From ce3f2964d68946f91e1866c9f81d6edf1314ea31 Mon Sep 17 00:00:00 2001 From: Kevin Maik Jablonka Date: Tue, 27 Sep 2022 13:20:31 +0200 Subject: [PATCH] feat: add causalimpact metrics --- paper/20220310_plot_causalimpact.ipynb | 345 +++++++++++++++++++------ 1 file changed, 263 insertions(+), 82 deletions(-) diff --git a/paper/20220310_plot_causalimpact.ipynb b/paper/20220310_plot_causalimpact.ipynb index c5b40ec..8ec3914 100644 --- a/paper/20220310_plot_causalimpact.ipynb +++ b/paper/20220310_plot_causalimpact.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 30, "metadata": {}, "outputs": [], "source": [ @@ -12,6 +12,10 @@ "from aeml.models.gbdt.plot import make_forecast_plot\n", "from aeml.utils.io import dump_pickle, read_pickle\n", "\n", + "from darts.metrics import mae, mape, ope\n", + "\n", + "from scipy.constants import golden\n", + "\n", "TARGETS_clean = ['2-Amino-2-methylpropanol C4H11NO', 'Piperazine C4H10N2']\n", "\n", "colors = ['#e41a1c', '#377eb8', '#4daf4a', '#984ea3', '#ff7f00', '#ffff33', '#a65628', '#f781bf', '#999999']\n", @@ -34,75 +38,51 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/kevinmaikjablonka/miniconda3/envs/aeml/lib/python3.8/site-packages/darts/timeseries.py:39: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n", + " VALID_INDEX_TYPES = (pd.DatetimeIndex, pd.RangeIndex, pd.Int64Index)\n", + "/Users/kevinmaikjablonka/miniconda3/envs/aeml/lib/python3.8/site-packages/darts/timeseries.py:512: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n", + " times: Union[pd.DatetimeIndex, pd.Int64Index],\n", + "/Users/kevinmaikjablonka/miniconda3/envs/aeml/lib/python3.8/site-packages/darts/timeseries.py:738: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n", + " def time_index(self) -> Union[pd.DatetimeIndex, pd.Int64Index]:\n", + "/Users/kevinmaikjablonka/miniconda3/envs/aeml/lib/python3.8/site-packages/darts/timeseries.py:2947: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n", + " pd.Int64Index,\n" + ] + } + ], "source": [ - "# result_1_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-200842-causalimpact_1_0')\n", - "# result_1_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-202007-causalimpact_1_1')\n", - "\n", - "# result_2_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-202512-causalimpact_2_0')\n", - "# result_2_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-204246-causalimpact_2_1')\n", - "\n", - "# result_3_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-204448-causalimpact_3_0')\n", - "# result_3_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-204910-causalimpact_3_1')\n", - "\n", - "# result_4_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-205014-causalimpact_4_0')\n", - "# result_4_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-212054-causalimpact_4_1')\n", - "\n", - "# result_5_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-213821-causalimpact_5_0')\n", - "# # result_5_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-215031-causalimpact_5_1')\n", - "\n", - "# result_6_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-220119-causalimpact_6_0')\n", - "# result_6_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-221523-causalimpact_6_1')\n", - "\n", - "\n", "# using the half during length as output sequence length \n", - "result_0_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220315-232215-causalimpact_0_0')\n", - "result_0_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220315-232013-causalimpact_0_1')\n", - "\n", - "result_1_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-222048-causalimpact_1_0')\n", - "result_1_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-222743-causalimpact_1_1')\n", - "\n", - "result_2_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-223044-causalimpact_2_0')\n", - "result_2_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-224338-causalimpact_2_1')\n", - "\n", - "result_3_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-224455-causalimpact_3_0')\n", - "result_3_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-224749-causalimpact_3_1')\n", - "\n", - "result_4_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-224834-causalimpact_4_0')\n", - "result_4_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-231030-causalimpact_4_1')\n", + "result_0_0 = read_pickle('results/20220315-232215-causalimpact_0_0')\n", + "result_0_1 = read_pickle('results/20220315-232013-causalimpact_0_1')\n", "\n", - "result_5_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-232205-causalimpact_5_0')\n", - "result_5_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-232935-causalimpact_5_1')\n", + "result_1_0 = read_pickle('results/20220313-222048-causalimpact_1_0')\n", + "result_1_1 = read_pickle('results/20220313-222743-causalimpact_1_1')\n", "\n", - "result_6_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-233648-causalimpact_6_0')\n", - "result_6_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220313-234657-causalimpact_6_1')\n", + "result_2_0 = read_pickle('results/20220313-223044-causalimpact_2_0')\n", + "result_2_1 = read_pickle('results/20220313-224338-causalimpact_2_1')\n", "\n", + "result_3_0 = read_pickle('results/20220313-224455-causalimpact_3_0')\n", + "result_3_1 = read_pickle('results/20220313-224749-causalimpact_3_1')\n", "\n", - "# using a third of the sequence length \n", - "# result_1_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220314-082226-causalimpact_1_0')\n", - "# result_1_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220314-082938-causalimpact_1_1')\n", + "result_4_0 = read_pickle('results/20220313-224834-causalimpact_4_0')\n", + "result_4_1 = read_pickle('results/20220313-231030-causalimpact_4_1')\n", "\n", - "# result_2_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220314-083301-causalimpact_2_0')\n", - "# result_2_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220314-084555-causalimpact_2_1')\n", + "result_5_0 = read_pickle('results/20220313-232205-causalimpact_5_0')\n", + "result_5_1 = read_pickle('results/20220313-232935-causalimpact_5_1')\n", "\n", - "# result_3_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220314-084717-causalimpact_3_0')\n", - "# result_3_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220314-085027-causalimpact_3_1')\n", - "\n", - "# result_4_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220314-085107-causalimpact_4_0')\n", - "# result_4_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220314-091146-causalimpact_4_1')\n", - "\n", - "# result_5_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220314-092433-causalimpact_5_0')\n", - "# result_5_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220314-093230-causalimpact_5_1')\n", - "\n", - "# result_6_0 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220314-093932-causalimpact_6_0')\n", - "# result_6_1 = read_pickle('/home/kjablonk/documents/aeml/scratch/20220314-094931-causalimpact_6_1')" + "result_6_0 = read_pickle('results/20220313-233648-causalimpact_6_0')\n", + "result_6_1 = read_pickle('results/20220313-234657-causalimpact_6_1')" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -116,36 +96,36 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 53, "metadata": {}, "outputs": [], "source": [ - "from scipy.constants import golden" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1.618033988749895" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "golden" + "def _get_metrics(results, case: int = 1): \n", + " mae_score = mae(results['before'][case], results['predictions'][0])\n", + " mape_score = mape(results['before'][case], results['predictions'][0])\n", + " try:\n", + " ope_score = ope(results['before'][case], results['predictions'][0])\n", + " except Exception:\n", + " ope_score = np.nan\n", + " \n", + " return {\n", + " 'mae': mae_score,\n", + " 'mape': mape_score,\n", + " 'ope': ope_score,\n", + " }\n", + "\n", + "def get_metrics(results_0, results_1): \n", + " metrics_0 = _get_metrics(results_0)\n", + " metrics_1 = _get_metrics(results_1)\n", + " return {\n", + " '0': metrics_0,\n", + " '1': metrics_1,\n", + " }" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 50, "metadata": {}, "outputs": [], "source": [ @@ -219,12 +199,34 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 47, "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/kevinmaikjablonka/miniconda3/envs/aeml/lib/python3.8/site-packages/darts/timeseries.py:3006: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n", + " elif isinstance(key, (pd.Int64Index, pd.RangeIndex)):\n", + "/Users/kevinmaikjablonka/miniconda3/envs/aeml/lib/python3.8/site-packages/darts/timeseries.py:3006: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n", + " elif isinstance(key, (pd.Int64Index, pd.RangeIndex)):\n", + "/Users/kevinmaikjablonka/miniconda3/envs/aeml/lib/python3.8/site-packages/darts/timeseries.py:3006: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n", + " elif isinstance(key, (pd.Int64Index, pd.RangeIndex)):\n", + "/Users/kevinmaikjablonka/miniconda3/envs/aeml/lib/python3.8/site-packages/darts/timeseries.py:3006: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n", + " elif isinstance(key, (pd.Int64Index, pd.RangeIndex)):\n", + "/Users/kevinmaikjablonka/miniconda3/envs/aeml/lib/python3.8/site-packages/darts/timeseries.py:3006: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n", + " elif isinstance(key, (pd.Int64Index, pd.RangeIndex)):\n", + "/Users/kevinmaikjablonka/miniconda3/envs/aeml/lib/python3.8/site-packages/darts/timeseries.py:3006: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n", + " elif isinstance(key, (pd.Int64Index, pd.RangeIndex)):\n", + "/Users/kevinmaikjablonka/miniconda3/envs/aeml/lib/python3.8/site-packages/darts/timeseries.py:3006: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n", + " elif isinstance(key, (pd.Int64Index, pd.RangeIndex)):\n", + "/Users/kevinmaikjablonka/miniconda3/envs/aeml/lib/python3.8/site-packages/darts/timeseries.py:3006: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n", + " elif isinstance(key, (pd.Int64Index, pd.RangeIndex)):\n" + ] + }, { "data": { - "image/png": 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", + "image/png": 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XLkWr7WAmceCFF17gwQcfZNKkSdx8883Y7fYeGGHP0Z+3aVTaJipKhKJSpxLWS7Ly/pZWrFGxaealWDwbU0uexAlESe5SHGo4KiIIAnI7m/D5fNx333289dZbXfIk7kjZuLU2m+3eTvc0wLnnnnv6egjtYu/evTzyyCO8/vrrzb4eCATYtWtXr7unJxTrnDlz2L59OxdddFGr5ycSRICiWN94440u9d+eFevbb7/dae/vSZMmUVBQQGlpKf/4xz+YP38+O3bswGxu6uxxMtKft2n6i2z2JeGISDgm4g/FyEk1dui9ieQPCSV56NAhJk+enHw9JkoINF2xCoLQptJcvuIOwl1ISRiKimgFAW8oSrkjQF66CZ1WaOABXZ+rrroKi8XC6tWr+eabbzj33HMpKiri7LPPZvr06e3ut/E2TWsbW3OsVuunVqv1b4mfjlzgQGfevHl9PYR2UVZWxueff96i4gwEAtjtdsrLy3t1XAnFOm/evHbtiXX3irWtKhrFxcWUlZUxf/78TveRmZnJ9OnT+fOf/8y0adP6xOT+baS/yCbQJUedzhKJKavVqCjj68SKVZQUc2sideCiRYs4cuRI8vWYJCEIQgNzrCjJGLSaNlesKy4/m3Ab5uIEoaiI0x9pcCwck9BqBBz+MN8cqePVTcV8caCaf351tMkzcP/+/ezcuZN///vfrFu3jqqqKp5++mm2bdvG4sWLu/SMaU2x3o0SZvN8vZ9upT+bm1577bW+HkK7CAQCOByOFtO8BQIBNBoNe/bs6XQfX331Fffe2zHjRkcUqyRJiKKITqcYWCZMmMCxY8cIh8OdHvOHH37Y6uvvvPMO3/nOdzplBm6Op556ir/+9a9diq3rzVzBJyPH6/zUedv+zLtbNpVKLd1v0bF7w3y0q2sp/DqKKMm8uqmYYDSGRgB3I8XU3jYkGQJxxRoIBBo4A8YkGY0gNEhpKEoyOo2GWBupDn/15D/avWI9Uu1l8+Ha5P9y3PNYq9EQjsoUVnk5Xudn7b4qSh0BQo2U+iOPPMLPfvYzjEYj+fn5vPLKK3z22We89NJLPPLIIyxfvrzT0QetOS/tRMklugI4L/5/t9KfE337fL6+HkK7CAQCAC3GfgYCAc4880w2bdrU6T4OHjzI+++/36H3JBTr6NGjCYfDDXKE1tXVNfhCJ7IuJbwXE+87fPhwp8fs9Xpbff2dd97hiiuu6HT7jRk5ciRLlizhT3/6U6fb6KhX8EDjSJWXSlfbD7ruls3tx+zsL+/2aEMCkRieQMcVW1eIihK+UBRfKEaaSc+RGuVexUSJ1zYXI8syv/nNb1qdtCYckUJRZbUbCoUaKFZRlBEEGnjmKqZg5e/WVq0er7fdK9Yadwh3INpoXKARZCKiiCsQQRAg3yKw6e1/cO45i7jjjjsIhUJ8+eWXbNy4kV/+8pfNtn3DDTcwdepU7rzzzk5tk7XmvPQ3wA48AQhWq7Vrm1oDjDvuuKNH2y+q8eHwdX5FliChoPbt29fs64FAgMsuu4z169d3ug+Hw0FBQUGHZncJxSoIQpNV6z333MPNN9+c/L++GThBVz2DV6xY0eJrBw8e5NChQ91e1/Ohhx7iueee6xNnsY5yMlqT/OFYu0yn3S2b7kC0W2SxMZGY1ClTbFcQ47l0PcEo6WY9JXV+IjEJpz/CsRofMVHm6aefbrXuccIRKRgRkSSJaDTaaMUqIQg0WbEmCLaiWP/5xK/bTHuYoMIVbFDJJhJT9nZlwOvx4qkspmTPBu6/7kKqS4/w01