From b1880dc5a773d89ce9eb98de2ca941e6aa88f51d Mon Sep 17 00:00:00 2001 From: Adam Li Date: Wed, 21 Jun 2023 11:38:19 -0400 Subject: [PATCH] WIP Signed-off-by: Adam Li --- experiments/plotting_cmi_analysis.ipynb | 364 ++++++++++++----------- sktree/experimental/__init__.py | 2 +- sktree/experimental/ksg.py | 317 ++++++++++++++++++++ sktree/experimental/meson.build | 1 + sktree/experimental/mutual_info.py | 377 +++--------------------- sktree/experimental/simulate.py | 13 + sktree/neighbors.py | 16 +- 7 files changed, 572 insertions(+), 518 deletions(-) create mode 100644 sktree/experimental/ksg.py diff --git a/experiments/plotting_cmi_analysis.ipynb b/experiments/plotting_cmi_analysis.ipynb index 0cf705ed1..ad0f7cd8c 100644 --- a/experiments/plotting_cmi_analysis.ipynb +++ b/experiments/plotting_cmi_analysis.ipynb @@ -20,15 +20,57 @@ "\n", "The data we will simulate comes from the following distributions for conditional mutual information:\n", "\n", - "- Uniform: X is conditionally dependent on Y\n", - "- Gaussian: X is conditionally dependent on Y\n", + "- Uniform: X is conditionally (in)dependent on Y given Z\n", + "- Gaussian: X is conditionally (in)dependent on Y given Z\n", "\n", - "For each distribution, we will add a varying number of independent dimensions to the data (i.e. sampled from Gaussian distribution)." + "For each distribution, we will add a varying number of independent dimensions to the data (i.e. sampled from Gaussian distribution).\n", + "\n", + "## Graphical models of the simulation\n", + "\n", + "For our purposes, we are motivated by the feature selection problem in cancer research, where cancer status (1-4 severity) is the outcome variable of interest and certain feature sets (X and W) are possibly high-dimensional sets that may have causal impact on each other. With prior knowledge, we know that cancer status cannot cause any of the features in the feature sets. We are also typically concerned with comparing sets of features conditioned on at most one other feature set. This allows us to enumerate all possible causal DAG settings that match this. We have the following 8 possible DAGs:\n", + "\n", + "1. W is completely independent: $(X \\rightarrow Y, W)$\n", + "2. W is an observed covariate: $(X \\rightarrow Y, X \\leftarrow W \\rightarrow Y)$\n", + "3. W is an observed confounder that explains the correlation between X and Y: $(X, X \\leftarrow W \\rightarrow Y)$\n", + "4. W affects the outcome only: $(X \\rightarrow Y, W \\rightarrow Y)$\n", + "5. W affects the treatment only: $(X \\rightarrow Y, W \\rightarrow X)$\n", + "6. W affects the outcome only but X is independent: $(X, W \\rightarrow Y)$\n", + "7. W affects the treatment only but X is independent: $(Y, W \\rightarrow X)$\n", + "8. All are d-separated: $(Y, W, X)$\n", + "\n", + "With these, we assume that there are no other relevant latent confounders that are not controlled for in our experimental design.\n", + "\n", + "# Estimation Methods for Y discrete\n", + "\n", + "1. Direct estimation of entropy using supervised forests:\n", + "\n", + "$$I(X; Y) = H(X) - H(X | Y) = H(Y) - H(Y | X)$$\n", + "\n", + "-> H(Y| X) = clf.predict_proba(X) after fitting forest to (X, Y) pairs\n", + "-> H(Y) = empirical entropy calculuation\n", + "\n", + "$$I(X; Y|Z) = H(Y | Z) - H(Y | X, Z)$$\n", + "\n", + "-> Train two forests and directly estimate using pairs of (Y, Z) and (Y, X \\cup Z)\n", + "\n", + "2. Indirect estimation of entropy using KSG with unsupervised forests\n", + "\n", + "The (conditional) mutual information KSG estimator just requires training a forest.%load_ext lab_black" ] }, { "cell_type": "code", - "execution_count": 142, + "execution_count": 1, + "id": "705fb134-54c2-42fd-bbc3-1d4541ae8769", + "metadata": {}, + "outputs": [], + "source": [ + "%load_ext lab_black" + ] + }, + { + "cell_type": "code", + "execution_count": 2, "id": "2e7b6950-44a0-40a9-bf2a-b6eca06725c1", "metadata": {}, "outputs": [], @@ -39,17 +81,32 @@ "\n", "from sklearn.neighbors import NearestNeighbors\n", "import sktree\n", - "from sktree.experimental.simulate import (simulate_helix, simulate_multivariate_gaussian, simulate_sphere)\n", + "from sktree.experimental.simulate import (\n", + " simulate_helix,\n", + " simulate_multivariate_gaussian,\n", + " simulate_sphere,\n", + " embed_high_dims,\n", + ")\n", "from sktree.experimental.mutual_info import (\n", - " entropy_gaussian, entropy_weibull,\n", + " entropy_gaussian,\n", + " entropy_weibull,\n", " cmi_from_entropy,\n", " mi_from_entropy,\n", - " mutual_info_ksg,\n", - " mi_gaussian, cmi_gaussian,\n", - " mi_gamma, \n", + " mi_gaussian,\n", + " cmi_gaussian,\n", + " mi_gamma,\n", ")\n", + "from sktree.experimental import mutual_info_ksg\n", "from sktree.tree import compute_forest_similarity_matrix\n", - "from sktree import UnsupervisedRandomForest, UnsupervisedObliqueRandomForest, ObliqueRandomForestClassifier\n", + "from sktree import (\n", + " UnsupervisedRandomForest,\n", + " UnsupervisedObliqueRandomForest,\n", + " ObliqueRandomForestClassifier,\n", + " NearestNeighborsMetaEstimator,\n", + ")\n", + "\n", + "from dodiscover.ci import CMITest\n", + "import pandas as pd\n", "\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns" @@ -60,16 +117,7 @@ "execution_count": 3, "id": "bf387bc2-f1d1-4b7a-9dab-e9c8fb992b2a", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The autoreload extension is already loaded. To reload it, use:\n", - " %reload_ext autoreload\n" - ] - } - ], + "outputs": [], "source": [ "%load_ext autoreload\n", "%autoreload 2" @@ -90,23 +138,26 @@ "metadata": {}, "outputs": [], "source": [ - "seed =12345\n", + "seed = 12345\n", "rng = np.random.default_rng(seed)" ] }, { "cell_type": "code", - "execution_count": 125, + "execution_count": 16, "id": "4fcde0a4-7413-4f09-bbd8-fe62fcd62c2d", "metadata": {}, "outputs": [], "source": [ "n_jobs = -1\n", + "n_estimators = 100\n", + "feature_combinations = 2.0\n", + "n_nbrs = 5\n", "\n", "# hyperparameters of the simulation\n", - "n_samples = 500\n", - "n_noise_dims = 10\n", - "alpha = 0.01\n", + "n_samples = 1000\n", + "n_noise_dims = 1\n", + "alpha = 0.001\n", "\n", "# dimensionality of mvg\n", "d = 3\n", @@ -134,17 +185,26 @@ }, { "cell_type": "code", - "execution_count": 139, + "execution_count": 22, "id": "3cc73c4e-78b6-48b3-83b3-091d365d8ada", "metadata": {}, "outputs": [], "source": [ "# generate helix data\n", - "helix_data = simulate_helix(radius_a=radius_a, radius_b=radius_b, alpha=alpha/2, n_samples=n_samples, return_mi_lb=True, random_seed=seed)\n", + "helix_data = simulate_helix(\n", + " radius_a=radius_a,\n", + " radius_b=radius_b,\n", + " alpha=alpha / 2,\n", + " n_samples=n_samples,\n", + " return_mi_lb=True,\n", + " random_seed=seed,\n", + ")\n", "P, X, Y, Z, helix_lb = helix_data\n", "\n", "# generate sphere data\n", - "sphere_data = simulate_sphere(radius=radius, alpha=alpha, n_samples=n_samples, return_mi_lb=True, random_seed=seed)\n", + "sphere_data = simulate_sphere(\n", + " radius=radius, alpha=alpha, n_samples=n_samples, return_mi_lb=True, random_seed=seed\n", + ")\n", "lat, lon, Y1, Y2, Y3, lb = sphere_data\n", "\n", "# simulate multivariate Gaussian\n", @@ -154,13 +214,13 @@ }, { "cell_type": "code", - "execution_count": 124, + "execution_count": 23, "id": "aa1a67bb-55fa-4983-b2d1-a23102945b7c", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -172,11 +232,11 @@ "source": [ "# helix data\n", "fig = plt.figure()\n", - "ax1 = fig.add_subplot(111, projection='3d')\n", + "ax1 = fig.add_subplot(111, projection=\"3d\")\n", "\n", - "ax1.plot( X, Y, Z, '*', c='b', label='Helix')\n", - "ax1.legend(loc='upper left');\n", - "ax1.axis('equal')\n", + "ax1.plot(X, Y, Z, \"*\", c=\"b\", label=\"Helix\")\n", + "ax1.legend(loc=\"upper left\")\n", + "ax1.axis(\"equal\")\n", "# ax1.set(\n", "# xlim=[-1, 1],\n", "# ylim=[-1, 1],\n", @@ -188,18 +248,18 @@ "roll = 0\n", "ax1.view_init(elev, azim, roll)\n", "\n", - "plt.show()\n" + "plt.show()" ] }, { "cell_type": "code", - "execution_count": 100, + "execution_count": 24, "id": "a841ffc8-e821-4c0a-8df0-9b55b1be3aba", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -211,18 +271,18 @@ "source": [ "# sphere data\n", "fig = plt.figure()\n", - "ax1 = fig.add_subplot(111, projection='3d')\n", + "ax1 = fig.add_subplot(111, projection=\"3d\")\n", "\n", - "ax1.plot( Y1, Y2, Y3, '*', c='b', label='Sphere')\n", - "ax1.legend(loc='upper left');\n", - "ax1.axis('equal')\n", + "ax1.plot(Y1, Y2, Y3, \"*\", c=\"b\", label=\"Sphere\")\n", + "ax1.legend(loc=\"upper left\")\n", + "ax1.axis(\"equal\")\n", "\n", - "plt.show()\n" + "plt.show()" ] }, { "cell_type": "code", - "execution_count": 140, + "execution_count": 25, "id": "383a17a7-6c4f-49fc-aa4d-322f820ac18e", "metadata": {}, "outputs": [ @@ -244,13 +304,13 @@ }, { "cell_type": "code", - "execution_count": 141, + "execution_count": 26, "id": "570cf521-f62f-4e62-98e4-0aea8e4f72db", "metadata": {}, "outputs": [ { "data": { - "image/png": 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h3wjl/k2i8FQqRb8ukE9zQSCcJkap9RfyYcxkMpzIwwBrxMYu8AcCAQCAwWCAXq+H0+ks2wOmGF5LUUguuJ7D4Ytw2KiEfNjv23xg3yQJ5NOcEAiniVBI4LKU+gshnEqRSqVo5LKyskI9YPR6PYxGI8RiMRQKBXp7e6t9mutQSUPCuYZGquGUCzb5hMPhguRD2ttL2Z9APs0JgXAaGLn1FzbBlFt/KffQTiQSWfWXUChEpVHsdvs6D5hoNNqUH+xm3HM14EO1oJxrqFar0d3dje7ubko+4+PjlHyAtfb4clCMfIjSgUKhEMinASAQTgOhFIOxSusvxQiH1F/YBEM8YPR6PdxuN/R6fdECP59RCN8RTr2iJ3LNl5aWsLy8DIZhYLfbqWI1X4djLVJqpSCXfGZmZjA/P489e/bkjXxKQS75jI6OIpPJYHBwMK++m4DaQiCcOoFdf0mn0wiFQkin02hpaeHFYCy36yccDmeZjCWTSWg0Guj1evT09JRd4K82ZbfR2ucC2F17S0tLiMfjaG1thcFgQG9vL6RSKfx+Pw4cOICWlhY4HA44HA5eohIu1+Li9VGr1ejo6MDo6CguvfRSLCwsYGxsrGDarRSwswDkpoXcyJGbN4F8aguBcGqEYgZjADA2NgaZTIbu7m4A3B6ymUwGkUgEsVgMhw8fxsrKChiGoR1kXBX4z8UopFKQG4r5+XlMTExgeXkZ8Xickno+WR6ZTAar1Yp0Oo35+XnMzMxg7969VFnBZrNBqVRWvTeuIxyuQD4LxF21u7sbq6urmJ2dxZkzZyoiH4Zh1s3vsNNuAvnUFgLh8AQSveS2J+czGCtlkr8cpFKpvB4wwFoXWWdnJ1pbWzmViOE7pcYXuDx8SQRDUmSZTAZzc3MwmUxl6b5JJBLY7XbY7XYkk0kcOHAA4XAYO3fuhE6ng8PhgN1uL3mGKXefXIPr14e9XmtrK1pbWyn5+P1+Sj4WiwV2ux0Wi6Xgdc3X9SaQT/0gEA5HKKX+wk6R5aKaAzuRSGQpKK+urkIul0Ov18Nms6G/vx/RaBSnT5+G2+2u6nkWQjPXWSpZmyhXs1NkZO7IYDDA4XDgyJEj2Lx5M9RqdcV7k8lkUCgU9M6eWEefPHkSRqMRDoejrKl+oHFqOLkgEU6h9VpbW9HT04Oenh5KPqdPn8bRo0cLks9GWm+FyKeQp4+A6iAQToXITY8Vm38ptc2z1O6caDSaRTCkwK/T6dDe3k49YNiIx+O8HtrNEIVUA0IwJHpZXl5GKpWiacm2tjZO545yIRKJ0NLSArfbDbfbTcU0yVS/xWKBw+GA1WotuodGreGwUcp6pZIPUS4o9XEF8uEXAuGUgGL1F/Y0dDVpMbFYTFs5cx+bfSe9vLyMRCJBJWK6u7uh0+k29ICpxSxLo0Uh1T4eaawgJJNOp6HT6XgZbAXKe9+wxTRJh9fo6CiOHTsGq9UKh8MBs9mc97Bt9BpOuftjk08oFILf78fo6CiOHj0KuVxOiaOabjc2+USjUchkMqhUKoF8yoRAOHmQK3AZDoexuLgIm82Wt/7CBUiXF/GAYbcoEw8YInKp1WrL9oDhm3CavYbDMEzWdWcTjMFgQHt7Oy/WCFxArVajp6cH3d3dCIVCmJmZwYkTJ5BOp2Gz2eBwOGA0Gjl/jbiOcLhQQdBoNNBoNOjt7UUoFMKrr76KxcVFPPfcc7BarbDb7TCbzVWRD0lnejweIfIpEwLhYOP6SyQSwdjYGNra2jh/Q6XT6Sx75J07d0IsFkOv10On08Hj8UCj0VR90DUz4QDc300TgllYWEA4HMauXbvAMAyNYNxuNyfXvZYQiUTQarXQarXo6+vD8vIyZmZmcPjwYYhEItjtdiQSCc4fkytwKbsDrJGPWq2GwWCA2WyG3+/HqVOn1qXdyolSyfucdL4Jabfy8JoknELpsUIDllKplLMPQzKZzJLoD4VCkMvlkMlkkMvlOP/886FWq3nJi7+WazjsyHFpaYm2hhNzN+LB0ogEU8nrJhKJYDAYYDAYMDAwgEAggJmZGQQCAQSDQaTTaTgcDrS2tlZ8fbkmCK7XI2tKJBIa+bBrPiMjIxWRD6kLCTWf8nHOEw5Jj7Hbk4k8DMFG9RexWFzxUCOZJmdHMSqVCjqdDk6nkxb4vV4vlpaW0NraWtkT3QCvtQgnk8kgFAplpchEIhH0en1Wa/j8/Dympqag1Wp52jk3qObAEovFMJvNMJvNSKVSkEgkiEQi2LdvH1QqFW2zLrebjg+C4INw2GuKRKKqySeTyay7MRHIpzScc4STW38pNP9SzgvPntLf6LFJgZ8QTCwWo8N+nZ2d0Ov1eQv8zU4IAH+F/VJeJ0IwpMBP7KmJuGhXV1feu/nX4odfo9Ggs7MTqVQKc3NztOFAq9VSaZ3cLsdaoBy7ai7WzCUf0nDAJh/SfMEmn2parQFQM7nXIvk0PeFsVH+phGByQQr6uXdLJE3DblEmBX6dTlfWsF+ppFYpmp3Qctcm9ghsgiHq1SaTCT09PSWnJhtdxYDr/ZFrIpVK0dbWhra2NiQSCTrjMzIyQhtU7HZ7wQ7IZkmplZImZde/SMOB3+/H8PAwjhw5ktVwwFWrNfDaI5+mI5zc+guZqCeaU9UIXBYCeXOlUilaB1hZWaF30Tqdjs7AVNrJREiNL9RifT7XZhgmawaGEIzBYIDFYkFvby8vta9GAd+tzHK5HO3t7Whvb0csFoPf74fP58PQ0BBMJhMdMGXfPDUL4ZS75kbkIxKJsLKysi7yKWXdQuRDbpRJHfFcfR83FeF4vV6cd955OHXqFH3xIpEIZmZm4HK5OH+RkslklrnY7t27IZPJ6F10d3d3VUVXNpo9AuF6/XQ6TSMYcv2PHz8OvV4Pq9WKvr6+LHuEcwF8HLj5sNFjKBQKdHR0oKOjg5qnjY+PZw2YkqHKc5Fw2MhHPi+99BJ8Ph8mJibozJPJZKqKfObm5uDz+XDxxRcDAI168nlbNTOainBkMhmVECEFTi47yOLxeFb9ZXV1FUqlkhaUL7roImg0Gl7eAHyn1EjUxeehVs3+2e3hS0tLCAaDVJ7HbDYjGAzi8ssvb/gidaOj3NefbZ62urpKU25Hjx6F0WikDTlcdPfx8d7kam/AWfKRSqXYvHkzZDIZ/H4/hoaGkEgkYLPZaNqtnMckN2u5qtYikQjJZPKcIp+mIhxSyIzH45RwKu0gY4stEpKJRqN0gr+jowM6nQ4tLS3IZDKYnZ1FS0sLby94rVJefBFOuREO20GUCIzK5XKqQzY4OAilUgmRSIRYLIYzZ85wvudmQaPUmFpbW9Hb24uenh4Eg0GMj48jlUrh+eefp80GBoOhYdqs+VxTIpHQVHpfXx+CwSAln2QymVXzKYV8CDEWSrudK+TTVIRDpNnj8Tj9WqmEkztJvrKyQsUW9Xo9+vr6Chb42W8AvlCrORk+O8mKrU0IhtRhQqEQWlpaqA7Zpk2boFAo8n6I+P5gNcqBXgx813DKAalbut1uBAIBbNu2DTMzM3jllVeo0nUlJnLNQji5XWrsOm6l5FNKqzUAWr9mkw/50wxoKsKRSqWQSCSIxWL0a4UIh3QxsVNkAOgkucvlKlkLi7zwfEYgtehSA2rXukzqXyRFtrq6Si2qyfxRud4utapxnOvgkrzEYjGMRiOMRiMGBwexuLiImZmZdSZypcyX1YIcuECxLrVC5HPixAmkUqmC5LNR5xt5DuwbO0I+AJqGfJqKcACgpaUlK8IhRJCbogmFQrRNlsxhqNXqil+MaoY/S0EtU2p8IJ1OI5FI4NSpU/T6K5VKqkOWT8G6VPDdAdfo4Fr/jK9oSSwWw2KxwGKxrDORU6vVtM1apVIVXI/rw5KPNUslsVzyWVlZWUc+pOGgnFpTM5NPUxGOSLQm0R6LxRAMBhGLxbCwsIB0Oo2dO3fSO2iHw4GBgQFOu5hqUdRvpgiHSPSQFNnq6irEYjHS6TTcbjf0en1FBmHF0AypL77QqMRYaF9sE7lUKkVnfE6dOlXQRI6P17eesz1skCFk4vZKyOf48eNIpVJQKBS0XlxuwwH5Ox/55Coc1Pt91BSEwzAMxsbGsHPnTrS0tODGG2+EUqnEgw8+CI1GAwC47LLLeJ2OrkUE0siEk0gksszGwuEw1Go19Ho9PB4P0uk0vF4vBgYGuNw2AKGGwyXqES1JpVI4nU44nU4kEgn4/f68JnLNWsMpF/nI58SJE1heXsZzzz1Hu91MJlPV5DM8PAwA6O3tbQjyaXjCiUQi6O/vh9/vx/bt25HJZHDrrbfi5ptvhsVioW/gchwPK0Gzp9QISj1wSIs4+UMIhuiQ5Ur0LCws8LVlinONGAiJLy0tYWlpCSKRCG1tbXA4HAXTTlyAy5RauWvJ5XJqIheLxTAzM0NN5DQaDR2CLNd+oxC4bIsGzr4HuWy1JuRDOjRnZmZw/PhxpNNpWvOplHzItSTnSyFtt1qRT8Wvqs/nw+c+9zn8/ve/RyQSQU9PDx555BFs376dy/1BpVLhF7/4BbZt2waVSoWBgQFs27YNFosFwNkXPpPJ8Oa2SB6n2VNqxaKoeDyeNckfiURoi3hXVxf0en1RUuczQqt3GoArsNOQJEpsbW2FwWBAd3c3xGIx1TXT6XRoa2uD3W5vmhpOuVAoFFkmcsPDw1hYWMDzzz8Pi8WCtra2smda8u2Ry/cPuSnkoy5E5s70ej0GBgawvLwMv9+PY8eOIZPJwGazwWazlUU+ue3W5DVjk49cLuf17GSjIsJZWlrC5Zdfjquuugq///3vYbFYcOrUKRgMBq73BwB43eteR/+d2zTAJhw+0ewptdzHICrWhGSi0SgVGe3u7t6QYPKhGcVB+SQzhmGwsrKCmZkZLC0tIRQKQaVSFYwSZTIZHA4Hjdqnp6cxNDQEiUSC5eVl2Gy2mh0MpYKr66dWq2G1WpFKpTA4OEifezKZpLUgk8lU9uPxoYYA8KNqzSYRkSjbXiIf+djtdhiNxqLkk3sjnpt2q3XWoCLCuffee9He3o5HHnmEfq2zs5OzTRWDQqFY16UG8E84tYhA+HwO0WgUDMPg9OnTCIVCiMfj9O66t7cXer2+qjRGM0c4XO2bqCUQEie1R6PRiPb2dhgMhpIaKdhpp0gkggMHDmB2dhbT09Ow2Wxoa2ujDp7lgusIhw9pG41Gg/7+/iwTuSNHjgAAnfHR6/UlPTbXbdF8RjjFWq3zkc/Ro0c3JJ+NUopNQTi//vWvcfXVV+O6667Djh074HQ68bGPfQy33nor1/tbB4VCkTWHQ/KRzR7hcCk9wzAMYrFYVoosHo+DYRhIpdKyVKxLRS0itEar4bAVq4kcj0wmo7n4YDCICy64oKp6jEqlgkKhgNvthlqtxvT0NA4fPgyxWAyHw4G2tjaMjGjxhS9I8Y1vpHDRRcWvUaOm58h6he7yBwcHqYncwYMHIZPJKPkUkpviut4CnCWcejUi5COfmZmZguTDdQ2rWlR04pw5cwYPPPAAPvOZz+ALX/gCXnrpJXziE5+AXC7H3/3d33G9xyzI5fIswgH4L+jX4jHYkVq5aRO2TA8hmUQiQVUUCMHs27cPLpeLdvZxvf9mjXBKBbGjIASzvLxMFattNhsGBgaoHA8AjIyMcPK45GAnMx39/f1YXFzE9PQ0fvKTE/jmNy/BwoIYP/kJg4su2ni9Rqnh5Fuv0N5EIhFMJhNMJhM2bdqEhYUFzMzMYP/+/VAoFHTAlG0ix0f6i6+UWiXEkEvIS0tL6yKfeDzeMJ8foELCyWQy2L59O77xjW8AAC644AIcO3YMDz74IO+Ek5tSA2pHOI3StswwZ43eCMkQmR5yd63T6dYRV7OTQq1rOEQOiZAL6SSrxHOHy32KxWJEIhak01bs2yfGwsLax/jxx4Ht24//xa7BiO5u/ptQ+UipbQSxWAyr1UprPmTA9PTp09BoNJR8SA2S65QaH11d1UYiIpEoS/GBkE8oFMLJkycRDAZht9thMBjWRZG1JKSK3pEOhwObNm3K+trg4CCeeuopTjZVDPUinFqm1HJBCIadIkulUjSCaWtrK0mmh8/n0OxkBmRfZ3KtM5nMOlvqet8xTkwA/f3ra0ErK3LceuuF9P8vvrh/XadXM9RwyoFUKqUEk0wms0zkdDodgLXW4EImcpXskY8UFdeq1oR8lpeXYbVakUgkcPjwYQCgaTe+mryKoSLCufzyy+lAEcHIyAg8Hg8nmyqGekY4tUqpMQyDcDiclSJLp9NUB87pdJasA5f7GHxGac1Ww2EYBvF4HMlkEsePH8fS0hJSqRR0Oh0MBgPcbjc0Gk1D5cCB/GSzhrOH9QMPrHXEnThxAul0Gna7HW1tbQ1fw6kGMpkMLpcLLpcL8XgcXq8Xy8vL2LVrV0ETuXLBV02ETyLTarWwWq1ZkQ8hn56eHnR3d3P+uIVQ0ZX/9Kc/jcsuuwzf+MY3cP311+PAgQN46KGH8NBDD3G9v3XIbYsG+E938f0YhGAAYGhoCKFQiBIM0SKr1EmUDb6jkGaIcEgzBfmTSCQgEomgVCrR1tYGnU7XcASTe10feSSJW2+VIpXKf12+8pUUPvhBOYA+9Pb2Ynl5GdPT0zh06BBSqRRmZmagVqtLEtTcaF98Ng1Ug5aWFrhcLpw6dQqvf/3rMTs7m9dErpJ6KR8RLl9Exq4J56bdAoFAzd/rFRHOxRdfjF/+8pe46667cPfdd6OzsxP3338/brrpJq73tw5ES42NZkup5dYGSAstsOY50tnZycudNZ+k2ag1nEQikUUwsVgMGo2GFloZhsHIyAi6urp42DF3YF/f970vg4GBJF73uvxpoquvPvs+zS0s79y5E7FYDHv37kVraytVNuBa964S8BUxFTORs9lsVECzHN8arlHrdQn5NEVbNABcc801uOaaa7jcS0lQKpXUaoCg0VNqpLuJpMhWVlbAMAydKu7o6EBrayt27ty5rtOGSzRrhEPWLwXFpvnzzRstLS01XLt1eWAAiCASMWAYEYxGBhZL/ucjFoshlUrpYC+Z7RkeHobJZEJbWxusVmvJKadGqOEUQ74Cf66JHFtGphQTOT7sDvhedyMia/imgXoiX0qtFjpk5UQHmUwGoVAoS4uMdDexi8/5DJf4PrTPtRpOKpXKIpjV1VWq+VaKJE+zwmJhYLMxaGtjcMstKTz6qAReL/D88wm4XBv/PrveEY1GMTMzgzNnzuD48eMl3/U3OuFs1GbNbjNfWlqiJnJkximfiVwzNA3UYt1K0XSEkzv4CaxJodczpUYIhqTIVlZWKMEQL55Suptq0Xrd7BEOe5qfyMUoFAoYDAZ4PB5ebBHqjdyD8+BBEb7wBSkefzyJ//N/GIhEwN//fQaJBLDRU893CCuVSnR1daGzsxOhUAjT09M4duwYGIahw6X53DubmXDYyK1tFDOR4ysSaTYiqxRNRzj1jHBSqRSA7AlzQjDE7K2a+Yxm1mvjKyzPZDJYWVlBJpPB8ePHsbq6CrlcDoPBAKfTCYPBwKstRSPipz8VY8cOMZ58UozXvW7N90Qk2phsgOJRqEgkglarhVarRX9/PwKBAKanp3HgwAEoFIp1Sta1HPysBJUcthuZyFXbaMHlXjcCwzBF161HKrnpCEepVCKRSGR9je8aTjqdRjwex+rqKg4dOoRgMEgJZm3IrpeTAcBmTqlxtTY7WiT1LiKvbjabsXnz5qxp/mpRC0keLuD1SuD1iiASAU88sdZ19ItfSPD+92fAMIDJxKDUqYRS7/rZk/1zc3OYnp7OUrImasNcodEipnwmcuPj41hdXcW+ffto5MNFRM0X4QDc675Vg6YjnFp0qZG0Dam/BINBiEQiSKVStLW1ob+/n1M3UYJazPrwHeGU+yFnd+yRiJF0VlksFvT19UGlUmHnzp2wWCy8+sQ0KhiGwWWXtdH/i0Rrr+HCArI61WKx+Lrf5QISiYQerolEAjMzM5iensbKygrkcjn8fn9FLca54DqtxCWBERM5kUiEiYkJOJ1OzMzMYHh4OMtErtJ6IR+EU4rQaFMoDdQTheZwqjmoc1V+2SKMNpsN/f39WFhYQCgUgquUimyFaOYIh2CjDzmZOWITDOnYI4X+fPWuek/31xv//u+LuPNOI1IpERiGkPva31Ipg4cfTpW0TrWHsFwuh8fjgcfjwcmTJ7GwsICRkREcO3aMdnk1gpI1H+sBa4e4VCrNMpHz+/2YmprC8ePHYTab4XA4yu7242uvABrK0qLpCEepVFYd4aRSKRrBkMIzMT9yOBwYHBxcl7YJBAIN1QlXCWoV4bBBhEXZszDpdJoSDGkJL+XurtZaao2Ed787iksuyT97s2tXEhdcUNq14fIaymQyaDQanHfeeVhZWcmrZF2OUGwj1HBKWZO9R4VCgY6ODnR0dCAcDsPv99NuP/aAaSkWAVzvNZ0m9b3GeY83HeG0tLTkreEkk8mCv0NaZ8mfUCiElpYWqkNGCs/FXphaDZc2O+EAoARDCD2RSFDVBJfLVZFqQiN9aOoNsZhBJiOif5cLLq8lScmwnSqJkvW+ffugVqtps8FGzR3NEOEUS/up1Wp0d3eju7sboVAIMzMzOHny5LoB09w98e2xU+wa1Ppz1XSEo1QqqbcLuVi5ZJBMJrNSZOzWWafTCb1eD6VSWdbj1kI+p1m71OLxOBYXFwEA+/fvRzwez5rmz6dcXQn4lBZqZAwPa/DlL5vx2c8CNhsDl4vBzTefnb0pNOiZD3xrqbG7vEihfXp6GiMjIzAYDNQ2O1+6qRkIp9S2aI1GA41Gg97eXur6evToUTAMs85Erh6mbvVC0xFOvqYBkrY5deoUHf5TKpXQ6/Vob2+HXq+vunW20YZLKwFXhJNIJLKGLSORCG0X7e7uhslk4tTcDTj3I5x0Ok2VAHLxxz/asXevAn/6UwojIwnI5Shr9iYXtVKLJoV2p9NJax2Tk5M4ceIErFYrr0rWAH+dX+WsmRv9ERO5Q4cO0WYMo9EIoD6EI0Q4G0ChUEAsFuOnP/0p1Go1nE4nVldXIZFIoFar4Xa7S7byLQfNptfG5fpELoaQDHuan8ikiMVi7NixAwaDgXOyITiXajjs9u9AIICVlZWs2kcwaEAgIIZIBLzwgh3AWhv0RRcx+M//lOALX0jhmmuYssmGS5TzerBrHaurq5ienqZK1qQDjuuhynpGOPmQ22pOTOReeeUVAMDp06c5lbYSIpwKsby8jD/96U/YsWMH/vCHP2Bqagr33nsvPvShD+Gyyy6jCsADAwO87aFWKbVGiHDS6XRWBBMKrUndkyK/Xq9f5y9SCzJuZrC9dgKBADVzY7uFAsD09DReeeUVvPOd72D/NoC1Nuhbbllru33ve+UVtUFzfQhXslZrayv6+taUrJeWljA9PY2DBw+CYRikUilYrVZODt1a13DKAdtEbmVlBS+++CKCwWCWiZzdbi879c/GOU043/rWt3DXXXfhk5/8JO6//36ulgUAvPrqq7j77rtx5ZVX4o477sA//uM/4siRI/TNNDMz0/TRB1C/lFo6nabKCUtLSwgGg2hpaaHWCKVEjIW61LhEs9VwGIbB/Pw8wuEwAoEA9doxGo3o6OiARqPJOhBlMhlNvdx//wLuvNOIdFoM4nND2qABQKNh8MororKHPhvJD4ctKbNp0ybs378fiUQCu3fvhlarrXqwstEinEIQi8WQSCS48MIL15nIkc5Zu91etoncOUs4L730En7wgx/gvPPO42K5dbjyyitx5MgRAMD4+Dg++clPZvk8NLpadKmoVdMAW5qHEIxUKqX21Js2bar4zqrRlQz4RCqVymr/ZhgGfr8fZrMZmzZtKto8ceiQGP/8z3J84xspXHSRGLfdpsGll6YKWhCsrmYPfb7xjZm//O7G16hWNZxyIBaLIZfLaSux3++vSskaaIwaTilg7zPXRI5ch6GhobJN5EhdsBCaUtpmdXUVN910Ex5++GF87Wtf42JPRUEOwlgsRsPuZjdgI+DrUGUYBqFQCOFwmDohisXirMHWapUTahHhNBqIzhtJk4VCISiVSjrAevToUWzdurUkdYSf/UyGHTvEeOwxMS66KJ3z3TULgqyvsIY+r7wygz/9SVLgd/kDX1pqMpkM7e3taG9vRzQaxfT0dJaSdVtbG4xG44YHP18RDteDlIWIsaWlhQ7ZRqNR+P1+TExMlGwid042Ddx+++145zvfibe85S01IRzSbRaPx7MIp9mjD4A7Uss3zQ+s3T0pFAqcd955nGi/5aIZtNryrVsq2DI8gUAAy8vLNDIkhyC7G3KjtScnRVhcXNNHe/rptY8i0Uc7cUKE//xPCYxGBmZzEFdfLcZ3v7t+iPITn3gFP/rRFgAS/OIX4g211RqhhlMIhZSsu7u70dXVRZWsjx49CgDUNjufknWh9fjYY7UohRiUSiU6OzvR2dlZsokcH+RYLaoinMcffxyHDh3CSy+9xNV+NgSJcNjyNrVKqTXqHA67IE0IJpPJZBm8aTQanD59GplMhjfFWz7vlvhcu9jrSoZYSaGfXNdqVMEJtmw5+zoU0ke77bYU/uZv9gO4AN/9rmbdsOd3vnMhSFPB/LxoQ201rms4tdI+y1WyJsOlhZSsAf6UBuq9Zq6JnN/vzzKRs9vtMBqNG65bax01oArCmZqawic/+Un88Y9/rKk8vFQqhVgszprFea1FOAzD0M488ocUpA0GA9xud16L6kbpgqsUtUjXJZPJLIKJxWLQarUwGo0VqyQUwsMPR/HRjyry6qORNNpTT0mwZYsGOp0YZjMDj2dt6PNf/1WC8XER1lJt5HfW/pZIMvjMZ45iaIiB0+mEVqvNetxGrOGUsx5RDjebzUin01lK1uwiezNFOJWsKRKdNZHr6+vD8vIyZmZmcPjwYYhEIpom52PPlaJiwjl48CDm5uZw4YUX0q+l02ns3LkT//mf/4l4PM5bOKdQKOoS4dRT2oZNMMvLy4jH49BqtTSdo9VqN7zezUw4fH1g0uk0MpkMRkdHaQu4Wq2G0WjMa0nNJW64IYX+/giuuKJwC/D8PHDHHa+j/5+aStChzwMHRHjjG/Nrq3k8Fvh8Puzfvx8qlQptbW1oa2trqC41LtbLp2Tt8/kwNDQElUoFmUyGdDrN2VnUqI0IpMXeYDDQAdORkRGEQiHs2rWLqhuUo23HByr+JL35zW+muVSCD37wgxgYGMDnPvc53shGJBKtU4yuFeEA/NzhELCjqEQikRXBRKNRaLVa6PV69Pf3Q6/Xl32Na6UW3chrkwaKQCBABy4ZhkEymSy5BZwPnE2VkQaB7KhFJGLwox+lQN56IhFAumRztdXYA4apVIp2Oo2MjIBhGCwsLEClUjVcyyyXStbhcBjHjx/HysoKnn/+eVrvMRgMVT0GH23RXJOYWCyG2WzG8vIyWltbYbPZMDMzg3379kGlUnHq41MuKiYcjUaDLVu2ZH1NrVbDZDKt+zrXyLWZrkW6i7zJ+CrEJZNJRKNRRKNR7N+/H+FwGK2trTAYDJzdab8WI5zcgUvSQGEwGGC1WuF2u3Hs2DEMDg5yuNvSYbEwsFozcLkYfPCDGXz/+xIMDa1/rjodg4EBBocOiWhDgMXCbKitJpVKaZttJBLBzp07MT4+jtOnT8Nut8PpdEKn01V0fRshwikEooShVCrR3t5OB2pJRFSukjV7j/Wu4ZSzrkQigc1mg81mQyqVwtzcHGZmZjA6Ogqz2YxLLrmE88cthqZQGsiFXC7PinAkEglvnhIE5A3BFeEQBWu2wKhMJoNMJkNXV1feaf5qUQvC4ROl7j0ej2fVYZLJJK1v5Q5crq6u1jW/7XQyOH48DLkcaGmR46KLGFx2Gft1X4t4lpfXNwS4XChLW43k9C+++GIkEgn4fD68/PLLaGlpQVtbG5xOZ1n12EYmHLKeWCzO0jJbWFioSMmaoBkiHILcORxiINnW1oZEIoFQKNQ8TQP58MILL3C5XF6IRKK8EQ7AbxsgO6VWCdgmb6RWoFAoqMCowWDA9PQ0otEorFYrl1unOFcjHELehGDC4TA0Gg2MRiOnatV8oaVlrUU6GBRhbm4tfXa2eSD771yzNTa5iEQbC3mSQ53k+wcHB6mi8+joKIxGI5xOZ0lDlnzN4fC1HltOJlfJmrh2FlKyZq/ZLBEOwzAF3/dyuRwGg4Hzx9wITRnh5KvhAPwSDpvUSgEZCiRRDLHjJRYJxIMn9zGalRAIalHDYQ9cEqUEhUIBo9GIzs5OGAyGkq1+G6V7J1+LdD6UY7ZWCOznLJFI6F1vLBbLGrIkKbdCdY9Gj3CKRSO5StYzMzOYmJgoqGRdypp87LMapNPpgp8DkhGqNZqScPJ1qQH8CkiSnvVCj8FW/yUEI5FIssQZc11Ec9Es9gS1Xp/I8RB13eXlZYjFYnpXWo0UT71x6JAYX/5yC774xRi+9a0WpNMisDXTcjE8XL5+GgF5bQq9BxUKBbq6utDZ2YlgMAifz4dXXnmFpmKcTuc61YRGJpxid/hsKBQKOlRJhkvZStZtbW20zsVHhMPHmsA5rKVWa+R64pQbfVQKNiGwp85JHYakKiwWC/r6+sqWi6mVllozrJ87cJlMJiESiWC329Hd3c2pUkKt7/QIydx9dxw/+5kMO3dKMToqRjq98fO5+eazd6yVqEWXAvZ8x8DAAObn5+Hz+bBr1y7qksvHnEsj2BNoNBr09/ejr6+PKlm//PLLkMvlcDgcSKVSTZNSO+eUBuqFfITDd2s0OZRmZmboYcgwDPR6PdXOam1treoDU4sIh29CqxSFBi6JLfXo6Cja29ths9k43HF98NBDayTz3e8y2Llz7UCYnhajuzuD06dLO3geeaSwpXohVPLeEovFtMspkUhgenoaU1NTGBoagkwmg1wu55R46k047H0QJevBwUHMz89jZmYG4XAYJ0+eRDQahd1u56S1mE/COWeUBuqJ3JQawP0sDsMwlFhIBEN8Ysxmc8Fp/mrwWopwSBMFIZiNBi5rUX/iE2zdtMceW+s2e+opGYgsDYCSyeYrX0nhfe+r/H1S6SEjl8upiVooFMKhQ4cwPT2Nubk5mnKrRjaJj4iJi8+nRCKhkjE7duyAxWKB3+/HyZMnYTabqYJzpdEEXzUcIaXGEfginFy5mEQiQdtpXS4Xjh07hp6eHuj1+qoepxAaiRAqRaH12QOXpMYlk8lgNBpLGrjkc9i2FmA3BWSrP5f/+OedV9n7fKMaTjnQaDRobW2F2WyGSqWCz+fD3r17odFoaKtxJf4tjRLhFFvTZrNhcHAQkUgEMzMzOH36dJaStclkKutxM5kML2oWAuFwhNwuNaAywiHzGuRPPB6HRqOh7aK57bQSieQ1E4FUuz6JEAnBLC0tAQCtcfX392/YRJELPo3S+AJ5fmzdtEpIhk1S7353ZW6fXIMUuy0WCywWC5LJJPx+P3w+H06ePAmr1Qqn05m326sQmoFwyHNRqVQFlazZw6Ub7aFeKbV6oCkJp9IIh9QJyJ9IJAKNRgO9Xo++vr4Np/n5rhPVYn2+25aXlpYwPz+/buDS4/GU9OErhEZpX64UpeimFcfa8xeLGfzwh6kNfjY/+J6bYfvYhMNh+Hw+nDhxAplMBg6HA06ns+h7oBkinHx7FInyK1nv378fSqWSSskU8kUSutQaHLlNA0D+w5Q9zb+0tITV1VUqedHd3Q29Xl/yvEahx+ASzRbh5Bu4TKfTsFqtvAxcNmsN53e/k+Dee+V4xztyiYJELesN1gphzx5u53CqQbHXQ61Wo6+vD729vQgEAlRIVKlUwul0oq2tLW8KtRFrOGxsRA5sJetcKRl2hx/73KmV0kCh/dYSTUk4SqWSamIRiMVipFIpLC4uZk3zEwdGj8cDg8FQlVwM30X9Ric0Yk1NCCZ34HJ8fBwej4eXTrJmruHceOPane0rr0iRn2RK2UPppFRwBQ5rOAQbrZUrJDo7Owufz4eRkRGYzWZqHU3S1c0Y4RQCW0qG2EV7vV46XOpwOGC1WoWUWqOD1HAikQgikQiCwSDC4TBOnDiBlpYW6l2Sb5q/GvCd8mq0LjWGWXMOJQSz0cDl1NRUw6tF12rd3/1Ogn/6pzfgU58SQ6NhEArll6pZk7Fhf70QRLDZmCxhznqj3AOdPd1PrKNPnTqF48ePw+FwNLxUDlmzkkOcbRcdDocxPT2N4eFhHDt2DBKJBEqlkpcuPWEOpwokk0m8/PLL2L9/P7xeL9xuN/7lX/4Fl156KRQKBWw2GzweD693w40cgXCxfiwWowQTCASowyVJQxYbuGxEteh6YS2qUeGOOwB263MuiqkKsPHpT4/hU59SwWrVodJIh+sIp5oDkm0dvby8DJ/PBwB4+eWX4XK50NbWVrV6BNd3+EQOpto11Wo1dexcXl7Gq6++Cq/Xi9nZWRoRceHKW+z51ys93TSEc9999+Huu++myrYOhwMPP/wwzjvvPIjFYhw5cgRSqZTXg6nZi/r5CIHdSBEIBLIGLrdu3VqWw2WjqEXXA5lMBsePr2J8fBXB4AqUygsQjZI8fXXX5dprT+P66+dx9OgiFApF0RpILcHFHTlR59DpdPB6vejs7MTc3BxGR0ep7qDNZquobZgPqRyyZy5AnrtSqYTL5YJcLsf09DT27t2L1tZW2mxQaZbmnEupffOb38TTTz+NkydPQqlU4rLLLsO9996L/v5+rvZH8Vd/9Ve4+uqrsWXLFnzve9/D//7v/+L888+n36+VCVuzKwFkMpmsCIYMXHLlu9NsEU6l6xKfHWLktry8jGuvvYa1LnfX4Te/6cbSUju++c0MnM4ZeL1ejIyMlN12zEcNhyuQvdlsNrjdbiqoOTY2hhMnTlADNaPRWPL++UhRAeClEUEqlWYpWfv9fszMzFAl67a2trKIl+gPbtTgUGtURTg7duzA7bffjosvvhipVApf+MIX8La3vQ0nTpyAWl1p+2d+sE3d8nWp8X1Y1+Ix+EhJsQcu5+fnkUgkMDQ0BIPBwLnDJd8pwXpHOCQaXFxcRCAQoG3fJpMJ3d3dePjhCD76USVSqeICnOXC6Qxi924tHn88hX/917WUSyQSoW3HDMNwMulfLrg80HPJkAhqdnR0IBgMYnp6Gq+++iokEgmN8DY6Y7huNyaffT4aEXJ9a4hpHiHe8fFxHD9+vKiSNRvkep5TXWrPPPNM1v8fffRRWK1WHDx4EFdccUVVGysGrgY/y0UzpNSKDVwaDAZEo1FcdtllvLzRmrmGk+/wZHflBQIBBINBKr8zMDCwzub7hhvSVc7a5IfPpwUA/OIXErz//Zm/qEWraB1gYWEBPp8Pe/bsgU6ng8vlyuvr0kg1nHxrAesPSLaQaH9/PxUS3b17N3Q6HZxO57o2YwI+ut7y7bFaFItEylGyzl2Tj71WC05rOCsrKwAAo9HI5bLroFQq887hvFZTaolEIitNRiR5jEYjPB4PWltbIRaLsbq6iunp6YZLT5WKWsjyELIm15N05TmdTmzdunVdNMhWfr7wwrOvnVjMIJMpb8amyM4AiDA/j3WunyKRiE76JxIJ6usyNDQEu90Ol8sFvV7Py2vD5etRylq5QqIzMzNUSJSdXiTPla+UWr1arYspWZO6Non6SiGcpkupsZHJZPCpT30Kl19+eVb6iw+0tLQgkUhkfa0WhFOrlNpGHxT2QGsgEKAOl4UkeXLX53v/fK3NB9LpNABgeHgYgUAA8Xgcer2ezhZtpABO7AUefzyDCy+Mw2JhYLVm4HIxuPTSY3jggW0c7DK7lTrX9ZNALpfT1ttgMAiv14tDhw5BJpPB5XLRG8FazuGUinKjB/ZzJXf+x44dAwDa6cWXQRzfKbWNkE/Jenp6GqdPn4ZWq0VbWxvVezxnI5zbb78dx44dw+7du7lasiCUSiXi8XjWG0osFiOZLF+yvRzUIqUGrL8zI6kdQjBk4NJgMJTlcFlP8c5GWTtfmgxYu/b9/f3r0mT5wFZ+fvrptY/QU09J8bd/mwTDAM88E0F3N4MXXpjgiHCyUYrrp1arxaZNm9Df34+5uTl4vV6cOnUKADA7OwuLxVL1YcRHSq0SkDv/3t5eLC4uwufzYd++fWAYBnNzc9BoNFUNfBM04oAmW8k6kUjQZoOTJ08CAPx+Px2sbQRwQjh33HEHfvvb32Lnzp1wuVxcLFkUhaRtapFSS6Uq07EqBeTDm8lkEIlEKMGQgUuDwVCVw+VrNcJhd5Plpsn6+vrw8ssvo6enp+QPfT476IUFUVbtJhgMAQC+970V3H67ruK9s7E2JFredZBIJLS9NhAI4MCBAzh58iSOHz+OtrY2uFyuihsN+GwaqAS5QqI7duxAIBDA5OQkLBYLnE5nVUTLxyApwB2RyeVyuN1uuN1uzM/P45VXXsHo6CiOHTuWV8m66VJqDMPg4x//OH75y1/ihRdeQGdnJ1f7Kopa+OHkA58ptVgshoWFBQDAvn37kE6naWqHC3M3oPSUXbXr84VS104mk1TjbXFxEfF4nNa0ctNkue+jUsBWfiYEQP6WShk88MDazdDcnBK9vWn89V8n8KtfVXOHvVbD6e5mEAqhYrUBhUIBkUiEK664AoFAAF6vl1oKkEaDcrQFua7hcJmukslkEIvF2LJlC6RSKaanpzE0NIRjx47RlJtWqy3r8fiKcPgQ75TL5ZBKpXj9619Pu/yOHDkCkUgEh8MBu93Om81KMVRFOLfffjsee+wx/OpXv4JGo4Hf7wcA6HQ6Xj3m60U4XD5GrnJ1NBqFRqMBAAwODsJoNHL+JuSrmMpevx4RTiaToa3fJE2mVCphNBo3VAGv5DoUU35+7rkIzj9/7T1y661vLXvt/Fjb4+ioGCsrcVTaxc4+1Im+WTKZzCq+k0YDg8Gw4bVplJRasTXFYnHWZH8gEMD09DQOHDhAhURLHa7kwyitlHmZSkDWzO3yW1xcxMzMDF5++WVcccUVNR8eropwHnjgAQDAlVdemfX1Rx55BDfffHM1SxdFPQmn0g8GcbjMN3BJTN3EYjFeeOEFzp1ECdiEwwdq2aWW200GgGq8bd68uezp7EqvCelGI+mukyfFOP/8DA4dEsPlCsLr1aD6LrU1fOUrKRw/LoLJxMDjKf/38z1HmUxG0zChUAherxevvPIKZDIZ1T0rdi25JBw+Dl32/thEOzg4iNnZWUxPT2NkZAQmkwlOp7NovYOPPday1To35chFXatcVJ1SqwdIlxpbnK7RUmpk4JIQDHG4JO6hRqNx3d0F27yMD7CbEvgCnwKb4XCYdpPFYrGs1u9qvHYqAbsb7QMfSOLrX5djfl6EXbsk0GoZ3HGHAgsLXB4iDL7yFSm+8pW1/1VqwFbsGmk0GgwODmY1GoyOjsJkMsHlcsFqtWYdYlxHOHxED4XWLCYkarfb4XQ617WT8xHh1GqYNBck+qk1mkZLjQ2SrovFYrTvvN4RDpnhIARD7rr1ej0sFgv6+vqgUqmKvsgk3cHX86hFhMPV2gzDZHWTraysQCqVwm63cyLBUy2cTgbPPBNBMCgC+3P9s5/J8F//xcedY/GWaC4hFotp51MsFqN2AuxGA41G09SEw0aukOj09DQOHjwIuVxOVQ2ImjMfkQhQ22HSeqIpCYeE+PF4vKaEk0sGxQYu3W53RamxWtRBGpVwiqXJWlpaoFKp0NXVxdV2AVR3Z3nhhezurrXnvWYhzR9KaYkuhEoOdYVCQQ/jpaUleL1evPjii