{ "cells": [ { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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SparkSession - hive

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SparkContext

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v2.3.4
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AppName
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pyspark-shell
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\n", " " ], "text/plain": [ "" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from pyspark.sql import SparkSession\n", "spark = SparkSession.builder.getOrCreate()\n", "spark" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[Row(AVGHEARTBEATSPERMIN=93, PALPITATIONSPERDAY=22, CHOLESTEROL=163, BMI=25, HEARTFAILURE='N', AGE=49, SEX='F', FAMILYHISTORY='N', SMOKERLAST5YRS='N', EXERCISEMINPERWEEK=110),\n", " Row(AVGHEARTBEATSPERMIN=108, PALPITATIONSPERDAY=22, CHOLESTEROL=181, BMI=24, HEARTFAILURE='N', AGE=32, SEX='F', FAMILYHISTORY='N', SMOKERLAST5YRS='N', EXERCISEMINPERWEEK=192),\n", " Row(AVGHEARTBEATSPERMIN=86, PALPITATIONSPERDAY=0, CHOLESTEROL=239, BMI=20, HEARTFAILURE='N', AGE=60, SEX='F', FAMILYHISTORY='N', SMOKERLAST5YRS='N', EXERCISEMINPERWEEK=121),\n", " Row(AVGHEARTBEATSPERMIN=80, PALPITATIONSPERDAY=36, CHOLESTEROL=164, BMI=31, HEARTFAILURE='Y', AGE=45, SEX='F', FAMILYHISTORY='Y', SMOKERLAST5YRS='N', EXERCISEMINPERWEEK=141),\n", " Row(AVGHEARTBEATSPERMIN=66, PALPITATIONSPERDAY=36, CHOLESTEROL=185, BMI=23, HEARTFAILURE='N', AGE=39, SEX='F', FAMILYHISTORY='N', SMOKERLAST5YRS='N', EXERCISEMINPERWEEK=63)]" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\n", "import ibmos2spark\n", "# @hidden_cell\n", "credentials = {\n", " 'endpoint': 'https://s3-api.us-geo.objectstorage.service.networklayer.com',\n", " 'service_id': 'iam-ServiceId-56ce77ac-9d82-41cc-96e9-1a4689ce5806',\n", " 'iam_service_endpoint': 'https://iam.bluemix.net/oidc/token',\n", " 'api_key': 'fwcL_7HeZADPUr-jsL5P7scQbjmaoY0H3dqqC3Bsp9_5'\n", "}\n", "\n", "configuration_name = 'os_a2d5a67716ea4f0db7f2711634a21cc0_configs'\n", "cos = ibmos2spark.CloudObjectStorage(sc, credentials, configuration_name, 'bluemix_cos')\n", "\n", "from pyspark.sql import SparkSession\n", "spark = SparkSession.builder.getOrCreate()\n", "df_data_1 = spark.read\\\n", " .format('org.apache.spark.sql.execution.datasources.csv.CSVFileFormat')\\\n", " .option('header', 'true')\\\n", " .option('inferSchema', 'true')\\\n", " .load(cos.url('patientdataV6-1.csv', 'heartfailure-donotdelete-pr-iafaq9zj55qih4'))\n", "df_data_1.take(5)\n" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "root\n", " |-- AVGHEARTBEATSPERMIN: integer (nullable = true)\n", " |-- PALPITATIONSPERDAY: integer (nullable = true)\n", " |-- CHOLESTEROL: integer (nullable = true)\n", " |-- BMI: integer (nullable = true)\n", " |-- HEARTFAILURE: string (nullable = true)\n", " |-- AGE: integer (nullable = true)\n", " |-- SEX: string (nullable = true)\n", " |-- FAMILYHISTORY: string (nullable = true)\n", " |-- SMOKERLAST5YRS: string (nullable = true)\n", " |-- EXERCISEMINPERWEEK: integer (nullable = true)\n", "\n" ] } ], "source": [ "df_data_1.printSchema()" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "+-------------------+------------------+-----------+---+------------+---+---+-------------+--------------+------------------+\n", "|AVGHEARTBEATSPERMIN|PALPITATIONSPERDAY|CHOLESTEROL|BMI|HEARTFAILURE|AGE|SEX|FAMILYHISTORY|SMOKERLAST5YRS|EXERCISEMINPERWEEK|\n", "+-------------------+------------------+-----------+---+------------+---+---+-------------+--------------+------------------+\n", "| 93| 22| 163| 25| N| 49| F| N| N| 110|\n", "| 108| 22| 181| 24| N| 32| F| N| N| 192|\n", "| 86| 0| 239| 20| N| 60| F| N| N| 121|\n", "| 80| 36| 164| 31| Y| 45| F| Y| N| 141|\n", "| 66| 36| 185| 23| N| 39| F| N| N| 63|\n", "| 125| 27| 201| 31| N| 47| M| N| N| 13|\n", "| 83| 27| 169| 20| N| 71| F| Y| N| 124|\n", "| 107| 31| 199| 32| N| 55| F| N| N| 22|\n", "| 92| 28| 174| 22| N| 44| F| N| N| 107|\n", "| 84| 12| 206| 25| N| 50| M| N| N| 199|\n", "| 60| 1| 194| 28| N| 71| M| N| N| 27|\n", "| 134| 7| 228| 34| Y| 63| F| Y| N| 92|\n", "| 103| 0| 237| 24| N| 64| F| Y| N| 34|\n", "| 101| 39| 157| 20| N| 49| M| N| N| 33|\n", "| 92| 2| 169| 26| N| 36| M| N| N| 217|\n", "| 80| 27| 234| 27| N| 50| M| N| N| 28|\n", "| 82| 14| 155| 30| N| 70| F| N| N| 207|\n", "| 63| 9| 204| 26| N| 42| M| N| N| 88|\n", "| 83| 12| 209| 29| N| 38| M| Y| N| 220|\n", "| 80| 37| 157| 20| N| 48| M| N| N| 54|\n", "+-------------------+------------------+-----------+---+------------+---+---+-------------+--------------+------------------+\n", "only showing top 20 rows\n", "\n" ] } ], "source": [ "\n", "\n", "df_data_1.show()\n", "\n" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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AVGHEARTBEATSPERMINPALPITATIONSPERDAYCHOLESTEROLBMIHEARTFAILURESEX
0932216325NF
11082218124NF
286023920NF
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" ], "text/plain": [ " AVGHEARTBEATSPERMIN PALPITATIONSPERDAY CHOLESTEROL BMI HEARTFAILURE SEX\n", "0 93 22 163 25 N F\n", "1 108 22 181 24 N F\n", "2 86 0 239 20 N F\n", "3 80 36 164 31 Y F\n", "4 66 36 185 23 N F" ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_data_1.select(\"AVGHEARTBEATSPERMIN\", \"PALPITATIONSPERDAY\",\"CHOLESTEROL\",\"BMI\",\"HEARTFAILURE\",\"SEX\").toPandas().head()" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "+-------+-------------------+------------------+------------------+------------------+------------+------------------+-----+-------------+--------------+------------------+\n", "|summary|AVGHEARTBEATSPERMIN|PALPITATIONSPERDAY| CHOLESTEROL| BMI|HEARTFAILURE| AGE| SEX|FAMILYHISTORY|SMOKERLAST5YRS|EXERCISEMINPERWEEK|\n", "+-------+-------------------+------------------+------------------+------------------+------------+------------------+-----+-------------+--------------+------------------+\n", "| count| 10800| 10800| 10800| 10800| 10800| 10800|10800| 10800| 10800| 10800|\n", "| mean| 87.11509259259259|20.423148148148147|195.08027777777778| 26.35972222222222| null|49.965185185185184| null| null| null|119.72953703703703|\n", "| stddev| 19.744375148984474|12.165320351622993|26.136731865042325|3.8201472810942136| null|13.079280962015586| null| null| null| 71.14706006382843|\n", "| min| 48| 0| 150| 20| N| 28| F| N| N| 0|\n", "| max| 161| 45| 245| 34| Y| 72| M| Y| Y| 250|\n", "+-------+-------------------+------------------+------------------+------------------+------------+------------------+-----+-------------+--------------+------------------+\n", "\n" ] } ], "source": [ "df_data_1.describe().show()" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "10800" ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\n", "\n", "df_data_1.count()\n", "\n" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [], "source": [ "import pixiedust\n", "\n" ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Collecting pixiedust\n", "Collecting mpld3 (from pixiedust)\n", "Collecting requests (from pixiedust)\n", " Using cached https://files.pythonhosted.org/packages/1a/70/1935c770cb3be6e3a8b78ced23d7e0f3b187f5cbfab4749523ed65d7c9b1/requests-2.23.0-py2.py3-none-any.whl\n", "Collecting astunparse (from pixiedust)\n", " Using cached https://files.pythonhosted.org/packages/2b/03/13dde6512ad7b4557eb792fbcf0c653af6076b81e5941d36ec61f7ce6028/astunparse-1.6.3-py2.py3-none-any.whl\n", "Collecting geojson (from pixiedust)\n", " Using cached 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but you'll have urllib3 1.25.9 which is incompatible.\u001b[0m\n", "Installing collected packages: mpld3, idna, chardet, urllib3, certifi, requests, wheel, six, astunparse, geojson, colour, setuptools, markdown, lxml, pixiedust\n", "Successfully installed astunparse-1.6.3 certifi-2020.4.5.1 chardet-3.0.4 colour-0.1.5 geojson-2.5.0 idna-2.9 lxml-4.5.0 markdown-3.2.1 mpld3-0.3 pixiedust-1.1.18 requests-2.23.0 setuptools-46.1.3 six-1.14.0 urllib3-1.25.9 wheel-0.34.2\n" ] } ], "source": [ "!pip install --upgrade pixiedust\n", "import pixiedust" ] }, { "cell_type": "code", "execution_count": 49, "metadata": { "pixiedust": { "displayParams": { "handlerId": "tableView" } } }, "outputs": [ { "data": { "text/html": [ "
Hey, there's something awesome here! To see it, open this notebook outside GitHub, in a viewer like Jupyter
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Field types:
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AVGHEARTBEATSPERMIN: int32
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PALPITATIONSPERDAY: int32
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CHOLESTEROL: int32
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BMI: int32
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HEARTFAILURE: object
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AGE: int32
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SEX: object
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FAMILYHISTORY: object
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SMOKERLAST5YRS: object
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EXERCISEMINPERWEEK: int32
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AVGHEARTBEATSPERMIN
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PALPITATIONSPERDAY
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CHOLESTEROL
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BMI
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HEARTFAILURE
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AGE
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SEX
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FAMILYHISTORY
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SMOKERLAST5YRS
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EXERCISEMINPERWEEK
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AVGHEARTBEATSPERMIN
PALPITATIONSPERDAY
CHOLESTEROL
BMI
HEARTFAILURE
AGE
SEX
FAMILYHISTORY
SMOKERLAST5YRS
EXERCISEMINPERWEEK
922817422N44FNN107
841220625N50MNN199
78523325N53MNN204
110822728N53FYN39
971117032N38FNN222
821515426N46FNN227
883815422N47FNN204
1003021223N72MNN22
1001715332N49MNN244
82321827Y49FNN182
1053615732N66FYN5
1364223326N44MNN195
76320527N40MNN189
1402421624N66MYN104
1293815425N30FNN67
1241923727N29FNN96
1112020326N57FNN60
1053915030N43MNN135
792015823N67MNN166
1063720730N66FYN140
723015426N64MYY81
1162721529N36MNN150
1191622021N32MNN226
662223721N40MNN148
642818029N45FNN113
943822128N72MNN123
