diff --git a/percom_moves_collect_2014/Project_scratch_mode_inference.ipynb b/percom_moves_collect_2014/Project_scratch_mode_inference.ipynb new file mode 100644 index 0000000..333cd28 --- /dev/null +++ b/percom_moves_collect_2014/Project_scratch_mode_inference.ipynb @@ -0,0 +1,8613 @@ +{ + "metadata": { + "name": "", + "signature": "sha256:61ddedfc806016babe2016aa5320aed173a1c1ffad051b2507cb5af77fde7fc7" + }, + "nbformat": 3, + "nbformat_minor": 0, + "worksheets": [ + { + "cells": [ + { + "cell_type": "code", + "collapsed": false, + "input": [ + "import pymongo" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 27 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "Sections = pymongo.MongoClient('localhost').Stage_database.Stage_Sections" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 28 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "Sections.find({'type': 'move'}).count()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 29, + "text": [ + "14506" + ] + } + ], + "prompt_number": 29 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "import numpy as np\n", + "import scipy as sp" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 5 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "confirmedSections = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}]})" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 6 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "walkSections = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': 1}]})" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 7 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "modeList = []\n", + "for mode in pymongo.MongoClient('localhost').Stage_database.Stage_Modes.find():\n", + " modeList.append(mode)\n", + " print mode" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "{u'mode_id': 1, u'_id': ObjectId('5386df6d1e860a2013835797'), u'mode_name': u'walking'}\n", + "{u'mode_id': 2, u'_id': ObjectId('5386df6e1e860a2013835798'), u'mode_name': u'running'}\n", + "{u'mode_id': 3, u'_id': ObjectId('5386df6e1e860a2013835799'), u'mode_name': u'cycling'}\n", + "{u'mode_id': 4, u'_id': ObjectId('5386df6e1e860a201383579a'), u'mode_name': u'transport'}\n", + "{u'mode_id': 5, u'_id': ObjectId('5386df6e1e860a201383579b'), u'mode_name': u'bus'}\n", + "{u'mode_id': 6, u'_id': ObjectId('5386df6e1e860a201383579c'), u'mode_name': u'train'}\n", + "{u'mode_id': 7, u'_id': ObjectId('5386df6e1e860a201383579d'), u'mode_name': u'car'}\n", + "{u'mode_id': 8, u'_id': ObjectId('5386df6e1e860a201383579e'), u'mode_name': u'mixed'}\n", + "{u'mode_id': 9, u'_id': ObjectId('5386df6e1e860a201383579f'), u'mode_name': u'air'}\n" + ] + } + ], + "prompt_number": 8 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "print Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}]}).count()\n", + "modeNameList = []\n", + "modeCountList = []\n", + "for mode in modeList:\n", + " modeCount = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': mode['mode_id']}]}).count()\n", + " print \"%s, %s\" % (mode['mode_name'], modeCount)\n", + " if modeCount > 0:\n", + " modeNameList.append(mode['mode_name'])\n", + " modeCountList.append(modeCount)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "7439\n", + "walking, 3277\n", + "running, 56" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "cycling, 1072\n", + "transport, 0" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "bus, 389\n", + "train, 303" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "car, 2237" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "mixed, 76" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "air, 29\n" + ] + } + ], + "prompt_number": 9 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "import matplotlib.pyplot as plt\n", + "import matplotlib.image as mpimg\n", + "import matplotlib as mpl\n", + "\n", + "%matplotlib inline\n", + "%config InlineBackend.figure_format='png'" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 31 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "import displayHelpers" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 11 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "cleanModeNames = {\"walking\":\"walk\", \"running\":\"run\", \"cycling\":\"cycle\"}\n", + "(fig, ax) = displayHelpers.showCategoryChart(modeNameList, [modeCountList], ['Confirmed'], ['r'],\n", + " \"Number of trip sections\", \"Trip sections by mode\", \n", + " cleanNameDict = cleanModeNames, figsize=(12,5))\n", + "ax.set_ylim(top=4000)\n", + "plt.show()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "8\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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3L3JycjBlyhTJN5U+++yzSEtLg4+PD/z8/HD58mUkJSXBzMwMn376aZX7TJw4ER999BGu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\n9/fHyZMnERUVhczMTFy9ehUREREQRVHu2AiC0ORrsDozNze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+ "text": [ + "" + ] + } + ], + "prompt_number": 259 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "startTimes = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}]}, {'section_start_datetime': 1, '_id': 0}).sort('section_start_datetime', pymongo.ASCENDING)" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 13 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "nSections = startTimes.count()\n", + "print \"Starting from %s\" % startTimes[0]\n", + "print \"Ending at %s\" % startTimes[nSections-1]\n", + "startTime = startTimes[0]['section_start_datetime']\n", + "endTime = startTimes[nSections-1]['section_start_datetime']" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Starting from {u'section_start_datetime': datetime.datetime(2014, 4, 12, 15, 57, 47)}\n", + "Ending at {u'section_start_datetime': datetime.datetime(2014, 7, 18, 22, 15, 35)}" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + } + ], + "prompt_number": 14 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "from datetime import datetime, timedelta" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 15 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "timeNameList = []\n", + "timeCountList = []\n", + "timeTotalList = []\n", + "currTime = startTime\n", + "while currTime < endTime:\n", + " currEndTime = currTime + timedelta(days=30)\n", + " if currEndTime > endTime:\n", + " currEndTime = endTime\n", + " currTimeSearch = {'section_start_datetime': {\"$gte\": currTime, \"$lte\": currEndTime}}\n", + " nTrips = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, currTimeSearch]}, {'section_start_datetime': 1, '_id': 0}).count()\n", + " nTotalTrips = Sections.find({\"$and\": [{'type': 'move'}, currTimeSearch]}, {'section_start_datetime': 1, '_id': 0}).count()\n", + " print \"%s - %s = %s, %s\" % (currTime.strftime(\"%m-%d\"), currEndTime, nTrips, nTotalTrips)\n", + " timeNameList.append(\"%s to %s\" % (currTime.strftime(\"%b-%d\"), currEndTime.strftime(\"%b-%d\")))\n", + " timeCountList.append(nTrips)\n", + " timeTotalList.append(nTotalTrips)\n", + " currTime = currEndTime" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "04-12 - 2014-05-12 15:57:47 = 3167, 3921\n", + "05-12 - 2014-06-11 15:57:47 = 2715, 4673" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "06-11 - 2014-07-11 15:57:47 = 1368, 4680" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "07-11 - 2014-07-18 22:15:35 = 189, 1166" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + } + ], + "prompt_number": 262 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "(fig, ax) = displayHelpers.showCategoryChart(timeNameList[:-1], [timeCountList[:-1], timeTotalList[:-1]],\n", + " [\"Confirmed\", \"Total\"], ['r', 'b'], \n", + " \"Number of trip sections\", \"Trip sections by start time\", figsize=(12,5))\n", + "# ax.set_ylim(top=5500)\n", + "plt.show()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "3\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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3PrC1bQ1BUCA19QquXj2I3NyHCAj4BoIgYODAr7B5cz98800fuLsPgaWlIxIT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\nr7Pfx1nyUmFr6pCt9tGjR6N9+/bYsGED4uLi8O677yIxMbH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+ "text": [ + "" + ] + } + ], + "prompt_number": 263 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "timeNameList = []\n", + "timeCountList = []\n", + "timeTotalList = []\n", + "currTime = datetime(year=2014,month=5,day=6)\n", + "while currTime < endTime:\n", + " currTimeSearch = {'section_start_datetime': {\"$lte\": currTime}}\n", + " nTrips = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, currTimeSearch]}, {'section_start_datetime': 1, '_id': 0}).count()\n", + " nTotalTrips = Sections.find({\"$and\": [currTimeSearch]}, {'section_start_datetime': 1, '_id': 0}).count()\n", + " print \"%s = %s, %s\" % (currTime.strftime(\"%m-%d\"), nTrips, nTotalTrips)\n", + " timeNameList.append(\"%s\" % (currTime.strftime(\"%b-%d\")))\n", + " timeCountList.append(nTrips)\n", + " timeTotalList.append(nTotalTrips)\n", + " currTime = currTime + timedelta(days=7)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "05-06 = 2508, 8603\n", + "05-13 = 3227, 11892" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "05-20 = 3974, 15365" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "05-27 = 4603, 18383" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "06-03 = 5195, 21629" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "06-10 = 5776, 25133" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "06-17 = 6229, 28305" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "06-24 = 6626, 31257" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "07-01 = 6882, 34503" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "07-08 = 7167, 37439" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "07-15 = 7351, 40357" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + } + ], + "prompt_number": 22 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "reload(displayHelpers)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 18, + "text": [ + "" + ] + } + ], + "prompt_number": 18 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "idList = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}]}).distinct('user_id')\n", + "idNameList = []\n", + "idCountList = []\n", + "confirmedCountList = []\n", + "for i, id in enumerate(idList):\n", + " count = Sections.find({\"$and\": [{'type': 'move'}, {'user_id': id}]}).count()\n", + " confirmedCount = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, {'user_id': id}]}).count()\n", + " print id, count, confirmedCount\n", + " idNameList.append(\"%s\" % i)\n", + " idCountList.append(count)\n", + " confirmedCountList.append(confirmedCount)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "f4254389-3592-3cd5-b206-462fb6eaa7b5 659 446\n", + "6a488797-5be1-38aa-9700-5532be978ff9" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + " 759 92\n", + "5dd35f51-3d1a-30db-9b22-ce0a432c2a59" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + " 669 465\n", + "89e30222-b446-30ad-852c-b305ddafe70d" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + " 339 301\n", + "ed8ca6a2-9092-37af-adde-46e51a18a310" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + " 129 128\n", + "527e98f8-710d-3719-93f2-ab140d1439ba" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + " 392 377\n", + 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"output_type": "stream", + "stream": "stdout", + "text": [ + " 857 164\n" + ] + } + ], + "prompt_number": 23 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "fig, axes = displayHelpers.showCategoryChart(idNameList, [confirmedCountList, idCountList],\n", + " [\"Confirmed Sections\", \"Total Sections\"],\n", + " ['r', 'b'], \"Number of trip sections\", \"Trip sections by user\", figsize=(12,5))\n", + "oldSize = mpl.rcParams['font.size']\n", + "mpl.rcParams['font.size'] = 16\n", + "labels = range(0, len(idNameList), 5)\n", + "axes.set_xticks(labels)\n", + "axes.set_xticklabels(np.array(idNameList)[labels])\n", + "fig.show()\n", + "mpl.rcParams['font.size'] = oldSize" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "45\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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7xRdfMGjQIAICArj55ptJTEzEbDbX8YqLiNQPg9VRLxEPYzAYNLapOOXMH+rz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\nR3UGg6GGKwLedG8bG29774k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'ytick.major.width': 0.5,\n", + " 'ytick.minor.pad': 4,\n", + " 'ytick.minor.size': 2,\n", + " 'ytick.minor.width': 0.5})" + ] + } + ], + "prompt_number": 65 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "from featurecalc import calDistance, calSpeed, calHeading, calAvgSpeed, calSpeeds, calAccels, getIthMaxSpeed, getIthMaxAccel, calHCR,\\\n", + "calSR, calVCR, mode_cluster, mode_start_end_coverage" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 52 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "def getSpeedsForMode(modeId):\n", + " modeSectionCursor = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': modeId}]})\n", + " speedList = []\n", + " for section in modeSectionCursor:\n", + " speeds = calSpeeds(section)\n", + " if speeds != None:\n", + " # currHistogram = sp.histogram(speeds)\n", + " speedList.append(speeds)\n", + " return speedList" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 53 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Feature matrix construction" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "# Features are:\n", + "# 0. distance\n", + "# 1. duration\n", + "# 2. first filter mode\n", + "# 3. sectionId\n", + "# 4. avg speed\n", + "# 5. speed EV\n", + "# 6. speed variance\n", + "# 7. max speed\n", + "# 8. max accel\n", + "# 9. isCommute\n", + "# 10. heading change rate (currently unfilled)\n", + "# 11. stop rate (currently unfilled)\n", + "# 12. velocity change rate (currently unfilled)\n", + "# 13. start lat\n", + "# 14. start lng\n", + "# 15. stop lat\n", + "# 16. stop lng\n", + "# 17. start hour\n", + "# 18. end hour\n", + "# 19. both start and end close to bus stop\n", + "# 20. both start and end close to train station\n", + "# 21. both start and end close to airport\n", + "featureLabels = [\"distance\", \"duration\", \"first filter mode\", \"sectionId\", \"avg speed\",\n", + " \"speed EV\", \"speed variance\", \"max speed\", \"max accel\", \"isCommute\",\n", + " \"heading change rate\", \"stop rate\", \"velocity change rate\", \"start lat\", \"start lng\",\n", + " \"stop lat\", \"stop lng\", \"start hour\", \"end hour\", \"close to bus stop\", \"close to train stop\",\n", + " \"close to airport\"]\n", + "bus_cluster=mode_cluster(5,105,1)\n", + "train_cluster=mode_cluster(6,600,1)\n", + "air_cluster=mode_cluster(9,600,1)\n", + "def generateFeatureMatrixAndResultVector(sectionQuery):\n", + " confirmedSections = Sections.find(sectionQuery)\n", + " featureMatrix = np.zeros([confirmedSections.count(), len(featureLabels)])\n", + " resultVector = np.zeros(confirmedSections.count())\n", + " for (i, section) in enumerate(confirmedSections):\n", + " featureMatrix[i, 0] = section['distance']\n", + " featureMatrix[i, 1] = (section['section_end_datetime'] - section['section_start_datetime']).total_seconds()\n", + " \n", + " # Deal with unknown modes like \"airplane\"\n", + " try:\n", + " featureMatrix[i, 2] = section['mode']\n", + " except ValueError:\n", + " featureMatrix[i, 2] = 0\n", + " \n", + " featureMatrix[i, 3] = section['section_id']\n", + " featureMatrix[i, 4] = calAvgSpeed(section)\n", + " speeds = calSpeeds(section)\n", + " if speeds != None:\n", + " featureMatrix[i, 5] = np.mean(speeds)\n", + " featureMatrix[i, 6] = np.std(speeds)\n", + " featureMatrix[i, 7] = np.max(speeds)\n", + " else:\n", + " # They will remain zero\n", + " pass\n", + " accels = calAccels(section)\n", + " if accels != None and len(accels) > 0:\n", + " featureMatrix[i, 8] = np.max(accels)\n", + " else:\n", + " # They will remain zero\n", + " pass\n", + " featureMatrix[i, 9] = ('commute' in section) and (section['commute'] == 'to' or section['commute'] == 'from')\n", + " featureMatrix[i, 10] = calHCR(section)\n", + " featureMatrix[i, 11] = calSR(section)\n", + " featureMatrix[i, 12] = calVCR(section)\n", + " if section['section_start_point'] != None:\n", + " startCoords = section['section_start_point']['coordinates']\n", + " featureMatrix[i, 13] = startCoords[0]\n", + " featureMatrix[i, 14] = startCoords[1]\n", + " \n", + " if section['section_end_point'] != None:\n", + " endCoords = section['section_end_point']['coordinates']\n", + " featureMatrix[i, 15] = endCoords[0]\n", + " featureMatrix[i, 16] = endCoords[1]\n", + " \n", + " featureMatrix[i, 17] = section['section_start_datetime'].time().hour\n", + " featureMatrix[i, 18] = section['section_end_datetime'].time().hour\n", + " \n", + " featureMatrix[i, 19] = mode_start_end_coverage(section,bus_cluster,105)\n", + " featureMatrix[i, 20] = mode_start_end_coverage(section,train_cluster,600)\n", + " featureMatrix[i, 21] = mode_start_end_coverage(section,air_cluster,600)\n", + " resultVector[i] = section['confirmed_mode']\n", + " return (featureMatrix, resultVector)" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 54 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "(featureMatrix, resultVector) = generateFeatureMatrixAndResultVector({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}]})\n" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 55 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "print(np.max(featureMatrix[:,10]))\n", + "print(np.max(featureMatrix[:,20]))\n", + "print(np.max(featureMatrix[:,12]))\n", + "print featureMatrix.shape, resultVector.shape" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "0.0246913580247\n", + "1.0\n", + "0.0582191780822\n", + "(7439, 22) (7439,)\n" + ] + } + ], + "prompt_number": 56 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "runIndices = resultVector == 2\n", + "transportIndices = resultVector == 4\n", + "mixedIndices = resultVector == 8\n", + "airIndices = resultVector == 9\n", + "unknownIndices = resultVector == 0\n", + "strippedIndices = np.logical_not(runIndices | transportIndices | mixedIndices)\n", + "print \"runIndices = %s\" % (np.nonzero(runIndices))\n", + "print \"transportIndices = %s\" % (np.nonzero(transportIndices))\n", + "print \"mixedIndices = %s\" % (np.nonzero(mixedIndices))\n", + "print \"airIndices = %s\" % (np.nonzero(airIndices))\n", + "print \"unknownIndices = %s\" % (np.nonzero(unknownIndices))\n", + "print \"strippedIndices count = %s\" % (np.count_nonzero(strippedIndices))" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "runIndices = [ 23 56 136 323 324 358 503 894 897 899 901 1078 1085 1099 1114\n", + " 1690 1757 1758 3060 3831 3868 3874 4154 4166 4201 4799 5009 5020 5027 5036\n", + " 5037 5041 5047 5059 5069 5078 5087 5088 5114 5120 5123 5124 5131 5158 5164\n", + " 5165 5173 5174 5175 5181 5182 5186 5697 5729 5734 5782]\n", + "transportIndices = []\n", + "mixedIndices = [ 3 230 1372 1380 1398 1762 3248 3249 3250 3253 3254 3255 3260 3273 3274\n", + " 3406 3408 3437 3439 3440 3528 3529 3530 3531 3532 3533 3535 3536 3537 3538\n", + " 3539 3540 3541 3542 3543 3544 3545 3627 3751 4193 4209 4726 5544 5545 5546\n", + " 5556 5575 5586 5587 5588 5589 5597 5917 6195 6199 6210 6211 6512 6513 6997\n", + " 7019 7055 7056 7241 7242 7244 7245 7246 7248 7251 7258 7278 7282 7288 7311\n", + " 7315]\n", + "airIndices = [ 906 1815 2080 2319 2328 4384 5388 5574 5581 5582 5583 5584 5585 5590 5591\n", + " 5592 5593 5594 5595 5611 5612 5613 5614 5615 5616 5617 5618 6487 7279]\n", + "unknownIndices = []\n", + "strippedIndices count = 7307\n" + ] + } + ], + "prompt_number": 57 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, we filter out \"mixed\" and \"running\", since there are few instances of them and we don't intend to predict them initially. We also filter out any \"transport\" since it should never be in the confirmed set, and we don't want to deal with it if it is." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "strippedFeatureMatrix = featureMatrix[strippedIndices]\n", + "strippedResultVector = resultVector[strippedIndices]" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 58 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "First, we visualize the distribution of some of the features. This is so that we can compare our dataset to Zheng et al 2010." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "def plotFeatureVector(featureMatrix, resultVector, featureIndex, modeList):\n", + " avgSpeedFig, avgSpeedAxes = plt.subplots(1,1)\n", + " currModeSpeedsList = []\n", + " currModeNamesList = []\n", + " for mode in modeList:\n", + " currModeMask = resultVector == mode['mode_id']\n", + " currModeSpeeds = featureMatrix[currModeMask, featureIndex]\n", + " # print \"For mode %s, shape is %s\" % (mode['mode_id'], str(currModeSpeeds.shape))\n", + " if np.count_nonzero(currModeMask) != 0:\n", + " currModeNamesList.append(mode['mode_name'])\n", + " currModeSpeedsList.append(currModeSpeeds)\n", + " avgSpeedAxes.hist(currModeSpeedsList, normed=True, histtype=\"bar\", label=currModeNamesList)\n", + " avgSpeedAxes.set_ylabel(\"number of segments\")\n", + " avgSpeedAxes.set_xlabel(featureLabels[featureIndex])\n", + " plt.legend()" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 59 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "for col in range(0, len(featureLabels)):\n", + " plotFeatureVector(strippedFeatureMatrix, strippedResultVector, col, modeList)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stderr", + "text": [ + "/Users/shankari/OSS/anaconda/lib/python2.7/site-packages/matplotlib/pyplot.py:412: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_num_figures`).\n", + " max_open_warning, RuntimeWarning)\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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RtWtXPD09uXXrFuvWrWPRokX6+w6HDx+mRo0a+RqwEKLoOHDgQLaylJQUjh8/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\nooi4d+8er776qqpt33zzTX7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hxOPJoZJDuRzn1aGSQ+FBBVi8eDHe3t58+umnrFu3juzsbFxdXenZsyfNmjUz\niW/QoAFNmjTh+PHjRjcA3U+n07F582aWL1/OypUriYiIQKfTUbNmTUJCQozuqjU3MHtxDdYeEhKC\no6MjH3zwAStWrKBy5cr06tWLMWPG4ObmZvKYzeNGU9EcMmQIFy5cIDQ0VB0yr0OHDuj1eiZMmEBQ\nUFCJJimEeDw96jOJFKRXr175zqP7d7du3eLs2bM8//zzvPDCC/nG6fV6QkJCjCaVMCcmJsakrV+/\nfvTr18+oLb9xvvPkt6x379707t3bqO27774DoF69egXm9qjTVDQBPvjgA0JCQvj222+5du0alStX\npkOHDkYTPQshhCi68PBwbt26VWgxLA9SU1Oxt7c3mvnqjz/+YPLkyeh0Orp27VqG2ZU8zUUTcv8r\neeONN0oqFyGEeKJ88MEHXLt2jc8++ww3NzcGDBhQ1ikV6rvvviMkJISXXnoJFxcXrl69SnR0NFev\nXiUoKOixH+SgSEUzOTmZ5ORkMjIyTJb5+fkVW1JCCPEkmDRpEjY2NjRt2pQlS5YUy7zFJa1Ro0b4\n+/uzb98+rl+/joWFBfXq1ePdd99l5MiRZZ1eidNUNC9cuMDrr7/Of/7zH7PLdTqd0agRQgghCvco\nTobh4eHB+vXryzqNMqOpaA4ePJjk5GQWL15MvXr1sLa2Lum8hBBCiHJHU9E8duwYERER9OjRo6Tz\nEUIIIcotTU+hOjs7y9GlEEKIJ56movnuu+8yd+5cbt26VdL5CCGEEOWWptOzAwYM4NSpUzz77LO0\nbNlSnUT1fmvWrCn25IQQQojyRFPRjIiIYOHChej1euLi4oxO1SqKUixDMwkhhBDlnaaiOWPGDF55\n5RVWrlyJo6NjSeckhBBClEuarmn+/vvvvPnmm1IwhRBCPNE0FU1vb29Onz5d0rkIIcQjLzY2Fr1e\nz4wZM8o6FVECNJ2e/eSTTwgMDMTR0ZFOnTqZvRHocZ9DTQghikLu9Xg8aSqaDRo0AKBv375ml8sw\nekKIB+FUsSKp6eVvPk2DgwM3bj6+05aJB6epaObNoZkf+Y9KCPEgUtPTUco6CTN05bCQi/JBU9EM\nDQ0t4TSEEOLxExsby9SpUzl+/Dg2NjZ07tyZefPm8fTTTwNw8eJFatWqRb9+/YiIiDDpr9fradeu\nndGk0pcvX+b9998nKiqKy5cvY2tri4uLC76+vnz00UdYWhZp8ipRRHIhUgghSsD333/PSy+9xNNP\nP81bb73LogMZAAAgAElEQVRFs2bN+OKLL2jdujU3btwwii3obN39y27fvo23tzfh4eE0btyY0aNH\nExwcjKurK+Hh4fz5558ltj8il+bnNPP7per1eipVqkTTpk1p3bp1sSYnhBCPqt27d7Ny5Ur69++v\ntk2bNo1Zs2YRGhrKxx9/XOR1fvfdd1y6dInFixebzF35xx9/YGdn97Bpi0JoOtKcMWMGoaGhZl/T\npk3jrbfeok2bNrRu3Zo//vijwHUlJyfTo0cPHB0dqVSpEt27dyc5OVlTshkZGYwfPx5nZ2fs7e3x\n9vbmwIEDJnGKojBnzhzc3d2xs7PDy8uLLVu2mF1neHg4np6e2Nra4unpyWeffWYSs2PHDl5//XU8\nPDzQ6/X4+vqaXVdoaCh6vd7k9eqrr2raPyHE48PT09OoYAJMnDgRR0dHvvzyy4dat62trUlbpUqV\n5P6SUqCpaCYkJFCnTh0WLFhAUlISd+/e5eLFi8yfP5+6dety6NAhNmzYwOnTp3n33XfzXc+dO3fw\n8/PjzJkzrFmzhs8//5yzZ8/i6+vLnTt3Cs1j0KBBrFixglmzZvH111/j7OxMx44d+fnnn43ipkyZ\nwowZMxg1ahRRUVG0bNmSwMBAdu3aZRQXHh5OSEgIgYGBREdHExgYyPDhw1m2bJlRXGRkJCdOnMDb\n25saNWoU+od56NAhjhw5or7mzZtX6L4JIR4v5s682dvb4+XlRWpqKpcuXSryOn18fHj66ad58803\n6dWrFxEREZw7d6440hVaKRr4+fkpH3zwgdllH3zwgeLr66soiqLMnTtXcXV1zXc9ixYtUiwsLJTz\n58+rbYmJiYqlpaXy0UcfFZjD8ePHFZ1Op6xatUpty87OVurVq6cEBASobVevXlWsra2V0NBQo/7+\n/v5Ko0aN1PdZWVlK1apVlf79+xvFDRw4UKlSpYqSlZWltuXk5Kg/t27dWt3fv5s+fbqi0+mUe/fu\nFbgvee7/+AcPHqHAxwoo/3uFKBYNLRVCyX31QXHW6ZT7AhSsrBR27FCIiVGIiVEqPlVdmcc8JYYY\nJYYYJUgXpLz33nuachGiJBT2FcN9f8/l6aXxq9GsmJgYRafTKZMmTTK7vHfv3opOp1NOnDihJCYm\nKjqdThkwYIDZWJ1OZ/J9c/HiRaVv376KwWBQdDqdotPplHr16ilfffXVA+dcXmj93B/m9/OwNB1p\nHjlyhBdeeMHssqZNm3LkyBEAmjVrxtWrV/Ndz/bt22nVqhW1atVS29zd3WndujWRkZEF5rB9+3as\nrKzo1auX2mZhYUHv3r2Jjo4mKysLQP05KCjIqH9QUBAnT54kKSkJgMOHD3P9+nWTuODgYFJSUjh4\n8KDaVtRTHrm/UyHEk+zatWtm2/O+IytVqqQOCpOdnW0Sl9+lrpo1a7J69WquX7/ODz/8wKxZs0hN\nTaVPnz5Gd9mKkqGpaFasWJE9e/aYXfbdd99RqVIlIPeaY8WKFfNdT3x8PM8995xJe4MGDUhISCgw\nh/j4eGrVqmVyLr9Bgwb8+eef6imK+Ph4bGxsqF27tkkcoG4nPj4ewCSfvLiHGTawRo0aWFpa4u7u\nzsSJE8nIyHjgdQkhHk33/+Od5/bt2xw/fhyDwYCbm5s6nvevv/5qEvvTTz8VuH69Xk/Tpk2ZNGkS\ny5cvB2Dnzp3FkLkoiKa7ZwcNGsScOXNIT08nMDCQatWqce3aNTZs2MCyZcvU65hHjx7l+eefz3c9\nqampZofgc3JyIjU1tcAcbty4kW/fvOVFjQNMYv8eVxR169Zl7ty5NGnSBJ1OR3R0NAsXLiQuLo7d\nu3cXeX1CiEfXmTNniIiIYMCAAWrbBx98QFpamnrna8WKFalXrx4HDhzg/Pnz6j/76enpZu8POX36\nNJUrV6ZatWpG7b/99htg/gYhUbw0P3ICsGjRIj799FO1/amnnmLSpEnq8i5dutC7d+8SSLNoyur0\naJ8+fYze+/v74+rqyujRo9m7dy9+fn5lkpcQovR16NCBYcOG8fXXX+Ph4cEPP/zAnj17qFWrltGA\nMePGjWPIkCG0atWKHj16kJOTQ1RUFC+++CJHjx41Wmd0dDTvvPMObdq0oU6dOjg5OXHmzBl27tyJ\nwWBg8ODBpbyXTx5Np2ctLCyYNWsWycnJxMbGsnbtWmJjY7l06RLvvfeeel6+efPm6ulNcwwGg9kj\nyhs3bqhHeAX1NXf0l9eW199gMJCWlqYpDjDJ5+9xDyvvn4hjx44Vy/qEEI8Gb29voqOjuXbtGh9/\n/DFxcXEEBwdz8OBBozNcgwcPZsmSJRgMBv79738THR3NgAEDWLt2rck6X3rpJd58803S0tLYvHkz\nixcv5uTJkwwaNIi4uDieffbZ0tzFJ1KRxlsyGAy0bdv2gTfWsGFDTp06ZdKekJBQYLHN67tt2zYy\nMjKMTkEkJCRgbW1NnTp11LjMzEyjUx15cfDXNcuGDRsCcOrUKapXr55vXEnL+4/zxx+PAvKMlXiy\nGBwcyuU4rwYHhwfu6+PjQ05Ojvp+//79hfYZNmwYw4YNM2m/fz2Q++znwoULHzi3R1VsbCyxsbFl\nnQZQhGH0/vvf/zJmzBiaNWvGs88+qxa/hQsXmpxCyE9AQABHjhwhMTFRbbt48SLff/89AQEBhfbN\nyspiw4YNalt2djbr16+nY8eOWFlZAdCpUyesrKxMHh7+4osveP7556lZsyaQ+19glSpVzMZVrly5\n2EY3ylt/ixYtzC7PGySiWbMWQN1i2aYQj4obN2+iKEq5e8kMJ+WLj4+P0aA6ZUnTkWZ8fDxt2rTB\nwsKCli1b8tNPP6ljHCYlJXHs2DG++uqrQtfzxhtvEBYWRteuXZk1axYAU6dOxc3NjaFDh6pxSUlJ\n1K5dm+nTpzN16lQAvLy86NWrF6NHjyYrKwt3d3eWLl1KUlKS0WmMqlWrMnbsWObMmYODgwNNmjRh\n/fr1xMTEsGPHjr923NKS9957j+HDh+Pi4oK/vz979+4lIiKCsLAwo0GP8/YRICUlBQsLCzZt2gTk\nnpJ2c3MDch+56d+/P3Xr1kVRFL799lvCwsLo1KkTPj4+Wj5qIYQQ5Zimojlu3Djq169PVFQUdnZ2\nWFtbq8u8vb2ZMGGCpo3Z29uzd+9exowZQ3BwMIqi0L59exYtWoS9vb0apygKOTk5Jjf0REREMHny\nZKZMmUJaWhpeXl5ERUXh5eVlFDd79mwqVKjA4sWL+e233/D09GTjxo107tzZKG7o0KHodDoWLFjA\n/PnzqVmzJkuWLCEkJMQoLiYmhoEDBwJ/PbPZs2dPdDodERER6jyjHh4eLF68mCtXrpCTk6MW/nfe\neUfT5yOEEKJ801Q0Dx48yFdffYWDg4PJQ7jVq1dXb3fWokaNGupRWn7c3d1NzuVD7u3UCxYsYMGC\nBQX21+v1TJ48mcmTJxeaz5AhQxgyZEiBMf379zcZQ9IccxfuhRBCPD40XdPU6/X5jopz/fp1GVlf\nCCHEE0FT0XzxxRdZuXKl2WUbN26UKcGEEEI8ETSdnp02bRr+/v506NCB119/HYA9e/awaNEitmzZ\noumWaiGEEOJRp+lIs127dkRGRpKYmMigQYOA3HnhDh48SGRkJC1btizRJIUQQojyQPPgBi+//DIv\nv/wyZ8+e5dq1a1SuXJl69erJpKfl2H+V//LjV/vYv/8bta1Llx6MGjW2DLMSQohHV5FGBILcQcnr\n1s19CD8lJYXKlSsXe1KieFzX/Y6razJ+fskAJCRAVJSVFE0hhHhAmk7PLl++nPnz56vvT548iYuL\nC1WrVqVZs2ZFeuRElK4aNaBly9xXvXplnY0QQjzaNBXNsLAwo/Fex44di8FgYNGiRfzxxx/qqD1C\nCCHE40zT6dmkpCTq168PQFpaGvv27WPr1q28/PLLVKlShYkTJ5ZokkIIIUR5oOlIMycnR53+K282\ncl9fXwBcXV25du1aCaUnhBCiID4+Pur3syh5mj7pOnXqsHPnTgDWr1+Pt7e3OlbslStXim3uSSHE\nk6WiwYBOpyt3r4r3zXf5IGJjY9Hr9cyYMaOYPqn85eUsSoem07Pjx48nODiY1atXk5qaysaNG9Vl\nMTExNGrUqMQSFEI8vtLT0iAmpqzTMJH+vzNpD6s0itmaNWu4e/duiW9H5NJUNF9//XXc3Nw4cuQI\nzZs3N5qIulq1aoXOhSmEEE+iv8/UVBJq1KhR4tsQf9F8Ivwf//gHb7/9tlHBBJg5c6bJlFtCCPGk\nCg0Nxc/PD4AZM2ag1+vVV1JSEv3790ev13PhwgXmz59P/fr1sbW1ZcyYMQCcOXOG8ePH4+XlhZOT\nE3Z2djz33HPMnj3bZJYpMH9NMzQ0FL1ez759+/jqq69o0qQJ9vb2PPPMM4wePZqMjIyS/yAeU0Ue\n3EAIIUT+fH19SUpKYvXq1fj4+BhNQO/o6Kj+PGLECI4dO0aXLl3o2rUrtWrVAmDLli2sWrUKf39/\n/vnPf5KZmUlsbCxTp07lhx9+YOvWrSbbzO80cFhYGFFRUbzyyiv4+/uza9cuPv74Y65fv84XX3xR\nvDv+hJCiKYQQxahdu3YoiqIWzWnTppmNO336ND///DPPPPOMUXu/fv14++23sbQ0/noeMmQIK1as\n4NChQ5pnlvruu++Ii4tTR3GbNWsWXl5erFu3jvnz5+Ps7PwAe/hkk/uUhRCiDIwfP96kYAI4Ozub\nFEyAkJAQILcQavXWW2+pBRPA1taW1157jZycHOLi4h4gayFFUwghysALL7xgtj0nJ4fw8HBat26N\no6MjFhYW6PV6Nf7KlSuat9GsWTOTNhcXFyB3oBpRdPmenm3atCmff/45DRs2ZObMmQwaNEj9sIUQ\nQjyc6tWrm20fOXIkS5cuxd3dnR49evD0009jbW1NamoqixcvJjMzU/M2KlasaNKWdxR77969B0v8\nCZdv0Tx58iTp6elA7p1YL730khRNIYQoJuZu3rl69SpLly7Fy8uLw4cPY2Njoy47evQoixcvLs0U\nhRn5Fk1nZ2e2bdum/jd05coVLl26lO+K3Nzcij87IYR4BFlYWABFP5pLTEwEoH379kYFE+DQoUPF\nk5x4KPkWzZCQEKZMmcK8efMA6NatW74r0el0cqgvhBD/kze0aEEHGubUrFkTgO+//96o/cyZM8yZ\nM6d4khMPJd+iOWnSJNq3b8/p06cZMGAA7777Ls8++2xp5iaEEI+k+vXr88wzz7Bu3TpsbGxwcXFB\nr9czcuTIAvs5OzvTrVs3tm7dyosvvoiPjw+XL19mx44ddOzYkc2bN5vtVxojD4lcBT6n2bx5c5o3\nb05ERARBQUHq9GBCCCHyp9fr2bJlCxMmTGDt2rWkp6ej0+kICgoqdID11atX4+bmxtatWwkLC6NO\nnTq8//77dOnSxWzRNLe+grYhA7w/HJ0i/6KUGZ1Op/6H+MYbI1mxwgPI+090GBYNV3Av8H/DZp0F\n5690XL7v16WzsoItW6BCBQAqdunNlNvjeJEXARipG0HzAfEEB+fGHzoEhw615Ztv9pXG7glh9Ddu\nTkWDIXfQ9nLGwdGRm6mpZZ3GE6ewv5eixpUEzc9pnjhxgu7du1OlShUsLCyoWrUqgYGBnDx5siTz\nE0I8xm6mpqIoSrl7ScEU+dE0jN6xY8do164ddnZ2BAQEUL16dX777Td27NjBN998w759+/J9UFcI\nIYR4XGgqmu+++y7PPfcc3333HQ4ODmp7eno67du359133+Xbb78tsSSFEEKI8kDT6dkjR44wceJE\no4IJ4ODgwIQJEzh8+HCJJCeEEEKUJ5qKZmF3WsmdWEIIIZ4EmopmixYtmDNnDjdv3jRqv3XrFnPn\nzqVly5YlkpwQQghRnmi6pvn+++/Trl073N3d6dKlC87Ozly5coVvvvmGO3fuEBsbW8JpCiGEEGVP\n05Fm8+bNOXr0KH5+fkRFRfHRRx8RHR2Nn58fR48epXnz5po3mJycTI8ePXB0dKRSpUp0796d5ORk\nTX0zMjIYP348zs7O2Nvb4+3tzYEDB0ziFEVhzpw5uLu7Y2dnh5eXF1u2bDG7zvDwcDw9PbG1tcXT\n05PPPvvMJGbHjh28/vrreHh4oNfr8fX1zTfHgwcP4u3tjb29Pc7OzowbN46MjAxN+yeEEKJ803Sk\nCdCoUSM2bdr0UBu7c+cOfn5+2NnZsWbNGgCmTJmCr68vJ06cwN7evsD+gwYN4ptvvuHDDz+kVq1a\nhIWF0bFjRw4fPkzjxo3VuClTprBgwQLef/99mjVrxtq1awkMDGTnzp106tRJjQsPDyckJEQdMnDP\nnj0MHz4cRVHUCV8BIiMjOXHiBN7e3mRmZuZ7DffEiRN06NCBTp068fXXX3PhwgXGjx/Pr7/+yrp1\n6x7moxNCCFEeKKVo0aJFioWFhXL+/Hm1LTExUbG0tFQ++uijAvseP35c0el0yqpVq9S27OxspV69\nekpAQIDadvXqVcXa2loJDQ016u/v7680atRIfZ+VlaVUrVpV6d+/v1HcwIEDlSpVqihZWVlqW05O\njvpz69atFV9fX7M5vvLKK4qHh4eSnZ2ttq1Zs0bR6XRKXFycSfz9H//gwSMU+FgB5X+vEMWioaVC\nKLmvPijOOp1yX4CClZXCjh0KMTEKMTFKxaeqK/OYp8QQo8QQozyna6gMHIgSE5P7mjULpVOntvl+\nxkIUt1L+ihGPOK1/L2X5d6V5RKDisH37dlq1akWtWrXUNnd3d1q3bk1kZGShfa2srOjVq5faZmFh\nQe/evYmOjiYrKwtA/TkoKMiof1BQECdPniQpKQmAw4cPc/36dZO44OBgUlJSOHjwoNqm5e7grKws\noqKi6NmzpzotEEBgYCDW1taF7p8QQojyr1SLZnx8PM8995xJe4MGDUhISCi0b61atbC1tTXp++ef\nf3Lu3Dk1zsbGhtq1a5vEAep24uPjAUzyyYs7ffq01t0C4Pz582RmZpqsz9bWltq1axd5fUIIIcqf\nUi2aqampGAwGk3YnJydSCxnr8caNG/n2zVte1DjAJPbvcVrlt768tqKuTwghRPlTqkWztCgycYsQ\nQogSUGjRzMzMxGAwsH379ofemMFgMHtEeePGDfUIr6C+5o7W8try+hsMBtLMTDVkLg4wyefvcVrl\nt768dRZ1fUI8CQwVDer8juXpZahoesZICNDwyImNjQ2WlpYm1xIfRMOGDTl16pRJe0JCgnotsaC+\n27ZtIyMjwyiXhIQErK2tqVOnjhqXmZnJ+fPnja5r5l3LzNtOw4YNATh16hTVq1fPN06r2rVrY2Nj\nw6lTp4xuVsrIyCAxMdGo7X6hoaEA/PjjUUCGIxRPlrT0NGKIKes0TPim5/8stih9sbGx5WYQHU2n\nZ1955ZWHfkYTICAggCNHjpCYmKi2Xbx4ke+//56AgIBC+2ZlZbFhwwa1LTs7m/Xr19OxY0esrKwA\n6NSpE1ZWVnz55ZdG/b/44guef/55atasCYC3tzdVqlQxG1e5cmVat25dpH2ztrbmpZdeYsOGDdy7\nd09t37RpE5mZmfnuX2hoKKGhoTRr1gKoW6RtCiHKr02bNuHv74/BYMDe3p66desSEhJiNJjLjz/+\nyJtvvknDhg2pVKkSFSpUoFmzZixdutTsOvMGV0lOTiYoKIjq1atjYWHBiRMnSmu3yoSPj4/6XZl3\noFFWNA1u0LlzZ0aOHEn37t3p1q0bzs7OJo9h+Pn5FbqeN954g7CwMLp27cqsWbMAmDp1Km5ubgwd\nOlSNS0pKonbt2kyfPp2pU6cC4OXlRa9evRg9ejRZWVm4u7uzdOlSkpKSWLt2rdq3atWqjB07ljlz\n5uDg4ECTJk1Yv349MTEx7Nix468dt7TkvffeY/jw4bi4uODv78/evXuJiIggLCwMS0tLo3yOHTsG\nQEpKChYWFuo/Ec2bN8fNzQ3ILYAtW7akZ8+eDB8+nIsXL/LOO+8QGBhIkyZNtHzUQojHwKhRowgL\nC6N69er06tULJycnLly4wKZNm+jcuTM1atQAcgdY+frrr2nXrh3/+te/SE9PJzo6mjfffJMzZ86w\ncOFCk3WnpKTQunVrqlWrRp8+fbh9+3ahA8OI4qOpaHbv3h2ArVu3snXrVpPlOp3O6OgqP/b29uzd\nu5cxY8YQHByMoii0b9+eRYsWGf3SFUUhJyfH5IaeiIgIJk+ezJQpU0hLS8PLy4uoqCi8vLyM4mbP\nnk2FChVYvHgxv/32G56enmzcuJHOnTsbxQ0dOhSdTseCBQuYP38+NWvWZMmSJUajAQHExMQwcOBA\ndV8BevbsiU6nIyIigr59+wLQuHFjdu/ezYQJE+jSpQuOjo7069eP999/v9DPRgjxeNi+fTthYWE0\na9aMvXv3Gk2pmJmZyZ07d9T3kydPZtmyZUb97927R5cuXfjkk08YM2aM+k95nlOnTvHGG2+YHfJT\nlDydouFWUy3nkn18fIohnSeLTqdT/zF4442RrFjhAYz839JhWDRcwb3A7Ny3Z8H5Kx2X7/t16ays\nYMsWqFABgIpdejPl9jhe5EUARupG0HxAPMHBufGHDsGhQ2355pt9pbF7Qhj9jee3vFxe08T3ge/C\n79SpE9HR0eo41A9iy5Yt9OjRg1WrVqn/lEPu6VlbW1t+/fVXs4+3PeoK+3spalxJ0HSkKQVRCCG0\nOXbsGE899ZSmgpmZmcnHH3/M+vXr+b//+z9u375ttPzKlSsmfdzd3R/Lgvmo0DxgO8D169c5cuQI\nKSkpdOnShcqVK3P37l2sra2Nho4TQogn1R9//MGzzz6rKfbVV19l165d1K9fn6CgIKpWrYqlpSWJ\niYmsXr2azMxMkz733+0vSp+moqkoCuPHj+eTTz4hKysLnU7HsWPHqFy5Mq+88gqtW7dm2rRpJZ2r\nEEKUe46OjmaPEP/u2LFj7Nq1S50V6X7r169n9erVZvtpGQtblBxNj5zMmTOHJUuWMH36dI4ePWp0\nLvlf//qXyS9cCCGeVM2bN+f27dscOnSowLjz588D8PLLL5ssK6yvKDuaiuaKFSuYOnUqkyZNMnl0\nonbt2upg6UII8aQbNmwYAG+99RY3b940WpaRkaGOGpb3zPj9MyoBHDlyhOXLl5dCpuJBaDo9++uv\nv9KqVSuzy6ytrU0uXgshxJOqS5cujBw5kk8++QQPDw+6du2Kk5MTly5dIjo6mpUrVxIQEECLFi14\n4YUXWLduHb/99hsvvPACFy5cYMeOHQQEBLB58+ay3hVhhqai+cwzz3Dy5El8fU2Hljpx4oTmi95C\nCPEkWLx4Md7e3nz66aesW7eO7OxsXF1d6dmzJ82aNQNyHx/ZuXMnEyZMYPfu3Rw9epQGDRqwevVq\nnJ2dpWiWU5qKZs+ePZk5cyZNmzY1OuL8v//7PxYsWMAbb7xRYgkKIR5fjg6O5XKcV0cHx4deR69e\nvfIdczpPtWrViIiIMLssJydHU5soXZqK5vTp0/n+++9p27ateh4+MDCQ5ORkvL29mThxYokmKYR4\nPKXeLHgeXSHKG01F097enpiYGNauXUtUVBR16tShcuXKTJs2jT59+hiN0yqEEEI8rjRXO0tLS4KD\ngwnOG5NNCCGEeMIU6RDx3Llz/Oc//+HXX3/FxcWFFi1aGM1ZKYQQQjzONBXNjIwMhg0bxueff250\nIVqv19OvXz8+/fRTbGxsSixJIYQQojzQNLjB22+/zVdffcXMmTM5e/YsN2/e5OzZs8yYMYMvvviC\nt99+u6TzFEIIIcqcpiPNdevWMW3aNCZNmqS2VahQgcmTJwOwcOFCPvnkk5LJUAghhCgnNB1pZmZm\n0qJFC7PLmjdvbnYkfiGEEOJxo6lo+vv7s3v3brPLvv32W/z9/Ys1KSGEEKI8yvf07IULF9Sfx40b\nR1BQELdu3aJnz55Ur16d3377jQ0bNrBr1y6++OKLUklWCCGEKEv5Fs06deqYtC1btoxly5aZtLdr\n14579+4Vb2ZCCCFEOZNv0Vy5cmVp5iGEEEKUe/kWzf79+5diGkIIIUT5p+lGICGEEMVv1apV6PV6\nVq9eXdapCI00D6O3a9cuNm7cyH//+18yMjLUdkVR0Ol07N+/v0QSFEI8vgyGiqSlpZd1GiYcHR1I\nTb1Z4tvR6XTqSzwaNBXNefPmMXHiRKpWrUqdOnWwsrIyWi6/cCHEg0hLSycmpqyzMOXrWzqFvFu3\nbrRq1Yqnn366VLYnHp6morlkyRKGDBnCkiVLsLCwKOmchBDiiVCxYkUqVqxY1mmIItB0TTMtLY2e\nPXtKwRRCiEJkZWXx8ccf06FDB1xcXLCxseGZZ56hT58+nDt3zijW3DXNixcvotfrGTBgAPHx8XTt\n2hUnJyf0ej03b5b8KWNRME1Fs3379hw5cqSkcxFCiEdeSkoK48aNQ1EUunbtytixY2nRogUbNmyg\nRYsWXLx40aSPuUtc586dw9vbmz/++IPBgwcTHByMXi/3bpY1Tadnw8LC6Nq1KwAdO3bEYDCYxNSq\nVat4MxNCiEeQk5MTycnJJtcp9+/fj7+/P7NnzyY8PLzQ9Rw6dIiZM2cyZcqUkkpVPABNRdPS0hKD\nwcCUKVPM/gJ1Op2MCCSEEIC1tbXZG3vatm1L/fr12bNnj6b1PPPMM7z77rvFnZ54SJqK5oABAzhy\n5AhjxoyhXr16WFtbl3ReQgjxyPrxxx+ZN28ehw4d4vfffycrK0tdZmNjo2kdjRo1kvtIyiFNRTM2\nNpZPPvmEAQMGlHQ+QgjxSDt48CD+/v5YWlrSsWNH6tSpw1NPPYVOpyMiIoJLly5pWk/16tVLOFPx\nIDQVTScnJ3mOSAghNJgzZw7Z2dns27ePli1bGi1bu3at5vXI8+/lk6ZbsUaOHMmnn35KTk7OQ28w\nOTmZHj164OjoSKVKlejevTvJycma+mZkZDB+/HicnZ2xt7fH29ubAwcOmMQpisKcOXNwd3fHzs4O\nL2idRg8AABvtSURBVC8vtmzZYnad4eHheHp6Ymtri6enJ5999pnZuG3bttGkSRPs7Oxwd3dn9uzZ\nJp9HaGgoer3e5PXqq69q2j8hxKPv/PnzVK5c2aRgXr16lfPnz5dRVqK4aDrSvHnzJidOnKBBgwZ0\n6NDB7N2zM2fOLHQ9d+7cwc/PDzs7O9asWQPAlClT8PX15cSJE9jb2xfYf9CgQXzzzTd8+OGH1KpV\ni7CwMDp27Mjhw4dp3LixGjdlyhQWLFjA+++/T7NmzVi7di2BgYHs3LmTTp06qXHh4eGEhIQwadIk\n2rdvz549exg+fDiKohASEqLGRUdH06NHDwYPHsyiRYuIi4tj0qRJpKen88EHH5jkeejQIaNrEU5O\nToV+NkKIx0PNmjU5e/Ysv/zyC56engD8+eefjBgxguzsbDmCfMRpKpqzZ89Wfz5z5ozZGC1FMzw8\nnMTERM6cOaM+otKoUSPq1q3LZ599xpgxY/Lt+/PPP7N27VoiIiLo168fkHs3WsOGDZk2bRqRkZEA\nXLt2jQ8//JBJkyYxduxYIHe+z3PnzjFx4kS1aGZnZzN58mT69u3Le++9p8ZdvnyZqVOnMnjwYCwt\ncz+eiRMn0qZNG3Uu0Xbt2nHr1i1mzZrFmDFjTK49tGjRQp6nEuIJNWLECL799ltat25Nz549sbS0\nZM+ePdy7d4/GjRvz888/l3WK4iFo+mbPyckp9KXF9u3badWqldEzne7u7rRu3VotegX1tbKyolev\nXmqbhYUFvXv3Jjo6Wr07Le/noKAgo/5BQUGcPHmSpKQkAA4fPsz169dN4oKDg0lJSeHgwYNA7unk\nn3/+2WxcVlYWu3btMslVUZTCPgohxGPqX//6F+vXr6dmzZqsWbOGzZs306pVKw4ePIijo6PRkaYM\n1v7o0TzLSXGIj4+nW7duJu0NGjRg06ZNhfatVasWtra2Jn3//PNPzp07R/369YmPj8fGxobatWub\nxAEkJCRQs2ZN4uPjAXjuuefMxp0+fRofH59849zd3bG3t+f06dMmudaoUYNr167h6upK7969CQ0N\nNclbCJE7m0hpDY5eFI6ODg/VPzAwkMDAQJP2mL+NTt+vXz/1zFked3f3Yrl/RJSMUi2aqampZq+H\nOjk5kZqaWmDfGzdu5Ns3b3lR4wCTWK1xeW15ywHq1q3L3LlzadKkCTqdjujoaBYuXEhcXBy7d+8u\ncP+EeBKVxvRbQhQnTUVTr9ej0+lMTjvmtZW3EYFK6/To37fTp08fo/f+/v64uroyevRo9u7di5+f\nX6nkJYQQomRoKprTpk0zaUtJSWH37t38+eef9O/fX9PGDAaD2SPKGzduFHqHqcFgMPtQcN6RXl5/\ng8FAWlqapjjIPfq9/0aeguL+Li0trdC8e/fuzejR/9/e3YdFVaZ/AP+eGZgZUIHBFyDToUaBwhfc\nQkQ3hdRVVyVTMTa0NVsXfl5pamm7AosgZLVq+lvfUhQVTYzNJC9dbNEB08q1fAmiSw15cf2FKS8t\nxtvA3L8/XI4cZoCT6ADO/ek61+U8c59znnM7ec9z5pznLMbZs2ctFs2VK1cCAL7++gwA/m2DMcaa\ny8rKQlZWVkd3A4DMotn4D3tz9fX1mDp1KpydnWXtzNfXF7m5uWbteXl54m+Jra176NAh1NTUSH4f\nzMvLg0qlwoABA8S42tpa5OfnS37XzMvLA3D3N0tfX18AQG5urqRothYXEBAgxhUWFqKqqqrNfrel\nMbfXr5fi/PmB7doWY4w9jIKCghAUFCS+jouL67C+tOu+CDs7OyxYsADr16+XFR8SEoIvv/wSBQUF\nYlthYSE+//xzhISEtLmu0WjEhx9+KLbV19fjwIEDmDBhAuzt7QEAkyZNgr29Pfbt2ydZf+/evRg8\neDB0Oh0AYOTIkejVq5fFuJ49e2LUqFEAgP79+2Po0KEW41QqleS+T0sa12tacBljjHVN7b4QqK6u\nDqWlpbJi58+fLz5mLCEhAQAQExOD/v37IyIiQowrKiqCXq9HbGwsYmJiAAB+fn544YUXsHjxYhiN\nRnh6emLLli0oKiqSTE3Vu3dvLF26FKtXr0aPHj0wbNgwHDhwAAaDAYcPH7574HZ2WLVqFRYsWIC+\nffti7NixOHHiBJKTk7Fx40bxHk0AeOuttzBlyhRERkYiLCwM58+fR2JiIl577TX06dNHjHvqqacw\nd+5cDBw4EESEf/7zn9i4cSMmTZok+ZbEGGOsa5JVNC39llhXV4ecnBy8+eabePrpp2XtzNHRESdO\nnMCSJUswZ84cEBHGjRuH9evXS2YDIiKYTCazC22Sk5MRFRWF6OhoVFRUwM/PDxkZGfDz85PEJSYm\nonv37tiwYQNKSkrg4+ODtLQ0/Pa3v5XERUREQBAErF27Fn/961+h0+mwadMmyWxAwJ3R69///nfE\nxcVh165dcHd3R1RUFKKioiRxXl5e2LBhA3744QeYTCax8C9fvlxWfhhjjHVuAsm41LS12W30ej3S\n09Pb/dueLWp6RfL8+QuRlOQFYOF/3/0fKH2T0BBaf+flFcDjAwH/1+SvS7C3Bw4eBLp3BwA4TQlD\n9M+vwx/+AICFwqsY/vK3mDPnTvzp08Dp06Nx9Gi2NQ6PMYtX3TPWErmfl478XMkaae7cudOsTaPR\nQKfTYfjw4fzMN8YYYzZBVtGUe0sJY4wx9jDjWcUZY4wxmWSNNIkIu3fvxv79+1FcXIyamhoA0hmB\nrl69+kA7yhjrerRaLU9IzmSzNF1pZyOraCYkJCA2NhaDBg2Cn58f1Gq15H3+n4IxZknTuZkZexjI\nKpo7duzAokWLZE9iwBhjjD2MZP2mWVpa2uaMPYwxxtjDTlbRHD16ND9tnDHGmM2TdXp2w4YNeP75\n5+Hq6orJkydbfLJHaxMgMMYYYw8DWUXTy8sLAPDyyy9bfL+zPU+TMcYYexDu+XmaTfHVs4wxxmxB\nu56nyRhjjNkS/iGSMcYYk4mLJnugtFonCIIgLlqtU0d3iTHG7lm7H0LNWGsqKiphMNx9HRxc2XGd\nYYyxduKRJmOMMSYTF03GGGNMJi6ajDHGmExcNBljjDGZuGgyxhhjMnHRZIwxxmTioskYY4zJxEWT\nMcYYk4mLJmOMMSYTF03GGGNMJi6ajDHGmExcNNlDq6Mni+/o/TPG7j+esJ09tDp6sviO3j9j7P7j\nkSZjjDEmExdNxhhjTCYumowxxphMVi+a165dw8yZM+Hi4gJnZ2fMmDED165dk7VuTU0Nli1bBg8P\nDzg6OmLkyJH47LPPzOKICKtXr4anpyccHBzg5+eHgwcPWtzm9u3b4ePjA41GAx8fH7z//vsW4w4d\nOoRhw4bBwcEBnp6eSExMhMlkMos7deoURo4cCUdHR3h4eOD1119HTU2NrONjjDHWuVm1aFZVVeHZ\nZ5/F5cuXsWfPHqSkpODKlSsIDg5GVVVVm+u/8sorSEpKQkJCAo4cOQIPDw9MmDABFy9elMRFR0cj\nLi4OixYtQkZGBkaMGIHQ0FD84x//kMRt374dkZGRCA0NxbFjxxAaGooFCxZg69atkrhjx45h5syZ\nCAgIQEZGBl577TUkJCRgxYoVkrhvvvkG48ePh7u7O44cOYKEhAQkJydj7ty595Ywxu5R8yt3+epd\n28FXbT9gZEXr168npVJJ+fn5YltBQQHZ2dnRunXrWl33woULJAgC7dq1S2yrr68nb29vCgkJEdtu\n3LhBKpWKVq5cKVl/7NixNGTIEPG10Wik3r1709y5cyVx8+bNo169epHRaBTb/Pz8KCgoSBIXHx9P\nKpWKSkpKxLZp06aRl5cX1dfXi2179uwhQRDo3LlzZsfUNP1/+MOrBPwvAfTfJZKUvnaElbizhIM8\nBIGaBBDs7QmHDxMMBoLBQE7d3OhdvEsGGMgAAw0SfGnePJDBcGdJSABNmjS61Tzfb8Dd/RsMIGt+\n5Dpy3x29/+b77ojjZx2joz/31tCRx2TVkeYnn3yCwMBAPP7442Kbp6cnRo0ahfT09DbXtbe3xwsv\nvCC2KZVKhIWF4dixYzAajQAg/nn27NmS9WfPno2cnBwUFRUBAL744gvcunXLLG7OnDkoLS3FqVOn\nANw5nXzx4kWLcUajURy9Go1GZGRkYNasWVAqlWJcaGgoVCpVm8fHGGOs87Nq0fz2228xaNAgs/Yn\nn3wSeXl5ba77+OOPQ6PRmK1bV1eH77//XoxTq9XQ6/VmcQDE/Xz77bcAYNafxrjvvvuu1ThPT084\nOjqKcfn5+aitrTWL02g00Ov1YlxX5uokPe3j6iQ97aN10pqdEpQrKyvrPve26+Jc3MW5uItz0TlY\ntWiWl5dDq9Watbu6uqK8vLzVdcvKylpct/H9XxoHwCxWblxj2y+N68rKKyvvnOv571JeVSUpkBWV\nFTA0+08u/gfhLs7FXZyLuzgXncNDOSPQnVPeD89+Oq2GBjSb8qbj+sIYY1Zg1aKp1WotjijLysrE\nEV5r6xYXF1tcF7g7QtRqtaioqJAVB9wZ/bq5ucmKa66iokJWXFlZGQYPHtzq8SmVCmg070Ol+hQA\nUF2dg4ZCE5w+unMKtL6yHqVUhalNT4lWVaFHYiIEuzt/jQ01Vdip3olP1J8AAIqrilF+TInLl7sB\nAEpL66HX27fYBycnV1RW3u1/jx5a/Oc/XWeErHXSoqLS/O/eVvbPGLMCa1519Oyzz9Kvf/1rs/Yx\nY8aYXZ3aXFxcHKlUKqqurpa0x8bGklqtprq6OiIi2r17NwmCQN9//70kLjk5mQRBoMLCQiIiys7O\nJkEQKDMzUxJnMBhIEATKysoiIqKioiISBIGSkpIkcQUFBZKreWtra0mj0VB0dLQkrrq6mjQajdnV\nvEREer2+6dlOXnjhhRdeZCx6vb7VevEgWf2WEzs7O7p69arYVlBQQPb29m3ecnL+/HkSBIF2794t\nthmNRvLx8ZHccvLjjz+SSqWiuLg4yfot3XLy8ssvS+JeeeUVi7ecBAcHS+JWrVpFarWabty4IbZZ\nuuUkJSWlxVtOGGOMdS1WLZo///wzDRgwgAYPHkzp6emUnp5OQ4YMIb1eTz///LMYV1hYSEqlkuLj\n4yXrh4WFkVarpaSkJMrMzKQZM2aQg4MDnT9/XhL3pz/9iTQaDa1bt44MBgNFRkaSQqGgI0eOSOK2\nbt1KCoWCoqOjyWAwUExMDCkUCtq8ebMk7ujRo6RQKCgiIoIMBgOtW7eONBoNLV++XBJ34cIF0mg0\nNH36dMrMzKSkpCRydXWlWbNm3Y/0McYY62BWv0O0uLiYZsyYQU5OTtSjRw96/vnnqaioSBLTeOqz\n+Wixurqali5dSu7u7qTRaGjEiBGUnZ1tto+GhgZKSEggnU5HarWahg4dSh999JHF/rz//vvk5eVF\narWavLy8aMuWLRbjDh48SEOHDiW1Wk06nY5WrVpFJpPJLO7kyZMUGBhIGo2G3N3dacmSJWanlBlj\njHVND99UEZ1c45cGZ2dncnJyounTp1NxcXFHd6tN165do1dffZVGjBhBDg4OJAiC2ZcdIqKysjLx\nFHe3bt1o3LhxlJOTYxZXXV1Nb7zxBrm7u5ODgwMFBgbSyZMnzeJMJhO99dZbpNPpSKPRtPoFaNu2\nbeTt7U1qtZq8vb1p69at7T9wC9LS0ui5556jfv36kYODA3l7e9Of//xnqqyslMTZQi4yMjIoODiY\n3N3dSa1W06OPPkqzZs2ivLw8SZwt5KK5CRMmkCAIZtc52EIuGq8Nab5otVpJXFfMBRdNK7J0enrw\n4MFmp6c7I4PBQG5ubjR58mTxH4PmRdNkMtGoUaOoX79+lJqaShkZGTRmzBjq1asX/fvf/5bEvvji\ni+Ti4kJJSUl04sQJmj59Ojk4ONCFCxckcStWrCC1Wk1r166lrKwsioiIIIVCQUePHpXEbdu2TTzV\nnpWVRdHR0aRQKFo8c9AeI0aMoJkzZ9K+ffsoOzub1q9fTy4uLjRixAjx7IOt5GL//v20fPly+uij\nj+jkyZOUkpJCvr6+5OTkJH4ZtJVcNPXBBx+Qh4cHCYJAMTExYrut5KKxaG7cuJHOnDkjLl9//XWX\nzwUXTStqz9y7Ha3pqejt27dbLJqHDh2SXHlMRPTTTz+Rq6srLVq0SGzryHmE74dbt26ZtTXOMXzi\nxAkisp1cWHLp0iUSBIHee+89IrK9XJSVlZG7uzulpqaaFU1byUVj0Tx+/HiLMV01F1w0rai1W27G\njBlj/Q7do5aK5rx58+jRRx81i//9739POp1OfN042X1btw81FqK2bh86efJkq7cPGQyGez1U2fLy\n8kgQBNq7dy8R2XYubt68SYIg0IYNG4jI9nIxf/58Gj9+PBGRWdG0lVw0brf5/prqqrngh1BbUXvm\n3u0KWju+4uJi8fFvHTWP8IOUnZ0NAHjiiSfEPtlSLhoaGlBXV4crV64gIiICbm5uCAsLE/tkK7k4\ndeoUUlJSsGnTJovv21IuACA8PBx2dnbo1asXwsPDJc9O7qq54KJpRe2Ze7craGve38Zj7Kh5hB+U\n69ev4y9/+QvGjx+PX/3qV+I+bSkXAQEB0Gg08Pb2xrlz55CZmYk+ffrI6vvDkou6ujpERERg2bJl\nGDhwoMUYW8mFi4sL3njjDezYsQMGgwExMTHIzMxEYGAgbt68KavvnTUXD+Xcs6xj/JKnmshFnXx+\n39u3b+O5556DSqVCcnKy2G5rudi7dy8qKyuRn5+PNWvWYOLEiTh16hR0Op3N5OLdd99FbW0toqKi\nWoyxlVz4+fnBz89PfP3MM89g9OjRGD58OP72t78hPj7+gezXGrngkaYVtWfu3a6gpae5NP9m11Zc\ne+YRbi3ufquursbUqVNRWFiIY8eO4ZFHHhHfs7Vc+Pj4wN/fH2FhYTh+/Dhu376Nt99+G8CdUcfD\nnovi4mIkJiYiPj4e1dXVqKioEPtYU1ODn376CQ0NDTb3uWhq2LBh8PLywtmzZ8U+dcVccNG0Il9f\nX+Tm5pq15+XliefTuzJfX1/x94Km8vLyoNPp4OjoKMYVFBSgpqbGLE6lUmHAgAFiXG1tLfLz883i\ngLu/Qfj6+gKAWW6bx91PRqMRM2fOxLlz53D06FGxD41sKRfNOTs7Q6/Xi321hVxcvXoVtbW1mD17\nNlxdXcUFANasWQOtVovc3FybyEVrmo4Eu2wuWr1MiN1X7Zl7tzNp65aTprM0WbqEvCPnEb4fGhoa\nKDQ0lBwdHcVbTJqzlVxYUlJSQt26daPIyEgiso1cVFRUUHZ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+/mItzwh/Vk1YPB4PJ0+elLnv1KlT4n+okpIS8OppgJC/vz9KS0tx6NAhcVlZ\nWRkOHjyIvn37yjWYkRCi+c6dOydV9ubNG9y4cQN8Ph+2trbi+fsePnwodez169erPT+Xy0Xnzp3x\n7bff4ocffgAA/Pbbb3UQecPB6g5k/PjxWLlyJYqKijB8+HBYWFjg2bNnOHToELZt2ybu97h06RI6\ndOhQ4/ni4uIAAFevXgUAHD16FGZmZrCwsICHhwfy8vLg6OiIsLAwhISEAAA6deqEkSNHYtasWSgt\nLYW9vT22bt2KvLw87N+/X6EXTwjRXBkZGYiOjsa4cePEZatWrUJhYaH4CSoej4c2bdrg7NmzyMrK\ngqOjIwCgqKhIZn9tWloaTE1NpZrHnjx5AkB253qjxmawSFlZGbN48WKmSZMmDIfDEW9NmzZllixZ\nwpSXlzMMwzCXLl1iUlNTazzfh+fgcrnin729vRmG+WfwT0REhES9t2/fMrNnz2aaNWvG6OvrMz16\n9GBOnz5d5XVYvjylAQ0kVHuggYQaM5Cwb9++jJ6eHjN06FBm0aJFjJ+fH8PhcBhHR0emoKBAfHzl\ngGVzc3NmypQpzKRJkxg7Oztm2LBhEp87DMMw69evZ3R0dBgfHx9m4sSJzMKFC5nPP/+c0dXVZQQC\nAZOdna1w3OqAzd9dnn8bVuuBVBIKhbh9+zYeP36M5s2bo0OHDjIfrVUXtB4IkVdDWg9EVh11wYHi\nf9Pk5GT4+PggPDwcnp6eCAkJwbVr16Cvr4+BAwdi9erVaNasmUSdrVu3YsOGDcjNzUWLFi0wduxY\nLF68GLq6uvDy8kJiYiIAID09Hdu3b8eZM2eQl5eH4uJiWFtbw9fXFwsWLICdnV1tX7pK1fV6IHIl\nEE1DCYTIqyElEAGPB6GazjnFNzJCwatXqg6j0VHJglJAxSy6wcHB6NKlCxwcHHDnzh0AwPr163Hp\n0iW2pyGEKEnBq1dgGEYtN0oeDQOrBJKamgpXV1fs27cPLVq0QF5ennhOmLy8PGzcuLFegySEEKJ+\nWCWQOXPmwNnZGdnZ2Th8+LDEvp49e+LixYv1EhwhhBD1xeox3nPnzuHHH3+EkZGR1IAcS0tL8SNu\nhBBCGg9WdyBcLrfK2XifP39OM1QSQkgjxCqBdOvWDbt27ZK5LzY2tl6ncSeEEKKeWC9p26dPH/j5\n+eGrr74CAJw8eRIbNmzAzz//jDNnztRrkIQQQtQP63Egv//+O2bOnIns7Gxxmb29PbZs2YL+/fvX\nW4C1QeO8Ii+RAAAgAElEQVRAiLwa0jgQQj6m8oGE9+7dw7Nnz2Bqaoo2bdoovEStMlACIfKiBEIa\nsrpOIKyasD7UunVrtG7dGgDw4sULmJqaynsKQgghDQCrTvQffvgBa9euFf9++/ZtWFlZwdzcHF26\ndKHHeAkhpBFilUAiIyMlpjGePXs2+Hw+NmzYgJcvX4qnXCeEENJ4sGrCysvLg7OzMwCgsLAQp0+f\nxuHDhzFw4ECYmZlh4cKF9RokIYQQ9cPqDkQkEoHLrTi0chWwymUdra2tq1xakhBCNJ2Xl5f4849I\nYvVXadWqlXgpx4MHD6Jnz54wNDQEADx+/BgCgYD1BfPz8zFs2DCYmJjA2NgYQ4cORX5+Pqu6ubm5\nGDNmDGxtbWFoaIg2bdogJCQExcXFrK9PSGPB4/PB4XDUcuPVch2h5ORkcLlcudbvVlRlzEQaqyas\nefPmITAwEHv27IFQKERsbKx4X1JSElxdXVldrLi4GD4+PjAwMEBMTAwAYMmSJfD29satW7fESUmW\n169fo0+fPgCAFStWwNbWFn/++SfCwsJw7949HDhwgFUMhDQWRYWFQFKSqsOQqeh/LRi1pYwP9piY\nGLx9+7ber6OJWCWQr776Cra2tkhJSYGbmxs8PDzE+ywsLODv78/qYlFRUcjJyUFGRgZatmwJAHB1\ndUXr1q2xfft2BAcHV1n3/PnzyMnJwfHjx+Hn5wcA8PT0REFBAdatW4eSkhJar5iQRkYZY2BsbGzq\n/RqainXD3qeffoq5c+dKJA8AWLp0KQYMGMDqHPHx8XB3dxcnD6BiNHuvXr1w5MiRauuWl5cDAIyN\njSXKjY2NxYvUEEIavvDwcPj4+AAAIiIiwOVyxVteXh7Gjh0LLpeL7OxsrF27Fs7OztDX1xd/Qc3I\nyMC8efPQqVMnCAQCGBgYoH379lixYoXUbOOA7D6Q8PBwcLlcnD59Gj/++CM++eQTGBoaokWLFpg1\naxZKSkrq/w+hBuQeSFgbqampGDJkiFS5i4sL4uLiqq3r5+eH9u3bY/78+di6dStsbGzw559/YtOm\nTZg8eTLNCExII+Ht7Y28vDzs2bMHXl5e8PLyEu8zMTER/zx9+nRcvnwZgwYNQkBAgPiL688//4zd\nu3ejT58++Ne//oV3794hOTkZISEhuHLlitSaR0DVTWWRkZFISEjAZ599hj59+uDYsWPYtGkTnj9/\njn379tXtC1dDSk0gQqEQfBmdZwKBAEKhsNq6Ojo6OHXqFAYPHox27dqJyydMmIDNmzfXeayEEPXk\n6ekJhmHECSQ0NFTmcWlpabh58yZatGghUf71119j7ty50NaW/PibOHEiduzYgfPnz7OeYfzUqVO4\ndu2aeHaO5cuXo1OnTjhw4ADWrl2L5s2bK/AKNYfGPJv25s0b9O/fH4WFhdi3bx/OnDmDtWvX4sCB\nA5g2bZqqwyOEqJl58+ZJJQ8AaN68uVTyAIDJkycDqEgKbM2cOVOcPABAX18fX375JUQiEa5du6ZA\n1JpFqXcgfD5f5p1GQUFBjY8C79ixA9euXUNmZqb4VvTTTz+FsbExJk6ciMmTJ8t8Giw8PFz888e3\nu4SQhqtr164yy0UiEXbu3Indu3cjNTUVRUVFEn2ojx8/Zn2NLl26SJVZWVkBqBh0rQmSk5ORnJys\nUN0qE0jnzp2xd+9etGvXDkuXLsX48ePFfxhFtWvXDnfu3JEqv3v3LlxcXKqte/fuXfD5fIkOeKBi\nsSsASE9PrzGBEEIaD0tLS5nlQUFB2Lp1K+zt7TFs2DA0a9YMurq6EAqF2LhxI969e8f6GjweT6qs\n8u6m8sEfdffxF2t5xtZUmUBu376NoqIiABUfwv369at1AvH398fcuXORk5MDBwcHABWDAy9cuIDV\nq1dXW9fa2hpCoRBZWVlwdHQUl1+6dAkAah0bIaRhkdXx/fTpU2zduhWdOnXCxYsXoaenJ9536dIl\nbNy4UZkharwq+0CaN2+OX375BTk5OQAqbuvu379f5cbGhAkTYG9vj4CAAMTHxyM+Ph4BAQGwtbXF\npEmTxMfl5eVBW1sby5YtE5eNHTsWPB4PAwYMQExMDJKSkrB27VrMmzcPXbt2pWV1CWlEtLS0AMj/\nLb/y88zX11cieQAVY82IfKq8A5k8eTKWLFmCNWvWAIDMx28rcTgcVv+QhoaGSExMRHBwMAIDA8Ew\nDHx9fbFhwwaJUegMw0AkEkm0S1Y+thsaGoolS5bg+fPn4sSzePFiVi+WENIwVPaZsv3yWsnOzg4A\ncOHCBYnyjIwMrFy5sm6Ca0SqTCDffvstfH19kZaWhnHjxmHRokXiZqfasLGxqXHMh729PUQikVS5\nk5MTTVlCCIGzszNatGiBAwcOQE9PD1ZWVuByuQgKCqq2XvPmzTFkyBAcPnwY3bp1g5eXFx49eoRf\nf/0Vffv2xU8//SSzHg1Ulq3ap7Dc3Nzg5uaG6OhojB49WjylOyGEqBKXy8XPP/+MBQsWYP/+/Sgq\nKgKHw8Ho0aNrnPxwz549sLW1xeHDhxEZGYlWrVrhu+++w6BBg2QmEFnnq+4ajWnyRbnXRNcktCY6\nkVdDWhOdx+dXTKiohoxMTPCqhsHDpO7V9ZrorAcS3rp1C0OHDoWZmRm0tLRgbm6O4cOH4/bt22xP\nQQhRoldCoXieOHXbKHk0DKwGEl6+fBmenp4wMDCAv78/LC0t8eTJE/z66684evQoTp8+XeWgHUII\nIQ0TqyYsX19fvHr1CqdOnYKRkZG4vKioCL6+vuDxePjjjz/qNVBFUBMWkVdDasIi5GMqacJKSUnB\nwoULJZIHABgZGWHBggW4ePEiq4sRQghpOFglkJqeKGgsTxwQQgj5B6sE0r17d6xcuRKvXr2SKH/9\n+jVWr16NHj161EtwhBBC1BerTvTvvvsOnp6esLe3x6BBg9C8eXM8fvwYR48eRXFxscIzORJCCNFc\nrBKIm5sbLl26hKVLlyIhIQFCoRACgQA+Pj4ICQlBhw4d6jtOQgghaoYGEioRPYWl/ugpLNKQqWwg\nISGEEPIhSiCEEEIUQgmEEEKIQiiBEEIIUYjSE0h+fj6GDRsGExMTGBsbY+jQocjPz2ddPy0tDcOH\nD4e5uTkMDQ3Rtm1bbNq0qR4jJoQQIkuNCeTdu3fg8/mIj4+v9cWKi4vh4+ODjIwMxMTEYO/evbh3\n7x68vb1RXFxcY/0rV66ge/fuKC0txc6dO3Hs2DHMmTNH5uJThDR2fB5fvDaFum18Hl/Vfx5SB2oc\nB6KnpwdtbW3o6+vX+mJRUVHIyclBRkYGWrZsCQBwdXVF69atsX37dgQHB1dZVyQSYcyYMfDz85NY\n9MXT07PWcRHSEBUWFSIJSaoOQybvIm9Vh0DqAKsmrM8++6zGZWjZiI+Ph7u7uzh5ABXL1/bq1QtH\njhyptm5ycjLS09Mxe/bsWsdBCNF8cXFx6NOnD/h8PgwNDdG6dWtMnjxZokn86tWrmDZtGtq1awdj\nY2M0bdoUXbp0wdatW2Wek8vlwtvbG/n5+Rg9ejQsLS2hpaWFW7duKetlaRRWI9EHDBiAoKAgDB06\nFEOGDEHz5s2lJlD08fGp8TypqakYMmSIVLmLi0uNCercuXMAgLdv36JHjx64du0a+Hw+vvjiC6xe\nvbpO7pAIIZphxowZiIyMhKWlJUaOHAmBQIDs7GzExcVhwIABsLGxAVDR6vH777/D09MTgwcPRlFR\nEY4fP45p06YhIyMD69evlzr3ixcv0KtXL1hYWGDUqFF48+YNDA0Nlf0SNQKrBDJ06FAAwOHDh3H4\n8GGp/RwOB+Xl5TWeRygUgs+XbvsUCAQQ1rBC2aNHjwAAI0eORFBQENasWYPLly8jNDQU+fn5+Pnn\nn9m8FEKIhouPj0dkZCS6dOmCxMREiWUm3r17J9GfunjxYmzbtk2ifnl5OQYNGoTNmzcjODgYtra2\nEvvv3LmDCRMmYPv27fX7QhoAVgkkMTGxvuOoUWVHeWBgIMLDwwEAHh4eKC8vx8KFC5Geno62bduq\nMEJCiDJUNj9t3LhRao0iPT096OnpiX+vvBP5kJaWFiZMmIDjx48jOTkZY8aMkdivr6+PVatW1UPk\nDQ+rBOLl5VUnF+Pz+TLvNAoKCiAQCKqta2pqCgDw8/OTKPfz88PChQtx8+ZNmQmkMtkAFa+jrl4L\nIUQ1Ll++jCZNmqBnz541Hvvu3Tts2rQJBw8exF9//YU3b95I7H/8+LFUHXt7e5ktJQ1VcnKywjOq\ns0oglZ4/f46UlBS8ePECgwYNgqmpKd6+fQtdXV1oaWnVWL9du3a4c+eOVPndu3fh4uJSbd327dvL\nE6rYhwmEEKL5Xr58CQcHB1bHfv755zh27BicnZ0xevRomJubQ1tbGzk5OdizZw/evXsnVcfS0rKu\nQ1ZrH3+xjoiIYF2X1VNYDMNg7ty5sLKygr+/P/79738jLy8PQMUTWitWrGB1MX9/f6SkpCAnJ0dc\nlpubiwsXLsDf37/auv3794eenh4SEhIkyit/79atG6sYCCGazcTEROadw8cuX76MY8eOoX///khN\nTcXWrVuxdOlShIaGol+/flXWoxVW2WOVQFauXIktW7YgLCwMly5dkpjqd/Dgwfj9999ZXWzChAmw\nt7dHQEAA4uPjER8fj4CAANja2mLSpEni4/Ly8qCtrY1ly5aJywQCARYtWoRt27Zh8eLFOHnyJFat\nWoVly5Zh7NixEo8GE0IaLjc3N7x58wbnz5+v9risrCwAwMCBA6X21VSXsMMqgezYsQMhISH49ttv\n8cknn0jsc3R0RGZmJquLGRoaIjExEU5OTggMDMTo0aPh6OiIxMREicfkGIaBSCSSmpM+NDQUa9as\nwaFDhzBw4EBs374d8+fPR1RUFKvrE0I035QpUwAAM2fOlFpmu6SkRNzPamdnB+CfIQCVUlJS8MMP\nPygh0oaPVR/Iw4cP4e7uLnOfrq6uVMdUdWxsbGoc82Fvb1/l9CTBwcHVjlgnhDRsgwYNQlBQEDZv\n3gwnJycEBARAIBDg/v37OH78OHbt2gV/f390794dXbt2xYEDB/DkyRN07doV2dnZ+PXXX+Hv7y8x\nowVRDKsE0qJFC9y+fRve3tLTD9y6dYt1hxYhhNSFjRs3omfPnvj+++9x4MABlJWVwdraGiNGjECX\nLl0AVIwq/+2337BgwQKcOHECly5dgouLC/bs2YPmzZtTAqkDrJa0XbBgAXbu3IlffvkF7u7u0NHR\nwZUrV9CkSRP06dMHEyZMQFhYmDLilQstaUvk1ZCWtOXz+CgsKqzXuBRlYmQC4avqBw+TulfXS9qy\nSiDFxcXo27cvzp8/Dzs7O+Tl5cHBwQH5+fno2bMnjh8/LjF4R11QAiHyakgJhJCPqSSBAEBZWRn2\n79+PhIQEPHv2DKampujfvz9GjRoFbW25hpMoDSUQIi9KIKQhU1kC0USUQIi8KIGQhqyuE4hctw6Z\nmZn4888/8fDhQ1hZWaF79+5wdHSU5xSEEEIaCFYJpKSkBFOmTMHevXslHq/lcrn4+uuv8f3336tl\nHwghhJD6w2og4dy5c/Hjjz9i6dKluHfvHl69eoV79+4hIiIC+/btw9y5c+s7TkIIIWqGVR+ImZkZ\ngoODsXjxYql9K1aswPr16/H8+fN6CbA2qA+EyIv6QEhDVtd9IKzuQN69e4fu3bvL3Ofm5iZzRktC\nCCENG6sE0qdPH5w4cULmvj/++AN9+vSp06AIIYSovyo70bOzs8U/z5kzB6NHj8br168xYsQIWFpa\n4smTJzh06BCOHTuGffv2KSVYQggh6qPKPhAul9XNScVJWK6JrmzUB0LkRX0gpCFT2jiQXbt2yRcZ\nIYSQRqXKBDJ27FglhkEIIUTTsG+nqiP5+fkYNmwYTExMYGxsjKFDhyI/P1/u86xatQpcLhe9e/eu\nhygJIQ3B7t27weVysWfPHlWH0iCxnsrk2LFjiI2NxYMHD1BSUiIuZxgGHA4HZ86cqfEcxcXF8PHx\ngYGBAWJiYgAAS5Ysgbe3N27duiWxKmF1srOzsXz5clhYWND6xf/D5/NQWFgk/t3ExAhC4atqapCG\n7uP3hDpR1vuTw+GIN1L3WCWQNWvWYOHChTA3N0erVq2go6MjsZ/tP05UVBRycnKQkZEhXsPc1dUV\nrVu3xvbt21mvNDhlyhQEBgYiPT0dZWVlrOo0dIWFRUhK+ud3b2/1/OAgyvPxe0KdKOv9OWTIELi7\nu6NZs2ZKuV5jwyqBbNmyBRMnTsSWLVugpaWl8MXi4+Ph7u4uTh5AxfK1vXr1wpEjR1glkB9//BE3\nbtzAwYMH8dlnn9E3C0JIlXg8Hng8nqrDaLBY9YEUFhZixIgRtUoeAJCamor27dtLlbu4uODu3bs1\n1hcKhQgODsaaNWtgYmJSq1gIIZqptLQUmzZtgp+fH6ysrKCnp4cWLVpg1KhRyMzMlDhWVh9Ibm4u\nuFwuxo0bh9TUVPGa6lwuF69eUbOvPFglEF9fX6SkpNT6YkKhEHw+X6pcIBBAKKx5ect58+ahbdu2\n+Prrr2sdCyFEM7148QJz5swBwzAICAjA7Nmz0b17dxw6dAjdu3dHbm6uVB1ZLRWZmZno2bMnXr58\niW+++QaBgYFyjX8jLJuwIiMjERAQAADo27evzCTwYbNUfTh79iz27t2L69ev1+t1CCHqTSAQID8/\nX6pf48yZM+jTpw9WrFiBqKioGs9z/vx5LF26FEuWLKmvUBs8VglEW1sbfD4fS5YskfnHZjsSnc/n\ny7zTKCgogEAgqLbupEmTMH78eFhZWaGwsBBAxTK7IpEIL1++hIGBAXR1daXqhYeHi3/28vKCl5dX\njXESQtSXrq6uzE5xDw8PODs74+TJk6zO06JFCyxatKiuw9M4ycnJSE5OVqguqwQybtw4pKSkIDg4\nGG3atJH5Qc1Gu3btcOfOHanyu3fvwsXFpdq66enpSE9Px7Zt26T28fl8bNiwATNmzJDa92ECIYQ0\nDFevXsWaNWtw/vx5/P333ygtLRXvY7u4naura637dRuCj79YR0REsK7LKoEkJydj8+bNGDdunNzB\nfcjf3x9z585FTk4OHBwcAFR0aF24cAGrV6+utm5SUpJEOybDMJg1axZEIhE2b95MS+sS0kicO3cO\nffr0gba2Nvr27YtWrVqhSZMm4HA4iI6Oxv3791mdx9LSsp4jbfhYJRCBQFAnz1FPmDBB3J+yfPly\nAEBISAhsbW0xadIk8XF5eXlwdHREWFgYQkJCAACenp5S5zM2NkZ5eTk8PDxqHRshRDOsXLkSZWVl\nOH36NHr06CGxb//+/azPQ0MAao/VIwdBQUH4/vvvJdZDV4ShoSESExPh5OSEwMBAjB49Go6OjkhM\nTJQYhc4wDEQiEatZI+lNQEjjkpWVBVNTU6nk8fTpU2RlZakoqsaJ1R3Iq1evcOvWLbi4uMDPz0/m\nU1hLly5ldUEbGxvExcVVe4y9vT2rZJWkrsNsCSH1xs7ODvfu3UN6ejratm0LAHj//j2mT5+OsrIy\n+lKpRKwSyIoVK8Q/Z2RkyDyGbQIhhJDamD59Ov744w/06tULI0aMgLa2Nk6ePIny8nJ07NgRN2/e\nVHWIjQarJiyRSFTjRgghyjB48GAcPHgQdnZ2iImJwU8//QR3d3ecO3cOJiYmEncg1Mxdv6pckbAh\naEwrEnI4nI8mU6SV6hTRkFYkpNl4yceUtiIhIUSz0Qc0qW+sEgiXy5WZlSrL1HVNdEIIIfWHVQIJ\nDQ2VKnvx4gVOnDiB9+/f0/K3hBDSCLFKIFVNB1JWVobBgwfD2Ni4LmMihBCiAWo1d7G2tjamTp2K\nDRs21FU8hBBCNEStJ79///49Xrx4URexEEII0SCsmrBkTU72/v173L59GwsWLEDXrl3rPDBCCCHq\njVUCsbe3r3Kfo6MjtmzZUlfxEEII0RCsEsiuXbukyvT19WFnZwc3NzeaU58QQhohVgmEHtMlhBDy\nMVpBnhBCiEJYJRCGYbB792707dsXzs7OcHBwgIODA1q2bCn+rzzy8/MxbNgwmJiYwNjYGEOHDkV+\nfn6N9S5fvozx48fDyckJTZo0gZ2dHUaPHo3c3Fy5rk9IQ6HN44knDKSNtpo2WUtx1Or9x+ag5cuX\nIywsDO3bt0enTp2k1hzmcNjPdllcXAwfHx8YGBggJiYGALBkyRJ4e3vj1q1bEgtLfezQoUNIS0vD\nzJkz0aFDBzx8+BDLli1D165dcePGDVhbW7OOg5CGoOzIkX9+8fZGEiTXyPGGN02ySeoNqwSyc+dO\nzJgxo04GDEZFRSEnJwcZGRniOxdXV1e0bt0a27dvR3BwcJV158+fD3Nzc4myXr16wcHBAVFRUXIt\nBk8IIaR2WDVhvXjxAv7+/nVywfj4eLi7u0s0e9nb26NXr1448uG3KRk+Th4AYGtrC3Nzczx69KhO\n4iOEEMIOqwTi4eFRZ6t8paamon379lLlLi4uuHv3rtznS0tLw7Nnz+Ds7FwX4RFCCGGJVRPWxo0b\nMWTIEAgEAgwcOBACgUDqGC6X3QNdQqFQZkeOQCCAUChkdY5KZWVlmDx5MiwsLDB+/Hi56hJCCKkd\nVgnEyckJADBu3DiZ+zkc1awHMn36dKSkpOD333+nGYFJg8Iz4aHopXquJkhIJYXXA/mQPE9h8fl8\nmXcaBQUFMu9sqrJw4UJERUUhJiYGvr6+rOsRogmKXhZJLq0bXsWBhKhQrdYDUUS7du1w584dqfK7\nd+/CxcWF1TlWrFiBNWvWIDIyEqNGjar22A9j9/LygpeXlzzhEkJIg5acnIzk5GSF6ip9TXR/f3/M\nnTsXOTk5cHBwAADk5ubiwoULWL16dY31N23ahJCQEHz33XeYOnVqjcfXZfIjhJCG5uMv1vIMh1D6\nVCYTJkyAvb09AgICEB8fj/j4eAQEBMDW1haTJk0SH5eXlwdtbW0sW7ZMXHbgwAHMmjUL/fr1g7e3\nN1JSUsRbWlqasl8KIYQ0akq/AzE0NERiYiKCg4MRGBgIhmHg6+uLDRs2SIxCZxgGIpFIYtTs8ePH\nweFwkJCQgISEBInzenl5ITExUWmvgxBCGjulJxAAsLGxQVxcXLXH2NvbQyQSSZRFR0cjOjq6PkMj\nhBDCEs3GSwghRCGUQAghhCiEEgghhBCFUAIhhBCiEEoghBBCFEIJhBBCiEIogRBCCFEIJRBCCCEK\noQRCCCFEIZRACFExHk8ADocjsRGiCVQylQkh5B9FRUIAzEellESI+qM7EEIIIQqhBEIIIUQhlEAI\nIYQohBIIIYQQhSg9geTn52PYsGEwMTGBsbExhg4divz8fFZ1S0pKMG/ePDRv3hyGhobo2bMnzp49\nW88RV+3ly5eYNWs6pk+fKN5mzJiKJ0+eqCwmQghRFqUmkOLiYvj4+CAjIwMxMTHYu3cv7t27B29v\nbxQXF9dYf/z48dixYweWL1+O33//Hc2bN0ffvn1x8+ZNJUQvLSsrC/v37wSHEyXe4uOjcfv2bZXE\nQ9QHn8+TejSXz+epOixC6pRSH+ONiopCTk4OMjIy0LJlSwCAq6srWrduje3btyM4OLjKujdv3sT+\n/fsRHR2Nr7/+GgDg4eGBdu3aITQ0FEeOHFHKa/iYQKCLoUNLxL9fvqxX59fg8fkoKiwU/25kYoJX\nQmGdX4fUncLCIiQlSZZ5exepJhhC6olS70Di4+Ph7u4uTh5AxdK1vXr1qjEBxMfHQ0dHByNHjhSX\naWlp4YsvvsDx48dRWlpab3GrWlFhIZCUJN4+TCaEEKIqSk0gqampaN++vVS5i4sL7t69W2Pdli1b\nQl9fX6ru+/fvkZmZWaexKg0XEs0cuh81e2jqqOTk5GRVh1A7OaoOoHZu4IaqQ6gVTX//aHr8bCk1\ngQiFQvD5fKlygUAAYQ1NMgUFBVXWrdyvkUQAwv/ZSlExJjnsf//9eHyyptD4/4FyVR1A7VACUS1N\nj58teoyXkBpoQ/IuUcCjznBCACV3ovP5fJl3GgUFBeI7ierq3r9/X2ZdANXWLy8vx2effSZRZmtr\nK3E+AwMDvH37VuIYGxsbiUeMTUxMUPhB/8PLly+Rn/8WISH/fKD89VcJuNz6zcta0KpV0xaPJ/jf\n/Ev/w0XFndAHjIyN8KrwlcLX0BRSfwsZyiB5J8gpLpb6+2tBG+Uoq/sACaklPo+PwiLJflMTIxMI\nX9XBgziMEvn4+DCffvqpVLmnpyfj5eVVbd2IiAhGV1eXefv2rUR5WFgYo6enx7x//16qjqOjY2Ur\nEG200UYbbSw2R0dH1p/pHIZhGCjJxo0bMXfuXGRkZMDBwQEAkJubCycnJ6xevbrax3hv3LiBzp07\nY/fu3RgzZgwAoKysDB06dICTk5PKHuMlhJDGSis8PDxcWRdzdXXFgQMHEBcXBysrK/z111+YOHEi\nDA0NsXPnTujo6AAA8vLyYGZmBg6HA09PTwBAs2bNkJ6eji1btsDMzAxCoRALFy7ElStXsG/fPjRr\n1kxZL4MQQgiU3IluaGiIxMREODk5ITAwEKNHj4ajoyMSExNhaGgoPo5hGIhEInx8cxQdHY1x48Zh\nyZIlGDRoEB4+fIiEhAR06tRJmS+DEEIIAKX2gSjD/fv3maFDhzLGxsYMj8djPv/8c+b+/fuqDouV\n/Px8Zvr06UyPHj0YAwMDhsPhMHl5eaoOi7XY2FgmICCAsbGxYQwMDJg2bdowixYtYoqKilQdWo0S\nEhIYb29vplmzZoyenh5jbW3NjBgxgrl7966qQ1NY3759GQ6HwyxZskTVodQoKSmJ4XA4Uhufz1d1\naHL5/fffmd69ezNNmzZleDwe07VrVyYxMVHVYdXI09NT5t+fw+Ew/fr1q7Jeg1qRsHKuLQMDA8TE\nxAAAlixZAm9vb9y6dUviLkcdZWZmIjY2Fl27doWHhwdOnDih6pDk8p///AfW1tZYtWoVrK2tcf36\ndXbekQ0AAA4YSURBVISHhyMpKQkXLlxQ60GRQqEQ3bp1w/Tp02Fubo68vDysWrUKPXr0wJ07d2Bj\nY6PqEOWyf/9+3Lp1CwDU+u/+sc2bN6Nbt27i37W1Necjavv27QgKCkJQUBDCwsJQXl6OmzdvSj3d\nqY62bt2KoiLJqXYuXLiA2bNnIyAgoOqKSkxy9W7Dhg2MlpYWk5WVJS7LyclhtLW1mf/+978qjIwd\nkUgk/jkqKkrj7kCeP38uVRYTE8NwOByN+Bb2sb/++ovhcDga8d75UEFBAdOsWTPmwIEDDIfDYUJC\nQlQdUo0q70BOnTql6lAUkpOTw+jr6zMbN25UdSh15t///jejr6/PCIXCKo9pUAMJazPXljrQpG+K\nspiamkqVde3aFQDw6NEjZYdTa5Vji7S0tFQciXwWLFiADh06SMwbpykY5T0UWqd27doFbW1tTJ48\nWdWh1Ini4mLExsZi8ODBMDExqfK4BpVAajPXFqkfp0+fBgA4OzurOBJ2ysvL8f79e9y7dw+TJk2C\npaUlvvjiC1WHxdq5c+ewd+9ebNmyRdWhKGTUqFHQ1taGmZkZRo0axXqtIFU7d+4c2rRpgx9//BGO\njo7Q0dFB69at8f3336s6NIUcPnwYr1+/Fs98XhXNaWBkoTZzbZG69/DhQ4SGhsLPzw+dO3dWdTis\ndO/eHdeuXQMA2NnZ4dSpU7CwsFBxVOy8f/8ekyZNwrx589C6dWtVhyMXExMTzJ07F56enuDxeLh2\n7Rq+++47uLu74/r16zA3N1d1iNV69OgRHj9+jPnz52PlypVwdHTEoUOHMH36dJSVlWHGjBmqDlEu\nMTExsLS0RP/+/as9rkElEKI+Xr9+jYCAAOjq6iI6OlrV4bC2b98+FBUVISsrC+vWrUPfvn1x7tw5\n2NnZqTq0Gq1Zswbv3r3D4sWLVR2K3Dp16iTxOH7v3r3h4eEBNzc3bN68GUuXLlVhdDUTiUQoKirC\nnj17xNMmeXl5ITc3FytXrtSoBPLo0SOcOnUKs2bNqnFapgbVhFWbubZI3Xn79i0GDx6M3NxcHD9+\nHC1atFB1SKy1bdsW3bp1wxdffIFTp07h9evXWLVqlarDqtH9+/exYsUKLF26FG/fvkVhYaF43raS\nkhK8fPkSIpGohrOol08++QROTk64fPmyqkOpkampKTgcDvz8/CTK/fz88PTpUzx9+lRFkclv3759\nEIlENTZfAQ0sgbRr1w537tyRKr979y5cXFxUEFHjU1paimHDhuHatWs4evQo2rVrp+qQFGZsbAxH\nR0dkZWWpOpQaZWdn4927dxg9ejQEAoF4A4B169aBz+fL/H9D3WlKp3q7du00Jtaa7NmzB506dUKH\nDh1qPLZBJRB/f3+kpKQgJydHXJabm4sLFy7A399fhZE1DiKRCKNGjUJycjJ++eUXuLm5qTqkWnn6\n9CnS09Ph6Oio6lBq9MknnyA5OVliS/rfmrqBgYFITk7WiNfxoStXriAjIwPdu3dXdSg1+vzzzwEA\nCQkJEuUJCQmwsbGBpaWlKsKS25UrV5CWlsbq7gNoYH0gEyZMQGRkJAICArB8+XIAQEhICGxtbTFp\n0iQVR8dOXFwcAODq1asAgKNHj8LMzAwWFhbw8PBQZWg1mjZtGuLi4rB48WIYGBggJSVFvM/GxgZW\nVlYqjK56Q4YMQZcuXdChQwfweDxkZGRg/fr10NXVxZw5c1QdXo2MjY2rfH/Y2dmp/Xtn9OjRaNWq\nFTp16gQej4fr169j5cqVsLa21oj+gwEDBsDb2xuTJk3C8+fP4eDggNjYWPzxxx/YvXu3qsNjLSYm\nBtra2hg1ahS7CsoalKIslVOZ8Hg8xsjIiBkyZIhGDcb7cAoBLpcr/tnb21vVodXI3t5eIuYPt4iI\nCFWHV63Vq1czXbp0YUxMTBhDQ0OmTZs2zOTJkzXqvSOLpgwkXLlyJePq6soYGxszOjo6jK2tLTNp\n0iTmyZMnqg6NtVevXjHTpk1jLC0tGV1dXaZjx47M/v37VR0Wa+/fv2fMzc0Zf39/1nWUOp07IYSQ\nhqNB9YEQQghRHkoghBBCFEIJhBBCiEIogRBCCFEIJRBCCCEKoQRCCCFEIZRACCGEKIQSCFELu3b9\nf3t3G9LU+8YB/Hv2WK7NljN0Fa5SR4RZITrt0UzUrEwrLc18CI1m+iKhSJiZYhMseiBEhH5mZGiY\nlfmiMtApNcFXZmIgYkZmZhpkSeXm+b8IDx0fcvn39zPj+sDAc+/efd333tye65yd6x+4ublBKpVy\nz3DSaDRITEyckfHr6upw9uxZm59X9O7dO+zevRsODg4QCAS4fPkyrl+/DoFAgNevX3P9NBoNEhIS\nph1nLqurq4NAIEB9ff1sT4XMkr/qUSZkbnr79i2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DVatWZcCAAaSnp2Nvb1/ab7HMUpVUevfuDcCGDRvYsGGD0XGNRkNW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\nMKkQEZFmmFSIiEgzTCpERKQZJhUiItIMkwrRGHA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66SeDQRn30ul0fPXVV6xevZrPP/+ciIgIdDodDRo0YPTo0QajDU1NxXlY03NG\njx6Nra0tCxYsIDw8nOrVq+Pv78/EiRNxdHQ0mgLwONApGsP8tGnT+OijjwwmI+v1eqZOnfpYNzlL\nQ6fToSgK+/bto3//D7l+fd//zlWpjDIkFwoHJ30Dfj+ase2eET56S0uU9euhcFHfWbPwO16L8fnj\n1TxddV3JuZOjjhASojwV/o6L4t28eZM6derg7OzMTz/99Kirc18OHDhAt27deP/991mwYMF9XUPr\n78vD/r3S/O24YMECRo8ezb59+/jzzz+pXr063bp1w8XF5aFVRgghHgdhYWHcvHmT0aNHP+qqlCg9\nPR0rKyuDHT6uX7/OzJkz0el09OnT5xHW7v6U6s96JycnRo4cWVZ1EUKICm3BggX8+eefrFq1CkdH\nR4YNG/aoq1SiAwcOMHr0aF599VXq1q3LlStX2LNnD1euXGHQoEGP5UTkUgWu1NRUUlNTjVZoB/D2\n9n5olRJCiIpoxowZWFhY0KpVK5YvX/5Y7FPYokULunTpwqFDh7h69SpmZmY0btyY6dOnM27cuEdd\nvfuiKXD9+uuvvPHGG/zf//2fyfM6nc5gtrYQQjyJHtaC4+WpUaNGbN68+VFX46HSFLhGjBhBamoq\ny5Yto3HjxlSuXLms6yWEEEKYpGkA/8mTJ1m2bBnjxo3jlVdewdPT0+gojdTUVPr164etrS02Njb0\n7dtX8+obOTk5BAQE4ODggJWVFR4eHibnWSxZsoTevXvj4OCAXq9nzpw5RnkuX77M1KlTeeGFF7C1\ntaVWrVp07drV5PWEEEJUDJoCl4ODw0NrZWVnZ+Pt7U1CQgLr1q1j/fr1XLhwAS8vL3Xfm+IMHz6c\n8PBwQkJC2LVrFw4ODvj4+KirIBcKDw/n6tWr+Pn5AaY3S/vhhx/YsmULfn5+bN26lTVr1mBpaYmn\npye7du16KM8rhBDi4dL0qnD69OksXLgQb29vqlat+kA3DAsLIykpiYSEBJydnYGCzsOGDRuyatUq\nJk6cWGTZM2fOsHHjRiIiIhg6dCgAnTp1olmzZgQFBREVFaXmjY+PBwpWSl65cqXJ67388stcvHhR\n3YoAwMfHh2bNmvHhhx/Ss2fPB3pWIYQQD5+mwDVs2DDOnTvHc889R7t27dSN1e61bt06TTfcsWMH\n7du3V4MWFAyz79ChA1FRUcUGrh07dmBubo6/v7+aZmZmxsCBA1mwYAG5ublGG7YVN+mtcAXne5mZ\nmdGyZUvdu+4AAAAgAElEQVROnz6t6XmEEEKUL02BKyIigo8//hi9Xs/p06cNXhsqilKqZUni4uLU\n13f3cnNzY+vWrSWWdXZ2xtLS0qjsnTt3uHjxIk2bNtVcF1Pu3LnD8ePHTW7UJoQQ4tHTFLjmzJnD\nP/7xDz7//HNsbW0f6Ibp6ekmW2z29vZGqzD/XVpaWpFlC88/qODgYH7//Xc2btz4wNcSQgjx8Gka\nnPHXX38xduzYBw5aFd2XX37JwoULCQoKokOHDo+6OkIIIUzQ1OLy8PDg/PnzdOnS5YFvaGdnZ7Jl\nlZaWpraciiv722+/mSwLlFi+ODt37mTYsGGMGDGC2bNnF5kvODiYxMREcnISgVjA877vKYR49GJj\nY/H29mb27NnF/r8vtIuNjSU2NrbMrq8pcP3rX/+if//+2Nra0r17d5Ov67Tu6dKsWTPOnTtnlB4f\nH4+bm1uJZb/++mtycnIM+rni4+OpXLkyrq6umurwdwcOHKB///689tprrFq1qti8wcHB7Nu3j507\n/+D2bc/7up8QouJ5GFuIiAJ/n99rah7tg9AUbdzc3IiLi2PIkCHUrFmTSpUqGRx/H8lXHF9fX06c\nOEFSUpKalpyczLFjx/D19S2xbG5uLlu2bFHT8vLy2Lx5Mz4+PqWqR6Hjx4/Tp08funXrxoYNG0pd\nXoinhb21tbpHVEU77K2tH/XHI8qRphZXUFBQsedL85fKyJEjCQ0NpU+fPoSEhAAQGBiIo6Mjo0aN\nUvOlpKTg4uLC7NmzCQwMBMDd3R1/f38mTJhAbm4uTk5OrFixgpSUFKPBFKdOnSI5OVldWywuLk4d\ntdizZ0+qVKnCL7/8Qs+ePalZsyZTpkzh5MmTBtdo166d5ucS4kmXnplJRd2pS5dZMTe4FGVDU+AK\nDg5+aDe0srIiJiaGiRMnMnjwYBRFoWvXrixduhQrKys1n6Io5OfnG83DioiIYObMmcyaNYuMjAzc\n3d2Jjo42Gr6+fPly1q5dCxQE1sjISCIjI9HpdCQlJeHo6MiJEyfIyMjg+vXreHl5GZSXhYOFePrE\nxsYSGBjITz/9hIWFBT169ODDDz/k2WefBQreDjk7OzN06FAiIiKMyuv1ejp37szBgwfVtEuXLvHB\nBx8QHR3NpUuXsLS0pG7dunh5ebFkyRLZNPY+PJJPrH79+iXO2XJycjK5ErOlpSWLFy9m8eLFxZaP\niIgw+Yt1r7feeou33nqrxPoKIZ58x44d44MPPqB379689957nDx5kg0bNnD06FFOnjxpMPiruLdM\n957LysrCw8ODy5cv06tXLwYMGEBWVhYJCQmEhYWxYMECCVz3QfM8rqL+ofR6PTY2NrRq1UqGkAsh\nHlt79+7l888/N/hjNigoiJCQEIKDg/nkk09Kfc0DBw7w22+/qYuU3+v69etUqVLlQav9VNIcuLRo\n37493377rcmllIQQoiJr0qSJ0RuYadOmERoayhdffHFfgavQ31f7AdNLzgltNI0qjI+Px9XVlcWL\nF5OSksKtW7dITk5m0aJFNGzYkKNHj7JlyxbOnz/P9OnTy7rOQgjx0Jl6Y2RlZYW7uzvp6ekm55CW\nxNPTk2effZaxY8fi7+9PREQEFy9efBjVfappClxjx45l+PDhTJw4kfr162NhYYGjoyOTJ0/m7bff\nZubMmfTr149p06axc+fOsq6zEEI8dLVq1TKZXrt2baDg1V5pWVtbc/z4cV5//XX27dvH8OHDadSo\nEU2aNJFl5R6ApsB14sQJXnzxRZPnWrVqxYkTJwBo3bo1V65ceXi1E0KIcvLnn3+aTC/8TrOxsVEX\nWsjLyzPKV1Rga9CgAWvXruXq1aucOnWKkJAQ0tPTefPNNw1GHwrtNAUua2tr9u/fb/LcgQMH1He1\nOTk5WMtEQCHEY+i7774zSsvKyuKnn37Czs4OR0dHdb3W33//3Sjvjz/+WOz19Xo9rVq1YsaMGaxe\nvRqAb7755iHU/OmjKXANHz6cDz/8kHfffZdDhw5x/vx5Dh06xNixY1m0aBHDhw8H4Pvvv+f5558v\n0woLIURZSEhIMJpCs2DBAjIyMhg0aBBQ8Ed848aNOXLkCImJiWq+zMxMk/3758+fN9mS++OPPwDT\ngzZEyUo1qnDp0qV8+umnavozzzzDjBkz1PO9evVi4MCBZVBNIYQoW926dWPMmDHs2rWLRo0acerU\nKfbv34+zs7PBIgyTJ0/mnXfeoX379vTr14/8/Hyio6N56aWX+P777w2uuWfPHt5//31efvllXF1d\nsbe3JyEhgW+++QY7OztGjBhRzk/5ZNAUuMzMzAgJCWHy5MmcPXuWy5cv4+DgwPPPP2+w4G6bNm3K\nrKJCCFGWPDw8mD59OoGBgURHR2NpacngwYNZuHChwffciBEjyM3NZenSpXz22WfUqVOHYcOGMXPm\nTINNdgFeffVVUlJSOHz4MF999RXZ2dnUq1eP4cOHM3XqVBo0aFDej/lEKNWUbTs7Ozp16lRWdRFC\nVGB21apV2DUB7apVu++ynp6eBqv0HD58uMQyY8aMYcyYMUbpf1/tp0mTJnz88cf3XTdhmra9SID/\n/Oc/TJw4kdatW/Pcc8+pW5N8/PHHRs1jIcSTJ+3GDRRFqZBH2o0bj/rjEeVIU+CKi4ujRYsWbNiw\ngTp16pCSksKdO3eAglXcly1bpvmGqamp9OvXD1tbW2xsbOjbty+pqamayubk5BAQEICDgwNWVlZ4\neHhw5MgRo3xLliyhd+/eODg4oNfri135IywsjCZNmmBpaUmTJk1K3I9LCCHEo6UpcE2ePJmmTZvy\n66+/sn37doNzHh4eHD9+XNPNsrOz8fb2JiEhgXXr1rF+/XouXLiAl5cX2dnZJZYfPnw44eHhhISE\nsGvXLhwcHPDx8eHMmTMG+cLDw7l69Sp+fn5A0QtihoWFMXr0aPr378+ePXvo378///znP1m5cqWm\n5xFCCFH+NPVxfffdd3z55ZdUq1bNaOJd7dq11aGdJQkLCyMpKYmEhAScnZ0BaNGiBQ0bNmTVqlVM\nnDixyLJnzpxh48aNREREMHToUAA6depEs2bNCAoKIioqSs0bHx8PwN27d4sMQnl5ecycOZMhQ4bw\n//7f/wOgc+fOXLp0icDAQEaMGCGrNgshRAWkqcWl1+uLbLVcvXpV8wrHO3bsoH379mrQgoLtSzp0\n6GAQeIoqa25ujr+/v5pmZmbGwIED2bNnD7m5uUZl/r6X172OHz/O1atX1fkZhQYPHsy1a9dMTkYU\nQgjx6GkKXC+99BKff/65yXORkZGatzOJi4ujefPmRulubm5qK6m4ss7OzkYT9tzc3Lhz506pF66M\ni4sDMKqPm5sbUDBxUAghRMWj6V1YUFAQXbp0oVu3brzxxhsA7N+/n6VLl7Jt2zZNw0cB0tPTDeZD\nFLK3tyc9Pb3YsmlpaUWWLTxfGoX5/37N+72eEEKI8qGpxdW5c2eioqJISkpSl3eaNm0a3333HVFR\nUbRr165MKymEEEIU0jz6oGfPnvTs2ZMLFy7w559/Ur16dRo3blzsFtZ/Z2dnZ7JllZaWZrAtdlFl\nTe2HU9gyKqm8qetBQSuwcNuCB7meEEKI8lHqYXMNGzakYcOGAFy7do3q1atrLtusWTN14vK94uPj\n1b6l4sp+/fXX5OTkGPRzxcfHU7lyZVxdXTXXo/B6AOfOnTMIXIV9bUXVJzg4mMTERHJyEoFYwLNU\n9xVCiCddbGwssbGxZXZ9Ta8KV69ezaJFi9Sfz549S926dalZsyatW7fWPBze19eXEydOkJSUpKYl\nJydz7NgxfH19Syybm5vLli1b1LS8vDw2b96Mj48P5ubmmupQyMPDgxo1avDFF18YpG/YsIHq1asX\nOeAkODiYIUOGYGnpggQtIYQw5unpSXBwsHo8bJoCV2hoqEErZ9KkSdjZ2bF06VKuX79OYGCgppuN\nHDkSJycn+vTpw44dO9ixYwd9+vTB0dGRUaNGqflSUlKoVKmSOr8KwN3dHX9/fyZMmMBnn33GgQMH\nGDhwICkpKUYrY5w6dYqtW7eybds2oGAE4datW9m6dSu3bt0CUK+/du1aAgMDiY2NJSgoiIiICObO\nnStzuIQQooLS9O2ckpJC06ZNAcjIyODQoUNs376dnj17UqNGDaZNm6bpZlZWVsTExDBx4kQGDx6M\noih07dqVpUuXYmVlpeZTFIX8/HyjeVgRERHMnDmTWbNmkZGRgbu7O9HR0bi7uxvkW758OWvXrgUK\nVs2IjIwkMjISnU5HUlISjo6OAIwaNQqdTsfixYtZtGgRDRo0YPny5YwePVrT8wghhCh/mgJXfn6+\numV14cRcLy8vAOrVq1fkltem1K9fn61btxabx8nJyWiVZSjYdG3x4sUsXry42PIRERFGG8IV5Z13\n3uGdd97RlFcIIR6Up6cnhw8fNvkdJ7TR9KrQ1dVV3WJ68+bNeHh4qC2ky5cvywg8IZ4C1nZ26HS6\nCnlYm5jjWRqxsbElLsj9sBTWWdw/TS2ugIAABg8ezNq1a0lPTycyMlI9d/DgQVq0aFFmFRRCVAyZ\nGRlw8OCjroZJmf99A/SgyiOgrFu3Tu1rF/dHU+B64403cHR05MSJE7Rp08ZgM8latWqVOCJQCCEe\nB8Wtb/qw1K9fv8zv8aTTvJFkx44dmTJlitEOyHPnzqVHjx4PvWJCCFEegoOD8fb2BmDOnDno9Xr1\nSElJ4a233kKv1/Prr7+yaNEimjZtiqWlpbqbRUJCAgEBAbi7u2Nvb0+VKlVo3rw58+bNM9pNAwr6\nuArHDNxbB71ez6FDh/jyyy954YUXsLKyok6dOkyYMIGcnJyy/yAeIzLmWwjxVPPy8iIlJYW1a9fi\n6emJp6enes7W1lb973fffZeTJ0/Sq1cv+vTpo+5ysW3bNtasWUOXLl145ZVXuH37NrGxsQQGBnLq\n1CmjPQyh6FeSoaGhREdH849//IMuXbqwe/duPvnkE65evcqGDRse7oM/xiRwCSGeap07d0ZRFDVw\nBQUFmcx3/vx5zpw5Q506dQzShw4dypQpU4zmfr7zzjuEh4dz9OhRzTtoHDhwgNOnT6urE4WEhODu\n7s6mTZtYtGgRDg4O9/GETx7NrwqFEOJpFhAQYBS0ABwcHEwuWFA4H/TAgQOa7/Hee++pQQsKpgC9\n/vrr5Ofnc/r06fuo9ZNJApcQQmjw4osvmkzPz88nLCyMDh06YGtri5mZGXq9Xs1/+fJlzfdo3bq1\nUVrdunWBgsUfRIEiXxW2atWK9evX06xZM+bOncvw4cPVD1AIIZ429y7Gfa9x48axYsUKnJyc6Nev\nH88++yyVK1cmPT2dZcuWcfv2bc33sLa2NkorbM3dvXv3/ir+BCoycJ09e5bMzEygYMTLq6++KoFL\nCPHUMjWg4sqVK6xYsQJ3d3eOHz+OhYWFeu77779n2bJl5VnFp0aRgcvBwYGvv/5a/Svj8uXLJvfD\nKlS4/p8QQjxuzMzMgNK3agp3uujatatB0AI4evTow6mcMFJk4Bo9ejSzZs3iww8/BMDPz6/Ii+h0\nOmnGCiEeW4XL1hX3x7kpDRo0AODYsWMG6QkJCcyfP//hVE4YKTJwzZgxg65du3L+/HmGDRvG9OnT\nee655x74hqmpqUycOJH9+/cbrA6vZTZ5Tk4OgYGBbNiwgevXr+Pu7s7ChQt5+eWXDfIpisKCBQtY\ntWoVV65coXHjxgQFBfHaa68Z5MvKymL+/Pls2bKF//znP9SoUQMvLy/mzp2r/kIKIZ58TZs2pU6d\nOmzatAkLCwvq1q2LXq9n3LhxxZZzcHDAz8+P7du389JLL+Hp6cmlS5fYuXMnPj4+fPXVVybLlccK\nHU+yYudxtWnThjZt2hAREcGgQYPUrU3uV3Z2Nt7e3lSpUoV169YBMGvWLLy8vPj5558NtjYxZfjw\n4Xz77bd89NFHODs7Exoaio+PD8ePH6dly5ZqvlmzZrF48WI++OADWrduzcaNG+nfvz/ffPMN3bt3\nV/MNGzaMXbt2MXfuXF588UVSUlKYPXs2Xbp04cyZMzzzzDMP9LxCiMeDXq9n27ZtTJ06lY0bN5KZ\nmYlOp2PQoEElLoq7du1aHB0d2b59O6Ghobi6uvLBBx/Qq1cvk4HL1PWKu4csymuCUo6WLl2qmJmZ\nKYmJiWpaUlKSUqlSJWXJkiXFlv3pp58UnU6nrFmzRk3Ly8tTGjdurPj6+qppV65cUSpXrqwEBwcb\nlO/SpYvSokUL9eesrCzFzMxMmTFjhkG+6OhoRafTKXv37jWqQ+HHtXfvXsXGpqsCinroqpgrjEIh\n+L/Hiyh+ZmbKvZl0lpYKkZEKBw8WHB06KH56P+UgB9XDTGem5Obmavg0hXj4ivtKqGZrqwAV8qhm\na1uOn5IopDWEPOxQo3ke188//0zfvn2pUaMGZmZm1KxZk/79+3P27FnNQXLHjh20b99eXSoFCvbe\n6tChA1FRUSWWNTc3x9/fX00zMzNj4MCB7Nmzh9zcXAD1vwcNGmRQftCgQZw9e5bk5GQAdaNKGxsb\ng3yFP8teOUIYupGejqIoFfK4kZ7+qD8eUY40Ba6TJ0/Srl07YmNj6d27NwEBAfTs2ZOYmBjatWvH\nqVOnNN0sLi6O5s2bG6W7ubkRHx9fYllnZ2csLS2Nyt65c4eLFy+q+SwsLHBxcTHKBwXLtgBUrVqV\nESNGsGzZMmJjY7l58yZxcXHqYpldunTR9ExCCCHKl6a1CqdPn07z5s05cOAA1apVU9MzMzPp2rUr\n06dPZ9++fSVeJz09HTsTG77Z29uTXsJfTGlpaUWWLTxfmnwAK1euZOTIkerK0ABt27Zl7969Jpdw\nEUII8ehpanGdOHGCadOmGQQtgGrVqjF16lSOHz9eJpW7X4rGETtjxoxh69atLF68mMOHD7N+/Xqu\nXbtG9+7dyc7OLuNaCiGEuB+amhUljWjROuLFzs7OZMsqLS1NbREVV9bUHIvCFlRheTs7O5Nrev09\n35kzZ1i9ejWfffYZw4YNAwr2HGvbti2NGjUiPDyc8ePHa3ouIYQQ5UdT4Grbti3z58+na9euBmtp\n3bx5k4ULF9KuXTtNN2vWrBnnzp0zSo+Pj1f7oIor+/XXX5OTk2PQzxUfH0/lypVxdXVV892+fZvE\nxESDfq7CPrTC+xT+/PeFM11dXbG1teWXX34xWY/g4GASExPJyUkEYgHPYusthBBPm9jYWGJjY8vs\n+ppeFX7wwQecO3cOJycnhgwZwtSpUxkyZAhOTk6cPXuWefPmabqZr68vJ06cUJdJAUhOTubYsWP4\n+vqWWDY3N5ctW7aoaXl5eWzevBkfHx/Mzc0B6N69O+bm5nzxxRcG5Tds2MDzzz+vTiyuV68eUDDw\n5F4JCQlkZGQUuS5jcHAwQ4YMwdLSBQlaQghhzNPTk+DgYPV42DS1uNq0acP333/P3LlziY6OJj09\nHXt7e7y9vQkMDOT555/XdLORI0cSGhpKnz59CAkJASAwMBBHR0dGjRql5ktJScHFxYXZs2cTGBgI\ngLu7O/7+/kyYMIHc3FycnJxYsWIFKSkpbNy4US1bs2ZNJk2axPz586lWrRovvPACmzdv5uDBg+zc\nuVPN17FjR1q1asWkSZNIS0ujdevW/Pbbb4SEhGBra8vQoUM1PZMQQojypXnoXIsWLdi6desD3czK\nyoqYmBgmTpzI4MGDDZZ8unfVDEVR1HlW94qIiGDmzJnMmjWLjIwM3N3diY6Oxt3d3SDfvHnzqFq1\nKsuWLeOPP/6gSZMmREZG0qNHDzWPTqdj//79zJs3j7CwMIKCgqhRowYdOnRg7ty5aotMCCFExaJT\ntA7BE+h0OhRFYd++ffTv/yHXr/9vCoCuSmWUIblQuLP2N+D3oxnb7ll8WG9pibJ+PdSoUZAwaxZ+\nx2sxPv9/g0C66rqScydHhuOLR6Lwd1wILbT+vjzs3yvZAVkIIcRjRQKXEEKIx4oELiGEEI8VCVxC\nCCEeKyUGrtu3b2NnZ8eOHTvKoz5CiArKztpO3Ruqoh121sbrk4onV4lD1ywsLKhUqZLRquxCiKdL\nRmYGBzn4qKthklem16OugihHml4V/uMf/3jgOVxCCFGRbd26lS5dumBnZ4eVlRUNGzZk9OjRpKam\nqnl++OEHxo4dS7NmzbCxsaFq1aq0bt2aFStWmLymXq/Hy8uL1NRUBg0aRO3atTEzM+Pnn38ur8d6\nImmaLNSjRw/GjRtH37598fPzw8HBwWhh3Xu3BhFCiMfJ+PHjCQ0NpXbt2vj7+2Nvb8+vv/7K1q1b\n6dGjB/Xr1wcgLCyMXbt20blzZ3r37k1mZiZ79uxh7NixJCQk8PHHHxtd+9q1a3To0IFatWrx5ptv\nkpWVZbDggig9TYGrb9++AGzfvp3t27cbndfpdNy9Z6KtEEI8Lnbs2EFoaCitW7cmJibGYPum27dv\nG2xxNHPmTFauXGlQ/u7du/Tq1Yt//etfTJw4EUdHR4Pz586dY+TIkaxatapsH+QpoilwxcTElHU9\nhBDikSh8zbds2TKjPQctLCywsLBQfy5sed3LzMyMkSNHsmfPHmJjYxkyZIjBeUtLSxYsWFAGNX96\naQpcnp6eZVwNIYR4NE6ePMkzzzyDh4dHiXlv377NJ598wubNm/n3v/9NVlaWwfnLly8blXFycjK5\nK7u4f6VaEO/q1aucOHGCa9eu0atXL6pXr86tW7eoXLkyZmZmZVVHIYQoM9evX+e5557TlPe1115j\n9+7dNG3alEGDBlGzZk0qVapEUlISa9eu5fbt20Zlateu/bCr/NTTNKpQURSmTJlC3bp18fX15e23\n3yYlJQUoGHGodT8ugNTUVPr164etrS02Njb07dvXYNROcXJycggICMDBwQErKys8PDw4cuSIyfrO\nnz8fJycnqlSpgru7O9u2bTN5zfT0dCZMmECDBg2wtLSkfv366o7IQognn62trcmW0t+dPHmS3bt3\n0717d+Li4lixYgVz584lKCiIV199tchyWneIF9ppClzz589n+fLlzJ49m++//95gld/evXuza9cu\nTTfLzs7G29ubhIQE1q1bx/r167lw4QJeXl4GHaBFGT58OOHh4YSEhLBr1y4cHBzw8fHhzJkzBvlm\nzZrFnDlzGD9+PNHR0bRr147+/fuze/dug3zp6el07NiRmJgY5s2bx/79+/noo48MdnkWQjzZ2rRp\nQ1ZWFkePHi02X2JiIgA9e/Y0OldSWfFwaXpVGB4eTmBgIDNmzCAvL8/gnIuLCxcvXtR0s7CwMJKS\nkkhISMDZ2Rko2OerYcOGrFq1iokTJxZZ9syZM2zcuJGIiAh1k8dOnTrRrFkzgoKCiIqKAuDPP//k\no48+YsaMGUyaNAmAzp07c/HiRaZNm0b37t3Va06fPp3s7GzOnj1L1apV1XR/f39NzyOEePyNGTOG\n3bt389577xETE2Pwh2tOTg63bt3Czs5O3T39u+++45///Kea58SJE6xevbrc6/0009Ti+v3332nf\nvr3Jc5UrVzbqoCzKjh07aN++vRq0oKDjskOHDmrgKa6subm5QVAxMzNj4MCB7Nmzh9zcXAD1vwcN\nGmRQftCgQZw9e5bk5GQAsrKyWLduHSNGjDAIWkKIp0uvXr0YN24cp0+fplGjRowaNYrp06fz5ptv\nUq9ePbU7om3btrz44ots2rQJb29v3n//ffr166fO6RLlR1PgqlOnDmfPnjV57ueff9bcsRkXF0fz\n5s2N0t3c3IiPjy+xrLOzs9HSU25ubty5c0dt9cXFxWFhYYGLi4tRPoDz588DBTPgc3JyqFWrFv36\n9cPKyopq1arh5+enBjchxNNh2bJlbNy4kcaNG7Np0yY++eQTTp06xYABA2jdujVQsArGN998w9Ch\nQ/n3v//N8uXLSUlJYe3atbz77ruP+AmeLppeFQ4YMIC5c+fSqlUrg5bXv//9bxYvXszIkSM13Sw9\nPd3ksFB7e3vS09OLLZuWllZk2cLzpcl36dIlAKZMmUKPHj3YuXMnf/75J9OnT8fT05Nz585JS0yI\ne9hWs62wawLaVrN94Gv4+/uX2E1Qq1YtIiIiTJ7Lz8/XlCYenKbANXv2bI4dO0anTp3U97z9+/cn\nNTUVDw8Ppk2bVqaVLC0tW0QX/kK5uLiwceNGNd3FxYV27dqxYcMGRo8eXWZ1FOJxk36j+D8uhSgv\nmgKXlZUVBw8eZOPGjURHR+Pq6kr16tUJCgrizTffpFIlbdPB7OzsTLas0tLS1BZRcWV/++03k2Xh\nfy0qOzs7MjIySsxXvXp1ALp06WKQr02bNlhbWxuNVCwUHBxMYmIiOTmJQCzgWWy9hRDiaRMbG0ts\nbGyZXV/zBORKlSoxePBgBg8efN83a9asGefOnTNKj4+PV/ugiiv79ddfk5OTY9DPFR8fT+XKlXF1\ndVXz3b59m8TERIN+rsI+tML7NGvWrMh7FddiCw4OZt++fezc+Qe3b3sWW2chhHgaeXp6Gqy4NGfO\nnId6/VLtgHzx4kW+/PJLFi1axJdffqnOa9DK19eXEydOkJSUpKYlJydz7NgxfH19Syybm5vLli1b\n1LS8vDw2b96Mj48P5ubmAHTv3h1zc3O++OILg/IbNmzg+eefV1911qtXjxdffJG9e/ca5Dt+/DiZ\nmZm89NJLpXq2h0VRFK5evWpwyHtyIYS4h6LBrVu3lLfeeksxMzNTdDqdepiZmSlvv/22kpOTo+Uy\nSlZWluLq6qo8//zzSlRUlBIVFaW0aNFCcXFxUbKystR8ycnJipmZmTJ37lyD8gMHDlTs7OyU8PBw\nZf/+/Urfvn2VKlWqKD/++KNBvmnTpimWlpbKkiVLlIMHDyqjR49W9Hq9smvXLoN8Bw4cUCpVqqT0\n7dtX+fbbb5W1a9cq9erVU9zc3Ew+U+HHtXfvXsXGpqsCinroqpgrjEIh+L/Hiyh+ZmbKvZl0lpYK\nkdK7/s4AACAASURBVJEKBw8WHB06KH56P+UgB9VDr0exsbFQbG0tFVtbS8XCwkxZunSpps9XiAel\n8StBCEVRtP++POzfK02vCqdMmcKXX37J3Llz8ff3p3bt2ly5coVNmzYxd+5crKys+Ne//lXidays\nrIiJiWHixIkMHjwYRVHo2rUrS5cuNdifRlEU8vPzjV7ZRUREMHPmTGbNmkVGRgbu7u5ER0fj7u5u\nkG/evHlUrVqVZcuW8ccff9CkSRMiIyPp0aOHQT5vb2927txJUFAQr732Gs888wy9evVi0aJFBitC\nlydFga++uk3h0o9hYXpNq4oIIcTTQlPg2rRpE0FBQcyYMUNNq1q1KjNnzgTg448/1hS4oGBbgJJ2\nU3ZycjL5eszS0pLFixezePHiYsvr9Xpmzpyp1q84r776arHrjAkhhKhYNPVx3b59m7Zt25o816ZN\nG5MrIgshhBBlQVPg6tKli9EghkL79u0zGlIuhBBClJUiXxX++uuv6n9PnjyZQYMGcfPmTQYMGEDt\n2rX5448/2LJlC7t372bDhg3lUlkhhBCiyMBVOC/qXitXrmTlypVG6Z07d+bu3bsPt2ZCCCGECUUG\nrs8//7w86yGEEEJoUmTgeuutt8qxGkIIIYQ2pVo5QwghnmZr1qxBr9ezdu3aR12Vp5rmtQp3795N\nZGQk//nPf8jJyVHTFUVBp9Nx+PDhMqmgEKJisLOzJiMj81FXwyRb22qkp98o8/vodDr1EI+OpsD1\n4YcfMm3aNGrWrImrq6u6LmAh+UcU4smXkZHJwYOPuhameXmVT0D18/Ojffv2PPvss+VyP2GapsC1\nfPly3nnnHZYvX45Z4VpEQgjxlLG2tsba2vpRV+Opp6mPKyMjgwEDBkjQEkI8cXJzc/nkk0/o1q0b\ndevWxcLCgjp16vDmm29y8eJFg7ym+riSk5PR6/UMGzaMuLg4+vTpg729PXq9nhs3yv715dNIU+Dq\n2rUrJ06cKOu6CCFEubt27RqTJ09GURT69OnDpEmTaNu2LVu2bKFt27YkJycblTHVPXLx4kU8PDy4\nfv06I0aMYPDgwej1Mv6tLGj6VENDQ/n666/54IMP+OGHH/j111+NDq1SU1Pp168ftra22NjY0Ldv\nX1JTUzWVzcnJISAgAAcHB6ysrPDw8ODIkSNG+RRFYf78+Tg5OVGlShXc3d3Ztm1bsdc+duwYer0e\nvV4v+18J8RSxt7cnNTWV/fv38+mnnzJ//ny2b9/OgQMHuHHjBvPmzdN0naNHjxIQEEBsbCwffvgh\na9eupWrVqmVc+6eTpsBVqVIl7OzsmDVrFi+99BKurq4GR8OGDTXdLDs7G29vbxISEli3bh3r16/n\nwoULeHl5adq6Y/jw4YSHhxMSEsKuXbtwcHDAx8eHM2fOGOSbNWsWc+bMYfz48URHR9OuXTv69+/P\n7t27TV43NzeXUaNG8eyzz8pAEyGeMpUrVzY52KJTp040bfr/27v3sKiq9Q/g3w0MDCDIICp4gxwV\nFEXsWIImgonX410uT6KmaXo6Ho9wtEzkqoZ46WBZ4kEjFEMlU+RokKiQnLTHtEwZDUEEs7wCXrkM\n8P7+8MfOcQYYEwYG38/z7Odp1rxrz3qReGfPrL1Wb2RkZGh1nk6dOuH9999v7OExDbSanDF79myc\nPHkSgYGBcHR0hLGx8Z96sbi4OBQUFCA3Nxfdu3cHALi4uKBnz57YsmULAgMD6+x79uxZJCUlIT4+\nHrNmzQLw+BfL2dkZoaGhSElJAQDcvHkT69evx/LlyxEUFATg8ZJUeXl5WLZsGcaMGaN27nXr1kEQ\nBMyZMwcffPDBn8qNMaa/Tp8+jbVr1+J///sfbt26BaVSKT6n7d58Li4uPA9AR7QqXJmZmfj4448x\ne/bs53qxAwcOwN3dXSxawOO9t4YMGYKUlJR6C9eBAwcgkUjg5+cnthkaGsLf3x9r1qyBUqmERCJB\neno6lEolAgICVPoHBARgzpw5KCwshL29vdien5+P1atXIz09Xet3Voyx1iM7Oxuvv/46jIyMMGrU\nKPTo0QPm5uYQBAHx8fEoKirS6jwdO3Zs4pGyWloVLmtr60a5byEnJweTJ09Wa+/Tp0+Dm0vm5OSg\ne/fukEqlan0rKyuRl5eH3r17IycnByYmJpDL5WpxAKBQKFQK14IFC+Dr64vXXnuNCxdjL6CoqChU\nVVUhKysLbm5uKs8lJSVpfR7+mkF3tPqO6x//+Ac+/fTT5560UFJSAplMptZubW2NkpKSevsWFxfX\n2bf2+WeJA4DExEScOXMG69at0z4Jxlirkp+fj3bt2qkVrRs3biA/P7+ZRsXqo9UV17179/Dzzz+j\nT58+8Pb21lgYIiMjG31wfxYRNRhTXFyMf/3rX4iKioKNjY0ORsUYa4ns7e1x6dIlXLx4EU5OTgCA\nyspKLFy4EFVVVXwl1QJpVbienA6am5urMUabwiWTyTReWRUXF4tXRPX11fRZc+0VVG1/mUyG0tLS\nBuNWrFgBOzs7+Pj4iPG1azCWlpbCxMQE5ubmaucJDw9Hfn4+ysvzAWQC8Kx33Iyxlm3hwoU4fPgw\nhgwZAl9fXxgZGSEjIwPV1dXo37+/2qxl1rDMzExkZmY22fm1KlyNdV+Ts7Mzzp8/r9auUCjE76Dq\n67t//36Ul5erfM+lUChgbGwsbnzp7OyMiooK5Ofnq3zPpVAoAPzxXdeFCxfw888/o127dmqvZWNj\ng0mTJmm89ys8PByHDx9Gaup1VFR4Npw0Y6xFGz9+PHbv3o2oqChs374dbdu2xejRo7FmzRr4+fmp\nXHHxArva8fT0hKenp/g4IiKiUc+v9erwjWHChAlYsmQJCgoK8NJLLwF4vFzKd999h+jo6Ab7hoeH\nY8+ePZg5cyYAoKqqCrt378aoUaPEhX/HjBkDiUSCnTt3IjQ0VOyfmJiIfv36iRMzYmJicPfuXZXX\niI+PR0JCAo4cOcIzhBh7ipWVhc4Ws31WVlYWz9Xfx8cHPj4+au3HnlpVeNasWeLtOLUcHBx40QId\n02nhmjdvHjZt2oSJEydi1apVAICQkBB069YN8+fPF+MKCwshl8sRFhaGkJAQAICrqyv8/PywePFi\nKJVKODg4YPPmzSgsLFSZ+dO+fXsEBQUhKioKFhYWGDBgAHbv3o1jx44hNTVVjOvfv7/a+I4ePQrg\n8X1fvFQLY6p0sW0IY9rQqnAZGBhAEAS1SQ+1bYIgoLq6usHzmJmZ4ejRowgMDMSMGTNARBgxYgRi\nYmJgZmYmxhERampq1F4vPj4ewcHBWLFiBUpLS+Hq6oq0tDS4urqqxK1evRpt2rTBxo0bcf36dTg5\nOSE5ORljx46td3z8MQBjjLV8WhWuJz9yq3Xnzh188803qKysxJtvvqn1C3bt2rXBe7bquvSWSqXY\nsGEDNmzYUG9/AwMDBAcHIzg4WOtxAUBYWBjCwsKeqQ9jjDHd0qpwhYeHa2yvqqrC+PHj0bZt28Yc\nE2OMMVan5/oix8jICO+88w5iYmIaazyMtTgymaXKlu0yGW8kyFhzeu7JGZWVlbhz505jjIWxFunp\nLetb6sw6xl4UWhUuTTf+VlZW4ty5c3jvvfcwcODARh8YY4wxpolWhcvBwaHO5+RyOT755JPGGg9j\njDFWL60K12effabWJpVKYW9vj1dffZX3oGGMMaYzWhWuZ5nuzhhjjDUlXh6CMcaYXtHqiouIkJCQ\ngKSkJBQVFYmrqD+5csbly5ebdKDsxSOTWaK0VHUGn5WVBS891IRkMhmvHsO0pmmLK13QqnCtWrUK\nYWFh6Nu3L1xdXWFiYqLyPP+is6bw9DR0gKeiN7UnN1plrKXSqnBt27YNixYt4huNGWOMNTutvuO6\nc+cOJkyY0NRjYYwxxhqkVeHy8PBo1F1Ar169imnTpsHKygpt27bF1KlTcfXqVa36lpeXY+nSpbCz\ns4OZmRkGDx6M48ePq8UREaKiouDg4ABTU1O4urqqbQz5+++/47333sOAAQNgZWWFDh06YMSIERrP\nxxhjrGXQqnBt3LgRn332GRISEnD79m3U1NSoHdp69OgRhg8fjtzcXGzfvh07duzApUuX4OXlhUeP\nHjXY/6233sLWrVuxatUqHDx4EHZ2dhg1apRaYV2xYgUiIiKwaNEipKWlwc3NDT4+Pvj666/FmNOn\nT2PPnj2YPHkyvvzyS3z++eeQSqXw9PTEwYMHtc6JMcaY7mj1HVevXr0AALNnz9b4vLb7cQFAXFwc\nCgoKkJubi+7duwMAXFxc0LNnT2zZsgWBgYF19j179iySkpIQHx8v7kLq4eEBZ2dnhIaGIiUlBQBw\n8+ZNrF+/HsuXL0dQUBCAx5tD5uXlYdmyZRgzZgwAYOjQocjLy1O5gXrUqFFwdnbG2rVrMW7cOK1y\nYowxpjt/ej+uJz3LrMIDBw7A3d1dLFrA4yWlhgwZgpSUlHoL14EDByCRSODn5ye2GRoawt/fH2vW\nrIFSqYREIkF6ejqUSiUCAgJU+gcEBGDOnDkoLCyEvb29xu1YDA0N0b9/f5w5c0brnBhranxrAGN/\neK79uP6MnJwcTJ48Wa29T58+DW4wmZOTg+7du0Mqlar1raysRF5eHnr37o2cnByYmJhALperxQGA\nQqGAvb29xteorKzEiRMn1HZVZqw58a0BjP3hubc1eVYlJSUab1qztrZGSUlJvX2Li4vr7Fv7/LPE\naRIeHo5r164hKSmp3rEwxhhrHq12yScieuY+X3zxBaKjoxEaGoohQ4Y0wagYY4w9L51fcclkMo1X\nVsXFxeIVUX19Ne0NVnsFVdtfJpOhtLS0wbgnpaamYvbs2Zg7dy7CwsLqHEN4eDjy8/NRXp4PIBOA\nZ71jZoyxF01mZiYyMzOb7Pw6L1zOzs44f/68WrtCoRC/g6qv7/79+1FeXq7yPZdCoYCxsTF69Ogh\nxlVUVCA/P1/ley6FQgEAaq9z5MgR+Pj4YMqUKdiyZUu9YwgPD8fhw4eRmnodFRWe9cYyxtiLyNPT\nE56enuLjiIiIRj2/zj8qnDBhAk6ePImCggKx7cqVK/juu+8aXJ1jwoQJUCqV2LNnj9hWVVWF3bt3\nY9SoUZBIJACAMWPGQCKRYOfOnSr9ExMT0a9fP5WJGSdOnMDEiRPh7e2NxMTExkiRMcZYE9L5Fde8\nefOwadMmTJw4EatWrQIAhISEoFu3bpg/f74YV1hYCLlcjrCwMISEhAAAXF1d4efnh8WLF0OpVMLB\nwQGbN29GYWGhymSK9u3bIygoCFFRUbCwsMCAAQOwe/duHDt2DKmpqWLcxYsXMW7cOLRv3x5LlizB\nqVOnVMbq5ubWlD+KFu3p6dc89Zox1lLovHCZmZnh6NGjCAwMxIwZM0BEGDFiBGJiYmBmZibGERFq\namrUJlnEx8cjODgYK1asQGlpKVxdXZGWlqY2fX316tVo06YNNm7ciOvXr8PJyQnJyckYO3asGPP9\n99+jtLQUd+/ehZeXl0r/Z7mpujV6evo1T71mjLUUOi9cANC1a9cG79lycHDQuJSUVCrFhg0bsGHD\nhnr7GxgYIDg4GMHBwXXGzJo1S1yBgzHGmH5otdPhGWOMtU5cuBhjjOkVLlyMMcb0ChcuxhhjeoUL\nF2OMMb3ChYsxxphe4cLFGGNMr3DhYowxple4cDHGGNMrXLgYY4zpFS5cjDHG9IrOC9fVq1cxbdo0\nWFlZoW3btpg6dSquXr2qVd/y8nIsXboUdnZ2MDMzw+DBg3H8+HG1OCJCVFQUHBwcYGpqCldXV3z1\n1VcazxkXFwcnJydIpVI4OTk1uB8XY4yx5qXTwvXo0SMMHz4cubm52L59O3bs2IFLly7By8sLjx49\narD/W2+9ha1bt2LVqlU4ePAg7OzsMGrUKJw9e1YlbsWKFYiIiMCiRYuQlpYGNzc3+Pj44Ouvv1aJ\ni4uLw4IFC+Dj44P09HT4+PjgnXfeQWxsbKPmzRhrPDKZJQRBUDlkMsvmHhbTIZ2uDh8XF4eCggLk\n5uaie/fuAAAXFxf07NkTW7ZsQWBgYJ19z549i6SkJMTHx4srunt4eMDZ2RmhoaFISUkBANy8eRPr\n16/H8uXLERQUBAAYNmwY8vLysGzZMowZMwbA4w0og4ODMXPmTKxcuVKM++233xASEoK5c+fCyKhZ\nFs9njNXj6S13AN5250Wj0yuuAwcOwN3dXSxawOPtS4YMGSIWnvr6SiQS+Pn5iW2Ghobw9/dHeno6\nlEolAIj/HRAQoNI/ICAA586dQ2FhIYDHOx/fvn1bLW7GjBm4c+cOsrOznytXxhhjTUOnhSsnJwd9\n+/ZVa+/Tpw8UCkWDfbt37w6pVKrWt7KyEnl5eWKciYkJ5HK5WhwA8XVycnIAQG08tXEXLlzQNq1W\nIzMzs7mH0GRac24A56fvWnt+jU2nhaukpAQymUyt3draGiUlJfX2LS4urrNv7fPPGgdALfbpuBdJ\na/6fpzXnBnB++q6159fYWuV0eCJq7iEwxhhrIjqdfSCTyTReWRUXF4tXOvX1LSoq0tgX+ONKSSaT\nobS0VKs44PFVYMeOHeuM08TAwADl5T/C0nK82Havogqmh00hMZcAAMqulSGbqjHe8o/ZTlRejjZr\n18LAxAQA8OjCBWQLubhleeuPk98HwsIsIQiPH165UgEXl1b5/oL9P0uZDPef+p21sLLCvQY+hWDs\nhUU6NHz4cHrttdfU2ocNG0aenp719o2IiCBjY2MqKytTaQ8LCyMTExOqrKwkIqKEhAQSBIHy8vJU\n4uLj40kQBLpy5QoREWVlZZEgCJSRkaESd+zYMRIEgTIzM9XGIJfLCQAffPDBBx/PcMjl8oYLxDPQ\naeGKiYkhIyMjunz5sthWUFBAEomEPvzww3r7/vjjjyQIAiUkJIhtSqWSnJycaMKECWLbzZs3ydjY\nmCIiIlT6v/766+Ti4qLSt3379jR79myVuLfeeotsbGxIqVT+qRwZY4w1LcPw8PBw6IiLiwt27dqF\nL7/8Ep07d8Yvv/yCt99+G2ZmZti2bRskkscfsxUWFsLGxgaCIGDYsGEAAFtbW1y8eBGffPIJbGxs\nUFJSgmXLluGHH35AYmIibG1tAQDm5uZ49OgR1q9fD3Nzc1RUVCA6Ohp79+7Ftm3b0LNnTwCPP+6z\ntLTEBx98gKqqKhgYGOCzzz7DRx99hHXr1mHQoEG6+rEwxhh7FrqulEVFRTR16lSytLQkCwsLmjx5\nMhUWFqrEFBQUkCAIaldNZWVlFBQURLa2tiSVSsnNzY2ysrLUXqO6uppWrVpF9vb2ZGJiQv3796e9\ne/dqHM+WLVuoV69eZGJiQr169aLNmzc3XrKMMcYanc4Ll76pLbRt27YlS0tLmjJlChUVFTX3sOp1\n9epVWrhwIbm5uZGpqSkJgqD25oCIqLi4WPxo1NzcnEaMGEHnzp1TiysrK6MlS5aQra0tmZqakru7\nO3377be6SEVNcnIyTZw4kbp27Uqmpqbk6OhI77//Pt2/f18lTh9zIyJKS0sjLy8vsrW1JRMTE+rS\npQv5+vqSQqFQidPX/DQZNWoUCYJAK1asUGnXxxxrvyN/+pDJZCpx+pjbkw4ePEhDhw6lNm3akKWl\nJQ0cOJCOHj0qPt/U+XHhqsfDhw+pR48e1K9fP0pJSaGUlBTq168fyeVyevjwYXMPr07Hjh2jjh07\n0rhx48Q/Ck8XrpqaGhoyZAh17dqVdu3aRWlpaTRs2DCysbGhX3/9VSX2jTfeICsrK9q6dSsdPXqU\npkyZQqampvTTTz/pMi0iInJzc6Np06bRzp07KSsri2JiYsjKyorc3NyopqZGr3MjIkpKSqJ3332X\n9u7dS99++y3t2LGDnJ2dydLSUnzDpM/5Pe2LL74gOzs7EgSBQkJCxHZ9zbG2cG3atIm+//578Th9\n+rQYo6+51YqNjSWJREJBQUGUkZFB6enptHbtWvrvf/9LRLrJjwtXPWJiYsjQ0JDy8/PFtoKCAjIy\nMmpwMklzqv0DTkQUFxensXDt379fbfbk3bt3ydramhYtWiS2/fTTTyQIAn3++ediW1VVFTk6OqpM\nitGV27dvq7Vt376dBEEQ3/Hpa251+eWXX0gQBPr3v/9NRK0nv+LiYrK1taVdu3apFS59zbG2cB05\ncqTOGH3Njejx3z+pVEobN26sM0YX+XHhqkd90/eHDRum+wH9CXUVrjlz5lCXLl3U4mfNmkX29vbi\n48jISK1uQ2hOCoWCBEGgxMREImpduRER3bp1iwRBEP9YtJb85s2bR97e3kREaoVLX3OsLVxP32bz\nJH3NjYgoJCSE2rRpQxUVFXXG6CI/vrO1Hs+ztmJLV19uRUVF4jYz2q4R2ZyysrIAAL179wbQOnKr\nrq5GZWUlLl26hPnz56Njx47w9/cH0Dryy87Oxo4dO/DJJ59ofF7fc5w+fTqMjIxgY2OD6dOnq+w5\nqM+5ZWdnw9HREV988QXkcjkkEgl69uyJTz/9VIzRRX5cuOrxPGsrtnQNrelYm5+2az82l2vXriE0\nNBTe3t54+eWXxTHpe26DBg2CVCqFo6Mjzpw5g4yMDHTo0EEclz7nV1lZifnz52Pp0qXi7SlP09cc\nrayssGTJEmzbtg3Hjh1DSEgIMjIy4O7ujlu3bmk15paaGwD89ttvuHTpEt59910sX74chw8fhre3\nNxYuXIiPPvpIHFdT58cbTr2ghNo1pfTYgwcPMHHiRBgbGyM+Pl5sbw25JSYm4v79+8jPz8f69esx\nevRoZGdnw97eXu/zW7t2LSoqKhAcHFxnjL7m6OrqCldXV/Hx0KFD4eHhgVdffRUff/wxIiMjm3F0\nz6+mpgb3799HQkICJk2aBADw9PTElStXEBUVhUWLFulkHHzFVY/nWVuxpZPJZBrf0Ty9an5Dcc31\ncygrK8P48eNx5coVpKeno1OnTuJz+p4bADg5OeGVV16Bv78/jhw5ggcPHmDNmjUAHr+r19f8ioqK\nsHr1akRGRqKsrAylpaXi2qLl5eW4e/cuqqurW8W/Ya0BAwagV69eOHXqFAD9/v1s164dBEGAt7e3\nSru3tzdu3LiB69ev6yQ/Llz1cHZ2xvnz59XaFQqFuG+XvnJ2dhb3JHuSQqGAvb09zMzMxLiCggKU\nl5erxRkbG6NHjx46Ge+TlEolpk2bhjNnzuDQoUNwdnZWeV6fc9Okbdu2kMvlyM/PB6Df+V2+fBkV\nFRUICAiAtbW1eADA+vXrIZPJcP78eb3OURN6YscKfc7N2dm5wd03dJLfs84qeZE8z9qKLUVD0+Gf\nXHlE05RVbdeI1JXq6mry8fEhMzMzlRsen6SvudXl+vXrZG5uTgsWLCAi/c6vtLSUsrKyVI7MzEwS\nBIFmzpxJWVlZ9ODBA73O8WmnTp0iQ0NDCgsLIyL9/vc7ePAgCYJAX375pUr7yJEjqVu3bkREtG/f\nvibPjwtXPTTdgOzi4tLib0AmerzCRHJyMi1YsIAEQaDNmzdTcnKy+MtUU1NDgwcPVrtJsF27dmo3\nCfr7+5NMJqOtW7dSRkYGTZ06lUxNTenHH3/UeV61+axYsYJOnDihctSOW19zIyKaNGkSrVy5kvbv\n309Hjx6l2NhYcnR0JJlMRpcuXSIi/c6vLppuQNbHHKdPn05hYWG0b98+OnLkCK1fv57atWtH9vb2\ndOfOHb3Ordbw4cOpXbt2FBsbS+np6TR37lyVAqSL/LhwNUCbtRVboieXmzEwMBD/28vLS4wpLi6m\nOXPmkLW1NZmZmdGIESPo559/VjuXtmtE6oKDg4NKPk8eT65tqY+5ERFFR0fTX/7yF7KysiIzMzNy\ndHSkBQsWqP3O6Wt+dXm6cBHpZ45RUVHk4uJCbdu2JYlEQt26daP58+fT9evXVeL0Mbda9+7do7//\n/e/UsWNHMjY2pv79+1NSUpJKTFPnJxDxdsGMMcb0B0/OYIwxple4cDHGGNMrXLgYY4zpFS5cjDHG\n9AoXLsYYY3qFCxdjjDG9woWLMcaYXuHCxRhrUp6envDy8mruYbBWhAsXY6xJCYKgt9uUsJaJCxdj\nrEnx4jyssXHhYkwLeXl5mDFjBrp37w4zMzPI5XK888474l5SALBu3TqYmJho3GOoT58+4sZ7wOPt\nPcaOHQtzc3N07NgRS5YswX/+8x8YGBigqKio3rGkp6dj8ODBsLKygoWFBZycnLBy5Urx+fDwcBgY\nGOD8+fPw8vKCubk5OnXqhLCwMLUicuvWLSxYsABdunSBVCpF7969ERcXp/aaBQUFmD59Ojp06ACp\nVIoBAwZg//79anG7du2Ck5MTpFIp+vbti3379tWbC2N/BhcuxrTw+++/o0uXLvjwww+Rnp6O0NBQ\nHDlyBGPHjhVjpk+fjurqauzevVul7+nTp3Hx4kXMmjULwOOt6729vXH+/HnExsbi888/R0FBAVav\nXt3gR2qXL1/GhAkTIJfLsWfPHqSmpiIoKAiPHj1Si500aRJGjhyJlJQUvPHGG1i5cqXKDrz37t3D\na6+9hrS0NERERODQoUMYP348/va3v2HTpk1i3NWrVzFo0CCcO3cOMTExSE1Nxcsvv4ypU6ciNTVV\njMvIyMAbb7wBR0dH7Nu3D0uXLsXixYuRm5v7bD9sxhrSKMsFM/aCUSqVdPz4cRIEQWULBm9vb3J3\nd1eJ/ec//0nW1tZUWVlJRERbtmwhQRDo1KlTKnH9+/cnAwODencfSE5OJkEQ6P79+3XGhIWFkSAI\nFB0drdI+b948srCwoLt37xIRUWRkJEmlUsrLy1OLs7GxoerqaiIimjNnDnXo0IGKi4tV4ry9vcnV\n1VV8PHjwYHJ2dlaJOXnypNquBIw9L77iYkwLlZWV+OCDD+Dk5AQzMzMYGxvDw8MDAFSuKGbOnImT\nJ0+KuxVXVVUhKSkJvr6+kEgkAICTJ0/C3t4eAwcOVHmNKVOmNPh90IABAyCRSODn54e9e/fi/UFI\nKAAABJJJREFU5s2bdcb6+vqqPPbz88ODBw/EXb3T0tLg5uYGBwcHVFVVicfIkSNx584dKBQKMW7s\n2LGwtLRUizt79iwePHiA6upq/PDDD5g2bZrKaw4aNAgODg715sTYs+LCxZgW3n//fURERGDmzJk4\ndOgQTp06ha+++goAVLYenzJlCszNzbFjxw4AwDfffINbt25h5syZYszvv/+ODh06qL1Gx44dGxyH\nXC5Heno6ampqMGPGDNjZ2cHd3R3ffvttg+erfXzt2jUAwM2bN5GVlQWJRAJjY2Px8PX1hSAIuHPn\njhiXkJCgFvfuu++Kcbdv34ZSqdSYg6ZcGXseRs09AMb0wa5duzBr1iwsX75cbLt3755anJmZGSZP\nnoydO3ciPDwciYmJkMvlcHd3F2Ps7Oxw4cIFtb43btzQaiyenp7w9PSEUqlEdnY2QkNDMW7cOBQW\nFsLa2lqMu379Ol566SW183fu3BkAYGNjA1tbW2zcuFHj6/Tq1UuM8/DwwHvvvacxzs7ODoaGhpBI\nJBpzuHHjhso4GHtefMXFmBbKyspgZKT6Pi8+Pl5j7MyZM5Gfn49vvvkGKSkpCAgIUHne3d0dRUVF\nOHXqlNhGRNi7d+8z3e8kkUjg5eWFpUuX4uHDhygoKFB5fs+ePSqPd+3aBQsLC/Tr1w8AMHr0aFy4\ncAFdu3bFyy+/rHa0adNGjDt79iz69OmjMc7Y2BiGhoZ45ZVXkJycrPJx5/fff4/CwkKtc2JMG3zF\nxZgWRo8ejYSEBPTr1w9yuRxfffUVTpw4oTH29ddfR6dOnTBnzhyUlZVhxowZKs+/+eabiI6OxpQp\nU7B69WrY2Nhg69atKC0tBRHBwKDu95OxsbE4fvw4xo4diy5duuD27duIiopC586d0bdvX5XYrVu3\noqamBgMHDkR6ejq2bduGiIgIWFhYAAACAwOxe/duDB06FIGBgejVqxcePnyIixcvIjs7W5zuHhkZ\niVdffRUeHh5YuHAh7O3tUVJSgvPnz6OgoADbtm0DAERERGDkyJGYNGkS3n77bdy6dQvh4eGwtbXl\ne7lY42rWqSGM6Ynbt2+Tv78/yWQykslkFBAQQKdOnSJBECghIUEtfunSpSQIAg0ZMkTj+fLz82ns\n2LFkampKHTp0oMWLF1N0dDQJgkD37t2rcxwnTpygiRMnUteuXcnExIT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VV1+lSpUqfPDBBzRp0oTVq1fTokULEhMTDermdZfp0W337t3Dx8eHsLAwPD09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\nns6IESPIzMyUnlQJpCpxPfpeU0xMjMk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OHOD27dsMGzasUj4gW6SElJSURFJSkt6zQICMXhNCVFozZ87EzMyM9u3b8/nn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\nePq8GD8/P3Ts2BHbt2+HXC7H6tWrkZmZ2eAluw8//BBhYWG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Wtm3bEhkZqS+7du0aH3/8Mbt37+batWtYW1vj4uKCj48Pn332Gebmj7VIh0Dl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\nKSgoiIqKiohoYt4XXLhG4esG5Hnz5j1XNyATDc0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gZWFhobjDjIwMhgwZgr29PXZ2dgwePFjxNtxz5syhb9++ODo6olar2bBhg8l6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\nrVkDNDaK/+4BAzSiQauPpbklNHfaP8N8klRKFco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Bgwczf/58GjdujIWFhaljAiAkJISQkJBsuZYQQhjKwcEBBweHnA7DbBjUJ/L3339z/vx5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\nELNNVuri008/pUePHri7uxMfHw+kt8z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mpjJgwAAqVaqkLMJ18uRJk/NlZGQQFhaGs7MzdnZ2+Pn5mX2mQQghRNmhKjk5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\nwnD27NkmP3CQteA+gNgHmxWxFZ0VCWPMBnX54rR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AOHv2LD4+PnTr1o3Y2FiD/TUaDUFBQXqL1F24cIF///vfbNq0iQsXLuDg4ICH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\ncuXMmUkIIcQT4pHmKbe1taVv37588sk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+mK+vL3/++ScAixYtYvv27Tp15s2bR8WKFTW/v/POO9StWxdfX1/WrFmjGc1y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\nx44lR0dHunfvXo/+8+fPJwsLC9q1axfl5+fTnDl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GamhosNnZ2VxaTk4Oq6mpyf7nP//hfZysrCyWYRiZlQBr3b9/n9XW1mZDQ0Nl\n0ocPH87269dP4fGU/DYQonT1XeMAWFZFX83520xMTGQZhmHDwsLYxMREdsiQIWznzp1ZExMTNiAg\ngL137x63b+1KotOmTVN4LIZhWLFYLJN29+5ddv78+aytrS2rp6fHCoVCtm/fvmxgYCBbUVHR5Hqr\nAr7ve3N+P0q9URMXFwc3NzfY2NhwaVZWVvDw8EBsbCzv47D1DO07deoUKioq4O/vL5Pu7++PGzdu\nQCqVNr7ihJB26+LFixg9ejR69OiBBQsWYODAgTh48CA8PDyQn58vs299vTgvbnv27Bnc3d0REREB\nZ2dnLFy4EAEBAejVqxciIiJQXl7eauejLnh1u4WFhdX5SxEIBDAyMsKAAQPg4eFR73HS0tIwfvx4\nuXRHR0fExMTwqUqD0tLSoKOjI7fCqqOjIwAgPT0dlpaWLVIWIUT1nT59Gvv27cO0adO4tJCQEKxd\nuxahoaHYsWNHo4+ZkJCAO3fuYPv27QgMDJTZ9uTJE+jp6TW32mqPd/Dhw83NDT/88AOMjIwUbi8o\nKFA4Uk4kEqGgoIBXGQ3Jz8+vs4za7YSQjuOVV16RCTwA8MknnyA8PBz//e9/mxR8aunq6sql1fX5\nR2Tx6nZLT0+HnZ0dtmzZAqlUiufPnyM3NxebN2+Gvb09UlJScPToUdy6dQvLli1r7To3qL5uOUJI\nx6KoR0ZfXx8uLi4oKCjAnTt3Gn1MsViMHj16YP78+Zg4cSIiIyORlZXVEtXtMHi1fObPn4+ZM2ci\nKCiIS7OwsMBHH32EyspKrFixAmfPnsXt27exc+dO7N69W+FxhEKhwhZOfn4+1zJpLqFQiMLCQoVl\nAKiznNDQUO7fYrEYYrG4RepDCGlb3bp1U5jevXt3ADXdZAYGBo06pqGhIS5duoSQkBCcPHkSx44d\nAwD07t0bq1atwuTJk5tXaRWVlJSEpKSkFjkWr+CTmpqK5cuXK9w2YMAArltu4MCBuH//fp3HcXJy\nws2bN+XS09PTuXsyzeXk5ISysjJkZ2fL3PdJT08HgDrLeTH4EELUx4MHDxSm135WvdhNVllZKbff\nkydPFOa3tLREVFQUqqur8fvvvyM+Ph7bt2/He++9hx49ekAikbRA7VXLy1/MmzN7BK9uN0NDQ5w5\nc0bhtoSEBO6XV1paCsN6Hgrz9vZGamoqcnJyuLTc3FxcvHgR3t7ejal3ncaMGQMtLS3897//lUk/\nePAgXn2nv9nrAAAgAElEQVT1VRpsQEgHc+HCBbm0Z8+e4ffff4dQKISFhQU3b+Xdu3fl9v3tt9/q\nPb5AIMCAAQOwfPlyfPHFFwCA7777rgVqrt54tXxmzpyJ9evXo7i4GBMmTEC3bt3w4MEDHD16FJ9/\n/jl3n+fnn3/Gq6++WudxZs2ahfDwcPj4+GDt2rUAgJUrV8LCwgJz5szh9pNKpbC1tcWqVauwcuVK\nLj05ORkPHz7E33//DQC4fPky92Bq7RLfXbt2xaJFi7B+/XoYGBigf//+OHLkCBITE3Hy5MnGvDeE\nEDWQkZGByMhITJ8+nUvbsGEDCgsLuZFqhoaG6NOnD86fPy/Ta1JcXKzwPvatW7dgYmIi16VX+9mk\naCACeQmfh4EqKyvZFStWsJ06dWIZhuFenTt3ZoODg9mqqiqWZVn2559/ZtPS0uo91p07d1hfX1/W\n0NCQNTAwYMePH89KpVKZfWof+AoLC5NJF4vFXNkCgUDm3y+qqqpi165dy1paWrI6Ojqss7Mz+803\n39RZJ55vAyHtVn3XOFTgYdLWfMjUy8uL1dHRYX19fdlly5axI0eOZBmGYW1tbdn8/Hxu/4iICJZh\nGLZr167svHnz2Dlz5rCWlpasn58fyzAMK5FIuH23bt3KamlpsZ6enuzs2bPZTz75hP3Xv/7Famtr\nsyKRiL19+3aT660K+L7vzfn9NCpnfn4+m5yczB4+fJhNTk6W+cW1ZxR8iLrryMEnLCyMTUpKYt94\n4w22U6dOrImJCTtlyhSZGQ5q7d69m+3duzerra3NWllZsaGhoWxFRYVc8Ll16xa7cOFCdsCAAayJ\niQmrp6fH2tvbs/PmzWNzc3ObXGdVoYzgw2sxOXVHC20RdVffNS4yNESBis6hJjQwQH5RUVtXo8NR\nmcXkAODPP/9EUFAQBg4cCGtra27U2tatW/Hzzz83qXBCSNvLLyoCW9MLonIvCjzqi1fwSUtLQ79+\n/XDw4EH07NkTUqmUm7tIKpVi+/btrVpJQggh6oVX8Pnoo4/g4OCA27dv4/jx4zLb3N3dcenSpVap\nHCGEEPXEa6j1hQsX8PXXX8PAwEDuIazu3btzwwsJIYQQPni1fAQCQZ2zWj969IhmcCWEENIovILP\n66+/jn379incduzYsQaXUiCEEEJexHsZ7eHDh2PkyJF49913AQBnzpzBtm3b8O233+LcuXOtWklC\nCCHqhfdzPt9//z0WLFiA27dvc2lWVlbYtWsXxowZ02oVVAZ6zoeoO7rGSWMo4zmfRj9kmpmZiQcP\nHsDExAR9+vSpd9nZ9oL+MIm6o2ucNIZKBp8XPX78GCYmJk3NrjLoD5OoO7rGSWOozAwHX3zxBTZv\n3sz9fOPGDZiZmaFr164YOHAgDbUmhBDSKLyCT3h4uMwU4YsWLYJQKMS2bdvw5MkTmWUPCCGEkIbw\nGu0mlUrh4OAAACgsLERycjKOHz+Ot956C126dMEnn3zSqpUkhBCiXni1fKqrqyEQ1Oxauypg7RKx\nvXr1qnOZWkII6SjEYjH3OUkaxuudsrOz45aFPXLkCNzd3bkVRO/duweRSMS7wLy8PPj5+cHY2BhG\nRkbw9fVFXl4er7ylpaVYsmQJTE1Noa+vD3d3d5w/f15uv4cPH+KDDz6AjY0N9PX1YWNjg8DAQDx6\n9Ih3PQnpKAyFQjAMo5IvQ6GwWeeWlJQEgUCAsLCwFnq36lZbZ8IPr263JUuWICAgAFFRUSgoKMCx\nY8e4bYmJiejXrx+vwkpKSuDp6Qk9PT1ER0cDAIKDgyGRSHD9+nUuoNVl5syZ+OGHH/DZZ5/BxsYG\n4eHh8PLywqVLl+Ds7AwAYFkW48aNw+3bt7FmzRo4ODggLS0NISEhuHLlCk2CSshLigsLgcTEtq6G\nQsX/38PSXMoICtHR0Xj+/Hmrl6MueAWfd999FxYWFkhNTYWrqyuGDh3KbevWrRu8vb15FRYREYGc\nnBxkZGTAxsYGANCvXz/Y29tj7969CAoKqjPvtWvXcOjQIURGRmLq1KkAgKFDh8LJyQkhISGIjY0F\nULNe+y+//IK9e/di1qxZ3H4CgQDz5s1DZmYm7O3tedWXEKIelDHM3NzcvNXLUCe8OyiHDBmCxYsX\nywQeAFi9ejXefPNNXseIi4uDm5sbF3iAmlkSPDw8uOBRX14tLS1MnDiRS9PQ0MCkSZNw6tQpVFRU\nAACqqqoAAEZGRjL5a3+urq7mVVdCSPsWGhoKT09PAEBYWBgEAgH3kkqlmDZtGgQCAW7fvo3NmzfD\nwcEBurq63JfgjIwMLFmyBC4uLhCJRNDT00Pfvn2xbt06udn9AcX3fEJDQyEQCJCcnIyvv/4a/fv3\nh76+Pnr27ImFCxeitLS09d8IFcWr5dNS0tLSMH78eLl0R0dHxMTENJjXxsZGZsh3bd7y8nJkZWXB\nwcEBjo6OGDVqFNasWQNbW1v06dMH6enpXJDs06dPi54TIUQ1SSQSSKVSREVFQSwWQywWc9uMjY25\nf3/wwQe4fPkyxo4dCx8fH+7L8bfffov9+/dj+PDhGDVqFMrKypCUlISVK1fiypUrcmubAXV374WH\nhyM+Ph5vv/02hg8fjh9//BE7duzAo0ePcPDgwZY98XZCqcGnoKAAQgU3EEUiEQoKCurNm5+fX2fe\n2u21jh8/jgkTJuD111/n0saOHYujR482teqEkHZm2LBhYFmWCz4hISEK97t16xauXbuGnj17yqRP\nnToVixcvhqam7Mfk7Nmz8eWXXyIlJYX3jP4JCQn49ddfuS7/tWvXwsXFBYcPH8bmzZthamrahDNs\n39RuXGB1dTX8/Pzw22+/Ye/evTh37hw+//xzXL58GX5+fjTFCCFExpIlS+QCDwCYmprKBR4AmDt3\nLoCagMLXggULZO416+rqYvLkyaiursavv/7ahFq3f0pt+QiFQoUtnPz8/AaHawuFQty5c0dhXuCf\nFtDJkyfx448/IiEhgXsWaciQIbCxscGoUaNw8uRJhQMkQkNDuX+/3EQnhKiv1157TWF6dXU1vvrq\nK+zfvx9paWkoLi6W+fJ679493mUMHDhQLs3MzAxAzYP77UVSUhKSkpJa5Fh1Bp8BAwbgwIEDcHJy\nwurVqzFz5kzuzWoqJycn3Lx5Uy49PT0djo6ODeY9ceIESktLZe77pKenQ1tbG3Z2dtzPgPwFVdsF\n98cffzQYfAghHUf37t0VpgcGBmLPnj2wsrKCn58fevToAW1tbRQUFGD79u0oKyvjXYahoaFcWm2r\nqnaQVHvw8hfz5jw/VWe3240bN1BcXAyg5oP57t27TS6klre3N1JTU5GTk8Ol5ebm4uLFiw0O1/b2\n9kZFRYXMfZvKykocOXIEXl5e0NLSAlAz4wIAXL58WSb/zz//DADNDqCEEPWiaJDA/fv3sWfPHri4\nuODWrVv48ssvsXbtWoSEhGDSpEltUEv1U2fLx9TUFCdOnOC+Fdy7d09ht1ctCwuLBgubNWsWwsPD\n4ePjg7Vr1wIAVq5cCQsLC8yZM4fbTyqVwtbWFqtWreImLXVxccHEiROxcOFCVFRUwMrKCnv27IFU\nKsWhQ4e4vOPHj0dwcDACAgKwcuVK9OnTB3/88QfCwsJgYWGhcLQdIUQ9aWhoAGh866L2C/KIESOg\no6Mjsy0lJaVlKtfB1Rl85s6di+DgYGzatAkA6v3QZhiG1y9XX18fZ8+eRVBQEAICAsCyLEaMGIFt\n27bJzG7Asiyqq6vlBgdERkZixYoVCA4ORmFhIVxcXBAfHw8XFxdun86dO+PSpUsIDQ3F5s2bce/e\nPfTo0QM+Pj4IDQ1tcBYFQoj6qL0XXN8XZ0UsLS0BABcvXpRJz8jIwPr161umch1cncFn+fLlGDFi\nBG7duoXp06dj2bJlsLa2bnaB5ubmDT7TY2VlpfBhUF1dXWzZsgVbtmypN3/Pnj3xxRdfNKuehJD2\nz8HBAT179sThw4eho6MDMzMzCAQCBAYG1pvP1NQU48ePx/Hjx/H6669DLBbjr7/+wsmTJ+Hl5YVv\nvvlGYT4aTctfvaPdXF1d4erqisjISPj7+3PLKhBCSHsgEAjw7bffYunSpTh06BCKi4vBMAz8/f0b\nnAg0KioKFhYWOH78OMLDw2FnZ4dPP/0UY8eOVRh8FB2vvjI6+kSkzVpGW13QEsNE3dV3jRsKhTWT\ni6ogA2NjFDXwADppeSqzjDYAXL9+Hb6+vujSpQs0NDTQtWtXTJgwATdu3GhSwYQQ1VBUUACWZVXy\nRYFHffFq+Vy+fBnDhg2Dnp4evL290b17d/z99984efIkSktLkZycXOeDWu0BtXyIuqNrnDSGMlo+\nvILPiBEjUFRUhISEBBgYGHDpxcXFGDFiBAwNDfHTTz81qQKqgP4wibqja5w0hsp0u6WmpuKTTz6R\nCTwAYGBggKVLl9ICbYQQQhqFV/BpaERGRx6xQQghpPF4d7s9efIECQkJMnMUPX36FMOHD6duN0JU\nHF3jpDFU5p7PL7/8wg04GDt2LExNTXHv3j388MMPKCkpQVJSElxdXZtUAVVAf5hE3dE1ThpDZYIP\nUDPUevXq1Th37hwKCgogEokwbNgwrFy5Eq+++mqTClcV9IdJ1B1d46QxVCr4qDP6wyTqjq5x0hgq\nM9qNEEIIaUkUfAghhCgdBR9CCCFKR8GHEEKI0ik9+OTl5cHPzw/GxsYwMjKCr68v8vLyeOUtLS3F\nkiVLYGpqCn19fbi7u+P8+fMK97179y5mzJgBU1NT6OrqwsbGBsuXL2/JUyGEENJEDQafsrIyCIVC\nxMXFNbuwkpISeHp6IiMjA9HR0Thw4AAyMzMhkUhQUlLSYP6ZM2dya6l///33MDU1hZeXF65duyaz\nX25uLlxdXZGVlYWdO3fip59+QmhoKLS0tJp9DoSoG6GhkFtbRtVeQkNhW789pJXwGmrdtWtX/Pe/\n/8WoUaOaVdj27dvx0UcfISMjAzY2NgBqAoW9vT02bdqEoKCgOvNeu3YN/fv3R2RkJKZOnQqgZl12\nJycn9OnTB7Gxsdy+o0ePRmFhIVJSUrg13OtDw1CJuqvvGmcYBolIVHKN+JFAQn+bbUBlhlq//fbb\nDS59zUdcXBzc3Ny4wAPULJnt4eEhEzzqyqulpYWJEydyaRoaGpg0aRJOnTqFiooKAEB2djZOnz6N\nwMBAXoGHEKLeYmJiMHz4cAiFQujr68Pe3h5z586V6e6/evUq5s+fDycnJxgZGaFz584YOHAg9uzZ\no/CYAoEAEokEeXl58Pf3R/fu3aGhoYHr168r67TavXqX0a715ptvIjAwEL6+vhg/fjxMTU3lJhP1\n9PRs8DhpaWkYP368XLqjo2ODwS0tLQ02NjbQ1dWVy1teXo6srCw4ODggJSUFAKCrq4uRI0fi/Pnz\n0NfXx7hx47B161aIRKIG60kIUQ8ffvghwsPD0b17d0ycOBEikQi3b99GTEwM3nzzTZibmwMAIiIi\n8P3332PYsGEYN24ciouLcerUKcyfPx8ZGRnYunWr3LEfP34MDw8PdOvWDe+99x6ePXsGfX19ZZ9i\nu8Ur+Pj6+gIAjh8/juPHj8ttZxgGVVVVDR6noKAAQqF8H65IJEJBAysW5ufn15m3djsA/PXXXwCA\nGTNmYMqUKVixYgUyMzOxbNkypKen45dffqFZuAnpAOLi4hAeHo6BAwfi7NmzMkvClJWVydxnXrFi\nBT7//HOZ/FVVVRg7dix27tyJoKAgWFhYyGy/efMmZs2ahb1797buiagpXsHn7NmzrV2PFlNdXQ0A\nkEgk2LlzJwBALBbDyMiI66IbPXp0W1aREKIEtV1m27dvl1uLTEdHBzo6OtzPtS2gF2loaGDWrFk4\ndeoUkpKSMGXKFJnturq62LBhQyvUvGPgFXzEYnGLFCYUChW2cPLz8xvsDhMKhbhz547CvMA/LSAT\nExMAwMiRI2X2q/352rVrCoNPaGgo92+xWNxi50wIaRuXL19Gp06d4O7u3uC+ZWVl2LFjB44cOYL/\n/e9/ePbsmcz2e/fuyeWxsrJS2BujzpKSkpCUlNQix+IVfGo9evQIqampePz4McaOHQsTExM8f/4c\n2travG7uOzk54ebNm3Lp6enpcHR0bDDviRMnUFpaKnPfJz09Hdra2rCzswMA9O3btzGnxHkx+BBC\n2r8nT57A2tqa177/+te/8OOPP8LBwQH+/v7o2rUrNDU1kZOTg6ioKJSVlcnl6d69e0tXWeW9/MU8\nLCysycfiNdqNZVksXrwYZmZm8Pb2xowZMyCVSgHUjIRbt24dr8K8vb2RmpqKnJwcLi03NxcXL16E\nt7d3g3krKipw9OhRLq2yshJHjhyBl5cX9wzP4MGD0aNHD8THx8vkr/359ddf51VXQkj7ZmxsrLDF\n8rLLly/jxx9/xJgxY5CWloY9e/Zg9erVCAkJqbeLnu4dNw+v4LN+/Xrs2rULq1atws8//ywzrnvc\nuHH4/vvveRU2a9YsWFlZwcfHB3FxcYiLi4OPjw8sLCwwZ84cbj+pVApNTU2sWbOGS3NxccHEiROx\ncOFCfPXVV0hISMCkSZMglUploq+GhgY2bNiA77//HvPmzcPp06exe/duzJ8/HxKJhNeoPEJI++fq\n6opnz55xI2Drkp2dDQB466235LY1lJc0Ha/g8+WXX2LlypVYvnw5+vfvL7PN1tYWWVlZvArT19fH\n2bNn0bt3bwQEBMDf3x+2trY4e/aszBBFlmVRXV0t9/BSZGQkpk+fjuDgYIwdOxZ3795FfHw8XFxc\nZPabMmUKoqOjceHCBXh7e2PdunUICAjAyZMnedWTENL+zZs3DwCwYMECFBUVyWwrLS3l7j9bWloC\nAC5cuCCzT2pqKr744gsl1LRj4nXP5+7du3Bzc1O4TVtbW+7mXH3Mzc0bfKbHysqKG7X2Il1dXWzZ\nsgVbtmxpsBx/f3/4+/vzrhchRL2MHTsWgYGB2LlzJ3r37g0fHx+IRCLcuXMHp06dwr59++Dt7Y1B\ngwbhtddew+HDh/H333/jtddew+3bt3Hy5El4e3vjm2++aetTUUu8gk/Pnj1x48YNSCQSuW3Xr1/n\nfVOPEEKUafv27XB3d8fu3btx+PBhVFZWolevXnjnnXcwcOBAADWzFXz33XdYunQpTp8+jZ9//hmO\njo6IioqCqakpBZ9Wwmtut6VLl+Krr77CiRMn4ObmBi0tLVy5cgWdOnXC8OHDMWvWLKxatUoZ9W0V\nNLcbUXf1XeNCQyEKiwuVXCN+jA2MUVBU/wPopOUpY243XsGnpKQEXl5eSElJgaWlJaRSKaytrZGX\nlwd3d3ecOnVK5oGt9oaCD1F3dI2TxlCZ4APUDGs+dOgQ4uPj8eDBA5iYmGDMmDF47733oKnZqMeF\nVA79YRJ1R9c4aQyVCj7qjP4wibqja5w0hjKCT6OaLFlZWfjll19w9+5dmJmZYdCgQbC1tW1SwYQQ\nQjouXsGntLQU8+bNw4EDB2SGQAsEAkydOhW7d+9u1/d8CCGEKBevh0wXL16Mr7/+GqtXr0ZmZiaK\nioqQmZmJsLAwHDx4EIsXL27tehJCCFEjvO75dOnSBUFBQVixYoXctnXr1mHr1q149OhRq1RQGag/\nnKg7usZJY6jMMtplZWUYNGiQwm2urq4KZ3wlhBBC6sIr+AwfPhynT59WuO2nn37C8OHDW7RShBBC\n1FudAw5u377N/fujjz6Cv78/nj59infeeQfdu3fH33//jaNHj+LHH3/EwYMHlVJZQggh6qHOez4C\nAa9GUc1BGAZVVVUtVillo/5wou7oGieN0abP+ezbt69JBySEEEIaQjMcgL4VEvVH1zhpDJUZ7daS\n8vLy4OfnB2NjYxgZGcHX1xd5eXm88paWlmLJkiUwNTWFvr4+3N3dcf78+XrzHD58GAKBAObm5i1R\nfUKIGtq/fz8EAgGioqLauiodBu/pdX788UccO3YMf/75J0pLS7l0lmXBMAzOnTvX4DFKSkrg6ekJ\nPT09REdHAwCCg4MhkUhw/fp1mdVMFZk5cyZ++OEHfPbZZ7CxsUF4eDi8vLxw6dIlODs7y+1fWFiI\nhQsXokePHrTeOiF1EAoNUVhY3NbVUMjY2AAFBUUN79hMDMNwL6IcvLrdNm3ahE8++QRdu3aFnZ0d\ntLS0ZA/CMEhMTGywsO3bt+Ojjz5CRkYGbGxsAAC5ubmwt7fHpk2bEBQUVGfea9euoX///oiMjMTU\nqVMBAFVVVXByckKfPn0QGxsrl2f27NnIy8tDjx49cObMmTpbWNQlQdRdfdd4zd+vkivEk0QCpfxt\nFhUV4e+//0aPHj1gaGjY6uWpOpWZ1drS0hJjxozBrl27oKGh0aSCgJrnhcrLy+W6ysRiMQAgKSmp\nzrxr1qzB2rVr8eTJE+jq6nLpoaGh2LBhA4qLi2WCYkpKCkaNGoUbN25g9erVSEhIoOBDOiwKPqQx\nVOaeT2FhId55551mBR4ASEtLQ9++feXSHR0dkZ6e3mBeGxsbmcBTm7e8vBxZWVlcWkVFBWbPno2P\nP/6Ya2ERQjqWiooK7NixAyNHjoSZmRl0dHTQs2dPvPfeezKfF4Diez65ubkQCASYPn060tLS4OPj\nA5FIBIFAgKKi1u8KVHe8gs+IESOQmpra7MIKCgogFArl0kUiEQoK6l8qNz8/v868tdtrbdy4ERUV\nFVi2bFkza0wIaa8eP36Mjz76CCzLwsfHB4sWLcKgQYNw9OhRDBo0CLm5uXJ5FN3zycrKgru7O548\neYL3338fAQEBjXoOkijGa8BBeHg4fHx8AABeXl4Kg4CqtDCysrLw6aef4sSJE9DW1ubS6UYiIR2L\nSCTi7vm+6Ny5cxg+fDjWrVuHiIiIBo+TkpKC1atXIzg4uLWq2iHxCj6ampoQCoUIDg5W+AvgO8OB\nUChU2MLJz8/nWjD15b1z547CvMA/LaAPP/wQnp6eGDRoEAoLCwEA5eXlqK6uxpMnT6CjoyPXdQfU\n3DuqJRaLuftQhJD2SVtbWy7wAMDQoUPh4OCAM2fO8DpOz549qRfl/yUlJdV7b74xeAWf6dOnIzU1\nFUFBQejTp49Mi6IxnJyccPPmTbn09PR0ODo6Npj3xIkTKC0tlQke6enp0NbWhp2dHQDg1q1bkEql\nCltnQqEQCxcuxH/+8x+5bS8GH0KIerh69So2bdqElJQUPHz4EBUVFdw2vgtg9uvXr9n3u9XFy1/M\nw8LCmnwsXsEnKSkJO3fuxPTp05tcEAB4e3tj8eLFyMnJgbW1NYCam3oXL17Exo0bG8wbGhqKo0eP\nYsqUKQCAyspKHDlyBF5eXtxIt8OHD8ss8cCyLDZs2ICrV68iJiYGZmZmzToHQkj7cOHCBQwfPhya\nmprw8vKCnZ0dOnXqBIZhEBkZqbAnRZHu3bu3ck07Jl7BRyQSKWy+NtasWbO4+0dr164FAKxcuRIW\nFhaYM2cOt59UKoWtrS1WrVqFlStXAgBcXFwwceJELFy4EBUVFbCyssKePXsglUpx6NAhLq+idYci\nIyOho6ODoUOHNvscCCHtw/r161FZWYnk5GQMHjxYZtuLnxkNofvFrYPXkI3AwEDs3r0b1dXVzSpM\nX18fZ8+eRe/evREQEAB/f3/Y2tri7NmzMrMbsCyL6upqufHjkZGRmD59OoKDgzF27FjcvXsX8fHx\ncHFxqbdcenKZkI4nOzsbJiYmcoHn/v37yM7ObqNakVq8Wj5FRUW4fv06HB0dMXLkSIX3U1avXs2r\nQHNzc8TExNS7j5WVlcJAp6uriy1btmDLli28yqoVGRnZqP0JIe2fpaUlMjMz8ccff+CVV14BUDP4\n6IMPPkBlZSV9IW1jvILPunXruH9nZGQo3Idv8CGEEGX44IMP8NNPP8HDwwPvvPMONDU1cebMGVRV\nVcHZ2RnXrl1r6yp2aLy63aqrqxt8EUKIKhk3bhyOHDkCS0tLREdH45tvvoGbmxsuXLgAY2NjmZYP\ndc0rH63nA5rbjai/+q5xmtWavExlJhZVdxR8iLqja5w0Rpsuo/0igUCgsJDaNL4zHBBCCCEAz+AT\nEhIil/b48WOcPn0a5eXlmDZtWkvXixBCiBrjFXzqmnqmsrIS48aNg5GRUUvWiRBCiJpr1rzgmpqa\n+Pe//41t27a1VH0IIYR0AM1elKK8vByPHz9uiboQQgjpIHh1uymagK+8vBw3btzA0qVL8dprr7V4\nxQghhKgvXkOt61u1z9bWFrGxsQ0uiaDKaBgqUXd0jZPGUJmh1vv27ZNL09XVhaWlJVxdXWmtC0II\nIY1CD5mCvhUS9UfXOGkMZbR8mj3ggBBCCGksXsGHZVns378fXl5ecHBwgLW1NaytrWFjY8P9vzHy\n8vLg5+cHY2NjGBkZwdfXF3l5ebzylpaWYsmSJTA1NYW+vj7c3d1x/vx5mX0yMjIQGBgIR0dHGBgY\noGfPnvDx8cH169cbVU9C1IVQKOQmz6QXvRp6KVo2p6Xxuuezdu1arFq1Cn379oWLi4vc2ucMw382\n2JKSEnh6ekJPTw/R0dEAgODgYEgkEly/fl1mUTlFZs6ciR9++AGfffYZbGxsEB4eDi8vL1y6dAnO\nzs4AgNOnTyMxMREzZszAa6+9hsLCQmzatAmDBw/GhQsXMGDAAN71JUQd5Ofnt3UV2h2GYZCY+M/P\nEgkUdjHVfP69mM4AoS/8GCq3FTIH/v+DJ+KfNAkkvMpuz3gFn6+++goffvhhizxMGhERgZycHGRk\nZHAtpn79+sHe3h579+5FUFBQnXmvXbuGQ4cOITIyElOnTgUADB06FE5OTggJCUFsbCwAYPLkyfjg\ngw9k8np6esLKygrbt29HVFRUs8+DEEJI0/Hqdnv8+DG8vb1bpMC4uDi4ubnJdNVZWVnBw8ODCx71\n5dXS0sLEiRO5NA0NDUyaNAmnTp1CRUUFAMDExEQur6GhIezt7fHXX3+1yHkQQghpOl7BZ+jQoS22\n6iPLv30AABaFSURBVF9aWhr69u0rl+7o6Ij09PQG89rY2EBXV1cub3l5ObKysurMm5+fj5s3b8LB\nwaFpFSeEENJieHW7bd++HePHj4dIJMJbb70FkUgkt099D6K+qKCgQOHNLJFIhIKCgnrz5ufn15m3\ndntdAgMDwTAMFi5cyKuehBBCWg+v4NO7d28AwPTp0xVuZxjVXs9n/fr1OHToEPbt29fokXmEkLah\naIVVWtlUfTR5PZ8XNWa0m1AoVNjCyc/PV9iiejmvonnmals8ivJ//vnnWLFiBdatW0frDhHSjhQW\nFisYFKaay32TxmvWej5N4eTkhJs3b8qlp6enNzg/nJOTE06cOIHS0lKZ+z7p6enQ1taGnZ2dzP4H\nDhzA/PnzsXjxYixbtqzeY794jmKxGGKxuOGTIYSQDiQpKQlJSUktcixewacleXt7Y/HixcjJyYG1\ntTUAIDc3FxcvXsTGjRsbzBsaGoqjR49iypQpAGoWtDty5Ai8vLygpaXF7Xv8+HHMmDEDs2bNwqZN\nmxqsV0sGWEIIUUcvfzEPCwtr8rGUHnxmzZqF8PBw+Pj4YO3atQCAlStXwsLCAnPmzOH2k0qlsLW1\nxapVq7By5UoAgIuLCyZOnIiFCxeioqICVlZW2LNnD6RSKQ4dOsTlPXfuHCZPngxnZ2dMnToVqamp\n3DYdHR30799fSWdLCCFEEaUHH319fZw9exZBQUEICAgAy7IYMWIEtm3bJjO7AcuyqK6ulnuqNzIy\nEitWrEBwcDAKCwvh4uKC+Ph4uLi4cPskJiaivLwcv/32Gzw8PGTyW1lZ4fbt2617koQQQupFs1qD\nZvwlRBW9PL0NoNxpZmh6nYY157OTZrUmhBCidBR8CCGEKB0FH0IIIUpHwYcQQojSUfAhhBCidBR8\nCCGEKB0FH0IIIUpHwYcQQojSUfAhhBCidBR8CCGEKB0FH9IqDA1FYBiGexka1r9WEyGkY1H6xKKk\nYyguLsCLM1oVF/NfcJAQov6o5UMIIUTpKPgQ5RBAthvO2LCta0QIaUPU7dbOFBcX4/nz59zPmpqa\nEInawf2UashMM18cWtxWNSFEjtBQiMLiwrauhlIYCoUoLvznXA2MjVFUUKD0eii95ZOXlwc/Pz8Y\nGxvDyMgIvr6+yMvL45W3tLQUS5YsgampKfT19eHu7o7z58/L7ceyLNavXw8rKyvo6enBxcUF3377\nbUufSpuwtjbHK69YwsGh5tWtW1fcunWrraulFEKhoUzrSSjsGK2njnreylRYXIjEl/5TV8WFhTXr\nCf3/68VApExKbfmUlJTA09MTenp6iI6OBgAEBwdDIpHg+vXrMiuZKjJz5kz88MMP+Oyzz2BjY4Pw\n8HB4eXnh0qVLcHZ25vYLDg7Gli1b8Omnn2LgwIE4dOgQJkyYgO+++w5jxoxp1XNsbSUlJfjmmwro\n6dX8PG+eoUxLSJ0VFha/tMBWx2g9ddTzJupNqcEnIiICOTk5yMjIgI2NDQCgX79+sLe3x969exEU\nFFRn3mvXruHQoUOIjIzE1KlTAQBDhw6Fk5MTQkJCEBsbCwB48OABPvvsMyxfvhyLFi0CAAwbNgxZ\nWVn45JNP2n3wIS1DZGiIguJ/PsSFBgbILypqwxoR0rEoNfjExcXBzc2NCzwAYGVlBQ8PD8TGxtYb\nfOLi4qClpYWJEydyaRoaGpg0aRI2bNiAiooKaGlp4dSpU6ioqIC/v79Mfn9/f8yYMQNSqRSWlpYt\nf3JNcOvWLUTs2iWTNnjIELwzaVIb1ajjKCgull3auJhaE6T9MTQU/f9jDTUMDIQoKspvwxrxp9Tg\nk5aWhvHjx8ulOzo6IiYmpsG8NjY20NXVlctbXl6OrKwsODg4IC0tDTo6OrC1tZXbDwDS09NVJvic\nPXsWP+/dC9/KSgDANQBLvvkGl3//ndvH1toac+fMqfc4V65cwYABA1qzqq0mKSkJYrG4ravRZFT/\nttXe6/9/7d17UFTl/wfw91l2QRZFlt0Eb18vm4AhqKMlZIZ4SVK8lTnOoEg0E6aW2ZhGYoCFpqFR\noqBJQJqieG9G+YkKmEpGXlPHu4KW5AXxAijb8vn9QXt02UWu7h7085o5f/Dsc/a8z3I4n132Oc/B\n0aNAjx71Xr0pX09n0eJz+/ZtqFQqk3ZnZ2fcrmG0RVFRUbXrGh6vSz9L+P77ROzY8eif9YIAREZ+\ngj59+ohtPeRyfPJf8fkGwGq9HrG3blU+ePcuHL5PwG9ZuWJ/vV5vsp1Dhw49nR2wgKdx8rDku8Gm\nfvLj/FbWwOLTGGxgA0F4VLScWjjh9t2nP/rtmRxqTUQ1d7KAn3/ejN9/7wWgcjCEXJ6MgICDRsWn\nKkGtBoKCKn84fRr69dvwwroXxMf1NhVPM/IzwZrvBqsWPsCy/wqpa+Gd//XXiI6OftTfSsNuG6qm\n/X5ev+Orut/m6KE3Gt3nf8//accCYOHio1KpzH7CKSoqqvFaFZVKhYKCArPrAo8+2ahUKhSbGTpY\ntZ8lKBQyKJW7IZf/CQAoKfsd06b9H6ZNmyb2aSuXo8Cxcujs+YcPQQUFcJwzBwCgv3cPD6DDb46/\nPXrSEuDLL1vAxqbyhHr16gOjdy3MuqoWvsq2uv1+GnLNSU2F1+zJ6LGhdKX+g6zyLrihTPa7RDD5\nu3guvuP772Lux1V9Ky6ZswVZ0IABA+i1114zaffz86P+/fs/cd3o6GiytbWlsrIyo/bIyEiys7Oj\n8vJyIiJKTU0lQRDo/PnzRv2Sk5NJEAS6fPmyyXNrtVpC5e+IF1544YWXWi5arbauZUBk0eITFxdH\ncrmcLl68KLZdunSJFAoFLV68+InrHjlyhARBoNTUVLFNp9ORh4cHjRgxQmy7fv062draUnR0tNH6\nAwcOJG9v70baE8YYYw1hExUVFQUL8fb2RlpaGjZs2IC2bdvizJkzeP/996FUKpGUlASFQgEAyM/P\nh0ajgSAI8PPzAwC4urri9OnTWLp0KTQaDW7fvo3PPvsMf/zxB1avXg1XV1cAgIODA0pLSxEbGwsH\nBwc8fPgQCxYswMaNG5GUlIQuXbpYancZY4xVw6Lf+SiVSuzZswfTp0/HhAkTQEQYNGgQ4uLijGY3\nICJUVFSYDBxITk7G7NmzERERgeLiYvTo0QMZGRnoUWW0SExMDJo3b47vvvsOhYWF8PDwQHp6OoYO\nHWqR/WSMMVYDK3/ysoozZ87Q1KlTqWvXrtS8eXNq3bo1jRgxgo4dO2a2/4oVK8jd3Z3s7OzI3d2d\nEhMTLZzY1KJFiygwMJBcXV1JEASKioqqtq/U8hcUFNDbb79NLVu2JEdHR3rrrbeooKDAqpmqc+XK\nFZo6dSr5+PiQvb09CYJA+fn5Jv2KiorovffeI41GQw4ODjRo0CD6888/rZD4kfT0dBo5ciS1b9+e\n7O3tyd3dncLDw+nevXtG/aSYnYgoIyOD/P39ydXVlezs7Khdu3Y0duxYOnXqlFE/qeY3Z8iQISQI\nAkVERBi1S3EfsrKySBAEk0WlUhn1q2/257L4LFmyhDw9Pembb76hrKws2rx5M/n6+pK9vT0dOnTI\nqO+KFStIJpNRREQEZWdnU0REBMlkMkpISLBS+kpdu3YlHx8f+uCDD0gQBJPvuAyklr+kpIRefPFF\n8vLyoq1bt9LWrVvJy8uLtFotlZSUWCXTk2RlZZGLiwsNGzZMPHFULT4VFRXUt29fat++PaWlpVFG\nRgb5+fmRRqOhq1evWik5kY+PD40ZM4Z+/vlnysnJobi4OHJyciIfHx+qqKiQdHYiorVr19LMmTNp\n48aNtHfvXlq1ahV5enqSo6Oj+GZFyvmrWrNmDbVu3ZoEQaA5c+aI7VLdB0PxiY+Pp4MHD4rL4+fI\nhmR/LovPzZs3Tdru3LlDKpWKgoODxTadTkcvvPAChYSEGPUNDQ0ljUZDOp3uqWetyb///ltt8ZFi\n/ri4OLKxsaELFy6IbZcuXSK5XF7joBNrMJykiYh++OEHs8Vny5YtJAgCZWdni2137twhZ2dn+uij\njyyWtSpzx/lPP/1EgiDQnj17iEi62atz5swZEgSBvv32WyJqOvmLiorI1dWV0tLSTIqPVPfBUHx2\n795dbZ+GZH8ubyanVqtN2hwdHdGlSxf8/fffYltubi5u3rxpMk/chAkTcOvWLezbt++pZ60JPeGC\nWinmr2l+P6mpzTVU27ZtQ9u2bcXBMUDl8TR8+HCr7pO547x3794AIB7nUs1eHcN1ejJZ5amrqeSf\nNWsWvLy8jOamNJD6PjzpHNOQ7M9l8TGnqKgIJ06cQNeuXcW2kydPAgC6detm1NcwT5zU76Mjxfwn\nT540yQNUZjp16pTF8zSGJ+1TQUEBSktLrZDKvJycHAAQj/OmkF2v16O8vBznzp1DWFgYXFxcMO6/\nyXebQv59+/Zh1apVWFplEmEDqe9DUFAQ5HI5NBoNgoKCjO6/1pDsXHz+8+GHH0IQBHz88cdim2FW\nhKpzxVljnrj6kGL+hszvJ1U1zScolf3666+/8MUXX2Dw4MHiRLRNIXufPn3QrFkzuLu74/Dhw9i1\naxdatWoFQPr5y8vLERYWhk8//bTayzykug9OTk6YMWMGkpKSkJWVhTlz5mDXrl3w9fXFjRs3ADQs\n+zNRfHbt2gWZTFbjMmDAALPrz58/H2vXrkV8fLzRv4MspaH5mXU1hemN7t+/j5EjR8LW1hbJycli\ne1PIvnr1ahw8eBBr1qyBWq1GQEAA8vPzAUg//8KFC/Hw4UPMnj272j5S3YcePXpg4cKFGDZsGPr1\n64dp06YhIyMD//zzD5YsWdLg538mJhbt27cvTp8+XWM/c3dKTUxMxOzZsxETE4OQkBCjxwwV/fbt\n23BxcRHbG3ueuIbkfxJL5a9rpvrO7ydVKpXK7KfI6j55WlpZWRmGDx+Oy5cvIycnB23atBEfk3p2\nAPDw8AAAvPzyy3jzzTfRsWNHfP3110hISICTk5Nk8xcUFCAmJgZJSUkoKyszuuPwgwcPcOfOHTRv\n3rxJ/A4MevbsCTc3N+Tl5QFo2PHzTBQfe3t7uLm51Xm9VatWYcqUKZgxYwbCw8NNHvf09AQAnDhx\nwujkbfhuwvDdSUPVN39NLJW/rplOnDhh0n7q1Cmr5GkMnp6e2Llzp0m74d5RdX3T0Jh0Oh3GjBmD\nw4cPIzMzUzwmDKSc3ZyWLVtCq9XiwoULACrzZ2ZmmvSTQv6LFy/i4cOHJgN+ACA2NhaxsbE4cuRI\nk/sdPD4AoUGvf+MMymt6Nm3aRHK5nMLCwqrtYxiq/O677xq1Gy6oksJQa51OV+NQaynlb8j8ftZW\n01DrnJwcsU0KQ2X1ej298847pFQqxaHVVUk1e3UKCwvJwcGBJk2aRETSzl9cXEw5OTlGS3Z2NgmC\nQMHBwZSTk0P379+X9D5UlZeXRzY2NhQZGUlEDXv9n8vik5OTQ3Z2dtSrVy86cOAA5ebmisvhw4eN\n+iYmJooXaWZlZdGcOXNIJpPRsmXLrJS+Ul5eHqWnp9O6detIEAQaO3YspaenU3p6OpWWlor9pJbf\n3EWm3t7ekr3IlIjE13XSpEkkCAIlJCRQenq6+AdXUVFBr776qsmFdmq12qoXCRryRkREGB3jubm5\nYi6pZiciGjVqFH355Ze0ZcsW2rNnDyUmJpK7uzupVCo6d+6c5PNXx9xFplLch6CgIIqMjKTNmzfT\n7t27KTY2ltRqNXXo0IFu3brV4OzPZfGJiooiQRBIJpOZTB3RqVMnk/7Lly8nNzc3srOzIzc3N6vP\nbkBEFBISImZ+fD9kMpnJO3Op5TdMr+Po6EgtWrSg0aNHm52yRioePz4ef639/f3FPkVFRRQaGkrO\nzs6kVCpp0KBBdPz4cSumJurYsaPZY7zqJ2UpZiciWrBgAfXq1YucnJxIqVSSu7s7TZo0yeRYkWr+\n6lQtPkTS3If58+eTt7c3tWzZkhQKBf3vf/+jsLAwKiwsNOpX3+wCkURu+8kYY+y58UwMtWaMMda0\ncPFhjDFmcVx8GGOMWRwXH8YYYxbHxYcxxpjFcfFhjDFmcVx8GGOMWRwXH8YawdGjRxEVFfVUpr/P\nzs5GdHT0E2/q9TiZTIbo6Og6byclJcVoxmvGniYuPow1gqNHj2Lu3LmSKD5A/abpT0lJwY8//ljn\n9RirDy4+jDWixpwwRKfTGT0fT0bCniVcfBirhbNnz2L06NFwcXGBvb09OnTogLFjx0Kv1yMlJQWh\noaEAgC5duog3/ysoKAAAxMfHw9fXF2q1GiqVCr6+vti+fbvR81++fBkymQwJCQmYOXMm2rRpg2bN\nmmH69OmYO3cuAEChUIjPXRfnz5/HhAkT0LlzZyiVSmi1WkyePBnFxcVin/79+2Pv3r3Yv38/37yQ\nWcQzcT8fxp62YcOGQa1WIzExERqNBlevXsWOHTtQUVGBwMBARERE4KuvvsKGDRvQrl07AICrqyuA\nysISGhoKrVYLvV6Pbdu2ITAwEDt27MCQIUOMthMTE4NXXnkFK1euhF6vR8+ePVFSUoKkpCTs378f\nNjY2dc5+7do1tGvXDosXL4ZarcbFixcxb948DB06FAcOHAAAJCQkYPz48aioqMDy5csBAI6Ojg15\nyRh7skafCpWxZ8yNGzdIEAT65Zdfqu2TnJxMgiDQhQsXnvhcer2edDodvfHGGzRy5Eix/dKlSyQI\nAvXq1ctkncjISBIEgfR6fa3yVnd/JwOdTke//vorCYJAR44cEdv9/PyoX79+tdoGYw3F/3ZjrAYa\njQadO3fGrFmzsHLlSpw7d65O6x86dAiBgYFwdXWFQqGAra0tMjMzcfbsWZO+o0aNaqzYovLycsyb\nNw8eHh5QKpWwtbXF66+/DgBmMzBmCVx8GKuFzMxM9O7dG+Hh4XB3d4dWq0ViYmKN6125cgUDBw5E\ncXEx4uPjkZubi7y8PAQEBODBgwcm/Vu3bt3o2cPDwxEdHY3g4GBs374deXl52LRpEwCYzcCYJfB3\nPozVQqdOnZCamgoAOHbsGOLj4zF58mR07NgRAQEB1a6XkZGBu3fvYv369WjTpo3YXlJSYrZ/fYZI\n1yQtLQ0TJ07E559/LrbdvXu30bfDWF3wJx/G6qh79+5YtGgRAODkyZMAADs7OwBAaWmpUV/Dz3L5\no/d5Z8+exf79+2u9veqeu7bKysqMtg/A7MWkdnZ29d4GY3XFn3wYq8Hx48cxbdo0jBs3ThyxlpKS\nAoVCIQ5HfumllwAAS5cuRXBwMBQKBbp3747BgwdDLpcjODg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OncOePXtw584dLFy4sNp9FRUVwcPDA+np6di5cye+//573L17F+7u7igqKqox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\nHb2ALZt/crkc7e3tmn+6YmJi0NXVhefPn2vqDA0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aYMuWLayWlhabnZ3NpeXk5LDa2trsf/7zH97HycrKYhmGkVsJsNa9e/dYXV1d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\nCSoVEBxc/0NhIerSd6PH1z3Ex7Vm2nsZ+b5gyne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SkSNHMnPmTPr168e1a9c4cOCAzkBlhw4duHnzJlOmTMHHx4d3332XzMxM9u3b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\nLlruTgghRF+0eHEGIYQQokuCEhdjDFu3bkVgYCA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/z7Zt27h06RIWFhbUrVsXX19fPvroI0xNC7VpQJUjD2qEEJXagQMHeOmll6hd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\nYII=\n", 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79u1cvHgRc3NzGjdujI+PDx9++CGmpqVaNKDWkRs1okJoNFa65YJVKhUajVVV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\nFy+m0NDQCXonjDHGxsMlOzs7GzYSGhqKffv2oay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WrBkmTpyIJUuWSEykBwD9+/dHWloaTp8+jQMHDiA3NxempqaYNGkSFi5cCHNz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\nIdi4caOyQlY58lw3VbKzIVGOmTNnIjE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GDRtiwoQJWLp0qcREegDQu3dvpKSkIDY2FocPH0ZOTg6srKwwceJELFq0CDY2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\nrJDVjjz3TbXsbEiUY8aMGYiLi8Pvv/8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flqyXk5Mjt532xo0bcq9w/vnnHwDyG9yJfBV6OmvlypVYt26dpLxWrVqYO3eu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\nyBGp8jlz5jBtbW2Wn5+vkphVRSwWS/4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ItH0DfrjYYcHHalcAAAAASUVORK5CYII=\n", + "text": [ + "" + ] + } + ], + "prompt_number": 60 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The air modes are such outliers that we are unable to see the variation in the other modes. Let's strip out the outliers and focus on lower speed trips." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "speedNormalEntries = strippedFeatureMatrix[:,4] < 50\n", + "plotFeatureVector(strippedFeatureMatrix[speedNormalEntries], strippedResultVector[speedNormalEntries], 4, modeList)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "display_data", + "png": 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WVoZFixYhISEBgYGB+OWXX5CTk4Pa2lq9SUmvX7+OTZs24cqVK7C2toa9vX2L9bbvVEwU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\nEwURERn0/9HXfTrnxs0VAAAAAElFTkSuQmCC\n", + "text": [ + "" + ] + } + ], + "prompt_number": 48 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Using the graphs above, we can estimate the separability of our input. Clearly, there is some separability - the car and train trips that are at 20-30+ are clearly separable from the walk/bike trips that are at lower speeds. But are they separable from each other? And at least eyeballing the data, it looks like at least 75% of car trips are actually not that fast - the mean EV is < 10mph. Even with max speed, at least 25% of car trips appear to have a max speed ~ 10 mph. Max accel doesn't seem to have as much predictive power as one might hope - most max accel clusters at less than 5. It would be nice to visualize the clusters in this data, but I'm just going to start trying decision trees and SVMs on this data now." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We used to strip out outliers here, but the outliers actually correspond to plane trips, so we want to retain them. The rest of the code assumes that we stripped outliers to get \"cleaned\" trips, so we just reassign the values here instead of changing all the code. We can restore outlier detection at that point." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "cleanedFeatureMatrix = strippedFeatureMatrix\n", + "cleanedResultVector = strippedResultVector" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 67 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Feature Indices" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "genericFeatureIndices = list(xrange(0,10))\n", + "AdvancedFeatureIndices = list(xrange(10,13))\n", + "LocationFeatureIndices = list(xrange(13,17))\n", + "TimeFeatureIndices = list(xrange(17,19))\n", + "BusTrainFeatureIndices = list(xrange(19,22))\n", + "print genericFeatureIndices\n", + "print AdvancedFeatureIndices\n", + "print LocationFeatureIndices\n", + "print TimeFeatureIndices\n", + "print BusTrainFeatureIndices" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\n", + "[10, 11, 12]\n", + "[13, 14, 15, 16]\n", + "[17, 18]\n", + "[19, 20, 21]\n" + ] + } + ], + "prompt_number": 68 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Generic model, generic features" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "genericCleanedFM = cleanedFeatureMatrix[:,genericFeatureIndices]\n", + "print genericCleanedFM.shape" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "(7307, 10)\n" + ] + } + ], + "prompt_number": 71 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "from sklearn import cross_validation\n", + "from sklearn import svm" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 72 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "svmClf = svm.LinearSVC()\n", + "svmScores = cross_validation.cross_val_score(svmClf, genericCleanedFM, cleanedResultVector, cv=5)" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 73 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "print svmScores\n", + "print svmScores.mean()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "[ 0.70656635 0.41450068 0.53114305 0.69609856 0.70773443]\n", + "0.611208615054\n" + ] + } + ], + "prompt_number": 74 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Using svm.SVC() takes significantly longer (hours instead of seconds) but generates higher accuracy. The accuracy is still lower than the random forest, though." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "from sklearn import ensemble" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 75 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "forestScores = cross_validation.cross_val_score(forestClf, genericCleanedFM, cleanedResultVector, cv=5)" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 76 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "print forestScores\n", + "print forestScores.mean()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "[ 0.84062927 0.86525308 0.85147159 0.85352498 0.84804928]\n", + "0.851785642388\n" + ] + } + ], + "prompt_number": 58 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "These results look pretty good, and pretty much parallel what the Zheng paper got, even with just the basic features. We get 82% average accuracy for a linear SVM and 86% average accuracy for a random forest. But the 82% and 86% values are for cross validation, where we have a known value that we can validate against.\n", + "\n", + "But what we really want to do is to decide, while looking at a section that we have no ground truth on, whether we want the user to classify it or not. And then we want to see, for the high confidence predictions that we will not prompt the user for, how accurate our classification really is.\n", + "\n", + "In order to do this, we get the probabilities for each prediction in addition to the prediction itself. We can then test the accuracy of the high confidence predictions and compare it to the accuracy of all predictions.\n", + "\n", + "To recap, we now return three metrics:\n", + "\n", + "- The number of entries that would be autoclassified given a particular target confidence interval\n", + "- The accuracy of the entries that would be autoclassified\n", + "- The accuracy of all entries, including ones that had low confidence" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "# Generate folds of indices\n", + "def generateFoldArrays(nIndices, nFolds):\n", + " currPermutation = np.random.permutation(nIndices)\n", + " currPermutationParts = np.array_split(currPermutation, nFolds)\n", + " \n", + " foldArrays = []\n", + " for i in range(0, nFolds):\n", + " testIndices = currPermutationParts[i]\n", + " trainIndicesParts = [currPermutationPart for (j, currPermutationPart) in enumerate(currPermutationParts) if j != i]\n", + " trainIndices = np.concatenate(trainIndicesParts)\n", + " foldArrays.append((trainIndices, testIndices))\n", + " return foldArrays\n", + "\n", + "def kFoldValidationWithProb(algo, X, y, nFolds, prob_threshold):\n", + " foldArrays = generateFoldArrays(len(y), nFolds)\n", + " \n", + " scores = []\n", + " highConfidenceScores = []\n", + " percentAutoClassified = []\n", + " percentAutoClassifiedByMode = []\n", + " for (trainIndices, testIndices) in foldArrays:\n", + " # print testIndices[0]\n", + " model = algo.fit(X[trainIndices], y[trainIndices])\n", + " testX = X[testIndices]\n", + " testy = y[testIndices]\n", + " \n", + " predictedY = model.predict(testX)\n", + " if hasattr(algo, \"decision_function\"):\n", + " predictedYProb = algo.decision_function(testX)\n", + " else:\n", + " predictedYProb = algo.predict_proba(testX)\n", + " \n", + " # print (\"predictedY.shape = %s, predictedYProb.shape = %s\" %\n", + " # (str(predictedY.shape), str(predictedYProb.shape)))\n", + " \n", + " # As we can see below, we take the max confidence along the first axis\n", + " highConfidencePredictions = np.max(predictedYProb, 1) > prob_threshold\n", + " print \"Found %s high confidence predictions out of %s\" % (np.count_nonzero(highConfidencePredictions),\n", + " len(testIndices))\n", + " \n", + " cmc = lambda m:np.count_nonzero(testy[highConfidencePredictions] == m)\n", + " \n", + " # Let us see how many of each mode were autoclassified\n", + " # print(\"Autoclassifications split by confirmed modes: walk: %s, bike: %s, bus: %s, train: %s, car: %s\" %\n", + " # (cmc(1), cmc(3), cmc(5), cmc(6), cmc(7)))\n", + " \n", + " pcmc = lambda m: float(np.count_nonzero(testy[highConfidencePredictions] == m))/np.count_nonzero(testy == m) if ((np.count_nonzero(testy == m) != 0)) else 0 \n", + " # Let us see what percentage of each mode was autoclassified\n", + " # print(\"For threshold %s, autoclassifications split by confirmed mode percents: walk: %s, bike: %s, bus: %s, train: %s, car: %s\" %\n", + " # (prob_threshold, pcmc(1), pcmc(3), pcmc(5), pcmc(6), pcmc(7)))\n", + " \n", + " percentAutoClassified.append(float(np.count_nonzero(highConfidencePredictions))/len(testIndices))\n", + " percentAutoClassifiedByMode.append([pcmc(1), pcmc(3), pcmc(5), pcmc(6), pcmc(7), pcmc(9)])\n", + " \n", + " # so now we are going to generate two scores.\n", + " # the first is the score on only the high confidence predictions\n", + " highConfidenceScore = model.score(testX[highConfidencePredictions], testy[highConfidencePredictions])\n", + " highConfidenceScores.append(highConfidenceScore)\n", + " \n", + " score = model.score(X[testIndices], y[testIndices])\n", + " scores.append(score)\n", + " # print scores\n", + " \n", + " print(\"for prob %s, percentage auto classified %s\" % (prob_threshold, np.array(percentAutoClassified).mean()))\n", + " print(\"for prob %s, scoring only on high confidence predictions %s\" % (prob_threshold, np.array(highConfidenceScores).mean()))\n", + " print(\"for prob %s, scoring on all predictions %s\" % (prob_threshold, np.array(scores).mean()))\n", + "\n", + " return (np.array(percentAutoClassified), np.array(percentAutoClassifiedByMode), np.array(highConfidenceScores), np.array(scores))" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 193 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "def exploreKFoldValidationSpace(algo, X, y, nFolds):\n", + " (pac0, pacm0, hcs0, s0) = kFoldValidationWithProb(algo, X, y, nFolds, 0.90) \n", + " (pac5, pacm5, hcs5, s5) = kFoldValidationWithProb(algo, X, y, nFolds, 0.95)\n", + " (pac9, pacm9, hcs9, s9) = kFoldValidationWithProb(algo, X, y, nFolds, 0.99)\n", + " \n", + " probs = [0.90, 0.95, 0.99]\n", + " pacs = [pac0.mean(), pac5.mean(), pac9.mean()]\n", + " hcs = [hcs0.mean(), hcs5.mean(), hcs9.mean()]\n", + " ss = [s0.mean(), s5.mean(), s9.mean()]\n", + " \n", + " pacmWalk = [pacm0[:,0].mean(), pacm5[:,0].mean(), pacm9[:,0].mean()]\n", + " pacmBike = [pacm0[:,1].mean(), pacm5[:,1].mean(), pacm9[:,1].mean()]\n", + " pacmBus = [pacm0[:,2].mean(), pacm5[:,2].mean(), pacm9[:,2].mean()]\n", + " pacmTrain = [pacm0[:,3].mean(), pacm5[:,3].mean(), pacm9[:,3].mean()]\n", + " pacmCar = [pacm0[:,4].mean(), pacm5[:,4].mean(), pacm9[:,4].mean()]\n", + " pacmAir = [pacm0[:5].mean(), pacm5[:,5].mean(), pacm9[:,4].mean()]\n", + " \n", + " fig, axes = plt.subplots(1, 1, figsize=(15, 10))\n", + " print pacs\n", + " axes.set_yticks(np.arange(0,1,0.1))\n", + " axes.plot(probs, pacs, label=\"percentage auto classified\")\n", + " \n", + " print pacmWalk\n", + " axes.plot(probs, pacmWalk, linewidth = 5, label=\"percent walk auto classified\")\n", + " print pacmBike\n", + " axes.plot(probs, pacmBike, label=\"percent bike auto classified\")\n", + " print pacmBus\n", + " axes.plot(probs, pacmBus, linewidth=5, label=\"percent bus auto classified\")\n", + " print pacmTrain\n", + " axes.plot(probs, pacmTrain, label=\"percent train auto classified\")\n", + " print pacmCar\n", + " axes.plot(probs, pacmCar, linewidth=5, label=\"percent car auto classified\")\n", + " print pacmAir\n", + " axes.plot(probs, pacmAir, linewidth=5, label = \"percent air auto classified\")\n", + " \n", + " print hcs\n", + " axes.plot(probs, hcs, label=\"accuracy of high confidence samples\")\n", + " print ss\n", + " axes.plot(probs, ss, linewidth = 5, label=\"accuracy of all samples\")\n", + " plt.legend(loc='best')" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 191 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, genericCleanedFM, cleanedResultVector, 5)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Found 13 high confidence predictions out of 1462\n", + "Found 6 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 11 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 7 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 9 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.9, percentage auto classified 0.00629527776919\n", + "for prob 0.9, scoring only on high confidence predictions 0.54622044622\n", + "for prob 0.9, scoring on all predictions 0.408376006914\n", + "Found 15 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 7 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 7 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 8 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 5 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.00574742671052\n", + "for prob 0.95, scoring only on high confidence predictions 0.581904761905\n", + "for prob 0.95, scoring on all predictions 0.40016039461\n", + "Found 6 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 10 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 8 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 4 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 11 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.99, percentage auto classified 0.00533731089494\n", + "for prob 0.99, scoring only on high confidence predictions 0.557424242424\n", + "for prob 0.99, scoring on all predictions 0.406049676449\n", + "[0.0062952777691946838, 0.0057474267105247136, 0.0053373108949419986]\n", + "[0.0073529291840749491, 0.0063897833377123004, 0.0067274306186164397]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[0.0018626860535145833, 0.0055846539529053624, 0.0065610664050082066]\n", + "[0.0074146025578759921, 0.0078679311556023885, 0.0077443131487021782]\n", + "[0.0060035842293906811, 0.0, 0.0027397260273972603]\n", + "[0.0066977060961155967, 0.0054922684710748196, 0.0026864006359301924]\n", + "[0.0048885846868286335, 0.0, 0.0026864006359301924]\n", + "[0.54622044622044619, 0.58190476190476192, 0.55742424242424238]\n", + "[0.4083760069139159, 0.40016039461006692, 0.40604967644858431]\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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qNeaTTz7R5MmTnbouAtebsn4nquP3gxY4AAAAXLcuXryoHTt2KC8vT8nJyXru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+ "text": [ + "" + ] + } + ], + "prompt_number": 261 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The results of these three metrics for confidence intervals of 90%, 95% and 99% are shown above, and they are all largely similar. The accuracy of the high confidence predictions is, as expected, really high at 97 - 98%. However, we were only able to auto-classify ~ 50% of the sections. Now, let's retry using the linear SVM above." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "svmClf = svm.LinearSVC()\n", + "exploreKFoldValidationSpace(svmClf, genericCleanedFM, cleanedResultVector, 5)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Found 902 high confidence predictions out of 1462\n", + "Found 1263 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 509 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 1280 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 271 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.9, percentage auto classified 0.578168261718\n", + "for prob 0.9, scoring only on high confidence predictions 0.306717629676\n", + "for prob 0.9, scoring on all predictions 0.358955459362\n", + "Found 190 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 1113 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 429 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 1219 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 1349 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.58851591446\n", + "for prob 0.95, scoring only on high confidence predictions 0.221808535634\n", + "for prob 0.95, scoring on all predictions 0.250286285184\n", + "Found 281 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 1381 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 981 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 1447 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 1097 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.99, percentage auto classified 0.709905982354\n", + "for prob 0.99, scoring only on high confidence predictions 0.287679597199\n", + "for prob 0.99, scoring on all predictions 0.314912578851\n", + "[0.5781682617175613, 0.58851591445995333, 0.70990598235378388]\n", + "[0.58641379672519545, 0.59407927924812021, 0.71891425750745785]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[0.56757552472793149, 0.57882483708430521, 0.68262570293175417]\n", + "[0.58155476228208802, 0.60267122931731942, 0.72200895638833429]\n", + "[0.59344852201019005, 0.58706918127792151, 0.69118491002513527]\n", + "[0.5689482984109101, 0.58353708012778494, 0.71075421898848479]\n", + "[0.56870443640700497, 0.61666666666666659, 0.71075421898848479]\n", + "[0.30671762967592492, 0.22180853563407163, 0.28767959719872072]\n", + "[0.35895545936248524, 0.25028628518405116, 0.3149125788513199]\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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FkofDsRGrdQVGY8zgH3lBtN9ox71NC21tl9qw5FmwFlqxFFiISo3q93MS4IQQQgghhHgF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+ "text": [ + "" + ] + } + ], + "prompt_number": 262 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We see that the SVM is able to classify more trips than the decision tree, but at the cost of unacceptably lower performance on the high confidence predictions. It is hard to understand the results with line plots, let's switch to bar graphs instead." