From 77e8268f65871bac7fcd7b20b68e751988b74cf2 Mon Sep 17 00:00:00 2001 From: Tuan-Dat Tran Date: Fri, 6 Aug 2021 23:49:37 +0200 Subject: [PATCH] Ok now this should be the final one --- 1-first-project/Abgabe.ipynb | 100 +++--- 2-second-project/tdt/DataViz.ipynb | 469 ++++++++++------------------- 2 files changed, 224 insertions(+), 345 deletions(-) diff --git a/1-first-project/Abgabe.ipynb b/1-first-project/Abgabe.ipynb index bfb02c1..aa2bf4a 100644 --- a/1-first-project/Abgabe.ipynb +++ b/1-first-project/Abgabe.ipynb @@ -3,7 +3,7 @@ { "cell_type": "code", "execution_count": 1, - "id": "25366fc5", + "id": "4f19089f", "metadata": {}, "outputs": [], "source": [ @@ -28,7 +28,7 @@ { "cell_type": "code", "execution_count": 2, - "id": "0394ccfe", + "id": "fb26acd0", "metadata": {}, "outputs": [], "source": [ @@ -39,7 +39,7 @@ { "cell_type": "code", "execution_count": 3, - "id": "de4b0575", + "id": "369eda91", "metadata": {}, "outputs": [], "source": [ @@ -68,7 +68,7 @@ { "cell_type": "code", "execution_count": 4, - "id": "fb2cbb23", + "id": "69ef44d7", "metadata": {}, "outputs": [], "source": [ @@ -81,7 +81,7 @@ { "cell_type": "code", "execution_count": 5, - "id": "da88ad64", + "id": "7b98dc5f", "metadata": {}, "outputs": [], "source": [ @@ -98,7 +98,7 @@ { "cell_type": "code", "execution_count": 6, - "id": "e0eb540b", + "id": "a4681cd9", "metadata": {}, "outputs": [ { @@ -130,7 +130,7 @@ { "cell_type": "code", "execution_count": 7, - "id": "06d7c640", + "id": "5809f73a", "metadata": {}, "outputs": [], "source": [ @@ -186,7 +186,7 @@ { "cell_type": "code", "execution_count": 8, - "id": "4d60cf83", + "id": "c8b0cedc", "metadata": {}, "outputs": [], "source": [ @@ -202,7 +202,7 @@ { "cell_type": "code", "execution_count": 9, - "id": "e9ee34bc", + "id": "a00f25da", "metadata": {}, "outputs": [], "source": [ @@ -232,7 +232,7 @@ { "cell_type": "code", "execution_count": 10, - "id": "435cc54c", + "id": "c79e017b", "metadata": {}, "outputs": [], "source": [ @@ -251,7 +251,7 @@ { "cell_type": "code", "execution_count": 11, - "id": "f521d549", + "id": "4cacc665", "metadata": {}, "outputs": [], "source": [ @@ -269,7 +269,7 @@ { "cell_type": "code", "execution_count": 12, - "id": "c0d35f7e", + "id": "f44a38fa", "metadata": {}, "outputs": [], "source": [ @@ -298,7 +298,7 @@ { "cell_type": "code", "execution_count": 13, - "id": "9972009a", + "id": "0ef2c100", "metadata": {}, "outputs": [ { @@ -312,7 +312,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 26179/26179 [01:29<00:00, 291.28it/s]\n" + "100%|██████████| 26179/26179 [01:28<00:00, 294.18it/s]\n" ] } ], @@ -355,7 +355,7 @@ { "cell_type": "code", "execution_count": 14, - "id": "d65fcf35", + "id": "54adc91f", "metadata": {}, "outputs": [ { @@ -385,14 +385,14 @@ { "cell_type": "code", "execution_count": 15, - "id": "e3b48487", + "id": "0c77f574", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - " 19%|█▉ | 3717/19640 [00:00<00:00, 18600.96it/s]" + " 18%|█▊ | 3624/19640 [00:00<00:00, 18199.99it/s]" ] }, { @@ -406,7 +406,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 19640/19640 [00:01<00:00, 18565.30it/s]\n" + "100%|██████████| 19640/19640 [00:01<00:00, 19054.38it/s]\n" ] } ], @@ -427,7 +427,7 @@ { "cell_type": "code", "execution_count": 16, - "id": "ba0c9798", + "id": "224a0acc", "metadata": {}, "outputs": [], "source": [ @@ -465,13 +465,15 @@ " metrics=[\"acc\"],\n", " )\n", " \n", + " model.summary()\n", + " \n", " return model" ] }, { "cell_type": "code", "execution_count": 17, - "id": "08d775aa", + "id": "8b1920de", "metadata": {}, "outputs": [], "source": [ @@ -480,8 +482,6 @@ "def train(X_train, y_train, X_test, y_test):\n", " model = build_model(X_train[0].shape, 52)\n", " \n", - " model.summary()\n", - " \n", " # Create a callback that saves the model's weights\n", " model_checkpoint = ModelCheckpoint(filepath=checkpoint_path, monitor='loss', \n", "\t\t\tsave_best_only=True)\n", @@ -504,7 +504,7 @@ { "cell_type": "code", "execution_count": 18, - "id": "0666829a", + "id": "830bc0c4", "metadata": {}, "outputs": [], "source": [ @@ -529,7 +529,7 @@ { "cell_type": "code", "execution_count": 19, - "id": "adfe695d", + "id": "52c4202a", "metadata": { "tags": [] }, @@ -539,8 +539,36 @@ "output_type": "stream", "text": [ "Loaded weights...\n", - "CPU times: user 400 ms, sys: 145 ms, total: 545 ms\n", - "Wall time: 573 ms\n" + "Model: \"sequential\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "flatten (Flatten) (None, 1050) 0 \n", + "_________________________________________________________________\n", + "dropout_10.0 (Dropout) (None, 1050) 0 \n", + "_________________________________________________________________\n", + "batchNorm (BatchNormalizatio (None, 1050) 4200 \n", + "_________________________________________________________________\n", + "HiddenDropout_10 (Dropout) (None, 1050) 0 \n", + "_________________________________________________________________\n", + "Hidden_1 (Dense) (None, 525) 551775 \n", + "_________________________________________________________________\n", + "HiddenDropout_20 (Dropout) (None, 525) 0 \n", + "_________________________________________________________________\n", + "Hidden_2 (Dense) (None, 262) 137812 \n", + "_________________________________________________________________\n", + "HiddenDropout_30 (Dropout) (None, 262) 0 \n", + "_________________________________________________________________\n", + "Hidden_3 (Dense) (None, 131) 34453 \n", + "_________________________________________________________________\n", + "Output (Dense) (None, 52) 6864 \n", + "=================================================================\n", + "Total params: 735,104\n", + "Trainable params: 733,004\n", + "Non-trainable params: 2,100\n", + "_________________________________________________________________\n", + "CPU times: user 338 ms, sys: 217 ms, total: 554 ms\n", + "Wall time: 574 ms\n" ] } ], @@ -557,7 +585,7 @@ }, { "cell_type": "markdown", - "id": "35a8741f", + "id": "a9ac22d1", "metadata": {}, "source": [ "# Evaluation" @@ -566,7 +594,7 @@ { "cell_type": "code", "execution_count": 20, - "id": "f0fa25f6", + "id": "6c7a4243", "metadata": {}, "outputs": [], "source": [ @@ -577,7 +605,7 @@ { "cell_type": "code", "execution_count": 21, - "id": "fc983eae", + "id": "81f43c20", "metadata": {}, "outputs": [ { @@ -655,8 +683,8 @@ " macro avg 0.79 0.78 0.78 3928\n", "weighted avg 0.77 0.77 0.76 3928\n", "\n", - "CPU times: user 1.01 s, sys: 209 ms, total: 1.22 s\n", - "Wall time: 966 ms\n" + "CPU times: user 998 ms, sys: 195 ms, total: 1.19 s\n", + "Wall time: 963 ms\n" ] } ], @@ -685,7 +713,7 @@ { "cell_type": "code", "execution_count": 22, - "id": "70716586", + "id": "3fbedc43", "metadata": {}, "outputs": [], "source": [ @@ -720,11 +748,13 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "d28c3de8", + "execution_count": 23, + "id": "12fec3a9", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "exit()" + ] } ], "metadata": { diff --git a/2-second-project/tdt/DataViz.ipynb b/2-second-project/tdt/DataViz.ipynb index 528aabe..48f251e 100644 --- a/2-second-project/tdt/DataViz.ipynb +++ b/2-second-project/tdt/DataViz.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "7b267a00", + "id": "9c890798", "metadata": {}, "source": [ "# Change Scenario here.\n", @@ -24,18 +24,18 @@ { "cell_type": "code", "execution_count": 1, - "id": "89e64979", + "id": "1c9e114c", "metadata": {}, "outputs": [], "source": [ "# Possibilities: 'SYY', 'SYN', 'SNY', 'SNN', \n", "# 'JYY', 'JYN', 'JNY', 'JNN'\n", - "cenario = 'JNY'" + "cenario = 'SYN'" ] }, { "cell_type": "markdown", - "id": "78d89b56", + "id": "a3c8b624", "metadata": {}, "source": [ "## Constants" @@ -44,7 +44,7 @@ { "cell_type": "code", "execution_count": 2, - "id": "ac30b29b", + "id": "5f120a31", "metadata": {}, "outputs": [], "source": [ @@ -57,7 +57,7 @@ { "cell_type": "code", "execution_count": 3, - "id": "93caedf8", + "id": "3be386b5", "metadata": {}, "outputs": [], "source": [ @@ -72,7 +72,7 @@ }, { "cell_type": "markdown", - "id": "85df72a7", + "id": "375756bc", "metadata": {}, "source": [ "# Config" @@ -81,7 +81,7 @@ { "cell_type": "code", "execution_count": 4, - "id": "95998d2f", + "id": "fe73e572", "metadata": {}, "outputs": [], "source": [ @@ -104,7 +104,7 @@ }, { "cell_type": "markdown", - "id": "dbb78517", + "id": "0173497c", "metadata": {}, "source": [ "# Helper Functions" @@ -113,7 +113,7 @@ { "cell_type": "code", "execution_count": 5, - "id": "ff7846ef", + "id": "ef82a419", "metadata": {}, "outputs": [], "source": [ @@ -131,7 +131,7 @@ }, { "cell_type": "markdown", - "id": "8b24a0b6", + "id": "556c7dde", "metadata": {}, "source": [ "# Loading Data" @@ -140,7 +140,7 @@ { "cell_type": "code", "execution_count": 6, - "id": "208b2541", + "id": "51195751", "metadata": { "tags": [] }, @@ -185,7 +185,7 @@ { "cell_type": "code", "execution_count": 7, - "id": "2b0d4f09", + "id": "457bc16f", "metadata": {}, "outputs": [], "source": [ @@ -200,7 +200,7 @@ { "cell_type": "code", "execution_count": 8, - "id": "c1dba068", + "id": "9482bc78", "metadata": {}, "outputs": [], "source": [ @@ -215,7 +215,7 @@ { "cell_type": "code", "execution_count": 9, - "id": "24618fd1", + "id": "230fb3b8", "metadata": {}, "outputs": [ { @@ -225,8 +225,8 @@ "Loading data...\n", "../data.pickle found...\n", "768\n", - "CPU times: user 548 ms, sys: 2.58 s, total: 3.13 s\n", - "Wall time: 3.13 s\n" + "CPU times: user 572 ms, sys: 2.57 s, total: 3.14 s\n", + "Wall time: 3.14 s\n" ] } ], @@ -251,7 +251,7 @@ { "cell_type": "code", "execution_count": 10, - "id": "c7aa13b0", + "id": "effa570d", "metadata": { "tags": [] }, @@ -260,8 +260,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 90 µs, sys: 305 µs, total: 395 µs\n", - "Wall time: 399 µs\n" + "CPU times: user 393 µs, sys: 0 ns, total: 393 µs\n", + "Wall time: 397 µs\n" ] } ], @@ -309,7 +309,7 @@ }, { "cell_type": "markdown", - "id": "2d57c298", + "id": "2ad62c63", "metadata": {}, "source": [ "# Preprocessing" @@ -318,7 +318,7 @@ { "cell_type": "code", "execution_count": 11, - "id": "c3e6103d", + "id": "55619c6e", "metadata": { "tags": [] }, @@ -338,7 +338,7 @@ { "cell_type": "code", "execution_count": 12, - "id": "60c0fdc1", + "id": "d7be5822", "metadata": {}, "outputs": [], "source": [ @@ -367,7 +367,7 @@ { "cell_type": "code", "execution_count": 13, - "id": "6999b99e", + "id": "da77d0a9", "metadata": {}, "outputs": [], "source": [ @@ -395,7 +395,7 @@ { "cell_type": "code", "execution_count": 14, - "id": "58c8236d", + "id": "ac13ea7d", "metadata": {}, "outputs": [], "source": [ @@ -411,7 +411,7 @@ { "cell_type": "code", "execution_count": 15, - "id": "3b92ad51", + "id": "2f6b0535", "metadata": {}, "outputs": [], "source": [ @@ -436,7 +436,7 @@ { "cell_type": "code", "execution_count": 16, - "id": "a0a84f32", + "id": "be9a3bee", "metadata": { "tags": [] }, @@ -445,7 +445,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 96/96 [00:07<00:00, 12.98it/s]\n" + "100%|██████████| 96/96 [00:05<00:00, 16.33it/s]\n" ] } ], @@ -472,7 +472,7 @@ { "cell_type": "code", "execution_count": 17, - "id": "f273c028", + "id": "bf571416", "metadata": {}, "outputs": [], "source": [ @@ -483,7 +483,7 @@ { "cell_type": "code", "execution_count": 18, - "id": "f8f39e17", + "id": "dc70c74b", "metadata": {}, "outputs": [], "source": [ @@ -507,7 +507,7 @@ { "cell_type": "code", "execution_count": 19, - "id": "34559bb8", + "id": "45877405", "metadata": {}, "outputs": [], "source": [ @@ -525,22 +525,22 @@ { "cell_type": "code", "execution_count": 20, - "id": "25a4490b", + "id": "d7a30d7b", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 96/96 [00:15<00:00, 6.08it/s]" + "100%|██████████| 96/96 [00:14<00:00, 6.67it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 14.8 s, sys: 1.46 s, total: 16.2 s\n", - "Wall time: 15.8 s\n" + "CPU times: user 13 s, sys: 1.93 s, total: 14.9 s\n", + "Wall time: 14.4 s\n" ] }, { @@ -594,13 +594,13 @@ { "cell_type": "code", "execution_count": 21, - "id": "42fbd7f3", + "id": "c88f53a4", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[]" + "[]" ] }, "execution_count": 21, @@ -609,7 +609,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -629,13 +629,13 @@ { "cell_type": "code", "execution_count": 22, - "id": "2ac72178", + "id": "b9518087", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[]" + "[]" ] }, "execution_count": 22, @@ -644,7 +644,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -664,13 +664,13 @@ { "cell_type": "code", "execution_count": 23, - "id": "e630d26e", + "id": "09687aab", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[]" + "[]" ] }, "execution_count": 23, @@ -679,7 +679,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -699,13 +699,13 @@ { "cell_type": "code", "execution_count": 24, - "id": "1cb13163", + "id": "9ae9b71e", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[]" + "[]" ] }, "execution_count": 24, @@ -714,7 +714,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -734,15 +734,15 @@ { "cell_type": "code", "execution_count": 25, - "id": "a0c5c99a", + "id": "29e9063e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 120 µs, sys: 96 µs, total: 216 µs\n", - "Wall time: 226 µs\n" + "CPU times: user 234 µs, sys: 0 ns, total: 234 µs\n", + "Wall time: 252 µs\n" ] }, { @@ -767,23 +767,23 @@ { "cell_type": "code", "execution_count": 26, - "id": "435315a3", + "id": "a52352aa", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 96/96 [00:39<00:00, 2.42it/s]\n" + "100%|██████████| 96/96 [00:36<00:00, 2.62it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "(59496, 5, 408) (59496,) (54212, 5, 408) (54212,)\n", - "CPU times: user 1min 55s, sys: 17.4 s, total: 2min 12s\n", - "Wall time: 40 s\n" + "(57800, 5, 336) (57800,) (37106, 5, 336) (37106,)\n", + "CPU times: user 1min 48s, sys: 14.9 s, total: 2min 3s\n", + "Wall time: 37 s\n" ] } ], @@ -841,7 +841,7 @@ { "cell_type": "code", "execution_count": 27, - "id": "c7bee077", + "id": "8c85c181", "metadata": { "tags": [] }, @@ -850,22 +850,22 @@ "name": "stdout", "output_type": "stream", "text": [ - "Key: 1: 3907\n", - "Key: 2: 2358\n", - "Key: 3: 2044\n", - "Key: 4: 5157\n", - "Key: 5: 5080\n", - "Key: 6: 4624\n", - "Key: 7: 7405\n", - "Key: 8: 1386\n", - "Key: 9: 2344\n", - "Key: 10: 561\n", - "Key: 11: 1397\n", - "Key: 12: 748\n", - "Key: 13: 3929\n", - "Key: 14: 3588\n", - "Key: 15: 6981\n", - "Key: 16: 7987\n" + "Key: 1: 1347\n", + "Key: 2: 1583\n", + "Key: 3: 8568\n", + "Key: 4: 3034\n", + "Key: 5: 1960\n", + "Key: 6: 3311\n", + "Key: 7: 3971\n", + "Key: 8: 1407\n", + "Key: 9: 1135\n", + "Key: 10: 7466\n", + "Key: 11: 6494\n", + "Key: 12: 1813\n", + "Key: 13: 3596\n", + "Key: 14: 3260\n", + "Key: 15: 2825\n", + "Key: 16: 6030\n" ] }, { @@ -880,7 +880,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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mWAPCtUwKn7FqYti0C570IVkutY56gRv71GPc9b7JYlO+ab2/jRhOyIh6165dUQCe87gjgtggdKz5jbGgp1ys9Xs9YiIS1yR+yShAMLvbh2S5ph/tdaVbWgzY9i4Z0673UALubh1Qoiaib9hjvC8Q0TcVNn8G8hlYVWBC8lH9xaVvGI+c7KJ+XyTid4go6Gctn/jAcXfbs9SZMurrCre0usNR0qG53jf5TKBlIQ0YUdsLev8lgCUA5gPYQkQubfLvP5AqAJJXjsf10uCSNw3HYo/oygskSFZvjOEKkyPSVsYZJ7kZOMPJkq3TcXitwtVvzfW+i2/724ChBIyoAaQD+JSZ+5jZCqAAgKslUT67avXrkbPnHC3Q6QbUzyRCiKzQ3Vj7qrGg6obQ5tH81m0TiHTrkraCQG59sUiWqmuOXlNyoIMBSXO97+JhU75phr+NuEkgifo8gNVEFEdEEQDuB+Ba7DLwPBFPSky8snbZ8t9HLFi490hUVLPq4aBWkuZ8oD+X/q7h9OFBWNQ9/+wCOsEwZ2nCFreqfIxW5lbJlpbmeo+ICGCHv424ScCImpnLAfwbgI8BfAigCIDTfeP9B1JnQq49DQAgQti4ce2rshd8OGfZ8j0lkyZVHIeabjNBaBI61/zWeHjgvHjd7Xmuu0yLTF8x3pCoOBMpWxsdR34pWP0uMFGX0rHHCE+Y8k0+zSHviIARNQAw80vMvIiZ1wBoBzDq/qqdx+GgZI5eb85KnXVq+arVrzfPnnPkkF4/MPrWjhJbCYkn9JeXv24sPN1JfTVq9esMIjKsT95mJpDCQBnLbEdlbl1dKNNc71EZB+Bz/jYCCDBRE9FE+7/TIM+nX3eh2Zed98vJiYlX1y1d9vvIBQv3HomOblItwKSPzDm/NxyPL9CV+WwhTS8Y5+XEf0apG66TLDUjl7klwaXPQU84StqjNNd7FB7xtwFAgIkawB+JqAzAewC2M3PHaBfvP5C6HMBMVzu/6ZrPz/4ofdnyPSWTJper45oTwi/r6tfmGwuu1gqtaqclGpEZ47KWRuvjFdXMkiyXOkZ63tU7dUGm5no7YXMg1OIKKFEz82pmnsfM85l5vwtNlKY2uoVeb85KTT29fNXq15vnzC0s0Ov7nZ47doaNpLQP9UWZ7xhOFXp7IY2IwjYmP9oNwOXEDzZrTbijzpy1ZUB6b6kQ8Gmh/Iw+yib5vbJHQIlaCfsPpBKAhzzth4iTJ06sXrt02R+iFi5872h0dKNnrjmBmoWu1b8xHjaXiNeOeWrfaBjEsKyFEza57oZLI5e5ZRdWynrCUNoeJU+PNO7EIHHVpt6+gjfqGi4fu1671d/26PxtgAcsBqCoZtRoEMEYOa5j5fzsj2G16s9fv5bVXVc3dzEguPceERJO6isTSnXXz+SaF8bHcuR0tWwdyqzohTmXu85c77a2T3Ph8jjJ1lotiHEpQ590ZUurwEQ+38ILZIySdHldX/+NZzq7pqSbLakAbn5hpmBXTAx2dbr0fhHRVACvAkgEwAB+ycw/88S2oL1TA8j1Vsc6nSVzZuqZ5atWv94yZ27hIb2+3+0Klf1kXvQHw4nEg/rzBTZIbsdvO4KIIjZMeqwV8gfCKZL58gghr6OLWnO9ZcIk6eL9Pb0Ff6itv3L6Wm3aT5pb19oFPRQ9lH02rQB2MPM8AMsAbCcij7LJBO2d+st4c30s2k8uw9GBTfhoZiIap6g9BhEnTZxYnZSQUD3Y1xd7tLJyyfiuzkTlbzghrEpsXFstNFdttJh6pknx89W0M0yMWJA1fm1hSXvBamfX2ixXJF34smH2jf7dbne9VbU5WAiXpIpNvX0Nz3R2paRarHMAzHGh2Wfh2s4NmLkeclJNMHM3EZVDztpT5q7NQSnqpINFE0DiyjbECx/gAXyAB6Bnc9VclNVuxMcxC3A6QwfbqCeTlEAEY2Rkx8r582+55l03bsxdzCwoGsNGUurH+mKO46jC+8zZmWEwOM9K4iJzY5ZmV3UX1fVaO0dO42SHbS13VZpgJ6o+bKIOD80LKiIkqeze3r7mpzu7UmZYrHOhPG+8W8cxiSgFcmkoj04HErMq9cZ9StLBoocAvOnwAubuBDRdWIFCywbsmxUPZfWaXYGZGluap5VXXcnJsJgjlO/dMlpyrDMrsm0zVqllU7+15/S7NT/PcXKZZIx5vpuEsJibTxjMXWdXHfvOwpHNhPTcdrG5LZoS1bIzEImUpAube/panu7sSp1mtarh9WVgV6fLd1siGgf5vMO/MPNbngwclHdqDAkLHRGiqGYkLnsHX8I7+BIMPHgpA6X1G/HR+PkoyhAgiZ4aQMSJCROvJcYnXDP39cUcrapcMr6zM8l115wQf1p/ZdV5Xc25+80LYyfwOI8PBITrxuVkxK48cqHj6GhfFIJkra4UDXMX3XxitH3qnjCUtkWHoOvNzFESn7+/t7ftyc6uWVOstgyVR1gHF11oItJDrsj6mqeCBoJX1GuUXGwm4+xzyJl9DjkAc2ci6stWo0Bah09mj0eHRxFSRDBERnauzJq/D1ar/kLNdVNnXV26y675AFkWvGX4dHCGNPHQOkvGchGCRxUgMmJXmq50lzT027odFnSzmSt7RMNQj9Kx+12YGUKuN7MULUnnt/T0tT/Z2TU72WYzeXG01QD+x9lF9iy5LwEoZ2ZV6nUFnfuddLAoAkA31Fi5Z+YwDFSYUNy0CR/Gz8P5dAHscb/MaGppmV5+pSon3WyOcHlvV2C6utFi6pwuJWR7Mn6vtevk3ppfLHF4AUWcDYt99pa7rbP0FK85+nd33Y0Z4Oe3i42t0RQ0FR/vglmKlaTSz/X0dj7e2T0n0Wbz1TTiGnaNnpwCAIhoFYBCyNlybwYS/T0zf+DuwMEo6iXwcCHBEcRS6yTUVazGQVqLA3Oj0e1RyB8zzP19MacrqxbHdHYku+zejZfGHb3fvGBuOAxuF3Evbjt4rKLzpKPCB13G2G+NI5Lv0DpLb8mao9/OGn5RTxhKnv6W7q7nAx5m23hJKnmgu7fn8a6uuQk2yV/x6pOwq9Pn6aeD0f322vyOSYirw9SVv8Pj+B1/WQpH3/lsnG3dhI8S56B8Djk4DeYIIhgiIjtXZGV9IrvmNZkddbXpi5lFw2jt2oWela8ZC9sW2GYULrTOWEVuZAbMGr9ubnXPheYBW+9IH+hotjVcJl1y2i1LR6Awg9qVjus3mK1xNqn4Cz09fY91dqfHSdICf5sEed/5bV8PGoyi9s2dg0joR2TmcazGcawGsdQ8FdcvrcV+YTUK5kWiN8Z5J7fR6SwZM2acQ0rKuebWlmkXqqoWp5vNEY5dQcKEc7qrq8vEmuL7zQvHxXHUiCGejs2nCRuSHz3+Qe0vR7xL2cyV9YJd1Ex3z6kZ4HeXCrOVjOlzmC3xNqnki909fY92dWeMl6RFzhv5lCxoonYJv6zEMgkJ15GS8Bs8g9/w09ZI9JQswqn2TfhoUioq01zthwgJ8QnX18XFX7f090cfq6pcEt3RkZzp6PpBss5/23DSPF2KL1hvyVyqgxjm6lhR+vHLZ0UtPFHZfXbZ8Nck61VRXsuxWzWM3jCcb40hby4kuQezeaLNVvxQd8/gtq6ezJjAE/JQ/HL2PBhF7f8PGpGuF1FZh7EBh7EBAtvqp+Nq5Xp8YliBwoxwDDjNPU4EfURE1wpT1iewWnVlNTWZ7XW180Z2zQmGa2LL2leFgmvrLBktM6VElz/IC+M2pl7vLW8zS/13rA+wrW3oXuxdoi7MIPVzvbkL82CSzVb8cFeP5eHu7swYiRf72yQX8Yuog2qhLOlg0TQADhPoBQTM5mh0XcjBp12b8NGU6ah22W1mRnNr69QLVZWL55rNkQ5XnGOliKP3mxfOjoDRpQWgTnPLsQ/rXrpr0cwY87UWEiLjBdvgxXWFf30r/JEBfv55saE1hlQP2nEZ5oFJVlvx1u5u20NdPZlRzKqlf/YmNqbGLkTW13BCd5GUav5H69P3Vufl+rQuerDdqQN/JZbI0IWYBQdwLw7gXghsrU1F5ZUN2Be+FMczjBh0mMeKCAnx8TXr4uJqZNe8anF0R/uku1zzDqFv5evGIx3zbdMLc6ypThfSYgzxK2aMM5282lN6xzaXzXLlis5oih/ufvcaUdoaQ75/r5n7p1itxdu6eviL3T2mSOalPrfBBSRGRy/C625wXEcFT7UWS7P0xdLMCRU8bUovwhMhn7i6yWQAPkt3BQSfqFP8bYBSJNJNuYy5Uy5jLv6Xvz4Qi/YzS3G8dxM+nD4JN0Y8jnnLNTfth82mK6+pyWirrcnIYRZvB6YQYot111aXi3Wl95kXhCVw9Kjz+pz4zdNq+y51WqTBWwt8krmyH0aT3NsQCjN9uOrN3DvNai15pKsbX+juzYpgvmv+7w+Y0TcAQ20jj2+7zJMHSqSZ+iKeFXNBSpnUhugJcL0I40y4IGoiehnAFgBNzOxwjcUVgk3UwV0LmSisAxMWfYRcfIRc6NhSnYaL1zdgX+RinMjUw3pXNJkoWtNTUooxfXpxS2vr1BNVlYvnDHXNzWQ1vWM4ZZkqxR3aaDEt1UEcMbuJQELS+qRtRz6+8cqtENLbZW5vr377ZNWbuSfFYi15rKtbeKCnd34Y83KvjufQDFgs0NW2ILr5qpTcX8IzhSJpVtR5KSWxDvFJAKnxPsyEHNPtjFcA/Dfks9UeoYnaj1hJn1KOzJRyZALMfRPQemo5jgxsxMczhh8lJUJ8fHzN2ri4Gmt/f9TxK1WLI9vbJ8suMkFfI7auyxcKatZa5jXOkpJGPNQx3pi4alpk+unrveXy6zyQxmyzMN2OzuszemnVm7kr1WI5/1hXt+6zPb1ZRoajwBiVhwXbINzowLima5zYfV5KQZE0K7yUZ0y8ysmTbRBnAPBmIn6XovGY+bD9lJbHaKIOFIgi2hC/+H18Hu/j8w6PkhJBFxHRvTzTdOCma95aW5OxmFk0MvHUQ4YLU89KV47nmhfOjETYXfvgSxO2JN/oq+q2sjkKQLhkvVEmiMm35vmqrnozd6ZZLKVf7uw25vb0ZhngPSFLTC3diKiv5fjOcp5uLZZSw4qlmXGXeMqUARgnQ57b+gOfp4DSRB2gWMiQWors1FJk3zxKenYlDls2YN+sOLQmAXe65m2tU05UVS2ZPTgYmdwl9C9/w3i002SbdniJddYqGuJeCyRMXpv08OH99b9dAwCS5XIzxOQUwO56L/PM9Sbmjtlmy/nHu7qMm3v65hsA1Y6WMqOrF2F1DTyh/RJPsRRLqfoiKTW2jKdP7kZkPALz8+HzEFVN1MGAfJR06Z/wEP6Eh+4+SkpSfFx87doJcbXWgf6o41V217xUd31NhVh34T7zAt1Ejrm1ZRVnnLR6ckTaubq+ywskS7UBYWtFQHa9W9xwvYm5Ld1sLnuiszvsnt6++XoPhMyMgUHoa5s5trWSJw2U8EyxSJoVdUGaPqkJExKgYmVTH6FaIgxX0UQdhAw7StqRhPry1TgkraP9s2MjOm665hW1NfNaamozct41nNZNliYUbLKYcvTQRRIRrZj4QNxb137Wa5PL3EoAcGSe6643MbdkDJrLn+zqjtzY25elUyBkZtisEOvaENV0lZP7zkszUCSljivlGYnXeWIyQ5gFwKWKp0FArK8HDLbgk34ALodJjjlGOEpKzO1tbZNLqyqXzDYPRPFq69y62bZJSwCgqf/64YMNb6wJG/flkvVHd5m+/pxY3xxLkxx1T8zNWYPm8ic7u6LX9/WbRLkwnENsLDR0IrLhOk/sLpOmS0WcGl4ipSZU8aTJFuhGPdQSQlyozst1ukVFRG9ATqwQD6ARwPeY+SV3BgyaO7X9HLUm6NEgogGEp5/CsvRTWCYfJaXai2viDhrWTPhErx/gqvNVi8PPtcw6kWteND0hbOqqpPAZJW3mS819Rpxvjr3b9RaYG7MHByue6uiOXdPfbxKGJaiQGO09CK+7wfEdFTzVViTNMhRLqXEXeerkPoQlwcXV3xDGpc8sM29Ta8CguVMnHSwaBzk5goY7MEsR6LswH2fbVliOcPwNsy3m6mZh4WDa1L3X37xixWHjS5vFtQAgMNcvHBi8/HRnV+zK/oFMYvT3w1jbyOPbLvFkc4mUqiviWTFl0rTJ7Yj2+ZwxyKiuzsv1ae1qp6ImorkAHsDtLYE6AO/aS8/6jKSDRQYAg74cM5QhlpomcV3FgpbGtnvP9lpfTvxlWliEvvmeDr0lo9cYfoFniMVyIEbSDcSP9butJ9RU5+W6UmhBNUYVNRH9HYBtAH4HoNb+9BTINax+x8x5XrdwCEkHi4LDrQgiqM9aO63s8NlHzpTAwi0rENwFHgIOBtX/7Z73PAr7VIqzOfUzADKY2TL0SSL6dwAXAPhU1AAskCsgaHiKjfv1pW0nhcaBJQvGHxRTWvuN1ybnXrT078+AH1ZsQxUC+7xSqLNvZQnASKuhyVBQbVFFVC9bMxYRr/ccN+6/0SY2DqwVIRkSwy8arsXd0M9srJcM0U91A3qfTq1CHJuvB3R2p/4mgP1EdBm3T5pMg7yH+HUv2uUIM4BIP4wbElCXudJwurWbLNKtAxSbhVPFNwxsOG8Sku75zXtzGhKXnKTY5+abu98sZFuD0zI+Gk7xvP65QkYVNTN/SESzASzBnQtlp5jZ599A0O7U7mGROg3nWoup3byChv3Nn9e90/vXOl1Y/WTMZqA958yPZhxd8cMuY/Qjq639nx6xDhxdCMDhGXANp/g8g4zTRRFmlpj5BDP/0f444SdBA5qolcEs6S53FhoP1FuFdvOa4YLWw2rOoOqsNlGIAxE1xuKi0dKdMPfi61cBQBe+dJUh6pE6QLjqn18gJHC7Yqq7BNtKZ5+/DQgWhJaBUuP++ou6Kz2rCRgxf/gXxcPnQIgeJJoMACdnkxkAJjUcXxLVff0IAAi6pDRj7HNxJMSc8J31IYUmaic0+NuAgGfA1mg42nhUf6Y1k2w8auK7r4rv2xpFsRFE4QBQYBKm3nxtQdFPs0myXgcAImO0MeaZZaJxfgH8MEcMckJL1ET0MhE1EdH5Ic9NIKJ9RHTZ/q+SiKRa55eMUSQ26863FxgLGiKEHutKZ4UHIjDQO4Pqsy8a9E03n6uZSDNsJNdK1tkGx2WV7u7EkKmWPmLjWv24L5QB5POqE0FMaIkacoqWzcOe2wlgPzOnAdhv/9lV6lSyK6QQbvSdNn5yo05X17eWgChX2jwq7i8mQkSZ0XDHPmpdHK7c/H9ce7kpvrX0yNDXRf2MLGPMV3Wg8LPqWB/yNDm/RF28KmpmPoy7V/8eAJBv/38+gM8r6NKnWRkDHeqxXDMWNJw0lLbnECtLyfOk7kMdAJQbDHe408fThTui9jIv/GqFaBu8Y9+ahMgEY8yz2YI+9RAALcpvdELuTj0Sicx8031rwJ3pVJ1Rrb45QYhV6tWfbS0wHG1KogGb4+qWDohBT8cktGYDwFW9/o5kh4WZdMeXg8CSfuHZFw1gHhj6PBEJhnEPrNNHfOY0gA7Fv8PYodLXA/p1oYzlwHMl3/SXvWVLsCBe7T5m3F/fJTYPrCXArVrWX9F9UEoEAwA06cQ7aoI1xdJkq3BnwYSo3rrUKXUFI1YaFY0Ziw3RT/VoUWgj0g/A59uB/hB1I5Fc+cH+r5I5x1X4IewuEKAO80Xj/hsl+ktdK0gO03WbR8T9t8oC9dPdSRGuJuL68OfSKn+/xmDuOjNSf4I4foox9rmZJCYd9sSuEKRix569Pg+n9oeo3wXwhP3/TwB4x9WGDeuzzcDdH7iQxmxrM5xoKjR82pxGVva4akYS2honoHs+AHQIQgcTxQ6/5ug84a5IQwIo58yPJoG5Y6R+iXRGY/Qja3RhK49Ciye4SZk/BvX2ltYbAI4DmENEtUT0DOSTXffY48k3QflJL7+8UT6H2aar6DxsPNggCJ2W1aTS3+o53bsVZM/zfdmgvzHSNUczKI1HmBaFDbYnz6r646jvvy586UpD1KNaFJrMBX8M6u3V723MnMzMemaewswvMXMrM29k5jRm3sTMSmNjj3nF2ABCaOovMn5SX6W71rOGVD4G+aBYeCt5Y7nB0DHSNZ2RFG/WjbzAM6324IqI3vqjo40h6BLTjLHPxZMQc9wjY4Of0LtTe4lRP1BBTb+13lDYeMxwri2bJFa99E0K1ddEUX/GzZ/LjAaHsfSXJ9OId3EAWHTuxUywzeHrAEBkjDLGPLPcHoVmGe3aECb07tRe4iRC7UNi40F9SVuB8XBjjNBn9VoVi7/S/alq6M+Ver3DU3qHM8jhySy9tT8m88JLjXAhwZ0chfZgxRiMQmvesWevz7ezgCAUdcP67H4A5/xth1qINb0njftvNIr1/WvJy0cc7xc+vaP0TL1OdBh99ukcmsOj7DRMbCleML7jkkur3aI+xWSM+ap+jEWhHfLXwEEnajtB74JTt+WK8WD9aX1ZxxJieD0xXQZdrQwn8x3lbnsEwWHgT38YRfcbUDFan1ml/7NUsJlduhuREBkvR6HNOoSxEYV2yF8Da6L2NRapS3+6pcBwrGkqmaURq1N6g2/o3rrjMEw/UZ/kJJqvbBq1jPa6KFnDFhT/pw3MLp1zl6PQPrdOH7H5NADf1cD2D4f8NbAmal/BzGJl1xHjgfpBsXVwLfk4geJ6oeiO8M8ren0diEY9yVVgIqeHQ2K6rs5JavhU0Sq3aJy32BD9dC+gD9XtyaYde/b67XcLSlE3rM9uAG6fJgp0qG2wzHigvkxf1b2K/FAFcZlw4YKebNOHPldu0DvdSjw7i+axC7nW0y/+drXO0luixCZBjJ1ijH0ulcTkUIxCO+TPwYNS1Hb2+tsApwzamg3Hmo4YTrWkk5UznDfwDi+Ib9/lRpcZDQMjXTsUi47CusOd77USWMg5++PxYFZUQUWOQtu2Rhe+KtSi0A76c/BgFvUefxvgEImturKOAuOhBoPQbVnlLGGBNyFI0lKhfM7w5y8ZDC7ZVDyDXMpbHdHfPHVG9QfFSu0DAF3YklCKQmPIodB+I5hFfRwBeL5aaOg/a9x/45qupnctATHOW3iXTcLZEpH4rrI5dTqdS6mWC0w0Yn6zkZhx7YNVYf0tbuUyux2FFhvsUWgnduzZO2pgjrcJWlE3rM9mAG/6246bUK+1xnC44YShuG0hSUj1tz032a57Z0SXuEMUXJrbn0+huaygMGHO2R+ngSW3EgPIUWhPLxeN2cEchfZHVy4aKdWX/fm/IqIKIrpARD9yx4CgFbUd/7vgNu7Xn2stMBxpTBD6bcv8bc5QdLBasqjqrjpOVsBqHbnyyl1IAunaokbfrx6KwdITl17x22oFZt6FPmJDsEahMYDfu3jtKxiW6ouI1kPODDSfmTMA/MQdI4Ja1A3rs0/Bj6vg4jV7+ZqmgbUUgLWzHxCOFQmEuxI71uh1dSByuTb5mVmkaBErufHTxdFdVz1a1b4dhRYRTFFoR3bs2evS0WAHqb6eA5DHzIP2a9zKbxbUorbjcxecOs2XjQfqz+krOpcTY7LzFv7ha7r3RgwKKTcYRg0qGU6BSVCclGFB0X8uIslarbTdUOQotK9lC/pZBQiOKLTXPGw/G8BqIvqUiAqIaLE7nYSCqH3ngpulDsPJ5sOGE80zySIt8Nm4bhCGwf40qps/0mtlRkOvkr4uT0KapLB8jCiZI+eX/LwXHlZzsUehrdVH3HcGgR2F1g/XXW9H6ABMALAMwN8CeJOcBAiNRNCLumF9dhGAIq8OwizpLnUWGg/W2+zla0SvjqcC28QDRUQYN9JrFw0GZXc9ImqKxUWlNkzouJSR0FJ0xPmVzhGN6TkBHoX22o49ez2tm1UL4C2WOQm5smy8kzZ3EfSituPWgoIr3Cpfc9Vx+ZpA5GnxQ4d/22t6XbjS/j6dQ25V5sgoe3mlaB1QRYhyFNrzswI0Cu1nKvTxJwDrAcBemNIAQNFUCQgdUe+B2rnLBqwNhiONxwxnWk3OytcEGlHo7ZxCzdmOXm8ThAlK+ywwCVPcsUVgSbfo3IvhYFYlYoxINMhRaKuPAlA0jfAiB3bs2Xve+WW3cZDq62UAM+3bXL8D8AS7cGZ9OCEh6ob12VYAP1Wls1vlaxrHCb3eS1jgTZ4SPyolGjl9MAN8syCeEmoTbpfkUcq43hszptYeOO1OW0fowhavNEQ9Wg+IgRCFpvgu7SDVl5mZH2PmTGZeyMwH3DEmJERt51fwMKm8cKPvlPGTGzfs5WtGnI8GA4/p9jl0rxuGFMRTSl28+9uHaVVvrTEMdqgqbEGXOMsY+6y/o9CuIMDOIYSMqBvWZ/cA+IU7banHUm08VH/KUNq+mBgp6lrmW+LR0ZyAzmxHr18y6Bvd7fvYsJI8Ssk58+OpYFZ1BXtIFNph+CcK7b/8kdt7NEJG1Hb+Ey4cFbyFVerRn2kpMBxtmkSDklt7goHGs7q95USOV+fLjAZFJ6mGUphBM91tCwBh5o7E2ZVvuhydpgR9xIY1+nFf9HUUWgNkDzGgCClR289Z/9aVa8Wr3UeN++t7xJbBtSSvMoYED4mHYkd7fXhBPCU0x9Iki+BZPbMpdYeXR/bUeSXJhaif7usotB/s2LM3UBbrbhFSoraTh1HcMGofrLCXr1lJwF2nl4KZqdRUF40+02jXDC+Ip5TqJM9Pxi069+8mkmxeqTU+JArtELwbhVaFALxLAyEo6ob12ZUA/ueuFwZtrYYTTYWGky2z1ShfE4h8XfxTJdHoZ7eHF8RTypERSvIoRWcbiM688KsWMHtlLno7F9p9Z6AwEk4B/7Bjz96APEkWcqK2833cDClktukqOgqMhxpENcvXBCKfFY87LQs8UkE8JRydR7NHKsmjlITW0uwJ7eWFnvYzGnIU2jP9XohCO4tAOCHogJD8gDesz24D8E/28jVXdNd616pdvibQmEPXr0bQ4NzRrnFUEE8JXZEUZ9apU1I4q3T3csFmvqRGX44QxJjJchTaJDWj0Hbu2LM3YA+YhKSoAUBX2fXfhnNtepI4zfnVwc8LurevObvGUUE8pVyarM4Ks8A2w8KinxLsRw29hRyF9hdqRaG9v2PP3n1q2OUtQlbUtX+5xgZgu7/t8BX3CGemO7vGUUE8pRzOdFySRynR3dfSkuuPuZUCSSlyFNpjDYDobhBNN+QzzwFNyIoaAKrzcgvg+RnXgCeHLpYbyDrD2XUXjAZVFnZOzqG5DLi9NTacuZfeWK239BSp1d9oCLqJqcbY5yaSMN6d6qnf2bFnb8DlxRtOSIvazg64cdIlmHhB95ZLGTKq9HpVjoz2Gymqz+h6iiNnEFjIOfPjeDC7lLnU4/HIMM4Y89QKhbnQjmCkXZUAJORFXZ2X2wjgK/62w3swrxAuuLRuMFpBPKWUTaNWtfoCgPCBlikzr75XqmafzpBzoX3xogtRaIMAvhLIi2NDCXlRA0B1Xu47AP7X33Z4g/VCUYmOJJe2qXoEQbVgmwITRavV101Srn+0Mry/2aeHM0T99ExjzNcMoIgzo1z2gx179ipOEuEvxoSo7fw1oJ7LGCh8XfenTleu6yfqk4ic7mO7yrlUSmfAaZUPpSw6++M5YMntQyfuQEJEnDHmawsEfdoh3L0HfxKAW6l6/cWYEXV1Xm4fgEcAuFShMRgQYbMuoMp5rlx7Ra+vU3Nsi47CuiJQrmafAGCw9E6YV57v88UoOQrts8Oj0DoAbA3UyDFHjBlRA0B1Xu45AP/gbzvU4n7h0yKB2KUcVuVGvepJ+1wtyaOUpKbTOTGdVX5JWXQ7Cs1wHsBTO/bsrfaHHZ4wpkRt5ycAAjp4wFWe173rsvt7wWDoV3t8JSV5lJJd/N85JFn8ktXEHoX25x179v7JH+N7ypgTdXVeLgN4GEE+vzbCPDCXrrt8MOWyiwXxlHBhurKSPEoQJXNEdvHP+8Gs2n64Ag4SCd/xw7iqMOZEDQDVebkdAHIBuFXzKRB4SCwoIoLLK9C1Op3q6ZmUluRRyvjOy/MmNp9VJcWwAmoAbN2+e4NH+cr9yZgUNQBU5+VeAfB5KMmUEkB8RfxA0Z5ppygozh/tCqcVluRRSkbZ/60Wrf0XvDnGENoBbN6+e0PQftkDY1jUAFCdl3sMwFMIjpIut4hEf/d0anS5QoiSgnhKcackjxIILOac/UkkmL2dYaQfwGe3794QqMUCXGZMixoAqvNy3wDwPX/boYTHxY9LiFwvyKe0IJ4SKuWSPKpGlw0nsq8hZVrNPm+mKLIB2LZ99wavpFnyNWNe1ABQnZf7AwC/9rcdrvKE7mNFOdWUFsRTBBE1jodXz0QDwKwr76w2Dnac8lL3z2/fveEdL/XtczRR3+arCNCcU0MZj662RLRnK2mjtCCeUk66WZJHKTlnfjQdLKntFXxv++4Nv1S5T7+iidqOfavrawjwkzhf1b1/ngh6JW0UF8RTSEGmMNWb/d/EaO6cOOfSHlWyrtjZtX33hu+r2F9AoIl6CNV5uVydl7sdcv7wgOQvxIOKD1K4UxBPCbUJlGIjqJJVxRmT648sG9ddq8Y213e3797wTyr0E3Booh6B6rzcbwB40d92DGcSWupj0aM4E6o7BfGUUhsPn0V/LSz69/kepBhmAN/cvnvDD9W0KZDQRO2A6rzcvwHwr/62YyjP6965RKTsb+ZuQTyleFqSRwk622BU1vndbW6kGLYCeHL77g1qlJ0NWDRRj0J1Xu7fA/g65C0Pv/N58WiC0jaeFMRTQmEmpXp7jKHEtZVlxbVdUJJiuBvA57fv3vCqswuJ6GUiarKXlL353C4iqiOiIvvjfnfs9gWaqJ1QnZf7c8ghpS6dW/YWqVR3bRwNuHTMciieFMRTQksMJVtE37ngAGA6/8vlgm3QleQFlQCWbd+94X0Xu34FwOYRnv8PZs62Pz5w1U5fo4naBarzcj8CsALyh8MvvKB72y3BeFIQTylXE+GVUjqOENhmWHTuP0QnKYb3AViiJFKMmQ/De5U9vI4mahepzsstA7AYgKvf9qryGeGUW9tGZQaDz6YORzIERVttahDVUzNr8o1CRymGfwrgvu27N6h1lvzrRFRid8/Hq9Sn6miiVoD9dNdnIZf18VlN4vlUeSmMLG7NWa8a9D4T2rF0SlOjJI9SZl/es0Zv7j435Kk+AE9t373hWyqetvoFgFQA2QDqEYC7IzcZM6J2sPjxEBFdICKJiHJc6ce+l/09AGsgVz70Oi/o3nZ7D7hZFGNVNGVUuiIpblCvTkkeJRBAOWd/lAjmTgBnACzcvnvDK2qOwcyNzGxjecX9VwCWqNm/mowZUWPkxY/zAB4EoDh1TnVe7lEA8yFHoHn17rRGKJnlbts+H2xnDUWtkjxKCR9oS5x9ec8PASzfvnuD6pk/iWjoabQvQP7sBCReObkTiDDzYSJKGfZcOQAQuZcUpDovtxfA9pSd7/8JwMsApnhm5d2sEkpL9WQbtea0IzoEoR0+nvsdzqSIrGqfe+CXADxxz4FfnrhHhc6I6A0A6wDEE1Et5FN864goG/IXeDXkkOKAZCzdqb1GdV7uPgAmAL9Ru++/0r3t9irsZYPe53fNU7PVLcnjBCvkuW12ekW5avW4mHkbMyczs56ZpzDzS8z8ZWY2MXMWM3+Omf3ikbiCJmqVqM7L7ajOy30cwD0AStToU4Bky6GLivemb1KmUkE8JahdkmcUPgBgSq8o/5v0inLVkyoGM5qoVaY6L/cTAAsAPAN5ldRt7hVOFYvEiqPIblJmNPglx/kFlUvyDKMcwH3pFeW56RXlQZ080ltoovYC1Xm5UnVe7ssA0iBvf7mVx2u77h2PzkFX6fV+WTPxRkkeyMEgLwDISq8o/9AL/YcMxBxU6bncZujiB4BGyIsfbQD+C0AC5GoMRcz8GbXHTtn5/mQA/wzgywBcqjyph9V8yfh4PxFi3B135bTJJV2iqPhUl6forDz42o9tTHA95dIo9ADYDeCH6RXlqhckCEXGjKgDgZSd708H8A3IVThHrUD5sHjw5I/0v/JoL3R+ytRGNetnKeFXP7OejenDQg+6aIf8hfuz9IryoA3Z9Aea++1DqvNyr1Xn5f41gKkA/hZyjukR+Zq416MVZLUL4imlaCa5G3N+BcA3AUxPryj/niZo5Wii9gPVebmd1Xm5PwEwE8CjAO7IlBmBgd6ZVJ/tyRhqF8RTSoGJlOQZlwAcgBwIlJZeUf6z9Ipynx1ECTXGTPBJIFKdl2sF8DqA11N2vp8Nec79yKPi/itEWOFJ394oiKeEsmk0l4EuwqhVRIoAvAbgjfSKcr9+CYUSmqgDhOq83CIARSk73//2JvHMWgDbIFcQcauyhjcK4ilBEkhsjcLF+G4sHvZSNeQvstfSK8qDPnF+IKItlAUyu2JEyCv2DwLYBGC2q00fS048XBxmXOMly1zi6Y9sBZvP8mrIhyw+AvBnAMfTK8rd+tAR0csAtgBoYubMYa/tgFzRNIGZvZfnPAjQRB1M7IqZDGADgPUAVmIUka+bOvlsq070ZPXZXSTIhx0Oz6znT/JesR1JryhXJRiFiNZA3uJ6daioiWgq5GIMcwEs0kStiTp42RUTB2AZgOWQY8/nQD7zq1uQMvW6lWialy1ogRzhVWF/lAH4tPSJUq/N5+2HcvYOE/UfAPwAwDsAcsa6qLU5dTCzq7MVciaW29lYdsXoAcwUZHGnAJhuf0wCEAkgYtgjHMDwY2oDAHoh52VrHfKox20BV5Q+UerVGlquQEQPAKhj5mJ3T9uFGtqdWgOmfFM4ZHFbAPSVPlEaENlTR2LonZqIIgAcBHAvM3cSUTW0O7Umao3gYpioTQD243Zs/RQANwAsYeYGP5nod7TgEz/jIM3Sj4mowp7k7m0iivWjiQELM5cy80RmTmHmFAC1ABaOZUEDmqgDgVdwd5qlfQAymTkLclaP7/jaqEDEfijnOIA5RFRLRM/426ZARHO/A4CRVnSHvPYFAF9i5kd9bthtG+7aHyaiHwB4APIWVhOAJ5nZJ0XyNEZHu1MHPk9DDtrwJ6/gbm/ix/bUPtkA9gL4R18bpTEymqgDGCL6LuQ8XK/5046RKlYwc9eQHyPhh3zfGiOj7VMHKET0JGSXdyMH6ByJiP4FwOOQ97PX+9kcDTvanToAIaLNAL4N4HPM7FYqJF/AzN9l5qmQPYmv+9seDRlN1H7GwYruf0POjLLPXjZ1t1+NdM5rAL7obyM0ZDT3288w87YRnn7J54YohIjSmPlmiZ0HAJ+kBdZwAU3UGk5xULHifiKaA3lL6xqAZ/1nocZQtH1qDY0QQ5tTa2iEGJqoNTRCDE3UGhohhiZqDY0QQxO1hkaIoYlaQyPE0EStoRFiaKLW0AgxNFFraIQYmqg1NEIMTdQaGiGGJmoNjRBDE7WGRoihiVpDI8TQRK2hEWJootbQCDH+PwONVZGdoDM7AAAAAElFTkSuQmCC\n", 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" ] @@ -902,7 +902,7 @@ { "cell_type": "code", "execution_count": 28, - "id": "a8a3cba9", + "id": "92991de2", "metadata": { "tags": [] }, @@ -911,22 +911,22 @@ "name": "stdout", "output_type": "stream", "text": [ - "Key: 1: 2292\n", - "Key: 2: 1617\n", - "Key: 3: 1958\n", + "Key: 1: 790\n", + "Key: 2: 59\n", + "Key: 3: 4330\n", "Key: 4: 0\n", - "Key: 5: 1463\n", - "Key: 6: 3972\n", - "Key: 7: 7160\n", - "Key: 8: 561\n", - "Key: 9: 3797\n", - "Key: 10: 3175\n", - "Key: 11: 5723\n", - "Key: 12: 773\n", - "Key: 13: 2487\n", - "Key: 14: 6576\n", - "Key: 15: 2338\n", - "Key: 16: 10320\n" + "Key: 5: 545\n", + "Key: 6: 348\n", + "Key: 7: 5245\n", + "Key: 8: 3558\n", + "Key: 9: 2565\n", + "Key: 10: 4163\n", + "Key: 11: 3654\n", + "Key: 12: 2868\n", + "Key: 13: 2130\n", + "Key: 14: 2360\n", + "Key: 15: 2390\n", + "Key: 16: 2101\n" ] }, { @@ -941,7 +941,7 @@ }, { "data": { - "image/png": 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b1zhv6NDDnyb/76CumYfE0yG3G87MturO4wF3DRVMWRulqJlez7QY3LVjWMHm9yasXsgUMG+36QBuDlDbfhNxpWxTN5QkAig3s7VmGf5mnYntIbfz3RfMaNuz+8uNVmvCCAAgRu13uheYzZAT9LbtAt2Kdf87VX8JaDIBElOLzfG3eO1cokKteW/86qaahBPBiO8+BGBS6dLSkKtwGokj9c8BJHaTJesp+tnUe/Hv3Scw9qjeRnkCEeKmTH2/k0ixAQATkj8w7QspT7Nz1vLAVhyh2F2muG95HUHXLXYeeGnab6UgCRoAJgBYEqS+vCKiRurUDSUpAE4CuHTNx8zpOL31J1g5IgXn/Y7oCTRNTalFB0uv/9Rr6jpb9r6RarJPa0ut2VDz6qHarsoJgWldPmxO/MEIIpNXa/ba2MridyY8NUsVFI/ztGvEUQATSpeWhlQyyUgbqX+CywUNAERUTcPn/gSrk/6A3xa1IS6k61slJp5bkJx8cteFnwvlgwMdULr6eyYYMHNLXVeVr/Wo3CCcNifckeSNoBlsLxmyvvit7CfmB1vQ0ap6eEVdQ0tJeZVXKYaJaBgRbSCiw65ECj/W2raIGalTN5RYAFQDcF8fmbllPjbuuwP/mmWGzeL2fh1gRsOunV+zdXfHpAHAMGVQ0eftOX75PPtLh715R0H1P/1y0+yDJlP8bc2CmOSx6yZDrfsg85mzVQMOBzVZYJyiHvhlQ6N9UUfnNNel/VjRkuPp80SUBiCNmfe6yvnsAXATMx9286jHRNJI/R14ImgAIEoopmty78ZLzW/im8UqhJCaPgEAEQZNmbr2PMAqAJwWGubWUouuewMBCrXskmO/etobQduErrL/Tvm9PZiCHqAoJU+er9u3tap60kWCBoDJWJHgcSQWM9cw817Xv9sAlAFwGyziDZEk6h95+4BKYtpbtGT+nXi5fCOuDbkMJLLcnZOZVez0LiNIH5j2KXoWAwhAqKUqWa7ZJ8qjJnn6QJPl3JY10381si2qcYjGtvRKksOx++lztaWbqs7kfK7T2te+xi98aZuIRgKYAmftc80IqqiJ6DkiqiWigxddG0hEHxPRcdd3r50FUjeU5ALI9tUuO5nGPEP3zvw+nt9/ENkhVdFw8ODKeQMHVu8HADsp47dKR3XJQqqyerbFXq9pqKVonlwsRU2Z48m9DFYOJ28pys95dK4i2gO7ZGLmIXbHzv/UnD9cePrs9LnWLnfvrVysSPDq7J6IYgG8CeABZm712dZeCPZI/Tx6Bo0vB7CemcfCWQvalwCM+/20CwDQQXGTH6UVEx/E6u2nMaxcizb9hQji+AkbkyWpqxEAjohnZrRQZ9C9zVpsdZpWtRSk9CI5+nMe7REwuPmTsWtKNmW8Ftg9BWZ1hN2+7b9nzx9fV3125vSubm+Ox+729EYikuEU9MvM/JbXdrprP9gbZa4pRwEzT3T9fBRALjPXuDYRNjLzOE/bS91QMhzAKWgduMHsGINjWx/A45kD0KR7naiuruidu3bePBMALGzac2v3/GnuntGSkobCrUdbd2mSgZWEhO2m+DtnEpHbQcVB9hNvTH5MbrbUBs5DkFkZY7dvf7SuITXTZs/wsZV6AEOxoqXfRBeuvORrADQy8wM+9tUvobCmTmHmC8EL5+CsB+wNyxCISCwi6QSNW3Afnol5Ej8rssKia3LAqKjOmRkZOzcBgJVs00rEii3B6puZubLjsDZBEWQuNcUvzfFE0K3mhu1rZvwyNWCCZrZndduK3z1TU/32mXNz/RA0AAwGcJMH980FcBuAa4moxPWlaYE+ScvG/IWZmYi8nTp8OyDGXIAoZhdmL9zNM+s+j7V7v40Xr5agBKRMjzvShhydXVc3sqy1NTlrt3Qya5wypN4CU8DzbivsON6ldFzlf0tCuTn+jqFEUr9ZaBjMJwft2/TJ2DULQNrWOHN2wN053bYdj9bVZ6Q7FC0L490G4LX+u+bN0Lhu2+WEwkh93jXtvnCGV+vpg6kbSmYDGBkguy6BSUj6kG5ceCdePvshFm1jHfI5E8GUPenjaFG0t4EwcK1pz7Fg9FvfXa1FGGidKf67IgnR/R47MritaHT+zk+uWrNQc0Ezd86ydhV9cvps84s15xekOxRNj5IAfB4rEgZp3KbXhIKo3wWw1PXvpQD+58WzQfe9VUge8SLdOeduvFi2BzNKgt2/IKgjJud8cAAAmoXOq08I53YHus/yttJYP5voNMV+o04QBw7v7yaFHJVvTHq89kjKNm0dXJjbFnRaN26sOtP573O1C1MUJVBF8GSEgD94sI+0XgGwDcA4IqomorvgzPJ5PREdB3AdvMv6+fUAmOkRXRQ9/glannMfntl9EhnH3T+hHTExLXOHD9+/GQCK5MOpdjg6AtUXM9vO+BdqqUjRnz8oyMP63UnukFt2r5n+q8SGmDP+rGsvhbnl+o7OouKqM47V5+tyB6lqMEoEfSsIffRL2LqJpm4omQYg4KOURzCrw1C57Sf448hk1Go9peujS3Ts27v4fEfHgNFpyoBNi+xTfS3h2i/dSmfJO1V/zfH1edE8fZMcvaBf26oSy4rez/znfD/zh30KMTcs6ugsfai+cWocs095zfxAATAYK1qag9zvp4TC9NtXvqy3AZ9CJJymkXMfxN8HrcSvi9oR2xz4LhEzOecDOwmOrhqhad5ZofFQIPqpsZa3uL+rdwR51Mb+BM1g67bh/9vyftbT/iYEdPbHXHtza3vR9srqqEfrGnJ1EDTgPIm5QYd+PyWcRf0VvQ3oAVFUKeUs/AGex7/wwyIb5IBGVomiMm5S9ic7QRDWyftNKlS71n2Utx3wacpKwsAtcsxNfTqLqFDO/G/CUxX7hxb6nUdOYK75Tkvrpp2Vp+NXNDQujGbWu162pkdU3hKWonbFTQc1OscriBKL6HML78LLjW/hG5tVUMCyY8Qn1C1ISzu6XSF1bJFcttX9E57jDLU87X2oJVn2meJvm9FXAfguqWP/i9N+Yz4XX+5XWiSJ+fTdzS3FuypOD/pFY/MCM+tbsMHBwplSddTmh+x3+pT5VCvCck2duqHkJjiLxocFJu4+fif+2TwfRQHJQsmMlt27bmrrssYlfc026+xAjtXER7vd3rxjrdehluIJc8IPkkiI6jUFU03cqU3vjf/rHFVQfT7rl5nLf9Dccuau5tbZko6+FsxoO4tBZeuUGV35Su6wozz84r/7xIqViwKyJHJHSDmfeEHQCsZrgY3MY5/G/XiJby/5Mf4kj8chTTOHECFhytS1Vdu2fjN1rWlP63e6FzCh91HSG7wPtaRzpvjbo3sTNINte4d+tGPX8Pd93tAzq+rx+5ta6r7T2jZbAIJex4sZajssZVvVCXX5Su7ATeqkLAekmX3c/jk485gFnXAVtUeRPaFGO8XnPILfIYVrtuXh0SFDcUYz90dJsmePn1BUdPjQNQt3SyeLZzjG+O0pVd52oN9z5ctoM8V9q0UQE3r47atQa9/Pevp8deJRn2yyqOqRnzY2N3+jrX0WAUGsDALYWaw+zCPK31TmS/9T5ma1INbTD+R5AP4SSNv6IuxEnbqhRIYzRWvYcp7S5vycn7KPxdFND+DxrEQ0a1LtYuDA6vmDB1fu3V+HSeMd6edjEOWzk4XKSnWrvWGkh7c75JgvHROktB5BJjax69Brkx8d2G5u9jo0NkZVD/1fQ1PnV9o7gpY8nxmtZzC47ANlZne+kjviBKePgLPWtLcENeDmYsJuTZ26oWQmNA4q1xXm9lnYuvt7+Pt0C7r89dwCM+p27LgZUV0DTy2xzfXZM6ux+9zmj8+umefJvVLUnM2SZU6Pexuiz2x+M/uJGargMHvTd4Ki7P9NfaNyQ6c14OmdmaG0wVK2Wc2uz1dyB21Ws7MUiFoNdgMrVi4Kej68sBupEWbrabcQxe7A3NydPKfuS3h37xK8fLUI1ef/FyIkTZ26ds+O7V+fWSZWb89S0n2qIVXZfsijkxFBvmqjZJmTe/E1BjsOphZv2TLqTa/inwc5lD0P1zfIC61dAT3ZsLN4+iCPqnhTmS+/q8zJakXsxAB1NR3Ax57cSETPAVgMoPZCWLKvhKOow3I97Q4mIWktbkpax4sqbsWamhvwgc+/p8nUNW3sVduKth6lcaOVlBZviwEwM1e2H3YblUVicrEpdnHuJc+CGz+66rnK8kEHPBZ0isOx85G6hphZXd0BmbIyo6Wak468r86y5Su5w0/xkBEAtE7N1BvT4KGo4Uwg8jcAL/jbaTiK2uN8VuGIg+SRa3D3yNf4lkM/xJOOqdjj06iVknJybl3tqCMfNpY0fcU2w6sNKoUdx7vVzv5FTTG7TXG3XPLBYxdsx96Y9JilxVLnPkc5M6c7HDtW1jUMmNxt62sH2SeY4WhFdFmxmt2Qr1wzeIs6MUuFEIgsqO7w+EOKmTe5Eoj4TViJOnVDiQhgtN52BAMrRU9YhYcwkOt3PYg/Jo7GKa92fYkgTZi4PnHHtoHpVY76/cPVwR5/ONR1VdcA6EfU8hFzwh2ZRMKn75+WqLptr096bJJDtPXvzcWsjrI7tq+sq08eb7NrUV4WAGBjsaqUR1e8oSwwFyizM9sQ43POOg0JeM2x3girjbLUDSWj4azAcWXBrI5AxdYH8ceMJNR55a1ktcZt27vzq6lLu3OHiBA82rDaVvvunqqOsj5GGao2J9wtkxCXAgAMVo8P3r2pcOxLuW5+B8c4m337yrqGoWPsdr/PmJnRUsXJZWvV2fbXlIUjKzgtGNNpb+kCEF2xcpFHIrs81ZevhNVIjW4lAyZBhQepcCIKIqESo+Y9wP+wTsa+onvxZE4MOjxaJ1ssbXOGj95TXHhiUNX19slu17nM3N1PqGWLKe7WbhLi0gGAwa0bMl4+eix5V24/Ddomdtt2rKxrGDnC4fBoN733ZuBoQczhTeqkpnzlmkHb1PFZKgTNRvoAEQXncVhQE0WGlaijNp7LYMABwlnIQgNbxA41RlY5XjarcXICx0qpMImeJfQPR4gs+zF14fd5TdO1+Ljou3h2tgz3x0Xp6YdmlNQNP1XXMOp4Esf3O43vVq2HFXb0tia2yTFfKRek5BwAUMhR/mb2n9AYU9P7GTKzdVpX964/1DeMHeJjyiAbSxX7eXTVG8qCqLXK7Mx2RIfjfsooGKLul2EEmMAYCZs6kmwqhBY7cPazGxhog0A1MAlNarTYxbEycbwcpcbJAzlGGgJRiNbPfI0gGlCIGxZu5M9Vfx2vVt6It+cI6Dt0kQhRk3PWmddtHdRya+fnVELfM51znad6y0HNkmXhbtGUcTUAtJuad702eeVVNsnac7bA3HG1tWv3/6tvGJ+kqF65hKqM5ipOOVKgzra/riwcVcmpIxGkdFUBxCOvQVcCkVwAg4moGsBvmflZXzoMN1G7dVskIA4qx6FLgdilAI2XZmxloA4S1bJJbOEYyc5xsqDGyTEcJw1mizQEAoXN30QlMf013Jr+Dt989G483TYXxX162gmCmpE1+f3N23YN23y1Y1yfYitvL+3h3SaaJhRJUdNyAaBiQGnRh+Oe7ZnQgLn1mk7r3ofrGycNUFXP8nkz7M2IKStSJze9qlwzeIealcWhP6X2Fo/W+sysWQLNsHkDu/A7qwgBSXBwEjkcQKcDqPss5JkBBYRqSEI9R4ntHCs51DhZ5jg5Xo2Vk2EWktFHOKGe2Chq3N/xAF7kO/Y9gMejMlHW65o4Nq5xXv3IdUWtJ4dVx3N0D9dHZm6uvayqJYlDNskxn89lcMeWkW8dOJi26RLBEnPTFzo69/+yoXFKgsq57mztZql8P2ecfl1ZaHlfmZXVAUs4Tqm9IejLwXATdUAzWRAggpEOu5pOdhVos0OssX76OgNdEC6s5yWrGisxx8lmNU5O5Fg5DbLglZOH1rRRwpTf8+85FWe3/hQr09NwtsfMZsSovVOKGwp3LWpa3EPUHY7mIwA+GymFuJ2muG/OVUmpfmfCk521cVWfnksTc91X2jsO/6KhaWos9y1mlamxglOOvqfOcbyhLBx9mpNHQYcIKx3xuoyUv4SbqP32jfYHAqKgYjS61dHUbYPQ3GNq3wKRzrJJaOFoqZvjZFLj5GiOkwdytDQEIgU+iJ+IzmHo1T/lv9gzcbjofqyakICWwZ+9jPiRU95JO1Q8fssE++hLso5Udxy7KHOK6ZA5/vaJXXLHgfycR0d0yR3pACAwn/tmW/vRnzQ2z7Aw95hmM8PWhNiyjWpO86uOa5J28bhMhhCRXoAeYojaDXqnqekXAhKgcAJZFcCqAA2fhSO78oSfh0TnOUps42jJrsbJEsfLsRwrJ7FFTNP0qI5IPoIJC3/Iz7bNweaiu/GP6VHojgEASXKMb5vyzHrrzocbLTB9Oj081V7qGtmFSnPCHSlnEyp2FYz/+1wmVRKZz9zW0nbyR03Ns0zAJWLuZvnkPh5z5jXHQsuH6szxnYgK3aw0wccQtRt0Han9gZxVGVLg4BRqdwDtDoi1l6zn7SCchiw0cJTYwbGSosbJJo4zJaixUgrMom/pbYnitmH+wu08t3Yx3tnzDbxytQhVik2oufbwiDfWTqu8ZTHgDLVsszeMANAgx3/Htnt40ek9w9YtlJgr725qrfp+c8ts2bWnoTI1lHPq0ffUOerrjoUZZ5CUAUC71L6RhSFqN4T0SO0PBMhgjIBNHUE2FWi1Q8Ql6/kOCDgLk9jEFtGqxsrgeNmixskDOEZKgyT0+4HHJCS/h68lf8A3ln8Xz53/HH00O+aqj+bU1M7elWYdPaPZVlcBYBDFLTqyNvuVxPq442kPNLZsvb2ldZbASGtE3KFCZUpLvnJN8m6+KhOgyIqWCxxxwe4wbNxERy5fawLgZXqdKwcGGiDSeTZ/up4X1Xg5mmPlwRwtDYFAl+QEi+aO0nvxZ55sP+IYs+GvmaUNRXsPkK1145SipNutFY6vtnQPKlHH1rym5MasU2eMt8Ic/uf7+lBZsXLRyGB26FbURJQJZzreC8dJZwC8y8xlAbbtEkYuX5sIIOgB55EAAyoI5yBRHZvFNo6VFTVOljhOjkuNPl9/f+P+zobtZ7vODS83JbUNG/i2smBMDQal6m13hFBdsXJRUP3S+51+E9Ev4Kwq+SqAna7L6QBeIaJXmdmbEjn+ogSxr4iCAAGMIbDzELK71vPnnFN7VWg603hs2w5VNGWnNMhJwDnc7Czc2Kir0RECg1qARUHt092a+i4AE5j5kiTxRPQEnJkSgynqziD2FfGYYeu6Nu61jbauA9FfOKgu+mhq7mZFOd0jaaCBfxA46HXN3R2hqACG9HI9zfVa0KhYuUgBoHkFiiuRm8WNO65L/1XR/gEHpjz4pjqaALPJNDsaOpTnvQII+gzT3Uj9AID1roqUFyJNhgMYA+C+ANrVF50AdPXaCmfGUnXFCsufKx5KF+KbBOH6p/+q7BVVZ2ZWmeJNVrKUgK3us5YYeEPQN3f7FTUzf0hEVwGYiUs3ynYxsx5rXCsMUXtNNLo6/ib/ZXdjwgn5nsEDsplo0INvK0UDOj5zIjHZWq1S1EzBYS3S09RIJOh7E27PqZlZBbA9CLZ4grGu9pK7xbVbH5BfHXJP2mAqiRp4NQDMO6Tunn2EL4lxjupqVMTYnJkOa1EDgEG6GBuZNAS7w3BzPjFE7SGT6OTxNaY/dpw125Jy09Ls3YKwAABSmrj6vnfV0XTZfkq0tZaIRJMgDT+oOqq8Su1r0C9BF3W4pQWq1duAUCce7S35pt9t+p/p16OeGSS1fmtIyrBuQRgLAJKDux97TmkVegkHjO48HwUAkmWBL9UoDPqmPtgdhttIXaW3AaEL84PSG1t+JL6T2SzShBuGDtl7TpIuSYbw8MvKTosNvaYWirbWxQGAICVngMwHwN2RHuccLIzptxsq9TYgFJlFhw//27SK48g676Noy96fJQ8eqhJdkkv7q1vUzWPP9i5oAIiy1n86ekvmaW2OLk1LXV/JGKJ2gyHqixiElvrnTY8dmUjlcx0Ex7KUpI1bLFELL8/OknGWj31rk9pvYnmzrSUJzA4QSWLUtCmOrq0tME4atKAi2B2G25raEDUAAaryG+mFTbvN98jZQvm8Uyapct6I9ONboi25lws6uotbfv+iYibA0l+bBBYArgcAIjmaxLT9gfwdriCOBrtDQ9RhxrXC3v2HzHeevFP6cAEREv6RGL/5pqFpgzsFYXxv9z/2nHJEUj3LaCkq3Z9OFeXoBcla2XwF0wmgOtidhtv0+zScrowhl/wv0AxBfc0LppXlY4SzVwNAq0AttwxJPVQpy30myF+2VilKboHHx1OyvaNdkZwDuiANzQTkMsCuS+mYCOF4Xn5B0F1vw2qkrli5yAagXG87gokMh+0x6Z9FW8z3x10Q9GZL1IEFw9PbKmW5z0QF04+pJdccYK8qYphtLZe4NIrmyXW+WW3gIuhTbyBIoiai54iologOXnTtG0R0iIhUIuozX3UvlGhvYWhyo7B19yHznWe+KRUtJEKsAih5yYOL7klJmqAQ9XmePKiVz/30LXUoAaI3/Vms9ZcE6UiWWTkwHH78IXJFDWft3S9cdu0ggK8B2ORlW/u0MCiUGUk1pzeb79/xV9PfppvIMQoAqiXxzILhQw99FBO9EER9ilVQ2fH4v5VagdEjKb87ojtrL8mOQmSOJzFpr/e/gYGLg+5v0Z6giJqZN+Eyx3ZmLmNmXz7JIvZNFoVu69/lJzduMOUlpVP9p/WUX4qP2/bF9CGxraLo1iHkV6+qW2K7favhHW0932OHXLLMN461fGebHp2G20YZ8FkGlojiVvGTHQ9Lzw+VSM29cK2TqGNpWsq+I2aTR2vjL+xWt02s7JmL21MsnbU9BCzKI7PtEE8CipEt1DtO5+UXBLUw3gXCaqMMACpWLqoHcEJvO7Qik6pO7TLfs+cR+blZEqmfrpP3mM1l80ak13oq6OG1fOqOj1W/6hpHdTX2OmUXzRODfiwTAejmkheOIzXgDAUdo7cR/hADa9s/5Cf3zhdKrybC6AvXGeAVgwcWvRUbMxd0aQbQvjDbuOMPzytMfqajlRVrPJg7QHRJKmYpak620r2/G4BHResNAOgo6rAbqV1s1NsAf1gmvrv1gPnuzgVi6UIifCrc86J4Pnf40H1vxcXmeipoAFj5vLLfpGiTTJ9Y6REJR0L0QBIG7NGi/SuILXp1HKwjrVfg3DQYR0TVRHQXEX3VVYd3DoC1RLTOiybfRxjm05pCx4+WmL93YLn86tUiccrFr70TG7Pz+mFDpEZRnOpNm0s/VjYNbYBmifUlR1dLr9ct8/p1MzW4hHYAurnZBmX63U/t3bd9aa9i5aKakcvX7gPglQD0IgHtzc+ZHj8wlY7PJbr07Lib0PW91OSd+6KivCrQDgDZ5erBL+1mTYvPyfa2DrupZ7EPQR6TAwhVgOq2RrgBPszLL3Do1Xm4Tr8BYK3eBriDoKo/k14t3mf+gTJNOL7gckEfNskn5g5PP+2LoBM6uP6hfHUQAR5P0z0hqqux14ytRESCKfOUln1FMP/Ts/NwFnWB3gb0x1zh4MGD5ruP3iu9O18g7pHz6/GBiZuWDElNv5CVxBuIWf3Tv5UqkZGmjbWfEW2t6/M9IVvmZgHQbQQKExzQecAJ191vANgFZ3qjkIomSkZT3fOmPx7LoqqriXoGnjQJQuOSoaknai7LSuINP31TLU7o9DxQwxuiref7HPlJiEuBEL8Dauusvu4xQHFefoGu5aHCdqSuWLmIAXygtx0XEKE4fif9p2iH+V7TeKFqbm+C/jjasjd3+FBbjSTN7K0NT8g9oO6cfpx9/kBwh6Wztt9jMTlqTti+Z4LEu3obEM4jNQDkA1iqtxE3CLv2/UX+W1wU2XsdPe2A/f6UpC2be8lK4g2pjXz6nrXqOApg6Gm0tT6xv9cFU9ZUdH5UA7DmU/8IQdf1NBD+ov4IzuICQ93dGAjSqe7si/KjlaOEc33uQJ+SpcpvD0nt6BSEXH/6kh3c9dhzSgcBAa2gaO5uTAEz9/XhQySIgpxxVLWfMETdk815+QW6hwaH9VTKVV/r+WD3a4K9+8/y6qJi048T+xP004nxW74yNG1QX1lJvOH3Lyi7o+zI9LcddwisygD3myxPsiwYgyDXUgsTntHbACDMRe3iOQTREeVmYdOuQ+Y7z31V3LKQCL0WYm8VqOXGoWlbVw9InAuinoe+XvLNTcrm0efhVcIDfxBUe7+iFsTEdFB0xIfAekkLgNf1NgKIAFFXrFx0CkFwGx1NZyu3me/btcr09AyZlD5zfm2xRJUuGJ7eVmHqOyuJN1xVzUdu3sLeJJHwG9ne2eruHilqli0YtoQR/83LL7DqbQQQAaJ28VygGragu/MZeVXRetNPU9OocUZf9ymA8rOkQRuXpSSN7y8riTfEWrl5xctKDAFRWrTnKSZbS5e7e0TzpOkAjHRHn/FvvQ24QKSI+k0AzVo3erv44bZS813N14t7FhL1HaHkykpy8MPYmNz+spJ4BTM/9qxyTFIDuzHWG5auBrcVTYlEWZBGHA6GPWHA3rz8gpBJ3hERoq5YucgKYLVW7U2g8hN7zD/Yt0J+YY5E6pD+7n05PvZCVpLJWvUPAPe9p24a3Aafz7P9Ibqz1qMPJil6geEH7uRPehtwMeF+pHUxfwbwYwA+b0zForP1X/IT++YIh+cS9f+36STquD0tZV+Zh0kMvGF2mbp3/iHus0ROoLFYaz2KyBLEpFGgqP3gLk0/0MKMEwBe09uIi4mIkRoAKlYuagDwtG9PM/9IfGvLfvP3uq8WDy90J+i9ZlPZvBHptYEQ9OAWrnngHXX45aVmg0m0G6+yi5HM09sDaUsYsDIvv8DtciWYRNJIDTinQffBi42lGXSk7FnTnxzx1DnX3b0M8MODBm56My5mDohM/hjaG6LC9sefVRoEwK+0RP5i6aof7Om9YtSUqY6uzVdq3a3TAF7Q24jLiZiRGgAqVi46Dw8dAAagtfEd06+LXzP9blw8dWa7u79WFGuvGTZ075vxsQsDIWgA+M0ryraYbn0FDQAme/sgMHt0ZEUkW0gaWhJgk0KVx/PyC3oNVdWTiBK1i8cA9PmGJKjqQ9LLm/aYl1GOcHI+kfu/wf9iY3ZdN2yI0CCJ/VaO9IfFO9StWacRsEANbyFWe6Q16gvZsuBKdBk9hxA6xrqYiBN1xcpF1QD+1dtrC4T9Bw6Z7zr+fWntAoEwwF1b3YSupWnJm36VNGgGE3k8JfWWkef45G2FakhtNolKt8fhg4KUdhUgX2nHW78KFWeTy4m0NfUFVgC4FXAKNxWN59eYVp4YJ1S7XTdf4LBJPvHdtBTuFoSAjp6Wbm575AVFICDG/d3BQ7a3tzvkXr1ge0WMmtKgdEVkSvbe2AvgP3ob0RcRN1IDn+6EPyzBYX9UeqZom/m+aG8EvWpA4qYlQ1KH+pKVxFtW/kc5KCsYFeh+vMXc3eSVG6gUNXMKnAn3rgR+nJdfELIBLZE6UgPA6t3mexYlUsf1nj7QJAiNS4akHq+Rfc9K4g13rVOK0poCk8HEXyzWejQPGOfx/USmWBKTi1mp1e18PUjk5+UXbNbbiP6IyJEaACpWLnIkUsdKT+//JNqyL3f4UFuNLAUlVU/OSfXADXvZ49lDsIm21nr9gS9ZFgwMhC0hhBXAz/U2wh0RK2oAwIqWQgAv9neLHbD/MCWp6MHkwZNVotRgmJXYznXLX1dTKIRnStGd571e44vy8AmAdDwQ9oQIf8jLL6jS2wh3RLaonTwIZ4LCHpySpcr5I9KPF0dbFoIoKH8LQWVl1b+VMwIjxf3d+hFtrXN7OtAbonniWa1tCRH2AfB45qcnISvqPgrVP05ER4joABG9TUSJbhta0dIA4N7LL/8zwZmVpEODrCTe8IvX1c1xVuQEs09f6KtYnjukqDmTAbgN3Qwz7ADu0DNBvzeErKjRe6H6jwFMZOZJAI4B+D+PWlrR8gaAVwFnVpIvD03b+reB2mQl8Ybr9qrbp5zyvdRsMBFVWzSYey3B0x8kWBJJGBhpdbd+l5dfoFsZHW8JWVH3Uaj+I2a+8Gm5HYA3yQju2WSJWr9geHpbuUZZSbwhvY4rvrdODeqswF8E1VHvy3OSZV5QPywDzFYAj7q7qbeZpev6j1yzy0NE9FjArLyIkBW1B9wJb/J+r2hpvjc1eYVCFHSXRpOdOx99XrETEB/svv1BUqzNvjwnmsZMBoQKba3RhTYAt3kYhfU8LptZEtE1AL4CYDIzT0CQ4q7DUtRE9Es4y5u87M1zpUtLN8PpbRZU/rBG2Wd2IOCOLFpjsrX67AYpmrIqNDRFDxjAd/PyCzyqH9bbzBLAPQBWMnO36x6P/en9IexETUS3A1gM4FZm9iWL6B8AeFM21y9u3aAUD69DyJ5H90dUV6PPccKSZe4EODeYwpVH8vIL3vGzjasAzCeiHURURER95rjTkrASNRF9Ac7D/y8zc6cvbZQuLVUBLAFwREvbemN8JR/+8nbWJSWRFlistT5XAiEhNomEhHDdMFsL4LcatCMBGAhgNoCfAXiN/KjQ4ikhK+reCtUD+BuAOAAfE1EJEfmU6aR0aWkLnKP95dMlzYjr5MZfv6rEE/pOWBjqRHfW+pXFVIq6OmSda/rhOIBbNfLtrgbwFjvZCWcBhIBF+10gZEXNzN9m5jRmlpk5nZmfZeYxzDyMmXNcX8t8bb90aelJADcjAFNEV6nZU6Lq1e58yBHdWevXLrZgypwK0Bmt7AkC7QC+mpdf4PVRXh+8A+AaACCiqwCYAPh0ouANISvqYFC6tHQjgB9q3e4D76jFAzoQ1AT8gcDSVeeXLzcRCYI8NlzcRrsB3JSXX3DIl4f7mFk+B2C065jrVQBLfdwH8s6WIPQR8mSvyX4UwHIt2pp3SN39o3fVqXomDtQKBikbFv4V/uQyV5WWs7bWZ1MR2n8PBcA38vIL3tbbEC0I5T900ChdWvp/AP7hbzspTVx937vq6EgQNAAQWATYryocgpgwBBQTMonue4EBfC9SBA1EyJtPI+6FH5khJQd3P/ac0io4dzsjBlGx+b2ZKFlmh7LP9M/y8gtCNouJLxiidlG6tJQB3AEvHVou8PDLyk6LDWHlBuoJsqPD72wmoil7OkBBcbzwkt/n5Res0tsIrYkYUfcR1fV7V0RXCRF9RET9ltBxnWEvBfBfb/r+6hZ189iziMiMH+buZr8jrogESZBGlmlhj4b8Ii+/4Dd6GxEIIkbU6D2q63FmnsTMOQAKALj9TyxdWqoAuA3AXz3pNOMsH/vWJjVgqYP1Jspar0kuLil6wUgEsY54P6hwrqGDElyhBxEj6j6iui6usxwDD99UpUtL1dKlpffDuSPe5zPRXdzy+xcVMwEe1Z4KR6KttbIW7QjioBEgS4kWbfmBDcCSvPyCkMzXrRURI+q+IKJHiOg0nCmDvZpulS4t/SOc0/FeHVQee045IqnoswB9JOCvV9nFSFEz9MyT3QFgcV5+wRs62hAUIl7UzPxLZh4G5wbYfd4+X7q09EUAN+Ky9LfL1ipFyS0ISpJCPYm21iZq1ZZozpkGwOMiARpSAWBeXn7Bxzr0HXQiXtQX8TKcbqFeU7q0dB2AOXCWLcW042rJNQdY84qXoUhUV4NPaY16g0gyC1L6Aa3a85BPAEzPyy8oCXK/uhHRoiaii2OYvwI/IrNKl5YeBDAjqZlf+dmb6lACfPayCidkhzUePkbE9YZkWdjvCYTG/AnAF/LyCxqC2KfuhGMUTa+4fG9zAQwmomo4Q+e+RETj4NzxrATgcwAIAJQuLW0uy8y6Fc4NtN/jChE2sVLHJGmydyBIKWNBpoNgWyCre3YCuCsvv+DVAPYRshi+3z5Slpk1D8Ar8C5PWlhSPPePJXY5Nker9uzWrcVK1/ZAnevvhjNjSaidiweNiJ5+B5KsI2WbAUwB8JretgQa2dbWoWV7UtT0qXDm/9ISO5yzszlXsqCBCJp+60HWkbJ6AEvKMrNeAPB3AMN1NikgRHU3OTpjtMvXSGSKITG1mJVzWo3Wh+AcnUM5cCRoGCO1BmQdKVsLYDyAP8MZxhdRWKx+BWr1imxZMEiDZhwAHgMwzRD0ZxgjtUZkHSnrAPCTssysl+Esej9VZ5M0I7rzvEnrNgU5fTwgHQUcnpfWvJSPADxwpU+1e8MYqTUm60jZHgAzAeRB+3WjLvib1qgvRPOk8z48dgLAl/PyCz5vCLp3DFEHgKwjZUrWkbInAIyCs7pDWBdjt3T5VizPHVLU7Mlwlof1hDYAvwAwIS+/4L1A2BMpGEdaQaAsM2swnCli74UzsCSsUEm0bVzwlIwApLftbn1hMyv1/XnnNQP4C4Cn8vILApb9NZIwRB1EyjKzkuAcbX6IMIvsKlz41waQoMXm1iUo9lMH7O3vTOrlpToATwD4e15+QWsvrxv0gSFqHSjLzEoB8BM4M61o5lsdSDbOf+KoKpp93dTql66mp04BymjXj6cBrALwTF5+gWbuqVcShqh1pCwzS4bTJ/1uANcjhPc4tsx5ZFe3OTEgZWPsHZ9sVGwHrACeBrDWw4J0Bn1giDpEKMvMGg5nJc87AQzT2Zwe7Jr68+K2+BFau3ZWwJmx5vl7n762UuO2r1gMUYcYZZlZAoDPw5nU4YsIkeykpePv2liXPDVXg6ZOAHgbzuoV2+59+lrjDagxhvNJiJF1pEyFs+72B2WZWSKAuXAmafgSoF+20mhrna8RaQxgH5wifvvep6892P/tBv5ijNRhRFlm1hAA18G5/p4HYGSw+q5JmbWrLOu7nqypVQClADYD2Ahg471PXxvw+lEGn2GIOowpy8xKADD5sq+JADTLK3aBlvhRR/dM/enlu98dAA4DOOj6OgBg571PX2scQemIIeoIwzVlvwpAFoAUAMkXfb/434mXPaq6vpSLvjcDqAVwvtsUX7Hl6keb4DxyqgJwFMApY00cehiivkJxiR8A1KwjZcabIIIwRB1kiOg5OAve1zLzxMtey4Mzr1YSMxvrUAOfCFlnhwjmefSsJAIiGgbgBjinthFHH2WRVhDRGVdZpBIi+pKeNkYKhqiDTG+VRFz8GcDPERqlaQLB8+jlwwzAn5k5x/X1fpBtikgMUYcARPQVAGeYeb/etgSKfj7MDDTGELXOEFE0gIfgZUmgCOI+V2XS54goIHHbVxqGqPUnA85kCvuJqALOlMN7iShVV6uCwz/g/P1zANTAGZ1l4CeGm6jOMHMpnOfGAACXsKdfCbvfzPxpOiMiegbOcsMGfmKM1EHGVUlkG4BxRFRNRHfpbZNeENHFeYe/CqdXmoGfGOfUBkHh4rJIAM7DmXg/F86pN8MZhvkDZq7RxcAIwhC1gUGEYUy/DQwiDEPUBgYRhiFqA4MIwxC1gUGEYYjawCDCMERtYBBhGKI2MIgwDFEbGEQYhqgNDCIMQ9QGBhGGIWoDgwjDELWBQYRhiNrAIMIwRG1gEGEYojYwiDAMURsYRBiGqA0MIgxD1AYGEcb/B32gTmsouYJpAAAAAElFTkSuQmCC\n", + "image/png": 