From 3f43f7ef948195af38bb3ab3b1f758a25ceac719 Mon Sep 17 00:00:00 2001 From: rchan Date: Fri, 24 Nov 2023 14:41:29 +0000 Subject: [PATCH] add esig opt dependency and cdf plotting --- paper-examples/examples.ipynb | 665 +++++++++++++------------ pyproject.toml | 3 + src/signature_mahalanobis_knn/utils.py | 88 +++- 3 files changed, 447 insertions(+), 309 deletions(-) diff --git a/paper-examples/examples.ipynb b/paper-examples/examples.ipynb index fb07e98..03bec6c 100644 --- a/paper-examples/examples.ipynb +++ b/paper-examples/examples.ipynb @@ -7,40 +7,24 @@ "metadata": {}, "outputs": [], "source": [ - "import sys\n", - "import os\n", - "\n", - "sys.path.insert(0, os.path.join(\"..\", \"..\"))\n", "import random\n", "import time\n", "\n", - "import sklearn\n", "import numpy as np\n", - "import matplotlib.lines as mlines\n", "import matplotlib.pyplot as plt\n", - "import pandas as pd\n", "\n", "import Data\n", "from signature_mahalanobis_knn import SignatureMahalanobisKNN\n", - "from signature_mahalanobis_knn.utils import compute_auc_given_dists\n", + "from signature_mahalanobis_knn.utils import (\n", + " compute_auc_given_dists,\n", + " plot_cdf_given_dists,\n", + ")\n", "import UCR_data_support" ] }, { "cell_type": "code", "execution_count": 2, - "id": "34fc097e-0eb5-4c0d-9973-4dc8810ec398", - "metadata": {}, - "outputs": [], - "source": [ - "DATA_DIR = \"/Users/zoos/PycharmProjects/Anomaly_detection/data/\"\n", - "# importlib.reload(Data)\n", - "# importlib.reload(SigMahaKNN)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -57,7 +41,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "id": "b7a56abc", "metadata": {}, "outputs": [], @@ -67,7 +51,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "1dd07d56-fd79-4918-b9f8-db9190a837d9", "metadata": {}, "outputs": [], @@ -82,7 +66,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "id": "a9b82cb0-4754-409c-891b-b19ec7e9b1a3", "metadata": {}, "outputs": [ @@ -94,21 +78,21 @@ "len(data.corpus) 780\n", "len(data.test_inlier) 363\n", "len(data.test_outlier) 3135\n", - "fit_time: 10.063539028167725\n", - "compute_auc_time: 9.991588115692139\n", + "fit_time: 9.688912153244019\n", + "compute_auc_time: 10.269761800765991\n", "depth: 1 , Auc of digit: 0 is 0.9236207222288126\n", "doing digit 1 doing signature level 1\n", "len(data.corpus) 779\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.3015568256378174\n" + "fit_time: 1.2819938659667969\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n" ] }, @@ -116,20 +100,20 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 6.059915065765381\n", + "compute_auc_time: 6.245326042175293\n", "depth: 1 , Auc of digit: 1 is 0.8300113256239612\n", "doing digit 2 doing signature level 1\n", "len(data.corpus) 780\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.3631317615509033\n" + "fit_time: 1.3130040168762207\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n" ] }, @@ -137,27 +121,27 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 6.2524518966674805\n", + "compute_auc_time: 6.352444171905518\n", "depth: 1 , Auc of digit: 2 is 0.9320072476980582\n", "doing digit 3 doing signature level 1\n", "len(data.corpus) 719\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.3106367588043213\n", - "compute_auc_time: 5.999101161956787\n", + "fit_time: 1.315458059310913\n", + "compute_auc_time: 6.223802804946899\n", "depth: 1 , Auc of digit: 3 is 0.922022303545074\n", "doing digit 4 doing signature level 1\n", "len(data.corpus) 780\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.4209661483764648\n" + "fit_time: 1.4521958827972412\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n" ] }, @@ -165,20 +149,20 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 5.9232141971588135\n", + "compute_auc_time: 6.100835084915161\n", "depth: 1 , Auc of digit: 4 is 0.9830396151391684\n", "doing digit 5 doing signature level 1\n", "len(data.corpus) 720\n", "len(data.test_inlier) 335\n", "len(data.test_outlier) 3163\n", - "fit_time: 1.2171669006347656\n" + "fit_time: 1.3075149059295654\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n" ] }, @@ -186,20 +170,20 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 5.923392057418823\n", + "compute_auc_time: 6.035906076431274\n", "depth: 1 , Auc of digit: 5 is 0.9057290216637331\n", "doing digit 6 doing signature level 1\n", "len(data.corpus) 720\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.161789894104004\n" + "fit_time: 1.3131701946258545\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n" ] }, @@ -207,34 +191,44 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 5.955906867980957\n", + "compute_auc_time: 6.04359769821167\n", "depth: 1 , Auc of digit: 6 is 0.8962102986355833\n", "doing digit 7 doing signature level 1\n", "len(data.corpus) 778\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.4109997749328613\n", - "compute_auc_time: 5.941327095031738\n", + "fit_time: 1.364300012588501\n", + "compute_auc_time: 6.059554100036621\n", "depth: 1 , Auc of digit: 7 is 0.8957924255068479\n", "doing digit 8 doing signature level 1\n", "len(data.corpus) 719\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.2382440567016602\n", - "compute_auc_time: 5.920679092407227\n", + "fit_time: 1.1893792152404785\n", + "compute_auc_time: 6.056625843048096\n", "depth: 1 , Auc of digit: 8 is 0.9399820412035783\n", "doing digit 9 doing signature level 1\n", "len(data.corpus) 719\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.2690927982330322\n", - "compute_auc_time: 5.920597791671753\n", + "fit_time: 1.2779922485351562\n", + "compute_auc_time: 6.125757932662964\n", "depth: 1 , Auc of digit: 9 is 0.8178161049365983\n" ] }, { "data": { - "image/png": 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", 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O8SVKlNDWLiaWlnPs27cPb9++xbhx45IMNkhpNEti+r4/GjdujIoVK37wvHny5MHJkyfx5MmTD+77Ic+fP8e///6Lvn37olixYjrXpeU+AoCvry+cnJzg7OyMJk2a4M6dO5g9ezY6duyI8+fP49atW+jevTtevnypfQwiIiLQvHlz/Pvvv0lGc6XlNZAe8TUb8e/95OzduxcuLi749NNPtWU2Njbo379/hm47OS9fvgSAJO+n+M+R4cOH65S/X7uTns/HXr166bwnO3XqhMKFC2tvMy0+9NkRfzv79u374N/69evTfLvJiX/ssuO0G2waM5LFixejbNmyCA0NxapVq/Dvv//C2tpae/3t27chhMCkSZMwadKkZM/x7NkzuLi44M6dO/jss89Svb1bt27h2rVrcHJySvFcKalWrRrKly+PgIAA9OvXD4BsFitQoID2i+L58+d48+YNli1bhmXLlqXpNkqUKJFqzPHiPwzevn2LPHnyJLtPSslSmTJlkuxbtmxZbN68GYB+j3NqcUdGRsLPzw+rV6/G48ePdYbzv/+Fr6/3v/TiP1Bev34NALh//z4AoHTp0jr7WVhYpGnulPhq6tS+dPSNK/6cx44dg6+vL44fP56k+j00NBSOjo7a7ZReD2k5R3wTT+XKlfW6D/H0fX+k9bX7/fffw8fHB66urvDw8EDr1q3Rq1cvlCxZUu8Y47+80nsfAWDAgAHo3LkzzMzMkCdPHlSqVEn7uXPr1i0ASNIEnlhoaKhOMpCW10B6xM/Tk1pyfv/+fZQqVSpJEvj++8CQEr+v42MwMzNLMhIqvlk3Xno+H9//7FKpVChdurReU2986LMDAEqWLJmu16O+4h+7tCbtWQkTISOpVasWatSoAUDWWjRo0ADdu3fHjRs3kDt3bu0vr9GjRyf7KxnQ7w2v0WhQpUoVzJs3L9nrXV1dUz3e29sbM2bMwIsXL2Bvb4+dO3eiW7du2hqI+Hg///zzFD9I32+DT0ttECD70OzYsQMXL15Eo0aNkt3n4sWLAJCmX+mJpedxTi7uYcOGYfXq1fjqq69Qt25dODo6QqVSoWvXrhmeEyWlKQHe/1BOr/LlywMALl26pNcQ6g/FdefOHTRv3hzly5fHvHnz4OrqCisrK+zZswfz589P8rgk97jqe4700vf9kdbXbpcuXdCwYUP89ttv+PvvvzFnzhzMnj0b27dvR6tWrTIct77KlCmj04cusfjHcs6cOSm+Dt7vg2Ks12b85HvGTGr0Ed+H6vXr1+maQiI9n4+GkJbnJzw8PE0TRJqbm6f4QyEt4pOvAgUKpPscSmEilAnMzc3h5+eHpk2bYtGiRRg3bpw2Q7e0tEzxgyteqVKlPjhrZ6lSpXDhwgU0b948XRm5t7c3pk6dim3btqFQoUIICwtD165dtdc7OTnB3t4earX6g/Hq65NPPoGfnx/WrFmTbCKkVquxYcMG5M2bF/Xr19e5Lv5XbmI3b97U1pTo8zinZuvWrfDx8cHcuXO1ZVFRUXjz5o3Ofsb4NVS8eHEAsnaradOm2vK4uDgEBQV98AO2VatWMDc3x7p16/TuMJ2aXbt2ITo6Gjt37tT5ZfqhzqzpOUf8L/LLly+n+uWZ0uOf0fdHagoXLozBgwdj8ODBePbsGapXr44ZM2ZoE6G03l78a9VYM/TGP4YODg4Gfw/ra+3atVCpVPj4449T3Kd48eK4evUqhBA6j+Ht27c/eH59n+P4Hwv37t1DlSpVdGLQaDS4c+eOTi3QjRs3dI5Pz+fj+59dQgjcvn1b5/1siNfqDz/8oJ1TKTXFixfP0ESw9+7dg5mZWYqd37My9hHKJE2aNEGtWrWwYMECREVFoWDBgmjSpAmWLl2Kp0+fJtn/+fPn2sufffYZLly4gN9++y3JfvGZf5cuXfD48WMsX748yT6RkZHa0U8pqVChAqpUqYKAgAAEBASgcOHCOkmJubk5PvvsM2zbti3ZD+rE8eqrXr168PT0xOrVq/HHH38kuX7ixIm4efMmvvnmmyS/1Hfs2KHTx+fUqVM4efKk9ktIn8c5Nebm5kl+Bf/0009Qq9U6Zbly5QKAJAlSRtSoUQP58+fH8uXLERcXpy1fv369ThV4SlxdXdG/f3/8/fff+Omnn5Jcr9FoMHfuXDx69EivuOJ/jb7fTLh69WqDn6NFixawt7eHn58foqKidK5LfGyuXLmSbarM6PsjOWq1OsltFSxYEEWKFEF0dPQHY3qfk5MTGjVqhFWrVuHBgwc61xmidtDDwwOlSpXCDz/8kGwNQUbew/qYNWsW/v77b3h7eyfbtB3Py8sLjx8/xs6dO7VlUVFRyT6H77OzswOQ9vehh4cHrKysksywHv858uOPP+qUvz/bc3o+H+NHvMbbunUrnj59qlOTmNbXTmoyq49QYGAgKlWqpNMcnl2wRigTjRkzBp07d4a/vz8GDhyIxYsXo0GDBqhSpQr69++PkiVLIiQkBMePH8ejR49w4cIF7XFbt25F586d0bdvX3h4eODVq1fYuXMnlixZgmrVqqFnz57YvHkzBg4ciEOHDqF+/fpQq9W4fv06Nm/ejL/++kvbVJcSb29vTJ48GTY2NujXr1+S2adnzZqFQ4cOoXbt2ujfvz8qVqyIV69e4ezZs9i/fz9evXqV7sdmzZo1aN68Odq1a4fu3bujYcOGiI6Oxvbt23H48GF4e3tjzJgxSY4rXbo0GjRogEGDBiE6OhoLFixA/vz58c0332j3SevjnJpPPvkEa9euhaOjIypWrIjjx49j//792ir1eO7u7jA3N8fs2bMRGhoKa2trNGvWDAULFkz3Y2NlZYUpU6Zg2LBhaNasGbp06YKgoCD4+/sn24ciOXPnzsWdO3cwfPhwbN++HZ988gny5s2LBw8eYMuWLbh+/bpODWBatGjRAlZWVmjbti2+/PJLhIeHY/ny5ShYsGCySWdGzuHg4ID58+fjiy++QM2aNdG9e3fkzZsXFy5cwLt37/Drr78CkF9oAQEBGDVqFGrWrIncuXOjbdu2Bnl/vO/t27coWrQoOnXqhGrVqiF37tzYv38/Tp8+rVNzmFJMyfnxxx/RoEEDVK9eHQMGDECJEiUQFBSE3bt3Z3ipDDMzM6xYsQKtWrVCpUqV0KdPH7i4uODx48c4dOgQHBwctFNZGEJcXBzWrVsHQCYw9+/fx86dO3Hx4kU0bdo0xb408b788kssWrQI3bp1w4gRI1C4cGGsX79e21k+tde9ra0tKlasiICAAJQtWxb58uVD5cqVU+x/ZWNjgxYtWmD//v2YNm2attzd3R3dunXDzz//jNDQUNSrVw8HDhxItlZK38/HfPnyoUGDBujTpw9CQkKwYMEClC5dWqczuD6vnZSkt4/Q/fv3sXbtWgDQJojfffcdAFl7lLh2OTY2Fv/88w8GDx6s9+1kCZk6Rs0EpDShohByhtpSpUqJUqVKaYdn37lzR/Tq1Us4OzsLS0tL4eLiIj755BOxdetWnWNfvnwphg4dKlxcXLSTwfn4+OgM1YyJiRGzZ88WlSpVEtbW1iJv3rzCw8NDTJ06VYSGhmr3e3/4fLxbt25ph1K+P8FavJCQEDFkyBDh6uoqLC0thbOzs2jevLlYtmyZdp/0znr69u1bMWXKFFGpUiVha2sr7O3tRf369YW/v3+S4cOJJ5CbO3eucHV1FdbW1qJhw4biwoULSc6dlsc5tefu9evXok+fPtpJ1by8vMT169eTfSyXL18uSpYsKczNzdM0oeL7j1NKE+39+OOPonjx4sLa2lrUqlVLHDt2THh4eIiWLVum4dGVM0ivWLFCNGzYUDg6OgpLS0tRvHhx0adPH52h9SnNLB3/+CSeRHLnzp2iatWqwsbGRri5uYnZs2eLVatWJdkvfkLF5KT1HPH71qtXT9ja2goHBwdRq1YtsXHjRu314eHhonv37iJPnjxJhgSn9f2B/0+omBwkGjIdHR0txowZI6pVqybs7e1Frly5RLVq1ZJMBplSTCk9z5cvXxYdOnQQefLkETY2NqJcuXIfnLE3pQkVk3Pu3DnRsWNHkT9/fmFtbS2KFy8uunTpIg4cOKDdR5/XQHJ8fHx0hmbb2dkJNzc38dlnn4mtW7cmO8t8chMq3r17V7Rp00bY2toKJycn8fXXX4tt27YJAOLEiRM6t/f+8O///vtPeHh4CCsrqzQNpd++fbtQqVQ6kxoKIYfsDx8+XOTPn1/kypUr1QkV9fl83Lhxoxg/frwoWLCgsLW1FW3atEkybUJKrx19PzvSI/42kvt7/3n6888/Bf4/AWd2pBIim6xmSZRIUFAQSpQogTlz5mD06NFKh6MIjUYDJycndOzYMU3NBUQ5wYIFCzBy5Eg8evRIZ7RnRqnValSsWBFdunTB9OnTDXbe9x0+fBhNmzbFli1b0KlTJ6PdTmZq3749VCpVst03sgP2ESLKBqKiopL0E1mzZg1evXqV5kUlibKbyMhIne2oqCgsXboUZcqUMWgSBMh+PtOmTcPixYvTNMqKpGvXruGPP/4wavJobOwjRJQNnDhxAiNHjkTnzp2RP39+nD17FitXrkTlypXRuXNnpcMjMoqOHTuiWLFicHd3R2hoKNatW4fr169nuGNvSry9vbWTyFLaVKhQQWcQR3bERIgoG3Bzc4Orqyt+/PFHvHr1Cvny5UOvXr0wa9asFNdwI8ruvLy8sGLFCqxfv17bdLVp0yYmK2RQivYR+vfffzFnzhwEBgbi6dOn+O2339C+fftUjzl8+DBGjRqFK1euwNXVFd9++y169+6dKfESERFRzqJoH6GIiAhUq1YNixcvTtP+9+7dQ5s2bdC0aVOcP38eX331Fb744gv89ddfRo6UiIiIcqIsM2osvsd5ajVCY8eOxe7du3UmrOratSvevHmDvXv3ZkKURERElJNkqz5Cx48fTzJ9uZeXV5KVgBOLjo7WmeVVo9Hg1atXyJ8/f7ZcHI6IiMgUCSHw9u1bFClSJMmEvxmRrRKh4OBgFCpUSKcsfl2syMjIZBdK9PPzS9M6K0RERJT1PXz4MF2L46YkWyVC6TF+/HiMGjVKux0aGopixYrh4cOHcHBwUDAyIiIiZQgBvHwJhIYCV68Cb94A794BFy4At24B168DYWGZH1fRosCjR0CrVsCzoAgULZsLb94A7u5AXFwYFi92hb29vUFvM1slQs7OzggJCdEpCwkJgYODQ7K1QQBgbW0Na2vrJOUODg5MhIiIKEeKiZGJzMOHwIMHwOvXwKFDwJo1xrvN3LmB2FggOhqwtQUKFwYqVAA+/hiIipKXra2BggWBAgXkZRsbIFcu4P/rLyfYsQPo3x9Yuh1o2BCAvD+LF6e+zlx6ZKtEqG7dutizZ49O2b59+1C3bl2FIiIiIlLOnTvAL78AR44AFy/KhMPQzM1l8pIrF9C8uUx0WrQAVCpZg1OkCFCihNzOsOho4JtvgB9/lNvdugHnz8vMyUgUTYTCw8N1VvG9d+8ezp8/j3z58qFYsWIYP348Hj9+jDX/T2EHDhyIRYsW4ZtvvkHfvn1x8OBBbN68Gbt371bqLhARERmNWg3cvg2EhADHj8smK39/oFgxWdOTUcWLAy1bAk+eyOYoJydZXqECULYsYGmZ8dtIszt3AG9vIDAwoaxuXaMHoWgidObMGTRt2lS7Hd+Xx8fHB/7+/nj69CkeJHqmS5Qogd27d2PkyJFYuHAhihYtihUrVsDLyyvTYyciIsqIuDjg2TPg6VMgKEg2/ezYIROc8+cBe3vg7dvkj01LEmRjI5Obly+BmjWBMmWA/PkBT08gTx7D3Q+D2LIF+OKLhI5J1tbA/PnAwIEGqmpKWZaZRyizhIWFwdHREaGhoewjREREBhcRAdy7J/vnPHkC3LghE5r794HTp4EXLwx7e9bWsjWpVy/AzQ2wyE6dXqKigFGjZPtevDJlgM2bZQ/pRIz1/Z2dHi4iIqIsITpa1ubcuiVHXJ05A/j5Gee26tYFrl0DRoyQ282aAdWqAY6Oxrm9THPrFtCli6z+ite9O7BkiawOyyRMhIiIiBJRq2Vz0suXstvK/v3Avn3AzZuyOcuQihWTo6tcXWWH5Hr1ZLNVrVqyf3COnvc3JkZWlwGyHe+nn4B+/TL9TjMRIiIik6HRAM+fyz45V67IROfvv+V37+nThrsdJyfZsuPmBlSsCOTNC5QuDTg7y1FWKcz4YloqVQIWLQLmzJFNYVWqKBIG+wgREVGOEhUlBx5duyaTm8uXgf/+M+xtODnJ5rEaNWQS9emncnBTo0by+52SceuWrAJLPLefEPKBtLH54OHsI0RERPSet2/lsPJDh2RfnSVLDHPe6tVl01ibNvI2atQA2rWT3+M5urnKWNasAQYNkiPDFi5MKFep0pQEGRMTISIiyhbevAFWrgQCAjLWjGVpCTRtKoeSOzvL/jjlysmaHCsrg4VLgBxCN3SonPwIkBMltmwpx/VnEUyEiIgoy4iJAS5dkvPp7NghJ/xL75y5/fvLjsju7vLP1TWbDS3P7i5flqPCrl1LKPviC6BxY+ViSgZfEkRElGk0Gjn66vJl4MAB4NgxmZycO5f8/pcvf/icDg5ywsCWLYEGDWTNTiaOvqb3CQGsWiVrguLX/MidG1i6VA6Pz2KYCBERUYYJIScKDAoCTpyQU8OcPi1bRjQaWa5Syf0yonhxObjou+9kwsManizm7VvZF2j9+oSyatXkqLCyZZWLKxV8CRERUZrFxABXrwKPHslOypcuAbt2pe3YtCZBBQrIxTw7dpS1PBUqyAU/2Uk5i3v4UK7fcfNmQtnAgXKpDIU7RKeGiRAREWmp1cA//8hanStXgJMngfBwuehnRjk4yKWk6tWTI7I8PYHy5eVorCJF5CrnlI05O8ss9uZN2Ta5YoXsI5TFMREiIjJB4eFyUt9r14Avv5QJydmzGT9v6dJySYgSJWTCU7687LDM0VgmwNIS2LRJdoj++WegVCmlI0oTJkJERDmQRiNnTf7zT+DUKdkZ+c4d2acmIiLp/mlNgtzdZf8fT0+gdm05sWCtWnKeHUtLQ94DyvICA2U1XuLFUV1dgb/+Uiyk9GAiRESUQwQFAZMnA2vXprxPdHTazuXpKZusypaViY6jI/vo0P8JIZfGGD1aJj5nz8p2z2yKiRARUTby5o3srHzypPx78UIOQ0+PPHmAOnVkU1bTpnLoOZMdStXr13Jh1N9+k9t37si1wqZPVzauDGAiRESUhcTEyHWxTp+W/XdevJDLR4SHp+987u4ywfn0U6BqVbnCOZMdSpdTpwBvb1n1GG/UKGDSJMVCMgQmQkRECggPBy5eBA4eBI4eBfbtk/16DOGnn4DPP5c1PkQZJoQcAj92LBAXJ8vy5gV+/RVo21bZ2AyAiRARkZG8fg3s2SO7UNy6JefbyZcPePUqY+ctV052Ti5fHvDwkBMLurhw+DkZwcuXQO/ewB9/JJTVqwds3ChXoM0BmAgREWXAw4eyVufatYTJdB89Snn/tCZBbdvKUVnxiU6hQhyCTpksOlq+CO/cSSgbO1b2B8pBQwSZCBERvUcIOYHgtWtAaKhc7+rhQ5mI/POP7Lfz9GnGbqNkSTm/Ttmysu9OvXoy4cmVyzD3gSjDrK3lemEjR8qJEteulVN95zBMhIjIJMXFAdevAxcuyMTm+nXZTyfxj19DKFVKJj0+PnKpiEqV5PcLUbYwYoQcqti/v2x/zYGYCBFRjqdWA9u2ydqcn382zm3Mni0TnnLlZLJjZmac2yEymn//Bc6ckSPB4qlUwJQpioWUGZgIEVGOoFbLDslXrgC3bwN79wKHD2fsnPXrA1FRQNeusktEyZJy9fM8eeSySuyzQzmCWg34+QG+vrJduEoV4OOPlY4q0zARIqJs5eVLwN9f9t85eFD23Ykf0ZserVrJBKd+fdkNolgxoEwZ1uiQiQgJkXMt7N+fULZyJRMhIiIlCZEwg/L167LGfvdumQRlROPGclLcOnVkskNk0g4eBLp3l8kQILN/X19g4kRl48pkTISISFHv3snh5idOADNmADdvpv9c1tayf06dOnLUb9mycvh5DhrpS5RxajUwbZocBi+ELCtcGNiwAWjSRNHQlMBEiIiMTgjg3j1Zu3P8uFym6MqV9J/P0RH45BNgyBCgRAk5xw6XjSBKgydPgB49dDvQtWghh8YXLKhYWEpiIkREGRIZCdy9Kz9XAwPlzPsBAcDjx/J6c3P5AzQ9SpQAKleWP1JdXWUtTw6ZzJZIGX37JiRB5uayVmjsWJPuFMdEiIg+SKOR/XPu3pWTC/7xB3DpUtrm3ElLElSyJJA/P+DlJedrq1vXpD+XiYznp5+A6tVlteqmTXJFXhPHRIiIEBEhR2E9fSr76AQHy6UgVq0yzPlVKrkK+uPHcvFqFxegY0egdGk2aREZlRC6b7IyZeSid5Ury2GSxESIyFSo1XKV8wcP5JpYgYHA27dyOSFDaNJE/tBs2lQ2XxUpws9ZIkXt2QPMmSOHXNrZJZSbYIfo1DARIsqBXr0CLl4Eli2Ti0QbgpmZHIXVuDHg4AA0awZUqyYHmxBRFhIbK4fAz5kjt0eMAJYvVzamLIyJEFE29uKF7LOzZQtw8qSs5UmvkiVlTU6bNrIm3c1NlpUty4VAibKN+/flVOgnTiSUPX8OxMRwKvQUMBEiyibUauD8edlvZ9u2hDnQ9FGoEFC0KDBwoKzJadBA9pkkohzg99+BPn2A16/ltqWlrBUaPpyd8VLBRIgoixFCdli+dAk4dEjWaMfG6n8ed3eZ9HTtKkdi5c9v8FCJKCuIiQG++QZYuDChrEQJOY9FzZrKxZVNMBEiUlBUFLB1q+zLc+WK7NuTHiNGyMVAO3WSyQ9//BGZiLt35VDMM2cSyj77DFixQq4OTB/ERIgok7x4AZw7B6xbB6xZA1hYpG+x0MaNZT+eAQPYrEVk8jZvTkiCrKyA+fOBQYP4a0gPTISIDOzGDVlDffo0EBQkE6DkfCgJsreXNT2lS8sV0k109nsiSs2YMXLl+Pv3ZVL00UdKR5TtMBEiyqBXr4BTp+QK6X5++h/v7i6btb79Vn6GmZsbPEQiyinevpW/kuKZm8s5Mqyt5bwWpDcmQkR6EAI4e1b+APvpp4T1tNLC2lrW6lSsCLRrB3TvzqYtItLDpk3A4MFyjZt69RLKnZyUiykHYCJElIqYGODIEWDlSv0nJvz5Z9mXx8WFtTxElAGRkcBXX8lRFYAcCnruHIeCGggTIaL/02jkCNRjx3TnIkurzz8HPDyA9u3lZIRERBl2/TrQpYucTyNekyayipkMgokQmRwhZEfmY8dkTXNgYNpWSE/M0RGYNk1+HlWuzJXSicgI1q6VI8AiIuS2rS2weDHQuzdHhRkQEyHK0TQa4N074NYtOSPzokX6n6NgQaB2bTlHT7t27NdDREYWEQEMGwasXp1QVrGiXEunYkXl4sqhmAhRjhEbK1dVX7cOOHAgfecwNweqVJETspYsKef6ISLKNFevAp07y//x+vaVozMSryBPBsOPecq2hJDD1r/6Kn19eqpVkyO3WrSQzVtMeohIcWq1nC0akKsdL1kiOyCS0fCjn7KV0FDA11d3SZ0PyZcPqFtXTr/x8ceyyZ2DLYgoS6pSBfjxR9mOv3kzUK6c0hHleCohhFA6iMwUFhYGR0dHhIaGwoGTT2V58QuQurvLdbnSoksXubp6o0Yctk5EWdzVq3L6eCurhDIh5NwdHBmmw1jf3xzrQllKXJzs2LxihUxkzMyA8uVTT4KsreVAipgY+fkREAA0bcokiIiyMCGApUuB6tWB8eN1r1OpmARlIjaNkeKePpVD0ZcsSdv+uXMDX3wBTJjACVWJKBsKCwP695dNXwAwb55cUNDTU9m4TBQTIcp0ERFy9fXly+XkqGmhUsn9+/UzbmxEREZ19qxsv79zJ6Fs2DCgYUPlYjJxTIQoU5w+DYwcKScxTIuWLYFixYDPPpOTFiZuPiciynaEkG34X38t2/EBOSnZqlVAx47KxmbimAiRUdy7J3/k7N6d9mNWrgR69GDTOBHlMG/eyOrs7dsTymrWlB0aS5RQLCySmAiRQbx6BYwYIQdAnD2btmP69ZPzhNWty9niiSiHuncPaN5c/o83ciQwaxarurMIJkKUIc+eAWXKyL5/qbG2BqKjgW3b5KKkXJuLiExC0aJAoUIyEcqbF/D3Bz79VOmoKBF+HVG63Lkja3EKFUo9CfLzk0tfREXJJvKOHZkEEZEJsbSUqzu3bi1HhzAJynL4lURpcu2aTGJKlJAJUOnSye/n6ws8fiyTHiGAceO4dAURmZD//gMuXNAtK15cdpgsXlyZmChV/IqiFEVFAcuWyb4/HzJzpkx62NeHiEySRgP88IOc4KxkSSAwELC3VzoqSgPWCJGOhw+B3r1lQmNr++