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "def exploreKFoldValidationSpaceBarGraph(algo, X, y, nFolds):\n", + " (pac0, pacm0, hcs0, s0) = kFoldValidationWithProb(algo, X, y, nFolds, 0.90) \n", + " (pac5, pacm5, hcs5, s5) = kFoldValidationWithProb(algo, X, y, nFolds, 0.95)\n", + " (pac9, pacm9, hcs9, s9) = kFoldValidationWithProb(algo, X, y, nFolds, 0.99)\n", + " \n", + " probs = [0.90, 0.95, 0.99]\n", + " pacs = [pac0.mean() * 100, pac5.mean() * 100, pac9.mean() * 100]\n", + " hcs = [hcs0.mean() * 100, hcs5.mean() * 100, hcs9.mean() * 100]\n", + " ss = [s0.mean() * 100, s5.mean() * 100, s9.mean() * 100]\n", + " \n", + " mpl.rcParams['font.size'] = 16\n", + " fig, axes = displayHelpers.showCategoryChart([\"90%\", \"95%\", \"99%\"], [pacs, hcs, ss],\n", + " [\"% high confidence\", \"high confidence accuracy\", \"overall accuracy\"],\n", + " ['r', 'g', 'b'], \"Percent\", \"High confidence predictions\",\n", + " width=0.15, figsize=(6,5))\n", + " axes.set_yticks(range(0, 100, 10))\n", + " axes.axhline(50, label = \"50%\")\n", + " axes.axhline(90, label = \"90%\")\n", + " # axes.get_legend().set_bbox_\n", + " axes.set_ylim(top=100)\n", + " fig.show()" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 257 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpaceBarGraph(forestClf, cleanedFeatureMatrix, cleanedResultVector, 5)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Found 788 high confidence predictions out of 1462\n", + "Found 744 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 779 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 821 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 774 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.9, percentage auto classified 0.534558811825\n", + "for prob 0.9, scoring only on high confidence predictions 0.987197387575\n", + "for prob 0.9, scoring on all predictions 0.90283185907\n", + "Found 754 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 748 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 763 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 772 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 725 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.51484909517\n", + "for prob 0.95, scoring only on high confidence predictions 0.984854972652\n", + "for prob 0.95, scoring on all predictions 0.902013125579\n", + "Found 734 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 774 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 747 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 764 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 755 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.99, percentage auto classified 0.51649124384\n", + "for prob 0.99, scoring only on high confidence predictions 0.98519408598\n", + "for prob 0.99, scoring on all predictions 0.90009344648\n", + "3\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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KCsbGxhoXYz09Pdm1a5fG5x6ddgFUU5DZ2dnVpnv06FEA/Pz8qtW9+edNdPR1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\nmZAkSXh7e1vbevfuLR5++GHZ+mvXrhWSJFnnHUwmk7jrrruEJElCkiT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+ "text": [ + "" + ] + } + ], + "prompt_number": 241 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "svmClf = svm.LinearSVC()\n", + "exploreKFoldValidationSpaceBarGraph(svmClf, cleanedFeatureMatrix, cleanedResultVector, 5)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Found 1440 high confidence predictions out of 1462\n", + "Found 1405 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 964 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 286 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 1197 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.9, percentage auto classified 0.724168930263\n", + "for prob 0.9, scoring only on high confidence predictions 0.535224088718\n", + "for prob 0.9, scoring on all predictions 0.585364202507\n", + "Found 1076 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 447 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 672 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 1297 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 632 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.564402228109\n", + "for prob 0.95, scoring only on high confidence predictions 0.606181832672\n", + "for prob 0.95, scoring on all predictions 0.609287905984\n", + "Found 1007 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 360 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 688 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 842 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 594 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.99, percentage auto classified 0.477763857561\n", + "for prob 0.99, scoring only on high confidence predictions 0.717835049772\n", + "for prob 0.99, scoring on all predictions 0.606016436468\n", + "3\n" + ] + }, + { + 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o1KmT3DQ9PT2Fx8mL4JGE4lZUVNRabkFBAQDAwMCgVt3CwkKFNkpCTAvlhB43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\nGYYDERHJMByIiEiG4UBERDI+D4eNGzfi7rvvxjXXXAO1Wo3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+ "text": [ + "" + ] + } + ], + "prompt_number": 258 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We now get the most important params for the decision tree so that we can better understand what it is doing." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "forestClf.get_params()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 63, + "text": [ + "{'bootstrap': True,\n", + " 'compute_importances': None,\n", + " 'criterion': 'gini',\n", + " 'max_depth': None,\n", + " 'max_features': 'auto',\n", + " 'min_density': None,\n", + " 'min_samples_leaf': 1,\n", + " 'min_samples_split': 2,\n", + " 'n_estimators': 10,\n", + " 'n_jobs': 1,\n", + " 'oob_score': False,\n", + " 'random_state': None,\n", + " 'verbose': 0}" + ] + } + ], + "prompt_number": 63 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "for (i, importance) in enumerate(forestClf.feature_importances_):\n", + " print featureLabels[i], importance" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "distance 0.0793686984768\n", + "duration 0.0495176408306\n", + "first filter mode 0.246502353725\n", + "sectionId 0.0185056232685\n", + "avg speed 0.172221930925\n", + "speed EV 0.139177761603\n", + "speed variance 0.123555472446\n", + "max speed 0.101279842943\n", + "max accel 0.0606474336459\n", + "isCommute 0.00922324213502\n" + ] + } + ], + "prompt_number": 64 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "So the highest importance features are:\n", + "\n", + "- first filter mode (moves mode)\n", + "- speed EV\n", + "- avg speed\n", + "- distance" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, let's try another non-parametric method like nearest neighbor" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "from sklearn import neighbors" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 99 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "knnClf = neighbors.KNeighborsClassifier()" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 100 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "exploreKFoldValidationSpace(knnClf, cleanedFeatureMatrix, cleanedResultVector, 5)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'exploreKFoldValidationSpace' is not defined", + "output_type": "pyerr", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mexploreKFoldValidationSpace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mknnClf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcleanedFeatureMatrix\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcleanedResultVector\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;31mNameError\u001b[0m: name 'exploreKFoldValidationSpace' is not defined" + ] + } + ], + "prompt_number": 101 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "knn does almost the same as decision tree, except that the accuracy of the high confidence predictions is a bit lower.\n", + "I think that the percentages are around the same as well. Basically, we can classify walk pretty well and the others pretty poorly.\n", + "So I am not sure what we are adding here over moves :)\n", + "\n", + "I'm surprised at the low prediction rate for cycling. Moves seems to get that pretty accurately for me.\n", + "\n", + "I'm now going to plot this data and see what it looks like." + ] + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Advanced features added" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "Advanced_indices=[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18]\n", + "print(Advanced_indices)\n", + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,Advanced_indices], cleanedResultVector, 5)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18]\n", + "Found 755 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 745 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 742 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 706 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 738 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.9, percentage auto classified 0.504445449447\n", + "for prob 0.9, scoring only on high confidence predictions 0.980703906413\n", + "for prob 0.9, scoring on all predictions 0.884904460805\n", + "Found 720 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 749 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 740 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 776 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 738 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.509513376049\n", + "for prob 0.95, scoring only on high confidence predictions 0.983854702231\n", + "for prob 0.95, scoring on all predictions 0.88901133062\n", + "Found 747 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 763 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 766 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 734 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 787 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.99, percentage auto classified 0.519639584978\n", + "for prob 0.99, scoring only on high confidence predictions 0.981833978001\n", + "for prob 0.99, scoring on all predictions 0.888874250813\n", + "[0.50444544944667136, 0.50951337604904912, 0.51963958497777596]\n", + "[0.78740955066637341, 0.77442720721708957, 0.78137585183576319]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[0.4713827111133323, 0.47748932741182692, 0.51976612061029503]\n", + "[0.066596822313189474, 0.054671198728429314, 0.069466743981272686]\n", + "[0.088546039641050539, 0.083359333238589836, 0.098420698924731181]\n", + "[0.24533069810859262, 0.28000089733767097, 0.27671110718064451]\n", + "[0.28580356289968234, 0.028571428571428571, 0.27671110718064451]\n", + "[0.9807039064134665, 0.98385470223072657, 0.9818339780007117]\n", + "[0.88490446080538132, 0.88901133061982729, 0.888874250812975]\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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Y2LBgwQKGDBlCQkICAQEBxMbGYmpqyquvvsq2bduAWzOHZ86cISwsjCVLlqAo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+AAAg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\nB7T6B0xXhGyBAAAAAElFTkSuQmCC\n", + "text": [ + "" + ] + } + ], + "prompt_number": 68 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Spatial knowledge added" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "Spatial_indices=[0,1,2,3,4,5,6,7,8,9,13,14,15,16,17,18,19,20]\n", + "print(Spatial_indices)\n", + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,Spatial_indices], cleanedResultVector, 5)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'exploreKFoldValidationSpace' is not defined", + "output_type": "pyerr", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mSpatial_indices\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mforestClf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mensemble\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mRandomForestClassifier\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mexploreKFoldValidationSpace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mforestClf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcleanedFeatureMatrix\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mSpatial_indices\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcleanedResultVector\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;31mNameError\u001b[0m: name 'exploreKFoldValidationSpace' is not defined" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 13, 14, 15, 16, 17, 18, 19, 20]\n" + ] + } + ], + "prompt_number": 95 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Location and time features added" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix, cleanedResultVector, 5)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Found 720 high confidence predictions out of 1462\n", + "Found 776 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 751 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 717 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 763 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.9, percentage auto classified 0.510058418095\n", + "for prob 0.9, scoring only on high confidence predictions 0.986661290954\n", + "for prob 0.9, scoring on all predictions 0.902696277403\n", + "Found 775 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 734 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 758 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 731 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 776 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.516491150206\n", + "for prob 0.95, scoring only on high confidence predictions 0.984477501552\n", + "for prob 0.95, scoring on all predictions 0.903791043183\n", + "Found 786 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 803 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 789 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 769 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 746 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.99, percentage auto classified 0.53277387169\n", + "for prob 0.99, scoring only on high confidence predictions 0.983652800765\n", + "for prob 0.99, scoring on all predictions 0.90557027166\n", + "[0.51005841809528363, 0.51649115020632197, 0.53277387168992996]\n", + "[0.76510212047330917, 0.7570729762254238, 0.77305762023811164]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[0.41424100415154008, 0.39923720868748119, 0.42664216430654739]\n", + "[0.025180525969119016, 0.049078994242941168, 0.049709991282712529]\n", + "[0.077891652886922486, 0.13797916879519151, 0.16532873367459833]\n", + "[0.331672532469861, 0.35805738372907175, 0.3717980290312643]\n", + "[0.2745701948806808, 0.09166666666666666, 0.3717980290312643]\n", + "[0.98666129095410826, 0.98447750155181402, 0.98365280076502193]\n", + "[0.90269627740308667, 0.90379104318294823, 0.90557027165959281]\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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ptC87duzA19eXVq1a8be//U1NZJpannfw4EG8vLw4cOAAAOvXrycgIACj0cjT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\noapNTEwMJEnCrFmze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UVORK5CYII=\n", + "text": [ + "" + ] + } + ], + "prompt_number": 70 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "knnClf = neighbors.KNeighborsClassifier()\n", + "exploreKFoldValidationSpace(knnClf, cleanedFeatureMatrix, cleanedResultVector, 5)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Found 686 high confidence predictions out of 1462\n", + "Found 725 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 702 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 665 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 695 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.9, percentage auto classified 0.475295671967\n", + "for prob 0.9, scoring only on high confidence predictions 0.920504558887\n", + "for prob 0.9, scoring on all predictions 0.759270817825\n", + "Found 688 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 677 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 717 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 658 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 705 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.471466988018\n", + "for prob 0.95, scoring only on high confidence predictions 0.919366854269\n", + "for prob 0.95, scoring on all predictions 0.759684210822\n", + "Found 678 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 679 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 686 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 711 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 692 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.99, percentage auto classified 0.471604629627\n", + "for prob 0.99, scoring only on high confidence predictions 0.919296182806\n", + "for prob 0.99, scoring on all predictions 0.758724745808\n", + "[0.47529567196727313, 0.47146698801768927, 0.4716046296270287]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[0.76634114335052517, 0.76044594004086297, 0.7584405112930499]\n", + "[0.17891544121294012, 0.17111911792202023, 0.1803876501592378]\n", + "[0.12516107813717867, 0.13608746575711689, 0.1395413774585626]\n", + "[0.17157891627331354, 0.20847147513051403, 0.18257272035103711]\n", + "[0.29615052225738825, 0.2889486955374026, 0.29163799556147796]\n", + "[0.30334197718935135, 0.18333333333333329, 0.29163799556147796]\n", + "[0.92050455888676264, 0.91936685426862985, 0.91929618280622916]\n", + "[0.75927081782524386, 0.75968421082200133, 0.75872474580778293]\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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BA5Kkbdu2qXXr1vLw8FBgYKAWLFggyfEQ0x49eighIUETJkyQh4eHfvzxxwqH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\nJMLMs8LJY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+ "text": [ + "" + ] + } + ], + "prompt_number": 71 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "for (i, importance) in enumerate(forestClf.feature_importances_):\n", + " print featureLabels[i], importance" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "distance 0.0471277355802\n", + "duration 0.0241100637166\n", + "first filter mode 0.226354019305\n", + "sectionId 0.00952695330572\n", + "avg speed 0.163697963259\n", + "speed EV 0.0554421827286\n", + "speed variance 0.0781562318165\n", + "max speed 0.0519512817229\n", + "max accel 0.0543447396795\n", + "isCommute 0.00312059283358\n", + "heading change rate 0.0308448579055\n", + "stop rate 0.025621877112\n", + "velocity change rate 0.0450951520883\n", + "start lat 0.0288594489748\n", + "start lng 0.030583666619\n", + "stop lat 0.0324661548608\n", + "stop lng 0.0250727639855\n", + "start hour 0.0111926914363\n", + "end hour 0.0101041393076\n", + "close to bus stop 0.0285357545407\n", + "close to train stop 0.0177917292227\n" + ] + } + ], + "prompt_number": 72 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Some more contour plots to help us visualize the data" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "from matplotlib import colors\n", + "import itertools" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 73 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "def printColorMap(algo, Xall, y):\n", + " # we want to split roughly into roughly 10-20 sections\n", + " nSplits = 20\n", + " \n", + " # setup parameters\n", + " cmap_light = colors.ListedColormap(['#FAAAAA', '#AFAAAA', '#AAFAAA', '#AAAFAA', '#AAAAFA', '#AAAAAF'])\n", + " cmap_bold = colors.ListedColormap(['#F00000', '#0F0000', '#00F000', '#000F00', '#0000F0', '#00000F'])\n", + " \n", + " # nFeatures = Xall.shape[1]\n", + " nFeatures = 10\n", + " fig, axes = plt.subplots(20, 5, figsize=(15,50))\n", + " plt.tight_layout()\n", + " axesArr = axes.flatten()\n", + " \n", + " i = 0\n", + " for selCombo in itertools.product(np.arange(nFeatures), np.arange(nFeatures)):\n", + " if selCombo[0] == selCombo[1]:\n", + " continue\n", + " # print(\"Generating grid for combo %s,%s in slot %s\" % (featureLabels[selCombo[0]], featureLabels[selCombo[1]], i))\n", + " \n", + " selMask = np.zeros(Xall.shape[1])\n", + " # Otherwise, we won't be able to plot it properly below\n", + " assert(len(selCombo) == 2)\n", + " selMask[selCombo[0]] = 1\n", + " selMask[selCombo[1]] = 1\n", + " \n", + " X = Xall[:,selMask == 1]\n", + " \n", + " algo.fit(X, y)\n", + " # Plot the decision boundary. For that, we will assign a color to each\n", + " # point in the mesh [x_min, m_max]x[y_min, y_max].\n", + " x_min, x_max = X[:, 0].min() - 1, X[:, 0].max() + 1\n", + " y_min, y_max = X[:, 1].min() - 1, X[:, 1].max() + 1\n", + " # we want to split roughly into \n", + " h_x = float(x_max - x_min) / nSplits\n", + " h_y = float(y_max - y_min) / nSplits\n", + " \n", + " xx, yy = np.meshgrid(np.arange(x_min, x_max, h_x),\n", + " np.arange(y_min, y_max, h_y))\n", + " Z = algo.predict(np.c_[xx.ravel(), yy.ravel()])\n", + " \n", + " # Put the result into a color plot\n", + " Z = Z.reshape(xx.shape)\n", + "\n", + " axesArr[i].pcolormesh(xx, yy, Z, cmap=cmap_light)\n", + "\n", + " # Plot also the training points\n", + " axesArr[i].scatter(X[:, 0], X[:, 1], c=y, cmap=cmap_bold)\n", + " # plt.scatter(X[:, 0], X[:, 1], c=y)\n", + " axesArr[i].set_xlim(xx.min(), xx.max())\n", + " axesArr[i].set_ylim(yy.min(), yy.max())\n", + " axesArr[i].set_title(\"%s v/s %s\" % (featureLabels[selCombo[0]], featureLabels[selCombo[1]]))\n", + " # axesArr[i].legend(loc='best')\n", + " i = i+1 " + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 74 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "printColorMap(forestClf, cleanedFeatureMatrix, cleanedResultVector)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "display_data", + "png": 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K2mjj22inTp2Qnp6OvLw8mJqaYtCgQQDqbg85OTmIj4/Hl19+CUtLSxgaGnKzXWhrbzWX\n6bruf/nlF67M/Pnz4eDgAGtra4wfP15rjqF79+7h0qVL+OCDDyAQCDBs2DCMHz++wzxa1Zyys7Mh\nEok0lnXt2lVrWTc3N3z66adYtWoVhEIhgoKCkJOTo3PfR48ehY+PD2xtbWFtbY24uDg8fPiQW29r\naws+/38fv01NTVFcXIy8vDyUlZWhR48etfaZkZGBf//737C2tuZe58+fx/3797XGMH36dOzbtw8A\nsHfvXrz66qvcupqPAXTu3Bn79+/Hl19+CScnJ4wbNw43b97Uus+0tDSMGzcOjo6OsLS0xIoVK7h6\n8Xg8TJs2TesxtZ1rZ2dnndfxxx9/DMYYvL294eHhgZ07d9batpqLiwuys7O5c7RgwQLu/Nja2gIA\nFAoFMjIykJiYqHH+9u7di9zcXOTl5UGpVNbaL3k+1MYa38YiIyORlpaGPn36wNvbm/tsVq2ua3/y\n5Mlc3BKJBIaGhsjNza2zXtnZ2bC2toaJiQm3X12/o2pOTk549OgR98rPz+e2d3FxwfDhwxEVFYXi\n4mIcPny47T5qA8pJooEadOMbdHZ29nPdWOzs7NCpUyfufUlJCd544w24urrC0tISvr6+KCws1LiZ\n6spLkpeXh8rKSo3fmYuLCxQKBffewcGB+7n6mfbi4uJGxdyeURtofBtoiJptpLHnTZtnzc3TkPPV\nkNlxhEIh97OJiYnGe2NjY65NZWdna/yfwOPx4OzsDIVCgZycnDqvtYyMDGzcuFEj1qysrEafq/aG\n2mjTffCsK7bMzEzY2NjA0tJS5/nSpa7rvlrNe5GJiYnW+9CzfIAlDePo6Kjx+wCqrgddgoKCcPbs\nWWRkZIDH42Hp0qUAav9fXF5ejilTpmDJkiX4888/8ejRI4wZM6ZBHVtdunSBsbExbt26VWudi4sL\ngoODNf44KSoqwpIlS7Tua+rUqTh9+jQUCgUOHTqE6dOnc+tqtiMAGD16NI4dO4b79++jd+/eOmdp\nCgsLg0Qiwa1bt1BYWIh//etfUKvVGufowIEDyMjIQFJSEqZMmQJA+7m+d++ezvuYUCjE9u3boVAo\n8NVXX2HevHm4ffu2xrY1f67+/9DFxQXbt2/XOEePHz/G4MGD4eLiAl9f31rn7/PPP0eXLl1gaGhY\na7/k+VAba3wbc3Nzw969e/HgwQMsXboUU6dORWlpKbe+rms/Pj5eI/aSkhI4OTnVWS9HR0eubLXq\n8/+sQkNDERUVhf/85z/o1q0bl0emLaJOkhqoQTe+QTs6OtZ5YzE1NdVofDk5ORrn5+lztXHjRqSl\npSEpKQmFhYVISEjQ+MazrobbpUsXCAQCjemA7927B7FYrHMboonaQOPbQEM8fT4aet6edf+6ljfk\nfD1LDLp+j9WzkNQsl5mZCbFYXO+15uLighUrVmjEWlxcjMDAwEbH155QG22aD54lJSV1xubs7Iz8\n/HwUFhbW2l99bUTXdf9051Z9muMDLKkyZMgQGBoaYsuWLaisrMT333+Pixcvai2blpaGkydPory8\nHEZGRjA2NoaBgQGAqs6uu3fvcu2koqICFRUV6NKlC/h8Po4ePYpjx441KCY+n49Zs2Zh0aJFyMnJ\ngUqlwq+//oqKigrMmDEDR44cwbFjx6BSqVBWVsa1E23s7OwwYsQIzJw5E927d0evXr0AVH0RdfHi\nRYwcORIA8Oeff+Lw4cN4/PgxBAIBOnfuzNXtacXFxTA3N4epqSl+//13fPHFFxrrvby80KVLF8yZ\nMwcBAQGwsLDgzrWBgQE+++wzKJVKHD58WOe5BqpGKGdlZQEArKyswOPxNDpnN2zYgIKCAmRmZmLL\nli3cPeHNN9/E2rVrkZqaCgAoLCzkkrOOGzcOaWlp+Pbbb1FZWYnKykpcvHgRv//+OwwMDPD3v/8d\nq1atQmlpKVJTU7F7925qZ8+J2ljj29i3336LBw8eAAAsLS1rXfsffvghSktLkZKSgl27dmlc++Hh\n4dzfYA8ePEBsbCwA1Fmvrl27YsCAAXj//fdRWVmJc+fO4YcffmjQudRlypQpuHfvHlatWoWZM2c+\n1770jTpJaqAG3fgGLZfLsW7dOhQUFCArKwtbt27VWO/l5YXvvvsOKpUK8fHxOHPmTJ31LS4uhomJ\nCSwtLZGfn4/Vq1drrBcKhTqzjhsYGEAul2PFihUoLi5GRkYGNm3ahBkzZtR5TPI/1AYa3wYaqzHn\nTZea6+t6ROfp9tKQ89WUQ/lfeeUV/Pjjjzh58iQqKyuxceNGGBsbY8iQIfDx8anzWps7dy6+/PJL\nJCUlgTGGx48f48cff+zwI7+ojTbNB08DA4M6Y3N0dMTLL7+MefPmoaCgAJWVldz9SygU4uHDh/jr\nr7+0Hq+u674xmuMDLKkiEAjw/fffY9euXbC1tUVMTAw38qFa9R/J5eXlWL58Oezs7ODo6Ii8vDys\nW7cOALgZLmxtbTFgwACYm5tjy5YtkMvlsLGxwb59+zBx4kSt+9Vmw4YN8PT0xMCBA2Fra4vly5dD\nrVZDLBbj8OHDWLt2Lezt7eHi4oKNGzdqjOR42vTp0/Hzzz9rdDSePHkSQ4YM4UbwqtVqbNq0CSKR\nCLa2tjh79mytzo+ase3duxcWFhZ4/fXXMW3atFp1mT59Ok6ePKlxzOpzHRkZCWtra3z33XcYN26c\nxijimi5dugQfHx+Ym5tj4sSJ2LJlC1xdXbn1EydORP/+/SGTyTBu3DjMmjULADBp0iQsXboU06ZN\ng6WlJTw9PfHTTz8BAMzMzHDs2DFER0dDJBLB0dERy5cvR0VFBQDgs88+Q3FxMRwcHDBr1ixun+TZ\nURtrfBv76aef4OHhAXNzcyxcuBDR0dEwMjLi1vv6+sLNzQ2jRo3CP//5T4waNQpA1cw6EyZMwOjR\no2FhYYHBgwcjKSkJAOqt1969e5GYmAgbGxusWbMGoaGhOuvL4/GQnZ0Nc3NzjVf1I7JA1ZfjU6ZM\ngUKh0BgJ2iY1JHGJUqlkXl5ebNy4cYyxqiQ6IpGIeXl5MS8vLxYXF8eVXbt2LXNzc2O9evXSSK50\n6dIl5uHhwdzc3DQy1ZeVlTG5XM7c3NzYoEGD2N27dxsSUrO5dOlSrVkDaiYZqk5Keu3aNebt7c3M\nzc2ZjY0NGz9+PJcc7+HDh2zo0KHM2tqa9e/fnzHG2Oeff86EQiGzsrJiwcHBLCgoSOt+q9VMuFha\nWsreeecdJhKJmKWlJfP19eVmDUhMTGS+vr7MxsaG2dnZsXHjxrF79+7prF9UVBTj8Xhsw4YN3LIj\nR46w8ePHc+9zcnKYr68vs7S0ZFZWVmzkyJEamflrKikpYSEhIczKyopJpVK2fv16jbpcunSJSaVS\nLtnc9OnT66x3dnY2GzFiBDMzM2O9evViX331FePz+VwCpl9//ZX17NmTWVtbswULFjDGNBO3Pnr0\niM2YMYPZ2dkxZ2dn9sEHH3Cz2+zatatW4i4+n691Bo+OjNpA49rA09fV03V5OnlqY8/b0+pL3Frz\n2IcPH2YuLi7MysqKbdy4Uef5yszM1LpvbZ6uz4wZM7hErYxVzfjj7+/PvT948CCTSCTM0tKSjRgx\ngptNgLG6rzXGqjKjDxw4kFlZWTFHR0cml8u5pJ4dGbXRxrXRGTNmMHt7e2ZmZsY8PDzY4cOHuXV1\nxZafn89CQ0OZUChk1tbWbMqUKdx2s2bNYra2tsza2pplZ2fXSoRb13X/dBuque3T5/n27dts2LBh\nzMzMjPn7+7O3336bEreSZzZv3jz2xRdf6DsM5u3tzXbt2tXo7Z6eDICQ1qY52lh14taayWhJ8+Mx\nVv/Xhp988gkuX76MoqIixMbGYvXq1TA3N8eiRYs0yqWmpmL69Om4ePEiFAoFRo0ahfT0dPB4PHh7\ne+Ozzz6Dt7c3xowZg/nz5yMgIADbtm3DjRs3sG3bNuzfvx8HDx5EdHR0s3UKkdr+8Y9/wNPTE2++\n+aa+QyFEL6gNENK6URsl5Pl9/fXXmDBhgkYeqZZw5swZ9OzZE126dMF3333H5RlpbBx8Ph+3bt3i\nElAT0to0Rxu7e/cuunfvDqVSqfH4DWle9Z7prKwsxMXFYc6cOdywXKZjePfhw4cRFBQEgUAAV1dX\nuLm5ITExETk5OSgqKuIy1IeEhODQoUMAgNjYWG5oz5QpU/Dzzz83WeVIw3h5eWHy5Mn6DoMQvaE2\nQEjrRm2UkOc3d+7cFu8gAYCbN2/Cy8sL1tbW2LRpEw4cOPBMcVCeENLaNVcbo2u/5Wmf37GGhQsX\nYv369RrP3vJ4PGzduhV79uzBgAEDsHHjRlhZWSE7Oxs+Pj5cObFYDIVCAYFAoJE8UyQScc8jKxQK\nbjYFQ0NDLheFjY1Nk1WS1O15ElIS0h5QGyCkdaM2SkjbNXfu3CZpwyqVqgmiIaRtcXV1pWtfD+oc\nSfLDDz/A3t4eMplMY+RIWFgY7ty5g+TkZDg6OmLx4sXNHighhBBCCCGEEEJIc6pzJMkvv/yC2NhY\nxMXFoaysDH/99RdCQkKwZ88ersycOXMwfvx4AFUjRDIzM7l1WVlZEIvFEIlE3HReNZdXb3Pv3j04\nOTlBqVSisLBQ6ygSV9e+yMi49ny1JUSPfH19cfr0aX2HoaGbqyvu1jF9KCGtXWtsVwY8HnTnwyek\n9Wtt7aqvqyuu0b2KtGGtrU0BgKtrN2Rk3NV3GIQ8s+ZsVw1K3AoACQkJ2LBhA44cOYKcnBw4OjoC\nADZt2oSLFy9i7969XOLWpKQkLnHrrVu3wOPxMGjQIGzZsgXe3t4YO3asRuLW69ev44svvkB0dDQO\nHTqkNXErj8dDTExFPVH+2OgT8LSYmGjI5dMaWHpsA8rUjqlxx3h2dJzWdRy5fHKTTq/aFHg8Hg7G\nxNRZphKTnusYMTFrIJevfK590HHa9nGa8xhyeadW2a5MjIywZtUquPXo0SzHiI6JwTS5/LnbZ33a\n03XYUsdpD3Vpbe2Kx+Ohop57VUMdgkDnusbc/yeh8pmP19Y/z7T0MdrDcVrrZ8CYmIN1lmnodV6X\nNTExWCmXP/d+OtJx2lNdmvM4neTyZmtX9eYkqcYY45LGLFmyBP/973/B4/HQrVs3fPXVVwAAiUQC\nuVwOiUQCQ0NDbNu2jdtm27ZtmDlzJkpLSzFmzBgEBAQAAGbPno3g4GC4u7vD1taWZrYhhBDS5nl6\neqIHzcBACCGEENLmNLiTZMSIERgxYgQAICoqSme58PBwhIeH11rev39/XL9+vdZyIyMjxDTRtwOE\nEEJIa7D03XcpGz0hhBBCSBtEky0/RSr1aBfHoOO0/uN0FFKpLx2ngx+nperSmvD5zXt79ZBKm3X/\n1drTddhSx2lPdelo2tvnDPpM23qP05H4ttD9qj0dpz3VpSWP05QanJNE31oqJ0njPFtOEtIxtfTz\nqDdv3sS0af97rvb27dv44IMPMH/+fG5ZS+QkIaQ5NVfuhFmzZuHHH3+Evb09Nwpy1apV+Oabb2Bn\nZwcAWLduHffoaE0NaVdNhdonaQ4dNSdJYzxPThLS8XTknCSENJdWkZOEENK29OrVC1evXgUAqNVq\niEQiTJ48Wc9REdI2vPbaa3j77bcREhLCLePxeFi0aBEWLVqkx8gIIYQQQkhzosdtCOkATpw4gR49\nesDZ2bnWusny1/C4pEQPURHSeg0bNgzW1ta1ljf0G4v1n3zS1CERQgghhJAW0KY6SXJzb+s7BELa\npOjoaEyfPl3H2p4Iee31Fo2HkLZq69at6Nu3L2bPno2CggKd5a5euIBLly+3YGSEEEIIIaQptKlO\nkiVLhuP+/T/0HQYhbUpFRQWOHDmCV155RUeJuVAzkxaNiZC2KCwsDHfu3EFycjIcHR2xePFinWUl\nAH65cKHlgiOEEEIIIU2iTeUkKSsLRlzcl5g1a72+QyGkzTh69Cj69+/PJZus7XMARYiOiYGHVNpi\ns2YQ8ixSUhKQkpKgl2Pb29tzP8+ZMwfjx4/XWfYGAElBAbUr0ibos10RQgghrU2b6iRhzBZlZXf1\nHQYhbcq+ffsQFBRUR4m7CF+2BAP79WuxmAh5VlKpr8bUpwcOfNhix87JyYGjoyMA4ODBg/D09NRZ\ntouVFVYnED+kAAAgAElEQVSuWNFSoRHyXPTZrgghhJDWpkGP26hUKshkMu5bs/z8fPj7+6Nnz54Y\nPXq0xnPZ69atg7u7O3r37o1jx45xyy9fvgxPT0+4u7tjwYIF3PLy8nIEBgbC3d0dPj4+yMjI0BlH\np05bMHz4lEZXkpCO6vHjxzhx4gT+/ve/6yyzPuI96iAh5ClBQUEYMmQIbt68CWdnZ+zYsQNLly7F\nCy+8gL59+yIhIQGbNm3Suf1n27e3YLSEEEIIIaSpNKiTZPPmzZBIJODxeACAiIgI+Pv7Iy0tDX5+\nfoiIiAAApKamYv/+/UhNTUV8fDzmzZvHzQQQFhaGyMhIpKenIz09HfHx8QCAyMhI2NraIj09HQsX\nLsTSpUt1xvH225vh4THyuSpMSEfSuXNn5OXlwdzcXGcZt+7dWzAiQtqGffv2ITs7GxUVFcjMzMSs\nWbOwZ88eXLt2Df/9739x6NAhCIVCfYdJCCGEEEKaWL2dJFlZWYiLi8OcOXO4Do/Y2FiEhoYCAEJD\nQ3Ho0CEAwOHDhxEUFASBQABXV1e4ubkhMTEROTk5KCoqgre3NwAgJCSE26bmvqZMmYKff/5ZZyyD\nBk1+jqoSQgghhJDm5urqihdeeAEymYz77Pcso5AJIYQQfai3k2ThwoVYv349+Pz/Fc3NzeW+QRMK\nhcjNzQUAZGdnQywWc+XEYjEUCkWt5SKRCAqFAgCgUCjg7OwMADA0NISlpSXy8/OboGqEEEIIIaSl\n8Xg8nD59GlevXkVSUhKAxo1CVqvV+gyfEEJIB1dn4tYffvgB9vb2kMlkOH36tNYyPB6PewyHEEII\nIUBIcDD2REXpOwxC9KZ69HG12NhYJCRUzaATGhqKESNGICIiQuso5KSkJPj4+Ogj7AY7BIG+QyCk\n2bX8dT62AWV+bPYoCKmzk+SXX35BbGws4uLiUFZWhr/++gvBwcEQCoW4f/8+HBwckJOTw02LKBKJ\nkJmZyW2flZUFsVgMkUiErKysWsurt7l37x6cnJygVCpRWFgIGxsbrfHExKzhfn46EzshrU1Kyg2k\npNzQdxiEED1g5eXYsWcPZoWE6DsUQlocj8fDqFGjYGBggDfeeANz586tcxRyzQ6R6lHIhBBCiL7U\n2Umydu1arF27FgCQkJCADRs2ICoqCkuWLMHu3buxdOlS7N69G5MmTQIATJgwAdOnT8eiRYugUCiQ\nnp4Ob29v8Hg8WFhYIDExEd7e3oiKisL8+fO5bXbv3g0fHx8cOHAAfn5+OuORy1c2Vb0JaXZSqQek\nUg/u/YED+/UYDSGkJfUEcP36dX2HQYhenD9/Ho6Ojnjw4AH8/f3Ru3dvjfX1jULWtm5NTAz3s69U\nCl+ptOkCJqSJ0RdlhLRtdXaSPK36prVs2TLI5XJERkbC1dUVMU9uXBKJBHK5HBKJBIaGhti2bRu3\nzbZt2zBz5kyUlpZizJgxCAgIAADMnj0bwcHBcHd3h62tLaKjo5uyfoQQQkiL+x3A+CcJKwnpaBwd\nHQEAdnZ2mDx5MpKSkho1ClkkEtXa50q5vGWCJ6QJ0BdlhLRtDe4k8fX1ha9v1eMtNjY2OHHihNZy\n4eHhCA8Pr7W8f//+Wr9VMzIy4jpZCCGEkPbA2MIC0155Rd9hENLiSkpKoFKpYG5ujsePH+PYsWN4\n//33uZHDDR2FTAghhOhLo0aSEEIIIaR+kd98o+8QCNGL3NxcTJ48GQCgVCrx6quvYvTo0RgwYECj\nRyETQggh+kCdJIQQQgghpEl069YNycnJtZY/yyhkQgghRB/4+g6AENJ8CgoKMHXqVPTp0wcSiQQX\nLlzQd0iEEEIIIYQQ0mpRJwkh7diCBQswZswY/Pbbb7h27Rr69Omj75AI6RCKior0HQIhhJB2RKVS\nQSaTYfz48QCA/Px8+Pv7o2fPnhg9ejQKCgq4suvWrYO7uzt69+6NY8eO6StkQtos6iQhpJ0qLCzE\n2bNnMWvWLACAoaEhLC0t9RwVIR1D6Oy3UFxcrO8wCCGEtBObN2+GRCLhcvZERETA398faWlp8PPz\nQ0REBAAgNTUV+/fvR2pqKuLj4zFv3jyo1Wp9hk5Im0OdJIS0U3fu3IGdnR1ee+019OvXD3PnzkVJ\nSYm+wyKkQ2AYi/CVq/UdBiGEkHYgKysLcXFxmDNnDhhjAIDY2FiEhoYCAEJDQ3Ho0CEAwOHDhxEU\nFASBQABXV1e4ubkhKSlJb7ET0hZR4lZC2imlUokrV67gs88+w8CBA/HOO+8gIiICa9as0SgXXWMK\nbg+pFB5SaUuHSkiDpaQkICUlQd9hNMBAPHp0St9BEEIIaQcWLlyI9evX46+//uKW5ebmQigUAgCE\nQiFyc3MBANnZ2fDx8eHKicViKBSKlg2YkDaOOkkIaafEYjHEYjEGDhwIAJg6dSo3FLOmaXJ5S4dG\nyDOTSn0hlfpy7w8c+FCP0dRlK/42pJ++gyCEENLG/fDDD7C3t4dMJsPp06e1luHxeHVOnU3TahPS\nOHU+blNWVoZBgwbBy8sLEokEy5cvBwCsWrUKYrEYMpkMMpkMR48e5bbRlSjo8uXL8PT0hLu7OxYs\nWMAtLy8vR2BgINzd3eHj44OMjIymriMhHZKDgwOcnZ2RlpYGADhx4gSkNEqEkBbRxVaJN+fO1XcY\nhBBC2rhffvkFsbGx6NatG4KCgnDy5EkEBwdDKBTi/v37AICcnBzY29sDAEQiETIzM7nts7KyIBKJ\ntO47Jiaae6Wk3Gj+yhDyHFJSbmhcs82pzpEkxsbGOHXqFExNTaFUKjF06FCcO3cOPB4PixYtwqJF\nizTK10wUpFAoMGrUKKSnp4PH4yEsLAyRkZHw9vbGmDFjEB8fj4CAAERGRsLW1hbp6enYv38/li5d\niujo5q00IR3F1q1b8eqrr6KiogI9evTAzp079R0SIR3C119s0XcIhBBC2oG1a9di7dq1AICEhARs\n2LABUVFRWLJkCXbv3o2lS5di9+7dmDRpEgBgwoQJmD59OhYtWgSFQoH09HR4e3tr3bdcPq3F6kHI\n85JKPSCVenDvDxzY32zHqvdxG1NTUwBARUUFVCoVrK2tAYBLGlSTtkRBiYmJ6Nq1K4qKirgGGhIS\ngkOHDiEgIACxsbFYvboqud2UKVPw1ltvNVnlCOno+vbti4sXL+o7DEIIIYQQ0gSqH51ZtmwZ5HI5\nIiMj4erqipgnOeYkEgnkcjkkEgkMDQ2xbds2etyGkEaqt5NErVajX79++OOPPxAWFgapVIoDBw5g\n69at2LNnDwYMGICNGzfCyspKZ6IggUAAsVjMLReJRFwCIYVCAWdn56pgnkxRmp+fDxsbm6auKyHk\nGUzCoXrLHIKgCY9X2aLHI4QQ0vbRfYF0BL6+vvD1rcrLZWNjgxMnTmgtFx4ejvDw8JYMjZB2pd5O\nEj6fj+TkZBQWFuKll17C6dOnERYWhpUrVwIA3nvvPSxevBiRkZHNHmxMzP9m5Xg6eR8hrU1Kyg16\nvpOQDupRQQGsraz0HQYhhBBCCGmkBs9uY2lpibFjx+LSpUsYMWIEt3zOnDkYP348AO2JgsRiMUQi\nEbKysmotr97m3r17cHJyglKpRGFhoc5RJHL5ykZVjhB9asnn5gghrcuC11/Hl3v2wNTYWN+hEEII\nIYSQRqhzdpu8vDwUFBQAAEpLS3H8+HHIZDIukzIAHDx4EJ6engCqEgVFR0ejoqICd+7c4RIFOTg4\nwMLCAomJiWCMISoqChMnTuS22b17NwDgwIED8PPza5aKEkIIIS3FEsBXX3+t7zAIIYQQQkgj1TmS\nJCcnB6GhoVCr1VCr1QgODoafnx9CQkKQnJwMHo+Hbt264auvvgJQd6Kgbdu2YebMmSgtLcWYMWMQ\nEBAAAJg9ezaCg4Ph7u4OW1tbmtmGEEJIm2cD4HFxsb7DIIQQQgghjVRnJ4mnpyeuXLlSa/mePXt0\nbqMrUVD//v1x/fr1WsuNjIy4bMyEEEJIe3ALwPtTp+o7DEIIIYQQ0kh1Pm5DCCGEkMb7e1AQerq7\n6zsMQgghhBDSSNRJQgghhDSxKZMn6zsEQgghhBDyDBo8uw3R5kd9B0BInVxdXWFhYQEDAwMIBAIk\nJSXpOyRCSBMS4JC+QyCkFpVKhQEDBkAsFuPIkSPIz89HYGAgMjIy4OrqipiYGFg9mSJ73bp12LFj\nBwwMDLBlyxaMHj1az9ETQgjp6GgkCSHtGI/Hw+nTp3H16lXqICGEENIiNm/eDIlEwiXvj4iIgL+/\nP9LS0uDn54eIiAgAQGpqKvbv34/U1FTEx8dj3rx5UKvV+gydEEIIoU4SQto7xpi+QyCkw/lo/Xp9\nh0CIXmRlZSEuLg5z5szh7j+xsbEIDQ0FAISGhuLQoaoRUIcPH0ZQUBAEAgFcXV3h5uZGHfqEEEL0\njjpJCGnHeDweRo0ahQEDBuDrr7/WdziEdBjXL17EqdOn9R0GIS1u4cKFWL9+Pfj8/33EzM3NhVAo\nBAAIhULk5uYCALKzsyEWi7lyYrEYCoWiZQMmhBBCnkKdJIS0Y+fPn8fVq1dx9OhRfP755zh79qy+\nQyKkQxAB+OzLL/UdBiEt6ocffoC9vT1kMpnOUYw8Ho97DEfXekIIIUSfKHErIe2Yo6MjAMDOzg6T\nJ09GUlIShg0bplEmOiaG+9lDKoWHVNqiMRLSGCkpN5CSckPfYdRLBfpjj3Q8v/zyC2JjYxEXF4ey\nsjL89ddfCA4OhlAoxP379+Hg4ICcnBzY29sDAEQiETIzM7nts7KyIBKJtO57TY17la9UCl+6V5FW\nrK3cqwgh2tU5kqSsrAyDBg2Cl5cXJBIJli9fDgDIz8+Hv78/evbsidGjR6OgoIDbZt26dXB3d0fv\n3r1x7Ngxbvnly5fh6ekJd3d3LFiwgFteXl6OwMBAuLu7w8fHBxkZGU1dR0I6pJKSEhQVFQEAHj9+\njGPHjsHT07NWuWlyOfeiDhLS2kmlHpDLp3Gv1uo+gMU17nWEdARr165FZmYm7ty5g+joaLz44ouI\niorChAkTsHv3bgDA7t27MWnSJADAhAkTEB0djYqKCty5cwfp6enw9vbWuu+Vcjn3og4S0tq1lXsV\nIUS7OjtJjI2NcerUKSQnJ+PatWs4deoUzp0716gs5dXDLcPCwhAZGYn09HSkp6cjPj4eABAZGQlb\nW1ukp6dj4cKFWLp0aTNXmZCOITc3F8OGDYOXlxcGDRqEcePG0dSKhLSQof7+GOzjo+8wCNGr6tFU\ny5Ytw/Hjx9GzZ0+cPHkSy5YtAwBIJBLI5XJIJBK8/PLL2LZtG43AIoQQonf1Pm5jamoKAKioqIBK\npYK1tTViY2ORkJAAoCpL+YgRIxAREaE1S3liYiK6du2KoqIi7tuBkJAQHDp0CAEBAYiNjcXq1asB\nAFOmTMFbb73VXHUlpEPp1q0bkpOT9R0GIR3Sm3Pn6jsEQvTK19cXvr6+AAAbGxucOHFCa7nw8HCE\nh4e3ZGiEEEJInepN3KpWq+Hl5QWhUIiRI0dCKpU2Okv508tFIhGXvVyhUMDZ2RkAYGhoCEtLS+Tn\n5zddDQkhhJBGmjVrFoRCocYjanU9akoIIYQQQtqHejtJ+Hw+kpOTkZWVhTNnzuDUqVMa6+vLUt6U\nYmLWcK+UlIQWOSYhzyol5QZiYqK5FyGk7Xjttde4x0Kr6XrUlBBCCCGEtB8Nnt3G0tISY8eOxeXL\nlxuVpVwsFkMkEiErK6vW8upt7t27BycnJyiVShQWFsLGxkZrDHL5ymeqJCH6IJV6QCr14N4fOLBf\nj9EQQhpj2LBhuHv3rsYyXY+aavN3uRxL//lPDBo4sLlDJYQQQgghTajOkSR5eXnccOLS0lIcP34c\nMpms0VnKHRwcYGFhgcTERDDGEBUVhYkTJ3LbVO/rwIED8PPza7bKEkIIIc9K16Om2pgC+HjDBqSl\np7dQdIQQQgghpCnUOZIkJycHoaGhUKvVUKvVCA4Ohp+fH2QyGeRyOSIjI+Hq6oqYJ3PX18xSbmho\nqJGlfNu2bZg5cyZKS0sxZswYBAQEAABmz56N4OBguLu7w9bWFtHR9FgCIYSQ1q2+R00NARgyhktX\nrqCnu3vLBUYIIYQQQp5LnZ0knp6euHLlSq3lz5KlvH///rh+/Xqt5UZGRlwnCyGEENJa6XrUVJsy\nAJUAbqal4UZKCjyk0haLk5DGupGSghspKfoOgxBCCGkV6k3cSgghhBDofNRUGxUAc3NzLH7nHeog\nIa2eh1SKaXI59yKEtC5lZWUYNGgQvLy8IJFIsHz5cgB1z7q2bt06uLu7o3fv3jh27Ji+QiekTWpw\n4laizdgGlPmx2aMghBDStIKCgpCQkIC8vDw4OztjzZo1WLZsmdZHTbUZNnw4ZoaGwsLcvNa6Sgia\nM3RCCCHtjLGxMU6dOgVTU1MolUoMHToU586dQ2xsLPz9/bFkyRJ89NFHiIiIQEREBFJTU7F//36k\npqZCoVBg1KhRSEtLA59P348T0hDUSUIIIYQ8Zd++fVqX63rU9Gnz33qrKcMhhBDSwZmamgIAKioq\noFKpYG1trXPWtcOHDyMoKAgCgQCurq5wc3NDUlISfHx89FkFQtoM6k4kpB1TqVSQyWQYP368vkMh\nhBBCCCHPSK1Ww8vLC0KhECNHjoRUKtU561p2djbEYjG3rVgshkKh0EvchLRFNJKEkHZs8+bNkEgk\nKCoq0llmslyO6dOmweuFF2BjbQ0bGxvweDwwxpD755941LkzrDp3Bo/HQ2FJCfgAHldUoIuZGcqV\nSnQ2Nq61z/LycggEhuDzDRoca1lZGYyMjPC4vAwmnTrpHBKqVqtRVlEKY2OTBu9bG8YYysvLYGRk\nXOcsJYQQQggh+sbn85GcnIzCwkK89NJLOHXqlMb6+mZd07YuJuZ/s4pKpR6QSj2aLmBCmlhKyg2k\npNxokWNRJwkh7VRWVhbi4uKwYsUKfPLJJ3WW3Rsdjb3RRwCUgsczRoD/UBx9kuQrDIAh3wAWpqbI\nLy4CYAKgHIAafB4PrvZCvLNiJRwcHFFYWICIiH/hzp3b4PP5ePXVEIwdW/coluxsBdau3Yi8PAUY\n48GAVcBUYIitb7yBoOHDNcp+f+ECZn32OcqUlejSxR4rVrwHR0enRp+be/cysHbtBygoKICRkREW\nLnwXXl6yRu+HEF0my+U4SDO3EUIIaWKWlpYYO3YsLl++rHPWNZFIhMzMTG6brKwsiESiWvuSy6e1\nWNyEPK+nO/IOHNjfbMeix20IaacWLlyI9evX15+ky7T6B18AtmAsEkePnQFgBMACQGco1SrkFxc/\nKbwUgDEAM6iZOe78WYgPP1wDAPj0009w964CarUZlEoT7Nu3FzduXNN5aMYYPvxwPf78802o1blg\nLB4CmODrykq8u307rmVkcGXTsrPx2mefo6RCALXaDA8eFOLDD1eDMdao86JSqfDBB6uQn18Ctboz\nSkt52LjxY+TnP2zUfgipiwmAd959V99hEEIIaQfy8vK4mWtKS0tx/PhxyGQynbOuTZgwAdHR0aio\nqMCdO3eQnp4Ob29vvcVPSFtTbydJZmYm99ybh4cHtmzZAgBYtWoVxGIxZDIZZDIZjh49ym2ja8qp\ny5cvw9PTE+7u7liwYAG3vLy8HIGBgXB3d4ePjw8yavxhRAhpvB9++AH29vaQyWT1dyII8OR/gjsA\n8gCMAuCAqoFmvBr/dkJVx4nTk58NAPDAmAAPHz5ASUkJbt1Kh0pVXZ6Pykrg5s2bOg/9+PFjFBTk\nAXjjyTYyGMAHxQBG83i4dOsWV/by7dsw4GseNz8/H6WlJY06N48e5aO0tOxJHarqZ2AgwN27dxu1\nH0LqIgGQce+evsMghBDSDuTk5ODFF1+El5cXBg0ahPHjx8PPzw/Lli3D8ePH0bNnT5w8eRLLli0D\nAEgkEsjlckgkErz88svYtm0bPVpMSCPU+7iNQCDApk2b4OXlheLiYvTv3x/+/v7g8XhYtGgRFi1a\npFFe25RT6enp4PF4CAsLQ2RkJLy9vTFmzBjEx8cjICAAkZGRsLW1RXp6Ovbv34+lS5ciOjpaR0SE\nkPr88ssviI2NRVxcHMrKyvDXX38hJCQEe/bsqV24FIAaAJSo6jHJB/BnjQLsyUsN4PGTZSpUdTDw\nAKjB5xvA2NgYFhYWePCgGFW9LgydOvFhbW2tM04TExNU3bN/A9AHQAkYfoMtgGs8HuQ1tnWytgZj\n1TFWH5cHYy05UepiZmYOtVr1pA4GABhUqkrY2Ng0aj9EP1ryedTncRtV909CCCHkeXl6euLKlSu1\nltvY2OicdS08PBzh4eHNHRoh7VK9nSQODg5wcHAAAJiZmaFPnz5cdmRt31Brm3IqMTERXbt2RVFR\nETfUKyQkBIcOHUJAQABiY2OxevVqAMCUKVPwFk2dSMhzWbt2LdauXQsASEhIwIYNG7R3kABAZfUP\nWQDcAAyGuZkxiorzUfVfhKpGQUMAiwGYAcgFj2cIgYCHf7z5Joz4Kiz4xzx8sC4CPJ4KgBpdXcR4\ncfjfIPjfQTQIDIB5b8zCF9vHgrGhqKy8DGt+If4pMIKThweUXl748UlZJpFA1r8fLl25AsAAanUl\n5r3xJoz4ajzp5WkQgbEBZoWGYFfUt+DzAcaUGOE7HO6u4pong7RSXtJe8JL24t435/Ooz6MSQMx3\n3+k7DEIIIYQQ0kiNStx69+5dXL16FT4+Pjh//jy2bt2KPXv2YMCAAdi4cSOsrKyQnZ2tMQd39ZRT\nAoFAYyoqkUjEdbYoFAo4OztXBWRoCEtLS+Tn59M3u4Q0kTqHWHJ9naVwFD7E7NdeRz+ZDIePHMHZ\nc+fQ2cwMQXI5zM3NcfSnn5CdkwOzzp1hY92vqiO0Rw84P2nbUokEWzZuQOrvv6Nz587o5+UFA4O6\nZ7gZMXwYundzxR+3b4Oxqv3YWFuj7wsvaMTN4/GwaMF8XL9xAw/z8zWO21gvv/QSevfqhTt370Jo\nbw+pRPJM+yFElyhK2koIIYQQ0iY1uJOkuLgYU6dOxebNm2FmZoawsDCsXLkSAPDee+9h8eLFiIyM\nbLZACSHPxtfXF76+vjrX65qBY9KECZg0YYLGsrmzZtV7PHt7ey67ekO5ODvD5UlHaV14PB5e8PRs\n1L516ebqim6urk2yL0IIIYQQQkj70KBOksrKSkyZMgUzZszgsibX/CNozpw5GD++appPbVNOicVi\niEQiZGVl1Vpevc29e/fg5OQEpVKJwsJCraNIYmLWcD9Lpb6QSnX/4UeIvrWV3AmEEEJIUykrK4Ov\nry/Ky8tRUVGBiRMnYt26dcjPz0dgYCAyMjLg6uqKmJgYWFlZAahK+L9jxw4YGBhgy5YtGD16tJ5r\nQQghpCOrt5OEMYbZs2dDIpHgnXfe4Zbn5OTA0dERAHDw4EF4Pvl2d8KECZg+fToWLVoEhULBTTnF\n4/FgYWGBxMREeHt7IyoqCvPnz+e22b17N3x8fHDgwAH4+flpjUUuX/ncFSakpbTkXN6EEEJIa2Bs\nbIxTp07B1NQUSqUSQ4cOxblz5xAbGwt/f38sWbIEH330ESIiIhAREaE14X9aWlr909cTQgghzaTe\nTpLz58/j22+/xQsvvACZTAagKinkvn37kJycDB6Ph27duuGrr74CoDnllKGhocaUU9u2bcPMmTNR\nWlqKMWPGICAgAAAwe/ZsBAcHw93dHba2tjSzDSGEkDZtslyu81E2Qto7U1NTAEBFRQVUKhWsra0R\nGxuLhIQEAEBoaChGjBiBiIgIrQn/k5KSNPLbEUIIIS2p3k6SoUOHQq2uPXPEyy+/rHMbXVNO9e/f\nH9evX6+13MjICDH0YZIQQkh7wQOCgoOxLypK35EQ0uLUajX69euHP/74A2FhYZBKpcjNzYVQKAQA\nCIVC5ObmAoDOhP+EEEKIvjRqdhtCCCGENIABUFZeru8oCNELPp+P5ORkFBYW4qWXXsKpU6c01vN4\nvDpnXdO2bk2NL9N8pVL4SqVNFzAhTYzy0hHStrWpThIBDtW5vhKCFoqEEEIIqYMKMDYy0ncUhOiV\npaUlxo4di8uXL0MoFOL+/ftwcHBATk4ONwGAtoT/IpGo1r5WyuUNPm5FRQUePcqHlZU1jKgdEj2g\nvHSEtG2UFasNKCsrxa1babh/P0ffoRBCCGkIBnrUhnRIeXl5KCgoAACUlpbi+PHjkMlkXJJ+ANi9\nezc3W+KECRMQHR2NiooK3Llzh0v4/zTf//s/LNixA2dTU+s8/vXr1zBnzky8++5CzJ4diosXE5u4\nhoS0H1u2bIJCkVV/QUI6mDY1kqQjysi4i9WrV0KlYlAqKzBixEjMmfNGncNUCSGE6BclbSUdVU5O\nDkJDQ6FWq6FWqxEcHAw/Pz/IZDLI5XJERkZyUwADdSf8r+nXtFv4Ne0OIk/8jPdemYqlkyfXKlNa\nWor169ehrMwAVR9xldiyZRM+++xLWFpaNXPNCWl7zp07j/Pnz+GDD9aiZ89e+g6HkFaDOklauY0b\n16O4WAmgEwBjnDlzBv369Uf//gP1HRohhBBCiAZPT09cuXKl1nIbGxucOHFC6za6Ev5rMgPAQ4VS\njTUx/8a8gACYm5holPjzz1zweNUdJABgCD6fh+zsbOokIUSrzmCsBJ99thlbtmzTdzCEtBr0uE0r\n9+BBLsDlWuFBqeRR1nfSIGVlZRg0aBC8vLwgkUiwfPlyfYdECCGEPCMVAAaAD0MDAxQ8flyrhI2N\nDZTKyidlAUANpbICdnZ2LRgnIW0JDwAfJSW12xMhHRl1krRyQqEDgMon7xgMDRnEYmd9hkTaCGNj\nY5w6dQrJycm4du0aTp06hXPnztUqN7kRyfAIIQ1DM9sQ0sR4jwEUAyhDF3NzONnY1Cpibm6BWbPm\noFOnSpiaqtGpUwWCgl5Fly7USUKIdioAlejb10vfgRDSqtDjNq3c4sVLsGrVe1AqlVAqKzFypD9k\nsgRvQZoAACAASURBVH76Dou0EaampgCqMv2rVCrYaPlQCVR1lFAOBUKazqzgEHyzayfXBgkhz8kc\nQIkatiadcOz9lTDga/+ez8/PHx4ensjOVkAodICTU+2Zcggh1YrRu7cEYWFv6zsQQlqVekeSZGZm\nYuTIkZBKpfDw8MCWLVsAAPn5+fD390fPnj0xevRoLpM5AKxbtw7u7u7o3bs3jh07xi2/fPkyPD09\n4e7ujgULFnDLy8vLERgYCHd3d/j4+CAjI6Mp69imOTu7YNu27Vi1ag0+/XQrZs2aQ0lbSYOp1Wp4\neXlBKBRi5MiRkEgktcrQcDJCmp4RGF6dOUvfYRDSfvAACABfqRQ9HBzqLCoUOkAm608dJITUIybm\nINas+RcMDel7c0JqqvfvI4FAgE2bNiElJQUXLlzA559/jt9++w0RERHw9/dHWloa/Pz8EBERAQBI\nTU3F/v37kZqaivj4eMybNw+MMQBAWFgYIiMjkZ6ejvT0dMTHxwMAIiMjYWtri/T0dCxcuBBLly5t\nxiq3PUZGRujWrTvs7Oz1HQppY/h8PpKTk5GVlYUzZ87g9OnTOstGx8TgRkpKywVHyDO4kZKC6JgY\n7tVadQdQ9VcdIaRJMMAUnTCkV0vMwDG2AS9CCCHtVb2dJA4ODvDyqnpOzczMDH369IFCoUBsbCxC\nQ0MBAKGhoTh06BAA4PDhwwgKCoJAIICrqyvc3NyQmJiInJwcFBUVwdvbGwAQEhLCbVNzX1OmTMHP\nP//c9DUlpAOztLTE2LFjcenSpVrr1E/+nSaXw0MqbdnACGkkD6kU0+Ry7tVa/Qagc2eTessRQhqm\nU4khxvUbgH+8/LK+QyGEENLONWqk/d27d3H16lUMGjQIubm5EAqFAAChUIjc3FwAQHZ2NsRiMbeN\nWCyGQqGotVwkEnGztCgUCjj/P3t3HhZV2T5w/HtmwwVwFxRQXFACF1wy01xScU3Tn4maueRS2Vtp\ntmiW61uK2fJaZouZmZlL5pplZqWWpZhLGZhSbjgoZuSCwKzn98fIKAEywDADeH+uay6ZmWfOcx+Y\n2zPznOfcT4ijGKlOp6NSpUqkpqYWbc+EuMVduHDBeRlcRkYGX3/9NS1atMi17arlyz0ZmhBlXgYa\nln+wxNthCFFmnHr3XT6eMDHPWiRCCCGEu7h8AVpaWhoDBw5kwYIF+Pn5ZXtOURSpkyFECXP27FlG\njhyJ3W7HbrczfPhwunbtmqOdFGwVwv3Wr1nl7RCEKFOq/euzpxBCCFFcXBoksVgsDBw4kOHDh9O/\nf3/AMXvk3LlzBAYGcvbsWWrWdNTLCAoKIikpyfnaM2fOEBwcTFBQEGfOnMnxeNZrTp8+Te3atbFa\nrVy6dCnXVThuvP68SWSkXBogSrT4+N+Ij//Na/03bdqUAwcOeK1/IYQQQgghhCht8p2zqKoqY8aM\nISIigokTJzof79evH8uWLQNg2bJlzsGTfv36sWrVKsxmMydOnCAxMZE2bdoQGBiIv78/e/fuRVVV\nli9fzr333ptjW2vXrs31bDeQ7Tp0GSARJV1kZBNiYoY4b0IIIYQQQhSUO1cbFULkL9+ZJLt37+bj\njz+mWbNmznoGc+fOZcqUKcTExLBkyRJCQ0NZc22WR0REBDExMURERKDT6Vi0aJHzUpxFixYxatQo\nMjIy6N27Nz179gRgzJgxDB8+nLCwMKpVq8aqVTJNWQghROm17euv6R4dnW+7Q4cO8Msvhzh//jw1\natSkRYuWNG8e5YEIhRBClBZZq41GRUWRlpZGq1atiI6OZunSpURHR/Pss88yb948YmNjiY2Nzbba\nqNFopFu3bhw7dgyN1PQRwiX5DpLcdddd2O32XJ/bvn17ro9PnTqVqVOn5ni8VatWHD58OMfjPj4+\nzkEWIYQQorR7Z/FiqtWoQauovAc8Nm/eyOrVqzCbVcAG2Pj662088MBwevWSJUaFKAtUVWXNmpV8\n/vlmVNVO585dGD16LBqN1tuhiVIkMDCQwMBAIOdqozt37gQcq4127tyZ2NjYXFcbjYuLo23btt7c\nDbeyWi0YjUb0ej21atWW+pjCrVwu3FoSWOifT4stHolDiLJEvooJUTxenDMnz8LIqqqycuXHWK3l\ncVz5qgJXsVgUVqxYTs+eveUDnxAlWH8sLrV77Jvv+PzzzzGZ9ADs3LmLSpUqM2jQYJden5DwG++9\n9y5paVdo3jyKceMeoVy5coWOW5R+rq42euOASNZqo2XFxYv/MG3a81y6dAm73UaTJk155pkpaLUy\n+CjcQ+ZcCSGEEG6W3/CGzWbDZrPf0FIh65BstVpQVbUYoxNCeMq+fXGYTODIbw0mk+MxVyQnG5k7\n90WSk1O5fNnGnj37WLhwQXGGK0q4oqw2WpYG3t95ZxEXLlwkM1OH2ezDb78l8NVXX3o7LFGGlKqZ\nJKVNcvJRjMa91KpVm+DgEG+HI4QQwkPs4JwanRudTkdERCS///4HNpsOx+U2VrRaDZGRzeS6cSHK\niMqVK6PRwPUr11UqV67s0mt/+eUQdruOrI/rFouG/ft/LpY4RclX1NVGg4KCcmxzzQ3L1UdGNiEy\nskkx74V7nD59CptNS9aJBrPZzvHjx70blCh2nlw5tFQNkthsVrTa0hHyl1++xYoVz6PVarHZzMTE\nDKFfv/wuFxJCCFFWvH1t9YG8PPPMZN56600OH/4Vi8WCXl+O5s2jGD/+MQ9FKIQoboMGDWHfvjjM\nZguqCjqdwogRo1x6rY+PD9nHS+0YDIbiCFOUcPmtNjp58uQcq43ef//9TJo0CaPR6Fxt9N9K6+qL\nwcEhpKb+jt3uSBCDQUNoaKh3gxLF7t8DeWvXri62vkrHiMM1U6dGM2vW55QrV9HbodzUpUvn+fjj\n57BY9DimV+r55JOPSUw8RqNGjenVqzc6nd7bYQohhCgmedUiuVGFChV55pkpHohGCOEOv/66nbfe\nmkBaWgrtGjXmkycfpoa/f65tfzcaWfrNtxy1w6RJT5OcnIzdbqd16zZUr17dpf7atWvPunWfkZp6\nCavVjsGgMHTocHfukigl3LnaaFnwyCP/Ydq057hyJQ1VtdO4cTg9e/b2dliiDFHUUnLhsyOx76F3\n70aMGhWbRytPF27NveTl8eMHmTWrOxkZ4CjGl4Fj8rUeg0FDo0YNeOGFmTKd+hYTEzPAo3UGkpKS\nGDFiBOfPn0dRFB566CGeeOKJbG0URcEsK0uJUswQE+Px+h2hoaH4+/uj1WrR6/XExWWvL6Aoyk0H\nSSzIILko2YpyvMrr2JOamsrgwYM5deqU88tc1mUnc+fO5YMPPkCr1fLGG2/QvXv3bNtUFAWDTk/L\nevVY/fRT1KpSJUe/G9yaVzk/3509m8izz3bCZHoXaIleG0tUvT3snvN8jraHT5+m4/MvkG5yfAr0\n8VGZNm0mjRqFFziS9PR0tm3byqVLF2nevAVRUS0KsT/C2zz9GdAViqJQsaIvzZtH8cgjj1KuXHlv\nh4Rrywk4vu9ZLBaSkk5jMBgICgouU4NAwjXFmVel7Ft6X/bu/crbQQDw/a4d/O+/PVn0SgynTv2a\n7bnAwAaoqh2w4jg8WoGKgA9ms47ExETOnEnKuVEh3Eiv1/P6668THx/Pnj17eOuttzhy5Ii3wxKi\n1FMUhR07dnDw4MEcAyRC3OryOvbExsYSHR3NsWPH6Nq1K7GxjhNeCQkJrF69moSEBLZu3cqjjz6K\n/XoBDyezVWFP4jE6TZuW6/PF7ciR3UA3oCtQBYvtJfb/GY/Zas3RNnbdumsDJD6ADyaThlWrVuVo\n54oKFSrQv///MXLkaBkgEW539arCvn0HeOON/3k7lALT6/XUr9+A4OAQGSARblfKBknWoKo5D0ae\ntm3rF2xe/A5jDn9Lt7iNvPRCJ5KTjzqfr1DBn2efXUv58hr0+sx/vVpBo9FiNps8G7S45QQGBhIV\nFQWAr68vt912G8nJyTnaBTz4oKdDE6LUy+/MxcAhQ7DZbB6KRoiSI7djj9FoZNOmTYwcORKAkSNH\nsmHDBgA2btzI0KFD0ev1hIaG0rBhwzwGH8sDBpIu/E3S3397aG+u8/WtjKL8iWNmMMBJDDoD+lyW\nHL2SkYmabY0rhczMDE+EKUQBabBYdBw8uN/bgQhRouRbk2T06NFs2bKFmjVrcvjwYQBmzpzJ+++/\nT40aNQCYM2cOvXr1AvKeMrl//35GjRpFZmYmvXv3ZsECxxJmJpOJESNGcODAAapVq8bq1aupW7du\nrrEoyp+0aTOg6HtdRNs3rmexycTtAKhcMKdz9rsXeHTYMGeb/k1g8pJ3WZp6mRdfnMVff13CZtOg\n0dioWNGXOnVCvRS9uBWdPHmSgwcPcscdd+R4LvPqVRo/+ihHFy3yQmRClD6KotCtWze0Wi0PP/ww\n48aNy9HGbrfz+COPcGrx4hzPbXBjLP2xuHFrQrjXjceelJQUAgICAMeKHCkpKQAkJyfTtm1b52uC\ng4MxGo15bFGDqlrwLVeuCFHlP52/fy5Z2qelle9DzBw+3RezpQUG3VpeHjE81zPYIzt3YldCAukm\nx4k9Hx+Vzp3vLkLMQhQnOwaDj7eDEKJEyXeQ5MEHH+Txxx9nxIgRzscURWHSpElMmjQpW9sbp0wa\njUa6detGYmIiiqIwfvx4lixZQps2bejduzdbt26lZ8+eLFmyhGrVqpGYmMjq1auZPHlynlMSGzVq\nyLBhM4q4y+6gZpuCo1XVXM8q6nU6atYMYPbsObz77iJOnTpJUFAIjzwyXqqTC49JS0vjvvvuY8GC\nBfj6+uZ4PhrYdOGC5wMTopTavXs3tWrV4q+//iI6Oprw8HA6dOiQrY0GOHvpEmmZmUX8QidE6ZSW\nlsbAgQNZsGABfn5+2Z5TFOWm0+Nzf84CmLindWuq/Wt7nqDX6fhm1mRW/fAD5y6m0j78UdqH515j\nZOCdd3I5I4N56zdwxa7Sq1dvoqN7eDhiIVxhwmCA4cNvPqtYVVV++eUgFy5coEGDhtSrV99D8Qnh\nHfkOknTo0IGTJ0/meDy3QYHcpkzu3buXunXrcuXKFefSUyNGjGDDhg307NmTTZs2MWvWLAAGDhzI\nY4/lvfTh7NlbSsQ1Z5179+WRNSuZYTJxDljm48P2zp3zbF+5cmUmT57qsfiEyGKxWBg4cCAPPPCA\nc1m4fzt27d/Za9bQKTKSTpGRngtQiALaGR/Pzvh4r8ZQq1YtAGrUqMGAAQOIi4vLMUiSNSE/dt06\nops3l7wSJZq78yrr2DN8+HDnsScgIIBz584RGBjI2bNnqVmzJgBBQUEkJV2v03bmzBmCgoJybLO8\nwUpUaBjN6tZlZ3y8V3LKoNMx4iaf9270YJcuPNili5sLyorSIj7+N+Ljf/N2GPny8QGbzcq+fXtp\n1649FSrkXEFUVVVef/0VDh06hKo6ZnONHj2WLl26eSFiITyj0EsAv/nmm3z00Ue0bt2aV199lcqV\nK+c5ZVKv1xMcHOx8PCgoyDmV0mg0EhIS4ghGp6NSpUqkpqZStWrVHH2WhAESgF739KNc+fIs3/EN\nvhUqsHnwYCJu2D8hSgJVVRkzZgwRERFMnDgxz3YngYBKlZgeE+Ox2IQorH8P5L24dq1H+09PT8dm\ns+Hn58fVq1fZtm0bM2bkPsOxcoXyvHj//R6NT4jCcGde5XXs6devH8uWLWPy5MksW7bMOXjSr18/\n7r//fiZNmoTRaCQxMdF5Uu1Gz957LyO7dCG4WrV8Y/jjj2MkJMTj71+Ju+7qgE7n/oGKk+fPk5ya\nSuOgIK/MbBElW2RkEyIjmzjvr1272ovR5M1ksgHlOHz4d/73v9eYOnVajjZHjsRz8OBBTCY9XKu1\n8/7779KxY2d0ukJ/lRSiRCvUO3v8+PFMnz4dgGnTpvHUU0+xZMkStwaWG7vdzrp189i8+X3M5jSq\nV6/DxInv0KBBq2Lv+0aKotClW3f6d5PrS0XJtXv3bj7++GOaNWtGixaOivhz586lZ8+e2dpp9HqS\ncqmbIITIKSUlhQEDHLWxrFYrw4YNy7FcaZakxe97MjQhSoS8jj1TpkwhJiaGJUuWOJcABoiIiCAm\nJoaIiAh0Oh2LFi3K9aRY8mef0e6LL/j+5Zepe60mXm527vyOxYvfxWbTotPB1q1f8uKLc9w6UDLv\n00/534YN1NPrOWm3s+LZZ7m7SZP8XyhECTMAC1uxkmH15bfffs21zcWLl9BodOAsRuwoVpyRkY6f\nn79nAhXCwwo1SJI1RRJg7Nix9O3bF8h9ymRwcDBBQUGcOXMmx+NZrzl9+jS1a9fGarVy6dKlXGeR\nAMya1YMjR/YBDYEXSEmBmTPvYcGCn6laNefUTCG8ydtTLe+66y6Xlkm8uGKFB6IRomyoV68ehw4d\nyred+doXQCFuNTc79mzfvj3Xx6dOncrUqTe/LHm+3U7F9HQWbt7M/NGj82y3ZMlizGY9oMVmUzEa\nzxIXt5d27e5yeR9u5uDx47y9cSM/WSzUtFjYBQyfP5/TS5ei0ZSyRSPFLW8pMACV7zBRrlz5XNs0\nbNgQm82M42ujFkWxUKVKNXx9ZQaVKLsK9b/52bNnnT+vX7+epk2bAo4pk6tWrcJsNnPixAnnlMnA\nwED8/f3Zu3cvqqqyfPly7r33Xudrli1bBsDatWvp2rVrnv0ajacAK/AtMBgYjNXahoSEXYXZDSGK\nVWRkE2JihjhvQgghhCi8IFUl7erVPJ+32+2YTJlc/3irYLfDlStX3BbDsbNnuV2jIet0YUfAZLHw\nz03iEqIkCwK0Whtjxz6U6/M1awYwadIzVKgAinKFWrWqMm3ajBJTBkGI4pDvTJKhQ4eyc+dOLly4\nQEhICLNmzWLHjh0cOnQIRVGoV68e7777LnDzKZOLFi1i1KhRZGRk0Lt3b+eU/zFjxjB8+HDCwsKo\nVq1anivbAGg0WdfC/QXUAlQU5RzlyuVcsUMIIYQQQpQNe4A3DAbebN8+zzYajYbGjW8jMfEENpse\nsKEoViIi3Ffk9bbgYPbY7SQBIcBXQAUfH6pUzFnwUoiSbjOwUavl8cefpF27vHOrZctWfPjhx1it\nVqlDIm4JiprbMjUlkKIojBmzkKVLZ2G3+wLDgd0EBV1k/vyd6HQGYEuO16Wnp/Pxxx9x4sRxQkND\nGT58ZK6Vm12hqirff7+L3bsP4udXnvvue43AwIb5vCpnTOLWFBMzINdVobxJURS5LECUaoaYmBKZ\nV6AnOLgBk54YTb3Q0GzPW8h9panikJqazLJFYzmT9BuBtRox6j9LqFGjrsf6F6VTTIyhROWVoiiE\nV63K04MHM+Lu3OvBZa0ic+XKZV577RWOHv2dihUr8sgjj9Kq1e1ujefLzRtZu2oFATodqSg8OXUa\njRvnvhywEFByPwOGBwUzeOzD2YrMelcfF9rIdyvhUJx5VaqGAnv0eAg/v6p8/vnbZGZu4vbbezJw\n4HPXBkhystttzJo1jaSkc1itcOqUo2r6vHmvoNVqC9z/559/zpo1OzGZnkFRTrJvX2deffUnqlcP\nKequCSGEKFPCOXMmg+enz2XhgliqVqni8QisVgvzZnSh/1+nGWy3svnSX8yZ1ol5bxzBYMj92nMh\nSqpf33knz+dsdju/H0sgM9NEWFgjZsyYDcD58ylcuXKFzMxMypUr57ZYevW9l3YdO3Hx4kUCAgLy\nrOUgREk3+/U3vR2CECVSqRokAWjX7j7atbvPpbZGo5Hk5LNYrY7LdKxWlZSUFJKSThMaWq/AfW/c\n+CUm06dAE1QVzOa/+OGHVfTv/0yBtyWEEKIsexPoi83envj4eDrc5Z6ikQVx9uwx7JfOM91uRQHC\n7TbWZVzh1KnDhIXlXGJViNLIbLXSfdZsDpw6jaJo0GoV/vvfOXz55Xa+++57dLoAdLq/mTFjKnXq\nuG8WVaVKlalUqbLbtieEEKLkKFVluI8fP1ig9o4pzzmn4BS20JCjWruP876qGrDZrIXalhBCiLLs\nL7JqaBl8fPJrXCx8fCpwxWYl49p9M3DJbsPHR856i7LjvW3bOHjiNJmZOjIytFy9amX+/Fh27kzA\nYjlIRsZPXLkyjVdffcvboQpR4iQk/ObSSohC3GpK1SDJ9Ol9iI/f6XL72rWDqFOnDnq9FbCg11sJ\nCgoiJMRxeczBg/uJjX2JV155mcTEY/lur1u3u/HxGQN8A7yPXv+py7NahBBC3EpGA7UJqHmFFs2b\neyWCGjVCad6qD/f6VGAh8H+G8tQJb09ISEm59lyIojuWfJYMsx3HoCSoqpbU1L+xWrsCla616s/5\n86ezvU5VVQ4c2M8XX2zmt99+9WjMQpQUsfNeYm7si9jtNm+HIkSJUqoutzGbY1mxYi5z5nRyqb1G\no2HatFmsWbOS48ePExpajyFDhqLRaNm3by8LFryO2awBVA4dOsDMmbNp2LBRntsbMmQQvr5b2L37\nRfz8ynP//VuoVSvMTXsnhBCi7LjC0MFR9OvTG4Mh97pZxU1RFB6e+DHffruUH48foFGdJkRHPyTL\nNopSaeDLL/PUvffSrnHjbI+3aRTGRzt3kW5yzBzWau0EBQVz5sw32GwXgcrABmrWrJPtde++u4jd\nu3djtytoNHb69LmHIUOGeWhvhCgZMvWZHDkaz48//shdd3XwdjhClBilapAEAsnMLNg69OXKlWPE\niAdzPL5+/TrMZi1cq4ZuNpvYsuVzJkyYlOe2NBoN/fr1pV+/vtceaVGgWIQQQtwa1peQVaM0Gi3d\nuo31dhhCFNnmnw/y+c/7+fSZp+l3+/XVaoZ16MBPvx/lg+++Q6vVEhgYyJQpz7NixRq+/74ZilID\ng+ESTz31gvM1Z84k8cMP32M2++CYgWJn06aN9OrVR+qMiFuLAmabmT/+OCaDJELcoFRdbqMoY0lN\nTWbevGFcvJhSpG3ldv2dXJMnypLRo0cTEBBA06ZNvR2KEEIIUUQVUdHy6LvvZXtUURTeemgcixcv\n5Y033uLll1+7dinNj4AJqzUJi+UyFy9edL7m8uXL6HSOov4OGnQ6PVeuXPHY3ghRItgBCxw+fNjb\nkQhRopSqQRIYQXr6Cg4dCmTmzH6FLJraB+hDnz7TMBgUwAKYMRg09Ogxy/m8azchSq4HH3yQrVu3\nejsMIYQQwg0UQEO6yZTrs76+vlStWg2NRsOXX24hLc2MzVYOKI/FouPDDz9wtq1Tpy6qeu3bISpg\nxsfHQEBAoAf2Q4gS5AqgKlitFm9HIkSJku8gSW5no1NTU4mOjqZRo0Z079492+j83LlzCQsLIzw8\nnG3btjkf379/P02bNiUsLIwJEyY4HzeZTAwePJiwsDDatm3LqVOn8oxFVacCzbDZZvP33/9w7twf\nBd1fpw4dhvLII+/QqFFzbrvtdp59di0RER0LvT0hSpoOHTpQpUqVfNsZYmI8EI0Qt5YBMTHsP3TI\n22EIUYbYAAvRUfkXQk5Lu4rdfuPqhhoyMjKc93x9fZk2bSbVqlVAUa4QGFiFGTNmo9fr3R+2ECVa\neUAlODjY24EIUaLkO0iS29no2NhYoqOjOXbsGF27diU2NhaAhIQEVq9eTUJCAlu3buXRRx9FVR0H\nqfHjx7NkyRISExNJTEx0bnPJkiVUq1aNxMREnnzySSZPnnyTaLJGOTOx269iMBRtGcO77hrMiy/u\nZNas7TRr1q1I2xKitKqEDJQI4X7leXHOHDIyM70diBBlgsJVOkbcxvIbTrTl5Y477sBRL9kK2DAY\n7LRt2zZbm4YNw3j77cWsWvUZb7zxFsHBIcUStxAlWwYajY6WLVt7OxAhSpR8B0lyOxu9adMmRo4c\nCcDIkSPZsGEDABs3bmTo0KHo9XpCQ0Np2LAhe/fu5ezZs1y5coU2bdoAMGLECOdrbtzWwIED+eab\nb24SzQDgPeAeKlTwo1w53wLurhDi32QRayGKwx0AGI1GL8chRNlw7K2FfDV9OgZd/msONGsWxdix\n46hSxQdfX4XOnTsxbNiIXNvKak/iVqbVlqdSJX/atm3n7VA8KjMzg927v2fHjm9JTU31djiiBCrU\n6jYpKSkEBAQAEBAQQEqKo4hqcnJytpH64OBgjEYjer0+2zSuoKAg5wdHo9FISIhj9F6n01GpUiVS\nU1OpWrVqLj0fB/YDfbh0aRPjx0cyb94OgoLCC7MbQghgy7V/Z69ZQ6fISDpFRno1HiFuZmd8PDvj\n470dhguOAVCpUiUvxyFE2dD8yVlU8yvH1zOfof61z6A307lzFzp37uKByIQofqNHj2bLli3UrFnT\nWWQ1NTWVwYMHc+rUKUJDQ1mzZg2VKztWZ5o7dy4ffPABWq2WN954g+7du+e63T59etKvX38qVqzo\nsX35N7vdzh9/JGIymWjQ4C4qVMj7uKmqKpcvX0SvN1ChQoVC9ZeWlsbkyU9z5cpVVBU0GjuzZ79E\n3bqhhdwDURYVuXCroigeHIVvBbwDTAKex2yuxcKFT3iobyHKprRr/06PiZEBElHidYqMZHpMjPNW\ncl1EUXTUqF7d24EIUSakm49hTB1DzCtvZ3v8859/ptXTz/DEE//hyy+3OC/zFqIsKWr5g7xW8Hzg\ngRH4+/sXe/x5sVqt/Pe/8/jvf9/llVe28PjjLUhOPppr27S0f5g6tT3jxz/EmDEjWLz43ULl++bN\nG/jnn8tkZmoxmbRkZKi8//57+b9Q3FIKNUgSEBDAuXPnADh79iw1a9YEHDNEkpKSnO3OnDlDcHAw\nQUFBnDlzJsfjWa85ffo04EiUS5cu5TGLBOAHoAYQBawD6nDmTEJhdkGIYhcf/xtr1qxy3jxt6NCh\ntGvXjmPHjhESEsLSpUtzbZcGmNes8WxwQpRxvuVV1q3+xNthCFGm2NXRHDnzp/P+t4cPE/PKqxw+\nfYpz586ydOkSrxxvhShuRS1/EBcX5/GYXbF9+zYSE8thMsWRkbGNtLTHeOut3OsOvffefzh1tMD/\ncwAAIABJREFU6nes1vLYbBXZtWsnO3d+V+A+L1z4G6s1e2Hnf/75p5B7IMqqQg2S9OvXj2XLlgGw\nbNky+vfv73x81apVmM1mTpw4QWJiIm3atCEwMBB/f3/27t2LqqosX76ce++9N8e21q5dS9euXW/S\n83TQ6cFwCvgUqIpGU6grhoQodpGRTYiJGeK8edrKlStJTk7GZDKRlJTEgw8+mGs7GSARwv2WXzuu\nCSHc6TtqV63lvPfy+g1Y7XbAD/AHfNi4cb23ghPCo25W/uDGMgdZ5Q8KKj09nbi4PcTF7c22OpQ7\nJSefx2zuCjhWllLVbqSkHM+1bWLiHqxWcCwHrmAyqfz++5EC99m8eXN8fBTADqjo9SpNmzYr5B6I\nsirfEYahQ4eyc+dOLly4QEhICLNnz2bKlCnExMSwZMkS5zVwABEREcTExBAREYFOp2PRokXOS3EW\nLVrEqFGjyMjIoHfv3vTs2ROAMWPGMHz4cMLCwqhWrRqrVt3sDMBPoDFDORXMVmAjQbVro8cxcmpB\nlm4ToqTaIPkphIN+g7cjEKLYFFfthEoV7sFuj+fjCU85H0vLzMDxUTbrnJ8Bq/UydrsdjabIV5QL\nUWrkV/4gr+dunHkVGdmEyMgmgCNnn3vuGTIyzABUqOBDbOwrzrx1l4YNQ/HxWYvJNArwR6ddxu11\nA+lPzuPkghp+/Jj6N6qqxTG4oSEwsFaOdvnp0KETRqORTZvWo6oqzZu35sEHRxd5X0Txi4//jfj4\n3zzSV76DJCtXrsz18e3bt+f6+NSpU5k6dWqOx1u1auU8WN7Ix8fHOciSL2UzlLOBc4aUlfv+7948\nm584cZwTJ45TvXp1mjZtLhXMhRBCeMTWbdvomceXPSHKsgcffJDHH3+cESOuryaTVTvh2WefZd68\necTGxhIbG5utdoLRaKRbt24cO3Ys1wGOjyd2pGX9UdS4oX7CA506EffHUhwfDBXAiq+vnwyQiFtC\nVvmDwMDAfMsfBAUF5bqNvGY6f/zxh1y6lIHdbgDAYknnk0+W8+ijj7t1Hzp06MSRI3+yc2ckquqD\n3ZbJzsNX6TtjBh898wxVfK+vZPrOIw/T6YVpZNhsqKpK7dq16N27T4H7VBSFoUOHMXjwUFRVRavV\nunOXRDG6cSAPYO3a1cXWV+k6iqgayATS9EA5opqFc8ftt+fa9Ouvv2LatKksXbqMV155mYULF0gx\nLyGEEB7x3vtLGBATI8cdccsprtoJPaKisg2QADzcvTv9bm+FVnMVrTYDg8HG5MnZT9R9//1OJk2a\nwMSJj7N9+zZ37aYQXlfQ8gcFkZJyHrv9+sllm01xXs7jToqi8PDDY5gw4VGqaa6wh6skA7UTE3n0\nzTeztW1cuzZH3ljAhAkTePbZZ3nxxVgMBp9C963RaGSAROSplBX0aAPmX4HygJVGjcJybWU2m1m6\ndAlWqw+gBTTExcWRmHiURo3u8WC8QgghbkXlUUkHlq9YwYgHHvB2OEJ41c1qJ7Rt29bZrqC1ExRF\nYe0zz/DrqVNsvJxO3bqh2VbqiIvbw7vvvoPZrAEUli37EJ1OJ0sDi1LHXeUPXNWkSVNOnUrCbHYM\n9BsM0LRpU7fvV5ZTp04y3GKm0bX7z1qtdPz99xztqvj60rJl62KLQ4gspWyQ5HWgC9AZWE+b1q1y\nbZWefvXafwZZy13ZUBQtFy9e9EiUQgghbm2N0XIQG7/kcpmpELeywtZOmH3DpdmdIiOzLVnfrG5d\njudS92r79q8xmxWyikKaTBa2b/9aBklEsXN37QR3lT9w1aBBMZw9m0xc3F5ApXXr9gwYcF+ht5ef\nypWrcMhgQDWbUYBDQKCfX7H1J0R+StkgSRJgAR4ADpOamkqD+vVztPL3r4RO54PFUgF4HPiVzMzP\nqVWrtmfDFUIIcUtKxAZAo7DcZzwKcStxR+2E6TExBe7Xx+ffU/FVDAZDgbcjREF5snZCcdDp9Eya\n9AwmkwlFwXlZy/Hjf/Ltt9+g0ShER/cgJKROttdduPAXn3yynL//TqVFi5b063cvGk3+l7R07tyF\nH7dvo8+5s9RVVb4GVo4fXxy7JoRLStkgyVigKnAvEIHdbs+1lUajwW7XAJ8Djg+oOt0gEhOPERLi\noVCFEELcsjLQAjbGjZaK+UJk1U6YPHlyjtoJ999/P5MmTcJoNBaqdsLNDBgwkEOHDmIymQAwGFQG\nDRrstu0LUdbdOND4++9HePHFWZjNAArfffcts2e/RL16jhPWly9fZvLkp7l61YLdrvDnnyc4f/48\nDz30SL79GAwGXpgzD+XnPVxOT2d6RAQNAgOLaa+EyF/pKtzKRBwh24HfaNKkSZ4trVYTUMN5X1EC\nMTuyWgghhChWjW9rxLrVq2WVDXHLGTp0KO3atePo0aOEhISwdOlSpkyZwtdff02jRo349ttvmTJl\nCpC9dkKvXr1uWjshLjGRDXFxnDx/3uVY6tdvwH//O4fo6E507dqBmTNnc9ttEW7ZTyFuNWvWrL5W\n36cc4IPJBOvXf+Z8/sCBnzGb7ddWxNFjNmv57rvteZ7U/jedTs/Atm15sEsXGSARXlfKZpIsA84B\n5VGUK1SsUAGAvfv2sTduH77+lenb914qV65Mmzbt+fnnR7BYXgB+R6PZTFTUHGCLG+Mp+LJTQggh\nyr6XZs3K+0lLf88FIoSHFVfthI7TXqOCvjF29X2WT3yIvq3/Xbwx989koaEwbtxj+W5fiFvRggWL\nGDXqfipVqpxvW5MpE8dS21kUMjMz/9WqaCu6bciltpAQ3lDKTnFdAnwAO+XKOaZ/bdi0mfmvvc53\nO/fw+edf8vTTE7l8+RL9+vWgWbOrVK06jLp1FzBt2mQCA2t5NXohPG3r1q2Eh4cTFhbGvHnzvB2O\nEEIIUSh2+3jSTCdINy9m+IK3XT47LYTI2549DXn++dkuzbbv2rUbPj4qYAWsGAwqXbp0cz7fsmVr\n9HoNimIGLPj42Lj77q4yo1KUSkV614aGhtKsWTNatGjhvIY0NTWV6OhoGjVqRPfu3bOtKDN37lzC\nwsIIDw9n27bra9Xv37+fpk2bEhYWxoQJE27S4x4c9Y4jyMhQUFWV5Z98gs3mmPalquW4fPkqs2fP\nYObM6SQkHMRi+Ycnn3yYRo3Ci7KrQpQ6NpuNxx57jK1bt5KQkMDKlSs5cuSIt8Nyq8TEY+zZ8yPn\nzp31dihCZDMgJoYXY2NJPnfO26EIUUY8DbQDkjFbLKTlOIMthCgom60mly7pOH78j3zb3n13V4YN\ne4DAQH9q1arM2LHjaNv2Tufz/v7+zJv3Cnfe2YrGjesyYMAAxo59qDjDF6LYFOlyG0VR2LFjB1Wr\nVnU+FhsbS3R0NM8++yzz5s0jNjaW2NhYEhISWL16NQkJCRiNRrp160ZiYiKKojB+/HiWLFlCmzZt\n6N27N1u3bqVnz5659HgbjnokdwNa/rpwAbvdRvapXypnziRjt5cHFBTFzIIFrzFv3qtF2VUhSp24\nuDgaNmxIaGgoAEOGDGHjxo3cdttt3g3MTd59921++OF7NBodNpuZxx57grZt23k7LCGc9h84wP4D\nCTw76VHubNvW2+EIUQbYgT0EVqmBX/ny3g5GiDIgBZPJyJkzSYSH37xej6Io9OzZm549e+fZpkaN\nmkyc+JS7gxTC44o8/0lVs197tmnTJkaOHAnAyJEj2bBhAwAbN25k6NCh6PV6QkNDadiwIXv37uXs\n2bNcuXLFORNlxIgRztfkVAEYBCQAjkrljilc6TimfpkB27WVbZRr8ek4J2fyxC3IaDQScsNyTsHB\nwRiNRi9G5D5Hj/7ODz98j8mkJyNDg9msZ+HCBdcGTYUoAXyzfgjk1QVv5zhWCiEKahawlYBK3/H5\n80/mWeBVCFEQscCrfPtt3E1bJScbefLJJxgyZCCPPvoQf/yR6JnwhPCSIs8k6datG1qtlocffphx\n48aRkpJCQEAAAAEBAaSkpACQnJxM2xvOpGV9YdPr9QQHBzsfDwoKyvuLnHIB1I+B6vj6+lKjenUa\nhzXiyNFE4CpZAyM6nYrVqgIKGo0t2xdFIW4Vrn6AnL1mjfPnTpGRdIqMLK6Q3ObChb9QFB3XZ5Fp\nsdvtpKen4+vr583QRDGLj/+N+PjfvB1G/rRZP6Rgs1nJzMykvJz5FqLQhtx1mIl9phNVr57UOBDC\nrRpw9Wp6tkeOHv2dXbt2oNPpiY7uzuzZM7h4MRPw5cKFq8yaNZ0BA/4PPz9/2rW7i4oVK3ondCGK\nSZEGSXbv3k2tWrX466+/iI6OJjw8e90PRVHcO9LvB6SrYFWw280oisK0qc8xcsxYLFYfQI9jJkk6\nOl0GOp2OihV9eeKJSe6LQYhSIigoiKSkJOf9pKSkbAOSWabHxHgyLLeoV68+drsZR85rATN+fv5U\nrOibzytFaRcZ2YTIyOvLv69du9qL0dyEswZeQypWPCcDJEIU0UdPSG0DIdzvNBrN89x+ezPnI4cO\nHeSVV+ZhNisoCnzzzdc4Tkr5XGuhYDKZ+PTT9Wi1Gj777FPmz38NPz9/b+yAEMWiSIMktWo5Voup\nUaMGAwYMIC4ujoCAAM6dO0dgYCBnz56lZs2aQM4vbGfOnCE4OJigoCDOnDmT7fGgoKDcOzRl/XAJ\nk8kxrd5isVxbbCprySgtPj4Vuf/++4mMjCQwMBCdTpaTEp7n7TPerVu3JjExkZMnT1K7dm1Wr16d\n59KMpU3t2kE8/PB43nlnEQAVK/ry/PPTZfq1KDkyHP/otKeY+9+ZXg1FCCGEyF0b7KicPXd9dtbK\nlSswm7WAHlUFsznz2oo1ehyDJRlAOWw2AzYbXLqUzhdfbGHw4KHe2QUhikGhB0nS09Ox2Wz4+flx\n9epVtm3bxowZM+jXrx/Lli1j8uTJLFu2jP79+wPQr18/7r//fiZNmoTRaCQxMZE2bdqgKAr+/v7s\n3buXNm3asHz5cp544oncO/XBcVUNFvx8KtIHsPn68phexxWr9dru2LHZbFitYZw7F0S1ap3R6bw5\n/b6PF/sW3hQZ2Ycbr1zx9BlvnU7HwoUL6dGjBzabjTFjxpSZoq0AHTp04s4723P1ahp+fv4y/VqU\nKN27dqVf377UCgzM8d7sT151t7LbgLsG+F09Dm1xU39CuN/YtxYzf+RQqvjKjEEh3MZgB72Zffvi\n+OmnH7nzznbXlgO+8aSTQnDwbaSknMRsVq4957ymFJtN5dIlf+Q7jyhLCj1IkpKSwoABAwCwWq0M\nGzaM7t2707p1a2JiYliyZAmhoaGsuVbvICIigpiYGCIiItDpdCxatMh51nfRokWMGjWKjIwMevfu\nncfKNsDl62EP69geAK1Gw5qnnmLQK69g1xiwWExotQZWr34RRYHy5SsSG/sTlSsHFnZXhSi1evXq\nRa9evbwdRrHR6XRUqlTZ22EIkcP4hx/2dghClCkf7fyRdXsPYHx/AeUNBm+HI0TZYL4brLtA9eOj\njz7lzjvb0aVLV1avXoXZbAFU9HotI0fO54cf1vL990ZstlrAZzhWm1IxGLS0aiUDJKJsKfQgSb16\n9Th06FCOx6tWrcr27dtzfc3UqVOZOnVqjsdbtWrF4cOH8++0PM4pzA907Oh8uGuzZhxbuJD3kxuw\nZcub/PzzV9hsjgEYs/kiy5dP4fHHP8x/+0IIIUQ+tm7dysSJE7HZbIwdO5bJkyd7OyQhbgGdSMvc\nwdDXXmPDlCneDkaIMmIX2BVgNJmZSwHo2LEza9euAWyAgqqqGAwVMJtt2Gy9gCE4VhbdgKLYGDbs\nFRkkEWVOkWqSeJwBsABWM3Wv1TrJUt3fn3D/9qxcOR2b7fpSizabSkrKCc/GKYQQokyy2Ww89thj\nbN++naCgIG6//Xb69euX41K2ATcURPbz9eWRhx6iebNmzH/1VcaePEnNSpV4deRIAqtUYfO+fRxN\nTqa6nx8ZFgsh1arRIyoK6jd2buPQoYP88Uci1atXp0OHTmi1Wm5GVVV++ulHkpONhISYadOmf541\ne9LTL7Nr18ekp+8jPPw2Tp8+RXp6Os2bR9GgQUOXfzd2u43du38gJSWFevXq0arV7S6/Voj8dQPS\n+eLAPgwxo6joU4H1kx+lc5Mm+b5SCJGXDEADvMzVq1qee24m4eF1MJtVoAIAVquZDz6YSIcOw/j5\n5/WYzUOAd9FqK9GmTSa9ev3Hi/ELUTxK1yCJCcfMLhyDIrmJiOjIn38eupbcYDBoiYzsmGtbIYQQ\noiDi4uJo2LAhoaGhAAwZMoSNGzfmGCTxBdIAKM+VtLuY/9pHKFxCxQbo+PtKMr1fegmdVovVVg6o\nA/wCZKCgIXbdep6Y9DQtW7bms88+ZcOGdZjNYDBo2LVrJy+8MCPPOjyqqvLmm++wb99ZzOZuGAz/\npUOH73nooddytE1Pv8TTT7fm8uVURyF01YRO54PdDuvWrWXChCe5/fY78v29qKrK/Pnz+O23eMxm\nOwaDQs+ePRk2bITrv1whbmoqjrNlVuA+rpq602P2eI4ufJnQf504E0K4piJwFTuOwo/7OXlyIX//\nvS7bCWfQkpaWSu/e/+HIkTh++SUSjaY8NWvWZuzYjd4JXIhiVroqHVpwDpLkZeDAqbRsGY1Wm45W\nm07z5l0ZNGiaR8ITQghRthmNRkJCQpz3g4ODMRqNOdpdLxf+GHAI+AYVFcdH0vLX/gWrTQf445i+\nbAcqoFKOdLOWJUsWYzabWbt2NSaTHlX1wWTS8ccff5CQEJ9njMnJRuLiDmEybUVVZ2AybWHnzk+4\ncCEpR9tvv/2QS5f+xmzWoKoAWqxWH+x2H8xmHR988L5Lv5c///yD3377DZNJ54xzy5bNpKWlufR6\nIVxjAUJx1EP4HyoN2Lh3r3dDEqIUc6xWr+D4Stgam+1x0tKu4Cj7YwMcg94tW/ZGq9XxzDMfs2DB\nXubP38b8+Tvx86vmveCFKEalayZJRRyn5m4yUKLT6Zk0aRWZmY4PZuXKSRV0IYQQ7lHwZab34Dhw\nhQAq11cMyDpHoQC1cVQmt3J9xQAt6enpZGZmoiiaG16noCha0tOv5tnj1atpaLUBZA3EQCW02uqk\np1+8FseNbf/BYsnqVyX7uRMN6enpLu3l1atX0Wp12eLUaLRkZKTjK6uRlHjeXrLeJeUzIVMB9RyO\n92o4sIddR44xoa+XYxOilLLoAYsKjAOWAvdQqVIN7r23B6tWfYLVaqNt2/9j5Mj5gOMYWL16HS9G\nLIRnlK5BkqyBTjvs//NPWjVokGdTGRwRQgjhbkFBQSQlXZ+RkZSURHBwcI52F50/mYAoYDKO6cxm\nQE/W+TvHmfEEoCuOg5wV0FBOb6Vlyzvw8/MjMDCQ5OQL2O06wIaqqoSFNcozxjp16qLTpZD1gVdR\nPqVcOSu1auV8TVRUDzZv/h9mc9ZASca1+DTo9TZatmzl0u+lfv36OM5g2AAtGo2VypUrU62anGUs\nDSIjmxAZeb22h6eXrHeJAdCqkHYJx3s0FBjP3sShXg1LiFKtAo7DVOabOC4UPUdGhi/du/egZ8/e\nyLK+4lZVugZJLDg+PwLz9+5j+LVBEpvNxslTp7CoC6hbNxSdrnTtlhBCiNKhdevWJCYmcvLkSWrX\nrs3q1atZuXJljnYZzp9+BexUqnScrp2jWbdxE5AJQHjtIFo2aMCGuL1kmt9GwY6iseKj09KndSv6\nPvQIiqLwwgsz+d//XuX48T+pUqUKjz8+kSpVquYZY7ly5Zk16wVef/1tUlJmULt2UyZN+hy93idH\n28aN72T8+Pf48MOnMJkuUadOY1JSzmEyZdKiRSsefvhRl34vfn7+zJgxm//97zX+/vsCderUZdKk\np9Fobl5gVojCMQCNADtmRWGLt8MRojTTgCOnAoFTpKdbMJ76k/r16mHxbmRCeE2pGk3QpTvHSCjn\nYwAgPT2dl2bMIDMlBQXQ1ajBlNlzqVixYp7bEUIIIQpDp9OxcOFCevTogc1mY8yYMTmKtgKsX7Mm\n19cPHzYsl/Nyj+XadgN6AKpWrcrs2S8VKM7g4BBefXXOtXs3PxPYvn0M7dvHQBG/atarV58FCxYW\naRtC5MlK1vgi8AzwHnCGPj07eS0kIUo9O9fyyoSjNtY3wCH+PH6c+vXqeTMyIbyqVBVuDbrh565d\n7gbg01WraGY08nNmJj9nZtLm7FnWrvjIOwEKUUJ8+umnREZGotVqOXDggLfDEaJM6dWrF0ePHuWP\nP/7gueee83Y4QpR6W7duJTw8nLCwMObNm5d7o0yul+zBChwlIEDDwAH9PBOkEKWMS3mVrbb2F0AM\nMJfdP/5a/AEKUYKVmEESVxL5CRxXyzVr2pTKlSoBcO7UKfpYrWSVtbvHauXcqZOFjsMThcs8VRxN\n+inZ/RSnpk2bsn79ejp29P7y1zvj816Fw53K2vujLPVTFnKqpClL74+y1k9Z2hdPsNlsPPbYY2zd\nupWEhARWrlzJkSNHcmmou17KhwWEhdXmlbkzClFMOW/x8Tvdtq1bpZ+ytC+e7Ke4uZpXOi2OclkA\nxANdgKqYzNYcbQurrP3tJK9Kbj/uVCIGSVxN5F+4VuLuyFG2bd8OQFD9+qzV67HiKBf3qV5PUP2G\nhY5FPkBJP2Xhg2d4eDiNGuVd2NGTZJBE+ikLOVXSlKX3R1nrpyztiyfExcXRsGFDQkND0ev1DBky\nhI0bN+ZoV47rX9oahwXz8kvT3b5yUln7wiBf5kpuP8XN5byygsZZRMsH2ITB8ALRXdu4LZay9reT\nvCq5/bhTiRgkcTWR1+K4Ys5qtfH70WMADBoyhKT69WliMBDp48OxuqHcN+wBz+6AEEIIIYQoMKPR\nSEjI9aWpg4ODMRqNOdqt4/oJ7xeee8YzwQlRSrmaV4/gmKXvYKVG9fd5cERPunSWWj/i1lYiCrfm\nlsh79+7N0a4ZjnUC0rFTu1YgAD4+Pjw/axZnz53Dio7AwFpoNCVi7EeIYhUdHc25c+dyPD5nzhz6\n9u3rhYiEEEKIgnH1cpl2QEUcJ8vcPYNEiLLG1bx6Enj92s/3Dx7AoIFS40cIANQSYO3aterYsWOd\n95cvX64+9thj2do0b95cBeQmt1J769Spk4czS1U7d+6s7t+/P8/nGzRo4PXfi9zkVpRb8+bNPZhR\nrpHjldxK+82Tx6uffvpJ7dGjh/P+nDlz1NjY2Gxt5Fglt9J+8/SxSvJKbrfCrTjzqkTMJAkKCiIp\nKcl5PykpieDg4GxtDh065OmwhCgTVFXN87k//vjDg5EIcWuQ45UQrmvdujWJiYmcPHmS2rVrs3r1\nalauXJmtjRyrhCgYySshiqZEXJdyYyKbzWZWr15Nv34y3UuIwlq/fj0hISHs2bOHPn360KtXL2+H\nJIQQQuSg0+lYuHAhPXr0ICIigsGDB3Pbbbd5OywhSjXJKyGKRlFvdprZg7788ksmTpyIzWZjzJgx\nPPfcc94OSQghhBBCCCGEELeQEjGTBKBXr14cPXqUhQsXsmzZMsLCwpg3b16ubZ944gnCwsJo3rw5\nBw8eLHBfW7duJTw8PM8+VqxYQfPmzWnWrBnt27fn119/LXAfrvSTZd++feh0OtatW1ds/ezYsYMW\nLVrQpEkTOnfuXCz9XLhwgZ49exIVFUWTJk348MMPC9zH6NGjCQgIoGnTpnm2Kerf35V+3PUeKAlc\neX+443cqedXZ7X24I6fAM3l1K+UUSF7d6nklx6riIXlV8LySz4AFJ3mVU2nJq7J0rHKlH8krLyq2\naieFYLVa1QYNGqgnTpxQzWaz2rx5czUhISFbmy1btqi9evVSVVVV9+zZo95xxx1u7+PHH39UL168\nqKqqqn755ZcF7sPVfrLa3X333WqfPn3UtWvXFks///zzjxoREaEmJSWpqqqqf/31V7H0M2PGDHXK\nlCnOPqpWrapaLJYC9bNr1y71wIEDapMmTXJ9vqh/f1f7ccd7oCTwRE652o/kVcH7cEdOqapn8upW\nySlVlbySvJJjVXGQvCp4XslnQMmr/JSlvCpLxypX+5G88p4SM5MEIC4ujoYNGxIaGoper2fIkCFs\n3LgxW5tNmzYxcuRIAO644w4uXrxISkqKW/u48847qVSpkrOPM2fOFMu+ALz55pvcd9991KhRo8B9\nuNrPJ598wsCBA53FcKtXr14s/dSqVYvLly8DcPnyZapVq4ZOV7DawB06dKBKlSp5Pl/Uv7+r/bjj\nPVASeCKnXO1H8qrgfbgjp8AzeXWr5BRIXkleybGqOEheFTyv5DOg5FV+ylJelaVjlav9SF55T4ka\nJDEajYSEhDjvBwcHYzQa821TkF+yK33caMmSJfTu3dvl7RekH6PRyMaNGxk/fjzg+prmBe0nMTGR\n1NRU7r77blq3bs3y5cuLpZ9x48YRHx9P7dq1ad68OQsWLChwP4WJo7iTrLDvgZLAEznlaj83krwq\nOTmVVyzFmVelOadA8gokrwoThxyrbk7yquB5JZ8BJa/yU5byqiwdq1ztR/LKe0rEEsBZXH0jq/+q\nNVuQBChI2++++44PPviA3bt3u/yagvQzceJEYmNjURQFVVVvulRrUfqxWCwcOHCAb775hvT0dO68\n807atm1LWFiYW/uZM2cOUVFR7Nixgz///JPo6Gh++eUX/Pz8XO7HFUX5+xdUUd4DJYEncqqg7SWv\nXO/DUzkFnsur0p5TIHkleeUaOVYVjORVwfNKPgNKXuWnLOVVWTpWudqP5JX3lKhBkqCgIJKSkpz3\nk5KSnNOY8mpz5swZgoKC3NoHwK+//sq4cePYunXrTacOFaWf/fv3M2TIEMBRmOfLL79Er9cXaPlj\nV/oJCQmhevXqlC9fnvLly9OxY0d++eWXAiWyK/38+OOPPP/88wA0aNCAevXqcfToUVq3bu1yPwWN\no6B//4Io6nugJPBETrnaD0heFbQPT+RUbrEUV16VhZwCySvJq4LHIceq/EleFTyv5DPSmq4KAAAg\nAElEQVSg5FV+ylJelaVjlav9SF55kWdLoNycxWJR69evr544cUI1mUz5Fhf66aefClz0xZU+Tp06\npTZo0ED96aefinVfbjRq1Cj1s88+K5Z+jhw5onbt2lW1Wq3q1atX1SZNmqjx8fFu7+fJJ59UZ86c\nqaqqqp47d04NCgpS//777wLv04kTJ1wqLlSYv7+r/bjjPVASeCKnXO1H8qrgfbgrp1TVM3l1K+SU\nqkpeSV45yLHKvSSvCp5X8hlQ8io/ZSmvytKxytV+JK+8p0QNkqiqqn7xxRdqo0aN1AYNGqhz5sxR\nVVVV33nnHfWdd95xtvnPf/6jNmjQQG3WrJm6f/9+t/cxZswYtWrVqmpUVJQaFRWl3n777cW2L1kK\nm8iu9jN//nw1IiJCbdKkibpgwYJi6eevv/5S77nnHrVZs2ZqkyZN1BUrVhS4jyFDhqi1atVS9Xq9\nGhwcrC5ZssTtf39X+nHXe6Ak8EROudKP5FXB+3BHTqmqZ/LqVsopVZW8utXzSo5VxUPyquB5JZ8B\nC07yqvTmVVk6VrnSj+SV9yiqWoiLtYQQQgghhBBCCCHKmBK1uo0QQgghhBBCCCGEt5SpQZJRo0Yx\nbdo0AL7//nvCw8O9HJH4t5kzZzJ8+HCP9DV+/HhefPFFj/QlspNcFHnZsWNHtqXmhBBCCCGEKEnK\n1CCJoijOJYs6dOjA77//nu9rPPml3Z3MZjM1atQgPT3d26EUSHEuKfVvb7/9Ni+88ILH+hPXSS4K\nUbxkIFIAfPjhh3To0MHbYZRakkc3N3fuXMaNG+ftMEQZdGPuecKKFSvo0aOHx/pzN/m/yvPK1CAJ\n5FznuazatWsXLVq0oEKFCt4OpUSy2+3eDuGWJ7koRPGRgUghik7y6Oaee+45Fi9e7FLbr776io4d\nO+Lv70/NmjXp3LkzmzdvLmy4HqPRaDh+/Li3w7jl3Jh77nby5Ek0Gk227wLDhg3jq6++Kpb+8rNy\n5UqGDRtWpG3cSv9XlRSlepDk4MGDtGzZEn9/f4YMGUJmZqbzuX9P6Z43bx7BwcH4+/sTHh7Ot99+\ny9atW5k7dy6rV6/Gz8+PFi1aALB06VIiIiLw9/enQYMGvPfee9m2GxwczGuvvUZAQAC1a9fmww8/\ndD6fkZHBU089RWhoKJUrV6ZDhw7OuPbs2UO7du2oUqUKUVFR7Ny5M9f9mjdvHoMGDcr22IQJE5gw\nYYLz/hdffEHv3r0Bx5mkBg0a4O/vT/369fnkk09y3W5cXBytW7emUqVKBAYG8tRTTwHX/zNZvHgx\nQUFB1K5dm1dffdX5OlVViY2NpWHDhlSvXp3Bgwfzzz//OJ+/2X6dOHGCTp064e/vT/fu3blw4UKu\nsQHcdtttbNmyxXnfarVSo0YNDh06BMCgQYOoVasWlStXplOnTiQkJDjbjho1ivHjx9O7d298fX35\n7rvvso26/vPPP9xzzz3UrFmTqlWr0rdvX4xGo/P1nTt3Zvr06dx11134+/vTo0cP/v77b+fzffr0\nQa/Xo9VqqVOnDsuWLQPAZDLx9NNPU7duXQIDAxk/fjxPPPEELVq0oEWLFjRu3LjkrwPuBpKLBcvF\nmTNnMmjQIIYPH46/vz/NmjUjMTGRuXPnEhAQQN26dfn666+d7W/2e5g3bx5t27bFZrMBjhlUTZo0\nwWw25+j3woUL3HPPPVSpUoVq1arRsWNH53OhoaHExsYSGRlJ1apVGT16NCaTyfn8559/TlRUFFWq\nVKF9+/YcPnzY+VxycjIDBw6kZs2a1K9fnzfffDPb32HUqFFUrVqVyMhI9u3b53xu9OjRBAQE0LRp\n01x/TzeaNGnSLZdX+ZGBSJEbyauCkTwqurVr1xITE8OoUaMwGo2cP3+e2bNnl4pBEnDtPSB55X6F\nzb3/Z+/Ow6Iq2z+AfwcGUBbZBIQZFhUUZyTEBdFXw0IMMc3SUCjArVwqt95cyBRbhF5tMYu0IkX9\nKZpvKSoSrpQb5JaEFmiAbGKKoMgyDHP//iDO68iAmMIweH+ua66LOec557nPYZ4zc57zLM19ENpW\nyvbevXsxatSoh95PWzmeR6XNlyktzarz0Kqrq8nJyYk+/fRTUiqVtGPHDjIwMKB33nmHiIgOHz5M\nUqmUiIh+//13cnR0pKKiIiKqm6f58uXLREQUGRlJoaGhavveu3cv/fnnn0RElJKSQsbGxnTmzBlh\nv2KxmJYtW0ZKpZISExPJ2NiYSktLiYho1qxZ9NRTT1FhYSHV1tbSiRMnqLq6mvLz88na2pr27dtH\nRET79+8na2tr+uuvvxocW25uLhkbG9Pt27eJiEipVJK9vT2lpqYKadzd3SkzM5PKy8upU6dOlJmZ\nSUR1c2g3Nk+3j48Pbd68mYiI7ty5QydPniSiujmtRSIRhYSEUEVFBaWnp5ONjQ0dOHCAiIg+/fRT\nGjRoEBUUFJBCoaDp06dTcHAwEVGjx3X9+nUhzzfffJMUCgX99NNPZGZm1uB813v33XfppZdeEt7v\n2bOHZDKZ8H79+vVUXl5OCoWC5s6dS3369BHWhYeHk7m5OR0/fpyIiKqqqmjSpEnC5+HGjRv0/fff\nU2VlJd2+fZtefPFFGjt2rLC9r68vubq6UlZWFlVWVtKwYcNo0aJFRESUk5NDxsbGFBUVRXK5nG7c\nuEHnzp0jIqK5c+fSc889Rzdv3qTbt2/T6NGjafHixcJ+16xZQ1OnTtV4vO0Fl8UHL4vLli2jDh06\nUHJyMimVSgoLCyNnZ2dasWIFKZVK+vrrr6lr167NOg8qlYqefPJJioyMpMzMTLK0tBQ+n/datGgR\nzZgxg5RKJSmVSjp69KiwztnZmTw8PCg/P59KSkroX//6Fy1ZsoSIiM6cOUO2traUlpZGKpWK4uLi\nyMXFhRQKBdXW1lLfvn3pvffeo5qaGvrzzz+pW7du9OOPPxIR0cKFC+nJJ5+kmzdvUl5eHsnlcnJ0\ndCQiop9++onOnDlDvXv31hhvYx6HcnWvM2fOkJeXF5mZmdGECRNo4sSJwv/n7jJGRBQdHU0SiYTM\nzMyoZ8+edPDgQdq3bx8ZGhqSgYEBmZqaCtfPb7/9lnr16kVmZmbUrVs3WrdunbCfw4cPk0QioY8+\n+ohsbW3J3t6e1q9fL6yvqKig+fPnk7OzM5mbm9OQIUOosrKSiIhOnDhBgwYNIgsLC/L09KQjR45o\nPK7o6GgaP3682rLZs2fT7Nmzhffz5s2jTz75hIjqvge6detGZmZm1LVr10anQ1y2bBmNHz+eXn75\nZTIzMyMPDw/KzMykFStWkK2tLTk5OVFycrKQvqnzEB0dTQMHDiSlUklERDExMSSXy6m6urpBvjdv\n3qRRo0aRjY0NWVpa0rPPPkv5+fnC+hs3btCkSZPIwcGBLC0t1b6Hdu7cSZ6entSpUyfq3r07JSUl\nERFRaWkpTZkyhezt7UkikdCSJUuotrZWOB9DhgxRi4HLVeO4HD14OXr55ZeJiKiyspJeeuklsra2\nJgsLCxowYABdu3aNVCoVOTo60qpVqxo97yqVit577z1ydnYmW1tbCgsLo7KyMiL632/Q9evXk6Oj\nI1lZWdGXX35JaWlp5OHhQRYWFvT6668L+1q/fj0NHjyY5s2bRxYWFtS9e3c6duwYffvtt+To6Ei2\ntrYUFxcnpPf19aVvvvlGbfv6MjN06FASiURkYmJCpqamtH37diIi2r17N3l6epKFhQUNHjyYzp8/\nz+XqITVV9jRdx0QikfD7MDw8nGbMmEEjR44kExMTOnjwIO3Zs4f69OlDnTp1IkdHR4qMjBS2dXR0\nJJFIRKampmRmZkYnTpxokMexY8eof//+ZG5uTgMGDBDuH4jqPjPvvPMO/etf/yIzMzMaMWKEcF9z\nL3d3d9qzZ4/wvqamhjp37kxnz54lIqLa2lqys7OjGzduaCxDxcXFD3y+dPladbe2XqZ0tpIkJSWF\nHBwc1JYNHjxY441ZVlYW2dra0oEDB0ihUKhtc/cXQGPGjh0rzH99+PBh6tixo/ADhYjI1taWUlNT\nqba2ljp27Ejnz59vsI/o6OgGN4DPPPOM2oX8bkOGDKGNGzcSEVFycjJ1795dWHfp0iVydXUlIqLy\n8nKysLCg//73v1RRUdHkcTz55JO0bNmyBjeD9V9Qf/zxh7BswYIFwgfQ3d2dDh48KKwrLCwkAwMD\nUiqVTR5Xbm4uicVitbhCQkIaPd+XLl0iMzMzocCFhITQe++9pzHtzZs3SSQS0a1bt4io7gIaHh6u\nlmbSpEnCBeVeZ8+eJUtLS+H9sGHD6IMPPhDex8TEUEBAABERrVixgl544QXKzs5WK8hZWVmkr69P\nvXv3pqFDh9Lvv/9Ox48fV7u5HTRokFDZ1F5xWXzwsrhs2TIaMWKE8D4hIYFMTU1JpVIREdGtW7dI\nJBIJPyKbOg9EdRV5VlZW1KtXL4qOjm4036VLl9Jzzz1Hly5darDOxcVF7csyMTFRONYZM2YI/896\nPXv2pJSUFDp58iQ5OTmprVuxYgVNnjyZiEitwoSI6KuvvlL7cr+3XF26dIkCAgKoX79+Qrm61+NQ\nru7GFZG6UxF5vwr5wMBAmjhxIpWWllJNTQ399NNPRESUmppK5ubmwue6oKBA+OyPHTuWZsyYQRUV\nFXTt2jXy9vYWyqqmmwsiLleacDl68HJ097GuXbuWRo8eTZWVlaRSqejMmTN069YtunjxIolEIsrJ\nyWn03MfGxpKrqytlZ2dTeXk5vfDCC8J+63+Dzpw5k6qrqyk5OZkMDQ1p7Nix9Ndff1FBQQHZ2tpS\nSkoKEdV95sViMW3YsIFUKhUtWbKEJBIJvf7666RQKCg5OZnMzMzozp07RFT3+y42NlaI5d4yc/fN\nOFHjDwWqq6u5XP1D9yt7zakkufdB6JEjR+i3334jIqLz58+TnZ0d7dy5k4jqfhOJRCK134d353Hj\nxg2ysLCgzZs3U21tLW3dupUsLS2ppKSEiJp+cHqv+z3gPXHiBA0ePJiIGi9DD3q+dPlada+2XKZ0\ntrtNYWEhJBKJ2jJnZ2eNaV1dXfHpp58iMjISdnZ2CA4ORlFRUaP73rdvH3x8fGBtbQ1LS0skJiaq\ndb2wtraGnt7/Tp2xsTHKy8tx/fp1VFVVoXv37g32mZubi++++w6WlpbC69ixY7h69arGGEJCQrB1\n61YAwJYtW9T6st3dvN/ExATbtm3D2rVr4eDggGeffRZ//PGHxn3GxsYiMzMTvXr1gre3t1rXFgBq\nXSKcnJxQWFgoxP78888LcctkMojFYhQXFzd5XIWFhbC0tETHjh2F/Tb2PwKA7t27o1evXkhISEBF\nRQV2796NkJAQAEBtbS0WLVoEV1dXmJubo2vXrgAgdN8RiURNzphRUVGB6dOnw8XFBebm5vD19UVZ\nWZla07UuXboIf3fs2BHl5eUAgLy8PHTr1q3BPidPngyVSoX8/HycO3cOvXv3xsiRI4WYcnNzkZOT\ng6effrrRuNoDLosPXhYBwNbWVvi7Y8eO6Ny5s9DftL7M1H8G73cenJ2dMWzYMOTm5uK1115rNM+3\n3noLrq6uGDFiBLp3744PP/xQbX1T14CPPvpI7Zzl5+ejqKgIubm5Qlmvf0VFReHatWsA6j4f9+63\nKa+++irWrFmDU6dOYeXKlZg1a5ba+selXN3t5MmTUCqVmDNnDvT19TFu3DgMGDBAY1p9fX1UV1cj\nIyMDNTU1cHJyEq5fVPdgRC19YGCgcD198sknMWLECPz888/CegMDAyxduhT6+voYOXIkTE1N8ccf\nf0ClUmH9+vVYvXo17O3toaenBx8fHxgaGmLz5s0IDAxEQEAAAGD48OHo378/EhMTG8Tr5OSEvn37\n4ocffgAAHDp0CMbGxvD29gYAXL58GUqlEm5ubgDqxg9IT09HZWUl7OzsIJPJGj1vTz75JPz9/aGv\nr4/x48fjxo0bWLRoEfT19TFhwgTk5OTg1q1b9z0PIpEIGzduxGeffYbnnnsOCxcuhKenp8Y8rays\n8Pzzz6NDhw4wNTVFRESE0J2vqKgISUlJWLt2LczNzSEWi4VBV2NjYzF16lT4+fkBABwcHNCzZ08U\nFxdj3759+OSTT9CxY0fY2Nhg7ty5iI+Pb/S4NeFyxeXon5Sju4/V0NAQN27cQFZWFkQiEby8vGBm\nZiZ8F9nb2zd67v/v//5P6P5qYmKCqKgoxMfHq3WbeOedd2BoaAh/f3+YmZkhJCQEnTt3hoODA4YO\nHYqzZ88Kabt27Yrw8HCIRCIEBQWhsLAQS5cuhYGBAfz9/WFoaIhLly41Gk9TvvrqK0yfPh0DBgyA\nSCRCWFgYjIyMcPLkyQZpuVw1z4OUvcaMHTsWgwYNAgAYGRnB19cXcrkcAODh4YGJEycK19p7y+e9\n9u7di549e+Kll16Cnp4eJk6cCHd3dyQkJACou+ZPnjwZrq6u6NChA4KCgoSu//cKCQlBQkKC0J17\ny5YtCA4OVsur/ndiY2XoXu35WnU/balM6Wwlib29vdqYEkDdiWtMcHAwfv75Z+Tm5kIkEmHhwoUA\nGs62Ul1djXHjxmHBggW4du0abt68icDAwGb1A+vcuTM6dOig8cLs5OSE0NBQ3Lx5U3jdvn0bCxYs\n0Liv8ePH48iRIygoKMDOnTuFygJA/cYMAEaMGIHk5GRcvXoV7u7ujY5E7urqii1btuCvv/7CwoUL\nMX78eFRWVgrrr1y5ovZ3/Y2vk5MTkpKS1GKvqKiAg4NDk8dlb28vpK1Xf/4bExwcjK1bt2LXrl2Q\nyWRCQd+yZQsSEhJw8OBBlJWVITs7G8D9L4T1eX300UfIzMxEWloaysrKkJKSovHioYmTkxMuX76s\ntqy8vBynTp2CSCSCRCJB9+7d0aNHD5SWlgo/uuPj4/Hiiy+26ow+2sBl8cHL4oN8JppzHvbu3YuT\nJ0/Cz88P//73vxvdl6mpKVatWoXLly8jISEBH3/8MQ4fPiysb+oa8Pbbb6uds/LyckyYMAFOTk7o\n2rWr2rpbt25hz549AOo+H/futzHl5eU4ceIEXnzxRXh5eWHGjBkNKq8el3J1N66I1J2KyKYq5PPy\n8mBlZQVzc/MG2+Xn5zd6LmtqamBvby+cyxkzZuCvv/5qNIZ7cbmqw+Xon5WjeqGhoXjmmWcwceJE\nSCQSLFy4EEqlEtbW1gDQ5PkpKipSO9dOTk5QKpUoLi4WltnZ2Ql/d+zYscH7O3fuNJoWAGxsbNSW\n1ZftB9XUQ4G7cblqvgcpe5poehCampqKp556Cra2trCwsMC6devUytz94rn3gY2zs7PwYAho/MHp\nvZp6wAvUXRvqy15jZUhTfO35WtWYtlamdLaSZPDgwRCLxfjss89QU1OD77//Xm1AwLtlZmbi0KFD\nqK6uhpGRETp06AB9fX0AdYUgJydHuOFQKBRQKBTo3Lkz9PT0sG/fPiQnJzcrJj09PUyZMgXz589H\nUVERamtrceLECSgUCrz88svYvXs3kpOTUVtbi6qqKuHGSxMbGxsMGzYMkyZNQrdu3dCzZ08AdT/A\nfvnlFzz11FMAgGvXrmHXrl24c+cODAwMYGJiIhzbvTZv3iz8sDI3N4dIJFIrCO+//z4qKyuRkZGB\nDRs2YMKECQCAGTNmICIiQri5+euvv4Ta1qaOy9nZGf3798eyZctQU1ODo0ePCjdOjZk4cSJ+/PFH\nrF27Vu0Lvry8HEZGRrCyssKdO3cQERGhtp2mG+e7K0HKy8vRsWNHmJubo6SkBMuXL9eYXpOQkBAc\nOHAAe/fuBRHhxo0b+PXXX2FpaYk33ngDcrkcycnJyMjIQEFBgfB52bZtm1ptcnvFZfHBy2JzKnrq\n3e88XL9+Ha+88gpiY2OxYcMG7N69G/v27dO4r7179+LSpUsgInTq1An6+vrCNYCIEBMTg4KCApSU\nlOCDDz4QrgGvvPIK1q5di7S0NBAR7ty5g71796K8vBze3t4wMzPDf/7zH1RWVqK2tha//fYbTp06\nBQAICgpCVFQUSktLkZ+frzao671UKhUsLCxw9uxZ4ZWRkaGW5nEpV3fjikjdqYhsqkLe0dERJSUl\nKCsra7Cdo6OjxnPp6OgIIyMj3LhxQziXZWVlagMn3w+Xqzpcjh6uHInFYixduhQZGRk4fvw49uzZ\ng40bN8Ld3R2Ojo7YsWNHo8fp4OCAnJwc4f2VK1cgFovVKjtaiomJiVoFy/1u3Jp6KHA3LlfNd7+y\nZ2JiovZAtTk31yEhIRg7dizy8/NRWlqKGTNmCC2T7nf9l0gkDcp+bm5ug4qJ5mrsAe/Vq1dRVFQk\nTEbQWBm6V3u/VjWmrZUpna0kMTAwwPfff48NGzbA2toa27dvx7hx49TS1H84qqursXjxYtjY2MDe\n3h7Xr19HVFQUAAgzV1hbW6N///4wMzPDZ599hqCgIFhZWWHr1q147rnnNO5Xk1WrVsHDwwMDBgyA\ntbU1Fi9eDJVKBalUil27dmHFihWwtbWFk5MTPvrooyZHaA4JCcHBgwfVvugOHTqEwYMHw9DQEEDd\nB+qTTz6BRCKBtbU1fv75Z3z55Zca9/fjjz+id+/eMDMzw7x58xAfHw8jIyNhva+vL1xdXTF8+HC8\n9dZbGD58OIC62TzGjBmDESNGoFOnThg0aBDS0tIA4L7HtWXLFqSmpsLKygrvvvsuwsPDGz1eoO5G\nefDgwThx4oTaF1JYWBicnZ0hkUjQu3dvDBo0SO3/oGkqsbuXzZ07F5WVlejcuTMGDx6MkSNHakyv\naVsnJyckJibim2++wcWLF+Hl5YU///wTXbt2xcCBA+Hq6gofHx+YmZnB398fmZmZ+P3333Hz5k34\n+Pg0ebztAZfFBy+LjX1eNb2/33mYPn06xo4di4CAAFhZWSE2NhbTpk1Tm4GqXlZWltCUefDgwXjt\ntdfg6+sr5BcSEiJ0xXFzc8OSJUsAAP369cPXX3+N119/HVZWVnBzcxO+2PX09LBnzx6cO3cO3bp1\ng42NDV599VWhRdWyZcvg7OyMrl27IiAgAGFhYY3+3zp16oSuXbsKP7aJCOfPnxfWP07l6m5cEak7\nFZFNVcjb29tj5MiRmDVrFkpLS1FTU4OffvoJADB16lSsX78ehw4dgkqlQkFBAf744w/Y29tjxIgR\nmD9/Pm7fvg2VSoXLly8L2zUHl6s6XI4erhwdOXIE6enpqK2thZmZmTDjHwB8/PHHeO+997Bhwwbc\nunULKpUKR48exfTp0wHU3cR98sknyMnJQXl5OSIiIjBx4kS1B3X38yBl+m59+vTB999/j8rKSly6\ndAmxsbFq6+3s7NRaCzf1UOBuj6Jc1dbWwsvLC6NHjwZQN/OdVCoVZvG4+zoTFRUFNzc3uLu7q32+\nTp8+DQ8PD7i5uanNvFddXY0JEybAzc0NPj4+Td5kt7T7lT1PT09kZGTg119/RVVVFSIjI9W21/S/\nLy8vh6WlJQwNDZGWloYtW7YIvy1sbGygp6fXoBV4vZEjRyIzMxNbt26FUqnEtm3b8Pvvv+PZZ59t\nMs/GNPaAd9++fRg5cqTwvqkydLf2fq1qTJv7rmqBcU5YC5o1axZ9+eWXj3Sf9YNm3T3AEVM3ceJE\nsre3JwMDA5JKpfTtt99SdnY2BQQEkKenJ8lkMrVBZiMjI9VmuWHtT0uURW1ycXFRG6C5NXC5ar5T\np041GOn+7kHc6mcMOn/+PHl7e5OZmRlZWVnR6NGjhQHdbty4QUOGDCFLS0vq168fERF98cUXZGdn\nRxYWFhQaGkrBwcEa91vv7s9JZWUlzZ07lyQSCZmbm5Ovr68w8HZqair5+vqSlZUV2djY0LPPPktX\nrlxp9Pg2bdpEIpFIbYaM3bt30+jRo4X3RUVF5OvrS+bm5mRhYUFPPfUUXbx4UeP+7h2wbv/+/WoD\ntdbU1JCenh4VFBTc9zy88MILNHPmTGHbffv2kYODgzDI390KCwtp2LBhZGpqSj179qR169aRnp6e\n8P1aUlJC4eHhZGdnR5aWljRu3Dhh2x9++IGeeOIJMjMzI1dXV2H2nbKyMpo5cyZJpVIyNzcnLy8v\n2rZtGxERbdiwgYYOHaoWA5erxnE5+uflaOvWrdSzZ08yMTEhOzs7mjNnjtrvxqSkJBo6dCiZmpqS\njY0NPfXUU5SYmEhEdYMfv/vuu+To6Eg2NjYUGhoqDAaZnZ2tVkaIiKRSqTBQKxHRyy+/LAyuf+9n\nPisri/T09NTilkqldOzYMSIiun79Oo0YMYLMzMxoyJAhFBkZqbb92rVryd7eniwsLOi7774TjmXA\ngAFkYWFB9vb2FBQUROPGjXvk5eqjjz6ikJAQ4f8TGRlJH330UYN0GRkZ5OnpSQqFgrKzs6l79+7C\nQO8DBgwQBugdOXKkMHjmF198IVy34uPjacKECU3G0tKaKntERB988AF17tyZnJycaPPmzaSnpycM\nQHr3bJX1duzYQc7OzmRmZkbPPvssvfHGG2rX/KVLlwqzjJ08ebLB5+bo0aPUr18/Mjc3p/79+wuf\nF6KGg/1qus7ey8/PjwwMDNRmqxk3bhz997//Fd7frww193y1h2sVUdv/rhIRtbNJl9u5r7/+GmPG\njHmkTRRzcnLQrVs3KJXKB6rVZ+xx1hJlUZu6du2K2NjYx36AOdZ2vPbaa/Dw8MCMGTO0HQpjOovL\nUduUn5+PSZMm4e2338bHH3+M3bt3IzIyEmZmZnjzzTfV0kZFRUFPT0/oRhEQEIDIyEg4Ozvj6aef\nxsWLFwHUjddw5MgRrF27FgEBAVi+fDkGDhwIpVIJe3v7BxrLiD2c+nOenZ0NU1NTbYfD/gG+I9Yx\nr7zySovclD3ug0ox9qBaqiwyxur06dMHzz//vLbDYEyncTlqm+bNm4eVK1eqPZwUiURYs2YNPD09\nMXXqVJSWlgKoG8hTKpUK6aRSKQoKChosl0gkQheHgoICYbBTsVgsdAFkrePmzf52x9oAACAASURB\nVJt4//33uYJEh3ElCYOLiwtqa2u5FQljj7Hs7GxuRcLaFK6IZOzhcTlqe/bs2QNbW1t4eXmpjX0x\nc+ZMZGdn49y5c7C3t2/QooTpDhsbG2FMHqabxNoOoLk8XVxwXouDDjH2sHx9fXHkyBFth6GGyxXT\ndVyuGHv02lq54jLFdN3dZer48eNISEhAYmIiqqqqcOvWLYSFhanNdDJt2jRhQFeJRIK8vDxhXX5+\nPqRSKSQSCfLz8xssr9/mypUrcHBwgFKpRFlZGaysrNRi6urighwuV0yHteR3lc6MSSISiaDYvr3J\nNDth8ND5bN8ej6CgTc1KOxY775tGU0x1eUx84NgeFOfTtvIJCnr+H4/O3lKaU64e1rvbt2NpUFCL\n5sH5tO18WjIPw6AgnStXj+67Snevh+05n/ZwLG3t+6p1fwNOBDDqoffVdD7vIihoaYvm0Vr5tKdj\nacl8goIMNZaplJQUrFq1Crt370ZRURHs7e0BAJ988gl++eUXbNmyBRcuXEBISAjS0tJQUFCA4cOH\n49KlSxCJRBg4cCA+++wzeHt7Y9SoUZg9ezYCAgIQExOD9PR0fPnll4iPj8fOnTsRHx+vlrdIJMIP\n9ylXNfx9pZV82tOxtGQ+LfldpTMtSQBgwcYt+Pdzo2Brbq7tUBhjjDHGGGPsHyMiYVzABQsW4Ndf\nf4VIJELXrl2xbt06AIBMJkNQUBBkMhnEYjFiYmKEbWJiYjBp0iRUVlYiMDAQAQEBAOqmFQ8NDYWb\nmxusra0bVJAwxpqmU5Uknyd2RvzRpfj14w9gyQPhMMYYY4wxxnTUsGHDMGzYMADApk2Nt2SPiIhA\nREREg+X9+vVDenp6g+VGRkbY3sIthRlrz1pkpM4pU6bAzs4OHh4ewrK33noLvXr1gqenJ1544QWU\nlZUJ66KiouDm5gZ3d3ckJyc3ul+lahVuVfTF9ydPtkTYAAC5vHeL7bs18+B82n4+jwtfuZzzeczz\naa1jeZy0t+the8qnPR3L46b1/ne+7Saf9nQsrZnP46S9XRP5e6Tt5vMotciYJD///DNMTU0RFhYm\n1G7u378ffn5+0NPTw6JFiwAA0dHRQj+7X375Rehnl5mZ2WCmlbpmZaXoYDALH4Z2wMy/m5Pd7VH0\nR63TvL6o/3RMEvZ4amt9vIHWGZOEsZb0uI5JwlhLamvfV601Jsn/tOyYJOzx09iYJNrUWmOSMNZS\nWvK7qkVakgwdOhSWlpZqy/z9/YWKj4EDBwqjMe/atQvBwcEwMDCAi4sLXF1dkZaW1sie4yDW34eR\nffu2RNiMMcYYY4wxxhh7jLVIJcn9fPvttwgMDAQAFBYWCtNVAYBUKkVBQYHG7Qb12IiDkQvhYmvb\nKnEyxhhjjDHGGGPs8dHqA7d+8MEHMDQ0REhISKNp6kdsvpffE12x+9Qp7D51Cr5yOfdzZ21aRsZv\nyMj4TdthMMYYY4wx1kCtSgV9Pa08M2esTWvVSpINGzYgMTERBw8eFJZJJBLk5eUJ7/Pz8yGRSDRu\nvzQoqMVjZOxRkct7qw1UtGPHNi1G07J4jAXW3pSWlmLatGnIyMiASCTC+vXr4ebmhgkTJiA3Nxcu\nLi7Yvn07LCwstB0qY4wx9o/MeH0B3lv2FrrY2Wk7FMbalFarOkxKSsLKlSuxa9cudOjQQVg+ZswY\nxMfHQ6FQIDs7G1lZWfD29n7o/BSKalRXVz/0fhhjjD1+5syZg8DAQFy8eBHnz5+Hu7s7oqOj4e/v\nj8zMTPj5+SE6OlrbYTLGGGP/2I0b0xC98ktth8FYm9MiLUmCg4ORkpKC69evw9HREcuXL0dUVBQU\nCgX8/f0BAIMGDUJMTAxkMhmCgoIgk8kgFosRExPTaHeb5lAqlfj8889w8uQxAMDAgT544415EItb\nvWcRY4wxHVRWVoaff/4ZcXFxAACxWAxzc3MkJCQgJSUFABAeHo5hw4ZxRQljjDGdRTQF+QUfaDsM\nxtqcFmlJsnXrVhQWFkKhUCAvLw9TpkxBVlYWcnNzcfbsWZw9exYxMTFC+oiICFy6dAm///47nnnm\nmUb3233Wa5DPmYv/njjRaJoffvgvTp06DZXKFCqVKU6fPocdO3iKU8YYY82TnZ0NGxsbTJ48GX37\n9sUrr7yCO3fuoLi4GHZ/N0m2s7NDcXGxliNljDGmq2pra+Hl5YXRo0cDAEpKSuDv748ePXpgxIgR\nKC0tFdJGRUXBzc0N7u7uSE5OFpafPn0aHh4ecHNzw5w5c4Tl1dXVmDBhAtzc3ODj44Pc3NxGojgM\nSwvuasPYvXRqpJ686xXIKirFlC9icCg9XWOa335Lh0IBACIAIigUdcsYY4yx5lAqlThz5gxmzZqF\nM2fOwMTEpEGLEZFI9FCtHhljjD3eVq9eDZlMJnyXNNal88KFC9i2bRsuXLiApKQkzJo1C0QEAJg5\ncyZiY2ORlZWFrKwsJCUlAQBiY2NhbW2NrKwszJs3DwsXLtQYQ8cOs/HmvFdb4WgZ0y06VUlS1zvI\nAJUKEeKPHtWYwtbWFvr6JLzX0yPY8pTBjDHGmkkqlUIqlWLAgAEAgPHjx+PMmTPo0qULrl69CgAo\nKipq8rvl3e3bhVdKRkarxM3YP5WR8Ru2b48XXo/KlClTYGdnBw8PD43rjxw5AnNzc3h5ecHLywvv\nv//+I8ubsbYsPz8fiYmJmDZtmlDhkZCQgPDwcAB1XTp37twJANi1axeCg4NhYGAAFxcXuLq6IjU1\nFUVFRbh9+7YwlmNYWJiwzd37GjdunNqkGXeLWfMfuPfo0aLHypgu0smBOvREgGmHjhrXvfRSKNLT\nz6Oiom7Q1o4dO+Lll8NbMzzGGGM6rEuXLnB0dERmZiZ69OiBAwcOQC6XQy6XIy4uDgsXLkRcXBzG\njh3b6D54NjamS1pqNrbJkyfjjTfeQFhYWKNpfH19kZCQ8EjyY0xXzJs3DytXrsStW7eEZY116Sws\nLISPj4+QTiqVoqCgAAYGBpBKpcJyiUSCgoICAEBBQQEcHR0B/G9crZKSElhZWanFYWFu3jIHyJiO\n07FKkiroiUQw7aCHN0YFakxhYWGJTz5Zg/T0X0FE8PB4AsbGJq0cJ2OMMV22Zs0avPTSS1AoFOje\nvTvWr1+P2tpaBAUFITY2VpgCmDHWuKFDhyInJ6fJNPVP0Rl7XOzZswe2trbw8vLCkSNHNKbhLp2M\naZdOVZK8NvJpdDQ0xKv+/nBpoplzx44d4e3t0+h6xhhjrCmenp745ZdfGiw/cOCAFqJhrH0SiUQ4\nfvw4PD09IZFIsGrVKshkMm2HxViLOn78OBISEpCYmIiqqircunULoaGhsLOzw9WrV9GlSxe1Lp0S\niQR5eXnC9vn5+ZBKpZBIJMjPz2+wvH6bK1euwMHBAUqlEmVlZQ1akQBA/F2V/b3lcvSWy1vqsBl7\naBkZvyEj47dWyUunKkk+mTxZ2yEwxhhjjLFHoG/fvsjLy4OxsTH27duHsWPHIjMzU9thMdaiVqxY\ngRUrVgAAUlJSsGrVKmzatAkLFizQ2KVzzJgxCAkJwfz581FQUICsrCx4e3tDJBKhU6dOSE1Nhbe3\nNzZt2oTZs2cL28TFxcHHxwc7duyAn5+fxlgmctdQpkNaqmuoJjpVScIYY4wxxtoHMzMz4e+RI0di\n1qxZGsdNAOoGQ67nK5fDl594szYsIyMFGRkpzUpb361m0aJFGrt0ymQyBAUFQSaTQSwWIyYmRtgm\nJiYGkyZNQmVlJQIDAxEQEAAAmDp1KkJDQ+Hm5gZra2vExz+6AZkZexxwJQljjDHGGGt1xcXFsLW1\nhUgkQlpaGohIYwUJwIMhM90il/tCLvcV3u/YoXnmJl9fX/j61qWzsrJqtEtnREQEIiIiGizv168f\n0tPTGyw3MjLicbMYewhcScIYY4wxxh654OBgpKSk4Pr163B0dMTy5ctRU1MDAJg+fTp27NiBL7/8\nEmKxGMbGxvy0mzHGWJvAlSSMMcYYY+yR27p1a5PrX3vtNbz22mutFA1jjDHWPHraDoAxxhhjjDHG\nGGOsLeBKEsYYY4wxxhhjjDFwJQljOqW2thZeXl4YPXo0AKCkpAT+/v7o0aMHRowYgdLSUiFtVFQU\n3Nzc4O7ujuTkZG2FzBhjjDHGGGM6gytJGNMhq1evhkwmE6Z+i46Ohr+/PzIzM+Hn54fo6GgAwIUL\nF7Bt2zZcuHABSUlJmDVrFlQqlTZDZ4wxxhhjjLE2r0UqSaZMmQI7Ozt4eHgIy/iJN2MPJz8/H4mJ\niZg2bRqICACQkJCA8PBwAEB4eDh27twJANi1axeCg4NhYGAAFxcXuLq6Ii0tTWuxM8YYY4wxxpgu\naJFKksmTJyMpKUltGT/xZuzhzJs3DytXroSe3v+KbXFxMezs7AAAdnZ2KC4uBgAUFhZCKpUK6aRS\nKQoKClo3YMYYY4wxxhjTMS1SSTJ06FBYWlqqLeMn3oz9c3v27IGtrS28vLyEViT3EolEQjecxtYz\nxhhjjDHtqaqqwsCBA9GnTx/IZDIsXrwYABAZGQmpVAovLy94eXlh3759wjaNtbo/ffo0PDw84Obm\nhjlz5gjLq6urMWHCBLi5ucHHxwe5ubmtd4CMtQPi1sqoqSfePj4+Qjp+4s1YQ8ePH0dCQgISExNR\nVVWFW7duITQ0FHZ2drh69Sq6dOmCoqIi2NraAgAkEgny8vKE7fPz8yGRSDTu+93t24W/feVy+Mrl\nLXswjD2EjIzfkJHxm7bDYIwxxv6RDh064PDhwzA2NoZSqcSQIUNw9OhRiEQizJ8/H/Pnz1dLf3er\n+4KCAgwfPhxZWVkQiUSYOXMmYmNj4e3tjcDAQCQlJSEgIACxsbGwtrZGVlYWtm3bhoULFyI+Pl5L\nR8yY7tHKwK38xJuxB7NixQrk5eUhOzsb8fHxePrpp7Fp0yaMGTMGcXFxAIC4uDiMHTsWADBmzBjE\nx8dDoVAgOzsbWVlZ8Pb21rjvpUFBwosrSFhbJ5f3RlDQROHFGGOM6RpjY2MAgEKhQG1trdACX1Nr\nYU2t7lNTU1FUVITbt28Lv+/CwsKElvp3t+AfN24cDh482BqHxVi70WotSfiJ9z+nUtXixo0bMDEx\ngbGxibbDYc3Ukk+86ysSFy1ahKCgIMTGxsLFxQXb/y4jMpkMQUFBkMlkEIvFiImJ4cpHxh6Ai4sL\nOnXqBH19fRgYGCAtLQ0lJSWYMGECcnNzhfJmYWGh7VAZY4zpGJVKhb59++Ly5cuYOXMm5HI5duzY\ngTVr1mDjxo3o378/PvroI1hYWDTa6t7AwEBt/DmJRCK0xi8oKICjoyMAQCwWw9zcHCUlJbCysmrd\nA2VMR7VaJUn9E++FCxc2eOIdEhKC+fPno6Cg4L5PvB83xcVXERm5FOXlt1Fbq8Tzz4/Hiy9O0HZY\nrBnk8t6Qy3sL73fs2PZI9uvr6wtfX18AgJWVFQ4cOKAxXUREBCIiIh5Jnq1rVDPS7G3xKNjjTSQS\n4ciRI2o/KOsHIF+wYAE+/PBDREdHC4OQM8YYY82lp6eHc+fOoaysDM888wyOHDmCmTNnYunSpQCA\nd955B2+++SZiY2O1HCljj6cWqSQJDg5GSkoKrl+/DkdHR7z77rv8xPsfWrnyQ5SUlIPICIABEhJ2\nolevXujd+wlth8YYY+3avc2eExISkJKSAqBuAPJhw4a1u0qS3NwcbNmyGeXl5Rg8+F8IDHyWv5MZ\nY6yFmJubY9SoUTh16hSGDRsmLJ82bRpGjx4NQHOre6lUColEgvz8/AbL67e5cuUKHBwcoFQqUVZW\nprEVSfxdrfR7y+Xo/Zi00me6qTXHpWuRSpKtW7dqXN7+nni3vIKCPBDVd7HRg1Kphz///JMrSRhj\nrAWJRCIMHz4c+vr6mD59Ol555ZVGByBvL65eLcI770SgqgoARLhyZSvKy8sxYUKwtkNjjLF24/r1\n6xCLxbCwsEBlZSX279+PZcuWCcMSAMAPP/wADw8PAI23uheJROjUqRNSU1Ph7e2NTZs2Yfbs2cI2\ncXFx8PHxwY4dO+Dn56cxlomPYSt9prtaqpW+Jq3W3Yb9M5aWVrh+/Q4AAwAEsRjCj3TGGGMt49ix\nY7C3t8dff/0Ff39/uLu7q62/3wDkujiG1vHjx1BTAwCGAIDq6lr8+OM+riR5DPCsUYy1nqKiIoSH\nh0OlUkGlUiE0NBR+fn4ICwvDuXPnIBKJ0LVrV6xbtw5A063uY2JiMGnSJFRWViIwMBABAQEAgKlT\npyI0NBRubm6wtrbmmW0Ye0BcSdLGzZ37Jj74YDlEIhVqa2vg5dUX3t4+99+QMcbYP2Zvbw8AsLGx\nwfPPP4+0tLRGByDXRBfH0NLTa1jpw11tHg+t+XSOscedh4cHzpw502D5xo0bG92msVb3/fr1Q3p6\neoPlRkZGwtAGjLEHp5UpgFnz9ejRE2vWfIm5c+chMvI9zJv3b/7RyhhjLaiiogK3b98GANy5cwfJ\nycnw8PBodMrt9uJf/xoKQ0MRRCIFAAWMjGoxevQYbYfFGGOMMdaquCWJDujUyRx9+nhpOwzWTvV8\nYxG2zH0F/bp313YojLUJxcXFeP755wEASqUSL730EkaMGIH+/ftrHIC8vbCxsUVU1H/w3XfbcPv2\nbQwe/C889ZTmfuyMMcYYY+0VV5I8oD//PINz55JhbNwJTz9pgU7GxtoOibGHkl38Np559y38vuY/\n6Nypk7bDYUzrunbtinPnzjVY3tSU2+2Fg4MEc+bM13YYjDHGGGNaw5UkD+CXXxKwevVMKJXBEItP\n49Ceczj1n+UaK0qKbt7EjLXrkHYlD1KpI2bOnAUrK2stRM3Y/YwDRN/gbHY2/D09G6zdCYNWjmdv\nK+fHWGsb9Qj3xeWFtV1TpkzB3r17YWtrq3HcBACYPXs29u3bB2NjY2zYsAFeXtxyljHGmHbxmCQP\n4Ntvl0ChiIVK9S4UijhcvemJjUeONEhXo1TiqaXLsP/8Rdy4UYn09ItYsmQxFApF6wfN2H1VQVmb\nBytTU20HwhhjrB2ZPHkykpKSGl2fmJiIS5cuISsrC1999RVmzpzZaFrDoCAYBgXhi8RE3K6sVFuX\nfuUK0tPP49atW48s9sbk5WUgPf0QysqutXhejDHGtINbkjyAioqbALoJ76uVrigpz2uQ7vfCQlwr\nK4Oy1gCACCqVPu7cqUBe3hV07+7aegEz1gwmRiPg38cVfbt1u39ixhhjrJmGDh2KnJycRtcnJCQg\nPDwcADBw4ECUlpaiuLgYdnZ2DdJ2BFAJYN6GDVj8f//F6VXvw7VLF0xfuw7bjx0HxAYgUiIiYil6\n9nRvsP2j8M03b+HIke0Qi7tDpfodixbFQyZ7skXyYowxpj3ckuQB9O07EgYGbwMoAnASHQw24pk+\nDbsndDQ0RK1KddcSgkpVC0NDw9YKlbFm+2rm04ifN4NnTWKMMdaqCgoK4OjoKLyXSqXIz8/XmDYJ\ngNHff1fVmCJsdSx+PHcO3x0/gQqFISoq9FBZKcLHH69skVh/++0IUlL2QKE4iYqKPaiqWodVq8Jb\nJC/GGGPaxS1JHsCMGZ+CaDbOnBkKI6NOiJn8Mgb26NEgXXc7Ozzt4YFD6RdQqVDB0FAPPXu6Qyp1\n1LBXxrTrxcGDtR0CY4yxxxQRqb1vrMI+EcD/1pTiz2sq/FlcjFqV3l1rxCgtvQkieuQV/8XFfwLw\nAWD+95KncefOVdTUVMPAwKiJLdnjKCMjBRkZKdoOgzH2D+lUS5Ier7+GhF9+0Vr+RkbGmDv3G2zc\nWIivv/690ZtLkUiE7/79JlaEBMHXdxAmTpyARYve5if1jDHGGGN/k0gkyMv7X7fl/Px8SCQSjWkH\nqr2zgKezMzycnKCnVwugvvVuDezsurTI7y1nZw8QHQZQ39IlHlZWrlxBwjSSy30RFLRUeN2tqqoK\nAwcORJ8+fSCTybB48WIAQElJCfz9/dGjRw+MGDECpaWlwjZRUVFwc3ODu7s7kpOTheWnT5+Gh4cH\n3NzcMGfOHGF5dXU1JkyYADc3N/j4+CA3N7eFj5ix9kWnKklyyv9C6GerkZaVpe1Q7kusr4/XAgPx\n2muz8eyzYyAWc6Mdxhh7XLwVtxWVPFg3Y00aM2YMNm7cCAA4efIkLCwsNI5HAgAhAKr+/ruzmQob\n50zDUJkMC8Y+B0NxJTp0UMDc3AgLFixukVhdXQcgKGgexOJBMDLqAzOzFVi06P9aJC/WvnXo0AGH\nDx/GuXPncP78eRw+fBhHjx5FdHQ0/P39kZmZCT8/P0RHRwMALly4gG3btuHChQtISkrCrFmzhBZY\nM2fORGxsLLKyspCVlSUMlBwbGwtra2tkZWVh3rx5WLhwodaOlzFdpFt37hVApViBd7/bgT0RLfMl\nyBhjjD2sdckKpF9Zg31L5nMrQvbYCg4ORkpKCq5fvw5HR0csX74cNTU1AIDp06cjMDAQiYmJcHV1\nhYmJCdavX9/ovqoAdDMxwdYlS/BE167Q16t7zhcxbhxmPPMMtt2uhI2NDcTilpu2fsyYOXj66TDc\nuvUXbG1dIBbzWHPsnzE2NgYAKBQK1NbWwtLSEgkJCUhJqeuiEx4ejmHDhiE6Ohq7du1CcHAwDAwM\n4OLiAldXV6SmpsLZ2Rm3b9+Gt7c3ACAsLAw7d+5EQEAAEhISsHz5cgDAuHHj8Prrr2vnQBnTUbpV\nSQITQHkHh85fwv5ff4W/Z8NBUxljjDFtq6pZj2MXXXGtrAx2FhYtmNOoZqTZ24L5M9a4rVu33jfN\n559/3qx9KbZvb3Sdlakp7E0tmx3XwzA1tYRpK+XF2i+VSoW+ffvi8uXLmDlzJuRyudrMTnZ2digu\nLgYAFBYWwsfHR9hWKpWioKAABgYGkEqlwnKJRIKCggIA6oMii8VimJubo6SkBFZWVq11iIzpNJ3q\nblNXpyOCUvUSDqVnaDsYxhhjrBEqAI9+8EjGGGO6T09PD+fOnUN+fj5++uknHD58WG29SCTi7w/G\ntKjVW5JERUVh8+bN0NPTg4eHB9avX487d+5gwoQJyM3NhYuLC7Zv3w4LjU/eagCYw0hcADsLrsVn\njDHWNnU0DIWv3AO25ub3T8wYY+yxZG5ujlGjRuH06dOws7PD1atX0aVLFxQVFcHW1haA5gGOpVIp\nJBKJ2pTZ9cvrt7ly5QocHBygVCpRVlamsRVJ/F0ttHrL5egtl7fUoTL20DIyfkNGxm+tklertiTJ\nycnB119/jTNnziA9PR21tbWIj49vdKCihpToYNANTjYXMG348NYMnTHGGGu2uc9aYcdb3AecMcaY\nuuvXrwsz11RWVmL//v3w8vLCmDFjEBcXBwCIi4vD2LFjAdQNcBwfHw+FQoHs7GxkZWXB29sbXbp0\nQadOnZCamgoiwqZNm/Dcc88J29Tva8eOHfDz89MYy8SgIOHFFSSsrZPLeyMoaKLwakmt2pKkU6dO\nMDAwQEVFBfT19VFRUQEHBwdERUVpHKjoXqvCg2FpaopxPj4wNuIp1xhjjLVNyyeO03YIjDHG2qCi\noiKEh4dDpVJBpVIhNDQUfn5+8PLyQlBQEGJjY4WW9QAgk8kQFBQEmUwGsViMmJgYoStOTEwMJk2a\nhMrKSgQGBiIgIAAAMHXqVISGhsLNzQ3W1taIj4/X2vEypotatZLEysoKb775JpycnNCxY0c888wz\n8Pf3b3SgonvNHtWcAeoYY4yxh1dbW4v+/ftDKpVi9+7dKCkpaWbXUMYYY0wzDw8PnDlzpsFyKysr\nHDhwQOM2ERERiIiIaLC8X79+SE9Pb7DcyMhIqGRhjD24Vu1uc/nyZXz66afIyclBYWEhysvLsXnz\nZrU0ujBQUW2tEls3vAnZq69iwBtvYGdamrZDYu1cVVUVBg4ciD59+kAmk2Hx4ropsEtKSuDv748e\nPXpgxIgRQvNNoG78Hzc3N7i7uyM5OVlboTOms1avXg2ZTCZ8JzW/ayhjjDHGGNNVrdqS5NSpUxg8\neDCsra0BAC+88AJOnDiBLl26aByo6F7v3lUj6iuXw7eRvnPV1dU4ceIYKisr4eHxBKRSx0d6HNs3\nLcTVA99gk6ISVwHM+Owz2C5ZgsHu7o80H6bbHuXgQh06dMDhw4dhbGwMpVKJIUOG4OjRo0hISIC/\nvz8WLFiADz/8ENHR0YiOjsaFCxewbds2XLhwAQUFBRg+fDgyMzOhp9ewXnRdcjK6WFhgdP/+Gtcz\n9jjKz89HYmIi3n77bXz88ccAgISEhGZ1DWWMMcYYY7qrVStJ3N3d8d5776GyshIdOnTAgQMH4O3t\nDRMTE8TFxWHhwoVqAxXda2lQ0H3zqKqqxKJFC3Djxk2oVIBItAkLFizGE094PrLjOHXiO2xTVKIX\ngF4ApikUSEhN5UoSpkYu7w25vLfwfseObQ+1P2NjYwCAQqFAbW0tLC0tG71p27VrF4KDg2FgYAAX\nFxe4uroiLS0NPj4+Dfa7YGMV9PWSMbjnMSQsnqMzFSX5+XlYuzYGN25ch7t7L7zyynQYG5toOyzW\nTsybNw8rV67ErVu3hGXN7RrKGGOMMcZ0V6veDXl6eiIsLAz9+/fHE088AQB49dVXsWjRIuzfvx89\nevTAoUOHsGjRon+cx6FDB/DXXyWortZHTY0YCoU+vvrqy0d1CAAAI0MTFN31/qqeHkz/voFlrKWo\nVCr06dMHdnZ2eOqppyCXyxu9aSssLBSmgQMAqVSKgoICjfutVHyO8qqDOP5HKZJ//bXlD+QRuHWr\nDEuWLEZmZi5u3KhCauppREev0HZYrJ3Ys2cPbG1t4eXlBSLSmEYXuoYyxhhjjLEH16otSQBgwYIF\nWLBggdqypgYqelBlZbdQU1MLwODvJfooLy9/JPuu93zYh3h1dSimKypxVV8fycbGOO7v/0jzYOxe\nenp6OHfuHMrKyvDMM8/g8OHDauvvd9PW9A2dAYBeuFZW9miCbWEXLmSAOLJ6CQAAIABJREFUSA/1\nlzClUg9ZWX+goqJCaHHD2D91/PhxJCQkIDExEVVVVbh16xZCQ0NhZ2fXrK6hQPO7hzLWFjzK7qGM\nMcaYrmv1SpKW5uHxBPbu3QOFohaAHsTiWnh4PLquNgAwYMAYdHonCWWpK+FkbIzjw4ejC89wwFqJ\nubk5Ro0ahdOnTzd60yaRSJCXlydsk5+fD4lE0sgePwBQhCrFXuiJprX8ATwChoZGIFIBEP39IhAB\nYnG7u6Sxe7TGzdyKFSuwYkVdy6SUlBSsWrUKmzZtwoIFC5rVNRRoXvdQxtqKR909lDHGGNNlujH4\nwAPo3dsDkydPQceOKujr34GHRy/MmvXGI8+nZ89BWBEWhojx47mChLW469evCzPXVFZWYv/+/fDy\n8sKYMWMQFxcHAGo3bWPGjEF8fDwUCgWys7ORlZUFb29vjfsWiT6Ghck+bP/3HLzs69s6B/SQPDye\ngI1NZxgY1ACohpGREgEBgTA0NNR2aKyFyeW9ERQ0UXi1hvpWWI+yayhjjDHGGGub2uVjVz8/f/j5\n+YOIuM84axeKiooQHh4OlUoFlUqF0NBQ+Pn5wcvLC0FBQYiNjYWLiwu2/93EXyaTISgoCDKZDGKx\nGDExMY2Whcqt/6czg7XWMzAwwAcfRCMxcQ+Ki69CLu+NoUN1o4KH6RZfX1/4/l15+Ci7hjLGGGOM\nsbapXVaS1OMKEtZeeHh44MyZMw2WN3XTFhERgYiIiPvuW9cqSOp16NABL7wwXtthMMYYY4w1W15e\nHsLCwnDt2jWIRCK8+uqrmD17NiIjI/HNN9/AxsYGQF3Xz5EjRwIAoqKi8O2330JfXx+fffYZRowY\nAQA4ffo0Jk2ahKqqKgQGBmL16tUAgOrqaoSFheHMmTOwtrbGtm3b4OzsrJ0DZkwH6ebdEWOMMdaG\n7UxL03YIjDHG2iADAwN88sknyMjIwMmTJ/HFF1/g4sWLEIlEmD9/Ps6ePYuzZ88KFSQXLlzAtm3b\ncOHCBSQlJWHWrFnCzGszZ85EbGwssrKykJWVhaSkJABAbGwsrK2tkZWVhXnz5mHhwoVaO17GdFG7\nbknS0nYKM+gwxhhj/xP+WRy+X9ABfn9Pd69do7QdAGMPbe991o9FTbP207zfbvfL7VHnxx4nXbp0\nQZcuXQAApqam6NWrFwoKCgBA47Tzu3btQnBwMAwMDODi4gJXV1ekpqbC2dkZt2/fFsacCwsLw86d\nOxEQEICEhAQsX74cADBu3Di8/vrrrXR0jLUP3JKEMcYYe8QqFf/GxpRUbYfBGGOsDcvJycHZs2fh\n4+MDAFizZg08PT0xdepUYcD+wsJCSKVSYRupVIqCgoIGyyUSiVDZUlBQAEdHRwB1M/+Zm5ujpKSk\ntQ6LMZ3HlSSMPeZqlEpth8BYuyPCDZgY8RNkxpKSkuDu7g43Nzd8+OGHDdYfOXIE5ubm8PLygpeX\nF95//30tRMlY6ysvL8f48eOxevVqmJqaYubMmcjOzsa5c+dgb2+PN998U9shMvbY4u42jD3m3F5/\nHQciI+H6d9NPxtjDM+nwFeY8G6ntMBjTqtraWrz++us4cOAAJBIJBgwYgDFjxqBXr15q6Xx9fZGQ\nkKClKBlrfTU1NRg3bhxefvlljB07FgBga2srrJ82bRpGjx4NoK6FSF5enrAuPz8fUqkUEokE+fn5\nDZbXb3PlyhU4ODhAqVSirKwMVlZWDeKI/3tWRADoLZejt1z+aA+UsUcoI+M3ZGT81ip5cUsSxh5z\nV6tuYuLHH2k7DMbalZPRkejp4KDtMBjTqrS0NLi6usLFxQUGBgaYOHEidu3a1SCdpnEYGGuviAhT\np06FTCbD3LlzheVFRUXC3z/88AM8PDwAAGPGjEF8fDwUCgWys7ORlZUFb29vdOnSBZ06dUJqaiqI\nCJs2bcJzzz0nbBMXFwcA2LFjB/z8/DTGMjEoSHhxBQlr6+Ty3ggKmii8WlK7aUnyZ3ExUnPyYG3d\nGa6ubtoOhzGdoRIT/igo1HYYjLUrPbiChDG1cRGAurEUUlPVx+oRiUQ4fvw4PD09IZFIsGrVKshk\nstYOlbFWc+zYMWzevBlPPPEEvLy8ANRN97t161acO3cOIpEIXbt2xbp16wAAMpkMQUFBkMlkEIvF\niImJgUgkAgDExMRg0qRJqKysRGBgIAICAgAAU6dORWhoKNzc3GBtbY34+HjtHCxjOqpdVJJ8f/Ik\nJn/+BaBvCJWqBr6+T2HatFe1HRZjukEJOHa21nYUjDHG2pn6G7mm9O3bF3l5eTA2Nsa+ffswduxY\nZGZmtkJ0jGnHkCFDoFKpGiyvn/JXk4iICERERDRY3q9fP6SnpzdYbmRkhO13daVhjD0Yna8kUdbW\nYvLnn6NSYYi63kOGSEk5DF/fYbC0tERWVibMzDpBJpNDT0+9d1FaWiqSkhKhr6+P558fB5mMm5mx\nx4+5yBhb5s1vVlqFQgGxWB96evotHBVjjDFdd+9YCnl5eWqzcQCAmZmZ8PfIkSMxa9YslJSUNBg/\ngcdOYLqkNcdOYIw9ejpfSVJ65w5UKgJQf9Mmgp6eAc6cOY09e5KhpzcQRH+iVy87LFw4T6goOX78\nGGJiPodCUfeU4+LF97BkyTK4u/fSnBFj7dTBZZFwvmuwME0qKu7gP/+Jxu+/X4BIJMILL4zHiy+2\nbF9Axhhjuq1///7IyspCTk4OHBwcsG3bNmzdulUtTXFxMWxtbSESiZCWlgYi0jjA5MSgoNYKm7GH\nJpf3hlzeW3i/Y8c2LUbDGHtQOl9JYm1mBgsTExSXVQMwBFCL2toa7N//E6qrYwH4AVDgwgV/pKWd\nhI/PYABAQsJOKBR6AOqmaFQoqpGUlMiVJOyx03/BQoj19bBk/HhEjBunMc3atV8iM/NPqFSmAOj/\n2bvzuKjq9YHjn9kBFQlTkEVJgRA0NQ0t9xTXNLt2MS2XtDKzxaybZqtmiS2/cq1umZndm5qVWhrX\nJaVF0zItRUvcEBAUJVBZZjvn98fAhLGICjMMPu/Xa14xZ77nnOeQh3PmOd/v82Xt2rU0a9acTp1u\ndm2wQgghPIZer2fBggX069cPu93O+PHjadWqlbPWwoQJE1i1ahVvv/02er0eHx8fqZ0ghKhx+/bt\nZeXK5ZjNFvr06UOfPn2rNDxQXD1cniTJzc3lvvvuIzk5GY1Gw5IlS4iIiGD48OGkpqYSFhbGypUr\n8fPzK7Ouqqpl/gFrNBrWPfsMg2a9TE5BAQATJjzEwoULgZIvcEbs9o6cOXPmgvWEEAC+2OwKr36x\nhi5RUfQopwvzgQP7sdm0gAbQYDar7Nu3T5IkQgghKjVgwIAytRYmTJjg/HnSpElMmjTJ1WEJIa5S\nBw/+QULCy8UPyzV89NFS7HY7/fsPdHdoohZx+RTAjz32GAMHDuTAgQP89ttvREVFkZCQQFxcHAcP\nHqR3794kJCSUu274pH+RUmp6rBI3NG9O6rvvsHDhOyxd+jHduvWgWbMotNoFgAocQ6tdR8uW4c51\nhgy5HaNRASyABaNRZcCAQTVyzELUflqsdg17jh4t99NrrrkGKCkypmIwaGnc+FqXRSeEEEIIIcSV\n2rJlc3G5BSNgwGzWkpi43t1hiVrGpUmSvLw8vvvuO8aNGwc4umE2bNiQtWvXMmbMGADGjBnD6tWr\ny10/7fREBr38ZrmfabVa/PyuQa93DJ8ZMWIoqjoPaAp05OabYy4YSnPzzV149NHJtG4dQbt2rZg+\n/Tmuvz6q+g5WCI+hAip6ncp1AQHltnjwwYfw8lLx8lLw8rITGHgtfftWXIVdCE9WVFREp06daNeu\nHdHR0Tz99NMA5OTkEBcXR2RkJH379iU3N9fNkQohhBDiUpSdfECVCQlEGS4dbnP06FEaN27Mvffe\ny6+//kqHDh146623OHnyJAHFX84CAgI4efJkBVu4jdTs5yi0WPA2Givcj6IoLFw4D1W14ag5omP7\n9u8ZNmwYgYFNne1iYzsRG9up+g5QCI9UBGjoGhXF4I4dy23RokVL3nprPvv27cXLy4t27W7EWMk5\nKIQn8/LyYsuWLfj4+GCz2ejatSvff/89a9euJS4ujqeeeoo5c+aQkJBQYc9HIYQQQtQ+/fsP4Ntv\nt2I2mwENRqPKsGF3ujssUcu4NElis9n45ZdfWLBgATfddBOTJ08uc4Op0WgqqRfSHlVVeW31anrE\nxJRbOwEgLy+XwsJCwLt4iRadTktq6rELkiRC1CTPmf7tINCPZo2vrbRWj79/I7p37+myqIRwJx8f\nH8Ax7bXdbueaa65h7dq1JCUlAY5ejz179pQkiRBCCOFBQkObMWvWbNas+Ryz2cKtt/amQ4eb3B2W\nqGVcOtwmJCSEkJAQbrrJ8Q/xzjvv5JdffiEwMJCsrCwAMjMzaVLBdKQmbIQ1bsTz8fEVJkgAGjRo\nUPyTvfi/Kopi5dprG1cx0nVVfAlRsZiY1sTH3+V81V5+wGiyzxa5OxAhag1FUWjXrh0BAQH06tWL\nmJiYS+j1KIQQQpQvLS3NeV1p3bo18+bNAyof0jl79mwiIiKIiopiw4YNzuW7du2iTZs2RERE8Nhj\njzmXm81mhg8fTkREBJ07dyY1NdV1B+gBmjcP49FHp/Cvf02TBIkol0uTJIGBgYSGhnLw4EEANm3a\nRExMDIMHD2bp0qUALF26lKFDh5a7vg5oXoVikXq9gYkTH8ZotOLtrWAyWejVq/cFhVuFECXs6LSb\n6NqqpbsDEaLW0Gq17Nmzh/T0dL799lu2bNlyweeV93qEmStXOl9Jyck1Ha4QVyQ5OYmVK2c6X0KI\nmmMwGHjzzTdJTk7mxx9/ZOHChRw4cKDCiSz279/PihUr2L9/P4mJiTz00EOoqgrAxIkTWbx4MSkp\nKaSkpJCYmAjA4sWLadSoESkpKTz++ONMnTrVbccrhCdy+RTA8+fP5+6778ZisdCyZUuWLFmC3W4n\nPj6exYsXO6cALo/WZGLYzVWbcrRr126Eh4dz7NgxGjduLAkSISrgY+xMm+Y+TOx3n7tDEaLWadiw\nIYMGDWLXrl0EBASQlZVFYGBgpb0eAZ6Pj3dhlEJcmZiYHsTE9HC+X7VqlhujEaJuCwwMJDAwEID6\n9evTqlUrMjIyKhzSuWbNGkaMGIHBYCAsLIzw8HB27NhB8+bNOXfuHLGxsQCMHj2a1atX079/f9au\nXcuMGTMAGDZsGA8//LB7DlYID+XyJEnbtm356aefyizftGnTRdd97LbbmNC3b5X3FRjYVGqQCHER\nXz1zD50jI9HrpLK3EACnT59Gr9fj5+dHYWEhGzdu5IUXXmDIkCEsXbqUqVOnVtrrUQghhKiKY8eO\nsXv3bjp16lThkM4TJ07QuXNn5zohISFkZGRgMBgICQlxLg8ODiYjIwOAjIwMQkNDgb9mE83JycHf\n399VhyaER3N5kuRKvDB8uLtDEKLO6dqq1cUbCXEVyczMZMyYMSiKgqIojBo1it69e9O+ffsq9XoU\nQgghLub8+fMMGzaMuXPnlqqn6HCxIZ3VZXmp61jrmBhaV1LzUQh3c+WkGB6VJBFCCCFqWps2bfjl\nl1/KLPf3969Sr0chhBCiMlarlWHDhjFq1Chnr8SKhnQGBweTlpbmXDc9PZ2QkBCCg4NJT08vs7xk\nnePHjxMUFITNZiMvL6/cXiR3ydBQ4UFiYloTE9Pa+X7VqhU1ti+XFm4VQlye6qyELhysVisnT2ZR\nVCSz+gghhBDCNVRVZfz48URHRzN58mTn8pIhnXDhRBZDhgxh+fLlWCwWjh49SkpKCrGxsQQGBuLr\n68uOHTtQVZVly5Zx++23l9nWqlWr6N27t4uPUgjP5vE9Sc4VFvLURx/x86HD1A8JZezYcTRs6Ofu\nsISoViWV0Nu1a8f58+fp0KEDcXFxLFmyhLi4OJ566inmzJlDQkICCQkJF1RCz8jIoE+fPhw8eBCt\nVvKiAH/88TuzZ8/CbrejKAoTJ06ia9fu7g5LCCGEEHXcDz/8wMcff8wNN9xA+/btAceDrWnTppU7\npDM6Opr4+Hiio6PR6/UsWrTIORRn0aJFjB07lsLCQgYOHEj//v0BGD9+PKNGjSIiIoJGjRqxfPly\n9xysEB7Ko5MkqqoyYNYsfj2ajtmmRZd+ikOHUnjjjbkYjUZ3hydEtamOSug7d+68oPDXpfrmm018\n8cVnKIrKwIGDGDjwNpeMl61uNpuV2bNnUVCgAibAzjvvLCIyMqrS2UqEuBSKokhSUgghRBldu3ZF\nUZRyP6toSOf06dOZPn16meUdOnRg7969ZZabTCapmyXEFfDoO7hj2dnsTT2O2WYA9Njtes6ePceR\nI4fcHZoQNaaqldBLVzwvqYR+ubZv/4ElSxZz8uQ5srPPs3z5J2za5JlDeP7880/sdjtgKF6iQ683\nkp5+3J1hiTpm9Ouvo6qqu8MQQgghhBCXyKN7kui12uJMrBmwARrsdr08vRN11pVUQq/os5mlnjT0\niImhRzmVzbds+QazWUPJnwyz2cqWLd8QF9fvMo6irLy8XNLS0vD39ycoKLhatlmRhg0bFv/dsAM6\nQMFms9CkSUCN7ldUD1dWNr8Su/buZWdKCp0iI90dihBCCCGEuAQenSQJadSIxg19ST+TC3gBdqxW\nC/Xq1Xd3aEJUuyuthB4cXH7y4eips7z9wGi8Khmi5u3tDZR+Kq7i5eV1xccE8Ouve3j99bnodBHY\nbEcYODCOkSNrbrpvo9HEpEmPsGjRAvR6DTabhdtvv4OQkNAa26eoPq6sbH4lmul05Jw/7+4whBBC\niDpBUeysXLmCpKQtGI0m7r77HmJjL38YuRCV8eguFxqNhj/z8wEfHPkeEzqdid27d7k5MiGqV3VV\nQi/PZ9vhsQ/+W+n+hw37JyYTOHptmTGZFO66a8QVH5eiKLzxxlzM5v9QULARi2UnX3+dxKFDKeW2\nt9lsfPPNJj79dAW//bbnsvd7yy1deeut+UyePJk5c17nn/+suaSMuDrtU1U6tGzp7jCEEEKICr33\nwX+wWCzuDqNKPv10BevWfcWZM0VkZv7J3Llvsn37D5w9m+fu0EQd5NE9SQD0Wh2ln3BrNBq0Wp37\nAhKiBlRnJfS/K7K+wpc/D+Zdxla4/2bNmpOQ8BqbN29CUez07HkrYWHXXfFxFRTkY7PZgC7FSxqh\n0dxIVlYW4eERF7S12+3MmPE8x46lYrEoGI1w553x3H77HZe172uvbcy11za+sgMQogJP3nknTRo2\ndHcYQgghRIUSN5zj9Jl3efpfj7g7lIv69tskzGYtjqHSGqzWIubOfROtVsvNN9/CpEmPSskFUW08\n6l9Sk7EP8dx/V11QDO+pobfjY7IBFrRaCyaTji5durovSCFqQEkl9D179rB79252795N//798ff3\nZ9OmTRw8eJANGzbg5/fX9NfTp0/n0KFD/P777/TrV1ntkCPkni/AYrNVGkNwcAijR49l7Njx1ZIg\nAahXrz7e3j7Al8VLjqEoO2jWrFmZtnv3/kpqaipmsx5VNWE2G1i+/D/FRViFqF1eXPEVyaWGvAlx\ntUpMTCQqKoqIiAjmzJlTbptHH32UiIgI2rZty+7du10coRBXL0X5iJ0/bcNewWw7rqSqKunpaRw8\n+AdFRYVlPjcaTfz1YLwI0KEo9bDZvNm58yc2b97oynBFHedRPUlyC/7H/K/H0sg3kcm3DQDgX0OH\nEuzvz+qdP5Hf8Br+8Y9hNGzod5EtCSH+ci82JZ+V27ZxT/fuLt2zRqPh6aef4OWXH8dufxab7Qx3\n3303zZo1L9M2Pz+fkqcHxWsDYLFYimumCFF7WGwDSUpOJiZUat2Iq5fdbufhhx9m06ZNBAcHc9NN\nNzFkyBBatWrlbLN+/XoOHTpESkoKO3bsYOLEifz4449ltnVHfLzz5xbXXUfXW25hYP/+GAwG9u7b\nx56DB2ndrBl927Uj/fRptu7bR15hIdfUq0eLgAD86tWjdbNmoDc4t5OTk0N29ikCAwMv+d4xNTub\nEzk5XB8cjH/9srXw7IrC3uPHOaJoCQkJ4cSJEyiKQrNmzdHrL+32OzPzBOfOnSUkpBk+Pj6XtK4Q\nlTsHaDAXFbn135aiKPx77v+RvOsnGuv0ZOv1TJv5MsHBf83UeM89o3jzzTewWOw4JuyoR8m9oNms\n8Mcff1TbhAJCeFSSBFpSYH6Gz7a/5kySAIzs3p2R3buzGkMl6wohyqcCGk6fPXvZWxiK9aJtKjo/\nw8MjeffdBWRnZ9OwoR/31DdBOdvrGBXB+1hxdIDTodPZCA1tLgkSUSvZlQNk5JTtESXE1WTnzp2E\nh4cTFhYGwF133cWaNWsuSJKsXbuWMWPGANCpUydyc3MvmN6+hBeOZ8eg4cjRkxw5+j0ff7KWa/29\nOHU6m5IvSya9HrPNWryGAbAAFryMRq5r0ph/zZxN/fr12bjxf3z44QcYDEZsNisPP/wonTvfUqXj\nWvPpCh5c/RnXGQykKgr/feoperb+q6B0flERfV6cwe8ZJ7DhKDip1erQaDT4+/vz0ksv06CB70X3\no6oq77//LklJW9HrDWg08MILM6utN6cQcCegryRxN6gK21h3xVFs2/Y9Z375md0WCz5YeF+j4dO3\nXmfra6852wzt0I4Bzz5DwrYd/PzzTs6cOY+qOsouGAxaQkNDKt6BEJfIo4bbAGg4QqMGkkUXovpY\n0Gk1dCt10+pqRqOJ4OAQ6pfzNK5ESKNGrJs+nRYBvnh5WYmKCueZZ55zYZRCXIpjaCuZkluIq0FG\nRgahpXpThYSEkJGRcdE26enpZbb1JWACHIn9XkAbFOVfnDpdgKOXYQPAF7PNBhiBAOAuHImSBhRZ\nTBzOymHZsg85ffo0S5cuwWo1UlCgw2IxsGDBPAoKCi56TEeOHGbTmi/YbrWyuaCAxUVF3PPaa8VT\nyzu89OmnJKdlkm82YDbbsVoVzGYDRUV6Tp3K4cMPl1Tp97d79y98++23WCwmCgp05OcrvP76q1Va\nV9Re48aNIyAggDZt2jiXvfjii4SEhNC+fXvat2/P119/7fxs9uzZREREEBUVxYYNG5zLd+3aRZs2\nbYiIiOCxxx5zLjebzQwfPpyIiAg6d+5MampqhbHodOfo2+dWjJXMcOgKJzIy6Gs2U/IN7zZV5eDJ\nk2Xa3RIVxbhx9/Hiiy/h62vC29uOl5eNsLAQBgy4zbVBizrN5T1J7HY7HTt2JCQkhC+//JKcnByG\nDx9Oamqqs/Bk6boKpRl0T2AyfMaskc9WeX8ZGen83/+9TlZWJgEBgUyZ8qRM9SlEKQYdvDPhQY+Y\nieOWqCh+nz9Peo0JD9Cct77aTK/Wrbm11I2wEFeTigqG/13pWnMVrbeJvwZbQiDwHfAykIAjEaLB\nkUBRi3/uA6QACo4kClhscOxYKqdOZaHXG7FYSp4V6tBqFc6cOY2PT+U9wDIzT9BRq6Wkn0sPwGy1\n8md+Po0aNADg19RUiqwlcail4gObTcPx4xV/aS3txIkM7HZNqSPXc/r0qSqtK9wrOXkfycn7yv3s\n3nvv5ZFHHmH06NHOZRqNhilTpjBlypQL2u7fv58VK1awf/9+MjIy6NOnDykpKWg0GiZOnMjixYuJ\njY1l4MCBJCYm0r9/fxYvXkyjRo1ISUlhxYoVTJ06leXLl5cby3339qdvn1ur78AvU2izZqwzmXjE\nbMYX+FSjISY4uML2TZoEMG/eIg4dSsFoNBIeHoFOJxN3iOrj8p4kc+fOJTo62nkBTEhIIC4ujoMH\nD9K7d28SEhIqXHfGXUXsen2WY0xpFVgsZl588TnS0k5htZpIT8/mhReepaioqFqORYi6IOP99xjV\ns6e7wwAcXZLTz5yhwGx2dyjiKpaWlkavXr2IiYmhdevWzJs3D3DUL4iLiyMyMpK+ffuSm5tbyVbO\nYrYOZ/zCD10SsxC1UXBwMGmlChinpaUREhJSaZv09HSCy/ly1I3ScxmmAdHAChwJBGupTzU4EiP/\nA6Jw3Oo6kicmPbRo0YLAwKbYbBagpPC3DVW1V2nGs+DgEHYqdkr6umwAvE0mrqlXz9mmQ4sWeBlK\nEiTaUvGp6PUqLVq0uOh+AEJDm6HTqcXHA2AlICCwSusK94qJaU18/F3OV2ndunXjmmuuKbPO35OF\nAGvWrGHEiBEYDAbCwsIIDw9nx44dZGZmcu7cOWJjYwEYPXo0q1evBi4cwjZs2DA2b95cYZz9+/ap\nFTPCdO58C2FdutHOYOAmLy+WXnMN706eXOk63t7etGlzA9dfHyUJElHtXHpWpKens379eu677z7n\nH4LSJ/KYMWOcJ3h5nrz9dq5r0qTK+8vIyMBiseLodqkFjNhsdtLTZcYBIUqEjB/PgXK6NrtaRkY6\nT0x8gM6PPUbIvffybmKiu0MSVymDwcCbb75JcnIyP/74IwsXLuTAgQOXlNSH94GNnDmX46qwhah1\nOnbsSEpKCseOHcNisbBixQqGDBlyQZshQ4bw0UcfAfDjjz/i5+dXph4JOCon/JU+/x7Yjl6/gOCg\nhjiSHWeBc/gYjTiSEtnAUhw1Sc7hZSiiVWgAo0aNwd+/EQ888CBGowVvbxsmk53HHnuiSjWuwsKu\n47b4EXQ1GLjF25uHvb1ZPnXqBV80n7nzTjq0bIaP0YLRCCaTHqPRjMlkITg4gNGj763S769t23bE\nxcVhMJjx9rbRoIGBJ5+cWqV1heeZP38+bdu2Zfz48c4k/IkTJy5ILJYMWfv78uDgYOdQttJD2PR6\nPQ0bNiQnp+JrkV1R+HnXLhZ/+CFfrV9Pbl5eTRxepTQaDWMfnMRPc+eyYtYsds+fT4ty/g4I4Sou\nHW7z+OOP89prr3G2VIHI0sW5AgICOFnO+LPLVa9efWw2K3/NiKFit9sqrXsgxNVGqyj84+WXOfD2\n226NY97sWUz580/Go3IM6P/xx9wUGcmNVXziJkR1CQwMJDDQ8bRZk05rAAAgAElEQVS2fv36tGrV\nioyMDNauXUtSUhLgSOr37NmzkkSJCTjPTeHuq/UjhLvp9XoWLFhAv379sNvtjB8/nlatWvHuu+8C\nMGHCBAYOHMj69esJDw+nXr16LFlSfr2Okj7AWqBtu0i6d+lCly5d0Ot0HD58GOPhw8SEhtI5MpLT\nZ8/y3f79WO324oKtTfAxmYgMCuJLraOySffuPWnf/kZOnz5NkyYB1CvVE+RiBgwZyszuXcjMzSU8\nMJD6Xl4XfO5tNPLNjBkczMxko6KladOmnDx5EkVRCAoKQqut+lPv0aPv5bbbhnD27FmCgoKKp0EV\ndc3EiRN5/vnnAXjuued44oknWLx4cY3v97/Ll7N56/fk5PwJtAXsfLJiKm+8OoNANyQpQq+9FimK\nICpS2TC26uayJMlXX31FkyZNaN++PVu3bi23jUajqXT8apHFUZ28qpo0aUL37j35/vvvsVoVDAYt\nt9zSlcDAppcavhB1Wvqff1apnc1m5fPP1/DHH8cIDm7CXXcNw8en6jeWlW33ePYp7i3uLh0G9NZo\n2HP0qCRJhFsdO3aM3bt306lTp0tM6o+lqZ+JT6ZMcE2gQtRSAwYMYMCAARcsmzDhwvNiwYIFF93O\nFytXVvhZeHg4g8LDne+D/P0Z3rXrRbfZoIFvlWaZKU+Anx8BFdTQA8c97fVBQRworqEVFFRxfYWL\n8fdvhL9/o8teX9R+TUr1lL/vvvsYPHgwUP5wtJCQEIKDgy8ocFyyvGSd48ePExQUhM1mIy8vD39/\n/3L3e+2115Kb6wU8AjiSNAWFr7J02WdMffKhaj5KIa5MTExrYmL+mkls1aoVNbYvlyVJtm3bxtq1\na1m/fj1FRUWcPXuWUaNGERAQQFZWFoGBgWRmZl7wR+LvWjzwAOP69sWo19MjJoYeMTEX3e8DDzxI\n+/Y3kp6eRnBwMLGxnavzsISokCuznVdCBYJ8qzYV4WuvzSM52YTFch8HDmxk796ZvPbarCv+S6LT\n6fHz8eGH/Hy6AeeBn4C7G198fLgQNeX8+fMMGzaMuXPn0qC4IGOJiyX1R3YL5oNJE2rFWG8hhBC1\nW2ZmJk2bOh7ifvHFF86Zb4YMGcLIkSOZMmUKGRkZpKSkEBsbi0ajwdfXlx07dhAbG8uyZct49NFH\nnessXbqUzp07s2rVKnr37l3hfrOyslEUXxy9SEq05cyfMuRZXN1cliR55ZVXeOWVVwBISkri9ddf\nZ9myZTz11FMsXbqUqVOnsnTpUoYOHVrhNroUFJB3/jzzH3igyvvVaDTExnYiNrbTFR+DEJfCldnO\nK2HQ61n65JMXbZeXl8vevb9hs6UAJmy2oZw505WDBw+yOvriCcvKaDQaJj7+JKNeS6CdTkeK3U7r\nzrdwrs2NrEamURWuZ7VaGTZsGKNGjXJely4lqb/8+++p76WnScOGVU7qC+EuyclJJCcnuTsMIa4K\nI0aMICkpidOnTxMaGsqMGTPYunUre/bsQaPRcN111zmHpEVHRxMfH090dDR6vZ5FixY5E/SLFi1i\n7NixFBYWMnDgQPr37w/A+PHjGTVqFBERETRq1KjCmW0AIsKvQ6fbht0+H+gC6NBoXqND+6hKj6Go\n6DyHD+/CZPKhRYv+lzSE7O9UVSUr6xBFRef5NCQag0GGlAn3c/kUwCVKTvBp06YRHx/P4sWLnVMA\nV6QbsGxf7X8yL4QnSV64kKblVFn/O0VR0Gh0lEylCKDR6FEUpeKVLsENN7QjYe5Cjhw5Ql8/P1q2\nDK/y9JFCVCdVVRk/fjzR0dFMLlVdv+TpXFWS+orakLyCQhbcf78rQhbiisTE9CAmpofz/apVs9wY\njRB12yeffFJm2bhx4ypsP336dKZPn15meYcOHdi7d2+Z5SaTqdLvU6V17tSJQf2PsnZdIo7ZoKBb\nlx7cecfgCtc5efIIzz7bA4vFjKLYadGiHc899zV6fdVLIpRQFDtvvjmO3bu3oNNdg4+PnZkz19G4\ncfNL3pYQ1cktSZIePXrQo4fjYuzv78+mTZuqtN5iqNKXOSFE1VV0Th08cYIx8+fze9ZJQkJCeeSR\nx2jZsiWHD9+H1ToanW4j9evnEhkZWW2xyLhrURv88MMPfPzxx9xwww20b98egNmzZ19SUh8iWbPz\nV9cELIQQQlwGjUbDvWNGMPyft1NQUICfnx96feVfD99++wHOnj2HqhoADYcP7yEx8W1uu+2xS97/\nli1L2bPnKBbLbsAbs/l1Fix4hBkz1l7eAQlRTdzWk+RyZGi1LB41yt1hCFHnnS8qotfzL3D6nAVV\n1ZOScowXX3yOV199gxUrPufgwZkEBwcwZsyLUmlf1Dldu3atsIdUVZP6YKLIms/gV+by4SPjaPS3\nmiZCCCGEu9kVBZ1Wi4+PDz4+PlVaJyvrMKpaUm9Lg8ViIT39wGXtPzX1AGbzAMAx/bai3EFGxseX\ntS0hqpNHJUnWvPgiHUtVLxdC1Iy9qamYrTZU1dF1UlGMnD9/ntzcXMaPH1PheqqqsnHj//jxx+34\n+voyfPgImjYNclXYQtQiPYHdbP4tktsT5vH9y8+4OyAhhBDiAmPHP8yzT0/m+kvoFRwW1o68vK3Y\n7Y4ZCU0mAxERsc7PT506xtmz2QQFXY+PT+UTAzRv3gqTaSlm8wOAN1rtaoKDK6+HIoQreFTZ/S5R\nctIIUd3Ke2Je39sbm2KH4il5QcVut+Pt7V3ptj77bCXLln3Evn2H2L59F9Om/YvTp09Xf9BC1HrL\nAS025V52HT5Agdns7oCEEEKIC5zPn8dLs9/EYrFUeZ2JE9+ladPmGI129HozsbGD6dVrLADLlk3j\n8cfb8tJLg3jooXAOH95V6bZ69RpD27bNMRpvxNv7Fvz8lvPww/Ov5JCEqBYe1ZNECFH9vEeM5H/P\nPkPP4unmAFqHhtK7TRs2702mwGzHZNLRuXNX/P0b8fPPO8nKyqRZszBuuKHtBdtat+4rzGZHcVdV\nBavVwrZt3zNkSMUFLoWom7oDW4AsNBoNJoPB3QEJIYQQfzMQu/0psk+fJjioaj1/GzZswuuv7+L0\n6eMYjd74+QUCjlmyNmz4N1arHqtVBay89tqdvPPO0Qq3pdXqeOKJpWRmplBUlE9ISCuMRq/qODAh\nrogkSYS4yqmqiX4vJZDz0WLqeTkuTBqNhpVPPsHHSUl8mZFJ8+ZhdOnSjYUL57Njxw7sdtDpVAYO\nHMiIEfeU2pYKpabsVVX4qzeKEFcTG1CAt/EJpv8jHp3WozpuCiGEuCpsw2rN5sjRozRp0gTDRYq2\nltBqdTRpct0FyzIy/iiuVVJyH6gnJ+cEimKvdIpgjUZDUFD1TQIgRHWQJIkQV73vURnO7M/XMGvk\ncOdSnVbLmF69aIjjCfjx46n8+ON2LBYjoMFmU/jyy7UMGjQYX9+GAPTrN4D169dhNiuAgtGooXPn\nLm44JiHcS6/9lHG9OzOow40MuPFGd4cjhBBClGMYWm0vFr37HV+s2cjsWdMxGUtP5buuCtsYBEBI\nSBQajR1HNQctYMXfP7jSBIkQtZU82hLiqtcSeIFv9x+rtNW5c+fQ6x3TvTlo0ev1nD9/3tnmrrtG\nctddI4iMbEaHDjfw8stzaNKkSU0FLkStdWjRqyy4/z5JkAghhLjAuHHjCAgIoE2pYc45OTnExcUR\nGRlJ3759yc3NdX42e/ZsIiIiiIqKYsOGDc7lu3btok2bNkRERPDYY39Nv2s2mxk+fDgRERF07tyZ\n1NTUSqKZi9W6nKKizWRkhLKxyjO4lRUd3Z0BAyZhMFjx9tZQr54XTz312WVvTwh38qgkyTd797o7\nBCHqqEME+lU+RWnz5mGAAlhwDKGx4OXldUESRKPRMGjQYGbNms3UqU8TEhJagzELIYQQQniWe++9\nl8TExAuWJSQkEBcXx8GDB+nduzcJCQkA7N+/nxUrVrB//34SExN56KGHioc2w8SJE1m8eDEpKSmk\npKQ4t7l48WIaNWpESkoKjz/+OFOnTq0kmpuK/6vBYr2J7NN/XtGxjRw5i3nz9vPCC//j7bcP06JF\n+yvanhDu4lFJknvmzOHHgwfdHYYQdcxD1DPN5aWRFxZXVRSFswUFzotx/fr1ee65F2nc2BetNp/g\n4Gt58cWXinuXCCFKi5g0jSMnT7o7DCGEELVMt27duOaaay5YtnbtWsaMGQPAmDFjWL16NQBr1qxh\nxIgRGAwGwsLCCA8PZ8eOHWRmZnLu3DliYx1T744ePdq5TultDRs2jM2bN1cYi1b7Bo4aWicw6JcR\nE339FR9fo0YhtGjRHi+v+le8LSHcxaOSJI9YLCzfutXdYQjhctXVNbN8uwlo2IDrS1U1/+rnn/Ef\nPYaAceN48MH7SEs7DkDLluEsXPgOy5ev4s035xEUFFytxylEXWG1t+PO1xa5OwwhhBAe4OTJkwQE\nBAAQEBDAyeIk+4kTJwgJCXG2CwkJISMjo8zy4OBgMjIyAMjIyCA01NGTV6/X07BhQ3Jycsrdr6J8\nBQQC7bDazvHBhys5U0FbIa4mHpUkyQf0Os8t/mOz2dwdgvBQV9o1U1GUSrY+hxN/FjrfpWZnM/L/\n3qTAYsGuKPz5Zw7PPz8dRbHXxKEJUTdptrI/7ZC7oxBCCOFhNBoNGo3m4g2rRX3gCHAC2MHJUyeY\nOv0lLBaLi/YvRO3kUbPbvGc08k1cnLvDuGRHjx5hzpzZ5OScwc/PjyefnEpk5JV3ZxNXj27dunHs\n2LELlq1du5akpCTA0TWzZ8+eJCQklNs1c+fOnXTu3LmCrW+mSUMf57tdhw9jttkAL8AA2MnPz+fI\nkcOEh8sUbUJUiQ8o+ZIYF0IIcXEBAQFkZWURGBhIZmams95bcHAwaWlpznbp6emEhIQQHBxMenp6\nmeUl6xw/fpygoCBsNht5eXn4+/tXsOdcoA9wPXAv4ENunpFjqalERkTUyLEKcbmSk5NITk5yyb48\nqidJgVqfkW/9m1N5ee4OpcrMZjMvvfQiOTn5QANyc828/PJM8vPz3R2a8HCX2jWzYm+zetqjznc+\nRiOOKiSOqX4duVQd2dnZ1XwEQtRhGqD4TBJCCCEqM2TIEJYuXQrA0qVLGTp0qHP58uXLsVgsHD16\nlJSUFGJjYwkMDMTX15cdO3agqirLli3j9ttvL7OtVatW0bt370r2/A2QCtpNwINAC+z2cxgMUm9O\n1D4xMT2Ij3/e+apJHtWTxGw9TErmM4xbsISvnplcTotBLo/pYrKyfsNu1+L4wglgQKPRkp4eyvXX\n3+zO0EQdcrGumZV32/Rm455fad2sGQA9W7dGq9GgqHZAB6jo9VoaN5apfIWosgI91/r6ujsKIdwm\nJyeH4cOHk5qaSlhYGCtXrsTPz69Mu7CwMHx9fdHpdBgMBnbu3OmGaIVwnREjRpCUlMTp06cJDQ1l\n5syZTJs2jfj4eBYvXuw8XwCio6OJj48nOjoavV7PokWLnPd0ixYtYuzYsRQWFjJw4ED69+8PwPjx\n4xk1ahQRERE0atSI5cuXVxJNE8AO9c1wvgiU+kAhzYvvCWvjdyshXMGjkiSgwWYfz+6jt7k7kCrz\n9W2MzWbGMWxBC6jYbEU0bChfOMWVuZSumcHBlRVYvY2pH6/g9xMZjOzWjR4xMSx64H4e++ADNOhR\nNApdu/YkPFy6XQr3S07eR3LyPneHcVFeOiM7E2a5Owwh3KakbtZTTz3FnDlzSEhIcNbOKk2j0bB1\n69ZKhgMIUbd88skn5S7ftGlTucunT5/O9OnTyyzv0KEDe/fuLbPcZDI5kywXNw70etDYQKeCcgyT\nyQ+t1qMGGwhR7Vx6BqSlpdGrVy9iYmJo3bo18+bNAyqfpeNCyWg0m2nexHMSDNdc05Tbb38Ck0nF\naASTSSEu7gECA1u6OzTh4S61a2bFpgH1+XTbbpo3bgzAuN692T57NosmjGf69OeYMGHiBWsoisJP\nP+1gw4ZEjhw5XBOHJ0S5YmJaEx9/l/NVUy51Rqm/a+jTkIBynpoLcbWoaErT8pRMNS+EcDHN9+BV\n5JgF2Aqg48nHHyi3qaIo/Oc/0xk7tjH33hvAZ5/NlnNX1FkuTZIYDAbefPNNkpOT+fHHH1m4cCEH\nDhyocJaOsvpQ3/QyH0wa68qwr1h8/As888yXjBnzCtOmfcGYMa+5OyThYUaMGMEtt9zCH3/8QWho\nKEuWLGHatGls3LiRyMhIvvnmG6ZNmwZc2DVzwIABF3TNLN+/gNuxK7ey4ddfnUtbN2vGPd27Ex0d\nc8H6iqLw6quzmT9/Hh999DHPP/8M33xT/tMPITzVpcwoVZ6TeeeZ+O9/13SYQtRaFdXN+juNRkOf\nPn3o2LEj7733nitDFEKowXDeC/LrAxq8vBrQ8cYby2361VdvkZj4LgUFdvLzraxe/RrffLPEtfEK\n4SIuHW4TGBhIYGAgAPXr16dVq1ZkZGRUOEtHWY+j171HVKVDB2qnqKguREV1cXcYwkNVV9fM8oUA\nL1FoGcwj769m2+9Hef+h8RVOt71v32/s37+foiI9juqUGt5//9/07NkLrdZzp+gWorRLmVGqfF1Y\ns3M37z9Us3EK4U5xcXFkZWWVWf7yyy9f8L6yulk//PADTZs2JTs7m7i4OKKioujWrVuNxCuE+Lvv\ngDYUVxsnOKji71jbt3+G2VxSrw7MZis//vg5vXuPq/kwhXAxt9UkOXbsGLt376ZTp05VftoA7fgz\n38KB9HRalZq9QwhxJZoBE4A0VPUAX+wYR8vAtTz3zzvKbZ2Xl4fjAllyw6tFURTMZgve3t6uCVkI\nN6j6tQrgMGarxTWBCeEmGzdurPCziupm/V3Tpk0BaNy4MXfccQc7d+4sN0myvFSNhdYxMbSOibnC\n6IWoOZ5SPwvqA8HAROB/hIYWVtiyQYNGOO79zDi+Qurx9m7giiCFcDm3VOU5f/48w4YNY+7cuTRo\ncOHJVfksHf8HdKD9E8/SbMIUnv54JTa7vcbjFaJuywKigT+BRhRaJrHp10MVto6IiERRLDgGsKpo\nNFYCA5tKgkRcVS42oxQsK54hSoirU0V1s0orKCjg3LlzAOTn57Nhw4YL6gCVdld8vPMlCRJR27mq\nftaV+xI4DjwF9CEt/XSFLcPC2gItgcNAGjAQm016EIu6yeU9SaxWK8OGDWPUqFHOC2ZVnzY4Mpfd\nUNR8sv5swNv/S0NRPmXO6Nr8x0dcrZKTk0hOTnJ3GFXwCpANvAVo0Gh20rxJwwpbBwY2ZcqUf7Fg\nwVvk558jNLQ5U6c+7apghXCbql+rAJYAFmauXEmPmBh6yJc6UYvVxPWqoilNT5w4wf3338+6devI\nysriH//4BwA2m427776bvn37VmscQojKzAQeBN4BXqZ5aNsKW546lQWMA0oecD9AWtq/ajxCIdzB\npUkSVVUZP3480dHRTJ482bm85GnD1KlTK3za4LCl+L86oIAC8wj++92dkiQRtVJMTA9iYno4369a\nVVunA/0UeANoAtxGPdMBXrn7lUrXuPHGDnzwwTIURZFp4sRVo+rXKoA1dLk+iqeGDsXLaHRZjEJc\njpq4Xvn7+5dbNysoKIh169YB0KJFC/bs2XPF+xJCXC5v4COgFfATg2/7K0mZm5dHgWUJjRpdi1ar\nJSjIgsGwBat1NKBFq00iMNAHWOee0IWoQS5Nkvzwww98/PHH3HDDDbRv3x6A2bNnV/i0oazVQD7w\nHvAFkI230eSa4IWos6aA5jyoPkA2zRuHUWipWi0FSZCIumrEiBEkJSVx+vRpQkNDmTlz5iVcqwAi\n2bp/Pzc//RLbZj+HtyRKhBBC1DqhOOqM/Aoo+Hh5oSgKcxcs5Ift29FqtQQGNuWFF2YyZMgQfv55\nFllZXdFofDEaj3H//TPcHL8QNcOlSZKuXbuiKEq5n1U0S8eFJgAqEAaMR6s5zWO3VfYkTwhxcQqo\nXsAzwD/Yn/45t76QwMEFr8kXO3HVutQZpcpaiaqGczgrkA+/+YaJ/ftXX3BCCCHqpLCwMHx9fdHp\ndBgMBnbu3ElOTg7Dhw8nNTXVmaD38/MDHA+bP/jgA3Q6HfPmzXMOV9u1axdjx46lqKiIgQMHMnfu\n3Ar2GA3EA68BKdSrV481X33Ft99vA+pht0NaWibz57+Fr68vZnMuzZs3oF+/m7nxxkfw8fFxwW9F\nCNfzsMfASvHLG3gdVZ3ES59+xZniol9CiMvRAzAADwGBqOpDFJh9+T093c1xCeHJhgN2iqxGTuad\ndXcwQgghPIBGo2Hr1q3s3r2bnTt3ApCQkEBcXBwHDx6kd+/ezqnn9+/fz4oVK9i/fz+JiYk89NBD\nqKoKwMSJE1m8eDEpKSmkpKSQmJhYwR4tOMoZTAQUdu/Zw/rERBz3hZril4HffvuV7dt/IjMzl5SU\nVP7734/R66Voq6i7PCtJ4mXFMaPGMaAtKk9isbVj89697o1LCI/WDUdR5PPF789js5/GV54OCHEF\nvgeMwHe0bd6s0pYZGb/zzDMDuP/+ViQkjOTs2WyXRCiEEKL2KUl0lFi7di1jxowBYMyYMaxevRqA\nNWvWMGLECAwGA2FhYYSHh7Njxw4yMzM5d+4csbGxAIwePdq5Tll7cdSkmwOo2BUFc5GZkhkMHayo\nqorN5pj2V1GM5OcXcPjw4eo9cCFqEc9KkhQ1w3HT6ctfRYIK0UtdBCGuwHs4kiQ9gZepZxrAPzp3\noGVgoHvDEsKDaVCAsxh1TWlS3C26PPn5uTz33AAOHepHXt4n/PprE2bO/EeFQ1OFEELUXRqNhj59\n+tCxY0fee+89AE6ePElAQADgmGXt5MmTgGOmqJCQEOe6ISEhZGRklFkeHBxMRkZGBXv8BngVaAgY\nib3pJmJionH03D8PnAMsf5vyXkVVVfR6l0+SKoTLeNi/7hAgCziFY9rSnzDo/6BvuwfcG5YQHi0S\nOAkc4o7YJIZ27sVdXbq4OyghPJqKCvhhtZ8hrJKpglNSdqIoLVFVx3XMbn+ZzMwIcnMz8fcPdlG0\nQgghaoMffviBpk2bkp2dTVxcHFFRURd8rtFo/pawuEL1cDwnsx0DNHh7eTHxgQdISTnEmZwzOB5O\nawArer0Fm02DwaAhKCiIFi1aVl8cQtQyHpYk2Vb837bAIeBbBndoR30vLzfGJISnO4zjiYGWxD05\nnC3cQfwtt6CrzouwEFcdL0BHPS8dwf7+FbfyqoeiZAN2HNPb56EoRRiNMtxNCCGuNk2bNgWgcePG\n3HHHHezcuZOAgACysrIIDAwkMzOTJsWJ9+DgYNLS0pzrpqenExISQnBwMOml6sqlp6cTHFxB0t1G\n8biCc4A3iqLg26ABgU0DOZNTgCNJAqqq4dpr/WnWrBmhoaEMHToMnU5qkgjXSk7eR3LyPpfsy7OS\nJPUpLptwEvABcoiNuNWtIQnh+U7j+IJmotAyjh0py/nq55+5vXgsKwxyY2xCeKpIYB992lTeKysy\nsjNhYSEcOXIXFkt3TKbP6dZtLPXrX8Nfw0qFEELUdQUFBdjtdho0aEB+fj4bNmzghRdeYMiQISxd\nupSpU6eydOlShg51zOw5ZMgQRo4cyZQpU8jIyCAlJYXY2Fg0Gg2+vr7s2LGD2NhYli1bxqOPPlr+\nTr1wPCezAOiwWCx4eXmh1fy9lIGGwMAbePLJtTX3CxDiImJiBhET89f7VatW1Ni+PCtJosMRsS0f\nRzEhlWE33+zemITweLnF//UDXsauDOVkbm5lKwghLuoI0IrN+w6gKAraCmpnabU6nn/+CzZs+Dcn\nThwlMvJRunUb6dpQhRBCuN3Jkye54447ALDZbNx999307duXjh07Eh8fz+LFi51TAANER0cTHx9P\ndHQ0er2eRYsWOYfiLFq0iLFjx1JYWMjAgQPpX9E09AU4epM49opXce/8oUMG88fBN7BYLAAYDCon\nThxk/PggIiI6MWnS+zRo0KimfhVCuJ1nJUnsxS+U4h/asXTLFqYMGeLWsITwaN4qFAKcBWwoyld0\ninzGzUEJ4elaASM5VzibF1es4Pn4ePQVdE3W640MHPiwa8MTQghRq1x33XXs2bOnzHJ/f382bdpU\n7jrTp09n+vTpZZZ36NCBvVWZ/VPlr0lsKHIuvrFdO57+15Os/upnbDYLKSk7OHUqC9Dy669beeWV\nwcyeva2cDQpRN3jUtDBe5yk+kUuK4AVyMDPLfQEJURcYKf5LcCugxduopW1YmFtDEsLzpQI/Aw14\n88sUhibMKzOtoxBCCOFW9QCT48e/J/LbtW3LM898Sb9+E9DpTIAB0GG36zh27Dfy86XXsai7PCpJ\nMgbHiBtHGeZ6wBbOFRS6MyQhPJ8dR+csmgM2cgvySUpOdm9MQni8+sBG4CRm21d8/3sav6amujso\nIYQQ4i8qznEFjRqVP3zGy6s+qmrnry4nKqBgMMjEGaLu8qgkSRgl5/EJHIPouhB4jYyHE+JKeJ0v\n+ekw4A3UI3H3bvcFJESdkAdk40jq+6HXNiK/qOgi6wghhBAudBbHVyooM91widatexEcfD1GowoU\nYTKpDBnyJEajJElE3eVRNUleBcyYcGQwY/A2buPu7tPcHJUQni0O+BKA74AbAb8KaycIIaqq5MxS\ngOfwMp6UYWxCCCFqF18gH7DDoAqKu+r1BmbM2MzmzYvJzk7l+utvplOnO1waphCu5lFJklwMlFRv\n7djSypxRk7mxRQt3hyWER1OcP9mBGRh0wxka+6T7AhKiTtgF+AOPALN4dOBg6ntV/tQtKeljPvro\nKYqK8rnxxgFMmvRP50wDQgghRLXT4JgGOB/O5OQQUUEzo9GLAQMmuTAwIdzLo5IkWnqh8A2+vg14\nZvYznAXWlfp8KKvdFZoQHmuz8ycdev1QRgwfRlbLlhecW0KIS5WOI/HYA5jPi59uxB7eghvatCn3\nWvXd/v188N5sCi16QM+vvySy7t1TLHvsURfHLYQQ4qpSPGQBzGoAACAASURBVAXwsv+soXNs7N8+\nlLtBcXXyqJokdv4JeHFDmzbuDkWIOsNMAAAGg43333mLO24f5OaIhKjdEhMTiYqKIiIigjlz5lTQ\nqhBHkuQd4E9sNj1bvv2hTCurzUZyWhort22j0AKOZxdaiqw6NpQzFaQQQghRbfJwlM4C8s7+NVvN\nqVOneHP2bF6c8gjL3n8Hs9nsnviEcJNa05MkMTGRyZMnY7fbue+++5g6dWo5rd5HpYjbb7vN5fEJ\nUVep3AO8wT0jR9LQ19fd4QhRq9ntdh5++GE2bdpEcHAwN910E0OGDKFVq1YXNjQAVjuwEvgB+Jod\nO17n3j0PcP7cOfzq+TBz+HCeXb6C3PwCFFVBg56/Jgm207BeAwBUVeU/333Hd/v30zIwkIcHDMDH\nZKo0ziKLhdfXfMWeY1kUmvNo7GWg1XXX8djgwXgZjRe0PZWXx9uJieTmFzAk9iZ6tW59Wb8bs9XK\nwq+/5veMDDpFRHDvrbei1XrUsxghhLiqNAJycFR7jLr+egDy8/N5/umnuf/8eW5RVd4+eZKFWVlM\nefZFN0YqhGvViruXkpvOxMRE9u/fzyeffMKBAwfKtPNiB2Djuuuuu2B5fkEBP2zbxspt2/jz/Pky\n6wlxtaraE++lAHS5+WbXBSaEh9q5cyfh4eGEhYVhMBi46667WLNmTZl29a0lP1mA/wEPUliUS27e\nWWyKgdPn8nno/ffJOW9GUesB9VGxAvnotGa8jXbm3zcegClLlvDwe4tZ8s02Zn36BT2eew6LzVZh\njIqi0P+lN3h1TR5rf7qTzb/V55ede9n2+ecMmzULRfmrElH22bPc+OSTzFm9noWJW7gjYQ7//fbb\nS/692BWFuBkzmLHycz7csp0nli7jvrffvuTtiLrj008/JSYmBp1Oxy+//FJhu6pdp4QQl6oq59Za\nHCVJAB6ddC8A+5KTud5m40lV5RZgsdXKnuR9FBQUuCRuIWqDWpEkqepN54OAEThfKhGSk5PDU5Mn\n88s777DsnXeIffxx0s+cuexYkpKTL3vd2rQP2U/t309Nq2ry0ZfTADTy96+ROJKTk2pku7Ifz9mP\nq47FFTIyMggNDXW+DwkJISMjo0y7xs6f7Dgq//wK6IB6gAmoX/y5EUflPG3xcjsajZXvZr1Ev3bt\nKDCbeXfjRgrMesBEkdXAkaxs5q9fX2GMvx0/zq/HzlBkWQbcg8JnpGJkhtXKoaNH+e34cWfbj7Zu\nJTffgs1uBEwUWPRM/89/nZ9X9e/hzpQU9h1PL66pYqLAbGDlDz+QffZsldavS3/f69KxXIk2bdrw\nxRdf0L179wrbVPU65SrJyftkP7VwH3VxPzWtqudWMFCS01+fmAiATq+nUFWdPRuLcPRo1F3mzId1\n7f+dnFe1dz/VqVYkSap60xmI43by+ZkvOZd9+skn3Hn2LJ8XFbGiqIh/njvHzI8/vuxY5AZK9lPb\nbzyrqqrJx3/WcBx16cu+7Kf27sNVNBpNldrlO39Sgd3AIBy9Sv5+2bWWamcDdKiqSutmzQAoslqL\n91myXw1oNPxy5EiF+7bZbGg0XjiSMgAGNBiwAz4aDdZSvVDOFxZis6ul1tZQaLE431X172GB2YxW\noy0VJ+i0OopKbasydenvuyceS1JyMjNXrnS+qkNUVBSRkZGVtqnqdcpV6toXBvkyV3v3U9Oqem49\nAngX/7zmyy8BaNO6NTl+fjys1/MfYJjJRK/uPTFdZJhnRera/zs5r2rvfqpTrahJUtWbzhdxZDOL\nTmSwLzmZ1jEx5GVn07FU1+GOisIH2dk1EqcQlyIpOdmtCZfyko87duwo0+43VwYlhIcLDg4mLS3N\n+T4tLY2QkJAy7f7q7+gF+KDXm3HkJopwFCwpSR6YcSRKVEDFoDXRq01rZy2Pa+rV48brWrD7aBoW\nmw6Nxo5Oq6PZtddWGGOb5s1p0tCK2fosVvtgtPyXxhTwiVaL2qABbYoTMABDbrqJ//vyKwotVkCL\nt9HOP2/pdsm/l5vCwzEZdGiLLCiqDqNOITwwkOAa6qEmqlePmBh6xMQ4389atcol+63qdUoIcWmq\nem5twVFmHHAOxTQZjcyYPZsvPvuMT0+eok1MG/r2H+iCqIWoPWpFkqSqN50lz7q6dulC6+KLeeQN\nN/D2oUP0tFjQAu8YjfSU2W9ELeCum84SVU0+lsyfsXzlSlrHxDjPLSFqo+TkJLf2TOnYsSMpKSkc\nO3aMoKAgVqxYwSeffFKmnWPktgG93kCz0Ho8+/QzHDp0iDmvv4FdccwS0KFlOD1iovnixx/Jys3D\noNMR17Yt7z44wbkdjUbDl9Of5qF//5vtfxykWeNreWfCBD7dtq3CGE0GA0kvPc1jiz/h12MbsdsK\n8NXV51TzGBLvv/+Cwq3tW7Tg0yef4IkPl3KuqJA7OnVizqhRl/x78fXx4dtZLzHhnXc5cjKLG1u0\n5J0JD0jh1jouLi6OrKysMstfeeUVBg8efNH1q3qdEkJcmqqeW+uAPjgGhvbq0dO5vF69etwzejRW\nDDURnhC1n1oLWK1WtUWLFurRo0dVs9mstm3bVt2/f/8Fbdq2bet4zCYveXnoq0ePHi49r7Zv3672\n69fP+f6VV15RExIS5LySV516ufq8UlVVXb9+vRoZGam2bNlSfeWVV8p8LueVvDz9VZ3nVc+ePdVd\nu3aV+1lVrlOqqqotW7Z0++9EXvK6klfbtm2r7ZyqCrkHlNfV8KrJe0CNqqoqtcDXX3/tnAJ4/Pjx\nPP300+4OSQiPZrPZuP7669m8eTNBQUHExsbyySeflJ2qVAghhKghvXr14vXXX6dDhw5lPpPrlBA1\nQ84tIa5MrRhuAzBgwAAGDBjg7jCEqDP0ej0LFiygX79+zuSjXByFEEK4whdffMGjjz7K6dOnGTRo\nEO3bt+frr7/mxIkT3H///axbt06uU0LUEDm3hLgytaYniRBCiP9n787joir3P4B/ZmOVfV9FQcQB\nt0JLy9QUXErTqyJohVqaem+Z9itNc1/A1NK82XbdN0DcyC3Dq2YuUa4BKmpCgogiKALCzDDf3x8j\n5zKyOCjMDPB9v168Xsw5z3me75lzvpzhmXOehzHGGGOMMWZIRjei2oEDBxAQEIBWrVph8eLFVZb5\n4IMP0KpVK7Rv3x5nz56t8zY2b96M9u3bo127dnjppZdw4cLTzf+hy74AwO+//w6pVIodO3bUWztH\njhxBx44dERQUhB49etRLO7m5uejbty86dOiAoKAgrFu3rtZtjBkzBi4uLmhbw+C7z3r8dWmnrs4B\nY6CPnNKlHc6r2rdRFzkF6CevmlJOAZxXTT2v+FpVPzivap9X/Bmw9jivKmsoedWYrlW6tMN5ZUD1\nNtrJU1CpVOTr60vXr18nhUJR5QCue/fupX79+hER0alTp+iFF16o8zZOnDhB9+7dIyKi/fv317oN\nXdspL9ezZ0967bXXKD4+vl7ayc/PJ7lcTjdu3CAiojt37tRLO7Nnz6Zp06YJbdjb25NSqaxVO7/8\n8gudOXOGgoKCqlz/rMdf13bq4hwwBvrIKV3b4byqfRt1kVNE+smrppJTRJxXnFd8raoPnFe1zyv+\nDMh59SSNKa8a07VK13Y4rwzHqO4kSUpKgp+fH3x8fCCTyRAeHo7du3drlUlISEBkZCQA4IUXXsC9\ne/eQk5NTp2106dIFNjY2QhuZmZn1si8AsHLlSgwdOhROTk61bkPXdrZs2YIhQ4YI0yo7OjrWSztu\nbm4oKCgAABQUFMDBwQFSae2GvenWrRvs7OyqXf+sx1/XduriHDAG+sgpXdvhvKp9G3WRU4B+8qqp\n5BTAecV5xdeq+sB5Vfu84s+AnFdP0pjyqjFdq3Rth/PKcIyqkyQrKwteXl7Ca09PT2RlZT2xTG3e\nZF3aqGj16tXo37+/zvXXpp2srCzs3r0bEyZMAKD7nOa1befKlSvIy8tDz549ERwcjI0bN9ZLO2PH\njkVKSgrc3d3Rvn17rFixotbtPE0c9Z1kT3sOGAN95JSu7VTEeWU8OVVdLPWZVw05pwDOK4Dz6mni\n4GtVzTivap9X/BmQ8+pJGlNeNaZrla7tcF4ZjtHMbgPofiLTY2PN1iYBalP28OHDWLNmDY4fP67z\nNrVp58MPP0R0dDREIhGIqNJ+1VU7SqUSZ86cwaFDh1BcXIwuXbrgxRdfRKtWreq0nUWLFqFDhw44\ncuQIrl27hpCQEJw/fx5WVlY6t6OLZzn+tfUs54Ax0EdO1bY855XubegrpwD95VVDzymA84rzSjd8\nraodzqva5xV/BuS8epLGlFeN6VqlazucV4ZjVJ0kHh4euHHjhvD6xo0bwm1M1ZXJzMyEh4dHnbYB\nABcuXMDYsWNx4MCBGm8depZ2Tp8+jfDwcACagXn2798PmUyGgQMH1mk7Xl5ecHR0hLm5OczNzfHK\nK6/g/PnztUpkXdo5ceIEZsyYAQDw9fVFixYtcPnyZQQHB+vcTm3jqO3xr41nPQeMgT5yStd2AM6r\n2rahj5yqKpb6yqvGkFMA5xXnVe3j4GvVk3Fe1T6v+DMg59WTNKa8akzXKl3b4bwyIP0OgVIzpVJJ\nLVu2pOvXr1NpaekTBxc6efJkrQd90aWNjIwM8vX1pZMnT9brvlQ0atQo2r59e720c/HiRerVqxep\nVCoqKiqioKAgSklJqfN2Jk+eTHPmzCEiolu3bpGHhwfdvXu31vt0/fp1nQYXeprjr2s7dXEOGAN9\n5JSu7XBe1b6NusopIv3kVVPIKSLOK84rDb5W1S3Oq9rnFX8G5Lx6ksaUV43pWqVrO5xXhmNUnSRE\nRPv27SN/f3/y9fWlRYsWERHRt99+S99++61Q5p///Cf5+vpSu3bt6PTp03XexjvvvEP29vbUoUMH\n6tChA3Xq1Kne9qXc0yayru0sWbKE5HI5BQUF0YoVK+qlnTt37tDrr79O7dq1o6CgINq8eXOt2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r19CvXz8EBwfjlVde0WqrYsxNJa9u3rwJDw8PrWXNmzfXeXuRSFRpzKfffvsNPXv2hLOzM2xt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FNVcReK68iL4rMP/PyCGTLkNazWZHx87sVi6UyvXk8SEdGgrLdX10El5yciJZ5hdWXTpk3E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y7OhLD8t89dUQ1q37mrNnfZDle9i0aS7798fx9NNzSu35EISSsQYIBIYCx3CwDRt66BD8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\nzcc8+OCDhIaGMnDgQA4fPkx+fj4XL15k5syZ5pZV7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HrNGlu7oVDUGBoAc9Gm13YCtu3f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cdnkiiKwp/+9CdMJhOTJk0qPx4dHU1iYiIAiYmJ5cmT6Oholi1bht1u5/Dhwxw8eJB+/fpV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\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408bM59otA0Wm1y4uery961dP8YSotdw4e+aMzQrcw8MHF5f/Z+++o6Oo2gAO/2ZrOhBK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mjSbr8HYKLXkUWPPIPrqX6e8/ftZ1tm//k2+/ncbq1YuCcpDsT374gVsnv8CXX85FVVXp\nIBGmMgyDSZNTOFKwnwJLLoXWo+zO3MWXX84pV7uKohAbewH16ztP6SAxDINlyz7i+edv5o03/s3+\n/dvL+QqEKJ2Q6qZ7afJr3H//K1x4YVssFjtuy/F5slVwez2sXbuEmJjG5oYUQogy2rZ9O65CDbAD\nFsBFzuEcbtQM00+My3f6I86Xrnt59tlb2LJlH4ZxEYbxFI888g5t215/ynJHjx3FrbnBUAEH4MGt\nuNmzew9NmjYxJbsQZtmzZz0ewwXH3y69ips9ezadcfklS95j2rRnUJTuwCratbuUhx56w/T322Iv\nfvklo9M+Jd+loCiwYsWvTJ78EjVr1jI7mqiEDMNg8uSBbN26FiKODySsgNtws3v3Lp9so/c/zjYm\nfzGXd2d9Rr5LQVXgj1/T+GPypFKNySjnLaI8QupKEk2Dzz5LpU6deDxud/HYpUVjmXqtfPPNh2bG\nE0KIcvlryxaK+q7DKeooqWJuIGGaX3/9hc2bD1BYuAiX6w007UNee23wacvZ7fbj335HUrTPhGMY\nKoWFhYGOLITpLkrohF0JL5okwwAbYSQkdChxWY9HY+rUR9G0ebhcU3C5vuW335axcePywIY+iwlz\n5pLvsgJ2DMOOy+Xlxx+XmR1LVFLp6d+xZs2fYNwAmv1EndkVBwkJzfyyzZNrQDfsHHN5SVsePDUq\nKq6Q6iQB0HUPDkcELVteA8cckBsBR8OBUeTlyXS4QojQZbfZKOltORgvARf+lZOTg6635O8LPluT\nn7//tH3BMAxU9eR9RsFms1GjZulmThOiIrn55qEkNeuGtcCBrcBBk4btGND/uRKXzc8/gqLYgKbH\nn4lAVZuTk5MZsLzn4tW9pzzWdfB4vGdYWgj/KqqNROBFcDshNwxyoXXLNlxzzbV+2aZX1zlxaRhg\nGODxSg0I/wt4J0lqaipOp5MWLVrQv39/XC4X2dnZJCcnk5CQQI8ePcjJySlxXYdD4eqr/w3A5Zff\nit0eD8ZcYD022x84nZ0D+EqECA7lqSkRXK7o1g1wAxpFl8pp1K5a4x8fgkUgmF1XCQkXoSjzgPWA\nF1WdSKNGnU67DSA8PJyWrVpis3kAD6qqER7hwJnk9Fs2IcrK33VltdoZOnQuU177i1de2ciokYsJ\nCyv5iryqVWsfH9D1TUAHfkXXf6Fx4zZl3r6v3du9OxEOL8XHA5vNoGPHS82OJYJMoI5XF154Cbq+\nFNgKLAYGEx2dyGOPPomqWsrdfknuvvJKIhxFxzfQsFsNenco+eowIXwpoGfe27dv5+2332bVqlWs\nXbsWr9fLjBkzGD9+PMnJyWzatInu3bszfvz4Etfv338sN9zwXwAuvbQPPXv2x2LphaomkJjo4f77\nJwby5QhhuvLWlAgul7RpQ//bbkNVNCCf6GpV+Xn8WLNjVTrBUFcXXtiE++5LxW6/BkWJpUGDn3ni\nieklLvv4kMfpnnw59RvUonVbJ6kTnqNKFblVSwSXQNZV9eqx1Kx59oGRFUVh+PDPiIn5CEWJJjz8\nDh555B2ioxuVe/u+Mq5/f4bedCMt4+vgdDZh9OixxMXVNTuWCCKBrKu4uAQefvh1wsL6oiixxMV9\nyzPPzPbBqziz8XfczpO9e9Eyvg5XJDXh2zGjaRIb69dtCgEBHrg1KioKm81Gfn4+FouF/Px84uLi\nSE1NZenSpQAMHDiQbt26lVjM11476MTPiqJw663D6Nt3KLruwWq1B+x1CBEsyltTIvj0vfkmpt3U\nG83jwWGzmR2nUgqWuurW7Xa6dh2Ax6Nhs515akW7w84999/jtxxC+EKw1NXJ4uISeOWVlWhaITab\nI2gGbC2mqipDb76ZoTffzBzkeCBOF+i6at++N9On34jb7cJuDzv+7Ppyt3smFlVl2C23MOyWW/y2\nDSFKEtArSWrWrMljjz1GgwYNiIuLo3r16iQnJ5OVlUVMTAwAMTExZGVllbpNVVUrbAeJYRhs3bqF\n9PQ15OcfMzuOCEL+qClhLsMwWLtzJz9t2MChvDyz41RKwVRXiqKctYPEn3bv2s2a1Wvkdj3hE8FU\nV/9kt4eZ2kGSvnMnS9asYf+RI6ZlEKHJjLpSFOWkDpKy2blzB2vWrCY3V/Z5EZwCeiXJli1beOml\nl9i+fTvVqlWjb9++fPjhqTPSKIpyxgNVWtqYEz87nV1xOrv6Na+ZdN3LKxNS2ZmRToxqYYdFpdXo\n0Tjr1zc7miiljIx0MjLS/bqN8tYUQFrajBM/O51JOJ1Jfssrzs4wDN567TXSf/2VhhYLmwyDz55+\nmg4JCWZHCxoZGUvJyFjq121IXcEnU9/jx4WLudBqZYPXy+CnnqBlq5ZmxxJ+Egp1NSYt7cTPXZ1O\nujorxrg7H7zzJiu//5YmVivrdZ1PhgypMK+tMgvEOSCEXl0ZhsEHb7/Bb8u+p5HVykZd5z9Dh5OY\nKPu8OLdA1RUEuJNk5cqVdOrUiVq1iuZ3v/nmm/n555+JjY0lMzOT2NhY9u3bR3R0dInrp6SM8EmO\ngoIC3nnnTdaty6BGjZo88MC/adgweO5BBVi69HvcGen87nJhB6ah8H//+x/fT5RxV0LFPz8YzZo1\n0+fbKG9NAaSk3ObzXKJsVq5axZZffuFXTaMK8CXQb/ILvPDmVLOjBY1/dpDPmuX7MVv8WVeGYTB3\n7ucsXrwQi8VK3763ctllXcoe1t373MvY5pxXkxvWb+C3RUv4TdOormn8ANw5YTJvfPgeJ88yICqO\nUKirESkpPs9ktvT0taxZ+h2/aBrVNI1vgTsmTmTne++ZHU2UUyDOAcH8utq9ex1vvPEUBw8eoFmz\n5jzwwL+JiDjzmFjp6WtZ98MyftM0ojSNRcDgyRN4ZWrRmFtyW5k4m0DVFQT4dptmzZrxyy+/UFBQ\ngGEYLF68mMTERHr27Mn06UXFMX36dHr3LsVJXzlMmvQ8v/zyG4cOFbJ58y5GjhxOdna2X7d5vrIy\n93Hl8Q4SgGQMth44YGomEXyCpaaEb/y1eTMdj3eQACQDew9nyxTAAebPupo37ws++2wW+/cfZd++\nw7zxxmv8+ecqX7+EcsnKzKKdolD9+OPLgPxCF4WFhWbGEiFOjleny8zcRxtNo9rxx1cA+/Pz5bYb\nUWpm1lVu7gGGD+/Gpk07yM52sWLFKlJTx511naysTDoYOlHHH3cHDuTl4fF4fJ5PiPII6JUkrVq1\n4s477+SSSy5BVVXatGnDAw88QF5eHikpKUydOpWGDRuSdtKlX77mdrvJyFiLrkdS9I2YBcPwkpGx\nli5dguf2nfiGjZjjcPBvl4tqwAeqSssGDcyOJYJMMNSU8J38/Hy+A7KAGOADINzcSJWSP+vqu+++\nxeVSKT78aprO0qXfc/HFwTPtaIP4BqTpOjuAeOAzoGZUFGFhYUWzMApRBnK8Ol2NGjVIMwx2A/WA\nj4FwFFZv305yq1YmpxOhwMy6WrfuBwxDgeNf6Xo8Kps3/0V+fj4RERElrtOgQTyvKgp7gLoU7fMN\n6tTBag3oR1Ihzinge+STTz7Jk08+ecpzNWvWZPHixQHZvsWiHr8vz6Cok8QADOz24Br8tWPHTmxZ\nt46kJQuJtFgIq1adJQ8/bHYsEYTMrinhO40aNmSJxUYLr5uqQD4KHps16GZcqAz8VVdhYQ5AP/FY\nUSjqfAgijRo3otft/en0/ofUsFpx2aw8/sxTsh+KcpPj1akuuqgZ+YpCG8MgCjiGAnYH4UF2TiqC\nm1l15XBEYBg6J3+mMgzjrB0eCQkXcfUtKbRP+4QaVituu50nhgzza04hyqLSddupqoVevW5i/vyv\ncLkMrFaFWrVq0bp18HyLB0WDLN1+7/306ptCfn4+depEU9+in3tFIUTI6tSxIzM/nUX24TwOeXXs\ndoVbZcyYCqVfv9t5/vnn0LRCFEUhLEyhZ88bzY51mqt7XsdlV3Yl90gutevUxibTUQvhc5GRVbns\niu78/OOPHNR0wmwWWsXXp6MM1i1CQIsWVxIdHc++fZtxu3UcDoXu3a875xfP1/e+ma5X9SAvL5c6\ndepgtcrxRQSfStdJAnDbbf2Jj49n7do11K5dh+uuuwG73ZwpFs8lKqoaUVHFd6tKJ4kQFVl4eDgv\nTHieufO/ISfnMBdf3Ib27TuYHUv4UIsWLRk5cgzLli3FZrPRo8fVxMZeYHasElWpUoUqVc48AJ8Q\novz+9a9B9LuoKcs3buSiuDgGXXMNVovF7FhCnJPVamfcuGXMnz+Y/fuzSEx0ctlll5dq3cjISCIj\nI/2cUIiyq5SdJIqi0KnTZXTqdJnZUYQQ4hSRkZEy41AF17RpAk2byjfFQoiic9KBV1zBwCuuMDuK\nEOfN4YjgpptuMTuGED4X0NlthBBCCCGEEEIIIYJVpbySJFTJ3OFCCCGEEBWLnN8JIURwkStJhBBC\nCCGEEEIIIZBOEiGEEEIIIYQQQghAOkmEEEIIIYQQQgghAOkkEUIIIYQQQgghhACkk0QIIYQQQggh\nhBACqESz26xb9wOzZ4/H7d7L1VdfQ6dOl5kdSQghTrMvM5P3PvyEnJzDtG17CTfe2BtVtZgdS/jQ\n8uU/8s03C7DZbNx8cx8SE51mRxJC+FF29iE+/HA6WVn7SUpqQd++KVitMqONqLwMw+D777/lu+++\nJSwsjJSUW2nSJMHsWEKcUCk6STZt+pXnnuuJphkAbNnyGh6Ph8sv7+bX7eq6Tk5ODhER4YSFhft1\nW0KI0Hc4J4cnnnqK/HwvhqGyY8dOsrMPce+9D5gdTfjIsmXf89Zbb6JpCgAbNjzLiBGjSUi4yORk\nQghfy8s7RH5+FiNGDOPIkQJ0XWHHjl3s3buHxx570ux4QgREYWEB+fkFVK9eHVUtuonhm2++5qOP\nPsDlUgGddetGMG7ceOLjG5qaVYhilaKTZMbDB2oAACAASURBVOHCN9A0HXAAoGluvvjiOy6/fOJp\nyy5b9jELF36MzeagT5+HcTq7lmmbhw7tZvToHhw6tBNd17nppltISbmtPC9DCFHBrfjtNwoK3BhG\nOKDicmksWrSQe+65H0VRzI4nzsv1JT47d+4zxzvswwEDTTvGN9+sISHh0YCmE0KU11dn/I3H42bS\npAmsWfMnuq5jGCqGEQFY0DSNFSt+pbCwkLCwsMDFFcIHfv/9K7744m0Mw6Bnz3tp167XWZf//PPP\n+PTTGaiqhWrVqjNy5Biio6OZN+9LXC4LxR9FNa2Q775bwl133RuAVyHEuVWKMUkU5fSXWdIHju++\ne5+33hrNpk13kJFxLamp/di06ZcybfOFF/qxf/8+3O4wvN5wvvzyC/78848ytSWEqBy27diBrqvA\nf4G3gAR0XW61qUiysrYD1YCXgecAO1u3rjI1kxDCt2bN+pT09HV4PBHouh3DsAKPUvS+3gTDsEnH\ntwg5f/yxgBdffJD1629hw4a+vPzyw6xc+eUZl09PX8vs2bPweMLRNAcHD+YyadLzAJS0+0tNiGAS\n8E6SnJwc+vTpQ/PmzUlMTOTXX38lOzub5ORkEhIS6NGjBzk5OT7d5tVXP4jdrgIuQMNuV+jd+4nT\nlps37100bTLQE+iPpv2XRYs+KNM2d+xYc/zDjgKoaJrB1q2by/4ihDgDM2pK+Ef2oUNAMvDI8f+n\nATqGYZiaqzLyV115PA5gCtAL6A88zdGjBT5OL0RwqizHq/Xr16FpUHQOCHAdRZ3fycBMFEXB4XCY\nFU9UMIGqq/nz30PTRgC3ADejaaP56qv3zrj81q1b8HhUij5uKhiGjV27dgBw44034XB4AQ3QcDgU\nrrzyqnJnFMJXAt5J8p///IfrrruO9evXs2bNGpo1a8b48eNJTk5m06ZNdO/enfHjx5+1jaNHs1mw\n4HW++GIyu3evP+c2mzS5hBEjFtC27VW0bHkZDz/8Hp07p5y2XNF9cu6TnvGcuHfufNWoEQd4jj8y\nsNtVateuU6a2hDgbX9SUCA61atXi7/cNKHo/UuXbFRP4q64cjnBOPc5oVKtW/mNDevp3zJ49nmXL\nPsLr9Zx7BSFM4Ou6ysrJ4dX583nhiy/IzNzix+Tn54IL4rBYAIo7uE+ueTc2mwzaKnzHn+eBO3as\nYc6ciSxc+CaG4eXUc5Szf06qU6cOViv8XQceqlevAcBVV/XgX/96kBYtEmjXriVjxoyjfv0GZcoo\nhD8oRgC/ojxy5AitW7dm69atpzzfrFkzli5dSkxMDJmZmXTr1o0NGzacGlRRcDp7YrWqbN26isLC\n9uh6bazWz3jqqZkkJnYpd77ly2cxZcoTaNrTQC52+0SuvfZuwsIiadWqB02aXFLqtjZv/o1nn70G\nAF330Lx5c4YOHSazVFRiKSk3+fyKgPLUFBTVVVra5z7NVF69TzmZDA5nvvPctw4ePMj9gx4H/gW0\nAJ6nSRMrzz03NkAJzqbkMTbMlpJiD9K60kps+5tv3mDq1JHAWOAoMJpRo74s1zFs7twXmTVrCm73\njdhsK2natAbDh8/6+3hjm1Pmtv+pdynKcw4lfwDMzj7Ejz/+gK7rdOx4KbGxF/gsV2nYAvze4qZ3\nQLfnS8FWV4qi0L9LMjsPHiG5ZVOevKkne7OzaffkSI65rkTXI1CtXzJ69Fc0btzap7nPrOQjw6ZN\nG1m5cgWLFy/C4/EC4HIBDMIwEnE4XuCaaxIZMKBfgHKKYOCPc0Aof11paWlnbPubP//klklv4fWm\nYLHsJjz8TwoKCtC0YYCKqo7k/vvH0717TInr67pOauo40tPXoigKqqowfPhImjVrXu7XLQT4r64g\nwAO3btu2jTp16nD33XezevVq2rZty0svvURWVhYxMUUFFhMTQ1ZWVonrZ2TcAnwAXA68BoDX25F3\n3x3OpElLy52vU6c+2O1hLFr0CaqqsHWrg/nz38Tr9fL55xN4+OH3aN++dCc9TZq043//W8/mzVOo\nUiWShISLynxVihBnUt6aEsHl519/BS4EDgNzgGvZsuVNc0NVQv6sqypVamCxKHi9rwMGFosVu73s\ngze63S5mzBiF1/sbUA+Xy8Pmzd1IT/+eli27l7ldX9u/P4shQx7D5dIxDJg9+1NGjx5Ho0aNzY4m\nAqS8dTXzJyde/RJWbXmNLZnTcNitHMm/Da/+bNEC3lZMnz6K0aPnBuolneann37g9ddfw+1WsFpV\nqlYN5957HyAuLo7PP/+KnJxfuOSSy7j66h6mZRQViz+PVw+9MwNNex1IxusFXb+P+PgdbNv2PLp+\nIbp+E++/P4IWLcYQHX16R0lu7hG2bdsCWPB6QVUNdF0v5ysWIjAC+qnd4/GwatUqBg0axKpVq6hS\npcppl38pinKWS8sfBVZSNCtAsQs5dsx3969ecskNPPXUR7RseSlHj+bhdqvoug1NU3j33UfOq61q\n1aJp27YdzZo1lw4S4RflrylRHtnZ2YwcM4Y777mHJ4YOZdfu3eVq78flyym6guQl4H3gCQxDk5OK\nAPNnXc2d+yZeb1cgCziM13sFCxZMK3NWl+sYimIF6h5/xoqiNOTYscNlbtMfZs36lPx8Lx6PHa/X\nTmGhwocfvm92LBFA5a0rrz4KuJ58rRMfLP2GD79fhFffd9ISF5KXZ+5+/+6776BpVgzDgdtt5ejR\nAo4cyaFu3XoMHvwvhg9/jGuuuVqOycJn/Hm8ys0/StFnrh5AIzyen9mxYwO6/jlFV1K9iMt1I8uX\n/1ji+l99NY+jRzW8XgeG4UDTVN57793zziGEGQJ6JUm9evWoV68e7dq1A6BPnz6kpqYSGxtLZmYm\nsbGx7Nu3j+jo6BLXt5GNAXh4B4gFBmC3P0vbtr7vkT92LAePxwPYjz+jUlCQ5/PtiIorIyOdjIx0\nv26jvDUFkJY248TPTmcSTmeSXzNXFF5d55lRozi8fz9WXWfP0aM8PWIEr7/6KlUiIsrUZkREBDAX\nuA1wAs9QPHW5KJKRsZSMjPJfOXg2vqmrMSd+djq7nphO/kjOTlR+IwIXBpDPfA4eLNtU81B0ZUps\n7EXs3TsOXR8E/Ixh/EJCwv/K3KY/5OXlYhgnn6Qr5OXJMTVYhEZdpQK/ActwAKpbQ+EzDFoBvXE4\nUmnf/mq/voZzKSws5O/3bAWv1yA//5iZkYRJAnEOCOWvqzEn3W7T1emkq9N54vFVLZNIW34LDtzY\n0dE4jOY5dfxGRVE4090OublH0PWTf2nh2LGjZX6tQgSqriDAnSSxsbHUr1+fTZs2kZCQwOLFi3E6\nnTidTqZPn86QIUOYPn06vXuXfEtL8ceOY4Bi+x+q+jodO97MwIHnc79+6UYXuPjiCObM0dE0D6Bi\ns3lp3bpNqdcX4p8dDrNmzfT5NspbUwApKbf5PFdlcOjgQbKzs7HrOgpF3am6rrNl61ZaJpWto6nP\nTTfx5+pRQD+KBkezUqNGhFyJdpKTOxwAZs3y/Xgtvqmrtic9OkrxscNiOUY4LopHp3Lgxmo5QMnH\nlnOPA6MoCsOHz+KFF+5j27bWVK9el4ce+pRateqV9uUGxKWXdiI9PR2Xq2iMBofDoGPHS01OJYqF\nQl1ZVA9efRsReE6MehOGgUcdg8M+mc5dB9K37xAfpS3bud7FF7fmjz/W4PFYAR2LRadFi1Y+yiRC\nSSDOAaH8dTUi5fSJLIo9eHVXPv/1B8K8RVezhgGG1Yqh3IPbPRLYjs02m06dni1x/Q4dLuWnn35C\n07yAgt2u0759h3K+YlGZBaquIMCdJACvvPIKAwYMQNM0LrzwQqZNm4bX6yUlJYWpU6fSsGFD0s4y\niJAB2Ozh3Pev/9GlS3+/5WzSJIHBgx9m2rSpFBQU0KZNW/797//z2/aEKKvy1pQoG0dYGN6TboMx\nAI/XS1hY2ceXcCYm8tCgQbz5zru43R7i4qIZM2acD9KK8+WvuqpVqxa7sg/9/YSiEBNb8qB3pVWz\nZhxjx84vVxv+1qVLV3JycpgzZza6rtO9+9X07n2z2bFEgJWnrvpcupoFqw6inTxjtqKQ0rkj0x56\niDlBMFDu4MH/YcqUV1i9+k8iIiK4774HZNwd4Xd+O15FRaFabBheNwrH56hRVHr3vp21az8mMjKK\n/v0XExOzrcT127Rpy1133c2MGR/jdrvp3LkLAwbcWa7XKkSgBHR2m/JQFIUwQLGFUbNOPM9PWIHd\nHn7O9U4nV4IIc/hzBOayktltSudM7xpvvPUWy374Ad3lwmK3k9CsGc8MG1buKz/cZ5gdxFyVZ3ab\n8jpbXW3YsI5xY8egaC4UVUUJC+P55ycTExNbwtI++psHyew2ZpPZbUov2OqqeBaO3zZvpsfo0Xg1\nDUVRsDkc/JSaykVxcT7uJJFzReFbwXoOeLbZbQzD4PIXPmHNnwvRXflYHFVofckNPPzw+/8Y40Tq\nRZijwsxuU17JPR+lRo1YrrrqvjJ2kAghhO/86/77cTqdbN6yhbpxcXS/4gq5NUacVbNmiYwdN57l\ny3/EarVxxRVXUrt2HbNjCRES2jVpwk+pqcz48Uesqsod3brR6CxjAwkhyk5RFB55ZAZLl37Arl0Z\nxMe3oEuXATLwsKgUQqqT5I47xp97ISGECBBFUejSuTNdOnc2O4oIIfHxDYmPb2h2DCFCUmK9eoy5\nTcbSEiIQVFXliisGmh1DiICTrzyFEEIIIYQQQgghqOSdJEeO5JCZuQ+v12t2FCGEOCEvL5e9e/fg\n8QTf+Cyi/HRdZ//+LA4dOmh2FCHEedJ1L1lZmWRnZ5sdRQhTeTxu9u37i9zcXLOjCOFzIXW7ja8Y\nhsG0ae+wePEiLBYLUVFRjB49Vu4Lr4Q8Hg+FhYVUqVJF7rEUQWFG2qfM+vxzLBYr4eFhjBr1LHXr\nBtd0rqLsjh07xpgxI9m9exeGYXDxxW147LEnsFgs515ZCGGq3NxcRo9+hqys/ei6l/btO/Dww/9F\nVaV+z4eue8nPz6dKlUg59wpR+/b9xejRPTh27Aher4sbbuhF//63mx2r0jEMg2PHjhEWFobVWik/\n1vtNpfxrrljxC9999x0eTzgeDxw6lMdLL01m7FgZ86QyWbToG6ZNewfDgDp16jB8+CiiZQA4YaL0\njAxmff45Xq8Hr9eDpmmkpr7Aq69uNDuaOG8lz0zz9tu3s23bdqDoCsZVq1bx5Zcb6d37idMXLs2s\nNO7QnUFFiOBVcv2++WZf9u49hNdrB+D331exePEievS4JpDhQtqqVb/z4ouT8Ho9RERUYdiwZ2jc\n+EKzY4nzNGnSrRw+fBjDsAFhfP31fJzOJFq1utjsaJXGwYMHGTt2FFlZWSgK3Hnn3VxzzXVmx6ow\nKuXtNtu3b8fl0uH4rN+6rrBjxw6zY4kA2rJlM9OnT8PjCcPrjSArK4fnn3/O7Fiikvv1t9+O3/4X\nCUQBNvbv3xZ00waKsvvzz4UUHXuigCh03cvy5WeeglEIETy2bl2F12sAOgAul85ff20yN1QIyc4+\nxIsvTsLlsuDxVCE3V2Ps2NFya2kI0HUve/duPHFOsnfvRgyj+Lt2FY9HYceObaZmrGwmTEglMzMb\nrzcCjyeMDz/8gE2bNpgdq8KolFeSxMbG4nBYcLkKAA1QcLtV9uzZLZe1VxKbN/9F0e5fdImsYdjY\nvXsnuq7LFK7CNIUuFyfvl+AAXOYFEj7n9bop+nctvsTcgabJv7EQwU7XvbjdLqCA4vq12RzUq1ff\n1FyhZOfOHVgsNv7+jtaO2+0iOzub6OgYM6OJs8jLO8SoUcns378dw/DidHajRo04Dh7cD9gBA6sV\nYmMvMDtqpWEYBjt3bkfXIyl6P7JgGDqbN/9FQkIzs+NVCJXy02CXLpfToEE9wA1UpejbPDuTJk0w\nOZkIlFq1aqEoBlD8Db2XKlUipYNEmKpmjRoU3Ybx936pKKrcs12BOBxVAM/xRwbgoWrVWiYmEkKU\nxpIl71JYmE/ReWMkYMVms3DddTeYnCx01KxZC49H4+RjnNfrJSoqysxY4hymTv0Pe/duw+VS0TQb\nGRk/csklNxARYSciQsXh0GjX7hLatetgdtRKQ1EUqlaNovjWXTBQVahZs7aZsSqUSnkliapa6NCh\nI1u37sLrLf5QbCMzc6+puUTgtGlzCS1aJJGeno6iWNB1Dw8//KTZsUQlVzyAsGEcpagP24thFH1j\nIB0lFUNYWBVycw/wd2eYTmRkDZNTCSHOZevWVWiah6IrwQDsOBx2bDabmbFCSoMG8fTocTWLFi1E\nUWzoupuBA+8lLCzc7GjiLLZt+5OiiUCLzkM0zU1OTiavvrqR7dtXExmZQXx8QzlPCbCHHvovEyeO\nR1VVDMNL8+bNad9eOqp8pUJ0kuTnH2Hduh+wWm0kJnbFbg875zpxcXWxWpXj95YqgEdmt6lEVFXl\niSeGkpGRzpEjOTRtmiCXegrT1Y2Lw2a1ormh6AO0Su3asXLiUYHEx7fkwIFMDKPo2x+rNYzGjduY\nnEqIikHTClm3bikej5vExC5ERFTzWdv16ydit9vQtKLzRlX1EhdX12ftVxZ33nk3l17amaysLOLj\n46lfv4HZkcQ/GIbBTxs2cCA3l0MXtqVevWbs37/n+GcmsNksNGiQRGRkTZKSrgDyzQ1cSbVs2YrJ\nk19m8+ZNVK0ahdOZJFfE+1DId5IcOLCDYcOuQtMaYxhHqVnTw3PPLTzngbFt23Z06nQpP/30I1ar\nDUVRefTREmYXEBWWoigkJbUwO4YQJ1zcsiXVqsdw4IAHaAz8Tu/ecoVTRXLTTU+wcuUSIBHIR1H2\nk5z8gNmxhAh5+flHGDasB9nZVhQlErv9EZ57bjF16sT7pP0ePf7NqlVfs3HjL6iqlfDwCAYNGuyT\ntiubpk0TaNo0wewYogS6rpMyeQpL1uxCVS9E0zswaND/2L59DUePHkbXvTRs2JJevR4zO6oAoqOj\nZWZOPwn5TpKpU4eRl3c7uv4EYLB//2A++2wid9wx9qzrKYrCgw8OpmfPGzl6NI8GDeKJiKgSmNBC\nCFGC337/nbzcKGAJRZd0L+HTTx+jRw/5EF1RpKW9ADx6/D8Dw3iQr756jQEDRpucTIjQNnv2JPbv\nb47H8xqg4HJNZOrUpxg69GOftG+12hg2bB47d65F0wqIj9+Lw+E494pChJB5v//OkjWHOOb6haLz\nkG+ZOvURpkxZy/btq7Fa7TRs2BJVtZyrKSFCWkh1kvRmzmnPjchKR9fvOf5IwePpTGbmslK3KaOS\nCyGCxYGDB/Hq7fn7nvfO5ObuwjDmBcEtN9ebvP3QUtLxCmD4/nUYxr+OPyo6ZqmZs0tcvuQW/sFW\nqqWEqPD27duJx3MZxeMm6PplZGUt8uk2VFWlYcNWxx995dO2hQgGOw8cwPOP85C8vN3YbA4SEmS8\nC1F5hPyNS5c1v5Aw25sUzVSTh8PxIYmJ7cyOdUY7dmxn+fIf2bZtq9lRhBBBpumFF6Io84EdgIGi\nTKF+/YuCoINE+ErnZo1xWIuPWblEOKbTJbGx2bGECHmJie1wOD4C8gA3Nts7NGtW9vNBlyuf33//\nihUr5nLsWI7PcgoRzC5p0gSL8jV/n4e8Sb16bUs8D9mzZwPLl6fx11+bAp5TCH8LeCeJ1+uldevW\n9OzZE4Ds7GySk5NJSEigR48e5OSc34Fo4p0pdEzYg80Sj8WSQIcOzbn22kH+iF5uX345l6efHsqb\nb77FM888zWefpZkdSVQQvq4rYY6Epk2JruMA2gJ1MYzJ9OqVbHasSssfdTX4uivxGouAesCFWNQt\nDOjS2bfBhQhi/jpeXXvtg3To0ByLJQGLpREJCQUMHHj2W6/P5OjRbB5/vA3/+9/dvPba/fz3v0kc\nOLCjTG0JEQi+qquOCQk82/96bJYOOKzx1KkzkyFDPjhtue+/f58hQzry5psPMWbMSKZNm+rT1yOE\n2QLeSfLyyy+TmJh4okdy/PjxJCcns2nTJrp378748ePPq70qYWEsHPkEu99+lXff3c3gwa8H5X1y\nOTk5zJjxMZpmp6CgaJ7x2bM/48CB/WZHExWAr+tKmOPX337j4KEDQDhgAQzef/89c0NVYv6oq6c+\n+BBdL55GNAyXu5CJc+f6NrgQQcxfxytVtTB48OtMm7aHt9/ewsiRcwgLK9tYc7NmjePQof0UFOgU\nFBjk5R1l2rRHy9SWEIHgy7p66LqryX5/KlvfeIFXXllFdHSjU36vaQW8/fb/oWkqBQU6LpedJUsW\ns337Np++JiHMFNBOkt27dzN//nzuu+8+DKNoGqkvvviCgQMHAjBw4EDmzCnb/dU1IiMJD6/qs6y+\nlpNzGKvVxt9/chWr1c7hw9lmxhIVgD/rSgTWwUOH8Hqh6H1CBazk5eWe+HcVgeOvutp+YD+6oVI0\nboKK5oEtmVk+TC5E8ArE8SosLJLIyBrlaiMzcwsej5e/xzdR2L9friQRwckfdeWw2agTFVXibTa5\nuQdRFAtFX+YAKFgsNg4dOlielyFEUAloJ8kjjzzCxIkTT5nDOSsri5iYGABiYmLIyqqYJ4uxsbGA\nQdF96AAeDMNLXFxdE1OJiqAy11VF07RJExTFC+gU3QvspkGDhjImiQn8VVddmicSZjMoOh4YRDig\nmzPRR6mFCG6hcrxyOrvhcFgprlObTSExsYvZsYQoUaDrqkaNC3A4qgDa8Wc8eL0a8fENfbYNIcwW\nsE6SefPmER0dTevWrc/4raiiKGf9MPDRstLPWhNswsLCeeqp4VSpomK15hMebvDkk0OJjAzeq19E\n8PNFXQWr/2fvvMOjqL4G/M5syaYQkJbQI0IoCU1R/BBpgqhYUBAUf4AFKyKKShMVsQAiSBMURUEQ\nERURpIoIIlUURELvJCS09GT7zPfH3SSEJBqym2wS7vs8+2y7e+fM7Jy5d849ZcuBA9zzxhvc9uqr\nzFq16qrwpmgcGcmA/z2CwWDFaMwkLOwahg0b4W+xrjqKU68+GNCf+mGVUUhFIZVbmzTm6dtv91Zk\niaTU461edRg6lFc+/ZQMm604xQSge/fB3HxzD1Q1E4PBSlRUO/73v/eKfbsSyZXiy/Eq3Wpl0Ecf\n0emVV3hs8mTOJObv7W4wGHn99RVUrBiK0WgjIMDFCy+8RNWq1bzaF4mkNFFiJYC3bNnCsmXLWLly\nJTabjdTUVPr160dYWBgJCQmEh4cTHx9P9erVC+xj0IwZzFy1im6tWtEhKooOUVElJb5PaNy4CXPm\nzCM9PZ2QkJBcFl9J+SMmZi8xMXuLdRu+0KvFixdlv46KiiYqKrpYZS4Mu48f59633uI9t5twYPjc\nuSSlpTGqd29/i1bs3HXHHXTqcic2m5Xg4JAyaeAqTmJiNhITs7FYt+ELvRq7OCcx96Xj1VcbN5IS\nF8dngBUYvedvft+/n/ZlbDyTlC/Kgl7Vi41ldWwsy/78k9nPP0/H6OIbq1TVwKBBcxg4cDqa5i7V\n4dyS0klJzAHBe73KGqsupKby1bp1dNA0hgG/nj5N10OHeH1Kn3xz+0REtGT27FOkpycSHLy5VOaD\nlJQ/SkqvABTdD8uzGzdu5IMPPmD58uUMGzaMKlWqMHz4cMaPH09ycnK+yYUURWEB8IKi8PvUqTQI\nD8/TZik9CrF1Wdde4h96976/WL0hiqpXixf/UGwyFYUeOHlg3Dia7trFKM9nfwEPm82cXrDALzKV\n9FXDWahrmQSgd29zqdQrx+L8q5c1euwxPsjI4DbP+1nAivr1WZ9PP0tNPtyR0oizMDvYvdjFkOSl\ntOmVoigkIwKWr1UU9n/yCWGVKuVqU9jrtO+ur3I+KSk8xT0HhKLplWPxYnRdp+kzz3A+KYmjQNaV\nuWtAAN1e/YHmzbv8x5alLkj8Q3Hqld9cGbJWR0eMGMHPP/9MZGQk69evZ8SIgl3L7UCIorD7uMye\nLJHkR1H0qjSSkJjIpQ7VNsDhcvlLHMlVji/1ymq35zm3E1NTfSOoRFKGKIpeOQGXrmOQnrgSSb4U\nRa/SrFbOpKSgA1kzLR2wapr0EJFctZRYuM2ldOjQgQ4dOgBQuXJl1q1bV6jfjQAUVaVOlSrFKJ1E\nUjYpql6VRjq1bMmskycJBcKB94AwqfcSP+BrvapXuzZDTpzgApAGTAYeLMawAYmkNFIUvfoW+BKo\nHBhI1dDQ4hVQIimDFHW8CrFYsJhMtLbb6Qv0BdYCrooVadSobbHJK5GUZsqUKV41mejdsSNtIiP9\nLYpEIilGRj/4IA1r1WKOqvKBqpJpNrNw+HB/iyWReM28l1+GwEA+VFU+VlVqVK3KhEcf9bdYEkmp\n511V5W+jkW9Hj/a3KBJJuUJVVT4ZPJg/TSbOGY2MUhSO1q7NbxMnYjIF+Fs8icQv+MWTpKh89+ab\n0kAikVwFBJrN/D5xIhtiYsiw27mlcWOqyZVDSTmgflgYMR99xKb9+zEZDHSKjsZiNvtbLImk1DPh\npZdo26hRnlwkEonEe3rcdBPNJk1i1/Hj1KpcmZsjI2XieMlVTZkykkgDiURy9WAyGunaooW/xZBI\nfM41ISHce+ON/hZDIilT3N+mjb9FkEjKNdeFh3NdPoUxJJKrkTIVbiORSCQSiUQikUgkEolEUlxI\nI4lEIpFIJBKJRCKRSCQSCWUs3Gapz2rbSyQSiURSfPhmvFrqgz4kEolEIpFIJFdCmfIk0TTN3yJI\nJJIS5NSFCxyIi8PldvtbFInEZ2iamzNnDnHu3HF0Xfe3OBJJmeDgmTO45TxQIilWUjIz2XvqFCmZ\nmf4WRSLxK2XKk2TsiDa8+ubPBAfLzOYSSXlG0zSemT6d5Tt2EGowEFKxIj+NHUuNa67xt2gSiVek\npyfy/pgupJw9hkPXadS0Pc8PW4LRaPK3aBJJqab78OGEV6/Oj2PGUKVCBX+LI5GUO5bu2MEz06ZR\nzWDgnNvNJy+8ADdJL37J1UmZ8iRp1UXpSAAAIABJREFUHbufRV8M9bcYEomkmJm3YQP7du5kj9PJ\nXzYbt58/zwsffeRvsSQSr1k4Zwj/d+YQMfZM9jmsmPf9xqqfpvhbLImk1PO33U6LM2cY9tln/hZF\nIil3XExL45lp0/je4WC71coSh4Nnpk0jLe2iv0WTSPxCmTKS9HE5iD32l7/FkEgkxcw/R49yj91O\nMKAAfTSNvSdP+lssicRrYo/v4iGXAxUIAHo6rMQe3elvsSSSUo8C9HG7iTl+3N+iSCTljuNnz1LH\nYKCV530roI7BwNmzUt8kVydlKtxmhcFEWJ2m/hajxNF1nd27/+LcuXNce+21REY29rdIEkkudF3n\n7793c/ZsAvXqRdC4cROv+ousW5fvzWaedjgwA6sUhYY1a/pGWInEj4TVasw3CUc5oLkxAMtNFsLq\nNvO3WBJJmWCVqtKgdm1/i1FqcLmc7NixnfT0dKKioqlVSx4bSdGoW60ap1wuDgGRwCHglMtFtWp1\n/SxZyeJw2NmxYztWq5VmzZoTHl7D3yJJ/ESZMpKsqlqHUY8X3i3Zbs/kl1/mkJh4lujo9rRseXsx\nSlc86LrORx9NZ/v2bei6iqK4efDB3tx77/3+Fk0iyebjjz9iy5Yt6LoKuOnZsxf339+zyP0N7NKF\ndX/8wY0HD1JZVUkJCGDVoEG+E7gUY7XZWL1uKsnJ52nRojPNmnX2t0gSH9Kp+2DG/LEcMAA6Breb\n6Z0G+FssiaTU0z4wEEdwMKsHDsz+zOZw8Pn69cReSMLStBE3XH+9HyUsWZxOJ6NHjyQ+PgFNUwAn\nr7wyjJYtr55jIPEd1StW5IOBA7ljzhwaGo0ccjrp0a4dy5dPpV69KNq1exhFUfwtZrFis9kYOfJV\nLl5MQtMUFMXFa6+9TuPGV98CvaSMGUnemfw3JlNAodo6HDZGjepKQkIYTmczVq8exMMPv0j37hHF\nK6SPOX78GNu3b8VuNyOcTVUWLVpIly7dCAoK8rd4EgknT55g8+bNOBw55+i3335D167dCAkJKVKf\nRoOBb197jT0nT5Jpt9O8Xj2CLRafyl0asdvtvDJ8LOcvROF0NmX16ifp338Et9/+pL9Fk/iIefOG\nARbgSSAVt7aIxYvf4rnnZJ4FieTf+Oi112gREYHFbAbA4XLR/vVxHIyridVxIwFrFvDgA3H0vP8e\nP0taMmzatJEzZ+Kx242IsVdn1qyP+OSTOf4WTVJG6depE51btOBofDzvL13LN1tSybSbCQiYyp49\nvzNo0Ex/i1isrFu3lnPnEnE6s3RK4+OPZzJlygx/iybxA2XKSPKfBhLT0uyXO7dv4dx5E07nfEDB\n4XiQhQtv5a67EsuUJTQ1dQ2qGgRklUBVMRgCSE+/kaCgCD9KJpEIUlJSMBpNOBxZeqViMBhJT08r\nspEEQFEUWkRE+ETGssKWbdu4mFgbp3Mu4rp1LwsW3Mnt3av5WzRwygz3V8Ql49GlxMaeBD4EHvJ8\nUpF9+7/Pt73J+d+bccqiOJKrhPjIYcRf8v6PXcs4EB+MzbEYULDb+/L14hu5+77ZqKqhBCTqXgLb\nuJQVud6lpqbgdOqImzkAlYwMayHlWvHfTSSU/H/sf2pVrkxyRga/HzhOpn03YMFuf4YtW1rQp88I\nqlYtv+E3yclJOJ1uIGtgNZCamupPkSR+pEwlbr0SMjMzQa9NzuBRE7fbjqa5/+1npY6IiJbougNw\nAjrgJDAwlCpVZNyppHQQERGBprnIOUcdWCwBVK1aCm7syxhWqxVNq0POdas2Dkcmuq77UyyJDwkI\nsACXXr8jqFBBlraWSK4UqzUVqEXO9TIcXXfjcjn8KFXJ0aRJFEajhlhE0zEY3DRufIu/xZKUA9Ks\nVoxqVYTXI0AFDIZryMws3waD6OhmmM0KWTplNLqJjm7ub7EkfqJEjSSnT5+mU6dOREVFER0dzbRp\n0wBITEyka9euREZGcvvtt5OcnJzv7+fOfRmX69+X1vbF7GPEK++y5LtfcLlWAT8AJzAaXyQq+gYM\nhjLlPEOlSmGMGLGU0NAQII0aNWoxZszaMrcfkuLBW53yBaGhFRk1ajSVKgUAaYSFVeLNN8diNJb/\nczQxKYkxY8cy4IknGDZyJLFxcV7116J5c8Q1qxPQFkW5nWYtbihT3m/lgeLUq253tQeeBm4F2qOq\nb3F/r275to3Zt4/BL77IgCeeYPLUqVhttqLvlETiZ7zVq8GDb2L06Ls4dmwXAE2bdgA2AUuAHShE\noaAz9q2uJCQcKZmd8iONGjXm8ccHEhDgQlHSiIyMYMiQ+f4WS1LCeKtXuq4zcelSqg14nKCHnqbu\nU69wMDYOi/kCqvIRcBJVnURwsJGaNSNLcM9KnpYtr+fhh/tiNjtQ1XSiohrxzDPP+VssiZ9Q9BJc\nokxISCAhIYGWLVuSnp7ODTfcwNKlS/niiy+oWrUqw4YNY8KECSQlJTF+/PjcgiqKJ80dVKkWyYQJ\nmwgJyb36durMNEYNfweHfRJQF5NpFCbzSVQFmkY35bnnHyXI3LekdtfnaJq7hFxIJcVB795mn3sE\neKNTIPRq8eIffCaPL87RHghD6J6TJ5n87bdkWq080LEjD916qy9ELBL5OSa7NY0hL71E4tmzGDQN\nt6JgCglh5vTpBBcxX9C5c+cYNGQELve7QDTwFje0djP8tSHeiO8bSmm4TanVqx8W59v38qUrmT/v\nV+AjIB1FeYZRbwyiRcsWudrFn4ln+NBhqHY7KqCZTES3aMHIYcNytSvT4TaFEv7qc3cvDZQ2vRKG\n4l+AGCyWsQwaNJPPPx9FUtJRVPUadD0Fs+7GBLgVFVNIZe5/YCSBgSHcdFOPPPPFskn+ITK6rqPr\nmmfsLay+yHCbwuG7609x6BR4r1e3Rkay+dBhNMKBjxFewU+hKqnUrFybJJuD2rWjeOGFmVSrVq8A\nKcrX+ZRbpySlmd697y82b+sS9SQJDw+nZcuWAISEhNCkSRPi4uJYtmwZAwaI7P4DBgxg6dL8Y7kD\nAQ0D588nMfDJSCa8fz+//bYw+/vtW3fgdPQHegI34nR+jKoqfD5/Bq8Mf46gYHHjomlurNa04tzV\nYkEqq+RyvNUpX+Orc/RAXBx3jB5N0x07uPuffxgzezaz16zxSd++4uKFC1y8eBGTpmEAzLqO5nJx\n9NixIve5as0aXO5uwADgBuBL/ty5XYbblDDFqVeLFv4ETAPaAXeg668xZ/bXedrt+XsPBk3DhKiD\nY3Q6+XPXrgLPBV3XSU9LR3NrVyyTRFISeK9XNwD9sds7M3lyX5KSqgKr0bRHQXdjRkxqzbpGetpF\nvvpqNV988RNDh95McvLZ4t9BP6EoipwfXsV4q1dHDh1CpwIwCegAdAHeRtODib14lubNb+H117/7\nFwNJ+UPqlAT8mJPkxIkT7Nq1izZt2nD27FnCwsIACAsL4+zZ/AczMfUTSqq5w/nz7xXM/uxZfvxx\nEgDmABOqmnTJL5IwGnOvVK1fP5f//a8ajz1WmxdfbMOFC6eKJL+maZw4sZtDh7bjcFiL1IdE4kuK\nolOllfnr19Pfbud5oBcw027n42XL/C1WLgIsFtxazg2pjvAusXhRhWfbjh3ApdewZMpx6qgyga/1\nyul0If7XLBJJiE/I085isYCqkmUS0QCT0Zhv6FXs6VieffJZnnr8Kfr37c/WzVuvWC6JpCTxRq90\n/Ty66gLLNuA+YCU6QaRhIhUTdhR0jLhcb2K3zyctrRs//DC5+HdKIvEzRdGrZoCCxuXjksjL4WLr\n1hW8/noHNE0a4CVXF35JGpCenk7Pnj2ZOnUqFSpUyPWdoigFxt9nAhAGnANUcILDbGXpj+9z330v\n06FjB3784TUyM0ahaRGYA6bS+6GcUnDHjh7j888/xOX6FWhAfPxkxo9/hA8+2HRF8rtcDt55pxdH\njx5EVSsQFGTn3XdXU7lyrSvqR1K+iYnZSEzMxhLZVlF1CmDx4kXZr6OioomKii42OQuLruu5TANG\nz2eliYqhoXTq2JFNmzah2e0YzGYiIyNpUL9+kftMSU0FtgMvAVHADMCApmkYDHJVA8qQXi3KCbeJ\nio4iKjrK884KDAZOAenAdMCV5/dt/q8NS775jpTERNxOJ4rZTL9HHsnTTtd13h7zNknpSdn2tBnT\nZhBxbQQ1ata4kt2VXMWUDb16EEgADoHbBGYnYANOA68grpsHsdEVoWcCt7spSUk7imFPJJKCKUmd\ngqLrlRgl0oEXgB1ATUQFtplAD+Ajjh8fR2xsDHXrNiu+HZBICkFMzF5iYvaWyLZK3EjidDrp2bMn\n/fr1o0cPEeMeFhZGQkIC4eHhxMfHU7169QJ+3RAxsXwQ+BUIAJcdzSAq1lS6phITJ4/lh+9/4uLF\nv7m1/YO0bdc2+9dHDh9B1+/w9AO6/gKnT7+HpmmoauFXa1eunMGRIxoOxw7AhN3+Hh9//DKjRi36\nz99Krh6iojoQFdUh+/13371TLNvxTqegd++HCvzOX/Tt2JHbf/6ZGnY7YcDbAQE83b305SZ45skn\niWralCNHjlCzZk263nbbFV1LLsfhcAD3A5WBvcAIQCYNu5Qyo1cP9S7gm0BgNHAAUWbwRWBqnlYW\ni4U3Xn+dyVOmkJySws033cSd3fImeE1PS89JyGcC3ODSXRw5ckQaSSSFpizolcrfaPQFlgK7wNoP\n4cNnBYYgqtw0Bu7y/OI5YAEBAR9z/fUvF8v+SCQFUVI6Bd7pVaiioOpGNLoBW4EzwC2IuQjAIOBN\nkpPPUbf8Vv+VlBEuX8z97rtvim1bJWok0XWdJ554gqZNm/Liiy9mf37vvfcyb948hg8fzrx587IV\nPC/xwG6gKsLqGQ12O527P4bL5WThlzvZsOFrMjIuYDLVZO+eLzEb2tO69d0AXBOqYjC8g9PpAMzA\nHwQHh13xTc3Jk4dxOG4nq462pt1FXNzgKzsYEokP8F6nSifRdeuy7M03+WDxYjKsVoZ27MijnTv7\nW6w86LpOZmYm6RkZnvK93nl8CHfW/cAsxPXlNyAA3XEfXAXVgkoLPtGrAhPdPonwi/wAcYP3vHi+\nrH1GRjJDXo7AoWWCAZavXIHDVYcnnpiWq52RdHTtCaiA8CTRQU/XSblY13/Jdk0lkwNJUrbwVq90\nugNjPO/+D+FF0gUxL/wLuBGwAzEIr5IfMJnacc89Q+nQ4X/FtVsliC8XCkrfooOkaHirV+vCw3HH\n24EFwGxgHWJB2oow6v8NGPn7719o3vy2AqSQ55Ok/FGis+7NmzezYMECmjdvTqtWrQAYN24cI0aM\noHfv3syZM4eIiAgWL86/KgAEIwwk24CdQCAGYybxCYd58qlryUgPBy4Aj+Jw9AJ0pk7tw8cf78fp\ntGEwGImIqMqJE52ARmjaRp5//vMr3o+qVatjNH6Py/UIYMFgWExERNMrPyAe0tOTSE5OoHr1CMzm\nwCL3I7n68F6nSi+tGzRg0ahR/hbjX5k6YwY7//gDzW5nu8nEjj/+4J2xYzEU0ZtEhBSdAiIQl2dZ\n8tUfFK9euYBxwGREphEdEfudm4ULR+NwZQp7vg4Ewpo1H+cxkmiaC1U1oCmePhQwmExUrVqnCLLl\ncObMQabPeJzExDiimnbg6adnERBQtKpNEgn4QK+UJaA/A2xBVIdSENbBZoibtDbAeURlsDOAhf79\nx9Gt25PFvWsSid/wVq+OxsejY0J4jsQBR4Fw4CagJcJzvyabNy/mf/9791/DTCWS8kSJGknatWtX\nYOKfdevWFaKHVOBhUNaAQQMXuN3w1+6VnjmmghgsNaA3MBqHowKzZj3Nrl3rUNVINO0sjRpF07Hj\nvURGvkt4+HVXtA979qzjpxVT0HQDEImiBBIWVounn/7pivrJYs2aT/nyy1EYDFVR1XRGjfqOyMg2\nRepLcvXhvU5JikpycjJbt20j0OVCAXSnk1OnTnHkyBEaRUZ60bMTYRA2I1ZyHDJhWglTvHqViRh6\nKyHGqiTAkafVkSM7xNcOhIeIx17mdrtzeSsFB1ci4tqWnIjbjWZ0gxvMqoXGjdvm6RNg587lLFs+\nGQWF++57leuvvzNPm9TU87zySltcLiNwLb//vpT4hEOMey//hLCnT8dw6NB2KlaszvXX3yVTDUvy\nxVu9qqqnkEg73FRGJGxVgBWg2kUDLSu/nA2xGt6E+fPHUatWA6KjO3m/AxJJKcRbvXJgRHiuxiEG\nHAXUOE+1jNMIo+MpEhPNbNr0Ne3b9/WV6BJJqaZMzWWCcQOrIEgTRhEV4QlmRIyVVAPWABOAJcBI\ndD2OHTtW43TegN1+HqezMQcO7MViCb5iAwnAzFlP4jRa0YLTISQNY0Aqd9/9FKGh1a64r9jYfcyf\n/xZO50Zstj/JzPyQceN6yxsiiaQM4HA4coXqKYCqKJ68It7gBHMyBMWDqgKGUpe0VuINZnGyBMaD\n5SxiJpo3RMvtdol2wUCQ5xnyDQ/t1PFRdIcOGaDYFRo3aUfFimF52u3cuZwpUx/hwInN7D/xO5Mm\n92H37ryltVetmonLFYQIY1gPLOHokb3Y7Zl52m7btoSRo9oy96uhTJvRj/fG3S3LEEuKhR2AGwXY\nBLwP/AA4xBzQgmdGa0Ak99eBQzgcXdm7t+SSZ0okZQ0VF8JLPw4CTkKgS6iP6nkoexGL1JFs2VK0\nBWGJpCxSpowkGdT0vLB4FNgC1iBwhHiMJIF4XgCRCIuoAfgWkehrC3AQl8vMJ5+8zI4dy5k06VGm\nTXuGY8d2FUqGtNQLoktFdO1WXKSlXSjS/pw+vQ+D4SaEaz3AXdjttjz9OZ129u7dwN69v+Y7SZVI\nyiMut5tf9+7lp507uZiW5m9x8lC1alXCw8NxGgy4AaeqYgoIoMF1V258zYWqgytQXNtUBXBz4ULR\nrjGS0ogTAp3CUSgAsOStbAOQnHwWDGpONI5ntL7ciO52u/jyy1fQgzQIBT1EZ9/+3zh4cEuePpcs\nGYdDtYltm8FpsPHD0gl52mVkJAH1gQcQVZZmAy4cjtzhX7quM2vWkziMVuyGTGzGDA4d3spff/51\nRUdEIikM92BEWAyzElD+KuZizmCwBoPBiFCWOkAoEIbRuJeKFa98EUsiuVrQMCK8VhVwBIFmFLdT\nmiIeFjx2/F1YrYn+FFUiKVHKWCbA9xFhNLWAeHD9HzAJOAp6f0TiricQRodTiME0w9MexFJcK6A6\naWnH+OCDR4DmgImtW7tgsZhwODNpcN2NDB++hKCgirm2vnXrdyLpqxvhmWYAxakQEBCEy+XAaDRz\n4cIpzp07Sc2akVSqlHcl71LCwq7D7f4LEUNbDdiG0agSElI5u016ehKvvdaN5GRhlQkJyeC9936m\nYsWCqypIJGUdm8PBPWPGkBgbSzVFYZCqsurtt2lau7a/RctGVVXGvvEGs2bP5ujRo9SoUYPnnnmG\nwEAv8wppAYib0sbgGoNwG5eUH/RcT4K8OUlSU8/jsWQgqh0lAnmTA2dmpuByuyBDBV0DVLRAjcTE\nM3n6TDh7LM9nZ84czvNZdHRnVq/+AlGCujXwIYoSQkjINbnaaZobmy1dpIUAUEBTdJKSkgrce4mk\nqOylMiIccQpiIWwC6FWAb4BgcD4GHEHkI6kHnKZKFQOdOj3qJ4klkrKAZ9WXH0G3gP1RUI8hQkJT\nwekURnq3lWbN2vlTUImkRCljRpLvEdaJMMQgOANR4TsDCEHEoa4AxXbJBLQ+0BERv7rY00bxtK8L\n9Af243YfJCMDoA/79//IqFHtGTXqR1asmInVmknr1l2ZOrUfmHVx1OyA3YCmRLFo0QJ++WURt97a\ni2+/nYDJ1BCX6wiDB8+iTZuCqwvUr9+Ke+55iuXL22I0NsTtPsTQoXMxGHL+lm++eY/z51vgck0B\nFByO1/jyyzcYPPhj3xxSiaQU8vHatQSdOsUPDgcqMAd4aeZM1rz3nr9Fy4XRaCQ4OJjAwECCg4Iw\nmUw+6LUmkBXzawHsZGZKD7LygxEyXeS2kpgLaBuKMPKnICp3/IHL5cp1noWEVEbXdFA04Zni0nBa\nrfmGgDocNjF2uT2bd4Ida552dns6RmNnXK6enk8moSgLcTisuZK3GgxG6tZrxumzMWgmt4gccuk0\natyo0EdDIik8dyBWvN9CzOOyvKqeAnohSv8uQuT5icdsNjBp0haZEF8i+VdMiMXa2xDWkBtAsyB0\nzSlyjXuGqICAYD/JKJGUPGXMSJJVC3knQmNPASOAH7Oq8YLTKCZ/JsQY6jgOvATKZOFIogJWHZwZ\nCKNJhOeHpxCGl6nAi5w5cyMvvNASTXsUiGDDhv5gcAsXNBBHLlVD19dhsxmIje3LokXvoWmbcDrr\nAruZPr0HLVp0xWIp+KLSp88o2rd/kIsX46hdu0ke75O4uOOeiaoII3K7OxMXN6MoB08iKTOcio+n\nrcdAAtAOmFXKQk50XWfM229z8vhxdE0jPi6Ow0ePMmPKFAICArzo+ahY1DEAnvCG06dP07BhQ1+I\nLfE7HgNJ9pgF+SVuFVwA4wUxbjlPgJ43Qvb8+ROAJuz+nhLApMOaNbOIju6Yq63ToeWI4MFhzxvu\nExgYitF4DpdL83SagKKoGI15jTkjhi9l/Pj7OHUqBnNAIM888wl16xVk9Ckc58+f49NPF5CQcI5G\njVby2GPjCAoK9arPwnLhwilmzXyKM2cOUrdeM559djaVKoWXyLYl/8VCck5e3ZMvAdCOgmkCuAyg\nqQjlchEW1kQaSCSS/6QzKCuFLhk1cP4hxpHseQjgUAEza9d+zj33vORPYSWSEqOMGUksiLJUnYBf\ngHtBcYjxMGsctNuFQmctdik62H8QNhXDJd04NcSsMousBjrCcKKgaY2AjQh396znS92ilexnXb8O\nVTmH8E4BaIlJCWb37rXExu4jKCiUDh36ERxcKdce7d27gc8+G0lGRhKtWnVh4MCJuQb1Ro1acejQ\nQhyOboABk2kBjRq1utIDJ5EUSA9xl1aqaN24MZM2buR6hwMD8I2qcn2DBv4WKxcXLl7kmMdAYgJc\nuggzOHj4MM2jo4vesQFh0FUQl6V0OHfunE9kLs24XA6WLZvEqVP7ad68I506PVZOSw3qYrzKsiOI\nAkb5Y0CMZdnngobLlduocfGiJ6wmZzgCBf7559ecRqalYsu6Jx9JoBADK2jOzOzvs2jZ2kWNmpnE\nxfbG4biRgICF3N+zFwbLT+DM7R1ZpUptJk78E5fLicFgFP+ZF5eUzMxURo1qTVraI2haRy5c+IL4\n+N68/faqYj8fHA4ro0e3x5p8FoPm5kDKWd58ozOTP9yTy8NT4i9cQh9UhANxMJCGCPdSAd0NaW6P\nMdFB1apV/SeqRFJm2Em2oV3BY5QnZx5iAjI04FHOnVvoNyklkpKmjI36gcBmhOZeACJFksNLCwNc\nvtBmADiV414s8iB6GvYF3gD2I+qAVwZmImK/TUA6EA98AtwC7p/BagCj21OOMcsgkgFsQtePAgeB\nRsDvuLVUpk8fhMvVD6NxLz/9NJsPPvg9O9dJbOx+Jkzoi90+BWjE5s1vYbMNYujQz7PF79nzVY4d\n688//zRGUVQiI9vQt+8bXh5HiaR08+D//R8Tvv6aARcuUBG4oCis7dXL32LlIjMzE7emEUKO81qG\nppGQkOCdkSRrdTTrNRAXF+eVrKUdTXMzZMhNnD9/CriWLVuWsXPnWoYNW+Rv0YoBRYxbWRg8n+VH\nPueC05nbAnH48Hbxwoon3AZwi1wl+ZI16mdNfvMxaBhNRt4eN5L169Zz4cIBmjZ9mOtbX1/gHrnd\nLpKSzhASUpnAwAoFtisMhw5tw+Gojaa9CoDL1YrjxyNJSTn3n3m+vOXEib+xW9Mwa2IxRHW7SE6K\nJz7+MLVrNynWbUsKgaKASRdzuMuMgtmv1RBwizLblSqVnhxWEknppRIoCbmHoawCFVmvAViEopSp\neh8SiVeUKSNJEE4ycSCMJFUBC+hWsOs5Cm1DhKlmOXzYLMCD4PoKMnQxOXWCmB3uBV5BeI4sQ9QI\nf1KE1ZgywRbk+f4zT2dVwJEKjlDE8kVVoAHgwqCGMPC2W5i3oQsmY3V0/SKBpkDOp30KdMDphJSU\ngaxfP5e77x4CwO7da3G77wfuBsDpnMqff+b2EjEazYwcuYjk5LPoukalSuHldHVVIsnhs3XrcF64\nQCAiG0Mjt5vhn37K2nHj/C1aNoEWCyrClKoiLjsqUK2al5UUnIgbXRWPMRZiY2O967OUs2nT15w/\nHwtsR+Tg2M7OnfeSmnq+SOXVSzcmzBkuVDQUwI7qqS6QD07Pw0D2uXB5ienq1T1hWC5PW8/wUOA4\n4SBn5P+XatVms5k77rrjP/YF4uIO8NZb3bBaU3G7nTz88Dvcc8+L//m7gjAazeh6OjmrGjY0zZFv\nqI+vMZsDcWvuXPcHbs0tQzZKCRZdR8sAR5YnlB08SiQ8pDwGwixr4Q03dPaXqBJJmSGAQxg1yMhE\neNpriLHBhCdFgcHzxoamObl4MY4qVWoV3KFEUk4oUybBB0gniG4Iz41PAA00HXRF3KmkAVp9IEC8\nTw8F7SVgAtA+x5skCFCyZp8PIhJ9RQOnhYFE0cEWjMiSPhM4B1wDPI7wR6vm6fMo0JoAYw06RtVj\nyhOPceKTqWx4+1lOfjIVp5YVuiNwuSLIyEjOfm+xBKOq8Zfs4RnM5vzzl1SqFMY119SQBhLJVcHs\n1atJA74EfkOkr/zz6FH/CnUZwSEhnrSBFjRCATMaEBrqbe4ERVzi0vAYdM0kJpbvsnsJCUeAZuRU\nImsDBHg8S8oXJjSaorEdEcAZJrKdFtBagUwuORfg4sWLuVqcOLFTvAgFKnqeDaDruUsFZ6MBqZ5H\nAU2uhPHje5CcnILdbsTlCuCbb97iyJE/itxf48ZtqV7dgsn0FPAlAQG9adu2d57KOsVB3brNaBh5\nMy5zIHbAFRBEq+vvpFq1esUoAxicAAAgAElEQVS+bcl/swOIdoEpDTGXcyDOYTuQZgJrBCKBa1Vy\nu5hIJJKCiEHjHURl+kvHGjLMkGYBlxlRMEOEr40YcZtf5JRISpoyZSSZDNg4hCj99gYoKmAEfQDC\n0HECcVsVAEoQMAt4GegOxk1g0bMz+mPWEFUkJgPDgdHi4XaC61VEkOtU4BCwCUhADL6rgLOIUsPr\nAAN33VCZFa+9hEFVqRwSQrO6dakQGEj361thMr0GxAJbMJnm06pVt+z9adu2N6GhRzAanwYmYzb3\npW/f14vvAEokZYTYCxd4FlGwuybwtp/lyQ9xs2oB5iESP68FAonz2utDR4QWGhEWXQdWa/kOt4mK\n6gjsRlzDQeSAclCnTpS/RCo2AnHxHqJAaRQi9XhQgdaKYETFjnbA7UAFbDZbrhbx8UfEi6yJ7aWe\nlHkwiu+NnocGORlkrxy328XZs8fJcU1RAQPHj+8ucp9Go5l33lnJ3Xc34uabd/Dwww8yaNBHRe7v\nSlBVlZEjl9O77zu07fwYfftN4KWXFpbY4oTL5eDbb8czfvwjLFz4Fna7rGp1KXWBcWSloKtBToKS\nrGStscA+T2sne/ZsKHEZJZKyRlXgMcRcC0yenD5mclaVQ4CmiKpRBlJS8paXl0jKI2Uq3OY4wutY\nIwKoA3oFYCWwGngaMTMc7Xm2ej7rDcpeCHLnJL9LBVQFeA5YD8qnIs5V18H5AKIs8BSEUQREjpE2\nQAxiopqJmF1ei0IyXVu0QFXz2ptmPt2fU6xn587bsFhCefTRKURG3pz9fVBQKBMn/sbatbNJTU2k\nVatPaN68iy8PmURSJrG7XBy85P1RSt+aYEpKCuImNsvw2RJoyNFjx2h/661e9ByEqOLQFHE9+wk4\n6Y2opR6bLWtp+GbElE14S1itqZjNFj9K5ns0FI6i09bz/iD/lue0MsIwD8IgZ8Vszh12cs01nrwL\nmQgl0S95zoPnQ9clDf9FsU4cP0FSYhL1rq1H5cqV83xvMBipUKEKaWmZiJtUHUXRqV49ouBOC4HF\nEsLDD/sn95bRaOKuuwaX+HZ1XWf8+Ic5cMCJw3E///yzmn/+uZd3312Dqhr+u4OrhKOARkugPvA7\n4jw2IuLRdGAXwjM4lqpVa/hLTImkTJGByPQIzYG/yInFTEVc239HmCjfIjv2UyIp55QpI8kdeJyS\nDYdBP+pZBXMi1LsDwgJSGegO+kbP5wtFaM3lE0FNAf4AfgNdE31pKsLAUtHTaBdiLTsZcdF4CFV5\nAU0PQKE3cIomtRX6d+yYr7yBZjODB3/8r/sUHFyJ++8fdgVHQSIp/9g1jaWI4bkm8BXCo7o0sWXr\nVkTGlCbAeUScg5VfNhzlsQEDvOi5G7AB+A5xXfuO8m4kiYs7iPCtGAgcANoCz5KZmULFitX9Kpuv\nSSeQYdjZhZsUYCUmnAUOxafBrIiyjDYnaCbS09NztcgJ0Qz02EBcoBdkdglETHitnvdBoOefmOSz\n2fPZsP4PjIaGuN2zeHn4c7Rs1TJPu3bt+rJq1TSy6g+rSgWvjf1Hjuxk2rRnSUw8Sd26rRg69DOq\nVq3jVZ+lnfPnT3DgwA4cjn8AM05nL+Li2nDixN/Ur19w0tyriaHA14CV6sAHQGPEHLA6Ik7gLcQ1\npDdmc0W/GLskkrLGGwhTvJhjORD3UZlkeQbCq4hF5SWATvv2D/pFTomkpClT4TaPADoWcL8K2miE\n8rqFJ5gJhLfHh4gbjFSEytvExNFGjoMJFYGtwHICLCbGvjeWls1vQKUyIgPCeIQ3yd0YjfdgMt1M\nUJBCcPAwbrxJuAL/r18Xvnn5HnZOHIPZWKZsTRJJqUdHrJs3QJgemuJNUEDxsPrnnwEXJuIJxoWZ\nRMBKRkaGlz3/gkiqdAMi5K+07bnvqVWrMcJ7ZBHCk2YsoOQpmV4eMOHkWhSuQYQPVMzOkpcPRhUC\nNXEKBIvMrAkJCbmaHDq0HaEt9RDW/hqe9/lh9zxGIQJ9rOS3Krh/3342rt+Nw76dzMzl2O0L+XDi\nTHQ9r3vKmlXTCEBk5glEx2ZLZd68V/7rMBRISso53n67BwkJL+Bw/MmxY20YO/Z+NM0HCVRKMW63\nC0UxkTt0yYLbXVC+mquPz+mMlRcQVQ6XIOaAWVmNQ4A/gT5YLIeZNWu/TLgrkRSCadzFYWpiyzag\nV0UkP56D0K+5wCsoyovcdltPBg36xH/CSiQlSJm6u0/AAowEhng+CQOGgiENAh3g/A1ojVByKyiB\noAeAKV0YSJx4VtquB8IJMIYx97le9KgfyfDhw5jzy3q+2byLgxfXUqlSTZo3H0ZERDOqVq1NRETu\nFbSssJmfSmLHJZKrDBPwIjma3gvo6mWfmTYbt7/+OodOnkRVFB654w4mPfaYl72KKYSTnGqt+UY5\nXBGtEaukAJ2AmwDowVKve/aGpfQotr537lyOOJIrEB6BzwHRZGSkltnqNgX9X4E4+QCyw20icDOy\nwPZ5DQMdk+fS4xLXyLnGs+xDRRj/GyOMTOdzy5DtWGJGuEz397wPBt6kx2WOJ2lnzuF2RgNzPMFB\nXXHYM+mSZqNCYI6cyenp2SaerPNeBXZtmc/SR4sWcrby6F+YaIyVngBo2nBSEmdzc/JcauYT8lNe\n0MI0Pq8Ryv7YIThcfTAZVlCrYiYvRJwkAJkDQLDE89wEGAEGK7gDgInAMOBnDIZARo78ngoVqpSA\nPCt81lOPfwm6y2LpVWAw9xWFOZ6SLBYiPOYbIO6f+gIfIXJhRQAHqV17PS+/PJ5atWoj0hxcTncf\nyiP1qrRytelVqfEkWb16NY0bN6Zhw4ZMmDAh3zZWVODSlcWKgCJmZ24QL+aQPSOsYBWlfLMyoOsq\n6NcjVtpux+46y9AZM2g7dCjnUlIY2OU2fn7zFaZN28nYscvo1WskrVvfncdAIpGUFQqjV6URF6JA\n9zlEKs+D/9q6cHQdPZq0kyf5GvhQ1/l81Sqmr/B+MHYgLqTZNlivufwaV75X0AEOHtyK8ITIyrdR\nHbCwc6fvJku+xBu90hDn8ykgHpFmssBphwuxSJ4VVQocPnw4V5OklBSEea424mbxTgr2PjKQE06K\n53XefBfxiYmYtVW0Zywj+YpwHgXNRYglt4dKoCc/ignh8RXi2b9Mx7/UFv4PrgkOxq2fJse75hwu\nt5UKgSXjFZBmtTJ07hd0HfsWIxcswOrFvlwJqqry85uv0ueW80TVGU6PNofY+M5IAkxXxwT+ynSq\nIjlX2+eAbz2vO+J2u0lPL9/VwCSSwlJ4vQpGjCOpiOqhYxApB/YDVXE4VMLDZY4fydVFqfAkcbvd\nPP/886xbt45atWpx4403cu+999KkSZNc7daRSQhDsDMEIwpWgoEMMXl0K4i15m1kuw+nmUD3uKpq\nZmANIrkiwA3cgp2FDpgYH899Y8bwZv/+tImMhBA4e/YY33wzgZSUJNq06UrXrgOzM9yfP3+SEyf+\n5ppratKgQeviPjwSSZEorF6VRnTEmuFPCPunEREh6w0HT51iGTlXgEPAxO++Y3B371ZAQsjJCZ2V\nftQ7VgJfIJIPjkHcxJZvl/uoqA7Exc0HfkDkYfkMcNO69d3+FSwfvNWrdIQ/ZFZ+VRf/9u+qqHa3\npyCNigtITU3N1eLPkycRZor3gGPAvYgI86359JcBvIKo3qZ5JMkbHjZhyRLqAUsRBsBHgOZoHDh9\nmiZ162a3c7lFGR2LZ18MHknUfKrB6LrOsHnz+Gj1anRdp+fNNzP3hRcwGnIbado0bEi7xjX4ff+d\nWB3tsJh/5KW7e+RrJHG53Qyd+wXLdu6kUlAwnz37LK0bNMhnvwuHy+2m85tvcuBcHHacbD92iG2H\nD7F+zFslUuGmUnAwcwY9Xqi2u44d44dt27CYzQzo3JlaZdjLprA6FUAldOrgwAHYPItjU4H/Q1gS\nZwBrWb36S2688Z6S3g2JpFRRWL0KohKZNEDMtNIQV/ORiNmNAfiK1NQBnDx5gvr1ryvp3ZBI/Eap\nMJLs2LGDBg0aEBERAcBDDz3Ejz/+mEeRzUBHYBpwCp37SCcZPANlALAJhXRMiDWoQN1JkOebeEzo\nNEMo/yYsmDADfYBJus6XZ87w/Pvv47RYePLlWkyePIDMzMfQ9Vs5dOhDkpLO06fPKHbu/ImpU59C\nVW9A0w5wyy3dadeuB9HRHX12PGJiNhIV1eGyY7SUL754A5stldatu/Pkk5MKVfUhv758LVt57e/y\nvjRNY8mSD9iy5SeCg0Pp1290rmpFpY3C6pUv2RgTQ4co35RtrQz8iPAk+RzY4oM+UzzPm4BE4LzX\n+UNycOOjcBujDfTRoOlgcoEPV7J9+f9k4Qude/zxqaxf/w0u1xCEkdtCWFhdatSo7xMZfYm3ehWA\nqB8wH5E96x3gdAFtQ3CzApGT53U05kOeKjPi7HBjoRV1MHIGBw4qFOCd4kbUMHgMcaam5tsqzW6n\nFjmupmGIc/t0YmIuI4nTJcw7GjlhZ27I1/ti3JIlTF25EqOnr8VbtxJgNjNn0KBc7VRVZc+Jfaj2\nZEL5E6cd4hOvzVfO2958g61HDkMgnMlIpO2oUez98EMia9XK09bcuzeVPNtOB+Jmz6ZSpdw5b/4+\ncYJ/Tp1EUy3gNmEzaGw9eJAjCQk0rJF7FfXMmTM0evFFghBH0mo0krZwYb5yPjp9Ois3bUIBgkJC\n2D9zJhZL3vF7za5dPDJuHCrimE559ln+16lTnnY/795N7/fe4xmEN1KL779n1/Tp1KlaNU/biUuX\n8uGiRdg1jfDKldn+4YeE5GNwSrfZeHXePLYePMh1YWH57kdxUVidmg1M4TR7ASeBZCXLFiveSxGz\nxO/Yu3c3AwbUJzy8Hk6ni3r1mvL44+/lCcHRdZ316+eyevUCTCYzDz44hFat7shXxiu5zum6zpQp\nk9i58w8MBgM9e/bivvseKLC90+lk1Fdz+X3PHmpUqcI7jz+e63ybvGwZP2zfQYLDSZcuXbn99jt8\nZrSbP38ea9asBnQ6duzMwIFP5fo+JmYvUVHRPtnWleLPbRfHWFnSFFav3gTe5ggiJbiKGKWEC2MQ\n1XHwHTZbEiNGjEWMOA7CwurTokUU/fo9TEBAQK7+NE1j6dJJbN68gpCQivTrN5oGDW4slMxCz/L/\nzuGw8847Yzly5Ahms4mBA5+mXbuCwzrT09N59ovZ7D1+nMg6dRj3+ONUr5jjSTl/wwamr1xFmsFI\nz569aN36pnzkufJzUNM0Jk16n927d2EwGOjT52G6d/eN0dafOnE55UFH/otSEW4TFxdHnTo5metr\n165NXFxcnnZuxITyGqAFkHUpF7kAbJg9Kp7lsH0nIqL/H+BmNAw8CmxAZQzVOMV8ROT2fOA6IETT\nuD8zk3kfPY7D0QVdHw48gN0+j5UrZ6JpGlOnDsRuX4TV+g12++9s3ryGjRsX+PR4xMRszPX+8OEd\nTJv2PBcvTiQjYxVbtsTx6acvF6kvX8tWnvu7vK+FC9/ixx9/JDZ2NAcP9uDttx/g9OkYn23P1xRW\nr3zJxhjfHI8A4HnEzeHfCL33tghmKjAA+NjT3xd47KtekpUT2oaPAmNcQEAGGDNBcwAKg+v4prKH\nr/6fS/GFzqmqyvz5Z7jttl5Urlyd3r1fYvr0PT6Qzvd4q1dBiBocYQi/j1cRfh35cS9irDMhJrJW\n4NChQ3naBaCxmEz+IJW/sBHsyUlyOYFAMDoBOLAgFhEKCmLZAnyPMFK+itDJw6dzm3MCPOE2GQhP\nLyuePOnOvCaaMd98gxnh1B3s6W/+xrznzuPTp5OSnMwziEj5rsDiX38lMTFvCMXWQ4dFZ0ZPhya4\n4dVX87Sz9OlDMCLTzxygFlDrqafytFu5cyeaFgiufqD3ANcDaFogB/P5fxu/+CLXIlIavguoLhfh\n+eQ4GrlgAT9s2sS7nrah6elcl8+2UzIzeXjcOO7z7PcjwOBZszgaH5+nbb/x45kJvI7wo+jrdnPf\nO+/kaffN5s28vXAhIzWNu4HQxESaPfdcnna6rnPfuHF889tvnIyN5Zddu/K0KU4Kq1P7EL51IQBY\nsZCJ8IwCeBQx66uArs/Han2Q48cPEhs7nG3bjLzxRvc8SXB/+eVz5s6dyMmTQzhypB+TJg0s8Hp2\nJde5SZPeZ+vWrTidJmw2+Oqr+axdu6bA9rOnTiJm3Tpej43l+j176DJqFOc9HmNbDhxg9MKv2X74\nNCdPnmXBgvmsXp1fTogrZ/Hir1m+/EccDhWHw8Datav54ovPcrWJidnrk20VBX9uuzjGypKmsHqV\nCOSY8DQsaIgcPxrXc4JGTMVEXURi9fuBQM6eTWD9eo2JE6fm6W/hwjH88MNSTp8ewf79d/LWW/cR\nF3egUDL/m56NGPEqBw4cxOUykZnpZtq0yezbl/85omluJo4ZjbZ1K2/GxhK6Ywd3jh6N3TM2ffXb\nbwye8zm7T5zl6NE4pkyZzO7dea97RTkHx49/lz/++AOn04jNBvPmfc6GDb9ecT/54U+duJzyoCP/\nRakwkhTWIm5AuMiDmIj9c8nnWWlJLIibFQWxc10833+HlW78jIH+RPI3v2AlyNP2S+BJIAoxeUrL\nSELXL70lM6DrGjZbOi6XDVF1AqACitKSzMwUipO//lqN09kfuBWoh9M5rtTG6pdn1q9fgN2elcyq\nLw7Hw2zb9oO/xSqQknAPLy5ciAlxFgfx/mKVFQ4zFthJfjU9ioYDsTLtC4NLNpmAExQXgM700wX5\nGpQfDAYjTz/9MZ07P0qvXq/5W5wC8VavNESR4yz2UXC4zT/knFf/IOwAS/Kp8qIC7T2vwxCpyfMj\nABGQcBYrCViZTM6iwuU0A2Yh0vElIQwgX27YkKvN7wdFtqBLj0hBnlRZxSSzyPIouZwFmzbRAHgN\nkdxWBF5B13yMAPlt0O7KezQDdJ1XEQmgOyP2KzhPK3hvyRJEZYcJQB3E0QrkiRkz8rQ1IgwuHRAG\njaeBpHw80+asXcuTnjYdPL+x2fJefd5evJgAhNGjLSJ4qhowdO7cPG1dmsalvjL1gGNn8iZ3Hff9\n9/QCnkBUUpoPXMhHxvOpqew4fBjVKYpRm0q4ktCV6NQBhA61AvqjI86qQYiz9DjijGmLMCvWB1Tc\n7ve5eDElz43a6tXzsdvfR8wUe+BwvMwvv3zt9f78+edOhPnRiNCwAFasWJZvW5fLyZadfzDH4eAW\nYLCuc4PLxbo9wkg899cNuDQ8/Ziw21WP54f3rFmzBjFrNnkegT67mZP4nyvRq/2e5yHALSjAtcBd\nbMPEPMDEKYRefYQ4Z9JxuV4nJmYXmZm5g6F/+WU+dvssxKjUH6ezt9dzZV3XiY09jVhmyLGK//RT\n/nqVkJBA8tkEJrlctAXecbvRUlLYc/IkADNXrSbTrpJ17jscKj//XLAh80rYs+dvhP6b+C/9l5Ru\nSkW4Ta1atTh9yU3A6dOnqV27dp52mYicy9GIeVFW+roARBjOL4DVc00w6mLo/BbogVDpCtipjh0d\n+AvhnGlDpHGNRNQKD1RV6l97PftOrsLtboiuNyQg4H26dn2CwMAKVKpUm4sXFwD9gMNo2iYqVSq+\nqg8AwcGhGI2HyFmcO4nFElqs25TkxWAwcWn8vqpmYDIV7JYcE7PR554yV0Jh9Wrs4sXZrztERZUK\n9zk3sBwRHpMATEcULvUGHTFkZXl8WHzQZ3EQSu4gCJWCb2SvRsq6XqUiCvD+BexAJHC1FrCt4whv\nyKYIfbABn9x5Z552OiLjVjdE6M7OAvpzkzsDSSYFG2j+BqYANwKTEFPTWy5z0w5XFAwIb5f9iAlF\nPXIbgbIwIPQtyzhio+D0slkeKYrnNxpwTUhI/o0zEMqcVcEuH3Tw+JkKCspvZDQY0Fx29GyfMFF2\n2ZJP8lSF3P9bQYF7iqrm2l5B2w4JDMTp2aIZsc92yHfbNmAoIr1iEvA+4FbzmpFNRmOe/zu/2yaT\nwYBb07IXmHyTgLrwFFanvkAUCncDo4HvURBnUSKe7PwIs7XR89rqee1C1+0YDLmnvGJMz/3vGI3e\nT4vz3pzqGI35+0IqipqtD0FZUigKRs//GZBHHh2DwVu/SoHBoJL739ZRVd/0LREr7f5cbS+sXs0k\nZ9GoC7AjW68yUMi6tmWdF+KaKNDRdR31smvP5XqlKJkYjcWRgFrPo9M5Mhhw6nqu66lN17P1ymTK\nukbk9OUL3Yf89d9XOispYb3SSwFOp1OvX7++fvz4cd1ut+stWrTQ9+3bl6tNhw4ddMQZLR/yUSYf\nHTp0KHV61aJFC78fF/mQD28epVGv5HglH2X9UZJ6JXVKPq6Ghxyr5EM+fP8oTr0qFZ4kRqORGTNm\n0K1bN9xuN0888USexEIbLnPzlUgk/05h9Gr37t1+kk4iKZvI8Uoi8S1SpyQS3yP1SiLxDkXXdd3f\nQkgkEolEIpFIJBKJRCKR+JtSkbhVIpFIJBKJRCKRSCQSicTflHojyerVq2ncuDENGzZkwoQJBbaL\niIigefPmtGrViptuErWuExMT6dq1K5GRkdx+++0kJydntx83bhwNGzakcePGrF27lscff5ywsDAa\nNGhAs2bNaNiwIU8//XShf5/Fn3/+SbNmzQgNDSUoKIhmzZoBYLfbiYqKwmg0EhwcTFRUFKtWrSpU\nf40aNSIoKIgqVaoQHR3NtGnTsNvt9OjRg6CgIAIDA2nfvn2h5Suov6LKFxUVhcVioVq1ajRt2pSR\nI0d6JV9B/RVVvmbNmtGgQQOqVavGPfeIWuXx8fGEh4djNpupWLEie/bsKXRfDRs2ZPDgwbRq1Yp7\n7rnHa9kaNmzIkCFDsj+32+306dOHhg0bcvPNN3PSk427OPj222+JiorCYDDw119/edVXYXW1sGTp\nZJYO+YLTp0/TqVMnoqKiss99b7DZbLRp04aWLVtmn6u+wu12Z59jviC/a6Q3JCcn06tXL5o0aULT\npk3Ztm2bV/0dPHiQVq1aZT8qVqzo9f9TWvG1rvgbX59bJU1+15p/mz+UdvLbnzFjxlC7du1s/Vq9\n2jcVUkqC4taXK/3/CxrTi0JBY1JJbL+g8auk9h3yjnMltW1v7xn+n707D4uqbP8A/h1gUHbZQQYE\nQTJGAxQ1LV80t9RUDEWwkNzSLN+0RbNcskXRtNQyW34uaCmSGaLivqBlSu6J9rormySyCcjMMHP/\n/iBOso8wzBnw/lyXl8ycM89znzPnPssz5zxPcyDGcUjMXKtMzNyrjiHkY2Vi5afBaLTeTnSgtLSU\nvL296caNG6RUKqvtdKicp6cn3bt3r8J77777Li1atIiIiKKjo2nmzJlERJSSkkL+/v6kVCrpxo0b\n5O3tTUlJSXT69GkyMzOjEydOEBGRl5cXjRs3TqvPazQaIiLq0qULnThxgo4cOUI9evQgT09PIiJa\nuXIlBQUF0dKlSyk2NpZGjRolxFlXeYmJiXTmzBkaOHAgbd26lXx9fWnOnDkUEBBAixYtotjYWHrq\nqae0jq+m8uob34kTJ6ioqIgGDhxIO3bsoG7dutH06dPrHV9N5TUkvqVLl5Krqyt169aNiIj69u1L\nTz/9NBERRUREUPv27bUui4ioffv21KtXLxoyZEiDvtvy8gYOHEi7du0StpXXXnuNiKhKebp26dIl\n+t///ke9evWiU6dO1bucR8lVbR05coROnz5NHTp0aFA5D8vMzKQzZ84QEdH9+/fJ19e3wXEWFRUR\nUVknad26daOjR482OE4ioqVLl9Lo0aNpyJAhOimvun1kQ4wZM4ZWr15NRGXLnpeXp7Oy1Wo1ubi4\n0O3bt3VWpqFojFwRm663LX2rbl9T0/lDU1Dd8nz44Ye0dOlSEaOqH33ky6N8/9Ud09Vqdb3rrumY\npK/6qzt+6atuoqrHOX3V3dBrhoYut9jEOg6JmWuViZ171RE7HysTKz8NhUHfSZKcnAwfHx94enpC\nKpUiPDwc27Ztq3F+qtS9SkJCAqKiogAAUVFRiI+PBwBs27YNERERkEql8PT0hI+PD0xNTaFSqaDR\naIRWZYVCAdU/4+7W9fkTJ04gMzMT9+/fR9euXdGzZ0+Eh4ejoKBAiCUgIABEhNDQUBw4cECIs67y\nBg4ciICAAIwZMwZ79uzBk08+iV27diE3NxdRUVEIDQ1FWlqa1vHVVF594+vatSvMzc0xZswYbN26\nFWq1GsnJyfWOr6by6htf69atkZiYiPHjxyMzMxMA8Pvvv2POnDkAgMWLF+PKlStax5aWlgYTExNY\nWlqCiJCQkAB/f/96rzsAGDNmjLB+Ht5uK5ena+3bt4evr2+Dy3nUXNVGz549YWtr2+DYHubi4oKA\ngAAAgKWlJZ588klkZGQ0qExz87KBG5VKJdRqNezs7BocZ1paGhITEzFhwoQq+7WG0FVZ+fn5OHr0\nKMaNGwegrIM4GxsbnZQNAPv374e3tzfc3d11VqahaIxcMQS63E71rbp9TU3nD01BTfvOpvgd6SNf\nHuX7r+6YnpycXO+6qzsmpaen663+yscvW1tbvdVd3XFOX3UDDbtmaGjdYhPrOCRmrlUmdu5VR8x8\nrEzs/DQEBt1Ikp6eXuEkWSaTIT09vdp5JRIJ+vbti6CgIHz//fcAgKysLDg7OwMAnJ2dkZWVBQDI\nyMioMFZ4eblZWVkVxskuKChAbm6u1p+v/L6zs7PQyJKeng4bGxt8+eWX6Ny5MxQKBW7cuPFI5bm5\nueHKlSs4c+YMioqKkJeXB2dnZ5iYmKBVq1a4c+dOg8prSHwajQZz5sxBTEwMevfujfz8/AbFV115\n9Y1v+vTp+Oyzz+Dk5ISSkrLR4B88eCDsHN3c3EBEyMnJ0Sq26dOnY9q0abh3757w3bZq1arB3235\ntv3wdl9+8ZmTkwND9ii5aihu3ryJM2fOoFu3bg0qR6PRICAgAM7Ozujduzf8/PwaHFv5NmtkpLtd\ndHX7yPq6ceMGHB0dMbc7MsQAACAASURBVHbsWHTq1AkTJ05EcXGxjiIFYmNjMXr0aJ2VZ0iaYq7U\nRZfblqGo6fyhKfvyyy/h7++P8ePHN5nHh8TKl0c9f9SFh49J+qq/8vFLLpfrre7qjnP6qlsX1wxN\nmSEdhwxhvYuRe9URMx8rEzM/DYVBN5JIJBKt5/3tt99w5swZ7Nq1CytXrsTRo0erlPUo5VUXS0M+\nD5TdLXDjxg2cPXsWxsbGwp0M2iouLsapU6ewfPlyGBsbNzi+yuU1JD4jIyOsWbMGffv2xZEjR1BY\nWNig+Korrz7x3b17F05OTggMDKzxV7RHiWvHjh1wcnKCr69vhfIa+t02pn79+qFjx45V/m3fvl1n\ndTQ0N/StsLAQI0aMwPLly2FpadmgsoyMjHD27FmkpaXhyJEjDR5Sr3wbq22brY+69pGPorS0FKdP\nn8aUKVNw+vRpWFhYIDo6WidxKpVKbN++HSNHjtRJeYamqeWKNnS5bRkiXRz/xfbaa68JxyhXV1e8\n/fbbYoekFUNY73V9/7qIsbCwEKGhoVi+fDmsrKz0Vn/l49ehQ4f0Urc2x7nGXO6GXjMYwnbZEIYa\nvxjrXazcq45Y+ViZ2PlpKAy6kcTNzQ2pqanC69TU1AotVQ9zdXUFADg6OmL48OFITk6Gs7OzcPdC\nZmYmnJycqi03LS0NMpkMLi4uKC0tFd63srISbgvT5vNubm5IS0sT3r9z5w6kUqnwmeLiYkgkEqjV\nakgkEpw7d07r8lQqFd59913I5XKEhITAzc0NNjY2uHPnDkpLS5Gbmyu07tW3vIbEV/6+l5cXBg8e\nLHSIWt/4qiuvvvElJCTAy8sL8+bNQ05ODiIjI2FmZoYzZ84AKNuuJBIJ7Ozs6izr2LFjSEhIQGho\nKM6fP4+DBw8iJydHJ+uufNt2c3PD7du3AZRdjObn5zfoEY59+/bhzz//rPJPVx2CAo+Wq2JTqVQI\nDQ3Fyy+/jJCQEJ2Va2Njg8GDB+PkyZMNKqd8G/Py8kJERAQOHjyIMWPGNDi+6vaR9SWTySCTydCl\nSxcAwIgRIxrc8W+5Xbt2oXPnznB0dNRJeYamKeWKtnS5bRmKms4fmionJyfhpHbChAlN5jsSK18e\n5fzRzc2tQXWVH5MiIyOFY5I+6wf+PX6dOnVKL3VXd5yLjIzU23I39JpBF+tcTIZ0HBJzvRtC7lVH\n3/lYmdj5aSgMupEkKCgIV65cwc2bN6FUKrF582YMHTq0ynzFxcW4f/8+AKCoqAh79+5Fx44dMXTo\nUMTExAAAYmJihAQYOnQoYmNjoVQqcePGDVy5cgVdu3aFo6MjjIyMcOLECRARWrZsKTx+o83nXVxc\nYG1tLXx+69atsLa2Fj7z9ddfAwC2bNmCNm3aCL0711Xe8ePHMX78eNy/f1+4Q2Ho0KGwtbVFTEwM\ntmzZAplMpnV8NZVX3/j27NmD3NxcbNiwAc8//zz27duHAQMG1Du+mspbtWrVI8fn7e2NLVu24Pr1\n6/D19UWnTp2wYcMGdO/eHR9//DEAYMaMGWjXrp1WsQ0bNgy3b99GUFAQ5s2bh+eeew4ffPBBvddd\n+bayYcMGDBs2TPhM+Xa7ZcsW9OnT55Fzpz4acteCtrkqNiLC+PHj4efnh2nTpjW4vOzsbOG29QcP\nHmDfvn0IDAxsUJkLFixAamoqbty4gdjYWDz33HNYv359g8qsaR9ZXy4uLnB3d8fly5cBlPUhIpfL\nGxRjuU2bNiEiIkInZRmippIr2tL1tmUoajp/aKrK++MCgF9++aXJfEdi5cujnj/WV03HJH3UX9Px\nSx91V3ec27Bhg17q1tU1Q1NmSMchsda7mLlXHTHzsTIx89Og6KuH2PpKTEwkX19f8vb2pgULFlQ7\nz/Xr18nf35/8/f1JLpcL8927d4/69OlD7dq1o379+lFubq7wmU8//ZS8vb3piSeeoN27d1N4eDi5\nurqSiYkJmZiYkKOjI02cOFHrz5c7efIkdejQgSwtLcnCwoKkUinJZDL65ptvqE2bNmRqakrm5ubU\nr18/unPnjlbleXl5EQBycHCggIAACggIoISEBBo2bBiZmZlRy5Yt6dlnn9U6vurK27ZtW73j8/Hx\nIVNTU3JwcKCOHTvS4sWLqaSkpN7x1VRefePr0KEDeXt704svvij00JyRkUFOTk4klUrJ2tqazp07\n90hlTZ06lQ4dOkRDhgyhkpIS8vDwaFBsU6dOFd4vKSmhkSNHko+PD3Xr1o1u3LhBjWXr1q0kk8mo\nZcuW5OzsTM8//3y9y9ImVx9FeU6ampqSTCajNWvWNLjMo0ePkkQiIX9/f2HbLx9VqD7Onz9PgYGB\n5O/vL2yrunT48GGdjG5T0z6yIc6ePUtBQUH01FNP0fDhw3Uyuk1hYSHZ29tTQUFBg8syZLrOFTE1\nxralb+X7mvLj9Zo1a2o9fzB0lZdn9erVFBkZSR07dqSnnnqKhg0bVuEYZegaO18e9fuv6ZheHzUd\nk/RRf03HL30te7mHj3P6qFsX1wzNgRjHITFzrTIxc686hpKPlek7Pw2JhKgJdnfOGGOMMcYYY4wx\npmMG/bgNY4wxxhhjjDHGmL5wI4kWPD09ceDAAb3UZWVlhZs3b+qlLqZ/N2/ehJGRETQajdihGAzO\nL1Yfhw8frjCE4eOO80i3fvzxRwwYMEDsMBjTqVdeeUX00fd69eqF1atXA+A8Y82DoeWVPixcuBAT\nJ07UW31i4EYSLehz+L/79+/D09NTL3XpyhNPPIGrV6+KHQZroji/asf5xbTBeVS7R82jl156CXv2\n7NFq3uTkZAwaNAi2trawt7dHt27dsG7dunpGqj+enp44ePCg2GEwPWrofmLhwoX44IMPdBaDtnlm\nCBehjNXE0PJK16r7UWrWrFn4/vvvG6U+Q8GNJAbi4aGHm5Jr165Bo9HAx8dH7FAYqxHnF2MNx3lU\n1e+//44+ffqgd+/euHbtGu7du4dVq1Zh9+7dOq9L1yQSSYNGNWNNU0O+88TERAwePFiH0TDWPDTV\nvCIiPg7UwOAbSRYtWgSZTAZra2u0b99e+NXjww8/xIgRIxAeHg5ra2t07twZ58+fFz6XkZGB0NBQ\nODk5oW3btvjyyy+FaUSE6Oho+Pj4wMHBAaNGjUJubq4wfcOGDWjTpg0cHBywYMGCGmM7ceIEXF1d\nK2xcv/zyC/z9/QGU/brUvXt32NraonXr1pg6dSpUKpUwr5GREb7++mu0a9cOTzzxhPDe9evXAQA7\nd+5EYGAgbGxs4OHhgfnz5wufLX9sY/369WjTpg0cHR0rxKrRaLBgwQL4+PjA2toaQUFBSEtLAwD8\n9ddf6NevH+zt7dG+fXv89NNP1S7f5s2b0aVLlwrvffHFF8JQteUxlid2YmIi5HI5rK2tIZPJsHTp\n0mrLXbduHZ555hm89dZbsLW1hY+PD44dO4a1a9fCw8MDzs7OFYY8rW09bN68GW3bthWGc9u1axdc\nXV1x7969KvWWlJTg5ZdfhoODA2xtbdG1a1fcvXsXQNltarNmzUK3bt1gY2ODkJCQCtvE8ePH0aNH\nD9ja2iIgIABJSUnCtPz8fIwfPx6tW7eGTCbDnDlzhMdpNBoN3nnnHTg6OsLb2xs7d+6sdp2IhfOL\n80tX+QUAI0eOhKurK1q1aoXg4GBcvHhRmPbgwQO8/fbb8PT0RKtWrdCzZ0+UlJQAAH799Vchvzw8\nPIQh5hQKBd555x20adMGLi4ueO2114TPGBLOo+aZRz179gRQ9l1Mnz4dzs7OsLGxwVNPPSVs2+++\n+y5eeeUVvPvuu7CzswMAdOrUCbGxsUJZ33//Pdq1awd7e3sMGzaswnC8RkZGWLVqFdq1awdra2vM\nnTsX165dQ/fu3dGqVSuEh4cL38fhw4chk8nw2WefwcnJCa1bt0Z8fDwSExPh6+sLe3t7REdHC2VX\n/vX94V8DIyMjcfv2bQwZMgRWVlZYsmQJgNqPdc2Fp6cnlixZgqeeegpWVlYYP348srKyMHDgQNjY\n2KBfv37CUJxAzfs1pVKJwMBAfPXVVwAAtVqNZ555Bp988km19da07ZV/rwsXLoSjoyO8vLywceNG\n4XN17Qd37NiBgIAA2Nra4plnnsGff/4pTDtz5gw6deoEa2trhIeH17j/VCgUaNWqFVJSUoT37t69\nC3Nzc2RnZwMAcnNzcfnyZXTv3h3Z2dl44YUXhLun/vOf/9R4obVv3z60b98erVq1wtSpUyvMV1ee\npaSk4LvvvsPGjRuxePFiWFlZCbldvn+0traGXC5HfHx8hXKfffZZIS/btm1boeEyJycHY8eOhZub\nG+zs7DB8+HCt1ierGedVVWLl1YcffojIyEjhdeVH/Xv16oXZs2fjmWeegYWFBa5fv461a9fCz88P\n1tbW8Pb2xnfffQegbJjsgQMHIiMjA1ZWVrC2tkZmZmaVOhISEiCXy2Fra4vevXvjr7/+EqZ5enpi\n6dKl8Pf3F45rCoWi2uUyKHoeTeeR/PXXX+Tu7k6ZmZlERHTr1i26du0aERHNmzePpFIp/fzzz1Ra\nWkpLliwhLy8vKi0tJbVaTZ06daKPP/6YVCoVXb9+ndq2bUt79uwhIqJly5ZR9+7dKT09nZRKJU2a\nNIkiIiKIiCglJYUsLS3p6NGjpFAo6K233iITExM6cOBAtTF6e3vTvn37hNcjRoygRYsWERHRqVOn\n6MSJE6RWq+nmzZv05JNP0rJly4R5JRIJ9e/fn3Jzc6mkpER4r3wZDx8+TBcuXCCisqGhnJ2dKT4+\nnoiIbty4QRKJhF599VUqKSmhc+fOUYsWLeivv/4iIqLFixdTx44d6fLly8Ln7927R4WFhSSTyWjd\nunWkVqvpzJkz5ODgQBcvXqyybMXFxWRlZUVXrlwR3gsKCqLNmzcLrwcMGEB79+4lIiIXFxf69ddf\niYgoLy+PTp8+Xe06W7t2LZmYmNC6detIo9HQ7Nmzyc3Njd544w1SKpW0d+9esrKyoqKiojrXAxHR\nSy+9RK+88gplZ2dT69ataefOndXW+80339CQIUPowYMHpNFo6PTp08JQo8HBweTm5kYpKSlUVFRE\noaGh9PLLLxMRUVpaGtnb2wtDxe7bt4/s7e0pOzubiIhCQkJo8uTJVFxcTH///Td17dqVvv32WyIi\nWrVqFbVv357S0tIoJyeHevXqRUZGRqRWq6uNUZ84vzi/6loPRNrnV3ndhYWFpFQqadq0aRQQECBM\nmzJlCvXu3ZsyMjJIrVbT77//TgqFgm7evElWVlYUGxtLpaWldO/ePTp79iwREU2bNo2GDRtGubm5\ndP/+fRoyZAjNmjWLiIgOHTpEMpmsxlj0hfOo+ebRs88+S0REu3fvps6dO1N+fr7wnWdmZlJRUREZ\nGxvT4cOHqy2DiOjAgQPk4OBAZ86cIYVCQVOnTqX//Oc/FdZvSEgI3b9/n1JSUsjU1JR69+5NN27c\noPz8fPLz86OYmBgiKtvmTUxM6OOPP6bS0lL6/vvvyd7enkaPHk2FhYWUkpJCZmZmdPPmTSIieuWV\nV2jOnDlCXZVzxtPTs8I2U9Ox7u7duzUuX1Pk6elJ3bt3p7///pvS09PJycmJAgMD6ezZs1RSUkLP\nPfcczZ8/X5i/tv3ahQsXyNbWli5dukSffPIJde/enTQaTbX11rTtlX+vb7/9NimVSkpKSiILCwv6\n3//+R0S17wdPnz5NTk5OlJycTBqNhmJiYsjT05OUSiUpFAry8PCgZcuWUWlpKW3ZsoWkUmmFbeJh\n48aNow8++EB4/dVXX9HAgQOF15s2baLRo0cTEdF7771HkydPptLSUiotLRWWq7K7d++SlZWVsA/8\n4osvyMTEhFavXi2s27ryjKjqtkxE9NNPPwnTN2/eTBYWFsLQ1mvXriWpVEr/93//RxqNhlatWkWt\nW7cWPjto0CAKDw+nvLw8UqlUdOTIkVrXp0KhqHb52L84rwwnrz788EPhGobo32Nx+bVHcHAwtWnT\nhi5evEhqtZpUKhXt3LmTrl+/TkRESUlJZG5uLqzLw4cPVznferiO//3vf2RhYUH79++n0tJSWrx4\nMfn4+JBKpSKism2jW7dulJmZSTk5OfTkk0/SN998U+2yGRKDbiS5cuUKOTk50f79+0mpVFaYNm/e\nPOrevbvwWqPRkKurKx09epSOHz9OHh4eFeZfsGABjR07loiI2rdvX+HEICMjg6RSKZWWltL8+fOF\nE1EioqKiIjI1Na3x5HP27Nk0btw4IiIqKCggCwsLun37drXzfvHFFzR8+HDhtUQioUOHDlWY5+GT\nz8refPNNmj59OhH9u8Gnp6cL07t27SqcGPr6+lJCQkKVMmJjY6lnz54V3nv11Vcr7Lge9vLLL9NH\nH31ERESXL18mKysrevDgARGVrRt7e3vhu/Hw8KBvv/1WOMDVZO3atdSuXTvh9fnz50kikdDff/8t\nvGdvb0/nzp2rcz0Qle0UPTw8qGPHjjR58uQa612zZg316NGDzp8/X2Var169hJ0jEdHFixfJ1NSU\n1Go1RUdHU2RkZIX5BwwYQDExMXTnzh1q0aKFsE6IiDZu3Ei9e/cmIqLevXsLDSZERHv37q2woxIT\n51dFnF9V1wOR9vlVWW5uLkkkEiooKCC1Wk1mZmbV5t6CBQvoxRdfrPK+RqMhCwuLCt/XsWPHyMvL\ni4gMp5GE86ii5pRH5RdvBw4cIF9fXzp+/HiFfXdaWhpJJBLhpLs648aNo5kzZwqvCwsLSSqV0q1b\nt4iobF0eO3ZMmN65c2davHix8Prtt9+madOmEVHZNm9mZiZcLBQUFJBEIqHk5OQKn9+2bRsRlV1Y\nzp49W5hWVyNJbce65sTT05M2btwovA4NDaUpU6YIr7/88ksKCQmp9rMP79fKLV26lHx9fcnOzo6u\nXr1aY701bXvlF3PFxcXCe2FhYfTxxx/XuR+cPHlylYuzJ554gpKSkigpKalCwwARUY8ePWq8mNu/\nfz95e3tXmHfDhg3C65dffpl++OEHIiKaO3cuDRs2rNblJSKKiYmpsA8kIpLJZNU2ktSUZ0RVt+Xq\nBAQECNv+2rVrycfHR5hWVFREEomEsrKyKCMjg4yMjCgvL69KGbWtT1Y7zivDyat58+bV2kjSq1cv\nmjdvXq11hISE0PLly4mo+vOth+v46KOPaNSoUcI0jUZDbm5uQt54enrSjz/+KEyfMWPGI51PisWg\nH7fx8fHBsmXL8OGHH8LZ2RkREREVblOVyWTC3xKJBDKZDBkZGbh9+zYyMjJga2sr/Fu4cCH+/vtv\nAMCtW7cwfPhwYZqfnx9MTEyQlZWFzMzMCuWam5vD3t6+xhhHjx6NrVu3QqlUYuvWrejcubNwO+vl\ny5fxwgsvwNXVFTY2Nvjggw+q3KZe2+gMJ06cQO/eveHk5IRWrVrh22+/rfJ5FxeXCrEWFhYCANLS\n0uDt7V2lzFu3buHEiRMV1s3GjRuRlZVV4/Jt2rQJALBx40YMHz4cLVu2BAAcOHAAzzzzDKRSKQDg\n559/RmJiIjw9PdGrVy8cP368xmVzdnYW/jYzMwMAODo6VnivfFnqWg82NjYYMWIELly4gLfffrvG\nOiMjIzFgwACEh4fDzc0NM2fOrPCM/cPfhYeHB1QqFbKzs3Hr1i389NNPFdbZb7/9hjt37uD27dtQ\nqVRwdXUVpk2ePFl4jCczM7NKuYaC84vzS5v1oG1+aTQavPfee/Dx8YGNjQ28vLwAANnZ2cjOzkZJ\nSUm16ywtLQ1t27at8v7du3dRXFyMzp07C+ty4MCBwi2qhoLzqPnmUbnnnnsOb7zxBl5//XU4Oztj\n0qRJuH//PmxtbWFkZFTh+64sMzMTbdq0EV5bWFjA3t4e6enpwnuV8/Xh1y1bthTWFwDY29sLnfOV\n53blzz88/6Oo7VjX3Gi7ztVqdZX9mkQiqbAfGjNmDG7fvo1BgwZVuz2Xq23bs7W1Fb5PAGjTpg0y\nMzORnZ1d637w1q1bWLp0aYXvLC0tDZmZmcjIyICbm1uFGNq0aVPj7fu9evVCcXExkpOTcfPmTZw7\nd054DEWj0WD//v14/vnnAZQ9Zubj44P+/fvD29sbixYtqrbMjIyMCvsqoOb9SU15VpP169cjMDBQ\nWO4LFy5U2PdU3u8AQGFhIVJTU2FnZwcbG5sqZda2PlndOK+qEjuvalJ5/l27duHpp5+Gvb09bG1t\nkZiYWOOj1dXF8/D1jUQigbu7e4Xj3MP52JDjlD4ZdCMJAERERODo0aO4desWJBIJZs6cKUxLTU0V\n/tZoNEhLS4Obmxvc3d3h5eWF3Nxc4V9BQQF27NgBoOxCdffu3RWmFxcXo3Xr1nB1da1QbnFxca0b\nyZNPPok2bdpg165d2LhxI0aPHi1Me+211+Dn54erV68iPz8fn376aZWhX2vriXj06NEICQlBWloa\n8vLyMHnyZK2HjnV3d6+2J38PDw8EBwdXWPb79+9j5cqV1ZbTt29f3L17F+fOnUNsbGyF5UtMTMSg\nQYOE10FBQYiPj8fdu3cREhKCsLAwrWKtS13r4ezZs1i7di1Gjx6NqVOn1liOiYkJ5s6di5SUFBw7\ndgw7duyo0DfD7du3K/wtlUrh6OgIDw8PREZGVllnM2bMgEwmQ4sWLXDv3j1hWn5+vvDsoqura5Vy\nDQnnF+eXrvLrxx9/REJCAg4cOID8/HzcuHEDQNlz5g4ODmjZsmW168zd3R3Xrl2r8r6DgwPMzMxw\n8eJFYV3m5eWhoKBAB0utW5xHzT+Ppk6dipMnT+LixYu4fPkyPvvsM5ibm6N79+7YsmVLjZ9r3bp1\nheGSi4qKcO/evSon2TVpyGgFFhYWKC4uFl5XbuyoXHZtx7rmrqYLnI0bN1bZr1Gljg6nTJmCF154\nAbt378Zvv/1WYx21bXvl+V3u1q1baN26dZ37QQ8PD3zwwQcVvrPCwkKMGjUKrq6uFS5SysutaZsy\nNjZGWFgYNm3ahE2bNmHIkCGwsLAAAPzxxx9o06aN0BhraWmJJUuW4Nq1a0hISMDnn39e7UhJrVu3\nrrCvIqIKryurLs+AqtvqrVu38Oqrr2LlypXIyclBbm4uOnTooFUHlO7u7sjJyUF+fn6VabWtT/bo\nOK/EyStLS8ta9/1AxZxSKBQIDQ3FjBkz8PfffyM3NxeDBg0Svo+6jkNubm64detWlXhqOs7payS+\nhjLoRpLLly/j4MGDUCgUaNGiBVq2bAljY2Nh+qlTp/DLL7+gtLQUy5YtQ8uWLfH000+jS5cusLKy\nwuLFi/HgwQOo1WpcuHABJ0+eBABMnjwZ77//vnDBevfuXSQkJAAARowYgR07duC3336DUqnE3Llz\n6zzhGz16NJYtW4ajR49i5MiRwvuFhYWwsrKCubk5/vrrL6xateqRlr+wsBC2trYwNTVFcnIyNm7c\nqPWGNWHCBMyZMwdXr14FEeH8+fPIycnBCy+8gMuXL+OHH36ASqWCSqXCH3/8UaGDnYdJpVKMHDkS\n77zzDnJzc9GvXz9h2u7du4XO8FQqFX788Ufk5+fD2NgYVlZWFb6rhqhtPZR3xrpw4UKsWbMG6enp\nNa7nw4cP488//4RarYaVlRWkUqkQIxHhhx9+wKVLl1BcXIy5c+di5MiRkEgkePnll7F9+3bs3bsX\narUaJSUlOHz4MNLT0+Hq6or+/fvjrbfewv3796HRaHDt2jUcOXIEABAWFoYVK1YgPT0dubm5FTrV\nExvnF+cXoLv8KiwsRIsWLWBnZ4eioiK8//77wjQjIyOMGzcOb731FjIzM6FWq/H7779DqVTipZde\nwv79+/HTTz+htLQU9+7dw7lz52BkZISJEydi2rRpwp1Z6enp2Lt3r06WW1c4j5p/Hp08eRInTpyA\nSqWCubl5he948eLFWLduHZYsWSI0VJ07dw4REREAyhrQ1q5di3PnzkGhUOD999/H008/XetdhQ9f\nKGhz0VeTgIAAJCYmIjc3F3fu3MGyZcsqTHd2dq7QQFnbse5xVdt+DSjrQPnMmTOIiYnBihUrEBUV\nhaKioirlaLPtzZs3DyqVCkePHsXOnTuFc5Da9oMTJ07EN998g+TkZBARioqKsHPnThQWFqJHjx4w\nMTHBihUroFKpsHXrVvzxxx+1Lu/o0aMRGxtbpTE1MTERL7zwgvB6586dQt5aW1vD2Ni42lwaPHgw\nUlJShH3gihUrarwzqbY8c3Z2FjqLBsoaGyUSCRwcHKDRaLB27VpcuHCh1mUr5+rqioEDB2LKlCnI\ny8uDSqUSztlqW59MdzivyjRWXgUEBODIkSNITU1Ffn4+Fi5cWKWMh48tSqUSSqUSDg4OMDIywq5d\nuyqcazk7O+PevXs1/kg1cuRI7Ny5EwcPHoRKpcLSpUvRsmVL9OjRo9r5G3Jc0yeDbiRRKBSYNWsW\nHB0d4erqiuzsbOGLlkgkGDZsGDZv3gw7Ozv8+OOP2Lp1q7BB7dixA2fPnkXbtm3h6OiIV199Vfhy\n33zzTQwdOhT9+/eHtbU1unfvjuTkZACAn58fVq5cidGjR6N169aws7Or8xamiIgIHDlyBH369BF6\ntweAJUuWYOPGjbC2tsarr76K8PDwCieP1Z1IPvze119/jblz58La2hoff/xxlZbs2k5E33rrLYSF\nhaF///6wsbHBxIkTUVJSAktLS+zduxexsbFwc3ODq6srZs2aBaVSWWNZo0ePxoEDBzBy5EgYGZVt\nMhcuXIClpWWF271++OEHeHl5wcbGBt999x1+/PHHasurbizv2pal8np4uJV41qxZaNOmDSZNmgRT\nU1P88MMPmD17drW/TN+5cwcjR46EjY0N/Pz80KtXL6FnZolEgsjISLzyyitwdXWFUqnEihUrAJTd\nLr9t2zYsWLAATk5O8PDwwNKlS4WLkvXr10OpVMLPzw92dnYYOXKksLOaOHEiBgwYAH9/fwQFBSE0\nNNRgWlA5vzi/YPb+hwAAIABJREFUqlsP9c2vMWPGoE2bNnBzc0OHDh3QvXv3CvUuWbIEHTt2RJcu\nXWBvb49Zs2ZBo9HA3d0diYmJWLp0Kezt7REYGCiMALNo0SL4+Pjg6aefFnrHv3z5slbLpS+cR80/\njwoKCvDqq6/Czs4Onp6ecHBwwLvvvgsA6N69Ow4ePIiDBw/C29sb9vb2mDRpktAw06dPH3z88ccI\nDQ1F69atcePGjQoj39S1fivn86PkdmRkJPz9/eHp6Ynnn3++ync7a9YsfPLJJ7C1tcXnn39e57Gu\nOatpnde2X7t9+zamT5+O9evXw9zcHBEREQgKCsJbb71VbR21bXsuLi7CCFORkZH49ttv4evrC6D2\n/WDnzp3x/fff44033oCdnR3atWsn3CErlUqxdetWrFu3Dvb29oiLi0NoaGit66Fr166wtLREZmYm\nBg4cKLxf+Y6sK1euoF+/frCyskKPHj3w+uuvIzg4uEp59vb2+Omnn/Dee+/BwcEBV69exbPPPlvt\nuq4tz8aPH4+LFy/C1tYWL774Ivz8/PD222+je/fucHFxwYULF2os9+H3ym3YsAFSqRTt27eHs7Oz\ncL5X2/pkj47zqoy+86pv374YNWoUnnrqKXTp0gVDhgypNR+srKywYsUKhIWFwc7ODps2baowQlz7\n9u0RERGBtm3bws7ODpmZmRW+zyeeeAI//PADpk6dCkdHR+zcuRPbt2+HiYlJteujuvw0RBJqKs05\nlcyfPx9Xr17Fhg0bxA7lsbR48WLk5OQY1J0RDdG7d29ERkZi3LhxYodiEDi/xNXc8utxxXkkLs4j\n1hQcPnwYkZGRtT6GIqasrCx06tTpsb6jiDU9nFesoapv4mkCmmjbTrPh5eVVoZWxOeBt6l+8LsTV\nHPPrccR5JC7OI8YarqCgAJ9//rnYYTDWrHBeGb4m20jSVG7Vaa4efqa9ueDt6V+cX+Jqjvn1OOI8\nEhfnEWsqDHk/0a5dO7Rr107sMBh7ZJxXrCGa7OM2jDHGGGOMMcYYY7rUZO4k8fPrgEuXUsQOg7F6\nCw4OxuHDh8UOo4L/+Pnh6KVLYofBWL1xXjGme4aWV56eXrh166bYYTBWb4aWUwDg18EPl1L4WMWa\nrsbMqyZzJ4lEIsGIEaMQFhZey1yDdVpnXNxHCAub28BSdj5CfbF1LJ/u6LMu3danzXe8U8/LN1ir\nbSUszNTg+iiQSCSYPWIE5j40okll8ZDqtM6mu+0ZVl1cX5mwsOFNLq/iEaLzOmvbB4UgXmf1xENq\nkNuBdrQ7R9DNsV97+qxP27oM7XglkUgQF/dLrfOEQKVVWbXl37/rp+5zN+3rq3oM1VcO6aOe5rQs\njVmPoR6r4n6Jq30mlTbHq7J8qXvdaX+dputrMF1/r4ZcniHHpuvyGjOvDHoIYMYYY4wxxhhjjDF9\n4UYSxhhjjDHGGGOMMTSxRhK5vIOe6wvWc336Wz79r8vmXp9+txVdCpbL9Vpfc94WmvOyPQ716ZL+\n80p/+6Dmvh3o/9ivz++u6R6r9EFf60df27Q+6mlOy6LPepojXa47Xeeirr9XQy7PkGNrjPIaS5Pq\nk6Su51F13SeJbmjfJwnThnZ9kuiXdtudoT3jDZTllTKu9udRdd0nCWO6ZKjPedeWV43RJ0ltdN0n\nSdNliOcIhsnQjlf66pPkX43bJwl7/BjqsUqXfZLUTd/7YL4Ga+64TxLGGGOMMcYYY4yxRsaNJIwx\nxhhjjDHGGGPgRhLGGGOMMcYYY4wxAICJ2AEwxhomLy8PEyZMQEpKCiQSCdauXYt27dph1KhRuHXr\nFjw9PREXF4dWrVqJHSpjjDHWBNTdd0I893fAGGPNFt9JwlgT9+abb2LQoEG4dOkSzp8/j/bt2yM6\nOhr9+vXD5cuX0adPH0RHR4sdJmOMMcYYY4wZPG4kYawJy8/Px9GjRzFu3DgAgImJCWxsbJCQkICo\nqCgAQFRUFOLjdTe6BWOMMcYYY4w1V9xIwlgTduPGDTg6OmLs2LHo1KkTJk6ciKKiImRlZcHZ2RkA\n4OzsjKysLJEjZYwxxhhjjDHDx40kjDVhpaWlOH36NKZMmYLTp0/DwsKiyqM1EokEEolEpAgZY4wx\nxhhjrOngjlsZa8JkMhlkMhm6dOkCABgxYgQWLlwIFxcX3LlzBy4uLsjMzISTk1ONZXwUFyf8HSyX\nI1gub/S4GauvlJQLSEm50Chljxs3Djt37oSTkxP+/PPPKtMPHz6MYcOGoW3btgCA0NBQzJ49u1Fi\nYYwxxhhj4uBGEsaaMBcXF7i7u+Py5cvw9fXF/v37IZfLIZfLERMTg5kzZyImJgYhISE1ljE3LEyP\nETPWMHJ5B8jlHYTXW7Zs1lnZY8eOxdSpUzFmzJga5wkODkZCQoLO6mSMMcYYY4aFG0kYa+K+/PJL\nvPTSS1AqlfD29sbatWuhVqsRFhaG1atXC0MAM8Zq17NnT9y8ebPWeYhIP8EwxhhjjDFRcCMJY02c\nv78//vjjjyrv79+/X4RoGGu+JBIJjh07Bn9/f7i5uWHJkiXw8/MTOyzGGGOMMaZD3EjCGGOMaaFT\np05ITU2Fubk5du3ahZCQEFy+fFnssBhjjDHGmA5xIwljjDGmBSsrK+HvgQMHYsqUKcjJyYGdnV2V\neblDZNaUpKQkISUlSewwGGOMMYPAjSSMMcaYFrKysuDk5ASJRILk5GQQUbUNJAB3iMyaFrk8GHJ5\nsPB6y5ZPRIyGMcYYExc3kjDGGGMAIiIikJSUhOzsbLi7u2P+/PlQqVQAgEmTJmHLli1YtWoVTExM\nYG5ujtjYWJEjZowxxhhjusaNJIwxxhiATZs21Tr99ddfx+uvv66naBhjjDHGmBiMxA6AMcYYY4wx\nxhhjzBBwIwljjDHGGGOMMcYYGvFxG7VajaCgIMhkMmzfvh05OTkYNWoUbt26BU9PT8TFxaFVq1YA\ngIULF2LNmjUwNjbGihUr0L9//8YKizH2iEKgqnOeeITosMadOixLnwaLHUA19L0uDXEdMMb0TYxz\nQN0ehxgzPHxtxZj+NNqdJMuXL4efnx8kEgkAIDo6Gv369cPly5fRp08fREdHAwAuXryIzZs34+LF\ni9i9ezemTJkCjUbTWGExxhhjjLFGxOeAjOke5xVj+tMojSRpaWlITEzEhAkTQEQAgISEBERFRQEA\noqKiEB8fDwDYtm0bIiIiIJVK4enpCR8fHyQnJzdGWIwxxhhjrBHxOSBjusd5xZh+NUojyfTp0/HZ\nZ5/ByOjf4rOysuDs7AwAcHZ2RlZWFgAgIyMDMplMmE8mkyE9Pb0xwmKMMcYYY42IzwEZ0z3OK8b0\nS+eNJDt27ICTkxMCAwOFls7KJBKJcKtYTdMZY4wxxljTweeAjOke5xVj+qfzjluPHTuGhIQEJCYm\noqSkBAUFBYiMjISzszPu3LkDFxcXZGZmwsnJCQDg5uaG1NRU4fNpaWlwc3Ortuy4uFjhb7m8A+Ty\nDroOnzGdSUlJQkpKkthhMMYYY3rB54CMlUlJuYCUlAs6KatR8yo2Tvhb3kEOeQe5TmJmrDHoMq/q\nIqGamiR1ICkpCUuWLMH27dsxY8YM2NvbY+bMmYiOjkZeXh6io6Nx8eJFjB49GsnJyUhPT0ffvn1x\n9erVKi2eEokEcXG/1FGjIY6s0FRH6jBU2nzHhjmiR1iYaY2/AIhFIpFAGRdX94x14NFtAN7/AGKs\ng6aYV/oehSME8TorKx5SnZWlf4aYo4ZJF3nV/M8Bm+qxiokhLGy4To5VOs+rX+o4B1Rpc7zSNhc4\nR5lu6SqvqtNoQwCXK0/I9957D2FhYVi9erUwTBUA+Pn5ISwsDH5+fjAxMcHXX3/Nt4Qx9og8PT1h\nbW0NY2NjSKVSJCcn1zo0HGOMMdbY+ByQMd3jvGKs8TXqnSS6ZJi/Ihii5v/LcVPVmL94e3l54dSp\nU7CzsxPemzFjBhwcHDBjxgwsWrQIubm5wvBw5fhOEl0yxFxo/vsDvpOkbnwnSTlDzFHDZGh51bTP\nAZvqMY3pUmP+4l1ffCcJa+qa9J0krHEQEQ4dWoeTJ3egVSsXjBjxAezsWosdFhNR5Z1EQkICkpLK\n+kSJiopCr169qjSSGIpff92Mo0c3wtzcGqGhz0Amcxc7JMYYY4wxxpiWNBoN9uxJxPnzf8LJyREj\nR46CpaWV2GHVCzeSNFFxcR9hx47lUCjUMDIyQnJyPD7//BysrcWOjIlBIpGgb9++MDY2xqRJkzBx\n4sQah4YzNHv2fIMffpgFhUIDiQQ4dSoBixcvhYuLq9ihMcYYY4wxxrTwf//3LY4ePQqFAjA2Bk6e\n/ANLly5Hy5YtxQ7tkXEjSRO1ffsXUCqNAZhCowFKShRITo5H3758Yfk4+u233+Dq6oq7d++iX79+\naN++fYXptQ0N99FDjwUEy+UIluu3Z/P4+M+gUACAKYgAhUKBw4cPIjz8Jb3GwZoGHjWKMcYYY8yw\nqFQqHDy4HxqNJQAJ1Grg/v1inD9/Fl27Pi12eI+MG0maKI1GDcBYeE1EUKtLxQuIicrVtaxxzNHR\nEcOHD0dycnKNQ8NVNjcsTJ+hVlG2Lf/bgENUdrseY9WRy4MhlwcLr7ds+UTEaBhjjDHGGFH15+5q\ntVrPkeiGkdgBsPoJDn4JpqYAUApACRMTCTp3NtROy1hjKi4uxv379wEARUVF2Lt3Lzp27IihQ4ci\nJiYGABATE4OQEP12Fqmt559/DS1aAIAKgBItWgA9ewbX8SnGGGOMMcaYITA1bYHAwM6QSksBlEIi\nKbs+7djxKbFDqxe+k6SJmjDhK9jYOOPkyZ2wsXFEVNRncHBwB3Be7NAeW7dv/4kvv5yK7Oxb8PIK\nxH//+zVatXJp9HqzsrIwfPhwAEBpaSleeukl9O/fH0FBQdUODWdoQkJmoGVLKxw58gPMzKwxevQA\nuLt7iB0WY4wxAzJu3Gvw938KkyaNbZLPtzNmiCZEvQkTEylGjhqEPv2fEzsc1sRNn/4OfvxxAy5c\n+BOOjo4YO3Y8d9zK9MvY2ATh4fMRHj5f7FAYgMLCHMyb9wKKimYBCMalS2sxf34Ili49BiOjxr1h\ny8vLC2fPnq3yvp2dHfbv39+odeuCRCLBwIFTMHDglH/e4SHbGGOMVVRYuBvJyfOgUn2Hd975r9jh\nMNYsFBT8AqAAa9eMhY2tNYK6BIkdEmvCTE1NMXbseLHD0AluJGFMB65cSQbREwDGAADU6nm4e9cX\neXmZsLNzEze4ZokfLdMOrydtjRs3Djt37oSTkxP+/PPPauf573//i127dsHc3Bzr1q1DYGCgnqNk\n7HHmCZVqGc6c6SB2IIw1I2Ud/SsV03Hs6B5uJGHsH9xIwpgOmJlZQaPJRFkfMSYAcqFWF6NFCwuR\nI2OMaWPs2LGYOnUqxowZU+30xMREXL16FVeuXMGJEyfw2muv4fjx4zWWZ6qDDpFNTMzg4CBDScl9\nqNWleOKJZxEQ0A82Ng7IyroBd3c/yOXBMDU106o8IsJf6elQlpbCTyaD1KTxTwHu3MlEcXExZDJ3\nmJZ1pNUs5eXdQXZ2GlxcvGFpaSt2OM1YKqRS7bZ3xpj2jIxuw8KyhdhhMGYwuJGEMR3w9e0Ob29v\nXL0aCoXiWbRoEY8+fV6DhUUrsUNjjGmhZ8+euHnzZo3TExISEBUVBQDo1q0b8vLykJWVBWdn52rn\nNwPgAuAOAA0ABfDvIE4kASADcA9A8b8fEqYDQAuUljrhzp00lDW+qnDyZDxOnowHYPrPP1uYmSkQ\nHX0Irq7tal0+hUqFUQsW4PzVq2gpkcDKzg47PvoIjtbWtX6uvjQaDVauXIETJ47D2NgELVqY4qOP\nPoWLS/Mbpn7v3v9DTMwHMDHxgEaThrfeWovAwOfFDqsZWgRT07UYMyZc7EAYazYkkvmQGOXBrGUC\nhoZ8JHY4jBkMHt2GMR0wMjLCBx/8hKioURg6VInXX5+NqKhPxQ6LMaYj6enpcHd3F17LZDKkpaXV\nOP9ZAGcArEPZYO3GAGAJwAqAiRRAPwALyt5sgbKfLKz++ScFgM4Azv1TkiVggbIjtgQAWgH4C8Cf\nePBgGj7/fEKd8S/fvh2aK1dwRqHAHyUleDorCzP/7/+0XwGP6NixX5Gc/AeUyhZ48MAE+fkKLF/+\nRaPVJ5asrOtYv34OVKqDePAgCQrFRnz++StQKh+IHVqzM2zYFbz33hQ891wfsUNhrNl4cUQqRo56\ngCXLPoGjk6PY4TBmMPhOEsZ0xMREir59675YYYw1TURU4bVEIqlhTqD8/pIBKLsPxAiAGihr5DBV\nAqV/AvgQwDtlt5pI8e+dJKYAVDkPldQd0CSWzVMKQO2BshYXAAhFZuaSOmO/dOMGBiuVZe0vAIar\n1Zh161adn6uv1NRUKBRq/NPiAyJjZGSkN1p9YsnMvAITk6egVHr98043AJbIycmAi4u3mKE1Oy+9\n9JLYITDW7Iwa3fBHQxlrjriRhDHGGKuDm5sbUlNThddpaWlwc6u5U+bZKLv54xrK2j7U5RMIgNIU\nQEcAvwBoCRgVAipAaMFQAYDdPy/+BvB7WSGqfz6P2wAKUdZQshWurk/UGf+TXl5IPHMG4UolTADE\nGxvjyTZt6vxcfbm7u6NFC2MoFARAAolEjdatm18n1q6u7VBaeh7ATQCeAJIBFMHOrrWYYT2ylJQk\npKQkiR0GY4wxZhC4kYQxxpjBys6+jbi4xcjPz0WXLn3Qp8/YWu/gaCxDhw7FV199hfDwcBw/fhyt\nWrWqsT8SAFiDsj5JMv95rQbK2jUAgEoB7AcQC6D4nw5LANwvnw4ApwAEAMgCUFqh6xIgD8CTKOuT\npATTpx+sM/43hwzBb3/+iU5Xr8JMIoG5rS12Tmi8O9969HgWp0+fQnLyiX/6JGmBN9+c3mj1icXZ\nuS0iIz/C+vW9YWLSBhpNKt56a63WnekaCrk8GHJ5sPB6y5ZPRIyGMcYYExc3kjDGGDNIeXlZmDEj\nGMXFEdBognDx4grk5NxBWNj7Oq8rIiICSUlJyM7Ohru7O+bPnw+VSgUAmDRpEgYNGoTExET4+PjA\nwsICa9eurbW8YgDXK78pPK2jQdndIDVNBwAFjI0zYWcng1JZCLVaBV/fHggMHPDP6DbX4e4uh1ze\nCy1amNe5fC2kUvwyZw7+ysiAsrQU8kYe3cbIyAhTp05DVtadf0a3kcHUtHmOnDBgwER07foC7t0r\nH93Gru4PMcYYY8xgcSMJq8VgsQNgjyXe7liZ48e3QqF4FhrNbACAQtEVO3b0bZRGkk2bNtU5z1df\nfaV1ecq4uBqnxSNE63J0ycjICH4ymd7qk0gkzXI0m+rY2rrC1vbxWNbHw06xA2CMMSYiHt2GMcaY\nQdJo1Cgb+qWcKTSaUrHCYYwxxhhjjwFuJGGMMWaQunYdChOT3QC+AXAQpqbj8dxzr4gcFWOMMcYY\na864kYQxxphBcnDwwCef7EFAQDK8vJYjJGQQXnllodhhMcYYY4yxZoz7JGGMMWaw3N3leP/9WLHD\nYIwxxhhjjwm+k4SxZkCtViMwMBBDhgwBAOTk5KBfv37w9fVF//79kZeXJ3KEjDHGGGOMMWb4dN5I\nUlJSgm7duiEgIAB+fn6YNWsWgNov2hYuXIh27dqhffv22Lt3r65DYqzZW758Ofz8/CCRSAAA0dHR\n6NevHy5fvow+ffogOjpa5AgZY4w9Dvg8kDHd47xiTL903kjSsmVLHDp0CGfPnsX58+dx6NAh/Prr\nrzVetF28eBGbN2/GxYsXsXv3bkyZMgUajUbXYTEDU1iYi+PHf0ZycjxKSgrFDqdJS0tLQ2JiIiZM\nmAAiAgAkJCQgKioKABAVFYX4+HgxQ2SMMfaYaKzzwJSUC/j11yPIyEjX9yIxJjp9Xl9du3oNR5OO\n4vq16425SIwZtEbpk8Tc3BwAoFQqoVarYWtri4SEBCQlJQEou2jr1asXoqOjsW3bNkREREAqlcLT\n0xM+Pj5ITk7G008/3RihNdixYz8hIeFzAMDQoW+jR48RIkfUmHbqqJzBFV7dvXsLs2b1gUrVHkQK\nWFrOQXT0QVjb/1Z3UaoQLerTVdzaGlz3LI1o+vTp+Oyzz1BQUCC8l5WVBWdnZwCAs7MzsrKyxAqP\nMcbYY6YxzgOjo9dCIpFDo1mH11+fgO7de1SqVdtjv/6P2SdPJuPnn7dArVZj0KDB6NXrOb3HwJo+\nfVxf/RS7DdviD8BI0hUaikPoi4Thw99u9GXTN41GjZ9/3oLjx3+HpaUVoqJeQdu23mKHxQxIo/RJ\notFoEBAQAGdnZ/Tu3RtyubzGi7aMjAzIZDLhszKZDOnphvkrwfHjv+Drr1/F9euXcP36JXz99UQk\nJ28TO6wmZ926OSgsfAkPHsShpGQbcnODERfHj4PUx44dO+Dk5ITAwEDhLpLKJBKJ8BgOY4wx1tga\n4zxQofgVJSUboFRuw8qVq5rMXcdnz57BsmWf49q1dNy8eQerV3+PI0cOix0Wa4Ia+/oq+2424rfu\nhFKRhJKS9VAqDmPLlsXIyclovIUSyfr1MUhISEBqajYuXbqGefNmIzOz+S0nq79GuZPEyMgIZ8+e\nRX5+PgYMGIBDhw5VmF7XRZuhXtDt2bMKSqUGgCmAspbc3btXoWvXYeIG1sTcvZsBjSZceK1Wd0NW\nlr7v/mgejh07hoSEBCQmJqKkpAQFBQWIjIyEs7Mz7ty5AxcXF2RmZsLJyanGMj6KixP+DpbLESyX\n6yN0xuolJSUJKSlJYofBGKtF45wHmv/zf0eUlpZCoVDAzMxMd0E3kn379kCpNAIgBQAoFCrs2pWI\n//ynl6hxsaansa+vcnJyYCKVQaVy/ucdV5iYuCEvLwt2dq0bGr5BOXz4ABQKY5TfL1BaqkRy8gkM\nGzZc3MCYwWjUIYBtbGwwePBgnDp1qsaLNjc3N6SmpgqfSUtLg5ubW7XlxcX9OwykXN4BcnmHxgy/\nChMT0yrvSaVV32O169ChOzIyvoVS2Q2ACi1arEHHjs2voUkfF3MLFizAggULAABJSUlYsmQJNmzY\ngBkzZiAmJgYzZ85ETEwMQkJqfkxpblhYo8bImC7J5cGQy4OF11u2fCJiNIyx2uj2PHA6ACcAp2Bl\nZdMkGkgAwMTEBMDDd3oSpFKpWOEwPUlJuYCUlAuNUrYu8you9t8fyry9vQFKB3AAQB8AewD8DVdX\nn0ZZDjEZGRnj4byUSCQwNuZBXw1dY+ZVZTrfGrKzs4WelR88eIB9+/YhMDAQQ4cORUxMDABUuGgb\nOnQoYmNjoVQqcePGDVy5cgVdu3attuywsHDhn74bSABg+PCZMDWVAFAAUMDUVIKQkBl6j6Opi4iY\nDX9/axgZecHIqB2eftoPL7wwVeywdE4uD0ZY2Fzhnz6U/0rw3nvvYd++ffD19cXBgwfx3nvv6aV+\nxhhjj7fGOg+USuNgbLwCjo5X8dFH+jmm6sKQIcPQogXh33NHDUJDR4odFmtkcnmHCtctDdVYeRUW\nHib869ylM96bPQ0WFq/C2NgVlpav4/33f4KZmVWD4zc0w4eHwtS0FIASRkZKtGxpjGee6Sl2WKwO\nus6r2uj8TpLMzExERUVBo9FAo9EgMjISffr0QWBgIMLCwrB69Wp4enoi7p9b/P38/BAWFgY/Pz+Y\nmJjg66+/NtjHbfz8emLOnF3YtassxoEDp8DX1zA7mDVkUmkLvPvuBigUxZBIjGBq2lLskJqF4OBg\nBAeX/cJuZ2eH/fv3ixwRY4yxx01jnQdu2BCDkpISmJmZG+x5YnV8fNrhww8/wc6d26HRaNCv3wBR\nfuhjTZu+rq+e9HsSazZ8jeLiYpibm0NS2r2xF00UQ4YMQ6tWrXDixHFYW1vjxRdHwNbWTuywmAGR\nUE29PRoYiUSCuLhf6phL3FFGDIMh9u2h5fci1WKY2iY8uk1YmGmNnauKRSKRQPlQnyT1FQ9tvhfG\ndK8p5pW+8yUEuhsCPB5N+TEBPkfQlqHllXbngNrSZjswxHMp1pSFhQ03qJwC/smrX+o4B9Tpebe+\n98Gcx81dY+ZVo/ZJwhhr+ogI3+07gDUHTsC8hSnmhw/Gf/z8xA6LMcYYY4wxxnSOG0mYHmjZkqvS\n5hdKbhXWt68S92BO7FEUKxYAuIchC97DgQ9nIMin+XXkxViTo8UdePFa7VuBEKh0Mo/2d8rod3+u\nqztq4rW9mUbL9a5ffDcNn0cwJhZtco/3UcwwcCMJY6xWK3cfRbFiBYCy51IfKDMQc+g3biRhjDHG\nGGOMNTs81hFjrFYmRkYo65W/3ANITYzFCoexRrN79260b98e7dq1w6JFi6pMP3z4MGxsbBAYGIjA\nwEB88gkPP8yYvhQXF4sdAmPNjkajETsExgwSN5Iwxmr1wYgBMDN9DcB6SPAFLFp8j4n9eokdFmM6\npVar8cYbb2D37t24ePEiNm3ahEuXLlWZLzg4GGfOnMGZM2cwe/ZsESJl7PE0fsIYrFy5gi/qGNOh\nyRMm4/at22KHwZjB4UYSxlitIno+ix+nRWJI0FaEP3sMRz+djSdlMrHDYkynkpOT4ePjA09PT0il\nUoSHh2Pbtm1V5jO00QkYe1yozdU4nnwMe/Ykih0KY81GXkkePv3oUz62MVYJN5Iwxur0QlAQfp4x\nBTH/nYgOHh5ih8OYzqWnp8Pd3V14LZPJkJ6eXmEeiUSCY8eOwd/fH4MGDcLFixf1HSZjjy8JoIAC\nl/6qeocXY6yeTIGCggJ+nI2xSrjjVsYYY489iURS5zydOnVCamoqzM3NsWvXLoSEhODy5ct6iI4x\nBgKkEilcXVzFjoSx5qMUMDY2hpmZmdiRMGZQuJGEMS0RkVYXUoyxpsfNzQ2pqanC69TUVMgqPVZm\nZWUl/D1w4EBMmTIFOTk5sLOzq1LeR3Fxwt/BcjmC5fJGiJox3UhJSUJKSpLYYdSqpbolHOwdERIS\nqtX8fMwoSuNFAAAgAElEQVRmrG6mpab477T/wshIu4cLyh/L4dxizR03kjQ7uhxfXJvxzHVIqqp7\nHpW08eOo5OzZ01i58ksUFOTD3d0DM2bMgpOT80Nz6Hk9McZ0LigoCFeuXMHNmzfRunVrbN68GZs2\nbaowT1ZWFpyc/p+9+46OonobOP6dbekBAqRAgNBLIASQIr0YEFFE8RdEmvQqolRRqghBxAIoLwoI\nNhBRAaVIB0WKUgRC70kgCSGkJzu7O/P+sSEQSCCE3WwC93OOR3b2zswzm0z23mdu8UaSJA4cOICq\nqjkmSAAmh4YWRNiCYBOBga0IDGyV9Xr16sK3ctPbb46lQoUAnJ2d71suIuIKc+aEERMTTcmSpRgz\nZjyVKlW+o0Re6knie114Msya+RHe3t4PrF+bzSa++mo4f/75AxqNluefH0W3blMfMlliyzaKINhX\nkUqShIa+hKdncWbNmk3p0t6ODkd4zJlMJmbPnsnRo0cAV8CDiIhYpk2bzPz5C/OcdRcEofDT6XQs\nWLCADh06YLFY6N+/PzVr1mTRokUADB48mNWrV7Nw4UJ0Oh2urq6sXLnSwVELwpNj5sz3AQlPT0/e\ne28KAQEV7ykjyzJTp04iOdkEeBAXl8L06VP44otFuLq6FXjMglDYjR49EknS0KJFC4YNewONRptj\nuVWrprFnz8+YzU4ArF8/H2/vANq27VuQ4QpCgSlirTwPkpJSGT9+jKMDEZ4AK1Z8nzkxow7QAxKq\nqichIYGkpEQHRycIgq117NiR06dPc+7cOd555x3AmhwZPHgwAMOHD+f48eMcOXKEv//+myZNmjgy\nXEF4wrgBniQlybz//lQsFss9JaKjr2EymQEDIGX9/8oVscSpIOTME1V1Z+/eA/z227pcSx08uAFZ\nVrA2HTUYjRb+/Vf0uBIeX0UsSaIBXEhJSUZRFEcHI9iI0WgkKSmp0C0/Fh5+HLNZAhTgVmwqqqrg\n6urqwMgEQRAE4Ulzq/OzAaNR5ubN+HtKeHh4YDabsH5vA6iYzSY8PT0LKkhBKGIkQMJkguPHj6Gq\nKikpyWRkpGcrVby4D7fvK9BqNZQoISZRFh5fRSxJAtYbVHqihjrIcgaynOHoMOzihxXf8frrPRgy\ntD9j3x5LYkLh6aFxa+4B0AIpQBoaTTrdu/fEYHBycHRWGRkZNG7cmODgYGrVqpX19Ds+Pp6QkBCq\nVatG+/btSUhIcHCkgiAIgvAobj2wsKCqFjw87k18lCjhRadOz+PkZEavN+HkZKJly9aUKVO2wKMV\nhKJEo1EpWbIkU6e9x6BB/ejbtxcLFy4gJcVaf+zTZw4uLnr0egWDQcXNzY1XXpno4KgFwX6K1Jwk\nkA6YaNu2naMDKRAWi5kFC4axd6918sAmTboxYsRCdLqCn7zUHg4c2M/GTb9jcbWABFExUcz/dD7v\nTX3P0aEB0KdPP06dGktGhglFsWAwaBkxYhQNGjzl6NCyODs7s2PHDlxdXTGbzTRv3py//vqLdevW\nERISwrhx45g9ezZhYWGEhYU5OlxBEARByCcj1qfeRvr3H46TU84PK3r06E1QUDAREZfx8ytDcHD9\nAo1SEIqWFAC8vLzIyEjn3KWzmF3NIEvs2LGLnTvL4edXi/fe+4m5cw9z6NBGtFodjRq9iIdHSQfH\nLgj2U6SSJHXq1KRx48a0b9/R0aEUiF9++Yh//rmEopwHJP79tyc//zyHbt0ej8zt2bOnMSrGrP5M\nFp2Fc+fOOTaoO5QqVYrPPlvA8ePHkCSJOnXqPnBWfUe4NfRHlmUsFgslSpRg3bp17NplXc6xT58+\ntG7dWiRJBEEQhCIsFtgNhFKnTt37lqxTJ4g6dYIKJCpBKMrq169Hq1ZtqFevPuPGv4VJMlk7bWW4\nA9tR1Spcu/YxYWE9+OijP2nffpCjQxaEAlGkkiSTJk11dAgF6tixvcjyAMAdAFkeyLFjy+nWzbFx\n2Urp0t4YtAZkVbY+HLJAyZIlHbLMb25cXd1o1KhwT86oKAr169fn/PnzDB06lMDAQGJiYvDxsS5T\n7OPjQ0xMjIOjFARBEIRH1RKoRGxsDKVLl3Z0MIJQ5E2Y8G7Wv71L+xCTEIuqKkBHoCoAqjqSiIiZ\nKIryRE13IDzZxG96IebtXQat9p+s1xrNP3h7Pz7jatu2bUfF8pVwNjvjorjiggvDh7/p6LCKHI1G\nw5EjR4iMjGT37t3s2LEj2/uSJD3kOvaCIAiCUBjdQKe7hpeXl6MDEYTHzoABg3HXu2PAABwC5Mx3\n/sHNzUckSIQnSpHqSfKk6dFjMseOtSE9/Rgg4ex8gZ49dzxwv6JCp9MzbeoMwsPDSU9Po1q1GhQv\nXtzRYRVZxYoVo1OnThw8eBAfHx+io6Px9fXl2rVreHt757rf9FWrsv7dKjCQVoGBBRGuIORLePgu\nwsN3OToMQRAKmF7fA0k6RMeOHfDzK+PocAThsePr68dnn37OyZPh/PLLBiIjmyNJgSjKbkaMWOro\n8AShQIkkSSFWooQfn3xygKNHtwIqQUHP4OpazNFh2ZRGoxXjhh9BXFwcOp2O4sWLk56ezpYtW5gy\nZQqdO3dm+fLljB8/nuXLl9OlS5dcjzE5NLQAIxaERxMY2IrAwFZZr1evnuHAaARBKCiDB1fBz68l\nVatWc3QogvDYcnd3p2HDxjRo0JDjx4+SmFiRqlVn4utb2dGhCUKBEkmSQs7V1ZMmTV52dBhCIXXt\n2jX69OmDoigoikKvXr1o164d9erVIzQ0lCVLlhAQEMCqO3qLCIIgCEJR07Jla0eHIAhPDI1GQ1BQ\nMNDJ0aEIgkOIJIkgFGF16tTh0KFD92z38vJi69atDohIEARBEARBEASh6LL5DDwRERG0adOGwMBA\nateuzbx58wCIj48nJCSEatWq0b59exISErL2mTVrFlWrVqVGjRps3rzZ1iEJjzFVVUlJScZsNjs6\nFEEQBEF44ol6oO2ZzSZSUpJRVdXRoQgOIu6rokNVVZKTk1AUi6NDER6BzZMker2eTz75hPDwcPbt\n28fnn3/OyZMnCQsLIyQkhDNnztCuXTvCwsIAOHHiBD/++CMnTpxg06ZNDBs2DEVRbB2W8BiKjY1h\n5MhhDBrUj969u7N1q/gCEARBEARHEvVA29q4cT29er3GoEH9eOutN4iLi3N0SIIDiPuqaLh06SKD\nBvVj8OD+9O7dgwMH9js6JCGfbD7cxtfXF19fX8A6+U/NmjWJiopi3bp17NplXZGgT58+tG7dmrCw\nMNauXUv37t3R6/UEBARQpUoVDhw4QJMmTWwdmlAAtm3bwsaNG9BqtXTt+j8aNWpst3PNmvUBsbGJ\nqKoroLBs2VIqVapMpUoFPbnU4zVeMz4lhfUHD6KqKh3r12ePZ29HhyQIgiAUEY6uB5rNJr7//lsO\nHz5MiRLF6dt3AOXLV3jIozz4e70La/J0pDXoH/Lct506dZLvv/8Oi8UFkIiOjmfOnDBmz/4o38cU\niiZH31d5sXfvHn799RdUVaVTp+dp3bqt3c5VGFksFmbMmEZSkgy4AWbmzfuETz6ZR+nSua8yKRRO\ndl3w+tKlSxw+fJjGjRsTExODj48PAD4+PsTExABw9epV/P39s/bx9/cnKirKnmEJdrJ9+1aWLVvK\nlSuxXLx4jXnzPuG//47Y5VyKYiEqKhJV1QMSoAX0nD9/zi7ne1JE3rhBo1Gj+HXxYn5bsoRGo0YR\nG3vJ0WEJgiAIRZAj6oFffLGALVu2cfXqTcLDzzNp0kRu3CiavS/OnTuLomiwVtclFEXP5cuXHByV\n4GiFsX118OA/fP75fC5diuby5RgWL/6Kv/7abbfzFUYJCTfJyMgADJlbdOh0Bi5fvuzIsIR8stvE\nrSkpKXTt2pXPPvsMDw+PbO9JkoQkSbnum9t7q1atzPp3YGBtAgNr2yZYwSb++OMPjEYNZD41kWWV\nLVv+oG7d4HwdT5aNXL16FXd3d0qVKp3tPY1Gi5ubG6mpFqy/xioajULJkiUf7SJsKDx8F+Hhuxwd\nxkP5YMUK/peSwqTMLpkfmkz8/O0Eho5e+YA9BUEQBOE2W9cD81IHVBSFvXv3YLG4YX2AAhaLmcOH\nD/HMM+3zeSXZxcdHkZgYS4pfBu7OzjY5Zm5KlSqFVgtms4r1esx4enra9ZyCbYSHHyc8/LjNj+uI\n+yovNm/+A1m+sw1gYtOmjTRv3jJfx3sYspzB1auncXX1xNu7ot3PlxsPDw9UVQEsWB/eqlgspkLV\nNinq7HVf5cQuSRKTyUTXrl3p1asXXbp0AazZzejoaHx9fbl27Rre3tZuR2XLliUiIiJr38jISMqW\nLZvjcUNDX7VHuE+cEyf+5KuvxpOcfIO6ddsyaNBcnJxcH/m4er01WXGbil6fv26mkZERTJnyAWZz\nMczmWJ55pi2vv94z2x/4kSNH8fHHc9BoNCiKmaCgutSr1+DRLsKGAgNbERjYKuv16tUzHBhN3sTe\nuEHLO8as1lUUNsVHOjAiQRAEoaixRz3wzz8P0qtXVxo1yn24gLWRqMFaF5Eyt4FOZ5vq7qpVs1i7\n9lN0ujLMkqLZOGkMDSrbb4hvo0ZN2L59G6dOnUKStCiKwsiRo+x2PsF27k44rF794yMf0x731a22\nVWxsLAsWLObq1YX4+/szYsSAex5Q3o+1vn93G8CQW3GbiY29yOTJnUhP12Gx3KBJk84MH/7FfZNF\n9mIwODFw4BAWL/4SrVZCUUy0adOOihUrFXgsjyt73Fe5sflwG1VV6d+/P7Vq1WLUqNt/yDt37szy\n5csBWL58edbN3blzZ1auXIksy1y8eJGzZ8/SqFEjW4clZLp69QyzZnUjKuoNkpJWsW/fDebPH2KT\nY7/ySigGgwIYASNOTtC5c5d8HevDD+eRnDyB9PQDmExH2L79KIcPZ1/qtl69Bsyd+xmDBw9iwoSJ\njB49ziF/FB8nLerV4wsnJ+KBBGCBwUCN4GcdHZYgCIJQRNirHhgTM4d585Zw6tSJXM8tSRIvvPAi\nTk5mQEarlXF1daJhw0efH+306b389tsSTKb9pKfvISFtLi/Nnp9r+etJSSzZupXNmzcRHx+fr3Nq\nNBomTHiXsWPHM3jwYD7++DNq1w7K7yUIRZg921eyLDN58vucOfMsSUm/cepUOyZNmoHJZMpzfF26\nvISTk8qtNoDBoNC16yv5vt68+vTTIdy82Zv09H3I8mH27z/Enj0P1/s5MjKCjRvXs3v3TmRZfqR4\nWrduS1jYHAYPHsSkSVPp12/AIx1PcByb9yTZs2cP3333HUFBQdSrVw+wLkE1YcIEQkNDWbJkCQEB\nAaxatQqAWrVqERoaSq1atdDpdHzxRe7Zv927d1KtWnV8ff1sHfYT47//tqAoLwAvAmAyfcrBg7Vs\ncuzg4HpMnDiJrVs3o9Xq6NTpeQICcu72JstGdu7cQWJiInXq1KFGjdsxXL0aRXT0JeDWH9fimM3P\nEBl5hfr1s/cU8fb2wdvbxybxCzDy+eeJiI2l1rZtqKpKn6ZNafPyBFJSbvL55yM4depvihXzYdiw\nT6lWTUyuLAiCIGRnv3pgG2R5CPv2/ZOtznC3V199DV9fXw4fPkSJEl68/HJX3NzcHvm6IiNPAi2A\nWxMwvkhMYn+MJhNOd/WajYiLo9H4CaQbLZiBH374jpkzZ1OmTM49pe9Ho9FQp45IjDzp7HVfLV36\nFYGBtUlPd0NRRgOgKONJTV1FVFQkAQF5i69KlWpMm/YBGzasR1UV2rd/lurVa9jk2u/n6tWTqOqt\nZKU7RmMHIiJO5nn/I0cO89FHs1FVHRoNrF37K7NmfYjB4JTvmPz9y+HvXy7f+wuFg82TJM2bN891\niamtW7fmuH3ixIlMnDjxgcdevHgJimJizJhxBAfXf6Q4n1ROTm5oNNF3bLmGweBus+PXqhVIrVqB\n9y0jy0YmTBhHbGwcJpPC2rW/0r//QNq0aQfAt99+AzgDa4GeQBKq+gdlynS3WZxCzjQaDXMHDGBO\nv35Zr79LSeb997sSEVEZs3kDqamHmTHjZT7+eB+lSpV3cMSCYDubNm1i1KhRWCwWBgwYwPjx4+8p\nM3LkSDZu3IirqyvLli3LqqwKgmBlz3ogRHDp0vn7lpAkiTZt2mXVKWylbNnqwCzgBlAS2EBpT+97\nEiQA01etIiHVhEWxDjcwmWS++WYZEya8a9OYhCeHve6rTZs28ccfG9FqSwEZWOvfaShKIs4POedO\npUqVGTFi5EPt86j8/Kpz4cJvqOpQIA0np62ULTs8z/t/+eVCZFnLrfkNY2Li2LlzB+3bi17UTzq7\nTdxqDxkZ1klwFiyYx+LFyxwdTpHUtOkr/PLLZ8THD8JsroHBsIzu3d8r0Bj27dvL9es3kGUdICHL\nFpYtW5pVoUlIuAmYgXHAXCCOYsU8aNDgqQKN80mm0VhH4i3bvothiwdgNqcCa7D+yaiAqv5GePgu\nWrXq5cgwBcFmLBYLI0aMYOvWrZQtW5aGDRvSuXNnatasmVVmw4YNnDt3jrNnz7J//36GDh3Kvn37\ncjyeITTUpvFpNHoqVKhD1aoNKVWqAu7uJbh5Mxqt/jQZcgbOBmd8/XwJCg7C3d0do9FIVEQUJrMJ\nv9Ll8PQslq/zmi0WwiMiiEtKom5AAKUyJ41UVZWLsbGoqkolHx8kSSJDlrkQG0uS53U8PbOPZU9J\nuUls7CVUVaF06fL3vH8nRbEQHR0NSMTGRpOWlkalSlXw8fHBYjFz+vRpJAlKlCiJqir4+vqi0Wgf\n+trSjEYuxsai02qxKAqVvL1xNtw7hj4lPZ0/T52ilIcHHi4uxLk7UapUqaz3ZaNMbGwsnsU87zup\nZkpKMjdv3sTb2wcnp/w/pcyNLBuJjo7GbDbj4uKCj49v1t/yu6mqSlzcFUwmI76+lfP1+RW8kcBP\nnDiRQXp6Oi4uLgV69ho1mvHssz3ZsKEROl159Fzm57Fv51j26s0ELHe0Z1VVIiEhoYAiFYSH4Y6q\nJqEo6Tg5vYjR+BxOTr9Tr15dfHx8HR3cA7355kImTXoOWf4Bi+U69eu3p3nzvD9UTUlJ4XZzWMJk\nUkhKSrRLrELRUqSSJFZaUlOSeVGV7+k2lrcV659szs7ufPjhTjZv/pKEhDiCgz8nOLhDjmW7kPex\niA8jKjUJSbk9qRpoMBnTs36m4Q3qMScyijSjBojB2WBhcpcOvCSZ83T8NeRvslghuwsxMby59HvM\n5i1AG+AaUA5QkaQoXFzEDPvC4+PAgQNUqVKFgMy+xa+++ipr167NliRZt24dffr0AaBx48YkJCRk\nW37xTu5YFwE0AqmA9elcMSABPSZMaHDGnLnFOhe+Gax/Fu+c+47igBFFKcbFi+FcvHg088iazMK6\nzLMomcdfRGj3F1i3ZgsZ6U7ATSRJpXv3ULp06fpQn8m1mzd55p13iIqPxxNIkiTe79mTAR068PwH\nM/n3vPWJflCFCnzYuxcvzZ6HbHYlwzyVV16ZwMsvjwFg+/avWbz4DcxmM9aVyHR06zaZl166dxWF\n5OQkpk2dRExMNEZZzrxOT0ChSpUArly5giwbgCSsEwOq+Pn5MWXKdDw88v43ad+ZM7wwcyYmo4xi\nMeOt06G4uLBm8mSCKlTIKrfj+HGemzETi6IACpIkodVpadS4ESPfGsmF8xf4YJr1fbPJRPeer/LC\niy/cc74//tjIN998jVarR6OReOed92zaFf3cuTPMmDGNjAwjimJBq9Xj7+/PlCnTcXfP3lvUYjEz\nd24f/vtvBxqNC97efkyduhYPj8K+AsMqrL8/GpKSEgs8SQLQo8cUQkL6kJgYy6Cy5yjmmvOk9883\nqM+eU6dJM1ozJQYDNGhQeCaWF4TbJECDoqTQp099rlw5REBAI1q3blsk5vnz9a3CggVHiIg4gaur\nB35+1R4q7naBgWz5LxzZrAcUnPUqQwJr0vyONpBoVzyZbD5xq32paDUmggMqFokbt7BydS1Gly5j\nef312bkmSOypTZ06SJIFMAEKBp2JNrVrZ/1MJ7z8Mr1aNcegy8BJb2Joh/YMe1Z0eytop6Oi0GuD\ngOrARKAzEIZe3x0fH6hfvyNJSXH88886jh7dhsWStySWIBRGUVFRlCt3ewyxv78/UVFRDywTGZnz\n6k9ngfPAq4ALEvA1cBrYjwVXXDEzP3PLEcADrPkOD6w5gaxvZyOwADgFHM4s4A48nXmG5ViTI0cz\njzaLVSvWk5E+P3OfA6iqM6tWreLcuTMP9Zm8+fnn3IiP5/8yj7RPVZm1YgXDv/qKf85dIl12Il12\n4r9LkTw342PiUz4gJeM/zOb9/PrrF5w5s5/o6PMsXToKs9mQGbsrimJm9epZnD17bzyLv1pE3NWr\nOMkynoAWCRgNnOPcuRhkeQxwBjgJlMZk0nL16nWWLPkqz9elKAovzgojMc2Cs8XMEeCo2czE5GR6\nzZ6dVU5VVTrP/BCLos/8zD1RVQ1myczBQwfZtmUbYTPCSE1VyEjXYzY78+OKVVy8cDHb+SIjI/j2\n2+WYTM5kZOhJS1MJC/sARbE81M8jN6qqMmvWB6SlmVAUCfDEYnEhMjKar79efE/5DRsWcPTodUym\n4xiNR7l6tS6LF4+zSSz2pQNknJwMlCxZ6oGl7cXbO4CqVRvlmiABGNKhA0M7hOCkz0CnS6dly+Z0\n7fq/AoxSEPIqA1ApXz6AZ55pT79+r9O27TO59kIrjJycXKlS5SnKlKn+0O3DZW+MoFVgNXSaVDxc\nLMzr34/mdzwcEZ5cRaoniVaTQo2y/qweN9bRoQiPoJa/Pz+NGc2QRV+SkJpKq8BAlr0xIut9rUbD\n/AEDmNe/P5Dzuu6C/VXy9cVkOQ5cBUYAWjSa6XTvPp327Qdx+fJRJk16FlUtiSSZKF++ItOnr8dg\neLgxrIJQGOT174yqZuvmket+t55x9wJWoQIdM7cEYKA+GezOmpraD2gJrNVyu4OdAWvdlXTg5cyN\nZYDmwH6ga2ahk8Cz3J5M8jXgLaBZ5usKQEPgL65cuUKVKtXydJ0ARy9dwog1PQpQHmisqvx77jwZ\nJrKCzTCpQCJwqxHoB7TiypXjeHn5odU6Y+3pAreqHZKk5cqVy1Stmj2eixcvIFnMd3wMFtI5lHmt\nKUCPzHdKZEa2BLNZx4UL95+n4k43UlJIk42AlrbArQ7l3YARcXGYLRZ0Wi0JqakYzTLWn+YdPxgl\nHaNi5MzpM6SmpmJNoABo0Eh6Iq5EULHS7UnLIyMj0Gpv9f4B0CPLaSQlJVO8ePE8x52btLQ00tLS\nMmPUZ8VqsWg4f/7ez+XcuePI8ktYezeBxdKNCxeKQr0qBRcXV6ZNm2GzJX3tRZIkZvXsycwePViD\nXtRjhELMiI+PH++882TOl1PM1ZX1776LqqriPhWyKdzfMneJ+uorvDw8HB1GkWQyGdm//1dSUxMI\nDGyFv7/9s6TJ6em4OTnlmI1uHxzMhYVf3Hd/8cfqwSIiIujduzexsbFIksSgQYMYOXIk8fHxdOvW\njcuXL2fNdv6wlfHqZcow6X8vMPWnFuh0VTGbz/Lmm9/SsGFnLBYzU6Z0wWxuDrQDVnHxYhRbtnxJ\np04FO2mXINhC2bJliYiIyHodERGBv7//fctERkZStmzOq1V8gLVJ/CdgXVDwb6ApcB0TR3ECtgIh\nWIfb7IXbeQQVbvf0NQDbsd5nCVgTJAB/AKFAJWAh1uEnnsBGrI36Y1hTL3HAYSRJxc+vTF4/DgCq\nlS3LjaQkdmce6QZwUJJoVq4cF2PiMZqtCSODTkKS3DGatgDts67Iz+91ihf3wWKxJiSsn4g58wIV\n/PzuXamubFl/Tl6PBUXJ/Bi0QGDmh+MObMCaKEkDtmBN3qqULet/z7Fy4+Xujl6rw2hS+QtreqcY\n1k+0fLFi6LTW+TmKubqi02oxW1Ruj4EygQYMGgMBFQP4Z/8/pKWZsVanFFTVjK9f9nH8vr5+WCwm\nrAkM62eg1WrxsFF9xsXFBYPBQHq6yRpfZtdwjUa553cYoHz5qvz77xZMpp5YP79NFCvmyapV020S\nj72MHTvBJkv52oqiKKTJMu73mdxSkiQkRF1GKLz69x+EVqt9ourcqqqSkZFhnZg287KfpOsX8qbo\n9KUCyg0YQKuxY7maz/Xmn1SynMF77zZn8aKhrPxmPO9MaMKRI3/Y7XynoqIIGjYM/7598evTh7UH\nDtjtXE86vV7PJ598Qnh4OPv27ePzzz/n5MmThIWFERISwpkzZ2jXrh1hYWH5Ov6YFzvx8cd/M3bs\n+yxYcJiGDa3PlM+e3Y8suwDfAf2Bn1HVGK5cOW2zaxOEgvTUU09x9uxZLl26hCzL/Pjjj3Tu3Dlb\nmc6dO/PNN98AsG/fPooXL57jfCRgvTN+xjqUxgjAy0g8jUQwEqmkY6AX1kEzQVgb6piA5Mz/skZi\nlMaaFHgaqJNZMh1r4iQIGIs1EVIbaAIMpsOzLdAbembuUw+NJo327TtQs+bDLff+2fDhuLi50R1r\nv5T6kkTf555j0ZDBVC1TGndnMx7OZip6l+Cn0cPwcB5MMdd2GAyNadv2JQIDW1G2bA1eeeVddDoZ\na0+QNLRaA888049ate6dk2TgoCG4enkhOzmRDJhRgW+A2vj6uqLVjgcaY02cRGAwqHh5uTFw4JA8\nX5dWo+HH0W/j5gSpOh11gNZ6PaNcXFg+ZkxWOY1Gw7cjRyBJGViTMtYfjEFjoFqVanTo2IEx48fg\n7GzB1dWCwWDk2ec6UK169t4xAQEV6dz5RQwGGVdXBScnC2+/PQ6t1jaTpWo0GsaMGY+TkwaNRgWS\n0ekyKFnSkwEDBt1T/oUX3qRixTScnRvj4tIaL6/fePvt5YSGTs76rzD6aE4YE8ePvqc3lyMc2L8G\n3969Kfv669QdPpzTV686OiRByJflS77k26Vf8fZbbxARccXR4djdhQvnGTWoH4P79mJo355sP3bM\n0UR6kcYAACAASURBVCEJhZSkFoZvmzyQJIkbwEyNhoOVKrF55sx7yqyhS8EHVgRs27aUb5e9jc6Y\nhoT1OZ6TVxn+7/8u3Xe/LvmYCldVVQKHDmV4fDyvYx1B/z+DgT1z51Ipl8aErRX8BEud8lQqNNRg\n98pdly5dGDFiBCNGjGDXrl34+PgQHR1N69atOXXq1D3lJUlCXrXqvsfM6b46enQbM2dOQFF2ZW5R\ngAD69XufZ58daoMrEYS8seV9tXHjxqwlgPv3788777zDokWLABg8eDAAI0aMYNOmTbi5ufH1119T\nv/69y9Hb64mUXu9G+fI1KVmyPO7uXiQnx6FqIpFlGYPWQOVqlWnarCl+ZfxISkzizOkzpKenUzmg\nOmXK5Nzj5U45TdadmpHBrvBwriUk0KJGDapl9pwxmc0cvngRVVWpV6kSBp2OG8nJhEdEcLx4V8qU\nqZ7tOLGxF7l8+TiKYqFcuZqZ76/PMQ5ZNnLx4kVk2UhERATJyUkEBQVTrVp1MjLSOXBgP6qq4u3t\ng16vp2LFihgMD14t5u7ri01M5FRUFBkmE856PbXLl8frrklOASJv3OD3f//F08UF/5IlOejpSoWA\nClm9JJMSk4iMiKSEVwn8ytzRO8aU/bsoOvoaN27cwN/fn2LFHn2Yzd2SkhK5cuUyqampFC9egooV\nK2G4Z7Ue6/eVoli4ePEIZrNMxYrBGAzZJ0EtiO+rhyFJEp5Y02yv9exN584vPcLR8vadnZvo6HNM\nHtOANXI6dYGlwJclS3L0iy9yvPfFpI8CQGjoS4XqngLrfXVr3TMZqFK7DpMm392jLC/3S85/y+/1\naPfew8selyzLvDWkP7NTUngZ2A30c3bmyPz5eBfLfQU4cQ8XXva8r4rUcBstMEZRKH/hghg79hAS\nE2NRTMY71pKB1JTbS9FFRp5kw4ZFyLJM27avUqtWy3yfKy45mRvJyfTNfF0faKLVcvjixQJLkjyp\nLl26xOHDh2ncuHG2FTd8fHyIiYmx6bmqVm2Eu/tNkpI+Ap4BFuPpWZL27Qfb9DyCUJA6duxIx44d\ns227lRy5ZcGCBXk61v2SjzZN6OtzTmZ7FvPkqUaZy6ab8l/Bc3N25rkcVuXQ63Q0qlo127aSHh60\nrFWLeKrfU97buyLe3hXv2Z4Tg8Epa+WXOnXqZo/HzT1rufhH5V2s2H0rxrf4lyzJkA63JzmPv+vj\n9CzmSa1iD+6l4+vrh6/vvUOMbMXTsxi1awflqaxGo6Vy5aK12oqEdRaV00ePQh6SJAkJCaxd+xsJ\nCSk0bBhE06bNHrhPXly4cIimWh3Bma/7A9MSE7mZmppjkk0QigIN2G2Z6qSkRNas+Y2bN9fSoEFb\nmjXr5pA2XFzcdVzM5qxZvloC1TQawiMi8vRdIDxZitRwG7D2TPBxcxMJkodQq1ZLVJ0BC9ZR1Wad\ngRo1rZWFyMgTvPNOO7ZuLcbu3ZWYOfM1Dh3akO9zFXN1xaSq3OqzkAqcUBTKlCjxqJch3EdKSgpd\nu3bls88+u2ecuyRJ+b5fZLOZRYve4vXXKzBoUC127/4BABcXD2bO3EKdOv9RsuQwGjVS+PTTfUVq\nNnRBEASh6JCx9oT1y2GelbulpCQzduxENm0qxZ49z7Jw4S+sWbPWJnGUKFGGE4pCWubrk4AqSXg6\nYEliQXhUCta2gUWvJ7jevT0jH1Vqaipjx05k48bi7NlTl0WLPuDnn+fY/Dx54enpyQ2zhVuDim4C\n581m/EQbRchBkepJMsDJma2qwpDhI4tM16e8DFmx9zChGjWa0q//PL7+ehSynEHNak14881vAVi/\nfhFG4yDAuvyfLPvz448fU7/+c/n7jHV6Xh80lOcWL6KFRsNRFao1eZroaoGsEZOX2YXJZKJr1670\n6tWLLl2sv0u3htn4+vpy7do1vL29c91/+h1PvFsFBtIqMDDr9djlK/nzzxRkeSNpaf+wcOFIzp07\nQGjoZLy9KzJp0s/2uzBByEF4+C7Cw3c9uKAgCI8VBfAqUYIur3R7YNm//95DenojLJYPATAaW/DL\nL+3p0uVF8j40IGc1aqhUbfQUrQ7sI0iS2K0oLBg0KGvCX0EoSlIAJInmTZ6me/ceDyr+0Pbv30ta\nWjAWy1wAjMY2rFnTgq5daxX4A293dw+69ehFuxXf0Uyj4R9V5fWQEGrkMgG78GQrUkmS0v0GMLV6\njTyNrRaya9OmD23a9EFRlGxP+2XZiHVFhFuKYTLJj3Sulq3bUrFyFS5evEC9UqWoWTNQ9PyxE1VV\n6d+/P7Vq1WLUqFFZ2zt37szy5csZP348y5cvz0qe5GRyaGiu7605cARZXgFcAyZgsbzMH38cZ8+e\nBsydu4/ixcUQKqFgBQa2IjCwVdbr1atnODAaQRAKytBRo6lfvwHOzg/usWE2m1DV7HUb6wpDj06S\nJAaMeBOvE62JvHGDSZUqUSsPvVsEoTCa+O4UateuY7OJpO9mMtnvXsyPZzu9QI3A2ly5cpmnfH0Z\nV62yw2IRCrcilSSx1TjkJ9ndwyHatHmV/ft7IcvlAE8kaRTx8UnMnfsqgwd3wd09f0sUlitXnnLl\nytsgYuF+9uzZw3fffUdQUBD16tUDYNasWUyYMIHQ0FCWLFmStQRwfni6uHDt5mVgPjAJWIKqmkhO\nVnjnnWf47LN/MBhyX/5QEARBEGyhadPmub53+PBBvvvuW4zGDJo3b0mrVq1ZufI9TKZGQA0Mhhk0\nbdrCZrFIkpSt16UgFFV16wY/uFAuYmMv8n//N4Rr145RqVJlBg8eiqdn9rk96tdvwPffTwCWAYEY\nDLNo3LilQx+eBgRUJCDg1hxZjkvYCIVbkUqSCLZXu3ZrRo1ayIoVc4iMPIWqppOWpuXgwc28//5/\nhIXNEb1ACrHmzZujKEqO723duvWRj/9x31d4ac5IZNkA/AG0AD4ALNy40Y2+fctRrlwwQ4bMISAg\n/1+0giAIgpAfZ86cZu7cOciyFpBYv/53FEVh6tR3Wbp0OUlJyTz1VB1eey33XpOCIDycjIwU3nuv\nFYmJSaiqhoSEY0ybNpk5cz7J9kC2dGlvpk+fxJIl35GYmEz9+oH07PmqAyMXhLwRSRKB4OD27N//\nK1evHsJisfYKMJtVIiMjSEi4SYkSXg6OUHCUkLp1GTjwQ5Yte4/U1EPASKxrDOiAlzGZTnLhAkyZ\n8jyffHIAL68yjg1YEARBeKL8/fceZBnInEfNaLSwe/dOXnutJzNmvJvrfrJs5NdffyEi4gqVK1fh\nhRdeRKcT1WJByItz5/7FaMxAVa33ncWiISYmhri463h7Zx+KHRBQkfffz/1efBhXr0axbt0a0tPT\nadWqDfXrF61VuoSio0h9GyiKBY1GTIz1qBISYkhIuIavbxWcnNwIC3uJEyf+yhwj6ASZE6wqioJe\nb3BorIJj7T9zhq+++gRZHgV8BawEmmDtnrgO6AUsQFFac/z4dlq27OnAaAVBEITHVUpKco5DgJ2d\nndBoJG53qlQfWHdRFAvTpk3m0qVITCaVI0eOcurUSSZMeFf0nhWeKDEx0RiNRvz8yqDX533BBoPB\nBVW1YG0z3G43GAz2azdER1/jnXfGkpGhoqpw8OBBhgwZSvPmLe12TuHJVaTW63z11Vfo06cHUVER\njg6lyPrll48YOrQ6777bhUGDqrJ372pOndqD2azD+kcuDTCi11to2bIV7u7uDo5YcKSPf9uGLI8H\n3gB2AtuAGkAw1t+XUYABiMNgcHVUmIIgCMJjrl+/3gwfPpiMjPRs2595pgMuLjo0GiNgxGAw89pr\nPZBlI3v37mHnzu3Ex9/Its/FixeJiIjAZNIBBmRZx/Hjx4iLu15wFyQIhcAbbwxlzJgxDBs2kpiY\n6DzvV6XKUwQE1MVgUAEjTk5mmjR5muLFH7yc7vnz59i+fSvHjx9DVdU8n3Pz5j8yEyROgBOyrGXV\nqh/zvL8gPIwi1ZMEPEhPz2DixAksX/59gZ5ZVVV++eUjNm9ehiRpefnlN2jffmCBxvCoTp7cw8qV\nkwBXLJZUTCYTCxcOR5I0WBu8boARjcbC88+Polu3ho4NWHA4k1kBbk3M6gW8g0YzDkUZCLwEjAdc\nKVEig/r1OzoqTEEQBOGx587162lMnTqZsLA5WVtLlSrFnDkfs3HjetLT02natDmVK1dh7NjR3LyZ\ngKpKaDQWpk6dQcWKlQCwWMyZdZ/bNBoNZrO5QK9IEBzPFUgnMdHEZ58tYubMKfctnZqawBdfjOTU\nqb0UL+5L27a9ycg4RdWqVWnXLuSBZ/v993WsXLkCSdIBFlq1asWAAYPzFKnZbL4nqSLuWcFeiliS\nRAO4kJ6edM9StrbUhTX3bJu3YRO/rdlLmnExIPPDt/1xd79I06bNbHDG9TY4xoP9/nsY1h/5ra6k\nKkZjEmXKlCEmJh6LRUKr1VKqVAleeaW+3T7fx0/B/PwcYeizzdl8bCay7AEYMBhm0737NP75ZzsR\nEX1wcXGnWbPedPlfDQwuf9z/YKbclyEWBEEQhPvbDRziwoU3iIu7TqlSpbPeKVWqNL16vZ71+uef\nf+L69XjMZj3WOo+FRYsWZiVXAgIq4e7uhiwnY7Fo0OlUfHx88fHJ+7L2a8j70ARBKLz0gAzEExOp\n0OWu1V7ubhHNnt2Dc+fKYDb/SnLyP1y//h6ffjoLL6+SDzxTWloqP/zwHWazM9Y2nYadO3cSEtKB\nChUCHrh/y5Yt2b59K7IsAxqcnBTat2+ft8vMhbiPhdwUsSQJgAJIBd6A/+HPw6QZpwN1AUgzTuDP\nP1fZKElSMCyW7GMHQYskwbRpM/j668VcunQRf//yDBgw6KHGJQqPr5C6dXnrrYX88ssXKIqFTp0+\noHnzbnTqNDJ7Qf29iUVBEARBsJ1Kmf/9zPHjx2jdum2uJePi4jCbVe6s7yQk3Mx632Aw8MEHYSxe\n/CWRkRFUqlSZfv0GinnvhCeQirVtpaGy7/0n35fldM6c2Y2iRGFtQlYCNhIefpwWLVo98EzJyclo\ntVrM5lttOAmdTk9CQgIVKjw40ipVqjFhwkR++OF7jEYjrVu34fnnOz94R0HIhyKWJEkHTHTq9LzN\nj6yqKhkZKTg7u9/+Tr2Dp6sTcC3rtSRF4erqlK9zrfvnH6YtX05yRgYvNG7M030HotPZPynRvHkL\n/vvvPywWa6IJjAQFBVOsWDFGjRpt9/MLRVODBp1o0KATAElJ11m6dBxxcdEEBzcnJGSgmOROEARB\nKCAqBkMczs517luqTp0g/vrrT4xGa31Hr1cIDMy+T/HiJRgzZrwdYxWEoiAFUHE1uLJ0RN/7ltRq\n9Zl1vuuAH9YEyzWcnWvk6UwlS5bCyckJo1HG2oPFgqJYqJCXDEmm2rWDmDkzKM/lBSG/ilSSpHHj\n+jRp0oxmzZrb9LinTu1h9uzXSE9PwM3NixvdO/HNpk1cT0ykVVAQHw0cyIzuL9B++mTSjReRJCNu\nzit4+eXpD32u/WfOMPTTT3nBZGIXsHLLFnZFRvHetA/yHf+t8XkPaqw2a9aCiIgI1q79FVVVqF07\niNGjx+b7vMKTJS0tiXHjWpOY2BqLpSXHjn1FVNQFevSYwuef/R//7N+LTu/Eq6915bnnOzg6XEEQ\nBOGxMhfYh7d30j3LfqqqiqqqWb2Mn366KRERV1iz5mdUVaVWrboMHDjIATELQuHmjIIRF9LkDBqO\nm8iwZ5/joz7dc2xTaLU6unZ9l7VrX8BofA29/iA+PhL16tXPVi63KRF0Oh2TJ09j1qwZxMffwNXV\njdGj38nTZK+CUNDskiTp168f69evx9vbm2PHjgEQHx9Pt27duHz5MgEBAaxatYrixYsDMGvWLJYu\nXYpWq2XevHm5ji8bPdr2Gf/U1ARmzepGevrnQAjJyRsZ/mU/5pNOI2D2vn0MSk3lhwkT+OuD91j5\n19/otBp6t57OUR//hz7fhn//pb7JxD6sC6qagN4nT/D333/RtGnekz/WCoHC0qWL2bZtK6DSrl0I\n/foNyLW7qCRJdO/eg27dXkVRlALpvSI8HlJSbvLTT++TnFwCi+VDIAOj8RobN35AVNQpTp40YDaH\nYzZf54fvuuLjU4oGDcXa9YIgCE8ae9UB4TLwJ127DstaZlRVVVas+J7ff1+Holho1qwFQ4cOR6fT\n061bd/73v24oikXUd4Qiz173VQWcOEMrYDkWJZUl214ksNwO+rXLeTjbK6+Mp0KFmpw48TelSrUh\nJGQgOt12ACIjI/jww1nExETj6VmM0aPHUaNGzWz7ly9fgYULv0KWZfR6veiNLBRadpnYo2/fvmza\ntCnbtrCwMEJCQjhz5gzt2rUjLCwMgBMnTvDjjz9y4sQJNm3axLBhw1BuL3Zvd1evngHKArdmZO6I\njtLUBqoB80wm1h05gqIo1C5fnhmvvcrUbqFUeojJve7k7urKGWAyUB9oDEwHDu7ckaf9L1++xIgR\nQ3j11a7069eHHTt2YrG4YLG4smvXbtatW/vAY2g0WlFhEPIsPHwX/ftXYuPGHZhMEUBPIAR0c8BJ\n4ejxjZhMFbCuflMd2TiYQ4eOOzZoQRAEwSHsVwecB/yPkyfDs7bs2LGN33//DbPZjKIo/PXXn3z9\n9ZKs9zUajajvCI8Fe91XJgyojAGcAC/SjP3YcfzcfWNp2LAzffqE0anTSAwGF8C6ysz06VOIjo5H\nVTUkJiYwefK77N+/N8djGAwGkSARCjW7JElatGhBiRLZu06tW7eOPn36ANCnTx/WrLFO9Lh27Vq6\nd++OXq8nICCAKlWqcODAAXuElaPixX0wmy8DsZlborFwHe/MVzGAs1Zrsxu5b9u2JGu1xNyx7Rpg\ncHV54L5Go5Fp0yYTG5uMqnqQlqZgMhmxzi+iwWiEQ4cO2iROQbglLKwnqvo+sAf4DzgNmtPgmmFd\nHdhNBRYDFgB0uhMUL+bmsHgFQRAEx7FfHdAM/EOZMrd78e7Z8ydmswnrMqaeqKqOXbvy9tBJEIoS\ne91X3ijA/sxXKgbdfiqULv7Q8cXFXSctzTp3pHW+EU/AhXnzPiUuLu6hjycIjlZgc5LExMRkLa3m\n4+NDTIw1TXD16lWaNGmSVc7f35+oqCi7xpKWlshvv33K2bP7KVOmOiEhr7NtW1sk6WkUZQ8lDM5M\nzjBR22xmucHApG7dbJYkKeXpydfjx9Nj9myuWCyYJIlvnZx4r2voA/e9du1q5qSrt56KGAAj1sap\nDo1GvecPqCA8KqMxGbjVTdMAVAfNudsTHEsAFnS6kWi0N/DwCKfj89McEaogCIJQCNmmDlgdZ72Z\nZ5/tmLXFWifScbs664wsJ6GqqnhKLTz2bHFfXSMVLe+jshmtNgX/kvF4uj7N5BUraRdUBwK7EB6+\ni7Nn9+PlVZZmzbqh1d7bfHR398BiMWOdzNWAtXKoR6ORuHDhHKVKlbLx1QuCfTlk4lZJku775ZX7\ne50e+dxpaUm89VZjbt68DrzA0aPXMRi2MmLEFxiNqfj7v41f+dNs3riZg/HxhAbXpULDBvesEw7Q\nxWTKYeuDdQgOZsfs2azctQtXrZY/W7emWhk/4P7HW+LhkfnERJP5n4p1pncFSTKj1+vo0aN3vmIS\nHsWj/14WZgaDG7L8NfAekAgcRavqsMhm0IHObKB8pdq0bNkAJydXnn76W1ydij3o11kQCo37jeu+\nU0BAAJ6enmi1WvR6fYH2ehSEx0X+64BPY1J2kZiYSIkSXoB11b4TJ05irQ9JgAVnZxeRIBGeOPm9\nrwJa9aIqGjROLlSv3pSffvqIaT+lYDLV4OP1i2nQ4DSHDv2NyfQiev0GduxYxaRJv9w1/2En3N3h\n5ZdP89NPM7h9P6qABk/PZ4FmtrvYPFufhzKPdx1eyL8CS5L4+PgQHR2Nr68v165dw9vbOqClbNmy\nREREZJWLjIykbNmyOR5j1arbq8kEBrYiMPDBa3Lfbffu70lIkIAxwJsAyPIctm1bQf/+YSxePIHY\n6yepWbMSfQe8hrOL80OfIy/qlC9PnV69HmqfkiVL0bFjJ/74YxOKokGjUWjWrB3VqlVHVVWeeqoh\nxYo9fBc5wT7Cw3cRHr7L0WHk2+ELF/j3/HlefHEYq1fPRVWXAml4eZXhzTe38NVXw0hIiKFG7WYM\nH7YENzfxuycUTbfGdY8bN47Zs2cTFhaWNbb7TpIksXPnTry8vBwQpSAUXbaoA0IgFksEb731Fm++\nOZJ69RrQpk07duzYxsWLl1FVDRqNhSFDRhbAFQnC/YWHHyc83L7zs9nivipd+vbyu1euHOXmTV9M\npuWAhCw/x969IcBBoDxGo5nz59ty7Nh26tYNydrPaExj2bJ3CQ/fi5dXdRITLyBJBnQ6LXXrPkP1\n6k3tcfnCE6gg21YFliTp3Lkzy5cvZ/z48SxfvpwuXbpkbX/ttdd4++23iYqK4uzZszRq1CjHY4SG\nTn7kONLTk1BVHVDljq3VOXp0IWPGNMdkGomqvsGNuIXExMxj6oxxj3zOvFJVlV3h4VxLSKBBpUpU\nK1PmnjI9e/YmODiYiIgIypYtS1BQcIHFJzycuxN5q1fPsMt5HnbG87xYsnUHby/7CYn2KJqfCQ4O\nQa/XcOjQZhITY9iy5Rtmzz6AxWLm0qX/uH79Eq6udcXTO6FIWrduHbt2Wb90+/TpQ+vWrXNMksDt\nJdcFQcg7W9QB4R3Ai7S0Jaxd+wf16jVAq9UyffpM9u/fR1JSIjVq1CQgoGK2vdLT0zl27D8URaVO\nnSDc3MScWYL9BQbWJjCwdtbr1at/tPk5bN222rBhARbLTW6Ppy6Z+e9yma91qGp5UlLisx3jo49e\n58QJCZNpNpJ0AGfnT+nSZST+/jVp0OB5u9cNExNjCQ/ficHgQlBQCAaDfR5wC45XUG0rsFOSpHv3\n7uzatYu4uDjKlSvH9OnTmTBhAqGhoSxZsiSr0QZQq1YtQkNDqVWrFjqdji+++MKuN1Pduu358cc5\nKMpsIDBz6yxUtT2yfIFbvUtMpv/j9KkKpKamFsgXqqqq9PpsHusPHkKSdFgUmWUjhvPSHWMKb6ld\nO4jatYPsHpNQNPTt25c33niD3r1vD7XK65PxnJjMZkYtXY7RvBtrMjGDY8eCkSRXzOadgBcHDgxB\nkt7g6NGdyLIXihJPjRrBTJjwQ45jVQWhMMttXPfdJEnimWeeQavVMnjwYAYOHFiQYQpCkWC/OmA4\nsBCYzunTQ7LqZ1qtlqZNc+7Kn5iYwIQJY0lNzQDAyUnHrFlzxPwIQpFTEG2roKC2aDQfAB2AGmg0\n01AUF6zrcI4E9iPLO6he/dOsfYzGNI4d24iiXAGcUNWGqOoefHwq0bBh53xd68PMKRQREc6kSW1Q\nVQlVVShZsgyzZu3B2dk9X+cWhFvs0ppZsWJFjtu3bt2a4/aJEycyceJEe4QCQFzcFVasmEl8/HUa\nNGjN6NFLmT9/OBkZTbBOgjoQKAEc4fY4ujRAQavV5n5gG9p+7BjrDx0i1ajn1mRHfT//nC6NG4un\n88J9tWjRgkuXLmXb9jBPxu+WlJ6OigaonLnFGVV1x2welLktFlkuyV9/rUFVnwX+D5A5ebIr27Yt\npX37Qba5MEGwoZCQEKKjo+/Z/sEHH2R7fb9x3Xv27MHPz4/r168TEhJCjRo1aNGihV3iFYSiyn51\nwFeAt4FWWCwyI0a8xfDhA3nqqYa57rFy5Q8kJKRhsVgnvJdlI9988zVvvz02D+cThMKjINpW/v61\nGDfuW778cjwpKXF4enoTHd0L68qGdYHSODu7UapU+ax9bj8YS8O6jLAKJKHTGVAUhQ0bPufgwZ14\neZWme/eJ2fa92/nzB5k7tx83bpzFxyeQsWOXUa5cYK7lARYtGkZamoy1PacSGxvB+vXz6NrVfu1K\n4cnw2D/yTUqKY/z41qSmvoqitOLs2fm0adOc7t0nsGz5WFTFB6gKTARKAYOxTi70FS1btcbZuWC6\nbEXFxyOh5XYXNw1Gk4k0oxG3AopBeHzk9cl4Trzc3SnjVYor1+ejqMOB/ahqNFrtCSyWeCAEeAZV\nfRf4HOuTvaHI8jNERp61/cUIgg1s2bIl1/dyG9d9Nz8/PwBKly7NSy+9xIEDB3JNkkzPfKIH0Cow\nkFaB96/oCYIjFY05tJphXTXjOaA9qalv8OmnrzF7th9ly/rnuEdsbCwWy+3XiiIRGxtbEMEKQpEh\nyxlYLCZcXDyoU6cdn322H61Wx59//sCXX36K0bgW8ESjmU6VKuez7avTGWjffig7dryM0dgHne4f\nihVLpG7dEJYvn8j27bsxGt9AoznGkSOt+eSTA3h63tuT68CBNXz8cV8UZT7QiejoH5k6tTMLF4bf\nd/jMjRuRWBezAJAwmczExFy02WcjPLke+yTJv//+hiw/haK8B4AsP80ff9QCjQVcVFAvQ9pQoD6w\nFpgP7EejvcLL/xtcYHE2qFwZi3JrORANkmSiQmlvkSARHtmDZjzPqfymSaPpEjaf01en4epamgED\n/o9vv51KUlJnzOYgYG5m6RbAi0AvnJx+o1KlIXa4AkGwr9zGdd8pLS0Ni8WCh4cHqampbN68mSlT\npuR6zMmhD17WXRAKi4Ic551/lYADQG1ABp5GkkI4ffpUrkmSOnXqcObMWYxG61xCBoN1myAIVkuX\nvsXmLYuQAK+S5bgZH4fl/9k787CqiveBf+7CZRNQFFBARHFBQUFzS3Pfc8Gl0iyt1LLM1BZLc2t1\nKTXX6vctt6zUMs1yS80t971SMy0xUURFQFnvOr8/Bq6QqCwXBJvP89wH7rlz5p2Zc94zc9555x1r\nOqGh7XjttSW0aHGQ7dvrotG4U65cWQYMWHJLHs88M42goIX8/vtefH2D6NVrFgaDK5s3/x8Wy1HA\nF5stCpPpLw4d+pG2bZ/Jcf7p0/uZNXsANlsQ0Dvz6EDM5rlcvvz3Hb1J6tRpwb59P2A2yx0/rqZM\nqgAAIABJREFUnZ31hIe3dlDrKP7L3PdGEiEEQmRfMpP5v7O4WXsDYDqf+dubQCw260oSEhLwq+hX\nLOUMq1yZT4c+x9BPP8VqsxHgXZ4f3xxbLLIV9x95nRmH3Ge8q/n58evMd5m+Zh2f7PyTtWsXMHjw\nVHbtWs7+/WWw2bLOKAdcx8mpHo0b96RlyyeLtF4KRVHMeN9uXXdsbCzPPvss69atIy4ujt695eDN\nYrHwxBNP0LFjR4eWQ6FQ3Iks9/mlwFbAghB/4OkZctszevToyYULF9i1aycAkZGN6dv38SIvqUJR\nWti2YxE2Nwto4GpCNFgeBhZz5swY5s4dxptvLqdz50FMm/Yk16+nMm5cJ5o1e4Rhw+bZJ+BkvK7B\ntG8/2J6vfP8S2N+7ABn49dbg57/88hUWjMBl4AbgCcRjtV7Fw6P8Hcs/ZMhcEhIu8scfuwFo3344\nLVr0L0yTKBRAKTOS/PnnXipXroObm1eez3ngga58+eXbmEwfINfTzQbKAEn/SlkBOSveDFgPeisz\nPpjB/xb8D61OS25k7b59+swZrl69SnBwMAH/2pEmP7tvP96iBY81b05KRgaerq4qFkkpwYnv73UR\nbiEvM+NZ/HvG22qz8fHGTSzYsofTsYlYbHOAVGbNGkq7dv3Q6b7GZmsC1MRgeJ/IyCgGDZqKt/ft\ntm1UKBxHUcx4e3t757qu29/fn3Xr5JO+WrVqHDt2rNCyFApFQfkOsADjgEZAS6pUMdCgwQO3PUOr\n1TF8+Eiee+4FhBA4OzsXU1kVitKB0ZImw3loABcg5TfACYvldU6degicvmfxFzO5dq0LNtsEIIV9\n+7oRHvEKrdq0um2+GqBNuzb8sqM/RuMraLTH0eu380DTjuCUc9zs5HIBjU6DwAjmZkAbNJrNdO06\nnLJlK96x/K6uHkyatJmMjBT0egN6vSHbr/l5C1MoclKqjCRTprwCXGTixO+pVq3BbdPFx8dw/vzv\nVKhQmaCgukyZspUJE7pz/fo3wBXACOllID3rDDOwAFgFmnngZgS93DYu6XoS3t7et5W1dOFC9m/b\nRj2tlgVWK0899xytWrYscB11Wi1ebm4FPl/x3yM/Ec/zwpCPF7J6fyJpxheBn4EXgdcwmx9g48Yv\nATMGw9t4eHjTtGlXnnhi0r86JYVCoVAoHM0IQAu6ZLAeQKfTERLSBptNoM19LsuOwaD6KIUiN1zM\nkGHWg4sFMjyAq0AloAHOzmU4cugI587+jc02H2n68MBo7MX6tctp2qzpHQ2PQ54bQPnyP3Lk8AeU\n8/bgyYETKVu27C3pOnbqyM+bfiZdmw5OF9DZlhMV9Rr9+k3MJdfb1CPbbjYmUzoLFrzOsWNbKVOm\nPM8+O5XQ0GZ5zkuhgFJmJElL+xn4jhkzBjF/fu4zegcOfM+cOcPQ6yOwWE7SqdPTDBjwNhMnfsur\nrzYH6gEXgIeAl4G9wASkJ0ks6IWM/5MBNqsNvf72TfT32bPs3baNvUYjZYFTQLv/+z8ebNpUdciK\nYiO/Ec/vxNUbN1j+y3as4htkZzgTGXPkLaA8YAWew2RyJjn5M9q06acMJAqFQqEoBpyADLC6A59h\ntQaydesY4GsGDRp4j8umUJROpFZZIMMF6AusAnoCx7l+PZ5ZM3ZjNGYA7wKLkfGAfuKfc1bemTid\nd6eMRXsbK6VWp6XPY1H0eSzqjmWoWKkiU6dPZe0Pa8lIq0DLlk8SEdGhwHWaN28Yhw9fx2z+gsTE\nU7z//iNMm7Ydf/+aBc5T8d+jVBlJJF2Jjx+a6x7aFouZOXOew2RajclUH0hg7drG7D+wAjdXb8AG\nHEK+/DUGOgNG5PKbpvJ/swnMLkBrbJoTPD/oBcLrhTH4ucG3xCeJv3aNOlotWTbRUMBFoyElJeWO\n3icKRUlk1x9/0H3yZKzCBvRHBsm7CvgD7YG6wN/A50ArTKah/PDDxwwf/km+9rRXKBQKhSL/7EUu\ns3kUOX4Dk+kj9uyJUkYShaKAJKNFBmd0ApYDTwC7gLPAPjIyqgDnkO9JdZFb/Vqx2bz560w0Z06f\noVZorUKXo5J/JZ59/lkw3355eF45eHA1VutJoCxQG5ttJ7/+ulkZSRT54i4OiiWRb/HzC8v1hSwl\n5VpmkNb6mUe8EaI2Vy7HcO7caeTe3VrACpo3oUwieKSB7ioaEoE00LojraVuaEU8BquZU0eP8ebr\nY7lx40YOeVWrVOGI1UqWT8u3gJOLC165uJIpFCWZdJOJqKlTSDUa0WHFCSvSIPIksqMsi+xEuwIt\nkXp0iMTEqwwdWpu+fV0YMMCHXbuW37M63EvOnDnAxIndefXVVqxc+QFWq4WNG/+PV15pwejRbTl4\n8Id7XUSFQqEo5VQCqgK/ZDt2GYNBxRlRKAqKEzYgA2kAsQDLQHMaqW9VMlMFA35ADJCM9L7/ESF6\nsvq7jfa8LBYLZ/48w+rvVrNl0xaMRmPxVSQbTk5uyCCwEq32Ms7OKpSBIn+UKk8SV9cm6PVpvPba\nmlx/9/T0wcXFFbN5DXKJwJ/AEeSLXlvgA+AM4A3O8TcDLrsKRArSwQQtcknOGFyxYkM2kjCbOXbk\nGC1b34w34uvry3MvvUT3uXPR2Gy4ubvz+rhx6O62OFahKGHExMdjNFvQA+4IwIgZSGMl0ttqCzAa\nGIMMgNwIeI4//rBgsTgBT2E07mPOnGHs2LGcsWNX3db98n5i27YlfLNiEgkJcQi6AGO5cuU9Tp78\nhTNnzmE0fgCkMnv2cF5/3Z169drd6yIrFApFKeUY8BcyoNxIIBiD4RP691e7qikUBcUJMOMMHEWO\n7YaCWAesBvYhPUj2AJfle5PNBOIy8AYwlKtXxhIfH8/U96Zy/p/zMlNNZwxOV1n3wzamzpjI1StX\nuXLlCpUrV8bH16fI69Sv33i+/rovJtMg9Po/8PA4S9OmfYpcruL+olQZSd5992sqVqyOweCa6+9a\nrY5+/d7k8wXDELaRSJewmsBHmSmaZX6Pl6EVssjaztQVsBjBNBkQpOAGhAOn0Zkyct3lpmmTJjRq\n2JDU1FQ8PDzUkgNFqeRyUhImi5yNS8YZN1IzbYhX0GpdESINIVpwM5bPOwQFhXD+/FGkIbIy0pjy\nIL/+upl16+bRvfuIe1KX4uLQoR9ZtGAkOlMa7kAa27DRBKPxE06c6IgQclkSgMl0kW3bVigjiUKh\nUBSYKCAQOIPB8B1NmjSlbduXCAsLv9cFUyhKLWm4IJdRP4v0iXdBeg3vQuqcK5AOrkbpUGwDkpOB\n3cBfWK1pjBw+ErPZDM5IQ0raDkymbcTHv8ms6bP4/fff0Rl0WE1WXnjxBZq3aH5LOSwWCyeOn8CY\nCqGhzfH0LLgx5eGHh1GxYjBHjvxMuXKhdO48Gzc3zwLnp/hvUqqmeoOC6t7WQALw118H+fzzFxGG\nVHBJQgYXqgRsRAZnHYZUdg8wO0GqRk5IpAFoIE0PFjPywaAHfgI2AUew2lwoXz73vbp1Oh2enp7K\nQKIolSSmpNBr2hxgFvA3NsaSiitpgEFnxcPDG53OgEYDen0sLi5d8fJax1NPvYPsMQMzc3IGagBW\n9u2T7pcWi4kbN64ihLgHNStadu78Co0pDT1yTCBbbDmQkvksyL487wZOTirArUKhUBQcF+S4Dkym\nVPbvP0xiYtK9LZJCUeoJARogrR8aYAMyDl0qcvlNEmC++caozUxGOlCR2IsXMWvNmRPNmR+NGRiD\n0Sg4duwYJoOJdG06JicTH8/7+JZlOCaTiXFvTGbGtDXMn7+AESMacP7874WqVYMGDzNkyAz69BmL\nu7sKg6DIP6XKk+Sff+ZTqVKl264//eSTCQgnId/VQL65pO4ETgDtkOvoAoApwAtgsQBpoEkH4QkY\nwNYBue1p1vo8AG+cnRuSkhQG5h52eeY8lfr7PKQofJCiomHdvS5ALpS8Pc/zdh+UXOqPGMGN9MrI\nYHgAwxHMIqRSWc5eNnP9+kykMeQFLJY/sVgsmM1uzJkzFNlbhgCPAG2QgfUq4eVVnm3bvuCzz0YB\negwGJ5q3aECLVs0JrR1a6DL3dFCjf+9U8HPd3BNBo4FMA5B0SEvD2XkgLVs1YMf2VzCZLoImBWfn\nj+nWczw43f15oFAoFIrcaABsy/zfFZNpNZ980pWmTZtm7kRY8sYHCkXJJxZp9dACnZBxRz5GvkwN\nALoA1SF1HrjekEmFBvAFgsFpuzxVizSUpAD4ZOZ7ETQ60Ga67+vAYrGyaV0c3buPBODatQu8Oe4h\nEhNiAU/ksu6H+fjjV5g6dXMx1F+hyJ1SZSSZOHE+ev0NJk16k6CgKjl+S09PIybmpHyXA/nGkg5y\n1uESsBRpNSkLJALvgfZlEEYZzxUjcucbH+Aa0kCSFdvkBEIcJShIuXQq7j+apqSwiovAc0g96AEk\nE3NFj8U2jawlI9JjJAXoh9V6kOvX/0C6Zvplnvs1IHB2zqBNm0eZPXsYFssPSONKHTb/VI0d2+bw\nwvAnad6i9O9XH9W7J3v37MOYkYEQAotWS+3QcnR+uA0PNm9K85bN2LplB05OOh7uNoHKQZXvdZEV\nCoWiFLMB+YamR05PzAf0pKam4OWlZooVioJhAlogX4ZOAa8jjSVjM39fjww9MA/SX8hMPx05mTxe\nqqIt8+ME8kXsd6SevovV/H9gMdnVVtgMLFs2C61Wh9VqYu3aj0hKvyztI9YbkDoYqEp09BW++GIc\nTz75DnFxf3PixA7c3Dxp1CgKg8GleJpG8Z+mVBlJ0tMDgAf48MO5zJ07HQCTycjH8+eyZ+9umcik\nAQSYnAEPIB7ckRbOdCtYriGX01QHrQ0MNkjTAt5IAwlAeWRE59HAq2g0KTz//Gf4+VUrtroqFMVF\nDQBu4Mw3aAAjaxBoMFmNwNvIjtKK7BgPI3XDgoxPkoIM6jUdGIizs4mZM3/h+PFtaDRtkYbH2sAi\nAEymjixeOOi+MJJU8q/EBzM/YOuWrVisFh5q8RBVq1W1/14nrA51wurcwxIqFArFfYQHkC4yvYBd\nge9wdfXFw0PFGlAoCoqGVAROyHGdE3JXmGvA5+BiloeMB8E0HjkO7AGEAdWBsVCGzICuSId92nHz\n9fJh4DO5cifz9QyqYrFcYsmSSchdcjINJFn2T70RLFURYiJr107lr78OEh19HCE6o9H8w+rV85g8\nedMdwy8oFI6gVBlJZGTzFC5ftiKE4Mcfv2fZsq+wWq2AG/JFTg+mDCAS2C+9xbJq6UKmG9hxYBm4\nZGT6yNuQD4Qvgb5Iq+kVYC4GwxsMGTKNhx7qW3zVVCiKkb+Rdv8su7wGSMcZK8HIDm4V0oD4G1Ax\nM5UeuXTtc2TQ1reA6xiNabz7bh8qVPDDYjmN3DYuKJu0yhgzUou0PsWJX0U/Hn/y8XtdDIVCobj/\nyXLnTwboA6ymXbuH/hM7qSkURUUj4AA3kNYOM/AVcBi05pvhC1ysYDqfacj4Dsw/AoNAI27uFJq1\n5MZ2Full4kyWhzEGMiexf0Yum/sHuZnGFXmSzSbzEYBNBzyN9GZpzKlTkcCCzO+CuLjH2bZtCZ06\nPX/HeqWnJ3P58lm8vf1zDQIrhODXXzcTHx9DtWoNqFatfr7bTnF/U8qMJPOAqcAZ9u/fyzfLv0Zr\ntWLFHXgC6fnxJa68CxwgHR3Ysm1jk7WLDYfBySZtKhlZx4ygeR3ES7i4+OLq6o3B8AFRUW/SuvWA\nYqqfQlH8rCMzBlcOXJFrv12BEUhXSwMyEHJV5PKaI0ilaoncCq4fMJErcb8SF+eO9CBZgFSytkBV\nNJrRuOj0bNnwE+06d3RosGObzcactWtZt3s3nu7ujHvySRpUU95fCoVCcT+gywBr1gsZLYCNrF27\nnr59H1eGEoWigBxDh3TliALGISfEHpcGC0E2DxCkHUWL3AY4+VN53IJ8m7QCNi3S8FEdaSTJAPfU\nzOB9rkgDCUiP5KpIY4gXpLwETkawasDmDXTIVkILN2NEajCbw7l+/cod63Ty5C9Mm/Y4UB6LJZYB\nA96jc+eh9t+FEMyd+zyHDu1DiAcQ4m2eemoSHToMzk/TKe5zSpmRpDvS5lmXmTNnYMCWGTQzA2lh\nPIQ7HzAp0xryNlZSzcjdazRki7BpA3Om5dIJtCb5qqd1MeLtXpnZs0/g5JR7cFiF4n7jIWAz2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6mgx0mOUuwCbwNIObBeRYLjBHbmFoKI/0Ndm4fz9LV6/mo//7P56dPZtr1y4ycWJ3hgwJ4fXX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\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wQ8ycuQV//2BOnNjPhg2L2LPnZ1RVxWIpRFXDOT/APhRFsaM4l+gsKMjh999/YOfO1Vgs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pGTcwLYBEQCU5gwof9ZjSQnTuTj8VjQG0gAInC5kti/f8sZjSRCBJPy11U2UAuYhN4teTBu9+ds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wMDAxkeHs7LL79cd6SPbWJiYqkjnKNJeZqUJWlenqroVf2alEeWxaFX9WpSlqRZeZqUpWp6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\nP11pllYtxv1d6HMvVia9+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+ "text": [ + "" + ] + } + ], + "prompt_number": 75 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let us also quickly take a look at the confusion matrix for the overall model. Because maybe we should not care about the confidence of the predictions, and just weight them lower." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "from sklearn import metrics\n", + "from matplotlib import cm" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 80 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "def printConfusionMatrix(algo, X, y, title):\n", + " skf = cross_validation.StratifiedKFold(y, 5)\n", + " nClasses = np.count_nonzero(np.unique(y))\n", + " print \"nClasses = %s\" % nClasses\n", + " sumPCM = np.zeros([nClasses, nClasses])\n", + " for train, test in skf:\n", + " X_train, X_test, y_train, y_test = X[train], X[test], y[train], y[test]\n", + " print \"Number of distinct classes in training set = %s, test set = %s\" % (np.unique(y[train]), np.unique(y[test]))\n", + " y_pred = algo.fit(X_train, y_train).predict(X_test)\n", + " # This has the raw number of entries (e.g. [610 12 1 0 32 1])\n", + " # Since the total number of entries for each mode is different, we want to convert this to a percentage\n", + " cmraw = metrics.confusion_matrix(y_test, y_pred)\n", + " # We do that by summing up the entries for each mode (e.g. 656)\n", + " sumArr = np.sum(cmraw, axis=1)\n", + " # and repeating it across the row (e.g. [656 656 656 656 656 656])\n", + " repeatedSumArr = np.repeat(sumArr, cmraw.shape[1]).reshape(cmraw.shape)\n", + " # And dividing the raw numbers by the sums to get percentages (e.g [92.98 1.82 0 4.87 0.15])\n", + " sumPCM = np.add(sumPCM, np.divide(cmraw.astype(float), repeatedSumArr))\n", + " \n", + " finalPCM = sumPCM / 5\n", + " logFinalPCM = np.log(finalPCM + 1)\n", + " np.set_printoptions(precision=0, suppress=True)\n", + " # np.set_printoptions(precision=4, suppress=False)\n", + " print(finalPCM * 100)\n", + "\n", + " oldSize = mpl.rcParams['font.size']\n", + " mpl.rcParams['font.size'] = 16\n", + " (fig, ax) = plt.subplots()\n", + " # First element is \"\" because of http://stackoverflow.com/questions/3529666/matplotlib-matshow-labels\n", + " ax.set_xticklabels([\"\",\"walk\", \"\", \"bus\", \"\", \"car\", \"\"])\n", + " ax.set_yticklabels([\"\",\"walk\", \"cycle\", \"bus\", \"train\", \"car\", \"air\"])\n", + " cax = ax.matshow(logFinalPCM, cmap=cm.gray)\n", + " ax.set_title(title, color='green', weight='bold', size=16, y=1.1)\n", + " \n", + " fig.colorbar(cax)\n", + " ax.set_ylabel('True label', size=\"large\")\n", + " ax.set_xlabel('Predicted label', size=\"large\")\n", + " fig.tight_layout()\n", + " plt.show()\n", + " return (finalPCM, fig)" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 175 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Model selection" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "modelCMList = []\n", + "saveDir = \"/tmp/ml_results/\"" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 90 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "printConfusionMatrix(forestClf, genericCleanedFM, cleanedResultVector, \"Generic features, random forest\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[[ 95. 1. 0. 0. 3. 0.]\n", + " [ 4. 85. 3. 0. 8. 0.]\n", + " [ 8. 8. 33. 2. 49. 0.]\n", + " [ 4. 1. 3. 39. 52. 0.]\n", + " [ 3. 2. 5. 3. 88. 0.]\n", + " [ 11. 3. 0. 0. 0. 86.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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oqxMdHY2rqyv379+nc+fO1K1bl6NHj7Jv3z5cXFwIDw/XO+bu//3f/zF79myq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\n7Ow0joHSahuRmJiIMWPGICEhQZAMDwkJweHDhxUEIVNTUxE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+ "text": [ + "" + ] + }, + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 168, + "text": [ + "(array([[ 1., 0., 0., 0., 0., 0.],\n", + " [ 0., 1., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 0., 1.]]),\n", + " )" + ] + } + ], + "prompt_number": 168 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,Spatial_indices], cleanedResultVector, \"Spatial Features, random forest\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[[ 95. 1. 1. 0. 3. 0.]\n", + " [ 5. 88. 1. 0. 6. 0.]\n", + " [ 7. 3. 74. 1. 16. 0.]\n", + " [ 5. 1. 4. 63. 27. 0.]\n", + " [ 2. 2. 3. 2. 91. 0.]\n", + " [ 7. 3. 4. 3. 10. 72.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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FqbunlG7TSn6dzJLoJViZWOFs7ZynNryLJjZNqFC6AktPLlW6Sn/45mFOxp/Ey0H54Qd1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\n3aEIwgehJATKYjdGKZfL2bBhA2fPnqVevXoMHz6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+ "text": [ + "" + ] + }, + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 96, + "text": [ + "(array([[ 1., 0., 0., 0., 0., 0.],\n", + " [ 0., 1., 0., 0., 0., 0.],\n", + " [ 0., 0., 1., 0., 0., 0.],\n", + " [ 0., 0., 0., 1., 0., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 0., 1.]]),\n", + " )" + ] + } + ], + "prompt_number": 96 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix, cleanedResultVector, \"All features, random forest\")\n", + "fig.savefig(saveDir+\"cm_all_random_forest.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[[ 96. 1. 0. 0. 3. 0.]\n", + " [ 5. 88. 1. 0. 5. 0.]\n", + " [ 9. 4. 71. 2. 14. 0.]\n", + " [ 5. 1. 2. 67. 26. 0.]\n", + " [ 3. 2. 3. 2. 91. 0.]\n", + " [ 3. 7. 0. 3. 7. 79.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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foymuFAwvStu2bWVTU1P58ePHStm+fftkSZJkSZLkIUOGaNTv06ePrFKp5Js3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\njCyDwWAYEWZkGQwGw4gwI8tgMBhGhBlZBoPBMCLMyDIYDIYRYUaWwWA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+ "text": [ + "" + ] + } + ], + "prompt_number": 170 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Adding start and end points does improve the accuracy of the bus and train. Train trips in particular, are significantly improved." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "knnClf = neighbors.KNeighborsClassifier()\n", + "printConfusionMatrix(knnClf, genericCleanedFM, cleanedResultVector, \"Generic features, k-nn\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 95. 2. 0. 0. 3. 0.]\n", + " [ 11. 60. 6. 0. 23. 0.]\n", + " [ 12. 34. 15. 2. 36. 0.]\n", + " [ 6. 6. 3. 25. 60. 0.]\n", + " [ 5. 14. 3. 4. 73. 0.]\n", + " [ 32. 0. 0. 3. 24. 41.]]\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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pnZ0dDg4OhISEKNPS0tL4+++/kcvlKukJCQmcP39eGbM+NDSU48eP06VLF3x8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\ntmjRguvXr/PgwQPq1Kmjcu/hw4c6bUzhA9mAMjI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+ "text": [ + "" + ] + }, + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 141, + "text": [ + "(array([[ 1., 0., 0., 0., 0., 0.],\n", + " [ 0., 1., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.]]),\n", + " )" + ] + } + ], + "prompt_number": 141 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "knnClf = neighbors.KNeighborsClassifier()\n", + "currCM, fig = printConfusionMatrix(knnClf, cleanedFeatureMatrix, cleanedResultVector, \"All features, k-nn\")\n", + "fig.savefig(saveDir+\"cm_all_k_nn.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[[ 95. 2. 0. 0. 3. 0.]\n", + " [ 11. 61. 5. 0. 23. 0.]\n", + " [ 11. 35. 15. 2. 36. 0.]\n", + " [ 6. 6. 3. 23. 62. 0.]\n", + " [ 4. 15. 3. 4. 73. 0.]\n", + " [ 32. 0. 0. 3. 24. 41.]]\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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VFRUYMmQITp48iaCgIPD5fCQnJ2PJkiVgGEbo/wEOh4M2bdrIq+mkAdAYqZQcHBxgYGCA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\nC+fj41PtvfHjxzMcDoeZMGGCUFkOh8OEhoZWK79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+ "text": [ + "" + ] + } + ], + "prompt_number": 176 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "knn does significantly worse, primarily because of bus trips. I suspect this is because different people make the same trip using different modes. Time for per-user trips?" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "svmClf = svm.LinearSVC()\n", + "currCM, fig = printConfusionMatrix(svmClf, cleanedFeatureMatrix, cleanedResultVector, \"All features, Linear SVM\")\n", + "fig.savefig(saveDir+\"cm_all_linear_svm.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[[ 93. 4. 0. 1. 2. 0.]\n", + " [ 21. 42. 0. 17. 21. 0.]\n", + " [ 15. 45. 0. 15. 25. 0.]\n", + " [ 5. 38. 0. 19. 39. 0.]\n", + " [ 6. 39. 0. 19. 35. 0.]\n", + " [ 11. 23. 0. 13. 35. 17.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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pUyAvLw8HBwcAJXf0GzRogKioKAQEBLBl3dzcsHr1aqxcuRJdunRBZGSkxOkE\nSlu/fj3k5OQwfPhwFBcXY8iQIZV2PoSQ/9TFHmmNDaQA0LlzZzRo0ABAyR19Z2dnnD59mu9Gk7+/\nPzIzM7F+/Xrk5ubC2dkZ58+fF1jdWpJHvYKCgiAvL48RI0aAYRgMHTq0ks+MEFIXAyktWlIOtGgJ\nLVpSXerSoiUvX74ss1yTJk0E6nz16hV8fX1x6dIlMAyDnj17YsOGDRKlSxa1sHZcXBzatm3Lt+3N\nmzdYtGgRzp07h8+fP8PQ0BDDhg3DihUrRB6/RvZICSF1lzRBuaLpmAFg9OjRmDBhAt+2Zs2a8b1+\n8eIF7OzsYGlpieDgYOjr6yM1NRXPnz8Xe2wKpIQQmZImkO7atQupqal86Zjbtm2LZs2aYceOHRIt\nRmJkZAQbGxuxZSZOnAgTExNERUWx6bN592nEqXF37QkhdZus0zHzlBXAnz9/jgsXLmDatGlsEJUU\nBVJCiEzJOh0zz7Zt26CsrAw1NTX06NGDTdPMw1ssSVlZGb169YKysjIaNWqEkSNHIiMjQ+yxKZAS\nQmRKmkBakXTMAODl5YVt27bh8uXL2LlzJz59+gRXV1dER0ezZXgrxo0ZMwZWVlaIiIjA6tWrcebM\nGfTp00dsj5aukRJCZErY0P3WrVu4detWldXJu0EFAHZ2dvD09ETr1q2xaNEiNg00r10uLi4IDg4G\nUJJCXUNDA8OGDcP58+fh5uYm9PgUSAkhMiWsZ2djY8N3I2jz5s1871ckHbMwDRo0gLu7O99TkOLS\nNgNAfHw8BVJCSM0gzV37iqRjFqf0/GBJ0zYLQ4G0nNzd3aut7v/973/VVjcAzJs3r9rqtrW1rba6\nAbBP2FUXXurgukCaZ+krko5ZmC9fvuCvv/7i6wXb2trCwMAAERERmDJlCrv9+7TNwtDNJkKITElz\ns2ncuHEwMzODp6cnTp06hVOnTsHT0xNNmjThm2SflpYGeXl5LF26lN0WFBSESZMm4ffff8eVK1ew\nf/9+2NnZ4cOHD1i+fDlbTk5ODqtWrcKZM2cwadIkXLhwAVu3bsWUKVPg4uLCLqAkDPVICSEyJc3Q\nnpeO2dfXF97e3nyPiJaVjtnKygrh4eE4duwYsrKy0LBhQ9jb2yMkJASdO3fmq8fHxwdcLherV69G\nSEgItLW14e3tjZUrV4ptHwVSQohMSbtMnrTpmH/44Qf88MMPEtfj5eUFLy+vcrWNAikhRKbq4jpJ\nFEgJITJsLmWxAAAgAElEQVRFgZQQQiqoNq6AXxYKpIQQmaIeKSGEVBD1SAkhpILqYo+03kzIDwwM\nFJlugBAiO9JMyK/p6lWPtLrz7hBCaGhf69XGTzpC6pq6+HdYI8a68fHxGDBgAHR0dKCqqgorKyus\nWrUK06ZNg4GBAQoLC/nK//vvv1BXV8f8+fPZbenp6Zg8eTJMTEygrKyMJk2awMfHB/n5+SLrLSws\nxMqVK2FlZQVlZWUYGRlh9uzZyMvLq7JzJaS+q4tD+2oPpLdv30a3bt2QmpqKDRs24OzZs5g5cybe\nvHmDyZMn48OHDzhx4gTfPocPH0Z2dja7WMHnz5/RvXt3/PHHH5g9ezbOnTuHNWvWoLCwUGwaWy8v\nLyxfvhxeXl44e/Ys5s2bhz179mDEiBFVes6E1GfS5GwCStIxDxo0CJqamtDQ0MDAgQPx6tWrcte/\natUqcLlcoUnt0tPTMXXqVFhYWEBVVRUWFhaYNm0aPn78KPaY1T60nz17NnR1dREbGwtlZWUAJatS\n8zg5OWHHjh0YPHgwu23Hjh3o06cPTE1NAQDr169Hamoq7t27h3bt2rHlhg0bJrLea9eu4ejRozh4\n8CAbOF1dXdGoUSN4eXkhPj6e71iEkMpRXemYASAlJQXLli2Dnp6ewD0ThmHg4eGBlJQULF26FC1b\ntkRCQgL8/f1x9+5dxMTEiDxutQbS7Oxs3Lx5E35+fmwQ/d7kyZMxbNgwPHv2DE2bNsWdO3cQFxfH\n10u9cOECbGxsyhX4IiIioKioiJ9++onv0gFvNeyrV69SICWkClRXOmYAmDRpEry9vfHkyROBS4ZJ\nSUm4ffs2duzYgXHjxgEAHB0dweVyMWnSJCQnJ6NZs2ZCj1utQ/vPnz+juLgYxsbGIssMGDAA+vr6\n2LFjBwBg+/btMDIygoeHB1vm06dPYo8hzIcPH5Cfnw81NTUoKiqyX/r6+uBwOCKzBiYnJ7Nfnz59\nKledhJDqS8d8+PBhxMXFYeXKlWAYRqBHWlRUBADQ0NDg2857LW62QbX2SLW0tMDlcvH69WuRZeTl\n5fHLL79g27Zt8PPzQ1hYGObMmcM3J1RXV1fsMYTR1taGsrKyQEpWnsaNGwvdLuoTiRAiGWl6pAkJ\nCRgwYIDAdmtr6zKX1gNKOm2+vr5Ys2YNNDU1hZaxtrZG7969sXTpUlhaWqJFixZITEzEkiVL4O7u\njhYtWog8frX2SFVVVWFvb4/Q0FDk5uaKLDdhwgRkZmZi0KBBKCgoYLvdPL1798bt27fx4MEDievu\n27cvcnNzkZmZiY4dOwp8iQqkhJCKqY50zHPmzIGVlRVGjhwpttyJEydgamqKLl26oGHDhrC1tUXT\npk3LDNYie6Tm5uZST2BPSUmRuGxQUBCcnJzQrVs3zJo1C0ZGRkhJSUF8fDw2bdoEAOxQPjw8HP37\n94eRkRHfMXx9fXH48GH07NkTCxcuROvWrfHx40ecOnUK27dvF5pvx8nJCT///DMGDRqEmTNnokuX\nLuByuXjx4gXOnTuH1atXU++TkCog6wn5165dw8GDB3H//n2x5YqLizFo0CDExcVhx44daNmyJRIT\nExEQEIBBgwbh9OnTImOiyEAq7Xyu8gbfzp0748aNG/D398e0adOQl5cHMzMzjB49mq/coEGDEB4e\nzpefhUdDQwM3btzAwoULsWrVKnz69An6+vro0aMHFBUV2XZ937bQ0FAEBwdj7969WL58OZSUlGBm\nZgY3Nzfo6+uX88wJIZIQFlfi4+MRHx8vcp+KpGOeMGECxo4dCyMjI2RmZgIomUNeXFyMrKwsqKio\nQFFREadPn8a5c+dw+fJluLi4AADs7e1hYWGB3r174/Tp0+jfv7/QOjhMLZn9OmLECMTExJSrt1vZ\nOBwO+vbtW231Ozo6VlvdQPVmEbW3t6+2ugHKIlpZYYLD4eD8+fNlluvTpw9fnT169EB+fj6uXbvG\nV87Z2RkcDgdRUVEij1XWGhsbNmzA9OnTsXLlSixYsABZWVlQV1dn38/KyoKWlhZWrVoFPz8/oceo\n9nmkZYmNjUVcXByOHj2K9evXV3dzCCEVJOt0zFFRUXyjUYZhMGPGDBQXFyM4OBiWlpYAwM78uXPn\nDl/G0Fu3bgGAwCXF0qTqkf77779ISkpCdna20KcDKhOXy4W6ujqGDBmCHTt2VOsKTtQjpR5pdalL\nPdKzZ8+WWc7d3Z2vzuzsbLRr1w4qKipYtmwZAGDRokX49u0b34T8tLQ0WFpaIiAgAIsWLRJ5fGdn\nZxQVFfH1cL9+/YpWrVqhsLAQixYtQosWLfDkyRMsXrwYysrKSExMFDnxv1xRKSUlBR4eHtDS0kKX\nLl34nkC6fv06rK2txXaxpcG7jrFr1y5aBo+QOkCau/a8dMzNmzeHt7c3vLy8YGlpicjIyDLTMQsj\n7J5JgwYNEBMTg379+uG3335j//X09ERMTIzYp6ckHtq/ePECtra2yMzMxI8//oi3b9/yPTLVtWtX\nfPz4EYcPH2Yv1BJCyPdknY5ZGFEdPkNDQ+zcubPcbZO4i7do0SJkZWXh6tWrOHbsGPsoJY+CggIc\nHBxw8+bNcjeCEFJ/1OvVny5evIiffvoJtra2IsuYmprizZs3ldIwQkjdVBcDqcRD+8zMTDRp0kRs\nmcLCQrHrfxJCSL1eId/Q0BBPnjwRWyYuLo6dmkAIIcLUxh5nWSQe2v/www84c+aMyEU+Tp48ievX\nr8PT07PSGkcIqXvq9dB+/vz5OH78OHr16oWxY8eyqy3t3LkTMTExOHjwIExMTDB79uwqa2xNkJ6e\nXm11S7p4bV1U3ZeMvl9ajUivXg/tDQwMcOXKFfj4+GDr1q3s9okTJwIAbGxscPjw4TKfeyWE1G+1\nscdZlnI9ItqsWTPExMTg77//xq1bt5CRkYGGDRuia9eusLGxqao2EkLqkHofSHl4a3YSQkh51euh\nfWlxcXF48OABsrKyoKGhgXbt2lF+I0KIROpij7RcD6/HxMSgXbt26NixI0aNGoVff/0Vo0aNQocO\nHdCuXTvExsZWVTsJIXWEtHftZZGOmWEYrFy5EmZmZlBRUUH79u3x559/lnlMiXukd+7cQY8ePZCb\nm4tevXrBzs4O+vr6eP/+Pa5fv45Lly6hR48euHLlCrp06VK+MyOE1BvSDO1lkY6Zd8y1a9dixYoV\n6NSpE44cOYLBgwfjr7/+Ervym8SBdO7cuSgqKsKlS5f41urjuXz5Mtzd3TFv3jxcunRJ0sMSQuqZ\nmpqO+cOHDwgKCsL8+fMxc+ZMACUpiZ49e4a5c+eKDaQSD+1v3bqFoUOHCg2iQMkK1kOGDKHhPSFE\nrJqajvn8+fMoKCiAl5cX33YvLy88fPgQaWlpIo8tcSBVVFSEiYmJ2DLGxsZQUlKS9JCEkHpImmuk\nCQkJaN26tcB2a2trJCYmllmnJOmYExISoKSkxK6YX7oOAGLrkTiQ9ujRo8xFm6Ojo0X2WCtLYGAg\nuFxunZxCQUh9UFPTMWdkZIisg/e+KBIH0qCgILx58wajR48WWCrv9evXGDVqFN68eYN169ZJekip\nSZsmmhBS/aQZ2lcELx3ztm3byiwr7dQskTebXFxcBAKWlpYW9u/fj0OHDsHU1BR6enr48OED0tLS\nUFhYiLZt22LkyJGIjIyUqjGSqovz0AipL4T9/T59+hRPnz4VuY8s0jFraWmx739fBwCx9YjskUZH\nR+PKlSt8Xw8ePGAb8fz5c8TExOD58+fs3a8HDx7gypUrYk+qsiQmJsLFxQVqamowNDREQEAA+wva\nt28fuFwuXr58ybcP77JAaRs3bkTLli2hqqqKRo0aoUuXLggPD5fJORBSHwkbyjdv3hweHh7s1/da\ntWqFR48eCWxPTExkr2GK8uTJE2zfvh1aWlpo1KgRGjVqhJs3byI2NhZaWlrYvn07W0deXh6eP38u\nUAcAsfWI7JHW9GuQP/74I8aOHYsFCxYgIiICS5cuBZfLRUBAgNj9SveyDx06hNmzZyMgIAAODg7I\nyclBfHy8RNdcCCHSqanpmPv27QsFBQUcOnQI/v7+bPnQ0FC0adMGpqamIuuo8XntRRk/fjz8/PwA\nAD179sSXL1+wdu1azJgxQ+x+pYcVMTExaNu2LRYuXMhuc3Nzq5oGE0IASHdpbty4cdi8eTM8PT35\n0jE3adIEEyZMYMsJS8fs5OQkcDwNDQ0UFRXxpTjX1dXFzJkzsXLlSqirq6NDhw74/fffERUVhdOn\nT4ttX63NbzxkyBC+10OHDsXXr1+Fdv9FsbGxQVxcHKZPn45Lly4hOzu7sptJCPlOTU3HDADLly/H\nwoULsXHjRri5uSEmJgZ//PEH3N3dxR6v3D3Sly9f4sqVK3j79i3y8vKElindLa4q+vr6Ql//888/\nEh/Dx8cHubm52LNnD7Zu3QoFBQW4u7tj3bp1IrvxpWcsqKuro2HDhlK0npD6qyanY+ZyuViwYAEW\nLFhQrraVK5D6+voiODi4zIbKIpC+e/eOLz/U+/fvAQBGRkbsTabvV1X/9OmTwHHGjx+P8ePHIysr\nC+fPn8esWbMwdOhQkU9oGRkZVdYpEFIv1cVZNxIP7bdt24aNGzeiV69e7KfCyJEjceTIEUydOhWK\niooYOHBgmZP2K8vRo0f5XoeFhUFdXZ3vovDDhw/Z9wsLC3HhwgWRc1A1NDQwZMgQDB48uFyXBwgh\n5VOvczbt3r0bFhYW+OuvvyAnJwcAMDc3x9ChQzF06FAMHz4cTk5OGDhwYJU19vv2FBcXo3Pnzjh/\n/jz27NmDxYsXQ11dHTY2NrC0tMScOXNQXFwMRUVFbN26Ffn5+Xy/pPHjx6Nhw4awtbWFnp4ekpKS\nEBoaij59+sjkHAipj2r6jCBpSNwjffr0Kfr06cMGUQB8q6fY2trCw8MDa9eurdwWfod3kfjkyZO4\nePEiPD09cfjwYSxatIi9SycnJ4eTJ0/CxMQEo0aNwrRp09CnTx+MGjWKr0dqb2+Pe/fuYcqUKejd\nuzdWrFgBb29v7N+/v0rPgZD6rF73SOXk5KCurs6+VlNTE8ioaWFhgXPnzlVe64QICAhg54qKe4LK\n2tpa6GWG0vNMfXx84OPjU/mNJISIVBsDZVkkDqTGxsZsCmYAaNGiBa5evcpX5u7duyJXViGEEKCe\nD+2dnZ0RHR3Nvh46dCgeP36Mfv36YevWrRg+fDiuXLmC3r17V0lDCSF1Q70e2o8ZMwZFRUV49eoV\nTExMMH36dFy5cgXnzp1jh/OdO3cu83EtQkj9VhsDZVkkDqSdOnVCp06d2NdKSko4c+YM7ty5g+fP\nn8PU1BRdu3YVWBSEEEJKq4tD+wo/a9+lSxdKdkcIkVhd7JFS95EQIlOyTseclpYGT09PmJmZQVVV\nFbq6unB2dhaYYZSUlIRp06bB2toa6urqMDQ0hKenJ7t8qDjlWthZUlW9sDMhpPaSdTrmb9++QVdX\nF8uXL4exsTGysrKwa9cu9OvXD3/++Sd+/PFHAMCFCxcQFRWFMWPGoHPnzsjMzMSaNWtga2uL69ev\no2PHjiLrEBlIS9+hJ4SQyiLrdMzW1tbYvXs337Z+/frB3NwcISEhbCD9+eefMXXqVL5yrq6uMDMz\nw8aNG8U+qCNyaC9JXhVZ5FshhNQt0gztKyMdc2lycnJo2LAh35Oa2traAuUaNmyIZs2albmqXK1d\n2Lm6fJ+GQJY+fvxYbXVXNzU1tWqt38rKqlrrr0uk6WwlJCRgwIABAtutra3LXFqPh2EYFBUV4ePH\nj9i5cyeSk5OxceNGsftkZGTg0aNHGDt2rNhyFEgJITIlzdC+oumYgZKUzLwsxyoqKjh06BB69Ogh\ndp9p06aBw+GUmXmDAikhRKaqa/qTr68vhg8fjnfv3mH//v3w8vKCiooK+vXrJ7T8ypUrceTIEezd\nu5fvkoIwFEgJITIlbGj/4sULpKWlidynIumYeYyMjNiF2d3d3eHi4oLZs2cLDaTbt2/HggULsHz5\ncowaNarMY1MgJYTIlLAeqampKV96n2vXrvG9X5F0zKJ06tRJ6DXSgwcPYsqUKZg9ezbmzZsn0bFo\nQj4hRKakuWvfv39/xMbGIjU1ld3GS8fcv3//crehuLgY169fR9OmTfm2nzhxAmPGjMG4ceOwZs0a\niY9HPVJCiExJc9e+IumYAwMD8fnzZ3Tv3h0GBgZ49+4d9uzZg7t37+Lw4cPsvlevXsXPP/+Mdu3a\nYeTIkXx525SUlNChQweR7aNASgiRKWluNvHSMfv6+sLb2xsMw6Bnz57YsGFDmemYO3XqhA0bNiAs\nLAxZWVkwMDBA+/btce3aNXTr1o0tFxUVhfz8fNy/fx92dnZ89ZuZmSElJUVk+8oVSAsKCrBp0yaE\nhYXhyZMnyM7ORlFREQAgLi4OO3fuxIwZM9C8efPyHJYQUo/IOh2zh4cHPDw8yjx+6ewb5SVxIP32\n7Rt69uyJW7duQVdXFw0bNsS3b9/Y983NzbFv3z5oampixYoVUjWGEFL31evVn5YvX45bt25hzZo1\nePv2LcaNG8f3voaGBpycnHDhwoUKNSg8PBzr16+v0DGEGTVqFMzNzSv9uISQ8qmLK+RLHEiPHj0K\nV1dXzJ49W+Tizebm5nj58mWFGhQeHs4+fVCZ/P39ER4eXunHJYSUT11cr0Piof3r16/LzFmvpqaG\nrKysCjdKEnl5eVBSUpK4fFlPJhBCZKM29jjLInGPVENDA+/evRNb5tmzZ9DX15e6MaNGjcKBAwfw\n5s0bcLlccLlcmJubIzo6GlwuFydOnMC4ceOgq6sLAwMDtk5vb29YWFhAVVUVlpaWmDx5MjIzMwWO\nXXpo/+LFC3C5XOzcuRP+/v4wNDSElpYW+vfvjzdv3kh9DoQQ8eri0F7iHqmjoyPCw8Px7t07NoiV\nlpSUhLNnz2L48OFSN8bf3x8fP37EnTt3cPr0aQAl87d4QXHatGlwd3fHoUOHkJubCwB4+/YtjI2N\nsW7dOmhrayMlJQUrVqyAu7s7bt68yXd8YQtVr1y5EnZ2dggJCcH79+8xa9YseHl5ISoqSurzIISI\nVhuH7mWROJDOnz8fp06dgr29PVatWsUGt6SkJMTExGDevHmQk5ODn5+f1I2xsLCAjo4OFBUVYWNj\nw26/cuUKAKBr167YuXMn3z4ODg5wcHBgX3fr1g2WlpZwdHREXFwc2rdvz74n7JPO3NwcoaGh7Ov0\n9HTMmTNH5AcGIaRiamOPsywSB9IOHTogLCwMI0eOxJAhQ9jtvHUaGzRogN9//x0tW7as/Fb+P2Hr\nEebn5yMoKAgHDhzAy5cv2Z4qUBLkSwdSYdzd3flet27dGgDw8uVLoYE0JyeH/V5eXh4KCgrlOgdC\n6rt6HUiBkkDm4OCAAwcO4NatW8jIyEDDhg3RtWtXjB49Grq6ulXVTgBA48aNBbbNmzcPmzdvRkBA\nALp37w51dXW8evUKP/30E19QFeX7lWN4N7BE7auioiJFywkhPPV6aM+jo6ODmTNnVkVbyiTsGiev\nlzx//nx225cvX2TZLEJIOdT7HqksKCkp8Q2fy5KTkwN5ef7TCAkJEVpW2qyohJDKU68D6eLFiyUO\nRP7+/lI3qFWrVti1axe2b9+OTp06QVlZWWx5Nzc37N+/H23atIGlpSX+/PNPxMTECC1bF3+BhNQ2\n0g7tX716BV9fX1y6dIlv0RITExOx+925cwfbt2/HtWvX8ObNG+jo6MDBwQHLli2DmZmZyP3CwsIw\nfPhwGBkZ4dWrV2LrKFcglVRFAukvv/yC2NhYzJ8/H5mZmTAzM0NISIjIIB4cHAyGYbBgwQIAJWlW\njxw5wnfXHyjpjUr6QUA9V0KqjjQdmorktT969CgeP36MX3/9FW3atMGbN2+wdOlSdO7cGXFxcTA2\nNhbYJzMzEzNmzICBgYFE8UDiQBoZGSl0e1ZWFu7fv4+NGzeiZ8+eAnmhy0tVVZVvjUAe3ipT39PW\n1saRI0cEtn//qff9cF/YKjEA4OzsLLIuQkjFyTqvvZ+fn8CNcDs7O5ibm2PXrl1CO4l+fn7o0KED\nDAwMcOnSpTLbJ3EgdXZ2Fvmep6cnRowYgY4dO5b5GCkhpH6TZmhfVl57cYFU2GyiJk2aQFdXV2i+\n+hs3buDQoUN4+PAhlixZIlH7Ki3VSLNmzfDjjz9i9erVlXVIQkgdJM0jogkJCewc79Ksra2RmJhY\n7jY8fvwYHz58EJj3XlBQgPHjx8PPz69c63NU6l17PT09PHnypDIPSQipY6orrz1PYWEhJk6cCD09\nPYwdO5bvvdWrV6OgoEDipHc8lRZI8/LycP78eWhqalbWIQkhdZCwof27d+/w/v17mdQ/depUxMbG\n4syZM9DQ0GC3P3v2DCtWrEB4eDgUFRXZ7ZV6s2n//v1CD1hYWIjXr1+z6UemT58u6SEJIfWQsB6p\nvr4+38pxDx484Hu/MvLaA8DcuXOxa9c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+ "text": [ + "" + ] + } + ], + "prompt_number": 177 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For parametric models, it is particularly import to tune the parameters correctly. We use the grid_search function from sklearn to find the correct parameters for SVC." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "from sklearn.grid_search import GridSearchCV\n", + "from sklearn.metrics import classification_report" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 105 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "First, we do some coarse tuning on the parameters." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "tuned_parameters = [{'C': [0.01, 0.1, 1, 10, 100, 1000],\n", + " 'dual': [True, False],\n", + " 'class_weight' : [None, 'auto']}]\n", + "baseClf = svm.LinearSVC()\n", + "clf = GridSearchCV(baseClf, tuned_parameters, cv=5)\n", + "clf.fit(cleanedFeatureMatrix, cleanedResultVector)\n", + "clf.get_params\n", + "clf.best_estimator_" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "ename": "KeyboardInterrupt", + "evalue": "", + "output_type": "pyerr", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mbaseClf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msvm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mLinearSVC\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mclf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mGridSearchCV\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbaseClf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtuned_parameters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mclf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcleanedFeatureMatrix\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcleanedResultVector\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 7\u001b[0m \u001b[0mclf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_params\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mclf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbest_estimator_\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/Users/shankari/OSS/anaconda/lib/python2.7/site-packages/sklearn/grid_search.pyc\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, X, y, **params)\u001b[0m\n\u001b[1;32m 705\u001b[0m \u001b[0;34m\" The params argument will be removed in 0.15.\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 706\u001b[0m DeprecationWarning)\n\u001b[0;32m--> 707\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_fit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mParameterGrid\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparam_grid\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 708\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 709\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/Users/shankari/OSS/anaconda/lib/python2.7/site-packages/sklearn/grid_search.pyc\u001b[0m in \u001b[0;36m_fit\u001b[0;34m(self, X, y, parameter_iterable)\u001b[0m\n\u001b[1;32m 491\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbase_estimator\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtrain\u001b[0m\u001b[0;34m,\u001b[0m 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"\u001b[0;32m/Users/shankari/OSS/anaconda/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.pyc\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, func, args, kwargs)\u001b[0m\n\u001b[1;32m 134\u001b[0m \u001b[0;31m# Don't delay the application, to avoid keeping the input\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 135\u001b[0m \u001b[0;31m# arguments in memory\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 136\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 137\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 138\u001b[0m \u001b[0;32mdef\u001b[0m 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691\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclass_weight_\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 692\u001b[0;31m rnd.randint(np.iinfo('i').max))\n\u001b[0m\u001b[1;32m 693\u001b[0m \u001b[0;31m# Regarding rnd.randint(..) in the above signature:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 694\u001b[0m \u001b[0;31m# seed for srand in range [0..INT_MAX); due to limitations in Numpy\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " + ] + } + ], + "prompt_number": 106 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Then, we do some fine tuning around the result of the coarse parameter tuning." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "tuned_parameters = [{'C': range(75, 125, 5)}]\n", + "baseClf = svm.LinearSVC()\n", + "clf = GridSearchCV(baseClf, tuned_parameters, cv=5)\n", + "clf.fit(cleanedFeatureMatrix, cleanedResultVector)\n", + "print clf.get_params\n", + "print clf.best_estimator_\n", + "print clf.best_score_" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "LinearSVC(C=115, class_weight=None, dual=True, fit_intercept=True,\n", + " intercept_scaling=1, loss=l2, multi_class=ovr, penalty=l2,\n", + " random_state=None, tol=0.0001, verbose=0)\n", + "0.662789106336\n" + ] + } + ], + "prompt_number": 97 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "tuned_parameters = [{'C': range(55, 125, 5)}]\n", + "baseClf = svm.LinearSVC(dual=False)\n", + "clf = GridSearchCV(baseClf, tuned_parameters, cv=5)\n", + "clf.fit(cleanedFeatureMatrix, cleanedResultVector)\n", + "print clf.get_params\n", + "print clf.best_estimator_\n", + "print clf.best_score_" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "LinearSVC(C=80, class_weight=None, dual=False, fit_intercept=True,\n", + " intercept_scaling=1, loss=l2, multi_class=ovr, penalty=l2,\n", + " random_state=None, tol=0.0001, verbose=0)\n", + "0.751060626796\n" + ] + } + ], + "prompt_number": 99 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "tunedSvmClf = svm.LinearSVC(C=80, dual=False)\n", + "currCM, fig = printConfusionMatrix(tunedSvmClf, cleanedFeatureMatrix, cleanedResultVector, \"All features, SVM(C=80,dual=F)\")\n", + "fig.savefig(saveDir+\"cm_all_tuned_svm.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[[ 92. 1. 0. 0. 7. 0.]\n", + " [ 43. 7. 2. 1. 48. 0.]\n", + " [ 4. 3. 26. 2. 66. 0.]\n", + " [ 7. 1. 2. 14. 76. 0.]\n", + " [ 1. 1. 1. 1. 97. 0.]\n", + " [ 32. 0. 0. 0. 10. 58.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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Finz66afZJuVOS0tj2LBhTJo0SS1o50YEUkEQCpU+gfTp06fY2NhkW67LAH9V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\nsgXx8fFQq9WYPn06PDw88P3336NXr17w8fHp1Azn8fHxWLx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+ "text": [ + "" + ] + } + ], + "prompt_number": 178 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "from sklearn.kernel_approximation import Nystroem, AdditiveChi2Sampler, RBFSampler, SkewedChi2Sampler\n", + "from sklearn.linear_model import SGDClassifier\n", + "from sklearn.lda import LDA\n", + "from sklearn import preprocessing" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 110 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "rbf_feature = RBFSampler()\n", + "cleanedFeatureMatrix_features = rbf_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "sgdClf = SGDClassifier()\n", + "currCM, fig = printConfusionMatrix(sgdClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SGD w RBF kernel\")\n", + "fig.savefig(saveDir+\"cm_all_rbf_kernel_sgd.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 90. 1. 1. 2. 7. 0.]\n", + " [ 37. 39. 2. 3. 18. 0.]\n", + " [ 42. 8. 16. 5. 29. 0.]\n", + " [ 39. 1. 3. 13. 44. 0.]\n", + " [ 20. 3. 1. 3. 73. 0.]\n", + " [ 66. 7. 4. 7. 17. 0.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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AXFxcgIy1IpKTk9XauXjxYi5fvsyePXuwtbXVWoe4jzQXND0nnRtBQUG4ubnl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\nQmCC\n", + "text": [ + "" + ] + } + ], + "prompt_number": 179 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "rbf_feature = RBFSampler(gamma=1)\n", + "cleanedFeatureMatrix_features = rbf_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "sgdClf = SGDClassifier()\n", + "printConfusionMatrix(sgdClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SGD w RBF kernel (gamma=1)\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 94. 1. 1. 1. 3. 0.]\n", + " [ 41. 51. 1. 2. 5. 0.]\n", + " [ 70. 9. 7. 4. 10. 0.]\n", + " [ 67. 4. 1. 6. 22. 0.]\n", + " [ 48. 4. 1. 2. 45. 0.]\n", + " [ 97. 0. 0. 0. 3. 0.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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NmhqPi9M3NGTIEDZv3szZs2fp1q0b1apVo2/fvsTGFrydcHmSlJSEQqHAxsZG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\nRo0axb/29vaGk5MTRo8ejf/85z/8Lw4g/odhZWWFb7/9tkf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+ "text": [ + "" + ] + }, + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 180, + "text": [ + "(array([[ 1., 0., 0., 0., 0., 0.],\n", + " [ 0., 1., 0., 0., 0., 0.],\n", + " [ 1., 0., 0., 0., 0., 0.],\n", + " [ 1., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.],\n", + " [ 1., 0., 0., 0., 0., 0.]]),\n", + " )" + ] + } + ], + "prompt_number": 180 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "rbf_feature = RBFSampler()\n", + "cleanedFeatureMatrix_features = rbf_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "ldaClf = LDA()\n", + "currCM, fig = printConfusionMatrix(ldaClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, LDA w RBF kernel\")\n", + "fig.savefig(saveDir+\"cm_all_rbf_kernel_lda.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[[ 85. 3. 1. 1. 9. 0.]\n", + " [ 28. 57. 4. 0. 10. 0.]\n", + " [ 30. 11. 39. 1. 20. 1.]\n", + " [ 44. 5. 2. 10. 39. 0.]\n", + " [ 19. 5. 4. 2. 70. 0.]\n", + " [ 57. 0. 7. 4. 21. 11.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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QvHlzatWqRYcOHQgODsbOzo7Hjx/j7e0N5Myh/ve//2Xq1Kn06NEDS0tLsrKy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\n", + "text": [ + "" + ] + } + ], + "prompt_number": 181 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "rbf_feature = RBFSampler()\n", + "cleanedFeatureMatrix_features = rbf_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "linearSVMClf = svm.LinearSVC()\n", + "currCM, fig = printConfusionMatrix(linearSVMClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SVM w RBF kernel\")\n", + "fig.savefig(saveDir+\"cm_all_rbf_kernel_svm.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[[ 88. 2. 1. 0. 9. 0.]\n", + " [ 29. 56. 0. 0. 15. 0.]\n", + " [ 45. 6. 12. 0. 37. 0.]\n", + " [ 31. 6. 1. 2. 59. 0.]\n", + " [ 14. 3. 1. 0. 81. 0.]\n", + " [ 71. 18. 4. 0. 7. 0.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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AGjVqEBsbS3R0dJ55l8pAmpKSwqlTp/jzzz9p1qwZ1atXp3379gQHB2Nvb8+T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\niQMpY4xZiQMpY4xZiQMpY4xZ6X+PUYbU1XtBFQAAAABJRU5ErkJggg==\n", + "text": [ + "" + ] + } + ], + "prompt_number": 182 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "nys_feature = Nystroem(kernel='polynomial')\n", + "cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "sgdClf = SGDClassifier()\n", + "currCM, fig = printConfusionMatrix(sgdClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SGD w poly kernel\")\n", + "fig.savefig(saveDir+\"cm_all_poly_kernel_sgd.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[[ 89. 2. 0. 1. 7. 0.]\n", + " [ 7. 75. 2. 3. 13. 0.]\n", + " [ 4. 17. 42. 5. 32. 0.]\n", + " [ 4. 3. 6. 30. 57. 0.]\n", + " [ 1. 5. 3. 3. 86. 1.]\n", + " [ 39. 7. 0. 4. 7. 44.]]\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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w9vYmNDSU5ORkwsPDiYuLY+rUqSgUCk6dOgVkBFJvb2/pnHXr1lGvXj0sLCww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\njuM4K/FEynEcZ6X/Ab4qFU8ak4BwAAAAAElFTkSuQmCC\n", + "text": [ + "" + ] + } + ], + "prompt_number": 183 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "nys_feature = Nystroem(kernel='polynomial')\n", + "cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "ldaClf = LDA()\n", + "currCM, fig = printConfusionMatrix(ldaClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, LDA w poly kernel\")\n", + "fig.savefig(saveDir+\"cm_all_poly_kernel_lda.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[[ 92. 2. 0. 1. 5. 0.]\n", + " [ 2. 83. 4. 1. 9. 0.]\n", + " [ 2. 7. 62. 5. 24. 0.]\n", + " [ 3. 1. 7. 47. 43. 0.]\n", + " [ 1. 2. 3. 4. 90. 0.]\n", + " [ 22. 3. 0. 13. 3. 58.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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BQYwfPx5vb28UCgVt2rRh1apVKvtzFQoFqampGdqYNWsWpqam/PjjjyxbtoyK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\n", + "text": [ + "" + ] + } + ], + "prompt_number": 184 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "nys_feature = Nystroem(kernel='polynomial')\n", + "cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "svmClf = svm.LinearSVC()\n", + "currCM, fig = printConfusionMatrix(svmClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SVM w poly kernel\")\n", + "fig.savefig(saveDir+\"cm_all_poly_kernel_svm.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[[ 93. 1. 0. 0. 5. 0.]\n", + " [ 3. 85. 1. 1. 11. 0.]\n", + " [ 3. 3. 60. 3. 31. 0.]\n", + " [ 4. 1. 7. 34. 53. 0.]\n", + " [ 1. 1. 3. 1. 94. 0.]\n", + " [ 11. 3. 7. 0. 10. 69.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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LmuiZ8/v5b/q/XLh7AYD/NdG9NgpgYWTB/oH7cbZyRqlUMmLPCOmhh8L8jZQ01e/2s4xn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\n", + "text": [ + "" + ] + } + ], + "prompt_number": 185 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "nys_feature = Nystroem(kernel='sigmoid')\n", + "cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "sgdClf = SGDClassifier()\n", + "currCM, fig = printConfusionMatrix(sgdClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SGD w sigmoid kernel\")\n", + "fig.savefig(saveDir+\"cm_all_sigmoid_kernel_sgd.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 90. 2. 0. 0. 8. 0.]\n", + " [ 5. 75. 2. 1. 17. 0.]\n", + " [ 3. 22. 34. 2. 39. 0.]\n", + " [ 5. 5. 4. 31. 54. 0.]\n", + " [ 1. 14. 2. 4. 80. 0.]\n", + " [ 33. 7. 3. 0. 17. 41.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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IRdMYqq2ZLf/8+w+lDEsR+3+xWX6veSFXGunLpJfs+/u/yYZ3JbyK5LRkyfwvSBpXbCwJ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\nxMLCAmKxGBUVFbh37x7vO8YYrl692qu+q6NIIBcSEqLyXU/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+ "text": [ + "" + ] + } + ], + "prompt_number": 186 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "nys_feature = Nystroem(kernel='sigmoid')\n", + "cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "ldaClf = LDA()\n", + "currCM, fig = printConfusionMatrix(ldaClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, LDA w sigmoid kernel\")\n", + "fig.savefig(saveDir+\"cm_all_sigmoid_kernel_lda.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[[ 92. 2. 0. 1. 4. 0.]\n", + " [ 2. 82. 5. 2. 9. 0.]\n", + " [ 2. 16. 58. 3. 21. 0.]\n", + " [ 3. 2. 7. 47. 42. 0.]\n", + " [ 1. 3. 3. 3. 91. 0.]\n", + " [ 11. 3. 3. 0. 0. 82.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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4cUJjGUtLS7WaZ3x8POXLl9fantIpevv27VXS27dvz+TJk4mKisLZ2ZkxY8bg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\nueHKlSsoLy9HdXU1rl27BqVSCYVCgQ0bNiApKQl6vR7Tpk2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+ "text": [ + "" + ] + } + ], + "prompt_number": 187 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "nys_feature = Nystroem(kernel='sigmoid')\n", + "cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "svmClf = svm.LinearSVC()\n", + "currCM, fig = printConfusionMatrix(svmClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SVM w poly kernel\")\n", + "fig.savefig(saveDir+\"cm_all_sigmoid_kernel_svm.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[[ 93. 1. 0. 0. 5. 0.]\n", + " [ 4. 83. 1. 1. 11. 0.]\n", + " [ 3. 6. 58. 2. 31. 0.]\n", + " [ 4. 1. 7. 39. 50. 0.]\n", + " [ 1. 1. 3. 0. 95. 0.]\n", + " [ 15. 10. 4. 0. 3. 68.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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51vWVZ+bv578p/3L+/nkAPm+oe2sUwMLIgr199lLdujpKpZLBOwdLDz3k5W+ksKl+t1+k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\nNWpIryEzqWZWqhn9r169qrWOMhlIXV1dpXvHtFF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+ "text": [ + "" + ] + } + ], + "prompt_number": 188 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "# nys_feature = Nystroem(kernel='chi2')\n", + "# cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "# sgdClf = SGDClassifier()\n", + "# printConfusionMatrix(sgdClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SGD w sigmoid kernel\")" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 286 + }, + { + "cell_type": "heading", + "level": 3, + "metadata": {}, + "source": [ + "Only for transport trips" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As we can see, the prediction rate is best for walk and bike, which are the ones for which we get the most data from moves. It may be a mistake to use the same model for both types of trips because moves will do a good job for walk/bike and a horrible job for transport, because we don't allow users to specify 'transport' in the output.\n", + "\n", + "These also have zero carbon footprint. Let us see how well we do on the motorized trips alone." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "transportTrips = cleanedFeatureMatrix[:,2] == 4\n", + "print np.count_nonzero(transportTrips)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "3280\n" + ] + } + ], + "prompt_number": 108 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "printConfusionMatrix(forestClf, genericCleanedFM[transportTrips], cleanedResultVector[transportTrips], \"Generic features, motorized only, random forest\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "[[ 35. 6. 6. 1. 51. 1.]\n", + " [ 8. 22. 21. 2. 47. 0.]\n", + " [ 6. 7. 35. 3. 50. 0.]\n", + " [ 3. 1. 3. 38. 55. 0.]\n", + " [ 2. 2. 5. 3. 89. 0.]\n", + " [ 13. 0. 0. 7. 5. 75.]]\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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EEMLApEUrhBAGJolWCCEMzFQSbfUdiVyGnj17EhkZCVDtJlIRQjwciqKU+2FM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\nCGFg0qIVQggDk0QrhBAGZiqJtlrfblw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+ "text": [ + "" + ] + }, + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 109, + "text": [ + "(array([[ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 0., 1.]]),\n", + " )" + ] + } + ], + "prompt_number": 109 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "printConfusionMatrix(forestClf, cleanedFeatureMatrix[transportTrips], cleanedResultVector[transportTrips], \"All features, transport only, random forest\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "[[ 32. 5. 10. 1. 50. 1.]\n", + " [ 8. 41. 7. 1. 43. 0.]\n", + " [ 6. 1. 76. 1. 16. 0.]\n", + " [ 2. 1. 3. 68. 27. 0.]\n", + " [ 2. 1. 3. 1. 92. 0.]\n", + " [ 0. 0. 5. 5. 22. 68.]]\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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Mrl270qFDB+Li4khOTsbW1pY5c+aQkJBAo0aNGD16NLm5ueXWERQURGxsLKGh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\np6cbVMbBwYGXX36Zli1b0qJFCxo3bsx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+ "text": [ + "" + ] + }, + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 110, + "text": [ + "(array([[ 0., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 1., 0., 0., 0.],\n", + " [ 0., 0., 0., 1., 0., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 0., 1.]]),\n", + " )" + ] + } + ], + "prompt_number": 110 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "knnClf = neighbors.KNeighborsClassifier()\n", + "printConfusionMatrix(knnClf, genericCleanedFM[transportTrips], cleanedResultVector[transportTrips], \"Generic features, transport only, k-nn\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "[[ 31. 5. 10. 2. 50. 1.]\n", + " [ 19. 15. 22. 0. 44. 0.]\n", + " [ 8. 6. 31. 3. 53. 0.]\n", + " [ 1. 1. 5. 25. 68. 0.]\n", + " [ 2. 2. 6. 4. 85. 0.]\n", + " [ 0. 0. 0. 5. 48. 47.]]\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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iFUIIjVlKYrWq6ACEEMJciqKY9WdKeHg4LVq0wNPTk5kzZ5a6joMHD2JjY8O6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\nMsukpqai1+u5devWbeuWoAghxAPu1q1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+ "text": [ + "" + ] + }, + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 111, + "text": [ + "(array([[ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.]]),\n", + " )" + ] + } + ], + "prompt_number": 111 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "knnClf = neighbors.KNeighborsClassifier()\n", + "printConfusionMatrix(knnClf, cleanedFeatureMatrix[transportTrips], cleanedResultVector[transportTrips], \"All features, transport only, k-nn\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "[[ 33. 6. 10. 1. 48. 1.]\n", + " [ 19. 16. 20. 0. 45. 0.]\n", + " [ 7. 6. 31. 3. 52. 0.]\n", + " [ 1. 1. 5. 25. 69. 0.]\n", + " [ 2. 2. 6. 4. 85. 0.]\n", + " [ 0. 0. 0. 5. 48. 47.]]