJnV800LUa7YjzztefoP9rPzZ+5nkj5y8/aCZeGqagrIxvLoigKlfVlhEtDlNWWcvn71rP5e88z0joKAqqnVaHrBvGeBEJApDxMtDLKSOeozXGgANKthwFShUAwQKgkiKGZaFltHJOjm8LomtRLa0qYf+kc9j962Dk1O205Jm/pVDX15kJAMBLkgjevomJquWe+dudJIO1+mZAaTGHX6ZDkYjme/OIzlNWVUTm1nGw8h64ZGHnbhF1aESE5lPbiTNzNxlaypBe8Z2kGh548ypSP2GybRt6gZVt7wQ3jH6t/zL5MDVURCKGgKgqqIqiZVUNZbSmj3TGaljZy1/+8mee+8wLPffcF9JxR6JDbphjTP1mohOqmq0pAT2kceeo4RzeeYP/jhzGcwMuJ5gLw3DCKonhzoSiCQGmQ0qoo6+9aS+PCU1sIDj15hO2/2I2W1rAsCzWgMGX+FJSAwt6HDjLQPIi0JMNto/QfG2Tq4il2Zs5Ippika4L+KY7yuez6Ray97dwysmzXmcDSC9Yof7yIggBFEggprH/rOq775NWEosGiNizT4okvPk28N4YAQhGVC9+y5rw+ByYxMeR5iKlwrx9L8jhRFuQrJZY835hcYa9iXPfn1zB4cpiBFrs6omchdR/iliSfyPHAZx7ihr+8lqqmyvN2byEE4dIQ13zkcqYtbeDRLzzFUOuw/TcLcvEcBx49RN+xfpqWNnDjX1/3spSLqQvqWfPGlWz5/ktIKVl96woaHP6FdbevYvaFM7n3Uw9gWRYbPnoFrTs62P3r/QhFUDurmtkXzmT3/XsxTYtoRdSuPGra9UKUgMKM1U285d9vZe9DB9n83RdJD6YKWaquQBWXJVGgCgVFVWyOBcum07Y3EuEwKzrEVe71QlBaGWWoZZhDjx1BGtLzt0tHjq4Fxi1SpWC3PdodI9YdJxQNsvq2lQy1DtO+p4tINAy6ndXg8lvbfXbXgE2pjbSr2+68ZxeLrphH0/JGEgMpBpuHwJB2NVNnrbivftINt39GVufeT/2aRH8SRbELg8VycRZcNo9gWOUnH7qHRF8SaRW36Xd/eLKxF49XVVQp9BhpSY5tOkEmlkVzaM7xy9Lpn3CCCSzLorymDMvJ8FAQqAGFtW9cyXV/fhXHnzvJPZ+4n8vedzEz1xayIo4+c5xtP91J38kB9LTmKIaCstoy1r9tHSPtI3YAq2VbVnIJey2Pdo4ybWkTrdvbvGJp7loRAYEaULEMC9O0UFWFGcun8fq/veGs1/qRjcdIDqRYddsKFNUJaB0zF+5aUbCroSqqGKdQAOx58AAduzqxdPuz5XVllNf/3xQ1m8T/HcZyMf3jP/4jn/vc54rec/mfAObNm8edd945YVunIpY835hUKl7FmDK/jlW3LuelH28jPZzxHrx+HVlL5zm26QTSgjv/502cawGyM0EIwaKrF3DwscPEukaxDIkUEqSFltXoPdTHUOsww+0j3PD/NjB91blH4V/xoUsZbB5ESsmVHy4m06qdWc27v/tWTN2kYko5C6+azyXvugApBZHyMJHyMNOXN9L8Qgu1c+tYev1iZxe1N7XSmlLCpSEufc9F9Bzq5ejG4+SzeXuz9naMwinbyBsYOYNQJIiW0WzLhKd0OCj+hVw8y9FnjmHkTKSXPeGUJ/esHCAVVznxRWpJu6LpwccOE4wGqJtZxdu/cQfNW5rZ9M3niXXFvLYUAZYT/OhZTqTE1EzadnbQtLyRE1tOome0glVi7JrxrACF8ul6Vqd7Xw+maaEogsxIhmhVhI7dnaQGUuQzuSKyH8/C7t1DIBXpG6NvrGPqxif640jL+Yz0teW2HVAory8nl8yhpTVAIg0LxwiFIqD1pVbu6xyl/+gAuWSe/mP9XPKe9Vz8jnXEeuI88Z9PM9w+gpQ2z4kiBEpQYeHlc7jwbWv57T89gZbKeZk77lru2N1FWV0pgYCCpZtF/QsEVaJVUXLxHDJnIUxJz6Ee7v7gLwhFAqy5fTXLb1pyyjU+0jnKk//9DFpaIx1Lo6d1n0WmeK0oikCNBiivL6NiSvm4tobbR3juG1vIZ/IoCgRDARZfPZ8l5yEraxJnxrkGWp6qDYDOzk4qKiq898daKc4HseT5xqRS8SrHlR+6lO4DPbS81IqW1cYxuUkJRs7g5JZmfv3XD3L9X15LxdTxD6JXipoZ1QTCQTRDQw0oqCEVPadjWRZaJk/Hri5+9dcPctmfrOeCu9aeU9uKInj9Z2/yzNtjUVpdoABXgyrV06uL/r785qVMW9lEZWPlhNeD/eC+9XOvo2Z6FXt+tY9YbwKXytNVGiR2ZkLf0X5KqqK2u8Q95uNj+ARvQ0XaPnJEcVtFQQ9+H8SYy+1TviSXyJJN2sGcD3/2EYLRIFPn15FP5LBMi3xaK7CLuiZ5XFO8wrxL5wBw6PEjHvNlwbRFYazC7YUs6ohleQZ/qqZVogYVRjpGC2Pz5Ohr0+vPmCesb6hKQCEYDaIgMA0TXdMnbsvpX1VDBWVTysnEMkgpycZymKaJIhSCJUHUoEKiP8loV5xgJIBQBLHuOJu+8iwnNh8n3pck1hfDMizPXaEEBHWzatjwZ1ejZXR6DvQgrcL4XR3UNEziAwnvb57rw7KzLFL9SU/LsJDk0xoduzpRAgqldWWnVSoOPnqYZH8SPafz/HdfQsvqvr/61oUiKK0pZfWbVrL6jSuonze+nsjBRw+THsl4Aa2lNSVc+8lrTnnvSZxfnE/yq4qKiiKlYizOB7Hk+cakUvEqh6Iq3PYvb+DZr2/h+OYTjHbFwC1ypGAXt5GSfCrH8WdPYOQN7vzf28+7xeLyD17K/ocOMZIdJlIZYc5Fs+je30MmlrXpvnWD0a5Rnvnyswy1DHHNJ64iXHb27hB/9sLLQfW0qjN+Jlwa4ppPXEXbzg4SA7Yv094T7WOzIgTStMgMp+1TO4WTts+IX3ApyIIS4bdIgGPCd6ttOimWhW0bx+wvC3uzU2Qsn8rT/GILilBYcuNi3vGtO9l57x4OPXoYy5SedcGzfligZfPse/AAF75tHbHOUdcrY1sEFNe07ru/sxnZ/fO1BQRCCtHyMCMdo5i64ekvXhu+ded38RQqi/qULwHRygg3/vV1VE+vYvd9ezj0xFH0nF5oSxTaRrFLoQ+3DGNpJopiu+D0jEa0MsKSG5ew/OYlPPu1LYz2xJi7fjaBUJDjz50k2Zekc283+bSGZZpFaZ6BkIpA8uS/P0V6JMNIx4gdc4IYMxe2O8S18LgGKXu+ZcFA5Vg/LNNCqJKqpkoufff4asLHN5/g6JPHWP/ei2xFRUqkaWHk9ILsx8yFuz7CkQD18+pQ1OJY+5Nbmjn8xBF7jNg6jhpQJmMpfoewLIH1CmMqzvb6tWvXeqmjO3bsmJBYcmRk5HdKLDm50v4IUFpTwo2fvo7pa6ax5VvPE++Oo2U075RlVwcDPaPTsbODE5tPsvDqBee1D8FwgMrGUuI9owhTMu/iWay7Yw2GZrDtx9vpPtiDntPIxjIc+O1B+o/0M21lE1f86eXnpFz8X0NRBFPm1NJ3qA8jb1taXMUgHA1gGjYFtJXXURQFNRhEURVM3fSIwbyNlfEbLMKOd3DfV5B2+W/v7/gPpsWbtbCVCyyQwmTgSB8HHjzAmttW0r6tndRQCsu0x2CZziauSISUWLrJI597lGw8a2e8uP1ThccrIZ2NG58S5K9zIh1f/nDbEHrWJvHy3Ble/wrXemP12nLG6slEEFAVpi1vpH5eHc9/+wUUJ3C1oPTYsRZuHEZmJIVp2BVZI1UlXP/X13Lw4QMEo2Fu/swNBEIqNf9Rw8CJAWZfNAuhKMxYPY1DjxyCgGC4eZiRzlEsy/L6Z+kmwy0jxDpiGIaJTVpWmAshQKgqlmH64kMm6N+YsaJAWW0pi6+ZT8OShnFrbeuPt9N7sJdQSZCSulKPIdOroKsIjybdnQspLbRkjpPPt7Dy1hXUzCrU+0n2J3n83560x2eavkJn5/cAMYk/LPyhEUtOKhV/JAiEVFa9YTnVjZVs+sqzdO7uxDItLKVQ+AppkYtn2fyVzUxfNY2S6nOrHHomrLptJUPHBsml8xzdeIx3/fCdADQunsrT/7OJrt1dJIdS5BM5Ond3MNI6TN/hXmasmcH6963/g1EurvrYlUgJ7dvbiffGCYRUpCWZvnoaK25dyf7f7Kd9ZzuBkMrs9bOZdcFsXvzei45JvmAWFwKPT0EI4cyFnfGg4Lw6m5IiwLTsDdeFP2DU86oIEIpEWoLRrlFi3TG69nVhOUyd7oYmsV9N59ScjWcYbRvBzGrePdzTuht/UdQ/BSyHGVQ6vwtVJRBSMA2zEGjpXi99Y1XsomNujIfXpmOVUQR2vxTpEakNtw6jpXJYhlnIjhHFlh5UQSCoYumWQyluUTmljJv/7iaCkYBX4K6ysYLKxoLJeNWtK6idVUPt7Bpe+O6LHHj4IPH+RCH7REosS9quQ0uiqGDat7PlGFBtV4nlWFp8niGhyMJYReFVVRSCYYUpC+rZMIHrITWYIt49iqkZ9B/tZ876OahKgYm1aC68NgWoKqX1ZTQsnlqkUEhL8ug/PUZqKIk0bSuOXfsEL0NoEr8bnM+YilcjJpWKPzLMXDeDG//meu7/5K9IDiTQsgaFQk4SaUrivTF+/Ze/5tq/vJbGJY3n7d7V06pQggrCkhj5gk+4aloVt/zT6zn06CGatzTTfaCbRF+S9GiKzPY0Q81D9B7p5dpPXUv9/Prz1p+Xi4qp5bzuszdy8JFDjrncIhBUWXDlfKqmVzF0YoCe/V0EoyGaljXSubMdPa/ZkfmepUF6ZnMAIaST/uie0n31Qyhs8AJnQ1akl9kBEqQoWBWc47I0TSwLRttHMDUTobon3UIAoeLcAykxNKdaqKsAWLKof+61wtloFdVVcgSldaU0Lm1g7vq57P3NXkbahjHyhr3hyzFjddxA48dYfA8ASzfoP97P8tcvp6qpkoHj/ehZwzb5OxYL17oRqSohGAliajGQFvlUnqe/+DTzr5yPlJLaObWsetOqCV17boDw1Z+4ir7DfWRGUrYVSoztnyxkqeA83C1bzn6eFKEUXDmujN22VBUqppbRtKKJDZ/aMKHrYec9O8nFs5iawUjHMIGw6s1/QU6F762qQPmUMhqXNbLgqvksu7mYjvvIU0foPdiDns4XQmqEXeCtpCJ6hhU/ifOJyYJik/ijQ8OSBq7/9HVMXTiVQFBxTrpuWWuJlsrTtauTx//pMfJjWDFfCYRnLy6crF2ESkKsecsabv23W7ngbRdQ2ViBGlSxLIvUcIq2l1r57Wd/y4lnT5y3/rwSBEIBVr9pFRe/80Iuec/FXPj2C6iaXgXAxe+5mMpplVQ0lFNaW0rf0T7MnIEaUEG6NS0U5/+2TFRFIVoRoaS6hKKCZPg3Y2cj9jFD2RuE8P7vBoR6PhIpsQzTthAgCte68+0LknSVEX8b/rYFEjWgogh7/OGSEMFwkEhFmBWvX8rMtdMRKtzw6etpWt6EGlTtTdUmAPHG6rbljemUYwUjp3Pi2RMIIaiaUeVZJ4KhAJGKMKFoyGvTzOmYml5w15gWI23DbP3RVnb+fCd7f72XYSet+ZTzGg5w3V9fS/nUcgLhgK9Am9s/V1bSUzKkE+vgydCVl2Jv2mpQIRAOoAYEoUiIyqZK1r11Hbf+663UzKwpun82luXEs8cxHM4RpCQ7mqX3YK8X1OrJyfneKoogVBpk6qIp3PzZm1jzljWESosrje799V7SI2ncMugCm6Ssbl4tG/7iGtSgelq5TITBk4P0HDh1QbpJTGIiTFoq/kixaMMiyqeUc/8n7iM9msa0CkF1SNuSEOsc5eG/fZANn7qWmtnjGfnOHZJQNEh2JEM+mSOfyo9zaYRKQ1z2wcuobKyka28XxzYeJR3LYOZ0Bo738+S/P8HgyUGi5WFmXzqX6hnV56Ff5xdqULXZOxHs+cUu8rEsZXWlRCujjHaOYuQM8FJHbatBSXUJS25cSve+LrKjaVf3KpxGPUuF8Hzq0pfv6ZZBd0+uwudC8SwD7snZc2ngzbmWzmMahp39YmH3D9+mjxPQFwmgKFDeUIaW0cnHcgRDIfoP9zFwfAA1qDLn0rlMW9FE78Fup+5RYaxn7J8o7l8wEmD+FfPtYTr9DQQV6ubVUVoTpWtvt60cSYme1TBzutdf6VOogmUhympKqZ2AWXIsGhY3cO3/u5aO3R0cfvQwuVi2qH+FH1tJs2NHiudCUQTBaIjpq6dTO6/OmU/bejFtxTSWvX58YS8pJU994QkysQy5RM4br7Qs8qksCFGYE5/8kBIzazB0YoAXvrWFm/7hdUVtnnz2BHEnQLtoLhSFqQumMPeyc08lPPncCXb/YhflU8ppWtF0zte/ljFpqZjEHy2aljdx1Z9dTe2sGtSAUjDVOj/5eI7WF1p49HOPFNIMXwGmr5lBVVMlgYBCZiTNjru3nfKzy9+wnJv+/iau/vNrqJtVgxoOIA2LRFeMl77zPBu/uJFH/v5hunafp5LV5xHbf7SVeNcow62DjHaOUlpXysXvvph5V8xzggz9JbElakChsqmCa/7iGmpmVTvzILy5UHw/rlJQtEE7bSEtx9RefO1pX51Nv+9Ad8E07p3O8TYvm9hLEC4LIRCYWQMtkUNaFloiR+/BHrKjGTLDGbr3dNF3qBfFUxZcZfUs+ycKvwdDARqXOkGMDqeFkIJIaZBYx6jNqul8VjgZEoqjqLjvR8rCLL5+CTd99uYJXR9+9B/tIxvLsuzmZdzwVzcQiYaKS6r750JSsGRQ/N1BWhgZjWRvDFUIpi1rZPqqJuaun82SGydOHe071Evf4V7aX2pj4Gg/Vt7wXFNY0ldKfaz8BNKys44Gjg6Q6CuwLDY/d5Jn/vtp4t0xcGnSvblwrZPnhraXWnj6Pzcy3DxE9RhLyyTODEuK8/LzasWkpeKPHKvetIq6ObX86hP3kk1ksSzTt0lJzJzO8MkBNn/pGa7727OvTzAR1KDK1IVT6NnbhZ7RGO04M4PbqjetYsrCKey6Zyc9+7qIdYxi5g0sw6TvYA+Pf/4RLnjXRTQsaaBh2R/GiSkXz2FpJliScEWUSz94GWvuWMtv//YhryaES88gJU7xrVq693SSHU77SoA7n1X8yoT0grTcYEgvDdPn3hDeP/6gSpvN0m3fTUmVmkkulnPSJH1tuf1zPy+lPS7TREvmvLRN07Qwc4azwVoku2OkB5OYumGn1frbxOdecfvnWCZcgirX6qII2yrhQnH6hGUycLgPLa97ZeTxKUJutoyl4LmVLvvQZZSdgTEyM5rhpe++QDAc4HX/eqstR1/ZdDvjonAfxT8X/hgZl2tEWoy2j7K7ayeBSAAjb1DZVEn7tjYWXLOQ6etmFqV8pgZTZEcyWIYBpi2xcWulYBCxFSQFRECAVCmfWs7CaxdS7vDMGHmDbT94kXjnCNIwnROi22G77o0aODe3h6EZvPSd54l3jlJaW0Lj8vMXczWJ1wYmlYrXAKatns7lH72SnT/ZRqxz1Hvu2A80ST6eo+2FZrp2dTB93cxXdC9VsdPxLN1i8HAfA0f7mLJ4fDqdH43LGnnDv9xC74EedvxkGwOH+hjtHsHKG8Rah3n2ixupmlbJBe9dT8OyJurm/X6DObVkzj4FhlQalkxl1ZtWM9wyxMChnkIWhuPfUIRddyE9kOLBT/0KaVlgSoSKt1G6J2N/wLfAl07qvbqfsLxr3Q3JNZuPtQx4nBl+3gNf//y+eyww0nk7ZiEiCEXsTAu/QgBgmabNGiml1wcotOUSNnj9o6AI+a0CakChYkq553qz91A7mwIBQVVFN/VieVAYqyoEZfWlrHzTaioaK888b+k83bs6CEaD7P/1HpbfssorKOfeY6xFwh2zOw63D16FUtPENEws3bCDoDtG2fuLnbRuaWbZrSu45EOXe/ff+8ud6KlCIOWEcyEL9wmGA5RNKaO0vpxwSYgL3nMxcy4puDKe+/IzDB3vt0ui+2OEgVA4SP3iqay+fc0Z5eLHlv/dxMCxARRFUDWtiqaV586A+1rH+az98WrEpPvjNYK1b7uAm//5FqLlEc/8jfMQw5LEu2K8+K3niPfEXtF9lt+2ikh5FJBkRtIed8PZoHFFE7f+55t4/b/fyvQ1MwmXhjBNEy2dZ+jEEBv/5XF+++nfcPTxQ7YP+feAE88cZ+BoL5YhUVWFaSunkRxIMNo2RHoojVtHwh/PYGR0evZ1kU/k0LOFmACvqiaAb+MVivDNkWvOpvi6oo1QFt4f+yySdvXWyoYKgpHg+Lac69w8OEu3UzrL68qIVpV4n3XXivD97lojitoqatP9XXipo/6xSsMil8wxeHygME5suVbPqCJUFhonJ2/jFwJVUahfMIXLP3rlWVXf3Pq9F8mOZkj0xNnz812kR9NONo0sats36MLB/1Rz4Y4VV3mzMHIGsc4RTmw8SmYkDUCyP0FqIOWRUuEoZOPa8v3N0g3S/UliLUNoqTwNvkyt/sO9tD7fQj6ZL54LV7kwLYIhlYZzsDR07+mkefMJtGSOkqoo1//dTQQj4+uKTOL0cFNKX+nPqxWTSsVrCDPWzWTRTUsJRoPeZuA+yUzTpGtXBw998n569ne97HtMWdxA+dSy4ofwOaJxxTTe/NU7WXLzMhpXNBEqCTt03xpDJwZ4/B9+y4Ofup+Tm44V6JR/B7BMi+3ff554dwxFsYMvG5Y38shf/4ZH/+4h8okcwUiQqUsaKastQ1EVJBJpWegupTcUy77wFghQAyoVUyvsrAfhmMBFQVkQfsH6a4wUdsSC9cE5VgtVMOOimYRKQkVteK+Krw1spQYpySey4/rn/nhcHIxpa4LdNxBWKW+oIBANFLdlSRJdMbZ974WCXIQgXBHhso9eWSBtUvD4L8AeT1l9ObMuncOqt5zdSVxKSax9BGlKLNNipHWIhz55P9lYpnhshRdfn84wVoVxc6EGVUpqS4lURunc1cELX99MZihV2PwVX9v+Nn1zIS2JntPRszqRyigRh1U2G8ui53QyIymHA8XXP6dNNahSO7f+jDEmfvm8+K3niHfFCEaCrL5z7RktjJOYxESYdH+8xnD5x6/CzBucePooejrvnZQk9il18EQ/L35jM7d/8+1n/UAai/lXLSDWNmz7/19mG+GyMDd87vXkU3k2/9dG+o70MtoyhJbVMDIWg8f7ePIfH2H1W/tY+86LUAKqt2n+X2Hrt59n8Fg/iqJQNbua9R+6gpnr59C6pZmR1iHAAgtKqyOsvmsthx4+wGjrENnRtE2s5Gy0XoDkmFcVQVltKa/7zzex5cvP0Hewh2BJEKEKcqNZu9AYBWXB/sW+1nVzeG26cQsA0s7KqZ1VQz6ZRepmwWXhP4kLO+WypLYUM284pccV7x6Ku1aczV96URS+OI+xUy5sS8mMC2bQuqUZw+0nzucsi6QTeCidgmUlVVFan7VPzIrTsWAkSEVTJSXVJShBlTVvu4AF1y4+67k7/PABRtvsORKANEwSvTFwKLsVn/zs6qBj6M6lf8yOAcOnR/jnAlVQPqWcDX99A0IRvPTN5+je04llmL45GtOWfy68RqWjICjMung2QhF07+nk4G/2EogGJ2jLYT1VFGpm13LZx648a/ns+MGL9O7vRhomwYowc688v4y7ryVYvPJAS+tlHcf+MDCpVLzGUFJTys3/eiuh0iCHHtiHltVwSgt4D9u+vd3s+slW1r7j4nG1Bc4G8zYsYt8vdiItsF6hHc9VLrS0xqb/eIKBw32MtA2j5zVyo2l2/WQru+/eRtWsai79+NXMWj/3ZeXknwkdW1s5+sgBTM2gorGKW/7rzd5J7obPvZ7yKWXs+OFL6DmNrp0dDB7pxzRMTNO0a4c4pchdeIdcUWDYVKMBVt21lqYV07jqU9ey4wcvMv3CWTQ/c4zu3Z0oYZVoRQmZWBppWKiRAEIKDMO0gyqF9JgrLScV0pIgTMmxRw8xdVkTMy6YRe+eTru+BgVlBCEIRoPMvHgOa95+Ift/tZu255q9OhwKY9p0x+Hsiu7m6MaAeIOUYOZ1mjcew3Lql/jZOgPhAPOuWsBo2whtW05iaQbJnhhH++NYul0NtryxkimLpnLFX1xL5VnUcHEhLZtjQlEV0oNJ8slcIXbFkkjDJBBUMTTTmwupQCCiYuTtWAtvrKJ4rPbYHYWqEGjhFbS75KNXUjOnll13b6V/fzdSM5HSsudmjIHJJyoUVRCtK6OivhwRUJCmpLyhgjmXzwPgpW9spmdPJ1LYcUuC4rkQQKQ8wlV/sYGSmtKzktPAkT4OP7gfPZVHDShUz6im2sfWOYlzw2s9pXRSqXiNYv2HriA3mqV1ywn0jI7i5LgjQc/k2fHt5+nd3cUtX77jnNt2vw5GNs+eH71E03+/cg76UGmIG//pFvSMxtP/9jgDh3uJdYygp2xry9Cxfh77q19TM7uWS//sGmZdOu8V39OFZVps/dZzJHviBMNBLnjP+nGm4QXXL2HvPTswshqWbpCNGd7fvAd/0Q5S8OMr0jF76xZ7f7qN/T/fwazL53PbV+8CIBgJ2pkF06pYcfsa9vxsO9nRLI2rpyNNSfuLJxhpHUEgUFzyrSJLhYWezpOLZbj1f+/gnrf9ADOvF6wK0ia7mrqkgfRgksf/5jcse/Nqqt9Rw5GH95McSBTaBCd2YwwZl6ucTGCpwLQwTYuS2jKMrI6e0+1AV2yeCgE88Kc/s1MlTcuuy6HbXBDVM2u47WtvpaLpzIGYY7HlS0+jZ/Jc+w+v9071nsEIiakZBMIBTK3A4SIkCAsnCFU4cvTCMseMtZCyqYYDlNaX2zEen9xArRNMHGsfwcjr+INo7Z8xbeEoBRJkXidaGeGNX3/bOAU52RPH1EykZXmpp16/3FfDYLR1iFmXnh0/xUtff5Z416jNoqoIpq+d8QdDmf9qhDwPKaGTSsUkXnUorSvj9V98M5v+7VEOPrAPI+fUTHc2vFwyS8dLLey/dxcr71x3jq07Zl3TYrT99AyH54pgSYib/uVWjJzO0//8KANHbOXCyBtoqTwDx/p47NMPsPqdF7P+w1e84vt17Wxny5eeYujYAJGKCHOunM+KCfz4u370Inom7zzc/UZtB95Rfszbzi4jEFiGSS6WBQHDJ/u9z6y6cx2rfHMw65LizeLoo008/fnfYuSMIkuF8HUjEAow86JZ2Hca40IBpGUyeKTPpvK2YKR5kFu/cheNK6bxxGcfREtpuMd0xR+DISYYq3/M3jgFDcsbqZ1Xz7HHDpLsT3gbbLInhp7VqJpeSSAcwLIk2ZEM0pJc+tGrXpZCAdB3oIuRliGmLG3Epd72lDsJpmYgNbPIEmHHrFoEQgEs3bI1PnxMpRM864UiqJpezS3/cwc1cwulyAeP9tG1o83mj/CKmJwhkE1K8skcnTvauffdP+KyP7+GmesL8y0Un3I0VnlzXpWASvlZZMMAHLhvN5072uwMEmFXjT2fCvkkXnuYVCpe47jog1eSGkjRubUVPaN5FReREiOrsfWrm+ja1srN/3Uu5dId8h5Lku5NcOSh/Sy5deUZr9r/y53s+sGLduyAJVn4uhVc/qlrJ/xsIBLkxn99I4ZmsPEfHqbtxWZyoxmkbpGPZdh790scum8Xy29fy8UfOXvfsh+mZrL1a88yeKQfJahy0YcuZ807LprwsyPNQ0jDRzbkM4l7KHKgM+6U6r5t72xnf1JZdPMyTjx1hPYtJ3x00q76IBGqoG5+PRd+4HK2f3sLWjo/LtRFGhaGodl6g1eiE7KjGTsF1j8EN77AdW1NoCyNHauQkr49XWBYXPbn1/LsFx7zMmE6t7YwdVkTN/zzrZTU2ib7fb/YSWY4xfzrzj5uwo8TTxwm1jpkZw4dH6C8sYLCid7pn+GUM/fLHjsGJBAJkk/k7Oxdr15LcVKpe4EQMHVpQ5FCAZAeSpEdTju1Vgr3sAuQ2cXVQBQHeTrylIbJ0NF+tn3jOYabBznwi10svHmZw4bqs3755kKoCiW1pSy6eRnzNiw6o4yGTw6w92fbMLIaAgUhBBWNleOU1kmcGybdH5N4TaO0voxbvnwnm/7tUQ7/ei9GzvAC05CQi2do3XycBz7wEy7/y+uZchYFyMrqy6mcVkk+mUXPagwe6T2tUiEtyeOf/jUdW1vIxbOe8tJ/oPuM9wqEAtz0729i3z072PezHUgsUn0J8skcWiLHvp9t48iDe1l86yrWf/Sqs5YLwL5fbKf/UA+qotC4Yhor75jYYnPiicMku2Mo0uZYcAMngcLT369MeAN3eBmEn9La/kOifYgf3vi/BKMhLvzg5Sx6/Ypx9937820cvHc3y25fw2Ufvxozo9Ozqw1DNwsxAAJUINUT4xd3fc8L1Cx6ZPlJMoRtmu/d3cb3N/wPlmGhZ/IoQin0z23bHas3sDGbo18GFujpHINH+7j+X2+lrL6cePsIRlZDVRVWvmWtp1AArHrrBaealrPC4NF+8uk8wpScfPIQZVMrCoaVifrnmwsMy2MfdS0LnmVgAqOMkDBwoIe+A900rPDzOogi1lJ3nj35WWPWChTNhaLYMScDh3qId46w/+fbPYbRieZCAUqqoqy868yyO/zAXrZ9azOZoTFKz6s4lfEPBRae7veK2ni1YjKldBIAXPShK5lx0RzCZWGPoEhxggstzaBvXyfbvvbsWaVwltaXMWP9HNSAHZHXs7ONxCn4LwYO9fDAB++mddMxtHi2mBr5HJ5wq952Ie/+7Ud514MfZd6GxUSroggFtFSOZE+MAz/bxk/e8FW2fePZs2qvb18X+3+xA6kblDeUc8nHr0YNTRwAOnCwx3N9uKyY3v/xUVOP+SlQcQNIL/NASJvbItUbJ94xckrlqndXJ/G2YXZ9ZwsPf+SnWHmNcGXUd1/pZX/kYhky/XGMtF1NVQg7ViNSGR7XPyFBS+Ts4MZExtlopLMmCgRWilKIDVD8Yx47VnxjdRRWBTsZX+omFU2VzD2Lk/W5wK3ZgbTIjaYZPdmPdDg4Tts/sAnKnBLsHpmYM1b3e+Efq0CS7BnliU/dx4Ff7PD6cOSB3Vh5l5dEFssZOX6tOPdTQyolNaU0rJrO+o9f7XB8SLRUzi5C5lsrRXMhOGtrYt/+LtIDCaSbkeL2b3JHmMQrxOQSmgRgx1jc+o23sfiWlahBpfCwczYNSzPo3tbKPW/+Jhv/7jdYxul16SlLGqmaXoWqKKT64qR89QpcWIbF1q9tom9PB5bmBLONue+5QlEVbvrPN3PJx6+hoqmKaEUUIewHcrxjhP0/287Pb/vGGZWLoWP95EfSBEIqy+9cS+OaGaf5dKG6qBDOxoN/HNILoPT/KE4VTMX5sYMDHSptYf9+Ok6nqSuaUIMKuXiGZF+C/gPdaKOZovsW/TibmAIEQyqzLplD0+rp9ubk75+Q4+ZiXHtu/2DMnJ1prLZbxt6MLZAW8bZBfnrL17j3rd+l5Zmj5zTfp4N3PyntTAmHpvys50KOn4ux3wu3LWmYJAcS7P3JNvoP9nD80YN0vNhsk4mdYS7GthUOB7jqb27k9h+8m8ZV052xUDwX/rWCRA0qdnXU915C1RnqdYy2DtG3r9MLFvb3TzlVfMwkzhqu++OV/rxaMen+mEQRLvrwFfTt7WDoRD/CKjbNGprOaOsgyZ4YmaEkl3zyOupP4Q5ZcNMyRlsHOXjvrgnTUgeP9vHS/zxF9+7OYgXFeaapQZW6RS+ffGfFnRew4s4LOHjfLnZ9bwt6RiOXyKKlcmjJLPt/to3mjYcJl0ZY98HLmX3lQgD6D3az7WubGGkeRAhB/dJGVr394jPfcOyzWJziVY75P45pQPje9zdrWjQ/dZiurc1Uza7j8r+6kQonrXLVOy6mbfNx+vbZMpRO5oRwTRWnQTASZPrFc9j3k60UuS3G9Y9C307TpsBdK6JgQx8TayEUhdKGCgLhgO1ec8wWWlojnxpGURR2fmcLU1dMo7S+/PQDOCNkcXqr20n/6znOhdtYYaxjPiclqb4Yj//FL7EsiZ7RPPKy02JMW4ZmsP0bm5CmxaI3rPQsWY5vanz/BCiKwszL57HoltPHLh1/7AA7vvkcyd64E9xRaEsJqFTPm3KGzk7iTLAkr5yn4lWs200qFZMoQkldGWvfdynP/9cT5IYzvgdaAWZOp2dXO49/6pfUzJ3CRR+7hvql45WL3l3tqEGFSGW06H3LsNj+lWfo3ulEneM81xwSBEUV1Myr44IPvfLsjeV3rGP5Hes4eO9Odv/gBbRkDi2dQ0/nGT2ZQ1EVnvuXR9heuYnKGdVkRtL0HehCGpKKGdVc/LGrz8h7UTO3jlA0hJbKeXEGE8nNfcfde8H+rFcgSxTiINxXpCQ7mCTn0D3n41lwlAo1qLLs9rUMHevFSGnefYt4Kty28O1dwuaO2PP958nGM97J+az7J4v7KXz73YRkHM7bwbDKnCvms/mfHybTn/BiGLy0zJBKIBwgn8idk1Kx98cvES4Ps+TNa323drI9zmJPn3Csiq14qeEglmGip525PdVY3WEaJun+BEJVvBTNcfKjeC7GtiUNk0x/krbNxzn6wB4Mw/A+d6q5sDSd5icOMeeqhcy8bP4ph9q+5QTxzmFPPh5PiqpQPaeWiz969ZmkNYlJnBaTSsUkxmHh61bQt7uDE48dQHNYN/1B7wDoJumeOPlYju7trRMqFdK0sLIaoiJK1wsnaVprFyvTMnmGj/eBS97jbxeIVkVZ/a5LiFaXnLcxLb/zApa+eS2H79/Fnh+9iJbIomXyCMsi3Z8gM5Ak1j5oE1XpFooqaFgxjWkXzj5j20vetIaOl5ppf+Yopmba5vBTZH0UNhNhF/lCepuVyy3hF3Uh30ASDAcoGVOJs7SujJLqEpJpzd7EpGP29/FUOLqJzbcgbIZGEVBsRcUqTj0d2z/XxXGm/uGMw/eHQpvONeGyMP37Ounf121nHCiFEt8ioDDzsnnc9N93nlUdDxedLzaz/+4XUcMBahdMZYoXKCmdQmvuXPjNDMVzowQVLN0qmgvVUYJmXzWfYGmEQ/ft9DGRnmGs/jlw5cfYufDJb0x/hCKoWzQVpKRvbydqUPWKtymnWCuoCoFwgETn6ClllegaZfhoX8Gt5rYFRCrCrHr7xZQ1VJy17CcxMSazPyYxiQlw+Wdupm5xAzu/9SzZoZT95hiTK87D81TVbyzNxMwbpHpidG9tgU9sAGxTbWldGdmRpH308p6MEiWkMmfDYha+YSW9u9rZ+8Pn0VOat7VWz6lj/aeuJ1QeOecxKQGF5W+9kEW3ruLor3dz4OfbyMUydl0OKR3WQzfAUjJ6vJ9Ub5yys8j5X/cnl9O/vY3saBqEWwLcJyufzGy4tSzcuIkCfbdXWdTRuFwZJ9qHefKTv+TCj1/D9EtsLoHp6+ey+A2rOHzvDiSQT+Y8zoGJ2lJUQUlNKaZukHPYMs/UP1fxk742wbVWOP3zr40ACBQvvRVhW1XmXruE7peasQyDUEmQQCSI5lRFrZxZw0Ufu+acFAqAtmeOkotlUBXBti9v5Oavv51AJOgFL1r+/vndHe76VQSRqhKyw7YlyJ0LAD2Zo+XJw0QqS0BaDtdFwT0iVJVQRRgza2DkNY9Zy8ukcOU3di4UUMMqgXAQSzfR8zpCKDbjpqJQs2AKS29fw94fvQimzcqqSEBxLUpj2lSgclYN1/zLm5iyrGliOT17jF1f30Sqe9Sl3nD4RiRCEVTPqmXJm9eck+wnMTFs98crb+PVikmlYhITQlEVlr5lHYOHemh98jBaJjdhOp1X9GkCuAFspmFiZHXv/VBZmAWvW0GsfQgzq/se+IJIRZS1H7wCLZlj2/88xeCRXvtgKG0CoeFjfQwd6yNUFmb21YtYfjbxDmMQLAmx/B0XM/91Kzj6mz0c+80eckNpTMvCzOmeZSbZPcqTf/FLLvj4Ncy8/PS1EIIlIaK1JeTi9uZUdII9hdXCe8Of5eJWr3Q2c+n9LjBzOkNHe9n25aepWTiVklrbarHuw1ex9M4LEELh6U/fz8jJfvKpvJc6Kn1tKaqCFs86LI+AamebeJwT407yTv+8qpqF14nHA8GSMNGqUtIjScyMjlAVqufUM2P9XLpeOEnVrBoW3rqahbeu5rnPPUSsbYiFb1hF7fxz8+fnYhkGD3aDJbEsSbxtiFRfnKrZdTbjpOum8fdv7BqW0ilHXuTXsD9nScycTjqfQFjSp5PYjYZKglzxd68n2THCru8+V7yW/fKTcty8BkIBZl65gMqZtbQ8cciuexJUUUIBpl04m3wiR3YoNYakzLdWBKihAEpQIVQWYeEbVp1SoQA4+ch+RpoH7e9R0V/s3xTl7GP2O7acINE5wrK3XXQO3DWTeK1gUqmYxGlx2d/cTMWMag7fu5N0X7yQR+8+SyyLvl1tyPdcghjzYCpvqmT4WD/SNMnH0gwe7KZ+uW2ejtaWEq0uIZ2NF518hQqjx/vZ96MXibUO2add50EtpYWZ0xg+0otQBLHmAaYsb2LKytNlZkwMIQTRmlJWv+8y5t24DGlKdn7zWTq2nECoAj2Vx8zrjJzo58V/e4RjC6ey+I4LmHHZxMpF5cwa5t6wnIO/2EZ+NHOK0z/F7+O3ADhkUmOsQYVfnUZMi8xAgt4dbcy7abn9MUV4CsYNX7qT7Giaxz9xD4mOkYJS4p6SdRNDFsrRh0rDhCsiZEbTWBl9XACi38rBWIsEuLb+omtKastZ95GraH50P50vNFMytZz5b1jOnu8+hxpSuerzt1K/bBpCCK7999vJjqQpb6qaUK6nQ/++TtIDCdvKJMDIa3S9eJKq2XWeXMb1zz8Xzlo2NcOxWvjmwg3YtPDGPXYujIzGjv99imAkVGytG2uZmODeelqj49mjVM+pJ1IVJlQWYf4tqzn54F6anziAIhSkYXpWEa8Jp39ISbg8zJWfu5Wq2XXnJj9//wSIgDgraxxAuj/Ojq9sRKgqi29fRyA8uYWMxaT7YxKTOA0C4QCr33cZ8ZYB2p89ip7VkaZ0TigSaRjEmgfIjqQpqSsOrlvxrkvp3dlGPpZBT+bY+p+Pc+M330moNEzTRbMJfEtFKAW/siLAzGq89J+PkeqLYxmWzZXhHTedk5oFWBZaIsvmzz5A3ZImlr19PVNWTj/n8QkhqJhWDcAVf/96Ep0j6GmNl/7rMVJ9CfREjsxAgvRAgpET/dQtaWLRm9YyfYJguDUfuJyhQ910vXTS3hAQBEqCGDkDpIU0nY1L4snP3iicTUux5VrE2ujaGqRNFS0RWJpO786CUuFHqDxCqDxCeWMl6Z5RJ7OmuC3hyFEiUAOCVe+7jNaNR+jd3uLNhXcAFfjcG6fpH45rQBEEAjD9krkMH+mmf08H1bNryQ2lMPM6wZDKsV/tZu93twCSmnlTWPsR2+2R6Bxhz3c2oyVzSEvaFqV3XuIpouMhQRbWiJnVOfyzbcy4dL4df6BIR0ny1/B05Gj55gLAoTUfNxfKacYqLVI9Mcft4bqJHBmPacuz+LhrWVoYmTxDh3uQ2BakWPMAuXgOI5PHsvDSV4VPofPPhZnOseNLT1K7tInVf3I5VXPrx0moe1sLR+/fydDhHgRWkfvE7V+kPMrK91xyChn7pC0lW//rCbLDScqbqpnQdDkJu0rpOO373Nt4tWJSqZjEGSGE4JK/vpnSqZW0PHGAZFfMjhp34iGMdJ7+PR3MuX5Z0XWh0hCKanMSSMvCNEx2/PcTBEpCpPsT5OIpO1DQNXBIMNMa6bxhk/IoovDcKjrBOw9WwyLZPUqmL0moNPyylIri/oapW2wHnF77H3cQbx9m51efJj2QQE/lyQ6m6Og/xsjRXmqXNhGpiLDy/VdQ1lgF2C6jtR++kkTnMInOYQQKDatmkBlMkR5MYGR1LNMCy/Lk556mPRZTd6ieGd7ZTHyvlqbTuekoA7esYsqqia00dYumMnSwC920UAIK0rB8W4DTlmVzEwzt7yTTPYI/DkRgW04UxaGA9vfPPxey0BaKPTW54RSb/vJelr/3ckaP95MbTtHRPkzZjBrKm6ro2HSMfCKLoghGj/cz9+YVpHpi7P7GJhLdI5g5w4kVUBg53s+U5U0suesi6pYVKxeF+BdHXpZNdPXSFx6lZtFUu7IqY/qH9CwU7jC8uXCVrrOcC6REjYYKLjNHNtIaLz+vMa8t59VyNnrdIt0XR5oFObpydvs3di5MzSThFNXrmFc/TqnIDqfY/t9P2BY/h/peUUVhrNKmcC+pKyV8FjFKnc8fp3dHGwBzrl9KIBw84zWvRchTh5mdUxuvVkwqFZM4K4Qroqz76DWkO0fQYllMTbcfUgLMrE7LowfGKRVCEZRUlaDFMwhhBwiOtgyS6Y2hZTTMnIYaUAiWhDA1AyWg2IyPzoNT8U6KE8A5cdm+b5PBfR08/7nfgCWZsmYWC9+0duLrzhKVM2upnFlLeVMVIycHOPD958gMpNDTObKDSTo2HSEUDTNytI+1H99A03o7cLJ+2TRmXjafjs0melqjfmkTs69fRqJzmIE9HXRtbSbhFFlTHfOznSboOxW7ZdL9Znsfn4BwNrTOLccnVCri7UO0PXUIqRmES0MESsJoiaxdmdTfpqOYdT57DCNv0z+rJSEs3bRdCro9D5YY07+xJ1R//6RET+cZOtBN+8ZDNF08l8M/34aWylG/tImeF09gpHK2hSEQJFwZ5eQDu2nffIzMUBLLMO0NX4AwJanuEdI9o4wc7WPZO9Yz/41rim8rXCpsW26WZpDsGiE6pQxFsRkn8f/4x+64ORRVoAQUAsGATc8t3IJszlyMHSuAIlBDAeoWNTJyog89a9fNcd0KBcZUN232NG05cnPVGr9VQzoWFG+tuHPhtKUogvLpVSx96/iaNM2PHSA3nAJHQR/LJmoJiFaXMu3ieWd0n+RG0+z5+rMY6Rxl06opbzg7d8kkXnuYVComcdZQVIWLP30zke8+R+fzx0l3x5zUNImlG+M+XzWnntpFjY6JWFLRVIkSqqU7niE3kkZBECwJsvhtF1ExrYYTD+9lYG97sYve8XX7LRZOTKd9cHS4LZJdoyTah1GCKn07WqmeP4X6Fa/McgFQPW8K1fOmUDWrhpGjfRz82VYyfXGstIGR1Rg92c+2f3+EpksXMPOaxTReOId1H7+WKSumIy3JtEvnEa4soXZRA7OuXkz904fZ/+3nyAwlMTQDNaCgp7WisUqnJkQhGEJ6Y5WmJFwaZvYNy1g6QZCqqRts+8Jj5EczhMsjTF03m1BpiJYnDtpBtaLg3pDC5quQppPZoAjCpREiFWHb9aPnPUZPt39qUGCZwlN6PHeCr39CSqRlITWD7EASDIvSujIy/QnyozYvhqooVEyvpnHtLNqfOUJmOOUpqV7/pATLQlqQ7Bxmz9c3keweZfl7LiNYGnYo3QtpqXaXbOpvm3XS3did+AG3fxQ2awmEIiGaLluAmdXo29uOldGcuhxy/FwoztYvIBAIoMUzmE49DqkU+uFWElX87hC3LVeghU4jFQhGQhg5HZCFTBuK2wQIhFSkVFBUhZIpFax87+UEoqGidTB8pIfuzcewdKMggzFtCVVQPrWCdR/fcNrvgJSS7V98nEx/HAGUN1Ux67qlZ/zuvFZhnYfS56/0+t8nJpWKSZwTorVlXPT/biTdGyM3lLTNta4JegKUTi23zbaW/Uhb+7ENlE+rZv/3t9gmcFUhP5QmHVAwsvkihaJAFOQLYnSqRbouA8BWakwLTAtTSrIjabb/56M0rp9HuCzCgtvXESo79xRUP2oXN1G7uImqefXs/eazDB7qtoMe8wbp3gQnf7Ob3m3NzLxmMYFIiPm3rqZkSnHOvxJQmXvjCkrrKxg61INQBd1bTjB4qAtpSgzNKBxmnbG6u4AnF2FbjRrXzSJaU8xZAXDkZ1tJtA0idZOSujIu/fs38Pzf/7ooR83dFIWb1SGxN0sLtESG/IidQqyogkA4iGmYqKqCBYRKwlimiZHVMDWjoAz5lQ9hK6DStOjacpxgSYiqOfXEWgbtUuMBxR6WbtD94kmbL8Ms7Ljuad1zx0iJaZhkR5K0PnaQ0ikVLHzLBXbmQ2mY3EjKt26E04xSUAB8a2Vs2zaplERPZKicVUd2ME6yM4aVytltKQIlpHqWBCWgoAZVTM3EyOZJ9uh231VRNEfC950oMpK4yoUCaijoKWMioFCzoIF426BdVM/XP3zXq0Gb9XL2TcsQEkobq5l+RXHwsJbMse0LjzByoh/TIZdD+Nryf690A0sz4BSuDC2Z5dBPXqJ/dztaKocqBKV1ZROy5E7Chkug/krbeLViUqmYxDlDCapc9Jc38dTH7iYzkChEyJ8Chdx+SSAaYt4bVnL4Jy9iRQJUz58CiuDoPdvsU5opEQFn03P94WLMyc09glpuoKN9f/dv0jCJtQwweqLfZmYUUDm7jqnrZhMsDb+isdevmMFln3sjzY/sp/O5Ywwf7sayTDAlqe5RjtyzDTWkMrC7jcaL5xKpKWPOzStQAgVWzqlrZzF17SwAZl27lJZH9mNqOq1PHCQ7mMAy7PFbDt+EZfk2JVWhdGoFM64uLsBlGSatjx7gxIO7yccyKEEFRRXs+/YmYi0DSOfE6smPwgbuHoqktANvpQlKQBAqjzL3ltUEokFnkxTUr5nJyOEeurYcZ+hwt+0qcZU8CtkJro9ei2eonFPP7BuXset/nvRtthaZ/gSmaRb4HYQ7h97C8V6FEA7jU+EDDRfORY0GUAKuecNeY6auk2gbBKfWh8vUOuFawc4a6d/VytCBTk+xc10XgfIIs65dQrS6zHFhCFJ9MTo3HQXTolA6XfpkO0axcBU4V7sQIII2ZfnsG5aDFKjhANOvnM8zf/ZzxJj+CUWC5bgtwirVC6aAKVEjARovmj0urfPEr3eS6Y9j5Q2E6ibLjmnLKZcqpeTkQ3tZ+o6JAzV3fukJerY2kx1OorjK6ISfnMQkbEwqFZN4WSifUcPsG5Zz8oHdmBmNYHTik44aVO2TnWl4p690fwKpG0hdJzeUZMrqGbaZ2zARQqIqAtOXYSIQdsEn14wtnRh84fqh7XalKMT4S91EGhZaPEPX5qOMHKkg3jzAsve9curvkikVrHjf5WjxNLHjfVia4T24MS2srMnQ/i4G93ZQ1lDJ6JFupqydzfSrFxcpFwClUytY8SeXA7ay0bXlOCAZOtiDkc2THUiST2URzsarKIKK6dWoweKv7rFfbOPkA7vJ9MYIlkcoqS1HVRVaHt6LmTfsLBs5Rn6cQn5CoqCgKFBWV0bN4gamXjjXu1fTRXMx0nlizf0YujmuLaFAuCqClsiiqgqVs2sJhALOfmoX77IsW/kTTq0SzzQvsN0nrjwdRKpKqF7cQP2qmcy52c566d/RgtQNW3lQFW+tmCmNVMewxxx52rUiJEIKpG5iWRIMCwKKPQ4EKlAxtYpFb72IoGPteunzDyLcrBN8+SBCImzy8cJYFXus/rUsBSiGbVkTlsWSd15KqCJKPp6x1zpyTP/cNiUyq9O58RDthkW4MsrIkV7W/8MbixQLUzNtl4wY/71w2wqEA1QvbGTqhbOZ94ZVE67z/p2tDOxuJzecQrEkIqCgBFQCp/iuT8LGZKDmJCbxMlG3pImRg12YmsmSd1w64WcWvuVC2p84QE5PIaTA0k32f20jeioLpiTTM8qJ+3ZgZvLeSUgNKChKwKb5Bs9nD+4pyUmLBGx/yHifsbuBSs1g5HA3yfYhymfU0L+zBaGqTFkz6xWPf9EdF9G16SiZ/jhKKEDdihmUTLGVl2TnMHrGJD0Qp/nB3fTvsE/CtUunUT67jppF42nNGy+aS+NF9uad7o/T/fxxep47Tqo3RnYgiZ7XUBWFgK8Eu2Va9L14nOYH95DpjREujzDjmqWseP8VtPx2H/kHdpIdTI0JBCzIr2AFchMuC7EJRiLLoR9spmxaNVf+99somVoIzlt4x4V0PHOIdN6wgyt9cxEujxIuCRGMBqlb1sS8W1bT8/xxhCWLgwUVgVTstGLLlJ41wX8aFopABBXKp1Vz5RfuKLI0SUtiOfEMBSsJSGkRLA0TKg2THUr4slYmjlVwr1V893YtJmY6z/Ff7SDe3M+Ma5eSG0kxuK8dM6eNiVXwyU84pd3dNov6J71skGx/nJMP7CIzkODCv30DvS+eQBHScxf6++H2z3II2qRpkR+xGDnUTbx5gKr5UzHzOqPH++yrpBzTP4rYVVVVMP3y+Sx773glO90bY/hgF8fu2062P25nuwChaJDaFTNYdOf4oNBJFDAZUzGJSbxMNF4yj0xfnFk3rSBaO96/D1BSX07plHLyQ0mEkDT/Zhexk70226OwA+fMdM7ej5y9MhgNoIQC6Mk8upn3kQi6dSZgrLvF+4znN5b2ZyxpKydBg9jhbnq2HENVFdb/0+1UTpDXfy4om1bNgtsv4PAPNmPmDQJBhUv+8TYyAwkOfn8zWjLPyKEu0n1xkp3DpO4bpTW6l2h9Gcs/tIFANIgaClC/auYEFoxKFt5+IdMvX0j7xkOYWY1Y8yCBSJD5b77A+9yJ+7bT/MAuUp1DBKJhpq6ayUWfeT1CCJa//0os3eDYPS+hZ0zPAlAkP8dt4W4cni8facd5pPNk+hMM7utgxjVLUZziaiVTKrjgUzex7xvPkOoctqnOhR1zUFpfjpHKER9OsfRPrqDtt3vp3HwEK2d4J3ghBOGKCFPWzUYogsF9HeRG0nZsjLT7JxRBqCJC1fwG1vzZ9eNcVw0XzqGsoZL8cAppWc46sFCEQrgsRKSmlNxwwjk6+sfqXyPumKXPO+HGCdlrRxtO0vP8MXqePw6qxMgYPnlRcNVRWHduW26Qpvd3X1qqNE30eIZEywA7/vkhRo72YGY1giVB9ETeF/vgtimL+yckRibvxCvB8V9uJ94yQG445ZRt9ylnY74Xp9uydn/pcQZ2tmJoOtI0PY9TMBpi/m1rqJqsZDqJ02BSqZjEy0awJMziU/hiXVimS30tyY+mibcOkk/k7IeryxvgBs45D349mbNz6AxZtMkhx9TUKApnx2ujYIq3PySExMob9O9pRxoWofIIo8d7EaqgYlbdK5LB1LWzOH5PCCOjefUjSqZUcNFnbgGgd1sz+7+20bZcpPLopomeyrHjXx/CyhtEGyqYceVipm1YSrgySvmM2qL2S6ZWTmgFklIyfKib5gd3keoYJlASYvoVC1n58euKTOGjR7qx8qazCYoCxwIUXv3yc10EnqwFeiLDvm8+TfxkPys/ep3XdtNlC6mYU8/erzxJ70snQUL1kkYC0RDD+7somVrhKCTtGImcXblTFNoWSMqnV7Pq49fT9cxhWh/fz/DBLq8ia6gszKzrV7DiIxsmrPUSiIa44K9fx6ZP/IR8LOP1V0qL3FCKshk1hErCaKmsT3A41OR+d0jxWinIwFEsJBhZrSAzWdikiwJd/W1JOU6O3qvPaqSoKkgYPd5HqnOESH05wdIQ8fRgoQ3sgFGhKAhp2imlKkRryph900oq59jKcbp3lO7njmLmdEzDmXOPVr24f4oo2Pr8SHQMk+oaQUvnCtcCQlWI1pXRcNG8Ca6ahB8F9e+VtfFqxaRSMYmXBUs3SPfE7MDBadXjgsVcnPjlVrL9MaRm0L+tBWmaXpqbRyaEz3QtsK0LTm79ROlwnl5RZFt2T2+umVd65l5wToaajhACI5Vj93/8lrJp1az9q9dTt2rmy5ZD5fyplE2rRk8UIvb9aLx4HpWz69j3zWfIj6SQEkb2d2Ikc0jLItM1yon7ttPy4G5Km6pY9YnriE6pIFpfedqg0pYHdnLivh0kW4dQwwEaL5zLxZ9707h5yA2lCwRLnnWC4mi7ieQnCvKTpkWuJ0bPc8eY+8Z1lDkMpABlTdWs/eRNPLX/O1i6RcX0GrLDKarmTSFaV8bJe7ehZwpl2b3bIdETWXqfP8bcW9cyfcNSpm9YSuczh2n57R4wJU2XL2LBHReeVv7VixqJVEbRY5mCq0BKzLxO2dQKrCWNDOztsGMvnJuroSDh6ij50QxmVhu/VmC8m+R0z3j/GvZdi+KWoReFewjhvarRIDVLp7PwLRey4z8eBilRVYUVf7qB7Z//DUZas+NbQioldRVE68ogqKAGAyiqwuzXr2bmdTY3TKp7lKE97egpnzLg67M9r05mTEAhXFPKrBtWFA0jdrKfHf/yIMmOYY+N3xWAIgTVixpeViG/1xomC4r9nnH//fcDMDIywty5c7nuuuvOcMUkfp/IjaaxdIMTP99K+6N7CdWUMufWtSy44yKU4PjlpI1mbEIrITGzOQCvSqL70CsoAmOUCxjjX8cLWCw6Zfs/K4rbGKtkAEjTxEhbJFoGOfS9Taz/lzsIV768MuuBSJD65dNIHO9DmJbDeFi8A5VMreSSz70JsJWxR2//ClYu7wUlWjkNqRkkTvbz0mfuRSgKdatmsubTb/Dak5YkEA4Qriol1TVM8692kGgdQEhJ6dQKVn/yxgkVO5ua2T11j5Gdq6WdzVxISW4kRXYwQWlTVdG9InVlVM2bSqpzhMEdLVimZNWfX0/XpsOY6Zy9QYkxbWPPiRbLeDEZUkrqVs6gdsV0orVl42rJnAoKdqyGpRSGpgi7Km39qhmMHOjENApjDQQFU1ZMp+fFE6dfK65VQsFJZfbJbaz8XDeHXxkTglBVxK7Wm9GwsANOK+bVI4DyWXWs/MQN7P3y45jJvK0jWyaVs+sIloSwMs4aMU20kSRmJkdpYyWrPnMjoZpSu3qqA2mY5EdTXixH0ffCVy1VDQUom1HL8j/dQKmP8Cofz5AZiJPuHnGUb2e8wifPV+/heRK/Q/xelYqWlhaeeuopvv3tbwNw/fXXTyoVf6AwMhrdm49w/KcvkOkewRJgpDX0ZJaj39tEqnWQdX/3xnHX2T7ZMcY8z+TgfmiMr9jnMy4QIRVbH6S/La8df1sU2sJ5QFogFLdNCYbByJ52nv/zu1nxZzdSs2TaOBKhs8GM65bT+dRB8kMJjv/kBRa9+/JTflZ3GUP9/RN2cKp0ZIq0GNh2kqfe9nWbXloFaUjKZtUy5YK59Dx/lFT7CIGAQtmsepZ9+BpKHarwsbAPzE4QoUvzPFZ+ZzkXZjLLzs//mvl3rmfB2wpuLyWgMnXtLNvVktUpn11H/ZrZdG085Lk7iufCflUDKhUz6yhtqsIyTJrv307zvdsw8zpzbr+Qxe+6fEJFdfwYbUuAQmGtKNKxdgk3KwRvrZhZjd7njmLqxqnXirve8L0KH+X2KeRX0DdsV4rMaXY/sFAVQWlTBVf+zztRI4UMinTnMDixC9pQik0f+j5GMl+YC9PCNDWsvE48mWXLJ34MCBovX8SF//gm78Zuxm1RRyjun6oqzLppBU2XLfTeix3vZfe/PUyifRAzbzhy9NOLC4JlYWaOsWxMYmK81gM1f68MJhs3bqSqqsr7vaqqio0bN/7+OjSJcbAMk84n9vPsB7/D3v94iERzn13wKJ23WQuxAy37XzxG+2/3FF2b6Y0x8NJJMAw7JRTpXaMI6Zwwfb87J3fFecArQhSu8Yoruf/3XQvj23KuUxQKbQt343GzH2wm0PjxPrb+1c/Z8rEfMnyg45xlVLN8OnNuW4s0Ldof2U38RN+En+t74ThbPvEj8sNJu2/+saqC+tUzqV0+nar5U203TSKDns6hJbIYmRzx47203LuVVJu9CalBhYV3Xcy0Kxefsm8Nly4kEFY9mRXJ7xznQpomub4YbQ/uJNk6WHQfoQjQDQKRAMs/ci2xIz3EjnXb9UWkNW4uApEgdWtmseLj16OoCrv/9Tcc/e4zpHtGyA8nOfnzF3npr35uV6k9E4Tdtn+tYJmM7G5Di6XsUzaFtSJMEyuvO9koxWtFCN+YKawVT36nWHee/JxUU0Wx5Sfzhs3wKexYinTrIM999Ick24YA6Hh0L6n2AQQWSAtpGBixjKNkjJ8LaZoYyRxGMku6c6ggA2nL4Uz9s/IaJ+7ewsFvPGVfZtpp1+meYYx0zk5zHTPWYCTAjGuXMsWXVjyJU6MgvVf282rF71WpaG5upra2EJhWU1NDLBab8LP5fJ5EIlH0M4n/W3Q/fZBn3v1N9vz7QyRaBjAzhVO230eOhPxompP3vGTXGnBg5HRyw0mUgM1V4U8ndE+IguKiUK6JVXEadkt/2GmD0ksftK8R3gYwri33aykLv9ttCvtE5yoYSDBNO1vheB9HvrPpZclqxrXLUFSFTPcoh7/zzISfyQ4nSXUOg2HimqP9Y6tfPYtrvvcBrvzWnzD9miVUL26iamED4coS293gBL26kf2WZtD20C67dPcpMH3DEtRIYGL5nW4uHJeC2z9XftKSpDqHeeEvfkLbg7u8+9jX2tkadetmc/RHm8kNJMetFbftYDTIus/cSsuvtvP4G79E19OH0FM5L7jQSOUY3NnK5g9/n+H9p1f0XAuDf61gWeSGU04she1COuNa8Y9VgBIOOAXxCmvFvcZra4z8xo/VF/pjScycTvx4L0e+a6+RdO+oXW+Es58LRRWUNFYyw2c5iNaXUzGrDsVhKx3XP7ctKbF0k9JpNcSO9bD5T7/P1r/5JWY6P+574d5fDQWYdvWS087BJApwYype6c+rFX9wXKsjIyMTvv+FL3yByspK72fGjImrM07ilaN740E2vu2r7P7X35BoHcBI58H0Bfn54CkWliTVPsjR7xU21JM/ew4jkyMQCVA+sw78VUeLLgYRVBGq/UYh1a/4M0X3L4rY9H1ubP9E8Z9dc34Ru4w7NMNgeE8rmz/4XUYOdXFOcPpjGaZtzh4DUzPoeGgXVl4v7p97uWHS/PMXeOx1/8HTb/0qajjIhrs/wrU/+ShL3n81FfOmUjFnCmo4UBijYRI/0sVTt/8PL3z8R4UMBR9KGqvswEpfJVjvdaK5OJ38XDnpJrnBBMk221qhxTN0bTyIpRtYWY3nPvR9Ykd7bPrqCW7hbnLdTx+kb8tRcsMprJxefH/LLg42eriLbZ++h5M/f3Hc2Lx2vcyGYkhLMrS7DamZnNVa8fcPWwnAkhOulTP9XrTeYEzWjSBSX05+JEXvpsN2/85mLpx/wjVlXPAPb2beneu9vwVKwky5cJ73HRoHJ8YiUl3K9OuXM/vWteRH06TaBjGSWaRhjXPlOD4fShoqKZ89mUY6ibPD7zWmYt68eUWWCTdYcyJ85jOf4VOf+pT3eyKRmFQs/g9w8MuP0fHYXrRExiPgOeXGLtyHphNMaBgkmwe8jyVabKpkRQiql00n1TWEZRWi8L02VIVQWZhARZRM57B9CkeiqArByihGJm+zQgqBCKkES8JoyQzSAiWkIjWzUBtkTP9s/kAfo6EibCpwx2fskj6BwC2MlmodIDeQAKfoasu9Wzn5s+cRQlA2q44L/u2t4zIzInXllE2rJp7Oe0qRH5ZhkukbRTh8Cu4tFWH3z67umcPIaIAkfqzHu3b+XZcw/65LMPM6u//lN8RP9GJpJiKokO0dJTeUQBtN88zbvgqWxYzXr2XJh68FIFxVypR1c4mf6AXDoZVGeFUux87FaeUnfHKTFkPbT5LuHkEJqujJLKHKKDUrZqInMqiqzYp6qraMVJYTP3kOM5O1XSu+uSjMCWCaaKMp2h7YTs2KGdSsGP+dr10xg2x/DNPUvewPIQRmLke2N4+QPuXmLMcqHR4JIX2xKP614imnTPj9cL8XirDLr3vrThVUzZvCovdcydHvP0OyfRCBhRoNoYQDGIksEpuOu6SxGsuwUIMKlm6iBoNIJLNuWUfdmtnj5OBak6xCJ2wognBVKaHqUua/9RJmv9HmOWm9bxtWzs5+KXwvCvKTQhIqi7D4fVdRMlmV9KwxmVL6e8R1113Hpz/9ae/3lpaWUwZqhsNhwuFXVrdhEmcBBays5vibxwSm+de5/7nqKhdC2LUFCk3ZwWmNlYQqIh5jof+5jGtiDarULG0i1z0M0jZqqAGVGTevZnh3K4kTvSAhFA2x4L1X0fP0QYxMnvL5DQzvabXTNS07/c7SDMDO61cUu+xnIBxwyqurdvnogIJlWnZ6YV0Z0rAQARVLNyifVU/ZrDosw2T3P9zHwM5m9GQWgUJuKMnmd36N8jn1rP38HQTLowCEKktouHg+yeZ+tMEkXY/vY/pNqzxZtP96O1YyV4ig98nPNTM7B0O77xM8U9RwkAv/+Q7vd2la7P6nXzF6pBsjlUcbSWFqOm33baXzkd1EaspY+CdX4zefS0CogmBVKULaBcSkSzg1wT2L+icoZEhYkkzHEMe/v4loYxXhiijz33EZ029chaUbvPTJuxne21Z0Avab5aVuYTrEZkIZmxXCmBROSbZ3lB1/9VPKZtez5CPXU7NqlvfXxR+4hviJXpIn+8BRmATYc6oqtnXHr3iOHeup5gKKM2F8c+QZyk5h6/V/Lzy3RjhA+ex6Fr//asLVpSSO9SJ0C1XYtVKEKrASWVy3nzBMAhbMvnUd894+Pvi3Z+NBhve0seB9VxGpK/cCVVVRbFwRApsOPa9j5QrWrFTHgKP0TzC/zoXRunKmbVg28SAnMSEmU0p/j5g7dy533XUX999/PyMjI3zmM5/5fXZnEsDCd1/F6O42Ysd7imiTi+C3Mgjf2U1aZLtG6H/hGNK0yPaM2A9VWYjMV8Zcb7/Yf69ZPoP4vg5yIymsvB3cFyoNs/A9V3L8h8+iJ3OUz66n8eolzHtbgRBqaHcrR7+5kfxIksol04gf7kYoEJlSCQiyvaNULmoi3T1CSWMV2f44kfoKcsMpqpdNZ8VfvmFCWViGiZ7IYmXyKBYIVSJ1g1xfjPxwgq1/9iMWfXADUy61i3tVLZlGqDSMnsjQ8tPnqF4xg9JpNYzsb6ft19uwNH3c+AtFtApyRFpkO4Z45vb/Bikpmz2F5X95CyVN1cXToCqs+7ytZCRO9nHoy48xsr8DM2MH8ukjKfZ/4Te2sue4IuyNUzD9mmU0XLWUY9/ZSLYvDkEVbSjhFAhzbuCcuKUzR/4NFgGWYdC36RBKSCVSX8n0G20lSgkGmHHjSmKHO22GTP9YBQRLIyglQaRmoiXSOPoohfPZBOc0w0SLZ8gNJhircZU0VbPwXVdw4IsPOdwOeMqqIgTls+tJtg0VXE9jFYqxc1Fsj/DaKuqfLL52vNvIN9ZoECWgUj67ntX/cDvh6lL6XzhGtnvEDoqUEiOWsmuEOA1J3SDbPQICTvx4Mx0PbGfmbRcy7x02rXa2P87JuzeTdtpY+MFrGXjpOMKN1/GPTUqMRAYjmaH1vq1UL51O9YqZKDh1RnxjtvuOzWZaVULd6llMYhLngt87T8Vb3vKW33cXJuFDqKqEBe+7iuPf30Smb9SOCLcAv3vBhXNsE45ZHCnRYmn2f+EBAPRUFjUUIFhZgnQrRgoBQQV002tTOG3MeN0a6tbO5dCXfsvowU5vo2m6djlN1y4/ZZ/r1s7h8u9+8LzLQgmoLP7wtez+/H1ku0e9jUcIgdQMkid7Of6DTVQtn0moIkrDVUsY3NlM54M7SHYM8dLHvo8aDWIkc+Rjabx4Dp/87DLk0ntFWPYmkMtjdOdACPR0nmzf6Dilwo+K+Q1c8rX3sfsf7mX0YAdWXscyLbS4s2m7ubn2LwgB9RfNo95hSLR0g11/+wvizX2YqTx6JgeG5XN74MyXVYgPsCRmTkOaKqXTa4r6UzqjjnBNKbmemH1PZ3cWiqBqSRPrv/o+uh7fy8EvPYyRykNR/0Thd/deAZVwRQlz7riYmpXjycqm3bCSk3dvJtXS7woWpERikR1M4PF1+Nv0w+2fKLh6EJbPlTWmf/5+2pcWQ9hjrV7axMVfed+4/lp5m2XWdZNI0yfXMZYUI5HBSGRpu28bVUtnULtmNrnBuO3yyeToeeYAueEEyeY+2702To6FPiElZt4N7HXmVbjfw8JYFVUw7YaVLPvk68b1fRKnx2s9pfT3rlRM4g8PDVctpeGqpfRtPsyBLz6MNpwsmHtdiMJL0SHNsuw6H469PVJbRs3SaUSn1RAsL8GIpymdVUe6Y9h5sFJkq62YN5VLvv5+dn/2l6Tbhyif+/sNEKteMZPZt6/n+LefwtLN4jg20yJ1so/Wnz/Poj+9HoC5d11K38YDaKksZiZvp+zF0nb1Sz/GWGv8b4/xDmFmNQ782wOUz2tg6SdfR7Tx1MrF2n+60/t/5293c+JHz2JmNfR0Hqnp9h4jJX2bDzG8swU1FKBm9WyW/MXruPCL7wRg9EAHh7/6OKmOIdRQAFM3UAMqpmbYJE6WUdS/QCTE7LdcXNSP2jWzqVoynf7emK+gl21dqVgwFYDpN61maFcLQ9tO2vVZ8gZ6NmfrVc4FgfIIQhGUzahjycdupGb17FNPlnc8L3BxCEuix1L4zA02JlrLovC2CATseB6/3MbMzTj4lAFbH5Ykjvey5V1fY/rr1zLnrQXrWuOG5bT+8kVG45mCjcDX/3H9kxItkWb0YAe1TjyFo3NjJLIMvHgcqRWsUcX9EwTKIgQiQWbeegF1F8ylb9Mhe136b+HKQAITxAVN4uwgOcX6OMc2Xq2YVComcUo0XLWU0f0ddD+2B1PTsdL5gnLhHoZc86nPFyuFfcqXpok2mKT36QOs/OxbqJxbz+jeDJXzGzBGU+Q12xztT8tzsfaf7/odj/bUmHPHejrue5HcQGKcq8LSDYZ3NgPXe58XQhIqCbP6n++ietkMtn38+ySO93iFn/xPjFO5F4pedYNs9yjacJIT33+alX9/dta9GW9Yy4w3rAVg7+fvpf/pQzbhkyXRhpLoQ0kQgkznIKP7W5GmRAQEiqoy5y3rabppTVF7qY4hDvzrr0l3DCN1Az2bRwnYcQKhqtJx96+cO5XhLUcwHYrsQDRExYJGFrz3Gu8zq//uzd7/ux/fy5GvPIoey6CWRQlEQ8x9x+XMvmviCrhjUTatlmz7EJZmTaAA+C0OE18vkBBQCVWWUDqjljX/+la2f+rHpE72FeIMgnZ6tJnXbTr5U7ZlBzwayQzJeJq2e7ZQtWQa1b5YkLLZdSSOdGHpfvfDBNYsVUEJBylprKZ0WsEipLhpspZEmoZNcjbGRRUoi6KGA8y6Yz36SIrkoQ4Gtx7n5A+eQabzXkJWkYEkqBKpqaBizisruDeJ1yYmlYpJnBaLP34ji/70Oo5/5ym6frsbKSRmIudkEjjmeyTC9pGgBlUsw0RRwbIk0tDJjyQ5/vXHMTQdYZmkjveAZaG4xz8hiE4phzG0zMO7mmm5ezNmOo9QFBquW8GsO89ugzmfEEJQNqMWM2XHKtjw+/0LWkL/poPInGanyAKB0jDTb1rN0bZ+ZK5w4sXNePCdrN1y1eN+lzahk5XXGHj2EFvbB1FCAWbddRlTr1x6VmNY+IFrSR3vJdXaDwLUaMjmbggG7DiRwYSdeWDa1WOPf/0J2u97CSEUpLQQioJ0aoiUNFaijaaR0qJm3RzWfeGdCHV8xOLcd17O6O5mEq39WBmN6pUzuOCL757wswDTblrN6J4Whne1MOPN65l9x/qzYtR0UTa9mhHVySDBkaOQHsW2dIJCcajevbkIKijBAIGSENGmGtZ84R2Eq0oRqkLZ9Boyrf1YpoVQIdJUSag0QuJED14xMYq9N847+OdRT2QY3Hq8SKmY966rGNxyFG0kVUjdFYX+oQhbmZhew7x3X83Uq5d51WxtncF2KU60VnDGGiwJ0nj9KqKNVbT99Dmb7O1oN0YyZ9eEUX3rT9hZICUzaljzL2+jfO7Us5b9JAqQvHL3x2T2xyT+aCGEQAQDLPrIjcx/zzWYhsG+v/058eO9WJk83lNUSpSgSrSxmkz3MFIz7EBPISCvkzjSjQwpICX5oSSBsjCGaqetqpEg025e41Fkj+xqofVnW0i3D5Ltj+Gag9MdQww8e5gp1yxj1h2nr456XmWgKqz7r3fTcvdmWn+6BTOvFwXsaYMJ4oe7EIqg89db7c1Xqgw+f5S6i+Y7/uqCeRkoxFdI/wboc4fbH/JtNrYSYmY04oc6EaodHHm2SkXJtFpm3HYRJ3/wNGY6T+OG5Sz+s9fZ6Q6WxNQN9n3mHlIdg1h5A8uySLcNIg23AJxiZ08oOKHpws5mmFV/SiVBDQW54EvvxdB0jvzHg0Qaq075WRfL/vo2jJxGoCTMqYrUnQrD2096xeo8+XkxK+7v/uwG+zpFUYhOrWTOO6+i8boVqOEChfb8919LunWQdFs/QlWIVJaRau5zKuj6TvfuPCmuslKwSglh80hEp1YV9dcj5PJ5ZjwrAyACCiUNVcx951U0Xrey6FpbiVEKFr4xawWkbZEaTtD1m20oJSHMdB4EaEN2sKunjOAPwxCESiPj+jqJs4eFm9b7ytp4tWJSqZjE2UEI2n/xPKP72hBAsDRM3iFbEopAiQQpnVHrpKDKwmbpONSltCBnk/xIwyA6ZQqWZaH1JwhXlRKuKQdAi6c5/vXHSJzotd0FVsEcbCQzjO5vJd05QOWSaVQtf/nVRc8WucEEJ7/9BNpomulvvIhwbRnZvtHCbmKBHktx4PO/AKlgpHNEp1Zj5XVGdrcgLYuRXc027bIoXAO+zch9qvtLVeM7eeL7vCtPy2J0Xyu7/9+PmPGWS6i/ZNEZxzLzLesZ3dfG0EvHSTf3gQXBMrvqZBBY96X3YOZ0W+6KIL6/nZa7N5NuH0QEFaQpkZaFldXsfugGPb/dRepYt2MFENSuX8jst13h3VMJBQiFAiz72zejBNUz9lGoCsHSc6uEqadynPj6Y2QHYkXrrkhuwik57lfYwFmPJtnOIdru3kTNypmUzKjz2i6fO5WaC+aS6R4CS5I82Yv0lMoxbfnfw9moFYEaCVN74TymO/wQLgZfOGrThZ+ifxgWmY5BWn/4DNXLZxBtsl0fsYMdnPz2E5j5/HgrxZg+YNqKqJnJF3mAPCXEDUr1WTzMnE5uIEbZnElLxSTOHZNKxSROC2lZtP7wGUb3t5E40o2R0xCmRCp20SYRUBGRIHXrF9Jw7UqOfvE3KKble1jZRyC3iJdEgKajDSeYevFCBrceo+7iBUy9xs6Fb/3hM2S6hhCOGR43Yt/3RJSaQWxv6+9EqTj5zScY2HIYK6eRbh3wqm6iSJRwCKkK0Jz0PwmByiiLP/k62u/ZQq5rmOHtJ0ke60IYpsdB4fAhOwqTO0aKx+q8SiF8cSvSZ2aXaEMJRoeTBErCZ6VUCCGY9yfXENvTQn4gTvxwJ3XrC4WlAiVhAiUFLpjI1cuoWDLNs8xIIeh5eCd9G/ehJ3MoigDLInakG+nwHySPdzOy/QRCQKS+krkfuoFwbfnLKtR2tmj7ybP0P3MAK6sRKAsj8zpSt1Mri2JghERajgvEFkjBB+LEmez/u58x7wPXU++zAAXCATv2QFqg5UEKFEUipTM30temoqAEVJRoCCuvE55SQcO1q5j9jis9y0vvk3vpf2of8WPdWLm83RaMb8vpoxINMbqvjWhTDUY6z4mvPGKToxkmiuL7jikCNRIC7O+lmcmDIuwATjeD55TrTkEpCRCoLGXqlUsmFYpXACkF8pW6P87h+j+0St+TSsUkJoS0LNp+vInYwXYSh7sw0jk7kM81GSNAsesjNN60mvkfvpGOXz5vl032PxTdtFH8aWsSM5EBabLis2+hctlMhBDED3XQ//R+OyZBOKZk17/stCUCAcrnNzDzrsv+z2Vg5nViB9uQ+TxCSvSRBNIwURQFNRKhas0cwvUV9D2xFzNrm5ZVRSFQapvutVia5m8/YfuuPUZFZ2MTOEU/3Ad7IbjOf+x10wy9V/zysIWTPNJJ+882M/PthY3rVAiWRIjUlpIfTDC6u7lIqXChJzK0fPcpcoPxohN42bwG5v7JBhquW+kQZtl9av3xZmJ7mkFRwdAZ3dMCpkWgNELqZC/h+gqnzDuUL57O7HdffdZlzc+E5LFu+p7YA9KifO4U5rz3Wroe2Epsb6vHiOmtP5wN250LxaekKYBukOkYpOvBbUVKhcAO97Gkbw3717Qv0lENqVSumMXcD15vW/ACAcrmTfXGm24boPnbT9gZVb400qK2HJeUCAiiM+tZ/Kk3ULXMVqAThzvJ9Y8iDKPg73CgKIJwZZTGm9dSvXoOnb96iXTnINmuEaRhFnRVtwCMb92JoKBsdj2L/+o2yuc3npe5ea3id+n++EOs9D2pVExiHHL9MVq+/TjDW0+gZ3I2K6LibmjS871Kh6xH64vR/uNn6H1iL1ZeQ/FsuK6d1TnVOa8IsHIaqRO9DEVC1KybD0DvI7swEhncappQeIC7kWfRxmpmv+PKcwrge7lIHu7ETGacE6QEy3JiRxRC1SWoCgxvOYzMayjuzmIYJPa2Eq4rQ0iL/FACqRuFGArcglZOoKZSsMZ4Y/VyMB1S7bHyUwDT/ruQEn04Sc9D22m85UJCFSWnHVOkoYq6SxYx8PQBRnecAG4e95mW7z1F/9P7MZJZlIBib36KQupELw03rqFiYVPR55f+zZvsDAlpMfzScUa2HSPbOwqqIN3SR6qlz+a8CCjED7STOtqJEgk547R345Lp9cx67zXnNK9mVuPElx9GajpVy2cw/2Ovp3xeA6HKKEe/GCPbNeQocBJpOfIrClopnguwwJRk2/ppu3sTs955FUJRiovonWYukIBpkT7RQ/9vdzLng9cTctx6Lnof3YURT4NherwZbltKaRh0EyUSxMppRJtqabx5HdXLC8GdEnsdCj93CO79Jfpwgr6HdpDrHKJq+UymXL2MY196CNM0ir+3isSlRBfCjr9QFUEgGvaCQcdCSknfIzspW9BE+aJpZz1PrzX8Lhk1T1Xp+/epWEwqFZMowsjOk7R++wkyXYMY6VwhiIvC5ueaUqUAoRvE9reSPNKJHkshhFI4QfkcvC59t0CCohCqKqVkei3p5l4O/8u9CFUhebgTm6RIeDwFdoCj01BAQUiTwWcPkDraxcx3Xo0S+r9Zwnoyy8lvPGqzabpjFXbKnmJaaH2jjAzGfaRegAQrrzH0whEWfOpWYjtOIE2LQGkYmcsjrYJbyAvoE45jxxG0CKhgFvgwPNEr0idH31xICdLESGZo+/5GZr/v2gnTO/2Y+4HrSRxoRxtJkm4foHRWgQskcbSLoc2HsDJZu2aGBVgWUoCZydH+k2eZ88EbHLZSG6GqUmousEm0qtfMZeSi+Zh5DStv0PnTZ8kNJrDyGkgwExlGdzYjAipKQPEqdKrlEZLNPQQrSrygVDfWwIX/OSuA/GCcXN8o4aoy5n3wBsrnNXh9qFo6g/xAHJl34n6EHWQq/DU8JpgLpEQfSdH3yE6mbFhBpKGa1Mke21ohJpiLMS46IU3MRIahLQfJtPcz5yM3U7VidmEMznpx42vc0SkBhaplM2h648W2hUVVUMMhai5cUDx5Dn2+IsQYBQnbcmWBHk8x+PwhYvtaCJRFkTkNxfveyiI6bvv7IwlWllGxZDqlsyZOI9Viadp/+DQjO06ghAKUL5pWlP2FEHaAsqrQcONaqlbPOc0KnMTZYmw17rHlKs6l0vfvCpNKxSQ8aMNJTn7lYbJdw47pGNvuK60iBcGGG/0ukekclqpS9PgvUizc/xe2hUA0yNwPXM/hz/+SwecOIjUToQiEKSEgCpdZBZcLpkWuP0b+qX0Eq0tQQgFmvvPq8yqDvkd2kjrRQ7ptgFzvqE1vrYpC8CR4Vgs7JtVhnXR3CMuyo+tNi1BVGUYyQ+mcqRiZHJaRK5afIlCjYSxNRwQDICWBsihGOmsHQ3pwH9ynmAspMVN5hjbtx0xlWfz3d57WDaIEA6iRINpompNfepAV//lelHAQM6tx8qu/RU+kiyjaPfGn8wy/eAQzkWHZF941oQtDCajUrS/Ed5TOqCN1opdUay8jLxwj1zOKUhKmctUc0A3ih9qxcjpSM0gc7EBRFaRhIoIBm63TsuwqngHn/YDq1PQQtisqEiI6vZbyxdOL+hGqKfcpw4yTnxc065tXV8zSsjBSWVLHe4jtbiHbMYSiCqQIIA3DF6TrWgl8P858GOk8iaPdNH/5YVZ+6U8IVpY6H3UtcH6h2V2LTK1iylWnZo717uX22c/W5f+jZYEB+mgaPZG1WTYVUfwpASKoUr6oiYab1qGGAwTKo5z834dwY63Bcv0+pFv7SbcOosdTEFCdbBjVVpJUBWmaqIEAliWJH2ij5sIFTNmwkkqfQvVawfksKDa2aOY//uM/8rnPfe60156q0vfvCpNKxSQASBzpoPVbj5MfiNnmeu90XqgJUGR5wH2euRHr1rhgQtvl70u9c0+gQiJzeZvG+IK5ZHuHMDMaqIXbSEV4p3ghsOM5FPukJyUYsTTDWw6fV6UitqeFth9uREuk7Y3M851TGJvbn3Fjdc3RYCTTdN79DJXLZ5AfTCAUCETDaKlcQX4CAhUlNL35EvSRFNmOQaQC4fpKhl88isw58kPam7dNhVnwGIydC8vCSGaJ72mm44dPMe3OKwiURU851kB5FHSdbOcgx/7zV8z5wA2M7mkh3zdqm+aVwt5ZCCKUWOkc6ZPdDGzcx9Qb1pxRphVLZlCxZAaWYXKoL46RzBCpL2fJZ25H6gb9T+/HyusFV5DvpomDHSSPdqGNJG0+BVM4TK3SLqtuStAMct1DNP/vQ6hlEQLRMA1vuBA1EiBYGsawbNeNZdruF5nTC5ahggjHjBWsTI6OHz8NoQBKULE3R2kRP2grQa7Vqmhf938vpATDJD8wSvNXHmbR398FUpLtHHImtqCUC+e8fzZRJrZRpGD181u7hFNJTOJU73UUYumUPEGxFUqpmCjBIMGaMub96c1ULJ1B36M7aP7x0+QH40hDFsYlQSgCy3TKs0sJpmkTf0nLdv1IE0ywMGyluneUvod3EN99kvorl1N96RIqlrx2KkqfT/dHZ2cnFRUV3vtji2qeS6Xv3xUmlYpJAND+vSdJHe10TKX4TqjCe4j5fdFewBquWdWpDum+gvN74UFt/1/arutUlp5fvYAIBe2iRj7/shASEQ2gqCpGKmtfpxTKMnt9O89Uwn0Pb0Ufsa0MQkpQRCGAzt8/p7+FMVP4HQl5nUznIHNefwE9972AmdcJVUYwRuI4T2YQgkA4wNRrVnD4H3+K1h/H0g3SqoKlGyiO/AAURxZmOme/J/EUHv9cCCz0kQR9j+xEG4iz4G/uOOVYp73xIuK7m9FHk8S3H6erLIKRyGJlc05MTGEuiufVQh9N0X3PZrThBIoCoZoK6q5dddrgSyWgsuCTt3L4sz9BCQZI7G6m5vKlTH/zeL4RM5MnvreFxjdcSN8jOzBSOa8cNxKyXYMkDrWjDadQAwpWMsPQM/swMnkCZRHie05SvmwWZfMbwLBQoiFK5zZg5nSGNx9AT6TtwmmOoubJzx2rYluicl1DBGvLqb1sGTPffQ29D2wlfbIbI6/h5eS4m/zYuRB2zIKVypE63k2+P0ZifyvZtj6EbhQxWdrrWZLt6Cexv5WKladxHQi76qnirjv3eyEEqlO4zNJNSuc3ULFiNoNP7SWvx72+lc6so/bSpYCkZG4DlStmEd/XQs/9L5DrHrL742cKldjfA6uwJrw/+Fw//jFjmiAtcl3DdN37HMMvHGbGO6+h7pqVZwwknkQxKioqipSKsTiXSt+/K0wqFZMAsN0dlrRLhTs+dOFYGvyxFOC85/r1PTKkQnEk7yHrM527bgNFARG0g9+MRIZMW7+jyBQ2LgTeg1NxPbcKeA9tCUpYpXLZ+Tv9xHadJNsxiLBML1Nj3Fjd3xWch6wbUCqcQFbnBOmcUtVwCLUkRKall2BVGYoq7BO225au0frVh8n3jiJ1A0wLaSkoXuyF/dFAKEB01hSyrf0YibSXvTCufwIwLYzRJPF9LcT3tVC5auJTS3RGPYGQgiVABBSMWIqRbceQmm4HnfpSDoWzBoQ7F5ZJrnOArh8/BRZEptUSrC2nau3808o4MrWK+quWM7zpAB0/eoqSuVOJNNUWfSbXM0L7dx7DMkxiu05SMquecFUJVRcvJlRdBthZOd33Po8+krRP5gLSRzrJtPVjpfOkjnSSPNDmySk0tZLSGbV2OfsL55HrsSnPtaG4Q+A2ZqxIW+GwTBRF0PD6CwhVl9H4pvUMb9lPNpt3MqHkKedCCJABgRJQ7DlJZ+m+/3mMeAola4GsmQAAriFJREFUoCAEWJblfMdsced7Rui8+xmW/uf7Tqmg5ftGEaZZpPjZ8R2CUEWUmitXoKiCxlvXM7r1qP09ctwfQlUpn9/I7A9cX9RmtnsYYySJ4qYlKWOtN8730B3rKZ4FQoBUHQujaX8Mw44/6n94O6HqMrShBFJaVK9fQvAMQcWvVpxP98eZ8IdY6XtSqZgEADPefjVDmw4Q23MSfShhBxVatpkWGGcVKFggxpRO9n3O22SdR5OdzqYQbazB0nS04Tj6SNL2+RZ93naPWKrq+J6dBz2F2AZ0ncS+Fox0jsA5kiWNRfJIB61feZBs74itLIwLfnf6JcaM1R/sJwv9E0GFSH0llavn0vvA81h5HTUaIBAO2twBThtmIkPyUDvkNNt07Tvt+uWhCEHTmy6l8+6NmKmM159x/fPNhTGaZOCxnadUKtzPCySBkpB9Os1rhb1i7Lz6rVRIpGF68QXaUJzY7maQksq18097Gp32lsuJbz+OmdPIDyWLlApLMzj5X78iebjDjp8QIJxA3KrnD1N/01oqVswhWFnKzHddU9RurmeY7nu3YGY14nua7fTfvE0rrvXHGXhku5NVoSNCQYxkxosbGbuWvbEGVELVpZQ6nA2h6jLm/vlttH/rUTIdA1gZJ54Aab8aFiIgkIYgWBYhPK2WkllTic5toO/+F9AH44Sqy6hYPY9scw/ZrmGsvIZaXkLZwmmEasqpunDhaS0+Q0/twczkC98Lz6JgYaUyBCMBZr7/RlueeR0jk3OsIYJASZiGWy4qas/M5Oj7zUuYmZwvDGrM99b7tBzz6nze+V6ooQDBunKsVB5LWlSsmINaFrGVZaD/0R0kD7RiZjSybQPM+tD4zKM/Bvwusz/gD6/S96RSMQkAqi9aRPVFixjdeoTBp/YQ39eKPhR3/irtAIsiz7NzcpXuQ0gUTu2ueR73kkLWtRCC0kVNJPe32UyMWa2gKDhkQnZNBdsEXaA79m9qAkyTXNcwPb/Y7D1EXy567nuebPcQGHYsCU4sgxck4Y7ZHassWChEKGD7nLN5Z4ASgUrpvAaUUAChqgjTtNMbcwV6bzcuwMprBbm5ch47Vssk3z9M/XVr6P3lZox03vbLq87jPiBs2mjFPmWq0RCRxlrqNqw65ZiNVMbhSQCpGwVOB98ZdexYOcVcmJkcffc+R+ylQ9RtWEPl6rmULZ05oXKhhIPM/YvbOPlvv6T3l88SKL2B0nl2imrH9x4n3dyLzNoBrVJi070Do7uOE9t9kuqLFtJw63pKFzQRKC+cdCNNtcz75G0AjLxwmI7vPU62ewglHKRy9Tw7wFNKFASJo50wahbGCNhJS66JzA7oFKaJmcww8PgOwlOrveXQdMfltH/nMYiGKV8xCy8LRwiEBEtAqLKU6e++llBNOSPPH2Lw4a0IKZn+9qtpuHU9ub5Run/6DEYqR7ihmhnvu76IHnwimDkNbTBu923sWpESSzMwEnZtGiORIdc7bAe+2mY/1GiI0gWFdGApJe3ffIRc56Azz47JxHLneAxbwqm+FygIRaKEAtRvWI2lG6iREE13Xkn6WCcDT+0htvME+mgKqeuIQMBTrifxx4dJpWISRahev4TozHqOff7nGMMxX8lnx5rgpqThey0ylzr571AcREbhVYDtd83lvYeZd61zYPfaxvfMRha9ounkOweRUpLvGSbcVHtOPlsjmSHbM0yuawhhGoV+ulwcbn8EY8Zc+F0NqSAEVrbYkuGi/vq1JPc2Y6ZzTpyG4iQgnGqsxWMUQmJlcnT/aCPRmfXUXLoELZ4pRP77dBHhCDxYUcL0915PpKEaPZ4m3zuCE81CoDRKdEY9Pb98DiuVRQgLM5Yic7LHO/3aOuE5zIVpIg2TXFs/3Xc/xcimOhpuv4IpN184odxLZk8FJIk9J2n+wihN79yAEILY1iNYiVSx6V1IezPLaUgpiW0/SnzHMaouWkTjW68iOr1+nKWq5rKlpA610/vACyiWRdmCJqa/2/YzSyk58pffQ+8bAd8JO9RQRbCyFLU0jBAKeipDrqUfrX+Ezm8/Ck7KJGCzdSoKakUJjXdeYRf+ciXkUmJKSX5glPxAjJ57NqENJyiZ3cDU19kyiTRUM+8vbz/rtaqPJOm6eyNmMm3H2zjuQH+dEUURdlaMZdHyP78mdaidcF054eUzybYN2MG5DizNYPDJXST2tSA1jVBNOaULpyGlIHO8E3006SUaefM+7nthv6qRAOGGWsoWTWPq6y8kWFNOtrWPzu8+yvCWgxjJDFbOsGWjCIJlUabcfMEEo/zjwO/aUvGHhkmlYhIepGWR2NdCxzd/S659oMgz6KXgOQ+TQvS7dDgFpBcP4QU14nt1LxeWZ3K2OSmcNhV3U5Zem/7AsELWZuF3IU3SzT20/Pf9CARli6dTd+MFZ02g1PrlB4jvOIaZNzyCI9e/7bkginL73aBFt3+OC0EIX3Cr9K4BqL1yOcNP7SK28ziKqqKWRdAG47aFQEww1rHyAzBtS4I+GKf2PddTecFCtKE4oSlVpx2rNC2a/+0eUkc7bRO0hMj0WpresYF896Dd13AQ8jp6LOEoPS9vLux+2spFtn2Avl8/T/mK2USnT8x7UH3RIvq6B8m29tH2pV85NUV0BE7K59i5cGueZO0YiNi2IyR2Hqfq4sXM/NgthKqLSabqb1jL0NO7MUZTaD3D3vv9D7xAtmPAuY8dqyMUCfk8ZkpQdcECajeswsxpDDy4lXzfiKcZa/0j5Prs+BehCMwRnROfvRsrp3mEVUokhJXTUCMhrJyOEg6ipzL2od/QSR7t9NJL3VO/Gg4Sqq+aUE5GIoMeS9HyxfvQRpJEGmsI1ZSTOtaJmcx6LKwiYgejVq6eS/dPnyZ1qA0zqzH9gzdTvmQGyUPtaD3DaAMxpBAMPvQSg0/uxtJ0Ig3VTH/PDdTfsBZpWXR+/3H6fv0CVs511Y39Xvh4NhRBsKqE+Z+5g7KFdlpv53cfY/DJnZjpPGYuX7DwKbYLpv7GNZQtmj7heP8Y8LuMqfhDxKRSMQnA9r/23fssA49uRxuI26XJoRAFDkUPdy8o01n8hTQ392TjO8lSsFgoAE4ApvA362+LwoZdsH4UWzvc9/XeIUYHRpFIYs/tQ+sfZfr7z85Xq/WOYKUyOM87z2sj3U65J0Ak1tj+OR9RAgqhukqsTM4jrXJZkG25CCpXzyW59ySBsggzP/5GWv79l8hMzqtw7bZZNDZPfs7viiBYU0a4qZaOr/+G+NZjVF21nMa3bkBRFQJVZePG1/vzZ0gdasPK5Dxq8FxLL+3/8UtMy0IRkpJ5DWRb+wqxHlIU5sKvOBT1T46fC1HwtAvTJN/aR/Pnf0LjW6+h9to14/rW+Larie8+TuZEN1LT7XgE0/Q2r3Fz4dzIXoIWZDUsIP7iIU50DTD7r++kZE6jZ6mKzp5K0x1X0v3jJ0kdaSex9yQl85oYemw7xkjMmV5nbLqOPhhDCIX+e55h4FfPgYSKdfOZ9zd32msgFEQbStDxnUfJHOuEUMCJB7ELgVngKRtYThpwQEEgiDjyDNWU0/XNh8l3DTpWKIFlmERm1NP0nuupungxQlEw4ikswwLTovmff0q2axAjmUMJqtS96TKm3nEF3T99huFHd2Bm8whFRQ0o6F2DtP/P/Vh5Hcvhfen65sM242skhJXVGHjoJZtKX1UwkznbPRJPEd96iMp18xh8ZDsjT+9BaLarTijOenDnwhfuYX/lJTKRpv1Lv2LuZ96G1jvM6PP70YcTToy3jyhPVSiZWc+0d1w7bj1M4o8Hk0rFJABo+497iO84juEUzJLuxu7uHBS/uqZp7/SOb7MR9kPUS0WUvlckCvZG7afzFt5mMkFbTqpmgR/CpVXG3shNEwDLMMn3DJ1xrNIwsTQdpJPa5z74ZGFsY8eqjB2rE+2uKoKyBU3kO/qd3H2KFCbADahHSIvSVXMIloXQczkCwRCB8hK04ZjjbvDLjwKLp5QoWBgDwxz7+FcwpYSczvCj2xl5dDuhxhoa334tNRsKm3f6WCcjT+9GZnJeeqoQAmkYDueA/bs5mkB1gg3HzYUc2x9ZmKOxc+FfK1KCaZFv66P/vmepunQJarTYRREojVCxdCb5lh7UaAgjnQOForUy0VyM7Z/M5cmd7KblH35Mw1uupP62Qk2YKbesJ/bCQTLHu+i9+0lm/dVdGCMJJ7vGN78O/boQEitnIPIaIElsPczhXccBQXh6HTM+cRsLPv8uWv/l51i6RuNbN1C+ymYS7frWwww/scMOc8gbBKdWMfUtV1J99Wo7YSgSwsprdH7jYbv8uwRTN9Da+8g1d9HxX/eSv+NKwg219Px8I1rPMDKoYiVztpLi9G/owRcYeXy7XeLdsDN1FGGBpkEkTHhavR1vo9j3cJUcS0ryrX3ITI5gXQWB6goiAoyhOPpgnMRLhzi885jNd5K1A3bVcNBWnIIB9L5hCASQmRxmTitSumU2T+5kF8c++TUszVZoFGkVfW9FKETpwulMe//NRW6YP0bI8+D+kK/w+t8nJpWKSQCQ6x7CyuS8tDJ/XIC3Y/jf8twFsuDm8DYX3+8Un3aFsAMK7Zi4MW2Ou9bHE+H4qoX0ZYq4x2S3f0JiWRaWU2xJUSeuYdD67/eQ3H0CI5N3DsEFy8N4e8hpxqqodpzDhjUkdhzFGE0hpK8ugzssJ8fOjKcYuG+zY+FQKV81hym3XUbrv/28EHPhyXHMWKVEpnL2mdeRm8zkkECuvZ++Xz5L+YULCZbbpvWeHz9BvnfYnk+nfsXYuQCJHkuhKApKKECgosSuS6Eb4+di3OuY/k20VkyTXGsf3T/dyIz3/3/2/jvOjqu+/8ef58zcsr1qtSqraslyt+Xem9wLNrYxhF5CSEhIQvKB+JdPPmnfTwik55MQICEQIASDMGBsA5ZscO/GtqwurepK2l7v3jYz5/fHmXLm7t3VSlrJEr4vPa7u3rkzZ97nfc6d8z7vevOEqAbtFKtwM1mE406kz5T0YveIzxVcl8KBAboffJa6C1dop0opkakE9WcvJbNpF5k3d7LxN/8JL5M9+LwTeiFWBUcvoFIyvm0vnX/6X7TdexXVy+bS88BT7P+vR6n9u08w/Ox6+n/xGs5QJqSzsLePPf/6I/b9x09QStF42Rks+N07WfD770QIoRNy5Qts/aP/YGz9TlTRoWrJXJJtjbjjeR3qGsw7Gcw3gd1QQ6KpNhS+cr5pJz1/Fo2Xn0G+q4+Rl7fQ+o5LaL/7ipDnSik6/+KbDL+0CXdwFCudYO77r8OqrWbf137CeOd+3EKRqvmzSPsmNWd0HGdgGCUEKptHJV1wHGTSItnWhFVbRW5Xt06F7nq6SKCfbCz+TJDY6QTzP3ErtacuLPub/FXCsSwodjxiZkoFVvArhmDXKiLVs/9xgtZiAvwvAlE7vEaFXwlFpGko11bpPWKZeMrRFy3+Y69sYd1df8bmT/4zw89tKEthbnePXjzzBcCb2FezzSnoE5ag7swlNJx/MsnWhvBrVbrN8Hf3ynEp7O2j6fIzqT93GfM/fgsNF52K3VhThp8B/6YYiwCeR27HPrZ9+ksMPb0OgJqTF5BoqtURIpOOhYBCES9bQCiFlUpCwgp5WbbvqvSPqehTqKLD4I+fZ+sffklXcp3ASA+cIBFVKX1MeyxQisLeXjZ/8p/Z8vtfJL9fL7b15y3HbqhGuS7eyJjOExLjxRR9NTtddHEGhun+xhrGfrkNuyaNMzKGm82z/7/X4vQNxehWnocaz+OMZHCHxxh6/FXevOcvePOev9D07etHppLM//VbSLbUAYrsjn3s+ecHcIbHJvQNtOBj11Vx0l99jFO++Hus+NffJTWnGSEFrTddQLKlnsGn11E4MEDPtx+j80++Fs5FIQTzPnoTidYGvHyBwoEBCt2D1J+3nHmfuA2ZSiA8j2L/CIXuQdyRDADu6Dje8Jiucuqb+ISCZFMdy//+EyQajFwT5eaKAKsmRd15yyfkJPlVRVD6/EhfJyoqmooKAGi6/Azc4TGKfSNaferbSzVMrQCxB36kpg+UBir+wCb+wJYJi8z6ToSr6zjg71DNxSRoM7xv6aIS0lJyXCnUWBYXyOcKdH/rUWrPXopVFU9tW3fOUgp7uvHypnu7ito0lRVG+0KASiVI1FVRHBoj0VBD3Upd8Kn+nGXkdx3AK3hYtWnqz9f1L9xsnrGXN5NqbcQdGkVKQccn3xGjJ4hkVEFfywpuZcbCXHQcl/yuA+z52/sZ37iLub9+K97YOD0/egY/33cJr/y23GDBAqd3EKsqgSejwQ7s4RHvJwpMU84VFF4my/iGnXR/+zHmfvRmAHJ7ehh7ZTMyYWPXJykOZSI6Jxvf2N9l5orj4A6PkVcebkanRK89bRFV81oZ6xue2GbYJ+O2pYKl2XelcMcyZDfsRCUsRJ/Lxg/9Nc5Qxk+GFp0b/i78O3q5gg47FgKUh5vRoZ81py5k1u2X0v3ttXR/ey1etqjTpJejT3nkdx3gwLceZf4n7wSg7swl9D/8PPu+9CNA4I1rjZc3Os7Ya1vp/eHTtN15OaC1GbUnz2dwbw+i6ND932vo/f6TJNubSM1qILtjXAsTSuGNSL/mjTGuAUmuQ3bzLjZ+0O97MBbCGAsJsjZNsq2RpivPYs77dMItZyTDvi89iDM8TqKljvm/f88hRWxVcPyjIlRUAEDrDecz8uTruMGOC+KL1yRaaAiqdEYRD7EFxrxICKyUhTs0hlWdItnWgHOgH18THyEwM4QZ/Ih2sqUaDnNxjd8KkU4iDBNIfl8fe//+uzpVsvK0T0dpf8oIFLK+Bi9XAMclUZtizodvpP+RF2i49HTqztZZJJtvOJeBnz4PxSLJ5loaLzlNc6DoUugeoO6UBeC4OIMjjK3rpPaMKCmV9sFQ8Qf4VH2dbCw8F3c0Q/9DzzD46Isox0O6TsnJU/DPdUi3zyZf7EH5dnOrtgqvUND5IkrHolTYm2QssC3sxloSLVGExoGv/5TCvl7sqhQNF53CwJqXwZlEYAmFpzL9DucKIX0ql6PvB0+y4H+9x+cvfmZWFRvXqebyRCHJONkSJJpqcXqGcPuGQx+PeHtBjpUS+vDpe+BJFnz21wBou/MyRl/YQGb9DoTnlWnLINhxyHXuC4+0v/saxl/fzvi2PbqCacgjncxs4EdPU3vaIqqX6+yzdSuXM/LMOlS+gDfm4GXzuKNjpDtmIy38MVBawBMWdkM17mhWJ8Izx6Lo4PYPRwVaffqEUMi6KhJN9TRdcw4tN13I7s9/m/UPPROm/3ZHsv65gtFXNlO9bD4L/+SD2tfkVwAV80cFb3sMP/EanZ/9N/K7D/g+AYR+AUJGIZLaHyL+Lv1zZeAvEVwriZ/vH1fZHNKCmhUdVJ80T9uXg7aDhxLxzxE9pZ+ZcG1IV0LSdMWZsdLoztAo2c4u3MERrcYtbUtOvJdMJ2l//3Ukm2qRtiQ9r5Wma1ay/F9+l9nvibzYB370NOTyCBRu9wA7Pvtv5Pf20v/g0zh9wwgJdectJ9/VS8/XH8ErOtEAyMgRdMq+ltJXbixQWu0+MII7Nq75IqfPP8azVC+Zo1OpS0HNyfNItjUcAn3GWCQlieZaak9fxOL//X5m3XE5+T097PjsvzHy/Js62iOfx+kfxqpL+742k/QVFZ+LE+ZKMN8Edm0VdkMUDaPPLTdXSsY6OAdvYt+EQlgCu7mOlhvO4+R/+h3sutTE30bp70KU0ucLvKloXsp0ksZLTkUmZbyvJb89iUImLWpOjwRSu7GWunOXIfzU3zH+oXAGRygciEJqW64/j/pzliFtK2yTokNhb48WaIzfrSWU/zzwJvJPRjyUtVXItO2PhU4rP+83bqVqQRudn/k3Mm9ux+kd0nOybxiKRSgWUYUCzoCueTO56enEQ5Cn4khfJyoqmoq3OYq9Q/T8z1oKe3ujXUfpbjPYOkWZj/SX/gVhzLqpOqbkPdjtuYrUrEbaP3QzB775M0JNuyDWvhCAJZC1Vai8gyp4xj1L2y/ZvgvAcRl+8jWab7oQmdSZCgceeg6CgmkmXbG++p+lRNZVU3vWSbTeegm5jbso9g0x+wM3ItPJiH99w3T94/cYfX0bOLomg8oXGHtjO51/+C84+SKM58lt3k1yTgsqmyff1adt1L5DXPXiOYx2D4bJlUhamhDzYTtBE3AYYyEM/pSOj22F88Edzfq7DUVuyx7cILww5I3Q0QxCQL6IqE2jxvM+vQJsC6u2ivTC2bR/7FaqT1kEwNBjr3Dgv36K0zeEKBR1hELRIbd1L4maKooj48ZcKTOPMD6XzhUBJG1S89uY/YEbaLj8LABGX95Ebm9vFGk05VwO2hKRFkb4/a2vJdFUR9uvXUfjNSvp/tbPdGSNSQtmW5OPhVWVpOWWS8LueNk8I8++iXBchKmmMOe1UGBLqpbOo+2eq+LsEIR5UkrniioUOfDlB/HGcjTffBFCCOZ8+CaK+3p1xJLAr1XjIAMnVUMboRw3Oh6jKRqH6jMXU9zZTbFnEOF6uCMZ9v7td0AI3OGxKZ4rkuScFuZ86KYpU5NXcGKhIlS8zVHoG6LYO6jVm0GyhvK61/jxsqYO4930UTAhBTWnL6Zq6VyddAiih0xgm03aqGIRu76GljuvoO97P8ctFCdv06Qp+Mp1yG7cxc77vsTsD9+COzTKyHNv6noVU9GHQNZXY1WlaL3nalrv0PboBX/8gbK3dAaGGd+4A7I5Y9XVuz+nf4QgrWhhfx+DDz2DSFiIRDwqZfaHbia/u4f87gMgBam5s7Dqqsjv78MbyepiYxOgIr5JwLKxm+r1LjBh4wyNwYS+etG1pb1OJUg011PY14c3mgnbdsey0dwI2gKSHW3UnLGEsVe30HLbpYw88ya5Pd2ookNqfhtzPvEOqk9eELaf39tDz3ceo3jADPlV2n4/lsHN5srSNZFQSsZN80FWJak6eSEdf/Q+Es3azOKOZen5xk/xhkbK8y9sU5WYvIw5bNsk25uZ/f4baLzm3PCSzJudYQrxsm2V+10kbOz6GlILZmOHCbCg74EnyG7d4xebC/hMJKjYEplOkZzbStv7rscySto7w2OM/XKL74Bahn9Fh2LvIN1ff5jxDZ3M+/17SS+ZS83pi8nv7TGEoYP8bsvyTSBsi+rlHQzv6o711c1kwxLpE58rwW8sTeudV1C17FcrEZZvQDriNk5UVISKtzn0Bs1XfYvggLGjFSU/kZLdhpBRdklEuXdzd6wAj+ymHRT291G1ZB6ZFzegHA+Ero4qbJvq0xdR7B6k7sLTqD3nJPpXP37o9KGgWCC3dQ/ZDTsp9Aygcjm/nUnasiV2Qy2z3nMdLe+4fFr8Uyb/goqt5egrerhDoyQXzkYKwcgTr9J0oy77nV4wm9a7rqDnWz/DG81g1yZZ+Je/jld02HXfl8jt3KdvZMmA6ch0CpFOQqGISCVJdbSx8M8+iqxKMfrcOvb87bdRY8Uwy2m8r6X06aZrz1rCcGYclSugCkVdAr7c+CqF2zdI/fkrmPubdwLQcvtlU/Ipv+sAbv+gDkOVIj4GykMU3EhDEMwVg74YfO2BTjIldBkUW5Jsqkb6ZoXMa1vo/trD5Dq7EJ7R9mRzGQjykOj2FSJhYzfUsPBPP0x60ZzwsvENOyjs7Y7mUiltRL8LIdBp7KuSVJ00n477PkDCiBQCcEYzPl/K0yelwqpJkGxIY5dU9nT6hike6Iv6WO53oRTu0AgjT7yKOzDM7I/eTnrpPBKNtbijGS20Hux3W3YsFNKGZGMNVUvmguOg8kXs5jpkVZLctq5425ZEVlVh1aSY9e5VNN96Kb+K0OaLUvXaobdxoqIiVLzNYdVVkV7QpnctjouXzfm7F1MQIHoAR5sN/z0QSEoWiuBdanU4Rdd/KLkU9/fR841HaP/UvQw/8gxOJou0LVSuQGpROwv+5MNYNVWMvbKJA19cDUVdGj24X+xBN5VML0B4DoMPPaHzASm/7HgpncFutzrFvD94N3Xnnzpt/o088eoh0OeBU0S5Hr3feJjc1j20/+ZdCNui+aaLSS9sZ8//+Qr5zi52/uE/IpJJ7IYqZNKCggNViVDdPud330XDFedMoKfn6w8xtPYlyIyHdvByfcXW9Sn000vnPyjs2o+lXOyOWeT39UImV358lcLLjDP26mZqzztlmpwKfA2mmCtlF7CpxlePpcDDy2QYfe4Nkh1ttNx5FT3/9Qi5rbsQriEwB9oW14j6Cdsi3lcUwtLRSqaTppcv0PP1h/AGhnXSqQk0xfuLb02wa1O0f+SWCQIFwKx7rmH05y/jDo2W76fj4PYOMj48yr7Pf4OWd11L082X+ndRfuTQJPMupEeA6/oRXkO03H4Z1acu5MC/fp/crgM610SpcFEqVJQbi3yBgQd+QceffIT0knnh4fFNO9nzJ1/GHS76t9djlZ7XxIK/+A3s5vryfa3ghEfFkPU2R6pjNov+9lMs//Zf0PbR27DqqxFJC9FQpctxBwJG8E78c8zDvfTdFtgtddjN9QiJn7YYKBQYf3E9mRff1M5eroOQkFw4m5Z7rsaqqcIZHqPv6w+R37ZHZwsscw/w4nSJMn+7Lk73IF7/EHjupHTKmhSpjlmxypcHw/gbWxle+yIUp0mf8vAGhvHGxvGGxhhZ+yJdf/Ef5Dq7GH9tC73//kOtISgUKOw+QH7rbvKbdoLrAB6iWNC8KBbJPL9uYj4MYOTJX+INDBkVXsuPjUjbJOfPQlSnEGmb2ivPwekdxBvNUNy1H+E4U4+v8shv6MQdHZ82v4S/ME05Z4J3VYZ/xkuI0muAQpHhB59k9x/+E/nOvX5oZjQWIpXAqkoyYT5PaMv/vljEGxym54urGV/fCcDgQ8+Q27Jbm5bEFL+LoE2BHvfhMXq/9uOomq2BsWdeR/nF9cr21S8ehutSPNBP3389woF/+o6ucAsTeBHyzaRPKOzGGjq+8NvUXagjk6pO6mDR336KRZ//LaqWzde/+3K8KDeXzTk9NELmtS0lvYoEkbAtz6O4+wB7/+zfybyyadrz5kRD+VE89NeJioqmogJyW3bT/52f4Y7lEEJgVaWw25op7jmgHQrLIdjpBVn/gge78j3ckwmSi+bQdNvl9H79YYQQus6A6+nQsvEcPV/5oc5w6HpYiQQdf/kJki16J5ffuZ/CgT6Eo9XlodObMt7N7eZk2kblP1iVlqB1ymtCZ0NhWSTmtdL2sTtIL1+AlU5N0lAc7ug4Pf/xIGosE3NEOxh9wvUQloVCQcEh++Z2uv7yqwhPad8W1zUsRfocnVZaIBwnrBkx9tw6dv/BPyGTNo3vuJK6i8/Q7fvaBxmMRajaj9OXaGqk/Xfexdjzb+L0DlG1qJ2RTA7hKUSxGO6wJ4xv0Jbnkd+5n/7vPUbbR247KL/07VXoACqCsShHH2WG0zxgzjuDPjydn6HgJ26SxMdCSBFTWIRP7knmsvI8KBTJbtzBgb/9Fk3vvJqx59ch8gWMVB4l9Ilwzpn0Cdcht20PXX/+H8z6yG2kl0f+JqPPrUMUCtEOr5Q+47eFp31Qspt24Q5nkOkkicY6PL/PsXln0qcUKpOn5x/+h1kfvZ3knFZ9viWpWraABX/9Sfb91dcYf3UzynOmNxZB+47LyE+fI9HSQP2VKwGw0mnSc1vJuTpyROWL2hSSL5DfvpfRp1+n5twVpS3/SqBSpbSCtzW8bJ7erzxAdssePxZd+zcURzN6s1Fid46vLGriE8cP2k90tNF43YUMfHcNXiYb7iRFkBHI87T2wL9GKcXIj5+k4caLSbS3knlpvS7QZKpdzVwVgjJPO3ynMDWRvnDxEjqqpLmBxhsuouGmS5DJBHZ9TZnGJkeucy/F7j5EoEo36Stz3xB+RkdZlQIkVkM1xf19+kRP10sIBSF/lxt6zofNK11vYWMnCEGhq4f81l20vP+WMGQxHItwd+nTl7AQddXUX3k2NWcuo/rUJRS6etj7l1+FfB6RtMFxEOaqEiC2sOsol9E1z1N3yRlUrVg0NcPMITPHIuhrWf6Vo8FgROmD1+eXeXnUJtrmb3YjmCsx5pahz3EpdvfT/81HdMRLeMoUPCoddwXk8mTXb6P3Kw8w7//7rTCKSCkd2SRK2yqlz++/qK2m/trzSLQ1AVB19nIK+3oN84VBjNlmPk/m5Q2gPOb+749iJp2y0ila338z+/f3U9xzYHpj4bv44LgU9hyg/xsPkT5pPsl5baQWzWHeX3xC19gBuv7i3yls2WMw40TOxFDBVKgIFW9zDH7/MfK794NbjB7Yge9B8CBRwTvRg850SpSKcOvmP4jUwBAD3/4J7siYzpxpgyoYDyplnC9AOEUK+3vZ/3+/itVYR3bLbq3qN23wlHvIltAXtFlKn0Fncv4sZn38ndSsXHHYoWwylcRurKUw4qdUDiUwg57geOyzh7RA1tVCwaF65QpGH3sBL+9HtwijLWWOAREPMD574A2OMPTgE+Q37cAdHvP7X9KW/56Y28qsD94KUrDvz7+MclycvmHcvn7Aw2ptwhsYQRWL+ppgXH3HSD1ewVi4eGMZ+r78feb9308iq+NFw0xkX9+kzTjmWJT21eQfZfhnCpiTzLuyc8XnnygW/UPmFtyfy5h0ldKHFoLHMtrkFLQRvvvnB21O9rtQClyX/M4uhh78Bc3vut6/RIDw4nPZpC8YT/+3Z6dsai8+PeRtcnYzsjqFN+rE50YpfUqBUyT3xhbGnnmNusvOiY1R1bIF1F1+NkM/fgpvLDONsQigTSNu/xC9X1rN3D/7BMKSMUE9NaeVQmeXH5GkyL6+ma7/80UCKU8oSJ+xjKZ7VnGiZ9h8uye/qggVb2Pkd3Qx/LNnIJ9Dhg/F6GGkgHgJc72biqpUBs5oKnooBkLFaAblefqQ4/mlt402/YCPYC2RaRurtorsvh4Ku/ahHAdZGg1QSp8y6BMYbfpq/5A2g76kRfXpS6k9b/rOmOXgdHVDoYC0he/4Zzx4mYI+oZApm5ozl1LYuZ+aM5eSfXUDTnd/1FcxjbEQhGOAcmDcIfumnyuj1BESQIKoSlN3wamkl3XQ9cf/D6d7QGscvCBhkqRqyVzyThF3sOgvjuXHN6BPuC7Frm4Gv/coLR+8vSyvlOdR2NuDtKW/WHtT9jXg48S5ojArX+oF13+FQuQkc8VvC0RsLMK2ys2VCfR5YRuUG4sg2kOYvwtFnG8eFIvkt+4O+ZOY1UjeEoAX9dUzfmNh3zQNamyMnv/7VZo/cAs1F51F0x1XMv76ZrK/1ILbxN9tNFeCrK25N7dPECoAWt97I+MvvEEhMxbxcbpj4TjkN+9g9OcvUr/qoli7TXddQ/b1TXgjRVAubk8/2e7+SFi1JLktO8lt2EbVaUtpvPu6E1a4MJVvR9LGiYqKo+bbGKNrnkONZhAqyBrov/xshjoboJ9G2hJhdkDpnxe8C4LriNTvQbVOP0wuzL4nyrQtFFJKmt99I7KuSl+LitoMaVOT0xd+ViV0GX2T+lznQG9YLv1wUNi1n/5v/FiHSHru1PTZFjJhxflnSZrfexN4DgPfeggvMx7j3bTGgnhfQWnziYp4HWvPtkgvnkvz+2+h94v34w7orKIo/xpA4OF292I31SETUjvuWWaWy4ljgfBQuRzjL6+flF9CSto+9R6qTluiK1hOaCve19hckcLouz5nwvjKGZwrZecd2h/DzzIqDjIWUpTQUTIWsjpF/Q3Rott81zUk57TG++pfG2/LF4yKRQp799P75dUM/Pcjuo17r8eqTR/8d5u0SC2Zq+dfubGyLETankD/xN9tyVgEm4lcjrEnX5nQrlVThbSEz2stHIXmVs/TwtDYOLnXNjHy02dwRzOH9ds8HqAQeEf4ijyYTjxUhIq3MWQ6BdUpvXBA/BU8UDDegwcuxvHgoZJMIBJ26AwXHi/9G73DCVMlG23JqhQyYRvnEhd4KKFTlNBRlj4RHffVz8WdXYyuff6weJZ55lV6/u7ruEMjOq1xrH+lfFRY1SnSZ56E1dxo0AmyKo2XzeH2DEAg2CkV59m0x8JYDIM+h4KCvt6qTtP4zqtxh0Yp7OmGQr5kLEB4Cm84gz27iUR7q37Na0NYMj4WxPuKUpM79PpIzmnVUUAiGouy88NcQJlk3pX2dcK8LT8WUUr4KeZKQEc47wQiYSGr01hNdcj6mhIhxGhLlYwFJWMRCBWWxGqI6qCkFs2l6uzliHRqcvqI+KXNKB5e/zCjjz9PYed+7PqaeKru8PdV0pbjUNy7n8H/eQQ3NN3FkWhq0FFBVUnj2VDmd6tK2haAp3C6+3AGhmNtCgFWQ20klJXhH8rTjtxhZtEKTkRUhIq3MWqvWEly7izfYUwZ9Qb8HRHoh4rUuxICLUTwffAudb6LqpUroraE+SD1tRXGbg3Lf/d3capQZPzVDaic79QpSu4V7sCNnaRJn5iCPozPKFQmS6bMbmo6GPzuzyjuPaCdGfUTfgJ9CKOvtkXDDReTWtTuh+xp+or7+1DjudB/JaI3anNaY0FJn82+hm2B3VCD3dpEoXMPKjsejoMQIKzgGgWFAmosg8pkEMql6Z2rSC5oR1YljXuUoW98nGJ3P5NBFYu4+7qj80v7asyVSGjQ44xVck3Z8Z3GWIQagynmSil9AhJtzbR86A7a//fHSbTo8GgR7LolJW2VmbslfaVYZPSRJ/1y6RqJ5ga9k58ufb4pRSZs/5iueRIKWVagESppS3kwMkbmqVfo+fxXyW3dNWGsWj58B7M+eieNd9+IPbs5xr/S320pXQKFNzxK/5fuj4U8J+a2kV46H5lMxH+3ZZ4rqpBn+IE1uGPTD1c+nhAGnB3h60RFRah4m0K5HoPffBBnzz4o5P1iVETqc3RpBnPnJSdThQqlHS03btN+BuFuMWhL6LbChcIvBBW0hV6UBv79e6ixLEGSpPi9/Gt9P4VwkQgWoXJ0WQKZSiJt/dANTQXKw+nr106NhwiRsLSa2n+olqMv/Dvgn2XR8pE7sWc1I9NJ7NoqRn/2NCqXN/jq0xeolGNj4d8PJo5FqXo/VtAKpBTImjSJRXMp7tnP0LcfhmwuNhYm/yjkcfb3IlIJVCaLs6eL2itXkj55EbIqWdLXaNeqMuMMfOk7k2osxl9ej9M/5JuLStX88blSasYI50ppX0UJLw42FlPNlVhbwVj41ysHKylJL+0gMXuWr7mJBKryY6EmpY9cjvEX3mDgy98J671EWpJDoC9hYflja89rI7loHjJlR/NusvsrDzWaobBtN2OPPjthrJLz2qi/8TJa3n0D1acvw25qCAVieRD6BB7k8hS27WT8+ddi7SZmNWsB1hyL0jZQkBln7OfPM/jV7x/y7/N4gDdDrxMVFaHibYrRR5+muHsvIpslVhUx2M2F1QrB3KmEVS9DjYG/+8pmIZtF4BptmeeWXme0mbAADzU+jnCL0XXm/YP2LKM9UdJWQI9EZ0Osq6bu+kuw21uQqQQiIfxduYcaHWPw3+O7qemg9srzsRtrELaYmj6f/kAwSy2cS+tH76L+1iupuXwlzu4urJoUdkON3rXZMs5TWdK2MI6ZYyFKeBqjx0NYYDfU0nDblYz+YA3Ovm6EcsqPhQCEh7QlVnM95HOMPfo0mbXPklzUjkzb/g6zhD6hoFiguGcfg//xXdwS1TcAnovK5w3a0PQdylyJ9VXF2zqSuVK2zeAaD29giKHv/YShb/2QmsvPQdakJ9I36VhMpA/las1O1wHym3RSrUBbNSl9E94V0nNxR4YY+Z8fozLjJOa0+rv+cr9bYjQjFbI6Tc3lK6ec780fu4uGd1xF1RnLsRprtVCdNOfBRP6Bhzc8ythjJSZGqbUrE8aipG8oDzWSIb91B04Qdl7BCYNK9MfbEO5ohrGfPoE3OEKo9pYQheb5FUH93U7gza78h5X2TBfxz/hOV1ISersHbeI3Z0WqaSX0NcoS2HNacIdHYWw8dq+YN77ZlvEeo89/uKngoWVBor2ZmgvPwBvN4uXyFDZ34g6NQC5HYdsOxp99lZpLo0JRU/JtZIzM2qe1acBzjb6W0Kf8Y7bUCbZ8O0XV+aehinmG738Yp28IWVuNPasFWZ1CSIHT0693+hYIS6I87XxZtq/C7GswFkEkR8A/vetPzG5Cjedxh4cRnp8JksjsEo6FoeVItrfgbt8JjkL1D5J97FmdxwJRMleiPqvBITJPvojT20/15edTdfYpWI06HbOQAitl6zoYtqVzM2h1zMS5wiT0BX2WRp9nZK6IGD9jUSXKT9bWN0Bm7fMkFu1GSoVXSp/Zliw3FiX0Se0XEWQ5EgkLmZR44yX0+b4MYcSVSR8e9A8xtuZZ3L5BrLZWZDqBcooIKVBFkz4vaksqRNLCaqnDGx5BFYoIv5JvKazaahruup7aGy5l9MHH8cayKKdI9qV1OsTWcfVcxYnoEwqhXNT4RPOFlJTM4Unmsi+YZF98nZprLkamkmWoOz5RSX5VwdsOYw//AndgKHKQIrDR+jpjFRzDj8TQn4V/ThCWFtqvg89BO8K8W7BoWLrUt5eP2hJ6t2831UOhgDc2Hm9L6/vjiNGnwkiRCfQpD0bHGPnOQ+B5pE5ZSusf/jqjDz5GfttOClt24Q6MkFn77LSECqUUQ1/9Hu6+HnB1ifNJ+wpQlSa1bBH2gjkoz2X82VfJbdxG9pcb8Lq6EUIilaLxA3cw+B/fRdZUoQoFvKFRRFWK5MlLKO7swusfjASL0rEQOkskltS2ctQE/smaaqovP5fxJ1+AbF6bODyfjybfhHYoDHgsEjbCtrAaG3DHs6hMFhkL2TTnig/XhfEc+fXbKGzcTu7c02j5/Y8gpCS98nTsBx9DJG2SC+aR3bQdRsaM6w3h0xxffyHUfXSi8RUcZN4Zc0UEhupJ5gr+XA55QdTPoE3XRY2OUti0XYftSgFuCf+ESc8U9FkS2dRA7dUXkjp5MQC111xM5vHnNE9M+vxrJqXPU6iRUYp7u6m67DxqMxlUJkt203ZUz0DUZ2N8BQqKDu7OvQx/+8e4/UPU33EdU8GqraHx16LMqWOPPk1+wzYQAk8p8q9vRI2N682Fn/ultBqvdu4MNCXCj9adfCwYG2P0wbWoXJ76O6+fkr7jCcHMPdI2TlRUhIq3IaouOhunu5f8xq24vYN6ATYz6EH0AAzfjSe2ucMMj6voeGhSiB6kQgLVKVQ+T+wnoxTu0DBeLkss10NM2AmOCcrSp4zP5neeh8pmQSkKO/cw9K0HaLj3NuprbmT4/ofJPvWS7vs0kHtlHU7Xfl3nI3JwKOlrRJ9MWNTddjWZx59j8IvfAil10SbX1UKCJVCug9VYB8Ui7v4RUqctg4JLYn479ffezMiPH2fk/ocglyvps/+HFIjqKpKnLiO/fjOEdSWUdgZIJUkunk/tNRdD0SH3yjqUUygR1kofX/rBX33pueR/uR6rrQkGLdzx8ZKxMK416fI8KOR1boqtOxi+/8fU334dsqaapo+/m8LmHdTccDkj33uE0R+uNXazKj6m5rimU8j6aryeAYNMY/5JocfEcwnnjDlXyrVpHi/bLzVxfJWKxt+y/bmjyrelvHibwe/CsrBbm2n44Dupvvic8FKroY7E3DbcrgOxsZj4GyilD0jYyFSCqjNPpvpcnRQr+8Ymhv7juzjdfeDmDR4Y9Dke3uAQbq9Zjn56qL3+MmqvjyrTZh57luwr6yN+WZKaKy+MXSMsCywtIMpZTXjDY5A3aqGUjoXy8AaHcXt7D5m+Ct46VISKtyES82aTPn0ZxW2deMp3rBPGQyp48JgPYlyttrWU3qH5mQdFykbhP8wl0YPL3NEG/wtBmNnPeMAJATKZQDHutxu8ShIulaUvOO76n41iSkFbyoORUbJPPI8az9Lyex+l8b23kzppwbTzVaRWnERy+SKc7h4dtVGOvgCWrnOSfe4Vclu2Q2ZcCwCeikwmeDCeYexHj4LnoMYyyGSCxl9/N7KmmuKBXvLrNiAcs8qjMRYCSFgkly+i/p7rGejcqSvMBn2uSpM+8xQaP3AnALKpHpGQkDXHx/g7yCBpgbAE+XUbITuOu68bVSzoHeh0xwLNU9XXz/jDj0M2R+NH7iW5uIPk4g4A0qctI/PI43hZgxZTAxLMPeEhPAeZSKDMAndSnytb6kksnI9Akd+6AzWaieuOy/U1nCtq4lwxX6XXB/Qpw53OoHNCW8G7IVgI5UJCt6FcVy+0PqqvvIDChi2ooFJwyNMp6EsnSSzpoO6u6xGJyISRXDRf+/04QVZaL847v03hFils7sTp7cee1VJu6k8LNddeQs21l0x9zjUXk/nFcyhvhKpTlpJ7cxNefnwS/qH9QzyH4tadOD392G2HT9+xRMX8UcHbDiPf+RHjjz8bmRu08TZ6UJVCKBASqtLYSxbg7u5CJGzsue0o16G4pVP/ChK2tonm8xN3wsIjMWcWTj4bLcq4IC2stmbY3YVn3l+UvMrRZ6ZhDnatsYe50ZbyIF/A2deNc6AH2VBP1YVnT59pAmpvX0Xul2/qxTtGn7mTFIiaKtJnn0Jh+y7E0HC0sEhBaFMXCjwPZ383QgqEUyT3/CsMOQ7VV1zAyH//kOLuLoTrxAU0Eb0Lt4izYTMD/98OlF/qHAHYNsnli2j5w48hLIuxBx9l9OHHYXw8VNFHY+O3mbSx57RhNTaQPOUkCru6wCnCyAiBH4wfejPJXCmhT2qeq1weZ393mIExPDufN1Tzpe0YbSnAdZD11STnnU5h115ddryxnuTC+VRfdzlVF5wFQPcf/CXOWCYal6C5UvrCueLF54ppVph03vnf+emmY21KyrSFIWwDeKgDvYx87X6cXXupf887wparL16Ju7uL3MZtFLft1Boqs82gXYM+4Tp4u/cy+u0fIlyP1DmnIyyp04oPD2uzWDBHy9EnJbK2Gqu5kaMNe3YryYVzcXYpaq6/HG98nPzIqF+zpIS+pMSa1Ybd0kRicQdWy9Gnb6bwds+oecyEinvuuYf77rsPgPvvv5/Pf/7zAKxevRqAgYEBlixZwqpVq44VSW9LFDZsIf/y66iRUX8RKtmpmhACEjquHMdB1laRXDiH/PZO8Iq4OzoBiQiqaPo27wkPZ38tSnTMxkonyb+5UT9IAIGHt2kLqugghU6bHNn7gaSNkLJEUPEhMcw2RItQuND7AobvCyBQqK4u+u77HKkzT6Hp9z8+LZ4p12Xw776Es7tLZyANaQz4F3QShBBYLQ3Uve8O+j7zV/qhHsRYCYW2HEf0uPsPYM9pp9jf7/skjDP0b/+FGhxBuK7RNxE3UUm0ur/gQrGg7eW+FkTYgvSpS8NdsDc4hBoe1rtkUaYtATJpU/+O66m68iJyL73G+BPP+udL3bYpQJWdK0xoU4+7h7f/ALlnX6Lq0gvC0zOPPIbIZeNzJWwrTp/Ag+Fham5bRW11FZmfPkHqknNJn7ECWRuVqq8670wy3T16p29byJZmpBQ4vf2REDDZXBEgG2pRxaK+3qxzIoxJDJrPtgVFP5W5MQ8D58q4RiEudOI5qKEhcs+/Qur05SRPX4EOKRXUv/t2anM5ej/1J3j5nE4BnkqgCgV9vVfCY89B5bRgMfyVb1Jz6ypqb79B90egBXVJJP+U0CcsQXLJfD9V9kF/CkeMmqsvxsuMkzrlJIrbd1LcsAnlFo2x0H0TlqT26ouovbN85s8Kjl8cM6Gis7OTa6+9lvPOO4/vfe974bE1a9bw5S9/GYDrrruuIlQcZXjjWbyREaTwk/gHO2hPRZ+Dh7olkPPasOpqKW7ejhoaIv+LZ/1CX/gPUokMnLM8D6Slw8Kk8B0CowVXCkHijJMpbtxi7PSAXF4n8bFsRFBETPltVKewmhtx9+zzdYIBfX6ESrhzZ6I63rRJS6HpKxah6OAc6MHL5xG2HVNBl4WUWM2NFDdvR7qOzycI602YffWFBau+juqLVzL+zEswOhppVTCrjioYHsH1nSKFbSHrqmF4BBFWJw0WWHNxwui70VbYXw+vWMTL5XXWVCH8MuDBWEzUVgg8vEIBJzPO2A9+An0DekyCcRVCj3vY14CMEgHFpM8SkEySWNRBYsnCGEvdvkHttFc6V5RJX9Se6h9g7Ec/o/F/f4rqVZcy8t0HGf3P/yF18bk0fvheRCJB7Tuup/jmBorbdyPramj81IfJ/3IdmR+v8S0ywRiYWpWoL8ICsBBFSw+u6/tMSEAJqK7G7piLrEphzWsnu/Yp398l3lbkmGmMW6wwmz7VO9DD0D9/lZrbrqf29hJHRKHHREgJ1WlEsRDxRpS0JYTvSDqG29MfXe8LFvqzQZ85V9wi2ceeQmXGafzND3K0UXVx5BSdXnk6hQ2bKbyxUftWmEXlYmanEwtv94JixyxPxX333cfg4CBr1qyhsbERgLVr14Z/AzQ2NrJ27dpjRdLbEoklC7FbmyNnQyAyUZgLk9LqaadI9bWXkTjjFLCl/xD1F/3Y7iJoylwQjB1RVYr0heeQOvs0RGNdfOHwHQ7l7NZwYQ53ukBy8QJC00ap4xroJ2dTA6SMsLhJ6QOUh7d3H72fvI/h//fVg/JMCEHq3DMQCTtqM+BB0KihHRFC4I1nKe7cBUXTMVXFG1aaTpXNYrU2IdIpkqevgNrqiUJROEZMbEsZ3wnAdcj95HH6P/uXZH/xjP+dmji+xhioXI6xb95P36f+GKdzp9aCVKWwZrciGuux2tt8r34V3WcCjcS+E40NVF93BY2f/g3sObNLeGo6OZb2M6DP6Kvr4u7cRf/v/QlD//hlvF17YHSUwtPP0//nf4szMIhIp6h7710kzzqFmnfciNXWQv6V17UZJzbHS/hnac2DGh2DsTFQLpETZvQSeFRdei7Nf/y71N5xk84eK9BRTbYdtWvKLqVjZPLedVCjY3g9JY6IKlj40XRkMr5gFzCPiW0JENVVpC88B9BRP/bC+ZCw4oSUzhWlIJvD3d/NsYY9t52mP/xNqq+9HLlkEaSTeiwSmpcnaqruwKfiSF8nKo6ZpuKll14CtJkD4OMf/zjbt2+npSVyvmlubmZoaKjs9fl8nrzhKTwyMnL0iP0VhtXcSHLZItw9e43drbnjjz/M1fAIoipN82c+ydAX/oXCG+u1lqF0Bx282wIamvTzanAo1DhYjXWkzjoNgNo7bmDsG9+FnD+eCYvkSQsR9XXk9+3HfFgKoUietpzcL9+A0TFtDqmpQY2O6gdtwsZqn031O25i7L9XowqBp/sk9AWOm8UiFIs4e/cdlGfK9cj99Be6XkbM+U5EGgjbIjAtJE8/mczqB3G270AUAxNGyVNCENrzhRQkly4k/9IvcTZtwW5qwB0dJbawipJrMdos7avyIJvF63MpbttJceNmbUqJmW1EvC3PhayLyPqRJlIg8jmkbERls9gL5+INDcLYOCRtZFsr2LauRjs8rBfVZEI7pTbUY7c0U33rdVRdcn55pgoiPw1TgjTNDLG+elpzMDyiD0l/rubzeNt3MvjZv8SeM5v63/s4zfd9SnMnl0dUV+ndPm5cIDRh++HO2ay+h+VrKUKnWl8zlsuSW/MLUqefgtXehr1wPsVNW3S/HUc7MAfOyIGZSKrouDL6CoQOlKVrpy9Ah/4vTjEuFIbCYfB7FZCwqbrsAlJnnKKbsCzq33cXI/+9GmfjFsgXys8VoSCRIHX2aeXH6ShDSEn9h++lTilGv/YdnJ5eZF0NamRMC9gnIAwR+4jaOFFxzISKwIcCYOnSpbzrXe8qe14gdJTic5/7HH/+539+VGh7u0Apxcg/fJHChi2hvTxMxBPmLjA/A8U8uUcfJ7XyTOp+7U5GPBdn0xatCofIXhu8W5Lqqy8huWI5Q//6HzA8Cgmb5IqTQjqqr76MwguvUly/SfsRJCzSF5xDfvO20LIQtCkEJE4+iaorLyH36OOIZJKau29h7IePwOAQpJLU/tqdJE9dQebb3zPsxypOn6BsX9VAP7lfPE36qig8rhTjP1lDsbMz8kkw+wxgC6yOOVitrWBJEovmM3r/D3SiKfP+Jgz6RLDAFgs4XfvCuhJxeoPrmPjEKe1r8K5ccs88CwVH+yWEPgEYtvky7QUHHQe3u1sLXzt2kjptBe6BHuy5s6n72PuQdbUUNmwm88BD2IsWIttayD/1AtU3XUt6MmHC6IYwxypwZqRMn821OOy/isbCdVCjozjZcTKrH6T+4x/U90inSJ95CpnOHVBUE8cgQOAjErRXbq74CbW87h6G//ofqH7nbdS9504y3/0hVFVR2LkLunsjTUDpWEjjXiEDBFRXkTozvqCLRILE4g6KY6P6nKoqGBmdfC77WpTCs88xtGsXtR97P/b8uSQWddD06U/Q//v/G1UslP9dSBB4qEk2c8cKQgjqP/Ket5SGCmYGMyJUfOELX6C/f2IxoZaWFj7zmc+wevVqXnrppVCwaGxspLOzk6VLl8Y0E4GzZjncd999fPrTnw4/j4yM0NHRMRPkv22glMLZtQeyfhSANHbc0thNhVEUgOfidnfj5QuMf+8B3AP7ELjGjtfYkSkFlk5ukzzrNKy2ZryxUUjbVF1phJt5HhRzCGmEkUGYflg/7LTWw54zC1lfR+07bkT1dINSpM4/h9yLr+CODGO1NpGYNweRsEksmEtxdEQLKuHu16fNKtdXvfsc/8mjJFYsw2qPq+gDiFqdShuXeF8D/lmC1NmnUfueuwHIPPBjRHac0BmwrJEx2GUGfgX64e71dGMvXICXtLQTpjkWJRvdiU2WjAVaYxH1GV+YKNNmOfrwwC3q90wGZ8sm0pdfQu377g3PSp56MslTTw4/11x/9STElbQepmT26Sp9l0AqpTUImcxEOkXEv0gjUKTw3AsM9/VS+4mPYjU3aTYHC/Bk/HMd/TLbKvu7AJwi3uAAme9+n+Tpp9Jw3+8hhGDwH7+I09sT6a1LxyJsk5ijq8BFZeNlvoUlSV90Lu6ePVhNjbiZMdTYSHRtOfrcImrMobhtOyNf+Eeq33m7FpSVMCJ3zJvE+ZZ/6WWSp68gdcH0sstWMDkqIaUzgM985jNTfr9kyZKY78TQ0BArV66ksbGRz372s+Hxzs7OSR01U6kUqVRqJsh920IIgb1wHsXBQf0QNXwewsU9cJBM2OC42ou+sYHhz/0tXudOhONGgoepsg4dv1wKr71B1Q3XkjppKbmu/VitzciWJgAKb25g7P4H8HbujqIb3CL5Z56D1hZtR61OQyqN1dRAzTtvQ9ZoD/+GP/htMt/5PsN//td4Y2M6BfXypaEwUHPvnQz/v69AT09k2imlr7SvKLz93WS+90Pqf+c3yjPOKRLmaSi1+ydsrHmzSSyLhOHE0kWI2moYCnIEGIsShvrZX+QEwTNfQTaL1dKIm0pqU07wZelWPdA6TDUWYZ9LhEVK2jwIfaC0eWRklNzjT+J27aPuNz6CbGw4tAloICgoNYG+wEQgBaK5ETmnHfe1N7QAKADL0t+7LjE1fmD2yecpbtrK+PcfpO7XP+grIIIntNlno6+e35ZlRW2V+10E/FPA6BjF7Z1hqGxQHTQy4UxjLHwz1di3v0dx42bqfuMjIX/sjnmkLzwXUVdL9sc/8aOIDkYfWugZGKS4vVMLFULFHYPLzRXlwXgWZ+fuilAxA9AzezK12PTbOFFxTMwfK1euZPXq1aHGYs2aNYAWNu69915Wr17NwMBAGHJawdFB/qlncXfvjQ74m9GYM6Ovl5Yd81H9A2Bb2PPmkn/mWS1khA8m/1wpIF0DTkHboZWH17WP8R89RPWdt4LnklixHGtWq75GKaPugxZeZHMToqYa+6TFOK++hqxKU/cbHyFx2ikhqd7ICGNf+TqFTVtgPEtQZ8TZshV3/wGsOe0kli6h6vpryH73AT+6xFwszf4Zf6PAKVJ8fR35514gdXE8C6CzczfZR34GhSKhE6nRlqiuou5Tv4k9d054OHnWGVhz5+AODRM+wFV4w5DH2BLR1IQ9b6626wfNJlPI1mbc8UxEf1nzR8lYlGJCX0uPGfwppS/0s1HaX0II7YeSy+Gs38jwX/8dNXffQfK8lahcjtF/+yrOXp3bwprTTs1778XumF+GqIB0ZdyLaCyE8ffgAO7YWJymRBKrtQl3f48vGJf0D8ApUnj5VQpnnxF1y1xMg4OxcOQS/njETTJl6Rti9Av/QM373k3ipCU4r77mz5MyNJUbC/x2RkYovPgK+dNPJXXpRQAkli4msXQxuedejN8/+Lvc7xYIMqkmli3Vh22bxNLFFHbtgaEhPycEE+G5FN94E++m65B1tWVOqKCC6eGY+VTcfffdsffS4xUcfRQ2bEL19etnymS2Y/+71PKlJM64ncJr6xDptNYgmA/U4OGcsEldcznO6+twu/YReLU727YjG+qp/cj7YzQkzziNpiWLGPpff4LKjGEvO4n6P/o0wrbxPI/8I4+ihgYZ//4PqV+6BJHW2qnsjx+muH49Il8wHooKr+cAI3//T1Tf+Q5Sl1xE9Q3X4m7crBP/WBbuwCAqX0AoF5Xzw/KUF/U12MHlsmR//DD20iVYbbNCelVBh7qJUnOBn6gnnkwK1HiWsa9+DW/P7uiagN8+zYDOXFlXS+Nf/R9ULs/o3/8zIiERtbV4/X1UXX8N4w//DNXb4y8EQnvyO26JOcUYi5CuiL5I00G8z8HnyegLNRVCe+WDNoVILYR5XV2Mfe0byPtX4+GhegdCwcsZHmbkb/4ee/58qt99D/aCiWbKRMc8Cn29UPDK0OWPSbGoQ4wDdQ4KLEisWI43MAhZJ97XcC4ryI1T3LwFUV1tOISW9NXkQ8C/4FWWfyX0OUWczVvIrv4BNZ/8DYqvvoa7ZavWopSZK+XHwr93Pkf2oYexly6OmeGE78iLbWnH0UAgL/e7DWRCS+jIFEAkEtT/we/gFQoM/eF9eqNQbq4oF69rL9mHHqHmPeX93SqYHhRHbr44wsvfUlQyar6NYC/qwHnpRb3jRIH0w+ZiPhQqtPkmV55NcuXZFF57nfyb66BrX7Q7DBYyqbAaG7BvXMX4Dx6E0RFwdabE7EOPUHjhBVCKxNlnU333OwHIP/s85DOIlE36qssQdhRCZrfPwhkbRo2PMfZvX8Lt6dUm474BnbJaKL0bM9S96sABxr9zP862rVS//33U/8HvTOh77udPUHztDbyhIdyeHoSQKCEQykMJAYUianQUd//+mFAha2t0euswdXDEH1IprPlzkVXp8HxvdBRn4yZEZjSiE4hUzYTtBAJJ9gc/wuvtxZ47G+ukpbhbtmKftITGP/5fjPzN3+Md6EbU1CDnz8XbvRclJeSzkUc/+AtZkFfBv1dw/3BcjXdVsriV0heMcZCKPIi2CE0oHgwN4Y0M+0KXiO7rFGBgACebw925q6xQkb5pFc7GDdqBsJSuUJugSugD3CLu3j1YHXPxdu70ozTMayP6nC2bSV19FaI6beQKMdozBQnFRP5N+F2Y9Pnfp3Tkh7Asau6+g9F//yr09BJm6wzHwr8myAlj5jgJTBiOM6Gyp2xpwe6Yq7/LZfH2d0/xu/XvkRsn861vk334J1TdejPJ88/zh9MQbMrNFaeIs3HThLGq4NBQ8amo4G0Dq7UZYVtGiFrwUDIefAJIJbDnGer8s8+i8eTlDH/mPhga9I8K7VxYU401q4XkBeeTOHkZma9+HbenB3vBPAovvYS3ezcoKPT24qxfh9WxgMKb63Uyn0RVbAcphCB94yqyq0ewly/H2bABtW+fXvw9jzCBUKgtMXawQ0MUn3qKke3bwFPIlhaq774La75WwaevvpL01VdOypvC8y9QXL8BWV8XO+507kAMDaLrPFjRQ9mySF5yITUf+VC8If97IQz6TMFCCpAWoq4O0dLM+Ff/k+Kb6xGei6hOI20LJzNK4YUXqL77LqpuuRFn02bS16/CMhyTi6+/wfj3f+AnHBN43T2IZBKVyWhzhZQIy9IF1Vwjm2SYCrlk8Q7oC00f+iXq6lAoCOqKmHOl7FgYbQbnloGsqUU21uONZ+L0YNInJtLnFlF7dyPa2/0qmK5fLVTE6VMu3v4u3H1dJC88j+ITT/omMYO+oK/BPUtfk/VVCqiqRiSTpG++ifSNNwCQOOVkEsuX4vT3RW2GTrMl9AUCqgAsC1FXS3rV1dhLFsf4lFh2Eg1/+scAZL72dQq9PZEQMhl9KBgaxBsZpvjaayTPPw8hJfa8OTi5rO+8awgYhiOnCKJTKqjgMFERKt4m8Pr7yf3gh3qHa6p5zReAbWGtWE7yyisY/8Y3cXbt8v0gFATFf4DgoS875pG8QIcPWvPmUffHf4TyPIRlMfyXf+kvXDrKwtuxE2/PXr+Ud1CqeyJULovavw/75OUUeronJv6Jqa2NBadQQO3cBYDb20tx48ZQqDgYkhddSOL888pk1zQXvGDXLhFz20nf+Y6ybQkpUMEDu9SnA6XNGM2NqHwOZ/16yOdASrzuA6jZbTA+TvGpp3DOPIPUpZeQvOhCvK4uRv/pn3W6bSmxTzmF2j/5/yGl1GPjaY1L9j//E1HfQNXddwEw9sUv4r6xDopG8SvL8iNkgv5NGAF9Xn0dtX/xZ2Q+/3kdxVM6VyYbi3Lfl8CaN5fUtVeT/f4PIDtunOsLExifw4ssLTAVCqg9e3yBSkbCkulnINChsM89R/qDH8TduhVvz57y4xEO3CSvCX0F0dpC7e/9LpaRZwfQY1E67iZ9Mb8M/92W2CvPJn3D1OW9TRnooGMhJdTUIOe060O2Te0ffprMgw9SfPgRP9eMIQwK9BwaHMTZuhV72bIpaalgckwuSh9aGycqKkLF2wTOtm2ogX7tRS5ktIMO3qWARBLmzaP6zjtRY2M427bpB7Gnk8bGHmqBnVvG4yWFZYULc3h+uIPVSafCImZCTCicI6urkQkbt7sbq6nRX1eCB3G4tY4/TEMYjbkO+ccfo/jKK9iLFpK+510HTcdd+r1SCmfdOr+2iX9/KaGtjfSqa7GamiY24ndIxOgz6Aad42P3bh114KdTDoQit7sblIfKjJL5j3/Ham7WD6mhIby+/tC/wtu7F2fLJkQiQXLVKpJnnwNAzUc+EmopAKpuvoXMlq2+dsqnv7kZhocMp8IS+sIOKPL3f0cnQAtOE0Aqqc0OpinM7Ks/l0RbG7I2rvkxkVq1iuKGjbibNmnBInb/knfLho4OZEsL3quv+iYX45zSkFQ/ukJls7ibNpI871zy3Qd0nyc8skvnVZm2TE2KUojeHrL/9m9U3XUX9qmnRi3JIAqkpM0JbRnfOw7uK6/gXHQR9imRc3IpVHC5tAirVpWjDyBhY599Fulbbolosyyqb7+dkaefgf7+sn1V4+MUXnmlIlQcAd7u5o9jlqa7grcWzpvrwAsc20xVuP8uBcxpo/Z3P0Xx+ecY//cvo/Ljun5D6Ghm7LKCa3v24/X0lL2nMB9aovSeWkXtbnwzdo29fDnW0iWIuhp/ETSuCbIPytI2jd1W8LfrwIEDeNu2UHzxBbzDyMCqCgXc7dvA8xdfWyDmzaH2d36b1FVXTTjf3buX7Le/BcXcRP7G6FOEZbNN2gt5VNdevWhLC4aHcbduwduyGa+7WwsGEn1tPou3dSvuxg3k/vub5H7wgA5vTCRiwpGsTiOb6nWK9YSFWDAfq7ZatzEpffqYyOdwXn8dsr6JwpJQlcZaeQ5yYQfUVOt2pdDal/o6qEohFi2k6kMfpPYPPk3inLMn5a8QgtpP/AaJiy7QIczh7tuYK76Tolgwn+qbb0KmkvE5UW4uB3NFCp39s6UZ2dwEtTWT9nUCH0rbMukSClXI4+3aSfa//pP8Tx6J+iTF1PSFbRhtojV52a//J/mf/WRSflmzWhHNzYh5c3TY9RT04RTxXnuV7Ne+Gpv7QggdiVVfq8eslAe4eJ3bdQG/Cio4DFQ0FW8DFDesx3n9l9rRMUiWE7wD2AlIJbFnz0bkcjgvPY8aGgYgrEEgFbpkIsR2N5lRii+/SOrmWyfcV7a2oPbs8ne0/m5KGW25Bdxt21DFIiIR1e0QCRuRzcBgfzzqAowdrCrfZij8eOF3Kp8l99UvI1IpEpdcRuLcqbM9hnQIgQoKe9kS2ttJXX459iQmleILz+Ft2Ywo5AmTLcnJ6CNuGxcCXXPCRaSrEPNaEdU1eBveBNf1o29K2gz6PjxE8fE1uJ3bsE86ieRtd/ipqcGaNx972TKKI8PIjgWk3nEn2S/9K8Itav5NSp+nHS494acmF5BOa8fVrt0krroWObud/Orv4g0OIua0U/3+D6GEQCYSWG1t0+NxKoWsSusEVWHuBaOvtoWY10H1b/4msqqa3MMPRtEcgbNkaeI2Y66IpI29YgXW4iXkn38WNTLk7/IPNhbR9IopckL6PPAUqr+fwk8fwVq8GHvFKVitLbgJ208aVo6+kraCA56DGuin8MQvSF53Qzh+JlI33khi5UpEQwNj//cvUd0HpvhduNrkuGsn7s4dyDPP0l9LSc1v/zbe8DDjX/9P1M6d+tyAPuWi+npw9+/DXrR4WmNYQRzK/3ekbZyoqAgVbwMUn3vGz6LpHwiqG0pASJg7h+r3fgCkIPfD1ah8DoSKnk9m+Fv4wBWhqn+y6W8vXoS3fh3k3QnXREmLvAktCClgbBRPeTqTZakdXEHs6RxLMFVCnxSQz+Ft3aIvLRSmLVQACFvqXWHLLKrf8z6sKdTCoroaUkktVJT2NaRPRnQGTn+ev7v1FzpRW43EI3HZpeR2dcLYaNTnCWOhtC08m8XbupnC7p04O3ZgL11K8pbbEVJizZqFOPNMEpddgWhq1OYnORl9Bv8wTGUSramxLVRvD8WfPoS1eCmyrZXkDTeROO00RH09xSd+DosWAdMTKnSvfFNGMB+l1P4T+TxUp0ldeSX27Hay//nvWtBUfn0Oz+CfIOJpOFcUIp8j/93vUP37f6gFVwna4VZqs57nxudK8LsIhLZwsY6ojc0/5UJ2nPx3v4P16f9F6sabKb7xGuzfp/1YpIiEcSXibSmjcQGkU8iG+sn5ZNtYc+cCIGe14vX3GL4xGPM+aFOhPA9r6dJYO7K2FllbS9WNN5L7wfdRB/Yb9CnUCV0j863H2938UREq3gZQnksYThYKCgISCbBtrNmzsRYvJvtPf4fXuR0RqD7Dhx+EoXCgH/jJZORFXuoY4cN5cx2iWNJW4BgWpouelGq9W0smtaYjXOjMe/kXT9gBEi0Mwb18vxCvZz/Zr34J+/yLSJx59kF5Zy9ejEKSvv2O8IE+6bkrz6Xw2KPRgi3K0BfLjxF0IfwDhEDOnQejw5p/lox1NTYWoZCI9nHwBIyP423eQPHAPuyLLsGa1Ubyuhvwurux5s/H7ek2fBEMTU9wMJHQIccx+oIO2oj2dlR/H4yO4L7xGtgWhd4DuBtewysUUV17EQkb2bEAFNjLTiZ55TVT8k2Z/hGWBfMXQE0NbNqg/UNqa3C2bMJZ9zoil4sbbUO1/yTaBdfB695H4acPYTU146bT0NyMaGpGbd+uTTvmXDFh8rnMtNN/69wRnvJwNq4ncf6FpK66hsLPfgI9ByKNS7lrTVgW8qSTSL/n/WW1FKVIXnEV+V07IDOmGy2XyEspGB2i8OAPSL/n/RPasFeeh73+TZyhISjkIh44RdytmyuaisNEsF060jZOVFSEil9xqFwWr+cAmKFiQmlfiTntpG68BXvJSRSeeQJ33x79cIntXPEXMv9aS0BtLWLhYtSm9VBVhQiSI5XCLUYLfPDECnaECEhaExw9far1Na3NMCShkCV0TAvoN9sKdpdgRAH4bYTqfUB5MDKC8+pLeMNDBxUqRDJJ6tY7EA31yLrJd5AAyvPIf/e/Na3CK7/7NekLEzAFdBLlGkgnUf15vAN7S/hHfCzK9dX1wAOVzVD46UOkbnsnsrExioIRAqyAHypaOKXSC3pDAwwP6nZK6fNDiLHQu3DQybh6unG7D/hj4qGkxD2wHywLb/NGvN5uUjffjqiuKc+8wA/BApqbSV53PVb7HLL/72/DbheefiLy7Qj6HtAX8CjQXAR8EhD4KxTXvU71b38a59RTkekq3P5eCju3E/OfMOdKIEwE7imlT/lUWgu7vtnOmj0b29eAJS+/EnfLJtzhgSjKYoKgGdDn/yEUamgAb/fOaZmOZFMjoqVZ+z25Xrwt83ebz+K89jLupZdjLVgUa0MIQfqed5PZvQPVc0BrhgAKeYpPPEZi5XnIltaD0lJBBSYqjpq/4nBeeRFGh6MHWvgAFci6OhLnXoC77pcUHn0ExsfiTmsSrWa2hNYYWEJf19BI+l2/hly0BGv+fJJXXF3+5qUOcEGbtg1JG+rrscqkctaqcIG0bURLiy94GIub2ZYUcfrC+4kSp7ygdV/l3d9D7vv/g7Nl6mQ/1vz5BxUoALx9e/G690NQr8OkL6RbxflRypvgmHJhdBgxPKTLagf9smTUt1ieAUP977clCjncN36J8+TjE4k1HWAD+mwL0TqL5B13aUfRMvQJKSKNQnA9SvPTczVvlReZFVwHxrQQV3zh2Ul5F5pjbBtr/jySF1yEbGoK04MrJ493oIuYc2k5/gW8KZ0rQoFbRDY2krzgIuwzz9IaoKDvYrI2/bbCY0pntqypxlq+nMS97yV1592k3vVrpN/zvlDDIKQk/e73Ql1dyZwkWvxL5zIe9PVQeOB/KPzsIVTBSGxWBtbipaRuuwPmzfOdZUv4EMwVpSAzRuHJn5fnfVUV6Q99DGv5CkinI0FsZJj8//wXyjSvVDAtBOaPI32dqKhoKn7F4e7fiyjk4g+xpN5dyeoq3B3bKT7xGGKwj1BxJ0WkTk4kQHmIufNQmTFQHvYZZ2DPbke88x5EXQMiMYmmAuWXtw4WQanbra1BNreSeOe9miTjeuW6qP4enZ5YgH3BxRT37YaxMUMw8P8wQmHFvIWo4QEYGYain8rbI9ohmipupWBkCPfJx3E3von1u59B1DUcMa9FUJAq5J95X2Mhj2kuSs6T6KqcvqOfnDUbVRjXx2ICkoh25aEWiagt14VCDqdzM9buneEuNTQ1mPcVEpqasM9ZifvC0zoxWTn6/PuHJcu9kr6WCnBSay4o5HyhYxK+pVKIqhR4CmvOXO2UCsjqavBc3FdehOEhBF6k2QoEmmDhFOgF3LYj01qgXrAs3Vbspv4pE+gtmSumFsQS0NiAfeZKkjffjqyffM7IunqtwRuDeGl1YZhUTP55OspoeJDiUz9H5XKk3jF5CQMhBImzz0UVCxR+tBoGB/x8LlILpTHaXby9O3DWv4592lkT2rLnL8D64K+T+cfPQfcBrV1xCni93bidW7GXrZiUjgomwlSqHkkbM4l77rknrK11//33hxXDV69eDUQVwicr6HkoqAgVv8JQ+Rzu5o3aryFQ7woLZs/GPv1srJNPpfjGK6jMqJ+/wt/166u1Orx9tnYQW7QUedIK1EAfiSuuBcBaujx2P2fPTrytmyN/tMxY9NAHgqQ81tJlJK64BmvZyZSi+ORavIFehOeixkeRLbO0yn18TD+Aq2t1e+NjeoFpaEAuXU7q9rtx9+ymsOYh2Ocn2HL8na3yF+BQte3pvx0XBvvJf/dbpD78m9OyZU8GMXc+orYKhuwoc2OAcFcPYTRAYI4y6ZOWFvj27tTRGZ4HSRvR0qoFJdcldGIsGjVAwrbx2xG6Tc9B7eok/52vU/U7n0FUVQfpQQzhRvMwcdUqqKrCffVFhOfEBZbA0TAwgQQLljlXwvsTp8tD+xz0lQ87BkhetUoLA0qRuOwq3VR9A8mbbsPdswv3tZf8tOdE2gPpr/qmo2siCfMWIhcsRiRsggEXSmGdevrEMQu1NWXGIjQzGSaVRALZPofUPb920JwnACKdjsYjbMvg1QRnDXwT3SDOxjdI3nJHmMJ+MiTOvRCRz1N47KfQ1xMJb+ZYKA+691P48WqsZSsQyYnVnkVdHclrb6D4yA911lyloJDTybwqOOHR2dnJtddey3nnncf3vve98NiaNWv48pe/DMB1111XESoqmBpqdBjGRohyIlhQW0v6ne9Bnnwq+W98BW/965AzsmwiCLMU2jb2shVYi09CdixEzp5T/j5K4a5/g/yPV0N/r178hPAXV+OhpHTKQ5Ubxx0ZxHv+SeS8BVgdiwDwRkcoPvukTvCUTOhcDDu2IlpnoYYGtYq+YwEikcTbsRUSSRKXXU3i2hsRiSSytQ1rdjuFZ5/A3boJDuwjqvegDFpERFM+i7dnB85Lz5K48LLDZ/aBfahc3vdFCKQqfK2BcV5QBCpYUAJSbBva5yKKBdTwsB4D20aMDGNdeg3uGy+j9u8PzQQMDxFz+jRV62E/lc590ddD4YFvk/y1j/rnK8LCVLU12OddTHLVTRSe/oWRcVUCZhVQEfoPhMJC4OSJIXSYgQOBicYp4G3fghrPlPWrEPUNpG5+x4TjifMvxtm8Qft4mDVAwgU58PvwX04RBvuQc9pJvetjE9qL3TPoj/D7JoyxKDdX/HNke/u0BAoA+4yzcIYHYHjYoJlISAnSdwdfSfR/lkSUCqaT9UNKEpddhUomKf7gf3TtHb+ZcCyUNv+o8cyUbSUuuhyy4xSffAwG+sFzUYP906KjgghBvuAjbWMmcd99900o3rl27VoaGxvDz42Njaxdu/aIBYuKUPErjMLPfwpZ3ztcKqiq0juVhYsprn0Yb9c2GM/4u2dfmKiqRixYjKip03kdLr8G2T551IPKZik+uRb31edhf5d/0BAkROkFLmpPJ87OLZBMIRoasa+/DVJp3BefgaF+REMj8vwL8Tasg2IRu2MRxd07EOkq0u/5ECSSFNc8hFyynMTKC2LNy7nzSd/9XryuPeR/eD/enp36QRvuQiFyDND0qaFBnKfWYJ99HiKV5nCglPL9KcwFCSI/ABWZLQIhLyDD/07WVOMNZqGQRcyZp+ttDA/ivfQU8rRzcEeGtNAR7NaRJe0QmVkCFbsEcuO4nVvwNr4Bs9qj8bYTyFmzSd50u+7D2JAv+KHbN9uyLazZ7VEIY7BImsqKsKS90Vfh+bvew0ymND6q1fnBvWKmlpK+eh6MDuHu7MTr2o2ct2DSZu2VF1B85nEteJsI/V5M/xW/k7Z9UM2BieR1t+JtXo+XGdUHJsgiJZqKVArRsQjZ2IK1fMUh3Stx3kW4rzyHt32rFgzLjYXroMbHymoqQAsoyWtvgnSa4kMPaL+cp9aijuB38XbETIaUjpQk7UulUqRS5cdvKrz00kuANnMAfPzjH2f79u20GGnmm5ubGRoaOjyCDVSEil9RKM9D9RxAeK5WU6drsc5cSeKWu3Ae/C7Oay9BPoew0A/NVBWiYzHWgsUkbrojloxqKjiPP4zz9OOQzWqbd2jLNh6Y4c4XrZ7NZfV3joPKjeN87xtQLKCkhSgWkC2t2KeeSbFzM2RHsa++CXf9LxHNLchW7Rmfuvt9U9Il53WQ/ugnyX/xb/By4/GHrOFxr5nlwoH9FB+8n8TdHwht+ocC2T4X2digF2bHia8XgTNl8Lfp5BgIO66D2rEF4er6IiKRQFVXw3A/9HajnnxU01UsIALawwVDEcvcCESZO/3vB/spPrWWxF3v93Nv1CAXLCb5jnchUmm8kSHcV1+IEncF7aJ8k4tASYHq2qXNI8GiHuzai8XoXmZfhYSqFNbChVBV4tcwHQTJxwJeBQmqSukL+65gbAhvdGRKL3RRXYOcOx9v/95ImyUBJY154r/bNrS0YS1agn3JldMmXSSTWPM6UHt2lPiUBG2L+E/FtpAnn0Li1DORHYunfR/QAkHq3g+S/9F3UZvW6bTngUkTAA+yGYqP/YTUXVP/dhIXXQFDgzgvPgXDgzhPPEri+tsPiZ4KZgYdRhFBgD/90z/lz/7szw65ncCHAmDp0qW8613ly9sHQseRoCJU/IrCeWoN9HbrbIipNPKU00m+5yN4Wzbg7d6OyI1DXQPMW6Cfx+1zSdxy9yHtjgDtj5HLxVXxwXu4qErtWZ5IakfKUpNIdhxQCBzfbFLQ54wM4u0sgLyF5K13H7L3kkhXkbzrfeT//e+1oyNEQo+AINmPFnDyuFvXI9e9gn3meYd0HwDV1wPFPEK5xi7dv59yI6e8gDehoKGiz8Vi5LjnFrHPuxi3v1vTXizoKIlgFTL9KMy+hIurr3kKq7t6kBnTDrLnX4rKjZO49R5EugqA4mMPI/q79Xlh1IOIfGI8B7ZtRLhuXEjCj/aIreA+HakUtLZjdSwkcfNdhyWsgRfdKhRWytBnzrtCDufptdgrJvpRmEhcfBWF3m7Yv1cXdSMQ1ETkUxGwe8lSUu+Z2qRSFkHETLnfBSXHC1nUYw9ReONl7KuuJ3HBFYd2q+ZW0h/8BPmv/D1q+2ZfO2TwRjmo3v2+s+7kYyEsi+Qt70R2LMR97SWsU848JDre9lAz4GjpX79nzx7q66Pos3Jaii984Qv09080U7W0tPCZz3yG1atX89JLL4WCRWNjI52dnSxdujSmmQicNY8UFaHiVxAqm8F9+SkYG4SqauTpK0neeg9CCGTHIuSCJXgNTdgXXoF91qEvoCascy/Bfe1FrX0woxtK1PtCKFQ6CRkMk79pxw6ph4EevI2v+yGJw3j58Ql0qmIBb3go9KYXiQSyoWkCfXLhEqzzLsF94UndnpA6GiH0wpcRHUP9uM+sPTyhwnMhMxKpz1Hah6WuUTuVBqGmmiE+cRjCgaHBUAoxMoAaHkDU1aM8PzIgZuoXhjBBnN+2DU0tiKaWKIhBWljnXKBt8LdOjCrwhvoJTTVhpzCEFE87tpq1IpThmxHmDjHoS1gkrrgW+6Lp7+4nIDBDeGXmikmfGVWjPBg++I7LOulkElesovjAN6FI+bHwAFxU1068fXuQczsma64s7PMvxX3jRW1mdFUkqIQdMP5WrvYn6tmH+9RarLMuQB6i2UFISfLu95N/8Luw5U1tCjHNVH0H8H75PNbKiw9O+5nnYp957iHdv4KZ9amor6+PCRXl8JnPfGbK75csWRLznRgaGmLlypU0Njby2c9+Njze2dlZcdSsoDyUp8B1EI3N2BdcgXXd7eHORFTXkLz3wzNzn0Ied/M6hOtEi1r4CkwL6MXHKSJaZml1eX9vVOES/1yzymRuHJXL6hoPuRzOow8i3/0xpK8+V/kc+e9/Aza8phe5YhFmtWNdfQty2anIRCJmA05c/w5EfhxlJXSGxb7ucMMY7tiUzuApTznrsPkhTLW2AKqrYcEi2Ph6tLv3nVVDM0wp3wKmFfKosVHIjGo+JBK6umkgsMTSgPt8M/JgyLPPJ3nz5CGJpbDOuRBvy5t6x66Ymj6JnwdBalNPEMIZLPIxE8ihcjEOETj9muaIUBidgj7lHXRHHtAX1hIp15YApEQkU3r+HiLkopMQtQ1aqLSU9kmJZVgNxtHgl+dCzz6cxx46pDEM79k6m/SHPknhP/8BtWWDdmAN5sp4RoeGV3DUcLyFlK5cuZLVq1eHGos1a9YAWti49957Wb16NQMDA2HI6ZGiIlT8CkJUVWOfexlibgfWESySU8FzXYr/+Q+ovTvByRNT9ws/n0CQxyB4iNY2QGbUr7cAMYOy+SBXHqK2Hlpmobp2w9Z1FP79b7Dv+QjCTuD8z1dg3x4dZhnYjffvwf3eV3GTKUTrbBIf/19I3yFNVNeQuPcwVNeHhJJFKZlCnnOhDqUM8gYAExbdQOUuZKR693flQiiU5+icFQnbz79hagN8/gnjCSS0qcJb/yruhVdgtUyvBofq2uXb/VU0jhPoM8dVQlWVThMdW+QN+pSH5xant7iXgfvL56BnL9qxdZK5Uo4+pWC4n+KTP8G+6FrkVI5tE4QhFQmFUoCdRCxYQuLmuw/bWdG68HLUji3af2OgN2rb1L6EgqF/b9tGzlt4WPcDrbFI3P5rFH58P2xdr7VzaKHW8xyU5x1RCHUFJxaCyI/SCJDSzzOByqz6FYSQEvvaW4+aQAHgPPEwavdWPy11oC5W0d+mWloqwIVNv4SeLqIS5kROd+ZLuaitbyDmLdBOpkrBgT24X/oriv/yF6iuTnByhOWtBaAcTUtmGNW1g+LaHx3TGPuwiqhE0zy7ncR174ir0s2+lqS/jipkquizZQgaza06m6MI2inDc9MBtG8fzn/8jTaDTQOqd782sZSORSm95ntrmxZ2QlpEnD4nj/rZ93EefeDweNo+3y/PXYZ/U9EnFOSzqLU/pPh3f0Tx6UcnnQs6Z4dX0haQSsCc+chzLiD5kd9DLpq8kNzBkLjqJpIf/l1Il5ZtJ+JV+FlAQyPyoiuxDsMMZ0K2zSH53o9DTVV0L6+AevxHFB/57hG1XcHk8GbodaKioqmo4LCgevZrs4fpMKhK3001r9KLPhA6LE64yP8THRoo8KuUNrVov4TMWJSkK2wDoy10O14RXnycYtd2Eh/4/WMWDieCJEfV1dg33qWzjVr+MZO+kF41Od/8BVL411oXXY37i4d0NIgy+25cbPqzKBdGBlD93YdAu2FSCUicir7Zc2Cg23esNboY/uFCfhzV0zUtGkqhBnoQXuCzUUJIaW2aCfNOCxYU83iP/ZDijk0k3/+pCfeQHUsQjc3Qu9+/KVqYW7CE5Ef/AJGcubkjwBAeA/oFE6qVegXo7dKaI+vIHtEikcI6dSXe+pe1llB52ry47nncxcuwTqv4TMw0lFJHvKE5kZOOVTQVFRwyvF1bYc+2aBcd7M7NOhfhS5S8T/YyvvcXYrFoua5WWdeAOPdynRArPFdNfj+B3qnu2krxK3+Ft+m1Y8MYCSQTyDPPx1pxVnQsprURZftafvft98UtoLa/CW1zpuCj0W4wFnh4m19DjQxNj/awjWnSp200k4+FJSGZRC4/47DYqQZ6ITc2+VxJ+DVkpppXAsiNoba8QeELn6b43/8ce2CL1tmwYInuZ8C3+gYSN9w1owIFMAkvS/gnlF70d27CeebRI76lsCwSd30IedM9Ohon5Mm45m8FFcwwKkJFBYcMNdiLyIyEeYGEEP4Lv+iURKSrELPmIOrqEdIuOde8Rkx6TC4/HdHchrAt7SOSSsXPlaVtGn+D1qT07MV5/EeoXPboMkUITV/7POxr3xEdVqV9LMMzIXy++e92EpFMI/btRBRyCMdBdW5E1NQgGpoRljUN/qEdR3sP4Dz+w4OTj++WUNoWZegTAqEUYtOriEJWj3fCRlgy3s9EArH4ZKzzDi00MoDsWKK1PVJO7JuUmkd2sjx9MT6AcIowNIDat3vCLtA66TRE21zErHZE21ysS69HLpn5ehdy+RmI+kaEtMqMmzEvfHrViz/H27l5Ru5tn3s58szz9O9RCITn4K17AZU/yr+LtyEqBcUqqOAQIdrm6lDJwPmrFFLArDkkf+tP8Ta9hvOD/9Tpwk11NUR/xI6VwHVgqA9v+5sGASVq+uiLiepwT8GB3RT/5U8QbfOw7/k4omqSEtxHAFFThzxlJXLxyYiG5hhJoUo+pM/kQwn/pISmWZq3vQci58lCDnr3YV1/F+5LT2h1fTYTOb1Oyr8iasPLeMtOR542hY2+1CIVHheTtK2i+itSQE29fh8b0WOmgIYW7OveOe201qWQi5bD7Hm+yafMXCkz9WL9UT79AHYSGpoRC0+a4DRqr7wUVl56WDQeChI33Yu34CScH3xNZ7qdYLYJzlT678yo9nVZNLFGzqFCSEni7o/jvPQE3pOPQG4cuvdS/OrnsVe9E7m8kotipqCY/Od4KG2cqKgIFRUcEpTn4T73KOSD9N7+F2ahJMvWVUPHR3FfeUJHLwQmgAkCgYi9hW0FEQ2uA7kMXneX0YaapC2YEM4o0fcf6kMVcqhs5ugIFbX12LfFMxV6OzZp23hAR0hfcJFxPOwbkB3VIYheIeKxUNB/AHftapg9H3nJtXgvPK7DaYsFnZyq3FigfQu8vdunFiog8lsQQtvyXSfeVmjKEfGxAHCyiOVnQaGAygzD6DDy0uuR85ccChsnwryXOVeE0r4cMbomea+pRyw/k8Tdv35ktMwA5GnnwhM/hn1jJXSac1mAlYD2+VqAn0HY518J51+J+8qTuA/9N/Tuw+vaWREqKpgxVISKCg4J7i+fRm14WS96gU0YjMVPQDqNnLuI4n/9PfTs0XHygX43Fk4ZvCtiK60Q4OTxXntGx/abC4tZaju4b6wtE4bQIwQUc7jf/HvcOR3Yt33oqAgXJryuHbp2RSwDpUlrCX0KwIPcqP9dwDPfzuM5MDoI2TG8/Tu1liJp+4tsSmsNspn4WCgAhdq5CZUZQdRMkkhn/iLY9oau7GonoGWODucMSRVxR8jgmBDa+a+Qh94u7Pd8CtE8vTDWaSEYd1XKP6UjfpD+vJCQrNZf5bI6AViqGpIprCtvw1p5+czRdKQIHI2Vr8YSJXNZCEhayPOuQC5cPmkzRwLr3Cvwtr2JGuiBvn24z6/Buui6o3KvtxtmsvbHiYiKUFHBIUGNjWhbfZjKmWjRD0pkC4X30lpET1cUKRBb9FXJ5wCm1kLB2LCvqvZg/46SnX25Rbq0rRL6vCIM9fiJpPJwlIUKEURvTIhUmYQ+FSzSIvoeIJWOFkv8fmSNCrCJJCxagTzpDLxnfqp5Xszrl19LhN4u3Kcfxr7hPWVptS++Afeln+sIgbkLobkN+rr0PQ5GXyAsDhzA+ebfQKpKJ3myLJACeeH1WGcdnnlBhAtwcCT4Q0b8U0I7hc6ZhzzjYrwX1iLmL8W+46OHdc+jDTF7DvTt0QJcXI0VwSmgnnsE1bEE0Tb/qNCRuPe39K0e+gZqdOio3OPtiIpQUUEFhwDR3IKyZFTOu1RREGRitKTeLbrFcLc8IZwyalXvNKtrtZ1eKV0rZP5SWP+8Do8c6CZmOjCvLWuBNE0AxntVNfLi6+N+D0cByilqPxAVJG6aJn1mDRVz/ayq034VZhXRAG4Rdm/GEwL5nk8h2hegerrwHv669ssIKtBmRqYm2ragsQlx7pWo5x+FsEDcQegL6XBgMIgoiAQOb8138V56HHn+NYcsXIjZ81Bd23UfTafCMLOmT5hyYP8u1ElnYP3W/zfBb+J4gnX1nbiDPbB/l9biTfhd+K+xYbw927COklAR0nPL+49q+xW8vVARKiqYNtRAD+qJB7UNvxQCQGpbfH0T1l2/hfvAl/SDM5aPQUx02BRAdR38xl/AD78C3Xuhvhn1/E/1vZIp/R6aA4K2MGL9S1e4klVP+P8Jgff60+AWsc67ZqZYMxH5nDZFKHdq+mJmBZNuU5NhwcLl2vThFifyL9BM7NqI+vn3ke/5PWR7B/JD9+m6IUHX5eQ/dyEEdCyDplmIZAo10j99+qYaC6VgfATGR/CeHEPOXYSYNW/abLSuvRt1xe243/8SbHktEqpK12EhtFPqi2twt61DVFUjL70FueDomA+OBLJpFuJDf4Tztc9B1474HAn5JyBdi6htPOr0HM8C2IkILRIemarhBFZUVISKCqYPb8d6XaQsVsobrX6WAhpaoX0xYu4C1Is/g5F+HZvvCWNxKlmkAmHEtrCSScS7fxd3xwbU0w9Bz36tsVh0Gmx+FaprdMGlXIYwPbcyaIjJEeYO23ho5jOwdyvewH7UppcRp5yHde7MCxeipg5xyrmo/v2RtmYy+iz/b9M/JTAz+Op/4ZceR5XhX1Ch1PNQXdtwV/8r1tV3IWbN06Xtp0NvIol924fATuBteCnKVyFERJ9ljKFJX2xcS4WQAAoyg7gPfBF52e3I0y6cHl1CIJIpXMvy55I0Ok6cPpSeG13bUJaF178fb9ZcrEtuQXQcfkbMowFh2dDSDj27tRmklH9SQNJGzD66WooKZh4V80cFFUwDSinUro2ABxbEd9pK+ymcch7W0tPxnnsEta8zUldLiEwX/rupsQAo5vBW/z+tph/sQwz36sJoqZROcmQJqK3Xgsu21/2Kj9Lf1SmjrZKdtPkeZFpUSidV2rMFlR+HoyBUANoEZEl9ezvtCxeeobYvMQHFNBAGb/wmwraCxcfcriulIzWKOdi5AXdtAeve30fI6YdziqBWSpDULLjU1DAFa3ppFEs4rkRsLx0D5UL/frzH7kd170Je+U69uE4HYcIt854mfcF7MB88GO6DsUHcgW7EBauwzr122rw4FrCuuA23eyf07yeq9krUj9wYqnMdYuXVby2hFRwSjreCYscaleRXFUwLKp+FfZ0I5eoEQ+HL0kmIGloQdQ14T/8Q9m6BYj46x5I6WZGU/jEZJTAKEv84edizFXZuhJE+wNPJmCyhd/3pNCI7ot/9hFj65SfWMpMemYmQwnuKOD1C6Af3+Aiqe/fRYZoQCFsiEknEaRciaht0oihLRjTHXjKiL3gFfenrQqCMvqLbMtsRUjuGKgf696NGBg+f9FJ+JZM6mVVIn4joM3k81VgEkQ7ZUdSGF1AjBy9PHtEjjTEN+hrQltYJwSzjmMAXgDwY7kU98xBq/47D5sfRgGxpR5x+oZ/gy/xdiChB1Z7NJ3TK5grefqgIFRVMD13b9C442IEGMyeZhDMuQd76MeS8pdqnwrK1FiHw3A/egzDH8N34Dl+LEJagFroN14HGNl3hNJeB7W/o/ASWpUMqA3u0eT9pa7MJJfcKEjUFaRYRoFzUjjfLdHiGkEzBrLlw8llaUxGYOEKTgu+HYpobwjSQUod3plIweEALC6V8E7Ikf4TfbjGP2rPpsEhWoHmF36adgIUrdFKugM/CoKGUt+ZYYGg8grFAQSGH98QDqKFppoqub4Z0NaSr4jxIJLUZIZGcSFc4zgryGdy1/3PcZZC0LrkV5i3WPA7nqs8/v34LxfxbTWYFhwCFwjvC15H6ZLyVqAgVFRwUanwU78kHdPRBsOAjtANhXRNi1jzkvCXI+Schr7wLTr1ACxsx9TjGQ19G7ZSeE5wXHHMKsPUVaJilD7gFyAz7mSaJVMZBW1Jop89Fp+qQUV+lH56HiM5PpaC5HXGU1OIimYalZ8A5V8Oml32hTEX8ExJqGiCZNgQJ410KaGzRAlWxGPVBWnoRCvKUIybysphHvfAT1Oj0tQERlLE4S2hsRV5xp7Fw+zcpO76l7yZ9xrgW87DzTbw134qcSaeAddltiHf8BsxZ7C+6wRdSzwfXKZlTJfR5Hgx14z3748Pgx9GDkBJ5+Z3QOGvi78K2obZ+5muQVHBUEZg/jvR1oqIiVFRwUKgNz2kP/iDEUKA1Bc1tiEtuRp59pT7PdVB7NyN2b9SLf2xXTfQ+IfOhKH9uYKLwHMTZV8CsOZCq8UuCEyU9MtsUAoSHOPtKxI0fgEWn+MJFWi/EyYS+pqoalpyOvPkjiETqqPBNnnMl1hmXYZ11mV70wsXa73MqBW3ztdAQ+J3EeAA4eZ1hM6hsKQWkkjr8NhDcSnfnEj1W2THU608eOuHhOPkC2tIzdKKw7Gg0NhYTx7V0fGOvMvQ5BRjsRvXvOzhJ6RqsJadDfUOUN0MIv52c5g++z4dt6XEOtTj+PCrkYNcGlDq4EHMsIds6YNEKnY/E5J/rIA7sxOva+hZTWEEF00fFUbOCg0J5HsJzInW2lNDQBMvOxjrtkui8fZ3w5jMwOmgEXfgLQCwyQMYXycDWHgoaxqIWLB51jXrHNq8F9m33aycYO2GCttAl1p/5AeL8G5A3fABv62tayEFC5zro3QO1jcgbP4hIVR81vgnLhg4d0hg6Pyo0/+qbYO5S5OXvxPv+PxmLbnCx/0duLGowuN4p6pciWoACZ0WJ/k9o05AKNDqHQ3siBa1zkJe/E/XMjxCB6cDcTZeOq/JPiI2riJxQpX+ebWvBNJki6vQ06DI1TUppjZXrxc1HySponQNDfXqeeG7k0+oWD4sfRxuiabZOGlbMRXPBdyhWrz8J846v6JUKJofnv460jRMVFaGigoMjFl5oaZX9ymuRZ14ZO02hdKZKPL1wekE0Q7ADl74PBH4YZJAVUYDybfJB+GnMtwD/P09HlNi2NgGEYaV+256xgA0eQD39AOrMK5FnXx2qkNWK81Ebn4f5Jx9VgWICAlOFJaGmEc65Rmt48lm9Y5dS90cKox+e30dZwj/hFxLzJYqAb0HIafAZBcM9KKU4lFwEwrJQ808CTyGveCcikcQLaFcl9IV0mWGR5ljIEvqk1hy1LYS5JyGa2hCth1DfIvDfQPl9xBdcTB8eYFYHLDod9m2D3r1aOLMS2i/jOIQ86wq8zS9AdhgweYyeHxWcMFBKHbFz7YnsnFsRKio4OIb7ojDIqlpYthLr3HidAJUdgx3rIqEBIsEglrQglBKM80rON4UJYZwwNqSFiVh7xvfhDtbTO/nRQXj9Cbze3chL70Q0tiGq6xDnvgU1DgR6Ua6qg6VnYp1/PQDesw/q3XQgXGH23f9jsgJspqBQ6rsg0Kmy+/ej+vcf0sItlp4NnotYenYojInTLkatf8b3XfAMXsOUY2Fk1iRwnLUTcOZlWMsPUuCsHMJbTTFXinnth9O+GBas0JqL+hZ9SccKhDj+rL4imYbG2VoACrROAsIIJaeIsBNvMZUVVHBwHH+/rgqOK3h9e2H3Rj/iwtZOe5e+I3aOUgrvifth/TO++taMsvAf+kGER2AzlsbxmB8Fhno9WohEsEA5Bb1A2EmjjdI28XfxHmRHtEPg2m++tbbpVLVeNE67BHn5O8PDqpiLtA8m7aUCxlT8C/1KSvnnq88zh+asKewE8pSL4g6C23/pf6ni9AUmp4ONRXhMaPPUiz9BDU8z8iNGXGk/iXgXzCPlQX4c9m2GFx6CgX2QTCIvvBm5+PRDv+cxgjjzcqipi/NKKMgMaYGughMCQfKrI32dqKgIFRVMCfXqWsgM+maPOsSV9070Rt+7GYa6oTBO3NlQRA9I8zXBsbBk8ZQl10L0vSW1vTxhT3T0NNsMHAkDQaRnF+rn38Zb9xTejjdQY4efw+FwIM+8AnHxLViX3RnnX6zPcmq+hQJEabguceHNbMvJw8uPopwj8yUQy8/X0R9B6OgE+oiPhZyEPoGutjo+jOraijpUHwc7oeeiX6xsIm+C+yodMeMWYaQX3vgF6qnVx7VaWXSsgI4VWgAN+oGCYvaIx6+CY4cjDScNXicqKkJFBZNCeR6M9usHeGMr4qJbkXMWTzyxfbHebVuSCQJBuVe4+JW++39bIr5oOHlUzx69UEgBc5Zqu7wsdz+iRczcMXtFGO6G5x6AtV9HPfndY8VGAET7YuTJF5T5Qvh8Y3J+BS9L+guqbfCnpK8mDyyhd+2D+1CvPXZk9DfNhtq6g9M4gSYoO8bFcXjpYdTzhxbiKc+4HJadCw0tPg9K+CbK0KM8KI6jDmxDbX7xiPhwNCGEQF75Lu0ELY2+gU4vX0EFJwAqQkUFk2PD04iaesScxcjrPog844ry5/XuRuAhUH5mQIzMhyVZI0XJ9+FL+sclQliIuiZEMoUQCjHai3jmewjX1Rve/Vu1g1/smtL2ML7376u8qCT4SN+08iMcbURuJCLKIDqBX37m0oZWRMscnVVU6poYwrZL+FeSyVIona10tH8GaFXl7yGJvwtzfK3y9CkPMkOwZz1qqHv6NLQvxrrxI4i2Ds2rUjomow8QowOw4anjLqTUhKiuR1x8ZzTGUiKUg9izHpWrCBYnAhQzkKfire7EEaAiVFQwOeavQLTOQ9z4cUT7kklPU8WCLlkeOA76b6G6O5nUEQ+WXeJUp0quCVZYz9+lWfocp6gFgVRK1/4Y7oWTztG5J6SlQ/FqmyKVf2DzjzkvGnQpD8YGUK/8ZCa5dZgIaPPV95ZvYvC/isxC6IgGgc4sKgW0ztXHgqRUsb6a5gYX9m/D69555LTGHEmZeC/zWCIFrfN0NszAwdakTymdsts9tLBXtXsD9HdFYaql4zuBLv9deTA+fIQ8OAaYt1zPaSCMnsqOHtfCUAUR3u7mjxmP/hgaGuIrX/kKAJ/5zGfC46tXrwZgYGCAJUuWsGrVqimPV/DWQzS2wXk3H/xEzyFKr02UPyKIGJGWTkgUOCROuFFwDZGIPj5MtAj5Ddc0gLRhaL+OmDj1Ep1zYsGpUNcCT39POwEG2RWDtsFYdP17ODnY/greojORszoOn0kzBcuCumb96toabVkCPqKga5MuAS98JmVH4cxr4MAO2P1mlM458CUJBTW0puKXP4UbP3EERCpNZ7pBO0I6eYO+MuMqJZxysR6bV34Cg936Gim0J1roC3OIVBSykB+LzGhB+CXGvJMWpGu143Ax738ny8+/4wwikUS1L4Hx1/3fFhAUZKvguMdMaBqOY9efg2LGNRVr166lvz+uau3s7GTNmjXcfffdfPzjH+fzn//8lMcrOHGglII3f66TS0lK/Bz8l1vQQsJkfgPB4mDa3/GM48Zr0Rn6u+0vw5Jz4NZPwplX6+MLTtHaDCl06Ga6yrDrB23J6J6jffDqI28N4wJI9EJd24C4/qPQMnei02FAr+On+Q4+ZwY1/XVNsPgM35ES42W0gQeHlbLbQDKls39efIfO6lnWh8G4p1uAVx7WNM5dpp1rEylo7dB+OLMXw+KzEHUth0SGaF+q+xz4l9Q1aW1Y6Vzx8oCraUpV6RTfKy46LkNKTQghEBfdobVyUhJWn/3lmreatAoqOChmXFNx9913MzAwwNDQUHhs7dq1NDY2hp8bGxtZu3YtnZ2dZY9XtBUnENb/Anp3E6bw9iM5tQNiQod/jo9oDUKo9sYwRRhJfswdrGe0JYWfLAtYchase0x79P/s33Q0gOtoDYZT0LtSCSjHPy5KNCcGfUpp34pDTA41o5BCpww/42pEawdq20vGzt3YxZv0hfxTOuJm8zP+QTda5L2SsRDA+CBq41OIUy4/PFqXX4iwbVTL3EiDFGh+zHENU5J4ejEcOqDHy/NzmOSGoL4NrvkwsrbpkMkQtY2otoUw3KO1V2dfDy89GGlOAiYVC5FgWlOPeMen37pxPkSI+lbUrPkw2uvz1NWOxhUc95gJ80XF/HEQbN++nZaWaDfS3NzM0NDQpMfLIZ/Pk89H1fpGRkaOGr0VTB9qcL+vohXxnasQWmuw7Hx48xeRrwNEC2KgrjZV9WHkQElbQkFmQOceaJoN3Z2+ajsXJygwDTh53a60QCT0rg+h1faZ4YiGsT7UQ/8Il70H0dR+1PlVCrHgdFRVHeJUY6EPBCFl8si8yPzs72KDvgb8SiShvhWQkQCVqoK61sOmVZ5+pf4jP45qbNO8LDWzxOhTkS+D62r6PFf7hBR2wU//BXX2jYiTzj9kWsTCM1Bj/bD0PJ3/w4z+CHTHJl3ZYdRD/wAX3YWYtfCweXBMseAM6Nqoa5ZIYKgbtfN1xKKz3mrKKpgCnpoBoeIEtn+8ZRk1BwbKq2InO/65z32OP//zPz+aJFVwODB9FUJHPqmzGCbT2jSSHy+xmwvjvdQeL4w2RdRmkG9iuBfmrYCRPr1Y5TLEM+WLknf0tYUsNLTDWdfBxichn/NvrXSW0LeoEqRYeCZi4ZmaypFe7TehPOL9n6AC0G8yoUNlMQ6LON/EuTchFp8zszSnqlFzlkHfnqhabIw+kyDj3aTPc2G4D7XuMZizDFHTeGg0LD4bsfhsALz9flKz2LwJ1TSaLteBvj2oVx6GG37zhNBYiGXnoXa9Brs3aM1bYRw10nOoLigVVHBMcUhCxRe+8IUJ/hIALS0tMafMUixdujSmgQicMoFJj5fivvvu49Of/nT4eWRkhI6O48DB7m0MNdClNQbCqPsgAQQ0tkHbYtjkq+aFjDsexh7qxq7cFDKCjzI4rIUXMXsxat8mndiomNcLq9lmYOZQfiOeozNrei60LUYexs74WEBlxyA34mtbRNTnUr6Fjog1fq0I3zNMGQKeV4TRXtQba6B9KaKqfmaJLXWMLPcO8bFQJeMqlK5N8vrPEJfce/ik1LWgZi+B/Vu1H0dMthERDZ4DPTtQm59FrLj0sO93rCCEhPNuQw33aNPHCSAIVQDK/3ekbZyoOCShYirBYSqsWrWKz372s+Hnzs5OVq1aRWdnZ9nj5ZBKpUiljk6J6goOE6P9iNxotAO1JCSq9GI3ZxksuxA6X9YLnBCGbwMli495DGIRJFaws43U22LeCu1XMbgXXbzMuG5CW8Z93Tw8+q+oxna49NcQVXVvDd8mgahpgJomrVUBg1+l7xiOrf6OPPRJwTAbKe3P8OgXUWffHGpEZoRWAaTTegxL6cVP3OR5Bx9X5cCuN1DzViAWHp5aX9Q2I67/DdQP/1pHBnmT8U2BV4CNv0C1LUI0z5sRXhxNiKY5cMY18OIPtFC0+03UissQyaq3mrQKJoHiyKuMnrgixVEwf6xdu5Y1a9YwNDTEkiVLuPvuu1myZAn33nsvq1evZmBggPvuuw9g0uMVHP9QSkHnS3pRCLz+lYKWeYibPqXPeemHWqCQZRbFcCcr4lqFQECJLQjEo0M0AdpMYFn+LthjgqASa0vqh3JmUJtRchkdIXI8QcooU6ZgisURw+cEYoJUMBZhlUtHO/v17YIZFCpo6dDtDeyFgS59LKAvqMtSyBJWo7UlVDVoTYznGWGgaOHnMEu0xxDk+gjyn8T4Jv05AuRGYaQbTgChAoDlF8OeN+HAFhjeBxt/AWfd9FZTVUEFZTHjQsWqVavKahvuvvvusudPdryC4xx++udQUyAFJKqhdUF0Tk+n9lqfIFQYgkToqBkcK10UzYXUCAW00AtwfRuM9PgmEBFpK4KtcRAJEe6S0RqL57+NOusmxNxTjgm7poXMEGQH9SJrOqkqk35fYLJsnaq8MBoJUpJIEDGvRUHPVlRuDJGunRFSxaKzUc3z4Kf/GNEbLN52IorECIRA24bTr4LNz2pTlLT0C6DjdMTilUdEj9q7HnLDkQBq8ktJza9UrfataGiDmuYjut+xhBACtfJmeKpfC4g9299qkiqYApXojwoqOBzsfgMKGf3wthNQNwvOvAGx8GwA1IEtkB3y/SGCHWnwTvyz6Xrmr5llBZFEEprmoHp3wFifPq9lnk6ElBsxBArjvWxbjlaTH9gKx5NQAQa9ls6u6RYif5Oga9KGpnbtbBpoYxCQSGs/E+WVCHAKxvq1lmaGhIqQ2FBwMOhzi5EwiXHszbV6UbdtSNVpc1l9O5xz6xFRobIj8MZPdRRMMN8CQRQIo2Euuhsx//itUjoVRPN81CmXw+s/iYSxCo5LKDUDPhUncPTH8Z0FpoLjF13r9UJhJ6G5A1b9ViRQFLL64ZcfK3NhIDUwxXsJZAJSNTBnBSw8B157WO92lafLWqdr0KGTEqx0yT3K3R997Z43UBt/fkjdPqpIpiFdBwiwU7DiSh1FE4PQ/Giap3lgpjpvXQTty7VwUdp/z4E9r88svUEWVZM28CNSTIdbX1tSGNcLfz4Dw/u1pmvvOnjiq6gj2X2P9GiBybRkx57JSicOe/kHqNff4mRnRwCx/DJoPxmcAqpv11tNTgUVlEVFqKjg8NAwW9fzWHoBXPfJuNPjWL/OKSEgLNVtvuy0TowVy8BovAe2cSn1eR1nwB3/By59H2x5Ri9GwQ49O6B9I5rnQdtJcPIlkU2/tC3zJdBZPne++tbwrwxEQzvMXaEFqLnLYcm5fgXTkld1nc4Gihfv4+gBaJgFp16jhZHwGj8/xIEtM0uwwjdjlMmiWm48YeJ3XhH6d8Prj6BKc44cCqTUGpxUrR7/Ur4htOZs23OofRtmoPNvEU65EprmVhJhHceo1P6ooILDwWnXwkkXQ7IKMUEdq4jSSQdq6GDXasG8U6B/h7/TNmH4QgRIVsPp1+l2XvsR7HodVDFSuXtFvZguuVifP9ar64w47sS2QvOLiO5VGEP170K0HCcJkWqboeM0OOVq/TlYgIN+WElonAN92wlDecO+ZGDnyzofhyX8SBBfgzMhjHcGYNlQVa81ENLPDR5qKUyUGVdzLISCkQOw+Qk4/YbDo0WgNVaXfxhefUCbt5RXMv+U9qfZ8wbMPfXw7vMWQ7QuRDW0IxKVSLjjFRWfigoqOAwIISe3zx/YrHfGQahnkCHSTmt7en0rDO4ybO6li47vwW8ldDEqOwHbnoZdr0LRD180w0iLedj2jD7mejpsMGg78Pova2pRur3Xfoy64mOIxFuTACuG5ZdBYRyRqkWN9kQ+FgrfCdKCoS6/MFeYwENfK9A+GEN7I/5LW2stPFdXcp1BiJom1KJzYNcrkPTnQm+nITuUjOukY4EWRna8hJp3GqJp/qERYiejTKHFcW1eCTRZ4fwD7Co9/2pmlg/HGhWB4vhGoGs40jZOVFSEigpmHvs3RLkpQGsnUlWw4CxYfKFWUe96hYmJsMydtISGOXDBu2D7s7D7l/HaDsL/T/h5Gtw8OEYT5q483M0b9wgjKhSMD8FgF7QtnWFGHDqEkJo/EAkSZp+dgp+CHGPNNvomVDysVnk6hHPuCjjjlpkneMVVetefroMXvk0UxRPrVMnfAh1mmvI1G77wY1nQsw0OUagQLQtQF71XCw/bnvUFTxEfcmHBnOVw6nXaqbiCCio4KqgIFRXMKNRIjy4gZiY8qm2B5ZfDonN17oJ1P9GLo/ngB8LVKFiEEkld92DvG346buLXSD/ZVmFcL0rBAiVK2jITMAWCiJ3wj3lahX88etSbO/4gy2ZYM8WMCDH7Kkr6rMDNaX+Kxnmw/IqZJVFIbW4BVJgiHIPeUvp8upLVcNbtsPd1/XnZ5XpcDlVLEdzBr3Qaet2HQqd/ggRGe2BwL6JxzmHdo4IKpoOK+aOCCmYSO1/SWgMh9O4wWa01AEsu1PH2e56Fnq2+iSKw9WMsgv4OVghI10faBAlGvm59r6CktXK1cJEf1X+b4ZRS+tUxZbTQWQlobIeOc7WTZ7IKjhefilIEjpb4/FS+MDYhNbbvkOh5kfYm7DM6+mHH86i5pyFqD63U+LQhZGSSmZQ+fyykrRNozVoMQiCqGmaOjsC/o9Q0ND4E259BLTqX4738eQUnLt7uQkXll1XBjEF5rg4VFJ524qtvhWWXwpm3EBZwUkrniQizP4q4l74ldUKrc+6AM27UmoSyUSK+xqFxHtQ2QnUNpKpLIhHM6A8R+SfgaIfOno3QfjKidTHHbYGpIMtmQ5t+BZVIy72C/pU7JtC+Bm/8SI/T0aJ1MtrCDKD+OZY2g4jqxpkVKBJVWgtVOldAz8viuB77Ciqo4KigIlRUMHMY2K0zPMqEVomfdgOcfFXcsUzg71SDxQbjHe1I19CGWHAOoroJRrvRu24iQcRMR51I6BwMuUyUEjxss9wLwK8BMXwAdr9yzNk0fQgtZFXXw6LzQXqE9T7K8s8U0EqENgFhyu6dLx4lcsU06DPG8GjgpEu1T0qpIBn8XczCuodQbvFgLVVQwWHBm6F/JyoqQkUFM4u6WdCyAM65EzH3tPIaAIFh8w52kb7mIVULiy4AQOUzsON57X8ROAASJFyS0WcUFDO+at2OnAEDQSRmXxeRSaWYga51R48XRwqltCamYY4Ooy2MR9/F+Oe/h33FePdtSwGvCmOw7yj1OaApdKCdjD6hNVBHQWMgklV+Gfug3wI9V0R0zC1C9+YZv3cFFQAooVDCO8LXiWv+qPhUVDBzaF6gEwy1LUekasqfY2obwtoUvmybqIZZJyFaFunPO57Rpb2DH1hp+XQpfT8KPx9Bskr7YWT69PeeE1/UwsJSyvc3AHIjqGIWkTgOqz7WzYL5Z0HzQtjzik5xbfIt1icMXwrzuO/DoHwfi6PpkGqntOkhUaV9JvJjvn+NmSfDp9vLw9ZfaOfOtuUza34KtBQq2DMFTq1Sz7H2U2D2yTN3vwoqqCBERaioYMYgpAUd50x9Un7UsPP7D/5gEaxtgtNuBvzc95k+wI0WiFhUg9ALZG4InKxeSGwbTrsJDmzQu9HerVrd7ZkLLVFbAE4GNv4Edcadx51fhRAC5unKoirQsMgSIcLkR9mibTLis/TzOSy78ugQvPRSSNboqJ3erZAfjvxalDSEGwF4MNYNW9ZCdRPUtc0cHYG5QxnaCdD3Tdiw4FyElZi5+1VQgQE1A46aR1o75K1ERaio4JhB5Ud10itVNBYbQFh6d7viOq2+Bn1epr+86QIip85ClrAGhZOFPS/D/HP0jhm0M6bjRgsbUjvsBYuNV9DlpId2Q9NxGgECkUARVmK1te9KEGlTTogw+xoU1TrpSsRR2qWLpg5o6kA5eTiwzjA/mcKOIUQqTwuZ+bGZFSqCFPBBIbtYcrA87H4Bll07c/eroAIDHh7iCH0iTmSfiopQUcGxg8JPTGSqwiVUN0LH+dBqJJ/yPH2uaQsHogVCavOGqVbHg75t0LcV0o06SZRyo4UN384fvvttFjKTFD87jhD4IwT9SKShulkLRMJQ75t+BGZfBVqY63wSZSUQbcuPHq3K0AyAH+Jp63fHi9PnFqHzaVTzwjLp3g8Tc06FTG+UfdWEtGHWUex7BRW8zVFx1Kzg2MH160KETntSO9WdegtiyaVx84O5ySx9Sam1G0GNEdNB0StqYWN8QEeimBk7g+uthI4aCepiuEXY+9rR7/8RwRDCEimoa9eOm0IROSJiCGvEX/g+JmN9sOuFY0CuT5OwtJ/L7BVas1JKn3JhZD9sXXtkBcVMLDgf6mbre8f4IHXelIZ5M3OfCioog5kpJ1bRVFRQwcGx61mtfoZIsEhUQcviMicbgoKZnTPMZ+Tvhs3MkTGhROmCWlIY7/45MqGdSoOwQgG0HeeOewKdCttK6XDdmlbY9gRhQS5PGH3FLyYmDP4Q8S0/jFLq6PmQ2CmdGbN3u17IV9yox2egU38f0BeMiZeDrl/CWC/qtNuNhGgC0rWHnKhKSBvVOB+Gu7SJxUzuqbzIabWCCo4CPOEhxPFl/hgaGuIrX/kKAJ/5zGfC46tXrwZgYGCAJUuWsGrVqimPTwcVoaKCY4fa2TqREy4g9SI59yxf61CCQEMe870whAfll/02FyDTShIkPAoycQalt4UAipDpgfnnwsKLZ07tfjQx+1RAQcf5iGQNas/LkWAm/Y6X62vo0OlFQpeTgd3Pw8KLjwqpQgjU8utBPKZNNG0roHcTUfIrgz7pv7sF7dfy/Jd1X4J+zF2JWnwZwjrER1Uwb0ortLpZ2PkcLLl8BntcQQURjkefirVr19Lf309LS5RNt7OzkzVr1vDlL38ZgOuuu45Vq1ZNeny6qAgVFRw7jPcCSpfvrmmFpVchWpeVPzcIGQ2jHfxFUSS0ySQ/DnhlhA1fqjCrlEovWnyDtopjsOc5HYFwxl3HoPNHBlE7C2qvig60LNE1S3IDaIFClO+rsKC6RUfKBEJGYD45mvRWNcKZEV8VIp74Kjau/jsuOE40jlLCvpdhrAt11nsOTWMRZtIsEUjxIDsws52toILjHHfffTcDAwMMDQ2Fx9auXUtjY2P4ubGxkbVr19LZ2Vn2+HQFi4pQUcGxQ3ZQaxNqWuHMdyHSU6Rn7npR+wCYIYkIHdVhJ/1EUCLagZa+Q5mwVfMdbf7I9h+dvh5liOpmVH07FIYAZSycJX0VaM1EdQucchuiquktIjgQesqNhTG+wtA8gZ4DiRoi+8U00bJMR6AUxgzHUannzqzj3NRVwQmNmdRUjIyMxI6nUilSqVS5Sw4Z27dvj2kumpubGRoamvT4dFExLFZwTKB6N+kFPJGGxVdMLVCAFkDCHXiwy/UdK/Oj5VNx20m9AMXSQcuSd2O3LBTkR1H7XzsGHDgKaF2mnU7FFH3F06G2I/vg1a+jfvlN1PhbIEjVzoaqhsnHwkzlLYzxQ8HQTth7aKnFRWMHzD0nCi8NXslqaK1Ef1Rw9DCTjpodHR00NDSEr8997nNHlfaBgfJavMmOl0NFU1HBsUGiWu+Wa9sQ09kpNnRAfsRPXIWvtq/SQknWd/aMJTaS2qwibe2ygS+AYDjqxUwl/mevAF0voRo6ENVHqXrn0ULbKbDzCcg7gNGnsn11dYjl2H7Y+SSceucxJVVUNaIa5sJ4nx4nK6VNUJ5jDGNpB0ALReOw+1nU8G449Z3T94GZfTrse1VHBIWEzGCnKqjgKGPPnj3U19eHn8tpKb7whS/Q3z9xo9DS0hJzyizF0qVLYxqIwCkTmPT4dFARKio4JhCNC+Ds907/AuWbPsw8C1UNURbN0L4uonevAG4uCjm1U2CndU0Q5eh8FLG6FP4CVhjT351oQoW0oLZNV94MSp0Hi3PYx5K+Kg+GdqJ63kS0nX5s6W1cqH1YZq2A+vmw/vs6b4VJX2k+kgBuXjvXKg+YplCx/9Uo0VrQppODA69rLUYFFRwFeLgIjqwSsOdfX19fHxMqymEqwWEqrFq1is9+9rPh587OztBRs9zx6aIiVFRwfCLjO3UGuQ7sKmhcAKP7/KgPIytmCF+rEaa0tuDsDyASVaieDbD9Z9qPIuYcKAAXet7Q7Z9AEEKiZp8OI11aoDITigWOrbHoD//dK8LeF1F1846pj4VoOw3aTgNA5Ya1o+lYkBE0GAuYOK7+MScHG76HWnQlom4auSbG9hNLtBbOp4rVt4KjB+Un6j7SNmYSa9euZc2aNQwNDbFkyRLuvvtulixZwr333svq1asZGBjgvvvuA5j0+HRRESoqOD5R2wbFUb0AJtKwZBWidQXqjW+VFIuaRJ8tfM3Fm99GKY8wEZKd1Or32LlBMq0TFFIQmnsmOGwG5iNDcyFt7Vugjmw3dSQQ6QbU/Itg97N6jIs5wImcKsuOqwtjB2D3M6hT7jq4GaR2Doz3ED3fJSRrYfYZM9aPCio4EbBq1aqy2oa777677PmTHZ8OKkJFBccn5pwDo7vBFdByMqJ1hT4eZMEU5TQVpXC1qQTjXCutF9SWkxHzj06ehmOKWK4KEe3KQ41NifkDAVWNiNPf/RYSrSFmnQqzTgVAda6Bwe3ah8bN+pqLclCQ69fmrIOZQeadBwObtU9GIKRUlBQVHGUcj8mvjiUqQkUFxycS1VDVAgjouMT4wk/NXVosyoSQIGzfJABRMSu/gNh4PxReQeUGYeHVx2fZ8+kiWad5VRiJq/VLM2kqg0/FLGqoE9E4feerow2x5DrgOm0WefNb5et2BHDysPUhVMfliJopCpEFTqphvZhA6KqggqMH7VNxZNKrd4Q+GW8lKnJ7BcclRHUrnPYeOO3diGSt8YW/+46Fhpa87GqYc24UbmnWGglyN6gCDG2HAy+/ZX2cCYiGDmiYr/ta1awjZCbwpIRfqgB7n0UVM281+RNh2VqYtKu1o23pGEsAF0b3wt6nUd4UD9/BrYQF5YJQ1lR9RbCooIKjiIpQUcFxCyHExPoUZg6DIOOmZR6ztAPg3PMgVWssKJTkrxB+Matdb0nfZhTVLdB8Evz/27u/5jau847j37MgAFIUSYiQJUoWY5lI7NiN24ZW3SROkyai3gEl9QV0pHtfSMMr2Vce6R1QfgUa4rIXnQGnF+1M2ykru4kdp3FKprZqWpZNEPwn/gP29OLs4g9JyZS4BLjA7+PBQFiD4NkjCHj2nOc857XLtaBiZw2P+v4yuKJZXz1b7YdmMMleeG0cfvz3cP5XkDzutriv/3szwVTW2lew8Psnv9hG0Y1qheeeSMHQ6OHteSICEEmNCk1/iDSHl9i95wfUZkG8lJunX3voEgA9j121D6pfKga217Bf/BO8+DYmEU2luqY78xb425hEChtWrdx5rvX3YUC18qAlzf0uxutylzsv/Ai79ghKn0GlHORR1LFl+OrfsZuL8OLPMDuTbYf+ClY+d1MpBrfvjKfrKDlcvg32Njrwa8ST/oVJvFTjgfovSeqGxxNudcPiZ65GQf3xXdMCgL8JpblgX5J4MsZgwhUt9X3xpFu4YVeyt4Wt3qfv/QJ++HfQ92LdJmF1uRHldfd3vddUTiJMUg0SVJO9u1f+iESs07c+V1AhMWN2BBL197jh7vJ2bfOy8P939bib8eqei3tO9dYGntgv9TfjltaebHLxq+dgvC5Md8btduqlwCQbzwvrRqRW/m/3D9vgSQb3996TxfQNN7P5Ih1H0x8SL2HSYbUug99Ydtt4sDwH5VUgmEu3uKHvntOu9PfWcm3HyobiSG3AhNND4TTHE654DFD6A7Yni+k52dQmPpczP4H+HBQ/gaXP3SiU77sRKFuBbz7C9g1jUn21nzHGLR/e2HTviziv8pHYsFSwB7xet1r9IdIkiWAqI9kNx88G+0iESYieG43YXg7KfNetGPA3YP2R+7m+M9B3FvqG3WqAVButCEh2B/3T60Yjwn5puBmgDI+/gvl/wdbvjXFEmUQa038Ozv0tnPoL6B50O9Z6wchT+THM/zPW1o04pfpdIJFIulUlXQoq5PD5Ef0XVwoqJF6SPe7LMt3nbom6L8pEwh0zNtjxsm6rbSzYTdj8Fta/diMZyRRkfwRn/hp6z7b6zKIx+Br0n4fe08GSWhqDiYY+8d226CtftLjR+2e6umHoLTjzU8j+OXRnguTLCmx8C0t/rD15a7k2JZbqgRf+sjWNFukgmv6QeBn6iVu10NUDW0tUt9HGc9Uy8es2kQoSEq2tTZWE+ROVx7C2AZUtzKnRVp5RtAZfd6WoLTD/TS2ACPsAqE312KBUd7zySYzxYOBlbP9LsPQCfPOhC478bfj2I6ytQOaHmPQANt0Pm4uQSLuAROSQHcW9P5pJQYXEikmfgPQJAOyj+3X5EMblE5QfuyvT6u6miVpeQcMUR8V90ZYfY8sbbfOFY4yBvpewa/Nuashfp5qs2PjM4N66K/oYMsaDzCvYZB+sfQnLs241yMJvwEvCwPch2a9lpNJU1lawB8zRslpSKtIC1VUAntviPHnMjVJUM/7DZMwguKjuUGlqq0D8dXj0r41z8e3g2BCkM8GKiQTVcyYY1YEgyCrD2hdu07WYMr1nMKcuwNDfuIDTVmDpv7GVrbq8mjbJmRE54jRSIfHlEXwxdkGqH2vLQKW2uVa1AFQ4NYKrS2HDYli4528WMesP4diZJp/A4THGww79HIofY9cfuikA/LrRmrov2fJjqGxiYp7IaI6fxaYvwjf/6UanSp8CBhsEnworpBn8CCpiKlFTpCU8bDoDvWewp34KfrjiI0xGrFvxkEhAzwtuRCNcdhmOdFQ2iVtewX6YVB9m6GfQe64xQbNhLw3j9gL5dqYtRmtM8jic+QUcOw19LwcBRbDBnEgTuCWlB7/Flf6lSXz1/wDjJWDgVQzGhQVhcaedl6b+lttHIn3CrRLYKrpRi6CWRf3YRdsxtjZCsefSWR82F2Dtczh+vpktOxTGeHDiz4AgVEz2wPFzLW2TSKdQUCGxZZK9cOINAPxw/tyGqz3Mju2/LWw8gqFfYbKj2IX7sFlykUSqH9P9QgvP5JDVFwzbczQiWF7afbrJDWsCAyTScKxNlgzLkWftwctsxznHSUGFtI9dQcWOe38VFj/CnnwLc/LC7g2o2pTpG8Fur8DWYlBpdEdgEUwD2cdfQt+Iu9JvF9UN1tp2HEqOmE7PqYg8qCiVSty9exeAGzduVI9fvnyZiYkJAO7du8ft27cByOfzABSLRUZGRhgbG4u6SdIJwsChuudFOEIR1qcwbrRicx7m/wHbPYQ59csWN7o5TDqLOfNr/MWPoPQ7quXJ69nHsHQfW1nBnPhxK5p5KMzx8+49kM62uinSITp9SWnkQcX09DQLCwtks43/iOfm5rh48SIXLlxgamqqeqxQKDA5OQnApUuXFFTI81n+HbBVV5MgTEb0gi2zw9UgFtiGza/xV/6A1/dqq1rcdObYMHZ11pUsD5fa1meTWB+SmZa17zCY1AlInWh1M0Q6RuTjnOPj4+RyuV3HJyYmWFxcpFAokMlkABeAhH8GyGQyTE9PR90k6QTlpaA8d7CiIZF2t+oxavcGYBtWP8Nux7Pw0/Mw6ZOQeQO6eoMt4sOy3UGfGaC80upmisRaWFHzYLf4rsRqWk7FzMwM4KY5AK5du8bs7GzDiMbg4CClUmnPn9/c3GRzc7P6eHm5c74M5Ons+rzLF6heeSfAJINqkiGPxqtzoLKKXf4tJvvzJre4dby+V/H9LVj+mNooRfgBZmH9T9juU5juodY1UiTGXKLmQac/lFPxncIcCoBcLseVK1f2fF4YdOz0/vvv89577x1K2yTebHkVKLtaBIleYBsq63XlunH3Jo0rzx1OhwDbnXdlbrpPYVePgV2nYfoDwN/GlleV1igiz+WZgoo7d+6wsLCw63g2m21Iytwpn88zMzNTDSwymQxzc3PkcrmGkYkwWXMvExMTvPPOO9XHy8vLDA8PP0vzpU2Z9CC2+yQkjkHXCVj9uK6qZliWugt6c7D5NZRLtR/uwPLNJn0a2/8KrP0xyK+AWvVRC5sPsL0vd8zqGJFoVSKYvOiQRM2nBQ5PMzIy0pA7USqVGB0dJZPJcPPmzerxubm5JyZqptNp0un0c/1+aW8mdRJz8tfY7SJ28d/A+Dt25Az+iW89gFQW8MFfc8c7dLMpr+91bCqLLf1HMGJRF1xVFrGP/wfT2zlJrCJRseFqswO/RjwdyuqPQqFAqVRiZGSE8fFxRkdHyefz1RGLQqEAuGDj6tWr5PN5isVidcmpyLOy1seufQI83jH6UPdnuwFbjyCZBbrd9uepzl1qaNKnsb05WJ91fVNVga1vQUGFiDwjY2Na8H95eZmBgQGWlpbo7+9vdXOkxXx/Gxb+cceXIzQumwzuTQJ6vo93/I2mt/Mo8tdnYeW/qBXsMZA6g5d5u4WtEolOM74vwt8xcOz1A08dWlth6fGnsfx+U0VNaRMG63muombweFcwUX+/+QU2PYRJtnF57n0yiWP4iQGwK1RXyPhr2PISpmug1c0TiRUfH3PQ6Y8YV9TszAllaTvGAIk+IO1uJkVQnGKPmwHK+Ou/x/rbLWrx0WFSZyDzS0icoNo/dgN//dNYz+2KSPNppELagjFdeANv41cqsPEb2H4Y7ANC4+Zi9SMW/mOsv4rxVHExkUji976CXfst2KAeTGUZ629jEkqQFtkvJWqKtAljEq4qdyUojOZ5tbpOBnY8AHzs9iO3DFXwUmepbC/C9v+6kt3Gx5YfQUJLt0X2K4p9O7T3h8hRUVkAtmsTew0XDOGDuqkQv/OKXz2N6XkVW1kAu4RbBTKLTWYx3rFWN00kFlyJ7QNufa4y3SJHg93+Elc4xntCjqYHySFIvQxYPK+3dY09gjyvi0r6Zdj6E9hVYBN/81O87jcxpvMKhYnIs1FQIe2nWtCqbjv0ajVqD0wZL9GPMcpT3ouXOofvHYetT9yW6HYV629gEj2tbprIkRdFPoRyKkSOCq8bbILaNudBRGHCe4BV/PI8ieS5Fjb06DLGkEieoMJ52P7cVShlGVBQIfJdOj2o0KWatBWTOg9esrad986bAShD5WGLW3r0eV3nMKlXwKSxla9b3RwRiQGNVEhbMSaNNV3ANrXEzJ33O/8sezHGYLpOUfHn0fWHyP5EUbgqzsWvFFRI+zEmqKxZn6WZwCVwJoAkdJ1tYQPjxet6CX1UiOxPp09/6JNC2o/XVRdUJIFjYPrcYwsm0YvxhlrbxhhRcTAR2S8FFdJWjPHAOwE2KL9tTuN55zEm1dqGiUhH0EiFSJsxZgBr1oA0nvmB6iuISBNFERAoqBA5MozJAlsYTiugEBFpIgUV0naMSWL4XqubISIdSNMfIiIiEgktKRUREZFIWBvBhmI2vhuKqaKNiIiIREIjFSIiIpGpcPCKvfEdqVBQISIiEhGXZHmwoCLO0x8KKkRERNpYqVTi7t27ANy4caN6/PLly0xMTABw7949bt++DUA+nwegWCwyMjLC2NjYvn+XggoREZHIHHykIurpj+npaRYWFshmsw3H5+bmuHjxIhcuXGBqaqp6rFAoMDk5CcClS5eeKahQoqaIiEhUrB/NLULj4+PkcrldxycmJlhcXKRQKJDJZAAXgIR/BshkMkxPT+/7d2mkQkRE5AhaXl5ueJxOp0mn05G9/szMDOCmOQCuXbvG7Oxsw4jG4OAgpVJp36+poEJERCQiNoKpi/A1hoeHG47funWLd99998CvHwpzKAByuRxXrlzZ83lh0LEfCipEREQiE11OxYMHD+jv768e3WuU4s6dOywsLOw6ns1mG5Iyd8rn88zMzFQDi0wmw9zcHLlcrmFkIkzW3C8FFSIiIkdQf39/Q1Cxl6cFDk8zMjLSkDtRKpUYHR0lk8lw8+bN6vG5uTmt/hAREWkNG8HijehXfxQKBUqlEiMjI4yPjzM6Oko+n6+OWBQKBcAFG1evXiWfz1MsFqtLTvfL2JhW2VhaWiKTyewaHhIREam3vLzM8PAwpVKJgYGBQ/sd7rUTEb1ihaWlpdh9v8V2pGJlZQXYncgiIiKyl5WVlUMLKlKpFENDQzx8+DCS1xsaGiKVSkXyWs0U25EK3/eZn5+nr68PYw6aFBNfYQSuERtH/dFI/dFI/VHTSX1hrWVlZYWzZ8/ieYdXnmljY4Otra1IXiuVStHd3R3JazVTbEcqPM/j3LlzrW7GkbGfhJ5Oov5opP5opP6o6ZS+OKwRinrd3d2xDASipIqaIiIiEgkFFSIiIhIJBRUxl06nuXXrVqSlW+NM/dFI/dFI/VGjvpDDENtETRERETlaNFIhIiIikVBQISIiIpFQUCEiIiKRiG2dik4X1mW/f/8+ly9frm74ks/ngdrOct91vB2USiXu3r0LNG6u04l9Ua9TzrOe3guN9DkhTWcldu7fv2+npqastdYuLi7aTCZjrbV2dnbWXrt2rfq8sbGxpx5vF1NTU/bGjRv29u3b1WOd2hehTjnPnfReqNHnhLSCpj9iqFgsVneUy2QyDA4O8uGHHzI9Pd2wlW0mk2F6evqJx9vF+Pg4uVyu4Vin9kWoU85zJ70XavQ5Ia2goCKGxsbGmJycrD4uFouMjo4yOztLNputHh8cHKRUKj3xeDvr9L7olPPcj059L+hzQlpBQUXMXb9+nQ8++OCJ/79YLD7T8XbW6X3RKee5H532XtDnhDSLEjWPoDt37rCwsLDreDab3ZV8dunSJcbHxwHI5XINVxZhshXwxONH3X77Yqd27Itn8bTz7zSd/l7ohM8JOUJandQhz6dQKNhCoWCtdQlZs7OzdnZ21o6Pj1efMzo6aq21TzzeTiYnJ3cl53VqX1jbOee5F70XavQ5Ic2mMt0xNDc3x5tvvll9XCqVCP8a65eEDQ4OVq9OnnS8HUxPTzM5OUmpVOL69evfec7t3Bf1OuU86+m9UKPPCWkFBRUiIiISCSVqioiISCQUVIiIiEgkFFSIiIhIJBRUiIiISCQUVIiIiEgkFFSIiIhIJBRUiIiISCQUVIiIiEgkFFSIiIhIJBRUiIiISCQUVIiIiEgk/h+WzjotTFhK9AAAAABJRU5ErkJggg==", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.scatter(leaf.cells[0][:,0],leaf.cells[0][:,1], \n", - " s=0.1, c=heights, cmap='magma', label='T = {}'.format(32))\n", - "plt.colorbar()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d438bea4", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "177.0\n", - "279.0\n" - ] - } - ], - "source": [ - "# Figuring out centering \n", - "size = np.shape(F)\n", - "print(np.floor(size[0]/2))\n", - "print(np.floor(size[1]/2))\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c184035d", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.matshow(makeFernPic(F,theta), origin = 'lower', cmap = cmap_viridis, vmin = -150, vmax = 150)\n", - "ax = plt.gca()\n", - "midx = 279\n", - "ax.set_xticks(midx+100*np.arange(-2,3))\n", - "ax.set_xticklabels(np.arange(-2,3)*100)\n", - "\n", - "midy = 177\n", - "ax.set_yticks(midy+100*np.arange(-2,3))\n", - "ax.set_yticklabels(np.arange(-2,3)*100)\n", - "\n", - "plt.colorbar()\n", - "\n", - "# plt.savefig('figures/Fern' + str(int(theta*1000)) + '.png', bbox_inches = 'tight')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ec2ad8d5", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.7853981633974483\n", - "[1.8 4.8]\n", - "1.8\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2.356194490192345\n", - "[1.8 4.8]\n", - "1.8\n", - "4.71238898038469\n", - "[1.8 4.8]\n", - "1.8\n", - "5.497787143782138\n", - "[1.8 4.8]\n", - "1.8\n" - ] - }, - { - "data": { - "image/png": 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", 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", 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NMdHjsztWHKcoNl6frM1LWvYc3+qmUmYbSnnNZ184Rgr+F7zPvnCM9OnJnaQdH9OfdD9bsB1sC0OfaNovbRPL4dhwXfZvhLQcaxfXaXu0TVbeamHnCcdvvHjMjo0dcyuSHmCOb255m0qZbSjlNf98pj7xq39mvOqu/tnsdiD/fGYn6cfy+JM9FoECsz6uPF23d+Xpxq09aBmebVoey9C62C4dM5Zj6zybLDhWUZ9hbJwxAkDD5XYu/m2xZYkv22yKRrahVCu58vROWH28vnPYlR27yDH+xL+WSR3r7bC2ixltf/Xxo3Dl6Rk9wfKCjoVnh+t3xhbuZxOcrbN6DTHvkMco0hfpsXNpde7coGWJL9psar6x6hfUXpABqo25Kl394W5uuy0fHF0UkCfVql8cgas/NG7dRycMHf/VHY1b/GF9wzgprv5wN1zZsYvbj3VlMdJzQscpmyt2PKxvtt8NWvqXWyebSrX6qc6qYfNNUK927xbK4j67tq9277bkW+TLzLZZTKyMFXu0DBuLzB49VtlcWh0DjXplwSGrfjlgKnP1yZSp3NUnjXvSi+SxLVqeJ2sm51ZMZjJsPwuWZ+M0i0/Uz7ab+VeJ75BVv864Zuvq92eXdiK7V7+/B1b9OkNk2WOZbSexWompGfsiXXZMVsbI0zdj3j3HXwisOmn+fVUAAFcf31uXnTkmujx7GLzufXxvgxwE0KxswNhO+2rwz953MLI8X7yYWIieYC0vGzNP1xDHTDuZv+83jo/WW3Xyee58N4u64lOs/l2/tP/KtrRB5sq2tCU9WtauT5Edq3Gwfu36s4tZLGw7HZ9Z/Kt/1y+cR4z6RxQHBNqRtIT/cNhQB4CGNl4RnSxW98q2tOFTFAOtd2VbuqGNlbczxmYL9scbQ/gPhxvazWKj46fHz47L9rluSnsRETl1CNrakK1ipqM/+izojz4LkVP8bydn5QGAyDuNQX/0Wa6MyKfTwvNDj0Pki22nY8PzhQsrw/oUzasV1FJnhjW5/2hou9S1X9hnB2xH5vNS135p3UpsZvHScbAysj67WPEj828Gb8wYtdSxSSCADOVS135Y+/JBWPvyQVLHn/Qxq8NrX/vywQZ/2C4ubAxsP1uwTbaN1qPjoBOEZxvrrn35oGGMPFvsPIhi480rhtW1A/Zt54eFRSU+ANz+6gFob58m5eIjfQ1tt796AC4+0kd02tunyefFR/oMOrid1aehfWG7bAz0J6+wMfL6sT7Pt0yPlePNB21fZIPtp+eB7mPnx2vUUgcA7nxtNqEvPHTQUMdtPDm2jQXLiHzS/Tw7OBb6Uxa7bAxsPLwxWmnj2TPzJfLHtsvmyyrqD1gW+cLr/06OP/rmTw11up2VlbWL9GmfvDY70PqimHl+eD5l47YSl9m8ieJkxyCL1Soq8S0SO70PAABKDx4ix7guk6XbeLp0XWaTtc1DZI/tEx2bxcDKsTJW7Mjis+oLz2UzqMS3wJf+ey+8/wD/r4asHOb9B57n1kV2aFksbybDkxfJ0PZkdkS+RXqsLDtmp3ZYWSvzbweV+C7x1YL8pSgZ78TNX3jDPt6JD9j2xdo30xfFI9Kj5bGM2ZhoW1Zlrc6TFdTjTJdoD0yT8k58wFCn23l9976xC+59w/yfK/CJ59mW+WBty/TbA9M811I92j72b2Usovh4su/EByzNkduol9QkxM/2wtKAuF7YPATxs70QP1vfPGppk5eRpYGb0liwj8Jm/i5nMn1sg6d77r6jxD6A2L5VzOLg+W816oovAV+5CpuHuFfEb5x7xlCXyX3j3DOW/ZkVkS2Rfyu69BhwvFZiNovDqQ2vaeqKX6vVYHh4GAAAUqnZtZ1o46iFtKHUQ28/BUsDAK9tehEAzK9ir216kejQbXb4r3tfgIfeforoPfT2U9L4ePaXBm6SWJz4psdt1wbP3nylqcQvFoswNjZm2DZE13UoFAqGjaM0TRO2z1fYpFpi4df3a5tehIf//CNSp49f2fhzW34f/vOPYInJ7+OH//yjBrtYXxYvT4/VseLfDHY+5hNNDS2RSEAkEjG0iTaOErWzTE1NweTkpKHMNVvf7YalgZvSsvXdbtj6bje8svHn8MrGnzf022Vp4CbXDtsm0xcV0Q+hHft2xrH13e6m7biN62t80cZRC2VDKR7B9hsQbL8BpzYMk2NeObVhGB7/4Al4/IMnGtrtgnVYH7Rtmd1TG4aF8T7+wROWfYpk7Ywj2H6jKRte0JKbW97GUaL2dDoNExMTpFy7ds3r8KT8YPR7cPKel+DkPS/BD0a/B0vapoUFAODkPS81tP9g9HuO/dN2sG38acWuLFarPpvFDRtuYznxu7q6IB6PQzweB13XhXLs0gffyIraWYLBICxbtsxQ5pJfrf8NOQ4GbkAwcAN+tf435Jiu7yhtgx2lbYY+XHaUtjn2T9ugP4MB8yspG6uVeGidxYrlm9tcLmdJTrRxlK7rC2JDKRE//vBROB77AznGN37/+cV6G74xxPUff/ioQR+3O0F2o/rjDx81tc3qW4kF61ixvxBp6pWFYrEI2WwWarUa9PT0kA2iRBtHLYQNpayw+69dAABw5O6coU5z5O5cQzuWb8Ynz48TfTM9Wr6ZuFuNelfHQ57928Nw+K5XDHUzaPlmfTdj26o+LedW7K1AvavjIWwifCLwL9Ny8MK3XPHNs21X//Bdr5jGhmUWUtLbQSW+C9zSdhP67vwT3NJ2U1j67vyTa77YYgccR9+dfzLE3P+/D3J9LVZU4rtA+o7TAAAQDPyLlPQdpw31wY/jrvly0zZtj7UTtPnbZCGhEt9FPtH2L1KO/+PrhnryNvPv+7JD8raCwb4b9pK3FeD4P75O2tywO19Rie8iO9a9Cbe03SSf9PGJi5s88+em/R3r3iTHi3mpo57qeMRvL32ZHD+25r2W+PLaz0JAPdWZQ05d7oTH1rwHt7TdgFvabsCpy52e+muVn8WE+g8sD9j6ufPwauVu+ERbvf6dyF899wcA8Grlbk/9LCbUFd8jlrbdJOW0fmdLfH4n8teW+VroqMT3CPqJy4PhCy3z+2D4AvzPP9e2zN9CRS11POKWtvqbjZtWV1ru+98+e7HlPhcaKvE9Yi4SXmEdtdRR+BKV+ApfohJf4UtU4it8SVM3t/l8HqrVKpRKJejq6jLdOGohbSilWOQgh5RKJZTL5RBCCI2Pj6NQKIQQQqhSqaDu7m4ip2matN2MiYkJBABoYmLCaagKH2E1Xxxf8avVKhQKBUgkEhAKhaCjowPK5TKcP3+eu3GUruvcdvaqPzU1BVNTU6Q+MTEBADAvNpZSzH9wniCTdy8dJ76maYakrVarEI1GYWRkpOkNpZ577rmG9vmwsZRi4XD9+nVYvny5sN+VP2D19PTAiRMnhP12N5RKJpOkPj09DdVqFVasWAFtbW1Nxzo5OQkrV66Ea9euefaas/Ixdz4QQnD9+nW49dZbpXKWE7+rq4tcobPZLNkMKp/PQzweJ1uFRCIRw5Wc3jhK1E4TDAYhGAwa2uglklu0YrMq5WNufMiu9JimNpTCG8FqmgblcpkcL8YNpRSLC8dLHV3XoatrdtOhWq1Gbii2bNlCHnWm02kAAAiHw9x2hWIucJz44XAYxsfHuX2iHdKs7JzmNcFgEH7yk580LKeUj8Xrg8e8/59bhcIL1CsLCl+iEl/hS1TiK3yJSnyFL1nU/3rYirdH5+IrT916y7VVsc/Lt3i9f19ubmjV26O5XA6lUimUyWRIm9s+aNywgWlF7K06D3ZZtEsd/PYoABjeHm3260hZvPjKUxlu2MC0IvZWnQe7LNrE1zSNfJk0wOzbo81+HakVvPThZpx27Dv1O5fnQcaiTXwaN98edYqXPtyM0459u37nw3nALJqb21a8PSrywdLsG6oyZLbdwKvY3X6Lt2k8uXOYJxQKBVQoFBBC9ZusSqWCKpUKSiQSRCYajSKEkLDdCtlstuEG0W0fZrad0orYW3Ue7LBo39XRdR1isRip02+Puvl1pK34ylMWN2y0KvZWnQe7LNrEVyhk+OLmVqFgUYmv8CUq8RW+RCW+wpeoxFf4EpX4Cl+iEl/hS1TiK3yJSnyFL1GJr/Al/w8s+sQPQhjEoQAAAABJRU5ErkJggg==", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Version without colorbars \n", - "\n", - "thetaStrs = [r'\\pi/4', r'3\\pi/4', r'3\\pi/2', '7\\pi/4']\n", - "thetaStrsFile = [r'pi_over_4', r'3pi_over_4', r'3pi_over_2', '7pi_over_4']\n", - "thetas = [np.pi/4, 3*np.pi/4, 3*np.pi/2, 7*np.pi/4]\n", - "\n", - "\n", - "for i, theta in enumerate(thetas):\n", - " print(theta)\n", - " im = plt.matshow(makeFernPic(F,theta), origin = 'lower', cmap = cmap_viridis, vmin = -200, vmax = 200)\n", - " ax = plt.gca()\n", - " midx = 279\n", - " ax.set_xticks(midx+100*np.arange(-2,3))\n", - " ax.set_xticklabels(np.arange(-2,3)*100)\n", - " ax.xaxis.set_ticks_position('bottom')\n", - "\n", - " midy = 177\n", - " ax.set_yticks(midy+100*np.arange(-2,3))\n", - " ax.set_yticklabels(np.arange(-2,3)*100)\n", - "\n", - " # plt.colorbar(fraction=0.035, pad=0.04)\n", - " plt.title(r'$f_{\\omega}$ for $\\omega = ' + thetaStrs[i] + r'$')\n", - " fig = plt.gcf()\n", - " fig.set_figwidth(1.8)\n", - "\n", - " print(fig.get_size_inches())\n", - " height_fig = fig.get_size_inches()[0]\n", - " print(height_fig)\n", - "\n", - " plt.savefig('figures/Fern_' + thetaStrsFile[i] + '_nocolorbar.png', bbox_inches = 'tight', dpi = 300)\n", - " plt.savefig('figures/Fern_' + thetaStrsFile[i] + '_nocolorbar.eps', bbox_inches = 'tight')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4e09dc67", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.7853981633974483\n", - "1.8\n", - "[7.54478873 1.8 ]\n", - "2.356194490192345\n", - "1.8\n", - "[7.54478873 1.8 ]\n", - "4.71238898038469\n", - "1.8\n", - "[7.54478873 1.8 ]\n", - "5.497787143782138\n", - "1.8\n", - "[7.54478873 1.8 ]\n" - ] - }, - { - "data": { - "image/png": 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", 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "\n", - "\n", - "thetaStrs = [r'\\pi/4', r'3\\pi/4', r'3\\pi/2', '7\\pi/4']\n", - "thetaStrsFile = [r'pi_over_4', r'3pi_over_4', r'3pi_over_2', '7pi_over_4']\n", - "thetas = [np.pi/4, 3*np.pi/4, 3*np.pi/2, 7*np.pi/4]\n", - "\n", - "\n", - "for i, theta in enumerate(thetas):\n", - " print(theta)\n", - " plt.matshow(makeFernPic(F,theta), origin = 'lower', cmap = cmap_viridis, vmin = -200, vmax = 200)\n", - " ax = plt.gca()\n", - " midx = 279\n", - " ax.set_xticks(midx+100*np.arange(-2,3))\n", - " ax.set_xticklabels(np.arange(-2,3)*100)\n", - " ax.xaxis.set_ticks_position('bottom')\n", - "\n", - " midy = 177\n", - " ax.set_yticks(midy+100*np.arange(-2,3))\n", - " ax.set_yticklabels(np.arange(-2,3)*100)\n", - "\n", - " plt.colorbar(fraction=0.03, pad=0.04)\n", - " plt.title(r'$f_{\\omega}$ for $\\omega = ' + thetaStrs[i] + r'$')\n", - " fig = plt.gcf()\n", - " # fig.set_figwidth(2.4)\n", - " print(height_fig)\n", - " fig.set_figheight(height_fig)\n", - "\n", - " print(fig.get_size_inches())\n", - "\n", - " plt.savefig('figures/Fern_' + thetaStrsFile[i] + '.png', bbox_inches = 'tight', dpi = 300)\n", - " plt.savefig('figures/Fern_' + thetaStrsFile[i] + '.eps', bbox_inches = 'tight')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1db8d134", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig,ax = plt.subplots()\n", - "plt.colorbar(im,ax=ax)\n", - "\n", - "ax.remove()\n", - "fig.set_figwidth(0.8)\n", - "plt.savefig('figures/OnlyColorbar.png', bbox_inches = 'tight', dpi = 300)\n", - "plt.savefig('figures/OnlyColorbar.eps', bbox_inches = 'tight')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "17c0ccc0", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "28dbfb28", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'5497'" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "str(int(theta*1000))" - ] - }, - { - "cell_type": "markdown", - "id": "d379223a", - "metadata": {}, - "source": [ - "## Thresholded Figure " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "08121a32", - "metadata": {}, - "outputs": [], - "source": [ - "def makeFernPicThreshold(F, theta, thresh, both = False):\n", - " maxRow, maxCol = np.shape(F)\n", - " omega = (np.cos(theta), np.sin(theta))\n", - " \n", - " # center origin \n", - " Col,Row = np.meshgrid(range(maxCol),range(maxRow))\n", - " Col = Col - np.floor(maxCol/2)\n", - " Row = Row-np.floor(maxRow/2)\n", - " \n", - " fMask = omega[0]*Col + omega[1]*Row\n", - " \n", - " fMaskBelow = fMask.copy()\n", - " fMaskBelow[fMaskBelow <= thresh] = np.nan\n", - " \n", - " fMaskAbove = fMask.copy()\n", - " fMaskAbove[fMaskAbove > thresh] = np.nan\n", - " \n", - " \n", - " DTdown = np.multiply(F,fMaskAbove)\n", - " DTup = np.multiply(F,fMaskBelow)\n", - " \n", - " # Why the fork is this backwards!?!?!?!?!\n", - " # Must have something to do with meshgrid but i just can't fight it right now\n", - " if both:\n", - " \n", - " return DTdown,DTup\n", - " else:\n", - " return DTdown\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "639dcbdd", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[1.25 4.8 ]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[1.25 4.8 ]\n", - "[1.25 4.8 ]\n", - "[1.25 4.8 ]\n", - "[1.25 4.8 ]\n", - "[1.25 4.8 ]\n", - "[1.25 4.8 ]\n" - ] - }, - { - "data": { - "image/png": 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", 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", 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", 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", 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "theta = 3*np.pi/4\n", - "\n", - "for thresh in [-150,-100,-50,0,50,100,150]:\n", - "\n", - "\n", - " heights = np.sum(leaf.cells[0]*omega, axis=1)\n", - "\n", - " # Plot colors above theshold\n", - " plt.matshow(makeFernPicThreshold(F,theta,thresh), \n", - " origin = 'lower', \n", - " cmap = cmap_viridis, \n", - " vmin = -200, vmax = 200)\n", - "\n", - " ax = plt.gca()\n", - " midx = 279\n", - " ax.set_xticks(midx+100*np.arange(-2,3))\n", - " ax.set_xticklabels(np.arange(-2,3)*100)\n", - " ax.xaxis.set_ticks_position('bottom')\n", - " ax.tick_params(axis='x', labelrotation=45)\n", - "\n", - "\n", - " midy = 177\n", - " ax.set_yticks(midy+100*np.arange(-2,3))\n", - " ax.set_yticklabels(np.arange(-2,3)*100)\n", - " \n", - " plt.title(r'$K_{' + str(thresh) + r'}$')\n", - "\n", - " fig = plt.gcf()\n", - " fig.set_figwidth(1.25)\n", - "\n", - " thresh_size_fig = fig.get_size_inches()\n", - " print(thresh_size_fig)\n", - "\n", - " # plt.colorbar()\n", - "\n", - " plt.savefig('figures/Fern_3pi_over_4_Thresh'+str(thresh)+'.png', bbox_inches = 'tight',dpi = 300)\n", - " plt.savefig('figures/Fern_3pi_over_4_Thresh'+str(thresh)+'.eps', bbox_inches = 'tight')\n", - "\n", - " # plt.clf()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d32f8502", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "theta = 3*np.pi/4\n", - "\n", - "fig,axes = plt.subplots(1,5,sharey = True, figsize = (6,2))\n", - "\n", - "for i, thresh in enumerate([-150,-50,0,50,150]):\n", - "\n", - " ax = axes[i]\n", - "\n", - " heights = np.sum(leaf.cells[0]*omega, axis=1)\n", - "\n", - " # Plot colors above theshold\n", - " ax.matshow(makeFernPicThreshold(F,theta,thresh), \n", - " origin = 'lower', \n", - " cmap = cmap_viridis, \n", - " vmin = -200, vmax = 200)\n", - "\n", - " # midx = 279\n", - " # ax.set_xticks(midx+100*np.arange(-2,3))\n", - " # ax.set_xticklabels(np.arange(-2,3)*100)\n", - " # ax.xaxis.set_ticks_position('bottom')\n", - " # ax.tick_params(axis='x', labelrotation=45)\n", - "\n", - "\n", - " # midy = 177\n", - " # ax.set_yticks(midy+100*np.arange(-2,3))\n", - " # ax.set_yticklabels(np.arange(-2,3)*100)\n", - "\n", - " ax.set_xticks([]) \n", - " ax.set_yticks([]) \n", - " ax.set_title(r'$K_{' + str(thresh) + r'}$')\n", - "\n", - " # fig = plt.gcf()\n", - " # fig.set_figwidth(1.25)\n", - "\n", - " # thresh_size_fig = fig.get_size_inches()\n", - " # print(thresh_size_fig)\n", - "\n", - " # plt.colorbar()\n", - "\n", - " # plt.savefig('figures/Fern_3pi_over_4_Thresh'+str(thresh)+'.png', bbox_inches = 'tight',dpi = 300)\n", - " # plt.savefig('figures/Fern_3pi_over_4_Thresh'+str(thresh)+'.eps', bbox_inches = 'tight')\n", - "\n", - " # plt.clf()\n", - "plt.savefig('figures/Fern_3pi_over_4_AllThresh.png', bbox_inches = 'tight',dpi = 300)\n", - "plt.savefig('figures/Fern_3pi_over_4_AllThresh.eps', bbox_inches = 'tight',dpi = 300)" - ] - }, - { - "cell_type": "markdown", - "id": "bd8361dd", - "metadata": {}, - "source": [ - "## ECC in one direction" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a416a675", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "theta = 3*np.pi/4\n", - "omega = (np.cos(theta), np.sin(theta))\n", - "heights = np.sum(leaf.cells[0]*omega, axis=1)\n", - "numThresh = 64\n", - "\n", - "threshes= np.linspace(heights.min(), heights.max(), numThresh)\n", - "\n", - "outECC = leaf.ECC(heights, numThresh)\n", - "\n", - "fig = plt.figure()\n", - "ax = plt.gca()\n", - "\n", - "positions = [-150, -50, 0, 50, 150]\n", - "for pos in positions:\n", - " ax.axvline(x=pos, color='grey', linestyle='--')\n", - "\n", - "\n", - "\n", - "plt.step(threshes,outECC)\n", - "plt.title(r'ECC for $\\omega = \\frac{3 \\pi}{4}$')\n", - "plt.xlabel('$a$')\n", - "plt.ylabel(r'$\\chi(K_a)$')\n", - "\n", - "# ax.set_xticks([-200,-150,-100,-50,0,50,100,150,200])\n", - " # midx = 279\n", - " # ax.set_xticks(midx+100*np.arange(-2,3))\n", - " # ax.set_xticklabels(np.arange(-2,3)*100)\n", - " # ax.xaxis.set_ticks_position('bottom')\n", - " # ax.tick_params(axis='x', labelrotation=45)\n", - "ax.tick_params(axis='x', labelrotation=45)\n", - "ax.tick_params(axis='y', labelrotation=45)\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(5,2)\n", - "# fig.set_size_inches(thresh_size_fig)\n", - "# print(thresh_size_fig)\n", - "# print(fig.get_size_inches())\n", - "\n", - "plt.savefig('figures/Fern_3pi_over_4_ECC.png', bbox_inches = 'tight',dpi=300)\n", - "plt.savefig('figures/Fern_3pi_over_4_ECC.eps', bbox_inches = 'tight')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3f9c12e4", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "-197\n" - ] - } - ], - "source": [ - "print(outECC[-1])" - ] - }, - { - "cell_type": "markdown", - "id": "7017e7c9", - "metadata": {}, - "source": [ - "## ECT\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "81210cb6", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[0. 0.0625 0.125 0.1875 0.25 0.3125 0.375 0.4375 0.5 0.5625\n", - " 0.625 0.6875 0.75 0.8125 0.875 0.9375 1. 1.0625 1.125 1.1875\n", - " 1.25 1.3125 1.375 1.4375 1.5 1.5625 1.625 1.6875 1.75 1.8125\n", - " 1.875 1.9375]\n" - ] - } - ], - "source": [ - "# Get all the directions around the circle\n", - "numCircleDirs = 32\n", - "circledirs = np.linspace(0, 2*np.pi, num=numCircleDirs, endpoint=False)\n", - "circledirs\n", - "\n", - "print(circledirs/np.pi)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "13cdd2ca", - "metadata": {}, - "outputs": [], - "source": [ - "# Choose number of thresholds for the ECC to stop at \n", - "numThresh = 100 " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "04b57d67", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "-285.68893688291087 285.68893688291087\n" - ] - } - ], - "source": [ - "ECT_preprocess = {}\n", - "\n", - "overallmin = 0\n", - "overallmax = 0\n", - "\n", - "for i, omega in enumerate(circledirs):\n", - " \n", - " omegavec = np.array((np.cos(omega),np.sin(omega)))\n", - " \n", - " # Function values of all the pixels\n", - " heights = np.sum(leaf.cells[0]*omegavec, axis=1)\n", - "\n", - " # Thresholds implicitly calculated by Erik's code\n", - " threshes= np.linspace(heights.min(), heights.max(), numThresh)\n", - " \n", - " if heights.min()overallmax:\n", - " overallmax= heights.max()\n", - " \n", - "\n", - " outECC = leaf.ECC(heights, numThresh)\n", - " \n", - " ECT_preprocess[i] = (threshes,outECC)\n", - " \n", - "print(overallmin,overallmax)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "17128b08", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "i = 2\n", - "\n", - "plt.step( ECT_preprocess[i][0], ECT_preprocess[i][1])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4ec3eefe", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_57600/1470381530.py:26: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", - " M[i,j] = ECT_preprocess[omegai][1][index]\n" - ] - } - ], - "source": [ - "# Making a matrix of size numThreshes x numCircleDirs\n", - "# M[i,j] = \n", - "\n", - "\n", - "# Make meshgrid. The +1 is to draw 2pi on both ends\n", - "X,Y = np.meshgrid(range(numCircleDirs+1),np.linspace(-250,250,numThresh))\n", - "M = np.ones_like(X)\n", - "\n", - "for i in range(X.shape[0]):\n", - " for j in range(X.shape[1]):\n", - " omegai = X[i,j]\n", - " \n", - " # Deal with redrawing the 2pi\n", - " omegai = np.mod(omegai,numCircleDirs)\n", - " \n", - " \n", - " omega = i*np.pi/numCircleDirs\n", - " a = Y[i,j]\n", - " threshes = ECT_preprocess[omegai][0]\n", - "# print(threshes)\n", - " try: \n", - " index = np.where(threshes>=a)[0][0] \n", - " except:\n", - " index = [-1]\n", - "\n", - " M[i,j] = ECT_preprocess[omegai][1][index]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "eac07698", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.pcolormesh(X,Y,M, cmap = 'viridis')\n", - "plt.colorbar()\n", - "\n", - "ax = plt.gca()\n", - "ax.set_xticks(np.arange(0,numCircleDirs+1,4))\n", - "\n", - "labels = [r'$0$',\n", - " r'$\\frac{\\pi}{4}$',\n", - " r'$\\frac{\\pi}{2}$',\n", - " r'$\\frac{3\\pi}{4}$',\n", - " r'$\\pi$',\n", - " r'$\\frac{5\\pi}{4}$',\n", - " r'$\\frac{3\\pi}{2}$',\n", - " r'$\\frac{7\\pi}{4}$',\n", - " r'$2\\pi$',\n", - " ]\n", - "\n", - "ax.set_xticklabels(labels)\n", - "\n", - "\n", - "plt.xlabel(r'$\\omega$')\n", - "plt.ylabel(r'$a$')\n", - "\n", - "plt.title(r'ECT of Fern Leaf')\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(3,2)\n", - "\n", - "plt.savefig('figures/Fern_ECT.png', bbox_inches = 'tight',dpi=900)\n", - "plt.savefig('figures/Fern_ECT.eps', bbox_inches = 'tight')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "930cb35f", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([ 1, 1, 1, 1, 6, 1, 1, 1, 1, 2, 1, 4, 1, 1, 3, 3, 2,\n", - " 1, 2, 10, 3, 3, 1, 1, 3, 3, 1, 2, 1, 1, 1, 1, 1])" - ] - }, - "execution_count": 34, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "M[0,:]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5afc592b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([ 4., 11., 19.])" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "bigvals = np.where(M[0,:] >3)[0]\n", - "\n", - "\n", - "circledirs[bigvals]/np.pi*16" - ] - }, - { - "cell_type": "markdown", - "id": "ad5f2a1d", - "metadata": {}, - "source": [ - "## Let's draw a cylinder!" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "203aece0", - "metadata": {}, - "outputs": [], - "source": [ - "import matplotlib\n", - "from mpl_toolkits.mplot3d import Axes3D\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "\n", - "# pip install ipympl\n", - "\n", - "# %matplotlib widget" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9b2acd4f", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(100, 32)\n" - ] - } - ], - "source": [ - "grid = M[:,:-1]\n", - "print(grid.shape)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f9ab03be", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(100, 32, 4)\n" - ] - } - ], - "source": [ - "color_dimension = grid # change to desired fourth dimension\n", - "minn, maxx = color_dimension.min(), color_dimension.max()\n", - "norm = matplotlib.colors.Normalize(minn, maxx)\n", - "m = plt.cm.ScalarMappable(norm=norm, cmap='viridis')\n", - "m.set_array([])\n", - "fcolors = m.to_rgba(color_dimension)\n", - "\n", - "print(fcolors.shape)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7131aa3f", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[0. 0.27318197 0.54636394 0.81954591 1.09272788 1.36590985\n", - " 1.63909182 1.91227379 2.18545576 2.45863773 2.7318197 3.00500167\n", - " 3.27818364 3.55136561 3.82454758 4.09772955 4.37091152 4.64409349\n", - " 4.91727546 5.19045743 5.4636394 5.73682137 6.01000334 6.28318531]\n" - ] - } - ], - "source": [ - "theta = np.linspace(0, 2 * np.pi, 24)\n", - "print(theta)\n", - "# theta = circledirs[:-1]\n", - "# print(theta, theta.shape)\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c071d904", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "\"\"\"\n", - "equation for a circle\n", - "\n", - "x = h + r cosθ\n", - "y = k + r sinθ\n", - "\n", - "where h and k are the co-ordinates of the center\n", - "\n", - "0 <= θ <= 360\n", - "\"\"\"\n", - "\n", - "fig = plt.figure(figsize=(4,3))\n", - "ax = fig.add_subplot(111, projection='3d')\n", - "\n", - "# theta = np.linspace(0, 2 * np.pi, 24)\n", - "radius = 1\n", - "\n", - "\n", - "x = np.linspace(0, numThresh, numThresh)\n", - "\n", - "# theta = circledirs\n", - "theta = np.linspace(0, 2 * np.pi, 32)\n", - "\n", - "thetas, xs = np.meshgrid(theta, x)\n", - "\n", - "y = radius * np.cos(thetas)\n", - "z = radius * np.sin(thetas)\n", - "\n", - "#ax.plot_surface(xs, y, z, color='orange')\n", - "#ax.plot_surface(xs, y, z, facecolors=fcolors)\n", - "surf = ax.plot_surface(xs, y, z, facecolors = fcolors,linewidth = 0.1)\n", - "surf.set_edgecolor('grey')\n", - "\n", - "ax.set_axis_off()\n", - "\n", - "plt.savefig('figures/fern_ECT_cylinder.png', bbox_inches = 'tight',dpi = 900)\n", - "plt.savefig('figures/fern_ECT_cylinder.eps', bbox_inches = 'tight')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b03f0104", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[-193.98518858 -190.40235323 -186.81951788 -183.23668253 -179.65384718\n", - " -176.07101183 -172.48817648 -168.90534113 -165.32250578 -161.73967042\n", - " -158.15683507 -154.57399972 -150.99116437 -147.40832902 -143.82549367\n", - " -140.24265832 -136.65982297 -133.07698762 -129.49415227 -125.91131692\n", - " -122.32848157 -118.74564621 -115.16281086 -111.57997551 -107.99714016\n", - " -104.41430481 -100.83146946 -97.24863411 -93.66579876 -90.08296341\n", - " -86.50012806 -82.91729271 -79.33445735 -75.751622 -72.16878665\n", - " -68.5859513 -65.00311595 -61.4202806 -57.83744525 -54.2546099\n", - " -50.67177455 -47.0889392 -43.50610385 -39.92326849 -36.34043314\n", - " -32.75759779 -29.17476244 -25.59192709 -22.00909174 -18.42625639\n", - " -14.84342104 -11.26058569 -7.67775034 -4.09491499 -0.51207963\n", - " 3.07075572 6.65359107 10.23642642 13.81926177 17.40209712\n", - " 20.98493247 24.56776782 28.15060317 31.73343852 35.31627387\n", - " 38.89910923 42.48194458 46.06477993 49.64761528 53.23045063\n", - " 56.81328598 60.39612133 63.97895668 67.56179203 71.14462738\n", - " 74.72746273 78.31029808 81.89313344 85.47596879 89.05880414\n", - " 92.64163949 96.22447484 99.80731019 103.39014554 106.97298089\n", - " 110.55581624 114.13865159 117.72148694 121.3043223 124.88715765\n", - " 128.469993 132.05282835 135.6356637 139.21849905 142.8013344\n", - " 146.38416975 149.9670051 153.54984045 157.1326758 160.71551116]\n", - "59\n", - "17.402097119801482\n" - ] - }, - { - "data": { - "text/plain": [ - "-83" - ] - }, - "execution_count": 41, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "omegai = 5\n", - "omega = i*np.pi/numCircleDirs\n", - "a = 17\n", - "threshes = ECT_preprocess[omegai][0]\n", - "print(threshes)\n", - "\n", - "index = np.where(threshes>=a)[0][0]\n", - "print(index)\n", - "print(threshes[index])\n", - "ECT_preprocess[omegai][1][index]" - ] - }, - { - "cell_type": "markdown", - "id": "554bc00c", - "metadata": {}, - "source": [ - "## Erik's version" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6e5a2a91", - "metadata": {}, - "outputs": [], - "source": [ - "# t = 32\n", - "# tic = time.perf_counter()\n", - "# ect = leaf.ECT(circle_dirs, T=t)\n", - "# toc = time.perf_counter()\n", - "# print(\"Complex with {} vertices\\n\".format(len(leaf.cells[0])))\n", - "# print(\"ECT with {} directions in {:.4f} seconds.\\n{:.4f}s per direction\".format(len(circle_dirs), toc-tic, (toc-tic)/len(circle_dirs)))\n", - "\n", - "# plt.figure(figsize=(15,2))\n", - "# plt.plot(ect);\n", - "# plt.title('ECT for {} directions and {} thresholds each'.format(len(circle_dirs),t), fontsize=24);" - ] - }, - { - "cell_type": "markdown", - "id": "719235ff", - "metadata": {}, - "source": [ - "# SECT" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "96766900", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'ECT of Fern Leaf')" - ] - }, - "execution_count": 43, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# THe original ECT\n", - "\n", - "plt.pcolormesh(X,Y,M, cmap = 'viridis')\n", - "plt.colorbar()\n", - "\n", - "ax = plt.gca()\n", - "ax.set_xticks(np.arange(0,numCircleDirs+1,4))\n", - "\n", - "labels = [r'$0$',\n", - " r'$\\frac{\\pi}{4}$',\n", - " r'$\\frac{\\pi}{2}$',\n", - " r'$\\frac{3\\pi}{4}$',\n", - " r'$\\pi$',\n", - " r'$\\frac{5\\pi}{4}$',\n", - " r'$\\frac{3\\pi}{2}$',\n", - " r'$\\frac{7\\pi}{4}$',\n", - " r'$2\\pi$',\n", - " ]\n", - "\n", - "ax.set_xticklabels(labels)\n", - "\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(3,2)\n", - "plt.xlabel(r'$\\omega$')\n", - "plt.ylabel(r'$a$')\n", - "\n", - "plt.title(r'ECT of Fern Leaf')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "731fe26b", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(100, 33)\n", - "[-100.72 -99.01 -96.97 -95. -93.24 -92.33 -91.34 -90.83 -90.69\n", - " -89.07 -87.98 -87.07 -87.2 -87.64 -88.43 -89.47 -90.97 -90.94\n", - " -91.8 -91.22 -93. -94.51 -96.85 -98.61 -99.98 -100.05 -100.44\n", - " -100.47 -101.04 -101.12 -101.03 -100.91 -100.72]\n" - ] - } - ], - "source": [ - "# Following Crawford2019 for the moment. Is this different in the Meng22 version?\n", - "print(M.shape)\n", - "\n", - "# Averages for a fixed direction \n", - "AvgOverOmega = np.average(M,axis = 0)\n", - "print(AvgOverOmega)\n", - "\n", - "# Mean centered \n", - "\n", - "Mcentered = M-AvgOverOmega" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "33144af2", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.pcolormesh(X,Y,Mcentered, cmap = 'viridis')\n", - "plt.colorbar()\n", - "\n", - "ax = plt.gca()\n", - "ax.set_xticks(np.arange(0,numCircleDirs+1,4))\n", - "\n", - "labels = [r'$0$',\n", - " r'$\\frac{\\pi}{4}$',\n", - " r'$\\frac{\\pi}{2}$',\n", - " r'$\\frac{3\\pi}{4}$',\n", - " r'$\\pi$',\n", - " r'$\\frac{5\\pi}{4}$',\n", - " r'$\\frac{3\\pi}{2}$',\n", - " r'$\\frac{7\\pi}{4}$',\n", - " r'$2\\pi$',\n", - " ]\n", - "\n", - "ax.set_xticklabels(labels)\n", - "\n", - "\n", - "plt.xlabel(r'$\\omega$')\n", - "plt.ylabel(r'$a$')\n", - "\n", - "plt.title(r'ECT of Fern Leaf with value centered')\n", - "\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(3,2)\n", - "\n", - "plt.savefig('figures/Fern-ECT-centered.png', bbox_inches = 'tight')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "cfbf9ef1", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([-1.09992015e-11, 1.23066002e-11, -1.07718279e-11, 0.00000000e+00,\n", - " -1.27613475e-11, -5.48538992e-12, 6.96331881e-12, -5.03064257e-12,\n", - " 4.71800377e-12, 7.78754838e-12, 1.33582034e-12, 7.78754838e-12,\n", - " -9.12336873e-12, -5.42854650e-12, -7.56017471e-12, -1.09992015e-11,\n", - " -1.09992015e-11, 4.71800377e-12, 9.35074240e-12, -1.09992015e-11,\n", - " 0.00000000e+00, 1.25339739e-11, -6.56541488e-12, 5.54223334e-12,\n", - " 1.33582034e-12, 9.40758582e-12, 4.66116035e-12, -1.09992015e-11,\n", - " -2.87059265e-12, -8.29913915e-12, 1.07718279e-11, -7.53175300e-12,\n", - " -1.09992015e-11])" - ] - }, - "execution_count": 46, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Mcentered.sum(axis = 0)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "101671c2", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[1 2 3]\n", - " [4 5 6]]\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[1, 2, 3],\n", - " [5, 7, 9]])" - ] - }, - "execution_count": 47, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "a = np.array([[1,2,3], [4,5,6]])\n", - "print(a)\n", - "np.cumsum(a,axis = 0)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f047f4f3", - "metadata": {}, - "outputs": [], - "source": [ - "Mint = np.cumsum(Mcentered,axis = 0)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a6cc372d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.pcolormesh(X,Y,Mint, cmap = 'viridis')\n", - "plt.colorbar()\n", - "\n", - "ax = plt.gca()\n", - "ax.set_xticks(np.arange(0,numCircleDirs+1,4))\n", - "\n", - "labels = [r'$0$',\n", - " r'$\\frac{\\pi}{4}$',\n", - " r'$\\frac{\\pi}{2}$',\n", - " r'$\\frac{3\\pi}{4}$',\n", - " r'$\\pi$',\n", - " r'$\\frac{5\\pi}{4}$',\n", - " r'$\\frac{3\\pi}{2}$',\n", - " r'$\\frac{7\\pi}{4}$',\n", - " r'$2\\pi$',\n", - " ]\n", - "\n", - "ax.set_xticklabels(labels)\n", - "\n", - "\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(3,2)\n", - "\n", - "plt.xlabel(r'$\\omega$')\n", - "plt.ylabel(r'$t$')\n", - "\n", - "plt.title(r'SECT of Fern Leaf')\n", - "\n", - "plt.savefig('figures/Fern-SECT.png',bbox_inches = 'tight',dpi=900)\n", - "plt.savefig('figures/Fern-SECT.eps',bbox_inches = 'tight')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f4478b3c", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.7" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Extra_Notebooks/Matisse_ECT.ipynb b/Extra_Notebooks/Matisse_ECT.ipynb deleted file mode 100644 index 5b66a5e..0000000 --- a/Extra_Notebooks/Matisse_ECT.ipynb +++ /dev/null @@ -1,386 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "23bd9d9b", - "metadata": {}, - "source": [ - "# ECT on Matisse's \"The Parakeet and the Mermaid\" \n", - "\n", - "Here, we are going to give an example of using the ECT to classify the cutout shapes from Henri Matisse's 1952 [\"The Parakeet and the Mermaid\"](https://www.moma.org/audio/playlist/6/312). \n", - "\n", - "![matisse.jpg](matisse.jpg)\n" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "b73a120d", - "metadata": {}, - "outputs": [], - "source": [ - "#-----------------\n", - "# Standard imports \n", - "#-----------------\n", - "import numpy as np # for arrays\n", - "import matplotlib.pyplot as plt # for plotting\n", - "from sklearn.decomposition import PCA # for PCA for normalization\n", - "from scipy.spatial import distance_matrix\n", - "\n", - "from os import listdir # for retrieving files from directory\n", - "from os.path import isfile, join # for retrieving files from directory\n", - "from sklearn.manifold import MDS # for MDS\n", - "import pandas as pd # for loading in colors csv\n", - "\n", - "#---------------------------\n", - "# The ECT packages we'll use\n", - "#---------------------------\n", - "from ect import ECT, EmbeddedGraph # for calculating ECTs\n" - ] - }, - { - "cell_type": "markdown", - "id": "c149a147", - "metadata": {}, - "source": [ - "We've taken care of the preprocessing in advance by extracting out the shapes from the image. You can download these outlines here: [outlines.zip](outlines.zip).\n", - "\n", - "\"Matisse" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "f7b7fe4c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "There are 150 files in the directory\n" - ] - } - ], - "source": [ - "data_dir = \"doc_source/notebooks/Matisse/outlines/\" # set data directory\n", - "file_names = [f for f in listdir(data_dir) if isfile(join(data_dir, f)) and f[-4:] == '.txt'] # create a list of file names\n", - "file_names.sort() # sort the list of file names\n", - "print(f\"There are {len(file_names)} files in the directory\") # print number of files" - ] - }, - { - "cell_type": "markdown", - "id": "6b082bf2", - "metadata": {}, - "source": [ - "Here we have an example of one of these leaves loaded in as an `EmbeddedGraph` class." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "3cb77aa4", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "i = 3\n", - "shape = np.loadtxt(data_dir + file_names[i])\n", - "# shape = normalize(shape)\n", - "G = EmbeddedGraph()\n", - "G.add_cycle(shape)\n", - "G.plot(with_labels = False, node_size = 10)" - ] - }, - { - "cell_type": "markdown", - "id": "aef7ef04", - "metadata": {}, - "source": [ - "We're going to align the leaf using the PCA coordinates, min-max center, and scale it to fit in a ball of radius 1 for ease of comparisons. " - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "3d930346", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "G.set_PCA_coordinates( center_type='min_max', scale_radius=1)\n", - "G.plot(with_labels = False, node_size = 10, bounding_circle=True)" - ] - }, - { - "cell_type": "markdown", - "id": "49bc6a0c", - "metadata": {}, - "source": [ - "And then we can compute the ECT of this leaf. " - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "e0e07987", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "num_dirs=50 # set number of directional axes\n", - "num_thresh=50 # set number of thresholds each axis\n", - "\n", - "myect = ECT(num_dirs = num_dirs, num_thresh=num_thresh) # intiate ECT\n", - "myect.set_bounding_radius(1) # set bounding radius\n", - "myect.calculateECT(G) # calculate ECT on embedded graph\n", - "\n", - "myect.plotECT() # plot ECT\n" - ] - }, - { - "cell_type": "markdown", - "id": "ebc64b1d", - "metadata": {}, - "source": [ - "Let's just make a data loader with all of this for ease in a bit. " - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "dcf72cc4", - "metadata": {}, - "outputs": [], - "source": [ - "def matisse_ect(filename, num_dirs, num_thresh):\n", - " shape = np.loadtxt(data_dir + filename)\n", - " G = EmbeddedGraph()\n", - " G.add_cycle(shape)\n", - " G.set_PCA_coordinates( center_type='min_max', scale_radius=1)\n", - " myect = ECT(num_dirs = num_dirs, num_thresh=num_thresh) \n", - " myect.set_bounding_radius(1) \n", - " M = myect.calculateECT(G) \n", - " return M" - ] - }, - { - "cell_type": "markdown", - "id": "91cb74c1", - "metadata": {}, - "source": [ - "And now we can load in all the outlines, compute their ECT and store it in a 3D array. " - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "2dfe86ec", - "metadata": {}, - "outputs": [], - "source": [ - "num_dirs=50 # set number of directional axes\n", - "num_thresh=50 # set number of thresholds each axis\n", - "\n", - "ect_arr = np.zeros((len(file_names),num_dirs,num_thresh))\n", - "for i in range(len(file_names)): # for each leaf\n", - " ect_arr[i,:,:] = matisse_ect(file_names[i], num_dirs, num_thresh)" - ] - }, - { - "cell_type": "markdown", - "id": "7be2f273", - "metadata": {}, - "source": [ - "Here, we are just going to compute the distance between two ECTs using $L_2$ distance. " - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "e1efac55", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "flattened_ect = ect_arr.reshape(len(file_names), num_dirs*num_thresh)\n", - "D = distance_matrix(flattened_ect, flattened_ect)\n", - "plt.matshow(D)" - ] - }, - { - "cell_type": "markdown", - "id": "ce93bb3f", - "metadata": {}, - "source": [ - "For visualization purposes, we can project this data into 2D using Multi Dimensional Scaling (MDS). Here we plot each figure at the MDS coordinates. " - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "0984d176", - "metadata": {}, - "outputs": [], - "source": [ - "n_components = 2 # select number of components\n", - "mds = MDS(n_components=n_components, # initialize MDS\n", - " dissimilarity=\"precomputed\", # we have precomputed the distance matrix\n", - " normalized_stress='auto',\n", - " random_state=5 # select random state for reproducibility\n", - " )\n", - "MDS_scores = mds.fit_transform(D) # get MDS scores" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "551aa2fd", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, \"MDS of Matisse's Leaves via ECT distances\")" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# read in color hexcodes\n", - "col_df = pd.read_csv(\"doc_source/notebooks/Matisse/colors.csv\", header=None) \n", - "\n", - "scale_val = 6 # set scale value\n", - "plt.figure(figsize=(5,5)) # set figure dimensions\n", - "\n", - "for i in range(len(file_names)): # for each leaf\n", - " shape = np.loadtxt(data_dir+file_names[i]) # get the current shape\n", - " shape = shape - np.mean(shape, axis=0) # zero center shape\n", - " shape = scale_val * shape / max(np.linalg.norm(shape, axis = 1)) # scale to radius 1 then mult by scale_val\n", - "\n", - " trans_sh = (shape + MDS_scores[i]) # translate shape to MDS position\n", - "\n", - " plt.fill(trans_sh[:,0], trans_sh[:,1], c=col_df[0][i], lw=0) # plot shape\n", - " plt.gca().set_aspect(\"equal\")\n", - "\n", - "plt.title(\"MDS of Matisse's Leaves via ECT distances\")\n", - "# plt.savefig(\"Matisse_MDS.png\", bbox_inches = 'tight', dpi=300) " - ] - }, - { - "cell_type": "markdown", - "id": "b3c3d0e7", - "metadata": {}, - "source": [ - "## Acknowledgements\n", - "\n", - "This notebook was written by [Liz Munch](https://elizabethmunch.com/) based on [original code](https://github.com/DanChitwood/matisse_test) from [Dan Chitwood](https://www.canr.msu.edu/people/dr_dan_chitwood). " - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.7" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/Extra_Notebooks/Mesh.ipynb b/Extra_Notebooks/Mesh.ipynb deleted file mode 100644 index 6d045a5..0000000 --- a/Extra_Notebooks/Mesh.ipynb +++ /dev/null @@ -1,79 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1 0\n", - "4 5\n", - "9 8\n", - "10 1\n" - ] - } - ], - "source": [ - "from CGAL.CGAL_Kernel import Point_2\n", - "from CGAL.CGAL_Triangulation_2 import Triangulation_2\n", - "from CGAL.CGAL_Triangulation_2 import Triangulation_2_Vertex_circulator\n", - "from CGAL.CGAL_Triangulation_2 import Triangulation_2_Vertex_handle\n", - "\n", - "points=[]\n", - "points.append( Point_2(1,0) )\n", - "points.append( Point_2(3,2) )\n", - "points.append( Point_2(4,5) )\n", - "points.append( Point_2(9,8) )\n", - "points.append( Point_2(7,4) )\n", - "points.append( Point_2(5,2) )\n", - "points.append( Point_2(6,3) )\n", - "points.append( Point_2(10,1) )\n", - " \n", - "t=Triangulation_2()\n", - "t.insert(points)\n", - "\n", - "vc = t.incident_vertices(t.infinite_vertex())\n", - "\n", - "if vc.hasNext():\n", - " done = vc.next();\n", - " iter=Triangulation_2_Vertex_handle()\n", - " while(1):\n", - " iter=vc.next()\n", - " print (iter.point())\n", - " if iter == done:\n", - " break\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "base", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.7" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Extra_Notebooks/Playing_with_Spirals.ipynb b/Extra_Notebooks/Playing_with_Spirals.ipynb deleted file mode 100644 index 1aa05a2..0000000 --- a/Extra_Notebooks/Playing_with_Spirals.ipynb +++ /dev/null @@ -1,1891 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/liz/Library/CloudStorage/Dropbox/Math/Code/ect/ect/ect/ect_graph.py:10: SyntaxWarning: invalid escape sequence '\\c'\n", - " \"\"\"\n", - "/Users/liz/Library/CloudStorage/Dropbox/Math/Code/ect/ect/ect/ect_graph.py:165: SyntaxWarning: invalid escape sequence '\\o'\n", - " \"\"\"\n", - "/Users/liz/Library/CloudStorage/Dropbox/Math/Code/ect/ect/ect/ect_graph.py:222: SyntaxWarning: invalid escape sequence '\\p'\n", - " \"\"\"\n", - "/Users/liz/Library/CloudStorage/Dropbox/Math/Code/ect/ect/ect/embed_graph.py:445: SyntaxWarning: invalid escape sequence '\\i'\n", - " \"\"\"\n" - ] - } - ], - "source": [ - "from ect import ECT, EmbeddedGraph, EmbeddedCW,create_example_graph\n", - "\n", - "import matplotlib.pyplot as plt\n", - "from matplotlib.patches import Circle\n", - "import numpy as np\n", - "import networkx as nx\n", - "import pandas as pd" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Recreating the sprial example from Arya \n", - "\n", - "# Create the graph\n", - "Spiral = EmbeddedGraph()\n", - "Spiral.add_node('a', .5, 0)\n", - "Spiral.add_node('b', 1, 1)\n", - "Spiral.add_node('c', -1.5, -.5)\n", - "Spiral.add_node('d', 3, -2.5)\n", - "Spiral.add_node('e',1.5,2)\n", - "Spiral.add_node('f',-1.5,2)\n", - "Spiral.add_node('g', -3,-3)\n", - "\n", - "nodelist = list(Spiral.nodes())\n", - "nodelist.sort()\n", - "for i in range(len(nodelist)-1):\n", - " Spiral.add_edge(nodelist[i], nodelist[i+1])\n", - "\n", - "fix, ax = plt.subplots()\n", - "Spiral.plot(ax = ax)\n", - "Spiral.plot_angle_circle(ax = ax, edges_only=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fix, ax = plt.subplots()\n", - "Spiral.plot(ax = ax)\n", - "Spiral.plot_angle_circle(ax = ax, edges_only=False)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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AngleSwapped VertsSorted list
00.00[(c, f)]gcfabed
10.32[(d, e)]gcfabed
20.52[(b, d)]gcfadbe
30.79[(a, d), (f, a), (f, d)]gcdafbe
41.15[(c, d)]gcdafbe
51.19[(b, f)]gdcafbe
61.57[(e, f)]gdcabfe
71.65[(d, g)]gdcabef
81.82[(a, c)]dgacbef
92.11[(b, c)]dgacbef
102.27[(c, e)]dgabecf
112.28[(a, g)]dagbecf
122.36[(b, g)]dabgecf
132.41[(e, g)]dabegcf
142.60[(c, g)]dabegcf
152.68[(a, b), (a, e), (b, e)]debacgf
162.85[(f, g)]debacgf
173.14[(c, f)]debacfg
183.46[(d, e)]debafcg
193.66[(b, d)]edbafcg
203.93[(a, d), (f, a), (f, d)]ebfadcg
214.29[(c, d)]ebfadcg
224.33[(b, f)]ebfacdg
234.71[(e, f)]efbacdg
244.79[(d, g)]febacdg
254.96[(a, c)]febcagd
265.25[(b, c)]febcagd
275.41[(c, e)]fcebagd
285.42[(a, g)]fcebagd
295.50[(b, g)]fcegbad
305.55[(e, g)]fcegbad
315.74[(c, g)]fcgebad
325.82[(a, b), (a, e), (b, e)]fgcabed
335.99[(f, g)]fgcabed
\n", - "
" - ], - "text/plain": [ - " Angle Swapped Verts Sorted list\n", - "0 0.00 [(c, f)] gcfabed\n", - "1 0.32 [(d, e)] gcfabed\n", - "2 0.52 [(b, d)] gcfadbe\n", - "3 0.79 [(a, d), (f, a), (f, d)] gcdafbe\n", - "4 1.15 [(c, d)] gcdafbe\n", - "5 1.19 [(b, f)] gdcafbe\n", - "6 1.57 [(e, f)] gdcabfe\n", - "7 1.65 [(d, g)] gdcabef\n", - "8 1.82 [(a, c)] dgacbef\n", - "9 2.11 [(b, c)] dgacbef\n", - "10 2.27 [(c, e)] dgabecf\n", - "11 2.28 [(a, g)] dagbecf\n", - "12 2.36 [(b, g)] dabgecf\n", - "13 2.41 [(e, g)] dabegcf\n", - "14 2.60 [(c, g)] dabegcf\n", - "15 2.68 [(a, b), (a, e), (b, e)] debacgf\n", - "16 2.85 [(f, g)] debacgf\n", - "17 3.14 [(c, f)] debacfg\n", - "18 3.46 [(d, e)] debafcg\n", - "19 3.66 [(b, d)] edbafcg\n", - "20 3.93 [(a, d), (f, a), (f, d)] ebfadcg\n", - "21 4.29 [(c, d)] ebfadcg\n", - "22 4.33 [(b, f)] ebfacdg\n", - "23 4.71 [(e, f)] efbacdg\n", - "24 4.79 [(d, g)] febacdg\n", - "25 4.96 [(a, c)] febcagd\n", - "26 5.25 [(b, c)] febcagd\n", - "27 5.41 [(c, e)] fcebagd\n", - "28 5.42 [(a, g)] fcebagd\n", - "29 5.50 [(b, g)] fcegbad\n", - "30 5.55 [(e, g)] fcegbad\n", - "31 5.74 [(c, g)] fcgebad\n", - "32 5.82 [(a, b), (a, e), (b, e)] fgcabed\n", - "33 5.99 [(f, g)] fgcabed" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "All_Angles = Spiral.get_normals_dict(num_rounding_digits=2, opposites = True)\n", - "keys = list(All_Angles.keys())\n", - "keys.sort()\n", - "\n", - "pd_table = pd.DataFrame(columns = ['Angle', 'Swapped Verts', 'Sorted list'])\n", - "pd_table['Angle'] = keys\n", - "pd_table['Swapped Verts'] = [All_Angles[key] for key in keys]\n", - "\n", - "\n", - "\n", - "pd_table.sort_values(by='Angle', inplace=True)\n", - "pd_table['Sorted list'] = [''.join(Spiral.sort_vertices(key)) for key in keys]\n", - "pd_table.head(100)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "dict_keys([5.82, 1.82, 3.93, 2.28, 2.11, 3.66, 1.19, 2.36, 4.29, 5.41, 0.0, 2.6, 0.32, 1.65, 1.57, 2.41, 2.85, 2.68, 4.96, 0.79, 5.42, 5.25, 0.52, 4.33, 5.5, 1.15, 2.27, 3.14, 5.74, 3.46, 4.79, 4.71, 5.55, 5.99])" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "All_Angles.keys()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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anglevertex_pair(s)_swappedsorted_order_at_next_midpoint
00.00[(c, f)][g, c, f, a, b, e, d]
10.32[(d, e)][g, c, f, a, d, b, e]
21.04[(b, f)][g, c, d, a, f, b, e]
31.19[(b, f)][g, d, c, a, b, f, e]
41.57[(e, f)][g, d, c, a, b, e, f]
51.65[(d, g)][d, g, c, a, b, e, f]
61.73[(c, e)][d, g, c, a, b, e, f]
71.82[(a, c)][d, g, a, c, b, e, f]
82.11[(b, c)][d, g, a, b, c, e, f]
92.24[(e, f)][d, g, a, b, c, e, f]
102.28[(a, g)][d, a, g, b, e, c, f]
112.36[(b, g)][d, a, b, g, e, c, f]
122.41[(e, g)][d, a, b, e, g, c, f]
132.49[(d, g)][d, a, b, e, g, c, f]
142.52[(b, d)][d, a, b, e, g, c, f]
152.60[(c, g)][d, e, b, a, c, g, f]
162.85[(f, g)][d, e, b, a, c, f, g]
173.02[(a, c)][d, e, b, a, f, c, g]
183.37[(a, d), (f, a), (f, d)][e, d, b, a, f, c, g]
193.59[(c, f)][e, d, b, a, f, c, g]
203.66[(b, d)][e, b, d, a, f, c, g]
213.93[(b, c)][e, b, f, a, d, c, g]
224.29[(c, d)][e, f, b, a, c, d, g]
234.47[(a, g)][e, f, b, a, c, d, g]
244.50[(c, d)][e, f, b, a, c, d, g]
254.59[(d, e)][e, f, b, a, c, d, g]
264.72[(b, g)][f, e, b, a, c, d, g]
274.87[(e, g)][f, e, b, c, a, g, d]
285.41[(c, e)][f, c, e, b, g, a, d]
295.47[(c, g)][f, c, g, e, b, a, d]
305.82[(a, b), (a, e), (b, e)][g, f, c, a, b, e, d]
316.26[(f, g)][g, f, c, a, b, e, d]
\n", - "
" - ], - "text/plain": [ - " angle vertex_pair(s)_swapped sorted_order_at_next_midpoint\n", - "0 0.00 [(c, f)] [g, c, f, a, b, e, d]\n", - "1 0.32 [(d, e)] [g, c, f, a, d, b, e]\n", - "2 1.04 [(b, f)] [g, c, d, a, f, b, e]\n", - "3 1.19 [(b, f)] [g, d, c, a, b, f, e]\n", - "4 1.57 [(e, f)] [g, d, c, a, b, e, f]\n", - "5 1.65 [(d, g)] [d, g, c, a, b, e, f]\n", - "6 1.73 [(c, e)] [d, g, c, a, b, e, f]\n", - "7 1.82 [(a, c)] [d, g, a, c, b, e, f]\n", - "8 2.11 [(b, c)] [d, g, a, b, c, e, f]\n", - "9 2.24 [(e, f)] [d, g, a, b, c, e, f]\n", - "10 2.28 [(a, g)] [d, a, g, b, e, c, f]\n", - "11 2.36 [(b, g)] [d, a, b, g, e, c, f]\n", - "12 2.41 [(e, g)] [d, a, b, e, g, c, f]\n", - "13 2.49 [(d, g)] [d, a, b, e, g, c, f]\n", - "14 2.52 [(b, d)] [d, a, b, e, g, c, f]\n", - "15 2.60 [(c, g)] [d, e, b, a, c, g, f]\n", - "16 2.85 [(f, g)] [d, e, b, a, c, f, g]\n", - "17 3.02 [(a, c)] [d, e, b, a, f, c, g]\n", - "18 3.37 [(a, d), (f, a), (f, d)] [e, d, b, a, f, c, g]\n", - "19 3.59 [(c, f)] [e, d, b, a, f, c, g]\n", - "20 3.66 [(b, d)] [e, b, d, a, f, c, g]\n", - "21 3.93 [(b, c)] [e, b, f, a, d, c, g]\n", - "22 4.29 [(c, d)] [e, f, b, a, c, d, g]\n", - "23 4.47 [(a, g)] [e, f, b, a, c, d, g]\n", - "24 4.50 [(c, d)] [e, f, b, a, c, d, g]\n", - "25 4.59 [(d, e)] [e, f, b, a, c, d, g]\n", - "26 4.72 [(b, g)] [f, e, b, a, c, d, g]\n", - "27 4.87 [(e, g)] [f, e, b, c, a, g, d]\n", - "28 5.41 [(c, e)] [f, c, e, b, g, a, d]\n", - "29 5.47 [(c, g)] [f, c, g, e, b, a, d]\n", - "30 5.82 [(a, b), (a, e), (b, e)] [g, f, c, a, b, e, d]\n", - "31 6.26 [(f, g)] [g, f, c, a, b, e, d]" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "All_Angles = Spiral.get_normals_dict( num_rounding_digits=2)\n", - "\n", - "# add pi + angle for all angles \n", - "All_Angles_2pi = {}\n", - "for key in All_Angles.keys():\n", - " All_Angles_2pi[round(key,2)] = All_Angles[key]\n", - " other_key = (key + np.pi) % 2*np.pi\n", - " other_key = round(other_key, 2)\n", - " All_Angles_2pi[other_key] = All_Angles[key]\n", - "\n", - "keys = list(All_Angles_2pi.keys())\n", - "keys.sort()\n", - "\n", - "pd_table = pd.DataFrame(columns=['angle', 'vertex_pair(s)_swapped', 'sorted_order_at_next_midpoint'])\n", - "pd_table['angle'] = keys\n", - "pd_table['vertex_pair(s)_swapped'] = [All_Angles_2pi[key] for key in keys]\n", - "\n", - "# sort the vertex pairs at the midpoint\n", - "\n", - "for i in range(len(keys)-1):\n", - " angle = np.average([keys[i], keys[i+1]])\n", - " sorted_order = Spiral.sort_vertices(angle)\n", - " pd_table.at[i, 'sorted_order_at_next_midpoint'] = sorted_order\n", - "\n", - "angle = np.average([keys[-1], keys[0]+2*np.pi])\n", - "sorted_order = Spiral.sort_vertices(angle)\n", - "pd_table.at[len(keys)-1, 'sorted_order_at_next_midpoint'] = sorted_order\n", - "\n", - "pd_table" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['a', 'b', 'c', 'd', 'e', 'f', 'g']" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "nodelist" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Modified version breaking the spiral" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Modified version with vertex added between C and D\n", - "\n", - "# Create the graph\n", - "G = EmbeddedGraph()\n", - "G.add_node('a', .5, 0)\n", - "G.add_node('b', 1, 1)\n", - "G.add_node('c', -1.5, -.5)\n", - "G.add_node('X', 1.5, -1)\n", - "G.add_node('d', 3, -2.5)\n", - "G.add_node('e',1.5,2)\n", - "G.add_node('f',-1.5,2)\n", - "G.add_node('g', -3,-3)\n", - "\n", - "nodelist = ['a', 'b', 'c','X', 'd', 'e', 'f', 'g']\n", - "for i in range(len(nodelist)-1):\n", - " G.add_edge(nodelist[i], nodelist[i+1])\n", - "\n", - "fig, ax = plt.subplots()\n", - "G.plot(ax = ax)\n", - "G.plot_angle_circle(ax = ax, edges_only=True)\n", - "# remove axes \n", - "ax.set_axis_off()" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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AngleSwapped VertsSorted list
00.00[(c, f), (X, e)]gcfabXed
10.25[(b, X)]gcfaXbed
20.32[(d, e)]gcfaXbed
30.52[(b, d)]gcfaXdbe
40.79[(a, X), (a, d), (f, a), (X, d), (f, X), (f, d)]gcdXafbe
51.15[(c, d)]gcdXafbe
61.19[(b, f)]gdcXafbe
71.41[(c, X)]gdXcabfe
81.57[(e, f)]gdXcabfe
91.65[(d, g)]gdXcabef
101.82[(a, c)]dgXacbef
111.99[(X, g)]dXgacbef
122.11[(b, c)]dXgacbef
132.27[(c, e)]dXgabecf
142.28[(a, g)]dXagbecf
152.36[(b, g)]dXabgecf
162.41[(e, g)]dXabegcf
172.60[(c, g)]dXabegcf
182.68[(a, b), (a, e), (b, e)]dXebacgf
192.85[(f, g)]dXebacgf
203.14[(c, f), (X, e)]dXebacfg
213.39[(b, X)]debXafcg
223.46[(d, e)]debXafcg
233.66[(b, d)]edbXafcg
243.93[(a, X), (a, d), (f, a), (X, d), (f, X), (f, d)]ebfaXdcg
254.29[(c, d)]ebfaXdcg
264.33[(b, f)]ebfaXcdg
274.55[(c, X)]efbacXdg
284.71[(e, f)]efbacXdg
294.79[(d, g)]febacXdg
304.96[(a, c)]febcaXgd
315.13[(X, g)]febcaXgd
325.25[(b, c)]febcagXd
335.41[(c, e)]fcebagXd
345.42[(a, g)]fcebagXd
355.50[(b, g)]fcegbaXd
365.55[(e, g)]fcegbaXd
375.74[(c, g)]fcgebaXd
385.82[(a, b), (a, e), (b, e)]fgcabeXd
395.99[(f, g)]fgcabeXd
\n", - "
" - ], - "text/plain": [ - " Angle Swapped Verts Sorted list\n", - "0 0.00 [(c, f), (X, e)] gcfabXed\n", - "1 0.25 [(b, X)] gcfaXbed\n", - "2 0.32 [(d, e)] gcfaXbed\n", - "3 0.52 [(b, d)] gcfaXdbe\n", - "4 0.79 [(a, X), (a, d), (f, a), (X, d), (f, X), (f, d)] gcdXafbe\n", - "5 1.15 [(c, d)] gcdXafbe\n", - "6 1.19 [(b, f)] gdcXafbe\n", - "7 1.41 [(c, X)] gdXcabfe\n", - "8 1.57 [(e, f)] gdXcabfe\n", - "9 1.65 [(d, g)] gdXcabef\n", - "10 1.82 [(a, c)] dgXacbef\n", - "11 1.99 [(X, g)] dXgacbef\n", - "12 2.11 [(b, c)] dXgacbef\n", - "13 2.27 [(c, e)] dXgabecf\n", - "14 2.28 [(a, g)] dXagbecf\n", - "15 2.36 [(b, g)] dXabgecf\n", - "16 2.41 [(e, g)] dXabegcf\n", - "17 2.60 [(c, g)] dXabegcf\n", - "18 2.68 [(a, b), (a, e), (b, e)] dXebacgf\n", - "19 2.85 [(f, g)] dXebacgf\n", - "20 3.14 [(c, f), (X, e)] dXebacfg\n", - "21 3.39 [(b, X)] debXafcg\n", - "22 3.46 [(d, e)] debXafcg\n", - "23 3.66 [(b, d)] edbXafcg\n", - "24 3.93 [(a, X), (a, d), (f, a), (X, d), (f, X), (f, d)] ebfaXdcg\n", - "25 4.29 [(c, d)] ebfaXdcg\n", - "26 4.33 [(b, f)] ebfaXcdg\n", - "27 4.55 [(c, X)] efbacXdg\n", - "28 4.71 [(e, f)] efbacXdg\n", - "29 4.79 [(d, g)] febacXdg\n", - "30 4.96 [(a, c)] febcaXgd\n", - "31 5.13 [(X, g)] febcaXgd\n", - "32 5.25 [(b, c)] febcagXd\n", - "33 5.41 [(c, e)] fcebagXd\n", - "34 5.42 [(a, g)] fcebagXd\n", - "35 5.50 [(b, g)] fcegbaXd\n", - "36 5.55 [(e, g)] fcegbaXd\n", - "37 5.74 [(c, g)] fcgebaXd\n", - "38 5.82 [(a, b), (a, e), (b, e)] fgcabeXd\n", - "39 5.99 [(f, g)] fgcabeXd" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "All_Angles = G.get_normals_dict(num_rounding_digits=2, opposites = True)\n", - "keys = list(All_Angles.keys())\n", - "keys.sort()\n", - "\n", - "pd_table = pd.DataFrame(columns = ['Angle', 'Swapped Verts', 'Sorted list'])\n", - "pd_table['Angle'] = keys\n", - "pd_table['Swapped Verts'] = [All_Angles[key] for key in keys]\n", - "\n", - "\n", - "\n", - "pd_table.sort_values(by='Angle', inplace=True)\n", - "pd_table['Sorted list'] = [''.join(G.sort_vertices(key)) for key in keys]\n", - "pd_table.head(100)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Simplified version from Arya paper " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Recreating the sprial example from Arya \n", - "\n", - "# Create the graph\n", - "Spiral2 = EmbeddedGraph()\n", - "# Spiral2.add_node('a', .5, 0)\n", - "Spiral2.add_node('b', 1, 1)\n", - "Spiral2.add_node('c', -1.5, -.5)\n", - "Spiral2.add_node('d', 3, -2.5)\n", - "Spiral2.add_node('e',1.5,2)\n", - "Spiral2.add_node('f',-1.5,2)\n", - "Spiral2.add_node('g', -3,-3)\n", - "\n", - "nodelist = list(Spiral2.nodes())\n", - "nodelist.sort()\n", - "for i in range(len(nodelist)-1):\n", - " Spiral2.add_edge(nodelist[i], nodelist[i+1])\n", - "\n", - "fig,ax = plt.subplots()\n", - "Spiral2.plot(ax = ax)\n", - "Spiral2.plot_angle_circle(ax = ax, edges_only=True)\n", - "# remove axes \n", - "ax.set_axis_off()\n", - "\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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AngleSwapped VertsSorted list
00.00[(c, f)]gcfbed
10.32[(d, e)]gcfbed
20.52[(b, d)]gcfdbe
30.79[(d, f)]gcdfbe
41.15[(c, d)]gcdfbe
51.19[(b, f)]gdcfbe
61.57[(e, f)]gdcbfe
71.65[(d, g)]gdcbef
82.11[(b, c)]dgcbef
92.27[(c, e)]dgbecf
102.36[(b, g)]dbgecf
112.41[(e, g)]dbegcf
122.60[(c, g)]dbegcf
132.68[(b, e)]debcgf
142.85[(f, g)]debcgf
153.14[(c, f)]debcfg
163.46[(d, e)]debfcg
173.66[(b, d)]edbfcg
183.93[(d, f)]ebfdcg
194.29[(c, d)]ebfdcg
204.33[(b, f)]ebfcdg
214.71[(e, f)]efbcdg
224.79[(d, g)]febcdg
235.25[(b, c)]febcgd
245.41[(c, e)]fcebgd
255.50[(b, g)]fcegbd
265.55[(e, g)]fcegbd
275.74[(c, g)]fcgebd
285.82[(b, e)]fgcbed
295.99[(f, g)]fgcbed
\n", - "
" - ], - "text/plain": [ - " Angle Swapped Verts Sorted list\n", - "0 0.00 [(c, f)] gcfbed\n", - "1 0.32 [(d, e)] gcfbed\n", - "2 0.52 [(b, d)] gcfdbe\n", - "3 0.79 [(d, f)] gcdfbe\n", - "4 1.15 [(c, d)] gcdfbe\n", - "5 1.19 [(b, f)] gdcfbe\n", - "6 1.57 [(e, f)] gdcbfe\n", - "7 1.65 [(d, g)] gdcbef\n", - "8 2.11 [(b, c)] dgcbef\n", - "9 2.27 [(c, e)] dgbecf\n", - "10 2.36 [(b, g)] dbgecf\n", - "11 2.41 [(e, g)] dbegcf\n", - "12 2.60 [(c, g)] dbegcf\n", - "13 2.68 [(b, e)] debcgf\n", - "14 2.85 [(f, g)] debcgf\n", - "15 3.14 [(c, f)] debcfg\n", - "16 3.46 [(d, e)] debfcg\n", - "17 3.66 [(b, d)] edbfcg\n", - "18 3.93 [(d, f)] ebfdcg\n", - "19 4.29 [(c, d)] ebfdcg\n", - "20 4.33 [(b, f)] ebfcdg\n", - "21 4.71 [(e, f)] efbcdg\n", - "22 4.79 [(d, g)] febcdg\n", - "23 5.25 [(b, c)] febcgd\n", - "24 5.41 [(c, e)] fcebgd\n", - "25 5.50 [(b, g)] fcegbd\n", - "26 5.55 [(e, g)] fcegbd\n", - "27 5.74 [(c, g)] fcgebd\n", - "28 5.82 [(b, e)] fgcbed\n", - "29 5.99 [(f, g)] fgcbed" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "All_Angles = Spiral2.get_normals_dict(num_rounding_digits=2, opposites = True)\n", - "keys = list(All_Angles.keys())\n", - "keys.sort()\n", - "\n", - "pd_table = pd.DataFrame(columns = ['Angle', 'Swapped Verts', 'Sorted list'])\n", - "pd_table['Angle'] = keys\n", - "pd_table['Swapped Verts'] = [All_Angles[key] for key in keys]\n", - "\n", - "\n", - "\n", - "pd_table.sort_values(by='Angle', inplace=True)\n", - "pd_table['Sorted list'] = [''.join(Spiral2.sort_vertices(key)) for key in keys]\n", - "pd_table.head(100)" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Modified version with vertex added between C and D\n", - "\n", - "# Create the graph\n", - "G = EmbeddedGraph()\n", - "# G.add_node('a', .5, 0)\n", - "G.add_node('b', 1, 1)\n", - "G.add_node('c', -1.5, -.5)\n", - "G.add_node('X', 1.5, -1)\n", - "G.add_node('d', 3, -2.5)\n", - "G.add_node('e',1.5,2)\n", - "G.add_node('f',-1.5,2)\n", - "G.add_node('g', -3,-3)\n", - "\n", - "nodelist = ['b', 'c','X', 'd', 'e', 'f', 'g']\n", - "for i in range(len(nodelist)-1):\n", - " G.add_edge(nodelist[i], nodelist[i+1])\n", - "\n", - "fig, ax = plt.subplots()\n", - "G.plot(ax = ax)\n", - "G.plot_angle_circle(ax = ax, edges_only=True)\n", - "# remove axes \n", - "ax.set_axis_off()" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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AngleSwapped VertsSorted list
00.00[(c, f), (X, e)]gcfbed
10.25[(b, X)]gcfbed
20.32[(d, e)]gcfbed
30.52[(b, d)]gcfdbe
40.79[(X, d), (f, X), (f, d)]gcdfbe
51.15[(c, d)]gcdfbe
61.19[(b, f)]gdcfbe
71.41[(c, X)]gdcbfe
81.57[(e, f)]gdcbfe
91.65[(d, g)]gdcbef
101.99[(X, g)]dgcbef
112.11[(b, c)]dgcbef
122.27[(c, e)]dgbecf
132.36[(b, g)]dbgecf
142.41[(e, g)]dbegcf
152.60[(c, g)]dbegcf
162.68[(b, e)]debcgf
172.85[(f, g)]debcgf
183.14[(c, f), (X, e)]debcfg
193.39[(b, X)]debfcg
203.46[(d, e)]debfcg
213.66[(b, d)]edbfcg
223.93[(X, d), (f, X), (f, d)]ebfdcg
234.29[(c, d)]ebfdcg
244.33[(b, f)]ebfcdg
254.55[(c, X)]efbcdg
264.71[(e, f)]efbcdg
274.79[(d, g)]febcdg
285.13[(X, g)]febcgd
295.25[(b, c)]febcgd
305.41[(c, e)]fcebgd
315.50[(b, g)]fcegbd
325.55[(e, g)]fcegbd
335.74[(c, g)]fcgebd
345.82[(b, e)]fgcbed
355.99[(f, g)]fgcbed
\n", - "
" - ], - "text/plain": [ - " Angle Swapped Verts Sorted list\n", - "0 0.00 [(c, f), (X, e)] gcfbed\n", - "1 0.25 [(b, X)] gcfbed\n", - "2 0.32 [(d, e)] gcfbed\n", - "3 0.52 [(b, d)] gcfdbe\n", - "4 0.79 [(X, d), (f, X), (f, d)] gcdfbe\n", - "5 1.15 [(c, d)] gcdfbe\n", - "6 1.19 [(b, f)] gdcfbe\n", - "7 1.41 [(c, X)] gdcbfe\n", - "8 1.57 [(e, f)] gdcbfe\n", - "9 1.65 [(d, g)] gdcbef\n", - "10 1.99 [(X, g)] dgcbef\n", - "11 2.11 [(b, c)] dgcbef\n", - "12 2.27 [(c, e)] dgbecf\n", - "13 2.36 [(b, g)] dbgecf\n", - "14 2.41 [(e, g)] dbegcf\n", - "15 2.60 [(c, g)] dbegcf\n", - "16 2.68 [(b, e)] debcgf\n", - "17 2.85 [(f, g)] debcgf\n", - "18 3.14 [(c, f), (X, e)] debcfg\n", - "19 3.39 [(b, X)] debfcg\n", - "20 3.46 [(d, e)] debfcg\n", - "21 3.66 [(b, d)] edbfcg\n", - "22 3.93 [(X, d), (f, X), (f, d)] ebfdcg\n", - "23 4.29 [(c, d)] ebfdcg\n", - "24 4.33 [(b, f)] ebfcdg\n", - "25 4.55 [(c, X)] efbcdg\n", - "26 4.71 [(e, f)] efbcdg\n", - "27 4.79 [(d, g)] febcdg\n", - "28 5.13 [(X, g)] febcgd\n", - "29 5.25 [(b, c)] febcgd\n", - "30 5.41 [(c, e)] fcebgd\n", - "31 5.50 [(b, g)] fcegbd\n", - "32 5.55 [(e, g)] fcegbd\n", - "33 5.74 [(c, g)] fcgebd\n", - "34 5.82 [(b, e)] fgcbed\n", - "35 5.99 [(f, g)] fgcbed" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "All_Angles = G.get_normals_dict(num_rounding_digits=2, opposites = True)\n", - "keys = list(All_Angles.keys())\n", - "keys.sort()\n", - "\n", - "pd_table = pd.DataFrame(columns = ['Angle', 'Swapped Verts', 'Sorted list'])\n", - "pd_table['Angle'] = keys\n", - "pd_table['Swapped Verts'] = [All_Angles[key] for key in keys]\n", - "\n", - "\n", - "\n", - "pd_table.sort_values(by='Angle', inplace=True)\n", - "pd_table['Sorted list'] = [''.join(Spiral2.sort_vertices(key)) for key in keys]\n", - "pd_table.head(100)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "base", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.7" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Extra_Notebooks/tutorial_cw.ipynb b/Extra_Notebooks/tutorial_cw.ipynb deleted file mode 100644 index 51df1ee..0000000 --- a/Extra_Notebooks/tutorial_cw.ipynb +++ /dev/null @@ -1,361 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Tutorial: ECT for CW complexes\n", - "\n", - "This tutorial walks you through how to build a CW complex with the `EmbeddedCW` class, and then use the `ECT` class to compute the Euler characteristic transform.\\n\\n**Note**: This tutorial uses `EmbeddedCW`, which is now an alias for the unified `EmbeddedComplex` class. The new unified class supports arbitrary dimensional cells beyond just 2-cells (faces). See `Tutorial-EmbeddedComplex.ipynb` for comprehensive coverage of the new capabilities." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from ect import ECT, EmbeddedCW\n", - "from ect.utils.examples import create_example_cw\n", - "import numpy as np\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The CW complex class extends the `EmbeddedGraph` functionality with the ability to add faces (2-cells). With the new unified `EmbeddedComplex` class, you can now add cells of any dimension!\\n\\n**Face/Cell Addition Methods:**\\n- `add_face(vertices)` - Add 2-cells (backward compatible)\\n- `add_cell(vertices, dim=k)` - Add k-cells of any dimension (new!)\\n\\nFaces are added by passing in a list of vertices. We generally assume that these vertices form a cycle bounding an empty region, and that all boundary edges are already included in the complex." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "K = EmbeddedCW()\n", - "\n", - "# Add vertices with coordinates\n", - "K.add_node(\"A\", [0, 0])\n", - "K.add_node(\"B\", [1, 0])\n", - "K.add_node(\"C\", [1, 1])\n", - "K.add_node(\"D\", [0, 1])\n", - "\n", - "# Add edges to form a square\n", - "K.add_edges_from([(\"A\", \"B\"), (\"B\", \"C\"), (\"C\", \"D\"), (\"D\", \"A\")])\n", - "\n", - "# Add the square face\n", - "K.add_face([\"A\", \"B\", \"C\", \"D\"])\n", - "\n", - "K.center_coordinates()\n", - "K.plot()\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " Just to have something a bit more interesting, let's make a more complicated example that's built into the class." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "K = create_example_cw()\n", - "K.plot(bounding_circle=True)\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " As with the `EmbeddedGraph` class, we can initialize the `ECT` class by deciding how many directions and how many thresholds to use." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "ect = ECT(num_dirs=100, num_thresh=80)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " Then we can compute the ECC for a single direction. In this case, the $x$-axis will be computed for the `num_thresh=80` stopping points in the interval $[-1.2r,1.2r]$ where $r$ is the minimum bounding radius for the input complex." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "OMP: Info #276: omp_set_nested routine deprecated, please use omp_set_max_active_levels instead.\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "override_bound_radius = 1.2 * K.get_bounding_radius()\n", - "result = ect.calculate(K, theta=0, override_bound_radius=override_bound_radius)\n", - "result.plot();\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " But of course it's easier to see this in a plot. This command calculates the ECC and immediately plots it." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " Similarly, we can compute the ECT and return the matrix. We make sure to internally set the bounding radius to use to control the $y$ axis of the plot." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "result = ect.calculate(K, override_bound_radius=override_bound_radius)\n", - "result.plot()\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " We can also look at the Smooth ECT:" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Calculate SECT and plot\n", - "smooth = result.smooth()\n", - "smooth.plot()\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " We can also compute the ECT in 3D." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import numpy as np\n", - "\n", - "vertices = [\n", - " (letter, coordinates) for letter, coordinates in zip(\"abcde\", np.random.randn(5, 3))\n", - "]\n", - "edges = [(\"a\", \"b\"), (\"a\", \"c\"), (\"a\", \"d\"), (\"b\", \"c\"), (\"b\", \"d\"), (\"c\", \"d\")]\n", - "faces = [\n", - " (\"a\", \"b\", \"c\"),\n", - " (\"a\", \"b\", \"d\"),\n", - " (\"a\", \"c\", \"d\"),\n", - " (\"b\", \"c\", \"d\"),\n", - " (\"a\", \"b\", \"c\", \"d\"),\n", - "]\n", - "K = EmbeddedCW()\n", - "K.add_nodes_from(vertices)\n", - "K.add_edges_from(edges)\n", - "\n", - "K.add_faces_from(faces)\n", - "K.plot(bounding_circle=True)\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "ect = ECT(num_dirs=100, num_thresh=80)\n", - "result = ect.calculate(K)\n", - "result.plot()\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "dataexp", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Extra_Notebooks/tutorial_graph.ipynb b/Extra_Notebooks/tutorial_graph.ipynb deleted file mode 100644 index 4cf0fe2..0000000 --- a/Extra_Notebooks/tutorial_graph.ipynb +++ /dev/null @@ -1,560 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Tutorial: ECT for Embedded Graphs\n", - "\n", - "This tutorial demonstrates how to use the `ect` package to compute the Euler Characteristic Transform (ECT) for embedded graphs.\n", - "\n", - "**Note**: This tutorial uses `EmbeddedGraph`, which is now an alias for the unified `EmbeddedComplex` class. All functionality shown here works identically, but `EmbeddedComplex` offers additional features like arbitrary dimensional cells. See the `Tutorial-EmbeddedComplex.ipynb` for the full capabilities." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from ect import ECT, EmbeddedGraph\n", - "\n", - "import numpy as np\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Basic Usage\n", - "\n", - "First, let's create a simple graph. The `EmbeddedGraph` class (now unified with `EmbeddedComplex`) allows you to create graphs with vertices embedded in Euclidean space." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Construct an example graph\n", - "# Note that this is the same graph that is returned by:\n", - "# G = create_example_graph()\n", - "\n", - "G = EmbeddedGraph()\n", - "\n", - "G.add_node(\"A\", [1, 2])\n", - "G.add_node(\"B\", [3, 4])\n", - "G.add_node(\"C\", [5, 7])\n", - "G.add_node(\"D\", [3, 6])\n", - "G.add_node(\"E\", [4, 3])\n", - "G.add_node(\"F\", [4, 5])\n", - "\n", - "G.add_edge(\"A\", \"B\")\n", - "G.add_edge(\"B\", \"C\")\n", - "G.add_edge(\"B\", \"D\")\n", - "G.add_edge(\"B\", \"E\")\n", - "G.add_edge(\"C\", \"D\")\n", - "G.add_edge(\"E\", \"F\")\n", - "\n", - "G.plot()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The embedded graph class inherits from the networkx graph class with additional attributes for spatial embedding. The unified `EmbeddedComplex` class provides:\\n\\n- `coord_matrix`: N×D matrix of vertex coordinates\\n- `node_list`: Ordered list of vertex identifiers \\n- `cells`: Dictionary storing k-cells by dimension (new feature)\\n\\nThe coordinates of all vertices can be accessed using the `coord_matrix` attribute." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[1., 2.],\n", - " [3., 4.],\n", - " [5., 7.],\n", - " [3., 6.],\n", - " [4., 3.],\n", - " [4., 5.]])" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "G.coord_matrix\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " It's often useful to center the graph, so you can use the `center_coordinates` method shift the graph to have the average of the vertex coordinates be 0. Note that this does overwrite the coordinates of the points." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[-2.33333333 -2.5 ]\n", - " [-0.33333333 -0.5 ]\n", - " [ 1.66666667 2.5 ]\n", - " [-0.33333333 1.5 ]\n", - " [ 0.66666667 -1.5 ]\n", - " [ 0.66666667 0.5 ]]\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "G.center_coordinates(center_type=\"mean\")\n", - "print(G.coord_matrix)\n", - "G.plot()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " To get a bounding radius we can use the `get_bounding_radius` method." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The radius of bounding circle centered at the origin is 3.2015621187164243\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# This is actually getting the radius\n", - "r = G.get_bounding_radius()\n", - "print(f\"The radius of bounding circle centered at the origin is {r}\")\n", - "\n", - "# plotting the graph with it's bounding circle of radius r.\n", - "G.plot(bounding_circle=True)\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " We can also rescale our graph to have unit radius using `scale_coordinates`" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The radius of bounding circle centered at the origin is 1.0\n" - ] - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "G.scale_coordinates(radius=1)\n", - "G.plot(bounding_circle=True)\n", - "\n", - "r = G.get_bounding_radius(center_type=\"origin\")\n", - "print(f\"The radius of bounding circle centered at the origin is {r}\")\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "myect = ECT(num_dirs=16, num_thresh=20)\n", - "\n", - "# The ECT object will automatically create directions when needed\n", - "print(f\"Number of directions: {myect.num_dirs}\")\n", - "print(f\"Number of thresholds: {myect.num_thresh}\")\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " We can override the bounding radius as follows. Note that some methods will automatically use the bounding radius of the input `G` if not already set. I'm choosing the radius to be a bit bigger than the bounding radius of `G` to make some better pictures." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "custom_bound_radius = 1.2 * G.get_bounding_radius()\n", - "result = myect.calculate(G, override_bound_radius=custom_bound_radius)\n", - "\n", - "print(f\"Thresholds chosen are: {myect.thresholds}\")\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " If we want the Euler characteristic curve for a fixed direction, we use the `calculate` function with a specific angle. This returns an ECTResult object containing the computed values." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "result = myect.calculate(G, theta=np.pi / 2)\n", - "print(f\"ECT values for direction pi/2: {result[0]}\")\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " To calculate the full ECT, we call the `calculate` method without specifying theta. The result returns the ECT matrix and associated metadata." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "result = myect.calculate(G)\n", - "\n", - "print(f\"ECT matrix shape: {result.shape}\")\n", - "print(f\"Number of directions: {myect.num_dirs}\")\n", - "print(f\"Number of thresholds: {myect.num_thresh}\")\n", - "\n", - "# We can plot the result matrix\n", - "result.plot()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " ## SECT\n", - "\n", - "\n", - "\n", - " The Smooth Euler Characteristic Transform (SECT) can be calculated from the ECT. Fix a radius $R$ bounding the graph. The average ECT in a direction $\\omega$ defined on function values $[-R,R]$ is given by\n", - "\n", - " $$\\overline{\\text{ECT}_\\omega} = \\frac{1}{2R} \\int_{t = -R}^{R} \\chi(g_\\omega^{-1}(-\\infty,t]) \\; dt. $$\n", - "\n", - " Then the SECT is defined by\n", - "\n", - " $$\n", - "\n", - " \\begin{matrix}\n", - "\n", - " \\text{SECT}(G): & \\mathbb{S}^1 & \\to & \\text{Func}(\\mathbb{R}, \\mathbb{Z})\\\\\n", - "\n", - " & \\omega & \\mapsto & \\{ t \\mapsto \\int_{-R}^t \\left( \\chi(g_\\omega^{-1}(-\\infty,a]) -\\overline{\\text{ECT}_\\omega}\\right)\\:da \\}\n", - "\n", - " \\end{matrix}\n", - "\n", - " $$" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " The SECT can be computed from the ECT result:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "sect = result.smooth()\n", - "\n", - "sect.plot()\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " ## ECT for higher dimensions\n", - "\n", - "\n", - "\n", - " The `ECT` class can also be used for higher dimensional graphs." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "# generate a 3d graph\n", - "list_3d = [\n", - " (\"A\", [0, 0, 0]),\n", - " (\"B\", [1, 0, 0]),\n", - " (\"C\", [0, 1, 0]),\n", - " (\"D\", [1, 1, 0]),\n", - " (\"E\", [0, 0, 1]),\n", - " (\"F\", [1, 0, 1]),\n", - " (\"G\", [0, 1, 1]),\n", - " (\"H\", [1, 1, 1]),\n", - "]\n", - "graph_3d = EmbeddedGraph()\n", - "graph_3d.add_nodes_from(list_3d)\n", - "\n", - "# add edges\n", - "graph_3d.add_edge(\"A\", \"B\")\n", - "graph_3d.add_edge(\"B\", \"C\")\n", - "graph_3d.add_edge(\"C\", \"D\")\n", - "graph_3d.add_edge(\"D\", \"E\")\n", - "graph_3d.add_edge(\"E\", \"F\")\n", - "graph_3d.add_edge(\"F\", \"G\")\n", - "graph_3d.add_edge(\"G\", \"H\")\n", - "graph_3d.add_edge(\"H\", \"A\")\n", - "\n", - "# plot the graph\n", - "graph_3d.plot()\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " lets center the graph" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "graph_3d.center_coordinates(center_type=\"mean\")\n", - "graph_3d.plot()\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " Now we can compute the ECT of the 3d graph." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "ect_3d = ECT(num_dirs=16, num_thresh=20)\n", - "result_3d = ect_3d.calculate(graph_3d)\n", - "result_3d.plot()\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " Note that the each of the directions are appended in a list for the ECT result, so we won't see the same periodic behavior as in the 2d case.\n", - "\n", - " ECT results inherit from ndarrays but they store the associated directions and thresholds." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "result_3d.directions.vectors\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "result_3d.thresholds\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " We can also define custom directions and thresholds for the ECT in case we need finer control. We use random sampling from the unit sphere for the directions and cosine sampling for the thresholds." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from ect import Directions\n", - "\n", - "directions = Directions.random(16, dim=3)\n", - "thresholds = np.cos(np.linspace(0, np.pi, 20))\n", - "ect_3d = ECT(directions=directions, thresholds=thresholds)\n", - "result_3d = ect_3d.calculate(graph_3d)\n", - "result_3d.plot()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# another example sampling from the half sphere\n", - "sample_size = 100\n", - "theta = np.linspace(0, np.pi / 2, sample_size) # Only go up to pi/2 for half sphere\n", - "phi = np.linspace(0, 2 * np.pi, sample_size)\n", - "theta, phi = np.meshgrid(theta, phi)\n", - "\n", - "# Flatten the meshgrid arrays and create vectors\n", - "half_sphere_vectors = np.column_stack(\n", - " [\n", - " np.sin(theta.flatten()) * np.cos(phi.flatten()),\n", - " np.sin(theta.flatten()) * np.sin(phi.flatten()),\n", - " np.cos(theta.flatten()),\n", - " ]\n", - ")\n", - "\n", - "# Normalize the vectors\n", - "half_sphere_vectors = half_sphere_vectors / np.linalg.norm(\n", - " half_sphere_vectors, axis=1, keepdims=True\n", - ")\n", - "\n", - "directions = Directions.from_vectors(half_sphere_vectors)\n", - "print(f\"Number of direction vectors: {len(directions)}\")\n", - "ect_3d = ECT(directions=directions, num_thresh=20) # Reduced number of thresholds\n", - "result_3d = ect_3d.calculate(graph_3d)\n", - "result_3d.plot()\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "dataexp", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Makefile b/Makefile index d941e22..0d15c22 100644 --- a/Makefile +++ b/Makefile @@ -28,6 +28,12 @@ html: mkdir docs sphinx-build -b html doc_source docs +html-local: + # Running sphinx-build to build html files in a local docs folder + rm -rf docs_local + mkdir docs_local + sphinx-build -b html doc_source docs_local + benchmark: python benchmarks/run_benchmarks.py diff --git a/doc_source/conf.py b/doc_source/conf.py index b1ce869..248cdb5 100644 --- a/doc_source/conf.py +++ b/doc_source/conf.py @@ -10,8 +10,10 @@ # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. # +# Add the src directory to sys.path so Sphinx can find ect.embed_complex import os import sys +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..', 'src'))) sys.path.insert(0, os.path.abspath('.')) sys.path.insert(0, os.path.join(os.path.dirname(__file__),'..')) sys.path.insert(0, os.path.join(os.path.dirname(__file__),'..', 'ect' )) @@ -76,7 +78,7 @@ 'canonical_url': '', 'analytics_id': 'UA-XXXXXXX-1', # Provided by Google in your dashboard 'logo_only': False, - 'display_version': True, + # 'display_version': True, # Removed because it is unsupported 'prev_next_buttons_location': 'bottom', 'style_external_links': True, 'style_nav_header_background': '#cececf', @@ -100,4 +102,4 @@ # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". -html_static_path = ['_static'] \ No newline at end of file +# html_static_path = ['_static'] \ No newline at end of file diff --git a/doc_source/contributing.rst b/doc_source/contributing.rst index ceae78c..c615dd3 100644 --- a/doc_source/contributing.rst +++ b/doc_source/contributing.rst @@ -33,11 +33,11 @@ The `ect` package uses the Sphinx documentation system for generating documentat - First, include docstrings in the code which will be autogenerated into the documentation. When in doubt, write too much. - Second, write documentation in the `doc_source` directory using the reStructuredText format. This package also supports writing files in markdown, although there are some issues when dealing with autogenerated content so it's a bit of a mix at the moment. Note that when the documentation is generated, everything in the `docs` folder is deleted and overwritten, so do not do your work in there, it will be lost! -Assuming everything is set up correctly (see the installation instructions in the main documentation), you can generate the documentation by running the following command from the top level folder:: +Assuming everything is set up correctly (see the installation instructions in the main documentation), you can generate the documentation on your local machine by running the following command from the top level folder:: - make html + make html-local -This will generate the documentation in the ``docs`` directory. You can view the documentation by opening the ``docs/index.html`` file in your browser. +This will generate the documentation in the ``docs_local`` directory. You can view the documentation by opening the ``docs_local/index.html`` file in your browser. Do not push anything in the ``docs_local`` folder to the repository, it is only for local viewing; the ``docs`` folder is generated automatically when changes in ``doc_source`` are pushed to the ``main`` branch. An example of a docstring for a function is given below. Note the use of indentation since rst is picky about it:: @@ -89,7 +89,7 @@ If you would like to fix an issue and you are a contributor to the project, plea - Note that in order for the `pip install` command to work, the version number in the `pyproject.toml` file must be updated. - You should also make sure to update the version number to match in the ``doc_source/conf.py`` file. This will ensure that the documentation is updated with the correct version number. -- Be sure to run ``make all`` before committing to ensure that the code is cleaned, the documentation is up to date, and the tests all pass. +- Be sure to run ``make all`` before committing to ensure that the code is cleaned, the documentation compiles properly, and the tests all pass. If you are not a contributor, you will need to fork the code and create a pull request from your fork. Note that all pull requests need to be approved by Liz Munch before they can be merged. diff --git a/doc_source/embed_complex.md b/doc_source/embed_complex.md index e9b0001..4d7a733 100644 --- a/doc_source/embed_complex.md +++ b/doc_source/embed_complex.md @@ -41,6 +41,6 @@ K.add_cell(["A", "B", "C"], dim=2) ```{eval-rst} .. automodule:: ect.embed_complex :members: - :show-inheritance: :undoc-members: + :no-index: ``` \ No newline at end of file diff --git a/doc_source/notebooks/Tutorial-EmbeddedComplex.ipynb b/doc_source/notebooks/Tutorial-EmbeddedComplex.ipynb index 18945fd..0f9ba12 100644 --- a/doc_source/notebooks/Tutorial-EmbeddedComplex.ipynb +++ b/doc_source/notebooks/Tutorial-EmbeddedComplex.ipynb @@ -14,9 +14,20 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[1;31mRunning cells with '.conda-ect-3-11 (Python 3.11.13)' requires the ipykernel package.\n", + "\u001b[1;31mInstall 'ipykernel' into the Python environment. \n", + "\u001b[1;31mCommand: 'conda install -n .conda-ect-3-11 ipykernel --update-deps --force-reinstall'" + ] + } + ], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", @@ -37,29 +48,9 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of nodes: 3\n", - "Number of edges: 3\n", - "Embedding dimension: 2\n" - ] - } - ], + "outputs": [], "source": [ "K = EmbeddedComplex()\n", "\n", @@ -92,29 +83,9 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of 2-cells (faces): 1\n", - "Faces: [('A', 'B', 'C')]\n", - "Internal cells dictionary: {2: [(0, 1, 2)]}\n" - ] - } - ], + "outputs": [], "source": [ "K.add_face(['A', 'B', 'C'])\n", "\n", @@ -139,30 +110,9 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Dimension 2: 4 cells\n", - "Dimension 3: 1 cells\n", - "\n", - "Total embedding dimension: 3\n" - ] - } - ], + "outputs": [], "source": [ "# Create a 3D tetrahedron with 0, 1, 2, and 3-cells\n", "K_tetra = EmbeddedComplex()\n", @@ -219,39 +169,9 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ECT result shape: (8, 20)\n", - "Directions: 8 directions in 3D\n", - "Thresholds: 20 threshold values\n" - ] - }, - { - "data": { - "image/png": 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# Compute ECT for the tetrahedron\n", "ect = ECT(num_dirs=8, num_thresh=20)\n", @@ -287,42 +207,9 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Edge Interior Validation: Vertex 4 lies on edge interior\n", - "adding intersecting edge failed\n", - "4D Simplex Cell Counts:\n", - " 1-cells: 1\n", - " 2-cells: 4\n", - " 3-cells: 1\n" - ] - }, - { - "data": { - "image/png": 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "K_tetra.enable_embedding_validation()\n", "#add intersecting edge\n", @@ -359,7 +246,7 @@ ], "metadata": { "kernelspec": { - "display_name": "dataexp", + "display_name": ".conda-ect-3-11", "language": "python", "name": "python3" }, @@ -373,7 +260,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.8" + "version": "3.11.13" } }, "nbformat": 4, diff --git a/doc_source/notebooks/Tutorial-ExactECT.ipynb b/doc_source/notebooks/Tutorial-ExactECT.ipynb deleted file mode 100644 index 1870585..0000000 --- a/doc_source/notebooks/Tutorial-ExactECT.ipynb +++ /dev/null @@ -1,179 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Tutorial for exact ECT computation \n", - "\n", - "*Warning: This is a work in progress. Proceed at your own risk.*\n", - "\n", - "The goal of this section is so show available tools for exact computation of the ECT. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": "from ect import ECT, EmbeddedComplex, create_example_graph\n\nimport matplotlib.pyplot as plt\nfrom matplotlib.patches import Circle\nimport numpy as np\nimport networkx as nx\n\n# Note: EmbeddedGraph and EmbeddedCW are now unified into EmbeddedComplex\n# For backward compatibility, you can still use:\n# from ect import EmbeddedGraph, EmbeddedCW" - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": "We can use the `EmbeddedComplex` class (which unifies the old `EmbeddedGraph` and `EmbeddedCW` classes) to find the angle normal to any pair of vertices in the graph, whether or not there is a connecting edge. Setting `angle_labels_circle=True` in the plotting command will try to draw these on the circle. Note that this doesn't tend to do well for large inputs, but can be helpful for small examples." - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": "# Super simple graph using the unified EmbeddedComplex class\nG = EmbeddedComplex()\nG.add_node('A', 0,0)\nG.add_node('B', 1,0)\nG.add_node('C', 2,1)\nG.add_node('D', 1,2)\nG.add_edge('A', 'B')\nG.add_edge('B', 'D')\nG.add_edge('D', 'C')\n\nfig, ax = plt.subplots()\nG.plot(ax = ax)\nG.plot_angle_circle(ax = ax)" - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "G = create_example_graph(centered=True)\n", - "G.rescale_to_unit_disk()\n", - "\n", - "\n", - "fig, ax = plt.subplots()\n", - "G.plot(ax = ax)\n", - "G.plot_angle_circle(ax = ax)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can extract the information directly for use in computation. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": "# If return type is `matrix`, the function returns the matrix of angles and the labels of the angles in the order of the rows/columns in the matrix \nM,Labels = G.get_normal_angle_matrix() # Updated method name\nprint(M)\n\nplt.matshow(M)\nplt.xticks(range(len(Labels)), Labels)\nplt.yticks(range(len(Labels)), Labels)\nplt.colorbar()" - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This can also be returned as a dictionary, with keys given by angles (note the negative angle is not repeated), and value a list of the pairs of vertices associated. Note that in the case of more than one pair of vertices having the same normal angle, it is given as a list of all pairs. " - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{5.497787143782138: [('A', 'B'), ('A', 'F'), ('B', 'F')],\n", - " 5.608444364956034: [('A', 'C')],\n", - " 5.81953769817878: [('A', 'D'), ('F', 'C')],\n", - " 5.034139534781332: [('A', 'E')],\n", - " 5.695182703632018: [('B', 'C')],\n", - " 0.0: [('B', 'D'), ('E', 'F')],\n", - " 3.9269908169872414: [('B', 'E'), ('D', 'F')],\n", - " 2.0344439357957027: [('C', 'D')],\n", - " 2.896613990462929: [('C', 'E')],\n", - " 3.4633432079864352: [('D', 'E')]}" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "angles_dict = G.get_normals_dict()\n", - "angles_dict" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can also get it to return the dictionary with rounded values, as well as to have it include all the opposite angles. " - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{5.5: [('A', 'B'), ('A', 'F'), ('B', 'F')],\n", - " 5.61: [('A', 'C')],\n", - " 5.82: [('A', 'D'), ('F', 'C')],\n", - " 5.03: [('A', 'E')],\n", - " 5.7: [('B', 'C')],\n", - " 0.0: [('B', 'D'), ('E', 'F')],\n", - " 3.93: [('B', 'E'), ('D', 'F')],\n", - " 2.03: [('C', 'D')],\n", - " 2.9: [('C', 'E')],\n", - " 3.46: [('D', 'E')],\n", - " 2.36: [('A', 'B'), ('A', 'F'), ('B', 'F')],\n", - " 2.47: [('A', 'C')],\n", - " 2.68: [('A', 'D'), ('F', 'C')],\n", - " 1.89: [('A', 'E')],\n", - " 2.56: [('B', 'C')],\n", - " 3.14: [('B', 'D'), ('E', 'F')],\n", - " 0.79: [('B', 'E'), ('D', 'F')],\n", - " 5.17: [('C', 'D')],\n", - " 6.04: [('C', 'E')],\n", - " 0.32: [('D', 'E')]}" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "G.get_normals_dict(opposites = True, \n", - " num_rounding_digits=2)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "base", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.7" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} \ No newline at end of file diff --git a/doc_source/tutorials.rst b/doc_source/tutorials.rst index 849d783..5e66cd6 100644 --- a/doc_source/tutorials.rst +++ b/doc_source/tutorials.rst @@ -6,6 +6,5 @@ Tutorials :caption: Contents: notebooks/Tutorial-EmbeddedComplex - notebooks/Tutorial-ExactECT notebooks/Matisse/example_matisse diff --git a/docs/.buildinfo b/docs/.buildinfo deleted file mode 100644 index c328c0c..0000000 --- a/docs/.buildinfo +++ /dev/null @@ -1,4 +0,0 @@ -# Sphinx build info version 1 -# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. -config: 4fa06ba1eba33764a2433ecca7acac59 -tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/docs/.doctrees/citing.doctree b/docs/.doctrees/citing.doctree deleted file mode 100644 index aabd86f..0000000 Binary files a/docs/.doctrees/citing.doctree and /dev/null differ diff --git a/docs/.doctrees/contributing.doctree b/docs/.doctrees/contributing.doctree deleted file mode 100644 index 5801f92..0000000 Binary files a/docs/.doctrees/contributing.doctree and /dev/null differ diff --git a/docs/.doctrees/directions.doctree b/docs/.doctrees/directions.doctree deleted file mode 100644 index 81dcbb0..0000000 Binary files a/docs/.doctrees/directions.doctree and /dev/null differ diff --git a/docs/.doctrees/ect_on_graphs.doctree b/docs/.doctrees/ect_on_graphs.doctree deleted file mode 100644 index adc0757..0000000 Binary files a/docs/.doctrees/ect_on_graphs.doctree and /dev/null differ diff --git a/docs/.doctrees/embed_complex.doctree b/docs/.doctrees/embed_complex.doctree deleted file mode 100644 index c380d3f..0000000 Binary files a/docs/.doctrees/embed_complex.doctree and /dev/null differ diff --git a/docs/.doctrees/environment.pickle b/docs/.doctrees/environment.pickle deleted file mode 100644 index 517cd9b..0000000 Binary files a/docs/.doctrees/environment.pickle and /dev/null differ diff --git a/docs/.doctrees/index.doctree b/docs/.doctrees/index.doctree deleted file mode 100644 index 9285db2..0000000 Binary files a/docs/.doctrees/index.doctree and /dev/null differ diff --git a/docs/.doctrees/installation.doctree b/docs/.doctrees/installation.doctree deleted file mode 100644 index d284db5..0000000 Binary files a/docs/.doctrees/installation.doctree and /dev/null differ diff --git a/docs/.doctrees/license.doctree b/docs/.doctrees/license.doctree deleted file mode 100644 index 126a980..0000000 Binary files a/docs/.doctrees/license.doctree and /dev/null differ diff --git a/docs/.doctrees/modules.doctree b/docs/.doctrees/modules.doctree deleted file mode 100644 index 2627e9c..0000000 Binary files a/docs/.doctrees/modules.doctree and /dev/null differ diff --git a/docs/.doctrees/nbsphinx/notebooks/Matisse/example_matisse.ipynb b/docs/.doctrees/nbsphinx/notebooks/Matisse/example_matisse.ipynb deleted file mode 100644 index ccef47b..0000000 --- a/docs/.doctrees/nbsphinx/notebooks/Matisse/example_matisse.ipynb +++ /dev/null @@ -1,362 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# ECT on Matisse's \"The Parakeet and the Mermaid\"\n", - "\n", - "\n", - "\n", - " Here, we are going to give an example of using the ECT to classify the cutout shapes from Henri Matisse's 1952 [\"The Parakeet and the Mermaid\"](https://www.moma.org/audio/playlist/6/312).\n", - "\n", - "\n", - "\n", - " ![matisse.jpg](matisse.jpg)\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# -----------------\n", - "# Standard imports\n", - "# -----------------\n", - "import numpy as np # for arrays\n", - "import matplotlib.pyplot as plt # for plotting\n", - "from sklearn.decomposition import PCA # for PCA for normalization\n", - "from scipy.spatial import distance_matrix\n", - "\n", - "from os import listdir # for retrieving files from directory\n", - "from os.path import isfile, join # for retrieving files from directory\n", - "from sklearn.manifold import MDS # for MDS\n", - "import pandas as pd # for loading in colors csv\n", - "import os\n", - "import zipfile\n", - "\n", - "import warnings\n", - "warnings.filterwarnings('ignore')\n", - "\n", - "# ---------------------------\n", - "# The ECT packages we'll use\n", - "# ---------------------------\n", - "from ect import ECT, EmbeddedComplex # for calculating ECTs\n", - "# Note: EmbeddedGraph is now unified into EmbeddedComplex\n", - "# For backward compatibility, you can still use:\n", - "# from ect import EmbeddedGraph\n", - "\n", - "# Simple data paths\n", - "data_dir = \"outlines/\"\n", - "colors_path = \"colors.csv\"\n", - "\n", - "file_names = [\n", - " f for f in listdir(data_dir) if isfile(join(data_dir, f)) and f[-4:] == \".txt\"\n", - "]\n", - "file_names.sort()\n", - "print(f\"There are {len(file_names)} files in the directory\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " We've taken care of the preprocessing in advance by extracting out the shapes from the image. You can download these outlines here: [outlines.zip](outlines.zip).\n", - "\n", - "\n", - "\n", - " \"Matisse" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "i = 3\n", - "shape = np.loadtxt(data_dir + file_names[i])\n", - "# shape = normalize(shape)\n", - "G = EmbeddedComplex() # Using the unified EmbeddedComplex class\n", - "G.add_cycle(shape)\n", - "G.plot(with_labels=False, node_size=10)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " We're going to align the leaf using the PCA coordinates, min-max center, and scale it to fit in a ball of radius 1 for ease of comparisons." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "\n", - "G.transform_coordinates(projection_type=\"pca\") # project with PCA\n", - "G.scale_coordinates(1) # scale to radius 1\n", - "G.plot(with_labels=False, node_size=10, bounding_circle=True)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " And then we can compute the ECT of this leaf." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "OMP: Info #276: omp_set_nested routine deprecated, please use omp_set_max_active_levels instead.\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "num_dirs = 50 # set number of directional axes\n", - "num_thresh = 50 # set number of thresholds each axis\n", - "\n", - "myect = ECT(num_dirs=num_dirs, num_thresh=num_thresh); # intiate ECT\n", - "result = myect.calculate(G); # calculate ECT on embedded graph\n", - "\n", - "result.plot(); # plot ECT" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " Let's just make a data loader with all of this for ease in a bit." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def matisse_ect(filename, ect):\n", - " shape = np.loadtxt(data_dir + filename)\n", - " G = EmbeddedComplex() # Using the unified EmbeddedComplex class \n", - " G.add_cycle(shape)\n", - " G.transform_coordinates(projection_type=\"pca\")\n", - " G.scale_coordinates(1)\n", - " result = ect.calculate(G)\n", - " return result" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " And now we can load in all the outlines, compute their ECT and store it in a 3D array." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "num_dirs = 50 # set number of directional axes\n", - "num_thresh = 50 # set number of thresholds each axis\n", - "\n", - "ect_arr = np.zeros((len(file_names), num_dirs, num_thresh))\n", - "myect = ECT(num_dirs=num_dirs, num_thresh=num_thresh, bound_radius=1)\n", - "\n", - "for i in range(len(file_names)): # for each leaf\n", - " ect_arr[i, :, :] = matisse_ect(file_names[i], myect)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " Here, we are just going to compute the distance between two ECTs using $L_2$ distance." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "flattened_ect = ect_arr.reshape(len(file_names), num_dirs * num_thresh)\n", - "D = distance_matrix(flattened_ect, flattened_ect)\n", - "plt.matshow(D)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " For visualization purposes, we can project this data into 2D using Multi Dimensional Scaling (MDS). Here we plot each figure at the MDS coordinates." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "n_components = 2 # select number of components\n", - "mds = MDS(\n", - " n_components=n_components, # initialize MDS\n", - " dissimilarity=\"precomputed\", # we have precomputed the distance matrix\n", - " normalized_stress=\"auto\",\n", - " random_state=5, # select random state for reproducibility\n", - ")\n", - "MDS_scores = mds.fit_transform(D) # get MDS scores\n" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, \"MDS of Matisse's Leaves via ECT distances\")" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# read in color hexcodes\n", - "col_df = pd.read_csv(colors_path, header=None)\n", - "\n", - "scale_val = 6 # set scale value\n", - "plt.figure(figsize=(5, 5)) # set figure dimensions\n", - "\n", - "for i in range(len(file_names)): # for each leaf\n", - " shape = np.loadtxt(data_dir + file_names[i]) # get the current shape\n", - " shape = shape - np.mean(shape, axis=0) # zero center shape\n", - " shape = (\n", - " scale_val * shape / max(np.linalg.norm(shape, axis=1))\n", - " ) # scale to radius 1 then mult by scale_val\n", - "\n", - " trans_sh = shape + MDS_scores[i] # translate shape to MDS position\n", - "\n", - " plt.fill(trans_sh[:, 0], trans_sh[:, 1], c=col_df[0][i], lw=0) # plot shape\n", - " plt.gca().set_aspect(\"equal\")\n", - "\n", - "plt.title(\"MDS of Matisse's Leaves via ECT distances\")\n", - "# plt.savefig(\"Matisse_MDS.png\", bbox_inches = 'tight', dpi=300)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Acknowledgements\n", - "\n", - "\n", - "\n", - " This notebook was written by [Liz Munch](https://elizabethmunch.com/) based on [original code](https://github.com/DanChitwood/matisse_test) from [Dan Chitwood](https://www.canr.msu.edu/people/dr_dan_chitwood)." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "base", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.7" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/docs/.doctrees/nbsphinx/notebooks/Tutorial-EmbeddedComplex.ipynb b/docs/.doctrees/nbsphinx/notebooks/Tutorial-EmbeddedComplex.ipynb deleted file mode 100644 index 1738074..0000000 --- a/docs/.doctrees/nbsphinx/notebooks/Tutorial-EmbeddedComplex.ipynb +++ /dev/null @@ -1,624 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Tutorial: ECT for Embedded Cell Complexes\n", - "\n", - "This tutorial will walk you through using the `ECT` package. Particularly we will show the features of `EmbeddedComplex` class for computing the Euler Characteristic Transform on complexes with arbitrary dimensional cells.\n", - "\n", - "The `EmbeddedComplex` class combines and extends the functionality of the previous `EmbeddedGraph` and `EmbeddedCW` classes, supporting:\n", - "- **0-cells** (vertices) with embedded coordinates\n", - "- **1-cells** (edges)\n", - "- **k-cells** for k ≥ 2 (faces, volumes, and higher-dimensional cells).\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "from ect import EmbeddedComplex, ECT, Directions\n", - "from ect.utils.examples import create_example_graph, create_example_cw, create_example_3d_complex" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Basic Usage: Creating Simple Complexes\n", - "\n", - "### Example 1: Graph (1-skeleton)\n", - "\n", - "Let's start with a simple triangle graph (for legacy users this can be equivalently done using `EmbeddedGraph`). " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of nodes: 3\n", - "Number of edges: 3\n", - "Embedding dimension: 2\n" - ] - } - ], - "source": [ - "K = EmbeddedComplex()\n", - "\n", - "K.add_node('A', [0, 0])\n", - "K.add_node('B', [1, 0])\n", - "K.add_node('C', [0.5, 0.866])\n", - "\n", - "K.add_edge('A', 'B')\n", - "K.add_edge('B', 'C')\n", - "K.add_edge('C', 'A')\n", - "\n", - "#using built-in plotting function along with matplotlib\n", - "fig, ax = plt.subplots(figsize=(6, 6))\n", - "K.plot(ax=ax, with_labels=True, node_size=400)\n", - "ax.set_title('Simple Triangle Graph\\n(0-cells: vertices, 1-cells: edges)')\n", - "plt.show()\n", - "\n", - "#print some information about the complex\n", - "print(f\"Number of nodes: {len(K.nodes())}\")\n", - "print(f\"Number of edges: {len(K.edges())}\")\n", - "print(f\"Embedding dimension: {K.dim}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now let's add a 2-cell (face) to fill in the triangle:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of 2-cells (faces): 1\n", - "Faces: [('A', 'B', 'C')]\n", - "Internal cells dictionary: {2: [(0, 1, 2)]}\n" - ] - } - ], - "source": [ - "K.add_face(['A', 'B', 'C'])\n", - "\n", - "fig, ax = plt.subplots(figsize=(6, 6))\n", - "K.plot(ax=ax, with_labels=True, node_size=400, face_alpha=0.3, face_color='lightblue')\n", - "ax.set_title('Triangle with Face\\n(0-cells: vertices, 1-cells: edges, 2-cells: faces)')\n", - "plt.show()\n", - "\n", - "print(f\"Number of 2-cells (faces): {len(K.faces)}\")\n", - "print(f\"Faces: {K.faces}\")\n", - "print(f\"Internal cells dictionary: {dict(K.cells)}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Adding Cells of Arbitrary Dimension\n", - "\n", - "The key new feature is the ability to add cells of any dimension:" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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PfehDOHLkCK6//npYrVbcf//92LJlC2ZnZ6N6vbvvvhuXXHIJDh48iM9+9rOctYzBYIh6JnC0HD16FD/60Y9gMBiwbds2APNRr40bN6K9vT2qyS/stI7vfOc7uOqqq6BQKHDZZZetKYI5PDyMV199FV/+8pcj/j4zMxMXXXQRfv/73+O+++6DQqFY9WtlZWXh2WefxaWXXoqdO3eGTSA5e/Ysfvvb33J2LbF8Fvjmmmuu4b4nkYQcMC/4X3jhBZw4cQL79+/Hn//8Zzz33HP49re/zaV/o/0+/uY3v8HPfvYzXH755aiqqoLD4cDPf/5z6PX6uN6kEERakcROZoIQFAutZVj+67/+i9mzZw+jUqkYnU7HbNu2jfnGN77BDA8Pc88ZHR1lPvShDzE6nY4BwFmHsLYwkWwubDYbc9111zG5ubmMVqtlLrroIqatrW2RrcdS23j11VcZAMyrr7666PGLLrqIMRgMjFKpZKqqqphrr72Wef/998Oe9/TTTzObNm1iMjMzmc2bNzPPPPMMc+LEiYjWMnfffXfEY/byyy8zhw8fZlQqFaPX65nLLruMaWlpCXsOa13CWoQs3K9IVi8Lee655xgAzCWXXBL2+Oc+9zkGAPPLX/5y0d9ggbUMwzDMD3/4Q2bdunWMVCoNe20AzE033bRoGytZrNxzzz0MAObUqVNLPufhhx9mADB//OMfGYZZvbUMy/DwMPO1r32N2bBhA6NUKhm1Ws3s2bOHufPOO5mZmZmw50bzWeDLWobF4/EwWVlZjMFgYNxu96LfnzhxgtFoNEx3dzfzwQ9+kFGr1UxBQQFz++23M4FAYNHzV/o+nj17lrn66quZsrIyJjMzk8nPz2f+4R/+YdHnnyCIvyNhmBWqowmCIAhilfj9fhQXF+Oyyy7DL3/5y0W/v/baa/HUU09FHZEmCCL+UM0gQRAEwRt/+MMfMDExgWuuuSbZSyEIYgmoZpAgCIKIO++88w4aGxvxwx/+ELt27cIFF1yQ7CURBLEEFBkkCIIg4s6DDz6If/qnf0J+fj4eeeSRZC+HIIhloJpBgiAIgiAIEUORQYIgCIIgCBFDYpAgCIIgCELEkBgkRMW1117LjbdikUgkcTdJFht0XPmBjis/0HEliHBIDBK84/F48M1vfhPFxcVQqVTYv38/XnrppWQvK2l84AMfgEQiwc0337zqbYyMjODWW29FXV0ddDodJBIJXnvttfgtMoV48skncfDgQWg0GhiNRhw6dAivvPLKqrZ16tQpXH/99diwYQPUajUqKyvxuc99DiMjI3FedeoQj8/r66+/jg9/+MMoLS2FUqlEYWEhLr74Yvz1r3+N40qFTXt7O772ta/h0KFDUCqVkEgk6OvrS/ayCAIAiUEiAVx77bW499578alPfQo/+clPIJPJcOmll+LNN99M9tISzjPPPIPTp0+veTvt7e348Y9/jKGhIW48mxj53ve+h6uvvhqlpaW49957cccdd2D79u0YGhpa1fa++c1v4rXXXsPll1+O++67D1dddRX++7//G7t27cLo6GicVy984vV57ejogFQqxQ033ICf/vSn+PrXv47R0VGcf/75eOGFF+KwUuFz+vRp3HfffXA4HNi0aVOyl0MQYZDPIMEr7777Ln73u9/h7rvvxte//nUA87NKt27dim984xt46623krzCxDE3N4d//ud/xje/+U3cdttta9rWnj17MDU1hezsbDz11FP4+Mc/HqdVpg5vv/02fvCDH+Cee+7B1772tbhs895778WRI0cglf79Pvniiy/GBRdcgAceeAB33HFHXF4nFYjn5/Vzn/scPve5z4U9duONN6KyshInT57ExRdfvKbtpwIf/vCHMT09DZ1Oh3//93+HyWRK9pIIgoMigwSvPPXUU5DJZPjCF77APaZUKvHZz34Wp0+fxuDg4IrbCAaD+MlPfoJt27ZBqVQiLy8PF198Md5///2w5z322GPYs2cPVCoVsrOzcdVVV0W1/YU4HA589atfRXl5OTIzM5Gfn48PfOADOHv2LPccl8uFtrY2TE5ORr3df/u3f0MwGORE8VrQ6XTIzs5e0zZS/biePHkShYWF+MpXvgKGYeIyzuz8888PE4LsY9nZ2WhtbY1qG6l+XFni+XmNhFqtRl5eHqanp6N6fqof1+zsbOh0upjXQRCJgMQgwSsNDQ3YsGED9Hp92OP79u0DgKjujj/72c/iq1/9KkpLS/HjH/8Yt956K5RKJd5++23uOXfeeSeuueYa1NTU4N5778VXv/pVnDp1Cueff37UFxuWG264AQ8++CA+9rGP4Wc/+xm+/vWvQ6VShYmBd999F5s2bcIDDzwQ1TYHBgbwox/9CD/+8Y+hUqliWg9fpPpxPXXqFPbu3Yv77rsPeXl50Ol0KCoqivo9iZbZ2VnMzs4iNzc3quen+nEF+Pu82u12TE5Ooq2tDd/+9rfR3NyM48ePR/W36XBcCUKwMATBI1u2bGHq6+sXPW6xWBgAzEMPPbTs37/yyisMAObLX/7yot8Fg0GGYRimr6+PkclkzJ133hn2+6amJkYul4c9fuLECWb9+vVhzwPA3H777dy/DQYDc9NNNy27rldffXXR3y3HFVdcwRw6dCjsNVd6jWj5/e9/zwBgXn311aj/JtWPq9VqZQAwOTk5jFarZe6++27mySefZC6++OKoPlex8MMf/pABwJw6dWrF56b6cWXh6/N60UUXMQAYAExGRgbzxS9+kXG73Sv+XbocV5a7776bAcD09vbG9HcEwRdUM0jwitvtRmZm5qLHlUol9/vlePrppyGRSHD77bcv+p1EIgEwX+QeDAbxiU98IixdU1hYiJqaGrz66qv49re/HfWajUYj3nnnHQwPD6O4uDjic44dOwYmyuE9r776Kp5++mm88847Ua+Bb1L9uLIp4ampKfzud7/DlVdeCQC44oorsG3bNtxxxx344he/GPXaluL111/H97//fXziE59AfX39is9P9eMK8Pt5/dGPfoR//ud/xuDgIH7zm9/A6/XC7/ev+HfpcFwJQsiQGCR4RaVSwePxLHp8bm6O+z0AWK1WeL3esL8zGAzo7u5GcXHxsvVxnZ2dYBgGNTU1EX+vUChiWvO//du/4cSJEygtLcWePXtw6aWX4pprrkFlZWVM2wEAv9+PL3/5y/jMZz6DvXv3xvz3ayVdjyv7uVEoFLjiiiu4x6VSKa688krcfvvtGBgYQFlZWczbZmlra8Pll1+OrVu34he/+EXY79L1uPL9ed25cyf3/5/+9Kexe/duXHvttXjqqacApO9xJQihQ2KQ4JWioqKINh+sbxt7x/3Rj34Uf/nLX7jfnzhxAg8//HBUrxEMBiGRSPDnP/8ZMpls0e+1Wm1Ma/7EJz6Bo0eP4tlnn8WLL76Iu+++Gz/+8Y/xzDPP4JJLLolpW4888gja29vxn//5n4s8xRwOB/r6+pCfnw+1Wh3TdqMlXY9rdnY2lEoljEbjorXl5+cDAGw226rF4ODgID74wQ/CYDDg+eefX1T4n67HNZGf14yMDHz4wx/Gj370I7jdbqhUqrQ9rgQhdEgMEryyc+dOvPrqq7Db7WFNJGwKio0U3HPPPbDZbNzvWZFYVVWF//u//4PVal0yKlBVVQWGYVBRUYENGzbEZd1FRUW48cYbceONN2J8fBy7d+/GnXfeGfNFYGBgAD6fD4cPH170u0ceeQSPPPIInn32WXzkIx+Jy7oXkq7HVSqVYufOnXjvvffg9XqRkZHB/W54eBgAkJeXt6o1Tk1N4YMf/CA8Hg9OnTqFoqKiRc9J1+Oa6M+r2+0GwzBwOBxQqVRpe1wJQuhQNzHBK1dccQUCgQD+67/+i3vM4/Hg17/+Nfbv34/S0lIA8755F154IfezefNmAMDHPvYxMAyD73//+4u2zdbqfPSjH4VMJsP3v//9RfU7DMNgamoq6vUGAgHMzMyEPZafn4/i4uKwdHe0lhJXXXUVnn322UU/AHDppZfi2Wefxf79+6NeX6yk63EFgCuvvBKBQAC/+c1vuMfm5ubw+OOPY/PmzUvWeS2H0+nEpZdeiqGhITz//PNLphzT9bjy9XkdHx9f9Nj09DSefvpplJaWctHcdD2uBCF0KDJI8Mr+/fvx8Y9/HN/61rcwPj6O6upq/OY3v0FfXx9++ctfrvj3dXV1+MxnPoP77rsPnZ2duPjiixEMBvHGG2+grq4ON998M6qqqnDHHXfgW9/6Fvr6+vCRj3wEOp0Ovb29ePbZZ/GFL3whaq80h8OBkpISXHHFFdixYwe0Wi1efvllvPfee7jnnnu457377ruoq6vD7bffvuw809raWtTW1kb8XUVFxaIIy7Fjx/CXv/wlqqJ01gDZYrEAAB599FFuqst3v/vdZf821Y8rAHzxi1/EL37xC9x0003o6OhAWVkZHn30UfT39+NPf/pT2HOjPa6f+tSn8O677+L6669Ha2trmI2IVqtdMSKW6seVr8/rJZdcgpKSEuzfvx/5+fkYGBjAr3/9awwPD+PJJ59ccT9T/bgCwMzMDO6//34A4MbwPfDAAzAajTAajWsa90cQa4b/hmVC7LjdbubrX/86U1hYyGRmZjJ79+5lXnjhhaj/3u/3M3fffTdTW1vLZGRkMHl5ecwll1zCnDlzJux5Tz/9NHPkyBFGo9EwGo2Gqa2tZW666Samvb2de85KlhIej4f5f//v/zE7duxgdDodo9FomB07djA/+9nPwv5mtZYSoa8ZybZiz549TGFhYdTbWOonGtLhuI6NjTEnTpxgsrOzmczMTGb//v0RP1vRHtf169cveUwX7t9SpMNxXchaP68PPPAAc+TIESY3N5eRy+VMXl4ec9lllzGvv/561GtI9ePa29u75s8WQfCFhGGoL54ghIDD4UB2djZOnjyJm266KdnLSRvouPIDHVeCSB+oZpAgBMLrr7+OdevW4fOf/3yyl5JW0HHlBzquBJE+UGSQIAiCIAhCxFBkkCAIgiAIQsSQGCQIgiAIghAxJAYJgiAIgiBEDIlBgiAIgiAIEUNikCAIgiAIQsSQGCQIgiAIghAxJAYJgiAIgiBEDIlBgiAIgiAIEUNikCAIgiAIQsSQGCQIgiAIghAxJAYJgiAIgiBEDIlBgiAIgiAIEUNikCAIgiAIQsSQGCQIgiAIghAxJAYJgiAIgiBEDIlBgiAIgiAIEUNikCAIgiAIQsSQGCQIgiAIghAxJAYJgiAIgiBEDIlBgiAIgiAIEUNikCAIgiAIQsSQGCQIgiAIghAxJAYJgiAIgiBEDIlBgiAIgiAIEUNikCAIgiAIQsSQGCQIgiAIghAxJAYJgiAIgiBEDIlBgiAIgiAIEUNikCAIgiAIQsSQGCQIgiAIghAxJAYJgiAIgiBEDIlBgiAIgiAIEUNikCAIgiAIQsSQGCQIgiAIghAxJAYJgiAIgiBEDIlBgiAIgiAIEUNikCAIgiAIQsSQGCQIgiAIghAxJAYJgiAIgiBEDIlBgiAIgiAIEUNikCAIgiAIQsSQGCQIgiAIghAxJAYJgiAIgiBEDIlBgiAIgiAIEUNikCAIgiAIQsSQGCQIgiAIghAxJAYJgiAIgiBEDIlBgiAIgiAIEUNikCAIgiAIQsSQGCQIgiAIghAxJAYJgiAIgiBEDIlBgiAIgiAIEUNikCAIgiAIQsSQGCQIgiAIghAxJAYJgiAIgiBEDIlBgiAIgiAIEUNikCAIgiAIQsSQGCQIgiAIghAxJAYJgiAIgiBEDIlBgiAIgiAIEUNikCAIgiAIQsSQGCQIgiAIghAxJAYJgiAIgiBEDIlBgiAIgiAIEUNikCAIgiAIQsSQGCQIgiAIghAxJAYJgiAIgiBEDIlBgiAIgiAIEUNikCAIgiAIQsSQGCQIgiAIghAxJAYJgiAIgiBEDIlBghAR4+PjeOONN5K9DIIgCEJAkBgkCBHBMAx8Ph+vr+F2uzE7O8vraxAEQRDxg8QgQYgIiUQChmF4fY2hoSG0trby+hoEQRBE/CAxSBBE3OFbcBIEQRDxg8QgQYiIREQGJRIJr9snCIIg4guJQYIQEYkQgwBFBgmCIFIJEoMEISIoMkgQBEEshMQgQYiIREUGCYIgiNSBxCBBEHGFBCdBEERqQWKQIEQE1QwSBEEQCyExSBAigmoGCYIgiIWQGCQIEZEoMUiRQYIgiNSBxCBBiAiK2hEEQRALITFIECJjYdTOZrPBbrfHNZqX7pFBt9sNm82W7GUQBEHEBXmyF0AQROIITeG6XC40NTVhYmKC+53RaERWVhb3X5VKtarXSHfGx8cxNDSEQ4cOJXspBEEQa4bEIEGICIlEgmAwiM7OTrS3t6O4uBgf+MAHoFAo4HA4YLPZYLPZ0N7eDrvdDqVSGSYOjUYjFArFiq+T7pFBgiCIdILEIEGICJvNBoZhMDg4iIMHDyInJ4f7ncFggMFgQHl5OQDA7/djenoaNpsN09PT6Ovrg9vthk6n48RhVlYW9Ho9pNK/V5yIITJIEASRTpAYJAgRMDc3B4vFgpGREQDAsWPHwgRcJORyOXJzc5Gbmxu2HVYcjoyMoKWlBcFgEAaDgROHHo8HwWCQ1/0RAiR6CYJIF0gMEkQawzAMent70draivz8fBw6dAhvvPHGikJwKZRKJYqKilBUVMRtf3Z2losgdnd3Y2ZmBgBw+vTpsBRzZmZm3PaLIAiCiB8kBgkiTbHZbDCbzfD7/di7dy/y8/PhdrsBzIu4eES2JBIJdDoddDodSktLAQCDg4Po7OxEQUEBbDYbhoaGMDs7C7VaHSYODQYD5HI6BREEQSQbOhMTRJrh9XrR2tqKwcFB1NTUoLq6GjKZDMDfU5vxEoORkEqlkMvlqKysDFsTGz2cmppCV1cXvF4v9Hp9WP2hTqdLifQrNcgQBJFOkBgkCB5h6+dWY9ESK2xjiMVigdFoRF1dHTQaTdhzEiG0Ik0gycjIQH5+PvLz87m1ut1uTiAODg6iqakJAMLEYVZWFpRKZUoIRIIgiFSFxCBB8EhfXx+cTid2797N6+vY7XaYzWa43W7s2LEDRUVFywqoZEe2JBIJ1Go11Go1iouLAQDBYBCzs7Nh9jYOhwMZGRlh6eWsrKyo7G0IgiCI6CAxSBA8wvecXp/Ph/b2dvT29qKyshIbN25ctg4vNE3MF6vdZ6lUCr1eD71ej/Xr1wOYt7eZmZnhOpgHBgbgcrmg1WoX2duwqXCCIAgiNkgMEgSP8CUGGYbB8PAwmpubodFocMEFF0Cv10e1HvbvUwG5XI6cnJwwP0SPx8OJw7GxMbS1tSEQCECv14ellzUaDaWXCYIgooDEIEHwCB9icHZ2Fo2NjbDb7diyZQtKSkqiFj3JqhmMJ5mZmSgsLERhYSGAeWHrdDq5+sPe3l6YTCbIZLKw6KHRaIRSqeRtXemI3++Hz+dLSM0rQRDJg8QgQfBIPIVRIBBAR0cHuru7UVZWhr179666di5VIoPRIJFIoNVqodVqUVJSAmC+/tBut3P1h8PDw5idnYVKpQoTh0ajkextlmFqagoWiwX19fXJXgpBEDxCZ0GC4BGpVBoX4TU2NobGxkZkZGTg8OHDyMrKWtV2hFwzGE+kUikn9ioqKgDM11cutLfxeDwR7W2iMeWmFDRBEOkCiUGC4BGJRLKm0WwulwvNzc2YnJzEpk2bUF5eviYRkmo1g/FEoVAgLy8PeXl53GNut5urPxwaGoLFYgHDMGHj9bKysqBSqUQp/vj0oyQIQjiQGCQIHlltlCwYDKK7uxvt7e0oLi7G8ePH4zLOTSyRwWhRqVRQqVScvQ3DMHA4HFwEsbOzE3a7HQqFIkwc+ny+JK88MZAYJAhxQGKQIHhkNcJocnISjY2NAICDBw+GddKmCqkiBhcikUg4e5uysjIA87WarL0Na5DtdDohk8lw5syZsPF66WZvk6rvI0EQsUFikCB4JBYxODc3B4vFgpGREdTW1qKysjKq2rVY1wPwHxlMJ2QyGbKzs5Gdnc091tnZieHhYWi1WkxMTKCjowM+n2+RvY1Wq03545Hq6ycIYmVIDBIEj0TTQMIwDHp7e9Ha2or8/HwcP36cVyuPVErjChW5XI7MzExs3LgRwPx76HK5uPRyf38/zGYz18gS2sGcSjYtlCYmCHFAYpAgeGSlBhKbzQaz2Qy/34+9e/dys3v5XhPVDMYXiUQCjUYDjUaDdevWAZiv+3Q4HFx6ubW1FQ6HA0qlcpG9jVDH65EYJAhxQGKQIHhkKWHk9XrR2tqKwcFB1NTUoLq6OmH1ZmIUa8lAKpXCYDDAYDCgvLwcwLy9TWj9YW9vL9xuN3Q6Xdj8Zb1eH/cSgdVAnxOCEAckBgmCRxYKL4ZhMDg4CIvFAqPRiLq6Omg0moSviyKDyUGhUCA3Nxe5ubncY3Nzc5w4HBkZQUtLC4LB4CJ7G7VanZQoHUUGCSL9ITFIEDwSKozsdjvMZjNcLhd27NiBoqKitL24kxiMHqVSiaKiIhQVFQGYP3azs7Nc/WF3dzdmZmagUCgW1R/Gw25oOShNTBDigMQgQfAIWzPY3NyMvr4+VFRU4ODBg0kdgZaImkExwNd+SiQS6HQ66HQ6lJaWApi3twkdr3fu3Dk4nU6o1eowcWgwGOL62SJRTxDigMQgQfAEwzCwWq1cl+n5558PvV6f7GUlJI1LIiK+yGQyTvSxeL1eLno4OTmJzs5OeL1ezt6GjSLqdLq4TK1JdzweD9577z0cPnxYNPtMECwkBgmCB2ZnZ9HU1ASbzQa5XC6oCwxFBteOEMRuRkYG8vPzuQ50hmHCxusNDg6iqakJAMLEYVZWFpRKZVTvk5jSxMFgEFNTU8leBkEkBRKDBBFHAoEAOjs70dXVhdLSUlRWVsJkMonmgkokD4lEArVaDbVaHWZvMzs7y6WX29vbYbfbkZmZGZZezsrKimhvIzYxKJFIRLO/BBEKiUGCiBNjY2NobGxERkYGDh8+jKysLNhsNkFEkUIhn0HxIJVKufF669evBwD4/f4we5v+/n64XC5otdowcWgwGEQlBhmGEYSdD0EkAxKDBLFG3G43mpqaMDk5iU2bNqG8vJy7gApRGFHNoLiRy+XIyckJm3nt8Xg4cTg2Noa2tjYEAgFkZmZCIpFgcHAQWVlZ0Gg0aSsO2cggQYgREoMEsUqCwSC6u7vR3t6O4uJiHD9+fJHVRzTj6BIN1QwSC8nMzERhYSEKCwsBzIt5p9OJ9vZ2WK1W9Pb2wmQyQSaTLbK3USqVSV59fBBTFJQgFkJikEgbzp49iw0bNkCr1fL+WpOTk2hsbAQAHDhwIMxEOJSVxtElA74veEKMhhKxIZFIoNVqYTAYEAwGsXfvXgSDQczMzHAdzMPDw5idnYVKpVo0Xi+Z1kmrhdLEhJhJvW8sQSzBxMQEN/aLL+bm5tDS0oLh4WHU1taisrJy2QuIUIWRENdECBupVMqJvoqKCgDz4/VYcTg1NYWuri54PJ6I9jZCF1qUJibEDIlBIm2QSqW8ReEYhkFfXx9aW1uRm5uL48ePQ6VSrfh3QhSDVDNIRMtKqVOFQoG8vDzk5eVxj7H2NjabDUNDQ2hubgYALmrICkqVSiUo8UVpYkLMkBgk0ga+UrI2mw1msxl+vx979uxBQUFBTGsSmjCimkEiWlYjkFQqFVQqFYqLi7ltOBwOzv+ws7MTdrsdGRkZi+oPMzIy+NiNqKA0MSFmSAwSaUO8mzW8Xi9aW1sxODiI6upq1NTUQCaTxbQN9kIqpKgDWcsQ0RKP91EikSyytwkEAmH2NoODg3A6ndBoNIvsbWL9zq0WShMTYobEIJE2xCtNzDAMBgcHYbFYYDQacezYsVU3pbCRBqGJQWJtiEns8vF5kclkyM7ORnZ2NveYx+Ph6g8nJibQ0dEBn88Hg8EQFkHUarW8rElI31GCSDQkBom0IR4RKbvdjsbGRjidTuzYsQNFRUVxmesaDAYFlYKiyODaEYNwSKRAyszMREFBAVeGwTAMXC4Xl17u7++H2WyGVCoNE4fseL21IrTvaCJwuVzIyMhIye5vIr7QJ4BIG9YSGfT7/Whvb0dPTw8qKytx4MCBuJwgQ9PEQkEsYo1YO8mMlkkkEmg0Gmg0GpSUlACYF2x2u52LILa2tsLhcECpVIaJQ4PBEHG83nKIMTL49ttvY8uWLTHVQRPpCYlBIm1YTQMJwzAYGRlBU1MTNBoNLrjgAuj1+riuiX0doUA1g0S0CE0gsVFBo9HI2Uj5fL6w+sOenh7Mzc1Bp9OF1R/q9fplI39C29dEIMZoKBEZEoNE2hBrA8ns7CyampowPT2NLVu2oLS0NO4XA6GKQYJIFxQKBXJzc8OM391uNxc9HBkZQUtLC4LB4CJ7G7VaLdhSjkQgxn0mIkNikEgboo0MBgIBdHZ2oqurC6WlpdizZw9vlhahDSRCIhHWMmKMtKQbqfoesvY2RUVFAOb3Y3Z2lqs/7O7uxszMDBQKBScOfT6f4L6nfENikGAhMUikDdFEBsfGxtDU1AS5XI7Dhw8jKysrIWsT0kWG0rhEtKSqGFyIRCKBTqeDTqdDWVkZgL/b24R2MHs8Hrz00kuL6g8TZW+TaEgMEiwkBom0YbnIoNvtRlNTEyYnJ7Fp0yaUl5cn5CInkUgEN584UabT6SIkiPRkob1Nb28vRkZGUF1dDZvNhsnJSXR2dsLr9UYcr5cOn20SgwQLiUEibYjUTRwMBtHT04O2tjYUFxejvr4+LjYUsSC0SJzQ1kMIFzEJeoZhIJPJkJ+fj/z8fO4xdrze9PQ0BgcH0dTUBABh4pC1t0m1Y0VikGAhMUikDQvTxFNTUzCbzQCAAwcOhBWYJxKxiS8hNs0Qq0NMI9oiCV+JRAK1Wg21Wo1169YBmBdQDoeDSy+3t7fDbrcjMzMzLL1sNBpjtrdJJAzDiOr9JZaHxCCRNrDpWI/HA4vFguHhYWzcuBFVVVVJPeEJTQyGroeNnFqt1rCLGJnQEoC4BH20UTKpVAqDwQCDwcCN1/P7/WH2Nn19fXC73dBqtWHfK4PBIBjxxWZRhLIeIrnQGZ9IGyQSCWw2G06dOoXc3FwcP34cKpUq2csSrBi02WwwmUxgGAYlJSWcR5vH4+FqpFYzAkwskcFUSwmuFrHs51pS4nK5HDk5OcjJyeEem5ubC7O3aW1tRSAQgMFgCEsxazSapBxjEoNEKCQGibSAPeEGg0Gcd955gnLUj9fM5HjBMAyGhoZgsVhQU1ODmpqasAsCWyNltVq5EWAymYwThtnZ2TAajSva8aS7GBQDYqsZjKcwUiqVKCwsRGFhIbd9p9PJ1R/29vbCZDJBJpMtGq+XmZkZt3UsBYlBIhQSg0RK4/V60draisHBQej1ehgMBkEJQUBYkcGRkRFMTk5CpVLh2LFj0Gq1i57DerQVFxcDmL9ohKbAzp07B6fTCa1Wi+zsbO4Cptfrue7pdEco7yffiEkMBoNBXvdVIpFAq9VCq9WitLSUe81Qe5vh4WHMzs5CpVItsreJd+kGiUEiFBKDRErCMAwGBwfR0tICg8GAY8eOob+/H36/P9lLW4QQxGCotY5Op0NJSUlEIRgJqVTKXZRYPB4PJw6HhobQ3NwMANyFi32OkAvoCSKUZAjf0O9WRUUFgPnxeqw4nJqaQldX16LSDaPRCJ1OtyYhx4pfsYh9FqfTCa/XmzCP2VSBxCCRctjtdjQ2NsLpdGL79u0oKiqCRCKJeRxdokimGGQYBr29vWhtbUVhYSGOHz+OxsbGNW83MzNzUQrM4XDAarViamoKAHDq1Cmo1eqw9LKQCuiJlRFTZFAonbUKhQJ5eXnIy8sDML+uubm5sMg8a2/DppfZ/6pUqqjfr0AgIIj9TTSjo6OYnJzE/v37k70UQUFikEgZ/H4/2tvb0dvbi/Lycuzfvz8s8iS02jyWZInBmZkZmM1meL1e7N27l/NO42M9EokEer0eer0eJSUlOHfuHC688EKuRmpiYgLt7e1cAT2bXs7Ozk5JfzaxICYxyHeaeLVIJJJFpRvszRdbf9jZ2Qm73Y6MjIwwcbhcba9QxG+iCQQCaTtRZi2QGCQED8MwGBkZQVNTE9RqNc4//3zo9fpFzxPapA+WRIvBUNFcWVmJjRs3hp38EjWBRC6XLzLwZcWh1WrlLmCh/mxs9JCsbYhEk0riKPTmK9Texm63cxHEgYEBuFwuaDSaRfY2MplMtJHBYDBIYjACdMYlYmJiYoIb45QInE4nGhsbMT09jS1btqC0tHTJu3ehpokTua7x8XGYzWZkZmYuKZqBxDRALHyNSAX0fr+fq4+y2Wzo7u4OG//FRhCTZb8hdsQWGUzlGle5XB42Xg+Yr9tlv19jY2Nob2+Hz+eDwWCASqXiDLRjsY5KdfgUwWNjY9BqtdBoNLxsn09IDBIxMTIykhAxGAgE0NnZia6uLpSWlmLPnj0rWpkIOTLI97o8Hg+am5sxOjqKzZs3Lzt7me+Tfizbl8vlyM3N5abDhI7/stlsnP2GXC4P667MyspK6Qt3qiAmMZiO+5qZmYmCggLOYYFhGLhcLq5zORAI4LXXXuMaWRaO10tH+EwTf/rTn8bVV1+N66+/npft8wmJQSImElGXNzY2hqamJsjlchw+fDjqri+hRgb5TMsyDIOBgQFYLBbk5uaivr5+RaPtRKWJV/MakcZ/BQIB2O12WK3WsPSXTqcLix7qdLq0u5gnm3QUSEshhn2VSCTQaDTQaDRQKBSYnZ3FsWPHuPTy9PQ0Wltb4XA4oFKpwsRhukwm4jMC7Ha7BTHoYDWk/jtLJBSpVAqfz8fLtt1uN5qbmzE+Pr5idGuptQk1MsiH+HI4HGhsbMTs7Cx27dqFoqKipK6HL0INr1kidVdKJBIYjcYw70M+zXvTXTgA4vFTBKIfR5cusOlSqVQKo9EIo9HI/c7n84V5i/b09GBubo67AWPFoV6vT7ljxmea2OVyQa1W87JtviExSMQEH4KLnY/b1taGoqIiHD9+fFUpCqGKnHivKxAIoKurC52dnVi/fj327dsX052uUI9TLCiVShQVFXECmK19YptTWPPe0OL57OzslLx4JRsxiF5AHJHBUJZrmFEoFGHlG8D8zTpbf8hOMGIYZtF4PbVaLejjyGeamCKDhGiItxicmpqC2WwGABw4cCDs5BMrQo0MxjN9PTU1xY2wiiWFnkiSMZtYKpXCYDDAYDCgvLwcwPx0munpaVitVoyNjaGtrQ2BQGBR9HA1J+9UF9PRIiaBJFRrGb6INULG2tuwN2AMw2B2djas+WtmZgYKhWJR/eFK9d6JhM9uYooMEqIhXoLL4/HAYrFgeHgYGzduRFVV1ZojNkIVg/FoIPF6vWhpacG5c+dQW1uLysrKVR+vREUGky2YMjIyFlnbhF682tvbYbfboVQqw8Sh0Wgk64m/ISYxmErWMvFgrfsrkUig0+mg0+lQVlYGYF5gsunl6elpbnSlRqMJE4esvU0y4DNNTJFBQjSsVXAxDIO+vj60trZyDQ/xupMSavpzLetiGIYb92YwGOJyvBJxnIQoICJdvFhrG3ZySldXF7xeL5f6YtPLQk99EWtHTMIX4EcUsU4ToW4TbISeNZ/v6OiAz+fj7KNYkZioBjA+08QUGSREw1rE4PT0NDcRY8+ePZzdgRDWxierFV8ulwtmsxkzMzPYtm0biouL43KyTJQYFKIwX8hS1jZs53JPTw8aGhqgUCjCooeBQCDJK08MYhJIYksTJyoSGilCH2ofNTg4GNYAFhpB5CPKxleamN0vigwSomA1gsvn86G1tRUDAwOorq5GTU0NL19GIfsMxiKMQhtqSkpKovJYjHU9QjxOQiDU2qakpARAeOrLarWir68PbrcbcrkcJpOJu3Clo7WNmMSg2NLEyZpAEsk+KrQBbHp6OqyEY6G9zVptYfiKDHq9XgSDQYoMEuIgFjHIMAzOnTsHi8UCvV6PY8eOQavV8ro2IUajYhGDNpsNZrMZgUAABw8eRE5ODs+r44dUiQxGQ2jqq6qqCgDQ0tKCqakpKBSKsMhGaGpZaIXzxPKISfgCwhK/oQ1gLGwJB5tiZm/CtFptmPl8rA4BfIlgt9sNABQZJMRBtGLQbrejsbERTqczrinO5RBqxCsakerz+dDW1ob+/n7U1NSgurqat7qWdBJqyUKhUEClUmHLli0A5iMbrHGv1WrF0NAQVzgfml5ONWsbMQkksfoMCpWFJRzAvL8oKw5HRkbQ2tqKQCAQVuNrNBqXHV/JV5rY5XIBIDFIiISVxKDf70d7ezt6enpQUVGB/fv3J2xsmJAjg8sds5GRETQ2NkKr1eKCCy6ATqfjfT1i6Cbmm9CLTahxb0VFBYD5tBErDkdGRtDS0gKGYcLSXtnZ2YIe+yUmMSimfQVSU/wqlUoUFhaisLAQwPx75nQ6w8yxZ2ZmOKP60O8aa0DPV5rY7XZDoVCk7JSW1Fw1kTSWEoMMw2BkZATNzc1QqVS44IILoNfrE7o2oUYGlxJfbrcbTU1NmJycxJYtW1BWVpaQi5FYu4kTTUZGxqK5sGxdVKi1jUqlCkstJ9N2YyFiEkhi2lcgNcXgQiQSCbRaLbRaLUpLSwH8fXwlW3/IGtCr1WoYjUb4/X7Y7Xao1eq4CrdU7iQGSAwSMRJJDDqdTjQ2NmJ6ehpbtmxBaWlpUk6qQo4Mhq6LtddpaWlBYWEhjh8/zuvYtEjrScRrCPG9SCYSiQR6vR56vR7r168HMF8ewKa9Jicn0dHRAb/fv8jaRqVSiUqoJIN0EEexEAwGUzaKtRyRxlf6fD7uJmx4eBhNTU04e/Zs2Hi9tTaBpXInMUBikIiRUDEYOhattLQ07l2va1mbkAgVRna7HSaTCR6PB3v37uXsFhINCbW1Ea/jp1AokJeXh7y8PG67LpeLs7bp7u7G2bNnkZGRESYOjUZjQi7kYoqWiWlfAXGJX4VCgfz8fGRnZ6OtrQ319fUIBoOL5psDWNS9HO2NGEUGCVHBCq7x8XE0NjZCLpcLZiyakNPEgUAALS0t6OnpQWVlJTZs2JC0u3LyGRQuEokEGo0GGo0mLO3FRg9tNht6e3sxNzcHvV4f1pyi1WrjLmbEJJCE1F2bCMQkBllYf1CZTIbMzEyoVCoUFxcDCC/jmJ6eRkdHB+x2O3cjxopEo9EYMehBkUFCVPh8Pvh8Prz33nvYtGkTKioqBHOxYE9sQruAzc3NYWpqClqtFkePHg2zT0gGJNRSC5lMhpycnDCboVDT3v7+fpjN5rD0GBs9JGub6BGb6bQYxSAbLIhUkxupjMPv92NmZoa7GRsYGIDL5YJGo+Gso8bGxnDo0KG4icHXX38dd999N86cOYORkRE8++yz+MhHPrLs37z22mu45ZZbYLFYUFpaiu9+97u49tprY3pdEoNEVIQaITMMg+PHjwuuC5I9kfM5iDwWPB4PmpubMT4+jqysLBw+fFgQFxuqGUx9VCpVWFQjGAxyxths2svpdHKebGwEUafTxSQAhHZjxSdi2ldAnGKQtdOJ9n2Wy+WLbsQ8Hg8nDk+fPo2vfvWrcLlcyMvLA8MwePTRR7Fv3z7U1NSs6vg6nU7s2LED119/PT760Y+u+Pze3l586EMfwg033IDHH38cp06dwuc+9zkUFRXhoosuivp1SQwSKzI1NYXGxkYEg0Hs3LkTZ86cSWjDQ7SERgaTCcMwGBgYgMViQW5uLtclLKQLTbKPERFfpFLpoqJ5j8fDicOhoSFYLBYwDBNWMJ+VlbXsTZ2YBBKlidOfeHgrZmZmci4BtbW1OHHiBCwWC+666y789a9/xUMPPYQvfOELyMzMxN69e7Fv3z58/OMfx86dO6Pa/iWXXIJLLrkk6vU89NBDqKiowD333AMA2LRpE9588038x3/8B4lBIj54PB5YLBYMDw9j48aNqKqqgtfrBSDMi0RoZDBZzM7Owmw2Y3Z2Frt27UJRURFaWlrg8/mStqaFUM2gOMjMzFzkycbWRFmtVrS2tsLhcECtVoellw0Gg2BLLviE0sTpDx8eg1KpFNu2bcP+/fsxNzeHZ555Bj6fD01NTXj33Xfx7rvvoq+vL2oxGCunT5/GhRdeGPbYRRddhK9+9asxbYfEILEIhmHQ39+PlpYW5Obmor6+nuuSYk8eQjyRJDMyGAwG0dnZic7OTqxfvx779u3jzLaFJoyEth4iMSxlbcNGDycmJtDe3s5NdMjOzobP54PH4xGFKBTDPoYilHKaRMLnPofWDCoUCuzevRu7d+/GDTfcwMvrsYyOjnJepiwFBQWw2+0x1TGSGCTCmJ6ehtlshtfrxe7du7moAkuoGBQayVrb1NQUTCYTpFJpxM5qofkfUmSQYGEtN1iLo9CJDlarFT6fD2fPnoXFYgnrXE6UtU0iEWOaWEziF+B3BB9ZyxBpgc/nQ2trKwYGBlBVVYUNGzZEvIMSshhMdJrY6/WipaUF586dQ21tLSorKyOeaIRmeSO2CwARPQsnOoyPj2P79u2Qy+Vh3oderxd6vT6sOWW5ebCpgNjEkRgjg3yNogOSZy1TWFiIsbGxsMfGxsag1+tjWg+JQYFhtVohk8kSZj/CMAzOnTsHi8UCvV6PY8eOQavVLvl8IdTlLUcionAMw3Au9gaDAXV1ddBoNEs+X4hRMooMro103rdQGIZZ1FHJMEyYtU1vby9MJhNkMllY9DArKythc8nXCvt+ik0Miml/AX4FsMvl4n2ufCQOHjyI559/Puyxl156CQcPHoxpOyQGBUZ/fz9UKlVCxKDdbkdjYyOcTie2bduG4uLiFU8OEolEsJM+AP6jcC6Xixu9t3XrVqxbty6qYyYk8SC09aQqYruQskgkEqjVaqjVaqxbtw7A3+fBstFD1o8tdNxXdnb2msZ98Ql7zhBbmliMkUG+3mO32x2XiVKzs7Po6uri/s3ebGVnZ6OsrAzf+ta3MDQ0hEceeQQAcMMNN+CBBx7AN77xDVx//fV45ZVX8N///d947rnnYnpdEoMCQyaTcS7pfOH3+9He3o7e3l6Ul5dj//79Md3BC1kM8hUZDPVZLCkpQX19fdSGvkITX1QzSERLtE0VkebBzs3NhVnbNDc3A0BYajkrK0sQNlUUGRQHfKaJ41Uz+P7776Ouro779y233AIAOHHiBB5++GGMjIxgYGCA+31FRQWee+45fO1rX8NPfvITlJSU4Be/+EVMtjIAiUHBwafQYhgGo6OjaGpqgkqlWvU0DKGLwXivzWazwWw2IxAI4ODBg2EGpNEgNGGUqAuAkPaZWB1r6bBVKpUoKipCUVERgHnxEWptMzw8jNnZWW6aA/sTam2TKMQqBsUWGUxUN/FaOHbs2LLnzocffjji3zQ0NKzpdUkMCgyZTMZ5+cUTp9OJpqYm2Gw2bNmyBaWlpas+8QlZDMZTePn9frS2tqK/vx81NTWorq5e1YlEaN3EQGJqBgkiFKlUCoPBAIPBgPLycgDzTVjT09OwWq0YGxtDW1sbAoEANweWjSDyXZgv1jSx2L6n1E28NCQGBYZUKo1rmjgQCKCrqwudnZ0oKSnB8ePH1zyvVMhiMF5rGx0dRWNjI9RqNS644II1FQYLsZtYaOKUECZ8e+9lZGQssraZnZ3l0ssdHR2YmZmBUqkME4dGozGuER6KDIqDdOwmjhckBgWGTCaLm3AYHx9HY2Mj5HI5Dh06hOzs7LhsV8hicK3Cy+12o6mpCZOTk9iyZQs3Sm6taxKS+KKaQSJaEm3ELJFIoNPpoNPpUFZWBmA+Qs9GD6emptDV1QWv1wuDwRDWnKJWq1e9VrGJQYZhROerCPDfTUyRQSJuxCMy6Ha70dzcjPHxcWzatAkVFRVxPckJWQyuNiXLMAz6+vrQ0tKCwsJCHD9+PG6F7UITRkJbDyFchDCVQy6XIzc3F7m5udya3G4317nc29uLhoYGKBSKMHFoNBqjboxjU6bJ3tdEIca0ODAfGeTLLJ0ig0RcWUtkMBgMore3F21tbZygWW4I/WoRuhiMdW12ux0mkwkejwd79+6Niz1AKEIUXxQZJFKVUGubkpISAPMX+ZmZGS693N/fD7fbDZ1OF9a5vJS1jRBEbyIRsxjkq3udIoNEXFltZHBqagqNjY0IBoPYt28f8vLyeFjdPEIWg7GIkEAggPb2dvT09KCiogIbN27k5a5RaA0kibjokRhMD1JFJLGG16GlMHNzc1z0cHBwEE1NTZBIJGHRw6ysLGRkZIiumUKsYjAVuomTBYlBgRGr0PJ4PGhpacHQ0BA2btyIqqoq3r/gQhaD0a5tYmICZrMZCoVi1RY7sSCk40VCjYiWVBGDkVAqlSguLkZxcTGA+e+g3W7noodNTU1wOp3QaDTQarVgGAbT09PQ6/VpL5LEKgapm3hpSAwKjGhNpxmGQX9/P1paWpCTk4P6+vqEfRCFLAZXaiDxeDxobm7G6OgoL/WUkRBiZDAR6xHSPvNBqooksSKVSmE0GmE0GlFRUQFg3trGZrNhZGQEDMPgr3/9KxiG4axt2J9UjvhEQmw1kix8dROzdayp/DkhMSgwohFa09PTMJvN8Hq92L17NwoLCxO0unmELAaXEl4Mw2BwcBAWi4UTz4n64gotEpeobmIi9UnlyGA0ZGRkoKCgAAqFAmNjY/jgBz/IGWPbbDa0t7fDbrdDpVKFpZYNBkNK27IEg0HRRQUB/tLEXq8XwWCQIoNE/FguMujz+dDa2oqBgQFUVVWhpqaGt86o5RCyGIwUGZydnYXZbMbs7Cx27tzJTURI5JqEJAaB8Kjd9PQ0Ojs7oVKpuLorPhqP0gmhvZ98ke5ikIXdT4lEAr1eD71ej/Xr1wOYP+9OT0/DZrNhcnISHR0d8Pl8MBgMYc0pa7G2STRiFYN8RQbdbjcAUGSQiB+RhBbDMDh37hwsFgv0ej2OHTsGrVabpBUKWwyGRgaDwSA6OzvR2dmJsrIy7Nu3L6YZzPFCaGKQvWCFNtCsX7+e+7fdbodareaEYXZ2NnQ6XUwXD6HtMxE7YvLeW070KhQK5OXlcU15DMPA5XJxY/W6u7sxMzODjIyMRdY2ybhZjwYxi0E+9tvlcgEgMUjEkYXWMg6HA42NjXA4HNi2bRuKi4uTfnIWuhgMBoOYmpqC2WyGRCLB4cOHkZWVlbQ1CU0YSSQS+P1+vPbaa5DJZIsaaHw+H3ehGxkZQUtLCxiG4S5y7M9ywlpo+0wQyxGLOJJIJNBoNNBoNIusbUK9D+fm5qDX68Oih1qtNunnb0C8YpCvNLHb7YZCoRCs+I+G1F15msJay/j9fnR0dKCnpwfl5eVJi2pFQshikGEYDA0Noa2tLWHd1SshpOPl9/vR09MDj8eDqqqqiMdHoVAsGhFmt9thtVphtVoxNDQEp9MZ5uGWnZ0tmAsdER8oMhg9kaxt3G53mO+h2WyGTCYLa0xhrW0SjVjFIF9pYpfLldJRQYDEoOBghcMrr7wClUqVENuTWBGSuGFhGAbDw8MYGxuDSqVCXV0dNBpNspcFQDhRsvHxcZhMJigUCmRkZKCmpiaqv5NIJDAYDDAYDFwXpsfj4cThwMAAN/aQFYZ+vz+uM7aJxCM2MRhvcaRSqaBSqRZZ27DRw3PnzsHpdEKr1Yall2MtyVgNYhaDfOy32+1O6eYRgMSgoHA6nTCbzQCAmpoalJeXC/JEHI+RefHE5XKhsbER09PT3AlVKEIQSL4Y9Hq9aG5uxsjICDZv3gy9Xo/3339/TdvMzMxEUVER14wTDAa5Inur1QqHwwGTyYTe3t6w1LJKpRLkZ5pYjJjEYCJMp0OtbVg8Hg8XPRweHg4ryQj9iXdDl1jFIF9pYooMEnEhEAigq6sLnZ2d3F1kSUmJYE/CUqkUPp8v2ctAMBhET08P2trasG7dOtTX16O1tTXZy1pEMsXg8PAwGhsbYTAYUFdXB7VaDZvNFvf1SKVSTvBVVVXhzTffRGFhIZRKJaxWK7q6umC325GZmRkmDg0GgygvSoSwSFbXdGZmJgoLCzl7MIZhOGsbq9WK1tZWOBwOqNXqMHG4VmsbMYpBhmF47SamyCCxJsbHx7kU26FDh2A0GjE4OIhAICCYGsGFCCFNPD09DZPJhEAggAMHDnBD7FcynU4GyRCDc3NzaGxsxOTkJLZt2xZ2c5Eon8GMjAyUlJRwRfZ+vx/T09OwWq2YmJhAe3s7AoEAjEZjmEDka3YoERtiigzykSZeDUtZ27DRw4mJCXR0dMDv98NgMIR5H8YSdRejGORz6kqqG04DJAaThtvthsViwdjYGDZt2oTy8vJFtihCJZli0O/3o7W1Ff39/aiurkZNTU3YnZ7Qpn0AiRWDrLl2c3Mz8vLycPz48UXiKlFicOFryOVy5ObmcsKdYRjMzs5yNVRsFESj0SyytRGiIBHimuKJmMSgkGcTR2rocjqdXPSws7MTdrsdGRkZYZ3Ly1nbiFkM8pUmpsggERPBYBC9vb1oa2tDYWEhjh8/HlYPIpFIoh5JlyySJQZHR0fR2NgItVqNCy64ADqdLuLahJDCDiVRx8vlcsFsNmNmZga7du1a0lxbKBc9iUQCnU4HnU7HRUHY8WBs13JzczMkEkmYrU1WVpZgo+ZEapJK5toSiQRarRZarRalpaUA5m+SQ61turu74fV6odfrw5pTNBoNlz0Rmxhkr6l8pYkpMkhEzdTUFBobGxEMBrFv3z7OxHQhQkjDLkei1zc3N4empiZMTExgy5YtKCsrW/LEnexmjUjwvSaGYdDb24uWlhasW7cOe/bsWdGuIhmRwWhgx4MVFBQAWNyBOTg4CJfLFebfFnqRSxRC+4zxgdgig6ksjuRyOXJycpCTkwNg/r2bm5vjvjcLrW2AeQHp8/lEc2PFikE+Ps8UGSSiwuPxoKWlBUNDQ9iwYQOqq6uXPfEIrVt3IYkSgwzDoK+vDy0tLSgoKEB9ff2KXXVCFNLsyYeP6APbtTs3N4d9+/ZxqaSV1pMqYiZSByZ7kbNarejr64PZbIZcLg9LLRuNxpSeHSsExCQGUykyGA0SiQQqlQrr1q3DunXrAMwL3pmZGU4cOp1OPP/889BqtWE3VkIty1grbCcxH/tGkcEUIhAIoLe3F5WVlQm7A2QYBv39/WhpaUFOTg7q6+ujuntYOIVEaCRCcNntdpjNZszNzeG8887jIkUrIdQGEiC+F5xgMIju7m60t7dj/fr12LRpU9Tu98mqGYwXSqUSxcXFXOd96PQHdjyY1+vlZseG2toQ0UNiML2QSqVcytjn88HpdGLz5s1ccwpblgEgLLWclZWVFk1dfHUSAxQZTCkYhoHFYkFZWVlCHN+np6fR2NgIj8eD3bt3c9YB0SDE6FYofK4vdF5uRUUFNm7cGNOIH6E2kADxSy3OzMygoaEBgUAAhw4dCpt6EO16hHaM1sLC6Q/s7FhWHHZ2dmJmZgYqlSosAkK2NgRLqqeJY4XdX6VSGeYXyk4bYgWixWLB7OwsN6s81Nom1Y4XX4bTAEUGUwr2joDv9KvP50NraysGBgZQVVWFmpqamOcVirWBZGJiAmazGQqFYtWTV4QYGWRPQGs1PA0EAujo6EB3dzeqqqqwYcOGVW0vERGQZArO0NmxbIG9z+fjbG3Gx8fR3t6OYDC4yNYmGaPBhApFBtOXpcRv6LSh8vJyAPNNXex3Z2xsDG1tbZwl1EJrGyHDd2QwUkNjKiEaMSiRSHitxWNn4jY3N0On0y3Z7RoNYosMejweWCwWjIyMYNOmTaioqFj1iVnIkcG1YLVa0dDQAJlMFpcRhUI7RnyjUCiQl5fHNW0tNPdlIyBiqZ+KBjEJJDHtKxBbJDQjI2ORtc3s7CwXPezo6MDMzAyUSmWYOBRa3S5f00eA+chgNPXaQkY0YhDgT2Q5HA40NjbC4XBg27ZtKC4uXvPQczFEBllPPIvFguzsbNTX16/57lKIQpr9LKxmXaG+ihs3bkRVVdWaUx18NrSEvoaQBWckc192NJjVasW5c+fQ3NzM1VmFNqaIpftSTIgxTbzaz3GoJVRZWRmAvxvK22w2TE1Noauri7O2CU0vJ7rrPxQ+08RUM5hiyGQy+P3+uG3P7/ejo6MDPT09WL9+Pfbt2xeXC4UQBU0o8Vjf7OwszGYzZmdnsWPHDq4ZYK0IUYSstmZwfHwcZrMZSqVyTZHm5dYjpmjISiwcDRZqa2O1WtHf3w+3281FZeVyOZxOJ9RqdVoeRzF9PsS0r0D8xW8kQ3m3283dXPX29qKhoQEKhSKsOSWRN1d8pompZjDFiGeX7sjICJqamqBUKuOStgslnSODwWAQnZ2d6OzsRFlZWdwEdDzWxhexikGfz4fm5mYMDQ1h8+bNa0qbL7cePhGiKI+VUFubyspKAPMnfXbWssPhwKlTp7jJD6HzloWUHlstYhJIYtpXgP9IqEQigVqthlqt5qxt2K5/Nr3M3lzpdLqw6CFfpRl8pokpMphixENkOZ1ONDU1wWazYfPmzcsaIK8WIQqaUFa7PqvVCpPJBIlEsqouWD7XxiexiMGRkRGYzWYYDIaorYhWS6qLtWTAerfZ7XZ4vV5s3bqVK66fmppCZ2cnNzc2VCCu5I8pRMT0+RBjmjjR+7uw6x+Y9wxlo4eDg4NoamriJg6F/sTD2oa6iZeHxGCUBAIBdHV1obOzEyUlJTh+/DhvnYfp5jPo8/nQ0tKCwcHBuNW9LYVQI1IrNbaETlnZunUrSktLea3nA/i92Av1fYgX7L7JZLJFkx+cTic3+aG9vR12uz3MmiM7Oxt6vT4lxIdYomUMw6TE+xEvhCJ+F1rbBINBOBwO7vszNDQEp9MJjUYTll5ezfeHfAaXh8RgFIyPj6OxsRFyuZy3iFYo6TKBhGEYDA8Po6mpCXq9HnV1ddBoNIJYW6JZyvKGYRicO3cOTU1NyMvLi2rKSjzWwr42EV9C58ayxfU+n4+LfoyOjqK1tRUMwyyatyw0WxsxpU7FtK+AcMTgQqRSKWdtU1FRAeDv88ptNlvY94e1tmF/VorM8d1NTJHBFCJWMeh2u2GxWDA2Noba2lpUVFQk5AuUCpFBhmGWPYG6XC40NjbCZrNh69atKCkpSVitmhCPXaRImdvthtlsxvT0NHbu3Bm3Jppo1pKI1yCxOY9CoVhkzcFGP6xWK5qamuB0OjlbG/ZHq9UmVaCISSAJVRzxRSrt78J55ay1zcLou0qlCoseLqzdpW7i5SExGIFgMIje3l60tbWhsLAQx48fT2jNj1Qqhc/nS9jrxcpyJsrssWttbcW6det4TacvtTYhipBQcRQ6c7moqAj19fVJiQrxfZyE+D4IgVBbG9bY1+PxcOJwcHAQjY2NYTVWbOdlrAb28VirGBCT8AVSSwwuJNTahrWFYk3lWWubzs5O+Hw+GAwGThzOzc3xdp6lyGCKEY0YtFqtMJvNCAaD2LdvH2dSm0iEmupkWUoMTk9Pw2QyIRAI4MCBA5zNQCIRemRwdnYWJpMJLpcLe/fuTYpRaaJqBonoyczMXFQ7FTpvube3Fx6Ph/NtC523zNexFpOYp5rB1CaSqbzL5eLKM7q7uzE9PQ2ZTAaXy8VFEONlbeNyuUgMphLLiUGPx4OWlhYMDQ1hw4YNqK6uTtqXJRWsZYC/myj7/X60tbWhr68P1dXVqKmpSZq1hlAjgwAwMDCAgYEBlJWVYf/+/UkzL6aaQeHDml1nZWWhqqqK821jxWFXVxfsdjsyMzPD6g6NRmPczltiipYFg0HR7CuQfmJwIaEjKUtKSgAA77//PmQyGXQ6HWw2G/r6+uB2u6HX68PSy7GWZ7DfTUoTpxCRIm4Mw2BgYAAWiwU5OTm823lEQypFBkdHR9HY2Ai1Wh1XY+S1rE1ox25mZgY+nw+jo6M4ePAg13maLKibOPUI9W1jL27s1Aer1YqJiQm0t7dzM2NDBeJaSlzEIpDEJHyB9BeDkWBnkVdXV3OPscbYNpttkbVNqPfhcullr9eLYDBIkcFUYuEEkpmZGZjNZng8HuzevZubPJBshB4ZZE+aJpMJNpsNW7Zs4cVvcTUIKU0cCATQ2dmJrq4uyGQy7Ny5M+lCMJGQGOSXSFMfQgvrW1tb4XA4OFsOViDq9fqovqtiev8oTZz+RKpxV6lUUKlUXPNe6NQhm82Gc+fOcc1dodFDnU7HHT+32w0ASQ8irRXRiUGv1wufz4e2tjb09/ejqqoKNTU1CS/MXg4hRrdY2OYHlkRYocSCUNLErMG2VCrFkSNH8P777wtCLANUM5iuRCqsZ205rFYrhoeHYbFYwiIfbPQjUsmCmKJllCZOf6LpJg6dOsTCziy32WwYGRlBS0sLgsEg7r77bmzYsAGbN28GgLhEBn/605/i7rvvxujoKHbs2IH7778f+/btW/L5J0+exIMPPoiBgQHk5ubiiiuuwF133bWqa7JwFFACkEql3AgpnU4niLRmJIRqLWO322E2mzE3NweZTIbNmzcLSggCyY8MhtZPhtaeCi1tyvd6hLa/YmWhLUeoqS/buexyubiRYOyPRqMRlRgU074C4hWDq6llXziznGEYLvL+9ttv49577wUAVFdX48CBA9zPrl27Ypqc8uSTT+KWW27BQw89hP379+PkyZO46KKL0N7eHrHR8IknnsCtt96KX/3qVzh06BA6Ojpw7bXXQiKRcGuKBdGIQYfDgYGBAbjdbuzatQvr1q0T7JdfaKbTgUAAHR0d6O7uRkVFBTZu3IiXX35ZkIKVPcEl4+Q+MTEBk8kEpVK56EZDaOJIaOtJNVL12EUy9Z2bm+PSYv39/TCbzZDL5dBoNPB6vZicnEyKrU0iEZs4Etv+AvEznZZIJMjOzsY3vvENAEBTUxMOHz6MX/ziF3j77bfx8ssv44477oDD4cBNN90UtTC799578fnPfx7XXXcdAOChhx7Cc889h1/96le49dZbFz3/rbfewuHDh/HJT34SAFBeXo6rr74a77zzzqr2K32/3X/D7/ejo6MDPT09XDE1W4AtVIQUGZyYmIDZbIZCocDRo0dhMBgACDeVzQpAPt3mF+Lz+WCxWHDu3Dls3rwZFRUVi4SoUNLXLIkQg0LaXz4Q6s1krCiVShQXF3N1U4FAADMzMxgYGIDdbsf7778Pr9e7aN5yqhfMh0KRwfSHr3F0brcbGo0GF154IS688EIA85+n7u5urp5wJbxeL86cOYNvfetb3GNSqRQXXnghTp8+HfFvDh06hMceewzvvvsu9u3bh56eHjz//PP4zGc+s6r9SGsxODIygqamJiiVShw9ehQOhwO9vb3JXtaKCCEy6PF4YLFYMDIygtraWlRWVoadLIUqBkMjg4lgdHQUZrMZOp1u2U70ZKevI0E1g0QkWLNrn88Hq9WKurq6MM+2zs5OzMzMQKVShc1bNhgMKSswxNRAwjCMaMUgH/scyXBaIpGEdS2vxOTkJAKBAFfOwVJQUIC2traIf/PJT34Sk5OTOHLkCBiGgd/vxw033IBvf/vbse8E0lQMulwuNDU1YWpqKqzT1eVyJV1kRUMyhRY7K7e5uRnZ2dmor6+PGAEQuhjke20ejwdNTU0YHx+PqptaaGnZRIg1Ie0vETtstCySZ5vf7+fE4fj4ONrb2znrjtDGlFhqppKJmBpI2O+l2MQgX9miZI2ie+211/Cv//qv+NnPfob9+/ejq6sLX/nKV/DDH/4Q//Iv/xLz9tJKDAYCAXR3d6OjowMlJSU4fvx42MlI6JYtLMla5+zsLMxmM2ZnZ7Fjxw4UFRUteYIUqhjku1OWYRgMDQ2hqamJ86WMpolGiGKQIoPEapHL5YsmPjgcDk4gWiwWzM7OQqPRhKWWdTqdID8bYkoTs+dtsYlBPtPEay2ZyM3NhUwmw9jYWNjjY2NjS1re/cu//As+85nP4HOf+xwAYNu2bXA6nfjCF76A73znOzG/v2kjBicmJtDY2AipVIpDhw4hOzt70XNSRQwmWmgFg0F0dXWho6MDZWVl2Ldv34rTMYQqBvmMDLrdbpjNZkxPT68olhciRjEopP0lYicWgRQ6bznU1obtWh4aGkJzczNXfB9q6JusSTyhiCltKmYxyMc+xyMymJGRgT179uDUqVP4yEc+AmD+fTp16hRuvvnmJV934f6wYnc1596UF4Nzc3Nobm7G2NgYamtrUVFRseQbLlQBsxBWtCbibpX1w5NIJEuK6EgI9ViGNpDEC4Zh0N/fD4vFgqKiItTX18c88Fxo4kho6yGEx1rPPxkZGWGWHKGGvlarFf39/dw4sNDooVqtTniUjiKD6Q3DMGAYRrCRQQC45ZZbcOLECZx33nnYt28fTp48CafTyXUXX3PNNVi3bh3uuusuAMBll12Ge++9F7t27eLSxP/yL/+Cyy67bFX7mbJiMBgMore3F21tbSgoKFiyti2UhRNIhEoi7FF8Ph9aWlowODi4qlnMQhWDQHw7d51OJ0wmE5xOJ84777xFBb7JWFMqIMSGGSK5hBr6VlZWAvj7ODCr1Yre3l40NDQgIyMjrDHFaDTy7gwgRjEolv0FwGUEhVwzeOWVV2JiYgK33XYbRkdHsXPnTrzwwgvcNWdgYCDsGv3d734XEokE3/3udzE0NIS8vDxcdtlluPPOO1f1+ikpBq1WK8xmM4LBIPbt28fVrawEa9ki9C8++4HlI6zNMAxGRkbQ2NgIvV6Puro6aDSamLcjZDEYDyHCWgO0tbWhtLQ0qtQ532uKJxQZJFYiEefJhePAAoEAN2/ZarWiq6sLPp8vrDElOzs77mb3YksTs0b4YoEVg4nqJl4tN99885Jp4ddeey3s33K5HLfffjtuv/32uLx2SorB4eFhrFu3DlVVVTEpfZlMxoWLhfxF4KvuzeVyobGxETabDVu3bkVJScmqj4OQxeBao3B2ux0NDQ3w+Xw4cOAAN/t1LQhNfFHNILESyThPymQy5OTkcDO8GYaBy+XixGF7ezvsdjvUanVY9FCv16/pQi/0a0I8EZPwZWGvVUKODCablBSDW7duXdXf8RlxiyfxFoMMw6Cnpwetra1Yt24djh8/HnPN20KELgZXs7ZgMIiOjg50dXWhoqICtbW1cTt5CE0cCW09qUi6iwchCKRQW5vS0lIA8yUubGp5dHQUra2tYBhm0bzlWM5xQtjXRCFGMche8/l4j+MZGUwmKSkGV0uoGBRCB9tSSCSSuBlPT09Pw2Qywe/3xy3KBQhbDK5G6NhsNjQ0NEAikeDw4cPIyspK+pr4hCKDRDQIUSApFArk5+dz81pZWxs2etjU1ASn0wmtVhuWWtZqtUvuj5gEkpj2lYXPABA72zvVEZUYZO8MxGAv4/f70dbWhr6+PlRVVWHDhg1xDZELWQzGsja/34/29nb09vaipqYGNTU1vJw0xNZAQqQ+qfJ5DbW1KS8vBzBvCs+Kw8HBQTQ2NnKTVdgIYlZWFjdvmSKD6Q2f40ndbjd3Y5LKiEoMAqnjNbiWdY6NjcFsNkOlUuH888+HXq+P8+qELQajbdaYnJyEyWRCRkYGb8cpFCEdL4oMro103jeWVBZImZmZKCoqQlFREYD5797MzAwnEPv6+uDxeDhbm2AwiLm5uWWjh+mCGMUgX4bTANUMpiypIgZXI7bm5ubQ1NSEiYkJbN68GevXr+ftxCZkMbhSFC7UVmfTpk2L5i4nY02JZqFYc7vd8Hq90Ov1aX8xJKInXT4LUqmUM7muqqoCMP+ZZ8UhwzA4ffo0Z2vD/hgMBt5tbRKNWMUgX/tMNYMpSqqIwVjWGWqKzHouxtt6YSFSqRQ+n4/X11gtywnV0dFRmM1maLXaVdvqrAahRcrY9TAMg97eXrS0tHCPsxfCnJwcGI1GLpW2mu0TqUu6v38qlQrr1q1DcXExenp6UFdXx6WXp6am0NnZCb/fv2jeMt/nVr4RqxikyODyiE4Mxqsxg2+ijbzZ7XaYzWa43e41mSLHipAjg5GEiMfjQXNzM0ZHR7F161aUlZUlNOohNHEkkUgwNzeHv/71r3C73di/fz9ycnJgt9sxNTXFmQB7vV7uYpiTk4Ps7Oywed9E+pLKaeJYYL+XGRkZ0Ol0XJMdwzBwOp1c9LC1tRUOh4OztWF/Ui2aLkYxyHfNIEUGU5BUigwuJ7YCgQA6OjrQ3d2NiooKbNy4cVURnNUiZDEYujaGYTA8PIzGxkZkZ2dHNamGD4QkBhmGgcfjQVNTE8rKyrB//36uu56dEFFVVbXI4429GGo0Gk4Y5uTkQKPRLLoYCml/idUhFjG41EQOiUQCrVYLrVaLsrIyAPPzlllbm5GREVgsFgAIE4dCmbe8FEK3VuMDvruJSQymICuJLKGwXARzYmICZrMZCoUCR44cgdFoTOziIGwxyDaQuN1uNDY2wmq1Yvv27SguLk7axU0o4sjlcqGhoQEejwc1NTXYtGnTks+N5PHm9Xo5cTgwMIDGxkbI5fKwyGEyPo9E/BHC5zURsPsZzbkhIyMDBQUFXAaGYZiwecuDg4Oc1UioQIx0w5QsGIYRpRjkMzJIaeIUJFUig5HEltfrRXNzM4aHhxPW+BDL+oSCRCLB5OQkmpqaUFhYiPr6+qSnNpNdnhBaV7pu3Tr4/f5VdU9nZGSgsLAQhYWFAOZPsjMzM5iamsLU1BQ6OjoQDAaRmZkJmUyGsbExZGdnCzpSQiyNUAQMn7BicDUCSSKRwGAwwGAwoKKiAsB8I5/VaoXNZkN/fz/MZjN3wxQ6bzmRmZxQxBgZ5DNNTJHBFCVVxGDoOhmGwblz59Dc3MylOpN9JyJUMeh0OmG32zEzM4M9e/ZwoiXZJDMy6HK5YDKZ4HA4sHfvXuTn5+ONN96Iy7ZZ77bs7GwA85/V2dlZtLa2YmZmhjMAZi082Ohhsj+/8SDdhZLY08SrRalUori4OGzecqitTU9PD7xeLwwGQ1j0MFGCQqyRQT67idPhfEZiUKCwYsvpdMJsNsNut2PHjh0oKioSxAlaaGIwdOReRkYGKioqBCMEgeSIQYZhMDAwgObmZhQXF2Pv3r1hETo+1iORSLgUmUQiwd69e7lIydTUFLq7u3H27FkolcqwruVUK8IXA2IRg7GkiVdDpBumUFubzs5OzMzMhH0nWFsbPgSMGCODfHcTU2QwBUklMTg+Po62tjaUlpYuupAnGyGJQbvdDpPJBK/XiwMHDqC3t1dwF7FEi0G32w2TyQS73R6xyzyR61kYKfH7/WGzZVtaWuJmaZMoxCKUxEAwGIREIknY+ymRSKBWq6FWq1FSUgIg/DsxMTGB9vZ2BINBGI3GsJnL8Sh3EWNkkK80MSvsKTKYgqSCGLRarRgbG4NEIsGhQ4e4O0ohIQQxGAwG0dnZic7OzrCO6r6+vqSvbSGJEl8Mw2BwcBBNTU0oKipCXV0dMjIyEr6e5bYvl8uRl5eHvLw8APPvY2gRPjsdwmAwhHUtJ7vuU2yIRfAKYT8XfifYcgv2O9HS0oLZ2VloNJqw6KFOp4t57WKNDPJxc+n1ehEMBikymIoIWQyGTsZga6yEKASB5IvB6elpNDQ0gGEYHD58GFlZWWFrE1onZCLEoNvthtlsxvT09Ir1kolYT7Tbl0qlnKVNZWUld7fN+h22tbUtsrTJzs4WxeiwZCIEkZQIhLifbLmFTqfD+vXrAYTb2gwNDaG5uZmLqIfOW14pgyTGyGAgEODlZtLtdgMARQZTEZlMBq/Xm+xlhMEwDEZGRtDY2Ai9Xo9jx46hv79fsKIVSJ4YDAQCaGtrQ29vL2pqalBTU7PoxBbtbOJEwufxYhuMmpqauAk0kaKBiWQtF9fQNFqopY3NZsPU1BQGBweXtLQR20WOWDupYsK80NZmYUR9YGAAbrc7LJDANmuFfh/5ipIJGb7SxC6XCwAoMpiKCC0yGOqFt3XrVpSUlEAikUAmkwl23BuQHDE4OTkJk8kEhUKB888/f0lrFDFFBufm5mA2m2Gz2bBr1y4UFRUldT18sfBCuNDShh0dxkZIWIEopDrbVEOIETM+SNX9XBhRB+avJ2z0sLe3Fw0NDcjIyAirOwwEAkm/WUw0fKXG3W43FApFWojr1N+DGEm23xtLaPdrcXHxIi88oaxzKRIpBkPT57W1taiqqlr25J3sFHYk4i2+GIbB0NAQGhsbkZ+fj7q6upjSIMmsGYwHS1nasF3LS1naqFSqlLzwJ4NUFUmxwjaQpAMqlQoqlSrM1mZ6epqLHnZ3d8Pj8UCpVCIQCHCp5XSIbC0HX93E6dJJDIhQDAphAsn09DTMZjN8Ph/279/PFQ2HIoR1LkeiBNfY2BjMZjM0Gg3q6uqg0WhW/BshRr3iuSaPxwOz2YypqSns3LmTO/Enaz1CIFKNFWtpw14Ez549i8zMzLCmFLK0WRqxiMF0rqGTyWTIyclBTk4OgPl9feedd7gMWXt7O+x2O1Qq1aJ5y+l0TPhKE6dLJzEgUjGYrIib3+9HW1sb+vr6UFVVhQ0bNiz5ARV7ZNDr9aKpqQmjo6PYsmUL1q9fH/WFSSqVCi7FHi/xxUYDc3Nz1zRZJdUjg9GwkqVNa2srACArK4sTiFlZWWmR8iGiRyyiFwBnoZOdnY2qqioA85kXm80Gm82GsbExtLa2gmEYZGVlhaWXUzm1zFdk0O12U2QwVUmWGGQjXCqVatl6NxYhpjpD4Wt9oc00RqMR9fX1MX/ZhNhAstY1eTweNDY2YnJyEtu3b8e6deviuLr4IwQxuJBI9h12u53rWo5kaZOdnQ2lUhlxe+kuIMQiktIpTRwNCyOhCoUC+fn5yM/P537vcDi4qHpzczOcTie0Wm1Y9DCVuvn5qhl0uVwUGUxVEi0G5+bm0NzcjLGxsZgiXEJrdFkIKwbjecGYm5tDY2MjpqamsG3bNqxbt25V2xZiA8laTkTDw8Mwm83IyclBXV3dkuIkFoQo1hJN6FzZUEsbtu6QTaGx3m6sQNRqtcleekIQixhM5zRxJFYSRhKJBHq9Hnq9HuXl5QDmb0bZqDrbzS+TycIih0KOqvOZJqbIYIqSKJHFMAz6+/vR0tKCvLw8HD9+PKaLeCpEBoH4XDDYsWkWiwX5+flrSn8C6RMZ9Hq9aGxsxPj4OBcNjNfFWUg+g0Ih0mQIn8/HicNQSxu5XA6VSgWr1QqDwcDbqKtkIxYxKIb9ZFmN+M3MzERhYSHnXRoMBrl5yzabDf39/XC73RHnLQvh2PLZQEKRwRQlEWLQ4XDAZDLB7XZjz549i0aBRUMqRAaBtXt0uVwumEwmOBwO7N69Oy7zhIUYGYxVfI2MjMBsNiMrKwv19fVxiQauZT2r2X46oFAoFnm7TU9Pw2KxYG5uDu+8884iS5usrKyUrq9iEYtIEluaOB4pU6lUytUUsoTOW2YbtjIyMhbNW07GjROf1jIUGUxR+BRZgUAAHR0d6O7uRnl5OQ4ePLjqsHmqRAZXu8ZQa52SkpK4zl4WamQwGvHFNs6MjY1h27ZtnO8kHwhNMKcCUqk07KK2efPmsLFhrKWNTqcL61oWSoQkFsSSPhXLfrLwtb8qlQrr1q3j6pn9fj9naxPqBWo0GsOmpsT7RjcSfJpOU2QwReFLDLKGyHK5HEeOHIHRaFzT9lIpMhgrbOR0bm5uSWudta5NaEInGjE4OjoKk8kEo9GIuro6Xu84+RYmYqlJXMnSpqenBw0NDWGWNqyYFLo4FEtkUCz7yZKo2cRyuRy5ubnIzc0FMH+cnU4n991gx0yq1epF85bjuT6GYaibOApEKQYZhonbCCKv1wuLxYKhoSFs2rQJFRUVcdluOkYGg8Egurq60NHRgfLyctTW1vJScCzEY7ecQPX5fGhqasLIyAi2bduG0tLSlBdrYhGDkYhkaTM9PY2pqSnOugMgSxuhkCrj6OJFsvZXIpFAq9VCq9WirKwMwN9tbaxWK0ZGRmCxWAAgrDFlrZOE2GsBdRMvj+jOPuzdwVrvjth5sM3NzVxdVzw/FEIUNAuJZY3T09MwmUwIBoM4dOgQNzmCD4QoRJZKXY+NjcFkMkGv16/KRmct6xHaMUpXIkVIlrK0Ce1aTkT6bDnEEjETy36y8JUyXQ2RbG1C5y0PDQ1xZRehXcux2Nqw512KDC6P6MQgKwADgcCq7zacTifMZjPsdjt27NiBoqKiuJ9MhJ4mBqITg6zLfU9PD6qrq1FTU8P7iUiIQnqh+PL5fGhubsbw8DC2bt2KsrKyhF6QKDKYPBZa2gDzEYalLG1YgZhoXzexiCSx7CeLkBtmQr8bFRUVAObLLtjoYX9/P8xmM+RyeVj00Gg0LhlZZ6+jfNUMpovVlGjF4GrEQmias7S0NK5NDwth04pCPlGtJLqmpqa4OsqjR4/CYDAIYl3JIFQcjY+Po6GhATqdDnV1dUlLM5BYEw5LWdpYrVacO3cOTU1NkMvlYeKQ785MIZ974okY08RCiQxGg1KpRFFREYqKigDMi7tQW5uenh54vd6Itjbs8wF+6qTdbjcX1Ux1RCcGJRLJqqJuVqsVZrMZDMPwnuYEwtPZQq0lWkp0+Xw+tLa2YmBgALW1taisrEzoyVaIUSk2TWwymTA0NBTziD0+1sP39oX2HqQSS1nasNHDrq4urjMztDElHSxtEo1YRC+LkCOD0SCTybjPO4Aws3ir1YrOzk7Y7XZkZmYiOzsbGo2GC67Ee79dLheliVOZWMRgqLDZsGEDqqurEyJs1mrdkggiicHx8XGYTCao1WocO3YsKSF0IUYGp6enMTc3B6fTmdRoIIuQxBrrS+b1emE0GlFbW5tSkYtEwFraZGdno7q6muvMZOsO2ZFhoZY22dnZUKvVq74AikUkic1aJtUigysRySw+dA75+Pg4gsEgnnvuuUXzltcy3ACYjwwm+1weL0gMLgE7I7epqQlarTbhwiY0MihUQkWX1+tFc3MzRkZGsHnzZpSXlyc16iUUMej3+2GxWDA4OAi5XI5Dhw4J4gIrhJrBhoYG/Pqxx2GddaGkZhPkGRlwTltxrv3HOH7BUVz1iY+v2aKJL5ItpEM7M1lLG4/Hw0UOe3t7OUub0NSyXq+PWviIRQymeqQsFtjzYrrvb+gc8tzcXLz33ns4fPgwFz1saWnB7OxsWF0ua2sTy7GhyGCKs5IYdLvdaGxshNVqxZYtWxJi9bEQiUQiKFETCVYMDg8Po7GxEUajMaEdscutK9kXawCYmJiAyWSCSqXCeeedh7NnzwrmJJzMzxbDMLj/Zw+isbsfF155LXLywyf0BINBWN5/B5+78Uv48Q+/h6qqqqSscyWE8l6yZGZmhtVWhVrajI+Po62tDQzDhIlDsrQRj+gF+O2sFSrBYBByuXyRH6jX6+Wih0NDQ2huboZEIlk0b3m5vgCKDKY4S4lBdipGW1sbioqK1jwjd61IpVJBRwYBoKOjA06nE1u3buV1WkYsJDtN7Pf70dLSgoGBAWzevBkVFRVwOByCEKiJYrnI4M9/+SsMzLhw5Ze+HvH3UqkU2/YdxPoNtfjGbd/DT++5Oy5jCsXGUpY2bHRkYGAAc3Nz0Ov1yMnJWWRpIxaRJKY0sVgig6EsZTidkZGxqC6X/X7YbDYMDg7C5XJBr9eHTUzRaDTc8aPIYIoTSQzOzMzAZDLB5/Nh3759cZ+KsRpkMpkgI4MMw2BwcBAOh4OLBiZTNC8kmfVwk5OTaGhogFKpDCstEFKNHpC89UxOTuLVt9/Fdd/+4YrP1Ruz8I9f/Ar+/eRP8O8/uisBq0tvItl2uN1uru6QtbRRq9XIycmB0+mEWq1Oe1EoxjSxmCKD0XoKS6VSGI3GsNIUt9vNRQ/7+vpgNpvxi1/8AtPT09i/fz8mJibidix/+tOf4u6778bo6Ch27NiB+++/H/v27Vvy+dPT0/jOd76DZ555BlarFevXr8fJkydx6aWXrur1RS8G/X4/2tvb0dvbi6qqKmzYsEEwX5RkR7gi4XK5YDabMTMzA61Wi/LyckEJQSA5x83v96O1tRX9/f3YtGkTKisrwy4wYhODS23/iSf/Gwcv+ceoL75Fpevxf1PTmJ6eFmz9YCqjUqlQUlISZmljs9m4aSnd3d3o7+8PM8M2Go2COUfGg3QXu6FQZDA2VCoVVCoVN00oEAhAq9XixRdfxNtvv43h4WF89KMfxZ49e3Do0CHuh31+tDz55JO45ZZb8NBDD2H//v04efIkLrroIrS3t0e0rvF6vfjABz6A/Px8PPXUU1i3bh36+/vXdI4UtRgcGxtDY2MjlEolzj//fOj1+mQvLQwhGU8zDIPe3l60traiuLgY5513Ht5//33BiVUg8fVwU1NTXLH+Uo1GQqljZEmWOP3rO+/h+ts/tuhxhmHgdrmg1mgW/W7nsQvxP//7v7jm059OxBJFTehECLvdjtzcXGRnZ3PRw+7ubvh8PhiNxjCBmMqWNmLyGWT3VUxiMJ7d0zKZDHV1dairqwMA5OXl4Ze//CUcDgfeeust3HnnnWhsbMSuXbvw/vvvR73de++9F5///Odx3XXXAQAeeughPPfcc/jVr36FW2+9ddHzf/WrX8FqteKtt97iahrLy8vXtG+iFIMA0N/fD5fLlXS/t+UQSmTQ4XDAZDJhbm4uLIUulPUtJFHCKxAIoLW1FX19faitrUVVVdWSnyNWfAklCpEMn0GGYSCRyRZdeBkmiMnJKQAMgkwQWq0u7PcFJWU49/ZrvK6XWAxbS8facbCPhVraWCwWzM7OcuPCWHG4FkubRCO2msFUeV/ixVpHzy6H2+1GdXU1Nm/ejE996lMA5q+XPT09UW/D6/XizJkz+Na3vsU9JpVKceGFF+L06dMR/+Z//ud/cPDgQdx000344x//iLy8PHzyk5/EN7/5zVULX1GJQYZhMDAwgLGxMWi1Whw/fjzp8z+XI9mRwdCJK+vXr8emTZvCOg+FKgYTERm0Wq04e/YsMjIycMEFF0Cn0y37fPYELBQxCCTfHoVdg91uh18mg18uB9xzUCpVou9wFQKRPqvLWdpYrVbO0iYjI4MThrFa2iQaIX0n+SbdPAajYS1p4uVgza4XdhPrdDrs2LEj6u1MTk4iEAhwjSwsBQUFaGtri/g3PT09eOWVV/CpT30Kzz//PLq6unDjjTfC5/Ph9ttvj31nICIx6HA4YDab4XK5kJeXB71eL2ghCCRXbM3MzKChoQGBQGDJiStCFYPsRYePk3wgEEBbWxt6e3uxceNGVFVVRXWRCxWDQiAZNYMSiQRBv59LVTEMA/vMDFzBIDx/qzudy8zAzMw0jMYs7gQ+OtiPknVFvK2VWJpovj8LLW0CgUCY4S9raZOVlcUJxJUsOxKJ2NLEYhG+LHwJYK/Xi2AwmJRu4mAwiPz8fPzXf/0XZDIZ9uzZg6GhIdx9990kBpciEAigs7MTXV1dKC8vx4EDB9DW1iZIEbOQZEQGA4EAOjo60N3dvWJDjdDFYLxPAjabDWfPnoVcLo+5xlRsYnApjhzYh7aG97Fp917MzMzAzQThUWYiM1MJr8eDgEyOOYbhBKFUKoXptZfxs3//UcLXKnZW+/mQyWSLLG0cDgeXWh4YGIDb7YbBYAiblpIsiw6KDKY3fKWJ3W43AKzZZzA3NxcymQxjY2Nhj4+NjS1pqVVUVASFQhH2Xm7atAmjo6Pwer2rquFNazE4OTkJk8kEuVyOI0eOcJ02MpkMHo8nuYuLgkSLLavVioaGBshkMhw9ehQGg2HZ5wtVDMZbeAUCAbS3t6Onp2fVIwnFJgaX2v4nr/wEbv7mt1FUUQ23RAJfphJKZSakUhlkcjn8Ph98CgUkDDMvFu3TKM7Nok7iJBAvkSSRSKDX66HX6yNa2nR2dmJmZgZqtTqs7jDWaRCrRWxiUCz7ysJXmtjlcgHAmm9iMjIysGfPHpw6dQof+chHAMy/T6dOncLNN98c8W8OHz6MJ554Iiyq3dHRgaKiolU3c6WlGPR6vbBYLBgaGsKmTZtQUVERdvFOdi1etCTKZzDUFiWW1KdQxWA85zrbbDY0NDRAKpWuqeNcaGIwWajVaiiZAP745GOoO/E5ZP5NCALzJsl+nw8A4MvIhHN8FL//8Q/w2C//K5lLXhIxXFT52sflLG3YaRCh85hzcnJ4s7QRW5pYbJHBYDDIS0mC2+2GQqGIS33zLbfcghMnTuC8887Dvn37cPLkSTidTq67+JprrsG6detw113zfqv/9E//hAceeABf+cpX8KUvfQmdnZ3413/9V3z5y19e9RrSSgwyDINz586hubkZWVlZqK+vjxjCTRUxmIgJJOPj4zCbzVCpVDHPXxbqhBT2ArYWMRgMBtHe3o7u7m7U1NSgpqZmTReMeArUeJCMyKDT6cSjjz4K6aGDaOroxMx/3Y+Lrz6BrIL5VIhUKoVUKoXf50NvUwP+58lHsXffHrz33nsoLi4WhfgSEom8cQm1tAHmvyczMzPcrOWenh7eLG0oMpje8Jkmjldpw5VXXomJiQncdtttGB0dxc6dO/HCCy9wTSUDAwNh+1BaWor/+7//w9e+9jVs374d69atw1e+8hV885vfXPUa0kYMOp1OmM1m2O12bN++fdmLR6qIQT4jgz6fD83NzRgeHsbmzZtRXl4e80lCKpXC97dIjpAIbSBZDdPT02hoaIBEIokqXR4NQosMJrpm0OFw4JFHHsF7ajXO1dbiwquvhqOjA0898SikMw6U19RCocjA1MQ4WhrPQrN7Fw7edxJ9vb14vaEB2lOncOGFFyZsvSshlPeRT5IpkkItbaqqqjhLG7ZrmbW00Wq1YV3Lq7G0EZsYFFtkkM80cTznEt98881LpoVfe+21RY8dPHgQb7/9dtxeP+XFYDAYRHd3N9rb21FaWoq9e/euGBJOFTHIV+RtZGQEZrMZBoMBdXV1q/5ACzVNvNrIYDAYREdHB7q6ulBdXY0NGzbE7Y5SbGIwdPszMzPzQlCvx8jGjdixfTvUajU0u3ahcNcuuK1WTPf2wuPxQK9SIbf+CCRyObIKCyFRKtEYDEJx5gx0Oh3279/P25qJcIQkkkItbcrKygCEW9r09fXBZDKFWdpkZ2fDYDCs+B0WW5pYLPvKwpcAjmdkUAiktBi0Wq0wm81gGAYHDx5ETk5OVH+XSmIwnmJrbm4OTU1NmJiYwNatW1FaWrqmk71QxSAQu/E0a6XDMExYs1E8EdJIukQV5ttstnkhmJOD8Zoa7Ni+fdEJVJWdDVWIddGU2YyZv9mSrF+/Hj6vF6ZAALKXX4ZWq8WWLVt4XzshLDEYiUiWNtPT05iamsLExATa29sRDAZXtLQR+n7GEzGKQb7SxPGODCablBaDnZ2dKC4ujrmeK1XEYLy6ntlayqamJuTl5aG+vj4uHotCF4PRrC0YDKKzsxOdnZ2oqqrCxo0beTtZCm0kXeha/H4/JiYmYDAY4nKCk0gkmJubw8MPP4z3CgowVV2NHdu3R/W5yy8omBeDY2MoKytDaVkZPF4vzH4/Mv74R6jVaq4rlSBYZDIZcnJyuKDAQkubwcFBuFwuGAyGsLpDsU0gEcu+svCVJqbIoIDYt2/fqu7ohCxiQonHOt1uN8xmM6anp7Fz586YB2gvh5CPYzRROLvdjrNnzyIYDOLw4cPcyC0+EcrxCj0+7DSVQCAAj8cDpVLJXVRzcnKg1Wpj/p5NTU2hpaUFTRUVsFVXY+f27cj4m7H0SuTm5qJTLofb5cKswwGdXo+qqiq0+Xxo8PmQ8eSTuP7aa5f04CLiQ6pHzJaytGGbUlhLG/Y85vf7kZOTkzBLm2QgRjHIV5rY5XKRGBQKq/3CymQy+P3+OK8m/qwlgskwDPr6+tDS0oLi4mLU19fHfZi8kMXgcmsLHbNXWVmJjRs3JqSoWkiRQXZkX2trK7q7u7Fx40ZUV1cjEAhwdVhDQ0NoamqCXC4PE4cGg2HZ797o6CieeeYZmKqq4Kiqwo7t22P67MnlcuTm5mJydBSjY2PQ/W2UWe3GjWjyenHW50Pm44/js5/9LPkP8kiqi8FIqFQqrFu3DuvWrQMw30j3+uuvIzMzE8PDw7BYLAmztEkGYhSDfEYGKU2c4iTKv2+trFZszc7OwmQyweVyYe/evZxdQ7wRshhcKjJot9vR0NAAv9+fsGjgSmtKBnNzc5ienobP5wvrmJbL5YssPkLrsNhZmeyFcuHFcnh4GL959FGcqazE9Lp1OG/HjlV5fBXk52NibAyTExOoqqyEVCaDVCbDli1bYPL7cdbjQeZjj+H6669PqxMykVjYKQ6lpaUoKipa0tJm4bSUzCij3EJDrGKQr5pBigymOKlUMxjLOkM7q8vKynDgwIG4GGIuhZDF4MK1MQyDrq4utLe3o6KiArW1tQm/2xeCGGQYBj09PWhvb0dGRgbOP//8ZY9DaJSkpqZmfp6w3Y6pqamwi2VWVhYYhsHrb76Jsxs2YK68HNla7arNXo1ZWVBkZMDv8cBqs3GjzeQKBbZt2waT348zra1QPvEErrnmmrhHvYn0jAxGInQ/I1nauFwuru6wpaVlkaVNdnY2NBpNShwrMYpBPruJ0+lGVLRiMBgMCv5kF4vYmpmZgclkgt/vj6mzei0IWQyyaVBg3uOuoaEBXq8Xhw4dQnZI52qi15RMMehyudDQ0ACXy4WamhpMTEzEfJKUSCQwGAwwGAyorKzk/N8sFgv+/NJLMG/eDEdhIQqMRvj8fjjsdqjU6phvSqRSKfILCjDS34/x8XFODALzXaTbtm+HORDA+01NUD/1FK688sqkiPt0Rujnx3ixXAOJRCKBRqOBRqOJaGnT398Ps9kMhUIR1pQSjaVNMhCjGOTTZ5AigykO+8EIBAK8Rs7WSjTp7EAggM7OTnR1dSW0/g0Qthhk19bV1YW2tjaUl5dj06ZNSa39SZYYZLvJGxsbsW7dOuzbtw/j4+MYHx9f87YlEgnGx8fxwssvo2HrVqCiArs2boTL6cTE5CQmp6bgHR5GRmYm1CoVlCoV1Gp1VBHD/Px8DA0OYmpyEn6fD/KQv1Gr1di8dSuaAwFkmEzQ/O//4sMf/rAoxEuiSHYUO1HEOpUjFksbViBGsrRJBmI1neZrAglFBlOcVBGDK5lOW61WmEwmSKVS3rzxlkPIYpBhGFgslpg9KPkkGcfL4/HAbDbDarViz549XAduvIRpZ2cnHv/973F261ZIKyuxefNmyGQySCQSTE1NoaKiAn6/H263G263G9PT0xgdHYVCLodKpYKKFYcZGYsuyFqtFmqNBu7ZWUxMTnIXXxaDwYDaLVtg8fshb2iA9pVXcPz48TXvUzSIRSiJQVyvNQK6lKUNW3d47ty5iJY2yYgq8TWnV6gwDAOGYXiLDMYyvlXoCFcJ8Qh7lyD0usGlxIPf70dbWxv6+vqwYcMGVFdXJyX0L0QxyNbEzc7OoqCgAOedd55gBH+iI4Ojo6MwmUzIzs5GXV3doqL3ta6ltbUVv3vmGZzdvh2Kigps2rQJ0r+ddEMvrXK5HDqdDjqdDgAQDAQ4cWh3ODA+MQGpVMqJQ5VKBaVSCYlEgvyCAvTPzmJsbGyRGASAnJwcVGzaND+l5P33odVqaUpJnKA08eoItbQpLy8H8HdLG6vVylnaqFSqsFF6ibC0EVuamL3G81UzyFdzZjIQxlUywUgkkpRoIom0xomJCZhMJiiVSlxwwQXcBTYZCE0Msl3UbrcbOp0OJSUlghGCQOLEoN/vR3NzM4aGhrBt27aIk2bWetFpbm7Gk3/4Axp27kRmZSVqN27khCDLUnsqlcmg0Wqh+dtddTAQwJzHA7fbPV+sPzkJAFCp1cjIyAAjkcA+M7OkyWtRURG8NKUk7ohFDMaaJl4NkSxtbDYbrFZrREsbdlpKvEWMWMUgdROvjHCulAkmFcRgqNjy+XywWCw4d+4cNm/ejIqKiqSfqIUiBhmGQW9vL1paWrgu6nfeeUcQawslEWJwamoKZ8+ehVqtXnbu9FrWYjab8fvnnsPZ3buhqaxc8wxnqUwGtVrNrZVhGMzNzXHRw0ylEl63e37iUFHRfORQpQq7UJaVlcHr8XBTSjQaDReVIVZPss8xiSAZolehUCyycGK79K1WK3p6euD1emE0GuNqaSM2McheA6ibeGVEKwaFImSWgxWso6OjMJvN0Ol0qK+vF8wHUAjH0Ol0cp6K+/fvR15eHoDkd+5Ggs81BYNBtLW1oaenB7W1taiqqlr2ArfatZw5cwZPv/ACGnbtgq6qaulRkGvYV4lEwqWLgfnvQWdrK9wuF7w+H+x2O3x+P5RKZVhquaq6+u9TSn73O3z2uutQUFCwqjUQ4qmLFIJAkkqlMBqNMBqNES1tWltb4XA4oNVqw+oOY7W0EcK+JhK2eYQPsU+RwTQhFaaQ+P1++P1+nD17Flu3bo2Y7ksmyRSD7IQVi8WC0tJS7Nu3L6wwWghCdSF8iUG73Y4zZ85AIpHg/PPPh16v52Ut7777Lp49dQoNe/bAWFWF6urqhHwe2fF0nrk56LRaFBcXw+fzzUcOXS5MTk7C6/EgIzMTWdnZGCktRYPPh8cee4ymlKwBsaSJhbifkSxtvF4v15Sy0NKGFYgrWdqIVQzyAUUG0wQhTyFhGAZDQ0NobGwEANTV1QnyDoQdr5bokynrl+d0OrFv376IRbyhPoNCId4ClWEYdHd3o62tDVVVVdi4cWNMJ75YxOBbb72F//nLX9Cwezdyq6tRUVm5YuQRcRK+kcbTKRQKKBQKTviGdiwbs7IwUlyMsx4PmF/8ApdddhnWrVuXMsbAQkIMx0uIYjASGRkZKCws5BwBWEsbq9WKyclJdHR0rGhpIzYxyKeVDkUG0wSh1gy63W6YzWZMT0/Pj94ymQQ7XYE9qSTKu4phGPT398NisXB+eUvZJAhpDjBLPCODLpcLZ8+exdzc3KqMtGO5+L3++ut47vRpNOzZg/yaGpSXlyf84hlpPF0ooR3L+fn5KCoshEkqRYvXC9nzz6OiogJKpTJsjN5KM5ZXIhUExFoQ2veHL1JVIIVa2rDTgVhLG6vVCrPZDJfLBb1ez6WV/X5/Su7rauHLcBqgyGDaIDQxGCp0ioqKUF9fD4lEApPJJFij0ESKQbfbjYaGBjgcjqjmLQsxMhgPMcgwDAYGBtDc3IySkpJVjxyMZi0Mw+DVV1/Fn8+cgWn3bhRt2ID169fHvN54iCZjVhYUmZnwLRhPtxQqtRrbt2+HORhERlMT8p1OHDp0CNPT0xgfH19xxjKROhGztcB+B9JhP1eytOnq6sLMzAwaGxsxOjrKpZf1en1a7H8k+EwTU2QwTRCSGGSbIJxOJ8477zyu6J0VM4FAQJBGoaFikC9CxU9xcTH27t0b1bFIx8igx+OByWSCzWYL+5zwsRaGYfDSSy/hRbMZpl27sG7DBq52KRlIpVLk5+dHHE+3FBqNBltCppRoT5/Ghz/8YWzYsAEMw2BmZoabsdzd3Q2/34+srCxOHGZnZy8ptIX22eIDEoOpz0JLm1OnTqG0tBTBYBAjIyOwWCyQSCRhdYdGo1FQllxrgc9ABUUG0wQhiMHQmq+ysrJFaU/2BCW0CBcL32LQ7XbDZDLBbrfHLH7SrYFkZGQEJpMJubm5qK+vX3PpwHJrYRgGf/7zn3GqtRWmXbuwvrYW60pKYtt+yLbidaEtKChYcjzdUhgMBmzcvJmbUqJ79VUu6r6we3N2dpYTh4ODg5ibm4PBYODEYU5OjmBLNvhADIKXPUeIJXXKMAyysrI414WFlja9vb2cpU1o1/JaLW2SBZ9pYooMpgnJFoN2ux0NDQ3w+XxLjksTujm2RCLhJR3LMAwGBwfR1NSEoqIi1NXVxXwRFqK1zGoEqs/nQ3NzM0ZGRrBt2zaUlJTwGsVgGAZ/+tOf8Gp3Nxp37kTFpk0oKi7m7fViQaPRQK3Vwu1wYGJiIup15ebmwsdOKXnvPWi1Wuzbty/sORKJhKs5ZFNsodYeLS0tmJ2dhU6nQ05ODpxOpyiEYbpGzFjSPTK4kIX1kUtZ2rCpZdbSRqPRhE1LSZVmLL7SxAzDUGQwXUiWyAoGg+jo6EBXVxcqKyuxcePGZe9chBjhCiXe6wttoAmdpZvsdcWDWAXq5OQkGhoaOAPpeN6FRlpLMBjEH//4R/ylrw9NO3agcvPmVR9/sBeKOApyiUSC/Px89DscGBsfj0mkhk4pkb/0ErRaLTZv3rzs37BG2KWlpQDm0/SsOGQL9UdGRsIih6lykYwGShOnHys1y4Ra2rCfe9bSxmq1YmBgAI2NjZDL5WFm2EajUZDRVb4ig16vF8FgkCKD6UAyxKDNZkNDQwMkEgmOHDkSlf+ZkCODQPxEF8MwOHfuHJqamlBQULDmVKgQI4PRrikQCKCtrQ29vb3YtGkTKlewcYnHWgKBAJ599lm8PjSE5p07UbNliyDnbhYUFKCvp2fZ8XRLwU4pMfn9UPzhD7hWrY5pSklmZiaKi4tRXFwMr9cLpVKJ3NxcLq3c2NgIhUIRJg5TuThfDGJQbGni1XROR7K0Ca23ZS1tFk5LEUKdO181g263GwAoMpgOSKVSeL3ehLyW3+9HW1sb+vr6UFNTs/TUhggIMcIVSjzWNzc3B7PZDJvNhl27dqGoqCgu6/L5fGveTjyJRgzOzMzgzJkzkEqlvM6eDl2L3+/HU089hTcnJtCyYwc2btmC3L/VFAmNzMxMGLOzMTM1hfHx8Zi6myUSSVynlMhksrCRYqzv29TUFMbGxtDa2goAYeJQqBEUsUKRwdiRyWSc4AMQVm9rtVrR1NQEp9MJvV4fVneYDOHEV5rY5XIBAEUG04FERdwmJyc5r8Bop0OEImRzbGBtYjDUXDs/Px91dXVxK1RONWsZhmHQ2dmJjo4OVFdXr3neb7Rr8fl8+O///m+cttnQum0bardti1i/KiQK8vMx8zfBVVZWFtOFXCqVora2Fo1/E4SPP/44rr/++rhMKQn1fQPCi/OnpqbQ1dWFQCDAdSyzF1Shdm6KITJIYnDtRKq3nZub46aldHd34+zZs5zPJysQExE15ytN7Ha7oVAoBPvdXQ3psycxwrfI8vl8aGlpweDg4JpSfVKpNC3TxB6PB2azGVNTU9i5cyeK49ykkErWMk6nE2fPnoXH48Hhw4eRlZWVkPUEAgH89re/xduzs2jbvh2btm6N2bx6KdjPOh/vQE5uLiCXY87lgsPhiPkGSyqTYcuWLTD7/Tjj8SDjscdw/fXXxz1yEak4P7RjeWBggOtYzs3N5S6SQmhMEYtISlXD6dXATotKxP4qlUqupAKYzz7YbDZYrVaMjo6ipaUlIZY2fKaJ0ykqCIhcDPIlskZHR2E2m6HValFXVweNRrPqbaVjZJCNBrI2KXzYFggxvb5wTazReHNzM8rKyrB58+aE3Wn6fD50dnaiU6NB57Zt2LJ1K4wJEqFrJXQ83djYWMxiEAAUCgW2bdsGk9+Psy0tUP32t7jmmmt4rXNarmN5ampqUccy+5NuFx0hIYboJ0sy6yPlcjny8vIWWdqw0cO+vj54PB7OyokViGu9NgQCAV7OqelmKwOQGIzrNj0eD5qbmzE6OoqtW7fGnMKKRDpFBj0eDxobGzE5OYnt27dzRqh8IPQGkrm5OZhMJszMzCw5X5kv5ubm8PTTT6Ndp0P35s3Ysm0bDAZDXF8j1GeQD9jxdBNLjKeLhszMTGzdtg3mQAAZTU1QP/UUrrzyyoReLJfqWGbTymfOnIFarU54x7JYIoOJipQJASE1y4RGzSsrKzmrFrbusK2tbZGlTXZ2NrRabUyfyUAgwEuwId1sZQASg3HZFsMwGB4eRmNjI7Kzs1FfXx+3uwYhRrhCiXZ9w8PDMJvNyMnJQV1dHZRKpSDWlUhYMcgei7y8vFV5KK4Fl8uFxx57DO9JJOjauBE7tm+HbhWRtWQT63i6pVg4pUT9pz/hwx/+8IoXHL5EbmjHMjAfwWWjJ6ytRyI6lsUiBoPBYNrvI4uQxOBCJBLJohujUEsbtltfLpeHNaWs1JDFV5qYIoNpRLzEoNvtRmNjI6xWK7Zv347i4uK4nlyEbi2zUhrb6/WisbER4+PjXDQwESdfIUYGGYbB6Ogo+vv7sWPHDl4jo5FwOp145JFH8H5GBvo2bUKWXp+SQhBYMJ5ubGzVYhAIn1KiCJlSshKJ+BwrFAoUFBRwHc+BQAA2mw1TU1Nc7ZVUKl00Y3mtF3yxiEFKEwuXlSxtOjs7uRGSoQIxtNSDr25iigymEWsVWaEzcwsLC3H8+HFeIjxCjHCFslzX7sjICMxmM7KyslBfX897NDAUoR23iYkJnDt3DgqFIu4G0tHgcDjwyCOP4D21Gudqa7Fl82aMjowkdA3xhhtPNzUFn8+3pnq/3Nxc+GprYQ4GIX/vPeh0OuzduzeOq40PMpkMubm5nPgNBoOYmZmB1WrF5OTkoo7lnJwcZGVlrbpuKt2FktjSxOzUqFRkKUsbNnIeydLG6/XyZi1DkcE0YS1i0Ol0wmQyYXZ2NuaZubGSipFBr9eLpqYmjI2NJWSEWiSEYi0TCATQ0tKC/v5+zmsr0SeRmZmZeSGo12P0b6lhVjjxFhnhYQLJQrRaLTeebjKG8XRLUVRcDK/PNz+l5MUXodVqsWnTpjitlh+kUimysrKQlZXFdSyz01FCO5ZZQ2A2erLSjavQoup8IbY0cToJ39CGLNZvlLW0sVqt6O7uxvT0NBwOB6ampuJqaUORwTRiNSKLYRj09PSgtbUVpaWl2LdvH+8u60KLcC1koegaHR2FyWSC0WhMSgSMRQjWMtPT0zh79izkcjmOHTuGwcHBhBmds9hstnkhmJOD8ZoabN++HSqVCv6/GXLzJQb5tJYJZbXj6ZaCnVJi9vmgePZZXKtSxTSlJNlIJBLo9Xro9fqIHcsWiwWzs7PQ6/Vh4nDh95TSxOlHuonBSCy0tHnttddQWFgIiUSC0dFRzgiejTBmZ2evKnJOkcE0ItYuXbvdDpPJBK/XiwMHDqypRikWhG4tw67P5/OhqakJIyMj2LZtG0pLS5N6kk2miA4Gg/O2LZ2dYRNnEh2tnJqamheCBQWYqq7Gju3b/56qT5ML4FrG00WCnVLS6vPB7PPhiTVOKRECCwvzQw2BOzs7MTMzE9a1mZuby10c010oiUEgsYhpX1nYMXls3SHDMJwRvNVqjWhpk52dvWJJE0UG0wi5XI5gMLjinWHohb2iogIbN25MqOu4EMeqhSKRSGC32/HKK69Ar9fHtZN6retKRmRwdnYWZ8+ehc/nWzR/OpFrmpiYmG8WKS6GrboaO7dvR0Yki4UUTweuZTzdUrBTSpp8PjT4/Xj88cfx2c9+Nu72O8liYfRkqY5lAOjr60NeXh50Ol1aCkOKDKY3C7uJJRIJDAYDDAZDREub9vZ22O12aDSasKaUhZY2FBlMI9gvxXKt59PT02hoaACAhE6GCEUmk8Hj8ST8daPB5/PBZrPB5XJh+/btcfFVjBeJjgwyDIO+vj5YLBasX78emzdvXvS5SpQYHB0dxaOPPor3ysrgqKrCju3bEz7VIpGfg7WMp1sKGTulxOfDWY8HmY89huuuuy7togFA5I7lsbExvPfee1xqTSqVhpkBp8uMZRKD6c1K4+iWsrRhO/ZDLW0mJiZgsVhQX18Ph8MRt3PBT3/6U9x9990YHR3Fjh07cP/992Pfvn0r/t3vfvc7XH311fjHf/xH/OEPf1jzOkQrBtkPSKQPSyAQQFtbG3p7e8PSfMlAqKbT4+PjnFAuLS2NS0QmniQyJet2u2EymeBwOLB//37OZT/SmvgWg8PDw/jNo4/iTGUl3JWVYc0iC9cC8F/TlwjWOp5uKRQKBWdKfdZigTIBU0qEgEwm4258Dx06BIZhwiw94t2xnEzEJJDEtK8sq7GWycjIWHRzNDMzg5deeglvv/02HnroIczOzqK4uBharRZHjhzBwYMHVxUsevLJJ3HLLbfgoYcewv79+3Hy5ElcdNFFaG9vX3YQQV9fH77+9a/j6NGjMb/mUqTetzdOhIrBUCYnJ2EymZCRkYHzzz8/bheW1SK0BhKfzweLxYKhoSFs2bIFs7OzSW/UiESiGkiGhoZgNptRUFCAurq6ZYUC32saHBzEo48/jjM1NfBUVmL71q2QL7EevieEzL9IYiKh7KiriZERjI2OxvU7q1Qq/z6lxGzmppSIidCO5erqaq5jmRWH/f398Hg8YR3LOTk5KSGaKTKY3sTDdJq1tLnyyitx5ZVXIhgM4vLLLwcwn4X56le/iq6uLmzZsgVHjhzB97///agnSt177734/Oc/j+uuuw4A8NBDD+G5557Dr371K9x6660R/yYQCOBTn/oUvv/97+ONN97A9PT0mvaPRbRiUCKRhEXdfD4fWlpaMDg4iE2bNqGyslIQJwkhWctMTEygoaEBGo0GdXV1UKvVaGlpEWRNI98imjXTnpiYwM6dO7n6q5Xga019fX145Ikn0FBbC39lJbZt3Zr0SI1EIklYTWJ+fj7GR0cxMTmJqqqqVY2nW4rQKSWKhgZo/vd/o36/U5XluolDO5YrKirAMExYx3JzczPn9xYqDhPpMxotYhJIYtpXYP4zvFKaeDVIpVKoVCrs3r0b3/jGNwAAY2NjeOutt/Dmm29Co9FEtR2v14szZ87gW9/6Vti2L7zwQpw+fXrJv/vBD36A/Px8fPazn8Ubb7yxtp0JQbRiEPi70BobG4PZbOZETrRvZiIQQmTQ7/fDYrFgcHAQW7ZsQXl5OXeREGpNI58pWTZFbjAYYhqtx1dksKenB4/+9rc4u2ULUFGBrVu2JF0IJhqj0RiX8XRLsXBKyZ7ZWUGaUseLWCJmEokEGo0GGo0GZWVlAP7esTw5OYnOzk68//77XMcy+6NWq5N+w02RwfSFz4krC7uJCwoKcPnll3MRw2iYnJxEIBBY5FRQUFCAtra2iH/z5ptv4pe//CVMJtOq1r0c4rpiLEAqlaKlpQVWqxVbtmzB+vXrBXdiSHZkcGJiAiaTCSqVKqJQFoq580L4ENF+vx8tLS0YGBjA1q1bY/688CFQOzo68MRTT+Hs1q2QVlZGbFxZYjHz/+UxcpfIb5JUKkVBfj6G4zCebinCppScOQOj0Yiampq4v45QWMu5cLmO5f7+fphMJmRmZoaJw2R0LJMYTF/Y83+6zCZ2OBz4zGc+g5///Oe8nN9EKQYZhsHw8DA8Hg98Pp9g7FAikazIYKjw2bx5MyoqKiKeNIXqgxhvkWqz2XD27FlkZGSsOnocbzHY2tqK3z3zDM5u3w5FRQU2bdoUdXo0nRpIWPILCnAuTuPplqKouBgerxdmvx/yM2dQ8bfjnm7EWyQtN2N5ZGQEFouF61hmfwwGA+/iRUwCSUz7Cvy9H4APMRgPn8Hc3FzIZDKMjY2FPT42Nsb5IobS3d2Nvr4+XHbZZdxj7DVOLpejvb0dVVVVq16P6MTg3NwcGhsbMTU1BZVKhZqaGsEKQSA5kcHJyUk0NDRAqVTi2LFj0Gq1Sz5XyJHBeAivYDCIjo4OdHV1YcOGDaipqVn1RTKeYrC5uRlP/uEPaNi5E8rKSmzcuDGmOrlERUMSKTZDx9NNTEzwVte3fv16TE9Pw7xjBxTPPovr1GrBddOvFb4bf5aasczWHXZ0dCAYDHJWNmzHcrwv7BQZTF/Y6yYf7288IoMZGRnYs2cPTp06hY985CMA5t+jU6dO4eabb170/NraWjQ1NYU99t3vfhcOhwM/+clPOGuc1SIaMcgwDAYGBmCxWFBQUID6+nq8/fbbghQyoSQyMuj3+9Ha2or+/v6om2iEGhmMx3FzOBw4e/YsAoEAjh49umbT4XiJQZPJhKeefx5nd++GprISGzZsENVJfjkKCgrQ53BgfGyMNzEokUiQl5eHcYYJm1ISbQdhKpBokbRSxzI7KSIrK4ubkpKdnb3m6C+JwfSF7STm4/2N1wSSW265BSdOnMB5552Hffv24eTJk3A6nVx38TXXXIN169bhrrvumnc22Lo17O/ZoQYLH18NohCDLpeL84HbvXs3F4KVy+WC6dRdikT5DE5NTaGhoQGZmZkrRgNDEWpkkEuDruJkHzqDuqKiArW1tXGJSMRDoJ45cwZPv/ACGnbtgq6qam0emHxbvyRhCkxBfj56e3pgt9vjMp5uKSQSCUpLSnAOQIPXi8ceeyytppQAyR1Ft1LHclNTU1w6lsUkkMS0r8DKhtNrIV41g1deeSUmJiZw2223YXR0FDt37sQLL7zAlVMMDAwk7D1LazEYelEvKSnB3r17w+4khWroHArfkbdAIIDW1lb09fWhtrYWVVVVMV0EhBwZBGL3mXK73WhoaMDs7GzcZ1CvNTL4zjvv4A+vvIKGPXtgrKpCdXX1/2fvz6PjOM8rYfxW7/uOHQRAEOCGhZtIipJIioptWV4myurJHFuypCz+nZG/2MoksR3bX3IyieM4cZR4nZmcJNZCy7Is299YimKHkixbokASGwEQ3ECCIND7vlR1d22/P7qr2I21G+ilGuh7jo6PwQa6urqq3vs+z3Pv3dCCXUnrl0pBpVbDYrWWNJ5uJchkMvT192OcYTBC01A/9xwef/xxSY+dFAqpeYeupFjObSsLMWLFKJbrlcHNi/UYTheKUmYTP/nkk8u2hQHgzTffXPV3/+3f/q0kxwBsYjIYi8UwNjaGVCq1YiqEVIlMLsrZJg4Gg6Io4uTJkzAajUX/DYIgJEmocyuDhYDneczPz2NiYgItLS1LNg6lOqb1LrLvvPMO/r+f/xyjBw/C0dOD7SXwwcz9bYok4c4OMuu0Wuh0Omh1ug1Z1FQrH7oc8XQrQUgpGcumlGi/+1187GMfqwnD5dVQCyRJo9Ggra0NbW1tADKK5dy2ciGK5Vr4nKXCViODpTCcXgn1bOIaAMdxuH79Oq5evYquri7s3r17xQWt2rYthUA4xlI+tHLj9nbt2pUx6V3nQ0Iul0uuigDkVwbXQjqdxvj4OPx+Pw4cOICWlpayHNN6ydFbb72FV86exeihQ2js7c3zedwoWI6D3+9HKBgUUyPIbHB7yumESq2GTquFVqeDTqtdMdFESrA7HCDKEE+3EjQaDQb6+++klPzgB/jt3/7tml54a5EkKZVKNDc3i2NADMMgFAohGAzC6XQuq1guZ/VIathqZLBcbWKe58s6glItbCoyGA6HMTY2Bo7jcM8998Bms636+logg8LNW6qHs2CRolAoShK3J/XK4Fpk0OPxYHR0FFarFQ888ADUanVZj6kYMsjzPN544w38+/Awxg4eRMvOnSVve3rcbvAAtnV0iPNWxuw1wTAMKIoCRVEIBoNwJZNQqlSZqmG2eijFCphCoYCjTPF0K0FvMOSnlLzyCj70oQ/VHKHaTBBiChsaGrBr1y5wHIdwOCz6HV69ehUMw0CtVkOj0ZRNsSwVcBwnyfu1XCgX0U+n0+A4rmRtYqlgU5BBlmVx5coV3LhxAz09PQWrK2uBDOZmKG/kws49Rzt37kRPT09JbhSpVwZXOjYhVWV+fh79/f1lbycCxYlteJ7Hz372M/x0fBxjBw6gfdeuDVsH5P7taDQKjuOgUqnQ3Ny8rC2NQqGA0WgUxwdYls2QQ5JEOByG2+2GUqHIVA2z/0llsSlnPN1KWJxSYvz5z3H//feX/X3LgVqsDK4FmUwGm80Gm80mKpZHRkZAURRisVieYlmoHJZCsSwVbLXKYLnaxBRFAUC9Mig1cByHt956CzKZrOhKl1wul2Subi6KaXeuhHA4jJGRkXWdo7Ug5crgSuRLmJUUfBQrFT9YqPchz/P493//d5yZnsbYgQPo3LNHnIvaKIT4RZIkM3YeNlvBREkul8NgMIhKc5ZlkaQokMuQQ+FBWa2NgsVigUqjQTqZLEs83UpwOBxIZ1NKlGfPwmAw4K677qrIe5cSm5EMLgZBEFAqldBoNOjr61tRsWw2m/PIoRQzlgvBViOD5WoT18mgRCGTybBv3z5YLJaiL3S5XI5kMlmmIysNNkIGOY7DlStXMDMzg97e3o3ZkKwAqVYGgaVt2dzzsR7ldKmPZzlwHIef/OQneGNmBhf378f2PXvQUiK/PJIk4Xa5oFKr0dXZidlbtzb09+RyOfQGA/RZcsgJlUOKQjQSAcswcDqd0GfFKDqtFkqVqiLnXCaTobGhoXzxdKt8j62trUin0xhjGCh++lPo9fqaTCnZ7GQQyCe9aymWr1y5IiqWBZ9Dh8MBrVZbE+dqK5LBcnxekiShUCg2TcVYQM2TQQBrzgauhFpoExMEsS4LnHA4jNHRUQAoiWHySpBqZRDIV2JHo1GMjIyA5/mSV0cLxVpkkOM4/PjHP8bPZ2cxsW8fduzdi6ZlYomKBcdxCAQCCIdCcDQ0wGKx3Fm8SkjkZYvI4czMDKxWKziOQzQahdfrhUwmy7SUhZnDMpLDpgrE062Ezs7OO4TwBz/A4488IhKMWoBUN3ilBs/zqxKGxYrldDotzhzmKpYFclitjOVCsBXJoFSj6KSITUEG14taIINAcfYyufFpxcxPrhdSrwxyHIeZmRlMT0+jOxvbVq0B8dXIIMuy+OEPf4i3FhYwuX8/evv6SpJokU6l4HK7wXMcOjo78wQyZZ+RRGYxFR6cHMsimUqBJElEYzF4fb4MOcyxslGVkBzqDQbojUaQ0WhZ4+mWA0EQ6OnpwXQ6jXGaxvPf/W5NpZRshTYxkHleFvM5hRnbxYrlQCAgKpblcnlejF4lMpYLwVYjg+WaGdyMtjLAFieDtWA6DRROWiORCEZHR8HzPO677z4xqqacEIiqFBcPgiAwNjYGmqZx7Ngx2O32qh/PcmSQYRi89NJL+KXPh0v79mFXXx8cy/hiFgOe5xGJRODzemG2WOCw25fMBhKobHawTC4XhSZAPjmMxePw+XwgZDJRqazVaqFWqzd0XTU2NmI2Gi1rPN1KkMlk2L1nDyZouuZSSqR4P5cDG/2cuYplAKJiORAIwO/3VyxjuRBsNTJYrjZxvTK4CbFZKoMcx+HatWu4du0aduzYgV27dlXspi+19U0pwPM8bt++jXQ6DZvNhnvvvVcS8x3LfY80TePFF1/E2VAI0wMD2D0wsGHSyjAMPB4PKIpCa2ur2LaVGpaQQ45DKpkESVFIJBLw+3wAQYg+h1qtFhqNpqjrLC+ejiShrfBDXC6Xo6+/H2MMg5F0elOllGwGrNUmLha5iuXe3l5RuS/MHd68eRM0TcNisVRcsbwVyWC9Mlg4tjwZlHoCCbA6aRVm4TiOw7333gur1VrRYxMeLlIxb02lUhgfH0cwGIRarcaOHTskQQSBpZXBdDqNF154AWfjcVwZHMTegYENf3+JRAJutxsatRpdXV2rJ4hILJtYJpNlSF8uOUylQJFkRuXp9wOAKEbR6nRQq9WrXne58XQerxddXV0b+kjrgVKpxECNpZRIaXNXThTbJi4WBEHAbDbDbDaju7sbPM8jkUisqli22+1l8TuVyjO6UiiXr2K9MrgJIZfLwTBMtQ9jTSxXUcpNWqnmLNxafn6VhNvtxtjYGGw2G06dOoVf/OIXkiL7uWQwlUrh9OnTGEqlcG1gAH0DAxtq63MsmxGJhMNoaGiAOVckUqOQZVvGWq0WNmSusWQyCYokQVEUAsEgwPN3yKFWC7VGs2TBa2psRDgYFLOKq3Feai2lZKuQwUp/ToIgRHsmwUBeMHX3+/2iYtlgMCzJWN4oSl0FlTrqlcHisOXJoJTIwkpYXBmMRqMYHR0FwzAFJa2UE7mVwWqBpmlMTU1hYWEBg4ODaG9vF1XYUiCpAgQymEwm8fzzz2OIZTHT34++gYENzZGlUyk4XS4AGRWrqsCqAkEQJVUTl/vvEwQhkkMgs7ilsjOHueRQk5051GXJod3hgEwuR5IkEY1GqzazpzcYsLevD5doGsrxccmnlEj1uEoJKbROtVrtiorlmzdvYnR0VExIEf4zGAxFfz9brTJYnxksDlueDNbSzCDP87h+/TquXLmC7du3Y/fu3VWPThLMnatFugKBAEZGRqDT6XDq1Km8m7QYFXYlQBAEaJrGM888g/MEgRt9fRgYGBDj34oFz/OIhMPw+XyZGSSHY0s97AmCgEajEU2AeZ5HOp3OkEOSRCgUAs9xUGs0MJpMiAWD8Ho8pSOD6yBLFosFO/v6MMVxkk4pkdImqpyQYgV0NcXywsICJicnIZfL88ihyWRa897fapXBupq4ONTJYA2QQblcDpIk8Ytf/ALpdLrq1cDFqIYqm2VZXL58GTdv3sSePXvQ3d295KFeTZK6HEiSzJD5hgbM7d6NwcFBMc2jWDAMA4/bjWQqhda2tnWlqFRaTVxuEAQBtVoNtVoNq9UqkkOKJJFOpxEJheD2eKBWq6HT66HT6aBRqysSVZcLR0MD0rt34yLLQnn2LIxGIw4dOlTRY1gLUiRJ5UAtfM7VFMs+nw+XL18Gz/OiGMXhcMBisSwhQluxMlj3GSwcdTLIspJ+IPA8D4qicOXKFXR3d2PPnj1VrwYuRqXbsdFoFMPDwyAIYlUDaSlVBmOxGF544QVMNzZiPksE1xuDl4jH4XK7odVq0dnZubpIZDVI9JovFXLJoclsht/vRzqZBA+ATqfhikTAsmzGC1FQLGs0BZHDjV7tra2tSKdSGGNZKP7jP6DX67F79+4N/tXSQqrPxFJCCm3iYlGoYtlqtYrkUNgc1dpn3QjKmUBSrwxuMgikqlzl5I0iHo9jdHQUJEmis7MT/f391T6kZVGpymBum7wQCx2pkMFIJJJpDZtMuN3djQMDA+sighzLwuf3IxqJoKGxEWazecMLdjlJvJQqj0I83cLcHOLxuJhFS6fTICkKFEki6naDZhhoNZo8UUq5KoedXV1IZVNKlD/4AR772Mckk1Ii5Q1yKbEZPudaiuXx8XGQJAkgkwrU0tJSNsWylFCudb1eGdyEEC6UcpWT1wue53Hjxg1MT0+js7NT9FeTKipRGUwkEhgdHUUymSy4TS6FNnEoFMoQQbsd3p4e2IxGaNaxq0ylUnA6nZDJZEWJRFZDuQUkUqs8LhdPp1KrM/YzFkuGHNI0KIoCSZLweDygGUasHOp0Omi02pI9KwiCQG9vLy7RNMYkllJS7fumUii3tUw1sJJi+Wc/+xl4nsfly5cRi8XKoliWEsqpJl7veI+UUSeDqK4SdjHi8TjGxsZAURTuvvtuOBwOjI+PS6LCtRLKWRnkeR5zc3OYnJxEe3s77r777oLbotWuDAYCgQwRbGpCoKcHg/39mJubK2qh5Xk+Mzzu92faPnZ7SVsfTJnHJKREKsR4ulhs2Xg6giCgUqmgUqlEkQlN0yCzPocerxc0TUOj0YgtqI0uODKZDHv27MHFbErJ888/j8cff7zqKSWboWJWCLZK61Sj0YDneezduxc6nQ7pdFqsHN64caNkimUpoZxqYils2EqNLU0GBSWsFMggz/O4efMmLl26hI6OjjzSI/XYvHJVBpPJJMbHxxEKhXDXXXehqampqN8XsomrAZ/Ph2eeeQYXWlsR6unB/sHBomf7GJqG2+NBOpVCW3t7yXfuOq0Wfp8PgUBAnJnTlTgfuKyVx3Wg2Hg6pVIptuAAiJVDv8+HRCKB69euQa3R5EXoFfs9y+Vy9GdTSobTaaiffx6PPfZYVeeSthIZ3CqfE7hjBaZSqdDS0oKWlhYAGUFaMBhEMBjEwsICJiYmoFAo8shhKcZSKom6mrg4bGkyCEjDazCRSGBsbAwkSeLo0aOiakxALZDBUh+fy+XC2NgYHA4HHnjgAahUqnUdVzUqU263G88++yzOd3QgtmMH9g0OQqVSicdSyDHF43G43W7odTp0dnWV5aHW0NgIu8MhRsDF43H4s/nApSCHUlw4NhpPp1QqoVQqEYvFoNVqYTIaxbay3+9HOpWCWq2+Qw51uoLIYW5KyfDkJLQvvICPfvSjkk4p2QzYjG3i5SA8n1d6jigUCjQ2NooVL5ZlEYlE8hTLAPIylpdTLEsJdTVxcaiTwSqmkPA8j9nZWUxNTWHbtm04cuTIsg9/uVyOdDpdhSMsDKUkXTRNY2JiAm63G4ODg2hra1v3w7oabWKn04nvPPsshru7QXV3Y9/gYFELOsey8Pl8iEajaGxqKnu7MDcCzm635+UDLyaHArlZixwKQpd0KlWS2cZSotTxdAqlEkalUvSKZBjmTnxeIICU0wmVWn3n/Gm1UKxwPYgpJQwD1cWL0L38Mn7rt36rKm3MrVQx2wptYuH5XOh3KpfLV1Us37hxQ1QsC+TQarVKavNSVxMXhzoZrFJlkCRJjI6OIpFI4MiRI6vOIFR79m0tlKoy6Pf7MTIyAoPBgFOnTm34hqu0gOT27dt49vnnMdzbi1R3Nwb7+/MWfoIgVs3rpSgKbrcbcpkMnV1d66qGbhSrkcNYPA7fGuRwvWkolUQ54+kUCgWMJtNScphNSEklkyI51GbJYe4CqjcYsLe/H5cYJpNS8uqr+OAHP1hxYraVyOBW+JxrVQbXQiGKZYqi8jKWbTZb1RTLPM+D5/l6ZbAI1MlghY2neZ7HrVu3MDU1hba2thWrgbmQujn2Rskqy7KYnp7G7Ows9u7di+3bt5fkAV1JEj07O4tnTp/G6O7dYLq7MdDfv2x7cDkFL8/zCGXjp6zZ3bhUqhXLkcNkMgmSJJeQQ4IgEIvHYbFY4JBwGkol4+mWJYcUJebRppJJKFUqsWqo0+nElJJJloVybAxGoxEnT54s2zGuhK1AkmrRZ3A9KLYyuBZWUiwL5HB6ehqxWAxGozFv7rBSFbWNkt/VUK8MblJUkmhRFIXR0VHEYjEcPny4YEVSLVQG13t84XAYIyMjkMvlOHnyJIxGY8mOq1KVwZmZGTz3wgsY6esDurvRv3fvinNiix/FNE3D5XKBoWm0t7cXPcNWachkskzub/Y4OY4DRZLw+XxIpdMgCALRaBQMTRfcVq40hEQHn8u1/ni6dV5XCoUCRqNRvM5Zls2QQ5JEOByG2+2GUqGAVqdDS1cXLnIclO+8A4PBUNGUEimpwMuJrVQZLPd8n1arRXt7O9rb2wEgT7E8MzODkZERaLVa0QjbZrOVTbEsrOnlUhPXyeAmRCXIYK49SmtrKw4fPlzUbEUtCEiKJYMcx+H69eu4evUqenp6sHPnzpLfuJUg0VevXsXpl17CSH8/5Dt2YO+ePWuaFAvLbCwahdvjgcFgQFtbm6SHsVdCKpmEx+OBUqXCjvb2TMVthcqhlMhhY1MTPG43vD4fduzYUfFIOgFyuVyssACZRSxJUSApCnKFAkqbDWMHDkD+2msgSRIHDx6ETqcr+/nbKiRpq3zOaghlVlIsBwIB3L59GxcvXoRSqcwTpZRKsSw898tVGay3iTchyk0GKYrC2NgYotHouuxRAGkonldDsaQrHo9jZGQENE3j3nvvhdVqLctxldtaZnp6Gi+8/DKGBweh6u7Gnt271yQVRJbYu1wuxONxNDc1iS3EWgLP8xkrikAgMzxus4kP8cWVQymSQ7PZDJVGAzqZRDAYhGORgr8QlOOY5XJ5xg8xSw7b29tx+fJljNM0FG++idu3b8Nut8PhcIj/q9frS34sW4kkbYU2sRRStpZTLAsZy16vt6SKZUE8Uo5ruF4Z3KQoFxnkeR63b9/GxMQEWlpacOrUqXULAjZLm1iYl5ycnERHRwf2rtJOLdVxlYvoT05O4ns/+hFG9++Hprs7E41XSKYtz8PtckGhVKKrq0tS6rtCwdA0nC4XGIZB+7Ztqz4Yl2srr0YOdTodlBUgh7nxdB6vd11ksBKQy+XYs2cPLvE8LtI0NNeu4dChQ+B5HvPz85iYmIBSqcwjh7VuFlxJbCXSK7XPKZfLRdIHZL4Lwc5mJcWyzWYraM0ol5IYqFcGNy3KQQYpisL4+DjC4TAOHTqE5ubmDf29zSAgSSaTGBsbQyQSWVM9XcnjWg/Gxsbw0quvYuTgQei7uwtqcQuVNI5lYTIa0djUJLmHcyFIxONwZf0P19PalhI5XC6eTorISymhaWhefRVPPPEEdu/eDZZlMwk1gQCcTicmJyehVCrFxdPhcMBoNBZ9/rYKSdoq1jJSqAyuBYIgYLFYYLFYsGPHDvA8j3g8jmAwCL/fj/n5+SWKZbvdvmyRpVyfl+f5emVws6KURCt3t97U1LRus+TFqPXKoNPpxPj4OBobGzdUIS0W5RCQDA8P4wevvYbRgwdhzBLBtRZNUSTCMJBn1aW1ttAK3oHRSKSk/odLyCHLIplKgSRJRLOxceUih3qDAQajEYlYDD6vF61tbRv+m+XCkpSS554TU0ocDgccDgd27doltt78fj/cbjcuXbqUV4FxOBwwFXD9bQUyKNiPbPbPCUizMrgWCIIQxVbFKpbLJZhJp9PgOK5eGdyMKBXRyo1OO3DggDg0WwrUamWQpmlcvHgRHo8H+/btQ1uFF9tSk+ihoSH86PXXMXroECw7dqCnp2fNB6wgEjEajWhva8Ps7GzJjqdSqKR3oEwuryg5bGxqws1oFB6Jk0Egk1LS39+P8VVSSha33jiOE8mh1+vF9PQ0ZDJZ3tzhSkP7tUYeikWp7VakjFqoDBaCxYrlVColilJyFcs6nQ4syyIej5d0ppaiKPE4Nhu2PBncaAIJz/NYWFjAxYsXxcpXqY02a6EySNN03s98Ph9GRkZgMplKYiC9HpSyMvj222/j/771FkYPHoSjpwfbu7tXfcCwLAuv14tEIoHm5uY7ljkEAV7C32UuhBken9cLi8WS8eercEttLXLo9fky1cV1ksPGhgbcmJlBLBJZVzxdpaHVasWUEnUBKSUymUxMkgAypCASicDv9+fFjC0mh1vBWmZxXu9mRi1WBguBWq3OUyzTNI1QKIRbt26BYRi88cYb4tiEYGlTSGV8JdTJ4CbGRqLeUqkUxsfHEQgEsH///oKC79eDWqoMsiyLS5cu4datW+jr60NXV1fVHkKlItE///nP8eq772L00CE09vau+ZkokoTL5YJSpUJnZ2de5aZWHsgsy8Lj8YAkSbS2torq1mqj1OSw1PF0lYDeYMDevj5cYhioxsaKSimRyWSwWq2wWq1izJhADgOBAK5evQqe56FWq6FQKBAMBmGxWDYlYRKeDbVyT24Em6UyuBaUSiUaGxuRTqeRTCZxzz33LKtYziWHxVzfJElCoVBIdr54I6iTwXUSLaEa6HA48MADD5Q1dqcWKoMcxyEUCmFkZARKpRL333+/6J1WLWy0MsjzPN544w38+/Awxg4eRMvOneLsynLgOA7BYBChYBB2hwNWq3XJQkPgjs+gVJFLZrs6O1fM0pUCCiaHOp1IEBeTw3LG05ULFqsVvX19uMiyUIyMrDulJHdov6enR8ygvXTpEmKxGIaGhsCyrLhwChm0m4EcbrU28Vb4nAKEmcG1FMszMzNgGEasnq+lWN6sUXRAnQwWTQZTqRQuXrwIv9+PwcHBiszByWQy8DwvWU8sgiAQiUTw9ttvo7e3F729vZI4zo2QaJ7n8dOf/hQ/u3gRYwcOoH3XLmzbtm3F16fTabhcLnAch20dHdBoNMu/sMJ5ycVgNe/AWsF6yGGx8XQ8z4OVwOasoaEB9O7dGOc4KN55B0ajEQcPHtzQ3xQyaK1WK7RaLfbt24dYLCZWDmdmZsCyLKxWax45rMWqk/BskMKzqtzYKpVBASutlSsplgVyePv2bSSTyRUVy5s1ig6ok8GiyKCgirXb7Th16tTKC36JIdzEUiSD8XgcN2/eBE3TuO+++2CxWKp9SCLWazrN8zxeffVVvH75MsYOHEDnnj0rkn6hkuL1eGAymdDQ0LCq3+By2cRSQK7ieS3vwFpCoeRQbzAgEQ7D5XKtOlPEMAzcbjcYmoZer6/kR1kWrW1tSKXTGGNZKF57DXq9Hrt27drw382tmplMJphMJnR3d4PnecRiMXHxFO79XKNgm81WE8SjXhncvChUTZyrWBZGREiSRCAQQDAYxKVLlxAIBPBnf/ZnOHDgAFpbW0vWIv7GN76Br3zlK3C73di3bx++9rWv4ciRI8u+9v/8n/+DZ555BpOTkwCAQ4cO4a//+q9XfP16UCeDBZDBdDqNixcvwuv1itXASt5YAgGUUquY53ncvHkTly5dEtuhUiKCwJ2KajHgOA4/+clP8MbMDC7u34/te/agZYVZUIZh4PV6QZIkWlpbq94WXy/i8TjcG/AOrCWsRA59Ph9ikQh8Pl8mBUSvX9JWJrPtc41Gg86uLsmcp66uLqRTKYzRNJQvvYTHH3lk1Sp2IVjJciWXHG7fvn1JZeXWrVtIp9PrMgquNLYaGZTK9VoJbMRaRng+CPdQNBpFLBbDz3/+c7z00ktYWFjAjh07cPz4cRw/fhwnTpwoyFkiF9/73vfw1FNP4dvf/jaOHj2Kp59+Gg8++CCuXLmyrAfvm2++id/5nd/BPffcA41Ggy9/+ct43/veh6mpqZJ1J6V3h1YYa5FBl8uF8fFxWK1WPPDAAxWrBuZCuKilIiKhKAqjo6OIx+M4evQoKIrC7du3q31YS1Bsm5jjOPz4xz/Gz2dnMbFvH3bs3YumFQzDSZKE2+WCSq0uaq6OIAjJzAyWyzuwliCQw23btsHlcoFOJqHLRuTlVg4VcjlS6bRYAZNShZ4gCPTu3IlLDIMxmsZzp0/jdx9/HA0bSFUp1H9vcWWF53mQJAm/3w+/3y+23QRy6HA4JEMOpdhpKRe2YmWwVN+tyWTCE088gSeeeAIvv/wy/uf//J/40pe+hF/84hf4zne+g//+3/87rFYrvvnNb+LXfu3XCvqbX/3qV/F7v/d7eOyxxwAA3/72t/HKK6/gX/7lX/CZz3xmyeuff/75vP//z//8z/jBD36AM2fO4JFHHtn4h0SdDK5IBtPpNCYmJuDxeDAwMID29vaq3UwEQZQ9Z7dQzM/P4+LFi2hubsbhw4ehVCoxPz8vyTm4YgQkLMvi5Zdfxi+cTkzu34/evr5ld2gcxyEQCCAcCsHR0ACLxbKudIdqQ/AOJAii7N6BtYDceLpwOIy+vj4Amfa50+lEOp2GRqNBKBRCJBJZVZBSreMXUkrGaBrPPfccnnjiCZgqnHtNEAT0ej30er0otsolh+Pj46AoKmNVlEMOq6HO3CqG08DWqwyW6/OSJAmDwYAHH3wQDz74IICMx/D58+dXFRfmIp1OY3h4GJ/97GfFn8lkMrznPe/B2bNnCz4OYTyjVKiTwWXIoNvtxtjYGCwWS9U88haj2vYyQqvc5/MtsdEpZwbwRlBoZZBhGLz00kv4pc+HS/v2YVdf37JZtelUCi63GzzHoaOzc10K8nKkohQDKXgHShWL4+mY7BylWq1G2/btUCgU61IrVwpiSglNYzSVwvPPP4/HHntsXd2MUhIlnU6Hjo4OdHR0ALgzk+X3+zExMYFEIpFHDu12e0XI4VYjg1vlswKZzX05rqHl1MQajQbHjx8v+G/4/X6wLIumpqa8nzc1NYnWN2vhT//0T9Ha2or3vOc9Bb/vWtjyZDCXyNA0jYmJCbhcLgwMDGDbtm2SuYGqaS/j9XoxOjoKs9m8rHBmPbN5lUAh1VSapvHiiy/ibCiE6YEB7BkYgC1rQyAgl0CZLRY47PZVRSJrHVO1BCRS9Q6UCnLj6WZnZwGeX2IRVAorm3JCqVSif2AAYyyLC1NTYkpJsW3ZchKlxTNZQsSY3+/H1NQU4vG4qOYUyGE5Iiy3Wpt4K1UGWZYti92bFNTEf/M3f4MXXngBb775ZknH1rY8GRQqbh6PB2NjYzCZTHjggQeq/oUvhlwurzgZZBgGly5dwu3bt9Hf34+Ojo5lFwgpVwZXI6npdBovvPACzsbjuDI4iL0DA7BarXmvYRgGHo8HFEXVNIESvAOLnXHcanA0NCARjcLv92P/vn1rJpJIkRxqtVoMDgxgnGXFlJLf/M3fLJr4VIrALo4YSyaTIjkU8mdNJlMeOSzFQr/VKoNSmNOsFMpFfkvhM+hwOCCXy+HxePJ+7vF40LzCjLqAv/u7v8Pf/M3f4D//8z8xODi4oeNYjK1zdawAnufBsiwuXLiwKuGpNipNuILBIEZGRqBWq3H//fevaqMh1crgatXUVCqF06dPYyiVwrWBAfQNDCxRQycSCbjdbmjUanR1dZXkYVpp0+nN4B1YKVAkiVQyCU4mA51Kret7kgo5XJJS8u//jg984AMFv08172eNRoO2tjZRJZlKpURyeOXKFUSjURiNxjxyWO1WuNSxFSuD5ZoZ3GihSKVS4dChQzhz5gwefvhhAJnv58yZM3jyySdX/L2//du/xV/91V/hP/7jP3DXXXdt6BiWw5Ymg0L7EwBOnjwpaWuQSlUGOY7DlStXMDMzg127dhUkmZdqZXCl+bxkMonnnnsO5zgOM/396BsYyFPSciybEYmEw2hoaIB5HSKRVQ4KLMtWZCHarN6BpQbP8wiFQgj4/bDb7aCSSUQCAXg9HnRt376hv11NcmixWtG7dy8mclJKTpw4UdDvSokoqdVqtLa2inPKAjkMBAK4du0aLly4AIPBIBJDu91e0LW+1drEUvk+K4FSqolzUaoEkqeeegqPPvoo7rrrLhw5cgRPP/00EomEqC5+5JFH0NbWhi996UsAgC9/+cv44he/iNOnT6OrqwtutxsAYDAYSsZbtiQZpGkaU1NTWFhYwO7duzE5OVnWOLlSoBKEKxaLYXh4GDzP4/jx4wVbjdRSZZAkSTz33HMYkskw29eHgYEBGHMUl4LKFkBZVLYajQb+rJ2LNksSdDpdyYedt5J34EbAMAw8bjdSqRTa29uh1elAM0wmns7nQ2eJs7UrTQ4bGhuRFlJK3n4bBoOh4JQSqZKHxeQwnU4jGAzC7/fj+vXrGB4ehl6vF8mhw+FYlhxKifCWG1utMlhuNfFG8ZGPfAQ+nw9f/OIX4Xa7sX//frz22muiqGRubi6PzH7rW99COp3Gb/7mb+b9nf/3//1/8ed//ucbPh5gC5JBn8+H0dFR6PV6UQwxOTlZNvVRqVDOyiDP87hx4wamp6exfft27N69u6gbScqVwdxzFo/H8eyzz+K8Wo253bsxODgo3tg8zyMSDsPn85VVZWu322G1WEBRFEiKQjgchtvthlKpFEmCTqtd90xf3TuwcFAUBZfTCZVajY7OTnEMwOFw4JpCUXA83UZQCXLY1taGdDqNcYYpOKVEipu7laBSqdDc3CzOW9E0LZLDGzduYHR0FFqtViSGDocDOp1uy5HBrfJZgfK1iSmK2pB/Zy6efPLJFdvCb775Zt7/n52dLcl7roYtQwYZhsHU1BRu376Nvr4+dOXs+Ils607KKBfhoigKIyMjIEkSx44dEwO9iz02KS4euccVi8XwzDPP4LxOh/ksERTmIIWIsVQqhda2trLHjMnkcugNBlGMwrIskhSFBEkiGAzClUxCpVaLi79WpytoXrHuHVgYFreFF89RyuVyNDgc8Llc8Ho8FSXU5SKHYkoJwxSUUlLLREmpVKKpqUmssgjkMBAIYHZ2FmNjY9BoNNDr9WAYBolEAjqdrmY/byHYapXBcrWJSZIsSZtYitgSZNDv94u7w1OnTi1Z7Kvt4VcISm0tw/O8aCDd2tqKI0eOrLsyKtXKoHDOIpEIvvOd7+CC2Qz3rl3YNzgo3tCJeBwutxs6rRadOdWhSkK+iBwyDJOpHJIk/IEA0k4n1Gp1Xls598Fe9w4sHCzLwu12I5lMoq29fcUHe2NTEzxuN7w+H3bs2LFuK6GNolTkkCAI9Pb2iiklz3/3u3jiscdWrHLUMhlcjMXkkGEYBINB3Lp1CzRN48yZM1Cr1XltZb1ev2k+P7C15iOB8qqJN+vs9aYmg4I1ytzcHPbu3Yvt27cve4PXAhks5TGmUilcvHgRfr8fBw8eREtLy4b+nvCQkdoCQhAEUqkU/u3f/g3n7XZ4e3sxODgIrVa7pJ1qMpkkc+wKhUKM+AKy5JAkxSSHdCoFjVYLnVYLjUaDaCxW89Y3lUBuW3gt4m82m6HSaEAnkwgEgyVrDW0UGyGHMrkcu3fvxgRNY5Sm8fzzz+Pxxx9fklLC8zzS6XTZK+TVgkKhQGNjo7jpuvfee8XK4fz8PCYmJqBUKvPIocFgkMzzYT3YamSwnGriemWwxiBUAzUaDe6///5Vhz5rgQyWqjLo8XgwOjoqZi2XQjgjPGRYlpWUl1U4HMb169cx2dWFQE8P9g0OQqPRIJVKwel0QiaT1UQ7VaFQwGgyiUIXmqZBkiRisRiCoRDA89BotaAoCiAIaDWaqlWypAie5xEOh+H3+WCz22ErwF5HJpOhsbERC7duwevxSIYMLsZ6yGFfXx/GaRojqRTUi1JKGIbB2NgYIpEI9u7dW82PVnYIc3RyuRwNDQ3id8yybGaMIBCA0+nE1NQUFAqFqFR2OBwwGo01RQ63Ihksl5q4XhmsETAMg+npady6dQt79uxBd3d3zVqj5GKjhJVhGExOTmJhYaHk6Sq5lUGpwOv14vnnn8fE9u0I9fRg/+AglCpVpgLg98NqtcJmt9fkA1KhUIjVwgaHAwajESRJgiJJRNxusCwLjUYjkgSNRlOTn7MUYFkWHrcb1Bpt4eXQ1NiI+bk5MZ5OygIzAYWSw8amJiwwDEZyUkooisL58+ehVqtx8uTJkqYbSBErdTLkcrkoNNm1axc4jkMoFILf74fb7calS5cgl8vzyKGUOgvLYauRwXKqieuVwRpAIBDA6OgoVCrVmtXAXGz2yqBgIK3RaHDq1KmSX8y5lUEpLJhutzujGu7ogL+9HQf7+yGTybCwsIB0KlU0KZASVvIOVKlUsFgs4HkedDoNkiRFtTLPcZm2crY6pN4i5JCiKLhcLiiVynXNg+bG0/m8XrRmTZBrCauRw8bGRlxjGCgnJ0H+7/+N9vZ2bNu2DYODg1tCbFAoQZLJZCLxE34vHA7D7/fD6/VienpafI3QWjabzZIih1uJDApBEvWZweKwachgOp3G0NAQdu7ciR07dhR1I1Yj6q1YrIewchyHy5cv48aNG9i9e3fR56VQCH9TCpXBhYUFPPPccxju7gbV3Q2bTod0Oo2FhQXodTp0dnXV7EInegfq9St6BxIEAZVaDZVaDYvVKs5/kdmZw2AwCPB8Royi1UKbrRxKaeHaKHJtgqw2G+x2+7o/X2NTE25Go/DUKBlcjFxy6HA4YLNaMc1xUI2NQZE1svV6vZtaTCFgvTPOMpkMNpsNNpsNAESRmt/vh8/nw+XLlwEgr3JoNpurSsa2EhkU1vK6mrg4bBoyqFKp8N73vnddlalaqQzSNF3w66PRKEZGRgAAJ06cWDIkXkoQBCGJVvvt27fx7PPPY7i3F6nubvTv3YubN2/C6/HUtOfeRrwDCYKAWq2GWq2GNUsOk8lkRpBCUQgEAgBBZObJ9HrodDqoypydW04IOeMkSZakAtzY0IAbMzOIRSKbbiFgaBrxRAKWhgZMDAxAMTKCXbt2oa+vDy6XC0PnzmHe5YJcroTVakZP13b09/dJviVaKHieLwlhkMlksFqtsFqt6O3tFdX9fr9fTEnheR42m00k2RaLpaLkbCuSwXplsDhsGjIIYN0tylohg4VUL3mex8zMDC5fvozu7m7s3r27Ig+BUlvfFIvZ2Vk8c/o0RnfvBtvdjZ09PVhwOgGgptvCpfYOJAgCWq0WWq0WNmQenKls2zAej8Pv84GQyUSxQbmyc8uBZDIJp9MJpVKJrs7OdRt350KlVsNqsyHs95cknk4qoEgSTpcLWq0We3bvhstsxjjHQf7LX8Lt9cHR0obdh47gmM0OiqIQDAYxe/MG3vnX78BqMmD/4KA4V1erlcNyGTETBAGLxQKLxYKenh7wPI9oNCqSw+vXr4NlWdiyVWuHwwGr1VrW5/RWIoPCWl6fGSwOm4oMrhe1QAYLOUaSJDEyMgKKonDPPfeIbYxKoJpkcGZmBs+98AJG+vqA7dvR1tYGp9MJq82GQDoNRQ22hSvlHSiTyURyaLfbwXEckslknuBALpeLLWW9Xi+JudBclLItvBwaGxsR9vvh8XpLHk9XaeQqq+1ZEkIQBNra20FRFIamL0PtdOO/DB5AY1Mm0UOpVMJkMqGrqwvcyftx7cpl3Lp9CxRFYWJiAiqVqibbypWywiIIAmazGWazGTt27ADP84jFYiI5vHHjBliWhdVqFc+j1WotKZnZimSw1N8tz/P1yuBmRy2QwdXIFs/zuH37NiYmJtDe3o6777674hYv1SKDV69exemXXsJIfz+I7dthNpsRjUbFnNlQMIjqTzIWh9xWZ6W9A0UbkhzBAZVtK0cjEXg8HigVirLmKheDvHNVpvQYh8OBa0olUhRV9ni6coLLnqvECi10UzQG4+Gj8FFJvPX223jvAw/A4XDkvUYmk2HXnr1YMBqgA4977rlHVNoKHn0CORSIjVTJYanaxMWCIAiYTCaYTCZ0d3eD5/lMVT5LDm/evAmapvPIoc1m2xA53EpkUFASl/qao2kaHMfVK4ObGbVABlc6xlQqhbGxMYRCIdx1112iy36lUQ0yOD09jRdefhnDg4OQbdsGrUYDlUqFxsbGOw9OgpCEsKVQUCQJl8sFlVpdslbnRiCTy6HX60WSxbGsmI4SDofhdrmgVKmgzxLDQqPzSgGhLaxQKMp6rnLj6TwVjqcrFdI53prLnSuaoqBM0ejoH8Dc3G3cZFi8+fO38L73vmfZeeO29g5MjVzArt4ekfgBdzz6/H4/bt++jYsXL0qWHEolr5cgCNFkfvv27eB5HolEQiSHt27dQjqdhsViySOHhd5nPM9vKTJYTsNpAPXK4GZGLZDB5ciWy+XC+Pg47HY7Tp06VRID6fWi0mRwcnIS3/vRjzC6fz/41lbodDo0NzeLxswCiBohgzzPIxgMIhgILJuXKxUsl6tMURQSiQQCgQBS2YSPYnOVi0FuC70cbeHl0JSNp/P5fOipYjzdehCLxeB2uWDOkonlSEHs5k00tm8DIZOhfVs7bnEsbjAM3nzzTbz3ve9ddgG0NjZhfmEBnR0d4s9yPfqAzPUhpHtIjRxKLTFJAEEQMBgMMBgM6OrqAs/zYvqQQLKTyeQScrhShV54/tXJ4MZAURSAOhnc1JDL5Uin09U+jFWRS1hpmsbk5CScTicGBwfR3t5e9YdaJcng2NgYXnr1VYwcPAi+oQGNDgdaWlqWfRjWAhlcyTuwFiCXy8WFC1gUnSfkKucYYGu12o21u3JanZVsoZstFqg1GqQlFk+3GnieR8DvRygUWnajlAs6GIKuoxtA5jvt7OjADYbBDEMj9ZOfYP/+/ejt7c37nYamZixcu5xHBhdjuXQPqZDDWqmWEQQhVuc7OzsBII8cXrx4ERRFwWw2i+fQbreLz8NyWq1IEeX6XkmShEKhkNzMdKlQJ4OojQQSgWwFAgGMjIxAp9PhgQcekAxxqBQZHB4exg9eew2jBw+CdzjQ3d29aryY9Pb9+SjEO7CWsDg6j6FpkNm2stfrBU3Td9JRssKVQqtsQoygXC6veAudIAg01EA8nQCGYcQNRkdn55pdAxlBADwPKplEPB5HIpEATdPwOhqgpihMTk4uIYNKpRI0wxR1XFIih1KtDBYCnU6Hjo4OdGSJOEVRIjmcnJxEIpEQyaEw1rBVyGA5K4ObdV4QqJNBALXRJgYyF+PZs2cLjtmrJCpBBoeGhvCj11/H6KFDkDc0YM/evWuSYUImAy9BQ/GNeAfWEhRKJUxZNSpwJ1eZJEl4PB7QDANtjo2NRq1elhyGw+FMW7iKMYK1Ek9HURRc2YpsR0fHqgtjMplEKBSC6/Y8aJUWLMMAfGYTxcsIEHIZaLUaDWbLkt9lWXbDSv1qksNaJoOLodVqsW3bNmzbtg1A5hoIBALw+/24cuUKAOAXv/hFnupbpVJV85DLhnLODEql+FIO1MkgpE8GI5EIJiYmwDAMTp06BaPRWO1DWoJyk8G3334b//ettzB68CC0ra3Yu3dvzVbRSu0dWEtQKpWizQbP8yI5pEgSznAYHMeJlUN91uPQ5/MhkUhUXFm9GGI8XTQKr9eLNoklkuRa7Kw0d8rQNMKRCELBIMLhMCiKAsFxSFMJmMNhqM1mGLItSYPBAL/fD7hcsNmsS97P7/OiqcGx5OcbQbHk0OFwQKfTrYvUlSu/VgrQarVob29He3s7SJLEz372M/T29iIQCODy5cuIxWIwmUx5EXrVnDkvJcrVJq5XBrcApBpHx/M8rl+/jitXrqCtrQ1ut1uSRBAoHxnkeR5vvvkmXjt3DqOHDsHS2YmdO3cW/PAnCAKcRGYGK+UdWCsgCAIqlWr5XGWSRCgUAseykMnlmcQGubzq1Rwhnk5qZJBjWXi83gxpzrHY4VgW0VgM4VAIoXAYsWgURPY+5QFAJoPBYoHh8GEYfEH07N4NYvE1yS/v2RZwudB39+Gyfq7F5JBhmFXVyoWSw/n5eczNzeHgwYNlPX4pQCBHAjkEMiMXuZXDaDQKo9GYRw41Gk2Vj3x9qFcG14c6GYQ0K4OJRAIjIyNIpVK45557oFAo4MwmakgR5SCDPM/j1VdfxZuXLmHs4EE09fRge5EJEER2FqraqKZ3YK0gN1eZkMkQTyRgMpuhVqlAURTmQyEAEFXKOp0OarW6ouRQivF06XQaTqdTrDSn02kszM8jFA4jHA6DYxgQwj0gk0Gj18OSjU+zmM3i7KV36BxS8Tg0BURX+n1e2M3GirfKFQrFquRwfHwcarV6RXLI8zwuXbqE2dlZHD58uGpWXJXEcpUytVqN1tZWtLa2AshcQwI5vHbtGi5cuACDwZBHDmuFCNVnBteHOhmEtMggz/O4desWJicn0dHRgb1790KhUCAej0uyeimg1GSQZVm8+OKLGJ6fx9iBA2jftUuchykGBFB102mpeQdKGbkVrrZFpDkvV5kkEfD7QWQTVASfw3JH50ktni4Rj2N+fj4jguM4DA8PI51MiuSPJwgoVSpYrFZYLBZYrdYVKz72A/sx9+4QOnp2iYRwuXsn4PMh7FrAvXcfLdfHKhjFkEOLxQKn04lUKoUTJ05ItstSahTSNlWpVGhpaUFLSwuADDkMBoPw+/24fv06hoeHodfr88ihVIlROdXEtUKI14M6GYR0yGAymcTY2BgikQiOHDmCxsZG8d+EVna122QroZRkMB6P44UXXsB0JIKxAwfQuWfP+ltyVbSWqRXvQKkgnUphwemEXCZDZ2fnkqrTsrnKySQSOdF5YoKKVgtdNjqv1Oe82vF0DMMgGonA6XIhGo2CpmkQHCdufAiFAmazWSR/BoOhoGOUq1RouPso5kfHoOFlsGc3X0SWEgYDAXgX5mHSqnHv3UclOeKwEjlcWFjApUuXxJnUq1evbnjmsFawHnKkUqnQ3NyM5uZMJCFN0yI5vHHjBkZHR8UIy9zzKAWUszJYJ4ObHFIgg06nE+Pj42hoaMCpU6eWKL2Em1mqQ8+lIINCVfSVV17B9XQaF/fvx/Y9e9CSbWWsB9XyGaxl78BqIBKJwOvxFDVLKZPJoM22jIFMVTGZSom5yh6vtyzReZWOp+M4Dol4HKHs3F80EgHPcSB4/s7cn8mUIX82G0wm07qfEXKVCo1HjyAdj8N14ybmpi9Df+UKuoJ+NN1zDMcO7qupWTKFQgGGYbCwsICenh709PRkspkLbCtvBpSiUqZUKtHU1CS21WmaFiuws7OzGBsbg0ajWUIOq3EeyzkzKBXCWw7UySCqSwZpmsbExATcbrdoIL0chIt7s5LBdDqNsbExnDt3DtdpGhP79mHH3r1oyu5M14tqzAxuNu/AcoJjWXh9PsRiMbS0torm1euBTC5fmqtMUSApKhOd53ZDqVSKr9Fptetq2QvxdN4yxtNRFIVQKIRwOIxQKASWpvNav3KlEo5stdlisZTcJkRlMMAxOACfUgFjPIrBvbvRt2d3Sd+j3OB5HlevXsW1a9dw8OBBcT5urbayVEhNqVCOtqlSqURjY6PYvWIYRlR9z83N5Ql7BBPsQivUG0U51cSbeVNfJ4OoHhn0+XwYHR2FwWDAqVOnVr3QhIubZVlJ+ptthAz6/X5cuHABs7OzuMqymNy/H719fXlt8vWCAJCmaVGVWk5sFe/AUkHIyyVkMnR1dZX8ul4uOi9JUUiQJILBIFzJ5Lqj80odT0fTNMLhsKj6TZLkEvKn1+sBns9UaJqbJdmmlQoYhsHIyAgikQiOHz++4r242szh3NzcpiCHlUhaUSgUeeQw1xJofn4eExMTUCqVeeTQaDSW5TyyLFsWm5x6ZXALQCaTVTTMm2VZTE9PY3Z2Fnv37sX27dvXvClkMlnGJkWiIpL1pLhwHIfLly/j+vXr8Pl8mKRpXNq3D7v6+8Vs041Cr9cjkPVUy/WvU2s0Jf2uc4lNZ1fXpjV0LRWi0Sg8bndFLXbki8ghwzCZymFudJ5anddWXqmqK8bTUdS64uk4lkU0GkUoW/mLx2JAztwf5HIYTSZYrVaYzWYx/7mlubnySnSJzimvhEQigaGhIajVapw4caIoYrAZyWE1YveW84sMhUIIBAJwOp2YmpqCQqEQiaHD4SgZOazPDK4PdTIIiNUAlmXLftOEw2GMjIxALpfj5MmTRSnapBybJ5PJQNN0wa+Px+MYHh4WZ0+Gk0lMDw5ib38/bHZ7yY7LYrXCbLGI/nWJrH8deF6sBun1eqjWqUKtewcWB45l4fP5EC1BW3ijUCgUMBqN4j2Yl6vs9yOdSkGj1d6pHOZE5xUbT8fzPMhEQiR/EcHyRXiBTAadwSBavpjNZigUCtA0LVpKLSeqqSMfXq8XFy5cwLZt29DX17fhe3EzkEMpZDDL5XLx/OzatQscx4nk0O1249KlS5DL5Xnk0GQyres8lmsdJ0myqs+rcqNOBlGZFizHcbh27RquXbuG3t5e9Pb2Fn3BVir/dz0o9Nh4nsfc3BwmJibQ3t6O8fFxvJtI4MrAAPoGBmC1Lk062Chy/essVuuKFiW6nIpQIZW9undgcSh3W3ijWJyrvGx0Xra6rNXp0LhGPF0qlcqIPkIhhEMh0On0ndavTAZl1qZGUP0urmAl4nG43G4YDQY0NDSUfcxhWWSPV0rkZjnwPI8bN25genoag4ODYmZvqVGL5FAKZHAxZDKZSPx27twJjuMQDocRCATg9XoxPT2d9xohY7mQ81iuuXqKoiSfSb4R1Mkg8pW65UA8HsfIyAhomsa99967bsIjBdXzSiiEDAoikWAwiP379+NnP/sZhlIpXMsSQYvFUpFjXc6iJJlMZlSokQg8Hg+UCgV0ev2KQoM878CuroJnzbYqYtEo3G43zBYLHDVSPc2NzgMy5DCRSIAiSUTcbrAsC5VGA5qisDA/j7b29kzrN0sAKZK80/olCMjkcpizxM9qsUC3QsZuriVRffZ0bbAsi7GxMfj9/g09X9eDWiCHUiSDiyGTyWCz2WCz2dDb2wuO4xCJRJbkKy8mh8t9rrqaeH2or2DIkAO5XA6GYUr6d3mex+zsLKamptDZ2bnhPN1argx6vV6Mjo7CYrHg2LFj+P73v49zHIeZ/n70Dw7CVEDqQbkgy6kKwuEQVahLhAbZ16SSSYRCobp3YAHIbQs3t7TUtNGvUqmExWIRo/PS6XTGf42iMHf7Nm7NzYl+f0Cm+mc0m0XyZzKZ1qzusSwLt8uFVColCUsiHoBMwjODFEXh3LlzIAgCJ0+erLrtTaHkUBBSVIIc1gIZXAyZTJa5b6xW9PT0iOM4uSkpHMflkUOLxSKOUtXVxMWjTgazKHU+MUVRGBsbQzQaxdGjR0tSXq7FymCuWKa/vx8NDQ14/vnnMSSTYbavDwMDA2JbTipYrEIVZsni8ThcLhd4joNKrQbHcRlXeo2mOi08iWNxTFqti2p4ns+zfAmHwxnLFwAEwwByOZQajXg9qFUq6A0G6LRaqDWapZm/i5BMJuF0OqFSqdDR2VmvNq+BQCCA8+fPo6mpCYODg5K0cFqOHOZasFSCHNYiGVwMgiDEjdiOHTvA8zyi0Sj8fj8CgQBmZmbAsixsNps42lHqCmG9MrhFUEqitbCwgPHxcTQ1NeGBBx4o2WxUrVUGo9EohoeHxV07QRB45plncF6txtzu3dg3OFgTc3YKhQKETIYEScJoNMJms2XayomE2C7UaDTQZ9vKGo1GspWUSkFoC5vM5sy8W40uRul0WvT6C4dCSKVSILLXuWD5IpPJwCSTaGltRW9vb+bfcudSKQqBQAAgiCVzqcJ1IphuW2022O126Vw/Ep0ZnJ2dxeTkZMFuDFLBYguWSpDDzUAGF4MgCHGEQyCHsVgMfr8foVAI165dw5UrV2Cz2cRzabVaN0QO65XBLYJSkMF0Oo2JiQl4PB7s379fNDktFWqlMpjbHu/u7sbu3buRSCTwne98B+d1Oszv3o3BwcGMb5rEsZJ3oFqthtlsBs/zoNNpJLK70WAwKCqVhZnD9SqVaxFiWzgaRXNzs+SqvmuBZVlEIhGEs9W/eDyeR/4IuRwmiwXW7Oyf3mDIzDRNTSEYDIpxkctG52XTUeLxOPw+X0a0pNWCYVmksmRSkmrFKsU5LgeO4zAxMQGn04m77767ZBZU1UK5yaGg2q12+7zcIAgCJpMJJpMJ169fx4EDB6DRaMTK4c2bN0HTNKxWq3gubTZbUeSwXhncItgo0RJm4kwmEx544IGy3Hy1UBlMpVIYHR1FJBIRH9aRSATf+c53cMFigXvnTuwbHKyJm6oQ78BcpbJ1kVI5d9HX59jYSE1FWyqk0+lMG53na8Zrked5xLNRb+Fs1BvHsqLqFzIZdCYTrNkWlSlr+ZILu90OIhtPF4lElhVCyWQykRza7XYxYs7r84FjWfAAPB4PYtGopK4TgQZKYTOTSqVw/vx5MAyDkydP1sQzpFiUkhym02mcP38e6XQag4ODlf4oVQPHcXm2Udu3bwfP80gkEiI5vHXrFlKp1BJyuNpoRr0yuEWwXjLIMAwuXbqEubk59Pf3o7Ozs2wPzlLPNZYSMpkMqVQKb7zxBux2u5ivHAqFMkTQ4YC3txeDg4OSv6E24h2YVxGy2+/k5SYSd5TK2Ug0gSBuhtkwsS1sMlXPBqVAJLMCIKH6t9jyRaXRiOTParVCtYZpcW48nTd7zawFiqLg8Xqh1+vRlF34qewmIlfRXupc5VpFOBzGuXPnYLPZsH///k1xzxSC9ZBDvV6PeDyOd999F0ajEUeOHNlS185ys4IEQcBgMMBgMKCrqyvj+5n1Ew0EAhgbG0MymYQl63YgkMPc81avDG4RrMfQORQKYWRkBEqlEvfff3/ZWzxSNZ1mWRZzc3MgSRIHDhzAtm3bQBAEAoFAhgg2NyPQ04N9g4OSb1eU2jtwcV4uK+TlkiQCgQBS2dQLoaWs1WolOQi/EjiOy7SFIxHJtoUZmkY4EkEoGMxEvVFUXutXplBkiJ/FAovVuq4ZrULj6XieRyi7mDc0NuYRR71eL45OcDnXSTgchtvlglKlgj57LVVsE8HzGYFMFSuD8/PzGBsbw65du9DT0yOJKmW1UAg5VKlUSKfTaGhoQH9//5YigkBh1jIEQYj3W2dnJwDkkcOLFy+Coij86Ec/As/zeOCBB5BIJEpSyPjGN76Br3zlK3C73di3bx++9rWv4ciRIyu+/vvf/z6+8IUvYHZ2Fr29vfjyl7+MD3zgAxs+jsWok8EsFApFwUSL4zhcvXoV169fx86dO9HT01OxOC2pVQaj0SguXLgAnueh1WpFs1ev14tnnnkGw21tCPX0YP/g4JoVlmqjEt6Bcrlc3KECd5TKCZKE1+sFTdOisbFOr4dGrZZslU1Ix+B5PqMWlsj3y7EsorGYmPMbi0bvkD8AkMlgEOb+bDYYDYYNn+O8eLos0VsMlmXhdruRSibXtI1ZLldZiKQTNhHrzVWuFfA8j0uXLuHWrVs4fPgwmpqaqn1IksNicnjjxg1MTU2hsbERNE3jzJkzYuUw1+dws4LnefA8v671WKfToaOjQ1zDKIqCz+fDK6+8gs9+9rMIBAJ49NFH8eCDD+L+++/H8ePHi/a0/N73voennnoK3/72t3H06FE8/fTTePDBB3HlyhXxO8zFO++8g9/5nd/Bl770JXzoQx/C6dOn8fDDD2NkZAT9/f1Ff8bVQPC8hKaDq4jz58/DYrGIasCVEIvFMDIyApZlcfDgwYoZJQPA6OgotFotdu/eXbH3XAm5jv87duyAw+HA6Ogo3ve+98HtduPZZ5/F+Y4OxHt6MDAwIOn5sVyTX7vDAavVWrXqQ66xcYIkwXMcNFqt2FKWilI5Fotl2sJGY9XbwkLLJ9fyhWOYvNavVqsVo94sZvMSE/FS4ObNm5ifnYU1W5HJRSqVwsLCApRKJVpaWjZM3HKj80iKQjqVglrYRJSwwjw5OYmGd97BJ+66CwcPHtzw3ysU6XQaw8PDIEkSR48elaawRkLgeR5TU1OYm5vDkSNHRGGNUDkUKl6CmGSzkkOGYfDKK6/goYceKumaw/M85HI5/uEf/gHT09P4+c9/jqtXr2JgYACPPvooPv3pTxf0d44ePYrDhw/j61//OoBMYWnbtm345Cc/ic985jNLXv+Rj3wEiUQCP/nJT8Sf3X333di/fz++/e1vl+bDZbG5tpIbwFpVN57ncfPmTVy6dAldXV3Ys2dPxdt5UhGQJJNJjI6OIhaL4dixY7Db7QiFQuA4DgsLC3jmuecw3N0Nqrsbg4ODkm5T0DQNl8sFhmEkYfK7nLExSZIgsxWhXHsSvU4HZYWVyhzHwe/3IxIOV7UtnM5GvYXDYYTCYaSTyTvkjyCgVKlgsVrFub9KjCc0Njbi9q1bCAYCSKfT4mIUjUbhcbthtVphdzhK8n0tjs5jaBpktq0sVJg1AjnMzrBKtcK8GNFoFOfOnYPRaMSJEyck/fyQAmiaxvDwMBKJBE6cOJFHnFdqK/v9fty6dQtjY2ObihwK3b1Sr800TYPnefzX//pfxQq12+3GW2+9VfB7CRucz372s+LPZDIZ3vOe9+Ds2bPL/s7Zs2fx1FNP5f3swQcfxI9+9KP1fZBVUCeDWayWQEJRFEZHRxGPx6tqZyAFaxmXy4WxsTE0Njbi1KlT4oNaJpNlVMPPPovh3l6kursx2N9flgpMqRCPx+F2u6HX69He1ia5xZIgCKjVaqizSuXF9iQ+nw9yuTzTKszOHJZz4RTbwhxX8bYwwzCIRiIIZT3/EomEmPbBA5ApFDCZzSL5MxgMFa+g6vV6GIxGJKJR+Hw+tLS0iPOU5baNUSiVMCmVYpLPsrnK2ZayTqcravyA4LiKnUuXy4WRkRHRkkoKVXApgyRJDA0NQa1W4/jx42tWwzY7ORSKJaUe2yJJEgDyigXNzc347d/+7YL/ht/vB8uyS8YdmpqacPny5WV/x+12L/t6t9td8PsWijoZzGK5yiDP81hYWMDFixfR3NyMw4cPV3WXKpPJQNN0Vd6bYRhMTU1hfn4eg4OD2LZtW96/Lyws4NLVq7jY1we2uxsD/f2SnWHK9cKrpezXJfYkLCsqUMPhMNxuN5RKZVlEBkL6SqXawoL1Sig79xeNRMBzHAievzP3ZzJlyJ/NBpPJJAnhTWNTE25mK4Esw4CrAnEG8nOVeZ4XySFFknCGw+A4Tqwc6nU6qDWaqhoT8zyPq1ev4tq1azh48GDJPVo3I4LBIM6dO4eWlhYMDAys6/vbbORQiKIr9SaCoigAqHrnqJyQ5mpdBcjlcqRSKfH/p9NpjI+Pw+/3l8VAej2Qy+VIJpMVf99wOIzh4WGoVCqcOnVqycNgZmYG3//hDzE2MAB0d6O/r08SC/NyKMQ7sFYgk8tFRZwDy4sM1DkL/npahRzHIeD3IxwOo6m5uawZ0mLUW5YAsjSd1/pVazTi3J/VapVk+7CxsRE3ZmYQj8VgdzjQ0dFR9YozQRBQqVRQqVTi+AEtjB9kNxI8x2VsbLTavNlUYaS8nBU6mqZFb9ITJ05UNae8ViAorPfs2YPu7u6SfT+rkcPZ2VmMjY2Jm1EpksNSR9AJIEkSCoViQ88ch8MBuVwOj8eT93OPx4Pm5uZlf6e5ubmo128EdTKYRW4L1uPxYHR0FFarFadOnZKMHUqlZwZ5nsf169dx5coV9Pb2ore3d8nu8+rVqzj90ksY6e9HsqkJd0mUCG7EO7BWsESpnDNHJrYKNRqxpaxZoxpE0zRcTmfZqls0Td+JeguHkSTJPPInz85PCpYvWq1W0m1DwcBarVYjTVGZGDAJ3gu5RumWrFG6MH5AZS2PgIy6ks5mL5cLiURCbHOePHmypjdnlQDP87hy5QpmZmYqorCuNXJYrug9iqI2/LlUKhUOHTqEM2fO4OGHHwaQOd4zZ87gySefXPZ3jh07hjNnzuBTn/qU+LOf/exnOHbs2IaOZTnUyWAWcrkcNE1jfHwc8/Pz6O/vR0dHh6QWn0r6DFIUhZGREVAUhXvuuQc2m23Ja6anp/HCyy9jeHAQyu3bYVYoyrpwrBcsy8LjdoOkqJJ4B9YKFs+RpQusBgFAIh6H0+WC0WhEY4nawhzLIhqNinN/8VgMyJn7g1wOo8kkVv4MBkPNEHYuaxtDJZNoa2/HzWvX4PV40NXVJalnyHIgCAIajSaz6bXZ8lJ02Owc9cTEBGiaFhf8Usxker1eXLhwAR0dHdi7d2/NfNfVAsuyGBkZQTgcxvHjx6tSQZU6OSxnZbAULeKnnnoKjz76KO666y4cOXIETz/9NBKJBB577DEAwCOPPIK2tjZ86UtfAgD84R/+IU6ePIm///u/xwc/+EG88MILuHDhAv73//7fGz6WxaiTwSySyST8fj/MZjPuv/9+SebmVspn0Ol0YmxsDC0tLSu6109MTODFH/8Yo/v3Q9Pdjd7eXszMzEBqPkWV8A6sFSxuFabTadHGJlepzHEcKIpC0wbnKXmeB5lIIJit/EUEyxfhBTIZdAaD2Po1LxP1VgtIp1JYcDohl8vFBKJbt24hlUyuGE8nZeSm6MwvLAAAuru7YTKZ4HQ6MTk5CaVSCYfDgYaGhqLzcnmex8zMDC5fvozBwUHR162OlZFMJjE0NASZTIYTJ05ALRFPT6mRw3KRwVJF0X3kIx+Bz+fDF7/4Rbjdbuzfvx+vvfaaWOGdm5vL2xTdc889OH36ND7/+c/jc5/7HHp7e/GjH/2o5B6DQJ0MguM4seyu1Wpx3333SXYnX+42McMwmJiYgMvlwr59+9DW1rbs68bGxvD9V17B6MGDMHR3o3fnTjHMXiq2lTzPZ3y1gsGqewdKEblKZdhsGcFGIgGf1ytWn/1+vxjBVKhSOZW1fBFm/xZHvSk1mkzlL9v6lcqitl4IMXyLRw8cdju8Lhc8Hk/NkcHlYDAYsGvXLuzatQssyyIUCsHv9+P27dt5kWgCQVxp4WRZFmNjY/D7/bj33nuLNu3diohEInj33XfhcDiwf/9+SY7hCKg2OSxXm7iUUXRPPvnkim3hN998c8nPfuu3fgu/9Vu/VZL3Xg1bmgxGo1GMjIyA53ns3bsXCwsLkiYM5bSWCYVCGB4ehlarxalTp1Z8mA8PD+MHr72G0YMHYdqxA729vXmD5lIgg1LzDqwFUNm5wsVZublxaMslXjAMg0gkIhJAiiTvtH4JAjK5HOas3YvVYoFOr5f0PVYocoU1y/ktCvF0fr8fvT09kpwdLBSLrWXkcrm4kAPLL/g6nS5PgarRaEBRFIaGhiCXy3Hy5EnJzGJLGS6XC8PDw9i5c6f4rK0lVJocSr0yKGVsSTKYm56xfft27N69Gz6fr+oefmuhHJXBXEuHtbI/h4aG8KPXX8fooUOw9vRgx44d4msJggBySGG1IHXvQKmB4zgEAgGEQ6ElNju5Wbksy4rm106nE4lEAjRNZxT4OeQPBAFj1jTbarHAZDJtuu+AoWk4XS6wLLuisKaQeLrNgsULPk3TCAaD8Pl8uH79urjJTKVSsNlsOHjwYJ0IroFc8d5mstoplBw6HA6RIBZKDhmGwdzcXFlIWykrg1LFliODJElidHQUJEmK6RmANHN/F6PUlUGSJDEyMoJUKoX77rtv1XbW22+/jf/71lsYPXgQjp4ebF/GzkBGEGK7uNKoVe/AakKooLIsi47OzmVbtjzP51m+hCORPMsXyGSQq1RQKZUwGI2wWa0wmkxrKpVrFRRJwulyQavVrrrZIAgCjU1NmJ+dhcfrrV0yuA5rGaVSiaamJnEO6vr165ienobVakUqlcJPf/pTmEwmsaVst9slaRNULXAch/HxcXi93jWfy7WOUpHDZDKJd999F0qlEvv27Sv5cdYrg5sIPM/j9u3bmJiYQFtb2xJhxGoJJFJBKSuD8/PzGB8fR3t7O+6+++4VB/d5nsdbb72FV999F6OHDqGptxedKykkCQJcFcjgZvIOrBQS8ThcK1RQ0+l0xvIlGEQ4HEYqlQKRve4Ey5fcuT+NRpMxNU4kQFKUmFIiKJV1ej3UanXNtbhywfM8wuEw/D5fwTOojY2NmJubWxJPt1XAcRwmJibgdDpx7Ngxsa2cSqXg9/vh9/sxOTmJRCIBi8UitgntdntNColKgVQqhfPnz4NhGJw4cWLTE5DFWA85ZBgmb6ZS6jODUsWWuONSqRTGx8cRDAZx6NChZQ0bt0plkKZpXLx4EV6vFwcPHkRLS8uKr+V5Hq+//jpeGxnB2MGDaNm5E52dnSu+nqhwm3greAeWGjzPI+D3IxQKoaGxERaLBSzLIhgMZip/4TDi8TjA85m0D4IAIZfDlG37Wq1W6JexfBGVyot868isUpmQycR5Q10VMpU3Ao5l4fF4kCBJtLW3F7wo6PV6GI1GJLLXaFt7e5mPtPTgARAo3nQ6mUzi/PnzYFkWJ0+ezDtnarUabW1tokCNoiiRHF68eBEURcFqtYrk0GazSVo0USrEYjEMDQ3BZDKtukHfSlhuBEEQL83OzmJ0dBQAxEpzMpksC2mrVwY3AdxuN8bGxmCz2XDq1KkV1YtSyP1dCxutDAYCAYyMjECv169pps3zPH7605/iZxcvYuzAAbTv2rUkgm7J8REEopEIwPNlj7faqt6BG4Ew68YwDOx2O6LRKObm5hCJRMCzbF7rV280Zip/FgvMFktRi3Gub50tq1ROJZNIkCSisRi8Ph8UcnmmcliEUrkayLWN6ersLDpru6mxETciEXhqlAyuB6FQCOfOnYPdbsf+/fvXJDVarRbbtm0Tny8kScLn88Hv92NkZATpdBo2m00kh1arddNt+rxeL86fP4/t27djz549NbNRqjSUSqVIDufn5zE6Ooquri7I5fINzxyuhnplsIbBMAwmJyexsLCAgYEBbNu2bdUbTKgM8jwv2RtxvdVLjuNw9epVXL9+vaD4Ip7n8eqrr+LM5csYP3AAnXv2rGgzk4uGhgbEYrGMNxnPZxZ6vR76EleC6t6BxSMUCuH23BwYlkUqmcT83Fye5YtKoxHJn9VqLWnaiEwmgzarQAYylTYqm4yymlK52ojFYnC7XDBnW5jrISANjY2YmZlBPBqtzQWlyJlBwWpmLTHaatDpdOjs7ERnZyd4nkcikRArhzdv3gTDMHnk0GKx1DQ5vHnzJqamprBv3741N9x1ZNana9eu4dq1azh69KhYNQSWVg5LRQ7ffvttyReLNorqP3HLAKECptPpls3SXQ5C5YNlWUksRMtBSCAphrAmEgkMDw+DYRgcP358TWEFx3H4yU9+gjdmZnBx/35s37t31VZyLowmE4wmU16CQSwWgy+nEqTPRqGt5xzXvQMLB0PTCEciCAWD8AcCGb+/nLk/mUKRF/VWjGnwRiGTy6E3GMRqLsMwGXKYSMAfCCDtdEKj1d4hh+vIVN4IeJ6H3+9HOBRa1jamGKhUKtjsdoR8Png8Hmzfvr2ER1ohFDD6wXEcLl26hLm5uZLGpBEEIUYsdnV1ged5xGIxkRxev34dPM/nWZOYzeaaeC5wHCcWLHLFjHWsDI7jcPHiRbjdbtx3331L1rPcyiFwR9m+HDkUCOJq/IDjOHzmM5/B8PAwvvzlL5f1s1Ub0mQ9G0AoFMLZs2eLDvCuFTIIoCAymCuY2bZtG/oKyAzmOA4//vGP8fPZWUzs24cde/eiaR2B2LkJBja7Pa8SFAwG4XI6oVarxaphIYt93TtwdXAsi2gshnAohFA4jFg0eof8AYBMBoMw92ezwWgwSMbyRaFQwGg0wmg0Ash818K8ocfjAcOy0Gg00Ol00Ot0ZR1BYBhGvM5WUlgXi8bGRoR8vpqJp8uFQANXO+Z0Oo0LFy6AoiicOHFCzMYuBwiCgMlkgslkQnd3tzg3LJDDK1eugCCIPI9Do9EouXNO03TeOZNi4pXUwDAMLly4AJIkceLEiYKKPIuV7bnk8ObNmxgdHc0jhyzLoqurC0BGa/DYY4/h3LlzuHDhAnp6esr58aoOabKeDcBiseCBBx4ouhQsLC5SLgXnEtbVFsN0Oo3x8XEEAgHcddddBe3SWZbFyy+/jF84nZjcvx87+/pKZoeRWwlqQLYSRJJILLfY6/V5GblA3TtwOfA8D5IkM5Yv4TDCQtRbztyfTKWCQa9Ha2srrFZr0fNu1YJSqYTZbIbZbAbP86BXylTO/lcqpTJFUZmNikaDjo6OkokW7HY7ZCoV0skkIuEwLJsodSMajeLcuXMwGo04ceJExWc/CYKAJTve0NPTA47jMqIynw9utxuXLl2CQqHII4f6KhufJxIJDA0NQavV4vjx45Kdl5UScq1jNnLOViOH09PT+NCHPgSHw4EDBw5gZmYGarUa77zzTl4rerNi05FBIpuvup7fk7qIRCCAq80N+v1+DA8Pw2w2ryqYyQXDMHjppZfwS58Pl/btw67+ftEGohxQKBR5LWXBliSRJTcAxPZgKplEPB5HU3NzVYLZpYR0NuotHA4jFA4jnUzemfsjCCizucNKlQo0TaOluRlmi0VyVZFiQBAEVGo1VGp1vlI5kcgolf3+jFI5x8ZGqVQW9Zl5nkckHIbP54PdbofVZivpORMSO7xOJzxeb22RQZ6HbIVOhMvlwsjICHbs2IFdu3ZJ4jqTyWQZ2yOrFTt37gTHceIM2cLCAiYmJqBSqfKi8yo5xxkIBHDu3Dm0t7ejr6+vpmcdK4VoNIp3330XdrsdBw4cKOk5yyWHfX19cLvd+O53v4svfOEL4DgO8Xgcx44dw/333y/+t1nnOjcdGdwIhJk8qWK16iXHcbh8+TJu3LiBvr6+gttRNE3jxRdfxNvhMKYHB7G3vx+2Cs6uEASxxJYkmUwiGo0i4PeD4zgolEokEgkAWPe8YS2CYRhEIxGEwmGEQiEkEolMNBgy7TuZQgGT2SyKPrQaDVxuN2iaxvbt2zdlykOeUhmZ6z6Zjc2LxmLweL1QKhR35lO12lUrohzLwuP1IpFIFGUbUyyaGhvhcbng9/vR09NT01YpPM+Lee4HDhyQdDqGTCaD3W6H3W4Xc5WFStDc3BzGx8fz2oQOh6NsIyhzc3O4ePEi+vr6anN2tArw+/04d+6cmBRW7g2Hy+XCl7/8ZfzGb/wGvvWtb4GiKLz99tt488038Y1vfAOPPfYY/vVf/xUf+9jHynoc1cDWWFULhNQrgwRBLGsvE4vFMDw8DJ7nceLEiYIraOl0Gi+88ALOxuO4MjCAvoEBSQTHp1IpRCORDMmx2ZDKLvbivKFGA322RVhpcUE5wXEcEvF4Juc3HEY0EgHPcRm/PyAz92cywZKtfJhzot5IksTsrVvQabVo7eysabJRDGRCVXAZpXIwGIQrmbyjVM6Kl4Rzk06nM2blBIHOzs6ytuvEeLpkEsEaiqdbPDNI0zRGRkYQjUZx/PjxmqvWy+VyNDQ0oKGhAUBmwxUIBOD3+3Hjxg3RequhoUEkhxudG+V5HtPT05idncWRI0e2RMuxFJifn8fY2BgGBgZW9bctFd566y386q/+Kj71qU/hi1/8IgiCgNFoxPvf/368//3vB5BZa6VQAS8H6mQwB1Ing0D+MfI8j1u3bmFychJdXV3Ys2dPwSQglUrh9OnTGEqlcC1LBKsde7SSd6Bi0bwhSZJIJBJ584aCSnnxvKHUkRv1FgqHxag3gfypNRqR/Fmt1iWEJVdh3dDQUPNt4Y1ipflUkiTh9/uRTqeh0WigVCiQSCRgNJnQ2NhY9nbdZoini8fjOHfuHDQaDU6ePLkpElUUCsWSGbJAIACfz4erV6/iwoULMBqNedF5xXxuhmHyyLMgkqpjZeRax1SKPH//+9/HY489hn/8x3/EE088seLrNvP3VyeDOaiFFBKhMphKpTA2NoZQKFT0DUNRFJ5//nmc4zjM9Pejf3Cw6jv8Qr0DFQqFqCbMFRckspUgAKLqdD3zY+UGTdOZmb9QCKFQCCmKypv7kyuVeZYvWq12xeNnGAZutxvpdLqusF4BufOpQOb8ez0exOJxyGQyRKNRpNPpiiiVm5qaajOeLqvYvXHjBjo6OrB3795NO+umVCrR3NwsplSlUimxcnjp0iXE43GYzeY8a5KVKsoURWFoaAgKhQInTpyone+7iljLOqYc+Md//Ed8/vOfx/e+9z188IMfLPv7SRV1MpiDWqkMBgIBDA0NwWq1FiwSEUCSJJ599lmck8txq68PAwMDG/JR2yg24h24nLggmUwikUjkzY+JFjZVmDfkWBbRaFSc+4vHYkDO3B/kchhNJrHyZ1gm6m05kFnyrNVo0LmF2sIbAcMw8Hg8SKfT6MpmWOduJkKhkGiWLswcqkpolq7T6Wounk6Il7x27RpOnjy5aYfnV4JarUZra6s4F5lMJvNylUmSzMtVttlsUCgUCIVCGBoaQlNTE/bt27dpyXMpsR7rmI2A4zj86Z/+Kb7zne/g9ddfx+HDh8v6flJHnQzmQOpkkGVZ0DSN6elpcY6imIUqHo/j2WefxXm1GnO7d2NwcLCqMW6l9g7M9TcE7syPJbL5uKkKzBvyPA8ykUAwW/mLRiLgFkW96QyGO3N/ZnNRBJXneQSDQQQDATgaGmDZ4m3hQiHaxqjVeeR5uc2E0FbOUypn/9todaeW4uk4lgWdTgMA9u7du+WI4HLQaDRob29He/a7oyhKjM4bGxtDMpmEXq9HIpFAZ2dnXTFcIEplHVMoUqkUPv7xj+PChQs4e/YsduzYUdb3qwXUyWAOpEwGo9EohoeHwXEc+vv7RWPMYn7/2WefxXmdDvMCEayi0WksFoPH4ymrd+CSpAuaBklRSCQScHs8YLPzhga9HtoNzBumspYvwuwfnU7nRb0p1epM5W+DUW9iWziVqreFi0A4HIbP64XNbodtFduYPLN0LFIqRyLweDxipVkgh8VWmmslno6maSwsLIgCknIaSdcytFotOjo60NHRAY7jMDU1hdnZWdhsNrhcLszNzYnReQ3ZzVudHOajnNYxyyEcDuPXfu3XQJIk3nnnHVFMtNVRJ4M5kCIZ5Hkes7OzmJqaQnd3N3w+X9HViUgkgu985zu4YLHAvXMn9g0OVm0R4lgWPp8P0Wi04t6BCqUSJqUyb94wQZIgEwkEAgGAIMSqoS7bIlwODMOIRs+hUAgUSd5p/RIEZHI5zFniZ7VYoCuBya3QFtZoNOjMBrPXsTo4loXX50M8HkdrW1vRm588pbLDkVdpzk3SEVrKWq12ze9FjKfz+yUbT0eSJJxOJwwGA1RKJWQFxNFtdbAsi7GxMQQCAZw4cUI0TI/H42Jb+caNG2BZNi86b6tX9ittHTM/P4+HHnoInZ2d+MlPflJPfslBnQzmQGpkMJVKYXR0FJFIBHfffTccDgfefvvtokQuoVAoQwQdDnh7ezE4OFi1ilI6lcpYechk6MzObFULufOGVqs1I8pJJpFY5FcnVIFYYfYvFEI0GgVYViR/IAgYsykIVosFphzLl42C53mEgkEEAoF6HnMRECpbpbSNWTZTOdtS9nq9oGk6o2zPzhxqNZplr4MmCcfThUMh+Hy+TBXLaoVzYQHA6nF0Wx2pVArnzp0Dx3E4ceKE6O8pWJMYjUZs374dPM8jGo2K5PDq1asAkOdxaDKZtsy5rrR1zNTUFN7//vfjoYcewje/+c0t41dbKOpnIwdSIoMejwejo6Ow2+04deqUSJyKMcb2+/145plncKG5GYGeHuwbHKyKEbGQH+rLpi/Y7XbJtUpkMllmAdfpxLk/r88H58ICEiQJftHcn0avFxW/FoulLDMu9bbw+pCIx+Fyu2E0GNDQ0FA2H8rllMpkttIcdrnAcRy0Wq1YXRTGEGwSjKfjOA5erxfxeLys5tubDdFoVBTzHThwYNXKMEEQYszijh07wPM8wuEw/H4/vF4vpqenxbQa4T+DwbDpyGGudczhw4cLikvdKH7+85/j4Ycfxqc//Wl84Qtf2HTntBSok8EcSIEMsiyLqakp3L59GwMDA9i2bVvehbuc6fRy8Hq9eOaZZ3C+vR2RHTuwf3Bw3bNqG8FK3oFSQzqdzrR9g0GEHUuktQAAhAxJREFUw2GkUikQ2fMsWL4YDIZMDi4AQiaDRquFXCYDwzBQKBQlfcAIVjtqtRodnZ31XWwByFWmNzY1VcSWIhfLZSonspXDYDAoKpV1ej1sNhv8brck4ukYmobT6QTH88tXUVeIo9vq8Hg8uHDhwrrj+AiCEF0Eent7wXFcZr7V54PT6cTk5CSUSmWeAbZOp6vp74LjOExMTMDlcuHee++tiLftiy++iMcffxz/9E//hMcff7zs71erqK8wOZDJZEhn1XPVQCQSwfDwMBQKBe6///5l5xkKIaxutzsjFunoQLynB/sGBqrSki3UO7AaYFkWkUgE4WzWbzwezyx6PA+eIEDI5TBl275WqxX6HMuX5eYNCZlMTLnQZ/0N14N6W3h9YFkWLpcL6VQK2zo6qh7Ft3gMIVepHI/HwbIseIKAz+tFQ0MDjEZj2RWUy4GiKDidTui0WjQ1NW2aNJ9ygud53LhxA9PT09i/f7+oLN4oZDIZbDYbbDabGJ0n5Crfvn0b4+Pj0Gg0ebnKtdQtqLR1DAA8/fTT+OIXv4jvf//7eOihh8r+frUM6azOEkC1KoO5D5eenh7s3LlzxTbqWpXBhYUFPPPccxju7gbV3Y3BwcGKLzIb8Q4s5zHFs1Fv4XAYkUhkSetXbzRmWr8WC8wWy4otn1XnDaPRjOpUqbxjYVOg6pRhGHjcbqRSKbS3t0Nbb9UVhGQyCafTCZVKJdkqap5S2W5HW2srzp0/DzqZhMfths/ng1KpFM2vK+GJGYlE4PV4YLfbYV1BZb04jm6rI7eydc8998Bms5XtvXJbxkDm+SDkKs/OzmJsbAw6nS6vrVztTdBKqLR1DMdx+OM//mM899xzeP3113HXXXeV9f02A6T31KwiqpFAkkwmMTIygkQigWPHjsFut6/6+tUI69zcHJ47fRrDvb1IdXdjsL8figoTwVJ7B24EFEVlVL9ZAphn+UIQUGk04tyf1WJZdxs9d94QyFSpqKyFjT8QQNrphCZndmw5YUGuD55UCY0UIRAaq80Gu91eM6RFJpejKRtPx3Icdu7aJWYqi56YarUoYCpEqVwoOI6D3+9HJBKR9OiG1JBOp3H+/Hmk0+mKVbZyoVAo0NjYKKZN0TSNYDAIn8+H69evY3h4GIbsnKxADqWQehKLxXD27NmKWcekUik8+uijGB4exjvvvFP3ECwQ9RUnB5WuDLpcLoyNjaGxsRGHDx8uaLe0UmVwdnYWz5w+jdHdu8F2d2Ogv7/ihKIS3oGrgaFphCMRhIJBhMJhJCkqb+5PplDkRb2Va/5GLpfDYDCI3mwMTYuzY263GxzLQqPVihUgKksAVqvQ1JEP0aIoFqtZQpMbT8eybP41k1UqJ3KUylqNRpw51KjV67q/GIYRN2udHR1rboB4noesPjOIeDyOd999FwaDAffdd19VWvqLoVQq83KV0+m0GJ13+fJlxGIxmEymvFzlSh93pa1j6h6C60edDOagUmSQYRhMTU1hfn4e+/btK2rmRJYVLORiZmYGz73wAkb6+oDubvT39VXUh65a3oEcyyIaiyEcCiEUDiMWjd4hfwAgk92xfLHZYDQYqjITpVgkLEin00gkEiBJEj6/PyMs0Oshk8vBMIwkFhopg84KHnieR1dXV82er9Xi6ZZTKicSCVBZD0Ce4/I2FIUYpqdSKSzMz2eqzx0dda/KAiEQmo6ODvT19UmWGKtUKrS0tKClpQVA5vvOjc5LJBJ50Xl2u72sBYNKW8cIHoJdXV11D8F1oE4Gc1AJMhgOhzE8PAyVSoVTp04V3WqQy+V5IperV6/i9EsvYaS/H/IdO7B3z56KEp5UKgVXhbwDeZ4Hmc2QFUyfOYZZYvkiRL1ZzOaKt8nXAkEQUKvVGeVgKAR91qKGSibvpFzkzBvq9Pr6op2DRCIBl8sFvV6PpsbGmhc8FBpPp1QqYclubIQNBbnIMF0YQ9DrdFAuylSORaNwu93Ft9Oz95ZUCVC5cevWLUxMTFSM0JQSarUabW1taGtrA5AZRRHI4cWLF0FRFKxWa16ucimeNTzP4/r167h69WrFrGMmJyfx0EMP1T0EN4D6GctBOcmgcINcuXIFvb292Llz57oesLlt4unpaXz35ZcxMjgIVXc39uzeXbHFked5RLI2COX0Dkxno97C4TBC4TDSyWTe3J9SpRK9/qxWq2QHqAWI3mI+X15bWG8wAA7H0nnDbOqIfoPtwVpHrsq6obGxIpYUlUBuPF0ikSiomiFsKNS5AqZUCmRWqezz+SCXy6HTaqHV6ZBKpRCNRNDc3CxWGovCFkwg4XkeU1NTmJubEw3/ax1arRbbtm0TM6ZJkhRzlUdGRpBOp8XoPEdW+FfsM70a1jGCh+BTTz2Fz3/+8xXbuLz11lv4yle+guHhYbhcLvzwhz/Eww8/vOrvvPnmm3jqqacwNTWFbdu24fOf/zw+/vGPV+R410KdDOagXGSQoiiMjIyAoqgNK9CEY5yYmMCLP/4xRvfvh2bHDuzaubNiJIFhGHg9nrJ4BzIMg2gkglA26i2RSIAQot4AyBQKmMxmWCwW2Gw26EsQ9VYpsCwLt9uNZDK5orHv4nnDXCNjoT2o1elEGxu1Wl0zn3+9EM5bKpmsuiip1BDj6Xw+eL3edcXTyWQyUalst9szsXnJJBKJBHw+HziWhVKpBEmSAFCUUnkrqolpmsbIyAhisRhOnDixaXOZdTodOjs70dnZCZ7nMxvQbOXw5s2bYBgmL1fZbDavSg6rYR3zve99D0888QS+9rWv4bHHHiv7++UikUhg3759ePzxx/Hrv/7ra77+5s2b+OAHP4hPfOITeP7553HmzBn87u/+LlpaWvDggw9W4IhXR50M5qAcZNDpdGJsbAwtLS04cuTIhuebZDIZbt++jZHLlzF68CAM3d3oXcWKptQotXcgx3FIxOMIZqt/0UgEPMdl/P4AQCaDwWQSW7/mEka9VRKCWlilVqOzCLXwYiPj3HlDwd9QmBvbiL+hVJFKpbCwsCBp25iNotTxdDK5HEqFAolEAhqNBk1NTeJ1IyqVs2IUfVapXIv3VDlAkiSGhoagUqlw4sQJSahxKwGCIMRNaFdXF3ieRywWE8nh9evXwfN8Xq6y2WwWr9VKW8cAwFe/+lX8+Z//edU8BIW2dKH49re/je3bt+Pv//7vAQB79uzBL3/5S/zDP/xDnQxKDaUkgzRNY3JyEi6XC/v370dra2tJ/u61a9cwnCWCph070NvbW5Fdeym9AymSRChr+RIKh8HSdB75U2s0sFitsFmtsFitNU1wctvpNrsdtg2ohXPbgzabDRzHIZlMgiRJcd5QpVKJVUOdTlfT84bRaBQetxtWqxV2h2PTVqfsJY6nS8TjcLpcMJvNcDgckMlkUKlUeep2Mmtj4/F4QDNMRqmcvWY0Gs2dzSXPZxJ3Num5z0UwGMS5c+fQ0tKCgYEByUVmVhIEQcBkMsFkMqG7u1uMFBXI4ZUrV0AQBBwOB4xGI27dugWHw4GDBw+W/bxxHIf/8T/+B55//vma8hA8e/Ys3vOe9+T97MEHH8SnPvWp6hzQItTJYA6Kyf1dDcFgECMjI9BqtTh16lTJ2lrvvvsu3hgexuihQ7D29GDHjh0VeUhv1DuQpunMzF8ohFAohBRF5c39ybPD8YLli1ar3RSLT24UXznyXmUymSgaEOYNhZay3+9HOp3OnzfMXeQlDI7jRHV6S2vrpm3TCZBlzYW9Tic8Hs+6yWDuXOVqcXwKpRImpVJU/YtiFJJEOBzOG0Xgtsi8oKB83bNnD7q7uzfF86eUIAhCFDD19PSA4zhEIhHcunUL165dAwD4fD6MjIyIlcNyjPCkUik88sgjGB0dxdmzZ9Hd3V3Sv19OuN3uJWKapqYmRKNRUBRV9fGXOhnMgWA6za/TV4vneVy9ehXXrl3Drl270NPTU7Kb4e2338b/festjBw8CLndDpVSiWAwKO7ky/XwisVicLvdMBgMBXsHciyLaDQqzv3FYzEgZ+4PcjlMOa1fQ07U22YBRVFwuVxQKpUVi+KTy+UwGo0wGo0AVpk3zLaUVYsUp1IATdNwOZ3gOA6dnZ1bpk3X1NQEj8sFfyCAHpYtuqLLsSzcHg8oiip6w6ZSqaBSqfKUyoKNjWBjNT09DY7j4HA4YDAYJHfdrBc8z+PKlSuYmZmpmPJ1M0AmkyGRSGB+fh6Dg4Po6OgQo/MWFhYwMTEBlUqVF5230c1wOBzGww8/jGQyibfffrvuIVhi1MlgDoQHMMuyRS/eJElieHgY6XQa9913X8lUVDzP46233sKr776L0UOH0NTbi9bWVpBZQ9qgkIubs8iXoq1ajHcgz/MgEwkEs5W/aCQCblHUm85guDP3ZzZvytkvIL8tXO1UjFXnDf1+cd5QaA9Wux1PZj30NottTDEwm81QazRIJ5OZyl42ZaIQ0DSNhYUFyAgCnR0dG7JTyh1FgM2GBacTBMfBaDTC6XRicnISKpVKTLmotXzcXLAsi9HRUYRCIRw/frxi/qi1jpWsY+x2O+x2u5irLETnzc3NYXx8HFqtNi86r5jr5vbt23jooYfQ3d2NV199teLpL6VAc3MzPB5P3s88Hg9MJpMk7qHNuSKvEwIZLDaSbn5+HuPj42hvb0dfX1/JiA7P83j99dfx2sgIxg4eRMvOnaLXlUqthmVRLm4kd25Mp4NBr1/XcHgh3oGprOVLKBRCOBTKj3qTyaDM2l5Ys5Yv6416qyWwLAuPxwOSJMvSFt4IVpw3TCQQDofhdrurNm+YZxvT0ACzxbJpKk+FgiAINGbj6bxeb8FkUCDQRoMBDY2NZauwd3R0YNu2beIi7/P5cPPmTYyOjsJgMIjEUCoRaGshmUxiaGgIMpkMJ06cyJDfOtZEodYxcrkcDQ0NYvWOYRgxHeXGjRsYGRmBXq/Pi85b6TuYmJjAQw89hA996EP4+te/XrOFhGPHjuHVV1/N+9nPfvYzHDt2rEpHlI/aPKtlQm5lsBDQNI2LFy/C6/Xi4MGDovN7KcDzPH7605/iZxcvYuzAAWzbvXvZpJLcXFyHMDeWrf54PB4wLJuZG8sZDl9poV3NO5BhGNHoORQKgSLJO61fgoBMLoc5S/ysFgt0NWT5Ugokk0k4nU4oFAp0dXZKzux6MXLnDR1A3ryhz+e7E3+2nKighBDmKqlkEu3t7WK+81ZEbjxdOpVadQOVe682NDRsWHRSKBYv8jRNi6ICIQLNbDaLr7HZbJJbvCORCIaGhmC327F///6aFllVEhuxjlEoFHnReTRNIxAIwOfz4erVq7hw4QKMRiNkMhlu3LiBD37wg2hqasIbb7yBX/u1X8Mf//Ef43Of+5yk1pR4PI7r16+L///mzZsYGxuDzWZDR0cHPvvZz2JhYQHPPPMMAOATn/gEvv71r+NP/uRP8Pjjj+P111/Hiy++iFdeeaVaHyEP0rpLqwyCIAoWkQQCATEY/NSpUyU1O+Z5Hq+++irOXL6M8QMH0Llnj+givxbkcnlejFU6nQaZSCCRSOS1lPWLWoN53oFtbdBqtYjFYiL5i0ajAMvemfvLjXqzWGCqUcuXjUJKbeGNYLl5Q6GlnCcqKOG8YTqVwoLTCblcXpTdzmaFTqeDyWRCPByG1+dbMaaS4zh4vV7E4/GqV6CVSmVeBFoymYTf74fP58PY2BiSySRsNptYAVqPkXEp4XK5MDIygt7e3oo5MWwGlNo6RqlUorm5Gc3NzQAynaZAIIAzZ87gL/7iL/B7v/d7aGxshN/vx5NPPolPfvKTkvuuLly4gFOnTon//6mnngIAPProo/i3f/s3uFwuzM3Nif++fft2vPLKK/j0pz+Nf/zHf0R7ezv++Z//WRK2MgBA8PwWkYsViFdffRX33nvviko8juPEgeNyKM84jsNPfvITvDEzg4uDg9i+d2/JKo65ViSJRAJJioIq2zpMJBKQy+VQKpWIRiIIRyKi5QuQaf1qtFpR8WuxWKo+Y1ZtcNm2cIIk0dLSsmmzMHmezyRcJBIgKQoUSW543lCIRytnek0tYmFhATeuXoXeZMLBQ4eW/DuTzWXmeB5tbW1lvweHhobQ/8tf4qmPfKSoDHXgTnykkHLh8/nAsizsdrtYOTSZTBWzxhISoA4ePFgyq6+tgFgshrNnz1a0kvpnf/Zn+Pu//3ucOnUK165dw+zsLO666y6cOnUKDzzwAI4fPy75tKlaw9beii+D1bwGE4kEhoeHwTAMjh8/viJhXC84jsOPfvQjvDU3h4l9+7Bj7140ZXdOpUBea9DhAEVRmLt1Cz6fD+l0OiP6yM5L8gQBRVZhmGv5UkcGqVQKzmxVqxbawhsBQRDQaDTQaDSwIUOCk1lyGA6H4c6akAtVQ61Wu+KCwXEc/H4/IuEwmltaxEpkHRk0NjZi5vp1xOPxJfF0FEXB6XRCp9WiqampYpX49VI1giCg1+uh1+tFI+NoNCoSw8uXL0OetdURKoflsCPhOA7j4+Pwer249957Ya1QS30zwO/349y5c9i+fTt2795dduLOcRz+6I/+CKdPn8bbb7+NQ9kN0dzcHN544w288cYbeOKJJ/Dqq6+iv7+/rMey1VAng4uwHBnkeR63b9/GxMQEOjo6sHfv3pLvjliWxcsvv4xfOJ2Y3LcPO/v60FCEorDQ94hEIgiHQgiGQiATiby5P0Iuh85gECPOVCoVDHo9dHr9lm/hCRDMV31eb023hTcCmVyeN2/IMAyorE+d1+tdcd6QoWk4XS6wLJuxjakP7S+BUqlcNp4uEonA6/Hk5VlXBNnOQCnejyAIUd2+Y8cOcByHcHbEQrAjUavVeeRwoxvQdDqNc+fOgWEYnDhxor6hLQKC92J/fz+6urrK/n7JZBKPPvrosh6CHR0dePTRR/Hoo4+i3swsD+or/CIsJoPpdBrj4+MIBAK46667yuJDxTAMXnrpJfzS58Olffuwq7+/JMHoPM8jHo+Lit9INAqeYe7s9GUy6IzGTNKHxQKzxZKnqM5Tm2arP3q9fstGWOW2hUudyVzLUCgUeXOqy80bqtVqpFIpaHU6tLW11Yf2V0FuPF1nRwf8gQAikcimu+ZkMhlsNhtsNht27doFhmFEpbKgODUYDHmK02KUyrFYDENDQzCZTLj77rvrG9oCsZJ1TDkRCoXw8MMPI5VK4Z133ll1/dtqm+9KoX53LEKugMTv92N4eBhmsxmnTp0qi/0ATdN48cUX8XY4jOnBQezt74fNbl/336MoKqP6zUa9MbmWLwQBuUoFlVKJxqYmtDQ3r1idWaw2Fao/iRyVslarFefGhGriZkVuW7izs3PLz0uuBmU2UcZisYDjOAT8fgRDIahUKpAkidnZ2Tu+mDrdpm6xrwe58XQzMzNQKJXo7OioWiWV4LiK3NsKhQKNjY2irU46nRYVp9PT04jH47BYLGLlcDWlstfrxYULF9DV1YU9e/Zs6mdTKVGodUwpcfv2bbz//e9HT08Pvvvd70rKkmsroU4GF0GhUICmaUxNTeHmzZvo6+vbUHh8IpFANBqFXC6HxWLJ29mm02l897vfxbuJBK4MDKBvYKDoeRYmN+otHEaSovLm/mQKBSwWC4xGo2hX0dLSUrQXWG71h+d50Ok0ElkrkkBWpSwQw822wAstOqvVCltd7FAwciup27Ztg06nA8eyoLIipmLnDbcKZHI5bDYb/G434okEBgcHt+Q5UalUeUpliqLylMqpVAo2m00khxaLBTKZDDdv3sTU1JSYjFFHYdiIdcx6cfHiRTz00EP4L//lv+BrX/tavXpbRdTP/CJwHIerV69CqVTixIkT63KlFwaWXzvzOkiGh8FiAc9xiAb86GhpwgcffB8aGxtx+vRpvJtK4XqWCBayC+NYFtFYTKz8xaLRO+QPuGP5kk37MBoMiEajy3oHrhcEQUClVkOVNZZerqWszraUdTXcUuZYFh6vF4lEYtO16MqNXNuYXIGNTC4XRQXACvOGWq1YNVTXSJ5yKRGLRsGxLHiCQCKRqOqxCNNZUqisabVabNu2Ddu2bQPP80hkM7iFtjLHcVAqlUin0xgcHMS2bduqfcg1g1JbxxQCwUPwT/7kT/DZz35WEtfYVkadDGbB8zxu3bqFUCgEm82GY8eOrWs3TlEU/uFr34CuuQ13f/g3YTDmk0mPcwH/6/SLCM3fQrq/Dzf6+9E/OLgi6RSi3kJZw+dwKLQk6k2j14vkz2I2iwsvwzBwu92id2C5rE9WainHE4mabSkv9sCrt4ULRywWg9vlgjnb0luNzC2eNxR8MXPnDXU5FWelBPOUSwWe5xHw+xEKhdDR0YF4IoE0RRUdT1dqSPFsEwQBg8EAg8GArq4upNNpvPvuuyBJEhaLBRcvXsTU1FRebJ5Op9u0185GEIvF8O6778Jms1XMOuaFF17AE088gW984xv4+Mc/Xvb3q2Nt1MkgMvNgY2NjCIVCsNvtcDgc67ohaJrG3/3jP6Hv+HuwbXv3sq+xNzVj77ETOPOLNzEeDuO+wUFxIRSQzka9hcNhhMJhpJPJvLk/pUolev1ZrdZl/ZZIkhRbcF1dXRUtvy/XUo4Lmbg10FIW2sJ1D7ziwHEcAoEAwqEQmpubl1zXhUClUkGVvb55nkcymcxsLOJx+Hw+yHOUzFK8dtYLlmXhdrmQSqfR0dkJtVqNxsbGouPpSg2+hGriciGRSGBoaAharRa/8iu/AqVSCY7jEAqF4Pf7MT8/j4sXL0Kj0Yj+hg6Ho+5Th8pbx/A8j69+9av4i7/4C7z88suSMVyuo04G4fV6MTIyApvNhgceeACXLl0qOptYwGv/8VO07tm3IhFkGAY3bt5EQCZD74cfRuSVHwHxOBidDtFIBKHs7F8ikcgMbSPTppEpFDCZzbBYLLDZbKt6cfE8j0AggFAwCHvW8b+aD3KhpWxblImbkGBLud4WXj8YhoHT6SypbQxBENBqtdBqtbDZ7XfmDRMJhEIh8drR1bjCXahCKxQKdHR0iBu3YuLptioCgQDOnTuHtrY29Pf3ixs3mUwGu90Ou92+RKl8/fp1DA8Pw2g05imVt1r1v9LWMSzL4o/+6I/wwgsv4I033hA9BOuQBrYsGWRZFtPT05idncXAwAA6OjpAEMSqptOrged5vHNhBL/6xP9v2X+naRo3bt5EUKEAaTLBYDSi79hx/PRf/xWq48czfn88L879GUwmsfVrLjDqjaZpuFwuMAyD9m3bJOmpldtSBvJbym6PByzLZv5dq4XeYChJ7FkhENvCMlm9LVwkBDNkrUZTVtuY3HnDBixVuNMMU3Pzhol4HE6XCxazGfZFLfVC4+nKCglXBm/fvo3x8XH09fWJfowrYTmlsjBveOnSJSQSiSWZyptVtFMN65hkMomPfexjuHjxIs6ePbvm91VH5bElyWA0GsXw8DAIgsD9998PQ04FSC6Xg6bpov/m9PQ0Gru6l32AJFMpzN68iaBajYTBAPA8opEI1GYL4PKCo2los3N/NqsVFqu1+HivWAxutxsGgwHtbW01UyEpqKWcJQA6na4s7e5oNAqP2w2LxbJkQa5jZeTmMlfcDBmrzxuGQiGA5yU7b8jzPELBYGYesKlpxTSjxsbGDBn0eKpDBgFRoCYV8DyP6elp3Lx5E0eOHFlXC12lUqG1tVWMpaMoSozNGxkZQTqdzstUFpTKtY5qWMeEQiH86q/+KhiGwdtvv10SD906So8tRQZ5nsfNmzdx6dIldHd3Y/fu3UtucLlcjmQyWfTfXnC64GhpW/LzYCiE+fl5xAwGkDodwHEAQYjt07aOTjTt2gVrW9u6FiqOZeHz+RCNRtHU3Lwu9bNUsKSlnGNDEgwG4XI6odZoxHlDrUazIdLLsSy8Ph9isRhaWlvzNgV1rI7clnpbe7skvMGWmzckSRKxWAw+nw8KuRzarIVNuTYWhYBjWbg9HlAUtWYFf7V4ukpCKiSaYRiMjIwgGo3ixIkTJYsz1Gq16OjoQEdHh6hU9vl8YluZ53mxndzQ0ACj0SiZc1IoqmEdMzc3h4ceegi9vb04ffq0JJ4TdSyPLUMGk8kkxsbGEI1Gcffdd6+4O1lvm5jjOMiIpdW8dCoFAFDSNDTJJGiVCqxCIS5cKo1m3eraVCoFl9MJQiZDZ1dX0d6BUkdeW7ChAQzDgCRJJBIJuN1ucCwLrSAm0OuLaimnsybShEyGrq6uelu4CKTTaTgXFiCTcEs9d97QLswbUlT+xqIK84Y0TWNhYQEygkBnR8eaAhilUgm73Y6gzwePx5MX0bXVQFEUhoaGoFAocOLEibI973KVytu3b78TQZmNCJyenoZCoViSqSxlJJNJ8dxVyjpG8BD81V/9VXzta1/btG33zYItQQY9Hg9GR0dht9tx//33r/oQyU0gKQZ2mxUzN+aX/Ly5uRkgCMhkMiQpCvFQCEkAabUaKZUK8zMz8F6+DEc4DJvNBrPZvGbFIrc9t5UUrwqFAiaTCaZsSzmdTouxZwG/X8zMXavyE4tG4a63hdeFeDwOl8sFk8mEhoaGmjl3MrkceoMBeoNh2XlDhmWh0WjE60ej0ZS88kOSJJxOJ4wGAxoaGws+d41NTQj6fPBls4orWZHikbGWqXYVLBwOY2hoCI2Njdi3b19FrzuCIMREnd7eXlGp7PP5MDc3h/HxcWi12jwbm3KkVa0X1bCOef311/Hrv/7rdQ/BGsKmJoMsy2Jqagq3b9/GwMAAtm3btuZFud7K4ODgIF565d9x170nlrxHc86ALo/MDjcei8HlcsLqvI3OkREE7XbM2mwgDQaYzOZM2sUyymGGYeD1eMruHSh1EAQBtVoN9eKWciKR31IWVMpZGwmfz4dovS1cNHJV6rU+jgAsP6tKZslhKBQCAFGIotvgvGHu5q2hoQGWIlOG7DabGE8XCYeL/v1ah9PpxMjICHbt2oWenp6qE4tcpfLu3bvBMIwYmycolU0mk0gM7XZ71arnlbaOAYDTp0/j937v9/DNb34Tjz76aNnfr47SYNOSwUgkguHhYSgUCtx///0Fk6b1kkGVSoU93d24ffMGOrp3rPg6AoBOq4VOq8Xl4SH8+ec+C41Gg5mZGcxcuwZPPI6A3Y6A3Y4FqxXQ6WC12WC1WKDRahHw+6viHSh1LKc0FVrKLpcLXNaqRy6Xo7WlBbotSqLXA8G8PJ3jgbeZkJuos3jeMBqLwbuBeUNhLjUej697tlIml6OhoQGehQV4sv6XlUI1fQZ5nse1a9dw9epVHDp0SIylkxoUCgWamppEVW4qlRLJ4eTkpGiELVQOK6VUrrR1DM/z+Lu/+zv85V/+JX74wx/ife97X9nfs47SYdOyCZqm0draip07dxbVUpDL5ev2GXz4v3wIf/33T8P23z4OwxqVk5kr0+BjIezfvx8EQWDPnj3geR7BYBDXr1/HjRs3cPPcOQTUagRsNrhtNkTNZqh1OjgcDsRjMZgKtJzZishtKQtqYXW29Scki+h0Ohj0emirKCaQOiiKEufrOjs7t8TcT0HzhoKQaZV5Q4amseB0AsCGZyubmprgdjrh8/vRw7IV/R6qoSZmWRZjY2Pw+/04fvz4imprKUKtVi+rVPb5fBgeHgZN02K4gZCpXEqyXQ3rGJZl8elPfxrf//738eabb+LgwYNlf886SotNuwIKyq9iIZfLwTDMut7TbDbjDz/xe/in//V/cNd7PoCO7h1LbnKGYXDx/LsI3riKP/rDT+b9O0EQYvvh6NGjYBgG169fx7vvvgv/tWuIUBRCVisCdjuuWa1IGQxiConNaoW2rtTKg6i0jsXQ3NIiKg9zF/dAIIBUTktZmBerlVm4ciIcDsPn9VbFNkZKWG7eUKg6584bClVDjUaDZDIJp9MJnVaLpqamDW/aTCYT1Fot0hQFv99fkQU+F5X87lOpFM6dOweO43Dy5MmaTwpZrFQW0nT8fn+eUlmoHG5EqVwN65hkMomPfvSjmJycxNmzZytShczFN77xDXzlK1+B2+3Gvn378LWvfQ1HjhxZ8fVPP/00vvWtb2Fubg4OhwO/+Zu/iS996Us1f51tFJuWDK4XG6kMAkBrays++9Sn8H9f/Xe8fObf0b6rHyarFSzDIOBaQMh5G/ffewy/+9Sn1tzdCwHs+/btw8DAAJLJZKadPDODmYkJ+DkOfrsdIZsNs2YzlEYjrBYLrDYbLBbLlq52pdPpjFqYIDKJGDmioSWLO00jQZIgEwk4nU7wHCeqlA16vaT86SqB3NbmVp5LXQmLhUy584bBQABAZlE2GI2w2+0gSrCxIAgCTY2NuJ2Np6s0GawUotEohoaGYLFYcPDgwU1XiSYIAkajEUajEd3d3eB5HuFwGH6/H263G5cuXYJCoViSqVwIqmEdEwwG8fDDD4segna7vezvmYvvfe97eOqpp/Dtb38bR48exdNPP40HH3wQV65cWdZ/8vTp0/jMZz6Df/mXf8E999yDq1ev4uMf/zgIgsBXv/rVih671EDwwlBIHQAy1ZCzZ8/ioYce2vDfomkaU1NTCIZCUCoUaGlpwY4dS6uFi5ErfNm3b9+yZrM8z8Ptdost5dm5OYSMRvjtdoStVsSzw/FC1dBQg75Y64WgFjaZzWhwOIqqyogq5XgcCZIERVHivNhWaCkL1icEQaC1tVWStjFSBcdx8Hm9iEajMBiNoGkaFEVBqVDcsbDZwPVDkiTOnz8PAsDdd99dkXi6t99+G0feegt//Pu/X/aF3uPx4MKFC9ixYwd27dq1ZZ5XuWBZVlQq+/1+hEIh6LKjQQJBXG5mN9c65vDhwxWxGZubm8P73/9+7Nq1C6dPn65K4tXRo0dx+PBhfP3rXweQuQe3bduGT37yk/jMZz6z5PVPPvkkpqencebMGfFnf/RHf4ShoSH88pe/rNhxSxGbd1VbJ9YrIFkOSqUS+/fvL+p3hHQUuVy+qvCFIAi0tLSgpaUFx48fRyqVwuzsrFg5dEejohBlymIBn004EcjhZsw55VgWPr8f0UgEzc3NYjJFMchTKS+aFxNayhqtVjS+3kwtZSEazZTNbK3PoxaOvGzmHM9P4fpJLB5JWGPecDlUI56uEgISnudx48YNTE9PY//+/VVLWpEC5HJ53ogTTdMIBALw+/24evUqLly4INo6ORwO2O12JJPJilvHjI+P4wMf+AAefvhh/NM//VNVKrjpdBrDw8P47Gc/K/5MJpPhPe95D86ePbvs79xzzz147rnncO7cORw5cgQ3btzAq6++io997GOVOmzJok4GF0EggzzPV9bPi+dx69YtTE5OrpiOshrUajV27dqFXbt2AchEAF2/fh0zMzO4eeECAgoF/A4HvDYbrplM0JlMYku50OxjKSOdTsPlcoHn+ZIacBfSUpZq5FmhyLWNWS0arY7lkUwm4VxYgHqZbObc6wfIXD8kRWWM07NZ3BqNRqw6r+VvWI14unJezbkzbvfccw9sNlsZ3632oFQq0dzcnPGrRWaeUshUFpTKAGC1WtHR0VGRYzpz5gx+/dd/HZ/5zGfwmc98pmrPO7/fD5Zll4xMNDU14fLly8v+zn/7b/8Nfr8f9913H3ieB8Mw+MQnPoHPfe5zlThkSaNOBhdBeJALeauV2PGk02mMjY0hGAzi6NGjaGho2PDftFqtOHz4MA4fPgyWZTE/Py+Sw/mxMQRtNgTsdsxYrUgaDDALQhSbDVqttqYITSwahdvjqUhFS6FUwmw2w2w2g+d5pFIpkImEOBSukMtL0hKsFETbmFQK2zo6tvwQdbEQRhKsNltmPnCN+0ahVMKkVObNGwqbi0AgABCEWDXUZVN1cpEXTxePiySzbChjZTCdTuP8+fNIp9MVm3GrdajVarS1taGtrQ0LCwsYGRkRVcvDw8NgGGZJpnIpv7vnn38ev//7v49vfetbeOSRR0r2dyuFN998E3/913+Nb37zmzh69CiuX7+OP/zDP8Rf/uVf4gtf+EK1D6+qkPZKVQWoVCp0dXVhdHQUNE3D4XCgsbERjY2NSwygS4FAICCalJ46daosHm5yuRydnZ3o7OzEr/zKryCRSODGjRuZlvKlS/Cl0wg4HAjabJizWCDX6zPehlYrrBbLmpFZ1QLHcRm18AbawhsBQRDQaDTQaDR5LeUEScIfCCAt8ZayUNFSqdXo6OyUPHGVEnieRyA705WrVC8Guf6GVqsVHMchlUwikfU39Hi9S+YN8+LpvF5016hxejwex9DQEPR6Pe677776bGoRyLWOOXLkiFgZ43kesVhMrBxevXoVBEHkZSobDIZ1rWE8z+MrX/kK/uqv/koyHoIOhwNyuRwejyfv5x6PR6ykLsYXvvAFfOxjH8Pv/u7vAgAGBgaQSCTw+7//+/izP/szST2fK436038RCILAvn37MDg4iFgsBq/XC7fbjampKWg0GpEYOhyODT3AeJ7H1atXce3aNezZswfd3d0Vq8bp9XoMDAxgYGAAPM/D6/WKVcPZ6WkE9XoE7XbM22y4bDRmhChZcmgwGCRxw9A0nWnT8nxGLSyBGcjFLUGapkFKtKUciUTg9XgKrmjVcQcsy8LtciFVYhNumUwGbZb0AVh2c6HWaKDVasETBLwViqcjOK6k7yGkYnR0dKCvr69+7RWB1axjCIIQVe7d3d3gOE7MVBbWMJVKJRLDhoaGgkQfiz0EDxw4UMZPWDhUKhUOHTqEM2fO4OGHHwaQOT9nzpzBk08+uezvkCS5ZP0Sun9bXUtbJ4MrIPfG6unpAcMw8Pv98Hq9mJqaAkmSsNvtIjk0mUwFP9QoisLw8DBSqVTVDVUJghDd8++9916k02ncunVLJIfuUAgBux1Bux3TVitYgwFWiwWWbEu5GmkUsVgsoxaWuNBBuUJLORaLVa2lnOu92NraWv424yZDOpXCgtMJpVKJjo6Osn5ny80bJkgSiXgchFwOOpnE9WvXYLfbC5o3lAJu3bqFiYkJDAwMoLOzs9qHU1NgGAbDw8OIx+MFtdVlMlmmu2O1YufOnWBZFsFgEH6/H7OzsxgbG4NOpxOJocPhWDKWQFEUPvrRj2JqaqoqHoJr4amnnsKjjz6Ku+66C0eOHMHTTz+NRCKBxx57DADwyCOPoK2tDV/60pcAAB/+8Ifx1a9+FQcOHBDbxF/4whfw4Q9/eNPZGBWLOhksEAqFIm+QN5FIwOv1wuv14sqVK1AoFCIxXC2o3OVyYXR0FC0tLbj77rsl15pTqVTo7e1Fb28vgIzVjqBQvjEygoBcjoDdDp/NhhmzGRqDQYzLM1ssZb2hOI6D3+9HJByuuXzcNVvKLtcS4+JSV2Bzq6ldXV311lyRSMTjcDqdsFgscDQ0VJx45c6rxhMJeBcWQCWToCgKgUAAhEyWibrMmqeX4vsVaiUb/aw8z+PSpUu4detWyeaitxJyrWOOHz++LoGcPBtr2NDQgD179ohKZZ/PhytXruD8+fP4z//8T8RiMbzvfe/DsWPH8Mgjj4DjuKp4CBaCj3zkI/D5fPjiF78It9uN/fv347XXXhNb53Nzc3nP0c9//vMgCAKf//znsbCwgIaGBnz4wx/GX/3VX1XrI0gGdZ/BEoDjOASDQZEcRiIRWCwWNDY2oqmpCRaLBTzPY3JyEvPz89i/fz/a2tqqfdhFg+M4LCwsiFXD204nQhYL/A4HQhYLkkYjTGYzbFlyqCvhjKVIZDgOra2tkmgLlxJCSzmRSIAkSbGlrNfrlxUSFAsho9lgMKBRwtVUKUKIiQwGApLZhEQiEYyPjkKmUODYsWMgCEKcNyQTCVDJJJRK5R0Lm3VWnn/xi1/g3rfewp88+eS6OxhCRSsWi+Huu++GoV6NLgqxWKwi1jHJZBI/+MEP8IMf/AC//OUvRRHlH/zBH+D9738/jh49WhH/wjqqgzoZLAOSyaRIDH0+n5hoolKpcPDgQUnusNYDiqJw48YNkRz6UqlMS9lmQ8higSzbUhbmDddbqYjH43C5XDAajVuCyPA8j2QyKZJDwbhYqBrq9PqCF4RcItPQ2FiReKrNBI5l4fZ4kKQotLS2VsVYdznwPI9z584hTVHYuWfPEnsNVqg8ZzcX6VQKGq02c/3odNBqNAXdR2+99Rbu+8Uv8Kef/OS6SDBJkhgaGoJKpaqYGfJmQiAQwNDQELq6urBnz56KVKPHxsbwgQ98AKdOncLJkyfxxhtv4PXXX0c8Hsfx48fxK7/yK/j0pz8tua5WHRtDnQyWETzPY3Z2FpOTk2J1MBwOZ6oz2ZZypexryg2e58WszZmZGdy6dQsBjSZTNbTZEDMaYTCbRXJoNBrXbINyHIeA349wDbaFSwmhpRwXFvZ0Wmwp63U6qFdoKYtCh1RKUkSmViCkschkMrS2tkpu8Zu9eRO3Z2dhcTgwMDCw6mtFMVN2g8FzXJ7SXa1WL0s0NkIGg8Egzp07h5aWFgwMDEhCeFZLWFhYwOjoKPr7+ys2q/ef//mf+I3f+A187nOfw5/8yZ+I1wTP85iamsKZM2cwMTGBf/7nf67I8dRROdTJYJmQ6x146NAhcUYmnU6LQhSPxwOapvOEKOuV/ksNNE1jbm5OJIeuQCCTiGKzIWS1ghGqhlYrLFbrEqJC0zRcTie4TdoW3ghomhYrPmJLOUsMhZZyKpXCwsICVCoVmpubJUdkpA6SJOF0OmE0GNDQ2ChJIrPeeDoxcjF7DVEkmZk3zFYNc+cNBTL4mf/n/ynKPmd+fh5jY2MVd0rYDMi1jrnrrrsqlkP93HPP4Q/+4A/wv/7X/8JHP/rRirxnHdJBnQyWAbnegQcOHFhRTCL4Qgkt5UAgUFL7GikhGo2KQpSZmRkEANHbMGyxQJ3jbahUKuH1eqHX69HU2Ljp28IbwXItZSFFx2gwoLGpqU4Ei4BQvff7fGhoaIDFaq32Ia2K0dFRxMNhbO/tXXciCcdx4jW0eN7wytWrOP7zn+NPP/Wpgsggz/O4cuUKZmZmKkpkNgt4nsfFixfhcrlw9913V2Ssg+d5/O3f/i3++q//Gi+99BLe+973lv0965AeNi0ZjEaj+I//+A+85z3vgbVCD/Rc78C9e/cW7QHGMAwCgYBIDhOJBGw2m0gOzWbzpthhcxwHp9MpEsO5+XkEzWYE7HaEbDaQej30BgMcDQ2w2WxlMfvejOA4Dl6vF7FoFFqdDjRNI51OQ6vRiJXDlVrKdWTa8Z7sfdfa2loTiRjOhYX/f3v3Hd9kvfYP/NNBR0aTO6PpAFoQkVWKlDYMmSIUEPGcg4LwWBD1d1DBgRsZPkdliAMFlHFU1Of4iPAAes6hYXlYQltoqZRRoIvRkdmVpG3W/fujzW0DBdrSZrTX+/Xyn5A0d5AmV77X9/u5kH/pEvhhYRickNAmP7PxfsOLubkYeeQIRg8diq5du0Iul4NhmCa3ttjtdpw+fRoGgwFDhw7ttNs6WqtxdMywYcPc8u/Pbrfj5Zdfxo4dO5CamopBgwa1+3MS79Rhi8GzZ8/iiSeewIULF6BUKpGcnIxJkyZh8ODB7fJh2Dg7cMiQIW2SHWg2m7l2sk6n46IBnMWhJzL+2kNtbS0uXryIjIwM6PV6VNnt0MnlMDAMKhgG4PMhaWgnMwxDm9Cb4NJWj47m/o64lrLJBJPZDLDsTS1lUp/hV1xSAgCIiorymRV5q9WKE8ePAwASEhLaPDfyyOHDGHnkCJ58/HFu5KLNZoNUKuViSsLCwlBXV4eMjAz4+fkhKSmpw7w3uYszOiYgIABJSUlu+b2sqanB7NmzceHCBaSmpnpdhiBxrw5bDDpdv34de/fuhUqlwv79+9GlSxdMnDgRycnJmDBhAsLDw+/6ORpnB8bFxbVLW66p+BqRSASFQoHw8HAwDOOzKz4ajQaZmZmIiIjAgAEDUFlZya0aFhUVQR8czMXXVIlE4AuFXLZhWFhYp28jO/e33amt7mwpc3vFamr+iB9pOKncEQ4ztVSN2YyS0lLwQkOhUCh87t/TubNnYdBqER0Tg549e7bpzz5y+DBGHTmCtxYtAp/P57a2aLVaaLVa6HQ6+Pv7w+FwICwsDIMHD6bomBZyV3RMY3q9Ho888gj8/Pzwyy+/QCKRtPtzEu/W4YvBxmw2G9LS0qBSqaBSqXD69Gncf//9mDRpEpej1JJCzm63eyw7sLa2FlqtlisOHQ6Hy6qhL7S4HA4Ht79o4MCB6N69+033sdlsuHbtGncQpVirrT+EIpHAIJHAwudzB1EYhuFGeXUGLMui3GCAXq+HXC6HqIVD6bl2oNEIc03NTS3lkNDQDt+ed47lk8pkYBjGJ1+vTqvF+XPnEBQSgqSkpDb7UsiyLI4eOeJSDN6opKQEWVlZEIvFcDgcqKioAJ/Pd5lq4SurrJ7gieiYoqIiJCcno1+/fvjHP/5BKQMEQCcrBm+k0Wiwb98+pKamYu/evbDZbHjooYcwadIkTJw48bbFXVVVFU6dOoXAwMD69kwTb5TuwrIsKisroVarodVqYTAYwOfzudBrb4yvadxWT0xMbPb+ourqahQUFHArhzqHA7qGbMNKkQhdhEIuvkYsFnfYwxN2ux3qsjLU1ta2WWzMTS1lgAst5gsEHepD3eFw1I/lq6pCVGSkT4/lc9jtOJGWBrvVirj4+DbbI924GHz71VddvmCyLIv8/Hzk5uZi8ODBiIqKAlD/b0in03ErhyaTCWKxmCsOJRKJz3Yw2ponomOys7MxadIkTJ8+HWvXrvW6zwXiOZ26GGzMbrcjKyuLWzVMT09Hv379kJycjOTkZIwYMQLBwcFwOBxYtWoVMjMz8d5776FPnz5e9+ZmtVpdVg3r6uogk8m8Jr7G2RZWKBQYOHBgqws2lmVRWlrKFYZXrl1DuVAIXcNBFJNQiLCwMG7VUCAU+uTKz42c83EDAgLaLf/udi1lvkCA0NBQn/0gsdlsKCkpgd1uR3Sj/ZW+7PKlS1AXF0MeGYn7+vRpk595q2LQ4XDg999/h1qthlKpvG3xWVNTwxWGzv2GMpmMKw6FHeR3siUaF9KJiYluO3G9f/9+TJ8+He+88w5ef/31Tvf3Tm6PisFbMBgMOHDgAFccVlVVYeTIkSgoKIBGo8HXX3+NP/3pT56+zDtiWRZGo5ErDHU6HYKDg13mKLtrxYdlWeTm5iI/Px9xcXHo3r17m74h1dXVoaioiGspq6ur67MNpVJUiMVg+XyIGQYS50EUH9zkXl1VhbKyMogZBjKZzG1v6Ha7nYseMZnNsFqtCG2YaMHn8xESEuITHy61tbUoKS5GcEgIIiMifG5/4K3cOJ6uLQp1h8OBY0ePYvShQ3jr9dfB4/FgsViQkZEBm80GpVLZohXpxlFaWq0Wer0egYGBXGEol8s7fMuSZVnk5OSgpKTEbdExAPD9999j/vz52Lx5M2bPnu2W5yS+hYrBZmBZFt9++y1efvll+Pv7o6qqCvfccw93Qnn06NE+8yZmt9u5+Bq1Wg2TyQSGYbiWcnvF19TW1iIzMxO1tbUtagvfDYPBwK0aFhYWQh8YyE1EqQwLAy8sDIxYDIlE4vUHURwOB3Q6HSorKhARGdmiAOD2YLFYuMLQ3LilzOe7hBZ7E2chzUgkkEqlPlG8NhfLsjh58iTqTCb07tevTVabGheDb7/xBmw2G9LT07mDIne7Iu08FOdcNSwvL4dAIOiw+w09ER3DsixWr16NlStX4v/+7/8wfvz4dn9O4puoGLwDu92ODz74AKtXr8aqVauwYMECGI1G/Prrr1CpVEhNTYVarcbo0aO54rB3794+80HjjK9xflv39/d3WTUMCQm56+fQarXIzMyEXC5HfHy8R/bx2e12XLt2jSsOr5eWwtAwEaWCYVArENRH1zTsNwz1osMTNqsVJaWl9W1NL5zG4nA4UFdbW18YNoQWBwUFgRcaCr5AAF5oqEcLbeeoxIrycq8opNtLS8bTNYfDbsexY8cw+tAhPDtvHnJyctr1oINzv6HzvchsNoNhGK449OXEBE9Ex9jtdrz44ovYtWsX9uzZQxmC5LaoGLyDadOm4eLFi/jxxx+b/GVyJu4728mHDh1CZGQkt9dw3LhxPvPh43A4UF5ezhWHFRUVEIlEXHHY0s3fzr+bvLy8dmkL3w2TyeRyEEVrsbhMRAlomIgiYZj6gygeWqHgYmN4PJ+JPblVS5nfEF/jzpay3W5HaWkpLBYLukZHe10h3ZZaO57uVhoXg4Pj4zF48OAmT/y3F7PZ7LLf0G63++R+Q2d0DMMwuP/++92y17ampgazZs1Cbm4uVCoVYmJi2v05iW+jYvAO0tLSEBcX1+zTwmazGYcPH+aKw8LCQowYMYKLr4mLi/OJNzCgfg+eVqvlTik734yd2Ya3a3M428I1NTVITExskxDu9sKyLNRq9R/ZhlevwsDnw9BwStkoFEIYFsYVh3yBoN1XKFiWRXl5OfQ6HWRyOcQtjI3xJi4tZZPplnNw2/x5Gw7adOnSBZGRkT574KUl2mI8nZPNZsPx337DmEOH8Ndnn+VODHsCy7KoqqriCkNf2W/oiegYyhAkrUHFYDsrKCjgQq8PHjwIkUiEiRMnYtKkSW4dlXe3nPE1zlXDxvE14eHhkEqlXPtXp9Ph1KlTkMlkiI+P97l9PxaLBUVFRVxxWFZe/sdBFIaBXSAAIxbXH0aRSNp82oLDbkeZWo2amhpERUZ2qOzEW7aUGwrDtmopm4xGlJSUQCwWQyaX+2wh3VJtNZ7ObrejuLgYRYWFGHPoEBa/9ZZXTRWx2+1cF0Or1aKiogJCoZArDKVSqcffdzwRHePMEOzfvz/+53/+xysLZOKdqBh0o7q6Ovz222/cquH58+e5UXnJyclISEjwmT0xjff3aDQa1NbWcpvydTod9wbYET6EKyoquMKwoKAA+oAA6GQyGBgGlSIRQgWC+okoDAORSHRXK1AusTGRkR5rT7uL3W6HuSG+xmQywWqz3VVLmWVZGAwGGPR6KCIiOt18XKvVihMnTgAs2+rxdBaLBcXFxQgICPDaYvBGFovFJd/Qk/sNG0fHDBkyBBEREW553tOnT2Py5Ml47LHH8Omnn3aKlXDSdqgY9CB3jMpzB+cH8OnTp1FbWwuWZREUFMS1k90ZX9PeHA4Hrl+/zhWHV4uLYZBIYJBKUd5wECVMJIKkoTjk8XjNLma42BixGFKZzGe+GLQlrqXcUCC2pKXsXFGtralpsyBuX3Tu3DkYNBpEd++Onvfc06LHOveoCgUCSGUyHP/tN4w7dAhvv/22T+Ux3rjf0OFwQCaTcXsO22u/oaeiY/bt24fp06dj6dKleO211zrEl3DiXlQMeglnbENqaqrLqDznCeWWjspzJ51Oh8zMTG62pr+/Pxdfo9FoYDQaufia8PBwn97/diOz2ex6EKWujgu9LheLEdBwSlnCMBAzTJPFjMPhgF6nQ0VFBSIiIiDsZKtZt+JwOFBbW8utGtY2aikL+HyENmopW61WFF+/Dv92DOL2Fa0dT+cczSeXyyFmGG7PoC8Wg405t7g03m8YFBTkst+wLVITPBEdAwDfffcdnnvuOWzZsgWzZs1yy3M2tmHDBqxZswZlZWWIj4/HunXrkJSUdMv7V1RU4J133sHOnTthMBgQExODtWvXYvLkyW68anIjKga9lHNUnkqlwt69e2G1WvHQQw8hOTkZEydOvOvN4W2BZVlcvnwZly5dQv/+/W/ZFq6pqeEKQ41GA39/f5c5ym3xRuwNWJaFVqv94yBKURH0fD70DXOUTWFh4DdkGzISCYRCIRwOxx/TMLwwNsab2Gw21DTkGppMJtjsdoSEhCAoKAjVVVUICwuDPDy8U66oNtbS8XSNo3eioqK41nLjYnDx4sUdZnXfbre75Bu2xX5DT0THsCyLlStXYvXq1di5cycefPDBdn/OG23btg0pKSnYuHEjlEol1q5di+3bt+PixYtNdrYsFgtGjBiB8PBwLF68GNHR0bhy5QrEYjHi4+Pdfv3kD1QM+gCHw4HMzMw7jspzp7q6OmRlZcFoNCIxMbHZ7RDnMHu1Wu0SXyOXy6FQKDrU7FKr1YorV65wxWGJXl+fbSiVolwshq1h3q9QKERMTIzbVhI6ApZlYW3YJ1ZdXQ0/f3/4+/tzwdc8Hq/DFC+t0dzxdA67HaVlZairrUXXrl1dvox01GLwRk3tN5RIJFxxKBaLb/ue5InoGLvdjoULF2L37t1ITU31WCGlVCqRmJiI9evXA6h/f+/WrRsWLlyIt95666b7b9y4EWvWrEFubm6H/ffkq6gY9EHl5eXYv3+/y6i8cePGcfE1PXr0aNfn1+v1OHXqFPfmdze/1M74Gueqoc1mc1k1bG6kjy+orKzkCsO8vDyU+/tDJ5ejnGFQIRYjWCAA09BSFonFtAH8Nhx2O9QaDUwmE6KjohAcElLfUm6IsKmtqUFQcDD4fD74PJ5LS7kz4MbTBQRg6LBhTbbNrVYriouL4e/v32Rr3Waz4fixYxh3+DDeeeedTtN6N5lMXGGo0+m4/YbO4rDxbHdPRMc4MwSd+bbuzH5szGKxgMfjYceOHXj00Ue52+fMmYOKigr8/PPPNz1m8uTJkEgk4PF4+PnnnyGXyzFr1iy8+eab9H7nYZ3jt7uDYRgGjz/+OB5//HFuw7JKpcL27dvx0ksvoUePHtyq4ZgxY9psIz3LssjLy8PFixfRr18/9OjR467f/IKDg9G1a1d07dqVyxLTaDQoKSlBTk4OeDweVxjKZDKf/kASiUQYOHAgAEAgEKBbt27Q6/X1B1FycmAQiaCXSlEokcAsFEIUFgYxw0AqkYDH53eYfZZ3y2q1oqSkBAAQExPDfRlxHjSR4Y+Wsslshlqt5lrKAj4fPD4fwcHBHfrvMywsDCE8HupMJuh1OihuONFaU1ODkpIS8Jxh5k2tfHXSdQJ+w0jF2NhYl/2GZWVlOHfuHLffMDAwEFeuXEFcXJzbomP0ej2mTp2KwMBAHDt2zKMZgjqdDna7/abRhwqFArm5uU0+pqCgAL/++itmz56NPXv2IC8vD88//zysViuWL1/ujssmt+C7n6wEAODn54eBAwdi4MCBeOONN1BdXc2NynvuuedcRuUlJyfjvvvua9WHoMViQVZWFqqrqzFixIh2yUf08/ODSCSCSCTCvffe6xJfk5OTg9raWkgkEu6Usq9MIHAymUzIyMhAYGCgS5E+evRo1NbW/nEQ5dIlaEwm6ORyGBgGxQwD8PncIRSJRNJpWyw1ZjOKS0rA5/OhCA+/5WpfYGAghGFhEIaFcS1lZ7ahXq+HX6OWMp/H63ARPn5+fggPD8e1wkKoNRqXYtB5al0qlYKRSJr1O+RLv2dtyc/PD2KxGGKxGPfeey832/3y5cvQ6XQAgMLCQhiNRm6/YXt9YS0sLERycjIGDhyI77//3if3WjscDoSHh2Pz5s0ICAhAQkICiouLsWbNGioGPYyKwQ5GKBRi2rRpmDZt2k2j8t56661WjcozGAw4efIkGIbBmDFj3FaIOCdHREZGgmVZmEwmrp3s3HPSeI6yN592LCsrQ1ZWFrp164b+/fvftBITEhKCfv36oV+/fmBZFnq9Hnl5efUHUdLToQ8JgV4mQ5lYjEsiUf1BFIYBwzAIEwo7RQu0oqICWo0GUpkMDMM0u0Dx8/NDUHAwgoKDwTDMH6eUTSZUVFSgrLQUwcHBXGHYUVrKivBwXLlyBRXl5bDU1aFLUBCXwdicGc0sgM5ZAt6av78/ysrKUF1djVGjRoHH43H7Dc+cOYOampoW7TdsrqysLEyePBkzZszAJ5984hUtVZlMhoCAAKjVapfb1Wr1LbMVIyMj0aVLF5fr79u3L8rKymCxWLz6Pbyjo2KwA/Pz80OfPn3Qp08fvPzyyzCbzThy5AhSU1PxxhtvcKPynPE1N47Kczgc+P777yGVStG3b1/07NnTYysEfn5+EAgEEAgE6NmzJ3ciUKPR4NKlS8jMzIRYLOaKw5YUC+2JZVnk5uYiPz8fgwYNatYpcD8/Py4TbejQobDZbLh69Sq337D4zBnoJRKUSyS4JJHAwufXn1BmGDASSYfL13M4HNBqNKiqrkZUdPRd7yP1b5RdeKuWcmhoKLdy6Kst5VAeD2FhYTBWVKBMrUaXLl1gNpvRtVu3Fv8b8cXX39YaR8c4C0EAiI6ORnR0NADX/Yb5+flgWZbbb+jcA93Sv8u9e/fisccew7Jly/Dqq696zf+LoKAgJCQk4ODBg9yeQYfDgYMHD2LBggVNPmbEiBH44Ycf4HA4uCL50qVLiIyMpELQw+gASSd246i8sLAwbtVw4MCBePbZZ3H58mWkpaW5bU9MazWOr9FqtQDgsmroiQLJYrHg1KlTMJvNSEpKarNpGNXV1S4TUXQOB3QNc5QrRSJ0EQq5VUOxWOzT+yxtNhtKSkrgsNsRFR3d7h8YjVvKJpMJNQ3B177aUnaOpwsMCUFUVBSio6Kaff1WqxVpv/2GsYcPY+nSpR3mlH9r1NXVIS0trUXRMSzL1q9mNxSHBoMBwcHBLvmGd0qB+Pbbb/H88897LEPwTrZt24Y5c+Zg06ZNSEpKwtq1a/HTTz8hNzcXCoUCKSkpiI6OxsqVKwEA165dQ//+/TFnzhwsXLgQly9fxrx58/Diiy/inXfe8fCr6dyoGCQAXEfl7dy5E/n5+QgLC8P8+fMxffp0nxqVx7IsN7dUo9GgvLwcYWFhXHEokUjavc1SXl6OkydPQiwW3/WJ69thWRalpaVcS/nq9evQh4VxE1FMQiHCRCKuOGx8EtLb1dbWoqS4GMEhIYiMiPBI69bZUnZORKmtqUFwwyllng+0lE1GIzKzsgCHA/cnJDRrW4hT42Jw2bJlPvPvpq21VXSMzWZzyTesrKysz8ZsKAz5fD4EDRmPjTMEd+3ahXHjxrXlS2pT69ev50KnBw0ahM8//xxKpRIAMGbMGMTGxmLr1q3c/U+cOIFXXnkF2dnZiI6OxtNPP02nib0AFYOEw7IsPvnkE26kUbdu3bBv3z5uVN6ECRMwadIknxqVB9Sv0Dnja9RqNWw2G2QyGVccCloxv/V2rly5gpycHNx3333o1auXWz9E6+rqUFhYyK0cqqur61cNG4pD8HjcRBSGYbw25Np5yIGRSLiZ197A2VI2NhSH9kYtZb5AgKCgIK+5VpPRiJKSEhhNJhgrKlo8no6KwfaNjqmrq+P2G164cAEpKSmIi4vDqFGjUFhYiJMnT0KlUnEJBIS0JyoGCYD6QyJPPfUUsrOzsW3bNgwdOpT7M+eoPOdBlKysLG5UXnJyMoYOHeozrUiWZVFdXc2FXhsMBoSGhrZJfI3dbseZM2dQVlaGIUOGQC6Xt/HVt5zBYOBWDQsLC6EPDuYmolQ1TERxFodhYWEeX+VqPA0jMiqqzQv1tuRsKTsLQ66l3LBq6KmWsrM9qdNqoYiIgKWurlXj6SwWC9J/+w1jjxzplMVgcXExTp8+jf79+7d7dqvD4UBOTg527tyJL774AgaDAQKBAOPHj8f48ePx0EMP4Z577ul0/w+I+1AxSAAAKpUKX375Jb755ps7Zlf5wqi85rLZbFx8jUajgdlshlQq5YrDsLCwZr0Bm81mZGRkwN/fH4mJiV55iMNut+PatWtccVhcVvbHRBSGQR2fD3HDiiHDMAgNDXXrh4/dbkdpaSksFgu6Rkd77arlrTjsdtQ0mqVcV1uL4JAQbr9haEhIuxfbzsM21UYjoqOiEMrjtXg8nVPjYrAzxX6wLIv8/Hzk5uZiyJAhtzwZ29Z0Oh2mTp2KLl26YOfOnSgsLMSBAwdw4MABHDt2DJGRkXj11VexcOFCt1wP6VyoGCQclmVb/OHvcDiQlZWF1NRUblRe3759uWkonhiVdzcax9dotVoEBgZyhWF4eHiTG8fVajUyMzMRHR2NAQMG+MzeF6PR+Ee2YX4+dFYr9DIZ9FIpKkQiBAoEXDtZLBa36yqXpa4OxSUlXJyQr/wd3o7NZuMKQ7PZDIfdjtCGU8x8Pr/NW8p2u71+zrXNhuiuXV32qTZ3PF1jlro6pB8/3qmKQWeIf0lJCZRKZbvkqTaloKAAycnJiI+PbzJD0Gw249ixYwgNDcXIkSPdck2kc6FikLSp8vJyHDhwgGspV1ZWYty4cVxLuWfPnp6+xGZrHF+j0WhQVVUFhmG4wlAkEiEvLw+XL19GfHw8unXr5ulLbjWWZaFWq//INrx6FeUCAXQyGSoYBkahEMKGgygShgFfIGizA0VGoxGlJSUQMwxkMlmHbIWxLAuLxcIVhjVmM/wDArjCkMfj3dVWizsV080ZT9fUz8w4fhxjOkkx2Dg6ZtiwYW6bFZ6ZmYnJkyfjiSeewCeffOIzB/VIx0LFIGk3jUflqVQqHDt2zGVU3ujRo932htsWamtrucLQOUfZ398fvXr1QkxMjFe2hlvLYrGgqKiIKw7Lqqqgl0phYBhUMAzsDXOUxWIxpBJJq1q6LMtyIciKiIg2i97xBVxLuWGW8t20lM1mM4qLiyESiSCXy5ssplmWxcmTJ1FnMqF33743jadrirMYHHv0KJYtW9bi1+hLWhMd0xZUKhUef/xxLF++HIsWLeqQX4SIb+g0xeCGDRu44+/x8fFYt24dkpKSbnn/7du3Y+nSpSgqKsK9996L1atXY/LkyW684o6n8ai81NTUNhuV526VlZVIT09HaGgopFIp9Ho9ysvLIRAIoFAouLFUHaHV6VReXu6SbWgIDIROJoOBYVApEiFUKOTG5YlFojsWMg67HWVlZaitrUVkVFSHKqRbo3FL2WQygXU4mtVSdk5lkcvlEN+hpVlUVIRrhYUQSaXNOqHaWYrBtoqOaamtW7fihRdewN///nc88cQTbnlOQm6lUxSD27ZtQ0pKCjZu3AilUom1a9di+/btuHjxYpMRKcePH8eoUaOwcuVKPPzww/jhhx+wevVqZGVlYcCAAR54BR0Py7K4dOkSt9fw0KFDiIiI4ArDBx98sEWZaO5y9epVnDlzBvfeey969+7NfUA3jq/RaDSwWq0u8TWtmTzgrex2O4qLi7lVw2slJTBIJFx8Ta1AAJFzIgrDgMfjubx2i8WCkuJi+AcEICoqymdOortLc1rKAQEB0Gm1qKisRFRUVLOmstSYzTh58iTg54ehSuUdV3Pr6upw6tgxjD1+HEuXLm2rl+dVnNExMTEx6Nevn1t+R1mWxYoVK7BmzRrs2rULY8eObffnJOROOkUxqFQqkZiYiPXr1wOoP/TQrVs3LFy4EG+99dZN958xYwZMJhP+9a9/cbcNHToUgwYNwsaNG9123Z2Jc1Ses6Wcn5+PBx54wGUiiieLKbvdjrNnz6KkpAQJCQm3zVl0xtc4C0O9Xo+QkBCX+Bp3zXd2B7PZ7HIQRVtXx2UbVojFCGg4pSyRSBAUFAStVguhQAB5eDjtj2qGplrK/v7+gJ8fwsPDIRQImt1Szj59GtUVFYjt1euOe1w7ejHozugYJ5vNhgULFuBf//oXUlNTERcX55bnJeROOvxXcovFgszMTLz99tvcbf7+/hg/fjxOnDjR5GNOnDiBRYsWudw2ceJE7N69uz0vtVPj8Xhc4Qe4jsp77733XEbljR8//o7xN22ppqYGGRkZANCsfY5+fn4ICwtDWFgYevXqBZvNBr1eD41Gg3PnznHxNXK5HAqFotnxNd6Kx+NhwIABGDBgAFiWhUaj4QrDKxcuQM/nQy+V4nrDQZRQPh+BgYGorq6GUCikgvAO/AMCwOfzwefzIbZacf36dQBAcHBw/Wq0Ws21lAV8Prrc5pRyuEKB6ooKaDSaOxaDznUCX/632RRPRceYzWbMnDkTBQUFOHHihE8fOCMdT4cvBnU6Hex2OxQKhcvtCoUCubm5TT6mrKysyfuXlZW123USVz179sRzzz2H5557DhaLBb/99htSU1Px/vvvY9asWUhKSuLia9pzVJ5Go0FmZiYiIyMRFxfXqv1EgYGBUCgUUCgUiIuLc4mvuXTpkkt8TXPmlXozPz8/7rUOHz4cVqsVhYWFSEtLQ+n586i2WOoPokilyBWLYWs4iOL878ZIDfKHGrMZxSUlEAgECG9YVeVaykYjTCYTdDodAhpaygI+H6E3nFKWy+XIy8uDqboaJqMRfC8O9W4PjaNjRowY4bboGK1Wi6lTpyI4OBhHjx512/MS0lwdvhgkvi8oKAhjx47F2LFj8eGHH6K4uJhbNfz444+5UXnJycmYMGHCTYV8a7Asi8uXL+PSpUuIi4tDTExMG7ySenw+Hz169ECPHj3gcDi4+Jq8vDxkZmZCLBZzxSHDMD69cmaz2VBWVoaYmBg89thjsFgsfxxEyc6Gzt8feqkUeoZBvliM4IbiUMIwEInFHeoQzt1wjueTymRgGIZbrfPz80NwcDCCg4MhkUrrW8o1NTCbzdDr9agrKUFIaCi33zAkJARSqRTlDaMZe96mGGRZFn7oOCuDjaNjRo4c2ax9lm3BmSE4aNAgfPfdd/SFh3ilDl8MymQyBAQEQK1Wu9yuVqtv2R6IiIho0f2Je0VHR2PevHmYN2+ey6i8zz//HHPnzr3rUXlWqxVZWVmoqqrCAw88ALFY3D4vBPVbFmQyGWQyGfr168fF12i1WmRkZMDhcHDt5PDwcJ86dWswGJCRkYHw8HDEx8cjICAAoaGhGDx4MAYPHgyHw4Hi4mKuOLyak4NysRh6iQQFEglqhEKIGmUb8jrQIZzmYlm2/rS6wdCs8Xz+AQHgCwTgCwSQA7BZrTCZzTCbTCgpKQHrcCAwIAAs6t/TYmNjPT6C0B0aR8eMHDnSbdExzgzBWbNm4eOPP/bpL3akY+s0B0iSkpKwbt06APUHSLp3744FCxbc8gCJ2WzGP//5T+624cOHY+DAgXSAxMvd7ai8qqoqZGRkgM/nIyEhwW0fGk1xzph1tpSd8TXOVUNvjq+5cuUKcnJy0LdvX/Ts2bNZRVxNTQ0KCwu5U8pasxk6uRwGiQTlYjH8BQIwYjEYiQQMw3SoQzhNcdjtKFOrUVtTg+iuXe96+wDLsqirq4PRaETuhQtw2O2QyeWQSKXg83g3tZRrampw+vhxPJiejsWLF9/ty/EYo9GIEydOuD06xpkh+O677960B50Qb9MpisFt27Zhzpw52LRpE5KSkrB27Vr89NNPyM3NhUKhQEpKCqKjo7Fy5UoA9dEyo0ePxqpVqzBlyhT8+OOPWLFiBUXL+BjnqDxnrqFzVJ5z1fCBBx5w+YBdt24djEYj/vSnP3ll5qHVanWJr7FYLC5zlAUCgcev2eFw4OzZsyguLsaQIUMgl8tb9XNYloVOp+NWDYuKiqAPCYFOJkO5RIJqoRD8sDBur2GYUNihVrhsViuKS0oA1K+Et3X8jnM8nVguR3h4OMwmE+rq6hASGsoFXwNA9vHjeDAjw2eLQU9ExwDAN998gwULFuCrr77CzJkz3fKchNyNTlEMAsD69eu50OlBgwbh888/h1KpBACMGTMGsbGx2Lp1K3f/7du3Y8mSJVzo9Icffkih0z7uVqPyHnzwQRw8eBD/+c9/sGXLFp9483bG12i1WqjVauj1egQHB3Oh13K53O0rZ3V1dTh16hQsFguSkpLadE+WzWbDlStXuOKwRKeDXiKpn6PMMLAKBBA3yjb0pXb6jWpra1FSXIzQ0FAoFIp2KXKbGk9ntVphbmgpm8xmWK1WlBcXY1x6Ol566SWfy8osKSlBVlaWW6NjWJbF+++/j48//hi7d+/GmDFj3PK8hNytTlMMEtKY81Thtm3bsH79elRVVSE2NhaPPPKIT47Kaxxfo9FoYDKZIJFIXOYot+cHuXMqi7MV195B0tXV1VxhmJ+fDz3LukxE6SIU1u81lEggEol8JtjaOaeZkUgglUrb7f/ZncbTsSyLyspKnD91CmPT0hAfH4/g4GCXrExPbqG4HU9Fx9hsNjz//PPYs2cPZQgSn0PFIOm0Dh06hBkzZmDy5MlYvXo10tLSkJqaitTUVJSVlXGj8iZNmuSVbePbMZvNXGGo1WoREBAAeUNLMDw8vE3ja5zhvb1798a9997r9r8nh8OB0tLSP7INr12DQSSCQSqFQSKBWSBAmPMgikTilStcLMui3GCAXq9HREQEhG6Y03yn8XRmsxm/Hz+O8adO4bXXXoNer+e2KVRXV4NhGO7flLecem8cHaNUKt0W4WIymTBz5kwUFhYiNTWVMgSJz6FikHQ6LMvi448/xvLly/Hpp5/i2WefdSkOnKPynO3kQ4cOQaFQcHsNx40bhzA3fFi3FYfDgfLycqjVamg0GlRWVkIkEnEnlFv7Qc6yLC5cuIDCwkIkJCR4zWn72tpaFBYWcsWh2mjksg3LGQbg8eoPoTQcRvH0CpfD4YBarYbJZEJ0dLTbWtw1NTU4mZFxy/F0jYvBGw/a1dTUcIWhVquFw+Hgxi/K5XKPFNyNo2OGDh3qtugYZ4ZgSEgIdu/e3a7pA4S0FyoGSaf0zjvvYNq0aUhKSrrjfWtqanD48GGvHZXXUnV1ddyqoUaj4eJrnKuGzWmPW61WnDp1CiaTCUql0ivnSAP1BavBYOAKw8LCQuiDg6GXSGCQSFAlEoEvFNaPy2MYhIWFufUgis1mQ0lJCRwOB6Kjo92+z/N24+mcxeBDmZl48803b/kznC1lZ3FoMBi48Yvu2r/aODomKSnJbQV+fn4+kpOTMXjwYHz33Xc+HRhPOjcqBglpocLCQuzduxepqak4ePCgR0fl3S3nB7mzMDQYDODz+S57w26M4qiurkZ6ejoEAgESEhJ8KuLFZrPh2rVrXHF4XaNBOcNA37BqWNfoIIqEYRDajvtGLXV1uF5cjOCgIERGRnrkNHRJSQnyL10CTyhEQkKCy581txi8UeP9q1qtFkaj0SVIXSwWt2lL2VPRMSdPnsTDDz+M2bNn46OPPvJIm3zDhg3cwcj4+HisW7euWV9wf/zxRzzxxBOYNm0ajVklAKgYJOSuOEflOeNrzp8/j6SkJK44HDJkiFfspWouZ3yN85RyXV0dpFIp11I2Go3IyspCjx490LdvX59aEW2K0Wisn4ZSUID8/HzorFZo5XKUSySocB5EaWgni8XiNjuIYjIaUVJaCrFYDJlM5rG/R6vVWj+j3eFAwpAhLuPpWlsM3qimpoYrDG9sKYeHh99VO9dT0TF79uzBjBkz8Le//Q2vvPKKW57zRtu2bUNKSgo2btwIpVKJtWvXYvv27bh48SLCw8Nv+biioiI88MAD6NmzJyQSCRWDBAAVgx1OS74pbtmyBd999x3Onj0LAEhISMCKFSua9c2SNK3xqLz9+/cjMDCwzUfluQvLsjAajS4HUViWhUwmQ48ePTwSX9OeWJZFWVnZH9mGV6+iXCiEriG+xhgWBmFDtqGEYSAQCltVfFSUl0Or1SJcoYBIJGqHV9Iy58+dg0GjQVT37uh5zz3c7SaTCTnHj+Oh06fxxhtvtMlzNV6J1mq10Ov1CA0NbVVL2RPRMQDw9ddfY+HChfj6668xY8YMtz3vjZRKJRITE7F+/XoA9XtPu3XrhoULFzY5TAEA7HY7Ro0ahXnz5uHo0aOoqKigYpAAoGKwQ2npN8XZs2djxIgRGD58OEJCQrB69Wrs2rUL586dQ3R0tAdeQcfSeFSeSqVCVlYWBg0ahEmTJrV6VJ4n2Gw2nD59GgaDAb1794bJZIJGo4HRaATDMC7tP19fKWysrq4ORUVFXHFYVlVVP0dZKkWFWAyWz4e4IddQwjA3HcC4Ecuy3EncqKgor4ku0ul0uJCTg8CQECiVSm4luz2KwRvZbDbodDpuv6HJZHI5pdxUS9lT0TEsy+K9997Dp59+il27dnk0Q9BisYDH42HHjh149NFHudvnzJmDiooK/Pzzz00+bvny5Thz5gx27dqFuXPntksxyLIsHnroIQQEBGDv3r0uf/bFF19g8eLFOHv27B2nQRH3omKwA2nNN8XG7HY7GIbB+vXrkZKS0t6X2+loNBrs378fqamp3Ki88ePHcy1lb3xzNJlMyMjIQFBQEIYMGeKyQd7Z/lOr1dBqtfD39+cKQ7lcjpCQEA9eedsrLy/nRuUVFhZCHxgIvUwGg0SCyrAwhAqFkDAMGIkEohsOotjtdpSWlsJqtSI6OtrjJ5gbc9jtSEtPh81iwYCBA7k9ryajETknTmBCdjZef/11t1xL45ayRqMBy7JcYSiXy8Hj8TwSHdM4Q1ClUnl8ElVJSQmio6Nx/PhxDBs2jLv9jTfewOHDh5Genn7TY44dO4aZM2ciOzsbMpms3YpBALh27Rri4uKwevVq/PWvfwVQv9c6Li4OX375JZ588sk2f05yd7x/WYI0i8ViQWZmJt5++23uNn9/f4wfP75+T1AzmBumDvjSAQhfEh4ejtmzZ2P27Nkuo/K2bt2K+fPn33ZUnidotVqcPHkSXbt2xYABA25aoQkNDUVMTAxiYmK4+BqNRoOCggJkZWVBJBJxxaFEIvGpvZNNYRgGiYmJSExMhN1ux/Xr17lVw2vZ2TA0TETJZxjUCgQQNRxEEQqFMBgMCAwMRPfu3b1unrR/QADkMhnKiouh0Whcfv/93LxW0PjflHM2t1arxfXr13HmzBn4+/vD398fffv2haDR/sb25MwQLCoqQlpamld+abuT6upqPPnkk9iyZQtkMlm7P1+3bt3w2WefYcGCBZgwYQJiY2Px9NNPY8KECVQIeikqBjsInU4Hu91+0540hUKB3NzcZv2MN998E1FRURg/fnx7XCJpxN/fH0OGDMGQIUOwZMkSl1F5KSkp3Kg8Z3HYs2dPt10by7IoKCjAhQsXEBcXh5iYmDs+xt/fH1KpFFKpFH379kVdXR23unPq1CnY7fY2OzTgDQICAriiZdy4cTCbzX9MRDl/HlqLhVs1vCoWA6GhkEqlMBgMYMRiBHrZXktFRARKS0qg02ph69XLZfuCp1r/fn5+3HjBmJgYpKWlwW63QyKRoKCgADk5Odw2Bblc3uanlIH61fypU6ciNDQUR48e9ZoMQecpf7Va7XK7Wq1usm3unO89depU7jaHwwEACAwMxMWLF3FPo/2ibWHOnDnYtWsX5s2bhz//+c84e/Yszp0716bPQdoOFYMEALBq1Sr8+OOPOHToUIdr7/kChmHw2GOP4bHHHgPLsjh79ixUKhV27NiBl19+GbGxsdw0lPYclWe32/H7779Do9Fg+PDhrV4lDg4ORteuXdG1a1eXQwPFxcXIyckBj8fjTihLpVKf2Dt5OzweD3FxcYiLi+P2BmZmZiI3NxfV58+jXCCAQSrFdYkEuUIhBM6DKBIJBAKBx1dNhUIhQng81JlM0Ot0N42n86RbRceYzWbuC0d+fj4AuHzhuNvfkby8PC4R4Ntvv/X4Sn1jQUFBSEhIwMGDB7k9gw6HAwcPHsSCBQtuun+fPn2Qk5PjctuSJUtQXV2Nzz77rN0mpmzevBn9+/fHkSNH8H//93+Qy+Xt8jzk7vn2OzDhtPSbYmMfffQRVq1ahQMHDjQ5loq4l5+fH1dYvP7666iursZ//vMfqFQqPP/88ygtLeVG5SUnJ6NPnz5tsnpTU1ODjIwM+Pn5YfTo0W02CcPPzw9isRhisRi9e/eG1WqFTqeDRqPBmTNnUFtbC6lUyn2IC1t5StebGAwGsCyL//qv/wLDMC4HUUoNBm4iygWGgY3P51bAJBKJR4oOPz8/KBQKXC0ogFqjgSIiAiwAsKxH/18YDAakp6eje/fuN0XH8Hi8m1rKGo2GaynzeDxu1VAmk7Xo5PvJkycxZcoUpKSk4MMPP/R4sd6URYsWYc6cORgyZAiSkpKwdu1amEwmPPXUUwCAlJQUREdHY+XKlQgJCblpn6NzlbM99z+Gh4fjr3/9K3bv3u1y0IV4HyoGO4iWflN0+vDDD/HBBx9g7969GDJkiJuulrSEUCjEI488gkceeeSmUXmLFy9uk1F5BoMBGRkZUCgUGDhwYLvua+vSpQsiIyMRGRkJlmW508kajQa5ubno0qULwsPDoVAoIJPJvOqwxZ04T15XVFRg1KhR3GSWe++9F/feey8AoKKigisMC7KyoA8IgF4qhVYiQb5IhBCBgBuXJxKL3bbHMDw8HFeKilBRUQFLXZ1bnvN2WhId07ilfN9993FfOLRaLc6dOwez2QyJROJySvlWRe6///1vzJw5E++99x5efvnldnhlbWPGjBnQarVYtmwZysrKMGjQIKhUKm6r0NWrV72iiA0MDPT5lf/OgE4TdyDbtm3DnDlzsGnTJu6b4k8//YTc3FwoFAqXb4oAsHr1aixbtgw//PADRowYwf0cgUDgts3Z5O7U1NTgyJEjSE1N5UbljRgxgouvac6ovCtXriAnJwf9+vVDjx49PLoSZLfbuekVvhZfU1NTg/T0dAQGBiIxMbFZK3wOhwPFxcXIy8tDQUEBrhYXo1wshk4mQ7lYjFqhEGEiERdfw2vnmb+Nx9OJxWKcP34cyefOYdGiRe32nDdqvGe1raJjzGazS/A1AMjlchQXF6NPnz7o06cPAOCrr77Ciy++iG+++QaPP/74XT8vAd59913s3r0b2dnZnr4UchtUrncgLf2m+OWXX8JisWD69OkuP2f58uV499133XnppJVCQ0MxceJETJw4EcAfo/JUKhXef/99CIVCTJw4EcnJyXjooYdc9gDW1dVhyZIlGDlyJIYNG+YV+3kCAgK4wg/4I2rEuS/Mz8/PZY6yt+xvraioQHp6OuRyOeLj45u9mufv749u3bqhW7duGDt2LGpqarhpKPkXL0JTW1vfUpZIcE0shr9AwE1EYRimzUO/FQoFqisroVarPXJYwrlftri4GCNGjGiz6Bgej4fY2FjExsaCZVmUNwR/v/vuu1CpVIiOjgbDMMjPz8eOHTswadKkNnleQnwFrQwS0kE1HpWnUqlw7tw5blTe/fffj6VLl8JoNGLfvn1uPa3cWg6Hg9sXplarUVFRgbCwMK4wlEqlHmmLOduZ9913H3r16tVmK3csy0Kn03HZhleuXIE+JKR+1VAiQbVQCIFIxBWHQqHwrl+/czwda7cjIjgYRSdOYPi1a1iyZEm7R5LYbDZkZmbCaDRi6NChbjtxXlZWhhkzZuDUqVOQyWQoLS3F8OHDMWHCBEyYMMGt8447IloZ9A1UDBLSSThH5f3v//4vDh48iMDAQEybNg2PPPKIz43KA+qLXeeqoUajgc1mc1k1bO9igmVZXL58GZcuXUJCQgIiIyPb9fmsViuuXr3KFYelen39RBSJBOUMA5tAAHFDtiHDMK06AGStqcHBD9dAvScV9/S6D3JFBPxq66C9WgCJgIeXXngeI0eObPPXVldXh/T0dPj7+yMpKclt+0RNJhMef/xxXL16FampqejatSsKCgqwf/9+7N+/HwcOHEBgYCAuX77stoBrQjyBikFCOpEff/wRzzzzDN5++22MGTMGe/fuRWpqKjcqzxlf4yuj8pxYlkVVVRVXGOr1eu40aXh4OGQyWZu+HmcEj1arhVKp9EhLtaqq6o+DKAUF0LEsl21YIRYjmM/n2skikeiOr7+6tBSps2Zj/MRpGDn5EQQFu7bgtSXXkbp1E2JlYnz60Zo2WwE1Go1IS0uDWCx26yqcRqPBww8/DD6fj127djX5/9Bms+H3339HQkKCW66JEE+hYpCQTsBut2Px4sXYtGkT/vGPf2DKlCkuf+4cladSqbB3715YLBavH5V3O86Zt2q1GhqNBrW1tZBIJNwp5buJr6mrq0NGRgYcDgeUSqVX7Ft0OBwoLS3lVg2vXr8Og0gEvVSKcokENQIBwkQiiBvia/g3HESprazEL9MexcK33kNUj9uHD+/7x9cIs5rw4coVd33dt4uOaU/ODMHExERs3brVqzIECfEEKgYJ6QSc+6I2b96M++6777b3bTwqT6VSIS0tzetG5bWU0WjkVg11Oh0XX+PMoWtuW7Kqqgrp6encKpa3rp7W1taisLCQKw41JhN0cjkMDIMKhgF4PC6+hpFIkL78XYzuHY/44aOa9fM3v/My1r7/39wp3NZoSXRMW8rIyMDDDz+MOXPmYPXq1V4Rv0KIp1ExSAi5rfLychw8eJCLr6moqMC4ceO4+BpfOHzSmN1uh8Fg4IrDqqoql/gahmGaXKFSq9U4deoUevbs2WZB3+7AsiwMBgNXGBYVFUEfHMzF11TweChZ/t9Y/fVPzX5NhRfOIu/AP/Hl+s9bdU35+fltGh3TXM4Mwffffx8vvfSS256XEG9HxSAhpNkaj8pTqVQ4evQoNyovOTkZY8aMabdRee3FGV/jHG0G4Kb4msLCQpw/fx7x8fHtNrrLXWw2G65du8YVhwePHIEgtg+mznm2RT/no/n/hSP797ZodbRxdIxSqXTroYy///3veOmll7B161Y89thjbnteQnwBFYPEp23YsAFr1qxBWVkZ4uPjsW7dOiQlJd3xcT/++COeeOIJTJs2Dbt3727/C+2gGo/KS01NbbdRee7izKBzrhpWVFQgMDAQDocDffv2RWxsbIeLGXl/xUrYo3shbugDLXrcliWL8D8b10MqlTbr/jabDVlZWaiurnZrdAzLsvjv//5vfPbZZ9i9ezdGjx7tluclxJd454YXQpph27ZtWLRoETZu3AilUom1a9di4sSJuHjxIhda3JSioiK89tpr7RKR0dncOCrv8uXLXDt58eLFCA8P504ot3ZUnjv5+flBIpFAIpHgnnvuQXp6OkwmE+RyOfLy8nDhwgXIZDJu1bAjTOrp0qUL7Gh5we7n5weHw9Gs+zqjY/z8/DBy5Ei3RcdYrVbMnz8f+/fvx7Fjx9C/f3+3PC8hvoZWBonPUiqVSExMxPr16wHUH3zo1q0bFi5ciLfeeqvJx9jtdowaNQrz5s3D0aNHUVFRQSuD7cQ5Ks+5augclecsDpszKs9TjEYj0tPTwefzkZCQgC5duoBlWVRXV3Oh1waDASEhIS5zlL31QMnt/LhtG45euooHH/+vFj3uo/lP4sh+1R1fs6eiY4xGIx5//HFcv34dqampiI6OdsvzEuKLqBgkPslisYDH42HHjh149NFHudvnzJmDiooK/Pzzz00+bvny5Thz5gx27dqFuXPnUjHoRo1H5R08eBACgYBrJ984Ks+TdDodMjIy0L17d/Tv3/+WBaszvsbZUjabzZBKpdyqYVhYmNcWu43V1NRg/JSpePXL75v9mGt5l5C963/wzd+33PZ+noqO0Wg0mDJlCoRCIXbt2gWRSOSW5yXEV/ne11hCUP+Bbbfbb5qaoVAokJub2+Rjjh07hq+++orGInlIjx49MH/+fMyfP99lVN6KFSswa9YsJCUlcSeUExISPLI378qVK8jJycGAAQMQGxt72/sGBgYiIiKCOw1rMpm4wvDixYsIDAzkCsPw8HC3tUZbKjQ0FAmD4pGbdRJ9Bic26zEH/3cr3nv95dvex1PRMc4MwaSkJHzzzTc+F4NEiCdQMUg6herqajz55JPYsmVLu89YJXcWFBSEsWPHYuzYsVi9ejWKi4uxb98+pKam4tNPP0VAQAAmTJiA5ORkTJw4sd1H5bEsi/Pnz+PKlStQKpWQy+Ut/hl8Ph89evRAjx494HA4YDAYoFarcfnyZWRmZkIsFkOhUCA8PBxisdir8u2Wvv0Wpv55OmTvfQxZ5O3bqUd/2YGIMB7i4+NveR9PRcdkZGRgypQpeOqpp7Bq1Sqv+jsmxJtRm5j4pJa2ibOzs2/ar+Tc/O7v74+LFy/inntuP3mBuIfNZkNGRgYXX5OZmcmNyktOTsawYcPadG+ezWZDZmYmd8q1PQ6F1NbWcquGWq0WLMu6xNe0Zo5wWysoKMCsOU/hwdlPY9CocTetzFZXlGPfP75GF3Mlvtq0scmVW09Gx/zrX//CE088QRmChLQCFYPEZymVSiQlJWHdunUA6ou77t27Y8GCBTcdIKmtrUVeXp7LbUuWLEF1dTU+++wz9O7d22vbeJ2dVqvFvn37mhyVN3HixLvK/aupqUFaWhqCgoKQmJjoln8DLMuioqKCKw7Ly8shEAi4wlAqlXosvqaiogJfbNqEX/6dil6DhkAUHgG71YpruedgN1dh/jNPY9ojjzS5989T0TEAsHnzZrzyyiv49ttvMX36dLc9LyEdBRWDxGdt27YNc+bMwaZNm5CUlIS1a9fip59+Qm5uLhQKBVJSUhAdHY2VK1c2+Xg6QOJ7HA4HTp8+zcXXpKWloU+fPtwJ5ZaMyisvL0d6ejoiIiIwcOBAj7UULRaLyxxlq9UKmUwGuVwOhUJx0xxhd7Db7Th58iTUajWCg4PRu3fv206aaRwdo1Qq3fbFimVZLF++HOvXr8fPP/9McVGEtBLtGSQ+a8aMGdBqtVi2bBnKysowaNAgqFQqbn/Z1atXac9QB+Pv74+EhAQkJCRgyZIl3Kg8lUqFOXPmoLy8HOPGjeOKw1sVMGfPnkVRURH69u2Lnj17evTUb1BQEKKiohAVFXVTfM358+e5+Jrw8HDIZDJ06dKl3a8pICAAQ4cObdZ9ndExIpEIgwcPdtuqptVqxV//+lccOHAAx44dQ79+/dzyvIR0RLQySAjpEJozKi8kJAQvv/wyfvrpJy4+xpvZbDbo9XqupWwymSCRSLjiUCQSebSQ9VR0jDNDsLi4GHv27KEMQULuEhWDhJAOyWg04tdff+VCr0tKSiASiVBTU4PNmzdj5syZPpED2JjZbOZWDXU6HQICArh2slwud2uMijM6pl+/frdtIbc1tVqNKVOmQCQSYefOnZQhSEgboGKQENLhlZaWYtKkSaisrERMTAzS09O5UXnJycl48MEHvX5U3o2c8TXOVcPKykqIxWJu1ZBhmHbbJuGMjklISEBkZGS7PEdTLl26hEmTJmHo0KH45ptv6NAXIW2ENlQRQjq0M2fOYOjQoRgwYAAuXLiAQ4cOwWAwYPPmzeDxeFi8eDGkUinGjBmDVatWITs7G77wHdnf3x8ymQz9+vXDmDFjMHHiRPTs2RNmsxkZGRlITU1FRkYGioqKYDab2+Q5WZZFTk4OLl++jBEjRri1EExLS8Pw4cPxl7/8Bd9//73HCsENGzYgNjYWISEhUCqVyMjIuOV9t2zZgpEjR4JhGDAMg/Hjx9/2/oR4Cq0MEkI6rHPnzmHYsGF48803sXjx4lu2hYuKiri9ht48Kq+5moqv4fP5XOh1a+Jr7Ha7Sx6jO6Nj/vnPf+KJJ57AihUr8OKLL7rteW+0bds2pKSkYOPGjVAqlVi7di22b9+OixcvIjw8/Kb7z549GyNGjMDw4cMREhKC1atXY9euXTh37hztcyRehYpBQkiHZbfbcfz48RZFjlgsFhw/fpyLrzl79iySkpK4E8qeGpV3N6xWK7RaLVcc1tXVQSaTcS1lgUBw2/2TnoqOAYBNmzbh1Vdfxbfffou//OUvbnvepiiVSiQmJmL9+vUA6lv13bp1w8KFC2/KNm2K3W4HwzBYv349UlJS2vtyCWk2KgYJIeQ2SkpKsHfvXqhUKuzbt8/to/LaGsuyMBqNXGGo0+kQHBzMFYZyudwlvsZT0TGNMwR/+eUXPPDAA2553ltp6dSjplRXVyM8PBzbt2/Hww8/3I5XS0jLUDFICCHN1NSovPj4eEyaNAnJyckYOnSoW3IA25Ldboder+dCrxvH1wQHB+PcuXOIiYlxa3SMM0PQmSHZt29ftzzv7ZSUlCA6OhrHjx/HsGHDuNvfeOMNHD58GOnp6Xf8Gc8//zz27t2Lc+fOISQkpD0vl5AWoQMkhPiQlmxeB+rHi73wwguIjIzkJkns2bPHTVfb8QQGBmL48OH429/+hoyMDJSVleHVV1/F1atX8Ze//AUymQx/+ctf8Pe//x3Xrl3z9OU2S0BAAMLDwxEXF4cHH3wQ48ePR9euXVFWVobs7Gw4HA7U1tbi+vXrqKura/frMRqNeOSRR5CZmYkTJ054RSHYFlatWoUff/wRu3btokKQeB2aQEKIj9i2bRsWLVrksnl94sSJt9y8brFY8NBDDyE8PBw7duxAdHQ0rly5ArFY7P6L76Dkcjlmz56N2bNnc6PyVCoVtm7divnz53Oj8pKTkzFy5Ei35gC2Fo/Hg91uR1VVFYYMGYKQkBBoNBrk5+cjKysLIpGIaylLJJI2ja8pKyvDlClTwDAMjhw54lUZgjKZDAEBAVCr1S63q9VqRERE3PaxH330EVatWoUDBw5g4MCB7XmZhLQKtYkJ8REt3by+ceNGrFmzBrm5uT7XuuwIGo/KU6lULqPykpOTcc8993j6Em/inOJSXFwMpVIJhmFc/ryuro7ba6jVamG32yGXy7nikMfjtfq5L126hOTkZAwfPhxff/21V2YIKpVKJCUlYd26dQDqfwe7d++OBQsW3PIAyYcffogPPvgAe/fubfaIP0LcjYpBQnxAazavT548GRKJBDweDz///DPkcjlmzZqFN9980+dOw/o6lmVx7tw57oTy0aNHERMTw+01HDNmzF0VUm3BGR1TVVWFYcOG3TE6hmVZVFZWcsWhwWAAn893maPc3H9naWlpePjhh/HMM89gxYoVXjtTfNu2bZgzZw42bdqEpKQkrF27Fj/99BNyc3OhUCiQkpKC6OhorFy5EgCwevVqLFu2DD/88ANGjBjB/RyBQACBQOCpl0HITahNTIgP0Ol0sNvtN51cVSgUyM3NbfIxBQUF+PXXXzF79mzs2bMHeXl5eP7552G1WrF8+XJ3XDZp4OfnhwEDBmDAgAF4/fXXYTQa8Z///Aepqal44YUXUFpailGjRnHxNX369HHrqLzG0TGjRo1q1qqcn58fxGIxxGIxevfuDavVCp1OB41Gg99//x11dXWQSqXcqDyhUNjka/rll18wa9YsrFq1CgsWLGiPl9dmZsyYAa1Wi2XLlqGsrAyDBg2CSqXifi+vXr3qUsh++eWXsFgsmD59usvPWb58Od599113Xjoht0Urg4T4gNacZOzduzdqa2tRWFjIrdB88sknWLNmDUpLS9127eT2WJbF5cuXuXbyf/7zH7eOymuP6Jgb42v0ej2CgoJw8eJFhISE4NFHH4VcLucyBL/77jv8+c9/boNXQwhpDVoZJMQHtGbzemRkJLp06eLy4d63b1+UlZXBYrF45Z6szsjPzw+9e/dG79698eKLL6KmpgZHjhyBSqXC4sWLkZeXh+HDh3Mt5fj4+DZbNTQYDEhPT0f37t3bNDrGz88PQqEQQqEQ99xzDxdfc/ToUXz//feYP38+ZDIZqqqqsG7dOpetD4QQ9/POjRmEEBdBQUFISEjAwYMHudscDgcOHjzoslLY2IgRI5CXlweHw8HddunSJURGRlIh6MVCQ0MxceJEfPrpp7hw4QIuX76MWbNmIS0tDSNHjkRUVBTmzp2Lbdu2wWAwtPp5SkpKcPz4cdx3333o379/u7alnfE17733Hi5fvoxp06bBarVi1KhReO2116BQKDB79mx89913KCsra7frIIQ0jdrEhPiIlm5ev3btGvr37485c+Zg4cKFuHz5MubNm4cXX3wR77zzjodfDWkN56g8Z0v57NmzSExM5FrKQ4YMaVabNz8/HxcuXEBCQgIiIyPdcOX1qqur8dhjj6GsrAx79uxBVFQUbDYb0tPTuSkvmZmZ2Lt3L8aPH++26yKks6NikBAfsn79eqxZs4bbvP75559DqVQCAMaMGYPY2Fhs3bqVu/+JEyfwyiuvIDs7G9HR0Xj66afpNHEHcrtReRMmTLhpC4Hdbsc333yD6OhoDB069KbomPbUOENw586dt9wHqdPpwOfzERoa6rZrI6Szo2KQkBvY7XaMHDkSERER2LlzJ3d7ZWUlBgwYgJSUFHzwwQcevEJCbmaz2XDy5EkuvsY5Ks95QnnAgAH485//zIVHy2Qyt13bxYsXkZycjAceeABfffUVbVMgxMtQMUhIEy5duoRBgwZhy5YtmD17NgAgJSUFv//+O06ePEkfZsTrabVa7N+/HyqVCnv27EF5eTkEAgGWLFmCmTNnolu3bm65jhMnTmDq1Kl49tlnsWLFCrdG5hBCmoeKQUJu4fPPP8e7776Lc+fOISMjA4899hhOnjyJ+Ph4T18aIc2Wl5eHSZMmITY2FsOHD8evv/6KEydOuGVU3s8//4zZs2dj9erVeOGFF9r85xNC2gYVg4TcAsuyGDduHAICApCTk4OFCxdiyZIlnr4sQprtxIkTeOSRRzB37lysXr2aC0SuqKjAgQMHXEbljR07louvaYtReV9++SVef/11fP/99/jTn/501z+PENJ+qBgk5DZyc3PRt29fxMXFISsrC4GBFM1JfINOp0OvXr3w/vvv33ayh3NUnrMwPHLkCGJiYri9hi0dlceyLJYsWYKNGzfil19+cRnDRgjxTlQMEnIbb7zxBjZs2AB/f3/k5OQgNjbW05dESLNdvXoV3bt3b9FjnKPyVCoVUlNTUVJSwo3KS05ORt++fW+5789qteKZZ57B4cOHkZqair59+7bFyyCEtDMqBgm5hePHj2P06NHYt28f3n//fQDAgQMHaAM86TRaMiqvuroa06dPh0ajwZ49e9yaX0gIuTs0gYSQJpjNZsydOxfPPfccxo4di6+++goZGRnYuHGjpy+tU9qwYQNiY2MREhICpVKJjIyM295/7dq1uO+++xAaGopu3brhlVdeQW1trZuutuNwjsp78cUXsWfPHhgMBmzZsgU8Hg+LFy+GVCrF6NGjsXjxYiiVSrAsi8OHD1MhSIiPoZVBQprw0ksvYc+ePfj999+5/VKbNm3Ca6+9Ru1iN9u2bRtSUlKwceNGKJVKrF27Ftu3b8fFixcRHh5+0/1/+OEHzJs3D19//TWGDx+OS5cuYe7cuZg5cyY++eQTD7yCjquoqAh79+7FF198AZvNhtOnT1PsEiE+iIpBQm5w+PBhPPjggzh06BAeeOABlz+bOHEibDYbtYvdSKlUIjExEevXrwdQP5O5W7duWLhwId56662b7r9gwQJcuHDBZY7zq6++ivT0dBw7dsxt192ZOD9G6HeCEN9EbWJCbjB69GjYbLabCkEA2Lt3Lw4ePEgfem5isViQmZnpMqfW398f48ePx4kTJ5p8zPDhw5GZmcm1kgsKCrBnzx5MnjzZLdfcGfn5+dHvBCE+jHIyCCFeS6fTwW63Q6FQuNyuUCiQm5vb5GNmzZoFnU6HBx54ACzLwmazYf78+Vi8eLE7LpkQQnwOrQwSQjqUQ4cOYcWKFfjiiy+QlZWFnTt34t///jfee+89T18aIYR4JVoZJIR4LZlMhoCAAKjVapfb1Wo1IiIimnzM0qVL8eSTT+KZZ54BAMTFxcFkMuH//b//h3feeYebwkEIIaQevSsSQrxWUFAQEhISXA6DOBwOHDx4EMOGDWvyMWaz+aaCLyAgAMAfBx0IIYT8gVYGCSFebdGiRZgzZw6GDBmCpKQkrF27FiaTCU899RQAICUlBdHR0Vi5ciUAYOrUqfjkk09w//33Q6lUIi8vD0uXLsXUqVO5opAQQsgfqBgkhHi1GTNmQKvVYtmyZSgrK8OgQYOgUqm4QyVXr151WQlcsmQJ/Pz8sGTJEhQXF0Mul2Pq1Kn44IMPPPUSCCHEq1HOICGEEK+2YcMGrFmzBmVlZYiPj8e6deuQlJR0y/tv374dS5cuRVFREe69916sXr2aooUIuQ3aM0gIIcRrbdu2DYsWLcLy5cuRlZWF+Ph4TJw4ERqNpsn7Hz9+HE888QSefvppnD59Go8++igeffRRnD171s1XTojvoJVBQgghXqulE2hmzJgBk8mEf/3rX9xtQ4cOxaBBg2i2OCG3QCuDhBBCvFJrJtCcOHHC5f5A/RjJW92fEELFICGEEC91uwk0ZWVlTT6mrKysRfcnhFAxSAghhBDSqVExSAghxCu1ZgJNREREi+5PCKFikBBCiJdqzQSaYcOGudwfAPbv33/L+xNCqBgkhBCvdeTIEUydOhVRUVHw8/PD7t277/iYQ4cOYfDgwQgODkavXr2wdevWdr/O9rRo0SJs2bIF3377LS5cuIDnnnvupgk0b7/9Nnf/l156CSqVCh9//DFyc3Px7rvv4tSpU1iwYIGnXgIhXo+KQUII8VImkwnx8fHYsGFDs+5fWFiIKVOmYOzYscjOzsbLL7+MZ555Bnv37m3nK20/M2bMwEcffYRly5Zh0KBByM7OvmkCTWlpKXf/4cOH44cffsDmzZsRHx+PHTt2YPfu3RgwYICnXgIhXo9yBgkhxAf4+flh165dePTRR295nzfffBP//ve/XQKWZ86ciYqKCqhUKjdcJSHEF9HKICGEdBCUsUcIaQ0qBgkhpIO4VcZeVVUVampqPHRVhBBvR8UgIYQQQkgnRsUgIYR0ELfK2AsLC0NoaKiHrooQ4u2oGCSEkA6CMvYIIa1BxSAhhHgpo9GI7OxsZGdnA6iPjsnOzsbVq1cBAG+//TZSUlK4+8+fPx8FBQV44403kJubiy+++AI//fQTXnnlFU9cPiHER1C0DCGEeKlDhw5h7NixN90+Z84cbN26FXPnzkVRUREOHTrk8phXXnkF58+fR9euXbF06VLMnTvXfRdNCPE5VAwSQgghhHRi1CYmhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnEqBgkhBBCCOnE/j9fVKR3kto4BgAAAABJRU5ErkJggg==", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Dimension 2: 4 cells\n", - "Dimension 3: 1 cells\n", - "\n", - "Total embedding dimension: 3\n" - ] - } - ], - "source": [ - "# Create a 3D tetrahedron with 0, 1, 2, and 3-cells\n", - "K_tetra = EmbeddedComplex()\n", - "\n", - "# Add vertices (0-cells)\n", - "vertices = {\n", - " 'A': [0, 0, 0],\n", - " 'B': [1, 0, 0],\n", - " 'C': [0.5, 0.866, 0],\n", - " 'D': [0.5, 0.289, 0.816] \n", - "}\n", - "\n", - "for name, coord in vertices.items():\n", - " K_tetra.add_node(name, coord)\n", - "\n", - "# Add edges (1-cells) - all pairs\n", - "edges = [('A', 'B'), ('A', 'C'), ('A', 'D'), ('B', 'C'), ('B', 'D'), ('C', 'D')]\n", - "K_tetra.add_edges_from(edges)\n", - "\n", - "# Add faces (2-cells) - all triangular faces\n", - "faces = [['A', 'B', 'C'], ['A', 'B', 'D'], ['A', 'C', 'D'], ['B', 'C', 'D']]\n", - "for face in faces:\n", - " K_tetra.add_cell(face, dim=2) # Explicitly specify dimension\n", - "\n", - "# Add volume (3-cell) - the entire tetrahedron\n", - "K_tetra.add_cell(['A', 'B', 'C', 'D'], dim=3)\n", - "\n", - "# Plot the tetrahedron\n", - "fig = plt.figure(figsize=(10, 8))\n", - "ax = fig.add_subplot(111, projection='3d')\n", - "K_tetra.plot(ax=ax, face_alpha=0.3, face_color='cyan', node_size=100)\n", - "ax.set_title('Tetrahedron with All Cell Types\\n0-cells: 4, 1-cells: 6, 2-cells: 4, 3-cells: 1')\n", - "plt.show()\n", - "\n", - "# Display cell counts\n", - "for dim in sorted(K_tetra.cells.keys()):\n", - " print(f\"Dimension {dim}: {len(K_tetra.cells[dim])} cells\")\n", - " \n", - "print(f\"\\nTotal embedding dimension: {K_tetra.dim}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## ECT Computation with Higher-Dimensional Cells\n", - "\n", - "The ECT computation now properly includes all cell dimensions in the Euler characteristic calculation:\n", - "\n", - "**χ = Σ(-1)^k × |k-cells below threshold|**\n", - "\n", - "Let's see how this works:" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ECT result shape: (8, 20)\n", - "Directions: 8 directions in 3D\n", - "Thresholds: 20 threshold values\n" - ] - }, - { - "data": { - "image/png": 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Compute ECT for the tetrahedron\n", - "ect = ECT(num_dirs=8, num_thresh=20)\n", - "result = ect.calculate(K_tetra)\n", - "\n", - "print(f\"ECT result shape: {result.shape}\")\n", - "print(f\"Directions: {len(result.directions)} directions in {K_tetra.dim}D\")\n", - "print(f\"Thresholds: {len(result.thresholds)} threshold values\")\n", - "\n", - "# Plot the ECT matrix\n", - "fig, ax = plt.subplots(figsize=(10, 6))\n", - "result.plot()\n", - "plt.title('ECT of Tetrahedron (includes 3-cells in computation)')\n", - "plt.show()\n", - "\n", - "# Show a single direction\n", - "\n", - "single_direction = ECT(num_thresh=20, directions=Directions.from_vectors([[1, 0, 0]])).calculate(K_tetra)\n", - "fig, ax = plt.subplots(figsize=(8, 5))\n", - "ax.plot(single_direction.thresholds, single_direction[0], 'b-', marker='o', linewidth=2)\n", - "ax.set_xlabel('Threshold')\n", - "ax.set_ylabel('Euler Characteristic')\n", - "ax.set_title('ECT Curve for Single Direction (v=[1, 0, 0])')\n", - "ax.grid(True, alpha=0.3)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "You can also restrict self-intersections by using the 'validate_embeddings' argument. Currently without checks we can add a node inside of our tetrahedron." - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Unexpected exception formatting exception. Falling back to standard exception\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Traceback (most recent call last):\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/interactiveshell.py\", line 3548, in run_code\n", - " exec(code_obj, self.user_global_ns, self.user_ns)\n", - " File \"/var/folders/81/3x5xj5kx4ys30p1c2z55bhbw0000gn/T/ipykernel_80902/4266954845.py\", line 1, in \n", - " K_valid = K_tetra.copy()\n", - " ^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/networkx/classes/graph.py\", line 1642, in copy\n", - " G.add_nodes_from((n, d.copy()) for n, d in self._node.items())\n", - " File \"/Users/yayub/Code/ect/src/ect/embed_complex.py\", line 177, in add_nodes_from\n", - " File \"/Users/yayub/Code/ect/src/ect/embed_complex.py\", line 120, in wrapper\n", - " )\n", - " \n", - " File \"/Users/yayub/Code/ect/src/ect/embed_complex.py\", line 142, in wrapper\n", - " def wrapper(self, *args, **kwargs):\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/Code/ect/src/ect/embed_complex.py\", line 157, in add_node\n", - " return wrapper\n", - " ^^^^^^^^^^^\n", - "TypeError: float() argument must be a string or a real number, not 'dict'\n", - "\n", - "During handling of the above exception, another exception occurred:\n", - "\n", - "Traceback (most recent call last):\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/interactiveshell.py\", line 2142, in showtraceback\n", - " stb = self.InteractiveTB.structured_traceback(\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py\", line 1435, in structured_traceback\n", - " return FormattedTB.structured_traceback(\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py\", line 1326, in structured_traceback\n", - " return VerboseTB.structured_traceback(\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py\", line 1173, in structured_traceback\n", - " formatted_exception = self.format_exception_as_a_whole(etype, evalue, etb, number_of_lines_of_context,\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py\", line 1088, in format_exception_as_a_whole\n", - " frames.append(self.format_record(record))\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py\", line 970, in format_record\n", - " frame_info.lines, Colors, self.has_colors, lvals\n", - " ^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py\", line 792, in lines\n", - " return self._sd.lines\n", - " ^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/utils.py\", line 144, in cached_property_wrapper\n", - " value = obj.__dict__[self.func.__name__] = self.func(obj)\n", - " ^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/core.py\", line 734, in lines\n", - " pieces = self.included_pieces\n", - " ^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/utils.py\", line 144, in cached_property_wrapper\n", - " value = obj.__dict__[self.func.__name__] = self.func(obj)\n", - " ^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/core.py\", line 681, in included_pieces\n", - " pos = scope_pieces.index(self.executing_piece)\n", - " ^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/utils.py\", line 144, in cached_property_wrapper\n", - " value = obj.__dict__[self.func.__name__] = self.func(obj)\n", - " ^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/core.py\", line 660, in executing_piece\n", - " return only(\n", - " ^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/executing/executing.py\", line 116, in only\n", - " raise NotOneValueFound('Expected one value, found 0')\n", - "executing.executing.NotOneValueFound: Expected one value, found 0\n" - ] - } - ], - "source": [ - "K_valid = K_tetra.copy()\n", - "\n", - "K_valid.add_node('E', [0.5, 0.289, 0.204])\n", - "K_valid.add_cell(['E', 'B'], dim=1)\n", - "\n", - "\n", - "\n", - "# Display cell counts\n", - "print(\"4D Simplex Cell Counts:\")\n", - "for dim in sorted(K_valid.cells.keys()):\n", - " print(f\" {dim}-cells: {len(K_valid.cells[dim])}\")\n", - "\n", - "# Plot (showing 3D projection)\n", - "fig = plt.figure(figsize=(10, 8))\n", - "ax = fig.add_subplot(111, projection='3d')\n", - "K_valid.plot(ax=ax, face_alpha=0.1, node_size=80)\n", - "ax.set_title('4D Simplex (5 vertices, cells up to dimension 4)')\n", - "plt.show()\n", - "\n", - "# Compute ECT\n", - "ect_4d = ECT(num_dirs=6, num_thresh=15)\n", - "result_4d = ect_4d.calculate(K_valid)\n", - "\n", - "fig, ax = plt.subplots(figsize=(10, 6))\n", - "result_4d.plot()\n", - "plt.title('ECT of 4D Simplex\\n(alternating sum includes all dimensions 0-4)')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Understanding ECT with Projection Visualization\n", - "\n", - "Let's visualize how the ECT computation works by showing projection values:" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Create a simple 2D example for visualization\n", - "K_viz = EmbeddedComplex()\n", - "\n", - "# Square with center point\n", - "K_viz.add_node('A', [-1, -1])\n", - "K_viz.add_node('B', [1, -1])\n", - "K_viz.add_node('C', [1, 1])\n", - "K_viz.add_node('D', [-1, 1])\n", - "K_viz.add_node('E', [0, 0]) # center\n", - "\n", - "# Add edges\n", - "edges = [('A', 'B'), ('B', 'C'), ('C', 'D'), ('D', 'A'), # boundary\n", - " ('A', 'E'), ('B', 'E'), ('C', 'E'), ('D', 'E')] # to center\n", - "K_viz.add_edges_from(edges)\n", - "\n", - "# Add triangular faces\n", - "faces = [['A', 'B', 'E'], ['B', 'C', 'E'], ['C', 'D', 'E'], ['D', 'A', 'E']]\n", - "for face in faces:\n", - " K_viz.add_face(face)\n", - "\n", - "# Visualization function\n", - "def plot_with_projections(K, theta, ax):\n", - " \"\"\"Plot complex with nodes colored by projection values\"\"\"\n", - " direction = np.array([np.sin(theta), -np.cos(theta)])\n", - " node_projections = np.dot(K.coord_matrix, direction)\n", - " \n", - " # Plot edges\n", - " for u, v in K.edges():\n", - " u_idx = K.node_to_index[u]\n", - " v_idx = K.node_to_index[v]\n", - " x = [K.coord_matrix[u_idx, 0], K.coord_matrix[v_idx, 0]]\n", - " y = [K.coord_matrix[u_idx, 1], K.coord_matrix[v_idx, 1]]\n", - " ax.plot(x, y, 'k-', alpha=0.5, linewidth=1)\n", - " \n", - " # Plot faces with transparency\n", - " for face_indices in K.cells.get(2, []):\n", - " face_coords = K.coord_matrix[list(face_indices)]\n", - " face_projection = np.max(node_projections[list(face_indices)])\n", - " ax.fill(face_coords[:, 0], face_coords[:, 1], \n", - " alpha=0.3, color=plt.cm.Blues(0.5))\n", - " \n", - " # Plot nodes colored by projection\n", - " scatter = ax.scatter(K.coord_matrix[:, 0], K.coord_matrix[:, 1], \n", - " c=node_projections, cmap='plasma', s=300, \n", - " edgecolors='black', linewidth=2, zorder=10)\n", - " \n", - " # Add node labels with projection values\n", - " for i, node in enumerate(K.node_list):\n", - " ax.annotate(f'{node}\\n({node_projections[i]:.2f})', \n", - " (K.coord_matrix[i, 0], K.coord_matrix[i, 1]),\n", - " ha='center', va='center', fontsize=9, fontweight='bold',\n", - " bbox=dict(boxstyle='round,pad=0.2', facecolor='white', alpha=0.8))\n", - " \n", - " # Direction arrow\n", - " ax.arrow(0, 0, direction[0]*0.7, direction[1]*0.7,\n", - " head_width=0.1, head_length=0.1, fc='red', ec='red', linewidth=2)\n", - " \n", - " ax.set_xlim(-2, 2)\n", - " ax.set_ylim(-2, 2)\n", - " ax.set_aspect('equal')\n", - " ax.grid(True, alpha=0.3)\n", - " ax.set_title(f'θ = {theta*180/np.pi:.0f}°')\n", - " \n", - " return scatter\n", - "\n", - "# Show projections in multiple directions\n", - "fig, axes = plt.subplots(2, 3, figsize=(15, 10))\n", - "axes = axes.flatten()\n", - "\n", - "thetas = np.linspace(0, 2*np.pi, 6, endpoint=False)\n", - "for ax, theta in zip(axes, thetas):\n", - " scatter = plot_with_projections(K_viz, theta, ax)\n", - "\n", - "# Add shared colorbar\n", - "fig.subplots_adjust(right=0.9)\n", - "cbar_ax = fig.add_axes([0.92, 0.15, 0.02, 0.7])\n", - "fig.colorbar(scatter, cax=cbar_ax, label='Node Projection Values')\n", - "\n", - "plt.suptitle('Complex Colored by Projection Values in Different Directions\\n' + \n", - " 'Red arrows show projection direction, faces use max vertex projection', \n", - " fontsize=14)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Comparing Graph vs. Complex ECT\n", - "\n", - "Let's compare ECT results for the same geometry with and without 2-cells:" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ECT value ranges:\n", - "Graph only: [0, 1]\n", - "With face: [0, 1]\n", - "\n", - "The face contributes +1 to the Euler characteristic when included.\n" - ] - } - ], - "source": [ - "# Create two versions: graph only vs. complex with faces\n", - "K_graph = EmbeddedComplex()\n", - "K_complex = EmbeddedComplex()\n", - "\n", - "# Same vertices and edges for both\n", - "vertices = {'A': [0, 0], 'B': [2, 0], 'C': [1, 1.732]}\n", - "edges = [('A', 'B'), ('B', 'C'), ('C', 'A')]\n", - "\n", - "for K in [K_graph, K_complex]:\n", - " for name, coord in vertices.items():\n", - " K.add_node(name, coord)\n", - " K.add_edges_from(edges)\n", - "\n", - "# Add face only to the complex version\n", - "K_complex.add_face(['A', 'B', 'C'])\n", - "\n", - "# Compute ECT for both\n", - "ect = ECT(num_dirs=20, num_thresh=30)\n", - "result_graph = ect.calculate(K_graph)\n", - "result_complex = ect.calculate(K_complex)\n", - "\n", - "# Plot comparison\n", - "fig, axes = plt.subplots(2, 2, figsize=(15, 10))\n", - "\n", - "# Visualizations\n", - "K_graph.plot(ax=axes[0,0], with_labels=True, node_size=400)\n", - "axes[0,0].set_title('Graph Only (no 2-cells)')\n", - "\n", - "K_complex.plot(ax=axes[0,1], with_labels=True, node_size=400, \n", - " face_alpha=0.3, face_color='lightblue')\n", - "axes[0,1].set_title('Complex with 2-cell (face)')\n", - "\n", - "# ECT comparisons\n", - "result_graph.plot(ax=axes[1,0])\n", - "axes[1,0].set_title('ECT: Graph Only\\n(χ = vertices - edges)')\n", - "\n", - "result_complex.plot(ax=axes[1,1])\n", - "axes[1,1].set_title('ECT: Complex with Face\\n(χ = vertices - edges + faces)')\n", - "\n", - "plt.tight_layout()\n", - "plt.show()\n", - "\n", - "# Show numerical difference\n", - "print(\"ECT value ranges:\")\n", - "print(f\"Graph only: [{result_graph.min()}, {result_graph.max()}]\")\n", - "print(f\"With face: [{result_complex.min()}, {result_complex.max()}]\")\n", - "print(f\"\\nThe face contributes +1 to the Euler characteristic when included.\")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "dataexp", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/docs/.doctrees/nbsphinx/notebooks/Tutorial-ExactECT.ipynb b/docs/.doctrees/nbsphinx/notebooks/Tutorial-ExactECT.ipynb deleted file mode 100644 index 7ec6520..0000000 --- a/docs/.doctrees/nbsphinx/notebooks/Tutorial-ExactECT.ipynb +++ /dev/null @@ -1,215 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Tutorial for exact ECT computation \n", - "\n", - "*Warning: This is a work in progress. Proceed at your own risk.*\n", - "\n", - "The goal of this section is so show available tools for exact computation of the ECT. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from ect import ECT, EmbeddedComplex, create_example_graph\n", - "\n", - "import matplotlib.pyplot as plt\n", - "from matplotlib.patches import Circle\n", - "import numpy as np\n", - "import networkx as nx\n", - "\n", - "# Note: EmbeddedGraph and EmbeddedCW are now unified into EmbeddedComplex\n", - "# For backward compatibility, you can still use:\n", - "# from ect import EmbeddedGraph, EmbeddedCW" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can use the `EmbeddedComplex` class (which unifies the old `EmbeddedGraph` and `EmbeddedCW` classes) to find the angle normal to any pair of vertices in the graph, whether or not there is a connecting edge. Setting `angle_labels_circle=True` in the plotting command will try to draw these on the circle. Note that this doesn't tend to do well for large inputs, but can be helpful for small examples." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Super simple graph using the unified EmbeddedComplex class\n", - "G = EmbeddedComplex()\n", - "G.add_node('A', 0,0)\n", - "G.add_node('B', 1,0)\n", - "G.add_node('C', 2,1)\n", - "G.add_node('D', 1,2)\n", - "G.add_edge('A', 'B')\n", - "G.add_edge('B', 'D')\n", - "G.add_edge('D', 'C')\n", - "\n", - "fig, ax = plt.subplots()\n", - "G.plot(ax = ax)\n", - "G.plot_angle_circle(ax = ax)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "G = create_example_graph(centered=True)\n", - "G.rescale_to_unit_disk()\n", - "\n", - "\n", - "fig, ax = plt.subplots()\n", - "G.plot(ax = ax)\n", - "G.plot_angle_circle(ax = ax)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can extract the information directly for use in computation. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# If return type is `matrix`, the function returns the matrix of angles and the labels of the angles in the order of the rows/columns in the matrix \n", - "M,Labels = G.get_normal_angle_matrix() # Updated method name\n", - "print(M)\n", - "\n", - "plt.matshow(M)\n", - "plt.xticks(range(len(Labels)), Labels)\n", - "plt.yticks(range(len(Labels)), Labels)\n", - "plt.colorbar()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This can also be returned as a dictionary, with keys given by angles (note the negative angle is not repeated), and value a list of the pairs of vertices associated. Note that in the case of more than one pair of vertices having the same normal angle, it is given as a list of all pairs. " - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{5.497787143782138: [('A', 'B'), ('A', 'F'), ('B', 'F')],\n", - " 5.608444364956034: [('A', 'C')],\n", - " 5.81953769817878: [('A', 'D'), ('F', 'C')],\n", - " 5.034139534781332: [('A', 'E')],\n", - " 5.695182703632018: [('B', 'C')],\n", - " 0.0: [('B', 'D'), ('E', 'F')],\n", - " 3.9269908169872414: [('B', 'E'), ('D', 'F')],\n", - " 2.0344439357957027: [('C', 'D')],\n", - " 2.896613990462929: [('C', 'E')],\n", - " 3.4633432079864352: [('D', 'E')]}" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "angles_dict = G.get_normals_dict()\n", - "angles_dict" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can also get it to return the dictionary with rounded values, as well as to have it include all the opposite angles. " - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{5.5: [('A', 'B'), ('A', 'F'), ('B', 'F')],\n", - " 5.61: [('A', 'C')],\n", - " 5.82: [('A', 'D'), ('F', 'C')],\n", - " 5.03: [('A', 'E')],\n", - " 5.7: [('B', 'C')],\n", - " 0.0: [('B', 'D'), ('E', 'F')],\n", - " 3.93: [('B', 'E'), ('D', 'F')],\n", - " 2.03: [('C', 'D')],\n", - " 2.9: [('C', 'E')],\n", - " 3.46: [('D', 'E')],\n", - " 2.36: [('A', 'B'), ('A', 'F'), ('B', 'F')],\n", - " 2.47: [('A', 'C')],\n", - " 2.68: [('A', 'D'), ('F', 'C')],\n", - " 1.89: [('A', 'E')],\n", - " 2.56: [('B', 'C')],\n", - " 3.14: [('B', 'D'), ('E', 'F')],\n", - " 0.79: [('B', 'E'), ('D', 'F')],\n", - " 5.17: [('C', 'D')],\n", - " 6.04: [('C', 'E')],\n", - " 0.32: [('D', 'E')]}" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "G.get_normals_dict(opposites = True, \n", - " num_rounding_digits=2)" - ] - } - ], - 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a/docs/_modules/ect/directions.html b/docs/_modules/ect/directions.html deleted file mode 100644 index 0766b24..0000000 --- a/docs/_modules/ect/directions.html +++ /dev/null @@ -1,374 +0,0 @@ - - - - - - ect.directions — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - -
- - -
- -
-
-
- -
-
-
-
- -