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H3pFARFe99yzCUO2O3IfzQaHhQANgIYA71Q5iNIJR1DUA1hHRJCKKAnAzALd8uXbtzpwGPxWwMxgGl65Y8RqmTD3ziT/aV4JgNPxnZvu+5lclOO2ixIjl5YKYNHP4OTLk5h35DyUE2Uy3O/wqGA0Vgk7UzFwLR7nYDwG8D6ACgN3Ny38KwG9vDCJMzso6sMSY+2ERkd3sr368JggN/y+bGw+0my86srAo5ogucu1V6YwMHnp7weMdfYauaaM2ENxkAPii2kGMJOhEDQDM/AwzL2Hm9QA6Abi0xXWOpb/v79iIQAkJLRtWrd5+Ljq647S/+/OUYDL8Z5bbilteuzJh2WmIu2PmyHNKZr15tCn+VLDOdLtDwEsbuyIoRU1EU53fZ8Ixnv6rG5fdBYd5XEAQRfu8RYt3Ts/IKCsOVJ/uYIY1t4cGgyILraZr/wmrbI4HAClyYx0JsVdlWJ1NqtpbNX3PyOJ3ocYq4zZjQLKv3CUoRQ3gNSI6DuBtAFuc2+zGZNfuTBHAPQGI6yqIEJmadnzdsuWvH5akoY5A9z8qBCqXzpxSOwyLfbDqeFfJGgAgIfGgFLH4qmWqHsPlQx/MeyZUZrpdEVR366AUNTOvY+YFzJzHzLvcuKQAjlKlqhAR0b9i5apXLZMmnwuKGtJnhNZRzfoCBTPbi5pfiQBAADXrY796VcqkVTDX7cgrzA2hmW5X3GrcZpyldhBXCEpRe8EP1A6AiFOys/ctWpizq4hItqoZi9qG/21D5/d3WJrmAYAu6qZGEiI/HRbJkFu35z8UbxOt1yRwhDAiHJO0QUHIi3rX7swMADeqHQfgmERLSrq0YeWq7fVRUV0NasailuE/s9y6v+X1RQBAYkqxaMj+NKWSwUPvLPjftj5DZyjOdLviu8ZtxqBYkgt5UQP4HoLs3yFJtgWLl7w9Zeasyv1qxaCW4X9V5756K1viAOGcPvZLV5keHJr5Vtml+PprMrLChDg49lSoTlCJwVN27c4kAN9QO47RIEL0rFlVa5cu+1uJJJkDviHEafhfHsg+zfaBirruw2sAyLqYL3QT6aOvvNaQWL23csbucatWhgG3qx0AEOKiBrAEwAy1gxiPyMjeVStXvdKXmNRYGei+y6WzQ4Hqi5ltRc07YgBAkNKLRV3Gpz7ePYb2Q+9nPR0uM93jUWDcZox2fZp/CXVRf0HtANyBiGcsXLgnJ3vB3iJAtgWq307qzwuU4X/LUMOBTkvLHECq18V84dPlK6tgPrEjr9AYRjPd4xEF4Ba1gwh1UXtj3aoKRBAnT76wYdXqHbURkT0XAtNpYAz/ZZabDrS8sQSARR/7ZZlI1AMAQ27bkVcYaxMtqt+9Aojqj+AhK+pduzPTAeS6Oi/YkCSrcenSN+NTU2sOBKK/QBj+V3bsabCxNUbQZ5cI0rQsAGCw+Z3sP7f0RnRM93f/Qcbn1a7qEbKiRgjdpUdChLiM2eVrFi9566AoWnv92Ze/Df+H7APlJ3s+WQXSV+uibvzUmP/wzLc/uZhwMiDumUFGBFQeFmqiVpHo6O7VK1dt70xIaKrxWycEqUJq8IsFMjNb9za9HA9gQB97RxyRIALAuYRjRRUzdoX7TPd4BMQ1dCxCUtS7dmfGA7jGOSMUEQSemWP8eH7W/OIi+GlduV5sUqoo+1U0DZ452G1tmy0alnwiiJNmAUCvvqP0vflPhWS1SAVR9b0ZkqKGY5HfpfVvqEAEaerUhg0rV+2oNhj6Lindvj8M/2WWLx1sfXMpKKpMily/DgCsguXkjvzCBSAO1feVUqSpuRc8VP/4n1M7AH+g01nyli1/I2qaH+p8KW34X96+67ydrTZD3NemExEx5LZX8gqjrKI5Rsl+QhjV7tahKurlagfgL4iQMGfOkVWLFu1UtM6Xkob/g7a+slO9R1dKkWuPkRA3jcGWd+c/0dQT0a5qdliQodoQJORE7XQ4Uav6YcCIie1Yu2r1jta4uFZFqloqZfjPzJa9zS9PIiG+RIpYvhoAjqS9W3ohsS7klhf9jHan9oAlCM24PUYQ5IzcvA8y584t2auERXG5dKbT1zYuDZwq6bF2ROlj75gHAOcTavceTf1wravrJiBZxm3GqWp0HHLiOIPMHDP0IVM5w1eIoE+Zdmqjo87XQIsvbbVSj9EXw3+Z7Y0lbW8tk6JuaCAhalKvvrP03flPhMUqhJ9wa1mPiNKIaA8RHXcWsLjbl04lXy5Wg1/RI6vArNfBenoqWpqzUGvLRUVcNo5lxKAvQe34/IWjztdr7fX1K0tbmud6N6fgMPwvnW+f4dX1Ze0fXZKFpAaDYeFam2Cp35H3ULY20z0uuQDecOM8G4B7mfkoEcUCKCOij5jZq/0FISdqAEYQiVboMy8iLfMi0rAbNwAABLY3JqH9UibqB4yojMpBVeoUtIXNNkUiTJo379CklOTT+6qrr18my5LHSfmV4jl5vt3zxLYBW++RM73V0w0JP4xnyJd35D4caZXMQeNcGqS4NffDzE0Ampw/9xJRLRzZh16JmjjIq8kMJ2VPhQSgH4Db+5mJ5Y5Y9JybhYaeHFRJRlSmpOFchoDQvsPY7eKpqsobuK9v8jX1qMaFYf6Gef2QAbp4ty9hHnrv4tPNQ/p1XYJ+9oJ35z9RdyGxVpsYc01V9Z3VHtV0I6J0APsA5DBzjzedhpqos+Hlp9dVMA9EYuDMDDR2LkANjKicNAcnZ+thjfA9ysDBDHPTpazDp08v92hcm29L37/Ulun25NaF/rqiQx3l0Md+acOR1Pf2l6W9r02MjQezWc9onGq3Nb3X2LQBpm63dgoSUQwcZaYeZObXve0+1B6/3Sq/4xKiqEFE55xCFk4hC2/hNoDZpoOlPhktrcPG6bOj0e/2HS3QXKnzNWny+SPlRwvSrdZIt7aD1ooXY5faMt3qQ2b7hcNtH0zRxX9v9oX4uqKytPcngtmBa5itOqAxyW6/PMtqG8i2WCjHbInOGrLGT7WRvQux3eflZPlu+63T/wQ0umqOiHQAXgPwoi+CBkLvTv0tAH8JZJ8C2xonob0xE/VmIyojF6I6bQrags44jxltJ+rWnmtry1jq+mTwVyyrL8VxpMvBdWnbe4cuUnb8QFR03/8tNi2ZUBNjzHYJaEy029tmWm398y0WGM2WqAyzrE+2inyZE/tP83TbMTldrOH0+BPyzKnNSJwK0HBDiA0NhQX7xuuGiAjANgAdzHyPr2GH2p064JNeMkmpbUhObUMyDsHx1Ekst8ehp2EWzvbloEpnRGVKKs6nqzlOJ8KUrPn7J6dMq99XU33dCmbRMPbJDsP/DdaF44q639Zdes48NCTETp28Pe8X88NS0MyyCFxKsMstaTZb/3yLhbOHLPqZFqIpFj218mTzCTmNazgj4qA8K+l5njF9ABGemD6kwzFGHo81cHjtdRLRFjhmw29j5ne9+SeFmqiD4g7JJEzqRsKkKixCFRY5D3J/FAbOzMCFzgWoIec4PVMH29jiUhhnna/1q1ZvP1FZcZPU35805jP2GaE1dQPGNvZk5sF9LW9bpOjbsrfnFZpDeqabmQWgOV6Wm2fYbH1ZZqs82ywj1SLxZHOE2CJPtR/nWVKNnBH3Ps+c+jRPTmEISn2AuRwyMvN+OG7Y6wH0AXjeW0EDoSfq4F2eIooeQLSxHvNRj/l4E18CmG16WOqT0dyShVp7Liri5+N4hr/H6aJoz1q0eOdgY+PC4oazi0fdg3zF8D+ZE7JGe/1C/8mDg4ZNaR/Of7apO7It35/xKoXA3BIry83TbfaeORarLdUs2lLMBkwyR0nN9hQ6xhkRNXL6lNd4xrReRAdqrsTttFdm3uec/fYJTdT+hEiywDD3AmbNvYBZ+NiZOy+y7UISLl+ci5NDRlRGL0BN6mRcVvQphAiRaWnH1k2Z0nC4/OjNc222iKSR55RJZ5pvti6+RtR2tp8r67koVMwdaDmXdCyocqOJuS1G5qbpNlvPTKs8NNVssE4ZikSiOU7fYp+mr5Ezomp55qwyTp5uhxgM7+/Jge4wGP7RnhBaoh4DO0lpbUhJa0MKDjr3/RPLl+PQfS4dZ3pzUGUwoiplBi7M8nWc7qzz1Vx7fH15e/vMRcNfu2L4T6Cr+ijvKD12KXlK1JGZf1ZF0MTcGcV8Kdlm75pqEfsnmSOtSeYYih1MMLTbp0fWcHr8STltwSeIu+aDKggJeIyhJuqAlaoNNEzC5G4kTq7EElRiifMg90Vh4GwqzncuRDXloGpKJuozPB2nE3FK9oKiqZ2d04uOH9u0mlnQOfpE8lmhtWy2nLzkyrn9tt6SY4bYiJ0L/Sxo5u4o5ouTbNyRYDX0JwzFWGPNCUL0YGJEp2163HGeNamWp82phC5gcxJ+IuBLoqEm6lCL1zeIYgYQbTyJbJxENt7AVwBmqx6Wkyloas3CcXsuKhLmozYjCgNx4zcFwVnn63hlxeejBgYS0gGH4f9si6NsNDMP7Oqva3996UvrmVj0OX7mvgjmi3F24XK0JaovxhxvjR6aJEUMTY7qsk5PPCmnJh9HUigXnHeHcf9f/EGorVOb4cEW0QkDM4uwX5iEy5cc4/SK6AWomTkJ7cmjn46+8+dyK86fz1sLRt+d5o2CDmLUOXPTzvuznsjpimx134qHeVDPuBBh1182WGL6Is1JNv3gFL1uaGpMv3Xa5DM8ffogDOFU4dJTzjQUFri104eIXgKwEY5xeAuAB5j5GU87DDVR2+AoG6rhBsRyWzy6z6XjdJ8RVYYcVE6bgcZZBEe1jIGBuIOVFTctXDy48NhCW1rKj1Ie6zqfdHbxNQ0xm0UWLkj2iDbJEt8vmSfL0mCKXhxKiR+wJKc0Y1KygktA4ca5hsKC9EB26FLURDQfDh/jKxsVLgJ4i5kVceTwhJQ9FaHzCRSsMPdFof9MmmOcLmTZa8XY2tmdpwdZ/9bUPXNgj2ojS1I/DSUzDU2LoMFpSRbrlOn9iA74Y2SY0NhQWKDM9mY3GVfURPQzAHcAeBmf7V9NBfBVAC8zc6HfI3SSsqdChGOnjYaCUJ/13E3H3ipfUtlrHxT6ksjWMh/gUJ+cChoY1HTf9rcDWtTA1cTTXQAWMrN1+EEi+i8AxwAETNTQHruVxSp36yo7KoR286pCw3OXX5Fje6bxPUJXfGqUbai0ym6pSgRbJmKFDUUheJc+6QuuxkEyRl8bnuZ8LZBoYzYlYLZLJ7r3GXY32cR284aVdPxUMvUs+etGmr+44g9LJ3fWl+ui1q+LSPhxjj7uG2cF3ey9ACnuRT6BsAe6Q1d36nsA7CKiegBXKjXOBDAHwI/9GNdomOH4A2l3bC8RmgY+0dV0JpD8mdPlI7onewCgL5Kk+uk4mle9deOx+XcWtaQs3yCIUzL0Mf+QwcyybK0/ahssGWS5fREcJVs13CPgQ0Z3JsoEOHy2h0+UHWHmgH8CpeypaIUHe2k1HFCv9Yy+7HIHmeWr0jLn0YWzH+h/NosIwqL0tHPT22B/9Bl7BgF0Ys6Xiy7O2LAedFUaIZjNvfaho5U2c3kMeCgPmBB1p32h9N7t76wIZIcuN3MwswzgUABicYd2aKJ2H4u9U1/RUU2dltUEXGPm/6juiUYiZACAjnno/FQhqysaZYn9WJJ16pUNOttAccOsz68BfbaNlMgQK0WuWitFroJs77xgGzxwWraeygBk1crMBDmtge4w1Mapl9UOICSQ2Sod7yoy7GkmodOynkb58E5GR2sunfnUVVTHPAQAL1wnfProNrth57o5p18/BOZRHyEFMTFNH3PLxojEe2bpYr5YRWJyMYCATwwFOT7ZOntDqIm6Xe0Agh2xsb/U8PGlRulC/wYCEsY67yHd08eJ8OnSVQSzBQD2L6AlVhFnrhyf2bh79fwTLx4Fs3ncfnUZuYa4r68zJPxEJ0WuOwCKKkPgJ1ODkYCLOtT2UmuiHgPqttTrj7b3kkV26ekdi/6eTULFVTvHIq8sWxLRe0up8e8P86eP69ObS5ZL9qGjNQvumg+icSfJiHSRUsSyNVLEMrDc02QbLDlht9SlAXb3TNHCD+1O7QLt8XskZnub/lBrsf5Q22yyyNdu8RyFX0kvHCW6OtEgWpY/nfh8Za2whIHu4a9PbStfnFf9v6fggW0tCXHTdNE3boxIvDtTH/Pl4yRO3wfA59I/IYYmahcEfNIhaLGzWarp3GvY22wQuq3ryM2lPj2s5tvE4msyo2Lkzwrem/UUXZlBFSPPmdRxPHdxxR8ugrnD03AFXdoCQ9xX1xsS7o6WIjcfAsWWYmLsENRE7YJTagcQDIjn+w4Zdl1qkS4ObCQPU/t+Kr1eKhJfU7gtVpavWtt8+iZhDo+ycSKh+3T2srKHO8CyVx+wRKJeishfGZHwT8sN8d/vFA15RYB00pu2QoTmQHfod1ET0bNE1EpENcOOJRHRR0RU7/zurvlBOP/nu4Q6zbWG3ZcqdbXdK4kx0+PrIcvfE3eOmlwQL189p9WaQDNaEnBktHNj+y7MWXHkt4Mk2y96GsNV8QjRU3RR122ISPzpPH3sHScEKa0IQJsvbQYZduCzScdAEYg79XOA05zrM+4HsIuZ5wLY5fzdHU5DhW13qjNkb9EfbDmgL708n6zsURmX4fyj+HGpnmzpo70Wb5eveS88e4Mw5qRY9EDLrJWlvwHJtgZv4xmOIE3L0sd+eYMh4Z5EKerGUhLiS+DYRRjKnLp3+zsuq4yOduNzHv8JEdU5K2E+4m6nfhc1M+8DMHIM9gU4zMvh/P4P7rTVvCnfAoewJwZ2HtRVdhQZippjhF7bGvJx99bPpJfHfFRPkO3XjMkrMoXcQR3GTLGNHGqfsfrQr6MEu6Xel7iGQyRIkmHhckP8XasM8T8cFA1L9wH6Y0q1H2DcLRH1HEbc+IhoExw6yWPmhQB+726nao2pk52V/gDHmGNUh44xqPZDPMEFM4tnew8Ydl3qFJsHNxDgiXn8qNwolJbH0NCY1kEJdlk32vE3VgvjTooZLN1T15T8crJoG/K9xtkISIhM0EWtXx+R+OOF+thvnBF0GXsBanJ5YfDg1ofRGDe+HwIoZOf+AGZ2ew5D9Ykydmw+98T8oMpfsQQDQvtQjWF30zHdyZ41xMq5p/6n7i/jbgSJk+VRbaLeWUHLZBp/1UFn609cU/KLVMnaX+lLjOMhSFNm62O+uNGQcE+yLrqgjISkAwAG/NWfQpT7cO08AOuI6DARFRHRMncvVEvULUQ0DQCc3z2ZSfXbG0dNaMB2Ub+/5aDuk/aFZGNF85gX08m6qdS9ZLxz4scQtU0kfcl8cnkXluxDcWtKfjlXb+4u8zZOdyAiQdRnLTHEf2uNIWGLXYxYWQyKqIRnN4ZAcdSHayU47IVXArgPwA4akVwzFmqJ+i0Adzp/vhPAmx5ce1j5cFTEJvfrytv36otbkoR+22pfx82j8ajuCZfrynF2ecwyvs9dLyxkNyatRNkStfrQr3MihtoD8n9EZIjVRa5eF5Hwozx93LcuCLq5ewHhgssLA0PHvdvfafDh+kYAr7ODUji23LpVGCAQS1ovASgBkEVEjUR0FxyOKZ9z5mlfDw8cVJo35TcDY0/ehAzMLJ7q2W/Y1dQntg5tJCDSH91k0KXzs6nJZepfnCyP2X93DE05N3X05a2RCGwzrDxsWhLV33TAkzh9RRCTZupj/m6jIeHuVF30P1SSOLUYQG8gYxiBrx9sfwOwCQCIaB4cLrpu7aj0+95vZr5jjJeu86HZ3QCyfbheVYTWwUpdVaee7Oz34u2P6p5sIHK9ph0jy+NOxj11kzjlwefdW00UWJZWHHlw1SeL7yvujZsV0CofRESifnaeqJ8NZuuA3Vx+0DZ0NAI8kI/APpl+5O6Jw62BiagRwAMAngXwrHOZywLgTnbT+jekLIKvkLKn4lY4CnSHFNRvPa8ra78kDNpXBqK/yehqO2L4UQyR66cAGZDzMmaO+6Z/5o+2ithB5HsSw9G8nxZ1JWapXqie7T1N1qGDJ2TLiVmAPSMAXebcu/0dVZbiVJ/99pK9CKW0Pqvcoyu7XKTf35ocKEEDwO90zxxzR9AAIAACmMedTX5pg+DxZpDFlf+9YXJbRZGn1ykNiXHT9NE3bYxIvDtDF/OlYyRO2wegy0/dXVRL0ECIirp5U34HQmEWnNkunezeZ9jdZBYvmzcQEDDr3WgM9l0vlOV7cg0B/eO9viufltkEeDwRlXvsqQ3Tmg7u9fQ6fyHqZi40xN2x3pDw00gpctMhUMwRKJtc4vajtz8ISVE72a12AOMhNA8eNXzcdEY627eeVLBg+rn01zKBxjZJGA3RxbovEwm788irvczZJ17cmHbh430IovEekWSQIhatjEj43jJD/Pc6RX2uUsklHyrQhteEsqhV/cONBfVazxqKmo/oKzsWk8xz1YhBgs36VXHPPE+v0zEPujrnrxuFfAb6vIlr7uk31mc0vHMAKphWuoKEmCm66OudySVfvZJc4k3+PkO7U3vNbgRTRo9F7tIdadunP9iaSkN2t3f/+IMfiW8dlkj2uIi93mlpNB4DERRflwqvN5hknHt/7bxTO0oxokBEMCFI068klyRIUTeUkhB/CI4ZaHc4eu/2d1Q18whZUTdvyrcB2KF2HJDZJtV2FRn2NLHYYVlPwKh7qAMH8xbpTY8FDQAGFz5kV3jqJnEW+7CDK/XivlXZdc9XwGl2GKw4kktylhvi71ppiP9hv2hYvA/Qudpd90pAghuHkBW1k7+q2blwceCIYdel89L5/g0EuJsT7le+Ku4pNZDVKz+wSDfvno1TKL0jFp9408cVprWULjPWPFkHZq8e5QMNCZGJuqiN6yMSf7JAH/uPpwUpvQigkQYIDOAlNeIbTkiLunlT/kEAZwPdL/VYThn2NJXpazqXkXytn7aa/Lv0V6+rZwz3KXPF89cJPldKmdJelZ9f+f8awNzt+uzgQZCmZupjb91gSLh7ii765k9ISDoIYBDA/nu3v3Ne9fjUDkABAvfJaLa36w+1FutL2jLIIo+bIKEGm4TyyjgaMHp7fewwnzJXlGQLiy2S7/ZSSV0ncpaUP9YMlkPOVJJIEEX9/KWG+G+tNiRssUqRG7eqHRMQHqJ+0e89yGyRjnUWGfY2S56Y/AWa3+mecXcyZ1RG+pS5YucyZXKb43vOZi3/5KEesBxKudJXQWQQpYjFb6sdBxAGom7elH8cvuWtjot4of+w4eNLTVLjwAYC4v3Vj68Y6Ux9CjqWuj5zbOJk2aMMsdfWCEvla5P7vSKm/9LslaX/YSPZHixZVp6yY8vWzWomkHxKyIvayX8r3SB1WU4YdjdV6I53rSBG0NeJ+r1uayuRb2mb8XbPRG3RUWT5HFLMiSZqsC1t1eEHJJKtATfrU4Cn1Q7gCuEi6r8CUKaG8pC9VX+wtVh/uG0uWeV8Rdr0M2nUenEeNfpcWXE0nzJXPHODMI8V3GIZYe6ctqbkV3GC3XxCqTYDQPWWrZsPqh3EFcJC1E5Dwj/51Iidh3RVHUWGouYoode6jkLob/Oo7olTRL6n0Y7lUzYel+NpWlOSe7nW7qK39k5eU/LLZNE2GCqGgw+qHcBwQuaN6wZPwMukeLGh76Bh16XLYtPgBgJiFI7LrySip2MF1Sqygy1e9lzUAPDMDUKsEv0PR2cbSFhT8otZOktfhdJtK0wtgmDDyXDCRtTNm/K7ATzpyTXUYT5u2HWpSneiezUxUv0Uml/5T91fqojg9dr0cOJk2asssuoMIWdA755zpidIdnPM6kO/zNKbu3za6OJnHtyydXNQpQGHjaid/BGA611Rg7Ym/YGWA/ojl7PJxrl+j8pPRMI8cLNQqlj84/mUueLVtYJfNpCIsjVy9aFf50YOtpX4o30fOQngZbWDGElYibp5U34jxtuMYpcHdBXtew37WuKFPt/N8dXmPmn7EYE4San2xvMpc8V7S2mZnfxTN0pgu37l4d8sj+lr3O+P9n3gd1u2bg66jLOwErWTBzAyo4aZxdO9+w0fN3WLLUMbCco8rqqJCLvtm+KHitZ8duVTNh52kXQHFpDfZqwJLC775KE18d2n9/mrDw85g0BsfPKCsBN186b8BgD/c+V34fJQlWFXU63uVM9aArzKXgpG/knceVgiWdF5gGhmnyYJn79OyGHAb5lXBNCS8v9an9R+bK+/+vCAh7Zs3RyUpXjDTtROfkv91mP64uYSfVl7Ltl5zHIzocrd0uvXlKP1FXd8ysajJ5omnUnxLXvLHfKr/3djcssRNX3P6vFZLbigIyxF3bwpv9Owv/UpYcC+Su1Y/MEXheIjkWTxi6uKK58yVzx1k+hJXTSvWVj73IYZF/epJeyfbtm6OXhNHtQOwI88DverDoYUv9a9MGqJHCVw5VPmijPTaG53lP/24g8nq377hlnn3i8Gu59dpgB/27J18/sB7M9jwlbUDYUFNgB3qx2H0qwRamoSqc/rGtWucMenzBUvbhQCdhfLPPv2uswzfysBcyDGtwMA7glAPz4RtqIGgIbCgo8BvKB2HEpSKD3p0+OxK/RuWhqNR1EuLbUJOKdEPO4w68LHa7JOvlQGBWJ3wX9s2bo5YP8ubwlrUTv5KYCLagehBPPp/JlUurzcn31EuGE+6AomEj5aRA0KhOM2M5oOrFh4/C81vkz0uaAMbhR+J6JniajVWS7nyjETEV0kogrn181+ihHABBB1Q2FBF4Dvqh2HEjym+/MlX9MrXREpK/MY+/IGYTEDPUq05S7JbWVLcqv/XA9mpfu1AbjLzY0mzwG4aZTjf2DmfOfXu4pGN4KwFzUANBQWvI8gynf1hum43LSAzvn1Lg0AUSwrIupBA8Uem0UBmTAbzuSOY3mLKv7YCOZOBZt9eMvWzW5VhGHmfVDIOMJbJoSonfwLELhxntI8rHvqJBH8Nut9BU98ylzx1I1CBqtQ8yyx+9SCpUcfuQyWlfCFPwDgNwq082MiqnI+nvvVeXbCiLqhsKAXwLcABN1eXVfEoa97rVC9OBB9eepTNh5Nk2jm5Thlc63dJa73/NwVRx7sJ9nuy3xKC4CvKLAm/WcAmQDyATQBeMzH9sZlwogaABoKC/YC+He14/AUk+75ciIonrM8Gp5aGrniuc8JASsKOJLogeb0laW/Ack2b57Q7AC+umXrZp8ddZi5hZnt7FhPfwqAX4dRE0rUANBQWPAIgiypfTwMsAz9g3BgYaD6i5dlRd8TR+YJ+WYJqlkTRQ61z1h96NeRgt3iqZ3xv2/ZunmvEjEQ0fCcgy8CqBnrXCWYcKJ28h1A+aR+f/Av0iulAnHAqmbGy3bF3xNvraRWpdv0BIOle+rqQ79MEm1DtW5e8saWrZsf8aYvInoJQAmALCJqJKK7ADxCRNVEVAVgE4B/9qZtd5mQom4oLOiD4xMzqCtDCJDt3xHfTw9kn974lLnib6uEZbJ3FSQVQ2/tT1pT8osZknWgysWp9XDMvXgFM9/BzNOYWcfMqcz8DDN/g5mNzJzLzH/PzH71N5+QogaAhsKCegBfhwqzs+7yLfGDwzqyzwxkn976lI2HVaKIT+aRXx853UGyD8WtKfnFHJ2l5+gYp/QDuG3L1s0BXV9XmgkragBoKCzYCeCHascxFv8q7VDM1cRd4r30KXPFs58Tstkdqyk/I8qWqDUlv1poGOooHfGSFQ5BK+ZjrhYTWtQA0FBY8CSAn6sdx0gKhENlUWSeH+h+4+zeWxqNR0ccJTdOxkghqYLANsOqww8sjhpovuLVLQP45patmz9QMy6lmPCiBoCGwoJCAF5NjPiL3+ieU8U/LVb23nzQFc/cIAZFuV8AEFiWVpT+dmVs7/liOPKjg85A0Fs0UTtpKCz4GYJkK+lyqj0+mXoCstlkJL74lLni+Cxa0G9A0DzeElhYVvbwzi1bNz+udixKoon6ar4PYIfaQTyie1K1WXlffcpcsWOdEExF5n+ZXVf7sNpBKI0m6mE0FBbIAL4G4Hm1YphLjQ2zqMXnulje4vQp81vO9gdLaJmdFKp75hu/ya6rDapyOUqhiXoEDYUFdjjWKf+sRv+P6p64QKTu/4vgo0/ZeMgCSfuMVO+v9t2AAfxbdl2tScUY/Iom6lFoKCzghsKCHwH4j0D2m4yO1jw67ff0SleIgM+WRuPxwmYhj330QvOSQQBfzq6rfVSFvgOGJupxaCgseACOdeyAbFD5ne6Z40RQLQHiCpICPmXj0RdJCaemo8yffYxCK4BN2XW1rwW434ATlqIew1Lmy0R0jIhkIlrqblsNhQVbAXwBft5SGoOBns1C+SJ/9uEuSviUueLJm8Tp7HgUDgS1AFZk19UeDlB/qhKWosboljI1AG4F4HHZlobCgnfgSJfzWxLIr6QXjhIh3l/te4ISPmWuOJdMmV3RGGu7ppLsBrA6u662IQB9BQVhKerRLGWYuZaZvU4BbCgsOAlgJfyQtqmH1fwlcV+20u16S6TMAdnO+X+bBH/fqZ8FcFN2XW2Xn/sJKsJS1P6iobCgr6Gw4CsA7oOCDio/kd4oFYkDUtnCHaJZDog7THEOLbGKOOuHpvsA3JldV3tXdl2t6vvNA40mai9oKCz4PYDrAVzwtS2CLH9ffCeoCt7HKOhTNi5E9P4S8vlvOIIyAIuz62pV22ugNpqovcRpjZQD4Blf2vm6uKtUT7YMRYJSCCV9ylyxY52whJWZhLQDKASwKruuVs11cNXRRO0DDYUFPQ2FBd8F8HkAjd608TPp5YB4j3mC0j5l42HWU3RVBlX42MwJAGuz62p/PhEft0cSlqIezVKGiL5IRI0AVgHYSUSKpdk5fcVzAPzFk+tuED6piKXBgPmPuUu8bA9ohtjTNwqZ7N0chR3AHwAsyq6rPaRwWCGLpHYA/oCZ7xjjpTf81WdDYUE3gO+k37/zrwD+C4DR1TW/1T0blEXL42U5oO+LlkRKbU3AoeQurPTgsvcA3JddV+vWMiMRPQvgFgCtzJwz4rV74SipM4WZVbVdUoKwvFOribMo3yIA34PDN3pUFlH9ianU5fYmmECSYA+sqAHg2c8J7pozVAO4Mbuu9mZ3Be3kOYxSDoeI0gDcAOC8B20FNZqo/UBDYYG9obDgKQBzATwEYGjkOY/qnmgPeGBu4g+fMleUzxHyhnQYz+2zBY4PykXZdbUfetr+OOVw/gDg3xC43W1+RxO1H2koLOhtKCz4dwBZcNwpbACQTk0XMumSaumVrvCXT5kr3lgljPZBNwjgtwDmZNfVPpVdV6vYGjoRfQHARWZ2q05WqKCJOgA0FBacbygs+DaAOQD+/HvdE/VEENWOayz85VPmirdX0nKZcKX+VSeA3wGYnV1X+6vsulpFzRWIKAqOai2/VrLdYICYw+apI3QwxU+FI/vrRwCmqhzNNTSLYvPnZs5IUaPv771rf+P6St4L4JnsulpF87qJKB3AO8ycQ0RGALvwWQpoKoBLAJYzc7OS/QYaTdRqYoo3wOG0cg+AXHWD+Yxeot7V6WmBXD9nAB8AeBzAu9V3VvtlR9twUY/yWgOApeEw+62JOlgwxS8DcJvza46aociAnJcxMxBDszo4EmSer76z2tNaVx7h3LuwEcBkOCbdHmDmZ4a93gBN1Bp+wxSfB4e4vwRAlewtY3paP4j84Sx6HA4hv1J9Z3VI1DMLNTRRBzum+Gx8dgfPD1S3eelprTKREuN9hmNt+XU4hHxcgTY1xkETdShhis8EcCOAFXDkds8F4JctnYvT0xqsjjGop9jhMJPYB2AvgKLqO6tD/pE2lNBEHcqY4hPhcGRZBse21BwA86DA9t/ls1LrBgXBVdmfbgCnAZwCUAnHfvsj1XdWB5O394RDE3W4YYrXA5gPx1h8CoBJAJKcXyN/TsC1exUYgHlj2oxP2iVxOhzrxV1wTC6dGv5VfWd1GzSCDk3UExlTPMEhbB0AM4AhmLr9bjqo4V80UWtohBnaNlENvzOGZfN/ElEVEVUQ0YdENF3NGMMJTdRBxhgCeJSI6pwieIOIElQM0Ruew7Vpj48ycy4z5wN4B2G4B1stNFEHH8/hWgF8BCCHmXMBnATw80AH5QtjWDb3DPs1GmGU+qg2Yel8Esow8z4asT7MzMPzhw/BsdMs5CGiBwF8E46lsU0qhxM2aHfq0OM7cFj5hDzM/AtmTgPwIoAfqx1PuKCJOoQgol/AYbTwotqxKMyLcGyD1VAATdQhAhF9Cw7jvK9zGKxDEtHcYb9+AY6MLQ0F0MbUIQAR3QSHj9YGZlajrrNPDE97dNo0PwDgZiLKgqNM8DkAP1AvwvBC23wSZIyW9wvHbLcBwBUPr0PMrIlAY1Q0UWtohBnamFpDI8zQRK2hEWZootbQCDM0UWtohBmaqDU0wgxN1BoaYYYmag2NMEMTtYZGmKGJWkMjzNBEraERZmii1tAIMzRRa2iEGZqoNTTCDE3UGhphhiZqDY0wQxO1hkaYoYlaQyPM+P+k2CyaLx5aeQAAAABJRU5ErkJggg==\n", 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" ] @@ -962,15 +962,15 @@ { "cell_type": "code", "execution_count": 29, - "id": "edb7b3d8", + "id": "419d603a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 206 ms, sys: 23.9 ms, total: 230 ms\n", - "Wall time: 229 ms\n" + "CPU times: user 355 ms, sys: 13 ms, total: 368 ms\n", + "Wall time: 367 ms\n" ] } ], @@ -988,7 +988,7 @@ { "cell_type": "code", "execution_count": 30, - "id": "4dfb1c95", + "id": "da224750", "metadata": {}, "outputs": [], "source": [ @@ -1005,17 +1005,17 @@ { "cell_type": "code", "execution_count": 31, - "id": "02a4352e", + "id": "073c2c51", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "(59496, 5, 408)\n", - "(59496, 16)\n", - "(54212, 5, 408)\n", - "(54212, 16)\n" + "(57800, 5, 336)\n", + "(57800, 16)\n", + "(37106, 5, 336)\n", + "(37106, 16)\n" ] } ], @@ -1028,7 +1028,7 @@ }, { "cell_type": "markdown", - "id": "047824bd", + "id": "cee9b1c3", "metadata": {}, "source": [ "# Building Model" @@ -1037,7 +1037,7 @@ { "cell_type": "code", "execution_count": 32, - "id": "c75e2dfb", + "id": "75c9ba6d", "metadata": {}, "outputs": [], "source": [ @@ -1082,7 +1082,7 @@ { "cell_type": "code", "execution_count": 33, - "id": "614e0dd3", + "id": "8f71c4bf", "metadata": {}, "outputs": [], "source": [ @@ -1115,172 +1115,44 @@ { "cell_type": "code", "execution_count": 34, - "id": "e68a9c14", + "id": "77e0fc90", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ + "Loaded weights...\n", "Model: \"sequential\"\n", "_________________________________________________________________\n", "Layer (type) Output Shape Param # \n", "=================================================================\n", - "flatten (Flatten) (None, 2040) 0 \n", + "flatten (Flatten) (None, 1680) 0 \n", "_________________________________________________________________\n", - "dropout_10.0 (Dropout) (None, 2040) 0 \n", + "dropout_10.0 (Dropout) (None, 1680) 0 \n", "_________________________________________________________________\n", - "batchNorm (BatchNormalizatio (None, 2040) 8160 \n", + "batchNorm (BatchNormalizatio (None, 1680) 6720 \n", "_________________________________________________________________\n", - "HiddenDropout_20 (Dropout) (None, 2040) 0 \n", + "HiddenDropout_20 (Dropout) (None, 1680) 0 \n", "_________________________________________________________________\n", - "Hidden_2 (Dense) (None, 226) 461266 \n", + "Hidden_2 (Dense) (None, 186) 312666 \n", "_________________________________________________________________\n", - "HiddenDropout_30 (Dropout) (None, 226) 0 \n", + "HiddenDropout_30 (Dropout) (None, 186) 0 \n", "_________________________________________________________________\n", - "Hidden_3 (Dense) (None, 75) 17025 \n", + "Hidden_3 (Dense) (None, 62) 11594 \n", "_________________________________________________________________\n", - "HiddenDropout_40 (Dropout) (None, 75) 0 \n", + "HiddenDropout_40 (Dropout) (None, 62) 0 \n", "_________________________________________________________________\n", - "Hidden_4 (Dense) (None, 25) 1900 \n", + "Hidden_4 (Dense) (None, 20) 1260 \n", "_________________________________________________________________\n", - "Output (Dense) (None, 16) 416 \n", + "Output (Dense) (None, 16) 336 \n", "=================================================================\n", - "Total params: 488,767\n", - "Trainable params: 484,687\n", - "Non-trainable params: 4,080\n", + "Total params: 332,576\n", + "Trainable params: 329,216\n", + "Non-trainable params: 3,360\n", "_________________________________________________________________\n", - "Epoch 1/50\n", - "1860/1860 - 9s - loss: 1.1439 - acc: 0.8277 - val_loss: 4.1534 - val_acc: 0.3367\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 2/50\n", - "1860/1860 - 8s - loss: 0.6508 - acc: 0.9432 - val_loss: 4.2615 - val_acc: 0.3517\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 3/50\n", - "1860/1860 - 8s - loss: 0.5574 - acc: 0.9578 - val_loss: 4.6319 - val_acc: 0.3213\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 4/50\n", - "1860/1860 - 8s - loss: 0.5164 - acc: 0.9626 - val_loss: 4.2537 - val_acc: 0.3229\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 5/50\n", - "1860/1860 - 8s - loss: 0.4962 - acc: 0.9650 - val_loss: 4.4670 - val_acc: 