\n" + ] + }, + { + "metadata": {}, + "output_type": 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NCli3bh1+fn74+/szZMgQWrZsSW5uLgAZGRm0bNkSo9FIUlISjzzyCP7+/nTs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\nqxBCaOz/AePZCAVQoNGsAAAAAElFTkSuQmCC\n", + "text": [ + "" + ] + }, + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 112, + "text": [ + "(array([[ 0., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.]]),\n", + " )" + ] + } + ], + "prompt_number": 112 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As we can see, we are actually able to predict car trips with a fair degree of accuracy. But bus and train trips are pretty much a tossup. Ignore the entries for 0 and 1 above, since we stripped out all walk and bike trips, and so these are only trips which moves misclassified, and not the entire dataset. Now we know why the Zheng paper only attempted to distinguish between bus and car trips, and not bus, train and car. The new features helped in the decision tree case, but not by that much, and did not help us at all in the knn case." + ] + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "User-specific models" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "def getUserModelComparison(isTransportOnly):\n", + " userIds = Sections.distinct(\"user_id\")\n", + "\n", + " # I'm not going to bother with testing against only the generic features\n", + " # because the main issue here is personalization\n", + "\n", + " userIdList = []\n", + " numberOfSections = []\n", + " percentWalkBikeSections = []\n", + " percentAutoClassified = []\n", + " percentAutoClassifiedWalk = []\n", + " percentAutoClassifiedBike = []\n", + " percentAutoClassifiedBus = []\n", + " percentAutoClassifiedTrain = []\n", + " percentAutoClassifiedCar = []\n", + " autoClassifiedAccuracy = []\n", + " overallAccuracy = []\n", + "\n", + " labels = [\"Number of sections\", \"% walk+bike trips\",\n", + " \"% autoclassified\", \"% auto classified walk\",\n", + " \"% auto classified bike\", \"% auto classified bus\",\n", + " \"% auto classified train\", \"% auto classified car\",\n", + " \"auto classified accuracy\", \"overall accuracy\"]\n", + " \n", + " for userId in userIds:\n", + " # decision tree with all features\n", + " if not isTransportOnly:\n", + " query = {\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, {'user_id': userId}]}\n", + " else:\n", + " query = {\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, {'mode': 4}, {'user_id': userId}]}\n", + " \n", + " wbQuery = {\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$in': ['1', '3', '7']}}, {'user_id': userId}]}\n", + " walkBikeTripCount = Sections.find(wbQuery).count()\n", + " (userFeatureMatrix, userResultVector) = generateFeatureMatrixAndResultVector(query)\n", + " \n", + " # we only focus on users who have enough history with us\n", + " if len(userResultVector) < 150:\n", + " print(\"Skipping user with userId %s who has %s unconfirmed sections\" % (userId, len(userResultVector)))\n", + " continue\n", + " \n", + " forestClf = ensemble.RandomForestClassifier()\n", + " # printConfusionMatrix(forestClf, userFeatureMatrix, userResultVector)\n", + " (pac5, pacm5, hcs5, s5) = kFoldValidationWithProb(forestClf, userFeatureMatrix, userResultVector, 5, 0.95)\n", + " userIdList.append(userId)\n", + " \n", + " numberOfSections.append(len(userResultVector))\n", + " percentWalkBikeSections.append(float(walkBikeTripCount)/len(userResultVector))\n", + " percentAutoClassified.append(pac5.mean())\n", + " percentAutoClassifiedWalk.append(pacm5[0].mean())\n", + " percentAutoClassifiedBike.append(pacm5[1].mean())\n", + " percentAutoClassifiedBus.append(pacm5[2].mean())\n", + " percentAutoClassifiedTrain.append(pacm5[3].mean())\n", + " percentAutoClassifiedCar.append(pacm5[4].mean())\n", + " autoClassifiedAccuracy.append(hcs5.mean())\n", + " overallAccuracy.append(s5.mean())\n", + " resultArray = np.array([numberOfSections, percentAutoClassified, percentAutoClassifiedWalk,\n", + " percentAutoClassifiedBike, percentAutoClassifiedBus, percentAutoClassifiedTrain,\n", + " percentAutoClassifiedCar, autoClassifiedAccuracy, overallAccuracy])\n", + " print resultArray.shape\n", + " return (userIdList, resultArray, labels)" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 227 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "import displayHelpers" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 228 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "def displayUserVariation(userIds, ra, labels):\n", + " ''' ra has rows = plots and cols = users\n", + " '''\n", + " fig, (axes, axesNum) = plt.subplots(2, 1, figsize=(25, 25))\n", + " nUsers = len(userIds)\n", + " \n", + " for i in [1,-2,-1]:\n", + " # each row is one plot\n", + " print ra[i]\n", + " axes.plot(np.arange(nUsers), ra[i], linewidth=2, label=labels[i])\n", + " axes.legend(loc='best')\n", + " for i in [0]:\n", + " # each row is one plot\n", + " print ra[i]\n", + " axesNum.plot(np.arange(nUsers), ra[i], linewidth=2, label=labels[i]) \n", + " axesNum.legend(loc='best')" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 230 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "(userIds, userResultArray, labels) = getUserModelComparison(isTransportOnly=False)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Found 71 high confidence predictions out of 93\n", + "Found 70 high confidence predictions out of 93\n", + "Found 70 high confidence predictions out of 93\n", + "Found 68 high confidence predictions out of 93\n", + "Found 58 high confidence predictions out of 93\n", + "for prob 0.95, percentage auto classified 0.724731182796" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, scoring only on high confidence predictions 0.997058823529\n", + "for prob 0.95, scoring on all predictions 0.954838709677\n", + "Skipping user with userId 6a488797-5be1-38aa-9700-5532be978ff9 who has 92 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId acd105e3-b221-35c5-81ac-fee5ffe9de66 who has 89 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 34 high confidence predictions out of 90" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 28 high confidence predictions out of 89\n", + "Found 30 high confidence predictions out of 89\n", + "Found 28 high confidence predictions out of 89" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 31 high confidence predictions out of 89\n", + "for prob 0.95, percentage auto classified 0.33847690387\n", + "for prob 0.95, scoring only on high confidence predictions 0.993333333333\n", + "for prob 0.95, scoring on all predictions 0.831810237203\n", + "Skipping user with userId 7327a0b3-4959-31f5-86cb-ea0c59fd0c83 who has 8 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 26 high confidence predictions out of 61" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 30 high confidence predictions out of 60\n", + "Found 29 high confidence predictions out of 60\n", + "Found 27 high confidence predictions out of 60\n", + "Found 20 high confidence predictions out of 60\n", + "for prob 0.95, percentage auto classified 0.438579234973\n", + "for prob 0.95, scoring only on high confidence predictions 0.992307692308\n", + "for prob 0.95, scoring on all predictions 0.84393442623\n", + "Skipping user with userId adaa57a8-7fb8-3389-acce-db50ddc9e2dd who has 24 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId ed8ca6a2-9092-37af-adde-46e51a18a310 who has 128 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId f8fee20c-0f32-359d-ba75-bce97a7ac83b who has 137 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId fb457463-9a06-3c84-947d-db1fefb5a199 who has 0 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 40 high confidence predictions out of 76" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 38 high confidence predictions out of 76\n", + "Found 40 high confidence predictions out of 75\n", + "Found 41 high confidence predictions out of 75\n", + "Found 42 high confidence predictions out of 75" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.533263157895\n", + "for prob 0.95, scoring only on high confidence predictions 1.0\n", + "for prob 0.95, scoring on all predictions 0.915052631579\n", + "Skipping user with userId 5322f635-a82c-3677-a1a4-5c26804a90b7 who has 83 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 560a0ea4-fcdf-3c1b-adf0-22d2b79af3ea who has 5 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 38 high confidence predictions out of 89" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 42 high confidence predictions out of 89\n", + "Found 46 high confidence predictions out of 89\n", + "Found 45 high confidence predictions out of 89\n", + "Found 44 high confidence predictions out of 88" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.484269662921\n", + "for prob 0.95, scoring only on high confidence predictions 0.995652173913\n", + "for prob 0.95, scoring on all predictions 0.90771195097\n", + "Found 33 high confidence predictions out of 57" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 31 high confidence predictions out of 57\n", + "Found 18 high confidence predictions out of 57\n", + "Found 42 high confidence predictions out of 57\n", + "Found 37 high confidence predictions out of 57\n", + "for prob 0.95, percentage auto classified 0.564912280702\n", + "for prob 0.95, scoring only on high confidence predictions 0.981818181818\n", + "for prob 0.95, scoring on all predictions 0.978947368421\n", + "Found 23 high confidence predictions out of 56" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 27 high confidence predictions out of 56\n", + "Found 27 high confidence predictions out of 56\n", + "Found 29 high confidence predictions out of 56\n", + "Found 28 high confidence predictions out of 55\n", + "for prob 0.95, percentage auto classified 0.48038961039\n", + "for prob 0.95, scoring only on high confidence predictions 0.977777777778\n", + "for prob 0.95, scoring on all predictions 0.889025974026\n", + "Skipping user with userId e0509a4e-9842-3c73-8050-875b6383c097 who has 112 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId e1a99120-9a5a-31ae-9d7a-93b9a3e0c51c who has 32 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId e211dd91-423f-31ff-a1f8-89e5fdecc164 who has 148 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId ea3f7719-f4a3-36fd-9477-924114cfe0bd who has 18 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId ff860db0-f3fe-387c-a005-c5837f5ba970 who has 0 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 25 high confidence predictions out of 60" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 23 high confidence predictions out of 59\n", + "Found 25 high confidence predictions out of 59\n", + "Found 28 high confidence predictions out of 59\n", + "Found 25 high confidence predictions out of 59\n", + "for prob 0.95, percentage auto classified 0.425706214689" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, scoring only on high confidence predictions 0.992\n", + "for prob 0.95, scoring on all predictions 0.885310734463\n", + "Found 26 high confidence predictions out of 61" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 28 high confidence predictions out of 61\n", + "Found 28 high confidence predictions out of 61\n", + "Found 24 high confidence predictions out of 61\n", + "Found 27 high confidence predictions out of 60" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.437540983607\n", + "for prob 0.95, scoring only on high confidence predictions 0.962016687017\n", + "for prob 0.95, scoring on all predictions 0.85825136612\n", + "Skipping user with userId 3c1f13e8-b063-3d6c-a1eb-8fd39b874110 who has 28 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 6dbe9b5a-26a1-31d0-aeb6-7b08ffa49b10 who has 0 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 7a88d272-3b9e-3d18-9749-57ddb6214440 who has 0 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 45 high confidence predictions out of 58" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 41 high confidence predictions out of 58\n", + "Found 39 high confidence predictions out of 57\n", + "Found 40 high confidence predictions out of 57\n", + "Found 35 high confidence predictions out of 57\n", + "for prob 0.95, percentage auto classified 0.696551724138\n", + "for prob 0.95, scoring only on high confidence predictions 0.97635501355\n", + "for prob 0.95, scoring on all predictions 0.9444646098\n", + "Skipping user with userId 8d235d9c-7af6-3132-ba91-626e40181449 who has 16 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 8d718272-c46c-3e24-8bae-9696917deeec who has 28 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 8e230f78-6e37-3588-bf2c-6888a5b63c82 who has 43 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 951779de-a10c-3373-b186-c1c9b14b5e38 who has 3 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 48 high confidence predictions out of 87" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 55 high confidence predictions out of 87\n", + "Found 53 high confidence predictions out of 87\n", + "Found 46 high confidence predictions out of 86\n", + "Found 51 high confidence predictions out of 86" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.584202085004\n", + "for prob 0.95, scoring only on high confidence predictions 0.98784914361\n", + "for prob 0.95, scoring on all predictions 0.8983159583\n", + "Skipping user with userId 9cc9d577-3a22-3659-8cd5-9142936f44ec who has 29 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId a1a10092-0136-37f1-8109-9ebf47ef72b2 who has 8 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId b3b9fe85-d510-3e5b-bec2-031ca9da7c83 who has 0 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId bbd4e1ad-bd2d-3126-a58c-2c2fe1895fba who has 0 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId bcbefbfc-8021-353f-9f5c-648d539c8cff who has 5 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 19 high confidence predictions out of 34" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 18 high confidence predictions out of 34\n", + "Found 17 high confidence predictions out of 34\n", + "Found 18 high confidence predictions out of 34\n", + "Found 20 high confidence predictions out of 34\n", + "for prob 0.95, percentage auto classified 0.541176470588\n", + "for prob 0.95, scoring only on high confidence predictions 1.0\n", + "for prob 0.95, scoring on all predictions 0.882352941176\n", + "Found 17 high confidence predictions out of 53" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 14 high confidence predictions out of 52\n", + "Found 22 high confidence predictions out of 52\n", + "Found 24 high confidence predictions out of 52\n", + "Found 22 high confidence predictions out of 52\n", + "for prob 0.95, percentage auto classified 0.379535558781\n", + "for prob 0.95, scoring only on high confidence predictions 0.976623376623\n", + "for prob 0.95, scoring on all predictions 0.827721335269\n", + "Found 16 high confidence predictions out of 98" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 17 high confidence predictions out of 98\n", + "Found 17 high confidence predictions out of 98\n", + "Found 17 high confidence predictions out of 97" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 17 high confidence predictions out of 97\n", + "for prob 0.95, percentage auto classified 0.17214390911\n", + "for prob 0.95, scoring only on high confidence predictions 0.976470588235\n", + "for prob 0.95, scoring on all predictions 0.741826215022\n", + "Skipping user with userId d8a6b737-b6a5-3fc7-a144-76ac2d434252 who has 28 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 04a9dec3-5a20-38ef-85b7-414dc7a2cf4e who has 0 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 27 high confidence predictions out of 33" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 25 high confidence predictions out of 33\n", + "Found 31 high confidence predictions out of 33\n", + "Found 30 high confidence predictions out of 32\n", + "Found 30 high confidence predictions out of 32\n", + "for prob 0.95, percentage auto classified 0.87803030303\n", + "for prob 0.95, scoring only on high confidence predictions 0.985925925926\n", + "for prob 0.95, scoring on all predictions 0.981439393939\n", + "Found 10 high confidence predictions out of 33" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 17 high confidence predictions out of 33\n", + "Found 14 high confidence predictions out of 33\n", + "Found 15 high confidence predictions out of 33\n", + "Found 21 high confidence predictions out of 32\n", + "for prob 0.95, percentage auto classified 0.470643939394\n", + "for prob 0.95, scoring only on high confidence predictions 0.990476190476\n", + "for prob 0.95, scoring on all predictions 0.835416666667\n", + "Found 23 high confidence predictions out of 31" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 26 high confidence predictions out of 31\n", + "Found 21 high confidence predictions out of 31\n", + "Found 24 high confidence predictions out of 31\n", + "Found 25 high confidence predictions out of 31\n", + "for prob 0.95, percentage auto classified 0.767741935484\n", + "for prob 0.95, scoring only on high confidence predictions 0.991666666667\n", + "for prob 0.95, scoring on all predictions 0.974193548387\n", + "Skipping user with userId 2491630e-bb62-39c2-8349-df4dad434dee who has 103 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 18 high confidence predictions out of 41" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 25 high confidence predictions out of 40\n", + "Found 30 high confidence predictions out of 40\n", + "Found 22 high confidence predictions out of 40\n", + "Found 21 high confidence predictions out of 40\n", + "for prob 0.95, percentage auto classified 0.577804878049\n", + "for prob 0.95, scoring only on high confidence predictions 0.984\n", + "for prob 0.95, scoring on all predictions 0.845853658537\n", + "Found 43 high confidence predictions out of 69" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 45 high confidence predictions out of 69\n", + "Found 41 high confidence predictions out of 68\n", + "Found 51 high confidence predictions out of 68\n", + "Found 41 high confidence predictions out of 68\n", + "for prob 0.95, percentage auto classified 0.646248934356" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, scoring only on high confidence predictions 0.967697515005\n", + "for prob 0.95, scoring on all predictions 0.918201193521\n", + "Skipping user with userId 399ed209-2e4e-37fc-a6ac-37c25f7ee1f2 who has 114 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 01477d94-e0bb-3903-a428-338551801391 who has 64 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 14 high confidence predictions out of 43" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 10 high confidence predictions out of 42\n", + "Found 12 high confidence predictions out of 42\n", + "Found 14 high confidence predictions out of 42\n", + "Found 18 high confidence predictions out of 42\n", + "for prob 0.95, percentage auto classified 0.322259136213\n", + "for prob 0.95, scoring only on high confidence predictions 0.985714285714\n", + "for prob 0.95, scoring on all predictions 0.815503875969\n", + "Skipping user with userId 1a65368b-888e-3e77-8f7c-1128f16da1df who has 22 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "(9, 20)\n" + ] + } + ], + "prompt_number": 231 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "displayUserVariation(userResultArray, labels)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "[ 1. 0. 0. 0. 0. 1. 0. 0. 1. 1. 1. 1. 0. 0. 1. 0. 1. 1.\n", + " 1. 0.]\n", + "[ 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.\n", + " 1. 1.]\n", + "[ 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.\n", + " 1. 1.]\n", + "[ 465. 446. 301. 377. 444. 285. 279. 296. 304. 287. 433. 170.\n", + " 261. 488. 163. 164. 155. 201. 342. 211.]\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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QWLmSZq/t3Vu5r7l7lwoAsrOpJ+9HH2l3jEz7UlOpaj0hAfjgA2D5cu3ub8YM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DzTVv2AAAgs2pQNu2ze4cgA3OdnOvXrX/VFpdUakBAIB7ETi7HIEzIs3p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5vd5YYbzDUnRzp92m6WcEXhDAAAAKCB+oVzTY3dLE6wZo1UUiJdfLE0aZLtNHCTuDgpOloq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\npWnJkiXq3Llzg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+ "text": [ + "" + ] + } + ], + "prompt_number": 116 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "reload(displayHelpers)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 307, + "text": [ + "" + ] + } + ], + "prompt_number": 307 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "selIndices = [2, -2, -1, 1]\n", + "mpl.rcParams['font.size'] = 16\n", + "fig, axes = displayHelpers.showCategoryChart(np.arange(len(userIds)), np.multiply([userResultArray[i] for i in selIndices], 100), [labels[i] for i in selIndices],\n", + " ['b', 'g', 'c', 'm', 'y', 'k', 'w'],\n", + " \"Percentage\",\n", + " \"Accuracy of various predictions\",\n", + " figsize=(12,5), width=0.2)\n", + "ax2 = axes.twinx()\n", + "# ax2.bar(np.arange(len(userResultArray[0])) + 3 * 0.2, userResultArray[0], 0.2, color = 'c')\n", + "nSecLine, = ax2.plot(userResultArray[0], 'r-+', linewidth=2, label=\"Number of confirmed sections\")\n", + "axes.set_ylim(top=115)\n", + "axes.axhline(98, linewidth=2, label = \"98%\")\n", + "axes.axhline(85, linewidth=2, label = \"85%\")\n", + "axes.text(x=15.5, y=98.5, s=\"98%\")\n", + "axes.text(x=15.5, y=85.5, s=\"85%\")\n", + "axes.get_legend().set_bbox_to_anchor((0.4, -0.1))\n", + "print axes.get_legend_handles_labels()\n", + "ax2.legend([nSecLine], [\"Number of sections\"], loc=\"upper right\", framealpha=0.3, bbox_to_anchor=(1, -0.1))\n", + "ax2.set_ylabel(\"Count (number of sections)\")\n", + "axes.set_xlabel(\"Users\")\n", + "ax2.set_ylim(bottom=0)\n", + "fig.show()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "20\n", + "([, ], ['98%', '85%'])" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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ZAjdvwh9/wIcfQvXq6oija9ZAt25QogS89pr68717pg5bkiRJklTGGmQDKIqs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\nEAhjK+UKDfzf2/D++2xrvwh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JEyQmJjJ27FjCwsKoXr16trYnE4oCQNuFLMuWFd6Gjz/+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\nG6Z1TatWrejZsyf79+9nzZo1VFRU6Cx3AvD19QXuL3fR9216T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+ "text": [ + "" + ] + } + ], + "prompt_number": 407 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let us pick users with really high accuracy. Unfortunately, they also have the least confirmed sections. Let us see whether this is because they are heavy walkers or otherwise." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "userIds[5], userIds[6], userIds[2]" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 397, + "text": [ + "(UUID('a47da5c4-3ced-34ac-af25-6c3aa7998827'),\n", + " UUID('b0d937d0-70ef-305e-9563-440369012b39'),\n", + " UUID('89e30222-b446-30ad-852c-b305ddafe70d'))" + ] + } + ], + "prompt_number": 397 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "for i in [2,5,6]:\n", + " userId = userIds[i]\n", + " query = {\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, {'user_id': userId}]}\n", + " (userFeatureMatrix, userResultVector) = generateFeatureMatrixAndResultVector(query)\n", + " indicesToStrip = (userResultVector == 2) | (userResultVector == 4) | (userResultVector == 8)\n", + " for mode in [1,3,5,6,7,9]:\n", + " # nFolds = 5\n", + " if np.count_nonzero(userResultVector == mode) <= 10:\n", + " print \"number of instances of mode %s = %s\" % (mode, np.count_nonzero(userResultVector == mode))\n", + " indicesToStrip = indicesToStrip | (userResultVector == mode)\n", + " userStrippedIndices = np.logical_not(indicesToStrip)\n", + " strippedUserFeatureMatrix = userFeatureMatrix[userStrippedIndices]\n", + " strippedUserResultVector = userResultVector[userStrippedIndices]\n", + " forestClf = ensemble.RandomForestClassifier()\n", + " printConfusionMatrix(forestClf, strippedUserFeatureMatrix, strippedUserResultVector, \"All features, random forest, user %s\" % i)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "number of instances of mode 9 = 3\n", + "nClasses = 5\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7.], test set = [ 1. 3. 5. 6. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7.], test set = [ 1. 3. 5. 6. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7.], test set = [ 1. 3. 5. 6. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7.], test set = [ 1. 3. 5. 6. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7.], test set = [ 1. 3. 5. 6. 7.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[[ 98. 0. 0. 0. 2.]\n", + " [ 7. 87. 0. 0. 7.]\n", + " [ 6. 0. 75. 3. 16.]\n", + " [ 0. 0. 10. 77. 13.]\n", + " [ 7. 2. 14. 5. 71.]]\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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48eIFI0aMoHbt2piZmVG9enX69esnTTDnRkJCAl27dqVq1arcuHEjX/ZJEARl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\nBKFAiR6pIAhCHolAKgiCkEdiaC8IgpBHJbFHWqz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+ "text": [ + "" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "number of instances of mode 5 = 0\n", + "number of instances of mode 6 = 3\n", + "number of instances of mode 9 = 1\n", + "nClasses = 3\n", + "Number of distinct classes in training set = [ 1. 3. 7.], test set = [ 1. 3. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 7.], test set = [ 1. 3. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 7.], test set = [ 1. 3. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 7.], test set = [ 1. 3. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 7.], test set = [ 1. 3. 7.]\n", + "[[ 98. 2. 0.]\n", + " [ 3. 97. 0.]\n", + " [ 0. 0. 100.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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L1FbTxo4BOzD297EoKS/BmN/HCKWZ2HkiAKBfy37QVNVEUVkRfk76GT8n/QwAsDO2Y09V\nVOVs4Yzj946DYRg47K5s/bhauyJ6QjS6WnRFS6OWeJD7AH+k/QG9tXr4UPZB6l9HUefXnJs5Y6bT\nTITcCEHmm0z0/KWnUBr+hZ3Hbx9jycUlWHJxiVAaXXVd9GwuvG51rsqK+i6qu9+kllFlH6x2X42+\nB/uigqnA0otLsfRiZbersXZjvCp8JbDeyA4j2dZ30r9JQk+oODZ1xNxucyWWJ7VuNTwWg/sHY/yJ\n8SgtL4VPmI/A55qqmuyFJ2llVue4LiorwuaEzSJvf+NwOOzFOKDyYs/ZtLPIysuCUVBlUK36tCG7\nngzHzBj7Mex52m57u0FbTRvF5cVQV1FHSXmJwH6PfBiJqEzRF7W8WlTWrzq/A3kVlRUh+FqwwOkF\nPi6Hi+D+wew5W1nJ1SLl3zvK4XAwvuN4oc89bDxgoW9ReVX5SQL7iCV/naqq82STuDwAYFSHUYib\nHIev2n0Fc11zqKmowVTHFF0susCvpx8Wdl8IoLJ7cXr0aTg0cYCWmhZsDW0RMjAEvh18ReY9u+ts\nzHCagSZ6TcDlcAVuc1HhquDM6DNwt3GHnoYeDDQNsMB5AXuFUdS2SnoCZsfAHTg09BBcrV3RSLMR\n1FXUYWlgCXcbd2zos4E9gJyaOmFS50loZ9IOjTQbQZWrChMdE3i39saliZfY24aqBiGnpk7S96+E\n76K6+03cMnY/VNkH7jbuODnqJDqYdoCGqgbsjO2wx3sPe+Gsaj5cDhenR53Gpr6b4NDEATrqOtBU\n1UQ7k3ZY7rocMRNjhLrIH5f3qY9FX3tfXJp4CV+2+hKNtRtDTUUN5rrmGNlhJK5NvSZwW6C0MmU9\nro20jDDfeT66WnSFiY4JVLmq0NfQR4/mPXBk6BGB1mlw/2AMsBsAIy0joZ5kdY+ZcR3HYY37Glg3\nsoaWmhYcmjjgwrgLaKLXRGi/T+w8EQPsBsDSwBJaalpQV1GHnbEdFnZfiIND/ruLQ9bfwcf7UFaT\nHCZhnvM8ODRxEPh+hrYdithJsfC1961WfgDAoalG6q+pp6di38198GrphYgxEbVdHVIH0DEjHwqk\n9VjzLc1RUl6C2zNvi7y4QcjH6JiRDwVSQgipIRqPlBBCaogCKSGE1BAF0jouMDAQXK7g18jlcuHv\n719LNSKS8L+vigrpg5iTuoMCaT2gqMFpiXLQd1P/UCCtB+h6Yd1C31f9Q4FUCZKSksDlchEfH88u\nCw4OFuqCp6eng8vlIiIiAq9evcL06dPRunVr6OjooHnz5hgzZgz+/fffapdfWFgIb29vNG3aFHfu\n3JG+Avnk7t27Bzc3N+jo6KBp06YICAhgA+yBAwfA5XLx6NEjgXVEncbZunUr2rZtC21tbRgZGaFL\nly44efKk0raDVKJAqgQODg5o1KgRoqL+ezwuKioKWlpaQsvU1NTQu3dv5ObmQkNDA2vWrMG5c+ew\nceNGpKeno0ePHiguln1kotzcXHh6eiI9PR0JCQmwtxceXIYo3+DBg9G3b1+cOnUKvr6+WLVqFVau\nXCl1vaqnBQ4fPoxFixZhzJgxiIiIwJEjRzBs2DC8efPmU1adiKDYoW+ISFwuF71790Z0dDT8/f1R\nUVGBmJgYzJw5E9u2bUNhYSG0tbURHR0NR0dH6OjooFWrVti2bRubR3l5Obp37w4rKytERERg8ODB\nUst99OgRvLy8oK+vj/j4eBgbG3/KzSTVMG3aNCxevBgA4Onpibdv32LTpk2YN2+exPWqnhZISEhA\nx44dsWzZMnZZv341ew6dyIdapEri5uaGhIQElJSUIDk5GXl5eVi8eDE0NDQQGxsLAIiOjoab239z\n54SEhKBTp07Q09ODmpoarKwqx85MS0uTWl5KSgpcXFxgZWWF6OhoCqKfmREjRgi8HzlyJN6/f4+7\nd+/KnEfXrl2RnJyMuXPn4sKFCygsLJS+EvkkKJAqiZubG4qLixEfH4/o6Gh07twZpqam6NmzJ6Ki\nopCSkoKcnBy4u7sDqDyHOnv2bPTt2xcnTpzA9evXkZhYOe11UZHwAMofi4mJwbNnzzB58mRoa3/a\n2ShJ9ZmZmYl8X51z4OPHj0dISAiuXr2Kfv36wdjYGF999RWys7Olr0wUirr2SmJvb4/GjRsjKioK\nN2/eZAOmu7s7jh07hmbNmkFdXR09evQAAISFhcHT0xMbNvw342ZmZqbM5c2YMQN5eXkYN24cVFVV\nMXToUMVuEKmR58+fw8bmvxk2X7yoHAjZwsKCvchUUiI459nr18LDFU6bNg3Tpk1Dfn4+IiMjsXDh\nQowcOZL9o0uUg1qkSsLhcMDj8fDXX38hNjZWIJDevHkTJ0+eRLdu3aCpWTldwocPH6CqKvh3bv9+\n4flrJJUXHByMWbNmYdSoUQgPD1fcxpAaO3bsmMD7sLAw6Onpwd7enj2FU/UOi7KyMpw/f17sPagG\nBgYYMWIEhg8fXq3TA0QxqEWqRG5ubpg9ezZUVVXRq1cvAJVX9HV1dREdHY2AgP8G1u3Xrx+CgoKw\ndu1adOnSBVFRUTh+/Hi1y9yyZQtUVFTg6+uLiooKoXNzpHbs3bsXFRUVcHJyQmRkJPbt24cVK1ZA\nT08PXbt2RYsWLfDdd9+hoqIC6urq2LlzJ0pKSgQuNk2bNg36+vpwdnaGqakp0tLScOjQIXh5eUko\nmXwSDFGa+/fvMxwOh+nevbvAch8fH4bL5TKXL19ml3348IGZOXMmY2Jiwujp6THe3t5MZmYmw+Fw\nmBUrVrDpAgMDGS6XK5Afh8Nh/P39BZZ9//33jKqqKhMWFvYJtozIiv99paSkMG5uboyWlhbTpEkT\nZvny5QLpUlJSGB6Px+jq6jJWVlbMli1bhL7r0NBQhsfjMaampoyGhgZjY2PDLFiwgHn37p2yN6vB\no2H0CCGkhugcKSGE1BAFUkIIqSEKpIQQUkMUSAkhpIYokBJCSA3RfaTV4OrqipiYmNquBiFKp6ib\ne4yMjGQancrQ0BC5ubkKKVMZ6PanauBwOCgrK6u18lesWCFw076y1eYz+2VlZUJPeinTx49rNjSK\nChMcDkemvGRN97mgFikhRKnq43xVFEgJIUpVl1qasqJAWoe4urrWdhVqzcdTbJC6qz62SOkcaTXU\n9jnS2taQxzWlc6SKO0cqy1Q5GhoadarlSi1SQohS1aUAKSsKpIQQpaqPXXs68UQIUSqGYaS+RHn8\n+DGGDRuGRo0awcDAAF999RUeP34sc7n379/H8OHDYWJiAm1tbbRp00ZggsmPhYWFgcvlwtLSUmre\n1CIlhCiVPF37wsJCuLu7Q0tLC7/++isAYNmyZXBzc8Pt27elnr+/ceMG3N3d4e7ujn379sHAwABp\naWkoKCgQmT4vLw/z5s2Dubm52FkJqqKLTdVAF5voYlNDpciLTW/fvpWaTl9fX6DMrVu3YuHChUhL\nS4OtrS0AICsrC3Z2dli/fj3mz58vNq+Kigp06NABbdu2lXmWiWnTpuHx48cwNzfHhQsXpLZ8qWtP\nCFEqebr2p0+fRvfu3dkgCgDW1tbo0aMHTp06JbG8S5cuITU1FQsWLJCpfvHx8Th8+DB27Ngh8x8Q\nCqSEEKWSJ5CmpKSgQ4cOQsvbtWuHe/fuSSwvLi4OQOWEks7OzlBXV4eZmRm+/fZboanNS0tLMW3a\nNCxevFggaEtDgZQQolQVFRVSXx978+YNDA0NhZbLMgjKv//+CwAYOXIk+vXrhwsXLmDx4sXYu3cv\nfH19BdIGBQWhtLQUS5YsqdY20cUmQohSKfuyDD8wjxs3DoGBgQCA3r17o7y8HH5+fkhNTUWbNm3w\n4MED/Pjjjzh58iTU1dXZ9WW52ESBlBCiVKICaVxcHOLj48WuY2hoKLLlmZubCyMjI4nlGRsbAwD6\n9OkjsLxPnz7w8/PDrVu30KZNG8ydOxfu7u7o1q0b8vLyAFReZKyoqEB+fj40NDSgqakpsgwKpIQQ\npRLVdXdxcYGLiwv7fsOGDQKft2/fHnfv3hVa7969e2jXrp3E8kSdWxXl/v37yM7OFnkKwdDQEPPm\nzcPmzZtFrkuBlBCiVPJ07QcNGoRFixYhMzMTNjY2ACpvf7py5QqCgoIkrtu/f39oaGjg3LlzGDhw\nILv83LlzAIAuXboAqLwBv+o4AAzDYN26dUhKSkJ4eDgsLCzElkH3kVYD3UdK95E2VIq8j/T58+dS\n05mbmwuUWVhYiE6dOkFLSwurV68GAPj7+6OgoEDghvzs7Gy0aNECAQEB8Pf3Z9dfuXIlVq1ahcWL\nF8PNzQ03btzAypUrMWrUKPzyyy9i6zFx4kRcvHhR6n2k1CIlhCiVPM/aa2trIyoqCvPnz8e4cePA\nMAw8PT3x008/CfyBZxgGFRUVQoF/+fLl0NPTw86dO7Fx40Y0bdoUixcvFgi2onA4HHqySdGoRUot\n0oZKkS3Sp0+fSk1nYWFRp0aJohYpIUSp6lKAlBUFUkKIUtXHYfQokBJClIpapIQQUkMUSAkhpIbq\nY9e+wQxaEhgYKDQTJZfLlXr7AyFEseQdIf9z1qBapKLuB5PlHjFCiOLUxUApTYMKpPXxCySkrqGu\n/SeWlJQELpcrMApMcHCwUBc8PT0dXC4XERERePXqFaZPn47WrVtDR0cHzZs3x5gxY9gxCKujsLAQ\n3t7eaNq0Ke7cuaOQbSKECKqPXfvPKpA6ODigUaNGiIqKYpdFRUVBS0tLaJmamhp69+6N3NxcaGho\nYM2aNTh37hw2btyI9PR09OjRQ2AAAmlyc3Ph6emJ9PR0JCQkwN7eXqHbRgipVBuziHK5XJGv27dv\nC6V9+vQpJk+ejCZNmkBTUxO2trZYunSpxPw/q649l8tF7969ER0dDX9/f1RUVCAmJgYzZ87Etm3b\nUFhYCG1tbURHR8PR0RE6Ojpo1aqVwJSq5eXl6N69O6ysrBAREYHBgwdLLffRo0fw8vKCvr4+4uPj\n2fELCSGKJ0/XvqaziALApEmTMH36dIFldnZ2Au+zsrLQo0cPtGjRAsHBwTAzM0NmZiYePnwoMe/P\nKpACgJubG/z8/FBSUoK7d+8iLy8Pixcvxu7duxEbGwsvLy9ER0fj66+/ZtcJCQnBrl27kJGRITC9\nalpamtTyUlJS4OLigg4dOuD333+X+oWsWLGC/b+rqyt4PF71N5KQBkyervuePXuQmZkpMItox44d\nYWdnh927d0ucRZTPwsICXbt2lZhmxowZsLS0RHR0NFRUVAAAvXr1kpr3ZxlIi4uLER8fj7///hud\nO3eGqakpevbsiaioKDRr1gw5OTlwd3cHUHkO9dtvv8XChQvh5eUFQ0NDlJeXw9nZWWhiK1FiYmKQ\nm5uLzZs3y/RXLSAgoMbbSEhDJk8glTaLqCyBVFq5Dx8+xPnz53Hw4EE2iMrqszpHCgD29vZo3Lgx\noqKiEB0dzQZMd3d3REVFISoqCurq6ujRoweAysFYPT09sWHDBnh6esLR0REmJiYylzdjxgzMmjUL\n48aNw++///5JtokQ8h95Jr+rySyifCEhIdDU1ISOjg48PDzY2UX5+Be5NTU10adPH2hqasLIyAgT\nJkxAbm6uxLw/u0DK4XDA4/Hw119/ITY2ViCQ3rx5EydPnkS3bt3YuVM+fPgAVVXBhvX+/furVV5w\ncDBmzZqFUaNGITw8XHEbQwgRIs/FpprMIgoAY8eORUhICC5evIiff/4Zr1+/hru7Oy5fvsym4d/p\nM3nyZLRp0wbnzp1DUFAQzp49Cy8vL4kt2s+uaw9Udu9nz54NVVVV9vyEg4MDdHV1ER0dLdC97tev\nH4KCgrB27Vp06dIFUVFROH78eLXL3LJlC1RUVODr64uKigqMGDFCYdtDCPlPbdzexL9ABQA9evSA\nj48POnToAH9/f8TExAD47yKYm5sbgoODAQA8Hg8GBgYYNWoUIiMj0a9fP5H5f7aBFACcnJygq6sL\noPKKPo/Hw5kzZ9jPgcqRr/Py8rBlyxYUFRWBx+MhMjJS4FwKINtI1xs3boSqqirGjBkDhmEwcuRI\nBW8ZIURU1/3GjRu4ceOG2HVqMouoKLq6uhgwYIBA71XSbKMAcOvWLbGBlEbIrwYaIZ9GyG+oFDlC\nflJSktR80FItAAAgAElEQVR0jo6OAmV6eHigpKQEsbGxAul4PB44HA6io6OrXZdZs2bhwIEDKCws\nBFB5jrRXr14IDg7G7Nmz2XRv3ryBsbEx1q5di++//15kXp/dOVJCSP0mz8WmQYMGITExEZmZmewy\n/iyigwYNqnYd3r59iz/++EPgdihnZ2eYm5uzs4vyfTzbqCjUIq0GapFSi7ShUmSL9Nq1a1LTde3a\nVWGziG7cuBEPHz4Ej8eDmZkZsrOz2ScgL168yN4BBFSeS504cSKmT5+OIUOG4MGDB1i2bBkcHBxw\n8eJFsfX9LM+REkLqL3mCck1mEW3Tpg1OnjyJ8PBw5OfnQ19fHz179sT+/fvh5OQkUM748ePB5XIR\nFBSE/fv3w9jYGOPGjcPatWsl1o9apNVALVJqkTZUimyRJiQkSE3XvXv3OjV4CbVICSFKVZcCpKwo\nkBJClIoCKSGE1FB9HNiZAikhRKmoRUoIITVEgZQQQmqIuvaEEFJD1CIlhJAaalCB1MbGRu453zMy\nMuSuECGkfquPXXuxg5bwH7Wq7qs+/rUhhChObcwiWtW6devA5XJFzsWUk5ODOXPmwNbWFtra2rC1\ntcU333yDV69eScxTbIs0Kyur2hUkhBBp5GlsKWIWUaCyt7x69WqYmpoK9bgZhoG3tzcyMjKwatUq\ntG3bFikpKVi+fDlu3Lgh8dFWOkdKCFEqebr2iphFFABmzpyJcePGITU1VWjcjLS0NFy7dg27d+/G\n1KlTAQC9e/cGl8vFzJkzkZ6eLjR9M59c45G+e/cOSUlJQoOsEkKINPJ07aXNIiqLI0eOIDk5GWvX\nrgXDMEIt0vLycgCAgYGBwHL+e0l/AKoVSDMyMuDt7Q1DQ0N06dJFYE73uLg4tGvXTq6RqgkhDYc8\ngbSms4i+efMG8+fPx/r169GoUSORadq1a4e+ffti1apVSEpKwvv373Ht2jWsXLkSAwYMQOvWrcXm\nL3MgzcrKgrOzMyIjIzF48GChYa66deuGV69e4ciRI7JmSQhpgOQZIb+ms4h+9913aNOmDSZMmCAx\n3YkTJ2BlZYUuXbpAX18fzs7OaNmypdTZhWUOpP7+/sjPz0dMTAzCw8OFJohSU1NDr169cOXKFVmz\nJIQ0QPJetZdXbGwsDh48iJCQEInpKioqMGzYMNy8eRO7d+9GTEwMdu3ahevXr2PYsGGKmY75r7/+\nwtChQ+Hs7Cw2jZWVlcTh+AkhRFRAunPnDu7evSt2nZrMIjp9+nRMmTIFFhYWyMvLAwCUlZWhoqIC\n+fn50NLSgrq6Os6cOYOIiAhcvHiRnam4Z8+esLW1Rd++fXHmzBmx80PJHEjz8vLQvHlziWnKysoa\n/EjihBDJRHXd27dvj/bt27Pvw8LChD4XFWjv3buHdu3aSSwvNTUVqamp2LVrl9BnhoaG+OmnnzB3\n7lz2XOvH04/wJ71LTU2teSBt2rQpUlNTJaZJTk6GjY2NrFkSQhogebrugwYNwqJFi5CZmcnGGP4s\nokFBQRLXjY6OFrhCzzAM5s2bh4qKCgQHB6NFixYAgGbNmgEArl+/Dnd3dzb91atXAQAWFhZiy5D5\nHOmXX36Js2fPIi4uTuTnp06dQlxcHHx8fGTNkhDSAMlzjnTq1KmwtraGj48PTp8+jdOnT8PHxwfN\nmzfH9OnT2XTZ2dlQVVXFqlWr2GWurq7o3bs3+3J1dYWBgQH09fXRu3dvNkAOGTIElpaWGDduHHbt\n2oXo6GiEhIRg/PjxaN68OYYMGSJ2m2RukS5duhTHjx9Hnz59MGXKFDx58gQA8PPPPyMhIQEHDx6E\npaUlFi1aJGuWdZK4Wycagnfv3tV2FWqNhoZGbVeh3pDnhvyazCIqCofDEbqPVFdXFwkJCQgMDMSG\nDRvw7NkzmJubw8fHB4GBgRKfnqrWLKLp6ekYP34829StqmvXrjhy5IjADbP1DYfDga6ubm1Xo9a8\nfv26tqtQaxp6IFXkLKLHjh2Tmm7EiBF1atyOaj0iamdnh4SEBPz999+4evUqcnNzoa+vj27duqFr\n166fqo6EkHqkLgVIWcn1rP0XX3yBL774QtF1IYQ0APVxGD25AmlycjJu376N/Px8GBgYoFOnTujU\nqZOi60YIqYcafIs0ISEBM2bMwJ07d4Q+s7e3x+7duyXesE8IIQ06kF6/fh0eHh4oKipCnz590KNH\nD5iZmeHFixeIi4vDhQsX4OHhgUuXLrE3sBJCyMcadNfez88P5eXluHDhgsDNqnwXL17EgAEDsGTJ\nEly4cEGhlSSE1B/1sUUq8w35V69exciRI0UGUQDw8PDAiBEjkJiYqLDKEULqH3lGf/rcydwiVVdX\nh6WlpcQ0zZo1a/D32xFCJKuPLVKZA6mHh4fUQZsvX74stsVKCCFA/QykMnftN27ciKdPn2LSpEl4\n+vSpwGdPnjzBxIkT8fTpU2zevFnhlSSE1B/ydu2VMYsowzBYu3YtrK2toaWlhc6dO+P333+XmqfY\nFqmbm5vQs6iGhoYIDQ3F4cOHYWVlBVNTU7x8+RLZ2dkoKytDx44dMWHCBERFRVV74wghDcPnOoso\nP89Nmzbhxx9/hKOjI3777TcMHz4cf/zxB/r37y82X7HP2nO5cs2LB6B+3t4A0LP29Kx9w6XIZ+1/\n/vlnqemmTZsmUObWrVuxcOFCgVlEs7KyYGdnh/Xr18s8i6iXlxdsbW3ZWUSrTuD58uVLWFpaYunS\npQgICGCXe3p6IicnB7du3RKbr9hoKUvzu75ccSOEKI88MUQZs4hGRkaitLQUY8eOFVg+duxY3Llz\nB9nZ2WLzlr/ZSQghcvhcZxFNSUmBhoYGO9Bz1TIASCxHrmftCSFEXvKcJlDGLKK5ubliy+B/Lk61\nA+mjR49w6dIlPHv2DMXFxSLTLF++vLrZEkIaCGWf/uPPInrz5k2paeU9F1ytQDp//nwEBwdL3REU\nSAkh4ogKVunp6UhPTxe7jjJmETU0NGQ//7gMABLLkfkcaUhICLZu3Yo+ffogPDwcADBhwgT89ttv\nmDNnDtTV1fHVV19JvWmfENKwiTon2rJlS/Tv3599fayms4ju2rULhoaGMDIygpGREa5cuYLExEQY\nGhqys4u2b98excXFePjwoVAZACSWI3OLdO/evbC1tcUff/wBFRUVAICNjQ1GjhyJkSNHwtfXF66u\nrvjqq69kzZIQ0gDJ07VXxiyi/fv3h5qaGg4fPizQqz506BDs7e1hZWUltgyZA+k///yDCRMmsEEU\nqGwe8zk7O8Pb2xubNm3CqFGjZM2WENLAyHMecurUqdi+fTt8fHywevVqAIC/v7/IWURbtGiBgIAA\n+Pv7A6icRfRjBgYGKC8vR+/evdllJiYmWLBgAdauXQs9PT04ODjg6NGjiI6OxpkzZyTWT+ZAqqKi\nAj09Pfa9jo4OcnJyBNLY2toiIiJC1iwJIQ2QPIFUGbOIAsCaNWugq6uLrVu34vnz52jTpg3+97//\nYcCAARLzkzmQNmvWjJ2CGQBat26NmJgYgTQ3btxo0NMVE0Kkk/eqvaWlJXt9Rhxra2uZ8hd3LYfL\n5eKHH37ADz/8UK26yXyxicfj4fLly+z7kSNH4v79+xg4cCB27twJX19fXLp0CX379q1WBQghDYs8\nN+R/7mRukU6ePBnl5eV4/PgxLC0tMXfuXFy6dAkRERFsd97JyUnqiV9CSMNWFwOlNDIHUkdHRzg6\nOrLvNTQ0cPbsWVy/fh0PHz6ElZUVunXrVqPBTj6lwMBArFy5ksYCIKSW1cffYI0fEe3SpUudmexO\n1MllQohyNegWaX1QH79AQuqa+vg7rNbAzrKq7sDOt27dQmBgIGJjY1FYWIjmzZuzI+7/73//w5Mn\nT6Cq+l9V3717h6ZNm+Kbb77Bjz/+CADIyclBQEAAzpw5g5ycHJiamoLH42Hv3r1QV1cXWW5ZWRk2\nbNiA0NBQZGVlwdjYGKNHj8aaNWsa/PiThHwqDaprX/UK/ad07do18Hg8tGrVCj/99BOaNWuGtLQ0\n3LlzB7NmzcKOHTtw4sQJDB8+nF3nyJEjKCwsZG/EffPmDVxcXJCXl4dly5ahY8eOePHiBU6fPo3S\n0lKxgXTs2LH4448/4OfnBxcXF9y7dw/+/v7IysqSepsFIUQ+DapFqqy/GosWLYKJiQkSExOhqakJ\noPJWKz5XV1fs3r1bIJDu3r0bXl5e7CNbW7ZsQWZmJpKSktCpUyc2naQnrGJjY3Hs2DEcPHgQY8aM\nAQC4u7vDyMgIY8eOxa1btwTyIoQoRn0MpLV6ib2wsBBXrlzBmDFj2CD6sVmzZiE6OhoPHjwAAFy/\nfh3JyckCj4WdP38eXbt2rVbgO3fuHNTV1TF06FCUlZWxrz59+gCA0MMGhBDFqI+zbNRqIH3z5g0q\nKirQrFkzsWmGDBkCMzMz7N69GwCwa9cuWFhYwNvbm03z+vVriXmI8vLlS5SUlEBHRwfq6ursy8zM\nDBwOR+wgrsXFxeyr6lgDhBDZyHtDvryziGZnZ8PHxwfW1tbQ1taGiYkJeDye0OPsaWlp+Oabb9Cu\nXTvo6emhadOm8PHxwe3bt6WWUatX7Q0NDcHlcgUePf2Yqqoqvv76a4SEhGDx4sUICwvDd999J3C/\nqomJicQ8RDE2Noampibi4uJEft6kSRORy+kiFCE1o+xZRAsKCmBiYoI1a9agWbNmyM/Px549ezBw\n4ED8/vvvGDx4MIDKnm10dDQmT54MJycn5OXlYf369XB2dkZcXBy++OILsWWInUVUWXg8HjIyMpCW\nlia2e//06VNYW1vDxcUFCQkJyMzMhIWFBft5YGAgVq9ejb///hsdO3YUmcfHN+RfvnwZbm5uuHDh\nAtzd3WWqK80iSrOINlSKnEV02bJlUtOtXr36k8wiyldeXg4bGxs4ODiwk+e9fv0axsbGAunevn0L\na2treHt7IzQ0VGx+tf4Y0saNG/H69Wt0794dhw4dQnR0NPbt24e5c+eyafhd+djYWAwYMEAgiAKV\nI/fb2trC09MT27ZtQ1RUFI4dO4axY8fi/fv3Ist1dXXF6NGjMWzYMKxevRqRkZH466+/sGfPHgwd\nOlTiaN2EEPnJ07VXxCyiVamoqEBfX19gWNCPgygA6Ovrw87ODv/++6/E/Go9kDo5OSE+Ph6Wlpb4\n5ptvMHDgQGzatAmWlpYC6YYNGwYAAheZ+AwMDBAfH48hQ4Zg3bp16N+/PxYtWgQ1NTX21idRw2Yd\nOnQIgYGBCA8Px+DBgzF8+HDs2LEDrVq1gpmZ2SfaYkIattqYRZRfbllZGZ4/f46VK1ciPT0ds2fP\nlrhObm4u7t69i7Zt20pMV+tde1mNGTMGCQkJyMjIqLU6UNeeuvYNlSK79n5+flLTrVu3TqBMDQ0N\nLFy4kH0Ah2/ZsmUICgpCaWmp1DwXLVqEzZs3AwC0tLQQGhrKNtDEGTNmDE6dOoXbt28LtIY/9tk/\nIpqYmIjk5GQcO3YMW7Zsqe3qEEJqqLbabvPnz4evry+eP3+O0NBQjB07FlpaWhg4cKDI9GvXrsVv\nv/2GX375RWIQBaoZSEtLS7Ft2zaEhYUhNTUVhYWFKC8vBwAkJyfj559/xrx589CqVavqZCuRi4sL\n9PT0MHHiRMyaNUth+RJCaoeo+0QfPXok8VammswiymdhYcFeXxkwYADc3NywaNEikYF0165d+OGH\nH7BmzRpMnDhRat4yB9KCggJ4enri6tWrMDExgb6+PgoKCtjPbWxscODAATRq1Eio+V0TdfHmXEKI\neKJapJaWlgLXRa5cuSLweU1mERXH0dERW7duFVp+8OBBzJ49G4sWLcKSJUtkykvmi01r1qzB1atX\nsX79ejx79gxTp04V+NzAwACurq44f/68rFkSQhogeS42DRo0CImJicjMzGSX8WcRHTRoULXrUFFR\ngbi4OLRs2VJg+YkTJzB58mRMnToV69evlzk/mVukx44dg7u7OxYtWiQ2jY2NDZKSkmQunBDS8MjT\ny6zJLKKBgYHswEbm5uZ4/vw59u3bhxs3buDIkSPsujExMRg9ejQ6deqECRMmIDExkf1MQ0MDDg4O\nYusncyB98uSJ1DnrdXR0kJ+fL2uWhJAGSNmziDo6OuKnn35CWFgY8vPzYW5ujs6dOyM2Nhbdu3dn\n00VHR6OkpAQ3b95Ejx49BMq3traWeMeQzIHUwMAAz58/l5jmwYMHdP8lIUQiea/ayzuLqLe3t8DY\nHOIEBAQgICBArrrJfI60d+/eOHnypNhgmpaWhj///BMeHh5yVYQQ0jA06NGfli5diqKiIvTs2RPh\n4eHIy8sDUBlAQ0NDwePxoKKigsWLF3+yyhJC6r4GPR2zg4MDwsLCMGHCBIwYMYJd3qZNGwCArq4u\njh49KvVRKkJIw1YXA6U01bohf8iQIejVqxd+/fVXXL16Fbm5udDX10e3bt0wadIkmJiYfKp6EkLq\nibrYdZem2o+INm7cGAsWLPgUdSGENAANvkVKCCE11aAD6YoVK2Sennn58uVyV4gQUr/Vx669zMPo\nVZ3aQ5r6uKMAGkaPhtFruBQ5jN7XX38tNd3evXvrVMtV5hZpVFSUyOX5+fm4efMmtm7dCk9PT8yZ\nM0dhlSOE1D91KUDKSuZmJo/HE/ny8fFBYGAgrl27hnPnzuHZs2efsr6EkDpO3hvy5Z1F9Pr165gy\nZQpatWoFHR0dWFlZYezYscjKypK4XlhYGLhcrtBsHaIobKoROzs7DB48GEFBQYrKkhBSD8lzQz5/\nFtG0tDT8+uuvOHjwINLT0+Hm5obCwkKJ5R07dgz379/Ht99+i4iICKxbtw5///03nJycxM4+nJeX\nh3nz5sHc3Fyma0MKvWpvamqK1NRURWZJCKln5Ona79mzB5mZmQKziHbs2BF2dnbYvXu3xFlEFy9e\nLHSPe48ePWBjY4M9e/ZgxYoVItdxcHCAubk5Lly4ILV+CmuRFhcXIzIyEo0aNVJUloSQekiern1N\nZhEV9aBQ8+bNYWJiInJ20Pj4eBw+fBg7duyQOejL3CINDQ0V2cQtKyvDkydP2OlHqk6jTAghH5On\nRZqSkoIhQ4YILW/Xrp3UEaFEuX//Pl6+fCn0SHtpaSmmTZuGxYsXS52nqSqZA+mkSZMkfs7hcODr\n64t169bJXDghpOGRJ5C+efMGhoaGQsuNjIxEzuUkSVlZGWbMmAFTU1NMmTJF4DP+jKSyTjHCJ3Mg\n/eWXX0Qu53K5MDQ0hJOTE5o0aVKtwgkhDU9t32c+Z84cJCYm4uzZszAwMGCXP3jwAD/++CNOnjwJ\ndXV1drlCLzbJMpMeIYRII6pF+uLFC7x8+VLsOoqYRRQA/Pz8sGfPHvz666/w9PQU+Gzu3Llwd3dH\nt27d2GFCS0pKUFFRgfz8fGhoaEBTU1NkvjIHUiMjIwwZMgT79u2TudKEEPIxUYHU1NQUpqam7PuU\nlBSBzxUxi+iaNWuwfv16bN++HWPGjBH6/P79+8jOzhZ5CsHQ0BDz5s3D5s2bReYtcyAtLy+nYfIA\nvH//vrarUGsa8mOS9fFpHFnJOsaGrOTp2g8aNAiLFi1CZmYmbGxsAPw3i6gs965v27YN/v7++PHH\nHzFr1iyRacLCwlBcXMy+ZxgG69atQ1JSEsLDw2FhYSE2f5mftff09ISGhgbOnj0rS/J6SdEHFKk7\nGnogVeSz9sOGDZOaLjw8XKDMwsJCdOrUCVpaWgKziBYUFOD27dvsBHiiZhENCwuDr68v+vXrh4CA\nAIF8DQwMJA5GP3HiRFy8eFHqE1Qy30caGBiICxcu4NChQ7KuQgghQuR5sok/i2irVq0wbtw4jB07\nFi1atEBUVJTUWUQjIyPB4XBw7tw5dO/eHS4uLuxr9uzZEuvK4XBkakDJ3CJdsWIF4uPjceHCBTg5\nOcHJyQlmZmYiC6mvw+hRi7Thohap4lqkou4H/diJEyfq1D6XGEhtbGwwf/58zJ07l4bRAwXShqwu\n/agVTdGBdPDgwVLTnTx5sk7tc4kXm7Kzs9nbAMQNo0cIIdVRlwKkrGS+as/j8T5hNQghDUV97LHS\nnE2EEKVq0C1SQghRhPrYIpV4sYnL5aJRo0bVHhovIyOjxhX7HNHFpoarPraiZKXoi039+/eXmi4i\nIqJO7XOpLdK8vDz2ghMhhNRUXQqQspJ6T1NAQIBMA7FKm2+FEEIA+eds+pxJbZFSd5YQokgNskVK\nCCGKJM8jooD8s4gCwNKlS9G3b18YGxuDy+UiNDRUbNqnT59i8uTJaNKkCTQ1NWFra4ulS5dKzJ8C\nKSFEqeTp2tdkFlEA2L59O4qLi+Ht7Q1AfE87KysLXbt2xYMHDxAcHIy//voLgYGBUFNTk5i/1K59\nfWyGE0Jqj7JnEQWAt2/fAgAePnyIX3/9VWy6GTNmwNLSEtHR0VBRUQEA9OrVS2r9JAbSunjSlxDy\neZMnkEqbRVRaIJWl7IcPH+L8+fM4ePAgG0RlRV17QohSydO1T0lJQYcOHYSWt2vXDvfu3VNIveLj\n4wEAmpqa6NOnDzQ1NWFkZIQJEyYgNzdX4roUSAkhSiXPxSZFziIqDn+O+8mTJ6NNmzY4d+4cgoKC\ncPbsWXh5eUlszdIjooQQpfpcr7vwW8Jubm4IDg4GUDlYk4GBAUaNGoXIyEj069dP5LoUSAkhSiWq\n656fn4/8/Hyx6yhqFlFJjI2NAQB9+vQRWM5/f+vWLQqkhJDPg6gWqb6+PvT19dn3T548EfhcEbOI\nSiPqHKys6BwpIUSp5DlHOmjQICQmJiIzM5Ndxp9FdNCgQQqpl7OzM8zNzXHu3DmB5fz3Xbp0Ebsu\nBVJCiFLJc9V+6tSpsLa2ho+PD06fPo3Tp0/Dx8cHzZs3x/Tp09l02dnZUFVVxapVqwTWv3z5MsLD\nw9mgeP36dYSHhyM8PJxNo6KignXr1uHs2bOYOXMmzp8/j507d2L27Nlwc3ODu7u72G2irj0hRKnk\nudjEn0V0/vz5GDduHBiGgaenJ3766Seps4gClbMgX758GUDlU007duzAjh07wOFwUF5ezqYbP348\nuFwugoKCsH//fhgbG2PcuHFYu3atxPrJPIsooQFcGrKG/DNR9HikTk5OUtPduHGjTu3zOte1DwwM\nBJfLpaeuCKmjGuQwep8jahkSUnfVpZamrOpkIK2PXwQhDUV9/P3Wua4937179+Dm5gYdHR00bdoU\nAQEB7Bd04MABcLlcPHr0SGAd/mmBqrZu3Yq2bdtCW1sbRkZG6NKlC06ePKm07SCkoaGu/Wdk8ODB\nmDJlCn744QecO3cOq1atApfLRUBAgMT1qp4WOHz4MBYtWoSAgAD06tULHz58wK1btxT27C4hRFh9\nbJHW2UA6bdo0LF68GADg6emJt2/fYtOmTZg3b57E9ap+iQkJCejYsSOWLVvGLhP3CBghRDEokH5G\nRowYIfB+5MiR2Lt3r8jHyMTp2rUrQkJCMHfuXAwaNAguLi4C96QR0hBdunQJly5d+mT518WuuzR1\nNpCamZmJfM8fCksW48ePR1FREfbt24edO3dCTU0NAwYMwObNm2FlZaXQ+hJSV/B4PPB4PPb9ihUr\nFJp/fWyR1tmLTc+fPxd4/+LFCwCAhYUFNDU1AQAlJSUCaV6/fi2Uz7Rp03D16lW8fv0aoaGhuHbt\nGkaOHPmJak0IkXfyu89ZnQ2kx44dE3gfFhYGPT092Nvbs63JO3fusJ+XlZXh/PnzYu9BNTAwwIgR\nIzB8+PBqnR4ghFSPvFftazKLaFFREb777js0adIE2tracHFxQWxsrFC6nJwczJkzB7a2ttDW1oat\nrS2++eYbvHr1SmL+dbZrv3fvXlRUVMDJyQmRkZHYt28fVqxYAT09PXTt2hUtWrTAd999h4qKCqir\nq2Pnzp0oKSkR+Gs3bdo06Ovrw9nZGaampkhLS8OhQ4fg5eVVi1tGSP0mT4uTP4uolpYWO3ndsmXL\n4Obmhtu3b0u9tjFlyhT8+eef2LhxI2xtbbF9+3Z4eXkhISEBnTp1Yuvl7e2NjIwMrFq1Cm3btkVK\nSgqWL1+OGzduICEhQeJG1SmBgYEMl8tlUlJSGDc3N0ZLS4tp0qQJs3z5coF0KSkpDI/HY3R1dRkr\nKytmy5Yt7Lp8oaGhDI/HY0xNTRkNDQ3GxsaGWbBgAfPu3TuRZQOgVwN9NWSK3H4ATMuWLaW+Pi7z\np59+YlRUVJiHDx+yyzIzMxlVVVVm8+bNEstMTk5mOBwOc+DAAXZZWVkZ07p1a2bQoEHsstTUVIbD\n4TA///yzwPq7du1iOBwOk5aWJrYMGrSkGujR1IarIf9MFD1oSdWZQMXJyMgQKNPDwwMlJSVC3XH+\nRTFJdxmsWrUKq1evRn5+Pnv9BKh8QGfdunV49+4d1NTUcO/ePXTo0AFhYWECdwWFhYXB19cX9+/f\nR+vWrUWWUWfPkRJC6iZGjotNNZlFNCUlBba2tgJBlL9uSUkJHjx4wL7v27cvVq1ahaSkJLx//x7X\nrl3DypUrMWDAALFBFKBASghRMnkuNtVkFtHc3Fyx6/I/5ztx4gSsrKzQpUsX9vpJy5YtBQaAFoUC\nKSFEqeRpkSpDRUUFhg0bhps3b2L37t2IiYnBrl27cP36dQwbNoymYyaEfD5EBaSioiIUFxeLXacm\ns4gaGhoKDWDEXxf4r2V65swZRERE4OLFi3BzcwMA9OzZE7a2tujbty/OnDkjdn4oapESQpRKVFde\nXV0denp67OtjNZlFtH379sjMzERRUZHQuurq6mjZsiX7HoDQCP78Se9SU1PFlkGBlBCiVPJ07Wsy\ni+igQYNQWloq8BBPWVkZjh49Ci8vL6ipqQEAmjVrBqByYryqrl69CqDyqUlx6PanaqDbnxquhvwz\nUfTtT02aNJGa7tmzZwJlFhYWolOnTtDS0sLq1asBAP7+/igoKBC4IT87OxstWrRAQEAA/P392fVH\nj0WYQvgAAA5eSURBVB6NyMhIbNiwAdbW1ggJCcGff/6JK1euoHPnzgCA9+/fo3379igrK4O/vz9a\nt26N1NRUrFixApqamrh37574G/8l3slKBOAzuDGcXnRDvrIpcvsBMGZmZlJfosp89OgR89VXXzH6\n+vqMnp4eM2TIECY7O1sgTWZmJsPhcJgVK1YILP/w4QOzYMECxtzcnNHU1GScnZ2Zy5cvC5Xx9OlT\nZurUqYytrS2jpaXF2NjYMNOmTWP+/fdfidtFLdJqoBZpw9WQfyaKbpGamppKTffy5cs6tc/pqj0h\nRKnqUoCUFQVSQohS0cDOhBBSQ9QiJYSQGqJASgghNURde0IIqSFqkRJCSA1RICWEkBqirj0hhNRQ\nfWyR0qAlhBClYuQcj1QZs4gyDIO1a9fC2toaWlpa6Ny5M37//XeZNorICJ/BM9/0omftlU2R2w+A\n0dDQkPr6uMyCggKmZcuWjL29PXPq1Cnm1KlTjL29PdOiRQumoKBAarm+vr5Mo0aNmL179zJRUVHM\n0KFDGS0tLSY5OVkg3dKlSxkNDQ1m06ZNzKVLl5jp06czXC6X+fPPPyVvV/V3RcNV2z9melEgrQ2K\n3H4AjLq6utTXx2UqYxbRFy9eMOrq6kxgYKDA+h4eHkzHjh0llkFde0LqAEmzZNY1jBxd+9OnT6N7\n9+4CM5BaW1ujR48eOHXqlMTyTp8+DTU1NYwcOZJdpqKiglGjRiEyMhKlpaUAwP5/7NixAuuPHTsW\nd+7cQXZ2ttgyKJASUgfUp0Aqz+R3yphFNCUlBRoaGmjRooVQOgASy6Gr9oQQpRLV4pRGGbOIVme2\n0Y9RICWEKJU8gVRZ5K0bde2rwdXVtbarQGoJh8Op1deKFStqrWxFH/eynCPV1dUVWKems4iKak1+\nPIuooaEh8vLypKYThVqk1VCfzlMRUhvkbfHVdBbRkydPoqioSOA86ceziLZv3x7FxcV4+PChwHlS\n/rlRSeVQi5QQ8tlTxiyi/fv3h5qaGg4fPiyw/qFDh2Bvbw8rKyuxZagEBgYGyrFdhBCiNB07dkRY\nWBjCw8NhYWGBf/75B9OmTYO2tjb27dvHBsPs7Gw0btxY4JSEubk5UlNTsWPHDjRu3Bhv3ryBn58f\nbty4gUOHDsHc3BwAoKOjg8LCQmzcuBE6OjooLi5GUFAQjh8/jn379sHOzk58BSXeZUoIIZ8JZcwi\nWl5ezqxevZqxsrJiNDQ0mE6dOjHHjx+XWjeaRZQQQmqIzpESmVlbW8PGxkZgWWBgILhcLi5fvlxL\ntZINv54xMTEypedyuXBzc6tRmYrIQxJR3wepHRRIP0NZWVngcrkCL01NTdjY2GDKlCnIyMiotbpx\nOByh9/yXPHg8Hrjcz/MwlHebFJ1HbeZPZEO3P33GWrVqBV9fXwDA27dvER0djf379+PEiRO4evWq\n5JPfSjJnzhyMHj0alpaWcudBwYDUdRRIP2OtWrXC8uXLBZZNmjQJoaGhWLNmDQ4cOFA7FavC2NgY\nxsbGtV0NQmrV59mnImLNmjULAJCUlATgv9MAkyZNQkpKCnx8fGBkZAQul4u3b98CAIqLi7FhwwZ0\n6tQJOjo6aNSoEfr06SP2fGF0dDR69OgBbW1tmJmZ4euvvxb7nLGkc4/h4eHw8PCAoaEhtLW1YWdn\nhxkzZrCD8fLXYxhG4DTGpEmThOozYMAAGBsbQ0tLC+3bt0dQUBDKy8uFyszJycGUKVNgYmICXV1d\n9OrVS+bzotIkJSVh9uzZaN++PQwMDKCrqwtHR0eEhIRIXC87OxvDhw+HkZERdHV14eHhgevXr4tM\n+/z5c8ydO5cdZMPc3Bzjxo1DVlaWQraBfBrUIq1j+DdZfNwdfvDgAVxcXODg4ICvv/4aL168gIqK\nCoqKitC3b1/ExcWha9eumD59Ot6/f49Tp07Bw8MDx44dw5AhQ9h8zp8/j4EDB0JDQwNjxoxB48aN\ncfbsWfTp0welpaXQ0NCQqZ5z587F9u3bYWZmhpEjR8LIyAgZGRkIDw/HgAEDYGlpiYCAABw4cADZ\n2dmoejtz586d2f9v374dc+fOhampKYYMGQJDQ0PExsZiyZIluHbtGo4fP86mff/+PVxdXZGamgoe\njwcXFxf8888/6Nu3L3g8nhx7W9CePXtw9uxZuLq6wtvbG+/evUNkZCRmz56NtLQ0bNmyRWid3Nxc\n9O7dGxYWFpg5cyYeP36Mo0ePwtXVFRcvXkT37t3ZtOnp6eDxeHjx4gUGDhyI4cOH49GjRzh27Bgi\nIyORmJgoMIwc+YzIf1cX+VT498J5e3sLfTZp0iSGw+EwkydPFkjL4XCYVatWCaX38/NjOBwOExQU\nJLA8JyeHsba2ZkxMTJgPHz4wDFM52K21tTWjpqb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+ "text": [ + "" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "number of instances of mode 5 = 0\n", + "number of instances of mode 9 = 0\n", + "nClasses = 4\n", + "Number of distinct classes in training set = [ 1. 3. 6. 7.], test set = [ 1. 3. 6. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 6. 7.], test set = [ 1. 3. 6. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 6. 7.], test set = [ 1. 3. 6. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 6. 7.], test set = [ 1. 3. 6. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 6. 7.], test set = [ 1. 3. 6. 7.]\n", + "[[ 97. 3. 0. 0.]\n", + " [ 7. 82. 0. 11.]\n", + " [ 0. 0. 95. 5.]\n", + " [ 1. 4. 0. 95.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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UrFmTL7/8kl69etGmTRt69uzJzz//THx8POHh4Trt986dO7Rq1YqMjAxOnjxJ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\nkk4E0mKsZs2azJo1S2XZkCFD2LRpEwsXLuT7778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+ "text": [ + "" + ] + } + ], + "prompt_number": 243 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "So there's quite a bit of variability in both the overall accuracy, and in the number of trips for a user. The two don't seem to be correlated though. We get some fairly uneven improvement - for some users, the general classification is over 90%. We are also able to classify over 80% of the trips for some users.\n", + "\n", + "But that might just be due to a higher ratio of walk trips, which are classified more accurately. I can explore this only for transport, but first, I'm going to try to build a gesture library and build the associated features. Then maybe Mogeng can continue some of the exploration." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "(userResultArrayTransOnly, labelsTransOnly) = getUserModelComparison(isTransportOnly=True)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Skipping user with userId 5dd35f51-3d1a-30db-9b22-ce0a432c2a59 who has 108 unconfirmed sections\n", + "Skipping user with userId 6a488797-5be1-38aa-9700-5532be978ff9 who has 38 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId acd105e3-b221-35c5-81ac-fee5ffe9de66 who has 11 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 11 high confidence predictions out of 45" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 10 high confidence predictions out of 45\n", + "Found 12 high confidence predictions out of 44\n", + "Found 4 high confidence predictions out of 44\n", + "Found 10 high confidence predictions out of 44\n", + "for prob 0.95, percentage auto classified 0.211515151515\n", + "for prob 0.95, scoring only on high confidence predictions 0.98\n", + "for prob 0.95, scoring on all predictions 0.720202020202\n", + "Skipping user with userId 7327a0b3-4959-31f5-86cb-ea0c59fd0c83 who has 8 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 89e30222-b446-30ad-852c-b305ddafe70d who has 132 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId adaa57a8-7fb8-3389-acce-db50ddc9e2dd who has 11 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId ed8ca6a2-9092-37af-adde-46e51a18a310 who has 29 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId f8fee20c-0f32-359d-ba75-bce97a7ac83b who has 67 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId fb457463-9a06-3c84-947d-db1fefb5a199 who has 0 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 527e98f8-710d-3719-93f2-ab140d1439ba who has 107 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 5322f635-a82c-3677-a1a4-5c26804a90b7 who has 24 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 560a0ea4-fcdf-3c1b-adf0-22d2b79af3ea who has 2 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 5c035ff1-e0d5-397f-b989-9cb8faa0a1da who has 112 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId a47da5c4-3ced-34ac-af25-6c3aa7998827 who has 119 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 23 high confidence predictions out of 40" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 24 high confidence predictions out of 40\n", + "Found 23 high confidence predictions out of 40\n", + "Found 27 high confidence predictions out of 40\n", + "Found 27 high confidence predictions out of 40\n", + "for prob 0.95, percentage auto classified 0.62\n", + "for prob 0.95, scoring only on high confidence predictions 0.992592592593\n", + "for prob 0.95, scoring on all predictions 0.93\n", + "Skipping user with userId e0509a4e-9842-3c73-8050-875b6383c097 who has 22 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId e1a99120-9a5a-31ae-9d7a-93b9a3e0c51c who has 23 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId e211dd91-423f-31ff-a1f8-89e5fdecc164 who has 54 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId ea3f7719-f4a3-36fd-9477-924114cfe0bd who has 8 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId ff860db0-f3fe-387c-a005-c5837f5ba970 who has 0 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 3a307244-ecf1-3e6e-a9a7-3aaf101b40fa who has 107 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 7 high confidence predictions out of 34" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 6 high confidence predictions out of 34\n", + "Found 11 high confidence predictions out of 34\n", + "Found 5 high confidence predictions out of 34\n", + "Found 5 high confidence predictions out of 34\n", + "for prob 0.95, percentage auto classified 0.2\n", + "for prob 0.95, scoring only on high confidence predictions 0.948484848485\n", + "for prob 0.95, scoring on all predictions 0.817647058824\n", + "Skipping user with userId 3c1f13e8-b063-3d6c-a1eb-8fd39b874110 who has 20 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 6dbe9b5a-26a1-31d0-aeb6-7b08ffa49b10 who has 0 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 7a88d272-3b9e-3d18-9749-57ddb6214440 who has 0 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 35 high confidence predictions out of 51" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 42 high confidence predictions out of 51\n", + "Found 44 high confidence predictions out of 51\n", + "Found 40 high confidence predictions out of 51\n", + "Found 38 high confidence predictions out of 51\n", + "for prob 0.95, percentage auto classified 0.780392156863\n", + "for prob 0.95, scoring only on high confidence predictions 0.965404420141\n", + "for prob 0.95, scoring on all predictions 0.945098039216\n", + "Skipping user with userId 8d235d9c-7af6-3132-ba91-626e40181449 who has 5 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 8d718272-c46c-3e24-8bae-9696917deeec who has 16 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 8e230f78-6e37-3588-bf2c-6888a5b63c82 who has 15 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 951779de-a10c-3373-b186-c1c9b14b5e38 who has 1 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 11 high confidence predictions out of 37" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 8 high confidence predictions out of 37\n", + "Found 10 high confidence predictions out of 37\n", + "Found 10 high confidence predictions out of 37\n", + "Found 12 high confidence predictions out of 37\n", + "for prob 0.95, percentage auto classified 0.275675675676\n", + "for prob 0.95, scoring only on high confidence predictions 0.963333333333\n", + "for prob 0.95, scoring on all predictions 0.794594594595\n", + "Skipping user with userId 9cc9d577-3a22-3659-8cd5-9142936f44ec who has 8 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId a1a10092-0136-37f1-8109-9ebf47ef72b2 who has 1 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId b3b9fe85-d510-3e5b-bec2-031ca9da7c83 who has 0 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId bbd4e1ad-bd2d-3126-a58c-2c2fe1895fba who has 0 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId bcbefbfc-8021-353f-9f5c-648d539c8cff who has 0 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId bd01c81f-feff-3249-a6de-5cf7f06accc8 who has 98 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 12 high confidence predictions out of 43" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 14 high confidence predictions out of 43\n", + "Found 8 high confidence predictions out of 43\n", + "Found 14 high confidence predictions out of 43\n", + "Found 6 high confidence predictions out of 42\n", + "for prob 0.95, percentage auto classified 0.251827242525\n", + "for prob 0.95, scoring only on high confidence predictions 0.904761904762\n", + "for prob 0.95, scoring on all predictions 0.789479512735\n", + "Found 12 high confidence predictions out of 64" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 11 high confidence predictions out of 64\n", + "Found 7 high confidence predictions out of 64\n", + "Found 15 high confidence predictions out of 64\n", + "Found 8 high confidence predictions out of 64" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.165625\n", + "for prob 0.95, scoring only on high confidence predictions 0.983333333333\n", + "for prob 0.95, scoring on all predictions 0.709375\n", + "Skipping user with userId d8a6b737-b6a5-3fc7-a144-76ac2d434252 who has 12 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 04a9dec3-5a20-38ef-85b7-414dc7a2cf4e who has 0 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 1c97e50a-aa2a-3016-ad31-f9f6b726d4c4 who has 103 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 1cc03940-57f5-3e35-a189-55d067dc6460 who has 60 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 202a0732-d5c2-307d-aa29-2b39bc5e6660 who has 43 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 2491630e-bb62-39c2-8349-df4dad434dee who has 63 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 298a1c8e-74c7-3631-b59f-a5ce246c4e6d who has 68 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 3537737e-8db4-3706-8c6c-ad4cafd9dc82 who has 35 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 399ed209-2e4e-37fc-a6ac-37c25f7ee1f2 who has 101 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Skipping user with userId 01477d94-e0bb-3903-a428-338551801391 who has 41 unconfirmed sections" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + 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PyR4ty1pWadHgkswlVUZTlOsW2826nfdaNNijdQ8FB+5//CFL+gD/QsgMNHaO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\nFStW5NRTT+Xtt9+mTp063/t+t95667fXrVu39pBAqZh9/DF06xZWWww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JLO2hggK45JKw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\nXdm3p6aGZpisovOpp0KJEtHlV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jPPTLp1S959N3n88eS885I+farXf/7yl5NrrklefHHT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\nAACALcRPf5rMmpXsuWdy/PGbZk7LZQAAAAAAbAHefDPp3DlZujR5+OGkf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szlzZJZkiRJ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iGRkZjBs3jrFjx2779R2NS1fyvxxJkiTtpKKisIf5yy/D3uCzzoqdKDUdcQTceWc4X3QRPPNM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\n005LOlF6W7UKHngA+vWDOXNirWbNGDF18sl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+ "text": [ + "" + ] + } + ], + "prompt_number": 118 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "So looking at transport-only trips, and focusing on users with enough transport history (50+ motorized transport trips), we are able to get an overall accuracy of around 70 - 80% even for the motorized trips. However, there are some clear outliers, like the one who has only 60% accuracy. Also, because our current threshold for high confidence is set so high, the high confidence predictions are > 95% correct as before. We have to decide what to use.\n", + "\n", + "We can autoclassify 20 - 50% of the motorized transport trips. In general, this is related to the number of trips - there is a very clear spike in the data for user 4. But the correlation is not exact. In particular, user 5 has > 50 trips, but only ~ 10% autoclassified trips.\n", + "\n", + "It might be worthwhile to take a closer look at these 6 users, see what their transport trips look like, and get a sense of what the difference between user 4 and user 5 is, for example. This might help us figure out how to build better user models." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "def buildRouteLibrary(userId, threshold):\n", + " '''\n", + " Here we attempt to build a route library for each user.\n", + " Then, the probability of the top match can be a factor in our machine learning.\n", + " Let us just start with the start and end points instead of a full dynamic time warp.\n", + " \n", + " userSections = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, {'user_id': userId}]})\n", + " existingRoutes = RouteLibrary()\n", + " for section in userSections:\n", + " existingRoutes.update(section)\n", + " return existingRoutes\n", + " '''" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 119 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "A summary comparision of models" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "modelCMList = []\n", + "saveDir = \"/tmp/ml_results/\"" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 205 + }, + { + "cell_type": "heading", + "level": 3, + "metadata": {}, + "source": [ + "Generic model" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices], cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices], cleanedResultVector, \"Generic\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Found 795 high confidence predictions out of 1462\n", + "Found 763 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 758 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 755 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 753 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.9, percentage auto classified 0.523331189121\n", + "for prob 0.9, scoring only on high confidence predictions 0.976614660881\n", + "for prob 0.9, scoring on all predictions 0.858768472768\n", + "Found 797 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 772 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 773 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 764 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 776 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.531269926432\n", + "for prob 0.95, scoring only on high confidence predictions 0.975768145661\n", + "for prob 0.95, scoring on all predictions 0.855208517675\n", + "Found 753 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 803 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 792 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 781 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 795 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.99, percentage auto classified 0.537020630324\n", + "for prob 0.99, scoring only on high confidence predictions 0.975552792373\n", + "for prob 0.99, scoring on all predictions 0.856711245694\n", + "[0.52333118912050769, 0.53126992643196425, 0.53702063032366376]\n", + "[0.79982058845572457, 0.82560250618875786, 0.82452630894330581]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[0.61932054789292057, 0.60332227946040162, 0.6297343777432276]\n", + "[0.074363308678113318, 0.070130473123226747, 0.063852958222271342]\n", + "[0.079426505473742137, 0.057469131853368306, 0.079881336986600132]\n", + "[0.21651666561666313, 0.21486677351753034, 0.22146216903488028]\n", + "[0.31629682490841621, 0.018181818181818181, 0.22146216903488028]\n", + "[0.97661466088064053, 0.97576814566063175, 0.97555279237322767]\n", + "[0.85876847276802903, 0.85520851767477457, 0.85671124569401813]\n", + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + 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kgOGPiIiIiIhIBhj+iIiIiIiIZIDhj4iIiIiISAYY/oiIiIiIiGSA4Y+IiIiIiEgGGP6I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xYgU0NDRgY2MDb29vmJmZVfHKCSGykCeuKJpF9KeffoKDgwNGjx5daTnBVMtP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\nciRMTEygqqqKzMxM7N+/X+wq/KamppW2R/AzF/y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+ "text": [ + "" + ] + } + ], + "prompt_number": 206 + }, + { + "cell_type": "heading", + "level": 3, + "metadata": {}, + "source": [ + "Generic + Advanced model" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices], cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices], cleanedResultVector, \"Generic + Advanced\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic_advanced.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Found 735 high confidence predictions out of 1462\n", + "Found 741 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 703 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 723 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 709 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.9, percentage auto classified 0.494180756205\n", + "for prob 0.9, scoring only on high confidence predictions 0.978976787753\n", + "for prob 0.9, scoring on all predictions 0.85534306937\n", + "Found 757 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 753 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 754 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 705 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 723 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.505265868345\n", + "for prob 0.95, scoring only on high confidence predictions 0.975358821359\n", + "for prob 0.95, scoring on all predictions 0.860681972039\n", + "Found 734 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 759 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 759 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 709 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 741 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.99, percentage auto classified 0.506636385513\n", + "for prob 0.99, scoring only on high confidence predictions 0.974602074088\n", + "for prob 0.99, scoring on all predictions 0.85671339927\n", + "[0.49418075620487445, 0.50526586834533249, 0.50663638551261203]\n", + "[0.78596433129605692, 0.79515331684599189, 0.80085535231060057]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[0.48528159980865826, 0.50270866397210123, 0.5232251902060554]\n", + "[0.045530508068490683, 0.050964418464418473, 0.066271462619777233]\n", + "[0.068974358974358968, 0.08116171771811978, 0.0867461430575035]\n", + "[0.21319424620138672, 0.22284629252546581, 0.2048834205032275]\n", + "[0.27315750739149192, 0.097142857142857142, 0.2048834205032275]\n", + "[0.97897678775336949, 0.97535882135887297, 0.97460207408839139]\n", + "[0.85534306937043481, 0.86068197203909025, 0.8567133992702185]\n", + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[[ 95. 1. 0. 0. 3. 0.]\n", + " [ 6. 85. 3. 0. 6. 0.]\n", + " [ 8. 10. 30. 5. 47. 0.]\n", + " [ 3. 2. 4. 36. 54. 0.]\n", + " [ 2. 2. 4. 3. 89. 0.]\n", + " [ 11. 3. 0. 0. 21. 65.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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YfH19sWbNGkilUiEdYwxyuVypp4DjOFy9ehU//vgjysrK0KNHD8ycOROffPIJ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\nSE0TTQdUO0DNdoRM6+mA5B4Y/oiIiIhIURYNQtJ8pxgyWpGj8JAkeEsSv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cuXJFqF9ubm4ICQkBALi6ukJXVxcjRoxAZGQk+vTpI7J+CqSEELkSNbLr2LEj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\nx0wIIfJA50iJxCwtLWFlZSW0LSgoCFwuV+a7Gb4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+ "text": [ + "" + ] + } + ], + "prompt_number": 207 + }, + { + "cell_type": "heading", + "level": 3, + "metadata": {}, + "source": [ + "Generic + Advanced + Location model" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices\n", + " +LocationFeatureIndices], cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices\n", + " +LocationFeatureIndices], cleanedResultVector, \"Generic + Advanced + Location\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic_advanced_location.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Found 784 high confidence predictions out of 1462\n", + "Found 795 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 727 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 740 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 787 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.9, percentage auto classified 0.524561255666\n", + "for prob 0.9, scoring only on high confidence predictions 0.984334593737\n", + "for prob 0.9, scoring on all predictions 0.884356516113\n", + "Found 732 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 773 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 791 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 758 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 747 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.520187623304\n", + "for prob 0.95, scoring only on high confidence predictions 0.983670522976\n", + "for prob 0.95, scoring on all predictions 0.883535629046\n", + "Found 768 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 778 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 762 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 748 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 756 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.99, percentage auto classified 0.521689602253\n", + "for prob 0.99, scoring only on high confidence predictions 0.983495304427\n", + "for prob 0.99, scoring on all predictions 0.887640438918\n", + "[0.52456125566601208, 0.52018762330394175, 0.52168960225320249]\n", + "[0.7923154590793885, 0.79365722753438539, 0.78699205352499269]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[0.51583278452420178, 0.50410882813551205, 0.51882235054872794]\n", + "[0.050097610046562324, 0.054180009758103068, 0.049827603795201417]\n", + "[0.11549248750814307, 0.11461119894875904, 0.085787983859926947]\n", + "[0.28222124923696768, 0.26954733183961943, 0.28212881941009826]\n", + "[0.30099326506587726, 0.050000000000000003, 0.28212881941009826]\n", + "[0.9843345937372916, 0.98367052297622715, 0.98349530442680277]\n", + "[0.88435651611296362, 0.88353562904556315, 0.8876404389175564]\n", + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[[ 96. 1. 1. 0. 3. 0.]\n", + " [ 5. 88. 2. 0. 6. 0.]\n", + " [ 9. 4. 48. 3. 37. 0.]\n", + " [ 5. 1. 4. 55. 35. 0.]\n", + " [ 3. 1. 3. 2. 92. 0.]\n", + " [ 7. 7. 0. 3. 0. 83.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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TE0pKSpCZmYm4uDiMGjWq0e0//vhjyGQy+Pj4wNzcHNeuXcPu3bvxyiuvYMeO\nHaLAffXq1QgPD4e9vT2mTJkCXV1dXL16Fb/99hsOHz4MPz8/AMC+ffswevRoWFpaIjAwEMbGxigu\nLsaJEyewc+dOTJo0qcF2nTNnDnJyciRt5+zsrLI88Kh3dcqUKdixYwecnJyE51j37duHcePGYcWK\nFZg1a5ZQ/vTp0/D09ER1dTUmTJgAW1tb4YsgVUP0CSGEEPL8q/+Zq03nXWCNWLFiBVNTU2N//vmn\nkFZQUMDU1dXZV1991dimKl29epUZGRmxmJgYlflNVKfZZUTlo/BMf1pTcnIy4ziOcRzH4uLiRHmR\nkZGM4zgWHh4upJWUlDBdXV3WrVs3VlxcLCq/bNkyxnEc+/LLL1Xuf9OmTZLjBwUFMY7j2KJFiyR5\n165dE34/c+YMU1NTYx4eHqyiokJULiwsjHEcx3766SchLS4ujnEcxzQ0NNhvv/0mpNfW1jIfHx/G\ncRw7duyYkF5YWMg4jmOhoaENNZVKY8aMYerq6uzOnTtCmqWlJRs6dCjjOI7FxsYK6XPnzmUcx7FT\np06JzvHhw4eS/b799tuM4ziWnp4uSvfy8mI8z4vSPv30U8ZxHEtJSWGMMbZ9+3amoaHB+vXrx/7+\n++9mnUd1dbXkejLGWEpKClNTU2PTp08XpU+bNo1xHMcuX74s2aZ+fRj7330QHR2t8vheXl4q75EF\nCxY0+7rcu3ePWVpaMnV1ddGxla5evdpkfQoLCyXb3bhxg3Xu3JnZ29uL0l1cXFjnzp3ZvXv3JNvc\nvHlT+D0oKIjJZDJWUlLSaDnGGLOxsWFdu3YVpTXWdqquw7p16xjHcSwsLIwpFAohvaqqirm7uzNN\nTU3Ra8vT05NxHMd27dqlct/17zfy9LX0PYoQQgipry3fSxod9vn222/D1tYWY8aMQUJCAhISEjBm\nzBhYW1vjnXfeEcpdvnwZampq+Pzzz4W0mpoazJkzB3v27MGRI0fw7bffwtXVFb169RL1EJGWc3R0\nREhIiCht/vz5MDAwwObNm4W0jRs3orKyEjExMTA3NxeVf//992FqaoqtW7dK9u/q6oqpU6eK0q5f\nv47du3fD0dFRMnQSgGgY7/r161FbW4uVK1dCV1dXVG7RokXgOE7lcV977TV4eHgIf/M8j2nTpgEA\nTpw4IaSzx3wWzcfHBzU1NUIvYl5eHoqLizFt2jTY2toKvYDAo+53IyMj9OnTR3SOqp7XmjFjBgA0\nONxQFcbm5UBEAAAgAElEQVQY1q9fj8mTJ2PgwIGQy+XN6i0DAA0NDcn1BIAhQ4agR48ekmGMreny\n5ctITU2Fs7Oz5B6JiIiAiYkJtm3bhocPHza6nz179qC4uBghISEYMmSIJL85k6Ko6iFV9jTn5+eL\nhkJyHAd1dXWVzxrXH8Kupqam8jo3NdT9caxevRoGBgb4+uuvRb2C2tra+OSTT/DgwQP8/PPPAB61\nfXp6OlxdXUU93gDw+eef03PUhBBCCGlSo8M+tbW1ceTIEcyZMwdvvPEGGGPw8/PDihUroK2tLZRj\njEGhUIg+lHMch0uXLuHHH3/E7du30aVLF0yfPh0fffQRTXjwhAYNGiRJ09bWhrOzM+RyOYqKimBt\nbY3MzEwAQHp6usrhu2pqasjNzZWku7q6StKUwZevr2+TQwgzMzPBcRz27t2Lffv2SfJlMpnK4/bv\n31+SZmVlBQC4fft2o8dsDmV3ulwux6uvvioMAfX19YVcLsehQ4cAPHreLycnB6NHjxZtr1Ao8P33\n32PDhg04e/Ys7ty5I7rnlZN9NMfy5cuxb98+jBkzBtu2bYOGhkaLziU7OxtffPEFMjIyUFJSIgq2\nNDU1W7Svljh16hQAqAzYZDIZ3NzccODAAeTl5cHJyanB/WRlZQEA/P39H7su169fx5IlS3Dw4EH8\n9ddfuH//vii/uLhYeJZz0qRJmD9/Pnr16oXJkyfD29sbAwYMEP0/BgCTJ0/G7t270atXL0yZMgW+\nvr4YOHCgMOS1Nd29exdnzpyBtbU1Fi5cKMlXDre+cOECgEdDPgFg8ODBkrJdunSBtbU1Ll++3Or1\nJIQQQsg/R5NRWJcuXfDTTz81WsbW1layaHuHDh2aNWkDablOnTqpTFfOMFheXg7gf8tprFy5ssF9\nqQrkVM1UqNxnc3pkysrKwBgT9QTXP+bdu3cl6Xp6epI05RcF9SeJeRy9e/eGoaGh0MMnl8vRrVs3\nWFlZwcvLC3Fxcbhw4QIuXrwIhUIhGnsNAOHh4Vi7di1sbW0xfvx4mJubQ0NDA7du3cI333yD6urq\nZtclIyMDADB8+PAWB37p6ekYOnQo1NTU8Morr8De3h4dO3YEx3GIi4tr08k/KioqAKi+RwAIPZLK\ncg1pyf2kSllZGdzc3HD16lV4enoiICAA+vr64HkeycnJSElJEV2PDz74AEZGRli3bh0WLlyIhQsX\nQlNTE+PHj8fy5cuF19TEiROhrq6Or776Cl9//TWWL18ONTU1DB8+HF9//bXwTGhrUE6mVVRUhM8+\n+0xlGY7jhImZlG3WUA+xmZkZBX+EEPIMMcbAwKBgCijYo04R4fcG0hvLe9r7emGPj+eoLq10/Lb0\n3HXB1e89JFJ///23yvQbN24A+N/EHMpgKjc3Fw4ODs3ev6p2NzAwAABcu3atye319PTA8zwqKysh\nk8mafdy2xvM8PD09ceDAAVRUVEAulyMgIACAuFfw4sWLojTgUduuXbsWzs7OOHr0qKh3LTMzE998\n802L6vL999/js88+w7vvvgsNDY0WLVi/ZMkS1NTUICUlBQMGDBDl/fjjj5LyyuGAqmYkVQYUzaW8\np5T3Wn3KdFWBfF3K++nq1astOr7S999/j7/++guLFy/G/PnzRXnFxcVISUmRbDN9+nRMnz4dpaWl\nwmRCW7ZswZUrV0QTAQUFBSEoKAh37txBWloatm/fjo0bNyI3Nxdnz56VTJD0uJRtNGDAAPz2229N\nlle+rpU9gvU1dE0IIf9T98P5i/Zh8EmP/0zPBe2jLQh5ETx3wR//Wes+t8I+/eetVZaeni5Jq6qq\nQk5ODgwNDYWhbu7u7ti1axeOHj3aouBPFVdXV3Ach6SkJCgUikafL3J3d8fJkyeRmZkJLy+vJzqu\nKh06dADweL2BPj4+SEhIwHfffYfr168Ls3laW1vDzs4OycnJuHTpkuR5v4KCAgCAn5+fZFilshev\nJYyMjJCYmIihQ4di+vTpANDsADA/P19YYqOuGzduID8/X1JeOQvkX3/9JSyToXTy5ElJ+cba18XF\nBQCE5ybrun//Po4fPw4tLS289NJLjZ6Dm5sbAODw4cOYMGFCo2VVUZ5n/aG5jDEcPXq00W1NTEww\nbtw4jBs3Di4uLkhNTcWdO3ckz6fq6upixIgRGDFiBG7fvo2EhATk5uaid+/eLa6vKrq6unB0dMTZ\ns2dRWVkJHR2dRsv37dsXgOq2LyoqouUeniP/PvxvcPjfl2j1v1Crm1c/v7G8+vmqZo9tlQ+2/+CA\nhxBC2rvnLvgjTbtw4QLi4uJEwUJMTAxu376N8PBwIS00NBQLFy5EREQEPDw8JAFgeXk5CgoKRFPR\nN8TMzAxBQUH4+eefsWTJEnz88cei/KtXrwrP57377ruIjY1FeHg4fvnlF8majjdu3MCtW7fg6OjY\n4nMH/hfMPM6HXWVv3rJly8BxnKh3z9vbG7t370Z5eblkmQHl5CL1e2jy8vKwZMmSFtcDeBQAJiUl\nwdfXF2+//bZogpvG2NjY4OLFi8jNzRXa8MGDBwgLC0NNTY3kA6Ey0NqwYYPoWb2ffvoJqampkvLK\niU1UtW+XLl3g5eWFlJQU/Pjjj5gyZYqQt3TpUpSUlCA0NLTJ53qVyyls2LABU6dOlXxJUPd+aqgN\ngEdfhNRddmbFihU4ffq05JxSUlIkx7h37x7Ky8uhrq4uBLxpaWkYNGiQ6MsNhUKB0tJScBzX6j3Z\n4eHheO+99zBjxgx8//33ki8Wzp49i06dOsHU1BTW1tbw9PREWloadu3aJVrKIjIyEgqFgkZLPCeW\nH5Wue0oIIYQ8Dyj4ewH5+/tj5syZ2L9/PxwcHHDixAkkJibCzs5OtE6iqakptmzZgkmTJqF3794Y\nMWIE7O3tUVVVhYKCAqSkpCAkJARr1qxp1nHXrFmD06dPIzIyEgkJCfDy8sKDBw9w9uxZnDx5Uljg\nu1evXvj2228RFhYGBwcHBAQEwMbGBrdu3cKlS5eQnp6OhQsXPnbwp6OjAzc3N6SmpiI4OBj29vbg\neR7BwcGSxdrr69OnDwwMDFBSUgJ7e3vRM2fe3t744YcfhN/rsrCwQFBQEHbt2oWXX34Z3t7euHbt\nGvbu3YtXXnlF5bqFQNMzk9YNAN966y1wHIfg4OBGtwkLC8Ovv/6KQYMGYeLEiVBTU0NiYiJqa2vR\nt29fYVIWpTFjxqBbt27YsGEDrly5AmdnZ5w/fx7JyckYMWIEDhw4ICrfo0cPWFpaYuvWrdDU1ISV\nlRU4jsOsWbOgp6eHtWvXYvDgwXjjjTfw888/o3v37sjOzsavv/4KOzs7LF26tNH6A48mpfnxxx8x\nYsQIDB06FAEBAXByckJZWRkyMzNha2vb6LqJb7zxBpYuXYqwsDDI5XJYWlrixIkTyMzMREBAAPbv\n3y9pA0NDQ7i7u8Pa2hr379/HwYMHUVhYiPDwcGHil/DwcNy4cQODBg2CjY0NGGNITk7GqVOnMGrU\nKHTv3r3Jc2uJmTNn4rfffsOWLVuQlpYmrFlYXFyMP/74Azk5OaJ1E7/99lsMHjwYEydOxIQJE2Bj\nY4OUlBRcvXoVffr0ESaFIYQQQghRhYK/F9DAgQMRERGByMhIHDp0CDKZTPgwXH+h51GjRgkzQyYl\nJeHAgQPQ19eHtbU1/vWvf0mWjGhMp06dcPz4cXzxxRfYuXOnsJRD9+7dERkZKSo7Y8YMODs746uv\nvkJqaipu3rwJY2Nj2NraYsGCBXjttdeEshzHtbjHYtOmTZgzZw727dsnPLc2ZMiQJoM/juPg5eWF\nhIQESYCnHAJav0dQKT4+HtbW1ti1axdWrVoFe3t7LF68GCNHjlQZ/Kk6L1VpxsbGOHLkiBAA8jwv\nWUahrlGjRmHbtm1YsmQJNm7cCH19fQwfPhwxMTGYNGmSZP8ymQyJiYmYM2cOkpKScOzYMXh4eCAt\nLQ179+7FwYMHReV5nsfPP/+MDz/8ED/++CPu3LkjBKV6enpwdHREVlYWoqKicPjwYSQkJMDCwgJh\nYWFYsGABTExMGqx7XZ6ensjOzsaiRYuQmJiIQ4cOwcTEBM7Ozvi///u/Rrft3Lkz5HI5PvjgAxw6\ndAgKhQIeHh5IT0/Hvn37JAFtTEwMDh48iMzMTOzZswd6enp46aWXEBUVhddff10o99FHH2Hnzp3I\nzs7GwYMHoaWlBTs7O3z77bei5W2Alj+T3NB9vmnTJrz66qv4z3/+g4SEBNy9exfm5ubo0aMH1q5d\ni169egll+/Tpg9TUVHz44YdISEiApqYmhg4diu3bt+ONN96gnj9CCHnGOHDgOR4c9+hfnuOFtPrp\njeW1NP1J9/VYx3/S7f9JbdHK59IxqmPb3aPscRdNawMcxwFRTRSKevx13l50crkcvr6+iIqKwoIF\nC551dQghhNTTrPcx8kxx4F7ID4Mt3tc/+IPx83wuhLQGjuPaLN557nr+GpqgRdkAfBQtZEwIIeT5\n9YXfF8LvDOL3tPpv5nXzG8urn68q70X4YPysP+QrAz9CCGmvnrvgryH0nzUhhJAXwbxB8551FQgh\nhBCVqBuNEEIIIYQQQtqB5+6Zv6aq05ZjYAkhhJAnQe9RhBBCnlRbvpdQzx8hhBBCCCGEtAMU/BFC\nCCGEEEJIO0DBHyGEEEIIIYS0AxT8EUIIIYQQQkg7QMEfIYQQQgghhLQDFPwRQgghhBBCSDtAwR8h\nhBBCCCGEtAMU/BFCCCGEEEJIO0DBHyGEEEIIIYS0AxT8kXZjw4YN4Hke8fHxzd6G53n4+PiI0ry9\nvcHz9NJpK49znZ4GVfcCABw9ehTe3t4wMjICz/MYO3YsgLa/T2xtbdG1a9c22z8hhBBC/nnoEyx5\n4RQWFoLneYSGhj7W9hzHPXH5lu7jefa8BlvPYxvXr9Pt27cxatQonD59GsHBwYiKisLkyZOFsm19\nDs9jGxFCCCHk+aX2rCtASEspP/A+jQ++ubm50NbWbvPjPA8okGicqnshKysLZWVliImJwQcffCDK\n27hxI+7du/c0q0gIIYQQ0igK/sgLhzEm+rctOTg4tPkxnhdPoz1fZKruheLiYgCAmZmZJK9Lly5t\nXidCCCGEkJagYZ8vELlcDp7nER0dDblcDk9PT+jq6sLExATBwcG4fv26yu1OnjyJCRMmwMzMDDKZ\nDPb29vjoo49QVVXV4P7T09Ph5+cHfX19GBkZCWXKy8sRGRkJJycnaGtrw9jYGAMGDMDy5cslx01O\nTsaIESNgbGwMLS0tODk5YenSpaitrRWVqzvs8PDhwxg4cCB0dHRgYmKCkJAQlJWVicra2dkBAOLj\n48HzvPCTmprarHZkjGHnzp3o378/tLW1YWlpiVmzZqGiokJStqHnvFSJjY1Fhw4dMGTIEJSXlwvp\nO3fuhLe3N/T19aGtrY1+/fohNja2WfsEgIqKCsTExMDT0xPm5ubQ1NSEjY0NZsyYgRs3bkjKN/as\nWUhICHieR1FRkfD3m2++CQAIDQ0VtWddp06dwrhx42BqagqZTAYHBwd88sknknuoKb///jsmTZoE\nCwsLyGQydOnSBWPHjkVGRkaT2/7www8YPXo0bGxsIJPJYGpqisDAQGRnZ0vKMsawfv16uLq6wsjI\nCB07doSNjQ3Gjx+P33//XVR2x44d8PT0hKmpKbS0tNC5c2cEBAQgMTFRVK7+vcDzPEJCQgCI2055\nHzZ0Haqrq7Fs2TL07dsXHTt2hIGBAYYNG9bg/ZucnIxBgwZBW1sbZmZmmD59uug1QQghhBDSXNTz\n9wI6evQolixZglGjRmH27NnIysrC5s2bkZGRgaysLFGwtmvXLkyePBkymQyBgYEwNzdHdnY2YmJi\nkJycjNTUVKirq4v2n5GRgcWLF8PPzw8zZ85ESUkJAODGjRvw9PTEpUuX4ObmhvDwcFRXV+OPP/5A\nTEwM5s6dK+xj1apVmDVrFjp16oSgoCAYGhoiLS0NEREROH78OHbu3Ck5r4SEBOzfvx+jR4/G4MGD\nkZKSgo0bNyI/Px9paWkAABcXF8yePRvffPMNnJ2dERgYKGxvY2PTrPb76aef8Ouvv2LSpEkYPnw4\njhw5glWrViEzMxPp6emS9mjOcMglS5bg448/xqhRo7B9+3ZoamoCAObNm4fly5fD1tYWU6ZMgba2\nNg4fPox33nkH58+fx1dffdXkvs+dO4fo6GgMHToUEydOhJaWFnJycvDdd9/h8OHD+P3332FgYNDs\nOtfNCwoKQnl5Ofbs2YPAwEA4OztLyqekpODVV18FYwwTJ06ElZUVjhw5gsWLF+OXX35BWloaZDJZ\nk+exbds2vPHGG1BTU8OYMWNgZ2eH4uJipKWlYefOnRg0aFCj24eFhaFfv34YPnw4jI2NUVBQgD17\n9uCXX36BXC6Hu7u7UPaDDz7A8uXL0bdvX4SEhEBTUxNXrlyBXC7HsWPH0K9fPwDA6tWrER4eDnt7\ne0yZMgW6urq4evUqfvvtNxw+fBh+fn4Ntt2nn36KnJwcSdvZ2tqqLA8A9+/fh7+/P9LT0+Hm5oZ3\n3nkHlZWV2LNnD4YOHYrt27cjKChIKH/48GEEBARAU1MTr7/+OkxMTLB//34MGzYMDx8+FO4zQggh\nhJBmYc+R5lTnOavyU5WcnMw4jmMcx7G4uDhRXmRkJOM4joWHhwtpJSUlTFdXl3Xr1o0VFxeLyi9b\ntoxxHMe+/PJLlfvftGmT5PhBQUGM4zi2aNEiSd61a9eE38+cOcPU1NSYh4cHq6ioEJULCwtjHMex\nn376SUiLi4tjHMcxDQ0N9ttvvwnptbW1zMfHh3Ecx44dOyakFxYWMo7jWGhoaENNpZLyOBzHsSNH\njojygoODGcdxbPny5aJ0juOYj4+PKM3Ly4vxPM8YY0yhULD333+fcRzHpk2bxmpra4Vyhw4dYhzH\nsaCgIFZdXS2kP3z4kAUGBjKO41hWVlaT9S4vL2e3bt2SpG/evJlxHMcWLlzYYP3qmzZtGuM4jl2+\nfFlIU7ZLfHy8pHxNTQ2zs7NjHTp0YKmpqaK8kJAQxnEci46ObvIciouLmba2NjMwMGDnzp2T5Ne9\nfxqqT2FhoWS78+fPM11dXebn5ydKNzQ0ZC+//DJTKBSSbeq2pYuLC+vcuTO7d++epNzNmzdFf6u6\nFxprO1XXYf78+YzjOLZ06VJReklJCbO1tWWmpqZCXWpqapitrS1TV1dnJ06cEMrW1NSwoUOHMo7j\nWNeuXSXHJc9We36PIoQQ0jra8r2Ehn2+gBwdHYXhZkrz58+HgYEBNm/eLKRt3LgRlZWViImJgbm5\nuaj8+++/D1NTU2zdulWyf1dXV0ydOlWUdv36dezevRuOjo6IiIiQbGNhYSH8vn79etTW1mLlypXQ\n1dUVlVu0aBE4jlN53Ndeew0eHh7C3zzPY9q0aQCAEydOCOnsCZ9N8/f3lwzlXLhwITp06ICNGzc2\nez+1tbUIDQ3F119/jTlz5gjDV5VWr14Nnuexfv16aGhoCOlqamr4/PPPATzqDWuKnp6epGcPeNRe\nurq6SEpKanadWyo9PR0FBQUYNWoUPD09RXmLFy+GhoZGs2YJjY+Px7179zBv3jz06NFDkl/3/mmI\nqp5dR0dHeHt7Iy0tDTU1NUI6x3HQ1NRU2QNaty05joO6urrK4Zl1e9Bbg0KhwLp16+Dk5CSZHMbE\nxARz585FaWmpcD0zMjJw+fJlBAYGon///kLZDh06CPcPIYQQQkhLtJ9hn097JsM2nDxD1fA4bW1t\nODs7Qy6Xo6ioCNbW1sjMzATw6AP8mTNnJNuoqakhNzdXku7q6ipJUwZfvr6+TQ6DzMzMBMdx2Lt3\nL/bt2yfJl8lkKo9b9wOukpWVFYBHU+q3lvpBDPBoco4uXbrg7NmzYIw1eY6MMQQFBWHfvn1YtGiR\nyoA4MzMTOjo6WL16tSTv4cOHAKCyHVRJSkrCihUrcPz4cZSVlYmem1ROOtIWTp06BQDw8vKS5FlY\nWMDe3h7nz59HVVUVOnbs2OB+srKyADwKvB/XpUuXsHjxYiQnJ6O4uBgPHjwQ8jiOw82bN4WJVyZN\nmoR169ahX79+GD9+PLy9veHq6ioKwpXl5s+fj169emHy5Mnw9vbGgAED2mSG1wsXLqC8vBw2NjaI\nioqS5F+8eFEoFxAQILT94MGDJWXd3d3RoUOHVq8jIYQQQv7Z2k/w9w+aybBTp04q05UffJWTjSgn\nhVi5cmWD+1IV5KiauVC5T0tLyybrV1ZWBsZYg70THMfh7t27knQ9PT1Jmprao1u0/iQxT6Kx9rt8\n+TIqKyslPZaqZGRkoGPHjnjllVdU5iuDtM8++0xlfkPtUN+2bdswZcoU6OvrY/jw4bC1tYWWlhYY\nY1ixYgWqq6ub3MfjUk6Co+qeAABzc3OcO3cOFRUVjQZ/Lbl/VLl48SLc3NxQWVmJYcOGYdy4cdDR\n0QHP89i1axdOnTolaoeVK1eia9euiIuLwyeffAIA0NXVRXBwMGJiYoS6fvDBBzAyMsK6deuwcOFC\nLFy4EJqamhg/fjyWL1/e4L3yOJSvx9OnT+P06dMqy3AcJ0yio2wzU1NTSTme52FiYtJqdSOEEEJI\n+9B+gr9/kL///ltlunLmR319fQD/C6Zyc3NbtGRBY0Plrl271uT2enp64HkelZWVzZoI5GlrrP14\nnoeOjk6T++A4DomJiRg6dCiGDRuGxMREuLi4iMro6elBU1OzWW3WmM8++wza2trIzs4WZjpVWrp0\nqaS8cgijQqGQDGesOwtpcyjvIVWziirTOY5TGbjXpbx/rl69+lgB4IoVK1BeXo7//ve/wiLqSkeP\nHhV6yZTU1NQwb948zJs3D1evXkVycjJiY2OxevVq3LlzBxs2bBDKTp8+HdOnT0dpaakwydCWLVuE\nCWJai7KNJk+ejP/+979Nlle+jpUTLtWlUChQWlpKy0kQQgghpEXomb8XUHp6uiStqqoKOTk5MDQ0\nhLW1NQAIsx8ePXr0iY/p6uoKjuOQlJQEhULRaFl3d3coFAph2GlrUw53e9zeQFVT6hcVFaGoqAi9\nevVq9mLnLi4u+PXXX8EYg5+fH06ePCnKd3d3x/Xr13H58uXHqqdSfn4+evbsKQn8fv/9d9y/f19S\n3tDQEIwx/PXXX6J0hUKBU6dOSc6vsfZUBrQpKSmSvOLiYuTl5cHOzq7RXj8AcHNzA/Bo9srHkZ+f\nD47jMHr0aFH6/fv38fvvvzd6zaysrDB16lQkJibCxMQEe/fuVVnOxMQE48aNw549e9C3b1+kpqbi\nzp07j1VfVXr27AldXV1kZWU1+RoCIMweqpzptq5jx461am84IYQQQtoHCv5eQBcuXEBcXJwoLSYm\nBrdv3xZN1BIaGgodHR1EREQgLy9Psp/y8nLk5OQ065hmZmYICgrChQsXsGTJEkn+1atXhd/fffdd\ndOjQAeHh4SqfR7tx40azn3VTxdDQEACEtepaKjExEUeOHBGlRUZGQqFQIDg4uEX76t+/Pw4fPgyF\nQoFhw4aJ2jM8PBwA8NZbb6nscSssLGxWYGhjY4O8vDxRD1BFRQVmz56tsrwy0KrbuwUAX331FQoL\nCyXllRObqGrPwYMHw87ODgkJCZK1+D7++GM8fPiwWW0WHBwMbW1tLFu2DOfOnRPlMcYaXKNSycbG\nBowx0RcfjDFERERIesYePHig8guPiooK3Lt3T9QbrSqovXfvHsrLy6Gurt6qz9V16NABM2bMQH5+\nPiIiIlQGgJmZmbh37x6AR8/22traYvfu3aIJj2pqahAZGdlq9SKEEEJI+0HDPl9A/v7+mDlzJvbv\n3w8HBwecOHECiYmJsLOzE00kYWpqii1btmDSpEno3bs3RowYAXt7e1RVVaGgoAApKSkICQnBmjVr\nmnXcNWvW4PTp04iMjERCQgK8vLzw4MEDnD17FidPnkRpaSkAoFevXvj2228RFhYGBwcHBAQEwMbG\nBrdu3cKlS5eQnp6OhQsXwtHR8bHOX0dHB25ubkhNTUVwcDDs7e3B8zyCg4OFXs/GjBgxAiNGjBDW\nrEtOTsbx48fx8ssvCwFbU+rOOOrq6orDhw/D398ffn5+SEpKQt++ffHqq68iIiICS5YsQffu3fHK\nK6/AysoKJSUlOH/+PDIzM/Hjjz82uT5hWFgYZs+ejX79+mHs2LGorq7GoUOHYGVlBUtLS8nsp6Gh\nofjiiy8QFRWFnJwc2NnZ4cSJEzh79iy8vLwkAc/AgQOhpaWFFStW4NatW8KzZJ988gk4jsMPP/yA\n4cOHw8/PDxMnToSlpSXkcjkyMzPh6uoqmblSFTMzM/zwww+YOnUq+vfvj8DAQHTt2hV///03UlNT\nERAQgK+//rrB7d955x3ExcVh7NixmDRpEvT09JCWlobCwkJ4e3uLhmfevXsXgwYNgqOjI1xcXNCl\nSxeUl5cjISEBd+/eFT2DOWbMGBgaGsLd3R3W1ta4f/8+Dh48iMLCQoSHhz/xxC/1r81nn32GEydO\nYNmyZUhISMDgwYNhZGSEv/76C9nZ2cjLy8P169ehpaUFnuexbt06jBw5El5eXpgyZQqMjY1x4MAB\naGhowMLC4olnviWEEEJIO9Nmi0g8huZU5zmr8lOlXIcvOjqayeVy5unpyTp27MiMjY1ZcHCwZC0/\npXPnzrGQkBDWpUsXpqGhwUxNTVn//v1ZREQEu3Dhgsr9N+TWrVssIiKCOTg4ME1NTWZiYsI8PDzY\nihUrJGWPHj3KJkyYwCwsLJiGhgazsLBgHh4e7PPPP2dXrlwRym3YsIHxPK9yrbSG6pSXl8cCAgKY\noaEh43me8TzPUlJSGm2/usfZuXMn69+/P9PS0mLm5uYsPDxcsiYhY6rXdvP29la5jt7x48eZgYEB\nMzU1ZadPnxbSDx48yAICApiJiQnT0NBgnTt3Zt7e3uyrr75ipaWljdZZafXq1axnz55MS0uLWVtb\ns4h+YokAACAASURBVDlz5rA7d+4wW1tblWu9nTp1ivn5+bGOHTsyAwMDFhQUxPLz81lISAjjeV60\nzh9jjB04cIC5ubkxbW1txnGc5PxycnLY2LFjmbGxMdPQ0GDdu3dnH3/8MauqqmpW/ZWysrLYuHHj\nmKmpKdPU1GTW1tZs/PjxovUdG7ofkpKS2MCBA5muri4zMTFh48ePZ5cuXZKc08OHD9nSpUuZv78/\n69y5M9PU1GSWlpbM39+f7du3T7TPtWvXstGjRzNbW1smk8lYp06dmKenJ9u8ebOk7qruhcbu3Ybu\nk5qaGrZ69Wo2YMAApqenx7S0tFi3bt1YUFAQ27RpE6upqRGVP3LkCBs4cCDT0tJinTp1Ym+99RYr\nKytr8NqTZ6s9v0cRQghpHW35XsL9/wM8FziOa/Kb7OaU+aeSy+Xw9fVFVFQUFixY8KyrQwghpJ72\n/B5FCCGkdbTlewk980cIIYQQQggh7QAFf4QQQgghhBDSDlDwRwghhBBCCCHtAD3zRwghhLQSeo8i\nhBDypOiZP0IIIYQQQgghT4SCP0IIIYQQQghpByj4I4QQQgghhJB2gII/QgghhBBCCGkHKPgjhBBC\nCCGEkHaAgj9CCCGEEEIIaQco+COEEEIIIYSQdoCCP0IIIYQQQghpB5oM/q5cuYLx48fDwMAA+vr6\nGDduHK5cudKsnRcWFiI4OBjW1tbQ1tbGSy+9hMjISNy9e/eJK05IS23YsAE8zyM+Pv5ZV4X8fyEh\nIeB5HkVFRc+6KgK5XA6e5xEdHS3Ji4+PR58+fdCxY0fwPI+VK1cCAHieh4+PT5vUp7CwEDzPIzQ0\ntE32TwghhJD2o9Hg7+7du/D19UVeXh42btyITZs24eLFi/Dx8WkygKusrMTQoUORkZGBRYsW4eDB\ng5g+fTqWL1+ON998s1VPgrQvT/phmOO4Vq7Ri+N5DLae1+tRv17p6ekIDQ3Fw4cPMXv2bERFRWHA\ngAENlm/r+hBCCCGEtJRaY5mxsbEoKChAXl4e7OzsAAB9+vRB9+7dsX79esyZM6fBbTMyMlBQUIBf\nfvkFw4YNAwB4eXmhrKwMX375Je7fvw+ZTNaKp0LaC+WHYPow/Hiet3ZjjD3rKoi4u7sjNzcXJiYm\novSDBw8CeNT75+bmJsrLzc2Ftrb2U6sjIYQQQsjjaLTnLyEhAR4eHkLgB/w/9u48Lqrq/x/46w7b\nMLLIviiLQkiBhUooKLK4ESgwlrj8EuFTfpIE+Vi2YKG4gqbllmZWAuo3NQ1FyTSVVRGBUHKDVJZU\nQBQEMUWF8/vDz8yH4V42BZd4Px8PHg7nnnvOuedenHnPOfdcwNLSEkOHDsXevXtbLbihoQEAoK2t\nrZCura0Nxthz94GPvDhk1w5dQ4+H/v5ap66uDhsbG+jq6iqkl5WVAQCMjIx4+9jY2KB3795PpX2E\nEEIIIY+r1eDv7NmzsLe356W/8sorOHfuXKsFjxo1Cvb29vj4449x/vx51NXV4ejRo1izZg1mzJgB\ndXX1J2t5N9T0XqSUlBS4urpCU1MT+vr6CAwMRHl5ueB+eXl5mDBhAoyMjCAWi2FtbY25c+fizp07\nLZafkZGBkSNHQltbW+FDcE1NDSIjI2FnZweJRAI9PT0MGTIEK1eu5NWbnJwMb29v6OnpQV1dHXZ2\ndli2bJn8iwGZpvfiHTp0CC4uLtDQ0IC+vj6CgoJQVVWlkFf2ZURcXBxEIpH8Jy0trV39yBjD7t27\nMWjQIEgkEpiammLWrFmora1tsT+aa2nqaWFhIQIDA2FpaQmxWAx9fX0MGjQIUVFR7WpbYWEhPvro\nIzg4OEBXVxfq6uqwt7fHkiVL8PDhQ17+1u41s7S0RJ8+fRR+j4+PBwD06dNH3m/N909ISJBfWxoa\nGnj99dfx/ffft6v9Te3atQsjRoyAjo4OJBIJXnrpJcyYMaPNe4Zra2sRExMDV1dXGBsbQ01NDRYW\nFpgxYwYqKip4+W/duoXPPvsMtra20NDQQM+ePdGvXz9Mnz5d4dq5d+8eli9fjv79+0NLSwuampqw\nsrLC1KlTcfnyZXm+5udd9ntsbCyv72RaOg/l5eWYNWsW+vbtC7FYDGNjY0ydOhXFxcWCx75+/Xq8\n/PLLUFdXh5WVFZYuXcr7eyGEEEIIeVytTvusrq6Gjo4OL11XVxfV1dWtFqyiooIjR45g3LhxsLOz\nk6dPnz4da9eufczmEgDIzMxEdHQ0xo0bh/DwcGRnZ2Pr1q04duwYsrOzFYK1hIQETJo0CWKxGP7+\n/jA2NkZubi5iYmKQnJyMtLQ0qKioKJR/7NgxLF26FCNHjkRISAgqKysBABUVFXB1dcXFixfh5OSE\nsLAw1NfX448//kBMTAw+/PBDeRnr1q3DrFmzYGhoCKlUCh0dHaSnpyMiIgInT57E7t27eceVmJiI\npKQk+Pr6YtiwYUhNTUV8fDwuXbqE9PR0AMCAAQMQHh6O1atXw8HBAf7+/vL9LSws2tV/u3btwm+/\n/YaJEyfCy8sLR48exbp165CVlYWMjAxef7Q2TbLptqtXr8LJyQkNDQ3w8/ODpaUlqqurcf78eWzc\nuLFdAeDPP/+M2NhYjBgxAqNHj0Z9fT1SUlIQGRmJnJwcJCQktNqG1rbNnj0bsbGxOH36NP7zn/+g\nZ8+eAB4FhTLLly/Hp59+CkNDQwQHB0NVVRW7du3C9OnTkZeXh3Xr1rV5DAAwa9YsrFu3DkZGRpg4\ncSJ0dXVx+fJl7Nq1C97e3jAzM2tx33PnzmHBggUYMWIEAgICoK6ujlOnTuHbb7/FoUOH8Pvvv8vb\nzhjD6NGjkZubizFjxsDf3x8PHjzA5cuXsWPHDsyePVv+9zB16lTs3r0bw4YNw5gxYyASiVBcXIxf\nf/0VkydPVpjh0LTv+vTpg/nz52PPnj28vmuprwHgzz//hLu7OyoqKuDj44MJEyagtLQUO3fuxMGD\nB3HixAmFOufNm4fFixejd+/eCAkJQUNDA9asWYPjx4+3q88JIYQQQtrEWqGqqsoiIiJ46Z999hlT\nVlZubVdWV1fHBg0axPr168e2bdvG0tPT2YoVK5iWlhYLCQkR3KeN5rQ7j0L+5ORn+tOZkpOTGcdx\njOM4tnnzZoVtkZGRjOM4FhYWJk+rrKxkmpqazMrKipWVlSnk/+KLLxjHcWzFihWC5W/ZsoVXv1Qq\nZRzHsSVLlvC2Xbt2Tf76zJkzTFlZmTk7O7Pa2lqFfKGhoYzjOLZr1y552ubNmxnHcUxVVZUdP35c\nnt7Q0MA8PDwYx3HsxIkT8vTi4mLGcRwLDg5uqasEyerhOI4dPXpUYVtgYCDjOI6tXLlSnibrjwUL\nFvDKKioq4rVh9erVjOM4lpiYyMtfVVXVrjZeu3aNPXjwgJc+ffp0xnEcy8jIUEjnOI55eHgIlmVh\nYcH69OmjkDZt2jTGcRwrKSnh5f/zzz+ZkpIS6927N6uoqJCn3759m9nb2zOO41hqamqbx7B3717G\ncRxzdHTknf979+4p9IVQe2pqalh1dTWv3K1btzKO49jixYvlaadPn2Ycx7EPPviAl//vv/9md+/e\nZYwxduvWLcZxHBs/fjwv34MHD9jt27flv7d03lvrO6HzMGTIECYWi1l6erpCemZmJlNRUWFjx46V\npxUWFjIlJSXWt29fhWMvKytjRkZGj3W9k2ejo+9RhBBCSHNd+V7S6rRPHR0dwRG+qqoq3v0wzX33\n3Xf4/fff8csvv2DKlCkYNmwYPvzwQ6xcuRLffPMN8vPzBfeLioqS/6SkpLQvgu1mbG1tERQUpJD2\n6aefomfPnti6das8LT4+HnV1dYiJiYGxsbFC/g8++AAGBgbYvn07r3xHR0e8/fbbCmnl5eXYs2cP\nbG1tERERwdvHxMRE/nrjxo3yUQtNTU2FfEuWLAHHcYL1TpkyBc7OzvLfRSIRpk2bBgDIycmRp7Mn\nvF9t9OjRvCl6ixcvhpKSknxa5JMQWshIaARdiImJCZSV+QPyM2bMAAAcOXLkyRrXim3btqGxsRFz\n5syBoaGhPF1DQ0M+atmex2Rs2LABALB69Wre+VdTU2uzL7S0tARH1qZMmQJNTU3BPhDqc3V1dXm6\nbFROKJ+ysjI0NDRabVNH/f7778jKysI777yDYcOGKWwbMmQIfH19ceDAAdy+fRsA8OOPP6KxsREf\nfvihwrEbGxsjPDy8U9tGCCGEkOdLSkqKQgzUlVqd9mlnZ4czZ87w0s+dO4dXXnml1YLPnTsHHR0d\n3lSq119/HcCj1fFeffVV3n5z5s7534IeYKitr6XFKZoZOnQoL00ikcDBwQEpKSkoLS2Fubk5srKy\nADxaol7oPCorK+PChQu8dEdHR16aLPjy9PRsc7XIrKwscByHffv2Yf/+/bztYrFYsN5Bgwbx0nr1\n6gXg0X1dncXV1ZWXZmZmBjMzM5w9exaMscdaEdPX1xdz586FVCpFQEAARo0aBVdX1w4tBNLY2Ijv\nv/8esbGxOHv2LG7fvq1w/csWHekKp0+fBvBoVd7m3N3dAaDFL22ays7ORo8ePeDi4vLYbTly5AhW\nrVqFkydPoqqqSuG+t6Z9YGdnB3t7e8TExODUqVMYO3Yshg8frjDVHHgUUHp5eeHHH3/ElStX4O/v\nDzc3Nzg4OCjcu9dZZH97V65cEfxPvKysDI2Njfjzzz8xcOBAed83DxQB4b938nxz/PbR/6EMiotT\nyX4XSmv6d97Sfq3lAR59yaHEKUFJpAQlTgkiTiR/rST67+/t3C5//Rj7Nt/+JO14WmU9b6sgE0K6\nF3d3d/lnLQCC6010llaDP19fX8yZMwdFRUXyhSOKi4tx/PhxLFu2rNWCe/fujerqaly6dAlWVlby\ndNmHItmH+uY0ozUF08n/NB2VaUq2CmFNTQ0AyBe7kD2IWojQG57QaoayMk1NTdtsX1VVFRhjWLRo\nUYt1Cj0nUktLi5cmGwXrzEUvWuu/kpIS1NXV8Uas2sPS0hKZmZmIiorCzp075QuEDBw4ENHR0fJH\nnrQmLCwMGzZsgKWlJd566y0YGxtDVVUV1dXVWL16Nerr6zvcrvaSLXgjdP719PSgpKTEWxRHSE1N\njcJCMx21Y8cOTJ48Gdra2vDy8oKlpSXU1dXBGMOqVasU+kBJSQnJycmYP38+du/eLX8cQ69evfDR\nRx9h1qxZ8ry7du3C4sWL8eOPP8rvT9XT08P777+PyMhIwRHXxyX720tMTERiYqJgHo7j5Isuyf6+\nDAwMePmEzgd5vuWW5T7rJpAO4sB1TrDcmQHtU27H0y5LxIko6CbkGWj108706dOxbt06+Pn5YfHi\nxQCAyMhImJub47333pPnKykpgZWVFebPn4/IyEgAjx4mvXLlSnh7e+Ozzz6DmZkZcnJysHjxYjg6\nOtK32U/g+vXrgumylRBlj9eQBVMXLlyAjY1Nu8sX+s9YNhXt2rVrbe6vpaUFkUiEurq65/JZjq31\nn0gkkk8BlI0ICa2yKfuw3lz//v2xe/duPHjwANnZ2UhKSsLatWvh6+uLU6dOoV+/fi22q6KiAhs2\nbICDgwMyMzOhpqYm35aVlYXVq1cL7ifUPlkb2zvdFPjf9VJRUaEwjRcAbt68iYaGBsEAvbmePXs+\n0QjlwoULIZFIkJuby5s5IPSlk56eHtatW4d169bh7NmzOHz4MNasWYP//Oc/0NLSkk+RlkgkWLp0\nKZYuXYpLly7h6NGj+Prrr7Fo0SJwHNep0yxk/fTNN9/g3//+d5v5ZX+zlZWVvL4XWuGUENK5GBga\nWAOtrvuUyYLC52H093kPljurLAq4SavBn0QiwdGjRzF79mxMnToVjDGMHDkSq1atUnigMWMMjY2N\nCtNPzMzMcPLkScybNw+ff/45bty4IQ8aP/vss647omZYkyHUf4qMjAxe2p07d3Dq1Cno6OjA3Nwc\nwKOHVSckJCAzM7NDwZ8QR0dHcByHI0eOoLGxsdWpcoMHD0ZeXh6ysrIEpxA+KSUlJQCPPxqYlpbG\nuwZLS0tRWlqK/v37y/9jlAVOV65c4ZWRl5fXah0qKipwcXGBi4sLDA0NMXv2bBw6dKjV4K+oqAgA\nMHLkSIXAD3i0AqsQHR0dXL16lZdeXFwsGPy11ncDBgzAnj17kJqaCgcHB4VtqampAMBLF+Lk5IQD\nBw7g2LFjj/Ulz6VLl/Dqq6/yAr/ff/8d9+7da3VfOzs72NnZwd3dHQMGDMC+fft498cCgJWVFays\nrPDWW2/BwMAA+/bt69Tgb/DgwQAerczbnuDPwcEBCQkJSE9P502HF/p7J4SQf4JG1ohG1vjoF4q7\nn5rnbdr18xwsd0ZZz9sod5vznMzMzLBr165W81haWqKxsZGXbmNjI7iwB3kyBQUF2Lx5s8Iz5mJi\nYnDr1i2EhYXJ04KDg7F48WJERETA2dmZFwDW1NSgqKioXR/ojYyMIJVK8fPPPyM6OpoXPF29elU+\nlff999/Hpk2bEBYWhoMHDwqOZFRXV8PW1rbDxw78LygrLS19rP0PHz6Mo0ePwtPTU54WGRmJxsZG\nBAYGytNsbW2hqamJxMREhceeVFRUyEfCm8rLy4OVlRVvdEz2/MW2RkFlj6povrR/YWEhoqOjBfdx\ncnLCwYMHkZaWhuHDhwMA7t+/jw8++EAwv2yhptLSUt7UzClTpmDhwoVYsWIFpkyZIp+CWFdXh6io\nKHAcp9A/LQkJCcGBAwcQHh6Oo0ePKvTHvXv3cPfu3VZHJC0sLFBYWIjKykp5G2prawUXPikpKZHv\n01TzPr9x4wYqKip49wJWVFSgsbGx00eonZyc4OTkhC1btsDf3x9+fn4K2x88eICsrCz5PX6TJk3C\nwoULsXLlSkyZMkXeP2VlZS2O+BJCCCGPg0a5nz7ZVOf2Bo5dqfNucukkPVR6APjf1EMOnMLvtWj7\nnqN/utGjRyMkJARJSUmwsbFBTk4ODh8+jL59+yqMXhgYGGDbtm2YOHEi+vfvD29vb1hbW+POnTso\nKipCamoqgoKCsH79+nbVu379euTn5yMyMhKJiYlwc3PD/fv3cfbsWeTl5eHGjRsAAHt7e6xduxah\noaGwsbGBj48PLCwsUF1djYsXLyIjIwOLFy9+7OBPQ0MDTk5OSEtLQ2BgIKytrSESiRAYGCgf9WyN\nt7c3vL29ERAQgF69eiE5ORknT57E66+/rhA8q6ioICwsDEuXLsXAgQPh6+uL27dvY//+/XBzc1N4\nMDjwaCXM7777Dq6urujbty80NTWRn5+PgwcPwsLCAgEBAa22y8TEBFKpFAkJCXj99dfh7u6Oa9eu\nYd++fRgzZozgsxE/+OADHDp0CN7e3pg8eTLU1dXx22+/QUdHByYmJrzFkkaMGIGVK1fi3//+N8aP\nH48ePXrA0tISb7/9tvyh4p988gleffVVvPXWW1BRUUFCQgJKSkowc+ZMwcVymhs7dizCwsKwdu1a\n2NjYwM/PD7q6uigtLcXBgwfxww8/wNfXt8X9Q0NDER4ejoEDB2L8+PGor6/Hr7/+il69esHU1FTh\nmPLy8vDmm29iyJAhsLW1hZGREUpLS7Fnzx6oqanJz+eVK1cwcOBADBgwAPb29jA1NcX169exZ88e\niESiFoPlJ/F///d/8PDwgFQqxbBhw+Dg4ABlZWWUlJQgPT0d+vr6OHfuHADgpZdewty5c7Fo0SJ5\n3zc0NGDnzp1wcnJCUlJSp7ePdJ2T755s8T1M9rtQWtNvhlvar6U8jLFHUxcbG9DAGtDIGuWvGxr/\n+/t/X3d0e5eV9YRlP0k7mm6XjzwRQkgXkY1yP8TDZz7K/dwFf3Vz61rdzkU8P8Omz4qLiwsiIiIQ\nGRmJX3/9FWKxGFOnTsWyZct4Iyrjxo1Dbm4uli9fjiNHjuCXX36BtrY2zM3N8Z///EdwSlxLDA0N\ncfLkSSxfvhy7d++WP8rhpZdekt/rKTNjxgw4ODjgyy+/RFpaGm7evAk9PT1YWlpi3rx5mDJlijwv\nx3EdHg7fsmULZs+ejf3798vvvxs+fHirwZ+sngkTJiA4OBhLly7Frl27oK2tjdDQUCxZsoS36Mei\nRYugqqqK77//Hhs3bkSfPn0wb948jB07lheMTZkyBffu3cOxY8dw4sQJPHjwABYWFvjoo48wZ84c\n+X1drYmLi4O5uTkSEhKwbt06WFtbY+nSpYL1AcCoUaOwc+dOLFy4EFu2bIGenh4mTJiAJUuWwN7e\nntevXl5eWL58OTZt2oQvv/wSDx48gLu7u/zRHh999BGsra3x5ZdfIjY2FowxvPzyy/j888/xzjvv\ntNl+mdWrV8PFxQXr16/H9u3b8fDhQ/Tu3RsBAQEKq7oKnfuwsDAoKSnh66+/xqZNm2BgYIA333wT\nCxcuVJiWCzxaPfjjjz9GSkoK9u/fj9raWpiamkIqleKTTz6Bvb09gEcPao+KisLRo0fx22+/oaqq\nCkZGRhg+fDg++uijdq1M2tHrtG/fvsjLy8OKFSuwd+9efPfdd1BVVUWvXr3g5+en8DcAPFrZy9jY\nGGvWrMGGDRvQq1cvhIeHY+LEiRT8vWBe7/X6s24C6YDmgfOzDJY7K6BtMe9z9AVA09VvCSFPD8ee\no+coyL69fNI8/1QpKSnw9PREVFQU5s2b96ybQwghpJnu/B5FSEcwxp7/YPkFD7yF8pIXRNSTP9e6\nJc/dyB8hhBBCCPln4zgOytx/P4Z27S1OpInHDSxfiKnkTfM+R18APG+j3BT8EUIIIYQQ0g2IOBFE\nSiKoQOVZN6XbYIx1OLC0irJqu+DHRMEfIYQQQgghhHQBjuMereIJpedilJvu+SOEEEI6Cb1HEUII\neVJd+V7S8pO6CSGEEEIIIYT8Y1DwRwghhBBCCCHdAAV/hBBCCCGEENINUPBHCCGEEEIIId0ABX+E\nEEIIIYQQ0g1Q8EcIIYQQQggh3QAFf4QQQgghhBDSDVDwRwghhBBCCCHdAAV/hBBCCCGEENINUPBH\nSBextLREnz59nnUz/hFSUlIgEomwYMGCZ90UBS2d4/Pnz2Ps2LEwNDSESCTCgAEDAABBQUEQiUQo\nLS3tkva4u7tDJKL/1gkhhBAijD4lkBdOcXExRCIRgoODO7RfbGwsRCIR4uLiuqhlijiOA8dxT6Wu\nzva8BlvPW38KneOGhgZIpVIcOXIE48ePR1RUFEJCQlrM3xVtIoQQQggRovysG0BIR8k+3D7uh9yn\n9eH46NGjT6WerkSBROuEzvHly5dRWFiIGTNmYP369QrboqOjERERAVNT06fVREIIIYQQOQr+yAuH\nMabw7+Pu39X+CVM+n1ZfvaiEznFZWRkAwMjIiLfN2NgYxsbGXd4uQgghhBAhNO3zBdJ0Kl5KSgpc\nXV2hqakJfX19BAYGory8XHC/vLw8TJgwAUZGRhCLxbC2tsbcuXNx586dFsvPyMjAyJEjoa2tDV1d\nXXmempoaREZGws7ODhKJBHp6ehgyZAhWrlzJqzc5ORne3t7Q09ODuro67OzssGzZMjQ0NCjkazod\n89ChQ3BxcYGGhgb09fURFBSEqqoqhbx9+/YFAMTFxUEkEsl/0tLSWuy7oKAg/Otf/wIABAcHK+wn\nI7tfqr6+HnPnzkWfPn2gqqqK1atXAwByc3Mxc+ZM2NnZQVtbGxoaGhg0aBA2bNggWKfQ/WCye76K\ni4uxZs0a2NraQiwWw9LSEgsXLmx3sPXgwQOsWbMGo0aNQq9evaCmpgZTU1P8v//3/3Dx4kXB42/p\nXrOoqCiF/ouKioKnpycAYMGCBQp91XT/oqIiTJs2DSYmJlBTU4OlpSVmzZqFGzdutOsYZC5evIh3\n3nkH5ubmEIvFMDU1hZeXF/bt29fmvgkJCZg4cSL69u0LiUQCXV1djBo1CkeOHBHM/9NPP8HV1RUG\nBgZQV1dH79694ePjg8OHDyvkO3z4MEaPHg0TExOIxWKYmJjA09MTO3bsUMjX/BxbWlrC3d0dgGLf\nxcfHA2j5PDQ2NmLTpk0YPHgwNDQ0oKmpiaFDhyIhIUHwOE6dOoUxY8ZAQ0MDurq6mDBhQpfdR0gI\nIYSQfw4a+XsBZWZmIjo6GuPGjUN4eDiys7OxdetWHDt2DNnZ2QrBWkJCAiZNmgSxWAx/f38YGxsj\nNzcXMTExSE5ORlpaGlRUVBTKP3bsGJYuXYqRI0ciJCQElZWVAICKigq4urri4sWLcHJyQlhYGOrr\n6/HHH38gJiYGH374obyMdevWYdasWTA0NIRUKoWOjg7S09MRERGBkydPYvfu3bzjSkxMRFJSEnx9\nfTFs2DCkpqYiPj4ely5dQnp6OgBgwIABCA8Px+rVq+Hg4AB/f3/5/hYWFi32mVQqRU1NDfbu3Qt/\nf384ODi0mNff3x9nz57FG2+8AS0tLZiZmQEANm3ahKSkJLi5uWHcuHG4ffs2Dh48iJkzZ6KwsBBf\nffUVr6yWpk1+9NFHSE1Nxbhx4/DGG28gISEBUVFRuH//PhYvXtxi22Ru3ryJDz/8EG5ubvDz84O2\ntjYuXLiAnTt34tdff0Vubi4sLS3b1ZbmPDw8UFJSgri4OLi7u8uDGQDQ1tYG8GhBE1dXV1RXV0Mq\nlaJfv37Izs7GunXrkJSUhBMnTsDAwKDNutLS0uDj44O7d+9i7NixsLOzQ2VlJbKysrB582aMGzeu\n1f0/++wziMVieHh4wNjYGNeuXcOePXswZswY/PTTT5BKpfK8X3/9NcLCwmBtbY3JkydDU1MTV69e\nxfHjx3Ho0CGMHDkSALB//374+vrC1NQU/v7+0NPTQ1lZGXJycrB7925MnDixxX6dPXs2Tp06xeu7\nptdb8/PAGMPkyZPx008/wc7OTn4v6/79+/Hmm29i1apVmDVrljx/fn4+XF1dUV9fjwkTJsDS0lL+\nZZCOjk6bfU4IIYSQbow9R9rTnOesyU9VcnIy4ziOcRzHNm/erLAtMjKScRzHwsLC5GmVlZVMQngz\njAAAIABJREFUU1OTWVlZsbKyMoX8X3zxBeM4jq1YsUKw/C1btvDql0qljOM4tmTJEt62a9euyV+f\nOXOGKSsrM2dnZ1ZbW6uQLzQ0lHEcx3bt2iVP27x5M+M4jqmqqrLjx4/L0xsaGpiHhwfjOI6dOHFC\nnl5cXMw4jmPBwcEtdZUgWT1xcXGC293c3BjHcczR0ZHV1NTwtpeWlvLSHj58yLy8vJiSkhIrKSlR\n2GZhYcH69OmjkDZt2jTGcRyzsrJi5eXl8vQbN24wHR0dpqWlxe7fv9/msdTX1/POKWOMpaamMmVl\nZfbuu+8K1tu8jYwxNn/+fMZxHEtNTZWnya6FBQsWCNYv66vm18m8efPafW7u3r3LTE1NmYqKikLd\nMlevXm2zPcXFxbz9KioqWO/evZm1tbVC+oABA1jv3r3Z3bt3efvcvHlT/loqlTKxWMwqKytbzceY\n8Dlure+EzsM333zDOI5joaGhrLGxUZ5+584dNnjwYKampqbw9+Xq6so4jmMJCQmCZYtEIl695Onp\nzu9RhBBCOkdXvpfQtM8XkK2tLYKCghTSPv30U/Ts2RNbt26Vp8XHx6Ourg4xMTG8+4w++OADGBgY\nYPv27bzyHR0d8fbbbyuklZeXY8+ePbC1tUVERARvHxMTE/nrjRs3oqGhAWvWrIGmpqZCviVLloDj\nOMF6p0yZAmdnZ/nvIpEI06ZNAwDk5OTI01kX34e2YMECaGlp8dJlI4BNKSkpYfr06WhsbERKSkq7\n64iMjFS4J0xPTw++vr64ffs2CgsL29xfVVVV8N6x4cOH4+WXX+ZNY+xMJSUlSEtLg4ODA+86iYiI\ngL6+Pnbs2IEHDx60Ws7evXtRVlaGoKAgDB8+nLe9PYuiCI32ykabL126pDAVkuM4qKioCD4Koelo\nOQAoKytDWZk/MaJ5vs7w9ddfo2fPnvjqq68URgUlEgk+//xz3L9/Hz///DOAR32fkZEBR0dHhVFv\nAFi0aBE95oEQQgghreo20z5TuJSnWp87c++ysocOHcpLk0gkcHBwQEpKCkpLS2Fubo6srCwAQEZG\nBs6cOcPbR1lZGRcuXOClOzo68tJkwZenp2eb0wezsrLAcRz27duH/fv387aLxWLBegcNGsRL69Wr\nFwDg1q1brdbZWTiOEzx+AKivr8eaNWuwY8cOFBQU8O6ZlC300R5Cx9q7d28A7T/W3NxcLF++HMeO\nHUNlZaVCsKWmptbutnTU6dOnAUAwYBOLxXBycsIvv/yCwsJC2NnZtVhOdnY2AGD06NGP3Zby8nJE\nR0fjwIEDuHLlCu7du6ewvaysDObm5gCAiRMn4tNPP4W9vT0mTZoEd3d3DBkyBBKJRGGfSZMmYc+e\nPbC3t8fkyZPh6ekJFxcX+ZTXzvT333/jzJkzMDc3F5zuK5tyXVBQAODRlE8AGDZsGC+vmZkZzM3N\nUVJS0untJIQQQsg/Q7cJ/royGHvaDA0NBdNlI0k1NTUAIF8oZc2aNS2WJRTICa1SKCuzPaMxVVVV\nYIxh0aJFLdb5999/89KFRttkoy/NF4npSi317/jx43HgwAG8/PLLePvtt2FgYABlZWUUFRUhLi4O\n9fX17a7jSY81IyMDI0aMgLKyMsaMGQNra2v06NEDHMdh8+bNXbr4R21tLQDh6wSAfERSlq8lHbmm\nhFRVVcHJyQlXr16Fq6srfHx8oK2tDZFIhOTkZKSmpiqck48//hi6urr45ptvsHjxYixevBhqamp4\n6623sHLlSvl5DwgIgIqKCr788kt89dVXWLlyJZSVleHl5YWvvvoKVlZWj9VeIdXV1QCA0tJSLFy4\nUDAPx3HyLxpkfdbS/ZRGRkYU/BFCCCGkRd0m+PsnuX79umB6RUUFgP8tyiELMC5cuAAbG5t2ly8U\nEPbs2RMAcO3atTb319LSgkgkQl1dHcRicbvrfZ5lZ2fjwIEDeOONN5CUlKSwbceOHU/twfEy0dHR\nePjwIVJTUzFkyBCFbT/++CMvv2w64MOHD3nbZAFFe8muK9n11pwsXSjAbUp2TV29erVD9ct8//33\nuHLlCpYuXYpPP/1UYVtZWRlSU1N5+7z77rt49913cePGDfmCQtu2bcNff/2lMG1XKpVCKpXi9u3b\nSE9Px86dOxEfH48LFy7g7NmzvEWSHpesj4YMGYLjx4+3mV/2ty0bEWyupXNCCCGEEALQox5eSBkZ\nGby0O3fu4NSpU9DR0ZFPcxs8eDCAR6uDPilHR0dwHIcjR46gsbGx1byDBw9GY2OjfNppZ1NSUgLQ\n8dHAx90PAC5dugQA8PHx4W07duxYh8t7UpcuXZI/ZqOpiooKeVubkq0CeeXKFd62vLw8XlprfTVg\nwAAAkK/A2tS9e/dw8uRJqKuro1+/fq0eg5OTEwDg0KFDreZriew4fX19FdIZY21e8/r6+njzzTex\nd+9evPbaa0hLS8Pt27d5+TQ1NeHt7Y3Y2Fj4+vri4sWLglOWH5empiZsbW1x9uxZ1NXVtZn/tdde\nAyDc96WlpfS4B0IIIYS0ioK/F1BBQQE2b96skBYTE4Nbt24pLMARHBwMDQ0NRERECC4iUlNTg1On\nTrWrTiMjI0ilUhQUFCA6Opq3venozfvvvw8lJSWEhYUJ3gdXUVHxRB+gZYFMRz/oyhbreJwPyLKF\nRZoH3idOnMC3337b4fKelIWFBW7evKnQj/fv30doaKjg6J4s0IqNjVVI37VrF9LS0nijva31lZmZ\nGdzc3JCXl8cbZVy2bBkqKysxadIkwQVTmpI9TiE2NlZwlK6tEcGWzsmqVauQn5/POyahOu7evYua\nmhqoqKjIA9709HTeFxyNjY24ceMGOI7r9NHssLAw3L59GzNmzBCcOnz27Fn5SJ+5uTlcXV2Rm5vL\newZgZGRkm1/MEEIIIaR7o2mfL6DRo0cjJCQESUlJsLGxQU5ODg4fPoy+ffsiKipKns/AwADbtm3D\nxIkT0b9/f3h7e8Pa2hp37txBUVERUlNTERQUhPXr17er3vXr1yM/Px+RkZFITEyEm5sb7t+/j7Nn\nzyIvL0/+cG97e3usXbsWoaGhsLGxgY+PDywsLFBdXY2LFy8iIyMDixcvhq2t7WMdv4aGBpycnJCW\nlobAwEBYW1tDJBIhMDBQPuopxMXFBerq6li1ahWqq6uhr68PAPj888/leVpaSXTw4MFwdHTE9u3b\nUV5eDkdHR1y+fBn79u2Dr6+v4HMLu1JoaCh+++03DB06FAEBAVBWVsbhw4fR0NCA1157Tb4oi4yf\nnx+srKwQGxuLv/76Cw4ODjh//jySk5Ph7e2NX375RSH/yy+/DFNTU2zfvh1qamro1asXOI7DrFmz\noKWlhQ0bNmDYsGGYOnUqfv75Z7z00kvIzc3Fb7/9hr59+2LZsmVtHoOamhp+/PFHeHt7Y8SIEfDx\n8YGdnR2qqqqQlZUFS0vLFh9yDgBTp07FsmXLEBoaipSUFJiamiInJwdZWVnw8fHhTc/18/ODjo4O\nBg8eDHNzc9y7dw8HDhxAcXExwsLC5Au/hIWFoaKiAkOHDoWFhQUYY0hOTsbp06cxbtw4vPTSS+09\nTe0SEhKC48ePY9u2bUhPT5c/s7CsrAx//PEHTp06pfDcxLVr12LYsGEICAjAhAkTYGFhgdTUVFy9\nehWvvvqqfFEYQgghhBCeLnuIxGNoT3OesyY/VU2fH5aSksJcXV1Zjx49mJ6eHgsMDBR87htjjJ07\nd44FBQUxMzMzpqqqygwMDNigQYNYREQEKygoECy/JdXV1SwiIoLZ2NgwNTU1pq+vz5ydndmqVat4\neTMzM9mECROYiYkJU1VVZSYmJszZ2ZktWrSI/fXXX/J8sbGxTCQSCT5/r6U2FRYWMh8fH6ajo8NE\nIhETiUSCz4pr7pdffmFOTk5MIpHwnonm7u7e6jPSKioqWFBQEDM1NWUSiYQ5OjqyH3/8kaWkpAi2\n0dLSkvcMuKCgICYSiQSftxcVFdXu42CMsZ07d7IBAwYwiUTCTExMWHBwMKuoqGjxOIqLi5lUKmVa\nWlpMQ0ODjRo1iuXm5rZYb1ZWFnN3d2daWlryvmra7suXL7PAwEBmbGzMVFVVmYWFBQsLCxN8Pl5r\nCgoKWGBgIDM1NWWqqqrM1NSUeXt7s19++UWep6XrIC8vj40aNYrp6OgwbW1t5uXlxXJycgSPacOG\nDczX15dZWloysVjMDA0NmaurK9u6datCmTt27GABAQHMysqKSSQSpqenx15//XW2bt069uDBA4W8\nQue4tb+j1s7/tm3bmIeHB9PR0WFqamrMwsKCeXl5sW+++YbduXOHd9yjR49mPXr0YLq6umzChAns\nr7/+avMaJl2vO79HEUII6Rxd+V7C/beC5wLHcW0+w609ef6pUlJS4OnpiaioKMybN+9ZN4cQQkgz\n3fk9ihBCSOfoyvcSuuePEEIIIYQQQroBCv4IIYQQQgghpBug4I8QQgghhBBCugG6548QQgjpJPQe\nRQgh5EnRPX+EEEIIIYQQQp4IBX+EEEIIIYQQ0g1Q8EcIIYQQQggh3QAFf4QQQgghhBDSDVDwRwgh\nhBBCCCHdAAV/hBBCCCGEENINUPBHCCGEEEIIId0ABX+EEEIIIYQQ0g1Q8EcIeWpEIhE8PDyedTMU\nBAUFQSQSobS0VCH91q1bCAkJgYWFBZSUlCASiVBTU4PY2FiIRCLExcV1SXuioqIgEomQlpbWJeUT\nQgghpPui4I+8cIqLiyESiRAcHPysm/Lcex6DLY7jnnUTFHAcJ9imOXPmYOPGjRg0aBAiIyMRFRUF\nsVjc6j6EEEIIIc+zdgV/f/31F9566y307NkT2traePPNN/HXX3+1uZ/sG2yhH3V19SduPOmeZB+6\n6cN3+1A/tS46Ohrnz5+HqampQvqBAwdga2uLn3/+GVFRUZg3bx7U1NQwfvx4nD9/Hv7+/s+oxYQQ\nQgghj0e5rQx///03PD09oa6ujvj4eADA559/Dg8PD+Tn50MikbS47/Tp0+Ht7a2QVldXBy8vL/j5\n+T1h00l3xRhT+JeQJ2FsbAxjY2NeellZGfr168dL19LSgpaW1tNoGiGEEEJIp2pz5G/Tpk0oKirC\nnj174OvrC19fXyQmJqKkpAQbN25sdd9evXrByclJ4efq1at4+PAhpk2b1mkH0V2kpKRAJBJhwYIF\nSElJgaurKzQ1NaGvr4/AwECUl5cL7peXl4cJEybAyMgIYrEY1tbWmDt3Lu7cudNi+RkZGRg5ciS0\ntbWhq6srz1NTU4PIyEjY2dlBIpFAT08PQ4YMwcqVK3n1Jicnw9vbG3p6elBXV4ednR2WLVuGhoYG\nhXxN76E6dOgQXFxcoKGhAX19fQQFBaGqqkohb9++fQEAcXFxCqPJ7blHqrGxEZs2bYKLiwu0tLSg\noaGBV155BR988AFu3bolz3f06FEEBwfDxsYGGhoa0NLSwtChQ7Fz505emU2noZ49exZ+fn7Q1dWF\nSCRCbW1tq+1JSEjAxIkT0bdvX0gkEujq6mLUqFE4cuQIL29r95o1PXdNf2/6WvbTdP+6ujp89tln\neOmllyAWi2FoaIi33noL+fn5bfZlUx25LprLzc3FzJkzYWdnB21tbWhoaGDQoEHYsGGDYP6cnByM\nHz8eZmZmEIvFMDIygouLC77++muFfIWFhQgMDISlpSXEYjH09fUxaNAgREVFKeRrfs+f7HdAse9k\n04xbOw/tveYBoLKyEu+88w4MDAygoaEBV1dXus+PEEIIIV2qzZG/xMREODs7yz9wA4ClpSWGDh2K\nvXv3Yvbs2R2qMC4uDsbGxhgzZkzHW0sAAJmZmYiOjsa4ceMQHh6O7OxsbN26FceOHUN2drZCsJaQ\nkIBJkyZBLBbD398fxsbGyM3NRUxMDJKTk5GWlgYVFRWF8o8dO4alS5di5MiRCAkJQWVlJQCgoqIC\nrq6uuHjxIpycnBAWFob6+nr88ccfiImJwYcffigvY926dZg1axYMDQ0hlUqho6OD9PR0RERE4OTJ\nk9i9ezfvuBITE5GUlARfX18MGzYMqampiI+Px6VLl5Ceng4AGDBgAMLDw7F69Wo4ODgoTL2zsLBo\ntd8aGxvx5ptvYu/evbC0tERQUBDU1dXx559/YtOmTQgKCkLPnj0BAF988QWKiorg7OyMXr164ebN\nm0hMTMSkSZNQVlaG8PBwXvkXL16Ei4sLBgwYgHfffRcVFRXyIKIln332GcRiMTw8PGBsbIxr165h\nz549GDNmDH766SdIpVLePq1N45Rt69OnD+bPn48FCxbIj1VmwIABAIC7d+/C3d0dv//+O4YMGYKA\ngACUlpZi586dOHDgAH799Ve4urq22n6gY9eFkE2bNiEpKQlubm4YN24cbt++jYMHD2LmzJkoLCzE\nV199Jc+bl5eHoUOHQlNTE35+fjAxMcGNGzdw+vRpxMfHY+bMmQCAq1evwsnJCQ0NDfDz84OlpSWq\nq6tx/vx5bNy4kRcANu1TqVSKPn368PrOwcGhxX2Ajl3zdXV1cHNzw4ULF+Du7g4XFxcUFBRg9OjR\ncHd3b7PPCSGEEEIeC2uDkZERmzFjBi89JCSEGRgYtLW7gtLSUqakpMTmzJkjuL0dzWlXnqaSk/FM\nfzpTcnIy4ziOcRzHNm/erLAtMjKScRzHwsLC5GmVlZVMU1OTWVlZsbKyMoX8X3zxBeM4jq1YsUKw\n/C1btvDql0qljOM4tmTJEt62a9euyV+fOXOGKSsrM2dnZ1ZbW6uQLzQ0lHEcx3bt2iVP27x5M+M4\njqmqqrLjx4/L0xsaGpiHhwfjOI6dOHFCnl5cXMw4jmPBwcEtdZWg1atXM47jmI+PD7t//77Cttra\nWlZXV6dQR3N37txhr732GtPW1mZ///23PL2oqEjeb4sWLepQm4TqqaioYL1792bW1tYK6bJ+iouL\n4+0jO3cLFixQSOc4jnl4eAjWPX/+fMZxHHv33XcV0o8cOcI4jmPW1tassbGxzWNo73XRUntKS0t5\n+z18+JB5eXkxJSUlVlJSIk+fPXs24ziO5efn8/apqqqSv5ad68TExFbzMcbYtGnTGMdxCvW01FbG\nhM9DR6952d9reHi4Qt4ffviBcRzHRCIRS01N5dVNnn8dfY8ihBBCmuvK95I2p31WV1dDR0eHl66r\nq4vq6uoOBZpbt25FY2MjTfl8Qra2tgojOQDw6aefomfPnti6das8LT4+HnV1dYiJieHd0/TBBx/A\nwMAA27dv55Xv6OiIt99+WyGtvLwce/bsga2tLSIiInj7mJiYyF9v3LgRDQ0NWLNmDTQ1NRXyLVmy\nBBzHCdY7ZcoUODs7y38XiUTyayUnJ0eezh7zXr8NGzZARUUFX3/9NW+0U1NTEz169JD/LjSKKJFI\nEBgYiNraWpw8eZK33dTUVLBvWiNUj2zk6NKlS7zHD3SmuLg4qKmpYcmSJQrpnp6e8PHxwaVLl5CR\nkdFqGR25LlpiZmbGS1NSUsL06dPR2NiI5ORk3nbZqptNCf0/1d58T6qj1/zWrVuhrq6OefPmKeQN\nDg5Gv3796H5WQgghhHSJNqd9dqb4+HgMHDgQ9vb2T7Paf5yhQ4fy0iQSCRwcHJCSkoLS0lKYm5sj\nKysLAJCRkYEzZ87w9lFWVsaFCxd46Y6Ojrw0WfDl6enZ5uqRWVlZ4DgO+/btw/79+3nbxWKxYL2D\nBg3ipfXq1QsAFO7Hexx1dXUoKCjAK6+80ub0UACora3F8uXLsXfvXly+fBl3795V2C50f+Wrr74K\nJSWlDrWrvLwc0dHROHDgAK5cuYJ79+4pbC8rK4O5uXmHymyP2tpalJSU4NVXX4WhoSFvu5ubG5KS\nkpCfn9/q1M+OXBctqa+vx5o1a7Bjxw4UFBTw7kVt2tcBAQFYs2YNhgwZgsmTJ2PEiBEYNmwYDAwM\nFPbx9fXF3LlzIZVKERAQgFGjRsHV1RW9e/d+rDa2pSPXfG1tLYqLi+Hg4KAwRVvG2dkZBQUFXdJO\nQgghhHRvbQZ/Ojo6giN8VVVVgh9cWnLy5EkUFBRg9erVHWsh4RH6sA4ARkZGAB4tvgFAvlDKmjVr\nWixL6AO7rJymZGU2Xw5fSFVVFRhjWLRoUYt1/v3337x0oRUUlZUfXaJCC2Z0REfaf//+fbi5ueH0\n6dNwdHTEv/71L+jq6kJJSQl5eXnYu3cv6uvrefsJ9Vtrqqqq5Isgubq6wsfHB9ra2hCJREhOTkZq\naqpgPZ1BthBNS22WjRS3tWBNR/q1JePHj8eBAwfw8ssv4+2334aBgQGUlZVRVFSEuLg4hT4YMmQI\njh49iqVLl+K7777D+vXrwXEchg8fjhUrVsi/QLC0tERmZiaioqKwc+dOxMbGAgAGDhyI6OhojBo1\n6rHbK6Qj17ysT5sHrDIdvY4IIYQQQtqrzeDPzs5OcNTo3LlzeOWVV9pdUVxcHFRVVTFlypRW8zVd\niMHd3Z0WPxBw/fp1wfSKigoAgLa2NoD/BVMXLlyAjY1Nu8sXCghlC6Fcu3atzf21tLQgEolQV1cn\nOO3uWZD1SXvav3fvXpw+fRr//ve/8c033yhsW7ZsGfbu3Su4X0dHvr7//ntcuXIFS5cuxaeffqqw\nraysDKmpqQppssVjHj58yCtLFoS1l+zakF0zzcnS23qkQUeuCyHZ2dk4cOAA3njjDSQlJSls27Fj\nh+CKmsOHD8fw4cNx9+5dZGZmYs+ePdi4cSO8vLxw4cIF6OnpAQD69++P3bt348GDB8jOzkZSUhLW\nrl0LX19fnDp1SvAxDo+rI9e8rE9lCyk119I5IYQQQsg/U0pKClJSUp5KXW0Gf76+vpgzZw6KiorQ\np08fAI+Wtj9+/DiWLVvWrkru37+P7du344033pB/MGtJ81X4npS7+z/v3hmh+7Du3LmDU6dOQUdH\nRz5NcPDgwUhISEBmZmaHgj8hjo6O4DgOR44cQWNjY6urWA4ePBh5eXnIysqCm5vbE9UrRDa1siOj\ngRoaGnj55ZdRWFiIkpKSVqd+Xrp0CcCja7+5Y8eOdbC1LWupHsYYMjMzefll96pduXKFty0vL0+w\nDo7jBPtJS0sLlpaWKCgowPXr13mjybLAs/kKl8115LoQIusDHx8f3ra2+lpdXR2enp7w9PSEkpIS\nVq9ejePHj2PcuHEK+VRUVODi4gIXFxcYGhpi9uzZOHjwYKcGfx255mV9f+HCBdy8eVPh/0TGGI4f\nP95p7SKEEELI86/5gJfs0V1doc1PatOnT4elpSX8/PyQmJiIxMRE+Pn5wdzcHO+99548X0lJCZSV\nlQWnPe3fvx/V1dW00EsnKSgowObNmxXSYmJicOvWLYWFWoKDg6GhoYGIiAgUFhbyyqmpqcGpU6fa\nVaeRkRGkUikKCgoQHR3N23716lX56/fffx9KSkoICwtDWVkZL29FRYXgPX/tJQuCOroYSkhICB4+\nfIiZM2fiwYMHCttqa2vl95rJAsPmQfbPP/8seD/X42qpnlWrViE/P583kigLtLZv364wFfLPP/9s\ncTq1rq6uYLAIANOmTUN9fT0iIyMV0lNSUrB//35YW1sL3l/aVEeuCyEt9cGJEyfw7bff8vJnZmbi\n/v37vHTZfYGyUbe8vDzBKauyfOrq6q22q6M6es1PnToV9+7dw8KFCxXybd68GYWFhY99/yQhhBBC\nSGvaHPmTSCQ4evQoZs+ejalTp4IxhpEjR2LVqlWQSCTyfIwxNDY2Cq5SFx8fDz09PYwdO7ZzW99N\njR49GiEhIUhKSoKNjQ1ycnJw+PBh9O3bV2Hk1MDAANu2bcPEiRPRv39/eHt7w9raGnfu3EFRURFS\nU1MRFBSE9evXt6ve9evXIz8/H5GRkUhMTISbmxvu37+Ps2fPIi8vDzdu3AAA2NvbY+3atQgNDYWN\njQ18fHxgYWGB6upqXLx4ERkZGVi8eDFsbW0f6/g1NDTg5OSEtLQ0BAYGwtraGiKRCIGBga0ujjJz\n5kwcOXIEe/fuhY2NDcaOHQuJRILLly/j119/xbFjx/Dqq69i3LhxMDc3x7Jly3D27Fn069cPZ8+e\nxcGDByGVSpGQkPBY7W5u6tSpWLZsGUJDQ5GSkgJTU1Pk5OQgKysLPj4+vGmQJiYmmDx5Mv7v//4P\ngwYNwpgxY3D9+nXs2bMHXl5egs9OHDFiBHbu3AmpVAoHBwcoKSnBz88P/fv3xyeffIL9+/dj06ZN\nOHPmDIYPH44rV65g586dkEgk+OGHH9p1HO29LoQMHjwYjo6O2L59O8rLy+Ho6IjLly9j37598PX1\n5R3TsmXLkJqaiuHDh8PS0hKqqqrIyspCRkYGBg0aBE9PTwCPppl/9913cHV1Rd++faGpqYn8/Hwc\nPHgQFhYWCAgIaNextVdHr/mPP/4Yu3btwtq1a5Gfnw9nZ2cUFhZi//79GD16NA4dOtSp7SOEEEII\nAfB8PZCoPc15zpr8VDV9lltKSgpzdXVlPXr0YHp6eiwwMJD3LD+Zc+fOsaCgIGZmZsZUVVWZgYEB\nGzRoEIuIiGAFBQWC5bekurqaRUREMBsbG6ampsb09fWZs7MzW7VqFS9vZmYmmzBhAjMxMWGqqqrM\nxMSEOTs7s0WLFrG//vpLni82NpaJRKIOPb+usLCQ+fj4MB0dHSYSidr9XLSGhga2YcMG9vrrr7Me\nPXowDQ0NZmdnx+bMmcNu3bolz3fp0iUmlUqZgYEB09TUZMOHD2eHDh0SbKvsOX8dfe4gY4zl5eWx\nUaNGMR0dHaatrc28vLxYTk4Oi4qKEjymu3fvsvDwcGZsbMzEYjFzcHBgP/74I0tJSRHsp/LycjZx\n4kRmYGDAlJSUeG2/ffs2mzt3LrO2tmaqqqpMX1+fvfnmm4LP0WtNe68LoWfnVVRUsKCgIGZqasok\nEglzdHRs8ZgOHjzIpk2bxvr168c0NTWZtrY2e+2119jSpUvZ7du35fmysrLYe++9x+xlcWzZAAAg\nAElEQVTt7VnPnj1Zjx492CuvvMI++eQTVllZqVB/UFAQE4lE7X7OX2vXa3uvecYePYfzX//6F9PX\n12c9evRgw4YNY6mpqS2ee/Ji6M7vUYQQQjpHV76XcP+t4LnAcVybz7dqT55/qpSUFHh6eiIqKor3\nfDBCCCHPXnd+jyKEENI5uvK9pGOrMxBCCCGEEEIIeSFR8EcIIYQQQggh3QAFf4QQQgghhBDSDdA9\nf4QQQkgnofcoQgghT4ru+SOEEEIIIYQQ8kQo+COEEEIIIYSQboCCP0IIIYQQQgjpBij4I4QQQggh\nhJBugII/QgghhBBCCOkGKPgjhBBCCCGEkG6Agj9CCCGEEEII6QYo+COEEEIIIYSQboCCP0IIIYQQ\nQgjpBij4I6QFUVFREIlESE1NfdZNeeEUFxdDJBIhODj4WTdFgbu7O0Qi/n97V69exZQpU9CrVy+I\nRCLo6OgA6PprICgoCCKRCKWlpV1SPiGEEEJIUxT8kRfO0wosOI6T/zzvntdg63nru5bO57Rp07Bj\nxw6MHDkS8+fPR0REhEL+rjyO562PCCGEEPLPpfysG0BIR8k+LHf1h+bQ0FBMnjwZZmZmXVpPZ3ha\nffKii4+Px927dxXS6uvrkZycjDFjxiAuLk5h29O4BhhjXVY2IYQQQkhTFPyRF47sw3JXf2jW09OD\nnp5el9bRWZ5Wn7zohIK4iooKMMZgZGTE2/YiXQOEEEIIIW2haZ8vkJSUFIhEIixYsAApKSlwdXWF\npqYm9PX1ERgYiPLycsH98vLyMGHCBBgZGUEsFsPa2hpz587FnTt3Wiw/IyMDI0eOhLa2NnR1deV5\nampqEBkZCTs7O0gkEujp6WHIkCFYuXIlr97k5GR4e3tDT08P6urqsLOzw7Jly9DQ0KCQLzY2FiKR\nCHFxcTh06BBcXFygoaEBfX19BAUFoaqqSiFv3759AQBxcXEQiUTyn7S0tFb7r7a2FjExMXB1dYWx\nsTHU1NRgYWGBGTNmoKKigpdfdr9X03Lb00ct+eGHH+Dr6wsLCwuIxWIYGBjA398fubm57aq7eX/F\nx8d3qE+uX7+O0NBQWFhYQE1NDaampggKCkJxcXGbbW+qrKwM4eHhsLa2hrq6OgwNDeHu7s4bNRNy\n9OhRBAcHw8bGBhoaGtDS0sLQoUOxc+dOwfyHDx/G6NGjYWJiArFYDBMTE3h6emLHjh0K+XJycjB+\n/HiYmZlBLBbDyMgILi4u+PrrrxXyNb/nz93dHZaWlgAU+27hwoUAWj8Pu3fvhru7O7S1tSGRSDBw\n4EBs2rRJ8DiKiorw1ltvoWfPntDW1oaXlxfy8/Pb7C9CCCGEkM5EI38voMzMTERHR2PcuHEIDw9H\ndnY2tm7dimPHjiE7O1shEElISMCkSZMgFovh7+8PY2Nj5ObmIiYmBsnJyUhLS4OKiopC+ceOHcPS\npUsxcuRIhISEoLKyEsCjERJXV1dcvHgRTk5OCAsLQ319Pf744w/ExMTgww8/lJexbt06zJo1C4aG\nhpBKpdDR0UF6ejoiIiJw8uRJ7N69m3dciYmJSEpKgq+vL4YNG4bU1FTEx8fj0qVLSE9PBwAMGDAA\n4eHhWL16NRwcHODv7y/f38LCotV+O3fuHBYsWIARI0YgICAA6urqOHXqFL799lscOnQIv//+O3r2\n7Nmuc9BSH7UmNDQUAwcOhJeXF/T09FBUVIS9e/fi4MGDSElJweDBg9tVd3Pt6ZPr169j8ODBKCkp\nwejRo/H222/jwoUL2LJlC5KSkpCRkYF+/fq1Wdf58+fh4eGB69evw9PTEwEBAaitrUVubi7WrFmD\nadOmtbr/F198gaKiIjg7O6NXr164efMmEhMTMWnSJHlQKbN//374+vrC1NQU/v7+0NPTQ1lZGXJy\ncrB7925MnDgRwKMvN4YOHQpNTU34+fnBxMQEN27cwOnTpxEfH4+ZM2cqtKHp1Njg4GAMGDCA13fu\n7u6tHsdHH32ElStXwtLSEpMnT4ZEIsGhQ4fw3nvv4fz58/jyyy/lea9evYqhQ4eivLwcvr6+sLOz\nw++//47hw4fjtddea7PPCSGEEEI6DXuOtKc5HW0ygGf605mSk5MZx3GM4zi2efNmhW2RkZGM4zgW\nFhYmT6usrGSamprMysqKlZWVKeT/4osvGMdxbMWKFYLlb9myhVe/VCplHMexJUuW8LZdu3ZN/vrM\nmTNMWVmZOTs7s9raWoV8oaGhjOM4tmvXLnna5s2bGcdxTFVVlR0/flye3tDQwDw8PBjHcezEiRPy\n9OLiYsZxHAsODm6pqwTV1NSw6upqXvrWrVsZx3Fs8eLFCunz589nHMex1NRUeVpbfdSa4uJiXtr5\n8+eZpqYmGzlyZJt1y8j6Ky4uTqHs1vpk2rRpjOM4tmjRIoX0H374gXEcxzw8PNp1DAMHDmQcx7Gt\nW7fytjW9BoqKigTbI9QHd+7cYa+99hrT1tZmf//9tzxdKpUysVjMKisrefvcvHlT/nr27NmM4ziW\nn5/Py1dVVaXwu5ubGxOJRLw2tdR3Qufh119/ZRzHMalUyurr6+XpDx48YP7+/ozjOJadnS1Pnzp1\nKuO4/8/efYdFdex9AP+eBWnC0sSGCgoqUSzYUFFZsMQSURDbjQVzfcnVoIYbTaKJEUtii0pM9Rq7\n5sYWxXJjrIDYe0EQJaJEURQVFJQ67x/e3cu6y+6CIuh+P8/DI8yZMzNn9qxnf3vmzEhi0aJFamV/\n8cUXQpIkIZPJxPXr1zXqptdTJbusEhHRa6g8ryUc9vka8vDwQEhIiFrap59+Cjs7O6xdu1aVtnr1\najx+/Bhz5sxBzZo11fL/85//hJOTE3799VeN8tu0aYNhw4appd2+fRtbt26Fh4eHaibE4mrVqqX6\nfcmSJSgsLMTixYthY2Ojlu/LL7+EJEla6/3b3/6GDh06qP6WyWSqO0knT55UpYsyPtcml8u13tn7\n29/+BhsbG+zbt8/gsrT1kT7a7kx6eHhAoVDg4MGDKCgoKFV5xenqk9zcXKxfvx41atTAxx9/rLZt\n1KhRaNq0KaKjo5GamqqzjmPHjuHMmTPo1q0b3n33XY3txc+BkmjrAysrK4wYMQJZWVk4fvy42jZT\nU1OYmmoOUNA2zNbCwkIjTblkgy6lPZ++//57yGQyLFmyBGZmZmptnTlzJgCohqXm5uZi48aNqF27\nNsaNG6dWzieffGLwnWYiIiKil4HDPl9DPj4+GmlWVlZo2bIloqOjcePGDdSrVw/Hjh0DAMTFxeHi\nxYsa+5iamiIxMVEjvU2bNhppyuDL399f74ySx44dgyRJ2L59O3bs2KGx3cLCQmu9rVu31khzdnYG\nADx8+FBnnYbat28fIiMjcfz4cdy/f1/t+cO0tDSDy9HWR/pcvXoVX331FQ4cOIC0tDTk5eWptkmS\nhIyMDK2Tjryoy5cvIzc3F97e3mrBipKvry/i4+Nx/vx5nbNanjhxAgDQo0ePMrclKysL8+bNQ1RU\nFP7880+NmTeLP7c6ZMgQbN26FZ6enhg6dCj8/f3RsWNH2Nraqu0zaNAgLF68GO3bt8fQoUPRtWtX\ndOrUCU5OTmVupy7Hjh2DtbW1xvOEAJCfnw8AqvM7KSkJubm5aNeuHUxMTNTyFn/PEhEREb0KDP5e\nQ9WrV9eargwcMjMzAUA1UcrixYtLLEtbIKctAFGWWbt2bb3tu3//PoQQqrsg2urMycnRSJfL5Rpp\nyrs+z08SUxbr16/H0KFDVRNuuLq6wtLSEkIIREZGIjc31+CyShukXblyBe3atcPjx4/RvXt3DBgw\nANbW1pDJZNiyZQvOnTtXqvpLIysrC0DJbVbeFVbmK0lpzgFt8vLy4Ovri3PnzqFNmzZ477334ODg\nABMTE5w5cwZRUVFqfTBo0CBUqVIFCxcuxKJFi7BgwQKYmpqiZ8+eWLRoEdzc3AAA7du3x/79+/HV\nV1/h559/xg8//ABJktClSxd8/fXXWr9UeBHKLw2Uk8I8r/j5reyzkgLR8gj2iYiIiErC4O81lJ6e\nrjVdOWOl8s6IMphKTExEo0aNDC5fW0CoHJ5269YtvfvL5XLIZDI8fvxY61C8ijJjxgxYWVnh1KlT\nqtkxlebOnVuqskq7nl5kZCQyMzPxyy+/YMiQIWrbjhw5gnPnzqmlKWek1DYUVBlQGEp5Hmib0bR4\nurbguzjlOXDz5s1S1a8UFRWFc+fOITQ0FD/99JPatrlz5yIqKkpjn8DAQAQGBuLRo0c4ePAgNmzY\ngNWrVyMxMRHx8fGqyYq6dOmCLl264MmTJzhy5Ai2bt2KJUuWoGfPnkhMTHypyzXI5XKYm5sb9F5Q\nvhdLmhCopNeEiIiIqDy88c/8CSEq9Kc8xMXFaaRlZ2fj7NmzsLe3R7169QBANXvkkSNHXrjONm3a\nQJIk7Nu3D0VFRTrzent7o6ioSDXs9GVTDp8r7d3A5ORkNGnSRCPwO336NJ4+ffrS2ldS3ZIkISAg\nQC396dOnOH36tEYwqXxW7a+//tIo68yZMxppuvrEw8MD5ubmOH78uNpQU6XY2FhIkqR35sl27doB\nAHbv3q0zX0mSk5MBQKMPgGezp+piY2OD3r17Y+XKlQgICMDVq1e1Dh22tLSEv78/Fi9ejLFjxyIj\nI0Nv2aXl7e2N27dv4/r163rzNmrUSNX3zwfyyvdsab9IICIiIiqrNz74exNdvnwZK1asUEubM2cO\nHj58qDYJyahRo2BtbY3JkycjKSlJo5zMzEycPXvWoDpr1KiBwMBAXL58GbNnz9bYXvxu0NixY2Fi\nYoJx48ZpfY7uzp07Wj+4G0oZGN24caNU+7m4uCApKUntLkxWVpba8gLlxcXFBUIItcBdCIHJkydr\nvSukDLRWr16t9iXCkSNHsG7dOo38uvrEzMwMQ4YMwe3btzXWY1y1ahUuXLgAhUKBOnXq6DyGtm3b\nolWrVti3b5/WNui7I6ic7OX5Ly9+++03rc+GHjx4UOOLhqKiIty7dw+SJKnuKh85ckRrUKt8ftDS\n0lJnu0pLOXHL3//+d613YVNSUlSBobm5OQYNGoRbt27h22+/Vcs3d+7cl/YsKxEREZEhOOzzNdSj\nRw+MGTMGO3fuRKNGjXDy5Ens3bsXDRo0QEREhCqfk5MT1q1bh8GDB6NZs2bo3bs33N3dkZ2djWvX\nriEmJgYhISH44YcfDKr3hx9+wPnz5zF16lRs27YNvr6+yMvLQ3x8PM6cOYN79+4BADw9PfHtt98i\nLCwMjRo1Qp8+feDi4oIHDx7g6tWriIuLw6xZs+Dh4VGm47e2tka7du0QGxuLESNGwN3dHTKZDCNG\njFDd9dQmLCwMEyZMQKtWrRAUFITc3Fzs2rULzs7OqF27drndqQWA999/HytWrEBQUBAGDx4MuVyO\ngwcPIiUlBQqFQmPSD29vb/j4+GD//v3o0KEDOnfujOvXr2Pbtm0ICAjAli1b1PLr65N58+YhJiYG\nn332GWJjY+Hl5YXLly9j69atqFatGn788UeDjmPt2rVQKBQYPnw4VqxYgbZt2+LRo0c4e/YscnJy\ncPr06RL37du3L+rVq4e5c+ciPj4ejRs3Rnx8PP744w8EBgZqHNO4ceNw584d+Pj4qILnAwcO4Ny5\nc+jbty8aNmwI4FkQFRMTgy5dusDV1RVmZmY4duwY4uLi0Lp1a/j7+6uV+6Kvc69evTB58mTMnj0b\nDRs2xNtvvw1nZ2fcvXsXCQkJOHbsGP7973+rgt3Zs2djz549+OijjxAdHa1a5+/o0aPo3Lmzag1L\nIiIionJXTktIlIkhzalkTX6llGvMTZ8+XURHR4vOnTuLqlWrCkdHRzFixAiNtfyULl26JEJCQkTd\nunWFmZmZcHJyEq1btxaTJ08Wly9f1lp+SR48eCAmT54sGjVqJMzNzUW1atVEhw4dRGRkpEbeI0eO\niIEDB4patWoJMzMzUatWLdGhQwcxc+ZMkZqaqsq3cuVKIZPJ1Nat09empKQk0adPH2Fvby9kMpmQ\nyWRa18R73vfffy+aNGkiLC0tRb169UR4eLh49OiRcHV1FfXr11fLGxERoVGuIX1Ukn379omOHTsK\nGxsbUa1aNREcHCyuXr0qQkJCtK71lpGRIUaOHCkcHR2FlZWV6Nixo9izZ0+J/aWvT9LT00VYWJio\nV6+e6vUYOXKk1rX3dLl586b44IMPhKurqzAzMxM1atQQfn5+auselrTOX3JysggMDBROTk7CxsZG\ndOnSRezevVvrMa1fv14MGjRIuLm5CSsrK+Ho6Cjatm0rvvvuO5Gfn6/K98cff4iRI0eKxo0bCxsb\nG2FraytatGghvvrqK/Ho0SO1+hUKhcY6fyW1VQjt54DS77//Lvr06SOqVasmzMzMRJ06dYRCoRAL\nFy4U9+7dU8v7559/igEDBghbW1shl8tFz549xYULF0p87en1ZczXKCIiejnK81oi/beCSkGSJL3f\nyhuS500VHR0Nf39/RERE4Isvvqjo5hAR0XOM+RpFREQvR3leS/jMHxERERERkRFg8EdERERERGQE\nGPwREREREREZAT7zR0RE9JLwGkVERC+Kz/wRERERERHRC2HwR0REREREZAQY/BERERERERkBBn9E\nRERERERGgMEfERERERGREWDwR0REREREZAQY/BERERERERkBBn9ERERERERGgMEfERERERGREWDw\nR/SS7dy5E97e3pDL5ZDJZAgPD9eZ39XVFfXr1ze4/IiICMhkMsTExJS5jSkpKZDJZBg1alSZy6iM\nHj58iDFjxsDFxQUmJiaQyWTIzMzEypUrIZPJsGrVKoPKiY6Ohkwmw/Tp08u5xfSyKRQKyGS8tBER\nEWljWtENIHqTJCcnIygoCE5OTvjHP/4Ba2trtG/fXu9+kiQZXIckSaqfF/UyyqhMJk6ciOXLl6N/\n//4YNWoUZDIZLCwsAKBMffam9Y+x4OtGRESkHYM/opdo//79yM/Px8KFCzFo0KByqSMsLAxDhw5F\n3bp1y6X819nvv/8ODw8P/Pbbb2rpQUFB6NixI2rWrFlBLSMiIiKqeAz+iF6itLQ0AECNGjXKrQ5H\nR0c4OjqWW/mvs7S0NDRu3FgjXS6XQy6XV0CLiIiIiCoPvQ9GpKamIjg4GHZ2drC1tcWAAQOQmppq\ncAUJCQkYOHAgnJycYGVlBQ8PDyxevPiFGm2s8vPzsXjxYnTv3h3Ozs4wNzdH7dq18e677+Lq1ata\n93n69Cnmz5+PVq1awcbGBra2tvDy8sLUqVNRUFCglvf06dMYPHgwatWqBQsLC9StWxdBQUE4dOiQ\nKk9ISAhkMhlu3LihUZfyWbTY2FhVWvFnp+Li4tCtWzfY2trCwcGh3I7p0aNHsLGxQbNmzbTu/+TJ\nE9jZ2cHDw0N3h/9Xeno6wsLC4OLiompfSEgIUlJSVHmUz9BFREQAAPz8/CCTyUrsK22ys7MxYcIE\n1K5dGxYWFmjRogU2b96skU9bPwPA48ePER4ejtq1a8PKygqtW7fGpk2b9D7vdvXqVQQGBsLe3h7W\n1tbo3r07zp8/b1CbldLS0jBhwgS4u7vD0tIS1atXh0Kh0KgzPz8f8+bNg6enJ6ysrODg4IBevXpp\nHAvwv3MtJSUFixcvhoeHBywsLODq6ooZM2ZACKGRF/jfOVf8mcaS+qCgoACzZs1C/fr1YWlpiSZN\nmuBf//qXzmM9c+YMBg4ciBo1asDCwgLu7u6YMmUKsrOz1fIVP/dPnjyJ7t27w8bGBnZ2dggKCsL1\n69e1lm/I+xAAcnNzMX/+fLRo0QJVq1aFnZ0dunfvrrUvS/Lw4UN89tln8PDwgLW1Nezs7NC4cWP8\n3//9H+7fv6/Kd+vWLXzxxRdo164dnJycYGFhgYYNG2LSpEl4/PixRrnK5+5yc3PxySefoE6dOqha\ntSo6deqEEydOAABu3LiBIUOGwNHREdbW1ggKCsLt27fVyin+bOr58+fRs2dP2NrawtbWFv3790dS\nUpLBx1qa/rp16xbCwsLg7u6uOk+bNWuG8ePHa/y/SURE9DrReecvJycH/v7+sLS0xOrVqwEAn3/+\nOfz8/HD+/HlYWVnpLPzkyZPw9/eHv78/li1bBltbWyQlJWl8SCLDZGRk4KOPPoKvry/69esHW1tb\nJCYmYsOGDdi1axdOnToFV1dXVf6cnBx07doVx44dQ5MmTRAaGgpJkpCQkID58+dj0qRJqrsh69ev\nx/Dhw2Fqaop+/fqhQYMGSEtLw8GDB7F582b4+Pioyi3L8zSHDh3CV199hW7dumHMmDG4e/duuR7T\n0KFD8fPPP+P48eNo166dWls2bdqErKwsfP7553rbnZ6eDm9vb1y/fh09evTAsGHDkJiYiDVr1mDn\nzp2Ii4tD48aNYW9vj2nTpiE6OhoxMTEICQlRtdvW1lZvPXl5eejRowcePnyIgQMHIjs7G7/++isG\nDRqEXbt2oXv37jr3LywsRO/evREXF4e2bdti1KhRuHnzJoYPH45u3boB0P66Xbt2DR06dICnpydG\njx6Nq1evIioqCn5+fkhISED16tX1tj0hIQF+fn5IT0+Hv78/Bg0ahKysLJw6dQqLFy/GyJEjAQBF\nRUUIDAzEf/7zHzRt2hTjx49HRkYG1q9fD39/f6xbtw6DBw/WKH/SpEmIiYlB37590atXL2zZsgUR\nERHIy8vDrFmzAACBgYGoX78+pk+fDldXV4SEhAAAWrZsqVbW833w3nvvYe3atWjUqBHGjx+Phw8f\nYtKkSejcubPWY92yZQuGDBkCCwsL9O/fHzVr1sSpU6cwZ84cHDhwALGxsahSpYraPidOnMC8efPg\n7++PMWPG4PTp09i6dSsuXLiAixcvwtzcXJXX0Pfh06dP0aNHD8TFxaFdu3Z4//338fjxY0RFRaFr\n167YsGEDAgMDdb5uQgj06NEDp06dwttvv43+/fsjPz8ff/75J9avX4/w8HDVlzSxsbGIjIxEt27d\n0KlTJ0iShKNHj2LBggWIjY3FoUOHYGqqeTkZPHgwEhISEBwcjIyMDPz666+qgKtXr15wd3fHe++9\nh7Nnz2Lr1q24f/8+oqOjNcr5888/0aVLF7Rv3x7jxo1DYmIitmzZgkOHDuHo0aNwc3PTeayl6a/s\n7Gx07NgRaWlpeOeddzBo0CBkZ2cjKSkJS5cuxZw5c7QeKxER0WtB6BAZGSlMTExEcnKyKu3atWvC\n1NRULFy4UNeuorCwULz11lsiKChIZ77i9DTH4DxvqtzcXJGWlqaRHhMTI0xNTcXo0aPV0sPDw4Uk\nSSI0NFRjn/T0dFFQUCCEECItLU1YWVkJOzs7cenSJY28t27dUv0+cuRIIUmSuH79uka+adOmCUmS\nRExMjCrtwIEDQpIkIUmSWLNmzSs7phMnTpSYz9fXV5iZmYn09HSNbc9THu/MmTPV0pcvXy4kSRJ+\nfn5q6dr6QB8XFxchSZIIDAwU+fn5qvR9+/YJSZJEz5499dbxr3/9S0iSJAYOHKiWNyYmRtX/q1at\nUqVfu3ZNlT5v3jy1faZOnSokSRJz5swxqP2tWrUSkiSJtWvXamwrfu6sWLFCdTyFhYWq9Pj4eNX5\nl5WVpUpX9r2bm5u4ffu2Kv3evXvC3t5eyOVykZeXp1afttekeN3F+0DZv97e3iI3N1eVfunSJWFh\nYSEkSRLTp09Xpd+9e1fY2NgINzc3jXN2/vz5QpIk8fXXX6vSip/7GzZsUMs/YsQIIUmS+PXXX1Vp\npXkffvrpp0KSJDF37ly1PHfv3hWurq7CyclJPHnyRKOM4s6dOyckSRL//Oc/Nbbl5OSo7X/37l2R\nk5OjkW/WrFlaX3tfX1/Va/H06VNV+oIFC4QkSUIul4tPPvlEbZ+AgAAhSZI4deqUKq34eTpt2jS1\n/MuWLROSJIm+fftq1C2TydTSStNfUVFRQpIksXjxYo3jffjwoSgqKtJIL86Yr1FERPRylOe1RGfJ\n/v7+olOnThrpvr6+wtfXV2fByg9WcXFxhjeGwV+ZNWvWTLi6uqr+zs/PFzY2NqJatWri0aNHOved\nM2eOkCRJfPnll3rrKWvw17Zt21IczTMvckxCCOHl5SVsbW3VPrReuXJFSJJk0JcST58+FRYWFqJm\nzZpqwYGSp6enkCRJ3LhxQ5VW1uBPJpOJlJQUrduqVaumlqatDuUH3sTERI0yevXqVWLw5+bmppE/\nJSVFSJIkgoOD9bb96NGjQpIk0b17d715FQqFkCRJnD17VmNbWFiYkCRJrF69WpWmPNdWrlypkV+5\n7eLFi2rppQn+Ro0aJSRJEjt37tTIHxoaqhH8KQOXjRs3auQvLCwU1atXF23atFGlKc99hUKhkT86\nOlpIkiQmTpyoSjP0fVhYWCjs7OyEp6en1u3ffvutkCRJ7NixQ2c5yuBvypQpOvPpkpGRISRJEqNG\njVJLVwZ/z////9dff6mCv+eD07Vr12q83srz1NHRUWvw2bhxY2FiYiIyMjLU6i4e/JW2v5TB37/+\n9S8De0Edr1FERPSiyvNaonPsSnx8vNahQ02aNMGmTZt03lGMi4sD8Oz5qvbt2+P06dOwt7fHkCFD\nMHfuXNX066/Kq575u9jjSC/VqVOnMG/ePBw6dAh3795Ffn6+alvx4WOJiYl4/PgxunTpAmtra51l\nKp/B6dGjR/k0GkCbNm1K3FYexwQAoaGhGDt2LDZu3IgRI0YAAJYvXw4AGD16tN79L1++jNzcXHh7\ne8PMzExju6+vL+Lj43H+/PkXnnnTzs4OLi4uGul16tTBsWPH9O5/7tw52Nraap3spEOHDti1a5fW\n/Z4fFgkAzs7OAJ49D6ZPac6dc+fOQS6Xo0WLFhrbfH198f3332t91rB169YaaXXq1DG4jbraI0kS\nOnXqpLHNx8cHS5cuVUtTvg5xcXG4ePGixj6mpqZITEzUSNfWfm19bGhfXr58GXLwD04AACAASURB\nVJmZmXBxcVE9Y1rclStXADx7v/Tp06fEcpo2bQpPT0/MmTMHZ8+exTvvvIMuXbqgadOmWvNv3LgR\nS5YswdmzZ/Hw4UMUFRWptiknOipOkiSN11o522rDhg01rgHKSZJu3bqlUZaXlxcsLS010jt27Iik\npCRcuHABvr6+Wttd2v5SKBSoWbMmPvjgA+zduxc9e/ZE586d4e7urrV8IiKi14nO4O/Bgwewt7fX\nSHdwcMCDBw90Fqy8gA8ePBjjxo3DvHnzcOLECXzxxRdITU3VmIq9vJVXMPYqxcXFoWvXrjA1NcXb\nb78Nd3d3VK1aFZIkYcWKFWoTi2RmZgIAateurbfc0uQtq5JmvyyvYwKAd999F5MmTcKyZcswYsQI\nFBYWYtWqVahTpw569uypd/+srCydbVd+kFXmexElPRdoamqq9iG7JI8ePSrxuSddz+1pmwFT+TxT\nYWGh3npL85pkZWWV2EZdffmibSxJZmYmqlSporV8ba+5cgIUXRNWaXuu0tD2G9qXynacP3++xIl5\nJElCTk6OznJMTExw4MABTJs2DZs3b8bvv/8O4FlgOmnSJIwfP16Vd/78+fjkk09Qo0YN9OnTB87O\nzrCwsIAQAtOnT0dubq7WOp7/ksbExASA7j4p/uWPUknnsPJ10vUeLG1/yeVyHDlyBF988QW2b9+O\njRs3AgAaNWqEadOmYejQoSXWRUREVNmV21Pryg+sw4cPV33b2qVLFxQWFuLTTz9FYmKiwbMt0jOz\nZ89GQUEBYmJiNBYO//e//632t52dHQDt36I/T5n35s2bej94KmdU1DbjnfLDqzYlTRJTXscEADY2\nNhg8eDCWL1+Oq1evIjExEWlpafj8888NmrRG+QH1zp07Wrcr0yvDEgI2NjaqSXSel56eXm71Fj93\n9JHL5SW2pSL60tbWFteuXUNWVpZGvdpec2WexMRENGrU6KW3x9D3obIdQ4YMwS+//PJCdTo6OuK7\n777Dd999h/j4eOzduxeLFy/Ghx9+CLlcjpCQENWMqM7Ozjh37pxqEhjgWT9Nnz79hdpgCH3nja5J\nlcrSXy4uLli1ahWKiopw9uxZ7Nq1C9988w3effdd1KxZE35+fqU8AiIiospB51IP9vb2Wu/w3b9/\nX+0DgDbKdcien6VQ+fe5c+e07hcREaH60TbrmzFLTk6Go6OjRpB0584dJCcnq6Upp24/evQoHj16\npLNc5WyYu3fv1tsG5Z3gv/76S2PbmTNn9O7/vPI6JqXQ0FAAz4Z7Llu2DJIk4b333jNoXw8PD5ib\nm+P48ePIy8vT2B4bG6t1aFtFaNmyJR4+fIjLly9rbDty5Ei51Vuac8fLywuZmZla3/sxMTEAtA9D\nLS8tW7aEEAIHDx7U2KYctl6ct7c3gPLrT0P7skmTJrCxscGJEycMuitsqKZNm2LChAmqURnbt28H\nANy7dw+PHj1Chw4dNP7ff375ifJy5swZjTuZQggcPnwYJiYmJS7rArxYf8lkMrRq1QpTpkxRLQGy\nY8eO0h8AERGRDtHR0WoxUHnSGfw1bdpU67Mtly5dQpMmTXQW7OnpWaYGFT9whUJRpjLeVC4uLsjI\nyFB7rigvLw9hYWEad+JMTEwQGhqK+/fvY+LEiWprogHPvklXDjkbMWIErKysMH/+fFy6dEktnxBC\nbe0t5QfUlStXquXbtGmTKhiqDMdUvL3NmzfHsmXLsHPnTvj7+6stHaGLmZkZhgwZgtu3b2PBggVq\n21atWoULFy5AoVConj+rSMqhaF988YVaelxcXInP+70Mbdu2RatWrbBv3z6sW7dOY3vxO4LK5y4n\nT56s9iE8ISEBP//8M+zs7NCvX79ya+vzhg0bBgCYMWOG2rDFS5cuqZa2KW7UqFGwtrbG5MmTta4v\nl5mZibNnz5a5PYa+D01MTPCPf/wDycnJGn2pdOzYMTx58kRnfdevX9e61qCyHuUzedWrV4eFhQVO\nnTqFp0+fqvKlpaVhypQppTvIMrp//z7mzp2rlrZ8+XIkJSWhd+/eWh9PUCptfyUkJGi90/h8vxAR\nEb0sCoXilQV/Ood9BgQEYOLEibh27Rrq168P4Nmiu4cPH9a4ED+vV69eMDc3x65du9QmHVB+EG3b\ntu2Ltt3ohIWFYc+ePfDx8cGgQYNgamqKvXv3orCwEC1atNC4ozJz5kwcOnQIS5cuxaFDh9CjRw/I\nZDIkJSVh9+7dSE9Ph1wuR40aNbB8+XIMGzYMrVu3Rv/+/VG/fn2kp6cjNjYWffr0waJFiwAA/fr1\ng5ubG1auXInU1FS0bNkSCQkJOHDgAHr37o3//Oc/leKYigsNDUVYWBgAwyZ6KW7evHmIiYnBZ599\nhtjYWHh5eeHy5cvYunUrqlWrhh9//LFU5ZXF80GuNn//+9+xevVqbNy4ESkpKfD390daWho2bNiA\nPn36YOfOnaohuy/b2rVroVAoMHz4cKxYsQJt27bFo0ePcPbsWeTk5OD06dMAngU3mzZtws6dO9Gy\nZUv06tULDx48wK+//or8/HysXLnSoIl8XhY/Pz8MHz4ca9asQYsWLdC3b19kZWWp1qLbuXOnWn4n\nJyfVWoTNmjVD79694e7ujuzsbFy7dk21vuMPP/xQpvaU5n04Y8YMnDx5EvPnz8e2bdvQqVMnODg4\n4K+//sKpU6eQlJSE27dva50kRenMmTMYMGAA2rdvDw8PD9SoUQM3btzA1q1bYW5ujnHjxgF4dvdr\nzJgxWLRoEby8vNC7d2/cv38fO3fuhEKhKHGhdUPOW0N17twZ33zzDY4ePYrWrVvj8uXL2LJlCxwd\nHVV9oqvu0vTXH3/8gY8//lg1yYuDgwOSkpKwY8cO2Nvbl/r/ECIiokpF11Sg2dnZwt3dXTRr1kxE\nRUWJqKgo0bx5c+Hm5iays7NV+VJSUoSJiYmYMWOG2v7Tp08XpqamYsqUKWLPnj1i9uzZwtLSUmNa\ncCU9zTE4z5tsw4YNwsvLS1hZWYlatWqJUaNGiTt37giFQqGxtpUQQjx58kTMnj1bNGvWTFhaWgo7\nOzvh5eUlpk2bpramnBDP1sYbMGCAcHJyEubm5qJevXoiODhYHD58WC1fSkqKCAwMFHK5XFhbW4vu\n3buLU6dOiYiICCGTybQu9VB8yvxXeUxCPFubSyaTCUdHR61LNuiTnp4uwsLCRL169YSZmZmoVauW\nGDlypNalGbT1gT6urq6ifv36Wrdp64OS6nj06JGYMGGCqFWrlrC0tBStWrUSmzZtEl9//bWQJEls\n3bpVlVc5hX5J78WSlkwoyc2bN8UHH3wgXF1dhZmZmahRo4bw8/PTWNsxPz9fzJ07VzRt2lRYWFgI\ne3t70bNnTxEbG6tRZkhIiJDJZFqXFSmpD0pq98qVK4VMJlNb6kEIIQoKCsTMmTOFq6urMDc3F02a\nNBFLlixRLcWg7by9dOmSCAkJEXXr1hVmZmbCyclJtG7dWkyePFlcvnxZlU/Xua+r/w19HxYUFIjv\nv/9etG/fXsjlcmFpaSnc3NxEYGCgWLNmjWrNy5L89ddf4tNPPxXt27cX1atXFxYWFqJBgwZi2LBh\n4sKFC2p58/LyxIwZM4S7u7uwsLAQ7u7uYvr06SIvL09rn5f03hWi5NdIW38V76cLFy6Inj17Crlc\nLmxtbUW/fv1EUlKSRjkl1W1ofyUkJIgPP/xQtGrVSjg6OgpLS0vRsGFDMWbMGK3v+ecZ+zWKiIhe\nXHleS6T/VlCi1NRUhIeHY8+ePRBCoFu3boiMjES9evVUeVJSUtCgQQNERERoDDtbtGgRfvjhB9y4\ncQO1a9fGyJEjMXXqVNWsb8VJkqT322JD8hAVFxsbC4VCgfHjxyMyMrKim/PKDR8+HOvWrcOlS5c4\nyRK9VpTXlpCQENUyLZUdr1FERPSiyvNaojf4e5UY/FF56NevH3bs2IGLFy/irbfequjmlJvbt2+r\nlkxQiouLg5+fH9zc3LSuQUdUmTH4IyIiY1Se15JyW+qBqCKlpqZi3bp1uHDhArZv346BAwe+0YEf\n8Ox5xrS0NLRp0wa2trZITEzEzp07YWpqqnNtOiIiIiIyDgz+6I2UnJyMKVOmQC6XIzg4GD/99FNF\nN6ncDR48GEuWLMFvv/2GzMxM2NnZ4Z133sHkyZM1ltIgIiIiIuPDYZ9EREQvCa9RRET0osrzWlI+\nc78TERERERFRpcLgj4iIiIiIyAgw+CMiIiIiIjICDP6IiIiIiIiMAIM/IiIiIiIiI8Dgj4iIiIiI\nyAgw+CMiIiIiIjICDP6IiIiIiIiMAIM/opds586d8Pb2hlwuh0wmQ3h4+EstXyaTwc/PTy0tJCQE\nMpkMN27ceKl1vS5WrlwJmUyGVatWVXRTiIiIiCot04puANGbJDk5GUFBQXBycsI//vEPWFtbo337\n9i+9HkmSDEozNuwDIiIiopIx+CN6ifbv34/8/HwsXLgQgwYNeqV1CyFeaX1ERERE9HrhsE+ilygt\nLQ0AUKNGjQpuCRERERGROgZ/r5H8/HwsXrwY3bt3h7OzM8zNzVG7dm28++67uHr1qtZ9nj59ivnz\n56NVq1awsbGBra0tvLy8MHXqVBQUFKjlPX36NAYPHoxatWrBwsICdevWRVBQEA4dOqTKo+vZsoiI\nCMhkMsTGxqrSoqOjIZPJMH36dMTFxaFbt26wtbWFg4NDuR3To0ePYGNjg2bNmmnd/8mTJ7Czs4OH\nh4fuDv+v9PR0hIWFwcXFRdW+kJAQpKSkqPKkpKRAJpMhIiICAODn5weZTGbQc3j79+/HqFGj0KhR\nI1hbW0Mul8PHxwcbNmwwqH1lsXHjRnTu3BlOTk6wtLREnTp10KdPH+zdu1ct3/LlyxEQEAAXFxdY\nWFjAyckJ/fv3x6lTpzTKLP7cXVRUFNq0aYOqVavC1dUVCxcuBAAUFRVhzpw5cHd3h6WlJTw9PbFj\nxw6NshQKBWQyGZ4+fYqPPvoIderUgaWlJVq2bIm1a9eW6lgPHDiA3r17w9HREZaWlmjatCnmzp2L\nwsJCtXxCCCxZsgRt2rSBg4MDqlatChcXFwQHB+P06dOlqpOIiIioMuKwz9dIRkYGPvroI/j6+qJf\nv36wtbVFYmIiNmzYgF27duHUqVNwdXVV5c/JyUHXrl1x7NgxNGnSBKGhoZAkCQkJCZg/fz4mTZoE\nuVwOAFi/fj2GDx8OU1NT9OvXDw0aNEBaWhoOHjyIzZs3w8fHR1VuWZ6rOnToEL766it069YNY8aM\nwd27d8v1mIYOHYqff/4Zx48fR7t27dTasmnTJmRlZeHzzz/X2+709HR4e3vj+vXr6NGjB4YNG4bE\nxESsWbMGO3fuRFxcHBo3bgx7e3tMmzYN0dHRiImJQUhIiKrdtra2OuuYP38+rl27hg4dOsDZ2RkZ\nGRnYtm0bhgwZgrS0NEyYMKF0na3H999/j3HjxsHd3R1Dhw6FjY0Nbt68icOHD2P37t3o1q2bKm9Y\nWBhatWqFnj17wtHREdeuXUNUVBT++OMPREdHw9vbW6P83377Dfv27UNQUBC6dOmCzZs3Y+LEibC0\ntMTp06exa9cu9O3bF4WFhVi7di2CgoJw6dIluLu7a5QVHByM+Ph4DBkyBLm5udiwYQNGjBiBe/fu\n4cMPP9R7rN999x3Gjx+P6tWrIzAwEPb29jh48CAmT56M48ePY/Pmzaq8H3/8MRYsWIAWLVogJCQE\n5ubmSE1NRXR0NI4ePYpWrVqVsceJiIiIKglRiRjSnNI2GRGo0J+XKTc3V6SlpWmkx8TECFNTUzF6\n9Gi19PDwcCFJkggNDdXYJz09XRQUFAghhEhLSxNWVlbCzs5OXLp0SSPvrVu3VL+PHDlSSJIkrl+/\nrpFv2rRpQpIkERMTo0o7cOCAkCRJSJIk1qxZ88qO6cSJEyXm8/X1FWZmZiI9PV1j2/OUxztz5ky1\n9OXLlwtJkoSfn59aurY+0CclJUUjLTs7W7Ro0ULY2tqKnJwctW3a6tX1ujzPy8tL1KlTRzx58kRj\nW0ZGht62JSQkCBsbG9GtWze19BUrVghJkoSFhYU4e/asKv3mzZvCwsJCyOVy0aRJE3H//n3Vts2b\nNwtJkkRYWJhaWb6+vkKSJOHp6Smys7NV6bdu3RI1atQQFhYWauelsu5Vq1ap0i5evChMTU1Fhw4d\nRFZWllr5YWFhQpIksWnTJlWavb29aNu2rSgqKtI45gcPHmikEWlTyS6rRET0GirPawmHfb5GzMzM\nULNmTY30Ll264K233lIbsldQUICff/4Zjo6OWLBggcY+Tk5OMDExAQCsWrUKT548waRJk/DWW29p\n5K1Vq9YLt71NmzYYNmyYRnp5HVObNm3QsmVLrF+/Hk+ePFHluXr1KmJjY/HOO+/AyclJZ5tzc3Ox\nfv161KhRAx9//LHatlGjRqFp06aIjo5Gamqq7oPXw8XFRSPNysoKI0aMQFZWFk6cOPFC5T9PkiRU\nqVIFMpnm2185HFdX2zw8PKBQKHDw4EGNocMAMGzYMLRo0UL1d+3ateHj44NHjx5hypQpsLe3V23r\n378/qlSpgosXL2pt62effQYrKyvV37Vq1cKECRNUr40uS5YsQWFhIRYvXgwbGxu1bV9++SUkScKv\nv/6qSpMkCebm5lrvbNvZ2emsi4iIiOh1wGGfr5lTp05h3rx5OHToEO7evYv8/HzVNnNzc9XviYmJ\nePz4Mbp06QJra2udZSqDix49epRPo/EsGCtJeRwTAISGhmLs2LHYuHEjRowYAeDZM2wAMHr0aL37\nX758Gbm5ufD29oaZmZnGdl9fX8THx+P8+fOoW7eu3vJKkpWVhXnz5iEqKgp//vmnWrAK/G8SmZdl\n8ODB+PTTT+Hp6YkhQ4ZAoVCgffv2akGW0tWrV/HVV1/hwIEDSEtLQ15enmqbJEnIyMjQmNymeOCn\npPwC4fltMpkMTk5OuHXrlta2du7cWSNNOQT5/PnzOo/z2LFjkCQJ27dv1/pcoYWFBRITE1V/Dx48\nGD/99BNatWqF4OBgKBQKtGnTRutrT0RERPQ6YvD3GomLi0PXrl1hamqKt99+G+7u7qhatSokScKK\nFSvUJhbJzMwE8Oyuiz6lyVtWJc1+WV7HBADvvvsuJk2ahGXLlmHEiBEoLCzEqlWrUKdOHfTs2VPv\n/llZWTrbrrxjqcxXFnl5efD19cW5c+fQpk0bvPfee3BwcICJiQnOnDmDqKgo5Obmlrl8bT7++GM4\nODjgp59+wqxZszBr1iyYm5sjODgYCxYsQPXq1QEAV65cQbt27fD48WN0794dAwYMgLW1NWQyGbZs\n2YJz585pbZvyOdLilHdktW0zNTVVC/iVJElStaU45euhPB9Kcv/+fQghMHPmTK3bJUlCTk6O6u/F\nixejfv36WLFihep5UBsbG4wYMQJz5sxB1apVddZHREREVNkx+HuNzJ49GwUFBYiJidFYOPzf//63\n2t/KYWol3VHRlvfmzZt6AyvlUEFtw/10fRgvaZKY8jom4NkH98GDB2P58uW4evUqEhMTkZaWhs8/\n/9ygSWuUgcqdO3e0blemawtoDBUVFYVz584hNDQUP/30k9q2uXPnIioqqsxl6zJ69GiMHj0a9+7d\nQ0xMDFavXo1169apJjgBgMjISGRmZuKXX37BkCFD1PY/cuQIzp07Vy5tUxJCID09Hc7Ozmrpyn7X\nN5GOXC6HTCbD48ePYWFhobc+U1NTTJo0CZMmTcLNmzdx4MABLF26FN9//z0ePXqElStXlvlYiIiI\niCqDNz74E9PenIWvk5OT4ejoqBEk3blzB8nJyWppHh4esLa2xtGjR1VLH5SkXbt22Lx5M3bv3o22\nbdvqbIPyea2//voLDRo0UNt25syZ0hwOgPI7JqXQ0FAsX74cy5cvR0JCAiRJwnvvvWdQ2zw8PGBu\nbo7jx48jLy9PY/hfbGwsJEnSOszRUMpjDAgI0NhWfImN8lKtWjUMGDAAAwYMgJeXF2JjY1V9m5yc\nDEmSNNr29OlTnD59ukyzvpZWbGwshg4dqpYWFxcHQPvw0uK8vb1x5swZHDt2DL6+vqWq19nZGcOG\nDcPgwYPh7OyM7du3l67hRERERJUQJ3x5jbi4uCAjI0PtOaW8vDyEhYVp3IkzMTFBaGgo7t+/j4kT\nJ+LZxEH/k56erlrnbMSIEbCyssL8+fNx6dIltXxCCNy+fVv1t3LZhOfvgmzatEkVDFWGYyre3ubN\nm2PZsmXYuXMn/P391ZaO0MXMzAxDhgzB7du3NSaYWbVqFS5cuACFQoE6deqU4ojVKSdUUQY0Sr/9\n9pvW59RehpiYGI20J0+eIDMzE1WqVFEN0XRxcYEQQq1tQghMnjxZtVRHefvyyy+RnZ2t+jstLQ3f\nfPMNLCwsMGjQIJ37jh07FiYmJhg3bpzW5ybv3LmjOu/y8vJw5MgRjTxZWVl48uSJQXcOiYiIiCq7\nN/7O35skLCwMe/bsgY+PDwYNGgRTU1Ps3bsXhYWFaNGihcYwvJkzZ+LQoUNYunQpDh06hB49ekAm\nkyEpKQm7d+9Geno65HI5atSogeXLl2PYsGFo3bo1+vfvj/r16yM9PR2xsbHo06cPFi1aBADo168f\n3NzcsHLlSqSmpqJly5ZISEhQLaT9n//8p1IcU3GhoaEICwsDYNhEL8XNmzcPMTEx+OyzzxAbGwsv\nLy9cvnwZW7duRbVq1fDjjz+Wqrzn9e3bF/Xq1cPcuXMRHx+Pxo0bIz4+Hn/88QcCAwOxZcuWFypf\nm379+sHe3h7e3t6oV68enj59it9//x0pKSkYN26cauKX999/HytWrEBQUBAGDx4MuVyOgwcPIiUl\nBQqFQjU8tDw1aNAAnp6eGDBggGqGz4yMDCxcuFDvLLSenp749ttvERYWhkaNGqFPnz5wcXHBgwcP\ncPXqVcTFxWHWrFnw8PBATk4OfHx84OHhAS8vL9StWxeZmZnYtm0bcnJyMGPGjHI/ViIiIqJyV26L\nSJSBIc2pZE1+5TZs2CC8vLyElZWVqFWrlhg1apS4c+eOUCgUQiaTaeR/8uSJmD17tmjWrJmwtLQU\ndnZ2wsvLS0ybNk3k5+er5T1x4oQYMGCAcHJyEubm5qJevXoiODhYHD58WC1fSkqKCAwMFHK5XFhb\nW4vu3buLU6dOiYiICCGTybSu8zd9+vQKOSYhhHj48KGQyWTC0dFR5Obm6u3j56Wnp4uwsDBRr149\nYWZmJmrVqiVGjhypdQ08bX2gT3JysggMDBROTk7CxsZGdOnSRezevVusXLlSyGQytbXrhNC+zl9I\nSIiQyWQGrfP3448/ioCAAOHq6iosLCxE9erVRefOncXatWs18u7bt0907NhR2NjYiGrVqong4GBx\n9epVrfWV1F597XN1dRX169dXS/P19RUymUw8ffpUfPTRR6JOnTrC3NxcNG/eXOt6kbrqPnLkiBg4\ncKCoVauW6vXr0KGDmDlzpkhNTRVCCJGfny/mzp0revTooaqrdu3aokePHmLHjh16+5RIydivUURE\n9OLK81oi/beCSkGSJI2hfGXJQ1RcbGwsFAoFxo8fj8jIyIpuDhlAuY7g88N4iSo7XqOIiOhFlee1\nhM/80RtvwYIFkCQJ77//fkU3hYiIiIiowvCZP3ojpaamYt26dbhw4QK2b9+OgQMH4q233qroZlEp\n8O4JERER0cvF4I/eSMnJyZgyZQrkcjmCg4M11tCjyk2SpFeylAQRERGRMeEzf0RERC8Jr1FERPSi\n+MwfERERERERvRAGf0REREREREaAwR8REREREZERYPBHRERERERkBBj8ERERERERGQEGf0RERERE\nREaAwR8REREREZERqHSLvCckADIZIEma/0oSYGdnz8WfiYioUrK3t6/oJhAREZWo0i3y3rixgBBA\nURG0/qtrmyF5nk9TKh5g6go+S9rG/bl/Re6v/CEiIiKi11t5LvJe6e78JSa+2vqUAWFZg8cXDT6N\nZf/Cwte7/ZV9f6XXNXjl/pWjjsqwP7/EICJtlNdA5e/a0vRtL8s+5VEm28F26NunPFW64O9VK/5h\nw8SkYttCVFbK/zjKGjwamsfY9y8qqvj6K3sfvcj+Sq9z8FqR+xf/v0D5u7a08vqwUtp92A62w5Dt\nz1Oe68X/Lel3Q9Mqoky2g+3Qt095Mfrgj+hNUPw/DaLX2YsEj/q2ven7V4YPK5XlQxPb8Wa2g+iV\nKSoC8vL0/+TmGpavlD8LyvHQKt0zf5WoOURERERE9DII8ew5oIoKqkpTZlERYGZm2I+5ueF5DfyR\nunUrt5io8gV/9vaAqan6j4mJZtqbsk2ZXnzcDhERERGRIYQA8vPLJwh62WXKZBUaVBlcpolJhX4u\nL88bYpUv+MvIAAoKNH8KC7WnvwnbCguffcNQWQPUFw1sS7sPg2AiIiKqaIYO/avooCo/H6hSpXyC\noJdZZpUqnGDDQMYV/FWe5rxaRUXag8PKEqC+SGBbmn0KC599K1QZgtdXGfRq2yaTVfRZSURE9HKV\nZuhfRQdVhYWlD5IqKqjiF+dvlAoP/lJTUxEeHo69e/dCCIFu3bohMjISdevW1VuBrIQPsGfPnkXz\n5s3VG2PMwR89o7woVJbg9VUFvc9vy89/9h/5mxrYlmYb7wYTEelX2qF/FRlUlWboX0UGVbz+UAWp\n0OAvJycHLVq0gKWlJWbNmgUA+Pzzz5GTk4Pz58/DyspKZwUymQyjRo3C+++/r5berFkzWFpaqjeG\nwR/R/xQVvZmBbWm3FRVpDxDfhMC2NNtMTHg3mKgilHboX3kFVvrKK8vQv4oIrDj0j0ivCl3kfenS\npbh27RqSkpLQoEEDAEDz5s3RsGFDLFmyBOHh4XorcXZ2Rrt27V68tUTGpPg3o8ZMeTe4ogPbvDwg\nJ6diA2KZ7M0MbEu7jRNkvf7KMvSvou5WlWXonyFBlVz+8oMqvi+ISA+9zfGkCAAAIABJREFUwd+2\nbdvQoUMHVeAHAK6urvDx8UFUVJRBwR/v5hFRmRUf/mrMlIu5VYY7tk+fVsxdYOW24hNkVdYAtby3\nKdOf/7BflqF/FRVUlWXonyFBlbX1yy2TQ/+I6A2id9hnzZo1ERgYiB9//FEtfezYsdi0aRPS09N1\nViCTyeDg4IDHjx/DxMQE7du3x/Tp09GpUyfNxnDYJxER6fP8BFmVZUh0eWzTt49ygiwTk2dpLzL0\nr7yG/2krl0P/iIhKVKHDPh88eAB7e3uNdAcHBzx48EBvBcOGDUPfvn1Ru3ZtpKSkYP78+fD398ee\nPXvg6+tbtlYTEZHxksme/VSpUtEtqVjF7wYXFDzrDw79IyIiHcp9HNXq1atVv/v4+KBfv37w9PTE\n1KlTERsbW97VExERvZkk6X8z4pqbV3RriIjoNaA3+LO3t9d6h+/+/ftwcHAodYXW1tbo3bs3VqxY\noXV7RESE6neFQgGFQlHqOoiIiIiIiF4H0dHRiI6OfiV16X3mr2vXrsjLy8PBgwfV0hUKBSRJwoED\nB0pd6dixY7Fy5Urk5OSoN4bP/BERERERkRErz5hI76JRAQEBOHr0KK5du6ZKS0lJweHDhxEQEFDq\nCrOysrBjxw4u/UBERERERPQKlWmR96lTpyI7O1ttkffr16/Dzc0N06ZNw9SpUwEAX3/9NZKTk6FQ\nKFCjRg1cv34dX3/9Na5cuYJ9+/bBx8dHvTG880dEREREREasQmf7tLKywv79+xEeHo7hw4dDCIFu\n3bohMjJSFfgBz9byKyoqUmuoh4cHtm7dik2bNiEzMxNyuRydOnXCihUr0KZNm3I5ICIiIiIiItKk\n987fq8Q7f0REREREZMwq9Jk/IiIiIiIiev0x+CMiIiIiIjICDP6IiIiIiIiMAIM/IiIiIiIiI8Dg\nj4iIiIiIyAgw+CMiIiIiIjICDP6IiIiIiIiMAIM/IiIiIiIiI8Dgj4iIiIiIyAgw+CMiIiIiIjIC\nDP6IiIiIiIiMAIM/IiIiIiIiI8Dgj4iIiIiIyAgw+CMiIiIiIjICDP6IiIiIiIiMAIM/IiIiIiIi\nI8Dgj4iIiIiIyAgw+CMiIiIiIjICDP6IiIiIiIiMAIM/IiIiIiIiI8Dgj4iIiIiIyAgw+CMiIiIi\nIjICDP6IiIiIiIiMAIM/IiIiIiIiI8Dgj4iIiIiIyAgw+CMiIiIiIjICDP6IiIiIiIiMAIM/IiIi\nIiIiI8Dgj4iIiIiIyAgw+CMiIiIiIjICDP6IiIiIiIiMAIM/IiIiIiIiI8Dgj4iIiIiIyAgw+CMi\nIiIiIjICDP6IiIiIiIiMAIM/IiIiIiIiI8Dgj4iIiIiIyAgw+CMiIiIiIjICDP6IiIiIiIiMAIM/\nIiIiIiIiI8Dgj4iIiIiIyAgw+CMiIiIiIjICDP6IiIiIiIiMAIM/IiIiIiIiI8Dgj4iIiIiIyAgw\n+CMiIiIiIjICDP6IiIiIiIiMgN7gLzU1FcHBwbCzs4OtrS0GDBiA1NTUUlc0Z84cyGQydO7cuUwN\nJSIiIiIiorKThBCipI05OTlo0aIFLC0tMWvWLADA559/jpycHJw/fx5WVlYGVfLnn3+iefPmsLa2\nRqNGjRAbG6u9MZIEHc0hIiIiIiJ6o5VnTGSqa+PSpUtx7do1JCUloUGDBgCA5s2bo2HDhliyZAnC\nw8MNqmTMmDEYPnw4EhMTUVBQ8OKtJiIiIiIiolLROexz27Zt6NChgyrwAwBXV1f4+PggKirKoAp+\n+eUXnD17FrNnz4YQApIkvViLiYiIiIiIqNR0Bn/x8fHw9PTUSG/SpAkuXbqkt/AHDx4gPDwc8+bN\ng52dXdlbSURERERERC9EZ/D34MED2Nvba6Q7ODjgwYMHegufNGkSPDw8MHLkyLK3kIiIiIiIiF6Y\nzmf+XsTBgwexZs0anDlzpryqICIiIiIiIgPpDP7s7e213uG7f/8+HBwcdBb8/vvv4+9//zucnZ3x\n8OFDAEBBQQGKioqQmZkJS0tLmJmZaewXERGh+l2hUEChUBhwGERERERERK+f6OhoREdHv5K6dC71\n0LVrV+Tl5eHgwYNq6QqFApIk4cCBAyUWLJPpXkIwMjIS48ePV28Ml3ogIiIiIiIjVmFLPQQEBGDi\nxIm4du0a6tevDwBISUnB4cOHMXfuXJ0FHzhwQG1mTyEEPvzwQxQVFeHbb7+Fm5vbS2g+ERERERER\nGaLUi7xPnToV2dnZaou8X79+HW5ubpg2bRqmTp1aYmUKhQKFhYUadxJVjeGdPyIiIiIiMmLlGRPp\nHJtpZWWF/fv3o1GjRhg+fDiGDRsGNzc37N+/XxX4Ac/u6hUVFeltpCRJXOePiIiIiIioAui88/eq\n8c4fEREREREZswq780dERERERERvBgZ/RERERERERoDBHxERERERkRFg8EdERERERGQEGPwRERER\nEREZAQZ/RERERERERoDBHxERERERkRFg8EdERERERGQEGPwREREREREZAQZ/RERERERERoDBHxER\nERERkRFg8EdERERERGQEGPwREREREREZAQZ/RERERERERoDBHxERERERkRFg8EdERERERGQEGPwR\nEREREREZAQZ/RERERERERoDBHxERERERkRFg8EdERERERGQEGPwREREREREZAQZ/RERERERERoDB\nHxERERERkRFg8EdERERERGQEGPwREREREREZAQZ/RERERERERoDBHxERERERkRFg8EdERERERGQE\nGPwREREREREZAQZ/RERERERERoDBHxERERERkRFg8EdERERERGQEGPwREREREREZAQZ/RERERERE\nRoDBHxERERERkRFg8EdERERERGQEGPwREREREREZAQZ/RERERERERoDBHxERERERkRFg8EdERERE\nRGQEGPwREREREREZAQZ/RERERERERoDBHxERERERkRFg8EdERERERGQEGPwREREREREZAQZ/RERE\nRERERsCg4C81NRXBwcGws7ODra0tBgwYgNTUVL37Xb9+Hf369YOrqyusrKzg5OQEhUKB33///YUb\nTkRERERERIbTG/zl5OTA398fSUlJWL16NdasWYMrV67Az88POTk5OvfNzs6Gk5MTvvzyS/z+++9Y\ntmwZbGxs0KdPH2zduvWlHQQRERERERHpJgkhhK4M33zzDT766CMkJSWhQYMGAICUlBQ0bNgQ8+bN\nQ3h4eKkqLCwsRP369eHl5YWoqCj1xkgS9DSHiIiIiIjojVWeMZHeO3/btm1Dhw4dVIEfALi6usLH\nx0cjeDOEiYkJ5HI5TExMSr0vERERERERlY3e4C8+Ph6enp4a6U2aNMGlS5cMqkQIgYKCAty+fRsz\nZszAlStX8MEHH2jNe/LkSd79IyIiIiIiesn0Bn8PHjyAvb29RrqDgwMePHhgUCWTJk2CmZkZateu\njblz52LdunXo2rWr1rxt27aFq6srwsPDERcXh8LCQoPqICIiIiIiopK9kqUewsPDcfLkSezYsQPv\nvPMOhg0bhp07d5aY/8aNG4iMjETnzp3h7OyMMWPGYM+ePcjPz38VzSUiIiIiInrj6J3wpWbNmggM\nDMSPP/6olj527Fhs3rwZd+7cKXWlfn5+uH37NhISEtQbI0k697O3t0dAQAAGDBiA7t27w8LCotR1\nExERERERVRbR0dGIjo5W/T19+vRyewxOb/DXtWtX5OXl4eDBg2rpCoUCkiThwIEDpa504sSJ+Oab\nbzTu5OkL/oqztrZGnz59EBQUhN69e8Pa2rrU7SAiIiIiIqpMKnS2z4CAABw9ehTXrl1TpaWkpODw\n4cMICAgodYVFRUX4f/buPDqK60wb+NOtXYBAQljsi9j3xexmR+wSkqowGBCqjud4mXjiY8bOjCef\ncUjiOOPMJEMSx/EkJ5MusZmlShJiFyB2MIsNGAwWOzK7kARCEtr6fn8odBBrl1C1utXP7xwdN029\nt9573bT67Vt17+7du9GpU6fH/r2rq4DevXsXK1aswKxZsxAZGYn4+HikpKS4fB8iERERERGRL3nm\nzF9xcTH69u2LkJAQfPTRRwCABQsWoKioCMeOHUNoaCgA4OLFi+jYsSN++tOfYsGCBQCAhQsXIj8/\nH8OHD0fz5s1x7do1/PWvf8W2bduwbNkyzJw5s3oyFgtyc3ORkZEBTdOwefNmlJWVGeqQv78/xo0b\nB0mSkJCQgKioKEPxREREREREdcXMmb9nFn8AkJOTg/nz5yMzMxNCCMTExGDRokVo27at85gLFy4g\nOjoaCxcuxIcffggAyMjIwKJFi3D8+HHcvn0bzZs3R79+/fDv//7vGDZs2KPJPNTRO3fuYP369dB1\nHevXr0dRUZGxzlksGDFiBGRZhiRJaNOmjaF4IiIiIiIid6rz4s9dntbRkpISbN68GZqmYc2aNbh9\n+7bh9gcNGgRJkiDLMjp37vy86RIREREREdUqFn8PKSsrQ1ZWFnRdR1paGm7cuGH4XL169XLOCPbu\n3dvQYjNERERERERmYPH3FJWVldizZw80TYOu6/j+++8Nn7dTp07OGcFBgwaxECQiIiIiojrhU8Vf\nTs4iWCz+D/0EPOa5R58H/PDVV6eQkZGF9PRMnD170XAOrVu3hiRJkCQJI0aMcHn1USIiIiIi8i1C\nOCBEORyOcghRDiHKHnhc/sDflT103P2/K3M+zs6+hJUrd+OPf9zsO8VfDbYNfCwhgPPngZ07gV27\ngHPnjLcRHm7FqFGNMG5cYwwcGIbAwMCnFqNWq2tFak2fr732ObNJRERERHVHCAEhKl0qimqjsHrw\n7x58/tntP70NwPFc41BYCGzbBmzcCJw6VX18zFBvi7+H5eQAu3dXFYMPDqyrGjYEhg0DRo0CBg0C\ngoJqP0f38fPy4rUm7T9zS0siIiIir1Cbs01mFUWutOGrKiuBAweATZuAvXuB8scMBYu/WnT9etVs\n4K5dwDffVM0SGhEcDAwZUlUIDh0K/H2rQ/JoFi8vXmvyvB9neYmIiB5Qs9km9xdFzyrcnne2ierG\nuXNVBV9mJpCf//RjWfyZJC8P2LOnakbw66+rKnEjAgKAgQOrCsFhw4DGjc3Jk6hm/EwsLj21OOYs\nLxGRGR6dbXpSQWNmYWW0fc42Ud26fRvYsqWq6Dt92vU4nyn+srPfhhAVD/yUP/Tnpz9f9Q/cteMf\n/taksLBq6nXXrqqp2MdNwT6N1Qr07w+MHFn1ExFRe2NDRK6ymFxcemJxzFleIk/mntmmxxdFnG0i\nMt8/fj8HwmoNQEWFP/btq8CGDSXYs6fI0ORSt25NcerULd8p/tyZTtU3WI8rFCtQWFiAjRu3ID19\nEzZu3I67d4sNtW2xWDBwYDSmTu2HSZN6onXrxrVevNbs+QqTRpOI6tLjC0VvKV5r0j5neX2F67NN\ndVcUuVK4EdHjWGGxBPz9d0DA3x8HOh9X/7vAasc9fGzN26h6/uE2XG/f31nDfP3111BVFcuWLUNu\nbq7Lo9CsWTMkJSVBURT07dvX1JrIp4s/V927dw+ZmZnQdR3p6enIf9ZFuo/x4osvOvcS7Nq1qwlZ\nuuYf3z6aU1yaXbzWrH3+0iWqn6xeXLzWrP2qPrs2y/uP93vPLoo420RUM1XvD0aKFjMKn+dpPwAW\ni/dvqXbt2jUsXboUqqrim2++cTkuICAA06dPh6IomDx5MgICApx/x+LPg5SXl2PHjh3QNA2pqam4\nfv264TZ69OgBWZYhSZKzuidzPTrL603Fa83aBwzewEpEXuHxxaIfhKjkbBORS6wuFCaeMKP0tPb9\n+fmxDt27dw8ZGRlQVRUbN25EpYHrOgcOHAibzYZXXnkFTZs2fewxLP48VGVlJfbt2wdN06DrOi5d\numS4jejoaOeM4ODBg2G18jImqh3VZ3m9r3itWTv8sEtEZCbPKHyet31+1iLjhBA4cOAAVFXF8uXL\nUVBQ4HJsixYtMG/ePCiKgh49ejzzeBZ/XkAIgcOHD0PXdWiahuzsbMNttGrVComJiZAkCSNHjoS/\nv78JmRLVb/fvD/LO4rVm7XOWl8gbWD2k8Hme9jnbRL7n8uXLWLx4MVRVxSkDm4UHBQUhMTERiqIg\nJibG0Od6Fn9eRgiBb7/91jkjePToUcNtREZGIj4+HrIsY9y4cQjy7l3lichEVQXv89/L623FMfkO\nzyh8jLb/cBucbSLyFsXFxUhLS4OqqsjMzDRUnwwfPhyKomDmzJlo0qRJjc7P4s/LnTlzBqmpqdA0\nDV9++aXh+LCwMMTFxUGSJEyePBmh3FWeiHxc1e8Kh6nFpecUxw8WvEYXP7F6xYzS09rgViZE5A5C\nCOzZsweqqmLlypW4c+eOy7Ft2rRBcnIykpOT0aVLl+fOhcVfPfL9998jNTUVuq5j586dcDiM/SIP\nCQnBlClTIMsypk2bhsbcVZ6IyGc8Osv7j4LxHwvAcLaJiMhVFy9eREpKClJSUnDmzBmX40JDQyHL\nMhRFwdixY2t13Q4Wf/XUjRs3sGbNGmiahq1bt6Lc4K7ygYGBiImJgSRJiI+PR2RkpEmZEhERERHV\nD3fv3oWmaVBVFVlZWYZiR48eDUVRMGPGDDRq1MiU/Fj8+YCCggKsXbsWuq5j48aNKCkpMRRvtVox\nevRoyLKMhIQEtGrVyqRMiYiIiIi8i8PhwI4dO6CqKlavXo2ioiKXYzt06ABFUTBv3jxER0ebmGUV\nFn8+pqioCBs3boSmaVi7di0KCwsNtzFs2DDnFhIdOnQwIUsiIiIiIs929uxZqKqKlJQUXLx40eW4\nhg0bYubMmVAUBSNGjHDrdmws/nxYaWkptmzZAl3XkZ6ejlu3bhluo3///s5CsHv37iZkSURERETk\nGe7cuYOVK1dCVVXs3r3b5TiLxYJx48bBZrMhMTERDRo0MDHLp+fB4o9QUVGBnTt3QtM0pKam4urV\nq4bb6NatG2RZhiRJ6N+/P1dQIyIiIiKvV1lZiW3btsFutyM1NdXQLVSdO3eGzWZDUlIS2rZta2KW\nrmHxR49wOBzYv3+/c1P5CxcuGG6jffv2zhnBoUOHunU6m4iIiIjoeZ06dQqqqmLx4sW4fPmyy3GN\nGzfGrFmzYLPZMHToUI+aEGHxR08lhMCRI0egaRo0TcOpU6cMt9GiRQskJiZCkiSMHj0a/v7+JmRK\nRERERPR88vPz8cUXX0BVVUN7aFutVkycOBE2mw3Tp09HSEiIiVnWHIs/MuTkyZPOGcGvv/7acHxE\nRATi4+MhyzJiYmIQFBRkQpZERERERK6pqKjApk2boKoq0tPTUVZW5nJsjx49oCgKkpKS0LJlSxOz\nrB0s/qjGzp8/D13Xoes69u7dazi+UaNGiI2NhSRJmDJlSp3d+EpEREREvuebb76BqqpYunQprl27\n5nJcREQEZs+eDZvNhhdffNGjLut8FhZ/VCuuXLmCtLQ0aJqGHTt2oLKy0lB8cHAwJk+eDFmWERsb\niyZNmpiUKRERERH5qtzcXCxbtgyqquKrr75yOc7Pzw9Tp06FzWbDtGnTvPbqNRZ/VOtyc3OxZs0a\n6LqOzMxMQ1PnABAQEIDx48dDkiQkJCSgWbNmJmVKRERERPVdWVkZNmzYALvdjnXr1qG8vNzl2L59\n+8Jms2HOnDl44YUXTMzSPVj8kalu376N9evXQ9M0bNiwAcXFxYbirVYrRo4cCVmWkZiYiNatW5uU\nKRERERHVF/cXLbTb7Vi2bBlyc3Ndjm3WrBnmzp0LRVHQr18/E7N0PxZ/5DbFxcXYtGkTNE1DRkYG\n7ty5Y7iNIUOGOLeQ6NixowlZEhEREZG3un79OpYuXQq73Y5vvvnG5biAgADExcXBZrNh8uTJCAgI\nMDHLusPij+pEWVkZtm7dCl3XkZaWZujbmPv69Onj3FS+Z8+eXnWzLRERERHVjtLSUmRkZMBut2Pj\nxo2G1p4YOHAgbDYbXnnlFTRt2tTELD0Diz+qcxUVFdi9ezc0TUNqaqqhTTTv69Kli3NG0NtWXSIi\nIiIiY4QQOHjwIFRVxfLly5Gfn+9ybIsWLZCUlARFUdCzZ08Ts/Q8LP7IozgcDhw4cMC5l+C5c+cM\nt9G2bVtIkgRJkjB8+HD4+fmZkCkRERERudvly5exZMkS2O12nDp1yuW4oKAgJCQkwGazISYmBv7+\n/iZm6blY/JHHEkLg2LFj0DQNuq7jxIkThtuIiopCQkICZFnGmDFj6u3120RERET1VUlJCdLS0mC3\n27FlyxY4HA6XY4cNGwZFUTBr1ixuJQYWf+RFvvvuO+eM4OHDhw3Hh4eHY/r06ZAkCRMnTkRwcLAJ\nWRIRERHR8xJCYO/evVBVFStWrDC0UGDr1q2RnJyM5ORkdO3a1cQsvQ+LP/JKFy9ehK7r0HUde/bs\nMfz/tmHDhpg6dSpkWcaUKVPQqFEjkzIlIiIiIlddvHgRixcvhqqqOHPmjMtxISEhkGUZiqJg7Nix\nvO3nCVj8kde7evUq0tPToWkasrKyDK3wBFRdAz5p0iRIkoTp06cjPDzcpEyJiIiI6GF3796Fruuw\n2+3IysoyFDtq1CgoioIZM2YgLCzMpAzrDxZ/VK/k5eVhzZo10HUdmzdvRmlpqaF4f39/jB07FrIs\nIyEhAVFRUSZlSkREROS7HA4Hdu7cCbvdjtWrV6OoqMjl2A4dOjgv64yOjjYxy/qHxR/VW4WFhVi/\nfj00TcP69esNvakAVa+ZESNGQJZlJCYmom3btiZlSkREROQbzp49i5SUFKSkpODChQsuxzVs2BAv\nv/wyFEXByJEjYbVazUuyHmPxRz6hpKQEmzdvhq7rWLNmDQoKCgy3MXDgQOem8l26dDEhSyIiIqL6\n586dO1i1ahXsdjt2797tcpzFYsG4ceOgKAokSUKDBg1MzNI3sPgjn1NWVobt27dD0zSkpaXhxo0b\nhtvo1auXsxDs3bs3N5UnIiIiekBlZSW2bdsGVVWh6zpKSkpcju3cuTMURcG8efN45VUtY/FHPq2y\nshJ79uxxrhyak5NjuI1OnTpBkiTIsoxBgwaxECQiIiKf9d1330FVVSxevBjff/+9y3GNGzfGrFmz\noCgKhg0bxs9TJmHxR/R3QggcOnQImqZB0zRDywvf17p1ayQmJkKWZYwYMYLLDBMREVG9l5+fjxUr\nVkBVVezfv9/lOKvViokTJ0JRFMTHxyMkJMTELAlg8Uf0WEIIHD9+3Lmp/DfffGO4jWbNmiEhIQGy\nLGPs2LEIDAw0IVMiIiIi96uoqMDmzZuhqirS09MNrbDeo0cPKIqCpKQktGzZ0sQs6WEs/ohccPr0\naWchePDgQcPxTZo0QVxcHCRJwqRJk/jNFhEREXml48ePQ1VVLFmyBNeuXXM5Ljw8HHPmzIGiKBg4\ncCAv66wjLP6IDLp06RLS0tKgaRp27dpl+HUVGhqKqVOnQpZlTJ06lRuSEhERkUfLzc3F8uXLoaoq\nDh8+7HKcn58fpk6dCkVREBsbi6CgIBOzJFew+CN6DtevX0d6ejo0TcO2bdtQUVFhKD4wMBATJ06E\nJEmYPn06mjZtalKmRERERK4rLy/H+vXroaoq1q5di/Lycpdj+/TpA5vNhjlz5iAqKsrELMkoFn9E\ntSQ/Px8ZGRnQdR2bNm3CvXv3DMX7+flhzJgxkGUZCQkJaNGihUmZEhERET3ekSNHYLfbsWzZMty8\nedPluGbNmmHu3LlQFAX9+vUzMUN6HnVe/OXk5GD+/PnYsmULhBCIiYnBokWL0KZNm6fGHTx4EJ9/\n/jl27dqFy5cvIzIyEiNHjsRHH32E9u3bP5oMiz9yo7t372LDhg3QdR1r167F3bt3DcVbLBYMHz4c\nkiRBkqTHvqaJiIiIasP169exdOlSqKqKY8eOuRwXEBCAuLg4KIqCKVOmICAgwMQsqTbUafFXXFyM\nvn37IiQkBB999BEA4IMPPkBxcTGOHTuG0NDQJ8b++Mc/xp49ezB37lz07t0bly9fxi9+8QvcuHED\nR44cQevWrasnw+KP6si9e/eQmZkJXdeRnp6O/Px8w20MGDDAual8t27dTMiSiIiIfElpaSkyMjKg\nqio2bNiAyspKl2NffPFF2Gw2vPLKK4iMjDQxS6ptdVr8/e53v8O7776L7OxsREdHAwAuXLiAzp07\n49e//jXmz5//xNibN2+iWbNm1Z67dOkSOnTogA8++AA/+9nPqifD4o88QHl5OXbs2AFN05Camorr\n168bbqNHjx7OTeX79u3L1bKIiIjIJUIIHDx4EKqqYvny5Ya+kG7evDnmzZsHRVHQs2dPE7MkM9Vp\n8Td+/HiUlZVh165d1Z4fM2YMAGD79u2GT9q8eXPExcXhL3/5S/VkWPyRh6msrMS+ffucW0hcunTJ\ncBvR0dHOS0OHDBkCq9VqQqZERETkzS5fvowlS5ZAVVWcPHnS5bigoCDEx8fDZrNhwoQJ8Pf3NzFL\ncoc6Lf6aN2+OxMRE/OlPf6r2/A9/+EOsXr0aN27cMHTCkydPomfPnvjv//5v/Ou//mv1ZFj8kQcT\nQuCrr76CpmnQNA3Z2dmG22jZsiUSExMhyzJGjhzJN2giIiIfVlJSgrS0NKiqiszMTDgcDpdjhw4d\nCpvNhpkzZyI8PNzELMnd6rT4CwoKwrvvvouPP/642vMffPABPvnkE0NLylZUVGD8+PH47rvv8N13\n36Fx48bVk2HxR15CCIFvv/3WOSN49OhRw21ERkYiPj4ekiRh/Pjx3FeHiIjIBwghsHfvXqiqihUr\nVuDOnTsux7Zu3RrJyclITk5G165dTcyS6pKZNZFbpx3+5V/+Bfv378e6deseKfyIvInFYkHPnj3R\ns2dPLFiwAGfPnoWu69B1Hfv373epjdzcXPz1r3/FX//6V4SFhSE2NhayLGPy5MlPXUiJiIiIvM+l\nS5eQkpKClJQUnD592uW4kJAQyLIMRVEwduxY+Pn5mZgl1XfPLP4AJnX+AAAgAElEQVTCw8Mfe6Np\nXl4eIiIiXD7R+++/j7/85S9ISUlBTEzME49buHCh8/GYMWOc9xYSebKOHTvixz/+MX784x/j+++/\nR1paGjRNw86dO126hOPOnTtYtmwZli1bhpCQEEyZMgWSJCE2NpZflBAREXmpoqIiaJoGVVWRlZVl\naDZn5MiRsNlsmDFjBsLCwkzMkura9u3ba7SOSk0814IvFosFWVlZzzzJL3/5SyxYsACffvopfvjD\nHz45GV72SfXMzZs3kZ6eDl3XsWXLFkOXSQNVe/PExMRAlmVMnz79kdVziYiIyLM4HA7s2rULdrsd\nq1evNrSPcPv27aEoCpKTk52r7JPvqfOtHt577z1kZ2ejQ4cOAKq2eujSpQs++eSTp271AAC///3v\n8c477+Djjz/G+++///RkWPxRPVZQUIB169ZB0zRs3LgRJSUlhuKtVitGjx4NWZaRkJCAVq1amZQp\nERERGXX27FnnZZ0XLlxwOa5BgwZ4+eWXYbPZMHLkSK4KTp63yfuCBQtQVFRUbZP3ixcvomPHjvjp\nT3+KBQsWAAC++OILzJkzB5MnT8ZPf/rTap1o3LgxunfvXj0ZFn/kI4qKirBx40bouo6MjAwUFhYa\nbmPYsGHOLST47SAREZH73blzB6tXr4bdbn/kKrmnsVgsGDt2LGw2GyRJQoMGDUzMkrxNnRZ/AJCT\nk4P58+cjMzMTQgjExMRg0aJFaNu2rfOYCxcuIDo6GgsXLsSHH34IAPjBD36AlJSUxyY/ZswYbNu2\nrXoyLP7IB5WWlmLr1q3QNA3p6em4deuW4Tb69esHWZYhSRJ69OhhQpZEREQEVO0BnJWVBbvdDl3X\nDV3J06lTJyiKgnnz5qFdu3YmZknerM6LP3dh8Ue+rqKiAjt37nSuHHr16lXDbXTr1g2SJEGWZfTv\n3x8Wi8WETImIiHxLdnY2VFVFSkoKvv/+e5fjwsLCMGvWLNhsNgwbNoy/l+mZWPwR+SCHw4Evv/zS\nuam8kfsH7mvfvr3z0tBhw4bxPgIiIiIDCgoKsGLFCtjtdpe3cgKq7tOfMGECbDYb4uPjERISYmKW\nVN+w+CPycUIIHDlyxLmp/MmTJw230bx5cyQmJkKWZYwaNQoBAQEmZEpEROTdKioqkJmZCbvdjvT0\ndJSWlroc2717dyiKgqSkJC7MRjXG4o+Iqjl58qTz0tCvvvrKcHxERATi4+MhSRImTJiAoKAgE7Ik\nIiLyHsePH4eqqliyZAmuXbvmclx4eDhmz54Nm82GgQMH8rJOem4s/ojoic6fP+8sBPfu3Ws4vlGj\nRpg2bRpkWcbkyZPRsGFDE7IkIiLyPLdu3cLy5ctht9tx+PBhl+P8/PwwZcoUKIqCuLg4folKtYrF\nHxG55MqVK0hLS4Ou69i+fTsqKysNxQcHB2Py5MmQJAlxcXFo0qSJSZkSERHVjfLycmzYsAF2ux1r\n165FeXm5y7G9e/eGzWbD3LlzERUVZWKW5MtY/BGRYbm5ucjIyICmacjMzERZWZmheH9/f4wfPx6y\nLCM+Ph4vvPCCSZkSERGZ78iRI7Db7Vi2bBlu3rzpclxkZCTmzp0LRVHQr18/XtZJpmPxR0TP5c6d\nO1i3bh00TcOGDRtQXFxsKN5qtWLkyJHOlUNbt25tUqZERES15/r161i2bBnsdjuOHTvmclxAQABi\nY2Nhs9kwZcoULpJGbsXij4hqTXFxMTZt2gRd15GRkYHbt28bbmPw4MHOTeU7depkQpZEREQ1U1pa\nirVr18Jut2PDhg2GboF48cUXoSgKZs+ejcjISBOzJHoyFn9EZIqysjJs27YNmqYhLS0Nubm5htvo\n06ePc1P5nj178nIYIiJyOyEEDh06BFVVsXz5cuTl5bkc27x5cyQlJUFRFPTq1cvELIlcw+KPiExX\nUVGB3bt3O1cOvXz5suE2Onfu7JwR5HLXRERktitXrmDJkiWw2+2G9sANCgpCfHw8FEXBxIkT4e/v\nb2KWRMaw+CMit3I4HDh48CA0TYOmaTh37pzhNtq0aeOcERw+fDj8/PxMyJSIiHxNSUkJ0tPToaoq\nNm/eDIfD4XLs0KFDoSgKZs2ahfDwcBOzJKo5Fn9EVGeEEDh27Bh0XYemaThx4oThNqKiopCQkABZ\nljFmzBjeOE9ERIYIIbBv3z6oqooVK1YYul+9devWmDdvHhRFQdeuXU3Mkqh2sPgjIo/x3XffOS8N\nPXTokOH48PBwTJ8+HZIkYcKECQgJCTEhSyIiqg8uXbqExYsXQ1VVnD592uW4kJAQSJIERVEwbtw4\nXn1CXoXFHxF5pIsXLyI1NRWapmHPnj2G//02aNAA06ZNgyRJmDp1Kho1amRSpkRE5C2Kioqg6zpU\nVcW2bdsM/W4ZOXIkFEXByy+/jLCwMBOzJDIPiz8i8njXrl1DWloadF3Htm3bDC2tDVTdfD9p0iRI\nkoTp06fzXgwiIh/icDiwa9cuqKqKVatW4e7duy7HtmvXDoqiIDk5GR07djQxSyL3YPFHRF4lLy8P\nGRkZ0DQNmzdvRmlpqaF4f39/jB07FrIsIz4+Hs2bNzcpUyIiqkvnzp1DSkoKVFXFhQsXXI5r0KAB\nXn75ZSiKglGjRsFqtZqXJJGbsfgjIq9VWFiI9evXQ9d1rFu3DkVFRYbiLRYLXnrpJecWEm3btjUp\nUyIicofCwkKsWrUKqqpi586dhmLHjRsHRVEgSRIaNmxoUoZEdYvFHxHVCyUlJcjMzISmaVizZg0K\nCgoMtzFw4EBnIdilSxcTsiQiotpWWVmJrKwsqKoKTdNQUlLicmzHjh1hs9kwb948tGvXzsQsiTwD\niz8iqnfKy8uRlZUFXdeRmpqKGzduGG6jV69ezr0Ee/fuzU3liYg8THZ2NlRVxeLFi5GTk+NyXFhY\nGGbNmgVFUTB8+HC+v5NPYfFHRPVaZWUl9u7dC03ToOu6oQ8I93Xq1AmSJEGSJAwaNIj3fxAR1ZGC\nggKsWLECqqpi3759LsdZrVZMmDABiqIgISGBWwGRz2LxR0Q+QwiBQ4cOQdM0aJqGM2fOGG6jdevW\nSExMhCzLGDFiBPd3IiIyWUVFBTIzM6GqKtLS0gwt9NW9e3coioKkpCS0atXKxCyJvAOLPyLySUII\nHD9+HLquQ9M0fPPNN4bbaNasGRISEiBJEsaNG4fAwEATMiUi8k0nTpyAqqpYsmQJrl696nJceHg4\nZs+eDUVRMGjQIF7WSfQAFn9ERABOnz4NXdeh6zoOHDhgOL5x48aIi4uDLMuYOHEiQkNDTciSiKh+\nu3XrFpYvXw5VVXHo0CGX4/z8/DBlyhQoioK4uDgEBQWZmCWR92LxR0T0kJycHKSmpkLTNOzatcvw\ne0doaCimTp0KSZIwbdo0hIWFmZQpEZH3Ky8vx4YNG6CqKjIyMlBeXu5ybO/evWGz2TBnzhzu20rk\nAhZ/RERPcf36daSnp0PXdWzduhUVFRWG4gMDAzFhwgTIsozp06ejadOmJmVKRORdjh49CrvdjqVL\nl+LmzZsux0VGRmLu3LlQFAX9+vXjZZ1EBrD4IyJyUX5+PtauXQtN07Bp0ybcu3fPULyfnx/GjBkD\nSZKQmJiIFi1amJQpEZFnunHjBpYuXQpVVXH06FGX4/z9/REbGwubzYYpU6bwHmuiGmLxR0RUA3fv\n3sWGDRug6zrWrl2Lu3fvGoq3WCwYNmyYc1P59u3bm5MoEVEdKy0txbp162C327FhwwZDV1AMGDAA\nNpsNs2fPRmRkpIlZEvkGFn9ERM/p3r172LJlCzRNQ3p6OvLz8w23MWDAAOem8t26dTMhSyIi97m/\ntY6qqli+fDny8vJcjo2KikJSUhIURUHv3r1NzJLI97D4IyKqReXl5dixYwd0XUdqaiquXbtmuI3u\n3btDlmXIsoy+ffvyfhYi8hpXrlzBkiVLoKoqvv32W5fjAgMDER8fD5vNhokTJ8Lf39/ELIl8F4s/\nIiKTOBwO7Nu3D5qmQdd1XLx40XAbHTp0cM4IDhkyBFar1YRMiYhqrqSkBOnp6VBVFZs3b4bD4XA5\ndsiQIVAUBbNmzUJERISJWRIRwOKPiMgthBD46quvnJvKf/fdd4bbaNmyJRITEyFJEkaNGsVvxomo\nzgghsH//ftjtdqxYsQK3b992ObZVq1aYN28eFEXhZe5Ebsbij4jIzYQQOHnypHNG8MiRI4bbiIyM\nRHx8PCRJwvjx47mhMRG5xaVLl7B48WKoqorTp0+7HBcSEoLExETYbDaMGzcOfn5+JmZJRE/C4o+I\nqI6dPXvWuan8/v37DceHhYUhNjYWsixj0qRJaNCggQlZEpGvKioqQmpqKux2O7Zt22bo89SIESNg\ns9nw8ssvIywszMQsicgVLP6IiDzI5cuXkZqaCl3XsWPHDkP3zgBV365PmTIFkiQhNjYWjRs3NilT\nIqrPHA4Hdu/eDbvdjlWrVhnazqZdu3ZQFAXJycno2LGjiVkSkVEs/oiIPNTNmzexZs0aaJqGLVu2\noLy83FB8QEAAYmJiIMsypk+fjmbNmpmUKRHVF+fPn0dKSgpUVcX58+ddjmvQoAFmzJgBm82GUaNG\ncXEqIg/F4o+IyAvcvn0ba9euha7r2LBhA0pKSgzFW61WjB49GpIkITExEa1atTIpUyLyNoWFhVi9\nejXsdjt27txpKHbs2LGw2WyQJAkNGzY0KUMiqi0s/oiIvExRURE2bdoETdOwdu1a3Llzx3AbQ4cO\nhSzLkCQJ0dHRJmRJRJ7M4XAgKysLdrsduq6juLjY5diOHTtCURTMmzcP7du3Ny9JIqp1LP6IiLxY\naWkptm7dCl3XkZaWhlu3bhluo1+/fs69BLt3785N5YnqsdOnT0NVVaSkpCAnJ8fluLCwMMycORM2\nmw3Dhw/n+wSRl2LxR0RUT1RUVGDnzp3QdR26ruPq1auG2+jatatzRnDAgAH8gEdUDxQUFGDlypWw\n2+3Yt2+fy3EWiwUTJkyAoihISEhAaGioiVkSkTuw+CMiqoccDge+/PJL56byRhZuuK9du3bOGcFh\nw4ZxAQciL1JZWYnMzEyoqorU1FSUlpa6HNutWzcoioKkpCS0bt3axCyJyN1Y/BER1XNCCBw9ehSa\npkHTNJw8edJwG82bN0diYiIkScLo0aMREBBgQqZE9Ly+/fZbqKqKxYsXG5r9b9KkCWbPng1FUTB4\n8GDO+hPVUyz+iIh8zMmTJ52Xhn711VeG4yMiIjB9+nTIsoyYmBgEBwebkCURuerWrVv44osvYLfb\ncejQIZfj/Pz8MHnyZCiKgri4OP5bJvIBLP6IiHzY+fPnnZvK79271/D7ZKNGjTBt2jRIkoQpU6Zw\nqXciNykvL8fGjRtht9uRkZFhaB/QXr16wWazYe7cuWjevLmJWRKRp2HxR0REAICrV686C8Ht27ej\nsrLSUHxwcDAmTZoEWZYRGxuL8PBwkzIl8l1Hjx6FqqpYunQpbty44XJc06ZNMXfuXCiKgv79+/Oy\nTiIf5VPF3+4Xdj/wRPW/q37wEx7XNO7hwx6Me0r7tRFnet+eFmdy354ax76ZE8fX8jPbqC99yyvO\nw7az27ApexN2X9iN8krXZxUAwN/qj2Hth2FS10mY2G0iIhtE1jxHM+Lq82u5tvtmAayhVvg18INf\nw8f8NPCDNZCLAZnpxo0bWLZsGex2O44ePepynL+/P2JjY6EoCqZOnYrAwEATsyQib+BTxV/ptaqV\nrqql9XCG4gmPaxj3yBA8pf1ajzO5b0+NM7tvT4tj30yJ42v5GTnWNM4L+lZ4rxDbTm3DphObkPVd\nFkrKS2CE1WLFwLYDMbnHZEzqPgktG7es36/l+tY3B1BZUonKu1U/jiKH83Hl3UpUFFbAYrU8tih8\nbLHY0A/WBtYnFpIPPrZYH65WfUdZWRnWrl0LVVWxfv16VFRUuBw7YMAAKIqC2bNno1mzZiZmSUTe\nxqeKPw9Kh4jIKxUXF2Pz5s3QNA0ZGRm4ffu24TYGDx7s3EuwU6dOJmRJ7iSEgCgTVcVgUWW1wtD5\nY/T5u5VwFDtgDbE+u5h8wvNPKjCtQVaPveRRCIHDhw9DVVUsW7YMeXl5LsdGRUUhKSkJiqKgd+/e\nJmZJRN6szou/nJwczJ8/H1u2bIEQAjExMVi0aBHatGnzzBP85Cc/waFDh3D48GHk5+fjb3/7GxRF\neXwyLP6IiGpVWVkZtm3bBl3XkZaWhps3bxpuo0+fPpAkCZIkoVevXh77oZzcTzgEHCUOQwWjK0Wm\nqBCGC0lXikyrf80vfb169SqWLFkCVVVx4sQJl+MCAwMRHx8PRVEwadIk+Pv71zgHIvINdVr8FRcX\no2/fvggJCcFHH30EAPjggw9QXFyMY8eOITQ09KknCAsLQ//+/dGhQwekpKTAbrcjOTn58cmw+CMi\nMk1lZSV2794NTdOg6zouX75suI3OnTs7N5UfOHAgC0EyhaPcUa0YfPgy1prOVloCLIYKyfKgcmzJ\n3oJV+1Yh62gWHA6Hy30YMmQIFEXBrFmzEBERYeJoEVF9U6fF3+9+9zu8++67yM7ORnR0NADgwoUL\n6Ny5M379619j/vz5Lp3o7Nmz6Ny5M4s/IiIP4HA4cPDgQei6Dk3TcPbsWcNttGnTxlkIDh8+HH5+\nfiZkSlQ7hBBw3HM8sTC8X2BWFFbg0KlDWH1oNdadXIc7ZXdcPkczv2aY2nQq4lrFodMLnWp8Oaxf\nQy7QQ+TL6rT4Gz9+PMrKyrBr165qz48ZMwYAsH37dpdOdObMGXTp0oXFHxGRhxFC4JtvvnHOCB4/\nftxwG1FRUUhISIAkSRg7diwCAgJMyJTIPDk5OVi8eDFUVUV2drbLccHBwUiIS8DcxLkY3X80UIJn\nFpjPnK0srNrCxdBCPK4UmQ38YPHjbD2Rp6vT4q958+ZITEzEn/70p2rP//CHP8Tq1atd3r+GxR8R\nkXfIzs52zggeOnTIcHyTJk0wffp0yLKMCRMmICQkxIQsiZ5fcXExdF2HqqrYunWroc8gI0aMgKIo\nePnll9G4ceNaz81R5qj5QjxPKjKLK2ENcmGBHldXe71/bLDnLtBD5I3MrImeeddxfn7+YzcBjoiI\nQH5+vilJERFR3enSpQvef/99vP/++7h48SJSU1OhaRr27Nnj0i+jgoICpKSkICUlBQ0aNMC0adMg\nSRKmTp2KRo0auaEHRE8mhMCuXbugqipWrVqFwsJCl2Pbtm0LRVGQnJxs+iq41kArrBFWBETU3iy6\nEMYW6Cm7WubSLKajzFGrq70696YM4KWvRLWNS04REdETtWvXDu+88w7eeecdXLt2Denp6dA0DVlZ\nWS7taVZUVISVK1di5cqVCAoKwsSJEyHLMuLi4rgIBrnV+fPnnV9KnDt3zuW4Bg0aYMaMGVAUBaNH\nj4bV6r0FicVigV+oH/xC/YAXaq9dR4Wj+mzjM2Yry26UubZAj5+xvSldKjJDfXtvSqJnFn/h4eGP\nneHLy8sz5Rf3woULnY/HjBnjvLeQiIjqVvPmzfHGG2/gjTfeQF5eHjIyMqDrOjZt2oTS0tJnxpeW\nliIjIwMZGRnw9/fH2LFjIUkSEhIS0Lx5czf0gHxNYWEhVq9eDVVVsWPHDkOxY8aMgc1mgyzLaNiw\noUkZ1g9Wfyusja3wb1x7cwpCCDhKHS6v9FqeW457F+49c5sRR7ED1lBrjQvJJz1vCbTw0leqse3b\nt7u8jsrzeq4FXywWC7Kyslw6Ee/5IyKqnwoLC7F+/Xrouo5169ahqKjIULzFYsFLL70EWZaRmJiI\ndu3amZQp+QKHw4GsrCyoqgpN01BcXOxybHR0NGw2G+bNm4f27dublyTVGeEQqCx28R5JA/tVwgFD\n90m6UnxaG1ifa29K8l51vtXDe++9h+zsbHTo0AFA1VYPXbp0wSeffOLyVg8s/oiI6r+SkhJkZmZC\n13WsWbOmRveGDxw40LmFRJcuXUzIkuqj06dPQ1VVLF68GJcuXXI5rlGjRpg5cyZsNhteeuklzt5Q\njTjK/r6NSE0W4nnKZbLWwOoFpeEC8zF/Zw3hAj2ezuM2eV+wYAGKioqqbfJ+8eJFdOzYET/96U+x\nYMECZ/yOHTtw8+ZNXLt2DW+//TbeeustjB49GgAwY8aM6smw+CMiqjfKy8uxfft2aJqG1NRUl1eH\nflDPnj0hyzIkSUKfPn34gYWqKSgowMqVK6GqKvbu3etynMViQUxMDGw2GxISEpyfZYg8iXNvSgMF\noyvbiThKHVUFYS2t9uqcqeTelLWmTos/oGrvm/nz5yMzMxNCCMTExGDRokVo27at85gLFy4gOjoa\nCxcuxIcffuh8fuzYsc7r7B/siMViQWVlZfVkWPwREdVLlZWV2Lt3r3MvwZycHMNtdOzY0TkjOGjQ\nIK9eeINqrrKyEpmZmVBVFWlpabh3757LsV27doXNZkNSUhJat25tYpZEnktUiurFYy1tJwLL4/em\nrOlqr/f/64sL9NR58ecuLP6IiOo/IQQOHTrk3Evw9OnThtto1aoVJEmCJEkYOXIk/Pz8TMiUPMm3\n334LVVWxZMkSXLlyxeW4Jk2aYPbs2VAUBYMHD+bsMZEJhBAQZaJGheRTZzGLK2ENdmFvSoOzmNYg\nz770lcUfERHVS0IInDhxwlkIHjt2zHAbzZo1Q3x8PGRZxrhx4xAYGGhCplQX8vLysHz5cqiqioMH\nD7oc5+fnh0mTJsFmsyEuLg7BwcEmZklEZhGOx+xNWYNC8uHnRYWo1dVe7xeYtbVAD4s/IiLyCWfO\nnHEWggcOHDAc37hxY8TFxUGSJEyaNIn3cnmh8vJybNq0CXa7HRkZGSgrK3M5tlevXrDZbJg7dy63\nDyGiJ3KUVy3Q48o9kkZmMS0BBvamfErx2ahvIxZ/RETkW3JycpCamgpd17Fr1y44HA5D8aGhoZgy\nZQpkWca0adMQFhZmUqZUG44dOwa73Y6lS5caWhyoadOmmDNnDmw2G/r37+/Rl3IRUf11f2/K2ljp\ndfA3g1n8ERGR77px4wbS09OhaRq2bt2KiooKQ/GBgYGYMGECZFnG9OnT0bRpU5MyJSNu3ryJZcuW\nwW6348iRIy7H+fv7Y9q0abDZbJg6dSov9SWieoWXfRIREf1dQUEBMjIyoOs6Nm7caGi1R6DqfrAx\nY8ZAkiQkJCSgZcuWJmVKj1NWVoZ169bBbrdj/fr1hgr5/v37w2azYfbs2WjWrJmJWRIR1R0Wf0RE\nRI9x9+5dbNy4EZqmYe3atbh7966heIvFgmHDhjlXDu3QoYNJmfo2IQS++uor2O12LF++HLdu3XI5\nNioqCnPnzoWiKOjTp4+JWRIReQYWf0RERM9w7949bNmyBbquIz09HXl5eYbb6N+/P2RZhizL6Nat\nmwlZ+parV69iyZIlUFUVJ06ccDkuMDAQ06dPh81mw6RJk+Dv729ilkREnoXFHxERkQHl5eXYuXMn\nNE1Damoqrl27ZriN7t27Q5ZlSJKEfv36cSERF927dw/p6elQVRWbNm0ytFDP4MGDoSgKXnnlFURE\nRJiYJRGR52LxR0REVEMOhwP79u1zbiFx8eJFw2106NABkiRBlmUMGTIEVmvt7OVUXwgh8OWXX8Ju\nt2PFihUoKChwObZly5aYN28eFEVB9+7dTcySiMg7sPgjIiKqBUIIfP3119A0DZqm4bvvvjPcRsuW\nLZGYmAhJkjBq1CifviQxJycHixcvhqqqyM7OdjkuODgYiYmJUBQFMTEx8PPzMzFLIiLvwuKPiIjI\nBN9++61zRtDIVgP3NW3aFPHx8ZBlGePHj0dQUJAJWXqW4uJipKamwm63Y+vWrYZ+b7/00ktQFAUz\nZ85E48aNTcySiMh7sfgjIiIy2blz56DrOnRdx759+wzHh4WFITY2FpIkYfLkyWjQoIEJWdYNIQR2\n794Nu92OVatWobCw0OXYtm3bIjk5GcnJyejcubOJWRIR1Q8s/oiIiNzo8uXLSEtLg6Zp2LFjh6FF\nSwAgJCQEkydPhizLiI2N9dpZrgsXLiAlJQWqquLcuXMux4WGhmLGjBmw2WwYPXo075EkIjKAxR8R\nEVEduXnzJtasWQNd15GZmYny8nJD8QEBAYiJiYEkSYiPj/f4zcnv3r2L1atXw263Y8eOHYZix4wZ\nA0VRIMsyGjVqZFKGRET1G4s/IiIiD3D79m2sW7cOmqZhw4YNKCkpMRRvtVoxatQoyLKMxMREtGrV\nyqRMjXE4HNi+fTtUVcXq1atRXFzscmx0dDQURUFycjLat29vXpJERD6CxR8REZGHKS4uxsaNG6Fp\nGtauXYs7d+4YbmPo0KHOLSSio6NNyPLpzpw5A1VVkZKSgkuXLrkc16hRI8ycOROKomDEiBHcA5GI\nqBax+CMiIvJgpaWl2Lp1K3RdR1paGm7dumW4jb59+zo3le/Ro4dpBdXt27excuVKqKqKPXv2uBxn\nsVgQExMDRVGQmJiI0NBQU/IjIvJ1LP6IiIi8REVFBXbt2gVN05CamoorV64YbqNr167OGcEBAwY8\ndyFYWVmJLVu2QFVVpKam4t69e4ZyURQFSUlJaNOmzXPlQUREz8bij4iIqIaEEBAAHH//75MeOx48\ntpYeVzgcOHrgALasWYMta9bg8oULhvOPatMGI2JjMSI2Ft0GD4bFaoUQouo8D5zLAsBqscCKqt+n\nVgA52dnI/OILbFm5ErlXr7p8zrAmTTBFlpGYlIT+gwbBz2qF9e/tWwDn42rPPfBn60P5PHwMLxMl\nInoyFn9E9NzEMz741tZjM9s2nAtq/8N8TR8/+EG9rh/X9f8Xd75ePOo3ihDA2bPAzp1VPxcvGm8j\nIgIYMQIYNQro2xfw93/0mDt3gG3bgE2bgFOnXG/bagUGDQImTQJeegkIDDSenwGPKxAfLFwfKRwN\nHlOTovRJxzzunDXN/XHnrGnutZmXJ4ypK3nxiwPyBSz+aoK/l1wAAA+mSURBVJnzQxA/qOHEnj3o\nNny4x3xQ84UP9kWHDiH4xRfd/hrxaUeOAP361XUWvoVj/myXLv2jEDx92nh8WBgwf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mREREUK9ePfz8/Bg6dCiurq5ERESo7WpSKpUoFIo8wjooKIjFixezY8cOevbs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\ns9D/AeYeXdDnxbdOAAAAAElFTkSuQmCC\n", + "text": [ + "" + ] + } + ], + "prompt_number": 208 + }, + { + "cell_type": "heading", + "level": 3, + "metadata": {}, + "source": [ + "Generic + BusTrain model" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+BusTrainFeatureIndices], cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+BusTrainFeatureIndices], cleanedResultVector, \"Generic + BusTrain\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic_bustrain.