1Cr1UilUpx1bfIxM1MuQRAxTYPBgIGBAczNzWF6epoKifIhG8QX4ZRivlYPNCXhkAiHXcfhWwWAIB6P49SpU9RBtLW1taDUSSXg83k0Wg2H7RgaCAQQjUah1WrzpsmCwWDdtdRy8fDDUdx2mwLptAhc1WkKoZKWaG4f/+ywYSqVwszMDE6cOIGDBw/CZrPB6XRmtdyWi0ZTdma3k8fjcUxPT2NiYgKxWAxHjhyB0+ksS0iUr30WQinCnUJKrURIpVKIxeKsWRyxWEynxrlC7sDlysoKRCIR0uk0Ojo6oNfrOS+81UKEtF4RDltIlFxP4hja3d0Ng8HAaTdZOajkmtxwQwq33sr/h9ZsDqO9vQXT05KqDNi4OtSlUina29sxPDyMrVu3YmlpCUeOHIFYLIbL5YLT6Sy7S7XRCIeNlpYWdHZ2Qi6XY2xsDDKZDIcPH4ZYLKaiqZWKFbO7ybhEI5qvAU1KOMD6TjWuhC/D4XDBgUu73Q6fz4eBgYFqt18QfKfUaj0rQwzdyB9gTUjUZrNhcHCwrIOp0SKcWmFhQY1f/CIIsViBau6p+FAiV6vVsNls6Ovro8Kap0+fpoO1NputpIOPL8LhY76FNFYQ0VQiJEr0zMqZZaqXekG9PktNSTgikWidYnSlNZxYLJZV6E+lUgUHLhcXFxu69boU8E1oqVQKCwsLedNk7e3tFbd81yP8LwX33hvF5z6nAL8pNQZvepOW/q/SDjWAv+vIFtaMx+OUeE6cOEGjgGKDls0gtMnuUhOLxdS/hgiJ+nw+nDx5kgqJmkymDd/rfHS+kXWFGg6HUCgU61JqpZABewqdPXBJTI50Ol3BF6oWdaJaCYRyBXaabHZ2FvF4HMvLyyWlySp5LK5RzYf9xRfFyGSAa65J4re/5XOmoXYdauWgEEm0tLSgq6sLnZ2d1D76wIEDUKlUtOsrNxXdyCk19pr5zga2kOjq6ip8Ph8VEnU4HHA6nXSoOxeNqM/GJ5qWcORyeVaEU+igZg9cLi0tIRgMQqVSVXQg1qK+0gx6Z+w02dLSEjKZDIxGI9RqNXQ6HS9q4Y1Yw3nb27j1vdkI1XSoAfwc6hu1+bO7vvx+P3w+H4aHh2mjAbETaAbCKeUQb21tpRYCbCHR1tZWKqnDJtt6EY7QNFAGRCLRughHIpFQmYhwOLxufqOYp0mpqPesDxeohHDS6TRNO5I0GYkK2WmyM2fOVKRNVioarYbzoQ8l8MMfysBfOm1NQ42rDjU+ajilHlpsF8twOAyv14tjx45BJBLRORc+0l+1JFg2RCIRzGYzzGYzkskk/H4/pqenMTw8nCUkysdsDyBEOJyD1HDIwOX8/DwAYPfu3WAYBgaDoeSBy1LxWkmpMQyD1dVVSjDLy8toaWmhda1Cdgh814cagXDYhmv/9m9x/PCHfKTSGKjVgMuVwV/91SJ++1sZFhaUWFo6hZUVG3S6ytWnG0H7TK1WUzsBUngfGxuDWCyGz+eD3W6vusOKj0HSSg9xmUyG9vZ2tLe3U2vwkydP4tixY9Dr9bwI6hbrUiOPVw80JeHMzc2BYRj88Ic/xH333YevfvWr0GrXiqqbN2+GwWDgTYvsXE2pxePxrG6yTCZDSbu/v7+kO9BGUYsuB6V+yAnRmM0MNVwzmxN461uT+OMfS+9KKhXhsAjDwxIMD1vxy1/+Clu2XIiVlQQOHDgAtVoNl8uFtra2uqotANXbCZDC+9TUFE6fPo2xsTGcOHECDocDLpcrr31yKeCLcKpdU6U6aw2+tLSE0dFRRCIR7Nmzh6bcytUBLLTXcrrlaoWmIpwvfelL+M1vfoOjR49CrVajvb0dn/rUp/CGN7yBCl8SO2U+UIsIh++0HSHNdDqdNXQZDodpN9nWrVuh1WorUkngC/Ws4UxOivAf/yHHzp1SKJVrP/fEExI8+CD3k+drONsk8NBDSYhEgMWiRXu7FQMDA1TdeXh4GHa7He3t7SUdzI3mX8OGVCqFQqHApZdeipWVFfh8Prz88stQKBS00aCcVDhfUjlcnS1kkNblciGdTsPj8cDn8+HUqVMwmUxoa2sruaU8H855pYHvfe97uO++++D3+7Ft2zZ897vfxSWXXMLV8gDWZE6+8IUv4KqrrsLf/u3f4i1veQve/e53Azj7AeDbkZNPPxmAvyiBpMlSqRROnTqFcDgMuVwOk8lUlmtoMTRjhFMMxNnzjW882xwQja79vbjI/4d5164ktm1L49lnzx7sZOiyvb0dwWAQU1NT9GBub29HW1tbwdeR6+5EgNsUHam56PV66PV6DAwMYHZ2Fl6vFyMjI7Td2Gw2l9RuzLf6NFdrSiQSGt0QIVHSUl5ISLSUdc/ZpoGf//zn+MxnPoMHH3wQl156Ke6//35cffXVGB4ehtVq5eIhAACf/vSn6b8VCgUSiQT9v0gkqkl0APA7xctlFJUvTQaAdpJxXagFGlenrVxkMhls2cKulawV8M82CPD3YSWWBxtBq9Vi8+bN6O/vh9/vh9frpVFPIU+bRqjhFFovd2/sg5jUPk6cOAGGYehsTyF9s0aPcAhyiYEtJEoivUOHDkEmk9FroVKpSlr3nFUa+M53voNbb70VH/zgBwEADz74IP73f/8XP/rRj/D5z3+ei4dYh9wuNYD/dFQt5P2rOVjzpclIN9mWLVug0+nw0ksvwWQylfSmLReNUtgvB+xDKRaLYXFxkV6/f/gHF/7t385DOi1GIYJ54xuT2LGDm1x5W1sGd92VxqOPSuD1lu7sye4AY3vayOVyKjUjl8sbbo6JjY0Igl37II0Ge/bsgU6no26l7HoWXzUcrmtmhUiMHekNDg5ibm6ODtMaDAa0tbWte865ez0nU2qJRAIHDx7EXXfdRb8mFovxlre8Bfv27at2+YLIVRogj1urCIfPxyjHc4e0gC8uLlLPHaPRiI6ODhiNxnXplVqIg/K1Ntf7Ju3eAHDw4EHEYjFotVqYTCZ4PB5ccYUGl1wSw/XXFybnyy5Lc0I4Oh2DHTuSaG8H/v7vM0gkgJYWIJ0uL3VFPG36+vowOzuLqakpjIyMwGaz0cYaLsBXSm0jiEQiaiJGJvwnJiay3Er1ej0vB24tIpx8YNtFxOPxrOdM5plyhUTPWcJZWFhAOp2GzWbL+rrNZsPJkyerXb4g6uH6SV7AWtSJCoFYIpA/qVQKBoMBZrO5ZM+dcyXtVQkikQgl6KWlJXqH6Ha7YbVa1xF0MbIBgG9+s9qOorVU3Uc/Gsf73y/Hd76TwkUXMRXbSBOw01Fk7uXMmTNIp9M4ffr0hk6eG+66ToTDBnvCPxgMwuv10vSTwWDg/L3IpxV0qWhpaUFHRwc6OjoQDAbh8/nyComes4RTL9QrwqlF2zL7ORClBEIwq6urNE22efPmolI8hdZvxsJ+pftmD60uLi4iFotBr9fDZDKhu7sbSqUSO3bsgNlszltsr41WGvCtb60d/o89JsZFF3Grek7mXvR6PYaGhhAIBDA6OgqLxYL29nY67V8OGoFw2NBqtdi0aRN1Kz1z5gyi0SgOHjwIl8sFi8VS9QHMV9NApWtqtVpotdp1QqJarRaxWGzDs7ApmwbMZjMkEglmZ2ezvj47Owu73V7t8gWhVCqxvLyc9bVGs5muFPF4HJOTk3TokqTJPB4PDAZDVZYI53qEk5tmJEOrJpMpr1PoRq/lRz+agssVxU03cV/zWgP50K9FOr/4hQTvf38GDAOYTAycTu6up0gkglQqxcUXX4xIJJI17V+urUA9VQuKgfjYSCQSDA8PQ6fT4eTJk1lupZUaqdUrpbYRcoVE/X4/Tp48iaNHj2Jubg5tbW0ldfbVAlUTjlwux0UXXYQ///nP+Ju/+RsAaxfxz3/+M+64445qly/6uPkinGack2GnychQq9FopIckV0oJQPMSTrG1U6kUvX6Li4tIJpM0zbjR0Gop15U/slmPhQXgda87e0OxusqtWCd5viqVCn19fejp6cH8/Dy8Xi9Onz4Ns9lcVkTQKBFOLkiBv6enB93d3QgEAvB6vdi7dy80Gg1tNCjXSqBR1AsKQS6Xw+1248yZM+jt7cXq6iqOHz9eUmdfLcBJSu0zn/kM/u7v/g7bt2/HJZdcgvvvvx/hcJh2rfEBpVKZt0uNaxO2XHBBaplMJqubjO0cajQaoVAo0NfXx9GOs9HMhENAZooWFxexuLiIYDAIpVIJk8lUsfMq2TdRFPjbv03iscdkuPtu/rThskHcWPMrQ/OV/mDbCsRiMXi9XgwNDeHEiRNwOp1wuVx5OxobLaVWbD2RSASTyQSTyYRkMkkHZ9mNBvlayPOtyUcjAh/ty5lMBmq1Gk6nc52QqFqtxsDAABwOB+ePuxE4IZwbbrgB8/Pz+PKXvwy/34/zzz8fzzzzzLpGAi7R0tKSNYcDNK7WGcMwtFhNFJaJoKjb7YbRaKRpslOnTjVs23U9kU6nEYvFcOLECQQCAaTTaRgMBtjtdmzatKlsh8lC+NnPZNi5U4pAQIRjxyS4/34Gb3xjCjt2SMB3HYcNogyd4jDA2ehQVygUNCJYWFiA1+vFrl27qEir1WrNGg2olzBmNevJZDK43W643e6sFnKZTAan01m0mYKvCIcPCRr2HA5bSJTYg3PtVFwqOGsauOOOO3hNoeVCqVTWvGmgnMdIJBJZCsvJZJIau3V3d0OtVud984rFYqS4PGVywCfhcEn4DMMgGAzSuZhgMAipVAqDwVBRs0QhiEQizM0pcfiwFEtLEvz852sfiePH19b+n/+pjR4VGfYsdeizEpT62rBbj4mZ2sjICDVTc7lcvNzp19pKgLSQk0YDr9eL0dFRmEwmuFyuLIIle2zEGk6hdfNdT6lUCqfT2dxKA/WAXC6v+eAneYx8H9xMJpPVTRYKhWiabHBwEDqdrqTQuRHUoqtBNWsTZQRCMgCorYTJZMLq6iq6u7u52irFhz/8tnVfq2UQqFYz6O/P4IMfzKwb+uQ6dVXuOmwztUAggKmpKezZs4caiqXTaU5SQvWMmNhzLrFYjBIsaTQgbqXNIpdDbFrOWaWBeiDfHE6t1Jwzmcy6NNny8jIkEglNPxgMhop8d+qlFl2Ptdkkvbi4iNXV1Sw7arYlsdfr5W3fn/70QXz3uxcilWJ/8Gtz99famsHDD8ewdSuDnh5p1tAn16jm+rHrIIlEAmNjYwgGg3jhhRdo1FPI1bLUvTVCik6hUFBpmaWlJXi9Xrz44otobW1FIpHgvEbMV10IQEN0peWiaQlHqVTmreHwSTjJZBLpdJqKCSaTSeh0OjrTUShNVg5qYcDG1zUq5blHo9GswUuxWAyTybSullVLvPGNXrzjHZ1461uNNX/s1VUx3ve+taJ8LBaHSMQP2RBwcajL5XK0tbVhcnISF154IaamprBv3z5oNBq0t7cXlVwpBD5SatWsR9ScjUYjNm3ahJmZGQwNDeHYsWNYWFigUXe1e+YragKKE0490mlAExNOS0sL7ym1fGkysVgMpVJZcTfURmjmlFq+tdn6bouLi4hGo1Q+prOzE62trSVLmtRGkoeIdJK/+YdUyuDBB+N5H48PhWeuIBKdtZAeHBzE9PQ0JiYmcPLkySw/m1L3xnWEw9VBThS6x8bG0NnZiXA4jCNHjkAsFpc9v5SLehFOvdC0hENSauw3arWEwzAMvQMn3WRisZj6VhiNRpw4cQJWqxUmk4mrp5KFZk6pAWtv9kgkQuswS0tLkMlkMJlM6OrqgtForLtpWD6YTCRVwr8adC5+9atZOJ2z8HpbC0YH9arhFEIuQchkMng8HrjdbqysrMDr9ZZlFtcoKbWN1iQ+XH19fZifn6eCmqTWWK6HjRDhNAkKqUUnk8my1kkmk1ndZPF4nHaT5bsD5zvlVYuUGl8imNPT04jFYti/f3+WfAwXqUaAX5XutrYMHnggio9/XJFTy+ETa1HU6OgojEYpFhcXcfLkSbS1taG9vb2qmkjeR+M4Wsr3mrJVjssxi+O6lsG34yd7fol08hEPG3ajwUZ74INw0ul03brQNkJTE04lNZxMJoNgMEgJJhgMQq1Ww2g0Ur2pYncotXLk5HP9ag+eQvIxra2tkEqluOyyy3hJNfI9P3TTTSls3hzBFVeoN/5hTiCCxZLGW9+6De3ta7Izy8vLtCai0+k4H86r5aBmMbM4kooiMyj1aIsuF4VIkd3Jt7y8DJ/PhwMHDkClUlG30kK1yWZQL+ASTU04pdRwiqXJnE4ntm7dWlY3WTMQAh/rk0iQpMqIfIzFYkF/fz9UKhWWl5dx4sSJhmzHbFScOBGhTQLsmsjAwAB8Ph/GxsYArA0Eu93uqnyMuDzUy30P5TOLGxkZoZP+XB+8fEU4G6Wp2K+f3++Hz+fD8PAwtRHIFUrla7anUT+DTUs4xdSi86XJdDpdwTRZOahFSq0RCC2ffIxKpSo6V9RILdflrk1gsTCwWjNIp/m2kWbwxS/GC3akyeVydHZ2wuFw4IUXXkA0GqVT/263mxP142pRyWeokFkcwzDQ6XRIJBKcdCryVcMpdU328yT2EMeOHQOALMmgelge1FNppGkJh6TUyJ1RKBRCIBDAysoKdu/eDaVSCaPRiL6+PhgMBs4Yv9kjnGJKBmwR0cXFRWQyGRiNRtjtdmzevLkk/5RmlM0Bzu7b6WTwox9F8Y1vtGDvXj4PdBEOHpRgcjIFt7vwNSMH3LZt25BIJODz+ajWmcvlQnt7e8m+NrWo4ZQDtlncSy+9hEgkgueffx42mw0ul6uqtuNGSlURe4je3l5qI7Br1y4YDAYkk8m6+PYITQNlYm5uDi6XC+9617vQ3t6Ov/3bv4VKpYJMJsMll1xSlblUMdTC5K1WKbV88jGtra0wmUzUkrpRvHZqUcOZnBRhcVGEa66pTQ3nmWdkeOYZGXbsCMNsBvKJKLCfM3socX5+HlNTU9ixY0dZvjaNKLYpkUigUChgtVphs9ng9Xpx5MgRSCQSWusp9/PMtSgmwzBVP2e2jQBx7lxaWsIrr7yS1UbeiLM9XKGpCGd2dhZf/epX8eyzz2JychIKhQJbtmzBe97zHlx88cWYm5vD1NQUb2QDNGcXGRvpdBrhcBjHjh1bJx9Tbj0rF43YFVMOtmxhy7bXYg5n7THe+MY1govFSlOmFolE9OCKRqOYmprC0aNHIZFI0N7eDpfLlTctVc8aTikQiURZ0QD5PFdiFsdHmzXA3WwLce48deoUNm/ejKWlJdpQQRoNKv0sllJrOqcinPHxcdxzzz147rnn4Pf70dbWhve///344he/WFV+Vq1WQyqV4v7778frXvc6mM1mfOpTn6KdPLUyYOPTAoHrlB0ZXiVRzOrqKjV0y5WPqRbNGuGQ5//ww1F89KOkLboWH8izVgSFBj9z95gLpVJJfW3m5uYwOTmJ0dFR2Gw2KrHEx+HC99wMW9+sErM4vgiHj7qQVqtFW1sbBgYGMDs7SxsqLBYLXC5X2eZpr7kI5+TJk8hkMvjBD36Anp4eHDt2DLfeeivC4TC+/e1vV7xua2sr/uM//gPA2p26WCzO6lSrlQFbubM+5YCLgzVXPoZovHk8HoTDYUSjUXR2dnK042zURg2AW5DU4vbtfnz3uwl89KOX8PZY+fDccxFccAEDoHJlavYBvbq6Sovxcrkc7e3tcDqdvCgNcIViNRe2WdzCwgKmpqY2NIvjuobD1/Q+u0tNIpGgra0NbW1tiEQi8Pl8OHHiRNnmaeRsbETwQjhvf/vb8fa3v53+v6urC8PDw3jggQeqIhw2RCLROgHPZjFg22j9ciOcfPIxhbryJicnmzIKAbgls0QiQTvwMpkMTp06BbPZDIejDQAgEjHUDI17rKXS+HqM1tZWDAwMoLe3F36/H1NTUxgZGYFGo+HsIOKjC2yj9dg1kI3M4vgYJC1lj+WuWWifKpUKvb29lGR9Ph/27NkDnU5H3UoLKTcIXWoAVlZWYDRyJ44oEonWtUY3qgFbuetv9BzIbFE++Zju7m4YDIaCb8baaZI11toMwyAUClGSIfYRJpMJYrEYF1xwATQaDXQ6EczmDEymtfboXbu498Pp7c3gIx9ZcxT1ekXUiqDQvoHKnr9EIqGmYsFgECdOnMDy8jL27t2L9vZ2OByOimWG6i22Wcwsjo+5Hj4inFIlaIg3USKRwMzMDCYmJrLcSvV6fdZzfc3P4YyOjuK73/0uZ9ENQe7wZz39cPheP5VKYXl5mR6YRILHZDKhp6cHKpWqIUQwGynCSaVSCAQCWFhYoC6hpEHCaDTSoqzX66XXzulksLAgxsICMDzM9Yd2LbL5f/8vhgsuyODWW5MsKwJ+a0ZarRZ2ux0ymQwWiwWTk5MYHh6uWEaHr6aBSn4n1yzu1KlTiEajSCaTsFgsJaWhNgI5V+pJYnK5HB6PBx6PBysrK/D5fDh48CDkcjnVq1MoFBuSbdM0DXz+85/HvffeW/RnhoaGMDAwQP/v8/nw9re/Hddddx1uvfXWynZZAHK5fF2E0yiOn5WCRFBEPoZEMcvLy1AoFDCZTFXNFjUaKZSKUjuTyDVbXFzEysoKVCoVTCbThi6h7H0//HAUt92mQDrN3YeypSWD3l4Gc3MiWK0kauHXiiAXpFXY7Xajvb0dKysrmJycpDI67e3tZYlP1jPCyQe2xMyLL76IVCqFPXv2QK/Xl/3ccsGXIgBQWdSk0+mg0+my3EpJWlgikZwbNZw777wTN998c9Gf6erqov+enp7GVVddhcsuuwwPPfRQRRssBFLDYUc4fKe7+H6MZDKJQCCATCaDvXv35pWPqRZ87p8cGHzk98m6uSDCoYuLi1hYWKDXzGq1YnBwsGzZ+BdfFOPXv5ZwSDZrUc073pHGo4/GyjZX45PA2SKb09PTOH36NIaGhuB0OtHe3g61uvA8UiOrO4tEIshkMiquSYQ1h4aG4HA4Koro+BokJfutFBKJBA6HAw6HA9FoFD6fD+Pj48hkMpDL5XA6nVnPldSN6oWyCIeErqXA5/PhqquuwkUXXYRHHnmEF8bNreFIJBJOBrSKgcsIh11XIIOXZIZoYGAABoOB8+tWixoO3wVlYn9AhEPlcjnMZjMnHkVvexu3Q58SCZBOAzt2SHD4sBgMA5hMTFF1gVzwPTsjl8vR0dEBj8dDbaR3795NW+etVuu692EjEw57PSIR1NHRkSWMWq5ZHB8RDtkjV89bqVSip6cHyWQS0WgU8XicPteNGg1qBV4e3efz4corr4TH48G3v/1tzM/P0+/Z7XbOHidflxrAb9Gs2hoOkY8hJEPkYxwOBzZv3gyRSIQ9e/bwQjZAczYNZDIZhEIhxONxvPjii4hGo7R+1dvbW3L9KheHDonx5S+34P/7/3SYnm7Bvn1ytLZmsLrK3RwOaZpcWhJlqVAHgyFO1i8XG+X2iY10PB6H1+vFyZMnMTQ0RHXBKjUa2wh8NyGwhTXZZnFDQ0PUIruYWVw9NM8qBfHt6e/vRzKZpBYRpNGA+PbUA7wQzh//+EeMjo5idHQULpcr63tcHna5rp/kDcYn4ZSbkiKHJbs7SqPRwGg0YuvWrdBqtVlvOmK50IyFfXaEUy3i8TgWFhayrKgZhtmwC68c/OxnMuzcKYVe78Svf8021OPy+pBrcnbI84EHYsV+gTeUc6i3tLRQGZ2FhQVMTk5i586ddOKfjxQT1xFOocO8ErO4eqhPV7MusX2QyWRwu91wu91ULHVxcZHTG/9ywAvh3HzzzRvWerhALuGwIxy+UEqEE4/HaQQTCAQgEolou6bJZCqqtkCeQzMSDkEl6xOfIkLM4XA4y4o6kUjQ6etqQPTSRCLg6afX3v7PPedEX18CIyMyrBEEfx08zz0Xwfnnl/7+rLcYKrsLLBqN0ol/cqjF4/Gq5JAI6mFPkFvHKmYW10wRTqHBT41Gg4GBgeap4TQack3YakE4+SKcXPmYcDgMjUYDk8kEt9sNjUZT8oeJHaXxgUaKcEh6kbQtE2L2eDwwGo30Lg0AlpaWONkjWy9NJFrb5+qqHCMjnCyfBxsPeZLDttAh2SiCm0qlEr29veju7sbQ0BD8fj9eeOEF2Gw2uN3uqmR06l0TyjWL83q9WWZxLS0tvEQ4fKShX3PSNrVCqSZsXIKsX0w+JvewLAdcpqUKrV8vwik2fFmKrhsX+2brpfGnJMDG2ZSa1ZqhQ56k9Z38LRKJIJFIIBKJIBaL6zYnUQrEYjE0Gg2i0SgGBwcxNTW1Tkan3Pc/HzWcSg9drVaLTZs2oa+vj5rFraysQCKRIBAIcKZPx2dKTSAcHlDMhI1rEPmYmZkZWrzW6XQ05VONqRsbfEc4fA6u5nv+ZPiSkAwZvmxra4PJZCo5HcPVYXTDDSn099fSRvps3eZd70pAJssgkTj72hKiIbJMJIImxNNoHjZsiERr6s5ERmd2dhaTk5MYGRmh7celyu3XO8LJB7aJ2tjYGMbGxiixEgHRasSI+eh8AwSlAd6Q26UGcEc4DMMgEonQw3J5eRkymYwW+V//+tfz0mJI2iSbOcIJh8OYmZkpe/hyI3C9b7GYQSYjAndWBPnXefbZIM47b830jmHWiEQsFucd0CNt/ZlMBplMhkbwfLb6V4Lc/bCFJ0OhEKampvDSSy9BrVaXJKPDh/YZl9dLoVBApVLh4osvzlJ0rsYsrp4RTlMoDTQauI5wUqkUtaZeXFxEIpGAXq+H0Wik7bdkBoTPfna+oxCu1ybDlwsLCwCAw4cPVzV8mQ9cfkCIjbTLxeADH0jiU5/iyj9pbY+kXkP+TqfTNF1WyhR4MBjEwsIC5ufnEQ6HYTabqSgtuXOt5Hpw7YdTaC2NRkNTUqQQf/LkSTpQmm/okuv3JB9aauT1I8RKrKMrNYsTUmpNBqVSieXl5ayvlUM4+aRQiHxMf39/3iHCWgmENjrhEPHQhYWFrOFLANi+fTsn+lW54OqaOJ0Mjh8PQy5fk5fxeofxne+c95dop3KIRAyUSgadnRncckscjz4qgdcrgtd7iA5R5pveT6VS9FouLCwgk8nAbDajs7MTJpMJUqmUPvdUKkVrPOUODXKdntsIpBDvcrmwsrJChy61Wi0duiSfLz4iHL7Xq9YsTiCcJkOulhqwMeEkk0kqhUJqCuRufGBgYEP5GHJg85ni4Ft+ptK2ZbZ4aKHhS5/Px9vAKpdgl47e/OYZnHdeGz7wgeparhlGhEhEhOPHxbjttgQ+8pEM4nEG8fhmTE1N4cUXX4Rer4fb7YZarcbi4iLm5+cRCASgVCphsViwdetW6PX6ddeQ/bqxJVHY5FMKuK7hlPpz7PZjn8+HM2fOZEU9XN9g1bIJIdcszufzUbM4YpuQL8qvR5davdvsm5pwlEpl3i419kXNJx9DagqbNm3K++EuhlqoGTRKhEPmici1k0gkG1og8Jkb5vPDYjJx46MkkTD44heTmJwUwe1moFCIoFDooNVqYbPZMD4+jsOHD4NhGCiVSjgcDvT39xfVLSMg15Z905NKpSjhlEs+1aDSA10mk1EZnaWlJUxOTmL37t0AgEAgwJlnT73sE4iPDbFNmJqaws6dO2knJtssrtZzOI2ApiaclpaWrDkcYI0Q4vE4/H4/PSgZhoHBYKDyMaXmWPOB78FM8hj1iHAYhqHzRLnDlx0dHSV14vFFlnweoiMjWjzwgIHVRFA50mkR7r5bjrvvBlZWgnlTZU6nE8CauO34+DhisRhtCy8V7OaS3PbqQsRTqxpOKSAzV0ajEfF4HC+88ALGx8cxPj7OiYwO14d5uSm6Uszi+JS22chjp15oasJRKpWIx+NIJBIIBoMIBoMIhUJYXl4uKh9TDfhuWyaPUasIh63ttri4SA8Ct9sNk8lU0TwRX3vnYl2in3b33XFceOHaa/jnPztx8uRajs3hSGFmprqPhUTC4AtfGMELLwwXTZXldnSR2kY+scxCYBMLO+ph2xaTn6t1DadUkKHK7du3IxaL0ajAbDbD7XZvWAsptL96RDj5UMgsTqlUQi6Xc048pUQ4QpdamfD5fHjppZfg9Xrh8Xjwuc99Dm9961uhVCphtVrR0dHBy+PWKsLhc/1MJoOxsbF1w5fbtm3bcPhyIzR6hEP00x5+OIN3vSuFlRUGzz3noN+vlmwA4MEHX8HllythNr9uw1QZ6ejq7e3F9PQ0RkdHMTw8XHbHE7A+6iF/SMTDZSGdj7kZiUSSV0ZHLBbTqKfUuS0+9lfttWPLBMXjcRw5cgTLy8t4/vnnadTDlVmckFLjCL/5zW/wxS9+ESdOnKADlz//+c9x2WWXQSqV0jcoXyAf6lrL51QD9vDlwsICGIbB6upq2cOXpaARazhs/bSnnlp7y//0p3L89KeVD+2xcVa2Zm0OZ3BwEB5PeXtlC0ouLi5iamoKY2NjsFqtcLvdJQ9Qru0ne5YrlUohEolgdXUVGo2Gs8OYz0FNtowOuwPMZrOhvb0dRqOx4OPz0dTDdYG/paUFOp2O1vGmpqawd+9e6HQ6aiVQSY2YpFdf0ym1eDyOSy+9FIcPH8Yrr7yC888/v+K1Ojo68E//9E94y1vegj/96U+49957ccUVV9Dv18L1sxaEU02UQIZWCcGwhy/7+vpw/PhxbNmyhZc3XiNGOPn007gY9lQq01AqgY4O4Oab03j0UQl8PhGs1srXFIlEMJvNMJvNiEQiVDZGqVSuayUuBtJVOD8/j/n5ecTjcRiNRlgsFtpo0EgzPYX2we4AI3Mvr776KpXRaWtrWzftT9Zr5DZr4GwkQiwhEokEpqencebMGWqbUK5ZHHnur2mlgX/8x39EW1sbDh8+XPVaW7duxdatWwGsV4sGauP6yXfKq5L12c6XZGg13/AlaSPns627EWo4ZFI/k8nggQdC+PjHW3P006p/7tGoBD5fhM7z3HJLqmxHz2JQqVTo7+9HT08PZmZmMDk5iVOnTtGDKLeonkql6MDowsICxGIxzGYz+vr6YDKZsgwKS2kyKIZaEQ4bZO6lp6cHs7OzmJqawsjICOx2e1YUWOp65YAvx082ibGN8Co1i6vGtroW4J1wfv/73+PZZ5/FU089hd///vecrk2kbdhvfolEck5EOKWsT4YviYAoGb4sNLRK1gaaTxx0ow87OUDJYUp+RywW433vy2DzZm7106RSBj/4QSKLXEQi7siGDfYU+/LyMiYnJ7Fnzx6YTCbY7XYkk0mquK1SqWCxWHDBBRfkTcMVazIg14v8XK1QLkHkk9F5+eWXaRRo/UuIyUeNiUtkMpmCowWVmsWVQjjnbEptdnYWt956K/7nf/5nw4HKSpBPLbpWEU49UmrFhi97enpKcr5sVsIB1u85V3GZPD5bRsbrlWBxETh1KvfgXau7aDQZRCIi6PUJhEJiJBKldeW98