Source code for ect.directions

-from typing import Optional, Sequence
-from enum import Enum
-
-import numpy as np
-
-
-

-[docs]
-class Sampling(Enum):
-    UNIFORM = "uniform"
-    RANDOM = "random"
-    CUSTOM = "custom"

-
-
-
-

-[docs]
-class Directions:
-    """
-    Manages direction vectors for ECT calculations.
-    Supports uniform, random, or custom sampling of directions.
-
-    Examples:
-        # Uniform sampling in 2D (default)
-        dirs = Directions.uniform(num_dirs=8)
-
-        # Uniform sampling in 3D
-        dirs = Directions.uniform(num_dirs=10, dim=3)
-
-        # Random sampling in 2D
-        dirs = Directions.random(num_dirs=10, seed=42)
-
-        # Custom angles (2D only)
-        dirs = Directions.from_angles([0, np.pi/4, np.pi/2])
-
-        # Custom vectors in any dimension
-        dirs = Directions.from_vectors([(1,0,0), (0,1,0), (0,0,1)])
-    """
-
-

-[docs]
-    def __init__(
-        self,
-        num_dirs: int = 360,
-        sampling: Sampling = Sampling.UNIFORM,
-        dim: int = 2,
-        endpoint: bool = False,
-        seed: Optional[int] = None,
-    ):
-        self.num_dirs = num_dirs
-        self.sampling = sampling
-        self.dim = dim
-        self.endpoint = endpoint
-
-        self._rng = np.random.RandomState(seed)
-        self._thetas = None
-        self._vectors = None
-        self._initialize_directions()

-
-
-    def _initialize_directions(self):
-        """
-        Initialize direction vectors using the chosen sampling strategy.
-        For 2D, the angles may be stored; for n-dim (n>2) the vectors are generated from
-        random normal samples and normalized to lie on the unit sphere.
-        """
-        if self.sampling == Sampling.UNIFORM:
-            if self.dim == 2:
-                self._thetas = np.linspace(
-                    0, 2 * np.pi, self.num_dirs, endpoint=self.endpoint
-                )
-            else:
-                # generate random normal samples and normalize to lie on the unit sphere
-                self._vectors = self._rng.randn(self.num_dirs, self.dim)
-                self._vectors /= np.linalg.norm(self._vectors,
-                                                axis=1, keepdims=True)
-        elif self.sampling == Sampling.RANDOM:
-            if self.dim == 2:
-                self._thetas = self._rng.uniform(0, 2 * np.pi, self.num_dirs)
-                self._thetas.sort()
-            else:
-                self._vectors = self._rng.randn(self.num_dirs, self.dim)
-                self._vectors /= np.linalg.norm(self._vectors,
-                                                axis=1, keepdims=True)
-
-

-[docs]
-    @classmethod
-    def uniform(
-        cls,
-        num_dirs: int = 360,
-        dim: int = 2,
-        endpoint: bool = False,
-        seed: Optional[int] = None,
-    ) -> "Directions":
-        """
-        Factory method for uniform sampling.
-
-        Parameters:
-            num_dirs: Number of direction vectors.
-            dim: Dimension of the space (default 2).
-            endpoint: Whether to include the endpoint (for 2D angles).
-            seed: Optional random seed.
-        """
-        return cls(num_dirs, Sampling.UNIFORM, dim, endpoint, seed)

-
-
-

-[docs]
-    @classmethod
-    def random(
-        cls, num_dirs: int = 360, dim: int = 2, seed: Optional[int] = None
-    ) -> "Directions":
-        """
-        Factory method for random sampling.
-
-        Parameters:
-            num_dirs: Number of direction vectors.
-            dim: Dimension of the space.
-            seed: optional random seed.
-        """
-        return cls(num_dirs, Sampling.RANDOM, dim, seed=seed)

-
-
-

-[docs]
-    @classmethod
-    def from_angles(cls, angles: Sequence[float]) -> "Directions":
-        """
-        Create an instance for custom angles (2D only).
-        """
-        instance = cls(len(angles), Sampling.CUSTOM, dim=2)
-        instance._thetas = np.array(angles)
-        return instance

-
-
-

-[docs]
-    @classmethod
-    def from_vectors(cls, vectors: Sequence[tuple]) -> "Directions":
-        """
-        Create an instance from custom direction vectors.
-        Works in any number of dimensions.
-        """
-        vectors = np.array(vectors, dtype=float)
-        norms = np.linalg.norm(vectors, axis=1, keepdims=True)
-        if np.any(norms == 0):
-            raise ValueError("Zero-magnitude vectors are not allowed")
-        normalized = vectors / norms
-        instance = cls(len(vectors), Sampling.CUSTOM, dim=vectors.shape[1])
-        instance._vectors = normalized
-        if instance.dim == 2:
-            instance._thetas = np.arctan2(normalized[:, 1], normalized[:, 0])
-        return instance

-
-
-    @property
-    def thetas(self) -> np.ndarray:
-        """Get the angles for 2D directions. Raises an error if dim > 2."""
-        if self.dim != 2:
-            raise ValueError(
-                "Angle representation is only available for 2D directions."
-            )
-        if self._thetas is None:
-            # Compute the angles from the vectors.
-            self._thetas = np.arctan2(self.vectors[:, 1], self.vectors[:, 0])
-        return self._thetas
-
-    @property
-    def vectors(self) -> np.ndarray:
-        """Get unit direction vectors.
-        For 2D, they are computed from thetas if not already created.
-        For n-dim (n>2), they should be available.
-        """
-        if self._vectors is None:
-            if self.dim == 2:
-                self._vectors = np.column_stack(
-                    (np.cos(self._thetas), np.sin(self._thetas))
-                )
-            else:
-                raise ValueError(
-                    "Direction vectors for dimensions >2 should be generated during initialization."
-                )
-        return self._vectors
-
-    def __len__(self) -> int:
-        return self.num_dirs
-
-    def __getitem__(self, idx) -> np.ndarray:
-        """Return the direction vector at index idx."""
-        return self.vectors[idx]

-
-
- -
-
- -
-
-
-
- - - - - - - \ No newline at end of file diff --git a/docs/_modules/ect/ect.html b/docs/_modules/ect/ect.html deleted file mode 100644 index 1adced2..0000000 --- a/docs/_modules/ect/ect.html +++ /dev/null @@ -1,424 +0,0 @@ - - - - - - ect.ect — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - -
- - -
- -
-
-
- -
-
-
-
- -

Source code for ect.ect

-import numpy as np
-from numba import prange, njit
-from numba.typed import List
-from typing import Optional
-
-from .embed_complex import EmbeddedComplex
-from .directions import Directions
-from .results import ECTResult
-
-
-

-[docs]
-class ECT:
-    """
-    A class to calculate the Euler Characteristic Transform (ECT) from an input :any:`EmbeddedComplex`.
-
-    The result is a matrix where entry ``M[i,j]`` is :math:`\chi(K_{a_i})` for the direction :math:`\omega_j` where :math:`a_i` is the ith entry in ``self.thresholds``, and :math:`\omega_j` is the ith entry in ``self.thetas``.
-
-    Attributes
-        num_dirs (int):
-            The number of directions to consider in the matrix.
-        num_thresh (int):
-            The number of thresholds to consider in the matrix.
-        directions (Directions):
-            The directions to consider for projection.
-        bound_radius (float):
-            Either ``None``, or a positive radius of the bounding circle.
-    """
-
-

-[docs]
-    def __init__(
-        self,
-        directions: Optional[Directions] = None,
-        num_dirs: Optional[int] = None,
-        num_thresh: Optional[int] = None,
-        bound_radius: Optional[float] = None,
-        thresholds: Optional[np.ndarray] = None,
-        dtype=np.int32,
-    ):
-        """Initialize ECT calculator with either a Directions object or sampling parameters
-
-        Args:
-            directions: Optional pre-configured Directions object
-            num_dirs: Number of directions to sample (ignored if directions provided)
-            num_thresh: Number of threshold values (required if directions not provided)
-            bound_radius: Optional radius for bounding circle
-            thresholds: Optional array of thresholds
-            dtype: Data type for output array
-        """
-        self.directions = directions
-        self.num_dirs = num_dirs
-        self.num_thresh = num_thresh
-        self.bound_radius = bound_radius
-        self.thresholds = thresholds
-        self.dtype = dtype

-
-
-    def _ensure_directions(self, graph_dim, theta=None):
-        """Ensures directions is a valid Directions object of correct dimension"""
-        if self.directions is None:
-            if self.num_dirs is None:
-                raise ValueError("Either 'directions' or 'num_dirs' must be provided.")
-            self.directions = Directions.uniform(self.num_dirs, dim=graph_dim)
-        elif isinstance(self.directions, list):
-            # if list of vectors, convert to Directions object
-            self.directions = np.array(self.directions)
-            self.directions = Directions.from_vectors(self.directions)
-        elif not isinstance(self.directions, Directions):
-            raise TypeError(
-                "directions must be a Directions object, ndarray, or list of vectors."
-            )
-
-        if theta is not None and graph_dim != 2:
-            raise ValueError(
-                "Theta must be provided for 2D graphs. "
-                "Use 'directions' or 'num_dirs' to specify directions."
-            )
-
-        if self.directions.dim != graph_dim:
-            raise ValueError(
-                "Dimension mismatch: directions dimension does not match graph dimension."
-            )
-
-    def _ensure_thresholds(self, graph, override_bound_radius=None):
-        """Ensures thresholds is a valid 1-dimensional ndarray."""
-
-        # determine if we need to generate thresholds
-        if self.thresholds is None or override_bound_radius is not None:
-            if self.num_thresh is None:
-                raise ValueError(
-                    "Either 'thresholds' or 'num_thresh' must be provided."
-                )
-            # determine the radius based on priority
-            if override_bound_radius is not None:
-                radius = override_bound_radius
-            elif self.bound_radius is not None:
-                radius = self.bound_radius
-            else:
-                radius = graph.get_bounding_radius()
-
-            self.thresholds = np.linspace(-radius, radius, self.num_thresh)
-        else:
-            # validate existing thresholds are valid
-            if not isinstance(self.thresholds, np.ndarray):
-                raise TypeError("thresholds must be a numpy ndarray")
-
-            if self.thresholds.ndim != 1:
-                raise ValueError("thresholds must be a 1-dimensional array")
-
-            self.thresholds = self.thresholds.astype(float)
-
-

-[docs]
-    def calculate(
-        self,
-        graph: EmbeddedComplex,
-        theta: Optional[float] = None,
-        override_bound_radius: Optional[float] = None,
-    ):
-        """Calculate Euler Characteristic Transform (ECT) for a given graph and direction theta
-
-        Args:
-            graph (EmbeddedComplex):
-                The input complex to calculate the ECT for.
-            theta (float):
-                The angle in :math:`[0,2\pi]` for the direction to calculate the ECT.
-            override_bound_radius (float):
-                If None, uses the following in order: (i) the bounding radius stored in the class; or if not available (ii) the bounding radius of the given graph. Otherwise, should be a positive float :math:`R` where the ECC will be computed at thresholds in :math:`[-R,R]`. Default is None.
-        """
-        self._ensure_directions(graph.dim, theta)
-        self._ensure_thresholds(graph, override_bound_radius)
-
-        # override with theta if provided
-        directions = (
-            self.directions if theta is None else Directions.from_angles([theta])
-        )
-
-        simplex_projections = self._compute_simplex_projections(graph, directions)
-
-        ect_matrix = self._compute_directional_transform(
-            simplex_projections, self.thresholds, self.shape_descriptor, self.dtype
-        )
-
-        return ECTResult(ect_matrix, directions, self.thresholds)

-
-
-    def _compute_node_projections(self, coords, directions):
-        """Compute inner products of coordinates with directions"""
-        return np.matmul(coords, directions.vectors.T)
-
-    def _compute_simplex_projections(self, graph: EmbeddedComplex, directions):
-        """Compute projections of each k-cell for all dimensions"""
-        simplex_projections = List()
-        node_projections = self._compute_node_projections(
-            graph.coord_matrix, directions
-        )
-        num_dirs = node_projections.shape[1]
-
-        simplex_projections.append(node_projections)
-
-        all_cells = {0: [(i,) for i in range(len(graph.node_list))]}
-
-        if graph.edge_indices.shape[0] > 0:
-            all_cells[1] = [tuple(edge) for edge in graph.edge_indices]
-        else:
-            all_cells[1] = []
-
-        all_cells.update(graph.cells)
-
-        max_dim = max(all_cells.keys()) if all_cells else 0
-        for dim in range(1, max_dim + 1):
-            cell_projections = self._compute_cell_projections(
-                all_cells.get(dim, []), node_projections, num_dirs
-            )
-            simplex_projections.append(cell_projections)
-
-        return simplex_projections
-
-    def _compute_cell_projections(self, cells, node_projections, num_dirs):
-        """Compute projections for k-cells of any dimension k >= 1"""
-        if len(cells) > 0:
-            return np.array(
-                [
-                    np.max(node_projections[list(cell_indices), :], axis=0)
-                    for cell_indices in cells
-                ]
-            )
-        else:
-            return np.empty((0, num_dirs))
-
-    @staticmethod
-    @njit(parallel=True, fastmath=True)
-    def _compute_directional_transform(
-        simplex_projections_list, thresholds, shape_descriptor, dtype=np.int32
-    ):
-        """Compute ECT by counting simplices below each threshold
-
-        Args:
-            simplex_projections_list: List of arrays containing projections for each simplex type
-                [vertex_projections, edge_projections, face_projections]
-            thresholds: Array of threshold values to compute ECT at
-            dtype: Data type for output array (default: np.int32)
-
-        Returns:
-            Array of shape (num_directions, num_thresholds) containing Euler characteristics
-        """
-        num_dir = simplex_projections_list[0].shape[1]
-        num_thresh = thresholds.shape[0]
-        result = np.empty((num_dir, num_thresh), dtype=dtype)
-
-        sorted_projections = List()
-        for proj in simplex_projections_list:
-            sorted_proj = np.empty_like(proj)
-            for i in prange(num_dir):
-                sorted_proj[:, i] = np.sort(proj[:, i])
-            sorted_projections.append(sorted_proj)
-
-        for j in prange(num_thresh):
-            thresh = thresholds[j]
-            for i in range(num_dir):
-                simplex_counts_list = List()
-                for k in range(len(sorted_projections)):
-                    projs = sorted_projections[k][:, i]
-                    simplex_counts_list.append(
-                        np.searchsorted(projs, thresh, side="right")
-                    )
-                result[i, j] = shape_descriptor(simplex_counts_list)
-        return result
-
-

-[docs]
-    @staticmethod
-    @njit(fastmath=True)
-    def shape_descriptor(simplex_counts_list):
-        """Calculate shape descriptor from simplex counts (Euler characteristic)"""
-        chi = 0
-        for k in range(len(simplex_counts_list)):
-            chi += (-1) ** k * simplex_counts_list[k]
-        return chi

-

-
-
- -
-
- -
-
-
-
- - - - - - - \ No newline at end of file diff --git a/docs/_modules/ect/embed_complex.html b/docs/_modules/ect/embed_complex.html deleted file mode 100644 index d35dcb6..0000000 --- a/docs/_modules/ect/embed_complex.html +++ /dev/null @@ -1,1048 +0,0 @@ - - - - - - ect.embed_complex — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - -
- - -
- -
-
-
- -
-
-
-
- -

Source code for ect.embed_complex

-from collections import defaultdict
-from typing import Dict, List, Tuple, Optional, Union
-
-import networkx as nx
-import numpy as np
-import matplotlib.pyplot as plt
-from mpl_toolkits.mplot3d.art3d import Poly3DCollection
-from sklearn.decomposition import PCA
-
-from .utils.naming import next_vert_name
-from .utils.face_check import (
-    point_in_polygon,
-    validate_face_embedding,
-    validate_edge_embedding,
-)
-from .validation import EmbeddingValidator, ValidationRule
-
-
-CENTER_TYPES = ["mean", "bounding_box", "origin"]
-TRANSFORM_TYPES = ["pca"]
-
-
-

-[docs]
-class EmbeddedComplex(nx.Graph):
-    """
-    A unified class to represent an embedded cell complex with cells of arbitrary dimension.
-
-    This combines the functionality of EmbeddedGraph and EmbeddedCW, supporting:
-    - 0-cells (vertices) with embedded coordinates
-    - 1-cells (edges)
-    - k-cells for k >= 2 (faces, volumes, etc.)
-
-    Args:
-        validate_embedding (bool): If True, automatically validate embedding properties
-            when adding cells. Default: False
-        embedding_tol (float): Tolerance for geometric validation. Default: 1e-10
-
-    Attributes:
-        coord_matrix : np.ndarray
-            A matrix of embedded coordinates for each vertex
-        node_list : list
-            A list of node names
-        node_to_index : dict
-            A dictionary mapping node ids to their index in the coord_matrix
-        dim : int
-            The dimension of the embedded coordinates
-        cells : dict
-            Dictionary mapping dimension k to list of k-cells, where each k-cell
-            is represented as a tuple of vertex indices
-        validate_embedding : bool
-            Whether to automatically validate embedding properties
-        embedding_tol : float
-            Tolerance for geometric validation
-    """
-
-

-[docs]
-    def __init__(self, validate_embedding=False, embedding_tol=1e-10):
-        super().__init__()
-        self._node_list = []
-        self._node_to_index = {}
-        self._coord_matrix = None
-        self.cells = defaultdict(list)
-
-        self.validate_embedding = validate_embedding
-        self.embedding_tol = embedding_tol
-
-        def edge_checker(v1_idx: int, v2_idx: int) -> bool:
-            # closure to check if edge exists by converting indices back to node names
-            if v1_idx >= len(self._node_list) or v2_idx >= len(self._node_list):
-                return False
-            v1_name = self._node_list[v1_idx]
-            v2_name = self._node_list[v2_idx]
-            return self.has_edge(v1_name, v2_name)
-
-        self._validator = EmbeddingValidator(embedding_tol, edge_checker)

-
-
-    @property
-    def coord_matrix(self):
-        """Return the N x D coordinate matrix"""
-        if self._coord_matrix is None:
-            return np.empty((0, 0))
-        return self._coord_matrix
-
-    @property
-    def dim(self):
-        """Return the dimension of the embedded coordinates"""
-        if self._coord_matrix is None:
-            return 0
-        return self._coord_matrix.shape[1]
-
-    @property
-    def node_list(self):
-        """Return ordered list of node names."""
-        return self._node_list
-
-    @property
-    def node_to_index(self):
-        """Return a dictionary mapping node ids to their index in the coord_matrix"""
-        return self._node_to_index
-
-    @property
-    def position_dict(self):
-        """Return a dictionary mapping node ids to their coordinates"""
-        return {node: self._coord_matrix[i] for i, node in enumerate(self._node_list)}
-
-    @property
-    def edge_indices(self):
-        """Return edges as array of index pairs"""
-        edges = np.array(
-            [(self._node_to_index[u], self._node_to_index[v]) for u, v in self.edges()],
-            dtype=int,
-        )
-        return edges if len(edges) > 0 else np.empty((0, 2), dtype=int)
-
-    @property
-    def faces(self):
-        """Return list of 2-cells (faces) for backward compatibility"""
-        return [
-            tuple(self._node_list[i] for i in cell) for cell in self.cells.get(2, [])
-        ]
-
-

-[docs]
-    def add_node(self, node_id, coord):
-        """Add a vertex to the complex.
-
-        Args:
-            node_id: Identifier for the node
-            coord: Array-like coordinates for the node
-        """
-        # validate coordinates using validator
-        expected_dim = (
-            self._coord_matrix.shape[1] if self._coord_matrix is not None else None
-        )
-        coord_result = self._validator.validate_coordinates(coord, expected_dim)
-        if not coord_result.is_valid:
-            raise ValueError(coord_result.message)
-
-        # validate node doesn't already exist
-        node_result = self._validator.validate_nodes(
-            [node_id], lambda n: n in self._node_to_index, expect_exists=False
-        )
-        if not node_result.is_valid:
-            raise ValueError(node_result.message)
-
-        coord = np.asarray(coord, dtype=float)
-
-        if len(self._node_list) == 0:
-            # initialize coordinate matrix with first node
-            self._coord_matrix = coord.reshape(1, -1)
-        else:
-            # append new coordinate as row
-            coord_reshaped = coord.reshape(1, -1)
-            self._coord_matrix = np.vstack([self._coord_matrix, coord_reshaped])
-
-        self._node_list.append(node_id)
-        self._node_to_index[node_id] = len(self._node_list) - 1
-        super().add_node(node_id)

-
-
-

-[docs]
-    def add_nodes_from_dict(self, nodes_with_coords: Dict[Union[str, int], np.ndarray]):
-        for node_id, coordinates in nodes_with_coords.items():
-            self.add_node(node_id, coordinates)

-
-
-

-[docs]
-    def add_nodes_from(
-        self, nodes_with_coords: List[Tuple[Union[str, int], np.ndarray]]
-    ):
-        for node_id, coordinates in nodes_with_coords:
-            self.add_node(node_id, coordinates)

-
-
-

-[docs]
-    def add_edge(self, node_id1, node_id2):
-        """Add an edge (1-cell) between two nodes"""
-        # validate nodes exist
-        node_result = self._validator.validate_nodes(
-            [node_id1, node_id2], lambda n: n in self._node_to_index, expect_exists=True
-        )
-        if not node_result.is_valid:
-            raise ValueError(node_result.message)
-
-        super().add_edge(node_id1, node_id2)

-
-
-

-[docs]
-    def add_cell(
-        self,
-        cell_vertices: List,
-        dim: Optional[int] = None,
-        check: Optional[bool] = None,
-        embedding_tol: Optional[float] = None,
-    ):
-        """
-        Add a k-cell to the complex.
-
-        Args:
-            cell_vertices: List of vertex identifiers that form the cell
-            dim: Dimension of the cell. If None, inferred as len(cell_vertices) - 1
-            check: Whether to validate the cell embedding. If None, uses self.validate_embedding
-            embedding_tol: Tolerance for geometric validation. If None, uses self.embedding_tol
-        """
-        if check is None:
-            check = self.validate_embedding
-        if embedding_tol is None:
-            embedding_tol = self.embedding_tol
-        if dim is None:
-            dim = len(cell_vertices) - 1
-
-        # check vertex existence before validation (can't validate non-existent vertices)
-        missing_vertices = [v for v in cell_vertices if v not in self._node_to_index]
-        if missing_vertices:
-            raise ValueError(f"Vertices do not exist: {missing_vertices}")
-
-        # convert vertex names to indices for storage
-        cell_indices = tuple(self._node_to_index[v] for v in cell_vertices)
-
-        # always validate structural requirements
-        cell_coords = (
-            self._coord_matrix[list(cell_indices)]
-            if self._coord_matrix is not None
-            else None
-        )
-        all_coords = self._coord_matrix
-        all_indices = list(range(len(self._node_list)))
-
-        # Always check structural rules (vertex count, dimension validity)
-        structural_result = self._validator.validate_cell(
-            cell_coords, all_coords, list(cell_indices), all_indices, dim, check_geometric=False
-        )
-        if not structural_result.is_valid:
-            raise ValueError(structural_result.message)
-
-        # Optionally check geometric rules (embedding properties)
-        if check:
-            geometric_result = self._validator.validate_cell(
-                cell_coords, all_coords, list(cell_indices), all_indices, dim, check_geometric=True
-            )
-            if not geometric_result.is_valid:
-                raise ValueError(geometric_result.message)
-
-        # update graph structure and store cell
-        if dim == 1:
-            # also add to networkx graph structure
-            self.add_edge(cell_vertices[0], cell_vertices[1])
-
-        self.cells[dim].append(cell_indices)

-
-
-

-[docs]
-    def enable_embedding_validation(self, tol: float = 1e-10):
-        """
-        Enable automatic embedding validation for all subsequent cell additions.
-
-        Args:
-            tol: Tolerance for geometric validation
-        """
-        self.validate_embedding = True
-        self.embedding_tol = tol
-        self._validator.set_tolerance(tol)

-
-
-

-[docs]
-    def disable_embedding_validation(self):
-        """Disable automatic embedding validation for all subsequent cell additions."""
-        self.validate_embedding = False

-
-
-

-[docs]
-    def get_validator(self) -> "EmbeddingValidator":
-        """
-        Get the embedding validator instance for advanced configuration.
-
-        Returns:
-            The EmbeddingValidator instance used by this complex
-        """
-        return self._validator

-
-
-

-[docs]
-    def set_validation_rules(self, rules: List["ValidationRule"]) -> "EmbeddedComplex":
-        """
-        Set custom validation rules.
-
-        Args:
-            rules: List of ValidationRule instances
-
-        Returns:
-            Self for method chaining
-        """
-        # replace validation rules
-        self._validator.rules = rules
-        return self

-
-
-

-[docs]
-    def add_face(self, face: List, check: Optional[bool] = None):
-        """Add a 2-cell (face) to the complex. Provided for backward compatibility."""
-        self.add_cell(face, dim=2, check=check)

-
-
-

-[docs]
-    def add_faces_from(self, faces: List[List]):
-        """Add multiple 2-cells (faces) to the complex."""
-        for face in faces:
-            self.add_face(face)

-
-
-

-[docs]
-    def get_coord(self, node_id):
-        """Return the coordinates of a node"""
-        # validate node exists
-        node_result = self._validator.validate_nodes(
-            [node_id], lambda n: n in self._node_to_index, expect_exists=True
-        )
-        if not node_result.is_valid:
-            raise ValueError(node_result.message)
-
-        return self._coord_matrix[self._node_to_index[node_id]].copy()

-
-
-

-[docs]
-    def set_coord(self, node_id, new_coords):
-        """Set the coordinates of a node"""
-        # validate coordinates
-        expected_dim = (
-            self._coord_matrix.shape[1] if self._coord_matrix is not None else None
-        )
-        coord_result = self._validator.validate_coordinates(new_coords, expected_dim)
-        if not coord_result.is_valid:
-            raise ValueError(coord_result.message)
-
-        # validate node exists
-        node_result = self._validator.validate_nodes(
-            [node_id], lambda n: n in self._node_to_index, expect_exists=True
-        )
-        if not node_result.is_valid:
-            raise ValueError(node_result.message)
-
-        idx = self._node_to_index[node_id]
-        self._coord_matrix[idx] = new_coords

-
-
-

-[docs]
-    def add_cycle(self, coord_matrix):
-        """Add nodes in a cyclic pattern from coordinate matrix"""
-        # generate sequential node names and add cyclic edges
-        n = coord_matrix.shape[0]
-        new_names = next_vert_name(self._node_list[-1] if self._node_list else 0, n)
-        self.add_nodes_from(zip(new_names, coord_matrix))
-        self.add_edges_from([(new_names[i], new_names[(i + 1) % n]) for i in range(n)])

-
-
-

-[docs]
-    def get_center(self, method: str = "bounding_box") -> np.ndarray:
-        """Calculate center of coordinates"""
-
-        coords = self._coord_matrix
-        if coords is None or coords.size == 0:
-            return np.zeros(0)
-
-        if method == "mean":
-            return np.mean(coords, axis=0)
-        elif method == "bounding_box":
-            return (np.max(coords, axis=0) + np.min(coords, axis=0)) / 2
-        elif method == "origin":
-            return np.zeros(self.dim)
-        raise ValueError(f"Unknown center method: {method}")

-
-
-

-[docs]
-    def get_bounding_box(self):
-        """Get (min, max) for each dimension"""
-        return [(dim.min(), dim.max()) for dim in self._coord_matrix.T]

-
-
-

-[docs]
-    def get_bounding_radius(self, center_type: str = "bounding_box") -> float:
-        """Get radius of minimal bounding sphere"""
-        coords = self._coord_matrix
-        if coords is None or coords.size == 0:
-            return 0.0
-
-        center = self.get_center(center_type)
-        return np.max(np.linalg.norm(coords - center, axis=1))

-
-
-

-[docs]
-    def get_normal_angle_matrix(
-        self, edges_only: bool = False, decimals: Optional[int] = None
-    ) -> Tuple[np.ndarray, List[str]]:
-        """
-        Optimized angle matrix computation using vectorized operations.
-
-        Args:
-            edges_only: Only compute angles between connected vertices
-            decimals: Round angles to specified decimal places
-
-        Returns:
-            angle_matrix: NaN-filled matrix with pair angles
-            vertex_labels: Ordered node identifiers
-        """
-        coords = self._coord_matrix
-        vertices = self._node_list
-        n = len(vertices)
-
-        angle_matrix = np.full((n, n), np.nan, dtype=np.float64)
-
-        if edges_only:
-            # compute angles only for connected vertex pairs
-            edges = np.array(list(self.edges()))
-            if edges.size == 0:
-                return angle_matrix, vertices
-
-            u_indices = np.vectorize(self._node_to_index.get)(edges[:, 0])
-            v_indices = np.vectorize(self._node_to_index.get)(edges[:, 1])
-
-            dx = coords[v_indices, 0] - coords[u_indices, 0]
-            dy = coords[v_indices, 1] - coords[u_indices, 1]
-
-            # angles from u to v and reverse direction
-            angles = np.arctan2(dx, -dy) % (2 * np.pi)
-            rev_angles = (angles + np.pi) % (2 * np.pi)
-
-            if decimals is not None:
-                angles = np.round(angles, decimals)
-                rev_angles = np.round(rev_angles, decimals)
-
-            angle_matrix[u_indices, v_indices] = angles
-            angle_matrix[v_indices, u_indices] = rev_angles
-
-        else:
-            # compute angles between all vertex pairs using broadcasting
-            x = coords[:, 0]
-            y = coords[:, 1]
-
-            dx = x[:, None] - x[None, :]
-            dy = y[:, None] - y[None, :]
-
-            angle_matrix = np.arctan2(dx, -dy) % (2 * np.pi)
-            # nan for coincident points
-            angle_matrix[np.isclose(dx**2 + dy**2, 0)] = np.nan
-
-            if decimals is not None:
-                angle_matrix = np.round(angle_matrix, decimals)
-
-            np.fill_diagonal(angle_matrix, np.nan)
-
-        return angle_matrix, vertices

-
-
-

-[docs]
-    def get_normal_angles(
-        self, edges_only: bool = False, decimals: int = 6
-    ) -> Dict[float, List[Tuple[str, str]]]:
-        """
-        Optimized angle dictionary construction using NumPy grouping.
-
-        Args:
-            edges_only: Only include edge-connected pairs
-            decimals: Round angles to specified decimal places
-
-        Returns:
-            Dictionary mapping rounded angles to vertex pairs
-        """
-        angle_matrix, vertices = self.get_normal_angle_matrix(edges_only, decimals)
-        n = len(vertices)
-
-        # extract upper triangle to avoid duplicate pairs
-        rows, cols = np.triu_indices(n, k=1)
-        angles = angle_matrix[rows, cols]
-        valid_mask = ~np.isnan(angles)
-
-        if not valid_mask.any():
-            return defaultdict(list)
-
-        valid_rows = rows[valid_mask]
-        valid_cols = cols[valid_mask]
-        valid_angles = angles[valid_mask]
-
-        # group vertex pairs by their angle
-        angle_dict = defaultdict(list)
-        unique_angles, inverse = np.unique(valid_angles, return_inverse=True)
-
-        for idx, angle in enumerate(unique_angles):
-            mask = inverse == idx
-            pairs = [
-                (vertices[i], vertices[j])
-                for i, j in zip(valid_rows[mask], valid_cols[mask])
-            ]
-            angle_dict[float(angle)].extend(pairs)
-
-        return angle_dict

-
-
-

-[docs]
-    def transform_coordinates(self, center_type="bounding_box", projection_type="pca"):
-        """Transform coordinates center and orientation"""
-        if projection_type not in TRANSFORM_TYPES:
-            raise ValueError(f"Unknown transform type: {projection_type}")
-        self.project_coordinates(projection_type)
-        if center_type not in CENTER_TYPES:
-            raise ValueError(f"Unknown center method: {center_type}")
-        self.center_coordinates(center_type)

-
-
-

-[docs]
-    def center_coordinates(self, center_type="mean"):
-        if center_type not in CENTER_TYPES:
-            raise ValueError(f"Unknown center method: {center_type}")
-
-        center = self.get_center(center_type)
-        self._coord_matrix -= center

-
-
-

-[docs]
-    def scale_coordinates(self, radius=1):
-        """Scale coordinates to fit within given radius"""
-        # scale so largest distance from origin equals target radius
-        current_max = np.linalg.norm(self._coord_matrix, axis=1).max()
-        if current_max > 0:
-            self._coord_matrix *= radius / current_max

-
-
-

-[docs]
-    def project_coordinates(self, projection_type="pca"):
-        """Project coordinates using a function"""
-        if projection_type == "pca":
-            self.pca_projection()
-        else:
-            raise ValueError(f"Unknown projection type: {projection_type}")

-
-
-

-[docs]
-    def pca_projection(self, target_dim=2):
-        """Dimensionality reduction using PCA"""
-        # only reduce dimension
-        if self.dim <= target_dim:
-            return
-
-        pca = PCA(n_components=target_dim)
-        self._coord_matrix = pca.fit_transform(self._coord_matrix)

-
-
-

-[docs]
-    def validate_plot_parameters(func):
-        # decorator to check plotting requirements
-        def wrapper(self, *args, **kwargs):
-            bounding_center_type = kwargs.get("bounding_center_type", "bounding_box")
-
-            if self.dim not in [2, 3]:
-                raise ValueError("At least 2D or 3D coordinates required for plotting")
-
-            if bounding_center_type not in CENTER_TYPES:
-                raise ValueError(
-                    f"Invalid center type: {bounding_center_type}. "
-                    f"Valid options: {CENTER_TYPES}"
-                )
-
-            return func(self, *args, **kwargs)
-
-        return wrapper

-
-
-

-[docs]
-    def plot_faces(self, ax=None, **kwargs):
-        """
-        Plots the 2-cells (faces) of the complex.
-
-        Parameters:
-            ax (matplotlib.axes.Axes):
-                The axes to plot the graph on. If None, a new figure is created.
-            **kwargs:
-                Additional keyword arguments to pass to the ax.fill function.
-
-        Returns:
-            matplotlib.axes.Axes
-                The axes object with the plot.
-        """
-        if ax is None:
-            _, ax = plt.subplots()
-
-        # render each 2-cell as filled polygon
-        for cell_indices in self.cells.get(2, []):
-            face_coords = self._coord_matrix[list(cell_indices)]
-
-            if self.dim == 2:
-                ax.fill(face_coords[:, 0], face_coords[:, 1], **kwargs)
-            else:
-                # 3d faces need polygon collection
-                verts = [face_coords]
-                collection = Poly3DCollection(verts, **kwargs)
-                ax.add_collection3d(collection)
-
-        return ax

-
-
-

-[docs]
-    @validate_plot_parameters
-    def plot(
-        self,
-        bounding_circle: bool = False,
-        bounding_center_type: str = "bounding_box",
-        color_nodes_theta: Optional[float] = None,
-        ax: Optional[plt.Axes] = None,
-        with_labels: bool = True,
-        node_size: int = 300,
-        edge_color: str = "gray",
-        elev: float = 25,
-        azim: float = -60,
-        face_color: str = "lightblue",
-        face_alpha: float = 0.3,
-        **kwargs,
-    ) -> plt.Axes:
-        """
-        Visualize the embedded complex in 2D or 3D
-        """
-        ax = self._create_axes(ax, self.dim)
-
-        if 2 in self.cells and len(self.cells[2]) > 0:
-            self.plot_faces(ax=ax, facecolor=face_color, alpha=face_alpha)
-
-        pos = {node: self._coord_matrix[i] for i, node in enumerate(self._node_list)}
-
-        if self.dim == 2:
-            self._draw_2d(ax, pos, with_labels, node_size, edge_color, **kwargs)
-        else:
-            self._draw_3d(ax, pos, node_size, edge_color, elev, azim, **kwargs)
-
-        if color_nodes_theta is not None:
-            # color nodes by projection in specified direction
-            direction = np.array(
-                [np.sin(color_nodes_theta), -np.cos(color_nodes_theta)]
-            )
-            node_colors = np.dot(self._coord_matrix, direction)
-            self._add_node_coloring(ax, pos, node_colors, node_size, self.dim, **kwargs)
-
-        if bounding_circle:
-            self._add_bounding_shape(ax, bounding_center_type, self.dim)
-
-        self._configure_axes(ax)
-
-        return ax

-
-
-    def _create_axes(self, ax, dim=None):
-        """Create appropriate axes if not provided"""
-        if dim is None:
-            dim = self.dim
-
-        if ax is None:
-            fig = plt.figure()
-            ax = fig.add_subplot(111, projection="3d" if dim == 3 else None)
-        elif dim == 3 and not hasattr(ax, "zaxis"):
-            raise ValueError("For 3D plots, provide axes with 3D projection")
-        return ax
-
-    def _draw_2d(self, ax, pos, with_labels, node_size, edge_color, **kwargs):
-        """2D visualization components"""
-        nx.draw_networkx_edges(
-            self, pos=pos, ax=ax, edge_color=edge_color, width=1.5, **kwargs
-        )
-        nx.draw_networkx_nodes(
-            self,
-            pos=pos,
-            ax=ax,
-            node_size=node_size,
-            node_color="lightblue",
-            edgecolors="black",
-            linewidths=0.5,
-            **kwargs,
-        )
-        if with_labels:
-            nx.draw_networkx_labels(
-                self, pos=pos, ax=ax, font_size=8, font_color="black", **kwargs
-            )
-
-    def _draw_3d(self, ax, pos, node_size, edge_color, elev, azim, **kwargs):
-        """3D visualization components"""
-        ax.view_init(elev=elev, azim=azim)
-
-        coords = np.array(list(pos.values()))
-        ax.scatter3D(
-            coords[:, 0],
-            coords[:, 1],
-            coords[:, 2],
-            s=node_size,
-            c="lightblue",
-            edgecolors="black",
-            linewidth=0.5,
-        )
-
-        for u, v in self.edges():
-            x = [pos[u][0], pos[v][0]]
-            y = [pos[u][1], pos[v][1]]
-            z = [pos[u][2], pos[v][2]]
-            ax.plot3D(x, y, z, color=edge_color, linewidth=1.5)
-
-    def _add_node_coloring(self, ax, pos, node_colors, node_size, dim=None, **kwargs):
-        """Add node coloring based on provided values"""
-        if dim is None:
-            dim = self.dim
-
-        if dim == 2:
-            # 2d colored nodes using networkx
-            nx.draw_networkx_nodes(
-                self,
-                pos=pos,
-                ax=ax,
-                node_size=node_size,
-                node_color=node_colors,
-                cmap=plt.cm.viridis,
-                edgecolors="black",
-                linewidths=0.5,
-                **kwargs,
-            )
-        else:
-            # 3d colored scatter plot
-            coords = np.array(list(pos.values()))
-            ax.scatter3D(
-                coords[:, 0],
-                coords[:, 1],
-                coords[:, 2],
-                s=node_size,
-                c=node_colors,
-                cmap=plt.cm.viridis,
-                edgecolors="black",
-                linewidth=0.5,
-                **kwargs,
-            )
-
-        norm = plt.Normalize(vmin=min(node_colors), vmax=max(node_colors))
-        sm = plt.cm.ScalarMappable(norm=norm, cmap=plt.cm.viridis)
-        sm.set_array([])
-        cbar = plt.colorbar(sm, ax=ax, orientation="vertical", shrink=0.8)
-        cbar.set_label("Node Values")
-
-    def _add_bounding_shape(self, ax, center_type="bounding_box", dim=None):
-        """Add bounding circle/sphere visualization"""
-        if dim is None:
-            dim = self.dim
-
-        center = self.get_center(center_type)
-        radius = self.get_bounding_radius(center_type)
-
-        if dim == 2:
-            # draw bounding circle
-            circle = plt.Circle(
-                center[:2],
-                radius,
-                fill=False,
-                linestyle="--",
-                color="darkred",
-                linewidth=1.2,
-                alpha=0.7,
-            )
-            ax.add_patch(circle)
-            padding = radius * 0.1
-            ax.set_xlim(center[0] - radius - padding, center[0] + radius + padding)
-            ax.set_ylim(center[1] - radius - padding, center[1] + radius + padding)
-        else:
-            # draw bounding sphere as wireframe
-            u = np.linspace(0, 2 * np.pi, 30)
-            v = np.linspace(0, np.pi, 30)
-            x = radius * np.outer(np.cos(u), np.sin(v)) + center[0]
-            y = radius * np.outer(np.sin(u), np.sin(v)) + center[1]
-            z = radius * np.outer(np.ones(np.size(u)), np.cos(v)) + center[2]
-
-            ax.plot_wireframe(
-                x, y, z, color="darkred", linewidth=0.5, alpha=0.3, rstride=2, cstride=2
-            )
-            padding = radius * 0.1
-            ax.set_xlim3d(center[0] - radius - padding, center[0] + radius + padding)
-            ax.set_ylim3d(center[1] - radius - padding, center[1] + radius + padding)
-            ax.set_zlim3d(center[2] - radius - padding, center[2] + radius + padding)
-
-    def _configure_axes(self, ax):
-        """Finalize plot appearance"""
-        if hasattr(ax, "zaxis"):
-            ax.grid(True, linestyle=":", linewidth=0.5, alpha=0.7)
-            ax.xaxis.set_pane_color((1.0, 1.0, 1.0, 0.0))
-            ax.yaxis.set_pane_color((1.0, 1.0, 1.0, 0.0))
-            ax.zaxis.set_pane_color((1.0, 1.0, 1.0, 0.0))
-            ax.set_xlabel("X")
-            ax.set_ylabel("Y")
-            ax.set_zlabel("Z")
-        else:
-            ax.set_aspect("equal")
-            ax.grid(True, linestyle=":", linewidth=0.5, alpha=0.7)
-
-            xlim = ax.get_xlim()
-            ylim = ax.get_ylim()
-
-            x_interval = self._get_nice_interval(xlim[1] - xlim[0])
-            y_interval = self._get_nice_interval(ylim[1] - ylim[0])
-
-            ax.xaxis.set_major_locator(plt.MultipleLocator(x_interval))
-            ax.yaxis.set_major_locator(plt.MultipleLocator(y_interval))
-
-            ax.xaxis.set_minor_locator(plt.MultipleLocator(x_interval / 2))
-            ax.yaxis.set_minor_locator(plt.MultipleLocator(y_interval / 2))
-
-        ax.tick_params(
-            axis="both",
-            which="both",
-            bottom=True,
-            left=True,
-            labelbottom=True,
-            labelleft=True,
-        )
-
-    def _get_nice_interval(self, range_size):
-        # calculate visually appealing tick spacing
-        rough_interval = range_size / 5
-
-        magnitude = 10 ** np.floor(np.log10(rough_interval))
-
-        normalized = rough_interval / magnitude
-
-        # choose from standard intervals: 1, 2, 5, 10
-        if normalized < 1.5:
-            nice_interval = 1
-        elif normalized < 3:
-            nice_interval = 2
-        elif normalized < 7:
-            nice_interval = 5
-        else:
-            nice_interval = 10
-
-        return nice_interval * magnitude

-
-
-
-EmbeddedGraph = EmbeddedComplex
-EmbeddedCW = EmbeddedComplex
-
- -
-
- -
-
-
-
- - - - - - - \ No newline at end of file diff --git a/docs/_modules/ect/sect.html b/docs/_modules/ect/sect.html deleted file mode 100644 index 7aed625..0000000 --- a/docs/_modules/ect/sect.html +++ /dev/null @@ -1,249 +0,0 @@ - - - - - - ect.sect — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - -
- - -
- -
-
-
- -
-
-
-
- -

Source code for ect.sect

-from ect import ECT
-from .embed_complex import EmbeddedGraph, EmbeddedCW
-from .directions import Directions
-from .results import ECTResult
-from typing import Optional, Union
-import numpy as np
-
-
-

-[docs]
-class SECT(ECT):
-    """
-    A class to calculate the Smooth Euler Characteristic Transform (SECT).
-    Inherits from ECT and applies smoothing to the final result.
-    """
-
-

-[docs]
-    def __init__(
-        self,
-        directions: Optional[Directions] = None,
-        num_dirs: Optional[int] = None,
-        num_thresh: Optional[int] = None,
-        bound_radius: Optional[float] = None,
-        thresholds: Optional[np.ndarray] = None,
-        dtype=np.float32,
-    ):
-        """Initialize SECT calculator with smoothing parameter
-
-        Args:
-            directions: Optional pre-configured Directions object
-            num_dirs: Number of directions to sample (ignored if directions provided)
-            num_thresh: Number of threshold values (required if directions not provided)
-            bound_radius: Optional radius for bounding circle
-            thresholds: Optional array of thresholds
-            dtype: Data type for output array
-        """
-        super().__init__(
-            directions, num_dirs, num_thresh, bound_radius, thresholds, dtype
-        )

-
-
-

-[docs]
-    def calculate(
-        self,
-        graph: Union[EmbeddedGraph, EmbeddedCW],
-        theta: Optional[float] = None,
-        override_bound_radius: Optional[float] = None,
-    ) -> ECTResult:
-        """Calculate Smooth Euler Characteristic Transform (SECT)
-
-        Args:
-            graph: The input graph to calculate the SECT for
-            theta: The angle in [0,2π] for the direction to calculate the SECT
-            override_bound_radius: Optional override for bounding radius
-
-        Returns:
-            ECTResult: The smoothed transform result containing the matrix,
-                      directions, and thresholds
-        """
-        ect_result = super().calculate(graph, theta, override_bound_radius)
-        return ECTResult(
-            ect_result, ect_result.directions, ect_result.thresholds
-        ).smooth()

-

-
-
- -
-
- -
-
-
-
- - - - - - - \ No newline at end of file diff --git a/docs/_modules/ect/validation/base.html b/docs/_modules/ect/validation/base.html deleted file mode 100644 index 368ca74..0000000 --- a/docs/_modules/ect/validation/base.html +++ /dev/null @@ -1,318 +0,0 @@ - - - - - - ect.validation.base — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - -
- - -
- -
-
-
- -
-
-
-
- -

Source code for ect.validation.base

-"""
-Base classes for the embedding validation system.
-"""
-
-from abc import ABC, abstractmethod
-from dataclasses import dataclass
-from typing import List, Optional
-import numpy as np
-
-
-

-[docs]
-@dataclass
-class ValidationResult:
-    """Result of a validation check."""
-
-    is_valid: bool
-    message: str = ""
-    violating_indices: Optional[List[int]] = None
-
-

-[docs]
-    @classmethod
-    def valid(cls) -> "ValidationResult":
-        """Create a valid result."""
-        return cls(is_valid=True)

-
-
-

-[docs]
-    @classmethod
-    def invalid(
-        cls, message: str, violating_indices: Optional[List[int]] = None
-    ) -> "ValidationResult":
-        """Create an invalid result with error message."""
-        return cls(is_valid=False, message=message, violating_indices=violating_indices)

-

-
-
-
-

-[docs]
-class ValidationRule(ABC):
-    """Abstract base class for embedding validation rules."""
-
-

-[docs]
-    def __init__(self, tolerance: float = 1e-10):
-        """
-        Initialize validation rule.
-
-        Args:
-            tolerance: Numerical tolerance for geometric checks
-        """
-        self.tolerance = tolerance

-
-
-    @property
-    @abstractmethod
-    def name(self) -> str:
-        """Human-readable name of this validation rule."""
-        pass
-
-    @property
-    def is_structural(self) -> bool:
-        """
-        Check if this is a structural rule that should always be validated.
-        
-        Structural rules check basic requirements like vertex counts and dimension validity.
-        They should always be checked regardless of validation settings.
-        Geometric rules check embedding properties and are optional.
-        
-        Returns:
-            True if this rule should always be checked, False if optional
-        """
-        return False
-
-

-[docs]
-    @abstractmethod
-    def applies_to_dimension(self, dim: int) -> bool:
-        """
-        Check if this rule applies to cells of the given dimension.
-
-        Args:
-            dim: Cell dimension
-
-        Returns:
-            True if this rule should validate cells of this dimension
-        """
-        pass

-
-
-

-[docs]
-    @abstractmethod
-    def validate(
-        self,
-        cell_coords: np.ndarray,
-        all_coords: np.ndarray,
-        cell_indices: List[int],
-        all_indices: List[int],
-        dim: int = None,
-    ) -> ValidationResult:
-        """
-        Validate a cell against this rule.
-
-        Args:
-            cell_coords: Coordinates of vertices forming the cell
-            all_coords: Coordinates of all vertices in the complex
-            cell_indices: Indices of vertices forming the cell
-            all_indices: Indices of all vertices in the complex
-            dim: Dimension of the cell being validated
-
-        Returns:
-            ValidationResult indicating if the cell is valid
-        """
-        pass

-
-
-

-[docs]
-    def set_tolerance(self, tolerance: float) -> "ValidationRule":
-        """
-        Set the tolerance for this rule.
-
-        Args:
-            tolerance: New tolerance value
-
-        Returns:
-            Self for method chaining
-        """
-        self.tolerance = tolerance
-        return self

-

-
-
- -
-
- -
-
-
-
- - - - - - - \ No newline at end of file diff --git a/docs/_modules/ect/validation/rules.html b/docs/_modules/ect/validation/rules.html deleted file mode 100644 index bb368ec..0000000 --- a/docs/_modules/ect/validation/rules.html +++ /dev/null @@ -1,595 +0,0 @@ - - - - - - ect.validation.rules — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - -
- - -
- -
-
-
- -
-
-
-
- -

Source code for ect.validation.rules

-"""
-Unified validation rules for embedding validation system.
-
-This module contains all validation rules including both structural rules
-(which are always checked) and geometric rules (which are optional).
-"""
-
-from typing import List, Callable, Optional
-import numpy as np
-
-from .base import ValidationRule, ValidationResult
-from ..utils.face_check import (
-    validate_edge_embedding,
-    validate_face_embedding,
-    segments_intersect,
-)
-
-
-# ================================
-# STRUCTURAL RULES (Always checked)
-# ================================
-
-

-[docs]
-class DimensionValidityRule(ValidationRule):
-    """Validates that cell dimension is non-negative."""
-
-    @property
-    def name(self) -> str:
-        return "Dimension Validity"
-
-    @property
-    def is_structural(self) -> bool:
-        return True
-
-

-[docs]
-    def applies_to_dimension(self, dim: int) -> bool:
-        return True

-
-
-

-[docs]
-    def validate(
-        self,
-        cell_coords: np.ndarray,
-        all_coords: np.ndarray,
-        cell_indices: List[int],
-        all_indices: List[int],
-        dim: int = None,
-    ) -> ValidationResult:
-        """Validate that dimension is non-negative."""
-        if dim is not None and dim < 0:
-            return ValidationResult.invalid("Cell dimension must be non-negative")
-        return ValidationResult.valid()

-

-
-
-
-

-[docs]
-class VertexCountRule(ValidationRule):
-    """Validates that cells have the correct number of vertices for their dimension."""
-
-    @property
-    def name(self) -> str:
-        return "Vertex Count Validation"
-
-    @property
-    def is_structural(self) -> bool:
-        return True
-
-

-[docs]
-    def applies_to_dimension(self, dim: int) -> bool:
-        return True

-
-
-

-[docs]
-    def validate(
-        self,
-        cell_coords: np.ndarray,
-        all_coords: np.ndarray,
-        cell_indices: List[int],
-        all_indices: List[int],
-        dim: int = None,
-    ) -> ValidationResult:
-        """Validate vertex count matches cell dimension requirements."""
-        if dim is None:
-            return ValidationResult.valid()
-
-        vertex_count = len(cell_indices)
-
-        if dim == 0 and vertex_count != 1:
-            return ValidationResult.invalid("0-cells must contain exactly one vertex")
-        elif dim == 1 and vertex_count != 2:
-            return ValidationResult.invalid("1-cells must contain exactly two vertices")
-        elif dim >= 2 and vertex_count < 3:
-            return ValidationResult.invalid(
-                f"{dim}-cells must contain at least 3 vertices"
-            )
-
-        return ValidationResult.valid()

-

-
-
-
-

-[docs]
-class CoordinateDimensionRule(ValidationRule):
-    """Validates that coordinates have consistent dimensions."""
-
-

-[docs]
-    def __init__(
-        self, tolerance: float = 1e-10, dimension_checker: Optional[Callable] = None
-    ):
-        super().__init__(tolerance)
-        self.dimension_checker = dimension_checker  # function to get expected dimension

-
-
-    @property
-    def name(self) -> str:
-        return "Coordinate Dimension Validation"
-
-    @property
-    def is_structural(self) -> bool:
-        return True
-
-

-[docs]
-    def applies_to_dimension(self, dim: int) -> bool:
-        return True  # applies to all operations involving coordinates

-
-
-

-[docs]
-    def validate(
-        self,
-        cell_coords: np.ndarray,
-        all_coords: np.ndarray,
-        cell_indices: List[int],
-        all_indices: List[int],
-        dim: int = None,
-    ) -> ValidationResult:
-        """Validate coordinate dimensions are consistent."""
-        if self.dimension_checker is None or cell_coords is None:
-            return ValidationResult.valid()
-
-        expected_dim = self.dimension_checker()
-        if expected_dim is None or expected_dim == 0:
-            return ValidationResult.valid()
-
-        # check that all coordinates have the expected dimension
-        if cell_coords.ndim != 2:
-            return ValidationResult.invalid("Coordinates must be a 2D array")
-
-        if cell_coords.shape[1] != expected_dim:
-            return ValidationResult.invalid(
-                f"Coordinates must have dimension {expected_dim}, got {cell_coords.shape[1]}"
-            )
-
-        return ValidationResult.valid()

-

-
-
-
-# ================================
-# GEOMETRIC RULES (Optional)
-# ================================
-
-

-[docs]
-class EdgeInteriorRule(ValidationRule):
-    """Validates that no vertices lie on edge interiors."""
-
-    @property
-    def name(self) -> str:
-        return "Edge Interior Validation"
-
-

-[docs]
-    def applies_to_dimension(self, dim: int) -> bool:
-        return dim == 1

-
-
-

-[docs]
-    def validate(
-        self,
-        cell_coords: np.ndarray,
-        all_coords: np.ndarray,
-        cell_indices: List[int],
-        all_indices: List[int],
-        dim: int = None,
-    ) -> ValidationResult:
-        """Validate that no other vertices lie on this edge's interior."""
-        is_valid, error_msg = validate_edge_embedding(
-            cell_coords, all_coords, cell_indices, all_indices, self.tolerance
-        )
-
-        if is_valid:
-            return ValidationResult.valid()
-        else:
-            return ValidationResult.invalid(error_msg)

-

-
-
-
-

-[docs]
-class FaceInteriorRule(ValidationRule):
-    """Validates that no vertices lie inside face interiors."""
-
-    @property
-    def name(self) -> str:
-        return "Face Interior Validation"
-
-

-[docs]
-    def applies_to_dimension(self, dim: int) -> bool:
-        return dim == 2

-
-
-

-[docs]
-    def validate(
-        self,
-        cell_coords: np.ndarray,
-        all_coords: np.ndarray,
-        cell_indices: List[int],
-        all_indices: List[int],
-        dim: int = None,
-    ) -> ValidationResult:
-        """Validate that no other vertices lie inside this face."""
-        is_valid, error_msg = validate_face_embedding(
-            cell_coords, all_coords, cell_indices, all_indices, self.tolerance
-        )
-
-        if is_valid:
-            return ValidationResult.valid()
-        else:
-            return ValidationResult.invalid(error_msg)

-

-
-
-
-

-[docs]
-class SelfIntersectionRule(ValidationRule):
-    """Validates that face edges don't self-intersect."""
-
-    @property
-    def name(self) -> str:
-        return "Self-Intersection Validation"
-
-

-[docs]
-    def applies_to_dimension(self, dim: int) -> bool:
-        return dim == 2

-
-
-

-[docs]
-    def validate(
-        self,
-        cell_coords: np.ndarray,
-        all_coords: np.ndarray,
-        cell_indices: List[int],
-        all_indices: List[int],
-        dim: int = None,
-    ) -> ValidationResult:
-        """Validate that face edges don't intersect each other"""
-
-        if cell_coords.shape[1] > 2:
-            coords_2d = cell_coords[:, :2]
-        else:
-            coords_2d = cell_coords
-
-        n = len(coords_2d)
-        if n < 3:
-            return ValidationResult.invalid("Face must have at least 3 vertices")
-
-        for i in range(n):
-            edge1_start = coords_2d[i]
-            edge1_end = coords_2d[(i + 1) % n]
-
-            for j in range(i + 2, n):
-                if j == n - 1 and i == 0:
-                    continue
-
-                edge2_start = coords_2d[j]
-                edge2_end = coords_2d[(j + 1) % n]
-
-                if segments_intersect(
-                    edge1_start, edge1_end, edge2_start, edge2_end, self.tolerance
-                ):
-                    return ValidationResult.invalid(
-                        f"Face edges intersect: edge {i}-{(i + 1) % n} intersects edge {j}-{(j + 1) % n}"
-                    )
-
-        return ValidationResult.valid()

-

-
-
-
-

-[docs]
-class BoundaryEdgeRule(ValidationRule):
-    """Validates that required boundary edges exist for faces."""
-
-

-[docs]
-    def __init__(self, tolerance: float = 1e-10, edge_checker=None):
-        """
-        Initialize boundary edge rule.
-
-        Args:
-            tolerance: Numerical tolerance
-            edge_checker: Function to check if an edge exists (injected dependency)
-        """
-        super().__init__(tolerance)
-        self.edge_checker = edge_checker

-
-
-    @property
-    def name(self) -> str:
-        return "Boundary Edge Validation"
-
-

-[docs]
-    def applies_to_dimension(self, dim: int) -> bool:
-        return dim == 2

-
-
-

-[docs]
-    def validate(
-        self,
-        cell_coords: np.ndarray,
-        all_coords: np.ndarray,
-        cell_indices: List[int],
-        all_indices: List[int],
-        dim: int = None,
-    ) -> ValidationResult:
-        """Validate that all boundary edges exist for this face."""
-        if self.edge_checker is None:
-            return ValidationResult.valid()
-
-        n = len(cell_indices)
-        if n < 3:
-            return ValidationResult.invalid("Face must have at least 3 vertices")
-
-        for i in range(n):
-            v1_idx = cell_indices[i]
-            v2_idx = cell_indices[(i + 1) % n]
-
-            if not self.edge_checker(v1_idx, v2_idx):
-                return ValidationResult.invalid(
-                    f"Boundary edge between vertices {v1_idx} and {v2_idx} missing for face"
-                )
-
-        return ValidationResult.valid()

-

-
-
-
-# ================================
-# STANDALONE UTILITY FUNCTIONS
-# ================================
-
-

-[docs]
-def validate_coordinate_array(
-    coords, expected_dim: Optional[int] = None
-) -> ValidationResult:
-    """Standalone function to validate coordinate array format."""
-    if coords is None:
-        return ValidationResult.valid()
-
-    coords = np.asarray(coords, dtype=float)
-
-    if coords.ndim != 1:
-        return ValidationResult.invalid("Coordinates must be a 1D array")
-
-    if expected_dim is not None and coords.size != expected_dim:
-        return ValidationResult.invalid(
-            f"Coordinates must have dimension {expected_dim}, got {coords.size}"
-        )
-
-    return ValidationResult.valid()

-
-
-
-

-[docs]
-def validate_node_existence(
-    nodes: List, node_checker: Callable, expect_exists: bool = True
-) -> ValidationResult:
-    """Standalone function to validate node existence."""
-    if node_checker is None:
-        return ValidationResult.valid()
-
-    for node_id in nodes:
-        node_exists = node_checker(node_id)
-        if expect_exists and not node_exists:
-            return ValidationResult.invalid(f"Node {node_id} does not exist")
-        if not expect_exists and node_exists:
-            return ValidationResult.invalid(f"Node {node_id} already exists")
-
-    return ValidationResult.valid()

-
-
- -
-
- -
-
-
-
- - - - - - - \ No newline at end of file diff --git a/docs/_modules/ect/validation/validator.html b/docs/_modules/ect/validation/validator.html deleted file mode 100644 index c31fc15..0000000 --- a/docs/_modules/ect/validation/validator.html +++ /dev/null @@ -1,498 +0,0 @@ - - - - - - ect.validation.validator — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - -
- - -
- -
-
-
- -
-
-
-
- -

Source code for ect.validation.validator

-"""
-Main embedding validator class that orchestrates validation rules.
-"""
-
-from typing import List, Callable, Optional
-import numpy as np
-
-from .base import ValidationRule, ValidationResult
-from .rules import (
-    EdgeInteriorRule,
-    FaceInteriorRule,
-    SelfIntersectionRule,
-    BoundaryEdgeRule,
-    DimensionValidityRule,
-    VertexCountRule,
-    validate_coordinate_array,
-    validate_node_existence,
-)
-
-
-

-[docs]
-class EmbeddingValidator:
-    """
-    Main validator that orchestrates multiple validation rules.
-
-    This class manages a collection of validation rules and applies them
-    to cells based on their dimension and the configured rule set.
-    """
-
-

-[docs]
-    def __init__(
-        self, tolerance: float = 1e-10, edge_checker: Optional[Callable] = None
-    ):
-        """
-        Initialize the embedding validator.
-
-        Args:
-            tolerance: Default tolerance for geometric validation
-            edge_checker: Function to check if an edge exists between two vertex indices
-        """
-        self.tolerance = tolerance
-        self.edge_checker = edge_checker
-
-        self.rules: List[ValidationRule] = [
-            DimensionValidityRule(tolerance),
-            VertexCountRule(tolerance),
-            EdgeInteriorRule(tolerance),
-            FaceInteriorRule(tolerance),
-            SelfIntersectionRule(tolerance),
-            BoundaryEdgeRule(tolerance, edge_checker),
-        ]

-
-
-

-[docs]
-    def add_rule(self, rule: ValidationRule) -> "EmbeddingValidator":
-        """
-        Add a custom validation rule.
-
-        Args:
-            rule: ValidationRule to add
-
-        Returns:
-            Self for method chaining
-        """
-        self.rules.append(rule)
-        return self

-
-
-

-[docs]
-    def remove_rule(self, rule_class: type) -> "EmbeddingValidator":
-        """
-        Remove all rules of a specific type.
-
-        Args:
-            rule_class: Class of rules to remove
-
-        Returns:
-            Self for method chaining
-        """
-        self.rules = [rule for rule in self.rules if not isinstance(rule, rule_class)]
-        return self

-
-
-

-[docs]
-    def set_tolerance(self, tolerance: float) -> "EmbeddingValidator":
-        """
-        Set tolerance for all rules.
-
-        Args:
-            tolerance: New tolerance value
-
-        Returns:
-            Self for method chaining
-        """
-        self.tolerance = tolerance
-        for rule in self.rules:
-            rule.set_tolerance(tolerance)
-        return self

-
-
-

-[docs]
-    def set_edge_checker(self, edge_checker: Callable) -> "EmbeddingValidator":
-        """
-        Set the edge checker function for boundary validation.
-
-        Args:
-            edge_checker: Function that takes two vertex indices and returns bool
-
-        Returns:
-            Self for method chaining
-        """
-        self.edge_checker = edge_checker
-
-        for rule in self.rules:
-            if isinstance(rule, BoundaryEdgeRule):
-                rule.edge_checker = edge_checker
-
-        return self

-
-
-

-[docs]
-    def validate_cell(
-        self,
-        cell_coords: np.ndarray,
-        all_coords: np.ndarray,
-        cell_indices: List[int],
-        all_indices: List[int],
-        dim: int,
-        check_geometric: bool = True,
-    ) -> ValidationResult:
-        """
-        Validate a cell using applicable rules.
-
-        Args:
-            cell_coords: Coordinates of vertices forming the cell
-            all_coords: Coordinates of all vertices in the complex
-            cell_indices: Indices of vertices forming the cell
-            all_indices: Indices of all vertices in the complex
-            dim: Dimension of the cell
-            check_geometric: Whether to check geometric rules (structural rules always checked)
-
-        Returns:
-            ValidationResult for the cell
-
-        Raises:
-            ValueError: If validation fails
-        """
-        # check all rules that apply to this dimension
-        for rule in self.rules:
-            if not rule.applies_to_dimension(dim):
-                continue
-            
-            # Always check structural rules, only check geometric rules if requested
-            if rule.is_structural or check_geometric:
-                result = rule.validate(
-                    cell_coords, all_coords, cell_indices, all_indices, dim
-                )
-
-                if not result.is_valid:
-                    return ValidationResult.invalid(
-                        f"{rule.name}: {result.message}", result.violating_indices
-                    )
-
-        return ValidationResult.valid()

-
-
-

-[docs]
-    def validate_cell_safe(
-        self,
-        cell_coords: np.ndarray,
-        all_coords: np.ndarray,
-        cell_indices: List[int],
-        all_indices: List[int],
-        dim: int,
-        check_geometric: bool = True,
-    ) -> ValidationResult:
-        """
-        Validate a cell, catching and wrapping any exceptions.
-
-        Same as validate_cell but returns ValidationResult instead of raising.
-
-        Args:
-            cell_coords: Coordinates of vertices forming the cell
-            all_coords: Coordinates of all vertices in the complex
-            cell_indices: Indices of vertices forming the cell
-            all_indices: Indices of all vertices in the complex
-            dim: Dimension of the cell
-            check_geometric: Whether to check geometric rules (structural rules always checked)
-
-        Returns:
-            ValidationResult for the cell
-        """
-        try:
-            return self.validate_cell(
-                cell_coords, all_coords, cell_indices, all_indices, dim, check_geometric
-            )
-        except Exception as e:
-            return ValidationResult.invalid(f"Validation error: {str(e)}")

-
-
-

-[docs]
-    def get_rules_for_dimension(self, dim: int) -> List[ValidationRule]:
-        """
-        Get all rules that apply to a specific dimension.
-
-        Args:
-            dim: Cell dimension
-
-        Returns:
-            List of applicable ValidationRules
-        """
-        return [rule for rule in self.rules if rule.applies_to_dimension(dim)]

-
-
-

-[docs]
-    def get_rule_names(self) -> List[str]:
-        """
-        Get names of all registered rules.
-
-        Returns:
-            List of rule names
-        """
-        return [rule.name for rule in self.rules]

-
-
-

-[docs]
-    def disable_rule(self, rule_class: type) -> "EmbeddingValidator":
-        """
-        Temporarily disable a rule type.
-
-        Args:
-            rule_class: Class of rule to disable
-
-        Returns:
-            Self for method chaining
-        """
-        return self.remove_rule(rule_class)

-
-
-

-[docs]
-    def enable_strict_validation(self) -> "EmbeddingValidator":
-        """
-        Enable strict validation with tight tolerance.
-
-        Returns:
-            Self for method chaining
-        """
-        return self.set_tolerance(1e-12)

-
-
-

-[docs]
-    def enable_permissive_validation(self) -> "EmbeddingValidator":
-        """
-        Enable permissive validation with loose tolerance.
-
-        Returns:
-            Self for method chaining
-        """
-        return self.set_tolerance(1e-6)

-
-
-

-[docs]
-    def validate_coordinates(
-        self, coords, expected_dim: Optional[int] = None
-    ) -> ValidationResult:
-        """
-        Validate coordinate array format and dimension consistency.
-
-        Args:
-            coords: Coordinate array to validate
-            expected_dim: Expected dimension, if known
-
-        Returns:
-            ValidationResult for the coordinates
-        """
-        return validate_coordinate_array(coords, expected_dim)

-
-
-

-[docs]
-    def validate_nodes(
-        self, nodes: List, node_checker: Callable, expect_exists: bool = True
-    ) -> ValidationResult:
-        """
-        Validate node existence/non-existence.
-
-        Args:
-            nodes: List of node identifiers to check
-            node_checker: Function that takes node_id and returns bool for existence
-            expect_exists: Whether nodes should exist (True) or not exist (False)
-
-        Returns:
-            ValidationResult for the nodes
-        """
-        return validate_node_existence(nodes, node_checker, expect_exists)

-
-
-    def __repr__(self) -> str:
-        """String representation of the validator."""
-        rule_names = [rule.name for rule in self.rules]
-        return f"EmbeddingValidator(tolerance={self.tolerance}, rules={rule_names})"