v/l6KiIr73ve/x85//nKeffhqLxdJs24IgsHLlSjZs2MAVV1zRZvWqjpSNy7bZbG/bbLZjNpvtSaB3Upn0E7788ssebX9vqYsyR6DL7QQCAVJSUlo09QYCARYuXEhxcTF1dXWd6sPhcCCKYocyIgWCIaKy8vVrrFjLy8t55ZVXkoqzOcXa1X3W7dtbjh575JFHuO222zCZTJ1uvzlGjhzJs88+y0UXXcSll17aYF/qZONktCaFY2K7PEa7Wzb94RieYLTtEztIVJQIhHu3xFlUlOKr1hharYAsy1Q4A1TGlVRElAiFQhw/frzFNpR6q0poS3PFNGKi4qgkN9hjVT43AQi1Utbtnr++3e4k+jXuEIHIiYlJOKYo9ENb13Hdd8/h9d//jDf/cj83/uZPLLvjceaeuYjXX3+dMWPGsGDBgjYtUhkZGWzbto2bbrqpzS2hjjgvCVar9Vyr1ZputVqvpJm0Z99m7rvvvi63EYlEeOedd5p9zROMYPd23UwUCAQ455xz+Prrr1t8PT09ndNPP73TDySn04ler2fXrl3tfk8kEsYRUASosWKtrq7mvPPOS+YE7gnFeueddzZ7/D//+Q+bN2/mlltu6XTbrXH11Vdz7NgxFi9ezPz589sVw6uiEI5KbTq/QPfIZn2CUbFHFGskJhGMxnpk/7YlYpKyYo2KElpBQBDgaLUXVyCKQachFI4iimKbilWrEQhFxaTJuP62TExSVo6NV6yykjei1RXrm397tIFibWyhSNyrYESZ7DRcsYoEPW7efuY3PPj0P/jdf9bx+BtfM2G6FUEAVyCCwWjiqaeeYuXKlW0mxih3BLAHRC6++OJWz2uO1vZYr0KJX30BGBP/XyVOfn5+l9s4fPgwP/rRj5CkpjM0f1ikztf1KinBYJB58+bhdrspLS1t9vWUlBTOPvtsvvjii0714XA4OOOMM1pdBdYnGhOJRaPU+BWhSCjWxH2orq7mF7/4BW+++abikNCCKbgrDldDhw5tcqyuro7bb7+dt956q82E+13BYrFwxx138POf/5zrr7++2c9fpSkRUWrX/lt3yGZ9ghERb6jjJltfKNrq/pxSiUVqt+mzO4jF408lWUajEbAY9ewucQGgEQS8AWU7py3FqtNoCMdEQqEQ2dnZVFdXJ7eCRAm0GqFBAomYJCOj3IvGTkT1Sc3MTWZnCkVF/r3xWAMFvXprCXZfmDpvGK1GIFyvkk04KrHh/ZeYcsZixk+ZgV6rQatVHB71Wg27jjt5f3vTZ2Bz1HpCrPziMOsP1bZ9cjM0UaxWq/XR+O/HgBzgGDAocbw7ORn3cdpLd6xogsEgPp+vWZNgIByjrptWrKmpqSxcuJB169Y1+3pCsa5du7ZTfTgcDi6++GK2bNnSrvNdviAarY7iOj+gPAiHDBmCzWZDkiRqa2u58MIL0Wg07Nixo0XFarfbW30AtEZzK9bHH3+c5cuXM2vWrE612VHuvfdePB5Pu/MKf5u8gkvq/E0ewEqYSNsr1u62NoQiIt5OrFg/2llBpavlyXEgIiLKtJk/tzuJiooil+Keu2aj9sQ+rwD+uLNjcXExQHL1KMtycvV4YsUqEQ6HsVgsjBkzJvkci4nNewUnCLSyr3zGd35EVJQptfvxh2NUuUJUu4O4AxFK7H6KanwEwjGKanwIgpI2MSoqbR8+epRtn67m7KUrkOMThwRGvZZSe4D95Z5mTdGeYBRXPQ/pGk+ISEzCH+ncHnhzK9Y347/faPTzZjPndomTcR+nvUyZMqXLbSQ8dnfubOhwLcsygUgMpz/c5cQNgUAAs9nMOeec06pinTp1Kn6/P1kCqSM4HA7OO+88CgoK8Pv9LZ6XqMl4sLQOnV5PqT2QdJe/9NJL+eijj3A4HKSlpWEwGLjqqqt48803GySHSKDVarnkkkv46KOP2jVGl8vFzTffnKyV2njFGo1G+de//sVtt93WkUvvEjqdjldeeYUHH3yQtWvXtlnHtTe9gnty0tuePbRtRfYmSeIjUbFdoRityWalK8jhKk/bg6xHMCoSiMRaDRNpti93sFWnp2BEjOfQ7cUVqyQTjUmIsqIcEwrQoNMgy+APKPf8+PHjyLLMq5uO4fRHqHAG+XhXBQ5fGFcggkYjEBMl/IEgRqORiRMnJs3BoiTFX29qChYEcLcwSZFlmceuO5eoKPHVwRqqXEHcwSjHavx8c7iON785jsMfJirK7Ct1kW7WK0kn4pOtPz72O85Y8kOy84ai7OaewGLUMSrXgizLyQl9fQoqPGw/diI7WrkjiFGvbfceeJvOS/XCauT4307gvPhvlTidXd3VJ2E6aaxYlZRgypfxYEXzM6zm2L59e5MYvoSpd9GiRU32UGVZTipejUbD7bff3u48q8eOHUs6LjidToYMGcL06dObNQdLkozTH2FvqYu9ZW62Ha5GqzMwKM3Imv1VhKJiUrFWVVUlK8kkFGs4HG6yYgVYsmQJb731VrvGu3HjRv7+979z7bXXEgwGmyiMjz/+mIkTJzJhwoR2tdddTJgwgeeee45f/vKXvPfee73ad2v01KTX4Qvz4c62k5F4Qw33z0AxBbdHKbcmm2X2AEU1LU/+GiPLMqF4mrz2yiEosusORCh3tqxcAxFlf7UtxXqs1teuveX2EBPleKUZicSCbnh2CgadBmSodfnQ6XQcP34cuy9CiT2Ayx/BG4pxrNbHxsJaCio8CChK0uEJJBVrwoFJlGS0gkC03hZHNO5YpBGEFlf/MVHmpidfQwDsvjD+sIggwO4SJ4ervbgDUTSCgDsQweGPYNJrEQCnP0LRseNs+HINp11yNRqBpNm5PnqtBr1Ww5FmJlauYIQaz4nP6bjdT5pJlwwpaouOOC/dFP+9CthJvOxUMw1mJkpRxctR1T9+1Gq1rrRarQMuz/DRo0e73EYgEMBkMjVQRqIk4w1GFXd1WabSFaTc2T7v4K+++ooHH3ywSR8pKSlMmTIFn8/XwHSaUFgJj7ef/vSnrFmzpk1vVUmSmD9/Ptdffz2yLONwOMjKymLRokV88sknDc6VZZk3thzn72sPs6GgFpNeg93jR6c3YNRrERCodoc488wzKSoqYvfu3UnFOmPGDAwGA5s3b25WsV522WXs3bu3XZVqtm/fzi233IIgCCxevLjJyvyll17i2muvbbOdnmD58uXs3r2b5cuX90n/vUkoKrXLrOoLxZo1BbfHK7g12XT4ww08SVvC6XQSDoeT6fu0gtCq001jQhGRqChzsMLNC18eocbT1BoRjIhJJdcamw/XYu+mcB/FO1dIphhsiExJtYusvKHY7XYOl9dR5w3jDkQIRUXsvjAFlR68oVi8co1AnduL0WhkwoQJSTmMSYoZVqy3Yo2KSjYmrUaR9+YscTFJwl6hPJ8CkRj+cAyLQYfdF8bpjzAiJwWLUYcnGEUQBMXzGPhsbyW/f/JpLvjOMlJSM+Ieyc1fv8Wko6i2aZyzJxBN3mNPMEqVK0iqSU8oKnZvHCvtr8e6Athhs9nWcEIZJzjfZrPdZLPZTv7AvQ7y+ONdL2MZDAY566yz2Lp1a9KB5XCVhw93KTP6YVnKTPLz9VvaTGgAJ+JJ6xflTihWQRBYtGhRA3Nw4rUEaWlp3HzzzTzxxBOt9vPNN9+Qnp7OoUOH+MMf/oAoiqSkpHD11Vfz+uuvN/giBiMiR6q8yJIySUgx6PAFgmj1CUUpU2YPoNfrOf/883nxxReTzieCIHDVVVfx73//u1nFajKZuOGGG/jrX//a7DhjsVgy/mz79u0sXLiQ//znP0ycOJHvf//7SY/G2tpavvzyS5YtW9bqdbdEX6Sl669ERaldii0YEfGFTihgSZKTjjdt0Zps2r3hdlVPueuuu3j++ecJx1d2MrRr3AkCkRh6raJEXP4Ia/edyHy2Zl+lspotLUGQxOQeoSTJbD5c12TP1eGLtDsEpS2iooxeKxBrxqwtAXaPH0FnZMTIUWy07cNs0FLjUZRrIuwoGIkho8Sy2l0+TCZTI1OwjEZQFGWCxApZr9VQ5w03Wws2Jsp8+cbfFOtAskCAYrKW4uXtZJS44vpTgrIaJ6tfe4VLll+HViOgayYncAKjToM7EFUq+0RFXtlwDEmS8QSjOP0RREnmk10V6DTKJKD+Hm5HaE2xrgSuou16rPMAR/zvzEavzalXWHlA8cEHH3S5jUAgwKhRo8jNzU2GjhTX+qlwBhHiXx2jTssfH76PlSubNRg0wOFwYLFYePfdd5PHgsFgMvF7433WxooV4NZbb2X16tUt5g5euXIll19+OVdddRWvv/46Dz30ENnZ2QiCwMyZM7FYLNx3333JiYInqJhvBqUbGZplRhAgGo6gjyvKFKOOwmrFNLN06VLWrl3L8OHDk/0tX76cb775pkXX+J/+9Ke88sor/PrXv24woQDl4Thr1iyKi4sTeyBoNBpeeOEFLrroIubMmUN5eTmvvvoqS5YsIT09vc173Bh3IMI7tvZ5GqokFGvrKz9ZPpHEIEEsnlUn0o5VY2uy6QpECbVDSTldbt76dINiBkbRrO0xBVe6guwrdRGMiOg0GnJSDYzKTaWo1oc/FCMUETlW68cTjPLSU/dRuHVNUmnuL3PxwY4yjtVbUcVEZYXfmYc7KMq6/rhjopJLt6XJoNcXAK2eoSPHcKiwkMwUA9WeIO5ANJnGMKGU9VoN1U5fA1OwLMuIktJHfWf3xIpVMQfDgXI3MVGiqOaEmTsmydzw8IuAMuZAOIYkCwxKM5KfoTzDtBoBVyBSz9Ar881nbzN51qmk5w5DpxHISNGTbm6+DrIgKE/WSlcQhz9CmcOPKxDBG4wSiSn3+nC1l+x4YQJBaD1TVEu0Vt3GbrPZfmq1Wkdbrdb/RTEJt5t4keXVAFardRWwpvE569evT2ahmTlzZpcKV9ens/kdO8IvfvELnnnmmS61Ybfb0Wg0zJ4zlw8/+ZTcwfloYwEm5WjRagRSTQKZRoGgu45XX32VG264odX2qqqquPzyy1m1ahU33aQYDzweD7FYDKfTyezZs3n00UeT+WorKysxGo04nc7kPdNqtVx99dXcf//9PPnkk036+Prrr1m2bBnXXXcdGRkZXHvttXz22WfJNl9//XW+973vMWrUKJYtW4bPG2baYD2pJmUOl2USmJmv4zOzkbGZArJsIBCOYbc7WLx4Mfv27SMnJyfZ3rBhwwDYsGFDs3l209PTOeOMM3j22WcpLi7m2WefTV7Ltm3bSE9P58ILLyQzM5P09PRkG3q9nosvvpjvf//71NTUNLgv7SUYDBIJRMjQRbuUA7gttm7dmpw0vPLKK4t6w4HJZrOxfft25s6d2637rDFRiUUVJZkqV4D/7qkE4PtnjcGkV7YkEg493mCswfskWW5XaMrtt9/Oyy+/3OS4LMu4AhEyaWr9aIzXF+DI0eMcq/EhQ7yWaNsP2ANlLup8EWaOzEJCJiPFEO9bCRUZPzgVhy9CKCoR9PupOV5AVJTYcqSO/+6pxKTXsr3YwcQhyiQvKkoEo2ITRbihoIbMFAPTRmS2Op6iWh8FFR4una3IUSQmYTZoydI3vQdajUAgFMJgMJAxeCQlxUXMmn8BtfG9x9w0I2LcciDLYNJrOebwYDQaGTJkCH6/nxq7U6kkIwgNVqxR8cSertmgo9Qe4NM9lWw+UscpQ9M5d2o+n+2p5L2/PsB3f/YA4ZiIL6SsWBMKOTFGTzCa3EOVYiJbP/4PN9zzBIFIDK1GaHB+c5gMWtYdrOH08YOweyPYfWG84Rh6nSa+7XbCo1hAaJe1wGaz8dOf/jQpm60p1puAm1EU6j0oK9gLmzlvG5CNkkDClThotVpXAG/GFezY5jpYsGABCxYsaHPQnSErq2cTRc2dO7fLfQiCQFZWFrHM0bz6wVrkSRclSy7JQH6mlrGZUFdbg6uuGrfbzejRo1tsz+/3c/311/OjH/2IQCDAsGHDiEQi5Ofnk5WVxWmnnUY0GqWyspIpU6ag1+tJTU1NXkfi9+9+9ztmzZrFVVddxQUXXNCgj8rKSq677rrkOB566CEWLlzYoI3nnnuOH/7wh/zoRz/CbhfZWxVhcKby0BybCcedYSSNgSKXIhzV7gjWyWaGZpmbvacvvPACr776aov3+4033sDlcjF16lSefPJJzGalncOHD7N27Vrmz5/PP//5T7Kzs5PvOeuss7juuuu49dZbkSSJJUuWoNG0ZsBpHl9Iy47yOs6bnYm2FRNUVzj11FO58EJF9G677bZ1PdJJIzpSNu5wlYcNBbVct3Bcm+cmkhNERYmdxU4qnMokqM4bZni2Yj2JxpWoMxDhXVsp37WOICpK6LSadj3kWgqXCkVFwtH2hewEgkGqS46w9aiSjUyjAV+wbVNwQaVXUVDhqGJbjSPLMkW1PrQagWAkpsSABgNUFxcQiYrsK3ORYdZjNmg5Wq2ElKQYdcq+cjNFxY/V+qh2h5g4JF1xPGqBWneIGu8Js2soqqyks5spFacVBALBIEaTCV3WEByH9mDQaXD6IwheSDPpEQTwhmIIApgNWqqdPkS0CILAhAkTOHioEEGwIAg0MDdH4yE4oCi2Gk8IdyDC4AwTRTU+0s12ypwBho2fCijvVWJUm45RlORkvdWjuzdjtqSROWoqgbDYLhlMN+upcAawFdmJSRKl9gCSJCOA4jEsN2yjPZ7oHXFeau8e6/NAwnFpZbyTpSjhOWPjf9/d5sj6Gd3h6JLwyB027SyO7tqEQSMlXeATX8JIOEw0HOLyK5exalXrRgOHw8HgwYO59NJLkxmd6puCBUHgnnvu4frrr0cUxaTHcGNycnJ49tlnueeee5ps3B87dqyBcs/KymLp0qUNzlmwYAGzZs3i2WefpdodQt9I8GORCNp64TOyDFWtJFf/yU9+0mryCovFwrBhw7jnnns499xzeemll3A6nfj9fqZMmUJRUVGT9GUrVqxAr9fzt7/9ja+//rpTShUU01gwEus2r83+SDgmUWL3Y29H5ZloTClXFo1J+CMiZoMy4arvORuJKSsipz/C0WovMVGKV0yJm4TbCHtpSTb98QdvexygAsEgsXCIfYcK8Yej6DSaFsNEEniDUWq9IVyBCJ5gDI32xAM6zaxX/AzcSupAfyhGJBykurgQbyhKtTuE2aBFo1FSAZbYFc9lpSC52GTftc4bwR2IUljZenGAEkcAf73kFpGY1GxdUlBWg8FgCKPRSHruCOoqjidNp4GwiE4rJBM/CIKARiNgEETqgkpt1gkTJnCo4FDSsSgWa7hiTawi9VoNoaiIKxjFGH82FFZ58YdjzLtgGVFRwqDVKKvcRmM90b/y/95173Du5dcgo5iIddq2FasgCKSZ9Byt8ZGdaqSwyosgKLGuR6q8DTyKZeR2FwWoT1t7rMtoY4/VZrO5bDbb8zabbU3cgQmbzbY6fnxH/O8mZuD+zsiRI7vcRjAYxGgyY0zPIW/oSCoKdpGbbiI3w0RehpKn1mmvIzUzhwsuu4I332w9lDjhnZsIU4Gm+6iJFdoHH3zQ7B5rgiVLliCKYoPkBbFYjPLyckaMGNHmtT322GM8/vjjHCurwqhvmGczFo2gr2eKMuq1DfaVOsvdd9/N448/zrPPPsv999/P5MmTk1aBxqSlpXW5PwCXP0JElNu1CuptWvLYj7+21Gq1dt0DD2ViVOcNc6S6bQe7YPRE7GYgHEOn0aDTaih3nJhYxUQlrjIqKvus4agUt+QoD/nmHG8C4ROpAVuSTX84ltxfbCsmNRAIkJqZg7PsCAatBp1WCRNpbJJVJgFKW7YiB1pBMR1WuYLotScerxajjqHZKYSjIpGYhN2nTJiDPjeHjpYoVVniSsSg07Cv1J1sX5RkQvUe7rF4hZpMi4HNR+yteq1WOIMN9rTDMZGWFnUajUAwFMZoNDF45DhqSpQapoJGIBR/34Gt64jVM+tqEZEELX9be5isIaMoLDwMMpj1WkrsgWQyiGhMSi4WQFFumrgCTjXpqHIFMeo0PHTNaWg1AmlmPZF4bdX6aDXK/dVpNbgdtRTs2sKp516GNj7pqn/PWyPNrCfNpCM3zRh3pBJIMykeyPX7lKFdE7Em97LxgXoZls5HWaXeFD+W3fjcbzMdSTjfEoFAAI1OKYdmXXQJmz9rmjfYXldDauYgps45nZKSEo4cOdKiY5HT6SQ7O5sLLriAffv2UV5e3kR5CoLAnXfeyZNPPonP52tRsWo0Gt58802efvpp3njjDY4ePUpZWRl5eXkYjU3NSI2ZPHky//M//8O/n300OSsFEEWRY4f2oKunWC1GHcdqfV1OhiEIApdffjkvvvgib7zxRquJAuqXqesKzkCEWHxVoew99V7e13bQose+zWZbTVNnw04Ri68g2pNPNxQVk7GbwYiygjQbtA1CyiKi8hD2h2JERMUkGGsUutGYz/dVcjwe+N+SbCrerIDQdrajYDDI8AnTCdQUMzzHgl6rwR2M8K8NxxpMolZvOc7Xh2pwByJsPFxDTppSsam4zo/F2HBCqdUoXq0yUO0OEQ0FGTbuFLbYtsePKmSkGCio9FBWWY0/HMOo1yb7DEXFeNYhRRFUuYLJ+x4Ixxp4UociIjs2fYHX50tOJMLRhgquwfgEgXAojN5gIDUzB41Wi6uumnSTnlBExOdy8Oyvb6Ku/HjSmTAaCZNiNlHlCpI7bDSHCwuRAb1OQ0SU2FvqAk4k5k8gy3JSVixGHfmZZrQagV++sIb8TDPpZn2Dfdn69zAcFdFpBDb9923mnH0RppRUBqWbyEs3tZn/tz7ZqUZ0Wg1pJh06jYBOqyTJsBjr7ZDK7TMFN6a5Pdb6mZdUWmDjxo1dXrUGg0E0eiMCcOZFV3LfDxdTV1nKoCEnVoROex1pWYPYX+7FevYFXHLJJZSUlPDvf/+bS7/zXQoqPMwanY0oing8HjIyMtBqtUknpubMvVdeeSXPPPMMDz74YKsJESZNmsSLL77I4sWL0Wq1jB07ttU93sbc98DvOHPhYv7zx1/zg1/+Dq1Wxzdff8H7L/2ZeedcmjzPoNPg8Im4A8osPEEkJhGJiaSamvfwa46YKDF12jT2799PLNbynti6detYsmRJu9ttCbdfyUITikp8eaAaQYDF04Z0ud1uYh7KVg10UIl2xLFQJwY5a7QFixBu1YkrGAySpo0yd5iRkN/L6AzlYaYRBAIRxYFNoxEIByJMH6xHkpXHk8/rRhRlpg/WIwMet4tIIyuIRYjg87pw6qN88cUXXH755U36l8IBpg9Wvksul7OJJSWBKxAhEgpy9txZFB8+yNhMAVHSxc39MiUVNRTX+UmV/bz7j+f53o2/YF8swPTBBlJNWnwWpY9U04nHqyiKaLVaBhn1xHJ0pJokouEg86xWpJrDzBm6GKM+oRQE8oxaJo4bw1uffMGCMVlYNCE27ismxaCl3BlkxmA9FpOGwWYDTqcTKWygqEaxGIzNU6wx/lCML/71JD+46Q7s9nHodRryTCLmPH29vhSyTAKn5Oo4kCohpxo5Y1QKEydOQqwpZMqEIZySm0HZcaWUXNW2D7jk9F9hNgjs1kXJSzdx1hgLXvN4Xl35R34yWE+qSWBoihEx5MPp1DI8TWawWUuWSWBsJoxMUyIElNWhABiQJD2bvtrE2KmLiaTqCEcF9DoNpnpjlSQtg80GLCYdf/n8Le5+6EnGZjZVpol+2kXmiWfO2MzUBi/lmgwIUT/Nfa2DwSC7d+9OxsTXdyxsolgTmZcSv61Wa8djENpJT3ke9gYvv/wy11xzTZfaCAQCCDoDEjKpGVlc+sOf8/BPr+D2J15k9KTpADjstaRn51LqCDBk5jl89u7r/Pvf/+ZnP/sZ702ey+aSEDNGZuF2uzFbUvGGRDItWq666ioeeOCBZN3T+uh0Ot5++21uuukmJk+e3OoYzz77bD755BNOP/10Hn744SapBVtDMKZy3YP/4K0/3snf77+F85ddz64vPuWqn/0fC5c0vXfVnlADxXqk2suBMhdLTxtFlSvIoDRlhtkaXx+qwSAFOXPq6Bb3kgCef/75blGsnmAUQ3zPqKDSQ60nzNThmeRnmAhFRcyG1vwDO0Zjz8OepCOOhXuqIuyujBCUjZw5rXWHvtKyGFtKg8ybnMKOimpy001oBKh2RzljSgo56SYcES97qmsYnGGmxh1i9kQLokZiT1UNgkZg/rQ0stIafqf3flOFI6Jj+rgsXn/9da699lpK7X5Mei256cq2yq6KCPtqoiDTbBsJVu08jD8YwjJiGoUfvkeRS8lWVOOO4A1FiWnN7Drux+I8xOqX/8bMi75PgBSGZqdgCMlUuaIIyEmHPYAHf/IdbvrtX9BlDkUGNLKSrjRrzDR2bljDfH/CZVGh1u4nGAzy6dqvGHbqEtwxieI6H3qthkBYxKTXMDhTS5UrwrgRRkZkZPDFxkpy003MnaR8Bu5aH26Xh683fsPdt95EVqqRor1OHP5Yk8nq2Ew47pFxBWMEZcWxMHvERLbvLWDQ1LMBOFbpwWxJ44vPPub05beTlaqhyh0mIBkorBPJzx5HVVU1W47aGTMsj0BYIiUQ5bQpmdjKKkg369Hr5KTTokJDC8/bq95g6OzzCEUlqt1hsi0G0swnZF6WZQ5WBLBEavH5AhiGz2jU3onrae54RwlGZI44PNy8OL/hSjbOokWLWLRoEdDQsbC1QudvWq3WT1Gq2/wj/rtb6c+5ghunDuwMwWAQSaNPeridv+x6rlxxF6v++nsllVrQz96dNrIG5eHyRxg5xcrf3/qCcy6+nKuvvprfPXg/dV4lK8nBY+XozGkcjc9aFy9ezIEDB5Q9kkYmmJgokZeXxzvvvNMkU1NznHfeeVgsFh599FEeeuihdl+fOxBBbzJzyyMrGTRkBP9++jes+ehdZs+/oIEpGECn1XCowt3k/QcrPISiIm9vK0malVoiHBXZetROjSdMYRv5YLsjDlmWZbzhGDqtgD3+OZgNWr48UMWrm4p58auibjUNdyJXcMJjH3qw7GM4KmHQadpVtDsUEdEKGgKRWDIsA5R7WecNK7GEoRhy3DNTRo4XpAgrQYVyw8QDifcGwmLSnJyQzd3HnRTVnNi7dwUjyh6cQIthO7IsU+sNEwmHGDV+Co7aSsKhYDJ8JBRV+jEZdESDXmRZpnD7V4zOS01655r1GoyGhqvh2ooSDu3czKB0E+lmPV6/H73JzIjxUyg7erDJOHSS4sm7c8sGNPEQE1FSTKojclIYFJ8sCIJAnTdMYTwjUrU7mPzOBcIxgn4Px/Zto8YTTnojt2QKFgQBpBh6gzLhGDZuEmVF9ZLN+DyMmjQdWRLx1Sqx27GoEpOu0woEYjITJk+lski5HoNOg8sfpcYTIirKbU6KAW75vWJg0QoC0Wb2WAVByeh0yPY1005b2CHTb2cwG3QEIiIlzeQXbo3WrtRhs9kutNlsy20221U2m23g51vrADfeeGOX2wgEAkRkfQOv2bMuupJwKMjmz97hg5eeoez4MWafsYhxg9Mw6rUU+lMprPTwwAMPsH7Nx+z58h02btvBkgvPw2RJp7BSUSh6vZ6rf3Btkz73lbp49P39bCio6fL426LOG0YQBHR6A8t//mt++48P+cPKV8jOa2oqzUzRs7/c3SCcwuGL4ApEKKz0UOMJ89WhmgYVKA6Wu5UHLooJ+JPdFURFCaNOw87jrceVfu973+vy9fniDjM6rYaj8X2vrFQDhyo8ipesL4w70P11PDtASx77id9juyPdaCQmtluxKl6pyr2r/1DUagRKHQF2HXfGCzMoykGWoaDSw9p9VUTj4ReJHMKJ5AmJMmjeUAx3IJKUzRpvmNp6qQQ9gajiNSo3LQQQjioVbMJxZ6FoJExqWirDxkzkeMFeAIIRicwUQ3IC5XW7MJpS2L2xYW7iDIuBzJQTE8dwKEgkFOTwnm3Ja/V4/BhNZgaPGIPbUYff23BSGfR7SUlNZ9eWjchiLHmPh2SZ0cSzAgGY9BoOV3l5a1spg9IMREWZohof728vo7zGGd8nreK9jQfYX+YmEpNbteREI+