893919425Y32MNN83
1261022521N51MYN212
982420528N60FNN135
942222822N59FNN24
1001821220N37FNN221
89422731N72MYN78
692618420N68FNN37
874021928N37MYN103
1204423034Y38FYY0
1001316530N34MNN35
792723329N29MNN177
932517727N29FNN242
81418221N65MNN149
793419128N72FYN194
973620627Y42MYN116
862017126N41MNN187
1072015931N61MNN52
991116321N57MNN98
122622623N45MNN229
541221529N49FNN178
652122026N40FNN82
902818122N30FNN92
91518231N59MYN36
1263018930N58FNN58
952319721N32MNN165
88218022N63MNN141
661415024N43FNN124
844020130N56MNN118
1051919131Y52MYN3
89115428N53MNN206
68720932N44FNN99
693418829N46FNN208
752020323N70MYN191
104022025N48MNN5
94819222N61FNN218
1294319733Y30FNN139
903616021N56FNN135
1151716423N44MNN204
573516821N53FNN164
111315227N34FNN226
1103623227N57FNN153
1053621824N58FNN124
1072420427N39FNN103
803617225N54MNN214
75423427N72MNN7
81018624N69FNN10
603818523N30MNN238
932419922Y65MYN39
1072921124N66MNN66
1013915929N50FNN229
863823331N49MNY69
1083718030N61MNN194
1061721631N69MNY58
943218423N53MYN210
804023828N40MNN128
1024523228Y43MYN20
681223322N33FNN135
604322423Y29MNN16
924216723Y55MYN59
87620923N42FNN27
1163019228N70MNN121
77521723N41MNN137
741115229N39MNN142
792623626N33FNN220
941615232N48FNN112
753118223N62FNN189
1013620529Y40MNN60
67617729Y42MNN61
683917928N31MNN26
932117523N70FNN73
84119029N72FNN97
1113520025Y34FYN52
823416525N63FNN53
82218232N53FNN44
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" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "display(df_data_1)" ] }, { "cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of training records: 8637\n", "Number of testing records : 2163\n" ] } ], "source": [ "split_data = df_data_1.randomSplit([0.8, 0.20], 24)\n", "train_data = split_data[0]\n", "test_data = split_data[1]\n", "\n", "print(\"Number of training records: \" + str(train_data.count()))\n", "print(\"Number of testing records : \" + str(test_data.count()))" ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [], "source": [ "from pyspark.ml.feature import StringIndexer, IndexToString, VectorAssembler\n", "from pyspark.ml.classification import RandomForestClassifier, LogisticRegression, NaiveBayes\n", "from pyspark.ml.evaluation import MulticlassClassificationEvaluator\n", "from pyspark.ml import Pipeline, Model" ] }, { "cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [], "source": [ "stringIndexer_label = StringIndexer(inputCol=\"HEARTFAILURE\", outputCol=\"label\").fit(df_data_1)\n", "stringIndexer_sex = StringIndexer(inputCol=\"SEX\", outputCol=\"SEX_IX\")\n", "stringIndexer_famhist = StringIndexer(inputCol=\"FAMILYHISTORY\", outputCol=\"FAMILYHISTORY_IX\")\n", "stringIndexer_smoker = StringIndexer(inputCol=\"SMOKERLAST5YRS\", outputCol=\"SMOKERLAST5YRS_IX\")" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [], "source": [ "rf = RandomForestClassifier(labelCol=\"label\", featuresCol=\"features\")\n", "lr = LogisticRegression()\n", "nb = NaiveBayes(smoothing=1.0)" ] }, { "cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [], "source": [ "labelConverter = IndexToString(inputCol=\"prediction\", outputCol=\"predictedLabel\", labels=stringIndexer_label.labels)" ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "+-------------------+------------------+-----------+---+------------+---+---+-------------+--------------+------------------+------+----------------+-----------------+--------------------+\n", "|AVGHEARTBEATSPERMIN|PALPITATIONSPERDAY|CHOLESTEROL|BMI|HEARTFAILURE|AGE|SEX|FAMILYHISTORY|SMOKERLAST5YRS|EXERCISEMINPERWEEK|SEX_IX|FAMILYHISTORY_IX|SMOKERLAST5YRS_IX| features|\n", "+-------------------+------------------+-----------+---+------------+---+---+-------------+--------------+------------------+------+----------------+-----------------+--------------------+\n", "| 93| 22| 163| 25| N| 49| F| N| N| 110| 1.0| 0.0| 0.0|[93.0,22.0,163.0,...|\n", "| 108| 22| 181| 24| N| 32| F| N| N| 192| 1.0| 0.0| 0.0|[108.0,22.0,181.0...|\n", "| 86| 0| 239| 20| N| 60| F| N| N| 121| 1.0| 0.0| 0.0|[86.0,0.0,239.0,2...|\n", "| 80| 36| 164| 31| Y| 45| F| Y| N| 141| 1.0| 1.0| 0.0|[80.0,36.0,164.0,...|\n", "| 66| 36| 185| 23| N| 39| F| N| N| 63| 1.0| 0.0| 0.0|[66.0,36.0,185.0,...|\n", "| 125| 27| 201| 31| N| 47| M| N| N| 13| 0.0| 0.0| 0.0|[125.0,27.0,201.0...|\n", "| 83| 27| 169| 20| N| 71| F| Y| N| 124| 1.0| 1.0| 0.0|[83.0,27.0,169.0,...|\n", "| 107| 31| 199| 32| N| 55| F| N| N| 22| 1.0| 0.0| 0.0|[107.0,31.0,199.0...|\n", "| 92| 28| 174| 22| N| 44| F| N| N| 107| 1.0| 0.0| 0.0|[92.0,28.0,174.0,...|\n", "| 84| 12| 206| 25| N| 50| M| N| N| 199| 0.0| 0.0| 0.0|[84.0,12.0,206.0,...|\n", "| 60| 1| 194| 28| N| 71| M| N| N| 27| 0.0| 0.0| 0.0|[60.0,1.0,194.0,2...|\n", "| 134| 7| 228| 34| Y| 63| F| Y| N| 92| 1.0| 1.0| 0.0|[134.0,7.0,228.0,...|\n", "| 103| 0| 237| 24| N| 64| F| Y| N| 34| 1.0| 1.0| 0.0|[103.0,0.0,237.0,...|\n", "| 101| 39| 157| 20| N| 49| M| N| N| 33| 0.0| 0.0| 0.0|[101.0,39.0,157.0...|\n", "| 92| 2| 169| 26| N| 36| M| N| N| 217| 0.0| 0.0| 0.0|[92.0,2.0,169.0,2...|\n", "| 80| 27| 234| 27| N| 50| M| N| N| 28| 0.0| 0.0| 0.0|[80.0,27.0,234.0,...|\n", "| 82| 14| 155| 30| N| 70| F| N| N| 207| 1.0| 0.0| 0.0|[82.0,14.0,155.0,...|\n", "| 63| 9| 204| 26| N| 42| M| N| N| 88| 0.0| 0.0| 0.0|[63.0,9.0,204.0,2...|\n", "| 83| 12| 209| 29| N| 38| M| Y| N| 220| 0.0| 1.0| 0.0|[83.0,12.0,209.0,...|\n", "| 80| 37| 157| 20| N| 48| M| N| N| 54| 0.0| 0.0| 0.0|[80.0,37.0,157.0,...|\n", "+-------------------+------------------+-----------+---+------------+---+---+-------------+--------------+------------------+------+----------------+-----------------+--------------------+\n", "only showing top 20 rows\n", "\n" ] } ], "source": [ "vectorAssembler_features = VectorAssembler(inputCols= [\"AVGHEARTBEATSPERMIN\",\"PALPITATIONSPERDAY\", \n", " \"CHOLESTEROL\",\"BMI\",\"AGE\",\"SEX_IX\",\"FAMILYHISTORY_IX\",\n", " \"SMOKERLAST5YRS_IX\",\"EXERCISEMINPERWEEK\"], outputCol=\"features\")\n", " \n", "transform_df_pipeline = Pipeline(stages=[stringIndexer_sex, stringIndexer_famhist, stringIndexer_smoker, vectorAssembler_features])\n", "transformed_df = transform_df_pipeline.fit(df_data_1).transform(df_data_1)\n", "transformed_df.show()" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [], "source": [ "pipeline1 = Pipeline(stages=[stringIndexer_label, stringIndexer_sex, \n", " stringIndexer_famhist, stringIndexer_smoker,\n", " vectorAssembler_features, rf, labelConverter])\n", "m1Name = \"Random Forest\"\n", "\n", "pipeline2 = Pipeline(stages=[stringIndexer_label, stringIndexer_sex,\n", " stringIndexer_famhist, stringIndexer_smoker,\n", " vectorAssembler_features, lr, labelConverter])\n", "m2Name = \"Logistic Regression\"\n", "\n", "pipeline3 = Pipeline(stages=[stringIndexer_label, stringIndexer_sex,\n", " stringIndexer_famhist, stringIndexer_smoker,\n", " vectorAssembler_features, nb, labelConverter])\n", "m3Name = \"Naive Bayes\"" ] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [], "source": [ "model1 = pipeline1.fit(train_data)\n", "model2 = pipeline2.fit(train_data)\n", "model3 = pipeline3.fit(train_data)" ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [], "source": [ "from pyspark.sql.types import Row\n", "import numpy as np\n", "def getCMEntries(threshold):\n", " newThresholdDF = spark.sql(\"select label, p1, prediction as oldPrediction,\"\n", " \" case when p1 > \" + str(threshold) + \" then 1.0 else 0.0 end as newPrediction\"\n", " \" from inputToThreshold\")\n", " newThresholdDF.registerTempTable(\"newThreshold\")\n", " \n", " # Here is an SQL query to find true positives\n", " tpA = spark.sql(\"SELECT * FROM newThreshold WHERE label = 1 AND newprediction = 1\")\n", " \n", " # Write an SQL query to find the number of false positives\n", " ### spark.sql(\"???\")\n", " fpA = spark.sql(\"SELECT * FROM newThreshold WHERE label = 0 AND newprediction = 1\")\n", " \n", " # Write an SQL query to find the number of false negatives\n", " ### spark.sql(\"???\")\n", " fnA = spark.sql(\"SELECT * FROM newThreshold WHERE label = 1 AND newprediction = 0\")\n", " \n", " # Write an SQL query to find the number of true negatives\n", " ### spark.sql(\"???\")\n", " tnA = spark.sql(\"SELECT * FROM newThreshold WHERE label = 0 AND newprediction = 0\")\n", " return (tpA.count(), fpA.count(), fnA.count(), tnA.count())" ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [], "source": [ "\n", "\n", "import numpy as np\n", "numBins = 10\n", "thresholds = np.array(range(0, numBins + 1))*1.0/numBins\n", "\n" ] }, { "cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [], "source": [ "def getModelThresholdStats(model_df, data):\n", " tp = np.array([i for i in range(0, numBins + 1 )])\n", " fp = np.array([i for i in range(0, numBins + 1 )])\n", " fn = np.array([i for i in range(0, numBins + 1 )])\n", " tn = np.array([i for i in range(0, numBins + 1 )])\n", " \n", " #generate dataframe to be used in thresholding:\n", " predictionsForROC = model_df.transform(data)\n", " predictionsForROC.registerTempTable(\"predictions\")\n", " columnsForCM = spark.sql(\"select probability, prediction, label from predictions\")\n", " extractedProbability = columnsForCM.rdd.map(lambda x: Row(p1 = np\n", " .asscalar(x[0][1]), prediction=x[1] , label=x[2])).toDF()\n", " extractedProbability.registerTempTable(\"inputToThreshold\")\n", " \n", " # get the total number of positives and negatives in the predictions dataset:\n", " ### p = spark.sql(\"???\").count()\n", " ### n = spark.sql(\"???