EIMF1xQ2yE6MkApkUigUCjg9/tpJGMymXDppZeWlX7J11pN7ro3UjKoR4STD/lkdIaHhwEAq6urMBgMnOyRbWrGFUpJ021kFudwOLL29ZqNcBiGwc0334zbbrsN27dvx/j4OOePkeuHA6xd6GQyyflj5T5GrVJqhYYvu7q6YDQay9Z0qwXh8LkuO1XG/p5EIsmS9ycYHGSnnUjd5qw3TSi09rOLiy05P1MIa98/fvw4HA5jWS3MlSKTySAQCNB6TCqVoqkyo9GIQCBAW6uJSnM53U65TQZEtRoAvaZ8z/SQfVQKtp/N/Pw8Dh48mNVqXmkRnr1HvlNqxZCr1pBrFudyuaDX62nqr55RTDGUTTif//znce+99xb9maGhITz77LMIhUK46667Kt7cRqiHHw7fj0FSHHNzc/D5fBUNXxZDs0U4JHpJpVJgGAZLS0t0roooLgOF7+h++MM4PvIROVIpEc4SCTlMGTzwQBQSiSTPzxQCuX5W7NkzDotlhHrAVCNVn4tEIkHrMYuLi5DJZLBYLNi8eTMMBkPW83U4HHA4HFSvbP/+/dDr9VTPq5xDDUBWrafYTA+XLdbsx68WJMq78sorMTMzg7GxsSwZnVJUHXLRSI6f+cziDh48CIVCAYvFUvQ6Np20zZ133rmhfXRXVxeee+457Nu3b13L7fbt23HTTTfhxz/+cbkPvQ619MNhg+u0XTKZpFEM0XdTq9VVDV8WQi3miKpdO1+qrKWlBS6XC0ePHoVWq4Xb7YbVai344YpGo1hYWEBf3zz+5V/S+Mxn3rjuZ37wgwQeeqgFH/5wCl//ehyf+1wpMy9rEc5tt7kBuDE2No6pqSmcOXOGFq/LSWuxEQ6HaRSzsrKC1tZWWCwWdHV1lXSjodPpoNPp0NfXB5/Ph+Hh4ayZnnIIsdBMD4kg+Rgi5YpwyGdTLpfTdNTS0hKmpqawe/duGAwG+v4p9cDnK8Kpds1cs7iJiQlkMhkcPnwY7e3tec3imqqGQwaXNsJ//Md/4Gtf+xr9//T0NK6++mr8/Oc/x6WXXlruw+YFSamxdc1qFeFU27a8urqKhYUFOnypVqthNpuxbds2TE1NobW1FXa7ncNdr98DH6g0wiklVTY4OIienh74fD6MjIzg1KlTNLqQSCRYWVnJkvXX6/WwWCw47zz7X9bLtg145hkxDhyQ4MCBclItax9W0jRA5EtI8frAgQPQ6XTrdLPygUgJEZKJRCIwGo2w2+3YunVrxRJMcrkcnZ2d8Hg8VM/rzJkzdIalUME577PNaTLIZDJYWlpCMBiE0WjkhCy4Jpzc6IuoZxiNRioeOjw8jKGhIRr1bCSj00gRTj4Qszi1Wk1N4l555RXIZDLaPs7lvF3F++RrYbfbnfV/klPu7u6Gy+Xi5DHYrb6kKaFRI5xynC99Ph+vhMBnYb/UQ6NQwb+YORlwVvzR7XZjZmYG4+PjOHXqFP1dtqy/TCbDoUNifPGLMhiNDCQSBvPzIuj1a+Tz3HPk7V/+TE5u0wApXrMJcWTkbLqNRKnpdJqqRM/PzwMAzGYzuru7qRUBV2Drea2urmJqagoHDx5Ea2sr2tvbYbPZSjrwCu3ZarXSmZ5qhEP5IJxCa7W0tKCrqwudnZ1Z4ppms5neJOT73XrXcMpZUyqVYnBwEH19fevM4tra2mCz2Th9zHLQdEoDbJA7wFgsVlPCKeUx8g1fKpXKkpwv+SQEvtcvtnaxKIb8vdEHkKTK2LL+NpsN8XgcS0tLyGQyaGlpoQf3D34gwf79Erz73Uns2rX2taUlcnCUfw3OqgrkBzu6mJ+fx+TkJEZHR2mL8srKClpaWmC1WrFt27aqHFDLQWtrK40QZ2ZmcObMGYyMjFBJldxoil1DWlhYQEtLCywWS9aeyevM7m6r90xPqeuJRGdlZoh+2/HjxyESiaiHD/smkA9y4HOYFMhuHydDs6Ojo7xmTjZCzQino6OD80OOfEjYdZx6ptRKHb4sZf1GVjLYCOy1C5EMiWJyu8ryrVUoVZYr6x+NRjE1NYVnnx1GIqGB3W7Hf/93OwDg6adlOEswJKIpdQiUgd3O4LOfTeGnP91YTYBh1oz9wuEwjeDC4TBSqRS0Wi06Ojo2LO7yBZlMBrfbjfb2dgQCAWoPYLFYYLVakUgkMD8/TwVwLRYLuru7oVarC9YCSmkyKIZ6y9AoFAoqozM/P09ldIiskNForMngJ59rkqFZdgdiPdDUEY5UKoVYLM7qVKt1Si3f8CWRkDEYDBW1YjZ7hJNOp5FMJstKlbGxkQNmoSYKpVKJvr4+XHABe+aLnS6rTGXgkUdiuO46BiIR8JGP5FcTyCclYzKZ4HK5YLFYIJfLkUgkqEz9yMgI3G73ujmKWoHUNWQyGZRKJfx+P+bm5iCRSGA2m/G6120sPJq7XrEmg1rN9JD1KjnIxWIxbDYbbDYblRV69dVXIZPJ1t00cYFGrwvxgaYmHJFItG4WpxZKy6lUCvPz8/D5fBUNX26EZiMcdhQjEokwOzsLlUoFtVpNCaaSVFkxB8xiyN8KnQ+lzdz09q6pCADZagKku5AtJUMiL6PRuO5mQy6Xo6urCx0dHVSaZXR0lErVVNKuWy5I0Z8QYzKZpOoUBoOBCoceOHCA7qucoe3cGiHDMPSumk0+bNQjpbYRiKxQb28v/H4/jh8/jhMnTmBpaQnt7e3Q6/VVPwYfUVMjm68B5wDh5OqpicVipNPcuDcS5A5fMgwDtVpd8fDlRhCLxUilUpyuyUa1hEPu9PKlyvr7+6ngpNFohMfjyTvtXU6qrFzceGMa/f0xvP71G6Uwi3/YJRJAp8tgbk6EyUnA7WYQjUbpYb20tAS1Wg2LxYILL7ywZGsHsVicNTszOTmJffv2ZfkQcXkQkYhxbm4uixgHBwdhNBqzDiin04m2tja6r71791K3ynL2RX4un5JBbtRT75RaMYjFYrS1tWFsbAwulwvhcBgHDx6kMjptbW0Vf/6FCKcJkY9wqr17ZxgGweBZt8ZwOAyNRkOHL6empqBQKKhmE9fges4n3/rlXqNSu8oUCgV0Oh16e3sxNTWFw4cPQ6lUwuPxwGQyYWlpqexUWSXw+8mBV7zIXwzpNBAIiPHud6/VCv/0pz8jHA7DYDDQA7taySadToetW7eit7cXPp8Px48fp62sDoej4sMsHo9TYmRHjKUQI3uqPR6Pw+v14vjx45BIJPSQLee1yk235TYZcH2nz1cxXq1Ww+Px0JmXyclJDA8P00iwHMdWPve5kY6aUMOpArnDn5XWcNjDlySKMZlMtGjIHpojRVK+UIuUWinXaKOCf7FUWUtLC3p6emC323H69GmcOHGC6lGROZNyU2Xl4L3vXSMJtk9N+Vj7HbE4gy9/+TQ6OjpgNpt5qbkoFAp0d3ejs7OTHmbsdFspxBYOhzE3N4f5+XkEg0FotVpYrVb09fVVHDG2tLTQfbF9aYiETiXabcBZ4dBYLIbFxUX6NfJz1YCPFmb2mmTmxeVyZak7tLa2wu12l2UhIUQ4TQRSw6mEcMjwJSGZYDAItVoNk8mE8847r+hdIN+NCfUUB81VXCb7YbcvV9JV1t3dDbFYDL/fj5mZGYjFYqhUqoqHGzdC6XWcjZHJiPHZzzq52dgGICkcdrpt79691G6ZPTmeOzgajUbpbNe2bds4HfRj+9IEg8Gyh1zZIJ1wc3NzCAQCUCgU8Hg8WarV1dyJ13Jmhqg79Pf3Y3p6GmNjY1kDpcU07WpNOOSzXU80NeEA+VNqhQ7rVCpFUzrs4UuHw4EtW7aU/AElnVh8oZZNA5UOYLJRTleZ2+3G8vIyJiYmsHv3bthsNng8nrLTERuhr4/B1q0ZvPJK9ZLyX/5yYuMf4hjstBaZEzly5AjkcjmMRiPS6TS91qR1mevB0ULQarXYvHkztcUeGRmhEjoulyuvhE4sFsPc3Bzm5uZoyzU7+mK/H8nzr3SYlI9i/EYkxlZ1JhYSe/fupZp2+YZs+SKcRjVfA84RwsmNcNhMToYvFxcXsby8TIcvN23aVHFKh++iPt+ddiKRCKlUKqu7L1dGhs+uMnKQRiIRTE5O4qWXXoJOp4PH44HZbObksHjsMQknZAMAb3rTFNJpa90+yBKJBK2trTAYDFhYWIDX66WDi2RGph5gG4aRqf2xsTEqoSORSCjJEKsAq9WKLVu2rIts8zUZEBWDcsmnHrURApHorJdNIpGAz+fDqVOnMDQ0RAlZpVJltY3XY5/1QtMTTq5iNDmoh4eHEQgE6PClxWLBwMBAycOXxVCLoj6X6+dGMVKpFF6vFxKJhM4KcTmAWSpUKhUGBgbQ3d0Nr9eLEydO0MFEh8NR1gF/6JAYd94pw4c/nMLAQAZPPrn21haJGBgMaQQClb3VP/7xRaTTE9i58yRcLhfa29t5SwOyQSIC0g3HFvJUq9X0Lnrfvn2wWCxwu92ctOpWAkJ+ZrMZs7OzGB8fx4EDBwCsSf64XC5YrdaSxUPzNRmUOtMDNI7QJlGd6OjooO3mu3btgtlshtO5lqKtdYQjNA1UiZaWFszNzeH//b//h4svvhhLS0sA1t501QxfFkMzKAEUMyfbvHkzpqenceLECahUKnR0dOTtuKt0ALNcyGQyKgdDFG9Pnz5ND/hSDqrHHpPkCHGSORBsSDbvfGcS//u/65+LVpvBu9+txsUXX0oP+N27d8NqtcLj8ZQlgrkRSE2R1DZWV1eh1+thtVqxadOmdTdKRIySqCu8+uqrUCqVcLvdsNlsNYvG2HM9c3NzSKfTtN6UTCbh8/kwOjqKaDQKl8tV1g1fviaDUpQM+GoaqJQcRCIRzGYzzGYzYrEYHf4FgImJCbjdbs5uYvgwiuMSIqbeVaQKkEgksGfPHvzud7/DQw89hHA4jG3btuFHP/oRLBYLXnrpJVx++eW8qaNOTU1heXkZW7du5WV9v9+P6elpXHjhhWX9XrkyMqlUCj6fD5OTkxCJRHRmhhwg7FSZ2WzmtauMDYZhsLi4iImJCSwvL6OtrQ1ut3tdFDU5KcJfGpzwN38jx8KCBIU70krpVDtr0Mb+2XA4Qv9NJtB9Ph9aW1vh8XjKKpizkU+dwGw2U42vcg6OVCpFTbkSiQRN3/ARjRExTxKBsUVCc716GIah1gDz8/OwWCwFZfNLQTEVA7Le1NQUZmdnsX37ds6e8zPPPIMrrriCM+fiWCyGF154ASaTCYFAAFartexZp3w4cuQI1Go1uru7132PXLeWlpa6pd1qEuH87//+L+6++24cOXIECoUCb3zjG/E///M/Fa937bXX4siRI3jHO96BTZs24U1vehM+//nPZ/1MM6W8Kl2/2oK/VCqF2+2GVqvFxMQERkZGkMlkoFAo4HQ6qx7ArBTsO8JQKISJiQm8+OKLMJlM8Hg80Ov1YBgGg4PsDqDi902/+EUcH/2oHIGACAwjglqdQTwuglIJhMNAJpPfoO2hh7IbBsgEeldXFy2Y51OFLgT2Yb2wsAAARdUJSgUx5XK5XFkaaTabDW63u+poLJlMUmIkYp5WqxUXXHABFSbNByKhQ6Ixr9dLmx8qmTXKVTLIp2LAh3IBwI9t8/bt22mUeuTIEfo6Vmro95pXGnjqqadw66234hvf+Abe9KY3IZVK4dixY1Wt+dOf/pROSL///e9fl346V9uWgeKpMvJ3pV1lmzZtgkgkgtfrxfj4OJLJJNxuNyd1r0qh0WiwZcsW9PT0YHx8HIcOHaLX/7OfdeM73zkP6XQ+Ic61KIUMfh49KsaTT8Zx3XUKLCwAKpUIv/lNDMPDInzvezIcO7b+oN+xI9uCgA3SlUQsjScnJ3HmzBkajbHvhEkbMHHvJIf1+eefX/SwrgQikQgmkwkmkwnhcJhaEhBDv1ItCYC1u3CSKiN1JKvVWlDMcyMolUr09vaiq6sLs7OzdNaIzPSUq90GZAuHks7RRCLBKfGQzzqXBzmpCYlEoiwZHXJdTp06BbvdXraMzmu6aSCVSuGTn/wk7rvvPnzoQx+iX9+0aVNV65rNZvrvXC01oDaEw2cmMnf9UszJuOwqs9vtWFlZwcTEBPbs2QObzYaOjo6KnSyrQa6UDJndCYVCeNObZnDppVq8972d635vYIDBxz6WxD33SDE/L8I998hxzz1rTQQAsLAAvOlNuUS6RlJiMfOXiGdjsAUf2XMzBoMBKpUKq6urWFlZoW3APT09FR3WlUCtVmNgYAA9PT2Ynp7G6dOnMTIyQtNt+VLOxHV0bm4OwWAQOp2uYB2pUhDZfIfDQWd6XnzxRRgMBmqLXc71EYlEiEQimJ2dpfWvzs5OerdfbaGca78eIH8TAlvyiO1fpFAo4Ha7S5LRKYVwztmmgUOHDsHn80EsFuOCCy6A3+/H+eefj/vuuw9btmzh5DFy53CA2kQgfCtSZzKZqhSXq+0q0+l0OO+88xCJRDAxMYEDBw7AYDCgo6Oj4vx7KSCyQoRk2FIy7EMvk8lgfn4ezz67AKCTRjKELO68M4HBQQYMQ1Jca2RCZG7Oyt1k120uvDCNeBxYWChuQZBv38DaXbxSqUQgEKDq4b29vWhvb69f3vwvqdP29nbavjw+Pk7bl0UiEW1fjkQiMJlMcDqdOP/88ytK65QKkUhEByeJtM/Q0BDEYjG1xS6UoiRNFoRkotEoVQaxWCyQSqVZTQbsm7JK5noAbiOcjZoQiH9RX18frc0NDw/D4XDQNHihvb5m53DOnDkDAPjKV76C73znO+jo6MC//uu/4sorr8TIyAiMRmPVj6FQKLCyspL1tWaMcNhRDLFcmJiYgNPphEKhKElxmY+uMpVKhcHBQXR3d9M8s0KhoJ1tXHwI0+k0AoEAJZlS9k0ii6uussFiScNkiuCqq87ghRe6MTTUiltvXSuWk4imVBw6tPZhfe65KDaa7SUdWqR4Tjq0uru76V369PQ0JicnMT4+TmssfB7ixcBuXyb7Iu3LOp0OnZ2d9LCuNYgTZ0dHB01Rnj59Gna7HW63GxqNht5EEXJMJBIwm83o6uqC2Wxet+9C+m3lKhmwh1G5QqmpL4lEUlBGh9TA2ARzTqbUPv/5z+Pee+8t+jNDQ0P0hfriF7+I97znPQCARx55BC6XC0888QQ+8pGPVPLwWcgd/ASap4ZTKFVGogtyIDidTng8nrwdR1zK+heDXC5Hd3c3Ojo66DDb6OgoPB4P2trayr6ryq1ryOVyWK3WsvftcgHDw3HI5RJEIm2YmBjGf/+3GP/5n9uQTotZkUz+iKZQ7Yek29gdasAaqbOdMCUSCSwWCzZv3ryuQwsAJZmFhQVMTk5ibGyM3qUWkz3hGoTUCTkCgNVqRWdnJyKRCH1NY7FYxQVrLsBOUYZCIUxOTmL//v3UkwZYa7Lo6+uDyWTa8H1XSpPBRkTCV0qt3M8mW0aH2KufPHkyS0ZnI2mbeqMiwrnzzjtx8803F/2Zrq4uzMzMAMiu2ZA7mcnJyUoeeh2USmXNCafSlFo5XWWkNXZlZQXj4+PYs2cP7HY71ZziQ9a/FEgkErjdbrhcLszOztKZmfb29qIzMwyzZrnNFpckjpLV1jVIKUKtVmPTpkF85SsJXHbZGdxwQ8+6nyW1ne9/X4KTJ/MdVkSgkcEPfrBWGyTFc0LqKpUKVqu1ZEsCEllYLJasQ9RgMPBiR0BAfJsIOcpkMmptnVuI7uzszGp+qESckytkMpkscpRKpVAqlYhGo2AYBkqlEjqdrqybnHxNBqW6k7IL/FyhmkiE7dq6vLyMqakp7N27Fzqdbl09u9FQEeGQD89GuOiii9DS0oLh4WG8/vWvB7DWXjk+Pg6Px1PJQ69DoQinlkX9YqhGcRlYu6shg5qTk5OYnp6mraZ8yPqXClLgtNvtCAQCGB8fx/j4OI3GlEolMplMlrhkLBbjTVySYG02pwWrq66c76xFLv/8zxG8611iXHhhGq9/vRKF7At+//slOBwz2L9/DqFQCDqdjqpVVDOLodFosHnzZvT09FDZ/0rVFfKB2BIQYUy1Wk0jmdbW1qLty2SWhpAiEeckdRE+i825sz1SqXQdOTIMkyWhQyygy+30y1Uy2MidtJ5SOcXAltEZGBiAz+fDyMgIjhw5Qm8Ac9+r57TSgFarxW233YZ//ud/Rnt7OzweD+677z4AwHXXXcfJY+SqRQP8mLDlrl8owilmTlZoADMf8qXKrFYrtFotlpeX4fP5wDAM5HI5r0X8jcBuww0Ggzhz5gx2794NhUJBtbAsFgt6e3tLSoFUi8FBdifV+kHO972vFS+/fBAaTSdsthYYDMxfIp3sNupjx45BpZJmWURzCSL739HRkWVHQNQVyiHjaDRK6xorKyvUlqBSciSkSAr5J0+exPDwcMmzRqWCRGBkJqmlpQU2m61g5MiOFMkA7iuvvELN0Eq1BWCvV0jJgP0ZbQYbASKjMzY2hu7ubgQCAezatYs2UrA7e+sJ3quD9913H6RSKf7v//2/iEajuPTSS/Hcc8/ldYGsBIW61GrpJ8OF4nI5XWV2ux1dXV3U4EylUtGCbz2IJzflpFQqIZVKEY/HodfrYbfbYTQaa7K3/LYEZ9Nk99+/8heFhd14/HEL0mkTbrihA0ZjBG95iw8vvODBwoICb3/7hXC7+S++SiQS6rKZb2AzXzcS6dAiJBMOh2E0GmG323HeeedxFjmSQ8zj8WQV8olHTyU1KLY1weLiIo3Aurq6ikZguSCzK93d3ZSwT506RfdWbgt3Pv02kkojdR8uwYf8DlnXYDDA4/FQGZ0TJ04AWHNz5VJGpxI0pbQNGz/+8Y/x4IMP4tlnn6VfO3LkCIxGI1yu3LQKNwiHw3j55Zdx+eWXr4ti2MOXlXaVWSyWklNlRJ5mYmICUqkUHR0dsNvtvHaqsA+8+fl5rK6u0pSTxWKh5JhIJDA1NUUdUj0eT1mDh5XilVdEee2ld++OYsuWtQPP7/dToz2RSIGOjjZ0dnZALJYgkThbF6oHwuEwTZ9qtVqqoh0MBinJEBkcq9XKmylcPgSDQUxOTmJ2drbkuZl4PE73vbS0RGeSrFYrZzXHXAkdtnlipRI6mUwGi4uLmJmZQTAYxBVXXMFZSmp6ehpTU1O49NJLq16LjWeffRaXXXZZ1s1AJpOhTSsDAwMwmUycPmY5aHrxTqVSWZPBz1xzsnQ6Da/XC4fDAZlMti4MLwSuu8qkUimdeJ+ZmcHY2BhOnz4Nj8cDp9PJWQqLLdI4Pz+PZDKZFa7nSzmxO9vI4CHpbONyb4VAZnJImmxoaAiLi146Md/b2wuFQkHrY37/DB2wq+dHQ61WY3BwEF1dXTh16hSOHj1KUzDEQ6YW6cl80Gq12LJlC3p7e+ndM2kkYQ8m5qb5dDodbDYbpwOkbLAldMid/bFjx6hUTClDk8DZhgUy3yORSGj3JNsuoViTQSngI01Hzqbcdcn7xmw2171luukJRy6X8zb4WShVplQqsXnzZkxOTsLr9cLj8cDlcuU9APiQ9c8HsVhMUzNzc3MYGxvDmTNnaDdLJXfAyWQyqwVYKpXCYrFgcHCQSguVAolEQvP/c3NzGB8fx5kzZzbsbKsUFgsDiyUNqzWOt751Er/9rQ2BgBo9PVps3Xr5ugOPEPbc3Nw6pepapx9I1EvqGmQqXyaT0Ui4paUFGo2mrpJDbOtpthyLRqNBKpVCJBKh5oZcpvlKgUKhQE9PD5XQybXFzk0Fkpbx2dnZrIaFXJ24Su0S8oEvwgGKD6jWs2EAOAdSan/4wx9w++2349ChQ/RiDg0N0fbrclGO4jLpmhkbG0M4HIbb7Ybb7YZIJKo6VVYtGIZBIBDA2NgYgsEgXC5XSfnbSCRCo5jl5WXqw2KxWKDRaDh5w5L0x/j4OJaWltDW1gaPx1NV9xdRXiZpvkgkDbvdCKvVApPJDIaRlZQmYxgGy8vLGB8fRyAQoI6kfLYH51oukwYRi8WSVTwnNy8TExNUeZnYJNTjIMmd9o9EIpDL5YjH4zAajejo6KhZ7W4jkKHJ2dlZ6PV6OJ1OqrAwPz8PmUxG539KaXVnmzzmzvWUAvLev+CCC6p+bgSpVAp/+tOf8OY3vznvGUNUCOo1YwWcA4SzY8cO3HTTTThx4gR9sUdGRiAWi9HTs34OIxeFohh20X+jVBnDMPD7/Thz5gwikbVBQXJo1FLWvxDIAbq4uAiHwwGPx0MjK3KIEZIhd6ZkIp3vu+hQKITx8XHMzs6W7TNDogGyd7FYTMnRaDTi8GEZvvhFGb7+9SQuvLD8iDccDmNiYgIzMzO0EMvVAUo04nItl0uta0SjUVrnUalU8Hg8nCk/FEOhaX/yXpdKpTSl5fV6qSp0JcPBXCOdTtMGg9XVVTpk3dXVVVWth91WXWrUc+bMGQSDQZx//vlVPKNsJBIJPPfcc3jrW9+a91oLhMMB9u/fj2uvvRajo6P0BT516hQ1YMuHYl1l7KJ/MRRKlbW2tlLBRqfTiY6Ojrp2hbCxurqK8fFx+P1+6HQ6yGQyrKys0AjMarXCZDLVRdqEHKA+nw9arRYdHR15ByLJnAmpgSkUChoN5N7p/8M/yPDAAzJ89KNJfPvbyYr3xm5+aGlpgcfjKbsxg2EYhMPhdZbLFosFVqu14vdIKpWiNahMJgO3281p6zLZO5HwISZrZN/FaknpdJqm26LRKJ2Ir2UqkAxJz87OYmFhAQqFAjabDRaLhRLj8vIyVWYupFG2Ecg5wtZdK0Y8p0+fRjgcxnnnnVf5k8sB8di5+uqrCw6wCoRTJQ4fPow3vOEN1OcdWHsxk8kkBgYG6M+Va06WD+V0lQWDQYyNjWFhYQEOhwMdHR2cmTdVgng8TslxcXGRtntqtVr09PQ0TOojmUxiamoKk5OTaGlpoSrVZO9kzoQceMVM2f6//0+B+XkRLBYGv/zlWp3PZALc7sre8ul0GjMzM5iYmEAqlaKKC8UEJtmdZbFYDCaTiUYDXH7wGYbB/Pw8JiYmEAwGC5rWlQr2tP/c3BydgbHZbHklfDbaG3FMnZ+fp46gfM2Pkfme2dlZLC4uQqlU0nRZPkULosw8MzNDNcqq6aZkRz2FlAxOnTqFeDzOmYgxsJYO37VrF66++uq830+n05BKpQLhVIOTJ09i27ZtmJ+fpy/m2NgYIpEIBgYGCqbKSoligMJdZaWmykhUMTs7S2X+a6GhRe6oSTQQDAbpQU1al5PJJCYnJzE1NQW1Wo2Ojo66zfLk7n15eRljY2O0dVmtVsPlcsFmsxUtQKvVZ0mddKflqgnk6qNVsr+FhYV1h7tKpcor6Emuudlsrklaid26bDQaqZPrRq9roWl/q9ValidLMRATNq/XS2X3yx3YzAdiEEdIRq1Ww2azwWq1lvx5SyaTVJk5lUrB6XRW5ZrKrvMA2VmUkZERpNPpqq1a2AiFQnjxxRfx1re+Ne/30+k0ZDJZXS2om55wxsfH0dnZiaWlJTq4NTExgcXFRWzatAlyuZyTVBk5MCq9Y4xEIhgfH8fMzAxVQq40fC+EfJbFJpOJ7r3QQZ1KpeD1ejExMQGZTIbOzs6azMvk7p0oRs/NzWVFj5lMBlNTU4hEIrSzrdBzefxxCWvwMxtEH+3GG7lToSBF/NnZWSgUCiSTSdpKm89yuZZg11IKpQILTfsTVQu+bj5ItDg1NYV4PE7TbeUc7slkEnNzc5idnUUgEEBrayvdezXdn6ThZnJyEouLi9T+uVLSJUcs+8Z3eHgYYrEYg4ODFe8zFysrK3j55Zfx5je/Oe/3BcLhALOzs7Db7ZicnKQpq3g8jlOnTiEUCsHlcqGjo6NoGMnFAGapILYDXq+X6qHp9fqK18tXOGfvvZw7R3IIjI+Pg2EYdHR08FrszW27lslkNBrIPahJHWFiYgKBQGBd8wMbxQY/Czl4VrJ3tjCmXC6HTCZDOByGRqNpmGgROPu6Tk5OIplMwuFwQKFQYHFxMWvan0QDtdwzeV0nJyexsLCwoT5aIpGgab5AIACNRkNJho+UdSQSgdfrhc/ng0KhyGsJUCri8ThmZ2cxOzuLlZUVDA4Ooq2tjROTOABYWlrCq6++iquuuirv9zOZDGQyWV1qtARNTzjj4+PUtvbzn/883vOe99ALury8jDNnzmB5eZlquRHiqTZVVi0SiQQmJiYwNTUFrVaLzs7Okuso+dSLyUHNRYtsJpOhszzxeJzOGXFBvLm2xeSwK6ftOhQK0ajCbDajo6Mjq7ONEA4Z/CR/V0s4hSyXyR21SCRCMpmEz+fD5OQkxGJxxfYNXINM+3u9XqyurgJY00zr6uqCtRynOR5B9NGmp6ehVCppuo1EMuS6a7VaSjK1akBgd7jFYjEqobMRyZHrPjs7i+XlZToAa7VaIZfLs2ZnqiWexcVFHD9+HFdccUXe7wuEwxFisRgefvhh/Mu//AtaW1vxj//4j3mJh9wRpdNpRCIRTlJl1YJdRyGaaLlSIQzDIBQKUZJZXV2le7dYLLw1IzAMg8XFRYyNjWF1dZXO8pQzxMfuzpqfn0coFKJ7r/bAINGiz+ejUcWauZgYb3hDC5xOBjffnMajj0rg84mwa1ccTmd5b3f23tmWyxvtPZPJUPuGWCxWkShntcg37U/2nk6nMTk5iZmZGej1eqoY0QgRWSqVwuTkJCYnJ5FKpcAwDLRaLRwOR1UdfVyA1BenpqYwNzcHk8mE9vb2rI5KEoXNzs5iaWkpi2Ty7b2UJoNSMD8/n6XMnwuBcDhGLBbDD3/4Q9x7771QqVT4xCc+AZFIhJdeegnXXXcd7dJIJBJwOp3o6uqq6QFQDOw6Csm3y2QySjKpVIqmymqpnUXALuJvNKhJPpTkoCa1JD66s4A10vZ6vZicnIRMJvuLDbYdCoUYIhHAMChZH42Qe67lMonCyt17biqQeBrx1ThCCHJ2dpa2XpM24Hzv9UQiAa/Xi6mpKWpFXa+ILBaL0SHSlZUV6PV6qNVqhMNhLC8vU0HTUue0+EYsFoPP54PX64VYLIZWq0UikaCdlHa7vSyCzG0yKNeddHZ2FqdPn8Zll12W9/vpdBpyuVwgHC4xOTmJX/7yl3jooYcwNDQEm82Giy66CP/+7/9OC+FERn9xcbGhZmXIndHU1BQdTGObdNVbBwk4O6g5NzcHq9VK25ZJhxMhSOCsb1KtdL/YbcvpdJq2LW/0ActVKUgmk+uGGbnA6uoqjSq4GiTNnfaPRqMwGo2UZEq9MclkMjRlFI1GaybtE41G6d6DwSAMBgONwtgEGQ6HabqNi9ZlLsCOZAKBACQSCTKZDPUfqlSdIl+TQSnpNvLe/z//5//k/b5AODzg2muvRTgcxjXXXIOrr74au3fvxre+9S1IpVJ89rOfxQ033EA/hKFQCGfOnMHCwgLa2trQ2dlZc+IpJCVjNpvp4Q6AFvAbgXSAtX2fOXMGfr8fMpkMqVQKLS0tNBLgqo22EpCZlPHxcYTD4bypwFzLZTJnYrVay9KJqwTxeBxTU1O0NbhcFe1Spv0rRW4Rn4+ogji/zs7OIhQKwWg0UpLZKIJMJpNUaTmTycDlcsHlctVstoTIEBGSya0nBYNBTE1N0eHq9vZ2WCwWTmZ6NlIy8Pl88Pl8uOSSS/KulclkIJfL61pPPOcIJ58oXiKRwI9//GN885vfhEgkwmc/+1m8733vyyKesbExzM/Po62tDR0dHbwVI4tJyVgslnWER2oBY2NjSKVSRYVCa4F8BCmRSBAKhdDa2pq3BlUv5NNFa21tRTAYzLJc5nLOpByk02mqEkAiskIqAZVO+1eDSCRC5XM0Gg3cbjesVmtF1yk31VdNmhI4Ows1OTlJlQLcbjcvmne57dekM85msxU8JxKJBCVGhmGqJsZSiGdychJzc3PYvn173jUEwqkxEokEfvKTn+Cb3/wmGIahxEPeBKurqxgbG8Pc3BwcDgc6Ozs5IR52umlhYQEMw2S1LpdyR0ru2s+cOYNYLEYVjvkOj9k1DTKXlI8g2XUUuVyOjo6Ouqc8gLNSODMzM1heXgYA2pzhcDgahhiJSkAoFKJGWS0tLZxN+1cD0nk3NTUFAJQYN3rvEc+k2dlZhMNhmEymslN9pYCdqtRqtdQSu5rrQ9reiW9SKSSTD+S1nZqaonWo9vb2qiLGQk0GpE544YUX5v2dTCaDlpYWgXBqjWQyif/6r//CN7/5TaRSKfzDP/wDbrrpJko84XAYY2NjdMans7Oz7E6wXM0vdrpJp9NVFWKzO8fa29vhdrs5TSnk875ha60VOyzIXfv4+DhEIlFd2oJJyoYthUMiGbFYTG0l2J1tjUA8ABAIBDA6OoqVlRWIRKIsFeN6pimBtfcFIcbV1VVKjOQAJvUkQjLRaJS+bywWC+83R7nESKKKUsktV62ADJLabDZOOkHZdSi1Wk3rUJV+NtjEA4DejG7btm3d+0QgnAZAMpnET3/6U3zjG99AIpGgxENy/Wzisdls6OzsLNg+XYqUDJeHBUmxjI2NYWVlBS6XCx6Pp+Kuu1wfFmLaRJSXyyVIkgocHx9HIpGgqUA+Dh32Qce2XCb7z3dNyOFE1BU8Hg8cDkddIrJ80/4mk4kegMT1s1EGSYFshQWDwQCFQoGVlRXEYjGYzWbYbDZOGy7KASHGqakprKyswOFwwO125+0M5Jtk8iGVSlGVBdIx63K5ys6mkOyD3+/H7OwsUqkU+vv76fuYnW4TCKeBkEql8Nhjj+HrX/86YrEY7rzzTvzf//t/6UEViUQwNjYGv99P/dfVanVRKZlKc9OVYGVlhc4ZOZ1OeDyekt68JAojU9tkgJRLWZNczyCuIrLc1utEIpHVel1Od1auICfXasv5wPbAKTbtzx4kZTtr1vPQYIuS+v1+xONxAKAeVPUi7nwIhUJ/cXP1Q6/Xo729HQaDIUtBmitJnHJBJHSmpqawsLAAi8VC91fss7e6ugq/3w+/349EIgGr1QqbzUZngQrN9DAMg5aWlrq+NgLhsJBKpfD444/j61//OsLhMD7zmc/gAx/4AK1TRKNRnD59Gn6/Hy0tLVQ3i+3BUs+DgN38YLfb0dHRse4DlG+QkR2F8QW2IOfS0lJZxEjAVjCen58HwzCctV4TYhwfH6eSSKUY1pUDMnVOJubL8cAhbcsTExOIx+O8uaUWAiEZIs2STCZpPclkMoFhGErcmUyGOrzWU5mYjUgkgtHRUczPz9PiudPphMPhqNvQNxtE1NTn81EPIYfDQSPEcDhMI5loNAqLxQK73V7wfZ/bZJBMJrF37168/e1vFyKcRkM6ncbPf/5zfO1rX0MwGMQtt9yCVCqFoaEhfPCDH4RSqYREIsHq6iosFgu6urp4dYQsF+xUIDmQScopFovRdFMxQU8+wSbGjRS0c1N9xOaadJbxcbfGNqyrdlCz2LR/JQ0p5K54YmICS0tLRTXlqgXpqCRzMqlUKotk8l17tpI2SWfxtb+NkOuFo1KpYLVaIZVKabcckahpBNIBsj2EIpEIWltbkUqlEI1GYTKZYLfbS05VplIp7N27F0888QR+9atfoaWlBS+++CLa29tr8EzyQyCcAjh06BCefvpp/Pd//zcmJyfR1dWF7du349vf/jaMRiOAtUnj8fFx+Hw+mM3mhiEeMmMyMzND7+iI8CBfdZRKwFbQNplM6OjogF6vL9lymW+wHT+JZXIphft80/75hhmrxerqKiYmJuD3+8uyISgGEokSkslkMpRkyq3lsdNZXDumFkIuybC9cHJvGti20+wB63rWyYjagt/vRygUgkwmQzKZhF6vh8fj2bDBJZPJ4KWXXsKTTz6JX/7yl0gmk3jPe96DG2+8EW94wxvqruknEE4BXHvttVCr1XjXu96Ft73tbfjzn/+Mr33ta1hcXMSnPvUp3HLLLbSoyCYek8mErq4uzq0HNgJRXiY1ATJjYrFYoFQqaWeWwWBAZ2cnDAZDTfdXDLFYDGfOnMH09DQkEglSqVRWZ1m97z7j8Ti9fvl8g7ia9q9mf8SRVKlUlj1ISmqRZP8Mw9C6ABft1/F4nMrntLS0cOaBQ5BOp2nhfyOSKbY/r9cLqVRKLbFrdWOWSCQoyaysrFA5IjIIG4/HsyR0XC4X2traaLoyk8ng2LFjeOKJJ/D0009jaWkJf/3Xf40bbrgBb33rW+tqR5ALgXDKQDqdxtNPP42vfe1rmJubwyc/+Un8/d//fZYtwvj4OLUe6Orq4lX3KRqN0oYFol5M0k35ZOYTiQQVCtVoNGUpVHMNtqgnsVzW6XSQSqVYXl6GUqmkszyN0plF9O6IErTNZqMdUVxO+1cK0pI+MTEBhmGKRrSk9Z2QjEgkoiTDV6qSKC5PTEwgkUhUJWiaTqdpJDM/P182yeQD6awk6axSFaErARkm9fv9VOCTaK8Vuh7kvTY5OYlPfvKTtPtux44dmJqawjXXXIMbbrgBf/VXf1VTG+9yIBBOBchkMvjlL3+Je+65B36/nxIPuROPx+PUesBgMKC7u5sT4mG3/xLVaIPBQOs0pb7J2DbOSqUSnZ2dNWm5ZXc3FbNcTqfTtGWZLfFf784n0opO7kZTqRRtH+/t7W0IPT5gbZ9zc3N0XoZ9sAcCAXpIk73XesaHbXBGFCA8Hs+G6ehcklEoFFkkw9X+Se2KTO6bTCa43e6qb85I+7vf78fi4iI0Gg3sdjtsNltJ7x1iLvnUU0/hd7/7HVZWVjAyMoLu7m7cdddduOmmmxoqmskHgXCqQCaTwa9+9Svcc8898Pl8lHjIHRbb80av16Orq6tsszV26/Xc3BySyWRW63U1bzC2QrVcLqdOn1wePNVYLpPOrPHxcdqyXOsaFLszjj3tT9w8A4EA7WwjnXeNQjxA/kFScshx4Z1ULcLhMJXP0el0VCWA7IuodPj9/ixHUq5JphDYrqlyuRxut7ssA7bcdJ9KpaLXv5TIiWEY+P1+PP3003jqqadw8OBBXHXVVbjhhhvw7ne/GwzD4Mc//jG+973v4fvf/z7e9ra3VfuUeYVAOBwgk8ngN7/5De6++24a7n74wx/OIh7i76HT6dDV1VW0hsL2ll9YWKCHHF+t12x1ALFYjM7OznVWxOWuR/bPvpOu1HKZyIOMjY1Rm2mu1RWK7Z9YRheLBJaXlzExMUEFL4t13vENsn9yyEmlUhiNRnqHXWoBupZIJBJUJUAkEtH9Li4uQi6X00O61o6kBLkGbMQSO19WIZPJYGFhgZIkicTsdntJ9UiiJvKrX/0KTz75JPbu3YvXve51uP766/He9743701hJpMBgLpnATaCQDgcIpPJ4Le//S3uuecejI2N4ROf+AQ+8pGP0FRBMpmkEQ9xWyQdb7mdWQqFgt5J1+pOlAxBjo+PI5PJlGUxTSa2SdOCQqHIkvLhaoiUqCssLy9TdQUuIorc7iZyJ13uEGxuZxsXnWOlgJ1uIpbX+faf6x1U7h07n/snJEkaFwDAbreju7u7YWoSpItvcnIS8/PzsFgscLvd0Gq1WFpagt/vx/z8PJUkstvtJZNkMBjEb37zGzz11FN47rnncP755+P666/H9ddfj/b29oa5OagGAuHwgEwmg9/97ne45557MDo6io9//OO47bbbaOcacfkksioSiQSRSIRXKZxywDAMVahOJBLo6OjIq1BdiuUyXwgGgxgbG8PCwkLBIdeNUOq0fyVgd46pVCp0dHRUrLRcCIQkSSRWTk2DPUjKLuDXclAzk8lkkQwhSbJ/UkeZn5+H1WqF2+0uOyXNJ8gwKSFIqVQKh8MBh8NR8k1KJBLB73//ezz55JN49tln0dPTg+uvvx433ngjenp6zgmSYUMgHB6RyWTwzDPP4J577sHw8DBuv/12nH/++fjDH/6AK664AlqtFgqFAvF4HK2trejp6alb11g+sFNZ0WiUzimQmkYoFKL2ueU0LXCJcDiM8fFx+P1+mM1mdHR0FG3QqGbavxKkUikqTSMSidDR0VFVRJGru0a6syolSZK+mZiYwPLyMu+DmmySmZ+fh1QqpSRT6JCORqOYnJyEz+dDa2srtUmoR/qIPac0OzsLALBarZBIJFToloiGFoq84/E4/vSnP+HJJ5/E7373O9jtdkoyW7ZsaZjPPx8QCIdnJBIJ/PnPf8b3vvc9/PGPf4RYLMa2bdvwhS98AVdeeSWkUilSqRSmpqYwMTEBlUqFrq6uug+gEZDOMtKxk8lkoFQqqfRGo0iXxGIxTExMwOfzQafToaOjg5I319P+lSBXzJRI05TS9JGbrlSpVFkkwxVCoRAV5DSZTPB4PJx0r1VCMvnAJm8AVD6H784s8hkg0jLE1dNut2elS9ndd4uLi7BYLAiFQrjsssuQyWSwc+dOPPnkk/jVr34FjUaD6667DjfeeCMuuuiihq+9cAWBcHjGv/7rv+Lf/u3f8Nd//dd417vehVQqhW9961s4duwYPvaxj+FjH/sYbSAgXWPj4+NQKpXo6uqqS2G3mOWyVCqlplfEnrse8jiFkEgkaMu3RCKBWCxGLBbjbdq/XJCIYnx8HMFgcJ3EPwGZ0yAkU0uByVgsRh1JVSoVPB5P2REF6e4j6TKpVEoP6WrVIkjb9+TkJEKhENra2uB2uzmdlyEjCIRkiHac3W4vSXEhEolg//79uP7662G1WqlFyXvf+17ceOONuPzyy+teN6sHGopwXnjhBVx11VV5v3fgwAFcfPHFeb935ZVXYseOHVlf+8hHPoIHH3yQ8z2Wi3g8DrlcnvUBYxgGzz33HL761a/iyJEj+OhHP4o77riDEk86naYRD1Hg5XtOplzL5ZWVFYyNjWFxcZF3l9RSkG/aX6lUIh6PQyaTUcO1RrqTJBL/c3NzsNvtaGtro14+xPSLdMfxJZVfDKlUijqSMgyzofFaLslIJBIayfDV+ELqPLOzszCbzXC73VU1aZQrkpmLTCaDV199FU888QR++ctfIpFIYNOmTTh16hSSySRuu+023HXXXQ11k1ZLNBThJBIJBAKBrK996Utfwp///GecPn264JvoyiuvRF9fH+6++276NZVKVXN5mXLBMAyef/55fPWrX8Wrr76K2267DXfccQdMJhOANRIgEY9cLkdXVxenhedcORy5XJ4ljFnK45SiUM0X2ArGc3Nzeaf92Z136XS67hbduSCyKj6fD/F4HFKplAqG1oNk8oFtvBYOh2lUplAo1ikWEAWGWs/5kKjM5/NBoVBQ+ZxSbjAikQgd5o1EItTPx2KxlPQ+YRgGQ0NDeOKJJ/DUU09hdnYW1157LW644QZcffXV9Dr94Q9/wK9//Wt8//vfb4h0eT3QUISTi2QyCafTiY9//OP40pe+VPDnrrzySpx//vm4//77a7c5DsEwDHbs2IGvfvWrOHjwID7ykY/gE5/4RBbx+Hw+jI+PQyaTVUU8uR44XHVmsYv3FosFnZ2dvAiZktZokm4ig6TEjbTQAUHSMGNjY4jFYnSWpx6T2aRxYXZ2FsvLy7TxQq/XU+MwhUJBO9saJSojE/jj4+N0viSZTFKSsdvtdR8mJTNlk5OTSKVSVN4nt9aYK5JJ7K9J2ngjMAyDM2fO4KmnnsJTTz2F0dFR/NVf/RVuuOEGXHPNNXXX/2tUNDThPPXUU7j++usxMTEBl8tV8OeuvPJKHD9+HAzDwG6349prr8WXvvSlhrlDLBUMw2Dnzp24++678dJLL+HDH/4wPvGJT8BsNgM4+2EaGxuDVCpFV1dXScoAxSyXub5G0WgU4+PjmJ6ehslkQmdnZ9WyPrnT/gDo/stVMCaF3fHxcaysrNRMHSAWi1GSWVlZgV6vp88h97HZ0j71sunORW4kAwByuRyRSAR6vR4dHR0N0+gCnLVJIPVGh8MBu91OU2ZEJJPol5Vy48EwDHw+HyWZI0eO4M1vfjNuvPFG/M3f/A2vuonnChqacN7xjncAAH73u98V/bmHHnqIfiiPHDmCz33uc7jkkkvw9NNP12KbnINhGOzatQt333039u/fj1tvvRWf/OQnYbFYAKx9+AnxSCQSKklDDt5KLJe5BtGT83q90Ov1ZStUF5r2J2oFXBxs7Lt1PtqBSXfc7OwsgsFg2Y0LpLNtYmKCRmW1Nl0jJDM7OwuRSETTZSTlmkgkqBJ0va2684GofPh8PiQSCZqy7OzsLFm/bH5+Hv/zP/+DJ598Evv378frX/963HDDDXjve9/bUCTbDKgJ4Xz+85/HvffeW/RnhoaGMDAwQP/v9Xrh8Xjwi1/8Au95z3vKerznnnsOb37zmzE6Ooru7u6K9twIYBgGe/bswd133429e/fi7//+7/GpT30KVqsVQDbxkMOArV5cieUy12ArVLe2tqKzs7Pgh5Sraf9ysbq6ivHxcWpY19HRUXH9j0STs7OzCIVClOiJ1HwlYEdlpDuwXLfUch4rN5JhWxUUeg3YStDJZLJgKqsWIG3kfr8fgUAAWq2W+vnMzc3B6/UWVVkgsza/+c1v8OSTT2LHjh3Yvn07brjhBlx33XVoa2sTSKZC1IRw5ufnsbi4WPRnurq6st6c99xzD7773e/C5/OVfViGw2G0trbimWeewdVXX13RnhsJDMNg3759uPvuu7F7927ccsst+PSnPw2dToc///nP6Ojo+P/bO/O4pq70/38AJVRWkSWyJQEUF8QFBbWK+hWL4m4VsKMwjmP7YtRvEW2FjtW2WqFK3Ub71ZmO0JmKC+BWtXSQVlsVF9xRcUtCQAiLLEIgEJLz+6O/e4clYIIQApz368Ufuffc5BxN7ueec57n86CwsBBKpRJGRkZwcHCAm5ubXjnHMpYqOTk5MDExYSPvmuaYtGe2v7bU1NSwuTx9+/YFn8/XaDbVtOBaw1o47X3DffXqFcRiMYqKiliX5TcNjmmazEgIYWcy2s4mmyaSOjg46CQAgjHJZJyYTU1N2X2lpsLctFx3dnY2AgICYGtri3PnziE5ORlpaWkYMmQIgoKCEBwcDIFAQEWmHdDLJTVCCNzc3LBgwQLExcVpff3ly5cxYcIE3L17F15eXh3Qw86BCadet24dsrOzYWhoCFNTUyQlJcHNzQ0WFhbsxjghhPVC05flDeD3G4NYLEZOTg77Wp+KrQGNZ2XqCq4Bv4sMc4OWyWTsprMuCq4BjcWR2UPRxqVCnci0Z9E1oHEiqY2NDXg8XrsGFTR0km5YE0cbk0ypVIqlS5fixo0bbEJqWFgYQkJCMGjQICoy7YxeCk56ejr8/f2bLbMBwIsXLzB16lT861//go+PD54/f47ExEQEBgaiX79+uHfvHtasWQMnJ6dmuTldnbVr12Lfvn1wdXWFj48PiouL8fPPP+NPf/oTIiMj0b9/fwD/XfsXCoVQqVQQCASdLjxNs/0tLCzA4XBQUVEBIyMj1vJFn8SxYfkGxidLpVKxeT4NRaazynYzia5MZFtr1T6ZKDOpVMq6RrS3yKhDLpez+yimpqZsImlbbubq/Ne0dZJWKBT45ZdfkJycjDNnzqBv374ICAhAWVkZzpw5A29vb3z77bcYOHBgW4ZLaQW9FJz33nsPOTk5uHz5crNzYrEYAoEAv/zyCyZPnozc3FwsWbIEWVlZkMlkcHZ2xvz583H06FHWAoMhJiYGUVFRLX6uXC7H2rVrceTIEdTW1iIgIADffPMN7O3t232MbeHy5cuwsbGBh4cHgN9vIJmZmdi8eTPOnz+PsLAwREZGwtHRkT3PCI9SqdTK/bk9aLrUpG7TnFneEIlEWjtUdzQNs83z8/NRV1fHhgAPGDBAr5L3mlb75PF4cHR0hKGhISoqKtiZjK5ERh1NfeVcXFw0KuXcMEKusLCQnYlwuVyYm5trJDJKpRKXL19GcnIyTp48CWNjYzbrf+zYsey/Q1lZGb799lusWLFCr4xCuwt6KTjtAZ/Px/Lly7FixQr2mLm5eatT7fDwcJw9exYJCQmwtLTEqlWrYGhoqFb49AlCCG7evInNmzcjLS0NoaGhiIyMZEPJmRwUoVAIhUIBPp8PR0fHdr+pq8v2b7if0dpSU1OHaiZBU9czB0IIKisr2Zsbk0xqb2+Pfv36oaSkBGKxGHK5HC4uLhr7oemKhrNbuVwOAwODRuWjtQ0j76g+MhVJq6urWafqhlFjzJIfMxsDoHWuj0qlQmZmJpKTk3HixAnU1tZiwYIFCAkJwaRJk/Tioaan0a0FJyIiAhERERq1r6iogK2tLRITE7Fw4UIAQHZ2NgYPHoyMjAyMHTu2A3vbPhBCcPv2bWzevBmpqalYunQp1q5dC2dnZ/Y8IzytlR3Q9jNfl+2v7fuVlJRAKBSyDtUdfVNXNwZbW1tWZNRFMTX0Q2Pq8nS2RxtjMFlUVIT6+npYWlqirq4OVVVVbGSbPuWmMaKSk5ODly9fssm7jOC3ZJLZGiqVCg8ePGCz/ktLSzF37lwEBwdj2rRpemM221Pp1oIjl8uhUCjg4uKC9957D2vWrGnxBsiEUpeVlTWaSvN4PERERGDNmjU66vmbQwjBnTt3sGXLFpw7dw5/+MMfsG7dOri4uLDni4uLIRQKUVtbCx6PB2dnZ42Fp63Z/tqOobS0FCKRCJWVlexNvb1uGMx+BiMy9fX1rMhoU1W1vLwcIpEIpaWl6N+/P/h8vs5u6g2FsrCwsNEY+vXrx85kKisr2bBvOzs7dvNeH2Bmxbm5uZBKpVAqlWwpZxcXF42tZZ4+fYrk5GSkpKRAIpFg5syZCA4OxowZM/RKZHs63VZwduzYgVGjRsHa2hpXrlxBdHQ0li1bhh07dqhtn5iYiGXLlqG2trbRcR8fH0yZMuW1eUT6CCEE9+7dw5YtW3DmzBksXrwY69atA5/PZ883nE0wMx51otye2f7awlT5LCsre6Mqnw0js5hN84Yi8yZjaJrL05HWPpqIjDoa1pWxtLQEj8frtMRFZulVKpWitraWHYOFhQVbaprD4YDH46n1RCOEQCKR4Pjx40hKSsKjR4/wzjvvIDg4GHPnzu2Qf/uuwpdffomzZ8/izp07MDY2Rnl5ebM2EokE4eHh+OWXX2BmZoawsDDExMS0uiJRWlqK1atX44cffoChoSHeffdd7N69W6sSGV1KcNqSQMpw8OBBfPDBB6iqqlK79NEdBYeBEIKsrCxs2bIFp06daiQ8BgYG7BKRUChEdXU1O+MxMDDo8Gx/bWhY5bN///4QCASvTX5kSi00LF3ckZvmDcOVra2t2VyeN0HdvhIzhteJjDoYdwCJRAIOhwM+n99iZFt7os4kk8vlwsbGptlMRqlUoqCggE0kvXHjBkJDQ0EIwfHjx5GSkoLMzExMnjwZISEhmD9/fqd8J/WRTZs2wcrKCnl5efjnP//ZTHCUSiVGjBgBLpeL7du3o6CgAKGhoVixYgW2bt3a4vvOmDEDBQUFOHDgABQKBZYtW4YxY8YgMTFR4751KcFpSwIpw4MHD+Dp6Yns7Gw2yqsh3WlJrSUIIXj48CG2bNmCEydOICQkBOvWrWOT2piltidPnkAulwMAOBwO6zfVkdn+2lBVVQWRSMQmPwoEgkbBIE19vxpumltZWelk07xhiWkzMzPw+XytahupE5nW9pXaQtPItteVH2gLNTU17BgYk0wul6txKLlKpcK9e/ewYsUKPH/+HAqFAqNGjUJoaCgWLVqkkZdgTyUhIQERERHNBOfHH3/ErFmzkJ+fz0bg7t+/H+vXr0dxcbHa++ejR48wZMgQ3LhxA6NHjwYApKamIjAwEHl5eXBwcNCoT52TPNBGbG1tWT8xbblz5w4MDQ1ZW5imeHt7o3fv3khPT2etdB4/fgyJRIJx48a1uc/6hIGBAYYOHYrExEQ8evQIW7ZswejRozF37ly4u7vjwoULWLx4MQYNGgR7e3vIZDJUV1fD0NAQffr00ZsftpmZGYYNG4bq6mqIRCJcvXoVNjY2sLa2xqtXr9h6Pvb29vDy8uqUJ18OhwN3d3fweDzk5eXh4cOHMDY2bnU20TDKTyqVsiIzcODAdhOZhhgZGbEWNEVFRRCLxRAKhayTdlv3y2pra9kxvHr1CtbW1nByctLYJBP4fTZ75swZpKSkID09HV5eXggPD4dQKERqaiouXryIsLAwvflOdiUyMjIwbNiwRukeAQEBCA8Px4MHDzBy5Ei111hZWbFiAwD+/v4wNDTEtWvXMH/+fI0+u0sJjqZkZGTg2rVrmDJlCszNzZGRkYE1a9ZgyZIl7PJG0wRSS0tLLF++HJGRkbC2toaFhQVWr16NcePGdYkINW0wMDBAv379MHHiRIjFYiQlJcHOzg7Dhg2Du7s7xo0bx854ysrKIBQKIZFI4OzsDB6PpzdhwCYmJrCzs2M92IqKimBiYgI3Nzc4OTnpxc2IKf7m4uKC/Px8PH/+HM+fP2fNZg0NDVmRKSwsRG1tLWxsbDpMZNTBiLOdnR3KysqQk5OD3377TStD07q6OhQVFUEqlaK8vBxWVlbo378/RowYobFwVVdXIzU1FcnJyfjpp5/g5uaGoKAg7N69GwMGDGD/PyUSCQ4fPtyj92neBKlU2iy3kHktlUpbvKbpw3qvXr1gbW3d4jXq6JaCw+FwcOTIEXz22Weora2FQCDAmjVrEBkZybZRKBR4/Pgxqqur2WM7d+5kN8MaJn52Rw4ePIhz584hKCgIiYmJqK2txZdffol58+ZhwYIF+PjjjzFgwABYW1vD2tqaFZ7ffvuNjSDqjBDTpi7STBKgt7c3TExMIJFI8PTpUxQVFbEO1fogPMxswtHREVKpFEKhEE+ePIGRkREb5efu7q52P0NXGBgYsP/fjC0NM3vk8/nNItvUmWRyuVx4enpqHNRRW1uLn3/+GUlJSTh79izs7e0RFBSEL774AsOGDVP7f+fi4oL169e3y5i7Cm+yf61PdKk9HF0jFouxefNm/Pzzz5BKpXBwcMCSJUvw17/+tdWbrT6XvGYghDT7MTPhpVu3bsWRI0cwb948fPzxx/Dw8GDblpeXQygUory8nJ3xdLTwKJVKdgbDrDG35iLN2L1IJBKYmprC1dVVL2zkG85kampqYGFhgbq6OtTW1rLLWPrkXgD87r7BBEFYWFjAycmJTdItKSmBmZkZay2jqXt1fX09fvvtNyQlJeH06dMwNTXFwoULsXjxYowePbrTE1P1kbbsX7e0h7Nx40acPn0ad+7cYY+JRCK4urri1q1bapfUDh48iLVr16KsrIw9Vl9fDxMTEyQlJfXsJbX2Ijs7GyqVCgcOHIC7uzuysrKwYsUKyGSy15qKrlixolnJa31C3c3XwMAAAwcORHx8PDZs2ICtW7di/PjxmDNnDtavX49BgwbBysoKo0aNYoXn0qVLHZL4yIhM01IFo0ePfq2dibGxMdzc3MDj8ZCbm4usrCyYmJhAIBC0a4luTWgqMjY2NqxTNjOTKSsrg1gsxqVLl+Dg4AA+n98hpQfagomJCdzd3WFubo6cnBzcv38fhoaGsLGxwdixYzUOiVWpVLh27RqSkpJw8uRJqFQqvPvuuzhx4gQmTJhAs/5fw5vsXzdl3Lhx+PLLL1FUVMQuk6WlpcHCwgJDhgxp8Zry8nLcvHkT3t7eAH4PtFKpVPD19dX4s+kMR0u2b9+O//u//4NQKGyxTVcvec3AlNHdunUrDh06hFmzZiEqKgqDBw9mb9oVFRUQCoUoLS2Fk5MT+Hx+m4Wnvr6eLVVQUlKCt956i40ue5NSBQ1LdPfq1atZwbr2hqkq2VBk7O3tX+u8wCRoMtF3fD5fqxyH9oQxyWScmBnBt7W1ZZfblEol69nWUu7W3bt3kZSUhBMnTqCyshLz5s1DSEgIpkyZojd7gfrAhQsXMGXKFLXnrl+/jjFjxqg9p241hUn0Pn36NLZv347ffvsNAODu7g4zMzM2LNrBwQHbtm1jHbP//Oc/s2HR169fR2hoKNLT01lvxhkzZqCwsBD79+9nw6JHjx7dfcOi9YENGzYgNTUVmZmZLbbpLiWvGyIUChETE4N///vfmDlzJqKiojBkyBBWBF69egWhUIiXL1/C0dERfD5fo3V8hULBzmRevnyJPn36NBKZ9oQpWCcWiwGgXcs3NCxXUF1d/UZO0tXV1RCLxSgoKIC1tTUEAoFOjCSZcHLGHoepjmlvb99sVsmE0IvFYshkMlRVVcHLywsuLi549OgRm/VfUFCA2bNnIzg4GNOnT+/wUt5dlbq6OpSWljY69umnnyI9PR3Pnz9v8WFr8uTJGDhwYKPVlMjISBw+fLhZW8bwGABycnIQHh6OCxcuwNTUFGFhYYiNjWW/q4wAikQiNlG8tLQUq1atapT4uWfPnu6b+NnZPHv2DN7e3oiLi2tkCtqU7lbyuiEikQixsbH417/+henTpyMqKgqenp7sD6KyshJCoRAlJSUtCg+z2cyIjJmZGSsyuqiHwzhUi8Vi1NfXt9nMtGlNHGYm017lCmpra9m6PObm5q1WS20r6spIMyKjiUkmc/2aNWtw+vRp2Nvbo7CwEIGBgQgODsasWbM6bZbWlVEoFHB0dMTq1avx6aefttiuq62m9EjBaUvEx4sXLzBp0iRMnjwZ3377rVaf111KXjdELBYjNjYW3333Hd555x1ER0c3iiqqrKyESCRCcXExHBwc4OjoyCYylpaWwtzcnBWZzpr5NTUz1cShmsmWZ0ouMImMHVnGu2m1VCaXp63C09BHjjHJ1LbCJyEE+fn5SElJQUpKCu7evQt/f39UVlbixo0bmDFjBhtpRtGelJQUBAUFIScnh3V9V0dXW03pkYKjbcRHfn4+Jk+ejLFjxyIhIUHrJZjuVvK