EkaM4cWfMzfjyTICIyUc+fA598AowdKxdNvXVLvwURSVGsESIEBsqFSE+f/vC+y5cDPj6y2ZuIyOQdOQJ07Qo8eSK3VSpg4kRZRU7ZAhMhE6TRADt2yMkK06JFC+Cnn4CyZY0aFhFR9qHRyNEgkyfLywBQsCCwbh3w8cfKxkZ6YSJkImJjgZ07gU6d0rb/zJnA6NGs+SEiSiIkBOjZE9i3L6GsaVNg/XqgcGHl4qJ0YSKUg717J5eqOHLkw/uWLw/MmAF06MC+PkREKYqMBGrVAh48kNtmZnK47MSJgLm5srFRuijeWXrx4sVwc3ODjY0NateujVOnTqW6/4IFC1CuXDnY2trC1dUVI0eORFRUVCZFm320awfkypV6EuTqKkd5CpEwPJ5JEBFRKmxtgeHD5WVnZ+DAAdk8xiQo21K0RiggIACjRo3CkiVLULt2bSxYsABeXl64ceMGChYsmGT/DRs2YNy4cVi1ahXq1auHmzdvonfv3lCpVJg3b54C9yDriY1Nfdb21q3le7Z27cyLiYgoRxk5EoiIAAYOlP2CKFtTCSGEUjdeu3Zt1KxZE4sWLQIAaDQauLq6YtiwYRiXTI/7oUOH4tq1azhw4IC27Ouvv8bJkydx9OjRNN1mWFgYHB0dERoaCgcHB8PckSxAo5FLV+zalfS6kSOBuXNZ20NEpLd9+4DLl+UHKSnKWN/fijWNxcTEIDAwEJ6engnBmJnB09MTx48fT/aYevXqITAwUNt8dvfuXezZswetW7dO8Xaio6MRFham85eTxMbKubvMzZNPgp48AebNYxJERKSXuDjZ78fLC/j6a+DgQaUjIiNRLBF68eIF1Go1ChUqpFNeqFAhBAcHJ3tM9+7dMW3aNDRo0ACWlpYoVaoUmjRpggkTJqR4O35+fnB0dNT+ubq6GvR+KKlXL9kMlnhR48SE4AAGIiK9PXoENGsmh8/Grxe0bp3SUZGRKN5ZWh+HDx/GzJkz8fPPP+Ps2bPYvn07du/ejenTp6d4zPjx4xEaGqr9e/jwYSZGbBzxszivXZv0ukqV5MSmyjV4EhFlY3v2AO7uCSNNzM2B778HVqxQNCwyHsU6SxcoUADm5uYICQnRKQ8JCYGzs3Oyx0yaNAk9e/bEF198AQCoUqUKIiIiMGDAAEycOBFmySxrbm1tDWtra8PfgUwWHCybqDdtSv56d3fg7Fk2gRERpUtsrGwKmzMnoaxYMfmhW7eucnGR0SlWI2RlZQUPDw+djs8ajQYHDhxA3RRedO/evUuS7Jj/f8iign2+jW7+fNnElVIS9O4dcO4ckyAionS5fx9o1Eg3Cfr0U/nByiQox1N0+PyoUaPg4+ODGjVqoFatWliwYAEiIiLQp08fAECvXr3g4uICPz8/AEDbtm0xb948fPTRR6hduzZu376NSZMmoW3bttqEKCc5cABI1Jc8iZAQjtwkIsqw3r2BEyfkZUtL2RQ2YgR/XZoIRRMhb29vPH/+HJMnT0ZwcDDc3d2xd+9ebQfqBw8e6NQAffvtt1CpVPj222/x+PFjODk5oW3btpgxY4ZSd8HgNBr5Hhw/Pvnrp0yRCxzb2GRqWEREOdeSJYCHh/xlGRAA1KypdESUiRSdR0gJWXUeIbUaKFcOuHMn5X2Cg4H3BtkREZG+hEha23P4sOxsmSePAgFRWuS4eYQowa5dgIVFyknQP//I9y2TICKiDNq2DWjSRK4ZlliTJkyCTBQXXVWQRpPy8jSFCwOBgZwHiIjIIKKigNGjgcWL5faoUcAvvygbE2UJTIQUIIRcsDg5ZcoAN26wjx4RkcHcvg106SJHgcV780bOHm3Br0FTx6axTPbffyknQVeuADdvMgkiIjKYTZuA6tUTkiBra2DpUmDDBiZBBICJUKaaMAGoXz9p+aefylqiihUzPyYiohwpMhL48kugWzfg7VtZVq4ccOoUMGAAf3GSFtPhTLJlC/D/6ZB0xMWl3E+IiIjS4fp12RR26VJC2eefyz5BuXMrFxdlSawRygRffinfk4ktXSprgZgEEREZ2JYtCUmQrS2wahWwZg2TIEoWa4SMKKVRYbt3A61bZ348REQmYcIE4OBB4NkzYPNmuRo1UQqYCBlJWBjg6Ji0nEkQEZGBhYbqfuCam8sEyM4OyJVLubgoW2DTmJEklwS9eMEkiIjIYIQAVq8GihcHTp7Uvc7JiUkQpQkTIQN7/Tr5wQgaDZA/f+bHQ0SUI4WHAz4+QN++skbI21t+ABPpiYmQAZ08CeTLl7Q8uWVtiIgonS5eBGrUANauTSjz8uJq1JQuTIQM5NUroE6dpOXBwZkfCxFRjiQEsGwZUKuWnIIfkCPBNm6UQ3FtbZWNj7IlJkIG0Llz0mav1q25UCoRkcGEhQHdu8v5SKKjZdlHHwFnzwJduyobG2VrHDWWQck1eQ0enLCuHxERZdCFC0CnTnLNsHhDhgA//MDmMMowJkIZ8OOPScvmzpWLGhMRkYEIATx8KC87OgIrVwKffaZsTJRjMBFKJxubhNrZeG/eJD9snoiIMsDdHZg/Xw6V37QJKFlS6YgoB2EfoXRQqZImQYGBTIKIiAzi4kUgNla3bOBA4NgxJkFkcEyE9PT770nL7t0DqlfP/FiIiHIUIYAFC+TQ+IkTda9TqQBLS0XCopyNiZAeHjwA2rfXLYuMBNzclIiGiCgHefVKfsCOHClrg+bMAf75R+moyASwj1AaxcXJWdwTCwzkgAUiogw7flwOgX/wIKFszBigXj3lYiKTwRqhNEquRpbNYUREGaDRyJqfRo0SkqD8+YE//gC+/55NYZQpWCOUBhcv6m4XLZowkpOIiNLhxQu5VtiePQllDRrIWaKLFlUuLjI5rBH6ACGAatV0y5gEERFlwM2bckh8fBKkUgETJgCHDjEJokzHGqEPaN1ad3vrVmXiICLKMdzcgCJFgMePAScnYN06oEULpaMiE8UaoVRcvQrs3atbxslMiYgyyMoKCAiQo8QuXGASRIpijVAqOnfW3Y6IUCYOIqJs7fBh2Qm6SpWEshIlgN9+UywkonisEUrF1asJl4cNA+zslIuFiCjbUauBqVOB5s3lL8vwcKUjIkqCiVAKNBrd7RkzlImDiChbevpUNnlNmSI/UG/cAH75RemoiJJgIpSC92eLtrdXJAwiouxn3z45KuzgQbltZgZ89x0wapSiYRElh32EkiGE7hD5UqWUi4WIKNuIi5M1QDNnyg9SQI4O27hRTppIlAUxEUrG+yPFLl9WJg4iomzj8WOgWzfgyJGEspYtgTVr5BB5oiyKiVAy3p87iOuJERGlIjxcrhgfHCy3zc1lrdDo0bJZjCgL4yv0Pa9e6W4nnv2diIiSkTs38NVX8rKrK/Dvv8A33zAJomyBNULvWbJEd7tVK2XiICLKVsaMkX2EBg0C8uVTOhqiNGO6/p6JExMuN2umXBxERFnWrl3A/Pm6ZWZm8gOUSRBlM6wRSmT3bt3t92uHiIhMWkwMMH48MG+eTHyqVwcaN1Y6KqIMYY1QIm3b6m6XKaNMHEREWc69e0DDhjIJAuQkiQEBysZEZABMhP5PiIRpLwDg77+Vi4WIKEvZvh346CPg1Cm5bWUF/PQTsHixsnERGQCbxv5vzRrd7SZNFAmDiCjriI6WQ+AXLUooK1VK1gR5eCgXF5EBMRH6v969dbctLRUJg4goa7h9G/D2Bs6eTSjr0gVYtgxwdFQuLiIDY9MYZI1vYonf90REJkcI+esw/sPQ2lqOHtm0iUkQ5ThMhACcP6+7/X5iRERkUlQqYPlywM4OKFsWOHkS+PJLWU6Uw2SoaSwqKgo22Xz9CY1GdzsiQpk4iIgUJYRuolOhAvDnn/KXob29cnERGZneNUIajQbTp0+Hi4sLcufOjbt37wIAJk2ahJUrVxo8QGN7PxGys1MmDiIixaxfL+cDiorSLW/UiEkQ5Xh6J0Lfffcd/P398f3338PKykpbXrlyZaxYscKgwWWGcuUSLufPr1wcRESZ7t074IsvgM8/l6vGjx6tdEREmU7vRGjNmjVYtmwZevToAXNzc215tWrVcP36dYMGlxmKFUu4XKiQcnEQEWWqq1eBWrWAxDX5794lrSYnyuH0ToQeP36M0qVLJynXaDSIjY01SFCZ6fDhhMtHjyoWBhFR5vH3B2rWBK5ckdt2dnIytVWruGI8mRy9X/EVK1bEkSNHkpRv3boVH2Wz4VYvXuhu58qlTBxERJkiPBzw8QH69JG1PwBQpQoQGAj07KlsbEQK0XvU2OTJk+Hj44PHjx9Do9Fg+/btuHHjBtasWYM//vjDGDEaTfyPoXiJujwREeUsly7JCRETd2Ho3x9YuBCwtVUuLiKF6V0j1K5dO+zatQv79+9Hrly5MHnyZFy7dg27du3Cxx9/bIwYjSYoKOFyzZqKhUFEZHxbtyYkQblzAxs2yFmimQSRiUvXPEINGzbEvn37DB1LpgsOTrhcu7ZycRARGd2kScChQ8Dbt8DmzUCZMkpHRJQl6F0jVLJkSbx8+TJJ+Zs3b1CyZEmDBJVZQkISLleooFwcREQG9/q17raFBbBtG3D8OJMgokT0ToSCgoKgVquTlEdHR+Px48cGCSqzPHuWcDmbT5BNRCQJAfz8M1C8OHDmjO51Tk78sCN6T5qbxnbu3Km9/Ndff8Ex0cJ7arUaBw4cgJubm0GDM7bEEyjyBxIRZXuhoXKCxK1b5XaXLsC5c1wolSgVaU6E2rdvDwBQqVTw8fHRuc7S0hJubm6YO3euQYMztufPEy5bWysXBxFRhp05IxOfe/cSytq1Yw0Q0QekORHS/H+20RIlSuD06dMoUKCA0YLKLBs3JlwWQrk4iIjSTQjgxx+BMWOA+Elt8+SRkya2a6dkZETZgt6jxu4l/rWRjSUeOg8A5csrEgYRUfq9fg307Qvs2JFQVqcOsGmT7CNERB+UruHzERER+Oeff/DgwQPExMToXDd8+HCDBGZs27frbrMJnYiyldOngc6dgfv3E8pGjwZmzgQsLZWLiyib0TsROnfuHFq3bo13794hIiIC+fLlw4sXL2BnZ4eCBQtmm0Qod+6EywMGKBcHEVG6mJsDT5/Ky/nyybXC2rRRNiaibEjv4fMjR45E27Zt8fr1a9ja2uLEiRO4f/8+PDw88MMPPxgjRqNr2FDpCIiI9FS9OjB3LlC/PnD+PJMgonTSOxE6f/48vv76a5iZmcHc3BzR0dFwdXXF999/jwkTJhgjRqO4e1fpCIiI9BAYCMTF6ZYNGQIcPgy4uioSElFOoHciZGlpCTMzeVjBggXx4MEDAICjoyMePnxo2OiM6Ny5hMuRkcrFQUSUKo0G8POT6wBNnqx7nUolZ4wmonTTOxH66KOPcPr0aQBA48aNMXnyZKxfvx5fffUVKleurHcAixcvhpubG2xsbFC7dm2cOnUq1f3fvHmDIUOGoHDhwrC2tkbZsmWxZ88evW83LCzhcrlyeh9ORGR8z54BrVoBEyYAarVMiP77T+moiHIUvROhmTNnonDhwgCAGTNmIG/evBg0aBCeP3+OpUuX6nWugIAAjBo1Cr6+vjh79iyqVasGLy8vPEu89kUiMTEx+PjjjxEUFIStW7fixo0bWL58OVxcXPS9Gzo1yRw6T0RZzuHDgLs78PffclulkjVCXCGayKBUQig3lWDt2rVRs2ZNLFq0CICctNHV1RXDhg3DuHHjkuy/ZMkSzJkzB9evX4dlOoeHhoWF/X95kFAADgDkDNM5YH5IIsoJ1Gpgxgxg6lTZLAYAhQoBGzYAzZopGxuRguK/v0NDQ+Hg4GCw8+pdI5SSs2fP4pNPPknz/jExMQgMDISnp2dCMGZm8PT0xPHjx5M9ZufOnahbty6GDBmCQoUKoXLlypg5c2ayi8DGi46ORlhYmM7f++zt0xw2EZHxBAcDLVoAvr4JSZCnJ3DhApMgIiPRKxH666+/MHr0aEyYMAF3/z/s6vr162jfvj1q1qypXYYjLV68eAG1Wo1ChQrplBcqVAjBwcHJHnP37l1s3boVarUae/bswaRJkzB37lx89913Kd6On58fHB0dtX+uyYyu4DpjRKS4q1dlU9jBg3LbzAyYPh3Yu1fWCBGRUaQ5EVq5ciVatWoFf39/zJ49G3Xq1MG6detQt25dODs74/Lly+nqtKwPjUaDggULYtmyZfDw8IC3tzcmTpyIJUuWpHjM+PHjERoaqv3LTiPbiMiElCoFFC0qLxcpIhOib7+VEycSkdGkORFauHAhZs+ejRcvXmDz5s148eIFfv75Z1y6dAlLlixBhQoV9LrhAgUKwNzcHCEhITrlISEhcHZ2TvaYwoULo2zZsjBP9MFQoUIFBAcHJ1nqI561tTUcHBx0/oiIshxrayAgQC6bcf480Lix0hERmYQ0J0J37txB586dAQAdO3aEhYUF5syZg6Lxv2D0ZGVlBQ8PDxw4cEBbptFocODAAdStWzfZY+rXr4/bt2/rNMHdvHkThQsXhpWVVbriaNs2XYcREWXM3r3AlSu6ZaVKAZs3A05OysREZILSnAhFRkbCzs4OAKBSqWBtba0dRp9eo0aNwvLly/Hrr7/i2rVrGDRoECIiItCnTx8AQK9evTB+/Hjt/oMGDcKrV68wYsQI3Lx5E7t378bMmTMxZMiQdMcQG5uhu0BEpJ/YWGDcODk/UJcuQESE0hERmTS9piRdsWIFcv9/tdK4uDj4+/ujwHvjzvVZdNXb2xvPnz/H5MmTERwcDHd3d+zdu1fbgfrBgwfaWawBwNXVFX/99RdGjhyJqlWrwsXFBSNGjMDYsWP1uRs6Jk1K96FERPp5+BDo2jVhUsSrV4GVK4Fsslg1UU6U5nmE3NzcoFKpUj+ZSqUdTZZVvT+P0LFjQL16SkdFRDnerl1A797Aq1dy28ICmD0bGDlSTpZIRKky1jxCaa4RCgoKMtiNZiXKTSdJRCYhJgYYPx6YNy+hrHhx2TGas0QTKc7kV+srVUrpCIgox7p3TzaFJV5DsUMH2RyWN69ycRGRlsknQmYGm1ubiCiR0FCgZk3g5Uu5bWUF/PADMHQom8KIshCmAURExuDoKPv/AEDJkrKD9LBhTIKIshiTrxEiIjKa8eNltfPgwTIxIqIshzVCRESGsHkzsGCBbpmZmUyGmAQRZVnpSoTu3LmDb7/9Ft26dcOzZ88AAH/++SeuvD9LKhFRThcZCQwcCHh7A6NHA0ePKh0REelB70Ton3/+QZUqVXDy5Els374d4eHhAIALFy7A19fX4AEaG5ceI6J0u3EDqFMHWLpUbqvVwG+/KRsTEelF70Ro3Lhx+O6777Bv3z6d9b2aNWuGEydOGDS4zGBjo3QERJQtrV8PeHgAFy/KbRsbYMUKOTKMiLINvTtLX7p0CRs2bEhSXrBgQbx48cIgQWUW1gYRkd7evZNLYqxcmVBWoYLsI1S5snJxEVG66F0jlCdPHjx9+jRJ+blz5+Di4mKQoDILZ5UmIr1cvQrUqqWbBPn4AKdPMwkiyqb0ToS6du2KsWPHIjg4GCqVChqNBseOHcPo0aPRq1cvY8RoNG/fKh0BEWUbQsikJ35QiJ0d4O8v/3LlUjIyIsqANC+6Gi8mJgZDhgyBv78/1Go1LCwsoFar0b17d/j7+8Pc3NxYsRrE+4uuslaIiNLs8mVZI1SqlGwKq1BB6YiITIaxFl3VOxGK9+DBA1y+fBnh4eH46KOPUKZMGYMFZUyJE6FduxzwySdKR0REWZZGk3QdniNHZCdpOztlYiIyUYqvPh/v6NGjaNCgAYoVK4ZixYoZLBAl5MmjdARElCUJIUeArV0L7NsHWFsnXNewoXJxEZHB6d1HqFmzZihRogQmTJiAq1evGiMmIiLlvH0L9OgBDBgga3/GjlU6IiIyIr0ToSdPnuDrr7/GP//8g8qVK8Pd3R1z5szBo0ePjBEfEVHmOXcOqF4d2LgxoSw2lkNMiXIwvROhAgUKYOjQoTh27Bju3LmDzp0749dff4WbmxuaNWtmjBiJiIxLCODnn4G6dYHbt2WZgwMQEAAsXswV44lysAytPl+iRAmMGzcO1apVw6RJk/DPP/8YKi4ioswRGgp88QWwdWtCmYeHTIJKlVIuLiLKFOleff7YsWMYPHgwChcujO7du6Ny5crYvXu3IWMjIjKuM2dkU1jiJGj4cODYMSZBRCZC7xqh8ePHY9OmTXjy5Ak+/vhjLFy4EO3atYMdh5ISUXazfTtw9668nCcPsHo10L69khERUSbTOxH6999/MWbMGHTp0gUFChQwRkxERJlj6lTgn3/kqvGbNgFubkpHRESZTO9E6NixY8aIg4jI+F6+BPLnT9i2tAR27AAcHQErK8XCIiLlpCkR2rlzJ1q1agVLS0vs3Lkz1X0//fRTgwRGRGQwGg0wbx4wZQrw77+yX1A8JyfFwiIi5aVpiQ0zMzMEBwejYMGCMHt/uvnEJ1OpoFarDRqgoSVeYuPIEQc0aKB0RERkVC9fysVS4wdzlCoFnD0rh8cTUbah6BIbGo0m2ctERFna0aNAt25A4glfO3cGbG2Vi4mIshS9h8+vWbMG0dHRScpjYmKwZs0agwRFRJQhGg0waxbQpElCElSgAPDnn4Cfn+wbRESEdCRCffr0QWhoaJLyt2/fok+fPgYJiogo3Z49A1q3BsaPl6PBAKBRI+D8eaBlS0VDI6KsR+9ESAgBVTLTzT969Oj/fW+IiBRy7Bjg7g789ZfcVqmASZOAAwcAFxdFQyOirCnNw+c/+ugjqFQqqFQqNG/eHBYWCYeq1Wrcu3cPLflri4iUZGUFvHghLxcqBKxbB3h6KhsTEWVpaU6E2v9/ttXz58/Dy8sLuXPn1l5nZWUFNzc3fPbZZwYPkIgozWrWBGbPliPE1q0DnJ2VjoiIsrg0DZ9P7Ndff4W3tzdsbGyMFZNRcfg8UQ5y4gRQowaQqIYaQsjO0ubmysVFRAZnrOHzevcR8vHxybZJEBHlEHFxwOTJQL16cpmMxFQqJkFElGZpahrLly8fbt68iQIFCiBv3rzJdpaO9+rVK4MFR0SUxJMncm6gf/+V2zNmAJ9+KpvFiIj0lKZEaP78+bC3t9deTi0RIiIymr17gZ49EzpEm5sD330HeHgoGxcRZVt69xHK7thHiCgbiouTw+BnzUooK1oU2LgRfBMTmYYs00fo7NmzuHTpknb7999/R/v27TFhwgTExMQYLDAiIgDAw4dyhujESVCbNnKCRCZBRJRBeidCX375JW7evAkAuHv3Lry9vWFnZ4ctW7bgm2++MXiARGTCLlyQEyQeOya3LSyAH34Adu4E8udXNDQiyhn0ToRu3rwJd3d3AMCWLVvQuHFjbNiwAf7+/ti2bZuh4yMiU1auHFCsmLxcvDhw5Ajw9deAmd4fXUREyUrXEhvxK9Dv378frVu3BgC4urriRXwHRiIiQ7CxATZvBnr0AM6dA+rUUToiIsph9E6EatSoge+++w5r167FP//8gzZt2gAA7t27h0KFChk8QCIyITt2AFev6paVKSNnic6bV5GQiChn0zsRWrBgAc6ePYuhQ4di4sSJKF26NABg69atqFevnsEDJCITEB0NjBgBdOgAeHsD794pHRERmQiDDZ+PioqCubk5LC0tDXE6o+HweaIs5s4dmfwEBiaULVkCfPmlcjERUZZjrOHzaV509X2BgYG4du0aAKBixYqoXr26wYIiIhOxZQvwxRdAWJjctrYG5s8HBgxQNi4iMhl6J0LPnj2Dt7c3/vnnH+TJkwcA8ObNGzRt2hSbNm2Ck5OToWM0mv/3+SaizBYVBYwaBfzyS0JZmTKyY/T/R6USEWUGvfsIDRs2DOHh4bhy5QpevXqFV69e4fLlywgLC8Pw4cONEaPRlCypdAREJujmTTn6K3ES1K2bbBpjEkREmUzvPkKOjo7Yv38/ar63wOGpU6fQokULvHnzxpDxGVziPkJPnzrA2VnpiIhMyKtX8hdIaKjctrEBfvoJ6NdPrhpPRJSCLLPEhkajSbZDtKWlpXZ+ISKiZOXLJydEBIDy5YFTp2QfISZBRKQQvROhZs2aYcSIEXjy5Im27PHjxxg5ciSaN29u0OCIKAeaMAH4/nvg9GmgShWloyEiE6d3IrRo0SKEhYXBzc0NpUqVQqlSpVCiRAmEhYXhp59+MkaMRJRd/forsHChbpm5OTBmDJA7tzIxEREloveoMVdXV5w9exYHDhzQDp+vUKECPD09DR4cEWVTERHAkCEyETI3B2rWBDjhKhFlQXolQgEBAdi5cydiYmLQvHlzDBs2zFhxEVF2dfky0LkzcP263FargT17mAgRUZaU5kTol19+wZAhQ1CmTBnY2tpi+/btuHPnDubMmWPM+IgouxACWLkSGDZMzhMEyOavpUuB7t2VjY2IKAVp7iO0aNEi+Pr64saNGzh//jx+/fVX/Pzzz8aMjYiyi7dvgc8/B/r3T0iCqlWTcwMxCSKiLCzNidDdu3fh4+Oj3e7evTvi4uLw9OlTowRGRNnE+fOAhwewYUNC2cCBwIkTQNmyioVFRJQWaW4ai46ORq5cubTbZmZmsLKyQmRkpFECI6JsQAigTx/g1i25bW8PrFgBdOmibFxERGmkV2fpSZMmwc7OTrsdExODGTNm/H+mZmnevHmGi87IstGyaERZk0olR4bVrg1UrCjXCitVSumoiIjSLM1LbDRp0gSqD8z+qlKpcPDgQYMEZiyJl9gQwnBTdBOZDI0GMHuvVf3YMaBGDbl6PBGRERhriY001wgdPnzYYDeaFSRq5SOitBBCrgu2dSuwfz9gZZVwXf36ysVFRJQBes8sTUQm6PVroGNHYMQI4MgRYPx4pSMiIjIIvWeWJiITc/Ik4O0N3L+fUGZmJmuIuFgqEWVzrBEiouQJAcydCzRokJAE5csH7NoFzJnDJIiIcgTWCBFRUi9fAr17A3/8kVBWrx6waRPg6qpYWEREhpYlaoQWL14MNzc32NjYoHbt2jh16lSajtu0aRNUKhXat29v3ACJTMmxY4C7u24SNHYscPgwkyAiynHSlQgdOXIEn3/+OerWrYvHjx8DANauXYujR4/qfa6AgACMGjUKvr6+OHv2LKpVqwYvLy88e/Ys1eOCgoIwevRoNGzYMD13gYhSsnMn8OiRvFygAPDnn8CsWYClpbJxEREZgd6J0LZt2+Dl5QVbW1ucO3cO0dHRAIDQ0FDMnDlT7wDmzZuH/v37o0+fPqhYsSKWLFkCOzs7rFq1KsVj1Go1evTogalTp6JkyZJ63yYRpeK774A6dYBGjeTyGS1bKh0REZHR6J0Ifffdd1iyZAmWL18Oy0S/EOvXr4+zZ8/qda6YmBgEBgbC09MzISAzM3h6euL48eMpHjdt2jQULFgQ/fr1++BtREdHIywsTOePiBJ5v/bV0lJ2iD5wAHBxUSYmIqJMoncidOPGDTRq1ChJuaOjI968eaPXuV68eAG1Wo1ChQrplBcqVAjBwcHJHnP06FGsXLkSy5cvT9Nt+Pn5wdHRUfvnyj4ORJJaDUyfDpQoIWt+EitQALDgWAoiyvn0ToScnZ1x+/btJOVHjx41ejPV27dv0bNnTyxfvhwFChRI0zHjx49HaGio9u/hw4dGjZEoWwgOBry8gMmTgXfv5CKp4eFKR0VElOn0/snXv39/jBgxAqtWrYJKpcKTJ09w/PhxjB49GpMmTdLrXAUKFIC5uTlCQkJ0ykNCQuDs7Jxk/zt37iAoKAht27bVlmk0GnlHLCxw48YNlHpvwUdra2tYc/0jogQHDgA9egDx7zszM6BnT8DWVtm4iIgUoHciNG7cOGg0GjRv3hzv3r1Do0aNYG1tjdGjR2PYsGF6ncvKygoeHh44cOCAdgi8RqPBgQMHMHTo0CT7ly9fHpcuXdIp+/bbb/H27VssXLiQzV5EqVGrgWnTZHNY/FrLhQsDGzcCjRsrGxsRkUL0ToRUKhUmTpyIMWPG4Pbt2wgPD0fFihWRO3fudAUwatQo+Pj4oEaNGqhVqxYWLFiAiIgI9OnTBwDQq1cvuLi4wM/PDzY2NqhcubLO8Xny5AGAJOVElMiTJ0D37sA//ySUtWgBrF0LFCyoXFxERApLd29IKysrVKxYMcMBeHt74/nz55g8eTKCg4Ph7u6OvXv3ajtQP3jwAGZmWWLeR6Ls6dAhuVbY8+dy29xcDpH/5hvZLEZEZMJUQsTXkadN06ZNoUpljaGDBw9mOChjCgsLg6OjI3LlCkV4uIPS4RAZ34kTQMOGQFwcULSobApr0EDpqIiI9BL//R0aGgoHB8N9f+tdI+Tu7q6zHRsbi/Pnz+Py5cvw8fExVFxEZCh16gB+fnKJDH9/OTSeiIgApKNGKCVTpkxBeHg4fvjhB0OczmhYI0Q53pEjcoFUc/OEsv+PrmRTGBFlV8aqETLYp+Lnn3+e6rIYRGRkMTHA6NFyaYzp03WvMzNjEkRElAyDfTIeP34cNjY2hjodEekjKEgmQHPnyu1p05LOFk1EREno3UeoY8eOOttCCDx9+hRnzpzRe0JFIjKAHTuAPn2A+CVuLC2BH34AqlVTMioiomxB70TI0dFRZ9vMzAzlypXDtGnT0KJFC4MFRkQfEB0th8D/+GNCWcmSQEAAUKOGcnEREWUjeiVCarUaffr0QZUqVZA3b15jxUREH3LnjpwbKDAwoaxTJ2DFCuC9HytERJQyvfoImZubo0WLFnqvMk9EBnT6NFC9ekISZG0N/PwzsHkzkyAiIj3p3Vm6cuXKuHv3rjFiIaK0qFwZcHOTl8uUkRMmDhoEpDLRKRERJU/vROi7777D6NGj8ccff+Dp06cICwvT+SMiI7O1lbU/ffrIWqH3JjklIqK0S/OEitOmTcPXX38Ne3v7hIMT/QIVQkClUkGtVhs+SgPihIqU7WzcKJvCypVTOhIiIsUYa0LFNCdC5ubmePr0Ka5du5bqfo0bNzZIYMbCRIiyjchIYPhw2QG6alXZBGZrq3RURESKUHytsfh8KasnOkQ5wrVrQJcuwOXLcvviRdkcxvX8iIgMSq8+QqmtOk9EBvLrr3IeoPgkyM4OWL2aSRARkRHoNY9Q2bJlP5gMvXr1KkMBEZmsiAhgyBCZCMWrVEnWBFWsqFxcREQ5mF6J0NSpU5PMLE1EBnD5smwKS9wHr18/OWu0nZ1ycRER5XB6JUJdu3ZFwYIFjRULkWl69gyoU0fWCAFArlzA0qVAjx7KxkVEZALS3EeI/YOIjKRgQeDrr+XlqlXl3EBMgoiIMoXeo8aIyAgmT5bLYwwaxCHyRESZKM2JkEajMWYcRKZBCNnsFRMj5wiKZ24OjBqlXFxERCZKrz5CRJQBoaHAgAFyFJiFBVC7tvwjIiLF6L3WWE7x7p3SEZBJCQwEPDxkEgQAcXHA/v3KxkRERKabCLHLE2UKIYCffgLq1QPu3JFljo7Atm3AxInKxkZERKbbNFalitIRUI73+rWcC+i33xLKatUCNm0CSpRQLi4iItIy2RohIqM6eVKuGJ84Cfr6a+DIESZBRERZiMnWCBEZjUYja4KCguR2vnyAvz/Qtq2SURERUTJYI0RkaGZmwLp1gLW17Bt07hyTICKiLIo1QkSGoFbLuYDiubsDhw7JVeQtLRULi4iIUscaIaKM0GiA2bOBpk2B2Fjd6+rWZRJERJTFMREiSq/nz4FPPgHGjZOdoDkcnogo22HTGFF6/Psv0K0b8OSJ3FapABsbOW8QFygmIso2mAgR6UOtBvz8AF9f2SwGyNXj160DPv5Y2diIiEhvTISI0iokBPj8c92lMZo1k0lQ4cLKxUVEROnGPkJEaXHwIFCtWkISZGYGTJ0K/P03kyAiomyMNUJEafHHH7JGCJCJz4YNQJMmioZEREQZx0SIKC1mzQKOHgXy5gXWrpX9goiIKNtjIkSUnOBgwNk5YdvKCvjzT5kImbFFmYgop+AnOlFicXHAhAlAqVLAxYu61+XPzySIiCiH4ac6UbxHj+QM0X5+wLt3QJcuQESE0lEREZERMREiAoA9e+T6YEePym0LC+CLLwBbW0XDIiIi42IfITJtsbFyaYw5cxLKihUDNm2Sa4UREVGOxkSITNf9+0DXrsCJEwlln34KrF4N5MunXFxERJRp2DRGpunPP2VTWHwSZGkJLFgA7NjBJIiIyISwRohMk6Mj8PatvFyiBBAQANSsqWxMRESU6ZgIkWmqVw+YMQM4fRpYsQLIk0fpiIiISAFMhMg0HDoENGoEmJsnlI0ZA6hU8o+IiEwS+whRzhYVBQwdKleJ9/PTvc7MjEkQEZGJYyJEOdetW7IJbPFiue3rC1y5omxMRESUpTARopxp0yagenXg3Dm5bWMDLFkCVKyobFxERJSlsI8Q5SyRkcBXXwHLliWUlSsHbN4MVK2qWFhERJQ1MRGinOP6dbk+2KVLCWU9ewI//wzkzq1cXERElGUxEaKc4b//gBYtEhZJtbWVCVDv3oqGRUREWRv7CFHO4O4uJ0YEgEqVgDNnmAQREdEHMRGinMHOTvYDGjQIOHWKnaKJiChNmAhR9iOEXBj11i3d8goVZHOYnZ0ycRERUbbDRIiyl/Bw2QG6b1/A21tOmEhERJROTIQo+7hwAfDwANavl9vnzgG//65sTERElK0xEaKsTwhg6VKgdm3g5k1ZZm8vJ0309lY2NiIiytY4fJ6ytrAwYMAAICAgoax6dbldurRycRERUY7AGiHKus6eTUh64g0bJucMYhJEREQGwBohypqePgXq10/oDO3oCKxaBXTsqGxcRESUo7BGiLKmwoWBr7+Wl2vWlB2jmQQREZGBsUaIsq4pU4BChYAvvwSsrJSOhoiIcqAsUSO0ePFiuLm5wcbGBrVr18apU6dS3Hf58uVo2LAh8ubNi7x588LT0zPV/SkbEAKYPx9YvFi33MJC9gliEkREREaieCIUEBCAUaNGwdfXF2fPnkW1atXg5eWFZ8+eJbv/4cOH0a1bNxw6dAjHjx+Hq6srWrRogcePH2dy5GQQr14B7doBo0YBI0fKNcKIiIgyiUoIIZQMoHbt2qhZsyYWLVoEANBoNHB1dcWwYcMwbty4Dx6vVquRN29eLFq0CL169frg/mFhYXB0dISTUyiePXPIcPyUAf/9B3TtCjx8mFA2d65MioiIiBKJ//4ODQ2Fg4Phvr8VrRGKiYlBYGAgPD09tWVmZmbw9PTE8ePH03SOd+/eITY2Fvny5Uv2+ujoaISFhen8ydvJePyUThoN8P33QKNGCUlQgQLAnj1MgoiIKFMpmg68ePECarUahQoV0ikvVKgQgoOD03SOsWPHokiRIjrJVGJ+fn5wdHTU/rm6ugIA6tTJWOyUTs+fA598AowdC6jVsqxhQ+D8eaBVK0VDIyIi05Ot60VmzZqFTZs24bfffoONjU2y+4wfPx6hoaHav4eJm2Eocx05Ari7A3/+KbdVKuDbb4GDBwEXF0VDIyIi06To8PkCBQrA3NwcISEhOuUhISFwdnZO9dgffvgBs2bNwv79+1G1atUU97O2toa1tbVB4qUMiIsD+vcHnjyR2wULAuvWAR9/rGxcRERk0hStEbKysoKHhwcOHDigLdNoNDhw4ADq1q2b4nHff/89pk+fjr1796JGjRqZESpllIWFXDXeygpo2lQ2hTEJIiIihSk+oeKoUaPg4+ODGjVqoFatWliwYAEiIiLQp08fAECvXr3g4uICPz8/AMDs2bMxefJkbNiwAW5ubtq+RLlz50bu3LkVux+UjLg4mQDF8/AA/v0XqFEDMDdXLi4iIqL/UzwR8vb2xvPnzzF58mQEBwfD3d0de/fu1XagfvDgAcwSDfH65ZdfEBMTg06dOumcx9fXF1OmTMnM0CklajUwfTpw+DCwf79uMlS7tmJhERERvU/xeYQyW/w8BO3ahWLHDs4jZHBPnwLdu8skCADGjwdmzlQ0JCIiyv5y5DxClMP8/TdQrVpCEmRmBtjbKxoSERFRahRvGqMcIC4O8PUF/PzkumGAHA6/caOcI4iIiCiLYiJEGfPoEdCtG3D0aEJZq1bAmjVytmgiIqIsjE1jlH579sgJEuOTIAsLuXTGH38wCSIiomyBNUKUfnv3Ai9fysvFigGbNgGpzP9ERESU1TARovSbMwc4dgwoWhRYvRpIYeFbIiKirIqJEKXd48e6a4JZWwP79gF588p1w4iIiLIZ9hGiD4uJAUaOBMqWBa5c0b0uXz4mQURElG0xEaLU3bsHNGgALFgAvHsHdOkCREYqHRUREZFBMBGilG3bBnz0EXD6tNy2sgIGDwZsbJSNi4iIyEDYR4iSiooCRo8GFi9OKCtVCti8GaheXbm4iIiIDIyJEOm6fVs2f507l1Dm7Q0sWwYYcG0XIiKirIBNY5Rgxw5Z4xOfBFlbA0uXyqUymAQREVEOxBohSpAvHxARIS+XKyebwqpWVTYmIiIiI2IiRAkaNQKmTQNu3AB+/hnInVvpiIiIiIyKiZAp+/tvwNMTMEvUQjphgvzPuYGIiMgEsI+QKXr3DujbF/DyAmbP1r1OpWISREREJoOJkKm5cgWoWVOuDQYAkyYBN28qGxMREZFCmAiZCiFk8lOzJnD1qizLlUuWlS2rbGxEREQKYR8hUxAeDgwaBKxbl1BWpYocFVa+vHJxERERKYw1QjndxYtAjRq6SdCXXwInTzIJIiIik8caoZzs8GGgVSu5ZAYA2NvLGaK7dlU0LCIioqyCNUI5Wc2aQIkS8vJHHwGBgUyCiIiIEmEilJPlyiX7AX31FfDff0CZMkpHRERElKUwEcophACWLAHu3NEtr1wZmD8fsLFRJi4iIqIsjIlQTvDmjVwxftAguVJ8dLTSEREREWULTISyu9On5YrxW7fK7cBAYM8eZWMiIiLKJpgIZVdCAAsWAPXrA/fuybI8eYAdO4AOHRQMjIiIKPvg8Pns6NUroE8fYOfOhLI6dYBNm4DixZWLi4iIKJthjVB2c/y4HAqfOAkaMwb4918mQURERHpijVB28uAB0LgxEBsrt/PnB379FWjTRtm4iIiIsinWCGUnxYoBo0bJyw0aAOfPMwkiIiLKANYIZTfTp8smsP79AQs+fURERBnBGqGsSqMB/PyAX37RLbe0lPMFMQkiIiLKMH6bZkXPngE9ewJ//w1YWQG1a8u5goiICGq1GrHxfSUpR7G0tIS5uXmm3iYToazm8GGge3fg6VO5HRsrR4oxESIiQnh4OB49egQhhNKhkBGoVCoULVoUuXPnzrTbZCKUVajVwHffAdOmyWYxAHB2BtavB5o1UzY2IqIsQK1W49GjR7Czs4OTkxNUKpXSIZEBCSHw/PlzPHr0CGXKlMm0miEmQlnB06fA558DBw8mlHl6AuvWAYUKKRcXEVEWEhsbCyEEnJycYGtrq3Q4ZAROTk4ICgpCbGxspiVC7CyttH37AHf3hCTIzEzWDP31F5MgIqJksCYo51LiuWWNkJJiY+UIsGfP5HaRIsDGjUCjRsrGRUREZCJYI6QkS0uZ+FhaAi1bygkSmQQRERFlGiZCme39IZ81awL//Qfs3g04OSkTExERGd3x48dhbm6ONsmsCHD48GGoVCq8efMmyXVubm5YsGCBTtmhQ4fQunVr5M+fH3Z2dqhYsSK+/vprPH782EjRA1FRURgyZAjy58+P3Llz47PPPkNISEiqx4SEhKB3794oUqQI7Ozs0LJlS9y6dctoMaYHE6HMEhsLjBsHtGgBxMXpXlejhuwbREREOdbKlSsxbNgw/Pvvv3jy5Em6z7N06VJ4enrC2dkZ27Ztw9WrV7FkyRKEhoZi7ty5BoxY18iRI7Fr1y5s2bIF//zzD548eYKOHTumuL8QAu3bt8fdu3fx+++/49y5cyhevDg8PT0RERFhtDj1xT5CmeHBA6BbN1nzAwBTp8qlMoiIyCSEh4cjICAAZ86cQXBwMPz9/TFhwgS9z/Po0SMMHz4cw4cPx/z587Xlbm5uaNSoUbI1SoYQGhqKlStXYsOGDWj2/yldVq9ejQoVKuDEiROoU6dOkmNu3bqFEydO4PLly6hUqRIA4JdffoGzszM2btyIL774wiix6ovVEMa2a5ccFRafBFlYyFXjiYjIZGzevBnly5dHuXLl8Pnnn2PVqlXpmhRyy5YtiImJwTfffJPs9Xny5Enx2FatWiF37twp/sUnK8kJDAxEbGwsPD09tWXly5dHsWLFcPz48WSPiY6OBgDY2Nhoy8zMzGBtbY2jR4+mdjczFWuEjCUmBhg/Hpg3L6HMzQ0ICABq1VIsLCKinKRGDSA4OPNv19kZOHMm7fuvXLkSn3/+OQCgZcuWCA0NxT///IMmTZrodbu3bt2Cg4MDChcurNdxALBixQpERkameL2lpWWK1wUHB8PKyipJolWoUCEEp/AExCdK48ePx9KlS5ErVy7Mnz8fjx49wtP41ROyACZCxnDvHtC1K3DqVEJZhw7AqlVAKtk6ERHpJzgYMGL/YIO4ceMGTp06hd9++w0AYGFhAW9vb6xcuVLvREgIke65dlxcXNJ1XHpZWlpi+/bt6NevH/Llywdzc3N4enqiVatWWWqJFCZChrZ9O9C3LxAaKretrIC5c4EhQwBOAkZEZFDOzln/dleuXIm4uDgUKVJEWyaEgLW1NRYtWgRHR0c4ODgAkH1x3q91efPmDRwdHQEAZcuWRWhoKJ4+fap3rVCrVq1w5MiRFK8vXrw4rly5kux1zs7OiImJwZs3b3TiCwkJgXMqD4aHhwfOnz+P0NBQxMTEwMnJCbVr10aNGjX0it2YmAgZ2oEDCUlQqVKyKczDQ9mYiIhyKH2ap5QQFxeHNWvWYO7cuWjRooXOde3bt8fGjRsxcOBAlClTBmZmZggMDETx4sW1+9y9exehoaEoW7YsAKBTp04YN24cvv/+e53O0vHeT1QSy0jTmIeHBywtLXHgwAF89tlnAGRN14MHD1C3bt0Uj4sXn8jdunULZ86cwfQsNGCIiZChzZ0rO0aXLQssXw78P8snIiLT88cff+D169fo16+fNhmI99lnn2HlypUYOHAg7O3t8cUXX+Drr7+GhYUFqlSpgocPH2Ls2LGoU6cO6tWrBwBwdXXF/PnzMXToUISFhaFXr15wc3PDo0ePsGbNGuTOnTvFIfQZaRpzdHREv379MGrUKOTLlw8ODg4YNmwY6tatqzNirHz58vDz80OHDh0AyM7dTk5OKFasGC5duoQRI0agffv2SZJCRQkTExoaKgCIdu1CDXPCBw+Slr1+LYRGY5jzExGREEKIyMhIcfXqVREZGal0KGn2ySefiNatWyd73cmTJwUAceHCBSGEvH++vr6ifPnywtbWVpQoUUIMGDBAPH/+PMmx+/btE15eXiJv3rzCxsZGlC9fXowePVo8efLEaPclMjJSDB48WOTNm1fY2dmJDh06iKdPn+rsA0CsXr1au71w4UJRtGhRYWlpKYoVKya+/fZbER0dneptpPQcx39/h4Ya6Pv7/1T/D9xkhIWFwdHREe3ahWLHjgzU1kRGAqNGAWvXyrrZ8uUNFyQRESURFRWFe/fuoUSJEjpDsinnSO05jv/+Dg0N1fapMgTOI5QeN24AdeoAS5YAERFA587A/+dLICIiouyDiZC+1q+XnZ8vXpTbtrbAyJFydBgRERFlK+wsnVbv3gHDhwMrVyaUVagAbNkCpDIbJxEREWVdrBFKi6tX5WzQiZOgPn2A06eZBBEREWVjTIQ+ZPNmoGZNIH6SKTs7YM0aOUt0rlzKxkZEREQZwqaxDylYEIiKkperVJGJEUeIEREpxsQGO5sUJZ5bJkIf0qQJ4OsLPHoELFwoO0cTEVGmMzc3BwDExMTAlp/FOVJMTAyAhOc6MzARSkwIYM8eoFUrwCxRq+GkSVwnjIhIYRYWFrCzs8Pz589haWkJMzP27shJNBoNnj9/Djs7O1hYZF56wkQoXlgY8OWXwKZNwPffA2PGJFzHJIiISHEqlQqFCxfGvXv3cP/+faXDISMwMzNDsWLFoMrE710mQgBw7hzQpQtw+7bcnjAB6NQJKFFC2biIiEiHlZUVypQpo21CoZzFysoq02v6skQitHjxYsyZMwfBwcGoVq0afvrpJ9SqVSvF/bds2YJJkyYhKCgIZcqUwezZs9G6dWv9b1gI4Jdf5ISI8W8qBwc5TJ5JEBFRlmRmZsYlNshgFG9gDQgIwKhRo+Dr64uzZ8+iWrVq8PLywrNnz5Ld/7///kO3bt3Qr18/nDt3Du3bt0f79u1x+fJlvW7XNuaNrAUaMiQhCapRQ9YOdeqUwXtFRERE2YHii67Wrl0bNWvWxKJFiwDIzlKurq4YNmwYxo0bl2R/b29vRERE4I8//tCW1alTB+7u7liyZMkHby9+0bZbdsVR+l2iNuavvgJmzQKsrTN8n4iIiMiwcuSiqzExMQgMDISnp6e2zMzMDJ6enjh+/Hiyxxw/flxnfwDw8vJKcf+UFIxPgvLkAXbsAObPZxJERERkYhTtI/TixQuo1WoUKlRIp7xQoUK4fv16sscEBwcnu39wcHCy+0dHRyM60crwoaGhAIAwQC6e6u8PFCsmR40RERFRlhT2/+9pQzdkZYnO0sbk5+eHqVOnJil3BYDAQDlbNBEREWULL1++hKOjo8HOp2giVKBAAZibmyMkJESnPCQkBM7Ozske4+zsrNf+48ePx6hRo7Tbb968QfHixfHgwQODPpCkv7CwMLi6uuLhw4cGbe+l9OHzkXXwucg6+FxkHaGhoShWrBjy5ctn0PMqmghZWVnBw8MDBw4cQPv27QHIztIHDhzA0KFDkz2mbt26OHDgAL766itt2b59+1C3bt1k97e2toZ1Mn1/HB0d+aLOIhwcHPhcZCF8PrIOPhdZB5+LrMPQ8wwp3jQ2atQo+Pj4oEaNGqhVqxYWLFiAiIgI9OnTBwDQq1cvuLi4wM/PDwAwYsQING7cGHPnzkWbNm2wadMmnDlzBsuWLVPybhAREVE2pHgi5O3tjefPn2Py5MkIDg6Gu7s79u7dq+0Q/eDBA53sr169etiwYQO+/fZbTJgwAWXKlMGOHTtQuXJlpe4CERERZVOKJ0IAMHTo0BSbwg4fPpykrHPnzujcuXO6bsva2hq+vr7JNpdR5uJzkbXw+cg6+FxkHXwusg5jPReKT6hIREREpBTFl9ggIiIiUgoTISIiIjJZTISIiIjIZDERIiIiIpOVIxOhxYsXw83NDTY2NqhduzZOnTqV6v5btmxB+fLlYWNjgypVqmDPnj2ZFGnOp89zsXz5cjRs2BB58+ZF3rx54enp+cHnjvSj73sj3qZNm6BSqbQTn1LG6ftcvHnzBkOGDEHhwoVhbW2NsmXL8rPKQPR9LhYsWIBy5crB1tYWrq6uGDlyJKKiojIp2pzr33//Rdu2bVGkSBGoVCrs2LHjg8ccPnwY1atXh7W1NUqXLg1/f3/9b1jkMJs2bRJWVlZi1apV4sqVK6J///4iT548IiQkJNn9jx07JszNzcX3338vrl69Kr799lthaWkpLl26lMmR5zz6Phfdu3cXixcvFufOnRPXrl0TvXv3Fo6OjuLRo0eZHHnOpO/zEe/evXvCxcVFNGzYULRr1y5zgs3h9H0uoqOjRY0aNUTr1q3F0aNHxb1798Thw4fF+fPnMznynEff52L9+vXC2tparF+/Xty7d0/89ddfonDhwmLkyJGZHHnOs2fPHjFx4kSxfft2AUD89ttvqe5/9+5dYWdnJ0aNGiWuXr0qfvrpJ2Fubi727t2r1+3muESoVq1aYsiQIdpttVotihQpIvz8/JLdv0uXLqJNmzY6ZbVr1xZffvmlUeM0Bfo+F++Li4sT9vb24tdffzVWiCYlPc9HXFycqFevnlixYoXw8fFhImQg+j4Xv/zyiyhZsqSIiYnJrBBNhr7PxZAhQ0SzZs10ykaNGiXq169v1DhNTVoSoW+++UZUqlRJp8zb21t4eXnpdVs5qmksJiYGgYGB8PT01JaZmZnB09MTx48fT/aY48eP6+wPAF5eXinuT2mTnufife/evUNsbKzBF9gzRel9PqZNm4aCBQuiX79+mRGmSUjPc7Fz507UrVsXQ4YMQaFChVC5cmXMnDkTarU6s8LOkdLzXNSrVw+BgYHa5rO7d+9iz549aN26dabETAkM9f2dJWaWNpQXL15ArVZrl+eIV6hQIVy/fj3ZY4KDg5PdPzg42GhxmoL0PBfvGzt2LIoUKZLkhU76S8/zcfToUaxcuRLnz5/PhAhNR3qei7t37+LgwYPo0aMH9uzZg9u3b2Pw4MGIjY2Fr69vZoSdI6XnuejevTtevHiBBg0aQAiBuLg4DBw4EBMmTMiMkCmRlL6/w8LCEBkZCVtb2zSdJ0fVCFHOMWvWLGzatAm//fYbbGxslA7H5Lx9+xY9e/bE8uXLUaBAAaXDMXkajQYFCxbEsmXL4OHhAW9vb0ycOBFLlixROjSTc/jwYcycORM///wzzp49i+3bt2P37t2YPn260qFROuWoGqECBQrA3NwcISEhOuUhISFwdnZO9hhnZ2e99qe0Sc9zEe+HH37ArFmzsH//flStWtWYYZoMfZ+PO3fuICgoCG3bttWWaTQaAICFhQVu3LiBUqVKGTfoHCo9743ChQvD0tIS5ubm2rIKFSogODgYMTExsLKyMmrMOVV6notJkyahZ8+e+OKLLwAAVapUQUREBAYMGICJEyfqLBJOxpXS97eDg0Oaa4OAHFYjZGVlBQ8PDxw4cEBbptFocODAAdStWzfZY+rWrauzPwDs27cvxf0pbdLzXADA999/j+nTp2Pv3r2oUaNGZoRqEvR9PsqXL49Lly7h/Pnz2r9PP/0UTZs2xfnz5+Hq6pqZ4eco6Xlv1K9fH7dv39YmowBw8+ZNFC5cmElQBqTnuXj37l2SZCc+QRVcujNTGez7W79+3Fnfpk2bhLW1tfD39xdXr14VAwYMEHny5BHBwcFCCCF69uwpxo0bp93/2LFjwsLCQvzwww/i2rVrwtfXl8PnDUTf52LWrFnCyspKbN26VTx9+lT79/btW6XuQo6i7/PxPo4aMxx9n4sHDx4Ie3t7MXToUHHjxg3xxx9/iIIFC4rvvvtOqbuQY+j7XPj6+gp7e3uxceNGcffuXfH333+LUqVKiS5duih1F3KMt2/finPnzolz584JAGLevHni3Llz4v79+0IIIcaNGyd69uyp3T9++PyYMWPEtWvXxOLFizl8Pt5PP/0kihUrJqysrEStWrXEiRMntNc1btxY+Pj46Oy/efNmUbZsWWFlZSUqVaokdu/enckR51z6PBfFixcXAJL8+fr6Zn7gOZS+743EmAgZlr7PxX///Sdq164trK2tRcmSJcWMGTNEXFxcJkedM+nzXMTGxoopU6aIUqVKCRsbG+Hq6ioGDx4sXr9+nfmB5zCHDh1K9jsg/vH38fERjRs3TnKMu7u7sLKyEiVLlhSrV6/W+3ZVQrAuj4iIiExTjuojRERERKQPJkJERERkspgIERERkcliIkREREQmi4kQERERmSwmQkRERGSymAgRERGRyWIiREQ6/P39kSdPHqXDSDeVSoUdO3akuk/v3r3Rvn37TImHiLI2JkJEOVDv3r2hUqmS/N2+fVvp0ODv76+Nx8zMDEWLFkWfPn3w7Nkzg5z/6dOnaNWqFQAgKCgIKpUK58+f19ln4cKF8Pf3N8jtpWTKlCna+2lubg5XV1cMGDAAr1690us8TNqIjCtHrT5PRAlatmyJ1atX65Q5OTkpFI0uBwcH3LhxAxqNBhcuXECfPn3w5MkT/PXXXxk+d0qrhifm6OiY4dtJi0qVKmH//v1Qq9W4du0a+vbti9DQUAQEBGTK7RPRh7FGiCiHsra2hrOzs86fubk55s2bhypVqiBXrlxwdXXF4MGDER4enuJ5Lly4gKZNm8Le3h4ODg7w8PDAmTNntNcfPXoUDRs2hK2tLVxdXTF8+HBERESkGptKpYKzszOKFCmCVq1aYfjw4di/fz8iIyOh0Wgwbdo0FC1aFNbW1nB3d8fevXu1x8bExGDo0KEoXLgwbGxsULx4cfj5+emcO75prESJEgCAjz76CCqVCk2aNAGgW8uybNkyFClSRGdldwBo164d+vbtq93+/fffUb16ddjY2KBkyZKYOnUq4uLiUr2fFhYWcHZ2houLCzw9PdG5c2fs27dPe71arUa/fv1QokQJ2Nraoly5cli4cKH2+ilTpuDXX3/F77//rq1dOnz4MADg4cOH6NKlC/LkyYN8+fKhXbt2CAoKSjUeIkqKiRCRiTEzM8OPP/6IK1eu4Ndff8XBgwfxzTffpLh/jx49ULRoUZw+fRqBgYEYN24cLC0tAQB37txBy5Yt8dlnn+HixYsICAjA0aNHMXToUL1isrW1hUajQVxcHBYuXIi5c+fihx9+wMWLF+Hl5YVPP/0Ut27dAgD8+OOP2LlzJzZv3owbN25g/fr1cHNzS/a8p06dAgDs378fT58+xfbt25Ps07lzZ7x8+RKHDh3Slr169Qp79+5Fjx49AABHjhxBr169MGLECFy9ehVLly6Fv78/ZsyYkeb7GBQUhL/++gtWVlbaMo1Gg6JFi2LLli24evUqJk+ejAkTJmDz5s0AgNGjR6NLly5o2bIlnj59iqdPn6JevXqIjY2Fl5cX7O3tceTIERw7dgy5c+dGy5YtERMTk+aYiAjIkavPE5k6Hx8fYW5uLnLlyqX969SpU7L7btmyReTPn1+7vXr1auHo6Kjdtre3F/7+/ske269fPzFgwACdsiNHjggzMzMRGRmZ7DHvn//mzZuibNmyokaNGkIIIYoUKSJmzJihc0zNmjXF4MGDhRBCDBs2TDRr1kxoNJpkzw9A/Pbbb0IIIe7duycAiHPnzuns4+PjI9q1a6fdbteunejbt692e+nSpaJIkSJCrVYLIYRo3ry5mDlzps451q5dKwoXLpxsDEII4evrK8zMzESuXLmEjY2NdiXtefPmpXiMEEIMGTJEfPbZZynGGn/b5cqV03kMoqOjha2trfjrr79SPT8R6WIfIaIcqmnTpvjll1+027ly5QIga0f8/Pxw/fp1hIWFIS4uDlFRUXj37h3s7OySnGfUqFH44osvsHbtWm3zTqlSpQDIZrOLFy9i/fr12v2FENBoNLh37x4qVKiQbGyhoaHInTs3NBoNoqKi0KBBA6xYsQJhYWF48uQJ6tevr7N//fr1ceHCBQCyWevjjz9GuXLl0LJlS3zyySdo0aJFhh6rHj16oH///vj5559hbW2N9evXo2vXrjAzM9Pez2PHjunUAKnV6lQfNwAoV64cdu7ciaioKKxbtw7nz5/HsGHDdPZZvHgxVq1ahQcPHiAyMhIxMTFwd3dPNd4LFy7g9u3bsLe31ymPiorCnTt30vEIEJkuJkJEOVSuXLlQunRpnbKgoCB88sknGDRoEGbMmIF8+fLh6NGj6NevH2JiYpL9Qp8yZQq6d++O3bt3488//4Svry82bdqEDh06IDw8HF9++SWGDx+e5LhixYqlGJu9vT3Onj0LMzMzFC5cGLa2tgCAsLCwD96v6tWr4969e/jzzz+xf/9+dOnSBZ6enti6desHj01J27ZtIYTA7t27UbNmTRw5cgTz58/XXh8eHo6pU6eiY8eOSY61sbFJ8bxWVlba52DWrFlo06YNpk6diunTpwMANm3ahNGjR2Pu3LmoW7cu7O3tMWfOHJw8eTLVeMPDw+Hh4aGTgMbLKh3iibILJkJEJiQwMBAajQZz587V1nbE90dJTdmyZVG2bFmMHDkS3bp1w+rVq9GhQwdUr14dV69eTZJwfYiZmVmyxzg4OKBIkSI4duwYGjdurC0/duwYatWqpbOft7c3vL290alTJ7Rs2RKvXr1Cvnz5dM4X3x9HrVanGo+NjQ06duyI9evX4/bt2yhXrhyqV6+uvb569eq4ceOG3vfzfd9++y2aNWuGQYMGae9nvXr1MHjwYO0+79foWFlZJYm/evXqCAgIQMGCBeHg4JChmIhMHTtLE5mQ0qVLIzY2Fj/99BPu3r2LtWvXYsmSJSnuHxkZiaFDh+Lw4cO4f/8+jh07htOnT2ubvMaOHYv//vsPQ4cOxfnz53Hr1i38/vvveneWTmzMmDGYPXs2AgICcOPGDYwbNw7nz5/HiBEjAADz5s3Dxo0bcf36ddy8eRNbtmyBs7NzspNAFixYELa2tti7dy9CQkIQGhqa4u326NEDu3fvxqpVq7SdpONNnjwZa9aswdSpU3HlyhVcu3YNmzZtwrfffqvXfatbty6qVq2KmTNnAgDKlCmDM2fO4K+//sLNmzcxadIknD59WucYNzc3XLx4ETdu3MCLFy8QGxuLHj16oECBAmjXrh2OHDmCe/fu4fDhwxg+fDgePXqkV0xEJk/pTkpEZHjJdbCNN2/ePFG4cGFha2srvLy8xJo1awQA8fr1ayGEbmfm6Oho0bVrV+Hq6iqsrKxEkSJFxNChQ3U6Qp86dUp8/PHHInfu3CJXrlyiatWqSTo7J/Z+Z+n3qdVqMWXKFOHi4iIsLS1FtWrVxJ9//qm9ftmyZcLd3V3kypVLODg4iObNm4uzZ89qr0eiztJCCLF8+XLh6uoqzMzMROPGjVN8fNRqtShcuLAAIO7cuZMkrr1794p69eoJW1tb4eDgIGrVqiWWLVuW4v3w9fUV1apVS1K+ceNGYW1tLR48eCCioqJE7969haOjo8iTJ48YNGiQGDdunM5xz5490z6+AMShQ4eEEEI8ffpU9OrVSxQoUEBYW1uLkiVLiv79+4vQ0NAUYyKipFRCCKFsKkZERESkDDaNERERkcliIkREREQmi4kQERERmSwmQkRERGSymAgRERGRyWIiRERERCaLiRARERGZLCZCREREZLKYCBEREZHJYiJEREREJouJEBEREZksJkJERERksv4HvyVELbadAYYAAAAASUVORK5CYII=", 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", 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" ] @@ -251,77 +245,87 @@ "len(data.corpus) 780\n", "len(data.test_inlier) 363\n", "len(data.test_outlier) 3135\n", - "fit_time: 1.308121681213379\n", - "compute_auc_time: 6.258044958114624\n", + "fit_time: 1.3745968341827393\n", + "compute_auc_time: 6.313787221908569\n", "depth: 2 , Auc of digit: 0 is 0.9994156440437432\n", "doing digit 1 doing signature level 2\n", "len(data.corpus) 779\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.3163371086120605\n", - "compute_auc_time: 6.049156904220581\n", + "fit_time: 1.3893768787384033\n", + "compute_auc_time: 6.167309761047363\n", "depth: 2 , Auc of digit: 1 is 0.882206498032918\n", "doing digit 2 doing signature level 2\n", "len(data.corpus) 780\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.311708927154541\n", - "compute_auc_time: 6.092707872390747\n", + "fit_time: 1.3798871040344238\n", + "compute_auc_time: 6.319882392883301\n", "depth: 2 , Auc of digit: 2 is 0.9511227445177669\n", "doing digit 3 doing signature level 2\n", "len(data.corpus) 719\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.1984961032867432\n", - "compute_auc_time: 6.022700786590576\n", + "fit_time: 1.27274489402771\n", + "compute_auc_time: 6.294939994812012\n", "depth: 2 , Auc of digit: 3 is 0.9886656275413391\n", "doing digit 4 doing signature level 2\n", "len(data.corpus) 780\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.3563220500946045\n", - "compute_auc_time: 6.444512128829956\n", + "fit_time: 1.3157386779785156\n", + "compute_auc_time: 6.4051289558410645\n", "depth: 2 , Auc of digit: 4 is 0.9971212578104729\n", "doing digit 5 doing signature level 2\n", "len(data.corpus) 720\n", "len(data.test_inlier) 335\n", "len(data.test_outlier) 3163\n", - "fit_time: 1.2241871356964111\n", - "compute_auc_time: 6.081561088562012\n", + "fit_time: 1.2873790264129639\n", + "compute_auc_time: 6.221255779266357\n", "depth: 2 , Auc of digit: 5 is 0.9647887656249261\n", "doing digit 6 doing signature level 2\n", "len(data.corpus) 720\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.226757287979126\n", - "compute_auc_time: 6.031784296035767\n", + "fit_time: 1.2547879219055176\n", + "compute_auc_time: 6.341688871383667\n", "depth: 2 , Auc of digit: 6 is 0.9924061022258366\n", "doing digit 7 doing signature level 2\n", "len(data.corpus) 778\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.324833869934082\n", - "compute_auc_time: 6.246238946914673\n", + "fit_time: 1.333056926727295\n", + "compute_auc_time: 6.299951076507568\n", "depth: 2 , Auc of digit: 7 is 0.9607328695554606\n", "doing digit 8 doing signature level 2\n", "len(data.corpus) 719\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.1929960250854492\n", - "compute_auc_time: 6.09051513671875\n", + "fit_time: 1.288444995880127\n", + "compute_auc_time: 6.317756175994873\n", "depth: 2 , Auc of digit: 8 is 0.9951771030993043\n", "doing digit 9 doing signature level 2\n", "len(data.corpus) 719\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.4631941318511963\n", - "compute_auc_time: 6.044775009155273\n", + "fit_time: 1.2493579387664795\n", + "compute_auc_time: 6.216753244400024\n", "depth: 2 , Auc of digit: 9 is 0.8993403813138158\n" ] }, { "data": { - "image/png": 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", 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", 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", 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" ] @@ -338,77 +342,87 @@ "len(data.corpus) 780\n", "len(data.test_inlier) 363\n", "len(data.test_outlier) 3135\n", - "fit_time: 1.342965841293335\n", - "compute_auc_time: 6.445879936218262\n", + "fit_time: 1.4438748359680176\n", + "compute_auc_time: 6.563769817352295\n", "depth: 3 , Auc of digit: 0 is 0.9978321712119015\n", "doing digit 1 doing signature level 3\n", "len(data.corpus) 779\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.4032697677612305\n", - "compute_auc_time: 6.378614664077759\n", + "fit_time: 1.415640115737915\n", + "compute_auc_time: 6.474632024765015\n", "depth: 3 , Auc of digit: 1 is 0.970122092330133\n", "doing digit 2 doing signature level 3\n", "len(data.corpus) 780\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.4213371276855469\n", - "compute_auc_time: 6.583529949188232\n", + "fit_time: 1.3865909576416016\n", + "compute_auc_time: 6.617231845855713\n", "depth: 3 , Auc of digit: 2 is 0.9907229815494015\n", "doing digit 3 doing signature level 3\n", "len(data.corpus) 719\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.3599779605865479\n", - "compute_auc_time: 6.415704965591431\n", + "fit_time: 1.4027378559112549\n", + "compute_auc_time: 6.600866794586182\n", "depth: 3 , Auc of digit: 3 is 0.9952787566639559\n", "doing digit 4 doing signature level 3\n", "len(data.corpus) 780\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.3847181797027588\n", - "compute_auc_time: 6.45753288269043\n", + "fit_time: 1.4259991645812988\n", + "compute_auc_time: 6.604549884796143\n", "depth: 3 , Auc of digit: 4 is 0.9998316935138888\n", "doing digit 5 doing signature level 3\n", "len(data.corpus) 720\n", "len(data.test_inlier) 335\n", "len(data.test_outlier) 3163\n", - "fit_time: 1.3755779266357422\n", - "compute_auc_time: 6.4378650188446045\n", + "fit_time: 1.4912703037261963\n", + "compute_auc_time: 6.5209479331970215\n", "depth: 3 , Auc of digit: 5 is 0.9819583712798636\n", "doing digit 6 doing