\").count()\n", " p = spark.sql(\"SELECT * from predictions WHERE label = 1\").count()\n", " n = spark.sql(\"SELECT * from predictions WHERE label = 0\").count()\n", " \n", " # We know the number of true positives, etc. at the threshold edges:\n", " (tp[0],fp[0],fn[0],tn[0]) = (p, n, 0, 0)\n", " (tp[-1],fp[-1],fn[-1],tn[-1]) = (0, 0, p, n)\n", " \n", " for (i, threshold) in zip(range(0, numBins + 1),thresholds):\n", " print(i, threshold)\n", " if (i>0 and i" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { 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YTJLfS/LLdV3/YAbrAT4j/uCjkzl/abiYe7J9jCbhVXsbDHe2fzuZt6iY2t5X3rOoZVG+te5bxRwAAAAAAMA00bsFpt3uvmPF+LzmKl9dv7K8qa6TfQ2GOzd0JVV17bHRcOfjax7PPYvumVStAAAAAABwp830cGdyvUn4nSQtVVX9epLfqev6wsyWBdzNeho0CRfNa84XH1w+9uYznyQfvVXObewuhoeGh/LiwIvF3LMPPZuFLQvH/iYAAAAAAMDU07sFptWe/k+L8S+tXZGF85rLm47uS44PlHMdW679ePjM4bx39L3isq7WrknVCQAAAAAAU6Fphr9/9bjEOklzku4kv5nkUFVVf7+qqm/OWGXAXa2nr9wk/Nr6lZnXPM4fjft25vIfWwUdW4vhN4+8mWPnywOl3W3lgVAAAAAAAIBppHcLTLue/nIP9cn2VY03Nbq1M1XyyOZrTy/tf6nhKzav39wwBwAAAAAA02Umhzu/k+SfJbmYy43Cq5NSVZIVSf6TJN+vquonVVX9jaqq1s1MmcDdpq7r9DQ4AXbMJuFVe7eX46seTu7ZUExt7y/vWdi8MN9e9+3xvwkAAAAAADB19G6BaXf45PnsP3aumNvUtrrxxt4Gw53rnkgWX9+3c//O4rKOlR1pXd464ToBAAAAAGCqzNhwZ13X2+u6/m6StUn+cpJ3M/o02Fx5/lySX07SV1XVv62q6rtVVS2Y9oKBu0b/0bP55PSFYm5T+xhNwiQZHm58EuzG8g2cw/VwXux/sZj71rpvZfG8xWN/EwAAAAAAYArp3QIzoaevfCBvkmxqa3Ao7+CFpO/Vcm7Dlms/nrx4Mj88+MPisq7WrgnXCAAAAAAAU2kmb+5MktR1/Wld179a1/XXkjyZ5B8kOZnRzcIqSXOSrUn+SZJDVVX9g6qqvjkTNQNzW6NbO6sqebx15dibD76VnD1aznVsLYbf+fidfHzu42Kuu608EAoAAAAAADDd9G6B6dTTf6wYf/jeJblvWYO58YEfJJfOlnMd14c7v/fh9zJYDxaXda033AkAAAAAwOww48OdI9V1vaeu619I8mCSn03y8sj0ld+rJCuS/MdJvl9V1U+nt0pgrtvToEn4hQeWZ/nCeWNv3lu+gTPNC5L2bxdT2/q2FePzm+bn2YeeHft7AAAAAAAAM0DvFphqjW7ubHhrZ5L07ijHF6xI1nVee9y5f2dx2ZrFa/LoPY9OuEYAAAAAAJhKs2q486q6rs/Xdf1/1nW9OcnnkvwPSQ5m9ImwufK8ccRzkjxdVdWs/O8CZofdDZqEnWM1Ca/qbTDc2f5MMn/xTeHhejjb+7cXtzy97uksnb90/G8CAAAAAADMEL1bYCqcuTCYHx08WcyN2bfdVx7azCPPJs0tSZKLQxfz6oevFpd1re9KVVXFHAAAAAAATLdZ30ir63pfXdf/TZLWJP9ekt9NMpjLzcE615uD9ZXYP0lysKqqv1tV1dMzUDIwix0/ezG9R04Xc53t4wx3nj2WHOgp5zq2FsPvfvJuDp89XMy90PbC2N8DAAAAAACYRfRugTvlnf3HMzRcF3Od7avLm04dSg6/V85t2HLtxzcOvpGzg2eLy7pauyZVJwAAAAAATKVZP9x5VV3Xw3Vd/391Xf9MkoeS/NdJfpLLTcGRp8JWSe5L8heTvFpV1QdVVf1yVVWPzUTdwOyyp798a2cyRpPwqn07k3q4nOvoLoa395Vv7Wxpasnz658f+3sAAAAAAACzkN4tcLt295X7tqsWz8uG+5aUNzW6tTNJOq4Pd+7cX163bN6ydD7QOeEaAQAAAABgqs2Z4c6R6rr+uK7rX6nr+ktJnkny60nOZHSjMFee25L8jSTvVFX1+9NeLDCrNGoSPrhiYdatXDT25t4d5fjK1uTejTeF67rO9v7ycOfTa5/OsvnLxv4eAAAAAADALKd3C9yKnv5jxfimtlWpqqqYa9ivvfdzl3u2SYbr4by0/6XismfXP5t5TfMmWyoAAAAAAEyZOTncOVJd1z+o6/rnkzyY5M8n+UGunwhbZ3Sz8EszUiQwa+wZo0k4puHhpPfFcq6jOyk0GH909Ef56MxHxS3dbeWbPgEAAAAAAOYqvVtgIoaG67w1cLyY62xfXd40PJy8v6uc23D91s53P3k3n5z7pLisa33XpOoEAAAAAICpNueHO6+q6/pMXde/Vtf1M0keTfI/J/k415uFwGfchcGhvPPhiWLuyUZNwqsO/X5y5kg517G1GN7Wv60Yb6lasnn95rG/BwAAAAAAMEfp3QJj+emhUzl9YbCY62x0KO/Bt5OzR8u5juvDnTsHdhaXzG+an2fWPTOpOgEAAAAAYKrdNcOdI9V1/ZO6rv9qkoeS/Mkkv5dkaGarAmbaewdO5OLgcDE37s2djW7tbJ6fPPzsTeG6rrO9f3txyzce/EZWLFgx9vcAAAAAAADuAnq3wI16+o8V4/Obm/LYugZ91H07yvHmBUnb9aHNRsOd31z7zSyZt2RSdQIAAAAAwFRrmekCplJd14NJ/kWSf1FV1bokPzvDJQEzqKfv02J8yfzmfOGBZWNvbjTc2fpUsmDpTeGffvrT7D+1v7ilu6177G8BAAAAAADcZfRugasa9W2//NCKLJzXXN7UWx7aTNtTyfzFSZL3T7yfvpN9xWWb12+ebJkAAAAAADDl7urhzpHquj6Q5G/PdB3AzOnpLzcJn2hblZbmMS4yPnc82f/Dcq5jazG8rW9bMd5cNaertWvMOgEAAAAAAO5merfw2banQd+2s31VecP5E8n+N8q5DVuu/djo1s4qVZ5f//xkSgQAAAAAgGnxmRnunO2qqno4ydeSrE2yNMnBJP1JXqvr+tJM1gZ3g7quGzYJN7U1aBJe9f5LST1Uzm28+RbOuq6zvX97cXnnA51ZtXCc7wEAAAAAADAj9G1han10/FwOHD9XzHW2rS5v+uCVxv3ajuvDnbsGdhWXfPW+r+beRfdOqk4AAAAAAJgOhjtnWFVVfzLJf5XkqQZLjlVV9U+T/M26rj+ZvsrKqqpanOTdJI/ckPqNuq5/bvorgol5/5MzOXbmYjHXsEl4VW95UDPLH0ru+8JN4b3H96bvZF9xywttL4z9LQAAAAAAAKadvi1Mj54GB/ImYxzK27ujHF/2YLLm0STJkbNH8vuf/H5xWVdr16RqBAAAAACA6dI00wV8VlVVtbSqqt9K8s/TuEGYJKuT/EKS96qq+s60FDe2X87NDUKY9fb0lZuEzU1Vvta6svHGum7cLOzYklTVTeFGt3Y2VU0ahwAAAAAAALOIvi1Mrz19x4rxDZE3R4AAACAASURBVPctyeol829O1HWyr0G/dkPXtX7tS/tfavhNPVoAAAAAAGYrw50zoKqq5iT/NMl3b0h9nGRbLjcO30xSj8jdn+R3q6r61rQUWVBV1TeT/Bcz9X24HbsbNAm/+OCyLF0wxiXGh99LTh0s5zZ2F8Pb+8rDnZvu35R7F907Zp0AAAAAAABMD31bmH67GxzK29m2urzh6L7k+EA5t+H60ObOgZ3lJSs2pG1526RqBAAAAACA6WK4c2b8D0n+6IjnS0n+8yQP1XX9nbqu/3Rd15uSPJbkByPWLUjyO1VVPTh9pV5WVdX8JL+W6/+bOTXdNcDt2NM/ySbhVb0vluNNLcnDz90U3nd8X/ad2Ffc0t1WHgYFAAAAAABgRujbwjQ6fWEwPzl0spjb1L6qvKnRrZ2prg13nr54Om8ceqO4yq2dAAAAAADMZoY7p1lVVY8k+S9vCP+puq7/t7quL44M1nX9oyRbMrpReE+SX5zaKov+ZpJHr/zcn+QfzEANcEuOnr6Q9z85U8x1NmoSXrW3wXDn+m8mC5ffFN7eX761s0qVLa1bxv4WAAAAAAAA00LfFqbfWwOfZrgu555sb3Aob2+D4c51TySLL+/53oHvZXB4sLjMcCcAAAAAALOZ4c7p94tJ5o14/kd1Xf9uo8V1XZ9L8nNJRjYQf/5Ks3FaVFX11SR/fUToF5KUJ+VgFuppcGtnMs7NnedPJvtfL+c2bi2GGw13Pr7m8axZvKbxtwAAAAAAAJhO+rYwzXb3lfu29yyZn/Z7Ft+cGLyQ9L1aftmG6wfr7hzYWVyyZvGaPHrPo8UcAAAAAADMBoY7p1FVVYuS/Mkbwv/jePvquv7DJL8zItSS5M/ewdIaqqqqJcn/ceWbSfJbdV3/6+n4NtwpexoMd65buSgPrFjYeOMHLycNTnhNR/dNob4TffnDT/+wuLy77eb1AAAAAAAATD99W5gZe/qPFeOb2lalqqqbEwOvJ5fOll/WcXm48+LQxbxy4JXiks3rN6ep8s9iAAAAAACYvfwt9vT6TpKRx03+oK7rn0xw76/f8Pwn7kxJ4/prSZ648vOxJH95mr4Ld0xPX7lJ+GT7qrE37i3fwpllDyb3f+mm8IsDLzZ81da28k2fAAAAAAAATDt9W5hmg0PDeWvgeDH3ZPvq8qbeBv3XBSuSdZ1Jkt2HdufMpfIFtl3ruyZdJwAAAAAATCfDndPrj9zw/NIk9r6aZOQVgo9XVXX/bVc0hqqqPp/kF0eE/kpd10em8ptwp52/NJR3D5wo5jY1ahImSV03bhZ2bEkKJ8du69tWXP6V+76SB5Y8MG6tAAAAAAAATAt9W5hmPz54KmcvDhVzmxodyrtvZzn+yLNJ8+VLbHcOlNcsnbc0Tz7w5KTrBAAAAACA6WS4c3o9dsPzDya6sa7rM0nevSF889WBd0hVVU1Jfi3JgiuhnXVd/6Op+h5Mld//8EQuDdXFXGfbGDd3fvyT5OSBcq6j+6bQ/lP78+NjPy4uf6HthXHrBAAAAAAAYNro28I06+k/VowvaGnKY2tX3Jw4dSg5/F75ZRu2JEmG6+Hs2r+ruOTbD30785rn3VKtAAAAAAAwXQx3Tq8v3vDcO8n9+254fvQ2ahnPX0ryzJWfzyX5C1P4LZgyjZqEyxa25HP3L2u8ce/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AAADIjpc7gUy8vDr55c4xA7sX7pCd6yJWPptcG31B4c4BCMFOAAAAAACg5Vm4bkfieod2RTG4Z6fGbb7i6Yjqfck14U7g7zy37rm4+qGrY3/N/tSez5702finI/4pw6kAAAAAIFte7gSa3Pode2L9jr2JtYK+3LnwjxGR8pnZ0RcW7hygzdtUuSmm3DclXt/+emrP0K5D467z74o+nfpkOBkAAAAAAEC6xet3Jq4f0adLFBflGrf5skeT1zt0j+g3pnF7A63KyxtfjiseuCL2Vif/LElExFXHXRUfHv3hDKcCAAAAgOwJdwJNbu7K5Fc7Iwr8cueCe5LXe4+M6H1E4c4B2rRNlZvi4vsujqXbl6b2DO06NGadPysO6XRIhpMBAAAAAADUbtH6isT1EX27NH7ztHDnsNMjiooavz/QKizasiim3z89du/fndoz5ZgpMeWYKRlOBQAAAADNo7nDnX95Yu8/c7ncnizOy+fz52ZwDvAWL6/enrg+sEfH6FlWWphDKrdGlD+WXBt9QWHOANq8jbs3xsWzL45l25el9gzrNizumnSXYCcAAAAA0NK4u4U2YNG6HYnrI/t1btzGe7ZHrHkxuTbszMbtDbQay7Yvi0vmXBI79iX/XRQR8f9G/b/45LGfzHAqAAAAAGg+zR3ujIjIRcTJGZ2TP2AXUHBzVyWHO8cW8tXOxfdF1OxPrgl3AgWwcffGmHzf5CjfUZ7ac1i3w+Ku8++K3h17ZzcYAAAAAEDhuLuFVmzb7n2xfsfexNrIfl0bt/nyJyPyNck14U4gIlbtXBVTZk+JLXu2pPb84+H/GJ856TORy+UynAwAAAAAmk9Rcw8AtG75fD7mrdqWWDtmYLfCHbTgnuT1boMjDh1buHOANmnD7g0HDHYO7zZcsBMAAAAAADhoLV5fkVob2bdL4zZf9mjyeud+Eb2PaNzeQIu3YfeGmDp7amzYvSG15x1D3xE3nnJjFOX8OBsAAAAAbcfB8HJnxBtfZgVaoVVbK2Pb7qrE2phChTv37YpYcn9ybfQ/RPiiI9AI63etj4tnXxzLdyxP7RnebXjMPH+mYCcAAAAA0Bq4WIFWatG6HYnrXTuURN+u7Ru3+dJHkteHneG+Ftq4LXu2xNTZU2NVxarUnrMGnhXfOP0bUVxUnOFkAAAAAND8DoZwZz4iro+ITc09CFB4c1Ne7YyIOGZAgcKdS+6P2L8nuTb6gsKcAbRJdQl2Ht798Jg5aWb06tgrw8kAAAAAAJqEu1toxRat35m4PrJfl8g1JoBZsTFiw/zk2mFnNnxfoMXbsW9HTJszLZZuX5rac/KhJ8ctZ90S7YraZTgZAAAAABwcmjvcmYs3Lgh/nc/nVzTzLEATmLdqe+L6YYeURZcOBfqH+QX3JK+XHRIx6OTCnAG0Oet2rYuL77s4VuxM/78oh3c/PO46/67o2aFnhpMBAAAAADQJd7fQyi1eV5G4PrJfl8ZtXP5Yem3YGY3bG2ixdlftjsvuvywWblmY2jPukHHx/bO/H+2LG/l6MAAAAAC0UM0d7gRauXkpL3eOHdi9MAfs3xex+L7k2qh3RxQVF+YcoE1Zt2tdTL5vcqzcuTK154geR8TMSTMFOwEAAAAAgINePp9Pf7mzbyPDncseSV7vMSyi++DG7Q20SHur98YnH/xkzN04N7VndM/R8aPzfhSd2nXKcDIAAAAAOLgIdwJNpqYmH6+s3pFYGzOwW2EOWfZoxN7kM2LUBYU5A2hT1lasjcn3TY5VFatSe0b0GBEzJ82MHh16ZDgZAAAAAABAw6zfsTe2V1Yl1kY0Otz5aPK6VzuhTaqqroprH742nln3TGrP8G7D446Jd0TX0q4ZTgYAAAAABx/hTqDJLN20Kyr27k+sFSzcueDu5PX2XV0WAvW2tmJtXHTfRbG6YnVqz8geI2PmpJnRvUOBXiAGAAAAAABoYmmvdkZEjOzXiHDntpURW5Ym19zXQptTXVMdn33ss/HoqpTQd0QM6jIo7px0pw/pAgAAAEBEFDX3AEDrNW/VtsT14qJcHHloAcKdNdURC/+YXBvxjoiS0safAbQZayrWHDDYOarnKMFOAAAAAACgxVm8Ljnc2bdr++jeqRH3qmmvdkYId0IbU5OviS8/+eWYvXx2ak/fTn1jxqQZ0adTnwwnAwAAAICDl3An0GTmrdqeuD6ib5foWFrc+ANWPhOxe1NybfQFjd8faDNWV6yOyfdNrjXYObrnaMFOAAAAAACgRVqYEu4c0bcRr3ZGpIc7+xwZ0Vl4C9qKfD4f33z2m/H713+f2tOrQ6+YOWlmDOg8IMPJAAAAAODgVtLcAwCtV9rLnWMGFODVzoiIBfckr5d0jDj83MKcAbR6qytWx+R7J8eaXWtSe0b3HB0zJs2Ibu0L9PcXAAAAAABAhhavTw53jurXiHBnPh+x7JHkmlc7oU257cXb4j8W/kdqvWtp17hz0p0xtNvQ7IYCAAAAgBbAy51Ak6iqron5a3Yk1sYMKkA4Kp9PD3cefm5EaVnjzwBavVU7V8VF915Ua7DzyF5HCnYCAAAAAAAtVnVNPl7b0AQvd25eErFzbXJt2JkN3xdoUWbMmxF3vXJXar2sXVncMfGOGNFjRIZTAQAAAEDL0Nzhznwznw80kcXrd8be/TWJtbEDuzf+gLUvRWxfmVwbfUHj9wdavZU7V8ZF910Ua3el/NBBRBzV66i4c+Kdgp0AAAAAQFvg7hZaqRVbdseequS725GNebkz7dXOXFHEkFMbvi/QYvz81Z/H9//8/dR6h+IO8cNzfhhH9z46w6kAAAAAoOVo7nBnrpnPB5rIy6u2J66XFhc17uuvf7HgD8nrRSURI85v/P5Aq7Zyx8qYfN/kWLdrXWrP0b2OjjsnCXYCAAAAAG2Gu1topRatS361M5eLOKJPI+5ul6aEOw8dF9GxAB/8BQ5q//3af8e3nvtWar2kqCS+d/b34oR+J2Q4FQAAAAC0LCXNePawt/x6dbNNATSJuSnhztH9u0ZpSQFy5QvuSV4fdkZExx6N3x9otVbsWBGT75sc63evT+05pvcxcfvE26NradcMJwMAAAAAaDbubqEVW7w+Odw5pGen6Fha3LBNa2oiyh9Lrh12ZsP2BFqMPy39U9z45I2p9eJccdxyxi0xYcCE7IYCAAAAgBao2cKd+Xx+eXOdDTS9eau2Ja6PGVCAF/A2LorYtCi5NuofGr8/0Gqt2LEiLrrvotiwe0Nqz5jeY+L2ibdHl9ICvDIMAAAAANACuLuF1m1RSrhzRN9G3IWsfyWicmtybdgZDd8XOOg9tOKh+Pzjn4985BPrucjFVyd8Nc4dcm7GkwEAAABAy9OcL3cCrdSequpYtC75gnDMwAKEO9Ne7YxcxKh3N35/oFVavmN5TL53cmyorCXYeciYuP08wU4AAAAAAKD1SLu7HdmvAfch+XzE3p0Ri/6UXC8ujRg0vv77Ai3CU2ueik898qmozlen9nzxlC/GBcMvyHAqAAAAAGi5hDuBgluwdkfsr0n+QuPYQd0btulfLgmrqyLm/09yz6CTI7r0a9j+QKtWvr08Lr7v4lqDnWMPGRu3n3d7dC7tnOFkAAAAAAAATWfv/upYtmlXYq3O4c718yNe/k3E6hci1s6N2LMtvXfgSRGlnRowKXCwe3H9i3HVQ1dFVU1Vas91J1wX7x/x/gynAgAAAICWTbgTKLh5q7YnrncqLY7hh9QjNFWfS8KIiNG+/Ai83bLty+Li+y6OjZUbU3vGHTIubp94e5S1K8twMgAAAAAAgKa1dOOuqE75MO/IvgcIdy6+L+Lx70WseLLuB25bHrF4dsSISfWYEjjYzd88Py5/4PKo3F+Z2nPZuMvi40d9PMOpAAAAAKDlE+4ECi4t3Hl0/25RXJQ78AYNuSSMiOjQrX79QKu3dPvSmHLflFqDncf2OTZ+ct5PBDsBAAAAAIBWZ9G6nYnr7YpzMbR3yt3I7i0Rf/p0xCu/qf+B21dG/PL9Ece8P+KdN0d06ln/PYCDypKtS2L6nOlRUVWR2vOJoz4R08dMz3AqAAAAAGgdipp7AKD1mbcq+YXNMQMPEL7cvSXiNxdH/PID9Q92RkTcfUXEb6e8sQ/Q5i3dvvSAL3Ye1+c4wU4AAAAAAKDVWrQ+Odw5/JDO0a444UdG1r0S8ZNTGxbsfKuXf/3GPuvnN24foFmt2LEips6ZGtv2Jv8cSETEB0Z8IK49/trI5erwsW8AAAAA4G8IdwIFVbF3fyzZmPy1xmNqC3e6JAQKaOm2pTH53smxqXJTao9gJwAAAAAA0NotTnm5c2S/Lm9fXPdKxL++O2Ln2sIcvnNtxE/f5e4WWqi1FWtjyuwptd65XnDYBfGF8V8Q7AQAAACABhLuBApq/urtkc8n18YO7J5ccEkIFNDr216Pi+67KDbv2Zzac3zf4+Mn5/0kOrXrlOFkAAAAAAAA2VqYEu4c0ffvwp27t0T84n0Re9Jf52uQPdsifv7eN/YHWoxNlZtiyuwpsXZX+s9xnDf4vPjKhK9EUc6PnwEAAABAQ/nXNaCg5q3anrjetUNJDOmVEKJySQgU0JKtS2LyfZNjy570//ZP7Hdi/PjcHwt2AgAAAAAArdrOPVWxeltlYm3U37/c+adPF+5jvG8bZG3E/17fNHsDBbdtz7aYOntqrNi5IrVnwoAJcfMZN0dJUUmGkwEAAABA6yPcCRRMPp+PF1ZsTayNGdg9crnc2wsuCYECeW3ra3Hx7ItrDXae1O+k+OE5PxTsBAAAAAAAWr3XNlSk1v7m5c7F90W88pumHeblX79xDnBQq9hXEdPvnx5Lti1J7Tmh7wlx61m3RrvidhlOBgAAAACtk8+nAY2ycN2OuPulNTF31bZ4ZfWO2F5Zldg3oHuHty9mdUl4zPsjRpzftOcAzWrx1sUx5b4psXVvcsA8IuLkfifHD879QXQs6ZjhZAAAAAAAAM1j0bqdietlpcUxoPtb7kse/142Az1xm3tbOIjtrtodlz9weczfPD+1Z0zvMfHDc3/ozhUAAAAACkS4E2iQBxeuj9sfXhrPlqe/kPdWv3p+VSzbtDsuPWt4nD2qzxuLLgmBAli0ZVFMnT219mDnoSfHD84R7AQAAAAAANqOtHDnEX27RFFR7o3frJ8fseLJbAZa/kTE+lcj+h6ZzXlAne2r3hdXP3R1vLjhxdSeET1GxI/P+3GUtSvLcDIAAAAAaN2EO4F62bprX3z57vlx99w19f6zz5ZviWf/dUu8Z1z/+Mr4XHRzSQg00qIti2LK7Cmxbe+21J7xh46P75/zfcFOAAAAAACgTVm8PjncOapfl7/+5uXfZDTNm175TUTfL2V7JlCrqpqquO6R6+KptU+l9gztOjTumHhHdGvfLcPJAAAAAKD1K2ruAYCWY8HaHfGO2x5tULDzrX7/0pr43b/dVqCp6uiVjC8lgSa3cMvCAwY7Tzn0FC92AgAAAAAAbVJauHNE37eEO1e/kNE0zXQeUKvqmuq44fEb4qGVD6X2DOg8IGZMmhG9O/bOcDIAAAAAaBu83AnUyYK1O+JDdz4d2yurCrLf4VWLIooLslXduCSEVmXB5gUxdc7U2L53e2rPhP4T4ntnfy86lHTIcDIAAAAAAIDmt6lib2yq2JdYG/mXlzvz+Yi1czOcKiLWvPTGublctucCb5PP5+OrT381/rTsT6k9fTr2iRkTZ0S/sn4ZTgYAAAAAbYeXO4ED2rprX3zip88WLNgZkY+ji8oLtFcd/eWSEGjxXt38akyZPaX2YOeACXHbObcJdgIAAAAAAG3S4nXJr3ZGvCXcuXdnxJ5tGU30pj3bIvZVZHsm8Db5fD5ufu7m+O1rv03t6dG+R8yYNCMGdR2U4WQAAAAA0LYIdwIH9OW758f6HXsLtl/nqIzuuV0F269OXBJCqzB/8/yYOntq7Ni3I7XntAGnxW1n3xbti9tnOBkAAAAAAMDBY9H65HBnr7LS6N35zTuU6kJ93Lee9ie/KApk50cv/Sh+vuDnqfUu7brEHRPviMO6H5bhVAAAAADQ9gh3ArV6cOH6uHvumoLu2S72F3S/OnNJCC3a/E0HDnaePuD0+N7Z3xPsBAAAAAAA2rRFKS93jujb5a+/KW6X0TR/p6S0ec4FIiJi1iuz4o55d6TWO5Z0jB+f9+MY3Wt0hlMBAAAAQNsk3AnU6vaHlxZ8z6ooKfiedeKSEFqsVza9ElPnTI2d+5J/ECEi4oyBZwh2AgAAAAAAbV4+n49X1yZ/LHNkv7eEO9t3iejQPaOp3tShe0Rp52zPBP7Pfy78z7j1hVtT66VFpfGDc34Q4/qMy3AqAAAAAGi7milhBbQEC9ftiGfLtxR834roGNvyZdE9t6vge6dySQgt1ssbX45pc6bFzqr0YOeZA8+M75713SgtFuIGAAAAAADanoXrdsTdL62Juau2xSurd8T2yqrEvm4d3/JaZy4XcejYiGWPZDRlRPQf98a5QOZ+v+T38fVnvp5aL8mVxK1n3xonH3pyhlMBAAAAQNsm3AmkuvulNU20cy5eqRkapxXPb6L9E7gkhBZp3sZ5MW3OtKioqkjtOWvgWfGds74j2AkAAAAAALQ5Dy5cH7c/vLTOH+297YHX4qnXN8elZw2Ps0f1iRhwfLbhzgHHZ3cW8H9ml8+OLz35pdR6Ua4ovnnGN+OMgWdkOBUAAAAAUNTcAwAHr7mrtjXd3vnhTbZ3IpeE0OLM3Tj3gMHOswed7cVOAAAAAACgzdm6a1988j/+HJP/9fk6Bzv/4tnyLXHRvz4XV/3nn2P74e9poglTHP2+bM8D4tFVj8ZnHv1M1ORrUntuOvWmOH/o+RlOBQAAAABECHcCKfL5fLyyekeT7X939alNtncil4TQory04aUDBjvPGXROfOfM70S74nYZTgYAAAAAANC8FqzdEe+47dG4e+6aRu3z+5fWxKRfbordh55UoMkOYMiEiL5HZnMWEBERz659Nq59+NrYn9+f2vP5kz8f/3j4P2Y4FQAAAADwF8KdQKKKvftje2VVk+2/KD84nqkZ1WT7/w2XhNCivLThpZh+//TYVbUrtefcwefGLWfdItgJAAAAAAC0KQvW7ogP3fl0rN+xtyD7rd+xN65fe05B9jqgCVdncw4QERFzN86NKx68IvZWp/99cfVxV8c/j/rnDKcCAAAAAN5KuBNIVFWdb/Izbt9/QZOfEREuCaEF+fOGP8e0OdNqDXZOHDIxvn3mt6NdkWAnAAAAAADQdmzdtS8+8dNnC/6R3j/sGRP3FZ1W0D3f5pj3R4yY1LRnAP9n4ZaFcen9l0bl/srUnkvGXBIXH3NxhlMBAAAAAH9PuBNI1K441+RnPFRzbPy++tSmPcQlIbQYL65/MabPmR679+9O7Zk4ZGJ864xvCXYCAAAAAABtzpfvnl+wFzv/3md2fzS2lfRukr2jy6ER77y5afYG3mbp9qUxbc602LlvZ2rPR0Z/JK4Yd0WGUwEAAAAASYQ7gUSd25dEt45NH576ctXHY12+R9Ns7pIQWowX1r8Q0++vPdg5acgkwU4AAAAAAKBNenDh+rh77pom239bdIkP7rouqkq7FXbjDt0jPvLbiE49C7svkGjlzpUx9b6psWXPltSe9x7x3rj+xOsjl2v6j34DAAAAALUT7gQS5XK5OHpA1yY/Z1t0iY/v+0xsy5cVdmOXhNBiPL/u+bj0/kujcn9las/5Q88X7AQAAAAAANqs2x9e2uRnLMoPjs92/eYbH9EthC6HRlz0p4i+RxVmP6BW63ati6mzp8aGyg2pPe8c9s744vgvCnYCAAAAwEFCuBNINXZg90zOWZQfHB/c98XY2e6QwmzokhBajOfWPReXPXBZrcHOdw59Z3zz9G9GSVFJhpMBAAAAAAAcHBau2xHPlqe/wldIv13VLV577+yIY97fuI2OeX/EpU+6s4WMbK7cHFNnT43VFatTe84adFZ8/bSvR3FRcYaTAQAAAAC1Ee4EUl04rn9mZy3KD451H37QJSG0Ic+tey4uf+Dy2oOdw94Z3zj9G4KdAAAAAABAm3X3S2syPe9/Fu2OeO/MiPGX1/8PD5kQ8f9+/caf79Sz8MMBb7N97/aYNmdalO8oT+0Zf+j4uOXMW6JdUbvsBgMAAAAADkhSAkg1ql/XOGloz0y+AnvSsJ5xxNDBEUNnRmxcFLFuXv02GDIhYsLVESMmNc2AQEE9u/bZuPyBy2NP9Z7UnncNe1d8/bSvC3YCAAAAAABt2txV27I9b+X2N36xr+LAzR26R/QfFzHg+Iij3xfR98imHQ74G7uqdsVl918Wi7YuSu05ts+xcdvZt0X74vYZTgYAAAAA1IW0BFCr6WcdFs/+a9OHOy89c/gbv6iuitj8+oH/gEtCaLGeWftMXPHAFbUGO9992Lvj6xO+HsVFxRlOBgAAAAAAcHDJ5/PxyuodmZ758urtkc/nI7fi6eSGYz8acd5NESWlEaWdI3K5TOcD3rBn/5648sErY96m9I9nH9nryPjRuT+KTu06ZTgZAAAAAFBXwp1Arc4Z1TcuHNs/7p67psnOeM+4/nH2qD5v/GbNSxFVu5IbP/r7iH7HuCSEFuzptU/HFQ9cEXur96b2XHDYBfHVCV8V7AQAAAAAANq8ir37Y3tlVaZnbq+sil3bNkTnTSkvAQ47M6KsV6YzAX+rqroqrnn4mnhu3XOpPYd3PzzuOO+O6FLaJcPJAAAAAID6KGruAYCD300XHhV9u7Zvkr37dm0fN15w1F8Xyh9LbmzXKWLohDcuCdt3EeyEFuipNU8dMNh54fALBTsBAAAAAADeVFWdb5Zz88tTXu2MiBhySnaDAG+zv2Z/fOaxz8Tjqx9P7RncZXDcOfHO6N6he4aTAQAAAAD1JdwJHFCPstL42eSTolvHdgXdt1vHdvGzySdFj7LSvy4ufyK5eVnc8qUAACAASURBVNDJEcWFPR/IzpOrn4wrH7yy1mDne4a/J75y6lcEOwEAAAAAAN7Urrh5Pnrbfu2zyYVugyK6Dcx2GOD/1ORr4stPfjnmLJ+T2tOvrF/MmDQjDul0SIaTAQAAAAANIdwJ1Mmofl3jV9PGF+wFz75d28evpo2PUf26/nWxen/EipQvwA49rSDnAtl7YvUTBwx2/uPh/xg3nXqTYCcAAAAAAMBbdG5fUvCP8B5It47tot2qlHvbwV7thOaSz+fjG898I+5+/e7Unl4desXMSTOjf+f+GU4GAAAAADSUcCdQZ6P6dY17rzoj3jOucZcA7xnXP+696oy/DXZGRKydG7GvIvkPDT29UWcCzePx1Y/HJx/8ZOyr2Zfa80+H/5NgJwAAAAAAQIJcLhdHD+h64MYCOv7Q9pFb+1JycfD4TGcB3pDP5+PWF26NXy36VWpPt/bdYsakGTGk65AMJwMAAAAAGkO4E6iXHmWlcduHjo1ZnzghOrcvqdefPWlYz/jpJ06M2z50bPQoK317Q/ljyX+wpGNE/2MbMC3QnB5b9Vhc9eBVtQY733vEe+PGU2+Mopz/SwIAAAAAAJBk7MDumZ43qfvKiJr9yUUvd0KzuGPeHfHT+T9NrZe1K4s7zrsjjuhxRIZTAQAAAACNVb9kFsCbzh7ZJ4pytfd069gujhnQLcYO6hYXjh0QI/t1qf0PLH8ieX3wyRElCWFQ4KD16KpH4+qHro6qmqrUnvce8d740ilfEuwEAAAAAACoxYXj+sePH349s/POK1uWXOjQPeKQUZnNAbzh3+b/W/zopR+l1jsUd4gfn/vjOKr3URlOBQAAAAAUgnAn0CAbK/bGjj3JX2ud8bHj45ThvaOstDhyuQMkQP+ien/E8qeSa0NOa+CUQHN4ZOUjcc3D19Qa7HzfiPfFF8d/UbATAAAAAADgAEb16xonDe0Zz5ZvafKzThrWM3pveTG5OHh8RJG7HcjSbxb/Jr79/LdT6+2K2sVt59wWx/U9LsOpAAAAAIBC8a/uQIMs2VC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"text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "%matplotlib inline\n", "\n", "import matplotlib.pyplot as plt\n", "\n", "dpi = 300 #dots per square inch when plotting...higher resolution for publications.\n", "plt.rcParams['figure.dpi']= dpi\n", "plt.rcParams[\"figure.figsize\"] = [4,1]\n", "\n", "plt.rcParams['figure.figsize'] = (15,5)\n", "plt.subplot(121)\n", "plt.plot(thresholds, mcc1, '-o')\n", "plt.plot(thresholds, mcc2, '-o')\n", "plt.plot(thresholds, mcc3, '-o')\n", "plt.title(\"Matthews Correlation Coefficient\")\n", "plt.xlabel(\"Threshold\")\n", "plt.xlabel(\"MCC\")\n", "plt.ylim(0,0.75)\n", "plt.legend([m1Name + \": AUC (train) = \"+ str(round(auc1,3)),\n", "m2Name + \": AUC (train) = \"+ str(round(auc2,3)),\n", "m3Name + \": AUC (train) = \"+ str(round(auc3,3))])\n", "plt.subplot(122)\n", "plt.plot( thresholds, mcc1Test, '-o')\n", "plt.plot( thresholds, mcc2Test, '-o')\n", "plt.plot( thresholds, mcc3Test, '-o')\n", "plt.title(\"Matthews Correlation Coefficient\")\n", "plt.xlabel(\"Threshold\")\n", "plt.xlabel(\"MCC\")\n", "plt.ylim(0,0.75)\n", "plt.legend([m1Name + \": AUC (test) = \"+ str(round(auc1Test,3)),\n", "m2Name + \": AUC (test) = \"+ str(round(auc2Test,3)),\n", "m3Name + \": AUC (test) = \"+ str(round(auc3Test,3))])\n", "plt.show()\n", "plt.subplot(121)\n", "plt.plot(thresholds, acc1,'-o')\n", "plt.plot(thresholds, acc2,'-o')\n", "plt.plot(thresholds, acc3,'-o')\n", "plt.title(\"Accuracy\")\n", "plt.ylabel(\"Accuracy\")\n", "plt.xlabel(\"Threshold\")\n", "plt.ylim(0,1.0)\n", "plt.subplot(122)\n", "plt.plot(thresholds, acc1Test,'-o')\n", "plt.plot(thresholds, acc2Test,'-o')\n", "plt.plot(thresholds, acc3Test,'-o')\n", "plt.title(\"Accuracy\")\n", "plt.ylabel(\"Accuracy\")\n", "plt.xlabel(\"Threshold\")\n", "plt.ylim(0,1.0)\n", "plt.show()\n", "plt.subplot(121)\n", "plt.title(\"Receiver Operating Characteristic\")\n", "plt.plot(fpr1, tpr1,'-o')\n", "plt.plot(fpr2, tpr2,'-o')\n", "plt.plot(fpr3, tpr3,'-o')\n", "plt.ylabel(\"True Positive Rate\")\n", "plt.xlabel(\"False Positive Rate\")\n", "plt.subplot(122)\n", "plt.title(\"Receiver Operating Characteristic\")\n", "plt.plot(fpr1, tpr1Test,'-o')\n", "plt.plot(fpr2, tpr2Test,'-o')\n", "plt.plot(fpr3, tpr3Test,'-o')\n", "plt.ylabel(\"True Positive Rate\")\n", "plt.xlabel(\"False Positive Rate\")\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/ibm/conda/miniconda3.6/lib/python3.6/site-packages/matplotlib/cbook/__init__.py:424: MatplotlibDeprecationWarning: \n", "Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead.\n", " warn_deprecated(\"2.2\", \"Passing one of 'on', 'true', 'off', 'false' as a \"\n" ] }, { "data": { "text/plain": [ "(0, 1)" ] }, "execution_count": 70, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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xO0rZh3Czp+d3YAfht+5mwvrcRshvfArht65w/zDgIjO70d07M9S9lXCsfohwDFpH2LcGEW4kzQBeRViPhaYBV0THg6z5qUcRAqqFN/7vJxzDnyIcDycTAq5vSFFed7T8UsJxYVX0WbqjuvYn7DMnsev+3AJcbGYPufvStI2PBvy+g+QbEdsJ52U3E36H1xG+30mEdXkc4XvvzQb+dgwyim/oLSf8vpZS8rfJzL4FfDThpdWENCT3RnVsIfzWHkrYpw+Mvf+DhM/32T7a05sfA20F/79ASLu1lPAdjiHcfJifsfwk/034jYh7GPgD8CjhPHMb4Xd4LGE7PIzw+9ySsGyPbnb9/TiQXX9/N5LuGmBHiveUpZbn8yLSAOrdVVyTJk2aNNVvIqf0I8CnEspZSxn56Ai9GjsSyrmSPnJqEgYLjD/u6YSgR59pJwjBraRUJ48Br0ux/GhCsPQOUjwSSug9F6/rPqJH10ssN5yQy3JnbNnVwNQU9aZOPxK9/+iEdn4l47b2x1g5G4ARfSxzQsL3sokQcBrZx7KvJjkX+3tStDWefqSbv+W+3BF9B8NKbctZ1lEvZb034TOsyav8hPpuTKjvf/pYJv5YdGHajc3AR3o7FhACcZcm1OnAG1O2eQLFOWa7o/1seh/LHtTLZ/55inqTHp0v3DcvB6aVs50QgmtrgG8Repilyp1PCMglHT8/VMZ3n2cO0zzTjxRuTz8CJpdY/jSScyd/LGW7DyUEeOLL/xbYs8RyRwJLYtt9vIyqpR8hPEESr29ltepL0Z6k9COF3+MiSqSeIuTET8ob/a0ytr9N0fZyWtK+1stys3s5HnytjM8e348KjwlPAK8psewgoDlh/p+Aa4HzSchv3EtZkwnpnOKf5Z4yPksT4QmJeBldhBsUac475gJfJ/zm95oCJesxo4+6z08ocxXwTqClxHJGuBG/OrZsN3B6inrj51qF28BGQoC86HsuXBcJ88pKP0II0sY/+3LgzJTrbiRhDJPrgB+neH9FOb9T7Eepfo+o8fm8Jk2a6j/VvQGaNGnSpKl+EzkEtQk9q5IG7fpOmeV8I6GMVIGIgjLiwUgH5vWxzDBCL7H4cjcAo7Os0z5ePzehrl9SxkBOhEdJ44Htb6ZYrqygdrRMfECrZaUuxnopI+ni6v/6WGY4oSdTvO6ZZdQ7nuIBCpfTR4Cjl+3IowulkttT3hMhGBBvx++qWN9XkvaFPpaJX8z2TNsoEcCJlfGthOVX0seNj2jZK2PLbQdeX8ZnbiI5b/mcPpYrlQ82682fIX1tnyWWHU7ofVfYjidIeXORxg1q90x9DloalXFKwrJLUy57U8Kyl6ZZh4SelneXaH81g9pfS6jvumrVl6I9pfK1/zfpbjbPpDiP9BpS5NwnBCX7zCvfy7LNFOcnX5+2vIT9qGd6AJiUsU2pc/0nLPu+hLa8KuWyH0tYdgtwXoZ2jKXEYNNZjxklymslBJALy3uIFIH4gjL2pTiPf5/jWZDcyaJnO8qU25zyg9qfSKj/mIx1D8+7fSnKK/v3iBqfz2vSpKkxJuXUFhGRzKK0I4sJ6TEKbQb+s4xyJhFy6Rb6lrt/q8wmfYaQP7DQp/tY5j2EwHyhB4Fz3L3snODu/kwfb/m32P/3EAbUTP0IprtfTfH6fU/0mHDefhL7fyrJOZ5LeUfCvL5Sj7yLcFHaows4190fTlupu68lpB3ZWTB7CvD2tGXE/Je7L8q4bFbTE+Zlefw+raSy98xY1r+5+/Up3/txQs+oQhOBN5VaKMpVuyA2+5/c/YqU9eLu3YR88U/GXvrntGXE/DHrsu6+zd23Zlx2M/BWQlC/x/4Up+Tojy5396+leaO730hI91DoEDNrTXp/DzM7hOJ19Rjw7mgb6ave9YT0EZvTtDNnSfvoipq3om9/BD7u7t7XG6NjfTwn+HhSjK3gwcYsDfSQrud9hIE/e4wmXWqQ3mwnDP7XVyqN3toUH9+inGV/AFwdm/3uvpaL0qR9KuGl97r7lRna8ZK7v1TuchX4R3ZNbbWR0Mt6edoC3P1pilOWzTGz0zO26RPufmfGZcsVHxviAXe/K0tB0W9Lf1Dr83kRaQAKaouISGpmNtTMWs3sLDP7ISGvY9KgZu9x975ysRb6CLsOIJQpb2F0ofzF2OxjexswLRr055MJL701a2CpFDN7NSFnX6GPuvvOpPf34SuEHlM9RgDVGKDsUnYNCkMZA0ZG6/htsdmPufvtJZZppjin7Y/d/Z609fZw90cJPeELxYOgaawF/j3DcpVKulGROcCRQlLZWQYyfYbw9EUq0b77kYSX4je74uLB40eAi9LWW1D/NkIP/UJnm1mW8Wc+mSZoVw0exhD4fWz2CfVoS452Uv5Ngp8lzOtr8OD3Jsz752jbSMXdn6WM7T5HSftoLQOIaX3Ke8/xniTL91gxD/mzfxObXcl+9CN3f7CC5Sv109j/aT7L2ygOEC5y90vzaVL1mNlYivfnL7v78+WW5e5/IKR/KZTlHOIhd6/GAM+9GRX7f00N6665Wp/Pi0jjUFBbRETiTjQzT5oIQdQXCL1+3kPxoGybCb2OLyuzztfH/v+FZx+U6RYgvuyJvby3jeIebje4e0fGuvsS/5yPlArulhL1QvtjbHZvnzMzd3+RkMuz0DlmtkfS+xOcSvE6jvf+jjuKMGBSoUouBq+J/f+KDMHKy+p0YTQsYV41g1VJZSe1oS8Xl/P0AUB00yK+7x1hZvEnQQCIvsN5sdk/SdOrthfx7WQk5QfQlrr73Rnrz8vjsf+PrUsr8rM4QzAq6Ts4uI9lTon9v5LiHq5p/JjwyHstJe2j1bz5lcXSDL1Ul7DrkwfQ9/eYlzz3ox9V0pAcxD/LvtETcqWcmzDvKzm1p9rOYNde2k6KgalLiP82ZDnXqqT+LOJB7DlmFh+UeXdS6/N5EWkQWXqfiIiIxG0k9Ib9QrnBBzObTPFFaqZAL4C77zCzF2JltlHcWxeSH8uvZi+k+IVQvPdPuZ6O/d9WYXm9+Qm7XuC2ABeQrkdsvFd3F8W9xuLi62kb8JcUdfUmvp5GEvJ8P1JGGTdVUH9/khSMswzltGes/0qKt+NjCQP1xR3BroELqOzYsdzMthJyu/ZoA8p5ZDv37cTM9gSOJzwVcyAhd/MoQiAz6buJ967cK+821dgt5S7g7s+a2U52vdYZ09v7zWwUMCs2+/osT9G4+9Nm9hBwSLnLViBpO6jL0wIlZPked5jZ84Q0Oj16/R5LiW6OnUDYj2YQcjyPJtycT1p/8Ru3Wfej9VT2+1XEzIYSBpI9nDC46UTCMWEkISd43JCEeXsRbtwkld8clV/oqaw34esgfg7xlLtXko4nfg4xw8yGufuWxHcnq/U5RPx3ayzwczN7e43TwNTKSQnzGv6pAhGpnILaIiKSh3uAi7I82gm8ImHehWaW9BhhWvHeGhN6ed9xCfMqDTQnino2z4jNPtvMllRQbDx41dvnrNTVhIvfwp5d76CPoLaZjQHmx2b/LkqRUEp8m2gC7jHLElsFki/oy11XuQYlypB00ZwpqJPS2IR55ebT