6IRKJBLGxsYiPj4e/vz+io6MxfPhwGBgYsEmYeXl5qKurQ+/eveHo6AgnJye92RQH/uspJxKJIJPJ2LBvRkDUiYwuq3syMM4AYrEYBgYGWi0JNnQukEqlqK+vb+TErOl7lJSU4OTJk0hJSUFGRgbefvttBAcHY+HChayTwosXL7B7927Mnj0bEydObI+h9zgCAwMBAOfOnWu1XVdbTemRgqMNL168wJQpU+Dt7Y3vv/++TdE03bXkdUNyc3MRGxuLgwcPYtiwYZDL5SgsLMTRo0fZPYAXL16gqKgIXC4XAoFA757CGia6VlRUwNLSEgqFolNKSLdGwyVBhULR6syMKSDHJJXa2tqCy+Vq5cFWXl6O06dPIyUlBRcuXIC3tzeCgoIQFBQER0fHTg8312faspqSl5cHHo+HY8eOsa4nmqLvqyk0LLoVXrx4gcmTJ4PH4yEuLg7FxcXsOS6Xy7bRpOS1n59ftxUbQghOnjyJ+/fvQ6FQID8/H9bW1hg9ejSMjIzg4uLCJhXKZDKIRCJkZGSo9UHrTORyOV69egWlUsnazNTX18PBwQGurq56s+FtaGgIBwcH9O/fn924F4lEbC6PQqFgZzI1NTVtSiqVyWQ4d+4ckpOTkZaWhkGDBiEoKAj79++Hq6srFRkNWbt2Lf74xz+22sbV1bXR6/j4ePTr1w9z5szR+vOYEGUqOF2QtLQ0PHv2DM+ePWu2jspMDJs6FhgbG+P8+fPYtWsXXr16xbbt27cvrl+/Dh8fnxY/LykpCZ9++inEYjEGDBiAr776ip1a6zMGBgZ48uQJQkJCcOzYMXC5XLx48QLbtm3D9OnT4efnh+joaHh7e8PU1BSenp5wdXVlfdA6U3iamks29f1iHKovX76s83o3r4MxJbW1tWXdC0QiEQCw0W3aBDDI5XKkpaUhOTkZP/74IxwdHREcHIyvvvqqUSg8RXO0zZ8hhCA+Ph6hoaFtmkkzyZz9+/fX+lpdQJfUOoijR48iNDQU+/fvh6+vL3bt2oWkpCQ8fvxYrYHolStX4Ofnh5iYGMyaNQuJiYn46quvcOvWLXh6enbCCNqHgoICbNu2DX//+98xYcIEREdHY8yYMezNq2EIsJ2dHQQCQYdHNdXU1KCoqAiFhYWsuSSzXNaSa0LDejednSPDIJfLWf8yZhyWlpaorKzEy5cvNeqnQqHAhQsXkJycjB9++AFWVlZYtGgRQkJCMHLkSJr13wQ+n4+cnJxGx2JiYhAVFdXiNXK5HGvXrsWRI0caWWY19TMDgPT0dPj7+6u1qdF0NcXJyalZbo6+QAWng/D19cWYMWOwd+9eAL+vuzs7O2P16tVqv5zBwcGQyWQ4c+YMe2zs2LEYMWKEXlnitBWpVIrt27fjwIEDGDduHKKjo+Hr68sKT01NDUQiEQoKCmBrawtXV9d2vaEze0qMyPTt25e1x9HGmqehQNrY2EAgEMDCwqLd+vk66urq2HEwJplM+YiG45DJZMjJyUFBQQH69esHOzs71kJeqVTiypUrSE5OxsmTJ9GrVy8sXLgQISEhGDduHBWZVuDz+Vi+fHmjtAhzc/NWZ+fh4eE4e/YsEhISYGlpiVWrVsHQ0BCXL19u1va9995DTk6O2nNisRgCgYDNp8nNzcWSJUuQlZUFmUwGZ2dnzJ8/Hxs2bNDpd1IbqOB0AHV1dejTpw+Sk5Mxb9489nhYWBjKy8tx6tSpZte4uLggMjISERER7LFNmzbh5MmTuHv3rg56rRsKCwsRFxeH/fv3w8fHB9HR0aw7NfC7MIhEIuTn57M2MG11BW46A2iryLT03mKxmC201pHJmQqFgp2RNTTJtLe3f62rg1wuh0QiwbJly6BSqeDh4YFLly6htrYWCxYsQEhICCZNmtSuNXC6M3w+HxEREY1+p61RUVEBW1tbJCYmYuHChQB+t8waPHgwMjIyup0T/eugjzIdQElJCZRKpVoL8Nbsv7Vp31Wxt7fH9u3b8fz5c3h7e2P+/PmYNWsWLl26BEIITExMMHjwYLz99tvgcDi4fv067ty5w+6HvQ7mBnvjxg1cunSJzQPy8/ODt7c3nJyc2sVs1MTEBIMGDcKECRNgZmaGW7duITMzE6WlpWiPZ7j6+noUFBTg9u3buHjxIvLy8mBtbY23334bPj4+Ghl9EkLw7NkzHDp0CDU1NSCEsGaZ33zzDfbv34+pU6dSsdGS2NhY9OvXDyNHjsT27dtRX1/fYtubN29CoVDA39+fPTZo0CC4uLggIyNDF93VK+g3jdIp2NnZYdu2bfjoo4/w9ddfY+HChRg5ciSio6MxceJE9obOrJnfuHED1tbWcHV1bWaTz8xkCgsLUVFRwS4zeXl5dbj7MofDwYABA8Dn8yGRSHD37l2YmppCIBBoVeET+K9hqVQqRUlJCfr06QMulwsPDw+NAxUYkWGsZcRiMQIDA7F582bMnDkThBB8++23WLduHSwtLTF9+vS2Dr1H8r//+78YNWoUrK2tceXKFURHR6OgoAA7duxQ214qlcLY2LjZ7Lc7PkxqAhWcDoAJPy0sLGx0vLCwkA2nbgqXy9WqfXfB1tYWsbGxWLduHXbs2IHg4GAMHz4c0dHR8PPzg4mJCTw8PFjhyczMZCPJ5HI5pFKpzkVGHb1792YdqpkKnxwO57UO1SqVivWSY0wyuVwu3NzcNN7DIoQgNzcXx48fR1JSEh4+fIhp06YhOjoac+fObbae/+GHHyI8PJzObP4/2uTKNKyp5eXlBWNjY3zwwQeIiYnRu9IS+gjdw+kgfH194ePjg7/97W8Afr+xuLi4YNWqVS0GDVRXV+OHH35gj40fPx5eXl7dImhAU16+fImdO3di7969GDZsGCs8hoaGKCkpQVVVFXJzcyGXy9GrVy/Wzl/ffuxNHar5fD64XC4MDQ2hUqlQWlqKwsLCRiaZXC5XY1dspibNiRMnkJKSghs3bsDPzw8hISFYsGABrK2taRizhrSl1gzDgwcP4OnpiezsbHh4eDQ7zyRilpWVNZrl8Hg8REREYM2aNW/c/64EFZwO4ujRowgLC8OBAwfg4+ODXbt24dixY8jOzoa9vT1CQ0Ph6OiImJgYAL+HRU+aNAmxsbGYOXMmjhw5gq1bt3b5sOi2Ulpaip07d2LPnj1wcnKCkZERnj59ilOnTsHFxQV9+/aFVCpFbm4uLC0t4erqypYP1ycYh2qRSASVSoU+ffpAJpPB0NAQ9vb24HK5aovIqYNxQjh16hSSk5Nx6dIl+Pr6IigoCIsWLQKXy6Uio2MOHTqE0NBQlJSUqP3+MUEDhw8fZl0DHj9+jEGDBvXIoAE6p+4ggoODUVxcjI0bN0IqlWLEiBFITU1lAwMkEkmj8NPx48cjMTERGzZswCeffIIBAwbg5MmTPVJsAOD06dPIyMhAdXU1Kisr0a9fP4wZMwZyuRxOTk4wNDSEubk5eDweJBIJ7ty5A3Nzc7i6usLa2rqzuw/gd4F49eoVqqqqoFKpoFQqUVVVBQMDA9aORpPM/8rKSpw5cwYpKSlIT0+Hp6cngoODER8fDx6PR0VGR2RkZODatWuYMmUKzM3NkZGRgTVr1mDJkiWs2DTNlbG0tMTy5csRGRkJa2trWFhYYPXq1Rg3blyPExuAznD0npiYGBw/fhzZ2dl46623MH78eHz11Vdqp+8MCQkJWLZsWaNjHA4Hcrm8o7vbbnzyySews7PDu+++C2dnZ5SXl2P37t3YvXs3BgwYgE8++QRTp05lRVuhUEAikUAikcDMzAxubm4aOx+3J4xJJuNfVl9f38yJuaioCCKRCHK5HDweD87Ozs32U6qrq/HTTz8hOTkZP/30EwQCAYKCghASEoKBAwdSkWmBjiwLf+vWLfzlL39BdnY2amtrIRAIsHTpUkRGRrJLuk1zZYD/Jn4ePny4UeJnd9+fVQcVHD1n+vTpCAkJwZgxY1BfX49PPvkEWVlZePjwYYvJZgkJCfjwww/x+PFj9piBgYHazOauRkVFBfbs2YNdu3bBzc0N0dHRmDZtWiPhyc3NRU5ODszMzNgZT0feoBnfNca/rK6uji290JJJJiEEL1++hFAoxLNnz5CZmYnIyEhkZWUhKSkJZ8+eha2tLSsyXl5eVGQ0IDU1FUePHsXixYsblYVfunRpq2Xh1RUy69Onj94mUHZVqOB0MYqLi2FnZ4eLFy/Cz89PbZuEhARERESgvLxct53TIRUVFdi7dy927twJPp+PqKgoTJ8+nb2519fXs8LTp08fuLq6tnvxsqalpBs6MWtqkqlQKHDo0CHs3bsXz549A4fDQUhICJYvXw4fHx+a9d8O9KSy8PoO/TZ3MSoqKgDgtfsUVVVV7HLN3Llz8eDBA110T2dYWlrir3/9K4RCId59912Eh4fDz88PZ86cgUqlQq9evSAQCDBhwgTY2toiKysL169fR3Fx8RslZjIWPFevXkVGRgYqKyvh6uqKSZMmwcvLC3Z2dq8VG5VKhatXr2Lt2rXw8PDAZ599Bj8/P+zatQuTJ0/GoUOH8OOPP1KxaScqKio02tc7dOgQbGxs4OnpiejoaNaQl9J+0BlOF0KlUmHOnDkoLy/HpUuXWmyXkZGBp0+fwsvLCxUVFYiLi8Ovv/6KBw8etFo9sCtTWVmJffv2YceOHXB0dERUVBRmzpzJ3rSVSiU74+FwOHB1dYWtra1GM56mPmzW1tbgcrla1cZRqVS4d+8ekpKScPz4cbx69Qpz585FSEgIpk6d2uh97t69C6FQiPnz57ftH4PCQsvC6xdUcLoQ4eHh+PHHH3Hp0iWthEOhUGDw4MFYvHgxNm/e3IE97HyqqqrwzTff4OuvvwaXy0VUVBRmz57dSHjy8vIgFotbFR7GJJNJLG2LDxshBNnZ2WzWf35+PmbNmoXg4GBMnz5dr6qe6ju0LHz3gApOF2HVqlU4deoUfv31VwgEAq2vX7RoEXr16oXDhw93QO/0j6qqKuzfvx9xcXGws7PD+vXrMWfOHHa5q2FiZu/evdk8nuLiYkilUpSVlcHS0pKNMNM0sZQQArFYjJSUFCQnJ+PJkycICAhASEgIZs+e3eklDboqtCx894AKjp5DCMHq1atx4sQJXLhwAQMGDND6PZRKJYYOHYrAwMAWPZ+6KzKZDAcOHMD27dthY2OD9evXY+7cuazw1NbW4unTpygsLIRKpcJbb70FJycncLlcjSt8EkKQn5+P48ePIyUlBXfu3MGUKVMQHByM+fPn62VCaneGloXXYwhFrwkPDyeWlpbkwoULpKCggP2rrq5m2yxdupRERUWxrz///HPy008/kefPn5ObN2+SkJAQYmJiQh48eNAZQ9ALZDIZ2blzJ3FwcCCDBg0iq1evJpMmTSKLFy8m58+fJ/fv3yf37t0jqampJC0tjTx79oxUVVURmUym9q+qqork5OSQ3bt3k4kTJ5JevXoRPz8/sm/fPlJYWEhUKlVnD1mv2Lt3L+HxeITD4RAfHx9y7dq1VtsfO3aMeHh4EA6HQzw9PcnZs2c1+py8vDzi7u5Opk6dSvLy8hr9Zhq28fDwYPvw7Nkz8sUXX5DMzEwiEonIqVOniKurK/Hz82v7gClqoYKj5wBQ+xcfH8+2mTRpEgkLC2NfR0REEBcXF2JsbEzs7e1JYGAguXXrlu47r0fI5XJy6tQpsmjRImJsbEzMzMzImDFjSGxsLKmoqGCFpLKykjx+/JikpqaS//znPyQ7O5uUlZWx5/Pz88n+/fvJtGnTSO/evYmPjw+Ji4sjEomEikwLHDlyhBgbG5ODBw+SBw8ekBUrVhArKytSWFiotv3ly5eJkZER2bZtG3n48CHZsGED6d27N7l///5rPys+Pr7F3wyDSCQiAMgvv/xCCCFEIpEQPz8/Ym1tTTgcDnF3dycfffQRqaioaJfxU/4LFZwexqZNm5r9ED08PFq9pq1Pm/rE9evXiUAgIFFRUeTOnTukurqa7Nmzhzg5OREPDw/yz3/+s5nwPHnyhGzYsIE4ODiQ999/nwQGBhIOh0O8vLzIl19+SZ4+fUpFRgN8fHzIypUr2ddKpZI4ODiQmJgYte2DgoLIzJkzGx3z9fUlH3zwQYf2k9LxUMHpYWzatIkMHTq00VJDcXFxi+3f5GlTn1CpVGrFoaamhuzdu5c4OzuTgQMHkn/84x+koqKCvHz5khw9epQsXLiQDBs2jJiamhIrKyvyxRdfkNra2k4YQdektraWGBkZkRMnTjQ6HhoaSubMmaP2GmdnZ7Jz585GxzZu3Ei8vLw6qJcUXUEzy3ogDe3wuVwubGxsWmy7e/duTJ8+HR999BEGDx6MzZs3Y9SoUdi7d68Oe/zmGBgYqM25MTExwcqVK/H06VNERERgy5Yt4PF4cHFxwUcffQQej4eDBw+itLQUe/bswffff48//elPnTCCrgmtfktpCBWcHsjTp0/h4OAAV1dX/OEPf4BEImmxbUZGRqPyuAAQEBDQ7crjcjgchIeH48mTJ5g/fz7+/e9/QyQSIS4uDqNHj4axsTGWLl2Khw8f4uuvv+7s7lIoXRJanqCH4evri4SEBHh4eKCgoACff/45Jk6ciKysLJibmzdr39OeNo2NjXHw4MEWzxsZGXULE1RdQavfUhpCZzg9jBkzZmDRokXw8vJCQEAAzp07h/Lychw7dqyzu0bphhgbG8Pb2xvp6ensMZVKhfT0dIwbN07tNePGjWvUHgDS0tJabE/pOlDB6eFYWVlh4MCBePbsmdrz9GmzexMTE4MxY8bA3NwcdnZ2mDdvXqOyFupISEhg98SYv9aSZCMjI/GPf/wD3333HR49eoTw8HDIZDK2ZlNoaCiio6PZ9h9++CFSU1Px9ddfIzs7G5999hkyMzOxatWq9hk0pdOggtPDqaqqwvPnz9G/f3+15+nTZvfm4sWLWLlyJa5evYq0tDQoFAq88847kMlkrV5nYWGBgoIC9i8nJ6fFtsHBwYiLi8PGjRsxYsQI3Llzp1n124KCArY9U/3273//O4YPH47k5OQeXf22W9HZYXIU3bJ27Vpy4cIFIhKJyOXLl4m/vz+xsbEhRUVFhJDmrgWXL18mvXr1InFxceTRo0dk06ZNXTIsmqIZRUVFBAC5ePFii23i4+OJpaWl7jpF6TbQGU4PIy8vD4sXL4aHhweCgoLQr18/XL16Fba2tgDo02ZPh9ZbonQk1LyT8kbw+Xy1yyl/+ctfsG/fvmbHExIS2LV7Bg6HA7lc3mF9pGgGrbdE6WhoWDTljbhx4waUSiX7OisrC9OmTcOiRYtavMbCwqLRxnR7ln2mtJ2VK1ciKyurVbEBft/Xa7iHN378eAwePBgHDhzo9vWWKG8GFRzKG8EsxTHExsbCzc0NkyZNavEaAwMDGuWmZ6xatQpnzpzBr7/+qvUspXfv3hg5cmSLkY4UCgPdw6G0G3V1daz1S2uzFrr+rz8QQrBq1SqcOHECP//8c5uK+ymVSty/f7/FSEcKhYEKDqXdOHnyJMrLy/HHP/6xxTYeHh44ePAgTp06he+//x4qlQrjx49HXl6e7jpKYVm5ciW+//57JCYmwtzcHFKpFFKpFDU1NWybpnkyX3zxBf7zn/9AKBTi1q1bWLJkCXJycvDnP/+5M4ZA6Up0cpQcpRvxzjvvkFmzZml1TV1dHXFzcyMbNmzooF51XXRRSqLp+4PWW6J0IHQPh9Iu5OTk4Pz58zh+/LhW19H1/9YZOnQozp8/z77u1avln+yVK1ewePFixMTEYNasWUhMTMS8efNw69atFsPYiQZBqhcuXGj0eufOndi5c6dmA6BQGkCX1CjtQnx8POzs7DBz5kytrqPr/63TE0tJULovVHAob4xKpUJ8fDzCwsKaPYHT9f83g5aSoHQn6JIa5Y05f/48JBKJ2sJkEokEhob/fa4pKyvDihUrIJVK0bdvX3h7e+PKlSsYMmSILrvcJaClJCjdDeo0QKF0EcrLy8Hj8bBjxw4sX7682XljY2N89913WLx4MXvsm2++weeff97M8ZtC6QzokhqlU/n1118xe/ZsODg4wMDAACdPnmx0nhCCjRs3on///njrrbfg7++Pp0+fvvZ99+3bBz6fDxMTE/j6+uL69esdNALdQUtJULo6VHAonYpMJsPw4cPV+q4BwLZt27Bnzx7s378f165dg6mpKQICAlr1Xjt69CgiIyOxadMm3Lp1C8OHD0dAQACKioo6ahg6gZaSoHR5Ojcqm0L5LwDIiRMn2NcqlYpwuVyyfft29lh5eTnhcDjk8OHDLb6Pj48PWblyJftaqVQSBwcHEhMT0yH97ihoKQlKd4POcCh6i0gkglQqbRR5ZWlpCV9f3xYjr+rq6nDz5s1G1xgaGsLf379do7X4fH6zqpcGBgZYuXKl2vbaVskEaCkJSveDRqlR9BYmukqbyKuSkhIolUq112RnZ7db33Thkn3kyJFWzzdNyASARYsWtdoHCqUzoYJDobQB6pJNoWgPXVKj6C3MzVmbyCsbGxsYGRnpNFqLumRTKJpBBYeitwgEAnC53EaRV69evcK1a9dajLwyNjaGt7d3o2tUKhXS09M7LFqLumRTKBrS2VELlJ5NZWUluX37Nrl9+zYBQHbs2EFu375NcnJyCCGExMbGEisrK3Lq1Cly7949MnfuXCIQCEhNTQ37Hv/zP/9D/va3v7Gvjxw5QjgcDklISCAPHz4k77//PrGysiJSqbRDxkBdsikUzaB7OJROJTMzE1OmTGFfR0ZGAgDCwsKQkJCAjz/+GDKZDO+//z7Ky8sxYcIEpKamNorwev78OUpKStjXwcHBKC4uxsaNGyGVSjFixAikpqY2CyRoD6hLNoWiOdTahkJ5Az777DMcOHAAubm5rZYOaIpSqcTQoUMRGBiIHTt2dGAPKRT9ge7hUChthLpkUyjaQZfUKJQ2Ql2yKRTtoEtqFAqFQtEJdEmNQqFQKDqBCg6FQqFQdAIVHAqFQqHoBCo4FAqFQtEJVHAoFAqFohOo4FAoFApFJ1DBoVAoFIpOoIJDoVAoFJ1ABYdCoVAoOoEKDoVCoVB0AhUcCoVCoegEKjgUCoVC0QlUcCgUCoWiE6jgUCgUCkUnUMGhUCgUik6ggkOhUCgUnUAFh0KhUCg64f8BM57+1snFKqQAAAAASUVORK5CYII=\n", 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\n", 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" ] @@ -262,229 +322,193 @@ "source": [ "# mvg data\n", "fig = plt.figure()\n", - "ax1 = fig.add_subplot(111, projection='3d')\n", + "ax1 = fig.add_subplot(111, projection=\"3d\")\n", "\n", - "ax1.plot(data[:, 0], data[:, 1], data[:, 2], '*', c='b', label='MVG')\n", - "ax1.legend(loc='upper left');\n", - "ax1.axis('equal')\n", + "ax1.plot(data[:, 0], data[:, 1], data[:, 2], \"*\", c=\"b\", label=\"MVG\")\n", + "ax1.legend(loc=\"upper left\")\n", + "ax1.axis(\"equal\")\n", "elev = 20\n", "azim = 50\n", "roll = 0\n", "ax1.view_init(elev, azim, roll)\n", "\n", - "plt.show()\n" + "plt.show()" ] }, { "cell_type": "code", - "execution_count": 11, - "id": "e642837c-d6b0-40c0-94b8-136127796ee1", - "metadata": {}, - "outputs": [], - "source": [ - "# fit an unsupervised forest\n", - "unsup_rf = Un" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "155e06b8-be96-421c-9bbe-ea8333670c8f", + "execution_count": 27, + "id": "438211c0-228c-453d-aaec-02813988177f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "(30, 2)\n", - "(30, 2) (30, 2)\n" + "(1000, 3)\n" ] } ], "source": [ - "print(X.shape)\n", - "print(indices.shape, dists.shape)" + "# now we will embed in high-dimensions\n", + "data, mean, cov = mvg_data\n", + "print(data.shape)\n", + "X = embed_high_dims(data, n_dims=50, random_state=seed)" ] }, { "cell_type": "code", - "execution_count": 13, - "id": "ed563ca6-fb7c-4ed0-a6c8-e12cebfad1e1", + "execution_count": 28, + "id": "ff5c92e5-65e6-4990-9287-708e4af32450", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[[0. 1.]\n", - " [0. 1.]\n", - " [0. 1.]\n", - " [0. 1.]\n", - " [0. 1.]]\n" + "(1000, 2) (1000, 3)\n" ] } ], "source": [ - "print(dists[:5, :])" + "X = embed_high_dims(data[:, [0]], n_dims=n_noise_dims, random_state=seed)\n", + "Y = embed_high_dims(data[:, [1]], n_dims=n_noise_dims, random_state=seed)\n", + "Z = embed_high_dims(data[:, [2]], n_dims=n_noise_dims, random_state=seed)\n", + "highdim_data = np.hstack((X, Y, Z))\n", + "\n", + "print(X.shape, data.shape)" ] }, { "cell_type": "code", - "execution_count": 68, - "id": "8d454e2c-3cee-4dcf-b386-cd613e6f8b32", + "execution_count": 38, + "id": "cc2209c6-3562-44e2-95d9-8343e24b5e28", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[0. 0.25 0.5 ]\n", - " [0.25 0. 0.75]\n", - " [0.5 0.75 0. ]]\n", - "[[0. 0.25 0.5 ]\n", - " [0. 0. 0.75]\n", - " [0. 0. 0. ]]\n" - ] - } - ], + "outputs": [], "source": [ - "X = np.arange(9).reshape((3, -1))\n", - "X = 0.5 * (X + X.T)\n", - "X = X / np.max(X)\n", - "X[np.diag_indices_from(X)] = 0.0\n", - "print(X)\n", - "\n", - "print(np.triu(X, 1))" + "clf = UnsupervisedObliqueRandomForest(\n", + " n_estimators=10,\n", + " feature_combinations=feature_combinations,\n", + " n_jobs=n_jobs,\n", + " random_state=seed,\n", + ")\n", + "# clf.fit(highdim_data)\n", + "est = NearestNeighborsMetaEstimator(\n", + " clf, n_neighbors=n_nbrs, algorithm=\"auto\", n_jobs=n_jobs\n", + ")" ] }, { "cell_type": "code", - "execution_count": 69, - "id": "e35dcdc7-f0d7-478e-a7f4-dc40f33af292", + "execution_count": 35, + "id": "aadc7bb0-40e5-4e5c-9e99-f810d570b19f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "(3, 3) (3, 3)\n", - "[[0 1 2]\n", - " [1 0 2]\n", - " [2 0 1]]\n", - "[[0. 0.25 0.5 ]\n", - " [0. 0.25 0.75]\n", - " [0. 0.5 0.75]]\n" + "[[ 0.31087872 0.01905156 -0.19413813]\n", + " [ 0.01905156 1.21114085 2.27200637]\n", + " [-0.19413813 2.27200637 5.13099624]]\n" ] } ], "source": [ - "\n", - "nbrs = NearestNeighbors(\n", - " n_neighbors=3, metric=\"precomputed\", n_jobs=n_jobs\n", - " ).fit(X)\n", - "\n", - "# then get the K nearest nbrs in the Z space\n", - "dists, indices = nbrs.kneighbors(X)\n", - "\n", - "print(dists.shape, indices.shape)\n", - "print(indices)\n", - "print(dists)" + "print(cov)" ] }, { "cell_type": "code", - "execution_count": 38, - "id": "b6769533-095a-46d3-ab25-5adf10503bcc", + "execution_count": 36, + "id": "3bded813-31ea-44ba-bf77-973b3338f0fc", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "(array([1, 2, 2]), array([0, 0, 1]))\n", - "[3 6 7]\n" + "0.8879202209746868\n", + "0.09749224201325823\n" ] } ], "source": [ - "# get the triu indices\n", - "triu_idx = np.triu_indices_from(X, 1)\n", - "\n", - "print(triu_idx)\n", - "print(X[triu_idx])\n", - "\n" + "# true MI and CMI\n", + "true_mi = mi_gaussian(cov, 1, 2)\n", + "true_cmi = cmi_gaussian(cov, 0, 1, 2)\n", + "print(true_mi)\n", + "print(true_cmi)" ] }, { "cell_type": "code", - "execution_count": 48, - "id": "6806acd9-bae0-4d08-9f34-a1026bcc9f31", - "metadata": {}, + "execution_count": null, + "id": "c051b1e1-4262-49c0-8383-74565b192a6b", + "metadata": { + "tags": [] + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[[0 1]\n", - " [0 2]\n", - " [1 2]]\n", - "[1 2 5]\n" + "Data shape: (1000, 4)\n", + "X shape: (1000, 2), Y shape: (1000, 2)\n", + "Preprocessing complete.