signature level 3\n", "len(data.corpus) 720\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.259742021560669\n", - "compute_auc_time: 6.417846918106079\n", + "fit_time: 1.4395511150360107\n", + "compute_auc_time: 6.649335145950317\n", "depth: 3 , Auc of digit: 6 is 0.9945587105810065\n", "doing digit 7 doing signature level 3\n", "len(data.corpus) 778\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.3221640586853027\n", - "compute_auc_time: 6.397592067718506\n", + "fit_time: 1.3501660823822021\n", + "compute_auc_time: 6.567941904067993\n", "depth: 3 , Auc of digit: 7 is 0.9778264970511301\n", "doing digit 8 doing signature level 3\n", "len(data.corpus) 719\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.28696608543396\n", - "compute_auc_time: 6.392870903015137\n", + "fit_time: 1.467175006866455\n", + "compute_auc_time: 6.605494022369385\n", "depth: 3 , Auc of digit: 8 is 0.9984290759314479\n", "doing digit 9 doing signature level 3\n", "len(data.corpus) 719\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.286924123764038\n", - "compute_auc_time: 6.4979729652404785\n", + "fit_time: 1.4061648845672607\n", + "compute_auc_time: 6.380589962005615\n", "depth: 3 , Auc of digit: 9 is 0.9264809418391013\n" ] }, { "data": { - "image/png": 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", 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", 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", 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" ] @@ -425,77 +439,87 @@ "len(data.corpus) 780\n", "len(data.test_inlier) 363\n", "len(data.test_outlier) 3135\n", - "fit_time: 1.4814271926879883\n", - "compute_auc_time: 6.84686803817749\n", + "fit_time: 1.4975659847259521\n", + "compute_auc_time: 6.91232705116272\n", "depth: 4 , Auc of digit: 0 is 0.9949666301993401\n", "doing digit 1 doing signature level 4\n", "len(data.corpus) 779\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.472062110900879\n", - "compute_auc_time: 6.747668981552124\n", + "fit_time: 1.502849817276001\n", + "compute_auc_time: 6.871154069900513\n", "depth: 4 , Auc of digit: 1 is 0.9852398718065597\n", "doing digit 2 doing signature level 4\n", "len(data.corpus) 780\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.555401086807251\n", - "compute_auc_time: 6.726560831069946\n", + "fit_time: 1.708885908126831\n", + "compute_auc_time: 7.093451976776123\n", "depth: 4 , Auc of digit: 2 is 0.9894510403444672\n", "doing digit 3 doing signature level 4\n", "len(data.corpus) 719\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.5977261066436768\n", - "compute_auc_time: 6.752060890197754\n", + "fit_time: 1.5545158386230469\n", + "compute_auc_time: 7.326997995376587\n", "depth: 4 , Auc of digit: 3 is 0.9959752718291617\n", "doing digit 4 doing signature level 4\n", "len(data.corpus) 780\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.5598111152648926\n", - "compute_auc_time: 6.753681182861328\n", + "fit_time: 1.5915489196777344\n", + "compute_auc_time: 7.074462890625\n", "depth: 4 , Auc of digit: 4 is 0.999876399924262\n", "doing digit 5 doing signature level 4\n", "len(data.corpus) 720\n", "len(data.test_inlier) 335\n", "len(data.test_outlier) 3163\n", - "fit_time: 1.5049867630004883\n", - "compute_auc_time: 7.039808034896851\n", + "fit_time: 1.531661033630371\n", + "compute_auc_time: 6.867708921432495\n", "depth: 4 , Auc of digit: 5 is 0.9878785018945739\n", "doing digit 6 doing signature level 4\n", "len(data.corpus) 720\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.3394172191619873\n", - "compute_auc_time: 6.674200057983398\n", + "fit_time: 1.3417651653289795\n", + "compute_auc_time: 6.920623779296875\n", "depth: 4 , Auc of digit: 6 is 0.9949408526851601\n", "doing digit 7 doing signature level 4\n", "len(data.corpus) 778\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.553976058959961\n", - "compute_auc_time: 6.760324954986572\n", + "fit_time: 1.7207341194152832\n", + "compute_auc_time: 6.845315933227539\n", "depth: 4 , Auc of digit: 7 is 0.9857894976752666\n", "doing digit 8 doing signature level 4\n", "len(data.corpus) 719\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.4829590320587158\n", - "compute_auc_time: 7.0328850746154785\n", + "fit_time: 1.491410255432129\n", + "compute_auc_time: 6.841398000717163\n", "depth: 4 , Auc of digit: 8 is 0.998694504683594\n", "doing digit 9 doing signature level 4\n", "len(data.corpus) 719\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.5755929946899414\n", - "compute_auc_time: 6.970922946929932\n", + "fit_time: 1.2827157974243164\n", + "compute_auc_time: 6.803714990615845\n", "depth: 4 , Auc of digit: 9 is 0.9442176063973977\n" ] }, { "data": { - "image/png": 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oER48eAClUql1fLFixTS1ix9KzzkOHTqEd+/eYfz48ckGG3zqlyqg+/9Ho0aNUL58+U+e18HBAf/++y+ePXv2yX0/5eXLlzhx4gS+/vprFC1aVOu29DxGAPDz84OTkxOcnZ3RuHFj3L9/H3PnzkWHDh0QFBSEu3fvonv37nj16pXmOYiKikKzZs1w4sSJZKO50vMeyIjEmo3E//2UBAYGwtXVFV988YWmzMLCAv3798/Ufafk1atXAJDs/ynxc2T48OFa5R/X7mTk87FXr15a/5OdOnWCi4uL5j7T41OfHYn3c+jQoU9eNm3apHXugIAAXL16Nd21f4nPXW6cdoNNY1lk2bJlKF26NJRKJdauXYsTJ07A3Nxcc/u9e/cghMCUKVMwZcqUFM/x4sULuLq64v79++jYsWOa93f37l3cvHkTTk5OqZ4rNVWqVEHZsmWxdetW9O3bF4DULObo6Kj5onj58iXevn2LlStXYuXKlem6j2LFiqUZc6LED4N3797BwcEhxX1SS5ZKlSqVbN/SpUtj27ZtAHR7ntOKOzo6Gv7+/li3bh2ePn2qNZz/4y98XX38pZf4gfLmzRsAwMOHDwEAJUuW1NrPxMQkXXOnJI7MSetLR9e4Es95+vRp+Pn54cyZM8mq35VKJezt7TXbqb0f0nOOxCaeihUr6vQYEun6/5He9+4PP/wAX19fuLm5wdPTE61bt0avXr1QvHhxnWNM/PLK6GMEgAEDBqBz584wMjKCg4MDKlSooPncuXv3LgAkawL/kFKp1EoG0vMeyIjEeXrSSs4fPnyIEiVKJEsCP/4/0KcP/68TYzAyMkKJEiW0yhObdRNl5PPx488uhUKBkiVL6jT1xqc+OwCgePHiOr8fIyIiMGHCBIwdOxZubm7pOibxuUtv0p6TMBHKIrVq1UKNGjUASLUW9evXR/fu3XH79m3Y2NhofnmNGTMmxV/JgG7/8Gq1GpUqVcLChQtTvP1Tb2YfHx/MmjUL4eHhsLW1xd69e9GtWzdNDURivF999VWqH6Qft8GnpzYIkPrQ/P7777hy5QoaNmyY4j5XrlwBgHT9Sv9QRp7nlOIeNmwY1q1bh5EjR6JOnTqwt7eHQqFA165dMz0nSmpTAnz8oZxRZcuWBQBcvXpVpyHUn4rr/v37aNasGcqWLYuFCxfCzc0NZmZm2L9/PxYtWpTseUnpedX1HBml6/9Het+7Xbp0QYMGDbB792789ddfmDdvHubOnYtdu3ahVatWmY5bV6VKldLqQ/ehxOdy3rx5qb4PPu6DklXvzWvXrgHI2qRGF4l9qN68eZOhKSQy8vmoD+l5fSIjI9M1QaSxsbHmh8L8+fMRFxcHHx8fTWL25MkTANJzFBISgsKFC2vVRiUmX46Ojhl6LHJiIpQNjI2N4e/vjyZNmmDp0qUYP368JkM3NTVN9YMrUYkSJTQfHGntc/nyZTRr1ixDGbmPjw+mT5+OnTt3olChQoiIiEDXrl01tzs5OcHW1hYqleqT8erq888/h7+/PzZs2JBiIqRSqfDbb78hX758qFevntZtib9yP3Tnzh1NTYkuz3NaduzYAV9fXyxYsEBTFhMTg7dv32rtlxW/htzd3QFItVtNmjTRlCckJCAkJOSTH7CtWrWCsbExfv31V507TKfljz/+QGxsLPbu3av1y/RTnVkzco7EX+TXrl1L88sztec/s/8faXFxccHgwYMxePBgvHjxAtWrV8esWbM0iVB67y/xvfqp//WMSnwO7ezs9P4/rKuNGzdCoVCgefPmqe7j7u6OGzduQAih9Rzeu3fvk+fX9TVO/LEQHByMSpUqacWgVqtx//59rVqg27dvax2fkc/Hjz+7hBC4d++e1v+zPt6r8+fP18yplBZ3d3dN0vPo0SO8efMGFSpUSLbf7NmzMXv2bFy6dEkroQ4ODoajo2Oqta45GfsIZZPGjRujVq1aWLx4MWJiYlCwYEE0btwYK1aswPPnz5Pt/+F05R07dsTly5exe/fuZPslZv5dunTB06dPsWrVqmT7REdHa0Y/paZcuXKoVKkStm7diq1bt8LFxUUrKTE2NkbHjh2xc+fOFD+oMzO9et26deHl5YV169bhzz//THb7pEmTcOfOHXz33XfJfqn//vvvWn18zp07h3///VfzJaTL85wWY2PjZL+Cf/rpJ6hUKq0ya2trAEiWIGVGjRo1UKBAAaxatQoJCQma8k2bNmlVgafGzc0N/fv3x19//YWffvop2e1qtRoLFizQ/OJLr8Rfox83E65bt07v52jRogVsbW3h7++PmJgYrds+PNba2jrFpsrM/n+kRKVSJbuvggULonDhwoiNjf1kTB9zcnJCw4YNsXbt2mST1+mjdtDT0xMlSpTA/PnzU6whyK4lEubMmYO//voLPj4+KTZtJ/L29sbTp0+xd+9eTVlMTEyKr+HHrKysAKT//9DT0xNmZmbJZlhP/Bz58ccftco/nu05I5+PiSNeE+3YsQPPnz/XqklM73snLRnpIzR8+HDs3r1b67JixQoA0qzhu3fvTtZ8fOHCBdSpUydTscqFNULZaOzYsejcuTMCAgIwcOBALFu2DPXr10elSpXQv39/FC9eHGFhYThz5gyePHmCy5cva47bsWMHOnfujK+//hqenp54/fo19u7di+XLl6NKlSro2bMntm3bhoEDB+LYsWOoV68eVCoVbt26hW3btuHgwYOaprrU+Pj4YOrUqbCwsEDfvn2TzT49Z84cHDt2DLVr10b//v1Rvnx5vH79GhcvXsThw4fx+vXrDD83GzZsQLNmzfDll1+ie/fuaNCgAWJjY7Fr1y4cP34cPj4+GDt2bLLjSpYsifr162PQoEGIjY3F4sWLUaBAAXz33XeafdL7PKfl888/x8aNG2Fvb4/y5cvjzJkzOHz4sKZKPVHVqlVhbGyMuXPnQqlUwtzcHE2bNkXBggUz/NyYmZlh2rRpGDZsGJo2bYouXbogJCQEAQEBKfahSMmCBQtw//59DB8+HLt27cLnn3+OfPny4dGjR9i+fTtu3bqlVQOYHi1atICZmRnatm2Lb775BpGRkVi1ahUKFiyYYtKZmXPY2dlh0aJF6NevH2rWrInu3bsjX758uHz5Mt6/f4/169cDkL7Qtm7ditGjR6NmzZqwsbFB27Zt9fL/8bF3796hSJEi6NSpE6pUqQIbGxscPnwY58+f16o5TC2mlPz444+oX78+qlevjgEDBqBYsWIICQnBvn37Mr1UhpGREVavXo1WrVqhQoUK6NOnD1xdXfH06VMcO3YMdnZ2mqks9CEhIQG//vorACmBefjwIfbu3YsrV66gSZMmqfalSfTNN99g6dKl6NatG0aMGAEXFxds2rRJ01k+rfe9paUlypcvj61bt6J06dLInz8/KlasmGr/KwsLC7Ro0QKHDx/GjBkzNOVVq1ZFt27d8PPPP0OpVKJu3bo4cuRIirVSun4+5s+fH/Xr10efPn0QFhaGxYsXo2TJklqdwXV576QmI32EqlevnmwqgcTaogoVKqBdu3Zat7148QJXrlxJNmVGrpGtY9QMQGoTKgohzVBbokQJUaJECc3w7Pv374tevXoJZ2dnYWpqKlxdXcXnn38uduzYoXXsq1evxNChQ4Wrq6tmMjhfX1+toZpxcXFi7ty5okKFCsLc3Fzky5dPeHp6iunTpwulUqnZ7+Ph84nu3r2rGUr58QRricLCwsSQIUOEm5ubMDU1Fc7OzqJZs2Zi5cqVmn0yOuvpu3fvxLRp00SFChWEpaWlsLW1FfXq1RMBAQHJhg9/OJRzwYIFws3NTZibm4sGDRqIy5cvJzt3ep7ntF67N2/eiD59+mgmVfP29ha3bt1K8blctWqVKF68uDA2Nk7XhIofP0+pTbT3448/Cnd3d2Fubi5q1aolTp8+LTw9PUXLli3T8exKM0ivXr1aNGjQQNjb2wtTU1Ph7u4u+vTpozW0PrWZpROfnw8nkdy7d6+oXLmysLCwEB4eHmLu3Lli7dq1yfZLnFAxJek9R+K+devWFZaWlsLOzk7UqlVLbN68WXN7ZGSk6N69u3BwcEg2JDi9/x/4/4SKKcEHQ6ZjY2PF2LFjRZUqVYStra2wtrYWVapUSTYZZGoxpfY6X7t2TbRv3144ODgICwsLUaZMGTFlypQU40n0qaHNH7p06ZLo0KGDKFCggDA3Nxfu7u6iS5cu4siRI5p9dHkPpMTX11draLaVlZXw8PAQHTt2FDt27EhxlvmUJlR88OCBaNOmjbC0tBROTk7i22+/FTt37hQAxNmzZ7Xu7+Ph3//884/w9PQUZmZm6RpKv2vXLqFQKLQmNRRCGrI/fPhwUaBAAWFtbZ3mhIq6fD5u3rxZTJgwQRQsWFBYWlqKNm3aJJs2IbX3jq6fHfqQ1nvsl19+EVZWVlrTAeQmCiFyyWqWRB8ICQlBsWLFMG/ePIwZM0bucGShVqvh5OSEDh06pKu5gCgvWLx4MUaNGoUnT55ojfbMLJVKhfLly6NLly6YOXOm3s77sePHj6NJkybYvn07OnXqlGX3k52qVauGxo0bayZ+zG3YR4goF4iJiUnWT2TDhg14/fp1uheVJMptoqOjtbZjYmKwYsUKlCpVSq9JECD185kxYwaWLVuWrlFWJAkMDMTdu3cxYcIEuUPJMPYRIsoFzp49i1GjRqFz584oUKAALl68iDVr1qBixYro3Lmz3OERZYkOHTqgaNGiqFq1KpRKJX799VfcunUr2eR/+uLj46OZRJbSp2XLlrk+cWQiRJQLeHh4wM3NDT/++CNev36N/Pnzo1evXpgzZ06qa7gR5Xbe3t5YvXo1Nm3apGm62rJlC5MV0itZ+widOHEC8+bNw4ULF/D8+XPs3r07WW/0jx0/fhyjR4/G9evX4ebmhsmTJ6N3797ZEi8RERHlLbL2EYqKikKVKlWwbNmydO0fHByMNm3aoEmTJggKCsLIkSPRr18/HDx4MIsjJSIiorwox4waUygUn6wRGjduHPbt26c1YVXXrl3x9u1bBAYGZkOURERElJfkqj5CZ86cSTZ9ube3d7KVgD8UGxurNcurWq3G69evUaBAgVy5OBwREZEhEkLg3bt3KFy4cLIJfzMjVyVCoaGhKFSokFZZ4rpY0dHRKS6U6O/vn651VoiIiCjne/z4cYYWx01NrkqEMmLChAkYPXq0ZlupVKJo0aJ4/Pgx7OzsZIyMcjO1GoiJkS5KJRAdDbx8CahUwJMngJERcP06YGcHPH4s7WdpCcTGAufOASVLSmUXLgCuroBCAcTHAy9eSOeytgYSEqQyPS3AnqsoFEBio72NjfR8GhlJ5YnXU7sEBwNlyyZtGxunvq9aDdy9C1SpIp078fy6XP/wAkjnq1gx5f0Sf8R+XPap7fh4IDwcKFo07X1Tuu3j+0vp2HfvADMz6bn+8JgP/6ZUlp6/WXFMSvEoFNL/jJGR9L+W0nsqJSmV67Kvvs6dmuyOW47Hnla5zdE9iKrTHMLSCpGREWjWzA22trYpH5BBuSoRcnZ2RlhYmFZZWFgY7OzsUqwNAgBzc3OYm5snK7ezs2MiZMBevwYePgT+/Vf6Mnz2DHj1SkpAwsOlL9PQUGlbCCAoCHB2BuLipGMz6+HDpOv37ye/PT1rgJqYSF/yiX/j46UkqmRJ6Qvh5UugWjXA1DTpcuMGUKuWdN3EJOnvgwfSviYm2uWxsdLjd3HRPs+7d0ChQskTjZSux8cDtrbS9ofxJl7MzAALi6T7NjFJShiIyEBFRQFDhgDr1wP9+gGrViEiQrpJ391aclUiVKdOHezfv1+r7NChQ7l2xVvSjVoNvH8v/X9EREhJSUyMVOOSkCDVwDx+LP2qjYwELl6UfkEHB0u1Nvb2wJUrGb//0NC0b3dykpKpmjWl+2zUSDqmZk0pVnNzoEgR6W9EBFC8uJQAxMVJx5qZSUmGkZGUOJiZaSclJibSsUwUiChPu3YN6NIFuHlT+rArWjSpijgLyJoIRUZGaq3iGxwcjKCgIOTPnx9FixbFhAkT8PTpU2zYsAEAMHDgQCxduhTfffcdvv76axw9ehTbtm3Dvn375HoIpKMPa18iI6XE5cYNqczSEjh9GvDwkGo2/v5bShauX8/4/V26lPbtHh5ASAjQq5cUm1oNlCiRVM3u5ASUKpVUo5E/v5S8mJtLzV6WllI5ERFlkhDA2rXAsGHSl4CLC/Dbb0AWLyMkayL033//oUmTJprtxL48vr6+CAgIwPPnz/Ho0SPN7cWKFcO+ffswatQoLFmyBEWKFMHq1avh7e2d7bGTRAgpqVEqgXv3gDdvpGTexga4fVuqwTl1SmqmEUJKLj7lw+TlU0lQkSJSzUlwMNCiBfD2rfS/U62aVB4VBZQuLSU2dnZAgQKAlRXg7i4lNURElANERgIDBwKJy6e0aAFs3AgULJjld51j5hHKLhEREbC3t4dSqWQfoU94/x64c0fqP3L3rlRzYmICHD8u1eJkthNviRJSchQTI/W/KVMGqFxZSqrKlpVqXQApabG2BhwdAQcHqUaGTUNERHnIkydA1arSr9nvvwe++y7ZB31WfX/nqj5CpF+RkcBff0k1OadOSc0/Bw9KtSgxMbqfz9FR6mjctq30nq5bV+oo6+YmJTqlSknJT6FCUr8XIiIiAFL1/ubNUn+D+vWz9a6ZCOVhQkhNUv/8IzUxnT4NPHoEPH0qJd3pZWoqNSm5u0t/a9WSRhOVLy9dypaVmpuIiIjSJSICGDAA6NoVSFxRonlzWUJhIpQHqNVSDcyePdIw76NHpWYsXXTpIvWpqV9fav4qXlxqqnJx0X3eCyIiolRduAD4+Ehzhxw7JvUHkvHXNBOhXOjRI2DbNmDBgk8P6f5Qw4ZSrU716tKEb5UqSc1UREREWU4IYOlSYMwYad4Qd3dgyxbZmxSYCOVwQkiT/m3cCPz3nzQrcVqMjYFWraSkp0kTqfOxmVn2xEpERJSit2+Bvn2BXbuk7XbtpKHy+fLJGRUAJkI5khDAn38CY8dKQ9BTU6aMNIvwhAlA7dpSkxYREVGO8vatNKdJSIjU6XT+fGmuoBzS74JfnTlEfLxU8zNihDQjckqcnaW+PO3aSbU9REREOZ6Dg9RUcfAgsHUrUKOG3BFpYSIko/h4qakrrZGCQ4YAkydLSRAREVGu8OqVNINuYkfUhQul4cb29vLGlQImQjJp2lTqLP8xCwupE/POndL8O0RERLnKP/9Iw+JLlgQOHZI6r1pYSJcciIlQNouJkeaL+liVKlKTGGdMJiKiXEmtBubNAyZNAlQqaXmA58+lyRJzMH7tZpO//pL6hX2cBD1+LHWODgpiEkRERLnUy5fA558D48dLSVC3btKv+xyeBAFMhLKUEMDixVIClNK6sGp1rniPEBERpe7kSWmdsAMHpOavlSulxVNtbeWOLF2YCGWRmTOlGp5Ro7TLv/lGmllciBwzcpCIiChjVCpg8GDg2TNpvaVz54D+/XPVFxz7COnZtWvSzM3x8drlAwdKtUOJK6oTERHlesbG0mKpS5YAixYBNjZyR6Qz1gjp0bp10oivD5Ogkyel2p9ffmESREREecDRo8CKFUnbFSsCq1blyiQIYI2Q3nxcCzhokJQcM/khIqI8QaUCZsyQ+n4YGwOenjlucsSMYCKUSUIkH+11+jRQt6488RAREends2dAjx7A8ePSdu/eQPnyckakN2way4STJ5MnQdHRTIKIiCgPOXhQGhV2/LjU/LVpk9QUJvOq8frCRCiDTp2SVnj/UFxcjp04k4iISHfTpgEtW0rzBFWpAly4AHTvLndUesVEKANOnAAaNEjaHjZMaiIzNZUvJiIiIr1zcJD+DhwInD0LlC4tazhZgX2EdOTjA2zblrS9YQPQs6d88RAREelVVBRgbS1dHzECqFYNaNRI3piyEGuEdPDokXYS5OfHJIiIiPKI+Hhg7FhpMrx376QyhSJPJ0EAa4TSTQjA3T1pOzwcKFBAvniIiIj05uFDacX4s2el7d9/N5hf+qwRSqcPR4dVr84kiIiI8og9e6RRYWfPAvb2wM6dBpMEAUyE0iUhQXv7wgV54iAiItKbuDhg5EigXTvg7VugVi3g0iWgQweZA8teTITSYfv2pOtv38oWBhERkf6MGyetEQYA334rTY5XrJi8MclAIYQQcgeRnSIiImBvbw+lUgk7O7t0HfPh8hmG9WwREVGeFRYGNGsG+PsDbdvKHc0nZeT7Oz1YI/QJJ04kXedkiURElGvFxEgrxScqVAi4ciVXJEFZiaPGPuHDUYMREfLFQURElGF37wJdugBBQdJ2t27S34/XiTJAfAbSsHVr0vU2bThzNBER5UKbN0vDnYOCAEdHIH9+uSPKUZgIpaFr16Trq1fLFwcREZHOoqOBAQOktcEiI6UFMoOCAG9vuSPLUZgIpeLvv5OujxwJODvLFgoREZFubt0CateWVolXKIDJk4EjRwBXV7kjy3HYRygVP/+cdP2HH+SLg4iISGf37wNXrwIFCwKbNgFeXnJHlGMxEUpFYtJcty77BhERUS7Tpo1UG9SmDeDiInc0ORqbxlKROGy+YUN54yAiIvqk69eBBg2kNcMS9evHJCgdmAilInEZjWfP5I2DiIgoVUIAa9cCNWsCp05JnVpJJ2wa+4QP5xEiIiLKMSIjgYEDpT5AANCiBbBihbwx5UKsEUrB8uVJ11u2lC8OIiKiFF2+DHh6SkmQsTEwezZw4IDUOZp0whqhFJw6lXS9cGH54iAiIkrm5EmgeXMgNlYa2bNlC1C/vtxR5VpMhFKQWMs4aJC8cRARESVTsyZQtqyUBK1fL80WTRnGRCgNnHeKiIhyhJs3gdKlpWYwCwvg8GFpqQyuFZZpfAY/olIlXff1lS8OIiIiCAEsXQpUrQrMmpVU7ujIJEhPWCP0kQ873LPPGRERyebtW6BvX2DXLmn78mVArWYCpGd8Nj8yaVLSdTMz+eIgIiIDdu4cUK2alASZmgKLFwM7djAJygJ8Rj/y9q3097PPZA2DiIgMkRDAokXSKLCQEKBYMeD0aWDECGnxVNI7JkIfuHQp6fqUKfLFQUREBio4GJg4EYiPBzp2BC5elEaJUZZhH6EPVK+edL11a/niICIiA1W8OLBsGRAdDQwezFqgbMBE6P9CQpKut2ghWxhERGRI1GpgwQJpwdTEPhlffy1vTAaGidD/rVqVdH3/fvniICIiA/HypTRPy4EDgLs7cO0aYGMjd1QGh4nQ/8XEJF03NpYvDiIiMgAnTgDdugHPnkkTJE6aBFhbyx2VQWJn6f9buFD627+/vHEQEVEeplZLEyM2aSIlQWXKAP/+K335sD+QLFgjBGDjxqTrH9YMERER6U1kJNChA3DokLTdsyfw889sDpMZEyEAvXolXV+7Vr44iIgoD7O2BiwtpcvPPwO9e8sdEYGJEADAzg6IiADatgVM+IwQEZG+qFRAXJyU/CgUwLp1QGgoUL683JHR/7GPEKQkCJCWdCEiItKL588BLy+p/48QUln+/EyCchiDr/+IjU26XqqUfHEQEVEe8tdfwFdfSUPkra2BBw+AEiXkjopSYPA1QolriwFA2bKyhUFERHlBQoI0FL5lSykJqlwZ+O8/JkE5mMHXCP36a9J1LupLREQZ9uQJ0L07cPKktP3NN9ICqpaW8sZFaTL4ROj5c7kjICKiXE+tBlq1kmaHtrWVlivw8ZE7KkoHg68DWbBA+tutm7xxEBFRLmZkBCxeDNSoIa0YzyQo1zD4RMjBQfprZydrGERElNs8eiR1ik7UrJk0S3TJkvLFRDoz+EQosbP06NGyhkFERLnJ3r1A1apAp07AvXtJ5exsmusY9Cv24EHSdSsr+eIgIqJcIi4OGDUK+PJL4M0babgxZ+LN1WRPhJYtWwYPDw9YWFigdu3aOHfuXJr7L168GGXKlIGlpSXc3NwwatQoxGRwgbAXL5KuFymSoVMQEZGhCA4G6teX+gIBUkJ06hTg4SFnVJRJsiZCW7duxejRo+Hn54eLFy+iSpUq8Pb2xosPM5QP/Pbbbxg/fjz8/Pxw8+ZNrFmzBlu3bsXEiRMzFUfx4pk6nIiI8rqdO4Fq1YDz54F8+YA9e4CFCwEzM7kjo0ySNRFauHAh+vfvjz59+qB8+fJYvnw5rKyssDaVlU//+ecf1KtXD927d4eHhwdatGiBbt26fbIWKTXv32cmeiIiMhj//AMolUCdOkBQEPDFF3JHRHoiWyIUFxeHCxcuwMvLKykYIyN4eXnhzJkzKR5Tt25dXLhwQZP4PHjwAPv370fr1q1TvZ/Y2FhERERoXRJt2iT95VxCRESUTOL6YADg7w8sWQL8/TdQtKh8MZHeyZYIhYeHQ6VSoVChQlrlhQoVQmhoaIrHdO/eHTNmzED9+vVhamqKEiVKoHHjxmk2jfn7+8Pe3l5zcXNz09yW2C8oOjrzj4eIiPKQLVuA1q2B+Hhp28wMGD4cMDWVNy7SO9k7S+vi+PHjmD17Nn7++WdcvHgRu3btwr59+zBz5sxUj5kwYQKUSqXm8vjxY81te/dKfwcPzurIiYgoV4iOlpbG6NYNCAyUZoimPE22MX+Ojo4wNjZGWFiYVnlYWBicnZ1TPGbKlCno2bMn+vXrBwCoVKkSoqKiMGDAAEyaNAlGKczfYG5uDnNz8xTPFxQk/WXTGBER4fZtoEsX4MoVQKEAJk4EBgyQOyrKYrLVCJmZmcHT0xNHjhzRlKnVahw5cgR16tRJ8Zj3798nS3aMjY0BAOLDttx0SEhIuv711zodSkREec2vvwKenlISVLAgcPAg8P33nCPIAMj6Co8ePRq+vr6oUaMGatWqhcWLFyMqKgp9+vQBAPTq1Quurq7w9/cHALRt2xYLFy5EtWrVULt2bdy7dw9TpkxB27ZtNQlRen3QZxrNm+vtIRERUW4zaxYwebJ0vUkTaSSNi4u8MVG2kTUR8vHxwcuXLzF16lSEhoaiatWqCAwM1HSgfvTokVYN0OTJk6FQKDB58mQ8ffoUTk5OaNu2LWbNmpWpOJjwExEZsE6dgB9+kNZamjwZ0PGHNeVuCqFrm1IuFxERAXt7e1y4oISnp7TSakIC3/dERAZDCKkJrEqVpLJXr4ACBeSLiT4p8ftbqVTCTo8rpeeqUWP6lLjYKsAkiIjIYERGAr16AdWrS3MCJWISZLAMNhHavFn6y2ZgIiIDceUKUKOG1DEaAK5dkzceyhEMNhFydJT+cug8EVEeJwSwciVQq5Y0RN7VFTh+HBgyRO7IKAcw2G7Cr15JfwcOlDcOIiLKQhER0gSJW7ZI261aARs2JP0aJoNnsDVCd+5Ifz8cRk9ERHnMnj1SEmRsLI0M+/NPJkGkxWBrhBKXOMufX944iIgoC331FXDpEtC5s7RyPNFHDLZGKFGxYnJHQEREevP2LTB0KPDmjbStUAALFzIJolQZbI1QZKTcERARkV6dPw/4+ADBwUB4eFK/IKI0GGyN0P790t+4OHnjICKiTBICWLwYqFdPSoKKFQO+/VbuqCiXMNgaoUR6nJySiIiy2+vXQJ8+wN690nbHjsDq1YCDg6xhUe5h8IlQ165yR0BERBly9Srw+efAo0eAmZnUF2jwYKlfEFE6GXwiZGsrdwRERJQhhQtLzWIlSgDbtknLZhDpyOATISIiykXevQNsbKRanwIFgAMHADc39nOgDDPYztJERJTLnDwJlCsHBAQklVWowCSIMsXgEyEjg38GiIhyOLUamD0baNIEePoU+OknQKWSOyrKIww+DTA2ljsCIiJK1YsXQMuWwKRJUvLz1VfAiRP88Ca9Meg+QkWLyh0BERGl6tgxoHt3IDQUsLQEli6VhspzVBjpkUEnQqxZJSLKoR4+BFq0ABISgPLlpVFhFSrIHRXlQQadCD19KncERESUInd3YMIE4MkTqU+QtbXcEVEeZdCJUJMmckdAREQahw8DHh5AyZLS9vTpbAajLGfQnaWDg+WOgIiIkJAATJ4sNYX5+ACxsVI5kyDKBgZdI+TtLXcEREQG7ulToFs3aY4gAKhZU5otmiibGHQiFBQkdwRERAbswAGgVy8gPFxa72jlSi4ASdnOoJvGvvtO7giIiAxQfDwwbhzQurWUBFWrBly4wCSIZGHQiRBnlSYikoEQ0hxBADBkCPDPP0CpUvLGRAbLoJvGTE3ljoCIyIAIIXWANjMDtm4FLl4EOnaUOyoycAadCLm7yx0BEZEBiIsDxo8HLCykNcMAoFgx6UIkM4NOhNg0RkSUxYKDpb4/585JtUG9egFly8odFZGGQacC/DFCRJSFdu2SOkKfOwc4OAC7dzMJohzHoBMh1ggREWWB2Fhg2DCp/49SCXz2mTRfyZdfyh0ZUTIG3TRmbi53BEREeYwQ0gzRJ05I2999B3z/PUenUI5lsIlQ4cJyR0BElAcpFEC/fsD168CGDdJcQUQ5GBuHiIgoc6KjgZs3k7Z79gTu3GESRLkCEyEiIsq427elPkBeXsDLl0nl+fPLFxORDpgIERFRxvz6K+DpCVy5Ii2bERwsd0REOmMiREREunn/HujbV2oCi4oCGjeWRoXVqiV3ZEQ6YyJERETpd+OGlPCsXSt1jPbzAw4f5ggUyrUMdtTYs2dyR0BElAvNnSuNCHN2BjZtApo2lTsiokwx2ETIyUnuCIiIcqEffwRMTKQ1wwoVkjsaokwz2KYxjuokIkqHq1eBsWOliRIBwN4eWLOGSRDlGQZbI0RERGkQAli9Ghg+HIiJAcqUkSZKJMpjmAgREZG2iAjgm2+ALVuk7VatuE4Y5VkG2zRGREQpuHRJmhtoyxbA2FjqHP3nn+xYSXlWpmqEYmJiYGFhoa9YiIhIThs3Ss1fcXGAm5uUDNWtK3dURFlK5xohtVqNmTNnwtXVFTY2Nnjw4AEAYMqUKVizZo3eAyQiomxSrBigUgFt20oTJDIJIgOgcyL0/fffIyAgAD/88APMzMw05RUrVsTq1av1GhwREWUxpTLpev36wJkzwJ49XCuMDIbOidCGDRuwcuVK9OjRA8bGxpryKlWq4NatW3oNjoiIsogQwJIlgIeHNFt0opo1pRmjiQyEzonQ06dPUbJkyWTlarUa8fHxegmKiIiy0OvXQPv2wMiRwNu3QECAzAERyUfnRKh8+fI4efJksvIdO3agWrVqegmKiIiyyNmzQLVqUvOXmRnw00/SyDAiA6XzqLGpU6fC19cXT58+hVqtxq5du3D79m1s2LABf/75Z1bESEREmaVWAwsXAhMmAAkJQIkSwNat0lB5IgOmc43Ql19+iT/++AOHDx+GtbU1pk6dips3b+KPP/5A8+bNsyJGIiLKrF9/lZbKSEgAunQBLlxgEkSEDM4j1KBBAxw6dEjfsRARUVbp3l1aLb59e2nWaHaIJgKQgRqh4sWL49WrV8nK3759i+LFi+slKCIiyiS1WlorLDZW2jYxAQIDgYEDmQQRfUDnRCgkJAQqlSpZeWxsLJ4+faqXoIiIKBNevJDWB+vfHxg3LqmcCRBRMuluGtu7d6/m+sGDB2Fvb6/ZVqlUOHLkCDw8PPQaXFZK/JFERJSnHD8uNYM9fw5YWgKVK8sdEVGOlu5EqF27dgAAhUIBX19frdtMTU3h4eGBBQsW6DW4rKRWyx0BEZEeqVTArFnA9OnSB1y5csD27UCFCnJHRpSjpTsRUv8/cyhWrBjOnz8PR0fHLAsqO/CzgYjyjNBQoEcP4OhRabtPH2l+IGtreeMiygV0HjUWHBycFXEQEVFGvX8P/PcfYGUFLF8O9Owpd0REuUaGhs9HRUXh77//xqNHjxAXF6d12/Dhw/USGBERpUGIpM7PxYsD27YB7u5A2bLyxkWUy+icCF26dAmtW7fG+/fvERUVhfz58yM8PBxWVlYoWLAgEyEioqz29Cnw1VfSLNEtWkhl3t7yxkSUS+k8fH7UqFFo27Yt3rx5A0tLS5w9exYPHz6Ep6cn5s+fnxUxEhFRosBAoGpVaXTY4MHSTNFElGE6J0JBQUH49ttvYWRkBGNjY8TGxsLNzQ0//PADJk6cmBUxEhFRfDwwfrw0P1B4uJQM7d8vTZRIRBmmcyJkamoKIyPpsIIFC+LRo0cAAHt7ezx+/Fi/0REREfD4MdC4cdIq8YMHA2fOAKVLyxoWUV6gcyJUrVo1nD9/HgDQqFEjTJ06FZs2bcLIkSNRsWJFnQNYtmwZPDw8YGFhgdq1a+PcuXNp7v/27VsMGTIELi4uMDc3R+nSpbF//36d75eIKFd4+lSq/fnnH8DOTpobaNkywMJC7siI8gSdE6HZs2fDxcUFADBr1izky5cPgwYNwsuXL7FixQqdzrV161aMHj0afn5+uHjxIqpUqQJvb2+8ePEixf3j4uLQvHlzhISEYMeOHbh9+zZWrVoFV1dXXR8GEVHu4OoKtG0L1KgBXLoEdOokd0REeYpCCCHkuvPatWujZs2aWLp0KQBp0kY3NzcMGzYM48ePT7b/8uXLMW/ePNy6dQumpqYZus+IiAjY29tj+nQlpk61y1T8RERZIiQEsLEBEieuff8eMDYGzM1lDYtITonf30qlEnZ2+vv+1rlGKDUXL17E559/nu794+LicOHCBXh5eSUFY2QELy8vnDlzJsVj9u7dizp16mDIkCEoVKgQKlasiNmzZ6e4CGyi2NhYREREaF2IiHKs3bulpjBf36S1gKysmAQRZRGdEqGDBw9izJgxmDhxIh48eAAAuHXrFtq1a4eaNWtqluFIj/DwcKhUKhQqVEirvFChQggNDU3xmAcPHmDHjh1QqVTYv38/pkyZggULFuD7779P9X78/f1hb2+vubi5uaU7RiKibBMbCwwfDnToACiVwKtX0l8iylLpToTWrFmDVq1aISAgAHPnzsVnn32GX3/9FXXq1IGzszOuXbuW5Z2W1Wo1ChYsiJUrV8LT0xM+Pj6YNGkSli9fnuoxEyZMgFKp1Fw4so2Icpz794F69aT1wQBgzBjg5EkgXz554yIyAOmegGLJkiWYO3cuxo4di507d6Jz5874+eefcfXqVRQpUkTnO3Z0dISxsTHCwsK0ysPCwuDs7JziMS4uLjA1NYWxsbGmrFy5cggNDUVcXBzMzMySHWNubg5zVikTUU61bRvQrx/w7h1QoACwfj3Qpo3cUREZjHTXCN2/fx+dO3cGAHTo0AEmJiaYN29ehpIgADAzM4OnpyeOHDmiKVOr1Thy5Ajq1KmT4jH16tXDvXv3tJrg7ty5AxcXlxSTICKiHC0mRlom4907qUYoKIhJEFE2S3ciFB0dDSsrKwCAQqGAubm5Zhh9Ro0ePRqrVq3C+vXrcfPmTQwaNAhRUVHo06cPAKBXr16YMGGCZv9Bgwbh9evXGDFiBO7cuYN9+/Zh9uzZGDJkSKbiICKShYUFsHUrMHGitGRGBn9YElHG6TQ3++rVq2FjYwMASEhIQEBAABwTh3f+ny6Lrvr4+ODly5eYOnUqQkNDUbVqVQQGBmo6UD969EgzizUAuLm54eDBgxg1ahQqV64MV1dXjBgxAuPGjdPlYRARyee336Th8P36Sds1akgXIpJFuucR8vDwgEKhSPtkCoVmNFlOxXmEiEgW798DI0YAq1cDZmZSM1i5cnJHRZRrZNU8QumuEQoJCdHbnRIRGZSbN4EuXYBr1wCFQuoXxHXCiHIELltMRJSV1q+XFkl9/x4oVEhqGmvaVO6oiOj/mAgREWUFIYD+/YE1a6RtLy/g11+lZIiIcgy9LbFBREQfUCiA4sUBIyNg5kwgMJBJEFEOxBohIiJ9EUJaFsPBQdoePx5o2RKoXl3WsIgodawRIiLSh3fvgB49gAYNpP5AgFQbxCSIKEfLUCJ0//59TJ48Gd26dcOLFy8AAAcOHMD169f1GhwRUa4QFAR4egKbN0sjxE6ckDsiIkonnROhv//+G5UqVcK///6LXbt2ITIyEgBw+fJl+Pn56T1AIqIcSwjgl1+Azz4D7t4F3NykJKhlS7kjI6J00jkRGj9+PL7//nscOnRIa32vpk2b4uzZs3oNjogox1IqAR8faWh8bCzQti1w6RJQt67ckRGRDnROhK5evYr27dsnKy9YsCDCw8P1EhQRUY43dCiwfTtgYgIsWADs2SOtHk9EuYrOiZCDgwOeP3+erPzSpUtwdXXVS1BERDmev7/UL+jUKWD0aGm4PBHlOjonQl27dsW4ceMQGhoKhUIBtVqN06dPY8yYMejVq1dWxEhEJL83b6RZohMVKQKcPw/Uri1fTESUaTonQrNnz0bZsmXh5uaGyMhIlC9fHg0bNkTdunUxefLkrIiRiEhe//4LVKsG9O4tNYElYi0QUa6n84SKZmZmWLVqFaZMmYJr164hMjIS1apVQ6lSpbIiPiIi+QgBLFwoTYyYkACUKCHVBBFRnqFzInTq1CnUr18fRYsWRdGiRbMiJiIi+b16JdUA/fmntN2lC7BqFWBnJ2tYRKRfOjeNNW3aFMWKFcPEiRNx48aNrIiJiEhep08DVatKSZC5uTRX0JYtTIKI8iCdE6Fnz57h22+/xd9//42KFSuiatWqmDdvHp48eZIV8RERZb9nz4AnT4BSpYCzZ4GBA9kfiCiP0jkRcnR0xNChQ3H69Gncv38fnTt3xvr16+Hh4YGmTZtmRYxERFlPiKTrnTsDAQHAhQtSzRAR5VmZWnS1WLFiGD9+PObMmYNKlSrh77//1ldcRETZ5++/pTmBPpwjzdcXsLWVLyYiyhYZToROnz6NwYMHw8XFBd27d0fFihWxb98+fcZGRJS1VCpg5kygaVNpeYypU+WOiIiymc6jxiZMmIAtW7bg2bNnaN68OZYsWYIvv/wSVlZWWREfEVHWCA0FvvoKOHJE2u7dG1i8WM6IiEgGOidCJ06cwNixY9GlSxc4OjpmRUxERFnryBGgRw8gLAywspJGhXFmfCKDpHMidPr06ayIg4goe+zeDXTsKHWOrlgR2LYNKFdO7qiISCbpSoT27t2LVq1awdTUFHv37k1z3y+++EIvgRERZYnmzYEyZYAGDYAlSwBLS7kjIiIZpSsRateuHUJDQ1GwYEG0a9cu1f0UCgVUKpW+YiMi0o/z56VRYUZGgI2NNDeQvb3cURFRDpCuUWNqtRoFCxbUXE/twiSIiHKUhARgwgSgVi1pzbBETIKI6P90Hj6/YcMGxMbGJiuPi4vDhg0b9BIUEVGmPX4MNG4MzJkjbXP2eyJKgc6JUJ8+faBUKpOVv3v3Dn369NFLUEREmbJvnzQj9OnT0vpg27dzaDwRpUjnREgIAUUKa+48efIE9qxuJiI5xcUBY8YAn38OvH4N1KghTZTYqZPckRFRDpXu4fPVqlWDQqGAQqFAs2bNYGKSdKhKpUJwcDBatmyZJUESEaXLzZvAjz9K10eMAObOlVaPJyJKRboTocTRYkFBQfD29oaNjY3mNjMzM3h4eKBjx456D5CIKN2qVAGWLgUKFgTSGOFKRJQo3YmQn58fAMDDwwM+Pj6wsLDIsqCIiNIlNhaYOBHo2TNplfgBA2QNiYhyF51nlvb19c2KOIiIdHP/PuDjA1y4APz5J3DtGmBqKndURJTLpCsRyp8/P+7cuQNHR0fky5cvxc7SiV6/fq234IiIUrR9O9CvHxARAeTPL80RxCSIiDIgXYnQokWLYGtrq7meViJERJRlYmKA0aOlRVIBoF49YPNmwM1N3riIKNdKVyL0YXNY7969syoWIqLUvXwJtGgBBAVJ2xMmADNmACY6t/ATEWnoPI/QxYsXcfXqVc32nj170K5dO0ycOBFxcXF6DY6ISCN/fsDREXByAgIDgdmzmQQRUabpnAh98803uHPnDgDgwYMH8PHxgZWVFbZv347vvvtO7wESkQF7/x6IjpauGxsDmzZJNULe3rKGRUR5h86J0J07d1D1/8NUt2/fjkaNGuG3335DQEAAdu7cqe/4iMhQ3bwJ1K4NjByZVFawIFC4sGwhEVHek6ElNtRqNQDg8OHDaN26NQDAzc0N4eHh+o2OiAzT+vXS8hjXrgF79kj9g4iIsoDOiVCNGjXw/fffY+PGjfj777/Rpk0bAEBwcDAKFSqk9wCJyIBERQG9e0uX9++BZs2kpjAnJ5kDI6K8SudEaPHixbh48SKGDh2KSZMmoWTJkgCAHTt2oG7dunoPkIgMxLVrQM2aUm2QkREwcyZw8CDg7Cx3ZESUh+k85KJy5cpao8YSzZs3D8bGxnoJiogMTFwc0KoV8OSJ1Afot9+ARo3kjoqIDECGx55euHABN2/eBACUL18e1atX11tQRGRgzMyA5cuBZcukGiE2hRFRNtE5EXrx4gV8fHzw999/w8HBAQDw9u1bNGnSBFu2bIETP8CIKD0uXwZevACaN5e227QBWrcGOHM9EWUjnfsIDRs2DJGRkbh+/Tpev36N169f49q1a4iIiMDw4cOzIkYiykuEkGp/ateWFk199CjpNiZBRJTNdK4RCgwMxOHDh1GuXDlNWfny5bFs2TK0aNFCr8ERUR6jVAIDBgDbtknbzZsD1tbyxkREBk3nGiG1Wg3TFFZ5NjU11cwvRESUzIULQPXqUhJkYgIsWADs3QsUKCB3ZERkwHROhJo2bYoRI0bg2bNnmrKnT59i1KhRaNasmV6DI6I84qefgLp1gQcPAHd34NQpaRV5NoURkcx0ToSWLl2KiIgIeHh4oESJEihRogSKFSuGiIgI/PTTT1kRIxHldtevS0Pk27UDLl2S+gcREeUAOvcRcnNzw8WLF3HkyBHN8Ply5crBy8tL78ERUS4mRFKNz6JFUo1Qz56sBSKiHEWnRGjr1q3Yu3cv4uLi0KxZMwwbNiyr4iKi3EoIKfE5dAj4809p1XhLS6BXL7kjIyJKJt2J0C+//IIhQ4agVKlSsLS0xK5du3D//n3MmzcvK+Mjotzk1StpnbA//5S2d+0COneWNSQiorSku4/Q0qVL4efnh9u3byMoKAjr16/Hzz//nJWxEVFu8s8/QLVqUhJkbg788gvQqZPcURERpSndidCDBw/g6+ur2e7evTsSEhLw/PnzLAmMiHIJtRqYOxdo2BB4/BgoVQo4exYYOJD9gYgox0t3IhQbGwvrDyY+MzIygpmZGaKjo7MkMCLKJYYPB8aPB1QqoHt3ab6gqlXljoqIKF106iw9ZcoUWFlZabbj4uIwa9Ys2Nvba8oWLlyov+iIKOcbMADYvBn44Qfg669ZC0REuUq6E6GGDRvi9u3bWmV169bFgwcPNNsKfgAS5X0qFfDff0lzAVWuDISEALa2soZFRJQR6U6Ejh8/noVhEFGuEBYGfPUVcPy4NDt0YjLEJIiIcimdZ5YmIgN19ChQpQpw+DBgZgY8eSJ3REREmcZEiIjSplIBfn6Al5dUI1SxotQ01rGj3JEREWWazktsEJEBefYM6NFDagoDgH79gCVLgA8GTRAR5WZMhIgodbt2SUmQjQ2wYoU0PJ6IKA/JEU1jy5Ytg4eHBywsLFC7dm2cO3cuXcdt2bIFCoUC7dq1y9oAiQzVkCHAmDHS3EBMgogoD8pQInTy5El89dVXqFOnDp4+fQoA2LhxI06dOqXzubZu3YrRo0fDz88PFy9eRJUqVeDt7Y0XL16keVxISAjGjBmDBg0aZOQhEFFKnjyR1gp7907aViiAefOA0qVlDYuIKKvonAjt3LkT3t7esLS0xKVLlxAbGwsAUCqVmD17ts4BLFy4EP3790efPn1Qvnx5LF++HFZWVli7dm2qx6hUKvTo0QPTp09H8eLFdb5PIkrBvn3SjNDr1wPffit3NERE2ULnROj777/H8uXLsWrVKpiammrK69Wrh4sXL+p0rri4OFy4cAFeXl5JARkZwcvLC2fOnEn1uBkzZqBgwYLo27fvJ+8jNjYWERERWhci+kB8PDB2LPD559Lq8Z6ewLhxckdFRJQtdE6Ebt++jYYNGyYrt7e3x9u3b3U6V3h4OFQqFQoVKqRVXqhQIYSGhqZ4zKlTp7BmzRqsWrUqXffh7+8Pe3t7zcXNzU2nGInytIcPpcVS58+XtocPB06fBkqUkDcuIqJsonMi5OzsjHv37iUrP3XqVJY3U7179w49e/bEqlWr4OjomK5jJkyYAKVSqbk8fvw4S2MkyjVOnpSaws6eBRwcgN27paHx5uZyR0ZElG10Hj7fv39/jBgxAmvXroVCocCzZ89w5swZjBkzBlOmTNHpXI6OjjA2NkZYWJhWeVhYGJydnZPtf//+fYSEhKBt27aaMrVaLT0QExPcvn0bJT76JWtubg5zfrATJVeqlJT01K4NbNkCeHjIHRERUbbTOREaP3481Go1mjVrhvfv36Nhw4YwNzfHmDFjMGzYMJ3OZWZmBk9PTxw5ckQzBF6tVuPIkSMYOnRosv3Lli2Lq1evapVNnjwZ7969w5IlS9jsRfQpr14BBQpI152dpTmCiheXlswgIjJAOidCCoUCkyZNwtixY3Hv3j1ERkaifPnysLGxyVAAo0ePhq+vL2rUqIFatWph8eLFiIqKQp8+fQAAvXr1gqurK/z9/WFhYYGKFStqHe/g4AAAycqJ6CM7dgB9+wIrVwI+PlJZ2bLyxkREJLMMzyxtZmaG8uXLZzoAHx8fvHz5ElOnTkVoaCiqVq2KwMBATQfqR48ewcgoR8z7SJQ7xcRIw+F//lnaXr8e6NJFmiOIiMjAKYQQQpcDmjRpAkUaH6BHjx7NdFBZKSIiAvb29pg+XYmpU+3kDocoa929KyU9QUHS9vjxwIwZwAdTXxAR5QaJ399KpRJ2dvr7/ta5Rqhq1apa2/Hx8QgKCsK1a9fg6+urr7iIKLM2bwYGDAAiIwFHR2DjRqBlS7mjIiLKUXROhBYtWpRi+bRp0xAZGZnpgIhID65cSVobrGFD4LffAFdXeWMiIsqB9Nb55quvvkpzWQwiykaVK0uLpU6ZAhw5wiSIiCgVGe4s/bEzZ87AwsJCX6cjIl1t2gQ0aAAULSpt//ADO0QTEX2CzolQhw4dtLaFEHj+/Dn+++8/nSdUJCI9iIoChg0D1q0D6taV5gYyNWUSRESUDjonQvb29lrbRkZGKFOmDGbMmIEWLVroLTAiSofr16VRYTduAEZGgLe39JeIiNJFp0RIpVKhT58+qFSpEvLly5dVMRHRpwgh1QANHQpERwMuLlKH6MaN5Y6MiChX0emno7GxMVq0aKHzKvNEpEdRUUCvXtIs0dHRUi1QUBCTICKiDNC5Dr1ixYp48OBBVsRCROlhZCQNjzc2Bvz9gf37gYIF5Y6KiChX0rmP0Pfff48xY8Zg5syZ8PT0hLW1tdbt+pztkYj+TwjpYmQEWFoC27YBL18C9evLHRkRUa6W7kRoxowZ+Pbbb9G6dWsAwBdffKG11IYQAgqFAiqVSv9REhkypVKaIbpSJWDyZKmsTBnpQkREmZLuRGj69OkYOHAgjh07lpXxENGHLlyQVoq/fx/Yu1fqF+TiIndURER5RroTocS1WRs1apRlwRDR/wkBLF0qzQ4dFwe4uwNbtjAJIiLSM536CKW16jwR6cnbt1LNz65d0na7dsDatQCnrCAi0judEqHSpUt/Mhl6/fp1pgIiMmgJCdLs0DdvSrNDz58vzRrNHyFERFlCp0Ro+vTpyWaWJiI9MjEBRoyQ1gnbuhWoUUPuiIiI8jSdEqGuXbuiIOcrIdKv16+B58+BChWk7QEDgK++Aj6amoKIiPQv3RMqsn8QURb45x+galXg88+lvkGA1AzGJIiIKFukOxFKHDVGRHqgVgNz5wINGwKPH0v9gV68kDsqIiKDk+6mMbVanZVxEBmOly8BX1/gwAFpu1s3YMUKwNZW3riIiAyQzktsEFEmnDghJT7PngEWFsBPP0lD5dn0TEQkCyZCRNlp4UIpCSpbVlovrFIluSMiIjJoTISIstOaNUDx4sCMGYCNjdzREBEZvHR3liaiDDh6FPj2W2nJDAAoUECqFWISRESUI7BGiCgrqFRSrc/MmVISVLs20KWL3FEREdFHmAgR6duzZ0CPHsDx49J2377SPEFERJTjMBEi0qe//pJmhX75UpoUccUKKSkiIqIciX2EiPRl3jygZUspCapSBbh4kUkQEVEOx0SISF+qVZP+DhoEnD0LlC4tbzxERPRJbBojyowXL4DEhYi9vICrV5MWTyUiohyPNUJEGREfD4wdK9X63L+fVM4kiIgoV2EiRKSrhw+BBg2A+fMBpRL44w+5IyIiogwy2KaxhAS5I6Bc6fffgT59gLdvAXt7YO1aoEMHuaMiIqIMMtgaIRODTQEpQ+LigJEjgfbtpSSoVi3g0iUmQUREuZzBJkLFi8sdAeUqS5cCS5ZI10ePBk6eBIoVkzcmIiLKNNaLEKXH0KHAoUPA4MFA27ZyR0NERHpisDVCRGmKiZEWR42Pl7bNzIADB5gEERHlMawRIvrY3buAj4/UB+jlS8DfX+6IiIgoi7BGiOhDW7YA1atLSZCjI9CwodwRERFRFmIiRAQA0dHAN98A3boBkZHSPEFBQUCrVnJHRkREWYiJENGdO0Dt2sDKlYBCAUyeDBw9Cri6yh0ZERFlMfYRIlKrgQcPpDXDNm2S1gwjIiKDwESIDJNaDRj9v0K0bFlg1y6gUiXAxUXeuIiIKFuxaYwMz/XrQNWqwIkTSWUtWjAJIiIyQEyEyHAIAaxZA9SsCVy9Cnz7rVRGREQGi4kQGYZ374CePYF+/aQRYi1aAPv2SZ2jiYjIYDERorzv8mWgRg2pI7SxMTB7tjRLdMGCckdGREQyY2dpyttu3pSGxsfGSsPht2wB6teXOyoiIsohmAhR3la2LPDFF0BUFLB+vTRbNBER0f8xEaK859IloFgxwMFB6gO0fj1gbp40XJ6IiOj/+M1AeYcQwNKlwGefSZ2iE0eEWVoyCSIiohSxRojyhrdvgb59pYkRASAhAYiJkZIgIiKiVPBnMuV+584B1apJSZCpKbB4MbB7N5MgIiL6JCZClHsJASxaJI0CCwmR+gWdPg2MGMH5gYiIKF2YCFHupVQCCxcC8fFAx47AxYvSrNFERETpxD5ClHs5OACbN0sTJg4ezFogIiLSGRMhyj3UamD+fMDZGejVSyqrX58TJBIRUYYxEaLc4eVLwNdXWhrDygpo0gRwc5M7KiIiyuWYCFHOd/Ik0LUr8OwZYGEhjQorUkTuqIiIKA9gZ2nKudRqYNYsoHFjKQkqUwb491+gf3/2ByIiIr1gjRDlTCoV0KYNcPCgtN2zJ/Dzz4CNjbxxERFRnsIaIcqZjI2BGjWk/kDr1gEbNjAJIiIivWMiRDmHSiV1ik40bRoQFAT07i1TQERElNfliERo2bJl8PDwgIWFBWrXro1z586luu+qVavQoEED5MuXD/ny5YOXl1ea+1Mu8fw50Lw50KoVEBsrlZmYAKVKyRsXERHlabInQlu3bsXo0aPh5+eHixcvokqVKvD29saLFy9S3P/48ePo1q0bjh07hjNnzsDNzQ0tWrTA06dPszly0pu//gKqVAGOHQNu3ZImSCQiIsoGCiGEkDOA2rVro2bNmli6dCkAQK1Ww83NDcOGDcP48eM/ebxKpUK+fPmwdOlS9EqcZC8NERERsLe3x8aNSnz1lV2m46dMSEgA/PwAf39p3bDKlYFt26TRYURERB9I/P5WKpWws9Pf97esNUJxcXG4cOECvLy8NGVGRkbw8vLCmTNn0nWO9+/fIz4+Hvnz50/x9tjYWERERGhdKAd48gRo2hSYPVtKgr75Bjh7lkkQERFlK1kTofDwcKhUKhQqVEirvFChQggNDU3XOcaNG4fChQtrJVMf8vf3h729vebixtmIc4b+/aWJEm1tgS1bgOXLAUtLuaMiIiIDI3sfocyYM2cOtmzZgt27d8PCwiLFfSZMmAClUqm5PH78OJujpBQtWyYtk3HxIuDjI3c0RERkoGSdUNHR0RHGxsYICwvTKg8LC4Ozs3Oax86fPx9z5szB4cOHUbly5VT3Mzc3h7m5uV7ipUx49EjqFN2vn7RdvDhw9Ki8MRERkcGTtUbIzMwMnp6eOHLkiKZMrVbjyJEjqFOnTqrH/fDDD5g5cyYCAwNRo0aN7AiVMmPvXqBqVWDAACkZIiIiyiFkX2Jj9OjR8PX1RY0aNVCrVi0sXrwYUVFR6NOnDwCgV69ecHV1hb+/PwBg7ty5mDp1Kn777Td4eHho+hLZ2NjAhjMP5yxxccC4cdIiqQBQsybnBSIiohxF9kTIx8cHL1++xNSpUxEaGoqqVasiMDBQ04H60aNHMDJKqrj65ZdfEBcXh06dOmmdx8/PD9OmTcvO0CktwcFS35/z56XtUaOAOXMAMzN54yIiIvqA7PMIZTfOI5QNfv9dWhZDqQTy5QMCAoAvvpA5KCIiys2yah4h2WuEKA+KiJCSoDp1pKHxRYvKHREREVGKmAiRfqhU0orxANCrF2BhAbRvD5iayhsXERFRGnL1PEKUQ2zZAlSqBISHJ5V16cIkiIiIcjwmQpRx0dHS0hjdugE3bwILF8odERERkU7YNEYZc+uWVOtz9SqgUAATJwIctUdERLkMEyHS3caNwKBBQFQUULAg8OuvQPPmckdFRESkMyZCpJsVK4CBA6XrTZoAmzYBLi7yxkRERJRB7CNEuunaFShZUmoGO3SISRAREeVqrBGitAkhLY7atKnUF8jeHrhyBbC0lDsyIiKiTGONEKUuMhLw9QW8vIDly5PKmQQREVEewRohStmVK9KosNu3ASMjqWM0ERFRHsNEiLQJAaxcCYwYAcTGAq6uwObNQIMGckdGRESkd0yEKElEBDBgALB1q7TdqhWwYQPg6ChvXERERFmEfYQoybVrwPbt0pphP/wA/PknkyAiIsrTWCNESerWBZYuBapWlVaOJyIiyuNYI2TI3r4FevaU1glLNGgQkyAiIjIYrBEyVOfPAz4+QHAwcOMG8N9/0jxBREREBoQ1QoZGCGDxYqBePSkJ8vCQ5ghiEkRERAaINUKG5PVroE8fYO9eabtDB2DNGsDBQdawiIiI5MJEyFAEBwONGwOPHgFmZsDChcDgwawJIiIig8ZEyFC4uQFFiwKmpsC2bUD16nJHREREJDsmQnnZq1eAra1UA2RiIs0RZGUF2NnJHRkREVGOwM7SedXJk0CVKsC4cUllzs5MgoiIiD7ARCivUauB2bOBJk2Ap0+BwEAumEpERJQKJkJ5yYsXQMuWwKRJgEoFfPWVNF+QtbXckREREeVI7COUVxw7BnTvDoSGApaWwLJlQO/eHBVGRESUBiZCeUFEBNCxI/DmDVC+vDQqrEIFuaMiIiLK8ZgI5QV2dsCKFcCBA8BPP7EpjIiIKJ2YCOVWhw8DRkZA06bSdufO0oWIiIjSjZ2lc5uEBGDyZKBFC6BbN+D5c7kjIiIiyrVYI5SbPH0qJT8nT0rb7dpxnTAiIqJMYCKUWxw4APTqBYSHAzY2wKpVQNeuckdFRESUq7FpLKdTq6XZoVu3lpKgatWAixeZBBEREekBE6GczshImhsIAIYMAf75ByhVSt6YiIiI8gg2jeVUCQnSQqmANDli587A55/LGxMRURZTqVSIj4+XOwySiampKYyNjbP1PpkI5TRxccD48cC9e8CePdLM0DY2TIKIKM+LjIzEkydPIISQOxSSiUKhQJEiRWBjY5Nt98lEKCcJDgZ8fKT1wQDg+HFp8VQiojxOpVLhyZMnsLKygpOTExRcHsjgCCHw8uVLPHnyBKVKlcq2miEmQjnFrl3A118DSqU0JD4ggEkQERmM+Ph4CCHg5OQES0tLucMhmTg5OSEkJATx8fHZlgixs7TcYmOBYcOktcKUSuCzz4CgIODLL+WOjIgo27EmyLDJ8fozEZJbjx7A0qXS9bFjgRMnAHd3eWMiIiIyEEyE5DZuHODiAvz5J/DDD4CpqdwRERERGQwmQtktOhr4+++k7Zo1gQcPgDZt5IuJiIgy5cyZMzA2NkabFD7Ljx8/DoVCgbdv3ya7zcPDA4sXL9YqO3bsGFq3bo0CBQrAysoK5cuXx7fffounT59mUfRATEwMhgwZggIFCsDGxgYdO3ZEWFhYmseEhYWhd+/eKFy4MKysrNCyZUvcvXtXa5/79++jffv2cHJygp2dHbp06fLJ82Y3JkLZ6fZtqQ+Qt7fUDyiRhYVsIRERUeatWbMGw4YNw4kTJ/Ds2bMMn2fFihXw8vKCs7Mzdu7ciRs3bmD58uVQKpVYsGCBHiPWNmrUKPzxxx/Yvn07/v77bzx79gwdOnRIdX8hBNq1a4cHDx5gz549uHTpEtzd3eHl5YWoqCgAQFRUFFq0aAGFQoGjR4/i9OnTiIuLQ9u2baFWq7PssehMGBilUikAiI0bldl7x7/+KoS1tRCAEE5OQhw7lr33T0SUg0VHR4sbN26I6OhouUPR2bt374SNjY24deuW8PHxEbNmzdK6/dixYwKAePPmTbJj3d3dxaJFi4QQQjx+/FiYmZmJkSNHpng/KR2vD2/fvhWmpqZi+/btmrKbN28KAOLMmTMpHnP79m0BQFy7dk1TplKphJOTk1i1apUQQoiDBw8KIyMjoVQmfd++fftWKBQKcejQoRTPm9b7IPH7+8Pz6QNrhLLa+/dAv37AV18BUVFA48ZSbVDjxjIHRkSUcwkhfWTKcdF1Psdt27ahbNmyKFOmDL766iusXbs2Q5NCbt++HXFxcfjuu+9SvN3BwSHVY1u1agUbG5tULxUqVEj12AsXLiA+Ph5eXl6asrJly6Jo0aI4c+ZMisfExsYCACw+aNEwMjKCubk5Tp06pdlHoVDA3Nxcs4+FhQWMjIw0++QEnEcoK924AXTpAly/Ls0QPXUqMGUKkM3ThxMR5Tbv30uT6sshMhKwtk7//mvWrMFXX30FAGjZsiWUSiX+/vtvNNbxB+/du3dhZ2cHFxcXnY4DgNWrVyM6OjrV203TGIgTGhoKMzOzZIlWoUKFEJq41uVHEhOlCRMmYMWKFbC2tsaiRYvw5MkTPH/+HADw2WefwdraGuPGjcPs2bMhhMD48eOhUqk0++QETISy0p49UhLk7Axs2gQ0bSp3REREpEe3b9/GuXPnsHv3bgCAiYkJfHx8sGbNGp0TISFEhufRcXV1zdBxGWVqaopdu3ahb9++yJ8/P4yNjeHl5YVWrVppasOcnJywfft2DBo0CD/++COMjIzQrVs3VK9eHUZGOadBiolQVvruO6meddgwoFAhuaMhIso1rKykmhm57ju91qxZg4SEBBQuXFhTJoSAubk5li5dCnt7e9jZ2QEAlEplslqXt2/fwt7eHgBQunRpKJVKPH/+XOdaoVatWuHkyZOp3u7u7o7r16+neJuzszPi4uLw9u1brfjCwsLg7Oyc6jk9PT0RFBQEpVKJuLg4ODk5oXbt2qhRo4ZmnxYtWuD+/fsIDw+HiYkJHBwc4OzsjOLFi+v0+LISEyF9unoVmDED2LABsLSUmsC+/17uqIiIch2FQrfmKTkkJCRgw4YNWLBgAVq0aKF1W7t27bB582YMHDgQpUqVgpGRES5cuAD3DybMffDgAZRKJUqXLg0A6NSpE8aPH48ffvgBixYtSnZ/HycqH8pM05inpydMTU1x5MgRdOzYEYBU0/Xo0SPUqVMn1eMSJSZyd+/exX///YeZM2cm28fR0REAcPToUbx48QJffPHFJ8+bXZgI6YMQwOrVwPDhQEwMULw4MHeu3FEREVEW+vPPP/HmzRv07dtXkwwk6tixI9asWYOBAwfC1tYW/fr1w7fffgsTExNUqlQJjx8/xrhx4/DZZ5+hbt26AAA3NzcsWrQIQ4cORUREBHr16gUPDw88efIEGzZsgI2NTapD6DPTNGZvb4++ffti9OjRyJ8/P+zs7DBs2DDUqVMHn332mWa/smXLwt/fH+3btwcgde52cnJC0aJFcfXqVYwYMQLt2rXTSgrXrVuHcuXKwcnJCWfOnMGIESMwatQolClTJsPx6p1ex6DlAnofPq9UCtG1qzQsHhCiZUshXrzQz7mJiAxEbhw+//nnn4vWrVuneNu///4rAIjLly8LIaTH5+fnJ8qWLSssLS1FsWLFxIABA8TLly+THXvo0CHh7e0t8uXLJywsLETZsmXFmDFjxLNnz7LssURHR4vBgweLfPnyCSsrK9G+fXvx/PlzrX0AiHXr1mm2lyxZIooUKSJMTU1F0aJFxeTJk0VsbKzWMePGjROFChUSpqamolSpUmLBggVCrVanGUd2D59XCJGBMX65WEREBOzt7bFxoxJffWWXuZNduiSNCrt3T2oGmz0bGDMGyEGdwIiIcoOYmBgEBwejWLFiWkOyybCk9T5I/P5WKpWaflf6wKaxjNq9G+jaFYiLA9zcgC1bgP9XbxIREVHuwEQoo2rUkCa5qFcPWLcOKFBA7oiIiIhIR0yEdPH0KZDYIc3NDTh3TuoYncF5H4iIiEhe7MySHkIAS5ZISc/evUnlJUowCSIiIsrFmAh9yuvXQPv2wMiRUn+gDxMhIiIiytWYCKXl7FmgWjVpqQwzM+Cnn4BVq+SOiogozzKwgcz0ETlefyZCKVGrgfnzgQYNgEePpCawf/4Bhg5lUxgRURYw/v9i1HFxcTJHQnJKfP2Ns3FxcnaWTsmJE8DYsdL1Ll2kWiA9zllARETaTExMYGVlhZcvX8LU1DRHLcpJ2UOtVuPly5ewsrKCiUn2pSdMhFLSuDEwYgRQtizwzTesBSIiymIKhQIuLi4IDg7Gw4cP5Q6HZGJkZISiRYtCkY3fu0yEAKkpbMkSoFs3IHGl3cWLZQ2JiMjQmJmZoVSpUmweM2BmZmbZXhuYIxKhZcuWYd68eQgNDUWVKlXw008/oVatWqnuv337dkyZMgUhISEoVaoU5s6di9atW2fszl+8AHr2BP76C/jzT+DQIS6RQUQkEyMjIy6xQdlK9m/8rVu3YvTo0fDz88PFixdRpUoVeHt748WLFynu/88//6Bbt27o27cvLl26hHbt2qFdu3a4du2a7nd+/DhQtaqUBFlaAj16sBmMiIjIgMi+6Grt2rVRs2ZNLF26FIDUWcrNzQ3Dhg3D+PHjk+3v4+ODqKgo/Pnnn5qyzz77DFWrVsXy5cs/eX+Ji7b922ECav0+V2oWK1cO2LYNqFhRfw+MiIiI9CarFl2VtUYoLi4OFy5cgJeXl6bMyMgIXl5eOHPmTIrHnDlzRmt/APD29k51/9SU3eUvJUF9+gDnzzMJIiIiMkCy9hEKDw+HSqVCoUKFtMoLFSqEW7dupXhMaGhoivuHhoamuH9sbCxiY2M120qlEgDw2tQCWLpEWkFepQIiIjLzUIiIiCgLRfz/e1rfDVk5orN0VvL398f06dOTlReLj5GGxn/zjQxRERERUUa8evUK9vb2ejufrImQo6MjjI2NERYWplUeFhYG58Rh7B9xdnbWaf8JEyZg9OjRmu23b9/C3d0djx490usTSbqLiIiAm5sbHj9+rNf2XsoYvh45B1+LnIOvRc6hVCpRtGhR5M+fX6/nlTURMjMzg6enJ44cOYJ27doBkDpLHzlyBEOHDk3xmDp16uDIkSMYOXKkpuzQoUOoU6dOivubm5vD3Nw8Wbm9vT3f1DmEnZ0dX4schK9HzsHXIufga5Fz6HueIdmbxkaPHg1fX1/UqFEDtWrVwuLFixEVFYU+ffoAAHr16gVXV1f4+/sDAEaMGIFGjRphwYIFaNOmDbZs2YL//vsPK1eulPNhEBERUS4keyLk4+ODly9fYurUqQgNDUXVqlURGBio6RD96NEjreyvbt26+O233zB58mRMnDgRpUqVwu+//46KHPVFREREOpI9EQKAoUOHptoUdvz48WRlnTt3RufOnTN0X+bm5vDz80uxuYyyF1+LnIWvR87B1yLn4GuRc2TVayH7hIpEREREcpF9iQ0iIiIiuTARIiIiIoPFRIiIiIgMFhMhIiIiMlh5MhFatmwZPDw8YGFhgdq1a+PcuXNp7r99+3aULVsWFhYWqFSpEvbv359NkeZ9urwWq1atQoMGDZAvXz7ky5cPXl5en3ztSDe6/m8k2rJlCxQKhWbiU8o8XV+Lt2/fYsiQIXBxcYG5uTlKly7Nzyo90fW1WLx4McqUKQNLS0u4ublh1KhRiImJyaZo864TJ06gbdu2KFy4MBQKBX7//fdPHnP8+HFUr14d5ubmKFmyJAICAnS/Y5HHbNmyRZiZmYm1a9eK69evi/79+wsHBwcRFhaW4v6nT58WxsbG4ocffhA3btwQkydPFqampuLq1avZHHneo+tr0b17d7Fs2TJx6dIlcfPmTdG7d29hb28vnjx5ks2R5026vh6JgoODhaurq2jQoIH48ssvsyfYPE7X1yI2NlbUqFFDtG7dWpw6dUoEBweL48ePi6CgoGyOPO/R9bXYtGmTMDc3F5s2bRLBwcHi4MGDwsXFRYwaNSqbI8979u/fLyZNmiR27dolAIjdu3enuf+DBw+ElZWVGD16tLhx44b46aefhLGxsQgMDNTpfvNcIlSrVi0xZMgQzbZKpRKFCxcW/v7+Ke7fpUsX0aZNG62y2rVri2+++SZL4zQEur4WH0tISBC2trZi/fr1WRWiQcnI65GQkCDq1q0rVq9eLXx9fZkI6Ymur8Uvv/wiihcvLuLi4rIrRIOh62sxZMgQ0bRpU62y0aNHi3r16mVpnIYmPYnQd999JypUqKBV5uPjI7y9vXW6rzzVNBYXF4cLFy7Ay8tLU2ZkZAQvLy+cOXMmxWPOnDmjtT8AeHt7p7o/pU9GXouPvX//HvHx8XpfYM8QZfT1mDFjBgoWLIi+fftmR5gGISOvxd69e1GnTh0MGTIEhQoVQsWKFTF79myoVKrsCjtPyshrUbduXVy4cEHTfPbgwQPs378frVu3zpaYKYm+vr9zxMzS+hIeHg6VSqVZniNRoUKFcOvWrRSPCQ0NTXH/0NDQLIvTEGTktfjYuHHjULhw4WRvdNJdRl6PU6dOYc2aNQgKCsqGCA1HRl6LBw8e4OjRo+jRowf279+Pe/fuYfDgwYiPj4efn192hJ0nZeS16N69O8LDw1G/fn0IIZCQkICBAwdi4sSJ2REyfSC17++IiAhER0fD0tIyXefJUzVClHfMmTMHW7Zswe7du2FhYSF3OAbn3bt36NmzJ1atWgVHR0e5wzF4arUaBQsWxMqVK+Hp6QkfHx9MmjQJy5cvlzs0g3P8+HHMnj0bP//8My5evIhdu3Zh3759mDlzptyhUQblqRohR0dHGBsbIywsTKs8LCwMzs7OKR7j7Oys0/6UPhl5LRLNnz8fc+bMweHDh1G5cuWsDNNg6Pp63L9/HyEhIWjbtq2mTK1WAwBMTExw+/ZtlChRImuDzqMy8r/h4uICU1NTGBsba8rKlSuH0NBQxMXFwczMLEtjzqsy8lpMmTIFPXv2RL9+/QAAlSpVQlRUFAYMGIBJkyZpLRJOWSu17287O7t01wYBeaxGyMzMDJ6enjhy5IimTK1W48iRI6hTp06Kx9SpU0drfwA4dOhQqvtT+mTktQCAH374ATNnzkRgYCBq1KiRHaEaBF1fj7Jly+Lq1asICgrSXL744gs0adIEQUFBcHNzy87w85SM/G/Uq1cP9+7d0ySjAHDnzh24uLgwCcqEjLwW79+/T5bsJCaogkt3Ziu9fX/r1o8759uyZYswNzcXAQEB4saNG2LAgAHCwcFBhIaGCiGE6Nmzpxg/frxm/9OnTwsTExMxf/58cfPmTeHn58fh83qi62sxZ84cYWZmJnbs2CGeP3+uubx7906uh5Cn6Pp6fIyjxvRH19fi0aNHwtbWVgwdOlTcvn1b/Pnnn6JgwYLi+++/l+sh5Bm6vhZ+fn7C1tZWbN68WTx48ED89ddfokSJEqJLly5yPYQ84927d+LSpUvi0qVLAoBYuHChuHTpknj48KEQQojx48eLnj17avZPHD4/duxYcfPmTbFs2TIOn0/0008/iaJFiwozMzNRq1YtcfbsWc1tjRo1Er6+vlr7b9u2TZQuXVqYmZmJChUqiH379mVzxHmXLq+Fu7u7AJDs4ufnl/2B51G6/m98iImQfun6Wvzzzz+idu3awtzcXBQvXlzMmjVLJCQkZHPUeZMur0V8fLyYNm2aKFGihLCwsBBubm5i8ODB4s2bN9kfeB5z7NixFL8DEp9/X19f0ahRo2THVK1aVZiZmYnixYuLdevW6Xy/CiFYl0dERESGKU/1ESIiIiLSBRMhIiIiMlhMhIiIiMhgMREiIiIig8VEiIiIiAwWEyEiIiIyWEyEiIiIyGAxESIiLQEBAXBwcJA7jAxTKBT4/fff09ynd+/eaNeuXbbEQ0Q5GxMhojyod+/eUCgUyS737t2TOzQEBARo4jEyMkKRIkXQp08fvHjxQi/nf/78OVq1agUACAkJgUKhQFBQkNY+S5YsQUBAgF7uLzXTpk3TPE5jY2O4ublhwIABeP36tU7nYdJGlLXy1OrzRJSkZcuWWLdunVaZk5OTTNFos7Ozw+3bt6FWq3H58mX06dMHz549w8GDBzN97tRWDf+Qvb19pu8nPSpUqIDDhw9DpVLh5s2b+Prrr6FUKrF169ZsuX8i+jTWCBHlUebm5nB2dta6GBsbY+HChahUqRKsra3h5uaGwYMHIzIyMtXzXL58GU2aNIGtrS3s7Ozg6emJ//77T3P7qVOn0KBBA1haWsLNzQ3Dhw9HVFRUmrEpFAo4OzujcOHCaNWqFYYPH47Dhw8jOjoaarUaM2bMQJEiRWBubo6qVasiMDBQc2xcXByGDh0KFxcXWFhYwN3dHf7+/lrnTmwaK1asGACgWrVqUCgUaNy4MQDtWpaVK1eicOHCWiu7A8CXX36Jr7/+WrO9Z88eVK9eHRYWFihevDimT5+OhISENB+niYkJnJ2d4erqCi8vL3Tu3BmHDh3S3K5SqdC3b18UK1YMlpaWKFOmDJYsWaK5fdq0aVi/fj327NmjqV06fvw4AODx48fo0qULHBwckD9/fnz55ZcICQlJMx4iSo6JEJGBMTIywo8//ojr169j/fr1OHr0KL777rtU9+/RoweKFCmC8+fP48KFCxg/fjxMTU0BAPfv30fLli3RsWNHXLlyBVu3bsWpU6cwdOhQnWKytLSEWq1GQkIClixZggULFmD+/Pm4cuUKvL298cUXX+Du3bsAgB9//BF79+7Ftm3bcPv2bWzatAkeHh4pnvfcuXMAgMOHD+P58+fYtWtXsn06d+6MV69e4dixY5qy169fIzAwED169AAAnDx5Er169cKIESNw48YNrFixAgEBAZg1a1a6H2NISAgOHjwIMzMzTZlarUaRIkWwfft23LhxA1OnTsXEiROxbds2AMCYMWPQpUsXtGzZEs+fP8fz589Rt25dxMfHw9vbG7a2tjh58iROnz4NGxsbtGzZEnFxcemOiYiAPLn6PJGh8/X1FcbGxsLa2lpz6dSpU4r7bt++XRQoUECzvW7dOmFvb6/ZtrW1FQEBASke27dvXzFgwACtspMnTwojIyMRHR2d4jEfn//OnTuidOnSokaNGkIIIQoXLixmzZqldUzNmjXF4MGDhRBCDBs2TDRt2lSo1eoUzw9A7N69WwghRHBwsAAgLl26pLWPr6+v+PLLLzXbX375pfj666812ytWrBCFCxcWKpVKCCFEs2bNxOzZs7XOsXHjRuHi4pJiDEII4efnJ4yMjIS1tbWwsLDQrKS9cOHCVI8RQoghQ4aIjh07phpr4n2XKVNG6zmIjY0VlpaW4uDBg2men4i0sY8QUR7VpEkT/PLLL5pta2trAFLtiL+/P27duoWIiAgkJCQgJiYG79+/h5WVVbLzjB49Gv369cPGjRs1zTslSpQAIDWbXblyBZs2bdLsL4SAWq1GcHAwypUrl2JsSqUSNjY2UKvViImJQf369bF69WpERETg2bNnqFevntb+9erVw+XLlwFIzVrNmzdHmTJl0LJlS3z++edo0aJFpp6rHj16oH///vj5559hbm6OTZs2oWvXrjAyMtI8ztOnT2vVAKlUqjSfNwAoU6YM9u7di5iYGPz6668ICgrCsGHDtPZZtmwZ1q5di0ePHiE6OhpxcXGoWrVqmvFevnwZ9+7dg62trVZ5TEwM7t+/n4FngMhwMREiyqOsra1RsmRJrbKQkBB8/vnnGDRoEGbNmoX8+fPj1KlT6Nu3L+Li4lL8Qp82bRq6d++Offv24cCBA/Dz88OWLVvQvn17REZG4ptvvsHw4cOTHVe0aNFUY7O1tcXFixdhZGQEFxcXWFpaAgAiIiI++biqV6+O4OBgHDhwAIcPH0aXLl3g5eWFHTt2fPLY1LRt2xZCCOzbtw81a9bEyZMnsWjRIs3tkZGRmD59Ojp06JDsWAsLi1TPa2ZmpnkN5syZgzZt2mD69OmYOXMmAGDLli0YM2YMFixYgDp16sDW1hbz5s3Dv//+m2a8kZGR8PT01EpAE+WUDvFEuQUTISIDcuHCBajVaixYsEBT25HYHyUtpUuXRunSpTFq1Ch069YN69atQ/v27VG9enXcuHEjWcL1KUZGRikeY2dnh8KFC+P06dNo1KiRpvz06dOoVauW1n4+Pj7w8fFBp06d0LJlS7x+/Rr58+fXOl9ifxyVSpVmPBYWFujQoQM2bdqEe/fuoUyZMqhevbrm9urVq+P27ds6P86PTZ48GU2bNsWgQYM0j7Nu3boYPHiwZp+Pa3TMzMySxV+9enVs3boVBQsWhJ2dXaZiIjJ07CxNZEBKliyJ+Ph4/PTTT3jw4AE2btyI5cuXp7p/dHQ0hg4diuPHj+Phw4c4ffo0zp8/r2nyGjduHP755x8MHToUQUFBuHv3Lvbs2aNzZ+kPjR07FnPnzsXWrVtx+/ZtjB8/HkFBQRgxYgQAYOHChdi8eTNu3bqFO3fuYPv27XB2dk5xEsiCBQvC0tISgYGBCAsLg1KpTPV+e/TogX379mHt2rWaTtKJpk6dig0bNmD69Om4fv06bt68iS1btmDy5Mk6PbY6deqgcuXKmD17NgCgVKlS+O+//3Dw4EHcuXMHU6ZMwfnz57WO8fDwwJUrV3D79m2Eh4cjPj4ePXr0gKOjI7788kucPHkSwcHBOH78OIYPH44nT57oFBORwZO7kxIR6V9KHWwTLVy4ULi4uAhLS0vh7e0tNmzYIACIN2/eCCG0OzPHxsaKrl27Cjc3N2FmZiYKFy4shg4dqtUR+ty5c6J58+bCxsZGWFtbi8qVKyfr7PyhjztLf0ylUolp06YJV1dXYWpqKqpUqSIOHDiguX3lypWiatWqwtraWtjZ2YlmzZqJixcvam7HB52lhRBi1apVws3NTRgZGYlGjRql+vyoVCrh4uIiAIj79+8niyswMFDUrVtXWFpaCjs7O1GrVi2xcuXKVB+Hn5+fqFKlSrLyzZs3C3Nzc/Ho0SMRExMjevfuLezt7YWDg4MYNGiQGD9+vNZxL1680Dy/AMSxY8eEEEI8f/5c9OrVSzg6Ogpzc3NRvHhx0b9/f6FUKlONiYiSUwghhLypGBEREZE82DRGREREBouJEBERERksJkJERERksJgIERERkcFiIkREREQGi4kQERERGSwmQkRERGSwmAgRERGRwWIiRERERAaLiRAREREZLCZCREREZLCYCBEREZHB+h9LJqRoJUPaZwAAAABJRU5ErkJggg==", + "image/png": 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", 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", 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" ] @@ -512,77 +536,87 @@ "len(data.corpus) 780\n", "len(data.test_inlier) 363\n", "len(data.test_outlier) 3135\n", - "fit_time: 1.8557980060577393\n", - "compute_auc_time: 15.691333770751953\n", + "fit_time: 2.2053072452545166\n", + "compute_auc_time: 17.268661975860596\n", "depth: 5 , Auc of digit: 0 is 0.9947574922781535\n", "doing digit 1 doing signature level 5\n", "len(data.corpus) 779\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.6090118885040283\n", - "compute_auc_time: 14.628620147705078\n", + "fit_time: 2.007657766342163\n", + "compute_auc_time: 22.80258798599243\n", "depth: 5 , Auc of digit: 1 is 0.9900453726235474\n", "doing digit 2 doing signature level 5\n", "len(data.corpus) 780\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 2.0345211029052734\n", - "compute_auc_time: 11.240407943725586\n", + "fit_time: 1.6560781002044678\n", + "compute_auc_time: 15.648115873336792\n", "depth: 5 , Auc of digit: 2 is 0.9912226414300441\n", "doing digit 3 doing signature level 5\n", "len(data.corpus) 719\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.4860689640045166\n", - "compute_auc_time: 14.095582962036133\n", + "fit_time: 1.6908342838287354\n", + "compute_auc_time: 12.489221096038818\n", "depth: 5 , Auc of digit: 3 is 0.9964675386283546\n", "doing digit 4 doing signature level 5\n", "len(data.corpus) 780\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.7567501068115234\n", - "compute_auc_time: 14.24120306968689\n", + "fit_time: 1.6653599739074707\n", + "compute_auc_time: 14.69511604309082\n", "depth: 5 , Auc of digit: 4 is 0.9999254893160445\n", "doing digit 5 doing signature level 5\n", "len(data.corpus) 720\n", "len(data.test_inlier) 335\n", "len(data.test_outlier) 3163\n", - "fit_time: 1.5514466762542725\n", - "compute_auc_time: 10.272958993911743\n", + "fit_time: 1.873572826385498\n", + "compute_auc_time: 13.695110082626343\n", "depth: 5 , Auc of digit: 5 is 0.9896433104789049\n", "doing digit 6 doing signature level 5\n", "len(data.corpus) 720\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.588888168334961\n", - "compute_auc_time: 9.079653024673462\n", + "fit_time: 1.7203340530395508\n", + "compute_auc_time: 15.188550233840942\n", "depth: 5 , Auc of digit: 6 is 0.9954961823439054\n", "doing digit 7 doing signature level 5\n", "len(data.corpus) 778\n", "len(data.test_inlier) 364\n", "len(data.test_outlier) 3134\n", - "fit_time: 1.7415499687194824\n", - "compute_auc_time: 9.925087928771973\n", + "fit_time: 1.8180418014526367\n", + "compute_auc_time: 14.598641157150269\n", "depth: 5 , Auc of digit: 7 is 0.9868265110766707\n", "doing digit 8 doing signature level 5\n", "len(data.corpus) 719\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.5423738956451416\n", - "compute_auc_time: 9.317086935043335\n", + "fit_time: 1.985002040863037\n", + "compute_auc_time: 23.181287050247192\n", "depth: 5 , Auc of digit: 8 is 0.9993119559651817\n", "doing digit 9 doing signature level 5\n", "len(data.corpus) 719\n", "len(data.test_inlier) 336\n", "len(data.test_outlier) 3162\n", - "fit_time: 1.5196259021759033\n", - "compute_auc_time: 9.053930044174194\n", + "fit_time: 2.2729718685150146\n", + "compute_auc_time: 23.99567413330078\n", "depth: 5 , Auc of digit: 9 is 0.9467071774946538\n" ] }, { "data": { - "image/png": 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", + "image/png": 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", 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", 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" ] @@ -595,8 +629,8 @@ "output_type": "stream", "text": [ "Overall, depth: 5 AUC: 0.9887056355253816\n", - "CPU times: user 14min 11s, sys: 3min 49s, total: 18min\n", - "Wall time: 8min\n" + "CPU times: user 21min 50s, sys: 4min 16s, total: 26min 7s\n", + "Wall time: 9min 11s\n" ] } ], @@ -645,6 +679,7 @@ " auc = compute_auc_given_dists(inlier_dists, outlier_dists)\n", " print(\"depth: \", depth, \", Auc of\", \" digit: \", digit, \" is \", auc)\n", "\n", + " # plot and compute auc\n", " all_inlier_dists = np.concatenate(list(digit_to_inlier_dists.values()))\n", " all_outlier_dists = np.concatenate(list(digit_to_outlier_dists.values()))\n", " auc = compute_auc_given_dists(\n", @@ -653,13 +688,24 @@ " plot=True,\n", " title=f\"Pen Digit (depth={depth})\",\n", " )\n", + "\n", + " # plot CDF\n", + " plot_cdf_given_dists(\n", + " all_inlier_dists,\n", + " all_outlier_dists,\n", + " bins=10000000,\n", + " xrange=(10e-7, 10e4),\n", + " xlog=True,\n", + " title=f\"\",\n", + " )\n", + "\n", " print(\"Overall, \", \"depth: \", depth, \"AUC: \", auc)\n", " depth_to_auc[depth] = auc" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -686,7 +732,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -696,7 +742,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "id": "a4675b42", "metadata": {}, "outputs": [ @@ -705,7 +751,7 @@ "output_type": "stream", "text": [ "doing digit 0 doing signature level 2\n", - "fit_time: 1.716937780380249\n" + "fit_time: 1.8049709796905518\n" ] } ], @@ -742,7 +788,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "id": "fa3d0039-5d50-4aa8-ac91-f76a83513315", "metadata": {}, "outputs": [ @@ -757,7 +803,7 @@ " 0.01140402, 0.02230901, 0.04476067, 0.0622557 , 0.02477818])" ] }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -805,7 +851,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -847,7 +893,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -861,7 +907,7 @@ " 0.01140395, 0.02230897, 0.0447607 , 0.06225568, 0.02477822])" ] }, - "execution_count": 12, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -879,7 +925,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -895,7 +941,7 @@ " -2.10565009e-08, 4.07364884e-08])" ] }, - "execution_count": 13, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -906,7 +952,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -922,7 +968,7 @@ " -2.62177412e-09, 2.01875338e-09])" ] }, - "execution_count": 14, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -933,7 +979,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -947,7 +993,7 @@ " 0.00013005, 0.00049769, 0.00200352, 0.00387577, 0.00061396])" ] }, - "execution_count": 15, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -965,7 +1011,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "id": "7b24a162-ab61-42ec-92d0-31067441e1ea", "metadata": {}, "outputs": [ @@ -980,7 +1026,7 @@ " 0.17178055, 0.2021866 , 0.50789138, 0.46324354, 0.2810891 ])" ] }, - "execution_count": 16, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -1035,7 +1081,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -1077,7 +1123,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -1091,7 +1137,7 @@ " 0.17178056, 0.2021866 , 0.57933628, 0.51903326, 0.2810891 ])" ] }, - "execution_count": 18, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -1102,7 +1148,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -1118,7 +1164,7 @@ " 5.57897246e-02, -7.37194078e-09])" ] }, - "execution_count": 19, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -1129,7 +1175,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 19, "metadata": {}, "outputs": [ { @@ -1145,7 +1191,7 @@ " 5.48009524e-02, -4.14434438e-09])" ] }, - "execution_count": 20, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -1156,7 +1202,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 20, "metadata": {}, "outputs": [ { @@ -1170,7 +1216,7 @@ " 0.02950856, 0.04087942, 0.25795365, 0.21459458, 0.07901108])" ] }, - "execution_count": 21, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -1190,7 +1236,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 21, "metadata": {}, "outputs": [ { @@ -1198,7 +1244,7 @@ "output_type": "stream", "text": [ "doing digit 0 doing signature level 4\n", - "fit_time: 1.2553520202636719\n" + "fit_time: 1.5386781692504883\n" ] } ], @@ -1238,7 +1284,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 22, "metadata": {}, "outputs": [ { @@ -1252,7 +1298,7 @@ " 0.03191909, 0.04620362, 0.10642687, 0.21951508, 0.04757213])" ] }, - "execution_count": 23, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -1300,7 +1346,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -1342,7 +1388,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 24, "metadata": {}, "outputs": [ { @@ -1356,7 +1402,7 @@ " 0.03191909, 0.04620365, 0.10642693, 0.21951484, 0.04757213])" ] }, - "execution_count": 25, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -1374,7 +1420,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 25, "metadata": {}, "outputs": [ { @@ -1390,7 +1436,7 @@ " -2.45914014e-07, -4.55573797e-09])" ] }, - "execution_count": 26, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -1401,7 +1447,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 26, "metadata": {}, "outputs": [ { @@ -1417,7 +1463,7 @@ " -1.07963610e-07, -4.33452318e-10])" ] }, - "execution_count": 27, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } @@ -1428,7 +1474,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 27, "metadata": {}, "outputs": [ { @@ -1444,7 +1490,7 @@ " 4.81868721e-02, 2.26310777e-03])" ] }, - "execution_count": 28, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } @@ -1462,7 +1508,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 28, "metadata": {}, "outputs": [ { @@ -1476,7 +1522,7 @@ " 1.66121212, 2.47344445, 8.79436824, 10.39406515, 3.76990887])" ] }, - "execution_count": 29, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } @@ -1531,7 +1577,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 29, "metadata": {}, "outputs": [], "source": [ @@ -1573,7 +1619,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 30, "metadata": {}, "outputs": [ { @@ -1587,7 +1633,7 @@ " 1.66121225, 2.47344389, 8.79436819, 10.39406662, 3.76990895])" ] }, - "execution_count": 31, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" } @@ -1598,7 +1644,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 31, "metadata": {}, "outputs": [ { @@ -1614,7 +1660,7 @@ " 1.47285028e-06, 8.01633524e-08])" ] }, - "execution_count": 32, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -1625,7 +1671,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 32, "metadata": {}, "outputs": [ { @@ -1641,7 +1687,7 @@ " 3.06178058e-05, 6.04417075e-07])" ] }, - "execution_count": 33, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } @@ -1652,7 +1698,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 33, "metadata": {}, "outputs": [ { @@ -1668,7 +1714,7 @@ " 1.08036590e+02, 1.42122129e+01])" ] }, - "execution_count": 34, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } @@ -1689,7 +1735,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 34, "id": "9f49674f-86c7-4d6e-88f9-98218ab69be3", "metadata": {}, "outputs": [], @@ -1705,7 +1751,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 35, "id": "60165b32-c950-4b0c-9526-3edcb7674e62", "metadata": {}, "outputs": [ @@ -1719,7 +1765,7 @@ "len(data.corpus) 5000\n", "len(data.test_inlier) 5000\n", "len(data.test_outlier) 5000\n", - "fit_time: 20.626681804656982\n" + "fit_time: 27.13375997543335\n" ] }, { @@ -1736,7 +1782,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 335.9436459541321\n", + "compute_auc_time: 332.76756405830383\n", "lead_lag: True inv_rest: True thres_distance: 4000 auc: 0.8228045999999999\n", "Threshold distance: 8000\n", "lead_lag: True\n", @@ -1744,7 +1790,7 @@ "len(data.corpus) 5000\n", "len(data.test_inlier) 5000\n", "len(data.test_outlier) 5000\n", - "fit_time: 23.2948579788208\n" + "fit_time: 21.94414520263672\n" ] }, { @@ -1761,7 +1807,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 338.6563048362732\n", + "compute_auc_time: 255.8750569820404\n", "lead_lag: True inv_rest: True thres_distance: 8000 auc: 0.8354452200000001\n", "Threshold distance: 16000\n", "lead_lag: True\n", @@ -1769,7 +1815,7 @@ "len(data.corpus) 5000\n", "len(data.test_inlier) 5000\n", "len(data.test_outlier) 5000\n", - "fit_time: 27.60756516456604\n" + "fit_time: 21.80716109275818\n" ] }, { @@ -1786,7 +1832,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 293.8441872596741\n", + "compute_auc_time: 294.45983505249023\n", "lead_lag: True inv_rest: True thres_distance: 16000 auc: 0.8360074\n", "Threshold distance: 32000\n", "lead_lag: True\n", @@ -1794,7 +1840,7 @@ "len(data.corpus) 5000\n", "len(data.test_inlier) 5000\n", "len(data.test_outlier) 5000\n", - "fit_time: 24.40476894378662\n" + "fit_time: 26.57306218147278\n" ] }, { @@ -1811,7 +1857,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 317.9939298629761\n", + "compute_auc_time: 333.42611503601074\n", "lead_lag: True inv_rest: True thres_distance: 32000 auc: 0.84355992\n", "Threshold distance: 4000\n", "lead_lag: True\n", @@ -1819,7 +1865,7 @@ "len(data.corpus) 5000\n", "len(data.test_inlier) 5000\n", "len(data.test_outlier) 5000\n", - "fit_time: 17.984686136245728\n" + "fit_time: 19.67205309867859\n" ] }, { @@ -1836,7 +1882,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 182.08021187782288\n", + "compute_auc_time: 380.14289903640747\n", "lead_lag: True inv_rest: False thres_distance: 4000 auc: 0.8257225199999999\n", "Threshold distance: 8000\n", "lead_lag: True\n", @@ -1844,7 +1890,7 @@ "len(data.corpus) 5000\n", "len(data.test_inlier) 5000\n", "len(data.test_outlier) 5000\n", - "fit_time: 17.325438022613525\n" + "fit_time: 16.292973041534424\n" ] }, { @@ -1861,7 +1907,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 207.74922394752502\n", + "compute_auc_time: 266.170264005661\n", "lead_lag: True inv_rest: False thres_distance: 8000 auc: 0.8343324400000001\n", "Threshold distance: 16000\n", "lead_lag: True\n", @@ -1869,7 +1915,7 @@ "len(data.corpus) 5000\n", "len(data.test_inlier) 5000\n", "len(data.test_outlier) 5000\n", - "fit_time: 15.623968124389648\n" + "fit_time: 16.08999800682068\n" ] }, { @@ -1886,7 +1932,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 234.3586070537567\n", + "compute_auc_time: 278.8102180957794\n", "lead_lag: True inv_rest: False thres_distance: 16000 auc: 0.84074052\n", "Threshold distance: 32000\n", "lead_lag: True\n", @@ -1894,7 +1940,7 @@ "len(data.corpus) 5000\n", "len(data.test_inlier) 5000\n", "len(data.test_outlier) 5000\n", - "fit_time: 18.165555000305176\n" + "fit_time: 21.187442302703857\n" ] }, { @@ -1911,7 +1957,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 252.45590329170227\n", + "compute_auc_time: 294.34289026260376\n", "lead_lag: True inv_rest: False thres_distance: 32000 auc: 0.8419482599999999\n", "Threshold distance: 4000\n", "lead_lag: False\n", @@ -1919,7 +1965,7 @@ "len(data.corpus) 5000\n", "len(data.test_inlier) 5000\n", "len(data.test_outlier) 5000\n", - "fit_time: 12.57522201538086\n" + "fit_time: 13.107696056365967\n" ] }, { @@ -1936,7 +1982,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 31.587750911712646\n", + "compute_auc_time: 60.903258085250854\n", "lead_lag: False inv_rest: True thres_distance: 4000 auc: 0.79083568\n", "Threshold distance: 8000\n", "lead_lag: False\n", @@ -1944,7 +1990,7 @@ "len(data.corpus) 5000\n", "len(data.test_inlier) 5000\n", "len(data.test_outlier) 5000\n", - "fit_time: 12.51298189163208\n" + "fit_time: 13.742963075637817\n" ] }, { @@ -1961,7 +2007,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 33.34321594238281\n", + "compute_auc_time: 78.29260683059692\n", "lead_lag: False inv_rest: True thres_distance: 8000 auc: 0.7972313600000001\n", "Threshold distance: 16000\n", "lead_lag: False\n", @@ -1969,7 +2015,7 @@ "len(data.corpus) 5000\n", "len(data.test_inlier) 5000\n", "len(data.test_outlier) 5000\n", - "fit_time: 12.596282005310059\n" + "fit_time: 13.91839075088501\n" ] }, { @@ -1986,7 +2032,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 32.92912983894348\n", + "compute_auc_time: 66.64873790740967\n", "lead_lag: False inv_rest: True thres_distance: 16000 auc: 0.7872241999999998\n", "Threshold distance: 32000\n", "lead_lag: False\n", @@ -1994,7 +2040,7 @@ "len(data.corpus) 5000\n", "len(data.test_inlier) 5000\n", "len(data.test_outlier) 5000\n", - "fit_time: 13.208525896072388\n" + "fit_time: 13.570491790771484\n" ] }, { @@ -2011,7 +2057,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 33.75607681274414\n", + "compute_auc_time: 73.1102991104126\n", "lead_lag: False inv_rest: True thres_distance: 32000 auc: 0.78283072\n", "Threshold distance: 4000\n", "lead_lag: False\n", @@ -2019,7 +2065,7 @@ "len(data.corpus) 5000\n", "len(data.test_inlier) 5000\n", "len(data.test_outlier) 5000\n", - "fit_time: 8.927592039108276\n" + "fit_time: 9.498934030532837\n" ] }, { @@ -2036,7 +2082,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 17.88940119743347\n", + "compute_auc_time: 18.494549036026\n", "lead_lag: False inv_rest: False thres_distance: 4000 auc: 0.80501948\n", "Threshold distance: 8000\n", "lead_lag: False\n", @@ -2044,7 +2090,7 @@ "len(data.corpus) 5000\n", "len(data.test_inlier) 5000\n", "len(data.test_outlier) 5000\n", - "fit_time: 9.03955888748169\n" + "fit_time: 9.560570001602173\n" ] }, { @@ -2061,7 +2107,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 18.115923166275024\n", + "compute_auc_time: 18.934290885925293\n", "lead_lag: False inv_rest: False thres_distance: 8000 auc: 0.80946924\n", "Threshold distance: 16000\n", "lead_lag: False\n", @@ -2069,7 +2115,7 @@ "len(data.corpus) 5000\n", "len(data.test_inlier) 5000\n", "len(data.test_outlier) 5000\n", - "fit_time: 8.920457124710083\n" + "fit_time: 9.271188974380493\n" ] }, { @@ -2086,7 +2132,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 18.476377248764038\n", + "compute_auc_time: 18.92277979850769\n", "lead_lag: False inv_rest: False thres_distance: 16000 auc: 0.79710896\n", "Threshold distance: 32000\n", "lead_lag: False\n", @@ -2094,7 +2140,7 @@ "len(data.corpus) 5000\n", "len(data.test_inlier) 5000\n", "len(data.test_outlier) 5000\n", - "fit_time: 9.18234395980835\n" + "fit_time: 9.519912004470825\n" ] }, { @@ -2111,10 +2157,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "compute_auc_time: 19.352643966674805\n", + "compute_auc_time: 19.96116018295288\n", "lead_lag: False inv_rest: False thres_distance: 32000 auc: 0.78804452\n", - "CPU times: user 4h 43min 7s, sys: 10min 21s, total: 4h 53min 28s\n", - "Wall time: 47min 7s\n" + "CPU times: user 5h 31min 42s, sys: 9min 42s, total: 5h 41min 24s\n", + "Wall time: 54min 25s\n" ] } ], @@ -2204,7 +2250,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 36, "id": "303b9c84", "metadata": {}, "outputs": [], @@ -2245,7 +2291,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 37, "metadata": {}, "outputs": [], "source": [ @@ -2254,7 +2300,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 38, "id": "a22e802a-c924-4ead-9c8d-0fb3c262e84d", "metadata": {}, "outputs": [ @@ -2262,101 +2308,101 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n", - "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:261: RuntimeWarning: invalid value encountered in divide\n", + "/Users/rchan/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:264: RuntimeWarning: invalid value encountered in divide\n", " rho = numerator / denominator\n" ] }, @@ -2364,8 +2410,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 4h 43min 46s, sys: 1h 8min 20s, total: 5h 52min 6s\n", - "Wall time: 59min 55s\n" + "CPU times: user 4h 3min 20s, sys: 1h 6min 6s, total: 5h 9min 27s\n", + "Wall time: 54min 29s\n" ] } ], @@ -2402,7 +2448,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 39, "id": "e6043a4d-1ba9-4e77-acbb-5a758d9c1693", "metadata": {}, "outputs": [ @@ -2431,7 +2477,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 40, "id": "4c52ba35-77cf-45e4-bc24-b8084a0a6583", "metadata": {}, "outputs": [ @@ -2724,7 +2770,7 @@ "27 Wine 0.774476 0.086879 0.53 0.02" ] }, - "execution_count": 41, + "execution_count": 40, "metadata": {}, "output_type": "execute_result" } @@ -2735,7 +2781,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 41, "id": "168f43f7-d6a7-49de-b95a-336ac6b2cb1c", "metadata": {}, "outputs": [ @@ -3028,7 +3074,7 @@ "27 Wine 0.774476 0.086879 0.53 0.02" ] }, - "execution_count": 42, + "execution_count": 41, "metadata": {}, "output_type": "execute_result" } @@ -3049,25 +3095,26 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 42, "id": "887c4530-28dd-4df7-b1f5-58c74e40f0eb", "metadata": {}, - "outputs": [], - "source": [ - "data.load_language_data()" - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "id": "cf434a5d-68dc-46f4-9a69-a8a1cff32d5d", - "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "len(data.corpus) 63862\n", + "len(data.test_inlier) 16138\n", + "len(data.test_outlier) 15862\n" + ] + } + ], "source": [ - "random.seed(1)\n", - "data.corpus = random.sample(list(data.corpus), 800)\n", - "data.test_inlier = random.sample(list(data.test_inlier), 10)\n", - "data.test_outlier = random.sample(list(data.test_outlier), 10)" + "data = Data.Data(if_sample=False)\n", + "data.load_language_data()\n", + "print(\"len(data.corpus)\", len(data.corpus))\n", + "print(\"len(data.test_inlier)\", len(data.test_inlier))\n", + "print(\"len(data.test_outlier)\", len(data.test_outlier))" ] }, { @@ -3080,19 +3127,27 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 46, "id": "87ec6dc8-75f7-436b-8528-00093a576ba7", "metadata": {}, "outputs": [ { - "ename": "RuntimeError", - "evalue": "Legitimate width 2 <-> 256 exceeded", + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/rchan/opt/miniconda3/envs/anomaly-detection-paper/lib/python3.9/site-packages/sktime/transformations/panel/signature_based/_signature_method.py:100: UserWarning: iisignature backend of SignatureTransformer is experimental and not systematically tested, due to lack of stable installation process for iisignature via pip. Kindly exercise caution, and report any issues on the sktime issue tracker.\n", + " warn(\n" + ] + }, + { + "ename": "ValueError", + "evalue": "iisignature does not name a valid backend", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", "File \u001b[0;32m:5\u001b[0m\n", - "File \u001b[0;32m~/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:139\u001b[0m, in \u001b[0;36mSignatureMahalanobisKNN.fit\u001b[0;34m(self, knn_library, X_train, signatures_train, knn_algorithm, signature_kwargs, **kwargs)\u001b[0m\n\u001b[1;32m 134\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39msignature_transform \u001b[39m=\u001b[39m SignatureTransformer(\n\u001b[1;32m 135\u001b[0m \u001b[39m*\u001b[39m\u001b[39m*\u001b[39msignature_kwargs,\n\u001b[1;32m 136\u001b[0m )\n\u001b[1;32m 138\u001b[0m \u001b[39m# compute signatures\u001b[39;00m\n\u001b[0;32m--> 139\u001b[0m sigs \u001b[39m=\u001b[39m Parallel(n_jobs\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mn_jobs)(\n\u001b[1;32m 140\u001b[0m delayed(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49msignature_transform\u001b[39m.\u001b[39;49mfit_transform)(X_train[i])\n\u001b[1;32m 141\u001b[0m \u001b[39mfor\u001b[39;49;00m i \u001b[39min\u001b[39;49;00m \u001b[39mrange\u001b[39;49m(\u001b[39mlen\u001b[39;49m(X_train))\n\u001b[1;32m 142\u001b[0m )\n\u001b[1;32m 143\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39msignatures_train \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39marray(pd\u001b[39m.\u001b[39mconcat(sigs))\n\u001b[1;32m 144\u001b[0m \u001b[39melse\u001b[39;00m:\n", + "File \u001b[0;32m~/Library/CloudStorage/OneDrive-TheAlanTuringInstitute/rough_paths/signature_mahalanobis_knn/src/signature_mahalanobis_knn/sig_mahal_knn.py:142\u001b[0m, in \u001b[0;36mSignatureMahalanobisKNN.fit\u001b[0;34m(self, knn_library, X_train, signatures_train, knn_algorithm, signature_kwargs, **kwargs)\u001b[0m\n\u001b[1;32m 137\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39msignature_transform \u001b[39m=\u001b[39m SignatureTransformer(\n\u001b[1;32m 138\u001b[0m \u001b[39m*\u001b[39m\u001b[39m*\u001b[39msignature_kwargs,\n\u001b[1;32m 139\u001b[0m )\n\u001b[1;32m 141\u001b[0m \u001b[39m# compute signatures\u001b[39;00m\n\u001b[0;32m--> 142\u001b[0m sigs \u001b[39m=\u001b[39m Parallel(n_jobs\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mn_jobs)(\n\u001b[1;32m 143\u001b[0m delayed(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49msignature_transform\u001b[39m.