3EbIY5lF0no+guSgdtKx44dmFu/ZWY74uXHdthMzOx/4ACG4lHnjJ/k77U/ivUzT2sCu6XtK7TeHUPwEayXfZQe1DWonHSca7XvP+j3Ge5yXdfwzszMIqY1Oo7Jr3xFmNijDjY4leaUjMrMZhFQ85xEC8pUotX3MpHg9V+XcqErivw1TKjzXiqfygHDTI22avZ2EgUJr6WpgNbv+hp0LPG1mlwJXALdnTH/XiGp2Pi8ijUVBbRERiXsZeCJh/mBC3s54IBXgZODPZvYOd7+8zPqSBsLbP2FeJXpLlTE59v9md38q57p7JA1SNjmhDZVImxKkLO6+08x+Rhh4qcdcMzvc3e8vsej5FD8W31fqESjeJgYDs1MsV45y11WmAb5ysC5hXjWDVUllJ7WhlCcruFBO6j3f22PySceOmRnr7U3NtxMz24vQw+xVlZYVqeZNkFpYm3G5ePqbwSXem/Q9P5OxXiju2VltSeuo0YLatfge/yrKq/wTim+sVmIM5ecmzuOYYMAXCAHtVJ8/hVLHhaTzkloHZSsR/20YQXXOIdIGtdeVm46rUu6+ycw+AsTTAY4FPhxNm8zsDkKv7ruA2/pxL+5ans+LSANRUFtEROLucfeTenvRzMYD5wCfZteexy3ApWa2yd2TelX2piqB2JjecgLHB+ErN3hXjnp+zjz8mF2D2hB6a8fnxV8vtAa4KkVdjbauuty93N7KeUm6aJ5WxfqSblqVM+grVJbLN2nZ3oJzjbadQOgdnJmZ7U14TH3fSsqJySsIVi+1CAYlDbSY93ZcTUn7aJ43TPNQs6CemY0jDJg6N+eis+xLlR4TDPhf4F2VlJOg1GdJGqC4mudHuYlSp9Tihk45vw0VbQNZufvlZjYE+C7J7R1JeILhtOj/bjO7F/gVYRyRvp6qayS1PJ8XkQaigSJFRKQs7r7W3S8B5gC/iL3cDPzMzPYpo8ikYEKtxB/f3VTFuur5OSvm7g8Cf47NfouZJV4YR49JxwfW+rm7p0kN0Wjrqp6P5z6aMO/IKtaXVHZSG0rJOshrb8smPfoNjbedQOXbyqUkB7TvBf6D0Ou0jRCwHAUMcncrnID/qrANA1FSiqJK0thsq2DZLJL20XIHOd2dXERyQPsR4OvAGwgDEk8lnAe0JOxHH8ipLZUeE95FckB7NWEA5b8n5ArfmxDMHZrwWcp9giUptUk1z4/yNIbK0jVVQ93OIdz9YkIHlB/S93fYRNgvvkpIU/L9qCNLf1DL83kRaSDqqS0iIpm4+zYzeyshuHJywUujgR8Bp6YsKikX6Ax3LzeQlkW890w1R4ZP+pzvd/cfVLHOvP2EcMHTYyJwFsmDAsYHiOxZPo0t7BrIvNPdk/IlDgRJeX33MLN93T3XFAdRj8CkQFi5uYVHVNCMpGU39vLe+D7lwIgyB+9qGGb2OooHZ1sOvMXdbyyjqGo+sbG7SupZ3dvNlDQqzXdcrnsT5k0ys33c/Zkat6WuzOxI4M2x2RuA9wC/LiO/dd33IzMbRriZVciBLwL/6e5bUxaVxxMn1Tw/ylPSU1W/cPc31bwlDcLdnwPeZ2YfB84ETiH81iSNJdCjBXgfcJaZvdbdGz39TC3P50WkgaintoiIZBblzX0bxSeTp5jZG1MWszphXp6P3pcSz41ZzZ6f9fycebkciF9EvyP+pujx37fEZne4e9qBmuLrqr+tpzx1kBxwO6MKdR1D8mPbN5VZTiU5nJOW7S3HZ3w7MUJvxf4qHnTZAby2zIA2JKcOkNKSHlWvJL1NLVLjFLqP5M9wSo3b0QjOT5j3Jnf/VZkDNjbCfnQq4eZxoa+5++fKCGhD+Z8lKW94Iz4ZUyRaL/HA9kA+h/grd9/s7r9x939w98MJv/enE26S3EO4YRI3Hbg2Gvi7kdXyfF5EGoiC2iIiUhF3fwH4t4SX/qO31BQxLybMO7yyVqW2Ivb/cDPLe5DKHvX8nLmIBhBaGJt9lpnFB/I7neK8z2l7aUPxupqcUMeAEN04Wpzw0rurUF1SmQ9nGGxpPzPL+jTgwQnzehtord/vUzGnxf6/qowbQYX2y6MxA8zzCfMOq6C8mm6H0XHiuoSX3lfLdjSI+H50r7tfm6GcRtiP4p9lB/DlDOWU+1ni50bQv46t8d+GmRX8Ju223H2ju1/v7v/m7kcRgv9fpTh90nRKj5/SCGp5Pi8iDURBbRERycP3gHjgaz/SDWx0d8K8MytuUTp3JMx7RTUqih7/jJ90n2RmQ6tRXxXFg9ODKH7U+x2x/7cDl5VRRz23iUZ0ccK8uWZ2dF4VRAOrJT1dUc7NiB5DgVkZm5KU/iQptQLsRtuJmY2mOGXFHzOU08LAzqWc1eMU93SOjwmQShQ8q8d38OOEeUeb2UDbHvaM/V/2fhRphJRX8c/yoLuvzVBOuZ/lEYr3h6qcG1VJ/LdhNP2r/XXh7s+6+6eAsynutf26OjSpHDU7nxeRxqKgtoiIVCwa/O8LCS/9SzTyeqllH6G4l9wJZQ42mdXNCfPeWsX6fh/7fxiNf6EQ9wfgudi8v+bUd/VoAAAgAElEQVTPjoKj58ZeX+TuSY8z9+aGhHnxdCYDyfWEIEPcd6JUL3n4KsU5KDeSHChLY37G5c5LmHdnL++9leIeZfPMrJJcyPUyIWFeluDVPJIHPUwjPphZXttWw4vSUtwVm32CmcWDimm8lvo8+n4jkJT3Ns/jREOLPmd83Ze9H0V5uRshZUX8uJDlswyl+De5JHfvpvhmwL5mVs0gYdJgilm3W51DVMDdfw/8LjZ7Vh/HkXr/ftycMK+a5/Mi0iAU1BYRkbz8DHgsNm86YXCmvlwV+38Q8Nk8GtWH+4D4YHuvNrO5VapvUcK8f+1Pj8VGF7uXxGYfVrDOLqA4qFZub9/bKM6P+GozO6HMcnYL0TpPSvFzJDk8EmxmpwLvTHjpG2XejCj09pTphwrbMRdoi82+191XJb3f3TdTfKNoHPDRcuptEC8nzEsKdPcqGujz4xW0IT4g50AbaOuXsf+bgE+UU0D0HXwytxaVIQrMfybhpWOA/5dnXWY2wczelmeZeXD3LorHfShrP4qU9b1XUfy4kOWzvJ1sOd7jqcYAPpWhnFSiFDrx7y7rMeg6QqqWQm83s0a4UdFfxG+kG6UHwK3370etz+dFpEEoqC0iIrmILia/mPDSZ1Kk2PgKIUVFoXeaWdbenqlEwcKvJrz00yqlBbkSeDg27+Be2tDILqb40dS/j/3tsYzQ0zg1d98GfD3hpUuinuADjrv/muScuV82s8y9kczsKOA3hAvWQo+RLXdrj/2Aj5XRDgP+O+Gl7/ex6L8nzPtsnqlZamQNxUGY15RZxj9QWcqEeLqBRsgpXEu/pLgn7IfMrJw0JO8DXplfk8rj7tcAv0p46UIz+0gedZjZ8cCfgePzKK8Klsf+Py06vqRiZmeRPNhkPcQ/y6FmNjXtwmY2nezH8Z8DL8TmnVvJ700KuRyD3H0ZxTfTBwOX9/X0oPxVfDvbQe+DNkOdfz/qcD4vIg1CQW0REcnTZRT37pgGvL/UQlG+6f+NzTbgUjM7J0tDzGyQmb3ZzC7s460/pjj9ySHAVVnSGJRKm1Kix+3HzOzCci68Y3W+0sx+mmXZLKKBA2+Nzb4gyt0az996SXTDo1wXUTzY037AdeVc1Bcysylm9mUzOzHL8g3g3YSbBIWagIvN7GNmVtZ5nZmdSbjhMCb20lbgze4e7zVXri9GvcDT+ArF+S9XAZeXWsjd7wSuic0eQth/MwV4zWyomX3QzD6UZfksol6K8ZygZ6Rdf2Z2LvC1CpsRT10x18wmV1hmv+HuWyheh83AtWlukpjZW4D/qUbbyvQB4InYvCbg22b2TTPL1IPSzMaZ2bcJx/59KmtiVcXTZsyk+GZrIjM7Brg09xZlF/8sTcB/pVkwGlz5amBslordfQfwnwkv/cDMFpRbnpmNMbO+2hI/Bp1SQUDy3ynu+X0McEU0hkHZzGw/M/uemR2UsU01Y2ZfzJpP38z2A+Ln3g9ET4P0Jv7dTapDPv+anc+LSONQUFtERHITBW0/n/DSp81seB+LfwpYEps3ElhkZt9Pe3JpZrPN7EuEi/qfAYf20eZthF5Z8V6SpwH3pLl4M7ORZvYmM7udPnqWuvsVFAfwAT4H/D7qBdcnM2s1s4+a2V2EIMNr0yyXo3iu5fEkBwMuzlK4u28iDFwY/16OAf5iZu9P0+PKzIaY2Twz+znwDPDPQH/MudzT+2wesCH2UhPwTeBOMzupr+C2mc00s18C11Ic8OgC3ubu91TQ1J5AQk9w+UO93bCJAmUXk5yy4cPunpSWI+5dFF/ITgZuNrP/jII7JVlwnJl9C3gW+A61D9wl9bD9jZnN620BMxtuZl8k9Lbv2R/i20dat8f+HxTVH08Jszv7KsUDk44Dbjezi8xsTuELZtZsZieb2ULC8a8nj2zSoGU1EQ0k+FqKByaG8PTEk2b2ETNLlZLCzA41s68T9ouP0Pi51pP2o++Z2XtKHIcGmdnHCOmMep4Gyrof5elqYEts3lvN7LtmNqy3haLe5ncCs6NZWT/L9yi+aTiMEBj+jplN6asAMzvczL5GOEbP6OPt8WPQBELv6rKDyO7+PMmDlZ8N3Gtm51uKXPPR+d0FZraI8ATT+4GWcttTB28gnMP+ycw+HPXa71N00/8PQPyc/Wd9LBr/7iD0kn5luTfcs6r1+byINIZ+k8NTRET6jV8R8mEfUjBvMvBBSvQkdPfNUfDmTnZ97NEIj3S/28zuBm4hXFyvJfyOjQMmEXLxHkHoGV4Wd7/dzD5OcS+7g4Arzew5wqA5S4HVhMDfWGB/YC6hh2lPb6L44DpJ/gE4ADg5Nv8UQs+khwmD3jxMSEuwM6pvD0KQ/oiobZl6dufkCsL6KgwQz4y950/uHs+znpq732Jm/wD8gF0/6xTCxfaXzOwWwgBvKwk5HUcStol9CetpDsUXZ/2Wu99jZq8hBBriQamjgJuA5WZ2NfAkIbC1nbDO9gROB2b1Uvw2QkD71xU28xbCvnkqYd1fBHzCzH4DPAqsJxwTjiYE6ZNuMvza3eM5jhO5+4vRseNWds3j2QJ8Gvh4dIH6R6CT8Jj0EMJ2MpWwDx9Btny1efo/wk2XwsEJxwDtZvZnQoDrScLxYDIhp/rZ7Dow3hLCNpAlt/YVhBQwhb0YX0G4ibSR8JRAvOfjNnc/JkNdDcndd5rZBYRtuDBg1wx8iJCOZANhvxocvSceXLySMFBd/EmBLE+sZOLuj5vZK4HFhN+pQpOAbwPfNLN7CfvFCsKTERsJ+2wr4Xh+Av0sDY27XxPd7C3cLluAHxKOBe2E39athHVxOKFXauF5xwvAd4H/qEmje+Huq8zsIopzWX8AeL2Z/Rr4C+GYOo7wXZ/NrudfOwk3M8oe9Nfd3UK6kbuAAwteaiKc073bzG4j7C/LCOkpRgATCQH1YwnnOmldTHiarTAIOh+Yb2ZrCU9vxVPVPe3uicFKd7/MzGYB/xJ76QDCU0DfNLObCDeyVhNymI8mrMsDCb8Lh9M/gti9OT6avm1mjwId/O1ctiedyFhCKrxT+duNkEIPEs65SrmV8PtUeLyZFc3fbGYvUHyDBuDUCsbuKFKH83kRqTMFtUVEJFfu3m1mn6e4t9SnzOx7pXpeuvtzFnL8/prigEBzNK+SnLG9cvfvRMGK/6V4oMO9SDfgZdq6dlhI/XBRL+XOpDhA3FCimxC/IrknVI+yL6IT6vlfM1tFGJwy/sjweGBBNA0Y7n5X9FjvL9k1cNNjKuVvr88Ab3T3uytsXo83EXqr9lzg7kP6wdeuA8rK2+ruHRZSRFxJcW/AIYQbSPGbSA3F3beZ2RsIN7Tij9wfFU2lPEsIzmVKm+LuL5vZp0junTaKEPSI25alrkbm7o+Z2UmE3oqtCW8ZTe8Dpl1P2HaTBl6tac9fd38iOk58j7A/xjWRbrtKcifwowqaV20XAHdTfOMvzW/rOuAsGidn+L8BryIEiAtNJASWS+kmpK26K2vl7r4ueoLsN1E7CrUQ3YzPWn6srmfN7CuEm5Fx46MprmR6Enf/bBRQ/TbFwekphH0jaf/Y3Rjht7Gv3vJxzwDn9ZWOLLoB8iHCE2DxDhfDCUHlJGUNKJ1GLc/nRaT+lH5ERESq4Qrg/ti8icCH+1rQ3TuBEwlpTEoNSpPGg4QLsVTc/VLCRdudFdQZzwPdW13b3P29hIvveP7Tcq2gPo9Jlgpav0y4OVExd28n9Er9LcUDVJZjB7CIsF30a+7+LCHo8kFC7+OsNgJfAg7JMaCNu68iDJj353IWI/TKXxA9RlxunQ8Ten//N8k9wspxF3XopeXudxFSR6wsc9HbgOPcPT6wW7n1/4CwTaVJ+7LbcvdHgcMIvXvTHHO2ABcCZ7v7ZnbtPQ+hR3vNbwC4+3p3v4DQAzOPlCj3AG9w9+PcvZx9u6aicR9OIfQcLceDhP0ofv5SN9F2cxblH4/WEo6ll+TQhtWEFA5fIvuxYQvh96YvnyWc/8VTSGTm7t8n9MCNjwVSrs2EATTjY1s0oqT0Q+VaSNgfUj1x5+6LgdcTekDXVS3P50WkvhTUFhGR3EWDyVyY8NInLcVgLe6+w90vBPYmPHZ7O+kucHYQgjsXAke4+6HuXnKguYS673b34wiP8C4iXe+6ZwnBuBPc/e1l1nc5oefMBYQeLmku+pxw8f1t4Exgurt/tpx68+DutxPSSSS5wt3TfJa0dT3u7ucSHgX+IfB0ykVXE4Lr7wVa3X2+u6ddtqG5e7e7f4+QHuACQtB/U4pFe/aTjwB7uftno0Bc3u1bTniy4oOEXKSl2nMd8Ep3f38lwT933+juHyX0DP8i4dH87hSLbiHk0/00MMPdj3X3G7K2oxLufhNhO/8GpY8/Tgi+vxl4VbS+86j/e4Qeyu8m5FFdQkhNUemNgn7F3de5+/sIaQg+QwiIPUNIW7GVkCN4MfCPwN7u/vlocD3YNXUJhABj3bj7je5+PKFX9jcovT8W2kHYh74MzHL3o6JxIRpeFJieSxivoq+bREsJacHaohsaDaUgT/rb6fum7ArC93Wwu1+VYxu2R+cZ+xLSsqS5ObwduJHwWzPN3ftcxt27ovO/6cBHCU/9PUT4La/kt+Eedz+RENz+GekD053AT4G3AFPc/S3R99HQ3P0kQrq6fyakK0ub4mMdocPCK9z9PHcvKzju7lcSekO/KSrnz4Tg8GYq65RQtlqfz4tIfZiXHMRWRESkMZjZCMIF+RTCI8VjCRc4GwknzI8CTxQEFfKqdxChl/BehN7mPfVuIAQ4HvYwIFFe9TUT8oPvQ/ic4wlBuY2EwMjjwCOl0rgMFGa2FyH4N4GwroYSgrobCBcmj3gYXHHAiLafQwiBuFZCjukmQu+6lYSei/e5e24BSjO7k13ToPzO3c9IeN9BhCDTdMIjwasIgYU/ufu6vNqTUO9YwrFjEmE7GU24wO7JE/0oIS9rzXIepxUdf44i5Cbdg5A6cAPwFHCPu5fbo1tqIMpVPbdg1g3u/pp6tSeJmY0nBL32Jvy2DSfkX14XTc8CS+rRwzxv0UB1hxPGWJhAOP5sJHzGDnd/ro7NK5uFgbOPJeTWH0U4ni0nBOeXeo0u8M2sZ0yCSYT1OpjwG7yKcFx9OM/fmrxFv0kzCcfWPQjt30jIUf404RxiVf1amC8z25uQEmwfwngNIwg3HjYSboYsJZxH75YBolqfz4tIbSioLSIiIiKZpQ1qiwwEZjadECBpLpj9pXo8TSMiIiKyO1P6ERERERERkXz8I7sGtKHyXL4iIiIiEqOgtoiIiIiISIXM7CRC/uBCTxPytYuIiIhIjhTUFhERERERAcxsspl9Jso5Xc5yrwOuoriX9nfcPc1gpSIiIiJSBgW1RUREREREgmHAfwAvmNlvzOztZnZwNNjgLsxsmpmdb2a3AFcQBu0r9Bfgouo3WURERGTgGVTvBoiIiIiIiDSYYcB50QSw1cxWARuAocB4YFyJ5dcCb3L37VVtpYiIiMgApaC2iIiIiIhIaUOBPVO+9xHgHHd/oortERERERnQlH5EREREREQkWA/8DtiRYdlVwL8ARymgLSIiIlJd6qktJZnZXOBAoDWa1Qk85u4d9WuViIiIiEj+3H0dcIaZjQVOAo4DDgX2ASYDI4DBhDQka4EVwB3ArcDv3X1L7VstIiIiMvCYu9e7DQOSme0HHAUcGf2dy66Dyzzr7vvUoWmY2WDgE8C7gf17edsTwP8B33D3LD1ZRERERERERERERMqmoHYNmdlJwGcIgezxfby9LkFtMzsQ+AUhyJ7GvcD5esRSREREREREREREakHpR2prDvCaejeiN2Y2BbgB2Dv20hPAg4ABh7Br7+0jgOvN7Fh3X1mThoqIiIiIiIiIiMiApYEiG8M24Ml6NsDMmoB2dg1oLwdOd/cD3X2+u89z9wOAMwn5A3vsCyw0M6tdi0VERERERERERGQgUlC79nYASwj5qN9H6Ok8ipC/up7eDBxT8P9a4Hh3vz7+RndfDBwPrCuYfTzwxqq2UERERERERERERAY85dSuITMbB2xx960Jr50E3FQwq2Y5tc2sGXic0OO6xzvc/ZI+lnsH8JOCWU8CB7l7d+6NFBEREREREREREUE9tWvK3dclBbQbwAnsGtDuBH6WYrlLo/f22J/QY1tERERERERERESkKhTUFoAFsf9/6u5dfS0UvSce/D4vt1aJiIiIiIiIiIiIxCioLQBnxP6/uYxl4+89s6KWiIiIiIiIiIiIiJSgoPYAZ2ZDgANis+8so4jbY/8faGYtlbVKREREREREREREJJmC2nIw0Fzw/0p335B24ei9qwtmNQMH5dQ2ERERERERERERkV0oqC3xXtrPZSgjvsyBGdsiIiIiIiIiIiIiUpKC2jI29v/KDGXElxmTsS0iIiIiIiIiIiIiJQ2qdwOk7kbG/t+SoYz4MqMytmUXZjYJmFjmYiOBI4ENwHrgeWB7Hu0REREREREREREZwFqAPQv+v8Xd19ejIQpqSzyovTVDGfGgdrzMrD4IfC6nskRERERERERERCQ/84Cr6lGx0o9InNdoGREREREREREREZGyKagtm2L/D8tQRnyZeJkiIiIiIiIiIiIiuVD6EWnkoPZ3gV+XucwM4Iqefy677DL222+/nJrTGLZs2cIDDzzw1/8PO+wwhg3L8rWJSFbaD0Uag/ZFkfrTfijSGLQvilSm252Hlm/ilifWcMdTL/Hy9q6at2HkkGZ++rbZmFnN607rqaee4oILLiic9Xy92qKgtsSTuZc7MCPApNj/L2Vsyy7cfSWwspxl4jv+4YcfziGHHJJHcxrGhg0bWL/+b1/b3LlzGT16dB1bJDLwaD8UaQzaF0XqT/uhSGPQviiSzaMrNrKwo5OrlnSybP02YCSMGUlLHdpy9AETOPbYY+pQc3ojRxYNo7e9Hu0ABbUFHo/9v3eGMuLLxMsUERERERERERGpuxXrt3LVfZ0s7FjGw8s31Ls5fzV7zzH1bkK/oqC2PAp0Ac3R/5PMbJS7b0yzsJmNBiYUzOpCQW0REREREREREWkQG7fuYPHSFbQv6eT2J9fgXu8WFTt3dmu9m9CvKKg9wLn7NjN7EjioYPZxwPUpizg+9v/j7r4tl8aJiIiIiIiIiIhksKOrm1sfW8XCjk5ueOhFtu3srneTenX0vuM5eMqoejejX1FQWwAWs2tQ+yTSB7VPiv1/XQ7tERERERERERERKYu70/H8S7R3dHL1/ctZ+3L2lM9jhg1mzp5jueWxVTm2MNkHTty/6nXsbhTUFoCFwEcK/n+rmf2ru5cc6tXMmoG3JJQlIiIiIiIiIiJSE0+vfpn2jk7al3Ty7JrNmctpaW7i1JmTmN/WykkHT2TIoGY+cnkHV923LMfW7mrenGmcPGNS1crfXSmoLQB/BJ4G9o3+n04IVl/Sx3JvAQoT/jwJ/Cn31omIiIiIiIiIiBRYs2kbV9+/nIUdnSx5/qWKyjpm3/EsaGvlzEOnMmb44F1e+/y5h3DX02t4cUP+2XYnjx7Checcknu5A4GC2rshM4unuz/Z3W/u7f3u3mVmnwN+WjD7G2Z2i7s/00sd+wDfjM3+rLs3boIiERERERERERHpt7Zs7+L6h1awaMkybnlsFV3d2Ud8PHDSSBbMbeXc2dOYPm54r+8bN6KFS955NG/8wZ2s37Ijc31xY4YN5pJ3Hs24ES25lTmQKKhdY2Y2neT1PiX2/6AocJxkk7uvzrNdwM+BfwCOif4fD9xuZu9w913ya5vZ6cDFwLiC2bcDv8y5TSIiIiIiIiIiMoB1dTt3PLmGKzte4HdLV/Dy9pLZckuaNGoI8+ZMY35bK7OmjsbMUi03Y8pofvm+Y3n7j+/Opcf25NFDuOSdRzNjyuiKyxqoFNSuvduAvVO8r5WQEiTJJcA78moQgLt3m9kC4E5gr2j2VOB3