\n", + "Using 10 neighbors to define D-dimensional volume.\n" ] } ], "source": [ - "# get the triu indices\n", - "triu_idx = np.triu_indices_from(X, 1)\n", - "\n", - "triu_ravel_argsort_idx = np.argsort(X[triu_idx], axis=None)\n", - "\n", - "triu_argsort_idx = np.vstack(triu_idx).T[triu_ravel_argsort_idx].squeeze()\n", - "\n", - "print(triu_argsort_idx)\n", - "print(X[triu_argsort_idx[:, 0], triu_argsort_idx[:, 1]])\n", - "# print(ravel_argsort_idx)" + "ksg_mi = mutual_info_ksg(X, Y, nn_estimator=est, n_jobs=n_jobs, k=10, verbose=True)" ] }, { "cell_type": "code", - "execution_count": 37, - "id": "1862eae0-ef26-4cfc-8448-c835053c9edb", + "execution_count": null, + "id": "162653a5-d2f9-4e17-91fa-04be2c8515d7", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(array([0, 0, 0]), array([0, 1, 2]))\n" - ] - } - ], + "outputs": [], "source": [ - "print(np.unravel_index(ravel_argsort_idx, (3, 3)))" + "print(ksg_mi)" ] }, { "cell_type": "code", - "execution_count": 34, - "id": "f321a9a1-1006-41d5-9eb0-5739929fa331", + "execution_count": 70, + "id": "ecc4b670-3099-457b-b783-3e0aab245e6c", + "metadata": {}, + "outputs": [], + "source": [ + "cmi_est = CMITest(k=0.2, n_jobs=n_jobs, random_seed=seed)" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "id": "4b5ce049-3722-4586-ae05-f2b6273fcead", "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "[0 1 2]\n", - "[[0 0]\n", - " [0 1]\n", - " [0 2]]\n" - ] + "data": { + "text/plain": [ + "0.6522836124816846" + ] + }, + "execution_count": 71, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "argsort_idx = np.unravel_index(ravel_argsort_idx, (3, 3))\n", + "df_x = pd.DataFrame(X, columns=[f'x{idx}' for idx in range(X.shape[1])])\n", + "x_cols = df_x.columns\n", + "df_y = pd.DataFrame(Y, columns=[f'y{idx}' for idx in range(Y.shape[1])])\n", + "y_cols = df_y.columns\n", + "df = pd.concat((df_x, df_y), axis=1)\n", "\n", - "print(ravel_argsort_idx)\n", - "print(np.vstack(argsort_idx).T)" + "cmi_est._compute_cmi(df, x_cols, y_cols, set())" ] }, { diff --git a/sktree/experimental/__init__.py b/sktree/experimental/__init__.py index bf88ce488..0b4eb9304 100644 --- a/sktree/experimental/__init__.py +++ b/sktree/experimental/__init__.py @@ -7,5 +7,5 @@ mi_from_entropy, mi_gamma, mi_gaussian, - mutual_info_ksg, ) +from .ksg import mutual_info_ksg \ No newline at end of file diff --git a/sktree/experimental/ksg.py b/sktree/experimental/ksg.py new file mode 100644 index 000000000..8b19c39a4 --- /dev/null +++ b/sktree/experimental/ksg.py @@ -0,0 +1,317 @@ +from typing import Optional + +import numpy as np +import scipy.linalg +import scipy.special +import scipy.stats +from numpy.typing import ArrayLike +from sklearn.base import BaseEstimator +from sklearn.neighbors import NearestNeighbors +from sklearn.preprocessing import StandardScaler + + +def mutual_info_ksg( + X, + Y, + Z=None, + k: float = 0.2, + nn_estimator=None, + n_jobs: int = -1, + transform: str = "rank", + random_seed: int = None, + verbose: bool=False +): + """Compute the generalized (conditional) mutual information KSG estimate. + + Parameters + ---------- + X : ArrayLike of shape (n_samples, n_features_x) + The X covariate space. + Y : ArrayLike of shape (n_samples, n_features_y) + The Y covariate space. + Z : ArrayLike of shape (n_samples, n_features_z), optional + The Z covariate space, by default None. If None, then the MI is computed. + If Z is defined, then the CMI is computed. + k : float, optional + The number of neighbors to use in defining the radius, by default 0.2. + If a number less than 1, then the number of neighbors is computed as + ``k * n_samples``. + nn_estimator : str, optional + The nearest neighbor estimator to use, by default None. If None willl default + to using :class:`sklearn.neighbors.NearestNeighbors` with default parameters. + n_jobs : int, optional + Number of parallel jobs, by default -1. + transform : one of {'rank', 'standardize', 'uniform'} + Preprocessing, by default "rank". + random_seed : int, optional + Random seed, by default None. + + Returns + ------- + val : float + The estimated MI, or CMI value. + + Notes + ----- + Given a dataset with ``n`` samples, the KSG estimator proceeds by: + + 1. For fixed k, get the distance to the kth nearest-nbr in XYZ subspace, call it 'r' + 2. Get the number of NN in XZ subspace within radius 'r' + 3. Get the number of NN in YZ subspace within radius 'r' + 4. Get the number of NN in Z subspace within radius 'r' + 5. Apply analytic solution for KSG estimate + + For MI, the analytical solution is: + + .. math:: + + \\psi(k) - E[(\\psi(n_x) + \\psi(n_y))] + \\psi(n) + + For CMI, the analytical solution is: + + .. math:: + + \\psi(k) - E[(\\psi(n_{xz}) + \\psi(n_{yz}) - \\psi(n_{z}))] + + where :math:`\\psi` is the DiGamma function, and each expectation term + is estimated by taking the sample average. + + Note that the :math:`n_i` terms denote the number of neighbors within + radius 'r' in the subspace of 'i', where 'i' could be for example the + X, Y, XZ, etc. subspaces. This term does not include the sample itself. + + The hyperparamter ``k`` defines the number of points in the D-dimensional + ball with a specified radius. The larger the k, the higher the bias in + the estimate, but the lower the variance. The smaller the k, the lower + the bias, but the higher the variance. The default value of 0.2 is set + to allow scaling with the number of samples. + """ + rng = np.random.default_rng(random_seed) + + if nn_estimator is None: + nn_estimator = NearestNeighbors(n_jobs=n_jobs) + + data = np.hstack((X, Y)) + x_idx = np.arange(X.shape[1]) + y_idx = np.arange(Y.shape[1]) + X.shape[1] + z_idx = np.array([]) + if Z is not None: + z_idx = np.arange(Z.shape[1]) + data.shape[1] + data = np.hstack((data, Z)) + + data = _preprocess_data(data, transform, rng) + if verbose: + print(f"Data shape: {data.shape}") + print(f"X shape: {X.shape}, Y shape: {Y.shape}") + if Z is not None: + print(f"Z shape: {Z.shape}") + print('Preprocessing complete.') + n_samples = data.shape[0] + + # get the number of neighbors to use in estimating the CMI + if k < 1: + knn_here = max(1, int(k * n_samples)) + else: + knn_here = max(1, int(k)) + + if verbose: + print(f"Using {knn_here} neighbors to define D-dimensional volume.") + + if Z is not None: + val = _cmi_ksg(data, x_idx, y_idx, z_idx, nn_estimator, knn_here) + else: + val = _mi_ksg(data, x_idx, y_idx, nn_estimator, knn_here) + return val + + +def _preprocess_data(data, transform, rng): + n_samples, n_features = data.shape + + # add minor noise to make sure there are no ties + random_noise = rng.random((n_samples, n_features)) + data += 1e-5 * random_noise @ np.std(data, axis=0).reshape(n_features, 1) + + if transform == "standardize": + # standardize with standard scaling + data = data.astype(np.float64) + scaler = StandardScaler() + data = scaler.fit_transform(data) + elif transform == "uniform": + data = _trafo2uniform(data) + elif transform == "rank": + # rank transform each column + data = scipy.stats.rankdata(data, axis=0) + return data + + +def _mi_ksg(data, x_idx, y_idx, nn_estimator: BaseEstimator, knn_here: int, verbose: bool=False)-> float: + """Compute KSG estimate of MI. + + Parameters + ---------- + data : ArrayLike + Stacked data of X and Y. + x_idx : ArrayLike + Indices for the X data stored as a 1D array. + y_idx : ArrayLike + Indices for the Y data stored as a 1D array. + nn_estimator : BaseEstimator + Nearest neighbor estimator. + knn_here : int + Number of nearest neighbors used in nn_estimator to estimate the volume + of the joint distribution. + + Returns + ------- + val : float + Estimated MI value. + """ + n_samples = data.shape[0] + + # estimate distance to the kth NN in XYZ subspace for each sample + neigh = nn_estimator.fit(data, force_fit=True) + dists, _ = neigh.kneighbors(n_neighbors=knn_here) + + # - get the radius we want to use per sample as the distance to the kth neighbor + # in the joint distribution space + radius_per_sample = dists[:, -1] + + # compute on the subspace of X + num_nn_x = _compute_radius_nbrs( + data, + radius_per_sample, + nn_estimator, + col_idx=x_idx + ) + + # compute on the subspace of Y + num_nn_y = _compute_radius_nbrs( + data, + radius_per_sample, + nn_estimator, + col_idx=y_idx + ) + + # compute the final MI value + # \\psi(k) - E[(\\psi(n_x) + \\psi(n_y))] + \\psi(n) + hxy = scipy.special.digamma(knn_here) + hx = scipy.special.digamma(num_nn_x) + hy = scipy.special.digamma(num_nn_y) + hn = scipy.special.digamma(n_samples) + val = hxy - (hx + hy).mean() + hn + return val + + +def _cmi_ksg(data: ArrayLike, x_idx, y_idx, z_idx, nn_estimator: BaseEstimator, knn_here: int) -> float: + """Compute KSG estimate of CMI. + + Parameters + ---------- + data : ArrayLike + Stacked data of X, Y and Z. + x_idx : ArrayLike + Indices for the X data stored as a 1D array. + y_idx : ArrayLike + Indices for the Y data stored as a 1D array. + z_idx : ArrayLike + Indices for the Z data stored as a 1D array. + nn_estimator : BaseEstimator + Nearest neighbor estimator. + knn_here : int + Number of nearest neighbors used in nn_estimator to estimate the volume + of the joint distribution. + + Returns + ------- + val : float + Estimated CMI value. + """ + # estimate distance to the kth NN in XYZ subspace for each sample + neigh = nn_estimator.fit(data, force_fit=True) + + # get the radius we want to use per sample as the distance to the kth neighbor + # in the joint distribution space + dists, _ = neigh.kneighbors(knn_here) + radius_per_sample = dists[:, -1] + + # compute on the subspace of XZ + xz_idx = np.concatenate((x_idx, z_idx)) + num_nn_xz = _compute_radius_nbrs( + data, + radius_per_sample, + nn_estimator, + col_idx=xz_idx, + ) + + # compute on the subspace of YZ + yz_idx = np.concatenate((y_idx, z_idx)) + num_nn_yz = _compute_radius_nbrs( + data, + radius_per_sample, + nn_estimator, + col_idx=yz_idx, + ) + + # compute on the subspace of XZ + num_nn_z = _compute_radius_nbrs( + data, + radius_per_sample, + nn_estimator, + col_idx=z_idx, + ) + + # compute the final CMI value + hxyz = scipy.special.digamma(knn_here) + hxz = scipy.special.digamma(num_nn_xz) + hyz = scipy.special.digamma(num_nn_yz) + hz = scipy.special.digamma(num_nn_z) + val = hxyz - (hxz + hyz - hz).mean() + return val + + +def _compute_radius_nbrs( + data: ArrayLike, + radius_per_sample: ArrayLike, + nn_estimator: BaseEstimator, + col_idx: Optional[ArrayLike] = None, +): + n_samples = radius_per_sample.shape[0] + + # compute distances in the subspace defined by data + nn_estimator.fit(data[:, col_idx], force_fit=True) + + num_nn_data = np.zeros((n_samples,)) + for idx in range(n_samples): + nn = nn_estimator.radius_neighbors(radius=radius_per_sample[idx], return_distance=False) + num_nn_data[idx] = len(nn) + return num_nn_data + + +def _trafo2uniform(X): + """Transforms input array to uniform marginals. + + Assumes x.shape = (dim, T) + + Parameters + ---------- + X : arraylike + The input data with (n_samples,) rows and (n_features,) columns. + + Returns + ------- + u : array-like + array with uniform marginals. + """ + + def trafo(xi): + xisorted = np.sort(xi) + yi = np.linspace(1.0 / len(xi), 1, len(xi)) + return np.interp(xi, xisorted, yi) + + _, n_features = X.shape + + # apply a uniform transformation for each feature + for idx in range(n_features): + marginalized_feature = trafo(X[:, idx].to_numpy().squeeze()) + X[:, idx] = marginalized_feature + return X diff --git a/sktree/experimental/meson.build b/sktree/experimental/meson.build index e92935a50..3d0620146 100644 --- a/sktree/experimental/meson.build +++ b/sktree/experimental/meson.build @@ -2,6 +2,7 @@ python_sources = [ '__init__.py', 'mutual_info.py', 'simulate.py', + 'ksg.py', ] py3.install_sources( diff --git a/sktree/experimental/mutual_info.py b/sktree/experimental/mutual_info.py index a1820e715..ac5384329 100644 --- a/sktree/experimental/mutual_info.py +++ b/sktree/experimental/mutual_info.py @@ -1,15 +1,5 @@ -from typing import Optional - import numpy as np -import scipy.linalg import scipy.special -import scipy.stats -from numpy.typing import ArrayLike -from sklearn.neighbors import NearestNeighbors -from sklearn.preprocessing import StandardScaler - -from sktree.ensemble import UnsupervisedObliqueRandomForest -from sktree.tree import compute_forest_similarity_matrix def entropy_gaussian(cov): @@ -24,14 +14,8 @@ def entropy_gaussian(cov): Returns ------- - true_mi : float - The true analytical mutual information of the generated multivariate Gaussian distribution. - - Notes - ----- - The analytical solution for the true mutual information, ``I(X; Y)`` is