\u001b[39;49mfit_transform)(X_train[i])\n\u001b[1;32m 144\u001b[0m \u001b[39mfor\u001b[39;49;00m i \u001b[39min\u001b[39;49;00m \u001b[39mrange\u001b[39;49m(\u001b[39mlen\u001b[39;49m(X_train))\n\u001b[1;32m 145\u001b[0m )\n\u001b[1;32m 146\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39msignatures_train \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39marray(pd\u001b[39m.\u001b[39mconcat(sigs))\n\u001b[1;32m 147\u001b[0m \u001b[39melse\u001b[39;00m:\n", "File \u001b[0;32m~/opt/miniconda3/envs/anomaly-detection-paper/lib/python3.9/site-packages/joblib/parallel.py:1863\u001b[0m, in \u001b[0;36mParallel.__call__\u001b[0;34m(self, iterable)\u001b[0m\n\u001b[1;32m 1861\u001b[0m output \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_get_sequential_output(iterable)\n\u001b[1;32m 1862\u001b[0m \u001b[39mnext\u001b[39m(output)\n\u001b[0;32m-> 1863\u001b[0m \u001b[39mreturn\u001b[39;00m output \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mreturn_generator \u001b[39melse\u001b[39;00m \u001b[39mlist\u001b[39;49m(output)\n\u001b[1;32m 1865\u001b[0m \u001b[39m# Let's create an ID that uniquely identifies the current call. If the\u001b[39;00m\n\u001b[1;32m 1866\u001b[0m \u001b[39m# call is interrupted early and that the same instance is immediately\u001b[39;00m\n\u001b[1;32m 1867\u001b[0m \u001b[39m# re-used, this id will be used to prevent workers that were\u001b[39;00m\n\u001b[1;32m 1868\u001b[0m \u001b[39m# concurrently finalizing a task from the previous call to run the\u001b[39;00m\n\u001b[1;32m 1869\u001b[0m \u001b[39m# callback.\u001b[39;00m\n\u001b[1;32m 1870\u001b[0m \u001b[39mwith\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_lock:\n", "File \u001b[0;32m~/opt/miniconda3/envs/anomaly-detection-paper/lib/python3.9/site-packages/joblib/parallel.py:1792\u001b[0m, in \u001b[0;36mParallel._get_sequential_output\u001b[0;34m(self, iterable)\u001b[0m\n\u001b[1;32m 1790\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mn_dispatched_batches \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m \u001b[39m1\u001b[39m\n\u001b[1;32m 1791\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mn_dispatched_tasks \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m \u001b[39m1\u001b[39m\n\u001b[0;32m-> 1792\u001b[0m res \u001b[39m=\u001b[39m func(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m 1793\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mn_completed_tasks \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m \u001b[39m1\u001b[39m\n\u001b[1;32m 1794\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mprint_progress()\n", "File \u001b[0;32m~/opt/miniconda3/envs/anomaly-detection-paper/lib/python3.9/site-packages/sktime/transformations/base.py:669\u001b[0m, in \u001b[0;36mBaseTransformer.fit_transform\u001b[0;34m(self, X, y)\u001b[0m\n\u001b[1;32m 604\u001b[0m \u001b[39m\u001b[39m\u001b[39m\"\"\"Fit to data, then transform it.\u001b[39;00m\n\u001b[1;32m 605\u001b[0m \n\u001b[1;32m 606\u001b[0m \u001b[39mFits the transformer to X and y and returns a transformed version of X.\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 665\u001b[0m \u001b[39m Example: i-th instance of the output is the i-th window running over `X`\u001b[39;00m\n\u001b[1;32m 666\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m 667\u001b[0m \u001b[39m# Non-optimized default implementation; override when a better\u001b[39;00m\n\u001b[1;32m 668\u001b[0m \u001b[39m# method is possible for a given algorithm.\u001b[39;00m\n\u001b[0;32m--> 669\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mfit(X, y)\u001b[39m.\u001b[39;49mtransform(X, y)\n", @@ -3100,13 +3155,9 @@ "File \u001b[0;32m~/opt/miniconda3/envs/anomaly-detection-paper/lib/python3.9/site-packages/sktime/transformations/panel/signature_based/_signature_method.py:142\u001b[0m, in \u001b[0;36mSignatureTransformer._transform\u001b[0;34m(self, X, y)\u001b[0m\n\u001b[1;32m 141\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_transform\u001b[39m(\u001b[39mself\u001b[39m, X, y\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m):\n\u001b[0;32m--> 142\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49msignature_method\u001b[39m.\u001b[39;49mtransform(X)\n", "File \u001b[0;32m~/opt/miniconda3/envs/anomaly-detection-paper/lib/python3.9/site-packages/sklearn/pipeline.py:696\u001b[0m, in \u001b[0;36mPipeline.transform\u001b[0;34m(self, X)\u001b[0m\n\u001b[1;32m 694\u001b[0m Xt \u001b[39m=\u001b[39m X\n\u001b[1;32m 695\u001b[0m \u001b[39mfor\u001b[39;00m _, _, transform \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_iter():\n\u001b[0;32m--> 696\u001b[0m Xt \u001b[39m=\u001b[39m transform\u001b[39m.\u001b[39;49mtransform(Xt)\n\u001b[1;32m 697\u001b[0m \u001b[39mreturn\u001b[39;00m Xt\n", "File \u001b[0;32m~/opt/miniconda3/envs/anomaly-detection-paper/lib/python3.9/site-packages/sktime/transformations/base.py:583\u001b[0m, in \u001b[0;36mBaseTransformer.transform\u001b[0;34m(self, X, y)\u001b[0m\n\u001b[1;32m 580\u001b[0m X_inner, y_inner, metadata \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_check_X_y(X\u001b[39m=\u001b[39mX, y\u001b[39m=\u001b[39my, return_metadata\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m)\n\u001b[1;32m 582\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39misinstance\u001b[39m(X_inner, VectorizedDF):\n\u001b[0;32m--> 583\u001b[0m Xt \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_transform(X\u001b[39m=\u001b[39;49mX_inner, y\u001b[39m=\u001b[39;49my_inner)\n\u001b[1;32m 584\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 585\u001b[0m \u001b[39m# otherwise we call the vectorized version of predict\u001b[39;00m\n\u001b[1;32m 586\u001b[0m Xt \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_vectorize(\u001b[39m\"\u001b[39m\u001b[39mtransform\u001b[39m\u001b[39m\"\u001b[39m, X\u001b[39m=\u001b[39mX_inner, y\u001b[39m=\u001b[39my_inner)\n", - "File \u001b[0;32m~/opt/miniconda3/envs/anomaly-detection-paper/lib/python3.9/site-packages/sktime/transformations/panel/signature_based/_compute.py:97\u001b[0m, in \u001b[0;36m_WindowSignatureTransform._transform\u001b[0;34m(self, X, y)\u001b[0m\n\u001b[1;32m 93\u001b[0m signature_group \u001b[39m=\u001b[39m []\n\u001b[1;32m 94\u001b[0m \u001b[39mfor\u001b[39;00m window \u001b[39min\u001b[39;00m window_group:\n\u001b[1;32m 95\u001b[0m \u001b[39m# Signature computation step\u001b[39;00m\n\u001b[1;32m 96\u001b[0m signature \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39mstack(\n\u001b[0;32m---> 97\u001b[0m [transform(x[window\u001b[39m.\u001b[39mstart : window\u001b[39m.\u001b[39mend]) \u001b[39mfor\u001b[39;00m x \u001b[39min\u001b[39;00m data]\n\u001b[1;32m 98\u001b[0m )\u001b[39m.\u001b[39mreshape(data\u001b[39m.\u001b[39mshape[\u001b[39m0\u001b[39m], \u001b[39m-\u001b[39m\u001b[39m1\u001b[39m)\n\u001b[1;32m 99\u001b[0m \u001b[39m# Rescale if specified\u001b[39;00m\n\u001b[1;32m 100\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mrescaling \u001b[39m==\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mpost\u001b[39m\u001b[39m\"\u001b[39m:\n", - "File \u001b[0;32m~/opt/miniconda3/envs/anomaly-detection-paper/lib/python3.9/site-packages/sktime/transformations/panel/signature_based/_compute.py:97\u001b[0m, in \u001b[0;36m\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 93\u001b[0m signature_group \u001b[39m=\u001b[39m []\n\u001b[1;32m 94\u001b[0m \u001b[39mfor\u001b[39;00m window \u001b[39min\u001b[39;00m window_group:\n\u001b[1;32m 95\u001b[0m \u001b[39m# Signature computation step\u001b[39;00m\n\u001b[1;32m 96\u001b[0m signature \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39mstack(\n\u001b[0;32m---> 97\u001b[0m [transform(x[window\u001b[39m.\u001b[39;49mstart : window\u001b[39m.\u001b[39;49mend]) \u001b[39mfor\u001b[39;00m x \u001b[39min\u001b[39;00m data]\n\u001b[1;32m 98\u001b[0m )\u001b[39m.\u001b[39mreshape(data\u001b[39m.\u001b[39mshape[\u001b[39m0\u001b[39m], \u001b[39m-\u001b[39m\u001b[39m1\u001b[39m)\n\u001b[1;32m 99\u001b[0m \u001b[39m# Rescale if specified\u001b[39;00m\n\u001b[1;32m 100\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mrescaling \u001b[39m==\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mpost\u001b[39m\u001b[39m\"\u001b[39m:\n", - "File \u001b[0;32m~/opt/miniconda3/envs/anomaly-detection-paper/lib/python3.9/site-packages/sktime/transformations/panel/signature_based/_compute.py:81\u001b[0m, in \u001b[0;36m_WindowSignatureTransform._transform..transform\u001b[0;34m(x)\u001b[0m\n\u001b[1;32m 80\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mtransform\u001b[39m(x):\n\u001b[0;32m---> 81\u001b[0m \u001b[39mreturn\u001b[39;00m esig\u001b[39m.\u001b[39;49mstream2sig(x, depth)[\u001b[39m1\u001b[39m:]\u001b[39m.\u001b[39mreshape(\u001b[39m-\u001b[39m\u001b[39m1\u001b[39m, \u001b[39m1\u001b[39m)\n", - "File \u001b[0;32m~/opt/miniconda3/envs/anomaly-detection-paper/lib/python3.9/site-packages/esig/__init__.py:126\u001b[0m, in \u001b[0;36m_verify_stream_arg..decorator..wrapper\u001b[0;34m(stream, *args, **kwargs)\u001b[0m\n\u001b[1;32m 123\u001b[0m str_types \u001b[39m=\u001b[39m \u001b[39mtuple\u001b[39m(\u001b[39mmap\u001b[39m(\u001b[39mstr\u001b[39m, types))\n\u001b[1;32m 124\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mTypeError\u001b[39;00m(\u001b[39m\"\u001b[39m\u001b[39mValues must be of one of the following types \u001b[39m\u001b[39m{}\u001b[39;00m\u001b[39m\"\u001b[39m\u001b[39m.\u001b[39mformat(str_types))\n\u001b[0;32m--> 126\u001b[0m \u001b[39mreturn\u001b[39;00m func(as_array, \u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n", - "File \u001b[0;32m~/opt/miniconda3/envs/anomaly-detection-paper/lib/python3.9/site-packages/esig/__init__.py:145\u001b[0m, in \u001b[0;36mstream2sig\u001b[0;34m(stream, depth)\u001b[0m\n\u001b[1;32m 142\u001b[0m \u001b[39mreturn\u001b[39;00m numpy\u001b[39m.\u001b[39mconcatenate([[\u001b[39m1.0\u001b[39m], numpy\u001b[39m.\u001b[39msum(numpy\u001b[39m.\u001b[39mdiff(stream, axis\u001b[39m=\u001b[39m\u001b[39m0\u001b[39m), axis\u001b[39m=\u001b[39m\u001b[39m0\u001b[39m)])\n\u001b[1;32m 144\u001b[0m backend \u001b[39m=\u001b[39m get_backend()\n\u001b[0;32m--> 145\u001b[0m \u001b[39mreturn\u001b[39;00m backend\u001b[39m.\u001b[39;49mcompute_signature(stream, depth)\n", - "File \u001b[0;32m~/opt/miniconda3/envs/anomaly-detection-paper/lib/python3.9/site-packages/esig/backends.py:130\u001b[0m, in \u001b[0;36mLibalgebraBackend.compute_signature\u001b[0;34m(self, stream, depth)\u001b[0m\n\u001b[1;32m 129\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mcompute_signature\u001b[39m(\u001b[39mself\u001b[39m, stream, depth):\n\u001b[0;32m--> 130\u001b[0m \u001b[39mreturn\u001b[39;00m tosig\u001b[39m.\u001b[39;49mstream2sig(stream, depth)\n", - "\u001b[0;31mRuntimeError\u001b[0m: Legitimate width 2 <-> 256 exceeded" + "File \u001b[0;32m~/opt/miniconda3/envs/anomaly-detection-paper/lib/python3.9/site-packages/sktime/transformations/panel/signature_based/_compute.py:68\u001b[0m, in \u001b[0;36m_WindowSignatureTransform._transform\u001b[0;34m(self, X, y)\u001b[0m\n\u001b[1;32m 65\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mesig\u001b[39;00m\n\u001b[1;32m 67\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mbackend \u001b[39m==\u001b[39m \u001b[39m\"\u001b[39m\u001b[39miisignature\u001b[39m\u001b[39m\"\u001b[39m:\n\u001b[0;32m---> 68\u001b[0m esig\u001b[39m.\u001b[39;49mset_backend(\u001b[39m\"\u001b[39;49m\u001b[39miisignature\u001b[39;49m\u001b[39m\"\u001b[39;49m)\n\u001b[1;32m 70\u001b[0m depth \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39msig_depth\n\u001b[1;32m 71\u001b[0m data \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39mswapaxes(X, \u001b[39m1\u001b[39m, \u001b[39m2\u001b[39m)\n", + "File \u001b[0;32m~/opt/miniconda3/envs/anomaly-detection-paper/lib/python3.9/site-packages/esig/backends.py:47\u001b[0m, in \u001b[0;36mset_backend\u001b[0;34m(cls_or_name)\u001b[0m\n\u001b[1;32m 45\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39misinstance\u001b[39m(cls_or_name, \u001b[39mstr\u001b[39m):\n\u001b[1;32m 46\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m cls_or_name \u001b[39min\u001b[39;00m BACKENDS:\n\u001b[0;32m---> 47\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\u001b[39m\"\u001b[39m\u001b[39m%s\u001b[39;00m\u001b[39m does not name a valid backend\u001b[39m\u001b[39m\"\u001b[39m \u001b[39m%\u001b[39m cls_or_name)\n\u001b[1;32m 48\u001b[0m _BACKEND_CONTAINER\u001b[39m.\u001b[39mcontext \u001b[39m=\u001b[39m BACKENDS[cls_or_name]()\n\u001b[1;32m 49\u001b[0m \u001b[39melif\u001b[39;00m \u001b[39misinstance\u001b[39m(cls_or_name, BackendBase):\n", + "\u001b[0;31mValueError\u001b[0m: iisignature does not name a valid backend" ] } ], diff --git a/pyproject.toml b/pyproject.toml index 55e87cf..e9855c2 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -38,6 +38,9 @@ dependencies = [ ] [project.optional-dependencies] +signatures = [ + 'esig; python_version < "3.10"', +] test = [ "pytest >=6", "pytest-cov >=3", diff --git a/src/signature_mahalanobis_knn/utils.py b/src/signature_mahalanobis_knn/utils.py index dc154de..8e6ec35 100644 --- a/src/signature_mahalanobis_knn/utils.py +++ b/src/signature_mahalanobis_knn/utils.py @@ -40,9 +40,9 @@ def plot_roc_curve( roc_auc = roc_auc_score(y_true, y_score) plt.title(f"Receiver Operating Characteristic {title}") - plt.plot(fp_rate, tp_rate, "b", label=f"AUC = {round(roc_auc, 2)}") + plt.plot(fp_rate, tp_rate, "b", label=f"AUC = {round(roc_auc, 2)}", linewidth=2) plt.legend(loc="lower right") - plt.plot([0, 1], [0, 1], "r--") + plt.plot([0, 1], [0, 1], "r--", linewidth=2) plt.xlim([0, 1]) plt.ylim([0, 1]) plt.ylabel("True Positive Rate") @@ -162,3 +162,87 @@ def compute_auc( plot=plot, title=title, ) + + +def plot_cdf_given_dists( + distances_in: np.ndarray, + distances_out: np.ndarray, + bins: int | np.array = 50, + xrange: tuple[float, float] | None = None, + xticks: list[float] | None = None, + xlog: bool = False, + xlog_base: int = 10, + title: str = "", +): + """ + Plot an empirical cumulative distributions of the + distances of inliers and outliers. + + Parameters + ---------- + distances_in : np.ndarray + KNN distances for the inlier data points. + distances_out : np.ndarray + KNN distances for the outlier data points. + bins : int | np.array, optional + Number of bins or the bins, by default 10. + If int, then the bins will be equally spaced. + If array, then the sequence defines the bin edges. + xrange : tuple[float, float] | None, optional + Range of the x-axis, by default None. + If None, then the range will be the minimum and maximum + of the distances. + xticks : list[float] | None, optional + Tick values of the x-axis, by default None. + If None, then the ticks will be automatically generated. + xlog : bool, optional + Whether to use log scale for the x-axis, by default False. + xlog_base : int, optional + Base of the log scale, by default 10. + Only used when xlog is True. + title : str, optional + Title for the ROC curve plot, by default "". + Only used when plot is True. + """ + # obtain the empirical cumulative distribution functions + sorted_inlier = np.sort(distances_in) + cumulative_inliers = np.arange(1, len(sorted_inlier) + 1) / len(sorted_inlier) + sorted_outlier = np.sort(distances_out) + cumulative_outliers = np.arange(1, len(sorted_outlier) + 1) / len(sorted_outlier) + + # define the empirical cumulative distribution functions + def empirical_cdf_inliers(x): + return np.interp(x, sorted_inlier, cumulative_inliers, left=0.0, right=1.0) + + def empirical_cdf_outliers(x): + return np.interp(x, sorted_outlier, cumulative_outliers, left=0.0, right=1.0) + + # obtain the range of x to evaluate the ECDFs + xmin = min(np.min(distances_in), np.min(distances_out)) + xmax = max(np.max(distances_in), np.max(distances_out)) + x = np.linspace(xmin, xmax, bins) + + # plot the cumulative functions + plt.plot( + x, + empirical_cdf_inliers(x), + c="blue", + label="inliers", + linestyle="--", + linewidth=2, + ) + plt.plot(x, empirical_cdf_outliers(x), c="orange", label="anomalies", linewidth=2) + plt.grid() + if title != "": + plt.title(title) + plt.legend(loc="lower right") + if xrange is not None: + plt.xlim(xrange) + if xticks is not None: + plt.xticks(xticks) + if xlog: + plt.xscale("log", base=xlog_base) + plt.ylim([0, 1]) + plt.ylabel("Cumulative probability") + plt.xlabel("Conformance") + plt.show()