-
-
- -
-
- -
-
-
-
- - - - - - - \ No newline at end of file diff --git a/docs/_modules/index.html b/docs/_modules/index.html deleted file mode 100644 index e2e0f34..0000000 --- a/docs/_modules/index.html +++ /dev/null @@ -1,188 +0,0 @@ - - - - - - Overview: module code — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - -
- - -
- -
-
-
-
    -
    • -
  • Overview: module code
    • -
  • -
    • -
-
-
-
- -
- -
-
-
-
- - - - - - - \ No newline at end of file diff --git a/docs/_sources/citing.rst.txt b/docs/_sources/citing.rst.txt deleted file mode 100644 index 9db2cbb..0000000 --- a/docs/_sources/citing.rst.txt +++ /dev/null @@ -1,7 +0,0 @@ -Citing -======= - -To cite `ect` please use the following publication: - - Munch, Elizabeth. An Invitation to the Euler Characteristic Transform. The American Mathematical Monthly, 132(1), 15-25. `doi:10.1080/00029890.2024.2409616 `_. 2024. - diff --git a/docs/_sources/contributing.rst.txt b/docs/_sources/contributing.rst.txt deleted file mode 100644 index 47a593f..0000000 --- a/docs/_sources/contributing.rst.txt +++ /dev/null @@ -1,102 +0,0 @@ -Contributing to the `ect` Package -================================= - -*Note this is a draft document and is subject to change.* - -Getting Started ---------------- - -- Prerequisites -- Setting up the development environment -- Forking the `ect` repository -- Cloning the repository - -Contributing Guidelines ------------------------ - -Code style and formatting -^^^^^^^^^^^^^^^^^^^^^^^^^ - -It is essential for this project to have well documented, clean, and readable code. The following guidelines should be followed when contributing to the `ect` package: - -- Use the PEP 8 style guide for Python code. -- Follow docstring format given below for documenting functions and classes. -- Use the Sphinx documentation system for generating documentation. -- Always include tests for new features and bug fixes. - - -Documentation guidelines -^^^^^^^^^^^^^^^^^^^^^^^^ - -The `ect` package uses the Sphinx documentation system for generating documentation. There are two things to be doing when contributing to the documentation: - -- First, include docstrings in the code which will be autogenerated into the documentation. When in doubt, write too much. -- Second, write documentation in the `doc_source` directory using the reStructuredText format. This package also supports writing files in markdown, although there are some issues when dealing with autogenerated content so it's a bit of a mix at the moment. Note that when the documentation is generated, everything in the `docs` folder is deleted and overwritten, so do not do your work in there, it will be lost! - -Assuming everything (TODO: Add install list) is set up correctly, you can generate the documentation by running the following command from the top level folder:: - - make html - -This will generate the documentation in the ``docs`` directory. You can view the documentation by opening the ``docs/index.html`` file in your browser. - -An example of a docstring for a function is given below. Note the use of indentation since rst is picky about it:: - - def sort_edges(self, theta, return_g=False): - """ - Function to sort the edges of the graph according to the function - - .. math :: - - g_\omega(e) = \max \{ g_\omega(v) \mid v \in e \} - - in the direction of :math:`\\theta \in [0,2\pi]` . - - Parameters: - theta (float): - The angle in :math:`[0,2\pi]` for the direction to sort the edges. - return_g (bool): - Whether to return the :math:`g(v)` values along with the sorted edges. - - Returns: - A list of edges sorted in increasing order of the :math:`g(v)` values. - If ``return_g`` is True, also returns the ``g`` dictionary with the function values ``g[vertex_name]=func_value``. - - """ - - - -Testing guidelines -^^^^^^^^^^^^^^^^^^ - -You should always include tests for new features and bug fixes. The `ect` package uses the `pytest` testing framework. The tests are located in the `tests` directory. To run the tests, you can use the following command:: - - pytest - -or the standard `unittest` python framework by running:: - - make tests - -Get in the habit of writing lots of simple tests. It is better to have too many tests than too few. The tests should be written in a way that they can be run quickly and easily. This will make it easier for you to test your code as you develop it and for others to test your code when they review it. Take a look at the existing tests for examples. - -Note that in order for a function written in the test folder to be run, the function must be prefixed with `test_`. For example, a test function for a function called `my_function` would be called `test_my_function`. - -Issue tracking and pull requests -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -If you find an issue, please post it on the `GitHub issue tracker `_. Provide as much information as possible, including the version of the `ect` package you are using, the operating system you are using, and any other relevant information. - -If you would like to fix an issue and you are a contributor to the project, please create a new branch for the fix. Note that the ``main`` branch is protected so you will not be able to push directly to that branch. Once you are ready to open discussion, you will create a pull request. The pull request should include a description of the issue and the fix. There is a template for pull requests that you can use to fill out helpful information. - -- Note that in order for the `pip install` command to work, the version number in the `pyproject.toml` file must be updated. -- You should also make sure to update the version number to match in the ``doc_source/conf.py`` file. This will ensure that the documentation is updated with the correct version number. -- Be sure to run ``make all`` before committing to ensure that the code is cleaned, the documentation is up to date, and the tests all pass. - -If you are not a contributor, you will need to fork the code and create a pull request from your fork. -Note that all pull requests need to be approved by Liz Munch before they can be merged. - -Conclusion ----------- - -- Acknowledgements -- Future development plans -- Contact information and support \ No newline at end of file diff --git a/docs/_sources/directions.md.txt b/docs/_sources/directions.md.txt deleted file mode 100644 index 35f204e..0000000 --- a/docs/_sources/directions.md.txt +++ /dev/null @@ -1,6 +0,0 @@ -# Directions - -```{eval-rst} -.. automodule:: ect.directions - :members: -``` \ No newline at end of file diff --git a/docs/_sources/ect_on_graphs.md.txt b/docs/_sources/ect_on_graphs.md.txt deleted file mode 100644 index eb95da6..0000000 --- a/docs/_sources/ect_on_graphs.md.txt +++ /dev/null @@ -1,11 +0,0 @@ -# ECT on Graphs - -```{eval-rst} -.. automodule:: ect.ect - :members: -``` - -```{eval-rst} -.. automodule:: ect.sect - :members: -``` diff --git a/docs/_sources/embed_complex.md.txt b/docs/_sources/embed_complex.md.txt deleted file mode 100644 index a65adcb..0000000 --- a/docs/_sources/embed_complex.md.txt +++ /dev/null @@ -1,52 +0,0 @@ -# Embedded Complex - -The `EmbeddedComplex` class is a unified representation for embedded cell complexes supporting arbitrary dimensional cells. - -## Overview - -`EmbeddedComplex` combines and extends the functionality of the previous `EmbeddedGraph` and `EmbeddedCW` classes into a single, more powerful interface. It supports: - -- **0-cells (vertices)**: Points embedded in Euclidean space -- **1-cells (edges)**: Line segments between vertices -- **k-cells for k ≥ 2**: Higher dimensional cells (faces, volumes, etc.) - -## Key Features - -- **Unified Interface**: Single class for all cell complex operations -- **Arbitrary Dimensions**: Support for k-cells of any dimension k ≥ 0 -- **Modular Validation**: Pluggable validation system for embedding properties -- **Backward Compatible**: `EmbeddedGraph` and `EmbeddedCW` remain as aliases - -## Basic Usage - -```python -from ect import EmbeddedComplex - -# Create a complex -K = EmbeddedComplex() - -# Add vertices -K.add_node("A", [0, 0]) -K.add_node("B", [1, 0]) -K.add_node("C", [0.5, 1]) - -# Add edges -K.add_edge("A", "B") -K.add_edge("B", "C") -K.add_edge("C", "A") - -# Add a 2-cell (face) -K.add_face(["A", "B", "C"]) - -# Or use the general method for any dimension -K.add_cell(["A", "B", "C"], dim=2) -``` - -## API Reference - -```{eval-rst} -.. automodule:: ect.embed_complex - :members: - :show-inheritance: - :undoc-members: -``` \ No newline at end of file diff --git a/docs/_sources/index.rst.txt b/docs/_sources/index.rst.txt deleted file mode 100644 index 89a6b83..0000000 --- a/docs/_sources/index.rst.txt +++ /dev/null @@ -1,85 +0,0 @@ -ect: Euler Characteristic Transform in Python -============================================= - -Python computation tools for computing the Euler Characteristic Transform of embedded cell complexes with arbitrary dimensional cells. - -Table of Contents ------------------ - -.. toctree:: - :maxdepth: 1 - :numbered: - :caption: Contents: - - Getting Started - Modules - Tutorials - Migration Guide - Contributing - License - Citing - -Description ------------ - -The package now supports ECT computation on embedded cell complexes with arbitrary dimensional cells through the unified `EmbeddedComplex` class. This includes graphs (1-dimensional), CW complexes with faces (2-dimensional), and higher dimensional cell complexes. - -**Note**: The previous `EmbeddedGraph` and `EmbeddedCW` classes are now aliases for the unified `EmbeddedComplex` class. All existing code will continue to work, but new code should use `EmbeddedComplex` directly. - -For more information on the ECT, see: - - Munch, Elizabeth. An Invitation to the Euler Characteristic Transform. The American Mathematical Monthly, 132(1), 15-25. `doi:10.1080/00029890.2024.2409616 `_. 2024. - -Getting Started ---------------- - -Documentation and tutorials -^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -* The documentation is available at: `munchlab.github.io/ect `_ -* A comprehensive tutorial for the unified `EmbeddedComplex` class can be found `here `_ -* The source code can be found at: `github.com/MunchLab/ect `_ - -Dependencies -^^^^^^^^^^^^ - -* `networkx` -* `numpy` -* `matplotlib` -* `numba` - -Installing -^^^^^^^^^^ - -The package can be installed using pip: - -.. code-block:: bash - - pip install ect - - -Alternatively, you can clone the repo and install directly - -.. code-block:: bash - - git clone git@github.com:MunchLab/ect.git - cd ect - pip install . - -Authors -------- - -This code was written by `Liz Munch `_ along with her research group and collaborators. People who have contributed to `ect` include: - -- `Sarah McGuire `_ -- `Yemeen Ayub `_ - -License -------- - -This project is licensed under the GPLv3 License - see the License file for details - -Contact Information -------------------- - -- Liz Munch: `Website `_, `Email `_ diff --git a/docs/_sources/installation.rst.txt b/docs/_sources/installation.rst.txt deleted file mode 100644 index 57c42cf..0000000 --- a/docs/_sources/installation.rst.txt +++ /dev/null @@ -1,37 +0,0 @@ -Installation -============ - -Prerequisites -------------- - -Before installing `ect`, make sure you have the following prerequisites: - -- Python (version 3.7 or higher) -- Pip (Python package installer) - -Installing `ect` ----------------- - -To install `ect`, run the following in a terminal. - -.. code-block:: bash - - pip install ect - -Alternatively, you can install directly from the source by cloning the repository and running the following command: - -.. code-block:: bash - - git clone https://github.com/MunchLab/ect - cd ect - pip install . - - -Uninstalling `ect` ------------------- - -To uninstall `ect`, simply run the following command: - -.. code-block:: bash - - pip uninstall ect diff --git a/docs/_sources/license.md.txt b/docs/_sources/license.md.txt deleted file mode 100644 index ba65064..0000000 --- a/docs/_sources/license.md.txt +++ /dev/null @@ -1,9 +0,0 @@ -# GPL-3.0 License - -![GPL-3.0 License](https://www.gnu.org/graphics/gplv3-127x51.png) - -The full text of the GPL-3.0 license agreement can be found at: - -- [GNU General Public License, version 3.0](https://www.gnu.org/licenses/gpl-3.0.en.html) - -Please read the license agreement carefully before using the software. diff --git a/docs/_sources/modules.rst.txt b/docs/_sources/modules.rst.txt deleted file mode 100644 index 9dbfbfa..0000000 --- a/docs/_sources/modules.rst.txt +++ /dev/null @@ -1,11 +0,0 @@ -Table of Contents -******************* - -.. toctree:: - :maxdepth: 2 - - - Embedded Complex - Validation System - ECT on graphs - Directions \ No newline at end of file diff --git a/docs/_sources/notebooks/Matisse/example_matisse.ipynb.txt b/docs/_sources/notebooks/Matisse/example_matisse.ipynb.txt deleted file mode 100644 index 9921e17..0000000 --- a/docs/_sources/notebooks/Matisse/example_matisse.ipynb.txt +++ /dev/null @@ -1,310 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# ECT on Matisse's \"The Parakeet and the Mermaid\"\n", - "\n", - "\n", - "\n", - " Here, we are going to give an example of using the ECT to classify the cutout shapes from Henri Matisse's 1952 [\"The Parakeet and the Mermaid\"](https://www.moma.org/audio/playlist/6/312).\n", - "\n", - "\n", - "\n", - " ![matisse.jpg](matisse.jpg)\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": "# -----------------\n# Standard imports\n# -----------------\nimport numpy as np # for arrays\nimport matplotlib.pyplot as plt # for plotting\nfrom sklearn.decomposition import PCA # for PCA for normalization\nfrom scipy.spatial import distance_matrix\n\nfrom os import listdir # for retrieving files from directory\nfrom os.path import isfile, join # for retrieving files from directory\nfrom sklearn.manifold import MDS # for MDS\nimport pandas as pd # for loading in colors csv\nimport os\nimport zipfile\n\nimport warnings\nwarnings.filterwarnings('ignore')\n\n# ---------------------------\n# The ECT packages we'll use\n# ---------------------------\nfrom ect import ECT, EmbeddedComplex # for calculating ECTs\n# Note: EmbeddedGraph is now unified into EmbeddedComplex\n# For backward compatibility, you can still use:\n# from ect import EmbeddedGraph\n\n# Simple data paths\ndata_dir = \"outlines/\"\ncolors_path = \"colors.csv\"\n\nfile_names = [\n f for f in listdir(data_dir) if isfile(join(data_dir, f)) and f[-4:] == \".txt\"\n]\nfile_names.sort()\nprint(f\"There are {len(file_names)} files in the directory\")" - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " We've taken care of the preprocessing in advance by extracting out the shapes from the image. You can download these outlines here: [outlines.zip](outlines.zip).\n", - "\n", - "\n", - "\n", - " \"Matisse" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": "i = 3\nshape = np.loadtxt(data_dir + file_names[i])\n# shape = normalize(shape)\nG = EmbeddedComplex() # Using the unified EmbeddedComplex class\nG.add_cycle(shape)\nG.plot(with_labels=False, node_size=10)" - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " We're going to align the leaf using the PCA coordinates, min-max center, and scale it to fit in a ball of radius 1 for ease of comparisons." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "\n", - "G.transform_coordinates(projection_type=\"pca\") # project with PCA\n", - "G.scale_coordinates(1) # scale to radius 1\n", - "G.plot(with_labels=False, node_size=10, bounding_circle=True)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " And then we can compute the ECT of this leaf." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "OMP: Info #276: omp_set_nested routine deprecated, please use omp_set_max_active_levels instead.\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "num_dirs = 50 # set number of directional axes\n", - "num_thresh = 50 # set number of thresholds each axis\n", - "\n", - "myect = ECT(num_dirs=num_dirs, num_thresh=num_thresh); # intiate ECT\n", - "result = myect.calculate(G); # calculate ECT on embedded graph\n", - "\n", - "result.plot(); # plot ECT" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " Let's just make a data loader with all of this for ease in a bit." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": "def matisse_ect(filename, ect):\n shape = np.loadtxt(data_dir + filename)\n G = EmbeddedComplex() # Using the unified EmbeddedComplex class \n G.add_cycle(shape)\n G.transform_coordinates(projection_type=\"pca\")\n G.scale_coordinates(1)\n result = ect.calculate(G)\n return result" - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " And now we can load in all the outlines, compute their ECT and store it in a 3D array." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "num_dirs = 50 # set number of directional axes\n", - "num_thresh = 50 # set number of thresholds each axis\n", - "\n", - "ect_arr = np.zeros((len(file_names), num_dirs, num_thresh))\n", - "myect = ECT(num_dirs=num_dirs, num_thresh=num_thresh, bound_radius=1)\n", - "\n", - "for i in range(len(file_names)): # for each leaf\n", - " ect_arr[i, :, :] = matisse_ect(file_names[i], myect)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " Here, we are just going to compute the distance between two ECTs using $L_2$ distance." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "flattened_ect = ect_arr.reshape(len(file_names), num_dirs * num_thresh)\n", - "D = distance_matrix(flattened_ect, flattened_ect)\n", - "plt.matshow(D)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " For visualization purposes, we can project this data into 2D using Multi Dimensional Scaling (MDS). Here we plot each figure at the MDS coordinates." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "n_components = 2 # select number of components\n", - "mds = MDS(\n", - " n_components=n_components, # initialize MDS\n", - " dissimilarity=\"precomputed\", # we have precomputed the distance matrix\n", - " normalized_stress=\"auto\",\n", - " random_state=5, # select random state for reproducibility\n", - ")\n", - "MDS_scores = mds.fit_transform(D) # get MDS scores\n" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, \"MDS of Matisse's Leaves via ECT distances\")" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# read in color hexcodes\n", - "col_df = pd.read_csv(colors_path, header=None)\n", - "\n", - "scale_val = 6 # set scale value\n", - "plt.figure(figsize=(5, 5)) # set figure dimensions\n", - "\n", - "for i in range(len(file_names)): # for each leaf\n", - " shape = np.loadtxt(data_dir + file_names[i]) # get the current shape\n", - " shape = shape - np.mean(shape, axis=0) # zero center shape\n", - " shape = (\n", - " scale_val * shape / max(np.linalg.norm(shape, axis=1))\n", - " ) # scale to radius 1 then mult by scale_val\n", - "\n", - " trans_sh = shape + MDS_scores[i] # translate shape to MDS position\n", - "\n", - " plt.fill(trans_sh[:, 0], trans_sh[:, 1], c=col_df[0][i], lw=0) # plot shape\n", - " plt.gca().set_aspect(\"equal\")\n", - "\n", - "plt.title(\"MDS of Matisse's Leaves via ECT distances\")\n", - "# plt.savefig(\"Matisse_MDS.png\", bbox_inches = 'tight', dpi=300)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Acknowledgements\n", - "\n", - "\n", - "\n", - " This notebook was written by [Liz Munch](https://elizabethmunch.com/) based on [original code](https://github.com/DanChitwood/matisse_test) from [Dan Chitwood](https://www.canr.msu.edu/people/dr_dan_chitwood)." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "base", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.7" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} \ No newline at end of file diff --git a/docs/_sources/notebooks/Tutorial-EmbeddedComplex.ipynb.txt b/docs/_sources/notebooks/Tutorial-EmbeddedComplex.ipynb.txt deleted file mode 100644 index 1738074..0000000 --- a/docs/_sources/notebooks/Tutorial-EmbeddedComplex.ipynb.txt +++ /dev/null @@ -1,624 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Tutorial: ECT for Embedded Cell Complexes\n", - "\n", - "This tutorial will walk you through using the `ECT` package. Particularly we will show the features of `EmbeddedComplex` class for computing the Euler Characteristic Transform on complexes with arbitrary dimensional cells.\n", - "\n", - "The `EmbeddedComplex` class combines and extends the functionality of the previous `EmbeddedGraph` and `EmbeddedCW` classes, supporting:\n", - "- **0-cells** (vertices) with embedded coordinates\n", - "- **1-cells** (edges)\n", - "- **k-cells** for k ≥ 2 (faces, volumes, and higher-dimensional cells).\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "from ect import EmbeddedComplex, ECT, Directions\n", - "from ect.utils.examples import create_example_graph, create_example_cw, create_example_3d_complex" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Basic Usage: Creating Simple Complexes\n", - "\n", - "### Example 1: Graph (1-skeleton)\n", - "\n", - "Let's start with a simple triangle graph (for legacy users this can be equivalently done using `EmbeddedGraph`). " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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ceeedCA4OhqenJyZNmoSff/65R69n06ZNiI+Ph5+fH/z9/TFu3LgO7V24cKHbte0PHToEhUKBL7/8ssNz6enpUCgU+O9//2t9rKSkBA8++CDCw8OhVqsxZswYfPbZZzb7td8HsWnTJjz33HMYMGAAvL298b//+7/4f//v/wEAZs+eDYVCYXO/hL17CFpaWvDiiy9i+PDh8PT0RGRkJG6//Xab12WxWPDBBx9gzJgx8PT0RHh4OB555BHU1dV1eK0ajQYhISHw8vLC4MGDe3zyV6vViIiI6NG+1/KPf/wDkydPhre3N4KCgjBz5swOV0l+/fVXzJgxAz4+PvDz88PNN9/c7boJ9jAajXjppZcwbNgweHp6ol+/fpg+fbrNdMtGoxFnzpxxeHltR/v0qVOnMGfOHHh5eWHgwIF49dVX7d7HY7FY8OKLL6J///7w9vbG7Nmzcfr0abv3Q9TX1+NPf/oToqKioFarMXToULz55psdjuvIeyUsLAzjx4/Hv//9b4deNyEu6AoBwcS+ffsAABMnTrR5/OjRowCASZMm2Tzev39/DBw40Pp8V2RmZuKWW25BZGQkVq5ciYiICBQUFOC///0vVq5cCaDthDht2jQMGDAATz/9NHx8fPCvf/0LCxYswPfff4/bbrvN4deSmZmJe+65BykpKdZFcQoKCrB3715rewCQkpICAF1+Xz9p0iTExsbiX//6V4eFcTZv3oygoCBoNBoAQEVFBaZMmQKFQoHHHnsMoaGh+PXXX7F06VJotVr86U9/stn/lVdegUqlwpNPPgmDwYC0tDT88Y9/xP/+7//imWeewahRowDA+t/rMZvNuOWWW5CdnY27774bK1euhE6nQ2ZmJk6ePIkhQ4YAaLvc+8UXX2DJkiX44x//iKKiInz00Uc4evQo9u7dCw8PD1RWViItLQ2hoaF4+umnERgYiOLiYvzwww8Oe+ebl156CS+++CKmTp2Kl19+GSqVCgcOHMD27duRlpYGAPj666/xwAMPQKPR4M0330RzczM+/vhjTJ8+HUePHmW62fTFF1/EunXr8NBDD2Hy5MnQarU4dOgQjhw5grlz5wJoK/hGjRqFBx54oNt7Ihzt0+Xl5Zg9ezZMJpN1uw0bNsDLy6vDMdesWYO33noL8+fPh0ajwbFjx6DRaNDS0mKzXXNzM5KTk1FSUoJHHnkEgwYNwr59+7BmzRqUlZXhgw8+AOD4ewUA4uPj8dNPPznskxARHEEw8Nxzz3EAOJ1OZ/P422+/zQHgLl++3GGfhIQEbsqUKV0e12QycYMHD+aio6O5uro6m+csFov1/1NSUrhx48ZxLS0tNs9PnTqVGzZsmPWxnJwcDgCXk5NjfeyBBx7goqOjrb+vXLmS8/f350wmU5fZoqOjbfbrjDVr1nAeHh5cbW2t9TGDwcAFBgZyDz74oPWxpUuXcpGRkVx1dbXN/nfffTcXEBDANTc327yG2NhY62PtfPfddx1eXzvJyclccnKy9ffPPvuMA8C99957HbZtd7t7924OAPfNN9/YPL9t2zabx3/88UcOAJeXl9etD1by8vI4ANznn3/u8D6FhYWcm5sbd9ttt3Fms9nmufbXptPpuMDAQG7ZsmU2z5eXl3MBAQE2j69du5a7/rQYHR3NPfDAA9bfJ0yYwN18881d5ioqKuIA2OzXGY726T/96U8cAO7AgQPWxyorK7mAgAAOAFdUVGR9Xe7u7tyCBQts2nnxxRc7ZHrllVc4Hx8f7ty5czbbPv3005xSqbS+nx19r3Acx73++uscAK6ioqLbbQlxQV8ZEEzU1NTA3d0dvr6+No/r9XoAbZeAr8fT09P6fGccPXoURUVF+NOf/tRhSeL2YWC1tbXYvn077rrrLuh0OlRXV6O6uho1NTXQaDQoLCxESUmJw68lMDAQTU1N3a6sV1xc7NDd/AsXLoTRaLT5azkjIwP19fVYuHAhAIDjOHz//feYP38+OI6zvobq6mpoNBo0NDTgyJEjNsd94IEH7P4V6Cjff/89QkJC7N7c2e72u+++Q0BAAObOnWuTKT4+Hr6+vsjJyQEA67/Nf//7XxiNxh5n4ouffvoJFosFL7zwQocRL+2vLTMzE/X19bjnnntsXptSqURiYqL1tTlKYGAgTp06hcLCwk63iYmJAcdx3V4dYOnTW7duxZQpUzB58mTr/qGhobjvvvtsjpmdnQ2TyYTly5fbPG7v3/+7777DjBkzEBQUZOMmNTUVZrMZu3btsr5mR94rQNu01EDbDaOEtKCvDAheaP/AMhgMHZ5raWmxPq/X69HQ0GDzfEREhPW77LFjx3baxvnz58FxHJ5//nk8//zzdreprKzEgAEDHMq8fPly/Otf/8KNN96IAQMGIC0tDXfddRfmzZvn0P7XM2HCBIwcORKbN2/G0qVLAbR9XRASEoI5c+YAAKqqqlBfX48NGzZgw4YNnb6Gaxk8eHCP8rRz4cIFjBgxwubejuspLCxEQ0MDwsLCusyUnJyMO+64Ay+99BLef/99zJo1CwsWLMC9995rtxjki4aGBpuiUqVSITg4GBcuXICbmxtGjx7d6b7tH9zt/wbX4+/vz5Tl5Zdfxu9+9zsMHz4cY8eOxbx583D//fdj/PjxTMcB2Pr0pUuXkJiY2OH5ESNG2Px+6dIlAMDQoUNtHg8ODrZ+WLdTWFiI48ePIzQ0tNO2Abb3Cvd/s+FfP58DIX6oICCY6NevH0wmE3Q6Hfz8/KyPR0ZGAgDKysoQFRVls09ZWZn1r5rNmzdjyZIlNs9zDi6n0X6T05NPPmn9Pv56rj8JdkVYWBjy8/ORnp6OX3/9Fb/++is+//xzLFq0yO7NgY6wcOFCvPbaa6iuroafnx9+/vln3HPPPdYP4/bX8Pvf/77DvQbtXP/B0purA45isVgQFhaGb775xu7z7R8YCoUCW7Zswf79+/Gf//wH6enpePDBB/Huu+9i//79Ha4c8cXKlStt/k2Sk5NtJp3qinbnX3/9td0bGLsqlOwxc+ZMXLhwAf/+97+RkZGBv//973j//ffxySef4KGHHmI6Ft99mhWLxYK5c+di9erVdp8fPnw4ALb3SvtNqCEhIU7LTTgHKggIJtqHDhYVFdl8cMXFxQFouwP92kuapaWluHr1Kh5++GEAgEajsXvZsf3GtpMnT3YYwdBObGwsAMDDw6PTbVhRqVSYP38+5s+fD4vFguXLl+Nvf/sbnn/++R6diBcuXIiXXnoJ33//PcLDw6HVanH33Xdbnw8NDYWfnx/MZnOvXgPLX19DhgzBgQMHYDQa4eHh0ek2WVlZmDZtmkMFyJQpUzBlyhS89tpr+Pbbb3Hfffdh06ZNzB+IjrJ69Wr8/ve/t/7e/pfukCFDYLFYcPr0aWsfvJ72vhUWFsZbvwkODsaSJUuwZMkSNDY2YubMmXjxxReZXz9Ln46Ojrb7NcXZs2c7bAe0XX249upSTU1NhxEjQ4YMQWNjo0NeHH2vFBUVISQkpNOrDoR4oXsICCaSkpIAtH3wX8uYMWMwcuRIbNiwAWaz2fr4xx9/DIVCgTvvvBNA25WE1NRUmx+gbdTC4MGD8cEHH6C+vt7m2O1XEMLCwjBr1iz87W9/szuci3XK1JqaGpvf3dzcrEXOtV99ODLssJ1Ro0Zh3Lhx2Lx5MzZv3ozIyEjMnDnT+rxSqcQdd9yB77//HidPnuzxa/Dx8QGADq7scccdd6C6uhofffRRh+fa3d51110wm8145ZVXOmxjMpms7dTV1XW4otP+QWzv6yK+GD16tE2fiY+PBwAsWLAAbm5uePnllzsMk2vPqdForPNh2Lvvobf9xtfXF0OHDrV5/Y4OO2Tp0zfddBP279+PgwcP2jx//VWdlJQUuLu74+OPP7Z53N6//1133YXc3Fykp6d3eK6+vt46y6ij7xUAOHz4sPU8QUgLukJAMBEbG4uxY8ciKyurw9jzt99+G7feeivS0tJw99134+TJk/joo4/w0EMPdTokrh03Nzd8/PHHmD9/PuLi4rBkyRJERkbizJkzOHXqlPWEtX79ekyfPh3jxo3DsmXLEBsbi4qKCuTm5uLq1as4duyYw6/loYceQm1tLebMmYOBAwfi0qVL+PDDDxEXF2eT15Fhh9eycOFCvPDCC/D09MTSpUs73Oz2xhtvICcnB4mJiVi2bBlGjx6N2tpaHDlyBFlZWaitre22jbi4OCiVSrz55ptoaGiAWq3GnDlz7N4DsGjRInz11VdYtWoVDh48iBkzZqCpqQlZWVlYvnw5fve73yE5ORmPPPII1q1bh/z8fKSlpcHDwwOFhYX47rvv8Je//AV33nknvvzyS/z1r3/FbbfdhiFDhkCn02Hjxo3w9/fHTTfdZG1z8eLF+PLLL1FUVNTtkL6PPvoI9fX1KC0tBQD85z//wdWrVwG03QgXEBDQ6b5Dhw7Fs88+i1deeQUzZszA7bffDrVajby8PPTv3x/r1q2Dv78/Pv74Y9x///2YOHEi7r77boSGhuLy5cv45ZdfMG3aNLsflp0xevRozJo1C/Hx8QgODsahQ4ewZcsWPPbYY9ZtWIYdOtqnV69eja+//hrz5s3DypUrrcMOo6Ojcfz4cevxwsPDsXLlSrz77ru49dZbMW/ePBw7dgy//vorQkJCbK4uPfXUU/j5559xyy23YPHixYiPj0dTUxNOnDiBLVu2oLi4GCEhIQ6/VyorK3H8+HGsWLHCYZ+EiBBodAMhYd577z3O19e3w1A4jmsblhYXF8ep1Wpu4MCB3HPPPce1trY6fOw9e/Zwc+fO5fz8/DgfHx9u/Pjx3IcffmizzYULF7hFixZxERERnIeHBzdgwADulltu4bZs2WLdxpFhh1u2bOHS0tK4sLAwTqVScYMGDeIeeeQRrqyszKY9R4cdtlNYWMgB4ABwe/bssbtNRUUFt2LFCi4qKorz8PDgIiIiuJSUFG7Dhg0dXsN3331n9xgbN27kYmNjOaVSafNarx92yHEc19zczD377LPc4MGDre3deeed3IULF2y227BhAxcfH895eXlxfn5+3Lhx47jVq1dzpaWlHMdx3JEjR7h77rmHGzRoEKdWq7mwsDDulltu4Q4dOmRznDvuuIPz8vLqMITUHtHR0VZf1/+0D6Xrjs8++4y74YYbOLVazQUFBXHJyclcZmamzTY5OTmcRqPhAgICOE9PT27IkCHc4sWLbbI7Muzw1Vdf5SZPnswFBgZyXl5e3MiRI7nXXnvNpp+zDDvkOMf6NMdx3PHjx7nk5GTO09OTGzBgAPfKK69wn376aQdXJpOJe/7557mIiAjOy8uLmzNnDldQUMD169eP+8Mf/mBzTJ1Ox61Zs4YbOnQop1KpuJCQEG7q1KncO++8Y31Njr5XPv74Y87b25vTarUOvW5CXCg4zsE7ugji/2hoaEBsbCzeeust6930BHEt4eHhWLRoEd5++22hoxD/R319PYKCgvDqq6/i2WefdUobN9xwA2bNmoX333/fKccnnAvdQ0AwExAQgNWrV+Ptt98W7fLHhHCcOnUKer0e//M//yN0lD6LvXk/2mcddNbS2Nu2bUNhYSHWrFnjlOMTzoeuEBAEQciML774Al988QVuuukm+Pr6Ys+ePfjnP/+JtLQ0uzcQEgRANxUSBEHIjvHjx8Pd3R1vvfUWtFqt9UbDV199VehohIihKwQEQRAEQdA9BARBEARBUEFAEARBEAQkcg+BxWJBaWkp/Pz8aMEMgiAIgmCA4zjodDr079+/w0Rp1yKJgqC0tLTDgjkEQRAEQTjOlStXMHDgwE6fl0RB0L6q3pUrV5iXKnUV16/+R3QPOWOHnLFDztghZ2yI3ZdWq0VUVFS3GSVRELR/TeDv7y/agsBgMIg2m1ghZ+yQM3bIGTvkjA2p+OruK3e6qZAnpNAZxAY5Y4ecsUPO2CFnbMjFFxUEPFFdXS10BMlBztghZ+yQM3bIGRty8SWJiYm0Wi0CAgLQ0NAgm0qMIAiCIFyBo5+hdIWAJ0pKSoSOIDnIGTvkjB1yxg45Y0MuvugKAU9wHEdzJDBCztghZ+yQM3bIGRti90VXCFxMaWmp0BEkBzljh5yxQ87YIWdsyMUXFQQ8ERISInQEyUHO2CFn7JAzdsgZG3LxRQUBT2i1WqEjSA5yxg45Y4ecsUPO2JCLLyoIeEKtVgsdQXKQM3bIGTvkjB1yxoZcfFFBQBAEQRAEFQR80draKnQEyUHO2CFn7JAzdsgZG3LxRQUBT/j4+AgdQXKQM3bIGTvkjB1yxoZcfFFBwBN1dXVCR5Ac5IwdcsYOOWOHnLEhF180MRFPWCwWuLlRfcUCOWOHnLFDztghZ2yI3RdNTORiysrKhI4gOcgZO+SMHXLGDjljQy6+6AoBQRAEQcgYukLgYuSyuIUrIWfskDN2yBk75IwNufiigoAnQkNDhY4gOcgZO+SMHXLGDjljQy6+3IUO0BXr16/H+vXrYTabhY7SLfX19QgLCxM6hqQgZ+yIxVlBQQFyc/cjNy8PxZcugeMAhQKIiY5GUkICkpKmYNSoUULHBCAeZ1KCnLEhF190DwFPNDY2wtfXV+gYkoKcsSOkM71ej2++/RZffbsJIYMGI3ZCPGLHjEd4VDQUCgU4jkPFlUu4eOo4Lh47jOrLRVh0792479574eXlJUhmgPpZTyBnbIjdl6OfoaK+QiAlTCaT0BEkBzljRyhnu3fvxlPPPIfEm2/Ho+/9DWrPjh/wCoUCEYNiEDEoBlNvvBWGFj1yt/6MTzU34q3XXsGMGTMESE79rCeQMzbk4osKAp6wWCxCR5Ac5IwdVzuzWCx46uk1OHu1DCve3wAfP8ev0Kk9vTDr9oVImHsj3nj3Vfz0n//i7TfWuXy8NvUzdsgZG3LxRTcV8oSnp6fQESQHOWPHlc4sFguWLHsYrQGheHDtm0zFwLX4+Plj6YtvoTUgFEuWPezykyf1M3bIGRty8UUFAU/IZT1sV0LO2HGls6eeXgP/2JGYfed9vBxv9p33wT92JFaveYaX4zkK9TN2yBkbcvFFBQFPhISECB1BcpAzdlzlbNeuXThzpZS3YqCd2Xfeh4JLV7F7925ej9sV1M/YIWdsyMUXFQQ8UVFRIXQEyUHO2HGFM71ej9XPPo+7//ycU45/95+fw1PPPAe9Xu+U418P9TN2yBkbcvFFBQFPDBgwQOgIkoOcseMKZ998+y0Sb769x/cMdIePfwAm33wbvv3nP51y/OuhfsYOOWNDLr6oIOAJuUxd6UrIGTuucPbVt5sw5cb5Dm1rNpnwr4/exeM3zsCf5s/Gnxek4uPnn0KTtqHL/ZJuvBVffuOagoD6GTvkjA25+KJhhzwRHh4udATJQc7YcbazgoIChAwabHeeAXv89dk/Q9dQh3Wb/gPfgEBwHIfc9P9C11APH/+ATvdTe3ohZFAMCgoKnD6jIfUzdsgZG3LxRVcIeKK6ulroCJKDnLHjbGe5ufsROyHeoW3LLhVhX/p/8Ni69+EbEAigbXKiqfPmIyIqutv9B4+Px/79B3oT1yGon7FDztiQiy8qCHhCrFMqixlyxo6zneXm5SF2zHiHtr14+gQio2PhH9SvR23FjhmP3Ly8Hu3LAvUzdsgZG3LxRQUBT7S0tAgdQXKQM3ac7az40iWEO/DXPR9EDIpBUXGx09uhfsYOOWNDLr6oIOAJhUIhdATJQc7YcbaztlULHWsjdvQ4lF26CF1dbY/aalsQqUe7MrdDsEHO2JCLLyoIeMLDw0PoCJKDnLHjbGcKBeDoAqiR0YMxJe1mrH/uz9ZRBW03Ff6C8iuXut2f4zi44jxK/YwdcsaGXHxRQcATTU1NQkeQHOSMHWc7i4mORoUDH+btrHjtPcSMGI2n77oZK2+ZhZU3J+PY3p3w+7+bDLui/HIxBsfE9Dysg1A/Y4ecsSEXXzTskCeCg4OFjiA5yBk7znaWlJCA06eOI2JQjEPbu3t44O4/PoW7//gUc1sXTx1HUkIC836sUD9jh5yxIRdfdIWAJyorK4WOIDnIGTvOdpaUNAUXjx12ahvtFB0/jClTEp3eDvUzdsgZG3LxRQUBT8hl6kpXQs7YcbazUaNGofpyEQwtzl1nwNCiR/XlYqdPSgRQP+sJ5IwNufiigoAn5DJ1pSshZ+y4wtmie+/G/l//49Q2cn/9GQ/cd49T22iH+hk75IwNufiigoAnIiMjhY4gOcgZO65wdt+99+LALz+gSeecNd6btA04+MuPuPce1xQE1M/YIWdsyMUXFQQ8UV5eLnQEyUHO2HGFMy8vL7z9+qvY9O6rTjn+pndfxTvrXoOXl2PrJfQW6mfskDM25OKLCgKeCAoKEjqC5CBn7LjK2YwZMzAyqj9ytnzD63FztnyDUdEDMX36dF6P2xXUz9ghZ2zIxRcVBDzR3NwsdATJQc7YcaWzt99YB+3FM7wVBTlbvoH24hm8te51Xo7nKNTP2CFnbMjFFxUEPOHuTlM6sELO2HGlMzc3N3y+cQM86ivx0f883uN7Cpq0Dfjbs6ug1lbj840b4Obm2tMO9TN2yBkbcvFFBQFPuPokJwfIGTuudubm5obbf3crYvoF4PUHF2LHD5sdHpJoaNFj+5Zv8eqS/4cR/cOw7tVXBPk3p37GDjljQy6+5FHWiICWlhb4+fkJHUNSkDN2XO1Mp9Nh165diB40CH945BGcOHkSH696BCGDYjB4fDxix4xHxKCY/1uoiEP55WJcPHUcRccPo+bKJdy38P8h6v7fo6WlBfv27UNycrLLsrdD/YwdcsaGXHwpOEdXMhEQrVaLgIAANDQ0iHbdaYPBALVaLXQMSUHO2HG1s59++gnHjh3DwIED8eCDD1pXdSsoKMD+/QeQm5eHouLi/1slERgcE4OkhARMmZJonXTo5MmT+P777+Hu7o7HHnsMAQEBLssPUD/rCeSMDbH7cvQzlK4Q8ER1dbVsZqtyFeSMHVc6KykpwbFjxwAA8+bNs1niddSoURg1ahSWLFnc7XHGjBmDvLw8XL58GdnZ2bj99tudFdku1M/YIWdsyMWXPL74EAH9+/cXOoLkIGfsuMoZx3HYtm0bAGDChAm9OtkpFApoNBoAwIkTJ3DlyhVeMjoK9TN2yBkbcvFFBQFPlJaWCh1BcpAzdlzl7MSJE7h69So8PDyQkpLS6+P1798fN9xwAwBg27ZtcOU3ldTP2CFnbMjFFxUEPCGXCtGVkDN2XOGstbUVWVlZANomKOLrZqk5c+ZApVKhtLTU+lWEK6B+xg45Y0Muvqgg4Am5VIiuhJyx4wpne/bsgU6nQ2BgIJKSkng7rq+vr3WUQVZWFgwGA2/H7grqZ+yQMzbk4osKAp4ICQkROoLkIGfsONtZfX099u3bBwBIS0vjfcKVxMREBAcHo6mpCbt37+b12J1B/YwdcsaGXHz1qCBYv349YmJi4OnpicTERBw8eLDL7T/44AOMGDECXl5eiIqKwhNPPIGWlpYeBRYrWq1zVoaTM+SMHWc7y8zMhNlsRkxMDEaOHMn78ZVKJdLS0gAA+/fvR21tLe9tXA/1M3bIGRty8cVcEGzevBmrVq3C2rVrceTIEUyYMAEajQaVlZV2t//222/x9NNPY+3atSgoKMCnn36KzZs345lnnul1eDHh6ekpdATJQc7Ycaaz4uJinD59GgqFosMwQz4ZPnw4hgwZArPZjMzMTKe0cS3Uz9ghZ2zIxRdzQfDee+9h2bJlWLJkCUaPHo1PPvkE3t7e+Oyzz+xuv2/fPkybNg333nsvYmJikJaWhnvuuafbqwpSw2KxCB1BcpAzdpzlzGKxWIcZxsfHIzw83CntAL8NQ1QoFDhz5gwuXrzotLYA6mc9gZyxIRdfTAVBa2srDh8+jNTU1N8O4OaG1NRU5Obm2t1n6tSpOHz4sLUAuHjxIrZu3Yqbbrqp03YMBgO0Wq3Nj9gxmUxCR5Ac5IwdZzk7evQoKioq4OnpidmzZzuljWsJDQ1FQkICgLZhiM48oVI/Y4ecsSEXX0wFQXV1Ncxmc4e/HsLDw1FeXm53n3vvvRcvv/wypk+fDg8PDwwZMgSzZs3q8iuDdevWISAgwPoTFRUFoG2+6NLSUlgsFpSUlABom02ttbUVlZWVaGxsRH19PWpra6HX61FeXg6TyWSzrdFoRHl5OZqbm1FbW4u6ujo0NTWhoqICRqPRZluz2YzS0lLo9XrU1NSgoaEBOp0OVVVVMBgMNtt6eXmhpKQEBoMBVVVV1kKmuroaer3e4dzNzc12c5tMpg65Gxsb7ea2WCzd5uY4zua/7bl1Oh0aGhpQU1PTaW6j0YiKigo0Njairq6OKXd9fT0aGxtRWVkJDw+PTnNXV1dbHdrL3b5PV7nNZrPd3E1NTR1yX++wPbder++Qu7W11W7ulpYWu7lLS0vt5q6srOyQu6ysrMvcRqOx2z5bVlZmk1un03WZu6GhAbm5ufD09MS0adPQ3Nzc7XtNp9PZvNe6y11XV9ch98iRI+Hl5QWj0Yi8vDxr7mv7bGVlZYf3GsdxKC0ttftes5dbq9WK4hxx/XtNzOcIrVYrinNEZ31WbOeI1tZW0Zwj7L3XHB0FwbSWQWlpKQYMGIB9+/bZDEdavXo1du7ciQMHDnTYZ8eOHbj77rvx6quvIjExEefPn8fKlSuxbNkyPP/883bbMRgMNkOStFotoqKiRL2WQWlpqWzGoroKcsaOM5ylp6dj//79CAkJwR/+8AcolUpej98VeXl52Lp1K7y8vPD444/Dy8uL9zaon7FDztgQuy+nrGUQEhICpVKJiooKm8crKioQERFhd5/nn38e999/Px566CEAwLhx49DU1ISHH34Yzz77rN1lI9VqtagXirBHZ6+f6Bxyxg7fzqqrq61f52k0GpcWA0Db/QqHDh1CZWUlduzYgRtvvJH3NqifsUPO2JCLL6avDFQqFeLj45GdnW19zGKxIDs7u9MJTJqbmzt86LefdCSw0KLDlJWVCR1BcpAzdvh2lpGRAYvFguHDh2Po0KG8HtsR3NzcrOsc5OXldTpaqTdQP2OHnLEhF1/MowxWrVqFjRs34ssvv0RBQQEeffRRNDU1YcmSJQCARYsWYc2aNdbt58+fj48//hibNm1CUVERMjMz8fzzz2P+/Pku/2vEmchhpStXQ87Y4dNZYWEhCgsL4ebmZp0bQAhiY2MxcuRIcByH9PR03v9QoH7GDjljQy6+mKchW7hwIaqqqvDCCy+gvLwccXFx2LZtm/VGw8uXL9tcEXjuueegUCjw3HPPoaSkBKGhoZg/fz5ee+01/l6FCCgpKZFNp3AV5IwdvpyZzWakp6cDaJs9sF+/fr0+Zm9IS0tDYWEhLl68iHPnzmHEiBG8HZv6GTvkjA25+GK6qVAoHL0hQkiMRiM8PDyEjiEpyBk7fDnLzc1FRkYGvL298fjjj4tiYpWsrCzs3bsXQUFBWL58OW/TJlM/Y4ecsSF2X45+htJaBjzhiilY5QY5Y4cPZ01NTdi5cycAICUlRRTFANC2sqKvry/q6ursjljqKdTP2CFnbMjFFxUEPOHj4yN0BMlBztjhw1lOTg4MBgMiIiIQFxfX+1A8oVarkZKSAgDYtWsXGhsbeTku9TN2yBkbcvFFBQFPGI1GoSNIDnLGTm+dlZeX4/DhwwCAefPm2R32KyQTJkxA//790draajOaqTdQP2OHnLEhF1/iOhtIGAnciiE6yBk7vXHGcZx1vYIxY8YgOjqar1i80b6wEgDk5+fzss489TN2yBkbcvFFBQFPiOV7WClBztjpjbOCggJcunQJ7u7uNuuRiI2oqCiMGzcOQNs6B7092VI/Y4ecsSEXX1QQ8IQUFmASG+SMnZ46MxqN1qWGp06disDAQB5T8U9qaio8PDxw5coVnDp1qlfHon7GDjljQy6+qCDgiZCQEKEjSA5yxk5PneXm5qK+vh7+/v6YNm0az6n4x9/fH9OnTwcAZGZm9uo7Wupn7JAzNuTiiwoCnrh+fQeie8gZOz1xptVqsWfPHgBtf3mrVCq+YzmFpKQkBAQEQKvVYu/evT0+DvUzdsgZG3LxRQUBT8hhlipXQ87Y6Ymz7OxsGI1GREVFYezYsU5I5Rw8PDwwd+5cAMDevXvR0NDQo+NQP2OHnLEhF19UEPBE+9rUhOOQM3ZYnV29ehXHjx8H0DbMUKFQOCOW0xg9ejSio6NhMpms90CwQv2MHXLGhlx8UUHAE+1rORCOQ87YYXF27TDDuLg4Ua/X3hnXDkM8deoULl26xHwM6mfskDM25OKLCgKeqK6uFjqC5CBn7LA4O378OEpKSqBSqawzAEqRiIgITJw4EUDbMESLxcK0P/UzdsgZG3LxRQUBT4h10SUxQ87YcdSZwWBAVlYWAGDmzJnw9fV1ZiynM2fOHKjVapSXlyM/P59pX+pn7JAzNuTiiwoCnmhpaRE6guQgZ+w46mzPnj1obGxEUFAQEhMTnZzK+fj4+CA5ORkAsH37dqa+Q/2MHXLGhlx8UUHAE2KbE14KkDN2HHFWV1eH3NxcAEBaWhpvywgLzeTJk9GvXz80NTVh165dDu9H/YwdcsaGXHzJ41WIALmcdF0JOWPHEWeZmZkwm82IjY3FiBEjXJDKNSiVSmg0GgDAgQMHUFNT49B+1M/YIWdsyMUXFQQ80dzcLHQEyUHO2OnOWVFREQoKCqBQKKDRaCQ3zLA7hg0bhqFDh8JisSAjI8OhfaifsUPO2JCLLyoIeELsc8OLEXLGTlfOLBaLdZjhpEmTEBYW5qJUrkWj0cDNzQ3nzp3D+fPnu92e+hk75IwNufiigoAnqqqqhI4gOcgZO105O3z4MCorK+Hl5YXZs2e7MJVrCQkJweTJkwEA6enpMJvNXW5P/YwdcsaGXHxRQcATcpm60pWQM3Y6c6bX65GTkwMAmDVrFry8vFwZy+UkJyfD29sb1dXVOHToUJfbUj9jh5yxIRdfVBDwhFymrnQl5Iydzpzt3LkTer0eoaGhmDRpkotTuR5PT0/rVZAdO3Z0+R0u9TN2yBkbcvFFBQFPREZGCh1BcpAzduw5q6qqwsGDBwG0rVcglyFQ3TFx4kSEh4ejpaXFenXEHtTP2CFnbMjFV984c7iA8vJyoSNIDnLGzvXOOI5Deno6OI7DiBEjEBsbK1Ay1+Pm5mZd5+Dw4cOdLkFL/YwdcsaGXHxRQcATQUFBQkeQHOSMneudFRYW4sKFC1AqlUhLSxMolXDExMRg9OjR1oWcOI7rsA31M3bIGRty8UUFAU80NTUJHUFykDN2rnVmNpuRnp4OAEhMTERwcLBQsQRl7ty5UCqVKC4uxpkzZzo8T/2MHXLGhlx8UUHAEyqVSugIkoOcsXOtswMHDqC2thY+Pj6YOXOmgKmEJTAwEFOnTgUAZGRkwGQy2TxP/YwdcsaGXHxRQUAQEqSxsdE6n39KSgrUarXAiYRl+vTp8PPzQ319Pfbv3y90HIKQJFQQ8ITBYBA6guQgZ+y0O9u+fTsMBgMiIyMRFxcnbCgRoFKpkJqaCgDYtWsXdDqd9TnqZ+yQMzbk4osKAp6Qy3rYroScsePv74+ysjIcPXoUAHDjjTfKbr2CnjJu3DgMHDgQRqMR2dnZ1sepn7FDztiQiy8qCHiiurpa6AiSg5yxU11dbV2vYOzYsYiKihI4kXhQKBTWYYjHjh2zThZD/YwdcsaGXHxRQcAT/fv3FzqC5CBn7NTW1uLy5ctwd3e3XiInfmPAgAGYMGECAFiHIVI/Y4ecsSEXX6IuCNavX4/Ro0cjISFB6CjdUlpaKnQEyUHO2DAajdYb5qZPn46AgACBE4mTlJQUeHh44OrVqzhx4gT1sx5AztiQiy8FZ28mD5Gh1WoREBCAhoYG2XxXQxCs7Ny5Ezt27EBAQABWrFgBDw8PoSOJlt27d2P79u3w8/PDY489JpthYQTRExz9DBX1FQIpIZfFLVwJOXOchoYG7NmzB4GBgZg7dy4VA92QlJSEwMBA6HS6Ltc5IOxD70025OKLCgKeCAkJETqC5CBnjpOVlQWTyYSAgACMHj1a6Diix93d3TqV85EjR1BfXy9sIIlB70025OKLCgKe0Gq1QkeQHOTMMS5fvoyTJ08CAKZMmULDDB1k5MiRiImJgUqlQmZmptBxJAW9N9mQiy8qCHjC09NT6AiSg5x1T/uiPQBwww03YMCAAQInkg7twxBNJhNOnz6N4uJioSNJBnpvsiEXX1QQ8ITFYhE6guQgZ92Tn5+PsrIyqNVqzJkzh5wxEh4ejjFjxgBoG4ZI/hyDPLEhF19UEPDE9QuqEN1DzrrGYDBYZ9ybOXMmfH19yVkPuOGGG+Dp6YmKigrrDI9E11A/Y0Muvqgg4Alvb2+hI0gOctY1u3btQlNTE4KDg5GYmAiAnPWE4OBgJCcnA2hbA6KlpUXgROKH+hkbcvFFBQFP1NXVCR1BcpCzzqmtrbVOQqTRaKBUKgGQs55QV1eHhIQEhISEoLm5GTt37hQ6kuihfsaGXHxRQcAT4eHhQkeQHOSsczIyMmCxWDBkyBAMGzbM+jg5Yyc8PBxKpRIajQYAcPDgQdnMPe8sqJ+xIRdfVBDwRHl5udARJAc5s8+FCxdw9uxZKBQKaDQam2GG5IyddmdDhw7F8OHDYbFYkJGRIXAqcUP9jA25+KKCgCdoOBg75KwjFosF6enpAIDJkycjNDTU5nlyxs61ztLS0uDm5obCwkIUFhYKmErcUD9jQy6+qCDgCblMXelKyFlHDh06hKqqKnh5eVlvhLsWcsbOtc769etnvUEzPT0dZrNZqFiihvoZG3LxRQUBT4SFhQkdQXKQM1uam5ut8+7Pnj0bXl5eHbYhZ+xc72zmzJnw9vZGTU0NDh48KFAqcUP9jA25+KKCgCdqa2uFjiA5yJktO3bsQEtLC8LCwhAfH293G3LGzvXOPD09kZKSAqBtBcmmpiYhYoka6mdsyMUXFQQ84evrK3QEyUHOfqOyshKHDh0CAMybNw9ubvbfmuSMHXvO4uLiEBERAYPBQKsh2oH6GRty8UUFAU+0trYKHUFykLM22tcr4DgOo0aNwuDBgzvdlpyxY8+Zm5sb5s2bBwA4fPiwbO4S5wvqZ2zIxRcVBDzBcZzQESQHOWvj7NmzKCoqglKpxNy5c7vclpyx05mz6Ohom3UOyO1vkAs25OKLCgKekMtqV66EnLXNgd4+Jj4pKQlBQUFdbk/O2OnK2dy5c+Hu7o5Lly6hoKDAhanEDfUzNuTiiwoCnpDLetiuhJwBBw4cQF1dHXx9fTF9+vRutydn7HTlLCAgAFOnTgUAZGZmwmg0uiqWqKF+xoZcfFFBwBP9+vUTOoLk6OvOGhsbsWvXLgBAamoq1Gp1t/v0dWc9oTtn06ZNg7+/P+rr65Gbm+uiVOKG+hkbcvFFBQFPVFZWCh1BcvR1Z9nZ2WhtbcWAAQMwfvx4h/bp6856QnfOVCoVUlNTAQB79uyRzV97vYH6GRty8UUFAU/IZepKV9KXnZWUlCA/Px9A2zDDa9cr6Iq+7KynOOJs7NixiIqKgtFoRHZ2tgtSiRvqZ2zIxRcVBDwhl6krXUlfddY+zBAAxo8fj4EDBzq8b1911hsccaZQKKzDEI8fP44rV644O5aooX7Ghlx8UUHAE3JZ/tKV9FVnJ0+exNWrV+Hh4WGdMc9R+qqz3uCos/79+yMuLg4ADUOkfsaGXHxRQcATtL46O33RWWtrK7KysgAA06dPh7+/P9P+fdFZb2FxlpKSApVKhdLSUhw/ftyJqcQN9TM25OKLCgKeCAgIEDqC5OiLzvbu3QutVovAwEAkJSUx798XnfUWFme+vr6YOXMmACArKwsGg8FZsUQN9TM25OKLCgKe0Ov1QkeQHH3NWX19Pfbt2wegbUIcDw8P5mP0NWd8wOosMTERQUFBaGxsxJ49e5yUStxQP2NDLr6oIOCJzhajITqnrznLysqCyWRCdHQ0Ro0a1aNj9DVnfMDqzN3dHWlpaQCA3Nxc1NXVOSOWqKF+xoZcfMnjVYgAd3d3oSNIjr7k7NKlSzh16pT1bnZHhxleT19yxhc9cTZixAjExsbCbDZbp5buS1A/Y0Muvqgg4Inm5mahI0iOvuLMYrFYhxlOnDgRERERPT5WX3HGJz1xplAooNFooFAocObMGRQVFTkhmXihfsaGXHxRQcATgYGBQkeQHH3FWX5+PsrLy6FWqzF79uxeHauvOOOTnjoLCwvDpEmTALQNQ7RYLDymEjfUz9iQiy8qCHiiqqpK6AiSoy84a2lpsc58N2vWLPj4+PTqeH3BGd/0xtns2bPh5eWFyspKHD58mMdU4ob6GRty8UUFAU/IZepKV9IXnO3atQvNzc3o168fEhISen28vuCMb3rjzMvLC7NmzQIA5OTkyOZu8u6gfsaGXHz1qCBYv349YmJi4OnpicTERBw8eLDL7evr67FixQpERkZCrVZj+PDh2Lp1a48CixW5TF3pSuTurKamBgcOHAAAaDQaKJXKXh9T7s6cQW+dTZo0CaGhodDr9dixYwc/oUQO9TM25OKLuSDYvHkzVq1ahbVr1+LIkSOYMGECNBpNp6s9tba2Yu7cuSguLsaWLVtw9uxZbNy4UTYVVTuRkZFCR5AccneWkZEBi8WCYcOGYdiwYbwcU+7OnEFvnbm5uVnXOcjLy5PN5eGuoH7Ghlx8MRcE7733HpYtW4YlS5Zg9OjR+OSTT+Dt7Y3PPvvM7vafffYZamtr8dNPP2HatGmIiYlBcnIyJkyY0OvwYqK8vFzoCJJDzs7Onz+Pc+fOwc3NzTqmnQ/k7MxZ8OEsNjYWI0aMAMdxSE9Pl/06B9TP2JCLL6aCoLW1FYcPH7auHQ60Vc+pqanIzc21u8/PP/+MpKQkrFixAuHh4Rg7dixef/11mM3mTtsxGAzQarU2P2InODhY6AiSQ67OzGYz0tPTAQCTJ09GSEgIb8eWqzNnwpeztLQ0KJVKXLhwAYWFhbwcU6xQP2NDLr6YCoLq6mqYzeYOKzuFh4d3WiFdvHgRW7ZsgdlsxtatW/H888/j3XffxauvvtppO+vWrUNAQID1JyoqCkDbHdulpaWwWCzW72xKSkrQ2tqKyspKNDY2or6+HrW1tdDr9SgvL4fJZLLZ1mg0ory8HM3NzaitrUVdXR2amppQUVEBo9Fos63ZbEZpaSn0ej1qamrQ0NAAnU6HqqoqGAwGm211Oh1KSkpgMBhQVVVlLWSqq6uh1+sdzt3c3Gw3t8lk6pC7sbHRbm6LxdJtbo7jbP7bnlun06GhoQE1NTWd5jYajaioqEBjYyPq6uqYctfX16OxsRGVlZWor6/vNHd1dbXVob3c7ft0ldtsNtvN3dTU1CH39Q7bc+v1+g65W1tb7eZuaWlBdXU19u3bh8bGRvTr1w9TpkxBaWmp3dyVlZUdcpeVlXWZu6ysrNs+W1ZWZpNbp9M5lPvaPtvde02n09m817rLXVdX53Dua/tsZWVlh/cax3EoLS21+16zl7uoqIiXc4TRaMTkyZMRGBiI9PR0XLlyhekccf17TczniOLiYlGcIzrrs2I7R5SWljKdI67Pzec5wt57rbS09PqPWbsoOIZrX6WlpRgwYAD27dtnszDL6tWrsXPnTusNVNcyfPhwtLS0oKioyHpT1XvvvYe3334bZWVldtsxGAw2i4potVpERUWhoaGBeXU4V6HVakWbTazI0VlzczM+/PBDtLS04JZbbkF8fDyvx5ejM2fDpzODwYAPP/wQTU1NmDt3LqZOncrLccUG9TM2xO5Lq9UiICCg289QpisEISEhUCqVqKiosHm8oqKi09nXIiMjMXz4cJs7rEeNGoXy8nK0trba3UetVsPf39/mhyCkQE5ODlpaWhAeHo4bbrhB6DgEz6jVaqSkpABoG1La2NgocCKC4A+mgkClUiE+Pt460QrQNi1rdnZ2p0u5Tps2DefPn7eZ5evcuXOIjIyESqXqYWzx0VeXSe0NcnNWUVFhnbxm3rx5TlnwRG7OXAHfzuLi4hAZGQmDwYDt27fzemyxQP2MDbn4Yj5jrVq1Chs3bsSXX36JgoICPProo2hqasKSJUsAAIsWLcKaNWus2z/66KOora3FypUrce7cOfzyyy94/fXXsWLFCv5ehQigqxjsyMkZx3HYtm0bOI7D6NGjERMT45R25OTMVfDtTKFQ4MYbbwQAHD16tNOvPqUM9TM25OKLuSBYuHAh3nnnHbzwwguIi4tDfn4+tm3bZr3R8PLlyzZvkKioKKSnpyMvLw/jx4/HH//4R6xcuRJPP/00f69CBNTU1AgdQXLIydmZM2dQXFwMpVKJuXPnOq0dOTlzFc5wFhUVhbFjxwKAtRCUE9TP2JCLL6abCoXC0RsihITjuB4vadtXkYszk8mE9evXo76+HjNmzMCcOXOc1pZcnLkSZzlraGjARx99BJPJhDvuuMNaIMgB6mdsiN2XU24qJDrH0WEdxG/IxVlubi7q6+vh5+eH6dOnO7UtuThzJc5yFhAQYP33zsrKgtFodEo7QkD9jA25+KKCgCfkNhWzK5CDM51Oh927dwMAUlNTnX6jrBycuRpnOps6dar1L699+/Y5rR1XQ/2MDbn4ooKAJ+SyuIUrkYOz7OxsGI1GDBw4EOPGjXN6e3Jw5mqc6czDw8N6z8iePXvQ0NDgtLZcCfUzNuTiiwoCnuBzetq+gtSdXb16FceOHQPQNszQFd8hSt2ZEDjb2ejRozFo0CCYTCZkZWU5tS1XQf2MDbn4ooKAJ+Tyl4ErkbKz9mGGADBhwgSXXTKUsjOhcLYzhUJhXQ3x5MmTuHz5slPbcwXUz9iQiy8qCHjCy8tL6AiSQ8rOTpw4gZKSEqhUKuvMda5Ays6EwhXOIiMjrTNTymEYIvUzNuTiiwoCnrh2JkbCMaTqrLW11XppeMaMGfDz83NZ21J1JiSucjZnzhyo1WqUlZUhPz/fJW06C+pnbMjFFxUEPGEymYSOIDmk6mzPnj3Q6XQICgrClClTXNq2VJ0Jiauc+fr6YubMmQDabjaV8nS21M/YkIsvKgh4wtvbW+gIkkOKzurq6qzDy9LS0uDu7u7S9qXoTGhc6SwxMRHBwcFoamrCrl27XNYu31A/Y0Muvqgg4In6+nqhI0gOKTrLzMyE2WzG4MGDMWLECJe3L0VnQuNKZ0qlEhqNBgCwf/9+yU5pS/2MDbn4ooKAJ8LCwoSOIDmk5qy4uBgFBQVQKBTQaDSCTFUqNWdiwNXOhg0bhiFDhsBisSAzM9OlbfMF9TM25OKLCgKeKC8vFzqC5JCSM4vFYh1mGB8fb13My9VIyZlYcLWzawvGs2fP4sKFCy5tnw+on7EhF19UEPCEXKaudCVScnbkyBFUVFTA09MTs2fPFiyHlJyJBSGchYaGYvLkyQCA9PR0yd2FTv2MDbn4ooKAJ+QydaUrkYozvV6P7du3AwBmzZol6A1EUnEmJoRylpycDC8vL1RVVeHQoUOCZOgp1M/YkIsvKgh4Qi7fIbkSqTjbuXMn9Ho9QkJCMGnSJEGzSMWZmBDKmZeXl/VqUk5ODpqbmwXJ0ROon7EhF19UEPBEbW2t0BEkhxScVVdXIy8vDwCg0WigVCoFzSMFZ2JDSGfx8fEICwtDS0sLduzYIVgOVqifsSEXX1QQ8ISvr6/QESSHFJy1f/87fPhwDB06VOg4knAmNoR05ubmZl3n4NChQ6isrBQsCwvUz9iQiy8qCHiitbVV6AiSQ+zOCgsLcf78ebi5uSEtLU3oOADE70yMCO1s8ODBGDVqlHVBLCmscyC0M6khF19UEBCEHcxmM9LT0wEAU6ZMQb9+/QROREiZuXPnQqlUoqioCGfPnhU6DkHYhQoCnlCpVEJHkBxidnbw4EHU1NTAx8fHOj+9GBCzM7EiBmdBQUFISkoCAGRkZIh+7nsxOJMScvFFBQFPNDY2Ch1BcojVWVNTE3bu3AngtxXsxIJYnYkZsTibPn06fH19UVdXh/379wsdp0vE4kwqyMUXFQQ8ERwcLHQEySFWZ9u3b4fBYEBkZCTi4uKEjmODWJ2JGbE4U6vVSE1NBQDs3r1b1B8iYnEmFeTiiwoCnpDK3cNiQozOysvLceTIEQDAvHnz4OYmrreIGJ2JHTE5Gz9+PAYMGIDW1lZkZ2cLHadTxORMCsjFl7jOdhJGLlNXuhKxOWu/CxwAxo4di0GDBgmcqCNicyYFxORMoVBYhyHm5+eLdoY7MTmTAnLxRQUBT4j1jS1mxObs9OnTuHTpEtzd3a2XdsWG2JxJAbE5GzhwIMaPHw8Aoh2GKDZnYkcuvqgg4ImIiAihI0gOMTkzGo3WpWqnTZuGgIAAgRPZR0zOpIIYnaWkpMDDwwNXr17FyZMnhY7TATE6EzNy8UUFAU/I5TskVyImZ7m5uWhoaIC/vz+mTZsmdJxOEZMzqSBGZ/7+/pg+fToAICsrS3QT24jRmZiRiy8qCHgiMDBQ6AiSQyzOtFot9uzZA6BtAhkPDw+BE3WOWJxJCbE6S0pKQmBgILRaLfbu3St0HBvE6kysyMUXFQQ8odfrhY4gOcTiLCsrC0ajEVFRURgzZozQcbpELM6khFideXh4YO7cuQCAffv2ob6+XthA1yBWZ2JFLr6oIOAJsQ1PkwJicHblyhWcOHECQNswQ4VCIXCirhGDM6khZmejRo1CdHQ0TCYTsrKyhI5jRczOxIhcfMnjVYgAoZfFlSJCO7t2mGFcXBz69+8vaB5HENqZFBGzs/ZhiAqFAqdOncKlS5eEjgRA3M7EiFx8ibogWL9+PUaPHo2EhASho3SLXC4ZuRKhnR07dgylpaVQqVRISUkRNIujCO1MiojdWUREBCZOnAigbRiixWIROJH4nYkNufgSdUGwYsUKnD59Gnl5eUJH6Ra53FTiSoR0ZjAYrDPFzZw5UzLrmVM/Y0cKzmbPng21Wo3y8nLk5+cLHUcSzsSEXHyJuiCQElVVVUJHkBxCOmufSz44OBiJiYmC5WCF+hk7UnDm4+ODWbNmAQCys7PR0tIiaB4pOBMTcvFFBQFPyGXqSlcilLPa2lrranNpaWlwd3cXJEdPoH7GjlScJSQkICQkBM3Nzdi1a5egWaTiTCzIxRcVBDwhl6krXYlQzjIzM2E2mxEbG4vhw4cLkqGnUD9jRyrOlEol0tLSAAAHDhxATU2NYFmk4kwsyMUXFQQ8ERkZKXQEySGEs4sXL+LMmTNQKBTQaDSiH2Z4PdTP2JGSs2HDhmHYsGGwWCzIyMgQLIeUnIkBufiigoAnysvLhY4gOVztzGKxID09HUDb5dmwsDCXts8H1M/YkZqztLQ0uLm54dy5czh//rwgGaTmTGjk4osKAp4IDg4WOoLkcLWzw4cPo7KyEl5eXtYbuKQG9TN2pOYsJCQEkydPBgCkp6fDbDa7PIPUnAmNXHxRQcATjY2NQkeQHK50ptfrkZOTA6BtiJeXl5fL2uYT6mfsSNFZcnIyvL29UV1dLciwayk6ExK5+KKCgCdUKpXQESSHK53t2LEDer0eYWFhiI+Pd1m7fEP9jB0pOvP09MScOXMAADt37kRzc7NL25eiMyGRiy8qCAjZU1VVZf0rS6PRyGbecULe3HDDDQgPD0dLS4v16hZBOBM6M/KE2NYzlwKucNa+XgHHcRg5ciRiY2Od3qYzoX7GjlSdubm5Yd68eQDa7n+pqKhwWdtSdSYUcvFFBQFPSGXqWzHhCmfnzp3DxYsXoVQqrUvNShnqZ+xI2VlMTAxGjx5tU9i6Aik7EwK5+KKCgCdqa2uFjiA5nO3MZDJZx3JPmTJFFncCUz9jR+rO5s6dC3d3dxQXF+PMmTMuaVPqzlyNXHxRQcATERERQkeQHM52duDAAdTW1sLX1xczZsxwaluugvoZO1J3FhgYiKSkJABARkYGTCaT09uUujNXIxdfVBDwRFlZmdARJIcznTU2Nlrng09JSYFarXZaW66E+hk7cnA2ffp0+Pn5ob6+Hrm5uU5vTw7OXIlcfFFBwBNyWdzClTjT2fbt29Ha2or+/ftjwoQJTmvH1VA/Y0cOzlQqFVJTUwG0rdSp0+mc2p4cnLkSufiigoAn5LK4hStxlrPS0lIcPXoUADBv3jzJrVfQFdTP2JGLs3HjxmHgwIEwGo3Izs52altyceYq5OKLCgKeCA0NFTqC5HCGs/a7sYG2E2hUVBTvbQgJ9TN25OJMoVBYhyEeO3YMV69edVpbcnHmKuTiiwoCnqivrxc6guRwhrNTp07hypUr8PDwsF5ilRPUz9iRk7MBAwZYvwJz5jBEOTlzBXLxRQUBT0h1bnwh4duZ0WhEZmYmAGDatGnw9/fn9fhigPoZO3JzlpKSApVKhZKSEhw/ftwpbcjNmbORiy8qCHhCiBXJpA7fzvbu3QutVouAgABMnTqV12OLBepn7MjNmZ+fn3UYbXZ2tlNmyZObM2cjF19UEPCExWIROoLk4NNZQ0MD9u7dC6BtIhcPDw/eji0mqJ+xI0dnU6ZMQVBQEHQ6Hfbs2cP78eXozJnIxRcVBDwhl0tGroRPZ1lZWTCZTIiOjsbo0aN5O67YoH7Gjhydubu7Iy0tDQCwb98+1NXV8Xp8OTpzJnLxRQUBT8jlphJXwpezS5cu4eTJkwDaVjOU0zDD66F+xo5cnY0YMQKDBw+G2Wy23jvDF3J15izk4osKAp4ICwsTOoLk4MMZx3FIT08HAEycOBGRkZG9PqaYoX7GjlydKRQKawFcUFCA4uJi3o4tV2fOQi6+qCDgifLycqEjSA4+nOXn56OsrAxqtRpz5szhIZW4oX7GjpydhYeHIz4+HkDbMES+vsuWszNnIBdfVBDwhFymrnQlvXVmMBisM7YlJyfDx8eHj1iihvoZO3J3Nnv2bHh6eqKiogJHjhzh5Zhyd8Y3cvFFBQFPyGXqSlfSW2e7du1CU1MT+vXrh8mTJ/OUStxQP2NH7s68vb0xa9YsAG1reOj1+l4fU+7O+EYuvqgg4Am5fIfkSnrjrKamBvv37wcApKWlQalU8hVL1FA/Y6cvOJs0aRJCQkKg1+uxc+fOXh+vLzjjE7n4ooKAJ2pra4WOIDl64ywjIwMWiwVDhw7FsGHDeEwlbqifsdMXnCmVSmg0GgBAXl4eqqure3W8vuCMT+TiiwoCnvD19RU6guToqbMLFy7g3LlzcHNzQ1pamqyHGV4P9TN2+oqzoUOHYvjw4bBYLNaRNz2lrzjjC7n4ooKAJ5wxfajc6Ykzs9lsPdklJCTIZpUxR6F+xk5fcpaWlgY3NzecP38ehYWFPT5OX3LGB3LxRQUBISkOHTqEqqoqeHt7Izk5Weg4BCEq+vXrhylTpgAA0tPTZTPHPuEaqCDgCZVKJXQEycHqrLm5GTt27ADQNtRKLtOFskD9jJ2+5mzmzJnw8fFBTU0NDh482KNj9DVnvUUuvnpUEKxfvx4xMTHw9PREYmKiw51u06ZNUCgUWLBgQU+aFTWNjY1CR5AcrM5ycnLQ0tKC8PBwTJw40UmpxA31M3b6mrNrJ+nauXMnmpqamI/R15z1Frn4Yi4INm/ejFWrVmHt2rU4cuQIJkyYAI1Gg8rKyi73Ky4uxpNPPmldtlNuBAcHCx1BcrA4q6iowOHDhwG0rVfg5tY3L25RP2OnLzqLi4tDZGQkDAYDtm/fzrx/X3TWG+Tii/ms+t5772HZsmVYsmQJRo8ejU8++QTe3t747LPPOt3HbDbjvvvuw0svvYTY2NheBRYr3RVEREccdda+XgHHcRg1ahQGDx7s5GTihfoZO33RmZubG+bNmwcAOHLkCPPUun3RWW+Qiy+mgqC1tRWHDx9Gamrqbwdwc0Nqaipyc3M73e/ll19GWFgYli5d6lA7BoMBWq3W5kfsyGXqSlfiqLOzZ8+iqKgISqUSc+fOdXIqcUP9jJ2+6mzQoEEYO3YsgLZ1DjiOc3jfvuqsp8jFF1NBUF1dDbPZjPDwcJvHw8PDO61A9+zZg08//RQbN250uJ1169YhICDA+hMVFQUAaGlpQWlpKSwWi3WqyJKSErS2tqKyshKNjY2or69HbW0t9Ho9ysvLYTKZbLY1Go0oLy9Hc3MzamtrUVdXh6amJlRUVMBoNNpsazabUVpaCr1ej5qaGjQ0NECn06GqqgoGg8Fm26tXr6KkpAQGgwFVVVXWQqa6uhp6vd7h3M3NzXZzm0ymDrkbGxvt5rZYLN3m5jjO5r/tuXU6HRoaGlBTU9NpbqPRiIqKCjQ2NqKuro4pd319PRobG1FZWYlLly51mru6uhparRZ1dXXYuXMn3N3dkZCQgMDAQJt9usptNpvt5m5qauqQ+3qH7bn1en2H3K2trXZzt7S0WHNrtVqr79LSUqvna3NXVlZ2yF1WVtZl7nPnznXbZ8vKymxy63Q6ptzV1dXdvtd0Op3Ne6273HV1dQ7nvrbPVlZWdnivcRyH0tJSu+81e7lPnDghinPE9e81V5wjpk6disDAQFy9ehUHDhxw+Bxx4sQJUZwjOuuz154jrn2vXZvXleeIs2fPiuYcYe+9VlpaCkdQcAxlY2lpKQYMGIB9+/YhKSnJ+vjq1auxc+dOa4drR6fTYfz48fjrX/+KG2+8EQCwePFi1NfX46effuq0HYPBAIPBYP1dq9UiKioKDQ0N8Pf3dzSuSzGbzX1m+ly+cMTZnj17kJ2dDV9fXzz++OOyuZu3p1A/Y6evO9uxYwd27tyJgIAArFixAh4eHt3u09edsSJ2X1qtFgEBAd1+hjJdIQgJCYFSqURFRYXN4xUVFYiIiOiw/YULF1BcXIz58+fD3d0d7u7u+Oqrr/Dzzz/D3d0dFy5csNuOWq2Gv7+/zY/Ykct3SK6kO2c6nQ67d+8GAKSmpvb5YgCgftYT+rqzadOmwd/fHw0NDV1+tXstfd0ZK3LxxVQQqFQqxMfHW5ecBQCLxYLs7GybKwbtjBw5EidOnEB+fr7159Zbb8Xs2bORn59v/SpADgQGBgodQXJ052z79u1obW3FgAEDMH78eNeEEjnUz9jp6848PDys997s2bPHoXuy+rozVuTii3mUwapVq7Bx40Z8+eWXKCgowKOPPoqmpiYsWbIEALBo0SKsWbMGAODp6YmxY8fa/AQGBsLPzw9jx46V1V98zc3NQkeQHF05KykpQX5+PgBg3rx5fWq9gq6gfsYOOQPGjBmDqKgoGI1GZGVldbs9OWNDLr6YC4KFCxfinXfewQsvvIC4uDjk5+dj27Zt1hsNL1++jLKyMt6Dih13d3ehI0iOzpxxHIdt27YBACZMmICBAwe6MpaooX7GDjkDFAqFdRjiiRMncOXKlS63J2dsyMUX002FQuHoDRFCotPp4OfnJ3QMSdGZs+PHj+PHH3+Eh4cHHn/8cfJ6DdTP2CFnv/Hvf/8b+fn56N+/Px566KFOr7yRMzbE7sspNxUSnaPX64WOIDnsOWttbbVe0pwxY4ao32RCQP2MHXL2GykpKVCpVCgtLcWxY8c63Y6csSEXX1QQ8ERAQIDQESSHPWd79+6FTqdDYGCg3RtV+zrUz9ghZ7/h6+uLmTNnAgCys7NthndfCzljQy6+qCDgierqaqEjSI7rndXX12Pfvn0A2tZ1l8v3cnxC/YwdcmZLYmIigoOD0djYaB3Wez3kjA25+KKCgCfkMnWlK7neWWZmJkwmE2JiYjBy5EiBUokb6mfskDNb3N3dkZaWBgDYv38/amtrO2xDztiQiy8qCHiifRpJwnGudVZcXIzTp09b74amYYb2oX7GDjnryPDhwxEbGwuz2YzMzMwOz5MzNuTiiwoCnujfv7/QESRHuzOLxWIdZjhx4sQOa2UQv0H9jB1y1hGFQgGNRgOFQoEzZ87g4sWLNs+TMzbk4osKAp7oi3Mv9JZ2Z0ePHkVFRQU8PT0xe/ZsgVOJG+pn7JAz+4SFhSEhIQEAkJ6eDovFYn2OnLEhF19UEPBEv379hI4gOfr164eWlhZs374dAJCcnAwfHx+BU4kb6mfskLPOmTVrFry8vFBZWYnDhw9bHydnbMjFFxUEPOHI/OCELVqtFjt37kRzczNCQkKsf60QnUP9jB1y1jleXl7Wq3I5OTnW8fTkjA25+KKCgCfUarXQESSHXq/HwYMHAQAajUbUy4eKBepn7JCzromPj0dYWBj0ej127NgBgJyxIhdfVBAQgrF3715YLBYMGzYMQ4cOFToOQfRJ3NzcoNFoAAB5eXmyWcqXYIcKAp5obW0VOoKkKCwsRElJic3JiOge6mfskLPuiY2NxciRI8FxHNLT08kZI3LxRQUBT/j6+godQTKYzWakp6fDYDAgMTFRNjfkuALqZ+yQM8eYO3culEolLl68iIqKCqHjSAq59DEqCHjC3mxfhH3y8vJQU1OD4OBg67zqhGNQP2OHnDlGcHAwpkyZAgDIzc2FyWQSOJF0kEsfo4KAJyIiIoSOIAmampqsNy4lJCTA09NT2EASg/oZO+TMcWbMmAFfX1+UlJTgwIEDQseRDHLpY1QQ8IRcJqZwNjk5OTAYDIiIiKAZCXsA9TN2yJnjqNVqpKSkIDAwELt27UJjY6PQkSSBXPoYFQQ8IZfFLZxJeXk5jhw5AgCYN28eoqKiBE4kPaifsUPO2JgwYQK8vb3R2tpqnTSM6Bq59DEqCHhCLotbOIv2u5c5jsOYMWMQHR1NznoAOWOHnLGhUCgwefJkAG3TipeWlgqcSPzIpY9RQcAToaGhQkcQNQUFBSguLoa7uztSU1MBkLOeQM7YIWfsjBo1CuPGjQMAbNu2DRzHCZxI3Milj1FBwBP19fVCRxAtRqPRusTq1KlTERgYCICc9QRyxg45Y6e+vh6pqanw8PDAlStXcOrUKaEjiRq59DEqCHjC29tb6AiiJTc3F/X19fDz88O0adOsj5MzdsgZO+SMHW9vb/j7+1vfr5mZmTAajQKnEi9y6WNUEPAEjdm1j1arxZ49ewC0TXyiUqmsz5EzdsgZO+SMnXZnU6dORUBAALRaLfbu3StwKvEilz5GBQFPXLuWOPEb2dnZMBqNiIqKwtixY22eI2fskDN2yBk77c48PDwwd+5cAG1rjzQ0NAgZS7TIpY9RQcATXl5eQkcQHVevXsXx48cBtA0zVCgUNs+TM3bIGTvkjJ1rnY0ePRrR0dEwmUzIysoSMJV4kUsfo4KAJ6hytoXjOGzbtg0AEBcXh/79+3fYhpyxQ87YIWfsXOtMoVBg3rx5AICTJ0/i0qVLQsUSLXLpY1QQ8ERISIjQEUTF8ePHUVJSApVKhZSUFLvbkDN2yBk75Iyd651FRERg4sSJAGCdT4T4Dbn0MSoIeIJWB/uN1tZW66XF9rnR7UHO2CFn7JAzduw5mzNnDtRqNcrKypCfn+/6UCJGLn2MCgKekMvUlXywe/duNDY2IigoyLp6mj3IGTvkjB1yxo49Zz4+PkhOTgbQdrOwwWBwdSzRIpc+RgUBT8hl6sreUldXh9zcXABAWloa3N3dO92WnLFDztghZ+x05mzy5Mno168fmpqasGvXLhenEi9y6WNUEPBEWFiY0BFEQWZmJsxmM2JjYzFixIgutyVn7JAzdsgZO505UyqV0Gg0AID9+/ejpqbGlbFEi1z6GBUEPEFvDKCoqAgFBQVQKBTQaDQdhhleDzljh5yxQ87Y6crZsGHDMHToUFgsFmRkZLgwlXiRSx8TdUGwfv16jB49GgkJCUJH6RZ/f3+hIwiKxWKxDjOcNGmSQxVzX3fWE8gZO+SMne6cpaWlwc3NDefOncOFCxdclEq8yKWPibogWLFiBU6fPo28vDyho3RLS0uL0BEE5ciRI6isrISnpydmzZrl0D593VlPIGfskDN2unMWGhpq/UMtPT0dZrPZFbFEi1z6mKgLAinR3eVxOaPX67F9+3YAwOzZsx1e6KMvO+sp5IwdcsaOI86Sk5Ph7e2NqqoqHDp0yAWpxItc+hgVBDxx7aI9fY2dO3dCr9cjNDQUkyZNcni/vuysp5AzdsgZO4448/LywuzZswEAO3bsQHNzs7NjiRa59DEqCHiisbFR6AiCUFVVhYMHDwIANBoN3Nwc71J91VlvIGfskDN2HHU2ceJEhIeHo6WlBTk5OU5OJV7k0seoIOCJ4OBgoSO4HI7jrNOYjhgxAkOGDGHavy866y3kjB1yxo6jztzc3KzDEA8fPiybGftYkUsfo4KAJyorK4WO4HIKCwtx4cIFuLm5IS0tjXn/vuist5AzdsgZOyzOBg8ejFGjRtn8gdDXkEsfo4KAJ+QydaWjmM1mpKenAwCmTJnSowq5rznjA3LGDjljh9XZ3LlzoVQqUVRUhLNnzzoplXiRSx+jgoAn5DJ1paMcOHAAtbW18PHxwcyZM3t0jL7mjA/IGTvkjB1WZ0FBQZg6dSoAICMjAyaTyRmxRItc+hgVBDwREREhdASX0djYaJ3HPCUlBWq1ukfH6UvO+IKcsUPO2OmJs+nTp8PX1xd1dXXYv3+/E1KJF7n0MSoIeKIv3Uyzfft2GAwGREZGIi4ursfH6UvO+IKcsUPO2OmJM5VKhdTUVADArl27oNPp+I4lWuTSx6gg4ImgoCChI7iEsrIyHD16FAAwb968Xk3I0Vec8Qk5Y4ecsdNTZ+PHj8eAAQNgNBqtk5X1BeTSx6gg4Im+MCkHx3HW9QrGjh2LQYMG9ep4fcEZ35AzdsgZOz11plAoMG/ePABAfn6+bL5b7w659DEqCHjC3d1d6AhO5/Tp07h8+TLc3d2tlwZ7Q19wxjfkjB1yxk5vnA0cOBATJkwAAGzbtq1PDEOUSx+jgoAnWGbokyJGoxGZmZkAgGnTpiEgIKDXx5S7M2dAztghZ+z01llKSgo8PDxw9epVnDhxgqdU4kUufUwer0IEyGW1q87Yt28fGhoa4O/vj2nTpvFyTLk7cwbkjB1yxk5vnfn5+WHGjBkAgKysLLS2tvIRS7TIpY9RQcATclkP2x4NDQ3Ys2cPgLYJSDw8PHg5rpydOQtyxg45Y4cPZ0lJSQgMDIROp8PevXt5SCVe5NLHqCDgierqaqEjOI3s7GyYTCYMGjQIY8aM4e24cnbmLMgZO+SMHT6cubu7W6c037dvH+rr63t9TLEilz5GBQFPyGXqyuu5fPmy9TvA3g4zvB65OnMm5IwdcsYOX85GjhyJmJgYmEwm6z1IckQufYwKAp6Q4/Caa4cZ3nDDDYiMjOT1+HJ05mzIGTvkjB2+nLUPQ1QoFDh9+jSKi4t5Oa7YkEsfo4KAJ/r37y90BN7Jz89HWVkZVCoV5syZw/vx5ejM2ZAzdsgZO3w6Cw8Px8SJEwG0DUO0WCy8HVssyKWPUUHAE6WlpUJH4BWDwYDs7GwAQHJyMnx9fXlvQ27OXAE5Y4ecscO3s9mzZ8PT0xMVFRXWmU7lhFz6GBUEPBESEiJ0BF7ZvXs3mpqaEBwcjMTERKe0ITdnroCcsUPO2OHbmY+PD5KTkwG0rYUil2F67cilj1FBwBNarVboCLxRW1trXa1Mo9FAqVQ6pR05OXMV5IwdcsaOM5wlJCQgJCQEzc3N2LlzJ+/HFxK59DEqCHiip0sAi5GMjAyYzWYMGTIEw4YNc1o7cnLmKsgZO+SMHWc4UyqV0Gg0AICDBw/KZqgeIJ8+RgUBYcPFixdx9uxZKBQKaDQaXocZEgTRtxk6dCiGDRsGi8WCjIwMoeMQ10EFAU/IYWpOi8ViHWaYkJCA0NBQp7YnB2euhpyxQ87YcaYzjUYDNzc3FBYWorCw0GntuBK59DEqCHjCx8dH6Ai95tChQ6iqqoKXlxdmzZrl9Pbk4MzVkDN2yBk7znTWr18/643K6enpMJvNTmvLVcilj1FBwBN1dXVCR+gVzc3NyMnJAdA2RMjLy8vpbUrdmRCQM3bIGTvOdjZz5kx4e3ujpqYGeXl5Tm3LFcilj1FBwBMRERFCR+gVO3bsQEtLC8LCwhAfH++SNqXuTAjIGTvkjB1nO/P09ERKSgqAtnNPU1OTU9tzNnLpY1QQ8ERZWZnQEXpMZWUlDh06BKBtvQJXre0tZWdCQc7YIWfsuMJZXFwcIiIiYDAYrFcnpYpc+hgVBDwh1cUtOI5Deno6OI7DyJEjMXjwYJe1LVVnQkLO2CFn7LjCmZubG+bNmwcAOHLkCMrLy53eprOQSx+jgoAnpLq4xblz53Dx4kUolUrrUqWuQqrOhIScsUPO2HGVs+joaIwZM8bmDxMpIpc+RgUBTzh7iJ4zMJlMSE9PBwAkJSUhKCjIpe1L0ZnQkDN2yBk7rnSWmpoKd3d3FBcXo6CgwGXt8olc+hgVBDxRX18vdARmDhw4gLq6Ovj6+mL69Okub1+KzoSGnLFDzthxpbPAwEBMnToVAJCZmQmj0eiytvlCLn2sRwXB+vXrERMTA09PTyQmJuLgwYOdbrtx40bMmDEDQUFBCAoKQmpqapfbSxVvb2+hIzDR2NiIXbt2AQBSUlIEmXpTas7EADljh5yx42pn06ZNg5+fH+rr65Gbm+vStvlALn2MuSDYvHkzVq1ahbVr1+LIkSOYMGECNBoNKisr7W6/Y8cO3HPPPcjJyUFubi6ioqKQlpYmm+9c2jGZTEJHYCI7Oxutra3o378/JkyYIEgGqTkTA+SMHXLGjqudqVQqzJ07FwCwZ88eyS0WJJc+xlwQvPfee1i2bBmWLFmC0aNH45NPPoG3tzc+++wzu9t/8803WL58OeLi4jBy5Ej8/e9/h8ViQXZ2dqdtGAwGaLVamx+xY7FYhI7gMKWlpcjPzwfQNsxQqPUKpORMLJAzdsgZO0I4Gzt2LKKiomA0Grv8fBAjculjTAVBa2srDh8+jNTU1N8O4OaG1NRUhy/zNDc3w2g0Ijg4uNNt1q1bh4CAAOtPVFQUAKClpQWlpaWwWCzWKwwlJSVobW1FZWUlGhsbUV9fj9raWuj1epSXl8NkMtlsazQaUV5ejubmZtTW1qKurg5NTU2oqKiA0Wi02dZsNqO0tBR6vR41NTVoaGiATqdDVVUVDAaDzbZqtRolJSUwGAyoqqqyFjLV1dXQ6/UO525ubrab22Qydcjd2NhoN7fFYuk0d0tLC7Zv3w4AGD9+PAYOHGiTW6fToaGhATU1NZ3mNhqNqKioQGNjI+rq6phy19fXo7GxEZWVlVAqlZ3mrq6utjq81jfHcTb7dJXbbDbbzd3U1NQh9/UO23Pr9foOuVtbW+3mbmlpsZu7tLTUbu7KysoOucvKyrrMbTAYuu2zZWVlNrl1Oh1T7urq6m7fazqdzua91l3uuro6h3Nf22crKys7vNc4jkNpaand95q93PX19aI4R7T3AbGfIwwGA+rr6615r8/trHOEXq/H9OnT4eXlhTNnzuDUqVOd9lmxnSNaWlpEc46w914rLS2FIyg4hnEepaWlGDBgAPbt24ekpCTr46tXr8bOnTtx4MCBbo+xfPlypKen49SpU/D09LS7jcFggMFgsP6u1WoRFRWFhoYG+Pv7OxrXpZSXl0titqoTJ07ghx9+gIeHBx577DFBfUrFmZggZ+yQM3aEdPbvf/8b+fn5GDBgAJYuXSqJFVfF3se0Wi0CAgK6/Qx16SiDN954A5s2bcKPP/7YaTEAtK0t7e/vb/MjdkJCQoSO0C2tra3IysoCAEyfPl1wr1JwJjbIGTvkjB0hnaWkpEClUqGkpATHjx8XLAcLculjTAVBSEgIlEolKioqbB6vqKjotjp655138MYbbyAjIwPjx49nTypyrnciRvbu3WutFK+9wiMUUnAmNsgZO+SMHSGd+fr6YsaMGQCArKwsSSwtLJc+xlQQqFQqxMfH29zw0X6DYFcfMG+99RZeeeUVbNu2DZMmTep5WhEj9qkrGxoasG/fPgBAWloaPDw8BE4kfmdihJyxQ87YEdrZlClTEBQUhMbGRuzevVvQLI4gtC++YP7KYNWqVdi4cSO+/PJLFBQU4NFHH0VTUxOWLFkCAFi0aBHWrFlj3f7NN9/E888/j88++wwxMTEoLy9HeXk5Ghsb+XsVIkDswygzMzNhMpkQHR2NUaNGCR0HgPidiRFyxg45Y0doZ+7u7tap1HNzc0W/vLDQvviCuSBYuHAh3nnnHbzwwguIi4tDfn4+tm3bhvDwcADA5cuXbVZ++vjjj9Ha2oo777wTkZGR1p933nmHv1chAtpfvxi5dOkSTp06BYVCIegww+sRszOxQs7YIWfsiMHZiBEjEBsbC7PZjMzMTKHjdIkYfPEB0ygDoXD0DkkhEetdphaLBRs3bkR5eTkmTpyI+fPnCx3JilidiRlyxg45Y0csziorK/HJJ5+A4zgsWrTIpauxsiAWX50hylEGckashUp+fj7Ky8uhVqsxZ84coePYIFZnYoacsUPO2BGLs7CwMOt9Z9u2bRPtBEBi8dVbqCDgiZaWFqEjdODaSYiSk5Ph4+MjcCJbxOhM7JAzdsgZO2JyNmvWLHh6eqKyshJHjhwROo5dxOSrN1BBwBNi+V7+Wnbt2oWmpib069cPkydPFjpOB8ToTOyQM3bIGTticubt7Y3Zs2cDALZv3w69Xi9woo6IyVdvoIKAJ8QwjO9aampqrDNHajQaKJVKgRN1RGzOpAA5Y4ecsSM2Z5MmTUJoaCj0ej127twpdJwOiM1XT6GCgCeampqEjmBDRkYGLBYLhg4dimHDhgkdxy5icyYFyBk75IwdsTlzc3ODRqMBABw8eBBVVVUCJ7JFbL56ChUEPNHVYk2u5vz58zh37pzNm0iMiMmZVCBn7JAzdsTobMiQIRgxYgQ4jkN6ejrENEBOjL56AhUEPFFZWSl0BACA2WxGeno6AGDy5MminmNbLM6kBDljh5yxI1ZnaWlpcHNzw4ULF1BYWCh0HCti9cUKFQQ8IZapKw8dOoTq6mp4e3sjOTlZ6DhdIhZnUoKcsUPO2BGrs+DgYEyZMgUAkJ6eDrPZLHCiNsTqixUqCHhCDFNXNjc3Y8eOHQCAOXPmdLmipBgQgzOpQc7YIWfsiNnZzJkz4ePjg9raWuuN00IjZl8sUEHAE5GRkUJHQE5ODlpaWhAeHo4bbrhB6DjdIgZnUoOcsUPO2BGzM7VajZSUFABtQ6vFsC6OmH2xQAUBT5SXlwvafkVFBQ4fPgwAmDdvHtzcxP9PK7QzKULO2CFn7IjdWVxcHCIjI2EwGKyTrwmJ2H05ivg/NSRCUFCQYG1zHIdt27aB4ziMHj0aMTExgmVhQUhnUoWcsUPO2BG7s/aF2gDg6NGjNgvqCYHYfTkKFQQ80dzcLFjbZ86cQXFxMZRKJebOnStYDlaEdCZVyBk75IwdKTgbNGgQxo4dCwDWP4iEQgq+HIEKAp5wd3cXpF2TyYSMjAwAwNSpUxEYGChIjp4glDMpQ87YIWfsSMVZamoq3N3dcfnyZZw+fVqwHFLx1R1UEPCEUN/Z5+bmor6+Hn5+fpg+fbogGXqKFO5zEBvkjB1yxo5UnAUEBFjPe5mZmTAajYLkkIqv7pDHqxABQqx2pdPpsHv3bgBtlbJKpXJ5ht4glxXCXAk5Y4ecsSMlZ1OnToW/vz8aGhqwb98+QTJIyVdXUEHAE0Ksh52dnQ2j0YiBAwdi3LhxLm+/t8hlDXFXQs7YIWfsSMmZh4eH9d6pPXv2oKGhweUZpOSrK6gg4Inq6mqXtldSUoJjx44BaBtmKMXlN13tTA6QM3bIGTtSczZmzBgMGjQIJpMJ2dnZLm9far46gwoCnujfv7/L2uI4Dr/++isAYMKECZKdNtOVzuQCOWOHnLEjNWfXDkM8ceIELl++7NL2pearM6gg4InS0lKXtXXixAmUlJRApVJZZ+ySIq50JhfIGTvkjB0pOouMjLTO0OrqYYhS9GUPKgh4wlUVYmtrK7KysgAA06dPh5+fn0vadQZyqapdCTljh5yxI1Vnc+bMgUqlQllZGfLz813WrlR9XQ8VBDzhqgpxz5490Ol0CAwMRFJSkkvadBZyqapdCTljh5yxI1Vnvr6+1lVes7OzYTAYXNKuVH1dDxUEPBESEuL0Nurr663DatLS0iQ/GYYrnMkNcsYOOWNHys4SExMRHByMpqYm67BsZyNlX9dCBQFPaLVap7eRmZkJs9mMwYMHY+TIkU5vz9m4wpncIGfskDN2pOxMqVRCo9EAAPbv34/a2lqntyllX9dCBQFPeHp6OvX4xcXFOH36NBQKBTQajSSHGV6Ps53JEXLGDjljR+rOhg0bhiFDhsBsNlundncmUvfVDhUEPGGxWJx67G3btgEA4uPjER4e7rS2XIkznckVcsYOOWNH6s6u/cPp7NmzuHDhglPbk7qvdqgg4AmTyeS0Yx85cgQVFRXw9PTE7NmzndaOq3GmM7lCztghZ+zIwVloaCgSEhIAAOnp6U790JaDL4AKAt7w9vZ2ynFbWlqQk5MDAJg1a5bT2hECOb0WV0HO2CFn7MjF2axZs+Dl5YWqqiocOnTIae3IxRcVBDxRV1fnlOPu3LkTzc3NCAkJwaRJk5zShlA4y5mcIWfskDN25OLMy8vLelU1JycHzc3NTmlHLr6oIOCJiIgI3o9ZXV2NgwcPAgA0Gg2USiXvbQiJM5zJHXLGDjljR07O4uPjERYWhpaWFuzYscMpbcjFFxUEPFFWVsb7Mdu/9xo+fDiGDh3K+/GFxhnO5A45Y4ecsSMnZ25ubtZ1Dg4dOoTKykre25CLL1EXBOvXr8fo0aOtN4aIGb4XGCosLMT58+fh5uaGtLQ0Xo8tFqS6KJOQkDN2yBk7cnPWPncLx3FIT0/nfZ0DufgSdUGwYsUKnD59Gnl5eUJH6ZaSkhLejmU2m5Geng6gbdatfv368XZsMcGns74COWOHnLEjR2dpaWlQKpW4ePEizp07x+ux5eJL1AWBlAgLC+PtWAcPHkRNTQ18fHwwc+ZM3o4rNvh01lcgZ+yQM3bk6CwoKMi6/kt6ejqvQwXl4osKAp7ga3rMpqYm7Ny5E0Dbyl1ymQHLHq6YUlRukDN2yBk7cnU2ffp0+Pr6oq6uDgcOHODtuHLxRQUBT/j4+PBynO3bt8NgMCAiIgJxcXG8HFOs8OWsL0HO2CFn7MjVmVqtRkpKCgBg165daGxs5OW4cvFFBQFPGI3GXh+jvLwcR44cAQDMmzcPbm7y/ufhw1lfg5yxQ87YkbOzCRMmoH///mhtbUV2djYvx5SLL3l/4riQ3t61ynGcdb2CMWPGIDo6mo9YoobvO337AuSMHXLGjpydKRQK6zDE/Px8lJaW9vqYcvFFBQFP9Pa7/oKCAly6dAnu7u6YO3cuT6nEjZzvj3AW5IwdcsaO3J1FRUVh/PjxAIBt27b1+gNdLr6oIOCJ3qyHbTQarUt0Tps2DQEBAXzFEjVyWUPclZAzdsgZO33BWUpKCjw8PHDlyhWcPHmyV8eSiy8qCHgiJCSkx/vm5uaioaEB/v7+mDZtGo+pxE1vnPVVyBk75IydvuDM398f06dPBwBkZWWhtbW1x8eSiy8qCHiioqKiR/tptVrs2bMHAJCamgoPDw8+Y4manjrry5AzdsgZO33FWVJSEgICAqDVarF3794eH0cuvqgg4ImeTl2ZnZ0No9GIqKgojB07ludU4kYu0326EnLGDjljp6848/DwsE4Nv2/fPjQ0NPToOHLxRQUBT/Rk6sorV67g+PHjANqGGSoUCr5jiRq5TPfpSsgZO+SMnb7kbNSoUYiOjobJZEJmZmaPjiEXX1QQ8ER4eDjT9tcOM4yLi0P//v2dEUvUsDojyFlPIGfs9CVn7cMQFQoFTp06hUuXLjEfQy6+qCDgierqaqbtjx07htLSUqhUKuvMWX0NVmcEOesJ5IydvuYsIiICEydOBNA2DNFisTDtLxdfVBDwhL+/v8PbGgwG6wxZM2fOhK+vr7NiiRoWZ0Qb5IwdcsZOX3Q2e/ZsqNVqlJeXIz8/n2lfufiigoAnWlpaHN52z549aGxsRFBQEBITE52YStywOCPaIGfskDN2+qIzHx8fJCcnA2hbU4bFgVx8UUHAE46uO1BXV4fc3FwAgEajgbu7uzNjiRq5r9XgDMgZO+SMnb7qbPLkyejXrx+ampqwa9cuh/eTiy95vAoR4OgHe0ZGBsxmM2JjYzF8+HAnpxI3fbkY6inkjB1yxk5fdaZUKqHRaAAABw4cQE1NjUP7ycUXFQQ80dzc3O02Fy9exJkzZ6BQKKDRaPrcMMPrccQZYQs5Y4ecsdOXnQ0bNgzDhg2DxWKxTinfHXLxRQUBTwQGBnb5vMViQXp6OgBg0qRJCAsLc0EqcdOdM6Ij5IwdcsZOX3eWlpYGNzc3nDt3DufPn+92e7n4ooKAJ6qqqrp8/vDhw6isrISXlxdmz57tolTipjtnREfIGTvkjJ2+7iwkJASTJ08GAKSnp8NsNne5vVx8UUHAE11NXanX65GTkwMAmDVrFry8vFwVS9TIZbpPV0LO2CFn7JAzIDk5Gd7e3qiursahQ4e63FYuvqgg4Imupq7csWMH9Ho9QkNDMWnSJBemEjdyme7TlZAzdsgZO+QM8PT0xJw5cwC0ncO7uk9ALr7kcWukABQUFCA3dz9y8/JQfOkSOA5QKICY6GgkJSQgKWkKRo0ahaqqKuTl5QFoW69ALsNT+CAyMlLoCJKDnLFDztghZ23ccMMNyMvLQ0VFBXJycnDzzTcDcPz8LzUUHMdxQofoDq1Wi4CAADQ0NAg6I5Rer8c3336Lr77dhJBBgxE7IR6xY8YjPCoaCoUCHMeh4solXDx1HBePHUb15SKMGBKL8LBQjB07Fnfffbdg2cVIaWlpn1zDoTeQM3bIGTvk7DeKi4vx5ZdfwmQyIahfP/z0n18cPv8vuvdu3HfvvYJ/TezoZyhdIXCQ3bt346lnnkPizbfj0ff+BrVnx39ghUKBiEExiBgUg6k33gpDix67f/4eW/71DyQlJQmQWtwEBQUJHUFykDN2yBk75Ow3YmJi4Obmhn/9+G/MvWcx0/k/d+vP+FRzI9567RXMmDFDgPRs0BWCbrBYLHjq6TU4e7UMC1c9Cx8/9vabdFpsevdVjIzqj7ffWEdfG/wf1dXVCAkJETqGpCBn7JAzdshZG+3n/4LLJbjnyecle/539DOUPpm6wGKxYMmyh9EaEIoH177Zo84AAD5+/lj64ltoDQjFkmUPM6+kJVdUKpXQESQHOWOHnLFDzmzP/w+99HafOP9TQdAFTz29Bv6xIzH7zvt4Od7sO++Df+xIrF7zDC/HIwiCIJxDXzz/U0HQCbt27cKZK6W8dYZ2Zt95HwouXcXu3bt5Pa4UMRgMQkeQHOSMHXLGTl931lfP/3QPgR30ej1mp83Divc39PgyUVc0aRuwftUjyMnYJvjdp0JiMBigVquFjiEpyBk75IydvuxMjud/uoegF3zz7bdIvPl2p3QGAPDxD8Dkm2/Dt//8p1OOLxWqq6uFjiA5yBk75IydvuysL5//qSCww1ffbsKUG+c7tY2kG2/Fl9+Ir0O4EhrnzA45Y4ecsdOXnfXl83+PCoL169cjJiYGnp6eSExMxMGDB7vc/rvvvsPIkSPh6emJcePGYevWrT0K6woKCgoQMmiw3XGm9tA3NuK+iUOx/tlVTO2oPb0QMigGBQUFPYkpC0pLS4WOIDnIGTvkjJ2+6oz1/P+HOZPx+Lzp+POCVPzxppl4/8/L0eLAUshiPf8zFwSbN2/GqlWrsHbtWhw5cgQTJkyARqNBZWWl3e337duHe+65B0uXLsXRo0exYMECLFiwACdPnux1eGeQm7sfsRPiHd5+76//Ruzo8TiQ+Sv0TU1MbQ0eH4/9+w+wRpQNclkQxJWQM3bIGTt91Rnr+R8AVr3/Cd79KQsf/HcHmht1yPlxs0P7ifH8zzxT4XvvvYdly5ZhyZIlAIBPPvkEv/zyCz777DM8/fTTHbb/y1/+gnnz5uGpp54CALzyyivIzMzERx99hE8++aSX8fknNy8PN9x+v8PbZ2/ZhDuX/wmZm7/G3l//jdQ773V439gx47H3h69x332O7yMnysrKaM50RsgZO+SMnb7qbO+BA4i/84Ee7WsytsKg18PXP8Ch7WPHjEfuT99gyZLFPWrPGTAVBK2trTh8+DDWrFljfczNzQ2pqanIzc21u09ubi5WrbK9nK7RaPDTTz912o7BYLAZ9qLValli9oriS5cwLyraoW2vnD+H6vJSxE2fBYvZhB83fMRUEEQMisH+Awewbt26nsaVNEqlstt1xglbyBk75IydvurswMGDuOmJF5j2ee+JP0Dl6YnKkqsYMmY8pt54q0P7RQyKwU/FxT1I6TyYvjKorq6G2WxGeHi4zePh4eEoLy+3u095eTnT9gCwbt06BAQEWH+ioqIAAC0tLSgtLYXFYrEuN1lSUoLW1lZUVlaisbER9fX1qK2thV6vR3l5OUwmk822RqMR5eXlaG5uRm1tLerq6tDU1ISKigoYjUa0thqhUCgc8pG95Z+Y9bs7oVQqMXFmCipKruDqhUKH9gXa5r5WKpVQqVTw8vKCt7c3PDw84O/vDzc3NwQGBgIAAgMD4ebmBn9/f6hUKnh7e8PLywsqlQp+fn5QKpU22yoUCgQEBMDd3R0+Pj7w9PSEWq2Gr69vh23b/6tUKuHr6wu1Wg1PT0/4+PjA3d0dAQEBUCgUHbb18/Ozya1SqbrM7eHh0SG3j4+Pw7nbsziS28PDw25uNzc3h3MrFAq7uTtzeH1uT09Ph3N7eXlZc/v7+3eZOzAw0Jrbz8/Podxd/du35/b19e1R7mv7bFe5r/+37yq3j49Pj3Jf22ev3TY0NNSa2957zV7uzt5r9nIHBARYc3f3Xrs2d0/fa644R4SGhoriHMGSm49zhELh5vD5v532rwy+yD2J0AED8fU7rzm0n0KhgNFogsFgQGlpKTiOs/msMhgMqKyshE6nQ0NDA2pqaqDX61FWVgaz2dzhc62iogJNTU2oq6vr8Lnm6D0holzcaM2aNTZXFbRaLaKiouDp6WkdQ9n+HVf7f8PCwjocp32M5/XbRkREAAC8vb2t2/r4+AAAVCoPcBzXbacwGY3Y+fMWuLt7YPd/fwQAtOr1yN7yLR74n7UOvU6O4xAaGoo///nPDm0vNxobG+Hr6yt0DElBztghZ+z0VWf/2Zbu0PnfHkp3d0xJuxlfvf0KFqP7zwCO4+Dh4Q61Wm0d1dGbz7X2P7zbP8uu/X9HR40wFQQhISFQKpWoqKiwebyiosL6IXs9ERERTNsDgFqtFmxSjJjoaFRcuYSIQTFdbpe3PQPhUdF4Y/N/rY9dvVCIFxbdgftWPQN3D49u2yq/XIzYwYP77Lzh7VdHCMchZ+yQM3b6qrPBMTEOnf874+T+PRgweIhD25ZfLsbgmJ614yyYvjJQqVSIj49Hdna29TGLxYLs7OxOl/dNSkqy2R4AMjMzRbsccFJCAi6eOt7tdtnf/xMzb7nN5rGBQ4YhODwCh3IyHWrr4qnjSEpI6FFOOWAymYSOIDnIGTvkjJ2+6szR8/+1vPfEH/DnBan40/zZuHrxPB585mWH9hPj+Z/5K4NVq1bhgQcewKRJkzB58mR88MEHaGpqso46WLRoEQYMGGC9UW7lypVITk7Gu+++i5tvvhmbNm3CoUOHsGHDBn5fCU8kJU3Bf996v9sbQ57b8A+7j7/zQ4bDbRUdP4yHVrPNXyAnrv3KhnAMcsYOOWOnrzpz9Pzfzifbu56DpyvEeP5nLggWLlyIqqoqvPDCCygvL0dcXBy2bdtm/f7i8uXLNus9T506Fd9++y2ee+45PPPMMxg2bBh++uknjB07lr9XwSOjRo1C9eUiGFr0Dk9O0RMMLXpUXy7GqFGjnNaG2Kmrq+vTazn0BHLGDjljp6866+vnf1rcyA5///RTnKhqRPJtdzmtjR0/bsaEMH8sffBBp7UhdsxmM5RKpdAxJAU5Y4ecsdOXncnx/E+LG/WC++69Fwd++QFNOufMf9CkbcDBX37Evffc45TjS4Wuhp4S9iFn7JAzdvqys758/qeCwA5eXl54+/VXsendV51y/E3vvop31r3WJy/JXUtfnR61N5AzdsgZO33ZWV8+/1NB0AkzZszAyKj+yNnyDa/HzdnyDUZFD8T06dN5Pa4UaZ9Yg3AccsYOOWOnrzvrq+d/uoegCywWC5Ysexj+sSMx+877en28nC3fQHvxDD7fuMHmxsu+itFohIcD8zUQv0HO2CFn7JAzeZ3/6R4CHnBzc8PnGzdAra3Gpy+u7vF3Sk3aBny69imotdVUDFxDbW2t0BEkBzljh5yxQ8765vmfrhA4yO7du/HUM89h8s23IenGWx0akmJo0SP3159x8Jcf8fbrr2LGjBkuSCodmpqabKbZJLqHnLFDztghZ7ZI/fzv6GcoFQQM6PV6fPvPf+LLb/6JkEExGDw+HrFjxiNiUAwUCgU4jkP55WJcPHUcRccPo+bKJSy6927ce889oryBRGjq6uoQFBQkdAxJQc7YIWfskLOOSPn8TwWBkykoKMD+/QeQm5eHouJimExmuLsrMTgmBkkJCZgyJVF0k06IjdraWgQHBwsdQ1KQM3bIGTvkrGukdv6ngsDFNDc399npPnsKOWOHnLFDztghZ2yI3RfdVOhitFrnTGIhZ8gZO+SMHXLGDjljQy6+qCDgiX79+gkdQXKQM3bIGTvkjB1yxoZcfFFBwBOVlZVCR5Ac5IwdcsYOOWOHnLEhF190DwFBEARByBi6h8DF9PWpPnsCOWOHnLFDztghZ2zIxRcVBDwRHh4udATJQc7YIWfskDN2yBkbcvFFBQFPVFdXCx1BcpAzdsgZO+SMHXLGhlx8UUHAEwEBAUJHkBzkjB1yxg45Y4ecsSEXX1QQ8IRerxc6guQgZ+yQM3bIGTvkjA25+KKCgCfEvIKVWCFn7JAzdsgZO+SMDbn4kserEAHu7u5CR5Ac5IwdcsYOOWOHnLEhF19UEPBEc3Oz0BEkBzljh5yxQ87YIWdsyMUXFQQ8ERgYKHQEyUHO2CFn7JAzdsgZG3LxRQUBT1RVVQkdQXKQM3bIGTvkjB1yxoZcfNHUxQRBEAQhY2jqYhcjl6krXQk5Y4ecsUPO2CFnbMjFF10h4AmLxSKboSeugpyxQ87YIWfskDM2xO6LrhC4mPLycqEjSA5yxg45Y4ecsUPO2JCLL0kMnmy/iKHVagVO0jnu7u6izidGyBk75IwdcsYOOWND7L7as3X3hYAkCgKdTgcAiIqKEjgJQRAEQUgTnU7X5boLkriHwGKxoLS0FH5+fpg8eTLy8vKEjmSDVqtFVFQUrly5Isp7HBISEsgZA2L0BZCznkDO2CFnbIjZF9Dm7ODBg9DpdOjfv3+X9zpI4gqBm5sbBg4cCABQKpWilA4A/v7+osxGztgQsy+AnPUEcsYOOWNDjL6ANmcBAQEOrcgouZsKV6xYIXQEyUHO2CBf7JAzdsgZO+SMHRZnkvjKQOxIYVik2CBn7JAzdsgZO+SMDTn5ktwVAjGiVquxdu1aqNVqoaNIBnLGDjljh5yxQ87YkJMvukJAEARBEARdISAIgiAIggoCgiAIgiBABQFBEARBEKCCgCAIgiAIUEFAEARBEASoIHCY9evXIyYmBp6enkhMTMTBgwe73P67777DyJEj4enpiXHjxmHr1q0uSioeWJxt3LgRM2bMQFBQEIKCgpCamtqtYznC2s/a2bRpExQKBRYsWODcgCKE1Vl9fT1WrFiByMhIqNVqDB8+vE+9P1l9ffDBBxgxYgS8vLwQFRWFJ554Ai0tLS5KKzy7du3C/Pnz0b9/fygUCvz000/d7rNjxw5MnDgRarUaQ4cOxRdffOH0nLzAEd2yadMmTqVScZ999hl36tQpbtmyZVxgYCBXUVFhd/u9e/dySqWSe+utt7jTp09zzz33HOfh4cGdOHHCxcmFg9XZvffey61fv547evQoV1BQwC1evJgLCAjgrl696uLkwsHqrJ2ioiJuwIAB3IwZM7jf/e53rgkrElidGQwGbtKkSdxNN93E7dmzhysqKuJ27NjB5efnuzi5MLD6+uabbzi1Ws198803XFFREZeens5FRkZyTzzxhIuTC8fWrVu5Z599lvvhhx84ANyPP/7Y5fYXL17kvL29uVWrVnGnT5/mPvzwQ06pVHLbtm1zTeBeQAWBA0yePJlbsWKF9Xez2cz179+fW7dund3t77rrLu7mm2+2eSwxMZF75JFHnJpTTLA6ux6TycT5+flxX375pbMiio6eODOZTNzUqVO5v//979wDDzzQ5woCVmcff/wxFxsby7W2troqoqhg9bVixQpuzpw5No+tWrWKmzZtmlNzihVHCoLVq1dzY8aMsXls4cKFnEajcWIyfqCvDLqhtbUVhw8fRmpqqvUxNzc3pKamIjc31+4+ubm5NtsDgEaj6XR7udETZ9fT3NwMo9GI4OBgZ8UUFT119vLLLyMsLAxLly51RUxR0RNnP//8M5KSkrBixQqEh4dj7NixeP3112E2m10VWzB64mvq1Kk4fPiw9WuFixcvYuvWrbjppptcklmKSPn8L4nVDoWkuroaZrMZ4eHhNo+Hh4fjzJkzdvcpLy+3u315ebnTcoqJnji7nv/5n/9B//79O7yx5EpPnO3Zsweffvop8vPzXZBQfPTE2cWLF7F9+3bcd9992Lp1K86fP4/ly5fDaDRi7dq1rogtGD3xde+996K6uhrTp08Hx3EwmUz4wx/+gGeeecYVkSVJZ+d/rVYLvV4PLy8vgZJ1D10hIETHG2+8gU2bNuHHH3+Ep6en0HFEiU6nw/3334+NGzciJCRE6DiSwWKxICwsDBs2bEB8fDwWLlyIZ599Fp988onQ0UTJjh078Prrr+Ovf/0rjhw5gh9++AG//PILXnnlFaGjEU6ArhB0Q0hICJRKJSoqKmwer6ioQEREhN19IiIimLaXGz1x1s4777yDN954A1lZWRg/frwzY4oKVmcXLlxAcXEx5s+fb33MYrEAANzd3XH27FkMGTLEuaEFpif9LDIyEh4eHlAqldbHRo0ahfLycrS2tkKlUjk1s5D0xNfzzz+P+++/Hw899BAAYNy4cWhqasLDDz+MZ599Fm5u9Dfl9XR2/vf39xf11QGArhB0i0qlQnx8PLKzs62PWSwWZGdnIykpye4+SUlJNtsDQGZmZqfby42eOAOAt956C6+88gq2bduGSZMmuSKqaGB1NnLkSJw4cQL5+fnWn1tvvRWzZ89Gfn4+oqKiXBlfEHrSz6ZNm4bz589biycAOHfuHCIjI2VdDAA989Xc3NzhQ7+9mOJoXTy7SPr8L/RdjVJg06ZNnFqt5r744gvu9OnT3MMPP8wFBgZy5eXlHMdx3P333889/fTT1u337t3Lubu7c++88w5XUFDArV27tk8OO2Rx9sYbb3AqlYrbsmULV1ZWZv3R6XRCvQSXw+rsevriKANWZ5cvX+b8/Py4xx57jDt79iz33//+lwsLC+NeffVVoV6CS2H1tXbtWs7Pz4/75z//yV28eJHLyMjghgwZwt11111CvQSXo9PpuKNHj3JHjx7lAHDvvfced/ToUe7SpUscx3Hc008/zd1///3W7duHHT711FNcQUEBt379ehp2KDc+/PBDbtCgQZxKpeImT57M7d+/3/pccnIy98ADD9hs/69//YsbPnw4p1KpuDFjxnC//PKLixMLD4uz6OhoDkCHn7Vr17o+uICw9rNr6YsFAcexO9u3bx+XmJjIqdVqLjY2lnvttdc4k8nk4tTCweLLaDRyL774IjdkyBDO09OTi4qK4pYvX87V1dW5PrhA5OTk2D03tXt64IEHuOTk5A77xMXFcSqViouNjeU+//xzl+fuCQqOo+s+BEEQBNHXoXsICIIgCIKggoAgCIIgCCoICIIgCIIAFQQEQRAEQYAKAoIgCIIgQAUBQRAEQRCggoAgCIIgCFBBQBAEQRAEqCAgCIIgCAJUEBAEQRAEASoICIIgCIIA8P8BQONqZ0Du41wAAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of nodes: 3\n", - "Number of edges: 3\n", - "Embedding dimension: 2\n" - ] - } - ], - "source": [ - "K = EmbeddedComplex()\n", - "\n", - "K.add_node('A', [0, 0])\n", - "K.add_node('B', [1, 0])\n", - "K.add_node('C', [0.5, 0.866])\n", - "\n", - "K.add_edge('A', 'B')\n", - "K.add_edge('B', 'C')\n", - "K.add_edge('C', 'A')\n", - "\n", - "#using built-in plotting function along with matplotlib\n", - "fig, ax = plt.subplots(figsize=(6, 6))\n", - "K.plot(ax=ax, with_labels=True, node_size=400)\n", - "ax.set_title('Simple Triangle Graph\\n(0-cells: vertices, 1-cells: edges)')\n", - "plt.show()\n", - "\n", - "#print some information about the complex\n", - "print(f\"Number of nodes: {len(K.nodes())}\")\n", - "print(f\"Number of edges: {len(K.edges())}\")\n", - "print(f\"Embedding dimension: {K.dim}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now let's add a 2-cell (face) to fill in the triangle:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of 2-cells (faces): 1\n", - "Faces: [('A', 'B', 'C')]\n", - "Internal cells dictionary: {2: [(0, 1, 2)]}\n" - ] - } - ], - "source": [ - "K.add_face(['A', 'B', 'C'])\n", - "\n", - "fig, ax = plt.subplots(figsize=(6, 6))\n", - "K.plot(ax=ax, with_labels=True, node_size=400, face_alpha=0.3, face_color='lightblue')\n", - "ax.set_title('Triangle with Face\\n(0-cells: vertices, 1-cells: edges, 2-cells: faces)')\n", - "plt.show()\n", - "\n", - "print(f\"Number of 2-cells (faces): {len(K.faces)}\")\n", - "print(f\"Faces: {K.faces}\")\n", - "print(f\"Internal cells dictionary: {dict(K.cells)}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Adding Cells of Arbitrary Dimension\n", - "\n", - "The key new feature is the ability to add cells of any dimension:" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Dimension 2: 4 cells\n", - "Dimension 3: 1 cells\n", - "\n", - "Total embedding dimension: 3\n" - ] - } - ], - "source": [ - "# Create a 3D tetrahedron with 0, 1, 2, and 3-cells\n", - "K_tetra = EmbeddedComplex()\n", - "\n", - "# Add vertices (0-cells)\n", - "vertices = {\n", - " 'A': [0, 0, 0],\n", - " 'B': [1, 0, 0],\n", - " 'C': [0.5, 0.866, 0],\n", - " 'D': [0.5, 0.289, 0.816] \n", - "}\n", - "\n", - "for name, coord in vertices.items():\n", - " K_tetra.add_node(name, coord)\n", - "\n", - "# Add edges (1-cells) - all pairs\n", - "edges = [('A', 'B'), ('A', 'C'), ('A', 'D'), ('B', 'C'), ('B', 'D'), ('C', 'D')]\n", - "K_tetra.add_edges_from(edges)\n", - "\n", - "# Add faces (2-cells) - all triangular faces\n", - "faces = [['A', 'B', 'C'], ['A', 'B', 'D'], ['A', 'C', 'D'], ['B', 'C', 'D']]\n", - "for face in faces:\n", - " K_tetra.add_cell(face, dim=2) # Explicitly specify dimension\n", - "\n", - "# Add volume (3-cell) - the entire tetrahedron\n", - "K_tetra.add_cell(['A', 'B', 'C', 'D'], dim=3)\n", - "\n", - "# Plot the tetrahedron\n", - "fig = plt.figure(figsize=(10, 8))\n", - "ax = fig.add_subplot(111, projection='3d')\n", - "K_tetra.plot(ax=ax, face_alpha=0.3, face_color='cyan', node_size=100)\n", - "ax.set_title('Tetrahedron with All Cell Types\\n0-cells: 4, 1-cells: 6, 2-cells: 4, 3-cells: 1')\n", - "plt.show()\n", - "\n", - "# Display cell counts\n", - "for dim in sorted(K_tetra.cells.keys()):\n", - " print(f\"Dimension {dim}: {len(K_tetra.cells[dim])} cells\")\n", - " \n", - "print(f\"\\nTotal embedding dimension: {K_tetra.dim}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## ECT Computation with Higher-Dimensional Cells\n", - "\n", - "The ECT computation now properly includes all cell dimensions in the Euler characteristic calculation:\n", - "\n", - "**χ = Σ(-1)^k × |k-cells below threshold|**\n", - "\n", - "Let's see how this works:" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ECT result shape: (8, 20)\n", - "Directions: 8 directions in 3D\n", - "Thresholds: 20 threshold values\n" - ] - }, - { - "data": { - "image/png": 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Compute ECT for the tetrahedron\n", - "ect = ECT(num_dirs=8, num_thresh=20)\n", - "result = ect.calculate(K_tetra)\n", - "\n", - "print(f\"ECT result shape: {result.shape}\")\n", - "print(f\"Directions: {len(result.directions)} directions in {K_tetra.dim}D\")\n", - "print(f\"Thresholds: {len(result.thresholds)} threshold values\")\n", - "\n", - "# Plot the ECT matrix\n", - "fig, ax = plt.subplots(figsize=(10, 6))\n", - "result.plot()\n", - "plt.title('ECT of Tetrahedron (includes 3-cells in computation)')\n", - "plt.show()\n", - "\n", - "# Show a single direction\n", - "\n", - "single_direction = ECT(num_thresh=20, directions=Directions.from_vectors([[1, 0, 0]])).calculate(K_tetra)\n", - "fig, ax = plt.subplots(figsize=(8, 5))\n", - "ax.plot(single_direction.thresholds, single_direction[0], 'b-', marker='o', linewidth=2)\n", - "ax.set_xlabel('Threshold')\n", - "ax.set_ylabel('Euler Characteristic')\n", - "ax.set_title('ECT Curve for Single Direction (v=[1, 0, 0])')\n", - "ax.grid(True, alpha=0.3)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "You can also restrict self-intersections by using the 'validate_embeddings' argument. Currently without checks we can add a node inside of our tetrahedron." - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Unexpected exception formatting exception. Falling back to standard exception\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Traceback (most recent call last):\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/interactiveshell.py\", line 3548, in run_code\n", - " exec(code_obj, self.user_global_ns, self.user_ns)\n", - " File \"/var/folders/81/3x5xj5kx4ys30p1c2z55bhbw0000gn/T/ipykernel_80902/4266954845.py\", line 1, in \n", - " K_valid = K_tetra.copy()\n", - " ^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/networkx/classes/graph.py\", line 1642, in copy\n", - " G.add_nodes_from((n, d.copy()) for n, d in self._node.items())\n", - " File \"/Users/yayub/Code/ect/src/ect/embed_complex.py\", line 177, in add_nodes_from\n", - " File \"/Users/yayub/Code/ect/src/ect/embed_complex.py\", line 120, in wrapper\n", - " )\n", - " \n", - " File \"/Users/yayub/Code/ect/src/ect/embed_complex.py\", line 142, in wrapper\n", - " def wrapper(self, *args, **kwargs):\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/Code/ect/src/ect/embed_complex.py\", line 157, in add_node\n", - " return wrapper\n", - " ^^^^^^^^^^^\n", - "TypeError: float() argument must be a string or a real number, not 'dict'\n", - "\n", - "During handling of the above exception, another exception occurred:\n", - "\n", - "Traceback (most recent call last):\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/interactiveshell.py\", line 2142, in showtraceback\n", - " stb = self.InteractiveTB.structured_traceback(\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py\", line 1435, in structured_traceback\n", - " return FormattedTB.structured_traceback(\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py\", line 1326, in structured_traceback\n", - " return VerboseTB.structured_traceback(\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py\", line 1173, in structured_traceback\n", - " formatted_exception = self.format_exception_as_a_whole(etype, evalue, etb, number_of_lines_of_context,\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py\", line 1088, in format_exception_as_a_whole\n", - " frames.append(self.format_record(record))\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py\", line 970, in format_record\n", - " frame_info.lines, Colors, self.has_colors, lvals\n", - " ^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py\", line 792, in lines\n", - " return self._sd.lines\n", - " ^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/utils.py\", line 144, in cached_property_wrapper\n", - " value = obj.__dict__[self.func.__name__] = self.func(obj)\n", - " ^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/core.py\", line 734, in lines\n", - " pieces = self.included_pieces\n", - " ^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/utils.py\", line 144, in cached_property_wrapper\n", - " value = obj.__dict__[self.func.__name__] = self.func(obj)\n", - " ^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/core.py\", line 681, in included_pieces\n", - " pos = scope_pieces.index(self.executing_piece)\n", - " ^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/utils.py\", line 144, in cached_property_wrapper\n", - " value = obj.__dict__[self.func.__name__] = self.func(obj)\n", - " ^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/core.py\", line 660, in executing_piece\n", - " return only(\n", - " ^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/executing/executing.py\", line 116, in only\n", - " raise NotOneValueFound('Expected one value, found 0')\n", - "executing.executing.NotOneValueFound: Expected one value, found 0\n" - ] - } - ], - "source": [ - "K_valid = K_tetra.copy()\n", - "\n", - "K_valid.add_node('E', [0.5, 0.289, 0.204])\n", - "K_valid.add_cell(['E', 'B'], dim=1)\n", - "\n", - "\n", - "\n", - "# Display cell counts\n", - "print(\"4D Simplex Cell Counts:\")\n", - "for dim in sorted(K_valid.cells.keys()):\n", - " print(f\" {dim}-cells: {len(K_valid.cells[dim])}\")\n", - "\n", - "# Plot (showing 3D projection)\n", - "fig = plt.figure(figsize=(10, 8))\n", - "ax = fig.add_subplot(111, projection='3d')\n", - "K_valid.plot(ax=ax, face_alpha=0.1, node_size=80)\n", - "ax.set_title('4D Simplex (5 vertices, cells up to dimension 4)')\n", - "plt.show()\n", - "\n", - "# Compute ECT\n", - "ect_4d = ECT(num_dirs=6, num_thresh=15)\n", - "result_4d = ect_4d.calculate(K_valid)\n", - "\n", - "fig, ax = plt.subplots(figsize=(10, 6))\n", - "result_4d.plot()\n", - "plt.title('ECT of 4D Simplex\\n(alternating sum includes all dimensions 0-4)')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Understanding ECT with Projection Visualization\n", - "\n", - "Let's visualize how the ECT computation works by showing projection values:" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Create a simple 2D example for visualization\n", - "K_viz = EmbeddedComplex()\n", - "\n", - "# Square with center point\n", - "K_viz.add_node('A', [-1, -1])\n", - "K_viz.add_node('B', [1, -1])\n", - "K_viz.add_node('C', [1, 1])\n", - "K_viz.add_node('D', [-1, 1])\n", - "K_viz.add_node('E', [0, 0]) # center\n", - "\n", - "# Add edges\n", - "edges = [('A', 'B'), ('B', 'C'), ('C', 'D'), ('D', 'A'), # boundary\n", - " ('A', 'E'), ('B', 'E'), ('C', 'E'), ('D', 'E')] # to center\n", - "K_viz.add_edges_from(edges)\n", - "\n", - "# Add triangular faces\n", - "faces = [['A', 'B', 'E'], ['B', 'C', 'E'], ['C', 'D', 'E'], ['D', 'A', 'E']]\n", - "for face in faces:\n", - " K_viz.add_face(face)\n", - "\n", - "# Visualization function\n", - "def plot_with_projections(K, theta, ax):\n", - " \"\"\"Plot complex with nodes colored by projection values\"\"\"\n", - " direction = np.array([np.sin(theta), -np.cos(theta)])\n", - " node_projections = np.dot(K.coord_matrix, direction)\n", - " \n", - " # Plot edges\n", - " for u, v in K.edges():\n", - " u_idx = K.node_to_index[u]\n", - " v_idx = K.node_to_index[v]\n", - " x = [K.coord_matrix[u_idx, 0], K.coord_matrix[v_idx, 0]]\n", - " y = [K.coord_matrix[u_idx, 1], K.coord_matrix[v_idx, 1]]\n", - " ax.plot(x, y, 'k-', alpha=0.5, linewidth=1)\n", - " \n", - " # Plot faces with transparency\n", - " for face_indices in K.cells.get(2, []):\n", - " face_coords = K.coord_matrix[list(face_indices)]\n", - " face_projection = np.max(node_projections[list(face_indices)])\n", - " ax.fill(face_coords[:, 0], face_coords[:, 1], \n", - " alpha=0.3, color=plt.cm.Blues(0.5))\n", - " \n", - " # Plot nodes colored by projection\n", - " scatter = ax.scatter(K.coord_matrix[:, 0], K.coord_matrix[:, 1], \n", - " c=node_projections, cmap='plasma', s=300, \n", - " edgecolors='black', linewidth=2, zorder=10)\n", - " \n", - " # Add node labels with projection values\n", - " for i, node in enumerate(K.node_list):\n", - " ax.annotate(f'{node}\\n({node_projections[i]:.2f})', \n", - " (K.coord_matrix[i, 0], K.coord_matrix[i, 1]),\n", - " ha='center', va='center', fontsize=9, fontweight='bold',\n", - " bbox=dict(boxstyle='round,pad=0.2', facecolor='white', alpha=0.8))\n", - " \n", - " # Direction arrow\n", - " ax.arrow(0, 0, direction[0]*0.7, direction[1]*0.7,\n", - " head_width=0.1, head_length=0.1, fc='red', ec='red', linewidth=2)\n", - " \n", - " ax.set_xlim(-2, 2)\n", - " ax.set_ylim(-2, 2)\n", - " ax.set_aspect('equal')\n", - " ax.grid(True, alpha=0.3)\n", - " ax.set_title(f'θ = {theta*180/np.pi:.0f}°')\n", - " \n", - " return scatter\n", - "\n", - "# Show projections in multiple directions\n", - "fig, axes = plt.subplots(2, 3, figsize=(15, 10))\n", - "axes = axes.flatten()\n", - "\n", - "thetas = np.linspace(0, 2*np.pi, 6, endpoint=False)\n", - "for ax, theta in zip(axes, thetas):\n", - " scatter = plot_with_projections(K_viz, theta, ax)\n", - "\n", - "# Add shared colorbar\n", - "fig.subplots_adjust(right=0.9)\n", - "cbar_ax = fig.add_axes([0.92, 0.15, 0.02, 0.7])\n", - "fig.colorbar(scatter, cax=cbar_ax, label='Node Projection Values')\n", - "\n", - "plt.suptitle('Complex Colored by Projection Values in Different Directions\\n' + \n", - " 'Red arrows show projection direction, faces use max vertex projection', \n", - " fontsize=14)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Comparing Graph vs. Complex ECT\n", - "\n", - "Let's compare ECT results for the same geometry with and without 2-cells:" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ECT value ranges:\n", - "Graph only: [0, 1]\n", - "With face: [0, 1]\n", - "\n", - "The face contributes +1 to the Euler characteristic when included.\n" - ] - } - ], - "source": [ - "# Create two versions: graph only vs. complex with faces\n", - "K_graph = EmbeddedComplex()\n", - "K_complex = EmbeddedComplex()\n", - "\n", - "# Same vertices and edges for both\n", - "vertices = {'A': [0, 0], 'B': [2, 0], 'C': [1, 1.732]}\n", - "edges = [('A', 'B'), ('B', 'C'), ('C', 'A')]\n", - "\n", - "for K in [K_graph, K_complex]:\n", - " for name, coord in vertices.items():\n", - " K.add_node(name, coord)\n", - " K.add_edges_from(edges)\n", - "\n", - "# Add face only to the complex version\n", - "K_complex.add_face(['A', 'B', 'C'])\n", - "\n", - "# Compute ECT for both\n", - "ect = ECT(num_dirs=20, num_thresh=30)\n", - "result_graph = ect.calculate(K_graph)\n", - "result_complex = ect.calculate(K_complex)\n", - "\n", - "# Plot comparison\n", - "fig, axes = plt.subplots(2, 2, figsize=(15, 10))\n", - "\n", - "# Visualizations\n", - "K_graph.plot(ax=axes[0,0], with_labels=True, node_size=400)\n", - "axes[0,0].set_title('Graph Only (no 2-cells)')\n", - "\n", - "K_complex.plot(ax=axes[0,1], with_labels=True, node_size=400, \n", - " face_alpha=0.3, face_color='lightblue')\n", - "axes[0,1].set_title('Complex with 2-cell (face)')\n", - "\n", - "# ECT comparisons\n", - "result_graph.plot(ax=axes[1,0])\n", - "axes[1,0].set_title('ECT: Graph Only\\n(χ = vertices - edges)')\n", - "\n", - "result_complex.plot(ax=axes[1,1])\n", - "axes[1,1].set_title('ECT: Complex with Face\\n(χ = vertices - edges + faces)')\n", - "\n", - "plt.tight_layout()\n", - "plt.show()\n", - "\n", - "# Show numerical difference\n", - "print(\"ECT value ranges:\")\n", - "print(f\"Graph only: [{result_graph.min()}, {result_graph.max()}]\")\n", - "print(f\"With face: [{result_complex.min()}, {result_complex.max()}]\")\n", - "print(f\"\\nThe face contributes +1 to the Euler characteristic when included.\")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "dataexp", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/docs/_sources/notebooks/Tutorial-ExactECT.ipynb.txt b/docs/_sources/notebooks/Tutorial-ExactECT.ipynb.txt deleted file mode 100644 index 1870585..0000000 --- a/docs/_sources/notebooks/Tutorial-ExactECT.ipynb.txt +++ /dev/null @@ -1,179 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Tutorial for exact ECT computation \n", - "\n", - "*Warning: This is a work in progress. Proceed at your own risk.*\n", - "\n", - "The goal of this section is so show available tools for exact computation of the ECT. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": "from ect import ECT, EmbeddedComplex, create_example_graph\n\nimport matplotlib.pyplot as plt\nfrom matplotlib.patches import Circle\nimport numpy as np\nimport networkx as nx\n\n# Note: EmbeddedGraph and EmbeddedCW are now unified into EmbeddedComplex\n# For backward compatibility, you can still use:\n# from ect import EmbeddedGraph, EmbeddedCW" - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": "We can use the `EmbeddedComplex` class (which unifies the old `EmbeddedGraph` and `EmbeddedCW` classes) to find the angle normal to any pair of vertices in the graph, whether or not there is a connecting edge. Setting `angle_labels_circle=True` in the plotting command will try to draw these on the circle. Note that this doesn't tend to do well for large inputs, but can be helpful for small examples." - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": "# Super simple graph using the unified EmbeddedComplex class\nG = EmbeddedComplex()\nG.add_node('A', 0,0)\nG.add_node('B', 1,0)\nG.add_node('C', 2,1)\nG.add_node('D', 1,2)\nG.add_edge('A', 'B')\nG.add_edge('B', 'D')\nG.add_edge('D', 'C')\n\nfig, ax = plt.subplots()\nG.plot(ax = ax)\nG.plot_angle_circle(ax = ax)" - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "G = create_example_graph(centered=True)\n", - "G.rescale_to_unit_disk()\n", - "\n", - "\n", - "fig, ax = plt.subplots()\n", - "G.plot(ax = ax)\n", - "G.plot_angle_circle(ax = ax)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can extract the information directly for use in computation. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": "# If return type is `matrix`, the function returns the matrix of angles and the labels of the angles in the order of the rows/columns in the matrix \nM,Labels = G.get_normal_angle_matrix() # Updated method name\nprint(M)\n\nplt.matshow(M)\nplt.xticks(range(len(Labels)), Labels)\nplt.yticks(range(len(Labels)), Labels)\nplt.colorbar()" - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This can also be returned as a dictionary, with keys given by angles (note the negative angle is not repeated), and value a list of the pairs of vertices associated. Note that in the case of more than one pair of vertices having the same normal angle, it is given as a list of all pairs. " - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{5.497787143782138: [('A', 'B'), ('A', 'F'), ('B', 'F')],\n", - " 5.608444364956034: [('A', 'C')],\n", - " 5.81953769817878: [('A', 'D'), ('F', 'C')],\n", - " 5.034139534781332: [('A', 'E')],\n", - " 5.695182703632018: [('B', 'C')],\n", - " 0.0: [('B', 'D'), ('E', 'F')],\n", - " 3.9269908169872414: [('B', 'E'), ('D', 'F')],\n", - " 2.0344439357957027: [('C', 'D')],\n", - " 2.896613990462929: [('C', 'E')],\n", - " 3.4633432079864352: [('D', 'E')]}" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "angles_dict = G.get_normals_dict()\n", - "angles_dict" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can also get it to return the dictionary with rounded values, as well as to have it include all the opposite angles. " - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{5.5: [('A', 'B'), ('A', 'F'), ('B', 'F')],\n", - " 5.61: [('A', 'C')],\n", - " 5.82: [('A', 'D'), ('F', 'C')],\n", - " 5.03: [('A', 'E')],\n", - " 5.7: [('B', 'C')],\n", - " 0.0: [('B', 'D'), ('E', 'F')],\n", - " 3.93: [('B', 'E'), ('D', 'F')],\n", - " 2.03: [('C', 'D')],\n", - " 2.9: [('C', 'E')],\n", - " 3.46: [('D', 'E')],\n", - " 2.36: [('A', 'B'), ('A', 'F'), ('B', 'F')],\n", - " 2.47: [('A', 'C')],\n", - " 2.68: [('A', 'D'), ('F', 'C')],\n", - " 1.89: [('A', 'E')],\n", - " 2.56: [('B', 'C')],\n", - " 3.14: [('B', 'D'), ('E', 'F')],\n", - " 0.79: [('B', 'E'), ('D', 'F')],\n", - " 5.17: [('C', 'D')],\n", - " 6.04: [('C', 'E')],\n", - " 0.32: [('D', 'E')]}" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "G.get_normals_dict(opposites = True, \n", - " num_rounding_digits=2)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "base", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.7" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} \ No newline at end of file diff --git a/docs/_sources/tutorials.rst.txt b/docs/_sources/tutorials.rst.txt deleted file mode 100644 index 849d783..0000000 --- a/docs/_sources/tutorials.rst.txt +++ /dev/null @@ -1,11 +0,0 @@ -Tutorials -========= - -.. toctree:: - :maxdepth: 2 - :caption: Contents: - - notebooks/Tutorial-EmbeddedComplex - notebooks/Tutorial-ExactECT - notebooks/Matisse/example_matisse - diff --git a/docs/_sources/validation.md.txt b/docs/_sources/validation.md.txt deleted file mode 100644 index 7d295ce..0000000 --- a/docs/_sources/validation.md.txt +++ /dev/null @@ -1,114 +0,0 @@ -# Validation System - -The validation system provides modular, extensible validation for embedded cell complexes to ensure they represent proper embeddings in Euclidean space. - -## Overview - -The validation system distinguishes between two types of rules: - -- **Structural Rules** (always checked): Basic requirements like vertex counts and dimension validity -- **Geometric Rules** (optional): Embedding properties like non-intersecting edges and faces - -## Architecture - -The validation system consists of several components: - -1. **Base Classes**: Abstract interfaces for validation rules and results -2. **Validation Rules**: Concrete implementations for specific validation checks -3. **Validator**: Main orchestrator that manages and applies rules - -## Validation Rules - -### Structural Rules (Always Enforced) - -- **DimensionValidityRule**: Ensures cell dimensions are non-negative -- **VertexCountRule**: Validates correct vertex counts for cell dimensions - - 0-cells must have exactly 1 vertex - - 1-cells must have exactly 2 vertices - - k-cells (k ≥ 2) must have at least 3 vertices - -### Geometric Rules (Optional) - -- **EdgeInteriorRule**: Ensures no vertices lie on edge interiors -- **FaceInteriorRule**: Ensures no vertices lie inside face interiors -- **SelfIntersectionRule**: Validates that face edges don't self-intersect -- **BoundaryEdgeRule**: Ensures required boundary edges exist for faces - -## Usage - -```python -from ect import EmbeddedComplex - -# Enable validation during construction -K = EmbeddedComplex(validate_embedding=True) - -# Or enable/disable later -K.enable_embedding_validation(tol=1e-10) -K.disable_embedding_validation() - -# Override per operation -K.add_cell(vertices, dim=2, check=True) -``` - -## Custom Validation Rules - -You can create custom validation rules by inheriting from `ValidationRule`: - -```python -from ect.validation import ValidationRule, ValidationResult - -class MyCustomRule(ValidationRule): - @property - def name(self) -> str: - return "My Custom Rule" - - @property - def is_structural(self) -> bool: - return False # Geometric rule - - def applies_to_dimension(self, dim: int) -> bool: - return dim == 2 # Only for 2-cells - - def validate(self, cell_coords, all_coords, cell_indices, all_indices, dim): - # Your validation logic here - if some_condition: - return ValidationResult.valid() - else: - return ValidationResult.invalid("Validation failed") - -# Add to validator -K.get_validator().add_rule(MyCustomRule()) -``` - -## API Reference - -### Main Module - -```{eval-rst} -.. automodule:: ect.validation - :members: -``` - -### Base Classes - -```{eval-rst} -.. automodule:: ect.validation.base - :members: - :show-inheritance: -``` - -### Validation Rules - -```{eval-rst} -.. automodule:: ect.validation.rules - :members: - :show-inheritance: -``` - -### Validator - -```{eval-rst} -.. automodule:: ect.validation.validator - :members: - :show-inheritance: -``` \ No newline at end of file diff --git a/docs/_static/ECT_Logo.png b/docs/_static/ECT_Logo.png deleted file mode 100644 index b3bfe44..0000000 Binary files a/docs/_static/ECT_Logo.png and /dev/null differ diff --git a/docs/_static/ECT_Logo_128x128.png b/docs/_static/ECT_Logo_128x128.png deleted file mode 100644 index 7d5fb2f..0000000 Binary files a/docs/_static/ECT_Logo_128x128.png and /dev/null differ diff --git a/docs/_static/_sphinx_javascript_frameworks_compat.js b/docs/_static/_sphinx_javascript_frameworks_compat.js deleted file mode 100644 index 8141580..0000000 --- a/docs/_static/_sphinx_javascript_frameworks_compat.js +++ /dev/null @@ -1,123 +0,0 @@ -/* Compatability shim for jQuery and underscores.js. - 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font-weight: bold } /* Name.Entity */ -.highlight .ne { color: #CB3F38; font-weight: bold } /* Name.Exception */ -.highlight .nf { color: #0000FF } /* Name.Function */ -.highlight .nl { color: #767600 } /* Name.Label */ -.highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */ -.highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */ -.highlight .nv { color: #19177C } /* Name.Variable */ -.highlight .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */ -.highlight .w { color: #bbbbbb } /* Text.Whitespace */ -.highlight .mb { color: #666666 } /* Literal.Number.Bin */ -.highlight .mf { color: #666666 } /* Literal.Number.Float */ -.highlight .mh { color: #666666 } /* Literal.Number.Hex */ -.highlight .mi { color: #666666 } /* Literal.Number.Integer */ -.highlight .mo { color: #666666 } /* Literal.Number.Oct */ -.highlight .sa { color: #BA2121 } /* Literal.String.Affix */ -.highlight .sb { color: #BA2121 } /* Literal.String.Backtick */ -.highlight .sc { color: #BA2121 } /* Literal.String.Char */ -.highlight .dl { color: #BA2121 } /* Literal.String.Delimiter */ -.highlight .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */ -.highlight .s2 { color: #BA2121 } /* Literal.String.Double */ -.highlight .se { color: #AA5D1F; font-weight: bold } /* Literal.String.Escape */ -.highlight .sh { color: #BA2121 } /* Literal.String.Heredoc */ -.highlight .si { color: #A45A77; font-weight: bold } /* Literal.String.Interpol */ -.highlight .sx { color: #008000 } /* Literal.String.Other */ -.highlight .sr { color: #A45A77 } /* Literal.String.Regex */ -.highlight .s1 { color: #BA2121 } /* Literal.String.Single */ -.highlight .ss { color: #19177C } /* Literal.String.Symbol */ -.highlight .bp { color: #008000 } /* Name.Builtin.Pseudo */ -.highlight .fm { color: #0000FF } /* Name.Function.Magic */ -.highlight .vc { color: #19177C } /* Name.Variable.Class */ -.highlight .vg { color: #19177C } /* Name.Variable.Global */ -.highlight .vi { color: #19177C } /* Name.Variable.Instance */ -.highlight .vm { color: #19177C } /* Name.Variable.Magic */ -.highlight .il { color: #666666 } /* Literal.Number.Integer.Long */ \ No newline at end of file diff --git a/docs/_static/searchtools.js b/docs/_static/searchtools.js deleted file mode 100644 index b08d58c..0000000 --- a/docs/_static/searchtools.js +++ /dev/null @@ -1,620 +0,0 @@ -/* - * searchtools.js - * ~~~~~~~~~~~~~~~~ - * - * Sphinx JavaScript utilities for the full-text search. - * - * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS. - * :license: BSD, see LICENSE for details. - * - */ -"use strict"; - -/** - * Simple result scoring code. - */ -if (typeof Scorer === "undefined") { - var Scorer = { - // Implement the following function to further tweak the score for each result - // The function takes a result array [docname, title, anchor, descr, score, filename] - // and returns the new score. - /* - score: result => { - const [docname, title, anchor, descr, score, filename] = result - return score - }, - */ - - // query matches the full name of an object - objNameMatch: 11, - // or matches in the last dotted part of the object name - objPartialMatch: 6, - // Additive scores depending on the priority of the object - objPrio: { - 0: 15, // used to be importantResults - 1: 5, // used to be objectResults - 2: -5, // used to be unimportantResults - }, - // Used when the priority is not in the mapping. - objPrioDefault: 0, - - // query found in title - title: 15, - partialTitle: 7, - // query found in terms - term: 5, - partialTerm: 2, - }; -} - -const _removeChildren = (element) => { - while (element && element.lastChild) element.removeChild(element.lastChild); -}; - -/** - * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions#escaping - */ -const _escapeRegExp = (string) => - string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string - -const _displayItem = (item, searchTerms, highlightTerms) => { - const docBuilder = DOCUMENTATION_OPTIONS.BUILDER; - const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX; - const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX; - const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY; - const contentRoot = document.documentElement.dataset.content_root; - - const [docName, title, anchor, descr, score, _filename] = item; - - let listItem = document.createElement("li"); - let requestUrl; - let linkUrl; - if (docBuilder === "dirhtml") { - // dirhtml builder - let dirname = docName + "/"; - if (dirname.match(/\/index\/$/)) - dirname = dirname.substring(0, dirname.length - 6); - else if (dirname === "index/") dirname = ""; - requestUrl = contentRoot + dirname; - linkUrl = requestUrl; - } else { - // normal html builders - requestUrl = contentRoot + docName + docFileSuffix; - linkUrl = docName + docLinkSuffix; - } - let linkEl = listItem.appendChild(document.createElement("a")); - linkEl.href = linkUrl + anchor; - linkEl.dataset.score = score; - linkEl.innerHTML = title; - if (descr) { - listItem.appendChild(document.createElement("span")).innerHTML = - " (" + descr + ")"; - // highlight search terms in the description - if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js - highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); - } - else if (showSearchSummary) - fetch(requestUrl) - .then((responseData) => responseData.text()) - .then((data) => { - if (data) - listItem.appendChild( - Search.makeSearchSummary(data, searchTerms, anchor) - ); - // highlight search terms in the summary - if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js - highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); - }); - Search.output.appendChild(listItem); -}; -const _finishSearch = (resultCount) => { - Search.stopPulse(); - Search.title.innerText = _("Search Results"); - if (!resultCount) - Search.status.innerText = Documentation.gettext( - "Your search did not match any documents. Please make sure that all words are spelled correctly and that you've selected enough categories." - ); - else - Search.status.innerText = _( - "Search finished, found ${resultCount} page(s) matching the search query." - ).replace('${resultCount}', resultCount); -}; -const _displayNextItem = ( - results, - resultCount, - searchTerms, - highlightTerms, -) => { - // results left, load the summary and display it - // this is intended to be dynamic (don't sub resultsCount) - if (results.length) { - _displayItem(results.pop(), searchTerms, highlightTerms); - setTimeout( - () => _displayNextItem(results, resultCount, searchTerms, highlightTerms), - 5 - ); - } - // search finished, update title and status message - else _finishSearch(resultCount); -}; -// Helper function used by query() to order search results. -// Each input is an array of [docname, title, anchor, descr, score, filename]. -// Order the results by score (in opposite order of appearance, since the -// `_displayNextItem` function uses pop() to retrieve items) and then alphabetically. -const _orderResultsByScoreThenName = (a, b) => { - const leftScore = a[4]; - const rightScore = b[4]; - if (leftScore === rightScore) { - // same score: sort alphabetically - const leftTitle = a[1].toLowerCase(); - const rightTitle = b[1].toLowerCase(); - if (leftTitle === rightTitle) return 0; - return leftTitle > rightTitle ? -1 : 1; // inverted is intentional - } - return leftScore > rightScore ? 1 : -1; -}; - -/** - * Default splitQuery function. Can be overridden in ``sphinx.search`` with a - * custom function per language. - * - * The regular expression works by splitting the string on consecutive characters - * that are not Unicode letters, numbers, underscores, or emoji characters. - * This is the same as ``\W+`` in Python, preserving the surrogate pair area. - */ -if (typeof splitQuery === "undefined") { - var splitQuery = (query) => query - .split(/[^\p{Letter}\p{Number}_\p{Emoji_Presentation}]+/gu) - .filter(term => term) // remove remaining empty strings -} - -/** - * Search Module - */ -const Search = { - _index: null, - _queued_query: null, - _pulse_status: -1, - - htmlToText: (htmlString, anchor) => { - const htmlElement = new DOMParser().parseFromString(htmlString, 'text/html'); - for (const removalQuery of [".headerlink", "script", "style"]) { - htmlElement.querySelectorAll(removalQuery).forEach((el) => { el.remove() }); - } - if (anchor) { - const anchorContent = htmlElement.querySelector(`[role="main"] ${anchor}`); - if (anchorContent) return anchorContent.textContent; - - console.warn( - `Anchored content block not found. Sphinx search tries to obtain it via DOM query '[role=main] ${anchor}'. Check your theme or template.` - ); - } - - // if anchor not specified or not found, fall back to main content - const docContent = htmlElement.querySelector('[role="main"]'); - if (docContent) return docContent.textContent; - - console.warn( - "Content block not found. Sphinx search tries to obtain it via DOM query '[role=main]'. Check your theme or template." - ); - return ""; - }, - - init: () => { - const query = new URLSearchParams(window.location.search).get("q"); - document - .querySelectorAll('input[name="q"]') - .forEach((el) => (el.value = query)); - if (query) Search.performSearch(query); - }, - - loadIndex: (url) => - (document.body.appendChild(document.createElement("script")).src = url), - - setIndex: (index) => { - Search._index = index; - if (Search._queued_query !== null) { - const query = Search._queued_query; - Search._queued_query = null; - Search.query(query); - } - }, - - hasIndex: () => Search._index !== null, - - deferQuery: (query) => (Search._queued_query = query), - - stopPulse: () => (Search._pulse_status = -1), - - startPulse: () => { - if (Search._pulse_status >= 0) return; - - const pulse = () => { - Search._pulse_status = (Search._pulse_status + 1) % 4; - Search.dots.innerText = ".".repeat(Search._pulse_status); - if (Search._pulse_status >= 0) window.setTimeout(pulse, 500); - }; - pulse(); - }, - - /** - * perform a search for something (or wait until index is loaded) - */ - performSearch: (query) => { - // create the required interface elements - const searchText = document.createElement("h2"); - searchText.textContent = _("Searching"); - const searchSummary = document.createElement("p"); - searchSummary.classList.add("search-summary"); - searchSummary.innerText = ""; - const searchList = document.createElement("ul"); - searchList.classList.add("search"); - - const out = document.getElementById("search-results"); - Search.title = out.appendChild(searchText); - Search.dots = Search.title.appendChild(document.createElement("span")); - Search.status = out.appendChild(searchSummary); - Search.output = out.appendChild(searchList); - - const searchProgress = document.getElementById("search-progress"); - // Some themes don't use the search progress node - if (searchProgress) { - searchProgress.innerText = _("Preparing search..."); - } - Search.startPulse(); - - // index already loaded, the browser was quick! - if (Search.hasIndex()) Search.query(query); - else Search.deferQuery(query); - }, - - _parseQuery: (query) => { - // stem the search terms and add them to the correct list - const stemmer = new Stemmer(); - const searchTerms = new Set(); - const excludedTerms = new Set(); - const highlightTerms = new Set(); - const objectTerms = new Set(splitQuery(query.toLowerCase().trim())); - splitQuery(query.trim()).forEach((queryTerm) => { - const queryTermLower = queryTerm.toLowerCase(); - - // maybe skip this "word" - // stopwords array is from language_data.js - if ( - stopwords.indexOf(queryTermLower) !== -1 || - queryTerm.match(/^\d+$/) - ) - return; - - // stem the word - let word = stemmer.stemWord(queryTermLower); - // select the correct list - if (word[0] === "-") excludedTerms.add(word.substr(1)); - else { - searchTerms.add(word); - highlightTerms.add(queryTermLower); - } - }); - - if (SPHINX_HIGHLIGHT_ENABLED) { // set in sphinx_highlight.js - localStorage.setItem("sphinx_highlight_terms", [...highlightTerms].join(" ")) - } - - // console.debug("SEARCH: searching for:"); - // console.info("required: ", [...searchTerms]); - // console.info("excluded: ", [...excludedTerms]); - - return [query, searchTerms, excludedTerms, highlightTerms, objectTerms]; - }, - - /** - * execute search (requires search index to be loaded) - */ - _performSearch: (query, searchTerms, excludedTerms, highlightTerms, objectTerms) => { - const filenames = Search._index.filenames; - const docNames = Search._index.docnames; - const titles = Search._index.titles; - const allTitles = Search._index.alltitles; - const indexEntries = Search._index.indexentries; - - // Collect multiple result groups to be sorted separately and then ordered. - // Each is an array of [docname, title, anchor, descr, score, filename]. - const normalResults = []; - const nonMainIndexResults = []; - - _removeChildren(document.getElementById("search-progress")); - - const queryLower = query.toLowerCase().trim(); - for (const [title, foundTitles] of Object.entries(allTitles)) { - if (title.toLowerCase().trim().includes(queryLower) && (queryLower.length >= title.length/2)) { - for (const [file, id] of foundTitles) { - const score = Math.round(Scorer.title * queryLower.length / title.length); - const boost = titles[file] === title ? 1 : 0; // add a boost for document titles - normalResults.push([ - docNames[file], - titles[file] !== title ? `${titles[file]} > ${title}` : title, - id !== null ? "#" + id : "", - null, - score + boost, - filenames[file], - ]); - } - } - } - - // search for explicit entries in index directives - for (const [entry, foundEntries] of Object.entries(indexEntries)) { - if (entry.includes(queryLower) && (queryLower.length >= entry.length/2)) { - for (const [file, id, isMain] of foundEntries) { - const score = Math.round(100 * queryLower.length / entry.length); - const result = [ - docNames[file], - titles[file], - id ? "#" + id : "", - null, - score, - filenames[file], - ]; - if (isMain) { - normalResults.push(result); - } else { - nonMainIndexResults.push(result); - } - } - } - } - - // lookup as object - objectTerms.forEach((term) => - normalResults.push(...Search.performObjectSearch(term, objectTerms)) - ); - - // lookup as search terms in fulltext - normalResults.push(...Search.performTermsSearch(searchTerms, excludedTerms)); - - // let the scorer override scores with a custom scoring function - if (Scorer.score) { - normalResults.forEach((item) => (item[4] = Scorer.score(item))); - nonMainIndexResults.forEach((item) => (item[4] = Scorer.score(item))); - } - - // Sort each group of results by score and then alphabetically by name. - normalResults.sort(_orderResultsByScoreThenName); - nonMainIndexResults.sort(_orderResultsByScoreThenName); - - // Combine the result groups in (reverse) order. - // Non-main index entries are typically arbitrary cross-references, - // so display them after other results. - let results = [...nonMainIndexResults, ...normalResults]; - - // remove duplicate search results - // note the reversing of results, so that in the case of duplicates, the highest-scoring entry is kept - let seen = new Set(); - results = results.reverse().reduce((acc, result) => { - let resultStr = result.slice(0, 4).concat([result[5]]).map(v => String(v)).join(','); - if (!seen.has(resultStr)) { - acc.push(result); - seen.add(resultStr); - } - return acc; - }, []); - - return results.reverse(); - }, - - query: (query) => { - const [searchQuery, searchTerms, excludedTerms, highlightTerms, objectTerms] = Search._parseQuery(query); - const results = Search._performSearch(searchQuery, searchTerms, excludedTerms, highlightTerms, objectTerms); - - // for debugging - //Search.lastresults = results.slice(); // a copy - // console.info("search results:", Search.lastresults); - - // print the results - _displayNextItem(results, results.length, searchTerms, highlightTerms); - }, - - /** - * search for object names - */ - performObjectSearch: (object, objectTerms) => { - const filenames = Search._index.filenames; - const docNames = Search._index.docnames; - const objects = Search._index.objects; - const objNames = Search._index.objnames; - const titles = Search._index.titles; - - const results = []; - - const objectSearchCallback = (prefix, match) => { - const name = match[4] - const fullname = (prefix ? prefix + "." : "") + name; - const fullnameLower = fullname.toLowerCase(); - if (fullnameLower.indexOf(object) < 0) return; - - let score = 0; - const parts = fullnameLower.split("."); - - // check for different match types: exact matches of full name or - // "last name" (i.e. last dotted part) - if (fullnameLower === object || parts.slice(-1)[0] === object) - score += Scorer.objNameMatch; - else if (parts.slice(-1)[0].indexOf(object) > -1) - score += Scorer.objPartialMatch; // matches in last name - - const objName = objNames[match[1]][2]; - const title = titles[match[0]]; - - // If more than one term searched for, we require other words to be - // found in the name/title/description - const otherTerms = new Set(objectTerms); - otherTerms.delete(object); - if (otherTerms.size > 0) { - const haystack = `${prefix} ${name} ${objName} ${title}`.toLowerCase(); - if ( - [...otherTerms].some((otherTerm) => haystack.indexOf(otherTerm) < 0) - ) - return; - } - - let anchor = match[3]; - if (anchor === "") anchor = fullname; - else if (anchor === "-") anchor = objNames[match[1]][1] + "-" + fullname; - - const descr = objName + _(", in ") + title; - - // add custom score for some objects according to scorer - if (Scorer.objPrio.hasOwnProperty(match[2])) - score += Scorer.objPrio[match[2]]; - else score += Scorer.objPrioDefault; - - results.push([ - docNames[match[0]], - fullname, - "#" + anchor, - descr, - score, - filenames[match[0]], - ]); - }; - Object.keys(objects).forEach((prefix) => - objects[prefix].forEach((array) => - objectSearchCallback(prefix, array) - ) - ); - return results; - }, - - /** - * search for full-text terms in the index - */ - performTermsSearch: (searchTerms, excludedTerms) => { - // prepare search - const terms = Search._index.terms; - const titleTerms = Search._index.titleterms; - const filenames = Search._index.filenames; - const docNames = Search._index.docnames; - const titles = Search._index.titles; - - const scoreMap = new Map(); - const fileMap = new Map(); - - // perform the search on the required terms - searchTerms.forEach((word) => { - const files = []; - const arr = [ - { files: terms[word], score: Scorer.term }, - { files: titleTerms[word], score: Scorer.title }, - ]; - // add support for partial matches - if (word.length > 2) { - const escapedWord = _escapeRegExp(word); - if (!terms.hasOwnProperty(word)) { - Object.keys(terms).forEach((term) => { - if (term.match(escapedWord)) - arr.push({ files: terms[term], score: Scorer.partialTerm }); - }); - } - if (!titleTerms.hasOwnProperty(word)) { - Object.keys(titleTerms).forEach((term) => { - if (term.match(escapedWord)) - arr.push({ files: titleTerms[term], score: Scorer.partialTitle }); - }); - } - } - - // no match but word was a required one - if (arr.every((record) => record.files === undefined)) return; - - // found search word in contents - arr.forEach((record) => { - if (record.files === undefined) return; - - let recordFiles = record.files; - if (recordFiles.length === undefined) recordFiles = [recordFiles]; - files.push(...recordFiles); - - // set score for the word in each file - recordFiles.forEach((file) => { - if (!scoreMap.has(file)) scoreMap.set(file, {}); - scoreMap.get(file)[word] = record.score; - }); - }); - - // create the mapping - files.forEach((file) => { - if (!fileMap.has(file)) fileMap.set(file, [word]); - else if (fileMap.get(file).indexOf(word) === -1) fileMap.get(file).push(word); - }); - }); - - // now check if the files don't contain excluded terms - const results = []; - for (const [file, wordList] of fileMap) { - // check if all requirements are matched - - // as search terms with length < 3 are discarded - const filteredTermCount = [...searchTerms].filter( - (term) => term.length > 2 - ).length; - if ( - wordList.length !== searchTerms.size && - wordList.length !== filteredTermCount - ) - continue; - - // ensure that none of the excluded terms is in the search result - if ( - [...excludedTerms].some( - (term) => - terms[term] === file || - titleTerms[term] === file || - (terms[term] || []).includes(file) || - (titleTerms[term] || []).includes(file) - ) - ) - break; - - // select one (max) score for the file. - const score = Math.max(...wordList.map((w) => scoreMap.get(file)[w])); - // add result to the result list - results.push([ - docNames[file], - titles[file], - "", - null, - score, - filenames[file], - ]); - } - return results; - }, - - /** - * helper function to return a node containing the - * search summary for a given text. keywords is a list - * of stemmed words. - */ - makeSearchSummary: (htmlText, keywords, anchor) => { - const text = Search.htmlToText(htmlText, anchor); - if (text === "") return null; - - const textLower = text.toLowerCase(); - const actualStartPosition = [...keywords] - .map((k) => textLower.indexOf(k.toLowerCase())) - .filter((i) => i > -1) - .slice(-1)[0]; - const startWithContext = Math.max(actualStartPosition - 120, 0); - - const top = startWithContext === 0 ? "" : "..."; - const tail = startWithContext + 240 < text.length ? "..." : ""; - - let summary = document.createElement("p"); - summary.classList.add("context"); - summary.textContent = top + text.substr(startWithContext, 240).trim() + tail; - - return summary; - }, -}; - -_ready(Search.init); diff --git a/docs/_static/sphinx_highlight.js b/docs/_static/sphinx_highlight.js deleted file mode 100644 index 8a96c69..0000000 --- a/docs/_static/sphinx_highlight.js +++ /dev/null @@ -1,154 +0,0 @@ -/* Highlighting utilities for Sphinx HTML documentation. */ -"use strict"; - -const SPHINX_HIGHLIGHT_ENABLED = true - -/** - * highlight a given string on a node by wrapping it in - * span elements with the given class name. - */ -const _highlight = (node, addItems, text, className) => { - if (node.nodeType === Node.TEXT_NODE) { - const val = node.nodeValue; - const parent = node.parentNode; - const pos = val.toLowerCase().indexOf(text); - if ( - pos >= 0 && - !parent.classList.contains(className) && - !parent.classList.contains("nohighlight") - ) { - let span; - - const closestNode = parent.closest("body, svg, foreignObject"); - const isInSVG = closestNode && closestNode.matches("svg"); - if (isInSVG) { - span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); - } else { - span = document.createElement("span"); - span.classList.add(className); - } - - span.appendChild(document.createTextNode(val.substr(pos, text.length))); - const rest = document.createTextNode(val.substr(pos + text.length)); - parent.insertBefore( - span, - parent.insertBefore( - rest, - node.nextSibling - ) - ); - node.nodeValue = val.substr(0, pos); - /* There may be more occurrences of search term in this node. So call this - * function recursively on the remaining fragment. - */ - _highlight(rest, addItems, text, className); - - if (isInSVG) { - const rect = document.createElementNS( - "http://www.w3.org/2000/svg", - "rect" - ); - const bbox = parent.getBBox(); - rect.x.baseVal.value = bbox.x; - rect.y.baseVal.value = bbox.y; - rect.width.baseVal.value = bbox.width; - rect.height.baseVal.value = bbox.height; - rect.setAttribute("class", className); - addItems.push({ parent: parent, target: rect }); - } - } - } else if (node.matches && !node.matches("button, select, textarea")) { - node.childNodes.forEach((el) => _highlight(el, addItems, text, className)); - } -}; -const _highlightText = (thisNode, text, className) => { - let addItems = []; - _highlight(thisNode, addItems, text, className); - addItems.forEach((obj) => - obj.parent.insertAdjacentElement("beforebegin", obj.target) - ); -}; - -/** - * Small JavaScript module for the documentation. - */ -const SphinxHighlight = { - - /** - * highlight the search words provided in localstorage in the text - */ - highlightSearchWords: () => { - if (!SPHINX_HIGHLIGHT_ENABLED) return; // bail if no highlight - - // get and clear terms from localstorage - const url = new URL(window.location); - const highlight = - localStorage.getItem("sphinx_highlight_terms") - || url.searchParams.get("highlight") - || ""; - localStorage.removeItem("sphinx_highlight_terms") - url.searchParams.delete("highlight"); - window.history.replaceState({}, "", url); - - // get individual terms from highlight string - const terms = highlight.toLowerCase().split(/\s+/).filter(x => x); - if (terms.length === 0) return; // nothing to do - - // There should never be more than one element matching "div.body" - const divBody = document.querySelectorAll("div.body"); - const body = divBody.length ? divBody[0] : document.querySelector("body"); - window.setTimeout(() => { - terms.forEach((term) => _highlightText(body, term, "highlighted")); - }, 10); - - const searchBox = document.getElementById("searchbox"); - if (searchBox === null) return; - searchBox.appendChild( - document - .createRange() - .createContextualFragment( - '

' + - '' + - _("Hide Search Matches") + - "

" - ) - ); - }, - - /** - * helper function to hide the search marks again - */ - hideSearchWords: () => { - document - .querySelectorAll("#searchbox .highlight-link") - .forEach((el) => el.remove()); - document - .querySelectorAll("span.highlighted") - .forEach((el) => el.classList.remove("highlighted")); - localStorage.removeItem("sphinx_highlight_terms") - }, - - initEscapeListener: () => { - // only install a listener if it is really needed - if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) return; - - document.addEventListener("keydown", (event) => { - // bail for input elements - if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return; - // bail with special keys - if (event.shiftKey || event.altKey || event.ctrlKey || event.metaKey) return; - if (DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS && (event.key === "Escape")) { - SphinxHighlight.hideSearchWords(); - event.preventDefault(); - } - }); - }, -}; - -_ready(() => { - /* Do not call highlightSearchWords() when we are on the search page. - * It will highlight words from the *previous* search query. - */ - if (typeof Search === "undefined") SphinxHighlight.highlightSearchWords(); - SphinxHighlight.initEscapeListener(); -}); diff --git a/docs/citing.html b/docs/citing.html deleted file mode 100644 index 019fd5a..0000000 --- a/docs/citing.html +++ /dev/null @@ -1,192 +0,0 @@ - - - - - - - 6. Citing — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - - -
- - -
- -
-
-
- -
-
-
-
- -
-

6. Citing

-

To cite ect please use the following publication:

-
-

Munch, Elizabeth. An Invitation to the Euler Characteristic Transform. The American Mathematical Monthly, 132(1), 15-25. doi:10.1080/00029890.2024.2409616. 2024.

-
-
- - -
-
- -
-
-
-
- - - - - - - \ No newline at end of file diff --git a/docs/contributing.html b/docs/contributing.html deleted file mode 100644 index 1735901..0000000 --- a/docs/contributing.html +++ /dev/null @@ -1,283 +0,0 @@ - - - - - - - 4. Contributing to the ect Package — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - - - -
- - -
- -
-
-
- -
-
-
-
- -
-

4. Contributing to the ect Package

-

Note this is a draft document and is subject to change.

-
-

4.1. Getting Started

-
    -

  • Prerequisites

    • -

  • Setting up the development environment

    • -

  • Forking the ect repository

    • -

  • Cloning the repository

    • -
-
-
-

4.2. Contributing Guidelines

-
-

4.2.1. Code style and formatting

-

It is essential for this project to have well documented, clean, and readable code. The following guidelines should be followed when contributing to the ect package:

-
    -

  • Use the PEP 8 style guide for Python code.

    • -

  • Follow docstring format given below for documenting functions and classes.

    • -

  • Use the Sphinx documentation system for generating documentation.

    • -

  • Always include tests for new features and bug fixes.

    • -
-
-
-

4.2.2. Documentation guidelines

-

The ect package uses the Sphinx documentation system for generating documentation. There are two things to be doing when contributing to the documentation:

-
    -

  • First, include docstrings in the code which will be autogenerated into the documentation. When in doubt, write too much.

    • -

  • Second, write documentation in the doc_source directory using the reStructuredText format. This package also supports writing files in markdown, although there are some issues when dealing with autogenerated content so it’s a bit of a mix at the moment. Note that when the documentation is generated, everything in the docs folder is deleted and overwritten, so do not do your work in there, it will be lost!

    • -
-

Assuming everything (TODO: Add install list) is set up correctly, you can generate the documentation by running the following command from the top level folder:

-
make html
-
-
-

This will generate the documentation in the docs directory. You can view the documentation by opening the docs/index.html file in your browser.

-

An example of a docstring for a function is given below. Note the use of indentation since rst is picky about it:

-
def sort_edges(self, theta, return_g=False):
-    """
-    Function to sort the edges of the graph according to the function
-
-    .. math ::
-
-        g_\omega(e) = \max \{ g_\omega(v) \mid  v \in e \}
-
-    in the direction of :math:`\\theta \in [0,2\pi]` .
-
-    Parameters:
-        theta (float):
-            The angle in :math:`[0,2\pi]` for the direction to sort the edges.
-        return_g (bool):
-            Whether to return the :math:`g(v)` values along with the sorted edges.
-
-    Returns:
-        A list of edges sorted in increasing order of the :math:`g(v)` values.
-        If ``return_g`` is True, also returns the ``g`` dictionary with the function values ``g[vertex_name]=func_value``.
-
-    """
-
-
-
-
-

4.2.3. Testing guidelines

-

You should always include tests for new features and bug fixes. The ect package uses the pytest testing framework. The tests are located in the tests directory. To run the tests, you can use the following command:

-
pytest
-
-
-

or the standard unittest python framework by running:

-
make tests
-
-
-

Get in the habit of writing lots of simple tests. It is better to have too many tests than too few. The tests should be written in a way that they can be run quickly and easily. This will make it easier for you to test your code as you develop it and for others to test your code when they review it. Take a look at the existing tests for examples.

-

Note that in order for a function written in the test folder to be run, the function must be prefixed with test_. For example, a test function for a function called my_function would be called test_my_function.

-
-
-

4.2.4. Issue tracking and pull requests

-

If you find an issue, please post it on the GitHub issue tracker. Provide as much information as possible, including the version of the ect package you are using, the operating system you are using, and any other relevant information.

-

If you would like to fix an issue and you are a contributor to the project, please create a new branch for the fix. Note that the main branch is protected so you will not be able to push directly to that branch. Once you are ready to open discussion, you will create a pull request. The pull request should include a description of the issue and the fix. There is a template for pull requests that you can use to fill out helpful information.

-
    -

  • Note that in order for the pip install command to work, the version number in the pyproject.toml file must be updated.

    • -

  • You should also make sure to update the version number to match in the doc_source/conf.py file. This will ensure that the documentation is updated with the correct version number.

    • -

  • Be sure to run make all before committing to ensure that the code is cleaned, the documentation is up to date, and the tests all pass.

    • -
-

If you are not a contributor, you will need to fork the code and create a pull request from your fork. -Note that all pull requests need to be approved by Liz Munch before they can be merged.

-
-
-
-

4.3. Conclusion

-
    -

  • Acknowledgements

    • -

  • Future development plans

    • -

  • Contact information and support

    • -
-
-
- - -
-
- -
-
-
-
- - - - - - - \ No newline at end of file diff --git a/docs/directions.html b/docs/directions.html deleted file mode 100644 index c6a28da..0000000 --- a/docs/directions.html +++ /dev/null @@ -1,292 +0,0 @@ - - - - - - - 2.4. Directions — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - - - -
- - -
- -
-
-
- -
-
-
-
- -
-

2.4. Directions

-
-
-class ect.directions.Sampling(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]
-
-
-UNIFORM = 'uniform'
-
- -
-
-RANDOM = 'random'
-
- -
-
-CUSTOM = 'custom'
-
- -
- -
-
-class ect.directions.Directions(num_dirs=360, sampling=Sampling.UNIFORM, dim=2, endpoint=False, seed=None)[source]
-

Manages direction vectors for ECT calculations. -Supports uniform, random, or custom sampling of directions.

-

Examples

-

# Uniform sampling in 2D (default) -dirs = Directions.uniform(num_dirs=8)

-

# Uniform sampling in 3D -dirs = Directions.uniform(num_dirs=10, dim=3)

-

# Random sampling in 2D -dirs = Directions.random(num_dirs=10, seed=42)

-

# Custom angles (2D only) -dirs = Directions.from_angles([0, np.pi/4, np.pi/2])

-

# Custom vectors in any dimension -dirs = Directions.from_vectors([(1,0,0), (0,1,0), (0,0,1)])

-
-
-__init__(num_dirs=360, sampling=Sampling.UNIFORM, dim=2, endpoint=False, seed=None)[source]
-
- -
-
-classmethod uniform(num_dirs=360, dim=2, endpoint=False, seed=None)[source]
-

Factory method for uniform sampling.

-
-
Parameters:
-
    -

  • num_dirs – Number of direction vectors.

    • -

  • dim – Dimension of the space (default 2).

    • -

  • endpoint – Whether to include the endpoint (for 2D angles).

    • -

  • seed – Optional random seed.

    • -
-
-
-
- -
-
-classmethod random(num_dirs=360, dim=2, seed=None)[source]
-

Factory method for random sampling.

-
-
Parameters:
-
    -

  • num_dirs – Number of direction vectors.

    • -

  • dim – Dimension of the space.

    • -

  • seed – optional random seed.

    • -
-
-
-
- -
-
-classmethod from_angles(angles)[source]
-

Create an instance for custom angles (2D only).

-
- -
-
-classmethod from_vectors(vectors)[source]
-

Create an instance from custom direction vectors. -Works in any number of dimensions.

-
- -
-
-property thetas
-

Get the angles for 2D directions. Raises an error if dim > 2.

-
- -
-
-property vectors
-

Get unit direction vectors. -For 2D, they are computed from thetas if not already created. -For n-dim (n>2), they should be available.

-
- -
- -
- - -
-
- -
-
-
-
- - - - - - - \ No newline at end of file diff --git a/docs/ect_on_graphs.html b/docs/ect_on_graphs.html deleted file mode 100644 index dac2781..0000000 --- a/docs/ect_on_graphs.html +++ /dev/null @@ -1,302 +0,0 @@ - - - - - - - 2.3. ECT on Graphs — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - - - - - -
- - -
- -
-
-
- -
-
-
-
- -
-

2.3. ECT on Graphs

-
-
-class ect.ect.ECT(directions=None, num_dirs=None, num_thresh=None, bound_radius=None, thresholds=None, dtype=<class 'numpy.int32'>)[source]
-

A class to calculate the Euler Characteristic Transform (ECT) from an input EmbeddedComplex.

-

The result is a matrix where entry M[i,j] is \(\chi(K_{a_i})\) for the direction \(\omega_j\) where \(a_i\) is the ith entry in self.thresholds, and \(\omega_j\) is the ith entry in self.thetas.

-
-
Attributes
-
num_dirs (int):

The number of directions to consider in the matrix.

-
-
num_thresh (int):

The number of thresholds to consider in the matrix.

-
-
directions (Directions):

The directions to consider for projection.

-
-
bound_radius (float):

Either None, or a positive radius of the bounding circle.