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Found 802 high confidence predictions out of 1462\n", + "Found 806 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 849 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 775 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 798 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.9, percentage auto classified 0.551526370541\n", + "for prob 0.9, scoring only on high confidence predictions 0.979724500288\n", + "for prob 0.9, scoring on all predictions 0.879430257371\n", + "Found 801 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 830 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 796 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 798 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 806 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.551661109504\n", + "for prob 0.95, scoring only on high confidence predictions 0.979616148206\n", + "for prob 0.95, scoring on all predictions 0.882987216184\n", + "Found 815 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 763 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 817 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 848 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 777 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.99, percentage auto classified 0.550160254159\n", + "for prob 0.99, scoring only on high confidence predictions 0.980492537775\n", + "for prob 0.99, scoring on all predictions 0.879295237507\n", + "[0.55152637054057574, 0.55166110950373182, 0.55016025415944525]\n", + "[0.79850561909002704, 0.79650899244536766, 0.7933711168569999]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[0.53220508451746174, 0.5114987172465304, 0.56132105513893671]\n", + "[0.044767199348490813, 0.074668724766346686, 0.051811100180147951]\n", + "[0.19297924297924302, 0.14309970753382456, 0.16840308478239513]\n", + "[0.34201873331075883, 0.3574956356079711, 0.3332740855308553]\n", + "[0.33428566241401275, 0.10500000000000001, 0.3332740855308553]\n", + "[0.97972450028844693, 0.97961614820615917, 0.98049253777549217]\n", + "[0.8794302573710826, 0.88298721618440612, 0.87929523750668304]\n", + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + 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KykR1LK97QgghhJDmQGP+XkMpKSmitIqKCmRmZsLAwACWlpYAAFdXVwBPZiJ8Xs7OzuA4\nDvHx8Qrd8pRxdXWFTCYTusO9aPKumMpaA4uLi3H//n24ubmJZnRMTU0V5ZeP81NWR2fOnBEFWy4u\nLuA47rnrNDc3FwDg5+cn2qasnPIA7caNG6JtZ8+eVXoOeT0pGyPp5OQExhgSExNF2+RptcdAKqOt\nrY2uXbsiJycH165dqzevMk29V7XxPI/evXvjs88+E5ZIUNbFGHjSDXTmzJn45ZdfAAAHDhxoclnr\n09TXmaOjIxhjwgy2tSl7bRNCCCGEvCgU/L2GLl++jOjoaIW0yMhI3Lt3T2GiluDgYGhrayMsLAw5\nOTmi45SWliIzM7NR5zQ1NUVAQAAuX76MZcuWibbXDko++ugjqKioIDQ0VOm4tdu3bysd89dY8inz\nCwoKRNvatm0LiUSCjIwMPHz4UEgvLCzEZ599Jsrv7u6O9u3bY8+ePQpj3GpqajB//nxRflNTU4wZ\nMwaJiYlYu3ataHtdAdXT5GPknv6wf+rUKaXrvenq6qJLly5ITk4WAkfgSbdVZRPwAIChoSEYY0rr\nST6xyMKFCxW6qN66dQtff/011NTU8Pbbbzd4HdOmTUN1dTWmT5+Ox48fK2wrKysTjWOsran36tKl\nS0pbveXrW8pbma9du6Y0GH0634vi7++PDh06YMWKFUq/8Hjw4IFCuvw1umjRIoVurRcvXqy36ygh\nhBBCyPOibp+vIV9fX0ybNg2HDh2CnZ0dzpw5g7i4ONjY2ChMOGFiYoLt27dj/Pjx6NGjB4YOHQpb\nW1tUVFQgLy8PiYmJCAoKwvr16xt13vXr1+P8+fMIDw9HbGwsPDw88OjRI2RlZeHs2bPCYtbdu3fH\nd999h5CQENjZ2cHPzw9WVla4e/curl69ipSUFCxevBj29vbPdP3a2tpwcXFBUlISAgMDYWtrC57n\nERgYCEtLS0ybNg2rVq2Ck5MThg4dipKSEhw6dAienp6iIJjneWzYsAH+/v7o378/Jk6cCENDQxw5\ncgSqqqqwsLAQulzKbdiwAdnZ2ZgxYwaio6Ph4uICbW1tFBQU4NSpUygqKmpwzJ+rqyucnZ2xY8cO\n3Lp1C87Ozvjzzz9x4MABjBgxQuk6iLNnz8a//vUvuLm5YcyYMZDJZDh69CjeeOMNpUHHoEGDsGfP\nHowePRpDhgyBRCKBo6Mjhg0bBg8PD0ybNg0bNmxAjx494O/vj0ePHmHXrl0oLi7GV199pXRx+6dN\nnz4d8fHx2L9/P+zs7DBs2DBoaWnhzz//xNGjR5GamoqePXsK+Wu3QvI836R79euvv2Lu3LnCJC+G\nhobIycnBwYMHYWBggClTpgB40hI6evRo9O3bF/b29jA1NUVBQQH27dsHDQ0NhIaGNnhdT5e1Purq\n6ti9ezfeeust9OvXD76+vujatSuqq6uRn5+PxMRE9O/fH4cPHwYAeHl54d1338XWrVvRq1cvDB8+\nHGVlZdixYwcGDx4s6gZMCCGEEPLCNNsiEs+gMcVpYUV+qeRrsy1cuJBJpVLm7u7O2rRpw4yMjFhg\nYKBoLT+5ixcvsqCgIGE9OxMTE9anTx8WFhbGLl++rPT4dbl79y4LCwtjdnZ2TENDgxkbGzM3Nze2\nevVqUd6TJ0+ysWPHMnNzc6aurs7Mzc2Zm5sb+/LLL9n169eFfJs3b2Y8z4vWWquvTDk5OczPz48Z\nGBgwnucZz/MsMTGRMcbYo0eP2KJFi5itrS2TSCTM1taWLVy4kD169EjpeniMMfbbb78xNzc3pqmp\nydq2bcvee+89dufOHaatrc0cHR1F+SsqKtjSpUuZk5MTa9OmDdPW1mZ2dnbs7bffZnv37q2z/mq7\nffs2CwoKYhYWFkxLS4s5Ozuzn376iUml0jrvw/r165mdnR1TV1dn1tbWLCIigj1+/FjpdVVXV7NP\nP/2UWVlZMTU1NcbzvGidwKioKNanTx+mpaXFdHR02MCBAxtdfrmamhq2YcMG9sYbbwh14eDgwP79\n73+ze/fuCfk8PT1Fa+c15V5dunSJffzxx6x3797MyMiIaWpqss6dO7Np06ax/Px8Id9ff/3F5s2b\nx/r27cvatm3LJBIJs7GxYZMmTWJ//PGHwvnrevaUlZWx+tdbLCgoYCEhIaxTp05MQ0ODGRoasp49\ne7IZM2awM2fOKOStrq5mX375JbO2tmYaGhqsW7dubNOmTfXee/J6aM3vUYQQQl6M5nwv4f7/BC0C\nx3ENftvemDz/VFKpFN7e3oiIiFDaJZG8WLm5uejcuTPGjRundF1CQgh5Wmt+jyKEEPJiNOd7CY35\nI61eRUUFysvLFdKqqqowe/ZsAMDIkSNfRbEIIYQQQgh5oWjMH2n1Ll26BC8vL7z11luwtrbG3bt3\ncfz4ceTl5cHT0xMTJkx41UUkhBBCCCHkuVHwR1o9S0tLjB49GklJSTh06BAYY8LkOZ9++qnSdQ8J\nIYQQQgh53dCYP0IIIeQFofcoQgghz4vG/BFCCCGEEEIIeS4U/BFCCCGEEEJIK0DBHyGEEEIIIYS0\nAhT8EUIIIYQQQkgr0GDwd/36dYwZMwb6+vrQ09PD6NGjcf369UYdPC8vD2PGjIGBgQG0tbXh7e2N\njIyM5y40IYQQQgghhJCmqTf4q6yshLe3N3JycrBlyxZs3boVV65cgZeXFyorK+s98J07dzBgwABc\nvHgR33//PXbs2AHGGLy8vJCdnf1CL4IQQgghhBBCSP3qXecvKioKeXl5yMnJgY2NDQCgZ8+e6Ny5\nMzZt2oRZs2bVue+GDRvw999/IyUlBR07dgQAeHt7w8bGBgsWLMDOnTtf4GUQQgghhBBCCKlPvev8\nDRo0CI8ePUJycrJCuqenJwBAKpXWeeBhw4YhLy8PWVlZCuljxozBkSNHcP/+ffC8YsMjrfNHCCHk\ndUbvUYQQQp7XK1vnLysrC927dxeld+vWDRcvXqz3wCoqKlBTUxOla2ho4MGDB8jNzW1iUQkhhBBC\nCCGEPKt6g7+7d+/CwMBAlG5oaIi7d+/We2B7e3tcuXIFJSUlQppMJsPp06cBQCGdkH8iT09PUet2\nREQEeJ5HUlLSKyrV60cqlYLneSxcuPBVF0WBtbW10KW9tkuXLmHYsGFo27YteJ6Hk5MTACAoKAg8\nz6OgoKBZyqPseSOEEEIIqa3ZPilMnToVMpkMgYGB+PPPP1FYWIgZM2YgPz8fHMfRhxTyzPLz88Hz\nPIKDg191URrEcdyrLkKTtdRgq6XVJcdxojLV1NQgICAA8fHxGDVqFCIiIjBt2rQ68zdHmQghhBBC\n6lLvhC8GBgZKW/hKSkpgaGhY74E7duyI7du3Y/r06bC1tQUA9OnTB7NmzcLXX38Nc3NzpftFREQI\nv3t6egrjCwmRk3/ApQ+6zYvqt37Hjx8Xpf3555/IycnB1KlTsX79eoVty5YtQ1hYGCwsLF5WEQkh\nhBDyGpBKpfXOpfIi1Rv8OTg44MKFC6L0ixcvolu3bg0efNSoUQgICEBOTg7U1dXRsWNHTJs2DZaW\nlmjfvr3SfWoHf4QoIx8AS5MqNC+q3/op6/JZWFgIADA1NRVtMzMzg5mZWbOXixBCCCGvl6cbvJqz\n91W9fS9HjBiBU6dOIS8vT0jLz8/HiRMnMGLEiEadgOM4dOnSBR07dsTNmzexa9cuoRsUaZra3fGk\nUinc3d2ho6MDY2NjBAYG4tatW0r3O3v2LMaOHQtTU1NIJBLY2tris88+Q0VFRZ3HT0lJgY+PD/T0\n9BRaeUtLSxEeHg4HBwdoaWnByMgIffv2xcqVK0XnTUhIwNChQ2FkZARNTU04ODhg+fLlqKmpUci3\nefNm8DyPmJgYHDt2DP369YO2tjaMjY0RFBSkMD508+bNwrIjMTEx4Hle+KlvHF1mZiZ4nkdYWJhC\n+n/+8x/wPA9LS0uF9NLSUqiqqiIgIEBIy8nJwZw5c+Do6AhDQ0Noamqie/fuWLJkCaqrq+s8d2Oc\nPn0axsbGaNeunWiG3Kc9fvwYa9asweDBg9GuXTtoaGjAwsIC77zzDq5evSrKX99Ys6fHIEZERMDb\n2xvAk/94atdv7f3z8vIwefJkmJubQ0NDA9bW1pgxYwaKi4ubdN1Xr17F+++/D0tLS0gkElhYWGDI\nkCE4cOBAg/vu3bsX48ePh42NDbS0tGBoaIjBgwcjPj5eaf7du3fD3d0dJiYm0NTURPv27eHn54e4\nuDiFfHFxcfD19YW5uTkkEgnMzc3h7e0tWp7m6TF/1tbWwn/ctetuy5YtAOq+DzKZDFFRUXB1dYW2\ntjZ0dHTQv39/7N27V+l1ZGZm4s0334S2tjYMDQ0xduzYZhtHSAghhJB/lnpb/j744AOsXbsWI0eO\nxOLFiwEA4eHhsLS0xIcffijku3btGjp16oQFCxYgPDwcAFBdXY05c+bA09MTOjo6yMrKwrJly9C9\ne3fMnj27GS/pn+/kyZNYtmwZhg8fjpkzZyI9PR3btm1Damoq0tPTFYK1vXv3YsKECZBIJPD394eZ\nmRkyMjIQGRmJhIQEJCUliWZlTU1NxdKlS+Hj44Np06ahqKgIAHD79m24u7vj6tWrcHFxQWhoKKqq\nqvDHH38gMjJS4b6uXbsWM2bMQNu2bREQEAADAwMkJycjLCwMp0+fxp49e0TXFRsbi0OHDmHEiBEY\nMGAAEhMTsWXLFuTm5grLjTg5OWHmzJn49ttv4ejoCH9/f2F/KyurOuusV69eMDAwEDWpJyQkAABu\n3LiB3NxcdOrUCQCQnJwMmUwGLy8vIe8vv/yCzZs3Y9CgQfD19UVVVRWkUinCw8Nx5syZOj+sNyQu\nLg4BAQGwsLDAsWPH6r0OALhz5w5mz54NDw8PjBw5Enp6esjOzsauXbtw9OhRZGRkwNraWmGfxnbh\n9PLywrVr1xATEyP6FkpPTw/AkwlN3N3dcffuXQQEBKBLly5IT0/H2rVrcejQIZw6dQomJiYNnisp\nKQl+fn548OABhg0bBgcHBxQVFSEtLQ3R0dEYPnx4vft//vnnkEgk8PLygpmZGW7evIl9+/bhzTff\nxO7duxUC93Xr1iE0NBS2traYOHEidHR0cOPGDZw4cQLHjh2Dj48PAODgwYMYMWIELCws4O/vDyMj\nIxQWFuLMmTPYs2cPxo8fX2e9zpo1C5mZmaK6c3R0VJofeNK6OnHiROzevRsODg7CONaDBw9i9OjR\nWL16NWbMmCHkP3/+PNzd3VFVVYWxY8fC2tpa+CJI2eRchBBCCCEKWAMKCgrY6NGjma6uLtPR0WEB\nAQHs2rVrCnny8vIYx3Fs4cKFQlp1dTUbNmwYMzU1ZRoaGszW1paFh4ezBw8e1HmuRhSnUXkU8kfg\nlf68SAkJCYzjOMZxHIuOjlbYFh4ezjiOY6GhoUJaUVER09HRYZ06dWKFhYUK+VesWME4jmNff/21\n0uNv3bpVdP6AgADGcRxbsmSJaNvNmzeF3y9cuMBUVVWZm5sbKysrU8gXEhLCOI5jP//8s5AWHR3N\nOI5j6urq7MSJE0J6TU0N8/LyYhzHsVOnTgnp+fn5jOM4FhwcXFdVKTVy5EimpqbG7t+/L6RZWFiw\nQYMGMY7jWFRUlJA+e/ZsxnEcO3funMI1Pn78WHTcDz74gHEcx1JSUhTSPTw8GM/zCmkLFixgHMex\nxMRExhhju3btYurq6qx3797s77//btR1VFVVie4nY4wlJiYyVVVVNmXKFIX0yZMnM47jRK9bZeVh\n7H/PQe3X89PXpewZmT9/fqPvy4MHD5iFhQVTU1NTOLfcjRs3GixPfn6+aL/bt2+z9u3bM1tbW4V0\nJycn1r59e6X//9y5c0f4PSAggEkkElZUVFRvPsYYs7KyYh07dlRIq6/ulN2HjRs3Mo7jWEhICJPJ\nZEJ6RUUFc3V1ZRoaGgqvLXd3d8ZxHNu7d6/SYz/9vJGXr6nvUYQQQsjTmvO9pMEpNzt06ICff/4Z\npaWlKCsrwy+//CLqImdtbQ2ZTIb58+cLaSoqKjhw4ABu3bqFhw8f4sqVK1i0aBEkEsmLjV5bIXt7\newQFBSmkzZs3D/r6+ti2bZuQtmXLFpSXlyMyMlI01uiTTz6BiYkJduzYITq+s7MzJk2apJB269Yt\n7Nu3D/Ykjr1lAAAgAElEQVT29qKukwAUJvDZtGkTampqsGbNGujo6CjkW7JkCTiOU3ret99+G25u\nbsLfPM9j8uTJAIAzZ84I6ewZx6J5eXmhurpaaEXMyclBYWEhJk+eDGtra6EVEHjSBdbQ0BA9e/ZU\nuEZVVXFj+dSpUwGgzu6GyjDGsGnTJkyYMAH9+vWDVCptVGsZAKirqysdOzZw4EB07dpV1I3xRbp2\n7RqSkpLg6OgoekbCwsJgbGyMnTt34vHjx/UeZ//+/SgsLERQUBAGDhwo2t6YSVGUtZDKW5pzc3MV\nukJyHAc1NTWlsww/PXmVqqqq0vvc0CRXz2LdunXQ19fHqlWrFFoFtbS08MUXX+DRo0f45ZdfADyp\n+5SUFDg7Oyu0eAPAl19+STMoE0IIIaRB9Xb7JC1T//79RWlaWlpwdHSEVCpFQUEBLC0tkZaWBgBI\nSUlROnGPqqoqsrOzRenOzs6iNHnw5e3t3WAXwrS0NHAchwMHDuDgwYOi7RKJROl5+/TpI0pr164d\nAODevXv1nrMx5N3wpFIp3nrrLaELqLe3N6RSKY4ePQrgyXi/zMxM0bhWmUyGH374AZs3b0ZWVhbu\n37+vEIjKJ/tojJUrV+LgwYMYOXIkdu7cCXV19SZdS0ZGBr766iukpqaiqKhIIdjS0NBo0rGa4ty5\ncwCgNGCTSCRwcXHB4cOHkZOTAwcHhzqPk56eDgDw9fV95rLcunULy5Ytw5EjR/DXX3/h4cOHCtsL\nCwuFL6rGjx+PefPmoXv37pgwYQI8PT3Rt29faGlpKewzYcIE7Nu3D927d8fEiRPh7e2Nfv36CV1e\nX6TKykpcuHABlpaWQrf62uTdrS9fvgzgSZdPABgwYIAob4cOHWBpaYlr16698HISQggh5J+Dgr/X\nUNu2bZWmy2cYLC0tBQBhopQ1a9bUeSxlgZyymQrlx2xMi0xJSQkYY/jyyy/rPGdlZaUoXVdXV5Qm\nb4F5epKYZ9GjRw8YGBgILXxSqRSdOnVCu3bt4OHhgejoaFy+fBlXrlyBTCYTLTMSGhqKDRs2wNra\nGmPGjIGZmRnU1dVx9+5dfPvtt6iqqmp0WVJTUwEAQ4YMaXLgl5KSgkGDBkFVVRVvvvkmbG1t0aZN\nG3Ach+jo6Gad/KOsrAyA8mcEgNAiKc9Xl6Y8T8qUlJTAxcUFN27cgLu7O/z8/KCnpwee55GQkIDE\nxESF+zF37lwYGhpi48aNWLx4MRYvXgwNDQ2MGTMGK1euFF5T48aNg5qaGr755husWrUKK1euhKqq\nKoYMGYJVq1YJY0JfBPkyOgUFBVi0aJHSPBzHCRMzyeusrhZiU1NTCv5aiO/SvgMDA2MMDAwyJhN+\nr/2vjMlEac+aHwA4PFlLkud4cPj/f1/S36/inHX9/bLPScviEEJeJxT8vYb+/vtvpem3b98G8L+J\nOeTBVHZ2Nuzs7Bp9fGVvZPr6+gCAmzdvNri/rq4ueJ5HeXl5i+rmy/M83N3dcfjwYZSVlUEqlcLP\nzw+AYqvglStXFNKAJ3W7YcMGODo64uTJkwqta2lpafj222+bVJYffvgBixYtwkcffQR1dfUmLVi/\nbNkyVFdXIzExEX379lXY9tNPP4nyy7sDKpuRVB5QNJb8mZI/a0+TpysL5GuTP083btxo0vnlfvjh\nB/z1119YunQp5s2bp7CtsLAQiYmJon2mTJmCKVOmoLi4WJhMaPv27bh+/brCREABAQEICAjA/fv3\nkZycjF27dmHLli3Izs5GVlaWaIKkZyWvo759++LEiRMN5pe/ruUtgk+r656Ql2/G0RkNZyL/KK0+\nGKYvB1p0GegLClJbiwv+vjn5Tb3fgjYVW/DPW6ssJSVFlFZRUYHMzEwYGBgIXd1cXV2xd+9enDx5\nsknBnzLOzs7gOA7x8fGQyWT1ji9ydXXF2bNnkZaWBg8Pj+c6rzIqKioAnq010MvLC7Gxsfj+++9x\n69YtYTZPS0tL2NjYICEhAVevXhWN95Mvd+Lj4yPqVilvxWsKQ0NDxMXFYdCgQZgyZQoANDoAzM3N\nFZbYqO327dvIzc0V5ZfPAvnXX38Jy2TInT17VpS/vvp1cnICAGHcZG0PHz7E6dOnoampiS5dutR7\nDS4uLgCAY8eOYezYsfXmVUZ+nU93zWWM4eTJk/Xua2xsjNGjR2P06NFwcnJCUlIS7t+/LxqfqqOj\ng6FDh2Lo0KG4d+8eYmNjkZ2djR49ejS5vMro6OjA3t4eWVlZKC8vh7a2dr35e/XqBUB53RcUFNBy\nD4S8QgwMNawGz/AxhZCXoqUEoi31C4qWVh/NqcUFf7OP0TIQDbl8+TKio6MVgoXIyEjcu3cPoaGh\nQlpwcDAWL16MsLAwuLm5iQLA0tJS5OXlKUxFXxdTU1MEBATgl19+wbJly/D5558rbL9x44YwPu+j\njz5CVFQUQkND8euvvypMBgM8CVLu3r0Le3v7Jl878L9g5lk+7Mpb81asWAGO4xRa9zw9PbFv3z6U\nlpaKlhmQTy7ydAtNTk4Oli1b1uRyAE8CwPj4eHh7e+ODDz5QmOCmPlZWVrhy5Qqys7OFOnz06BFC\nQkJQXV0t+oZPHmht3rxZYazezz//jKSkJFF++cQmyuq3Q4cO8PDwQGJiIn766SdMnDhR2LZ8+XIU\nFRUhODhY6YQptcmXU9i8eTMmTZok+pKg9vNUVx0AT74I6datm5C+evVqnD9/XnRNiYmJonM8ePAA\npaWlUFNTEwLe5ORk9O/fX+HLDZlMhuLiYnAc98JbskNDQzF9+nRMnToVP/zwg+iLhaysLLRt2xYm\nJiawtLSEu7s7kpOTsXfvXoWlLMLDwyGTyejbXUIIIUrRFxRErsUFf6Rhvr6+mDZtGg4dOgQ7Ozuc\nOXMGcXFxsLGxQUREhJDPxMQE27dvx/jx49GjRw8MHToUtra2qKioQF5eHhITExEUFIT169c36rzr\n16/H+fPnER4ejtjYWHh4eODRo0fIysrC2bNnhQW+u3fvju+++w4hISGws7ODn58frKyscPfuXVy9\nehUpKSlYvHjxMwd/2tracHFxQVJSEgIDA2Frawue5xEYGCiaifZpPXv2hL6+PoqKimBra6sw5szT\n0xM//vij8Htt5ubmCAgIwN69e/HGG2/A09MTN2/exIEDB/Dmm28qXbcQaHhm0toB4Pvvvw+O4xAY\nGFjvPiEhIfjtt9/Qv39/jBs3DqqqqoiLi0NNTQ169eolTMoiN3LkSHTq1AmbN2/G9evX4ejoiEuX\nLiEhIQFDhw7F4cOHFfJ37doVFhYW2LFjBzQ0NNCuXTtwHIcZM2ZAV1cXGzZswIABA/Duu+/il19+\nQefOnZGRkYHffvsNNjY2WL58eb3lB55MSvPTTz9h6NChGDRoEPz8/ODg4ICSkhKkpaXB2tq63nUT\n3333XSxfvhwhISGQSqWwsLDAmTNnkJaWBj8/Pxw6dEhUBwYGBnB1dYWlpSUePnyII0eOID8/H6Gh\nocLEL6Ghobh9+zb69+8PKysrMMaQkJCAc+fOYfjw4ejcuXOD19YU06ZNw4kTJ7B9+3YkJycLaxYW\nFhbijz/+QGZmpsK6id999x0GDBiAcePGYezYsbCyskJiYiJu3LiBnj17CpPCEEIIIYQoQ8Hfa6hf\nv34ICwtDeHg4jh49ColEInwYfnqh5+HDhwszQ8bHx+Pw4cPQ09ODpaUlPv74Y9GSEfVp27YtTp8+\nja+++gp79uwRlnLo3LkzwsPDFfJOnToVjo6O+Oabb5CUlIQ7d+7AyMgI1tbWmD9/Pt5++20hL8c1\nvT/61q1bMWvWLBw8eFAYtzZw4MAGgz+O4+Dh4YHY2FhRgCfvAvp0i6BcTEwMLC0tsXfvXqxduxa2\ntrZYunQphg0bpjT4U3ZdytKMjIxw/PhxIQDkeV60jEJtw4cPx86dO7Fs2TJs2bIFenp6GDJkCCIj\nIzF+/HjR8SUSCeLi4jBr1izEx8fj1KlTcHNzQ3JyMg4cOIAjR44o5Od5Hr/88gs+/fRT/PTTT7h/\n/74QlOrq6sLe3h7p6emIiIjAsWPHEBsbC3Nzc4SEhGD+/PkwNjaus+y1ubu7IyMjA0uWLEFcXByO\nHj0KY2NjODo64l//+le9+7Zv3x5SqRRz587F0aNHIZPJ4ObmhpSUFBw8eFAU0EZGRuLIkSNIS0vD\n/v37oauriy5duiAiIgLvvPOOkO+zzz7Dnj17kJGRgSNHjkBTUxM2Njb47rvv8OGHHyocs6nPbF3P\n+datW/HWW2/hP//5D2JjY1FZWQkzMzN07doVGzZsQPfu3YW8PXv2RFJSEj799FPExsZCQ0MDgwYN\nwq5du/Duu+9Sy18LMf2N6cI4m9pjbmr/K+/q8/S258lfe1IY+XCJZv8b/0t/6edW8vfLPuezDEch\nhJBXiWPPumhaM+A4DohoIFPEs6/z9rqTSqXw9vZGRESEwpqKhBBCWgZ5EEZaj5YSiLbUMsj/fmVl\nQAsqyysoA31B8ZqKaL54p8W1/H3s+nG934JGIvJVF5EQQgghBMCTgF+FU3nVxSCkTi0lEG3pZXhl\nX5oo+YLiv/hvsz0PLS74WzVkVb3bKfgjhBBCCCGkcegLitdPcwZ/zTuXKCGEEEIIIYSQFqHFjflr\nqDg0noIQQkhLRe9RhBBCnldzvpdQyx8hhBBCCCGEtAIU/BFCCCGEEEJIK0DBHyGEEEIIIYS0AhT8\nEUIIIYQQQkgrQMEfIYQQQgghhLQCFPwRQgghhBBCSCtAwR8hhBBCCCGEtAIU/BFCCCGEEEJIK0DB\nHyGEEEIIIYS0AhT8kVZj8+bN4HkeMTExjd6H53l4eXkppHl6eoLn6aXTXJ7lPr0Myp4FADh58iQ8\nPT1haGgInucxatQoAM3/nFhbW6Njx47NdnxCCCGE/PPQJ1jy2snPzwfP8wgODn6m/TmOe+78TT1G\nS9ZSg62WWMdPl+nevXsYPnw4zp8/j8DAQERERGDChAlC3ua+hpZYR4QQQghpuVRfdQEIaSr5B96X\n8cE3OzsbWlpazX6eloACifopexbS09NRUlKCyMhIzJ07V2Hbli1b8ODBg5dZREIIIYSQelHwR147\njDGFf5uTnZ1ds5+jpXgZ9fk6U/YsFBYWAgBMTU1F2zp06NDsZSKEEEIIaQrq9vkakUql4HkeCxcu\nhFQqhbu7O3R0dGBsbIzAwEDcunVL6X5nz57F2LFjYWpqColEAltbW3z22WeoqKio8/gpKSnw8fGB\nnp4eDA0NhTylpaUIDw+Hg4MDtLS0YGRkhL59+2LlypWi8yYkJGDo0KEwMjKCpqYmHBwcsHz5ctTU\n1Cjkq93t8NixY+jXrx+0tbVhbGyMoKAglJSUKOS1sbEBAMTExIDneeEnKSmpUfXIGMOePXvQp08f\naGlpwcLCAjNmzEBZWZkob13jvJSJioqCiooKBg4ciNLSUiF9z5498PT0hJ6eHrS0tNC7d29ERUU1\n6pgAUFZWhsjISLi7u8PMzAwaGhqwsrLC1KlTcfv2bVH++saaBQUFged5FBQUCH+/9957AIDg4GCF\n+qzt3LlzGD16NExMTCCRSGBnZ4cvvvhC9Aw15Pfff8f48eNhbm4OiUSCDh06YNSoUUhNTW1w3x9/\n/BEjRoyAlZUVJBIJTExM4O/vj4yMDFFexhg2bdoEZ2dnGBoaok2bNrCyssKYMWPw+++/K+TdvXs3\n3N3dYWJiAk1NTbRv3x5+fn6Ii4tTyPf0s8DzPIKCggAo1p38OazrPlRVVWHFihXo1asX2rRpA319\nfQwePLjO5zchIQH9+/eHlpYWTE1NMWXKFIXXBCGEEEJIY1HL32vo5MmTWLZsGYYPH46ZM2ciPT0d\n27ZtQ2pqKtLT0xWCtb1792LChAmQSCTw9/eHmZkZMjIyEBkZiYSEBCQlJUFNTU3h+KmpqVi6dCl8\nfHwwbdo0FBUVAQBu374Nd3d3XL16FS4uLggNDUVVVRX++OMPREZGYvbs2cIx1q5dixkzZqBt27YI\nCAiAgYEBkpOTERYWhtOnT2PPnj2i64qNjcWhQ4cwYsQIDBgwAImJidiyZQtyc3ORnJwMAHBycsLM\nmTPx7bffwtHREf7+/sL+VlZWjaq/n3/+Gb/99hvGjx+PIUOG4Pjx41i7di3S0tKQkpIiqo/GdIdc\ntmwZPv/8cwwfPhy7du2ChoYGAGDOnDlYuXIlrK2tMXHiRGhpaeHYsWP48MMPcenSJXzzzTcNHvvi\nxYtYuHAhBg0ahHHjxkFTUxOZmZn4/vvvcezYMfz+++/Q19dvdJlrbwsICEBpaSn2798Pf39/ODo6\nivInJibirbfeAmMM48aNQ7t27XD8+HEsXboUv/76K5KTkyGRSBq8jp07d+Ldd9+FqqoqRo4cCRsb\nGxQWFiI5ORl79uxB//79690/JCQEvXv3xpAhQ2BkZIS8vDzs378fv/76K6RSKVxdXYW8c+fOxcqV\nK9GrVy8EBQVBQ0MD169fh1QqxalTp9C7d28AwLp16xAaGgpbW1tMnDgROjo6uHHjBk6cOIFjx47B\nx8enzrpbsGABMjMzRXVnbW2tND8APHz4EL6+vkhJSYGLiws+/PBDlJeXY//+/Rg0aBB27dqFgIAA\nIf+xY8fg5+cHDQ0NvPPOOzA2NsahQ4cwePBgPH78WHjOCCGEEEIahbUgjSlOCyvyS5WQkMA4jmMc\nx7Ho6GiFbeHh4YzjOBYaGiqkFRUVMR0dHdapUydWWFiokH/FihWM4zj29ddfKz3+1q1bRecPCAhg\nHMexJUuWiLbdvHlT+P3ChQtMVVWVubm5sbKyMoV8ISEhjOM49vPPPwtp0dHRjOM4pq6uzk6cOCGk\n19TUMC8vL8ZxHDt16pSQnp+fzziOY8HBwXVVlVLy83Acx44fP66wLTAwkHEcx1auXKmQznEc8/Ly\nUkjz8PBgPM8zxhiTyWTsk08+YRzHscmTJ7Oamhoh39GjRxnHcSwgIIBVVVUJ6Y8fP2b+/v6M4ziW\nnp7eYLlLS0vZ3bt3Renbtm1jHMexxYsX11m+p02ePJlxHMeuXbsmpMnrJSYmRpS/urqa2djYMBUV\nFZaUlKSwLSgoiHEcxxYuXNjgNRQWFjItLS2mr6/PLl68KNpe+/mpqzz5+fmi/S5dusR0dHSYj4+P\nQrqBgQF74403mEwmE+1Tuy6dnJxY+/bt2YMHD0T57ty5o/C3smehvrpTdh/mzZvHOI5jy5cvV0gv\nKipi1tbWzMTERChLdXU1s7a2ZmpqauzMmTNC3urqajZo0CDGcRzr2LGj6Lzk1WrN71GEEEJejOZ8\nL6Fun68he3t7obuZ3Lx586Cvr49t27YJaVu2bEF5eTkiIyNhZmamkP+TTz6BiYkJduzYITq+s7Mz\nJk2apJB269Yt7Nu3D/b29ggLCxPtY25uLvy+adMm1NTUYM2aNdDR0VHIt2TJEnAcp/S8b7/9Ntzc\n3IS/eZ7H5MmTAQBnzpwR0tlzjk3z9fUVdeVcvHgxVFRUsGXLlkYfp6amBsHBwVi1ahVmzZoldF+V\nW7duHXiex6ZNm6Curi6kq6qq4ssvvwTwpDWsIbq6uqKWPeBJfeno6CA+Pr7RZW6qlJQU5OXlYfjw\n4XB3d1fYtnTpUqirqzdqltCYmBg8ePAAc+bMQdeuXUXbaz8/dVHWsmtvbw9PT08kJyejurpaSOc4\nDhoaGkpbQGvXJcdxUFNTU9o9s3YL+osgk8mwceNGODg4iCaHMTY2xuzZs1FcXCzcz9TUVFy7dg3+\n/v7o06ePkFdFRUV4fgghhBBCmqL1dPt82TMZNuPkGcq6x2lpacHR0RFSqRQFBQWwtLREWloagCcf\n4C9cuCDaR1VVFdnZ2aJ0Z2dnUZo8+PL29m6wG2RaWho4jsOBAwdw8OBB0XaJRKL0vLU/4Mq1a9cO\nwJMp9V+Up4MY4MnkHB06dEBWVhYYYw1eI2MMAQEBOHjwIJYsWaI0IE5LS4O2tjbWrVsn2vb48WMA\nUFoPysTHx2P16tU4ffo0SkpKFMZNyicdaQ7nzp0DAHh4eIi2mZubw9bWFpcuXUJFRQXatGlT53HS\n09MBPAm8n9XVq1exdOlSJCQkoLCwEI8ePRK2cRyHO3fuCBOvjB8/Hhs3bkTv3r0xZswYeHp6wtnZ\nWSEIl+ebN28eunfvjgkTJsDT0xN9+/ZtlhleL1++jNLSUlhZWSEiIkK0/cqVK0I+Pz8/oe4HDBgg\nyuvq6goVFZUXXkZCCCGE/LO1nuDvHzSTYdu2bZWmyz/4yicbkU8KsWbNmjqPpSzIUTZzofyYFhYW\nDZavpKQEjLE6Wyc4jkNlZaUoXVdXV5SmqvrkEX16kpjnUV/9Xbt2DeXl5aIWS2VSU1PRpk0bvPnm\nm0q3y4O0RYsWKd1eVz08befOnZg4cSL09PQwZMgQWFtbQ1NTE4wxrF69GlVVVQ0e41nJJ8FR9kwA\ngJmZGS5evIiysrJ6g7+mPD/KXLlyBS4uLigvL8fgwYMxevRoaGtrg+d57N27F+fOnVOohzVr1qBj\nx46Ijo7GF198AQDQ0dFBYGAgIiMjhbLOnTsXhoaG2LhxIxYvXozFixdDQ0MDY8aMwcqVK+t8Vp6F\n/PV4/vx5nD9/XmkejuOESXTkdWZiYiLKx/M8jI2NX1jZCCGEENI6tJ7g7x/k77//Vpoun/lRT08P\nwP+Cqezs7CYtWVBfV7mbN282uL+uri54nkd5eXmjJgJ52eqrP57noa2t3eAxOI5DXFwcBg0ahMGD\nByMuLg5OTk4KeXR1daGhodGoOqvPokWLoKWlhYyMDGGmU7nly5eL8su7MMpkMlF3xtqzkDaG/BlS\nNquoPJ3jOKWBe23y5+fGjRvPFACuXr0apaWl+O9//yssoi538uRJoZVMTlVVFXPmzMGcOXNw48YN\nJCQkICoqCuvWrcP9+/exefNmIe+UKVMwZcoUFBcXC5MMbd++XZgg5kWR19GECRPw3//+t8H88tex\nfMKl2mQyGYqLi2k5CUIIIYQ0CY35ew2lpKSI0ioqKpCZmQkDAwNYWloCgDD74cmTJ5/7nM7OzuA4\nDvHx8ZDJZPXmdXV1hUwmE7qdvmjy7m7P2hqobEr9goICFBQUoHv37o1e7NzJyQm//fYbGGPw8fHB\n2bNnFba7urri1q1buHbt2jOVUy43NxfdunUTBX6///47Hj58KMpvYGAAxhj++usvhXSZTIZz586J\nrq+++pQHtImJiaJthYWFyMnJgY2NTb2tfgDg4uIC4Mnslc8iNzcXHMdhxIgRCukPHz7E77//Xu89\na9euHSZNmoS4uDgYGxvjwIEDSvMZGxtj9OjR2L9/P3r16oWkpCTcv3//mcqrTLdu3aCjo4P09PQG\nX0MAhNlD5TPd1nbq1KkX2hpOCCGEkNaBgr/X0OXLlxEdHa2QFhkZiXv37ilM1BIcHAxtbW2EhYUh\nJydHdJzS0lJkZmY26pympqYICAjA5cuXsWzZMtH2GzduCL9/9NFHUFFRQWhoqNLxaLdv3270WDdl\nDAwMAEBYq66p4uLicPz4cYW08PBwyGQyBAYGNulYffr0wbFjxyCTyTB48GCF+gwNDQUAvP/++0pb\n3PLz8xsVGFpZWSEnJ0ehBaisrAwzZ85Uml8eaNVu3QKAb775Bvn5+aL88olNlNXngAEDYGNjg9jY\nWNFafJ9//jkeP37cqDoLDAyElpYWVqxYgYsXLypsY4zVuUalnJWVFRhjCl98MMYQFhYmahl79OiR\n0i88ysrK8ODBA4XWaGVB7YMHD1BaWgo1NbUXOq5ORUUFU6dORW5uLsLCwpQGgGlpaXjw4AGAJ2N7\nra2tsW/fPoUJj6qrqxEeHv7CykUIIYSQ1oO6fb6GfH19MW3aNBw6dAh2dnY4c+YM4uLiYGNjozCR\nhImJCbZv347x48ejR48eGDp0KGxtbVFRUYG8vDwkJiYiKCgI69evb9R5169fj/PnzyM8PByxsbHw\n8PDAo0ePkJWVhbNnz6K4uBgA0L17d3z33XcICQmBnZ0d/Pz8YGVlhbt37+Lq1atISUnB4sWLYW9v\n/0zXr62tDRcXFyQlJSEwMBC2trbgeR6BgYFCq2d9hg4diqFDhwpr1iUkJOD06dN44403hICtIbVn\nHHV2dsaxY8fg6+sLHx8fxMfHo1evXnjrrbcQFhaGZcuWoXPnznjzzTfRrl07FBUV4dKlS0hLS8NP\nP/3U4PqEISEhmDlzJnr37o1Ro0ahqqoKR48eRbt27WBhYSGa/TQ4OBhfffUVIiIikJmZCRsbG5w5\ncwZZWVnw8PAQBTz9+vWDpqYmVq9ejbt37wpjyb744gtwHIcff/wRQ4YMgY+PD8aNGwcLCwtIpVKk\npaXB2dlZNHOlMqampvjxxx8xadIk9OnTB/7+/ujYsSP+/vtvJCUlwc/PD6tWrapz/w8//BDR0dEY\nNWoUxo8fD11dXSQnJyM/Px+enp4K3TMrKyvRv39/2Nvbw8nJCR06dEBpaSliY2NRWVmpMAZz5MiR\nMDAwgKurKywtLfHw4UMcOXIE+fn5CA0Nfe6JX56+N4sWLcKZM2ewYsUKxMbGYsCAATA0NMRff/2F\njIwM5OTk4NatW9DU1ATP89i4cSOGDRsGDw8PTJw4EUZGRjh8+DDU1dVhbm7+3DPfEkIIIaSVabZF\nJJ5BY4rTwor8UsnX4Vu4cCGTSqXM3d2dtWnThhkZGbHAwEDRWn5yFy9eZEFBQaxDhw5MXV2dmZiY\nsD59+rCwsDB2+fJlpcevy927d1lYWBizs7NjGhoazNjYmLm5ubHVq1eL8p48eZKNHTuWmZubM3V1\ndWZubs7c3NzYl19+ya5fvy7k27x5M+N5XulaaXWVKScnh/n5+TEDAwPG8zzjeZ4lJibWW3+1z7Nn\nzx7Wp08fpqmpyczMzFhoaKhoTULGlK/t5unpqXQdvdOnTzN9fX1mYmLCzp8/L6QfOXKE+fn5MWNj\nYyl6vqwAACAASURBVKaurs7at2/PPD092TfffMOKi4vrLbPcunXrWLdu3ZimpiaztLRks2bNYvfv\n32fW1tZK13o7d+4c8/HxYW3atGH6+vosICCA5ebmsqCgIMbzvMI6f4wxdvjwYebi4sK0tLQYx3Gi\n68vMzGSjRo1iRkZGTF1dnXXu3Jl9/vnnrKKiolHll0tPT2ejR49mJiYmTENDg1laWrIxY8YorO9Y\n1/MQHx/P+vXrx3R0dJixsTEbM2YMu3r1quiaHj9+zJYvX858fX1Z+/btmYaGBrOwsGC+vr7s4MGD\nCsfcsGEDGzFiBLO2tmYSiYS1bduWubu7s23btonKruxZqO/Zres5qa6uZuvWrWN9+/Zlurq6TFNT\nk3Xq1IkFBASwrVu3surqaoX8x48fZ/369WOampqsbdu27P3332clJSV13nvyarXm9yhCCCEvRnO+\nl3D/f4IWgeO4Br/JbkyefyqpVApvb29ERERg/vz5r7o4hBBCntKa36MIIYS8GM35XkJj/gghhBBC\nCCGkFaDgjxBCCCGEEEJaAQr+CCGEEEIIIaQVoDF/hBBCyAtC71GEEEKeF435I4QQQgghhBDyXCj4\nI4QQQgghhJBWgII/QgghhBBCCGkFKPgjhBBCCCGEkFaAgj9CCCGEEEIIaQUaDP6uX7+OMWPGQF9f\nH3p6ehg9ejSuX7/eqIPn5+cjMDAQlpaW0NLSQpcuXRAeHo7KysrnLjghhBBCCCGEkMard6mHyspK\n9OrVC5qamli8eDEA4IsvvkBlZSXOnz8PLS2tOg9cXl6OXr16AQAiIiJgaWmJ06dPY8GCBRgxYgR2\n7NghLgwt9UAIIeQ1Ru9RhBBCnldzvpeo1rcxKioKeXl5yMnJgY2NDQCgZ8+e6Ny5MzZt2oRZs2bV\nuW9qairy8vLw66+/YvDgwQAADw8PlJSU4Ouvv8bDhw8hkUhe4KUQQgghhBBCCKlLvd0+Y2Nj4ebm\nJgR+AGBtbY3+/ftj//799R64pqYGAKCnp6eQrqenB8YYfTNKXrrNmzeD53nExMS86qKQ/xcUFASe\n51FQUPCqiyKQSqXgeR4LFy4UbYuJiUHPnj3Rpk0b8DyPNWvWAAB4noeXl1ezlCc/Px88zyM4OLhZ\njk8IIYSQ1qPe4C8rKwvdu3cXpXfr1g0XL16s98CDBw9G9+7dMXfuXFy6dAnl5eU4fvw41qxZg6lT\np0JTU/P5Sk5aref9MPx/7N19XM3n/wfw1+eUOqX7+6I60tJkhFaKlNy1mpQR9qWb3Tel2c13sjU1\nLZnZ3Ntm36nwHSYRzRg6JZJKiVCTbtxUopRCqOv3h985347z6Q65We/n4+Gx0/W5Ptd1fa7P5+yc\n97muz/XhOO4Jt+jF8TwGW8/r+Xi4Xenp6QgMDMS9e/cQGhqKiIgIjBgxos383d0eQgghhJCuanfa\nZ21tLbS1teXSdXR0UFtb227BvXr1wsGDBzFp0iTY2NhI0999912sWrWqzf1OVZ2SfsnhwPG+Jj2b\n9Jqg6+GRPG/99rzNAnBwcMC5c+egp6cnk753714AD0b/7O3tZbadO3eu3XugCSGEEEKeB+0Gf4+j\nsbERr732GhoaGrBp0yaYmZkhMzMTX3/9NRQUFLB27Vre/Qb/OLi7mkT+ISTBwvMWNLwoaNp1+1RU\nVGBlZSWXXlFRAQAwNDSU28aXn/RcN+7cAIf//Uj1pF4D9EMoIYSQx9Nu8Ketrc07wldTUwMdHZ12\nC/7ll19w4sQJnD9/XnrP4KhRo6CpqYn33nsPH3zwAQYP5gn0Ulq9FgHo19Eh9BxisRhubm5YuHAh\nXFxcEB4ejry8PCgrK8PDwwPffvstjIyM5PbLzc1FdHQ00tLSUFdXh759+8LX1xdffPEFevfuzVv+\n2LFjERERgaysLCgoKKCmpgYAUFdXh++++w47duxASUkJVFRU8NJLL2HatGn45JNPZOpNSUnB0qVL\nkZmZiVu3bsHCwgJ+fn749NNPoaCgIM0XGxuLt956Cxs2bICxsTEiIiKQn58PoVCI119/Hd9//730\nepPkBR6MwLS+f08sFmP06NEd9iNjDAkJCYiOjsbZs2ehpaWFqVOnIioqChoaGrz9sXDhQpkySktL\nYWFhAX9/f2zYsEGaXlRUhKioKKSlpaGyshJqamowNzfHpEmTEBER0WHbioqKsH79evz1118oLy/H\n7du30b9/f8ycOROff/45FBVl37ICgQAuLi5ISUmRK0skEoHjOJSUlEj/lkz37Nfvf2+sh/dPTEzE\n999/j7y8PDDG8PLLL+ODDz7A22+/3WH7W9u+fTvWrVuHEydOoKmpCX369MHYsWPxxRdfwNTUtM39\n6uvrsXbtWiQnJ+Pvv/9GbW0tjIyM8NprryEyMlIu+Lpx4waWLl2KhIQEXLp0CYqKijA0NMTo0aOx\nZMkS6bVz584drFy5Ehs3bkRZWRkYYzAwMICTkxMiIyOl/596+LxL/pZo3XctLS0A2j4PlZWViI6O\nxp49e3DlyhVoaWlh/PjxWLRoEUQikdyxr127FqtWrUJpaSlMTEzw9ttvY/r06V3qd/LsaS+RnzHT\nXR4OFAWcQPqa4/7/b57XD+ftUfs9T235h+/3rNtMyItCLBZDLBY/lbraDf5sbGxw+vRpufQzZ85g\n4MCB7RZ85swZaGtryywWAwCvvvoqgAfTpHiDv+5ZM+EfJSMjA4sXL8akSZMQGhqKrKwsbNq0CUeO\nHEFWVpZMYJ6YmIgZM2ZAKBTC29sbRkZGyMnJQUxMDFJSUpCWloZevXrJlH/kyBFER0dj3LhxCAoK\nQnV1NQCgqqoKzs7OOH/+POzt7RESEoKmpiacOnUKMTExMsHf6tWrMXfuXBgYGMDHxwfa2to4fPgw\nwsLCcPz4cSQkJMgdV1JSEpKTk+Hl5YVRo0YhNTUV8fHxKC4uxuHDhwEAQ4cORWhoKFasWAFbW1t4\ne3tL9zc3N+9U/23fvh1//fUXpk+fDnd3dxw6dAirV69GZmYm0tPT5fqjvQ+Q1tsuX74Me3t7NDc3\nY/LkyRCJRKitrcXZs2fx008/dSr427FjB2JjYzF27FhMmDABTU1NEIvFCA8PR3Z2NhITE9ttQ3vb\n5s2bh9jYWJw8eRIfffQRtLS0AEAmCPn2228xf/58GBgYIDAwEEpKSti+fTveffdd5ObmYvXq1R0e\nAwDMnTsXq1evhqGhIaZPnw4dHR1cuHAB27dvh4eHR7vB35kzZxAZGYmxY8fC19cXKioqyMvLw88/\n/4z9+/fjxIkT0rYzxjBhwgTk5ORg4sSJ8Pb2xr1793DhwgVs3boV8+bNk74fZs+ejYSEBIwaNQoT\nJ06EQCBAaWkp/vzzT8ycOVPu/1WSvuvXrx8WLlyInTt3yvVdW30NAH///TdcXV1RVVUFT09PTJs2\nDeXl5di2bRv27duHY8eOydT51VdfISoqCn379kVQUBCam5uxcuVKHD16tFN9TnomBtmZEM2s+Vk2\nh5DnSltB4osSPNMPIz1nP7MhZvAf4i9N51t07klpN/jz8vLCp59+ipKSEkh+7S4tLcXRo0exZMmS\ndgvu27cvamtrUVxcjP79+0vTMzMzAQB9+vR53LZ3CveUoui2MFfXJ17m/v378euvvyIgIECaJvni\nGBERIV2B8Nq1a/D394epqSnS09NlRgW/++47/Pvf/8bKlSvlRuwOHDiA+Ph4zJo1SyY9KCgI58+f\nR1RUFBYsWCCzTTIlDniwUNC8efMwYsQI7Nu3D+rq6tJtISEhWLNmDRISEvDGG2/IlLFnzx6IxWI4\nOjoCeDCqMm7cOIjFYmRmZsLBwQFDhgzBRx99JA3+vvrqqy73X3JyMg4ePCizOqO/vz82btyIVatW\n4eOPP+5ymQCQkJCA+vp67Nq1C5MmTZLZ1tE9sq3b8emnn8qN8L333nv45ZdfcOTIEYwcOfKR2hca\nGorc3FxpAGNmZiaz/fz581iwYAH69OmDnJwcGBgYAHjwnE5HR0esXbsWvr6+HY6uJiUlYfXq1Rg+\nfDgOHTokc/6bmppw69atdvcfOHAgKioq5AKszZs3Y/bs2VizZg2++OILAMCpU6eQnZ2NefPmYdmy\nZTL5b9++LQ3I6urqkJCQAB8fH7kfHu7fv487d+602R5zc3MsXLgQJSUlbfYdHz8/P9TU1EAsFmPU\nqFHS9GPHjmH06NEIDQ3F7t27ATwIFKOjo9GvXz/k5ORIjz0sLAy2trYd1kUIIUQeA6MfRgh5SLur\nfb777rsQiUSYPHkykpKSkJSUhMmTJ8PMzAzvv/++NF9ZWRkUFRWxaNEiaVpAQAA0NDTg4eGB+Ph4\n6RTAzz77DHZ2dm1+gbXRt4GNvg0G6g/Ey3ov42W9l2GtZ40BugMwQHfAEzrsF5u1tbVM4AcA8+fP\nh5aWFjZt2iRNi4+PR0NDA2JiYuSmg3788cfQ19fHli1b5Mq3s7OTC/wqKyuxc+dOWFtbIywsTG4f\nY2Nj6euffvpJOmrR+os/AHzzzTfgOI633jfffFMa+AEPptL5+/sDALKzs6Xpj3u/2oQJE+SW5Y+K\nioKCggLi4+Mfq2wAvM+v5Fs4iY+xsbFc4AcAH3zwAQDg4MGDj9e4dmzevBktLS349NNPpYEfAKip\nqUlHLTvzmIx169YBAFasWCF3/pWVlTvsCw0NDd6RtTfffBPq6uq8fcDX5yoqKtJ0SRDIl09RURFq\namrttqmrTpw4gczMTLz99tsygR8AjBgxAl5eXti7dy9u3rwJAPjtt9/Q0tKCTz75RObYjYyMEBoa\n+kTbRgghhJCeq92RP1VVVRw6dAjz5s3D7NmzwRjDuHHjsHz5cpmV7RhjaGlpkflSbmpqiuPHj+Or\nr77Cl19+iWvXrkmDRsmv9nxOfyg/zbQ1LoTmcPMFzqqqqrC1tYVYLEZ5ebl0gR3gwRL1fNN3FRUV\nce7cObl0Ozs7uTRJ8OXm5tbhPPrMzExwHIfdu3djz549ctuFQiFvvcOHD5dLk4wQ37hxo906u8LZ\n2VkuzdTUFKampigoKABj7JHuFfDy8sKCBQvg4+MDX19fjB8/Hs7Ozujbt2+ny2hpacF//vMfxMbG\noqCgADdv3pR5X7UeYX3STp48CeDBPYAPc/3/Eez8/PwOy8nKykLv3r3h5OT0yG05ePAgli9fjuPH\nj6Ompkb63FBAtg9sbGwwaNAgxMTEIC8vD6+//jpGjx4ts8Iw8CCgdHd3x2+//YZLly7B29sbLi4u\nsLW1hUDQ7m9gj0Ty3rt06RLvdN+Kigq0tLTg77//xrBhw6R9/3CgCPC/38nzTUP5wb3DjDGZaZmP\n8xr43xRPQggh5FF1uNqnqakptm/f3m4ekUgkXfigNSsrK94RHvJ4Wo/KtCZZCKOurg4ApIu0SKaB\n8uELcvhWM5SUaWJi0mH7ampqwBiTGQl+uE6+qX+tF1uRkIyCtf7y/7ja67+ysjI0NDTIjVh1hkgk\nQkZGBiIiIrBt2zbExsYCAIYNG4bFixdj/PjxHZYREhKCdevWQSQSYerUqTAyMoKSkhJqa2uxYsUK\nNDU1dbldnVVfXw+A//zr6upCQUFBmqc9dXV1aL0oSldt3boVM2fOhKamJtzd3SESiaCiogLGGJYv\nXy7TBwoKCkhJScHChQuRkJAgfRxDnz598Nlnn2Hu3LnSvNu3b0dUVBR+++036VRnXV1dfPjhhwgP\nD+cdcX1UkveeZMYEH47j0NjYCOB/7y99fX25fHzngzzf6ubXdXsdfIGi5L8trEUmrYW18L5+OC/t\n95zv94zb8tz0Qyf2I4S0rdse9UC6z9WrV3nTq6qqAACampoA/hdMnTt3rktL0fMFhJKpaFeuXOlw\nfw0NDQgEAjQ0NPBOs3vW2us/gUAgnQIoGRG6f/++XF7Jl/WHvfLKK0hISMC9e/eQlZWF5ORkrFq1\nCl5eXsjLy8OAAW1PXa6qqsK6detga2uLjIwMKCsrS7dlZmZixYoVvPvxtU/Sxs5ONwX+d71UVVXJ\nTOMFgOvXr6O5uZk3QH+YlpbWY41Qfv3111BVVUVOTo7cIix89xrr6upi9erVWL16NQoKCnDgwAGs\nXLkSH330ETQ0NKRTpFVVVREdHY3o6GgUFxfj0KFDWLNmDRYtWgSO4zq1IE9nSfrpxx9/xHvvvddh\nfsl7trq6Wq7vJe9rQlqTLBrw4I9n2xZCnkfPSyBK+z2F/Z6ntjyh/S7iYre9N/7xwV93LLjyrKWn\np8ulNTY2Ii8vD9ra2tLFKBwcHJCYmIiMjIzHfg6ZnZ0dOI7DwYMH0dLS0u5UOQcHB+Tm5iIzM5N3\nCuHjkjwm4lFHA9PS0uSmHpeXl6O8vByvvPKKNPiVBE6XLl2SKyM3N7fdOnr16gUnJyc4OTnBwMAA\n8+bNw/79+9sN/iSPZBg3bpxM4Ac8WIGVj7a2Ni5fviyXXlpayhv8tdd3Q4cOxc6dO5Gamiq3yEhq\naioAdGrxEXt7e+zdu/eRF6cpLi7G4MGD5QK/EydOtLswC/BgGqiNjQ1cXV0xdOhQ7N69W+7+WADo\n378/+vfvj6lTp0JfXx+7d+9+osGfg4MDgAcr83Ym+LO1tUViYiIOHz4stwoy3/udEEJI+1qvsEjI\ni4b7uPt+1aN3xAuosLBQ5tlyABATE4MbN27ILNQSGBgINTU1hIWFoaioSK6curo65OXldapOQ0ND\n+Pj4oLCwEIsXL5bb3joA+fDDD6GgoICQkBDeEaCqqiree/46SxLQSJ5Z11UHDhzAoUOHZNLCw8PR\n0tICPz8/aZq1tTXU1dWRlJQks1pnVVUVoqKi5MrNzc3lnRZZWVkJgH+xkdYkj6p4eGn/oqIi3j4H\nHgRaJSUlSEtLk6bdvXu3zRVLJY894Ou7N998EwoKCvjuu++kj/cAgIaGBkRERIDjOJn+aUtQUBCA\nB6uLPtwfd+7c6XDlU3NzcxQVFcm0ob6+nnfhk7KyMpSVlcmlP9zn165dQ0FBgVy+qqoqtLS0PPER\nant7e9jb22Pjxo3YtWuX3PZ79+7JBHUzZsyAgoICli1bJtM/FRUVbY74EkIIIYR01T9+5O+faMKE\nCQgKCkJycjKsrKyQnZ2NAwcOwMLCQmb0Ql9fH5s3b8b06dPxyiuvwMPDA5aWlmhsbERJSQlSU1MR\nEBCAtWvXdqretWvXIj8/H+Hh4UhKSoKLiwvu3r2LgoIC5Obm4tq1awCAQYMGYdWqVQgODoaVlRU8\nPT1hbm6O2tpanD9/Hunp6YiKioK1tfUjHb+amhrs7e2RlpYGPz8/WFpaQiAQwM/Pr1NL8Ht4eMDD\nwwO+vr7o06cPUlJScPz4cbz66qsICQmR5uvVqxdCQkIQHR2NYcOGwcvLCzdv3sSePXvg4uKCCxcu\nyJQbFxeHX375Bc7OzrCwsIC6ujry8/Oxb98+mJubw9fXt912GRsbw8fHB4mJiXj11Vfh6uqKK1eu\nYPfu3Zg4cSLvsxE//vhj7N+/Hx4eHpg5cyZUVFTw119/QVtbG8bGxmBMdoGIsWPHYtmyZXjvvfcw\nZcoU9O7dGyKRCLNmzUL//v0RHR2Nzz//HIMHD8bUqVPRq1cvJCYmoqysDHPmzOFdLOdhr7/+OkJC\nQrBq1SpYWVlh8uTJ0NHRQXl5Ofbt24dff/0VXl5ebe4fHByM0NBQDBs2DFOmTEFTUxP+/PNP9OnT\nByYmJjLHlJubizfeeAMjRoyAtbU1DA0NUV5ejp07d0JZWVl6Pi9duoRhw4Zh6NChGDRoEExMTHD1\n6lXs3LkTAoHgkR/v0Z7//ve/GDNmDHx8fDBq1CjY2tpCUVERZWVlOHz4MPT09HDmzBkAwEsvvYQF\nCxZg0aJF0r5vbm7Gtm3bYG9vj+Tk5CfePkIIIYT0QOw50pnmPGdNfqpSUlIYx3EsMjKSicVi5uzs\nzHr37s10dXWZn58fq6io4N3vzJkzLCAggJmamjIlJSWmr6/Phg8fzsLCwlhhYSFv+W2pra1lYWFh\nzMrKiikrKzM9PT3m6OjIli9fLpc3IyODTZs2jRkbGzMlJSVmbGzMHB0d2aJFi9jFixel+WJjY5lA\nIGBxcXHtHnNrRUVFzNPTk2lrazOBQMAEAgFLTU1tt/9a15OQkMCGDx/OVFRUmJGREQsJCWH19fVy\n+7S0tLDIyEhmZmbGlJWVmbW1NVu1ahUrKSlhHMexwMBAad7MzEz2/vvvs0GDBjEtLS3Wu3dvNnDg\nQPb555+z6urqdtsmcfPmTfbRRx8xc3NzJhQK2aBBg9qsT2L79u1s8ODBTFlZmZmYmLDQ0FDW0NDA\nRCIR69evn1z+pUuXMisrK6akpMQ4jmNjxoyR2b5jxw42atQopqamxnr37s3s7OzYL7/80qn2t7Zl\nyxY2evRopqGhwVRVVZmVlRULCgpily5dkuYJCAhgAoGAlZWVyey7Zs0aNnDgQKaiosLMzMzYvHnz\n2M2bN+WO6dKlS2z+/PlsxIgRzMDAgAmFQmZhYcFmzZrFTp06Jc1348YNFhkZyVxcXJixsTFTVlZm\nZmZmzNvbmx05ckSm7rauubbayhjj7UfGGLt+/ToLCwuTHoumpiYbOHAge+edd9ihQ4fk8q9du5ZZ\nW1szZWVlZmFhwaKjo1lxcXGb5548f3ryZxQhhJAnozs/S7j/r+C5wHGc3EjFo+T5pxKLxXBzc0NE\nRMQjPdycEEJI9+rJn1GEEEKejO78LKF7/gghhBBCCCGkB6DgjxBCCCGEEEJ6AAr+CCGEEEIIIaQH\noHv+CCGEkCeEPqMIIYQ8LrrnjxBCCCGEEELIY6HgjxBCCCGEEEJ6AAr+CCGEEEIIIaQHoOCPEEII\nIYQQQnoACv4IIYQQQgghpAeg4I8QQgghhBBCegAK/gghhBBCCCGkB6DgjxBCCCGEEEJ6AAr+CCGE\nEEIIIaQHoOCPkG4iEonQr1+/Z92MfwSxWAyBQIDIyMhn3RQZbZ3js2fP4vXXX4eBgQEEAgGGDh0K\nAAgICIBAIEB5eXm3tMfV1RUCAf1vnRBCCCH86FsCeeGUlpZCIBAgMDCwS/vFxsZCIBAgLi6um1om\ni+M4cBz3VOp60p7XYOt560++c9zc3AwfHx8cPHgQU6ZMQUREBIKCgtrM3x1tIoQQQgjho/isG0BI\nV0m+3D7ql9yn9eX40KFDT6We7kSBRPv4zvGFCxdQVFSEDz74AGvXrpXZtnjxYoSFhcHExORpNZEQ\nQgghRIqCP/LCYYzJ/PdR9+9u/4Qpn0+rr15UfOe4oqICAGBoaCi3zcjICEZGRt3eLkIIIYQQPjTt\n8wXSeiqeWCyGs7Mz1NXVoaenBz8/P1RWVvLul5ubi2nTpsHQ0BBCoRCWlpZYsGABGhsb2yw/PT0d\n48aNg6amJnR0dKR56urqEB4eDhsbG6iqqkJXVxcjRozAsmXL5OpNSUmBh4cHdHV1oaKiAhsbGyxZ\nsgTNzc0y+VpPx9y/fz+cnJygpqYGPT09BAQEoKamRiavhYUFACAuLg4CgUD6Ly0trc2+CwgIwFtv\nvQUACAwMlNlPQnK/VFNTExYsWIB+/fpBSUkJK1asAADk5ORgzpw5sLGxgaamJtTU1DB8+HCsW7eO\nt06++8Ek93yVlpZi5cqVsLa2hlAohEgkwtdff93pYOvevXtYuXIlxo8fjz59+kBZWRkmJib417/+\nhfPnz/Mef1v3mkVERMj0X0REBNzc3AAAkZGRMn3Vev+SkhL4+/vD2NgYysrKEIlEmDt3Lq5du9ap\nY5A4f/483n77bZiZmUEoFMLExATu7u7YvXt3h/smJiZi+vTpsLCwgKqqKnR0dDB+/HgcPHiQN//v\nv/8OZ2dn6OvrQ0VFBX379oWnpycOHDggk+/AgQOYMGECjI2NIRQKYWxsDDc3N2zdulUm38PnWCQS\nwdXVFYBs38XHxwNo+zy0tLRg/fr1cHBwgJqaGtTV1TFy5EgkJibyHkdeXh4mTpwINTU16OjoYNq0\nad12HyEhhBBC/jlo5O8FlJGRgcWLF2PSpEkIDQ1FVlYWNm3ahCNHjiArK0smWEtMTMSMGTMgFArh\n7e0NIyMj5OTkICYmBikpKUhLS0OvXr1kyj9y5Aiio6Mxbtw4BAUFobq6GgBQVVUFZ2dnnD9/Hvb2\n9ggJCUFTUxNOnTqFmJgYfPLJJ9IyVq9ejblz58LAwAA+Pj7Q1tbG4cOHERYWhuPHjyMhIUHuuJKS\nkpCcnAwvLy+MGjUKqampiI+PR3FxMQ4fPgwAGDp0KEJDQ7FixQrY2trC29tbur+5uXmbfebj44O6\nujrs2rUL3t7esLW1bTOvt7c3CgoK8Nprr0FDQwOmpqYAgPXr1yM5ORkuLi6YNGkSbt68iX379mHO\nnDkoKirCDz/8IFdWW9MmP/vsM6SmpmLSpEl47bXXkJiYiIiICNy9exdRUVFttk3i+vXr+OSTT+Di\n4oLJkydDU1MT586dw7Zt2/Dnn38iJycHIpGoU2152JgxY1BWVoa4uDi4urpKgxkA0NTUBPBgQRNn\nZ2fU1tbCx8cHAwYMQFZWFlavXo3k5GQcO3YM+vr6HdaVlpYGT09P3L59G6+//jpsbGxQXV2NzMxM\nbNiwAZMmTWp3/y+++AJCoRBjxoyBkZERrly5gp07d2LixIn4/fff4ePjI827Zs0ahISEwNLSEjNn\nzoS6ujouX76Mo0ePYv/+/Rg3bhwAYM+ePfDy8oKJiQm8vb2hq6uLiooKZGdnIyEhAdOnT2+zX+fN\nm4e8vDy5vmt9vT18HhhjmDlzJn7//XfY2NhI72Xds2cP3njjDSxfvhxz586V5s/Pz4ezszOampow\nbdo0iEQi6Y9B2traHfY5IYQQQnow9hzpTHOesyY/VSkpKYzjOMZxHNuwYYPMtvDwcMZxHAsJCZGm\nVVdXM3V1dda/f39WUVEhk3/p0qWM4zj23Xff8Za/ceNGufp9fHwYx3Hsm2++kdt25coV6evTLqQx\nsgAAIABJREFUp08zRUVF5ujoyOrr62XyBQcHM47j2Pbt26VpGzZsYBzHMSUlJXb06FFpenNzMxsz\nZgzjOI4dO3ZMml5aWso4jmOBgYFtdRUvST1xcXG8211cXBjHcczOzo7V1dXJbS8vL5dLu3//PnN3\nd2cKCgqsrKxMZpu5uTnr16+fTJq/vz/jOI7179+fVVZWStOvXbvGtLW1mYaGBrt7926Hx9LU1CR3\nThljLDU1lSkqKrJ33nmHt96H28gYYwsXLmQcx7HU1FRpmuRaiIyM5K1f0lcPXydfffVVp8/N7du3\nmYmJCevVq5dM3RKXL1/usD2lpaVy+1VVVbG+ffsyS0tLmfShQ4eyvn37stu3b8vtc/36delrHx8f\nJhQKWXV1dbv5GOM/x+31Hd95+PHHHxnHcSw4OJi1tLRI0xsbG5mDgwNTVlaWeX85OzszjuNYYmIi\nb9kCgUCuXvL09OTPKEIIIU9Gd36W0LTPF5C1tTUCAgJk0ubPnw8tLS1s2rRJmhYfH4+GhgbExMTI\n3Wf08ccfQ19fH1u2bJEr387ODrNmzZJJq6ysxM6dO2FtbY2wsDC5fYyNjaWvf/rpJzQ3N2PlypVQ\nV1eXyffNN9+A4zjeet988004OjpK/xYIBPD39wcAZGdnS9NZN9+HFhkZCQ0NDbl0yQhgawoKCnj3\n3XfR0tICsVjc6TrCw8Nl7gnT1dWFl5cXbt68iaKiog73V1JS4r13bPTo0Xj55ZflpjE+SWVlZUhL\nS4Otra3cdRIWFgY9PT1s3boV9+7da7ecXbt2oaKiAgEBARg9erTc9s4sisI32isZbS4uLpaZCslx\nHHr16sX7KITWo+UAoKioCEVF+YkRD+d7EtasWQMtLS388MMPMqOCqqqq+PLLL3H37l3s2LEDwIO+\nT09Ph52dncyoNwAsWrSIHvNACCGEkHb1mGmfYk78VOtzZa7dVvbIkSPl0lRVVWFrawuxWIzy8nKY\nmZkhMzMTAJCeno7Tp0/L7aOoqIhz587JpdvZ2cmlSYIvNze3DqcPZmZmguM47N69G3v27JHbLhQK\neesdPny4XFqfPn0AADdu3Gi3zieF4zje4weApqYmrFy5Elu3bkVhYaHcPZOShT46g+9Y+/btC6Dz\nx5qTk4Nvv/0WR44cQXV1tUywpays3Om2dNXJkycBgDdgEwqFsLe3xx9//IGioiLY2Ni0WU5WVhYA\nYMKECY/clsrKSixevBh79+7FpUuXcOfOHZntFRUVMDMzAwBMnz4d8+fPx6BBgzBjxgy4urpixIgR\nUFVVldlnxowZ2LlzJwYNGoSZM2fCzc0NTk5O0imvT9KtW7dw+vRpmJmZ8U73lUy5LiwsBPBgyicA\njBo1Si6vqakpzMzMUFZW9sTbSQghhJB/hh4T/HVnMPa0GRgY8KZLRpLq6uoAQLpQysqVK9ssiy+Q\n41ulUFJmZ0ZjampqwBjDokWL2qzz1q1bcul8o22S0ZeHF4npTm3175QpU7B37168/PLLmDVrFvT1\n9aGoqIiSkhLExcWhqamp03U87rGmp6dj7NixUFRUxMSJE2FpaYnevXuD4zhs2LChWxf/qK+vB8B/\nnQCQjkhK8rWlK9cUn5qaGtjb2+Py5ctwdnaGp6cnNDU1IRAIkJKSgtTUVJlz8u9//xs6Ojr48ccf\nERUVhaioKCgrK2Pq1KlYtmyZ9Lz7+vqiV69e+P777/HDDz9g2bJlUFRUhLu7O3744Qf079//kdrL\np7a2FgBQXl6Or7/+mjcPx3HSHxokfdbW/ZSGhoYU/BFCCCGkTT0m+PsnuXr1Km96VVUVgP8tyiEJ\nMM6dOwcrK6tOl88XEGppaQEArly50uH+GhoaEAgEaGhogFAo7HS9z7OsrCzs3bsXr732GpKTk2W2\nbd269ak9OF5i8eLFuH//PlJTUzFixAiZbb/99ptcfsl0wPv378ttkwQUnSW5riTX28Mk6XwBbmuS\na+ry5ctdql/iP//5Dy5duoTo6GjMnz9fZltFRQVSU1Pl9nnnnXfwzjvv4Nq1a9IFhTZv3oyLFy/K\nTNv18fGBj48Pbt68icOHD2Pbtm2Ij4/HuXPnUFBQILdI0qOS9NGIESNw9OjRDvNL3tuSEcGHtXVO\nCCGEEEIAetTDCyk9PV0urbGxEXl5edDW1pZOc3NwcADwYHXQx2VnZweO43Dw4EG0tLS0m9fBwQEt\nLS3SaadPmoKCAoCujwY+6n4AUFxcDADw9PSU23bkyJEul/e4iouLpY/ZaK2qqkra1tYkq0BeunRJ\nbltubq5cWnt9NXToUACQrsDa2p07d3D8+HGoqKhgwIAB7R6Dvb09AGD//v3t5muL5Di9vLxk0hlj\nHV7zenp6eOONN7Br1y4MGTIEaWlpuHnzplw+dXV1eHh4IDY2Fl5eXjh//jzvlOVHpa6uDmtraxQU\nFKChoaHD/EOGDAHA3/fl5eX0uAdCCCGEtIuCvxdQYWEhNmzYIJMWExODGzduyCzAERgYCDU1NYSF\nhfEuIlJXV4e8vLxO1WloaAgfHx8UFhZi8eLFcttbj958+OGHUFBQQEhICO99cFVVVY/1BVoSyHT1\ni65ksY5H+YIsWVjk4cD72LFj+Pnnn7tc3uMyNzfH9evXZfrx7t27CA4O5h3dkwRasbGxMunbt29H\nWlqa3Ghve31lamoKFxcX5Obmyo0yLlmyBNXV1ZgxYwbvgimtSR6nEBsbyztK19GIYFvnZPny5cjP\nz5c7Jr46bt++jbq6OvTq1Usa8B4+fFjuB46WlhZcu3YNHMc98dHskJAQ3Lx5Ex988AHv1OGCggLp\nSJ+ZmRmcnZ2Rk5Mj9wzA8PDwDn+YIYQQQkjPRtM+X0ATJkxAUFAQkpOTYWVlhezsbBw4cAAWFhaI\niIiQ5tPX18fmzZsxffp0vPLKK/Dw8IClpSUaGxtRUlKC1NRUBAQEYO3atZ2qd+3atcjPz0d4eDiS\nkpLg4uKCu3fvoqCgALm5udKHew8aNAirVq1CcHAwrKys4OnpCXNzc9TW1uL8+fNIT09HVFQUrK2t\nH+n41dTUYG9vj7S0NPj5+cHS0hICgQB+fn7SUU8+Tk5OUFFRwfLly1FbWws9PT0AwJdffinN09ZK\nog4ODrCzs8OWLVtQWVkJOzs7XLhwAbt374aXlxfvcwu7U3BwMP766y+MHDkSvr6+UFRUxIEDB9Dc\n3IwhQ4ZIF2WRmDx5Mvr374/Y2FhcvHgRtra2OHv2LFJSUuDh4YE//vhDJv/LL78MExMTbNmyBcrK\nyujTpw84jsPcuXOhoaGBdevWYdSoUZg9ezZ27NiBl156CTk5Ofjrr79gYWGBJUuWdHgMysrK+O23\n3+Dh4YGxY8fC09MTNjY2qKmpQWZmJkQiUZsPOQeA2bNnY8mSJQgODoZYLIaJiQmys7ORmZkJT09P\nuem5kydPhra2NhwcHGBmZoY7d+5g7969KC0tRUhIiHThl5CQEFRVVWHkyJEwNzcHYwwpKSk4efIk\nJk2ahJdeeqmzp6lTgoKCcPToUWzevBmHDx+WPrOwoqICp06dQl5ensxzE1etWoVRo0bB19cX06ZN\ng7m5OVJTU3H58mUMHjxYuigMIYQQQoicbnuIxCPoTHOesyY/Va2fHyYWi5mzszPr3bs309XVZX5+\nfrzPfWOMsTNnzrCAgABmamrKlJSUmL6+Phs+fDgLCwtjhYWFvOW3pba2loWFhTErKyumrKzM9PT0\nmKOjI1u+fLlc3oyMDDZt2jRmbGzMlJSUmLGxMXN0dGSLFi1iFy9elOaLjY1lAoGA9/l7bbWpqKiI\neXp6Mm1tbSYQCJhAIOB9VtzD/vjjD2Zvb89UVVXlnonm6ura7jPSqqqqWEBAADMxMWGqqqrMzs6O\n/fbbb0wsFvO2USQSyT0DLiAggAkEAt7n7UVERHT6OBhjbNu2bWzo0KFMVVWVGRsbs8DAQFZVVdXm\ncZSWljIfHx+moaHB1NTU2Pjx41lOTk6b9WZmZjJXV1emoaEh7avW7b5w4QLz8/NjRkZGTElJiZmb\nm7OQkBDe5+O1p7CwkPn5+TETExOmpKTETExMmIeHB/vjjz+kedq6DnJzc9n48eOZtrY209TUZO7u\n7iw7O5v3mNatW8e8vLyYSCRiQqGQGRgYMGdnZ7Zp0yaZMrdu3cp8fX1Z//79maqqKtPV1WWvvvoq\nW716Nbt3755MXr5z3N77qL3zv3nzZjZmzBimra3NlJWVmbm5OXN3d2c//vgja2xslDvuCRMmsN69\nezMdHR02bdo0dvHixQ6vYdL9evJnFCGEkCejOz9LuP+v4LnAcVyHz3DrTJ5/KrFYDDc3N0REROCr\nr7561s0hhBDykJ78GUUIIeTJ6M7PErrnjxBCCCGEEEJ6AAr+CCGEEEIIIaQHoOCPEEIIIYQQQnoA\nuuePEEIIeULoM4oQQsjjonv+CCGEEEIIIYQ8Fgr+CCGEEEIIIaQHoOCPEEIIIYQQQnoACv4IIYQQ\nQgghpAeg4I8QQgghhBBCegAK/gghhBBCCCGkB6DgjxBCCCGEEEJ6AAr+CCGEEEIIIaQH6FTwd/Hi\nRUydOhVaWlrQ1NTEG2+8gYsXL3a4X0REBAQCAe8/FRWVx248IeTFIhAIMGbMmGfdDBkBAQEQCAQo\nLy+XSb9x4waCgoJgbm4OBQUFCAQC1NXVITY2FgKBAHFxcd3SHsn/N9PS0rqlfEIIIYT0XIodZbh1\n6xbc3NygoqKC+Ph4AMCXX36JMWPGID8/H6qqqm3u++6778LDw0MmraGhAe7u7pg8efJjNp30VKWl\npbCwsIC/vz82bNjwrJvzXBMIBHBxcUFKSsqzbooUx3HPugkyOI7jbdOnn36KX3/9Fd7e3ggMDIRA\nIIBQKGx3H0IIIYSQ51mHwd/69etRUlKCoqIiWFhYAAAGDx6Ml156CT/99BPmzZvX5r59+vRBnz59\nZNI2btyI+/fvw9/f/zGbTnoqyZdu+vLdOdRP7Vu8eDHCwsJgYmIik753715YW1tjx44dMulTpkyB\nk5MTjIyMnmYzCSGEEEIeW4fTPpOSkuDo6CgN/ABAJBJh5MiR2LVrV5crjIuLg5GRESZOnNjlfQkB\nAMaYzH8JeRxGRkawsrKCoqLsb2EVFRW8AZ6GhgasrKygoaHxtJpICCGEEPJEdBj8FRQUYNCgQXLp\nAwcOxJkzZ7pU2cWLFyEWi/Gvf/0LAgGtNdNVYrEYAoEAkZGREIvFcHZ2hrq6OvT09ODn54fKykre\n/XJzczFt2jQYGhpCKBTC0tISCxYsQGNjY5vlp6enY9y4cdDU1ISOjo40T11dHcLDw2FjYwNVVVXo\n6upixIgRWLZsmVy9KSkp8PDwgK6uLlRUVGBjY4MlS5agublZJl/re6j2798PJycnqKmpQU9PDwEB\nAaipqZHJK/khIi4uTuY+0s7cI9XS0oL169fDyckJGhoaUFNTw8CBA/Hxxx/jxo0b0nyHDh1CYGAg\nrKysoKamBg0NDYwcORLbtm2TK7O0tBQCgQCBgYEoKCjA5MmToaOjA4FAgPr6+nbbk5iYiOnTp8PC\nwgKqqqrQ0dHB+PHjcfDgQbm87d1r1vrctf679WvJv9b7NzQ04IsvvsBLL70EoVAIAwMDTJ06Ffn5\n+R32ZWtduS4elpOTgzlz5sDGxgaamppQU1PD8OHDsW7dOt782dnZmDJlCkxNTSEUCmFoaAgnJyes\nWbNGJl9RURH8/PwgEokgFAqhp6eH4cOHIyIiQibfw/f8Sf4GZPsuMDAQQPvnobPXPABUV1fj7bff\nhr6+PtTU1ODs7Ez3+RFCCCGkW3U47bO2thba2tpy6To6Oqitre1SZZs2bUJLSwtN+XxMGRkZWLx4\nMSZNmoTQ0FBkZWVh06ZNOHLkCLKysmSCtcTERMyYMQNCoRDe3t4wMjJCTk4OYmJikJKSgrS0NPTq\n1Uum/CNHjiA6Ohrjxo1DUFAQqqurAQBVVVVwdnbG+fPnYW9vj5CQEDQ1NeHUqVOIiYnBJ598Ii1j\n9erVmDt3LgwMDODj4wNtbW0cPnwYYWFhOH78OBISEuSOKykpCcnJyfDy8sKoUaOQmpqK+Ph4FBcX\n4/DhwwCAoUOHIjQ0FCtWrICtrS28vb2l+5ubm7fbby0tLXjjjTewa9cuiEQiBAQEQEVFBX///TfW\nr1+PgIAAaGlpAQCWLl2KkpISODo6ok+fPrh+/TqSkpIwY8YMVFRUIDQ0VK788+fPw8nJCUOHDsU7\n77yDqqqqDn/k+OKLLyAUCjFmzBgYGRnhypUr2LlzJyZOnIjff/8dPj4+cvu0N41Tsq1fv35YuHAh\nIiMjpccqMXToUADA7du34erqihMnTmDEiBHw9fVFeXk5tm3bhr179+LPP/+Es7Nzu+0HunZd8Fm/\nfj2Sk5Ph4uKCSZMm4ebNm9i3bx/mzJmDoqIi/PDDD9K8ubm5GDlyJNTV1TF58mQYGxvj2rVrOHny\nJOLj4zFnzhwAwOXLl2Fvb4/m5mZMnjwZIpEItbW1OHv2LH766Se5ALB1n/r4+KBfv35yfWdra9vm\nPkDXrvmGhga4uLjg3LlzcHV1hZOTEwoLCzFhwgS4urp22OeEEEIIIY+EdUBJSYmFhYXJpX/xxRdM\nUVGxo91lWFtbs+HDh7e5vRPN6VSe1lJS8Ez/PUkpKSmM4zjGcRzbsGGDzLbw8HDGcRwLCQmRplVX\nVzN1dXXWv39/VlFRIZN/6dKljOM49t133/GWv3HjRrn6fXx8GMdx7JtvvpHbduXKFenr06dPM0VF\nRebo6Mjq6+tl8gUHBzOO49j27dulaRs2bGAcxzElJSV29OhRaXpzczMbM2YM4ziOHTt2TJpeWlrK\nOI5jgYGBbXUVrxUrVjCO45inpye7e/euzLb6+nrW0NAgU8fDGhsb2ZAhQ5impia7deuWNL2kpETa\nb4sWLepSm/jqqaqqYn379mWWlpYy6ZJ+iouLk9tHcu4iIyNl0jmOY2PGjOGte+HChYzjOPbOO+/I\npB88eJBxHMcsLS1ZS0tLh8fQ2euirfaUl5fL7Xf//n3m7u7OFBQUWFlZmTR93rx5jOM4lp+fL7dP\nTU2N9LXkXCclJbWbjzHG/P39GcdxMvW01VbG+M9DV695yfs1NDRUJu+vv/7KOI5jAoGApaamytVN\nnn9d/YwihBBCHtadnyUdzr3U1tbmHeGrqamRGWHqyPHjx1FYWNjhqF9ERIT0n1gs7nT5PYm1tbXM\nSA4AzJ8/H1paWti0aZM0LT4+Hg0NDYiJiZG7d+njjz+Gvr4+tmzZIle+nZ0dZs2aJZNWWVmJnTt3\nwtraGmFhYXL7GBsbS1//9NNPaG5uxsqVK6Guri6T75tvvgHHcbz1vvnmm3B0dJT+LRAIpNdLdna2\nNJ094r1+69atQ69evbBmzRq50U51dXX07t1b+jffKKKqqir8/PxQX1+P48ePy203MTHh7Zv28NUj\nGTkqLi6We/zAkxQXFwdlZWV88803Mulubm7w9PREcXEx0tPT2y2jK9dFW0xNTeXSFBQU8O6776Kl\npYV3pVLJqput8c1Q6Gy+x9XVa37Tpk1QUVHBV199JZM3MDAQAwYMoPtZCSGEkB5ELBbLxEDdqcNp\nnzY2Njh9+rRc+pkzZzBw4MBOVxQXFwclJSW8+eab7ebr7gP+Jxg5cqRcmqqqKmxtbSEWi1FeXg4z\nMzNkZmYCANLT03nPoaKiIs6dOyeXbmdnJ5cmCb7c3Nw6XD0yMzMTHMdh9+7d2LNnj9x2oVDIW+/w\n4cPl0iSrxba+H+9RNDQ0oLCwEAMHDuxweigA1NfX49tvv8WuXbtw4cIF3L59W2Y73/2VgwcPhoKC\nQpfaVVlZicWLF2Pv3r24dOkS7ty5I7O9oqICZmZmXSqzM+rr61FWVobBgwfDwMBAbruLiwuSk5OR\nn5/f7tTPrlwXbWlqasLKlSuxdetWFBYWyt2L2rqvfX19sXLlSowYMQIzZ87E2LFjMWrUKOjr68vs\n4+XlhQULFsDHxwe+vr4YP348nJ2d0bdv30dqY0e6cs3X19ejtLQUtra2vD+gOTo6orCwsFvaSQgh\nhJDnj6urq8xtH5I1HLpDh8Gfl5cXPv30U5SUlKBfv34AHixwcfToUSxZsqRTldy9exdbtmzBa6+9\nBl1d3cdrMeH9sg4AhoaGAB4svgFAulDKypUr2yyL7wu7pJzWJGU+vBw+n5qaGjDGsGjRojbrvHXr\nllw63+qJkhUY+RbM6IqutP/u3btwcXHByZMnYWdnh7feegs6OjpQUFBAbm4udu3ahaamJrn9+Pqt\nPTU1NbC3t8fly5fh7OwMT09PaGpqQiAQICUlBampqbz1PAmShWjaarNkpLijBWu60q9tmTJlCvbu\n3YuXX34Zs2bNgr6+PhQVFVFSUoK4uDiZPhgxYgQOHTqE6Oho/PLLL1i7di04jsPo0aPx3XffSX9A\nEIlEyMjIQEREBLZt24bY2FgAwLBhw7B48WKMHz/+kdvLpyvXvKRPHw5YJbp6HRFCCCGEdFaHwd+7\n776L1atXY/LkyYiKigIAhIeHw8zMDO+//740X1lZGfr374+FCxciPDxcpow9e/agtraWFnp5Qq5e\nvcqbXlVVBQDQ1NQE8L9g6ty5c7Cysup0+XwBoWQhlCtXrnS4v4aGBgQCARoaGnin3T0Lkj7pTPt3\n7dqFkydP4r333sOPP/4os23JkiVtPuKkqyNf//nPf3Dp0iVER0dj/vz5MtsqKiqQmpoqkyZZPOb+\n/ftyZUmCsM6SXBuSa+ZhkvSOHmfQleuCT1ZWFvbu3YvXXnsNycnJMtu2bt3Ku6Lm6NGjMXr0aNy+\nfRsZGRnYuXMnfvrpJ7i7u+PcuXPSH5heeeUVJCQk4N69e8jKykJycjJWrVoFLy8v5OXlYcCAAY/U\nZj5dueYlfSpZSOlhbZ0TQgghhJDH1WHwp6qqikOHDmHevHmYPXs2GGMYN24cli9fDlVVVWk+xhha\nWlp471WJj4+Hrq4uXn/99Sfb+k5wdf3n3TvDdx9WY2Mj8vLyoK2tLZ0m6ODggMTERGRkZHQp+ONj\nZ2cHjuNw8OBBtLS0tLuKpYODA3Jzc5GZmQkXF5fHqpePZGplV0YD1dTU8PLLL6OoqAhlZWXtTv0s\nLi4G8GDU+2FHjhzpYmvb1lY9jDFkZGTI5Zfcq3bp0iW5bbm5ubx1cBzH208aGhoQiUQoLCzE1atX\n5UaTJYHnwytcPqwr1wUfSR94enrKbeuor1VUVODm5gY3NzcoKChgxYoVOHr0KCZNmiSTr1evXnBy\ncoKTkxMMDAwwb9487Nu374kGf1255iV9f+7cOVy/fl1mNgRjDEePHn1i7SKEEEIIaa1T39RMTU2x\nfft21NXVob6+Hjt27JC7D0kkEqGlpUVuAQMA2LlzJ6qrq+UeokweTWFhITZs2CCTFhMTgxs3bsgs\n1BIYGAg1NTWEhYWhqKhIrpy6ujrk5eV1qk5DQ0P4+PigsLAQixcvltt++fJl6esPP/wQCgoKCAkJ\nQUVFhVzeqqoq3nv+OksSBHV1MZSgoCDcv38fc+bMwb1792S21dfXS+81kwSGDwfZO3bs4L2f61G1\nVc/y5cuRn58vN5IoCbS2bNkiMxXy77//xooVK3jr0NHR4Q0WAcDf3x9NTU1yI/VisRh79uyBpaUl\n7/2lrXXluuDTVh8cO3YMP//8s1z+jIwM3L17Vy5dcl+gZNQtNzeXd8qqJJ+Kikq77eqqrl7zs2fP\nxp07d/D111/L5NuwYQOKiooe+f5JQgghhJD2UDT2ApowYQKCgoKQnJwMKysrZGdn48CBA7CwsJBZ\nMEdfXx+bN2/G9OnT8corr8DDwwOWlpZobGxESUkJUlNTERAQgLVr13aq3rVr1yI/Px/h4eFISkqC\ni4sL7t69i4KCAuTm5uLatWsAgEGDBmHVqlUIDg6GlZUVPD09YW5ujtraWpw/fx7p6emIioqCtbX1\nIx2/mpoa7O3tkZaWBj8/P1haWkIgEMDPz6/dxVHmzJmDgwcPYteuXbCyssLrr78OVVVVXLhwAX/+\n+SeOHDmCwYMHY9KkSTAzM8OSJUtQUFCAAQMGoKCgAPv27YOPjw8SExMfqd0Pmz17NpYsWYLg4GCI\nxWKYmJggOzsbmZmZ8PT0lJsGaWxsjJkzZ+K///0vhg8fjokTJ+Lq1avYuXMn3N3deZ+dOHbsWGzb\ntg0+Pj6wtbWFgoICJk+ejFdeeQWff/459uzZg/Xr1+P06dMYPXo0Ll26hG3btkFVVRW//vprp46j\ns9cFHwcHB9jZ2WHLli2orKyEnZ0dLly4gN27d8PLy0vumJYsWYLU1FSMHj0aIpEISkpKyMzMRHp6\nOoYPHw43NzcADxaY+uWXX+Ds7AwLCwuoq6sjPz8f+/btg7m5OXx9fTt1bJ3V1Wv+3//+N7Zv345V\nq1YhPz8fjo6OKCoqwp49ezBhwgTs37//ibaPEEIIIQTA8/VAos405zlr8lPV+lluYrGYOTs7s969\nezNdXV3m5+cn9yw/iTNnzrCAgABmamrKlJSUmL6+Phs+fDgLCwtjhYWFvOW3pba2loWFhTErKyum\nrKzM9PT0mKOjI1u+fLlc3oyMDDZt2jRmbGzMlJSUmLGxMXN0dGSLFi1iFy9elOaLjY1lAoGgS8+v\nKyoqYp6enkxbW5sJBIJOPxetubmZrVu3jr366qusd+/eTE1NjdnY2LBPP/2U3bhxQ5qvuLiY+fj4\nMH19faaurs5Gjx7N9u/fz9tWyXP+uvrcQcYYy83NZePHj2fa2tpMU1OTubu7s+zsbBYREcF7TLdv\n32ahoaHMyMiICYVCZmtry3777TcmFot5+6myspJNnz6d6evrMwUFBbm237x5ky1YsIBZWloyJSUl\npqenx9544w3e5+i1p7PXBd+z86qqqlhAQAAzMTFhqqqqzM7Ors1j2rdvH/P392cDBgwlsTy+AAAg\nAElEQVRg6urqTFNTkw0ZMoRFR0ezmzdvSvNlZmay999/nw0aNIhpaWmx3r17s4EDB7LPP/+cVVdX\ny9QfEBDABAJBp5/z19712tlrnrEHz+F86623mJ6eHuvduzcbNWoUS01NbfPckxdDT/6MIoQQ8mR0\n52cJ9/8VPBc4juvw+VadyfNPJRaL4ebmhoiICN7ptYQQQp6tnvwZRQgh5Mnozs+Srq3OQAghhBBC\nCCHkhUTBHyGEEEIIIYT0ABT8EUIIIYQQQkgPQPf8EUIIIU8IfUYRQgh5XHTPHyGEEEIIIYSQx0LB\nHyGEEEIIIYT0ABT8EUIIIYQQQkgPQMEfIYQQQgghhPQAFPwRQgghhBBCSA9AwR8hhBBCCCGE9AAU\n/BFCCCGEEEJID0DBHyGEEEIIIYT0ABT8EUIIIYQQQkgPQMEfIW2IiIiAQCBAamrqs27KC6e0tBQC\ngQCBgYHPuikyXF1dIRDI/2/v8uXLePPNN9GnTx8IBAJoa2sD6P5rICAgAAKBAOXl5d1SPiGEEEJI\naxT8kRfO0wosOI6T/nvePa/B1vPWd22dT39/f2zduhXjxo3DwoULERYWJpO/O4/jeesjQgghhPxz\nKT7rBhDSVZIvy939pTk4OBgzZ86Eqalpt9bzJDytPnnRxcfH4/bt2zJpTU1NSElJwcSJExEXFyez\n7WlcA4yxbiubEEIIIaQ1Cv7IC0fyZbm7vzTr6upCV1e3W+t4Up5Wn7zo+IK4qqoqMMZgaGgot+1F\nugYIIYQQQjpC0z5fIGKxGAKBAJGRkRCLxXB2doa6ujr09PTg5+eHyspK3v1yc3Mxbdo0GBoaQigU\nwtLSEgsWLEBjY2Ob5aenp2PcuHHQ1NSEjo6ONE9dXR3Cw8NhY2MDVVVV6OrqYsSIEVi2bJlcvSkp\nKfDw8ICuri5UVFRgY2ODJUuWoLm5WSZfbGwsBAIB4uLisH//fjg5OUFNTQ16enoICAhATU2NTF4L\nCwsAQFxcHAQCgfRfWlpau/1XX1+PmJgYODs7w8jICMrKyjA3N8cHH3yAqqoqufyS+71al9uZPmrL\nr7/+Ci8vL5ibm0MoFEJfXx/e3t7IycnpVN0P91d8fHyX+uTq1asIDg6Gubk5lJWVYWJigoCAAJSW\nlnbY9tYqKioQGhoKS0tLqKiowMDAAK6urnKjZnwOHTqEwMBAWFlZQU1NDRoaGhg5ciS2bdvGm//A\ngQOYMGECjI2NIRQKYWxsDDc3N2zdulUmX3Z2NqZMmQJTU1MIhUIYGhrCyckJa9askcn38D1/rq6u\nEIlEAGT77uuvvwbQ/nlISEiAq6srNDU1oaqqimHDhmH9+vW8x1FSUoKpU6dCS0sLmpqacHd3R35+\nfof9RQghhBDyJNHI3wsoIyMDixcvxqRJkxAaGoqsrCxs2rQJR44cQVZWlkwgkpiYiBkzZkAoFMLb\n2xtGRkbIyclBTEwMUlJSkJaWhl69esmUf+TIEURHR2PcuHEICgpCdXU1gAcjJM7Ozjh//jzs7e0R\nEhKCpqYmnDp1CjExMfjkk0+kZaxevRpz586FgYEBfHx8oK2tjcOHDyMsLAzHjx9HQkKC3HElJSUh\nOTkZXl5eGDVqFFJTUxEfH4/i4mIcPnwYADB06FCEhoZixYoVsLW1hbe3t3R/c3PzdvvtzJkziIyM\nxNixY+Hr6wsVFRXk5eXh559/xv79+3HixAloaWl16hy01UftCQ4OxrBhw+Du7g5dXV2UlJRg165d\n2LdvH8RiMRwcHDpV98M60ydXr16Fg4MDysrKMGHCBMyaNQvnzp3Dxo0bkZycjPT0dAwYMKDDus6e\nPYsxY8bg6tWrcHNzg6+vL+rr65GTk4OVK1fC39+/3f2XLl2KkpISODo6ok+fPrh+/TqSkpIwY8YM\naVApsWfPHnh5ecHExATe3t7Q1dVFRUUFsrOzkZCQgOnTpwN48OPGyJEjoa6ujsmTJ8PY2BjXrl3D\nyZMnER8fjzlz5si0ofXU2MDAQAwdOlSu71xdXds9js8++wzLli2DSCTCzJkzoaqqiv379+P999/H\n2bNn8f3330vzXr58GSNHjkRlZSW8vLxgY2ODEydOYPTo0RgyZEiHfU4IIYQQ8sSw50hnmtPVJgN4\npv+epJSUFMZxHOM4jm3YsEFmW3h4OOM4joWEhEjTqqurmbq6Ouvfvz+rqKiQyb906VLGcRz77rvv\neMvfuHGjXP0+Pj6M4zj2zTffyG27cuWK9PXp06eZoqIic3R0ZPX19TL5goODGcdxbPv27dK0DRs2\nMI7jmJKSEjt69Kg0vbm5mY0ZM4ZxHMeOHTsmTS8tLWUcx7HAwMC2uopXXV0dq62tlUvftGkT4ziO\nRUVFyaQvXLiQcRzHUlNTpWkd9VF7SktL5dLOnj3L1NXV2bhx4zqsW0LSX3FxcTJlt9cn/v7+jOM4\ntmjRIpn0X3/9lXEcx8aMGdOpYxg2bBjjOI5t2rRJblvra6CkpIS3PXx90NjYyIYMGcI0NTXZrVu3\npOk+Pj5MKBSy6upquX2uX78ufT1v3jz2f+zdeVxUVf8H8M8dkE0YdskVVFRSTHHDJWXcyjQX0Fwe\nFbFMs1Cj3M0tLbc0H1utXNPKNHPJX2UugJhbLmgqmiZqiqKogKCs398fNPMwzjAMCILO5/16+WI4\n99xzzj0z4/Cdc885iqLI8ePHDfLdunVL7/egoCBRqVQGbSqo74w9D7/88osoiiLBwcGSkZGhS8/K\nypJevXqJoihy6NAhXfrgwYNFURT58MMP9cqeNm2aKIoiKpVKLl68aFA3PZ7K2ccqERE9hkrzs4S3\nfT6G/Pz8EBYWppc2ceJEuLi4YM2aNbq01atX4+7du5g7dy6eeuopvfxvvfUWPD098d133xmU36xZ\nMwwaNEgv7dq1a9i0aRP8/Px0KyHmV7lyZd3jpUuXIicnB0uWLIGTk5Nevvfeew+Kohit9z//+Q9a\ntWql+12lUulGkv744w9duhRzXptarTY6svef//wHTk5O2Llzp9llGeujwhgbmfTz84NGo8GePXuQ\nnZ1dpPLyM9UnGRkZWLduHby8vDB+/Hi9Y0OHDkWDBg0QGRmJy5cvm6zjwIEDOHr0KDp16oSBAwca\nHM//GiiIsT5wcHBAaGgoUlJScPDgQb1j1tbWsLY2vEHB2G22dnZ2BmnaLRtMKerr6ZNPPoFKpcLS\npUthY2Oj19ZZs2YBgO621IyMDKxfvx5VqlTBqFGj9MqZMGGC2SPNRERERCWBt30+htq0aWOQ5uDg\ngMaNGyMyMhKXLl1CjRo1cODAAQBATEwM/vzzT4NzrK2tERcXZ5DerFkzgzRt8NWhQ4dCV5Q8cOAA\nFEXB1q1b8dNPPxkct7OzM1pv06ZNDdKqVq0KALhz547JOs21c+dOLF68GAcPHsStW7f05h8mJCSY\nXY6xPirMuXPn8P7772P37t1ISEhAZmam7piiKEhKSjK66MjDOnPmDDIyMhAYGKgXrGgFBQXh5MmT\nOH78uMlVLQ8dOgQAeO6554rdlpSUFMyfPx+bN2/G33//bbDyZv55q/3798emTZvg7++PAQMGoEOH\nDmjdujWcnZ31zunbty+WLFmCli1bYsCAAejYsSOeffZZeHp6Frudphw4cACOjo4G8wkBICsrCwB0\nr++zZ88iIyMDLVq0gJWVlV7e/O9ZIiIiokeBwd9jqFKlSkbTtYFDcnIyAOgWSlmyZEmBZRkL5IwF\nINoyq1SpUmj7bt26BRHRjYIYqzM9Pd0gXa1WG6RpR30eXCSmONatW4cBAwboFtzw8fGBvb09RASL\nFy9GRkaG2WUVNUj766+/0KJFC9y9exedO3dG79694ejoCJVKhR9//BGxsbFFqr8oUlJSABTcZu2o\nsDZfQYryGjAmMzMTQUFBiI2NRbNmzfDyyy/Dzc0NVlZWOHr0KDZv3qzXB3379kWFChWwaNEifPjh\nh1i4cCGsra3RpUsXfPjhh6hduzYAoGXLlti1axfef/99fPXVV/j000+hKAratWuHDz74wOiXCg9D\n+6WBdlGYB+V/fWv7rKBAtDSCfSIiIqKCMPh7DCUmJhpN165YqR0Z0QZTcXFxqFu3rtnlGwsItben\nXb16tdDz1Wo1VCoV7t69a/RWvLLy7rvvwsHBAYcPH9atjqk1b968IpVV1P30Fi9ejOTkZHzzzTfo\n37+/3rF9+/YhNjZWL027IqWxW0G1AYW5tK8DYyua5k83Fnznp30NXLlypUj1a23evBmxsbEYPnw4\nPv/8c71j8+bNw+bNmw3OCQ4ORnBwMFJTU7Fnzx58//33WL16NeLi4nDy5EndYkXt2rVDu3btcO/e\nPezbtw+bNm3C0qVL0aVLF8TFxZXodg1qtRq2trZmvRe078WCFgQq6DkhIiIiKg1P/Jw/ESnTf6Uh\nJibGIC0tLQ3Hjh2Dq6sratSoAQC61SP37dv30HU2a9YMiqJg586dyM3NNZk3MDAQubm5uttOS5r2\n9rmijgaeP38e9evXNwj8jhw5gvv375dY+wqqW1EU9OjRQy/9/v37OHLkiEEwqZ2r9s8//xiUdfTo\nUYM0U33i5+cHW1tbHDx4UO9WU63o6GgoilLoypMtWrQAAGzfvt1kvoKcP38eAAz6AMhbPdUUJycn\ndO3aFStXrkSPHj1w7tw5o7cO29vbo0OHDliyZAlef/11JCUlFVp2UQUGBuLatWu4ePFioXnr1q2r\n6/sHA3nte7aoXyQQERERFdcTH/w9ic6cOYMVK1bopc2dOxd37tzRW4Rk6NChcHR0xKRJk3D27FmD\ncpKTk3Hs2DGz6vTy8kJwcDDOnDmDOXPmGBzPPxr0+uuvw8rKCqNGjTI6j+769etG/3A3lzYwunTp\nUpHO8/b2xtmzZ/VGYVJSUvS2Fygt3t7eEBG9wF1EMGnSJKOjQtpAa/Xq1XpfIuzbtw9r1641yG+q\nT2xsbNC/f39cu3bNYD/GVatW4cSJE9BoNKhWrZrJa2jevDmaNGmCnTt3Gm1DYSOC2sVeHvzyYuPG\njUbnhu7Zs8fgi4bc3FzcvHkTiqLoRpX37dtnNKjVzh+0t7c32a6i0i7c8sorrxgdhY2Pj9cFhra2\ntujbty+uXr2Kjz76SC/fvHnzSmwuKxEREZE5eNvnY+i5557DyJEjsW3bNtStWxd//PEHduzYgVq1\namHGjBm6fJ6enli7di369euHhg0bomvXrvD19UVaWhouXLiAqKgohIWF4dNPPzWr3k8//RTHjx/H\n1KlTsWXLFgQFBSEzMxMnT57E0aNHcfPmTQCAv78/PvroI4SHh6Nu3bro1q0bvL29cfv2bZw7dw4x\nMTGYPXs2/Pz8inX9jo6OaNGiBaKjoxEaGgpfX1+oVCqEhobqRj2NCQ8Px5gxY9CkSROEhIQgIyMD\nv/zyC6pWrYoqVaqU2kgtAIwYMQIrVqxASEgI+vXrB7VajT179iA+Ph4ajcZg0Y/AwEC0adMGu3bt\nQqtWrdC2bVtcvHgRW7ZsQY8ePfDjjz/q5S+sT+bPn4+oqChMmTIF0dHRCAgIwJkzZ7Bp0yZ4eHjg\ns88+M+s61qxZA41Gg8GDB2PFihVo3rw5UlNTcezYMaSnp+PIkSMFntu9e3fUqFED8+bNw8mTJ1Gv\nXj2cPHkSv/76K4KDgw2uadSoUbh+/TratGmjC553796N2NhYdO/eHXXq1AGQF0RFRUWhXbt28PHx\ngY2NDQ4cOICYmBg0bdoUHTp00Cv3YZ/nF154AZMmTcKcOXNQp04dPP/886hatSpu3LiB06dP48CB\nA/j22291we6cOXPw22+/4e2330ZkZKRun7/9+/ejbdu2uj0siYiIiEpdKW0hUSzmNKecNfmR0u4x\nN3PmTImMjJS2bdtKxYoVxd3dXUJDQw328tM6deqUhIWFSfXq1cXGxkY8PT2ladOmMmnSJDlz5ozR\n8gty+/ZtmTRpktStW1dsbW3Fw8NDWrVqJYsXLzbIu2/fPnnppZekcuXKYmNjI5UrV5ZWrVrJrFmz\n5PLly7p8K1euFJVKpbdvXWFtOnv2rHTr1k1cXV1FpVKJSqUyuifegz755BOpX7++2NvbS40aNSQi\nIkJSU1PFx8dHatasqZd3xowZBuWa00cF2blzp7Ru3VqcnJzEw8ND+vTpI+fOnZOwsDCje70lJSXJ\nkCFDxN3dXRwcHKR169by22+/FdhfhfVJYmKihIeHS40aNXTPx5AhQ4zuvWfKlStX5I033hAfHx+x\nsbERLy8vad++vd6+hwXt83f+/HkJDg4WT09PcXJyknbt2sn27duNXtO6deukb9++Urt2bXFwcBB3\nd3dp3ry5fPzxx5KVlaXL9+uvv8qQIUOkXr164uTkJM7OztKoUSN5//33JTU1Va9+jUZjsM9fQW0V\nMf4a0Pr555+lW7du4uHhITY2NlKtWjXRaDSyaNEiuXnzpl7ev//+W3r37i3Ozs6iVqulS5cucuLE\niQKfe3p8WfJnFBERlYzS/CxR/q2gXFAUpdBv5c3J86SKjIxEhw4dMGPGDEybNq2sm0NERA+w5M8o\nIiIqGaX5WcI5f0RERERERBaAwR8REREREZEFYPBHRERERERkATjnj4iIqITwM4qIiB4W5/wRERER\nERHRQ2HwR0REREREZAEY/BEREREREVkABn9EREREREQWgMEfERERERGRBWDwR0REREREZAEY/BER\nEREREVkABn9EREREREQWgMEfERERERGRBWDwR1TCtm3bhsDAQKjVaqhUKkRERJjM7+Pjg5o1a5pd\n/owZM6BSqRAVFVXsNsbHx0OlUmHo0KHFLqM8unPnDkaOHAlvb29YWVlBpVIhOTkZK1euhEqlwqpV\nq8wqJzIyEiqVCjNnzizlFlNJ02g0UKn40UZERGSMdVk3gOhJcv78eYSEhMDT0xOvvfYaHB0d0bJl\ny0LPUxTF7DoURdH9e1glUUZ5MnbsWCxfvhy9evXC0KFDoVKpYGdnBwDF6rMnrX8sBZ83IiIi4woN\n/i5fvoyIiAjs2LEDIoJOnTph8eLFqF69ulkVnD59GtOmTUNkZCTS0tJQo0YNvP766xg9evRDN56o\nvNm1axeysrKwaNEi9O3bt1TqCA8Px4ABA8x+D1qSn3/+GX5+fti4caNeekhICFq3bo2nnnqqjFpG\nREREVPZMBn/p6eno0KED7O3tsXr1agDAO++8g/bt2+P48eNwcHAwWfgff/yBDh06oEOHDli2bBmc\nnZ1x9uxZpKWlldwVEJUjCQkJAAAvL69Sq8Pd3R3u7u6lVv7jLCEhAfXq1TNIV6vVUKvVZdAiIiIi\novLD5MSIL7/8EhcuXMCmTZvQo0cP9OjRA1u2bMHFixexdOlSkwXn5uYiNDQUnTt31p0fFBSEV199\nFW+++WaJXoSlyMrKwpIlS9C5c2dUrVoVtra2qFKlCgYOHIhz584ZPef+/ftYsGABmjRpAicnJzg7\nOyMgIABTp05Fdna2Xt4jR46gX79+qFy5Muzs7FC9enWEhIRg7969ujxhYWFQqVS4dOmSQV3auWjR\n0dG6tPxzp2JiYtCpUyc4OzvDzc2t1K4pNTUVTk5OaNiwodHz7927BxcXF/j5+Znu8H8lJiYiPDwc\n3t7euvaFhYUhPj5el0c7h27GjBkAgPbt20OlUhXYV8akpaVhzJgxqFKlCuzs7NCoUSP88MMPBvmM\n9TMA3L17FxEREahSpQocHBzQtGlTbNiwodD5bufOnUNwcDBcXV3h6OiIzp074/jx42a1WSshIQFj\nxoyBr68v7O3tUalSJWg0GoM6s7KyMH/+fPj7+8PBwQFubm544YUXDK4F+N9rLT4+HkuWLIGfnx/s\n7Ozg4+ODd999FyJikBf432su/5zGgvogOzsbs2fPRs2aNWFvb4/69evjiy++MHmtR48exUsvvQQv\nLy/Y2dnB19cXkydPNvhSK/9r/48//kDnzp3h5OQEFxcXhISE4OLFi0bLN+d9CAAZGRlYsGABGjVq\nhIoVK8LFxQWdO3c22pcFuXPnDqZMmQI/Pz84OjrCxcUF9erVw6uvvopbt27p8l29ehXTpk1DixYt\n4OnpCTs7O9SpUwfjxo3D3bt3DcrVzrvLyMjAhAkTUK1aNVSsWBHPPvssDh06BAC4dOkS+vfvD3d3\ndzg6OiIkJATXrl3TKyf/3NTjx4+jS5cucHZ2hrOzM3r16oWzZ8+afa1F6a+rV68iPDwcvr6+utdp\nw4YNMXr0aIP/N4mIiB4rYkKHDh3k2WefNUgPCgqSoKAgU6fKzp07RVEUiYmJMZkvv0KaY3aeJ1VC\nQoJYW1tLx44dZeTIkTJx4kTp1auXWFtbi5ubm1y4cEEvf1pamrRs2VIURZEGDRrIW2+9JW+//bZ0\n7dpVbG1tJTk5WZf3u+++kwoVKoi9vb30799fJk+eLEOHDhVfX1+JiIjQ5RsyZIioVCq5ePGiQfum\nT58uiqJIVFSULm337t2iKIp07txZbGxspGvXrjJhwgR5+eWXS/WaXn31VVEURQ4cOGDQztWrV4ui\nKLJgwYJC+/z69evi4+MjiqLI888/L5MnT5aQkBBRqVTi4eEhcXFxIiJy584dmTFjhmg0GlEURYYO\nHSozZ86UmTNnyp07d0zW4e3tLVWrVpXWrVtL/fr1ZfTo0fLKK69IxYoVRaVSyfbt2wvt5+zsbGnb\ntq0oiiItWrSQyZMny5AhQ8TOzk5efPFFURRFVq1apct/4cIFURRFNBqNeHh4iEajkbFjx0qvXr1E\nURRxc3OT69evF9o/IiKnTp0SLy8vURRFOnbsKJMmTZI33nhDWrZsKU2aNNHly8nJkW7duomiKOLv\n7y8TJkyQYcOGiZOTk1hZWcl3332nV+6QIUNEURTp06ePeHp6yssvvyxvvvmmeHt7i6IoMmXKFF3e\nTZs2yYwZM0RRFKlZs6au7zdv3iwiIitWrDDoAxGRwYMHi6IoUq9ePRk/frwMHz5c1Gq1rp0zZ87U\ny79x40axsbERtVotoaGhMn78eOnYsaMoiiItW7aUzMxMXV7ta79bt27i4OAgL774oowbN06X39fX\nV+7fv69Xvrnvw3v37ume78DAQImIiJBXX31VKlWqJNbW1rJx48ZCn7fc3Fxp3ry5qFQqeeGFF2TC\nhAny1ltvSa9evcTJyUlOnjypy/vtt9+Kk5OTBAcHS0REhLz11lvSunVr3estKytLr+ygoCBRFEV6\n9uwpdevWlTFjxsigQYPE2tpanJ2dJTY2VqpUqSLt2rWTsWPHSqdOnURRFIPPFe3rtF27duLs7CzP\nP/+8TJkyRXr37q17D547d86gbpVKpZdWlP66e/eueHt7i42NjYSEhMikSZNk9OjR0qVLF7Gzs5O0\ntDST/WrJn1FERFQySvOzxGTJXl5e8tprrxmkjxw5Ujw9PU0WPHPmTFEURX777TcJDAyUChUqSKVK\nlWT06NFy7949441h8GdSRkaGJCQkGKRHRUWJtbW1DBs2TC89IiJCFEWR4cOHG5yTmJgo2dnZIpIX\ngDk4OIiLi4ucOnXKIO/Vq1d1j7V/kBc1+FMURb7++utHdk2HDh0qMF9QUJDY2NhIYmKiwbEHaa93\n1qxZeunLly8XRVGkffv2eunG+qAw2mAmODhY749o7RcoXbp0KbSOL774QhRFkZdeekkvb1RUlK7/\njQV/iqLI/Pnz9c6ZOnWqKIoic+fONav9TZo0EUVRZM2aNQbH8r92tAFYly5dJCcnR5d+8uRJ3esv\nJSVFl67t+9q1a8u1a9d06Tdv3hRXV1dRq9V6wZaIGH1O8tedvw+0/RsYGCgZGRm69FOnTomdnZ1B\n8Hfjxg1xcnKS2rVrG7xmFyxYIIqiyAcffKBLy//a//777/Xyh4aGiqIoegFvUd6HEydOFEVRZN68\neXp5bty4IT4+PuLp6Vng/7NasbGxoiiKvPXWWwbH0tPT9c6/ceOGpKenG+SbPXu20edeG/y1b99e\nL8BduHChKIoiarVaJkyYoHdOjx49RFEUOXz4sC4t/+t0+vTpevmXLVsmiqJI9+7dDep+MPgrSn9t\n3rxZFEWRJUuWGFzvnTt3JDc31yA9P0v+jCIiopJRZsGfjY2NTJo0ySB9ypQpYm1tbbLgESNG6EYQ\npk+fLlFRUfLBBx+Ig4ODBAcHG28Mg79ia9iwofj4+Oh+z8rKEicnJ/Hw8JDU1FST586dO1cURZH3\n3nuv0HqKG/w1b968CFeT52GuSUQkICBAnJ2d9f5o/euvv0RRFAkJCSn0/Pv374udnZ089dRTesGB\nlr+/vyiKIpcuXdKlFTf4U6lUEh8fb/SYh4eHXpqxOrR/8GpHIvN74YUXCgz+ateubZA/Pj5eN+JW\nmP379+tGdgujHRU9duyYwbHw8HBRFEVWr16tS9O+1lauXGmQX3vszz//1EsvSvA3dOhQURRFtm3b\nZpB/+PDhBsGfNnBZv369Qf6cnBypVKmSNGvWTJemfe1rNBqD/JGRkaIoiowdO1aXZu77MCcnR1xc\nXMTf39/o8Y8++kgURZGffvrJZDna4G/y5Mkm85mSlJSkG+nOTxv8PXjnxz///KML/h4MTtesWWPw\nfGtfp+7u7kaDz3r16omVlZUkJSXp1Z0/+Ctqf2mDvy+++MLMXtDHzygiInpYpflZUmpbPeTm5gIA\nBg8erJsH1a5dO+Tk5GDixImIi4sze85VSXjUK3/nm45Uog4fPoz58+dj7969uHHjBrKysnTHbG1t\ndY/j4uJw9+5dtGvXDo6OjibL1M7Bee6550qn0QCaNWtW4LHSuCYAGD58OF5//XWsX78eoaGhAIDl\ny5cDAIYNG1bo+WfOnEFGRgYCAwNhY2NjcDwoKAgnT57E8ePHH3rlTRcXF3h7exukV6tWDQcOHCj0\n/NjYWDg7Oxtd7KRVq1b45ZdfjJ7XuHFjg7SqVasCyJsPVpiivHZiY2OhVqvRqLBfRNcAACAASURB\nVFEjg2NBQUH45JNPjM41bNq0qUFatWrVzG6jqfYoioJnn33W4FibNm3w5Zdf6qVpn4eYmBj8+eef\nBudYW1sjLi7OIN1Y+431sbl9eebMGSQnJ8Pb21v3f2t+f/31F4C890u3bt0KLKdBgwbw9/fH3Llz\ncezYMbz44oto164dGjRoYDT/+vXrsXTpUhw7dgx37tzR/R8P/G+ho/wURTF4rrWrrdapU0e3BYeW\ndpGkq1evGpQVEBAAe3t7g/TWrVvj7NmzOHHiBIKCgoy2u6j9pdFo8NRTT+GNN97Ajh070KVLF7Rt\n2xa+vr5GyyciInqcmAz+XF1dcfv2bYP0W7du6RbsKIh2NcLOnTvrpXfu3BkTJ05EbGys0eAv/4ez\nRqOBRqMxWY+5SisYe5RiYmLQsWNHWFtb4/nnn4evry8qVqwIRVGwYsUKvYVFkpOTAQBVqlQptNyi\n5C2ugla/LK1rAoCBAwdi3LhxWLZsGUJDQ5GTk4NVq1ahWrVq6NKlS6Hnp6SkmGy79g9Zbb6H4ezs\nbDTd2tpa74/sgqSmpqJ27dpGj1WqVKnA84ytgGltnfffQk5OTqH1FuU5SUlJKbCNpvryYdtYkOTk\nZFSoUMFo+caec+0CKEuWLCmwTGP7y5nbfnP7UtuO48ePF7gwj6IoSE9PN1mOlZUVdu/ejenTp+OH\nH37Azz//DCAvMB03bpzedjwLFizAhAkT4OXlhW7duqFq1aqws7ODiGDmzJnIyMgwWseDX9JYWVkB\nMN0n+b/80SroNax9nky9B4vaX2q1Gvv27cO0adOwdetWrF+/HgBQt25dTJ8+HQMGDCiwLiIiouKI\njIxEZGTkI6nLZPDXoEEDo99wnzp1CvXr1zdZsL+/f7EaZOybWcozZ84cZGdnIyoqymDj8G+//Vbv\ndxcXFwDGv0V/kDbvlStXCv3DU7uiorEV77R/vBpT0KbLpXVNAODk5IR+/fph+fLlOHfuHOLi4pCQ\nkIB33nnHrE2gtX+gXr9+3ehxbXp52ELAyckJN27cMHosMTGx1OrN/9opjFqtLrAtZdGXzs7OuHDh\nAlJSUgzqNfaca/PExcWhbt26Jd4ec9+H2nb0798f33zzzUPV6e7ujo8//hgff/wxTp48iR07dmDJ\nkiV48803oVarERYWplsRtWrVqoiNjdX74u/69euYOXPmQ7XBHIW9bgr68gQoXn95e3tj1apVyM3N\nxbFjx/DLL7/gv//9LwYOHIinnnoK7du3L+IVEBERFezBAa/S/Gw1udVDjx49sH//fly4cEGXFh8f\nj99//x09evQwWfALL7wAW1tbg9vNtL83b968uG22WOfPn4e7u7tBkHT9+nWcP39eL027dPv+/fuR\nmppqstwWLVoAALZv315oG1xdXQEA//zzj8Gxo0ePFnr+g0rrmrSGDx8OIO92z2XLlkFRFLz88stm\nnevn5wdbW1scPHgQmZmZBsejo6ON3tpWFho3bow7d+7gzJkzBsf27dtXavUW5bUTEBCA5ORkxMbG\nGhyLiooCYPw21NLSuHFjiAj27NljcCwmJsYgLTAwEEDp9ae5fVm/fn04OTnh0KFDZo0Km6tBgwYY\nM2YMNm7cCADYunUrAODmzZtITU1Fq1atDO74eHD7idJy9OhRg5FMEcHvv/8OKyurArd1AR6uv1Qq\nFZo0aYLJkyfrtgD56aefin4BRERE5YTJ4O/VV1+Fj48PevbsiS1btmDLli3o2bMnatSogREjRujy\nXbx4EdbW1pg1a5Yuzc3NDZMmTcLnn3+OKVOmYMeOHZg7dy5mzZqFsLAw1KpVq/Su6gnl7e2NpKQk\nvXlFmZmZCA8PNxiJs7KywvDhw3Hr1i2MHTtWb080IO+bdO0tZ6GhoXBwcMCCBQtw6tQpvXwiorf3\nlvYP1JUrV+rl27Bhgy4YKg/XlL+9zzzzDJYtW4Zt27ahQ4cO8PHxMattNjY26N+/P65du4aFCxfq\nHVu1ahVOnDgBjUajm39WlrS3ok2bNk0vPSYmpsD5fiWhefPmaNKkCXbu3Im1a9caHM8/Iqiddzlp\n0iS9P8JPnz6Nr776Ci4uLujZs2eptfVBgwYNAgC8++67erctnjp1CqtXrzbIP3ToUDg6OmLSpElG\n95dLTk7GsWPHit0ec9+HVlZWeO2113D+/HmDvtQ6cOAA7t27Z7K+ixcvGt1rUFuPdk5epUqVYGdn\nh8OHD+P+/fu6fAkJCZg8eXLRLrKYbt26hXnz5umlLV++HGfPnkXXrl11X0oZU9T+On36tNGRxgf7\nhYiI6HFk8rZPBwcH7Nq1CxERERg8eDBEBJ06dcLixYvh4OCgyyciyM3NNfhjfNq0aXBycsKnn36K\nDz74AFWqVMH48eMxderU0rmaJ1x4eDh+++03tGnTBn379oW1tTV27NiBnJwcNGrUyGBEZdasWdi7\ndy++/PJL7N27F8899xxUKhXOnj2L7du3IzExEWq1Gl5eXli+fDkGDRqEpk2bolevXqhZsyYSExMR\nHR2Nbt264cMPPwQA9OzZE7Vr18bKlStx+fJlNG7cGKdPn8bu3bvRtWtX/N///V+5uKb8hg8fjvDw\ncADmLfSS3/z58xEVFYUpU6YgOjoaAQEBOHPmDDZt2gQPDw989tlnRSqvOB58XxnzyiuvYPXq1Vi/\nfj3i4+PRoUMHJCQk4Pvvv0e3bt2wbds23S27JW3NmjXQaDQYPHgwVqxYgebNmyM1NRXHjh1Deno6\njhw5AiAvuNmwYQO2bduGxo0b44UXXsDt27fx3XffISsrCytXrjRrIZ+S0r59ewwePBhff/01GjVq\nhO7duyMlJQXfffcdOnfujG3btunl9/T0xNq1a9GvXz80bNgQXbt2ha+vL9LS0nDhwgVERUUhLCwM\nn376abHaU5T34bvvvos//vgDCxYswJYtW/Dss8/Czc0N//zzDw4fPoyzZ8/i2rVrRhdJ0Tp69Ch6\n9+6Nli1bws/PD15eXrh06RI2bdoEW1tbjBo1CkDe6NfIkSPx4YcfIiAgAF27dsWtW7ewbds2aDSa\nAjdaN+d1a662bdviv//9L/bv34+mTZvizJkz+PHHH+Hu7q7rE1N1F6W/fv31V4wfP163yIubmxvO\nnj2Ln376Ca6urkX+P4SIiKhcKbV1RIvBnOaUsyY/ct9//70EBASIg4ODVK5cWYYOHSrXr18XjUZj\nsLeVSN7mxnPmzJGGDRuKvb29uLi4SEBAgEyfPt1gY+ZDhw5J7969xdPTU2xtbaVGjRrSp08f+f33\n3/XyxcfHS3BwsKjVanF0dJTOnTvL4cOHZcaMGaJSqYxu9fDgZtmP6ppE8vbmUqlU4u7ubnTLhsIk\nJiZKeHi41KhRQ2xsbKRy5coyZMgQo1szGOuDwvj4+EjNmjWNHjPWBwXVkZqaKmPGjJHKlSuLvb29\nNGnSRDZs2CAffPCBKIoimzZt0uXVLqH/4BL9WgVtmVCQK1euyBtvvCE+Pj5iY2MjXl5e0r59e4O9\nHbOysmTevHnSoEEDsbOzE1dXV+nSpYtER0cblBkWFiYqlcrotiIF9UFB7V65cqWoVCqDTd6zs7Nl\n1qxZ4uPjI7a2tlK/fn1ZunSpbisGY6/bU6dOSVhYmFSvXl1sbGzE09NTmjZtKpMmTZIzZ87o8pl6\n7Zvqf3Pfh9nZ2fLJJ59Iy5YtRa1Wi729vdSuXVuCg4Pl66+/1u15WZB//vlHJk6cKC1btpRKlSqJ\nnZ2d1KpVSwYNGiQnTpzQy5uZmSnvvvuu+Pr6ip2dnfj6+srMmTMlMzPTaJ8X9N4VKfg5MtZf+fvp\nxIkT0qVLF1Gr1eLs7Cw9e/aUs2fPGpRTUN3m9tfp06flzTfflCZNmoi7u7vY29tLnTp1ZOTIkUbf\n8w+y9M8oIiJ6eKX5WaL8W0G5oChKod8Wm5OHKL/o6GhoNBqMHj0aixcvLuvmPHKDBw/G2rVrcerU\nqUe6vQrRw4qPj0etWrUQFham26alvONnFBERPazS/CwpnfvAiMqRhQsXQlEUvXmqT6L8czO1YmJi\n8N1336Fu3boM/IiIiIgsXKlt8k5Uli5fvoy1a9fixIkT2Lp1K1566SU8/fTTZd2sUjVs2DAkJCSg\nWbNmcHZ2RlxcHLZt2wZra2uTe9MRERERkWVg8EdPpPPnz2Py5MlQq9Xo06cPPv/887JuUqnr168f\nli5dio0bNyI5ORkuLi548cUXMWnSJIOtNIiIiIjI8nDOHxERUQnhZxQRET0szvkjIiIiIiKih8Lg\nj4iIiIiIyAIw+CMiIiIiIrIADP6IiIiIiIgsAIM/IiIiIiIiC8Dgj4iIiIiIyAIw+CMiIiIiIrIA\nDP6IiIiIiIgsAIM/ohK2bds2BAYGQq1WQ6VSISIiokTLV6lUaN++vV5aWFgYVCoVLl26VKJ1PS5W\nrlwJlUqFVatWlXVTiIiIiMot67JuANGT5Pz58wgJCYGnpydee+01ODo6omXLliVej6IoZqVZGvYB\nERERUcEY/BGVoF27diErKwuLFi1C3759H2ndIvJI6yMiIiKixwuDP6ISlJCQAADw8vIq45YQERER\nUbmSnQ0kJQE3bwI3bhj/efNmqTaBc/4eI1lZWViyZAk6d+6MqlWrwtbWFlWqVMHAgQNx7tw5o+fc\nv38fCxYsQJMmTeDk5ARnZ2cEBARg6tSpyM7O1st75MgR9OvXD5UrV4adnR2qV6+OkJAQ7N27V5fH\n1NyyGTNmQKVSITo6WpcWGRkJlUqFmTNnIiYmBp06dYKzszPc3NxK7ZpSU1Ph5OSEhg0bGj3/3r17\ncHFxgZ+fn+kO/1diYiLCw8Ph7e2ta19YWBji4+N1eeLj46FSqTBjxgwAQPv27aFSqcyah7dr1y4M\nHToUdevWhaOjI9RqNdq0aYPvv//erPYVx/r169G2bVt4enrC3t4e1apVQ7du3bBjxw69fMuXL0eP\nHj3g7e0NOzs7eHp6olevXjh8+LBBmfnn3W3evBnNmjVDxYoV4ePjg0WLFgEAcnNzMXfuXPj6+sLe\n3h7+/v746aefDMrSaDRQqVS4f/8+3n77bVSrVg329vZo3Lgx1qxZU6Rr3b17N7p27Qp3d3fY29uj\nQYMGmDdvHnJycvTyiQiWLl2KZs2awc3NDRUrVoS3tzf69OmDI0eOFKlOIiIiesKJAKmpwN9/AwcP\nAtu2AatWAQsXAhMnAsOGAT17Am3aAHXrAm5ugJ0d0LAh8NJLwLRpwLffAseOARkZQK1aQLduwNtv\nl2qzOfL3GElKSsLbb7+NoKAg9OzZE87OzoiLi8P333+PX375BYcPH4aPj48uf3p6Ojp27IgDBw6g\nfv36GD58OBRFwenTp7FgwQKMGzcOarUaALBu3ToMHjwY1tbW6NmzJ2rVqoWEhATs2bMHP/zwA9q0\naaMrtzjzqvbu3Yv3338fnTp1wsiRI3Hjxo1SvaYBAwbgq6++wsGDB9GiRQu9tmzYsAEpKSl45513\nCm13YmIiAgMDcfHiRTz33HMYNGgQ4uLi8PXXX2Pbtm2IiYlBvXr14OrqiunTpyMyMhJRUVEICwvT\ntdvZ2dlkHQsWLMCFCxfQqlUrVK1aFUlJSdiyZQv69++PhIQEjBkzpmidXYhPPvkEo0aNgq+vLwYM\nGAAnJydcuXIFv//+O7Zv345OnTrp8oaHh6NJkybo0qUL3N3dceHCBWzevBm//vorIiMjERgYaFD+\nxo0bsXPnToSEhKBdu3b44YcfMHbsWNjb2+PIkSP45Zdf0L17d+Tk5GDNmjUICQnBqVOn4Ovra1BW\nnz59cPLkSfTv3x8ZGRn4/vvvERoaips3b+LNN98s9Fo//vhjjB49GpUqVUJwcDBcXV2xZ88eTJo0\nCQcPHsQPP/ygyzt+/HgsXLgQjRo1QlhYGGxtbXH58mVERkZi//79aNKkSTF7nIiIiMq9rCzzRuXy\nP7a2Bjw8AE9P/Z8eHkDt2obHXFwAK6uyvU4pR8xpTlGbjBko038lKSMjQxISEgzSo6KixNraWoYN\nG6aXHhERIYqiyPDhww3OSUxMlOzsbBERSUhIEAcHB3FxcZFTp04Z5L169aru8ZAhQ0RRFLl48aJB\nvunTp4uiKBIVFaVL2717tyiKIoqiyNdff/3IrunQoUMF5gsKChIbGxtJTEw0OPYg7fXOmjVLL335\n8uWiKIq0b99eL91YHxQmPj7eIC0tLU0aNWokzs7Okp6ernfMWL2mnpcHBQQESLVq1eTevXsGx5KS\nkgpt2+nTp8XJyUk6deqkl75ixQpRFEXs7Ozk2LFjuvQrV66InZ2dqNVqqV+/vty6dUt37IcffhBF\nUSQ8PFyvrKCgIFEURfz9/SUtLU2XfvXqVfHy8hI7Ozu916W27lWrVunS/vzzT7G2tpZWrVpJSkqK\nXvnh4eGiKIps2LBBl+bq6irNmzeX3Nxcg2u+ffu2QRqRMeXsY5WIyDLl5ookJ4ucOyeyf7/ITz+J\nrFghsmCByPjxIi+/LNK9u0irViK+viIuLiJWViKeniL164u0ayfSu7fIiBEi77wjsnixyNq1Ir/+\nKnL4sMilSyIP/H1Wkkrzs4Qjf48RGxsbPPXUUwbp7dq1w9NPP613y152dja++uoruLu7Y+HChQbn\neHp66h6vWrUK9+7dw5QpU/D0008b5K1cufJDt71Zs2YYNGiQQXppXVOzZs3QuHFjrFu3DosXL4a9\nvT0A4Ny5c4iOjkZwcLBefmMyMjKwbt06eHl5Yfz48XrHhg4dikWLFiEyMhKXL19G9erVTXeACd7e\n3gZpDg4OCA0NxdixY3Ho0CG0a9eu2OU/SFEUVKhQASqV4V3f2ttxTbXNz88PGo0G27dvR3Z2Nqyt\n9f8bGTRoEBo1aqT7vUqVKmjTpg127dqFyZMnw9XVVXesV69eqFChAv7880+jbZ0yZQocHBx0v1eu\nXBljxozBlClTsG7dOpOjf0uXLkVOTg6WLFkCJycnvWPvvfcePv30U3z33Xfo3bs3gLx+sbW1NTqy\n7eLiUmA9REREVMqysgxH3oyNxuVPs7ExHI3TPq5Tx/ionJG/jZ40DP4eM4cPH8b8+fOxd+9e3Lhx\nA1lZWbpjtra2usdxcXG4e/cu2rVrB0dHR5NlHjp0CADw3HPPlU6jkReMFaQ0rgkAhg8fjtdffx3r\n169HaGgogLw5bAAwbNiwQs8/c+YMMjIyEBgYCBsbG4PjQUFBOHnyJI4fP/5QwV9KSgrmz5+PzZs3\n4++//8a9e/f0jmsXkSkp/fr1w8SJE+Hv74/+/ftDo9GgZcuWekGW1rlz5/D+++9j9+7dSEhIQGZm\npu6YoihISkoyWNwmf+Cnpf0C4cFjKpUKnp6euHr1qtG2tm3b1iBNewvy8ePHTV7ngQMHoCgKtm7d\nanReoZ2dHeLi4nS/9+vXD59//jmaNGmCPn36QKPRoFmzZkafeyIiIiomESAlxfTtlQ8GdmlpeXPm\nHry90tMzL5Br1Uo/zd0d+PeLf9JX7oK/KlXKugXlV0xMDDp27Ahra2s8//zz8PX1RcWKFaEoClas\nWKG3sEhycjKAvFGXwhQlb3EVtPplaV0TAAwcOBDjxo3DsmXLEBoaipycHKxatQrVqlVDly5dCj0/\nJSXFZNu1I5bafMWRmZmJoKAgxMbGolmzZnj55Zfh5uYGKysrHD16FJs3b0ZGRkaxyzdm/PjxcHNz\nw+eff47Zs2dj9uzZsLW1RZ8+fbBw4UJUqlQJAPDXX3+hRYsWuHv3Ljp37ozevXvD0dERKpUKP/74\nI2JjY422TTuPND+rf+9vN3bM2tpaL+DXUhRF15b8tM+H9vVQkFu3bkFEMGvWLKPHFUVBenq67vcl\nS5agZs2aWLFihW4+qJOTE0JDQzF37lxUrFjRZH1EWvm+szLwKHZkUZS8f9rHxtIKO/6ozmE72A62\n4/Fvhyo7E7apN1Eh5SZsk2/AJuVm3r/kG6jw70+blJuocOffn8k3kWtjhyxnj7x/Lp66n9nOHsjy\nrIfsOh7Ids1Lz3H1QLajCxQrVeHtzAVwHVASH//npbSUu+Dvjz9MH69a9dG0ozyaM2cOsrOzERUV\nZbBx+Lfffqv3u/Y2tYJGVIzlvXLlSqGBlfZWwQdXCgVM/zFe0CIxpXVNQN4f7v369cPy5ctx7tw5\nxMXFISEhAe+8806B7clPG6hcv37d6HFturGAxlybN29GbGwshg8fjs8//1zv2Lx587B58+Zil23K\nsGHDMGzYMNy8eRNRUVFYvXo11q5dq1vgBAAWL16M5ORkfPPNN+jfv7/e+fv27UNsbGyptE1LRJCY\nmIiqD7zptf1e2EI6arUaKpUKd+/ehZ2dXaH1WVtbY9y4cRg3bhyuXLmC3bt348svv8Qnn3yC1NRU\nrFy5stjXQpalsO+DSvODXeR/AWb+nwU9Lstz2A6241GVaSqfJfaHyXNyBRWzk+F4/yacM2/AKeMm\n1Bk3oM68CXXmDagzbkKddRPOGTfyfmbegG1OOlIquCPZxhMpFTxwx8YTyRU88h5XqIc71m2QbOOJ\nO+4eSK7siTtW7shU2em3Ix2QNABXyll/lGGZpaXcBX8lPfgk00u5Bx+h8+fPw93d3SBIun79Os6f\nP6+X5ufnB0dHR+zfv1+39UFBWrRogR9++AHbt29H8+bNTbZBO1/rn3/+Qa1atfSOHT16tCiXA6D0\nrklr+PDhWL58OZYvX47Tp09DURS8/PLLZrXNz88Ptra2OHjwIDIzMw1u/4uOjoaiKEZvczSX9hp7\n9OhhcCz/FhulxcPDA71790bv3r0REBCA6OhoXd+eP38eiqIYtO3+/fs4cuSIWQH0w4qOjsaAAQP0\n0mJiYgAYv700v8DAQBw9ehQHDhxAUFBQkeqtWrUqBg0ahH79+qFq1arYunVr0RpOFs3UyB8R0SOV\nkfG/2yfNuc0yKSlvOwLtLZSVHrzN8mnD+XMuLnBTFLgV3hoyU2n+ifXkz2p8gnh7eyMpKUlvnlJm\nZibCw8MNRuKsrKwwfPhw3Lp1C2PHjoU88DVCYmKibp+z0NBQODg4YMGCBTh16pRePhHBtWvXdL9r\nt014cBRkw4YNumCoPFxT/vY+88wzWLZsGbZt24YOHTrAx8fHrLbZ2Nigf//+uHbtmsECM6tWrcKJ\nEyeg0WhQrVq1IlyxPu2CKtqARmvjxo1G56mVhKioKIO0e/fuITk5GRUqVNDdount7Q0R0WubiGDS\npEm6rTpK23vvvYe0tDTd7wkJCfjvf/8LOzs79O3b1+S5r7/+OqysrDBq1Cij8yavX7+ue91lZmZi\n3759BnlSUlJw7949s0YOiYiISpUIcPs28NdfwO+/A1u2AMuWAfPmAePGAWFhwIsvAoGBedsMqNWA\noyPQrBkweDDw3nvAxo3A6dN55T39NBASAkyZAqxZAxw+nLdvXUoKcP48cOAA8NNPwMqVwIIFwIQJ\nwMsvAz16AK1b5821c3Ut/fsUqUSVu5E/Klh4eDh+++03tGnTBn379oW1tTV27NiBnJwcNGrUyOA2\nvFmzZmHv3r348ssvsXfvXjz33HNQqVQ4e/Ystm/fjsTERKjVanh5eWH58uUYNGgQmjZtil69eqFm\nzZpITExEdHQ0unXrhg8//BAA0LNnT9SuXRsrV67E5cuX0bhxY5w+fVq3kfb//d//lYtrym/48OEI\nDw8HYN5CL/nNnz8fUVFRmDJlCqKjoxEQEIAzZ85g06ZN8PDwwGeffVak8h7UvXt31KhRA/PmzcPJ\nkydRr149nDx5Er/++iuCg4Px448/PlT5xvTs2ROurq4IDAxEjRo1cP/+ffz888+Ij4/HqFGjdAu/\njBgxAitWrEBISAj69esHtVqNPXv2ID4+HhqNRnd7aGmqVasW/P390bt3b93qq0lJSVi0aFGhq9D6\n+/vjo48+Qnh4OOrWrYtu3brB29sbt2/fxrlz5xATE4PZs2fDz88P6enpaNOmDfz8/BAQEIDq1asj\nOTkZW7ZsQXp6Ot59991Sv1YiIrIw2lE5cxc9SUoCHByML3ri6ZkXzD14zNmZwRnpYfD3GOnevTvW\nrVuHOXPmYPXq1XB2dkaXLl0wd+5c9OvXz2DUzd7eHrt378bixYvxzTff4PPPP4etrS1q1qyJiRMn\n6q3u2LdvX9SqVQtz587Fzp07kZKSAi8vL7Ro0UJvhMXOzg47duxAREQEdu7cif3796NVq1bYs2cP\ntm7dip9//rncXJPWwIEDMWrUKLi6uiI4OLhI7fP09MSBAwfw7rvvYsuWLdi1axfc3d0xePBgzJw5\n02ArBEVRijT66ejoiF27dmHs2LGIiYnB7t27ERAQgJ9//hlXr17Fpk2bzCqnKPXOnTsXP//8Mw4c\nOIDNmzdDrVajXr16mDFjBgYOHKjL16RJE/zyyy+YOnUq1q9fD1tbW2g0Gqxbtw6zZ882qM9UGwo7\nVlD6+vXrdds63LhxA/Xq1cOiRYsMtg0pqPzXXnsNjRs3xqJFixAdHY2kpCS4u7vDx8cH06ZNw3/+\n8x8Aec+D9rUfHR2NGzduwN3dHf7+/vjiiy/QrVu3gjuUiIgoNxe4c6fwLQjy/8zIMLyFUvuzQQPD\nbQo8PPK2LyB6CIo8eO9cGVIUxeBWvuLkIcovOjoaGo0Go0ePxuLFi8u6OWQGjUaDPXv2GNzGS1Te\n8TOK6Alx/755o3Han7duARUrGgZxxgI77U+1mqNyZFRpfpZw5I+eeAsXLoSiKBgxYkRZN4WIiIge\ntdzcvLly5i56cvMmkJlZcPDWsKHhMXd3jsrRY4HBHz2RLl++jLVr1+LEiRPYunUrXnrpJTz99NNl\n3SwqAo6eEBGRUffumTcal39UzsnJeCBXuXJeMPdgupMTR+XoicTgj55I58+fx+TJk6FWq9GnTx+D\nPfSofCvq3EkiInpMaUflzF305OZNICur4Fspn3nGMM3dHahQoayvlKhcwxyWTAAAIABJREFU4Jw/\nIiKiEsLPKLJ46elFW/Tk9u28uW+m5sY9OH/O0ZGjcvREs6w5fxs25O2Qq/1nY6P/OxERERGVvpwc\n06NyxtJycgoO2ho3Njzm5sZROaJHqPwFf99+m7f0bUZG3mRb7WPtPyIiIiIqurS0oi16cvt23j5x\nxkbhqlcHAgIMj1WsyFE5onKMt30SERGVEH5G0SOTk5O3kIm5i57cvAmImLcFQf5ROevyN05A9KQr\nzc8SBn9EREQlhJ9RVCwieXPlirLoyZ07gIuL6blxD/50cOCoHNFjwLLm/BERERE9zrKz9UflzLnN\nEsgL0IwFbd7ehoGdqytH5YioyDjyR0REVEL4GfUEEsmbK1eURU+Sk/OCM3NG47THKlYs6yslonKC\nI39EREREJSE7G0hKMn/Rkxs3ACurgoO3mjUN01xd884hIipnHrvgz9XVlZs/ExFRueTq6lrWTbAs\nIsDdu0Vb9CQlJW8hE2OjcbVqAYGBhsccHMr6SomISsRjd9snEZVDIkBWlvHtWYqbVhJlZWXp7xX6\n4L6hZZXGeTpExmVlFT4q9+Bja2vzb6/09MxbJIWjckRUjnG1TyKi4sjN/V8gWJKB6cOmAeYFiY86\nMFWpyvb5oieLCJCaWrRFT1JT80blTM2NezDN3r6sr5SIqEQx+CMiepLk5Dyakc+ipllbl68RUhub\nvH+81b98yMoqOIgrKM3GpuijcvwSgogsHIM/IiIqXaVx625J3PbLW3dLh0je3LeiLHqSlla0UTl3\nd47KEREVA4M/IiKyTI/7rbsPO/Jp7nkVKuRtL2Duoic3bwJ2duaNxmnzcFSOiOiRKPPg7/Lly4iI\niMCOHTsgIujUqRMWL16M6tWrF1qBqoAPimPHjuGZZ57RbwyDPyIiehyYc+tuSYx8mpuWmQk4O5t/\ne6W7e17wR0RE5U6ZBn/p6elo1KgR7O3tMXv2bADAO++8g/T0dBw/fhwOhSx/rFKpMHToUIwYMUIv\nvWHDhrB/4HYQBn9ERERERGTJynST9y+//BIXLlzA2bNnUatWLQDAM888gzp16mDp0qWIiIgotJKq\nVauiRYsWD99aIiIiIiIiKpZCb97fsmULWrVqpQv8AMDHxwdt2rTB5s2bzaqEo3lERERERERlq9Dg\n7+TJk/D39zdIr1+/Pk6dOmVWJZ999hns7OxQsWJFdOzYETExMUVvKRERERERERVbocHf7du34erq\napDu5uaG27dvF1rBoEGD8Nlnn2Hnzp344osvkJSUhA4dOiAqKqp4LSYiIiIiIqIiK/WNilavXq17\n3KZNG/Ts2RP+/v6YOnUqoqOjS7t6IiIiIiIighnBn6urq9ERvlu3bsHNza3IFTo6OqJr165YsWKF\n0eMzZszQPdZoNNBoNEWug4iIiIiI6HEQGRmJyMjIR1JXoVs9dOzYEZmZmdizZ49eukajgaIo2L17\nd5Erff3117Fy5Uqkp6frN4ZbPRARERERkQUrzZio0Dl/PXr0wP79+3HhwgVdWnx8PH7//Xf06NGj\nyBWmpKTgp59+4tYPREREREREj1CxNnmfOnUq0tLS9DZ5v3jxImrXro3p06dj6tSpAIAPPvgA58+f\nh0ajgZeXFy5evIgPPvgAf/31F3bu3Ik2bdroN4Yjf0REREREZMHKdJN3BwcH7Nq1CxERERg8eDBE\nBJ06dcLixYt1gR+Qt5dfbm6uXkP9/PywadMmbNiwAcnJyVCr1Xj22WexYsUKNGvWrFQuiIiIiIiI\niAwVOvL3KHHkj4iIiIiILFmZzvkjIiIiIiKixx+DPyIiIiIiIgvA4I+IiIiIiMgCMPgjIiIiIiKy\nAAz+iIiIiIiILACDPyIiIiIiIgvA4I+IiIiIiMgCMPgjIiIiIiKyAAz+iIiIiIiILACDPyIiIiIi\nIgvA4I+IiIiIiMgCMPgjIiIiIiKyAAz+iIiIiIiILACDPyIiIiIiIgvA4I+IiIiIiMgCMPgjIiIi\nIiKyAAz+iIiIiIiILACDPyIiIiIiIgvA4I+IiIiIiMgCMPgjIiIiIiKyAAz+iIiIiIiILACDPyIi\nIiIiIgvA4I+IiIiIiMgCMPgjIiIiIiKyAAz+iIiIiIiILACDPyIiIiIiIgvA4I+IiIiIiMgCMPgj\nIiIiIiKyAAz+iIiIiIiILACDPyIiIiIiIgvA4I+IiIiIiMgCMPgjIiIiIiKyAAz+iIiIiIiILACD\nPyIiIiIiIgvA4I+IiIiIiMgCMPgjIiIiIiKyAAz+iIiIiIiILACDPyIiIiIiIgvA4I+IiIiIiMgC\nMPgjIiIiIiKyAAz+iIiIiIiILACDPyIiIiIiIgvA4I+IiIiIiMgCMPgjIiIiIiKyAAz+iIiIiIiI\nLACDPyIiIiIiIgvA4I+IiIiIiMgCFBr8Xb58GX369IGLiwucnZ3Ru3dvXL58ucgVzZ07FyqVCm3b\nti1WQ4mIiIiIiKj4FBGRgg6mp6ejUaNGsLe3x+zZswEA77zzDtLT03H8+HE4ODiYVcnff/+NZ555\nBo6Ojqhbty6io6ONN0ZRYKI5RERERERET7TSjImsTR388ssvceHCBZw9exa1atUCADzzzDOoU6cO\nli5dioiICLMqGTlyJAYPHoy4uDhkZ2c/fKuJiIiIiIioSEze9rllyxa0atVKF/gBgI+PD9q0aYPN\nmzebVcE333yDY8eOYc6cORARKIrycC0mIiIiIiKiIjMZ/J08eRL+/v4G6fXr18epU6cKLfz27duI\niIjA/Pnz4eLiUvxWEhERERER0UMxGfzdvn0brq6uBulubm64fft2oYWPGzcOfn5+GDJkSPFbSERE\nRERERA/N5Jy/h7Fnzx58/fXXOHr0aGlVQURERERERGYyGfy5uroaHeG7desW3NzcTBY8YsQIvPLK\nK6hatSru3LkDAMjOzkZubi6Sk5Nhb28PGxsbg/NmzJihe6zRaKDRaMy4DCIiIiIiosdPZGQkIiMj\nH0ldJrd66NixIzIzM7Fnzx69dI1GA0VRsHv37gILVqlMbyG4ePFijB49Wr8x3OqBiIiIiIgsWJlt\n9dCjRw+MHTsWFy5cQM2aNQEA8fHx+P333zFv3jyTBe/evVtvZU8RwZtvvonc3Fx89NFHqF27dgk0\nn4iIiIiIiMxR5E3ep06dirS0NL1N3i9evIjatWtj+vTpmDp1aoGVaTQa5OTkGIwk6hrDkT8iIiIi\nIrJgpRkTmbw308HBAbt27ULdunUxePBgDBo0CLVr18auXbt0gR+QN6qXm5tbaCMVReE+f0RERERE\nRGXA5Mjfo8aRPyIiIiIismRlNvJHRERERERETwYGf0RERERERBaAwR8REREREZEFYPBHRERERERk\nARj8ERERERERWQAGf0RERERERBaAwR8REREREZEFYPBHRERERERkARj8ERERERERWQAGf0RERERE\nRBaAwR8REREREZEFYPBHRERERERkARj8ERERERERWQAGf0RERERERBaAwR8REREREZEFYPBHRERE\nRERkAazLugFERERUMJEc5OZmQiQLIlnIzc3SPf7f79lQqWxhZeUAlcrh35/2UBR+x0tERP/D4I+I\niJ44IgKR7H+Do0wjwZKp3wsLtIz9nlmEvEVrEyDF7geVyg4qlX2+gLC4P+0LPK5S2UFRlJJ78oiI\nqNQoIlL8T5USpigKylFziIgsjkjuIwtqSjPQEsku6660KOYEjw8bgCpKBQaZRGQRSjMmYvBHRPSQ\n8kaZcowEI5nlZvTI3DYBuWXdnUQFUD3k6KXpEcz/5eFNUURUthj8EdETKS9oejRBTWkHWkT0ZFCU\nCsW6/bVoAag9FMWqrC+ViMopBn9EpCdvAYjyO3pkbpuAnLLuSqLHgPLvLY8VoFJV0D3W/90aubmZ\nyM1NR05OOnJz05Gbe6+sG04mKMqDC/Q8/PxLzsckejIw+CMqAfkXgCivo0fmtulhFoAgshxWJoKl\nB3+3KULeClCpbMzO+2B+8+qxyfe4eCNEIrnIzb2vCwZN/7z3/+3deXhUVZ4+8PdWZWdN2JE17DsC\nyr6HJalCRPYk92I7re203TzN6HT39E8Uu217dKYd7LZtW5+Z1nsT9kW0KiQIJIBsIgqogCgSQJA9\nBEgISarO7w+sskK22m4tqffzPDzEa5265x7LSr11zv0eNx5T899ClPv5vxv5k7fLX+v/+8f7OO++\nXhkyifyF4Y+CqnoBiNCaPXK3TywAQeQez0LNvUElFIKW42ducxAIQthgs3kfHh2zlHU9xmYrAVcK\nhDLP78f0JoDyfkyKFAx/Yaj2AhChM3vkbp9YAILIHVIQZoT8H7QkKYrf4FNIstsr6py59DZ4Vg2g\nJeDKitBV/X5M36rI1hxAeT8mBV9EhT+73R7Ss0ee9ImI3GH0OqiEVtDihwWicHf3i9tyLwOk+wGU\n92OGNs/ux/QugPJ+TKpLRIW//Pxg94IoPIT+0jt3gxZ/+RFRZKn5fkzfls7WFECFuBPsS6U6+G8f\nzNrb837M8KRn+OPiaYowhrBYeldf0JIkI9/MiYjClCTdvUfOaEzQ9Tye34/peQDl/ZjeuzsLXKrz\nWdy9H9OXABoPgyFa5+sgf2H4I7fcvQ8oHJbe1Re0WACCiIgigyQZERXVGEBjXc/z4/2Y+hb+YQ0C\nb9hhs92CzXYLFTrekXT3s5avVWTrC6C8H9MfGP505c7eTKGy9K6uoMUCEERERFQzgyEaBkMzREU1\n0+0c7t2P6Z/CP+Q5ISpgs1XAZruh63nqvx/T921MGvr9mCEX/ux2wGBwd2+mUL/Hid9OEBEREflK\nkiRIUiwMhlgAibqdRwgBu73Mb/dd1r4/Ju/H9IYQd1BZeQdAka7n8XUZrDuPq+1+TL3LsYRcwZe2\nbdsiNTUVZrMZU6ZMQZMmTYLdLSIiIiIiv6n9fkz/Fv5h9flQVvV+zO+/j0JeXims1mv47ruyyKn2\n6So6Ohrjxo2D2WyGyWRCjx49gtQzIiIiIqLwcvd+TE+Xw3oeQHk/pndu3QIKCoAtW4DPP6/67yIy\n/N2rR48eMJlMMJvNGDt2LGJiYgLUMyIiIiIiulf1+zH9M3tZ079rCCorgQMHgLw8YM8e1FqIh+Hv\nHk2aNMGUKVNgMpmQlpaGtm3b6tgzIiIiIiIKFs/ux/Q+gOpxP6YQwIkTd2f4tm8Hrl9373r1ELbh\n717Dhg1zzgoOGTIEBgNL+hMRERERkfuEsMFuL/O5cqzNdhvnz1+D1fodrNZLOHXKs1AZMeFv06ZN\nsFqtsFqtOHfunFfP06ZNG6SlpcFkMmHKlClo2rSpn3tKRERERERU1c2bN7Fhwwaoqor8/HyPQlzv\n3l0xb14Kfv/7tyMn/Dm6I4TA4cOHnUFw3759Xg2Co2iMyWSCyWRCz549/d1tIiIiIiKKUDabDdu2\nbYOmadiwYQNKS92/P7FVq1ZIT0+HLMsYMmTID9uaSJEX/u51+fJl5Obmwmq1Ijc3F8XFxV6dw1E0\nxmQyYdy4cSwaQ0REREREHvv888+hqipWrFiB8+fPu90uNjYWM2fOhCzLmDZtGqKjo6v8e4a/e1RU\nVGDPnj3OWcGjR496dT4WjSEiIiIiIndduHABK1euhKqqOHTokEdtx44dC1mWMXfuXDRv3rzWxzH8\n1ePUqVPOIJifn487d7yr0uMoGmMymTB06FAWjSEiIiIiinC3b9/Gpk2boKoqtmzZApvN5nbb7t27\nQ5ZlZGZmIjk52a02DH8eKCkpwbZt21g0hoiIiIiIvGK327Fr1y6oqoq1a9fi5s2bbrdNTEzE/Pnz\noSgKRowY4fGOBgx/XhJC4MiRI7BYLCwaQ0REREREdfrqq6+gaRqysrJw+vRpt9tFRUXBZDJBURSY\nTCbExsZ63QeGPz9xLRqTl5eH6+7ssFiD7t27w2w2s2gMEREREVGYu3LlClavXg1VVfHxxx971PbB\nBx+EoiiYP38+WrZs6Zf+MPzpoLKyEnv27HHOCnpbNKZx48aYOnUqi8YQEREREYWJO3fuwGq1QlVV\n5OTkoKKiwu22nTp1gizLkGUZvXr18nvfGP4C4NSpU8jJyYHFYvGpaMzQoUOds4IsGkNEREREFBqE\nENi3bx9UVcXq1atRVFTkdtsmTZpg7ty5kGUZ48aN0/UzftDD39mzZ7FkyRJs3boVQgikpKRg+fLl\n6NixY53tTp8+jcWLF+Pw4cO4dOkSGjVqhH79+uE3v/kNUlNTq3cmiOHPVUlJCbZv3+6cFfSlaExq\nairMZjOLxhARERERBcGpU6egaRo0TcM333zjdjuDwYBp06ZBlmXMnDkTCQkJOvbyR0ENf6WlpRg0\naBDi4+Px4osvAgCeffZZlJaW4siRI3UOwtGjR/Hqq69i4sSJ6NChA4qLi/H222/DarViw4YNePjh\nh6t2JkTCnytH0Rir1QqLxeJT0ZixY8c6ZwVZNIaIiIiISB/Xr1/H2rVroWkadu3a5VHbwYMHQ5Zl\nLFy4EO3atdOph7ULavh77bXX8PTTT+PEiRPOvSkKCwvRo0cPvPLKK1iyZIlHJ7TZbOjatSvuv/9+\nbNq0qWpnQjD83evKlSvIzc2FxWLxuWiMyWSC2Wxm0RgiIiIiIh9VVFQgLy8PmqZh06ZNHt3G1a5d\nO2RkZECWZQwcOFDHXtYvqOFv8uTJKC8vr5aYJ0yYAAAoKCjw+KT9+/dHz549sWHDhqqdCYPw58pR\nNMYxK+hL0ZgpU6bAbDazaAwRERERkZuEEPjss8+gqipWrFiBy5cvu902ISEBs2bNgqIomDx5MoxG\no449dV9Qw1/btm0xa9Ys/P3vf69y/Oc//znWrVuHS5cu1XsSIQRsNhuuXLmCt956C3/84x+Rk5OD\nyZMnV+1MmIW/exUWFjo3l9++fbtPRWMcs4IsGkNEREREVNV3332H7OxsqKrq0QSMJEmYOHEiFEXB\nI488giZNmujYS+8ENfzFxsbi6aefxksvvVTl+LPPPouXX37ZrbKozzzzDF599VUAQHx8PN59913M\nmTOnemfCPPy5chSNccwK+lo0xmQyYerUqSwaQ0REREQR6datW9iwYQNUVcX27ds9yg19+vSBoijI\nyMiot2hlsOmZiaJ0edZ7LFmyBOnp6bhw4QLeffddZGZmIj4+HiaTKRCnD4pGjRphxowZmDFjRpWi\nMVarFXv37nX7P+jFixfxzjvv4J133nEWjXHMCrJoDBERERE1ZDabDdu3b4eqqtiwYQNKS0vdbtuy\nZUukp6dDlmUMHToUkiTp2NPw4NOyz/Xr1+PixYsen3TixIm4cOECjh07VrUzDWjmry6OojFWqxW5\nubk+F40xmUwYN24cYmNj/dxTIiIiIqLA++KLL6CqKrKzs3H+/Hm328XExGDmzJmQZRnTp09HdHS0\njr3UR8gWfJEkCfn5+R6f9JlnnsFrr71WbcmoJEl4/vnnq5zDUVimoXItGmO1WvHll1969TyOojEm\nkwlpaWlBKUtLREREROStixcvYsWKFdA0DZ999plHbceMGQNZljF37lwkJibq1EN9FBQUVCmi+cIL\nLwR3q4dnnnkGJ06cQNeuXQHcLWzSs2dPvPzyyx5v9WC32zFq1CgUFxdH7MxfXfxdNMZkMmHYsGEs\nGkNEREREIef27dvYtGkTNE1DXl4ebDab2227desGWZaRmZmJbt266djLwAq5Td6XLl2KkpKSKpu8\nnz59Gt26dcPzzz+PpUuXAgCWLVuGoqIijBo1Cm3btsWFCxfwv//7v9i+fTtWrFiBefPmVe0Mw18V\nrkVjrFYrvvvuO6+ep3Xr1khLS2PRGCIiIiIKOrvdjl27dkHTNKxduxY3btxwu23z5s0xf/58KIqC\nkSNHNsj7+IIa/gDg7NmzWLJkCT788EMIIZCSkoLly5ejU6dOzscUFhYiOTkZy5Ytw3PPPQcA+OCD\nD7B8+XJ88cUXKC4uRtu2bTF48GD85je/wciRI6t3huGvVvcWjdm3bx/sdrvHzxMVFYVx48Y5ZwV7\n9uzZIP+nISIiIqLQcuLECWiaBk3TcPr0abfbRUVFIS0tDYqiwGQyIS4uTsdeBl/Qw1+gMPy5z19F\nY7p16waz2cyiMURERETkd1evXsXq1auhqir279/vUdsHHngAiqJg/vz5aNWqlU49DD0Mf1SnyspK\n7N27FxaLhUVjiIiIiCio7ty5g5ycHKiqCqvV6ta+4A4dO3aELMuQZRm9e/fWsZehi+GPPOKvojFD\nhgxxzgqyaAwRERER1UYIgf3790NVVaxatQpFRUVut23cuDHmzp0LRVEwbty4iP/MyfBHXistLcX2\n7duds4IsGkNERERE/nLq1ClkZWVB0zR8/fXXbrczGAyYOnUqFEXBzJkznUUkieGP/EQIgc8//9wZ\nBH0pGjN27FjnrCCLxhARERFFjuLiYqxduxaapmHnzp0etR00aBBkWUZ6ejpvMaoFwx/p4urVq8jN\nzYXFYvG5aIzJZILZbGbRGCIiIqIGqKKiAlu2bIGmadi0aRPKysrcbtu2bVtkZGRAlmUMGjRIx142\nDAx/pDtH0Rir1QqLxeJ10ZhGjRphypQpMJvNLBpDREREFMaEEPjss8+gaRpWrFiBS5cuud02Pj4e\ns2bNgqIomDx5MqKionTsacPC8EcBV1hYiJycHFgsFuTn53v07Y6rIUOGOGcFWTSGiIiIKPSdO3cO\n2dnZUFXVowkBSZIwYcIEKIqC2bNno0mTJjr2suFi+KOgchSNccwK+lI0JjU11Vk0plmzZn7uKRER\nERF549atW9i4cSNUVcW2bds8+kzeu3dvKIqCjIwMdOrUScdeRgaGPwoZjqIxjiDoa9EYx6wgi8YQ\nERERBZbNZkN+fj5UVcWGDRtQUlLidtuWLVti4cKFUBQFQ4cO5ec4P2L4o5DlKBpjtVqRm5vr0Z4u\nrhxFY0wmE8aPH8+iMUREREQ6+fLLL6GqKrKysnD+/Hm328XExOChhx6CoiiYPn06oqOjdexl5GL4\no7DgWjTGarXiiy++8Op5HEVjTCYT0tLS0L59ez/3lIiIiCiyXLx4EStXroSmafj00089ajt69Ggo\nioK5c+ciMTFRpx6SA8MfhaXTp087g+D27dt9LhpjMpnwwAMPsGgMERERkRtu376N999/H6qqIi8v\nDzabze22ycnJUBQFmZmZ6Natm469pHsx/FHYcy0aY7VacfbsWa+eh0VjiIiIiGpnt9vx0UcfQVVV\nrF27Fjdu3HC7bfPmzTFv3jwoioJRo0bxPr4gYfijBkUIgS+++AIWiwVWqxV79+71uWiMyWRCr169\n+CZFREREEenEiRPQNA1ZWVkoLCx0u11UVBTS0tIgyzLMZjPi4uL06yS5heGPGjQWjSEiIiLy3LVr\n17B69Wqoqop9+/Z51HbYsGFQFAULFixAq1atdOoheYPhjyJGZWUl9u3b55wVZNEYIiIioh+Vl5cj\nJycHqqrCYrGgoqLC7bYdO3ZEZmYmZFlGnz59dOwl+YLhjyKWv4rG3H///TCbzSwaQ0RERGFHCIH9\n+/dD0zSsWrUK165dc7tt48aNMWfOHCiKgvHjx/MzUBhg+CPC3aIx+fn5zllBb4vGtGrVCmlpaSwa\nQ0RERCGtsLAQWVlZUFUVX3/9tdvtDAYDpkyZAkVRMHPmTDRq1EjHXpK/MfwR3cNRNMZqtcJisfhU\nNGbMmDHOWUEWjSEiIqJgKi4uxrp166CqKnbu3OlR2wEDBmDRokVIT09Hu3btdOoh6Y3hj6geV69e\nRV5eHiwWi09FY5KTk51BkEVjiIiIKBAqKyuxZcsWqKqKTZs2eXSbS9u2bZGRkQFZljFo0CAde0mB\nwvBH5AFH0RjHrKAvRWNSUlKcFURZNIaIiIj8RQiBQ4cOQVVVrFy5EhcvXnS7bXx8PGbNmgVZlpGS\nkoKoqCgde0qBxvBH5IPTp08jJycHFovF56IxJpMJZrOZRWOIiIjIK+fOnUN2djY0TfP4C+qJEydC\nlmXMnj0bTZs21amHFGwMf0R+4iga45gV9KVoTGpqKkwmE6ZNm8aiMURERFSrW7duYePGjdA0DVu3\nbvXo826vXr2gKAoyMjLQuXNnHXtJoYLhj0gH/i4a41ge2rt3bxaNISIiinA2mw35+fnQNA3r169H\nSUmJ221btGiBhQsXQlEUDBs2jJ8rIgzDH1EAOIrGWK1WbN682aeiMY4gOH78eMTFxfm5p0RERBSq\nvvzyS2iahqysLJw7d87tdjExMZgxYwYURcH06dMRExOjYy8plDH8EQWYHkVj0tLScN999/m5p0RE\nRBRsly5dwsqVK6GqKj799FOP2o4aNQqKomDevHlITEzUqYcUThj+iILMUTTGarVi27ZtPheNMZlM\neOCBB2A0Gv3cUyIiIgqEsrIyvP/++1BVFbm5ubDZbG637dq1KxRFQWZmJrp3765jLykcMfwRhRDX\nojFWqxVnzpzx6nlci8ZMnToVzZs393NPiYiIyJ/sdjt2794NVVWxdu1aFBcXu922WbNmmD9/PmRZ\nxujRo3kfH9WK4Y8oRLkWjbFardizZw+LxhARETUwX3/9tfM+vlOnTrndLioqCqmpqZBlGTNmzGAd\nAHILwx9RmHAtGpObm4tr16559Txdu3aF2Wxm0RgiIqIguXbtGlavXg1N07B3716P2g4bNgyyLGPB\nggVo3bq1Tj2khorhjygMuRaNsVqt+Pzzz716noSEBEyZMoVFY4iIiHRWXl6OnJwcaJoGi8WC8vJy\nt9t26NABmZmZkGUZffv21bGX1NAx/BE1AGfOnHEGQV+KxgwePNg5K8iiMURERL4RQuDAgQNQVRWr\nVq3C1atX3W7buHFjzJ49G4qiYPz48fydTH7B8EfUwPiraEzLli2RlpbGojFEREQeOn36NLKysqCq\nKk6cOOF2O4PBgJSUFCiKgocffhiNGjXSsZcUiRj+iBowIQS+/PIG/p5lAAAgAElEQVRLWCwWn4rG\nGI1GjBkzxjkryKIxREREVd24cQPr1q2DqqrYsWOHR2379++PRYsWIT09He3bt9eph0QMf0QR5dq1\na8jNzWXRGCIiIj+orKzEhx9+CFVV8d5773l020WbNm2QkZEBWZYxaNAgfqlKAcHwRxShKisrsX//\nflitVlgsFp+KxqSkpMBsNrNoDBERNXhCCBw+fBiqqmLFihW4ePGi223j4uIwa9YsyLKMKVOmICoq\nSseeElXH8EdEAO4WjcnJyYHFYvG5aIzJZILZbGbRGCIiajDOnz+P7OxsaJrm8RemEyZMgCzLmDNn\nDpo2bapTD4nqx/BHRNXcvn3bWTTGYrH4VDQmNTUVZrOZRWOIiCjslJSUYOPGjdA0DVu3bvXovvle\nvXpBlmVkZmaic+fOOvaSyH0Mf0RUJ0fRGEcQ9LVojGNWkEVjiIgoFNlsNhQUFEBVVaxfvx4lJSVu\nt23RogUWLFgARVHwwAMP8PcchRyGPyLyyLVr15CXlwer1YrNmzf7VDTGZDLBZDJhwoQJLBpDRERB\ndfToUWiahqysLHz33Xdut4uJiYHZbIaiKEhNTUVMTIyOvSTyDcMfEXnNZrNh3759zj0Fjxw54tXz\nOIrGOMIgi8YQEVEgXLp0CatWrYKqqjh48KBHbUeOHAlFUTBv3jwkJSXp1EMi/2L4IyK/cRSNsVqt\n2LZtG27fvu3V8ziKxphMJjz44IMsGkNERH5TVlaGDz74AKqqYvPmzbDZbG637dq1q/M+vh49eujY\nSyJ9MPwRkS5ci8ZYrVacPn3aq+dxFI0xmUyYNm0ai8YQEZHHhBDYvXs3VFXFmjVrUFxc7HbbZs2a\nYd68eVAUBaNHj+Z9fBTWGP6ISHeuRWOsVit2797tc9EYk8mEPn368JcwERHV6ptvvoGmadA0DadO\nnXK7ndFoRGpqKmRZxowZMxAfH69jL4kCh+GPiAKORWOIiEgv165dw5o1a6CqKvbu3etR26FDh0KW\nZSxcuBCtW7fWqYdEwcPwR0RBxaIxRETkq/LycmzevBmqqsJisaC8vNzttvfddx9kWYYsy+jbt6+O\nvSQKPoY/Igop/ioaM2jQIJjNZhaNISJqoIQQOHDgADRNw8qVK3H16lW32zZq1AizZ8+GoiiYMGEC\nf0dQxAh6+Dt79iyWLFmCrVu3QgiBlJQULF++HB07dqyz3YEDB/Dmm29i165dOHfuHFq2bImxY8fi\nxRdfRJcuXap3huGPKOywaAwREd3r9OnTyM7Ohqqq+Oqrr9xuJ0kSUlJSoCgKZs2ahUaNGunYS6LQ\nFNTwV1paikGDBiE+Ph4vvvgiAODZZ59FaWkpjhw5goSEhFrb/vu//zt2796NjIwMDBgwAOfOncMf\n/vAHXLp0CYcOHUKHDh2qdobhjyisCSFw9OhRWCwWWK1W7Nmzx6Py3A5GoxGjR492zgqyaAwRUei7\nceMG1q1bB03TUFBQ4FHb/v37Q1EUpKen85YAinhBDX+vvfYann76aZw4cQLJyckAgMLCQvTo0QOv\nvPIKlixZUmvby5cvo1WrVlWOnTlzBl27dsWzzz6LF154oWpnGP6IGpSioiLk5eXBYrH4VDSmS5cu\nMJlMMJvNLBpDRBRCKisrsXXrVqiqio0bN6KsrMzttq1bt0ZGRgYURcGgQYP4JR/RD4Ia/iZPnozy\n8nLs2rWryvEJEyYAgMff7ABA27ZtMWPGDLz99ttVO8PwR9Rg2Ww27N+/3zkr6EvRmMmTJ8NsNiMt\nLa3aCgIiItLf4cOHoaoqsrOzcfHiRbfbxcXF4eGHH4aiKJgyZQqioqJ07CVReApq+Gvbti1mzZqF\nv//971WO//znP8e6detw6dIlj0547Ngx9OvXD//93/+Nf/u3f6vaGYY/oohx9uxZ5OTkwGKx+Fw0\nxjEryKIxRET6OX/+PFasWAFVVfH555971Hb8+PFQFAWzZ89Gs2bNdOohUcMQ1PAXGxuLp59+Gi+9\n9FKV488++yxefvllVFRUuH2yyspKTJ48GV999RW++uqrav/zM/wRRabbt2+joKDAOSvoS9GY6dOn\nO4vGJCYm+rmnRESRpaSkBO+99x5UVcXWrVtht9vdbtuzZ08oioKMjIwaC/0RUc30zEQBnWv/xS9+\n4dwrjN/6EJFDfHw8UlNTkZqaitdffx1Hjx6F1WqFxWLxqGjMlStXkJWVhaysLGfRGMesIIvGEBG5\nx263o6CgAKqqYv369bh165bbbZOSkrBgwQIoioIHH3yQ77tEIabe8JeYmIiioqJqx69du4akpCS3\nT/Tb3/4Wb7/9NlRVRUpKSq2PW7ZsmfPnCRMmOO8tJKLIIEkS+vXrh379+uHXv/61s2iM1WpFTk6O\n20VjbDYbdu7ciZ07d+I3v/mNs2iMyWTCxIkTWTSGiOgex44dc97Hd/bsWbfbRUdHw2w2Q1EUpKWl\nISYmRsdeEjU8BQUFXtVR8YZPBV8kSUJ+fn69J/njH/+IpUuX4vXXX8fPf/7z2jvDZZ9EVAdH0RjH\nrKCvRWMcYZBFY4goUl2+fBkrV66Epmn45JNPPGo7YsQIKIqCefPmoUWLFjr1kCjyBH2rh2eeeQYn\nTpxA165dAdzd6qFnz554+eWX69zqAQD+8pe/4Fe/+hVeeukl/Pa3v627Mwx/ROQBR9EYq9WKrVu3\n+lw0xmQyYfjw4SwaQ0QNWllZGSwWC1RVxebNm1FZWel22y5dukCWZciyjB49eujYS6LIFXKbvC9d\nuhQlJSVVNnk/ffo0unXrhueffx5Lly4FAKxatQrp6emYPn06nn/++SoX0axZM/Tp06dqZxj+iMhL\njqIxjllBb4vGtGjRAqmpqSwaQ0QNihACu3fvhqZpWL16NYqLi91u27RpU8ybNw+KomD06NEwGAw6\n9pSIghr+gLvfri9ZsgQffvghhBBISUnB8uXL0alTJ+djCgsLkZycjGXLluG5554DAPzkJz+Bqqo1\ndn7ChAnYvn171c5IEgpiCxDVPArRidGIah5190/iPX/f87PjscZmRhii+IZEFOmEEM6iMVarFbt3\n73a7aIwr16IxJpMJffv2ZfECIgorJ0+ehKZp0DQN3377rdvtjEYjpk+fDkVRMGPGDMTHx+vYSyJy\nFfTwFyiSJKGytBKVRZWovP7Dnx9+riiqqHasys9Flai8UQljI2OtQbHGQOnys7GxkR/siBog16Ix\nmzdvxtWrV716HhaNIaJwUFRUhDVr1kBVVezZs8ejtkOGDIGiKFiwYAHatGmjUw+JqC4RFf586Y6w\nC9hu2moOijUFRtdQWVQJ+x17tdlET2YeDbGcdSQKda5FY6xWKw4fPuzV88THxyMlJYVFY4goJJSX\nlyM3NxeqquKDDz5AeXm5223vu+8+ZGZmQpZl9OvXT8deEpE7GP4CxF5uR2Wx9zOPUrRU58xinTOP\nTaMgGTnrSBRo/ioaM3DgQJjNZhaNIaKAEULgk08+gaqqWLlypUerGho1aoTZs2dDlmVMnDiR71lE\nIYThLwwIIWAvtdceFOuZebTdtMHYxFh95rGW2cZ7A6UhwcAlq0Q+ci0aY7VaUVhY6NXzsGgMEenp\nzJkzyMrKgqZpOH78uNvtJElCSkoKZFnGrFmz0LhxYx17SUTeYviLAMImUHmj9qBY38yjqBQ/BsNa\nlqrWupS1WRQMMVyySuRKCIFjx47BYrH4XDRm1KhRzllBFo0hIm/cuHED69evh6Zpbu2x7Kpfv35Q\nFAXp6elcok4UBhj+qF72O/bq9zF6MPNoiDXUHBTdmHk0NjFCMvDDLDVs/ioa07lzZ2cQnDBhAivo\nEVGtKisrsXXrVmiaho0bN3q0LL1169ZIT0+HoigYPHgwv3QiCiMMf6QrIQRst2x1zizWNfNoK7Eh\nqmktQdGNmUdDHJesUnix2Wz4+OOPnbOCvhSNmTx5MsxmM9LS0tCxY0c/95SIwtHhw4ehaRqys7Nx\n4cIFt9vFxsbi4YcfhqIomDJlCqKjo3XsJRHpheGPQpq90g5bsc3rmUcI1B4U65l5jGoexb0dKei+\n++475OTkwGKxYNu2bSgtLfXqeQYOHAiTyQSz2cyiMUQR5vvvv8eKFSugqiqOHDniUdtx48ZBURTM\nmTMHzZo106mHRBQoDH/UoNnKbLWGw3pnHosrYYyvfW/H+mYejU24tyP5V1lZGQoKCpyzgr4UjZk+\nfTrMZjOLxhA1UKWlpXjvvfegqio+/PBD2O12t9v26NEDiqIgIyMDXbt21bGXRBRoDH9EtRD2H5as\n1rR3oxszj7bbNkQ1qyMo1jPzaIzjzAzVzlE0xmq1wmKx+Fw0xjEryKIxROHLbrdjx44dUFUV69at\nw61bt9xum5SUhAULFkCWZQwfPpzvA0QNFMMfkU7sFbXv7VjvzGNRJSRj3Xs71jnz2Ix7O0aaoqIi\nbNmyBRaLxeeiMY7N5SdOnMiiMURh4NixY9A0DVlZWTh79qzb7aKjo2E2myHLMtLS0hAbG6tjL4ko\nFDD8EYUgIQTst+21VlCtd+bxRiWMjY01hkd3Zh6NjbhkNZw5isY4ZgV9LRrjCIMsGkMUOi5fvoxV\nq1ZBVVV88sknHrUdMWIEZFnG/Pnz0aJFC516SEShiOGPqAES9rr3dqxv5lGU17K3o5szj9zbMbQ4\nisZYrVZs3brV56IxJpMJI0aMYNEYogArKyuDxWKBqqrYvHkzKisr3W7buXNnyLIMWZbRs2dPHXtJ\nRKGM4Y+IqrGX22sMjO7OPErRUq17N9YbKJtGcW9HHTmKxjhmBX0tGmMymTBt2jQkJSX5t6NEBODu\nSpA9e/ZA0zSsXr0a169fd7tt06ZNMXfuXCiKgjFjxsBg4BdzRA2RvcIOe6kdtlIbbCW2uz87/nY9\nVmpDx192ZPgjIv8RQsBeav8xKHo482i7ZYOxibHWvRvrW8pqiOfeju5yLRpjtVrx0UcfeVU0xmAw\nYPTo0c5ZwX79+vG/AZGPTp48iaysLGiahpMnT7rdzmg0Ytq0aVAUBQ899BDv2yUKMmEXsJX+GL7s\nJfYf/7nEVvsx1wBXzzFhFzA2MsKYYIQhwQBjox//vvdYr7/1YvgjotAhbD8sWa1hZtGdmUdhE7UG\nxXpnHptHwRAdud+MO4rGWK1W5OTksGgMUYAVFRVh7dq1UFUVu3fv9qjt/fffD0VRsHDhQrRp00an\nHhI1LEII2O/Ya58pc/eYS4C795j9jh2GeJdAlmCs8rOhUe3HqgS4Oo5J0ZLbX7py2ScRNSi2Mhts\nxTbvZh6vV8IQZ6g9KNYz82hsYmwwS1Zdi8ZYrVYcOnTIq+dh0RiiulVUVCA3NxeqquL9999HeXm5\n223bt2+PzMxMyLKM/v3769hLouCwV9prDVVuzZ7VN6NWaoMULVUPVfXMntV4zDXAuQa5EFuRxPBH\nRPQDIX7Y27GWmcX6Zh5tpTZENa09KNY382iMD90CKv4qGjNgwACYzWYWjaGIJoTAwYMHoaoqVq5c\niStXrrjdNiEhAbNnz4aiKJg4cSL/H6KgEfa7lclrC1X+mD0Tth+WM7o5U+bp7Jkh3gBDVGSt+GH4\nIyLyE3ulHbZiW9Wg6O7MY1ElIKH2vRvrmXk0NjMG7BeYa9EYq9WKU6dOefU8SUlJSE1NZdEYihhn\nzpxBdnY2VFXF8ePH3W4nSRImT54MWZbxyCOPoHHjxjr2khqCKssZ61iS6Mvsmb3sh+WMtQUtP8ye\nebKckdzD8EdEFCJst211zizWOfN4oxLGhJr3dnRn5tHY2Lu9Hf1ZNGbUqFHOWUEWjaGG4ubNm1i/\nfj1UVUVBQYFHn0X69u0LRVGQkZGBDh066NhLCjR7pb3W4h11HvNg9kyKkry6z8zt2bM4Q4O51SGS\nMPwRETUAwi5gu2mrHhTdnHm0l9mr7O3o6cyjIfburOP169eRl5cHq9WKzZs3e7SczVWnTp2cQZBF\nYyjc2Gw2bN26FaqqYuPGjbh9+7bbbVu1aoX09HQoioL777+fX4IEgXM5o5sFPbyZPXMsZ6y3oIeX\ns2eGhMhbzkjuYfgjIiLYK1z2dvR05rGoElJU9b0dpaYSjpYfxc6LO1FwqgBHzx/1qm/x8fGYNGmS\nMwyyaAyFqiNHjkBVVaxYsQLff/+92+1iY2Mxc+ZMKIqCqVOnIjo6WsdehjchBES58KocvruzZ/Yy\nOwxxhhqLd9R5zIPZMymGyxkpOBj+iIjIJ0Lc/Za8xqDocuy7775D/ol87PhuB/Zf248ye5lX5+ub\n3BfTJ97dYH7M5DGIbhLND1EUNN9//z1WrFgBTdNw+PBhj9qOHTsWiqJgzpw5aN68uU49DKxqyxk9\nmD1zd0ZNipI8K4fv6ewZlzNSA8bwR0REAVdWVoYdO3bAYrH4VDSmKZriQelBjG48GqNajUKLFi1q\nXapa2z2PhhgujSLPlJaW4r333oOmadiyZQvsdrvbbbt37w5FUZCZmYmuXbvq2MvqXJcz+rzBdC2z\nZ6JSuD9T5uXsGZczEnmP4Y+IiIJKCIHjx487g6AvRWOGDxiOlCEpmNRnEro37g7b9RqK6NzzsxQj\n1R4Ua7nP0flz0yjOEEQIu92OnTt3QlVVrFu3Djdv3nS7bWJiIhYsWABFUTB8+PAaZ6qdyxl92Ey6\nvtmzassZdZg943JGotDG8EdERCHl+vXr2LJlCywWi89FYxyby0+aNKnGojFC3L13qNZwWM89j7Zb\nde/tWN/MY6ht/kvVHT9+HJqmISsrC2fOnHG7XbQhGhOSJ+Chbg9hXOtxMJYZ6549K7VBMko1Fu/w\n2+xZPJczEkU6hj8iIgpZNpsNBw4cgNVqhcViwaFDh7x6HkfRGEcY7NSpk1/6Z6+0w3ajenh0t9qq\nsItaK6jWO/PYLAqGaC5/A35Yzljm22bSrseuFl9F3qU85FzPwbGKYx71ZVCbQZjVfxZmDJmBli1b\nuj97Fm/gf08i0h3DHxERhY1z584hJycHFosFW7duRWlpqVfPM2DAAGcQHDFiBKKiovzcU/fYyupZ\nllpXoCyuhDG+7r0d65p5NDbxbm9HT7kuZ/R2M+n67j2z3767nNHdjaNrOlYRXYGtR7ZiTcEafLjv\nQ1RWVrp9jZ07d4Ysy8jMzESvXr10HE0iIt8w/BERUVhyFI1xzAp6WzQmKSkJ06ffrR46ffp0JCUl\n+bmn+hCi6t6O9+7dWF+gtN22IapZ7Xs3OkNiUyNEhfBpRk0ySB4V9Kjz3rOajnm5nFEIgb1790JV\nVaxZswZFRUVut23SpAnmzp0LRVEwduxYGAyctSOi0MfwR0REYc9RNMYRBH0pGjNq1CjnrGD//v0b\n7D159spa9na8NygW3y2K4/W9Zwmht5zx22+/haZp0DQNJ0+edLud0WjE1KlToSgKHnroISQkJOjY\nSyIi/2P4IyKiBsdRNMZqtSInJ0fXojEUHq5fv441a9ZA0zR89NFHHrUdPHgwFEXBwoUL0bZtW516\nSESkP4Y/IiJq0FyLxlitVnz22WdePU9cXBwmT57s96IxpJ+Kigrk5uZC0zS8//77uHPnjttt27Vr\nh8zMTMiyjAEDBujYSyKiwGH4IyKiiOIoGmO1WrF161aUlJR49TyhUjSGqhJC4ODBg9A0DStXrsTl\ny5fdbpuQkIBHHnkEsixj8uTJMBqNOvaUiCjwGP6IiChi+atoTGJiIlJTU8OuaExDcvbsWWRnZ0NV\nVRw75v72DJIkYdKkSVAUBbNmzUKTJk107CURUXAx/BEREaFq0Rir1YqPPvrIo3L/DgaDASNHjoTZ\nbG7wRWOC7ebNm9iwYQNUVUV+fr5Hv+f79OmDRYsWISMjAx06dNCxl0REoYPhj4iIqAauRWM2b97s\n0fJBV65FYyZOnMgKkT6y2WzYtm0bVFXFxo0bPdrrsVWrVli4cCEURcGQIUMYyoko4jD8ERER1cNm\ns+GTTz6BxWLxuWjMpEmTnLOCLBrjvs8//xyqqiI7Oxvff/+92+1iY2Px0EMPQVEUTJs2DdHR0Tr2\nkogotDH8ERERechfRWP69+/vDIIsGlPdhQsXsGLFCmiahkOHDnnUdsyYMVAUBXPnzkXz5s116iER\nUXhh+CMiIvLBnTt3sGPHDues4LfffuvV8yQmJmL69OnOojEtWrTwc0/DQ2lpKTZt2gRN05CXlwe7\n3e522+7du0OWZWRmZiI5OVnHXhIRhSeGPyIiIj8RQuCrr75yBkFfi8aYTCaYzeYGXzTGbrdj586d\n0DQNa9euxc2bN91u27x5cyxYsACKomDEiBENepyIiHzF8EdERKST4uJibNmyBRaLxaeiMR07dnQW\njZk0aVKDKRrz1VdfQdM0aJqGM2fOuN0uKioKJpMJiqLAZDIhNjZWx14SETUcDH9EREQBYLfbceDA\nAeeegr4WjXGEwc6dO/u5p/q6cuUKVq9eDVVV8fHHH3vU9sEHH4SiKJg/fz5atmypUw+JiBouhj8i\nIqIgOH/+PHJycmCxWHwuGuMIgiNHjgzJojF37tyB1WqFqqrIyclBRUWF2207derkvI+vd+/eOvaS\niKjhY/gjIiIKMkfRGMesYEMoGiOEwL59+6CqKlavXo2ioiK32zZp0gRz586FLMsYN24cDAaDjj0l\nIoocDH9EREQhxFE0xhEE/VE0xmQyYcCAAQEphvLtt98iKysLmqbhm2++cbudwWDA1KlToSgKZs6c\n2WDuayQiCiUMf0RERCHMUTTGarUiJycnJIvGXL9+HWvXroWqqvjoo488ajt48GDIsoyFCxeiXbt2\nfusTERFVx/BHREQUJkKpaExFRQXy8vKgaRo2bdqEO3fuuN22Xbt2yMjIgCzLGDhwoMfnJiIi7zD8\nERERhSlH0Rir1YoPP/zQ66Ix/fr1g9lsrrdojBACn376KTRNw4oVKzyahYyPj8cjjzwCRVEwefJk\nGI1Gr/pKRETeC3r4O3v2LJYsWYKtW7dCCIGUlBQsX74cHTt2rPcEv/vd7/DJJ5/g4MGDKCoqwj//\n+U8sWrSo5s4w/BERUQOmZ9GYs2fPIjs7G5qm4ejRo24/lyRJmDhxIhRFwSOPPIImTZp41SciIvKP\noIa/0tJSDBo0CPHx8XjxxRcBAM8++yxKS0tx5MiReu9HaNq0Ke6//3507doVqqrinXfegaIoNXeG\n4Y+IiCKEa9EYq9WKXbt2eV00plevXjh+/LhHv0P79OkDRVGQkZHh1pe5REQUGEENf6+99hqefvpp\nnDhxAsnJyQCAwsJC9OjRA6+88gqWLFni1olOnjyJHj16MPwRERHVwF9FY+rSsmVLpKenQ5ZlDB06\nNCCVRYmIyDNBDX+TJ09GeXk5du3aVeX4hAkTAAAFBQVuneibb75Bz549Gf6IiIjq4Vo0xmq14tNP\nP/X6uWJiYjBz5kzIsozp06cjOjrajz0lIiJ/0zMT1bsj65dffon+/ftXO963b1+P7ikgIiIi9xgM\nBgwfPhy///3vcfDgQZw7dw5vv/02Hn74YTRq1Mit5xgzZgz+8Y9/4MKFC1izZg1mzJjB4EdEFOFq\nLhXmoqioCImJidWOJyUloaioSJdOERER0Y/at2+Pn/70p/jpT39apWiM1WrFyZMnnY/r1q0bZFlG\nZmYmunXrFsQeExFRKKo3/BEREVHoiI2NxdSpUzF16lQsX74cJ06cwKFDh5CcnIxhw4bxPj4iIqpV\nveEvMTGxxhm+a9euISkpye8dWrZsmfPnCRMmOO8tJCIioqokSUKvXr3Qq1evYHeFiIi8VFBQ4HYd\nFV/5VPBFkiTk5+e7dSIWfCEiIiIiIqpbUAu+PPTQQ9i3bx9OnTrlPFZYWIg9e/bgoYce0qVTRERE\nRERE5F9ebfK+dOlSlJSUVNnk/fTp0+jWrRuef/55LF261Nl+x44duHz5Mi5cuIDFixfjqaeewvjx\n4wEAc+bMqdoZzvwREREREVEEC+o+fwBw9uxZLFmyBB9++CGEEEhJScHy5cvRqVMn52MKCwuRnJyM\nZcuW4bnnnnMenzhxInbs2HH3ZC4XIkkSbDZb1c4w/BERERERUQQLevgLFIY/IiIiIiKKZEG954+I\niIiIiIjCH8MfERERERFRBGD4IyIiIiIiigAMf0RERERERBGA4Y+IiIiIiCgCMPwRERERERFFgKhg\nd4CIiIjuEkLgjt2O23Y7Su12lNpsVf6+fc8/l9psuP3D46MlCQlGI+INBsQbDM6fEwwGxNfxc4wk\nQZKkYF86EREFAMMfERFRPRyhrMZA5kFIcyfQBXq3WwNwNzAajXcD4T0/1xgoazjmTuCMMxhgYNAk\nIgoabvJORERhSwiBsntCVU3By5OQVtNjbwchlDVUcY5A6GHg9CZ8Ghk0iSgM6ZmJGP6IiMjv7I5Q\nVkfwcs6GuRHS6nosUW2iJckZBPUOnNFcPktEfsLwR0REfmEXwhmi/BG8anssQxlFGiNQ572V/gyc\ncQYDgyZRA8bwR0TUwNmEwO1a7gurM5B5GNLKGMpCXswPhVsSfvjAn2Coupyx2jGjEXEGAypcCsW4\nvpZuu7wOavq5gr93w44El+WzHgZOb8In79MkCiyGPyKiIHGEMm+Dl7uPvcP3vpAXe08oi78niLkT\n0up7bDDuU6t0hEGXLwpc/67t55pCZn2Bk18+hKcYDyrJ+ho4ow3chYyI4Y+I6B6OD6z+qrBY22PL\n+Z4U8uJcApQvwauux8YZDCwe4geOe0FrDZReBM66ZjX5f2/4iZIkryrJerO8NpbLZylEMfwRUdio\ndAlQvgavuh7LUBb6XD9s+XN2jEvSyB1CCJQLUX+g9FPgrOR7UtiRAJ+2LvFktpPbnJAnGP6IyGcV\n93xw8WcZfNfH8v6h0KfX7JjrY/lBhyKN455LtwKlj8touUw8PMXWtnxWh8AZxeWzYY3hj6iBEkKg\nwqX6orcVFt0JafxWOvTpNTvmepxVAonCn82xfPae93q97kSpTMgAABCzSURBVNuk8BNd3/JZL2Y7\nawucMdzmxO8Y/ogCzBHK9CqD7/rPtmBfLNVJAnSbHXM9xlBGRKFICIE7jkDo5aymu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u3RubN2+WmI7ZxsYGEREROH78OHJzc6GjowNHR0eEhYWha9euAvWMGTMGXC4X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\nQ2hpacHJyUnq66KSJCQkYMaMGWjfvj10dXWhpaW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+ "text": [ + "" + ] + } + ], + "prompt_number": 209 + }, + { + "cell_type": "heading", + "level": 3, + "metadata": {}, + "source": [ + "Generic + Advanced + BusTrain model" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices+BusTrainFeatureIndices], cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices+BusTrainFeatureIndices], cleanedResultVector, \"Generic + Advanced + BusTrain\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic_advanced_bustrain.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Found 788 high confidence predictions out of 1462\n", + "Found 817 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 794 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 816 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 795 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.9, percentage auto classified 0.548788800655\n", + "for prob 0.9, scoring only on high confidence predictions 0.978341573209\n", + "for prob 0.9, scoring on all predictions 0.881894042178\n", + "Found 792 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 830 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 774 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 801 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 756 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.540984334138\n", + "for prob 0.95, scoring only on high confidence predictions 0.978013656103\n", + "for prob 0.95, scoring on all predictions 0.881073155111\n", + "Found 836 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 824 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 773 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 772 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 795 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.99, percentage auto classified 0.547414725405\n", + "for prob 0.99, scoring only on high confidence predictions 0.979356062844\n", + "for prob 0.99, scoring on all predictions 0.883810069561\n", + "[0.54878880065468716, 0.54098433413764724, 0.54741472540498926]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[0.79008694016134284, 0.79046055410527649, 0.79363503042505967]\n", + "[0.52809900619475081, 0.4854978348275244, 0.51790730238794569]\n", + "[0.058181517699703811, 0.048267991735483996, 0.035403916674729453]\n", + "[0.16395550186247859, 0.15525636257372083, 0.16476490722392362]\n", + "[0.34803798635856076, 0.34529305455983755, 0.3474681452403906]\n", + "[0.34115539680804424, 0.22000000000000003, 0.3474681452403906]\n", + "[0.97834157320913318, 0.97801365610338631, 0.97935606284397658]\n", + "[0.88189404217825818, 0.8810731551108576, 0.88381006956051134]\n", + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[[ 95. 1. 0. 0. 3. 0.]\n", + " [ 5. 85. 2. 0. 7. 0.]\n", + " [ 8. 7. 63. 1. 21. 0.]\n", + " [ 5. 2. 6. 49. 39. 0.]\n", + " [ 3. 2. 4. 2. 89. 0.]\n", + " [ 12. 3. 4. 3. 3. 74.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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xAx07dkRQUBAMDAyQlJSE8PBwnDlzBrt37xZdV2xsLA4ePIiRI0di4MCBSEhI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\nx+Txxx+X1tZW2bt3r8yZM0c/GDp/AAAAACzMp6d9PvPMM/Lgg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5tlUmk5W8yaaGDRtSoUIFwsPDpfjw4eHhmJmZER4ezvTp06U0IyMj2rRpw717\n9zAxMWHmzJnY29tz//595s+fT8uWLbl27ZrWjiISEhL44IMPSEhIICoqSgonLBAIihZdLUMnJ6d8\nw5K7uLho3Dk1bty4PHdAqUPbEOpvlUYql8tp06YNERERQPab68iRI3z22WecPn1aihUeERHBe++9\nh4WFBTVr1uTbb7+lR48etG7dmo8++ohffvmF+Ph49uzZo1W9t2/fpmXLlmRmZnL8+HEhRAWCN4gu\nC/Lfdt4qQQrZseOjoqJIS0vjwoULJCYmMmHCBExMTKR1ZhEREXh7e0vXrFy5kvr162NpaYmRkZEk\nCGNiYvKt7/Lly7Ro0QJnZ2ciIiKkpRKaULrCCw0NJTIyUveOCgRlFF29P73NvFWmPWQL0tTUVI4f\nP865c+do0KABdnZ2tGrVivDwcBwdHXn8+DE+Pj5A9hjq559/zvjx4+nUqRPW1tZkZmbi6emZa/uX\nOo4cOUJCQgILFy7M14MMUCh/ogKBoHRO+r51gtTDw4NKlSoRHh7O+fPnJYHp4+PDtm3bcHR0xNjY\nWBpD3bp1K+3bt+ebb76RyoiNjdW6vuHDh5OYmEhAQACGhoZ8+OGHRdshgUCgQmkUpG+daS+TyfDy\n8uLAgQMcPXpURZCeP3+eHTt20KxZM2mHwatXr3J51tF2gFhZ39KlSxkxYgS9e/fOdzBbIBAUDmHa\nFxPe3t6MHDkSQ0NDadtYw4YNKVeuHBEREYSEhEh5O3fuzNy5c5k9ezZNmjQhPDxcxeegtixatAgD\nAwP69OlDVlYWH3/8cZH1RyAQ/Edp1EjfWkEK0LhxYylWjlwux8vLi507d6pMNAUHB5OYmMiiRYtI\nSUnBy8uLffv25XKBpc16sPnz52NoaEjfvn1RKBT06tWriHsmEAhKoyAVwe8KgL4DcunbObA+TS59\nP6aFDX5XWEpT8Lvbt2/nm69atWp6/84LwlupkQoEgtJLSRKQ2iIEqUAgKFZKoyB962btBQJB6UYf\n4Zjlcrnaz8WLF3PlvXfvHoMGDaJKlSqYmpri6uqapws9EBqpQCAoZvQRjhngk08+UfEUBVCjRg2V\n47i4OFq2bImbmxtLly7F3t6e2NhYbt68mWfZQpAKBIJiRRdBWphwzEocHBxo2rRpnnmGDx+Ok5MT\nERERUgjtnJ77NSFMe4FAUKzoYtoXJhyzkvwE+M2bN9m/fz+jR4+WhKi2CEEqEAiKleIOx6xk5cqV\nmJqaYmGk4DRvAAAgAElEQVRhQbt27aQwzUqUfpBNTU3p0KEDpqam2NjYMGDAABISEvIsWwhSgUBQ\nrOgiSAsTjhmgX79+rFy5kkOHDvHdd9/x9OlTfHx8OHz4sJRH6Qx+0KBBuLu7s3fvXubOncuuXbvo\n1KlTnhqtGCMtILa2tnqr+8GDB3qrG7Id6+oLbTx5vUnKly+v1/r1vSC/KFFnup86dYpTp069sTqV\nE1QALVu2xN/fn3fffZegoCCOHDmi0i5vb2+WLl0KgJeXF1ZWVvTu3Zt9+/bRuXNnteULQSoQCIoV\ndZpdkyZNpCB0ACtWrFA5X5hwzOooV64cXbp0UXFwlFfYZoDo6GghSAUCwduBLrP2hQnHnBc5/W9o\nG7ZZHWKMVCAQFCu6zNr7+flx4sQJFV/DynDMfn5+BW7D8+fP+eOPP1SWQ3l6elK5cmUpTLOS18M2\nq0MIUoFAUKzoMtk0ZMgQXFxc8Pf3JywsjLCwMPz9/dWGYzY0NJQCZUK2V7fPPvuMn3/+mcjISNav\nX0/Lli159OgRM2fOlPIZGBgwZ84cdu3axWeffcb+/ftZsWIFI0eOxNvbW/KNrA5h2gsEgmJFF9Ne\nGY553LhxBAQEoFAoaN++PYsXL843HLO7uzs7duxg+/btJCUlUb58eVq1asW6deto3LixSj39+/dH\nLpczd+5c1q1bR8WKFQkICGD27Nl5tk+40SsAMpmMSpUq6a3+q1ev6q1uKNuz9lWrVtVr/cqlOfqi\nKN3onTt3Lt98jRo1KlHOTYRGKhAIipWSJCC1RQhSgUBQrJTEmEz5IQSpQCAoVkqjRlpmZu1DQ0OR\ny8tMdwWCtxZdZu3fdsqURppf8DuBQPDmEaZ9CackvukEgtJGafwdvhW2bnR0NN27d6dSpUqYm5vj\n7u7OnDlzGD16NJUrVyYjI0Ml/7///oulpaWK+//Hjx8zYsQInJycMDU1pVq1avTv35+0tDSN9WZk\nZDB79mzc3d0xNTXFwcGBwMBAUlNT31hfBYKyjjDt3wCnTp3Cy8uLmjVrsnjxYhwdHYmJieHSpUuM\nGDGC5cuX89tvv9GzZ0/pmi1btpCcnCztaHj27BktWrQgMTGRqVOnUq9ePR4+fEhYWBjp6ekYGxur\nrbtfv3788ccfTJw4kRYtWnDlyhWCgoKIi4tj+/btxdJ/gaCsIUz7N0BgYCC2tracOHECU1NTINt1\nlZK2bduyevVqFUG6evVqOnXqhLOzMwCLFi0iNjaWs2fPUr9+fSlf7969NdZ79OhRtm3bxsaNG+nb\nty8APj4+2NjY0K9fP6Kjo1XKEggERUNJ1DjzQ6+mfXJyMn/++Sd9+/aVhOjrjBgxgoiICG7cuAHA\n6dOnuXDhgsr+2v3799O0adMCCb69e/dibGzMhx9+SEZGhvRRusxS+igUCARFS2k07fUqSJ89e0ZW\nVhaOjo4a83Tv3h17e3tWr14NwKpVq3BwcMDX11fK8/Tp0zzLUMejR49IS0vDwsICY2Nj6WNvb49M\nJtMYWuDly5fSJ6/xV4FAoB59hGPOyZw5c5DL5WqD2j1+/JhRo0bh6uqKubk5rq6ujB49midPnuRZ\npl5Ne2tra+RyOXfv3tWYx9DQkE8//ZSVK1cyYcIEtm7dypdffqmyJtTW1jbPMtRRsWJFTE1Nc8Vt\nUVKlShW16RYWFgWqRyAQqKKvcMwAt27dYsaMGdjZ2eVaDqlQKPD19eXWrVtMnz6d2rVrc/nyZYKD\ngzlz5gxRUVEay9WrRmpubk6rVq3YtGlTnk4phg0bRmJiIj169CA9PZ0hQ4aonO/YsSOnTp3i4sWL\nWtf9/vvvk5KSQmJiIo0aNcr10SRIBQJB4dDFtFeGY96xYwd+fn74+fkRFhZGfHy8ZK1qw2effUZA\nQAC1a9fOVU9MTAynTp1i5syZDBs2jDZt2vDZZ58xY8YMTp48yfXr1zWWq1EjrV69us4L2G/duqV1\n3vnz59O2bVuaN2/O+PHjcXBw4NatW0RHR/Ptt98CSKa88iY6ODiolDFu3Di2bNlC+/btmTp1Ku++\n+y5PnjwhLCyMVatWUa5cuVz1tm3blv/7v/+jR48efPHFFzRp0gS5XE5cXBx79uxh7ty51KhRQ6f+\nCwQCzegya59fOGZt4tpv2bKFCxcu8PPPP9OtW7dc8i0zMxMAKysrlXTlcV7t1qiRKv36FfRTULW9\ncePGHD9+HCcnJ0aPHk3Xrl1ZsGBBLpdtPXr0AFCZZMrZ0ePHj9O9e3fmzJnD+++/T2BgIEZGRtLS\nJ5lMluvGbdq0idDQULZv3063bt3o2bMny5cvp2bNmtjb2xeoHwKBQDv0EY752bNnjBs3jnnz5lGh\nQgW1eerUqUPHjh2ZPn06Z8+e5cWLF5w6dYqvv/6aLl26UKtWLY3llxh/pH379iUqKqpA2m5RI/yR\nCn+k+qI0+SPdt29fvvleD39sYmLC+PHjmTVrlkq+qVOnMnfuXNLT0/Ms79NPP+X69etS+GUvLy+y\nsrJyrc559eoVPXv2ZPfu3VLaBx98wLZt2zSuLIK3YB1pfpw4cYILFy6wbds2Fi1apO/mCASCQqLO\nRL548WKB5jgKwtGjR9m4cSPnz5/Pt109evTgwoULrF69mtq1a3PlyhVCQkLo0aMHO3fu1DjcqZMg\n/ffff4mJiSE5OVntEoKipEWLFlhaWjJw4EBGjBjxRusSCARvHnXarYeHBx4eHtLx5s2bVc4XJhzz\nsGHDGDx4MA4ODiQmJgLZ28OzsrJISkrCzMwMY2Njdu7cyZ49ezh06BDe3t4AtGrVCldXVzp27MjO\nnTs1Btor0Kz9rVu38PX1xdramiZNmqjsQDp27Bh16tQhIiKiIEXmi7Kza9asEW7wBIJSgC5jpIUJ\nx3zt2jVWrVqFtbU1NjY22NjY8Oeff3LixAmsra1ZtWqVVBaQK46TMnrotWvXNNahtUYaFxeHp6cn\niYmJdOvWjfv376usq2rWrBlPnjxhy5YtkjQXCASC19Fl1t7Pz4/AwEBiY2OpXr068F845rlz5+Z5\nbUREhIpJrlAoGDt2LFlZWSxduhQ3NzcAaVPP6dOnVSKGnjx5EiDXaqGcaD3ZFBAQwLZt2zh8+DCe\nnp6Ehoby9ddfq9yUjz76iGvXrnH58mVtiixxiMkmMdmkL0rTZFNYWFi++fz8/FTqTE5Opn79+piZ\nmTFjxgwAgoKCePnypcqC/Pj4eNzc3AgJCSEoKEhj+V5eXmRmZnL06FEp7cWLF9StW5eMjAyCgoKo\nVasW165dY9q0aZiamnLlyhWNC/+1tpUPHDjAhx9+iKenp8Y8zs7O3Lt3T9siBQJBGUQX014Zjrlm\nzZoEBATQr18/3NzcCA8PzzccszrULYcsV64cUVFRdO3alW+++Ub66+/vT1RUVJ67p7Q27RMTE6lW\nrVqeeTIyMsT+c4FAkCe6utFzcnLK172li4uLVuVrmsupWrUq3333XYHbprUgrVq1ap6DrQAXLlyQ\nxi8EAoFAHSVk6XqB0Nq0/+CDD9i1a5dGJx+///47x44dw9/fv8gaJxAISh+l0Y2e1hrp5MmT+eWX\nX+jQoQODBw+WvC199913REVFsXHjRpycnAgMDHxjjX0byGt3w5tG346md+7cqbe6O3furLe6AerV\nq6fX+vU92VSUlGkP+ZUrVyYyMpL+/fuzYsUKKX348OEANG3alC1btuS7OFYgEJRtSqLGmR8F2tlU\no0YNoqKiOHfuHCdPniQhIYHy5cvTrFkzmjZt+qbaKBAIShFlXpAqUfrsFAgEgoJSpk37nFy4cIGL\nFy+SlJSElZUV9evX1/v4nUAgKBmUeY00KiqK4cOHc+nSpVznPDw8WL16dZ4L9gUCgaBMC9LTp0/T\nrl07UlJS6NChAy1btsTe3p6HDx9y7NgxDh48SLt27YiMjJQ2+QsEAsHrlEbTXut1pBMnTiQzM5OD\nBw+yb98+goODGTZsGMHBwezfv58DBw6QkZHBpEmT3mR7BQJBCUfXdaTFEUVUoVAwe/ZsXFxcMDMz\no0GDBvz666/5lqm1ID158iS9evVS8YqSk3bt2vHxxx9z4sQJbYsUCARlEF3CMSujiMbExLBhwwY2\nbtzI9evX8fb2Jjk5Weu684oiCtke96dNm8aYMWPYu3cvnp6e9OzZkz179uRZrtamvbGxcb7efxwd\nHTExMdG2SIFAUAbRZYxUGUU0JiZGCoBXr149atSowerVq7UKfgf/RRG9du0aGRkZKucePXrE/Pnz\nmTx5Ml988QWQHSTzxo0bTJw4kffff19juVprpO3atcvXafPhw4c1aqxFRWhoKHK5vFSOswgEZQFd\nTPv8oohqgzKK6OzZs1EoFLk00n379pGenk6/fv1U0vv168elS5eIj4/XWLbWgnT+/Pncu3ePTz75\nJJervLt37zJw4EDu3bvHwoULtS1SZ3QNEy0QCPSPLqZ9cUQRvXz5MiYmJpKj55x1AHnWo9G09/b2\nziWwrK2tWb9+PZs3b8bZ2Rk7OzsePXpEfHw8GRkZ1KtXjwEDBhAeHp5vxwpDaVw+IRCUFXT5/T57\n9gxra+tc6TY2NmpjOb3Ol19+ibu7OwMGDNCYJyEhQWMdyvOa0KiRHj58mMjISJWPMspfRkYGN2/e\nJCoqips3b0pjDRcvXiQyMjLfThUFV65cwdvbGwsLC6pWrUpISIj0Bf3444/I5XJu376tco1yWCAn\nS5YsoXbt2pibm2NjY0OTJk3YsWNHsfRBICiLFLf3J2UU0ZUrV2rVNl3QqJG+7WOQ3bp1Y/DgwUyZ\nMoW9e/cyffp05HI5ISEheV6XU8vevHkzgYGBhISE0Lp1a169ekV0dLRWbziBQKAb6mTL33//TUxM\njMZriiOKqLW1tXT+9TqAPOt56+Paa2Lo0KFMmDABgPbt2/P8+XMWLFjA2LFj87wu5xsnKiqKevXq\nMXXqVClN3+7aBILSjjqtr2bNmtSsWVM63rVrl8r5wkYRVUYSfR1ra2sWL17MmDFjqFu3Lqmpqdy8\neVNlnFQ5NppXPSU2vvHHH3+sctyrVy9evHih9mZromnTply4cIExY8Zw8ODBAq1HEwgEuqGLae/n\n58eJEyeIjY2V0pRRRDXFmlcSERGhMkQZERFB/fr18fDwIDIyko8++giA999/HyMjIzZv3qxy/aZN\nm/Dw8MDZ2VljHQXWSG/fvk1kZCT3798nNTVVbZ7g4OCCFltg7O3t1R4XxAFu//79SUlJYe3ataxY\nsQIjIyO6dOnCwoULNd60pKQk6X8TExO9OnoWCEoiugwbDhkyhGXLluHv768SRbRatWoMGzZMyqcu\nimjbtm1zlWdlZUVmZiZt2rSR0mxtbfniiy+YPXs2lpaWNGzYkJ9//pmIiIh8nZoXSJCOGzeOpUuX\n5nsjikOQPnjwQCU+1MOHD4Hs2NPKSabXA/E9ffo0VzlDhw5l6NChJCUlsW/fPsaPH0+vXr007tCy\nsrIqqi4IBGUSXSZ0lFFEx40bR0BAAAqFgvbt27N48eIiiyIKMHPmTMqVK8eSJUt48OAB7u7u/O9/\n/6NLly55lqe1IF25ciVLliyhU6dODBkyhB49ejBgwAA6d+7M8ePH+e677/D19WXUqFHaFlkotm3b\nxldffSUdb926FUtLSzw8PKQbdOnSJd555x0ge3B5//79GtegWllZSVtcdYkiKBAItEPXmfHiiCIq\nl8uZMmUKU6ZMKVDbtBak33//Pa6urvzxxx8YGBgAUL16dXr16kWvXr3o06cPbdu2lcYb3jTff/89\nWVlZNG7cmH379rF27VqmTZuGpaUlTZs2xc3NjS+//JKsrCyMjY1ZsWIFaWlpKl/i0KFDKV++PJ6e\nntjZ2RETE8OmTZvo1KlTsfRBICiLvO0rgnRB68mmv//+m06dOklCFFDZq+rp6Ymvry8LFiwo2ha+\nhlIl//333zlw4AD+/v5s2bKFoKAgaUzEwMCA33//HScnJwYOHMjo0aPp1KkTAwcOVNFIW7Vqxdmz\nZxk5ciQdO3Zk1qxZBAQEsH79+jfaB4GgLFOmo4gaGBhgaWkpHVtYWPD48WOVPK6urvl6SSksISEh\n0lrRvHZQ1alTR636nnOdaf/+/enfv3/RN1IgEGikJArK/NBakDo6OkohmAFq1arFkSNHVPKcOXNG\n4z5WgUAggDJu2nt5eXH48GHpuFevXly9epWuXbuyYsUK+vTpQ2RkJB07dnwjDRUIBKWDMm3aDxo0\niMzMTO7cuYOTkxNjxowhMjKSPXv2SOZ848aNmTt37htrrEAgKPmUREGZH1oL0vfee4/33ntPOjYx\nMWHXrl2cPn2amzdv4uzsTLNmzXI5BREIBIKclEbTvtB77Zs0aSKC3QkEAq0p0xqpQCAQFAVlSpCq\nc+ysLW/asbNAICi5lCnTPucMvUAgEBQVumqkd+7cYdy4cRw8eFBlr31+QTnj4+MZM2YM0dHRPHr0\nCAsLC+rWrctXX32lEtAuJiaGpUuXcujQIe7cuYOlpSVNmjRh+vTp1KtXL886NM4MaRNXRdt4KwKB\nQKBEl+VPhQnH/PLlS2xtbZk5cyZ79uxh7dq1WFpa0rVrV5VoGPv37yciIoJBgwaxc+dOVqxYwePH\nj/H09OTcuXN51iFTlMYBizeETCbL1xv3m+TFixd6qxvQ62aLr7/+Wm91AyqbUfSB0nWcvigqMSGT\nyQgNDc03X2hoqEqdS5YsYfz48SrhmOPi4qhRowbz5s3TOhyzkszMTKpXr07Dhg2lKKRPnz6lYsWK\nKvmeP3+Oi4sLvr6+eW4dF2uVBAJBsaKvcMw5MTAwoHz58iq+Q14XogDly5enRo0a+fo5FoJUIBAU\nK7oI0sKGY1bWm5GRwYMHD/j666+5fv06I0eOzPOahIQE/vrrL2rXrp1nPrH8SSAQFCu6zKMUNhwz\nZIdkXrhwIQBmZmZs3ryZdu3a5XnN6NGjkclk+caCE4JUIBAUK/qalhk3bhx9+vThwYMHrF+/nn79\n+mFmZkbXrl3V5p89ezY//fQTP/zwg8qQgjqEIBUIBMWKOkEaHx9PfHy8xmsKE45ZiYODAw4ODgB0\n6dIFb29vAgMD1QrSVatWMWXKFGbOnMnAgQPzLVsIUoFAUKyoM+2dnJxU1oMeO3ZM5XxhwjFr4r33\n3mPJkiW50jdu3MjIkSMJDAxk0qRJWpUlJpsEAkGxUtzhmNWRlZXFsWPHpJhuSn777TcGDRrEkCFD\nmDdvntblFUiQpqens2DBApo0aYKlpaXK0oELFy4wYsQIYmJiClKkQCAoY+iyqWfIkCG4uLjg7+9P\nWFgYYWFh+Pv7qw3HbGhoyPTp06W00NBQPv/8c37++WcOHz7Mzz//TOfOnTlz5gzTpk2T8h05coT/\n+7//o379+gwYMIATJ05In/Pnz+fZJ61N+5cvX9K+fXtOnjyJra0t5cuX5+XLl9L56tWr8+OPP1Kh\nQgVmzZqlbbECgaCMUdzhmN977z0WL17M1q1bSUpKonLlyjRo0ICjR4/SvHlzKV9ERARpaWmcP3+e\nli1bqtTv4uLCrVu3NLZPa4105syZnDx5knnz5nH//n2GDBmict7Kyoq2bduyf/9+bYtUy44dO1i0\naFGhylDHwIEDqV69epGXKxAICoauHvKV4ZiTkpJ4/vw5v/76K9WqVVPJowzHHBwcLKX5+vpy6NAh\nHj58SEpKCnFxcezYsUNFiEJ2PLesrCwyMzNzach5CVEogCDdtm0bPj4+BAYGanTeXL16dW7fvq1t\nkWrZsWOHtNarKAkODlbZVysQCPRDafTXobVpf/fu3Xxj1ltYWJCUlFToRmlDamoqJiYmWufPbx2Y\nQCAoHkqjew+tNVIrKysePHiQZ54bN25gb2+vc2MGDhzIhg0buHfvHnK5HLlcTvXq1Tl8+DByuZzf\nfvuNIUOGYGtrS+XKlaU6AwICcHV1xdzcHDc3N0aMGEFiYmKusnOa9nFxccjlcr777juCg4OpWrUq\n1tbW+Pn5ce/ePZ37IBAI8qZMB79r06YNO3bs4MGDB5IQy0lMTAy7d++mT58+OjcmODiYJ0+ecPr0\naXbu3Alkx4ZSCsXRo0fTpUsXNm/eTEpKCgD379/H0dGRhQsXUrFiRW7dusWsWbPo0qULf/75p0r5\n6hxVz549m5YtW7Ju3ToePnzI+PHj6devHxERETr3QyAQaKYkmu75obUgnTx5MmFhYbRq1Yo5c+ZI\nwi0mJoaoqCgmTZqEgYEBEyZM0Lkxrq6uVKpUCWNjY5o2bSqlR0ZGAtCsWTO+++47lWtat25N69at\npePmzZvj5uZGmzZtuHDhAg0aNJDOqXvTVa9enU2bNknHjx8/5ssvv9T4whAIBIWjJGqc+aG1IG3Y\nsCFbt25lwIABfPzxx1K6u7s7AOXKlePnn3/O10tKYejevXuutLS0NObPn8+GDRu4ffu2pKlCtpDP\nKUjV0aVLF5VjpYeZ27dvqxWkOZ3IGhkZYWRkVKA+CARlnTItSCFbkLVu3ZoNGzZw8uRJEhISKF++\nPM2aNeOTTz7B1tb2TbUTgCpVquRKmzRpEsuWLSMkJIQWLVpgaWnJnTt3+PDDD1WEqiZe36ernMDS\ndG3ONWsCgaDglGnTXkmlSpX44osv3kRb8kXdGKdSS548ebKU9vz58+JslkAgKABlXiMtDkxMTHj1\n6pXW+V+9eoWhoWo31q1bpzavrlFRBQJB0VGmBem0adO0FkQ5dxUUlLp167JmzRpWrVrFe++9h6mp\naZ75O3fuzPr16/Hw8MDNzY1ff/2VqKgotXlL4xcoEJQ0yrRpn3Nzf34URpB++umnnDhxgsmTJ5OY\nmIiLiwvr1q3TKMSXLl2KQqFgypQpAHTt2pWffvpJZdYfsrVRbV8EQnMVCN4cxR2O+fTp06xatYqj\nR49y7949KlWqROvWrZkxYwYuLi4ar9u6dSt9+vTBwcGBO3fu5FmH1oI0PDxcbXpSUhLnz59nyZIl\ntG/fnlGjRmlbpFrMzc3ZsmVLrvTMzEy1+StWrMhPP/2UK/31t97r5r5yT+7reHl5aaxLIBAUHl0E\nqTIcs5mZGRs2bABg6tSpeHt7c/HixTwngbdt28bVq1f5/PPP8fDw4N69e0yfPp3GjRtz4cIFHB0d\nc12TmJjI2LFjqVy5slaKldaC1MvLS+M5f39/+vbtS6NGjfLdRioQCMo2upj2a9asITY2ViUcc716\n9ahRowarV6/OMxzzhAkTcq0oatmyJdWrV2fNmjVqre0JEybQsGFDKleuzMGDB/NtX5E5dq5Rowbd\nunVj7ty5RVWkQCAohRR3OGZ1yzKrVauGra2t2jDLx48fZ/PmzSxfvlxr7blIPeTb2dlx7dq1oixS\nIBCUMvQVjjknV69e5dGjR7k2EKWnpzN06FAmTJhQIEdHRbb8KTU1lX379lGhQoWiKlIgEJRC9BWO\nWUlGRgbDhw/Hzs6OwYMHq5ybO3cu6enpWsdqUqK1IF2/fr3aQdeMjAzu3r3L1q1buXbtGmPGjClQ\nAwQCQdlCncb54MEDHj58WCz1jxo1ihMnTrBr1y6srKyk9Bs3bjBr1ix27NiBsbGxlF6kk02ffPJJ\nnudlMhl9+vRhzpw52hYpEAjKIOoEqb29vYoLzkuXLqmcL4pwzAATJ05kzZo1bNiwgfbt26ucGzNm\nDD4+PjRr1kxyypSWlkZWVhZJSUmYmJhoXNeutSD94Ycf1KbL5XKsra1p3Lix2r3wAoFAkBNdTPui\nCMc8c+ZM5s2bx7Jly+jbt2+u81evXiU+Pl7tEIK1tTVjx47VGL1Da0E6cOBAbbMKBAKBRnRZR+rn\n50dgYCCxsbGSg3ZlOGZtVgp9++23BAUFMWvWLEaMGKE2z9atW0lNTVVp55w5czh79izbt2/HwcFB\nY/laz9rb2NjkGpgVCASCgqLLrH1hwjFv3bqVsWPH0rlzZ7y9vVXCLF+9elXK16xZM9q0aSN92rZt\ni729PSYmJrRp0wY3NzeNfdJaI83MzHzjbvJKAtq45ntT6Hvrqj77ru9JzKdPn+q1/hkzZui1/qJE\nF9O+MOGY9+3bh0wmY+/evezdu1elXC8vL427NkH7reUyhZZ6dvv27TExMWHXrl3aZC+VyGQyvfoj\n1ffW1YIEGyxq9CnEQf+C1NLSUq/1F5XDH5lMRo8ePfLNt3379hLlZEhr0z40NJSDBw+qhOUQCASC\nglKmg98dOnSItm3b0r9/f7799lsaN26Mvb29WrW3MN6fBAJB6aY0utHL07SvXr0648aNY8yYMcjl\n2u8mLY03CoRpL0x7/VGaTPtu3brlm2/Hjh0lSjPNUyONj4+XFqbmNSArEAgE2lKSBKS2FIkbPYFA\nINCW0mixvnUxmwQCQemmTGukAoFAUBSUSY108eLF/PjjjwUq9NatW7q2RyAQlHLKpEaamJgoTTgJ\nBAJBYSmNgjTfNU0hISFkZWUV6CMQCASaKI0yJF9Bqu/93fpAoVCQnp6u72YIBKUSXXc23blzhx49\nelChQgWsrKz46KOP8g2TrGTy5Ml07NiRihUrIpfLWb9+vca89+7dY9CgQVSpUgVTU1NcXV2ZPHly\nnuUXacwmfRAdHU337t2pVKkS5ubmuLu7S86l9+/fT5cuXahatSoWFhZ4eHiwcOHCXG88FxcXAgIC\n+OGHH3B3d8fExITdu3frozsCQalHF0GqDMccExPDhg0b2LhxI9evX8fb25vk5OR861y2bBmpqan4\n+voCmhXEuLg4mjZtyo0bN1i6dCkHDhwgNDQUIyOjPMsv0bP2p06dwsvLi5o1a7J48WIcHR2JiYmR\nvGvHxsbi4+PDqFGjsLCw4PTp04SGhvL48WNmz54tlSOTyYiIiCA6Oppp06ZhZ2eHs7OzvrolEJRq\nijscM8Dz588BuHnzJhs2bNCYb/jw4Tg5OREREYGBgQEArVu3zrd9+QrSt3lgODAwEFtbW06cOCGF\nACWEnxEAABZdSURBVMi5cSCnn0KFQkHLli1JTU1lwYIFKoJUoVCQmJjIuXPnsLOzK7b2CwRlEV1k\nSn7hmPMTpNrUffPmTfbv38/GjRslIaoteZr2WVlZhISEFKjA4iI5OZk///yTvn37aoyjcv/+fYYN\nG4azszMmJiYYGxsTFBREUlISjx49Usnr6emplRBNS0uTPvre+y4QlETehnDM6jh+/DgApqamdOjQ\nAVNTU2xsbBgwYAAJCQl5Xltix0ifPXtGVlYWjo6Oas9nZWXh5+fH7t27CQ4OJiIigjNnzjBlyhQU\nCoWKEwyZTKZ1vCljY2PpU9C3lkAg0G3WvijDMWvin3/+AWDQoEG4u7uzd+9e5s6dy65du+jUqVOe\n2myJHSO1trZGLpdz9+5dtedv3rzJ2bNn2bRpE3369JHSf//9d7X5y+LqBIFAH6gTSImJiSQlJemh\nNf+hFODe3t4sXboUyB4qtLKyonfv3uzbt4/OnTurvbbEaqTm5ua0atWKTZs2qXWxppzJMzT8712R\nnp7O5s2bhdAUCPSIOlPeysqKatWqSZ/XKapwzHlRsWJFADp06KCSrjyOjo7WeG2J1UgB5s+fT9u2\nbWnevDnjx4/HwcGBW7duER0dzYIFC3B2dmbKlCkYGBhgaGjIokWLkMlkud6Ib/OEmkBQ2tBXOOb8\nUDcGqy0lViMFaNy4McePH8fJyYnRo0fTtWtXFixYgJOTE0ZGRuzYsYPKlSvTv39/Ro8ejZeXFxMn\nTsylkQoNVSAoPnSZbPLz8+PEiRPExsZKacpwzH5+fkXSLk9PTypXrpwrQJ7yuEmTJhqv1Tr4nUB4\nyBce8vVHafKQ7+npmW++EydOqNSZnJxM/fr1MTMzkyKqBgUF8fLlSy5evCj9LuPj43FzcyMkJISg\noCDp+sOHD/P48WMePHjAmDFjGDlyJG3btgVQCca3YcMGBg4cyLBhw+jevTs3btxg6tSpNGzYkEOH\nDmlsb4k27QUCQcmjuMMxQ3bwzsOHDwPZwnz58uUsX74cmUymoqD0798fuVzO3LlzWbduHRUrViQg\nIEBl3bk6hEZaAIRGKjRSfVGaNNK8TGQlp0+fLlFzF0IjFQgExUpJEpDaIgSpQCAoVkqim7z8EIJU\nIBAUK0IjFQgEgkIiBKlAIBAUEmHaCwQCQSERGqlAIBAUEiFIBVSvXl1vdcfHx+utbtDvVlpjY2O9\n1Q1o7WbxTaGM+qAPPDw8irQ8YdoLBAJBISmNGmmJdloiEAhKHvqIIpqSksKXX35JlSpVMDc3p0WL\nFhw9ejRXvsePHzNq1ChcXV0xNzfH1dWV0aNH8+TJkzzLFxqpQCAoVnQx7ZVRRM3MzKTgdVOnTsXb\n21vFaYkmBg8ezO7du5k/fz6urq4sW7aMTp06ERUVRf369YFsAe/r68utW7eYPn06tWvX5vLlywQH\nB3PmzBmioqI0li8EqUAgKFZ0Me0LE0U0Ojqan376iXXr1jFgwAAA2rRpQ926dQkODpaiZsTExHDq\n1ClWr17NkCFDpHxyuZzPPvuM69evU6NGDbV1CNNeIBAUK7qY9vlFEc2LsLAwjIyM6NWrl5RmYGAg\nhQ9JT08H/nMKZGVlpXK98jgvTVoIUoFAUKzoEvyuMFFEL1++jKura65ow3Xq1CEtLY0bN25Ixx07\ndmT69OmcPXuWFy9ecOrUKb7++mu6dOlCrVq1NNYhBKlAIChWdNFICxNFNCEhQeO1yvNKfvvtN5yd\nnWnSpAnly5fH09OTd955h+3bt+dZhxCkAoGgWNFFIy2udvXo0YPz58+zevVqjhw5wqpVqzh9+jQ9\nevQoneGYC8PAgQM5fPiwSvwXgUBQPKgTSCkpKXk67y5MFFFra2tu376t9lr4TzPduXMne/bs4dCh\nQ3h7ewPQqlUrXF1d6dixIzt37tQYH6pMaqTBwcHs2LFD380QCMok6kx5ExMTrKyspM/rFCaKaN26\ndYmNjc0lqK9cuYKxsTHvvPOOdAzZQTVzovTof+3aNY11lElB6urqKq0d04RyJk8gEBQtupj2hYki\n6ufnR3p6Otu2bZPSMjIy+Pnnn+nUqRNGRkYAODo6AtlhTnJy8uRJABwcHDTWUaoE6Y0bNwgICJB2\nJbi5uTFixAgSExNV8g0cOFBlz3xcXBxyuZyVK1cyYcIEqlatiqmpKUlJScXdBYGg1KPLZNOQIUNw\ncXHB39+fsLAwwsLC8Pf3p1q1agwbNkzKFx8fj6GhIdOnT5fSGjRoQK9evRg7dixr167l0KFD9O7d\nm/j4eKZNmybl6969O05OTgQEBLBq1SoiIiJYuXIl/fv3p1q1anTv3l1jn0rVGOn9+/dxdHRk4cKF\nVKxYkVu3bjFr1iy6dOnCn3/+qZJXnQOOmTNn0rR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KDw8npVJJnp6elJycTG1tbaTVak2m\n22RkZPQ6PzM3N5emT59OarWanJ2dyc/Pj5YvXy6ZDqTX6+nDDz8kjUZDDg4OpFAoTM7l3LlzlJiY\nSN7e3jRs2DDy9vamsLAw2rRpE129elUS29raSosXLyZ3d3dSqVQUERFBpaWlffZTjtz0p5aWFlq0\naBE999xz5OzsTMHBwbRv3z46efKk7BqYhmM0NTXRvHnzyNXVlVQqFUVHR9OFCxdk27158yalpqbS\nhAkTSKlU0ogRI2jChAm0ZMkSOn78uCRW7vNg1sHrkTLGmIV4jJQxxizEiZQxxizEiZQxxizEiZQx\nxizEiZQxxizEiZQxxizEiZQxxizEiZQxxizEiZQxxiz0P1XPNUr8bESCAAAAAElFTkSuQmCC\n", + "text": [ + "" + ] + } + ], + "prompt_number": 210 + }, + { + "cell_type": "heading", + "level": 3, + "metadata": {}, + "source": [ + "Generic + Advanced + BusTrain + Location model" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices+BusTrainFeatureIndices\n", + " +LocationFeatureIndices], cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices+BusTrainFeatureIndices\n", + " +LocationFeatureIndices], cleanedResultVector, \"Gen + Adv + BusTrain + Loc\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic_advanced_bustrain_location.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Found 775 high confidence predictions out of 1462\n", + "Found 732 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 786 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 797 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 809 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.9, percentage auto classified 0.533602904893\n", + "for prob 0.9, scoring only on high confidence predictions 0.985722229305\n", + "for prob 0.9, scoring on all predictions 0.90283260814\n", + "Found 813 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 797 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 766 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 800 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 810 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.545502911541\n", + "for prob 0.95, scoring only on high confidence predictions 0.98242845845\n", + "for prob 0.95, scoring on all predictions 0.902285131616\n", + "Found 801 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 816 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 778 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 776 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 813 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.99, percentage auto classified 0.545228471026\n", + "for prob 0.99, scoring only on high confidence predictions 0.983755333542\n", + "for prob 0.99, scoring on all predictions 0.904201533534\n", + "[0.53360290489339346, 0.5455029115413893, 0.54522847102644134]\n", + "[0.77490642888335937, 0.78178476079770809, 0.78540431186584814]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[0.43012419532982343, 0.48404153504153502, 0.4730632942462501]\n", + "[0.048117561292571998, 0.051124955520620373, 0.047993093049272829]\n", + "[0.12184994410320751, 0.12369233722691475, 0.15290578173566186]\n", + "[0.3758955560076247, 0.3764007594520356, 0.37549339076840671]\n", + "[0.3001489476027645, 0.15555555555555553, 0.37549339076840671]\n", + "[0.9857222293048109, 0.98242845844963966, 0.98375533354236799]\n", + "[0.90283260813995625, 0.90228513161627766, 0.90420153353352217]\n", + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[[ 96. 1. 1. 0. 3. 0.]\n", + " [ 6. 88. 1. 0. 6. 0.]\n", + " [ 8. 3. 66. 1. 21. 0.]\n", + " [ 5. 1. 4. 63. 28. 0.]\n", + " [ 2. 2. 3. 1. 91. 0.]\n", + " [ 0. 7. 4. 3. 7. 79.]]