ZvY48CBgwCHAAbHFnwHOc/fst8dEREREREREREQIAz4+uGwD7R2dXHXfMlZuzB5IHtHSzBmHTmVBWyvH7b8HzU3pAtlxM6aMZvFHX8WFv32QRUuy59ieN2caF55ziHpoV0hBbfkrd19uZqcBvwDaCl46MJqS/AV4o7u/WO32iYiIiIiIiIjI7uuFdZtZtGQZ7R2dPL5yU+ZympuMEw+ayPy2Vk6bOZlhLc25tG/ciBa+fX4b8+ZM4/u3PMXdT69NvezR+47nAyfur0Ehc6KgtuzC3R8zs2OATwDvAfbr5a1PAv8HfN3d80soJCIiIiIiIiIiA8b6zTu4dmkY8LGcIHGSOXuOZUFbK2cdPpUJI4fk1MJip8yYzCkzJvPoio1cdV8n9z2/nvtfeIkNW3f+9T2jhw7i8Oljmb3nGM6d3crBU0ZVrT0DkYLaNebu+9SgjmzPUfxt+R3Al4Evm9kRwEHAtOjlZcBj7n5vZa0UEREREREREZGBaNvOLm56ZBXtHZ3c+MhKtnd1Zy5r7z2GM39OK/PbWtl3wogcW9m3g6eM4p+mzABg/fr1LP7DzezshkFNcMapJzBmzJiatmcgUVBbSoqC1wpgi4iIiIiIiIhIZt3dzj3PrmNhRyfX3L9sl17N5Ro3fDDnzA4DPrbtOTb1gI/VZGYMbQaa//a/VI+C2iIiIiIiIiIiIlIVT6zcyMKOTto7ltH50pbM5QwZ1MRpsyazoK2VVx00kcHNTTm2UvobBbVFREREREREREQkNys3bOWq+5bRvqSTpZ0bMpdjBsfvvwfz57RyxqFTGDV0cI6tlP5MQW0RERERERERERGpyMvbdvK7B1ewsKOTPz2xmm7PXtasqaOZ3zaNc2e3MmXM0PwaKbsNBbVFRERERERERESkbDu7uvnjE6tp7+jk+gdfZMuOrsxlTRszlHltrcyf08rBU0bl2ErZHSmoLSIiIiIiIiIiIqm4O/e/sJ6FHZ1cff8yVm/anrmsUUMHcdZhU5nf1srR+4ynqUmDK0o6CmqLiIiIiIiIiIhISc+t2Uz7kk7aOzp5avXLmcsZ3GycfPAkFrS1cvKMSQwd3JxjK2WgUFBbREREREREREREiqx7eTtXP7Cc9o5O7n12XUVlHbXPOOa3tXLWYVMZO7wlpxbKQKWgtoiIiIiIiIiIiACwdUcXf3h4JQs7Orn50ZXsrGDEx/0mjuC8tlbmzWllz/HDc2ylDHQKaouIiIiIiIiIiAxgXd3OXU+toX1JJ9c9sIKN23ZmLmvCyCGcO3saC9paObR1NGbKky35U1BbRERERERERERkAHpkxQYW/qWTRUuWsWLD1szlDBvczBmHTmF+Wyuv2H8PBjU35dhKkWIKaouIiIiIiIiIiAwQy9dvYdGSZbR3dPLIio2Zy2kyeOWBE1nQ1sppsyYzYojCjFI72tpERERERERERER2Yxu27mDxAytY2NHJnU+vwbOnyebw6WOYP6eVs2dPZdKoofk1UqQMCmqLiIiIiIiIiIjsZrbv7OaWx1bR3tHJDQ+/yPad3ZnLmj5uGAuiAR8PmDQyx1aKZKOgtoiIiIiIiIiIyG7A3fnLc+tY2NHJ1fcv56XNOzKXNWbYYM4+fCoL2lo5Yu9xGvBRGoqC2iIiIiIiIiIiIv3Yk6s2saijk/Yly3hu7ebM5bQMauLVMycxf04rJx08iZZBGvBRGpOC2iIiIiIiIiIiIv3Mqo3buPr+MODjfS+sz1yOGRyz73gWtLVyxqFTGTNscI6tFKkOBbVFRERERERERET6gc3bd3LDQy+ysKOTPz6+mq7u7CM+HjR5JAvapjNvzjSmjR2WYytFqk9BbRERERERERERkQa1s6ub259cQ3tHJ4sfXMHm7V2Zy5o8egjz54QBH2dOHaU82dJvKagtIiIiIiIiIiLSQNydB5dtYGFHJ1fdt4xVG7dlLmvkkEGceegUFrS1csx+e9DcpEC29H8KaouIiIiIiIiIiDSA59du5qr7lrGwo5MnVm7KXM6gJuOkgycyv62VV8+czNDBzTm2UqT+FNQWERERERERERGpk/Wbd3DNA8tp7+jk7mfWVlTW3L3GsqCtlbMOn8b4ES05tVCk8SioLSIiIiIiIiIiUkNbd3Rx86MrWdjRyU2PrGJ7V3fmsvadMIL5c1qZ3zaNvfcYkWMrRRqXgtoiIiIiIiIiIiJV1t3t/PmZtbQv6eSa+5ezYevOzGXtMaKFc2ZPY35bK7Onj9GAjzLgKKgtIiIiIiIiIiJSJY+9uJH2jk4WLVlG50tbMpczdHATr5kVBnw84cAJDG5uyrGVIv2LgtoiIiIiIiIiIiI5enHDVq5aEgZ8fGj5hszlNBm84oAJzJ/TyumHTmHkEIXyREBBbRERERERERERkYpt2raTxUtX0N7RyZ+eXI179rIOmTaaBW2tnDN7GpNHD82vkSK7CQW1RUREREREREREMtjR1c0fH1/Fwo5l3PDQCrbuyD7gY+vYYcybE/JkHzR5VI6tFNn9KKgtIiIiIiIiIiKSkruz5PmXaO/o5Lf3L2fty9szlzV66CDOOnwq8+e0ctQ+42lq0oCPImkoqC0iIiIiIiIiItKHZ1a/TPuSTto7OnlmzebM5bQ0N3HyjIksaGvl5BmTGDKoOcdWigwMCmqLiIiIiIiIiIgkWLNpG9c8sJyFHZ10PPdSRWUdve945s9p5bWHTWHs8JacWigyMCmoLSIiIiIiIiIiEtmyvYvfP/wi7R2d3PLYKnZ2Zx/x8YBJI1nQ1sq8OdOYPm54jq0UGdgU1BYRERERERERkQGtq9u586k1LOzoZPHSFWzatjNzWRNHDWHe7DDg4yHTRmOmPNkieVNQW0REREREREREBhx35+HlG2lf0smiJZ28uGFb5rKGtzRzxqFTWNDWyvH7T6BZAz6KVJWC2iIiIiIiIiIiMmAse2kLi5Yso72jk0df3Ji5nOYm41UHTmB+WyunzZrM8BaF2ZlFOVwAACAASURBVERqRXubiIiIiIiIiIjs1tZv2cHipWHAxzufWltRWbP3HMuCOdM4e/Y0JowcklMLRaQcCmqLiIiIiIiIiMhuZ9vOLm5+dBWLlnTy+4dXsn1nd+ay9ho/nPltrcyfM439Jo7MsZUikoWC2iIiIiIiIiIisltwd+59dh1XdnRyzf3LWb9lR+ayxg0fzNmHhwEf5+41VgM+ijQQBbVFRERERERERKRfe2LlJto7Omlf0skL67ZkLmfIoCZePWsyC+a08qqDJtIyqCnHVopIXhTUFhERERERERGRfmflxq389r7ltHd08kDn+szlmMFx++3B/LZWzjh0CqOHDs6xlSJSDQpqi4iIiIiIiIhIv/Dytp1c/9AKFnYs47bHV9Ht2cuaMWUUC9paOXfONKaOGZZfI0Wk6hTUFhERERERERGRhrWzq5vbnlhNe0cnv3vwRbbs6Mpc1pTRQ5nXNo35c1qZOXV0jq0UkVpSUFtERERERERERBqKu/NA53oWdnTy2/uWsXrT9sxljRoyiDMPm8L8tlaO3XcPmpo04KNIf6egtoiIiIiIiIiINITn126mvaOThUs6eWrVy5nLGdxsnHjQJBa0tXLqzEkMHdycYytFpN4U1BYRERERERERkbpZ9/J2rnkgDPh4z7PrKirryL3HMb+tlbMOm8q4ES05tVBEGo2C2iIiIiIiIiIiUlNbd3Rx4yMrWdjRyc2PrmRHV/YRH/ebMIIFba3Mm9PKXnsMz7GVItKoFNQWEREREREREZGq6+527np6Le0dnVz7wHI2btuZuawJI1s4Z/Y0FrS1cljrGMyUJ1tkIFFQW0REREREREREqubRFRtZ2NHJoiWdLF+/NXM5wwY3c/ohk5nf1soJB0xgUHNTjq0Ukf5EQW0REREREREREcnVivVbueq+ThZ2LOPh5Rsyl9NkcMKBE1nQNo3XzJrCiCEKZYmIgtoiIiIiIiIiIpKDjVt3sHjpCtqXdHL7k2vw7GmyOax1DPPbWjln9lQmjRqaXyNFZLegoLaIiIiIiIiIiGSyo6ubWx9bxcKOTm546EW27ezOXFbr2GEsaGtlfts0Dpg0KsdWisjuRkFtERERERERERFJzd35y3MvsWhJJ7+9bxnrNu/IXNaYYYM56/CpLGhr5Yi9xtHUpAEfRaRvCmqLiIiIiIiIiEifnl798l8HfHx2zebM5bQ0N3HqzEnMb2vlpIMnMmRQc46tFJGBQEFtERERERERERFJtHrTNq6+bxkLlyzjvudfqqisY/Ydz4K2Vs48bCpjhg3OqYUiMhApqC0iIiIiIiIiIn+1ZXsX1z+0gvaOTm59fDVd3dlHfDxw0kgWzG1l3pxWWscOy7GVIjKQKagtIiIiIiIiIjLAdXU7tz+5moUdnfxu6Qpe3t6VuazJo4dw7uxpzG9rZdbU0ZgpT7aI5EtBbRERERERERGRAcjdeXDZBto7OrnqvmWs3Lgtc1kjWpo549CpnDe3lWP324NmDfgoIlWkoLaIiIiIiIiIyADywrrNLFqyjPaOTh5fuSlzOYOajBMPmsi8tlZOmzmZYS0a8FFEakNBbRERERERERGR3dz6zTu4dulyFnZ0cvfTaysqq22vsSxoa+Wsw6ayx8ghObVQRCQ9BbVFRERERERERHZD23Z2cdMjq2jv6OT/s3fn0XGd95nnn7cK+07sqEtS4ibuBEqSKduSrMWWRFtcqrzEns7MJJOcpOPJ6aTH7uzp2Ek7k+Vk6SydY2eynj6TiWMnVaTEaLFsydZiWbJUAHdR3Mlb2EHsa1W98wcoi4Ikgri4KBSA7+cc/3Ev7v3dR0eGWfX48n2/c6pLk+mM51m31pQoEp7e8HFdbamPKQFg7ii1AQAAAAAAlomMlV67NKCnT1/U4SNJDY6nPM+qLi3Qvl1NioQdtaypYsNHADmDUhsAAAAAAGCJ6xiVftgT0Gs9Rn0vH/E8pzAvoIe3NyoaDuneTXXKDwZ8TAkA/qDUBgAAAAAAWIK6Bsd1qC2pf33tsk52eK94jJHu3lCrSNjRI9sbVF6U72NKAPAfpTYAAAAAAMASMTKR0lPHOxRLuHrxTI8y1vusbU0VioYd7WsOqbGyyL+QALDAKLUBAAAAAAByWCqd0fNnehRPuHr6eKfGptKeZ4Uqi3Qg7CjS4mhzY7mPKQEgeyi1AQAAAAAAcoy1Vm1XBhRPuHqsLanekUnPs8qL8vTozukNH3ffWq1AgA0fASxtlNoAAAAAAAA54mLviOKJpOKtrs73jHiekx80emBzvaJhRw9sqVdRftDHlACwuCi1AQAAAAAAFlHfyKQOH0kqlnD1+qX+ec1aX27143dv0qd2r1NVSYFPCQEgt1BqAwAAAAAAZNn4VFrPnOxUPOHquTe6lZrHjo/raoq1rWRYd9Ra1RRJD9zepAoKbQDLGKU2AAAAAABAFqQzVj8416tYwtUTxzo0PJHyPKu2rFD7m0OKhh2tLZeee+45/4ICQI6j1AYAAAAAAFhAJ9sHFU+4OtiaVMfguOc5JQVBPbK9UZGwo7s31CgvGJAkDQ4O+hUVAJYESm0AAAAAAACftQ+M6WBrUvGEq1MdQ57nBANG926qVTTs6KFtDSopoMoBAP6XEAAAAAAAwAeD41N68miHYglXL5/vlfW+TLaaV1cqEna0d1dIdeWF/oUEgGWAUhsAAAAAAMCjyVRG3z3drXjC1bdOdmoylfE8a011saItjg6EHW2oK/MxJQAsL5TaAAAAAAAAc2Ct1euXriqWcPX4kXb1j055nlVVkq+9u5oUDTu6fe0qGWN8TAoAyxOlNgAAAAAAwE042z2sgwlXsVZXl/vGPM8pyAvooa0NioQd3XdbnQryAj6mBIDlj1IbAAAAAADgfXQPTejxI9MbPrZdGfA8xxjpg+tqFA072rOzURVF+T6mBICVhVIbAAAAAADgOqOTKX3rRKdiCVfPv9mjdMb7jo+bG8oVvd3R/uaQQlXFPqYEgJWLUhsAAAAAAKx4qXRGL57t1cGEqyePd2h0Mu15VkNFoSItjiJhR1ubKnxMCQCQKLUBAAAAAMAKZa3V8eSg/u11V4fakuoZnvA8q6wwTx/f0aho2NFd62sUDLDhIwAsFEptAAAAAACwolzuG9XBVlexhKuz3SOe5+QFjO7fXKdI2NHHtjaoKD/oY0oAwPuh1AYAAAAAAMte/+ikDh9tVzzh6tULV+c16/a1VYqGHT26K6Tq0gKfEgIAbhalNgAAAAAAWJbGp9J69lSXYglXz77Rpam09w0f19WWXlsnO6Rbakp9TAkAmCtKbQAAAAAAsGxkMlavXOhTPOHq8NF2DY2nPM+qKS3QvuaQomFHu1ZXyhjWyQaAXECpDQAAAAAAlrzTnUOKJVwdTLhKDox7nlOUH9Aj2xsVaXF0z6Za5QcDPqYEAPiBUhsAAAAAACxJnYPjOtSaVCzh6kT7oOc5ASPdvbFW0bCjh7c3qqyQugQAchn/Kw0AAAAAAJaM4YmUnjzWoXjC1Ytne2S9L5OtHU6FIi2O9jeHVF9R5F9IAMCCotQGAAAAAAA5bSqd0fNvdiuWSOpbJzo0PpXxPMupKlYkHFKkxdGmhnIfUwIAsoVSGwAAAAAA5BxrrVov9yuecPXYkXb1jUx6nlVRlKdHd01v+HjnLasUCLDhIwAsZZTaAAAAAAAgZ1zoGVG81VU84epC76jnOQXBgB7cUq9I2NEDW+pUmBf0MSUAYDFRagMAAAAAgEXVOzyhw0fbFUu4Slzqn9es3euqFQ07+sSOJlWW5PuUEACQSyi1AQAAAABA1o1NpvXMyU7FE66+e7pbqYz3HR831pcpGnZ0oCWk1atKfEwJAMhFlNoAAAAAACAr0hmrl8/1KpZw9eSxDg1PpDzPqisv1IHmkCJhR9tDFTKGdbIBYKWg1AYAAAAAAAvGWqsT7YM62JrUwVZXnYMTnmeVFgT1yI5GRcOOPryhVkE2fASAFYlSGwAAAAAA+C7ZP/ajDR9Pdw57nhMMGH1kU60iYUcPbWtQSQFVBgCsdPxJAAAAAAAAfDEwNqUnrm34+IPzffOa1bymStGWkPY2h1RbVuhTQgDAckCpDQAAAAAAPJtIpfXcG92KJ1x9+1SXJlMZz7NuqSlRpMVRJOxoXW2pjykBAMsJpTYAAAAAAJiTTMbqtUtXFUu4OnykXQNjU55nrSrJ175rGz6G11Sx4SMAYFaU2gAAAAAA4Kac6RpWPOEq3urqytUxz3MK8wJ6aFuDomFH926qU0FewMeUAIDljlIbAAAAAAC8r66hcT3W1q54wtVRd8DzHGOkD2+oUaTF0Z4djSovyvcxJQBgJaHUBgAAAAAA7zAykdLTJzoUSyT1wpvdyljvs7Y2VSgaDml/s6PGyiL/QgIAVixKbQAAAAAAoFQ6oxfO9CiecPXU8U6NTaU9z2qqLNKBFkeRcEhbGit8TAkAAKU2AAAAAAArlrVWR90BxRKuHmtLqmd40vOs8sI8fWJnkyJhR3etq1YgwIaPAICFQakNAAAAAMAKc7lvVPGEq1irq3PdI57n5AeN7t9cr2jY0YNb6lWUH/QxJQAA741SGwAAAACAFeDqyKQOH53e8PGHF6/Oa9adt6xSJOzo0Z1NWlVa4FNCAABuDqU2AAAAAADL1PhUWt8+2aV4q6vn3ujSVNr7jo/r60oVbXF0oMXR2poSH1MCADA3lNoAAAAAACwjmYzVy+d7FU+4euJoh4YmUp5n1ZYVaF9zSNGwo51OpYxhnWwAwOKj1AYAAAAAYBk41TGoWMLVodak2gfGPc8pzg/qke0NioQd3bOxVnnBgI8pAQCYP0ptAAAAAACWqPaBMR1qTSqWcHWqY8jznICR7tlUp2g4pIe3Naq0kLoAAJC7+FMKAAAAAIAlZGh8Sk8c61A84er753plvS+TrV2rK3WgxdG+5ibVlxf5FxIAgAVEqQ0AAAAAQI6bTGX0vdPdirW6euZEpyZSGc+zVq8qVjQ8veHjxvoyH1MCAJAdlNoAAAAAAOQga61ev9SveMLV40eSujo65XlWZXG+9u5qUiTs6I61qxQIsOEjAGDpotQGAAAAACCHnOseVrw1qXjC1aW+Uc9zCvIC+tjWekVaHN23uU6FeUEfUwIAsHgotQEAAAAAWGQ9wxN6vC2pWGtSbZf75zXrg+urFQ072rOjSZXF+T4lBAAgd1BqAwAAAACwCMYm03r6xPSGj997s0fpjPcdH29rKFM0vFr7W0Jyqop9TAkAQO6h1AYAAAAAIEvSGauXzvYolnD11LEOjUymPc9qqCjUgRZHkRZHW5vKZQzrZAMAVgZKbQAAAAAAFpC1VseTg4onXB1qS6praMLzrLLCPO3Z0aho2NEH19coyIaPAIAViFIbAAAAAIAFcOXqqA5e2/Dxza5hz3PyAkb33VanSNjRx7Y2qLiADR8BACsbpTYAAAAAAD4ZGJ3Svx9rVyzh6pXzffOaFV5bpWjY0aM7m1RTVuhTQgAAlj5KbQAAAAAA5mEildazp7oVT7j6zqkuTaYznmfdWlOiSHh6nexba0t9TAkAwPJBqQ0AAAAAwBxlMlavXuhTvDWpw0eSGhxPeZ5VXVqgfbuaFAk7allTxYaPAADMglIbAAAAAICb9GbnkGIJVwdbk3L7xzzPKcwL6OHtjYqGQ7p3U53ygwEfUwIAsLxRagMAAAAAcANdg+M61JZULOHqeHLQ8xxjpLs31CoSdvTI9gaVF+X7mBIAgJWDUhsAAAAAgBmGJ1J66liH4q2uXjzTo4z1Pmt7qELRsKN9zSE1VBT5FxIAgBWKUhsAAAAAAElT6YxeeLNHsYSrp090aHzK+4aPTlWxDrSEFAk7uq2h3MeUAACAUhsAAAAAsGJZa9V2ZUDxhKvH2pLqHZn0PKu8KE97dzUp0uLoA7dWKxBgw0cAABYCpTYAAAAAYMW52DuieCKpeKur8z0jnufkB40e3FKvaNjR/ZvrVZQf9DElAAB4L5TaAAAAAIAVoW9kUoePTG/4+Pql/nnN2n1rtSJhR5/Y2aiqkgKfEgIAgJtBqQ0AAAAAWLbGp9J65mSn4glXz73RrdQ8dnzcUFeqT96+WvubQ1pTXeJjSgAAMBeU2gAAAACAZSWdsfrBuV7FEq6eONah4YmU51m1ZYU60BJSNOxoe6hCxrBONgAAi41SGwAAAACwLJxsH1Q84epga1Idg+Oe55QUBLVne6MiYUcf3lCjvGDAx5QAAGC+KLUBAAAAAEtWsn9Mh9qSiidcneoY8jwnGDC6d1OtomFHD21rUEkBX5cBAMhV/CkNAAAAAFhSBsen9OTRDsUSrl4+3yvrfZlsNa+uVCTsaO+ukOrKC/0LCQAAFgylNgAAAAAg502mMvru6W7FE66+dbJTk6mM51lrqosVbXF0IOxoQ12ZjykBAEA2UGoDAAAAAHKStVavX7qqWMLV40fa1T865XlWVUm+9u5qUjTs6Pa1q9jwEQCAJYxSGwAAAACQU852DyuecBVvdXW5b8zznIK8gB7a2qBI2NF9t9WpII8NHwEAWA4otQEAAAAAi657aEKPtSUVb3V15MqA5znGSB9aX6NIi6M9OxtVUZTvY0oAAJALKLUBAAAAAItidDKlp493KpZw9cKZHqUz3nd83NJYrmjY0f6WkJoqi31MCQAAcg2lNgAAAAAga1LpjF4826t4wtVTxzs0Opn2PKuxokgHwiFFWhxtbarwMSUAAMhllNoAAAAAgAVlrdUxd1CxhKtDbUn1DE94nlVemKeP72xUJOzornU1CgbY8BEAgJWGUhsAAAAAsCAu943qYKurWMLV2e4Rz3PyAkb3b65XNOzoo1vrVZQf9DElAABYaii1AQAAAAC+6R+d1OGj7YonXL164eq8Zt1xyypFwo4e3dmk6tICnxICAICljlIbAAAAADAvUxnp+FWjg988oefP9mkq7X3Dx/W1pYqEHR1oCemWmlIfUwIAgOWCUhsAAAAAMGeZjNUPL/brn88G1NprNJY2kno9zaopLdC+5pCiYUe7VlfKGNbJBgAA749SGwAAAABw0053DimWcHUw4So5MC4p4GlOUX5Aj2yf3vDxno21yg96mwMAAFYeSm0AAAAAwA11Do7rUGtSsYSrE+2DnucEjHT3xlpFw44e3t6oskK+kgIAgLnjEwQAAAAA4F2Gxqf01PFOxROuXjzbI+t9mWztcCoUaXG0vzmk+ooi/0ICAIAViVIbAAAAACBJmkpn9L3T3Yq3JvWtEx0an8p4nuVUFSsSDinS4mhTQ7mPKQEAwEpHqQ0AAAAAK5i1VonL/YonXD1+pF19I5OeZ1UU5Wlv83SRfectqxQIsOEjAADwH6U2AAAAAKxA53tGFE+4ire6utg76nlO0FjtWGV1Z53V5w/crdrqKh9TAgAAvBulNgAAAACsEL3DE3r8SLtiCVetl/vnNeuuddXas7VGRd0nVXLtm2VBXsCHlAAAADdGqQ0AAAAAy9jYZFrfOjm94eP3TncrlfG+4+Om+jJFb5/e8HH1qhINDg7q2WdP+pgWAABgdpTaAAAAALDMpDNW3z/bq1jC1ZPH2jUymfY8q768UAdaQoqEHW1rqpAxrJMNAAAWF6U2AAAAACwD1lqdaB9UPOHqYGtSXUMTnmeVFgS1Z0eTomFHH9pQoyAbPgIAgBxCqQ0AAAAAS5jbP6aDra7iCVenO4c9zwkGjO67rU6RsKOHtjaouCDoY0oAAAD/UGoDAAAAwBIzMDalJ45Ob/j4g/N985rVsqZK0bCjR3c1qbas0KeEAAAAC4dSGwAAAACWgIlUWs+90a14wtW3T3ZpMp3xPOuWmhJFWhxFwo7W1Zb6mBIAAGDhUWoDAAAAQI7KZKxeu3RVsYSrw0faNTA25XnWqpJ87Wue3vAxvKaKDR8BAMCSRakNAAAAADnmTNeQ4omk4q2urlwd8zynMC+gh7Y1KBp29JHb6pQfDPiYEgAAYHFQagMAAABADugaGtdjbe2KJ1wddQc8zzFG+vCGGkVaHO3Z0ajyonwfUwIAACw+Sm0AAAAAWCQjEyk9faJDsURSL7zZrYz1PmtrU4Wi4ZD2NztqrCzyLyQAAECOodQGAAAAgCxKpTN64UyP4glXTx3v1NhU2vOspsoiHWhxFAmHtKWxwseUAAAAuYtSGwAAAAAWmLVWR64MKJZw9fiRpHqGJz3PKi/M0yd2NikSdnTXumoFAmz4CAAAVhZKbQAAAABYIJd6RxVvdRVPuDrXM+J5Tn7Q6IHN9YqEHT24pV5F+UEfUwIAACwtlNoAAAAA4KOrI5N6/Oj0ho+vXbw6r1kfuHWVImFHj+5sUlVJgU8JAQAAljZKbQAAAACYp/GptL59skuxhKvvnu7SVNr7jo/r60r1ybCjAy2O1lSX+JgSAABgeaDUBgAAAAAPMhmrl8/3Kp5w9cTRDg1NpDzPqi0r1P7mkKJhRzucChnDOtkAAADvh1IbAAAAAObgVMegYglXh1qTah8Y9zynOD+oPTsaFQk7untDjfKCAR9TAgAALF+U2gAAAAAwi/aBMR1qTSqWcHWqY8jznICR7t1Up2jY0UPbGlRayFcyAACAueITFAAAAAC8h8HxKT15rEPxhKvvn+uV9b5MtnatrlSkxdHe5ibVlxf5FxIAAGAFotQGAAAAgGsmUxl973S3Yq2unjnRqYlUxvOs1auKFb224ePG+jIfUwIAAKxslNoAAAAAVjRrrV6/1K94wtXjR5K6OjrleVZlcb727mpSNOzojltWseEjAADAAqDUBgAAALAineseVrw1qXjC1aW+Uc9zCvIC+tjWekVaHN2/uV4FeWz4CAAAsJAotQEAAACsGD3DE3q8LalYa1Jtl/vnNeuD66sVDTvas6NJlcX5PiUEAADAbCi1AQAAACxrY5NpPX1iesPH773Zo3TG+46PtzWUKRperf0tITlVxT6mBAAAwM2i1AYAAACw7KQzVi+d7VEs4eqpYx0amUx7ntVQUahIy/SGj1ubylknGwAAYJFRagMAAABYFqy1Op4cVCzh6lBbUt1DE55nlRXm6eM7GhUNO7prfY2CAYpsAACAXEGpDQAAAGBJu9w3qkNtScUSrs50DXuekxcwun9znSJhRx/b2qCi/KCPKQEAAOAXSm0AAAAAS87A6JQOH21XPOHqlQt985p1+9oqRcOOHt0VUnVpgU8JAQAAsFAotQEAAAAsCROptJ491aVYwtWzp7o1mc54nrWutvTaOtkh3Vpb6mNKAAAALDRKbQAAAAA5K5OxevVCn+Ktrg4fadfgeMrzrJrSAu1rDikSdtS8upINHwEAAJYoSm0AAAAAOefNziHFEq4Otibl9o95nlOUH9DD26Y3fLxnU63ygwEfUwIAAGAxUGoDAAAAyAldg+M/2vDxeHLQ85yAke7eWKtIi6NHdjSqrJCvPQAAAMsJn+4AAAAALJrhiZSeOtaheKurF8/0KGO9z9oeqlA07Ghfc0gNFUX+hQQAAEBOodQGAAAAkFVT6YxeeLNHsYSrp090aHzK+4aPTlWxDrRMr5N9W0O5jykBAACQqyi1AQAAACw4a63argwonnD1WFtSvSOTnmeVF+Vp764mRVocfeDWagUCbPgIAACwklBqAwAAAFgwF3tHFE8kFW91db5nxPOcgmBAD2ypUzTs6P7N9SrKD/qYEgAAAEsJpTYAAAAAX/WNTOrwkekNH1+/1D+vWbtvrVYk7OgTOxtVVVLgU0IAAAAsZZTaAAAAAOZtfCqtZ052Kp5w9dwb3UrNY8fHjfVlioYd7W8OaU11iY8pAQAAsBxQagMAAADwJJ2xevlcr2IJV08e69DwRMrzrLryQu1vDikadrQ9VCFjWCcbAAAA741SGwAAAMCcnEgOKt7q6mCrq87BCc9zSgqC2rOjUZEWRx/eUKO8YMDHlAAAAFiuKLUBAAAAzCrZP6aDrUnFE67e6BzyPCcYMPrIplpFwo4e2tagkgK+kgAAAGBu+AQJAAAA4D0NjE3pyWPtiiVc/eB8n6z3ZbLVvKZK0ZaQ9jaHVFtW6F9IAAAArDiU2gAAAAB+ZDKV0XNvdCne6uqZk12aTGU8z1pbXaJI2FGkJaT1dWU+pgQAAMBKRqkNAAAArHDWWr128apiCVeHj7arf3TK86xVJfnauyukSNjR7Wur2PARAAAAvqPUzgHGmHWSWiSFJJVJapd0UdJL1lrv3yjmn6ta0p2S1kmqkmQkDUi6IulVa23HYmUDAADA/J3pGtbBVlfxVleX+8Y8zynMC+hj2xoUbXH0kdvqVJDHho8AAABYOJTai8gY82lJX5D0ofe5pM8Y83VJv2Wt7clSJiPps5J+XtI9s1ybkPRVSX9nrU1lIR4AAADmqXtoQo+1JRVvdXXkyoDnOcZIH1pfo0jY0Z4djaooyvcxJQAAAPD+KLUXgTGmTNL/I+lzs1xaLenzkj5pjPkJa+1TC5yrUdI/SXrgJm8JS/qapJ81xnzOWntmwcIBAADAs9HJlJ4+3qlYwtULZ3qUznjf8XFLY7miYUf7W0Jqqiz2MSUAAABwcyi1s8wYE5T0dUmfmPGjbkkJTS/vsUHThfFbCxA2SDpojPmYtfaFBcpVJ+lZSVtm/GjqWq6LkjKSVku6Q1LRddfcIelZY8w91tqLC5EPAAAAc5NKZ/Ti2V7FE66eOt6h0cm051mNFUU6EA4p0uJoa1OFjykBAACAuaPUzr7f1zsL7SlNL0Hy19baybdOGmO2Sfobvb00SaGkuDFmp7W2fQFy/Xe9u9D+qqQvWWu7rj9pjKmS9CuSflnSWwsmrtb0W9t7FiAbAAAAboK1VsfcQcUSrg61JdUzPOF5Vnlhnj6+s1GRsKO71tUoGGDDRwAAAOQGSu0sMsasl/SLM05/xlp7cOa11toTxpiPSvq23i62ayR9SdLP+ZzrQsHRTQAAIABJREFUVkn/Ycbp37PW/vp7XW+t7Zf0a8YYV9JfXPejR4wxd1lrf+BnPgAAANzY5b5RHWx1FUu4Ots94nlOftDovtvqFQ07+ujWehXlB31MCQAAAPiDUju7viTp+h10/uG9Cu23WGvHjDE/KemopIJrp3/aGPOH1tpzPubaN+O4U9Jv38R9/0PSz0jaNWMWpTYAAMAC6x+d1OGj7YonXL164eq8Zt1xyypFwo727mzSqtKC2W8AAAAAFhGldpYYY4olfXrG6T+Y7T5r7WljTFzSj107lafpt6q/4mO89TOOn7bWzvp3Va211hjzmN5Zam/yMRcAAACuMz6V1rOnuhRLuHr2jS5Npb1v+Li+tlTRsKMDLY7W1pT4mBIAAABYWJTa2fOIpOu/LXzfWnvqJu/9e71dakvSJ+VvqV064/jKHO69PON41TyzAAAA4DqZjNUrF/oUT7g6fLRdQ+Mpz7Nqywq0rzmkaNjRTqdSxrBONgAAAJYeSu3smbmB4nNzuPd5SSm9/e8rbIxpsNZ2+hFMUseM46I53Dvz2r55ZgEAAICkNzqGpjd8bHWVHBj3PKc4P6hHtjcoEnZ0z8Za5QUDs98EAAAA5DBK7ezZMeP4+zd7o7V2xBhzVFL4utPbNb32tR+en3F8+xzuvWPG8avzzAIAALBidQyM61Cbq1giqZPtg57nBIx0z6Y6RcMhPbytUaWFfOwHAADA8sGn2+zZOuP4zBzvP6t3ltrbJH1nXone9m1Jb0jafO34XmPMLmvtkRvdZIxxJH3qulNTkv4/nzIBAACsCEPjU3ryWIfira5eOtsr632ZbO10KhUJO9rX3KT68rn85TsAAABg6aDUzgJjTLWk6hmnL81xzMzrfduQ0VqbMcb8lKZL8kJJAUnfNMY8bK298F73GGMaJMX1znXCv2KtTfqVCwAAYLmaSmf0vdPdiiVcfetEpyZSGc+znKpiRcOOIuGQNtaX+5gSAAAAyE2U2tlRNeN41Fo7MscZXTOOK+eR512stS8ZY/ZK+idJdZouzY8YY/5W0pOSLkqyklZL+qikn5VUc92Ir0n6b35mMsbUX8syFxuuPxgeHtbgoPe/upuLRkZGbngMYOHxewjkhqX2u2it1ZHkkA4f69JTJ7p1dcz7ho8VRXl6ZGutHt1Rr5bVFQoYI8kuu889yH1L7fcQWK74XQQW30r4PRweHl7sCD9i7Hz+fiNuijFml6S26071Wmtr5zjjFyT92XWn/s1a+6n3u94rY0yNpP8s6cclrbuJW05J+i1r7TcWIMuXJX1pPjP+/M//XGvXrvUnEAAAgAddY9JrPQH9sNuoZ8J4nhM0VjtWWd1ZZ7WtyiqP/R4BAACQRZcuXdIv/MIvXH9qh7X2+GJk4U3t7Cibcexl+/qxWWb65a3/TkzcxLUvSfqypGcWKAsAAMCSNDwlvd5j9MOegC4Oey+yJWljhdWdtRk111iV8OkdAAAAoNReJF5ej1/wV+qNMT8j6U8lld7kLR+W9LSkY8aYn7PWvrhg4QAAAHLcZFo6dtXo1W6jU/1GGXkvsxuLre6sy+iOWqvqQh9DAgAAAMsApXZ2zFxwptjDjJn3+LqIjTHmNyR9ZcbpH0r6K0nPS0pKykhqlPRBTa+p/cC163ZI+q4x5qettf/oY6y/kjTXZU02SDr41sHu3bu1detWHyMtvpGREb3yyis/Ot69e7dKS2/2/4cA4Ad+D4HckAu/i+mM1asX+/X4sS4980avRifTnmfVlRXo49vrtHdHvTbXl8qY+b3hDWRDLvweAuB3EcgFK+H38OTJk4sd4UcotbMjp0ttY8yDevcmj1+W9Dv23YuuX7j2n382xvyspK9KMpKCkv7WGHPGrze2rbVdevcGmTc088tfWVmZKioq/IiTs0pLS5f9PyOQ6/g9BHJDtn4XrbU60T6oeMLVwdakuoZuZtW291ZaENSeHU2Khh19aEONggGKbCxt/JkI5AZ+F4HFtxx/D8vKFmo15Lmj1M6OgRnHJcaYUmvtXLZBrZ9x3D/PTNf7Xekdfz/2H621vz3bTdbavzbGrJH0m9dOBTW9meWdPmYDAADICW7/mA62uoonXJ3u9P5+QTBgdN9tdYqEHT20tUHFBUEfUwIAAADLH6V2Flhre40xVyWtuu70WklzeWf/lhnHb847mCRjjKPp5USuN2uhfZ3fl/RFvf0m+R3GmF3W2iN+5AMAAFhMA2NTeuJou2IJVz843zevWS1rqhQNO9q7q0k1ZSyUDQAAAHhFqZ09JzW9seJbNmpupfb695jnh5YZx+estedv9mZr7Ygx5mW9vb62JN0liVIbAAAsSROptJ491a14wtV3TnVpMp3xPOuWmhJFWhxFwo7W1S6vNRUBAACAxUKpnT3H9M5S+0OSHruZG40xpZJ2vcc8P1TNOO7wMGPmPbUeswAAACyKTMbqhxevKpZwdfhIUoPjKc+zqksLtG9Xkw6EHYXXVLHhIwAAAOAzSu3seVLSz153fP8c7r1X7/x3lbDWdvoRSu9em9vLK0QzV4n3bRNLAACAhXSma0ixhKt4Iim3f8zznMK8gB7e3qhoOKR7N9UpPxjwMSUAAACA61FqZ89Tksb09trTHzLGbLHWnrqJe39yxnHMx1zJGcebjTEl1trROcy4fcaxl7e9AQAAsqJrcFyH2pKKt7o65g56nmOMdPeGWkXCjh7Z3qDyonwfUwIAAAB4P5TaWWKtHTXGfFPS/3bd6V+R9H/c6D5jzG2SotedSkn6Jx+jHZF0/SaWRdcyfu1mbjbG7JXkzDj9gm/pAAAAfDAykdJTxzsUS7h68UyPMtb7rG1NFYqGHe1rDqmxssi/kAAAAABuCqV2dn1Z0uckvfUaz08aY2LW2kPvdbExpkjS30squO7031prz97oIcaYmV/THrDWPvde11pr09fK9p+57vTvG2NetNbecN1uY8xaSV+dcfpFa237je4DAADIhlQ6o+fP9CiecPX08U6NTaU9zwpVFulA2FGkxdHmxnIfUwIAAACYK0rtLLLWnjPG/Jmk/3Ld6W8aY74g6a+ttZNvnTTGbJX0N3rn5pK9kn57AaL9jqT/VW8vjVIl6SVjzK9L+ruZS5EYYwok/S+S/kjv3hTy1xYgHwAAwE2x1urIlQHFEq4eP5JUz/Dk7De9j/KiPD26s0mRsKPdt1YrEGDDRwAAACAXUGpn369K2i7p49eO8yX9haT/aox5XdKQpPWaXqf6+m9Ok5KiC/EWtLX2ijHmxyV9Q1Lw2unya7n+0BjzmqbX3s5IapR0p969OaQk/Ya19nm/8wEAAMymZ1z62guX9MSJHp3rGfE8Jz9o9MDmekXDjh7YUq+i/ODsNwEAAADIKkrtLLu23MePafot7M9e96N6SXve57YuST+xkIWxtTZmjDkg6W8lNVz3o2JJ98xy+4ikX7XW/uVC5QMAAJipf3RKL3QY/bAnoPNDRtJFz7M+cOsqRcKOHt3ZpKqSgtlvAAAAALBoKLUXgbV2WNLnrq1l/UVJH3yfS/skfV3Sl6y13VnIddgYs03Sf5T005I2zHJLp6T/KekvrbXev0UCAADcpPGptL59skuxhKvn3uhSKuP9Ter1daX6ZNjRgRZHa6pLfEwJAAAAYCFRai8ia+03Nb2m9jpNLzcSklQqqUPTrxq9eP0623OY63nBR2ttn6Tfk/R7xpjVku6Q1KTpdbaNpAFJ3ZIS1tozXp8DAABwszIZq5fP9yqecPXE0Q4NTaQ8z6otK9T+5pCiYUc7nAoZwzrZAAAAwFJDqZ0DrLXnJZ1f7BwzWWuvSLqy2DkAAMDKdKpjULGEq0OtSbUPjHueU1IQ1CPbGxUJO7p7Q43yggEfUwIAAADINkptAAAA5Iz2gTEdak0qlnB1qmPI85yAke7dVKdP3u7ooW0NKingYy8AAACwXPDpHgAAAItqcHxKTx7rUDzh6vvnemWt91nNqysVCTvauyukuvJC/0ICAAAAyBmU2gAAAMi6yVRG3zvdrVjC1bdOdmoylfE8q6bQ6s5aq/9z7wfUvK7Rx5QAAAAAchGlNgAAALLCWqvXL11VLOHq8JF2XR2d8jyrqiRfD2+pVWjysm4tk4yR1tWU+JgWAAAAQK6i1AYAAMCCOtc9rHjCVbw1qUt9o57nFOQF9NDWBkXCju67rU7jo8N69tnLPiYFAAAAsBRQagMAAMB3PcMTeqwtqXjCVduVAc9zjJE+uK5G0bCjPTsbVVGU/6OfjfsRFAAAAMCSQ6kNAAAAX4xOpvStE52KJVw9/2aP0hnvOz5ubihX9HZH+5tDClUV+5gSAAAAwFJHqQ0AAADPUumMXjrbq3jC1ZPHOzQ6mfY8q6GiUJEWR5Gwo61NFT6mBAAAALCcUGoDAABgTqy1Op4cVCzh6lBbUt1DE55nlRXm6eM7GhUNO7prfY2CAeNjUgAAAADLEaU2AAAAbsrlvlEdaksqlnB1pmvY85y8gNH9m+sUCTv62NYGFeUHfUwJAAAAYLmj1AYAAMD7Ghid0uGj7YonXL1yoW9es25fW6Vo2NGju0KqLi3wKSEAAACAlYZSGwAAAO8wkUrr2VNdiiVcPXuqW5PpjOdZ62pLr62THdItNaU+pgQAAACwUlFqAwAAQJmM1asX+hRvdXX4SLsGx1OeZ9WUFmhfc0iRsKPm1ZUyhnWyAQAAAPiHUhsAAGAFe7NzSLGEq4OtSbn9Y57nFOUH9PC26Q0f79lUq/xgwMeUAAAAAPA2Sm0AAIAVpnNwXI9d2/DxeHLQ85yAke7eWKtIi6NHdjSqrJCPlgAAAAAWHt88AAAAVoDhiZSeOtaheKurF8/0KGO9z9rhVCjS4mh/c0j1FUX+hQQAAACAm0CpDQAAsExNpTN6/s1uxRNJPX2iQ+NT3jd8dKqKFQmHFGlxtKmh3MeUAAAAADA3lNoAAADLiLVWbVcGFE+4eqwtqd6RSc+zKory9OiukKJhR3feskqBABs+AgAAAFh8lNoAAADLwIWeEcVbpzd8PN8z4nlOQTCgB7fUKxJ29MCWOhXmBX1MCQAAAADzR6kNAACwRPUOT+jw0XbFEq4Sl/rnNWv3umpFw44+saNJlSX5PiUEAAAAAP9RagMAACwh41NpfetEp+IJV9893a3UPHZ83FhfpmjY0YGWkFavKvExJQAAAAAsHEptAACAHJfOWL18rlexhKsnj3VoeCLleVZdeaEONIcUCTvaHqqQMayTDQAAAGBpodQGAADIQdZanWwfurZOtqvOwQnPs0oKgtqzo1HRsKMPb6hVkA0fAQAAACxhlNoAAAA5JNk/poOtScUTrt7oHPI8Jxgw+simWkXCjh7a1qCSAj72AQAAAFge+HYDAACwyAbGpvTksekNH39wvk/W+zLZal5TpWhLSHubQ6otK/QvJAAAAADkCEptAACARTCZyui5N7oUb3X1zMkuTaYynmetrS5RJOwo0hLS+royH1MCAAAAQO6h1AYAAMgSa61eu3hVsYSrw0fb1T865XnWqpJ87d01veHj7Wur2PARAAAAwIpBqQ0AALDAznQN62Crq3irq8t9Y57nFOYF9LFtDfpk2NG9m+pUkBfwMSUAAAAALA2U2gAAAAuge2hCj7UlFW91deTKgOc5xkgf3lCjSIujPTsaVV6U72NKAAAAAFh6KLUBAMCyYq3V8ERKU2mr/KBRWWFe1pbmGJ1M6enjnfq3hKsX3uxWZh4bPm5tqlA0HNL+ZkeNlUX+hQQAAACAJY5SGwAALHmnOgZ1qDWptiv9OuYOamDs7bWqK4vztcOpUPPqKh1ocbS5sdzXZ6fSGb1wpkfxhKunT3RqdDLteVZTZZEOtDiKhEPa0ljhY0oAAAAAWD4otQEAwJL1nVOd+upz5/TKhb73vWZgbEovnunVi2d69VfPndXuW6v1+fs36IEt9Z6fa63VUXdAsYSrx9qS6hme9DyrvDBPn9jZpEjY0V3rqhUIsOEjAAAAANwIpTYAAFhyro5M6kuHjutQW3LO975yoU+v/EOfDrSE9OV927WqtOCm773cN6p4wlWs1dW57pE5P/st+UGj+zfXKxp29OCWehXlBz3PAgAAAICVhlIbAAAsKSfbB/WTf/+KOgcn5jXnYGtSL5/r1T/+1O4bLvVxdWRSh4+2K55w9cOLV+f1zDtvWaVI2NGjO5vmVKYDAAAAAN5GqQ0AAJaMk+2D+txfv/yONbPno3NwQp/92sv6+n/84DuK7fGptL5zqkuxhKvn3ujSVNr7jo/ra0sVDTs60OJobU2JH7EBAAAAYEWj1AYAAEvC1ZFJ/eTfv+Jbof2WgbEp/cTfvaJ//4V7dbpzWPGEq38/1q6h8ZTnmbVlBdrXHFI07GinUyljWCcbAAAAAPxCqQ0AAJaELx06Pu8lR95P5+CE7vmD72hsKuN5RnF+UI9sb1Ak7OiejbXKCwZ8TAgAAAAAeAulNgAAyHnfOdXpaVPIufBSaAeMdM+mOkXDIT28rVGlhXy0AgAAAICFxjcvAACQ87763LnFjvAOO51KRcKO9jU3qb68aLHjAAAAAMCKQqkNAABy2qmOQb1yoW+xY2j1qmJFWhxFwiFtrC9f7DgAAAAAsGJRagMAgJx2qHVhlx25kcrifD26q0nRsKM71q5SIMCGjwAAAACw2Ci1AQBATmu70p/V5xkj7dneqEjY0f2b61SYF8zq8wEAAAAAN0apDQAAcpa1Vsfcwaw+s7wwT3/147fLGN7KBgAAAIBcFFjsAAAAAO9neCKlgbGprD5zcDylkcl0Vp8JAAAAALh5lNoAACBnTaXtojx3MpVZlOcCAAAAAGZHqQ0AAHJWfnBxlgApyOMjEgAAAADkKr6xAQCAnFVWmKfK4vysPrOyOF+lBWwOCQAAAAC5ilIbAADkLGOMdjgVWX3mTqeSTSIBAAAAIIdRagMAgJzWvLoqu89bU5nV5wEAAAAA5oZSGwAA5CxrrbL90vT+Zie7DwQAAAAAzEneYgcAAAB4Lx0D4/qlb7bp+Td7svbM3euqtbmxPGvPAwAAAADMHaU2AADIKdZaHWpL6r/Gj2lwPJXVZ3/+vg1ZfR4AAAAAYO4otQEAQM64OjKp3zx4TIePtGf92QdaQnpgS33WnwsAAAAAmBtKbQAAkBOefaNLv/LNI+oamsj6sxsqCvXlfduz/lwAAAAAwNxRagMAgEU1MpHS7/77Sf3TDy7Nem1BnlHQBDQ2lfbt+ZXF+frHn9qtVaUFvs0EAAAAACwcSm0AALBoXrvYpy/8S5su9o7Oem3Lmir9yY81azKd0U/83SvqHJz/G90NFYX6x5/arS2NFfOeBQAAAADIDkptAACQdZOpjP70mdP62nfPKmNvfG1ewOgXP7pJn79/g/KCAUnSk7/4EX35seM62Jr0nOFAS0hf3redN7QBAAAAYImh1AYAAFl1qmNQ/9fX23SyfXDWazfVl+lPP9uiHU7lO86vKi3Qn30urAMtIX31u+f0yvm+m37+7nXV+vx9G9gUEgAAAACWKEptAACQFemM1d88f05//PRpTaYzN7zWGOmn716n//LIZhXlB9/3uge3NOjBLQ16o2NIh9pctV0e0FF3QANjUz+6prI4XzudSjWvqdT+ZkebG8t9+2cCAAAAAGQfpTYAAFhwl3pH9cVvtOrVC1dnvdapKtYffaZZH9pQc9PzNzeW65cat0iSrLUamUxrMpVRQV5ApQVBGWM8ZwcAAAAA5BZKbQAAsGCstfr6q5f13x4/oZHJ9KzXf/qO1frSvm0qL8r3/ExjjMoK86RCzyMAAAAAADmMUhsAACyIrqFx/dq/HtW3T3XNem1NaYH+70/u1CPbG7OQDAAAAACwlFFqAwAA3z1xtF2/Hjuqq6NTs1770LYG/d4nd6q2jFerAQAAAACzo9QGAAC+GRib0m8fOq5/S7izXltWmKcv7dumT9+xmjWvAQAAAAA3jVIbAAD44sUzPfqlb7QpOTA+67UfXF+tP/pMs1avKslCMgAAAADAckKpDQAA5mV8Kq3ff+KU/uGlC7NeW5AX0C8/slk/dfc6BQK8nQ0AAAAAmDtKbQAA4Fnb5X594V9adbZ7ZNZrt4cq9KefbdFtDeVZSAYAAAAAWK4otQEAwJxNpTP6y++c0V8+e0bpjL3htQEj/fwDG/WfHtykgrxAlhICAAAAAJYrSm0AADAnZ7qG9YV/adWRKwOzXruutlR//GPNun3tqiwkAwAAAACsBJTaAADgpmQyVv/w0gX9wZOnNJHKzHr9//6hW/SrH9+ikgI+bgAAAAAA/MO3TAAAMCu3f0y/9I02vXS2d9ZrGyuK9Ief3qWP3FaXhWQAAAAAgJWGUhsAALwva61iCVdfOnhcQxOpWa8/0BLS7+zfocqS/CykAwAAAACsRJTaAADgPfUOT+g3Ysf05PGOWa+tKsnXVyI7tHdXKAvJAAAAAAArGaU2AAB4l2+f7NSv/OtR9QxPzHrt/Zvr9Aef2qWGiqIsJAMAAAAArHSU2gAA4EeGJ1L6yuMn9M+vXp712uL8oH5z71b9h91rZYzJQjoAAAAAACi1AQDANa+c79MXv9Gqy31js157xy2r9MefadattaVZSAYAAAAAwNsotQEAWOEmUmn9ydOn9dfPn5O1N742P2j0nz92m37uvg0KBng7GwAAAACQfZTaAACsYMeTA/rC19v0RufQrNdubijXn3y2WdtDlVlIBgAAAADAe6PUBgBgBUpnrL763bP678+c1lT6xq9nGyP97L3r9YWHb1NhXjBLCQEAAAAAeG+U2gAArDAXekb0xW+06bWLV2e9dk11sf74My3ava46C8kAAAAAAJgdpTYAACuEtVb/7w8u6XcPn9TYVHrW6z/3gTX6zb3bVFbIxwUAAAAAQO7gWyoAACtA5+C4fvmbR/Td092zXltbVqg/+NROfXRrQxaSAQAAAAAwN5TaAAAsc48fSeo348fUPzo167V7tjfqd6M7VFNWmIVkAAAAAADMHaU2AADLVP/opH7r4HEdakvOem15UZ5+58B2RVocGWOykA4AAAAAAG8otQEAWIa+d7pbv/TNNnUOTsx67Yc31OiPPtOsUFVxFpIBAAAAADA/lNoAACwjo5Mp/d6/n9L/fPnirNcW5gX0qx/fop/40K0KBHg7GwAAAACwNFBqAwCwTLx+6aq++C9tOt8zMuu1u1ZX6k9+rFkb68uzkAwAAAAAAP9QagMAsMRNpjL6i++8qf/x7Bll7I2vDQaM/tODG/XzD2xUfvD/Z+/Ow+Qqy/SP308v6U66k046IensGyFr02EL27DJmiigyDYoAyM64owjisjPBUFRYVQERUWHccF9WETEIQGUTfYIQshKIIGE7Ht30um9n98fVU1XyqquXqpOnar+fq6rrzrnvO95zxOg28u73zynIJgCAQAAAABII0JtAABy2Oqte3X1Pa9q2ca6lHOnHFSm2y6cq5rxQwOoDAAAAACAzCDUBgAgB7W3u3727Fv61iOvq7m1PeX8y4+bpM/Pn6HS4sIAqgMAAAAAIHMItQEAyDHv7Nqva+5dohff2pVy7uiKUt1yQY2OP3hEAJUBAAAAAJB5hNoAAOQId9e9L2/QjX9aoX1NrSnnn3fYWN1wzmxVDCwOoDoAAAAAAIJBqA0AQA7Ysa9JX7h/qf68YmvKucMGFeumD1RrfvXoACoDAAAAACBYhNoAAITco8u36Av3L9XO+uaUc0+dMVI3f7BaIweXBlAZAAAAAADBI9QGACCk6hpbdOOfVui+lzeknFs2oFDXnz1LFx45XmYWQHUAAAAAAGQHoTYAACH0/JqduubeJdq4pyHl3KMmDdN3LpirCcMHBVAZAAAAAADZRagNAECINLa06duPvK6fPvNWyrkDCgv02TMO0UdPmKLCAnZnAwAAAAD6B0JtAABCYtnGWn3m7lf1xrZ9KefOHD1Et11UoxlVQwKoDAAAAACA8CDUBgAgy1rb2vWjJ9foe4+9odZ273JugUlXnjRVV502TSVFhQFVCAAAAABAeBBqAwCQRWu379Nn7lmiJe/sSTl34vBB+s4FNTpyUmUAlQEAAAAAEE6E2gAAZIG761cvrNNNC1eqsaU95fxLjp6gLy2YqbIS/qcbAAAAANC/8f+MAQAI2ObaBl1732t6+o0dKeeOHFyib55/qE6ZPjKAygAAAAAACD9CbQAAAuLuenDJJn35gWWqa2xNOf+9h47W18+do2FlAwKoDgAAAACA3ECoDQBAAHbXN+u6Py7TQ69tTjl3SGmRvvb+OTqnZozMLIDqAAAAAADIHYTaAABk2BOvb9O1972m7XubUs49YdoIffv8GlVVlAZQGQAAAAAAuYdQGwCADKlvatU3Fq7Ub19cn3JuaXGBvrhgpi49ZiK7swEAAAAA6AKhNgAAGfDyul26+p4lWrdzf8q5c8cP1a0X1mjKQeUBVAYAAAAAQG4j1AYAII2aWtv03b+8of9+ao3aveu5RQWmq06dpk+cPFVFhQXBFAgAAAAAQI4j1AYAIE1WbanTp//3Va3asjfl3Gkjy3XbRXM1Z2xFAJUBAAAAAJA/CLUBAOijtnbXj59ao1sfXa3mtvYu55pJVxw/WdecOV2lxYUBVQgAAAAAQP4g1AYAoA92NEof+fVremVDXcq5Y4cO1C0X1OjYqcMDqAwAAAAAgPxEqA0AQC+4Sy9sM/3h7QI1tacOtM8/YpxuOHuWBpcWB1AdAAAAAAD5i1AbAIAe2rGvWXeuKtCKPalf7ji8bIBuOq9aZ86uCqAyAAAAAADyH6E2AAA9sGjpZn3h/te0pyF1oH36rFG6+bxqjSgvCaAyAAAAAAD6B0JtAAC6obahRV99cLnuf2VjyrnlJUW64exZOv+IcTKzAKoDAAAAAKD/INQGACCFZ9/coWvuXaLNtY0p5x4zpVK3XFCKuUXYAAAgAElEQVSjccMGBVAZAAAAAAD9D6E2AABJNDS36ZsPr9Jdz72dcu6AogJde+Z0feT4ySooYHc2AAAAAACZQqgNAEACS97Zo8/c86rWbq9POXfGqDLdfskROmTU4AAqAwAAAACgfyPUBgAgRktbu37w+Jv6wRNvqq3du5xrcp0+1nXzh+dq+DACbQAAAAAAgkCoDQBA1Jvb9unqe17VaxtqU849qNT14YPbNGmwVFxYEEB1AAAAAABAItQGAEDt7a67nntb33x4lZpa21POv/iI0Tq88B2VFAZQHAAAAAAAOAChNgCgX9u4p0Gfu3eJnluzM+XcqiGl+tb5h2puVYmeeOKdAKoDAAAAAADxCLUBAP2Su+sPr2zUDX9crr1NrSnnnzt3jG48Z44qBhWrrq4ugAoBAAAAAEAihNoAgH5n574mfekPy/Tw8i0p5w4dVKyvv3+O3nfomAAqAwAAAAAAqRBqAwD6lb+s2KrP379UO/Y1pZx78vSD9M0PHqpRQ0oDqAwAAAAAAHQHoTYAoF/Y19Sqr/1phe5+KXUv7IHFhbrufTN1ybwJMrMAqgMAAAAAAN1FqA0AyHuL39qlq+95VRt2N6Sce/iEobr1wrmaNKIsgMoAAAAAAEBPEWoDAPJWY0ubbvvzat359Fq5dz23uND06dMO0ZUnTVVhAbuzAQAAAAAIK0JtAEBeWr6pVlffvUSvb92bcu70UYN160U1mj2mIoDKAAAAAABAXxBqAwDySmtbu/77r2v13b+sVktb19uzzaR/O2GKrj7jEJUUFQZUIQAAAAAA6AtCbQBA3nh7R72uvudV/X39npRzx1cO1HcumKt5kysDqAwAAAAAAKQLoTYAIOe5u37z4np946GVamhpSzn/4qPG67r3zVJ5Cf8zCAAAAABAruH/zQMActrWukZde99remr19pRzR5SX6JsfrNapM0cFUBkAAAAAAMgEQm0AQM7605JNuu6BZaptaEk596zZVfrGB+ZoeHlJAJUBAAAAAIBMIdQGAOScPfubdf0fl+vBJZtSzh1cWqQbz52t988dKzMLoDoAAAAAAJBJORtqm1mBpEpJgyWZu6/NckkAgAD8dfV2fe6+Jdpa15Ry7nFTh+uWC2o0ZujAACoDAAAAAABByJlQ2yLb6z4o6RxJJ0iaEDPsSvBnMbMpkiZFT/e5++IMlwkAyJD9za26eeEq/eqFdSnnlhQV6PPzZ+iyYyepoIDd2QAAAAAA5JOcCLXNbIGk76szoO5uQjFR0l8UCb2bzWysu+9Kf4UAgEz6+/rd+uw9S/TWjvqUcw8dV6FbL6zRwSMHB1AZAAAAAAAIWuhDbTO7UdIXJRVEL3nMsKuLgNvdnzCzFZJmSRog6SJJP8pQqQCANGtubdf3H39DP3ziTbV713MLC0z/+Z6D9R+nHKziwoKuJwMAAAAAgJwV6lDbzD4j6broaUeA3SDpBUl7JZ3bjWXulvTV6PF7RagNADlh9da9+szdr2r5prqUc6ccVKbbLpyrmvFDA6gMAAAAAABkU2hDbTObLulb6tyZ3SjpS5J+7O6NZjZR3Qu1H1Qk1DZJJ5hZgbu3Z6JmAEDftbe7fvbsW/rWI6+ruTX1j+vLj5ukz8+fodLiwgCqAwAAAAAA2RbaUFvSjZI6Eor9kt7Tyxc9vqbI7u6BksolTZP0eloqBACk1Tu79uuae5foxbdSv/5gdEWpbrmgRscfPCKAygAAAAAAQFiEMtQ2s1JJZ6tzl/YXexloy93dzFZKOjx6aboItQEgVNxd9768QTf+aYX2NbWmnH/eYWN1wzmzVTGwOIDqAAAAAABAmIQy1JZ0vKTS6HG9pB/3cb3NMcdj+7gWACCNduxr0hfuX6o/r9iacu6wQcW66QPVml89OoDKAAAAAABAGIU11J4Y/XRJi929uY/rxb5lrLyPawEA0uSR5Vv0xfuXamd96h/zp84YqZs/WK2Rg0tTzgUAAAAAAPkrrKH2QTHHm5PO6r7Yt4cVpGE9AEAf1DW26KsPrtDv/74h5dyyAYX68vtm6aKjxsvMAqgOAAAAAACEWVhD7aaY43RsyRsec5z67WMAgIx5bs0Ofe7e17RxT0PKuUdNGqbvXDBXE4YPCqAyAAAAAACQC8Iaam+POR6fhvVqYo53pGE9AEAPNba06duPvK6fPvNWyrkDCgv02TMO0UdPmKLCAnZnAwAAAACATmENtddEP01SjZmVu/u+3ixkZkdKGhFz6aW+FgcA6JmlG2p19T2v6o1tqX+Uzxw9RLddVKMZVUMCqAwAAAAAAOSasIbaf5NUK2mIpGJJV0j6Xi/X+mzM8Tp3f6ePtQEAuqm1rV13PLlGtz/2hlrbvcu5BSZdedJUXXXaNJUUFXY5FwAAAAAA9F+hDLXdvc3MHpJ0SfTSV8zsAXdf15N1zOx8SRdJ6khSfpvGMgEAXVi7fZ8+c88SLXlnT8q5E4cP0ncuqNGRkyoDqAwAAAAAAOSygmwX0IWvSWpTJJCukPSkmR3a3ZvN7KOSfh293yQ1SvpuBuoEAMRob3f98vm3teD2p7sVaF9y9AQt/NQJBNoAAAAAAKBbQrlTW5Lc/XUz+56kqxUJpidKesnMfifpHkm74u8xs8mSzpD0UUmHKxJmK3r/l92dl0QCQAZtrm3Qtfe9pqffSP3jduTgEn3z/EN1yvSRAVQGAAAAAADyRWhD7ahrJc2SdJYiwXSRpA9Hv6TOXdgys0ZF+m9LB4bZJuk+d781oJoBoN9xdz24ZJO+/MAy1TW2ppz/3kNH6+vnztGwsgEBVAcAAAAAAPJJqENtd283sw9I+oEiL4vs6I0dG1p3XItNRjrCbJN0p6T/yHy1ANA/7a5v1nUPLNNDSzennDuktEhfe/8cnVMzRmaWcj4AAAAAAEC8UIfakuTuTZI+ZmYLJX1Z0txkU6OfHWH2akVajtyb+SoBoH96YtU2Xfv717R9b1PKuSdMG6Fvn1+jqorSACoDAAAAAAD5KvShdgd3/4OkP5jZCZJOl/RPksZLGq7ILu0dkrZKek7SI5Iedff2LJULAHmtvqlVX39opX63eH3KuaXFBfrigpm69JiJ7M4GAAAAAAB9ljOhdgd3f1rS09muAwD6q5fe3qWr71mi9bv2p5w7d/xQ3XphjaYcVB5AZQAAAAAAoD/IuVAbANA77q59Ta1qaXMVF5rKS4p6tHO6qbVN3/3LG/rvp9ao3bueW1RguurUafrEyVNVVFjQx8oBAAAAAAA6EWoDQB5btaVOD766SUs27NGyjXWqbWh5d6xiYLHmjB2imnFDde7csZpeNTjpOis31+kzd7+qVVv2pnzmtJHluu2iuZoztiItfwYAAAAAAIBYoQ21zeyv0UOXdIG7b+vlOqMkdbws0t39pHTUBwBh9viqrfrxk2u1+O1dSefUNrTo2Td36tk3d+qOJ9do3qRKfeLkqTplxsh357S1u/7n6bW69dHVam7r+jUFZtIVx0/WNWdOV2lxYdr+LAAAAAAAALFCG2or8iJIKRJql/ZhndK4tQAgb+2ub9YNDy7Xg0s29fjexW/v0uK7duncuWP0lbNna29jqz5776v629u7U947duhA3XJBjY6dOrw3ZQMAAAAAAHRbmENtAEAPrNxcp8t/vlhb65r6tM4fX92kJ1ZtU3Nruxpbu96dLUnnHzFON5w9S4NLi/v0XAAAAAAAgO4g1AaAPLByc50uvvOFA3pm90VdY2vKOcPLBuim86p15uyqtDwTAAAAAACgO/pDqB37Z0yd0gBAjtld36zLf744bYF2d5w+a5RuPq9aI8pLAnsmAAAAAACA1D9C7RExx/VZqwIAMuSGB5f3ueVId5WXFOmGs2fp/CPGycwCeSYAAAAAAECs/hBqnxT9dEkbs1kIAKTb46u29uqlkL1x9ORK3XJBjcZXDgrkeQAAAAAAAIlkNdQ2s4JkQ3HnBV3MTaRE0mhJZ0j6Usz1pT1YAwBC78dPrg3kORMqB+l3HztGBQXszgYAAAAAANmV7Z3a3WkAa5LW9OEZsQnMg31YBwBCZdWWOi1+e1cgz1q/a7/e2LZP06sGB/I8AAAAAACAZHqy+zkTrIuv7s5L9eXRNVZI+n3m/igAEKwHXw2m7ci7z1tCBycAAAAAAJB92Q61pc7QOVNM0ouS3uvu3dkZDgA5YcmGPcE+753aQJ8HAAAAAACQSLbbjzyu5KH2qdFPl/ScpMZurumSmiTtkbRS0hPu/nxfigSAsHF3LdtYF+gzl26slbvLjL7aAAAAAAAge7Iaarv7acnGzKxdnYH3h9x9fTBVAUD47WtqVW1DsH/5pLahRfXNbSovyfbvQwEAAAAAQH8WhvYjXWE7IAAk0NKW6c5NiTW3tmfluQAAAAAAAB3CvN3uyzHHu7NWBQCEUHFhdn7nN6Ao7L8LBQAAAAAA+S60oba7fyPbNQBAWJWXFKliYHGgLUgqBharbEBhYM8DAAAAAABIhC13AJCDzExzxg4J9JnVYyt4SSQAAAAAAMg6Qm0AyFE144YG+7zxFYE+DwAAAAAAIBFCbQDIUefMHRPs82rGBvo8AAAAAACARELbUzsRMxsv6ThJMyUNk1ShngXz7u6XZaI2AAjajKohmjepUovf3pXxZ82bXKnpVYMz/hwAAAAAAIBUciLUNrMFkj4v6fi+LCPJJRFqA8gbV548RYvvynyo/YmTpmb8GQAAAAAAAN0R6vYjZlZoZndI+pMigbZFvxRznOitZZZiHADywntmjNJxU4dn9Bnnzh2jU2aMzOgzAAAAAAAAuivsO7W/I+nK6LHHXLcE57Hixwi2AeSlt3fUa+nG2oytP2pIib5y9uyMrQ8AAAAAANBToQ21zexESZ9SZ0DdKumHkn6vSEj91+h1lzRe0hBJYxTpuX2ppIOjY9skfUzS34OqHQCCUNfYoit+8TftbWzNyPoVA4v1i4/M07CyARlZHwAAAAAAoDfC3H7k2uinSWqSdKa7X+3uz0p6J3aiu29095Xu/pi7f03SdEn/Gb3vIEm/lTTF3TcGVz4AZE5rW7v+87evaM32+oysP2pIie7++DGaUTUkI+sDAAAAAAD0VihDbTMbJOkMRXZau6Rvu/uT3b3fI34o6f2K7PAuk3S/mY3KQLkAELibF63SU6u3Z2Ttc+eO0cNXnUigDQAAAAAAQimUobakeYq0RjFJbYq0Hekxd39Ukb7cklQp6UtpqQ4Asujuv63XT595K+n4CdNG6H8uPULzJlf2aN15kyv188uP0vcuPoyWIwAAAAAAILTC2lN7cvTTJa1y921dTTazQndvSzL8bUnXSCqUdJGZfdrd29NXKgAEZ/Fbu3TdA8uSjk8ZUaYf/PPhqhhUrNNnV+n1LXv14JKNWvJOrZZurFVtQ8u7cysGFqt6bIVqxlfonJqxml41OIg/AgAAAAAAQJ+ENdQeFnP8ZoLx+AC7RNL+RAu5+24ze0nSMZJGSDpW0rPpKBIAgvTOrv268tcvq6XNE44PKS3STy47UhWDit+9Nr1qsD5XNUOS5O6qb25Tc2u7BhQVqGxAocwskNoBAAAAAADSJaztR0pjjvclGN8bdz4ixXqxL5ac2KuKACCL9jW16mO/fEm76psTjhcWmH74ocM15aDypGuYmcpLilRZNkDlJUUE2gAAAAAAICeFNdSODa0HJRjfp0hrkg7jUqwX226kqrdFAUA2tLe7Pv2/r2rVlvjf53W6/n2zdMK0gwKsCgAAAAAAIDvCGmpvijkeFj8Y7Z+9PubS4SnWmxJzXNiHugAgcLc8+rr+snJr0vFLjp6gfzmWv4QCAAAAAAD6h7CG2q/HHM9MMmdpzPE5yRYys/GKhN4dO7u7fOkkAITJA69s1B1Prkk6fsyUSn31nNm0EgEAAAAAAP1GWF8UuVJSvaQySaPMrMrdt8TNeUTS+ySZpPeY2Rnu/mjsBDMrkHSHOndnu6SXMlp5L5nZZElzJY2RVC5ps6R1kp5z95Zs1iZJZlakyC8HZks6SNIARdrAbJS0WtJyd2/NXoVA/nll/W5d+/vXko5PqBykH33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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "\n", "\n", "plt.title(\"Receiver Operating Characteristic\")\n", "plt.plot(fpr1, tpr1,'-o')\n", "plt.ylabel(\"True Positive Rate\")\n", "plt.xlabel(\"False Positive Rate\")\n", "plt.axis('square')\n", "plt.grid('on')\n", "plt.ylim((0,1))\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3.6 with Spark", "language": "python3", "name": "python36" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.8" } }, "nbformat": 4, "nbformat_minor": 1 }