-
-
-
-
-
-
-__init__(directions=None, num_dirs=None, num_thresh=None, bound_radius=None, thresholds=None, dtype=<class 'numpy.int32'>)[source]
-

Initialize ECT calculator with either a Directions object or sampling parameters

-
-
Parameters:
-
    -

  • directions – Optional pre-configured Directions object

    • -

  • num_dirs – Number of directions to sample (ignored if directions provided)

    • -

  • num_thresh – Number of threshold values (required if directions not provided)

    • -

  • bound_radius – Optional radius for bounding circle

    • -

  • thresholds – Optional array of thresholds

    • -

  • dtype – Data type for output array

    • -
-
-
-
- -
-
-calculate(graph, theta=None, override_bound_radius=None)[source]
-

Calculate Euler Characteristic Transform (ECT) for a given graph and direction theta

-
-
Parameters:
-
    -

  • graph (EmbeddedComplex) – The input complex to calculate the ECT for.

    • -

  • theta (float) – The angle in \([0,2\pi]\) for the direction to calculate the ECT.

    • -

  • override_bound_radius (float) – If None, uses the following in order: (i) the bounding radius stored in the class; or if not available (ii) the bounding radius of the given graph. Otherwise, should be a positive float \(R\) where the ECC will be computed at thresholds in \([-R,R]\). Default is None.

    • -
-
-
-
- -
-
-static shape_descriptor(simplex_counts_list)[source]
-

Calculate shape descriptor from simplex counts (Euler characteristic)

-
- -
- -
-
-class ect.sect.SECT(directions=None, num_dirs=None, num_thresh=None, bound_radius=None, thresholds=None, dtype=<class 'numpy.float32'>)[source]
-

A class to calculate the Smooth Euler Characteristic Transform (SECT). -Inherits from ECT and applies smoothing to the final result.

-
-
-__init__(directions=None, num_dirs=None, num_thresh=None, bound_radius=None, thresholds=None, dtype=<class 'numpy.float32'>)[source]
-

Initialize SECT calculator with smoothing parameter

-
-
Parameters:
-
    -

  • directions – Optional pre-configured Directions object

    • -

  • num_dirs – Number of directions to sample (ignored if directions provided)

    • -

  • num_thresh – Number of threshold values (required if directions not provided)

    • -

  • bound_radius – Optional radius for bounding circle

    • -

  • thresholds – Optional array of thresholds

    • -

  • dtype – Data type for output array

    • -
-
-
-
- -
-
-calculate(graph, theta=None, override_bound_radius=None)[source]
-

Calculate Smooth Euler Characteristic Transform (SECT)

-
-
Parameters:
-
    -

  • graph – The input graph to calculate the SECT for

    • -

  • theta – The angle in [0,2π] for the direction to calculate the SECT

    • -

  • override_bound_radius – Optional override for bounding radius

    • -
-
-
Returns:
-

-
The smoothed transform result containing the matrix,

directions, and thresholds

-
-
-

-
-
Return type:
-

ECTResult

-
-
-
- -
- -
- - -
-
- -
-
-
-
- - - - - - - \ No newline at end of file diff --git a/docs/embed_complex.html b/docs/embed_complex.html deleted file mode 100644 index 5b7da88..0000000 --- a/docs/embed_complex.html +++ /dev/null @@ -1,689 +0,0 @@ - - - - - - - 2.1. Embedded Complex — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - - - -
- - -
- -
-
-
- -
-
-
-
- -
-

2.1. Embedded Complex

-

The EmbeddedComplex class is a unified representation for embedded cell complexes supporting arbitrary dimensional cells.

-
-

2.1.1. Overview

-

EmbeddedComplex combines and extends the functionality of the previous EmbeddedGraph and EmbeddedCW classes into a single, more powerful interface. It supports:

-
    -

  • 0-cells (vertices): Points embedded in Euclidean space

    • -

  • 1-cells (edges): Line segments between vertices

    • -

  • k-cells for k ≥ 2: Higher dimensional cells (faces, volumes, etc.)

    • -
-
-
-

2.1.2. Key Features

-
    -

  • Unified Interface: Single class for all cell complex operations

    • -

  • Arbitrary Dimensions: Support for k-cells of any dimension k ≥ 0

    • -

  • Modular Validation: Pluggable validation system for embedding properties

    • -

  • Backward Compatible: EmbeddedGraph and EmbeddedCW remain as aliases

    • -
-
-
-

2.1.3. Basic Usage

-
from ect import EmbeddedComplex
-
-# Create a complex
-K = EmbeddedComplex()
-
-# Add vertices
-K.add_node("A", [0, 0])
-K.add_node("B", [1, 0])
-K.add_node("C", [0.5, 1])
-
-# Add edges
-K.add_edge("A", "B")
-K.add_edge("B", "C")
-K.add_edge("C", "A")
-
-# Add a 2-cell (face)
-K.add_face(["A", "B", "C"])
-
-# Or use the general method for any dimension
-K.add_cell(["A", "B", "C"], dim=2)
-
-
-
-
-

2.1.4. API Reference

-
-
-class ect.embed_complex.EmbeddedComplex(validate_embedding=False, embedding_tol=1e-10)[source]
-

Bases: Graph

-

A unified class to represent an embedded cell complex with cells of arbitrary dimension.

-

This combines the functionality of EmbeddedGraph and EmbeddedCW, supporting: -- 0-cells (vertices) with embedded coordinates -- 1-cells (edges) -- k-cells for k >= 2 (faces, volumes, etc.)

-
-
Parameters:
-
    -

  • validate_embedding (bool) – If True, automatically validate embedding properties -when adding cells. Default: False

    • -

  • embedding_tol (float) – Tolerance for geometric validation. Default: 1e-10

    • -
-
-
-
-
-coord_matrix
-

np.ndarray -A matrix of embedded coordinates for each vertex

-
- -
-
-node_list
-

list -A list of node names

-
- -
-
-node_to_index
-

dict -A dictionary mapping node ids to their index in the coord_matrix

-
- -
-
-dim
-

int -The dimension of the embedded coordinates

-
- -
-
-cells
-

dict -Dictionary mapping dimension k to list of k-cells, where each k-cell -is represented as a tuple of vertex indices

-
- -
-
-validate_embedding
-

bool -Whether to automatically validate embedding properties

-
- -
-
-embedding_tol
-

float -Tolerance for geometric validation

-
- -
-
-__init__(validate_embedding=False, embedding_tol=1e-10)[source]
-

Initialize a graph with edges, name, or graph attributes.

-
-
Parameters:
-
    -

  • incoming_graph_data (input graph (optional, default: None)) – Data to initialize graph. If None (default) an empty -graph is created. The data can be an edge list, or any -NetworkX graph object. If the corresponding optional Python -packages are installed the data can also be a 2D NumPy array, a -SciPy sparse array, or a PyGraphviz graph.

    • -

  • attr (keyword arguments, optional (default= no attributes)) – Attributes to add to graph as key=value pairs.

    • -
-
-
-
-

See also

-

convert

-
-

Examples

-
>>> G = nx.Graph()  # or DiGraph, MultiGraph, MultiDiGraph, etc
->>> G = nx.Graph(name="my graph")
->>> e = [(1, 2), (2, 3), (3, 4)]  # list of edges
->>> G = nx.Graph(e)
-
-
-

Arbitrary graph attribute pairs (key=value) may be assigned

-
>>> G = nx.Graph(e, day="Friday")
->>> G.graph
-{'day': 'Friday'}
-
-
-
- -
-
-property coord_matrix
-

Return the N x D coordinate matrix

-
- -
-
-property dim
-

Return the dimension of the embedded coordinates

-
- -
-
-property node_list
-

Return ordered list of node names.

-
- -
-
-property node_to_index
-

Return a dictionary mapping node ids to their index in the coord_matrix

-
- -
-
-property position_dict
-

Return a dictionary mapping node ids to their coordinates

-
- -
-
-property edge_indices
-

Return edges as array of index pairs

-
- -
-
-property faces
-

Return list of 2-cells (faces) for backward compatibility

-
- -
-
-add_node(node_id, coord)[source]
-

Add a vertex to the complex.

-
-
Parameters:
-
    -

  • node_id – Identifier for the node

    • -

  • coord – Array-like coordinates for the node

    • -
-
-
-
- -
-
-add_nodes_from_dict(nodes_with_coords)[source]
-
- -
-
-add_nodes_from(nodes_with_coords)[source]
-

Add multiple nodes.

-
-
Parameters:
-
    -

  • nodes_for_adding (iterable container) – A container of nodes (list, dict, set, etc.). -OR -A container of (node, attribute dict) tuples. -Node attributes are updated using the attribute dict.

    • -

  • attr (keyword arguments, optional (default= no attributes)) – Update attributes for all nodes in nodes. -Node attributes specified in nodes as a tuple take -precedence over attributes specified via keyword arguments.

    • -
-
-
-
-

See also

-

add_node

-
-

Notes

-

When adding nodes from an iterator over the graph you are changing, -a RuntimeError can be raised with message: -RuntimeError: dictionary changed size during iteration. This -happens when the graph’s underlying dictionary is modified during -iteration. To avoid this error, evaluate the iterator into a separate -object, e.g. by using list(iterator_of_nodes), and pass this -object to G.add_nodes_from.

-

Examples

-
>>> G = nx.Graph()  # or DiGraph, MultiGraph, MultiDiGraph, etc
->>> G.add_nodes_from("Hello")
->>> K3 = nx.Graph([(0, 1), (1, 2), (2, 0)])
->>> G.add_nodes_from(K3)
->>> sorted(G.nodes(), key=str)
-[0, 1, 2, 'H', 'e', 'l', 'o']
-
-
-

Use keywords to update specific node attributes for every node.

-
>>> G.add_nodes_from([1, 2], size=10)
->>> G.add_nodes_from([3, 4], weight=0.4)
-
-
-

Use (node, attrdict) tuples to update attributes for specific nodes.

-
>>> G.add_nodes_from([(1, dict(size=11)), (2, {"color": "blue"})])
->>> G.nodes[1]["size"]
-11
->>> H = nx.Graph()
->>> H.add_nodes_from(G.nodes(data=True))
->>> H.nodes[1]["size"]
-11
-
-
-

Evaluate an iterator over a graph if using it to modify the same graph

-
>>> G = nx.Graph([(0, 1), (1, 2), (3, 4)])
->>> # wrong way - will raise RuntimeError
->>> # G.add_nodes_from(n + 1 for n in G.nodes)
->>> # correct way
->>> G.add_nodes_from(list(n + 1 for n in G.nodes))
-
-
-
- -
-
-add_edge(node_id1, node_id2)[source]
-

Add an edge (1-cell) between two nodes

-
- -
-
-add_cell(cell_vertices, dim=None, check=None, embedding_tol=None)[source]
-

Add a k-cell to the complex.

-
-
Parameters:
-
    -

  • cell_vertices – List of vertex identifiers that form the cell

    • -

  • dim – Dimension of the cell. If None, inferred as len(cell_vertices) - 1

    • -

  • check – Whether to validate the cell embedding. If None, uses self.validate_embedding

    • -

  • embedding_tol – Tolerance for geometric validation. If None, uses self.embedding_tol

    • -
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-enable_embedding_validation(tol=1e-10)[source]
-

Enable automatic embedding validation for all subsequent cell additions.

-
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-

tol – Tolerance for geometric validation

-
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- -
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-disable_embedding_validation()[source]
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Disable automatic embedding validation for all subsequent cell additions.

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-get_validator()[source]
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Get the embedding validator instance for advanced configuration.

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The EmbeddingValidator instance used by this complex

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-set_validation_rules(rules)[source]
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Set custom validation rules.

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Self for method chaining

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-add_face(face, check=None)[source]
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Add a 2-cell (face) to the complex. Provided for backward compatibility.

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-add_faces_from(faces)[source]
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Add multiple 2-cells (faces) to the complex.

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-get_coord(node_id)[source]
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Return the coordinates of a node

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-set_coord(node_id, new_coords)[source]
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Set the coordinates of a node

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-add_cycle(coord_matrix)[source]
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Add nodes in a cyclic pattern from coordinate matrix

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-get_center(method='bounding_box')[source]
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Calculate center of coordinates

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-get_bounding_box()[source]
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Get (min, max) for each dimension

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-get_bounding_radius(center_type='bounding_box')[source]
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Get radius of minimal bounding sphere

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-get_normal_angle_matrix(edges_only=False, decimals=None)[source]
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Optimized angle matrix computation using vectorized operations.

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    -

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    • -

  • decimals – Round angles to specified decimal places

    • -
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NaN-filled matrix with pair angles -vertex_labels: Ordered node identifiers

-
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Return type:
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angle_matrix

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-get_normal_angles(edges_only=False, decimals=6)[source]
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Optimized angle dictionary construction using NumPy grouping.

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    -

  • edges_only – Only include edge-connected pairs

    • -

  • decimals – Round angles to specified decimal places

    • -
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Dictionary mapping rounded angles to vertex pairs

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-transform_coordinates(center_type='bounding_box', projection_type='pca')[source]
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Transform coordinates center and orientation

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-center_coordinates(center_type='mean')[source]
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-scale_coordinates(radius=1)[source]
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Scale coordinates to fit within given radius

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-project_coordinates(projection_type='pca')[source]
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Project coordinates using a function

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-pca_projection(target_dim=2)[source]
-

Dimensionality reduction using PCA

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-validate_plot_parameters()[source]
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-plot_faces(ax=None, **kwargs)[source]
-

Plots the 2-cells (faces) of the complex.

-
-
Parameters:
-
    -

  • ax (matplotlib.axes.Axes) – The axes to plot the graph on. If None, a new figure is created.

    • -

  • **kwargs – Additional keyword arguments to pass to the ax.fill function.

    • -
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-

-
matplotlib.axes.Axes

The axes object with the plot.

-
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-plot(*args, **kwargs)[source]
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- -
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-ect.embed_complex.EmbeddedGraph
-

alias of EmbeddedComplex

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-ect.embed_complex.EmbeddedCW
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alias of EmbeddedComplex

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ect: Euler Characteristic Transform in Python

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Python computation tools for computing the Euler Characteristic Transform of embedded cell complexes with arbitrary dimensional cells.

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Table of Contents

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Contents:

- -
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Description

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The package now supports ECT computation on embedded cell complexes with arbitrary dimensional cells through the unified EmbeddedComplex class. This includes graphs (1-dimensional), CW complexes with faces (2-dimensional), and higher dimensional cell complexes.

-

Note: The previous EmbeddedGraph and EmbeddedCW classes are now aliases for the unified EmbeddedComplex class. All existing code will continue to work, but new code should use EmbeddedComplex directly.

-

For more information on the ECT, see:

-
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Munch, Elizabeth. An Invitation to the Euler Characteristic Transform. The American Mathematical Monthly, 132(1), 15-25. doi:10.1080/00029890.2024.2409616. 2024.

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Getting Started

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Documentation and tutorials

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Dependencies

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  • networkx

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  • numpy

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  • matplotlib

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  • numba

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Installing

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The package can be installed using pip:

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pip install ect
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Alternatively, you can clone the repo and install directly

-
git clone git@github.com:MunchLab/ect.git
-cd ect
-pip install .
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Authors

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This code was written by Liz Munch along with her research group and collaborators. People who have contributed to ect include:

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License

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This project is licensed under the GPLv3 License - see the License file for details

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Contact Information

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1. Installation

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1.1. Prerequisites

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Before installing ect, make sure you have the following prerequisites:

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  • Python (version 3.7 or higher)

    • -

  • Pip (Python package installer)

    • -
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1.2. Installing ect

-

To install ect, run the following in a terminal.

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pip install ect
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-
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Alternatively, you can install directly from the source by cloning the repository and running the following command:

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git clone https://github.com/MunchLab/ect
-cd ect
-pip install .
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1.3. Uninstalling ect

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To uninstall ect, simply run the following command:

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pip uninstall ect
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5. GPL-3.0 License

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GPL-3.0 License

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The full text of the GPL-3.0 license agreement can be found at:

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Please read the license agreement carefully before using the software.

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3.3. ECT on Matisse’s “The Parakeet and the Mermaid”

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Here, we are going to give an example of using the ECT to classify the cutout shapes from Henri Matisse’s 1952 “The Parakeet and the Mermaid”.

-

matisse.jpg

-
-
[ ]:
-
-
-
# -----------------
-# Standard imports
-# -----------------
-import numpy as np  # for arrays
-import matplotlib.pyplot as plt  # for plotting
-from sklearn.decomposition import PCA  # for PCA for normalization
-from scipy.spatial import distance_matrix
-
-from os import listdir  # for retrieving files from directory
-from os.path import isfile, join  # for retrieving files from directory
-from sklearn.manifold import MDS  # for MDS
-import pandas as pd  # for loading in colors csv
-import os
-import zipfile
-
-import warnings
-warnings.filterwarnings('ignore')
-
-# ---------------------------
-# The ECT packages we'll use
-# ---------------------------
-from ect import ECT, EmbeddedComplex  # for calculating ECTs
-# Note: EmbeddedGraph is now unified into EmbeddedComplex
-# For backward compatibility, you can still use:
-# from ect import EmbeddedGraph
-
-# Simple data paths
-data_dir = "outlines/"
-colors_path = "colors.csv"
-
-file_names = [
-    f for f in listdir(data_dir) if isfile(join(data_dir, f)) and f[-4:] == ".txt"
-]
-file_names.sort()
-print(f"There are {len(file_names)} files in the directory")
-
-
-
-

We’ve taken care of the preprocessing in advance by extracting out the shapes from the image. You can download these outlines here: outlines.zip.

-

Matisse Numbered

-
-
[ ]:
-
-
-
i = 3
-shape = np.loadtxt(data_dir + file_names[i])
-# shape = normalize(shape)
-G = EmbeddedComplex()  # Using the unified EmbeddedComplex class
-G.add_cycle(shape)
-G.plot(with_labels=False, node_size=10)
-
-
-
-

We’re going to align the leaf using the PCA coordinates, min-max center, and scale it to fit in a ball of radius 1 for ease of comparisons.

-
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[3]:
-
-
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G.transform_coordinates(projection_type="pca")  # project with PCA
-G.scale_coordinates(1)  # scale to radius 1
-G.plot(with_labels=False, node_size=10, bounding_circle=True)
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[3]:
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-<Axes: >
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-../../_images/notebooks_Matisse_example_matisse_5_1.png -
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And then we can compute the ECT of this leaf.

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[4]:
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num_dirs = 50  # set number of directional axes
-num_thresh = 50  # set number of thresholds each axis
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-myect = ECT(num_dirs=num_dirs, num_thresh=num_thresh);  # intiate ECT
-result = myect.calculate(G);  # calculate ECT on embedded graph
-
-result.plot();  # plot ECT
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-OMP: Info #276: omp_set_nested routine deprecated, please use omp_set_max_active_levels instead.
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-../../_images/notebooks_Matisse_example_matisse_7_1.png -
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Let’s just make a data loader with all of this for ease in a bit.

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-
[ ]:
-
-
-
def matisse_ect(filename, ect):
-    shape = np.loadtxt(data_dir + filename)
-    G = EmbeddedComplex()  # Using the unified EmbeddedComplex class
-    G.add_cycle(shape)
-    G.transform_coordinates(projection_type="pca")
-    G.scale_coordinates(1)
-    result = ect.calculate(G)
-    return result
-
-
-
-

And now we can load in all the outlines, compute their ECT and store it in a 3D array.

-
-
[6]:
-
-
-
num_dirs = 50  # set number of directional axes
-num_thresh = 50  # set number of thresholds each axis
-
-ect_arr = np.zeros((len(file_names), num_dirs, num_thresh))
-myect = ECT(num_dirs=num_dirs, num_thresh=num_thresh, bound_radius=1)
-
-for i in range(len(file_names)):  # for each leaf
-    ect_arr[i, :, :] = matisse_ect(file_names[i], myect)
-
-
-
-

Here, we are just going to compute the distance between two ECTs using \(L_2\) distance.

-
-
[7]:
-
-
-
flattened_ect = ect_arr.reshape(len(file_names), num_dirs * num_thresh)
-D = distance_matrix(flattened_ect, flattened_ect)
-plt.matshow(D)
-
-
-
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[7]:
-
-
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-<matplotlib.image.AxesImage at 0x32185cbd0>
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-../../_images/notebooks_Matisse_example_matisse_13_1.png -
-
-

For visualization purposes, we can project this data into 2D using Multi Dimensional Scaling (MDS). Here we plot each figure at the MDS coordinates.

-
-
[8]:
-
-
-
n_components = 2  # select number of components
-mds = MDS(
-    n_components=n_components,  # initialize MDS
-    dissimilarity="precomputed",  # we have precomputed the distance matrix
-    normalized_stress="auto",
-    random_state=5,  # select random state for reproducibility
-)
-MDS_scores = mds.fit_transform(D)  # get MDS scores
-
-
-
-
-
[9]:
-
-
-
# read in color hexcodes
-col_df = pd.read_csv(colors_path, header=None)
-
-scale_val = 6  # set scale value
-plt.figure(figsize=(5, 5))  # set figure dimensions
-
-for i in range(len(file_names)):  # for each leaf
-    shape = np.loadtxt(data_dir + file_names[i])  # get the current shape
-    shape = shape - np.mean(shape, axis=0)  # zero center shape
-    shape = (
-        scale_val * shape / max(np.linalg.norm(shape, axis=1))
-    )  # scale to radius 1 then mult by scale_val
-
-    trans_sh = shape + MDS_scores[i]  # translate shape to MDS position
-
-    plt.fill(trans_sh[:, 0], trans_sh[:, 1], c=col_df[0][i], lw=0)  # plot shape
-    plt.gca().set_aspect("equal")
-
-plt.title("MDS of Matisse's Leaves via ECT distances")
-# plt.savefig("Matisse_MDS.png", bbox_inches = 'tight', dpi=300)
-
-
-
-
-
[9]:
-
-
-
-
-Text(0.5, 1.0, "MDS of Matisse's Leaves via ECT distances")
-
-
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-
-../../_images/notebooks_Matisse_example_matisse_16_1.png -
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-
-

3.3.1. Acknowledgements

-

This notebook was written by Liz Munch based on original code from Dan Chitwood.

-
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- - - - - - - \ No newline at end of file diff --git a/docs/notebooks/Matisse/example_matisse.ipynb b/docs/notebooks/Matisse/example_matisse.ipynb deleted file mode 100644 index ccef47b..0000000 --- a/docs/notebooks/Matisse/example_matisse.ipynb +++ /dev/null @@ -1,362 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# ECT on Matisse's \"The Parakeet and the Mermaid\"\n", - "\n", - "\n", - "\n", - " Here, we are going to give an example of using the ECT to classify the cutout shapes from Henri Matisse's 1952 [\"The Parakeet and the Mermaid\"](https://www.moma.org/audio/playlist/6/312).\n", - "\n", - "\n", - "\n", - " ![matisse.jpg](matisse.jpg)\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# -----------------\n", - "# Standard imports\n", - "# -----------------\n", - "import numpy as np # for arrays\n", - "import matplotlib.pyplot as plt # for plotting\n", - "from sklearn.decomposition import PCA # for PCA for normalization\n", - "from scipy.spatial import distance_matrix\n", - "\n", - "from os import listdir # for retrieving files from directory\n", - "from os.path import isfile, join # for retrieving files from directory\n", - "from sklearn.manifold import MDS # for MDS\n", - "import pandas as pd # for loading in colors csv\n", - "import os\n", - "import zipfile\n", - "\n", - "import warnings\n", - "warnings.filterwarnings('ignore')\n", - "\n", - "# ---------------------------\n", - "# The ECT packages we'll use\n", - "# ---------------------------\n", - "from ect import ECT, EmbeddedComplex # for calculating ECTs\n", - "# Note: EmbeddedGraph is now unified into EmbeddedComplex\n", - "# For backward compatibility, you can still use:\n", - "# from ect import EmbeddedGraph\n", - "\n", - "# Simple data paths\n", - "data_dir = \"outlines/\"\n", - "colors_path = \"colors.csv\"\n", - "\n", - "file_names = [\n", - " f for f in listdir(data_dir) if isfile(join(data_dir, f)) and f[-4:] == \".txt\"\n", - "]\n", - "file_names.sort()\n", - "print(f\"There are {len(file_names)} files in the directory\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " We've taken care of the preprocessing in advance by extracting out the shapes from the image. You can download these outlines here: [outlines.zip](outlines.zip).\n", - "\n", - "\n", - "\n", - " \"Matisse" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "i = 3\n", - "shape = np.loadtxt(data_dir + file_names[i])\n", - "# shape = normalize(shape)\n", - "G = EmbeddedComplex() # Using the unified EmbeddedComplex class\n", - "G.add_cycle(shape)\n", - "G.plot(with_labels=False, node_size=10)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " We're going to align the leaf using the PCA coordinates, min-max center, and scale it to fit in a ball of radius 1 for ease of comparisons." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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MjAKLxRJsESIKi8UCgiBQ8eef+Ompp/DnW2/h9LZtIC3Yqd268YuXD/Dj0zdi5XL0+/e/EZeSgjOffILvp0zB+S+/hO2GHnl9MgtX+uRnDAoi7Ggw6GivX8eJ//wHNSdPIiomBh3uuw8d7rsvorNlsAk/Pn1DIBAgMzcX6f374+pPP+H0tm04vm4dKo4cwS1LlvD6ZBiu9MkvYBTw2amZw2o04ug778BWXY3Wd96JTg8/HNK1tsIBfnz6hzAqCq3vuAMt8vNx8ZtvIG3eHECDPg1KpaPKNE9g8Nnog0xdXR2fHy0ACIJA3dWrSGzVCiKxGNnjx6NFdjYSW7cOtmisYLVaIfLBBOrr9xvDj8/AiIqJQft773X8u/T0aZxauhTZI0ei0yOP8N6vAcLV+OTPwChI4XcIfqM6dw77/v1v7P/3v2FQKgEAnfLyInLxKikpweCCIbht5Bjk5hXg2LFjMJvNlP8dO3YMuXkFGDrqbgwuGIKSkhK/+uXHJ7Mky+WQt2uH87t24cfp03H1p594s2IAcDU++R0YBZWVlXxqGR8x63Q4tWkTLn//PSAQoO3o0Y60PpGqzykzZmDKa6sgkyugVaswbvwEPPLAfZTf3/bpDjz/3lbIU1KhrqnG1JmFOLjvZ5fv0NmdRao+g4VBLEb+m2/iyo8/4tQHH+DPt9/Gpe++Q69Zs5Bwo+gmD324Gp/8AkYBPzn4RsWRI/hr5UoYlUqkdO2KHtOnI7FVK8ffI02fJSUlmDx9BtQ6PRY9OhZJzdIhEAggFEXDZrMhyk0RRpvNBrFUBnlKQ6l1eUoqiKho6PV6iEQinD59GtOfnI2YOAmsJgPWrFyB7t27u+0/0vQZbEh9tr7jDmTm5qJk61Zc/v57WI3GIEsWnnA1PvkFjILS0lJ+kvABi04Hm8mEPk8/jZa33dbEuzCS9FlSUoI7R46GLCkZWo0GEqkUJoMB84o24sVHx2LhwoWU127cug3qmmrHDuzyhfN48803AQBbPt6OBes+cvxtxD1j0bJFc6xbsxo5OTku7USSPkMBZ33GSKXoOX06Oj34oCPouaakBKK4OD6dGU24Gp/8AkYBH5XvnfLDhyHNyoIsKwvN8/KQ1qsXYinSvkSSPqfMmIklWz93LDTL50yHuqYGMrkCLdpkQygUujUBWq1WpGdm4Z25hRBL4mHU1yNRroDNZgMAiOIkLrszmSIJk5Ysx50jR+OHb75yWcQiSZ+hgDt9kouX3WbDkbffhqG6Gh0ffBAdH3iAj1n0Alfjk3fioKCGZhLQmxGzVos/ly/Hb0uX4vjatQAa4myoFi8gcvRptVohErsuNBJZAqSJiVDXVENgs1CeX4lEIsSIhHj6zSLMXbEWT79ZBHmCDAsXLsS8efNQX6eBuqYaAKCuqYZWrYY8JRXSpGRMnj7Dpa1I0Weo4EmfdoLAgHnzIGvRAqe3bcO+Z5+F+tIlAA3jgacpXI1P/jWCAr4Ui3uqjh7Fn2+/DaNSifS+fdFr1ixa10WKPkUiESwGPWoryiFPSYVWrYJeWwedWoUPXnwWa1cXebx+7eoiTJ1ZCJFYAqtRj/XFqxETE4OYmBikKORYPmc6JLIE6LV1kMhk0KpV0KnVAEFgUH4+1q1Zg5ycnIjRZ6jQWJ9WqxVnz57F1JmFEEbHwmoyYvXbbyH1xAmc27EDm594Aps1WsSnNYPVqMfa1UVNzLw3M1yNTz4bPQVKpRJJfFCjA4IgULJ1K85++imixGL0mDbN7VkXFZGiz5KSEjz06GMw2ezQatSwGI1ISU7CJ9s+pHS4cIc7T8OSkhJMnVmIWo0WWrUKSekZIOx2mAx66HU6LN2yE+tfmI2D+36OGH2GCqQ+yd8gKjYOF87+DYlMBkVaesNLirIGkyaMh6C2Ftu++gbPOZmRyd+Fp4FAxyefjT5A+PLiTTFUV0Peti36PfccpBkZPl0bKfqcOrMQT69c73L+lRgX69PiBcCtmTEnJwcH9/2Mv/76C2PuHweLyQSdRgOJTIakZumQyRUNOzerNWL0GSoIhUJYrVZMnVmIya+ucIRFLJ8zHfOKNkJdU43Fj45tOK+UyxGXkeliRhZEiQIOTo8kuBqfvLYp4AdiA9XHjyM5JwdCkQg9Z86EICoKUX7U+YkEfVqtVkTFxjU5/4oSChidvHr37o1WLVvg8Zffcpgp35lbCK1ahQt/n0FJSQmys7MZ6YsHOH78OKbNehKi2DhcuXoNrxdOgjwlFUZ9QykWm9UKeUoqEhRJmDdvHkQiEb75YY+LN+mlCxcwoN8AbNr8Abp26xbsWwo6XD3v4T+rsIRer4dUKg22GEHDbrXi5Acf4PyXX6LTQw8hZ/x4R1CyP0SCPsnzL+eJS6+tQ3RcLOMPLHlWpqzToU6lRFJ6BpbPmY44mQwj7hmLrMxMbHy/mD93CQDSXOisY3lqGkwGvWPXtWjCvYgSiaCuqYYkJtqRHslmtbqcV8bLFSh8dyPuHDkaX330IfoMHhzkuwsuXD3v/AJGgVwuD7YIQUNfU4PfX3sNqnPnkJyTg9bDhgXcZqTos3jVCtz30MMQiSWo12qQopBj7ep1jPeTk5OD/T/uwW3DR+HVj3bBZrUiSiTC64WTECWqxZRX33GbxYOKxjvEm93c5c5c+M7cQjyzvBiLJ97vsut6Z9Yk2CwmbF6/1nFtYkoaZq9Y5/K7yOQKJKSmYdLjT+DHTz9BWs+ewb3JIMLV837zjmAvVFdX35SBosq//8Z/X30VRpUKHe6/HzkTJkDoJquEr7CpT3eTMVsTdOfOnfHoQ+Ngs9kwb948VhOWikQiWM3GJjs+nUYDeUqq4zzM0306OyVYDHrMfWY23nx7hSPbx9rVRejQocNNs5iVlJRgyowZiIppai4kCAIyuQLSG5OvuqYaSQlS/LT7axf9iEQiWI2uO3Gjvt7hMSqVJeDORybgw08/QZcuXYJ0p8GFq/nz5hi1fnAzLl6E3Y4jb78NS309+j//PJrfcgtjbbOhz8aTc/GqFQDQkI5JEs+qe3NUVBQnk/66Natx58jRkCYlQ6dWIy5e4nCvv/D3GZw9e9bj/ZG7DHKiLXzkbry67UvHv+8YORrtOna6KVzBXTKoqMsRJ5WCsNv+MRc+OrZhEVLW4t1npzt04u53pjTxxkugrVPjuS078a/CWTi472fYbTZGXgLDCT6VVJC5GVP1CIRC9J83D4TdDjnDTgJM69OdCWjc+AkA0CRZ7v4f94TtDiMnJwc/fPMVpsyYAdjtDvd68jzMkxnRndNJYnIKZHKF49+ypGTMeqsYWrUKU2bMxKH9+7i6Nc6ZPH0Glmz93MXDUF1T42IuXLfgSfzwzVded6V0PUbPffMNyvbvx8AXXkBsYiKHdxtc+FRSQSbDRzfxcMVcX48/33oL7e6+G2k9erBW8oQpfTrvuhqbgISiaETHxrpM2Mo6HW4bPgo2i4kRcxmZeYFM/8QFOTk5OLB3L24bPgqvffyV63mYgNpc6s7pRFNTDa1a5fi3Tq0G0KArlU6P3Lx8rC9eE1E7MTLxsqpR4mWBUIj4G4uKuqYaCqnE5wXck8fo+b/PoOT4cdhOn8ZPTz+N3EWLGH8xDFW4mj/5BYyCiooKZGZmBlsMVtGVl+O3l1+GtrQUsubNkdajB2t9MaXPxiYx5zidFx8dCwAuE3adSolXP9oVsLmMXDgJoQiXL15AolyBPfsOYH1x00S7bCASiWCzmJqch5VVVyH/9jso76d41QqMGz8BkoREiEVRkCfIXLzn4uIlDi+7OpUSc1fudJt7MVxxNhvqGiVeXjThXggAvPvsdBh1ddj4/nt+9UFlTpTIZCh8fx0+WPQCdF99hf1z56Lvs88ia9AgZm8yBOFq/uQXMAoUNxJ5Riqq8+dx6KWXYK6rQ49//QvZo0ax2h8T+iRNYjK5wmH2kcgSHP+/RZtsmI1Gl2S5SekZjr87m8t88eADmi6c78wtxNRlK31uJxDWri7CHeRkTJ6HJSRi8qsrKOXo3LkzHnngPthsNixcuBDnz59v2MEKgLLqKkgSEvF64aQGXd0wfZG5F387sJ+T+2ITT4mXExRJ+OSD9cjJyYHFYkFcXJxffXjyGBWKorF40yZ8/f77+O8rr+Dw66+j58yZaHPXXQzfaWjB1fwZMQtYUVERioqKGDPt1NfX+z2gQ52qo0fx31dfBWG3Y+ALLyBjwADW+2RCn2fPnsWFs39j8cT7oL0xgQNw7CAENgtio6Mws1EmBfLvzuYyOh58JO7OksSSeJfMGFycsXXo0AHtOnbCrLeKAcDFfdubHGR9MvLsxmq1Iv/2O5q4kTvnXgx3c6LVakVUjBjylFSXFx6rxeLwMCQzqKjV6oDGJ5XHaL1Gg2bJyUho2xb5//d/OPTSS44s95EMV/NnxCxghYWFKCwsdOTQCpSYmBgGpApN1BcuQBAVhUEvv4wUjiYnJvQ5dWYhljZ+m66qxIrZUxxmQfJ7IrEEF/4+gziZDK8XTmpiLqPjwUfi7iyJdJu2GvXcZR244b7tfIZFyuHL/ZBtefSkU6vw3Kr1YWtOdA5SfvKuW1zyShp0uiaJl5kYn+48RuPiJbh44bzDzDt01SpHKRajWo0YmSwiPRS5mj/5ZL4e2om0jN92qxVCkQgEQcCoUiGOw2SwgerTarXitpFj8PTK9Y7PXi+cBLFQgB92fQ5xoywhztnEo2LEuHDurEtiVpNBj7QkBW3z37FjxzBu/KMQS2VQVlUiPTMLMSIh567n7rJHkBOzu/sxm81YtmwZAGD+/PluJxbSk04qVzg86WLj4rB43UdYNPE+KOLjGDcnUu0WmdrNDi4Y0sSx4uk3i7B4wr349svPm+SuZOp5Lykpwe0jRkGWlIx6jQZx8RIIhFGYV7TRJeGvWavF/rlzIWvRAv3mzkVUhL0wB6pPPplvgJhMpmCLwBgEQaBkyxaozp3DoBdfhFAk4nTxAgLXp6c0To0XL/L7pLnMaDRi2N1jMXvlelcPPh9yGDY+S6IqWsk25HlL/rARTTN0ePBI9IQnTzqmzYnuYvc6d+6M06dPN8TvMRBgffz4cVy5eg3L50yHVq12LMgyuQJtO3Zyew9MPe8dOnRA+06dvZp5RXFxkLdrh2v79+Pg4sUYuGgRYuLjGZEhFOBq/uQXMAoiZfdFEASOrl6NS999h6SOHWE1GhEThJyETOjT3zROYrEYVpOBkRyG5FlSMOPKRCIR7Bazzx6JnuDKnNjYGWbc+Al45IH7sOXj7Viw7iNGAqxnPDUbS7bsdDE1KysrPJp8mXre6Zp5hSIR+j77LGLlcpz/8kv8Mn8+blm6NGJixbiaP/kFjIKampqwD2QmCAL/W7UKl/fsQVrPnhj4wgsBJeQNBCb0GUgap7Wri/DoE1NQb7JAp1EhJUnBSg5Drnjt5ZcwYcK9tD0SSecmqh0ancDcQL0T3WbzT0iExWKBKM61yrW/HqNWqxXC6Fi3jhvrFjyJdWvWuL2OyefdUyJm53sRCAToNnkyYhISULJlC3554QXc+uqrEbGIcTV/8gsYBeEeA0bY7fhr5Upc2bsXzfr0wcAFC4JqZ2dCn87l233dAeXk5OC3A/vwyiuvwG63Y/HixWFdU+uWWwbT8kg8ffo0tn26A0JRNDZu3YYWbbIhsFkodzVsmhNFIhHM+nqoa6odno9iURQWLFiATR9vd9lROnuMKut0OH78uNeaa54cN1IVco9Bykw+7x4TMTcy8woEAnQaNw5R0dGo+PNPRAXpBZNpuJo/+QWMgrKysrDegZm1WtSWlCC9Xz8MmD/frxpeTBKIPpkKIj59+jQ+2fkFxFIZNm37OGiOGExQVVVFaapyNpNNf3I2nn9vK96ZW4iXiza6pNii2tWwYU4kf0O7MAoLHh4DiVQGi9GAohVvQyKRIEUh9xhgPeLue7325y5W75nlxVg84V6s+3ibR/mYft59DTxvf++9aDtmjMMj0WY2h7VjB1fzJ7+AURDOixcAxCYmIu+NNxAtlQZ98QIC0ydTQcTkZO7czoxXV3EajMwUWVlZjoWGiIrG5QvnkShXYO38p7C+eDWAhjf9mBvxamJJvIuJzlPcGBvmRHe/4dNvfog3XpiNMaNH48NNH1AHWKdnwGwyeezPU6xe246d0KFDB6/6ZBpfA8/Jxevszp248uOPyFu2LGzNiVzNn+FrQ2GZ0tLSYIvgMwRB4GhxMSr+/BMAIFYoQmLxAvzXJ50gYrrtxDSaxP1pJ1QoLS11LDQ/fvUFpk16DA+MGYn9P/7geLN3digw3jDdAQ2ptujEr5HmxGfffg9v79qLeUUbIRAIHOZElU6PQfn5KCkp8dgOnd+QvJefdn+Nli2aY17RRsxdsRZPv1kEwm5HvUbjyNXorj9nL1XyHn2J1WPjeScDz5du3oG3d+3FG5/ubjjf8zLmBEIhtNeu4deFC2Gqq2NcLi7gav7kd2AUpKSkBFsEnyAIAifWr8fFb76Boboazfr0gUAgCLZYDvzVJ1NBxJ5qOHEZjMwUzvokZY9yExBL7tJiBAIsHH8PUtMzIImJduzSvEHHnOhtB+vLbygSiSgDgr2ZL8m8j86xeutfmO0SsEwFG8+7J49ET2Ou/T33gLDZcPKDD3Bw8WLcumwZosMsKxBX82d4PbUcUldXh9TU1GCLQZtzO3fi/JdfIqVrV/R//vmQWryAwPQZyMTkjDeTWzhBV5/kzkav1+PNN990xLHRzZRAt2yIt/gzX37DnJwcfPvl5xh+972QKZJomy/JWD2LxYLFixfDbre7jRF0B1vPu79jrsN998FmMuH0Rx/h99dec8RvhgtczZ/hoxGOoTvwQ4Ere/fi5AcfILF1awxcuDAkD38D0SdTQcSBTuahhK/69LRLo4Mn78QLf59BSUmJRy9BX3/D7t27o3Wrlj55Qzp7XG7a9rFXj0tn2HreAxlznR5+GEaVCld+/BGqc+eQ3LkzKzKyAVfzJ7+AUWC324MtAi20paX4a+VKSNLSMOjll0M2mp8JfTIVRBzoZB4KBGN8eopvGnHPWLRq2cLrYuHLb+irN6Q/HpckbOvTnzEnEAjQc8YMtBk+POzqiHE1PnknDgrC5VBflpWFHtOnY/CSJZynh/KFQPVps9k4LSIZ6gRjfJLxTanJyVj13a9YvO4jLNm8A4q0dEjlCjz+8luYOrOQ0f4O7vsZH657DwKBABaTCeqaGgiEUU3MiXQ8Lj0Rqs+7QCh0LF76mhpc3rMnyBLRgyt98jswCnzJ8hAM6isrG7wMY2KQPXx4sMXxir/6LCkpacigYbZAp1Zh17e7sW3zprCL22KaYI1PqrIhOo3G5zI1dKETXH3rbUNhNBhcPC5lcgVtj8tQf94B4Ojq1aj44w8IBAK0uv32YIvjEa70yS9gFKhUqpCtB2ZUq/HL/PmIz8jALa+8EnIOG+7wV59TZxai8K1il7x24Ri3xTTBHJ/uvAQlMplfZV3oQsecuHD8PVj19BTYrHY8d/9wxIjFkCUqIBYJUFJS4lGmUH7eSXrNmoX9c+fir1WrIE5ORrNevYItEiVc6ZM3IVLQrFmzYIvgFpvFgt9few366mq0vO22sFi8AP/06TZ3niwBUTHikDX5cIWv+iT1xYQZNicnBz988xWSpHGQJiRAr9UiNi7OJd8f09AxJyYkp0AcF4cEmRTpLVvhla2fY9knX2H2ivVeZQrV592ZuKQkDF6yBKK4OBx+4w1oQzhWlSt98gsYBRUVFcEWoQkEQeDYmjWoPX0a7e+9F62GDg22SLTxR5/uglP12jrYzMawi9tiGrr6LCkpweCCIbh91N14b+MmfLrrG+TffqfX4GNv5OTk4MDevUhLSWlyHhYVHcvaCwad4Opr10sbzo6cEvp6kykUn3d3yLKy0P/552HV6/HfpUthrq8Ptkhu4UqfN/cs4IFQTCV18euvcXnPHjTr3RtdH3882OL4hL/69LeESqRDV59MpeFyh6/5/pjCmzlx6ZadWDj+HiyeeB8EQiGUFeVISEryKFMoPu9UNOvVC90mT0b1iRMQhGhCaq70yS9gFJSWlobUoLZbrbj03XeQZWWh33PPhezApcJffQZSQiWSoaNPOimcAt3J+prvjwnoBFfL5ArM/s+7WDV/NpZu/dyrSz3bzzuTJlwAaDtmDNqOGROyRwhczZ/8AkZBWlpasEVwQSgSIe8//4FFqw3ZWC9PBKrPqKiom95s6IyzPqkmR6bScHmCzPfnrawLG3jyTtQoa6DTqGknMWbreSez8JssVpSVliI1PcOvSgqNIRcugiBw5qOPEJ+RgZZDhjAldsBwNX/yMwIFSqUyJA52LQYDlGfOoFmvXoiJjw/LxQsIHX1GCkqlErW1tV4nR6bScFHhb74/pqAyJ8rkCqx/dSGEUVEuCziVTGyNT9KE+87cQrzy4Rc+BVfTwaLT4fKePTBrNJBmZSHJS9Z9ruDqeecXMAqkUmmwRWjILl9UhOsHDiD/zTeR1LFjsEXym1DQZyQhlUox9sGHvE6OTKXh8kQwc0x6Kh6pVdUiNioKC8ffg5Rm6ZDERGPDe+4rMrMxPkkTrq/lbHwhRibDwBdewIHnn8fhN97AbStWICYEnjWunvfwOkjhELPZHGwRcOXHH3Ft/36k9+8PRYi8WflLKOgzktDr9V4nR2eYSsPlDm9lXdjG2ZmELIKp19YhSSbF+6veQUy0CMrqKtQZjJg4eapbD0w2xidpwvW3nA1dFO3aofvUqdBXVeF/q1aBIAhG2g0Erp53fgdGQbAHQd21azhWXIy4lBT0mT07ZA9r6RJsfUYaUVFRTSZHb2Yytglmjsm1q4saMraYLNBpVEhJUmDt6nWYPH0mpEkpmLO82KP5jq3xSZpwhaJovPjoWJcEw0zSetgwVB07htJff8Wl3buRPWIEo+37ClfPO7+AURDMbPRWkwmHX38ddqsV/Z97DjEyWdBkYYpwyu4fDojFYs4mx3AgJycHvx3Yh1deeQV2u91RTiVaHAdJjNh1hxob18R8x9b47Ny5Mx4ce49DJjZMuECDU0evWbNgUquR0Lo14+37Cp+NPsjU1dUFzWVbefo0dKWlyJkwIaxKKHgimPqMROrq6jg53wonTp8+jU92fgGxVIZN2z5GemYWKsrLII6Pd+RG1KpVsBjrm+iJjfFZUlKCRyY+hhqlClK5Art//AlbNqxjzbQaEx+PvGXLWGnbV7h63m/e0e6F5OTkoPWd1rMnhqxYgYSWLYMmA9MEU5+RSHJyssNMw+b5VjhBllNxDtp+efMOLHzkbix4eAzipFIYdDq0ym6LwQVDXIKa2RifU2cWwhoVjSVbdjLufeiN2tOnUfbf/6Lr448H5fiBq+edd+KgoKqqivM+DbW1MGu1AIDEVq3C/tzLmWDoM5Lh9ekKWU7FXdC2PCUVS7fshEyuwGsf7cLz7211BFqTMK1Pq9UKYXQsJLIEt+ZLtjm3cyfO7dyJa/v2sd6XO7gan/wCRgHXWTgIgsCfy5fjx1mzYNbpOO2bC0Ipq0kkQOqTr5PWABmP5uzpR8aj6TRqx4JG5a3J9PgUiUSwmozQa+tcvQ9NBk52yr2fegpihQLH3nsPBqWS9f4aw9Xzzi9gFJRynOn50u7dqD5+HBn9+4dEHAfTcK3PSOfnn/eh/6DB2LB1G7Z/vRu5eQUBJ+gNd9auLsL6F2bj/2Y+hoXj74FFr8fa+U8hWSF38da0Wa2orSh38dZkcnySCZTrtFpUXL2ChRPuxfwHR2HF7MmcOdjEyGToVVgIS309/vfuu5x7AXP1vN/cRnMPcJk1or6yEic3boQkNRVdJ03irF8u4bNwMMsLL70UtPOVUIWMR9Pr9XjzzTcdzi3nz5/H1JmFsBkMlHXCmByfztk3/vPZbkdhzQ9efJbTQqwZAwagRUEBru3bh2s//4yWt93GWd98OZUgU1NTw0k/BEHgr5UrYTUa0fuppxAdoZ56XOnzZsBqtUIgigna+Uqo0zgejVzYPNUJY2p8usu+ESUSITk9w22AOdv0+Ne/EJeSAkNtLaf9cvW88zswChITEznpp/TgQVQfP442d92FtJ49OekzGHClz5sBkUgEm9kIvdnqGsDM0fmKN2w2W4NTRUxMyMhhtVo9xoQxNT7dZd8IZoB5jEyGO9asgYjjOEyunvfgj/YQxWAwcFISO2vQIPScORMt8vNZ7yuYcKXPSIfMbl6n1aGqshILJ9wLWaIcYpEQH23eFFTZTp8+jS0fb4coToKN2z5GikKODzd9wKnZzJMcNrMReoPJ7aJfV1fH2PgMtQBzcvEy19dDe/UqJ7GlXD3v/AJGgZCjelsCoRDZw4dz0lcw8VefTNdRCndC5XzFHdOfnI0F6z5yLA7L50wPyrkclRxrVxfhkYmPYfGjYyFNVCA+NhpbNjQUR2Xyeecq+4YvEASBg4sXQ1daijvfew+xLO+QuJo/+TMwCtgecKWHDuG/r70WFBfXYOCrPklPrttH3Y33Nm7Cp7u+Qf7td97Unnahdr7SWLaYOImLeU4iS0BUjJhTuTzJ0aFDBxw+dBBPTHgE40YPx28H9jkWfaae95KSEod36Gfffo/cvAKcPXuWkbYDQSAQoMPYsbDU1+PUJvZ36lwt2JwsYEVFRWjdujXEYjEGDBiAw4cPU373gw8+gEAgcPkvGHn09Ho9a21bjUYcX7sW1cePQxiExKfBwFd9kjuNf6/ZjFc+/ALREgmmLlvpEnx6s3H27FlcOPs369nN/aEh7sngIpNeWweb2cipXHTkiIqKapJwmKnn3Tn7xmsf7ULhW8UhM2YzBw1CWs+euLxnD2rPnGG1LzbnT2dYH1mffPIJ5syZg+LiYgwYMADvvPMOhg0bhr///puyamdCQgL+/vtvx7+DkZFCLpez1vbf27fDUFODHtOmsb6VDxV80Se503CXVYHtKr+hzNSZhZDIZFg+ZzoEQiEWTbgXCYokJCVIQyKBL1VG+HCQg4nn3ZF9QxTrNXlwMBAIBOgxbRr2PvkkjhUXY8jy5RCwZOpjc/50hvUd2PLlyzF16lRMmjQJOTk5KC4uhkQiwYYNGyivEQgESE9Pd/wXjBii6upqVtrVlpbi3OefI7FNG7S5Cc6+SHzRJ+nJ5S6rQrB3GsGCnBwVaelYsnkHFq/7CKu++xWpycnY/+OeoJ9/kdisFmjVSsQnyhElig6KDGRm+nGjh+OJCY/g8KGDXvXDxPMe7OwbdJA1b452d98N9YULuLZ/P2v9sDV/NoZVrZrNZhw5cgTz5893fCYUCnH77bfjt99+o7xOp9OhVatWsNvt6N27N1577TV06dLF7XdNJhNMJpPj33V1dYzIzkYqFIIgcOy992C3WtFzxoybxnwI+K5P0pNLLJVBWVWJ9MwsrH9hdkjsNIKBY3I0mV286GwWU8hMjqT5bOnWz0MiuNqXumRMPe/Fq1bg7vsfwOJHxyJBkQRJTDQ2r1/LSNtM0emhhyBJS0PzW29lrY+ISCVVU1MDm83WZAfVrFkzVFRUuL2mY8eO2LBhA7788kts3boVdrsdgwYNwvXr191+f9myZUhMTHT816JFCwCA0WhEWVkZ7Ha7I61JaWkpzGYzqqqqoNPpoFaroVQqYTAYUFFRAavV6vjuiRMnYLFYUFFRAb1eD6VSCZVKhfr6elRWVsJisbi0a7PZUFZWBoPBgNraWmg0Gmi1WlRXV8NkMjV8x2SCOSkJLW67DcaEBJhMJlRXV6Ourg51dXWoqamBwWCgLbder28id2lpKaxWaxO5dTqdW7ntdrtXuQmCcPlfUm6tVguNRoPa2lpKuS0WCyorK3HhwgWoVCracqenp2PyxAl4YNRw/PeX/dj/w25s/3ArcnJymshdU1Pj0KE7ucn2Sbl1Oh3EYjHi4+Md48Rms7mVu76+HiqVCmq1GjExMUhISKCU22AwQKlUQq1WQ6fToaqqCmaz2a2+jUajW7nLysrcyl1VVYX/vLoUelUtFj86Fi88cjdWPfMvFK9aSUtumUzWRG6bzYby8nIXubVarU9y19TUwGg04urVq26T1wqiY6FSqaDRaCCRSBAdHY3Kykqv+vb2rJFyO4/Zqqoqx28P/GPGKi8vdxmzjX97u92OEydO+DxHkHI7P2sZGRmY8thEzPrXFPz20x58+dl2x5ilM0eQ7TZ+1picIypra9HyzjtRVVPD2hxx+fJln+cInU7nMkfQQUCwmCSrrKwMWVlZOHToEHJzcx2fP/fcc9i/fz9+//13r21YLBZ07twZDz/8MJYuXdrk7+52YC1atIBGo0FCQoLfstvtdlZcQQmCgN1qRVR0cMwrwcJXfZrNZiy7Udto/vz5jAbF+tM2m/J4g4z9MlmsKCstRUqzdEhiorHhvTVeTWNcyp2bVwCtyexS/Xj9C7NxcN/PnOuPqj+qz5l43hvX/4qPiWa1/legGJRKnNywAe3uvhuK9u0ZbTtQfdbV1SExMdHrPM6q7SElJQVRUVGorKx0+byyshLp6em02oiOjkavXr1w/vx5t3+PjY1FbGxswLI2pqKiApmZmYy1pysvR3x6OgQCwU23eAHM6/Nmwjn265UPvwgJ85w7wsF8RgUT4zOY9b/8wazV4vqBAzBpNLjFzeYgELh63lk1IcbExKBPnz7Yu3ev4zO73Y69e/e67Mg8YbPZcOLECWRkZLAlpluSkpIYa8ui12Pfs8/i99deY6zNcINJfd5MuIv9ApqWAwkFOnfujEkTxuOJCY/gz1/24c/fvDtPhAqBjs9g1//yh8RWrdBiyBBUHT2KqqNHGW2bq+eddS/EOXPmYO3atdi0aRNOnz6NGTNmoL6+HpNuZF2fOHGii5PHkiVL8MMPP+DixYv466+/MGHCBFy5cgVTpkxhW1QXdAzW5Dr3+ecwa7VI79+fsTbDDSb1eTPhLrceEBqxX1RERUWFpFyeCHR8hoMHojs6jx8PoUiEU5s2MVpyhavnnXXNPvjgg6iursbixYtRUVGBnj174rvvvnM4dly9etXFVqpSqTB16lRUVFRAoVCgT58+OHToEOdvckzZ6I1qNc5/8QVkzZtzWs4g1Ah2Ytdwxl1uPbvZhA3vrQm2aBEDE+MzHE2o8WlpyB45Eue//BKlBw+i+S23MNIuV887J68Gs2bNwqxZs9z+bV+jktdvv/023n77bQ6k4oa/P/kEVqMRXSZOvKnc5nmYw11uPb1eH5CTEg/ztG/fHpMmjIfFYsGCBQsgCZPSSB0feACXf/gBlX/+ydgCxhWhu7cNMs6ejf5SX1GBS999h6SOHZExcCADUoUvTOjzZqSxZ9vuH3/Clg3rkJqaGmzRIopAxmdjL9HU9AzsPfAr1hevDoszwNjERAxduRISBhNGcPW88wsYBUy83UaJxWh1xx1ofuutQUmHFUrwuwX/oPJs++n774ItWkQRyPgMFy9RT8Q7eYUTBBHwfMXV885no6egloEKpmK5HL1mzkRqt24MSMQ+7rylmPKgYkKfNxuePNsah6Z4wmaz8eVovODv+AwnL1Fv1FdV4cD8+bi0e3fAbXH1vPMLGAWBuu1XnzgBm9nMkDTsUlJSgkH5+RgyfBRy8wpw7NgxHDt2DLl5BRg66m4MLhgScBkTrsMgIgFPnm1kxhlPlJSUIDevANu/3o0NW7eh/6DBN3U5Gk/4Oz7D0UuUitiEBNRduYKzO3bAHuALD1fPe/hol2PILCL+YFAqcXDxYqT16oVBixczLBmzlJSU4M6RoyFLSoZWXY64eAnuvv8BxMaK8fx7WxkzhwSiz5sZKs82OvqcOrMQhW8VB73AZDgQyPgMtQrM/iISi9FuzBiUfPghrh84gJZDhvjdFlfPO7+AURCI8s9/+SXsVivaDBvGoETsMGXGTCxxSr66fM50GHQ6yBubrQIsY8IvXv5BBgfbbDbMmzePtmebu5I0ElkCooSCkCjtEWoEMj5DsQKzv2SPGoWzO3bg7GefoUVBgd9nYRGRzDecIZNN+opZp8Olb79FQsuWIR+4bLVaIRI3rV4rkysgFgkZNYf4q0+eBhoHB3vTp7uSNMEoMBku+Ds+Q7UCs7/ESKVoM3w46q5eRYWHwsPe4Op550cyBSkpKX5dd/Gbb2A1GtHh/vtD3vPQeZIjd2B6bR3iY2Pw3JxnUPjI3UhMToGmphryBBlKSkr8dgv2V5887qGjz+JVK3DfQw9DJJagXqtBikIelAKT4YC/4zPc8h/Sod099+Dit99Cc+kSMgYM8KsNrp53fgGjQKPRUFaMpsJqMuHCrl0NtXby8liSjFncTXKbN36AydNn4tVtX0ImV0CrVgV8fuKPPnn+8QJt7EVIR5/t27fHow+NC7vA2mDg1/Me4hWY/SUuKQnDN25EjEzmdxtcPe/hqWEOiIuL8/0igkD7++5DXEpK2GTd6Ny5Mx59aJzLGYvVakVMXFPTYiDnJ37pkyWoFoVQwl1w7J59BxzBsZ70SV5LCEW4fPECEuWKsAqsDQb+jE+qIqOhnv+QDuTi5W9MGFfPe3hrmUXsdrvP14jEYnQYO5YFadjH+Yyl4cE0NDEtRsfF+v1g+qNPpvG2KIQS3oJjPemTvJa85p25hZi6bGXYm7bYxN/xGY75D+lS/scfOLlxIwa99BLifdxNcfW88wsYBb4GINZXVSEqOhpihYIlibhl7eoiPPrEFNSbLNBpVEhJUgR0fhIKAZ3hkjGBTnAslT7deR+KJfGQyRUBe5JGMv6Oz3DNf0gHgVAI7bVruPzdd+gycaJP13L1vPNeiBT4OhBPbdqE7554AgalkiWJuCUnJwe/HdiHcaOH44kJj+DwocBqOwX7wQ6njAl0gmOp9OnO+9Cor4dWrQq7wFou8XV8lpSUYHDBEOTdMQzvbdyEr378GUPvGhFRgeLNevdGfHo6Lv/wA2wWi0/XcvW886OZArVaTduOa1SrUXboEJJzchAXYYUboxg6y/NFn2zgblFwnFmE4MTuLTjWkz7Ja8VSGZRVlUjPzML6F2aHXWAtl/g6PsNlNx8IAoEA2SNG4MSGDSg7dAgt8vNpX8vV8x5aT20I4YsHzeUffoDdakX2iBEsShTehIIHYjhlTOjcuTMeeeA+2Gw2LFy4sElwrCd9RlJgLVf4Mj7p7OYjRd+tbr8dJVu24OI33/i0gHH1vPMmRAoqKipofY+w23Fp926Ik5L8jpm4GaCrT2eYTkJLLgoPjBmJC2dKcOD7b3Fw388h58DhDLkDbjwhUunTOf/hB9s+Rv9Bg8M6sJYrfBmfkZT/0BsxMhma5+VBc+kSjCoV7ev8ed79IXI0zTB0U6FU/PknDDU16PzwwxBG0MBlGl9Sy5SUlDQ4kJgt0KlV2PXtbmzbvImxhYZqUQgnqPTJ5z/0D19TH4XTbj5QciZORPdp0xDtg0mQq1RS4fsEs0xpaSmtHyEqJgYpXbui1Z13ciBVcCB3QYGYRujqEwjdSTiU4sbc6TMc8h8yMZbYwJfxCXg38UYS/pzr+6pPf4lMjTMAXRtuWs+eSOvZk11hgsTp06ex7dMdEEtl2Lh1G9IzsxAjEmLt6iKfd0N09RmKkzDbO0IqPC2Y7vRJlRoskPg9piDHklAUjY1bt7nsWELBhOvPmY3z7xNs/bKNUaXC+V27kNqtG5r17u31+1ydgUW21gNAqVSimZcS2zazGVExMRxJxD3Tn5ztUlLlnbmFmPHqKr92Q3T0CYTmJMz1jrCkpASPTHwMNUoVpHIFvvnhR2zZsM5loqfSZ6jmPyTH0jtzC/Fy0caQ89qjOz4Ber9PpEEQBM7t2AFdaSmtBcwXfQYCv4BRIJVKvX7n0EsvAQIBbnnllZBP3OsrVqsVMY08rAIJiKWjT5JQmoSDsSOkkyCWSp/uUoMFG3IshbLXni/jMxIT+HojLikJqd27o+KPP2DWar3mSfRFn4HAeyFSYPZSTVlfXY3qEycQk5AQcYsXcCOdlJG5gFhv+nSGnITHjR6Ov48fxf/+OBy0t1uuy5I4EsQ2rsd2I0EsCZU+nb/D9aJAlWOSHEuh7LVHd3zS/X0ikRZDhsButaL04EGv3/XleQ+E4I+cMOXa/v0AgJYFBcEVhEXWri5qSAobFY3LF84jUa7A2vlPYX3xak76b1wDK1hwuSP0N0GsuwS+XOV5pJNjkhxLMQIBFo6/B6npGZDERHM2lpgikhP4eiMzNxdHV6/Gtf370eauu4ItDgB+AaMkxsvZ1vX9+xEjk6FZnz4cScQ9OTk5OLjvZ+j1erz55psOjytvunGHP9eEClyb5egkiG2sz2Am8KWTlYLJscQGvsgRyQl8PREtkSC9f3+U/vor6quqPCb45ep35RcwCnQ6HeLj493+TXPlCjSXL6PNXXfdFLFf5JtlIGmlPOkzXOBqR9i5c2dMmjDe44LprM9gJvD1NSsFE2OJDXwZn3R+n0ilw9ixaFlQ4NW1nqvnPfJnXz9J8vADaS5cgEAoRNYtt3AoUXjjSZ887vG0YDrr053nJlcJfMMtxyQV/ozPUDFxc4mifXta3+Pqeb+5tO8DVVVVlIF4LW+7Den9+0MkFnMsVXCx2WwNHmV+mAc86ZPHdxrrM5gJfCMhKwU/PulDEARUZ89CmpWFGApvQ670yS9gFHhTPtUPF4mcPn0aWz7eDlGcBBu3fYwUhRwfbvrAJ+cAfnJglsb6DGZmiFDNSuFL5hR+fNLn+i+/4I8330Tvp55C6zvucPsdrvTJu9FTUFpa6vbz8j/+wN+ffQazTsexRMFj+pOzsWDdR3jto114edNnsAhFmDqz0Kc2qPTJ4x9U+gxmnsdQyTFZUlKC/oMGY8PWbdj+9W7k5hV4rdPFj0/6NOvVCwKBABWHD1N+hyt9Bv81KURJT093+/nl775DxZ9/howbKdtYrVbExEkCDuSl0iePf/D6pMafQGNen/SJkcmQ3KULKv/3P8psRFzpk9+BUVBVVdXkM6vJhKqjR5HStetNY0JsiHsxBBzI606fPP7D69M9/gYa+6JPqoDtm4mM/v1hM5lQdeyY279zNT75HRgFcrm8yWfVR4/CZjYjo39/7gUKImtXFzUkszVZoNOokJKk8DmQ150+edxDZ4Lk9ekeb4HGVBki6OiTTsD2zUJ6//44sWEDKg4fRka/fk3+ztX45BcwCgwGQ5OS2BV//gmg4ce7mcjJycFvB/bhlVdeAQC/AlDd6ZPHFV8mSF6f1PgTaExHn3QCtm8WZFlZSOnaFVGxsW7/ztX45BcwCoTCptbV6uPHEd+sGaQZGUGQKPhERUX5Xc/JnT55XPFlggx3fQYSkuENfwKNvenT14Dtm4G8Zcso/8bV+Ly5NO4DjTMFEASBDvffDxBEkCQKLoHWBgu1zAuhhq8TZLjq8/Tp09i49UNYbXZ89u33kESLsHn9WlZMcL4EGnvTZ6QEbHMFV+MzYrReVFSEoqIixg5WDQYDZE4lAwQCAWXMw81AoLXBGuuTxxVfJ8hw1ef0J2dDmpSCOcuLQ8oER0efkRCwzSSE3Y7/rV6N6Ph4dJs0yeVvXI3PiFnACgsLUVhYiLq6OiQmJgbcXuNDSHN9PWLCPJefvzBRG4x3OvCOLxNkqOmTzouj1WpFtDgOkhixWw9BpnYx3pxg3H1OR5+hGrAdLARCIZRnzsCs1aLr44+7lJXianyGtyGdRaqrq13+ve+ZZ/DLCy8ESRr2oOPxxkRtsMb6DFSmSIScIB8YMxIXzpTgwPff4uC+n92a13zRJ5v4EjQsEolgMxuh19a51gRjqBRJSUkJBhcMQd4dw/Dexk348oe9yL/9Toc8JSUlyM0rwPavd2PD1m3oP2iw42++6DNUArZDgdTu3WFUKqErK3P5nKvxyf8CFDinQtHX1EBXXo6Url2DKBGz+Fo/KtDaYHRSywSzplUoQWeCDJXUR74GDa9dXYRHJj6GxY+OhTRRgfjYaGzZwExtNW9OMFNnFqLwrX9Ml8vnTHf8LVT0GW6kdO2KC199hZoTJyBz0iGfSirIOKdCqTlxAgCQ0q1bsMRhHPJh//eazXjlwy8QLZE46ke5g6zn9ONXX2DapMfwwJiR2P/jD7QXFjqpZXyV6WYmFFIf+RM0nJOTg8OHDuKJCY9g3Ojh+O3APkZeTrw5wRiNxiYlZySyBETFiGG1WkNCn+FI6o05sfrGHEnClT75BYyCDCdX+dobZoZIWcDo1I+iwnlX4EsJ9QwvoQeByMQ2oWjS9KZPLnAEDfthEoyKimLUU82dE4xDHqMeYrHYUXLGZrWitqLcJaMMXX3abLaQGgfBJkYmQ2Lr1qg5edLlc67GJ29CpKCiogKZmZkAANXZsxAnJUGSkhJkqZghkPpR/mamd9Yn0zKxRSibNL3pkytCqTqxNyeYuc/MxrQHhiM6VgxZohxatRKvrVoJwLs+S0pK8MjEx1CjVEEqV+CbH37Elg3rgj4OQoEujz8OYVQUCIJwOHJwNT75BYwCsiCb3WqFrqwsYnZfJP7WjyIz07s7R/AEnQJ3waxp5Q7SpOkcOkCaNIPt9h0qBUJDqTqxNy/BN99egWYtWrm48L/xwmyMGT3aqz79SRB8s5Dep0+Tz/iClkFGp9NBLBZDKBJh5LZtsERY+RR/XIIDyUxP6pNpmdiCjkkzmF5odPTJJaFSndjZvNfY3O3Jhd+TPh1nfaJYVt3/wxmb2QyzToe4GwsXV+OTPwOjwDnFTVR0NMQKRRClYQ9fXIIDyUzvS8qgUHBTdjZpAv6FDrAJGymYwhlv7vzeXPg96TOQs76bAbvViq8ffhhHi/6xlHA1Pnnte6H8jz8gEArRrHdvl0C9mxUmMtOHC6Fm0ow0/M2r6Q46Jr5AXPhD6awv1BCKRJA1bw7V+fOc980vYBSQZRdOf/ghjCoVRmzaFGSJQgN/M9NTlbEIZULJpNmYcNQnCZlXUyiKxsat21ycLfxxiqBr4iNd+N2NXW/6DKWzvlBE3rYtLu/ZA6NKBbFCwdn45E2IFEilUtgsFtRduQJ527bBFifk8NUNWhrGBUBDwaTZmHDWJ5lXM1oiwctbduLfqzdh8qsr/I7389XE527s0tVnqJz1hRry9u0BwLEL42p88gsYBUqlEtqrV2G3WvkFjAGUSmWwRYgoQkWfvsbIkXk1PWXd94fiVSugU9Zg8aNjsfCRu7H63zN8MvWGij7DFUW7dgAAzYULALjTJ/8qQUF6ejpKf/0VAJDQsmWQpQl/0tPTgy1CREGlTybPlTzhb3ViMq8m02VJAjXx8eMzMKTNmwMAjCoVAO70yS9gFJSXl0N3Ix2KlM+TFjDl5eV8vjkGaaxPps+VvBFIdWIyr2aMQICF4+9BanoGJDHRtPNqesJfEx8/PgMjOi4Oo7dvR/SNKsxc6ZNfwCjIysqCKTERivbtIQ2BjAehhq/pdPjJgVka65M8V3pnbiFeLtrIarBtoNWJybyaer0eb775psNJJpihAfz4DBxy8QL4ZL5Bp7S0FNkjRmDI8uUQhVDAaLDxpXyGM3yyVGZx1idb50pUeMs7SHcHRH4vFKpL8+MzcLTXr+PSd9/BXF/PmT75HRgFqampwRYhJPE3pQ6vT2Zx1idb50qeiLTqxPz4DJyKP/7AiQ0bIGvRAqk3vBLZhl/AKKguLcX1Tz5ByyFDkDFgQLDFCQkCSamjVquRlpbGlaiMwpVjhC801ieb50ruCOUYOX8I5/EZKpC+ArqyMthTUznRZ/iOOJaxqVQoPXgQyZ07B1uUkMERb2Myu77l00ipE+dkHw8XuHaM8IXG+gzWuVIoxsj5QziOz1DDsYCVliJ54EBO+gzvUcciuqoqAEA878Dhgr8pdcKxhhKXjhG+QqXPUDpXCifCcXyGGvHNmkEgFEJXWsqZPvkFjAKjWg0AkPC2cRf8jbex2+0sS8YsdBwjgrnrCDd9hhLuJlden4EjFIkgTkqCobaWM33yCxgF1hsBeXHJyUGWJDTxNd4m3Ew0wXCM8IVw06cnbDZbwwtDAOZOOhlBSkpKGhJRmy3QqVXY9e1ubNu8CTk5OV71GYpVuUOR1O7dIRAIOBuf/AJGQb3JBKFIhOgwzjkXSqjV6rCbdLl2jPCFcNRnY06fPo2NWz+E1WbHZ99+D0m0CJvXr/XpfNGXjCBTZxai8K1/ilk6F2Ol0qe/GUduVvo+8wyAhkBmLsYnv4BRkN2rFwyZmXwJFYYIRw+vUAy4JQlHfTZm+pOzIU1KcamQ7Ov5It2MIO4KlDoXY6XSZyAZR25muBqffCAzBaJ27dBp3LhgixExVFRUBFsEvwlFx4hw1ifgVCFZluA2JINuG94ygpC4K1DqXIzVnT59aZ+ngeoTJ3BkxQpcPn2ak/74HRgFfGoZZuH1ySzhrk9HhWSDyeeQDOc26jVqt+eU9Rp1k3aKV63AfQ89DJFYgnqtBikKuaMYqzt9uss4EkrnoKFIfUUFrvz4I7IGD+akP/4XcINRpcKPb72FDr17o8PYscEWJyIoLS0N+0k3lIgEfQZSIZnEZrVg+ZzpEAiFWDThXsgUSRBFRyPa3nR31LlzZzz60Di3HrRU+oy0jCNsI1YoAADl1dXgIh89v4C5wahUwlxSAnv37sEWJWKIhDObUMKbPpnw7GMbTxWS6WC1WpGYkobZK9bBZrUiSiTCshmP4blV6/Hus9MpQx3cedBS6TPSMo6wjTgpCQAQq9Fw0h9/BuYGs1YLNGuG2ISEYIsSMfAFA5mFSp+kZ9+GrdvQN28I+uYOppVsOZj4Wt2bhAx1UNdUI0okgrqmGiajAVq1ymcTn7fxGSkZR9gm5sacWWc2c9If/2u4waLXAxoNRGHuphxKcFVinA6hmNvQV6j0yYRnXzhBhjoQUdG4fOE8EuUKrJ3/lM+hDqE0PsMZcs4U6nTc9MdJL2GGzWgExGK+jAqDmM1mxMfHB1UGMrehWCrDxq3bkJ6ZhRiRkHZuw1Ayy7nTp8OzL0bsc7LlcIWpUIdQGJ+RQHRcHNrdfTdi27blpL/IG9EMYDEYAILgd2ARBpnbkNyZvDO3EDNeXeV1h8JEwC0XMOHZF66EYqjDzYhAKET3KVOgupHJiG0ie1T7SXq/fhDK5Uhs0ybYorAOV+a0YO9ayNyGzjsT8Y1ch95yG4aiWY5Kn0x49t2MBHt8Rhpc6ZN34nBDfFoaJO3aIUYmC7YorEGa0z7d9Q3adspB3rARGFwwhLUDfx1HNnEqnA/8gYZAVqO+3uuBPxMBt77i/FJBBZU+Sc++JyY8gnGjh+O3A/tCbqfoDjr3zCbBHp+RxO9vvIEjGzdy0he/A3OD1WRCYgQvXgD3pUKSbrjXBhN/Dvy5NMv5ckbnTZ/hYkoLlZproTA+IwXd9euw8uVUgsex4mJcvXgRI197DTEReLAbjFIhVVVVtANv2TJr+nvgz5VZzpczOl/0GcqESs21SNFnKCCKi4OBoxcoTkyIRUVFaN26NcRiMQYMGIDDhw97/P6nn36KTp06QSwWo1u3bvj222+5ENOBzWQCcfFixHohuisVAoDVFDl0JgeuzJq+Hvg7m+XuHzkMvx3Yhw4dOjAqE50zOmfo6DPYZjlv0HmR4gp+8WKOKLEY9gsXOOmL9QXsk08+wZw5c/Diiy/ir7/+Qo8ePTBs2DBU3ah43JhDhw7h4YcfxuTJk/G///0P99xzD+655x6cPHmSbVEdEAQBQXY2BMLIPSJcu7oI61+Y7SgV8vJj92Pt/KdYS5FTWlrq9Tvk23i0RIKXt+zEv1dvwuRXV2DqzEJWZPKF06dP45OdX2DH17tZWVx9PaPzpE+uzzf9JRgvUlR4G5+h/jIQSgiEQhAtW3LSF+sjZPny5Zg6dSomTZoEACguLsY333yDDRs2YN68eU2+v2LFCtx1112YO3cuAGDp0qXYs2cP3n33XRQXF7MtbgN2O4grVyK6lArXpULS0z1nRgv1CshcmLp8OaPzpM9QMcvRIVRqrlHpM9DYwZsRgVAIXLnCSV+szghmsxlHjhzB/PnzHZ8JhULcfvvt+O2339xe89tvv2HOnDkunw0bNgxffPGF2++bTCaYTCbHv+vq6gKWmyAICJo3D7idcMDf+Blfg3qrqqqQkZHhUY5QrYDsbnG1Wa20XPB9wZeXCip9hvqLQGNCpeYalT79jR28mWl3992QDhzISV+s2shqampgs9nQrFkzl8+bNWtGWc+ooqLCp+8vW7YMiYmJjv9atGgBADAajSgrK4PdbneYB0pLS2E2m1FVVQWdTge1Wg2lUgmDwYCKigpYrVaUlpaCsNsBiQQWiwUVFRXQ6/VQKpVQqVSor69HZWUlLBaLS7s2mw1lZWUwGAyora2FRqOBVqtFdXU1TCaTy3cJgkBpaSlMJhOqq6tRV1eHuro61NTUwGAw0JZbr9e7yE1+12q1NpFbp9O5ldtutyMxMREikQhKpdKt3KS8BEHgwIFfsPWT7dj+9W507NYTPfr0w6FDhyjltlgsqKysRExMDFQqlUe516xcgfeeL0Q0gIXj78GSxx/A+/Nm4fWlS2A2m5vITeq7pqbGoUN3cpPXkPrW6XQQi8WIj493jBObzeZW7vr6emi1WpjqtdCqVVDXVOP5B4bjmTFDsXjifTj/92mUlJSgoqICBoMBSqUSarUaOp0OVVVVlHIbjUa3cpeVlSEqKgpyuRxRUVEoLy+HyWRCVVUVtFotNBoNamtrIRaLUV5e3kRugiBg1GndmuUshoax6zxmy8vLXeTWarW05NZqtRCLxZBKpQ65qcasVqt1edbcyQ0AMpkMcXFxUKvVXp81Um7yWdPpdJBKpQ6dOeujrKwMJpPJoTexWAylUukyRxiNxiZyq9VqiMRxlOeSV65cuWnmCG9yO88RlpQUtBowANXV1S5j1tscodPpXOYIWhAsUlpaSgAgDh065PL53Llzif79+7u9Jjo6mti2bZvLZ0VFRURaWprb7xuNRkKj0Tj+u3btGgGA0Gg0fsttUCqJ6+fO+X19OGEymYiXXnqJeOmllwiTyeT1+wNvzSfW/3qM2HGmjFj/6zGiS/9cYlB+gdframpqaMtUX19PvPTSS8SiRYtoyeQrvt4zQRDEqVOniEH5BURWm7ZEl/65Ljqgc/9My+dJn6SsfQbdSmS0akN0HzCIGHhrPnHq1ClOZeSyPTrXe/oOlT4H5Re4/Nbdcm9h5TePNHx53t2h0WhozeOs2hJSUlIQFRXleOsjqayspLQ5p6en+/T92NhYxMbGMiPwDcQKBaQR7MDhL1arFTFxEsqy7J5MU76YrUIxLVBOTg72/7gHtw0fBSMBTnINejLTeuqrsVnOYrFgwYIFLvWveFyh0idTyYJvJv776quoLi3F6NXs64jVWTomJgZ9+vTB3r17HZ/Z7Xbs3bsXubm5bq/Jzc11+T4A7Nmzh/L7bKArL4f26lUQBMFZn+GASCSC1WSgLMvuCWEEvBCIRCLYLCbotXWuHnMMBzWfPn0aWz6+Yabt3hO9+vVv4kFIR5/nzp3Dxq0f4oNtH7NWWiVSvPOo9Em+DPz41ReYNukxPDBmJPb/+APvwOEBm8UCu5NfApuwfpo7Z84cPPbYY+jbty/69++Pd955B/X19Q6vxIkTJyIrKwvLli0DAMyePRv5+fl46623MHLkSHz88cf4888/8f7777MtqoOSLVtw/cIF3FNUBEEIHXiHAmtXF+HRJ6ag3mSBTqNCSpLCUZbdEwaDAbIIyG7CRVDz9CdnY8G6jxyOA8vnTG/iNEBHn2zmcIw07zxv+gxFq0CoQtjtAEcJIFifnR988EFUV1dj8eLFqKioQM+ePfHdd985HDWuXr3q8vYzaNAgbNu2DQsXLsSCBQvQvn17fPHFF+jatSvbojoQicVAbS2sJhNi+AXMhZycHPx2YJ/PVXQTExPZFo0TAq0i7A26Zlpv+mS7tApb3nnBKlkTKeMzFLAZjRDRdcIIEE5m51mzZmHWrFlu/7Zv374mnz3wwAN44IEHWJaKmiixGIKsLFgNhohMJcUEvr6J1tTURFS2A7bexJ3NtOTioNfWITou1mXR8aZPNnM4BpLZnwqmStb4uwBG2vgMJlaDAQKOdMlvL9wgiosDcfFiQ2FLHkbgJwf60DHT0tEnW+ZO56wh5MJIJ7O/JwI1d5LnhqI4CTZu+xgpCjk+3PQB7QWQH5/MYTUaIVarOemLX8DcIIqLgyA7G1aDIdiicIY/b66+JN0tLS0NuUkilCosO0PHTEtHn87mTrvdjsWLFzPmTMOkdx4T5k4654Yk7n73UByf4Uru4sWorKnhpC9+AXNDtEQCYXk5bBZLsEVhHX9MN/4c4GdmZrJ1Cz4T6Ns6V3gyU9LVJ5nDUSiKxqZtHzNWroTJDBqBmjvpnht6GuuhND7DnYQWLSDjKJMRv4C5IXvECIh79kTKTTCo/THd+HOAX15eHjKThC9v66EKXX2ynReRKe+8QMyddM8NPY31UBqf4QxBENCVlUFpNKJV27as98cvYBQkJycHWwTW8cd04+8BfqjoM5Bg7GBAZaalo89wyosYqHent3NDb2M9VMZnuGPR67Fn+nS0uOsutCpkv4pE+EeXsoBRrca5ffuguXw52KKwisN040Ngrq9lP0j8SbJMnlUwSSDB2FzIR0Kaab/8YS/adspBbsFQl5IodPQZSuVK6BIVFeXXbo48Nxw3ejiemPAIDh866GIi9TbWmUgCzgOH34BdKuWkv9AbwSGAUanE2a1bIRo1ComtWwdbHFbxx3TjzwG+L+m+mHKppsLfYGyu5AO8m2np6jNUypVwhafFz9NYZzod3c2K+caLgDgujpP++AXMDWKFAhAIYFQqgy0K6/hjumE71x6bGSQA/4OxuZLP1+rMnuAqL2KoenQ6w3YQOg9gqK0FAMRwFBjOmxDdEJuYCIFYfFMsYCT+mG7OnTuHLR9vx2fffk+Zs4/EbDbTatNxViFLcHtWwST+3DMX8tEx09LVJwlbeRHp5G0MNdz97nT1yabZOBIwqVQAgCiO0sbxOzA3CIRCxAgEMNxEC5g/+OLNJ6VpE2czgwQTcCUfafqzEAJcvXQRcVIpXnh4DOQJMpSUlCA7O9un9tjaNUaCRyfgfXyGS+hFsDHdMCEmcuQUE/wZIUSJbtkSxvPngy0Gp/gSmOyrN59SqaTtpsxFwtxA4EI+0vQ38NZ8vPbRLsjkCmjVKscC8em2D2nrk628iGx5dPoyDpm63tv4jJSFmm063n8/2o0Zg4qqKk764xcwCtJSU6G/8SBEOqTHm1AUjY1bt9EKdqUbe0NCVc/NHVyeVfgz2bGZ4cIZq9WK2EZnYeQCkZKSQrudxrtGmVzByK7R1zHgDX/Gobvr6QTYN/7dPY3PcAu9CDZRMTHI4Cimjtc8BakjR940qWX8DXb1xZuvvLzcZ32yWboi0HIgbGW4cMbTAlFdXe2TPteuLsLYB8bhufuHI0YshixRAbFIgJKSkoDkDdSj05lAg67pBNhTLZKvvPgihgwpcNsu0wt1JFP222+Ijo+HOTmZk/mT1z4FN8viFUiwq7M3n7edSKjpM9ByIGxnuCBxt0CsWVnssz5zcnKgSE6BSJrA6DmYL2PAE4EGXdMNsKf63Ra+MBsHhxRQts/kQh3JHHv/fYgVCgxZvpyT/ngvRArO/e9/+Ovdd1F7+nSwRWGVQINdyZ3IVz/+7DbglqS0tJS1e/CVQN3U6Uy2TJGTk4MN762B3WxEUmoaapUqTJ75JAYMvtUnbz82vSfpjgFPBDoO6XhuevrdBNGxHvXgHCj9+CMP4fChg+jQoQPt+7sZsFutMNbWIi4lhbPnnd+BUSCNisKJ77+HLCsLyZ07B1scVgkk2JXuTiY1NZXNW/CJQMuBuJtsHd6ILGS4mP7kbMx7/0MXHT/9ZpFPuyc2vSeZKm4ZaNC1twB7T7+bzeQ9Ewu5UIulMmza9nHYV6FmmvqKChAEAWlWFmfPO7+AUWC/EcegKysLsiTs429mcV/yIqrVaqSlpfksW6AeaVQEWg6k8WSb0iwdkphobHhvDWMyAswWj3T2noxPkEMqjsHG94tDRr5AM9zTCdqmWiT/8+pSr+2zVYU6UtDd2HXJsrL8ft59hTchUpCQkoLo+HjHj3Iz4GtmcV/yIvqa+YE8bP901zdo2ykHecNG+GyW8gQ52f341ReYNukxPDBmJPb/+APtN2ny+vdWvo2YaBGU1VWoMxgxcfJURgN5Pen4wt9ncPbsWdpt5eTkYNP6dYiXSCAEgaqqKkx/5t8B6dXf3Jje2gT8d+LxFGBP/m4H9nyHaZMew+jbh2Dvd9+iV69eHttkMjtKpKK9MVdKs7IYz/RCBb8Do8Bms0Gamen4UXjc4y3gllwQfH3AuXKSCHSynPXMs6ymlQL+0bGyToc6lRJJ6RlYPmc64mQyn/tiQ690xwBX0InZIjOTWG127PxuD8RRQmzduN5z2AjDVagjDVFcHBJbt4Y0MxMGjhZ0XusU2O12SLOyoDp3DhaDAdEcJacMBXzJa+ct4JacNOx2O+3+g1EGxJ9cfmwFCDcmJycH+3/cg9uGj8KrH+2CzWpFlEiE1wsnIUpA37zKll7pjgEuoIzZaqQnfzKTMFmFOhLJHj4c2cOHAwDqOcpixJsQKYiLi0PW4MHImTABhA+TbzhDZlnfsHWbT/nynANuo0SifyaNGLFj5xXnwwsAl2VAAsnl17hEh81qhbqmGhZjPeMLrEgkgs3S4IARJRI5YpEuXjiP/NvvoCWzO73arFbUVpQHrFc6Y8BX/Mk7SFUux1lP/npkNjY73zdqOPZ+9y3vwOEGX573QOB3YBRoNBpkDhyIzIEDgy0KZ/ibL49OoKdGo/FpUHNVBiTQFEFkgPCCh8cgTiqFQadDq+y2GFwwhHHvtLWri3DHyNGQJSVDp1YjLl4CSUIiJr+6grbMpF5tBgOjQc1MBvsGWq6Gjp4C8cgkz9hEcRJs+ng7nxcRDYUsj65Zg6zBg5E5cKDPz7u/8AsYBc6pegiCgEAgCKI07BOoOYwq4JbEl9RHADdlQJhIEUQGCD/3/ja8M7cQi9ZuY+0srEOHDmjXsRNmvdWgV9KM6IvHH6nX3LwCCGJaMXp2520M0CXQxMN09NTUIzMaG99/j7Z8fF5EV7TXruHavn2QtWiBzIEDfX7e/YU3IVJQWVkJgiCw79//xn9ffTXY4rCOP9WZnaEKuCU93CorK/2Si60yIAAz1ZndnSvZrFZWvNOcTYCkGdEfj0S2gpq9jQGuZPOkJ9JU2tgjs7KqmpZHJuVLTwCm0khAdSPxubxtWwDw+3n3FX4HRgGZqoew26E8c+am2IUFmmXdXcBtoHEybBePDDRFkPNkqa6pxvMPDIehXg+ZXA6tshZnz55l3IwYqEci20HNgYwBpmSj43Dh7JG5hKZHJp8X0T3qGwuYol07ANyljrt5Ne6F0tJSZGVlQd62LVTnzsFQWwsJR9viYBFIlnVvcTJXrlxBq1atfJKHCy8/JnL5kZOlvk4DeWoa5q/ZzJoZkfRIzL9zeEAeiaEc1MxEuRpvJuhAPDL5vIhNUZ8/j7iUFMTeqMRMzp9sw5sQKSCjyOU33ig0Fy4EUxzOINPl7Ph6t08BxN4CWunWrmrcZiBmTboEmsuPXFSy27bjpJK0SCQCYbME5JHIdVCzLyZO8kXqiQmPYNzo4fjtwD6/d7FUQc2BeLo650V8YsIjOHzo4E3twGEzm1F39apj9wWAkywcAAAiwtBoNAQAQqPRBNROeXk5QRAEoTp/ntgxahRxautWJsQLeQbemk+s//UY0S33FmL9r8eIHWfKiPW/HiMG5Rd4vfbUqVPEoPwCIve2O4iMVm2ITj16EwNvzSdOnTrl0KevnDp1iujRpy+R1aYt0bFnX6L3gFzi1KlTfrVFBXnP5L2S907nnp0ZlF9AdOmf67Pe/GH//v1EZutsomPvfkRWdnuiXbceRPsevX3qM5DfmgpyDHTq1ZfIbJ1NdB04mOjSP5do162HT+2aTCbipZdeIl566SXCZDL5LU/j37ZL/1yHHKSsfQbdSmS0akN0HzDIMV65ki8SsBgMxLkvvyTK/vtfx2f+Pu8kdOdx3oRIQUJCQsP/tmoFoUjksPFGMoEGunoy2+j1er9kYrt4ZKjnGqSiZ8+eAXkk0nE+8TeomYmgaxJ/AsxJvHmZOo/XFStWwGAw+Fw8la1cneGESCxGuzFjXD4j50+24U2IFBiNRgCAUCTCra+9hj5PPx1cgTiAqQBid2abY8eO+S2Xv2ZNOjCZy48NsxwVVqvVo0ciXZOvs/PJM2OGYvHE+3zOseiu7UCDrv0Nqm8shzsv08YmaJFIBJFI5FM6MTJX55c/7PW7hEykYHdjIifnT9YJaJ8XgjBlQlQqlQxJFF4EYlYhcWe2GXDLrX7LxIapyxlPps9Qk5VEqVR6NNdltWlLDMov8HgP5PVZbdoybvo8depUQCbOgbfmMyLTqVOniG69+xIdevQmMlpnEynpmUSXXn1ddGMymYg33njDJ3MgU2bnSGBPYSFxYMECl88CnT95E2KAOJsRCLsdmkuXIIyORkLLlkGUin0CDSCmMtuIQPhlZmHL1OUMU0HTXMhKEhMT49lcJ6rF4y+/5dEL0vl6IwFGPT0DCbpm0vs0JycH8fHxeHLpcshTUqFVq/DO3MIm2UtsNhttcyWTZudwx6TRoO7KFbQoKHD53B+Trz/wJkQKdDqd4/8b1Wr89PTTOLdzZxAl4hZ/A4ipzDaXL16gbT5q0h5Lpq7GeCrDEWqykuNTJBLBajY2MdfpNBpaFaJJcx/T+RwDCbpm0vuUXGyS0zMcORobLzanT5/G2o2baJsr2SghE67UnDwJAEjt3t3lc+f5k1UC2ueFIEyZEM1ms8u/f5g2jdj9xBMBtRlOBGLCCdR85K49tkxdznjyWAs1WZ3H56lTp4gsCn1ntc72ago9deoU0TGnC9GsRSuideeG/+2ff5tXE6Q3AvFIZNL7dFB+gUdznz9jnUmzczjzv9WriR2jRhHasjKXzxvPn77CmxADpKqqyiUQL6VbN1z67jvUV1UhnqsYhyARqAmHiZx9zrgzddms1obM59GxjJhs6JbhCAVZAdfxmZOTgx+++QpTZswA7HZo1SqfMnSwlc8xEI9EZ+9TAD57BzrjKSuHv2M90OrRkUL1iROIS0lBfHq6y+eN50+2iBgTYlFRQ+bvfv36MdJeY+WndOsGAKg5cYKR9kOZQE04dHLR+SWTxQRVVQUWT7wPS6Y8jCfvugXVylq/TJNuZfZShiNUZAWajs+cnBwc2LsXaSkpWPXdr1i87iMs2bwDirR0x8JJBZv5HD15JOYNvd2rLpw9A/2Vg1xsVv1nGSRxcbALBLheVobxjz2Os2fPBlQSx/k7N1suRLNOh/qyMqR269YkzR5XqaR4EyIF169fd/m3QakkdowaRfz59tsBtRsuOJtwOvToQ/QekEscO3bMp+sH5RcQ/fKGOExT6S1aEZ26dPXbzEKaJtny8mPS9OlO1u0nrxLv7zvCiKyNxydJY3NZl/65tDwSyeva9+jd4MWY3Z7o1LsfLROkNzzp1VP7R48eJTp06UZ06tGbaN6mLZF72x0BmTXdmYhz8xrMfu06dfbLhHr06FGibaccomOvvkTztu2Jnn373VRmRLNeT+hra5t8TjU+6UJ3HucXMAqsVmuTz/bPm0cce//9gNoNJ5iYQAbckueYvP09VyKxWCxE3rARxPaTV4l+Q4cRO86UOf7LGzaCsFgsfrXrrv3tJ68SO86UEf2GDiO2n7xKdOrV16cF3LmtrgMHE+179P5nUWjT1qe23OFufBKE/4swm2d3nvTasXc/Ijcvz+11TIYkWCwWIu/O4S5jpt/QYUTHXn2J3Lw8okefvn71xcS5aSRCNT7pQncejxgTItO4KweQt2wZuk+dGgRpggOZrTtaIsHLW3bi36s3OdyP6UBZpdeLSYsKNisKN26/semzTqXEjKdm+9WWsrICMbGxWLL5M7y67Uss2bLTp7bcQVWugjx/XLp5B97etRdvfLob8pRUr+ZAd/kcG5/d+YsnverUaohimuaLpJMVxmcZ3JiItWoVpry2CrUqjc993cylVQiCwLkvvoDm8mW3f+fLqQQZhUIRbBGCChMxTVSlJ8qqq5B/+x1+VSxmq6Kwc/tTZsyESqdvKFfSLB3vzC1EUnqGz04YDW3NQIJcQbko+LvoUo1P58WC1HnjDB3dG7k8O19rs5igUqqweOJ9EAiFUFaUIyEpye/fi4SyDEy8xHEetm7Nakf77l5WZHKFz1lhnFmzcgVG3DMWMkUStGo1JDIZkpqlQyZXQCaXO3TlUsbFQ183c2kV7fXrOLF+PbJHjEDPGTOa/J2z+TOgfV4IwpQJsaamxu3nJzZuJH7/z38CajtcYOJchGmXehKmMjVQkZvX1PRJ5yzJfVv5RLtuPYgu/XOJrgMHE5mts4lOvfsGdJ5DNT4JwrP7urd7YPuc8dixY0Rm62yiQ6++Xs/DyPvI6dmHSE7PJDJaZxMdevQhuvfpG5BL/fv7jjh+V/IeM1q1IXr27edzBppTp04RvQfkEh17NpwX9whAtnDizKefEjtGjSIqjhxx+3dP45MOvBt9gFC9QelKS1H+++8wT5+OGJmMY6m4hYk6V0y71ANN3fzZcFNft2YN7hg5GrKkZOjUasTFSyBJSGySwYFeW6txx8jRmL9mM96ZW4ilWz937Cb8dVP3llTZ3wwd5O/FVjaRnJwcyvEgTUrGlBkzcGj/fsd3D+77Gbl5BRDEtGKkqCnVTjA+IQGS+Hjs+fYbn7KxONeTAwJz9w8nKg4fhkgsdnhnN4arHSi/gFFAlfE8Y8AAlP33v6j480+0HDKEY6m4hYlUQ95MWv5ULCbd/NkwdZEwufA6LwoEQeD1wknQa7UNVZtVShw/fpzSrEeFt4z8zhk6nM1bjTN0NL4HtitMexoPOrUaaUlJLnIx/bLiLTaNTCJstdmx87s9kESLsHn9Wq/37Esi4HDHpNFAeeYMMnNzERUd7fY7TFaM8AS/gFFgNBohc7PDSu/XDwKBAOWHD0f8AgY4pRoKoMT72tVFmPSv6ajTG1zPP2gE2Xpqs/GuhskqyEwuvI0dOhSpaZjnVMJ+xlOzfZaXanw6s27Natw5cjSkzrtImczrPbBdYdrbeZjzSwgbLyvOsWmNz2bveeBBiKVSLGaxqna4U/HnnyAIAhkDBlB+h874ZALeC5ECqno2sYmJUHTsiMojR2CzWDiWKjisXV0Ekc2CxY+OxYKHxqDo2elYu7qI9vU5OTn46fvdSE1O9jnIlgo6pq5AWbu6COtfmI0XHh6DRRPuBUEQLguvr22tW/CkR4cOX6BTb4nM0JEkjYM0IQF6rRaxcXFe74FNj0Sy/YP7fsYnH6wHAJhNJqhragDAxUxLsnZ1EfRaLeYsL4ZAIMDSrZ/j1W27fPKIbcza1UVYNOFeLHjkbiyeeD9MBj0kCYl4ectOGOr1ft2zc22wSCY+IwMt8vPRrG9fyu9wVQ+M34FRUFNTQxlNnjFgAJRnzqDm5Ek069WLY8m4h4mikmq1mvKt1583aSpTlzQxETqV0qO3HV2YLM6Yk5ODQ/v3Y1B+AapvZOgIZDfhaXw27vfA3r24bfgovPbxVy73UFtbQ2m+ZNMj0Vk2KjOtsk6Hv/76C71793b7sgLQL7TqDk8mYmliIhY9OhbCqCha90zWBhNLZdi4dRvSM7MQIxIyoqNQJCUnByle7ovu+AwUfgdGgSfltygowC2vvIJUigPMSCTQopJZWVmUb73+vkmTOyR9nQYAIE9JQXRsLAgAD06azEiBQSaKMzqzbs1qRnYTvkwOVPegVas8xqOxsfNpLJenuLsx94/D4IIhOHv2LCOFVun2raquwsOzn6d9z2S85IubPsPLW3bCZLczpqNQw1xfD4IgvH6Pq1RS/A6MgtLSUsofQZKSAklKCscSBRfyIX1nbiFedjq/oXs+UFpaymqS34sXL7J2HkaetzHhkciUl5+n8ekOtzFQXmLb2PZIBDzH3VlMJofHJHluFiMQYOH4e5DSLB2SmGhseG9NQH27O4tLUCjwyar/Q5xU6nW3d7PVBvvfypXQXLqEoe++iygP3pa+jk9/iRzNMkxmZqbHvxN2O2pOnoQoLg6K9u05kio4MBHUnJmZCYFAwIpHotVsgEwuZ22iZXLhZcrLz9v4bEz37t3RqmULPP7yW47CjsvnTHcbRMy0rJ5oMK3uQ25ePuau3AmZXOGQzdljskOHDji472ccOXIE9z30MJTVVbAmJWPi5Km0vASp+qYyEWuUtai9UI6SP39Hx559KHd7zrXBGo/pSKsNZq6vR/nhw0jOyfG4eAG+j09/iRztMkxZWZnHNwijWo1fFy5ExsCBGLhgAYeScQ8TExmpT0oPtAA8EtetWYM7R44Oiuu3PwsvE15+3sYnVb/udpJTXluJO0eOxg/ffNXkPtj2SCRZX7yGlsfkrGeehTQphZGYMIDaI1GnVuGVrZ9j/kOjESUSecz24qlcSyRRdvAg7FYrLe9rf8anP/ALGAUpXkyEcUlJSO3RAxV//AGzVssHNXuZQEh9enSMEAr8ju1pqIc1k3vXbz8WXiZqhnkbn+7w6LjQKIiYSVnpQKem2f4f97ASwO4pxZQirRmeXV6M5PQMyrHUuDYY3SDocOPqzz8jKjoaGbm5Xr/rz/j0B96Jg4K6ujqv32lRUAC71YrSgwc5kCi4uHOtBlyDmj3hrE8qpwKb2ej3JNTgbfcjq67f+3/c4zYUoFajxfHjx31qj6pmWFVtDfKGDvXqHEJnfLrr09ekukzIShdPNc1IHdvMRsbrrHXv3h1ZmZmYs7wYb+/ai3lFGyEQCBp29FWVMNTraI2lc+fOYcvH2/HZt9+jY/ee6NWvP2O6CTb66mrUnDyJ9AEDEBMf7/X7/oxPf+AXMApiY2O9ficzNxdRMTG41uitNVJxBDX7UeiysT7Xri7CO09NxvwHR2HhhHtRefUKlDU1AT3wXBS99MebjwpnLz+TwQCJTAadpg4qnQF3jhztUV4645OqT7exbU5BxO76DURWX/Ck4zH3j4PJZIamtpZxz8hVy/8PH7z4LBY/OtZFLzKFAm8UTqI1lqY/ORsL1n2E1z7ahZc3fQaLUBQxnoh1V68iOj4eLQsKaH3f3/HpK7wJMQCiJRJkDBiA67/8gvqqKsSnpQVbJNZZu7oIj0x8DIsfHYv4BDmk4hhsfL/Y53ZycnIQHx+PJ5cud3EqCNTc5y5DR6B5B53xx5uPCmcvP71WC3lKiovpc8qMmTi0f19A8jaGNHcdP34cw+++F2aTCfUajVfPSi5lpdKxxWTCtNdXYenkhxh32OnUqROlaTtBkQyz2eTRu5WytIqfZvFQI71PH4zYvBmCEEuZFd5aZRGz2Uzre63vvBMxMhkEHOX+CjY5OTnYtH4dxo1/FEIQqKqqwvRn/g2BzeIxcLOxPskHPjk9A4DTA08zQNjdd6xWK2XeQWliInRqlSM41l/88eajwtmDTZqY2MT0KbpRV8qdLuiOTyq8BRE3DnAORFZf6d69O1q2aI5JS1xfbkivxDipDCcP/8aow47ZbEZCQoJbhw5VVRUEQiF0GvWN0itNF8ubobSKN89DZwIdn3SJDM2yQDwNOy8ApPXsibSePdkVJsTwJyassT79rRVWUlKCqTMLERUbB4tBj+JVKxwyxUjiYTXqoa+vd+QdlEilkKekQCAUgiAIjJ86DUkyacC1rXz15vPU1tSZhdCpVbBZLbSzXtAdn1R48qwki3c2/i39ldUfPOVx1GnUeP+leSAIO2RyOZZs/ixghx1Sn+5+2/jERMwr2oiF4++BMEpEuViuXV2ER5+YgnqTBTqNCilJCqxdvS5gXQSbo8XFiIqORtdJk2i/qAc6PmkTUNGWEISpemClpaU+fd9qMhG6ysqA+gwHnMvD9xs6jNhxpsxRKj5v2AjCYrG4vc6dPunUCmvcHlmjjKzn1KFLN6JDl24udav6DBxE5OblEZ1u1JxiuraVsw62n7zqKE+//eRVomPvfkRuXp7PbZJ1spxl3X7yKvH+viNuZfV1fLrj1KlTRG5ePtGpdz8is01bouvAwUS33FuIrgMHE7fePozyt3QnKxs12U6dOkUMvDWP6NirbxP5OvbqS7y/7wiRld3eMQZ3nCnzKLcnSH16+23f33fE472aTCZi0aJFxAsvvEDU19cHrINgY1Sric/vuYfYP2+eT9cFOj75emABkp6eTvu7dqsVP0ybBklaGvLfeINFqYKPvzkI3enTk1s3ERWNQfn5iIqJg9VkRPGqFWjfvj1MFivemVsIsSQeRn09hKJoxMbFuZw9xCfKsffrL3HrbUMBgYDx8xJfS4LQgTTp0TV9+jI+PfV5aP8+DMpvGkTsySTqLCtbGTrIfn47sB+5efl4btV6t0HOvuYtpILUp6ffVl1VCZ1GjeT0DMqSQmReRFGcBJs+3o4UhRwfbvogbHMiXv7hB9itVmSPHOnTdUyMTzrwCxgF5eXltAPxhCIRUrt3x9WffoLm8mUktm7NrnBBxjkmLM7ZRIeGHITuTHTu9Olpsrh8/hyS0jMgiY6D3mTG3fc/gEkTxqOstBSvfPiF4/svPjoWEnGMiymSDHwlg2PZCHD2pSQIHRqXXPFm+vRlfHqDqngnlUmUiwwdzngKclZVV+HJ11dge9FbAaUQc9Yn1W8rUyjwf7OnIjkjE+MKn3XrfUt6IpJyMOGYFCwIux2Xdu+GWKFA5sCBPl3L5Pj0SED7vBCEKROir9SeOUPsGDWK+KuoiNN+g4XFYiFuvX1YwCY6smx8p159iczW2UTXgYOJLv1zieT0TJf2stq0JV544QWi+4BBxI4zZY7/cm+7g+jeuw/RpX8u0W/oMKJL/1yiXbcejv5JM1lWm7ZEl/65LuZHf0x9jSHNaR1umCvdmUHp0iAre6ZPKryZzQbe2lRP5O/Gll7d9Zebl0d07NnHZZy069aD6DpgsE/mbDqQ49vZPNlv6LB/TJets4lTp041uSbvzuEu47Pf0GHErXfcFZAswaLs99+JHaNGEae2buW8b7rz+M3hOucHpaWlPn1f0aED5G3b4trPP8Oi17MkVehANwchCZU+HQHCjYJXUzIyIZMrADSYBRMUSQ3ZDWKiXWLQYDVDnpKGJZt3YO6Ktf/UGbvhFecc4CwQCvHO3EIsmfIwFj06FiqtHrl5+QHFMJHmtFe27MTbu/bijU93Q56S6uLN50tbh/bvh1wq8apXX8enJ7wFOKt0egzKd9WTc2B7Y72qdQYMyi9gNIjXU5Cz2WTCtXN/45nRQ/DMmKFYPPE+xy6cLo316VzR2jkejTRdyhRJTQKanR2TADASoB9MSg8ehEAoROthw3y/lsHx6Ynw0ypHpKam+vR9gUCA7JEj8dfKlbiyZw/a3X03S5KFDr7kIPSkT7LqrrMZUKdSupgWJTHRkEgkWF+8GlNnFjZM5EY91q1p+Lcn92UyOFZZUY6lWz/H64WTIJFKodVoAIHAZ8/BxrL76s3nDTqmz3bt2vksqyc8mUS1ahWeW7W+iSmssV7fmVuIpVt2slbJmDJvoUaFV7d9iQUPjcas11cgp+8An/t3Nz49eUJ68tSMFE/EPrNno+2oUX5V3vB1/vQXfgGjQK1WI83HwOQW+fm4+PXXEMXFsSRVaOFLDkJv+iQnUHJhWr3yHbzxwuyGg3KTAZvXr3X0eXDfzy6H53QmjTUrV+DBSZNZCcT1VBLEnwBnKr2STgxTZszAF59+6vP49NbnwX0/46+//sKY+8fBYjJBp9G45AV056DhrFc2HTqc+6PKWyhPa4ZPVv0fFq//yOccie7GJ/k7TJ4+AyCIhvyMzr+tm9i3BseTfXjllVcAAAsXLkSMD/FToYRAKPS70oY/86c/8AsYBf4k4oyKicGQd96BQCBgQaLQhDTReUv26k2f7hamMaNHU05AVJMGVcXo7t27I0kmZSUQ119vPm9tknpV6XR4Z24hCIKAsrICCXIFRo+9HxvfL2bcu613795NArXfmVvoyArf2MuU1CublbGdcRdITsqnu7GgzR6ZD6vFgqRmzZA3dCjWrVnjVU9U45P0hByU39QT0pNpMCrEMlb4gr6mBifWr0fnhx9GQsuWfrXBVSJjAUHQKK8ZRtTV1SExMREajQYJCQl+t6NWqyGXy/2+3qhSITYx8abJ0DG4YAiqlCrExklcgltJz7nMzMyA9OmNY8eOYdz4RyGWyqCsqnRb1p0Mgr5y9RripFJKWf1dFEpKSpp48wmEUZhXtBGLJ9zrl5lycMEQXL5y1WH6JOw2F3Oiv6ZPb/fR2JxI2O0wGfQw6HRo1bIFp3r1RT69ToelW3Zi/kOjAQiQlJZGS0/enveSkhJMnDwVeosFOrUayR7c481mM5YtWwYAmD9/ftjtwI6vXYvzu3Zh0EsvIb1PH7/aCHT+pD2Pc+FRwiVMeSHW1tb6fW3Zf/9LfHHvvcT1X38NSIZwggxKpgrEDUSfdBh4a76Ltx4pgzuvPV+DhunijzefN44dO0Z06t2X2H7yKpGV3b6Jx58/bdLBmxdeYz0x5ZXqC0eOHCGy2rQlOt7w2mzfozfRdeBgh7479x3g6D83L99jW3THp8Vi8epRaDKZiJdeeolYtGgRYTKZwsoD0ajREF/cdx+x96mnCLvd7nc7gT7vfCBzgIjFYr+vTerUCRAI8PennyJz0KCbwqToLQfhmTNnMGjQIFb69rWsu69Bw3TxFuAMgkBuXj7WF3s3aZE0Nn2SHn+EkznR1zZp30sjxxpnLzxlnc5FT1xUxm6MJ3OnTq2GNDERLz72AKYufs2riZju805HfjKYWSyVYePWbW6tAaHKha++gs1kQocHHgho3gpk/vSFm8O+5QeB1LOJTUxE6zvvhPrCBVQdPcqcUCFM40Bcwm6DPCUF0bGxIAgCk2fNxuCCIazUR3JONAvAa1l3b7KOnzrNb1k9lSvRqlWYumyVz+VH1q4uwgcvPgudWgVlRTmefrOooaTJDU9KdT2zJU1I1q1ZjcUT7sWCR+7G4on3w2TQu3jhjbl/nIue1q1ZA62y1uU8zF+3drqQumlcBoXU9zNvrcZr0yd6LanDZP0qMlfoi5s+w8tbdsJktwdc7oULLAYDLnz1FaSZmcgK8GWTq3pgvAmRgkC3/brKSuLzu+8m9s+bF9BWPJwIViAu2feg/AIi97Y7iIxWbYhOPXoTA2/NbxJsSkdWJsyJ3sxb/gT7HjlyhHNzIp18hM56YjtwnApP+u475A7io6MXPf6mTJn5SDNy42BmJoKr2ebaL78QO0aNIi59/33AbQV6n7wJMUAqKysDSoUSn5aGlrfdhst79qDq6FE069WLQelCEzIQNzcvn5UchN76PrjvZxw5cgQPTpgIu0CA62VlGP/Y424P293JSjiZE2VyObQqZZOyInTxZt7yJ19i7969OTcn0slH6Fx+xZP3ZKIiCYPyC3z2yKSDJ31fPfc3Zo8aAkVqKnRqldvfNNDnncTZGtDYjOzOGhBKNL/lFsSlpEDetm3AbTGlT68EtEyGIMFKJeWO+qoq4qennyaqjh8PtiiccurUKSLrhpNE+x69iXbdehBZ2e2JTr37uU3BwySNnTm69M/1uJNyljXTadfAxI6RKk1Wu249iKw2bYlB+QU+68I5hVMmhzom9eSuckBm6+wmehqUX8BJxvrGMlLpO6NVG0eqsZ59+7HSP8mXu3YRzbPbER179SWatWhJtOnclWjepi3x5a5drPYbSfCppAKEiVQoktRUFCxfjtRu3RiQKHwgA0DXLXgK+joNYuMkWLL5MyzZvANLtn6OKTNmsNIvZVXcG/FonmRdO/9JJMgVTeLDPF3rDXJX+MkH6wEAZpMJ6poaAHCpfuxPm+vXrEZCUpIjMLuxjidPZ1bHpJ4U8XGQJiZCr9MhNi6uScA2yZqVKxzyeUszxqSM+3/cg9Tk5CbppmRJyZi7Yi3mLC9GrUrdpH8mUx+98dZyvLx5B6JjY/HaR1/hjU+/xctbduKNt5Yz1geTGJRK7Js7F9UnTzLWJp9KKsg0a9aMkXZITx7VuXNIbNMGwhA2ITBJMExJ/hbJ/CdYtQDVVRUuhRplCgXtYFgqvFU/9sfrcejQ24JmTnQX1Ns4YJvrAGcSKu/Jeo0GQMNLjdRNfBJTz7vVakVUbBxkcgXi4qUuL1Nsmc8D5e9PPoHyzBlY6+sZa5MpfXqD1R2YUqnE+PHjkZCQALlcjsmTJ0On03m8pqCgAAKBwOW/6dOnsymmW2puvCkzwfVff8XPc+bg8p49jLUZDjjnynv6zSIIBAIs3bITr2z7ElNeW8mKV9ba1UVY1NhzjuZuZ92a1dBrtZizvLjBy08mg05TB5UuMC8/T8ly3Xnz0aGmpiaI3olrsGjCvVg08T4XHZPlV8j+SI9MfR25eNzw9ERD2R22vFLdeU/GxUscupdERzdZRJh63kUiESyGht/aqK938YwNxTMwXXk5Ln//PZI7d0Z6//6Mtcvk/OkJVrU5fvx4lJeXY8+ePbBYLJg0aRL+9a9/Ydu2bR6vmzp1KpYsWeL4N1dpSZwJJItHY9L79oVYLseZjz5CyyFDIOIoRiIU4DpXnqcimd76c45lc86XSO40Jk+fgd8O7PdLLk/5Ei0mEx5/+S2fks8mJCQgPT3dkb9w/NRprMjtDk86liYlO/ojTXq3DR+FixcvYv6azQ0JfwOo20WHf3JJzkBacjL02jpYrWaseGqyS15NZ5h83otXrcC48RMgFEXjxUfHokWbbAhsFqxdXcRYH0xRsnUr7DYbujz2GKPxqkzq0xOsLWCnT5/Gd999hz/++AN9+/YFAKxatQojRozA//3f/yEzM5PyWolEwllFTyqMRiNjC6dILEanhx/G0TVrcH7XLnQaN46RdsMBrk1JnoKJvb0BO3uQMW2WI/Ml5uY1zZdIFRzsCefxybV3oq8B21wHOAP/eJk6t+2pHyaf986dO+ORB+6DzWbDwoULIRQKQ27nBQDqCxdw/cABpPfti5QuXRhtm0l9eoQtL5L169cTcrnc5TOLxUJERUURO3fupLwuPz+fSElJIZKTk4kuXboQ8+bNI+rr6ym/bzQaCY1G4/jv2rVrjHghKpXKgK5vjM1iIb6fOpX48v77ifrqakbbDnVOnTpFDLjlViKrTVuiXbceRJf+uUTXgYOJzNbZRKfeff3yxvPW36D8AqJf3hCiWYtWROvOXYj0Fq2ITl26eu2HbS8/b958dL0TG49Prr0TPXn8ZbZp21CE9EZ/wfRKpQuTzzuZSuqll14iTCYTY+0yzaXvvye+GDuWUF28yHjbgeoz6F6IFRUVTdLpi0QiJCUloaKigvK6Rx55BFu3bsXPP/+M+fPnY8uWLZgwYQLl95ctW4bExETHfy1atADQ8AZQVlYGu93u8IgpLS2F2WxGVVUVdDod1Go1lEolDAYDKioqXAoFKpVKWCwWVFRUQK/XQ6lUQqVSob6+HpWVlbBYLC7t2mw2lJWVwWAwoLa2FhqNBlqtFtXV1TCZTCivrES3qVNhy8zEiY0bUVpaCpPJhOrqatTV1aGurg41NTUwGAy05dbr9U3kLi0thdVqbSK3TqdzK7fdbvcod2lpKQiCcPlfUm6tVguNRoPa2lpKuS0WC5KTk7Hzk4/ROjsbhno95iwvbjgP2/o5lmzeicdffguTpk5rIrdarYZOp0NVVRXMZjOl3DU1NQ4dVldXo23bttj+4VYI7Ta89tEu/OfT3Xj1o12Iipdh0r+muZXbZrOhtLQUOTk52P7hVuz8eBsSFNRefo9NmdpE3waDwavcnTp1wtaNGyCXiN1680nlCoc+yGtMJhOqqqpc5LbZbCgvLw9IbrINZ7m1Wq1HfRuNRtTU1KB58+bYvetLFP3fGxAIBLDc8LAUCKMc5U2kScl4fOq/0KJFC3z20Yd47/lZbr1SH5/yL1gsFlRWVqK+vh4qlcrrs0bK7Txmq6qqHGOW/C5BECgrK3P7rDnPEUql0uc5ghzf7uYImUwGoVCI8vJy2nNEY7nZniPE3bsjr6gI9sRExucIgiB8miMqKyuh0+mgUqkcctPC15Xx+eefJwB4/O/06dPEq6++SnTo0KHJ9ampqcTq1atp97d3714CAHH+/Hm3f2drB1ZRURHQ9VSc2rqVUF+6xErboUxFRUVD5ove/YjtJ68SXQcOJtr36P3Pm3ibtsSxY8cY64+qvHvHXn2J3Lw8Wm/9g/ILiPf3HSE69urrkoEis01bolOvvsTAW+m1Q8XAW/NcMlV06Z9LZGW3J7afvEp06tWXOHLkCOW1nsYn23JT9UfeBxn3lZXdnujo1B+Z8JcLmXyFyec91HdgZr2eMHuwajFBoPpkLRPHs88+i8cff9zjd7Kzs5Geno6qqiqXz61WK5RKpU/nWwMGDAAAnD9/Hm3dRIjHxsYiNjaWdnt0SUpKYrxNAMgZP56VdkOdpKQklwrOysoKKFLTMK9oo+McxZ/qxVRQudRTVRd2B1lkU6dWgSAIxqs5k5WXqSr+jrl/XJPSJSSexifbclP156maM9kfW5WxA4Wt5z0UOb11K67/8gvy3ngD0owMVvrgSp8+L2Cpqam0ykXn5uZCrVbjyJEj6HOjpsxPP/0Eu93uWJTocPRGMtwMlhRNRVVVFWupUAiCQOnBg7AaDGh9xx2s9BFqVFVVuVS4dQ4aBm7EycTGMXqg76l6Lx3nAecqxVRefoFUc/ZW8deTd6Kn8cm23J76o6rmTHonvvfuKtYqYwcCm897KKG5fBkXvv4aivbtEc+ioxxX+mTNNaZz58646667MHXqVBQXF8NisWDWrFl46KGHHB6IpaWlGDp0KDZv3oz+/fvjwoUL2LZtG0aMGIHk5GQcP34czzzzDPLy8lgJevQEm8q3W6049cEHMGk0aNanD+Jugrc/Up/OQcN12jqoa6odE6rVZGDUW8tT9V4yOzqdt313Xn5MlWChm2uwcft0xiebclP15yn/IwgC02Y9CbFQwEpl7EC4GRYvgiBwrLgYIAj0mD6d1TJPXOmT1YrMSqUSs2bNwldffQWhUIj77rsPK1euhFQqBQBcvnwZbdq0wc8//4yCggJcu3YNEyZMwMmTJ1FfX48WLVrg3nvvxcKFC2nHFTBVkbm0tJTVH6H88GH8tnQpmuflof/cuaz1Eyo01mdJSQnGPjAONUoVYsRiyBIVEIsE+GjzJkZNSJ6q96Yq5LTf9p2rDhMEAYlM5lJ5WKZQIEkW73fGjpKSkibmRLKa86IJ90IgEDjMiR06dKCdLJVtuan681QteeH4e5CWmoyaWlWTCs5My0MXJp/3UK3IfHXfPvz51ltoM3w4es2cyWpfgeqT7jzO6gIWDJhawOx2O4RCdlNFHlqyBBV//IHcxYuR0a8fq30FG3f6zM0rgNZkxpzlxQ4T0voXmDsHI7Farbht+Cg8/e5G2KxWR+BtnbIWSTKJT5PlX3/9hUem/As6TR2WbP4MrxdOAmG3wVCvb8hgT6N8PRUlJSWYPH0GVDq9w5woEAhAEAQsJhOeffs9vPT4A2jXsRMsBj3WraFfIJFNuan6G3P/OEjlCoc5MTYuDovXfYRFE++DVlmLjPRmuHr1Gl7f/g3r8niDyec9FBcwU10dfryRg/SO4mLEyGSs9heoPunO46EXXRciVFRUeAy2ZoKeM2di76xZ+N+77yK5qAgxN3amkUhjfVqtVkSL4yCJEbN6Dgb8k9IqEIcOkgazXDwEAiHjmS/omBNlScmY9VZxQ3HMEJGbqj9P5kSZIgnTXn8XSyc/xFkGEU9w8bwHkxipFB3HjUNcairrixfAnT75BYwChULBeh+SlBR0nzIFx957D+oLF5DWowfrfQaLxvoUiUSwmY3QG1wXFqbPwUg8OXQ417OiA+lNyVbmC0/eiTq1GgB8ztxBR26mkyx78k4kF+Q4qQzHD/3CiTye4OJ5DyYCoRDt7r6bs/640idfToUC2oF0AdJy6FDc8d57Eb14Ae71uXZ1EUQ2CxY/OhYLHhqDomens5YvjnTomLO8GG/v2ot5RRshEAgcLusznppNuy3Se3Dj4jmsJNIl20+SxkGakHAjIDnOMfmTSWl9TQRMJTdbSZady8kI0KicDLkga9RY98pCqGuqUXn1CmdJnxvD1fPONSaNBkfeeQeGG4HaXMGVPvkFjAKuvKAEAoHDC1FfUwOzl2z94Yo7febk5ODwoYN4YsIjuH/kMPx2YB86dOjAmgxrVxdh4+I5WDzxPix6dCwIgqCsZ+UNMrfhrs+2s1KXi8zlt33TBrRu1RIKqRTq6ioIhFF4vXBSk8wddCd5d3KzXa+re/fuNxZkidvsI4nJyVi6ZSdEMTGc1g9zhunn3WazwWazMdqmPxxdswZX9u5FLQtZ/z3B1fzJmxApYNuBozG68nL8/PTTyMzNRZ+nn+a0by6g0ufp06fxyc4vIBRFY9O2j10ydzNtNiIn70H5TRPqNq5nRRe2E+l2794dB/f9DKvViryht2PKaysDTgTsLDdXSZZpne8lynHy8G9u5Tl79iw6dOjA2sTI1PNeUlKCRyY+hhqlClK5At/88CO2bFgXlODs67/+itKDB5E1eDCa33ILp31zNX/yXogUVFdX0wrYZgqCIHDo5ZdReeQIchctQgaDtXlCASp95uYVYOqylXhnbiGefrOIVW9EkpKSEtwxcjRkblzWF0+412fvt8au6mSWCaa96nxxtafTj7Pcjd3ZE5KSkCSTMv4i4e0e7HYCBGFHrFgMmSIJElkCVFUV0Gu1aNexE6xGPSsvN0w974MLhkBjMLHuWesNo1qNvYUNu/LbV69GbGIip/0Hqk+68zhvQqSAq3o2JAKBAL1mzUJ0fHyDzbq2ltP+2cadPq1WK2Ik8S5mI8C1ei0bkPWslm7egbd37cUbn+5u2AHcyBgxZcYMn82JB/f9zJo50bmfH775Cor4OI+JgH0xJ+7/cQ+y27ajTLLM9PmTt3sgzYkmoxFzlhdjXtFGxMZJsHTr55i9Yh2twqT+wMTzbrVaIYyOpcwwwxUEQeDPt96Cqa4OPWbM4HzxAribP/kFjAKuKoo6I0lJQZ+nn4ZZq8Uf//d/sIeADZ0p3OnTua4Ul9VrPVVI1qnVUNbV47YRo32uGExlTlwy5WEsenQs1Do9cvPyA6pCTJriZOIYLN2yE4vXfYSn3ywCYbc3MSfSQSQSudTrIggCrxdOwjNjhuKtZ6bhytVrtNvy9R4UUgnlPZAvFDartemCwMLLDRPPe0P+TSP0NzLMAGDVs5YKq9EIgVCI1sOGcW46JImIiszhTLBiQjIHDkTb0aNx4auvUPbbb0EbgExDpU/S1TpGIMDC8fcgNT0DkphorC9ezao83hLQvvbxV35VDOYqke4Ha9/HsFFj/EoE3JjGSZYlUinkKSkQCIUgCALjp05jxZzoKVxAVV2Fv48eQU7fAY4FwRFqwcLLDRPPe0lJCVS1NahRqrBwwr2QJcohFgnx0eZNDEhIn+i4OAx66SXYOdz1NYar+ZM/A6OA7VRSnrBZLKg4fBiZgwaxmq+MS7zpU6/X480334TFYsGCBQu4qeYKzxkjokQirHhqMvZ+s8vnCZNMpLtk8048M2Yo5CkpmLO82OG8sHb+kwEF6ZaWlkKj0XjN3PHBi89i/497vMpPZgFR6/TQajRYsvkzx7kkmavygxefZfwsp6SkBFNmzICyrmEH7Jx6yqjTIbt9B2hqq6Gr10OmSIJYFIX1xczHhTHxvDuff7GpMyrMWi2u//or2tx1V9DnDa5SSfE7MAqCGZUfFR2NrMGDAQB2mw1WoxEx8fFBk4cJvOnz3Llz2Lj1Q1htduz8bg8k0SJsXr+Wde8tdxkjls+Z7jAtXjh3NiS9EzMzM5GVlUUrEfBtw0fBajZ6vAdnL0EIBC7mRLaS/5L9Hti7F7cNH4XXPv7KNdWXqBZmQz02rV+HL774AjabDQsXLmQlNVOgz7vj/EsU6zB3JqdnsJJZxh0EQeDIihUo//13SNLSkH6jAkiw4Gr+5M/AKCgrKwu2CLCZzfhl/nwcfuMNhPtG2Zs+pz85G9KkFCzZshOvfPgFZv7fGk4CWIEGs98HLz6Ld5+djkUT7oXJoMfrhZOwfM50SBISMeW1lX4FJZPtshHs7KzP9cVrsHjCvVg08T4snng/TAa9iznx6Xc30r6H9cVroFXWOsyJhN0GeUoKomNjHeZEX88GveGc6ot8cSBTfU1dtgrTn2wIMo+KimKsz8YE8ryXlJQg//Y7cOnC+aCdf1346iuU//47WhQUoBmDLxj+wtX8ye/AKEhJSQm2CIiKiYGseXNc3rMHf3/yCTo99FCwRfIbT/psnBeRLK1BBhezPQGQXoRGoxHD7rkPs1esc9kJONez8sXsR6cul1atwpQZM3Fg748+3aezPr3VFSP1SeceGtds02o0mL9mM96ZW4ilWz93mMZ8PRv0hqdUX9FxEthsNlYXsECe96kzCzH51RV4vXASTAY9Fk+8H1K5HLoboRNsU3v6NE5u3AhpZiZ6zpwZdPMhwN38yS9gFNTV1XEaB0ZF92nToL5wASUffoiEVq2QmZsbbJH8wpM+ybyIKqUKiyfe5xKLlH/7HazE/bhDLBbDatS7OAw4eyeCIPwy+1GZE8WS+IbdRp0Gtw0fBZvFhDUrV9AKIG6sz3/qrDU1J5K7GvIeBuXno3jVKsp+gmFO9Fi77ezf6N4+m9Xn0d/n3Wq1Iio2DjK5AvKUVMwraqh4AADvPjud1cwyQEP2nt9few2CqCj0nzcP0XFxrPZHF87mTyLC0Gg0BABCo9EE1E5dXR1DEgVOfVUV8fX48cSX999PqC9dCrY4fuFNn6dOnSIyW2cT6389RnTLvYVY/+sxYseZMmL9r8eIQfkFHEnZIMeg/AKiU6++RGbrbKLrwMFEl/65RLtuPYjMNm2J9b8eI7JaZxOnTp3yq92sNm0d97njTBnRrlsPokv/XKLrwMFEZutsolPvvsSg/AKv7VPpk+wnb9gIIqt1NtGuWw+i39BhTe+hTVuv/Zw6dYrIuiFrZpu2fstKF0+6T2/ZiigsLCRMJhMjfTXG3+c92OO29swZ4uvx44nrBw+y3pcvBDp/0p3H+QWMArVazZBEzFB96hTx+T33EL8sWhRsUfzCmz4tFguRN2wEsf3kVaLf0GHEjjNlxPaTV4ntJ68SecNGEBaLhSNJGzhy5AiR1aYt0bFXXyIruz3RvkdvouvAwcT2k1eJjr37EQNvzfO73U69+zruLyu7vcvkt/3kVeL9fUe8Tn509Hns2DHKe+jUux/x/r4jRG5evsd2Tp06RQy8NY/odKMNf2T1BYvFQtx6+z+//44zZUS/ocOIDr36Eu1zurK2gPn7vA/KL2i6sPdidmH3hrm+npN+fCHQ+ZPuPM6bECngMnKeDik5ORi4cCGSOnYMtih+4U2fzsHFXOTm84a3elZMmBNlckWTAGK6Jjo6+vRkltOq1ZCnpEJ1I7ia6j64Nic2BFYbm9Ruq9doEJ+QgLyhd2DDe8xXa/bneSc9DxVp6Q7TYZRIhHdmTcJPu79m9ez24rffIqlTJ8izsxHNUciJL3A1f/ILGAVcxSH5grNrrObKFSS2ahVEaXyDjj7JIGB9nQZxzsG0AB6cNJmVYFo68lAFOz+3ar1fQclkuyKxxMXjz5cAYrrjk+oenL0U567c6fU+yKBjLoKd161Z3STAuaGGmBrPv7uBcQcSwPfn3TmPpDw1zWXBtVlMrC5e5b//jmPFxVB06ID8N98MCaeNxnA2fwa0zwtBmDIhlpaWMiQR81z75Rdi5+jRxIVvvgm2KLShq0/ShMSFuYou3syJuXl5fpk4LRYLcerUKSI3z3cTna/j89ixY0RuXj7RsVdfIrNNW6LrwMFEt9xbfLoPLs2Jx44dIzJbZ7vVORsmZV/1OSi/gFj/6zGifY/eRLtuPYis7PZEx979/Dof9QX1pUvEl/ffT3z9yCOErrKStX4CJdD5kzchBkh6enqwRaAkrUcPxKen41hxMcRJScgcODDYInmFrj6pcvPptdqGrO4qpU/Vk5nAqznRbqcVLNwYkUjkqPvlq4nO1/HZvXt3RykZZy9Fd/dB5Q3JpTmxe/fuaN2qpVuds5FKyhd9kp6HEqkMiUnJmL9mEyeeh/VVVTj44ouwW63IffFFxKelsdIPE3A2fwa0TIYgTO3Arl+/zpBE7KAtKyO+Hj+e+OLee4mqEyeCLY5XfNFnY++3Lv1zg+aV6CwTpXdi62yHbP6+gfvq8efv+KR9Hx68FLnyTiRlzb3tDqJ5djui7+A81pwjfB2fzbJaEFnZ7YgOPfoQHXv1JVZ8s5/VsWnS6Ygfpk0jdo4eTVw7cICVPpgk0PmT90IMcAELB1QXLhBfPvAAsevBB8PWvZ4KZ3OVs1fijjNlxK23D+PcK5HEkzlxx5mygDwUuTTRebsP0ktxUH6BW11zKSvZf7B+88YMyi9o8lLVPLsdq56HdrudOLZ2LXF+1y5W2g81eBNigAQzmS9d5NnZyF24EIeWLEHd1atIbN062CJR4qs+/wnMLUB1VYVLgLNMoXAEOLNZpdcd3nInBuKhSNdEd/z4cSQmJqJVAE483u6D9FIkcynaLCYXfXNpTiR/XzZ/Z7rj013OQ3lKKtq0a4+f/Ej67A271QpBVBQEAgG6T5nCaNtswtX8yS9gFKSFsH3ZmdTu3XHX+vVBKVrnC/7qc92a1bhj5GjMX7MZrxdOgiKtGSSyBFRVVeCOkaNZrdJLhbMX4YW/zyBOJrsxcdcF7KEIUHv8SWQJsFktGH73vWjboSNsJkNA9+3pPpy9FF/9aBfUNdVu9c2ldyKb0BmfHj0PWch5SBAE/lq5EnarFX3nzIGQwxe1QOFs/uRgN8gpTJkQKyoqGJKIO4xqNXFk1SrCYjAEW5Qm+KtP5wBn0lS140yZw4QTTO9Eb8HCgXgoujPRNb7v9b8eI3Lz/DNXNr6PBm9Iai9F0jxK9kvqm7zWkzmR/H6omADdQWd8cul5aLfbiePr1xM7Ro0iDr78MmGzWhltn20CnT95E2KAxIdh+ZJr+/bh8vffQ1daikEvvgiRWBxskRz4q08ywLkh8FfuSPYrEApZL/VBRzZPwcKNPft8MXk2NtE53zeTZVnI+2jwhmzqpdjEPIoGk5mFEGDgrfmIlcTDajJgffEaPDFtuos50V2+R6vZgHVrmA9EDhRv45PrnIent23Duc8/R3Lnzuj//PMQspjImA24mj/5BYwCi8USbBF8pu2YMdBXV+P8l1/it6VLkbt4MUSxscEWC0Bg+iRNXVqV0mG2UVaUQyKThYS5im51Z39MnqSJzvm+2aryDDRUZ/ZkHiUXs6uXLuK1j3Y5TGh3jByNVtltobpyFX8fPQJlZQWWbtkJeUoqnn9gOOKkUly8eBEyuZwxWZnE2/g8e/YsLpz9G1q1CkZ9PasVos98/DHOfPwxFO3bI/fFF0PmGfYFruZPfgGjgAjD+lsCgQDdJk8GYbPhwtdf47+vvILcRYsQxUIBQF8JRJ9kWZLjx49jxlOzERUdC5lCAZ2mjpNSH3TlI6s7W0wmR3Vn53ImsqRkzHqruKHOlZOMnkrGkOVNpsyYCVGMGAlJSYyWZaG6F6vVirNnz2LqzEJECYCy6ipIEhLxeuEkGPX1iJNKIZMrAMBxb8+sXA+tWoUXHx2LREWSY9doqNc7ZCUn/SkzZuLQ/n1+y8k03sbnlBkzIZHJsHzOdAiEQiyacC8SFElISmh4YWIKs1aLi7t3Q962LQYvWRK2hWy5mj/5BYwCcQiZ33xBIBCg+7/+BcJux8Vvv0XJ1q3o9sQTwRaLEX12797dMbnmDR0KgUDo0VMvJycn9DwU0TDhE1HROHLkCGY98yxi4iSw3nDIcGdiJM17VqsV+bffQassS6AemqRZkdR3/u13YPKrKxyL5QsPj4FWrXIsSM73JlUkoU5Zi5I/f0e7rj0gTUyERJbgUutNFCPmpNYbXajGZ0lJCSZPnwGVTs9JzsMYmQx5y5YhRiZDjFTKWLtcw9X8GRqjJwSpq6sLyXyIdBAIBOgxfTriMzLQ+s47gy0OAGb1KRKJsG6Nd0+9UPRQJBezyxfO48EJE7Fg3UcuZjhPMotEIkf7OrUKBEFg6dbPHWY6eWoajASgUqoY9dB07lcklsBq1EOeILuRUzGhyb3VqZRYuvVzLHhoNJLTM6CuqYZBpw1qrTdvuBufJSUluHPkaCzZ+jkWPToWouhoVnIeEgSBvz/9FClduyIlJwfSzMyA2ww2nM2fAbmKhCBMeSGGsseUP1w/eJAw6XRB658NfXLpqecrpHfeoPyChtyObdoS7Xv0JvoNHUZ0y72F6NSjN9GhZx9ix5kyx3+Nvfw86ezw4cNuy7Kwff+kTJ7uzdkLk5ShWYtWxPv7jgS11psn3Ok6Ny+P6HTjHroOHEy079GbyMpuT3Tq3Y/IatOWOHbsWMD92u124uTmzcSOUaOIA/PnE3a7PeA2Q4FAn3feCzFAKisrQz6QmS61Z87g92XLIM/OxqCXXoJYoeBcBjb0yaWnnq94M8Gtnf8UrpeVubzRO5vhGgcQ5+TkuJjcMjMzm5Rl8XT/g/ILsG7N6oADv8lrPd2bixfmjftJTErGey89D2VlJXQatcObTySWhIQpsfH4tFqtiIqJg1ZdDq1aBYFAgHlFGx3nrB+8+GzA+TjtNhuOFRfj0nffQdGhAwa88EJIZpb3B67mTwFBhKG3ggfq6uqQmJgIjUaDhISEYIsTEhA3TBQlW7YgvlkzDF6yJCLMFCTOph55SiqevOsWh6ceYbfBUK9vSASsrA2a9xsZBEua4NauLsL4xx6HRShymOFMBj3e+HQ31DXVWDThXqz67leoa6rxzlOTER8fjxhJvItJ0LnNC3+fcXv/MbGxkMgSoKqqgF6rZcWsSsrh7IVJ2O2U97Nw/D1o3q4D9No6RNut+N8fhxmRgymcA5bjpFLExkn+MX06OW4Eoj+b2Yw/3nwTZf/9L9J69cLABQtCKuwl2NCdx/kdGAXhkEqKLgKBAJ3GjYNYocD/Vq3C/ueew6AXX4SifXvOZGBTn1x76vkrI7ljIfv+cNMHlF5+zt6LJpsdTy5d7jhPmjqzENs2feDeYzA61uX+5xVthDwlFYsn3tdIDzNwaP9+Ru/N2Uv04oXzlPeTkJyCuSvWQqtWYfW/ZzAiQ6A4j8+pMwsx+dUVjhcgdU0N4hMTIQDwyQfrGamEcP3AAZT9979okZ+PPk8/HVZZNujAp5IKMs2aNQu2CIzT+o47EJuQgMP/+Q8Ovvgi7ly7ljM3Xbb16Y+nnruSIWzjvHB6MsO55CXUqF3y7inrdJgwZRrsTt6GjdtyF/jNllmRxNlL1NP9OJsW4xPlIWFCJMfnX3/9BWWdjjJgmalda8uhQyGSSJCZmxsxZkNnuJo/I2YBKyoqQlFREWw2GyPt1dTUhHRNMH/JGDAAt7zyCgy1tZzGmHClTzqeeiqdDsqK8qBUefYmszvvRYvR6OKy7i0/IVXgN2lWVKSmQSJLQDVL+SS93Y+zxyIbtb384dChQ5i/+EVcuXoNBEGwErCsLS3F+S++QI9p0yAUiZA1aBCDdxBacPW882dgFOj1+rB1o/cFQ20tSn/9FW3HjGH1TTAY+vzrr78wfuo0vLptF2xWK54ZMxRLNn+Gd+YW4uk3ixy7g/UvzMb+H/eExETqYg6MEcNqMqBOWw+hWAyxJB5GfT0IgsDidR8hSiTCgkfuxtLNOxz34RwcXVJS4jDpVStrsWTzTocOSLPinOXFrOqh8f3otXWwWS1ISE7lPMTBE7l5BXhi6XK89cw0RMfGQiAQ/LNbVSRBIZX4VKy0MdXHj+P311+Hpb4et772GlK6dGH4DkKLQJ93/gwsQIxG402xgJ3avBlXf/oJyr//Ru/Zs1lLWxMMffbu3buJp56nPH1MBAAHSmPvRZFIhMEFQ2iZ46iCo7OzszH0ruGUZkUqPZCTdSAmPnf3E2ibTPPXX39BrauHPCUVOo0G8pQUPOO0sK+d/6TfWUMIgsCl3btx7L33EBUbi9zFiyN+8QK4e95DYwSFIEKhMNgicELPGTNgNRhw/ZdfoCsrw8CFCyFJSWG8n2Dp09mUpVXWOgKfnfP0sRUAHCjkBM9EcLTJZMbqf093a1ZsrAe9wYRHJj6GTevXYfqTs5t4PwZ6P43/f7Bw9jYkzYYSmQwmgx6LJ94PqVwO3Q3PVX+wW6049t57uPTdd5BmZGDgokVIaNGC4bsITbh63nkTIgU6nQ7SME7l4gsEQeDMRx/h9EcfQSyXY8ALLyC5UydG+wi2PklT1pQZM6DWGfDKti9dzIpcmdQCwdkcJxDF4PLFC5AkJEKekgqjvh4WvR52gQDLPv5nwm1sYly1/C08OedZh1mxsXmVXPgWPzoW8RIJnn9va8jqIxBIR5PHX37LrdlQJldAIZUEFDto1mrx09NPQ5qZif7PPYcYmYzhuwhdAn3eeRNigOj1+ptmARMIBOj8yCNIaNUKf779Ns5/+SXjC1iw9flPyZCGKs+eAoA9mdSCafpyNseVlZXhgUfG+xwc/fTzCwAA7771H8x4anYT8yr53fgEOYQIr5IodCgpKcGUGTMRFSOGsk7n0Wz42wH/wgzM9fWIiY9vyGv4+usQJyWFXTmUQOHqeecXMArkcnmwReCcrMGDIc3KguSGCyxht8NusyEqOjrgtkNJn+vWrHYxK9IxqY19YBwUySmMmdMCJSUlpUl+wvXFqzH+scc95igkvRcn/Ws6Nry3BtOffAoWmx2q6ir858nJMBkNGFf4LKTiGFRVVeHlG3Fk4VASxRvuAt6ZNhteO3AAR1evxoD585HWowckqakM30V4wNXzzi9gFFRXV0dMILMvJLZu7fj/Zz7+GOWHD6P/889DmpERULuhpE9PAcDOJUCcy38seHgMnnt/m+MN3VPJFi52adXV1QEFR9ebLNixYwfuGjoE2z7d4VLb68WJ9+Gbz3dg+jP/dlsSxTkoPJRKonhj8vQZkCUlO+4pKT0D78wtRGxc3D9mw/g47Nzi+8JsNZlw/L33cHnPHogVipAoYRRMuHre+QWMglCZbION5uJF/DR7NnrNmoUWeXl+txOK+nSXr7CxaREAZHIF4qRShznNqK9HjEAAvd41Luj06dOY/uRsRIvjYDMb3e7SmFrcnPXpT3C0TqMCANhsNoilMpdA6Rat26Bdu3YgLGaHPhoHhRv19YgVCELKm9AdzmefKp0eOo3GseMm7HYXs+G6BU/6lZ2k7urV/2/v3MOautL9/839AoQQLgkgpSAKXihSLxTtiI60tHh6tKdHW2u9dKyOnnaOPPVpa8+xdezUpx1r+0x1nHFOa0V7md5G285o9WdRj1ot3qBQUDsoigYSiBhIIPes3x+QfYgQDLBzZX2ehz+ys/bOu7+8e797vXutd6H8zTdhuH4dCbm5mLxmDUTR0T44m9DBX9c7HcThgXAqJTUUmn/8EWc3b4ZZr8fdRUW4Z/nyQQ21DwU9PdUWdPXAevZS1i2ci18/vcRt/50ffYxIRRyTvuM7bDh98nsA3gU3F94EBW/0vP18JFFRiElQ9bJtZNZYbOgeldnz3FpaWnDo6DFIZdHQqK+Dy+UxKVZXT+365X96K69fcGnnOneeSILLP1/C77qXRJF21zZ01Yc0GQwYmZkFs6EdO9/7y4B7XlaDAQeWLYPDYsHYRYsw+rHHwrKyxkAZ6vVOB3EMkcQhpszChYScHPxy61acffttXD14ECadDtN++9sBHycU9OwrtcgXSWAzdyA1faRbLyVelQiHwwFe98t5h8MBu8OJ59/Z7jaS7/XXXwePx/u/4CYUM8PUXQHEhSvIefOezRs9+0yVcjkQSER470/vQygUwm63Q5WU7NazipbHwOFwID4+Hk/OewwOhwM6nQ5lp0736qkFSw+sZ8CymTrR0dGBki07ECWPwauLH0OUPAYKpQoWkwl6nQ52mw0moxH7v96LsWPHgsvlDmrotzAqCuOXLkV0Whpix4zxwZmFJv663gPveUGKRqNBUhhVbB8KYrkc0157DT9/+SXixo9nthNCvH7aDCU9PU0m7jm6TyoUYN26dcw+drsdX+4/6HaDj4zuGtV3p+Dm4pMv/uY2bN3Teza73Y7m5mav9fQ0mdj1nZDPxaqNW91GM/Y8NxcFhQ+6acBx2IIieNntdqYArzwuHjc1Tdi8ejnzrsug199xSZTGxkav9dTV1uLCxx8jb+1aCKOikF5c7MvTC0n8db0H3vuClJgArJkVzHA4HGTOm8d81tXU4MInn+De3/wGEV7UPAtVPfuaTOwa8Sfs8aJeKBRCKuC73eAjRF1Brr/g5sLhcIDLF/T7nq1nGtJmNmHH9oGXNuor4Hg6t9uD3Y7tf8Izq1aBL5IyaVB/4KmX5+p1cQUiZkg80KWvoU3P/C8kEVK88/xKcLhcvPLUo25Lorjwxj/tFgtqP/wQl7/5BlyBADcvXkTi5MnsnWgY4a/rnQYwD3R0dEAikQTajKBFV1ODlqoqlP3mNxi3dCnSi4v77Y2Fup6eejA92b3jPSbtaLeY8OEHXWm6/oJbT3Z+9AkzbN31Luqtt97q8X2PNKTF2mcacjBkZGTgyP87yJzbhQsXkD99hlsqEwAWLlkK3a2uxSilAt/fOm5PC27f+i7G9EjTLfrVM3j27e3MkHiXvgb9LdjMZmY6AQDom7VIHzUaMpGgz1UI7uSfutpanH/3XRgbG6HIysLEkhJEBfk73UDir+udBjAPCIf5MNg7kTV/PmKzsnDu3Xfx4/btaPz+e9z7n//psTcWLnr2lzLrL8h5Cm4u7HY7UtLSPb5n8zYNyQZ9pTIBwMblY8OuL72aSsAGPdOCel0L5i98Ck/OewxAV4+1w2rrNSTe1XtVJiZBJhaCz+UgQRGD9z79pN8al/35Z0tVFU6sWweuQIDsZcuQ8a//Cs4wKTU3WPx1vdMARhk08ffcg1l//CNqSktxZf9+HC4pQdH770M4TCqYeKKvm+SdenB8Ph8ch83jezZv0pBs0FcqUwBAIBT2Gkbf11QCtrDb7SBcvtv5iiOj3AbOGPW3PA6Jd1XmH8ogE6fDAS6Ph7jx45FWXIyRjzxCe11BBg1gHrBYLIE2ISQQSCSYsGoVkqZORfvVq0zwsplMEPRIIVA9u+jvZtrfezZv05Bs0FcqE+h6D9pzGP3tKU62uXrlstv5tjZr3c73m/3fMmlCi6kTrz71KEb2KMQMeF80uKd/mvV6/LRzJ+ydnbjvv/8bHC4XE1auZPfkwhx/Xe80gHlgKHPIhiMJOTlIyMkBANg6O/Hdf/wHlJMmYdzixRDJZFRPL7hTL61nGtJq6uyVhmSDvlKZcUoVrGYzwOP1O5WATRwOB6LlMW49PlVSMrhcLqPNJ7t3MVMDvEkT9odMJoPT4UD9/v2o/egj2Do7kZCbC4fVOuyragwGf13vNIB5QKfTBf3E22DF1tmJyORkXD14EI0nT2LsokUQZWcjecSIQJsWEni6AfcMcFqt1if+2VcqM0IkRIRICIPF2u9UArY5dPQYlr+xxS0t6KnqyFDTmPWVlVB/9BHarl6FND4e965ejaT8fDopeZD46/5JK3F4YCBznCi9IYRAfeIEqt5/H+bWVsgzMjBh5UooMjMDbVpY4Ev/7FnB4/ZRiDdv6REpl0MqEGD3jvd8Wsy3Lzt89Xvfb9iAlspKjPq3f0Pm/Pk+W9h1uDBU//T2Pk4DmAdCofRRKGAzmXDx009xuaoK46ZPx6hHHw20SWGBP/yzr56N3W4H4N8FKX1R7cNmMqHhu++QPns2OFwuLtfWQimXIzJEJtsHO/4qJUUDGMUvGNRqRCiV4PL56NTp8POXXyLr8cchDtEJzpTQxGGz4eqBA7j42WewtLVhyksvYcT99wfaLMpteHsfp5MZPKBWqwNtQljRDoDb/RTdcPgwruzbh4PLl6Pmww9h7egIrHEhCPXPgUGcTjQcOYJDK1fix//5H3B4POQ+9xyS8vMBUD3Zxl960h6YBywWC0Q0D84aPfUkhEBz+jR+2rULhuvXIYyKQua8eUifPZuO+PIS6p8D4+Lnn6P2ww8hiIjo8rV/+Re391xUT3YZqp60Gv0QaW9vR/wwXU3VF/TUk8PhIDEvD6rJk9Fw5AhqP/oI1R98gKiUFKgmTQqwpaEB9c/+IU4n1CdPIiE3F8KICKQVFcFhsWDUo4/2OdGe6sku/tKTBjAPiMXiQJsQVvSlJ4fLReqsWRjxi1/gxvHjUE6cCAC4efEimsrLkTFnDsR+Wpo81KD+2TcOmw3XjxzBz3/7G4yNjRi3ZAky//3fIYqOxrhFizzuR/VkF3/pSQOYB5xOZ6BNCCv605MnFCJ11izmc8Phw6j/9ltc/uYbpBYWYtRjjyEiIcEfZoYM1D/dsZvNqD9wAHVffQXTzZsQREQg6/HHcfcDD3i1P9WTXfylJw1gHnANF6aww0D0nLBqFZS5ubj0xRe4sn8/6g8cQPL992PMk0/SWnTdUP905/rRo6jesQPimBiMf/pppD30EARSqdf7Uz3ZxV960gDmAekAnJ9yZwaiJ4fDQVJ+PhLvuw8tVVX4+YsvcOPYMWTOnw8AcNrtcNrt4A/jtM9w9k9CCJorKnBl/35k/+pXiExKwl2//CU4XC5SZswY1ECg4aynL/CXnjSAeeDWrVshvX5VsDEYPTkcDlNjsUOjYZZquXH8OH7cvh13zZqFtIcfhiwlxRcmBzXD0T+tBgOuffcd6r/9FsamJnA4HKgmT0ZkUhJ4QiHufvDBQR97OOrpS/ylJx1G7wFfFSkdrrCpZ1N5OWq769YBXcu6pBYWIik/f9j0yoabf17etw8/ffABHFYrRDIZUh98EGkPP8zau9HhpqevGaqedBj9ENFoNLSUFIuwqWdiXh5UU6bg5oULuLJvHxpPnkRLVRUz4gwI/1qW4e6fbVevoun0aWTOmwcOhwNJbCzkI0cirbgYydOmgScQsPp74a6nv/GXnrQHRgl5LO3tUJ84AdWUKZDGxcHS1obDq1cjaepUpMyYgZhRo8I6mIULnTodbvzv/+L60aNM73rG229DMXp02D+QUNyhPbAhQov5sosv9RTJZEgvLmY+dzY3gy8W4/Lf/47Lf/87IhMTkZifj6T77kPsmDE+scHfhJt//rBxI5rKy0EIgTAyEmkPPYSUmTMRM2oUAPg8eIWbnoHGX3rSHpgHbDYbBCynKYYz/taTEAJ9XR2uHz2KGydOwNzaitixY1Hw+98DAIyNjRDFxLitGh1KhKp/EqeTmagujIxE5rx5AICKP/0J1vZ23DVzJhLuvZf1FOGdCFU9g5Wh6kmr0Q8xgGm1WiiVShYtG94EUk9XMHPYbIjrXk/q2Nq1aL10CfE5OVBNmoT4nBxEjRgRMmmqUPJPq9EI7fnzaD5/HpozZ2BpbwcAxIwejZlvvx1g67oIJT1DgaHqSVOIQySyj3pplMETSD05HA6TinIxoqAAXKEQLT/+CO25cwAAUXQ08v7rvxA3dixcz3XBGtCC2T8tbW1oqa5G4pQp4AmFaLt6FWfeegsAEJ2WhrTiYiROmQJ5RkaALf0/glnPUMRfetIA5gGr1YqIiIhAmxE2BJue6Q8/jPSHH4atsxO66mq0VFejpaqKmWtmVKtx/OWXEZedjbjx4yHPyED03XcHTbX8YNLToFZDX1eHm7W1aKmuhuH6dQDALzZuRPw990AxejQmrl6N+JwcSIO0YG4w6RkO+EtPnwWwjRs3Yt++faisrIRQKIRer7/jPoQQrF+/Hu+99x70ej2mTZuGP//5zxh129OzPwizzGrACVY9BVIpEvPykJiX57bdajBAFBODG8eP48bx4wAALo+HuOxs3P+73zFteCJRQIJaIPQkhMCoVuNWXR0kcXGIHz8eAPDD66/DcOMGAEASF4e7Zs5EXHY2ZKmpALprXRYW+t3egRCs/hmq+EtPnwUwq9WKefPmIT8/Hzt27PBqn02bNmHLli3YtWsX0tLS8Morr6CoqAi1tbV+rxZNq1OzS6jpGTtmDGZt2QKrwYDWS5egr6vDrbo6CHo8VV789FNc2bcPUSkpiExORmRyMqKSkxGTmenzmo2+1NPpcIDbPQlVc+4c1MePw6BWo/3aNdhNJgBASkEBE8CynngC6E7TRqhUQZt27Y9Q889gJ+Sr0W/YsAEAUFpa6lV7Qgj+8Ic/YN26dZgzZw4AYPfu3VAqlfjqq6/wxBNP+MrUPmlvb6f10VgkVPUURkVBNWlSn+uURaenQzlpEtrq69F48iTz1Jk5fz6zdMf5rVtBHA6IY2MhjomBWKGAWKGA7K67BlRs9nYGqydxOgEOBxwOB6bWVmjPnoW5tRWm1lZ0NDXB2NgInkCAB7ZvBwAYGhpwrawMouhoyEeORExGBuQZGVBkZjLHTCkoGPR5BAuh6p/Bir/0DJp3YPX19dBoNCjskWqIjo5GXl4eTp065TGAWSwWWCwW5nN79winoRIbG8vKcShdhKOeqbNmMcvAOKxWdGg0MKrViEhMZNroqqthbGrqte/U3/4WqokTYTebcXTNGggiIsCXSsGXSMAXi8GXSDD2qacgkEphvnULmrNnu3o2HA44XC4chOBaTQ1ACAghcNrtcJjNSLzvPkQmJsJhteLcu+/CbjJ1/XV2wqzXw3LrFh4qLYVEoUCnVovzW7cyNvFEIkQlJyMqJYWZOJz64INIfeCBPheBDCfC0T8Dib/0DJoAptFoAKDX0EulUsl81xdvvPEG09vridlshtFohEqlQlNTE5KTk6FWqxEfHw+9Xg+pVAq73Q6n0wmJRIK2tjbExcVBq9UiOTkZFy9eRFZWFm7evAmZTAaz2QwOhwOhUAij0QiFQoHm5mbmuCqVClqtFjExMejs7ASfzweXy4XZbIZMJoNOp2PaJiUlobGxEXFxcWhvb2eW3na9+Lx165ZXdovFYrS3t7vZrVaroVQqodPp3OwWCATo6OjoZXdiYiI0Gk2/drvsvd1usVgMp9MJu90OqVTap90JCQlobW1lNCOEeG03l8sFn89HZ2cn5HI5Wlpa+rS7o6MDwu73UBaLpZfdrn36s9vlZ7fbHRkZCavV6mZ3bGysm4ZKpRK61lZEx8dDHBkJwuXCaDSis7MTM/74RzTduAGFUIgbDQ2QWizQ6fUQJSZCp9PBaTLBIZHAbLfDUVcHR0wMcO0aOGlpGEMI1Go1oNHg/JdfAh0dAI8HCATgKBQgHR2AWg1OairIlSvgpKdDnJCADi4XUokEN2prwRMIwCUE3Lg4SMViSCdN6lqtWK1G7IgRyHrpJSji4wGJBGKZDDweDyaTCTabzV1vqRQajQYKhQJGo5HR22q1IjIyEq2trR59ViKRwOFwMNeaXq9HQkJCv3oD6Pdaa25uhlwud/NZk8mE6OjoXtdaU1MTYmNje11rPe2+ePEisrOzB3SPcNlN7xG97xE2mw0REREDukdERETAZrOBEML4wJ0Y0DywtWvX4vfdE0E9ceHCBWRlZTGfS0tLUVJScsdBHCdPnsS0adPQ2NiIxB5PsPPnzweHw8Fnn33W53599cBSUlJoKSlKSEKcTtjNZthNJogVCnA4HFja2nCrro7pbcG1WGCPHhmXxwNfIkFkcjLTW3La7eDyg+YZlULxGp/MA1uzZg2WLl3ab5v09PSBHJJB1T18WavVugUwrVaLCRMmeNxPJBIxTydsQkvLsAvV0zs4XC4EUqnb+zFRdDRUEye6tfNGTxq8vIf6J7v4S88BeXh8fDzifTSPIy0tDSqVCmVlZUzAam9vR3l5OVatWuWT3+wPOiufXaie7EL1ZBeqJ7v4S0+urw7c0NCAyspKNDQ0wOFwoLKyEpWVlTAajUybrKws7N27F0BXxYOSkhK8/vrr+Oabb1BdXY3FixcjKSkJc+fO9ZWZHtHpdH7/zXCG6skuVE92oXqyi7/09FmO4dVXX8WuXbuYz7m5uQCAI0eOYMaMGQCAS5cuoa2tjWnz4osvoqOjAytWrIBer8f999+PAwcOBGSORnR0tN9/M5yherIL1ZNdqJ7s4i89aTFfD7S2tkKhULBo2fCG6skuVE92oXqyy1D19PY+7rMUYqjD5VJp2ITqyS5UT3aherKLv/Sk/zUP8OkILlaherIL1ZNdqJ7s4i89aQDzQGdnZ6BNCCuonuxC9WQXqie7+EtPGsA8IJfLA21CWEH1ZBeqJ7tQPdnFX3rSAOaBlpaWQJsQVlA92YXqyS5UT3bxl550FCKFQqFQggo6CnGIqNXqQJsQVlA92YXqyS5UT3bxl540gHmgZz1GytCherIL1ZNdqJ7s4i89aQDzQH9LuFAGDtWTXaie7EL1ZBd/6Rl2kx9cr/SGurAln89nbXFMCtWTbaie7EL1ZJeh6una905DNMIugBkMBgBASkpKgC2hUCgUylAwGAz91lUMu1GITqcTjY2NiIqK6lqCfRC4FsW8fv160I9knDx5Ms6cORNoM/qF6skuVE92oXqyCxt6EkJgMBiQlJTUb1mqsOuBcblcjBgxgpVjyWSyoHdoHo8X9Da6oHqyC9WTXaie7DJUPb2paE8HcYQ4zz77bKBNCCuonuxC9WQXqqc7YZdCZAM6GZpdqJ7sQvVkF6onu/hTT9oD6wORSIT169dDJBIF2pSwgOrJLlRPdqF6sos/9aQ9MAqFQqGEJLQHRqFQKJSQhAYwCoVCoYQkNIBRKBQKJSShAYxCoVAoIQkNYN1s3LgRU6dOhVQq9Xo1UUIIXn31VSQmJkIikaCwsBD//Oc/fWtoiNDa2oqFCxdCJpNBLpdj2bJlMBqN/e4zY8YMcDgct7+VK1f6yeLgYtu2bbj77rshFouRl5eH06dP99v+iy++QFZWFsRiMbKzs7F//34/WRoaDETP0tLSXn4oFov9aG1wc+zYMTzyyCNISkoCh8PBV199dcd9jh49invvvRcikQgZGRkoLS1lxRYawLqxWq2YN28eVq1a5fU+mzZtwpYtW7B9+3aUl5cjIiICRUVFMJvNPrQ0NFi4cCFqampw6NAh/OMf/8CxY8ewYsWKO+63fPlyNDU1MX+bNm3yg7XBxWeffYbnn38e69evx/nz55GTk4OioiI0Nzf32f7kyZNYsGABli1bhoqKCsydOxdz587FTz/95GfLg5OB6gl0VZHo6YfXrl3zo8XBTUdHB3JycrBt2zav2tfX12P27NmYOXMmKisrUVJSgmeeeQYHDx4cujGE4sbOnTtJdHT0Hds5nU6iUqnIW2+9xWzT6/VEJBKRv/71rz60MPipra0lAMiZM2eYbd9++y3hcDhErVZ73K+goICsXr3aDxYGN1OmTCHPPvss89nhcJCkpCTyxhtv9Nl+/vz5ZPbs2W7b8vLyyK9//Wuf2hkqDFRPb+8BFEIAkL179/bb5sUXXyTjxo1z2/b444+ToqKiIf8+7YENkvr6emg0GhQWFjLboqOjkZeXh1OnTgXQssBz6tQpyOVyTJo0idlWWFgILpeL8vLyfvf9+OOPERcXh/Hjx+Pll19GZ2enr80NKqxWK86dO+fmV1wuF4WFhR796tSpU27tAaCoqGjY+yEwOD0BwGg0IjU1FSkpKZgzZw5qamr8YW5Y4kv/DLtivv7CtWCbUql0265UKof94ngajQYJCQlu2/h8PhQKRb/aPPnkk0hNTUVSUhKqqqrw0ksv4dKlS9izZ4+vTQ4adDodHA5Hn3518eLFPvfRaDTUDz0wGD0zMzPxwQcf4J577kFbWxs2b96MqVOnoqamhrVC4cMJT/7Z3t4Ok8kEiUQy6GOHdQ9s7dq1vV7G3v7nyYkpvfG1nitWrEBRURGys7OxcOFC7N69G3v37sXly5dZPAsKpX/y8/OxePFiTJgwAQUFBdizZw/i4+Pxl7/8JdCmUW4jrHtga9aswdKlS/ttk56ePqhjq1QqAIBWq0ViYiKzXavVYsKECYM6ZrDjrZ4qlarXC3K73Y7W1lZGN2/Iy8sDANTV1WHkyJEDtjcUiYuLA4/Hg1ardduu1Wo9aqdSqQbUfjgxGD1vRyAQIDc3F3V1db4wMezx5J8ymWxIvS8gzANYfHw84uPjfXLstLQ0qFQqlJWVMQGrvb0d5eXlAxrJGEp4q2d+fj70ej3OnTuHiRMnAgAOHz4Mp9PJBCVvqKysBAC3B4RwRygUYuLEiSgrK8PcuXMBdC3SWlZWhueee67PffLz81FWVoaSkhJm26FDh5Cfn+8Hi4Obweh5Ow6HA9XV1SguLvahpeFLfn5+r2kdrPnnkIeBhAnXrl0jFRUVZMOGDSQyMpJUVFSQiooKYjAYmDaZmZlkz549zOc333yTyOVy8vXXX5OqqioyZ84ckpaWRkwmUyBOIah46KGHSG5uLikvLycnTpwgo0aNIgsWLGC+v3HjBsnMzCTl5eWEEELq6urIa6+9Rs6ePUvq6+vJ119/TdLT08n06dMDdQoB49NPPyUikYiUlpaS2tpasmLFCiKXy4lGoyGEELJo0SKydu1apv33339P+Hw+2bx5M7lw4QJZv349EQgEpLq6OlCnEFQMVM8NGzaQgwcPksuXL5Nz586RJ554gojFYlJTUxOoUwgqDAYDc38EQN555x1SUVFBrl27RgghZO3atWTRokVM+ytXrhCpVEpeeOEFcuHCBbJt2zbC4/HIgQMHhmwLDWDdLFmyhADo9XfkyBGmDQCyc+dO5rPT6SSvvPIKUSqVRCQSkVmzZpFLly753/gg5ObNm2TBggUkMjKSyGQy8vTTT7s9DNTX17vp29DQQKZPn04UCgURiUQkIyODvPDCC6StrS1AZxBYtm7dSu666y4iFArJlClTyA8//MB8V1BQQJYsWeLW/vPPPyejR48mQqGQjBs3juzbt8/PFgc3A9GzpKSEaatUKklxcTE5f/58AKwOTo4cOdLnvdKl4ZIlS0hBQUGvfSZMmECEQiFJT093u48OBbqcCoVCoVBCkrAehUihUCiU8IUGMAqFQqGEJDSAUSgUCiUkoQGMQqFQKCEJDWAUCoVCCUloAKNQKBRKSEIDGIVCoVBCEhrAKBQKhRKS0ABGoVAolJCEBjAKhUKhhCQ0gFEoFAolJKEBjEKhUCghyf8HHidlDi+MAD8AAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "\n", - "G.transform_coordinates(projection_type=\"pca\") # project with PCA\n", - "G.scale_coordinates(1) # scale to radius 1\n", - "G.plot(with_labels=False, node_size=10, bounding_circle=True)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " And then we can compute the ECT of this leaf." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "OMP: Info #276: omp_set_nested routine deprecated, please use omp_set_max_active_levels instead.\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "num_dirs = 50 # set number of directional axes\n", - "num_thresh = 50 # set number of thresholds each axis\n", - "\n", - "myect = ECT(num_dirs=num_dirs, num_thresh=num_thresh); # intiate ECT\n", - "result = myect.calculate(G); # calculate ECT on embedded graph\n", - "\n", - "result.plot(); # plot ECT" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " Let's just make a data loader with all of this for ease in a bit." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def matisse_ect(filename, ect):\n", - " shape = np.loadtxt(data_dir + filename)\n", - " G = EmbeddedComplex() # Using the unified EmbeddedComplex class \n", - " G.add_cycle(shape)\n", - " G.transform_coordinates(projection_type=\"pca\")\n", - " G.scale_coordinates(1)\n", - " result = ect.calculate(G)\n", - " return result" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " And now we can load in all the outlines, compute their ECT and store it in a 3D array." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "num_dirs = 50 # set number of directional axes\n", - "num_thresh = 50 # set number of thresholds each axis\n", - "\n", - "ect_arr = np.zeros((len(file_names), num_dirs, num_thresh))\n", - "myect = ECT(num_dirs=num_dirs, num_thresh=num_thresh, bound_radius=1)\n", - "\n", - "for i in range(len(file_names)): # for each leaf\n", - " ect_arr[i, :, :] = matisse_ect(file_names[i], myect)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " Here, we are just going to compute the distance between two ECTs using $L_2$ distance." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "flattened_ect = ect_arr.reshape(len(file_names), num_dirs * num_thresh)\n", - "D = distance_matrix(flattened_ect, flattened_ect)\n", - "plt.matshow(D)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " For visualization purposes, we can project this data into 2D using Multi Dimensional Scaling (MDS). Here we plot each figure at the MDS coordinates." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "n_components = 2 # select number of components\n", - "mds = MDS(\n", - " n_components=n_components, # initialize MDS\n", - " dissimilarity=\"precomputed\", # we have precomputed the distance matrix\n", - " normalized_stress=\"auto\",\n", - " random_state=5, # select random state for reproducibility\n", - ")\n", - "MDS_scores = mds.fit_transform(D) # get MDS scores\n" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, \"MDS of Matisse's Leaves via ECT distances\")" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# read in color hexcodes\n", - "col_df = pd.read_csv(colors_path, header=None)\n", - "\n", - "scale_val = 6 # set scale value\n", - "plt.figure(figsize=(5, 5)) # set figure dimensions\n", - "\n", - "for i in range(len(file_names)): # for each leaf\n", - " shape = np.loadtxt(data_dir + file_names[i]) # get the current shape\n", - " shape = shape - np.mean(shape, axis=0) # zero center shape\n", - " shape = (\n", - " scale_val * shape / max(np.linalg.norm(shape, axis=1))\n", - " ) # scale to radius 1 then mult by scale_val\n", - "\n", - " trans_sh = shape + MDS_scores[i] # translate shape to MDS position\n", - "\n", - " plt.fill(trans_sh[:, 0], trans_sh[:, 1], c=col_df[0][i], lw=0) # plot shape\n", - " plt.gca().set_aspect(\"equal\")\n", - "\n", - "plt.title(\"MDS of Matisse's Leaves via ECT distances\")\n", - "# plt.savefig(\"Matisse_MDS.png\", bbox_inches = 'tight', dpi=300)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Acknowledgements\n", - "\n", - "\n", - "\n", - " This notebook was written by [Liz Munch](https://elizabethmunch.com/) based on [original code](https://github.com/DanChitwood/matisse_test) from [Dan Chitwood](https://www.canr.msu.edu/people/dr_dan_chitwood)." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "base", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.7" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/docs/notebooks/Matisse/outlines.zip b/docs/notebooks/Matisse/outlines.zip deleted file mode 100644 index 1f11162..0000000 Binary files a/docs/notebooks/Matisse/outlines.zip and /dev/null differ diff --git a/docs/notebooks/Tutorial-EmbeddedComplex.html b/docs/notebooks/Tutorial-EmbeddedComplex.html deleted file mode 100644 index 363e4f2..0000000 --- a/docs/notebooks/Tutorial-EmbeddedComplex.html +++ /dev/null @@ -1,713 +0,0 @@ - - - - - - - 3.1. Tutorial: ECT for Embedded Cell Complexes — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - - - - - - -
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3.1. Tutorial: ECT for Embedded Cell Complexes

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This tutorial will walk you through using the ECT package. Particularly we will show the features of EmbeddedComplex class for computing the Euler Characteristic Transform on complexes with arbitrary dimensional cells.

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The EmbeddedComplex class combines and extends the functionality of the previous EmbeddedGraph and EmbeddedCW classes, supporting: - 0-cells (vertices) with embedded coordinates - 1-cells (edges) - k-cells for k ≥ 2 (faces, volumes, and higher-dimensional cells).

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[1]:
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import numpy as np
-import matplotlib.pyplot as plt
-from ect import EmbeddedComplex, ECT, Directions
-from ect.utils.examples import create_example_graph, create_example_cw, create_example_3d_complex
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3.1.1. Basic Usage: Creating Simple Complexes

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3.1.1.1. Example 1: Graph (1-skeleton)

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Let’s start with a simple triangle graph (for legacy users this can be equivalently done using EmbeddedGraph).

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K = EmbeddedComplex()
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-K.add_node('A', [0, 0])
-K.add_node('B', [1, 0])
-K.add_node('C', [0.5, 0.866])
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-K.add_edge('A', 'B')
-K.add_edge('B', 'C')
-K.add_edge('C', 'A')
-
-#using built-in plotting function along with matplotlib
-fig, ax = plt.subplots(figsize=(6, 6))
-K.plot(ax=ax, with_labels=True, node_size=400)
-ax.set_title('Simple Triangle Graph\n(0-cells: vertices, 1-cells: edges)')
-plt.show()
-
-#print some information about the complex
-print(f"Number of nodes: {len(K.nodes())}")
-print(f"Number of edges: {len(K.edges())}")
-print(f"Embedding dimension: {K.dim}")
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-Number of nodes: 3
-Number of edges: 3
-Embedding dimension: 2
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Now let’s add a 2-cell (face) to fill in the triangle:

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K.add_face(['A', 'B', 'C'])
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-fig, ax = plt.subplots(figsize=(6, 6))
-K.plot(ax=ax, with_labels=True, node_size=400, face_alpha=0.3, face_color='lightblue')
-ax.set_title('Triangle with Face\n(0-cells: vertices, 1-cells: edges, 2-cells: faces)')
-plt.show()
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-print(f"Number of 2-cells (faces): {len(K.faces)}")
-print(f"Faces: {K.faces}")
-print(f"Internal cells dictionary: {dict(K.cells)}")
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-Number of 2-cells (faces): 1
-Faces: [('A', 'B', 'C')]
-Internal cells dictionary: {2: [(0, 1, 2)]}
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3.1.2. Adding Cells of Arbitrary Dimension

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The key new feature is the ability to add cells of any dimension:

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# Create a 3D tetrahedron with 0, 1, 2, and 3-cells
-K_tetra = EmbeddedComplex()
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-# Add vertices (0-cells)
-vertices = {
-    'A': [0, 0, 0],
-    'B': [1, 0, 0],
-    'C': [0.5, 0.866, 0],
-    'D': [0.5, 0.289, 0.816]
-}
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-for name, coord in vertices.items():
-    K_tetra.add_node(name, coord)
-
-# Add edges (1-cells) - all pairs
-edges = [('A', 'B'), ('A', 'C'), ('A', 'D'), ('B', 'C'), ('B', 'D'), ('C', 'D')]
-K_tetra.add_edges_from(edges)
-
-# Add faces (2-cells) - all triangular faces
-faces = [['A', 'B', 'C'], ['A', 'B', 'D'], ['A', 'C', 'D'], ['B', 'C', 'D']]
-for face in faces:
-    K_tetra.add_cell(face, dim=2)  # Explicitly specify dimension
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-# Add volume (3-cell) - the entire tetrahedron
-K_tetra.add_cell(['A', 'B', 'C', 'D'], dim=3)
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-# Plot the tetrahedron
-fig = plt.figure(figsize=(10, 8))
-ax = fig.add_subplot(111, projection='3d')
-K_tetra.plot(ax=ax, face_alpha=0.3, face_color='cyan', node_size=100)
-ax.set_title('Tetrahedron with All Cell Types\n0-cells: 4, 1-cells: 6, 2-cells: 4, 3-cells: 1')
-plt.show()
-
-# Display cell counts
-for dim in sorted(K_tetra.cells.keys()):
-    print(f"Dimension {dim}: {len(K_tetra.cells[dim])} cells")
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-print(f"\nTotal embedding dimension: {K_tetra.dim}")
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-Dimension 2: 4 cells
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3.1.3. ECT Computation with Higher-Dimensional Cells

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The ECT computation now properly includes all cell dimensions in the Euler characteristic calculation:

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χ = Σ(-1)^k × |k-cells below threshold|

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Let’s see how this works:

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# Compute ECT for the tetrahedron
-ect = ECT(num_dirs=8, num_thresh=20)
-result = ect.calculate(K_tetra)
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-print(f"ECT result shape: {result.shape}")
-print(f"Directions: {len(result.directions)} directions in {K_tetra.dim}D")
-print(f"Thresholds: {len(result.thresholds)} threshold values")
-
-# Plot the ECT matrix
-fig, ax = plt.subplots(figsize=(10, 6))
-result.plot()
-plt.title('ECT of Tetrahedron (includes 3-cells in computation)')
-plt.show()
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-# Show a single direction
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-single_direction = ECT(num_thresh=20, directions=Directions.from_vectors([[1, 0, 0]])).calculate(K_tetra)
-fig, ax = plt.subplots(figsize=(8, 5))
-ax.plot(single_direction.thresholds, single_direction[0], 'b-', marker='o', linewidth=2)
-ax.set_xlabel('Threshold')
-ax.set_ylabel('Euler Characteristic')
-ax.set_title('ECT Curve for Single Direction (v=[1, 0, 0])')
-ax.grid(True, alpha=0.3)
-plt.show()
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-ECT result shape: (8, 20)
-Directions: 8 directions in 3D
-Thresholds: 20 threshold values
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-../_images/notebooks_Tutorial-EmbeddedComplex_9_2.png -
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You can also restrict self-intersections by using the ‘validate_embeddings’ argument. Currently without checks we can add a node inside of our tetrahedron.

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[26]:
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K_valid = K_tetra.copy()
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-K_valid.add_node('E', [0.5, 0.289, 0.204])
-K_valid.add_cell(['E', 'B'], dim=1)
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-# Display cell counts
-print("4D Simplex Cell Counts:")
-for dim in sorted(K_valid.cells.keys()):
-    print(f"  {dim}-cells: {len(K_valid.cells[dim])}")
-
-# Plot (showing 3D projection)
-fig = plt.figure(figsize=(10, 8))
-ax = fig.add_subplot(111, projection='3d')
-K_valid.plot(ax=ax, face_alpha=0.1, node_size=80)
-ax.set_title('4D Simplex (5 vertices, cells up to dimension 4)')
-plt.show()
-
-# Compute ECT
-ect_4d = ECT(num_dirs=6, num_thresh=15)
-result_4d = ect_4d.calculate(K_valid)
-
-fig, ax = plt.subplots(figsize=(10, 6))
-result_4d.plot()
-plt.title('ECT of 4D Simplex\n(alternating sum includes all dimensions 0-4)')
-plt.show()
-
-
-
-
-
-
-
-
-Unexpected exception formatting exception. Falling back to standard exception
-
-
-
-
-
-
-
-Traceback (most recent call last):
-  File "/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/interactiveshell.py", line 3548, in run_code
-    exec(code_obj, self.user_global_ns, self.user_ns)
-  File "/var/folders/81/3x5xj5kx4ys30p1c2z55bhbw0000gn/T/ipykernel_80902/4266954845.py", line 1, in <module>
-    K_valid = K_tetra.copy()
-              ^^^^^^^^^^^^^^
-  File "/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/networkx/classes/graph.py", line 1642, in copy
-    G.add_nodes_from((n, d.copy()) for n, d in self._node.items())
-  File "/Users/yayub/Code/ect/src/ect/embed_complex.py", line 177, in add_nodes_from
-  File "/Users/yayub/Code/ect/src/ect/embed_complex.py", line 120, in wrapper
-    )
-
-  File "/Users/yayub/Code/ect/src/ect/embed_complex.py", line 142, in wrapper
-    def wrapper(self, *args, **kwargs):
-               ^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/Users/yayub/Code/ect/src/ect/embed_complex.py", line 157, in add_node
-    return wrapper
-        ^^^^^^^^^^^
-TypeError: float() argument must be a string or a real number, not 'dict'
-
-During handling of the above exception, another exception occurred:
-
-Traceback (most recent call last):
-  File "/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/interactiveshell.py", line 2142, in showtraceback
-    stb = self.InteractiveTB.structured_traceback(
-          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py", line 1435, in structured_traceback
-    return FormattedTB.structured_traceback(
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py", line 1326, in structured_traceback
-    return VerboseTB.structured_traceback(
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py", line 1173, in structured_traceback
-    formatted_exception = self.format_exception_as_a_whole(etype, evalue, etb, number_of_lines_of_context,
-                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py", line 1088, in format_exception_as_a_whole
-    frames.append(self.format_record(record))
-                  ^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py", line 970, in format_record
-    frame_info.lines, Colors, self.has_colors, lvals
-    ^^^^^^^^^^^^^^^^
-  File "/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py", line 792, in lines
-    return self._sd.lines
-           ^^^^^^^^^^^^^^
-  File "/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/utils.py", line 144, in cached_property_wrapper
-    value = obj.__dict__[self.func.__name__] = self.func(obj)
-                                               ^^^^^^^^^^^^^^
-  File "/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/core.py", line 734, in lines
-    pieces = self.included_pieces
-             ^^^^^^^^^^^^^^^^^^^^
-  File "/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/utils.py", line 144, in cached_property_wrapper
-    value = obj.__dict__[self.func.__name__] = self.func(obj)
-                                               ^^^^^^^^^^^^^^
-  File "/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/core.py", line 681, in included_pieces
-    pos = scope_pieces.index(self.executing_piece)
-                             ^^^^^^^^^^^^^^^^^^^^
-  File "/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/utils.py", line 144, in cached_property_wrapper
-    value = obj.__dict__[self.func.__name__] = self.func(obj)
-                                               ^^^^^^^^^^^^^^
-  File "/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/core.py", line 660, in executing_piece
-    return only(
-           ^^^^^
-  File "/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/executing/executing.py", line 116, in only
-    raise NotOneValueFound('Expected one value, found 0')
-executing.executing.NotOneValueFound: Expected one value, found 0
-
-
-
-
-

3.1.4. Understanding ECT with Projection Visualization

-

Let’s visualize how the ECT computation works by showing projection values:

-
-
[7]:
-
-
-
# Create a simple 2D example for visualization
-K_viz = EmbeddedComplex()
-
-# Square with center point
-K_viz.add_node('A', [-1, -1])
-K_viz.add_node('B', [1, -1])
-K_viz.add_node('C', [1, 1])
-K_viz.add_node('D', [-1, 1])
-K_viz.add_node('E', [0, 0])  # center
-
-# Add edges
-edges = [('A', 'B'), ('B', 'C'), ('C', 'D'), ('D', 'A'),  # boundary
-         ('A', 'E'), ('B', 'E'), ('C', 'E'), ('D', 'E')]   # to center
-K_viz.add_edges_from(edges)
-
-# Add triangular faces
-faces = [['A', 'B', 'E'], ['B', 'C', 'E'], ['C', 'D', 'E'], ['D', 'A', 'E']]
-for face in faces:
-    K_viz.add_face(face)
-
-# Visualization function
-def plot_with_projections(K, theta, ax):
-    """Plot complex with nodes colored by projection values"""
-    direction = np.array([np.sin(theta), -np.cos(theta)])
-    node_projections = np.dot(K.coord_matrix, direction)
-
-    # Plot edges
-    for u, v in K.edges():
-        u_idx = K.node_to_index[u]
-        v_idx = K.node_to_index[v]
-        x = [K.coord_matrix[u_idx, 0], K.coord_matrix[v_idx, 0]]
-        y = [K.coord_matrix[u_idx, 1], K.coord_matrix[v_idx, 1]]
-        ax.plot(x, y, 'k-', alpha=0.5, linewidth=1)
-
-    # Plot faces with transparency
-    for face_indices in K.cells.get(2, []):
-        face_coords = K.coord_matrix[list(face_indices)]
-        face_projection = np.max(node_projections[list(face_indices)])
-        ax.fill(face_coords[:, 0], face_coords[:, 1],
-               alpha=0.3, color=plt.cm.Blues(0.5))
-
-    # Plot nodes colored by projection
-    scatter = ax.scatter(K.coord_matrix[:, 0], K.coord_matrix[:, 1],
-                        c=node_projections, cmap='plasma', s=300,
-                        edgecolors='black', linewidth=2, zorder=10)
-
-    # Add node labels with projection values
-    for i, node in enumerate(K.node_list):
-        ax.annotate(f'{node}\n({node_projections[i]:.2f})',
-                   (K.coord_matrix[i, 0], K.coord_matrix[i, 1]),
-                   ha='center', va='center', fontsize=9, fontweight='bold',
-                   bbox=dict(boxstyle='round,pad=0.2', facecolor='white', alpha=0.8))
-
-    # Direction arrow
-    ax.arrow(0, 0, direction[0]*0.7, direction[1]*0.7,
-             head_width=0.1, head_length=0.1, fc='red', ec='red', linewidth=2)
-
-    ax.set_xlim(-2, 2)
-    ax.set_ylim(-2, 2)
-    ax.set_aspect('equal')
-    ax.grid(True, alpha=0.3)
-    ax.set_title(f'θ = {theta*180/np.pi:.0f}°')
-
-    return scatter
-
-# Show projections in multiple directions
-fig, axes = plt.subplots(2, 3, figsize=(15, 10))
-axes = axes.flatten()
-
-thetas = np.linspace(0, 2*np.pi, 6, endpoint=False)
-for ax, theta in zip(axes, thetas):
-    scatter = plot_with_projections(K_viz, theta, ax)
-
-# Add shared colorbar
-fig.subplots_adjust(right=0.9)
-cbar_ax = fig.add_axes([0.92, 0.15, 0.02, 0.7])
-fig.colorbar(scatter, cax=cbar_ax, label='Node Projection Values')
-
-plt.suptitle('Complex Colored by Projection Values in Different Directions\n' +
-            'Red arrows show projection direction, faces use max vertex projection',
-            fontsize=14)
-plt.show()
-
-
-
-
-
-
-
-../_images/notebooks_Tutorial-EmbeddedComplex_13_0.png -
-
-
-
-

3.1.5. Comparing Graph vs. Complex ECT

-

Let’s compare ECT results for the same geometry with and without 2-cells:

-
-
[8]:
-
-
-
# Create two versions: graph only vs. complex with faces
-K_graph = EmbeddedComplex()
-K_complex = EmbeddedComplex()
-
-# Same vertices and edges for both
-vertices = {'A': [0, 0], 'B': [2, 0], 'C': [1, 1.732]}
-edges = [('A', 'B'), ('B', 'C'), ('C', 'A')]
-
-for K in [K_graph, K_complex]:
-    for name, coord in vertices.items():
-        K.add_node(name, coord)
-    K.add_edges_from(edges)
-
-# Add face only to the complex version
-K_complex.add_face(['A', 'B', 'C'])
-
-# Compute ECT for both
-ect = ECT(num_dirs=20, num_thresh=30)
-result_graph = ect.calculate(K_graph)
-result_complex = ect.calculate(K_complex)
-
-# Plot comparison
-fig, axes = plt.subplots(2, 2, figsize=(15, 10))
-
-# Visualizations
-K_graph.plot(ax=axes[0,0], with_labels=True, node_size=400)
-axes[0,0].set_title('Graph Only (no 2-cells)')
-
-K_complex.plot(ax=axes[0,1], with_labels=True, node_size=400,
-               face_alpha=0.3, face_color='lightblue')
-axes[0,1].set_title('Complex with 2-cell (face)')
-
-# ECT comparisons
-result_graph.plot(ax=axes[1,0])
-axes[1,0].set_title('ECT: Graph Only\n(χ = vertices - edges)')
-
-result_complex.plot(ax=axes[1,1])
-axes[1,1].set_title('ECT: Complex with Face\n(χ = vertices - edges + faces)')
-
-plt.tight_layout()
-plt.show()
-
-# Show numerical difference
-print("ECT value ranges:")
-print(f"Graph only: [{result_graph.min()}, {result_graph.max()}]")
-print(f"With face:  [{result_complex.min()}, {result_complex.max()}]")
-print(f"\nThe face contributes +1 to the Euler characteristic when included.")
-
-
-
-
-
-
-
-../_images/notebooks_Tutorial-EmbeddedComplex_15_0.png -
-
-
-
-
-
-
-ECT value ranges:
-Graph only: [0, 1]
-With face:  [0, 1]
-
-The face contributes +1 to the Euler characteristic when included.
-
-
-
-
- - -
-
- -
-
-
-
- - - - - - - \ No newline at end of file diff --git a/docs/notebooks/Tutorial-EmbeddedComplex.ipynb b/docs/notebooks/Tutorial-EmbeddedComplex.ipynb deleted file mode 100644 index 1738074..0000000 --- a/docs/notebooks/Tutorial-EmbeddedComplex.ipynb +++ /dev/null @@ -1,624 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Tutorial: ECT for Embedded Cell Complexes\n", - "\n", - "This tutorial will walk you through using the `ECT` package. Particularly we will show the features of `EmbeddedComplex` class for computing the Euler Characteristic Transform on complexes with arbitrary dimensional cells.\n", - "\n", - "The `EmbeddedComplex` class combines and extends the functionality of the previous `EmbeddedGraph` and `EmbeddedCW` classes, supporting:\n", - "- **0-cells** (vertices) with embedded coordinates\n", - "- **1-cells** (edges)\n", - "- **k-cells** for k ≥ 2 (faces, volumes, and higher-dimensional cells).\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "from ect import EmbeddedComplex, ECT, Directions\n", - "from ect.utils.examples import create_example_graph, create_example_cw, create_example_3d_complex" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Basic Usage: Creating Simple Complexes\n", - "\n", - "### Example 1: Graph (1-skeleton)\n", - "\n", - "Let's start with a simple triangle graph (for legacy users this can be equivalently done using `EmbeddedGraph`). " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of nodes: 3\n", - "Number of edges: 3\n", - "Embedding dimension: 2\n" - ] - } - ], - "source": [ - "K = EmbeddedComplex()\n", - "\n", - "K.add_node('A', [0, 0])\n", - "K.add_node('B', [1, 0])\n", - "K.add_node('C', [0.5, 0.866])\n", - "\n", - "K.add_edge('A', 'B')\n", - "K.add_edge('B', 'C')\n", - "K.add_edge('C', 'A')\n", - "\n", - "#using built-in plotting function along with matplotlib\n", - "fig, ax = plt.subplots(figsize=(6, 6))\n", - "K.plot(ax=ax, with_labels=True, node_size=400)\n", - "ax.set_title('Simple Triangle Graph\\n(0-cells: vertices, 1-cells: edges)')\n", - "plt.show()\n", - "\n", - "#print some information about the complex\n", - "print(f\"Number of nodes: {len(K.nodes())}\")\n", - "print(f\"Number of edges: {len(K.edges())}\")\n", - "print(f\"Embedding dimension: {K.dim}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now let's add a 2-cell (face) to fill in the triangle:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of 2-cells (faces): 1\n", - "Faces: [('A', 'B', 'C')]\n", - "Internal cells dictionary: {2: [(0, 1, 2)]}\n" - ] - } - ], - "source": [ - "K.add_face(['A', 'B', 'C'])\n", - "\n", - "fig, ax = plt.subplots(figsize=(6, 6))\n", - "K.plot(ax=ax, with_labels=True, node_size=400, face_alpha=0.3, face_color='lightblue')\n", - "ax.set_title('Triangle with Face\\n(0-cells: vertices, 1-cells: edges, 2-cells: faces)')\n", - "plt.show()\n", - "\n", - "print(f\"Number of 2-cells (faces): {len(K.faces)}\")\n", - "print(f\"Faces: {K.faces}\")\n", - "print(f\"Internal cells dictionary: {dict(K.cells)}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Adding Cells of Arbitrary Dimension\n", - "\n", - "The key new feature is the ability to add cells of any dimension:" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Dimension 2: 4 cells\n", - "Dimension 3: 1 cells\n", - "\n", - "Total embedding dimension: 3\n" - ] - } - ], - "source": [ - "# Create a 3D tetrahedron with 0, 1, 2, and 3-cells\n", - "K_tetra = EmbeddedComplex()\n", - "\n", - "# Add vertices (0-cells)\n", - "vertices = {\n", - " 'A': [0, 0, 0],\n", - " 'B': [1, 0, 0],\n", - " 'C': [0.5, 0.866, 0],\n", - " 'D': [0.5, 0.289, 0.816] \n", - "}\n", - "\n", - "for name, coord in vertices.items():\n", - " K_tetra.add_node(name, coord)\n", - "\n", - "# Add edges (1-cells) - all pairs\n", - "edges = [('A', 'B'), ('A', 'C'), ('A', 'D'), ('B', 'C'), ('B', 'D'), ('C', 'D')]\n", - "K_tetra.add_edges_from(edges)\n", - "\n", - "# Add faces (2-cells) - all triangular faces\n", - "faces = [['A', 'B', 'C'], ['A', 'B', 'D'], ['A', 'C', 'D'], ['B', 'C', 'D']]\n", - "for face in faces:\n", - " K_tetra.add_cell(face, dim=2) # Explicitly specify dimension\n", - "\n", - "# Add volume (3-cell) - the entire tetrahedron\n", - "K_tetra.add_cell(['A', 'B', 'C', 'D'], dim=3)\n", - "\n", - "# Plot the tetrahedron\n", - "fig = plt.figure(figsize=(10, 8))\n", - "ax = fig.add_subplot(111, projection='3d')\n", - "K_tetra.plot(ax=ax, face_alpha=0.3, face_color='cyan', node_size=100)\n", - "ax.set_title('Tetrahedron with All Cell Types\\n0-cells: 4, 1-cells: 6, 2-cells: 4, 3-cells: 1')\n", - "plt.show()\n", - "\n", - "# Display cell counts\n", - "for dim in sorted(K_tetra.cells.keys()):\n", - " print(f\"Dimension {dim}: {len(K_tetra.cells[dim])} cells\")\n", - " \n", - "print(f\"\\nTotal embedding dimension: {K_tetra.dim}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## ECT Computation with Higher-Dimensional Cells\n", - "\n", - "The ECT computation now properly includes all cell dimensions in the Euler characteristic calculation:\n", - "\n", - "**χ = Σ(-1)^k × |k-cells below threshold|**\n", - "\n", - "Let's see how this works:" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ECT result shape: (8, 20)\n", - "Directions: 8 directions in 3D\n", - "Thresholds: 20 threshold values\n" - ] - }, - { - "data": { - "image/png": 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Compute ECT for the tetrahedron\n", - "ect = ECT(num_dirs=8, num_thresh=20)\n", - "result = ect.calculate(K_tetra)\n", - "\n", - "print(f\"ECT result shape: {result.shape}\")\n", - "print(f\"Directions: {len(result.directions)} directions in {K_tetra.dim}D\")\n", - "print(f\"Thresholds: {len(result.thresholds)} threshold values\")\n", - "\n", - "# Plot the ECT matrix\n", - "fig, ax = plt.subplots(figsize=(10, 6))\n", - "result.plot()\n", - "plt.title('ECT of Tetrahedron (includes 3-cells in computation)')\n", - "plt.show()\n", - "\n", - "# Show a single direction\n", - "\n", - "single_direction = ECT(num_thresh=20, directions=Directions.from_vectors([[1, 0, 0]])).calculate(K_tetra)\n", - "fig, ax = plt.subplots(figsize=(8, 5))\n", - "ax.plot(single_direction.thresholds, single_direction[0], 'b-', marker='o', linewidth=2)\n", - "ax.set_xlabel('Threshold')\n", - "ax.set_ylabel('Euler Characteristic')\n", - "ax.set_title('ECT Curve for Single Direction (v=[1, 0, 0])')\n", - "ax.grid(True, alpha=0.3)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "You can also restrict self-intersections by using the 'validate_embeddings' argument. Currently without checks we can add a node inside of our tetrahedron." - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Unexpected exception formatting exception. Falling back to standard exception\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Traceback (most recent call last):\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/interactiveshell.py\", line 3548, in run_code\n", - " exec(code_obj, self.user_global_ns, self.user_ns)\n", - " File \"/var/folders/81/3x5xj5kx4ys30p1c2z55bhbw0000gn/T/ipykernel_80902/4266954845.py\", line 1, in \n", - " K_valid = K_tetra.copy()\n", - " ^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/networkx/classes/graph.py\", line 1642, in copy\n", - " G.add_nodes_from((n, d.copy()) for n, d in self._node.items())\n", - " File \"/Users/yayub/Code/ect/src/ect/embed_complex.py\", line 177, in add_nodes_from\n", - " File \"/Users/yayub/Code/ect/src/ect/embed_complex.py\", line 120, in wrapper\n", - " )\n", - " \n", - " File \"/Users/yayub/Code/ect/src/ect/embed_complex.py\", line 142, in wrapper\n", - " def wrapper(self, *args, **kwargs):\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/Code/ect/src/ect/embed_complex.py\", line 157, in add_node\n", - " return wrapper\n", - " ^^^^^^^^^^^\n", - "TypeError: float() argument must be a string or a real number, not 'dict'\n", - "\n", - "During handling of the above exception, another exception occurred:\n", - "\n", - "Traceback (most recent call last):\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/interactiveshell.py\", line 2142, in showtraceback\n", - " stb = self.InteractiveTB.structured_traceback(\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py\", line 1435, in structured_traceback\n", - " return FormattedTB.structured_traceback(\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py\", line 1326, in structured_traceback\n", - " return VerboseTB.structured_traceback(\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py\", line 1173, in structured_traceback\n", - " formatted_exception = self.format_exception_as_a_whole(etype, evalue, etb, number_of_lines_of_context,\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py\", line 1088, in format_exception_as_a_whole\n", - " frames.append(self.format_record(record))\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py\", line 970, in format_record\n", - " frame_info.lines, Colors, self.has_colors, lvals\n", - " ^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/IPython/core/ultratb.py\", line 792, in lines\n", - " return self._sd.lines\n", - " ^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/utils.py\", line 144, in cached_property_wrapper\n", - " value = obj.__dict__[self.func.__name__] = self.func(obj)\n", - " ^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/core.py\", line 734, in lines\n", - " pieces = self.included_pieces\n", - " ^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/utils.py\", line 144, in cached_property_wrapper\n", - " value = obj.__dict__[self.func.__name__] = self.func(obj)\n", - " ^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/core.py\", line 681, in included_pieces\n", - " pos = scope_pieces.index(self.executing_piece)\n", - " ^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/utils.py\", line 144, in cached_property_wrapper\n", - " value = obj.__dict__[self.func.__name__] = self.func(obj)\n", - " ^^^^^^^^^^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/stack_data/core.py\", line 660, in executing_piece\n", - " return only(\n", - " ^^^^^\n", - " File \"/Users/yayub/miniconda3/envs/dataexp/lib/python3.11/site-packages/executing/executing.py\", line 116, in only\n", - " raise NotOneValueFound('Expected one value, found 0')\n", - "executing.executing.NotOneValueFound: Expected one value, found 0\n" - ] - } - ], - "source": [ - "K_valid = K_tetra.copy()\n", - "\n", - "K_valid.add_node('E', [0.5, 0.289, 0.204])\n", - "K_valid.add_cell(['E', 'B'], dim=1)\n", - "\n", - "\n", - "\n", - "# Display cell counts\n", - "print(\"4D Simplex Cell Counts:\")\n", - "for dim in sorted(K_valid.cells.keys()):\n", - " print(f\" {dim}-cells: {len(K_valid.cells[dim])}\")\n", - "\n", - "# Plot (showing 3D projection)\n", - "fig = plt.figure(figsize=(10, 8))\n", - "ax = fig.add_subplot(111, projection='3d')\n", - "K_valid.plot(ax=ax, face_alpha=0.1, node_size=80)\n", - "ax.set_title('4D Simplex (5 vertices, cells up to dimension 4)')\n", - "plt.show()\n", - "\n", - "# Compute ECT\n", - "ect_4d = ECT(num_dirs=6, num_thresh=15)\n", - "result_4d = ect_4d.calculate(K_valid)\n", - "\n", - "fig, ax = plt.subplots(figsize=(10, 6))\n", - "result_4d.plot()\n", - "plt.title('ECT of 4D Simplex\\n(alternating sum includes all dimensions 0-4)')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Understanding ECT with Projection Visualization\n", - "\n", - "Let's visualize how the ECT computation works by showing projection values:" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Create a simple 2D example for visualization\n", - "K_viz = EmbeddedComplex()\n", - "\n", - "# Square with center point\n", - "K_viz.add_node('A', [-1, -1])\n", - "K_viz.add_node('B', [1, -1])\n", - "K_viz.add_node('C', [1, 1])\n", - "K_viz.add_node('D', [-1, 1])\n", - "K_viz.add_node('E', [0, 0]) # center\n", - "\n", - "# Add edges\n", - "edges = [('A', 'B'), ('B', 'C'), ('C', 'D'), ('D', 'A'), # boundary\n", - " ('A', 'E'), ('B', 'E'), ('C', 'E'), ('D', 'E')] # to center\n", - "K_viz.add_edges_from(edges)\n", - "\n", - "# Add triangular faces\n", - "faces = [['A', 'B', 'E'], ['B', 'C', 'E'], ['C', 'D', 'E'], ['D', 'A', 'E']]\n", - "for face in faces:\n", - " K_viz.add_face(face)\n", - "\n", - "# Visualization function\n", - "def plot_with_projections(K, theta, ax):\n", - " \"\"\"Plot complex with nodes colored by projection values\"\"\"\n", - " direction = np.array([np.sin(theta), -np.cos(theta)])\n", - " node_projections = np.dot(K.coord_matrix, direction)\n", - " \n", - " # Plot edges\n", - " for u, v in K.edges():\n", - " u_idx = K.node_to_index[u]\n", - " v_idx = K.node_to_index[v]\n", - " x = [K.coord_matrix[u_idx, 0], K.coord_matrix[v_idx, 0]]\n", - " y = [K.coord_matrix[u_idx, 1], K.coord_matrix[v_idx, 1]]\n", - " ax.plot(x, y, 'k-', alpha=0.5, linewidth=1)\n", - " \n", - " # Plot faces with transparency\n", - " for face_indices in K.cells.get(2, []):\n", - " face_coords = K.coord_matrix[list(face_indices)]\n", - " face_projection = np.max(node_projections[list(face_indices)])\n", - " ax.fill(face_coords[:, 0], face_coords[:, 1], \n", - " alpha=0.3, color=plt.cm.Blues(0.5))\n", - " \n", - " # Plot nodes colored by projection\n", - " scatter = ax.scatter(K.coord_matrix[:, 0], K.coord_matrix[:, 1], \n", - " c=node_projections, cmap='plasma', s=300, \n", - " edgecolors='black', linewidth=2, zorder=10)\n", - " \n", - " # Add node labels with projection values\n", - " for i, node in enumerate(K.node_list):\n", - " ax.annotate(f'{node}\\n({node_projections[i]:.2f})', \n", - " (K.coord_matrix[i, 0], K.coord_matrix[i, 1]),\n", - " ha='center', va='center', fontsize=9, fontweight='bold',\n", - " bbox=dict(boxstyle='round,pad=0.2', facecolor='white', alpha=0.8))\n", - " \n", - " # Direction arrow\n", - " ax.arrow(0, 0, direction[0]*0.7, direction[1]*0.7,\n", - " head_width=0.1, head_length=0.1, fc='red', ec='red', linewidth=2)\n", - " \n", - " ax.set_xlim(-2, 2)\n", - " ax.set_ylim(-2, 2)\n", - " ax.set_aspect('equal')\n", - " ax.grid(True, alpha=0.3)\n", - " ax.set_title(f'θ = {theta*180/np.pi:.0f}°')\n", - " \n", - " return scatter\n", - "\n", - "# Show projections in multiple directions\n", - "fig, axes = plt.subplots(2, 3, figsize=(15, 10))\n", - "axes = axes.flatten()\n", - "\n", - "thetas = np.linspace(0, 2*np.pi, 6, endpoint=False)\n", - "for ax, theta in zip(axes, thetas):\n", - " scatter = plot_with_projections(K_viz, theta, ax)\n", - "\n", - "# Add shared colorbar\n", - "fig.subplots_adjust(right=0.9)\n", - "cbar_ax = fig.add_axes([0.92, 0.15, 0.02, 0.7])\n", - "fig.colorbar(scatter, cax=cbar_ax, label='Node Projection Values')\n", - "\n", - "plt.suptitle('Complex Colored by Projection Values in Different Directions\\n' + \n", - " 'Red arrows show projection direction, faces use max vertex projection', \n", - " fontsize=14)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Comparing Graph vs. Complex ECT\n", - "\n", - "Let's compare ECT results for the same geometry with and without 2-cells:" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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4/PhxPfDAA3r77bdr5KTq3yJHjx5VXl5eteXyarN7925t2bKl3jkHgNNhAhqAUT169JB08sYlTW3mGnPszZs36+DBg2rXrp3r+W7duqlbt26SVO1qkJ/66RUGVW655Ra9+uqruvXWW5Wamqr4+Hg5HA5dfvnlTbpZx6nurH26q2B69uypjz76SFu2bNGYMWNq3abqpiq9evVyyzHT09OVlJSkN954Q2PGjNEbb7yh1q1bV1tfGgAAIJCZ7m83bdqk77//XsnJyW7d96n6w8b2jfXldDrVt29fPfXUU7V+/+fvc9OmTa4J0q+//lpXXHFFvY4zatQoLVy4UMXFxdqwYYPuu+8+9enTR82aNdPy5cu1fft2xcTEaODAgU16P57K16WXXqpVq1bp9ttv14ABAxQTEyOn06kpU6Y0+N8iTqdTkyZN0h133FHr96v+rQQA9cUSHACMOu+88yRJb7zxhtePXXWVc9XH1prqvffe07Rp0/Tkk0/qkksu0aRJkzRq1CidOHGi1u13795d7euCggIdPnxYHTt2dEs8Ve/vtddeq/X7lZWVeuutt5SQkKCRI0e65ZjBwcG68sor9d577yknJ0cfffSRrrjiilM22gAAAIHGZH/bkGN36NBBkrRz584a39u5c6fr++7UmP63S5cuOn78uCZMmKCJEyfWePz0Cu7CwkJNnz5dvXr10vXXX6/HHntM69atq1dso0eP1oEDB/T222+rsrJSI0aMUFBQkEaNGqXly5dr+fLlGjFixGn72lPdTNGTcnJytHDhQt1111164IEHdNFFF2nSpEnq3Llzte0SExMVFxenrVu31rm/Ll26qKCgoNZ8T5w4sdZPaAJAXZiABmBUamqqpkyZopdfftl1B+ufKisr0//7f/+vQfs8cOCAduzYcdrtLr30UvXq1UsPPfSQ1qxZU+s2DbkSITg4uMb2f//731VZWVnr9i+++KLKy8tdXz///POqqKjQWWedVe9j1mXEiBGaOHGiXn31Vf33v/+t8f177rlHu3bt0h133FHrFd2NddVVVyknJ0c33HCDCgoKTrmMCQAAQCAy2d9ecskl6tu3rx5++GGtXr26xvfz8/N1zz33SJKGDBmiVq1a6YUXXlBpaalrmy+++ELbt2/XOeec06AY66Mx/e+ll16qgwcP6qWXXqrxveLiYhUWFrq+vvPOO3XgwAH9+9//1lNPPaWOHTtq2rRp1d7fqVRdrf7oo4+qX79+io+Pdz2/cOFCrV+/vl5XtEdHR5/yAhRPqZoU//m/RZ555plqXwcFBenCCy/Up59+qvXr19fYT9XrL730Uq1evVoZGRk1tjlx4oQqKircFDkAu2AJDgAe9cUXX9TaLI8YMcL1F/nXXntNkydP1sUXX6zzzjtPEyZMUHR0tHbv3q23335bhw8f1hNPPFHvY06dOlVLly497eRxaGioPvzwQ6Wnp2vUqFG6+OKLNXr0aEVHR+vgwYP65JNPdODAgXo33+eee65ef/11xcfHq1evXlq9erUWLFigFi1a1Lp9WVmZJkyYoEsvvVQ7d+7Uc889p1GjRun888+v93s9nddee00TJkzQBRdcoCuvvFKjR49WaWmpPvjgAy1ZskSXXXaZbr/9drcdT5IGDhyoPn36uG4YM2jQILfuHwAAwCRf728/+OADTZw4UWPGjNGll16qkSNHKjQ0VNu2bXN9+u3hhx9WaGioHn30UU2fPl1paWm64oorlJWVpb/+9a/q2LGjbrvttoYlph4a0/9eddVVeuedd/Tb3/5Wixcv1siRI1VZWakdO3bonXfeUUZGhoYMGaJFixbpueee08yZM13956uvvqqxY8fqT3/6kx577LE6Y+vatatat26tnTt36pZbbnE9P2bMGN15552SVK8J6MGDB+v555/Xn//8Z3Xt2lWtWrVy3TDRU+Li4jRmzBg99thjKi8vV7t27TRv3jzt3bu3xraPPPKI5s2bp7S0NF1//fXq2bOnDh8+rHfffVcrVqxQs2bNdPvtt+uTTz7Rueeeq6uvvlqDBw9WYWGhvv76a7333nvat29fretQA8CpMAENwKPuu+++Wp9/9dVXXQ16YmKiVq1apeeee05z5szRPffco7KyMnXo0EHnn3++/vCHP3gsvm7dumnz5s3629/+pg8//FBffPGFysrKlJSUpJSUFM2cOdO1lMXp/PWvf1VwcLDefPNNlZSUaOTIkVqwYIHS09Nr3f4f//iH3nzzTd13330qLy/XFVdcob/97W9u/dhemzZttHbtWj355JN699139f777yskJET9+vXT7NmzNXXqVI98THDq1Km64447uPkgAAAIOL7e33bt2lWbN2/W008/rQ8//FAfffSRnE6nunbtqmuvvVa///3vXdteffXVioqK0l/+8hfdeeedio6O1kUXXaRHH33UIzdQbEz/GxQUpI8++khPP/20XnvtNX344YeKiopS586d9Yc//EHdunVTfn6+fvOb32jgwIGuK7ylkxPGf/jDH/Tkk0/q4osv1vDhw+uMb/To0Xr33Xc1atQo13ODBw9WVFSUKioqlJKSctr3eN9992n//v167LHHlJ+fr7S0NI9PQEvSW2+9pVtuuUXPPvusLMvS5MmT9cUXX6ht27bVtmvXrp2+/PJL/elPf9Kbb76pvLw8tWvXTmeddZaioqIkSVFRUVq6dKkeeeQRvfvuu3rttdcUFxenbt266YEHHnBdHQ4A9eWw3HVnAABAvcyePVvTp0/XunXr6ryDuj/761//qttuu0379u1jjTgAAACbs0P/CwA4NdaABgC4lWVZ+te//qW0tDQmnwEAAAAAsDmW4AAAuEVhYaE++eQTLV68WF9//bU+/vhj0yEBAAAAAADDmIAGALjF0aNHdeWVV6pZs2b6v//7P7feTBEAAAAAAPgn1oAGAAAAAAAAAHgEa0ADAAAAAAAAADyCCWgAAAAAAAAAgEcwAQ1Ajz32mHr06CGn02k6FJ90//33y+FwmA7DqCVLlsjhcGjJkiVG4/jmm28UEhKirVu3Go0DAAD4JvrautHX+k5f6y2PP/64OnfurODgYA0YMMB0OHW6/PLLdemll5oOA4AHMAEN2FxeXp4effRR3XnnnQoKsu+QUFRUpPvvv982jai/6tWrl8455xzdd999pkMBAAA+hr72JPpaVJk3b57uuOMOjRw5Uq+++qoeeeQR0yHV6c4779T777+vr776ynQoANzMvmdlAJKkV155RRUVFbriiitMh2JUUVGRHnjggVob9XvvvVfFxcXeDwq1+u1vf6sPP/xQ3333nelQAACAD6GvPYm+FlUWLVqkoKAg/etf/9LUqVN19tlnmw6pTgMHDtSQIUP05JNPmg4FgJsxAQ3Y3Kuvvqrzzz9fERERpkMxwul0qqSkpM5tQkJCbJsfXzRx4kQlJCTo3//+t+lQAACAD6Gvpa8NRFVLhuzbt6/Brz1y5IgiIyMVFhbm/sA85NJLL9UHH3yggoIC06EAcCMmoAEb27t3r7Zs2aKJEye6ntu3b59CQ0PVq1cvffLJJ9W2r1ozbvHixR6Prby8XM2bN9f06dNrfC8vL08RERH6f//v/7meKy0t1cyZM9W1a1eFh4crOTlZd9xxh0pLS6u91uFw6Oabb9abb76p3r17Kzw8XC+88IISExMlSQ888IAcDoccDofuv/9+SadeK++NN97QsGHDFBUVpYSEBI0ZM0bz5s2rts0XX3yh0aNHKzo6WrGxsTrnnHO0bdu2attkZmZq+vTpat++vcLDw9WmTRtdcMEFjWoy63Lw4EH95je/UVJSksLDw9W7d2+98sorNbb74YcfdOGFFyo6OlqtWrXSbbfdViOPVZ599ll17txZkZGRGjZsmJYvX66xY8dq7Nix1barb33mz5+vUaNGqVmzZoqJiVH37t31f//3f9W2CQ0N1dixY/Xxxx83LSEAACBg0NfS1/pjX+tJDodDr776qgoLC10/B7Nnz5Z08o8148ePV6tWrRQeHq5evXrp+eefr3U/X3zxhdLS0hQbG6u4uDgNHTpUb731VrVtvvzyS02ZMkXx8fGKiopSWlqaVq5cWW2b/Px83XrrrerYsaPCw8PVqlUrTZo0SRs3bqy23aRJk1RYWKj58+e7LxkAjAsxHQAAc1atWiVJGjRokOu5xMREPffcc3ruuef0q1/9SgcOHFBCQoJyc3P117/+VaNGjdK4cePq3G92dna9jh8bG6vw8PBavxcaGqqLLrpIH3zwgf75z39W+6v9Rx99pNLSUl1++eWSTl7tcf7552vFihW6/vrr1bNnT3399dd6+umntWvXLn300UfV9r1o0SK98847uvnmm9WyZUv1799fzz//vH73u9/poosu0sUXXyxJ6tev3yljf+CBB3T//fdrxIgRevDBBxUWFqYvv/xSixYt0uTJkyVJr7/+uqZNm6b09HQ9+uijKioq0vPPP69Ro0Zp06ZN6tixoyTpF7/4hbZt26ZbbrlFHTt21JEjRzR//nwdOHDAtU1TZWVlafjw4a5/qCQmJuqLL77QNddco7y8PN16662SpOLiYk2YMEEHDhzQ73//e7Vt21avv/66Fi1aVGOfzz//vG6++WaNHj1at912m/bt26cLL7xQCQkJat++vWu7+tZn27ZtOvfcc9WvXz89+OCDCg8P17ffflujeZWkwYMH6+OPP1ZeXp7i4uLckiMAAOC/6Gvpa/21r/WU119/XS+++KLWrl2rl19+WZI0YsQI1/vt3bu3zj//fIWEhOjTTz/VjTfeKKfTqZtuusm1j9mzZ+s3v/mNevfurbvvvlvNmjXTpk2bNHfuXF155ZWSTv4MnnXWWRo8eLBmzpypoKAg1wT38uXLNWzYMEknl9F77733dPPNN6tXr146duyYVqxYoe3bt1f7ve3Vq5ciIyO1cuVKXXTRRd5KFwBPswDY1r333mtJsvLz82t8b//+/VZQUJD18ssvW5ZlWQ888IAlyZo3b95p9yupXo9XX321zv1kZGRYkqxPP/202vNnn3221blzZ9fXr7/+uhUUFGQtX7682nYvvPCCJclauXJltdiCgoKsbdu2Vdv26NGjliRr5syZNeKYOXOm9dPhcvfu3VZQUJB10UUXWZWVldW2dTqdlmVZVn5+vtWsWTPruuuuq/b9zMxMKz4+3vV8Tk6OJcl6/PHH68xFU11zzTVWmzZtrOzs7GrPX3755VZ8fLxVVFRkWZZlPfPMM5Yk65133nFtU1hYaHXt2tWSZC1evNiyLMsqLS21WrRoYQ0dOtQqLy93bTt79mxLkpWWluZ6rr71efrppy1J1tGjR0/7ft566y1LkvXll182KA8AACAw0df+iL7Wv/ra01m8eLElydq7d2+DXztt2jQrOjq6xvNVOfqp9PT0aj+LJ06csGJjY62UlBSruLi42rZVPxtOp9M688wzrfT0dNdzVfvv1KmTNWnSJNdz8fHx1k033VSvuLt162adddZZ9doWgH9gCQ7Axo4dO6aQkBDFxMTU+N4ZZ5yhtLQ0zZkzR3l5eXrmmWc0fPhwTZo06bT7nT9/fr0e6enpde5n/PjxatmypebMmeN6LicnR/Pnz9dll13meu7dd99Vz5491aNHD2VnZ7se48ePl6QaH61MS0tTr169Tvs+TuWjjz6S0+nUfffdV+MO61UfaZw/f75OnDihK664olpMwcHBSklJccVUtSbbkiVLlJOT0+iY6mJZlt5//32dd955siyrWjzp6enKzc11ffTt888/V5s2bXTJJZe4Xh8VFaXrr7++2j7Xr1+vY8eO6brrrlNIyI8fpvnVr36lhISEatvWtz7NmjWTJH388cdyOp11vqeqY9T3qiQAABDY6Gsbh77WfF/7c7m5udX2nZubK+nkz8tPn2/KGsmRkZE1jpeWlqY9e/a4jjd//nzl5+frrrvuqrFueNXPxubNm7V7925deeWVOnbsmCu2wsJCTZgwQcuWLXO9/2bNmunLL7/UoUOHThtfQkICfT4QYFiCA8ApXXbZZbrpppt07733KicnR/fdd1+9XvfTtfeaIiQkRL/4xS/01ltvqbS0VOHh4frggw9UXl5erVHfvXu3tm/f7lrv7ueOHDlS7etOnTo1Ka7vvvtOQUFBdTb7u3fvliRXM/pzVctGhIeH69FHH9Uf//hHJSUlafjw4Tr33HM1depUtW7d+pT7Ly4udjWHVU61/dGjR3XixAm9+OKLevHFF2vdpipH+/fvV9euXWusDdi9e/dqX+/fv1+S1LVr12rPh4SE1Ph4ZX3rc9lll+nll1/Wtddeq7vuuksTJkzQxRdfrEsuuaTGP4gsy5KkWtcwBAAA+Dn62trR15rva3/uggsu0NKlS2s8/9NlKiRp2rRprjWdG2rlypWaOXOmVq9eraKiomrfy83NVXx8vL777jtJUp8+fU65n6qfjWnTpp1ym9zcXCUkJOixxx7TtGnTlJycrMGDB+vss8/W1KlT1blz5xqvsSyLPh8IMExAAzbWokULVVRUKD8/X7GxsTW+/4tf/EI333yz/v73v2vIkCE666yz6rXfzMzMem0XHx9f7a/vtbn88sv1z3/+U1988YUuvPBCvfPOO+rRo4f69+/v2sbpdKpv37566qmnat1HcnJyta9Pd0x3qPpL/+uvv15rA/3TqytuvfVWnXfeefroo4+UkZGhP/3pT5o1a5YWLVqkgQMH1rr/OXPm1LiRTdWk7Kli+fWvf33K5rCudQGbqr71iYyM1LJly7R48WJ99tlnmjt3rubMmaPx48dr3rx5Cg4Odr2m6qqali1beixuAADgP+hrPYe+tvrx3d3X/tyTTz5Z7Qryr776Sv/v//0/vfHGG0pKSnI937Zt20a9h++++04TJkxQjx499NRTTyk5OVlhYWH6/PPP9fTTTzfoiu2qbR9//HENGDCg1m2qPpVw6aWXavTo0frwww81b948Pf7443r00Uf1wQcf1Ph9zMnJ0Zlnntmo9wfANzEBDdhYjx49JJ28a3htjVrLli2VlpamhQsX6k9/+lO999umTZt6bffqq6/q6quvrnObMWPGqE2bNpozZ45GjRqlRYsW6Z577qm2TZcuXfTVV19pwoQJjf5LeUNe16VLFzmdTn3zzTenbLS6dOkiSWrVqlW9rpzp0qWL/vjHP+qPf/yjdu/erQEDBujJJ5/UG2+8Uev26enp9b4zdGJiomJjY1VZWXnaWDp06KCtW7fWuOpg586dNbaTpG+//bbazXsqKiq0b9++aj9PDalPUFCQJkyYoAkTJuipp57SI488onvuuUeLFy+uFvvevXsVFBSkbt26nT4BAAAg4NHX/oi+9iR/6Wt/bvDgwdW+rprgHzlypFtu5Pjpp5+qtLRUn3zyic444wzX8z9f3qWq7lu3bq1xdfjPt4mLi6vXz0abNm1044036sYbb9SRI0c0aNAgPfzww9UmoCsqKvT999/r/PPPb/B7A+C7WAMasLHU1FRJJ9c9q01xcbG2bdsmqeZHvurirrXypJON2yWXexhNxwAAWhBJREFUXKJPP/1Ur7/+uioqKqp9TFE6+df0gwcP6qWXXqr1PRQWFp72OFFRUZKkEydOnHbbCy+8UEFBQXrwwQdrXCFQdbVGenq64uLi9Mgjj6i8vLzGPo4ePSpJKioqUklJSbXvdenSRbGxsSotLT1lDG3atNHEiROrPU4lODhYv/jFL/T+++9r69atp4xFks4++2wdOnRI7733nuu5oqKiGh9xHDJkiFq0aKGXXnpJFRUVrufffPPNGmv+1bc+x48fr/H9qn8I/TwXGzZsUO/evRUfH3+qtw0AAGyEvvZH9LUn+Utf621VV1//9Crz3Nxcvfrqq9W2mzx5smJjYzVr1qwada167eDBg9WlSxc98cQTta5JXVWPysrKGsustGrVSm3btq2Rj2+++UYlJSUaMWJEI98hAF/EFdCAjXXu3Fl9+vTRggUL9Jvf/KbG91966SXXxw7fe+893XrrrfXar7vWyqty2WWX6e9//7tmzpypvn37qmfPntW+f9VVV+mdd97Rb3/7Wy1evFgjR45UZWWlduzYoXfeeUcZGRkaMmRInceIjIxUr169NGfOHHXr1k3NmzdXnz59al3zrGvXrrrnnnv00EMPafTo0br44osVHh6udevWqW3btpo1a5bi4uL0/PPP66qrrtKgQYN0+eWXKzExUQcOHNBnn32mkSNH6h//+Id27dqlCRMm6NJLL1WvXr0UEhKiDz/8UFlZWbr88svdlsO//OUvWrx4sVJSUnTdddepV69eOn78uDZu3KgFCxa4muTrrrtO//jHPzR16lRt2LBBbdq00euvv+76h0yVsLAw3X///brllls0fvx4XXrppdq3b59mz56tLl26VLsipL71efDBB7Vs2TKdc8456tChg44cOaLnnntO7du316hRo1z7Ky8v19KlS3XjjTe6LT8AAMC/0df+iL7Wf/paEyZPnqywsDCdd955uuGGG1RQUKCXXnpJrVq10uHDh13bxcXF6emnn9a1116roUOH6sorr1RCQoK++uorFRUV6d///reCgoL08ssv66yzzlLv3r01ffp0tWvXTgcPHtTixYsVFxenTz/9VPn5+Wrfvr0uueQS9e/fXzExMVqwYIHWrVunJ598slp88+fPV1RUVL1uEgrAj1gAbO2pp56yYmJirKKiomrPl5SUWO3atbO6d+9unXvuudbw4cMNRWhZTqfTSk5OtiRZf/7zn2vdpqyszHr00Uet3r17W+Hh4VZCQoI1ePBg64EHHrByc3Nd20mybrrpplr3sWrVKmvw4MFWWFiYJcmaOXOmZVmWNXPmTKu24fKVV16xBg4c6DpeWlqaNX/+/GrbLF682EpPT7fi4+OtiIgIq0uXLtbVV19trV+/3rIsy8rOzrZuuukmq0ePHlZ0dLQVHx9vpaSkWO+8805jUlWnrKws66abbrKSk5Ot0NBQq3Xr1taECROsF198sdp2+/fvt84//3wrKirKatmypfWHP/zBmjt3riXJWrx4cbVt//a3v1kdOnSwwsPDrWHDhlkrV660Bg8ebE2ZMqXadvWpz8KFC60LLrjAatu2rRUWFma1bdvWuuKKK6xdu3ZV29cXX3xhSbJ2797t9hwBAAD/RV/7I/rak3y9r62PxYsXW5KsvXv3Nvi106ZNs6Kjo2s8/8knn1j9+vWzIiIirI4dO1qPPvqo9corr9R6nE8++cQaMWKEFRkZacXFxVnDhg2z/vOf/1TbZtOmTdbFF19stWjRwgoPD7c6dOhgXXrppdbChQsty7Ks0tJS6/bbb7f69+9vxcbGWtHR0Vb//v2t5557rkZsKSkp1q9//esGv1cAvs1hWadY3R+ALeTm5qpz58567LHHdM0117ief/7553XjjTfqtddeU0hIiK688krt27fPtUYaUBun06nExERdfPHFtX400R0uvPBCORwOffjhhx7ZPwAA8E/0tXAnb/S1qG7z5s0aNGiQNm7ceMo1yQH4J9aABmwuPj5ed9xxhx5//HHXum/l5eX6y1/+oq5du+rKK6/U+eefr6ioKL3++uuGo4UvKSkpqXGH8tdee03Hjx/X2LFjPXLM7du367///a8eeughj+wfAAD4L/paNJaJvhY1/eUvf9Ell1zC5DMQgLgCGkANL7/8sq677jq98sormj59uiRp6tSpeu+993THHXfowgsvpCmAlixZottuu02//OUv1aJFC23cuFH/+te/1LNnT23YsEFhYWGmQwQAADZHX4v6oK8FAM9iAhpANRUVFerevbssy9KuXbsUEnLyXqVZWVm65pprtHjxYt1+++26//77zQYK4/bt26ff//73Wrt2rY4fP67mzZvr7LPP1l/+8he1atXKdHgAAMDm6GtRX/S1AOBZTEADAADAJy1btkyPP/64NmzYoMOHD+vDDz/UhRdeWOdrlixZohk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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ECT value ranges:\n", - "Graph only: [0, 1]\n", - "With face: [0, 1]\n", - "\n", - "The face contributes +1 to the Euler characteristic when included.\n" - ] - } - ], - "source": [ - "# Create two versions: graph only vs. complex with faces\n", - "K_graph = EmbeddedComplex()\n", - "K_complex = EmbeddedComplex()\n", - "\n", - "# Same vertices and edges for both\n", - "vertices = {'A': [0, 0], 'B': [2, 0], 'C': [1, 1.732]}\n", - "edges = [('A', 'B'), ('B', 'C'), ('C', 'A')]\n", - "\n", - "for K in [K_graph, K_complex]:\n", - " for name, coord in vertices.items():\n", - " K.add_node(name, coord)\n", - " K.add_edges_from(edges)\n", - "\n", - "# Add face only to the complex version\n", - "K_complex.add_face(['A', 'B', 'C'])\n", - "\n", - "# Compute ECT for both\n", - "ect = ECT(num_dirs=20, num_thresh=30)\n", - "result_graph = ect.calculate(K_graph)\n", - "result_complex = ect.calculate(K_complex)\n", - "\n", - "# Plot comparison\n", - "fig, axes = plt.subplots(2, 2, figsize=(15, 10))\n", - "\n", - "# Visualizations\n", - "K_graph.plot(ax=axes[0,0], with_labels=True, node_size=400)\n", - "axes[0,0].set_title('Graph Only (no 2-cells)')\n", - "\n", - "K_complex.plot(ax=axes[0,1], with_labels=True, node_size=400, \n", - " face_alpha=0.3, face_color='lightblue')\n", - "axes[0,1].set_title('Complex with 2-cell (face)')\n", - "\n", - "# ECT comparisons\n", - "result_graph.plot(ax=axes[1,0])\n", - "axes[1,0].set_title('ECT: Graph Only\\n(χ = vertices - edges)')\n", - "\n", - "result_complex.plot(ax=axes[1,1])\n", - "axes[1,1].set_title('ECT: Complex with Face\\n(χ = vertices - edges + faces)')\n", - "\n", - "plt.tight_layout()\n", - "plt.show()\n", - "\n", - "# Show numerical difference\n", - "print(\"ECT value ranges:\")\n", - "print(f\"Graph only: [{result_graph.min()}, {result_graph.max()}]\")\n", - "print(f\"With face: [{result_complex.min()}, {result_complex.max()}]\")\n", - "print(f\"\\nThe face contributes +1 to the Euler characteristic when included.\")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "dataexp", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/docs/notebooks/Tutorial-ExactECT.html b/docs/notebooks/Tutorial-ExactECT.html deleted file mode 100644 index 0d1cf12..0000000 --- a/docs/notebooks/Tutorial-ExactECT.html +++ /dev/null @@ -1,337 +0,0 @@ - - - - - - - 3.2. Tutorial for exact ECT computation — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - - - - - - -
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3.2. Tutorial for exact ECT computation

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Warning: This is a work in progress. Proceed at your own risk.

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The goal of this section is so show available tools for exact computation of the ECT.

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from ect import ECT, EmbeddedComplex, create_example_graph
-
-import matplotlib.pyplot as plt
-from matplotlib.patches import Circle
-import numpy as np
-import networkx as nx
-
-# Note: EmbeddedGraph and EmbeddedCW are now unified into EmbeddedComplex
-# For backward compatibility, you can still use:
-# from ect import EmbeddedGraph, EmbeddedCW
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We can use the EmbeddedComplex class (which unifies the old EmbeddedGraph and EmbeddedCW classes) to find the angle normal to any pair of vertices in the graph, whether or not there is a connecting edge. Setting angle_labels_circle=True in the plotting command will try to draw these on the circle. Note that this doesn’t tend to do well for large inputs, but can be helpful for small examples.

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# Super simple graph using the unified EmbeddedComplex class
-G = EmbeddedComplex()
-G.add_node('A', 0,0)
-G.add_node('B', 1,0)
-G.add_node('C', 2,1)
-G.add_node('D', 1,2)
-G.add_edge('A', 'B')
-G.add_edge('B', 'D')
-G.add_edge('D', 'C')
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-fig, ax = plt.subplots()
-G.plot(ax = ax)
-G.plot_angle_circle(ax = ax)
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G = create_example_graph(centered=True)
-G.rescale_to_unit_disk()
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-fig, ax = plt.subplots()
-G.plot(ax = ax)
-G.plot_angle_circle(ax = ax)
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We can extract the information directly for use in computation.

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# If return type is `matrix`, the function returns the matrix of angles and the labels of the angles in the order of the rows/columns in the matrix
-M,Labels = G.get_normal_angle_matrix()  # Updated method name
-print(M)
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-plt.matshow(M)
-plt.xticks(range(len(Labels)), Labels)
-plt.yticks(range(len(Labels)), Labels)
-plt.colorbar()
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This can also be returned as a dictionary, with keys given by angles (note the negative angle is not repeated), and value a list of the pairs of vertices associated. Note that in the case of more than one pair of vertices having the same normal angle, it is given as a list of all pairs.

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angles_dict = G.get_normals_dict()
-angles_dict
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-{5.497787143782138: [('A', 'B'), ('A', 'F'), ('B', 'F')],
- 5.608444364956034: [('A', 'C')],
- 5.81953769817878: [('A', 'D'), ('F', 'C')],
- 5.034139534781332: [('A', 'E')],
- 5.695182703632018: [('B', 'C')],
- 0.0: [('B', 'D'), ('E', 'F')],
- 3.9269908169872414: [('B', 'E'), ('D', 'F')],
- 2.0344439357957027: [('C', 'D')],
- 2.896613990462929: [('C', 'E')],
- 3.4633432079864352: [('D', 'E')]}
-
-
-

We can also get it to return the dictionary with rounded values, as well as to have it include all the opposite angles.

-
-
[6]:
-
-
-
G.get_normals_dict(opposites = True,
-                   num_rounding_digits=2)
-
-
-
-
-
[6]:
-
-
-
-
-{5.5: [('A', 'B'), ('A', 'F'), ('B', 'F')],
- 5.61: [('A', 'C')],
- 5.82: [('A', 'D'), ('F', 'C')],
- 5.03: [('A', 'E')],
- 5.7: [('B', 'C')],
- 0.0: [('B', 'D'), ('E', 'F')],
- 3.93: [('B', 'E'), ('D', 'F')],
- 2.03: [('C', 'D')],
- 2.9: [('C', 'E')],
- 3.46: [('D', 'E')],
- 2.36: [('A', 'B'), ('A', 'F'), ('B', 'F')],
- 2.47: [('A', 'C')],
- 2.68: [('A', 'D'), ('F', 'C')],
- 1.89: [('A', 'E')],
- 2.56: [('B', 'C')],
- 3.14: [('B', 'D'), ('E', 'F')],
- 0.79: [('B', 'E'), ('D', 'F')],
- 5.17: [('C', 'D')],
- 6.04: [('C', 'E')],
- 0.32: [('D', 'E')]}
-
-
-
- - -
-
- -
-
-
-
- - - - - - - \ No newline at end of file diff --git a/docs/notebooks/Tutorial-ExactECT.ipynb b/docs/notebooks/Tutorial-ExactECT.ipynb deleted file mode 100644 index 7ec6520..0000000 --- a/docs/notebooks/Tutorial-ExactECT.ipynb +++ /dev/null @@ -1,215 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Tutorial for exact ECT computation \n", - "\n", - "*Warning: This is a work in progress. Proceed at your own risk.*\n", - "\n", - "The goal of this section is so show available tools for exact computation of the ECT. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from ect import ECT, EmbeddedComplex, create_example_graph\n", - "\n", - "import matplotlib.pyplot as plt\n", - "from matplotlib.patches import Circle\n", - "import numpy as np\n", - "import networkx as nx\n", - "\n", - "# Note: EmbeddedGraph and EmbeddedCW are now unified into EmbeddedComplex\n", - "# For backward compatibility, you can still use:\n", - "# from ect import EmbeddedGraph, EmbeddedCW" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can use the `EmbeddedComplex` class (which unifies the old `EmbeddedGraph` and `EmbeddedCW` classes) to find the angle normal to any pair of vertices in the graph, whether or not there is a connecting edge. Setting `angle_labels_circle=True` in the plotting command will try to draw these on the circle. Note that this doesn't tend to do well for large inputs, but can be helpful for small examples." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Super simple graph using the unified EmbeddedComplex class\n", - "G = EmbeddedComplex()\n", - "G.add_node('A', 0,0)\n", - "G.add_node('B', 1,0)\n", - "G.add_node('C', 2,1)\n", - "G.add_node('D', 1,2)\n", - "G.add_edge('A', 'B')\n", - "G.add_edge('B', 'D')\n", - "G.add_edge('D', 'C')\n", - "\n", - "fig, ax = plt.subplots()\n", - "G.plot(ax = ax)\n", - "G.plot_angle_circle(ax = ax)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "G = create_example_graph(centered=True)\n", - "G.rescale_to_unit_disk()\n", - "\n", - "\n", - "fig, ax = plt.subplots()\n", - "G.plot(ax = ax)\n", - "G.plot_angle_circle(ax = ax)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can extract the information directly for use in computation. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# If return type is `matrix`, the function returns the matrix of angles and the labels of the angles in the order of the rows/columns in the matrix \n", - "M,Labels = G.get_normal_angle_matrix() # Updated method name\n", - "print(M)\n", - "\n", - "plt.matshow(M)\n", - "plt.xticks(range(len(Labels)), Labels)\n", - "plt.yticks(range(len(Labels)), Labels)\n", - "plt.colorbar()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This can also be returned as a dictionary, with keys given by angles (note the negative angle is not repeated), and value a list of the pairs of vertices associated. Note that in the case of more than one pair of vertices having the same normal angle, it is given as a list of all pairs. " - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{5.497787143782138: [('A', 'B'), ('A', 'F'), ('B', 'F')],\n", - " 5.608444364956034: [('A', 'C')],\n", - " 5.81953769817878: [('A', 'D'), ('F', 'C')],\n", - " 5.034139534781332: [('A', 'E')],\n", - " 5.695182703632018: [('B', 'C')],\n", - " 0.0: [('B', 'D'), ('E', 'F')],\n", - " 3.9269908169872414: [('B', 'E'), ('D', 'F')],\n", - " 2.0344439357957027: [('C', 'D')],\n", - " 2.896613990462929: [('C', 'E')],\n", - " 3.4633432079864352: [('D', 'E')]}" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "angles_dict = G.get_normals_dict()\n", - "angles_dict" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can also get it to return the dictionary with rounded values, as well as to have it include all the opposite angles. " - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{5.5: [('A', 'B'), ('A', 'F'), ('B', 'F')],\n", - " 5.61: [('A', 'C')],\n", - " 5.82: [('A', 'D'), ('F', 'C')],\n", - " 5.03: [('A', 'E')],\n", - " 5.7: [('B', 'C')],\n", - " 0.0: [('B', 'D'), ('E', 'F')],\n", - " 3.93: [('B', 'E'), ('D', 'F')],\n", - " 2.03: [('C', 'D')],\n", - " 2.9: [('C', 'E')],\n", - " 3.46: [('D', 'E')],\n", - " 2.36: [('A', 'B'), ('A', 'F'), ('B', 'F')],\n", - " 2.47: [('A', 'C')],\n", - " 2.68: [('A', 'D'), ('F', 'C')],\n", - " 1.89: [('A', 'E')],\n", - " 2.56: [('B', 'C')],\n", - " 3.14: [('B', 'D'), ('E', 'F')],\n", - " 0.79: [('B', 'E'), ('D', 'F')],\n", - " 5.17: [('C', 'D')],\n", - " 6.04: [('C', 'E')],\n", - " 0.32: [('D', 'E')]}" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "G.get_normals_dict(opposites = True, \n", - " num_rounding_digits=2)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "base", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.7" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/docs/objects.inv b/docs/objects.inv deleted file mode 100644 index c3b0eb1..0000000 Binary files a/docs/objects.inv and /dev/null differ diff --git a/docs/py-modindex.html b/docs/py-modindex.html deleted file mode 100644 index 0490d57..0000000 --- a/docs/py-modindex.html +++ /dev/null @@ -1,241 +0,0 @@ - - - - - - Python Module Index — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - - - - -
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- - - - - - - \ No newline at end of file diff --git a/docs/search.html b/docs/search.html deleted file mode 100644 index eaf6852..0000000 --- a/docs/search.html +++ /dev/null @@ -1,201 +0,0 @@ - - - - - - Search — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - - - - -
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- - - - - - - - - - - - \ No newline at end of file diff --git a/docs/searchindex.js b/docs/searchindex.js deleted file mode 100644 index 2b222a5..0000000 --- a/docs/searchindex.js +++ /dev/null @@ -1 +0,0 @@ -Search.setIndex({"alltitles": {"API Reference": [[4, "module-ect.embed_complex"], [13, "api-reference"]], "Acknowledgements": [[9, "Acknowledgements"]], "Adding Cells of Arbitrary Dimension": [[10, "Adding-Cells-of-Arbitrary-Dimension"]], "Architecture": [[13, "architecture"]], "Authors": [[5, "authors"]], "Base Classes": [[13, "module-ect.validation.base"]], "Basic Usage": [[4, "basic-usage"]], "Basic Usage: Creating Simple Complexes": [[10, "Basic-Usage:-Creating-Simple-Complexes"]], "Citing": [[0, null]], "Code style and formatting": [[1, "code-style-and-formatting"]], "Comparing Graph vs. Complex ECT": [[10, "Comparing-Graph-vs.-Complex-ECT"]], "Conclusion": [[1, "conclusion"]], "Contact Information": [[5, "contact-information"]], "Contents:": [[5, null], [12, null]], "Contributing Guidelines": [[1, "contributing-guidelines"]], "Contributing to the ect Package": [[1, null]], "Custom Validation Rules": [[13, "custom-validation-rules"]], "Dependencies": [[5, "dependencies"]], "Description": [[5, "description"]], "Directions": [[2, null]], "Documentation and tutorials": [[5, "documentation-and-tutorials"]], "Documentation guidelines": [[1, "documentation-guidelines"]], "ECT Computation with Higher-Dimensional Cells": [[10, "ECT-Computation-with-Higher-Dimensional-Cells"]], "ECT on Graphs": [[3, null]], "ECT on Matisse\u2019s \u201cThe Parakeet and the Mermaid\u201d": [[9, null]], "Embedded Complex": [[4, null]], "Example 1: Graph (1-skeleton)": [[10, "Example-1:-Graph-(1-skeleton)"]], "GPL-3.0 License": [[7, null]], "Geometric Rules (Optional)": [[13, "geometric-rules-optional"]], "Getting Started": [[1, "getting-started"], [5, "getting-started"]], "Installation": [[6, null]], "Installing": [[5, "installing"]], "Installing ect": [[6, "installing-ect"]], "Issue tracking and pull requests": [[1, "issue-tracking-and-pull-requests"]], "Key Features": [[4, "key-features"]], "License": [[5, "license"]], "Main Module": [[13, "module-ect.validation"]], "Overview": [[4, "overview"], [13, "overview"]], "Prerequisites": [[6, "prerequisites"]], "Structural Rules (Always Enforced)": [[13, "structural-rules-always-enforced"]], "Table of Contents": [[5, "table-of-contents"], [8, null]], "Testing guidelines": [[1, "testing-guidelines"]], "Tutorial for exact ECT computation": [[11, null]], "Tutorial: ECT for Embedded Cell Complexes": [[10, null]], "Tutorials": [[12, null]], "Understanding ECT with Projection Visualization": [[10, "Understanding-ECT-with-Projection-Visualization"]], "Uninstalling ect": [[6, "uninstalling-ect"]], "Usage": [[13, "usage"]], "Validation Rules": [[13, "validation-rules"], [13, "id1"]], "Validation System": [[13, null]], "Validator": [[13, "module-ect.validation.validator"]], "ect: Euler Characteristic Transform in Python": [[5, null]]}, "docnames": ["citing", "contributing", "directions", "ect_on_graphs", "embed_complex", "index", "installation", "license", "modules", "notebooks/Matisse/example_matisse", "notebooks/Tutorial-EmbeddedComplex", "notebooks/Tutorial-ExactECT", "tutorials", "validation"], "envversion": {"nbsphinx": 4, "sphinx": 62, "sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx.ext.intersphinx": 1, "sphinx.ext.todo": 2, "sphinx.ext.viewcode": 1}, "filenames": ["citing.rst", "contributing.rst", "directions.md", "ect_on_graphs.md", "embed_complex.md", "index.rst", "installation.rst", "license.md", "modules.rst", "notebooks/Matisse/example_matisse.ipynb", "notebooks/Tutorial-EmbeddedComplex.ipynb", "notebooks/Tutorial-ExactECT.ipynb", 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Tutorials — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - - - - - -
- - -
- -
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- - - - - - - \ No newline at end of file diff --git a/docs/validation.html b/docs/validation.html deleted file mode 100644 index c0a321a..0000000 --- a/docs/validation.html +++ /dev/null @@ -1,1547 +0,0 @@ - - - - - - - 2.2. Validation System — ect 0.1.5 documentation - - - - - - - - - - - - - - - - - - - - - - -
- - -
- -
-
-
- -
-
-
-
- -
-

2.2. Validation System

-

The validation system provides modular, extensible validation for embedded cell complexes to ensure they represent proper embeddings in Euclidean space.

-
-

2.2.1. Overview

-

The validation system distinguishes between two types of rules:

-
    -

  • Structural Rules (always checked): Basic requirements like vertex counts and dimension validity

    • -

  • Geometric Rules (optional): Embedding properties like non-intersecting edges and faces

    • -
-
-
-

2.2.2. Architecture

-

The validation system consists of several components:

-
    -

  1. Base Classes: Abstract interfaces for validation rules and results

    2. -

  2. Validation Rules: Concrete implementations for specific validation checks

    3. -

  3. Validator: Main orchestrator that manages and applies rules

    4. -
-
-
-

2.2.3. Validation Rules

-
-

2.2.3.1. Structural Rules (Always Enforced)

-
    -

  • DimensionValidityRule: Ensures cell dimensions are non-negative

    • -

  • VertexCountRule: Validates correct vertex counts for cell dimensions

    -
      -

    • 0-cells must have exactly 1 vertex

      • -

    • 1-cells must have exactly 2 vertices

      • -

    • k-cells (k ≥ 2) must have at least 3 vertices

      • -
    -
    • -
-
-
-

2.2.3.2. Geometric Rules (Optional)

-
    -

  • EdgeInteriorRule: Ensures no vertices lie on edge interiors

    • -

  • FaceInteriorRule: Ensures no vertices lie inside face interiors

    • -

  • SelfIntersectionRule: Validates that face edges don’t self-intersect

    • -

  • BoundaryEdgeRule: Ensures required boundary edges exist for faces

    • -
-
-
-
-

2.2.4. Usage

-
from ect import EmbeddedComplex
-
-# Enable validation during construction
-K = EmbeddedComplex(validate_embedding=True)
-
-# Or enable/disable later
-K.enable_embedding_validation(tol=1e-10)
-K.disable_embedding_validation()
-
-# Override per operation
-K.add_cell(vertices, dim=2, check=True)
-
-
-
-
-

2.2.5. Custom Validation Rules

-

You can create custom validation rules by inheriting from ValidationRule:

-
from ect.validation import ValidationRule, ValidationResult
-
-class MyCustomRule(ValidationRule):
-    @property
-    def name(self) -> str:
-        return "My Custom Rule"
-    
-    @property
-    def is_structural(self) -> bool:
-        return False  # Geometric rule
-    
-    def applies_to_dimension(self, dim: int) -> bool:
-        return dim == 2  # Only for 2-cells
-    
-    def validate(self, cell_coords, all_coords, cell_indices, all_indices, dim):
-        # Your validation logic here
-        if some_condition:
-            return ValidationResult.valid()
-        else:
-            return ValidationResult.invalid("Validation failed")
-
-# Add to validator
-K.get_validator().add_rule(MyCustomRule())
-
-
-
-
-

2.2.6. API Reference

-
-

2.2.6.1. Main Module

-

Embedding validation system for EmbeddedComplex.

-

This module provides a flexible, extensible system for validating that -cell complexes represent proper embeddings in Euclidean space.

-
-
-class ect.validation.EmbeddingValidator(tolerance=1e-10, edge_checker=None)[source]
-

Main validator that orchestrates multiple validation rules.

-

This class manages a collection of validation rules and applies them -to cells based on their dimension and the configured rule set.

-
-
-__init__(tolerance=1e-10, edge_checker=None)[source]
-

Initialize the embedding validator.

-
-
Parameters:
-
    -

  • tolerance – Default tolerance for geometric validation

    • -

  • edge_checker – Function to check if an edge exists between two vertex indices

    • -
-
-
-
- -
-
-add_rule(rule)[source]
-

Add a custom validation rule.

-
-
Parameters:
-

rule – ValidationRule to add

-
-
Returns:
-

Self for method chaining

-
-
-
- -
-
-remove_rule(rule_class)[source]
-

Remove all rules of a specific type.

-
-
Parameters:
-

rule_class – Class of rules to remove

-
-
Returns:
-

Self for method chaining

-
-
-
- -
-
-set_tolerance(tolerance)[source]
-

Set tolerance for all rules.

-
-
Parameters:
-

tolerance – New tolerance value

-
-
Returns:
-

Self for method chaining

-
-
-
- -
-
-set_edge_checker(edge_checker)[source]
-

Set the edge checker function for boundary validation.

-
-
Parameters:
-

edge_checker – Function that takes two vertex indices and returns bool

-
-
Returns:
-

Self for method chaining

-
-
-
- -
-
-validate_cell(cell_coords, all_coords, cell_indices, all_indices, dim, check_geometric=True)[source]
-

Validate a cell using applicable rules.

-
-
Parameters:
-
    -

  • cell_coords – Coordinates of vertices forming the cell

    • -

  • all_coords – Coordinates of all vertices in the complex

    • -

  • cell_indices – Indices of vertices forming the cell

    • -

  • all_indices – Indices of all vertices in the complex

    • -

  • dim – Dimension of the cell

    • -

  • check_geometric – Whether to check geometric rules (structural rules always checked)

    • -
-
-
Returns:
-

ValidationResult for the cell

-
-
Raises:
-

ValueError – If validation fails

-
-
-
- -
-
-validate_cell_safe(cell_coords, all_coords, cell_indices, all_indices, dim, check_geometric=True)[source]
-

Validate a cell, catching and wrapping any exceptions.

-

Same as validate_cell but returns ValidationResult instead of raising.

-
-
Parameters:
-
    -

  • cell_coords – Coordinates of vertices forming the cell

    • -

  • all_coords – Coordinates of all vertices in the complex

    • -

  • cell_indices – Indices of vertices forming the cell

    • -

  • all_indices – Indices of all vertices in the complex

    • -

  • dim – Dimension of the cell

    • -

  • check_geometric – Whether to check geometric rules (structural rules always checked)

    • -
-
-
Returns:
-

ValidationResult for the cell

-
-
-
- -
-
-get_rules_for_dimension(dim)[source]
-

Get all rules that apply to a specific dimension.

-
-
Parameters:
-

dim – Cell dimension

-
-
Returns:
-

List of applicable ValidationRules

-
-
-
- -
-
-get_rule_names()[source]
-

Get names of all registered rules.

-
-
Returns:
-

List of rule names

-
-
-
- -
-
-disable_rule(rule_class)[source]
-

Temporarily disable a rule type.

-
-
Parameters:
-

rule_class – Class of rule to disable

-
-
Returns:
-

Self for method chaining

-
-
-
- -
-
-enable_strict_validation()[source]
-

Enable strict validation with tight tolerance.

-
-
Returns:
-

Self for method chaining

-
-
-
- -
-
-enable_permissive_validation()[source]
-

Enable permissive validation with loose tolerance.

-
-
Returns:
-

Self for method chaining

-
-
-
- -
-
-validate_coordinates(coords, expected_dim=None)[source]
-

Validate coordinate array format and dimension consistency.

-
-
Parameters:
-
    -

  • coords – Coordinate array to validate

    • -

  • expected_dim – Expected dimension, if known

    • -
-
-
Returns:
-

ValidationResult for the coordinates

-
-
-
- -
-
-validate_nodes(nodes, node_checker, expect_exists=True)[source]
-

Validate node existence/non-existence.

-
-
Parameters:
-
    -

  • nodes – List of node identifiers to check

    • -

  • node_checker – Function that takes node_id and returns bool for existence

    • -

  • expect_exists – Whether nodes should exist (True) or not exist (False)

    • -
-
-
Returns:
-

ValidationResult for the nodes

-
-
-
- -
- -
-
-class ect.validation.ValidationRule(tolerance=1e-10)[source]
-

Abstract base class for embedding validation rules.

-
-
-__init__(tolerance=1e-10)[source]
-

Initialize validation rule.

-
-
Parameters:
-

tolerance – Numerical tolerance for geometric checks

-
-
-
- -
-
-abstract property name
-

Human-readable name of this validation rule.

-
- -
-
-property is_structural
-

Check if this is a structural rule that should always be validated.

-

Structural rules check basic requirements like vertex counts and dimension validity. -They should always be checked regardless of validation settings. -Geometric rules check embedding properties and are optional.

-
-
Returns:
-

True if this rule should always be checked, False if optional

-
-
-
- -
-
-abstract applies_to_dimension(dim)[source]
-

Check if this rule applies to cells of the given dimension.

-
-
Parameters:
-

dim – Cell dimension

-
-
Returns:
-

True if this rule should validate cells of this dimension

-
-
-
- -
-
-abstract validate(cell_coords, all_coords, cell_indices, all_indices, dim=None)[source]
-

Validate a cell against this rule.

-
-
Parameters:
-
    -

  • cell_coords – Coordinates of vertices forming the cell

    • -

  • all_coords – Coordinates of all vertices in the complex

    • -

  • cell_indices – Indices of vertices forming the cell

    • -

  • all_indices – Indices of all vertices in the complex

    • -

  • dim – Dimension of the cell being validated

    • -
-
-
Returns:
-

ValidationResult indicating if the cell is valid

-
-
-
- -
-
-set_tolerance(tolerance)[source]
-

Set the tolerance for this rule.

-
-
Parameters:
-

tolerance – New tolerance value

-
-
Returns:
-

Self for method chaining

-
-
-
- -
- -
-
-class ect.validation.ValidationResult(is_valid, message='', violating_indices=None)[source]
-

Result of a validation check.

-
-
-is_valid
-
- -
-
-message = ''
-
- -
-
-violating_indices = None
-
- -
-
-classmethod valid()[source]
-

Create a valid result.

-
- -
-
-classmethod invalid(message, violating_indices=None)[source]
-

Create an invalid result with error message.

-
- -
-
-__init__(is_valid, message='', violating_indices=None)
-
- -
- -
-
-class ect.validation.EdgeInteriorRule(tolerance=1e-10)[source]
-

Validates that no vertices lie on edge interiors.

-
-
-property name
-

Human-readable name of this validation rule.

-
- -
-
-applies_to_dimension(dim)[source]
-

Check if this rule applies to cells of the given dimension.

-
-
Parameters:
-

dim – Cell dimension

-
-
Returns:
-

True if this rule should validate cells of this dimension

-
-
-
- -
-
-validate(cell_coords, all_coords, cell_indices, all_indices, dim=None)[source]
-

Validate that no other vertices lie on this edge’s interior.

-
- -
- -
-
-class ect.validation.FaceInteriorRule(tolerance=1e-10)[source]
-

Validates that no vertices lie inside face interiors.

-
-
-property name
-

Human-readable name of this validation rule.

-
- -
-
-applies_to_dimension(dim)[source]
-

Check if this rule applies to cells of the given dimension.

-
-
Parameters:
-

dim – Cell dimension

-
-
Returns:
-

True if this rule should validate cells of this dimension

-
-
-
- -
-
-validate(cell_coords, all_coords, cell_indices, all_indices, dim=None)[source]
-

Validate that no other vertices lie inside this face.

-
- -
- -
-
-class ect.validation.SelfIntersectionRule(tolerance=1e-10)[source]
-

Validates that face edges don’t self-intersect.

-
-
-property name
-

Human-readable name of this validation rule.

-
- -
-
-applies_to_dimension(dim)[source]
-

Check if this rule applies to cells of the given dimension.

-
-
Parameters:
-

dim – Cell dimension

-
-
Returns:
-

True if this rule should validate cells of this dimension

-
-
-
- -
-
-validate(cell_coords, all_coords, cell_indices, all_indices, dim=None)[source]
-

Validate that face edges don’t intersect each other

-
- -
- -
-
-class ect.validation.BoundaryEdgeRule(tolerance=1e-10, edge_checker=None)[source]
-

Validates that required boundary edges exist for faces.

-
-
-__init__(tolerance=1e-10, edge_checker=None)[source]
-

Initialize boundary edge rule.

-
-
Parameters:
-
    -

  • tolerance – Numerical tolerance

    • -

  • edge_checker – Function to check if an edge exists (injected dependency)

    • -
-
-
-
- -
-
-property name
-

Human-readable name of this validation rule.

-
- -
-
-applies_to_dimension(dim)[source]
-

Check if this rule applies to cells of the given dimension.

-
-
Parameters:
-

dim – Cell dimension

-
-
Returns:
-

True if this rule should validate cells of this dimension

-
-
-
- -
-
-validate(cell_coords, all_coords, cell_indices, all_indices, dim=None)[source]
-

Validate that all boundary edges exist for this face.

-
- -
- -
-
-class ect.validation.DimensionValidityRule(tolerance=1e-10)[source]
-

Validates that cell dimension is non-negative.

-
-
-property name
-

Human-readable name of this validation rule.

-
- -
-
-property is_structural
-

Check if this is a structural rule that should always be validated.

-

Structural rules check basic requirements like vertex counts and dimension validity. -They should always be checked regardless of validation settings. -Geometric rules check embedding properties and are optional.

-
-
Returns:
-

True if this rule should always be checked, False if optional

-
-
-
- -
-
-applies_to_dimension(dim)[source]
-

Check if this rule applies to cells of the given dimension.

-
-
Parameters:
-

dim – Cell dimension

-
-
Returns:
-

True if this rule should validate cells of this dimension

-
-
-
- -
-
-validate(cell_coords, all_coords, cell_indices, all_indices, dim=None)[source]
-

Validate that dimension is non-negative.

-
- -
- -
-
-class ect.validation.VertexCountRule(tolerance=1e-10)[source]
-

Validates that cells have the correct number of vertices for their dimension.

-
-
-property name
-

Human-readable name of this validation rule.

-
- -
-
-property is_structural
-

Check if this is a structural rule that should always be validated.

-

Structural rules check basic requirements like vertex counts and dimension validity. -They should always be checked regardless of validation settings. -Geometric rules check embedding properties and are optional.

-
-
Returns:
-

True if this rule should always be checked, False if optional

-
-
-
- -
-
-applies_to_dimension(dim)[source]
-

Check if this rule applies to cells of the given dimension.

-
-
Parameters:
-

dim – Cell dimension

-
-
Returns:
-

True if this rule should validate cells of this dimension

-
-
-
- -
-
-validate(cell_coords, all_coords, cell_indices, all_indices, dim=None)[source]
-

Validate vertex count matches cell dimension requirements.

-
- -
- -
-
-ect.validation.validate_coordinate_array(coords, expected_dim=None)[source]
-

Standalone function to validate coordinate array format.

-
- -
-
-ect.validation.validate_node_existence(nodes, node_checker, expect_exists=True)[source]
-

Standalone function to validate node existence.

-
- -
-
-

2.2.6.2. Base Classes

-

Base classes for the embedding validation system.

-
-
-class ect.validation.base.ValidationResult(is_valid, message='', violating_indices=None)[source]
-

Bases: object

-

Result of a validation check.

-
-
-is_valid
-
- -
-
-message = ''
-
- -
-
-violating_indices = None
-
- -
-
-classmethod valid()[source]
-

Create a valid result.

-
- -
-
-classmethod invalid(message, violating_indices=None)[source]
-

Create an invalid result with error message.

-
- -
-
-__init__(is_valid, message='', violating_indices=None)
-
- -
- -
-
-class ect.validation.base.ValidationRule(tolerance=1e-10)[source]
-

Bases: ABC

-

Abstract base class for embedding validation rules.

-
-
-__init__(tolerance=1e-10)[source]
-

Initialize validation rule.

-
-
Parameters:
-

tolerance – Numerical tolerance for geometric checks

-
-
-
- -
-
-abstract property name
-

Human-readable name of this validation rule.

-
- -
-
-property is_structural
-

Check if this is a structural rule that should always be validated.

-

Structural rules check basic requirements like vertex counts and dimension validity. -They should always be checked regardless of validation settings. -Geometric rules check embedding properties and are optional.

-
-
Returns:
-

True if this rule should always be checked, False if optional

-
-
-
- -
-
-abstract applies_to_dimension(dim)[source]
-

Check if this rule applies to cells of the given dimension.

-
-
Parameters:
-

dim – Cell dimension

-
-
Returns:
-

True if this rule should validate cells of this dimension

-
-
-
- -
-
-abstract validate(cell_coords, all_coords, cell_indices, all_indices, dim=None)[source]
-

Validate a cell against this rule.

-
-
Parameters:
-
    -

  • cell_coords – Coordinates of vertices forming the cell

    • -

  • all_coords – Coordinates of all vertices in the complex

    • -

  • cell_indices – Indices of vertices forming the cell

    • -

  • all_indices – Indices of all vertices in the complex

    • -

  • dim – Dimension of the cell being validated

    • -
-
-
Returns:
-

ValidationResult indicating if the cell is valid

-
-
-
- -
-
-set_tolerance(tolerance)[source]
-

Set the tolerance for this rule.

-
-
Parameters:
-

tolerance – New tolerance value

-
-
Returns:
-

Self for method chaining

-
-
-
- -
- -
-
-

2.2.6.3. Validation Rules

-

Unified validation rules for embedding validation system.

-

This module contains all validation rules including both structural rules -(which are always checked) and geometric rules (which are optional).

-
-
-class ect.validation.rules.DimensionValidityRule(tolerance=1e-10)[source]
-

Bases: ValidationRule

-

Validates that cell dimension is non-negative.

-
-
-property name
-

Human-readable name of this validation rule.

-
- -
-
-property is_structural
-

Check if this is a structural rule that should always be validated.

-

Structural rules check basic requirements like vertex counts and dimension validity. -They should always be checked regardless of validation settings. -Geometric rules check embedding properties and are optional.

-
-
Returns:
-

True if this rule should always be checked, False if optional

-
-
-
- -
-
-applies_to_dimension(dim)[source]
-

Check if this rule applies to cells of the given dimension.

-
-
Parameters:
-

dim – Cell dimension

-
-
Returns:
-

True if this rule should validate cells of this dimension

-
-
-
- -
-
-validate(cell_coords, all_coords, cell_indices, all_indices, dim=None)[source]
-

Validate that dimension is non-negative.

-
- -
- -
-
-class ect.validation.rules.VertexCountRule(tolerance=1e-10)[source]
-

Bases: ValidationRule

-

Validates that cells have the correct number of vertices for their dimension.

-
-
-property name
-

Human-readable name of this validation rule.

-
- -
-
-property is_structural
-

Check if this is a structural rule that should always be validated.

-

Structural rules check basic requirements like vertex counts and dimension validity. -They should always be checked regardless of validation settings. -Geometric rules check embedding properties and are optional.

-
-
Returns:
-

True if this rule should always be checked, False if optional

-
-
-
- -
-
-applies_to_dimension(dim)[source]
-

Check if this rule applies to cells of the given dimension.

-
-
Parameters:
-

dim – Cell dimension

-
-
Returns:
-

True if this rule should validate cells of this dimension

-
-
-
- -
-
-validate(cell_coords, all_coords, cell_indices, all_indices, dim=None)[source]
-

Validate vertex count matches cell dimension requirements.

-
- -
- -
-
-class ect.validation.rules.CoordinateDimensionRule(tolerance=1e-10, dimension_checker=None)[source]
-

Bases: ValidationRule

-

Validates that coordinates have consistent dimensions.

-
-
-__init__(tolerance=1e-10, dimension_checker=None)[source]
-

Initialize validation rule.

-
-
Parameters:
-

tolerance – Numerical tolerance for geometric checks

-
-
-
- -
-
-property name
-

Human-readable name of this validation rule.

-
- -
-
-property is_structural
-

Check if this is a structural rule that should always be validated.

-

Structural rules check basic requirements like vertex counts and dimension validity. -They should always be checked regardless of validation settings. -Geometric rules check embedding properties and are optional.

-
-
Returns:
-

True if this rule should always be checked, False if optional

-
-
-
- -
-
-applies_to_dimension(dim)[source]
-

Check if this rule applies to cells of the given dimension.

-
-
Parameters:
-

dim – Cell dimension

-
-
Returns:
-

True if this rule should validate cells of this dimension

-
-
-
- -
-
-validate(cell_coords, all_coords, cell_indices, all_indices, dim=None)[source]
-

Validate coordinate dimensions are consistent.

-
- -
- -
-
-class ect.validation.rules.EdgeInteriorRule(tolerance=1e-10)[source]
-

Bases: ValidationRule

-

Validates that no vertices lie on edge interiors.

-
-
-property name
-

Human-readable name of this validation rule.

-
- -
-
-applies_to_dimension(dim)[source]
-

Check if this rule applies to cells of the given dimension.

-
-
Parameters:
-

dim – Cell dimension

-
-
Returns:
-

True if this rule should validate cells of this dimension

-
-
-
- -
-
-validate(cell_coords, all_coords, cell_indices, all_indices, dim=None)[source]
-

Validate that no other vertices lie on this edge’s interior.

-
- -
- -
-
-class ect.validation.rules.FaceInteriorRule(tolerance=1e-10)[source]
-

Bases: ValidationRule

-

Validates that no vertices lie inside face interiors.

-
-
-property name
-

Human-readable name of this validation rule.

-
- -
-
-applies_to_dimension(dim)[source]
-

Check if this rule applies to cells of the given dimension.

-
-
Parameters:
-

dim – Cell dimension

-
-
Returns:
-

True if this rule should validate cells of this dimension

-
-
-
- -
-
-validate(cell_coords, all_coords, cell_indices, all_indices, dim=None)[source]
-

Validate that no other vertices lie inside this face.

-
- -
- -
-
-class ect.validation.rules.SelfIntersectionRule(tolerance=1e-10)[source]
-

Bases: ValidationRule

-

Validates that face edges don’t self-intersect.

-
-
-property name
-

Human-readable name of this validation rule.

-
- -
-
-applies_to_dimension(dim)[source]
-

Check if this rule applies to cells of the given dimension.

-
-
Parameters:
-

dim – Cell dimension

-
-
Returns:
-

True if this rule should validate cells of this dimension

-
-
-
- -
-
-validate(cell_coords, all_coords, cell_indices, all_indices, dim=None)[source]
-

Validate that face edges don’t intersect each other

-
- -
- -
-
-class ect.validation.rules.BoundaryEdgeRule(tolerance=1e-10, edge_checker=None)[source]
-

Bases: ValidationRule

-

Validates that required boundary edges exist for faces.

-
-
-__init__(tolerance=1e-10, edge_checker=None)[source]
-

Initialize boundary edge rule.

-
-
Parameters:
-
    -

  • tolerance – Numerical tolerance

    • -

  • edge_checker – Function to check if an edge exists (injected dependency)

    • -
-
-
-
- -
-
-property name
-

Human-readable name of this validation rule.

-
- -
-
-applies_to_dimension(dim)[source]
-

Check if this rule applies to cells of the given dimension.

-
-
Parameters:
-

dim – Cell dimension

-
-
Returns:
-

True if this rule should validate cells of this dimension

-
-
-
- -
-
-validate(cell_coords, all_coords, cell_indices, all_indices, dim=None)[source]
-

Validate that all boundary edges exist for this face.

-
- -
- -
-
-ect.validation.rules.validate_coordinate_array(coords, expected_dim=None)[source]
-

Standalone function to validate coordinate array format.

-
- -
-
-ect.validation.rules.validate_node_existence(nodes, node_checker, expect_exists=True)[source]
-

Standalone function to validate node existence.

-
- -
-
-

2.2.6.4. Validator

-

Main embedding validator class that orchestrates validation rules.

-
-
-class ect.validation.validator.EmbeddingValidator(tolerance=1e-10, edge_checker=None)[source]
-

Bases: object

-

Main validator that orchestrates multiple validation rules.

-

This class manages a collection of validation rules and applies them -to cells based on their dimension and the configured rule set.

-
-
-__init__(tolerance=1e-10, edge_checker=None)[source]
-

Initialize the embedding validator.

-
-
Parameters:
-
    -

  • tolerance – Default tolerance for geometric validation

    • -

  • edge_checker – Function to check if an edge exists between two vertex indices

    • -
-
-
-
- -
-
-add_rule(rule)[source]
-

Add a custom validation rule.

-
-
Parameters:
-

rule – ValidationRule to add

-
-
Returns:
-

Self for method chaining

-
-
-
- -
-
-remove_rule(rule_class)[source]
-

Remove all rules of a specific type.

-
-
Parameters:
-

rule_class – Class of rules to remove

-
-
Returns:
-

Self for method chaining

-
-
-
- -
-
-set_tolerance(tolerance)[source]
-

Set tolerance for all rules.

-
-
Parameters:
-

tolerance – New tolerance value

-
-
Returns:
-

Self for method chaining

-
-
-
- -
-
-set_edge_checker(edge_checker)[source]
-

Set the edge checker function for boundary validation.

-
-
Parameters:
-

edge_checker – Function that takes two vertex indices and returns bool

-
-
Returns:
-

Self for method chaining

-
-
-
- -
-
-validate_cell(cell_coords, all_coords, cell_indices, all_indices, dim, check_geometric=True)[source]
-

Validate a cell using applicable rules.

-
-
Parameters:
-
    -

  • cell_coords – Coordinates of vertices forming the cell

    • -

  • all_coords – Coordinates of all vertices in the complex

    • -

  • cell_indices – Indices of vertices forming the cell

    • -

  • all_indices – Indices of all vertices in the complex

    • -

  • dim – Dimension of the cell

    • -

  • check_geometric – Whether to check geometric rules (structural rules always checked)

    • -
-
-
Returns:
-

ValidationResult for the cell

-
-
Raises:
-

ValueError – If validation fails

-
-
-
- -
-
-validate_cell_safe(cell_coords, all_coords, cell_indices, all_indices, dim, check_geometric=True)[source]
-

Validate a cell, catching and wrapping any exceptions.

-

Same as validate_cell but returns ValidationResult instead of raising.

-
-
Parameters:
-
    -

  • cell_coords – Coordinates of vertices forming the cell

    • -

  • all_coords – Coordinates of all vertices in the complex

    • -

  • cell_indices – Indices of vertices forming the cell

    • -

  • all_indices – Indices of all vertices in the complex

    • -

  • dim – Dimension of the cell

    • -

  • check_geometric – Whether to check geometric rules (structural rules always checked)

    • -
-
-
Returns:
-

ValidationResult for the cell

-
-
-
- -
-
-get_rules_for_dimension(dim)[source]
-

Get all rules that apply to a specific dimension.

-
-
Parameters:
-

dim – Cell dimension

-
-
Returns:
-

List of applicable ValidationRules

-
-
-
- -
-
-get_rule_names()[source]
-

Get names of all registered rules.

-
-
Returns:
-

List of rule names

-
-
-
- -
-
-disable_rule(rule_class)[source]
-

Temporarily disable a rule type.

-
-
Parameters:
-

rule_class – Class of rule to disable

-
-
Returns:
-

Self for method chaining

-
-
-
- -
-
-enable_strict_validation()[source]
-

Enable strict validation with tight tolerance.

-
-
Returns:
-

Self for method chaining

-
-
-
- -
-
-enable_permissive_validation()[source]
-

Enable permissive validation with loose tolerance.

-
-
Returns:
-

Self for method chaining

-
-
-
- -
-
-validate_coordinates(coords, expected_dim=None)[source]
-

Validate coordinate array format and dimension consistency.

-
-
Parameters:
-
    -

  • coords – Coordinate array to validate

    • -

  • expected_dim – Expected dimension, if known

    • -
-
-
Returns:
-

ValidationResult for the coordinates

-
-
-
- -
-
-validate_nodes(nodes, node_checker, expect_exists=True)[source]
-

Validate node existence/non-existence.

-
-
Parameters:
-
    -

  • nodes – List of node identifiers to check

    • -

  • node_checker – Function that takes node_id and returns bool for existence

    • -

  • expect_exists – Whether nodes should exist (True) or not exist (False)

    • -
-
-
Returns:
-

ValidationResult for the nodes

-
-
-
- -
- -
-
-
- - -
-
- -
-
-
-
- - - - - - - \ No newline at end of file diff --git a/src/ect/dect.py b/src/ect/dect.py index 2223b6c..7903bab 100644 --- a/src/ect/dect.py +++ b/src/ect/dect.py @@ -22,7 +22,22 @@ def __init__( dtype=np.float32, scale: float = 10.0, ): - """Initialize DECT calculator""" + """ + Initialize a Differentiable Euler Characteristic Transform (DECT) calculator. + + Args: + directions (Optional[Directions]): Directions for the transform. If None, directions are generated automatically. + num_dirs (Optional[int]): Number of directions to use. If None, determined from directions or defaults. + num_thresh (Optional[int]): Number of thresholds to use. If None, determined from data or defaults. + bound_radius (Optional[float]): Bounding radius for threshold generation. If None, computed from input. + thresholds (Optional[np.ndarray]): Array of threshold values. If None, thresholds are generated automatically. + dtype: Data type for computation (default: np.float32). + scale (float): Slope parameter for the sigmoid function controlling smoothness (default: 10.0). + + Notes: + - The scale parameter controls the sharpness of the sigmoid transition in the DECT calculation. + - All other parameters are passed to the parent :class:`ECT`. + """ super().__init__( directions, num_dirs, num_thresh, bound_radius, thresholds, dtype ) @@ -33,7 +48,26 @@ def __init__( def _compute_directional_transform( simplex_projections_list, thresholds, dtype=np.float32, scale=10.0 ): - """Compute DECT using sigmoid for smooth transitions""" + """ + Compute the Differentiable Euler Characteristic Transform (DECT) using a sigmoid function for smooth transitions. + + Args: + simplex_projections_list (list of np.ndarray): List of arrays containing projected simplex heights for each direction. + thresholds (np.ndarray): Array of threshold values. + dtype: Data type for computation (default: np.float32). + scale (float): Slope parameter for the sigmoid function controlling smoothness (default: 10.0). + + Returns: + np.ndarray: DECT matrix of shape + + .. math:: + + (\text{num\_dir}, \text{num\_thresh}) + + Notes: + - The DECT is computed as a sum over all simplices, using a sigmoid function $\sigma(x) = \frac{1}{1 + e^{-x}}$ to smoothly count contributions above each threshold. + - The sign alternates for even/odd simplex dimensions to match Euler characteristic conventions. + """ num_dir = simplex_projections_list[0].shape[1] num_thresh = len(thresholds) @@ -56,7 +90,22 @@ def calculate( theta: Optional[float] = None, override_bound_radius: Optional[float] = None, ) -> ECTResult: - """Calculate Differentiable Euler Characteristic Transform (DECT)""" + """ + Calculate the Differentiable Euler Characteristic Transform (DECT) for a given embedded complex. + + Args: + graph (EmbeddedGraph or EmbeddedCW): The embedded complex to analyze. + scale (Optional[float]): Slope parameter for the sigmoid function. If None, uses the instance's scale. + theta (Optional[float]): Specific direction angle to use. If None, uses all directions. + override_bound_radius (Optional[float]): Override for bounding radius in threshold generation. + + Returns: + ECTResult: Result object containing the DECT matrix, directions, and thresholds. + + Notes: + - Uses :meth:`_compute_directional_transform` for the core DECT calculation. + - The DECT matrix is computed for all directions and thresholds specified. + """ self._ensure_directions(graph.dim, theta) self._ensure_thresholds(graph, override_bound_radius) diff --git a/src/ect/directions.py b/src/ect/directions.py index f945a1a..e974304 100644 --- a/src/ect/directions.py +++ b/src/ect/directions.py @@ -15,7 +15,10 @@ class Directions: Manages direction vectors for ECT calculations. Supports uniform, random, or custom sampling of directions. - Examples: + **Examples:** + + .. code-block:: python + # Uniform sampling in 2D (default) dirs = Directions.uniform(num_dirs=8) @@ -40,6 +43,21 @@ def __init__( endpoint: bool = False, seed: Optional[int] = None, ): + """ + Initialize a Directions instance for ECT calculations. + + Args: + num_dirs (int): Number of direction vectors to generate (default: 360). + sampling (Sampling): Sampling strategy (UNIFORM, RANDOM, or CUSTOM). + dim (int): Dimension of the space (default: 2). + endpoint (bool): Whether to include the endpoint for 2D angles (default: False). + seed (Optional[int]): Random seed for reproducibility (default: None). + + Notes: + - For 2D, directions are represented as angles; for higher dimensions, as unit vectors. + - Use factory methods :meth:`uniform`, :meth:`random`, :meth:`from_angles`, or :meth:`from_vectors` for convenience. + """ + self.num_dirs = num_dirs self.sampling = sampling self.dim = dim @@ -111,7 +129,17 @@ def random( @classmethod def from_angles(cls, angles: Sequence[float]) -> "Directions": """ - Create an instance for custom angles (2D only). + Create a Directions instance for custom angles in 2D. + + Args: + angles (Sequence[float]): List or array of angles (in radians) for each direction. + + Returns: + Directions: Instance with direction angles set and corresponding unit vectors available via :attr:`vectors`. + + Notes: + - Only valid for 2D directions; for higher dimensions use :meth:`from_vectors`. + - Angles are stored in :attr:`thetas` and unit vectors are computed as needed. """ instance = cls(len(angles), Sampling.CUSTOM, dim=2) instance._thetas = np.array(angles) @@ -120,8 +148,20 @@ def from_angles(cls, angles: Sequence[float]) -> "Directions": @classmethod def from_vectors(cls, vectors: Sequence[tuple]) -> "Directions": """ - Create an instance from custom direction vectors. - Works in any number of dimensions. + Create a Directions instance from custom direction vectors in any dimension. + + Args: + vectors (Sequence[tuple]): List or array of direction vectors (each must be nonzero). + + Returns: + Directions: Instance with normalized direction vectors and associated angles (if 2D). + + Raises: + ValueError: If any vector has zero magnitude. + + Notes: + - Vectors are normalized to unit length. + - For 2D, angles are computed from the vectors and available via :attr:`thetas`. """ vectors = np.array(vectors, dtype=float) norms = np.linalg.norm(vectors, axis=1, keepdims=True) @@ -136,7 +176,19 @@ def from_vectors(cls, vectors: Sequence[tuple]) -> "Directions": @property def thetas(self) -> np.ndarray: - """Get the angles for 2D directions. Raises an error if dim > 2.""" + """ + Get the angles (in radians) for 2D direction vectors. + + Returns: + np.ndarray: Array of angles corresponding to each direction vector (2D only). + + Raises: + ValueError: If called for directions in dimension greater than 2. + + Notes: + - For 2D, angles are computed from the direction vectors if not already set. + - For higher dimensions, use :attr:`vectors` for direction data. + """ if self.dim != 2: raise ValueError( "Angle representation is only available for 2D directions." @@ -148,9 +200,18 @@ def thetas(self) -> np.ndarray: @property def vectors(self) -> np.ndarray: - """Get unit direction vectors. - For 2D, they are computed from thetas if not already created. - For n-dim (n>2), they should be available. + """ + Get the unit direction vectors for all directions. + + Returns: + np.ndarray: Array of shape (num_dirs, dim) containing unit vectors for each direction. + + Raises: + ValueError: If vectors are not available for dimensions >2 and were not generated during initialization. + + Notes: + - For 2D, vectors are computed from :attr:`thetas` if not already set. + - For higher dimensions, vectors are generated during initialization or via :meth:`from_vectors`. """ if self._vectors is None: if self.dim == 2: diff --git a/src/ect/ect.py b/src/ect/ect.py index 69a6116..2828f6a 100644 --- a/src/ect/ect.py +++ b/src/ect/ect.py @@ -10,22 +10,13 @@ class ECT: """ - A class to calculate the Euler Characteristic Transform (ECT) from an input :any:`EmbeddedComplex`, + A class to calculate the Euler Characteristic Transform (ECT) from an input :class:`ect.embed_complex.EmbeddedComplex`, using a set of directions to project the complex onto and thresholds to filter the projections. The result is a matrix where entry ``M[i,j]`` is :math:`\chi(K_{a_i})` for the direction :math:`\omega_j` where :math:`a_i` is the ith entry in ``self.thresholds``, and :math:`\omega_j` is the jth entry in ``self.directions``. - Attributes - ---------- - num_dirs : int - The number of directions to consider in the matrix. - num_thresh : int - The number of thresholds to consider in the matrix. - directions : Directions - The directions to consider for projection. - bound_radius : float - Either ``None``, or a positive radius of the bounding circle. + Example: >>> from ect import ECT, EmbeddedComplex diff --git a/src/ect/embed_complex.py b/src/ect/embed_complex.py index fe234cc..1deddc2 100644 --- a/src/ect/embed_complex.py +++ b/src/ect/embed_complex.py @@ -1,5 +1,6 @@ from collections import defaultdict from typing import Dict, List, Tuple, Optional, Union +import functools import networkx as nx import numpy as np @@ -24,7 +25,8 @@ class EmbeddedComplex(nx.Graph): """ A unified class to represent an embedded cell complex with cells of arbitrary dimension. - This combines the functionality of EmbeddedGraph and EmbeddedCW, supporting: + This combines the functionality of :class:`EmbeddedGraph` and :class:`EmbeddedCW`, supporting: + - 0-cells (vertices) with embedded coordinates - 1-cells (edges) - k-cells for k >= 2 (faces, volumes, etc.) @@ -34,25 +36,20 @@ class EmbeddedComplex(nx.Graph): when adding cells. Default: False embedding_tol (float): Tolerance for geometric validation. Default: 1e-10 - Attributes: - coord_matrix : np.ndarray - A matrix of embedded coordinates for each vertex - node_list : list - A list of node names - node_to_index : dict - A dictionary mapping node ids to their index in the coord_matrix - dim : int - The dimension of the embedded coordinates - cells : dict - Dictionary mapping dimension k to list of k-cells, where each k-cell - is represented as a tuple of vertex indices - validate_embedding : bool - Whether to automatically validate embedding properties - embedding_tol : float - Tolerance for geometric validation """ def __init__(self, validate_embedding=False, embedding_tol=1e-10): + """ + Initialize an EmbeddedComplex instance. + + Args: + validate_embedding (bool, optional): If True, automatically validate embedding properties when adding cells. Defaults to False. + embedding_tol (float, optional): Tolerance for geometric validation. Defaults to 1e-10. + + Notes: + - The complex supports arbitrary-dimensional cells (vertices, edges, faces, etc.). + - Embedding validation can be enabled or disabled at initialization or later. + """ super().__init__() self._node_list = [] self._node_to_index = {} @@ -74,36 +71,74 @@ def edge_checker(v1_idx: int, v2_idx: int) -> bool: @property def coord_matrix(self): - """Return the N x D coordinate matrix""" + """ + Get the coordinate matrix of the embedded complex. + + Returns: + np.ndarray: A matrix of shape :math:`(N, D)` where :math:`N` is the number of nodes (vertices) + and :math:`D` is the dimension of the embedding. Each row corresponds to the coordinates + of a node in the order given by :attr:`node_list`. + + Notes: + - If no nodes have been added, returns an empty array of shape :math:`(0, 0)`. + - The coordinate matrix is updated automatically as nodes are added or modified. + - The order of rows matches the order of node identifiers in :attr:`node_list`. + """ if self._coord_matrix is None: return np.empty((0, 0)) return self._coord_matrix @property def dim(self): - """Return the dimension of the embedded coordinates""" + """ + Get the dimension :math:`D` of the embedded coordinates. + + Returns: + int: The number of dimensions (D) for the coordinates of each node. Returns 0 if no nodes exist. + """ if self._coord_matrix is None: return 0 return self._coord_matrix.shape[1] @property def node_list(self): - """Return ordered list of node names.""" + """ + Get the ordered list of node names in the complex. + + Returns: + list: List of node identifiers in the order corresponding to the rows of the coordinate matrix :attr:`coord_matrix`. + """ return self._node_list @property def node_to_index(self): - """Return a dictionary mapping node ids to their index in the coord_matrix""" + """ + Get a mapping from node identifiers to their row index in the coordinate matrix :attr:`coord_matrix`. + + Returns: + dict: Dictionary mapping node ids to their index in the coordinate matrix. + """ return self._node_to_index @property def position_dict(self): - """Return a dictionary mapping node ids to their coordinates""" + """ + Get a dictionary mapping node ids to their coordinates. + + Returns: + dict: Dictionary where keys are node ids and values are coordinate arrays for each node (from :attr:`coord_matrix`). + """ return {node: self._coord_matrix[i] for i, node in enumerate(self._node_list)} @property def edge_indices(self): - """Return edges as array of index pairs""" + """ + Get the edges of the complex as an array of index pairs. + + Returns: + np.ndarray: Array of shape (E, 2) where each row contains the indices of the two nodes forming an edge. + Returns an empty array if there are no edges. + """ edges = np.array( [(self._node_to_index[u], self._node_to_index[v]) for u, v in self.edges()], dtype=int, @@ -112,7 +147,12 @@ def edge_indices(self): @property def faces(self): - """Return list of 2-cells (faces) for backward compatibility""" + """ + Get the list of 2-cells (faces) in the complex. + + Returns: + list: List of tuples, each representing a face as a sequence of node names. Provided for backward compatibility. + """ return [ tuple(self._node_list[i] for i in cell) for cell in self.cells.get(2, []) ] @@ -154,17 +194,36 @@ def add_node(self, node_id, coord): super().add_node(node_id) def add_nodes_from_dict(self, nodes_with_coords: Dict[Union[str, int], np.ndarray]): + """Add multiple vertices to the complex. + + Args: + nodes_with_coords (Dict[Union[str, int], np.ndarray]): Dictionary mapping node ids to coordinates + """ for node_id, coordinates in nodes_with_coords.items(): self.add_node(node_id, coordinates) def add_nodes_from( self, nodes_with_coords: List[Tuple[Union[str, int], np.ndarray]] ): + """Add multiple vertices to the complex. + + Args: + nodes_with_coords (List[Tuple[Union[str, int], np.ndarray]]): List of (node_id, coordinates) tuples + """ for node_id, coordinates in nodes_with_coords: self.add_node(node_id, coordinates) def add_edge(self, node_id1, node_id2): - """Add an edge (1-cell) between two nodes""" + """ + Add an edge (1-cell) between two nodes in the complex. + + Args: + node_id1: Identifier for the first node. + node_id2: Identifier for the second node. + + Raises: + ValueError: If either node does not exist in the complex. + """ # validate nodes exist node_result = self._validator.validate_nodes( [node_id1, node_id2], lambda n: n in self._node_to_index, expect_exists=True @@ -186,9 +245,9 @@ def add_cell( Args: cell_vertices: List of vertex identifiers that form the cell - dim: Dimension of the cell. If None, inferred as len(cell_vertices) - 1 + dim: Dimension of the cell. If None, inferred as `len(cell_vertices) - 1` check: Whether to validate the cell embedding. If None, uses self.validate_embedding - embedding_tol: Tolerance for geometric validation. If None, uses self.embedding_tol + embedding_tol: Tolerance for geometric validation. If None, uses :attr:`embedding_tol`. """ if check is None: check = self.validate_embedding @@ -256,7 +315,11 @@ def enable_embedding_validation(self, tol: float = 1e-10): self._validator.set_tolerance(tol) def disable_embedding_validation(self): - """Disable automatic embedding validation for all subsequent cell additions.""" + """ + Disable automatic embedding validation for all subsequent cell additions. + + After calling this method, new cells will not be checked for geometric embedding validity. + """ self.validate_embedding = False def get_validator(self) -> "EmbeddingValidator": @@ -283,16 +346,41 @@ def set_validation_rules(self, rules: List["ValidationRule"]) -> "EmbeddedComple return self def add_face(self, face: List, check: Optional[bool] = None): - """Add a 2-cell (face) to the complex. Provided for backward compatibility.""" + """ + Add a 2-cell (face) to the complex. + + Args: + face (list): List of node identifiers forming the face. + check (Optional[bool]): Whether to validate the embedding of the face. If None, uses the default setting. + + Notes: + Provided for backward compatibility with previous interfaces. + """ self.add_cell(face, dim=2, check=check) def add_faces_from(self, faces: List[List]): - """Add multiple 2-cells (faces) to the complex.""" + """ + Add multiple 2-cells (faces) to the complex. + + Args: + faces (list of lists): Each sublist contains node identifiers forming a face. + """ for face in faces: self.add_face(face) def get_coord(self, node_id): - """Return the coordinates of a node""" + """ + Get the coordinates of a node. + + Args: + node_id: Identifier of the node whose coordinates are requested. + + Returns: + np.ndarray: Coordinate array for the specified node. + + Raises: + ValueError: If the node does not exist in the complex. + """ # validate node exists node_result = self._validator.validate_nodes( [node_id], lambda n: n in self._node_to_index, expect_exists=True @@ -303,7 +391,16 @@ def get_coord(self, node_id): return self._coord_matrix[self._node_to_index[node_id]].copy() def set_coord(self, node_id, new_coords): - """Set the coordinates of a node""" + """ + Set the coordinates of a node. + + Args: + node_id: Identifier of the node to update. + new_coords: New coordinates to assign to the node. + + Raises: + ValueError: If the coordinates are invalid or the node does not exist. + """ # validate coordinates expected_dim = ( self._coord_matrix.shape[1] if self._coord_matrix is not None else None @@ -323,7 +420,15 @@ def set_coord(self, node_id, new_coords): self._coord_matrix[idx] = new_coords def add_cycle(self, coord_matrix): - """Add nodes in a cyclic pattern from coordinate matrix""" + """ + Add nodes in a cyclic pattern from a coordinate matrix. + + Args: + coord_matrix (np.ndarray): Matrix of shape (N, D) where each row is the coordinates of a node. + + Notes: + Nodes are named sequentially and connected in a cycle. + """ # generate sequential node names and add cyclic edges n = coord_matrix.shape[0] new_names = next_vert_name(self._node_list[-1] if self._node_list else 0, n) @@ -331,7 +436,18 @@ def add_cycle(self, coord_matrix): self.add_edges_from([(new_names[i], new_names[(i + 1) % n]) for i in range(n)]) def get_center(self, method: str = "bounding_box") -> np.ndarray: - """Calculate center of coordinates""" + """ + Calculate the center of the coordinates of all nodes. + + Args: + method (str): Method to use for center calculation. Options are "mean", "bounding_box", or "origin". + + Returns: + np.ndarray: The center coordinates as determined by the specified method. + + Raises: + ValueError: If an unknown method is specified. + """ coords = self._coord_matrix if coords is None or coords.size == 0: @@ -346,11 +462,24 @@ def get_center(self, method: str = "bounding_box") -> np.ndarray: raise ValueError(f"Unknown center method: {method}") def get_bounding_box(self): - """Get (min, max) for each dimension""" + """ + Get the minimum and maximum values for each coordinate dimension. + + Returns: + list: List of (min, max) tuples for each dimension. + """ return [(dim.min(), dim.max()) for dim in self._coord_matrix.T] def get_bounding_radius(self, center_type: str = "bounding_box") -> float: - """Get radius of minimal bounding sphere""" + """ + Get the radius of the minimal bounding sphere containing all node coordinates. + + Args: + center_type (str): Method to use for center calculation (see get_center). + + Returns: + float: The radius of the minimal bounding sphere. + """ coords = self._coord_matrix if coords is None or coords.size == 0: return 0.0 @@ -463,7 +592,16 @@ def get_normal_angles( return angle_dict def transform_coordinates(self, center_type="bounding_box", projection_type="pca"): - """Transform coordinates center and orientation""" + """ + Transform the coordinates by centering and projecting them. + + Args: + center_type (str): Method for centering coordinates. + projection_type (str): Method for projecting coordinates (e.g., "pca"). + + Raises: + ValueError: If an unknown transform or center type is specified. + """ if projection_type not in TRANSFORM_TYPES: raise ValueError(f"Unknown transform type: {projection_type}") self.project_coordinates(projection_type) @@ -479,21 +617,42 @@ def center_coordinates(self, center_type="mean"): self._coord_matrix -= center def scale_coordinates(self, radius=1): - """Scale coordinates to fit within given radius""" + """ + Scale the coordinates so that the largest distance from the origin equals the given radius. + + Args: + radius (float): Target radius for scaling. + """ # scale so largest distance from origin equals target radius current_max = np.linalg.norm(self._coord_matrix, axis=1).max() if current_max > 0: self._coord_matrix *= radius / current_max def project_coordinates(self, projection_type="pca"): - """Project coordinates using a function""" + """ + Project the coordinates using the specified projection function. + + Args: + projection_type (str): The type of projection to use (e.g., "pca"). + + Raises: + ValueError: If an unknown projection type is specified. + """ if projection_type == "pca": self.pca_projection() else: raise ValueError(f"Unknown projection type: {projection_type}") def pca_projection(self, target_dim=2): - """Dimensionality reduction using PCA""" + """ + Reduce the dimensionality of the coordinates using Principal Component Analysis (PCA). + + Args: + target_dim (int): Target number of dimensions (default is 2). + + Notes: + Only reduces dimension if current dimension is greater than target_dim. + """ # only reduce dimension if self.dim <= target_dim: return @@ -501,8 +660,10 @@ def pca_projection(self, target_dim=2): pca = PCA(n_components=target_dim) self._coord_matrix = pca.fit_transform(self._coord_matrix) + def validate_plot_parameters(func): # decorator to check plotting requirements + @functools.wraps(func) def wrapper(self, *args, **kwargs): bounding_center_type = kwargs.get("bounding_center_type", "bounding_box") @@ -550,6 +711,7 @@ def plot_faces(self, ax=None, **kwargs): return ax + @validate_plot_parameters def plot( self, @@ -565,9 +727,26 @@ def plot( face_color: str = "lightblue", face_alpha: float = 0.3, **kwargs, - ) -> plt.Axes: + ) -> plt.Axes: """ Visualize the embedded complex in 2D or 3D + + Args: + bounding_circle (bool): Whether to draw a bounding circle/sphere + bounding_center_type (str): Method for center calculation for bounding shape + color_nodes_theta (float, optional): Angle in radians to color nodes by projection + ax (matplotlib.axes.Axes, optional): Axes to plot on. If None, a new figure is created + with_labels (bool): Whether to display node labels + node_size (int): Size of nodes in the plot + edge_color (str): Color of edges in the plot + elev (float): Elevation angle for 3D plot + azim (float): Azimuth angle for 3D plot + face_color (str): Color for faces (2-cells) + face_alpha (float): Transparency for faces (2-cells) + **kwargs: Additional keyword arguments for plotting functions + + Returns: + matplotlib.axes.Axes: The axes object with the plot. """ ax = self._create_axes(ax, self.dim) diff --git a/src/ect/results.py b/src/ect/results.py index 5106839..83cf880 100644 --- a/src/ect/results.py +++ b/src/ect/results.py @@ -64,11 +64,36 @@ def _dense_to_csr_prefix(dense64: np.ndarray): class ECTResult(np.ndarray): """ - A numpy ndarray subclass that carries ECT metadata and plotting capabilities - Acts like a regular matrix but with added visualization methods and metadata about directions and thresholds + A numpy ndarray subclass that carries Euler Characteristic Transform (ECT) metadata and plotting capabilities. + + This class acts like a regular matrix but includes: + - Visualization methods for ECT and ECC plots + - Metadata about directions and thresholds used in the transform + - Support for both dense and compressed (CSR) representations + + Parameters: + matrix (np.ndarray): ECT matrix data. + directions: Direction metadata (angles or vectors). + thresholds: Threshold values used for the transform. + + Notes: + - Use :meth:`plot` to visualize the ECT matrix. + - Use :meth:`dist` to compute distances between ECT results. + - Supports loading/saving in compressed format via :meth:`save_npz` and :meth:`load_npz`. """ def __new__(cls, matrix, directions, thresholds): + """ + Create a new ECTResult instance from matrix data, directions, and thresholds. + + Args: + matrix (np.ndarray): ECT matrix data (float or int). + directions: Direction metadata (angles or vectors). + thresholds: Threshold values used for the transform. + + Returns: + ECTResult: A new instance with attached metadata and optional CSR fields. + """ # allow float arrays for smooth transform otherwise int if np.issubdtype(matrix.dtype, np.floating): obj = np.asarray(matrix, dtype=np.float64).view(cls) @@ -92,6 +117,12 @@ def __array_finalize__(self, obj): @property def has_csr(self): + """ + Check if the ECTResult instance has compressed sparse row (CSR) data attached. + + Returns: + bool: True if CSR fields (row_ptr, col_idx, data) are present, False otherwise. + """ return ( getattr(self, "csr_row_ptr", None) is not None and getattr(self, "csr_col_idx", None) is not None @@ -100,6 +131,20 @@ def has_csr(self): @classmethod def from_csr(cls, row_ptr, col_idx, data, directions, thresholds, dtype=np.int32): + """ + Create an ECTResult instance from compressed sparse row (CSR) data. + + Args: + row_ptr (np.ndarray): CSR row pointer array. + col_idx (np.ndarray): CSR column indices array. + data (np.ndarray): CSR data array (jump values). + directions: Direction metadata (angles or vectors). + thresholds: Threshold values used for the transform. + dtype: Data type for the dense matrix (default: np.int32). + + Returns: + ECTResult: Instance with dense matrix and attached CSR fields. + """ num_dirs = len(directions) num_thresh = len(thresholds) dense64 = _csr_prefix_to_dense(row_ptr, col_idx, data, num_dirs, num_thresh) @@ -111,6 +156,12 @@ def from_csr(cls, row_ptr, col_idx, data, directions, thresholds, dtype=np.int32 return obj def to_dense(self): + """ + Convert the ECTResult from CSR format to a dense matrix. + + Returns: + np.ndarray: Dense matrix representation of the ECTResult. + """ if not self.has_csr: return self num_dirs = self.shape[0] @@ -121,6 +172,16 @@ def to_dense(self): return dense64.astype(self.dtype, copy=False) def save_npz(self, path): + """ + Save the ECTResult in compressed .npz format, including CSR data and metadata. + + Args: + path (str): File path to save the .npz file. + + Notes: + - If CSR data is not present, it is computed from the dense matrix. + - Metadata (thresholds, dtype) is included for reproducibility. + """ if not self.has_csr: row_ptr, col_idx, data = _dense_to_csr_prefix( self.astype(np.int64, copy=False) @@ -138,6 +199,16 @@ def save_npz(self, path): @classmethod def load_npz(cls, path, directions): + """ + Load an ECTResult from a compressed .npz file, restoring CSR data and metadata. + + Args: + path (str): File path to load the .npz file from. + directions: Direction metadata to attach to the result. + + Returns: + ECTResult: Instance with dense matrix, CSR fields, and metadata. + """ z = np.load(path, allow_pickle=False) row_ptr = z["row_ptr"] col_idx = z["col_idx"] @@ -147,12 +218,22 @@ def load_npz(cls, path, directions): return cls.from_csr(row_ptr, col_idx, data, directions, thresholds, dtype=dtype) def plot(self, ax=None): - """Plot ECT matrix with proper handling for both 2D and 3D""" - ax = ax or plt.gca() + """ + Plot the ECT matrix, handling both 2D and 3D direction cases. + + Args: + ax (matplotlib.axes.Axes, optional): Axes to plot on. If None, uses current axes. + Returns: + matplotlib.axes.Axes: The axes object with the plot. + + Notes: + - For 2D, directions are shown as angles; for 3D, as indices. + - Uses color mesh and labels for visualization. + """ + ax = ax or plt.gca() if self.thresholds is None: self.thresholds = np.linspace(-1, 1, self.shape[1]) - if len(self.directions) == 1: directions = ( self.directions.thetas @@ -161,7 +242,6 @@ def plot(self, ax=None): ) self._plot_ecc(directions) return ax - if self.directions.dim == 2: # 2D case - use angle representation if ( @@ -172,22 +252,17 @@ def plot(self, ax=None): ect_data = np.hstack([self.T, self.T[:, [0]]]) else: plot_thetas = self.directions.thetas - X = plot_thetas Y = self.thresholds - else: X = np.arange(self.shape[0]) Y = self.thresholds ect_data = self.T - ax.set_xlabel("Direction Index") - mesh = ax.pcolormesh( X[None, :], Y[:, None], ect_data, cmap="viridis", shading="nearest" ) plt.colorbar(mesh, ax=ax) - if self.directions.dim == 2: ax.set_xlabel(r"Direction $\omega$ (radians)") if self.directions.sampling == Sampling.UNIFORM: @@ -205,12 +280,19 @@ def plot(self, ax=None): r"$2\pi$", ] ) - ax.set_ylabel(r"Threshold $a$") return ax def smooth(self): - """Calculate the Smooth Euler Characteristic Transform""" + """ + Calculate the Smooth Euler Characteristic Transform (SECT) from the ECT matrix. + + Returns: + ECTResult: New instance containing the SECT matrix, directions, and thresholds. + + Notes: + - The SECT is computed by centering each direction's values and taking the cumulative sum across thresholds. + """ # convert to float for calculations data = self.astype(np.float64) @@ -246,31 +328,27 @@ def dist( Args: other: Another ECTResult object or list of ECTResult objects metric: Distance metric to use. Can be: - - String: any metric supported by scipy.spatial.distance - (e.g., 'euclidean', 'cityblock', 'chebyshev', 'cosine', etc.) - - Callable: a custom distance function that takes two 1D arrays - and returns a scalar distance. The function should have signature: - func(u, v) -> float - **kwargs: Additional keyword arguments passed to the metric function - (e.g., p=3 for minkowski distance, w=weights for weighted metrics) + - String: any metric supported by scipy.spatial.distance (e.g., 'euclidean', 'cityblock', 'chebyshev', 'cosine', etc.) + - Callable: a custom distance function that takes two 1D arrays and returns a scalar distance. The function should have signature: func(u, v) -> float + **kwargs: Additional keyword arguments passed to the metric function (e.g., p=3 for minkowski distance, w=weights for weighted metrics) Returns: - float or np.ndarray: Single distance if other is an ECTResult, - array of distances if other is a list + float or np.ndarray: Single distance if other is an ECTResult, array of distances if other is a list. Raises: - ValueError: If the shapes of the ECTResults don't match + ValueError: If the shapes of the ECTResults don't match. Examples: + >>> # Built-in metrics >>> dist1 = ect1.dist(ect2, metric='euclidean') >>> dist2 = ect1.dist(ect2, metric='minkowski', p=3) - >>> + >>> # Custom distance function >>> def my_distance(u, v): ... return np.sum(np.abs(u - v) ** 0.5) >>> dist3 = ect1.dist(ect2, metric=my_distance) - >>> + >>> # Batch distances with custom function >>> dists = ect1.dist([ect2, ect3, ect4], metric=my_distance) """ diff --git a/src/ect/validation/validator.py b/src/ect/validation/validator.py index 7af7701..0853177 100644 --- a/src/ect/validation/validator.py +++ b/src/ect/validation/validator.py @@ -92,7 +92,7 @@ def set_tolerance(self, tolerance: float) -> "EmbeddingValidator": def set_edge_checker(self, edge_checker: Callable) -> "EmbeddingValidator": """ Set the edge checker function for boundary validation. - + Args: edge_checker: Function that takes two vertex indices and returns bool