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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h7dlsz5+RkZFoD1/j3rymdOvWDZs3b8YHH3wAR0dHAMDAgQPx4Ycf4ssvv4Sl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iIH3rpj+9zcT0JzH9SV/K0vSnO3fu5FmuZs2aev+Z58db2SMVBKHsKk0BUlci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\nhxMg3JFyOBxOgPwPFxCgkXP7Lt4AAAAASUVORK5CYII=\n", + "text": [ + "" + ] + } + ], + "prompt_number": 211 + }, + { + "cell_type": "heading", + "level": 3, + "metadata": {}, + "source": [ + "Generic + Advanced + BusTrain + Location + Time model" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix, cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix, cleanedResultVector, \"Gen + Adv + BusTrain + Loc + Time\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic_advanced_bustrain_location_time.png\", bbox_inches=\"tight\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Found 770 high confidence predictions out of 1462\n", + "Found 727 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 774 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 783 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 748 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.9, percentage auto classified 0.520325264913\n", + "for prob 0.9, scoring only on high confidence predictions 0.985606736312\n", + "for prob 0.9, scoring on all predictions 0.900642795679\n", + "Found 803 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 765 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 738 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 766 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 782 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.95, percentage auto classified 0.527437028964\n", + "for prob 0.95, scoring only on high confidence predictions 0.988390523231\n", + "for prob 0.95, scoring on all predictions 0.904611555715\n", + "Found 751 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 786 high confidence predictions out of 1462" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 796 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 754 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Found 783 high confidence predictions out of 1461" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "for prob 0.99, percentage auto classified 0.52963021224\n", + "for prob 0.99, scoring only on high confidence predictions 0.986077408666\n", + "for prob 0.99, scoring on all predictions 0.902420806917\n", + "[0.52032526491328102, 0.52743702896372735, 0.52963021223961626]\n", + "[0.76578072656747087, 0.78506420357397144, 0.76341808385831222]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "[0.43387146855572417, 0.43932739450275948, 0.45009813123244513]\n", + "[0.047872151540213001, 0.046903957549224502, 0.045325960188973891]\n", + "[0.073989469649846998, 0.086563728668991827, 0.14962091336236344]\n", + "[0.35005826462485012, 0.34173223369164757, 0.36502316516734279]\n", + "[0.30007682830449905, 0.10857142857142858, 0.36502316516734279]\n", + "[0.98560673631169027, 0.98839052323118626, 0.98607740866636973]\n", + "[0.90064279567898997, 0.90461155571535712, 0.90242080691691218]\n", + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + 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SeHl5yfP+9NNPiIuLw8iRI+Hr64v6+npIJBJEREQgMzOzyQ/rLUlISEBgYCDM\nzMxw/PjxZq8DeDiZ0rx58+Dh4YHXXnsNurq6yMvLw65du3Ds2DFkZWXB2tpaYZ/WduH08vJCSUkJ\n4uPj4enpKQ9mAEBXVxfAwwlN3N3dcePGDQQGBuKFF15ARkYG1q1bh8OHD+P06dMwMjJq8VzJycnw\n9/fHnTt38Oqrr8LBwQEVFRVIT0/Hli1bMGbMmGb3/+STTyASieDl5QUTExNcu3YN+/btw8svv4zd\nu3crBO7r169HWFgYbG1tMXXqVGhra+Pq1av49ddfcfz4cfj4+AAADh06hLFjx8LMzAwBAQEwMDBA\nWVkZMjMzsWfPHkyePLnJep07dy5ycnIEdefo6Kg0P/CwdXXq1KnYvXs3HBwcEBISIi/H+PHjsXbt\nWsyePVue/9y5c3B3d0d9fT0mTpwIa2tr+RdByr6oI52HrDsPz/EKXXt4jlf6+6N5W7OfrKcMAIWJ\nYJr6F0CH5iGEENL5NBv86enpKW3hq6qqUggwlOnVqxe2b9+OmTNnwtbWFgDg5OSEuXPn4vPPP4ep\nqanyHRMb/W4NQNizqk24qGc7boktbv83wOPHj+O7775DcHCwPO3TTz/FsmXLEBkZiZiYGABAZWUl\npk+fDgsLC6Smpip0Ofv888+xYMECxMTEKARtwMNgZOvWrZg2bZpCemhoKC5duoRly5bh448/Vtgm\n6+4GPOwuPHfuXAwZMgQ///wztLW15dvCwsKwfv167NmzB+PHj1c4xqFDhyCRSODm5gbgYYuIj48P\nJBIJ0tPT4erqioEDB+KDDz6QB3+ffvppq+qM4zi4u7vjyJEjqK2thZaWFoD/TW5y8uRJJCYmyoM/\nWZDYOPiZPn06PvroI6iqKr5s/vWvf+E///kP0tLSMGzYsFaVR2b37t2YNm0a+vXrh2PHjrUqaNLX\n18fly5cFXQiTk5MxcuRILF++HLGxsQrbWtuF08PDA4wxeQCjrH5DQ0NRVVUleEYWL16MpUuX4t//\n/je+++67Zs9z9+5dTJ06FfX19Th58qRg5tNr1661WNajR48KAuVVq1bByckJCxYsUAj+vv32W5ib\nm+PcuXMQiUQK+zRuWf7uu++goaGBnJwcGBoaNplPmTlz5kAikTRbd4/eh2+++Qa7d+/GzJkzERMT\nIw8OV61aBW9vbyxYsAATJ06U/385a9Ys1NXV4aefflL44kM2kyiN0+wc7i26JwjkuqrOFpC2NU9r\ny97Z8lAQCTkIAAAgAElEQVRdtmNddsYydcL725megedSEYDip3OqZoM/BwcHnD9/XpB+4cIF9O3b\nt8WDjxs3DoGBgSgoKIC6ujp69eqF0NBQWFpaomfPnsp38lKeTP7H3t5eIfADgIULF2LdunXYtm2b\nPPjbunUramtr8d133wkChQ8//BCrV6/Gjh07BMGfs7OzIPC7fv069u3bB3t7e0HXSQAKwfzmzZvx\n4MEDxMTEKAR+ALB8+XJs2LABO3bsEAR/r7/+ujzwAwCe5zF9+nRIJBJkZmbC1dUVwOOPRfPy8sKB\nAweQkpKCV155BQUFBSgrK0N0dDT+/PNPJCYmYsaMGQAeBn/6+voYMGCA0mts7L333sN//vMfnDhx\notXBH2MMmzdvxvvvv48RI0bgwIEDgrpqirq6utKxYyNGjMCLL74o6MbYnkpKSpCcnAxHR0fBMxIe\nHo6NGzdi586d2Lx5s9IxvzL79+9HWVkZZsyYoXTJi9ZMiqKshVTW0rxu3TqUlpbKu/NyHAc1NTWl\nPQ4e/SJLVVVVEOAry9ce1q9fj+7du+PLL79UCBDEYjEWLVqEsWPH4qeffsLMmTNRUlKC1NRUODs7\nKwR+ALB06VJs27btsV8bpH2pqTT97Hc1CpMXdN0YmBDylHW2gLStwX0/434dVjfNBn9jx47FRx99\nhKKiIvnYluLiYvz6669YtWpVq07AcRxeeOEFAA+/zd+1axcWLFjQZP70GenNdoUZEDmgyX27CmUB\nhlgshqOjIyQSifxDb3p6OgAgNTVVaRCvqqqKvLw8Qbqzs7MgLTMzE8DD5Tpa+hY7PT0dHMfh4MGD\nOHTokGC7SCRSel4nJydBmrm5OQDg5s2bzZ6zNWSteBKJBK+88oq8dc/b2xsSiQTHjh0D8HC8X05O\nDsaOHauwv1Qqxbfffou4uDjk5ubi1q1bCh+2G7d+tmTNmjU4dOgQXnvtNezcuRPq6uptupasrCx8\n9tlnSEtLQ0VFBe7fvy/fpqGh0aZjtcXZs2cBQGnAJhKJ4OLigiNHjqCgoAAODg5NHicjIwMA4Ovr\n+9hluX79OlauXImjR4/iypUruHv3rsL2srIyefA3efJkLFy4EP369cOUKVPg6emJIUOGCNYqnTJl\nCvbt24d+/fph6tSp8Pb2xtChQ+VdXtvT7du3cf78eVhaWsrXUW1M1t06Pz8fwMMunwAwfPhwQV4L\nCwtYWlqipKSk3ctJCCGEPG8aLz1BXzwpajb4e+edd7Bu3Tq89tpr8g8nERERsLS0xLvvvivPV1JS\ngt69e2Px4sWIiIgAADQ0NGD+/Pnw9PSEtrY2cnNzsXLlSvTr10/Q0tSYi7lLe1zXP1qPHj2Upstm\nGKyurgbwv25qspZAZZQFcspmKpQdszUtMlVVVWCMYenSpU2e8/bt24J0HR0dQZqsBebRSWIeR//+\n/aGnpycf5yeRSNC7d2+Ym5vDw8MDW7ZsQX5+Pv744w9IpVKFLp/Awy6rGzduhLW1NSZMmAATExOo\nq6vjxo0b+Oqrr1BfX9/qsqSlpQEARo8e3ebALzU1FSNHjoSqqipefvll2Nraolu3buA4Dlu2bOnQ\nyT9qamoAKH9GAMhbJGX5mtKW50mZqqoquLi44OrVq3B3d4e/vz90dXXB8zwSExORlJSkcD8WLFgA\nfX19bNq0CcuWLcOyZcugoaGBCRMmYM2aNfLX1KRJk6CmpoYvvvgCX375JdasWQNVVVWMHj0aX375\npbxbcHuQdakvLS3FkiVLlObhOE4+MZOszprqGmxsbEzBHyGEEEKa1WzwJxaLcfLkScydOxdvvvkm\nGGPw8fHB2rVrFb4xZ4xBKlVcioHjOFy6dAk//PADbt68CQsLC8yYMQMff/yx0i5VpPX++usvpenl\n5eUA/jcxhyyYysvLg52dXauPrywg7N69O4DWjcXS0dEBz/Oora0VjK96lniel4/7q6mpgUQigb+/\nPwDFVsE//vhDIQ14WLcbN26Eo6MjTp06pdC6lp6ejq+++qpNZfn222+xZMkSvP/++1BXV5dP9NEa\nK1euRENDA5KSkjBkyBCFbT/88IMgv6yro7IZSWUBRWvJninZs/YoWbqyQL4x2fN09erVNp1f5ttv\nv8WVK1ewYsUKLFy4UGFbWVkZkpKSBPvMmDEDM2bMQGVlpXwyoe3bt+Py5csKEwEFBgYiMDAQt27d\nQkpKCnbt2oWtW7ciLy8Pubm5zXZnbQtZHQ0ZMgS//vpri/llr2tZi+CjmronhBBCCCEyLUZhFhYW\nLa7pZ21tDalUqpCmoqLSqunaO1pHTLjyrKWmpgrS6urqkJOTAz09PXlXN1dXV+zduxenTp1qU/Cn\njLOzMziOw4kTJyCVSpudrdXV1RXZ2dlIT0+Hh4fHE51XGRUVFQCP1xooG/f3zTff4Pr16/LZPC0t\nLWFjY4PExERcunRJMN6vqKgIAODj4yPoVilrxWsLfX19JCQkYOTIkfJxhq0NAAsLC+VLbDRWXl6O\nwsJCQX7ZLJBXrlyRL5Mhk52dLcjfXP0OGjQIAOSzrzZ29+5dnDlzBpqamvKu3k1xcXnYwn/8+HFM\nnDix2bzKyK7z0a65jDGcOnWq2X0NDQ0xfvx4jB8/HoMGDUJycjJu3bolGHOpra0NPz8/+Pn54ebN\nmzhw4ADy8vLQv3//NpdXGW1tbdjb2yM3N1dhEqKmDBw4EIDyui8tLaXlHgghhBDSIlpv4TmUn5+P\nLVu2KKRFR0fj5s2bCpNwhISEQEtLC+Hh4SgoKBAcRza2rTWMjY0RGBiI/Px8rFy5UrC9cQvO+++/\nDxUVFYSFhSkdB1deXq50zF9ryYKZx/mwK2vNW716NTiOU2jd8/T0REJCAs6ePSsY0yabXOTRFpqC\nggKl9dEa+vr6OHHiBPr374933nkH8fHxrdrPysoKf//9t0Id3rt3D7NmzVLauicLtOLi4hTSf/zx\nRyQnJwtaemUTmyirXwsLC3h4eCA7O1vQyrhq1SpUVFRgypQpLbbuy5ZTiIuLU9pK11KLoOx+PPpF\nyNq1a3Hu3DnBNSk7x507d1BdXQ01NTV5wCtb4qMxqVSKyspKcBzX7i3ZYWFhuHXrFt577z2l3YZz\nc3PlLX2WlpZwd3dHVlaWYFmRiIgIQbkJIYQQQh5F/S+fQ76+vggNDcXhw4dhZ2eHzMxMJCQkwMbG\nBpGRkfJ8RkZG2L59OyZPnoz+/fvDz88Ptra2qKurQ1FREZKSkhAcHIwNGza06rwbNmzAuXPnEBER\ngQMHDsDDwwP37t1Dbm4usrOz5Qt89+vXD19//TVmzZoFOzs7+Pv7w8rKCjdu3MClS5eQmpqKZcuW\nwd7e/rGuX0tLCy4uLkhOTkZQUBBsbW3B8zyCgoIEi7U/asCAAejevTsqKipga2urMObM09NTvkTB\no+P9TE1NERgYiL179+Kll16Cp6cnrl27hoMHD+Lll19Wum4h0PLMpLIA0NvbG2+//TY4jkNQUFCz\n+8yaNQu//PILhg0bhkmTJkFVVRUJCQl48OABBg4cKJ+URea1115D7969ERcXh8uXL8PR0REXL15E\nYmIi/Pz8cOTIEYX8L774IszMzLBjxw5oaGjA3NwcHMdh9uzZ0NHRwcaNGzF8+HC8+eab+Omnn9Cn\nTx9kZWXhl19+gY2NTasmg9LQ0MAPP/wAPz8/jBw5Ev7+/nBwcEBVVRXS09NhbW3d7LqJb775Jlat\nWoVZs2ZBIpHAzMwMmZmZSE9Ph7+/Pw4fPiyoAz09Pbi6usLS0hJ3797F0aNHUVxcjLCwMHk39rCw\nMJSXl2PYsGGwsrICYwyJiYk4e/YsxowZgz59+rR4bW0RGhqKX3/9Fdu3b0dKSop8zcKysjL8/vvv\nyMnJUVg38euvv8bw4cMxadIkTJw4EVZWVkhKSsLVq1cxYMAA+aQwhBBCCCFKsU6kNcXpZEV+qhIT\nExnHcSwqKopJJBLm7u7OunXrxgwMDFhQUBArKytTut+FCxdYcHAws7CwYOrq6szIyIg5OTmx8PBw\nlp+fr/T4Tblx4wYLDw9ndnZ2TENDgxkaGjI3Nze2du1aQd5Tp06xiRMnMlNTU6aurs5MTU2Zm5sb\nW7p0Kbt8+bI8X1xcHON5nsXHxzd7zY0VFBQwf39/pqenx3ieZzzPs6SkpBbrkDHGAgICGM/z7J13\n3lFIv3LlCuM4jvE8z86ePSvY79atW+yDDz5gVlZWTCQSsX79+rGvv/6aFRUVMY7jWEhIiEJ+T09P\nxvO8QlpkZKTSslZWVrIBAwYwVVVV9v3337d4Dbt27WKDBg1iYrGYmZqaspCQEFZeXq70nIwxVlxc\nzAIDA5mOjg7T0tJio0aNYllZWU2WJz09nXl6ejIdHR15nZSUlMi3//nnnywoKIiZmJgwdXV1ZmVl\nxcLCwlhFRUWLZW8sPz+fBQUFMTMzM6aurs7MzMyYn58fO3LkiDxPU89AdnY2GzVqFNPT02O6urps\n9OjRLDMzU+k1bdy4kY0dO5ZZW1szkUjEevTowdzd3dm2bdsUjrlz5042adIk1rt3byYWi5mBgQF7\n6aWX2Lp169j9+/cV8lpbW7NevXoppDX3GgoODhbUo8z27duZl5cX09PTYxoaGszKyoqNHj2abdq0\nidXV1Qmu29fXl3Xr1o3p6+uziRMnssuXLzd578nT1ZXfowghhLSPjnwv4f7/BJ0Cx3EttpS0Js8/\nlWxB8sjIyFYvbk4IIeTp6crvUYQQQtpHR76X0Jg/QgghhBBCCOkCKPgjhBBCCCGEkC6Agj9CCCGE\nEEII6QJozB8hhBDSTug9ihBCyJOiMX+EEEIIIYQQQp4IBX+EEEIIIYQQ0gVQ8EcIIYQQQgghXQAF\nf4QQQgghhBDSBVDwRwghhBBCCCFdAAV/hBBCCCGEENIFUPBHCCGEEEIIIV0ABX+EEEIIIYQQ0gVQ\n8EcIIYQQQgghXQAFf6TLiIuLA8/ziI+Pb/U+PM/Dy8tLIc3T0xM8Ty+djvI49+lpUPYsAMCpU6fg\n6ekJfX198DyPcePGAej458Ta2hq9evXqsOMTQggh5J+HPsGS505xcTF4nkdISMhj7c9x3BPnb+sx\nOrPOGmx1xjp+tEw3b97EmDFjcO7cOQQFBSEyMhJTpkyR5+3oa+iMdUQIIYSQzkv1WReAkLaSfeB9\nGh988/LyIBaLO/w8nQEFEs1T9ixkZGSgqqoK0dHRWLBggcK2rVu34s6dO0+ziIQQQgghzaLgjzx3\nGGMK/3YkOzu7Dj9HZ/E06vN5puxZKCsrAwAYGxsLtllYWHR4mQghhBBC2oK6fT5HJBIJeJ5HVFQU\nJBIJ3N3doa2tDUNDQwQFBeH69etK98vOzsbEiRNhbGwMkUgEW1tbfPzxx6irq2vy+KmpqfDx8YGu\nri709fXleaqrqxEREQEHBweIxWIYGBhgyJAhWLNmjeC8iYmJ8PPzg4GBATQ1NeHg4IBVq1bhwYMH\nCvkadzs8fvw4hg4dCi0tLRgaGiI4OBhVVVUKeW1sbAAA8fHx4Hle/pOcnNyqemSMYc+ePXBycoJY\nLIaZmRlmz56NmpoaQd6mxnkpExsbCxUVFYwYMQLV1dXy9D179sDT0xO6uroQi8UYPHgwYmNjW3VM\nAKipqUF0dDTc3d1hYmICDQ0NWFlZ4b333kN5ebkgf3NjzYKDg8HzPEpLS+V/v/XWWwCAkJAQhfps\n7OzZsxg/fjyMjIwgEolgZ2eHRYsWCZ6hlvz222+YPHkyTE1NIRKJYGFhgXHjxiEtLa3Ffb/77juM\nHTsWVlZWEIlEMDIyQkBAALKysgR5GWPYvHkznJ2doa+vj27dusHKygoTJkzAb7/9ppB39+7dcHd3\nh5GRETQ1NdGzZ0/4+/sjISFBId+jzwLP8wgODgagWHey57Cp+1BfX4/Vq1dj4MCB6NatG7p3745R\no0Y1+fwmJiZi2LBhEIvFMDY2xowZMxReE4QQQgghrUUtf8+hU6dOYeXKlRgzZgzmzJmDjIwMbNu2\nDWlpacjIyFAI1vbu3YspU6ZAJBIhICAAJiYmyMrKQnR0NBITE5GcnAw1NTWF46elpWHFihXw8fFB\naGgoKioqAADl5eVwd3fHpUuX4OLigrCwMNTX1+P3339HdHQ05s2bJz/GunXrMHv2bPTo0QOBgYHQ\n09NDSkoKwsPDcebMGezZs0dwXQcOHMDhw4cxduxYDB8+HElJSdi6dSsKCwuRkpICABg0aBDmzJmD\nr776Co6OjggICJDvb2Vl1ar6+/HHH/HLL79g8uTJGD16NE6ePIl169YhPT0dqampgvpoTXfIlStX\n4pNPPsGYMWOwa9cuaGhoAADmz5+PNWvWwNraGlOnToVYLMbx48fx7rvv4uLFi/jiiy9aPPaFCxcQ\nFRWFkSNHYtKkSdDU1EROTg6++eYbHD9+HL/99hu6d+/e6jI33hYYGIjq6mrs378fAQEBcHR0FORP\nSkrCK6+8AsYYJk2aBHNzc5w8eRIrVqzAzz//jJSUFIhEohavY+fOnXjzzTehqqqK1157DTY2Nigr\nK0NKSgr27NmDYcOGNbv/rFmzMHjwYIwePRoGBgYoKirC/v378fPPP0MikcDV1VWed8GCBVizZg0G\nDhyI4OBgaGho4PLly5BIJDh9+jQGDx4MAFi/fj3CwsJga2uLqVOnQltbG1evXsWvv/6K48ePw8fH\np8m6W7x4MXJycgR1Z21trTQ/ANy9exe+vr5ITU2Fi4sL3n33XdTW1mL//v0YOXIkdu3ahcDAQHn+\n48ePw9/fHxoaGnjjjTdgaGiIw4cPY9SoUbh//778OSOEEEIIaRXWibSmOJ2syE9VYmIi4ziOcRzH\ntmzZorAtIiKCcRzHwsLC5GkVFRVMW1ub9e7dm5WVlSnkX716NeM4jn3++edKj//9998Lzh8YGMg4\njmPLly8XbLt27Zr89/PnzzNVVVXm5ubGampqFPLNmjWLcRzHfvzxR3nali1bGMdxTF1dnf3666/y\n9AcPHjAvLy/GcRw7ffq0PL24uJhxHMdCQkKaqiqlZOfhOI6dPHlSYVtQUBDjOI6tWbNGIZ3jOObl\n5aWQ5uHhwXieZ4wxJpVK2Ycffsg4jmPTp09nDx48kOc7duwY4ziOBQYGsvr6enn6/fv3WUBAAOM4\njmVkZLRY7urqanbjxg1B+rZt2xjHcWzZsmVNlu9R06dPZxzHsZKSEnmarF7i4+MF+RsaGpiNjQ1T\nUVFhycnJCtuCg4MZx3EsKiqqxWsoKytjYrGYde/enV24cEGwvfHz01R5iouLBftdvHiRaWtrMx8f\nH4V0PT099tJLLzGpVCrYp3FdDho0iPXs2ZPduXNHkO/vv/9W+FvZs9Bc3Sm7DwsXLmQcx7FVq1Yp\npFdUVDBra2tmZGQkL0tDQwOztrZmampqLDMzU563oaGBjRw5knEcx3r16iU4L3m2uvJ7FCGEkPbR\nke8l1O3zOWRvby/vbiazcOFCdO/eHdu2bZOnbd26FbW1tYiOjoaJiYlC/g8//BBGRkbYsWOH4PjO\nzs6YNm2aQtr169exb98+2NvbIzw8XLCPqamp/PfNmzfjwYMHiImJgba2tkK+5cuXg+M4ped9/fXX\n4ebmJv+b53lMnz4dAJCZmSlPZ084Ns3X11fQlXPZsmVQUVHB1q1bW32cBw8eICQkBF9++SXmzp0r\n774qs379evA8j82bN0NdXV2erqqqiqVLlwJ42BrWEh0dHUHLHvCwvrS1tXHixIlWl7mtUlNTUVRU\nhDFjxsDd3V1h24oVK6Curt6qWULj4+Nx584dzJ8/Hy+++KJge+PnpynKWnbt7e3h6emJlJQUNDQ0\nyNM5joOGhobSFtDGdclxHNTU1JR2z2zcgt4epFIpNm3aBAcHB8HkMIaGhpg3bx4qKyvl9zMtLQ0l\nJSUICAiAk5OTPK+Kior8+SGEEEIIaYuu0+3zac9k2IGTZyjrHicWi+Ho6AiJRILS0lJYWloiPT0d\nwMMP8OfPnxfso6qqiry8PEG6s7OzIE0WfHl7e7fYDTI9PR0cx+HgwYM4dOiQYLtIJFJ63sYfcGXM\nzc0BPJxSv708GsQADyfnsLCwQG5uLhhjLV4jYwyBgYE4dOgQli9frjQgTk9Ph5aWFtavXy/Ydv/+\nfQBQWg/KnDhxAmvXrsWZM2dQVVWlMG5SNulIRzh79iwAwMPDQ7DN1NQUtra2uHjxIurq6tCtW7cm\nj5ORkQHgYeD9uC5duoQVK1YgMTERZWVluHfvnnwbx3H4+++/5ROvTJ48GZs2bcLgwYMxYcIEeHp6\nwtnZWSEIl+VbuHAh+vXrhylTpsDT0xNDhgzpkBle8/PzUV1dDSsrK0RGRgq2//HHH/J8/v7+8rof\nPny4IK+rqytUVFTavYyEEEII+WfrOsHfP2gmwx49eihNl33wlU02IpsUIiYmpsljKQtylM1cKDum\nmZlZi+WrqqoCY6zJ1gmO43D79m1Buo6OjiBNVfXhI/roJDFPorn6KykpQW1traDFUpm0tDR069YN\nL7/8stLtsiBtyZIlSrc3VQ+P2rlzJ6ZOnQpdXV2MHj0a1tbW0NTUBGMMa9euRX19fYvHeFyySXCU\nPRMAYGJiggsXLqCmpqbZ4K8tz48yf/zxB1xcXFBbW4tRo0Zh/Pjx0NLSAs/z2Lt3L86ePatQDzEx\nMejVqxe2bNmCRYsWAQC0tbURFBSE6OhoeVkXLFgAfX19bNq0CcuWLcOyZcugoaGBCRMmYM2aNU0+\nK49D9no8d+4czp07pzQPx3HySXRkdWZkZCTIx/M8DA0N261shBBCCOkauk7w9w/y119/KU2Xzfyo\nq6sL4H/BVF5eXpuWLGiuq9y1a9da3F9HRwc8z6O2trZVE4E8bc3VH8/z0NLSavEYHMchISEBI0eO\nxKhRo5CQkIBBgwYp5NHR0YGGhkar6qw5S5YsgVgsRlZWlnymU5lVq1YJ8su6MEqlUkF3xsazkLaG\n7BlSNquoLJ3jOKWBe2Oy5+fq1auPFQCuXbsW1dXV+O9//ytfRF3m1KlT8lYyGVVVVcyfPx/z58/H\n1atXkZiYiNjYWKxfvx63bt1CXFycPO+MGTMwY8YMVFZWyicZ2r59u3yCmPYiq6MpU6bgv//9b4v5\nZa9j2YRLjUmlUlRWVtJyEoQQQghpExrz9xxKTU0VpNXV1SEnJwd6enqwtLQEAPnsh6dOnXriczo7\nO4PjOJw4cQJSqbTZvK6urpBKpfJup+1N1t3tcVsDlU2pX1paitLSUvTr16/Vi50PGjQIv/zyCxhj\n8PHxQXZ2tsJ2V1dXXL9+HSUlJY9VTpnCwkL07dtXEPj99ttvuHv3riC/np4eGGO4cuWKQrpUKsXZ\ns2cF19dcfcoC2qSkJMG2srIyFBQUwMbGptlWPwBwcXEB8HD2ysdRWFgIjuMwduxYhfS7d+/it99+\na/aemZubY9q0aUhISIChoSEOHjyoNJ+hoSHGjx+P/fv3Y+DAgUhOTsatW7ceq7zK9O3bF9ra2sjI\nyGjxNQRAPnuobKbbxk6fPt2ureGEEEII6Roo+HsO5efnY8uWLQpp0dHRuHnzpsJELSEhIdDS0kJ4\neDgKCgoEx6murkZOTk6rzmlsbIzAwEDk5+dj5cqVgu1Xr16V//7+++9DRUUFYWFhSsejlZeXt3qs\nmzJ6enoAIF+rrq0SEhJw8uRJhbSIiAhIpVIEBQW16VhOTk44fvw4pFIpRo0apVCfYWFhAIC3335b\naYtbcXFxqwJDKysrFBQUKLQA1dTUYM6cOUrzywKtxq1bAPDFF1+guLhYkF82sYmy+hw+fDhsbGxw\n4MABwVp8n3zyCe7fv9+qOgsKCoJYLMbq1atx4cIFhW2MsSbXqJSxsrICY0zhiw/GGMLDwwUtY/fu\n3VP6hUdNTQ3u3Lmj0BqtLKi9c+cOqquroaam1q7j6lRUVPDee++hsLAQ4eHhSgPA9PR03LlzB8DD\nsb3W1tbYt2+fwoRHDQ0NiIiIaLdyEUIIIaTroG6fzyFfX1+Ehobi8OHDsLOzQ2ZmJhISEmBjY6Mw\nkYSRkRG2b9+OyZMno3///vDz84OtrS3q6upQVFSEpKQkBAcHY8OGDa0674YNG3Du3DlERETgwIED\n8PDwwL1795Cbm4vs7GxUVlYCAPr164evv/4as2bNgp2dHfz9/WFlZYUbN27g0qVLSE1NxbJly2Bv\nb/9Y16+lpQUXFxckJycjKCgItra24HkeQUFB8lbP5vj5+cHPz0++Zl1iYiLOnDmDl156SR6wtaTx\njKPOzs44fvw4fH194ePjgxMnTmDgwIF45ZVXEB4ejpUrV6JPnz54+eWXYW5ujoqKCly8eBHp6en4\n4YcfWlyfcNasWZgzZw4GDx6McePGob6+HseOHYO5uTnMzMwEs5+GhITgs88+Q2RkJHJycmBjY4PM\nzEzk5ubCw8NDEPAMHToUmpqaWLt2LW7cuCEfS7Zo0SJwHIfvvvsOo0ePho+PDyZNmgQzMzNIJBKk\np6fD2dlZMHOlMsbGxvjuu+8wbdo0ODk5ISAgAL169cJff/2F5ORk+Pv748svv2xy/3fffRdbtmzB\nuHHjMHnyZOjo6CAlJQXFxcXw9PRU6J55+/ZtDBs2DPb29hg0aBAsLCxQXV2NAwcO4Pbt2wpjMF97\n7TXo6enB1dUVlpaWuHv3Lo4ePYri4mKEhYU98cQvj96bJUuWIDMzE6tXr8aBAwcwfPhw6Ovr48qV\nK8jKykJBQQGuX78OTU1N8DyPTZs24dVXX4WHhwemTp0KAwMDHDlyBOrq6jA1NX3imW8JIYQQ0sV0\n2CISj6E1xelkRX6qZOvwRUVFMYlEwtzd3Vm3bt2YgYEBCwoKEqzlJ3PhwgUWHBzMLCwsmLq6OjMy\nMmJOTk4sPDyc5efnKz1+U27cuMHCw8OZnZ0d09DQYIaGhszNzY2tXbtWkPfUqVNs4sSJzNTUlKmr\nq7E2CSsAACAASURBVDNTU1Pm5ubGli5dyi5fvizPFxcXx3ieV7pWWlNlKigoYP7+/kxPT4/xPM94\nnmdJSUnN1l/j8+zZs4c5OTkxTU1NZmJiwsLCwgRrEjKmfG03T09PpevonTlzhnXv3p0ZGRmxc+fO\nydOPHj3K/P39maGhIVNXV2c9e/Zknp6e7IsvvmCVlZXNlllm/fr1rG/fvkxTU5NZWlqyuXPnslu3\nbjFra2ula72dPXuW+fj4sG7durHu3buzwMBAVlhYyIKDgxnP8wrr/DHG2JEjR5iLiwsTi8WM4zjB\n9eXk5LBx48YxAwMDpq6uzvr06cM++eQTVldX16ryy2RkZLDx48czIyMjpqGhwSwtLdmECRMU1nds\n6nk4ceIEGzp0KNPW1maGhoZswoQJ7NKlS4Jrun//Plu1ahXz9fVlPXv2ZBoaGszMzIz5+vqyQ4cO\nKRxz48aNbOzYscza2pqJRCLWo0cP5u7uzrZt2yYou7Jnoblnt6nnpKGhga1fv54NGTKE6ejoME1N\nTda7d28WGBjIvv/+e9bQ0KCQ/+TJk2zo0KFMU1OT9ejRg7399tusqqqqyXtPnq2u/B5FCCGkfXTk\newn3/yfoFDiOa/Gb7Nbk+aeSSCTw9vZGZGQkPv3002ddHEIIIY/oyu9RhBBC2kdHvpfQmD9CCCGE\nEEII6QIo+COEEEIIIYSQLoCCP0IIIYQQQgjpAmjMHyGEENJO6D2KEELIk6Ixf4QQQgghhBBCnggF\nf4QQQgghhBDSBVDwRwghhBBCCCFdAAV/hBBCCCGEENIFUPBHCCGEEEIIIV0ABX+EEEIIIYQQ0gVQ\n8EcIIYQQQgghXQAFf4QQQgghhBDSBVDwR7qMuLg48DyP+Pj4Z10U8v+Cg4PB8zxKS0ufdVHkJBIJ\neJ5HVFSUYFt8fDwGDBiAbt26ged5xMTEAAB4noeXl1eHlKe4uBg8zyMkJKRDjk8IIYSQrqPF4O/y\n5cuYMGECunfvDl1dXYwfPx6XL19u1cGLi4sRFBQES0tLiMVivPDCC4iIiMDt27efuOCk63rSD8Mc\nx7VziZ4fnTHY6qz349FypaamIiQkBPfv38ecOXMQGRmJIUOGNJm/o8tDCCGEENJWqs1tvH37Nry9\nvaGpqYmtW7cCABYtWgQvLy+cO3cOYrG4yX1ra2sxcuRIAMDy5cthaWmJM2fOYPHixfjjjz+wY8eO\ndrwM0pXIPgTTh+HH09nqjTH2rIugwNXVFXl5eTA0NFRIP3r0KICHrX8uLi4K2/Ly8pr9/5AQQggh\npDNoNviLjY1FUVHR/7F333FRXHv/wD+ztKVLL0oRCBJRg0pQEKRYAxHBKJafIuSJiUaQa3JzI0mI\nGAuYxBtbNMYkFM21XBVFidGoLE1EQWwYwUKxIBYQsIHC+f3hs/uwzACLAprwfb9e+xLOnJlz5szg\n7nfPmXNQVFQEGxsbAMCAAQPw2muvYcOGDZg/f36L+2ZlZaG4uBgHDhzAqFGjAACenp6orKzEt99+\ni8ePH0MsFnfgqZDuQhosvGpBw18FY4zarhXq6uqwt7fnpZeXlwMATExMeNuE8hNCCCGEvGpaHfaZ\nnJwMV1dXWeAHANbW1hg2bBj27NnT6oEbGhoAALq6unLpurq69OHzOTV9FkkikcDDwwPa2towNDRE\ncHAwbt68Kbhffn4+Jk2aBBMTE4jFYtjZ2eGzzz7DgwcPWjx+ZmYmRo4cCV1dXejr68vyVFdXIyoq\nCo6OjtDQ0ICBgQGGDh2KFStW8MpNTU2Fr68vDAwMoK6uDkdHRyxfvlx2b0g1fRbv4MGDcHNzg5aW\nFgwNDRESEoLKykq5vNL7MSEhASKRSPZKT09XqB0ZY9i5cycGDx4MDQ0NmJubY968eaipqWmxPZpr\naehpUVERgoODYW1tDbFYDENDQwwePBjR0dEK1a2oqAiffPIJnJycoK+vD3V1dfTr1w9Lly7F06dP\neflbe9bM2toavXv3lvtd2oPfu3dvWbs13z8pKUl2b2lpaeHNN9/Ezz//rFD9m9qxYwdGjBgBPT09\naGho4LXXXsPs2bPbHDZeU1OD2NhYeHh4wNTUFGpqarCyssLs2bNRUVHBy3/v3j18/vnncHBwgJaW\nFnr06IE+ffpg1qxZcvfO48eP8fXXX6N///7Q0dGBtrY2bG1tMWPGDFy5ckWWr/l1l/4eHx/Pazup\nlq7DzZs3MW/ePNjY2EAsFsPU1BQzZsxASUmJ4LmvW7cOr7/+OtTV1WFra4tly5bx/l4IIYQQQp5X\nqz1/BQUFCAwM5KX37dsXO3bsaPXAo0aNQr9+/fCvf/0L69evh4WFBY4fP47Vq1dj9uzZUFdXf7Ga\nd2PZ2dmIiYnBuHHjEBERgRMnTmDz5s3IysrCiRMn5IK1pKQkTJkyBWKxGAEBATA1NUVeXh5iY2OR\nmpqK9PR0qKioyB0/KysLy5Ytw8iRIzFnzhzcvn0bAFBRUQEPDw9cunQJLi4uCA8PR11dHc6ePYvY\n2Fh8/PHHsmOsXbsW8+bNg7GxMQIDA6Gnp4eMjAxERkbi+PHj2LlzJ++8kpOTkZKSAn9/f7i7uyMt\nLQ2JiYm4fPkyMjIyAAADBw5EREQEVq1aBScnJwQEBMj2t7KyUqj9duzYgT/++AOTJ0/G2LFjceTI\nEaxduxY5OTnIzMzktUdrwySbbrt+/TpcXFzQ0NCA8ePHw9raGlVVVfjzzz+xYcMGhQLAXbt2IT4+\nHiNGjMDo0aNRV1cHiUSCqKgo5ObmIikpqdU6tLZt/vz5iI+Px+nTp/GPf/wDPXr0APAsKJT6+uuv\nsWDBAhgbGyM0NBSqqqrYsWMHZs2ahfz8fKxdu7bNcwCAefPmYe3atTAxMcHkyZOhr6+PK1euYMeO\nHfD19YWFhUWL+54/fx6LFi3CiBEjEBQUBHV1dZw6dQo//vgjDh48iJMnT8rqzhjD6NGjkZeXhzFj\nxiAgIABPnjzBlStXsG3bNsyfP1/29zBjxgzs3LkT7u7uGDNmDEQiEUpKSvD7779j6tSpcl9yNW27\n3r17Y+HChdi9ezev7VpqawC4ePEivLy8UFFRAT8/P0yaNAllZWXYvn07Dhw4gGPHjsmV+eWXX2LJ\nkiXo1asX5syZg4aGBqxevRpHjx5VqM0JIYQQQtrEWqGqqsoiIyN56Z9//jlTVlZubVfGGGO3bt1i\nQ4YMYRzHyV7vv/8+a2xsFMzfRnUUziOXPzX1pb46Umpqqqwd4+Li5LZFRUUxjuNYeHi4LO327dtM\nW1ub2drasvLycrn833zzDeM4jn377beCx9+0aROv/MDAQMZxHFu6dClv240bN2Q/nzt3jikrKzNX\nV1dWU1Mjly8sLIxxHMd27NghS4uLi2McxzFVVVV29OhRWXpDQwPz9vZmHMexY8eOydJLSkoYx3Es\nNDS0paYSJC2H4zh25MgRuW3BwcGM4zi2YsUKWZq0PRYtWsQ7VnFxMa8Oq1atYhzHseTkZF7+yspK\nhep448YN9uTJE176rFmzGMdxLDMzUy6d4zjm7e0teCwrKyvWu3dvubSZM2cyjuNYaWkpL//FixeZ\nkpIS69WrF6uoqJCl19bWsn79+jGO41haWlqb57Bnzx7GcRxzdnbmXf/Hjx/LtYVQfaqrq1lVVRXv\nuJs3b2Ycx7ElS5bI0k6fPs04jmMfffQRL//Dhw/Zo0ePGGOM3bt3j3EcxyZMmMDL9+TJE1ZbWyv7\nvaXr3lrbCV2HoUOHMrFYzDIyMuTSs7OzmYqKCnv77bdlaUVFRUxJSYnZ2NjInXt5eTkzMTF5rvud\nvBztfY8ihBBCmuvM95JOW+rhwYMHeOutt3Dv3j1s3rwZ6enp+Oabb7B161bMnTu3s4rtFhwcHBAS\nEiKXtmDBAvTo0QObN2+WpSUmJuL+/fuIjY2FqampXP6PPvoIRkZGghPvODs7Y/r06XJpN2/exO7d\nu+Hg4IDIyEjePmZmZrKfN2zYIOu10NbWlsu3dOlScBwnWO60adPg6uoq+10kEmHmzJkAgNzcXFk6\ne8Ehw6NHj+YN0VuyZAmUlJRkwyJfhNCzrHp6egrta2ZmBmVlfof87NmzAQCHDx9+scq14tdff0Vj\nYyP++c9/wtjYWJaupaUl67VUZJmM9evXAwBWrVrFu/5qampttoWOjo5gz9q0adOgra0t2AZCba6u\nri5Ll/bKCeVTVlaGlpZWq3Vqr5MnTyInJwf/8z//A3d3d7ltQ4cOhb+/P/bv34/a2loAwJYtW9DY\n2IiPP/5Y7txNTU0RERHRoXUjhBBCSPfV6rBPPT09VFVV8dIrKyvlhhYK+emnn3Dy5ElcunRJNrTJ\n3d0durq6eP/99zF79mwMGDCAt1/ToXFeXl7w8vJS4DS6l2HDhvHSNDQ04OTkBIlEgrKyMlhaWiIn\nJwfAsynqz507x9tHWVkZFy5c4KU7Ozvz0qTBl4+PT5uzRebk5IDjOOzduxf79u3jbReLxYLlDh48\nmJfWs2dPAM+e6+ooHh4evDQLCwtYWFigoKAAjLHnmhHT398fn332GQIDAxEUFIRRo0bBw8MDvXr1\nUvgYjY2N+PnnnxEfH4+CggLU1tbKBbvSSUc6w+nTpwE8m5ipOenf4ZkzZ9o8zokTJ6CpqQk3N7fn\nrsvhw4excuVKHD9+HJWVlXLPvTVtA0dHR/Tr1w+xsbE4deoU3n77bQwfPhyOjo5yx9PR0cHYsWOx\nZcsWXLt2DQEBAfD09ISTk5Pcs3sdRfq3d+3aNcHhvuXl5WhsbMTFixcxaNAgWds3DxQB4b93Qggh\nhPx9SCQSSCSSLimr1eDP0dFRMGg4f/48+vbt2+qBz58/Dz09Pd5zNG+++SaAZ1OjtxX8EWFNe2Wa\nks5CWF1dDQCyyS6kC1ELEQpyhGYzlB7T3Ny8zfpVVlaCMYbFixe3WKbQWo86Ojq8NGkvWEdOetFa\n+5WWluL+/fu8HitFWFtbIzs7G9HR0di+fbtsgpBBgwYhJiZGNutta8LDw7F+/XpYW1tj4sSJMDU1\nhaqqKqqqqrBq1SrU1dW1u16Kkk54I3T9DQwMoKSkxJsUR0h1dbXcRDPttW3bNkydOhW6uroYO3Ys\nrK2toa6uDsYYVq5cKdcGSkpKSE1NxcKFC7Fz507Zcgw9e/bEJ598gnnz5sny7tixA0uWLMGWLVtk\nz6caGBjgww8/RFRUlGCP6/OS/u0lJycjOTlZMA/HcbJJl6R/X0ZGRrx8QteDEEIIIX8fzTu8hCYb\n7CitfuXt7++PY8eOobi4WJZWUlKCo0ePwt/fv9UD9+rVC1VVVbh8+bJcuvQbcWmPDmm/W7duCaZL\nZ0KUzrAqDaYuXLiAxsZGwZdQUCUUEEqHot24caPN+uno6EAkEuHhw4ctltn8vuhKrbWfSCSSDQGU\n9ggJzbIp/bDeXP/+/bFz505UVVUhMzMTkZGRKCoqgr+/PwoLC1utV0VFBdavXw8nJyf8+eef+Omn\nn7BkyRJ8+eWXmDJlSov7CdWvtTq2RHq/CM2oeffuXTQ0NAgG6M316NHjhXoov/rqK2hoaCAvLw9b\ntmxBTEwMvvzySyxcuFAw+DUwMMDatWtRXl6Os2fP4rvvvoOqqir+8Y9/yAJw4Fnv+LJly1BcXIyL\nFy9iw4YN6NmzJxYvXowlS5Y8d32FSNvphx9+aPVvT9oLLf2blU6u1JTQ9SCEEEIIeR6tftU9a9Ys\nrF27FuPHj5d9OIqKioKlpSU++OADWb7S0lLY2tpi4cKFiIqKAgCEhIRgxYoV8PX1xeeffw4LCwvk\n5uZiyZIlcHZ27rKhTOxvOGw0MzOTl/bgwQOcOnUKenp6sLS0BPBsseqkpCRkZ2e/8Dpkzs7O4DgO\nhw8fRmNjY6tD5YYMGYL8/Hzk5OQIDiF8UUpKSgCevzcwPT0dn3/+uVxaWVkZysrK0L9/f1nwK302\n7dq1a7xj5Ofnt1qGiooK3Nzc4ObmBmNjY8yfPx8HDx5Enz59WtxH+iXLyJEjoaamJrctKytLcB89\nPT1cv36dl15SUoLq6mre83Wttd3AgQOxe/dupKWlwcnJSW5bWloaAPDShbi4uGD//v3Iysp6rr/z\ny5cvY8CAAbxRAydPnsTjx49b3dfR0RGOjo7w8vLCwIEDsXfvXt7zsQBga2sLW1tbTJw4EUZGRti7\nd2+HjjoYMmQIgGcz877//vtt5ndyckJSUhIyMjJ4IyKE/t4JIYQQQp5Hqz1/GhoaOHLkCOzt7TFj\nxgxMnz4dtra2OHLkCDQ0NGT5GGNobGyUezZJurTDwIED8cUXX8DPzw8///wzPvjgA/zxxx+dd0bd\nQGFhIeLi4uTSYmNjce/ePbmJWkJDQ6GlpSXrfWquuroap06dUqhMExMTBAYGorCwEDExMbztTQOQ\nDz/8EEpKSggPDxfsAaqoqBB85k9R0oCmrKzsufY/dOgQjhw5IpcWFRWFxsZGBAcHy9IcHBygra2N\n5ORkuWdfKyoqBHuK8vPzBYdFStdfFJpspCnpUhXNp/YvKioSbHPgWaBVXFwst8ZhfX09PvroI8H8\n0md1hdpu2rRpUFJSwrfffivXA3X//n1ER0eD4zi59mnJnDlzAAARERG89nj8+LHgc8RNWVlZoaio\nSK4ONTU1ghOflJaWorS0lJfevM3v3LmDgoICXr6Kigo0Nja2eW3ay8XFBS4uLti0aZPgmqhPnjyR\nC+qmTJkCJSUlrFixQq59ysvLsWrVqg6tGyGEEEK6rzYfcrGwsGhzTT9ra2s0Njby0u3t7QVndSQv\nZvTo0ZgzZw5SUlJgb2+P3NxcHDp0CDY2NnK9F0ZGRvj1118xefJk9O/fH76+vrCzs8ODBw9QXFyM\ntLQ0hISEYN26dQqVu27dOpw5cwZRUVFITk6Gp6cn6uvrUVBQgPz8fNy5cwcA0K9fP6xZswZhYWGw\nt7eHn58frKysUFVVhUuXLiEzMxNLliyBg4PDc52/lpYWXFxckJ6ejuDgYNjZ2UEkEiE4OFjW69ka\nX19f+Pr6IigoCD179kRqaiqOHz+ON998E+Hh4bJ8KioqCA8Px7JlyzBo0CD4+/ujtrYW+/btg6en\np9zC4MCzmTB/+ukneHh4wMbGBtra2jhz5gwOHDgAKysrBAUFtVovMzMzBAYGIikpCW+++Sa8vLxw\n48YN7N27F2PGjBFcG/Gjjz7CwYMH4evri6lTp0JdXR1//PEH9PT0YGZmxpsZdcSIEVixYgXef/99\nTJgwAZqamrC2tpZ9sbNs2TJ8+umnGDBgACZOnAgVFRUkJSWhtLQUc+fOFZwsp7m3334b4eHhWLNm\nDezt7TF+/Hjo6+ujrKwMBw4cwC+//NLqsPGwsDBERERg0KBBmDBhAurq6vD777+jZ8+eMDc3lzun\n/Px8vPPOOxg6dCgcHBxgYmKCsrIy7N69G2pqarLree3aNQwaNAgDBw5Ev379YG5ujlu3bmH37t0Q\niUQtBssv4j//+Q+8vb0RGBgId3d3ODk5QVlZGaWlpcjIyIChoSHOnz8PAHjttdfw2WefYfHixbK2\nb2howPbt2+Hi4oKUlJQOrx8hhBBCuqFOW0TiOShSnVesyl2q6fpjEomEeXh4ME1NTWZgYMCCg4N5\na/lJnT9/noWEhDALCwumqqrKjIyM2ODBg1lkZCQrLCwUPH5LqqqqWGRkJLO3t2dqamrM0NCQubq6\nspUrV/LyZmdns0mTJjEzMzOmqqrKzMzMmKurK1u8eDG7evWqLF98fDwTiUQsISGh1XNuqqioiPn5\n+TE9PT0mEomYSCRqcw26puXs3LmTDR48mKmrqzNTU1MWHh7OW5OOMcYaGxvZokWLmKWlJVNTU2MO\nDg5szZo1guv85eTksA8++ID169eP9ejRg2lqarK+ffuyTz/9lN2+fbvVuknV1tayf/zjH8zKyoqJ\nxWLWr1+/FsuT2rFjBxswYABTU1Nj5ubmLCIigt2/f59ZW1vz1vlj7Nkaj/b29kxVVVVwfbpdu3Yx\nd3d3pqWlxTQ1NZmzszP76aefFKp/U1u3bmXDhw9nOjo6TENDg9nb27M5c+awa9euyfKEhIQwkUjE\nWzvv+++/Z3379mXq6urM0tKSzZ8/n9XW1vLO6dq1a2zBggVs6NChzNjYmInFYmZjY8OmT5/Ozp49\nK8t37949tmjRIubp6cnMzMyYmpoas7S0ZAEBASwrK0uu7JbuuZbqyljL6y3evXuXRUZGys5FV1eX\n9e3bl7333nu8tSYZY2zdunXMwcGBqampMRsbG7Zs2TJ2+fJlWufvL+R536MaGxtZ3dM6VvO4ht15\ncIfdqLnBiquKWeGdQna24izLu5HHjpYdZZJiCTt46SDbW7iX7Ty/k205u4UlnEpgG/M2soRTCWzb\nuW0s+UIy++PyHyyzNJPl3chjBbcK2JXKK6y8tpzde3SP1T2ta3G9XUIIIS9fZ8Y73P8W8ErgOK7N\nNdwUyfN3JZFI4OPjg+joaHz55ZcvuzqEEEKa4TgOAVsDUN9QL3vVPa37v58b6gS3PWl80qX1FHEi\niJXFUFdWh7qKuuxfoTR1ZeH09u6vqqT6XMvoEEJId9OZ8U7HzW1OCCGEEOy+sPtlV6FNjawRD588\nxMMnD4FHXVMmB67LAk3pzxRwEkKIPAr+CCGEENLpGNhLCzgVCRRfNNCkgJMQ8ldAwR8hhBBC/pbk\nAs4uwoHjBYUv2svZUqApTVNTUqOAkxCiEHrmjxBCCOkgHMcB0c+3r4pIBWrKalBVUpW91JT+7/fW\ntqmIVFDfWI/HTx/j0ZNHePT0kdy/j58+lkt72vi0Q8+bvFxNA86u6uWkgJOQztOZ8Q4Ff4QQQkgH\n4TgOO8/vVDhok25XEal06Qfpp41PBQNFRYNHuTQF9+/qSW1I52t3L+UL9nKKlcUUcJJugYK/duYh\nhBBCXgZ6j2pZ84DzhYJPBfNSwPn30zxgbG04bFu9nIrsTwEneRko+GtnHkIIIeRloPeoV0tDY8OL\nB5pPHuFxg+L7U8D59yPtdXyRXk6FAtX//VdNWQ0iTvSyT5u8RBT8tTMPIYQQ8jLQexRpaGzgBZCd\nOZz20dNHqG+of9mnTTqYmpJalwSaTZ8VpYDz1UHBXzvzEEIIIS8DvUeRl6FpwNkZw2mF0ijg/Ptp\nGnB29nBaCjhb160WeX/89DHqG+pR97QO9Q31slddQx39R0MIIYQQ0oySSAmaqprQVNXssjIbGhtQ\n11DXpZMG1TXUddn5dUd1DXWoa6jDPdzrsjLVlNTa10v5Ar2cFHA+88oFf+pL1V92FQghhBBCSCuU\nRErQEGlAQ0Wjy8psZI1tThrUZqDZzkmDKODsXNKAs7quusvKVFVSfa5Jg55nOK007VUKOF+54I8Q\nQgghhJDmRJwIGiovJ+DsykmDKODsXNJRhS8j4FQ0eOxMFPwRQgghhBAiQC7g7KLBaY2sEXVP67p0\n0qDHTx93zcl1Uy8j4GwJBX+EdBJra2twHIfi4uKXXZW/PIlEAh8fHyxcuBALFy582dWRaeka//nn\nn/jkk09w/Phx3LlzB2+88Qby8/MREhKCxMRElJSUwNLSssPr4+XlhfT0dDQ2Nnb4sQkhhHQNESd6\n1gOkov5SAs6umjSIAs6X45UL/tSU1KCqpApVJVWoKf/fz6pKqlBTUkMe8l52FclLVlJSAhsbG8yc\nORNxcXEK7xcfH493330XcXFxmDlzZifW8BmO4/6yC8O+qsHWq9aeQte4oaEBgYGBKC0txcyZM2Fu\nbg5TU9MW83dGnQghhJD2kAs4uwhjrMsnDXr09FGXnd+r6pUL/h5/0fq3ANwH9MGmu5N+uH3eD7ld\n9eH4yJEjXVJOZ6JAonVC1/jKlSsoKirC7NmzsW7dOrltMTExiIyMhLm5eVdVkRBCCHklcRwHsbIY\nYmUx9KDXJWU2Dzi7qpfzVfLKBX+EtEW67snzrn/SVWtw9e7du0vK6Uy0XlnrhK5xeXk5AMDExIS3\nzdTUVNYLSAghhJCu9TIDzvYEmh9Gf9ipFXplKFKdV6zKXSo1NZVxHMeio6NZamoqc3d3Z1paWszA\nwIDNmDGDlZeXC+538uRJNnHiRGZsbMzU1NSYra0ti4yMZPfv32/x+BkZGWzEiBFMR0eH6enpyfLc\nu3ePffHFF6xv375MXV2d6evrsyFDhrBvv/2WV+6RI0fYW2+9xfT19ZlYLGZ9+/ZlsbGx7OnTp3L5\n4uLiGMdxLD4+nh04cIC5uroyTU1NZmBgwGbOnMnu3r3Lyyv0SktLa7HtZs6c2eJ+Up6enozjOPb4\n8WMWGRnJrK2tmYqKClu5ciVjjLHc3Fz24Ycfsr59+zIdHR2mqanJBg0axNatWydYppWVFbO2thas\nR3FxMVu1ahXr06cPU1NTY1ZWVmzRokWssbGxxXNoqr6+nq1atYqNHDmSmZubM1VVVWZmZsamTZvG\nLl682OL5l5aW8rYtXLhQrv2kvwu9mu5/5coVFhwczExNTZmqqiqzsrJi4eHh7Pbt2wqdg9TFixfZ\nu+++yywsLJiamhozMzNjY8aMYcnJybI80ntz0aJFcvvu2rWLBQUFsd69ezN1dXWmp6fHRo4cyQ4d\nOiRY1vbt25m7uzszNDRkYrGY9ezZk/n6+rI//vhDLt8ff/zBRo0axUxNTZmamhozNTVl3t7ebOvW\nrXL5ml9jKysrwXZLSEhgjLV8HRoaGtiPP/7IXFxcmKamJtPS0mJubm5s165dgueRn5/PRo8ezTQ1\nNZmenh6bOHEiKy0tZZ6enkwkErXR4qQzdef3KEIIIR2jM99LqOfvLyg7OxsxMTEYN24cIiIicOLE\nCWzevBlZWVk4ceIE9PX1ZXmTkpIwZcoUiMViBAQEwNTUFHl5eYiNjUVqairS09OhoqIid/ysrCws\nW7YMI0eOxJw5c3D79m0AQEVFBTw8PHDp0iW4uLggPDwcdXV1OHv2LGJjY/Hxxx/LjrF27VrMKFHf\n2AAAIABJREFUmzcPxsbGCAwMhJ6eHjIyMhAZGYnjx49j586dvPNKTk5GSkoK/P394e7ujrS0NCQm\nJuLy5cvIyMgAAAwcOBARERFYtWoVnJycEBAQINvfysqqxTYLDAxEdXU19uzZg4CAADg5ObWYNyAg\nAAUFBXjrrbego6MDCwsLAMDGjRuRkpICT09PjBs3DrW1tThw4ADmzp2LoqIifPfdd7xjtTRs8pNP\nPkFaWhrGjRuHt956C0lJSYiOjkZ9fT2WLFnSYt2k7t69i48//hienp4YP348dHV1ceHCBWzfvh2/\n//478vLyYG1trVBdmvP29kZpaSkSEhLg5eUFLy8v2TZdXV0AzyY08fDwQFVVFQIDA9GnTx+cOHEC\na9euRUpKCo4dOwYjI6M2y0pPT4efnx8ePXqEt99+G46Ojrh9+zZycnIQFxeHcePGtbr/559/DrFY\nDG9vb5iamuLGjRvYvXs3xowZg//+978IDAyU5f3+++8RHh4OOzs7TJ06Fdra2rh+/TqOHj2KgwcP\nYuTIkQCAffv2wd/fH+bm5ggICICBgQHKy8uRm5uLnTt3YvLkyS226/z583Hq1Cle2zW935pfB8YY\npk6div/+979wdHREaGiorB7vvPMOVq5ciXnz5snynzlzBh4eHqirq8OkSZNgbW0NiUQCDw8P6Ol1\nzbeYhBBCCPmL6rSw8jkoUp1XrMpdStr7wXEci4uLk9sWFRXFOI5j4eHhsrTbt28zbW1tZmtry+sV\n/OabbxjHcXI9dk2Pv2nTJl75gYGBjOM4tnTpUt62GzduyH4+d+4cU1ZWZq6urqympkYuX1hYGOM4\nju3YsUOWJu3NU1VVZUePHpWlNzQ0MG9vb8ZxHDt27JgsvaSkhHEcx0JDQ1tqKkHScqS9MM1Je/6c\nnZ1ZdXU1b3tZWRkv7enTp2zs2LFMSUmJ15tjZWXFevfuLZcm7fmxtbVlN2/elKXfuXOH6enpMR0d\nHVZfX9/mudTV1Qn29KalpTFlZWX23nvvCZarSM8fYy33tElJ26r5ffLll18qfG0ePXrEzM3NmYqK\nimCv7fXr19usT0lJCW+/iooK1qtXL2ZnZyeXPnDgQNarVy/26NEj3j5Ne5cDAwOZWCwW7MFsmo8x\n4WvcWtsJXYcffviBcRzHwsLC5Hp+Hzx4wIYMGcLU1NTk/r48PDwYx3EsKSlJ8NjU8/dydef3KEII\nIR2jM99LXp3l5onCHBwcEBISIpe2YMEC9OjRA5s3b5alJSYm4v79+4iNjeU9Z/TRRx/ByMgIW7du\n5R3f2dkZ06dPl0u7efMmdu/eDQcHB0RGRvL2MTMzk/28YcMGNDQ0YPXq1dDW1pbLt3TpUnAcJ1ju\ntGnT4OrqKvtdJBLJZuXMzc2VpbNOfg5t0aJF0NHR4aVLewCbUlJSwqxZs9DY2AiJRKJwGVFRUXLP\nhBkYGMDf3x+1tbUoKipqc39VVVXBZ8eGDx+O119/HYcOHVK4Lu1VWlqK9PR0ODk58e6TyMhIGBoa\nYtu2bXjy5Emrx9mzZw/Ky8sREhKC4cOH87YrMimKUG+vtLf58uXLKCsrk6VzHAcVFRWIRPz/9pr2\nlgOAsrIylJX5AyOa5+sI33//PXr06IHvvvtOrldQQ0MDX3zxBerr67Fr1y4Az9o+MzMTzs7Ocr3e\nALB48WLBcyOEEEIIkeo2wz4lnKRLy/NiXp127GHDhvHSNDQ04OTkBIlEgrKyMlhaWiInJwcAkJmZ\niXPnzvH2UVZWxoULF3jpzs7OvDRp8OXj49Pm8MGcnBxwHIe9e/di3759vO1isViw3MGDB/PSevbs\nCQC4d+9eq2V2FI7jBM8fAOrq6rB69Wps27YNhYWFePDggdx26UQfihA61169egFQ/Fzz8vLw9ddf\nIysrC7dv35YLttTU1BSuS3udPn0aAAQDNrFYDBcXF/z2228oKiqCo6Nji8c5ceIEAGD06NHPXZeb\nN28iJiYG+/fvx7Vr1/D4sfxsweXl5bL19CZPnowFCxagX79+mDJlCry8vDB06FBoaGjI7TNlyhTs\n3r0b/fr1w9SpU+Hj4wM3NzfZkNeO9PDhQ5w7dw6WlpaCw32lQ64LCwsBPBvyCQDu7u68vBYWFrC0\ntERpaWmH15MQQgghfw/dJvjrzGCsqxkbGwumS3uSqqurAQCVlZUAgNWrV7d4LKFATmiWQukxFemN\nqaysBGMMixcvbrHMhw8f8tKFetukvS8NDQ1tlttRWmrfCRMmYP/+/Xj99dcxffp0GBkZQVlZGcXF\nxUhISEBdXZ3CZbzouWZmZmLEiBFQVlbGmDFjYGdnB01NTXAch7i4OLker45WU1MDQPg+ASDrkZTm\na0l77ikhlZWVcHFxwfXr1+Hh4QE/Pz/o6upCJBIhNTUVaWlpctfkX//6F/T19fHDDz9gyZIlWLJk\nCdTU1DBx4kSsWLFCdt2DgoKgoqKCf//73/juu++wYsUKKCsrY+zYsfjuu+9ga2v7XPUVUlVVBQAo\nKyvDV199JZiH4zjZFw3SNmvpeUoTExMK/gghhBDSom4T/P2d3Lp1SzC9oqICwP9NyiENMC5cuAB7\ne3uFjy8UEPbo0QMAcOPGjTb319HRgUgkwv379yEWixUu91V24sQJ7N+/H2+99RZSUlLktm3btg0J\nCQldWp+YmBg8ffoUaWlpGDp0qNy2LVu28PJLhwM+ffqUt00aUChKel9J77fmpOlCAW5T0nvq+vXr\n7Spf6ueff8a1a9ewbNkyLFiwQG5beXk50tLSePu89957eO+993Dnzh3ZhEK//vorrl69KjdsNzAw\nEIGBgaitrUVGRga2b9+OxMREXLhwAQUFBbxJkp6XtI2GDh2Ko0ePtplf+rct7RFsrqVrQgghhBAC\nAPSAyF9QZmYmL+3Bgwc4deoU9PT0ZMPchgwZAuDZ7KAvytnZGRzH4fDhw2hsbGw175AhQ9DY2Cgb\ndtrRlJSUALS/N/B59wOAy5cvAwD8/Px427Kystp9vBd1+fJlGBgY8AK/iooKWV2bks4Cee3aNd62\n/Px8XlprbTVw4EAAkM3A2tTjx49x/PhxqKuro0+fPq2eg4uLCwDg4MGDreZrifQ8/f395dIZY23e\n84aGhnjnnXewZ88evPHGG0hPT0dtbS0vn7a2Nnx9fREfHw9/f39cunRJcMjy89LW1oaDgwMKCgpw\n//79NvO/8cYbAITbvqysrFN7fAkhhBDy10fB319QYWEh4uLi5NJiY2Nx7949uQk4QkNDoaWlhcjI\nSMFJRKqrq3Hq1CmFyjQxMUFgYCAKCwsRExPD29609+bDDz+EkpISwsPDBZ+Dq6ioeKEP0NJApr0f\ndKWTdTzPB2TpxCLNA+9jx47hxx9/bPfxXpSVlRXu3r0r14719fUICwsT7N2TBlrx8fFy6Tt27EB6\nejqvt7e1trKwsICnpyfy8/N5vYzLly/H7du3MWXKFMEJU5qSLqcQHx8v2EvXVo9gS9dk5cqVOHPm\nDO+chMp49OgRqquroaKiIgt4MzIyeF9wNDY24s6dO88Wh+3g3uzw8HDU1tZi9uzZgkOHCwoKZD19\nlpaW8PDwQF5eHpKSkuTyRUVFtfnFDCGEEEK6Nxr2+Rc0evRozJkzBykpKbC3t0dubi4OHToEGxsb\nREdHy/IZGRnh119/xeTJk9G/f3/4+vrCzs4ODx48QHFxMdLS0hASEoJ169YpVO66detw5swZREVF\nITk5GZ6enqivr0dBQQHy8/Nx584dAEC/fv2wZs0ahIWFwd7eHn5+frCyskJVVRUuXbqEzMxMLFmy\nBA4ODs91/lpaWnBxcUF6ejqCg4NhZ2cHkUiE4OBgWa+nEDc3N6irq2PlypWoqqqCoaEhAOCLL76Q\n5WlpJtEhQ4bA2dkZW7duxc2bN+Hs7IwrV65g79698Pf3F1y3sDOFhYXhjz/+wLBhwxAUFARlZWUc\nOnQIDQ0NeOONN2STskiNHz8etra2iI+Px9WrV+Hk5IQ///wTqamp8PX1xW+//SaX//XXX4e5uTm2\nbt0KNTU19OzZExzHYd68edDR0cH69evh7u6OGTNmYNeuXXjttdeQl5eHP/74AzY2Nli+fHmb56Cm\npoYtW7bA19cXI0aMgJ+fHxwdHVFZWYmcnBxYW1vzApymZsyYgeXLlyMsLAwSiQTm5ubIzc1FTk4O\n/Pz8eMNzx48fDz09PQwZMgSWlpZ4/Pgx9u/fj5KSEoSHh8smfgkPD0dFRQWGDRsGKysrMMaQmpqK\n06dPY9y4cXjttdcUvUwKmTNnDo4ePYpff/0VGRkZsjULy8vLcfbsWZw6dUpu3cQ1a9bA3d0dQUFB\nmDRpEqysrJCWlobr169jwIABsklhCCGEEEJ4Om0RieegSHVesSp3qabrh0kkEubh4cE0NTWZgYEB\nCw4OFlz3jTHGzp8/z0JCQpiFhQVTVVVlRkZGbPDgwSwyMpIVFhYKHr8lVVVVLDIyktnb2zM1NTVm\naGjIXF1d2cqVK3l5s7Oz2aRJk5iZmRlTVVVlZmZmzNXVlS1evJhdvXpVli8+Pp6JRCLB9fdaqlNR\nURHz8/Njenp6TCQSMZFIJLhWXHO//fYbc3FxYRoaGrw10by8vFpdI62iooKFhIQwc3NzpqGhwZyd\nndmWLVuYRCIRrKO1tTVvDbiQkBAmEokE19uLjo5W+DwYY2z79u1s4MCBTENDg5mZmbHQ0FBWUVHR\n4nmUlJSwwMBApqOjw7S0tNioUaNYXl5ei+Xm5OQwLy8vpqOjI2urpvW+cuUKCw4OZqampkxVVZVZ\nWVmx8PBwwfXxWlNYWMiCg4OZubk5U1VVZebm5szX15f99ttvsjwt3Qf5+fls1KhRTE9Pj+nq6rKx\nY8ey3NxcwXNav3498/f3Z9bW1kwsFjNjY2Pm4eHBNm/eLHfMbdu2saCgIGZra8s0NDSYgYEBe/PN\nN9natWvZkydP5PIKXePW/o5au/6//vor8/b2Znp6ekxNTY1ZWVmxsWPHsh9++IE9ePCAd96jR49m\nmpqaTF9fn02aNIldvXq1zXuYdL7u/B5FCCGkY3Tmewn3vwW8EjiOa3MNN0Xy/F1JJBL4+PggOjoa\nX3755cuuDiGEkGa683sUIYSQjtGZ7yX0zB8hhBBCCCGEdAMU/BFCCCGEEEJIN0DBHyGEEEIIIYR0\nA/TMHyGEENJB6D2KEELIi6Jn/gghhBBCCCGEvBAK/gghhBBCCCGkG6DgjxBCCCGEEEK6AQr+CCGE\nEEIIIaQboOCPEEIIIYQQQroBCv4IIYQQQgghpBug4I8QQgghhBBCugEK/gghhBBCCCGkG6DgjxDS\nZUQiEby9vV92NeSEhIRAJBKhrKxMLv3evXuYM2cOrKysoKSkBJFIhOrqasTHx0MkEiEhIaFT6hMd\nHQ2RSIT09PROOT4hhBBCui8K/shfTklJCUQiEUJDQ192VV55r2KwxXHcy66CHI7jBOv0z3/+Exs2\nbMDgwYMRFRWF6OhoiMXiVvchhBBCCHmVKb/sChDSXtIP3fThWzHUTq2LiYlBZGQkzM3N5dL3798P\nBwcH7Nq1Sy59woQJcHNzg6mpaVdWkxBCCCHkhSnU83f16lVMnDgRPXr0gK6uLt555x1cvXq1zf2k\nw5eEXurq6i9cedI9Mcbk/iXkRZiamsLe3h7KyvLfhZWXlwsGeDo6OrC3t4eOjk5XVZEQQgghpEO0\nGfw9fPgQPj4+KCoqQmJiIjZt2oSLFy/C29sbDx8+bHXfWbNm4dixY3KvQ4cOQVlZGePHj++wk+gu\nJBIJRCIRFi1aBIlEAg8PD2hra8PQ0BDBwcG4efOm4H75+fmYNGkSTExMIBaLYWdnh88++wwPHjxo\n8fiZmZkYOXIkdHV1oa+vL8tTXV2NqKgoODo6QkNDAwYGBhg6dChWrFjBKzc1NRW+vr4wMDCAuro6\nHB0dsXz5cjQ0NMjla/oM1cGDB+Hm5gYtLS0YGhoiJCQElZWVcnltbGwAAAkJCXJfKCjyjFRjYyM2\nbtwINzc36OjoQEtLC3379sVHH32Ee/fuyfIdOXIEoaGhsLe3h5aWFnR0dDBs2DBs376dd8ymw1AL\nCgowfvx46OvrQyQSoaamptX6JCUlYfLkybCxsYGGhgb09fUxatQoHD58mJe3tWfNml67pr83/Vn6\narr//fv38fnnn+O1116DWCyGsbExJk6ciDNnzrTZlk21575oLi8vD3PnzoWjoyN0dXWhpaWFwYMH\nY/369YL5c3NzMWHCBFhYWEAsFsPExARubm74/vvv5fIVFRUhODgY1tbWEIvFMDQ0xODBgxEdHS2X\nr/kzf9LfAfm2kw4zbu06KHrPA8Dt27fxP//zPzAyMoKWlhY8PDzoOT9CCCGEdKo2h31u3LgRxcXF\nKCoqkn3oHjBgAF577TVs2LAB8+fPb3Hfnj17omfPnnJpmzZtwtOnTzFz5swXrHr3lZ2djZiYGIwb\nNw4RERE4ceIENm/ejKysLJw4cUIuWEtKSsKUKVMgFosREBAAU1NT5OXlITY2FqmpqUhPT4eKiorc\n8bOysrBs2TKMHDkSc+bMwe3btwEAFRUV8PDwwKVLl+Di4oLw8HDU1dXh7NmziI2Nxccffyw7xtq1\nazFv3jwYGxsjMDAQenp6yMjIQGRkJI4fP46dO3fyzis5ORkpKSnw9/eHu7s70tLSkJiYiMuXLyMj\nIwMAMHDgQERERGDVqlVwcnJCQECAbH8rK6tW262xsRHvvPMO9uzZA2tra4SEhEBdXR0XL17Exo0b\nERISgh49egAAvvnmGxQXF8PV1RU9e/bE3bt3kZycjClTpqC8vBwRERG841+6dAlubm4YOHAg3nvv\nPVRUVMiCiJZ8/vnnEIvF8Pb2hqmpKW7cuIHdu3djzJgx+O9//4vAwEDePq0N45Ru6927NxYuXIhF\nixbJzlVq4MCBAIBHjx7By8sLJ0+exNChQxEUFISysjJs374d+/fvx++//w4PD49W6w+0774QsnHj\nRqSkpMDT0xPjxo1DbW0tDhw4gLlz56KoqAjfffedLG9+fj6GDRsGbW1tjB8/HmZmZrhz5w5Onz6N\nxMREzJ07FwBw/fp1uLi4oKGhAePHj4e1tTWqqqrw559/YsOGDbwAsGmbBgYGonfv3ry2c3JyanEf\noH33/P379+Hp6YkLFy7Ay8sLbm5uKCwsxOjRo+Hl5dVmmxNCCCGEPBfWBh8fH+bu7s5L9/T0ZJ6e\nnm3tzjNixAhmZmbGGhoaeNsUqI5CeZpKTcVLfXWk1NRUxnEc4ziOxcXFyW2LiopiHMex8PBwWdrt\n27eZtrY2s7W1ZeXl5XL5v/nmG8ZxHPv2228Fj79p0yZe+YGBgYzjOLZ06VLeths3bsh+PnfuHFNW\nVmaurq6spqZGLl9YWBjjOI7t2LFDlhYXF8c4jmOqqqrs6NGjsvSGhgbm7e3NOI5jx44dk6WXlJQw\njuNYaGhoS00laNWqVYzjOObn58fq6+vlttXU1LD79+/LldHcgwcP2BtvvMF0dXXZw4cPZenFxcWy\ndlu8eHG76iRUTkVFBevVqxezs7OTS5e2U0JCAm8f6bVbtGiRXDrHcczb21uw7IULFzKO49h7770n\nl3748GHGcRyzs7NjjY2NbZ6DovdFS/UpKyvj7ff06VM2duxYpqSkxEpLS2Xp8+fPZxzHsTNnzvD2\nqayslP0svdbJycmt5mOMsZkzZzKO4+TKaamujAlfh/be89K/14iICLm8v/zyC+M4jolEIpaWlsYr\nm7z62vseRQghhDTXme8lbQ77LCgoQL9+/Xjpffv2xfnz59sVaF69ehUSiQT/7//9vzZ7REjLHBwc\n5HpyAGDBggXo0aMHNm/eLEtLTEzE/fv3ERsby3t26aOPPoKRkRG2bt3KO76zszOmT58ul3bz5k3s\n3r0bDg4OiIyM5O1jZmYm+3nDhg1oaGjA6tWroa2tLZdv6dKl4DhOsNxp06bB1dVV9rtIJJL1EOfm\n5srS2XM+67d+/XqoqKjg+++/5/V2amtrQ1NTU/a7UC+ihoYGgoODUVNTg+PHj/O2m5ubC7ZNa4TK\nkfYcXb58mbf8QEdKSEiAmpoali5dKpfu4+MDPz8/XL58GZmZma0eoz33RUssLCx4aUpKSpg1axYa\nGxuRmprK2y6ddbMpPT295873otp7z2/evBnq6ur48ssv5fKGhoaiT58+9DwrIYQQQjpFm8M+q6qq\nBD8s6evro6qqql2Fbd68GY2NjTTk8wUNGzaMl6ahoQEnJydIJBKUlZXB0tISOTk5AIDMzEycO3eO\nt4+ysjIuXLjAS3d2dualSYMvHx+fNmePzMnJAcdx2Lt3L/bt28fbLhaLBcsdPHgwL006bLjp83jP\n4/79+ygsLETfvn3bHB4KADU1Nfj666+xZ88eXLlyBY8ePZLbLvR85YABA6CkpNSuet28eRMxMTHY\nv38/rl27hsePH8ttLy8vh6WlZbuOqYiamhqUlpZiwIABMDY25m339PRESkoKzpw50+rQz/bcFy2p\nq6vD6tWrsW3bNhQWFvKeRW3a1kFBQVi9ejWGDh2KqVOnYsSIEXB3d4eRkZHcPv7+/vjss88QGBiI\noKAgjBo1Ch4eHujVq9dz1bEt7bnna2pqUFJSAicnJ7kh2lKurq4oLCzslHoSQgghpHvr0qUeEhMT\nMWjQIMGeRKI4oQ/rAGBiYgLg2eQbAGQTpaxevbrFYwl9YJcepynpMZtPhy+ksrISjDEsXry4xTKF\nJgsSmj1ROgOj0IQZ7dGe+tfX18PT0xOnT5+Gs7Mz3n33Xejr60NJSQn5+fnYs2cP6urqePsJtVtr\nKisr4eLiguvXr8PDwwN+fn7Q1dWFSCRCamoq0tLSBMvpCNKJaFqqs7SnuK0Ja9rTri2ZMGEC9u/f\nj9dffx3Tp0+HkZERlJWVUVxcjISEBLk2GDp0KI4cOYJly5bhp59+wrp168BxHIYPH45vv/1W9gWC\ntbU1srOzER0dje3btyM+Ph4AMGjQIMTExGDUqFHPXV8h7bnnpW3aPGCVau99RAghhBCiqDaDPz09\nPcEevsrKSsFvrVty/PhxFBYWYtWqVa3mazoRg5eXF01+IODWrVuC6RUVFQAAXV1dAP8XTF24cAH2\n9vYKH18oIJROhHLjxo0299fR0YFIJML9+/cFh929DNI2UaT+e/bswenTp/H+++/jhx9+kNu2fPly\n7NmzR3C/9vZ8/fzzz7h27RqWLVuGBQsWyG0rLy9HWlqaXJp0qPTTp095x5IGYYqS3hvSe6Y5aXpb\nyxm0574QcuLECezfvx9vvfUWUlJS5LZt27ZNcEbN4cOHY/jw4Xj06BGys7Oxe/dubNiwAWPHjsWF\nCxdgYGAAAOjfvz927tyJJ0+e4MSJE0hJScGaNWvg7++PU6dOoU+fPs9VZyHtueelbSqdSKm5lq4J\nIYQQQv6eJBIJJBJJl5TVZvDn6OgoOGTw/Pnz6Nu3r8IFJSQkQFVVFdOmTWs1X/NZ+F6Ul9ff79kZ\noeewHjx4gFOnTkFPT082THDIkCFISkpCdnZ2u4I/Ic7OzuA4DocPH0ZjY2Orz2wOGTIE+fn5yMnJ\ngaen5wuVK0Q6tLI9vYFaWlp4/fXXUVRUhNLS0laHfl6+fBnAs6GDzWVlZbWzti1rqRzGGLKzs3n5\npcOvr127xtuWn58vWAbHcYLtpKOjA2traxQWFuLWrVu83mRp4Nl8hsvm2nNfCJG2gZ+fH29bW22t\nrq4OHx8f+Pj4QElJCatWrcLRo0cxbtw4uXwqKipwc3ODm5sbjI2NMX/+fBw4cKBDg7/23PPStr9w\n4QLu3r0rC1aBZ9f+6NGjHVYvQgghhLz6mnd4SZfu6gxtflLz9/fHsWPHUFxcLEsrKSnB0aNHBT8c\nC6mvr8fWrVvx1ltvyX3QIc+nsLAQcXFxcmmxsbG4d++e3EQtoaGh0NLSQmRkJIqKinjHqa6uxqlT\npxQq08TEBIGBgSgsLERMTAxv+/Xr12U/f/jhh1BSUkJ4eDjKy8t5eSsqKgSf+VOUNAhq72Qoc+bM\nwdOnTzF37lw8efJEbltNTY3sWTNpYNg8yN61a5fg81zPq6VyVq5ciTNnzvB6EqWB1tatW+WGQl68\neLHFHnV9fX3BYBEAZs6cibq6OkRFRcmlSyQS7Nu3D3Z2doLPlzbVnvtCSEttcOzYMfz444+8/NnZ\n2aivr+elS58LlPa65efnCw5ZleZTV1dvtV7t1d57fsaMGXj8+DG++uoruXxxcXEoKip67ucnCSGE\nEEJa02bP36xZs7B27VqMHz8eS5YsAQBERUXB0tISH3zwgSxfaWkpbG1tsXDhQt6HyX379qGqqoom\neukgo0ePxpw5c5CSkgJ7e3vk5ubi0KFDsLGxkes5NTIywq+//orJkyejf//+8PX1hZ2dHR48eIDi\n4mKkpaUhJCQE69atU6jcdevW4cyZM4iKikJycjI8PT1RX1+PgoIC5Ofn486dOwCAfv36Yc2aNQgL\nC4O9vT38/PxgZWWFqqoqXLp0CZmZmViyZAkcHBye6/y1tLTg4uKC9PR0BAcHw87ODiKRCMHBwa1O\njjJ37lwcPnwYe/bsgb29Pd5++21oaGjgypUr+P3335GVlYUBAwZg3LhxsLS0xPLly1FQUIA+ffqg\noKAABw4cQGBgIJKSkp6r3s3NmDEDy5cvR1hYGCQSCczNzZGbm4ucnBz4+fnxhkGamZlh6tSp+M9/\n/oPBgwdjzJgxuHXrFnbv3o2xY8cKrp04YsQIbN++HYGBgXBycoKSkhLGjx+P/v3749NPP8W+ffuw\nceNGnDt3DsOHD8e1a9ewfft2aGho4JdfflHoPBS9L4QMGTIEzs7O2Lp1K27evAlnZ2dcuXIFe/fu\nhb+/P++cli9fjrS0NAwfPhzW1tZQVVVFTk4OMjMzMXjwYPj4+AB4NtLgp59+goeHB2x+uJ8CAAAg\nAElEQVRsbKCtrY0zZ87gwIEDsLKyQlBQkELnpqj23vP/+te/sGPHDqxZswZnzpyBq6srioqKsG/f\nPowePRoHDx7s0PoRQgghhABQbBGJsrIy9s477zAdHR2mra3NAgMDeWtiSdc6a77OGGOMjR8/nhka\nGrInT560Wo4i1VGwyn9LTddyk0gkzMPDg2lqajIDAwMWHBzMW8tP6vz58ywkJIRZWFgwVVVVZmRk\nxAYPHswiIyNZYWGh4PFbUlVVxSIjI5m9vT1TU1NjhoaGzNXVla1cuZKXNzs7m02aNImZmZkxVVVV\nZmZmxlxdXdnixYvZ1atXZfni4+OZSCRq1/p1RUVFzM/Pj+np6TGRSKTwumgNDQ1s/fr17M0332Sa\nmppMS0uLOTo6sn/+85/s3r17snyXL19mgYGBzMjIiGlra7Phw4ezgwcPCtZVeu+3d91BxhjLz89n\no0aNYnp6ekxXV5eNHTuW5ebmsujoaMFzevToEYuIiGCmpqZMLBYzJycntmXLFiaRSATb6ebNm2zy\n5MnMyMiIKSkp8epeW1vLPvvsM2ZnZ8dUVVWZoaEhe+eddwTX0WuNoveF0Np5FRUVLCQkhJmbmzMN\nDQ3m7Ozc4jkdOHCAzZw5k/Xp04dpa2szXV1d9sYbb7Bly5ax2tpaWb6cnBz2wQcfsH79+rEePXow\nTU1N1rdvX/bpp5+y27dvy5UfEhLCRCKRwuv8tXa/KnrPM/ZsHc53332XGRoaMk1NTebu7s7S0tJa\nvPbkr6E7v0cRQgjpGJ35XsL9bwGvBI7j2lzfSpE8f1cSiQQ+Pj6Ijo7mrQ9GCCHk5evO71GEEEI6\nRme+l9BK64QQQgghhBDSDVDwRwghhBBCCCHdAAV/hBBCCCGEENIN0DN/hBBCSAeh9yhCCCEvip75\nI4QQQgghhBDyQij4I4QQQgghhJBugII/QgghhBBCCOkGKPgjhBBCCCGEkG6Agj9CCCGEEEII6QYo\n+COEEEIIIYSQboCCP0IIIYQQQgjpBij4I4QQQgghhJBugII/QgghhBBCCOkGKPgjpAXR0dEQiURI\nS0t72VX5yykpKYFIJEJoaOjLroocLy8viET8//auX7+OadOmoWfPnhCJRNDT0wPQ+fdASEgIRCIR\nysrKOuX4hBBCCCFNUfBH/nK6KrDgOE72etW9qsHWq9Z2LV3PmTNnYtu2bRg5ciQWLlyIyMhIufyd\neR6vWhsRQggh5O9L+WVXgJD2kn5Y7uwPzWFhYZg6dSosLCw6tZyO0FVt8leXmJiIR48eyaXV1dUh\nNTUVY8aMQUJCgty2rrgHGGOddmxCCCGEkKYo+CN/OdIPy539odnAwAAGBgadWkZH6ao2+asTCuIq\nKirAGIOJiQlv21/pHiCEEEIIaQsN+/wLkUgkEIlEWLRoESQSCTw8PKCtrQ1DQ0MEBwfj5s2bgvvl\n5+dj0qRJMDExgVgshp2dHT777DM8ePCgxeNnZmZi5MiR0NXVhb6+vixPdXU1oqKi4OjoCA0NDRgY\nGGDo0KFYsWIFr9zU1FT4+vrCwMAA6urqcHR0xPLly9HQ0CCXLz4+HiKRCAkJCTh48CDc3NygpaUF\nQ0NDhISEoLKyUi6vjY0NACAhIQEikUj2Sk9Pb7X9ampqEBsbCw8PD5iamkJNTQ1WVlaYPXs2Kioq\nePmlz3s1Pa4ibdSSX375Bf7+/rCysoJYLIaRkRECAgKQl5enUNnN2ysxMbFdbXLr1i2EhYXBysoK\nampqMDc3R0hICEpKStqse1Pl5eWIiIiAnZ0d1NXVYWxsDC8vL16vmZAjR44gNDQU9vb20NLSgo6O\nDoYNG4bt27cL5j906BBGjx4NMzMziMVimJmZwcfHB9u2bZPLl5ubiwkTJsDCwgJisRgmJiZwc3PD\n999/L5ev+TN/Xl5esLa2BiDfdl999RWA1q/Dzp074eXlBV1dXWhoaGDQoEHYuHGj4HkUFxdj4sSJ\n6NGjB3R1dTF27FicOXOmzfYihBBCCOlI1PP3F5SdnY2YmBiMGzcOEREROHHiBDZv3oysrCycOHFC\nLhBJSkrClClTIBaLERAQAFNTU+Tl5SE2NhapqalIT0+HioqK3PGzsrKwbNkyjBw5EnPmzMHt27cB\nPOsh8fDwwKVLl+Di4oLw8HDU1dXh7NmziI2Nxccffyw7xtq1azFv3jwYGxsjMDAQenp6yMjIQGRk\nJI4fP46dO3fyzis5ORkpKSnw9/eHu7s70tLSkJiYiMuXLyMjIwMAMHDgQERERGDVqlVwcnJCQECA\nbH8rK6tW2+38+fNYtGgRRowYgaCgIKirq+PUqVP48ccfcfDgQZw8eRI9evRQ6Bq01EatCQsLw6BB\ngzB27FgYGBiguLgYe/bswYEDByCRSDBkyBCFym5OkTa5desWhgwZgtLSUowePRrTp0/HhQsXsGnT\nJqSkpCAzMxN9+vRps6w///wT3t7euHXrFnx8fBAUFISamhrk5eVh9erVmDlzZqv7f/PNNyguLoar\nqyt69uyJu3fvIjk5GVOmTJEFlVL79u2Dv78/zM3NERAQAAMDA5SXlyM3Nxc7d+7E5MmTATz7cmPY\nsGHQ1tbG+PHjYWZmhjt37uD06dNITEzE3Llz5erQdGhsaGgoBg4cyGs7Ly+vVs/jk08+wYoVK2Bt\nbY2pU6dCQ0MDBw8exAcffIA///wT//73v2V5r1+/jmHDhuHmzZvw9/eHo6MjTp48ieHDh+ONN95o\ns80JIYQQQjoMe4UoUp32VhnAS311pNTUVMZxHOM4jsXFxclti4qKYhzHsfDwcFna7du3mba2NrO1\ntWXl5eVy+b/55hvGcRz79ttvBY+/adMmXvmBgYGM4zi2dOlS3rYbN27Ifj537hxTVlZmrq6urKam\nRi5fWFgY4ziO7dixQ5YWFxfHOI5jqqqq7OjRo7L0hoYG5u3tzTiOY8eOHZOll5SUMI7jWGjo/2fv\nzuOiqvo/gH/uBdmEYRPJJUElJcUUdyVlXDMtFTSXX4pYhtqDmqWWlrmWW5bZpi1uaeVSielTWSog\nZmbuoWiSqCmKuYCKIsv394fPTIwzzAzICDif9+vFy5lzzz3n3DMzzv3OufecoUV1lUmZmZly+fJl\no/SVK1eKoigyc+ZMg/QpU6aIoiiSkJCgT7PUR+akpaUZpR05ckQ8PDykc+fOFuvW0fXX8uXLDco2\n1ydDhgwRRVFkxowZBulLliwRRVGkQ4cOVh1D06ZNRVEUWblypdG2wu+BEydOmGyPqT64fv26NG7c\nWDw9PSU7O1ufHhERIS4uLnLhwgWjfS5evKh/PHbsWFEURQ4ePGiU79KlSwbPw8PDRVVVozYV1Xem\nXocffvhBFEWRiIgIycnJ0afn5uZK7969RVEU2b17tz598ODBoiiKvPPOOwZlv/7666IoiqiqKidP\nnjSqmyqmcva1SkREFZAtv0t42WcFFBwcjOjoaIO0V155BV5eXli5cqU+bcWKFbh27Rpmz56NBx54\nwCD/iy++CD8/P3z11VdG5Tdv3hyDBg0ySDt37hzWr1+P4OBg/UyIhVWrVk3/ePHixcjPz8fChQvh\n4eFhkO+NN96Aoigm6/2///s/tGnTRv9cVVX9SNLvv/+uT5cS3tem0WhMjuz93//9Hzw8PLBlyxar\nyzLVR5aYGpkMDg6GVqvF9u3bkZeXV6zyCjPXJzk5OVi9ejX8/f0xYcIEg21Dhw5Fw4YNER8fj9On\nT5utY9euXdi3bx86d+6Mp59+2mh74fdAUUz1gZubG6KiopCVlYXffvvNYJujoyMcHY0vUDB1ma2L\ni4tRmm7JBnOK+3764IMPoKoqFi9eDCcnJ4O2zpgxAwD0l6Xm5ORg7dq1qF69OkaNGmVQzssvv2z1\nSDMRERFRaeBlnxVQWFiYUZqbmxuaNGmC+Ph4nDp1CrVq1cKuXbsAAElJSfjjjz+M9nF0dERKSopR\nevPmzY3SdMFXx44dLc4ouWvXLiiKgu+++w4bN2402u7i4mKy3mbNmhml1ahRAwBw5coVs3Vaa8uW\nLViwYAF+++03XLp0yeD+w/T0dKvLMdVHlhw/fhxvvvkmtm3bhvT0dNy6dUu/TVEUXLx40eSkI3fr\n6NGjyMnJQatWrQyCFZ3w8HAkJyfj4MGDZme13L17NwCga9euJW5LVlYW5s6di7i4OPz1119GM28W\nvm91wIABWL9+PUJCQjBw4EB07NgRbdu2haenp8E+/fr1w8KFC9G6dWsMHDgQnTp1wqOPPgo/P78S\nt9OcXbt2wd3d3eh+QgDIzc0FAP37+9ixY8jJyUHLli3h4OBgkLfwZ5aIiIjoXmDwVwFVrVrVZLou\ncMjMzAQA/UQpCxcuLLIsU4GcqQBEV2b16tUttu/SpUsQEf0oiKk6s7OzjdI1Go1Rmm7U585JYkpi\n9erVGDhwoH7CjcDAQLi6ukJEsGDBAuTk5FhdVnGDtD///BMtW7bEtWvX0KVLF/Tp0wfu7u5QVRXf\nfvstDhw4UKz6iyMrKwtA0W3WjQrr8hWlOO8BU27duoXw8HAcOHAAzZs3xzPPPAMfHx84ODhg3759\niIuLM+iDfv36oVKlSnj77bfxzjvvYP78+XB0dES3bt3wzjvvoG7dugCA1q1bY+vWrXjzzTfx6aef\n4sMPP4SiKGjfvj3eeustkz8q3A3djwa6SWHuVPj9reuzogJRWwT7REREREVh8FcBZWRkmEzXzVip\nGxnRBVMpKSmoV6+e1eWbCgh1l6edPXvW4v4ajQaqquLatWsmL8UrK9OnT4ebmxv27Nmjnx1TZ86c\nOcUqq7jr6S1YsACZmZn44osvMGDAAINtO3fuxIEDBwzSdDNSmroUVBdQWEv3PjA1o2nhdFPBd2G6\n98CZM2eKVb9OXFwcDhw4gJiYGCxatMhg25w5cxAXF2e0T0REBCIiInD16lVs374da9aswYoVK5CS\nkoLk5GT9ZEXt27dH+/btcePGDezcuRPr16/H4sWL0a1bN6SkpJTqcg0ajQbOzs5WfRZ0n8WiJgQq\n6jUhIiIisoX7/p4/ESnTP1tISkoySrt+/Tr2798Pb29v1KpVCwD0s0fu3Lnzruts3rw5FEXBli1b\nUFBQYDZvq1atUFBQoL/stLTpLp8r7mhgamoqGjRoYBT47d27Fzdv3iy19hVVt6Io6Nmzp0H6zZs3\nsXfvXqNgUnev2t9//21U1r59+4zSzPVJcHAwnJ2d8dtvvxlcaqqTmJgIRVEszjzZsmVLAMDmzZvN\n5itKamoqABj1AXB79lRzPDw80L17dyxbtgw9e/bE8ePHTV467Orqio4dO2LhwoV4/vnncfHiRYtl\nF1erVq1w7tw5nDx50mLeevXq6fv+zkBe95kt7g8JRERERCV13wd/96OjR49i6dKlBmmzZ8/GlStX\nDCYhGTp0KNzd3TFx4kQcO3bMqJzMzEzs37/fqjr9/f0RERGBo0ePYtasWUbbC48GPf/883BwcMCo\nUaNM3kd3/vx5kyfu1tIFRqdOnSrWfgEBATh27JjBKExWVpbB8gK2EhAQABExCNxFBBMnTjQ5KqQL\ntFasWGHwI8LOnTuxatUqo/zm+sTJyQkDBgzAuXPnjNZjXL58OQ4dOgStVouaNWuaPYYWLVqgadOm\n2LJli8k2WBoR1E32cuePF998843Je0O3b99u9ENDQUEB/vnnHyiKoh9V3rlzp8mgVnf/oKurq9l2\nFZdu4pZnn33W5ChsWlqaPjB0dnZGv379cPbsWbz33nsG+ebMmVNq97ISERERWYOXfVZAXbt2xciR\nI7Fp0ybUq1cPv//+O37++WfUqVMHU6dO1efz8/PDqlWr0L9/fzRq1Ajdu3dHUFAQrl+/jhMnTiAh\nIQHR0dH48MMPrar3ww8/xMGDBzF58mRs2LAB4eHhuHXrFpKTk7Fv3z78888/AICQkBC89957iI2N\nRb169dCjRw8EBATg8uXLOH78OJKSkjBz5kwEBweX6Pjd3d3RsmVLJCYmIioqCkFBQVBVFVFRUfpR\nT1NiY2MxZswYNG3aFJGRkcjJycEPP/yAGjVqoHr16jYbqQWA4cOHY+nSpYiMjET//v2h0Wiwfft2\npKWlQavVGk360apVK4SFhWHr1q1o06YN2rVrh5MnT2LDhg3o2bMnvv32W4P8lvpk7ty5SEhIwKuv\nvorExESEhobi6NGjWL9+PapUqYKPPvrIquNYuXIltFotBg8ejKVLl6JFixa4evUq9u/fj+zsbOzd\nu7fIfZ988knUqlULc+bMQXJyMurXr4/k5GT8+OOPiIiIMDqmUaNG4fz58wgLC9MHz9u2bcOBAwfw\n5JNP4qGHHgJwO4hKSEhA+/btERgYCCcnJ+zatQtJSUlo1qwZOnbsaFDu3b7Ojz/+OCZOnIhZs2bh\noYcewmOPPYYaNWrgwoULOHLkCHbt2oUvv/xSH+zOmjULP/30E1566SXEx8fr1/n79ddf0a5dO/0a\nlkREREQ2Z6MlJErEmuaUsybfU7o15qZNmybx8fHSrl07qVy5svj6+kpUVJTRWn46hw8flujoaHnw\nwQfFyclJ/Pz8pFmzZjJx4kQ5evSoyfKLcvnyZZk4caLUq1dPnJ2dpUqVKtKmTRtZsGCBUd6dO3fK\nU089JdWqVRMnJyepVq2atGnTRmbMmCGnT5/W51u2bJmoqmqwbp2lNh07dkx69Ogh3t7eoqqqqKpq\nck28O33wwQfSoEEDcXV1lVq1asnYsWPl6tWrEhgYKLVr1zbIO3XqVKNyremjomzZskXatm0rHh4e\nUqVKFenbt68cP35coqOjTa71dvHiRRkyZIj4+vqKm5ubtG3bVn766aci+8tSn2RkZEhsbKzUqlVL\n/3oMGTLE5Np75pw5c0b+85//SGBgoDg5OYm/v7906NDBYN3Dotb5S01NlYiICPHz8xMPDw9p3769\nbN682eQxrV69Wvr16yd169YVNzc38fX1lRYtWsj7778vubm5+nw//vijDBkyROrXry8eHh7i6ekp\njRs3ljfffFOuXr1qUL9WqzVa56+otoqYfg/ofP/999KjRw+pUqWKODk5Sc2aNUWr1crbb78t//zz\nj0Hev/76S/r06SOenp6i0WikW7ducujQoSJfe6q47Pk7ioiISoctv0uU/1VQLiiKYvFXeWvy3K/i\n4+PRsWNHTJ06Fa+//npZN4eIiO5gz99RRERUOmz5XcJ7/oiIiIiIiOwAgz8iIiIiIiI7wOCPiIiI\niIjIDvCePyIiolLC7ygiIrpbvOePiIiIiIiI7gqDPyIiIiIiIjvA4I+IiIiIiMgOMPgjIiIiIiKy\nAwz+iIiIiIiI7ACDPyIiIiIiIjvA4I+IiIiIiMgOMPgjIiIiIiKyAwz+iIiIiIiI7ACDP6JStmnT\nJrRq1QoajQaqqmLs2LFm8wcGBqJ27dpWlz916lSoqoqEhIQStzEtLQ2qqmLo0KElLqM8unLlCkaO\nHImAgAA4ODhAVVVkZmZi2bJlUFUVy5cvt6qc+Ph4qKqKadOm2bjFVNq0Wi1UlV9tREREpjiWdQOI\n7iepqamIjIyEn58fRowYAXd3d7Ru3drifoqiWF2Hoij6v7tVGmWUJ+PGjcOSJUvQu3dvDB06FKqq\nwsXFBQBK1Gf3W//YC75uREREpjH4IypFW7duRW5uLt5++23069fPJnXExsZi4MCBePDBB21SfkX2\n/fffIzg4GN98841BemRkJNq2bYsHHnigjFpGREREVPYY/BGVovT0dACAv7+/zerw9fWFr6+vzcqv\nyNLT01G/fn2jdI1GA41GUwYtIiIiIio/eGNEBZKbm4uFCxeiS5cuqFGjBpydnVG9enU8/fTTOH78\nuMl9bt68iXnz5qFp06bw8PCAp6cnQkNDMXnyZOTl5Rnk3bt3L/r3749q1arBxcUFDz74ICIjI7Fj\nxw59nujoaKiqilOnThnVpbsXLTExUZ9W+N6ppKQkdO7cGZ6envDx8bHZMV29ehUeHh5o1KiRyf1v\n3LgBLy8vBAcHm+/w/8nIyEBsbCwCAgL07YuOjkZaWpo+j+4euqlTpwIAOnToAFVVi+wrU65fv44x\nY8agevXqcHFxQePGjfH1118b5TPVzwBw7do1jB07FtWrV4ebmxuaNWuGdevWWbzf7fjx44iIiIC3\ntzfc3d3RpUsXHDx40Ko266Snp2PMmDEICgqCq6srqlatCq1Wa1Rnbm4u5s6di5CQELi5ucHHxweP\nP/640bEA/77X0tLSsHDhQgQHB8PFxQWBgYGYPn06RMQoL/Dve67wPY1F9UFeXh5mzpyJ2rVrw9XV\nFQ0aNMDHH39s9lj37duHp556Cv7+/nBxcUFQUBAmTZqE69evG+Qr/N7//fff0aVLF3h4eMDLywuR\nkZE4efKkyfKt+RwCQE5ODubNm4fGjRujcuXK8PLyQpcuXUz2ZVGuXLmCV199FcHBwXB3d4eXlxfq\n16+P5557DpcuXdLnO3v2LF5//XW0bNkSfn5+cHFxwUMPPYTx48fj2rVrRuXq7rvLycnByy+/jJo1\na6Jy5cp49NFHsXv3bgDAqVOnMGDAAPj6+sLd3R2RkZE4d+6cQTmF7009ePAgunXrBk9PT3h6eqJ3\n7944duyY1cdanP46e/YsYmNjERQUpH+fNmrUCKNHjzb6f5OIiKhCEQtOnTolffr0EU9PT9FoNBIZ\nGSmnTp2ytJve4cOHpW/fvlKlShVxdXWV+vXry7vvvmsyrxXNsSrP/So9PV0cHR2lU6dOMnLkSHnl\nlVekd+/e4ujoKD4+PnLixAmD/NevX5fWrVuLoijSsGFDefHFF+Wll16S7t27i7Ozs2RmZurzfvXV\nV1KpUiVxdXWVAQMGyKRJk2To0KESFBQkY8eO1ecbMmSIqKoqJ0+eNGrflClTRFEUSUhI0Kdt27ZN\nFEWRLl26iJOTk3Tv3l1efvlleeaZZ2x6TM8995woiiK7du0yaueKFStEURSZN2+exT4/f/68BAYG\niqIo8thjj8mkSZMkMjJSVFWVKlWqSEpKioiIXLlyRaZOnSparVYURZGhQ4fKtGnTZNq0aXLlyhWz\ndQQEBEiNGjWkbdu20qBBAxk9erQ8++yzUrlyZVFVVTZv3myxn/Py8qRdu3aiKIq0bNlSJk2aJEOG\nDBEXFxd54oknRFEUWb58uT7/iRMnRFEU0Wq1UqVKFdFqtTJu3Djp3bu3KIoiPj4+cv78eYv9I3L7\nM+7v7y+KokinTp1k4sSJ8p///Edat24tTZs21efLz8+XHj16iKIoEhISIi+//LIMGzZMPDw8xMHB\nQb766iuDcocMGSKKokjfvn3Fz89PnnnmGXnhhRckICBAFEWRV199VZ93/fr1MnXqVFEURWrXrq3v\n+7i4OBERWbp0qVEfiIgMHjxYFEWR+vXry4QJEyQmJkY0Go2+ndOmTTPI/80334iTk5NoNBqJioqS\nCRMmSKdOnURRFGndurXcunVLn1f33u/Ro4e4ubnJE088IePHj9fnDwoKkps3bxqUb+3n8MaNG/rX\nu1WrVjJ27Fh57rnnpGrVquLo6CjffPONxdetoKBAWrRoIaqqyuOPPy4vv/yyvPjii9K7d2/x8PCQ\n5ORkfd4vv/xSPDw8JCIiQsaOHSsvvviitG3bVv9+y83NNSg7PDxcFEWRXr16Sb169WTMmDEyaNAg\ncXR0FE9PTzlw4IBUr15d2rdvL+PGjZPOnTuLoigSHh5uUI7ufdq+fXvx9PSUxx57TF599VXp06eP\n/jN4/Phxo7pVVTVIK05/Xbt2TQICAsTJyUkiIyNl4sSJMnr0aOnWrZu4uLjI9evXzfarPX9HERFR\n6bDld4nZkq9fvy5BQUHSqFEjiYuLk7i4OGnUqJHUrVvX4hegiMju3bvFw8NDevXqJXFxcRIfHy8f\nf/yxvPPOO6Ybw+DPrJycHElPTzdKT0hIEEdHRxk2bJhB+tixY0VRFImJiTHaJyMjQ/Ly8kTkdgDm\n5uYmXl5ecvjwYaO8Z8+e1T/WnZAXN/hTFEU+//zze3ZMu3fvLjJfeHi4ODk5SUZGhtG2O+mOd8aM\nGQbpS5YsEUVRpEOHDgbppvrAEl0wExERYXASvWXLFlEURbp162axjo8//lgURZGnnnrKIG9CQoK+\n/00Ff4qiyNy5cw32mTx5siiKIrNnz7aq/U2bNhVFUWTlypVG2wq/d3QBWLdu3SQ/P1+fnpycrH//\nZWVl6dN1fV+3bl05d+6cPv2ff/4Rb29v0Wg0BsGWiJh8TQrXXbgPdP3bqlUrycnJ0acfPnxYXFxc\njIK/CxcuiIeHh9StW9foPTtv3jxRFEXeeustfVrh9/6aNWsM8kdFRYmiKAYBb3E+h6+88oooiiJz\n5swxyHPhwgUJDAwUPz8/uXHjhlEZhR04cEAURZEXX3zRaFt2drbB/hcuXJDs7GyjfDNnzjT52uuC\nvw4dOhgEuPPnzxdFUUSj0cjLL79ssE/Pnj1FURTZs2ePPq3w+3TKlCkG+T/77DNRFEWefPJJo7rv\nDP6K019xcXGiKIosXLjQ6HivXLkiBQUFRumF2fN3FBERlY4yC/4WLFggDg4Okpqaqk87ceKEODo6\nyttvv2224Pz8fHn44YclMjLS+sYw+CuxRo0aSWBgoP55bm6ueHh4SJUqVeTq1atm9509e7YoiiJv\nvPGGxXpKGvy1aNGiGEdz290ck4hIaGioeHp6Gpy0/vnnn6IoilXvy5s3b4qLi4s88MADBsGBTkhI\niCiKYjASXtLgT1VVSUtLM7mtSpUqBmmm6tCd8OpGIgt7/PHHiwz+6tata5Q/LS1NP+Jmya+//qof\n2bVENyq6f/9+o22xsbGiKIqsWLFCn6Z7ry1btswov27bH3/8YZBenOBv6NChoiiKbNq0ySh/TEyM\nUfCnC1zWrl1rlD8/P1+qVq0qzZs316fp3vtardYof3x8vCiKIuPGjdOnWfs5zJ0bqUIAACAASURB\nVM/PFy8vLwkJCTG5/b333hNFUWTjxo1my9EFf5MmTTKbz5yLFy/qR7oL0wV/SUlJBul///23Pvi7\nMzhduXKl0eute5/6+vqaDD7r168vDg4OcvHiRYO6Cwd/xe0vXfD38ccfW9kLhvgdRUREd8uW3yVm\nJ3zZsGED2rRpgzp16ujTAgMDERYWhri4OLPrl8XHxyMlJQWffPLJ3V2XWkru9czfhW5HKlV79uzB\n3LlzsWPHDly4cAG5ubn6bc7OzvrHKSkpuHbtGtq3bw93d3ezZeruwenatattGg2gefPmRW6zxTEB\nQExMDJ5//nmsXbsWUVFRAIAlS5YAAIYNG2Zx/6NHjyInJwetWrWCk5OT0fbw8HAkJyfj4MGDdz3z\nppeXFwICAozSa9asiV27dlnc/8CBA/D09DQ52UmbNm3www8/mNyvSZMmRmk1atQAcPt+MEuK8945\ncOAANBoNGjdubLQtPDwcH3zwgcl7DZs1a2aUVrNmTavbaK49iqLg0UcfNdoWFhZm9H+X7nVISkrC\nH3/8YbSPo6MjUlJSjNJNtd9UH1vbl0ePHkVmZiYCAgL095gW9ueffwK4/Xnp0aNHkeU0bNgQISEh\nmD17Nvbv348nnngC7du3R8OGDU3mX7t2LRYvXoz9+/fjypUrKCgo0G/TTXRUmKIoRq+1brbVhx56\nSL8Eh45ukqSzZ88alRUaGgpXV1ej9LZt2+LYsWM4dOgQwsPDTba7uP2l1WrxwAMP4D//+Q9+/vln\ndOvWDe3atUNQUJDJ8omIiCoSs8FfcnIyIiIijNIbNGiAdevWmS04KSkJwO3JNVq3bo29e/fC29sb\nAwYMwJw5c4y++G3NVsHYvZSUlIROnTrB0dERjz32GIKCglC5cmUoioKlS5caTCySmZkJAKhevbrF\ncouTt6SKmv3SVscEAE8//TTGjx+Pzz77DFFRUcjPz8fy5ctRs2ZNdOvWzeL+WVlZZtuuO5HV5bsb\nnp6eJtMdHR0NTrKLcvXqVdStW9fktqpVqxa5n6kZMB0db/+3kJ+fb7He4rwmWVlZRbbRXF/ebRuL\nkpmZiUqVKpks39RrrpsAZeHChUWWaWp9OWvbb21f6tpx8ODBIifmURQF2dnZZstxcHDAtm3bMGXK\nFHz99df4/vvvAdwOTMePH4/Ro0fr886bNw8vv/wy/P390aNHD9SoUQMuLi4QEUybNg05OTkm67jz\nRxoHBwcA5vuk8I8/OkW9h3Wvk7nPYHH7S6PRYOfOnXj99dfx3XffYe3atQCAevXqYcqUKRg4cGCR\ndREREZV3ZoO/y5cvw9vb2yjdx8cHly9fNluw7tfb/v37Y9SoUZg7dy52796N119/HadPnzZah4ss\nmzVrFvLy8pCQkGC0cPiXX35p8NzLywuA6V/R76TLe+bMGYsnnroZFU3NeKc7eTWlqEWXbXVMAODh\n4YH+/ftjyZIlOH78OFJSUpCeno7XXnvNqkWgdSeo58+fN7ldl14elhDw8PDAhQsXTG7LyMiwWb2F\n3zuWaDSaIttSFn3p6emJEydOICsry6heU6+5Lk9KSgrq1atX6u2x9nOoa8eAAQPwxRdf3FWdvr6+\neP/99/H+++8jOTkZP//8MxYuXIgXXngBGo0G0dHR+hlRa9SogQMHDuhn6gVu99O0adPuqg3WsPS+\nKerHE6Bk/RUQEIDly5ejoKAA+/fvxw8//IB3330XTz/9NB544AF06NChmEdARERUPthsqQfdaMXg\nwYMxdepUtG/fHi+99BKmTJmC9evXm7w8isxLTU2Fr6+vUZB0/vx5pKamGqTppm7/9ddfcfXqVbPl\ntmzZEgCwefNmi23Q/Rjw999/G23bt2+fxf3vZKtj0omJiQFw+3LPzz77DIqi4JlnnrFq3+DgYDg7\nO+O3337DrVu3jLYnJiaavLStLDRp0gRXrlzB0aNHjbbt3LnTZvUW570TGhqKzMxMHDhwwGhbQkIC\nANOXodpKkyZNICLYvn270TbdlQuFtWrVCoDt+tPavmzQoAE8PDywe/duq0aFrdWwYUOMGTNG/8Pc\nd999BwD4559/cPXqVbRp08Yg8ANgtPyErezbt89oJFNE8Msvv8DBwaHIZV2Au+svVVXRtGlTTJo0\nSb8EyMaNG4t/AEREROWE2eDP29vb5AjfpUuXjE4C7qRbhLpLly4G6brnpk4AgdtrmOn+4uPjzdZh\nbwICAnDx4kWDwPnWrVuIjY01GolzcHBATEwMLl26hHHjxhmsiQbc/iVdd8lZVFQU3NzcMG/ePBw+\nfNggn4gYrL2lO0FdtmyZQb5169bpg6HycEyF2/vII4/gs88+w6ZNm9CxY0cEBgZa1TYnJycMGDAA\n586dw/z58w22LV++HIcOHYJWq9Xff1aWdJeivf766wbpSUlJRd7vVxpatGiBpk2bYsuWLVi1apXR\n9sIjgrr7LidOnGhwEn7kyBF8+umn8PLyQq9evWzW1jsNGjQIADB9+nSDyxYPHz6MFStWGOUfOnQo\n3N3dMXHiRJPry2VmZmL//v0lbo+1n0MHBweMGDECqampRn2ps2vXLty4ccNsfSdPnjS51qCuHt2l\n+VWrVoWLiwv27NmDmzdv6vOlp6dj0qRJxTvIErp06RLmzJljkLZkyRIcO3YM3bt3N3mFik5x++vI\nkSMmRxrv7BciIqLSEh8fbxAD2ZLZyz4bNmxocmKDw4cPo0GDBmYLDgkJKVGDbH3AFVlsbCx++ukn\nhIWFoV+/fnB0dMTPP/+M/Px8NG7c2CignjFjBnbs2IFPPvkEO3bsQNeuXaGqKo4dO4bNmzcjIyMD\nGo0G/v7+WLJkCQYNGoRmzZqhd+/eqF27NjIyMpCYmIgePXrgnXfeAQD06tULdevWxbJly3D69Gk0\nadIER44cwbZt29C9e3f897//LRfHVFhMTAxiY2MBWDfRS2Fz585FQkICXn31VSQmJiI0NBRHjx7F\n+vXrUaVKFXz00UfFKq8k7gxyTXn22WexYsUKrF27FmlpaejYsSPS09OxZs0a9OjRA5s2bdJfslva\nVq5cCa1Wi8GDB2Pp0qVo0aIFrl69iv379yM7Oxt79+4FcDu4WbduHTZt2oQmTZrg8ccfx+XLl/HV\nV18hNzcXy5Yts2oin9LSoUMHDB48GJ9//jkaN26MJ598EllZWfjqq6/QpUsXbNq0ySC/n58fVq1a\nhf79+6NRo0bo3r07goKCcP36dZw4cQIJCQmIjo7Ghx9+WKL2FOdzOH36dPz++++YN28eNmzYgEcf\nfRQ+Pj74+++/sWfPHhw7dgznzp0zOUmKzr59+9CnTx+0bt0awcHB8Pf3x6lTp7B+/Xo4Oztj1KhR\nAG6Pfo0cORLvvPMOQkND0b17d1y6dAmbNm2CVqstcqF1a9631mrXrh3effdd/Prrr2jWrBmOHj2K\nb7/9Fr6+vvo+MVd3cfrrxx9/xIQJE/STvPj4+ODYsWPYuHEjvL29i/1/CBERkSVarRZarVb/3Ka3\nVJibCnTBggXi6Ogof/31lz7txIkTUqlSJYtLPVy8eFFcXFwkNjbWIP3NN98URVEMlo/QsdAcq/Pc\nz9asWSOhoaHi5uYm1apVk6FDh8r58+dFq9UarW0lcntx41mzZkmjRo3E1dVVvLy8JDQ0VKZMmWK0\nMPPu3bulT58+4ufnJ87OzlKrVi3p27ev/PLLLwb50tLSJCIiQjQajbi7u0uXLl1kz549MnXqVFFV\n1eRSD3culn2vjknk9tpcqqqKr6+vySUbLMnIyJDY2FipVauWODk5SbVq1WTIkCEml2Yw1QeWBAYG\nSu3atU1uM9UHRdVx9epVGTNmjFSrVk1cXV2ladOmsm7dOnnrrbdEURRZv369Pq9uCv07p+jXKWrJ\nhKKcOXNG/vOf/0hgYKA4OTmJv7+/dOjQwWhtx9zcXJkzZ440bNhQXFxcxNvbW7p16yaJiYlGZUZH\nR4uqqiaXFSmqD4pq97Jly0RVVaNF3vPy8mTGjBkSGBgozs7O0qBBA1m8eLF+KQZT79vDhw9LdHS0\nPPjgg+Lk5CR+fn7SrFkzmThxohw9elSfz9x731z/W/s5zMvLkw8++EBat24tGo1GXF1dpW7duhIR\nESGff/65fs3Lovz999/yyiuvSOvWraVq1ari4uIiderUkUGDBsmhQ4cM8t66dUumT58uQUFB4uLi\nIkFBQTJt2jS5deuWyT4v6rMrUvRrZKq/CvfToUOHpFu3bqLRaMTT01N69eolx44dMyqnqLqt7a8j\nR47ICy+8IE2bNhVfX19xdXWVhx56SEaOHGnyM38ne/+OIiKiu2fL7xLlfxWYlJ2djcaNG8PV1RUz\nZ84EAEyePBnXr1/HwYMH4ebmBuD25UN169bFlClTMHnyZP3+06dPx4wZMzBhwgR06NABv//+O6ZP\nn44BAwbop9wvTFEUi78WW5OHqLDExERotVqMHj0aCxYsKOvm3HODBw/GqlWrcPjwYQQHB5d1c4is\nlpaWhjp16iA6Otrkd0Z5xO8oIiK6W7b8LjF72aebmxu2bt2KsWPHYvDgwRARdO7cGQsWLNAHfsDt\nS2wKCgqMGvn666/Dw8MDH374Id566y1Ur14dEyZMMAgQiWxt/vz5UBQFw4cPL+um2NS5c+f0Sybo\nJCUl4auvvkK9evUY+BERERHZObMjf/caR/6otJw+fRqrVq3CoUOH8OWXX+Kpp57C6tWry7pZNvXE\nE08gPT0dzZs3h6enJ1JSUrBp0yY4Ojriu+++s2ohdqLyhCN/RERkj8ps5I+ookpNTcWkSZOg0WjQ\nt29fLFq0qKybZHP9+/fH4sWL8c033yAzMxNeXl544oknMHHiRKOlNIiIiIjI/nDkj4iIqJTwO4qI\niO6WLb9LbLbIOxEREREREZUfDP6IiIiIiIjsAIM/IiIiIiIiO8Dgj4iIiIiIyA4w+CMiIiIiIrID\nDP6IiIiIiIjsAIM/IiIiIiIiO8Dgj4iIiIiIyA4w+CMqZZs2bUKrVq2g0WigqirGjh1bquWrqooO\nHToYpEVHR0NVVZw6dapU66ooli1bBlVVsXz58rJuChEREVG55VjWDSC6n6SmpiIyMhJ+fn4YMWIE\n3N3d0bp161KvR1EUq9LsDfuAiIiIqGgM/ohK0datW5Gbm4u3334b/fr1u6d1i8g9rY+IiIiIKhZe\n9klUitLT0wEA/v7+ZdwSIiIiIiJDDP4qkNzcXCxcuBBdunRBjRo14OzsjOrVq+Ppp5/G8ePHTe5z\n8+ZNzJs3D02bNoWHhwc8PT0RGhqKyZMnIy8vzyDv3r170b9/f1SrVg0uLi548MEHERkZiR07dujz\nmLu3bOrUqVBVFYmJifq0+Ph4qKqKadOmISkpCZ07d4anpyd8fHxsdkxXr16Fh4cHGjVqZHL/Gzdu\nwMvLC8HBweY7/H8yMjIQGxuLgIAAffuio6ORlpamz5OWlgZVVTF16lQAQIcOHaCqqlX34W3duhVD\nhw5FvXr14O7uDo1Gg7CwMKxZs8aq9pXE2rVr0a5dO/j5+cHV1RU1a9ZEjx498PPPPxvkW7JkCXr2\n7ImAgAC4uLjAz88PvXv3xp49e4zKLHzfXVxcHJo3b47KlSsjMDAQb7/9NgCgoKAAs2fPRlBQEFxd\nXRESEoKNGzcalaXVaqGqKm7evImXXnoJNWvWhKurK5o0aYKVK1cW61i3bduG7t27w9fXF66urmjY\nsCHmzJmD/Px8g3wigsWLF6N58+bw8fFB5cqVERAQgL59+2Lv3r3FqpOIiIioPOJlnxXIxYsX8dJL\nLyE8PBy9evWCp6cnUlJSsGbNGvzwww/Ys2cPAgMD9fmzs7PRqVMn7Nq1Cw0aNEBMTAwURcGRI0cw\nb948jB8/HhqNBgCwevVqDB48GI6OjujVqxfq1KmD9PR0bN++HV9//TXCwsL05ZbkvqodO3bgzTff\nROfOnTFy5EhcuHDBpsc0cOBAfPrpp/jtt9/QsmVLg7asW7cOWVlZeO211yy2OyMjA61atcLJkyfR\ntWtXDBo0CCkpKfj888+xadMmJCUloX79+vD29saUKVMQHx+PhIQEREdH69vt6elpto558+bhxIkT\naNOmDWrUqIGLFy9iw4YNGDBgANLT0zFmzJjidbYFH3zwAUaNGoWgoCAMHDgQHh4eOHPmDH755Rds\n3rwZnTt31ueNjY1F06ZN0a1bN/j6+uLEiROIi4vDjz/+iPj4eLRq1cqo/G+++QZbtmxBZGQk2rdv\nj6+//hrjxo2Dq6sr9u7dix9++AFPPvkk8vPzsXLlSkRGRuLw4cMICgoyKqtv375ITk7GgAEDkJOT\ngzVr1iAqKgr//PMPXnjhBYvH+v7772P06NGoWrUqIiIi4O3tje3bt2PixIn47bff8PXXX+vzTpgw\nAfPnz0fjxo0RHR0NZ2dnnD59GvHx8fj111/RtGnTEvY4ERERUTkh5Yg1zSlukzEVZfpXmnJyciQ9\nPd0oPSEhQRwdHWXYsGEG6WPHjhVFUSQmJsZon4yMDMnLyxMRkfT0dHFzcxMvLy85fPiwUd6zZ8/q\nHw8ZMkQURZGTJ08a5ZsyZYooiiIJCQn6tG3btomiKKIoinz++ef37Jh2795dZL7w8HBxcnKSjIwM\no2130h3vjBkzDNKXLFkiiqJIhw4dDNJN9YElaWlpRmnXr1+Xxo0bi6enp2RnZxtsM1WvudflTqGh\noVKzZk25ceOG0baLFy9abNuRI0fEw8NDOnfubJC+dOlSURRFXFxcZP/+/fr0M2fOiIuLi2g0GmnQ\noIFcunRJv+3rr78WRVEkNjbWoKzw8HBRFEVCQkLk+vXr+vSzZ8+Kv7+/uLi4GLwvdXUvX75cn/bH\nH3+Io6OjtGnTRrKysgzKj42NFUVRZN26dfo0b29vadGihRQUFBgd8+XLl43SiEwpZ1+rRERUAdny\nu4SXfVYgTk5OeOCBB4zS27dvj4cfftjgkr28vDx8+umn8PX1xfz584328fPzg4ODAwBg+fLluHHj\nBsaPH4+HH37YKG+1atXuuu3NmzfHoEGDjNJtdUzNmzdHkyZNsHr1aty4cUOf5/jx40hMTMQTTzwB\nPz8/s23OycnB6tWr4e/vjwkTJhhsGzp0KBo2bIj4+HicPn3a/MFbEBAQYJTm5uaGqKgoZGVlYffu\n3XdV/p0URUGlSpWgqsYff93luObaFhwcDK1Wi+3btxtdOgwAgwYNQuPGjfXPq1evjrCwMFy9ehWT\nJk2Ct7e3flvv3r1RqVIl/PHHHybb+uqrr8LNzU3/vFq1ahgzZoz+tTFn8eLFyM/Px8KFC+Hh4WGw\n7Y033oCiKPjqq6/0aYqiwNnZ2eTItpeXl9m6iIiIiCoCXvZZwezZswdz587Fjh07cOHCBeTm5uq3\nOTs76x+npKTg2rVraN++Pdzd3c2WqQsuunbtaptG43YwVhRbHBMAxMTE4Pnnn8fatWsRFRUF4PY9\nbAAwbNgwi/sfPXoUOTk5aNWqFZycnIy2h4eHIzk5GQcPHsSDDz5osbyiZGVlYe7cuYiLi8Nff/1l\nEKwC/04iU1r69++PV155BSEhIRgwYAC0Wi1at25tEGTpHD9+HG+++Sa2bduG9PR03Lp1S79NURRc\nvHjRaHKbwoGfju4HhDu3qaoKPz8/nD171mRb27VrZ5SmuwT54MGDZo9z165dUBQF3333ncn7Cl1c\nXJCSkqJ/3r9/fyxatAhNmzZF3759odVq0bx5c5OvPREREVFFxOCvAklKSkKnTp3g6OiIxx57DEFB\nQahcuTIURcHSpUsNJhbJzMwEcHvUxZLi5C2poma/tNUxAcDTTz+N8ePH47PPPkNUVBTy8/OxfPly\n1KxZE926dbO4f1ZWltm260YsdflK4tatWwgPD8eBAwfQvHlzPPPMM/Dx8YGDgwP27duHuLg45OTk\nlLh8UyZMmAAfHx8sWrQIM2fOxMyZM+Hs7Iy+ffti/vz5qFq1KgDgzz//RMuWLXHt2jV06dIFffr0\ngbu7O1RVxbfffosDBw6YbJvuPtLCdCOyprY5OjoaBPw6iqLo21KY7vXQvR+KcunSJYgIZsyYYXK7\noijIzs7WP1+4cCFq166NpUuX6u8H9fDwQFRUFGbPno3KlSubrY+IiIiovGPwV4HMmjULeXl5SEhI\nMFo4/MsvvzR4rrtMragRFVN5z5w5YzGw0l0qaOpyP3Mn40VNEmOrYwJun7j3798fS5YswfHjx5GS\nkoL09HS89tprVk1aowtUzp8/b3K7Lt1UQGOtuLg4HDhwADExMVi0aJHBtjlz5iAuLq7EZZszbNgw\nDBs2DP/88w8SEhKwYsUKrFq1Sj/BCQAsWLAAmZmZ+OKLLzBgwACD/Xfu3IkDBw7YpG06IoKMjAzU\nqFHDIF3X75Ym0tFoNFBVFdeuXYOLi4vF+hwdHTF+/HiMHz8eZ86cwbZt2/DJJ5/ggw8+wNWrV7Fs\n2bISHwsRERFReXDfB38y5f5Z+Do1NRW+vr5GQdL58+eRmppqkBYcHAx3d3f8+uuv+qUPitKyZUt8\n/fXX2Lx5M1q0aGG2Dbr7tf7++2/UqVPHYNu+ffuKczgAbHdMOjExMViyZAmWLFmCI0eOQFEUPPPM\nM1a1LTg4GM7Ozvjtt99w69Yto8v/EhMToSiKycscraU7xp49exptK7zEhq1UqVIFffr0QZ8+fRAa\nGorExER936ampkJRFKO23bx5E3v37i3RrK/FlZiYiIEDBxqkJSUlATB9eWlhrVq1wr59+7Br1y6E\nh4cXq94aNWpg0KBB6N+/P2rUqIHvvvuueA0nIiIiKoc44UsFEhAQgIsXLxrcp3Tr1i3ExsYajcQ5\nODggJiYGly5dwrhx43B74qB/ZWRk6Nc5i4qKgpubG+bNm4fDhw8b5BMRnDt3Tv9ct2zCnaMg69at\n0wdD5eGYCrf3kUcewWeffYZNmzahY8eOBktHmOPk5IQBAwbg3LlzRhPMLF++HIcOHYJWq0XNmjWL\nccSGdBOq6AIanW+++cbkfWqlISEhwSjtxo0byMzMRKVKlfSXaAYEBEBEDNomIpg4caJ+qQ5be+ON\nN3D9+nX98/T0dLz77rtwcXFBv379zO77/PPPw8HBAaNGjTJ53+T58+f177tbt25h586dRnmysrJw\n48YNq0YOiYiIiMq7+37k734SGxuLn376CWFhYejXrx8cHR3x888/Iz8/H40bNza6DG/GjBnYsWMH\nPvnkE+zYsQNdu3aFqqo4duwYNm/ejIyMDGg0Gvj7+2PJkiUYNGgQmjVrht69e6N27drIyMhAYmIi\nevTogXfeeQcA0KtXL9StWxfLli3D6dOn0aRJExw5ckS/kPZ///vfcnFMhcXExCA2NhaAdRO9FDZ3\n7lwkJCTg1VdfRWJiIkJDQ3H06FGsX78eVapUwUcffVSs8u705JNPolatWpgzZw6Sk5NRv359JCcn\n48cff0RERAS+/fbbuyrflF69esHb2xutWrVCrVq1cPPmTXz//fdIS0vDqFGj9BO/DB8+HEuXLkVk\nZCT69+8PjUaD7du3Iy0tDVqtVn95qC3VqVMHISEh6NOnj36Gz4sXL+Ltt9+2OAttSEgI3nvvPcTG\nxqJevXro0aMHAgICcPnyZRw/fhxJSUmYOXMmgoODkZ2djbCwMAQHByM0NBQPPvggMjMzsWHDBmRn\nZ2P69Ok2P1YiIiIim7PZIhIlYE1zylmT77k1a9ZIaGiouLm5SbVq1WTo0KFy/vx50Wq1oqqqUf4b\nN27IrFmzpFGjRuLq6ipeXl4SGhoqU6ZMkdzcXIO8u3fvlj59+oifn584OztLrVq1pG/fvvLLL78Y\n5EtLS5OIiAjRaDTi7u4uXbp0kT179sjUqVNFVVWT6/xNmzatTI5JROTKlSuiqqr4+vpKTk6OxT6+\nU0ZGhsTGxkqtWrXEyclJqlWrJkOGDDG5Bp6pPrAkNTVVIiIixM/PTzw8PKR9+/ayefNmWbZsmaiq\narB2nYjpdf6io6NFVVWr1vn76KOPpGfPnhIYGCguLi5StWpVadeunaxcudIo75YtW6Rt27bi4eEh\nVapUkb59+8rx48dN1ldUey21LzAwUGrXrm2QFh4eLqqqys2bN+Wll16SmjVrirOzszzyyCMm14s0\nV/fOnTvlqaeekmrVqulfvzZt2siMGTPk9OnTIiKSm5src+bMka5du+rrql69unTt2lU2btxosU+J\ndOz9O4qIiO6eLb9LlP9VUC4oimJ0KV9J8hAVlpiYCK1Wi9GjR2PBggVl3Ryygm4dwTsv4yUq7/gd\nRUREd8uW3yW854/ue/Pnz4eiKBg+fHhZN4WIiIiIqMzwnj+6L50+fRqrVq3CoUOH8N133+Gpp57C\nww8/XNbNomLg6AkRERFR6WLwR/el1NRUTJo0CRqNBn379jVaQ4/KN0VR7slSEkRERET2hPf8ERER\nlRJ+RxER0d3iPX9ERERERER0Vxj8ERERERER2QEGf0RERERERHaAwR8REREREZEd4GyfRERERERk\nU7r5S0TM/93LPOWxTbbG4I+IiMiOlNcTHrbp/m53eWxTRW13eWyTpTx3UhTzf/cyz72uz9o8tsLg\nj4iIqBQ9+SRQUADk59/+924fFyefpROxwsrjCU95bFNFbbct61PV8temitqX91ObrM1Dltmyrypc\n8Oft7Q0u/kxEROWRh4c3YmJunxyrKuDgUDqPLeVTFMMTcoAnYEREZKzCLfJO9k2k+L+Gl+QXdJZb\n+mUBpX/Ca6sTaZb772MGC0RERPeWLWOiCjfyV1pEys/JM8u1vlyR2yeiFfVE2tJjR0fAyal8t/Fu\ngggiIiIiKjvlLvgLC7s3AQVQsU+krQkiKlJ7rS2XoxBERERERCVT7i77TEqSexJQMIAgIiIiIqLy\nxpaXfZa74K8cNYeIiIiIiOiesmVMpNqkVCIiIiIiIipXGPwRERERERHZPNI5EAAAIABJREFUAQZ/\nREREREREdsCq4O/06dPo27cvvLy84OnpiT59+uD06dPWVaCqJv8OHjx4Vw0nIiIiIiIi61mc8CU7\nOxuNGzeGq6srZs6cCQB47bXXkJ2djYMHD8LNzc1sBaqqYujQoRg+fLhBeqNGjeDq6mrYGE74QkRE\nREREdqxMF3n/5JNPcOLECRw7dgx16tQBADzyyCN46KGHsHjxYowdO9ZiJTVq1EDLli3vvrVERERE\nRERUIhYv+9ywYQPatGmjD/wAIDAwEGFhYYiLi7OqEo7mERERERERlS2LwV9ycjJCQkKM0hs0aIDD\nhw9bVclHH30EFxcXVK5cGZ06dUJSUlLxW0pEREREREQlZjH4u3z5Mry9vY3SfXx8cPnyZYsVDBo0\nCB999BG2bNmCjz/+GBcvXkTHjh2RkJBQshYTERERERFRsVm85+9urVixQv84LCwMvXr1QkhICCZP\nnozExERbV09ERERERESwIvjz9vY2OcJ36dIl+Pj4FLtCd3d3dO/eHUuXLjW5ferUqfrHWq0WWq22\n2HUQERERERFVBPHx8YiPj78ndVlc6qFTp064desWtm/fbpCu1WqhKAq2bdtW7Eqff/55LFu2DNnZ\n2YaN4VIPRERERERkx2wZE1m8569nz5749ddfceLECX1aWloafvnlF/Ts2bPYFWZlZWHjxo1c+oGI\niIiIiOgeKtEi75MnT8b169cNFnk/efIk6tatiylTpmDy5MkAgLfeegupqanQarXw9/fHyZMn8dZb\nb+HPP//Eli1bEBYWZtgYjvwREREREZEdK9NF3t3c3LB161aMHTsWgwcPhoigc+fOWLBggT7wA26v\n5VdQUGDQ0ODgYKxfvx7r1q1DZmYmNBoNHn30USxduhTNmze3yQERERERERGRMYsjf/cSR/6IiIiI\niMielek9f0RERERERFTxMfgjIiIiIiKyAwz+iIiIiIiI7ACDPyIiIiIiIjvA4I+IiIiIiMgOMPgj\nIiIiIiKyAwz+iIiIiIiI7ACDPyIiIiIiIjvA4I+IiIiIiMgOMPgjIiIiIiKyAwz+iIiIiIiI7ACD\nPyIiIiIiIjvA4I+IiIiIiMgOMPgjIiIiIiKyAwz+iIiIiIiI7ACDPyIiIiIiIjvA4I+IiIiIiMgO\nMPgjIiIiIiKyAwz+iIiIiIiI7ACDPyIiIiIiIjvA4I+IiIiIiMgOMPgjIiIiIiKyA45l3QAiIiIi\nIqL7kghQUADk5gJ5ebf/dI9NpeXl2bQ5DP6IiIiIiOjeEvk32LEUEBUncCqP5QBApUq3/xwdb//p\nHptKsyFFRMSmNRSDoigoR80hIiIiIrq3Cgruj4DHUlp+PuDgYBz4WAqMTKWV930cHIr1FrBlTMTg\nj4iIiIjKt+JeOldeAx5rthcUlI+Axdb7ODgAKqcfMcWWMREv+yQiIiKqqApfOleRAx5r0hSlbAIW\nV9d7Gyw5ONw+ViIb4MgfERER3X+Ke+lceQuSrC2n8KVz5XF0pzT34SgR2QmO/BEREdHdu/PSuYoa\n8FiTJlI2AUvlyvc2MHJ05CgREVmNwR8Rkb0Q+ffkX/dv4b870yw9r4h5ynv7SnoMBQW3R4CsCZJU\n9d6P5OgunStuPXdTt6oyKCIiugODP6KKpPDJe1mfgJb1yW5Fy1Me2idy+2RYUW6fGOv+7nxuKq28\n5ymtcnUTEFTEY7A2cOKlc0REdovB371258l7eT5RLK912/MxAP+e6JX3k/F7ecJe+HnhX/wr6jHY\nKo8u8CMiIiK7VP6Cv2efLT8n2rbIA1T8k0lb1134l/eKegy2ysOTdyIiIiIqofIX/LVtW35OtG0V\ndBAREREREd1jXOqBiIiIiIionLBlTKTapFQiIiIiIiIqVxj8ERERERER2QEGf0RERERERHaAwR8R\nEREREZEdYPBHRERERERkBxj8ERERERER2QEGf0RERERERHaAwR8REREREZEdYPBHRERERERkBxj8\nERERERER2QEGf0RERERERHbAYvB3+vRp9O3bF15eXvD09ESfPn1w+vTpYlc0e/ZsqKqKdu3alaih\nREREREREVHKKiEhRG7Ozs9G4cWO4urpi5syZAIDXXnsN2dnZOHjwINzc3Kyq5K+//sIjjzwCd3d3\n1KtXD4mJiaYboygw0xwiIiIiIqL7mi1jIkdzGz/55BOcOHECx44dQ506dQAAjzzyCB566CEsXrwY\nY8eOtaqSkSNHYvDgwUhJSUFeXt7dt5qIiIiIiIiKxexlnxs2bECbNm30gR8ABAYGIiwsDHFxcVZV\n8MUXX2D//v2YNWsWRASKotxdi4mIiIiIiKjYzAZ/ycnJCAkJMUpv0KABDh8+bLHwy5cvY+zYsZg7\ndy68vLxK3koiIiIiIiK6K2aDv8uXL8Pb29so3cfHB5cvX7ZY+Pjx4xEcHIwhQ4aUvIVERERERER0\n18ze83c3tm/fjs8//xz79u2zVRVERERERERkJbPBn7e3t8kRvkuXLsHHx8dswcOHD8ezzz6LGjVq\n4MqVKwCAvLw8FBQUIDMzE66urnBycjLab+rUqfrHWq0WWq3WisMgIiIiIiKqeOLj4xEfH39P6jK7\n1EOnTp1w69YtbN++3SBdq9VCURRs27atyIJV1fwSggsWLMDo0aMNG8OlHoiIiIiIyI6V2VIPPXv2\nxLhx43DixAnUrl0bAJCWloZffvkFc+bMMVvwtm3bDGb2FBG88MILKCgowHvvvYe6deuWQvOJiIiI\niIjIGsVe5H3y5Mm4fv26wSLvJ0+eRN26dTFlyhRMnjy5yMq0Wi3y8/ONRhL1jeHIHxERERER2TFb\nxkRmr810c3PD1q1bUa9ePQwePBiDBg1C3bp1sXXrVn3gB9we1SsoKLDYSEVRuM4fERERERFRGTA7\n8nevceSPiIiIiIjsWZmN/BEREREREdH9gcEfERERERGRHWDwR0REREREZAcY/BEREREREdkBBn9E\nRERERER2gMEfERERERGRHWDwR0REREREZAcY/BEREREREdkBBn9ERERERER2gMEfERERERGRHWDw\nR0REREREZAcY/BEREREREZUDWVlZNi3f0aalExERERER3UdEClBQcAP5+dkG/xYUZCM///a/xd1+\n+PA/+Prrs/jhhys2bTuDPyIiIiIiqtBsEZAZbv/3sUhOqbT55k0gPh7YsAE4cqRUirSIwR8RERER\nEZW6ihiQ3QunTgHffQf88ANw7dq9rZvBHxERERGRnWBAVjZyc4GkpNtB3759ZdcOBn9ERERERGXI\ndgGZcV4GZPfWuXPAxo3Af/8LXL5c1q1h8EdEREREZIQBGZmjqq5QVVc4OLj977EbHBxu/yvigl9+\nycTatWlITDwDEevKbNw4GM899zRiYyfbrN2KiLXNsT1FUVCOmkNERERE5QgDMjLHXEBWON367UXl\ndYGiKEb1nzt3Dp999hk+/vhjnDp1yqo2u7q6YsCAARg5ciSaN28ORVFsGhNx5I+IiIiISowBGZlT\nWgGZ5bymAzJbExFs27YNixYtwrfffou8vDyr9gsODsaIESMQFRUFb29vG7fyXwz+iIiIiO4zpR2Q\nmcvLgKziKXlAVtzgrWwCsnvh0qVLWL58ORYtWoRjx45ZtU+lSpUQGRmJESNGIDw8vEz6ptwFf/Hx\nKhTFAYADFKWox7efm37sAEA1+djctvJVX1nUrd6Ll5eIiMhuMSAjc6wNyEp2+aJ9BGS2JiLYtWsX\nFi1ahNWrV+PmzZtW7RcQEIDhw4fjmWeegb+/v41baV65C/4AgUgegDyrb46k0lLeAuv7Lag3VZ/K\n/4CJiMoQAzIyx3JAdjf3kxXe7swf4suxa9euYdWqVVi0aBH2799v1T6qqqJHjx4YMWIEHnvsMTg4\nONi4ldYph8EflZ18iOQz6L7n1DIKPO09qGfQTVRelV5AZjkvA7KKxzggK80JPhiQ0b8OHjyIRYsW\nYeXKlbh69apV+zzwwAMYNmwYnnvuOdSqVcvGLSw+Bn9EZa4AIgXgaPe9pqAsA+v7L6i3tj6eSFVU\nDMjIHF0QdvcBFwMyKls3b97E2rVrsWjRIvzyyy9W79epUyeMGDECvXr1QqVKlWzYwrvD4I+I7JSA\no91lxV4C3XtZt4qCghwGZGRAVV1KKeBiQEb3vz///BOLFy/G0qVLcenSJav28fb2xtChQxETE4P6\n9evbuIWlo9yt81dQkPe/k7EC/HtiVvhxPm6PlBg/Nrft9v4FRTxmfURERGR7tg3ICj92YUBGZEFu\nbi42bNiARYsW4eeff7Z6v9atW2PkyJF46qmn4OrqWurtsqt1/v79NZPupX+DxfszuC2v9d0efSIi\norJUugGZubwMyIjKg9OnT+OTTz7Bp59+ivT0dKv2cXd3x6BBgzB8+HA0adLExi20nXIX/FHZ4HIP\nZUNE7uvgtuzqM183R7uJyr/SCcisycuAjMgeFBQUYPPmzfjoo4+wceNGFBRYdy7wyCOPYOTIkXj6\n6afh4eFh41baHoM/ojKkKAoUxRH8KN5bty+lKLBR4Hm/B9a8xNyelSQgK1nwxoCMiEpHRkYGlixZ\ngo8//hgnTpywah9nZ2f0798fI0aMQOvWrXE/zRDOM04isju3/xPnJeZl4f/bu/OoqK48D+DfKqBY\nBBEUFVzBHTeIoiibRrMY2yRGs5nEhQi8mnQ77Ul6pqcnJnZ3Oj3JnM6YdDr1gGiUaGtiYhITTWvH\nICC4gbvRuIHiigQQBIVa7vyR+NoKAg9rgaK+n3M8h67Uve/3XmNZ3/q9upe3mDvueBqNt40dMAYy\nIuoYhBDIy8uDwWDAp59+CqPRqGrcoEGDIEkS5s2bh65duzq4yrbB8EdERE7DW8yJiMhRqqqqkJWV\nBVmWcezYMVVjPD098eijj0KSJEyePBlabcf+N4rhj4iIiIiIXFZhYSEMBgPWrl2LGzduqBrTp08f\npKam4vnnn0doaKiDK2w/GP6IiIiIiMil1NbWYt26dTAYDCgqKlI1RqPRYNq0aZAkCdOmTYOnp/tF\nIfc7YyIiIiIicklHjx6FLMvIyspCdXW1qjHdu3fH888/j5SUFISHhzu4wvaN4Y+IiIiIiNqt+vp6\nbNiwAQaDAXl5earHJSUlQa/XY+bMmdDpdA6s0HUw/BERERERUbtz5swZZGRkYMWKFbh69aqqMYGB\ngZg/fz7S0tIwbNgwB1foehj+iIiIiIioXTCZTNi0aRMMBgO2bNmielxMTAz0ej2efPJJ+Pn5ObBC\n18bwR0REREREberChQtYvnw5MjMzcf78eVVj/Pz8MGfOHEiShDFjxji4wo6B4Y+IiIiIiJzOYrFg\n27ZtMBgM2LhxI8xms6pxw4cPhyRJeO655xAYGOjgKjsWhj8iIiIiInKa8vJyrFy5Eunp6Th16pSq\nMTqdDrNnz4Zer0dcXBw0Go2Dq+yYGP6IiIiIiMihhBAoKCiALMtYv3496uvrVY2LiIiAJEmYP38+\nQkJCHFxlx8fwR0REREREDlFdXY3Vq1dDlmUcPnxY1RitVouHH34Yer0eU6dOhVardXCV7oPhj4iI\niIiI7Gr//v2QZRlr1qxBbW2tqjFhYWFISUnBwoUL0bt3bwdX6J4Y/oiIiIiIyGZ1dXX4+OOPIcsy\ndu/erXrc/fffD0mSMGPGDHh6Mp44Eq8uERERERHdtePHjyM9PR0rV65EVVWVqjFdu3ZFcnIyUlNT\nMXDgQAdXSLeouoG2tLQUs2fPRpcuXRAYGIhZs2ahtLS0xXFnz57FI488gv79+8PPzw8hISGYNGkS\nvv76a5sLJyIiIiKittHQ0ICPP/4Y9957L4YNG4Zly5apCn7x8fFYvXo1zp8/jzfffJPBz8la7PzV\n1dXh3nvvha+vL7KysgAAL7/8MiZPnoxDhw7Bz8+vybG1tbUICQnBn/70J/Tu3RvXrl1DZmYmpk+f\njg0bNuDRRx+135kQEREREZFDlZSUIDMzE8uXL8eVK1dUjQkICMDcuXMhSRJGjBjh4AqpORohhGju\nCW+//TZefPFFnDhxAhEREQB+/D990KBBePPNN7F48eJWHdBsNiM8PBzR0dH44osvrIvRaNBCOURE\nRERE5ERmsxlff/01ZFnG5s2bVb9fj46Ohl6vx9NPPw1/f38HV9lxODITtRj+pkyZgoaGBuTl5Vk9\nPmnSJADA9u3bW33QESNGYPDgwdiwYYN1MQx/RERERETtwuXLl7F8+XJkZGTg3Llzqsb4+vriqaee\ngl6vx9ixY7kZ+11wZCZq8bbPo0ePYubMmY0ej4yMxCeffKLqIEIImM1mlJeXIyMjAydPnsTbb799\nx+dWVlYiKChI1bxERERERGQ/QghkZ2dDlmV89tlnMJlMqsYNHToUkiRh7ty5fC/fjrUY/poKY8HB\nwaisrFR1kN/85jd46623APz4acCaNWswZcqUOz63a9euGDVqFJKSkpCYmIjExESEhISoOg4RERER\nEbVeRUUFVq1aBVmWceLECVVjvLy88Nhjj0GSJCQlJbHL5wKcstXD4sWLMWfOHFy+fBmrVq3Cs88+\nC19fX0yfPr3Rc4UQOHjwIA4ePIh33nkHADBs2DAkJiYqgbBXr17OKJuIiIiIqMMSQmD37t2QZRkf\nffQRbt68qWpcv379kJaWhuTkZPTo0cPBVZI9tRj+goKC7tjhq6ioQHBwsKqD9OrVSwlsDz30ECZP\nnoyXXnrpjuHvTo4dO4Zjx44hPT0dABAREaEEwaSkJPTv35+fNBARERERqXD9+nWsWbMGsizjwIED\nqsZotVpMnz4dkiThgQcegIeHh4OrdB/bt2+/q3VU7oZNC75oNBpkZ2e3+qAvvfQS3n77bRiNRuti\n7jLA9e7d26ozOGTIEIZBIiIiIqLbHDp0CLIsY/Xq1aipqVE1pmfPnli4cCFSUlLQt29fB1dIQBuv\n9vn222/jpZdewokTJxAeHg7gx60eBg8ejDfeeKPVWz1YLBZMnDgR165dw7Fjx6yLsVNg6969u/J9\nwaSkJIwYMQJarar97ImIiIiIOoybN29i/fr1kGUZBQUFqsdNmTIFkiThkUcegZeXlwMrpJ9r0/BX\nV1eH0aNHw9fXF6+99hoAYMmSJaitrbXa5P3s2bMYMGAAXn31VSxZsgQAsHTpUlRWVmLixIno2bOn\nslzst99+i7///e944oknrIvRaHDp0iXk5uYiNzcXOTk5OHLkiM0nGRQUhPj4eKUzGB0dDU9Pp3zd\nkYiIiIjI6U6ePIn09HR88MEHqKioUDUmKCgICxYsQGpqKoYMGeLgCqkpbRr+AKC0tBSLFy/GP//5\nTwghMHXqVCxbtsyq9VtSUoKIiAgsXboUr7zyCgDgyy+/xLJly3DkyBFcu3YNPXv2RFRUFP7zP/8T\nEyZMaFzMHU70hx9+wI4dO5CTk4Pc3Fzs378fFovFppP29/dHXFyc0hkcO3YsvL29bZqTiIiIiKgt\nGY1GbNy4EbIs45tvvlE9LjY2Fnq9Ho8//jh8fX0dWCGp0ebhz1nUnGh1dTXy8/OVzuDevXtV7z/S\nFB8fH0yYMEG5VTQ2NlbpaBIRERERtWelpaXIzMzE+++/j0uXLqka4+/vj2effRZpaWmIiopycIXU\nGgx/zairq8OuXbuUzuCuXbtUL1PbFC8vL8TExCidwYkTJ6Jz5842zUlEREREZC8WiwVbt26FwWDA\nV199pfrOuFGjRkGv1+OZZ55BQECAg6uku8Hw1wr19fXYu3ev0hnMz89HbW2tTXNqtVpER0cr3xlM\nSEhQvc0FEREREZG9lJWVYcWKFcjIyEBxcbGqMd7e3njyySchSRJiY2O5Kn47x/BnA5PJhH379imL\nyOTl5aGqqsrmeUeOHKl0BhMSEtCzZ087VEtEREREZE0Igby8PBgMBnz66aeNtktryqBBgyBJEubN\nm4euXbs6uEqyF4Y/OzKbzThy5IjSGczNzcXVq1dtnnfIkCFW20v06dPHDtUSERERkbuqqqpCVlYW\nZFlutEVaUzw8PPDoo49Cr9dj8uTJ3O7MBTH8OZAQAsePH7faXuLChQs2z9u/f3/lNtHExEQMGDCA\nLXYiIiIialFhYSEMBgPWrl2LGzduqBrTp08fpKamIjk5GWFhYQ6ukByJ4c+JhBAoLi626gyeOXPG\n5nnDwsKsOoPDhg1jGCQiIiIiAEBtbS3WrVsHg8GAoqIiVWM0Gg2mTZsGSZIwbdo07mPdQTD8tbHz\n589bdQaPHz9u85zdunVTwmBiYiJGjRoFDw8PO1RLRERERK7i6NGjkGUZWVlZqK6uVjWme/fueP75\n55GSkoLw8HAHV0jOxvDXzpSVlSEvL0/pDB46dMjmugMDAxEfH6/cKnrPPffAy8vLThUTERERUXtR\nX1+PDRs2QJZl5Obmqh6XlJQEvV6PmTNnQqfTObBCaksMf+1cZWUlduzYoXQG9+3bB7PZbNOcnTp1\nwsSJE5XO4Lhx4+Dj42OniomIiIjI2c6cOYOMjAysWLFC9YKDgYGBmD9/PtLS0jBs2DAHV0jtAcOf\ni6mpqUFBQYFyq+iePXvQ0NBg05ze3t4YP3688p3BCRMmoFOnTnaqmIiIiIgcwWQyYdOmTTAYDNiy\nZYvqcTExMdDr9XjyySfh5+fnwAqpvWH4c3E3btzA7t27lc7gzp07Va/c1BRPT0+MHTtW6QzGx8cj\nMDDQThUTERERkS0uXLiA5cuXIzMzE+fPn1c1xs/PD3PmzIEkSRgzZoyDK6T2iuGvg2loaEBhYaHS\nGdyxYwdqampsmlOr1WL06NHKdwYTEhLQrVs3O1VMRERERC2xWCzYtm0bDAYDNm7cqPprQMOHD4ck\nSXjuuef4YT4x/HV0JpMJBw8eVBaQycvLQ0VFhc3zDh8+3Gp7idDQUDtUS0RERES3Ky8vx8qVK5Ge\nno5Tp06pGqPT6TB79mzo9XrExcVxCzBSMPy5GYvFgqNHj1ptL3HlyhWb5x04cKDVxvP9+/e3vVgi\nIiIiNySEQEFBAWRZxvr161FfX69qXEREBCRJwvz58xESEuLgKskVMfy5OSEETp48qXQGc3JyUFpa\navO8ffv2VbqCiYmJGDRoED91IiIiImpGdXU1Vq9eDVmWcfjwYVVjtFotHn74Yej1ekydOhVardbB\nVZIrY/ijRkpKSpQgmJubq/oWg+b07NnTauP54cOH88WJiIiICMD+/fshyzLWrFmD2tpaVWPCwsKQ\nkpKChQsXonfv3g6ukDoKhj9q0cWLF61uE/3uu+9snjM4OBgJCQlKZ3D06NHw9PS0Q7VERERE7V9d\nXR0+/vhjyLKM3bt3qx53//33Q5IkzJgxg++dqNUY/qjVrl69ih07diidwQMHDth8bQMCAhAfH6/c\nKjpmzBjodDo7VUxERETUPhw/fhzp6elYuXIlqqqqVI3p2rUrkpOTkZqaioEDBzq4QurIGP7IZlVV\nVcjPz1c6g4WFhaqXH26Kr68vJkyYoHQGx48fD19fXztVTEREROQ8DQ0N+PzzzyHLMrKzs1WPi4+P\nhyRJmDVrFnx8fBxYIbkLhj+yu+vXr2PXrl1KZ3D37t2qV6lqik6nw7hx45TO4IQJExAQEGCniomI\niIjsr6SkBJmZmVi+fLnq1dUDAgIwd+5cSJKEESNGOLhCcjcMf+RwN2/exJ49e5TOYEFBAerq6mya\n08PDA/fcc4/SGYyPj0dQUJCdKiYiIiK6O2azGV9//TVkWcbmzZtVv/+Mjo6GXq/H008/DX9/fwdX\nSe6K4Y+czmg0Yt++fVYbz1dXV9s0p0ajwahRo5TOYEJCArp3726niomIiIiad/nyZSxfvhwZGRk4\nd+6cqjE+Pj54+umnIUkSYmJiuC0WORzDH7U5s9mMQ4cOWW0v8cMPP9g879ChQ5XOYFJSEnr16mWH\naomIiIh+JIRAdnY2ZFnGZ599BpPJpGrc0KFDIUkS5s6dyzuXyKkY/qjdsVgsOH78uNXG85cuXbJ5\n3oiICKuN58PDw/kJGxEREbVaRUUFVq1aBVmWceLECVVjvLy88Nhjj0GSJCQlJfE9CLUJhj9q94QQ\nOH36tFVnsKSkxOZ5e/furWw6n5SUhCFDhvCFmIiIiO5ICIHdu3dDlmV89NFHuHnzpqpx/fr1Q1pa\nGpKTk9GjRw8HV0nUPIY/cknnzp2z2nhe7aduzQkJCbHqDI4cORJardYO1RIREZGrun79OtasWQNZ\nlnHgwAFVY7RaLaZPnw5JkvDAAw/Aw8PDwVUSqcPwRx3C5cuXkZeXp3QGDx8+bPOcXbp0QUJCghII\no6Oj4enpaYdqiYiIqL07dOgQZFnG6tWrUVNTo2pMz549sXDhQqSkpKBv374OrpCo9Rj+qEP64Ycf\nsGPHDqUzuH//flgsFpvm9Pf3x8SJE5XOYExMDLy9ve1UMREREbW1mzdvYv369ZBlGQUFBarHTZky\nBZIk4ZFHHoGXl5cDKySyDcMfuYXq6mrk5+crt4ru3bsXRqPRpjl9fHwQGxurdAZjY2Ph5+dnp4qJ\niIjIWU6ePIn09HR88MEHqKioUDUmKCgICxYsQGpqKoYMGeLgConsg+GP3FJdXR127dqldAZ37dql\n+ovbTfHy8kJMTIyyiExcXBw6d+5sp4qJiIjInoxGIzZu3AhZlvHNN9+oHhcbGwu9Xo/HH38cvr6+\nDqyQyP4Y/ogA1NfXY+/evUpnMD8/H9evX7dpTq1Wi+joaKUzGB8fj65du9qpYiIiIrobpaWlyMzM\nxPvvv696Kyl/f388++yzSEtLQ1RUlIMrJHIchj+iOzCZTNi/f7+ygExeXh6qqqpsnnfkyJFKZzAx\nMRE9e/a0Q7VERETUHIvFgq1bt8JgMOCrr75SvQ7AqFGjoNfr8cwzzyAgIMDBVRI5HsMfkQoWiwWH\nDx+22l7i6tWrNs87ePBgq+0luDIYERGR/ZSVlWHFihXIyMhAcXFyJxmYAAAgAElEQVSxqjHe3t54\n8sknIUkSYmNjuQcwdSgMf0R3QQiB77//XukM5uTk4MKFCzbP279/f6uN5wcMGMB/dIiIiFpBCIG8\nvDwYDAZ8+umnqhd4GzRoECRJwrx58/g1DeqwGP6I7EAIgeLiYqvO4JkzZ2yeNzQ0VOkKJiYmIjIy\nkmGQiIjoDqqqqpCVlQVZlnHs2DFVYzw8PPDoo49Cr9dj8uTJ0Gq1Dq6SqG0x/BE5yPnz563C4PHj\nx22es1u3blYbz48aNQoeHh52qJaIiMg1FRYWwmAwYO3atbhx44aqMX369EFqaiqSk5MRFhbm4AqJ\n2g+GPyInKSsrQ15ennKr6KFDh2z+nQwMDER8fLzSGRwzZgw3lyUiog6vtrYW69atg8FgQFFRkaox\nGo0G06ZNgyRJmDZtGjw9PR1cJVH7w/BH1EYqKyuxY8cOpTO4b98+mM1mm+b08/PDxIkTlVtFx40b\nBx8fHztVTERE1LaOHj0KWZaRlZWF6upqVWO6d++O559/HikpKQgPD3dwhUTtG8MfUTtRU1ODnTt3\nKp3BPXv2oKGhwaY5vb29MX78eKUzOHHiRHTq1MlOFRMRETlefX09NmzYAFmWkZubq3pcUlIS9Ho9\nZs6cCZ1O58AKiVwHwx9RO3Xjxg3s3r1b+d5gQUGB6u8yNMXT0xNjxoxROoNxcXHo0qWLnSomIiKy\nnzNnziAjIwMrVqxQvb1SYGAg5s2bB0mSMGzYMAdXSOR6GP6IXERDQwOKioqUzuCOHTtQU1Nj05wa\njQZRUVFWG89369bNThUTERG1jslkwqZNm2AwGLBlyxbV42JiYiBJEp566in4+fk5sEIi18bwR+Si\nTCYTDh48qHxnMC8vDxUVFTbPGxkZabW9BFdBIyIiR7tw4QKWL1+OzMxMnD9/XtUYPz8/zJkzB5Ik\nYcyYMQ6ukKhjYPgj6iAsFgu+++47q43nr1y5YvO8AwcOVLaWSExMRL9+/bjXIBER2cxisWDbtm0w\nGAzYuHGj6kXPhg8fDkmS8NxzzyEwMNDBVRJ1LAx/RB2UEAInT55UgmBOTg5KS0ttnrdPnz5KEExK\nSsKgQYMYBomISLXy8nKsXLkS6enpOHXqlKoxOp0Os2fPhl6vR1xcHP/dIbpLDH9EbuTs2bNWnUG1\n/+g2p0ePHladweHDh0Or1dqhWiIi6iiEECgoKIAsy1i/fj3q6+tVjYuIiEBaWhoWLFiAkJAQB1dJ\n1PEx/BG5sYsXL1ptPH/06FGb5wwODkZCQoISCEePHs2NdImI3FR1dTVWr14NWZZx+PBhVWO0Wi0e\nfvhhSJKE++67jx8oEtlRm4e/0tJSLF68GN988w2EEJg6dSqWLVuGPn36NDtu7969kGUZeXl5uHDh\nArp164aEhAS89tpr6N+/f+NiGP6IWlReXo68vDylM3jgwAGb/94EBAQgLi5O6QyOHTuW+y0REXVw\n+/fvhyzLWLNmDWpra1WNCQsLQ0pKChYuXIjevXs7uEIi99Sm4a+urg6jR4+Gr68vXnvtNQDAyy+/\njLq6Ohw6dKjZpXp/85vfID8/H8888wxGjhyJCxcu4I9//CPKyspw4MCBRi8aDH9ErVdVVYWCggKl\nM1hYWAiTyWTTnL6+vpgwYYLSGRw/fjx8fX3tVDEREbWVuro6fPzxx5BlGbt371Y97v7774ckSZgx\nYwbvFCFysDYNf2+//TZefPFFnDhxAhEREQCAkpISDBo0CG+++SYWL17c5NirV682uvf73LlzCA8P\nx8svv4zf//731sUw/BHZrLa2Fjt37lQ6g7t371b9vY2meHl5Ydy4cUpncOLEiQgICLBTxURE5GjH\njx9Heno6Vq5ciaqqKlVjunbtiuTkZKSmpmLgwIEOrpCIbmnT8DdlyhQ0NDQgLy/P6vFJkyYBALZv\n397qg/bs2RMzZsxAZmamdTEMf0R2d/PmTezZswe5ubnIzc1Ffn4+6urqbJrTw8MD99xzj9IZjI+P\nR1BQkJ0qJiIie2hoaMDnn38OWZaRnZ2telx8fDwkScKsWbPg4+PjwAqJ6E4cmYla7NsfPXoUM2fO\nbPR4ZGQkPvnkk1Yf8NixYygrK8OwYcNaPZaIWs/Hx0fZDB4AjEYj9u3bp3QGd+zYgWvXrrVqTrPZ\njL1792Lv3r34y1/+Ao1Gg5EjR1ptPN+9e3dHnA4REbWgpKQEmZmZWL58ueq9ZAMCAjB37lxIkoQR\nI0Y4uEIiaistdv68vb3x4osv4vXXX7d6/OWXX8Ybb7wBo9Go+mAmkwlTpkzB999/j++//77Rpp/s\n/BE5n9lsxqFDh5TOYG5uLsrLy22ed+jQoVbbS3BhACIixzGbzfj6668hyzI2b96s+v1UdHQ09Ho9\nnn76afj7+zu4SiJSo007f/b0y1/+Ert27cKmTZsaBT8iahseHh6Ijo5GdHQ0/v3f/x1CCBw7dsxq\nr8FLly61et7jx4/j+PHjyMjIAACEh4dbbTwfHh7ODYCJiGx0+fJlLF++HBkZGTh37pyqMT4+Pnj6\n6achSRJiYmL4WkzkRloMf0FBQaisrGz0eEVFBYKDg1Uf6Le//S0yMzORlZWFqVOnNvm8pUuXKj9P\nmjRJ+W4hETmHRqNBZGQkIiMjodfrIYTA6dOnla5gTk4OSkpKWj1vcXExiouLsXLlSgBAr169rDqD\nQ4cO5RsQIiIVhBDIzs6GLMv47LPPVK/wPHToUEiShLlz5/J72kTtyPbt2+9qHZW7YdOCLxqNRtUX\niP/0pz9hyZIlePfdd/Fv//ZvTRfD2z6JXMK5c+esbhP9/vvvbZ4zJCRE+b5gUlISRo4cyU2DiYhu\nU1FRgVWrVkGWZZw4cULVGC8vLzz22GOQJAlJSUn8kI3IBbT5Vg8vvfQSTpw4gfDwcAA/fpF48ODB\neOONN5rd6gEA3nnnHfz617/G66+/jt/+9rfNF8PwR+SSLl++jLy8POVW0cOHD9s8Z5cuXZCQkKAE\nwnvuuYd7SxGR2xFCYM+ePTAYDPjoo49w8+ZNVeP69euHtLQ0JCcno0ePHg6ukojsqd1t8r5kyRLU\n1tZabfJ+9uxZDBgwAK+++iqWLFkCAFi3bh3mzJmDBx98EK+++qrVSQQGBjZa8ZPhj6hjqKioQF5e\nntIZ3LdvHywWi01zdurUCXFxcUpnMCYmBt7e3naqmIiofbl+/TrWrFkDWZZx4MABVWO0Wi2mT58O\nSZLwwAMPwMPDw8FVEpEjtGn4A4DS0lIsXrwY//znPyGEwNSpU7Fs2TL07dtXeU5JSQkiIiKwdOlS\nvPLKKwCABQsWICsr647FT5o0Cd9++611MQx/RB1SdXU1CgoKlM7g3r17W7VS8J34+PggNjZW6QxO\nmDBB+TCKiMhVHTp0CLIsY/Xq1aipqVE1pmfPnli4cCFSUlKs3psRkWtq8/DnLAx/RO6hrq4Ou3bt\nUjqDO3fuVH0rU1M8PT0RExOjdAbj4uLQuXNnO1VMROQ4N2/exPr16yHLMgoKClSPmzJlCiRJwiOP\nPAIvLy8HVkhEzsTwR0QdWn19PQoLC5XOYH5+Pq5fv27TnFqtFlFRUcpqogkJCejataudKiYist3J\nkyeRnp6ODz74ABUVFarGBAUFYcGCBUhNTcWQIUMcXCERtQWGPyJyKyaTCfv371c6g3l5eXfccqa1\nRowYYbW9RM+ePe1QLRGRekajERs3boQsy/jmm29Uj4uNjYVer8fjjz8OX19fB1ZIRG2N4Y+I3JrF\nYsGRI0eUzmBubi7Kyspsnnfw4MFW20vwuzJE5CilpaXIzMzE+++/j0uXLqka4+/vj2effRZpaWmI\niopycIVE1F4w/BER3UYIge+//17ZdD4nJwcXLlywed5+/fopXcHExEQMHDiQe2IR0V2zWCzYunUr\nDAYDvvrqK9WrHo8aNQp6vR7PPPMMAgICHFwlEbU3DH9ERM0QQqCkpETpDObk5ODMmTM2zxsaGmrV\nGRw2bBg3nieiFpWVlWHFihXIyMhAcXGxqjHe3t544oknoNfrERsbyw+eiNwYwx8RUSudP3/eauP5\nY8eO2Txn165dlTCYmJiI0aNHcx8tIgLw44dQeXl5MBgM+PTTT1VvZzNo0CBIkoR58+ZxUSoiAsDw\nR0Rks7KyMmXj+ZycHBw6dMjm15vOnTsjPj5euVV0zJgxXG6dyM1UVVUhKysLsiyr/pDJw8MDjz76\nKPR6PSZPnsw7CojICsMfEZGdVVZWIj8/X+kMFhUVwWw22zSnn58fJk6cqHQGx48fDx8fHztVTETt\nSWFhIQwGA9auXYsbN26oGtOnTx+kpqYiOTkZYWFhDq6QiFwVwx8RkYPV1NRg586dSmdwz549aGho\nsGlOnU6H8ePHK53BCRMmwN/f304VE5Gz1dbWYt26dTAYDCgqKlI1RqPRYNq0aZAkCdOmTYOnp6eD\nqyQiV8fwR0TkZDdu3MCePXuUzmBBQYHqT/eb4unpiTFjxiidwfj4eHTp0sVOFRORoxw9ehSyLCMr\nKwvV1dWqxnTv3h3PP/88UlJSEB4e7uAKiagjYfgjImpjDQ0NKCoqUjqDO3bsQE1NjU1zajQajB49\nWukMJiQkICQkxE4VE5Et6uvrsWHDBsiyjNzcXNXjkpKSoNfrMXPmTOh0OgdWSEQdFcMfEVE7YzKZ\ncPDgQWXT+dzcXFRUVNg8b2RkpLK1RGJiIr8XRORkZ86cQUZGBlasWIGrV6+qGhMYGIh58+ZBkiQM\nGzbMwRUSUUfH8EdE1M5ZLBZ89913VhvPX7lyxeZ5BwwYYLXxfP/+/bn/F5GdmUwmbNq0CQaDAVu2\nbFE9LiYmBpIk4amnnoKfn58DKyQid8LwR0TkYoQQOHnypNIVzMnJwblz52yet0+fPladwcGDBzMM\nEt2lCxcuYPny5cjMzMT58+dVjfHz88OcOXMgSRLGjBnj4AqJyB0x/BERdQBnz55VgmBubi5Onjxp\n85w9evRQuoJJSUkYPnw49wwjaobFYsG2bdtgMBiwceNG1Vu8DB8+HJIk4bnnnkNgYKCDqyQid8bw\nR0TUAV28eNFq4/mjR4/aPGdQUBASEhKUzmBUVBSXlicCUF5ejpUrVyI9PR2nTp1SNUan02H27NnQ\n6/WIi4tjl52InILhj4jIDZSXlythMDc3FwcOHIDFYrFpzoCAAMTFxSmdwbFjx3IFQnIbQggUFBRA\nlmWsX78e9fX1qsZFREQgLS0NCxYs4Aq8ROR0DH9ERG7o2rVryM/PVzqDhYWFMJlMNs3p6+uL2NhY\npTMYGxsLX19fO1VM1D5UV1dj9erVkGUZhw8fVjVGq9Xi4YcfhiRJuO+++3j7NBG1GYY/IiJCbW0t\ndu7cqXQGd+3apbqT0RQvLy+MGzdO6QxOnDgRAQEBdqqYyLn2798PWZaxZs0a1NbWqhoTFhaGlJQU\nLFy4EL1793ZwhURELWP4IyKiRm7evIm9e/cqC8gUFBSofsPbFA8PD0RHRyudwfj4eAQHB9upYiL7\nq6urw8cffwxZlrF7927V4+6//35IkoQZM2bwe7FE1K4w/BERUYuMRiP27dundAbz8vJw7do1m+bU\naDQYOXKk0hlMSEhAjx497FQx0d07fvw40tPTsXLlSlRVVaka07VrVyQnJyM1NRUDBw50cIVERHeH\n4Y+IiFrNbDbj8OHDSmcwNzcX5eXlNs87ZMgQpTOYlJTEW+XIaRoaGvD5559DlmVkZ2erHhcfHw9J\nkjBr1iz4+Pg4sEIiItsx/BERkc2EEDh27JiygExOTg4uXbpk87zh4eFWG89HRERwSXyyq5KSEmRm\nZmL58uW4cuWKqjEBAQGYO3cu0tLSMHLkSAdXSERkPwx/RERkd0IInDlzRukM5uTkoKSkxOZ5e/Xq\nZbXx/NChQxkGqdXMZjO+/vpryLKMzZs3q35/EB0dDb1ej6effhr+/v4OrpKIyDYWkwXGMiMaLjWg\n/mI9Gi42oJfUi+GPiIgc79y5c8jLy1MC4ffff2/znCEhIVYbz48cORIeHh52qJY6osuXL2P58uXI\nyMjAuXPnVI3x8fHB008/DUmSEBMTww8biKjNCbNAQ1kDGi42oP7Sj6Gu/mI9Gi41WP1sLDfCM9gT\n3mHe0IXp4B3qjaHvD2X4IyIi57ty5YryfcGcnBzVe6Y1p0uXLoiPj1c6g9HR0fDy8rJDteSqhBDI\nzs6GLMv47LPPVO9nOXToUEiShLlz5yIoKMjBVRIR/RTqrjY0GeZude+UUBf6U6gL84YuVGf1s3eY\nN7x6eEHrab2vKG/7JCKidqGiogI7duxQOoP79u2DxWKxac5OnTph4sSJSmdw3Lhx8Pb2tlPF1J5V\nVFRg1apVkGUZJ06cUDXGy8sLjz32GCRJQlJSErt8RGQXSqhrIszd+tlYdlun7g5hThem+/HxHjpo\nvbQtH/gOGP6IiKhdqq6uRkFBgdIZ3Lt3L4xGo01zent7IzY2VukMxsbGolOnTnaqmNqaEAJ79uyB\nwWDARx99hJs3b6oa169fP6SlpSE5OZnbjRCRasIiYLxqbPbWSyXUdfFsMswpP9sQ6tRi+CMiIpdQ\nV1eH3bt3K53BnTt3qn5z3xRPT0/ExMQoi8jExcUhMDDQThWTs1y/fh1r1qyBLMs4cOCAqjFarRbT\np0+HJEl44IEH+F1RIlIIi4Cx3NjsrZcNlxrQcKUBnoG3hbqfhblbt2Xqeuig1Tk21KnF8EdERC6p\nvr4ehYWFSmcwPz8f169ft2lOrVaLqKgoq43nu3btaqeKyd4OHToEWZaxevVq1NTUqBrTs2dPLFy4\nECkpKejbt6+DKySi9kRYBIw/GJu99bLh4m2hrplbL73DvKHr2X5CnVoMf0RE1CGYTCbs379fWUQm\nLy8PlZWVNs87YsQIpTOYmJiI0NBQO1RLd+vmzZtYv349ZFlGQUGB6nFTpkyBJEl45JFHuAgQUQcj\nRONQp/x824qYDZcb4NHZo9lbL71Dfwp13q4V6tRi+CMiog7JYrHgyJEjSmcwNzcXZWVlNs87aNAg\nq43n+/XrZ4dqqSUnT55Eeno6PvjgA1RUVKgaExQUhAULFiA1NRVDhgxxcIVEZG9KqGthoZSGyw3w\n8Pdo9tZLpVPXQUOdWgx/RETkFoQQOHHihNXG8+fPn7d53n79+lltPD9w4ECuEmknRqMRGzduhCzL\n+Oabb1SPi42NhV6vx+OPPw5fX18HVkhEd0MIAVOFqdlbL+sv/fjfPDp5tLxQSk8dPHz4vV01GP6I\niMgtCSFQUlJi1Rk8ffq0zfOGhoZa3SYaGRkJrda9P2lurdLSUmRmZuL999/HpUuXVI3x9/fHs88+\ni7S0NERFRTm4QiK6EyEETJWmZm+9VDp1fh7N33r502MMdfbF8EdERPSTCxcuWG08f+zYMZvn7Nq1\nKxISEpTbREePHs2VJe/AYrFg69atMBgM+Oqrr1Tv8Thq1Cjo9Xo888wzCAgIcHCVRO5JCAFTlanF\nhVLqL9XDw9ej+VsvQ38Kdb58HWwLDH9ERERNKCsrs9p4/uDBgzb/W9K5c2fEx8crncGxY8e69QIk\nZWVlWLFiBTIyMlBcXKxqjLe3N5544gno9XrExsbyNluiu6SEuuZuvfzpMY23pukwd9vPDHXtG8Mf\nERGRSpWVlcjPz1c6g0VFRTCbzTbN6efnhwkTJiidwfHjx8PHx8dOFbdPQgjk5eXBYDDg008/hdFo\nVDVu0KBBkCQJ8+bN4xYcRM0QQsB0zdT8rZc//TeNTtPyQimhOnj4MdR1BAx/REREd+n69esoKChQ\nbhXdvXs3GhoabJpTp9Nh/PjxSmdw4sSJ8Pf3t1PFbauqqgpZWVmQZVn1LbUeHh549NFHodfrMXny\nZH5/ktyaEALmanPLC6VcbIDGS9P8rZc/PebRiaHOnTD8ERER2cmNGzewZ88e5TbRgoIC3Lhxw6Y5\nPTw8MGbMGKUzGB8fjy5dutipYucoLCyEwWDA2rVrVV+PPn36IDU1FcnJyQgLC3NwhURtSwgBc425\n2TB3K/BpPDQt3nqpC9XB09+zrU+L2iGGPyIiIgdpaGhAUVGR0hncsWMHqqurbZpTo9Fg9OjRViuK\nhoSE2Kli+6mtrcW6detgMBhQVFSkaoxGo8GDDz4IvV6PadOmwdOTb17J9ZlqTC3eell/sR7QAN69\nvJvu1oUx1JHtGP6IiIicxGw24+DBg0pnMDc3V/WG5c0ZNmyY0hlMTExEr1697FDt3Tl69ChkWUZW\nVpbqoBsSEoLnn38eqampCA8Pd3CFRPZhqml5oZT6i/UAoGqhFM8AhjpyPIY/IiKiNmKxWPDdd99Z\nbS9x+fJlm+cdMGCAsul8YmIi+vfv79AVMevr67FhwwbIsozc3FzV45KSkqDX6zFz5kzodDqH1UfU\nGqbrphZvvWy42ABhEf8KdXcIc7f+G0MdtScMf0RERO2EEAKnTp1SOoM5OTk4d+6czfP27t1bCYJJ\nSUkYPHiwXcLgmTNnkJGRgRUrVuDq1auqxgQGBmLevHmQJAnDhg2zuQYitcy15hZvvWy41ABhEsrt\nl3cKc7d+9gjw4DYj5HIY/oiIiNqxs2fPKkEwNzcXJ0+etHnO7t27W3UGR4wYoXoVTZPJhE2bNsFg\nMGDLli2qjxkTEwNJkvDUU0/Bz8/vbksnasRca7baj+6OAe/ij6Gu2Vsvb61+2Zmhjjouhj8iIiIX\ncunSJavbRI8ePWrznEFBQUhISFACYVRUVKPFVi5cuIDly5cjMzMT58+fVzWvn58f5syZA0mSMGbM\nGJvrJPdirjO3eOtl/cV6iAbR4q2XulAdPAM9GerI7TH8ERERubDy8nLs2LFD6QweOHAAFovFpjn9\n/f0RFxeHpKQkDBw4EOvWrcMXX3yhekP74cOHQ5IkPPfccwgMDLSpFup4zDd+FurucOtl/cV6iHrR\n4q2XujCGOqLWaPPwV1paisWLF+Obb76BEAJTp07FsmXL0KdPnxYP8Lvf/Q6FhYUoKipCZWUlPvjg\nA8ybN+/OxTD8ERGRG7h27Rry8/OVzmBhYSFMJpPDj6vT6TB79mzo9XrExcXxzbgbuhXqWurWmW+Y\nW7z1Uhemg2cXhjoie2vT8FdXV4fRo0fD19cXr732GgDg5ZdfRl1dHQ4dOtTidwI6d+6M6OhohIeH\nIysrCytXrsTcuXPvXAzDHxERuaHa2lrs2rVL6Qzu2rUL9fX1dps/IiICaWlpWLBgQbvcb5BsZ75p\n/ldnrpmFUsx1P4W6Frp1nkEMdURtxZGZqMV1bTMzM1FcXIwTJ04gIiICADBq1CgMGjQI6enpWLx4\ncbPjb+0fdPr0aWRlZdmhZCIioo6lU6dOmDJlCqZMmQLgx20Z9uzZo3QGCwoKUFtb26o5tVotHn74\nYUiShPvuu0/1YjHUvljqLc2GuVvdO3Ot+V8h7rYw5zfUz6pb5xnMUEfkzlrs/E2ZMgUNDQ3Iy8uz\nenzSpEkAgO3bt6s60KlTpzB48GB2/oiIiFrJaDRi//79SmcwLy8P165du+Nzw8LCkJKSgoULF6J3\n795OrpTUstRb0HC55YVSzNfN0PW88/fobr8tk6GOqONo087f0aNHMXPmzEaPR0ZG4pNPPnFIUURE\nRPQvXl5eGDduHMaNG4ff/OY3MJvNOHz4sNIZ/O677zBo0CAsWLAAM2bMaLQKKDmPEupa6NaZa8zQ\n9Wh862WXpC5W37HzCvaCRstQR0T20eK/DpWVlQgKCmr0eHBwMCorKx1SFBERETXNw8MDUVFRiIqK\nwqJFi9q6HLdgabitU9fErZcNlxpgumaCrqeu0ffoAhMCrbp1Xl0Z6ojI+fjRIBEREbkti/HHUNfS\nQimmKpPSqbs92AXGBVp177y6MdQRUfvVYvgLCgq6Y4evoqICwcHBdi9o6dKlys+TJk1SvltIRERE\npJbFaEHDlYYWF0oxVZng1d2r0UIpgRMDrVbEZKgjIkfZvn276nVUbGXTgi8ajQbZ2dmqDsQFX4iI\niMhWSqhr5tbL+ov1MFWa4BXi1eJCKV7dvKDxYKgjovajTRd8efjhh/HSSy+huLgY4eHhAICSkhIU\nFBTgjTfecEhRRERE5F4sJguMV4xN33r5022ZpoofQ93Pw1zn8Z2tFkrRhegY6oiIfuauNnlfsmQJ\namtrrTZ5P3v2LAYMGIBXX30VS5YsUcbn5OTg6tWruHz5MhYtWoQXXngBSUlJAIDZs2dbF8POHxER\nUYdiMVlgLDO2uFCK8QcjvLp5NerM/Xwzcl13hjoi6tgcmYlaDH8AUFpaisWLF+Of//wnhBCYOnUq\nli1bhr59+yrPKSkpQUREBJYuXYpXXnlFeXzy5MnIycn58WC3nYhGo4HZbLYuhuGPiIjIJQizQENZ\n87deNlz8KdR19Wp86+XPvmPnFeIFrSc3oiciavPw5ywMf0RERG1LmAUarjaxUMptK2Iay43wDPa8\n4/forBZK6c5QR0TUGgx/REREZBMl1LWwUIrx6k+hrplbL73DvOHVg6GOiMgRGP6IiIgIQggI0x3+\nNPx0C2YTt17WX6qHscwIzyDPZm+91IXqoOuhg9aLoY6IqK0w/BEREd1GmJsIQT/7YzFaVD1PmASE\nsY2e14o6YQY0npp//fH6189e3b2aXyilJ0MdEZEraNOtHoiIqH1qsgtkQwhR+9w2DVUmAWiaDkHN\n/dF6aVU9r6U5tT7aVh/bHjVC++ObAiIiorvB8EdELs/uXSAHhCWndIEcFEaaep5VALJjsGrxeR4a\naLQMQERERK3F8EfUQbAL5JhOi5o5fx6CnNUNYheIiIiIWoPhjzoUIQRgAbtAbdANumMAckY3iF0g\nIiIiIlUY/joodoEc02lRM2dTIcjR3SB2gYiIiIioOR06/HW0LlBrQlWLXSAHd4OaDUCO7AaxC0RE\nREREdEftLvwdfuSwc7tADu4GtRSCHNUNYheIiIiIiIhu18bgDN4AABAOSURBVO72+bv6+VX7doPY\nBSIiIiIiIhfBTd6JiIiIiIjcgCMzkdYhsxIREREREVG7wvBHRERERETkBhj+iIiIi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2bdqQnp7O6dOnRRAVhCKUnwn5JV2JCqSQmTs+LCyMlJQUIiIiiI+PZ/r06RgZ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\naePGjWrLiqApCLoheqQlXNeuXdm0aRMNGjTAxcW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+ "text": [ + "" + ] + } + ], + "prompt_number": 212 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "It seems that with all the features in, we can have the best prediction result." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "cmDiagList = []\n", + "modelLabels = [\"Generic\", \"G+A\", \"G+A+L\", \"G+B\", \"G+A+B\", \"G+A+B+L\", \"G+A+B+L+T\"]\n", + "for currCM in modelCMList:\n", + " cmDiagList.append(np.diag(currCM) * 100)\n", + "accuracyMatrix = np.vstack(cmDiagList)\n", + "print len(modelLabels), accuracyMatrix.shape\n", + "np.set_printoptions(precision=4)\n", + "print accuracyMatrix\n", + "np.set_printoptions(precision=0)\n", + "print accuracyMatrix" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "7 (7, 6)\n", + "[[ 95.0255 85.4536 33.673 37.2951 88.1527 69.3333]\n", + " [ 95.2391 85.4536 30.0699 36.2951 88.9574 65.3333]\n", + " [ 95.5443 87.504 47.7955 55.1148 91.5963 82.6667]\n", + " [ 95.4224 86.7585 59.3706 47.8415 89.8957 85.3333]\n", + " [ 95.178 84.8942 63.2368 48.8634 89.404 74. ]\n", + " [ 95.7273 87.5949 66.3137 63.0437 91.4167 78.6667]\n", + " [ 95.3919 88.2491 70.6727 62.0765 90.5672 82.6667]]\n", + "[[ 95. 85. 34. 37. 88. 69.]\n", + " [ 95. 85. 30. 36. 89. 65.]\n", + " [ 96. 88. 48. 55. 92. 83.]\n", + " [ 95. 87. 59. 48. 90. 85.]\n", + " [ 95. 85. 63. 49. 89. 74.]\n", + " [ 96. 88. 66. 63. 91. 79.]\n", + " [ 95. 88. 71. 62. 91. 83.]]\n" + ] + } + ], + "prompt_number": 213 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "cmDiagList = []\n", + "modelLabels = [\"Generic\", \"G+A\", \"G+A+L\", \"G+B\", \"G+A+B\", \"G+A+B+L\", \"G+A+B+L+T\"]\n", + "for currCM in modelCMList:\n", + " cmDiagList.append(np.diag(currCM) * 100)\n", + "accuracyMatrix = np.vstack(cmDiagList).round(decimals=0).astype(object)\n", + "print len(modelLabels), accuracyMatrix.shape\n", + "outputMatrix = np.insert(accuracyMatrix, 0, modelLabels, axis=1)\n", + "print outputMatrix" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "7 (7, 6)\n", + "[['Generic' 95.0 85.0 34.0 37.0 88.0 69.0]\n", + " ['G+A' 95.0 85.0 30.0 36.0 89.0 65.0]\n", + " ['G+A+L' 96.0 88.0 48.0 55.0 92.0 83.0]\n", + " ['G+B' 95.0 87.0 59.0 48.0 90.0 85.0]\n", + " ['G+A+B' 95.0 85.0 63.0 49.0 89.0 74.0]\n", + " ['G+A+B+L' 96.0 88.0 66.0 63.0 91.0 79.0]\n", + " ['G+A+B+L+T' 95.0 88.0 71.0 62.0 91.0 83.0]]\n" + ] + } + ], + "prompt_number": 214 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 214 + } + ], + "metadata": {} + } + ] +} \ No newline at end of file diff --git a/percom_moves_collect_2014/README.md b/percom_moves_collect_2014/README.md new file mode 100644 index 0000000..dcfe564 --- /dev/null +++ b/percom_moves_collect_2014/README.md @@ -0,0 +1,38 @@ +### Overview + +This directory contains the analysis included in the PerCom 2014 paper. Unfortunately, the underlying dataset cannot be published because it contains privacy-sensitive location data. However, the corresponding author can run analyses based on the notebooks here against the raw data and return the results. + +The analysis is represented in three notebooks: +- `mode_inference_percom_july_2014_data.ipynb`: base notebook. Since results are not included, can easily track changes to the analysis scripts. Needs access to the raw dataset to re-generate results. +- `mode_inference_percom_july_2014_data_with_result.ipynb`: copy of previous notebook with results included. Since results are included, diffs are going to be very hard to parse, but it shows a lot more detailed results than the paper without needing access to the data. +- `Project_scratch_mode_inference.ipynb`: original notebook used for paper. has bitrotted and cannot be run any more, but is useful as the source of the original results + +### Running + +The notebook *must* be run from the current directory because it uses some files that are relative to this directory. + +1. Install the e-mission server, including setting it up + +1. Set the home environment variable + +``` +$ export EMISSION_SERVER_HOME= +``` + +1. Set up this analysis + +``` +$ source setup.sh +``` + +1. Start the notebook server + +``` +$ ../bin/em-jupyter-notebook.sh +``` + +After completing analysis, tear down + +``` +$ source teardown.sh +``` diff --git a/percom_moves_collect_2014/TestFeatureCalc.py b/percom_moves_collect_2014/TestFeatureCalc.py new file mode 100644 index 0000000..77476cf --- /dev/null +++ b/percom_moves_collect_2014/TestFeatureCalc.py @@ -0,0 +1,176 @@ +import unittest +import json +from featurecalc import calDistance, calSpeed, calHeading, calAvgSpeed, calSpeeds, calAccels, getIthMaxSpeed, getIthMaxAccel +import pygeocoder + + +class TestFeatureCalc(unittest.TestCase): + # All the test data is obtained by using + # Sections.find_one({"$and": [{'type': 'move'}, {'confirmed_mode': }]}) + # and then picking the first two points from the track points for that section + def setUp(self): + self.walktp1 = {"track_location": {"type": "Point", + "coordinates": [37.8724267522, -122.2593326013]}, "time": "20140415T182218Z"} + self.walktp2 = {"track_location": {"type": "Point", + "coordinates": [37.8722939116, -122.2594439528]}, "time": "20140415T182251Z"} + + self.biketp1 = {"track_location": {"type": "Point", "coordinates": [37.8385561216, -122.2495945853]}, "time": "20140418T181035-0700"} + self.biketp2 = {"track_location": {"type": "Point", "coordinates": [37.838834329, -122.249646471]}, "time": "20140418T181100-0700"} + + self.traintp1 = {"track_location": {"type": "Point", "coordinates": [37.8419243845, -122.251608766]}, "time": "20140418T083731-0700"} + self.traintp2 = {"track_location": {"type": "Point", "coordinates": [37.841983358, -122.2516275124]}, "time": "20140418T083748-0700"} + + self.cartp1 = {"track_location": {"type": "Point", "coordinates": [37.8796206126, -122.272393763]}, "time": "20140418T013558Z"} + self.cartp2 = {"track_location": {"type": "Point", "coordinates": [37.8796948352, -122.2724807525]}, "time": "20140418T013618Z"} + + from datetime import datetime + + segments = json.load(open("testFeatureCalcData.json")) + self.walkSegment = segments[0] + self.walkSegment['section_start_datetime'] = datetime(2014, 4, 15, 18, 22, 18) + self.walkSegment['section_end_datetime'] = datetime(2014, 4, 15, 18, 31, 27) + + self.bikeSegment = segments[1] + self.bikeSegment['section_start_datetime'] = datetime(2014, 4, 19, 1, 10, 35) + self.bikeSegment['section_end_datetime'] = datetime(2014, 4, 19, 1, 23, 16) + + self.trainSegment = segments[2] + self.trainSegment['section_start_datetime'] = datetime(2014, 4, 18, 15, 37, 31) + self.trainSegment['section_end_datetime'] = datetime(2014, 4, 18, 15, 48, 3) + + self.carSegment = segments[3] + self.carSegment['section_start_datetime'] = datetime(2014, 4, 18, 1, 35, 58) + self.carSegment['section_end_datetime'] = datetime(2014, 4, 18, 1, 42, 46) + + # We spot check by using real values from the test data and comparing them to + # the calculations at http://www.movable-type.co.uk/scripts/latlong.html + def testCalDistance(self): + self.assertAlmostEqual( + calDistance([37.8724267522, -122.2593326013], [37.8678553385, -122.2597410423]), + 509.6, places=1) + + self.assertAlmostEqual( + calDistance(self.walktp1['track_location']['coordinates'], self.walktp2['track_location']['coordinates']), + 17.71, places=1) + + # points obtained from a bike trip + self.assertAlmostEqual( + calDistance(self.biketp1['track_location']['coordinates'], self.biketp2['track_location']['coordinates']), + 31.27, places=1) + + self.assertAlmostEqual( + calDistance(self.traintp1['track_location']['coordinates'], self.traintp2['track_location']['coordinates']), + 6.761, places=1) + + self.assertAlmostEqual( + calDistance(self.cartp1['track_location']['coordinates'], self.cartp2['track_location']['coordinates']), + 11.24, places=1) + + def testCalcSpeed(self): + # points obtained from a walk trip + self.assertAlmostEqual( + calSpeed(self.walktp1, self.walktp2), 0.53666, places=2) + + self.assertAlmostEqual( + calSpeed(self.biketp1, self.biketp2), 1.25, places=2) + + self.assertAlmostEqual( + calSpeed(self.traintp1, self.traintp2), 0.3977, places=2) + + self.assertAlmostEqual( + calSpeed(self.cartp1, self.cartp2), 0.562, places=2) + + def testCalcHeading(self): + # points from a walking trip + self.assertAlmostEqual( + calHeading(self.walktp1['track_location']['coordinates'], self.walktp2['track_location']['coordinates']), + -147, places=0) + + self.assertAlmostEqual( + calHeading(self.biketp1['track_location']['coordinates'], self.biketp2['track_location']['coordinates']), + -8.37, places=0) + + self.assertAlmostEqual( + calHeading(self.traintp1['track_location']['coordinates'], self.traintp2['track_location']['coordinates']), + -14.09, places=0) + + self.assertAlmostEqual( + calHeading(self.cartp1['track_location']['coordinates'], self.cartp2['track_location']['coordinates']), + -43, places=0) + + # The website returns only a positive heading - it converts a negative heading to positive + # by subtracting from 360. I think we can deal with negative headings, so we don't subtract + # but then we need to fix the value that we compare against + # 184deg 02'04'' + self.assertAlmostEqual( + calHeading([37.8724267522, -122.2593326013], [37.8678553385, -122.2597410423]), + - (360 - 184.035), places=1) + + def testAvgSpeeds(self): + self.assertAlmostEqual( + calAvgSpeed(self.walkSegment), 1.14025, places = 2) + + self.assertAlmostEqual( + calAvgSpeed(self.bikeSegment), 4.92509, places = 2) + + self.assertAlmostEqual( + calAvgSpeed(self.trainSegment), 4.36708, places = 2) + + self.assertAlmostEqual( + calAvgSpeed(self.carSegment), 4.52696, places = 2) + + def testSegSpeeds(self): + self.assertAlmostEqual( + calSpeeds(self.walkSegment)[0], 0.53666, places=2) + + self.assertAlmostEqual( + calSpeeds(self.bikeSegment)[0], 1.25, places=2) + + self.assertAlmostEqual( + calSpeeds(self.trainSegment)[0], 0.3977, places=2) + + self.assertAlmostEqual( + calSpeeds(self.carSegment)[0], 0.562, places=2) + + def testSegSecondSpeeds(self): + self.assertAlmostEqual( + calSpeeds(self.walkSegment)[1], 0.47711, places=2) # 52 secs + + self.assertAlmostEqual( + calSpeeds(self.bikeSegment)[1], 2.05027, places=2) # 181 secs + + self.assertAlmostEqual( + calSpeeds(self.trainSegment)[1], 5.61904, places=2) # 21 secs + + self.assertAlmostEqual( + calSpeeds(self.carSegment)[1], 0.26278, places=2) # 19 secs + + def testFirstAccel(self): + self.assertAlmostEqual( + calAccels(self.walkSegment)[0], 0.01626, places=3) # 33 secs + + self.assertAlmostEqual( + calAccels(self.bikeSegment)[0], 0.05, places=4) # 25 secs + + self.assertAlmostEqual( + calAccels(self.trainSegment)[0], 0.02339, places=4) # 17 secs + + self.assertAlmostEqual( + calAccels(self.carSegment)[0], 0.02810, places=4) # 20 secs + + def testSecondAccel(self): + self.assertAlmostEqual( + calAccels(self.walkSegment)[1], -0.00114, places=4) # 52 secs + + self.assertAlmostEqual( + calAccels(self.bikeSegment)[1], 0.00442, places=4) # 181 secs + + self.assertAlmostEqual( + calAccels(self.trainSegment)[1], 0.24863, places=3) # 21 secs + + self.assertAlmostEqual( + calAccels(self.carSegment)[1], -0.01574, places=4) # 19 secs + + +if __name__ == '__main__': + unittest.main() diff --git a/percom_moves_collect_2014/displayHelpers.py b/percom_moves_collect_2014/displayHelpers.py new file mode 100644 index 0000000..0a477b2 --- /dev/null +++ b/percom_moves_collect_2014/displayHelpers.py @@ -0,0 +1,115 @@ +import matplotlib.pyplot as plt +import numpy as np + +def showCategoryChart(nameList, countListList, countLabelList, countColorList, ylabel, title, cleanNameDict = None, figsize = None, width=0.35, barLabelSize=None): + N = len(countListList[0]) + print(N) + + ind = np.arange(N) # the x locations for the groups + + if figsize: + fig, ax = plt.subplots(figsize=figsize) + else: + fig, ax = plt.subplots() + + rectList = [] + for i, countList in enumerate(countListList): + # print "Added bar for %s" % countList + currInd = np.arange(len(countList)) + if countColorList != None: + currColor = countColorList[i] + else: + currColor = np.random.rand(3,1) + rectList.append(ax.bar(currInd + i * width, countList, width, color = currColor)) + # rectList.append(ax.bar(ind, countList, width, color = 'r')) + + cleanedNameList = [] + if cleanNameDict: + for name in nameList: + if name in cleanNameDict: + cleanedNameList.append(cleanNameDict[name]) + else: + cleanedNameList.append(name) + else: + cleanedNameList = nameList + + # add some + ax.set_ylabel(ylabel) + ax.set_title(title) + ax.set_xticks(ind+width/2) + # ax.set_xticklabels(cleanedNameList, rotation = 45, rotation_mode = "anchor") + ax.set_xticklabels(cleanedNameList) + + print("len(rectList) = %d, len(countLabelList) = %d" % (len(rectList), len(countLabelList))) + if len(countLabelList) > 1: + if len(countLabelList) > 3: + nCols = len(countLabelList) // 3 + else: + nCols = len(countLabelList) + plt.legend(rectList, countLabelList, loc="best", framealpha=0.3, ncol = nCols + 1) + # ax.legend(rectList, countLabelList) + + def autolabel(rects): + # attach some text labels + for rect in rects: + height = rect.get_height() + ax.text(rect.get_x()+rect.get_width()/2., 1.05*height, '%d'%int(height), + ha='center', va='bottom', size=barLabelSize) + + if not barLabelSize == None: + for rect in rectList: + autolabel(rect) + return (fig, ax) + + +def showHorizCategoryChart(nameList, countListList, countLabelList, countColorList, ylabel, title, cleanNameDict = None, figsize = None, width=0.35, barLabelSize=None): + N = len(countListList[0]) + print(N) + + ind = np.arange(N) # the x locations for the groups + + if figsize: + fig, ax = plt.subplots(figsize=figsize) + else: + fig, ax = plt.subplots() + + rectList = [] + for i, countList in enumerate(countListList): + currInd = np.arange(len(countList)) + rectList.append(ax.barh(currInd + i * width, countList, width, color = countColorList[i])) + # rectList.append(ax.bar(ind, countList, width, color = 'r')) + + cleanedNameList = [] + if cleanNameDict: + for name in nameList: + if name in cleanNameDict: + cleanedNameList.append(cleanNameDict[name]) + else: + cleanedNameList.append(name) + else: + cleanedNameList = nameList + + # add some + ax.set_xlabel(ylabel) + ax.set_title(title) + ax.set_yticks(ind+width/2) + # ax.set_xticklabels(cleanedNameList, rotation = 45, rotation_mode = "anchor") + ax.set_yticklabels(cleanedNameList) + + if len(countLabelList) > 1: + # ax.legend(rectList, countLabelList) + plt.legend(rectList, countLabelList, loc="best", framealpha=0.5) + + def autolabel(rects): + # attach some text labels + for rect in rects: + height = rect.get_height() + bw = rect.get_width() + print(rect.get_y(), rect.get_height(), bw) + ax.text(bw + 0.02 * (ax.get_xlim()[1] - ax.get_xlim()[0]), + rect.get_y()+rect.get_height()/2.,'%d'%int(bw), + ha='left', va='center', size=barLabelSize) + + for rect in rectList: + autolabel(rect) + return (fig, ax) diff --git a/percom_moves_collect_2014/featurecalc.py b/percom_moves_collect_2014/featurecalc.py new file mode 100644 index 0000000..774303a --- /dev/null +++ b/percom_moves_collect_2014/featurecalc.py @@ -0,0 +1,339 @@ + +from __future__ import division +import math +import logging +import numpy as np +from pymongo import MongoClient +import utm +from sklearn.cluster import DBSCAN + +Sections = MongoClient('localhost').Stage_database.Stage_Sections +Modes=MongoClient('localhost').Stage_database.Stage_Modes +# Returns distance in m +def Include_place(lst,place,radius): + # list of tracking points + count=0 + for pnt in lst: + count=count+(1 if calDistance(pnt,place)<=radius else 0) + if count>0: + return True + else: + return False + +def calDistance(point1, point2): + earthRadius = 6371000 + # Point is in GeoJSON format, ie (lng, lat) + dLat = math.radians(point1[1]-point2[1]) + dLon = math.radians(point1[0]-point2[0]) + lat1 = math.radians(point1[1]) + lat2 = math.radians(point2[1]) + + a = (math.sin(dLat/2) ** 2) + ((math.sin(dLon/2) ** 2) * math.cos(lat1) * math.cos(lat2)) + c = 2 * math.atan2(math.sqrt(a), math.sqrt(1-a)) + d = earthRadius * c + + return d + +# The speed is in m/s +def calSpeed(trackpoint1, trackpoint2): + from dateutil import parser + distanceDelta = calDistance(trackpoint1['track_location']['coordinates'], + trackpoint2['track_location']['coordinates']) + timeDelta = parser.parse(trackpoint2['time']) - parser.parse(trackpoint1['time']) + logging.debug("while calculating speed form %s -> %s, distanceDelta = %s, timeDelta = %s" % + (trackpoint1, trackpoint2, distanceDelta, timeDelta)) + if timeDelta.total_seconds() != 0: + return distanceDelta / timeDelta.total_seconds() + else: + return None + +# This formula is from: +# http://www.movable-type.co.uk/scripts/latlong.html +# It returns the heading between two points using +def calHeading(point1, point2): + # points are in GeoJSON format, ie (lng, lat) + phi1 = math.radians(point1[1]) + phi2 = math.radians(point2[1]) + lambda1 = math.radians(point1[0]) + lambda2 = math.radians(point2[0]) + + y = math.sin(lambda2-lambda1) * math.cos(phi2) + x = math.cos(phi1)*math.sin(phi2) - \ + math.sin(phi1)*math.cos(phi2)*math.cos(lambda2-lambda1) + brng = math.degrees(math.atan2(y, x)) + return brng + +def calHC(point1, point2, point3): + HC = calHeading(point2, point3) - calHeading(point1, point2) + return HC + +def calHCR(segment): + trackpoints = segment['track_points'] + if len(trackpoints) < 3: + return 0 + else: + HCNum = 0 + for (i, point) in enumerate(trackpoints[:-2]): + currPoint = point + nextPoint = trackpoints[i+1] + nexNextPt = trackpoints[i+2] + HC = calHC(currPoint['track_location']['coordinates'], nextPoint['track_location']['coordinates'], \ + nexNextPt['track_location']['coordinates']) + if HC >= 15: + HCNum += 1 + segmentDist = segment['distance'] + if segmentDist!= None and segmentDist != 0: + HCR = HCNum/segmentDist + return HCR + else: + return 0 + + +def calSR(segment): + trackpoints = segment['track_points'] + if len(trackpoints) < 2: + return 0 + else: + stopNum = 0 + for (i, point) in enumerate(trackpoints[:-1]): + currPoint = point + nextPoint = trackpoints[i+1] + + currVelocity = calSpeed(currPoint, nextPoint) + if currVelocity != None and currVelocity <= 0.75: + stopNum += 1 + + segmentDist = segment['distance'] + if segmentDist != None and segmentDist != 0: + return stopNum/segmentDist + else: + return 0 + +def calVCR(segment): + trackpoints = segment['track_points'] + if len(trackpoints) < 3: + return 0 + else: + Pv = 0 + for (i, point) in enumerate(trackpoints[:-2]): + currPoint = point + nextPoint = trackpoints[i+1] + nexNextPt = trackpoints[i+2] + velocity1 = calSpeed(currPoint, nextPoint) + velocity2 = calSpeed(nextPoint, nexNextPt) + if velocity1 != None and velocity2 != None: + if velocity1 != 0: + VC = abs(velocity2 - velocity1)/velocity1 + else: + VC = 0 + else: + VC = 0 + + if VC > 0.7: + Pv += 1 + + segmentDist = segment['distance'] + if segmentDist != None and segmentDist != 0: + return Pv/segmentDist + else: + return 0 + +def calSegmentDistance(segment): + return segment['distance'] + +def calSpeeds(segment): + trackpoints = segment['track_points'] + if len(trackpoints) == 0: + return None + + speeds = np.zeros(len(trackpoints) - 1) + for (i, point) in enumerate(trackpoints[:-1]): + currPoint = point + nextPoint = trackpoints[i+1] + currSpeed = calSpeed(currPoint, nextPoint) + if currSpeed != None: + speeds[i] = currSpeed + logging.debug("Returning vector of length %s while calculating speeds for trackpoints of length %s " % (speeds.shape, len(trackpoints))) + return speeds + +def calAvgSpeed(segment): + timeDelta = segment['section_end_datetime'] - segment['section_start_datetime'] + if timeDelta.total_seconds() != 0: + return segment['distance'] / timeDelta.total_seconds() + else: + return None + +# In order to calculate the acceleration, we do the following. +# point0: (loc0, t0), point1: (loc1, t1), point2: (loc2, t2), point3: (loc3, t3) +# becomes +# speed0: ((loc1 - loc0) / (t1 - t0)), speed1: ((loc2 - loc1) / (t2-t1)), +# speed2: ((loc3 - loc2) / (t3 - t2) +# becomes +# segment0: speed0 / (t1 - t0), segment1: (speed1 - speed0)/(t2-t1), +# segment2: (speed2 - speed1) / (t3-t2) + +def calAccels(segment): + from dateutil import parser + + speeds = calSpeeds(segment) + trackpoints = segment['track_points'] + + if speeds == None: + return None + + accel = np.zeros(len(speeds) - 1) + prevSpeed = 0 + for (i, speed) in enumerate(speeds[0:-1]): + currSpeed = speed # speed0 + speedDelta = currSpeed - prevSpeed # (speed0 - 0) + # t1 - t0 + timeDelta = parser.parse(trackpoints[i+1]['time']) - parser.parse(trackpoints[i]['time']) + logging.debug("while calculating accels from %s -> %s, speedDelta = %s, timeDelta = %s" % + (trackpoints[i+1], trackpoints[i], speedDelta, timeDelta)) + if timeDelta.total_seconds() != 0: + accel[i] = speedDelta/(timeDelta.total_seconds()) + # logging.debug("resulting acceleration is %s" % accel[i]) + prevSpeed = currSpeed + return accel + +def getIthMaxSpeed(segment, i): + # python does not appear to have a built-in mechanism for returning the top + # ith max. We would need to write our own, possibly by sorting. Since it is + # not clear whether we ever actually need this (the paper does not explain + # which i they used), we just return the max. + assert(i == 1) + speeds = calSpeeds(segment) + return np.amax(speeds) + +def getIthMaxAccel(segment, i): + # python does not appear to have a built-in mechanism for returning the top + # ith max. We would need to write our own, possibly by sorting. Since it is + # not clear whether we ever actually need this (the paper does not explain + # which i they used), + assert(i == 1) + accels = calAccels(segment) + return np.amax(accels) + +def calSpeedDistParams(speeds): + return (np.mean(speeds), np.std(speeds)) + +# def user_tran_mat(user): +# user_sections=[] +# # print(tran_mat) +# query = {"$and": [{'type': 'move'},{'user_id':user},\ +# {'$or': [{'confirmed_mode':1}, {'confirmed_mode':3},\ +# {'confirmed_mode':5},{'confirmed_mode':6},{'confirmed_mode':7}]}]} +# # print(Sections.find(query).count()) +# for section in Sections.find(query).sort("section_start_datetime",1): +# user_sections.append(section) +# if Sections.find(query).count()>=2: +# tran_mat=np.zeros([Modes.find().count(), Modes.find().count()]) +# for i in range(len(user_sections)-1): +# if (user_sections[i+1]['section_start_datetime']-user_sections[i]['section_end_datetime']).seconds<=60: +# # print(user_sections[i+1]['section_start_datetime'],user_sections[i]['section_end_datetime']) +# fore_mode=user_sections[i]["confirmed_mode"] +# after_mode=user_sections[i+1]["confirmed_mode"] +# tran_mat[fore_mode-1,after_mode-1]+=1 +# row_sums = tran_mat.sum(axis=1) +# new_mat = tran_mat / row_sums[:, np.newaxis] +# return new_mat +# else: +# return None +# +# # all model +# def all_tran_mat(): +# tran_mat=np.zeros([Modes.find().count(), Modes.find().count()]) +# for user in Sections.distinct("user_id"): +# user_sections=[] +# # print(tran_mat) +# query = {"$and": [{'type': 'move'},{'user_id':user},\ +# {'$or': [{'confirmed_mode':1}, {'confirmed_mode':3},\ +# {'confirmed_mode':5},{'confirmed_mode':6},{'confirmed_mode':7}]}]} +# # print(Sections.find(query).count()) +# for section in Sections.find(query).sort("section_start_datetime",1): +# user_sections.append(section) +# if Sections.find(query).count()>=2: +# for i in range(len(user_sections)-1): +# if (user_sections[i+1]['section_start_datetime']-user_sections[i]['section_end_datetime']).seconds<=60: +# # print(user_sections[i+1]['section_start_datetime'],user_sections[i]['section_end_datetime']) +# fore_mode=user_sections[i]["confirmed_mode"] +# after_mode=user_sections[i+1]["confirmed_mode"] +# tran_mat[fore_mode-1,after_mode-1]+=1 +# row_sums = tran_mat.sum(axis=1) +# new_mat = tran_mat / row_sums[:, np.newaxis] +# return new_mat + +def mode_cluster(mode,eps,sam): + mode_change_pnts=[] + # print(tran_mat) + query = {"$and": [{'type': 'move'},\ + {'confirmed_mode':mode}]} + # print(Sections.find(query).count()) + logging.debug("Trying to find cluster locations for %s trips" % (Sections.find(query).count())) + for section in Sections.find(query).sort("section_start_datetime",1): + try: + mode_change_pnts.append(section['section_start_point']['coordinates']) + mode_change_pnts.append(section['section_end_point']['coordinates']) + except: + pass + # print(user_change_pnts) + # print(len(mode_change_pnts)) + if len(mode_change_pnts) == 0: + logging.debug("No points found in cluster input, nothing to fit..") + return np.zeros(0) + + if len(mode_change_pnts)>=1: + # print(mode_change_pnts) + np_points=np.array(mode_change_pnts) + # print(np_points[:,0]) + # fig, axes = plt.subplots(1, 1) + # axes.scatter(np_points[:,0], np_points[:,1]) + # plt.show() + else: + pass + utm_x = [] + utm_y = [] + for row in mode_change_pnts: + # GEOJSON order is lng, lat + utm_loc = utm.from_latlon(row[1],row[0]) + utm_x = np.append(utm_x,utm_loc[0]) + utm_y = np.append(utm_y,utm_loc[1]) + utm_location = np.column_stack((utm_x,utm_y)) + db = DBSCAN(eps=eps,min_samples=sam) + db_fit = db.fit(utm_location) + db_labels = db_fit.labels_ + #print db_labels + new_db_labels = db_labels[db_labels!=-1] + new_location = np_points[db_labels!=-1] + # print len(new_db_labels) + # print len(new_location) + # print new_information + + label_unique = np.unique(new_db_labels) + cluster_center = np.zeros((len(label_unique),2)) + for label in label_unique: + sub_location = new_location[new_db_labels==label] + temp_center = np.mean(sub_location,axis=0) + cluster_center[int(label)] = temp_center + # print cluster_center + return cluster_center + +# +# print(mode_cluster(6)) + +def mode_start_end_coverage(segment,cluster,eps): + mode_change_pnts=[] + # print(tran_mat) + num_sec=0 + centers=cluster + # print(centers) + try: + if Include_place(centers,segment['section_start_point']['coordinates'],eps) and \ + Include_place(centers,segment['section_end_point']['coordinates'],eps): + return 1 + else: + return 0 + except: + return 0 +# print(mode_start_end_coverage(5,105,2)) +# print(mode_start_end_coverage(6,600,2)) diff --git a/percom_moves_collect_2014/mode_inference_percom_july_2014_data.ipynb b/percom_moves_collect_2014/mode_inference_percom_july_2014_data.ipynb new file mode 100644 index 0000000..a643fd7 --- /dev/null +++ b/percom_moves_collect_2014/mode_inference_percom_july_2014_data.ipynb @@ -0,0 +1,2133 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Data caveats\n", + "\n", + "1. This is based on data collected on the UC Berkeley campus in Spring 2014. Unfortunately, due to the sensitive nature of the data collected (location data), the dataset cannot be shared, but the corresponding author can run queries against it and return the aggregate results upon request.\n", + "2. Since the initial results were not run with a fixed random seed, the results in this notebook differ slightly from the published results, but they are generally consistent. And any subsequent results should be identical since this notebook contains a random seed" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import datetime" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We collected some more training data after this, but it was not included in these results.\n", + "So let us read the data from the backup database to ensure consistency with the published results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import pymongo" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "Sections = pymongo.MongoClient('localhost').Backup_database.Stage_Sections" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "Sections.find({'type': 'move'}).count()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import scipy as sp\n", + "np.random.seed(61297777)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "confirmedSections = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}]})" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "walkSections = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': 1}]})" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import json" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "modeList = json.load(open(\"modes.json\"))\n", + "print(modeList)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}]}).count())\n", + "modeNameList = []\n", + "modeCountList = []\n", + "for mode in modeList:\n", + " modeCount = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': mode['mode_id']}]}).count()\n", + " print(\"%s, %s\" % (mode['mode_name'], modeCount))\n", + " if modeCount > 0:\n", + " modeNameList.append(mode['mode_name'])\n", + " modeCountList.append(modeCount)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "import matplotlib.image as mpimg\n", + "import matplotlib as mpl\n", + "\n", + "%matplotlib inline\n", + "%config InlineBackend.figure_format='png'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import displayHelpers" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "cleanModeNames = {\"walking\":\"walk\", \"running\":\"run\", \"cycling\":\"cycle\"}\n", + "(fig, ax) = displayHelpers.showCategoryChart(modeNameList, [modeCountList], ['Confirmed'], ['r'],\n", + " \"Number of trip sections\", \"Trip sections by mode\", \n", + " cleanNameDict = cleanModeNames, figsize=(12,5))\n", + "ax.set_ylim(top=4000)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "startTimes = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}]}, {'section_start_datetime': 1, '_id': 0}).sort('section_start_datetime', pymongo.ASCENDING)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "nSections = startTimes.count()\n", + "print(\"Starting from %s\" % startTimes[0])\n", + "print(\"Ending at %s\" % startTimes[nSections-1])\n", + "startTime = startTimes[0]['section_start_datetime']\n", + "endTime = startTimes[nSections-1]['section_start_datetime']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from datetime import datetime, timedelta" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "timeNameList = []\n", + "timeCountList = []\n", + "timeTotalList = []\n", + "currTime = startTime\n", + "while currTime < endTime:\n", + " currEndTime = currTime + timedelta(days=30)\n", + " if currEndTime > endTime:\n", + " currEndTime = endTime\n", + " currTimeSearch = {'section_start_datetime': {\"$gte\": currTime, \"$lte\": currEndTime}}\n", + " nTrips = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, currTimeSearch]}, {'section_start_datetime': 1, '_id': 0}).count()\n", + " nTotalTrips = Sections.find({\"$and\": [{'type': 'move'}, currTimeSearch]}, {'section_start_datetime': 1, '_id': 0}).count()\n", + " print(\"%s - %s = %s, %s\" % (currTime.strftime(\"%m-%d\"), currEndTime, nTrips, nTotalTrips))\n", + " timeNameList.append(\"%s to %s\" % (currTime.strftime(\"%b-%d\"), currEndTime.strftime(\"%b-%d\")))\n", + " timeCountList.append(nTrips)\n", + " timeTotalList.append(nTotalTrips)\n", + " currTime = currEndTime" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "(fig, ax) = displayHelpers.showCategoryChart(timeNameList[:-1], [timeCountList[:-1], timeTotalList[:-1]],\n", + " [\"Confirmed\", \"Total\"], ['r', 'b'], \n", + " \"Number of trip sections\", \"Trip sections by start time\", figsize=(12,5))\n", + "# ax.set_ylim(top=5500)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "timeNameList = []\n", + "timeCountList = []\n", + "timeTotalList = []\n", + "currTime = datetime(year=2014,month=5,day=6)\n", + "while currTime < endTime:\n", + " currTimeSearch = {'section_start_datetime': {\"$lte\": currTime}}\n", + " nTrips = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, currTimeSearch]}, {'section_start_datetime': 1, '_id': 0}).count()\n", + " nTotalTrips = Sections.find({\"$and\": [currTimeSearch]}, {'section_start_datetime': 1, '_id': 0}).count()\n", + " print(\"%s = %s, %s\" % (currTime.strftime(\"%m-%d\"), nTrips, nTotalTrips))\n", + " timeNameList.append(\"%s\" % (currTime.strftime(\"%b-%d\")))\n", + " timeCountList.append(nTrips)\n", + " timeTotalList.append(nTotalTrips)\n", + " currTime = currTime + timedelta(days=7)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "idList = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}]}).distinct('user_id')\n", + "idNameList = []\n", + "idCountList = []\n", + "confirmedCountList = []\n", + "for i, id in enumerate(idList):\n", + " count = Sections.find({\"$and\": [{'type': 'move'}, {'user_id': id}]}).count()\n", + " confirmedCount = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, {'user_id': id}]}).count()\n", + " print(id, count, confirmedCount)\n", + " idNameList.append(\"%s\" % i)\n", + " idCountList.append(count)\n", + " confirmedCountList.append(confirmedCount)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "fig, axes = displayHelpers.showCategoryChart(idNameList, [confirmedCountList, idCountList],\n", + " [\"Confirmed Sections\", \"Total Sections\"],\n", + " ['r', 'b'], \"Number of trip sections\", \"Trip sections by user\", figsize=(12,5))\n", + "oldSize = mpl.rcParams['font.size']\n", + "mpl.rcParams['font.size'] = 16\n", + "labels = range(0, len(idNameList), 5)\n", + "axes.set_xticks(labels)\n", + "axes.set_xticklabels(np.array(idNameList)[labels])\n", + "fig.show()\n", + "mpl.rcParams['font.size'] = oldSize" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mpl.rcParams" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from featurecalc import calDistance, calSpeed, calHeading, calAvgSpeed, calSpeeds, calAccels, getIthMaxSpeed, getIthMaxAccel, calHCR,\\\n", + "calSR, calVCR, mode_cluster, mode_start_end_coverage" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def getSpeedsForMode(modeId):\n", + " modeSectionCursor = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': modeId}]})\n", + " speedList = []\n", + " for section in modeSectionCursor:\n", + " speeds = calSpeeds(section)\n", + " if speeds != None:\n", + " # currHistogram = sp.histogram(speeds)\n", + " speedList.append(speeds)\n", + " return speedList" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Feature matrix construction" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Features are:\n", + "# 0. distance\n", + "# 1. duration\n", + "# 2. first filter mode\n", + "# 3. sectionId\n", + "# 4. avg speed\n", + "# 5. speed EV\n", + "# 6. speed variance\n", + "# 7. max speed\n", + "# 8. max accel\n", + "# 9. isCommute\n", + "# 10. heading change rate (currently unfilled)\n", + "# 11. stop rate (currently unfilled)\n", + "# 12. velocity change rate (currently unfilled)\n", + "# 13. start lat\n", + "# 14. start lng\n", + "# 15. stop lat\n", + "# 16. stop lng\n", + "# 17. start hour\n", + "# 18. end hour\n", + "# 19. both start and end close to bus stop\n", + "# 20. both start and end close to train station\n", + "# 21. both start and end close to airport\n", + "featureLabels = [\"distance\", \"duration\", \"first filter mode\", \"sectionId\", \"avg speed\",\n", + " \"speed EV\", \"speed variance\", \"max speed\", \"max accel\", \"isCommute\",\n", + " \"heading change rate\", \"stop rate\", \"velocity change rate\", \"start lat\", \"start lng\",\n", + " \"stop lat\", \"stop lng\", \"start hour\", \"end hour\", \"close to bus stop\", \"close to train stop\",\n", + " \"close to airport\"]\n", + "bus_cluster=mode_cluster(5,105,1)\n", + "train_cluster=mode_cluster(6,600,1)\n", + "air_cluster=mode_cluster(9,600,1)\n", + "def generateFeatureMatrixAndResultVector(sectionQuery):\n", + " confirmedSections = Sections.find(sectionQuery)\n", + " featureMatrix = np.zeros([confirmedSections.count(), len(featureLabels)])\n", + " resultVector = np.zeros(confirmedSections.count())\n", + " for (i, section) in enumerate(confirmedSections):\n", + " featureMatrix[i, 0] = section['distance']\n", + " featureMatrix[i, 1] = (section['section_end_datetime'] - section['section_start_datetime']).total_seconds()\n", + " \n", + " # Deal with unknown modes like \"airplane\"\n", + " try:\n", + " featureMatrix[i, 2] = section['mode']\n", + " except ValueError:\n", + " featureMatrix[i, 2] = 0\n", + " \n", + " featureMatrix[i, 3] = section['section_id']\n", + " featureMatrix[i, 4] = calAvgSpeed(section)\n", + " speeds = calSpeeds(section)\n", + " if speeds != None:\n", + " featureMatrix[i, 5] = np.mean(speeds)\n", + " featureMatrix[i, 6] = np.std(speeds)\n", + " featureMatrix[i, 7] = np.max(speeds)\n", + " else:\n", + " # They will remain zero\n", + " pass\n", + " accels = calAccels(section)\n", + " if accels != None and len(accels) > 0:\n", + " featureMatrix[i, 8] = np.max(accels)\n", + " else:\n", + " # They will remain zero\n", + " pass\n", + " featureMatrix[i, 9] = ('commute' in section) and (section['commute'] == 'to' or section['commute'] == 'from')\n", + " featureMatrix[i, 10] = calHCR(section)\n", + " featureMatrix[i, 11] = calSR(section)\n", + " featureMatrix[i, 12] = calVCR(section)\n", + " if section['section_start_point'] != None:\n", + " startCoords = section['section_start_point']['coordinates']\n", + " featureMatrix[i, 13] = startCoords[0]\n", + " featureMatrix[i, 14] = startCoords[1]\n", + " \n", + " if section['section_end_point'] != None:\n", + " endCoords = section['section_end_point']['coordinates']\n", + " featureMatrix[i, 15] = endCoords[0]\n", + " featureMatrix[i, 16] = endCoords[1]\n", + " \n", + " featureMatrix[i, 17] = section['section_start_datetime'].time().hour\n", + " featureMatrix[i, 18] = section['section_end_datetime'].time().hour\n", + " \n", + " featureMatrix[i, 19] = mode_start_end_coverage(section,bus_cluster,105)\n", + " featureMatrix[i, 20] = mode_start_end_coverage(section,train_cluster,600)\n", + " featureMatrix[i, 21] = mode_start_end_coverage(section,air_cluster,600)\n", + " resultVector[i] = section['confirmed_mode']\n", + " return (featureMatrix, resultVector)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "(featureMatrix, resultVector) = generateFeatureMatrixAndResultVector({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}]})\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(np.max(featureMatrix[:,10]))\n", + "print(np.max(featureMatrix[:,20]))\n", + "print(np.max(featureMatrix[:,12]))\n", + "print(featureMatrix.shape, resultVector.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "runIndices = resultVector == 2\n", + "transportIndices = resultVector == 4\n", + "mixedIndices = resultVector == 8\n", + "airIndices = resultVector == 9\n", + "unknownIndices = resultVector == 0\n", + "strippedIndices = np.logical_not(runIndices | transportIndices | mixedIndices)\n", + "print(\"runIndices = %s\" % (np.nonzero(runIndices)))\n", + "print(\"transportIndices = %s\" % (np.nonzero(transportIndices)))\n", + "print(\"mixedIndices = %s\" % (np.nonzero(mixedIndices)))\n", + "print(\"airIndices = %s\" % (np.nonzero(airIndices)))\n", + "print(\"unknownIndices = %s\" % (np.nonzero(unknownIndices)))\n", + "print(\"strippedIndices count = %s\" % (np.count_nonzero(strippedIndices)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, we filter out \"mixed\" and \"running\", since there are few instances of them and we don't intend to predict them initially. We also filter out any \"transport\" since it should never be in the confirmed set, and we don't want to deal with it if it is." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "strippedFeatureMatrix = featureMatrix[strippedIndices]\n", + "strippedResultVector = resultVector[strippedIndices]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "First, we visualize the distribution of some of the features. This is so that we can compare our dataset to Zheng et al 2010." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def plotFeatureVector(featureMatrix, resultVector, featureIndex, modeList):\n", + " avgSpeedFig, avgSpeedAxes = plt.subplots(1,1)\n", + " currModeSpeedsList = []\n", + " currModeNamesList = []\n", + " for mode in modeList:\n", + " currModeMask = resultVector == mode['mode_id']\n", + " currModeSpeeds = featureMatrix[currModeMask, featureIndex]\n", + " # print \"For mode %s, shape is %s\" % (mode['mode_id'], str(currModeSpeeds.shape))\n", + " if np.count_nonzero(currModeMask) != 0:\n", + " currModeNamesList.append(mode['mode_name'])\n", + " currModeSpeedsList.append(currModeSpeeds)\n", + " avgSpeedAxes.hist(currModeSpeedsList, normed=True, histtype=\"bar\", label=currModeNamesList)\n", + " avgSpeedAxes.set_ylabel(\"number of segments\")\n", + " avgSpeedAxes.set_xlabel(featureLabels[featureIndex])\n", + " plt.legend()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for col in range(0, len(featureLabels)):\n", + " plotFeatureVector(strippedFeatureMatrix, strippedResultVector, col, modeList)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The air modes are such outliers that we are unable to see the variation in the other modes. Let's strip out the outliers and focus on lower speed trips." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "speedNormalEntries = strippedFeatureMatrix[:,4] < 50\n", + "plotFeatureVector(strippedFeatureMatrix[speedNormalEntries], strippedResultVector[speedNormalEntries], 4, modeList)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Using the graphs above, we can estimate the separability of our input. Clearly, there is some separability - the car and train trips that are at 20-30+ are clearly separable from the walk/bike trips that are at lower speeds. But are they separable from each other? And at least eyeballing the data, it looks like at least 75% of car trips are actually not that fast - the mean EV is < 10mph. Even with max speed, at least 25% of car trips appear to have a max speed ~ 10 mph. Max accel doesn't seem to have as much predictive power as one might hope - most max accel clusters at less than 5. It would be nice to visualize the clusters in this data, but I'm just going to start trying decision trees and SVMs on this data now." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We used to strip out outliers here, but the outliers actually correspond to plane trips, so we want to retain them. The rest of the code assumes that we stripped outliers to get \"cleaned\" trips, so we just reassign the values here instead of changing all the code. We can restore outlier detection at that point." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "cleanedFeatureMatrix = strippedFeatureMatrix\n", + "cleanedResultVector = strippedResultVector" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Feature Indices" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "genericFeatureIndices = list(range(0,10))\n", + "AdvancedFeatureIndices = list(range(10,13))\n", + "LocationFeatureIndices = list(range(13,17))\n", + "TimeFeatureIndices = list(range(17,19))\n", + "BusTrainFeatureIndices = list(range(19,22))\n", + "print(genericFeatureIndices)\n", + "print(AdvancedFeatureIndices)\n", + "print(LocationFeatureIndices)\n", + "print(TimeFeatureIndices)\n", + "print(BusTrainFeatureIndices)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Generic model, generic features" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "genericCleanedFM = cleanedFeatureMatrix[:,genericFeatureIndices]\n", + "print(genericCleanedFM.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn import cross_validation\n", + "from sklearn import svm" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "svmClf = svm.LinearSVC()\n", + "svmScores = cross_validation.cross_val_score(svmClf, genericCleanedFM, cleanedResultVector, cv=5)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(svmScores)\n", + "print(svmScores.mean())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Using svm.SVC() takes significantly longer (hours instead of seconds) but generates higher accuracy. The accuracy is still lower than the random forest, though." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn import ensemble" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "forestScores = cross_validation.cross_val_score(forestClf, genericCleanedFM, cleanedResultVector, cv=5)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(forestScores)\n", + "print(forestScores.mean())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "These results look pretty good, and pretty much parallel what the Zheng paper got, even with just the basic features. We get 82% average accuracy for a linear SVM and 86% average accuracy for a random forest. But the 82% and 86% values are for cross validation, where we have a known value that we can validate against.\n", + "\n", + "But what we really want to do is to decide, while looking at a section that we have no ground truth on, whether we want the user to classify it or not. And then we want to see, for the high confidence predictions that we will not prompt the user for, how accurate our classification really is.\n", + "\n", + "In order to do this, we get the probabilities for each prediction in addition to the prediction itself. We can then test the accuracy of the high confidence predictions and compare it to the accuracy of all predictions.\n", + "\n", + "To recap, we now return three metrics:\n", + "\n", + "- The number of entries that would be autoclassified given a particular target confidence interval\n", + "- The accuracy of the entries that would be autoclassified\n", + "- The accuracy of all entries, including ones that had low confidence" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Generate folds of indices\n", + "def generateFoldArrays(nIndices, nFolds):\n", + " currPermutation = np.random.permutation(nIndices)\n", + " currPermutationParts = np.array_split(currPermutation, nFolds)\n", + " \n", + " foldArrays = []\n", + " for i in range(0, nFolds):\n", + " testIndices = currPermutationParts[i]\n", + " trainIndicesParts = [currPermutationPart for (j, currPermutationPart) in enumerate(currPermutationParts) if j != i]\n", + " trainIndices = np.concatenate(trainIndicesParts)\n", + " foldArrays.append((trainIndices, testIndices))\n", + " return foldArrays\n", + "\n", + "def kFoldValidationWithProb(algo, X, y, nFolds, prob_threshold):\n", + " foldArrays = generateFoldArrays(len(y), nFolds)\n", + " \n", + " scores = []\n", + " highConfidenceScores = []\n", + " percentAutoClassified = []\n", + " percentAutoClassifiedByMode = []\n", + " for (trainIndices, testIndices) in foldArrays:\n", + " # print testIndices[0]\n", + " model = algo.fit(X[trainIndices], y[trainIndices])\n", + " testX = X[testIndices]\n", + " testy = y[testIndices]\n", + " \n", + " predictedY = model.predict(testX)\n", + " if hasattr(algo, \"decision_function\"):\n", + " predictedYProb = algo.decision_function(testX)\n", + " else:\n", + " predictedYProb = algo.predict_proba(testX)\n", + " \n", + " # print (\"predictedY.shape = %s, predictedYProb.shape = %s\" %\n", + " # (str(predictedY.shape), str(predictedYProb.shape)))\n", + " \n", + " # As we can see below, we take the max confidence along the first axis\n", + " highConfidencePredictions = np.max(predictedYProb, 1) > prob_threshold\n", + " print(\"Found %s high confidence predictions out of %s\" % (np.count_nonzero(highConfidencePredictions),\n", + " len(testIndices)))\n", + " \n", + " cmc = lambda m:np.count_nonzero(testy[highConfidencePredictions] == m)\n", + " \n", + " # Let us see how many of each mode were autoclassified\n", + " # print(\"Autoclassifications split by confirmed modes: walk: %s, bike: %s, bus: %s, train: %s, car: %s\" %\n", + " # (cmc(1), cmc(3), cmc(5), cmc(6), cmc(7)))\n", + " \n", + " pcmc = lambda m: float(np.count_nonzero(testy[highConfidencePredictions] == m))/np.count_nonzero(testy == m) if ((np.count_nonzero(testy == m) != 0)) else 0 \n", + " # Let us see what percentage of each mode was autoclassified\n", + " # print(\"For threshold %s, autoclassifications split by confirmed mode percents: walk: %s, bike: %s, bus: %s, train: %s, car: %s\" %\n", + " # (prob_threshold, pcmc(1), pcmc(3), pcmc(5), pcmc(6), pcmc(7)))\n", + " \n", + " percentAutoClassified.append(float(np.count_nonzero(highConfidencePredictions))/len(testIndices))\n", + " percentAutoClassifiedByMode.append([pcmc(1), pcmc(3), pcmc(5), pcmc(6), pcmc(7), pcmc(9)])\n", + " \n", + " # so now we are going to generate two scores.\n", + " # the first is the score on only the high confidence predictions\n", + " highConfidenceScore = model.score(testX[highConfidencePredictions], testy[highConfidencePredictions])\n", + " highConfidenceScores.append(highConfidenceScore)\n", + " \n", + " score = model.score(X[testIndices], y[testIndices])\n", + " scores.append(score)\n", + " # print scores\n", + " \n", + " print(\"for prob %s, percentage auto classified %s\" % (prob_threshold, np.array(percentAutoClassified).mean()))\n", + " print(\"for prob %s, scoring only on high confidence predictions %s\" % (prob_threshold, np.array(highConfidenceScores).mean()))\n", + " print(\"for prob %s, scoring on all predictions %s\" % (prob_threshold, np.array(scores).mean()))\n", + "\n", + " return (np.array(percentAutoClassified), np.array(percentAutoClassifiedByMode), np.array(highConfidenceScores), np.array(scores))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def exploreKFoldValidationSpace(algo, X, y, nFolds):\n", + " (pac0, pacm0, hcs0, s0) = kFoldValidationWithProb(algo, X, y, nFolds, 0.90) \n", + " (pac5, pacm5, hcs5, s5) = kFoldValidationWithProb(algo, X, y, nFolds, 0.95)\n", + " (pac9, pacm9, hcs9, s9) = kFoldValidationWithProb(algo, X, y, nFolds, 0.99)\n", + " \n", + " probs = [0.90, 0.95, 0.99]\n", + " pacs = [pac0.mean(), pac5.mean(), pac9.mean()]\n", + " hcs = [hcs0.mean(), hcs5.mean(), hcs9.mean()]\n", + " ss = [s0.mean(), s5.mean(), s9.mean()]\n", + " \n", + " pacmWalk = [pacm0[:,0].mean(), pacm5[:,0].mean(), pacm9[:,0].mean()]\n", + " pacmBike = [pacm0[:,1].mean(), pacm5[:,1].mean(), pacm9[:,1].mean()]\n", + " pacmBus = [pacm0[:,2].mean(), pacm5[:,2].mean(), pacm9[:,2].mean()]\n", + " pacmTrain = [pacm0[:,3].mean(), pacm5[:,3].mean(), pacm9[:,3].mean()]\n", + " pacmCar = [pacm0[:,4].mean(), pacm5[:,4].mean(), pacm9[:,4].mean()]\n", + " pacmAir = [pacm0[:5].mean(), pacm5[:,5].mean(), pacm9[:,4].mean()]\n", + " \n", + " fig, axes = plt.subplots(1, 1, figsize=(15, 10))\n", + " print(pacs)\n", + " axes.set_yticks(np.arange(0,1,0.1))\n", + " axes.plot(probs, pacs, label=\"percentage auto classified\")\n", + " \n", + " print(pacmWalk)\n", + " axes.plot(probs, pacmWalk, linewidth = 5, label=\"percent walk auto classified\")\n", + " print(pacmBike)\n", + " axes.plot(probs, pacmBike, label=\"percent bike auto classified\")\n", + " print(pacmBus)\n", + " axes.plot(probs, pacmBus, linewidth=5, label=\"percent bus auto classified\")\n", + " print(pacmTrain)\n", + " axes.plot(probs, pacmTrain, label=\"percent train auto classified\")\n", + " print(pacmCar)\n", + " axes.plot(probs, pacmCar, linewidth=5, label=\"percent car auto classified\")\n", + " print(pacmAir)\n", + " axes.plot(probs, pacmAir, linewidth=5, label = \"percent air auto classified\")\n", + " \n", + " print(hcs)\n", + " axes.plot(probs, hcs, label=\"accuracy of high confidence samples\")\n", + " print(ss)\n", + " axes.plot(probs, ss, linewidth = 5, label=\"accuracy of all samples\")\n", + " plt.legend(loc='best')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, genericCleanedFM, cleanedResultVector, 5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The results of these three metrics for confidence intervals of 90%, 95% and 99% are shown above, and they are all largely similar. The accuracy of the high confidence predictions is, as expected, really high at 97 - 98%. However, we were only able to auto-classify ~ 50% of the sections. Now, let's retry using the linear SVM above." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "svmClf = svm.LinearSVC()\n", + "exploreKFoldValidationSpace(svmClf, genericCleanedFM, cleanedResultVector, 5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We see that the SVM is able to classify more trips than the decision tree, but at the cost of unacceptably lower performance on the high confidence predictions. It is hard to understand the results with line plots, let's switch to bar graphs instead." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def exploreKFoldValidationSpaceBarGraph(algo, X, y, nFolds):\n", + " (pac0, pacm0, hcs0, s0) = kFoldValidationWithProb(algo, X, y, nFolds, 0.90) \n", + " (pac5, pacm5, hcs5, s5) = kFoldValidationWithProb(algo, X, y, nFolds, 0.95)\n", + " (pac9, pacm9, hcs9, s9) = kFoldValidationWithProb(algo, X, y, nFolds, 0.99)\n", + " \n", + " probs = [0.90, 0.95, 0.99]\n", + " pacs = [pac0.mean() * 100, pac5.mean() * 100, pac9.mean() * 100]\n", + " hcs = [hcs0.mean() * 100, hcs5.mean() * 100, hcs9.mean() * 100]\n", + " ss = [s0.mean() * 100, s5.mean() * 100, s9.mean() * 100]\n", + " \n", + " mpl.rcParams['font.size'] = 16\n", + " fig, axes = displayHelpers.showCategoryChart([\"90%\", \"95%\", \"99%\"], [pacs, hcs, ss],\n", + " [\"% high confidence\", \"high confidence accuracy\", \"overall accuracy\"],\n", + " ['r', 'g', 'b'], \"Percent\", \"High confidence predictions\",\n", + " width=0.15, figsize=(6,5))\n", + " axes.set_yticks(range(0, 100, 10))\n", + " axes.axhline(50, label = \"50%\")\n", + " axes.axhline(90, label = \"90%\")\n", + " # axes.get_legend().set_bbox_\n", + " axes.set_ylim(top=100)\n", + " fig.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpaceBarGraph(forestClf, cleanedFeatureMatrix, cleanedResultVector, 5)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "svmClf = svm.LinearSVC()\n", + "exploreKFoldValidationSpaceBarGraph(svmClf, cleanedFeatureMatrix, cleanedResultVector, 5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We now get the most important params for the decision tree so that we can better understand what it is doing." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "forestClf.get_params()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for (i, importance) in enumerate(forestClf.feature_importances_):\n", + " print(featureLabels[i], importance)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "So the highest importance features are:\n", + "\n", + "- first filter mode (moves mode)\n", + "- speed EV\n", + "- avg speed\n", + "- distance" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, let's try another non-parametric method like nearest neighbor" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn import neighbors" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "knnClf = neighbors.KNeighborsClassifier()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "exploreKFoldValidationSpace(knnClf, cleanedFeatureMatrix, cleanedResultVector, 5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "knn does almost the same as decision tree, except that the accuracy of the high confidence predictions is a bit lower.\n", + "I think that the percentages are around the same as well. Basically, we can classify walk pretty well and the others pretty poorly.\n", + "So I am not sure what we are adding here over moves :)\n", + "\n", + "I'm surprised at the low prediction rate for cycling. Moves seems to get that pretty accurately for me.\n", + "\n", + "I'm now going to plot this data and see what it looks like." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Advanced features added" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "Advanced_indices=[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18]\n", + "print(Advanced_indices)\n", + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,Advanced_indices], cleanedResultVector, 5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Spatial knowledge added" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "Spatial_indices=[0,1,2,3,4,5,6,7,8,9,13,14,15,16,17,18,19,20]\n", + "print(Spatial_indices)\n", + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,Spatial_indices], cleanedResultVector, 5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Location and time features added" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix, cleanedResultVector, 5)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "knnClf = neighbors.KNeighborsClassifier()\n", + "exploreKFoldValidationSpace(knnClf, cleanedFeatureMatrix, cleanedResultVector, 5)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for (i, importance) in enumerate(forestClf.feature_importances_):\n", + " print(featureLabels[i], importance)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Some more contour plots to help us visualize the data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from matplotlib import colors\n", + "import itertools" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def printColorMap(algo, Xall, y):\n", + " # we want to split roughly into roughly 10-20 sections\n", + " nSplits = 20\n", + " \n", + " # setup parameters\n", + " cmap_light = colors.ListedColormap(['#FAAAAA', '#AFAAAA', '#AAFAAA', '#AAAFAA', '#AAAAFA', '#AAAAAF'])\n", + " cmap_bold = colors.ListedColormap(['#F00000', '#0F0000', '#00F000', '#000F00', '#0000F0', '#00000F'])\n", + " \n", + " # nFeatures = Xall.shape[1]\n", + " nFeatures = 10\n", + " fig, axes = plt.subplots(20, 5, figsize=(15,50))\n", + " plt.tight_layout()\n", + " axesArr = axes.flatten()\n", + " \n", + " i = 0\n", + " for selCombo in itertools.product(np.arange(nFeatures), np.arange(nFeatures)):\n", + " if selCombo[0] == selCombo[1]:\n", + " continue\n", + " # print(\"Generating grid for combo %s,%s in slot %s\" % (featureLabels[selCombo[0]], featureLabels[selCombo[1]], i))\n", + " \n", + " selMask = np.zeros(Xall.shape[1])\n", + " # Otherwise, we won't be able to plot it properly below\n", + " assert(len(selCombo) == 2)\n", + " selMask[selCombo[0]] = 1\n", + " selMask[selCombo[1]] = 1\n", + " \n", + " X = Xall[:,selMask == 1]\n", + " \n", + " algo.fit(X, y)\n", + " # Plot the decision boundary. For that, we will assign a color to each\n", + " # point in the mesh [x_min, m_max]x[y_min, y_max].\n", + " x_min, x_max = X[:, 0].min() - 1, X[:, 0].max() + 1\n", + " y_min, y_max = X[:, 1].min() - 1, X[:, 1].max() + 1\n", + " # we want to split roughly into \n", + " h_x = float(x_max - x_min) / nSplits\n", + " h_y = float(y_max - y_min) / nSplits\n", + " \n", + " xx, yy = np.meshgrid(np.arange(x_min, x_max, h_x),\n", + " np.arange(y_min, y_max, h_y))\n", + " Z = algo.predict(np.c_[xx.ravel(), yy.ravel()])\n", + " \n", + " # Put the result into a color plot\n", + " Z = Z.reshape(xx.shape)\n", + "\n", + " axesArr[i].pcolormesh(xx, yy, Z, cmap=cmap_light)\n", + "\n", + " # Plot also the training points\n", + " axesArr[i].scatter(X[:, 0], X[:, 1], c=y, cmap=cmap_bold)\n", + " # plt.scatter(X[:, 0], X[:, 1], c=y)\n", + " axesArr[i].set_xlim(xx.min(), xx.max())\n", + " axesArr[i].set_ylim(yy.min(), yy.max())\n", + " axesArr[i].set_title(\"%s v/s %s\" % (featureLabels[selCombo[0]], featureLabels[selCombo[1]]))\n", + " # axesArr[i].legend(loc='best')\n", + " i = i+1 " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "printColorMap(forestClf, cleanedFeatureMatrix, cleanedResultVector)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let us also quickly take a look at the confusion matrix for the overall model. Because maybe we should not care about the confidence of the predictions, and just weight them lower." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn import metrics\n", + "from matplotlib import cm" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def printConfusionMatrix(algo, X, y, title):\n", + " skf = cross_validation.StratifiedKFold(y, 5)\n", + " nClasses = np.count_nonzero(np.unique(y))\n", + " print(\"nClasses = %s\" % nClasses)\n", + " sumPCM = np.zeros([nClasses, nClasses])\n", + " for train, test in skf:\n", + " X_train, X_test, y_train, y_test = X[train], X[test], y[train], y[test]\n", + " print(\"Number of distinct classes in training set = %s, test set = %s\" % (np.unique(y[train]), np.unique(y[test])))\n", + " y_pred = algo.fit(X_train, y_train).predict(X_test)\n", + " # This has the raw number of entries (e.g. [610 12 1 0 32 1])\n", + " # Since the total number of entries for each mode is different, we want to convert this to a percentage\n", + " cmraw = metrics.confusion_matrix(y_test, y_pred)\n", + " # We do that by summing up the entries for each mode (e.g. 656)\n", + " sumArr = np.sum(cmraw, axis=1)\n", + " # and repeating it across the row (e.g. [656 656 656 656 656 656])\n", + " repeatedSumArr = np.repeat(sumArr, cmraw.shape[1]).reshape(cmraw.shape)\n", + " # And dividing the raw numbers by the sums to get percentages (e.g [92.98 1.82 0 4.87 0.15])\n", + " sumPCM = np.add(sumPCM, np.divide(cmraw.astype(float), repeatedSumArr))\n", + " \n", + " finalPCM = sumPCM / 5\n", + " logFinalPCM = np.log(finalPCM + 1)\n", + " np.set_printoptions(precision=0, suppress=True)\n", + " # np.set_printoptions(precision=4, suppress=False)\n", + " print(finalPCM * 100)\n", + "\n", + " oldSize = mpl.rcParams['font.size']\n", + " mpl.rcParams['font.size'] = 16\n", + " (fig, ax) = plt.subplots()\n", + " # First element is \"\" because of http://stackoverflow.com/questions/3529666/matplotlib-matshow-labels\n", + " ax.set_xticklabels([\"\",\"walk\", \"\", \"bus\", \"\", \"car\", \"\"])\n", + " ax.set_yticklabels([\"\",\"walk\", \"cycle\", \"bus\", \"train\", \"car\", \"air\"])\n", + " cax = ax.matshow(logFinalPCM, cmap=cm.gray)\n", + " ax.set_title(title, color='green', weight='bold', size=16, y=1.1)\n", + " \n", + " fig.colorbar(cax)\n", + " ax.set_ylabel('True label', size=\"large\")\n", + " ax.set_xlabel('Predicted label', size=\"large\")\n", + " fig.tight_layout()\n", + " plt.show()\n", + " return (finalPCM, fig)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Model selection" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "modelCMList = []\n", + "saveDir = \"/tmp/ml_results/\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import os\n", + "os.makedirs(saveDir, exist_ok=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "printConfusionMatrix(forestClf, genericCleanedFM, cleanedResultVector, \"Generic features, random forest\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,Spatial_indices], cleanedResultVector, \"Spatial Features, random forest\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix, cleanedResultVector, \"All features, random forest\")\n", + "fig.savefig(saveDir+\"cm_all_random_forest.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Adding start and end points does improve the accuracy of the bus and train. Train trips in particular, are significantly improved." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "knnClf = neighbors.KNeighborsClassifier()\n", + "printConfusionMatrix(knnClf, genericCleanedFM, cleanedResultVector, \"Generic features, k-nn\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "knnClf = neighbors.KNeighborsClassifier()\n", + "currCM, fig = printConfusionMatrix(knnClf, cleanedFeatureMatrix, cleanedResultVector, \"All features, k-nn\")\n", + "fig.savefig(saveDir+\"cm_all_k_nn.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "knn does significantly worse, primarily because of bus trips. I suspect this is because different people make the same trip using different modes. Time for per-user trips?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "svmClf = svm.LinearSVC()\n", + "currCM, fig = printConfusionMatrix(svmClf, cleanedFeatureMatrix, cleanedResultVector, \"All features, Linear SVM\")\n", + "fig.savefig(saveDir+\"cm_all_linear_svm.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For parametric models, it is particularly import to tune the parameters correctly. We use the grid_search function from sklearn to find the correct parameters for SVC." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.grid_search import GridSearchCV\n", + "from sklearn.metrics import classification_report" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "First, we do some coarse tuning on the parameters." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "tuned_parameters = [{'C': [0.01, 0.1, 1, 10, 100, 1000],\n", + " 'dual': [True, False],\n", + " 'class_weight' : [None, 'auto']}]\n", + "baseClf = svm.LinearSVC()\n", + "clf = GridSearchCV(baseClf, tuned_parameters, cv=5)\n", + "clf.fit(cleanedFeatureMatrix, cleanedResultVector)\n", + "clf.get_params\n", + "clf.best_estimator_" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Then, we do some fine tuning around the result of the coarse parameter tuning." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "tuned_parameters = [{'C': list(range(75, 125, 5))}]\n", + "baseClf = svm.LinearSVC()\n", + "clf = GridSearchCV(baseClf, tuned_parameters, cv=5)\n", + "clf.fit(cleanedFeatureMatrix, cleanedResultVector)\n", + "print(clf.get_params)\n", + "print(clf.best_estimator_)\n", + "print(clf.best_score_)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "tuned_parameters = [{'C': list(range(55, 125, 5))}]\n", + "baseClf = svm.LinearSVC(dual=False)\n", + "clf = GridSearchCV(baseClf, tuned_parameters, cv=5)\n", + "clf.fit(cleanedFeatureMatrix, cleanedResultVector)\n", + "print(clf.get_params)\n", + "print(clf.best_estimator_)\n", + "print(clf.best_score_)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "tunedSvmClf = svm.LinearSVC(C=80, dual=False)\n", + "currCM, fig = printConfusionMatrix(tunedSvmClf, cleanedFeatureMatrix, cleanedResultVector, \"All features, SVM(C=80,dual=F)\")\n", + "fig.savefig(saveDir+\"cm_all_tuned_svm.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.kernel_approximation import Nystroem, AdditiveChi2Sampler, RBFSampler, SkewedChi2Sampler\n", + "from sklearn.linear_model import SGDClassifier\n", + "from sklearn.lda import LDA\n", + "from sklearn import preprocessing" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "rbf_feature = RBFSampler()\n", + "cleanedFeatureMatrix_features = rbf_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "sgdClf = SGDClassifier()\n", + "currCM, fig = printConfusionMatrix(sgdClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SGD w RBF kernel\")\n", + "fig.savefig(saveDir+\"cm_all_rbf_kernel_sgd.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "rbf_feature = RBFSampler(gamma=1)\n", + "cleanedFeatureMatrix_features = rbf_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "sgdClf = SGDClassifier()\n", + "printConfusionMatrix(sgdClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SGD w RBF kernel (gamma=1)\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "rbf_feature = RBFSampler()\n", + "cleanedFeatureMatrix_features = rbf_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "ldaClf = LDA()\n", + "currCM, fig = printConfusionMatrix(ldaClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, LDA w RBF kernel\")\n", + "fig.savefig(saveDir+\"cm_all_rbf_kernel_lda.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "rbf_feature = RBFSampler()\n", + "cleanedFeatureMatrix_features = rbf_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "linearSVMClf = svm.LinearSVC()\n", + "currCM, fig = printConfusionMatrix(linearSVMClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SVM w RBF kernel\")\n", + "fig.savefig(saveDir+\"cm_all_rbf_kernel_svm.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "nys_feature = Nystroem(kernel='polynomial')\n", + "cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "sgdClf = SGDClassifier()\n", + "currCM, fig = printConfusionMatrix(sgdClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SGD w poly kernel\")\n", + "fig.savefig(saveDir+\"cm_all_poly_kernel_sgd.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "nys_feature = Nystroem(kernel='polynomial')\n", + "cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "ldaClf = LDA()\n", + "currCM, fig = printConfusionMatrix(ldaClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, LDA w poly kernel\")\n", + "fig.savefig(saveDir+\"cm_all_poly_kernel_lda.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "nys_feature = Nystroem(kernel='polynomial')\n", + "cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "svmClf = svm.LinearSVC()\n", + "currCM, fig = printConfusionMatrix(svmClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SVM w poly kernel\")\n", + "fig.savefig(saveDir+\"cm_all_poly_kernel_svm.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "nys_feature = Nystroem(kernel='sigmoid')\n", + "cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "sgdClf = SGDClassifier()\n", + "currCM, fig = printConfusionMatrix(sgdClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SGD w sigmoid kernel\")\n", + "fig.savefig(saveDir+\"cm_all_sigmoid_kernel_sgd.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "nys_feature = Nystroem(kernel='sigmoid')\n", + "cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "ldaClf = LDA()\n", + "currCM, fig = printConfusionMatrix(ldaClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, LDA w sigmoid kernel\")\n", + "fig.savefig(saveDir+\"cm_all_sigmoid_kernel_lda.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "nys_feature = Nystroem(kernel='sigmoid')\n", + "cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "svmClf = svm.LinearSVC()\n", + "currCM, fig = printConfusionMatrix(svmClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SVM w poly kernel\")\n", + "fig.savefig(saveDir+\"cm_all_sigmoid_kernel_svm.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# nys_feature = Nystroem(kernel='chi2')\n", + "# cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "# sgdClf = SGDClassifier()\n", + "# printConfusionMatrix(sgdClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SGD w sigmoid kernel\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Only for transport trips" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As we can see, the prediction rate is best for walk and bike, which are the ones for which we get the most data from moves. It may be a mistake to use the same model for both types of trips because moves will do a good job for walk/bike and a horrible job for transport, because we don't allow users to specify 'transport' in the output.\n", + "\n", + "These also have zero carbon footprint. Let us see how well we do on the motorized trips alone." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "transportTrips = cleanedFeatureMatrix[:,2] == 4\n", + "print(np.count_nonzero(transportTrips))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "printConfusionMatrix(forestClf, genericCleanedFM[transportTrips], cleanedResultVector[transportTrips], \"Generic features, motorized only, random forest\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "printConfusionMatrix(forestClf, cleanedFeatureMatrix[transportTrips], cleanedResultVector[transportTrips], \"All features, transport only, random forest\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "knnClf = neighbors.KNeighborsClassifier()\n", + "printConfusionMatrix(knnClf, genericCleanedFM[transportTrips], cleanedResultVector[transportTrips], \"Generic features, transport only, k-nn\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "knnClf = neighbors.KNeighborsClassifier()\n", + "printConfusionMatrix(knnClf, cleanedFeatureMatrix[transportTrips], cleanedResultVector[transportTrips], \"All features, transport only, k-nn\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As we can see, we are actually able to predict car trips with a fair degree of accuracy. But bus and train trips are pretty much a tossup. Ignore the entries for 0 and 1 above, since we stripped out all walk and bike trips, and so these are only trips which moves misclassified, and not the entire dataset. Now we know why the Zheng paper only attempted to distinguish between bus and car trips, and not bus, train and car. The new features helped in the decision tree case, but not by that much, and did not help us at all in the knn case." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## User-specific models" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def getUserModelComparison(isTransportOnly):\n", + " userIds = Sections.distinct(\"user_id\")\n", + "\n", + " # I'm not going to bother with testing against only the generic features\n", + " # because the main issue here is personalization\n", + "\n", + " userIdList = []\n", + " numberOfSections = []\n", + " percentWalkBikeSections = []\n", + " percentAutoClassified = []\n", + " percentAutoClassifiedWalk = []\n", + " percentAutoClassifiedBike = []\n", + " percentAutoClassifiedBus = []\n", + " percentAutoClassifiedTrain = []\n", + " percentAutoClassifiedCar = []\n", + " autoClassifiedAccuracy = []\n", + " overallAccuracy = []\n", + "\n", + " labels = [\"Number of sections\", \"% walk+bike trips\",\n", + " \"% autoclassified\", \"% auto classified walk\",\n", + " \"% auto classified bike\", \"% auto classified bus\",\n", + " \"% auto classified train\", \"% auto classified car\",\n", + " \"auto classified accuracy\", \"overall accuracy\"]\n", + " \n", + " for userId in userIds:\n", + " # decision tree with all features\n", + " if not isTransportOnly:\n", + " query = {\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, {'user_id': userId}]}\n", + " else:\n", + " query = {\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, {'mode': 4}, {'user_id': userId}]}\n", + " \n", + " wbQuery = {\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$in': ['1', '3', '7']}}, {'user_id': userId}]}\n", + " walkBikeTripCount = Sections.find(wbQuery).count()\n", + " (userFeatureMatrix, userResultVector) = generateFeatureMatrixAndResultVector(query)\n", + " \n", + " # we only focus on users who have enough history with us\n", + " if len(userResultVector) < 150:\n", + " print(\"Skipping user with userId %s who has %s unconfirmed sections\" % (userId, len(userResultVector)))\n", + " continue\n", + " \n", + " forestClf = ensemble.RandomForestClassifier()\n", + " # printConfusionMatrix(forestClf, userFeatureMatrix, userResultVector)\n", + " (pac5, pacm5, hcs5, s5) = kFoldValidationWithProb(forestClf, userFeatureMatrix, userResultVector, 5, 0.95)\n", + " userIdList.append(userId)\n", + " \n", + " numberOfSections.append(len(userResultVector))\n", + " percentWalkBikeSections.append(float(walkBikeTripCount)/len(userResultVector))\n", + " percentAutoClassified.append(pac5.mean())\n", + " percentAutoClassifiedWalk.append(pacm5[0].mean())\n", + " percentAutoClassifiedBike.append(pacm5[1].mean())\n", + " percentAutoClassifiedBus.append(pacm5[2].mean())\n", + " percentAutoClassifiedTrain.append(pacm5[3].mean())\n", + " percentAutoClassifiedCar.append(pacm5[4].mean())\n", + " autoClassifiedAccuracy.append(hcs5.mean())\n", + " overallAccuracy.append(s5.mean())\n", + " resultArray = np.array([numberOfSections, percentAutoClassified, percentAutoClassifiedWalk,\n", + " percentAutoClassifiedBike, percentAutoClassifiedBus, percentAutoClassifiedTrain,\n", + " percentAutoClassifiedCar, autoClassifiedAccuracy, overallAccuracy])\n", + " print(resultArray.shape)\n", + " return (userIdList, resultArray, labels)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def displayUserVariation(userIds, ra, labels):\n", + " ''' ra has rows = plots and cols = users\n", + " '''\n", + " fig, (axes, axesNum) = plt.subplots(2, 1, figsize=(25, 25))\n", + " nUsers = len(userIds)\n", + " \n", + " for i in [1,-2,-1]:\n", + " # each row is one plot\n", + " print(ra[i])\n", + " axes.plot(np.arange(nUsers), ra[i], linewidth=2, label=labels[i])\n", + " axes.legend(loc='best')\n", + " for i in [0]:\n", + " # each row is one plot\n", + " print(ra[i])\n", + " axesNum.plot(np.arange(nUsers), ra[i], linewidth=2, label=labels[i]) \n", + " axesNum.legend(loc='best')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "(userIds, userResultArray, labels) = getUserModelComparison(isTransportOnly=False)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "displayUserVariation(userIds, userResultArray, labels)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "selIndices = [2, -2, -1, 1]\n", + "mpl.rcParams['font.size'] = 16\n", + "fig, axes = displayHelpers.showCategoryChart(np.arange(len(userIds)), np.multiply([userResultArray[i] for i in selIndices], 100), [labels[i] for i in selIndices],\n", + " ['b', 'g', 'c', 'm', 'y', 'k', 'w'],\n", + " \"Percentage\",\n", + " \"Accuracy of various predictions\",\n", + " figsize=(12,5), width=0.2)\n", + "ax2 = axes.twinx()\n", + "# ax2.bar(np.arange(len(userResultArray[0])) + 3 * 0.2, userResultArray[0], 0.2, color = 'c')\n", + "nSecLine, = ax2.plot(userResultArray[0], 'r-+', linewidth=2, label=\"Number of confirmed sections\")\n", + "axes.set_ylim(top=115)\n", + "axes.axhline(98, linewidth=2, label = \"98%\")\n", + "axes.axhline(85, linewidth=2, label = \"85%\")\n", + "axes.text(x=15.5, y=98.5, s=\"98%\")\n", + "axes.text(x=15.5, y=85.5, s=\"85%\")\n", + "axes.get_legend().set_bbox_to_anchor((0.4, -0.1))\n", + "print(axes.get_legend_handles_labels())\n", + "ax2.legend([nSecLine], [\"Number of sections\"], loc=\"upper right\", framealpha=0.3, bbox_to_anchor=(1, -0.1))\n", + "ax2.set_ylabel(\"Count (number of sections)\")\n", + "axes.set_xlabel(\"Users\")\n", + "ax2.set_ylim(bottom=0)\n", + "fig.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "fig, ax = plt.subplots()\n", + "ax.plot(userResultArray[1], userResultArray[-1], \"o\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let us pick users with really high accuracy. Unfortunately, they also have the least confirmed sections. Let us see whether this is because they are heavy walkers or otherwise." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "userIds[5], userIds[6], userIds[2]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for i in [2,5,6]:\n", + " userId = userIds[i]\n", + " query = {\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, {'user_id': userId}]}\n", + " (userFeatureMatrix, userResultVector) = generateFeatureMatrixAndResultVector(query)\n", + " indicesToStrip = (userResultVector == 2) | (userResultVector == 4) | (userResultVector == 8)\n", + " for mode in [1,3,5,6,7,9]:\n", + " # nFolds = 5\n", + " if np.count_nonzero(userResultVector == mode) <= 10:\n", + " print(\"number of instances of mode %s = %s\" % (mode, np.count_nonzero(userResultVector == mode)))\n", + " indicesToStrip = indicesToStrip | (userResultVector == mode)\n", + " userStrippedIndices = np.logical_not(indicesToStrip)\n", + " strippedUserFeatureMatrix = userFeatureMatrix[userStrippedIndices]\n", + " strippedUserResultVector = userResultVector[userStrippedIndices]\n", + " forestClf = ensemble.RandomForestClassifier()\n", + " printConfusionMatrix(forestClf, strippedUserFeatureMatrix, strippedUserResultVector, \"All features, random forest, user %s\" % i)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "So there's quite a bit of variability in both the overall accuracy, and in the number of trips for a user. The two don't seem to be correlated though. We get some fairly uneven improvement - for some users, the general classification is over 90%. We are also able to classify over 80% of the trips for some users.\n", + "\n", + "But that might just be due to a higher ratio of walk trips, which are classified more accurately. I can explore this only for transport, but first, I'm going to try to build a gesture library and build the associated features. Then maybe Mogeng can continue some of the exploration." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "(userIdsTransOnly, userResultArrayTransOnly, labelsTransOnly) = getUserModelComparison(isTransportOnly=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "displayUserVariation(userIdsTransOnly, userResultArrayTransOnly, labelsTransOnly)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "So looking at transport-only trips, and focusing on users with enough transport history (50+ motorized transport trips), we are able to get an overall accuracy of around 70 - 80% even for the motorized trips. However, there are some clear outliers, like the one who has only 60% accuracy. Also, because our current threshold for high confidence is set so high, the high confidence predictions are > 95% correct as before. We have to decide what to use.\n", + "\n", + "We can autoclassify 20 - 50% of the motorized transport trips. In general, this is related to the number of trips - there is a very clear spike in the data for user 4. But the correlation is not exact. In particular, user 5 has > 50 trips, but only ~ 10% autoclassified trips.\n", + "\n", + "It might be worthwhile to take a closer look at these 6 users, see what their transport trips look like, and get a sense of what the difference between user 4 and user 5 is, for example. This might help us figure out how to build better user models." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def buildRouteLibrary(userId, threshold):\n", + " '''\n", + " Here we attempt to build a route library for each user.\n", + " Then, the probability of the top match can be a factor in our machine learning.\n", + " Let us just start with the start and end points instead of a full dynamic time warp.\n", + " \n", + " userSections = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, {'user_id': userId}]})\n", + " existingRoutes = RouteLibrary()\n", + " for section in userSections:\n", + " existingRoutes.update(section)\n", + " return existingRoutes\n", + " '''" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## A summary comparision of models" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "modelCMList = []\n", + "saveDir = \"/tmp/ml_results/\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import os\n", + "os.makedirs(saveDir, exist_ok=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generic model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices], cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices], cleanedResultVector, \"Generic\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generic + Advanced model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices], cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices], cleanedResultVector, \"Generic + Advanced\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic_advanced.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generic + Advanced + Location model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices\n", + " +LocationFeatureIndices], cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices\n", + " +LocationFeatureIndices], cleanedResultVector, \"Generic + Advanced + Location\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic_advanced_location.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generic + BusTrain model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+BusTrainFeatureIndices], cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+BusTrainFeatureIndices], cleanedResultVector, \"Generic + BusTrain\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic_bustrain.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generic + Advanced + BusTrain model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices+BusTrainFeatureIndices], cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices+BusTrainFeatureIndices], cleanedResultVector, \"Generic + Advanced + BusTrain\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic_advanced_bustrain.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generic + Advanced + BusTrain + Location model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices+BusTrainFeatureIndices\n", + " +LocationFeatureIndices], cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices+BusTrainFeatureIndices\n", + " +LocationFeatureIndices], cleanedResultVector, \"Gen + Adv + BusTrain + Loc\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic_advanced_bustrain_location.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generic + Advanced + BusTrain + Location + Time model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix, cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix, cleanedResultVector, \"Gen + Adv + BusTrain + Loc + Time\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic_advanced_bustrain_location_time.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "It seems that with all the features in, we can have the best prediction result." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "cmDiagList = []\n", + "modelLabels = [\"Generic\", \"G+A\", \"G+A+L\", \"G+B\", \"G+A+B\", \"G+A+B+L\", \"G+A+B+L+T\"]\n", + "for currCM in modelCMList:\n", + " cmDiagList.append(np.diag(currCM) * 100)\n", + "accuracyMatrix = np.vstack(cmDiagList)\n", + "print(len(modelLabels), accuracyMatrix.shape)\n", + "np.set_printoptions(precision=4)\n", + "print(accuracyMatrix)\n", + "np.set_printoptions(precision=0)\n", + "print(accuracyMatrix)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "cmDiagList = []\n", + "modelLabels = [\"Generic\", \"G+A\", \"G+A+L\", \"G+B\", \"G+A+B\", \"G+A+B+L\", \"G+A+B+L+T\"]\n", + "for currCM in modelCMList:\n", + " cmDiagList.append(np.diag(currCM) * 100)\n", + "accuracyMatrix = np.vstack(cmDiagList).round(decimals=0).astype(object)\n", + "print(len(modelLabels), accuracyMatrix.shape)\n", + "outputMatrix = np.insert(accuracyMatrix, 0, modelLabels, axis=1)\n", + "print(outputMatrix)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.1" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/percom_moves_collect_2014/mode_inference_percom_july_2014_data_with_result.ipynb b/percom_moves_collect_2014/mode_inference_percom_july_2014_data_with_result.ipynb new file mode 100644 index 0000000..6301206 --- /dev/null +++ b/percom_moves_collect_2014/mode_inference_percom_july_2014_data_with_result.ipynb @@ -0,0 +1,6128 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Data caveats\n", + "\n", + "1. This is based on data collected on the UC Berkeley campus in Spring 2014. Unfortunately, due to the sensitive nature of the data collected (location data), the dataset cannot be shared, but the corresponding author can run queries against it and return the aggregate results upon request.\n", + "2. Since the initial results were not run with a fixed random seed, the results in this notebook differ slightly from the published results, but they are generally consistent. And any subsequent results should be identical since this notebook contains a random seed" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import datetime" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We collected some more training data after this, but it was not included in these results.\n", + "So let us read the data from the backup database to ensure consistency with the published results" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import pymongo" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "Sections = pymongo.MongoClient('localhost').Backup_database.Stage_Sections" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "14506" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Sections.find({'type': 'move'}).count()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import numpy as np\n", + "import scipy as sp\n", + "np.random.seed(61297777)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "confirmedSections = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}]})" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "walkSections = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': 1}]})" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import json" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[{'mode_id': 1, 'mode_name': 'walking'}, {'mode_id': 2, 'mode_name': 'running'}, {'mode_id': 3, 'mode_name': 'cycling'}, {'mode_id': 4, 'mode_name': 'transport'}, {'mode_id': 5, 'mode_name': 'bus'}, {'mode_id': 6, 'mode_name': 'train'}, {'mode_id': 7, 'mode_name': 'car'}, {'mode_id': 8, 'mode_name': 'mixed'}, {'mode_id': 9, 'mode_name': 'air'}]\n" + ] + } + ], + "source": [ + "modeList = json.load(open(\"modes.json\"))\n", + "print(modeList)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "7439\n", + "walking, 3277\n", + "running, 56\n", + "cycling, 1072\n", + "transport, 0\n", + "bus, 389\n", + "train, 303\n", + "car, 2237\n", + "mixed, 76\n", + "air, 29\n" + ] + } + ], + "source": [ + "print(Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}]}).count())\n", + "modeNameList = []\n", + "modeCountList = []\n", + "for mode in modeList:\n", + " modeCount = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': mode['mode_id']}]}).count()\n", + " print(\"%s, %s\" % (mode['mode_name'], modeCount))\n", + " if modeCount > 0:\n", + " modeNameList.append(mode['mode_name'])\n", + " modeCountList.append(modeCount)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "import matplotlib.image as mpimg\n", + "import matplotlib as mpl\n", + "\n", + "%matplotlib inline\n", + "%config InlineBackend.figure_format='png'" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import displayHelpers" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "8\n", + "len(rectList) = 1, len(countLabelList) = 1\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "cleanModeNames = {\"walking\":\"walk\", \"running\":\"run\", \"cycling\":\"cycle\"}\n", + "(fig, ax) = displayHelpers.showCategoryChart(modeNameList, [modeCountList], ['Confirmed'], ['r'],\n", + " \"Number of trip sections\", \"Trip sections by mode\", \n", + " cleanNameDict = cleanModeNames, figsize=(12,5))\n", + "ax.set_ylim(top=4000)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "startTimes = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}]}, {'section_start_datetime': 1, '_id': 0}).sort('section_start_datetime', pymongo.ASCENDING)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Starting from {'section_start_datetime': datetime.datetime(2014, 4, 12, 15, 57, 47)}\n", + "Ending at {'section_start_datetime': datetime.datetime(2014, 7, 18, 22, 15, 35)}\n" + ] + } + ], + "source": [ + "nSections = startTimes.count()\n", + "print(\"Starting from %s\" % startTimes[0])\n", + "print(\"Ending at %s\" % startTimes[nSections-1])\n", + "startTime = startTimes[0]['section_start_datetime']\n", + "endTime = startTimes[nSections-1]['section_start_datetime']" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from datetime import datetime, timedelta" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "04-12 - 2014-05-12 15:57:47 = 3167, 3921\n", + "05-12 - 2014-06-11 15:57:47 = 2715, 4673\n", + "06-11 - 2014-07-11 15:57:47 = 1368, 4680\n", + "07-11 - 2014-07-18 22:15:35 = 189, 1166\n" + ] + } + ], + "source": [ + "timeNameList = []\n", + "timeCountList = []\n", + "timeTotalList = []\n", + "currTime = startTime\n", + "while currTime < endTime:\n", + " currEndTime = currTime + timedelta(days=30)\n", + " if currEndTime > endTime:\n", + " currEndTime = endTime\n", + " currTimeSearch = {'section_start_datetime': {\"$gte\": currTime, \"$lte\": currEndTime}}\n", + " nTrips = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, currTimeSearch]}, {'section_start_datetime': 1, '_id': 0}).count()\n", + " nTotalTrips = Sections.find({\"$and\": [{'type': 'move'}, currTimeSearch]}, {'section_start_datetime': 1, '_id': 0}).count()\n", + " print(\"%s - %s = %s, %s\" % (currTime.strftime(\"%m-%d\"), currEndTime, nTrips, nTotalTrips))\n", + " timeNameList.append(\"%s to %s\" % (currTime.strftime(\"%b-%d\"), currEndTime.strftime(\"%b-%d\")))\n", + " timeCountList.append(nTrips)\n", + " timeTotalList.append(nTotalTrips)\n", + " currTime = currEndTime" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "3\n", + "len(rectList) = 2, len(countLabelList) = 2\n" + ] + }, + { + "data": { + "image/png": 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9qJdZTV7etbwUmEdnuIkkSZKkHvUyxvuNbQQiSZIk9bMhE+8kxwyzX1XVR8Yg\nHkmSJKkvDdfjvXiQsrWBw4ANARNvSZIkqUdDJt5V9ekVy0mmAUcCbwROAz491H6SJEmSHm/YMd5J\nNgDeBRwMnAy8oKp+30ZgkiRJUj8Zboz3p4C/A04AZlbVotaikiRJkvrMcD+g88/AM4APAL9NsrC5\nPZRkYTvhSZIkSf1huDHeK/WrlpIkSZKG1ssP6EiSJPUuGe8IJrAa7wA0huzVliRJklpg4i1JkiS1\nwMRbkiRJaoGJtyRJktQCE29JkiSpBSbekiRJUgtMvCVJkqQWmHhLkiRJLTDxliRJklpg4i1JkiS1\nwMRbkiRJaoGJtyRJktQCE29JkiSpBSbekiRJUgtMvCVJkqQWmHhLkiRJLRizxDvJV5Lcm+SGrrIN\nkpyb5FfN/fpd296X5NYktyTZq6t8hyTXN9uOS5KxilmSJEkaK2PZ430SsPeAsqOA86pqa+C8Zp0k\n2wAHAts2+3wxydRmny8Bbwa2bm4D25QkSZKe9MYs8a6qC4H7BxTvD5zcLJ8MvKKr/LSqWlJVvwZu\nBeYk2QxYt6ouraoCTunaR5IkSZow2h7jvWlV3dUs3w1s2ixvDtzRVe/OpmzzZnlg+aCSvCXJ3CRz\nFyxYMHpRS5IkSU/QuF1c2fRg1yi3eUJVza6q2RtvvPFoNi1JkiQ9IW0n3vc0w0do7u9tyucDW3bV\n26Ipm98sDyyXJEmSJpS2E++zgUOb5UOB73aVH5hkjSTPpnMR5eXNsJSFSXZqZjN5fdc+kiRJ0oSx\n2lg1nOQbwO7ARknuBD4IHAuckeQw4HbgNQBVdWOSM4CbgKXAEVW1rGnq7XRmSFkLOKe5SZIkSRNK\nOkOt+8/s2bNr7ty57R/YacZXWUZ3yP+k0qen8arzPFwlnoOrznNwAM/BVeZ5uOrG6zxMcmVVze6l\nrr9cKUmSJLXAxFuSJElqgYm3JEmS1AITb0mSJKkFJt6SJElSC0y8JUmSpBaYeEuSJEktMPGWJEmS\nWmDiLUmSJLXAxFuSJElqgYm3JEmS1AITb0mSJKkFJt6SJElSC0y8JUmSpBaYeEuSJEktMPGWJEmS\nWmDiLUmSJLXAxFuSJElqgYm3JEmS1AITb0mSJKkFJt6SJElSC0y8JUmSpBaYeEuSJEktMPGWJEmS\nWmDiLUmSJLXAxFuSJElqgYm3JEmS1AITb0mSJKkFJt6SJElSC0y8JUmSpBaYeEuSJEktMPGWJEmS\nWmDiLUmbkjOHAAAI9UlEQVSSJLXAxFuSJElqgYm3JEmS1AITb0mSJKkFJt6SJElSC0y8JUmSpBaY\neEuSJEktMPGWJEmSWmDiLUmSJLXAxFuSJElqgYm3JEmS1AITb0mSJKkFJt6SJElSC0y8JUmSpBZM\nmMQ7yd5Jbklya5KjxjseSZIkaWVMiMQ7yVTg34G/BbYBDkqyzfhGJUmSJPVuQiTewBzg1qq6rar+\nBJwG7D/OMUmSJEk9myiJ9+bAHV3rdzZlkiRJ0oSw2ngHMJqSvAV4S7O6KMkt4xmPVlY2Au4b7ygm\nomS8I1B/8BxcVZ6DGj2eh6tqHM/DZ/VacaIk3vOBLbvWt2jKHqOqTgBOaCsoja4kc6tq9njHIU1W\nnoPS+PM87G8TZajJFcDWSZ6d5CnAgcDZ4xyTJEmS1LMJ0eNdVUuT/CPwY2Aq8JWqunGcw5IkSZJ6\nNiESb4Cq+iHww/GOQ2PKYULS+PIclMaf52EfS1WNdwySJElS35soY7wlSZKkCc3Ee5JI8ookleR5\no9Tej5I8kOT7A8pPTXJLkhuSfCXJ6oPsOyvJy1byeLs38R8+oJ1K8u5VfySPOcZXktyb5IYB5Z9K\n8osk1yU5K8l6o3E8TS7Na/VrXeurJVkw8Bx6Au3/Y5Jbm+Ns1FV+cPPavT7JfyXZfoj9378Kx5zX\nfawnIsmrk9yYZHmS2V3lGyY5P8miJF8YjWNJKyRZNErtDHX+PS/Jz5MsGe69aqzOvyQnJTlgiG1D\nvY8P+lg0Oky8J4+DgIub+5WSZOogxZ8CDhmk/FTgecBMYC3g8EHqzAJWKvFu3AC8pmv9IODaVWhn\nKCcBew9Sfi4wo6q2A34JvG8Uj6nJYzEwI8lazfpLGWRa1CfgEuBvgNsHlP8a2K2qZgIfYejxoyv9\nxj/KbgD+DrhwQPkfgaOBUfmALY2Roc6/+4F3AP9nhP3H4/wb6n18qMeiUWDiPQkkWQfYBTiMzlSM\nK8p3T3Jhkh80vdTHJ5nSbFuU5NNJrgX+amCbVXUe8NAg5T+sBnA5nTnXu2N5CvCvwGuTXJPktUk2\nSPKdplfu0iTbDfFQbgfWTLJpktBJks/pavvNSa5Icm2Sbyd5apJpSX69ouc9ybrd6wNiv5DOP8mB\n5T+pqqXN6qUDH5O0En4I7NMsHwR8Y8WGJHOanrGrm57pv2zKL0wyq6vexYP1WlfV1VU1b5Dy/6qq\n3zerg75+kxwLrNWck6c2Ze9qvrm6Ick7h3tQSaZ3f1OU5N1JPtQsX5DkE0kuT/LLJC8erI2qurmq\nHvejZ1W1uKouppOAS6OueS/8ftf6F5K8oVmel+TDSa5qvjUa9FvjYc6/e6vqCuCRYY4/ZuffcIZ5\nHx/0sWh0mHhPDvsDP6qqXwK/S7JD17Y5wP8EtgG2otPjBLA2cFlVbd+86a2UJrE9BPhRd3lV/Qk4\nBji9qmZV1enAh4Grmx7l9wOnDNP0t4BXAy8CrgKWdG07s6p2rKrtgZuBw6rqIeAC/pzsHNjUG/Kf\n4AjeRFeyL62k04ADk6wJbAdc1rXtF8CLq+r5dM6RjzXlXwbeAJDkucCaVbWq3/QcxiCv36o6CvhD\nc04e3PyPeCPwQmAn4M1Jnr+KxwRYrarmAO8EPvgE2pHGw31V9QLgS4zBNy8tnH96EjHxnhwOovOG\nT3PfPdzk8qq6raqW0el926UpXwZ8+wkc84vAhVV1UQ91dwG+ClBV/wlsmGTdIeqeQSfxfkxvYWNG\nkouSXA8cDGzblJ9I558Yzf1/9PwouiT5F2ApneE00kqrquuA6XRevwOnR30a8M2m5+rf+PPr95vA\nvs2H2TfRGRK10pL8NZ3E+709VN8FOKvpbV4EnAkM2lPdozOb+yvpPH5pImn79Tva55+eREy8+1yS\nDYA9gBOTzAPeA7ymGaoBMHA+yRXrf2yScZK8sPkK7Jok+/VwzA8CGwPvGo3H8Jjgqu6m85XdS4Hz\nBmw+CfjHZizrh4E1m30uAaYn2R2YWlU3JNmy6zG9daTjNl877gscXM7BqSfmbDrjPQd+cPwIcH5V\nzQBezp9fvw/Tuc5gfzrXOKz4KvrHzev3xJEO2AzfOhHYv6p+N1oPpMtSHvt+suaA7Su+mVpG8/sR\nSf6jid/fZ9B4W5XXb8/nXwtGin+l38c1dibMD+holR0AfLWq/mFFQZKf8edPz3OSPJvO+OnXMsiF\nV1V1GZ0LIkeUzqwjewEvqarlQ1R7CJjWtX4RnR7qjzTJ8X1VtXCYwxwDbFJVy/78+QGaNu9qegYP\n5rEXrp0CfJ1OckNV3bESj2lv4H/RuUDt4V72kYbxFeCBqrq+eb2v8DT+/Jp9w4B9TgS+B1y0Yrx2\nVe3Vy8GSPJNOj9khzXCzoTySZPVmGNZFwEnN2NMAr2Twi7BWuAfYJMmGwCI6H1J/NEx9quqNw22X\nWnQ7sE2SNehMCvASOpMRDKnX828ljOn5tzLv4xpb9nj3v4OAswaUfZs/Dze5AvgCnTHRvx6k7qCS\nXETnK/CXJLkzyYp/QscDmwI/bz5ZHzPI7ufT+Sd3TZLXAh8CdkhyHXAscOhwx24uFvvOIJuOpjNm\n9hI642W7nQqsz+N7Gbsf0zeAnwN/2Tymw5pNX6CT1J/bxHz8cPFJw6mqO6vquEE2fRL4eJKrGdAp\nUlVXAgsZZphUknckuZPOxZPXdfXEHQNsCHyxef3OHaKJE5r9Tq2qq+h8g3Q5nXPqxKq6epB9VgOW\nNMnCvzb1z+Xx59+Ikryyif+vgB8k+XHXtnnAZ4A3NOfmNivbvjRQkhWv3zvoDGO8obkf7LU+UluD\nnn9Jnt6Uvwv4QPP6HWwoZevn31Dv48P8L9Eo8JcrJ7Gmt+3dVbXveMcy1tKZx3T/qhqu10B6Ukry\nDDoXCT9vmG+SWpVkY+Caqtp8vGORVkU6swP9v+bC3wnF82/issdbfS/J5+n0pH9kvGORVlaS19Pp\n9fqXJ1HSvR+dr8Od014TUnNtzzeAD4x3LCvL829is8dbkiRJaoE93pIkSVILTLwlSZKkFph4S5Ik\nSS0w8ZYkSZJaYOItSZIktcDEW5IkSWrB/wdWzQDMK7HAfAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "(fig, ax) = displayHelpers.showCategoryChart(timeNameList[:-1], [timeCountList[:-1], timeTotalList[:-1]],\n", + " [\"Confirmed\", \"Total\"], ['r', 'b'], \n", + " \"Number of trip sections\", \"Trip sections by start time\", figsize=(12,5))\n", + "# ax.set_ylim(top=5500)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "05-06 = 2508, 8603\n", + "05-13 = 3227, 11892\n", + "05-20 = 3974, 15365\n", + "05-27 = 4603, 18383\n", + "06-03 = 5195, 21629\n", + "06-10 = 5776, 25133\n", + "06-17 = 6229, 28305\n", + "06-24 = 6626, 31257\n", + "07-01 = 6882, 34503\n", + "07-08 = 7167, 37439\n", + "07-15 = 7351, 40357\n" + ] + } + ], + "source": [ + "timeNameList = []\n", + "timeCountList = []\n", + "timeTotalList = []\n", + "currTime = datetime(year=2014,month=5,day=6)\n", + "while currTime < endTime:\n", + " currTimeSearch = {'section_start_datetime': {\"$lte\": currTime}}\n", + " nTrips = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, currTimeSearch]}, {'section_start_datetime': 1, '_id': 0}).count()\n", + " nTotalTrips = Sections.find({\"$and\": [currTimeSearch]}, {'section_start_datetime': 1, '_id': 0}).count()\n", + " print(\"%s = %s, %s\" % (currTime.strftime(\"%m-%d\"), nTrips, nTotalTrips))\n", + " timeNameList.append(\"%s\" % (currTime.strftime(\"%b-%d\")))\n", + " timeCountList.append(nTrips)\n", + " timeTotalList.append(nTotalTrips)\n", + " currTime = currTime + timedelta(days=7)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "01477d94-e0bb-3903-a428-338551801391 117 64\n", + "03678a4f-efb9-3100-b0e5-8f296c197eb7 211 211\n", + "1a65368b-888e-3e77-8f7c-1128f16da1df 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"ea3f7719-f4a3-36fd-9477-924114cfe0bd 680 18\n", + "ed8ca6a2-9092-37af-adde-46e51a18a310 129 128\n", + "f4254389-3592-3cd5-b206-462fb6eaa7b5 659 446\n", + "f8fee20c-0f32-359d-ba75-bce97a7ac83b 244 137\n" + ] + } + ], + "source": [ + "idList = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}]}).distinct('user_id')\n", + "idNameList = []\n", + "idCountList = []\n", + "confirmedCountList = []\n", + "for i, id in enumerate(idList):\n", + " count = Sections.find({\"$and\": [{'type': 'move'}, {'user_id': id}]}).count()\n", + " confirmedCount = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, {'user_id': id}]}).count()\n", + " print(id, count, confirmedCount)\n", + " idNameList.append(\"%s\" % i)\n", + " idCountList.append(count)\n", + " confirmedCountList.append(confirmedCount)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "45\n", + "len(rectList) = 2, len(countLabelList) = 2\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/matplotlib/figure.py:403: UserWarning: matplotlib is currently using a non-GUI backend, so cannot show the figure\n", + " \"matplotlib is currently using a non-GUI backend, \"\n" + ] + }, + { + "data": { + "image/png": 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JkiTVl0r6XH8oM9cBU4HXAR8ELq5pVJIkSVIdqiS53tIz9V3AjzNzSVlZ2wdG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\nWH4aGFIsDwOeKNvvyaJMPZl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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = displayHelpers.showCategoryChart(idNameList, [confirmedCountList, idCountList],\n", + " [\"Confirmed Sections\", \"Total Sections\"],\n", + " ['r', 'b'], \"Number of trip sections\", \"Trip sections by user\", figsize=(12,5))\n", + "oldSize = mpl.rcParams['font.size']\n", + "mpl.rcParams['font.size'] = 16\n", + "labels = range(0, len(idNameList), 5)\n", + "axes.set_xticks(labels)\n", + "axes.set_xticklabels(np.array(idNameList)[labels])\n", + "fig.show()\n", + "mpl.rcParams['font.size'] = oldSize" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "RcParams({'_internal.classic_mode': False,\n", + " 'agg.path.chunksize': 0,\n", + " 'animation.avconv_args': [],\n", + " 'animation.avconv_path': 'avconv',\n", + " 'animation.bitrate': -1,\n", + " 'animation.codec': 'h264',\n", + " 'animation.convert_args': [],\n", + " 'animation.convert_path': 'convert',\n", + " 'animation.ffmpeg_args': [],\n", + " 'animation.ffmpeg_path': 'ffmpeg',\n", + " 'animation.frame_format': 'png',\n", + " 'animation.html': 'none',\n", + " 'animation.mencoder_args': [],\n", + " 'animation.mencoder_path': 'mencoder',\n", + " 'animation.writer': 'ffmpeg',\n", + " 'axes.autolimit_mode': 'data',\n", + " 'axes.axisbelow': 'line',\n", + " 'axes.edgecolor': 'k',\n", + " 'axes.facecolor': 'w',\n", + " 'axes.formatter.limits': [-7, 7],\n", + " 'axes.formatter.offset_threshold': 4,\n", + " 'axes.formatter.use_locale': False,\n", + " 'axes.formatter.use_mathtext': False,\n", + " 'axes.formatter.useoffset': True,\n", + " 'axes.grid': False,\n", + " 'axes.grid.axis': 'both',\n", + " 'axes.grid.which': 'major',\n", + " 'axes.hold': None,\n", + " 'axes.labelcolor': 'k',\n", + " 'axes.labelpad': 4.0,\n", + " 'axes.labelsize': 'medium',\n", + " 'axes.labelweight': 'normal',\n", + " 'axes.linewidth': 0.8,\n", + " 'axes.prop_cycle': cycler('color', ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf']),\n", + " 'axes.spines.bottom': True,\n", + " 'axes.spines.left': True,\n", + " 'axes.spines.right': True,\n", + " 'axes.spines.top': True,\n", + " 'axes.titlepad': 6.0,\n", + " 'axes.titlesize': 'large',\n", + " 'axes.titleweight': 'normal',\n", + " 'axes.unicode_minus': True,\n", + " 'axes.xmargin': 0.05,\n", + " 'axes.ymargin': 0.05,\n", + " 'axes3d.grid': True,\n", + " 'backend': 'module://ipykernel.pylab.backend_inline',\n", + " 'backend.qt4': 'PyQt4',\n", + " 'backend.qt5': 'PyQt5',\n", + " 'backend_fallback': True,\n", + " 'boxplot.bootstrap': None,\n", + " 'boxplot.boxprops.color': 'k',\n", + " 'boxplot.boxprops.linestyle': '-',\n", + " 'boxplot.boxprops.linewidth': 1.0,\n", + " 'boxplot.capprops.color': 'k',\n", + " 'boxplot.capprops.linestyle': '-',\n", + " 'boxplot.capprops.linewidth': 1.0,\n", + " 'boxplot.flierprops.color': 'k',\n", + " 'boxplot.flierprops.linestyle': 'none',\n", + " 'boxplot.flierprops.linewidth': 1.0,\n", + " 'boxplot.flierprops.marker': 'o',\n", + " 'boxplot.flierprops.markeredgecolor': 'k',\n", + " 'boxplot.flierprops.markerfacecolor': 'none',\n", + " 'boxplot.flierprops.markersize': 6.0,\n", + " 'boxplot.meanline': False,\n", + " 'boxplot.meanprops.color': 'C2',\n", + " 'boxplot.meanprops.linestyle': '--',\n", + " 'boxplot.meanprops.linewidth': 1.0,\n", + " 'boxplot.meanprops.marker': '^',\n", + " 'boxplot.meanprops.markeredgecolor': 'C2',\n", + " 'boxplot.meanprops.markerfacecolor': 'C2',\n", + " 'boxplot.meanprops.markersize': 6.0,\n", + " 'boxplot.medianprops.color': 'C1',\n", + " 'boxplot.medianprops.linestyle': '-',\n", + " 'boxplot.medianprops.linewidth': 1.0,\n", + " 'boxplot.notch': False,\n", + " 'boxplot.patchartist': False,\n", + " 'boxplot.showbox': True,\n", + " 'boxplot.showcaps': True,\n", + " 'boxplot.showfliers': True,\n", + " 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"cell_type": "code", + "execution_count": 24, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def getSpeedsForMode(modeId):\n", + " modeSectionCursor = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': modeId}]})\n", + " speedList = []\n", + " for section in modeSectionCursor:\n", + " speeds = calSpeeds(section)\n", + " if speeds != None:\n", + " # currHistogram = sp.histogram(speeds)\n", + " speedList.append(speeds)\n", + " return speedList" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Feature matrix construction" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Features are:\n", + "# 0. distance\n", + "# 1. duration\n", + "# 2. first filter mode\n", + "# 3. sectionId\n", + "# 4. avg speed\n", + "# 5. speed EV\n", + "# 6. speed variance\n", + "# 7. max speed\n", + "# 8. max accel\n", + "# 9. isCommute\n", + "# 10. heading change rate (currently unfilled)\n", + "# 11. stop rate (currently unfilled)\n", + "# 12. velocity change rate (currently unfilled)\n", + "# 13. start lat\n", + "# 14. start lng\n", + "# 15. stop lat\n", + "# 16. stop lng\n", + "# 17. start hour\n", + "# 18. end hour\n", + "# 19. both start and end close to bus stop\n", + "# 20. both start and end close to train station\n", + "# 21. both start and end close to airport\n", + "featureLabels = [\"distance\", \"duration\", \"first filter mode\", \"sectionId\", \"avg speed\",\n", + " \"speed EV\", \"speed variance\", \"max speed\", \"max accel\", \"isCommute\",\n", + " \"heading change rate\", \"stop rate\", \"velocity change rate\", \"start lat\", \"start lng\",\n", + " \"stop lat\", \"stop lng\", \"start hour\", \"end hour\", \"close to bus stop\", \"close to train stop\",\n", + " \"close to airport\"]\n", + "bus_cluster=mode_cluster(5,105,1)\n", + "train_cluster=mode_cluster(6,600,1)\n", + "air_cluster=mode_cluster(9,600,1)\n", + "def generateFeatureMatrixAndResultVector(sectionQuery):\n", + " confirmedSections = Sections.find(sectionQuery)\n", + " featureMatrix = np.zeros([confirmedSections.count(), len(featureLabels)])\n", + " resultVector = np.zeros(confirmedSections.count())\n", + " for (i, section) in enumerate(confirmedSections):\n", + " featureMatrix[i, 0] = section['distance']\n", + " featureMatrix[i, 1] = (section['section_end_datetime'] - section['section_start_datetime']).total_seconds()\n", + " \n", + " # Deal with unknown modes like \"airplane\"\n", + " try:\n", + " featureMatrix[i, 2] = section['mode']\n", + " except ValueError:\n", + " featureMatrix[i, 2] = 0\n", + " \n", + " featureMatrix[i, 3] = section['section_id']\n", + " featureMatrix[i, 4] = calAvgSpeed(section)\n", + " speeds = calSpeeds(section)\n", + " if speeds != None:\n", + " featureMatrix[i, 5] = np.mean(speeds)\n", + " featureMatrix[i, 6] = np.std(speeds)\n", + " featureMatrix[i, 7] = np.max(speeds)\n", + " else:\n", + " # They will remain zero\n", + " pass\n", + " accels = calAccels(section)\n", + " if accels != None and len(accels) > 0:\n", + " featureMatrix[i, 8] = np.max(accels)\n", + " else:\n", + " # They will remain zero\n", + " pass\n", + " featureMatrix[i, 9] = ('commute' in section) and (section['commute'] == 'to' or section['commute'] == 'from')\n", + " featureMatrix[i, 10] = calHCR(section)\n", + " featureMatrix[i, 11] = calSR(section)\n", + " featureMatrix[i, 12] = calVCR(section)\n", + " if section['section_start_point'] != None:\n", + " startCoords = section['section_start_point']['coordinates']\n", + " featureMatrix[i, 13] = startCoords[0]\n", + " featureMatrix[i, 14] = startCoords[1]\n", + " \n", + " if section['section_end_point'] != None:\n", + " endCoords = section['section_end_point']['coordinates']\n", + " featureMatrix[i, 15] = endCoords[0]\n", + " featureMatrix[i, 16] = endCoords[1]\n", + " \n", + " featureMatrix[i, 17] = section['section_start_datetime'].time().hour\n", + " featureMatrix[i, 18] = section['section_end_datetime'].time().hour\n", + " \n", + " featureMatrix[i, 19] = mode_start_end_coverage(section,bus_cluster,105)\n", + " featureMatrix[i, 20] = mode_start_end_coverage(section,train_cluster,600)\n", + " featureMatrix[i, 21] = mode_start_end_coverage(section,air_cluster,600)\n", + " resultVector[i] = section['confirmed_mode']\n", + " return (featureMatrix, resultVector)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + } + ], + "source": [ + "(featureMatrix, resultVector) = generateFeatureMatrixAndResultVector({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}]})\n" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.0266343825666\n", + "0.0\n", + "0.0582191780822\n", + "(7439, 22) (7439,)\n" + ] + } + ], + "source": [ + "print(np.max(featureMatrix[:,10]))\n", + "print(np.max(featureMatrix[:,20]))\n", + "print(np.max(featureMatrix[:,12]))\n", + "print(featureMatrix.shape, resultVector.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "runIndices = [ 553 590 596 1157 1169 1209 1277 1278 1279 2730 2731 2751 2833 3083 3098\n", + " 3107 3119 3120 3129 3135 3157 3169 3181 3192 3194 3225 3232 3238 3239 3248\n", + " 3289 3298 3299 3310 3311 3312 3313 3319 3320 3331 3332 3356 3409 3410 4296\n", + " 4754 4756 4771 4774 4776 5089 5096 5113 5129 6772 7394]\n", + "transportIndices = []\n", + "mixedIndices = [ 128 130 159 161 162 250 251 252 253 254 255 257 258 259 260\n", + " 261 262 263 264 265 266 267 349 473 1196 1287 1291 2512 2636 5277\n", + " 5573 5578 5590 5591 5922 5923 5925 5928 5929 5930 5936 5958 5960 5961 5963\n", + " 6567 6593 6693 6698 6743 6818 6819 7046 7047 7048 7050 7051 7052 7058 7059\n", + " 7060 7067 7072 7073 7082 7106 7124 7132 7133 7134 7135 7144 7145 7152 7184\n", + " 7189]\n", + "airIndices = [1403 1779 1808 3784 3872 3919 4900 5900 7105 7125 7126 7127 7128 7129 7131\n", + " 7137 7138 7139 7140 7141 7142 7202 7203 7204 7205 7206 7207 7208 7209]\n", + "unknownIndices = []\n", + "strippedIndices count = 7307\n" + ] + } + ], + "source": [ + "runIndices = resultVector == 2\n", + "transportIndices = resultVector == 4\n", + "mixedIndices = resultVector == 8\n", + "airIndices = resultVector == 9\n", + "unknownIndices = resultVector == 0\n", + "strippedIndices = np.logical_not(runIndices | transportIndices | mixedIndices)\n", + "print(\"runIndices = %s\" % (np.nonzero(runIndices)))\n", + "print(\"transportIndices = %s\" % (np.nonzero(transportIndices)))\n", + "print(\"mixedIndices = %s\" % (np.nonzero(mixedIndices)))\n", + "print(\"airIndices = %s\" % (np.nonzero(airIndices)))\n", + "print(\"unknownIndices = %s\" % (np.nonzero(unknownIndices)))\n", + "print(\"strippedIndices count = %s\" % (np.count_nonzero(strippedIndices)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, we filter out \"mixed\" and \"running\", since there are few instances of them and we don't intend to predict them initially. We also filter out any \"transport\" since it should never be in the confirmed set, and we don't want to deal with it if it is." + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "strippedFeatureMatrix = featureMatrix[strippedIndices]\n", + "strippedResultVector = resultVector[strippedIndices]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "First, we visualize the distribution of some of the features. This is so that we can compare our dataset to Zheng et al 2010." + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def plotFeatureVector(featureMatrix, resultVector, featureIndex, modeList):\n", + " avgSpeedFig, avgSpeedAxes = plt.subplots(1,1)\n", + " currModeSpeedsList = []\n", + " currModeNamesList = []\n", + " for mode in modeList:\n", + " currModeMask = resultVector == mode['mode_id']\n", + " currModeSpeeds = featureMatrix[currModeMask, featureIndex]\n", + " # print \"For mode %s, shape is %s\" % (mode['mode_id'], str(currModeSpeeds.shape))\n", + " if np.count_nonzero(currModeMask) != 0:\n", + " currModeNamesList.append(mode['mode_name'])\n", + " currModeSpeedsList.append(currModeSpeeds)\n", + " avgSpeedAxes.hist(currModeSpeedsList, normed=True, histtype=\"bar\", label=currModeNamesList)\n", + " avgSpeedAxes.set_ylabel(\"number of segments\")\n", + " avgSpeedAxes.set_xlabel(featureLabels[featureIndex])\n", + " plt.legend()" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/matplotlib/pyplot.py:524: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n", + " max_open_warning, RuntimeWarning)\n" + ] + }, + { + "data": { + "image/png": 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if+xqxRFRKWk88CBQRjYzxFJJF6fz04B5wKnASmAr2berWsumqicBcySNBV4F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\nSPfSop5DatsVwCzgvpb670W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ENbUdXUv5N3YnFjMzy0aa4b+/knSRpI6S2lUtmUdmZmZFIc0VyUfArcB1fDpa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\nQmCC\n", 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/DbQGHgj+fvNTFG7chGx3vaIni0VEIk49AhGRiFMiEBGJOCUCEZGIUyIQEYk4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\nSgQiIhGnRCAiEnH/H8L0O4QadovGAAAAAElFTkSuQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for col in range(0, len(featureLabels)):\n", + " plotFeatureVector(strippedFeatureMatrix, strippedResultVector, col, modeList)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The air modes are such outliers that we are unable to see the variation in the other modes. Let's strip out the outliers and focus on lower speed trips." + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "speedNormalEntries = strippedFeatureMatrix[:,4] < 50\n", + "plotFeatureVector(strippedFeatureMatrix[speedNormalEntries], strippedResultVector[speedNormalEntries], 4, modeList)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Using the graphs above, we can estimate the separability of our input. Clearly, there is some separability - the car and train trips that are at 20-30+ are clearly separable from the walk/bike trips that are at lower speeds. But are they separable from each other? And at least eyeballing the data, it looks like at least 75% of car trips are actually not that fast - the mean EV is < 10mph. Even with max speed, at least 25% of car trips appear to have a max speed ~ 10 mph. Max accel doesn't seem to have as much predictive power as one might hope - most max accel clusters at less than 5. It would be nice to visualize the clusters in this data, but I'm just going to start trying decision trees and SVMs on this data now." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We used to strip out outliers here, but the outliers actually correspond to plane trips, so we want to retain them. The rest of the code assumes that we stripped outliers to get \"cleaned\" trips, so we just reassign the values here instead of changing all the code. We can restore outlier detection at that point." + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "cleanedFeatureMatrix = strippedFeatureMatrix\n", + "cleanedResultVector = strippedResultVector" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Feature Indices" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\n", + "[10, 11, 12]\n", + "[13, 14, 15, 16]\n", + "[17, 18]\n", + "[19, 20, 21]\n" + ] + } + ], + "source": [ + "genericFeatureIndices = list(range(0,10))\n", + "AdvancedFeatureIndices = list(range(10,13))\n", + "LocationFeatureIndices = list(range(13,17))\n", + "TimeFeatureIndices = list(range(17,19))\n", + "BusTrainFeatureIndices = list(range(19,22))\n", + "print(genericFeatureIndices)\n", + "print(AdvancedFeatureIndices)\n", + "print(LocationFeatureIndices)\n", + "print(TimeFeatureIndices)\n", + "print(BusTrainFeatureIndices)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Generic model, generic features" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(7307, 10)\n" + ] + } + ], + "source": [ + "genericCleanedFM = cleanedFeatureMatrix[:,genericFeatureIndices]\n", + "print(genericCleanedFM.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/sklearn/cross_validation.py:44: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.\n", + " \"This module will be removed in 0.20.\", DeprecationWarning)\n" + ] + } + ], + "source": [ + "from sklearn import cross_validation\n", + "from sklearn import svm" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "svmClf = svm.LinearSVC()\n", + "svmScores = cross_validation.cross_val_score(svmClf, genericCleanedFM, cleanedResultVector, cv=5)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ 0.53278689 0.46653005 0.56262834 0.46369863 0.66255144]\n", + "0.537639069423\n" + ] + } + ], + "source": [ + "print(svmScores)\n", + "print(svmScores.mean())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Using svm.SVC() takes significantly longer (hours instead of seconds) but generates higher accuracy. The accuracy is still lower than the random forest, though." + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from sklearn import ensemble" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "forestScores = cross_validation.cross_val_score(forestClf, genericCleanedFM, cleanedResultVector, cv=5)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ 0.81352459 0.83879781 0.86516085 0.83630137 0.79355281]\n", + "0.829467487008\n" + ] + } + ], + "source": [ + "print(forestScores)\n", + "print(forestScores.mean())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "These results look pretty good, and pretty much parallel what the Zheng paper got, even with just the basic features. We get 82% average accuracy for a linear SVM and 86% average accuracy for a random forest. But the 82% and 86% values are for cross validation, where we have a known value that we can validate against.\n", + "\n", + "But what we really want to do is to decide, while looking at a section that we have no ground truth on, whether we want the user to classify it or not. And then we want to see, for the high confidence predictions that we will not prompt the user for, how accurate our classification really is.\n", + "\n", + "In order to do this, we get the probabilities for each prediction in addition to the prediction itself. We can then test the accuracy of the high confidence predictions and compare it to the accuracy of all predictions.\n", + "\n", + "To recap, we now return three metrics:\n", + "\n", + "- The number of entries that would be autoclassified given a particular target confidence interval\n", + "- The accuracy of the entries that would be autoclassified\n", + "- The accuracy of all entries, including ones that had low confidence" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Generate folds of indices\n", + "def generateFoldArrays(nIndices, nFolds):\n", + " currPermutation = np.random.permutation(nIndices)\n", + " currPermutationParts = np.array_split(currPermutation, nFolds)\n", + " \n", + " foldArrays = []\n", + " for i in range(0, nFolds):\n", + " testIndices = currPermutationParts[i]\n", + " trainIndicesParts = [currPermutationPart for (j, currPermutationPart) in enumerate(currPermutationParts) if j != i]\n", + " trainIndices = np.concatenate(trainIndicesParts)\n", + " foldArrays.append((trainIndices, testIndices))\n", + " return foldArrays\n", + "\n", + "def kFoldValidationWithProb(algo, X, y, nFolds, prob_threshold):\n", + " foldArrays = generateFoldArrays(len(y), nFolds)\n", + " \n", + " scores = []\n", + " highConfidenceScores = []\n", + " percentAutoClassified = []\n", + " percentAutoClassifiedByMode = []\n", + " for (trainIndices, testIndices) in foldArrays:\n", + " # print testIndices[0]\n", + " model = algo.fit(X[trainIndices], y[trainIndices])\n", + " testX = X[testIndices]\n", + " testy = y[testIndices]\n", + " \n", + " predictedY = model.predict(testX)\n", + " if hasattr(algo, \"decision_function\"):\n", + " predictedYProb = algo.decision_function(testX)\n", + " else:\n", + " predictedYProb = algo.predict_proba(testX)\n", + " \n", + " # print (\"predictedY.shape = %s, predictedYProb.shape = %s\" %\n", + " # (str(predictedY.shape), str(predictedYProb.shape)))\n", + " \n", + " # As we can see below, we take the max confidence along the first axis\n", + " highConfidencePredictions = np.max(predictedYProb, 1) > prob_threshold\n", + " print(\"Found %s high confidence predictions out of %s\" % (np.count_nonzero(highConfidencePredictions),\n", + " len(testIndices)))\n", + " \n", + " cmc = lambda m:np.count_nonzero(testy[highConfidencePredictions] == m)\n", + " \n", + " # Let us see how many of each mode were autoclassified\n", + " # print(\"Autoclassifications split by confirmed modes: walk: %s, bike: %s, bus: %s, train: %s, car: %s\" %\n", + " # (cmc(1), cmc(3), cmc(5), cmc(6), cmc(7)))\n", + " \n", + " pcmc = lambda m: float(np.count_nonzero(testy[highConfidencePredictions] == m))/np.count_nonzero(testy == m) if ((np.count_nonzero(testy == m) != 0)) else 0 \n", + " # Let us see what percentage of each mode was autoclassified\n", + " # print(\"For threshold %s, autoclassifications split by confirmed mode percents: walk: %s, bike: %s, bus: %s, train: %s, car: %s\" %\n", + " # (prob_threshold, pcmc(1), pcmc(3), pcmc(5), pcmc(6), pcmc(7)))\n", + " \n", + " percentAutoClassified.append(float(np.count_nonzero(highConfidencePredictions))/len(testIndices))\n", + " percentAutoClassifiedByMode.append([pcmc(1), pcmc(3), pcmc(5), pcmc(6), pcmc(7), pcmc(9)])\n", + " \n", + " # so now we are going to generate two scores.\n", + " # the first is the score on only the high confidence predictions\n", + " highConfidenceScore = model.score(testX[highConfidencePredictions], testy[highConfidencePredictions])\n", + " highConfidenceScores.append(highConfidenceScore)\n", + " \n", + " score = model.score(X[testIndices], y[testIndices])\n", + " scores.append(score)\n", + " # print scores\n", + " \n", + " print(\"for prob %s, percentage auto classified %s\" % (prob_threshold, np.array(percentAutoClassified).mean()))\n", + " print(\"for prob %s, scoring only on high confidence predictions %s\" % (prob_threshold, np.array(highConfidenceScores).mean()))\n", + " print(\"for prob %s, scoring on all predictions %s\" % (prob_threshold, np.array(scores).mean()))\n", + "\n", + " return (np.array(percentAutoClassified), np.array(percentAutoClassifiedByMode), np.array(highConfidenceScores), np.array(scores))" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def exploreKFoldValidationSpace(algo, X, y, nFolds):\n", + " (pac0, pacm0, hcs0, s0) = kFoldValidationWithProb(algo, X, y, nFolds, 0.90) \n", + " (pac5, pacm5, hcs5, s5) = kFoldValidationWithProb(algo, X, y, nFolds, 0.95)\n", + " (pac9, pacm9, hcs9, s9) = kFoldValidationWithProb(algo, X, y, nFolds, 0.99)\n", + " \n", + " probs = [0.90, 0.95, 0.99]\n", + " pacs = [pac0.mean(), pac5.mean(), pac9.mean()]\n", + " hcs = [hcs0.mean(), hcs5.mean(), hcs9.mean()]\n", + " ss = [s0.mean(), s5.mean(), s9.mean()]\n", + " \n", + " pacmWalk = [pacm0[:,0].mean(), pacm5[:,0].mean(), pacm9[:,0].mean()]\n", + " pacmBike = [pacm0[:,1].mean(), pacm5[:,1].mean(), pacm9[:,1].mean()]\n", + " pacmBus = [pacm0[:,2].mean(), pacm5[:,2].mean(), pacm9[:,2].mean()]\n", + " pacmTrain = [pacm0[:,3].mean(), pacm5[:,3].mean(), pacm9[:,3].mean()]\n", + " pacmCar = [pacm0[:,4].mean(), pacm5[:,4].mean(), pacm9[:,4].mean()]\n", + " pacmAir = [pacm0[:5].mean(), pacm5[:,5].mean(), pacm9[:,4].mean()]\n", + " \n", + " fig, axes = plt.subplots(1, 1, figsize=(15, 10))\n", + " print(pacs)\n", + " axes.set_yticks(np.arange(0,1,0.1))\n", + " axes.plot(probs, pacs, label=\"percentage auto classified\")\n", + " \n", + " print(pacmWalk)\n", + " axes.plot(probs, pacmWalk, linewidth = 5, label=\"percent walk auto classified\")\n", + " print(pacmBike)\n", + " axes.plot(probs, pacmBike, label=\"percent bike auto classified\")\n", + " print(pacmBus)\n", + " axes.plot(probs, pacmBus, linewidth=5, label=\"percent bus auto classified\")\n", + " print(pacmTrain)\n", + " axes.plot(probs, pacmTrain, label=\"percent train auto classified\")\n", + " print(pacmCar)\n", + " axes.plot(probs, pacmCar, linewidth=5, label=\"percent car auto classified\")\n", + " print(pacmAir)\n", + " axes.plot(probs, pacmAir, linewidth=5, label = \"percent air auto classified\")\n", + " \n", + " print(hcs)\n", + " axes.plot(probs, hcs, label=\"accuracy of high confidence samples\")\n", + " print(ss)\n", + " axes.plot(probs, ss, linewidth = 5, label=\"accuracy of all samples\")\n", + " plt.legend(loc='best')" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 804 high confidence predictions out of 1462\n", + "Found 776 high confidence predictions out of 1462\n", + "Found 759 high confidence predictions out of 1461\n", + "Found 763 high confidence predictions out of 1461\n", + "Found 755 high confidence predictions out of 1461\n", + "for prob 0.9, percentage auto classified 0.527846582977\n", + "for prob 0.9, scoring only on high confidence predictions 0.97467661137\n", + "for prob 0.9, scoring on all predictions 0.854111223784\n", + "Found 758 high confidence predictions out of 1462\n", + "Found 740 high confidence predictions out of 1462\n", + "Found 777 high confidence predictions out of 1461\n", + "Found 749 high confidence predictions out of 1461\n", + "Found 784 high confidence predictions out of 1461\n", + "for prob 0.95, percentage auto classified 0.521146526516\n", + "for prob 0.95, scoring only on high confidence predictions 0.973741723037\n", + "for prob 0.95, scoring on all predictions 0.854523118641\n", + "Found 774 high confidence predictions out of 1462\n", + "Found 766 high confidence predictions out of 1462\n", + "Found 801 high confidence predictions out of 1461\n", + "Found 796 high confidence predictions out of 1461\n", + "Found 765 high confidence predictions out of 1461\n", + "for prob 0.99, percentage auto classified 0.534010492598\n", + "for prob 0.99, scoring only on high confidence predictions 0.973068061579\n", + "for prob 0.99, scoring on all predictions 0.856301598047\n", + "[0.52784658297682285, 0.52114652651567284, 0.5340104925977841]\n", + "[0.80465255602437114, 0.79552653433482423, 0.80254572540808167]\n", + "[0.59738220608381476, 0.60298779512295042, 0.6247062070579833]\n", + "[0.074484732698767459, 0.069302665649697615, 0.084653615612208924]\n", + "[0.11044819815263611, 0.098516109596618079, 0.1245661010095869]\n", + "[0.23186938936759108, 0.22237879836228425, 0.23634406922831572]\n", + "[0.30869506927675228, 0.040000000000000001, 0.23634406922831572]\n", + "[0.97467661137023209, 0.97374172303698392, 0.97306806157863923]\n", + "[0.85411122378372095, 0.85452311864051289, 0.85630159804717465]\n" + ] + }, + { + "data": { + "image/png": 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2uEsEpOKQlOfOKwxV7uOVDlbl9lH8X1FfVid2Tvd82PM6t825klT2Bg++N3+o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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, genericCleanedFM, cleanedResultVector, 5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The results of these three metrics for confidence intervals of 90%, 95% and 99% are shown above, and they are all largely similar. The accuracy of the high confidence predictions is, as expected, really high at 97 - 98%. However, we were only able to auto-classify ~ 50% of the sections. Now, let's retry using the linear SVM above." + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 1265 high confidence predictions out of 1462\n", + "Found 446 high confidence predictions out of 1462\n", + "Found 1122 high confidence predictions out of 1461\n", + "Found 404 high confidence predictions out of 1461\n", + "Found 741 high confidence predictions out of 1461\n", + "for prob 0.9, percentage auto classified 0.544398314218\n", + "for prob 0.9, scoring only on high confidence predictions 0.643382926979\n", + "for prob 0.9, scoring on all predictions 0.605590122014\n", + "Found 1062 high confidence predictions out of 1462\n", + "Found 614 high confidence predictions out of 1462\n", + "Found 833 high confidence predictions out of 1461\n", + "Found 704 high confidence predictions out of 1461\n", + "Found 681 high confidence predictions out of 1461\n", + "for prob 0.95, percentage auto classified 0.532902618093\n", + "for prob 0.95, scoring only on high confidence predictions 0.750810288638\n", + "for prob 0.95, scoring on all predictions 0.561645463304\n", + "Found 643 high confidence predictions out of 1462\n", + "Found 391 high confidence predictions out of 1462\n", + "Found 912 high confidence predictions out of 1461\n", + "Found 693 high confidence predictions out of 1461\n", + "Found 964 high confidence predictions out of 1461\n", + "for prob 0.99, percentage auto classified 0.493127002007\n", + "for prob 0.99, scoring only on high confidence predictions 0.770121916836\n", + "for prob 0.99, scoring on all predictions 0.644310860298\n", + "[0.54439831421800378, 0.53290261809322359, 0.49312700200657122]\n", + "[0.59764353949445315, 0.7547652141914023, 0.63238923006304104]\n", + "[0.26887431316538646, 0.10222722571388995, 0.11063189980457097]\n", + "[0.32962247565877334, 0.194758910774359, 0.22534309785896825]\n", + "[0.80543344211152113, 0.72401009505096825, 0.70069764655698019]\n", + "[0.59372173214509227, 0.44248800444272546, 0.48634912819177972]\n", + "[0.57921591709587106, 0.76190476190476186, 0.48634912819177972]\n", + "[0.64338292697861876, 0.7508102886379735, 0.77012191683641262]\n", + "[0.60559012201413687, 0.56164546330446607, 0.64431086029751183]\n" + ] + }, + { + "data": { + "image/png": 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K4W+rlcDifR69MjRucZ+3QVloerm4yXcxxMW/ae8PT9WBkYvlnrgTLwFqm317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\nUFWVV155hccff5xXX321UmOorm5djfRhkPedEFXD5ZzLxKfHE5ceR1x6H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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "svmClf = svm.LinearSVC()\n", + "exploreKFoldValidationSpace(svmClf, genericCleanedFM, cleanedResultVector, 5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We see that the SVM is able to classify more trips than the decision tree, but at the cost of unacceptably lower performance on the high confidence predictions. It is hard to understand the results with line plots, let's switch to bar graphs instead." + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def exploreKFoldValidationSpaceBarGraph(algo, X, y, nFolds):\n", + " (pac0, pacm0, hcs0, s0) = kFoldValidationWithProb(algo, X, y, nFolds, 0.90) \n", + " (pac5, pacm5, hcs5, s5) = kFoldValidationWithProb(algo, X, y, nFolds, 0.95)\n", + " (pac9, pacm9, hcs9, s9) = kFoldValidationWithProb(algo, X, y, nFolds, 0.99)\n", + " \n", + " probs = [0.90, 0.95, 0.99]\n", + " pacs = [pac0.mean() * 100, pac5.mean() * 100, pac9.mean() * 100]\n", + " hcs = [hcs0.mean() * 100, hcs5.mean() * 100, hcs9.mean() * 100]\n", + " ss = [s0.mean() * 100, s5.mean() * 100, s9.mean() * 100]\n", + " \n", + " mpl.rcParams['font.size'] = 16\n", + " fig, axes = displayHelpers.showCategoryChart([\"90%\", \"95%\", \"99%\"], [pacs, hcs, ss],\n", + " [\"% high confidence\", \"high confidence accuracy\", \"overall accuracy\"],\n", + " ['r', 'g', 'b'], \"Percent\", \"High confidence predictions\",\n", + " width=0.15, figsize=(6,5))\n", + " axes.set_yticks(range(0, 100, 10))\n", + " axes.axhline(50, label = \"50%\")\n", + " axes.axhline(90, label = \"90%\")\n", + " # axes.get_legend().set_bbox_\n", + " axes.set_ylim(top=100)\n", + " fig.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 715 high confidence predictions out of 1462\n", + "Found 734 high confidence predictions out of 1462\n", + "Found 746 high confidence predictions out of 1461\n", + "Found 723 high confidence predictions out of 1461\n", + "Found 635 high confidence predictions out of 1461\n", + "for prob 0.9, percentage auto classified 0.486243517033\n", + "for prob 0.9, scoring only on high confidence predictions 0.985758576489\n", + "for prob 0.9, scoring on all predictions 0.88189282494\n", + "Found 701 high confidence predictions out of 1462\n", + "Found 706 high confidence predictions out of 1462\n", + "Found 716 high confidence predictions out of 1461\n", + "Found 697 high confidence predictions out of 1461\n", + "Found 733 high confidence predictions out of 1461\n", + "for prob 0.95, percentage auto classified 0.486247449651\n", + "for prob 0.95, scoring only on high confidence predictions 0.985937714804\n", + "for prob 0.95, scoring on all predictions 0.881347314725\n", + "Found 745 high confidence predictions out of 1462\n", + "Found 723 high confidence predictions out of 1462\n", + "Found 686 high confidence predictions out of 1461\n", + "Found 712 high confidence predictions out of 1461\n", + "Found 719 high confidence predictions out of 1461\n", + "for prob 0.99, percentage auto classified 0.490622299252\n", + "for prob 0.99, scoring only on high confidence predictions 0.986019297061\n", + "for prob 0.99, scoring on all predictions 0.887642030691\n", + "3\n", + "len(rectList) = 3, len(countLabelList) = 3\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/matplotlib/figure.py:403: UserWarning: matplotlib is currently using a non-GUI backend, so cannot show the figure\n", + " \"matplotlib is currently using a non-GUI backend, \"\n" + ] + }, + { + "data": { + "image/png": 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q1A7W1tbxO3fuHGPoFjZ06NA/X3vttflfffVVx0GDBiV/3hISEhzffffdWZMn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\nRvu8cfyFqrqmqhZU1YKZM2dOpCxJ0gS4zUOSJm5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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpaceBarGraph(forestClf, cleanedFeatureMatrix, cleanedResultVector, 5)" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 1121 high confidence predictions out of 1462\n", + "Found 593 high confidence predictions out of 1462\n", + "Found 394 high confidence predictions out of 1461\n", + "Found 1360 high confidence predictions out of 1461\n", + "Found 579 high confidence predictions out of 1461\n", + "for prob 0.9, percentage auto classified 0.553843618532\n", + "for prob 0.9, scoring only on high confidence predictions 0.512850091077\n", + "for prob 0.9, scoring on all predictions 0.548407055865\n", + "Found 843 high confidence predictions out of 1462\n", + "Found 819 high confidence predictions out of 1462\n", + "Found 307 high confidence predictions out of 1461\n", + "Found 874 high confidence predictions out of 1461\n", + "Found 765 high confidence predictions out of 1461\n", + "for prob 0.95, percentage auto classified 0.49375266271\n", + "for prob 0.95, scoring only on high confidence predictions 0.810332720036\n", + "for prob 0.95, scoring on all predictions 0.690722393728\n", + "Found 1262 high confidence predictions out of 1462\n", + "Found 1355 high confidence predictions out of 1462\n", + "Found 604 high confidence predictions out of 1461\n", + "Found 779 high confidence predictions out of 1461\n", + "Found 958 high confidence predictions out of 1461\n", + "for prob 0.99, percentage auto classified 0.678468170612\n", + "for prob 0.99, scoring only on high confidence predictions 0.645789657817\n", + "for prob 0.99, scoring on all predictions 0.574409803079\n", + "3\n", + "len(rectList) = 3, len(countLabelList) = 3\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/matplotlib/figure.py:403: UserWarning: matplotlib is currently using a non-GUI backend, so cannot show the figure\n", + " \"matplotlib is currently using a non-GUI backend, \"\n" + ] + }, + { + "data": { + "image/png": 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zT6WUUpcuXVIAVP369ZWpL774QgFQV69eVUopde7cOWUwGNSQIUNUVpYtW6YA\nqD179qQrnzhxorKzs1M3btzIctmMkpOTVVJSkipbtqwaPHhwWvlHH32kDAaDCg0NzXLZevXqqWLF\niqm7d+9mWcff31/16NEjUzkANXbs2LTnY8eOVQDUtGnTso03NTVVJSUlqYkTJ6oCBQqolJQUpVTu\n9tuFCxeUwWBQy5YtSys7duyYAqBWrVqV7XofF+t/3Odd9erVVenSpVVSUlJa2cWLF5WtrW2616NM\nmTKqU6dO6ZZt3bq1qlChQtrzTz75RDk4OKizZ8+mq/fWW28pLy+vtHUsXrxYAVDG91tWjMfL8uXL\nlYiomzdvps2rX79+uvfjrl27FAC1a9euXG97Vu3HxMQoV1dX1aZNmyyX/fnnnxUANX369CzrGLfz\n0qVL6cqN7xdTAJSfn5+Kj4/PNubk5GR19+5d5erqqr766qu08m7duikXF5e0/0Xm9OjRQ5UqVUql\npqamlbVp00aVL18+23UqpVR0dHS28wEcVtnkycbpmenmAQCTJk068e+///ZYuHBh/7CwsC6LFi3a\n16VLl5djY2N9165du2r9+vU+RYsWHWdvb7/K09NzuunPy9mpVKnSYdPnVapUCQOAQ4cOZTpbZHT9\n+vVyAQEBh/39/RONZY0bN4728fH5O7/WMW/evArJyclOrVu33pZVnYMHD1YCkDpnzpw9puWtW7fe\nlZqaarts2bJ0X0ODgoLSxREYGBiemppqt3fv3gLIg61bt5YFYOjXr99vpuWtWrX61fT5ihUr/O7e\nvetXt27d3XFxcQbjVLx48YTChQufDg8PT/caubm5/du1a9drxuf16tWLcXR0jLl586Y3oHUtiYiI\nqFC5cuU9pvve1Jw5c8onJyc7t2zZMt06mzVrFunu7v7P6dOnK+VlW8m8wYMHpzuWChUqFG7uDKvR\n+vXrA1JSUhybN2/+u2n5gAEDfs9qmbyuAwD+/PPPFxwdHaPnzp17MKs6165dq+Tv73/I9PqKihUr\n3gsMDPzj2rVr6Y5JGxubhMmTJx83Pvfx8Ul2d3f/9/bt294AsHTp0iqrVq0aBgDnz5/v27dv3yHH\njx/P9H66cOGCy8WLFxt7enrKwoUL5/To0WPCli1b/EuWLJkQGBiYLtYdO3ZUMxgMyZ9//vnvcXFx\nhtTUVCQnJ6NJkyYAgL1796Zr2/SsHIC0M8GXL2vXfu7cuROpqal4++23s9xvW7duhb+/f9pZauPU\npEkTJCWWZ2UQAAAgAElEQVQlme2yYWrnzp1o0KABvLy8YGtrCzs7O5w9ezbdz/Lbt29HzZo18cIL\nL5htIz4+Hr///ju6dOkCZ2fnbNeXF23atMlUdu3aNfTt2xf+/v6wt7eHnZ0dxowZg9u3byMiIiJt\nm3LabyVLlkTTpk0xb968tLJ58+bB29sbbdu2zbdteJbcvXsXoaGh6NixY7q+uYGBgahbty727Hnw\ncdetWzeEhIQgLi4OAHDr1i1s2bIF3bp1S6uzdetW1K5dG4GBgemO7aZNm+LWrVs4depUuvWbO15i\nY2MxfPhwlCpVCg4ODrCzs0O3bt2glMK5c+ceeptz0/6+fftw586dbI/H7du3Q0TQp0+fh47JqFmz\nZnBycspUvmbNGtSuXRsFChSAra0tXFxccOfOnUzv+RYtWqBIkSJZtv/OO+/gwoUL+Pln7QfHa9eu\nYdOmTdluZ357ppJpAPDy8kru3bv31WLFiiWeOnXK6fvvv+/dtWvX+f7+/on9+/cfWqBAgchz5871\naNy48cYpU6aMPnjwoFtObXp4eMSZPnd0dEwCgDt37thltcy9e/c83dzcYjKWu7i43M6vdURGRroB\nQPny5W9mVefu3btu9vb2d7y8vNJ1GitTpkw0AERFRaXb/kKFCqWLw8HBIQkAoqOj7bNahzkREREF\nAaBmzZrptrdUqVLRps/Pnz9fAND6krq7u28wna5cuVIzISEhXXwODg53Mq7LYDAkJSUl2QHA33//\n7QrA4O3tneU+uXbtmgcAfPHFFxMzrjMmJibg3r17OR4TlLPnn38+3bFkY2OTlJKSkuXxfOXKFU8A\nCAwMTPe+CQoKMvuesWQdAHDv3j03Z2fnW9nVSUxMdPPw8IjOWO7h4XE7MTHR1bTM3t4+0zGpx2G/\ncuXKiuvXr//E1tY2HgA8PT333Lp1q/Knn3468fbt22lZQEpKCsaOHfvxvXv3PFxcXC40b958Umpq\nqs2CBQs+O3z4sJe7u3u6fRAbG1sgNTXVNiAgYJ27u/uGGTNmwM7ODj4+2iULt26l37yCBQume268\nYMrYv9pYv1ixYlnuk4iICISHh8POzi7dVKtWLbPrNBUaGopXX30Vrq6uWLhwIQ4cOIBDhw6hatWq\n6fp437p1K9sYoqOjkZqamm0dS/j5+aV7npqailatWmHz5s0YM2YMfvnlFxw6dAijR48GkLf9BmjJ\nwO+//44TJ06kdXHp1asX7O3z9G+VdNHR0VBKZXrdAMDX1xdRUQ8GleratSvu37+PdevWAQBWr16N\n5ORkdO3aNa1OREQE9u7dm+nYbt++PYDMx7a59fbq1Qtz587F4MGDsWPHDhw6dAhff/01AKQ7xi2V\nm/ZzczzeunULBQsWNJv8Wsrc/ti0aRM6duyIChUq4Ntvv8Uff/yBQ4cOwdvbO0/veQCoVasWqlev\njrlztRGNFyxYAFtbW/To0SPftiEnz0yfaXO6dOnSxdvb+8K8efP+OHPmjFNkZGSFcePGzfb3909c\nu3btzw4ODr2XLVtWrlatWodzbi1vnJycouPi4jwylt+9ezdPZ3izU7hw4VgAOHv2rBcAs8OLubi4\nxCUmJrreunXL1jShPnfunCcAFCxYMM7ccg/Lx8cnCgAOHTpUoGTJkjeM5RcuXPA0rVeiRIlYAAgO\nDl766quvHsvYjpOTU3LGsuxUqFDhDoDUmzdvZnnxpre3dxwAdOjQYVqNGjUy7Tdvb2/2l7aC4sWL\nRwPApUuX0r1v9u/fn2/vGQBwdnaOjY6O9s+ujr29fVxsbGym9cbExBQwlzxnZfv27Z0dHR0jmjdv\nPnvDhg1zvby8Tnfq1Gnb4sWLv5oxY0YTY725c+fWjomJqeDs7HwxISEhqU+fPqFNmjQ5/d577y1Y\ntmxZu9jY2HSffK6urnEGgyFx8uTJIwDgzz///Or99x9cEpLdWR5zChXSrru9evUqypUrZ7aOl5cX\nAgMDsWbNGrPzAwICsmx//fr1sLW1xffffw87uwffdaKjo1GgwIPdXKhQIVy9ejXLdjw9PWEwGLKt\nAwCOjo5ITEz/w1R2yX7Gi6ouXLiAw4cPY/ny5emSrk2bNqWrl5v9Bmi/DAQEBGDevHmoWrUq4uLi\nHutZtf8aT09PiAiuX7+ead7169fTfXk0nq02foFZsWIFgoODUbx48bQ6Xl5e8PHxwfTp5m8TkfG1\nzXi83L9/HyEhIRg3bly6ixqPHz+O/JDb9k2Px8qVzf/wXqhQIURFReHevXtZJtTGvv25fQ+Zu233\nd999h9KlS2PJkiVpZUlJSem+6Bjjyen9DGhfSPv27YurV69iwYIFaN++faaTBI/SM3dm2mjGjBkB\nJ06ceGXq1KnzTMujo6MdAe1K+JSUFDul1CMZrt7X1/dMWFhYjfDw8LRTDzt37vSMiIiomF/r6Nev\n32lbW9t7GzZsaJpVndq1a58AYBg0aFBd0/KQkJBgg8GQ3L1790dyKXmzZs3OAkidO3fuS6blGzdu\nrGf6vHv37lednZ1vXL16tcSwYcPOZ5wGDhwYlpf1+vv7J/r4+Jw6fvx48D///GP2tE/fvn3/trW1\nvXf58mU/c+vs2bNnzu9synft2rULs7Gxuf/jjz+mO1ZnzZr1UlbLWOKFF1748/79+579+/evmVWd\nIkWKnAgPD69x5syZtE+bM2fOOIWFhdUqUqRIrj8hY2Jiyvn4+By1s7NLuy1F27Ztz9vZ2cVduHAh\nbRSakydP1rK3t48KDAw8HBkZWW7Tpk2F/P394wsXLnzw8uXLtS9dulTLtN1GjRodSU1NtY+MjHQe\nNmzY+cKFC6NGjRppU16T6caNG8NgMGQavcBUs2bNcOXKFbi6uqZbl3EyfpCbEx8fDxsbm3Qfur/8\n8ktaNxOjJk2a4ODBgzh2LNP3agCAs7MzXnrpJaxYsSLbURL8/f1x4kT6+wD9+OOPWdY3Fy+AdIl/\nUlISVq5cma5ebvYbABgMBvTt2xfLly/HrFmz0LhxY5QqVSrX8VB6Li4uqF69OtauXZtudJXw8HDs\n27cv081Punfvjt27d2P37t3Yv39/ui4eANJGsihRooTZY9vNLfsfKxMSEpCSkpLueAGQLpF8GLlt\nv06dOnB1dc32eGzSpAmUUliwINOgYmn8/bVzDabvoeTk5LSLAnMjPj4+0/B4y5cvzzQaTpMmTbB5\n82Zcu3YN2encuTPc3Nzwxhtv4PLly+jXr1+uY8kPz+SZ6eTkZEycOLF/3bp11xnvxleuXLl7Xl5e\nZ2bOnNkjKipqzfbt218UkdSuXbs+kmRy+PDhq/v27VunZs2an7Rp0+aHhIQEuw0bNnR0cHC4LSL5\ncr+ncuXK3WvSpMmyLVu29A0MDBzRqFGjPR4eHveOHTsWaG9vn7Rly5bNU6ZMObJmzZpTa9eufScq\nKsqjUqVKl3/55Zfqf//9d5NatWqtDQoKeiRnpnv27Hn1s88+27Nnz54uwcHBhurVq5/bs2fPCxcv\nXqxhWs/W1ha9e/ee+/XXX48pVaqUXXBw8G++vr6xV69eLXDs2LHy3t7ekdu3bw/Jy7rff//9xaNH\nj55UpUqVL5o1a7bB39//5rlz53zPnz8feOzYsW8qVqx479VXX128adOmfpUrV/aoW7fukYIFC94N\nDw/3OnbsWOXnn3/++MqVK/fmvCbKTy+88MLdmjVrbjxw4ED7mjVr3nv55ZeP/fnnn6UOHTr0CgAY\nDIZ8ed/Mnz9/9+7du5vOnz9/2KlTp9bVrFnzTExMjNP+/furvf/++yG9e/e++v77769+9913a9ap\nU2fia6+9tl5E1IYNG9olJyc7DBkyJC+X5qfa2Nhk+nVFRJLu3LnjD+AqAMTExJRwc3MLnzp1akj9\n+vWbd+nS5ZM2bdp8e+PGDRw8eNDbxsYm3SmhSZMmnVi7du3eadOmjTxw4MAGLy8v7NixA2FhYdiy\nZQs+//xzlC1bNtdBlipVCkOGDMFXX32FuLg4tGrVCjY2Njh48CDKly+Pjh07okuXLli8eDEaNWqE\noUOHomrVqkhMTMSFCxewceNGbNiwIct+zM2aNcO0adPQs2dP9OrVC2fPnsWECRNQtGjRdPWGDBmC\nb7/9Fo0bN8aYMWNQpUoV3Lx5EyEhIZg7dy7c3Nzw5Zdfon79+ggKCsLQoUNRrFgxXLx4EUePHsXM\nmTMBaKMV9O7dG0OGDEGLFi1w7NixPCU2FSpUgL+/P0aPHg0bGxvY2dlh6tSpFu03ozfffBPjxo3D\nsWPHMo22Qnk3YcIENG/eHC1atMA777yDO3fuYOzYsfDw8MDQoUPT1W3fvj0GDRqErl27wsnJCa+/\nnm6UVAwZMgSrV69GvXr1MGTIEJQrVw53797F6dOn8euvvyIkJPuPIA8PD7z44ouYMmUK/Pz8UKhQ\nISxatChXZ1xzI7ftu7m5YdKkSRg0aBDatWuHLl26wM3NDUePHoWjoyMGDRqEBg0aoF27dnj//fdx\n5coVNGzYEElJSdi7dy+aN2+O4OBg1KxZE6VKlcKwYcOQmpoKBwcHzJ49O93wlDlp1qwZNmzYkPYe\nPHz4MGbOnJnulygAGD9+PLZs2YI6depg1KhRKF26NK5evYqtW7dixYoVafWcnJzQs2dPTJ06FVWq\nVEGdOnUebqfmkeXJ9FN829pOnTo1vn//vtv69et/MC2fMWPGV0OHDh0wffr0US4uLhGDBg2a/KiS\nyT59+lw5ffr0J4sWLeq1YMGC4U5OTrcaNWq0/tixY9ViYmJ8cm4hd3788ccfe/fuHb1x48a2ixcv\nHmowGFI8PDyudOzYcTUAODg4qN27d4/v1KlT9z179rTbvn27m4uLS0STJk0W/vjjj3lKUvNqx44d\nX7do0eL+vn372vz222+2RYoU+WvYsGFfjh8//nPTejNnzjzi4+Mz4ptvvumwfPnyQSkpKfaOjo7R\nvr6+Z9q2bftrVu1nZfjw4efs7e0/nDp1apf169e/nZKSYufi4hJZo0aNncY6ISEhWwcNGhS5du3a\ntosWLaqvlLJxcnK6VaxYsZPBwcGX8mP7H5alt/N+mv3888/fNmzYEEePHm0SGhra0tvb++ywYcOm\njR079n8uLi75crOlAgUKpOzfv//jTp06dT58+HDTX3/9tZODg0Ocr6/v32XKlLkDAAMHDgyLjY0d\nNWvWrG5Lly59D4B4e3uf+fTTT0eaDouXE2dn56s3b94sB2CzsWz//v3eSUlJniKSdoomKSnJzdnZ\nOSIoKChu8uTJoydPnvz2ihUrhtjb2yeWKFECBQoU+P3gwYPpjoeTJ09Oad26dYs//vjjldi4OPy0\nfSc8CxdF2ep1sep4DBwvnkbUDe3D9qcT13Br64PzBhf+0s4If3vwMv64r5V7N34LrRNcsWnzKixa\nvAT2js7wDSyLZr3KIkxf9pWhM2C3Zj4mT52FqOv/wN7RGV5+xVGuVn1M23URNjZZfeT4o2W/0djy\nwxKsXrsOvv5l8Oqgifhl1VxcjorH5yaxdZqwBNuXTsdH4yciPi4GrgW8UKpqbczYdQm29vYA3PDW\n/1Zgx/KZeLv/ACQnJcLTpwiqv9ImrZ3UwrXRuOtALPl2Nb6eMxcBlarjtfe+xPE3m+K38zfT6v12\nXru04n/bTmeKvfWwqQiZPRFvdO0GJ1cP1GjSFlWfb4QL0z/GnD0XUPD0/VzvN6MSlWrgethZnHYo\nm26brW3yT9Zd/+dbLVkqAD3Gz8XPK79G29fbw8bWDiWfq4UeH07H8r9igb/S30OsbM1gHP9tG6oG\nN8fs3zMnuR0+WYKfv52NUeMmIvZWBBxd3OBdLBCV676S9lodPq6dPZ239wIKnU//HfnlfhMRNWs8\n+vTrDzt7Rzz3cjPU6/4BLoztn+59djkqXt9m7bm596I5uW0fpRujy6hp2Lt+ETZ2fgM2NrbwKVEK\nDTv3S1tntV7jEOdSDIu/XYOvpk6Do7MripWtDFWuYVo7rYZNxYavJ6BLtx5wcvPAS691R2mvUggP\n/zrTsbvvws1MZanF66FBp75YuGwlvp4zF8XKVEbbETOwfMIgHL8ak65+r89XYvuy6Xjvgw+ReC8e\n7l6FUTGoYaY27xfXfkwsWa91rt8/NknxOPRv7r8EZEVUNje9P3v2bL+yZcvyJ+3H5Pz5846VK1f+\nJjAw8NDff/8909rxED0NevfuXWfx4sUjxowZM2LChAmncl7iyfHll1/W37Nnz9By5cqt6dWr16Zr\n1665Ll26dGBMTEwFEUkOCQl5HQA6dOgw18PD48L8+fO/MF3+s88+e2X//v2DPvroo961atVKd1Ht\np59+2vTkyZNNASDZzrV09c4WDaNPj0l8XAwm92iIl17rjibd3815ASJKZ9uSafg9ZDlGrdgDRxfX\nnBdAzsn0mn51jiilamRZQfdMdvN4UlStWvXtKlWqnPb3948KDw8vuHXr1pZJSUmuAwYM2JTz0kTP\nns8++6zs5s2ba1SrVu2ss7Nz4pEjR0r/+uuvrxcqVOjM2LFjn6pEGgA++OCDPTdu3Ch29uzZNiNG\njOggIsrX1/dXOzu7w3FxcWkXQdrZ2d1JSkrK9OkQHx/vBgDFihXLdNHj6NGjtwHYBgBDhgzZOLwZ\nb/7xJIqMjMSZM2cwfeF02AqwYsrHZkc/ICLz/vzzT5w5cwYHN6/AgP59MbZdjrlvmtu3b+ODAllf\nw74ml12vmUxbUVJSkv3333/fMyEhoYDBYEgqVKjQuVGjRo3J60V1RM8KLy+v+xcvXqx85MiR5klJ\nSc4ODg4xZcuW/W358uVLM17M8rT44osvVl6/fn1daGiob/HixWOqVKlyu2PHjrO9vLzSvhy4u7tf\njoyMzDS48s2bN4s7ODhEFilS5OHH1iKr+PHHH9GrVy+UKFECS5cuZSJNlEdt2rTBjRs30LRpU4wf\nP94qMTydnz7/EadOnZpl7RiIniZ9+/a93Ldv31HWjiO/+fr6Jrz66qvhADB//vxq8fHxxdq0aTPD\nOL9SpUp/bNu2rfHy5csrd+vW7QQAXLlyxenGjRu1ihcvvierdunJ17NnT/Ts2dPaYRA9tUxvhW4t\nTKaJiKwkJCSk5IEDB6qXLFnyAgCcOXOm4rlz59qWKVNmfadOndKuoOnbt+/BAwcOnA4JCXk/MjJy\nsbu7+509e/a0ByBdu3b93mobQERETKaJiKzFwcEh+cqVKzVOnz7dNjU11c7Z2fmfoKCgr0eMGPGz\naT07Ozs1bty4T6ZMmdL7119/7Z+ammrv4eFxunfv3qMyXnhIRESPV07JdGpqaqrk1/itRET0QLNm\nzS43a9ZseG7qli5d+s6cOXNmAJiRY2UiIspWdqPZ5VW2d0BMTU29fe/ePZd8WxsRERERkZWlpKTA\nYMifG4Fn20p8fPzv169f97h7965ramrqI7mtNhERERHR46CUQnJyMuLj4+Ho6JgvbWbbzaNatWpX\nQ0NDNyUlJdU1GAy+yCH5JiKiJ4+9vT1u375t7TCIiJ4IBoMBjo6OsLe3z5f2sr0DIhERPf1q1Kih\nDh8+bO0wiIieKiKSqzsg8kwzEREREZGFmEwTEREREVmIyTQRERERkYWYTBMRERERWYjJNBERERGR\nhZhMExERERFZiMk0EREREZGFmEwTEREREVmIyTQRERERkYWYTBMRERERWYjJNBERERGRhZhMExFZ\nkYjUFZHtIhIhInEiEioivTPU8RSRBSJyU0TuishOEalirZiJiOgBJtNERFYiIs8B2AnADkAfAG0B\nHAKwUET663UEwCYAzQAMAtBOr79LRIpZI24iInrA1toBEBE9wzoBsAHQUil1Ry/boSfZ3QHMAdAK\nQF0ADZVSuwBARPYDuATgQwCDH3vURESUhsk0EZH12ANIBBCfoTwGgKf+dysA/xoTaQBQSsWIyCYA\nrcFkmp5gMl7ypR01VuVLO0SPArt5EBFZzxIAAmCGiBQRkQIi0gdAIwBT9TqVAJwws+xJACVExPWx\nREpERGYxmSYishKl1AkAwQBeA3AVQDSArwH0U0p9p1crqJdnFKU/epqZBxF5W0QOi8jhyMjIfI2b\niIgeYDJNRGQlIlIGwHpoZ5lbAmgMYC6AuSLS5WHaVkp9o5SqoZSq4e3t/fDBEhGRWewzTURkPZ8B\nSIJ2AWKiXvaziHgBmC4iq6CdlTZ39rmg/mjurDURET0mPDNNRGQ9VQD8ZZJIGx0E4AXAB9pZ60pm\nlq0I4LLJKCBERGQFTKaJiKznOoDnRMQ+Q3ltAPeh9YveCKCoiNQ3zhQRd2jdQjY+rkCJiMg8JtNE\nRNYzC0BJAJtEpLWINBGRWQA6A5ijn7HeCGA/gBUi0klEmuplAuB/1gqciIg0TKaJiKxEKbUOwKsA\nHAAsgHYx4ksABgAYptdJBdACwA4AswH8ACAFQAOl1BUrhE1ERCZ4ASIRkRUppX4C8FMOdaIA9NYn\nIiJ6gvDMNBERERGRhZhMExERERFZiMk0EREREZGFmEwTEREREVmIyTQRERERkYWYTBMRERERWYjJ\nNBERERGRhZhMExERERFZiMk0EREREZGFmEwTEREREVmIyTQRERERkYWYTBMRERERWYjJNBERERGR\nhZhMExERERFZiMk0EZGViMhuEVFZTFtN6nmKyAIRuSkid0Vkp4hUsWbsRESksbV2AEREz7B3ALhn\nKAsC8BWAjQAgIgJgE4AAAIMARAMYCWCXiDyvlPrnsUVLRESZMJkmIrISpdSpjGUi0gdAIoDv9KJW\nAOoCaKiU2qXX2Q/gEoAPAQx+PNESEZE57OZBRPSEEBFnAO0BbFJKRenFrQD8a0ykAUApFQPtbHXr\nxx8lERGZYjJNRPTkaAPADcBSk7JKAE6YqXsSQAkRcX0cgRERkXlMpomInhzdAUQA+MmkrCC0ftIZ\nGc9cez7qoIiIKGtMpomIngAiUgRAYwArlVLJ+dDe2yJyWEQOR0ZGPnyARERkFpNpIqInQ1do/5OX\nZiiPhvmzzwVN5meilPpGKVVDKVXD29s7/6IkIqJ0OJoHEdGToQeAY0qpYxnKTwJoYqZ+RQCXlVJ3\nHnlkRFYmkn9tKZV/bREBPDNNRGR1IlIDWnKc8aw0oI03XVRE6pvUdwfQUp9HRERWxGSaiMj6ugNI\nBrDSzLyNAPYDWCEinUSkqV4mAP73+EIkIiJz2M2DiMiKRMQOQGcAW5VSERnnK6VSRaQFgC8BzAbg\nCC25bqCUuvJYgyWi/x72oXloTKaJiKxIKZUEINsrBPUbuPTWJyIieoKwmwcRERERkYWYTBMRERER\nWYjJNBERERGRhZhMExERERFZiMk0EREREZGFmEwTEREREVmIyTQRERERkYU4zjQRERERPTQZnz83\ngFFjn66bv/DMNBERERGRhZhMExERERFZiMk0EREREZGFmEwTEREREVmIyTQRERERkYWYTBMRERER\nWYjJNBGRlYnIqyKyV0TuiEisiBwWkYYm8z1FZIGI3BSRuyKyU0SqWDNmIiLSMJkmIrIiEekLIATA\nEQBtALQHsBaAsz5fAGwC0AzAIADtANgB2CUixawRMxERPcCbthARWYmIBACYBmCYUmqayaxtJn+3\nAlAXQEOl1C59uf0ALgH4EMDgxxIsERGZxTPTRETW0xtAKoC52dRpBeBfYyINAEqpGGhnq1s/2vCI\niCgnTKaJiKznJQCnAXQSkQsikiwi50VkgEmdSgBOmFn2JIASIuL6OAIlIiLzmEwTEVlPEQBlAHwB\nYDKAJgB2AJglIu/qdQoCiDazbJT+6PmogyQioqwxmSYispCIpIhIrSzmVReRlByaMABwA9BXKTVf\nKfWLUqo/gK0ARj5kbG/ro4IcjoyMfJimiIgoG0ymiYgsJ9nMswGgclj+lv64I0P5dgCFRcQP2llp\nc2efC+qP5s5aQyn1jVKqhlKqhre3dw5hEBGRpZhMExHlkYgYRMRGf2rQn5tOLgD+D8DNHJo6mYvV\nnYTWbzqjigAuK6Xu5D5yIiLKb0ymiYjyQETGAkgCkAjtzPPv+nPTKRbAx9DGi87OD/pj0wzlzQD8\no5S6BmAjgKIiUt8kBncALfV5RERkRRxnmogob3brjwItYV4I4J8MdRIAnAKwOYe2tgDYBWCeiBQC\ncBHaTVuaAOil19kIYD+AFSIyDFq3jpH6+v/3MBtCREQPj8k0EVEeKKX2ANgDACKiAMxXSv1rYVtK\nRF4DMAnAeGh9o08D6KKU+lavkyoiLQB8CWA2AEdoyXUDpdSVh90eIiJ6OEymiYgspJQanw9txAIY\noE9Z1YmCdoOX3g+7PiIiyl9MpomIHoLel7kzgBLQzhqbUkqpRo8/KiKip5dkN05SHqmcxlTKB0ym\niYgsJCJ9AcyBdgOVs9D6Sqer8tiDIiKix4rJNBGR5YYC+BZAb6VUorWDISKix49D4xERWa4ogMVM\npImInl1MpomILHcEQElrB0FERNbDbh5ERJYbDGCliJxRSu21djCPTH5dDfQ4rgQiInrMmEwTEVlu\nEwB3ALtEJB7aDVVMKaWU/+MPi4iIHhcm00RElvsZ2i3F6TF72obOIqL/LibTREQWUkr1tHYMRERk\nXbwAkYiIiIjIQkymiYgegoi8ICLfi8hNEUkWkWp6+Wci0sza8RER0aPFZJqIyEIi8hKA/QDKQ7t5\ni+n/1FQA/awRFxERPT5MpomILDcZwDYAlQC8n2FeKIBqjz0iIiJ6rHgBIhGR5aoBaKuUUiKScUyI\nmwC8rRATERE9RjwzTURkufsAnLOY5wcgJruFRSRYRJSZ6XaGep4iskDvl31XRHaKSJV82gYiInoI\nPDNNRGS53wC8JyIhJmXGM9RvAvgll+0MBnDI5Hmy8Q8REWg3hwkAMAjajWFGQrtRzPNKqX8sC52I\niPIDk2kiIst9BOB3AMcArIOWSPcQka8AVAdQM5ft/K2UOpDFvFYA6gJoqJTaBQAish/AJQAfQkvE\nnxZio1sAABQJSURBVAoyPh/vtMJ75RDRE4LdPIiILKSUOgbgZQA3AIwGIAAG6rPrK6XO5MNqWgH4\n15hI6+uNgXa2unU+tE9ERA+ByTQR0UNQSoUqpRoBcANQDIC7UqqBUurPPDSzUkRSROSWiHwrIiVM\n5lUCcMLMMicBlBARV8ujJyKih8VuHkREFhIROwD2Sqm7Sqn7AP41mecCIFEplZRNEzEApgDYAyAW\nwAsARgHYLyIvKKUiABQEEGZm2Sj90RPAnezivBh5Fx3n7c/dRpnTeZLly5oonJAvzWg6P8T2ZNBx\nXr41RRkUTsifY4ev9yOUT+9vIB/f40/Z681kmojIcgsA2AF4w8y8eQASAfTOamH97LXpGew9IrIX\nwEFoFxt+ZGlgIvI2gLcBwNWvlKXNEBFRDkQpXsRBRGQJEbkMYJhSarWZeR0AfKGU8reg3VMAriil\nmorIHwBuK6WaZqjzIYDPAbgppbI9M12jRg11+PDhvIZhujLLlzVtZly+NKMZl3+fXfwYfHTy7aJT\nvt6PTj69v4F8fI8/Ia+3iBxRStXIqR77TBMRWc4HQEQW8yIBFM6HdZyE1m86o4oALueUSBPlmUj+\nTUTPACbTRESWiwCQ1c1TqgC4ldcGRaQGgHIA/tCLNgIoKiL1Teq4A2ipzyMiIitin2kiIsttBvCR\niOxWSv1lLNTvTjgawA/ZLSwiKwBcgNZv2ngB4kgAVwHM0KttBLAfwAoRGYYHN20RAP/L160hIqI8\nYzJNRGS5jwG8AuCIiBwC8A+AogBqQbupypgclj8JoDOA96Ddlvw6gO8BjFVK3QQApVSqiLQA8CWA\n2QAcoSXXDZRSV/J9i4iIKE+YTBMRWUgpdVNEagJ4H1pS/TyAmwA+BTBVv7lKdstPApDjuFRKqSho\no4JkOTIIERFZB5NpIiILiIgNgMrQ7k74MbSz1ERE9IzhBYhERJZRAA5D6+dMRETPKCbTREQWUEql\nArgCwMXasRARkfUwmSYistw8AO+JiL21AyEiIutgn2kiIsu5ASgF4KLI/7d3/7F21/Udx58v+SFq\nQdpRibaWBmGSVvwRm40FtwpOAQMtC8zFberAAboJjg06GdOpkxC6MqNMUMQQI46oxB8lM2RUiuIs\naGf8QYdVHEgRdRdaiqDBYd/74/u96+nlFM799vaeQ+/zkZx87/l8P+fT98knN+fVz/2c7zc3AD+h\n2f4xrqrqH4ZSmSRpWhimJam7v+v5ud+VNgowTEvSHswwLUkdVZVb5SRphvODQJIkSerIMC1JuyCN\nZUlWJbk6ySFt+9Ikzxt2fZKk3cttHpLUUZLZwBeB3wZ+DswCLgN+BJwBbAbOGVqBkqTdzpVpSeru\nn4DnA0cDvwGk59wa4FXDKEqSNH1cmZak7pYD51XVuvb24r3uoQnakqQ9mCvTktTdLODHOzm3Hzuu\nVEuS9kCGaUnqbiPwmp2cWwp8dxprkSQNgWFakrq7nOZ24hcCC9q2A5OcBrwN+NBkB0xyQ5JK8r4J\n7bOTXJXk/iSPJFmT5MhdfgeSpF3inmlJ6qiqrkxyKPAe4L1t843ANmBlVX1yMuMleT3wkj7tAa4H\nFgJnA1uAC4C1SV5aVfd2fhOSpF1imJakjpIcBLwbuIJmu8dc4AHgxqr670mONRt4P3Au8K8TTi+j\nuWLIsVW1tu2/DrgLWIGX35OkoTFMS9IktFfteCfwduAA4Nc0q8ZvrqoHd2HoS4Dbq+raJP3C9H3j\nQRqgqrYmuZ7miiKGaUkaEsO0JE3OW4B3AWuB9cALgJOBh4DTugyY5BXAG+mzxaO1GLi9T/sG4I1J\nZlXVw13+bUnSrjFMS9LknAF8tKrOGm9IchbwL0nOqqpfTWawJPsCHwFWVdXGnXSbA9zdp31ze5wN\nGKYlaQi8mockTc6hwGcmtH0K2As4pMN4K4BnABftYl07SHJmkvVJ1o+NjU3l0JKkHoZpSZqcWTRb\nOnr9vD3uP5mBkiwALqTZg/30JAcmObA9Pf58L5qrd8zuM8Sc9rhl4omqurKqllTVkrlz506mLEnS\nJLjNQ5Imb157Sbxxe/W07/AlxCe5qsehNHdKvKbPufPax8to9kb3uznMIuAe90tL0vAYpiVp8q7b\nSfvn+7Tt1adt3LeAY/q0r6UJ2B8D7gRWA6clWVpVXwZIcgBwEo+/jJ4kaRoZpiVpcjpdsaOf9lJ6\nN09sb+7Rwo+q6ub2+WpgHXBNkvPZftOWACunqh5J0uQZpiVpEqrq40P4N7clORFYRXML8/1owvUx\nVbVpuuuRJG1nmJakEVNV6dO2GTi9fUiSRoRX85AkSZI6MkxLkiRJHRmmJUmSpI4M05IkSVJHhmlJ\nkiSpI8O0JEmS1JFhWpIkSerIMC1JkiR1ZJiWJEm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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "svmClf = svm.LinearSVC()\n", + "exploreKFoldValidationSpaceBarGraph(svmClf, cleanedFeatureMatrix, cleanedResultVector, 5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We now get the most important params for the decision tree so that we can better understand what it is doing." + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'bootstrap': True,\n", + " 'class_weight': None,\n", + " 'criterion': 'gini',\n", + " 'max_depth': None,\n", + " 'max_features': 'auto',\n", + " 'max_leaf_nodes': None,\n", + " 'min_impurity_split': 1e-07,\n", + " 'min_samples_leaf': 1,\n", + " 'min_samples_split': 2,\n", + " 'min_weight_fraction_leaf': 0.0,\n", + " 'n_estimators': 10,\n", + " 'n_jobs': 1,\n", + " 'oob_score': False,\n", + " 'random_state': None,\n", + " 'verbose': 0,\n", + " 'warm_start': False}" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "forestClf.get_params()" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "distance 0.0410742868716\n", + "duration 0.0220718466215\n", + "first filter mode 0.230302584374\n", + "sectionId 0.0104999251548\n", + "avg speed 0.174684512399\n", + "speed EV 0.0871829707735\n", + "speed variance 0.0974444899536\n", + "max speed 0.0286995608278\n", + "max accel 0.0222992709551\n", + "isCommute 0.00647869028559\n", + "heading change rate 0.0418053039276\n", + "stop rate 0.0501905023869\n", + "velocity change rate 0.0234609141724\n", + "start lat 0.0350415502397\n", + "start lng 0.0351077068004\n", + "stop lat 0.032310289723\n", + "stop lng 0.0357251786338\n", + "start hour 0.0136034558231\n", + "end hour 0.0120169600776\n", + "close to bus stop 0.0\n", + "close to train stop 0.0\n", + "close to airport 0.0\n" + ] + } + ], + "source": [ + "for (i, importance) in enumerate(forestClf.feature_importances_):\n", + " print(featureLabels[i], importance)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "So the highest importance features are:\n", + "\n", + "- first filter mode (moves mode)\n", + "- speed EV\n", + "- avg speed\n", + "- distance" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, let's try another non-parametric method like nearest neighbor" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from sklearn import neighbors" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "knnClf = neighbors.KNeighborsClassifier()" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 710 high confidence predictions out of 1462\n", + "Found 661 high confidence predictions out of 1462\n", + "Found 684 high confidence predictions out of 1461\n", + "Found 692 high confidence predictions out of 1461\n", + "Found 714 high confidence predictions out of 1461\n", + "for prob 0.9, percentage auto classified 0.473656706845\n", + "for prob 0.9, scoring only on high confidence predictions 0.91975210439\n", + "for prob 0.9, scoring on all predictions 0.753386779477\n", + "Found 630 high confidence predictions out of 1462\n", + "Found 724 high confidence predictions out of 1462\n", + "Found 727 high confidence predictions out of 1461\n", + "Found 660 high confidence predictions out of 1461\n", + "Found 724 high confidence predictions out of 1461\n", + "for prob 0.95, percentage auto classified 0.474205868776\n", + "for prob 0.95, scoring only on high confidence predictions 0.924081725881\n", + "for prob 0.95, scoring on all predictions 0.756673792195\n", + "Found 687 high confidence predictions out of 1462\n", + "Found 651 high confidence predictions out of 1462\n", + "Found 717 high confidence predictions out of 1461\n", + "Found 708 high confidence predictions out of 1461\n", + "Found 683 high confidence predictions out of 1461\n", + "for prob 0.99, percentage auto classified 0.471606408668\n", + "for prob 0.99, scoring only on high confidence predictions 0.915178125439\n", + "for prob 0.99, scoring on all predictions 0.755852156057\n", + "[0.47365670684490785, 0.4742058687760477, 0.47160640866823789]\n", + "[0.76199626076847204, 0.76560531824648714, 0.75392084920018865]\n", + "[0.17352064595886266, 0.17170274416251852, 0.18351807075040311]\n", + "[0.12211850191315195, 0.11542529118462427, 0.14641993962619709]\n", + "[0.18642754087251712, 0.18715257193989779, 0.17145726531407418]\n", + "[0.2988419508963453, 0.29670639692562245, 0.29616989504266211]\n", + "[0.30500795959203436, 0.23047619047619045, 0.29616989504266211]\n", + "[0.9197521043901602, 0.92408172588091586, 0.91517812543904553]\n", + "[0.75338677947660604, 0.75667379219487807, 0.75585215605749478]\n" + ] + }, + { + "data": { + "image/png": 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VLofMdv1w5BzH9ddecJvcwrnJsS1Ux/m/lttEGwommM7l/Krnlsuo4/HcOWG0bhNie66N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\nzM4ys5vM7GEza5nZd83sHjP7wcmcEeqmivfRXJ1Lz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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "exploreKFoldValidationSpace(knnClf, cleanedFeatureMatrix, cleanedResultVector, 5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "knn does almost the same as decision tree, except that the accuracy of the high confidence predictions is a bit lower.\n", + "I think that the percentages are around the same as well. Basically, we can classify walk pretty well and the others pretty poorly.\n", + "So I am not sure what we are adding here over moves :)\n", + "\n", + "I'm surprised at the low prediction rate for cycling. Moves seems to get that pretty accurately for me.\n", + "\n", + "I'm now going to plot this data and see what it looks like." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Advanced features added" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18]\n", + "Found 728 high confidence predictions out of 1462\n", + "Found 778 high confidence predictions out of 1462\n", + "Found 711 high confidence predictions out of 1461\n", + "Found 721 high confidence predictions out of 1461\n", + "Found 763 high confidence predictions out of 1461\n", + "for prob 0.9, percentage auto classified 0.506498275735\n", + "for prob 0.9, scoring only on high confidence predictions 0.981667243778\n", + "for prob 0.9, scoring on all predictions 0.883536659017\n", + "Found 760 high confidence predictions out of 1462\n", + "Found 698 high confidence predictions out of 1462\n", + "Found 728 high confidence predictions out of 1461\n", + "Found 722 high confidence predictions out of 1461\n", + "Found 723 high confidence predictions out of 1461\n", + "for prob 0.95, percentage auto classified 0.496920292399\n", + "for prob 0.95, scoring only on high confidence predictions 0.981569856254\n", + "for prob 0.95, scoring on all predictions 0.882716052851\n", + "Found 719 high confidence predictions out of 1462\n", + "Found 762 high confidence predictions out of 1462\n", + "Found 751 high confidence predictions out of 1461\n", + "Found 715 high confidence predictions out of 1461\n", + "Found 727 high confidence predictions out of 1461\n", + "for prob 0.99, percentage auto classified 0.502804518016\n", + "for prob 0.99, scoring only on high confidence predictions 0.982343283753\n", + "for prob 0.99, scoring on all predictions 0.888190162651\n", + "[0.50649827573453332, 0.49692029239946783, 0.50280451801560122]\n", + "[0.77826571494033581, 0.77298540699594032, 0.79067247818930186]\n", + "[0.47525426468427867, 0.44064692264738542, 0.43560525881940781]\n", + "[0.06835267431219455, 0.048455532365718, 0.046294654688727767]\n", + "[0.081484515299463905, 0.075397361908710187, 0.0817228835978836]\n", + "[0.26242122272568402, 0.26067025588587928, 0.25497473219757855]\n", + "[0.28179639866032613, 0.068571428571428575, 0.25497473219757855]\n", + "[0.98166724377828962, 0.98156985625383475, 0.98234328375264646]\n", + "[0.88353665901678957, 0.88271605285063259, 0.88819016265118333]\n" + ] + }, + { + "data": { + "image/png": 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EhkJQSOHPUAgMKeFn4f7i+wKDK/oszsuVN9coIiIicqWy9gKW8flwM4kyb2rhpcyF3nxC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\nR3766Sfuvfdeli1b5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PfXL0ksk4gG2eOrDIET56q+FAiu17uS3uwQeqTLn9dgMPh6z73x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\nYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "Advanced_indices=[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18]\n", + "print(Advanced_indices)\n", + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,Advanced_indices], cleanedResultVector, 5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Spatial knowledge added" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 13, 14, 15, 16, 17, 18, 19, 20]\n", + "Found 775 high confidence predictions out of 1462\n", + "Found 730 high confidence predictions out of 1462\n", + "Found 778 high confidence predictions out of 1461\n", + "Found 808 high confidence predictions out of 1461\n", + "Found 724 high confidence predictions out of 1461\n", + "for prob 0.9, percentage auto classified 0.522104118855\n", + "for prob 0.9, scoring only on high confidence predictions 0.983697080266\n", + "for prob 0.9, scoring on all predictions 0.88490483534\n", + "Found 764 high confidence predictions out of 1462\n", + "Found 792 high confidence predictions out of 1462\n", + "Found 750 high confidence predictions out of 1461\n", + "Found 743 high confidence predictions out of 1461\n", + "Found 776 high confidence predictions out of 1461\n", + "for prob 0.95, percentage auto classified 0.523468268927\n", + "for prob 0.95, scoring only on high confidence predictions 0.985900153535\n", + "for prob 0.95, scoring on all predictions 0.889009270677\n", + "Found 757 high confidence predictions out of 1462\n", + "Found 789 high confidence predictions out of 1462\n", + "Found 753 high confidence predictions out of 1461\n", + "Found 711 high confidence predictions out of 1461\n", + "Found 761 high confidence predictions out of 1461\n", + "for prob 0.99, percentage auto classified 0.51607700814\n", + "for prob 0.99, scoring only on high confidence predictions 0.985330138564\n", + "for prob 0.99, scoring on all predictions 0.886821986328\n", + "[0.52210411885493424, 0.52346826892735976, 0.51607700813958179]\n", + "[0.79230772796633953, 0.7998697981818842, 0.78712820694929098]\n", + "[0.51183858489504963, 0.51497047366336124, 0.47847985179772029]\n", + "[0.06468267037303807, 0.05597507871218986, 0.050733487863843837]\n", + "[0.080054916327356465, 0.074988179669030736, 0.10287513658989988]\n", + "[0.2759828210136222, 0.27020791604600464, 0.28120164542235643]\n", + "[0.30784815713293801, 0.040000000000000001, 0.28120164542235643]\n", + "[0.98369708026555325, 0.98590015353459981, 0.98533013856409468]\n", + "[0.88490483534037279, 0.88900927067737467, 0.88682198632760001]\n" + ] + }, + { + "data": { + "image/png": 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6t8l0mSbo5xI2LuLZgLMOUwoMIiJnJZCCalBpZ0cvdGj1WHZrU4Y+gyopqIqcZ/6Eu7Nm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\ndQAAAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "Spatial_indices=[0,1,2,3,4,5,6,7,8,9,13,14,15,16,17,18,19,20]\n", + "print(Spatial_indices)\n", + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,Spatial_indices], cleanedResultVector, 5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Location and time features added" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 706 high confidence predictions out of 1462\n", + "Found 694 high confidence predictions out of 1462\n", + "Found 751 high confidence predictions out of 1461\n", + "Found 768 high confidence predictions out of 1461\n", + "Found 686 high confidence predictions out of 1461\n", + "for prob 0.9, percentage auto classified 0.493366517134\n", + "for prob 0.9, scoring only on high confidence predictions 0.985733861026\n", + "for prob 0.9, scoring on all predictions 0.889009457945\n", + "Found 728 high confidence predictions out of 1462\n", + "Found 751 high confidence predictions out of 1462\n", + "Found 718 high confidence predictions out of 1461\n", + "Found 723 high confidence predictions out of 1461\n", + "Found 658 high confidence predictions out of 1461\n", + "for prob 0.95, percentage auto classified 0.489663021505\n", + "for prob 0.95, scoring only on high confidence predictions 0.98592693703\n", + "for prob 0.95, scoring on all predictions 0.882989276127\n", + "Found 796 high confidence predictions out of 1462\n", + "Found 736 high confidence predictions out of 1462\n", + "Found 699 high confidence predictions out of 1461\n", + "Found 662 high confidence predictions out of 1461\n", + "Found 746 high confidence predictions out of 1461\n", + "for prob 0.99, percentage auto classified 0.498008503817\n", + "for prob 0.99, scoring only on high confidence predictions 0.984736398706\n", + "for prob 0.99, scoring on all predictions 0.885588923502\n", + "[0.49336651713357133, 0.48966302150486285, 0.4980085038169797]\n", + "[0.76063273303255163, 0.77627690682518735, 0.7680998202924687]\n", + "[0.43586421656656016, 0.40325734120483842, 0.44679703084052402]\n", + "[0.043714704967344822, 0.033210149466863362, 0.038669208424110382]\n", + "[0.061624365861654005, 0.06368757208497175, 0.097425854165767156]\n", + "[0.27103973022640576, 0.25559185838165821, 0.26717036463033839]\n", + "[0.26214595844241939, 0.0, 0.26717036463033839]\n", + "[0.9857338610259847, 0.98592693702995382, 0.98473639870577512]\n", + "[0.88900945794487041, 0.88298927612685885, 0.88558892350216423]\n" + ] + }, + { + "data": { + "image/png": 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0TkRERERERPxzQb8KQURERERERC4Ov0buREREpIysBeuA/NPgOF34mF/k9zMFP67thcte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XOsqimEEEJUctcyecnN6KOPPnLpbrZy5UoCAgKcXR27d+/O66+/TnR0tEsXOm/Vr1+f2NhYlixZ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\nERERaQEK7kRERERERFrA/w/wRm8lZpV57QAAAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix, cleanedResultVector, 5)" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 698 high confidence predictions out of 1462\n", + "Found 683 high confidence predictions out of 1462\n", + "Found 673 high confidence predictions out of 1461\n", + "Found 692 high confidence predictions out of 1461\n", + "Found 683 high confidence predictions out of 1461\n", + "for prob 0.9, percentage auto classified 0.469275209248\n", + "for prob 0.9, scoring only on high confidence predictions 0.922347451017\n", + "for prob 0.9, scoring on all predictions 0.75749336839\n", + "Found 710 high confidence predictions out of 1462\n", + "Found 707 high confidence predictions out of 1462\n", + "Found 655 high confidence predictions out of 1461\n", + "Found 681 high confidence predictions out of 1461\n", + "Found 695 high confidence predictions out of 1461\n", + "for prob 0.95, percentage auto classified 0.471872796681\n", + "for prob 0.95, scoring only on high confidence predictions 0.920737464683\n", + "for prob 0.95, scoring on all predictions 0.760503599749\n", + "Found 705 high confidence predictions out of 1462\n", + "Found 688 high confidence predictions out of 1462\n", + "Found 679 high confidence predictions out of 1461\n", + "Found 694 high confidence predictions out of 1461\n", + "Found 692 high confidence predictions out of 1461\n", + "for prob 0.99, percentage auto classified 0.473243969284\n", + "for prob 0.99, scoring only on high confidence predictions 0.918532765435\n", + "for prob 0.99, scoring on all predictions 0.760367175379\n", + "[0.46927520924801797, 0.47187279668087101, 0.47324396928438539]\n", + "[0.75879212687271047, 0.75711818545734888, 0.75870119985942153]\n", + "[0.16985138351100457, 0.17241406534481815, 0.18867903576571626]\n", + "[0.13415101424363543, 0.14052693847834002, 0.12878558997943296]\n", + "[0.184393511012963, 0.17100446015380705, 0.16901573215006052]\n", + "[0.28866469885267304, 0.29867254232035767, 0.29507688064788079]\n", + "[0.29073736051073584, 0.24285714285714283, 0.29507688064788079]\n", + "[0.92234745101680171, 0.92073746468261608, 0.91853276543512408]\n", + "[0.75749336838980852, 0.76050359974943615, 0.76036717537881882]\n" + ] + }, + { + "data": { + "image/png": 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JHQAAAAB4AZI7AAAAAPACJHcAAAAA4AVI7gAAAADAC5DcAQAAAIAXILkDAAAAAC9AcgcA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\n7vXXX8+3PyAgQB0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X11d//vOfNXbsWDVu3LjAfletWqUPPvhA06dP1+OPP+6U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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "knnClf = neighbors.KNeighborsClassifier()\n", + "exploreKFoldValidationSpace(knnClf, cleanedFeatureMatrix, cleanedResultVector, 5)" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "distance 0.0610581573388\n", + "duration 0.025508440715\n", + "first filter mode 0.251901933681\n", + "sectionId 0.0138428984453\n", + "avg speed 0.108949011418\n", + "speed EV 0.126735121335\n", + "speed variance 0.0998651200204\n", + "max speed 0.0581331018894\n", + "max accel 0.0226698777491\n", + "isCommute 0.00479097642193\n", + "heading change rate 0.0262546181839\n", + "stop rate 0.0225070432192\n", + "velocity change rate 0.0306983828318\n", + "start lat 0.03016909605\n", + "start lng 0.0316502458003\n", + "stop lat 0.0293086960919\n", + "stop lng 0.0327274481305\n", + "start hour 0.0113142880055\n", + "end hour 0.0119155426732\n", + "close to bus stop 0.0\n", + "close to train stop 0.0\n", + "close to airport 0.0\n" + ] + } + ], + "source": [ + "for (i, importance) in enumerate(forestClf.feature_importances_):\n", + " print(featureLabels[i], importance)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Some more contour plots to help us visualize the data" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from matplotlib import colors\n", + "import itertools" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def printColorMap(algo, Xall, y):\n", + " # we want to split roughly into roughly 10-20 sections\n", + " nSplits = 20\n", + " \n", + " # setup parameters\n", + " cmap_light = colors.ListedColormap(['#FAAAAA', '#AFAAAA', '#AAFAAA', '#AAAFAA', '#AAAAFA', '#AAAAAF'])\n", + " cmap_bold = colors.ListedColormap(['#F00000', '#0F0000', '#00F000', '#000F00', '#0000F0', '#00000F'])\n", + " \n", + " # nFeatures = Xall.shape[1]\n", + " nFeatures = 10\n", + " fig, axes = plt.subplots(20, 5, figsize=(15,50))\n", + " plt.tight_layout()\n", + " axesArr = axes.flatten()\n", + " \n", + " i = 0\n", + " for selCombo in itertools.product(np.arange(nFeatures), np.arange(nFeatures)):\n", + " if selCombo[0] == selCombo[1]:\n", + " continue\n", + " # print(\"Generating grid for combo %s,%s in slot %s\" % (featureLabels[selCombo[0]], featureLabels[selCombo[1]], i))\n", + " \n", + " selMask = np.zeros(Xall.shape[1])\n", + " # Otherwise, we won't be able to plot it properly below\n", + " assert(len(selCombo) == 2)\n", + " selMask[selCombo[0]] = 1\n", + " selMask[selCombo[1]] = 1\n", + " \n", + " X = Xall[:,selMask == 1]\n", + " \n", + " algo.fit(X, y)\n", + " # Plot the decision boundary. For that, we will assign a color to each\n", + " # point in the mesh [x_min, m_max]x[y_min, y_max].