given by:: - - I(X; Y) = H(X) + H(Y) - H(X, Y) = -\\frac{1}{2} log(det(C)) + true_entropy : float + The true entropy of the generated multivariate Gaussian distribution. References ---------- @@ -43,13 +27,17 @@ def entropy_gaussian(cov): return true_entropy -def mi_gaussian(cov): +def mi_gaussian(cov, x_index, y_index): """Compute mutual information of a multivariate Gaussian. Parameters ---------- cov : array-like of shape (d,d) The covariance matrix of the distribution. + x_index : list or int + List of indices in ``cov`` that are for the X variable. + y_index : list or int + List of indices in ``cov`` that are for the Y variable. Returns ------- @@ -62,12 +50,20 @@ def mi_gaussian(cov): H(X) = \\frac{d}{2} (1 + log(2\\pi)) + \\frac{1}{2} log(det(C)) """ + x_index = np.atleast_1d(x_index) + y_index = np.atleast_1d(y_index) + # computes the true MI - true_mi = -0.5 * np.log(np.linalg.det(cov)) + det_x = np.linalg.det(cov[np.ix_(x_index, x_index)]) + det_y = np.linalg.det(cov[np.ix_(y_index, y_index)]) + det_xy = np.linalg.det( + cov[np.ix_(np.concatenate((x_index, y_index)), np.concatenate((x_index, y_index)))] + ) + true_mi = 0.5 * np.log((det_x * det_y) / det_xy) return true_mi -def cmi_gaussian(cov, x_index, y_index, z_index): +def cmi_gaussian(cov, x_index, y_index, z_index=None): """Compute the analytical CMI for a multivariate Gaussian distribution. Parameters @@ -95,22 +91,28 @@ def cmi_gaussian(cov, x_index, y_index, z_index): where we plug in the analytical solutions for entropy as shown in :func:`entropy_gaussian`. """ - x_index = np.atleast_1d(x_index) - y_index = np.atleast_1d(y_index) - z_index = np.atleast_1d(z_index) - - xz_index = np.concatenate((x_index, z_index)).squeeze() - yz_index = np.concatenate((y_index, z_index)).squeeze() - - cov_xz = cov[xz_index, xz_index] - cov_yz = cov[yz_index, yz_index] - cov_z = cov[z_index, z_index] - + x_index = np.atleast_1d(x_index).astype(int) + y_index = np.atleast_1d(y_index).astype(int) + if z_index is None: + z_index = [] + z_index = np.atleast_1d(z_index).astype(int) + + xz_index = np.concatenate((x_index, z_index)) + yz_index = np.concatenate((y_index, z_index)) + + cov_xz = cov[np.ix_(xz_index, xz_index)] + cov_yz = cov[np.ix_(yz_index, yz_index)] + cov_z = cov[np.ix_(z_index, z_index)] + cov_xyz = cov[ + np.ix_( + np.concatenate((x_index, y_index, z_index)), np.concatenate((x_index, y_index, z_index)) + ) + ] cmi = ( entropy_gaussian(cov_xz) + entropy_gaussian(cov_yz) - entropy_gaussian(cov_z) - - entropy_gaussian(cov) + - entropy_gaussian(cov_xyz) ) return cmi @@ -136,312 +138,3 @@ def mi_from_entropy(hx, hy, hxy): def cmi_from_entropy(hxz, hyz, hz, hxyz): """Analytic formula for CMI given plug-in estimates of entropies.""" return hxz + hyz - hz - hxyz - - -def mutual_info_ksg( - X, - Y, - Z=None, - k: float = 0.2, - metric="forest", - algorithm="kd_tree", - n_jobs: int = -1, - transform: str = "rank", - random_seed: int = None, -): - """Compute the generalized (conditional) mutual information KSG estimate. - - Parameters - ---------- - X : ArrayLike of shape (n_samples, n_features_x) - The X covariate space. - Y : ArrayLike of shape (n_samples, n_features_y) - The Y covariate space. - Z : ArrayLike of shape (n_samples, n_features_z), optional - The Z covariate space, by default None. If None, then the MI is computed. - If Z is defined, then the CMI is computed. - k : float, optional - The number of neighbors to use in defining the radius, by default 0.2. - metric : str - Any distance metric accepted by :class:`sklearn.neighbors.NearestNeighbors`. - If 'forest' (default), then uses an - :class:`sktree.UnsupervisedObliqueRandomForest` to compute geodesic distances. - algorithm : str, optional - Method to use, by default 'knn'. Can be ('ball_tree', 'kd_tree', 'brute'). - n_jobs : int, optional - Number of parallel jobs, by default -1. - transform : one of {'rank', 'standardize', 'uniform'} - Preprocessing, by default "rank". - random_seed : int, optional - Random seed, by default None. - - Returns - ------- - val : float - The estimated MI, or CMI value. - - Notes - ----- - Given a dataset with ``n`` samples, the KSG estimator proceeds by: - - 1. For fixed k, get the distance to the kth nearest-nbr in XYZ subspace, call it 'r' - 2. Get the number of NN in XZ subspace within radius 'r' - 3. Get the number of NN in YZ subspace within radius 'r' - 4. Get the number of NN in Z subspace within radius 'r' - 5. Apply analytic solution for KSG estimate - - For MI, the analytical solution is: - - .. math:: - - \\psi(k) - E[(\\psi(n_x) + \\psi(n_y))] + \\psi(n) - - For CMI, the analytical solution is: - - .. math:: - - \\psi(k) - E[(\\psi(n_{xz}) + \\psi(n_{yz}) - \\psi(n_{z}))] - - where :math:`\\psi` is the DiGamma function, and each expectation term - is estimated by taking the sample average. - - Note that the :math:`n_i` terms denote the number of neighbors within - radius 'r' in the subspace of 'i', where 'i' could be for example the - X, Y, XZ, etc. subspaces. This term does not include the sample itself. - """ - rng = np.random.default_rng(random_seed) - - data = np.hstack((X, Y)) - if Z is not None: - data = np.hstack((data, Z)) - - data = _preprocess_data(data, transform, rng) - n_samples = data.shape[0] - - if k < 1: - knn_here = max(1, int(k * n_samples)) - else: - knn_here = max(1, int(k)) - - if Z is not None: - val = _cmi_ksg(data, X, Y, Z, metric, algorithm, knn_here, n_jobs) - else: - val = _mi_ksg(data, X, Y, metric, algorithm, knn_here, n_jobs) - return val - - -def _preprocess_data(data, transform, rng): - n_samples, n_features = data.shape - - # add minor noise to make sure there are no ties - random_noise = rng.random((n_samples, n_features)) - data += 1e-5 * random_noise @ np.std(data, axis=0).reshape(n_features, 1) - - if transform == "standardize": - # standardize with standard scaling - data = data.astype(np.float64) - scaler = StandardScaler() - data = scaler.fit_transform(data) - elif transform == "uniform": - data = _trafo2uniform(data) - elif transform == "rank": - # rank transform each column - data = scipy.stats.rankdata(data, axis=0) - return data - - -def _mi_ksg(data, X, Y, metric, algorithm, knn_here, n_jobs): - """Compute KSG estimate of MI.""" - n_samples = X.shape[0] - - # estimate distance to the kth NN in XYZ subspace for each sample - # - get the radius we want to use per sample as the distance to the kth neighbor - # in the joint distribution space - neigh = _compute_nn(data, algorithm=algorithm, metric=metric, k=knn_here, n_jobs=n_jobs) - dists, _ = neigh.kneighbors() - radius_per_sample = dists[:, -1] - - # compute on the subspace of X - num_nn_x = _compute_radius_nbrs( - X, - radius_per_sample, - knn_here, - algorithm=algorithm, - metric=metric, - n_jobs=n_jobs, - ) - - # compute on the subspace of Y - num_nn_y = _compute_radius_nbrs( - Y, - radius_per_sample, - knn_here, - algorithm=algorithm, - metric=metric, - n_jobs=n_jobs, - ) - - # compute the final MI value - # \\psi(k) - E[(\\psi(n_x) + \\psi(n_y))] + \\psi(n) - hxy = scipy.special.digamma(knn_here) - hx = scipy.special.digamma(num_nn_x) - hy = scipy.special.digamma(num_nn_y) - hn = scipy.special.digamma(n_samples) - val = hxy - (hx + hy).mean() + hn - return val - - -def _cmi_ksg(data, X, Y, Z, metric, algorithm, knn_here, n_jobs): - """Compute KSG estimate of CMI.""" - # estimate distance to the kth NN in XYZ subspace for each sample - neigh = _compute_nn(data, algorithm=algorithm, metric=metric, k=knn_here, n_jobs=n_jobs) - - # get the radius we want to use per sample as the distance to the kth neighbor - # in the joint distribution space - dists, _ = neigh.kneighbors() - radius_per_sample = dists[:, -1] - - # compute on the subspace of XZ - xz_data = np.hstack((X, Z)) - num_nn_xz = _compute_radius_nbrs( - xz_data, - radius_per_sample, - knn_here, - algorithm=algorithm, - metric=metric, - n_jobs=n_jobs, - ) - - # compute on the subspace of YZ - yz_data = np.hstack((Y, Z)) - num_nn_yz = _compute_radius_nbrs( - yz_data, - radius_per_sample, - knn_here, - algorithm=algorithm, - metric=metric, - n_jobs=n_jobs, - ) - - # compute on the subspace of XZ - num_nn_z = _compute_radius_nbrs( - Z, - radius_per_sample, - knn_here, - algorithm=algorithm, - metric=metric, - n_jobs=n_jobs, - ) - - # compute the final CMI value - hxyz = scipy.special.digamma(knn_here) - hxz = scipy.special.digamma(num_nn_xz) - hyz = scipy.special.digamma(num_nn_yz) - hz = scipy.special.digamma(num_nn_z) - val = hxyz - (hxz + hyz - hz).mean() - return val - - -def _compute_radius_nbrs( - data, - radius_per_sample, - k, - algorithm: str = "kd_tree", - metric="l2", - n_jobs: Optional[int] = None, -): - neigh = _compute_nn(data, algorithm=algorithm, metric=metric, k=k, n_jobs=n_jobs) - - n_samples = radius_per_sample.shape[0] - - num_nn_data = np.zeros((n_samples,)) - for idx in range(n_samples): - nn = neigh.radius_neighbors(radius=radius_per_sample[idx], return_distance=False) - num_nn_data[idx] = len(nn) - return num_nn_data - - -def _compute_nn( - X: ArrayLike, algorithm: str = "kd_tree", metric="l2", k: int = 1, n_jobs: Optional[int] = None -) -> NearestNeighbors: - """Compute kNN in subspace. - - Parameters - ---------- - X : ArrayLike of shape (n_samples, n_features) - The covariate space. - algorithm : str, optional - Method to use, by default 'knn'. Can be ('ball_tree', 'kd_tree', 'brute'). - metric : str - Any distance metric accepted by :class:`sklearn.neighbors.NearestNeighbors`. - If 'forest', then uses an :class:`sktree.UnsupervisedObliqueRandomForest` - to compute geodesic distances. - k : int, optional - The number of k-nearest neighbors to query, by default 1. - n_jobs : int, - The number of CPUs to use for joblib. By default, None. - - Returns - ------- - neigh : instance of sklearn.neighbors.NearestNeighbor - A fitted instance of the nearest-neighbor algorithm on ``X`` input. - - Notes - ----- - Can query for the following, using the ``neigh.kneighbors(X)`` function, which would - return: - - dists : ArrayLike of shape (n_samples, k) - The distance array of every sample with its k-nearest neighbors. The columns - are ordered from closest to furthest neighbors. - indices : ArrayLike of shape (n_samples, k) - The sample indices of the k-nearest-neighbors for each sample. These - contain the row indices of ``X`` for each sample. The columns - are ordered from closest to furthest neighbors. - """ - if metric == "forest": - est = UnsupervisedObliqueRandomForest() - dists = compute_forest_similarity_matrix(est, X) - - # we have a precomputed distance matrix, so we can use the NearestNeighbor - # implementation of sklearn - metric = "precomputed" - else: - dists = X - - # compute the nearest neighbors in the space using specified NN algorithm - # then get the K nearest nbrs and their distances - neigh = NearestNeighbors(n_neighbors=k, algorithm=algorithm, metric=metric, n_jobs=n_jobs).fit( - dists - ) - return neigh - - -def _trafo2uniform(X): - """Transforms input array to uniform marginals. - - Assumes x.shape = (dim, T) - - Parameters - ---------- - X : arraylike - The input data with (n_samples,) rows and (n_features,) columns. - - Returns - ------- - u : array-like - array with uniform marginals. - """ - - def trafo(xi): - xisorted = np.sort(xi) - yi = np.linspace(1.0 / len(xi), 1, len(xi)) - return np.interp(xi, xisorted, yi) - - _, n_features = X.shape - - # apply a uniform transformation for each feature - for idx in range(n_features): - marginalized_feature = trafo(X[:, idx].to_numpy().squeeze()) - X[:, idx] = marginalized_feature - return X diff --git a/sktree/experimental/simulate.py b/sktree/experimental/simulate.py index 17b56145f..56146b16c 100644 --- a/sktree/experimental/simulate.py +++ b/sktree/experimental/simulate.py @@ -221,3 +221,16 @@ def simulate_multivariate_gaussian(mean=None, cov=None, d=2, n_samples=1000, see data = rng.multivariate_normal(mean=mean, cov=cov, size=(n_samples)) return data, mean, cov + + +def embed_high_dims(data, n_dims=50, random_state=None): + rng = np.random.default_rng(random_state) + + new_data = np.zeros((data.shape[0], n_dims + data.shape[1])) + new_data[:, :data.shape[1]] = data + + for idim in range(n_dims): + new_col = rng.standard_normal(size=(data.shape[0],)) + new_data[:, data.shape[1] + idim] = new_col + + return new_data \ No newline at end of file diff --git a/sktree/neighbors.py b/sktree/neighbors.py index 1d6e1ed84..653e7ff97 100644 --- a/sktree/neighbors.py +++ b/sktree/neighbors.py @@ -38,7 +38,7 @@ def __init__(self, estimator, n_neighbors=5, radius=1.0, algorithm="auto", n_job self.radius = radius self.n_jobs = n_jobs - def fit(self, X, y=None): + def fit(self, X, y=None, force_fit=False): """Fit the nearest neighbors estimator from the training dataset. Parameters @@ -56,13 +56,19 @@ def fit(self, X, y=None): self : object Fitted estimator. """ - X, y = self._validate_data(X, y, accept_sparse="csc") + if y is not None: + X, y = self._validate_data(X, y, accept_sparse="csc") + else: + X = self._validate_data(X, accept_sparse="csc") self.estimator_ = copy(self.estimator) - try: - check_is_fitted(self.estimator_) - except NotFittedError: + if force_fit: self.estimator_.fit(X, y) + else: + try: + check_is_fitted(self.estimator_) + except NotFittedError: + self.estimator_.fit(X, y) self._fit(X, self.n_neighbors) return self