HkpHfM5JkcO3gi9acypjSmzZvP4V2bT5xvMKDTavCFYow7ZQZVRQeS1xmKihRVe9s9wfzHw3ck3xsRmypWgIlD0jiw9Wumn7awXW12lc5E0bWmWLdbrdb/tVqt/5P46fTIuhF3PLatMYFwjK8PVvfaOBJxhV0hGAwSkjQNnHs0Wi0/vPMR3nr+CbZ98SG/euBxxk6ZhVYjkJ1qZHCGiaPVPnySkWvu+TM7P1/Fj5YuYfgpczhj8RKO1fqTnouLlq3gmhW3J9sOR0U+21uJxaTjywPV1MTTioWiYoMHUHdR5Q5h0p+4Np1Oz6x5ZzR7rk6rQRJlVq49jNMfaZBo+5sjdeg0ShL0l9YXJR0xNh2uS4bpHKv1seu4k7wME0a9EgsYbCUF3WWXXdbl67N7w2gEJYVaqd2PSafsF47IsTAoTVlR7C1zUe7o2Gy3u2jJYz/x22aznd8d6UZDMQm9VkM0pnjvxkSJz/ZUNniY1nnDShagqIhGozgm1V9spBh1FNf6KHUoWYkSb014HIejomLSFeSkB/GxWh+f7a1MJsnXCrChoDYpm3ZvmJp6IUDeUAy9VoNM0/y86wtq+HRPhaK0ZRkpFsVgNDFxxjwK92wFYNSgFHJSjbgCEcx6LR63i1nzz6dg1zeEQy2Hi/lcDnR6A4V7tiHHq8p4vT4MJjNarY6xU2ZxeE/DohChgI+84aMZOmIkR/dsQZLjN6MRRp2WckcAnUaIbzvIvP7NcbYds3PgWAUpaRmMnDyb3bbNHK324Q5GMLSycoxFI0nFOmTkODwuO16XUvUl4POQkprO1HkLOLBtfYPzdVoBfzjGyInTqDiqKNZE2M2u485mzajNMf2Mc+LvBVFs3tFKjoUoOrCLU+ae2a42+4K2kvAPAsbV++lz7L4IR+KxbfWp9oTYUexoM8atu2gcu9kZAoEAQUmHUd/wYxg1cSpnXHAF5tRURo9r6FxkMeoocwZYd6iacVNmcduTLzJm1ll85+YHufjqnyBKMsfr/EqJtqCOC7//i+R7K1xBAhFJCfQGjsbDIw6UuzlS3XWv3MY4fJFWg9cbk5dhwhWI8N89Fbz0dRFOf4TcdBPV7hASkJNmxBuKUucNEYqKlNj9yYTu+8vcmAzauAs/IEN5PPlA4/R40D0r1mpPWHHbN+sx6rVkWJqatz/fW8Wne6uafX97wj76A5G4shQEgWBExBOMsr/c1aA6zWd7KpTQmZiIVhAaKE9Qkg3UuEOU1gWUNJjxZYJWozywzUYdRr2WFKOOgriZv8wepNQRSMYZDkozsf2YgwsvvZxwVMQfiWH3KonjQ/Hcw3qtUsWlvmdxKCpiK3JwpNqHNxRFjCqrNkEQmDjzVAp3KytNg06LyaAlL92ERiPg9bjJGzaKUROnc3D7phbvj9ftYMio8RiMJsqOHkQQBAxCFKNJiS+fOPNUDseVd4Kg34fZksY5F17Gzq8+VpIiNNO2Qa9BECArVfnumfVazAYtRq2Gipo6UlIzGD3NyuE9Wymq9Snm9zZWrAlTsEarZczkGclVa9DnxWxJ55Q5Z1K4ZyuxaCQZOqeJ5/HNGzOFssP7GrTp8EewmNqnWE877zuAopTzM83NxqUe2rGZMafMxJSS2uS1k4XWnnprbDbbPTab7cnET6+NqhUcvnDcRNjwQVnrCWP3Kc4FvUH9LD5tEYzEGgRpJ48Hg0RkbbOxV1f85E6W3vt3Vm2vbhAaIAgQiEQprvGTZTGQlZXD9+98lMwMxRPQoNNgO2anoNLDoUpPg6oYJXV+BEERT7NRqfIgSTKbCmsJRcV21x6saEe1nUT6OIOuec9LAF8oSqSeK7sgCGSnGth13EmNV8nMYtZrG7rAy7C7xMXWI3X4QzHsfmXv6FCFh4z6+UEFkvsia/ZV8tmehuE1Xd2bicaU1HwmvVKKKsvSNEVctsXAoDQD5Y4A7kDTovUbC2vZW3pyVmPsSD3WSDxGUUBRUr5QDHcgqnjXxu9TmSOAPxIjHJPQ6zRKhZJ6bSRWJp648tPHH6harUAgHEtOPi0GnRKbGY5xrM4XL2mmtKWJh+6MGjYYTzCKXqM4lb2x+Tjv7yg7Eb4hQK0nxK7jTiqcASqdQWKSTEySKK71Ew2H0BsVi8P46VaKD+0mHAwkx5nIWuR1u7CkZzLrrPPYteGzFu+P1+UgLTOb2fPPZ+eGzwHIMoHRpHjrT5x5KgW7tjR4Tyjgw2xJZeH5F7P3my8IBIPNmkU1gsDQrJTk/UtPMcQzJAm4XE5SUtOZMONUSvbb4rLW+kQuFok08H8YN3UOR/Yq1bcCcVNwakYW+SPGcXT/TqLRCLq4IhYQMGQNJeB14XMr3+vE5Kmlfd3GrDj3xEIit4Xwmb1b1jH9tEXtaq+3aLMeaz3mWK3WT61W698SPz0xmI4WU65yBQlFRZz+hlleSh1+glGRGk+IGneo1QLD3YHDodQdKCgoYOnSpVxxxRV88803zZ77zRE7f/zkYDKbCijepB6vH4PR3OTLEwjHEGWBqrCRUkeI7cWO5GsFlV72l3oYknXifRkpBjJSDFS6gnhDMQoqvby6sZi9pS5qPCEOVbjxh2MUVnlJNekJR0XMeg1HqryUOwM4/RG0GgFnMw//BCV1fmo8obgjUWky8LslghExmfC7PuGYxIFyN1FRYn1BLZsK6xq8btBpGZmTgimukDUagSFZ5mRSbYtRx1cHq/niYDWGeKWKj3ZVIEoNnSNSTToOV3kpdwTYfKSOSldDU3fj1XlHLB2iJCez8LSmoDVx85xGEPhkd0UT82OVK8SxWj/+UIxXNxW3ma6vsfD2JB1xLAyLEspCUMmn64tXQXH4I7y3vYwvD1YrxwJRonGzsTd0It9rEkH5XIZlpySVl04j4I+IGOt9HwTg/R3lVDqDaDQCNZ5Qsq2MFD3vbDyErciePCaj7NMmMgZZjDoKKj18uLOcf60/RoUzkPw+HK7yEo2EMRgUxZqSms7YKbPZu2Vdk+v2uF1Y0jOYveBCdm/+glis+Um9z60o1lnzz2fXBiVXTjgYwBjPiDZm8gxqK0rwOE8U2g76fUp8Zl4+w8ZMZNPXX7RZOm7/tvVI8WpOJr0Wu8OJJS2DGTNnE/Q5cVSVtRm6Fo2GkwUyAE6ZcyYHtm9UxuRTvIIBpp66gL3ffEmNw0tEOiF3/ojIyAlTOV6orFpTTboWE+I3x/NfHG71dVmW2bflq17bX21tO6k+HUlpeDdKjuDn4z9tl1fpIJ3xCq50hzDqtdTGvdze/OY4Fc4AFQ4lc8eXB6rZXeLkmyMnHtiRmNRqurWYKLX4YJUkmXe2lTZZcaxevZr9+/ezcOFCTj/9dC655BK++93vJj0SJUlO5kEtqfMTE2XW7qviXVspW4/U8dznhbi9vqTZJcGeEidvbS1l1ZYSKl0hls/L50iVl6PVXj7dU8nOYoeyX9VIMdR6Qny2p5K9JS6GZJpJLAc8wSjv2Mp4c3MxR6q9RGMir24qZuPhOr46VMP6QzVo48qhvmNQY7Yfs3Ow3I3Lr+x9Olo5t7DSw+bDtc0qnYIqP7YiO5/sqqDWE6LCGWTXcWeD+2/QaTHqtU0KXYOSMWVkjoWhmWaMOg213jAHy92UOwM4fMp9cQdjpBi0VLiCvG0rJc2kxxVP5ACKcK7858sNlOsHO8updAUJRUS2H7Mnz2uO97eXsrEF56+oKDWxTuSmGzlU4Uk6liWo9YYorfPz9aEadpc427QEdMIruFdIZtWRldR3bn+EmCSzs9jBjmIHhZUeZFmpLCPJSukulz/aZMswM8XQJDwpkRBAX88kmJtu5Gi1knpOA9R4wsm2Kl1B1nzyHrZjDjzBKGWOAFkWPfmZZkbkWABIMegUZSzLxESZAxVuDDoNqSY9dd4QsajikJPAes4lrP/ojeSqNYHH7SI1PYvsvCEMHj6arWs/4OCOTUnllsDrtJOakc3YU2bhcdZRW1FCJBTEEF+x6vQGJs8+nf3xfUuIm4Ljps555y1h+39fZ8cxB8fr/BTXKt+ZSEzicJWXMnuAWDTCn+++nv++/jw+txOTQYPb6cSSnoFGq2XWmYup2Lu+zb3OWCTS4NrHTJmVVPpBvxdzqhJ9Of3MC9i27mPsbj/FDuXZqtMIZJgNjJ82h8Ldimk71aQjpZ37q5GYxJ/+/s8Wk3eIkszRggNodXoGjxjTrjY7S2U88cYbm0saeJa3l9YU61yUfdar4jGt93ZyjN2GJMnUesIMSjPy1cFq/rrmMDuKnXy+txKHP4zFqKPcGSQjxcCeEhcvfnUUhy/MjmN2Vm8tYevROg5XeajzhpNhJwBfHqhmY2Ftk/68wSjbix18c7SOUkdDofroo49YunQpjz76KD+68RZGnHYpa9eu5fbbb2fjxo3sLHbwwpeHKanzU+EKkp+pJJveddzJx7srSDXqiIRD6OImp8T17Tru5Ip5IzhlaAaZKXqGZ5kYm5dKQaWHETkpTBqajsmgZfdxV4MHcWGVl6nDM7D7wsREiTpvOLmXZfeFeHH9MWxFDjYdrmNQmuIAJUoy6wtqMRm1CIKy6q//pZZlOTmhqHKHKLErJZacvgh13hAHy9181chhzO4Ls2prCbZjjgbH67zKuIrqgswenU1UlMhNN3HRzCEcr/PzzZE63ttexsbCWkRJJiNFT36miebQaAQqnEE+31eFOxBBkmBvqYs9pS7e3lrKn9YcV1Y0riC+UIzMFCV5eFGNL76f7OW5F9/gb2sO8//WHaXaHeRYjZcqV1B5MO+rJhiJ8dneKg6Vn/DWDEZibCqsxXbMwdEWhO1AmZuvDzVUuolV0t5SF5sKaym1+5EkGVcgiisQxXbMjsWg41hN3zg5dRZfKJos8ZbYY3P5w9R6w6Sb9Rws95CbZsQTjGLUaZW9Ur0muS+dWJXWecO4AhGMem0DRz5QJll6rabBJE0QBPIyTAzOMCur0Qo3GwtrsXvDbDlq54u1azEbtGw5YudguaLU60+SNPG0eEomJBmnP4pJryXFoFX2fmMRDPXk0rroEkxmC8/8340N2vG6XVjSMgC44sb/5YOXn+Hv99/Cpk/fTp4TDIXZUXAcPylotFomWBfy3rvvUud0YzSZk8+gaacuZO83XybfFwr4EAxmPtxTS8qkc4n5nYgl2zhQ5mbXcQehqKhM0o/WsaGwlrrqSkyWNNZ+/B73/fgiNm7diUEKkpqeCcCcsy9ky5r32/SjqL/HCorD4cRZp7F/29dx5yVlxVqjySUqGPCU7CMoanD4wuSkGbGYdEw/bVGzK/y2qPGEqD6wmfK4BcEfihEIx9hX6uLrgzV8tLOcVatWM+OMc3s8zGbrETsbCmpINetwBaId9oVobSpxvs1mW14vxWGfbwbVekOIkkS62UhEr0WWZcbkWjhU6SUnVZnt+kKKS31Mkiis9LD1qJ19ZS58oRiuAxGGZaXgCkS4YPoQPtpVzoUzhnKg3E04JnH6+EHJ0BdRUrzryh0BjDoNB8vdCChm1yPVXrIGD2eiRsf3f/hj1uyrZFNhLXdccgovvvgiy5ZdxY8e+TeZOXm8ta2EmKTkthyRk5L8QsRiUaKRMOlpyiw6FBVx+SNYjDpSTTpmj85KloQ6c2Jug/vg8EXYUexgeHYKQ7NSkCSZ4lofS+YMp9IVpModosoVYnSuhXJHkJK6AEOzzJgMyoNr1qgsHL4IpY4AO487qfOFmXrmELYUOSipC7B4Wj7Ds1Oo8YR4x1bGjeeMw+5Tkn6PzAmBAOWOIKV2P5WuIGaDltmjstl6tE6p7hHPl5qQYUmS+XRPBdNHZHK0NsjCU9LJzzAhyTLZqUbOGD+ID3aWs2BSLsfr/Gw9WscZE3IbrF6q3UGq3SHGDU6LT6ACxOKFocPx3KFHq32MH5zK8rnD2VQcYFNhLbNHZSXv+bvby/CHYwjAD+7+A1FRydn6zZE6nIEox+v8RLMkqlwBCiq9bD1ah8OfxqSh6dR5wxTV+PhwZzm56SbsvjATshVTnizLHCz3MGloOmWOQDxuTwkFSaRM0whQWOnmXxuOMSjVyE/OGQcoiQdMOsXhpLDKwzlTB/eM8PQAz39xhOHZKUREiRSjDoNOQ7VHiefNSVVCMEx6Lf5ITEmGYDHgisX3+OvFeW4qrCXdrGd0bipr91cxb2w2M0ZmEYqKOHxhRuQ0TbtZUOkh1aiYGfeUKI+mtfur8IViTLzyHgoqPUwckk44KvKOrZTcdBPnThmc3C4YnGFSCigEorgDEcYNTkMQBDJSDDhCISKyjhp3iLwMEyazhRX3/4X7r7uYgl1bmDz7dAA8HjeWuOKaNPM0Hn31S2zbtvCv39+OY9AcgqKO/W89Sc2eLzEu+TmvbDhGdMhcSjf8B2fkPIwxLa9tPs7sUVnMOftC3nr+CVz2WtKzB+H1eigLGsnzRqj2RLni5l/z0V/v58ErlmA0mZPxtikGHduP2VmzdQfm3JGc+bNnOfzNx7z3p1+RNfE0huYNUiYuaRPxBoLs2fIVU+edTTAikmrSNVFQsWgEUW6oFqafeSFf//ddpEgQvSmVMkcAuy9C5ilnU7buFfKz0ihzBJITpTGnzMRZW4WztpKs3PZnIatyBZlx9a+xFTnYUKBYvERJYlhWCsOzU8i1CHy+7SMW/vYFKuO5mLMtBsWRLBjlSLWXETkWclINlDrDyBiaVcCxuLexJDeNrQ1GYniDMey+MDIwfUQGowZZOly5qjXFKsRDbDJPllCb4toTM/r63qZjci3JG5j4cAdnmIlYJL4uqCHNpI+XchIprvMnEw84/UrojijLCLLAP9Yd4QdnjSESk1i9rYQKR4Bh2SlERZl9pS72lroYnp3C/sJjvPLPlfzt7Q385dNDeEMxdDoNH+0sZ9a0Mzjj0qt54f9+zA/veJCs8XOTRcuTSjUa4XcrvsOUuWeRlZZCVJT4cGc5wYjImFxL8lxJkhqYy2RZWbEbdMrDutodxFZkRyMIZFmMmPVaRuZYWH+oBkmWOS1/EOXOAOdMGYzFpMMTVJyJnP4IGSl6TIY0RuWksGZ/Ff/dX8e4IVnU+UK8tqkYs0HH6FwLx2t97DjmABSzWWGll2yLgZ3HHcREGXcgyl2v7eTaBWM5WusjRa8lJ82IOxBJVowpdwbQCAI7ip0MsujJTNETjEq4AxH8oRgGnYbFU/OxGJU6tBsLazFoNeRnKquSwiovO4udZFsMHK3xcc4pgzleF2BkTgrljiAWk44R2Sl4glFGDUpBA8oqv8LDO7YyzpgwCINWQzgqMjw7hVBU5IX7b+YX8WD0I/HVe4ndjyjJWEx6PthRhigpMYEFlR7e2lqKxaQjL8OExagjEI4lv4PHav1sPlKHhIzdFyY71cj72xVnmZgok5tuoiYezqTTCBTX+fjzpwXMGJEZL/4uEAzHTqpE/u3JihaTZA6Uu+MVmZRiCjWeEJ5AFJNBm7w/sZiMUa9hb7mXuqDA6FwL4ajIN0fq8IZieENR3MEo5U5lUrexsBajTsvO4050GmV1On9SLmX2ADqt4nm89agdjaBMdEVJZu6YbHYUOxmek8KXf/0VU77/Oy6fMxxBgPxMM+XOAK9vPs7Zk/MYnp2COxBlY2EtwYhIOCZR6w0zLCuFYdkp7C2uQdAZ+GxvJTIwNNOMNxRl2oU/5sN/PUM0ZzIyMg6HE605jZgoUVjlJRKTKIjkMXLSLIo/+gtT5pyB5/A3GAx6Fs2ewORTR6A/fTj3fPBHRkeqqIppmD88g53HnYyZN4KJp53Ps8/9lRGLfsjR41VMmjab688axhGHhEYzisINVt5+/kmuufW3yqo9niRiwaQ8Vu12kZ07hMvmDCM28wZedOxnz6YPSb3wRr7YX8WE/HROueDHvPK3PzI9MhKtRmDkIAvz45P2rw+7cIWgxuVjc5ELdzwmfMLgNMoskyk5tBtZECiwx/D4qhAEGHvqBZSte4XB2WmU2ANMG55Jid1PVJSZdub5fPneq1xxwy+VajU6LZ+8+RKnjBnC6HkX4ve6MaakUeEMsr/MjcOvmPPL3vkd1ut+z7yx2WSkGBokuPnsjX8w5pQZFIXSKd5fjVarhG1lWgwYdBrMBi0Hyt2YDTqCkRi56SZmjsyM16BVJrfljiDbix2kGnVotQJnTcjly7jV7dRxOVQ6gxRWeslJNeIORhgcL7DeHnlpVz1Wm812ldVq/RXKbl22zWb7abt66CHWHahie3Hz8VAtmQUMOg2jBylKNxHaUOdVqheU2v0YdYrHaTgicqDcoxQXN+o5UO7my4PVnDMlL1mJI9WsJxqVOFLl5cjG95ky5ww2lEsMz4qQYdEjSorjw4FyN/OWXE/u8DGsXvk4sUiEjEGDyR8+GutFVzNi7ES2fPw62XlDueJXfwaUGbtZryUUEZPC4gpECEVEPEGZMkckGaQ8PDuFy+cO46NdFewodlDhDFLrDXPhjCFUe0IMSjMyMT+da84cxebDdVx56kjc/iizRmZxqMLNGRMG4QxE2RV/aIHArJFZVDh9HHNUUe0OMXtUFrlpJmxFdvIyTGyIm8llAQ5WuBmfn0Y0JmHUa9lb6iIcldhd4mTs4LRksepMizLBkWWZvaUuRuakkGrSc8aoFArsIVJNOi6ZOZSNh+tIMWiZkJ+GKMksPGUw1e4d7Cl1EZUyOFCuTIBOG5fNsOwUvj5Uw3vbyxiSaWb84FTG5KZiNmi5eNZQPIEoE4eks/tIGZWuIJOGplHlCrH5cC0XTh9KmlkXD8+ROfsyJd+JKa4MTPEJRzQmk59hSpbvO1zl4Q8fHWREjrKCHz1ImfjkZZjQaZUZta3IzqxRWWw5YmfikDSGZaXg9EcYl5eKJCvm9vOmDqbSGUSrVVbzx+v8bD/mYPNhibljstlX5mJifo9lD+0w7anHWl/qBEHAqNNQ4w4hyTLpKYrDiicQJT/ThEYQ+HR3HXX+KEU1ZjzBKDmpRibmp6HXathT4iIvw8ioQRYiMYlvjtQxf2Iuw7NTeMdWyqd7KnH6lcxJkiwzKsfCaeNz2Hncyf4yN0MyzZw5QakLOujq7zF29rDkGNLMeibkp1HjDvH5vkryM8yUOQLkpBmZNNRCikFHqd1PQaVSVzYQCJKbmcaSOcOQZCh3BJg6PIP10bMoe/cFtmxejzboQIxF2HDUh8WsZIwy67WcMyUf3eh7eP2Z3/HRi39kUP5wrr/3SfKGjUKnV55dp563hDWrX+Ti79/MnNHZ+IIxDpa7MUy/jLp//pJbbr2NVz6XmTAiDzgRHnPNrffzuxWXM3ryDM644LvJe6/RCGTIHsaOHoVWI6DVaPn+bfdzePcW5s8Yy2mnjwJgxvDl/HbNy8wwlDJt3gK+2F/FJ7sriIkymSkadnzwEuX7NvPTa27APMhCqknHruNORgzO5vwrf8jH//kblQENg9K0yMCSc6zUfjGfMSOGsssts3prCaIkK8/MiZfyxT9uJct6BeU+gStPHcm6Tz/gM1cVKx4exZ9v/R/OvOOfZOePYHSuhfmTcympCzD1f77PrKmDk8/0xG97VTmfvPY89z63CtGSh1Gn1JSVZJmtR+2U1Pm5ZOZQfGHFfDxvhImXv6nhv7srk1EXWq1AqlHHRTOGEBUliuv8fHGgijmjs8lI0fPF/mqiokSWxcCQLDNzxmQxJNPcptNYQl7q+z+0uqvc0yE27c0VLEkyW44qDiXNhTUk8IXipaPqJVVOfDA6rQadVhEySZapcAbISDGQZTGwrciH2ail1B7gvR2lSLJiqtpX6mb3ccWMnGbWkWUxUFzjZdv7bzLlqv+jxhOiqMaLIAiY9Vqk+H6TdWwOM868gDkLLqRw3y6OltewZ/tWtvx6BWLYT0pKCufd8kc+21vFqEEp1HnD/Gj+WPaWurAYdVQ4A1iMOr535mgKSqr4wVmjldmcI8C8sTmkmfVMG5GFyx/BdszOliN2JFnm8rnDKa71YzZoWTApD0GAtfuq0WkFpo/M5Lxp+UmTxsLJecnalAUVbo5X1fH4f4tZODmPI9VeDlZ4OHVsDpkpBsWkadByqMJLca2PUYMsiJJEMKJMVCYOSSciykiSxO7jHsYPTsNiUpKWH6n24QnGuO3CyawvqGFolpnZE7IZnGEmJ82IdWxOk9i6R66aRSgS47rnv2HOmGysY7IZnmPh0llDGT84jbMm5pJu1vPRrnI2FdaRn2Fi7ujspFkn5Etn0sgU8jPN2I7ZeebTQjYdriXLYqCg0gvITBo0iRp3kLz4jFRCxmTQYveFGR23gCh5ST34QjHmjskmKso4/BGyLUqGmxpPjO3HPJgNWoZkGBkyc6gSXyDAkEwldV21J8QlM4di94VZMDmPifnpOPwR1h2o5suD1YweZGFvqYuMFD2zRmW2KS+9lSu4IyQ+OZ1WgyjJycQPDl+Yd2xlXDh9CHqdgDMQ5bRxOUgyDMuCCflpyc89N92YnJRNyE9jXF5q8rWLZg5l8+E6vjNnOKkmHdGYUk1Hp9Uwb2wOeelKUpD8TOWznLl4IVVRA6VHDvCfPz2ARqvliht+yYQZ8zh3Sj6bDtey7LSRmPTaZB+ThyqTGn84xq7IIXYdNpERz56UeOZcNncklh/cxrr/PI6g0fDk317GFjJQ4wnxP/NGnDArZo3i1sf+wf5t6wkHAwwd3TAWfeGSa1iz+sXkfRuTZ+GzvVXMnTEF3Znnsub1vyNFAkkPXKUSjOKhfN1vn+Nv91yLJXc4M2ZbESVZcQIsL2fk6LHJPtIysvm/594iPXtQ8phWp2P5zffw6p9+y/i/v83504ZwtMaLVqPhvAmpbP7rTgBSjAYmD1P2jkfkWJT+x99GenYuo0+bgoSGMmeAFKOOO554EYCRKH4ODl+YNJOetPGDcG89i/1frGLaRdfy3vZSfNXFWHKHs/KBW9BotTi3v8fs7yznq+cfYczMs7j4yu/hz5hHmSOQzPHsDUZxB6J8+s+nWXT59xg0ZGTyM5NlGWQ4bVwOs0dlodEIpJv1Sk5ircCiU/IIxcsUajVCEyeqhDNb8nM5JY9jtX7mjc1BgCZ1pDuC0MdlrtrVea0nxMovDjdYlgcjMcwGXXIzfutRO0eqvYgS/M/sXA7VhJk5Kis5Wzle56fCGeBotU+pbi/K6HUapg3PYE+Ji+/MHc6BcjfV7hAxUWLmyCxKHQFlXxQlfORwlReT+ygb//0EntpyHnhjKxlmPdq4mVEpSqysYGo8Yc6aOIitR+3kZ5qZOjyD3DQj2/YXcaguitmcwuQh6ewqcfKb707lvKlD2HK0jj0lLi6cMSSp9Gvr7OQOymn1/rj8kaQzUH1EScZWZCcn1cD4NlZDDoeD/TUxzpyYSzgq8pN/bKHOG2b0IAtTh2cQiYl8vKsSGZmoqDw8M8x6ctKMZKYY2F/mQqfVoBUEYpLMKUPT2H7MSZpZz60XTuTimcMIhGMEfB4G5bQvBrjcEWBI3AxnNuiaJJuIiRIbC2uZNjyTnHoJ1Z1OZ7IGqyTJOP1h7n1zN/tK3Tz5vdl4g1EuO3U8C+9/X3lvqhG9TuDrQ7UYdYpzjU6jBKjvPu5EEBQhjEkSNe4w04anU2IPcLzOj1Yj8MTVs+MlstycNi4nniXLwPDsFBw+Jf1dtSdEbpoxGe4QjUm8u72UeWNz2FvqYmxeKpOGpDebT7X+9dBwodiTtCmbT354AF84hl4rJGWzpM5Pid1PullPnTdMMCJS5Q5h1GmYOtTC7LF5PTPYeibD2y6bxX3/+Jgnb13Okh//AlOKhdefeYgVv/0LE2eeCjS1cgXiIUIZKXr2rv+EXZvWsuI3f2q2n1eeuo/Tzv8OFy88nSNOJdNUa/HakZiINxgjJ81ITJSw+yL89sqZnH35j7jo2v8l1azjWLWPQekmamtqeOFXy/C57PziD//hgvlWdpSHEQTlQR+Oipgqd/D4Q//HlXc8yeCxU9n51p/Y8tXnLP7hnUw763x0Gg3BiIigAQ2KU1li3ppm1vPfl5/meMFebnvin2i1irIZmylwxXmnkT9iLDf831Nk5w3B4Q1jMemaVAFqnH88ccwdiBKMiEQliTSjjpC9lN//