0.2816\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 6/50\n", - "1860/1860 - 8s - loss: 0.4865 - acc: 0.9677 - val_loss: 4.2317 - val_acc: 0.3228\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 7/50\n", - "1860/1860 - 8s - loss: 0.4641 - acc: 0.9696 - val_loss: 4.2347 - val_acc: 0.3028\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 8/50\n", - "1860/1860 - 8s - loss: 0.4593 - acc: 0.9693 - val_loss: 4.3525 - val_acc: 0.3061\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 9/50\n", - "1860/1860 - 8s - loss: 0.4479 - acc: 0.9708 - val_loss: 4.7173 - val_acc: 0.2928\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 10/50\n", - "1860/1860 - 8s - loss: 0.4377 - acc: 0.9709 - val_loss: 4.3594 - val_acc: 0.3111\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 11/50\n", - "1860/1860 - 8s - loss: 0.4305 - acc: 0.9712 - val_loss: 4.4137 - val_acc: 0.3213\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 12/50\n", - "1860/1860 - 8s - loss: 0.4305 - acc: 0.9712 - val_loss: 4.5386 - val_acc: 0.2677\n", - "Epoch 13/50\n", - "1860/1860 - 8s - loss: 0.4223 - acc: 0.9718 - val_loss: 4.2520 - val_acc: 0.2910\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 14/50\n", - "1860/1860 - 8s - loss: 0.4124 - acc: 0.9726 - val_loss: 4.0999 - val_acc: 0.3237\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 15/50\n", - "1860/1860 - 8s - loss: 0.4133 - acc: 0.9716 - val_loss: 4.8021 - val_acc: 0.2812\n", - "Epoch 16/50\n", - "1860/1860 - 8s - loss: 0.4052 - acc: 0.9730 - val_loss: 4.3781 - val_acc: 0.3171\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 17/50\n", - "1860/1860 - 8s - loss: 0.4016 - acc: 0.9715 - val_loss: 4.3116 - val_acc: 0.3006\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 18/50\n", - "1860/1860 - 8s - loss: 0.4027 - acc: 0.9730 - val_loss: 4.3661 - val_acc: 0.3093\n", - "Epoch 19/50\n", - "1860/1860 - 8s - loss: 0.3926 - acc: 0.9735 - val_loss: 4.4316 - val_acc: 0.3270\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 20/50\n", - "1860/1860 - 8s - loss: 0.3937 - acc: 0.9735 - val_loss: 4.3595 - val_acc: 0.3323\n", - "Epoch 21/50\n", - "1860/1860 - 8s - loss: 0.3894 - acc: 0.9726 - val_loss: 4.1465 - val_acc: 0.3015\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 22/50\n", - "1860/1860 - 8s - loss: 0.3807 - acc: 0.9748 - val_loss: 4.4357 - val_acc: 0.2999\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 23/50\n", - "1860/1860 - 8s - loss: 0.3821 - acc: 0.9742 - val_loss: 4.2996 - val_acc: 0.2980\n", - "Epoch 24/50\n", - "1860/1860 - 8s - loss: 0.3816 - acc: 0.9733 - val_loss: 4.3006 - val_acc: 0.3003\n", - "Epoch 25/50\n", - "1860/1860 - 8s - loss: 0.3813 - acc: 0.9738 - val_loss: 4.3178 - val_acc: 0.3021\n", - "Epoch 26/50\n", - "1860/1860 - 8s - loss: 0.3837 - acc: 0.9734 - val_loss: 4.1520 - val_acc: 0.3249\n", - "Epoch 27/50\n", - "1860/1860 - 8s - loss: 0.3731 - acc: 0.9738 - val_loss: 4.3379 - val_acc: 0.3001\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 28/50\n", - "1860/1860 - 8s - loss: 0.3770 - acc: 0.9740 - val_loss: 4.2641 - val_acc: 0.2848\n", - "Epoch 29/50\n", - "1860/1860 - 8s - loss: 0.3732 - acc: 0.9745 - val_loss: 4.4376 - val_acc: 0.2973\n", - "Epoch 30/50\n", - "1860/1860 - 8s - loss: 0.3661 - acc: 0.9754 - val_loss: 4.5851 - val_acc: 0.2762\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 31/50\n", - "1860/1860 - 8s - loss: 0.3703 - acc: 0.9746 - val_loss: 4.4630 - val_acc: 0.2816\n", - "Epoch 32/50\n", - "1860/1860 - 8s - loss: 0.3776 - acc: 0.9736 - val_loss: 4.3901 - val_acc: 0.2840\n", - "Epoch 33/50\n", - "1860/1860 - 8s - loss: 0.3629 - acc: 0.9757 - val_loss: 4.2703 - val_acc: 0.2749\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 34/50\n", - "1860/1860 - 8s - loss: 0.3709 - acc: 0.9744 - val_loss: 4.6455 - val_acc: 0.2860\n", - "Epoch 35/50\n", - "1860/1860 - 8s - loss: 0.3628 - acc: 0.9753 - val_loss: 4.5363 - val_acc: 0.3022\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 36/50\n", - "1860/1860 - 8s - loss: 0.3589 - acc: 0.9757 - val_loss: 4.0942 - val_acc: 0.3210\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 37/50\n", - "1860/1860 - 8s - loss: 0.3658 - acc: 0.9743 - val_loss: 4.4832 - val_acc: 0.2863\n", - "Epoch 38/50\n", - "1860/1860 - 8s - loss: 0.3729 - acc: 0.9739 - val_loss: 3.9867 - val_acc: 0.3346\n", - "Epoch 39/50\n", - "1860/1860 - 8s - loss: 0.3619 - acc: 0.9749 - val_loss: 4.2968 - val_acc: 0.2802\n", - "Epoch 40/50\n", - "1860/1860 - 8s - loss: 0.3606 - acc: 0.9759 - val_loss: 4.1525 - val_acc: 0.2883\n", - "Epoch 41/50\n", - "1860/1860 - 8s - loss: 0.3602 - acc: 0.9743 - val_loss: 4.2747 - val_acc: 0.2978\n", - "Epoch 42/50\n", - "1860/1860 - 8s - loss: 0.2673 - acc: 0.9859 - val_loss: 3.9356 - val_acc: 0.3196\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 43/50\n", - "1860/1860 - 8s - loss: 0.2155 - acc: 0.9865 - val_loss: 4.2117 - val_acc: 0.2991\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 44/50\n", - "1860/1860 - 8s - loss: 0.2059 - acc: 0.9860 - val_loss: 3.9830 - val_acc: 0.3013\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 45/50\n", - "1860/1860 - 8s - loss: 0.2032 - acc: 0.9851 - val_loss: 3.9253 - val_acc: 0.3093\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 46/50\n", - "1860/1860 - 8s - loss: 0.1954 - acc: 0.9858 - val_loss: 4.0545 - val_acc: 0.3242\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 47/50\n", - "1860/1860 - 8s - loss: 0.1898 - acc: 0.9867 - val_loss: 4.2185 - val_acc: 0.3063\n", - "INFO:tensorflow:Assets written to: training_JNY/cp.ckpt/assets\n", - "Epoch 48/50\n", - "1860/1860 - 8s - loss: 0.1980 - acc: 0.9855 - val_loss: 4.1222 - val_acc: 0.3030\n", - "Epoch 49/50\n", - "1860/1860 - 8s - loss: 0.1943 - acc: 0.9862 - val_loss: 4.0228 - val_acc: 0.3137\n", - "Epoch 50/50\n", - "1860/1860 - 8s - loss: 0.1900 - acc: 0.9871 - val_loss: 4.0491 - val_acc: 0.3201\n", - "CPU times: user 10min 53s, sys: 53.9 s, total: 11min 47s\n", - "Wall time: 7min 10s\n" + "CPU times: user 80.5 ms, sys: 3.3 ms, total: 83.8 ms\n", + "Wall time: 79.5 ms\n" ] } ], @@ -1298,7 +1170,7 @@ }, { "cell_type": "markdown", - "id": "ee1e64d5", + "id": "f2e6f8ad", "metadata": {}, "source": [ "# Eval" @@ -1307,7 +1179,7 @@ { "cell_type": "code", "execution_count": 35, - "id": "5c22d6a0", + "id": "b7ede2b1", "metadata": {}, "outputs": [], "source": [ @@ -1326,21 +1198,21 @@ { "cell_type": "code", "execution_count": 36, - "id": "830cd599", + "id": "a71bb247", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 3.76 s, sys: 476 ms, total: 4.23 s\n", - "Wall time: 2.89 s\n" + "CPU times: user 3.36 s, sys: 529 ms, total: 3.89 s\n", + "Wall time: 2.95 s\n" ] }, { "data": { "text/plain": [ - "(42, 42)" + "(43, 43)" ] }, "execution_count": 36, @@ -1360,21 +1232,21 @@ { "cell_type": "code", "execution_count": 37, - "id": "f5adf4c0", + "id": "ab3ecfc9", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 4.22 s, sys: 425 ms, total: 4.64 s\n", - "Wall time: 3.19 s\n" + "CPU times: user 3.85 s, sys: 448 ms, total: 4.3 s\n", + "Wall time: 2.99 s\n" ] }, { "data": { "text/plain": [ - "(48, 48)" + "(47, 47)" ] }, "execution_count": 37, @@ -1395,7 +1267,7 @@ { "cell_type": "code", "execution_count": 38, - "id": "8a214570", + "id": "ac226caa", "metadata": {}, "outputs": [ { @@ -1417,12 +1289,12 @@ { "cell_type": "code", "execution_count": 39, - "id": "934fdadf", + "id": "3c3bac5d", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -1438,29 +1310,29 @@ "text": [ " precision recall f1-score support\n", "\n", - " 1 0.50 0.67 0.57 3\n", - " 2 0.00 0.00 0.00 2\n", - " 3 0.25 0.67 0.36 3\n", + " 1 1.00 0.67 0.80 3\n", + " 2 0.00 0.00 0.00 1\n", + " 3 0.43 1.00 0.60 3\n", " 4 0.00 0.00 0.00 0\n", - " 5 1.00 0.50 0.67 2\n", - " 6 0.00 0.00 0.00 3\n", - " 7 0.17 0.33 0.22 3\n", - " 8 0.00 0.00 0.00 2\n", - " 9 0.50 0.67 0.57 3\n", - " 10 0.00 0.00 0.00 3\n", + " 5 0.00 0.00 0.00 3\n", + " 6 0.50 0.33 0.40 3\n", + " 7 1.00 1.00 1.00 3\n", + " 8 1.00 0.33 0.50 3\n", + " 9 0.00 0.00 0.00 3\n", + " 10 0.40 0.67 0.50 3\n", " 11 0.00 0.00 0.00 3\n", - " 12 0.00 0.00 0.00 3\n", - " 13 0.00 0.00 0.00 3\n", + " 12 0.60 1.00 0.75 3\n", + " 13 0.75 1.00 0.86 3\n", " 14 0.00 0.00 0.00 3\n", - " 15 0.50 0.67 0.57 3\n", - " 16 0.60 1.00 0.75 3\n", + " 15 0.00 0.00 0.00 3\n", + " 16 0.50 1.00 0.67 3\n", "\n", - " accuracy 0.31 42\n", - " macro avg 0.22 0.28 0.23 42\n", - "weighted avg 0.23 0.31 0.25 42\n", + " accuracy 0.49 43\n", + " macro avg 0.39 0.44 0.38 43\n", + "weighted avg 0.43 0.49 0.42 43\n", "\n", - "CPU times: user 648 ms, sys: 205 ms, total: 853 ms\n", - "Wall time: 623 ms\n" + "CPU times: user 646 ms, sys: 195 ms, total: 840 ms\n", + "Wall time: 610 ms\n" ] } ], @@ -1490,34 +1362,9 @@ { "cell_type": "code", "execution_count": 40, - "id": "6fc6759c", + "id": "43acba77", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "def plot_keras_history(history, name='', acc='acc'):\n", " \"\"\"Plots keras history.\"\"\"\n", @@ -1551,14 +1398,14 @@ { "cell_type": "code", "execution_count": 41, - "id": "07eaedf6", + "id": "af999e08", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Scenario: JNY\n", + "Scenario: SYN\n", "Window Size: 5\n", "Strides: 1\n", "Epochs: 50\n", @@ -1580,11 +1427,13 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "a8f8bfde", + "execution_count": 42, + "id": "b16af0c6", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "exit()" + ] } ], "metadata": {