bClDxkxk8fX38epDP+GRZ17kjh9/l/+59WE+efFJUjMHMfnUc9n79Yecd9WNfPD//sCHW4+wo9iJVqMUp3eUFPDiQzfz82feJyXuKW3Sa+PPXJn8TBMOXwQZGUlWXpuap6PC37JilGWZGk+InNS2C3tUuYIsPXUkp8QnGwkaySXUk82TXrHKsuIp++HOcgZnKAHDnmCU1VtLGJljododJMWgIxCJsfTUkRyp9vHNkTpyUg1EYhIZKQZ0GiG5Epk+IpNoTKnxKMmwu8TJ4DQjk4ZlYIinO6t2h5DleJo9SWZMXirpZh2ThqTzl0cfwBWGn/3iVqoCGvaXuzHotMREiVSTDl84hiyBP+5Bmp1q5LLZw/AGo/hCMfQ6DcW1PvIzzIzPT2Xh5MGMHHRi5iRJDXN5NvPh9QiN+wlHRbYfc3D/W3vwh2OY9FpyUo1878xRfHmgmnnjBvG3NYUsmJyHdXQ2//y6CINWwws/OY3bXrFR5w0zfUQms0Zl8aMFY1vspzeuBRQlfLzOz7jByirgjn9vJzNFz+d7q5BkGY0gMDhDEVCDXkkzWecNM2tUNuPzU/lwRzmCILBwch5FNT6O2/3cuGA4c8YPTa52eul6TirFGo4ngBg5yEKZPcC2Inty+8Ri1HHRzCGEIhJpZh1jMgWK3W212sag4sn6syyKY4ovFMVi1FHlCmE0aMhNM5Ehe7j1hmuYvuASll37MyqcQSoObmXVn+/jxiffIDUjmxS9lmBURAZl/z0mMX/iIDYW1rHvq/c4dmA7P7n3iVYTG4xOhwK72Gz5OcXHQLFkVbtDmA1aYqJiJj1rYi7BUJAKdxiD3kCpw88Z4wZxqNLD9BGZvP/Rf/njr67lt//vYxbOnsjUsUPRCAKrtpYwLi+VC6YP4c1Vq/jZz37OqfPP4ciBXZSVlvKnf73H+FOms6/MzYyRWRi0AiaDFocvwvQRmdR5w3y8uwJ/IMyrj/6csZOmsfSmuwDI1/u5cvHpPPvxHmSUiZ8r7nE/JCtu1ZFlHL4wsgQWkw53PPeyYkFQ4s1H5qQwfnAan+2tVCZWfg9fv/4sB20bGDZ8BM//6zW+2LCVoRNnsem9F/nv+2/z4rtfEnBW8oMrL+Pan97Gnx66izJHgI92VTAxP5Vf3bCMITMW8eT9vyIv3URxrY99ZW5cgQgzR2axZl8l4wansWCyUqzkQLmbXJPIvmqlDGUinj4UFTHotATCMZyBCLlpRlyBKEMyzUqu6FAsWVtYIwhKDVmNkpTk+2eNbrLf2q8V6+EqD//ZWMyhSg8xUWZolpmj1V4GpZnQawUmD03nUIUHi0nHtOGZxESJKruHzDQLFa4ggqC48+ekGrEYdUlTqABIKIrszAm57DzuTOY5HZefRlaKgWO1PpaeOjJZriwWizFhwgTefvtt1q1bxx133MGRKg/bihwsmJzHoDQjoYgY/1KU8+meSsbmpTIiJ4XcdBOLThnMhPiDvb1mhr5SrAkSRandwShZKQb0cYUzKM2Y9GLWaAT2lDjRagRmjMxiW5GdW/9l4707FpKXYWpXP71xLfVZuXIlN910E9uP1eH0x5iYn8rQrBR2H3fiDESYMSKTVzcf5/tnjibLYuCqZzZw3tR8rl84lj9+fAitRuCmBUP74rPpFcVqs9nktrZpnvzwABpBoNodxKjXsr6ghjMn5jI004wsKz4O9SeJYzOFdpXyisQkfKFosti1OxBFr1OsId5QlAyzAW8oilajTIZK6gIMilss7L4Q//n1NSyYfxbnXnsvBZVexual4g1FefNvj2EI1nDZbX9ARuDM8YPIzzKz9aidSEziR/PHUFjl4Yk//oXjRws4+4d3YYl7HovxCW80pniS56abGGaRKbCLBOMFBRI6WJYhxajFYtRR6w2zcFIe+Zkmthy1c+5UxeM+QUyUCMeUSUj9SXV1dTV5eXk4nc4Ws7xt3bqVzz77jB/96Efo9Xry8/MR4lVhdFqhRY9Yhz/Cv9bs5vHbvkdGdi7/c9ujDNV5+P19d3Lnc+8Rjilx/fMn5VJQ6Y3nxAZRlpk2PJNUo469ZS5OGzcIdzDKqJwUxg5Ow6jTJFd/siwTiIgIgE6QuOiii5g1axa/+c1vyMrKQpKUQufBYIDU1FSiMYktuw9w+QULueGGGzjjjDO44oor+Otf/8o/X3yRDz79kiHZJ1IYSpKyODLpFYel/PjWUoKyqlre2+vE7lN8aqIxiZw0I3av4vy56JTBnDIsg7e2llDmCCAIMHdMDhPy0yiu8eEORlk8LV/xdtdqmk0DWV8u49s05yS2aU56xbq7xMlTHx3EFYgSiopIkszEIemMzrWQGXdOEAQliDwiSviCMWbkG6gJaRiUZqSw0ktUklg8NR+zXpusmBCKKNliHP4IF88cSjAi4g/H8IZijMxRPHXDUalBfdAXXniB1157jbVr13Lttdfy8ssvtzjuSEyiPP6BeYJRpgzLaFfZpMb0tWLtDLIsc6Tax4T8tB7tpyXa08eKFSt4/vnnWz2nPhXOANkWI6Z6YSJ99NmcVCtWk17Dmn3VhGIiZ03MVZKTNIMoyYzP0nDM3XKzkiQnV3fDs1M4VOFGo9GwZPZQNhTWEY6KTB+ZyexRWWw+XEdhlZefL57Iu9tLGZuXyvjBaTz4p//Hv//4a2pqagiJAp/tqeD0CbmkmXQcLLXzy+uuZOSEKfz24ceZMkLZYpFlxYSYmHQ/8cQTVFdXc+u9D7FmXyWl9kDSnKoRBGaPysZ2zM6cYUbOmz2OwkpPctXu8EeIRCWGZJnJzzARjkoNvjMdpae+Y7Isc6TKzSMP/57/vvsaVy+/mj379nPdb5/DH47xvTNHk2LQEo5J7C9zJzNiDctqmimuPUSjUWKxGKFQqNXrufrqq8nOzuazzz7jlFNOYdu2bXz99ddMnDixQ/05nU7S0jOo8YTJTlX8RAalGdlf5gKEZCijPxRj53EHuWkmJnXQ8nTSrljbmhXHRIk/fHyQj3dWsGBSLjqdhkA4RnaqAa1Ggz8cQ6cRkjPJqCjxXesI8kwiI4fkJmdvwajYobRa9amtreXIkSOMHz+eGTNm8P777zNv3rx+qfC+Lf0MpGup30/jWXEP0+qDISZK/O9/dnDc7sds0LHolLzkAzcQjlHlCjJykAVJVmqwugIR5gwzsqNcWe35w0psa0xSzPCSpCRsOX3CIC6YPgStRqCg0oNRr2VMbiq18djgoVnKak+Kp5XMshiUzE/xUmpz5szh3nvvZdmyZc2O2+12s3z5curq6vj973/P3Llzyck54cOwZs0ali9fzssvv8xll12GJMl8uKucDJOe0XmppBgUp5qNBTUYCWGdNLK77nez9MZ3LFEY/qc//Sl//OPTSunFZszb3UF7r6euro53332X+fPnM3ny5B7rpyuctIqVdgjvHz46yLyx2Rj1Wtbur+a8qYOZOyabQFjEG4qyZl8VKQYtZ0zI5UC5i4tnDsPtdnXbTf3zn//MX/7yF84++2yys7N56qmnAJg/fz4bNmzolj5aY6Aqib7uY9GiRaxbt67H++kOTsYV69vbSvnnV0cZl5fKhHylVnAoKqIRlIIYE/LT2FfmIjPFkIwndDpdSPoUth21M31EJjqNQG66kcEZZvQ6DeWOAHNGZ7dafaU19u7dyyWXXMLIkSPZuHFjyxcmy/zjH//g5ZdfZt++fZx77rnk5+dz5ZVXcvvtt/Pwww9z+eWXNzi/uVWaw+HoUDGOztBb37H169czZMgQxo8f36P9tHU93SGX7emnO2hNsbYviWMfodNquOc7U5P/Tx2eGU9PpyQ3z0kzcv3CcQiCYg4ek9e9ZYSCwSA2m42ioiLq6uooLi5Ovnb33Xd3a18qvcsDDzzQ10Po11xhHR7P16uEgQ3NMiu5gCWZMyYM4qyJuYzMsTB3THYyzMGRIZCdnd0gA1J9WjIjt5fXXnuN73//+5x11lmtnicIAjfeeCM33ngjbrebd999l8rKSu666y7mzJnDd77znSbnt9TOQGHatGm9osDbYqDI5UmtWBvTXAxrZ2e3bVFbW8uECROwWCzcfvvtDBs2rMEXb9y4k6I8rUon6eiezbeNtmLME0rFH44xOZ7KccnsYYzMsZCRoken1bBgcl6z7+mMr0F7+Pzzz3nqqacYNGhQ2yfHycjI4Mc//jEA99xzT4+MS6X99Fe5bHfmpfZitVozgcWAK97BmtaO9xf27duH2+0mEonw5JNPotM1vFXnnXcelZWVfTQ6la5itVqpqKho+8RvKe3JvJTg0lnDSDPpu+Sk01XsdjuFhYWcfvrpjBo1SpXNfkp/lcsOZV5qJyuA1Tabrchqta4C1rRxvF+wf/9+LrzwQs4888wmShXgwIEDfTAqle6iPwpvR+npSe/4wUp2pEFpxj43i65Zs4b58+djMBhU2ezHDBS57A7FOg+lXitAZjuOJ1m/fj07duwAYObMmcycObMbhqPsjXaVHTt2cM4557BixQqczqaFfZ5++mnuuOOOLvfTFt1xLd+2ftrTx7PPPsstt9zS4/10B1u3buXQoUMAvPLKKx1Jadijk94r5vWsR2xHePnll7nmmmsA5bP9zW9+08cjUukMTz31FHfeeWdfD6PL9Oke64IFC1iwYEGPtN3VjfgjR47wgx/8oMV27HZ7r232q/10fx8uV/d4jvfGtZx66qlceOGFANx2223rOvDWTk96+xNlZWVs2bKF1atXA1BVVdXHI1LpLOqK9QTbgGwUs5KrHcdPeqLRKHv27GH69OktnvPwww/34ohUuptE2JRK8/SENamnVvgvv/wyF198MeFwmHA4zK9//etmrUzdzclifRlI/dx3333d8tn11meze/dudu/eDTS0JnWHYn0euMpqtRYBKwGsVuvS5o73FzZt2sS4cePIzc1t8ZxzzjmHXbt29d6gVLqVuXPnsn379r4eRk/T6UlvT1mTemKF//HHHydT5UHvyubJYH0ZSP10p1z2xvUsWrSIRYsWAQ2tSV1WrDabzcUJs1Li2Or4n+3PGXeSEA6HefPNN1myZEmr5z399NO9NCKVnqAj6Qz7MQNu0lufgoICHA4HhYWFnHvuucnjqmz2XwaKXParONbuRJZl1q9fT3l5OeXl5XzyySccPnyY6upqxowZw3vvvdfq+1NTuzcZhUrvkpbWNI/xQGOgTXrrI8sy5557LpWVlbz88ssYDCdi3FXZ7L8MFLnsmUjtdmKz2Vi5ciU2m61H+5Ekiffff58777yT1NRUxo4dS35+Pj//+c957733OHLkCHfccQfr1q3D7/dz6NAhJk2a1GqbCQ9Elf7JZZdd1tdD6DA2mw2r1bqor8dxMlBYWIhWq2XXrl384Ac/aPCaKpv9l/4ol83RpyvWjgShdxaPx8Py5cuprq7m1FNP5eDBg4RCIYxGIyNGjOh0/N22bdu6eaQqvUlhYWFfD6HDNA5C70nayrzUHcRiMRwOBzk5OWi17U8uIcsya9eu5dxzz2XGjBlNXldls//SH+USeiDzUk/z3nvvYTAYSElJwWKxYDabMRqNyR+DwYBWq0Wj0aDVatFqtUiSBCgf0rJlyzjrrLP44IMPmk300Fkee+wxHn/88W5rT6V3eeCBBwZMXtKeoK1J71tvvcVzzz1HSkoKZrMZs9mMyWRCp9Oh0+nQarXJ3xqNRintGA6TkpKCKIrs2LGDTZs2odPp8Hq9TJw4kby8PIYMGcLYsWOTP3l5eVgslqT8GwwGrrnmGlatWsVrr73W7NhU2ey/9Fe57InMSz3K66+/jsvlwu/34/f7CQaDSbf6cDhMJBJBkiREUUz+SJKELMvk5eVx9913c8cdd/R5ZhgVlYHE6aefTkZGBsFgMPkTCoWIxWKIotjgtyzLSZlMKN4VK1bwr3/9i9zcXMLhMPv378fhcFBZWUlRURHr1q3jn//8J3V1dfj9fgKBAH6/n1AoxDnnnIPf7yclJaXtgaqo9AEnddm4zuJ0OsnMzAR6rgLFQCqzNtD6GUjX0kw/J0XZuM7QHfcr8bxqTa4H0uc/kK5loPXTb8vGdQV1haqiMvBQ5VqlP/Ct8ApWURkI9KZXsCqbKirtp7FsDnivYBWVgUJvegWrsqmi0n4ay2Zf77GqqKioqKgMKPrUFKyioqKiojLQUBWrioqKiopKNzJgvYIhmXB8ns1mu7sb28wEFhOvCmKz2TpVJLqdfXX7+JvpIxMYC1gBR71cst3dz2KU2p+unrxn8b6WAkU2m21HD7WfCWxHKRC+sqf6ife1ArABVpvN1q/z+yboqe91b8nmQJLLeF8DQjZPJrkc0CvW+Jcxs5ubXQHsiH8Bb+rmthvQQ+NvzFUoAvU80CPpaqxW6xxOPBx69J7FhWseSlm0nuR8m812Uw8L72KU+7YD5WExIOjB73WvyOZAkUsYkLJ5UsjlgFasPcQ8wBH/O7MPx9Et2Gy25202W1H8S98jX8b4F7DIarXeBTzaE33Uw4pSb7SnmWO1WpfGhaynWAaMjfcxpwf7GSgMGNnsDbmM9zPQZPOkkMt+bwqOmxYa0JNmkwHMvcCNPdW4zWZzWa3W1cDd9NDM2Gq1LrbZbGua+050J/FybKvjfa6iZ1eTa2w22w6r1bo90Wd/QJXLbqNH5RIGjmyeTHLZ7xVrHwjrNhRThiv+0++Jf9kf5cR1dXf7dwGJGfhV9JzJyRGfRZ4PHKWHBCu+v/JmXJDH9kQfcbbT8ybtHqGPlOiAks2elst4HwNGNk8muRzQpuD4F3NsfB+hu3geWBz/kqzsxnab0EPjb9zHYpRZ8Qv03F7OGpTrWIEyK+4R4matRKqgnJ7qB3gT5XqW0rPX8zyKaWsxPW+m6zV68HvdK7I5gOQSBpZsnjRyqSaIUFFRUVFR6UYG9IpVRUVFRUWlt1EVq4qKioqKSjeiKlYVFRUVFZVuRFWsKioqKioq3YiqWFVUVFRUVLoRVbF2EavVOrbe33OsVmtPusa3m/rj6o7zOtBvn92DeN9zmjl2UnwmKr2HKpdN2lPlshdRFWvXSX45bDbbjp5MzN1B2vulHUhfbmtP5ghV6Veocnny8K2Ty36feakviWctWWy1WleiBCSPBZYDb6AIxg6UahsrgblAts1mWxZ/76p4M583ro5gtVo/t9ls58dnratsNtvc+Ixvef0HRPz1u1GygNxts9mKmhtXPBNJIuj8JpR8qivjY2twXv1xEa8SARTFzz0/0Uej8a7kRCaSR+u1aY2Pvf4437DZbKvj15O8RzabbW6j+5K8N63dq3bSYDydeL9KP0KVy+Q4VLnsI9QVaxew2WxPKL9sNyWEpNHrd6MIQabNZruJeGLwuIC9ERfm5r5Qn8eFbTFKguzM+N9vNHPuVcCN9QWrlXEtQymndFN8Ft/gvBbGVRQfe7N5ROMZW7bbbLZliYcTSuWHm4A18RyhRfE+ljVuI3GPrFZrImPO5/HzMuPC29a9SoxjKUrmleZoMJ6W2lAZGKhyqcplX6OuWHuOhEDZ6/3tigvjOGCc1WqdR/M5QNegzLAzOTGDPT8ucI15s7mHRws8DqyM720sa2aW29q4WirFNZem6ePqXzuQLE9lpWEOz8bnOYBl8XMTpqO27lWC7FbuQ5PxqHxrUeVSlcseR1WsfcN2WileHK+acG/8nDVxc4mrhbZaOt5cu0XA+fHZ4VKg8QOhwbgaOVAs5oQg1OcoimC2uIcSnz1nouRybS3JdyLZeP0cnK3eq3rjbG5sKiodQZXL5lHlsoOopuCu47Jaras64sUX348432q1rmy0d1EfB8qXF5TZ5OeJF1p6T6PjTcZltVrvip9zNydKHSXPa2Fc1vgDJGF2anwtTwBz4220dC1FKFUt7m3h9frXvDR+7uNWqzWznfdqsU0pbq2ikkCVS1Uu+ww1Cb9KiyScG+L7IL3R36p4f0Vxs9NN7enbarWu6KTzhIpKv0OVy5Mf1RSscjKxErjbarW6OLGP1Spx89m3clasotJLqHLZQdQVq4qKioqKSjei7rGqqKioqKh0I6piVVFRUVFR6UZUxaqioqKiotKN/H+5DxAXu2i6yQAAAABJRU5ErkJggg==", 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" ] @@ -239,6 +241,35 @@ "causalimpact_plot(result_0_0, result_0_1, 0, '20220314_ci_0.pdf')" ] }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[2022-09-27 11:59:50,222] ERROR | darts.metrics.metrics | ValueError: The series of actual value cannot sum to zero when computing OPE.\n", + "[2022-09-27 11:59:50,233] ERROR | darts.metrics.metrics | ValueError: The series of actual value cannot sum to zero when computing OPE.\n" + ] + }, + { + "data": { + "text/plain": [ + "{'0': {'mae': 0.2204904970993461, 'mape': 203.51038720482185, 'ope': nan},\n", + " '1': {'mae': 0.05486167548508333, 'mape': 668.3050810428863, 'ope': nan}}" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "get_metrics(result_0_0, result_0_1)" + ] + }, { "cell_type": "code", "execution_count": 27, @@ -261,6 +292,31 @@ "causalimpact_plot(result_1_0, result_1_1, 1, '20220314_ci_1.pdf')" ] }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'0': {'mae': 0.004724559831830777,\n", + " 'mape': 3.52921011128648,\n", + " 'ope': 1.9152944087451809},\n", + " '1': {'mae': 0.005935794237341377,\n", + " 'mape': 9.183912443072513,\n", + " 'ope': 9.42319266787561}}" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "get_metrics(result_1_0, result_1_1)" + ] + }, { "cell_type": "code", "execution_count": 28, @@ -283,6 +339,31 @@ "causalimpact_plot(result_2_0, result_2_1, 2, '20220314_ci_2.pdf')" ] }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'0': {'mae': 0.0064863643549892035,\n", + " 'mape': 4.404323783229881,\n", + " 'ope': 1.2509965472902185},\n", + " '1': {'mae': 0.004238735619285648,\n", + " 'mape': 8.572983873224636,\n", + " 'ope': 6.899042428072738}}" + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "get_metrics(result_2_0, result_2_1)" + ] + }, { "cell_type": "code", "execution_count": 29, @@ -305,6 +386,31 @@ "causalimpact_plot(result_3_0, result_3_1, 3, '20220314_ci_3.pdf')" ] }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'0': {'mae': 0.04048384384684695,\n", + " 'mape': 13.57750546203148,\n", + " 'ope': 15.08207698985565},\n", + " '1': {'mae': 0.23471300953260435,\n", + " 'mape': 45.7221103666684,\n", + " 'ope': 52.395973063090025}}" + ] + }, + "execution_count": 58, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "get_metrics(result_3_0, result_3_1)" + ] + }, { "cell_type": "code", "execution_count": 30, @@ -327,6 +433,31 @@ "causalimpact_plot(result_4_0, result_4_1, 4, '20220314_ci_4.pdf')" ] }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'0': {'mae': 0.015713700766674322,\n", + " 'mape': 8.890622907819836,\n", + " 'ope': 3.377363347288859},\n", + " '1': {'mae': 0.04325715657655422,\n", + " 'mape': 32.428378116697516,\n", + " 'ope': 35.51835853223632}}" + ] + }, + "execution_count": 59, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "get_metrics(result_4_0, result_4_1)" + ] + }, { "cell_type": "code", "execution_count": 31, @@ -349,6 +480,31 @@ "causalimpact_plot(result_5_0, result_5_1, 5, '20220314_ci_5.pdf')" ] }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'0': {'mae': 0.02575481116456133,\n", + " 'mape': 9.221255550550932,\n", + " 'ope': 10.380424458091934},\n", + " '1': {'mae': 0.012893713674348252,\n", + " 'mape': 13.859249044292815,\n", + " 'ope': 15.658679130013631}}" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "get_metrics(result_5_0, result_5_1)" + ] + }, { "cell_type": "code", "execution_count": 32, @@ -371,6 +527,31 @@ "causalimpact_plot(result_6_0, result_6_1, 6, '20220314_ci_6.pdf')" ] }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'0': {'mae': 0.058129025405499246,\n", + " 'mape': 17.68708364461607,\n", + " 'ope': 19.38478365752753},\n", + " '1': {'mae': 0.039070309400104294,\n", + " 'mape': 32.15274954177026,\n", + " 'ope': 36.445545687538385}}" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "get_metrics(result_6_0, result_6_1)" + ] + }, { "cell_type": "code", "execution_count": null,