\n", + " x_min, x_max = X[:, 0].min() - 1, X[:, 0].max() + 1\n", + " y_min, y_max = X[:, 1].min() - 1, X[:, 1].max() + 1\n", + " # we want to split roughly into \n", + " h_x = float(x_max - x_min) / nSplits\n", + " h_y = float(y_max - y_min) / nSplits\n", + " \n", + " xx, yy = np.meshgrid(np.arange(x_min, x_max, h_x),\n", + " np.arange(y_min, y_max, h_y))\n", + " Z = algo.predict(np.c_[xx.ravel(), yy.ravel()])\n", + " \n", + " # Put the result into a color plot\n", + " Z = Z.reshape(xx.shape)\n", + "\n", + " axesArr[i].pcolormesh(xx, yy, Z, cmap=cmap_light)\n", + "\n", + " # Plot also the training points\n", + " axesArr[i].scatter(X[:, 0], X[:, 1], c=y, cmap=cmap_bold)\n", + " # plt.scatter(X[:, 0], X[:, 1], c=y)\n", + " axesArr[i].set_xlim(xx.min(), xx.max())\n", + " axesArr[i].set_ylim(yy.min(), yy.max())\n", + " axesArr[i].set_title(\"%s v/s %s\" % (featureLabels[selCombo[0]], featureLabels[selCombo[1]]))\n", + " # axesArr[i].legend(loc='best')\n", + " i = i+1 " + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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kWoBvZs9ulfWpuLibdu/eO0XEioyuvxOpj9mtnWq+WmsbVVxcrN2794icl668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KczxpfdtE2UHHZwmDv/j27cjbhD2OF8UWzB2YFewBntYVZKWY5KyusoN22Cx3p1dac9lZJ+hpt/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\nCd4U3DfbV17YppZJ/mgNqxPuham4F0QscH4StRblKKt3PWsjDY/qKM5KW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LWe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\nqvq6q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afl8Alavt///k9UVlYPOhCNxojF4jz++NP88IffyWPJjGntxua7APWYme8CGGOM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\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5/OvUUykqKkpKPKZ2vB5Cd+N/0nwYsDtwoqo+r6rvecsCwCUR29geGI7rWfSoqn4EDAPm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bNnA+Dz+ag85hj22m+/jNIpXrCAusceI/bdd+Dz4d1pJwInnIAUFbVG2CoPaQGRUkoplRuTkv5/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K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\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TgPXA/2pJewdwsO/Y5EvzFHAhcBNwArASeFdE9sqgzIqiKIpSiYhcDLwBfAX8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F/MiwI3mVmqd0fqe3+0lfqdevpTqhExl+Oq9lhE68dJYY1BHdGwDw85pjucoA6jY7qWlEzsmNla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eZhIwHXhcRC7DTee/EhDglmbX2DBaASKyLXAFMAjYG2gH9FXV4kzqZRjNRUseR1VoJUV+qYvK\nyuRL6KlWNiR5wzBSIFu9ARP8ESygdq///1r//1zgcOAh3HoOY4C3gcGq+nkkrXOAR4GxwAvAdsAx\nqjqz6dTPLEOHHpY07ogjDm1GTQzDyCQff/wJjzzydzZu3EgikaC8vJyZM2dz9933Z1q1Vo+qKjAC\neArXdj0PDAbOVNVxXqYSOB63TtG9uFlHFcARqvpVBtQ2jNbAjsCpOIfrmxnWxTAyQYscRwmwbbeu\n7Np7awD22GM3KisrasgVFhZy6KEH1jd5wzBSJCtnEKlqrauSqeojwCMpprUJuNQfbYKioiJ+8pPT\n+dvfnqwW3qvX1px22sgMaWUYRnMzceLzJBKl1cLKysqZPXsOa9aspXPnThnSrG2gqmuB0f5IJrMS\nONcfhmE0njdUtSeAiJyHm7WXEl8Uz2f7n57KLhVwVKIPV+VtDQWzQCuA9lA2hHy9kS6dO3PMMd9w\n7LFfk5dX/40ES0uVyZPLmDKlAlU49NBcRozIp6jIFuU1Gk9LGkeJCO0LCsjJyaFDYQHPXPHzzYtP\nFxUVMXr0z7jnngeorFQqKiooKMhn8OD92HffvRtyOcMwUiArHURG4xk27Gj2338gzzwzibVr1zNk\nyEEMHjzIdgQwjDbE8uUrYsPz8nJZvXqNOYgMw2h1aCO+TVkvsD4HvhGYkVfMTRty+G1eLuQkQNZC\n4WTKKpawbNlrPPVUXz79tAuXXz6nvvoxdmyC+fMrKfX++8mTy5k1q4IbbywiJ8f6aUbrYcC22/Cr\nE0bSo1MnfrD3APIiy2AccMD+7LRTf955579s3LiJfffdi5126m/jFcNoQsxB1IbZaqseXHTRTzOt\nhmEYGWLAgF359ttlVFZWHy+pKtts0zNDWhmGYbRwBDYBj7ebT/eNt7O8w/Vs3tE790PIfYuyskP5\n6KNuFBd3oE+fDSkn/emnlRQXVzmHAMrKYOlSZebMCgYNsq670XoozM/n7MMPrlVmyy27ccIJxzaT\nRoZhZOsaRIZhGEYjGTnyBIqKqr+RLiws4LTTTqLALxJpGIZhxPNZDuxZ2Qkk7AAqh9xg+RXlyy/r\nNxPzf/+rpKysZnhJCcybZwvzGoZhGE2LvYYwDMNoo/To0Z1bbrmWCROeY+7cT+natQsjRgxj//0H\nZlo1wzCMFoGInA+c7/6pHrelwtfkgRaBBDt654L2dn/lwpZb1m+n7+7dhfx8qIiszVtYCN2723td\nwzAMo2kxB5FhGEYbZqutejB69HmZVsMwDKNFoqoPAA8ASJ5sXnG6vcIFiTyua38d7oOz4ISOUDYM\nkUo6dChjr71W1ut6+++fy6OPQiIBGlrfOi8PDjooN/mJhmEYhpEGzEGUpagqr7/+Bs899yJr165l\np5125KyzTmX77bfLtGqGYRiGAQyrI/6FZtHCMNKFKLTzTpvzEvn8ueKnUPAMUAYqoNvCxifJzc2n\nf/91XHLJXHLqOemnoEC47roi/vSnBIsXu4ttvbXwy18W0r69LcxrGC2ZkpIEEyY8y7Rp76BayQEH\n7M/pp59Ex44dM62aYaSMOYiylAkTJjJ58kubt6j+8MOP+fzzL7jxxj/Qu3evDGtnZDMi8jJwNHC9\nql4dCu8K3AqMANoB04FfqerHkfOLgD8CPwa6ALOBK1T1jea5g8xQWVnJ10u/Jkdy6LVNL9thwzAM\no5Wxc2Ue167ryq/0FP6csxgkQYEewsH9juaCo2DZDjnk5KymsPBdOnWKWUgoRXr1yuHmm9uxerWi\nCl27WntiGC0dVeW6625m4cJFlJWVAzBlyhvMmfMJt99+PXl5Nuw2sgMrqVlISUmCSZNeojS8xQVQ\nWlrGM89M5uKLL8iQZka2IyKnA3vHhAswGegD/AJYBVwJTBGRfVR1cUj8YdzUgcuA+cBo4BUROVBV\nZzftHWSGz//3OXfeeycbNm4Ahc6dO/ObX/yGPtv3ybRqhmEYRgQROdn/uZ//PVZElgHLVHVasvM6\n9NuekTfdxMgk8RPJBxruGIrSpYs5hgwjW5g79zMWL/56s3MIoLy8glWrVjNjxkwOOuh7GdTOMFLH\nVrvLQr777jtyc2tmXWVlJfPmzc+ARkZrwM8QuhO4NCZ6OHAwcJaqPqmqL/uwHODyUBp7A2fgZhY9\nqKr/AU4FFgHXNfEtZIR169dx/e3Xs3LVShKJBInSBN8t+45rb7qWRKJ+i5MahmEYzcIEf1zo/7/X\n/39txjQyDCOrKS5eSHl5eY3wkpIE8+cvyIBGhtEwzEGUhXTr1jW2AgLYZpuezayN0Yq4GZijqk/G\nxA0HlqjqlCBAVdfgZhWdGJErA8aH5MqBp4CjRaSwKRTPJG9Nf4vKippbD1dUVjDjgxkZ0MgwDMOo\nDVWVJMfhmdbNMIzsZKutepCXl18jvLCwkK23tvGZkT2YgygL6dixIwce+D0KCqpXQgUFBYwceUKG\ntDKyGRE5BDgb9zlYHLsDc2LC5wLbi0jHkNwCVd0YI1cA7JgGdVsUq1avorSstEZ4WVkZq9eszoBG\nhmEYhmEYRnMycODedOjQnpzQyvQiQn5+PgcfPDiDmhlG/TAHUZZy4YXncsQRh1JQkE9eXi5bbtmN\nSy65iF122SnTqhlZhogUAPcDt6nq50nEuuHWHYoS7N/bNUW5bjHXP19E3heR95evXZu64i2EAbsM\noKiwqEZ4Xm4eu+2yW+w5qsr7733IzTfczdgxdzL19XeoqKhoalUNwzAMwzCMJiAvL4+xY69mwIBd\nyM3NJTc3l5126sfYsVfRrl27TKtnGClji1RnKXl5efz0p2fzk5+cQUlJgg4d2tuuSUZDuRy3K9n1\nmbi4qj4APACwX//+mgkdGsNee+xFnx36ML94/uaF4wsLCtljwB7079s/9pxHH3qKKf95a/MuhJ9/\nNo+33niX311zSbU3T4ZhGIZhGEZ2sOWW3bjmmitIJBJUVlaaY8jISsxBlFGGNTqFvDzo2DFZ7AuN\nTt9o3YjI9sBVwHlAYWSNoEIR6QKsw80K6hqTRDAjaFXod4da5FbGxKWPsprffjc1OcDvL7mOV998\ngWlvTyMnJ4ehhw3lyCFHVnfaet2WLPmG1197k9LSqp1uEolSvvh8PrPf+4yBA2tsImcYrZTGt4GG\nYRiG0TDqaoMaPo4qLGx1S24abQhzEBlG26YfUAQ8HhP3G3/si1tD6KgYmQHAIlVd7/+fC/xQRNpH\n1iEaAJQC89KleEsiPz+fYUcPY9jRdQ945879FKg526+kJMGsWR+Zg8gwDMMwDMMwjIxg3zIYRttm\nNnBEzAHOaXQEzqkzCegtIkOCE0WkE3CCjwuYDOQDp4Tk8oDTgFdVtc3v+96hQ4fYz8jy8nLp1GmL\nDGhkGIZhGIZhGIZhM4gMo02jqquBqdFw/2nUQlWd6v+fBEwHHheRy3Cfkl2JmwpzSyi9WSIyHrhL\nRPKBBcBFQF/gzKa8l2xhv/32Jien5gyinJxchgw5OAMaGYZhGIZhGIZh2AwiwzBSQFUrgeOBfwP3\nAs8CFcARqvpVRPwc4FFgLO4D7u2AY1R1ZvNp3HIpLCzk6qsvo3PnTrRrV0S7du0oKiri4osvYKut\nemRaPcMwDMMwDMMw2ig2g8gwjBqoao0pLqq6EjjXH7Wduwm41B9GDDvu2I/777+LL774kvLyMnbe\neUcKCgoyrZZhGIZhGIZhGG0YcxAZhmFkgJycHHbddadMq2EYhmEYhmEYhgGYg6hJKWNEo84fwcTN\nf6/dmMuEd7ZmwXftGNhvLScMWkZ+njYq/Yk0/5bghtFqKTN7MgzDMGqj4dtmA4ygrNZ469dlhrry\nxWg5lJbmMH16D77+uj0jtnuXkYO/o6igMlbW7Mloq2TdGkQisq2I3C0i00Vko4ioiPSJkesqIg+J\nyHIR2XfMUwsAACAASURBVCAir4nInjFyRSJyq4gsFZFNPt3DmuNeUuXTxR3Y6eeH8pu/7cItE/tx\n3r17MOjyA1mz0fx7hmEYrQERedm3Z2Mj4Sm1ZYZhGIZRF21xHBWwYkUhv/jFATz88M5MnNiHnz84\ngAG/PJilq+wTf8MIk3UOImBH4FTcLkpvxgmI24JpMnAM8AvgJNzW21NEZNuI+MPAz4BrcIvwLgVe\nEZF9mkT7BnDOPXuwen0+GxLOIbS+JI/537Rj7IR+GdbMMAzDaCwicjqwd0x4fdoywzAMw6iLNjeO\nCnjooZ1YsyafkpKq8dQ3qwq59NFdM6yZYbQsstFB9Iaq9lTV44AJSWSGAwcDZ6nqk6r6sg/LAS4P\nhERkb+AM4Feq+qCq/gdXaS4CrmvKm0iVVevzmFPcEaX6msGJ8lzGv71NhrQyDMMw0oGIdAXuJH5R\n95TaMsMwDMNIkTY1jgpQhVmztqSysvrQt7wyh+dndENXrcqQZobR8sg6B5HfbrsuhgNLVHVK6Lw1\nOG/4iRG5MmB8SK4ceAo4WkQK06J0IyifOgWtrIiNy8lp3BpEhmEYRsa5GZijqk/GxKXalhmGYRhG\nnbS1cVSYnCSj3pzKcjZdfjm6dm3zKmQYLZSscxClyO7AnJjwucD2ItIxJLdAVTfGyBXgpmFmDC0v\np8OEhxjIB+RQXi2uUBKcNWRJhjQzDMMwGouIHAKcDYxOIpJqW2YYhmEY6aJVjKPCiMCgQcvIza3u\nH8snwYk8Bxs3UvbyyxnSzjBaFq3VQdQN921tlJX+t2uKct3SrFe90GXLoLKS+7mQrVhGR9aRTykd\nWM9euZ9w5cj5mVTPMAzDaCAiUgDcD9ymqp8nEUu1LYumfb6IvC8i7y+3N6KGYRhG/WgV46go5533\nP7buvGbzeKoj6+hLMTdyJZSVUfnxx5lW0TBaBLYNVgMQkfOB8wG279696a7TqRNUVNCHhXzEXrzE\nsSxie/bmQ4b0+452hX9ssmsbhlE/VJWpU99k+vT36Nq1CyefPIIePbZM6zWWL1/BjBkz2Wabnuyz\nz564dSSNLOVyoB1wfboTVtUHgAcA9uvf375FNgzDMFoMzTWOitKpUxn3XvUCG654iS/L+7ILn3Mk\n/yGXShBBevZsNl0MoyXTWh1Eq4h/s9otFB/87lCL3MqYuGbrfEuHDuQOHkzFjBkUlJVxIpNcRGEh\nBSN/1VSXNQyjnpSXl/Pzn/+GlStXbw6bMuVNLrhgFEceeXharnH99bfx4YdVM74LCwu44YY/sN12\nvdOSvtF8iMj2wFXAeUBhZJ2GQhHpAqwj9bbMMAzDMNJFqxhHxZHYrjcH9pvH0V++Qm5FaPmO/Hzy\nhw1rTlUMo8XSWj8xm4v7LjbKAGCRqq4PyfUVkfYxcqXAvKZTMTUKLrqI3MGDIT8fCguhfXvyzz6b\n3IEDM62aYRiehx56rJpzKOCBB/5GWVlZo9MfP/5f1ZxDAIlEKVdfbbMIs5R+QBHwOK6DHRwAv/F/\n70nqbZlhGIZhpItWM46KY9Zvr2LVHntUja06daLg4ovJ6ds306oZRougtc4gmgScIyJDVHUagIh0\nAk4AngjJTQauBU4B/ubl8oDTgFdVNdGsWscgBQUUXnwxumEDunYt0qMHktdas80wspPp02fEhqsq\n7777HoceelCj0n/ppX/Hhm/aVMLnn/+PXXbZqVHpG83ObOCImPApOKfRw7iOdaptWa2s25TLRwu3\noEenUnbuFV1L1DAMwzCq0WrGUXGUd9yCmVf9gRPXrkA3bkS22gpJtsWZYbRBstLTICIn+z/387/H\nisgyYJmvyCYB04HHReQy3NvYKwEBbgnSUdVZIjIeuEtE8oEFwEVAX+DMZrmZFJEOHZAOHTKthmEY\nMWgtE6QrKxs/e7q0NPkspOXLV5iDKMtQ1dXA1Gi4X1NqoapO9f+n1JbVxrerC9j2Z4eTn1dJWXkO\nu2+3nmevmEXPLqVpuRfDMAwju2iL46g4pFMnt96rYRjVyEoHETAh8v+9/ncacLiqVorI8cBtPq4I\nV9EdoapfRc49B7dI6FigC/AhcIyqzmwq5Q3DaF0MGrQvb701vUa4iHDQQd9rdPo77LAdX365IDZu\n3333anT6Rsuknm1ZLEtXFVKpuWwqzQVgdvEWnHLbPrwxNn7Wm2EYhtHqsXGUYRhJyUoHkarWuXWP\nqq4EzvVHbXKbgEv9YRiGUW/OP/8nzJ79EevXb6gWPmrUGeTn5zc6/dGjz+PXv74ajUxVGjp0CO3b\nRz/9N7KVuLYt1bYsGZWRJMsrcphdvAULvmsHWzVITcMwDCOLsXGUYRi1kZUOotbDC7XGTqTxA0vD\nMJqeoqIiHnzwz7zwwivMmDGTLl06c/rpJ9G7d6+0pL/ttr25884buP/+R5k/fyEdOrRn5MgTOOqo\noWlJ32hb5OcqK9bmm4PIMAzDMAzDqIY5iJqQVauUDz+soLAQ9t03l6KiOh32hmFkKbm5uQwffhzD\nhx/XJOn36rUN1177uyZJ22i9iGiNNbJUYY/t17M4MyoZhmEYBgDL1+Uza8EW7Nt3XaZVMQzDYw6i\nJuKOSTvw+/GbyMkB8X6hyy8vZI89cjOrmGEYhtFmyMtRcnIqSJTlAkr7gkpuPftzigoqM62aYRiG\n0cZZvLyII36/P4fstppnLp9FYX7jN/YwDKNx2J5+TcDM+Vtw7T93pKwMEgkoKXHHLbckSCSs4jMM\nwzCah9223cBlJy5gUP81DN//Oyb/biY//f7XmVbLMAzDMKhUYWNpHm9+2pVbn+ubaXUMw8BmEDUJ\nj03tRaKs5udkIjB7dgWDB9tjN4yGsHJlJd99p/TuncMWW6T3k83y8nLefvu/vPvue7Rv344f/OAI\ndt1157RewzCam7xc5ZpT53PNqfMzrYphGIZhxLKpNJeHX+vN1SdbW2UYmcY8FU3AhpJcKrXm5KyK\nCigry4BChpHlbCrN4ew/7cmLs0vIz3d2dOSReYwalU9OTuMdReXl5Vx77c0UFy8ikUgAMGPGB5x0\n0nBGjDi+0ekbhmEYhmEYydmYsGU4DKMlYJ+YNQF9e24Can5KVloKAwbYIzeM+vKrR3blxZndKSuD\njRudg+j118t56aXytKT/7rvvV3MOASQSpUyY8Bxr165NyzUMwzAMwzCMOJTSipwamyoYhtH82Ayi\nJuCjhVsANWc15OdX8O2St+jZbSUAZbaNvWHUSVm5MG5Krxqz8kpL4YUXyhk2LGxHw+pI7YXY0Pfe\n+6CacyggL6+QTz7pwAEHDEt6rmEYhmEYhtEYBFX4aGFH9u6zPsVzGtbnC5ho4zDDiMWmszQBibL4\nx5qXV0l5efLPYTZt2sSqVatRc58bxmbe+bwzlRpvN+vWpcdWOnbsiEj8Ndq12yIt1zAMwzAMwzDi\nyc2BsvKGDU0rKspZuXIppaUladbKMNoeNoOoCTj90KVMndONDYnqj7esLIcd+62pIb9hwwbuvfch\nZs78CFWloKCAkSNP4MQTj0s6aDWMtsLbn3ZNGrfllumxjyOPHMK0aW9TWlpaLTw/v5A99jg0Ldcw\njJbGxo3Kp59Wkp/vPn/Oy7P2xjAMw8gM+bmV7NN3XWxcSUmC55+fySeffE2fPttx8sl70b69i3vp\npQcZP/4mysvLEIEf/OAcfvzja8ixaRCG0SDMQdQEnHTAtzzxxja8/kk3SkqqFlzLyYELfn4YV14+\nm732WLk5/Kab7uKLL+ZtnjlUUlLCE09M4KOP5nD11ZeRYzWc0UZZuqqAed+0Jy9HKa+sOXg98MD0\nLGjYr18fzj77Rzz22D/Jzc0HlIKCdlx11Xhyc62aNLIXVZgypxtl5cIhu62ifWElAI9P24YLH9xE\nrjeh3Fz47W8L2XlnWyTUaN2IyHbAncAPcOsBvAZcoqqLMqqYYbRRCvMqyM2Fv//yY/Jya84M//bb\nVVx66fWUlW0ENjJnTjtefLEdY8fuzzfffMATT4wlkdi4Wf7VVx8lLy+PM84Y2Ix3YRitBxv5NAG5\nOXDxsIXMWtKBpd+0J1iPqLTUdbxvvGUfHn1gGrlFsHjxEubPL479rOyTTz5nxowPOOCA/ZtTfcNo\nEYx9uh83P9uX3CTOIYBBg9I3mD3qqKEccsgf+Oyzdykq6sCuux5ATo4Nlo3s5qOFW3DyrXsjQEWl\n8MjoOey23XpGPziAyIQ5brghwQMPtKOgwGYSGa0TEWkPvA4kgJ/gdhQZC0wRkb1UdUMm9TOMtkZh\nXiUF+f/P3nnHR1WlDfg5U1NI6IjUABFEFFFQWSwUBSzYYW1YP9uurrorrrrqir3r7squu/ZeUQEb\niCAgKCAgqCC991BDkun3fH/cO2QymUmdZCaT9/n9LmFOu+8597z3nPPeUwzy2ngojnOK2ZNPfkwg\nsAcwLBcPhuHj0UfH0LTpljLGIQC/38NXX73MRRc9j90u/ThBqC5iIKoDJsxvzeXPa3z20ZCzCHRb\n8N0BgZGAaS5auKgVxw/Yw65du+Ie020YBrNnzxUDkdDomPFrc56emIcvEL9hVwomTw5y0001a/wN\nAzZuzMbh0LRvX4JSkJWVy7HHDqup2IKQcoQMxQFP6UacV407itEDtxIIlW93tIZFi0L07y9dAyFt\nuQ7oCvTQWq8GUEr9DKwCbgCerSiysXYtxb//PQAfcjQ35GxC4cTtH4jX9wRQBGQB3wFPAZtxu7O5\n9NLzOP3009i4cTPvvvsRK1euxjAM/P4AhmGQnZ3NhReewxlnnIbT66XbRx9w6Jzv0DbF1lMGsfb8\nkeR8PYU/ffoZ75cEOYDCAJx2O6MG9OPVm66pcLa53+/jlbdeYca0+eig2X727n0Ud9zxJ1wuV/l8\nGgZffDGFKVOm4/V6OfbYo7n44gtp0SL+ku8VK1bxr3/9j127dmOz2ejX7xhuu+0PtR6gFxTs4r33\nxrNkyVKys7M488xhDBs2WGbXpwk+Yyk+x7H8su16rnz+eh6+xM2fztxUJsymTfMpNQ6FMSgq+o5A\nIDNmuqFQAI/HS5Mm2XUjuCCkMdILTDBaw59eC+FznwOUWJOH9kPmLaB2gv+PGBp81myizp07EQyG\n4qbndMojEhofL33TgZI4X5LCaA2//BJfdypi6dJm/OMfvfD5bGitaNbMzx13/EKnTjVKThAaDCED\nFq3NIRgqP7gyDPB4kiCUINQf5wBzw8YhAK31OqXUHOBcKjEQQekZtb9nCc4DJ3FN7my87kng2ADF\nk60QI4CBwFB8vgJee+1d1q/fyPffz495YmZRURFvvfU+mzdu4vXVP5O1bRv2YACAzl98Ruvp0xhU\naLABRTDilNxAKMS7381j+ZbtzH383pjyaq257/H7WPfrjoM50BqWLPmFP//5bv7972fKxRk37iXm\nz194cF++WbO+56effua55x6LOeDeuHEz9933yMHfoVCIefMWMGbMvTz33GOVFWlc9u3bx5133k9x\ncQlaaw4cOMA773zA5s1buPbaK2qcrpBCqBDYNkHGo3gCy7j//ee5fuhm3M7IlRXx+oM2OnY8ktWr\n55bzadKkOdnZWXUisiCkO2J+TzAev40dnqcBT9mT7lUJZDwG+DEMRZ/euwFo3rwZgwadFDMtl8vF\n4MGn1LnMgpBqFJY4KKtAscnNKcTJhIOXeaRp/Os8AvTfp3j68aPYv9+F1+vA57OzY0cGj47tg98v\nJwgK6Y0/aKN9Cx/ZGcFyfoYBRx0l3QIhrekF/BrDfSlwRHUSUsD5zEYFB4Dygv1XsP9g+TowZxJd\nZf3WfPvtd+UOQojEMAxmzZrDvp07DxqHAOyBAJMLS9geZRyKZNHaDazZvjOm34rVv7F+xbYIqUsp\nKNjN0qW/lXHbsWMn8+YtKCOrYRh4PF6mTZsZ8x4vv/xGTPctW7axdu36mH5V4csvp+L1+spsw+Dz\n+fn221ns27evxukKKYjygPMTDLawvqDsrKB27U6FckfSO8nIGMrVVw8tNwvO5XJx+eXnyUE/glBD\npCeYYDKcBsqxGFSsgWYIl3sLF49aQ4sWpV+QrrvuSs46a9jBF5nNZsPpdDB8+BB69+5VT5ILjRGl\n1Eil1ASl1CallEcptUIp9ZhSKicqXHOl1MtKqV1KqWKl1DdKqaNipJehlHpKKbXNSu8HpVS1rZyj\nBuwg211+ABuJ2x3kvHPWVzdp3p7ZjlC5iUeKQNDGokU1m5EkCA2FbHeIG4dt4qSee3G7S93dbjj7\nbAetWkm3QEhrWgB7Y7jvAeKvn6qA5qEe1v8CYF8S4eMGji8TNtZ+k5HYgeW+8m3fQuwUV/LRZOqS\npTHd125Ygw4q4n10+emnn8v8XrduAw5H+dnrfr+f335bETONjRs3x5UrOv3qsHz5SoLB8uXhdDrZ\nuHFLjdMVUhTtxq+X0Sa3rCH1rrvOxW7PxzS6uoFslMrj9tsv4rDDuvHAA3fTu3cvcnNzyM/vwu23\n38zJJw9IQgYEIT2Q9UsJxmaDVtktKCjZXs5PqRD3/20DR/T0R8WxceWVl3LRRRewYMFPlJR46N37\nSNq2bVNfYjcoDMNg1ao1eL0+evTIJyMjI9kiNWTGAFuAu4HNQB9gLDBYKTVAa20o03L5GZAH/Amz\nc3035qaefbTWkT3DV4CzgDuAtcBNwBSl1O+01ourKtTFJ23jtentWbwuh2KfA5syAIWyadzuEMGA\njXNGbOCUk8rrWUVordk8exXeYPdyfoGQYt8+mUEkpBc2pTGsap3tDjL4yD2c2nsPg4/aw91zRzBn\nThC3W3HqqQ569ZLNPAUhGqXU9cD1AB1j+B+whWfuuMCIDBHEbAarjgG0czogUNYo0hWDTDSeCoxE\nfbp0IlaL2LpVG5QddFATy0jUqVPZXLVp0xrDiN7vBRwOO+3bHxrz3s2bN6OkJPb61Ly8mq/dbtfu\nUFauXFNOnmAwRKtWLWucrpCiqABDj8qmeRNvGee2bZ28+updfPDBDpYv30mHDody8cWH0KqVqSfd\nunXh3nvvSIbEgpCWiIEowSxes4bA3tXgcoIqnSKslIvhAweWMw5FkpGRwUkn/a4+xGywbNy4mUcf\nfYaSEg9KKUKhENdcM5ohQ2QpXg05W2tdEPF7hlJqD/AGMAjztJdzgBOBIVrrbwGUUj8A64C/ArdY\nbkcDlwLXaK1fs9xmYk7df9BKp0q4HJqp9y/g03ltmPRjG1rl+LnmtC0szAqye4+bjh2Kyc6qeIZR\nLIxlyzhpy0+8wUCKaVLGTylNz54yQBbSi66HeDiq83b8QRuXnryNC/rvQCmwKxgwwMGAAdINEBoV\ne4k9UyjezCK01i8CLwIco0qnh2tgJV0IOL8GbQedA8HhETH9wMsHf3Xr1oVNm7ZUuMysS9c8Dtu2\nCh1QKMxbGcrGSBXiEQM8xDbytMppQv/u3ZgQI81jjuxLk5YODuyIniGrcbpcnHxy2X5nly6dadeu\nLRs3biYUMd3WbncwfPipMeUePfoinnjiH+XcMzMz6Nu3T9z8VsZZZw1nzpy5+HylZeZwOMjP70q7\ndm1rnK6QgmgXrbJ78v5tsfUjM1Nz1VVtgPDH8+r3AQVBqBoylzzBPPHhh2ivn0xPAGVg9iA0ZASC\nXH7BpckWr0ETCoV46KEn2bNnL16vF4/Hg9/v59VX32b9+g3JFq9BEmUcCvOj9be99fccYGvYOGTF\n2485q+jciHjnAAHgg4hwQeB9YLhSKmJBS+U47JpRA3bw1q2/8Nw1KziqUxGtW3k5vPv+GhmHAIJz\n5jA8+Dm9WEompceiZlHMWXm/0bmzvBKF9CI3K8gHt//Mp3cuZtSAHdiliguNm6WY+xBFcwSwrCoJ\nWN06dpHL77ICgMYZ6gFFX1k+PmAT5oFpqwDo27cPY8fexQ03XEVubk65k72UUhx77NHc9bfbmf/Q\nYxR27YrhcGDYHew/7DCWP/E0b/XuRm8MbJSd6dqpdQsWPTM2rrwOh4Mnxj7BIR2bRUgPTZo04emn\nHiq3T4tSinvvvYM+fY7C4bDjcDho2/YQ7rnndtq0aR3zHn379mH06IvKnCzWvHkznn764UpKs2I6\ndmzPHXfcSuvWrXA4HDgcDvr1O4a//vXWWqUrpBBWlXSHNHcNOZxMV/nZa4Ig1C/y6TDB/LrBNFS4\nAuAMgFbmdkQZbidFhQfIypQd9WvKsmUrYn55CwQCTJ06g+uuuzIJUqUlA62/4Z0rK9rU8wqlVBOt\ndZEVbp3WuiRGOBeQb/2/RoQMg19X/Uaxp4QjDutJTnaTyiNFoxR2DCZxDq9xFe9zCS58XOV8lyvP\naMGXnFBT8QRBEITUZxLwtFKqq9Z6LYBSKg9zluxdlUUuwclX9OYWLkEpLzmebPbrHAx6cFSbQnIO\n+4W2bYPYbUvo3Plc2rQ5k0MPbYnb2vDr5JMHcOKJ/SksLCQzMxOPx4vX66VZs6YHl8uXZGcz7/Gn\ncRQdABTBJlZbd+/f+dF7gN27dqNyc9m2r5A2TXNo0zS30ky3atma55/5J0XFRWzZvIXWrdtUeGR9\nTk4T7rzzNutDXIDc3JxKN/w955wzGDFiOFu2bCU3N4emTZtWKldV6N27F+PGPcX+/YVkZGSQkVGt\nb01CimMzoEkhKAIs37ip8giCINQ5YiBKMPnt2rF9zx7AnAQcnoystaZps2bJEywNKC4ujumutaaw\nsLCepUlPlFLtMZeDfaO1XmA5twDWxwi+x/rbHCii4s0/w+nEuufB/R06tWoVU66lWzZxxnMPsd86\nHjgYCnLZeRdz7rCzK8lRWRwnnURo1iwyfD7+wP/4A/+zhHDhPObFaqUlCIIgNDheAm4GJiql7sWc\nv/AQ5pSf/1UWuUnXjox8/E5GlvMxTwmbcHDp8sByIcLYbDaaWf1B03AU25ASbJJTzk1lZNCqgzm5\nt2Vuef/KaJLdhB49elQe0CIzM5PMzMzKA1rYbDY6duxQbbkqQylFs2aJMTgJqUV4+/QMl4uenWq+\nX5UgCIlDJpsnmDtGjiQz+rhFt5tBw87A5m5CAOfBS6gePXv2IBgsf8qU2+3muOP6JkGi9EIp1QSY\niLmw++r6uq/W+kWtdT+tdb9WueW/hIYMgzOfe5jt+/fh8XrweD0EAgHem/ghy1Ytr9a9PuvZm3VD\nTyfkcmHY7YRcLkIuF4tvvo2JWU2BLyq4BCFxJPoEQUEQKkdrXQwMAVYCbwHvYO6nN8SaCSsIQj2j\nALfTyaWDBydbFEEQSGMDkVJqkFJKx7j2RYVLaOd7wBFH8PKf/0zeIYeglCIjM4vh55zHhaMvr32m\nGjlNm+Zy4YVn43aXGuDcbhcdO7ZnwIDjK4gpVIZSKhNzT6GuwPCok8kq2tQz7F+VcHti+FXKD6tX\nUOQrfzqK3+9jysyvq53eqiuuYu7jT7P64stYOfpKvhv3P3b2l83hhXpnDBDCPBHwDOAF4A/AVKWU\nDSDiBMHTMU8QvBBwYp4gWOXP9IYBlZyuLQiNBq31Rq31hVrrXK11jtb6PK31+mTLJQipRH2Oo044\n/HC+fOghWsb4SCgIQv3TGJaY3ULpprsQse19NY/vrjLD+vZlWN++vFtiY9++bJo29bF06VK2b99B\nXl4n8vO7VrqWW4jNBRecQ/fuh/H119MpLi7hxBOP5+STB+BwNIaqXDcopZzAeKAfMFRr/UtUkKXA\nsBhRjwA2Rnx1XQqcr5TKitqH6AjM41xW10S+XUWF+PyBcu4aWPKrjQ0bm9C5U/U+/BZ36Ehxh1gH\nFgtCvZGwEwQrYuXWLLIuGYrTbnDxSdt55qrl5GaVn4kpCIIgCDGo03HU4R27MemBB4kcFoUMg29+\nXsbUgn1069aFrl3zEpEPQRCqSGMYVf+mtZ4bx6/Wne9YaA3PTMrjwY+7ojX4fEHs9u3YbOOw2UJ0\n6dKZe+65/eCmhUL1OPLInhx5ZM9ki5EWWDMV3sGccj8ijq5MAq5WSg3UWs+04uUCZwPvRoT7DHgA\nGIU5yEUp5QAuAr7WWvtqIuPrn0/GHwqVP9lXZ7F/10juvOd4Hrp/AYflyz5UQsOhNicIKqXCJwhW\n2kYVeR2Awhe08+bMdnz0wyHcO3INfxi+GTJqmQlBEAQh3anTcdSyzU044tYTeeuWX+iXX8jm3XsY\n/Pcn2VNUjC9knmh2xBE9+Otfb5WPwYJQT6TtErMqUtXju6vFu98dysPju+L1OvD5HEAGodC5BAJj\n8Pl8rFmzjo8+mlB76QWh9vwb06DzDFCslOofcYWXsEwCfgDeVkpdrJQabrkp4MlwQlrrnzCPuP+H\nUupapdSpmEfcdwHur4lwq7duZeHKVWR4sY5CtV5ZOgtCPcF/ET6fg9fe7F6T5AUh1ajOCYKdrH3D\nqozWihKfgwc+yOfke4/H75d1Z4IgCEKNqfU4SmvFmu3ZDH+oH7sKnVzxz5fZvHsvBzxe/H4/fr+f\nZcuW89lnX9VRFgRBiKYxGIjeUUqFlFK7lVLvKqUit8hPaOc7zGOfdKXEF23lzgQuBZwEAgFmzJhd\nk6QFIdGcYf29B9MIFHldC6C1NoARwFTgP8CnmHunDNZaR59JejXwGvAw5s7OHYHTtdaLaiLc2m3b\ncDkcuP2QXeyCwMUQOAM8T0Pxl4A5C2/NWjndRGjYVHCCYEUnA8Y/p7oCfEE763Zk8v33stRMEARB\nqJB6GUcFQ4qXvmnJ/NVrCRlGGT+/P8A338yskfCCIFSfdJ6rtx9zVsRMoBA4Bvgb8INS6hit9U6q\nfnx3GSo6lntPkYNte+MtHbMBWcB+gsFgnDCCUH9orfOqGG4PcI11VRTOA/zFumpNj44d8QXM/Yfs\noQB4ngTK9zdyc/3l3Pbt28eiRT+zb18hvXr1oHv3/Crv/bVs2QrmzVtAu3ZtGTp0MDZbY7ClC8ki\n0ScIRrZRpo22PMU+B4sWhRg0KJ27AYIgCEINqZdxVLiN8vjtbCzIjNtPk3GTINQfadsztJa7/BTh\npw1+aAAAIABJREFUNFMpNQuYj7mR2n21SPtF4EWAvt26aYDCEjvX/PsoJv/UAn9wHdCN8hO09gH7\nsdttHHfcsTW9vSA0Gjq3aUNW1ql4989A4cXFy/i5HtPQauJ2hzj33I0EcAKgtea998YzceKX6Iij\nm9q0ac3YsXfRqlXLuPcbEfTQ+y/3s3r7zoNub77+LrMfuZsNXfMTn0Gh0RN1guDAGp4gWIbINkqp\nY2KuI1NoWrSQwxIEQRCE8tTXOCrcRtmU5vAOIfJat2LF1u3l4hx2WDfmzv2R/PyuFfbjBEGoPY3q\ns7i1zGUlED4TvUad71hc/OzRTP6pJf7gx5inF3sxV+GEKQHG4na7adq0KZddNqra8gtCY2PB6lx2\nel7Fx80YtMDNk9iZBRg4nSFcrhBnnbWRYcO2HoyzcOFiPv98ShnjEMDOnQU89dS/KrzfNc+/XMY4\nBBAIhTht7NMJy5MghIk6QfDMOCcI9ooRNfoEwRoxdGjafiMSBEEQEkxdjqMMDY+O78rvevSI6b9g\nwSJeeOFVbr31Tl555c1yfTxBEBJHY+8dVvX47grZuCuD2b81xx+0YxrEV2PuzfYXoDewEfgXxx/v\n49hjL2XAgP5kZMgJZoJQGT+ty0Xjwse9+Li3jF/fvjv44x+Xk5FRdq36lCnT4k5F3rx5Czt27OSQ\nQ9qUcXcW7qfXf57n8kWrKH9cGhzwetmwYSOdO3cq5ycINSHBJwhW//62ErKzsyoPKAiCIAixScg4\nykQRCNn4ZO6SmL6GofF4PADMmDGHww7L55RTBlRbYEEQKqdRzSBSSvUDegDzLKdJQHul1MCIMOHO\n96Sqprt9r5tcRxHdWUEuOyzXlcCNwADgYuB72rVry5AhA8U4JAhVpHNrDw57eXeXK8Rhhx0oZxwC\nKC4uiZueUjZKSjxlHbWm3wN/p9WSxVS0ZW9RUXEVpRaEKpGwEwQrojl7yCBaJzSG62E++SSQmJwI\ngiAIaU9djKNc+DGPqQWP34Yn4K00js/n46uvplZLdkEQqk7aGoiUUm8rpR5QSp2nlBqilLodmAxs\nAcLrTGrd+QboOf8VFnsO51sGs4otPEcJDspPfazqBrmCIECR187+Egdup4HdFmkI0tjtmoEDy69R\nB/jd746Lu6m0w+GgY8f2ZdyarVhOZsFObKEQRxKCGLprU4qePWNPexaEGpLoEwRj0olNXMwHuPHi\nILyZuwdsy1mwQIyegiAIQnnqaxx1OL+xiGM5msVkugz6dj0SWxXGS+HZRIIgJJ50XmK2FLgEuA1z\nR9vtwCfA/VrrXWB2vpVSI4CnMTvfGZgvuip3vnVhIfYvPyWL0i+xV1j//zNlp+8Hg0GCwSAORzoX\nuyDUnsk/teLiZ3tjt2lChsLQCrvNQNmgXbsSbr75N3JzY89+GDp0CNOnz2LLlm1l3B0OBzfeeHU5\n/cvcuePg/1+jhH7kEEITudTskcsulJPMhISS6BME46HQ/IM/8xh3s5PWnMA8vABqJ9nZrpokKQiC\nIKQ/9TKOsqHpyjq+5Eyu6vAD/7jpfE782zI8fj++QOztAhwOByec0K+2+YvL9u07+PTTz1m1ag3t\n2h3K+eePoFu3LnV2P0FINdLWUqG1fgx4rArhatX51nv3QqjswhQ7cCUBbsfAiJik9fnnU5g69VvO\nO+8szjxzuCw1E4QY7N2nmfPkNOaGrsSNl88ZwaPcQ5G9Ofc/+BP5+QcqjJ+R4eaJJx5g+vRZTJ36\nLSUlHvLzuzJq1Ll06lT+yO/CLl1RhjlDqQuaZRRyF5n8gIP2rVrw+E3XMrBXDybUSW4FoX7IxEsb\nCmhOAdtUCFvoEkaMEAORIAiCUJ76GkeFyaCEj457mqxDz+bn5x7khcnf8vmqdbjdbn7++VeCwRCG\nYeB2u2jWrClnn31G5YnWgI0bN3PvvQ/h9wcwDIPNm7eyePEvjBlzM3369K6TewpCqpG2BqJ6IxR/\n15IcZWN/xGoVrTVer4/x4ycxd+4CHn307zKbSBAiCBmKDfeN47bQj2Sa8xy4nLcZyjecbHzPokXH\nkZ+fWUEKXwDgcrk4/fTTOP300yq9Z3HHTuzufTQtf16C3e/nEOAVux9/biZznnmMvZmZYhwS0oJi\nsthBe9BgC/yRCROCHHOMg9xcWf4sCIIgJA87sGvhfDqdfzZtmzXlgYvP4xicAGzduo0pU6ZRULCb\n3r2PZNCgE8nIyKgTOd5++wO8Xl8ZN7/fz0svvcm4cU/JdiFCo0CsE7XFZgOj/Ea5B1AU6rLLVMIE\ng0G2bdvBvHkLOPHE/vUgZO3ZvXsPX301ldWr15KX14kzzxxGmzatky2WkGbsXb+XfNZii9gHyEWA\nluzgaOM+xo+/iE8+aUp+/hYOPXQOTqfBKaeM5PDDa6dHS/5yB3mTJtBh6tfY/T4K+h7HqktHE8qs\nyBglCA2HEjL5G49iWM1+MATbt2teeMHHnXfWTUdbEARBEKpCEfDf7Xt5NIZfu3aHcvXVo+tFjhUr\nVsV0LyjYxeTJ3zB06GD5uC+kPVLDa4nKyYH9+8u5/2hz4LS78Qf8MWKZO/D/8suyBmEg2rx5K/fc\n8xCBgJ9gMMSKFauZPn0W999/l6zJFRJKc/bE3Dn/QR5kHpcD2RgGrFzZhZUr2wPn8d13HzF8+DWM\nHn1/je+rHU7WXTCKdReMqnEagpCK+HEym+N5ijuYyaAyfqEQLF5sEAhonE75KioIgiDUPyXAcuz8\nryQU00BUn+TkNMHjiX2S2jvvfMicOfMYO/YuMRIJaY3sulpLVPPm0LIlREw59NtcLDVG4w/E39/B\n4XDQqlWL+hCx1rz++jt4PB6CQXM5XSgUwuv18dJLbyRZMiHdiDVE3UQHXucqfGRHuGYCnYER+Hwl\nTJ78Mlu2xP7qIwiNmWX0YgRflDMOhdG6wpXSgiAIglBneIGncDOCbDKzmidbHM4++wzc7tjjN78/\nwMaNm5g/f2E9SyUI9YsYiGqLzYb7rrswmjVHYx6QvdVox9vcCLwDtI0ZzW63M3jwKfUoaM357bcV\nMd3XrdtASEYWQgLZTRYbaEsA+0G3ufTHSawTy7LBGvQahsGiRVPrRUZBSCfy8mxkZMjsIUEQBKH+\nWY6d58jARwZ7i29iQ0FylzwPGzaE008/DbvdHtPf6/Xx448/1bNUglC/iIGolnh9PjbdeT/G3v0o\nzBkQHdnAZIaQTRNgLvAq0AmXy0VGhpumTXO5885badmyYcwgircRnNPpkKO/hYSyiXyGMZ3ZnIQf\nJz5c5LIfFbEnUSkBzFNXwWaz43bLfkGCUHU0Dgf88Y9ykpkgCIKQHGxoMtBch49sfT6vTWufVHmU\nUlx22e+59dYbY84kstls5ObmJEEyQag/ZAFlLdmxdReZ2omD0pk0djRuDC5w9+ct/Qj4b0CpITz+\n+IcYhp8OHdo1KMPK0KGD+fzzyfj9pbM4nE4ngwadJLv5CwnGxg7acT4TyaEQJ17AIJsiDtCEsjbt\nIPCu9X/NCSeMAObXt8CC0GDJzYU2beQdLgiCICSHwzCYSiE2sigx3mfznrOTLRIA/fodg9vtxucr\nu5esw+Hg1FMHJkkqQagfxEBUS+w6ExfFgLm8bK+CTA1N8JBntIHMv0NwMO3b9aBDh6uTK2wNGTly\nGNu2/YEFCybjdLoJBv306nUSV1zxKuZeMIKQeA6QC+QCQRz44eAizgDgAW7H7d6KYTi55ZbraNrU\nNA4Fg0EKCw/QpEk2LpfMjhCE2Cj27IGxY7089lhGkoz9XyThnoIgCEKq4ARyAEUJeczj15Lz2Lzb\nTYeWPrZuPZz9+3fSufORZGWVztoJhYIYRgin011ncjkccN99+Tz22MWUlBShlMIwglx33dN06vT7\nOruvIKQCYiCqJSVkESDAPHuAWzJhs80cwvYNQm6wJbATnGdz7rnTgO5JlrZmOBxO/vznlyko2MSW\nLStp27YrbdvK6WVCfWEnSBamZn0EjAd+AvwEAjbsdhtLlvzKsccezZQp0/noo08JBkMoBcOHn8ql\nl45qUDP2BKE+WbtWs3BhiH79pDsgCIIg1C+/2qBXNjzhyWCx0YWvF7bm68WKzq0vZU3BFux2B6FQ\ngJEj7+C0067g5ZfvYN68LzCMEPn5x3DDDc/RqVPPOpGtc+de/Oc/S1i9eiFebwndu/cjIyO78oiC\n0MCRHmEt8eHnO9WW/8taQ0nEGHS+A3D8Zv3aw3vvjeTkk3/CZou96VlDoHXrjrRu3THZYghpTfRe\nQ5G/PwTux5w9ZGIYBoZhMHPmHLZs2caaNWvLTAeeMmUaDoeTiy++oC6FFoQGzcSJATEQCYIgCElh\nqw2uyPKivD4Mvx1/6CZ+27IecysBk/Hjn2batLfYvXsLoZC55cWqVQv5+99H8M9/zqVp09Z1IpvN\nZqN79+PqJG1BSFXks3otOYJdDNRrebcEbJFjWXXwH9A2SkoOsGzZD0mQUBAaGhpFCAiCfSY4PgX8\nwD+JNA5F4vf7WbZsebm14j6fny+//BrDMOpaaEFosGzcqJkwIcDEiQG2bRNdEQRBEOoJBWjzj+GY\nDewGfibSOATg93vYuXMjwWDZU20DAT/Tpr1dT8IKQuNADES1pARYTHueD72Aq3A5HPgBfJeZEx+U\nBtxg+x1KwYEDu5MsrSCkNj1YzlvqaJzZQ7Hl5EOT8yDrT9CkP1BQozT9fj8+ny+xggpCGuHxwAcf\nBHj//QBjxnj57LNA5ZEEQRAEoZY4Qr3oXvwshDpgJxNoBsQ76r78ibaBgJdNm36LEVYQhJoiBqJa\n4sLBZcxkBqPw0haMnuB9ErwPWiHcELgFny+Pww8/IamyCkKqsx+Dy7Ny8Kt1GLZ9pqMqBtsmUFkV\nxo23z1DTprlkZMTrbAhCY8fscIdC5hUIwPvvB9ixQ2YSCYIgCHVLECdrQ6NpVjyVULAPOD4EupUL\nZ7c7Ym7T4XJl0q3bsfUgqSA0HsRAVEsKaEMxTQiV2c4pG/w3QLAn6AAYvbHZHqF587ZJk1MQGgLb\n6QnF06FoDezfCJ6bQdtBBSBjP/G+KrndLs48c2i5U8tcLhdXXnlJkk5oEoTk04pdDGMyirDBJ3wa\nYDEQihlHa5g/P7afIAiCICSSIC48NOWIQF8wuuDIbk6my0V4qw6Hw01ubiu6dz+uzMllStnIyMhm\n8OBLkiS5IKQnsitlLSkiGz/lj1lU+NHFX2MWcSaG0areZROEhocNDupTLvgfgsCfIPtccOwC3gKe\nAX4mI8OB3a5o06YzF154O8cffyYDBjzPe++NZ8OGTRxySGtGjTqfPn2OSlpuBCHZtGUbPzAAffB7\nUNhYmoVpIIptPE2MTVWOsRcEQRAqx0MWPlqA0QNcXzLx9r9x7+Tl7N69lT59hnDmmdfjdmfywQdP\nMGPGe/j9Xo455jSuuOIBsrObJlt8QUgrxEBUS9z4KCEElIBzIth2QPA4dKg/qJmghwKajAyZwSAI\nVeFQtrCbVvhxgG0F6Cwomg7O/wHjgLkAeL2KrKwruP32J2nTxhz85ud35b77/po84QUhxSgkl2Dc\nycKxuwBKwfHHN9wTNwVBEIQGgtoBjrcgcBYt9VbWMJCg71j2leQzZsxd5YJffvlYLr98bP3LKQiN\nCFliVksyKcDp/CfkdofMMeB+BLIvgexTQZ9khVIEZM9PQaiUluzCAPyOjyAnH5oMhZz+kD0cgm2A\nmRGhNSUlbzBmzC0YRvmNCwVBgCAOPMTavyv2RwuHA0aPdh40ugqCIAhCXaHUNnP8lHs0G52LTEfv\no1z1/GAKC6VvJwjJQHqAtaQ1HjYHHuTlEg+5eEEZ5qa69l/Aff/BcIEAaC0vOkGoiA5s5md6sSJ0\nMxcE95q6pLxgXwrZjxDrBAuv9wNWrpQNdQUhFna8gKdKYW02ePBBN2ec4axboQRBEAQB6G3Al8U+\n8owDbM98G9BgHE0o5GLmTPm6LgjJQAxEtURh7pgyImjjg2JbWQ/nV2XCLlsmg1hBqIiwPh2iYZwH\nhoT7BsoA2x6wx944d98+Mb4KQiw2k41iB4qtgI94G1MrBYcfbiM/X5aWCYIgCPWDAk4IwdRiyNIB\nsC0ANL6gnR07pG8nCMlADEQJIgOD3iEXRwRyIlzLTuufPTtYv0IJQgMmC7jLF+kSAFtsI2uPHjKo\nFYRYaNqi6YqmHWCA42vIvATzFDNtuqHRGnr0SK298rTWrF69lh9/XMSePXuTLY4gCIJQB9iBTO3m\n/ADgmAMobMqgZ0/p2wlCMpBNqhNICCdd/GewzPkhaBf4R5fxl5O2BaF6dC5jDzIgWP6VlZ19GM2b\ni3IJQiy6soZr+BsvcSkbHL+B7Rfw/Buwgf0LcL4O9p1gHM2EiU9yzjkusrOTr0979+7joYeepKBg\nNzabjWAwyKmnnsLVV49GSWMqCIKQVjTBR16wHdj3AQpDwwkniIFIEJKBGIgSiBM/vwYvA/0JhPqB\n/7qDfpmuIH87eT4nse+g2wRqt8/DeVS8Nre26QtCMjFQLFHNgL2g3RA8CfQvmMtkTJzO5rz61l9B\nTUianIJQ1yilOgLPAUMxZ+R/A9ymtd5YWdxcDnAj/+Fq/sMFLpjnUJDxL/BfCd7nQHeBnBPBWIkO\nruDll09l1KiOtGt3aK3lrk0b9eyz/2br1u0YRqmV+NtvZ5Of35VTTjmx1rI1dCorW0EQhIbEAbL5\nhZMh1Pug20jHxCRKJAiNFzEQUbvOdxgNeMlgo2oBxW9A6AxKV/Bpbhy+iZN67qsgBUFIDxKhTwBe\n3DxivAuhq8H3dwhcBEwHOtPZ9SEX3d6PfsfLKlkhvVFKZWFWfB9wJWZz8zDwrVKqt9a6uKL4HmCF\nDdCKcSWa45paezq43oTQ0RD4BvY3tZJdzpw5K5g3z8HQoYO46qrLWL16LdOnz6KgYBd79+5jz569\nZGZmMnjwyZx11nCysjJpunIF3ncW8fK681mqjqRjzwDnj9rE/Hkf8MyseSzw+ClWNtxuF+cefwyP\nXzaSrAx3XJn37NnL6tVryxiHAHw+H1988XXCDEQLFy7hgw8+5sCBA/Tp05vLL7+IrKxYJ74J6YRS\n6i/AYKAf0BZ4QGs9NqlCCUIDprb9Pg1k4OP74HBM1QSlZP8hQUgWjd5AVNvO98F0gEy8nKwLmBU6\ni7DJCC4HFvHcZzZ+WjuMz/52Hm5n6Utv+fKVzJr1PVprTjyxP716HV6l6fN2j4fAzG8wVq5kfEjx\n7KadlARCXHLyCfztgrNwOJL/aOfNW8DHH0/C4/HSv38/fv/783E6ZVZTOlNbfQprhg9w4MdHEyha\nirlC/QfgRrrzBc88eSiezmIcEhoF1wFdgR5a69UASqmfgVXADcCzFUXOBHoZUIxmsw3aBlqz3VkA\nSoN7DBzcN6+03QkGg3zzzQw8Hi/ffz8fv99fJs3i4hI++mgCM2Z8xyuXXYB/3I9cEnwXLxkY2Nm7\naBcXLvojQzlgnZ+mAA0lHv47ZQZvz/yB9f99ErKaxpR5/cZ1hELBMjKFOXCgqPISqwJvvvk+n38+\n+eDvadNmMmvW97zwwrPk5uZUEFNIA64DCoEJwI1JlkUQGjSJGEcpwEGQs9jBG2QBmsubf4Lv+TdQ\nzZvjGDIEW7t2dZkNQRAiSL4VIfnUqvMdiRMfvVnKLIYAQeB4YP9B/xlLP6fp6HnseuMJmmSEeOut\n9/n66+n4fGbne/bsuQwceCLXXntFhfdx7d1D/7vuIFBSzGU+G18cnKaveHj857z8zSzW/ucJcCTP\nGDNu3EvMmjXn4O+JE79k2rSZ/Pe/z+FyuZIml1Dn1EqfwsNBNxDCYAKnczhbgADwNXA4D/3fF3g6\nH1VX8gtCqnEOMDesTwBa63VKqTnAuVSxjcoGOhjweEk2VzUtMB1t8bsAgUCQmTPnoHX8r7i7d+9l\nzouv8nlwEiVkH3S/med5nEI8Zc7BKDX2FHl9/Pm19zn7phtipjth8sdx75kI443H4yljHAoTCAT4\n739f5a9/vbXW9xBSml5aa0Mp5UAMRIJQWxIyjlLAFbzDm1zAJK7hhAMLCX3nBbud4OTJuG6+GUf/\n/nWVB0EQIpBP8HE630C4811lSoCO/Gr92kGkcSiMoQu46cUt/LZ5G1OmTDtoHAJz+vyMGbNZu3Z9\nhfc57N23cRXuZ7kvYBmHFJGd7+37Cnn0ky+qI3pCKSjYVcY4FKaoqJh33/0oCRIJ9UjC9MkOtKaY\nFhRgfpj6mJtuHY4aIcYhoVHRCw42LJEsBY6oTkKZQCfbBvOHVjiCPSsMX9lsVsMwmFziZym9yrgP\nZAK7Y8z+ieTzBUvi+q1ctSquXzBY+9NAv/9+fly/X35ZVuv0hdRGax37OExBEGpCQvp9RUCOWs5o\n+xuc4FiIK+A1PUIh8Pvxv/ACOiB7rwlCfSAGogR1vgPAfgV2+zTM2ZX3xg378dw3mfzTL+X2VwDz\nC+bChYsrvFebBT9iC4V4mfgzcd77bl4VJU88U6d+G9evoo65kBYkbDAL4AfasQ24h7+PupSBgw6v\npXiC0OBoAcQ6430P0DxWBKXU9UqpBUqpBbsj3ANAALu1ljObDG+vWNEP4nBUfoJMSwU5HIhyzY4Z\nNpKMCmaSOt3xZjbphGyenZ0dX75UWJ4tCILQgKh1vy8EeBWMdwZx5byGK+iNGc5Ys6bGQgqCUHXE\nQFTLzvcuzE73LDucnw2oLMz3ZHwjidOeSZbbhc1WvvNtt9txu+Nv3glgWPv4NCH+1P9Md/KWcWVm\nZsb1k+VlaU/CBrNeYLID1rGc/12fx72jjq0DcQUh/dBav6i17qe17tcywj0EfGr0g8B5NCmaRJHx\nVdw02rdvh91esYHI6XQw8tijuNb2CpmUHHR/gxs4GwNnBW3Un84YEtfv1FNORTkNiIpvs9s599wz\nK5SpKpxwQt+4eTvttIG1Tl8QBKERUetx1A92OCMbwEVTd5ztMQwDJWMIQagXVEX7CzQGlFJ+4Fmt\n9V1R7g8Dd2mtK/ycqJQ6AKyoQxFTjVbArmQLUY8kK7+dtdatk3DfWpEAfSoAimk8dUz0qf5oqDq1\nA5igtb4hyv0/wKjK8iRtVNrTqNsopdRpwNQqBJ2ptR4UFdeB+Y2vwlPMlFLXA9dbP3sAu5E6lq5I\nG1VNZBxVIemqOw0hXw1Sn1IFmUttWr1jWbjjWcSjWaG17pdYkVIXpdQCya9QAbXSJ61168ZU5o0p\nr9D48psglgKx1oIdAVRlwxxpo9KYxpbfGHwPVLyZlklJ5UFio7V+EXgx/LuxlXljym9jymsCkXFU\nHNK1PqVrvoRSxEBU+863IAiliD4JQmKZBDytlOqqtV4LoJTKA04E7qogniCkPVrrEmB5suUQhEaM\n9PsEIc2QPYjMznd/pVTXsENE53tSkmQShIaK6JMgJJaXgPXARKXUuUqpc4CJwCbgf8kUTBAEQWj0\nSL9PENIMMRDVvvP9YuVB0grJr1ARiRjMNqYyb0x5hcaX31qjtS4GhgArgbeAd4B1wBCtdVEVkmhs\nZS75FSpEKdVPKTUSuMByOkIpNdK6sqqQRGMr88aU38aU10Qh46j4pGve0jVfgkWj36QaQCnVCXgO\nGAooYBpwm9Z6fTLlEoSGiOiTIAiCkKoopV4Hrozj3UXaKkGoHtLvE4T0QgxEgiAIgiAIgiAIgiAI\njRxZYlYDlFIdlVLjlVL7lVKFSqlPLOt5g8GaSj1BKbVJKeVRSq1QSj2mlMqJCJOnlNJxrmZR6WUo\npZ5SSm2z0vtBKXVK/ecsNkqpQXHysS8qXHOl1MtKqV1KqWKl1DdKqaNipJfS+W1oNHSdEn0SfUol\nGro+geiU6FRqITolOpXq+U0laqMvqV7OtcxbPN3qU9dyV0G2Dkqp563yLrHkyqti3JR+ZkL1kVPM\nqoky16dPB3yYU5Q18DDwrVKqt7VfRENgDLAFuBvYDPQBxgKDlVIDtNZGRNjHKL/R3IGo368AZwF3\nAGuBm4ApSqnfaa0XJ178GnML8GPE72D4P0opBXwG5AF/wjye827MZ9tHa705Il5DyW/KkyY6Jfpk\nIvqUZNJEn0B0KozoVJIRnTqI6FTDyG9SSYC+pGw5J+hd8Drl92ZamUg5a0g+8HtgIfAdMKwacVP2\nmQk1RGstVzUu4FYgBORHuHXBbHD+kmz5qpGP1jHcrsB82Q2xfudZv6+tJK2jrXBXR7g5gBXApGTn\n1ZJnkCXjaRWEOdcKMzjCrSmwB/hXQ8pvQ7rSQadEn2KGEX1KzrNp8PpkySw6VT6M6FRyno3oVPl4\nKV/HRKeSVu411pdUL+favgusvD2c7HzEkc0W8f9rLVnzqhAvpZ+ZXDW7ZIlZ9TkHmKu1Xh120Fqv\nA+ZgNjQNAq11QQzn8BeW9tVM7hwgAHwQkX4QeB8YrpRy10jI+uccYKvW+tuwg9Z6P+bXpXOjwqVD\nflOFBq9Tok8xEX1KDg1en0B0Kg6iU8lBdKo86VLHRKcST230JdXLOS3eBbHQZWcQVodUf2ZCDRAD\nUfXpBfwaw30pcEQ9y5JoBlp/f4tyf0wpFbTW206KsTa7F7BOa10S5b4UcGFOW0wV3lFKhZRSu5VS\n70atG67o2XZSSjWJCNdQ8tsQSFedEn0SfUoG6apPIDolOpUcRKdEpxpSfpNNbfQl1cs5Ee+CPyil\nfNY+P9OVUicnTrykkOrPTKgBsgdR9WmBuUY5mj1A83qWJWEopdoDDwLfaK0XWM4+zHWyXwMFwOHA\n34DvlVLHaa2XW+EqKpOwf7LZDzwDzAQKgWMw8/KDUuoYrfVOTDnXx4gbzkdzoIiGkd+GRNrplOiT\n6FMSSTt9AtEp0amkIjolOtUQ8psq1EZfUr2ca/sueBv4HNgKdMbcs2e6Umqo1npGooSsZ1L9mQk1\nQAxEAtYXkomYa2ivDrtrrbcBN0YE/U4pNRnTKnwPcHl9ylkbtNY/AT9FOM1USs0C5mNuTHiIRdXg\nAAAgAElEQVRfUgQT0g7RJ9EnIbGITolOCYlFdEp0Sqh/tNaR+vOdUmoi5oykh4CGPpNISCNkiVn1\n2UtsK3E8C2pKo5TKxFxr3RUYrsue2FAOrfUmYDZwfIRzRWUCpVbklEJrvQjz5IBwXirLx94qhkvJ\n/KYwaaNTok+iTylA2ugTiE4hOpUKiE6JTjXI/CaJ2uhLqpdzQt8FWusDwBfAcbWUK5mk+jMTaoAY\niKrPUsz1ltEcASyrZ1lqhVLKCYwH+gFnaq1/qWFSS4Eu1vGPkRwB+IHV5aOkJBU9241a66KIcOmQ\n31QhLXRK9Kkcok/JIS30CUSnYiA6lRxEp8qTLnVMdCrx1EZfUr2c0+ZdkEBS/ZkJNUAMRNVnEtBf\nKdU17KCUygNOtPwaBEopG/AOMAQ4T2s9t4rxOgEnAfMinD8DnMCoiHAO4CLga621L1FyJxKlVD+g\nB6V5mQS0V0oNjAiTC5xN2WfbIPObwjR4nRJ9En1KIRq8PoHoFIhOpRCiU6JTDTK/SaI2+pLq5ZzQ\nd4FV10ZgLntsqKT6MxNqgNJaJ1uGBoVSKhtYAniAewGNuXY0B+gd8bUhpVFKvYC5zvwRzA3TItms\ntd6slHoGMIC5mFMEewB3A02BE7TWKyLSex8Yjrnh2jrgD5gvvQHWlN6kopR6G1iDuR49vFnh3UAJ\ncKzWepfVeZoNdMTMx14rTG/gaGuadTi9lM5vQyIddEr0SfQpVUgHfQLRKUSnUgbRKdEpK72Uzm+q\nUFV9UUp1xnw+D2qtH4yIn7LlXJu8KaXGYJ7o9S2wA3OT6jGYOnaq1vq7+s1NeZRSI63/nor5rvgj\n5mb1BVrrmQ3xmQk1RGstVzUvoBPwMWaDcwCYAOQlW65q5mE95ost1jXWCnMN8CNmgxkAtgPvAj1i\npJcJPGuF8WJ+nRmU7HxGyHc38DPmqRYBYBPwInBoVLgWwKuYHaMSYBpmJ6FB5behXQ1dp0SfRJ9S\n6Wro+mTlQXRKdCplLtEp0alUz28qXVXRFyAvsu41lHKuad4wZ6XNAXZZ9XE35qyj45OdpwgZ470f\nZjTkZyZX9S+ZQSQIgiAIgiAIgiAIgtDIkT2IBEEQBEEQBEEQBEEQGjliIBIEQRAEQRAEQRAEQWjk\niIFIEARBEARBEARBEAShkSMGIkEQBEEQBEEQBEEQhEaOGIgEQRAEQRAEQRAEQRAaOWIgqgZKqbFK\nKa2UGpRsWSpDKbVeKbU+2XI0dpRSg6w6MzbZsoSprB6nksxSj+sXZTJGKbVcKeW16sF5Sqk86/+v\nJ1vGaJRSVyqlflZKFVsy3ma5a6XUjKiwr1vueUkQtU6oy3ZJKTVDKZWwo05Fn4VIYuloPd67Snqj\nlLrKCndV/UgWUwbRG6FBUp32KZnvA+v+omd1iFKqg1LqeaXUD0qpktr0xcJ9kzjX5MRKXmWZkt5W\nJBIxEAmNEqXURqXU58mWI8n8I9kCCLWjDurxZcBTQBHwLPAAsDyB6cekpoYIpdRJwOuAG3geU965\n1UwjrRp1oeGSbu1Sog2MiSBCpqxkyyIkhnTTG0FIRRKgZ/nA74G9wHe1FOePwO+irr9YfpNqmXa9\nYBkk4xm5dLjtVEoNt35XWvZKqblW2L61lc9R2wSElOXUZAuQqiiljgU6Ag8nW5YUZT7QE9iVbEGQ\nehyXOqrHZ1h/R2itt0fcy4lZJ/Yn8F6JICzvlVrraMNQT6CknuURKkb0OQ6NtF0SHa0aojdxaKR6\nI9QNomdxSJCezdJaH2Kldy0wrKYJaa2XRbsppa4D/MD7NZaw/gkAj1YSZiqwCRiulGob2TePRCnV\nEzgB+FlrvbC2gomBKE3RWq9JtgwpzDmABj5LtiCpiNa6hHqYNVIVpB5XSF3U40MBohsgrXWAFKkT\nURxq/S3XYGqtU1HeRo3oc4U0unZJdLRqiN5USKPTG6FuED2rkFrrmdbaqEo4pVQXTEPUMCAX+A14\nQGv9aQVxsoBRwGda6z01lTEJ+LXWYysKoLU2lFJvAPcCo4Gn4wS92vr7akIk01rX2YX5sL4DCgAv\nsAX4EhgaESYPs9K9DvQGJgOF1jUR6BEn7W7Aa8BmTIvhZuA/QOs44Qdb995tybIMuAtwxAjbGnjF\nkrsYmA0MBMZasg6qJN+dAQP4Io5/a0yr4awIt77Av4GlVt6LgUWY0+hUjDQ0MAPTovs2sMO6Zx/L\nfz2wPipOd8zlI4sxp/h5rfvdCzhj3GO9dTUB/glsBXzAz8DIOHlrCjxkpesB9gDzgDG1eSYx4p5i\nlcG/4/gfY/m/GcNvETA/4rcNuAFYYJVLCbAR+Nh6LlWpx92s+x2wyqjIyn+x5f58nDofqx5rYE6U\nzDMs92HAaiBk/d5uldnxMerPz8AcytbjW614sa6rrHsNsn4/R1Q9Bs63yuKAlaYBrIxRj7dYafiA\nVcBaK/xu4A2gpdTj+q3HlchxVZw6sT66zsYp2+aY79/NmHXzvIhn9aYVxmeV0SLMxj7yXRbrer0C\neQfFixf9joyK97rlPh9TL0IV3D+yXZpuyW9YcXZh1tcuUemH3wM+TH0utp7DwTpdQd3RVpyxwIuY\nulAETAEOw2w3PrbS1kAQs718lKh2CXACfwV+xay/ezH1LGa7BPSx8qgx26bxQCfMuqQp3y7dAtwB\nLLHytx/4JlzmiD4nVZ8j0jgN+BrYZpXRduBb4OI4sn1kPTMfsAZ4DGhi+Ue3g7sx9eCAVaargXco\n1ZtK9TqivkS3gzus+++itA15JEKW8DPaa6Wxz6pDEyy3Ysz6eDTl+3P7rThPEqE3QDbwjFWfPNbz\nuBC43Qq3JE4ZS38u/fTmGsxlKhusMtqFOR7pFxXuCkuuO+Kkc77l/2CU+82YH1y8mH2jeyltO76l\n6uOm36y8hduxkJVer4iwr1t+3TDrdyGluriPGOMmqwyvs55h0AprYM5iKPdMMQfxz1rphdPebZXj\nWMq3T6OAnyLy9wxmfdbAbtGz9Ncz4FrrXrMo2z59j/mO/hXTGDI8ok79H2Ybtcd61tOB4630LrPC\nnG39bgv8C1MffNazLtdni8p73PYvKmy8tuIqIsZSVSiD9UBRFcN2terqr3H87RHl2LIqaVZ6z0Qk\nEkfYm6yCWg2Mswr6Dev30xHh8iIqyX7MzsyjViUzMF/M+VFp/84K67Me6JOYL3PDeqgtosLfbPnt\nxLSsPYOpfBr4JCpsE0yFC79IHsXsLPswO+plXnQV5P87zJdZOYOVJY8Gro9w+y9m5+hdKz8vWHnR\nwD9ipKGBXzBf2Isw95N5CegeUfGiX3R3WeX5IaYF8nnMl5YGJsSpvFswFfY3K/wrlBoGhkWFPwRY\nSekA7ClMBZ1O1Eu/Os8kTvkqzMa7gNhGvqettKJl7Gi53xPh9pTltsQqxycwO7pbgQ+oWj3+2ApX\nYtWVzdbfbRHu+VF1/gti12ON+dJpEZH+DEpfkiFgBeaLeZXltjaq/ryE2dHWlntkPV5NqXFpbMQV\nbiQHWf5jiajHmANObT2zcZQOKA82OJTW4x8i5AqHWWjVCw3Mlnpcr/X45krk6GM97/URz34scFtU\nnX09Rtluw+zsrbDqxTjMjkh7zA5jMWa9fBTzvfYtsCMijVj3HYtlZIojb54VZrEV7x/heFHvyBlR\n8eZa7ustOcdjdmo0pi6F7/0PStulA5gdMYNSfQ4bgAqAblHtkrb+FlLaYS4Ejquk7uynVGf3YRpo\nP7V+b6C0PdiNWcf2WL/DxthBVro24HNKDTtPAi9b+dCYHf7WEXL0tvzCg4yvMHVlI6aeacq2S5E6\nPZ9Snd0ZIavocxL12Yo/wsrLVuB/mPr3qlW246PCno9Zpw8Ab1n3nmbdfy6mQTCyHQwbDoOWfI9j\ntpXh+j4LU2c81u9wn6oEuDFKRxdRth18j9JB6QEr7+FnsAD4c8Qz+pBS/dJWuT+DaSjSmDqygrL9\nuQLrd7j9GoSpM99S2k49jtnO+yjVpTJ6E1VnNNKfSwu9sdLwWOX0klUX3rfcvED/iHA5mHV6cZx0\nxluydI9wCxv0N2G+4/+F2RcL17NIPYvX3+xJqdEmAKzD1I3tlvvBcROlBqLZlH7gWElpW6WJGDdZ\nz+KDCL8Sq75Ehv8kQpZWln/Yb5NVDwOUvj8i26drKNXN/1h1ZV1E/g1Ez9Jez6w8akyDTGT7tIco\nIwelbYHfqk+PYbZTfky9HIA5Pt+BuTLqMOsZhDBnPD2FqcNl+mzVaP9cEWGr0lZcVcX3zHqqaCCy\nwofve1wMvxGW30dVTa/S+yUqoRjCLrIeUFYMv8gHn0fpiyXayv5/lvtnEW4uq4LvAXpGhR9lhR8X\n4dYL80U1F2gapSjjrPAjI9wftNz+FZX2NRFyDqpC/m+wwpZTFMzBsw9oHuHWCbBFhXNgfiEOAZ2j\n/MKyvBQdL6LiRb/o2kVW9IhyeMlK66QYaWjMzlakgpxquU+OCv+J5X5vDHna1/SZVFDGj1lhR0S5\n26y6tw2wR/mFDZdHRbjtwWxco8PaMF9+FdZjYEjE8zhYj4EjMDsUYffPoup8UZx6HA4fWY/nR8Tp\nFKfMRsWoxxsi609UPY7XqRlE6WD9hoj/B62yaBtVj8Od/4FY9ZhSS3oA01gQrsddKH3J9UfqMdRP\nPW5emRxW2BmAjuGeZ93v9Thl+yWQEeUXHlSeG093KrtvFeR93bpHXgw/TXkDUXimzuERbuG6elOM\n/GrMzqQPOMXyC7dLs63n/zll26UydZoqtksRZRnuLI603J+PSPPbiDQc1j3LtEsR+ZlCRCfQumfY\nADUmwn2W5baCiHYJs9Ojo58LZodIY3ZUO0e4t46Q5VVEn5Oqz1a+fUCbivQPc4BXiGn4axcV7g5L\nrs2W7FmULjVYiPnlOzKtHhF14EEi9JrY/TmN2UbuwRz02jEHeAZwv+U/znoGr1u/Q+FnRFk9/Z6y\nevNQhN+/Iu454//Zu/MwKYr78ePvmmNnF5ZdjuUQEBZBUUBEUIzBA5Uo3qKIZyIx0cQkmsSYGI1X\nogbvmOhPvzEeJB7xwIjirQiINx4ccij3jdyw55z1+6O6mZ7Z3t1ZdmZndufzep59Zqe7p7umpz5d\n1dXV1Y7pGlPe2eXiVBz5lrplu9Tn2njcWMvW6WVg5c8K4N2k6f+10jA4aXopJm87e10caP3+y4GO\njundMSfWGtOQ0Nh5k937QlP3vOlKEuubk4nHzQ6s+iamcWuhYz0PWtN/RlKcWdPbYxoj7AsJ45O+\nf3KcDcA0LjnjrBRzrNnl3MeYC/POtEictfE4w7QRaJJ6G1lpeNb6He0/5zG4xGWfLrJ+7/uS8sox\nSes+0tqHrzqmpVL+OetLqZQVE1M8zqwi3mvc7e/8pOV/aK3/IZd12Y3RJ6ey7ZTSl64V1fPjrwQC\njSxXbn2p7UB7lyBcYv3w9sn42dbyf6hnfZ8DWxzv7VbKkS7LlmAqIlMc01ZgWiTL6kmLJrUGos5W\nBv04abrdjfSlFPej/X0nJk3XmMLHtSsZLge6BrYx3FrfLS7r0LgXlqtwtG5juvPFrH3kbWR7TfpN\nGljPEGs9/02abgfq31w+8xawImnadszJnluX1EbzMeZkyD4wJORjzK0iGnMFIgp0IbFSWycfW9Mr\nkvKxfevZb5uYjy9x5p+kfJxKA5Gdj9c6t+/Mx8B46//HHeuYaE37d3I+dsyzKzKSjzOcj1P9Y+8b\niIa4fMZuIDpxb7ebwucmW9soryeOZiZNsxuInFd07fw40eX72ldNH3LMc5ZLr1ivF1vL2b3sEvI0\nKZRLjn15kDPvAEcRb5BJLpduwFEBt6bNsN4f6rJP7ErtUut9X+v9ApLKJUzlO+L8XTCVvx3Ee11N\n1HX3uQYuqOf3WoXEc4vEM+bEo5JGKuuYJ79oYILLPA/manUVVjmI6WGmSToxSoqb7ZgTypl2/sG9\nPpdQDmIuMmjg5eS4wZyo2T2LRiZtbwXm5NMZN/a8KI64Id5AZPe+HU28N5Hbcexta14Yqc+1+bhp\nJI2vYOpDzhN/+8r9pKRl7RPJXzum3WJNu8Jl3dcSr/s1dt5kNxBV0ch5E4m3e/4hadkLrenfEY+z\n+cRvYx6ZtLz9XWOYE9IyazvVuJ833ePY9mjit+Td4/KdLnSsW+KsjccZ8QaioUnT7Z5n9f0l39b/\ntmPeIY7fpU4jirX8FCvP2g2fqZR/nzumpVJWTExxH6yi4e86NWn5IkyddDuOYwQmzu07V+o0fO7t\nXyYHqX4Oc6Xxa6XUs5hC+WNtBsB185XWuso5QWutlVIfYa5KHWyt4whr9mCl1C0u6ykCypRSZVrr\nrdbyGjhNKXWKy/I1mFZ9lFIlmB4O86zP1peWRmmttyul3gDOVEr11/HBzy60Xp9yLq+UCmBOqM6z\ntlGctMp9qGuV1npbKumxtuHBXMWbiGmNLsEUJg1tY6fWeqXL9HWY1ljbYda63tNaRxtJSsq/SUO0\n1l8rpeYBZyilirXWldasi6zX5H3cAVNI/V/Sqp4Dfg58qZSagslnc7TWIVLLx4c4/k/Oxx9g7uVe\niwnigzEHBVt9+dhDYj4usab3rmf5GuAopdTnJOafydarPfjwXudja9Is69WZj+1phzjy8S+saT9S\nSv3Iscp9gDnW/x2tV8nHmc/HmVSrtf7aZfo0zNWql5RSz2OexPC+1npdhtPTkJWYRs+3lFJPYfZR\nQQPLb8Tkr15JcVeDidF+1usPrOmDrddK4Eql9mTLVMqljpjK63kk5p0K63V3crmEy+DcmONRhdb6\nK5d5b2FOLgYopfpjejk6t7Enr2mt1yil1gD9XI4rduxerJQqd9lOL5dpriSeMxbPz2G6zn+tlPov\npmL7odY6+UmEdp1qlFJqEHWFMVdxyzHjQvTC5NMvG9j2V1rrKkf+r68+Z7PLQTsthdZ7Z9xsUEqF\nrGlnW7+RnQ+DmFvPnL+R/T2rXeIGTK/cAdb/hwC76jmOfYCJ7wXA96Q+V0dbixuUUgOA6zHjvfSk\nbhnRBVM2gOmtshW4UCl1vbbO2Kx0RzE9bGx2XfFjl81+ZL0W0/h506fWaxHwhFLqTUzZuswlzpyS\n65uljm22U0rti2lACFvT77YftW1pZ71GMb/p4ZjyrwjTyPQrZ8xjLnY42d//A+qyp21H4sxNW4uz\nOZhxf9626mLvYcZM3YYZ2uLOpGXXA2dheto52cfntVrreUqpK6zpyXU22z6YPLs/5gJEKuWfc7+m\nUlY0RZXWOjnfutJa11jHhcsx52TPW7Muwhyj/q1THAg8JelqaXJpGVOYE+MviLeG1WIyX3fHcuW4\ntGY65tvd4c603v+Lhlvc7L++1vJLU1h2pbVsb+v9O42kZXSK+8DuWXGTY9oSzH36gaRlX7OWXYy5\nH/M2zNWGybi3UmtgVgPbXkXdrpL/z/rcKkyvl7+SON7G5MbW4Zg3k8Qry/YAYXW6Sbp8NuXfJIV1\nXWMt/yPrfcDav4tdlrVv9Tg+abo9oKvzPurdmG6bxTSSjzH3h9u3biS3ytsDrM22Xs8ksQdRqvm4\nOsXlF1tp05huzHXyD/F83GgPoqR8rLG6vJKUjzEH0aXE87HdXfoVkvIxiT2UJB+3UD5OMR0J+8Mx\nvbyBfbu6gfUNxfRkqHKk6Qvq3uPuut0U0mvnq3KXeZr6B6le4EiPfcXqKpfvOy+F31hjGsOaEs9N\nKZfsWzE3uHzHiY7lR1vTIlg9hFyWP8qx/E3Eez5twb1csgcBtsulyaT2PW+WeM6JeD4bU2m1bwsJ\nW3l1gGOZd1L8TZtcn3P5PZLrc6ls1xk3qZSDdtzY9bntbnnEkb9G03DM2Lfc2LdxSH2uDccN5sRx\nB/GHANyHuV3yFuJj3pUnfcbOG/ZtyD0xMfdG0nL2QP69XLZr3575IanH2Urix2iNuU34QhxxRurH\nbI152Emqy6505JNU/kZjxsLTwCiX7x+w5tm3mkmcte04s3vBzSGxfFqL6RFalPS7fVzPeuwxvV6y\n3v8pxfx4rLV8SuWfY3uplBUTU/wdVtGEMYisz9gNhW84pn1lTRvQlHU1uq10rqyBL9QVc5JpD8A7\nyzGv3Jo2vZ7P2rfvjLbe32u9H5vitr/AdL2rc0+vy7Il1rrrO3FOSEsK6yu0gu4b6/0I6/OPJi13\nuP2DU/d+2vOo/0A3s5GMt8rxvru1H+Y6Ay8pw01uaB1J82YmBc2p1jpcu/Xt7W+Swrp6YQ4ub1nv\nz6GeAy6mkN1BA6P9YyqVPyQ+Lse/G8vHJBbm05PWZ3eptQN4NObWDXv5sUnLl7r9tsQHmHW7Nz0h\n/zjzsVv+ceTjVBuICok3gA1PzseYq2l2IW2n48c4DpTOdFC3gUjycQvm40bSkbA/HNPLm7pvk5Yr\nAEZhCnN70OcDG9tuCuudbKWr3GWeWxztWZ54PNuxucTl+9oD3P48aT31lkuN5en68k59+5J4l/Dt\nLvMm4qiAW9O2Y65wuW3Xzle11nc73fH5+soljVUuYa5Ia8xJjJRL9a8rJ+LZ8flSa1/Y40otxbpN\nhvgDFg5McV1brfzTaH3O5fdIjpuEcpD4balX17Nte9Drbknbm+yyrF0OViZNn2lNt5+4Nhpz1Xpn\nPdu8yVruMqQ+1+bjhniDwIUu8+zbK8uTph9pTf+n9d5+8t3FScvZDx1we6Ll0c7fjRTPmzDjdo3A\nnBjbDwqw0zmaxAai5PqmXRedab3vYL2vTOU3JbH8aPS8iXg5WecBFI60vI/EWZuNMytPj8cMKK6B\nKzDnSdcSL58imN49lxC/7XgbjmEsHOuzB0G/0npvD13x8xT3RVPLv1TKiokprmsVTWwgsj73tbWP\nemJ6NCUcH9L156EFaK23aK2naK3PwATaMUqp0qTFDlVKtXdOUKav4vcxQbHAmvyZ9fq9FDf/GaY3\n08gU0rkb0yo+UClVVk9aUqa1rsVkvgOUUodTTxc+zP21YB4/nNw9bFRTttmAfpj98K7WuiYD27Ab\nSY5XSnkbWTbl36QxWuv1mIPuCUqpHsRb5J92LqeU8gEnY1pdIw2sb53W+knM44G3YAbktOfVl4/n\nOVaRnI+Psl73JZ6PdzrmJ+fjQ+tJ2m7r1W2fJeQfZz7GDOK2R1I+Tin+rXxsx99F1M3Hx1qv9u0u\n9lUdJ8nHDWjJfJwNWuuQ1vpDrfX1wI2YK1YnORaJAqSwz9OZpi1a6ymYK8RgjvvJ5VIP63VPnLZ0\nuYSprAOUJJdL9ZhrLTvMZZ4dq59gHt/rlFwu7Umbo1xajGngG0x6SDy3QDxrrXdprV/TWl+CeVz3\nAOK3f+xN3g1gnhrUWH1uT1zXEzc2e9tzrddjkjeqlNqH+K0+brcCJLDKQYCieuLG+TvPA0qVUkNc\nlrPL8DBSn3PT1uLG/v1eSdpmIeYCmdt2Psb02D5XKVVgpbsK0yDkZNcV3WLNeetRyudNmIdDfKG1\nvh1z6wmYxouG4sxm5+151jYrML11CkjtN51D/IJDKudN9vc/irrsaTEkzty0lTh7wfr7ufX+IUzD\n0MmO8smLGefwr5gePgCdiJcPdvr8xGPSvkVxb8qzpiyfSlmRaU9g9tGPMBfjwTTEplXGGoiUUse6\nTCvCXMmKYFUcHDphWhCdLsWc5L6u4/eMTsV0Qfu9UqrOD6qUKlJKHeGY9JC1rQeUUj1dlu+ulHLe\nJ/sUpsfETUmL/pgUx21JYh/UfgScb6V9VtIya6zXhAOO9f0uJz3sbRypHDcJK6UOAK5r7sq11psw\nheFAt/UppZxjUjT1N2nMU5hguQI4BfhI173/9yjM2CPJhX5AKXUkdXXA3Fdd535Ol3zsLLj25GPr\nflZ7/J0uWPnYqrh+a03/g52PrXt9J1nTPUn52L7v1m2f2b/tyY5pdj6+NGlZZz7umvzdGmCfRP8M\n04V5LTBLKVWM6QkE5qAPko/tZXMpH9c2IR1poZQarsy4bsm6W6/ONG23XvfNbKr2bNvJboCxHwHs\nVIK59/2HSqmzrGl7yiVgt1LqKBzlkttG01AugckbyeXS0S6b+4/1OslZ6bTW91PM2Cx3W5NPxPQO\nBJOvnE5NXrFVSXyZ+NgVKnkZoINSqp3LdDcSzxmKZ6XU0cknHdZ4GvZJnL2OJzAxMEkpVaeOo5Qq\nVUr9xDHpYev1H5gxgJz1uYD1apeDzrh2q8+BGT/Irs99gLm94Ayl1FFJcXM7ps4ao2m/kYe6cQPx\n8YcgXobfZu0je33HkzimhNTnaNtxg8vvZ+3jSUC3Bj73NCbf/w7TcDNVJ42rihm3JQZc42zsUUp1\nBX7tttJ6zpvsvJt83tTdMT05zmLUrW/+yZr3vCPOHsDcPqSBB5N/U6XUYOvvICufTMHUNVM5b3oF\nc4HhMqVUP8c6ix1pAYkzezttLs601kprrTAXAXz2e6316KTy6TqtdS+ttX1RQGF6kzkdg8mrX2tr\nzEWt9aeYRh9nnc2Zdr9VZ7OlUv45L9ynWlZk0pOYCxY/xjTuVRA//0qfdHdJcnSB2onpPvUc5krT\nP4jfQ/mAY7ly4t0Kd2FGAf8rpgU5hunONSBp3UdgKh4x4vcI/wOTiXdR9zGCV2ACq9JKz52Yp0u9\nZ+3kPzqWLSb+2O6ZVlqmYCoxb+HoHp3ifvBgDm72LTp3uizjJd4SP8PaX1Osz9iPrrsl6TNN6ipp\nTbMfp/g55gThaUzGsrcxubF1OObNxNFV0prW3fEbf2Z9j/sxLcDbkpZN+TdJYR+XYLqe2/vY7QkR\n91nzS5Omd7Q+s9jaH3dgKsDrrek1pJaP7W6K1cSf+hXEDGRoT3eO+3CZNT1mva7B9BKy1x3BkY+J\nd4uvb5/Z67Hzj92V2f6bTd18rDEntjdjnoY01NrW6OQ8h8nHOx2f+8Lapyut9/+PxHxs3242h6R8\nTDNuMZN8vNf5+HcppqHO/tCJx+mm7Nv7MVdR37Tyxx2YRpUY5vHszsfVXuHIV7dZ+bSeHTMAACAA\nSURBVPH0FNI7GZcu//UdIx37dhrxeF5uTQsCf7e2bT995X0rb9m3tmwlflx4E9Olf4m1brtc0tZr\nU8ulXda2EvKOY9/b8TeTeLnkfOLHaEesvmpNW+DIk7ut7Z1P3XIpiDnm/BdzIvQR5phkj/mSXC7Z\ntzJsxYwLeCfxW3Y00EPiObvxjLnauglTNt1rbcu+nXJa0rJnONI61fodHsLcvlFj5Y9VxMtBeywW\njenuPslKpz0eil2fs+tS9vRq4PKkGP2CxPrc88RPhkOY+PzYkUeucvxG9thf37j9RtY8e/yzmZi4\n2WK9t59GMxoTDzMc6bkDc1W7lngsTUTqc/kQNyOsNFdhrsr/zdrH2xx5xK28OcCaZ6fb9XHT1r7R\nmOPrfZgyZ6Mjn1XQeH3zL8TLhCCmUXUJ8XrgDqz6JvEy8gPH/JXEn9C5Akf5hDkRt8ex1Na+WIwp\nS+zyL0K8fOqCOQbYy6/H9FC1n3xrjy9jl08/IV5GPoQ5Nq10fP+ZSJzlQ5w1pXzSmJ47azBlwSRM\nI0nQ+g7fT1q+P/Enrc7GxNF91rb21NkcyzdW/v2fY9mUyooUf4NVNPyY+1uovy7lPMf7V6q/e1P+\n0r7CpIz8irUDajGF8geY+xSVY7ly6wtOxgxo+iamIrvb+vzAetbfBzMY1nIrk+zAHMAeAA53Wf5I\nTAvbRusH2YQ5iN0E9ElatiumYNiKKSQ+xFQibsFxoGvCvrjL8UMeXM8y3a19sAFTifoC01NjNOk7\n0HXAHHhWW7/JQkxlqx9pONBZ0zthgvdb63fZZu1nt8ezp/ybpLCPnydeONd5hCVmIOk6g49jWp+v\nxTRMriPeqPMO5v7qVPOx/RjOSisNlZgDi105fcBl27/AFM5RzME9Qrwivc6Zj4k3ENW3z+60pjvz\nz88wJ+T2fknOx+9Z38cuwCda26ovzznzcbVjO5e55GP7e6wiKR/T/AYiycdNzMdN2H59+6N8L/bt\nEZiBI7/GVGSrMBWKu7DGEHEs68Pk4dXEGz0mp5DeyTStgcg+0VxHYjzfg6mcJQ+COxlTLk239mmU\neAVtMfAYcIJj/fY4CvZJdVPKJbsynZB3HPv+v9Qtl+5wpHW0S35YaH3PnZiG4WPriedzrbxTZaV5\nivVd7LGGksulExz7cbf1fVcQrzS6jlfgll+QeM5IPGPG4XgeU0eqxpyQfY4Zo6HAZflBmPxun5ht\nxTyp7A7MsTq5HFxi/e221r+UeCPhZEzcvGWlPUb85HSyY5va+s2S63O7MSetNZjjwTJM405x0m9k\nN1TWuP1G1rwPSYwb+8TYzv+jrWWLMScRG631fYUZm2MiieWj1OfacNxY6zkB00heYX3nFzGDV0+m\nnvLG+txn1vzvqP8YqKzf6RsrfSsxt13bY9qsoPH6pn383YY5tkcx8RXCDIQ90LGsneb+Vt6183/M\nypuu5ROmZ8IXxBsQNPHGqFtJjLP2mAs72xzL1mDKzeeoWz5NwDQQ1GIaFe7F9DzZEwdInLXpOKMJ\n5RPxcqIvpm6y3frMe8AR9ay/i7VPF1l5cTcudTbH8g2VfwcmLZtSWZHCPljlyOP1/dUZr8z6rHP8\nryOb8run+qesDWWNMo/IXYkZ1GpiVhMj2iSl1GDMSepVWusHMrSNciQfiwxqiXwsDIlnkWltMZ4l\nbkSmtcW4AbBu43wU+KXW+qFGli0nxThTSk3GDPbbT2u9Kg1JFXkgl+JMKaUxgzCPzmY68k2LDFIt\nRJbZA6a90uBSQuQ2ycdCtB0Sz0I0XauOG6VUV5exwfbBjMETw9ymIkS2teo4E80nDUSizdNaT9Jm\nELTV2U6LEHtL8rEQbYfEsxBN1wbi5hJglVLq30qpO5RST2FufekHTNJar2n440JkXhuIM9FMvmwn\nQAghhBBCCCHauA+AYzFPkOyMGe9kAWYg3P809EEhhGgpWR+DSAghhBBCCCGEEEJkl/QgaqaSkhLd\ntVtX95m6YyOf3pX29KRTRxpuPNyJaqGU5J8VK5Zv1VrXk7HarpKSEt21a7esbb+xPJ9JmT4a6GyG\na6PHwsxbseJLiammUo3EQ2O/q9q5d9u1dGxk8zsby9MZzPQqi8eKXLB8xYo8jacy3bVr32wnowEN\nlCSNxbPIqhXL8zOmykpKdN+u7l97Jxk+j8p0TGS14pXf8vU8Kl2kgaiZunbryh333OE+M3xWI59+\nLe3pSaezCDc4fyr+FkpJ/pkwYVxe3vfbtWs37rjjnqxtv7E8n0mZPhqEsxmujR4LM2/ChAKJqaby\nNxIPjf2u/ql7t13LWY1sfmpjeTqDmd6fxWNFLhg3YUKexlNf7rjjk2wnowENlCSNxbPIqgnj8jOm\n+nbtyid3uJ9HTSXD51GZjomsVrzyW76eR6WLDFIthBBCCCGEEEIIkeekgUgIIYQQQgghhBAiz0kD\nkRBCCCGEEEIIIUSekwYiIYQQQgghhBBCiDwnDURCCCGEEEIIIYQQeU6eYiaEEPlAnqYh2hrJ03st\nLE8hzT8SL0IkkpgQwpX0IBJCCCGEEEIIIYTIc9JAJIQQQgghhBBCCJHnpIFICCGEEEIIIYQQIs9J\nA5EQQgghhBBCCCFEnpMGIiGEEEIIIYQQQog8Jw1EQgghhBBCCCGEEHlOGoiEEEIIIYQQQggh8pw0\nEAkhhBBCCCGEEELkOWkgEkIIIYQQQgghhMhz0kAkhBBCCCGEEEIIkeekgUgIIYQQQgghhBAiz0kD\nkRBCCCGEEEIIIUSekwYiIYQQQgghhBBCiDwnDURCCCGEEEIIIYQQeU4aiIQQQgghhBBCCCHynDQQ\nCSGEEEIIIYQQQuS5VtdApJTqrZR6QCn1sVKqWimllVLlScuUW9Pd/jomLVuolLpbKbVRKVVjrfeY\nlvxOQmSTxJQQ6SPxJER6SUwJkT4ST0KIxrS6BiJgADAB2AHMbmTZScCRSX8VScs8BlwG3AScBmwE\n3lJKDUtjmoXIZRJTQqSPxJMQ6SUxJUT6SDwJIRrky3YC9sL7WuvuAEqpnwInNrDsCq31J/XNVEod\nAlwIXKq1fsKaNgtYCPwFOCNtqRYid0lMCZE+Ek9CpJfElBDpI/EkhGhQq+tBpLWOpXF1ZwBh4DnH\n+iPAs8BJSqlAGrclRE6SmBIifSSehEgviSkh0kfiSQjRmFbXQNREk5RSEaXULqXUK0qpg5PmDwZW\naq2rk6YvBAow3TCFEHESU0Kkj8STEOklMSVE+kg8CZGHWuMtZqkIAv8E3ga2AAcC1wMfKaUO11ov\nsZbrjLkHN9l2x/w6lFKXA5cDlHUtS2OyhchZGYuphHgq65rmZAuRk1qujJKYEvmhhcqoPmlOthA5\nqcXKqD5lch4lRK5pkw1EWuuNwM8dk2Yrpd7EtGj/CfhhM9f/CPAIQLfuPfQrU99i4IH9OWBgf5RS\nrp9Zs2YRGzYsp0+fg+jZUxrUReuSyZhyxlP//gN0c9Ip3FVWVjHl5bfZuXMXRx99JEOHDsl2kvJa\nS5ZR9cWU1pply1awePG3dOxYwsiRIygsLGzOZnPCqlWr2bRpM+XlfejRo3u2kyNaSMuVUSOkjGrE\nqlWrmT37Y4LBIMceexT7798/20kSTdSSZdSI/v1bbUyFw2FeffUt1q/fwCGHHMyoUUfg8bT1m3NE\nPmiTDURutNZrlVIfACMdk3cAfV0Wt1u8t7vMS7B1yzb++9RL+Hw+Dhq8P3+47pf4fPHdWltbyaRJ\nF7J8+Vy8Xh/RaJghQ47hd797HL+/Od9IiOzKVEyJ9Jr94Wfc9/d/7Xk/a9aH9OnTi7vuulUqMjmk\nJeMpGo1y770PsmDBIiKRCH6/j8cff4qbb/4j/fq5bS73VVVV8de/3seaNWvxeLxEIhFGjDiEq676\neUKZLPKHlFEtS2vNgw8+wgcffILW5pz/7bdn0L9/P/785+soKCjIcgpFc0g8JVq2bAU33ngb0agZ\n0un99z9i8uSneeCBu2jXrl2WUydE8+T72cFCoJ9SKjmSBwEhYFljK9BaE41GCQaDLFr4Le++/X7C\n/Mcfv55ly74kFKqhpqaCUKiWBQve5/nn70zblxAihzQ7pkT6RKJR7v/Ho3Wmr1mznmeffTELKRJN\nlJF4mjFjNgsWLCQYDBKNRqmtDVJdXcPdd/9jz4lda/PPf05m5crVBIMhampqCIfDfPnlfF5++fVs\nJ03kFimjMmTOnC/58MNP6xxDli9fyVNPPZ+lVIkMy9t4uu22u/c0DtkqKiq5994Hs5QiIdInbxqI\nlFJ9gKOATx2TpwF+4FzHcj7gPOBtrXWwKdsIBUNMf2f2nvexWIwPPniRcDhxNeFwLdOnP9Xk7yBE\nLmmJmBLN8/7sT4jVc8I/ffqsFk6NaEhLxtN7771PMBiqM72iopJ16zbszSqzKhwO8/nnXxKJRBKm\nh0Ih3n77vSylSmSblFEta/r0WcRi7g/ImjHjfdfpovWQeIrbvHkz1dU1rvMWLlziOl2I1qRV9rtW\nSo23/h1hvZ6slNoCbNFaz1JK3QvEgE8w3RsHAtdZ026316O1/kop9Rxwv1LKD6wErgD6ARftTdqc\nV05isSjRaMR1uWDQ/cAiRDbkckyJvVdTU3/dLBKJtmBK8kuux1N9J3FK1T8vl0UiEWIx94bQYLBN\nnp/knVyPKdHwsSMcdq8Li+yQeGqe2tr6y5XW2gtXCKdW2UAEvJD0/iHrdRYwGtPl8Qrgp0AxsA14\nD/iz1vqbpM/+GHOwuw3oCMwDxmqtv2xqogoKCjh29Pf3vPf5/PTvP4xlyxJXpZSHgw8+pqmrFyKT\ncjKmRPOMPuZ7PPrEf13nHXbYsBZOTV7J6Xg65phRrFu3gVAosRdRUVER++7ba29XmzVFRUX06rUP\na9euT5iulOLQQ4dmKVUizXI6pgSMHn0U8+cvdD1BHjz4wCykSDRA4qkZevfuhdfrJRqte6GtNZah\nQiRrlQ1EWmv3R4XF5z8OPJ7iumqAq62/JlNKoTUUFgboW74vY089LmH+5Zffy803n044HCISCeH3\nF1JQUMjEibcCi/dmk0KkXS7FlEif9u3bMe7Msbz08psJ04uKCvnJT5r1EBLRgFyPpxNPPI45c75g\n+fKV1NYGKSgowOPx8Nvf/jJx4PLwWenaZMZdccVP+Mtf7iQSiRCJRPH7/RQWFnLRRROynTSRBrke\nUwKOPHIk06e/z9dfL0qYHggEpLzJMRJPzePxeLj88ok8/PBjdab/7ne/ylKqhEifVtlAlEu6dOnE\n0aPHcNBB+zN02KA6TwUqLx/C3/72EW+99TirVy9iwIBDOfHEiZSUlCENREKITPvRRecwbOggnn7u\nFXbvruDwww9lwoSzCQTkiTL5yufzceONf2DBgkUsWrSETp06MmrU9+jQoTjbSdtrAwbsx333/ZW3\n3prO2rXrGThwAGPGHNeqv5MQrYnH4+HGG3/PnDlf8uqrb1JZWcWwYUM544yT6dixNNvJEyKtjjvu\naPr168OTTz7Hli1bOfDAA7j44vMoKemQ7aQJ0WzSQNRMJaUduOCicQ0u07nzPlxwwZ9aKEVCCJFo\n6MEHcdDBcquNiPN4PBxyyBAOOWRItpOSNmVlXaTHkBBZpJRi5MgRjBw5ovGFhWjlysv7cuONf8h2\nMoRIu7x5ipkQQgghhBBCCCGEcCcNREIIIYQQQgghhBB5ThqIhBBCCCGEEEIIIfKcjEEkMiYUCvHO\nOzOYNesjfD4vY8aMZvToo+oM5C2EyKzPv5zPy6++y65dFRx22DBOO22sDN6b53bu3MW0aW8wd+4C\nOnXqyBlnnMzQoW1nPCIhxN5btGgJU6e+zrZt2zj44EGcccYpdO7cKdvJEiKt1qxZx0svTWP16rX0\n61fOuHGn0ru3PKZeCGkgEhkRi8W49da7WLlyDaFQCIC1a9czb94CfvvbX2Y5dULkjxdfep0X/vca\nwaCJw02bNvH++x9x9923UlzcPsupE9mwc+cufv/7G6mqqiISibJ27Xq++WYpF100gbFjx2Q7eaIF\n+AlnOwkiI05txmdfA2DmzNk8+uiTe+puGzbEy4wuXTqnIY1CZN+SJUu5/fa7CYXCaK3ZsGETn332\nBTfffC0DBuyX7eQJkVXSlUNkxFdfzWf16rV7KhgAwWCQL7+cx6pVq7OYMiHyR1V1Nc9PeXVP4xBA\nOBxh9+4K3nprehZTJrJp2rQ39jQO2YLBEE8//ULCMVsIkV8ikQiTJz+TcByIRqPU1NTw4ouvZDFl\nQqTX448/STAYQmsNmAvbwWCQJ554KsspEyL7pIFIZMTXXy+itjZYZ3osFmPRom+zkCIh8s+KFWvw\n+et2FA2Hw3z11bwspEjkgrlzv05oHLJ5PIq1a9dnIUVCiFywadNmYrFYnenRaIwFCxZmIUVCpJ/W\nmlWr1rjOW758VcsmRogcJA1EIiM6deqI3++vM93r9dGxY2kWUiRE/unYsYSoS0MAQJcuXVo4NSJX\ndO7c0XV6JBKltLSkhVMjhMgVHToUE426lxlSdxNthVKKoqIi13nt27dr4dQIkXukgUhkxDHHjHId\njNrn83LYYcOykCIh8s++vXvSq1ePOrFYUFDAqaeemKVUiWw7/fSxBAIFCdO8Xi/7778fZWXScChE\nviotLWHIkEH4fIk9TwOBAs48sznjGwmRW0466QQKChLLwYKCAk4++QdZSpEQuUMaiERGdOxYynXX\nXU1paQmFhQECgQK6devKLbf8sc4BWQiROTde92sG9C+noMBPUVEhRUWF/PSnP+SAAwZkO2kiS4YO\nHcLFF59HYWGAoqJC/H4/AwcO4He/uzLbSRNCZNmvf/1zBg06EL/fT1FREYFAARMmjOOwww7NdtKE\nSJvzzhvHqFFH7Mnnfr+fY48dxdlnn57tpAmRdfIUM5ExgwYN5J//vJ81a9bh83np1asnSqlsJ0uI\nvNKxYwl33n4d6zfvpLKyin337eV6+6fILyeddALHHXc0a9eup7S0RHoOCSEAaNeuHTfccA3btm1n\n585d9OrVk8LCQLaTJURaeb1errjiJ1x00QQ2b95Cjx7dKC4uznayhMgJ0kDUTB01nFXP02KntmxS\nmuysFnjMrcfjoby8T8a3I4RoWLduE+nWLdupEC2vlPoefV1QAP37t2xqhBC5KvE40aWL+Yt7rUVT\nI0TmnUpJCZRkbOg9iRnROsktZkIIIYQQQgghhBB5ThqIhBBCCCGEEEIIIfKcNBAJIYQQQgghhBBC\n5DlpIBJCCCGEEEIIIYTIc9JAJIQQQgghhBBCCJHnpIFICCGEEEIIIYQQIs/JY+7zxMqVxaxcWUz3\n7rUcdNBOPNI0KETeCEcU3rkfsqPSz9GDdtCvW02Lbn8qZ7Xo9kRqNm6MsWRJjNJSxdChHnw+le0k\nCSGa4Sym7tXnYjGYvbgTK78r4pDyCg7dr6LOMlPxNzd5QmTVihXFrFpVTI8e5lxonGo4XqTuIvKV\nNBC1ceGw4s47h7JkSSlKgVKazp2D3HLLV9AxnO3kCSEybNXqYm76y2EQ8RCLQTSmuOwH67jnkm9Q\n0h6Ql2IxzSOPhPjggyhKgccDgQDcckshPXvK1QMh8snmXQWMueUw1m0rRGvQwJEH7OSla+dSWBDL\ndvKEaLZQyMMddxzM0qWlgDkXKisLctQtn9G1RM6FhEjW6mqCSqneSqkHlFIfK6WqlVJaKVXuslwn\npdSjSqmtSqkqpdS7SqmDXZYrVErdrZTaqJSqsdZ7TEt8l5bwv/+Vs2RJKaGQl2DQS22tj+++K+Lh\nhw/MdtJEjpCYartiMbjtjuFUVPipqPFRFfRRG/by+PRevPpF12wnr01qDfH0wQdRPvwwSigEwSDU\n1MDOnXDXXUG01s1ZtRBp1xpiqjW77OFBLN/UjspaU0ZUB318uKQTk/7XL9tJExmQj/E0ZUo533xT\nSjAYPxfauLGIK/45ONtJEyIntboGImAAMAHYAcx2W0AppYBpwFjgSuAcwA/MUEr1Tlr8MeAy4Cbg\nNGAj8JZSalhGUt/C3ntvH0Ihb8K0aNTD/PmdqQ4m/vyx7dsJPfUUtbfcQujxx4lt2tSSSRXZIzHV\nRq1YWUJVlQ9I7CpUFfTxyNvJP5tIk5yPp7ffjhAM1p2+bZtm48aWbyBS4TC93n6X4bfcytA776Xz\nvPktngaR03I+pnKdrq0l/Oqr1P7lLwT/8Q+i334LQE3Iw7vzyghHE+uDtWEvT7wnZUQblXfxNGN6\nd8LhuudCb3xZRjAsXamFSNYabzF7X2vdHUAp9VPgRJdlzgBGAcdrrWdYy34MrAT+AFxlTTsEuBC4\nVGv9hDVtFrAQ+Iu1nlYt3MCBz1QITPfh2IYN1F5/PYRCEIkQ++YbIjNmELjpJrz7799CqRVZIjHV\nRoVCHrzRCG6H+qoaqRRlSM7HUyjk3giklCkCWpIKRzj8hlsoXr0GXzCIBsq+msuqcWfC2eNbNjEi\nV+V8TOUyXV1N7XXXobdtMwGuFNHPPsN/6aVEjvwB9TUJB8Ot8RqySEFexVPxmtXoiuFAYZ15WkMk\n6iHgj7Z8woTIYa3u6K+1TuWG6DOADfZBzfrcLkxr+JlJy4WB5xzLRYBngZOUUoG0JDqLDj98K15v\n8i7T7LtvFaXtInumhP79b3OfQcSaFo1CMEjoX/9qucSKrJCYarsG9t6MJ1z3/vp2VDGh47tZSFHb\n1xri6aijvBQU1J3u90OfPi3bcNj9o4/3NA6B6evmCwbp9+JL6J07WzQtIje1hpjKZeG330Zv3Rpv\n/dUaQiHCTzxBsaeag/tUQFIzkc8b4/TDN7d8YkXG5Vs8DXziUU7mdXwk14ViDOtXQftCaRwSIlmr\nayBK0WDga5fpC4E+Sqlix3IrtdbVLssVYLphtmoXXLCCjh1DBAKm4cfvj1JUFOUXv1icsFxs4UJT\naUiiV69Gu5xgirwjMdUKdVmzlAf8v6aIavyYk4P2VHIwC7hwxwNZTl1ey2o8nXSSn169FAGr6u7z\nmUGqr7wygMfTsg1E3T6ds6dxyCnm8xFdtKhF0yJaNSmj6hGdMwfc6nEeD7GVK/nXLxZSUhShqMCc\nKLcPROhWGuK2C5e2cEpFDmkz8dRpyWL+zC10ZQvtqAKgiGpKqOCRny/IcuqEyE2t8RazVHQGVrlM\n3269dgIqreV2NLBcZ7eVK6UuBy4H6FNW1px0ZlzHjmH+9rdP+eCD7nz7bSk9e1Zz/PEbKUketb+w\n0P3eAp8PvN6600W+yVhMOeOprEwGTk6ncPv2nOZ5jaF8xZNczBa68QPe4RReY3vJKbwnj3DNlhYr\no8rK+tSZHwgobr+9kE8/jTJvXpSyMsVxx/no2rXlrxmFSkuIeTx4YokXtRWgiovdPyREXS1URtWN\np1ynOnRwv40sFkO1b8/QfStZ/MAH/HtGL5asb88R++/kgqM3USw9K/JZmzmPigYK6VH9HXM4nOc5\nl885jIF8y/kFUyjv8zeSx2gUQrTdBqKM0lo/AjwCMKJ//5x/5EthYYwxYzYyZszGepfxnXQSkZdf\nTmwk8vvxHn00ytNWO5qJXOCMp/79B+R8PLUmVX37EuzShfKNq7hZ37pnerSgHWtO+VX2EiYyKjGm\nRrjGlM+nGDXKx6hR2a0GrDtxDL3em5lQ9mggGijAM1ieMCOyL5V4ymX+U04huHAhCSPTK4Xq1g3V\n24w33LUkzDVnrspOAkXeacnzqHVjTqTPm69RHKriUiZzKZOJFhSw7vgxmLG4hRDJ2uqZ/w5M63ay\nzo75qSy33WVem+QfNw7vyJFmEIp27aCgAM+gQRRMnJjtpIncIDHVGinF/Ouvp7ZHDyKB9oSLSoj6\nC1l63s1sH3JctlOXzySeLJX9yll0+U+JBgKE2xURKSwk2KUzX9xyI0p6r4rUSUzVwzt0KL5zzonX\n7wIB1D77EPjjH+UEWdSnzcTTsvMvYMvwEUT9fsLt2hH1F7Bt6CEsvfiSbCdNiJzVVnsQLcR9VP5B\nwBqtdaVjuXFKqXZJ988OAkLAsswmM3con4/AVVcR27oVvW4dqkcPPD16ZDtZIndITLVStd268en9\n91O4si8Fu7eya/+RRNp3zHay8p3Ek8PGE0azedT3KF3yLdGiQnbtPwA8HuqMKSpE/SSmGlBw1ln4\nx4whtmwZqqQE1a+fNA6JhrSZeNI+P/Ov/gOFmzfTfsM6qvfpSU13+/xGChkh3LTVHkSvAL2UUsfa\nE5RSJcDp1jzbNMAPnOtYzgecB7ytta47cmYb5ykrwztsmDQOiWQSU62ZUlTsN5xtw06UxqHcIPGU\nJFpYyPZhQ9k18ADTOCRE00hMNUIVF5v63X77SeOQaEybi6fabt3YNmy4o3FICFGfVtmDSCk13vp3\nhPV6slJqC7BFaz0Lc/D6GHhKKfV7TBfI6zAjkd1lr0dr/ZVS6jngfqWUH1gJXAH0Ay5qkS8jRA6Q\nmBIifSSehEgviSkh0kfiSQjRkFbZQAS8kPT+Iet1FjBaax1TSp0G3GPNK8Qc6I7TWq9N+uyPgduB\n24COwDxgrNb6y0wlXogcJDElRPpIPAmRXhJTQqSPxJMQol6tsoFIa91o31it9XbgUuuvoeVqgKut\nvxxzaiPzX2vW2qfib9bnRduRPzElROblVjztYu/LisbKICFaRm7FVO6Sep1IhcSTMZWzsp0EIXKS\n3OifRkvWt2PWwk7sqm6V7W5CiDZKa1izJsaiRVFqa1vdU5pFjlu/PsbChVGqqyVvifwTjWq+/TbK\n0qVRYjGJASHSJRbTLFsW5ZtvokQiEltCtBRpyUiDLbv9nHXHoXy9pgN+X4xQ2MP156zgwLOznTIh\nRL7bujXArZOG893mWjweiEbh4ov9jB0rV5pF8+zcqbnzziBr18bw+SAchvHjfYwbV5DtpAnRIr7+\nOsp99wWJRk1DfEEB/P73AQYO9GY7aUK0al8sL+GKu2qpqdEoZZ5d8OtfBxg2GcV+hAAAIABJREFU\nTGJLiEyTHkRpcN49hzB3ZQk1IS+7q/3Uhr3c+VI/5syJZDtpQog8pjXcOmk469a3JxiEmhoIheDp\np8MsWhTNdvJEK3fvvUFWrYoRCkF1tWkg+t//InzxheQt0fbt3m0aSCsrzbG1thZ274bbbw9Kbzoh\nmqE66GHsrSPYsUNTW2viq6oK7rknyPbtsWwnT4g2TxqImml3tY9Pl5YSjibuyqqgj1dflQYiIUT2\nrFlbzHebi4jFEo9PwSC8/no4S6kSrcnmzTHmzo2yeXNipXzLlhgrVsSIJrUFBYPw6quSt0Tb9+GH\nEbRLO5DW8Mkn6W8krazUzJsXZcWKGNptw0K0Ea/M6UY0VneYpFgMZs2ScyshMk1uMWum5d8VobV7\nO9vu3VKACyGyp6LCj1Lux6GdO1s4MaJVCYcVf/97LV99FcPvN72Dhg3z8JvfBPD7FZWV7LmtLNmu\nXVL2ibavokITCtWdHomYeek0dWqIF16I4Peb24S7dFHccEOAsjK5zivanh2VfoKRug1EkYjppSeE\nyCwpWZrJPAig7kGswBdl+HC5T1YIkT379dtNba37dYB9923hxIhW5dln92Pu3BjhcPz2sblzYzzz\njGkR6t3b/SE4Ph+MGCFln2j7hgzxEgjUne7zwZAh6atez5sX5cUXI3tiMRiETZs0kyYF07YNIXLJ\nkL67CUfcY2j//eXUVYhMkx5EGRDwR+lcHObMM4uznRQhRB77bnMRPp8m4nIlbseOLCRIZEEpe/O4\n+nffra7TOyIchunTI1xySQF+v+LHP/bz6KPhPcv5/dChg+L002UAdNH2HXSQh8GDPSxcGCNotdUE\nAqaBtH//9DWSvv56eM/6bbEYbN6sWbcuRu/eqZ4wN3YceG1vkidE2i1YXYLXo+vcZqaUudUyd0jM\niLZJGojSrF0gwu/OWMUvxq5ldoemV8qFECJdqqr8FBREibhciauqykKCRKuRfELqnK61RinF6NF+\nevb08OqrYbZt0xx6qJexY/0UF7v3LhKiLVFK8fvfB5g9O8qsWRGUguOP9/H976e3B119t6t5PLl2\nsixEeuyo9Ft3aCRSSuouQrQEaSBKo0J/lGvHreS6s1c2e12VlT7WrYvSuXOM9etn8d13q+nX72AO\nOOBwlGq48r1gwSL+/e9nWLduA6WlJYwbdxonnXRCo58TQrQtA/rvJhKJAncD/wGCwGB8vrs44ohD\nsps4kVXLln3FY49dx8qV8ygqKuG00y5n3Ljf4PGYk9uBAz0sXlz3aTEHHOBJKEsOOMDL1Vfnxi1l\nsViM+fO/ZtOmzZSX92XgwAFS7omM8noVo0f7GD06c9XpkSO9rFkTqdOjLxaDHj0qeeutF5k163lW\nr/4apWIMHz6c0aN/Ro8e7enZsyZj6RIiU8YM3cY9L5dTFUyMK68XBg+ue0zXWvPWW9P53/+msWvX\nbjp2LOXss0/npJNOaKkkC9GmSANRmhQVRNmnU5BfjF3brPVoDc88sx+vv94bn28NNTXj8Xi24fVG\n8Xi8lJcP4YYbnicQaOf6+SVLvuXOO+8nZNUkduzYydNPP091dQ1nn316s9ImhGhdCgujlHW+iA2b\nPndMXUAkcjpDh34MlGcpZSKb1q37lptuOpNIxJw8VlVt5/nn/86mTZv45S/vBuDSSwu48cZaIhEz\nMKjPZ/5+8pOCbCa9Xjt27OSmm25n9+4KotEoSnkoL+/DDTdcQ8BtoBghWokTT/Tz3ntRtm83g2Ir\nZW7nPOGE2Vx55WUEg7VAvCfRJ598waef3oTP9y69e0e49tr5dO7sMpq2EDlq5P67OHn4VqZ92SOh\nN2ssBpMmhfj1rxXDhsUvTEyd+hovvvgyoZAZI2/Hjp089tiTvP/+R/z5z9fh88nprhBNISN9NVPn\n4jDHDt7GLect5ZM7Pub1L8sYe+sITr51OB98ECEWa1r335kze/Dmm70Ih73U1FwDrCcWqyIcriUY\nrGLFirm88MLd9X7+2Wdf3NM4ZAsGQ0yd+hqRiDwaUoh8smXrtqTGIVuEf/7z2hZPj8gNjz9+H5FI\nYjmhdQ3vv/9fKiq2A9C3r4frry+gVy9FURH06qW47roCystzs9rw8MOPsWXLNmpqagmFwgSDQVas\nWMULL0zNdtKEqCMW03z0UYTbbqvl1ltref/9+uuL7dop7rqrkPPP9zN4sIdRo7xce22Y6dMvJxis\nwdk4ZETQegfh8HusXt2eSZOGZvz7CJFOSsG9lyxhyJDE3kLRqLnF7N57g2zdanq4RiIRXnrp1T2N\nQ07Llq3gjTfebZE0C9GW5GZNrxUp71bDOzd/wW9OW8P59xfyk8ce5L2VpzN92Z94+JH5/P3vIbRO\nvZFo2rQ+BIM+oAb4CIgmzA+Hg8ya9Vy9n1+3boPr9Fgsxq5d8mxIIfLJW+8sqXfe8uVzWjAlIpcs\nXfo1yWULgNYFLFlibpFetSrGX/8aYt06TU0NrFunmTQpxIoVibedfb14Bn/9+xn8/s+H8dQL17Fr\n9+aW+AoJQqEQCxYsIhZLTFs4HGbWrA9bPD0iv30+dxp/ufck/vCXw5ky7Taqq3fVWebBB0M8/HCI\n+fNjLFgQ41//CnHPPcF664uFhYrTTvNz882FXHVVgIqKGXg8DVXhq4BvicU8bNrUjjVr2qfnywnR\nAtZsLeSQa4bw5cI7of0x0O508L2G3RgajcLMmeait91r1I3WmunTZ7VUsoVoM6TPXZo8Pmsj7628\nDrxBUFHwfEOYaXz+1cssX34UAwakNkZDRYX9k9Qd+8EWjdbfE6hnzx7s3l1RZ7rHoygp6ZBSGoQQ\nbUXXeudoLbfd5CuvdyCwlLrlTIhAYF8AHnssRG1tfE40av4efzzEbbcVAvDOrH/xn+d/TzBUDcD6\nTUuY9fGT3H3LF3Qs6Z75L2IxPS/cT6zNGFxCtIznXv4zr759P8GQGUl3/cZvmPXx09x90xwKC82T\nbVesiPHZZ9GEMYWCQViwIMbixTEGDWq8vhiJhBu5+Nge6A+A16vZvVueLChaj+uf7sFOToSC9aCs\ne8x8X0DwFxC8gUgEduww+b+kpAMeT/1jzcndE0I0nTQQpcmt0/4Jqjo+QUWBasK+a1mwYHbKDUQH\nH7yDDz/sjtbtgcHAfJwVX6/XyxFHDKW+Ryued97ZTJr0t4TbzAKBAk47bSx+v1QQhMgn+/Y+CHP8\nSK48abyB/Wi5R7TKEx2zZxfJv/MRR4xjxox3MD1VbYV4PKdz4IFfADGWLh1N3XwDS5fG0FoTjgR5\n8oVr9zQOAUQiIaqqd/LKm/fyowl3ZeC7uCssDNCvXznLlq1ImG7KyxEtlg7R9il24sf9tsVdFbt5\n5c27CEfit7qEI7Xs2LWWmR/8ltPHnErYD18vKicaHUByJ/5gULNgwRIGDVrVaDqGDYsQjdY3rpAH\nKAFOAiASUey3XwXySG7RWrz+9Tvg2RhvHAJzjhV4AEI/ozDQlUMOMedVPp+P004by4svvlJnPV6v\nl1GjjmhgSxITQriRW8zSZOPuem7l8HxFhw6pP0Xl/PNX0q5dBK83BtyDKeTN1drCwgCdO3figgvO\nqffzgwcfxNVX/5J99ukBQHFxMeeeexbnnntWymkQQrQNodi3UASmkchuaNbgiVLQYUv2Eiay6qKL\nCujQ4THgIGtKMR7Pj7n00h9TUGB6FRUWuve8KSw0j/det2Gx6xPCItEQcxe+naGU1+8Xv/gp7du3\no6DADKJtl5cXXji+xdMi8tPSlcvw++tedw2FQnyx4Ks974s7hPH56vYS9xfE6NCh7jgqbkpKSpg4\n8UIKCvwut5odB7wMBAgEopx33gratZOedKL1iHnfBuXyBD4dwBv4nD59PIwYEb/wPmHCOMaOTXxi\nmd/vp2fPHpx1llygEqKppAdRMy3fuJERv/oVPo+HcMzttrASvve91B8B3K1bLffe+xnTpvVh0aJ9\nKCv7Hz16PEM4vIr+/ffjyCMP31MBrs/w4YcwfPghxGKxRu5RF81RUVFJRUUl3bt3xevNjcc8i7Zl\n83ff8cqUKXyzeDGdu3ThtHHjOHjYsJQ/P3BAAFUQRvtqIVQAMQX+CHijlPctzWDKRS4rKQlz8027\n+b8HL2P12gEUFe7k9DPWceKJ8fGDxoxZz5tv9k24DaagAMaMMdWGkg5lRKLuJ7OdSntkNP1uevfu\nyYMP3s3s2R+zYcPGlMtLIfbGgrlzeXXqVLZv3coBBx3EmePHU9qhpM44WAAepejSqfOe99878jsm\nPzbQZTnNqFGpj+H1gx8cx6BBA5k9+2NCoRAjRhxKnz6DeOutffn88yJKS7dy6qnrGDp0x959yRwW\njUb57rstFBe3l+ET2qDBvdoxZ7UHVFI8qSinjO3J+ecG8HrjFyiUUlx66Q8ZP/5MZs78gK1bt3Hg\ngQMZOXK4PMGsHpWVVezeXUG3bmWyj0QdkiOaqbKmhjU1NXgDEA4kHcx0Ecd87wqKi1PvQQTQuXOI\nSy5Z5phytPXXNNI4lBnV1TU8+OAjzJu3AI/Hi8/n48c/vpBjjhmV7aSJNmTzpk3c/Mc/Ultbi47F\n2LJ5MytXrODCSy5h9JgxKa2jT6/e9OzRnfUb10JhvKu2RxVwwdljM5V0keN2bN/GnTf+imBtLe0A\nquG15z14Yudx+vgJgOnNumXLfnz+eRS/H8JhGD7cwwUXmFuVyzrvy/79RvLN8o+JOhqKAgXtOP3E\nq7PwraB9+/aMHZtabAixt2ZNn87TTzyx51b+rVu38uVnn3HLHXfQuWMXNm3ZlNBQ5PP7OfX4k/e8\nb9c+wvU3fcnddwwjHPagAI9Hc/Uf5lFamloPIluvXj05/3xnr/IY48evZvz41c35ijnto48+5dFH\nnyQcDhOLRTn44MFceeXltG8vA3G3BRXV1Wxd/zHgJXGcPA/du/Xk4gu+59p7FUzPujPOOKUlktlq\n1dYGefjhx/j88y/xer14PB4uvvg8xowZne2kiRwiDURpUhCEqCdGNKAo8hcRjob5/vfO52c/vCnb\nSRNpdv/9D7Fw4WLC4QgQIRgM8sgj/6asrIxBg+peFRRib0ydMmVP45AtFAzy3FNPcdTo0Slf8SmK\ndjB1LI8HM6ZMDBUqwO8pzEi6Re575onHCdbWJowwpGMxpr3wHCeedgaBwkJ8Ps1vfxtg69YYGzdq\n9tlHUVaWeNHhd1c8xz0PTWDZqjn4vAXEYhEuGHcrw4ac2LJfSIgWorXm2SefTBjnUcdi1NbW8vKU\nKfz56hv464N3sf67DXg9pmfxzy++jP369EtYz4EH7eSRx2exbGkJOqYYcMAufD4NYRkrsiHffruM\nhx56LGH/z5+/kHvueZCbb742iykT6fLUe+9RU1lNkQ5TU6Qwo6HE8MY0v/nJ5Hobh0RqHnroUb74\nYi7hcMQ6j4HJk5+hrKwzw4YNzXLqRK6QBqI0UUC7GijxtuO/f7yefl2782GHH2U7WSLNtm/fwcKF\nS/YcVG2hUIiXX35NGohE2nyzaFFC45AtFo2ydcsWeuyzT6PrWL9hE2vWbIRQMXiioDREvcSUh1df\nfZOrrvp5JpIuctzCeXNdhp+GmI7xzeJFDD10+J5pZWUeysrc19OhuAt//sN0Nm9dxe6KLfTuOYjC\ngFzFF21XJBIh5vJIba013yxeTFnnMu676S42fLeR6ppq+vbqU+8DQrxezcADd2U6yW3KK6+8kdA4\nBOY3+fbbZWzevIVu3ep/cqdoHWbNn09NKEQB4A9rot4oSkP7QAkV2zfaD+cTe6GyspIvvvjK9Rzm\npZdelQYisYc0EKXZPh07MXK//bOdDJEhO3fuwufzEg7X7Qa+deu2LKRItFWdOndm29atdaZHYzE6\ndEhtzIXt23fi8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oTG8OGDa0gqBdSsTj1k7A3JDeMCrsQgUdcJecutgN279/Drr7+TkXGI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KEw5HKCubRTgc9n9cKeURi8V49dU3a6U999xthEK1z63C4Wreffd5PedSagvR8a7NbPny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Eiz4nxIiAXAtsDeGC7hKuppbmzIGDvyBX1YumHJI5zMTmWlrPDEeeLTsVxy3EkE09wQxFq6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gfRowEddRHMN1Dv3HWvtxIK3Kd36U71SZ6obb76bK90UtzDu1nnr5tBvg6q7W0qfqgUx1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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "printColorMap(forestClf, cleanedFeatureMatrix, cleanedResultVector)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let us also quickly take a look at the confusion matrix for the overall model. Because maybe we should not care about the confidence of the predictions, and just weight them lower." + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from sklearn import metrics\n", + "from matplotlib import cm" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def printConfusionMatrix(algo, X, y, title):\n", + " skf = cross_validation.StratifiedKFold(y, 5)\n", + " nClasses = np.count_nonzero(np.unique(y))\n", + " print(\"nClasses = %s\" % nClasses)\n", + " sumPCM = np.zeros([nClasses, nClasses])\n", + " for train, test in skf:\n", + " X_train, X_test, y_train, y_test = X[train], X[test], y[train], y[test]\n", + " print(\"Number of distinct classes in training set = %s, test set = %s\" % (np.unique(y[train]), np.unique(y[test])))\n", + " y_pred = algo.fit(X_train, y_train).predict(X_test)\n", + " # This has the raw number of entries (e.g. [610 12 1 0 32 1])\n", + " # Since the total number of entries for each mode is different, we want to convert this to a percentage\n", + " cmraw = metrics.confusion_matrix(y_test, y_pred)\n", + " # We do that by summing up the entries for each mode (e.g. 656)\n", + " sumArr = np.sum(cmraw, axis=1)\n", + " # and repeating it across the row (e.g. [656 656 656 656 656 656])\n", + " repeatedSumArr = np.repeat(sumArr, cmraw.shape[1]).reshape(cmraw.shape)\n", + " # And dividing the raw numbers by the sums to get percentages (e.g [92.98 1.82 0 4.87 0.15])\n", + " sumPCM = np.add(sumPCM, np.divide(cmraw.astype(float), repeatedSumArr))\n", + " \n", + " finalPCM = sumPCM / 5\n", + " logFinalPCM = np.log(finalPCM + 1)\n", + " np.set_printoptions(precision=0, suppress=True)\n", + " # np.set_printoptions(precision=4, suppress=False)\n", + " print(finalPCM * 100)\n", + "\n", + " oldSize = mpl.rcParams['font.size']\n", + " mpl.rcParams['font.size'] = 16\n", + " (fig, ax) = plt.subplots()\n", + " # First element is \"\" because of http://stackoverflow.com/questions/3529666/matplotlib-matshow-labels\n", + " ax.set_xticklabels([\"\",\"walk\", \"\", \"bus\", \"\", \"car\", \"\"])\n", + " ax.set_yticklabels([\"\",\"walk\", \"cycle\", \"bus\", \"train\", \"car\", \"air\"])\n", + " cax = ax.matshow(logFinalPCM, cmap=cm.gray)\n", + " ax.set_title(title, color='green', weight='bold', size=16, y=1.1)\n", + " \n", + " fig.colorbar(cax)\n", + " ax.set_ylabel('True label', size=\"large\")\n", + " ax.set_xlabel('Predicted label', size=\"large\")\n", + " fig.tight_layout()\n", + " plt.show()\n", + " return (finalPCM, fig)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Model selection" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "modelCMList = []\n", + "saveDir = \"/tmp/ml_results/\"" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import os\n", + "os.makedirs(saveDir, exist_ok=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 95. 1. 0. 0. 3. 0.]\n", + " [ 9. 80. 3. 0. 9. 0.]\n", + " [ 8. 12. 15. 5. 60. 0.]\n", + " [ 5. 1. 5. 27. 62. 0.]\n", + " [ 3. 2. 4. 4. 86. 0.]\n", + " [ 25. 7. 0. 7. 13. 49.]]\n" + ] + }, + { + "data": { + "image/png": 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Rc89t7ZDlXXbJ6yit69OjhCi8N6f+92kLgiBoiK5urlejrrnzklbDfff1B+YA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\nYzNh+6WwUtuIauV2+46ltPb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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(array([[ 1., 0., 0., 0., 0., 0.],\n", + " [ 0., 1., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.]]),\n", + " )" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "printConfusionMatrix(forestClf, genericCleanedFM, cleanedResultVector, \"Generic features, random forest\")" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 95. 1. 1. 0. 3. 0.]\n", + " [ 10. 82. 1. 0. 7. 0.]\n", + " [ 10. 5. 29. 3. 54. 0.]\n", + " [ 5. 3. 4. 41. 48. 0.]\n", + " [ 4. 4. 4. 3. 85. 0.]\n", + " [ 17. 3. 7. 3. 23. 47.]]\n" + ] + }, + { + "data": { + "image/png": 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haRAEQSkaNdhe0hqSrpc0S9L7yb/xmtXKI+lXkiyt/1aWaizRR4ByDpc3AR6u\nIs8gCHo4jbBE00obY/AlfvbHJwONBO6VtFGlo4dS389JwNuVll2NEv0lcJ+k44DzzeyztYskLQ4c\ngy8//LUq8gyCoAfTwOr8wfgCl0PM7CUASU8CLwKHAudVmM8lwNXAECrUj6XWnS/kRX4CcBpwlKSJ\nuLZeERiafselk/lphQJXjaThQAuwWDhpDoKuT4N653cBHs4pUAAzmyxpPO4LuawSlfQD4EvA94Eb\nKi24lKb9SYljKwE7FQgfBmxLOyrRIAi6Fw2yRDcEbi4QPokKRgtJ6oevFPpLM5shVd61U0qJrl9x\nLkEQBDXSICXaH5hZIHwG0K+C9GcDLwCjqy241Lrzz1ebWQezvqQLgc3xqaeXAcPNbIGkA/B169dK\nS6QCbU0BZqZM2M9xq3sQ8BHwMnCqmd3YMacRBD2XKjzbD0hNiDlGmdmoRsggaRvgh8CXrAaNXvO6\n852Am4A/AqfjzqB/DSwgb235UkjaBzgXGAHcDywJbIR/1YIg6AAq1FvTzWxoieMzKWxxFrNQs1wK\n/AF4TdLyKawP0Dvtz02OlwpStRKVtBiwKbAKsEShOGbWEX7KLjOzM9L/uyUtCxwj6YIq8tgSeNLM\nRmTCbm+YhEEQlKVB1flJeLtoPhtQfnz7+mkr1A80EzgaKKpXqnVAcghwKsUtNeHjszpCieaXcS3w\nY6AaJ5sTgMMlXYQ3Sj+Yln4uSroGhwD06dOVDfkgaD4NXKjuFuAcSYNzvjskDQK2Bn5VJu12BcIu\nAHoDRwIvFTj+GRXPWJK0O/B7fFjTSbjCvB1oBe5J+zcCh1eaZ528VWR/tSryuAKf8785vjbUjDTL\nYVCxBGY2ysyGmtnQ3r17V1FUEASFaNAaS5fhjpFulrSrpF1ww+hVvLoOgKSBkuZLOjlT/tj8DXgP\nmJX2XytVcDXTPo/GFejmZnZ6CptgZiPMbAdgH+DbQEd1SK1UZP91vIMIYPG8OJ/P7phzqZltBgzA\nZzpsBlzXYFmDIChCI5RompG0Pd7DfiU+YH4ysL2Zzc5EFW5hVqP7SlJNfXRj4Lo8gT4zxczsz5J+\niA+EH9sY8UqyJ3BGZn9vYDbwFL6gHnjV/gUASX2AHYplZmYzgeskbY7PcAiCoANolCs8M5uGL11U\nKs4UKvDvYWbDKi23GiXaB5ie2Z/Lor1hT1J6kH4jOTi54JuA987/GB/iNEvSBHyo0tkpzjy8mWGh\njjBJo/DJDQOaAAAX1klEQVQVSh/CrewvAPsBd3fQOQRBj6aneXF6HVg1sz8Z+EpenHVxhdUR7Iq7\n3bsF2Bd3NnAKQJoOuiveHjIa+B3wDxYdSDse+DJwcTp+InAVXq0PgqAD6OrrzldjiT6EtxfmuBX4\npaTz0/+t8fmrtzVOvEUxs+G0jQUt1KuWizcJn4aaz/BMnD8Bf2qYcEEQVE1P8mx/FbCmpIFpbfkz\n8I6knwM/w9sZ3gSObbiUQRB0Wzq7pVmOipWomf0Dr/Lm9mdJGgp8F1gbmAbcYGazGi5lEATdkq5Q\nXS9HXaPFzewj3EINgiCoiZ5UnQ+CIGg43dYSLeKUuRLMzMKfaBAEZWngtM+mUatT5lIY4ZQ5CIIK\n6baWKOGUOQiCDqDbKtEu4JQ5CIJuQHeuzgdlmD9/PjNmzGha+fPmddTksML87W9/a1rZxx9/fNPK\nBnjvvfeaWn53occPcQqCIKiXUKJBEAR1ENX5IAiCOujqlmjDHJMGQRBUSyUenCpVspLWkHS9pFmS\n3k+rVKxZQbqBkm6WNFXSXEnTJY2T9K1Kyg0lGgRBU1mwYEHZrRySlgLGAOvhriz3w11z3itp6TLJ\nl8F9JZ8EfAs4CPcz/HdJe5QrO6rzQRA0lQZV5w8GBgNDzOwlAElPAi/iK1WcV6L8Sbji/AxJf8d9\nJh8I3FCq4KotUUnfknSFpEckPZ0J/4Kkn0lapdo8gyDouTSoOr8L8HBOgaZ8J+OO13etQab5wCxg\nfrm4FVuiaZmNK/G1jAR8DCyWifI+cC6wFAuvfRQEQVCQBs6d3xBf3TOfScD3Kskg6bhe+KKVh+DL\nBf28XLpqV/v8PvAHYEXyFKWZ/Qd4ANi5ijyDIOjhNMgS7Q/MLBA+g0XXgivGWcAnuHP5XwB7m9k9\n5RJVo0QPBCaa2SFmNh13NJLPi8BaVeQZBEEPp0IlOkDSxMx2SDuIcgG+bty3gTuAaySVNQqr6Vha\nG1/wrRQzyFvbvRok7QYMNrOijcA15jsaGGZmgxqZbxAE9VFFdX66mQ0tcXwmhS3OYhZqIVleA15L\nu7dJGgucQ5l146qxRD8ElisTZyAVClyE3YD/rSN9MU4Bdm+HfIMgqJMGVecn4e2i+WwAPFOjaBOB\ndcpFqkaJTgC+lcZjLYKkFfExVuOryLMmJC1RPlYbZvaymT3WXvIEQVA7DVKitwBbSBqcC5A0CF+F\n+JZqZUqdTF8FXi4Xtxoleh6wCnC7pC9mC5O0GXA7sDRwfnXifpbPaHyQ7GqSLG1TJA1L//eQdJmk\nd4C3Upp1JF0paXKaafCKpEsk9cvPW9KUzP6glOehkkZIelPSe5JulbR6LfIHQVAbjRhsD1wGTAFu\nlrSrpF3w3vpXgUtzkdLspPmSTs6EDZd0oaS9JG0raS/gTnyJ+JZyBVez2ufdkn4BnAk8AXyaDs1N\n+RhwjJnVaomeAqyAN+zuksLm0daEcBHe2Lsf0DeFrQq8ARwDvIt3ap2AK/QtKyjzeOBB4Ef4iINz\n8YX3htV4DkEQVEGjXOGZ2RxJ2+NG3JX4MMx7gKPMbHYmqoDeLGxA/hs4Ch++uRzwH1zHbVOJPqtq\nxpKZnSvpHuBwXEv3x8eHPgL8zswerSa/vLxfTlbmx2b2cC5c0rD09xEz+3FemvuA+zJxxwMvAfdL\n2rSCKvwUM/tBJv0KwNmSVjWzNwolSL2ChwD06hWzZoOgXhrlgMTMpgHfKRNnCq5Is2G3UEOVP0fV\n0z7N7HGSEulgbswPkLQ4cCzwQ7xTq2/m8BCgnBK9PW//qfS7Jm7hLoKZjQJGAfTp06dru58Jgk5A\nuMLrON4sEHY6cCQwAq+WfwCsjs917Vsgfj75bulzruIrSRsEQQPo6q7wqpn2uWelcc3sL7WJUzrb\nAmF7A1eY2chcgKRl2qHsIAjagZ62PMi1FFZkWZTi1KpE5wFLVhF/KXyaVpYDayw7CIIm0JOq84cV\nCV8O+BLwXXxIwV11yPMM0F/SYfhA14/KxL8T2F/SU3iH0h7AVnWUHwRBB9NjLFEzu7TUcUnb4krt\ngjrk+T9gC+A0YHlgKnBAifhH4tbvqWn/dtxJyiN1yBAEQQfSY5RoOcxsXHJkeiqwTY15zMGVYD4q\nEEZyhLJ3ufhmdkDe/pRCeZrZ2GJlBUHQeBroCq9pNLp3/hVgxwbnGQRBNyYs0YXZmrZhQkEQBGXp\nMUo0zY8vlsdq+Lz3LYCrGyBXEAQ9gJ5WnX+Y0kOchPeot4cruyAIuik9xhLFXecXOtsFuA/RCcB9\n1tWvSBAEHUpXVxnVDHH6VXsKEgRBz6SrV+crdkMk6UFJp7enMEEQ9Cwqccjc2S3Vany5bUT5aZ9B\nEARV0SCnzE2jmjbRp/HF6oIMzfxK9unTlZxwNZYzzzyzqeW/8sorTS3/pz/9aVPLbySd3dIsRzWW\n6DnArpI2by9hgiDoeTSqOi9pDUnXS5ol6X1JN0has4J0X5H0B0kvSvpQ0jRJV0uqaPn3akyZXsAY\n4D5J1wKP4msdLXKG7eQKLwiCbkajxommBTTH4JN99sf10kjgXkkbpSnlxdgLXyn0Qtwx+6rAr4GJ\nkjYxs1dLlV2LKzzh6xztx6IKtF5XeEEQ9DAaVJ0/GBgMDDGzlwAkPQm8CByKL7RZjLPM7NhsQFpq\naHLK9+SCqRKNcIUXBEFQMw1SorsAD+cUaMp3clKGu1JCiZrZ2wXCpqY131YrV3DDXOEFQRBUSwOn\nfW6I+zPOZxLwvWozk7Q+vgLws+XiluxYSuu4/6xaAYIgCCqlQR1L/fGZk/nMAPpVI4+kPsDvgXeA\nP5SLX84SHYQ7Rw6CIGgXKlSSAyRNzOyPSivvtge/xVfI2MnMCinmhei5Aw2DIGg6VVTnp5vZ0BLH\nZ1LY4ixmoRZE0hn4kvD7m9ndlaQJJRoEQVNpUMfSJLxdNJ8N8LXbyiLpROA44Egzu7LSgisZbN+1\npxMEQdCpaVCb6C3AFpIG5wIkDcIdxd9SLnHq+xkJnGhmv61G/kos0aMlVbMMsZlZTA8NgqAiGtQ7\nfxlwBHCzpJNw4+8U4FXgs5FFkgYCLwMjzGxECtsbX2DzTmCMpC0y+b5vZiUt2UqU6PL0wM4lSQIW\nM7OPmy1LEHRXGuWlyczmSNoeOB+4Ep/4cw9wlJnNzkQV0JuFa+E7pvAdWXSNuHHAsFJlV1KdH25m\nvarZKsizoUjaWNKNkt6VNFfS85KOT8d2kHS7pDfTvNinJR0jqXdeHlMkXSXpR5KeAz4GdurocwmC\nnkaj5s6b2TQz+46ZLWtmnzOz3dLKvtk4U8xMZjY8E3ZACiu0DStXbpfvWEprP40FXgKOBl4D1sVd\n94FPBRsLXAzMAYYCw4EVgHxH09sBmwCtwNvAlHYUPQgCur5T5i6vRHHvUu8CW5jZhylsTO6gmf0+\n9z9V0e8HFgeOlXSCmWXvYD/gy2b2n/YXOwgC6Pqu8Lq0Ek2eW7YGzs4o0Pw4q+CW5464d5bsOa8I\nZBXmw+UUqKRD8HFkuE4OgqBWuoLn+nJ0aSWKW4698Cr8IkjqhQ9vWBVXpM8Bc4HdgBOBvnlJ3ixX\nYJolMQqgT58+XfvuB0EnoFt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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(array([[ 1., 0., 0., 0., 0., 0.],\n", + " [ 0., 1., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.]]),\n", + " )" + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,Spatial_indices], cleanedResultVector, \"Spatial Features, random forest\")" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 95. 1. 1. 0. 3. 0.]\n", + " [ 10. 82. 1. 0. 8. 0.]\n", + " [ 10. 4. 33. 3. 49. 0.]\n", + " [ 5. 1. 5. 42. 47. 0.]\n", + " [ 5. 3. 5. 3. 85. 0.]\n", + " [ 17. 3. 0. 10. 10. 60.]]\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix, cleanedResultVector, \"All features, random forest\")\n", + "fig.savefig(saveDir+\"cm_all_random_forest.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Adding start and end points does improve the accuracy of the bus and train. Train trips in particular, are significantly improved." + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 95. 2. 0. 0. 3. 0.]\n", + " [ 15. 50. 5. 0. 29. 0.]\n", + " [ 12. 34. 10. 3. 40. 0.]\n", + " [ 6. 6. 3. 16. 69. 0.]\n", + " [ 5. 15. 3. 4. 73. 0.]\n", + " [ 32. 0. 0. 4. 27. 37.]]\n" + ] + }, + { + "data": { + "image/png": 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rYGYTzGyYmQ1bbrnlamgqCIJSNGmPpQvwwEjXSRojaWfcMHoRd9cBkLS+pEWS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\nlmNpA7Id2D5z/sN0FMqUJZR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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(array([[ 1., 0., 0., 0., 0., 0.],\n", + " [ 0., 1., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.]]),\n", + " )" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "knnClf = neighbors.KNeighborsClassifier()\n", + "printConfusionMatrix(knnClf, genericCleanedFM, cleanedResultVector, \"Generic features, k-nn\")" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 95. 2. 0. 0. 2. 0.]\n", + " [ 15. 51. 5. 0. 28. 0.]\n", + " [ 11. 34. 11. 2. 42. 0.]\n", + " [ 6. 7. 2. 15. 70. 0.]\n", + " [ 5. 15. 3. 4. 73. 0.]\n", + " [ 32. 0. 0. 4. 27. 37.]]\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "knnClf = neighbors.KNeighborsClassifier()\n", + "currCM, fig = printConfusionMatrix(knnClf, cleanedFeatureMatrix, cleanedResultVector, \"All features, k-nn\")\n", + "fig.savefig(saveDir+\"cm_all_k_nn.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "knn does significantly worse, primarily because of bus trips. I suspect this is because different people make the same trip using different modes. Time for per-user trips?" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 93. 5. 1. 0. 1. 0.]\n", + " [ 26. 24. 18. 0. 32. 0.]\n", + " [ 17. 40. 19. 0. 25. 0.]\n", + " [ 8. 34. 19. 0. 39. 0.]\n", + " [ 6. 35. 19. 0. 39. 0.]\n", + " [ 20. 24. 17. 0. 24. 15.]]\n" + ] + }, + { + "data": { + "image/png": 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QSjQIgqAOQok2CUnHVc4V7Uf73avt7kgo0ebR7B9ytN9z22/2vXcrQokGQRDUQaxYqoOB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\nEu6uAyBpE9zbHFX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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "svmClf = svm.LinearSVC()\n", + "currCM, fig = printConfusionMatrix(svmClf, cleanedFeatureMatrix, cleanedResultVector, \"All features, Linear SVM\")\n", + "fig.savefig(saveDir+\"cm_all_linear_svm.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For parametric models, it is particularly import to tune the parameters correctly. We use the grid_search function from sklearn to find the correct parameters for SVC." + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/sklearn/grid_search.py:43: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. This module will be removed in 0.20.\n", + " DeprecationWarning)\n" + ] + } + ], + "source": [ + "from sklearn.grid_search import GridSearchCV\n", + "from sklearn.metrics import classification_report" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "First, we do some coarse tuning on the parameters." + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/sklearn/utils/class_weight.py:65: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n", + " \" 0.19\", DeprecationWarning)\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/sklearn/utils/class_weight.py:65: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n", + " \" 0.19\", DeprecationWarning)\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/sklearn/utils/class_weight.py:65: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 'auto' will be removed in 0.19\n", + " \" 0.19\", DeprecationWarning)\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/sklearn/utils/class_weight.py:65: DeprecationWarning: The class_weight='auto' heuristic is deprecated in 0.17 in favor of a new heuristic class_weight='balanced'. 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'auto' will be removed in 0.19\n", + " \" 0.19\", DeprecationWarning)\n" + ] + }, + { + "data": { + "text/plain": [ + "LinearSVC(C=100, class_weight=None, dual=False, fit_intercept=True,\n", + " intercept_scaling=1, loss='squared_hinge', max_iter=1000,\n", + " multi_class='ovr', penalty='l2', random_state=None, tol=0.0001,\n", + " verbose=0)" + ] + }, + "execution_count": 73, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "tuned_parameters = [{'C': [0.01, 0.1, 1, 10, 100, 1000],\n", + " 'dual': [True, False],\n", + " 'class_weight' : [None, 'auto']}]\n", + "baseClf = svm.LinearSVC()\n", + "clf = GridSearchCV(baseClf, tuned_parameters, cv=5)\n", + "clf.fit(cleanedFeatureMatrix, cleanedResultVector)\n", + "clf.get_params\n", + "clf.best_estimator_" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Then, we do some fine tuning around the result of the coarse parameter tuning." + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "LinearSVC(C=90, class_weight=None, dual=True, fit_intercept=True,\n", + " intercept_scaling=1, loss='squared_hinge', max_iter=1000,\n", + " multi_class='ovr', penalty='l2', random_state=None, tol=0.0001,\n", + " verbose=0)\n", + "0.7028876419871356\n" + ] + } + ], + "source": [ + "tuned_parameters = [{'C': list(range(75, 125, 5))}]\n", + "baseClf = svm.LinearSVC()\n", + "clf = GridSearchCV(baseClf, tuned_parameters, cv=5)\n", + "clf.fit(cleanedFeatureMatrix, cleanedResultVector)\n", + "print(clf.get_params)\n", + "print(clf.best_estimator_)\n", + "print(clf.best_score_)" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "LinearSVC(C=100, class_weight=None, dual=False, fit_intercept=True,\n", + " intercept_scaling=1, loss='squared_hinge', max_iter=1000,\n", + " multi_class='ovr', penalty='l2', random_state=None, tol=0.0001,\n", + " verbose=0)\n", + "0.7269741343916792\n" + ] + } + ], + "source": [ + "tuned_parameters = [{'C': list(range(55, 125, 5))}]\n", + "baseClf = svm.LinearSVC(dual=False)\n", + "clf = GridSearchCV(baseClf, tuned_parameters, cv=5)\n", + "clf.fit(cleanedFeatureMatrix, cleanedResultVector)\n", + "print(clf.get_params)\n", + "print(clf.best_estimator_)\n", + "print(clf.best_score_)" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 91. 1. 0. 0. 7. 0.]\n", + " [ 48. 6. 0. 0. 45. 0.]\n", + " [ 4. 0. 0. 0. 96. 0.]\n", + " [ 7. 0. 0. 0. 93. 0.]\n", + " [ 1. 0. 0. 0. 99. 0.]\n", + " [ 42. 0. 3. 0. 27. 28.]]\n" + ] + }, + { + "data": { + "image/png": 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/+RcBq6X0a4EHy5TvS8f+Pftm0kf517JU3kKU9Y1w5/gpwFrt/gyK+wycWpR+Be5ovwYe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\n73sJgt5GK1yc0oqkEcDTwFX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DIAia4P8B5hPaLBSmJg8AAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "tunedSvmClf = svm.LinearSVC(C=80, dual=False)\n", + "currCM, fig = printConfusionMatrix(tunedSvmClf, cleanedFeatureMatrix, cleanedResultVector, \"All features, SVM(C=80,dual=F)\")\n", + "fig.savefig(saveDir+\"cm_all_tuned_svm.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/sklearn/lda.py:6: DeprecationWarning: lda.LDA has been moved to discriminant_analysis.LinearDiscriminantAnalysis in 0.17 and will be removed in 0.19\n", + " \"in 0.17 and will be removed in 0.19\", DeprecationWarning)\n" + ] + } + ], + "source": [ + "from sklearn.kernel_approximation import Nystroem, AdditiveChi2Sampler, RBFSampler, SkewedChi2Sampler\n", + "from sklearn.linear_model import SGDClassifier\n", + "from sklearn.lda import LDA\n", + "from sklearn import preprocessing" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 77. 4. 1. 0. 17. 0.]\n", + " [ 18. 58. 2. 0. 22. 0.]\n", + " [ 31. 14. 5. 1. 48. 0.]\n", + " [ 38. 4. 2. 1. 56. 0.]\n", + " [ 24. 5. 3. 1. 67. 0.]\n", + " [ 51. 15. 0. 0. 34. 0.]]\n" + ] + }, + { 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g6L7UMbJ9wyi173yhKPLjgd8CR0uagO+ItyIwOL2OxTeM+mn9Rf1MrhFAC7BE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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "rbf_feature = RBFSampler()\n", + "cleanedFeatureMatrix_features = rbf_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "sgdClf = SGDClassifier()\n", + "currCM, fig = printConfusionMatrix(sgdClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SGD w RBF kernel\")\n", + "fig.savefig(saveDir+\"cm_all_rbf_kernel_sgd.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 86. 3. 1. 2. 9. 0.]\n", + " [ 23. 54. 3. 1. 18. 0.]\n", + " [ 22. 13. 4. 3. 57. 1.]\n", + " [ 26. 4. 5. 5. 60. 0.]\n", + " [ 20. 6. 2. 2. 70. 0.]\n", + " [ 68. 7. 3. 7. 15. 0.]]\n" + ] + }, + { + "data": { + "image/png": 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KZGFK/EB8/n0l3scf4KdQ3zTuqqQH+G50zbQ7RXn9IE3D3hOfOfgX/PqchVvVd6X0vzZJ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\nu8NT/hFF6WuVyLsirrwnlqnD8Oi22WN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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(array([[ 1., 0., 0., 0., 0., 0.],\n", + " [ 0., 1., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 1., 0., 0., 0., 0., 0.]]),\n", + " )" + ] + }, + "execution_count": 79, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "rbf_feature = RBFSampler(gamma=1)\n", + "cleanedFeatureMatrix_features = rbf_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "sgdClf = SGDClassifier()\n", + "printConfusionMatrix(sgdClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SGD w RBF kernel (gamma=1)\")" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 79. 5. 1. 1. 14. 0.]\n", + " [ 25. 55. 3. 1. 16. 0.]\n", + " [ 35. 11. 12. 2. 41. 0.]\n", + " [ 38. 3. 2. 4. 51. 2.]\n", + " [ 22. 4. 4. 2. 68. 0.]\n", + " [ 46. 13. 0. 3. 37. 0.]]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/sklearn/discriminant_analysis.py:455: UserWarning: The priors do not sum to 1. Renormalizing\n", + " UserWarning)\n" + ] + }, + { + "data": { + "image/png": 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zG+qUqxIuNbOfp893S1oeOFbSeVXUsQ3wbC4kVuLOhkkYBEFZepUSlXQYcDrF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\nY+37OLUh/3EAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "rbf_feature = RBFSampler()\n", + "cleanedFeatureMatrix_features = rbf_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "ldaClf = LDA()\n", + "currCM, fig = printConfusionMatrix(ldaClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, LDA w RBF kernel\")\n", + "fig.savefig(saveDir+\"cm_all_rbf_kernel_lda.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 83. 4. 0. 0. 13. 0.]\n", + " [ 25. 61. 0. 0. 14. 0.]\n", + " [ 44. 6. 1. 0. 49. 0.]\n", + " [ 38. 5. 1. 0. 56. 0.]\n", + " [ 25. 3. 0. 0. 71. 0.]\n", + " [ 55. 11. 0. 0. 34. 0.]]\n" + ] + }, + { + "data": { + "image/png": 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ZwJcqFU6B3X8KfM/M5kqqVGQZNa1YMrNpkjbGo77vgEeSX4CvO7+qTACRbkn/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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "rbf_feature = RBFSampler()\n", + "cleanedFeatureMatrix_features = rbf_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "linearSVMClf = svm.LinearSVC()\n", + "currCM, fig = printConfusionMatrix(linearSVMClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SVM w RBF kernel\")\n", + "fig.savefig(saveDir+\"cm_all_rbf_kernel_svm.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 92. 2. 1. 0. 5. 0.]\n", + " [ 7. 77. 2. 1. 14. 0.]\n", + " [ 5. 14. 13. 2. 66. 0.]\n", + " [ 5. 5. 2. 8. 79. 1.]\n", + " [ 2. 5. 5. 4. 83. 2.]\n", + " [ 25. 7. 13. 3. 3. 48.]]\n" + ] + }, + { + "data": { + "image/png": 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AAElFTkSuQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nys_feature = Nystroem(kernel='polynomial')\n", + "cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "sgdClf = SGDClassifier()\n", + "currCM, fig = printConfusionMatrix(sgdClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SGD w poly kernel\")\n", + "fig.savefig(saveDir+\"cm_all_poly_kernel_sgd.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/sklearn/discriminant_analysis.py:455: UserWarning: The priors do not sum to 1. Renormalizing\n", + " UserWarning)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[ 92. 1. 1. 0. 5. 0.]\n", + " [ 4. 81. 5. 2. 8. 0.]\n", + " [ 2. 5. 35. 7. 50. 0.]\n", + " [ 3. 1. 5. 32. 59. 0.]\n", + " [ 0. 1. 8. 7. 84. 0.]\n", + " [ 20. 19. 0. 10. 0. 51.]]\n" + ] + }, + { + "data": { + "image/png": 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SBgBH4KP2P8QFbRAEQS6t0ERTaM4JeEzgA/DZQ6cCEyVtUq+7MSmB36Njr7Vc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\nCJoghGgQBEEThBANgiBoghCiQRAETfD/ap6dAA1xzFYAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nys_feature = Nystroem(kernel='polynomial')\n", + "cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "ldaClf = LDA()\n", + "currCM, fig = printConfusionMatrix(ldaClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, LDA w poly kernel\")\n", + "fig.savefig(saveDir+\"cm_all_poly_kernel_lda.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 92. 1. 0. 0. 6. 0.]\n", + " [ 6. 80. 2. 0. 12. 0.]\n", + " [ 2. 5. 11. 2. 81. 0.]\n", + " [ 4. 2. 2. 8. 84. 0.]\n", + " [ 1. 1. 2. 1. 96. 0.]\n", + " [ 24. 10. 3. 10. 11. 42.]]\n" + ] + }, + { + "data": { + "image/png": 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OrQLMAabl3E0vCILgHXrCwFEt6l07vx6+J9LuJWUXSboGOKZMmLogCIKK9Bkh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\nQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nys_feature = Nystroem(kernel='polynomial')\n", + "cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "svmClf = svm.LinearSVC()\n", + "currCM, fig = printConfusionMatrix(svmClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SVM w poly kernel\")\n", + "fig.savefig(saveDir+\"cm_all_poly_kernel_svm.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 94. 1. 0. 0. 4. 0.]\n", + " [ 12. 69. 0. 0. 18. 0.]\n", + " [ 4. 21. 3. 2. 69. 1.]\n", + " [ 6. 3. 1. 9. 80. 1.]\n", + " [ 2. 6. 1. 2. 88. 1.]\n", + " [ 41. 7. 0. 0. 3. 49.]]\n" + ] + }, + { + "data": { + "image/png": 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0tqTnJf1R0hrlW6na/gBJ10t6WdLGtUt0GetLmpDO72VJYyVfjy9pv/RbDM0WkDQmuS6y\naT+Q9ISkeZJmSposqUPBJLoaSRtLukbSG6n/T0r6STr2OUk3pd/mbUmPSzpS0lIldUyTdJmkb0n6\nNz49aKdWnE+Qjxhs6hgP43PtRtE+4X0UPvk4uyJjFD6H7g48Is27wHH4yO1gfK7k3ZLWM6saCON9\nJA3E5wsOArYxs6rr0LuYv+JRjk4GPo8Hh15EHbsJSPoGPs93LD4hfnl8FLwrlhc3hKQt8Dmwz+Dz\naV/AoxptlLIMS8fPw+drjsB/m1VZMt7qDvhcyzZ8Hu+0Tux60CAhSDuAmS2SdAd+sRe1ru3xCcbf\nl/QBM5uTjj9oZrPxVU6HFetIWsjd+OqdL+DBR6oiaQi+qmYOsK1ZrhU/XcmFZnZK+nyrpBWBIyWd\nVa1QCVsDj5rZ2ExawwGGu4jT8elOW5m9H3j7/QUAZnZ+8bMk4Q+KZYCjJB1jZosyda0CfMLMXun8\nbgeNEqZ9xxkPbC1pOVxzWBkP5juf9uhDO5AJkCHpIEmPSJqDa6rFaD15QvVtgK+QeR7YoRsKUfCV\nNFkux5fIfryOOiYBm0g6R9JnJA2oWaIbkPq5LfCHjBAtzTM4uXeexa2T94AT8WunNB7BfSFEew4h\nSDvOBHwt9Ta4wHzEzF7FTf0dJG2I3xzjwX2ouEn3DzyoxhZ4sBFYPFpUJT6FRxP6bdJ2uyOl8yOL\n3+vxA1+CB63eEte+Z0i6utS32g1ZBb+fyoaeS1bLdXgchhNxt8/mwEkpS+k18DJBjyFM+47zGL4O\nexQeZadowo3HQ3E9j2sdd6f0PYHbzOz9iDqSspHla3EBHmzlUkkLzOwvjXW/U/gQvnY6+x18/Xwx\nJFvp6PNioeXMJzZfAFwgaRU86M0ZeMCJLZvd4SYyE/cHV3pofAT3ie5jZpcVEyVVipwWE7x7EKGR\ndpB0w0/Eo+1vx+KCdFM8WPQDGTNvAEtGSN+f/JiZHYprtZdL+mqtAi2gNJbjnrg/9zHawwy+b+ZL\nWpoqEcnNbKaZXYG7DOpxD3Q56X++C9hbKhuPteiieP8akNSf9g0jgx5MaKSNMQGPCLUQHzgAH9Gf\nTRqIyuT9G/BjScfgIfdG4SEI68LMDpe0EPijpH5J0HQXDkgm7CR81P47wBgzmyVpEvAf4LSUZz4e\nRWqxvbwkjcN/v3vx0eqP4bus3tplZ9FxjsKjdd0r6QzczB+G+9CPxB8mJ6X/7z18ZD/oBYQgbYzi\nQNJkM3sLwMwWSrodDxmXjcQ+Fh9UOAL3h92OC5usKZwLMztS0gLgD0mYNrLJXTMZjW/E9lM8LNqJ\npIhHZrZA0mj8wXMxHo/yLDycWSFTx924pr4P7sp4Cd+9IJunW2JmkyRti//X5+APiWeBi8zsXUm7\n4jtYXoKf/+/wAccLW9TloEnEWvsgCIIGCR9pEARBg4QgDYIgaJAQpEEQBA0SgjQIgqBBQpAGQRA0\nSAjSIAiCBglB2iIkHRjtR/t9re3eSgjS1tHqizna77vtt/rcex0hSIMgCBokVjY1wKBBg2zo0KEd\nKvv666+z6qqrNtT+Qw891OGyZobHFu44ffnaWWqppWpnqsKiRYvo16/jeszChQsbar9RsrvcNsKO\nO+5o06dPr5nvwQcfvMXMdmxGm51BrLVvgKFDhzJ58uSWtb/MMq3dD23Bgr678/IHPvCBlrY/a9as\nlrbfLKZPn86kSZNq5uvXr9+gLuhOhwlBGgRBS+kNlk0I0iAIWkoI0iAIggYwMxYtWlQ7YzcnBGkQ\nBC0lNNIgCIIGCUEaBEHQAGHaB0EQNIHQSIMgCBqkNwjSPrNEVNIYSVaSZpJObFWfgiDwVV61Xt2d\n0EiDIGgZZhYaaRAEQaMUhWm1Vx4krSXpKkmzJL0l6WpJQ/L2Q9L6kq6UNF3SPElPSvpBnrLdSpBK\n+kQytz+ZSTus1ASXtG5K20nSqpIukPSUpLclPS/pj5LW6ED7AyRdL+llSRs367yCIKhMM0x7SQOA\n8cB6wL7APsC6wARJK+QoPwK4H1gW+A7wReAMIFd0mu5m2j8MvAmMAu5KaaOAeemdTNoC4A5gdeBd\n4DjgVWAwcCRwt6T1zOydPA1LGgjcAAwCtjGzqQ2fTRAEVWmiaX8AMAwYbmbPAEh6FHga+C5wZqWC\nkvoBlwC3mdmXM4cm5G28W2mkZrYIF447wPsnuD3wa2BzScWQOzsAD5rZbDN70swOM7M/m9ntwJXA\nbsDawBfytJvU/7uB/sC2IUSDoOtokmm/C3BfUYimeqfi9/XoGmVHAutTRdjWolsJ0sR4YGtJywGb\nACsDpwLzge1Snh3IPC0kHSTpEUlzcE31uXRoeI72NgDuAZ4HdjCz16tllnSgpMmSJr/+etWsQRDk\noEmj9hsCj5dJn4Lf49UouhKXk3SfpPckvSbpbEnL52m8OwrSCbifYhtcYD5iZq/ipv4OkjYEVsMF\nLpIOA84D/oFrolsAW6W6lsvR3qeANYDfmtmcWpnNbJyZjTCzEY0GZg6CoGka6UBgZpn0GcAqNcqu\nnt6vAG4FPosrb98B/pin8e7mIwV4DJiO+0E3JQnM9L4Hrjm+i6vsAHvivo0jixVIWqeO9i4AVgIu\nlbTAzP7SWPeDIMhLHUtEB0nKRlEfZ2bjmtSNokJ5mZkdnz5PlLQUcIqk9c3siWoVdDtBamYmaSL+\nVFgf1zbBBenJwFvAA2b2dkofkNKy7F9nk4dKWgBcLmkvM7uywycQBEFd5NQ4p5vZiCrHZ1Je86yk\nqWZ5I73/vST9VuAU3MXYswRpYgJwLrAQuDOlPQzMxs39sZm8fwN+LOkY4AFck9293gbN7HBJC4E/\nSupnZlc00P8gCHLSpFH7KbiftJQNgH/lKNsQ3dFHCu0DSZPN7C0AM1sI3F5yHFyoXgAcAVwDbAR8\nviONJvfAmcAfJH29I3UEQZCfomnfhMGm64CtJA0rJkgaCmybjlXjZnwwu1RuFDfbq7mpVOwi2gAj\nRoyw2Pyub7Liiiu2tP1Wb37XrF1EN9poI7vxxhtr5hsyZMiD1Uz7NOn+EXzO+XGAAScAHwQ2Kg4k\nS1ob+A8w1szGZsoXgJ/ig0zjgRFAAbjCzPar1b/uatoHQdBHaIYyZ2ZzJY0CfgFcCgi4DTi8ZDaO\n8NVKpdb4WNx1eDBwFPAycBoujGsSgjQIgpbSrOhOZvYc8JUaeabhwrQ03XC3Xocm5YcgDYKgZfSW\n6E8hSIMgaCkhSIMgCBqkJwRurkUI0iAIWkpopEEQBA0QPtIgCIImEKZ9EARBg4RG2seZMmUKG25Y\nbnlv13DPPfe0rG2AzTffvGVtS01ZWNNhNttss5a2P2FC7uDt3Z4QpEEQBA1QRxi9bk0I0iAIWkpo\npEEQBA0SgjQIgqABwrQPgiBoAqGRBkEQNEgI0iAIggYJ0z4IgqABessS0e66Z1MQBH2EJu1rj6S1\nJF0laZaktyRdLWlIzrJW4bVJnvJ9RiOVNAYoNGuvmSAImkMzTHtJA/C9luYD++J7Np0ITJC0kZnN\nzVHNxfhGmlmeytN+nxGkQRB0T5pk2h8ADAOGm9kzAJIeBZ4Gvku+LUReNLP7OtJ4mPZBELSMPGZ9\nTkG7C3BfUYimuqcCdwOjO6n779MtBKmkjSVdI+kNSfMkPSnpJ5LOkfSqpP4l+T8oabakUzJpq0o6\nT9Lzkuan90slLVul3aVTO/9OZV6SdIak5TrzfIMgaKdJ+9pvCDxeJn0KsEHOrhyU5MDbksZL2i7v\nObTctJe0BTAReAY4AngBWBfYCDgXOBT4MvDnTLG9gBVI/gxJqwD3AANxv8ijwGr4k2gZ3G9SjsuA\nLwE/T+XXx7dfHUqN3QiDIGgOTTLtBwIzy6TPAFbJUf4y4AbgJWBt4IfAeEmfNbOJtQq3XJACpwNv\nAFuZ2dspbXzxoKTbcR9HVpB+F7g1qe7gAngYMMLMHs7k+1OlRtPT5mvAvmZ2SUr+h6QZwGWSNjGz\nfzZwXkEQ5CCnIB0kaXLm+zgzG9fEPuyT+XqnpGtxDfcEoKZm2lJBmkbatgVOywjRUs4DLpe0rpk9\nLWlzYFNgt0yezwGTSoRoLXYE3gWukpT9HW5N758ClhCkkg4EDgTo379/6eEgCOqgjrX2081sRJXj\nMymveVbSVGv1a7akG4Fv5cnfah/pKqkPL1TJcw3wCq6FAnwPV7+vz+T5nxp1lGM13OyfC7yXeb2W\nqXMJzGycmY0wsxFLLbVUnU0GQVBKkwabpuB+0lI2AP7V1A6XoaJGKummDtZpZrZTzrwzgUXAGlUq\ne0/Sb4CDJZ0K7AmcYWYLMtmmV6ujAm8A71BZbX+pzvqCIOgATfKRXgecLmmYmf0XQNJQ3OI9ut7K\nJK0I7Aw8kCd/NdN+x3obT+T+VczsbUl3AXtLGmtm8ypkvQA4BrgSWBa4sOT4rcBxkjY2s0dyNv83\n4MfASmZ2W94+B0HQPJoYRu9CfGD6WknH4XLoBOB5MpPsJa0N/AcYa2ZjU9pRwEeBCcCr+GDTUcCH\ngW/kabyaIF2+3jPpIEcBtwP3SjoDN9GHAZuY2WEAZvaipOvw0fvrzez5kjp+gY/k/0PSicBjwCB8\n1P57Zja7tFEzmyjpT7iP9Ez8ybMIH7H/IvBjM8u1qiEIgo7TDI3UzOZKGoXLgksBAbcBh5vZnExW\nAUuxuFvzSVy27A6sBLyFzz/9tpk1ppGaWaUpQ03FzCZJ2hYYC5yDa5zPAheVZL0SP9nSJVyY2Zup\njhNxNf5/8CfLeHxAqRJ7A4fhDuVj8WlS04BbUvkgCDqZZkV/MrPnqDFt0cym4cI0m3Y9i4+51E2H\nR+3TiPsKZvZ6Ix0ASKPtX6qRbWdcwN5coY7XSKPpFY6PAcaUpC0CfpleQRC0gD4X/SmtKDpV0nPA\nbODlzLHNU7SVXNFS6mhzK0nfw+d8npmEXxAEvYAmLhFtKbk1UkkDgbuA9fCpBm/jK5CKTAE+A0yl\nzPzLBrgXmAP8Hp9TGgRBL6I3BHauRyMdgwvRfczsf4HLswfThPqJwKeb1blUr8zsg2b27ZIpT0EQ\n9AJ6g0ZajyAdDdxgZn9I38ud3TRgzUY7FQRB36E3CNJ6Bps+TJW164l38WAiQRAENWniPNKWUo8g\nfR2fqFqN9YEXO96dIAj6Gj1B46xFPab9eGC0pGHlDkraDPg8PgczCIIgF73BtK9HkJ4ILATukXQo\nsBZ4ODpJP8IF7Wzg1Kb3MgiCXknRtG9CYOeWktu0N7OnJO2M+0nPxgebhI/UC4/QtIeZPdsJ/QyC\noJfSEzTOWtS1ssnMbpe0Dr4Maws81t9b+Dr1K6sEHemVvPfee7z4Yutcwscff3zL2gZYfvmuCsew\nJK3WUn7+85+3tP1tttmmZW0vWNDcWYh9TpDC+2vw/5heQRAEDdHqh2Iz6NBae0kr4EFUVwJmAVMs\n377RQRAE79NTBpNqUZcglbQWvsfSriVlF0i6BvhhmRB3QRAEFelTgjRNe7ob+BC+gulePNTch4Ct\ngT2A7SVtW4xQHQRBUIu+ZtqfigvNQ4Hzs1GYJPUDDsJH838OfLWZnQyCoPfSGzTSeuaRfhr4q5md\nVxrKzswWmdm5eHDUzzazg0EQ9F6aGUZP0lqSrpI0S9JbKaznkHr7JOloSZa2QcpFPYK0H7V345tC\nSfTpIAiCajRjQn4KND8ej1C3L7APHuZzQhocz0VyYR5H+27CuajHtH8AqBW0eRPgvno6EARB36ZJ\npv0B+F5vw83sGQBJjwJP41u5n5mznl8DfwCGU4d8rEcj/RE+mPRjSctkD0haRtJP8K2Nf1xHnUEQ\n9GGaaNrvAtxXFKKp7qn4APnoPBVI2gvYDPhJvedRbV/7ctHoJwE/Aw6XNBlXf1cDRqT32/EnwyH1\ndiQvksYABaB/BHoOgp5Pk0btNwSuLZM+hRyD35JWwXcg/ZGZzZDq81BWU12/V+XYh4CdyqSPBLan\nEwVpEAS9i5wa56CkvBUZZ2bjMt8HAjPLlJsBrJKj/tOAp4CL83SmlGqCdP2OVBgEQVAPOQXpdDMb\n0RntS9oO+CawmXXQYVttX/snO9qxLmJ9SWcDW+LLVC8ExpjZIkn7ARcB66R9rIF2t4CZKZP2A1z7\nHgq8A/yx0j+TAAAaCElEQVQHOMnMruma0wiCvksTI+TPpLzmWUlTzXIB8FvgBUkrp7SlgaXS93kp\nxkhFOryvfTfgr8DvgJPxgNI/BRZRsnd9NSR9AzgDGAvcCSwPbIT/+EEQdAFNGrWfgvtJS9mA2tM2\n10+vcu7MmcARwFnVKqhbkErqD2wKDAaWLZfHzP5cb70d4EIzOyV9vlXSisCRkqqecAlbA4+a2dhM\n2k1N62EQBDVpkiC9Djhd0rDiEnVJQ4FtgaNrlN2hTNpZwFLAYcAzZY4vRr1BSw4ETqKyxiY84HNX\nCNLSNi4HvgN8vI46JgEHSzoHH/G7J20rXZH0GxyYPtfRVBAEpTTRtL8QX75+raTjcDl0AvA8broD\nIGlt3H03tqhAmdnE0sokvQksXe5YOXLPI5X0ZeB8fMrTcbjQvAloA25L368BDs5bZ4O8WuH7GnXU\ncQkeI2BLfK+pGWlZ2dBKBcxsnJmNMLMR/frVMw03CIJyNGMeaQrjOQofeb8Un1Q/FRhlZnMyWYVr\nmk29eevRSI/AheiWZjZH0knApKJUl/R14PfAOc3sYBU+BPy35Dv4LqZrps+LLRwA/if7JY3QXQBc\nkOaRfQ73mV6BC9cgCDqZZgUtMbPn8N07quWZRo5l7GY2sp6265HKGwPXlUj3pTIN/wnXTAv1dKAB\n9ij5vicwB3gMKO4b9b6ZL2lpXFCWxcxmmtkVuMugHvdAEAQN0Kc2v0t5p2e+z2PJ6QaPUn0ifzM5\nIIXvm4SP2n8Hn/40S9Ik3A9yWsozH3c5LDY4JmkcvvPpvbi2/TE82MGtXXQOQdCn6S0R8uvRSF8E\nVs98nwpsXpJnXVxodQWj8ZB91wF749tFnwCQlo6Oxh3NFwPnAn9nyVULdwOfAM5Lx48FLsOjxwRB\n0AX0hn3t69FI78V3Di1yPfAjSb9In7fFAwfc0LzuLYmZjaF9rmi5aQvFfFPwJauljMnk+T3u1w2C\noEX0BNO9FvUI0suAIZLWTnvXnwJ8CfgB8H3cgfsycFTTexkEQa+lJ2ictcgtSM3s77j5W/w+S9II\nYHfgI8BzwNVmNqvpvQyCoFfSU0z3WjS0RNTM3sE11SAIgg7R10z7IAiCptOrNdIKgZ3zYGYW8UiD\nIKhJE5eItpSOBnauhhGBnYMgyEmv1kiJwM5BEHQBvVqQ9oDAzkEQ9AJ6u2kf1EASyyxTGhel67jz\nzjtb1jbA/PldtYhtSYYMGdKytgEGDx7c0vZ7gxYHMf0pCIKgKYQgDYIgaJDeYNpHZOIgCFpKs4KW\nSFpL0lWSZkl6KwVpr+kDkrS2pGslPStpnqTpkm6X9MW85xCCNAiClpFHiOYRpJIGAOOB9fDobfvg\n0egmSFqhRvEP4CFCjwO+CHwbD695o6Td8pxHmPZBELSUJpn2BwDDgOFm9gyApEeBp4HvAmdWKpgi\nxX07mybpRjxU6P7A1bUaD400CIKW0iTTfhfgvqIQTfVOxWMOj+5AnxYAs4AFefLXLUglfVHSJZIe\nkPR4Jv1jkr4vqbXzQoIg6FE0SZBuCDxeJn0Kvrd9TST1k7S0pA9LOh7fMeNXecrmNu3Tlh2X4nsj\nCXgX6J/J8ha+cdwAPFZpEARBVZq41n4gMLNM+gyW3BKpEqcCR6bPc4A9zey2PAXr0UiPAL4O/BZY\njRJhaWavAHcBO9dRZxAEfZycGukgSZMzrwM7oStn4dsnfQm4GfijpFzyrJ7Bpv2ByWZ2IICkcvr2\n08BOddQZBEEfJ6fpPt3MRlQ5PpPymmclTbVcP14AXkhfb5A0ETidHNsn1aORfgS4o0aeGZTsHV8P\nknaV9H8dLV+l3oslTWt2vUEQNEbRtG/CdsxTcD9pKRsA/+pg9yYDH82TsR5B+jawUo08a5NT+ldg\nV6DpghTfXfTLnVBvEAQN0qTBpuuArSQNKyZIGopvynldvX1KY0KfxLd1r0k9pv0k4IuSBpjZ22Ua\nXg2fzPr3JUo2GUnLmlnuiBlmluvHCIKg62nSWvsLgUOBayUdh8dFPgHfkv2CYiZJa+PCcayZjU1p\nY3AXwN3AK8CH8XmlWwB75Wm8Ho30TGAwcJOkj2c61k/SFsBNwArAL+qo830kXYyvSFhDkqXXNEkj\n0+fdJF0o6XXg1VTmo5IulTQ1Le36r6RfS1qltO6saS9paKrzu5LGSnpZ0puSrpe0Zkf6HwRBx2iG\naW9mc4FRwFP47KI/4BPqR5nZnExWAUuxuOx7CPg4cA5wKz56/w6wnZldnucc6tlF9FZJPwR+DjwC\nLEyH5qV6DDjSzO7OW2cJJwCr4qNmu6S0+bS7E87BR9L2AZZLaasDL+FTFt4A1gGOwYX61jna/Alw\nD/AtfCbCGfhmfiM7eA5BENRBM8PomdlzwFdq5JmGC9Ns2nV0wPzPUtcSUTM7Q9JtwMG42jsQnz/6\nAHCumT3Y0Y6Y2X+Stvmumd1XTJc0Mn18wMy+U1LmDjIDYJLuBp4B7pS0qZk9XKPZaWb2vuouaVXg\nNEmrm9lL5QqkaRcHAvTrFwvDgqBR+mQYPTP7J0mQdDHXlCZIWgY4CvgmPtC1XObwcKCWIL2p5Ptj\n6X0IrukugZmNA8YB9O/fv+dfAUHQYnpDGL2eFLTk5TJpJwOHAWNxE302sCYeZGC5MvlLmVHyvTiA\nladsEARNoE9ppJL2yJvXzP7cse5Ur7ZM2p7AJWZ2YjFB0gc6oe0gCDqBvrjVyOWUF2ZZlPJ0VJDO\nB5avI/8A4L2StP072HYQBC2gr5n2B1VIXwnYDNgduBa4pYH+/AsYKOkgfFXBOzXy/w3YV9Jj+CDT\nbsA2DbQfBEEX06c0UjO7oNpxSdvjgu2sBvrzG2Ar4GfAysCzwH5V8h+Ga8Enpe834YFVHmigD0EQ\ndCF9SpDWwsxuT1GlTwK262Adc3FBWIrKpGFm03E/adX8ZrZfyfdp5eo0s4mV2gqCoPk0MYxeS2n2\nqP1/gR2bXGcQBL2Y0EiXZFvapxAFQRDUpE8J0rSevlIda+Dr5LfC17gGQRDUpC+a9vdRffqT8JH2\nzgiDFwRBL6VPaaR4RJRyZ7wIj0E6CbjDesOvEgRBl9EbREY905+O7syOBEHQN+kNpn3u8EWS7pF0\ncmd2JgiCvkWe6Pg9QWOtJw7cRtReIhoEQVAXTdqzqaXU4yN9HN8AL0gsXLiQ2bNnt6z9FVdcsWVt\nA7z99hI7znQZr7zySsvaBlh55ZVb2n5volkap6S18B06PosPfv8DODwFfK5WbnPge8Cn8BlI04E7\ngePMbGqetuvRSE8HRkvaso4yQRAEVWmGaS9pADAeWA+firkPsC4wQdIKNYp/Dd+B9Gx837mj8fgh\nk5Nwrkk9Gmm/1NE7JF0OPIjvnbTEWXZSGL0gCHoZTZxHegAwDBhuZs8ASHoUeBr4Lr7nXCVONbOj\nsglpt42pqd7jazXekTB6wqX9PiwpRBsNoxcEQR+jSab9LsB9RSGa6p2aBOJoqghSM3utTNqzaeuj\nNfI03owwekEQBB2mSYJ0QzyMZylTgK/WW5mk9fENMZ/Ik79pYfSCIAjqpYmm/UB8YVApM4BVyqRX\nRNLSwPnA68Bv85SpOtiU9on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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nys_feature = Nystroem(kernel='sigmoid')\n", + "cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "sgdClf = SGDClassifier()\n", + "currCM, fig = printConfusionMatrix(sgdClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SGD w sigmoid kernel\")\n", + "fig.savefig(saveDir+\"cm_all_sigmoid_kernel_sgd.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/sklearn/discriminant_analysis.py:455: UserWarning: The priors do not sum to 1. Renormalizing\n", + " UserWarning)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[ 92. 2. 1. 0. 5. 0.]\n", + " [ 5. 82. 6. 0. 7. 0.]\n", + " [ 2. 9. 35. 5. 49. 0.]\n", + " [ 3. 1. 4. 31. 61. 0.]\n", + " [ 1. 2. 8. 7. 83. 0.]\n", + " [ 13. 14. 0. 10. 3. 59.]]\n" + ] + }, + { + "data": { + "image/png": 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EPDwwSBAEQVV6+jzRYl4H1q6SZwPgP413JwiC3kZX1zSrUY85Pw7YTdKgUgcl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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nys_feature = Nystroem(kernel='sigmoid')\n", + "cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "ldaClf = LDA()\n", + "currCM, fig = printConfusionMatrix(ldaClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, LDA w sigmoid kernel\")\n", + "fig.savefig(saveDir+\"cm_all_sigmoid_kernel_lda.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 93. 1. 0. 0. 5. 0.]\n", + " [ 8. 79. 2. 0. 11. 0.]\n", + " [ 2. 9. 8. 0. 80. 0.]\n", + " [ 4. 2. 1. 5. 88. 0.]\n", + " [ 1. 1. 1. 0. 97. 0.]\n", + " [ 17. 18. 7. 0. 10. 49.]]\n" + ] + }, + { + "data": { + "image/png": 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w9pz6i9MWBEHQFD3dXK9FQ3Pn08JPmwOrAAuAmWnaVRAEQW56Q8dRLeoSopLW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\n7fVCFPcu9QIw2syKfukmFw+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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nys_feature = Nystroem(kernel='sigmoid')\n", + "cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "svmClf = svm.LinearSVC()\n", + "currCM, fig = printConfusionMatrix(svmClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SVM w poly kernel\")\n", + "fig.savefig(saveDir+\"cm_all_sigmoid_kernel_svm.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# nys_feature = Nystroem(kernel='chi2')\n", + "# cleanedFeatureMatrix_features = nys_feature.fit_transform(preprocessing.scale(cleanedFeatureMatrix))\n", + "# sgdClf = SGDClassifier()\n", + "# printConfusionMatrix(sgdClf, cleanedFeatureMatrix_features, cleanedResultVector, \"All features, SGD w sigmoid kernel\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Only for transport trips" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As we can see, the prediction rate is best for walk and bike, which are the ones for which we get the most data from moves. It may be a mistake to use the same model for both types of trips because moves will do a good job for walk/bike and a horrible job for transport, because we don't allow users to specify 'transport' in the output.\n", + "\n", + "These also have zero carbon footprint. Let us see how well we do on the motorized trips alone." + ] + }, + { + "cell_type": "code", + "execution_count": 89, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "3280\n" + ] + } + ], + "source": [ + "transportTrips = cleanedFeatureMatrix[:,2] == 4\n", + "print(np.count_nonzero(transportTrips))" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 32. 8. 7. 5. 47. 1.]\n", + " [ 11. 12. 20. 0. 57. 0.]\n", + " [ 4. 7. 21. 3. 64. 0.]\n", + " [ 3. 1. 3. 23. 69. 0.]\n", + " [ 3. 2. 6. 3. 86. 0.]\n", + " [ 5. 0. 0. 0. 28. 67.]]\n" + ] + }, + { + "data": { + "image/png": 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CKAZBENRBeJi2FiEUgyAI6iSEYusQQjEIgqBOwnzaOoRQDIIgqJPQFFuHEIpB\nEAR1EGOKrUUIxSAIgjoJ82nrEEIxCIKgTkJTbB1CKAadeOutt7j11lub1v6KK67YtLYBBg0a1LS2\nb7jhhqa1DbDOOus0tf3584vXwF9yaIRQlLQecBYeOEB46LgjzOyFLgt62XId2NrMHq67c21ECMUg\nCII6aMTap5IG4FFz3gP2AwwYC0yUtIWZzamimkvxsHFZnqqrY21ICMUgCII6aYCmeCAwGNjYzJ4B\nkPQo8DRwMHBmFXW8bGb31duRdifiKQZBENRJA+IpjgTuKwjEVOdzeODxxYIGBD1HCMUgCII6KJhP\nu/pUwebA4yXSpwCbVdmVQyW9J+kdSRMkbV/tPgQdhFAMgiCokwZoiqsAs0qkzwQGVlH+SuAw4HPA\nQcCHgAmShle3B0GBGFMMgiCokyoE36qSJmf+jzOzcQ1sf9/M37skXYdrnicBoTHWQAjFIAiCOqnC\nRDrDzIZ0sX0WpTXCchpkl5jZ25JuBL5da9l2J4RiEARBHTRombcp+LhiMZsBT9RbeVA9MaYYBEFQ\nJw0YUxwPDJU0uJAgaRAwLG2rCUkrAl8G7q+1bLsTQnEJRtLoLlayCIKgl2iA9+lFwFTgOkmjJI0E\nrgNeJDMhX9IGkhZIOjGTdrSkCyR9XdJwSfvhUznWBI5v4G62BWE+DYIgqJN6zadmNkfSTvgyb1fg\ny7zdji/zNjuTVUB/Ois0TwK7A3sCKwFv4ULxO2YWmmKNhFAMgiCog0aFjkprnH6lQp6puGDMpl0P\nXF93BwIgzKc9hqQtJV0r6XVJcyU9Keknks6VNF3S0kX5PyjpbUmnZtJWk/RrSS+mSbkvSrpC0ge6\naHep1M6/U5lXJJ0hadme3N8gaGcaYD4N+gihKfYAkrYBJgHPAEcCLwEbAVsA5wHfx80dv88U+yaw\nPGn8QNJA4O+4S/ZY4FFgdXzJp2XwhYNLcSWwK/DzVH5TfK7SICq8hQZB0D0idFTrEEKxZzgdeB0Y\nambvpLQJhY2S7sAX+c0KxYOBW9N6h+DCdDAwxMweyuT7XblG07JOXwf2M7PLU/JtkmYCV0raKsLI\nBEHjCaHYOoT5tMGkEDDDgKsyArGYXwMjJG2UynwK2JrOYV++ADxQJBArsTMwD/hjMqMuJWkpoBAg\ncYcyfT5I0mRJkxcuXFhDc0EQNGjt06CPEEKx8QzEj+tLXeS5Fvgvrh0CHAK8QufB8g9VqKMUq+Om\n1TnA/MzqzCrdAAAgAElEQVTn1Uydi2Fm48xsiJkN6d+/f41NBkHQgHmKQR+hrcynkm7qZlEzs12q\nzDsLWASUDWNuZvMl/QY4TNJpwF7AGWa2IJNtRld1lOF14F3Kr3X4So31BUFQBSH4Woe2Eoq4ebE7\nVH3Fm9k7ku4G9pE0xszmlsl6IXAc8AfgA/jk3Sy3AidI2tLMHqmy+b8CxwArmdnt1fY5CILuUzCf\nBq1BuwnF5XqpnaOBO4B7JZ2Bm0EHA1uZ2eEAZvaypPG4F+r1ZvZiUR1n4R6pt0kaCzwGrIp7nx5i\nZm8XN2pmkyT9Dh9TPBNf4mkR7nn6JeAYM3uq4XsbBG1OaIqtQ1sJRTMrN42h0e08IGkYMAY4F9cE\nnwcuKcr6B1woXliUjpm9keoYCxyLjwdOx71Y53XR/D7A4fjq+MfjUzemArek8kEQNJjQFFuHthKK\nlUieo8ub2Wv11pW8RnetkO3LuLC8uUwdr+IBQ8u1MRoYXZS2CPhl+gRB0AuEptg6tL33aVpJ5jRJ\nLwBvA9My2z4l6c+Stmpwm0MlHYLPKTwzCbIgCJZAKnmehsBcsmhrTVHSKsDdwCZ4PLN38JVnCkwB\nPgc8BzRy0vu9wGzgMnzOYhAESzBhPm0d2l1THI0LxH3N7OPA1dmNafL9JOCzjWzUzGRmHzSz7xRN\nwwiCYAkkNMXWod2F4ijgBjO7Kv0vdfVOBdbttR4FQbDEEUKxdWh3obgm8ESFPPPwhbqDIAgWI5Z5\nay3aekwReA3YoEKeTYGXe6EvQRAsoYQ22Dq0u6Y4ARglaXCpjZI+AXwRn+MXBEFQkjCftg7tLhTH\nAguBv0v6PrAeeAgmST/GhebbwGnN62IQBH2ZMJ+2Fm0tFNOSZ1/Gl0I7BzgAEO5xeio+RWNXM3u+\nWX0MgqDv0whNUdJ6kv4o6U1Jb6U50uvX2hdJx0qytAZzUCPtPqaImd0haUM8Kv02eKT7t/B1Q//Q\nxYLeLcn8+fN55ZXmBdMYMGBA09oG+MhHPtK0tldYYYWmtQ3woQ+VjCwWVEG9JtK0mtYEfFnG/XBP\n+LHARElbmNmcKusZDJxAR7i4oEbaXijC+2ui/jZ9giAIaqIBJtID8aABG5vZMwCSHgWexuOunlll\nPecDVwEbE8/3btHW5tMskpaXtI2kz6fvmIYRBEFFGrTM20jgvoJATPU+B9yDz6euiKRvAp8AftKN\n3QgSbS8Ukx3/GmAmvvzaX9P3TElXS1qvqR0MgqDP0wChuDnweIn0KcBmlQpLGoiHm/uxmc2sqfNB\nJ9pavU7293uANfCVa+7FwyutAWwHfA3YUdIwM/tPs/oZBEHfpgrz6aqSJmf+jzOzcZn/qwCzSpSb\nCQysogu/AJ4CLq0ib9AFbS0U8akWawDfBy7IRquQ1A84FPdK/Tnw1ab0MAiCPk8V2uAMMxvSE21L\n2h74FvAJi0mRddPuQvGzwF/MbLFIFUlAnifp88Dne71nQRAsETRogv4sSmuE5TTILBcCFwMvSVo5\npS0F9E//5/ZWgPVWoN3HFPtRee3TKfjcxSAIgpI0YPL+FHxcsZjNqPyM2hQ4BBeehc8wYGj6fWi1\n+xGEpng/UCmA8FbAfb3QlyAIllAaoCmOB06XNLjgvyBpEC7cjq1QdkSJtLOB/sDhwDMltgdlaHeh\n+GPgTknHAGeZ2bzCBknLAEcB2wM7NKl/QRD0cRpkPr0I9224TtIJ+OT9k4AXcfMoAJI2AJ4FxpjZ\nmNT+pOLKJL0BLFVqW9A1bSUUJZWKcv8A8DPgiOQd9iqwOjAkfd+BT6z9Xg/2azSQA5aOoMNBsORR\n7+R9M5sjaSd8WsUV+JDN7cARZjY7k1W4BtjuQ189RlsJRdzuXo41gF1KpA8HdqQHhWIQBEs2jXD6\nNLMX8OUmu8ozlSp8HMxseN0dalPaTShu2uwOBEHQesRMiNahrYSimT3Z7D5UYFNJ5wDbAm/i4wyj\nzWyRpP2BS4AN09si0GF6NTNl0n6Ia8WDgHfxMYiTzeza3tmNIGgfCqGjgtagrYTiEsBfgP8DTsGD\nG/8UD2s1utoKJO0NnAGMAe4ClgO2wOc7BUHQA4Sm2DqEUAQkLQ1sDawFfKBUHjP7fS905SIzOzX9\nvlXSisBRks6uoY7tgEcLnmmJmxrWwyAIFiOEYuvQ9kJR0kHAyZTXpIS7R/eGUCxu42rgu8DHaqjj\nAeAwSecC1wF/N7N3uiqQjsFBAP36hVNbENRCmE9bi7Z+AkraHbgAn4ZxAi4AbwLyuDu0gGuBw3qp\nS9PL/F+nhjoux1ew2Ba4BY/28ec0EbgkZjbOzIaY2RApFu8JglppQJSMoI/Q1kIROBIXiNua2Skp\n7QEzG2NmXwD2BnYFestBZ40y/1/GHWYAlinK0ylcujkXmtk2wKp4FO9tgGsa3NcgCBIhFFuHdheK\nWwLjiybH9i/8MLPf4Rpjrpf687Wi/3sBs4HHgOdT2vumVElLAV8oV5mZzTKza3CzbC0m2CAIaqAB\na58GfYR2H1NcCpiR+T+XxVeqf5SuJ/03kgNTyKoHcO/T7+JTMt6U9AA+teIXKc97uFm3k2OQpHHA\n23hsyFeBjwL7Arf20j4EQVsR2mBr0e6a4svA2pn/zwGfKsqzES6AeoNReJiq8cA+wFh8/UPS8m+j\n8LUQLwXOA/7G4kFF7wE+Cfw6bT8euBI3owZB0AOE+bR1aHdN8V58vK3A9cCPJZ2Vfg8DRgI39GQn\nzGw0HXMRS614X8g3BV92rpjRmTyXAZc1rHNBEFQkTKStQ7sLxSuB9SVtYGbPA6fijjU/BH6Ae59O\nA45uXheDIOjrhDbYOrS1UDSzv+EmxsL/NyUNAfYEPgy8APzZzN5sUheDIOjjhIm0tWhroVgKM3sX\n1yCDIAiqIsynrUMIxSAIgjoJTbF1aCuhWCbIcDWYmUU8xSAIFiOWeWst2koo0v35hkYEGQ6CoAyh\nKbYO7SYUI8hwEAQNpxFCUdJ6wFn4XGUBtwFHmNkLFcptAJwDbAWsDswBpgA/N7OIkFMjbSUUl4Ag\nw0EQLIHUaz6VNACYgC8Ush9unRoLTJS0hZnN6aL4CvjKXCcALwErAgcCN0r6ipn9ua7OtRltJRSD\nypgZCxYsaFr706ZNa1rbALfddlvT2v7Sl77UtLYBVlhhhaa238wILfVoeg2aknEgMBjY2MyeAZD0\nKPA0cDBwZhftTwG+k02TdCO+QtcBQAjFGmj3Zd6CIAjqpgHLvI0E7isIxFTnc/iyjaO60Z8FwJtA\n895wl1BCKAZBENRJA6JkbA48XiJ9CrBZNRVI6idpKUlrSjoRDwbwq6p3IgDCfBoEQVA3DTCfrgLM\nKpE+k8Uj95TjNOCo9Hs2sJeZ3V5vx9qN0BSDIAjqoJLpNAnMVSVNznwO6oGunI1H+dkVuBn4raQv\n90A7LU1oikEQBHVShYl0hpkN6WL7LEprhOU0yMUws5dw71OAGyRNAk6nh6P8tBqhKQZBENRJAxxt\npuDjisVsBjzRzW5NBj7SzbJtSwhFQNKXJF0u6X5Jj2fSPyrpB5LWamb/giDo2zRAKI4HhkoaXEiQ\nNAiP6Tq+1v5I6gd8Bni21rL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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(array([[ 0., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 0., 1.]]),\n", + " )" + ] + }, + "execution_count": 90, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "printConfusionMatrix(forestClf, genericCleanedFM[transportTrips], cleanedResultVector[transportTrips], \"Generic features, motorized only, random forest\")" + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 28. 6. 11. 4. 50. 0.]\n", + " [ 10. 24. 11. 1. 55. 0.]\n", + " [ 7. 3. 30. 5. 55. 0.]\n", + " [ 2. 0. 5. 43. 50. 0.]\n", + " [ 3. 2. 4. 4. 87. 0.]\n", + " [ 5. 0. 0. 0. 23. 72.]]\n" + ] + }, + { + "data": { + "image/png": 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WAUNZ/CX9UWA/4OPAysDLuBL5nJkNaEuk65SIpC2BscBOwHLA03gogrWAA4B1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\nnzCzq3OO2R74OnADcA7+AnAQsIOk95r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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(array([[ 0., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 0., 1.]]),\n", + " )" + ] + }, + "execution_count": 91, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "printConfusionMatrix(forestClf, cleanedFeatureMatrix[transportTrips], cleanedResultVector[transportTrips], \"All features, transport only, random forest\")" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 31. 6. 10. 3. 49. 1.]\n", + " [ 22. 11. 19. 1. 48. 0.]\n", + " [ 8. 5. 24. 3. 60. 0.]\n", + " [ 1. 1. 5. 18. 75. 0.]\n", + " [ 3. 2. 6. 4. 84. 0.]\n", + " [ 0. 0. 0. 7. 45. 48.]]\n" + ] + }, + { + "data": { + "image/png": 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EfLWD7QVB0AlaQQFXozM+5x072VfdV9rMZku6F/iGpLFmNqdC1fOB44BrgKXw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\nA3eZ2Y9zkCcIgiCviIyDgOH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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(array([[ 0., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.]]),\n", + " )" + ] + }, + "execution_count": 92, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "knnClf = neighbors.KNeighborsClassifier()\n", + "printConfusionMatrix(knnClf, genericCleanedFM[transportTrips], cleanedResultVector[transportTrips], \"Generic features, transport only, k-nn\")" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 32. 8. 12. 2. 46. 1.]\n", + " [ 20. 14. 22. 0. 44. 0.]\n", + " [ 8. 5. 24. 2. 61. 0.]\n", + " [ 1. 1. 4. 17. 77. 0.]\n", + " [ 3. 2. 6. 4. 84. 0.]\n", + " [ 0. 0. 0. 7. 45. 48.]]\n" + ] + }, + { + "data": { + "image/png": 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FrgG2pkr9WLUlmpZA7osvjbwYOALfNW8qcB4+5emzZvZctXUGQRA0yJ3fD3gw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\n01TgGeAE4EVgKzx0H3iMwan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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(array([[ 0., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 1., 0.],\n", + " [ 0., 0., 0., 0., 0., 0.]]),\n", + " )" + ] + }, + "execution_count": 93, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "knnClf = neighbors.KNeighborsClassifier()\n", + "printConfusionMatrix(knnClf, cleanedFeatureMatrix[transportTrips], cleanedResultVector[transportTrips], \"All features, transport only, k-nn\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As we can see, we are actually able to predict car trips with a fair degree of accuracy. But bus and train trips are pretty much a tossup. Ignore the entries for 0 and 1 above, since we stripped out all walk and bike trips, and so these are only trips which moves misclassified, and not the entire dataset. Now we know why the Zheng paper only attempted to distinguish between bus and car trips, and not bus, train and car. The new features helped in the decision tree case, but not by that much, and did not help us at all in the knn case." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## User-specific models" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def getUserModelComparison(isTransportOnly):\n", + " userIds = Sections.distinct(\"user_id\")\n", + "\n", + " # I'm not going to bother with testing against only the generic features\n", + " # because the main issue here is personalization\n", + "\n", + " userIdList = []\n", + " numberOfSections = []\n", + " percentWalkBikeSections = []\n", + " percentAutoClassified = []\n", + " percentAutoClassifiedWalk = []\n", + " percentAutoClassifiedBike = []\n", + " percentAutoClassifiedBus = []\n", + " percentAutoClassifiedTrain = []\n", + " percentAutoClassifiedCar = []\n", + " autoClassifiedAccuracy = []\n", + " overallAccuracy = []\n", + "\n", + " labels = [\"Number of sections\", \"% walk+bike trips\",\n", + " \"% autoclassified\", \"% auto classified walk\",\n", + " \"% auto classified bike\", \"% auto classified bus\",\n", + " \"% auto classified train\", \"% auto classified car\",\n", + " \"auto classified accuracy\", \"overall accuracy\"]\n", + " \n", + " for userId in userIds:\n", + " # decision tree with all features\n", + " if not isTransportOnly:\n", + " query = {\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, {'user_id': userId}]}\n", + " else:\n", + " query = {\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, {'mode': 4}, {'user_id': userId}]}\n", + " \n", + " wbQuery = {\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$in': ['1', '3', '7']}}, {'user_id': userId}]}\n", + " walkBikeTripCount = Sections.find(wbQuery).count()\n", + " (userFeatureMatrix, userResultVector) = generateFeatureMatrixAndResultVector(query)\n", + " \n", + " # we only focus on users who have enough history with us\n", + " if len(userResultVector) < 150:\n", + " print(\"Skipping user with userId %s who has %s unconfirmed sections\" % (userId, len(userResultVector)))\n", + " continue\n", + " \n", + " forestClf = ensemble.RandomForestClassifier()\n", + " # printConfusionMatrix(forestClf, userFeatureMatrix, userResultVector)\n", + " (pac5, pacm5, hcs5, s5) = kFoldValidationWithProb(forestClf, userFeatureMatrix, userResultVector, 5, 0.95)\n", + " userIdList.append(userId)\n", + " \n", + " numberOfSections.append(len(userResultVector))\n", + " percentWalkBikeSections.append(float(walkBikeTripCount)/len(userResultVector))\n", + " percentAutoClassified.append(pac5.mean())\n", + " percentAutoClassifiedWalk.append(pacm5[0].mean())\n", + " percentAutoClassifiedBike.append(pacm5[1].mean())\n", + " percentAutoClassifiedBus.append(pacm5[2].mean())\n", + " percentAutoClassifiedTrain.append(pacm5[3].mean())\n", + " percentAutoClassifiedCar.append(pacm5[4].mean())\n", + " autoClassifiedAccuracy.append(hcs5.mean())\n", + " overallAccuracy.append(s5.mean())\n", + " resultArray = np.array([numberOfSections, percentAutoClassified, percentAutoClassifiedWalk,\n", + " percentAutoClassifiedBike, percentAutoClassifiedBus, percentAutoClassifiedTrain,\n", + " percentAutoClassifiedCar, autoClassifiedAccuracy, overallAccuracy])\n", + " print(resultArray.shape)\n", + " return (userIdList, resultArray, labels)" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def displayUserVariation(userIds, ra, labels):\n", + " ''' ra has rows = plots and cols = users\n", + " '''\n", + " fig, (axes, axesNum) = plt.subplots(2, 1, figsize=(25, 25))\n", + " nUsers = len(userIds)\n", + " \n", + " for i in [1,-2,-1]:\n", + " # each row is one plot\n", + " print(ra[i])\n", + " axes.plot(np.arange(nUsers), ra[i], linewidth=2, label=labels[i])\n", + " axes.legend(loc='best')\n", + " for i in [0]:\n", + " # each row is one plot\n", + " print(ra[i])\n", + " axesNum.plot(np.arange(nUsers), ra[i], linewidth=2, label=labels[i]) \n", + " axesNum.legend(loc='best')" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId 01477d94-e0bb-3903-a428-338551801391 who has 64 unconfirmed sections\n", + "Found 11 high confidence predictions out of 43\n", + "Found 15 high confidence predictions out of 42\n", + "Found 11 high confidence predictions out of 42\n", + "Found 14 high confidence predictions out of 42\n", + "Found 14 high confidence predictions out of 42\n", + "for prob 0.95, percentage auto classified 0.308305647841\n", + "for prob 0.95, scoring only on high confidence predictions 1.0\n", + "for prob 0.95, scoring on all predictions 0.876965669989\n", + "Skipping user with userId 04a9dec3-5a20-38ef-85b7-414dc7a2cf4e who has 0 unconfirmed sections\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId 1a65368b-888e-3e77-8f7c-1128f16da1df who has 22 unconfirmed sections\n", + "Found 24 high confidence predictions out of 33\n", + "Found 23 high confidence predictions out of 33\n", + "Found 29 high confidence predictions out of 33\n", + "Found 22 high confidence predictions out of 32\n", + "Found 31 high confidence predictions out of 32\n", + "for prob 0.95, percentage auto classified 0.791856060606\n", + "for prob 0.95, scoring only on high confidence predictions 0.986206896552\n", + "for prob 0.95, scoring on all predictions 0.975378787879\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 13 high confidence predictions out of 33\n", + "Found 12 high confidence predictions out of 33\n", + "Found 15 high confidence predictions out of 33\n", + "Found 14 high confidence predictions out of 33\n", + "Found 15 high confidence predictions out of 32\n", + "for prob 0.95, percentage auto classified 0.421022727273\n", + "for prob 0.95, scoring only on high confidence predictions 0.986666666667\n", + "for prob 0.95, scoring on all predictions 0.87178030303\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 24 high confidence predictions out of 31\n", + "Found 28 high confidence predictions out of 31\n", + "Found 22 high confidence predictions out of 31\n", + "Found 23 high confidence predictions out of 31\n", + "Found 24 high confidence predictions out of 31\n", + "for prob 0.95, percentage auto classified 0.78064516129\n", + "for prob 0.95, scoring only on high confidence predictions 1.0\n", + "for prob 0.95, scoring on all predictions 0.974193548387\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId 2491630e-bb62-39c2-8349-df4dad434dee who has 103 unconfirmed sections\n", + "Found 19 high confidence predictions out of 41\n", + "Found 25 high confidence predictions out of 40\n", + "Found 21 high confidence predictions out of 40\n", + "Found 27 high confidence predictions out of 40\n", + "Found 21 high confidence predictions out of 40\n", + "for prob 0.95, percentage auto classified 0.562682926829\n", + "for prob 0.95, scoring only on high confidence predictions 0.992592592593\n", + "for prob 0.95, scoring on all predictions 0.860609756098\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 49 high confidence predictions out of 69\n", + "Found 42 high confidence predictions out of 69\n", + "Found 48 high confidence predictions out of 68\n", + "Found 42 high confidence predictions out of 68\n", + "Found 39 high confidence predictions out of 68\n", + "for prob 0.95, percentage auto classified 0.643179880648\n", + "for prob 0.95, scoring only on high confidence predictions 0.973979591837\n", + "for prob 0.95, scoring on all predictions 0.926939471441\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId 399ed209-2e4e-37fc-a6ac-37c25f7ee1f2 who has 114 unconfirmed sections\n", + "Found 29 high confidence predictions out of 60\n", + "Found 24 high confidence predictions out of 59\n", + "Found 33 high confidence predictions out of 59\n", + "Found 24 high confidence predictions out of 59\n", + "Found 31 high confidence predictions out of 59\n", + "for prob 0.95, percentage auto classified 0.476327683616\n", + "for prob 0.95, scoring only on high confidence predictions 0.981036168133\n", + "for prob 0.95, scoring on all predictions 0.895254237288\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 28 high confidence predictions out of 61\n", + "Found 32 high confidence predictions out of 61\n", + "Found 30 high confidence predictions out of 61\n", + "Found 34 high confidence predictions out of 61\n", + "Found 22 high confidence predictions out of 60\n", + "for prob 0.95, percentage auto classified 0.479890710383\n", + "for prob 0.95, scoring only on high confidence predictions 0.968651960784\n", + "for prob 0.95, scoring on all predictions 0.865300546448\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId 3c1f13e8-b063-3d6c-a1eb-8fd39b874110 who has 28 unconfirmed sections\n", + "Found 39 high confidence predictions out of 76\n", + "Found 38 high confidence predictions out of 76\n", + "Found 33 high confidence predictions out of 75\n", + "Found 42 high confidence predictions out of 75\n", + "Found 42 high confidence predictions out of 75\n", + "for prob 0.95, percentage auto classified 0.514631578947\n", + "for prob 0.95, scoring only on high confidence predictions 1.0\n", + "for prob 0.95, scoring on all predictions 0.896631578947\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId 5322f635-a82c-3677-a1a4-5c26804a90b7 who has 83 unconfirmed sections\n", + "Skipping user with userId 560a0ea4-fcdf-3c1b-adf0-22d2b79af3ea who has 5 unconfirmed sections\n", + "Found 39 high confidence predictions out of 89\n", + "Found 36 high confidence predictions out of 89\n", + "Found 35 high confidence predictions out of 89\n", + "Found 44 high confidence predictions out of 89\n", + "Found 40 high confidence predictions out of 88\n", + "for prob 0.95, percentage auto classified 0.436976506639\n", + "for prob 0.95, scoring only on high confidence predictions 0.990454545455\n", + "for prob 0.95, scoring on all predictions 0.900970377937\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 65 high confidence predictions out of 93\n", + "Found 63 high confidence predictions out of 93\n", + "Found 70 high confidence predictions out of 93\n", + "Found 63 high confidence predictions out of 93\n", + "Found 67 high confidence predictions out of 93\n", + "for prob 0.95, percentage auto classified 0.705376344086\n", + "for prob 0.95, scoring only on high confidence predictions 1.0\n", + "for prob 0.95, scoring on all predictions 0.939784946237\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId 6a488797-5be1-38aa-9700-5532be978ff9 who has 92 unconfirmed sections\n", + "Skipping user with userId 6dbe9b5a-26a1-31d0-aeb6-7b08ffa49b10 who has 0 unconfirmed sections\n", + "Skipping user with userId 7327a0b3-4959-31f5-86cb-ea0c59fd0c83 who has 8 unconfirmed sections\n", + "Skipping user with userId 7a88d272-3b9e-3d18-9749-57ddb6214440 who has 0 unconfirmed sections\n", + "Found 32 high confidence predictions out of 61\n", + "Found 22 high confidence predictions out of 60\n", + "Found 25 high confidence predictions out of 60\n", + "Found 25 high confidence predictions out of 60\n", + "Found 27 high confidence predictions out of 60\n", + "for prob 0.95, percentage auto classified 0.434918032787\n", + "for prob 0.95, scoring only on high confidence predictions 0.990909090909\n", + "for prob 0.95, scoring on all predictions 0.824043715847\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 37 high confidence predictions out of 58\n", + "Found 39 high confidence predictions out of 58\n", + "Found 43 high confidence predictions out of 57\n", + "Found 33 high confidence predictions out of 57\n", + "Found 43 high confidence predictions out of 57\n", + "for prob 0.95, percentage auto classified 0.679612825166\n", + "for prob 0.95, scoring only on high confidence predictions 0.974857700439\n", + "for prob 0.95, scoring on all predictions 0.937265577737\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId 8d235d9c-7af6-3132-ba91-626e40181449 who has 16 unconfirmed sections\n", + "Skipping user with userId 8d718272-c46c-3e24-8bae-9696917deeec who has 28 unconfirmed sections\n", + "Skipping user with userId 8e230f78-6e37-3588-bf2c-6888a5b63c82 who has 43 unconfirmed sections\n", + "Skipping user with userId 951779de-a10c-3373-b186-c1c9b14b5e38 who has 3 unconfirmed sections\n", + "Found 47 high confidence predictions out of 87\n", + "Found 46 high confidence predictions out of 87\n", + "Found 42 high confidence predictions out of 87\n", + "Found 55 high confidence predictions out of 86\n", + "Found 44 high confidence predictions out of 86\n", + "for prob 0.95, percentage auto classified 0.540577385726\n", + "for prob 0.95, scoring only on high confidence predictions 0.982503574132\n", + "for prob 0.95, scoring on all predictions 0.902993851911\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId 9cc9d577-3a22-3659-8cd5-9142936f44ec who has 29 unconfirmed sections\n", + "Skipping user with userId a1a10092-0136-37f1-8109-9ebf47ef72b2 who has 8 unconfirmed sections\n", + "Found 36 high confidence predictions out of 57\n", + "Found 26 high confidence predictions out of 57\n", + "Found 29 high confidence predictions out of 57\n", + "Found 30 high confidence predictions out of 57\n", + "Found 42 high confidence predictions out of 57\n", + "for prob 0.95, percentage auto classified 0.571929824561\n", + "for prob 0.95, scoring only on high confidence predictions 1.0\n", + "for prob 0.95, scoring on all predictions 0.975438596491\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId acd105e3-b221-35c5-81ac-fee5ffe9de66 who has 89 unconfirmed sections\n", + "Skipping user with userId adaa57a8-7fb8-3389-acce-db50ddc9e2dd who has 24 unconfirmed sections\n", + "Found 18 high confidence predictions out of 56\n", + "Found 23 high confidence predictions out of 56\n", + "Found 18 high confidence predictions out of 56\n", + "Found 19 high confidence predictions out of 56\n", + "Found 23 high confidence predictions out of 55\n", + "for prob 0.95, percentage auto classified 0.362207792208\n", + "for prob 0.95, scoring only on high confidence predictions 0.991304347826\n", + "for prob 0.95, scoring on all predictions 0.92474025974\n", + "Skipping user with userId b3b9fe85-d510-3e5b-bec2-031ca9da7c83 who has 0 unconfirmed sections\n", + "Skipping user with userId bbd4e1ad-bd2d-3126-a58c-2c2fe1895fba who has 0 unconfirmed sections\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId bcbefbfc-8021-353f-9f5c-648d539c8cff who has 5 unconfirmed sections\n", + "Found 14 high confidence predictions out of 34\n", + "Found 10 high confidence predictions out of 34\n", + "Found 21 high confidence predictions out of 34\n", + "Found 23 high confidence predictions out of 34\n", + "Found 23 high confidence predictions out of 34\n", + "for prob 0.95, percentage auto classified 0.535294117647\n", + "for prob 0.95, scoring only on high confidence predictions 1.0\n", + "for prob 0.95, scoring on all predictions 0.905882352941\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 17 high confidence predictions out of 53\n", + "Found 10 high confidence predictions out of 52\n", + "Found 18 high confidence predictions out of 52\n", + "Found 20 high confidence predictions out of 52\n", + "Found 20 high confidence predictions out of 52\n", + "for prob 0.95, percentage auto classified 0.325689404935\n", + "for prob 0.95, scoring only on high confidence predictions 0.96\n", + "for prob 0.95, scoring on all predictions 0.842960812772\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 17 high confidence predictions out of 98\n", + "Found 14 high confidence predictions out of 98\n", + "Found 20 high confidence predictions out of 98\n", + "Found 24 high confidence predictions out of 97\n", + "Found 16 high confidence predictions out of 97\n", + "for prob 0.95, percentage auto classified 0.186555859457\n", + "for prob 0.95, scoring only on high confidence predictions 0.955616246499\n", + "for prob 0.95, scoring on all predictions 0.782726698927\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId d8a6b737-b6a5-3fc7-a144-76ac2d434252 who has 28 unconfirmed sections\n", + "Skipping user with userId e0509a4e-9842-3c73-8050-875b6383c097 who has 112 unconfirmed sections\n", + "Skipping user with userId e1a99120-9a5a-31ae-9d7a-93b9a3e0c51c who has 32 unconfirmed sections\n", + "Skipping user with userId e211dd91-423f-31ff-a1f8-89e5fdecc164 who has 148 unconfirmed sections\n", + "Skipping user with userId ea3f7719-f4a3-36fd-9477-924114cfe0bd who has 18 unconfirmed sections\n", + "Skipping user with userId ed8ca6a2-9092-37af-adde-46e51a18a310 who has 128 unconfirmed sections\n", + "Found 29 high confidence predictions out of 90\n", + "Found 26 high confidence predictions out of 89\n", + "Found 32 high confidence predictions out of 89\n", + "Found 30 high confidence predictions out of 89\n", + "Found 36 high confidence predictions out of 89\n", + "for prob 0.95, percentage auto classified 0.343096129838\n", + "for prob 0.95, scoring only on high confidence predictions 0.96202991453\n", + "for prob 0.95, scoring on all predictions 0.82279650437\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId f8fee20c-0f32-359d-ba75-bce97a7ac83b who has 137 unconfirmed sections\n", + "Skipping user with userId fb457463-9a06-3c84-947d-db1fefb5a199 who has 0 unconfirmed sections\n", + "Skipping user with userId ff860db0-f3fe-387c-a005-c5837f5ba970 who has 0 unconfirmed sections\n", + "(9, 20)\n" + ] + } + ], + "source": [ + "(userIds, userResultArray, labels) = getUserModelComparison(isTransportOnly=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ 0. 1. 0. 1. 1. 1. 0. 0. 1. 0. 1. 0. 1. 1. 1. 0. 1. 0.\n", + " 0. 0.]\n", + "[ 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.\n", + " 1. 1.]\n", + "[ 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.\n", + " 1. 1.]\n", + "[ 211. 163. 164. 155. 201. 342. 296. 304. 377. 444. 465. 301.\n", + " 287. 433. 285. 279. 170. 261. 488. 446.]\n" + ] + }, + { + "data": { + "image/png": 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Fxgsb4WTnhM/Gf4YH73uwQfeLuxSHD09+CCc7J2yauOmu4TYRERERUXuh0qiw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6F/1KIA+um/TKDI3UGGP8dvQo/PCDu1+zJixZ4r4U+qlAAWjeHMaMcV2lg1q/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KQAAMyaNctOVFT0g7+//79tx/IlMzOzeZKSkvvJZPIVKpV6SUFBwd3Dw4MpGGb27NkTMAwLCwoK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\nAOiKogsAAEBXFF0AAAC68gN7epDHBU3V4QAAAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "selIndices = [2, -2, -1, 1]\n", + "mpl.rcParams['font.size'] = 16\n", + "fig, axes = displayHelpers.showCategoryChart(np.arange(len(userIds)), np.multiply([userResultArray[i] for i in selIndices], 100), [labels[i] for i in selIndices],\n", + " ['b', 'g', 'c', 'm', 'y', 'k', 'w'],\n", + " \"Percentage\",\n", + " \"Accuracy of various predictions\",\n", + " figsize=(12,5), width=0.2)\n", + "ax2 = axes.twinx()\n", + "# ax2.bar(np.arange(len(userResultArray[0])) + 3 * 0.2, userResultArray[0], 0.2, color = 'c')\n", + "nSecLine, = ax2.plot(userResultArray[0], 'r-+', linewidth=2, label=\"Number of confirmed sections\")\n", + "axes.set_ylim(top=115)\n", + "axes.axhline(98, linewidth=2, label = \"98%\")\n", + "axes.axhline(85, linewidth=2, label = \"85%\")\n", + "axes.text(x=15.5, y=98.5, s=\"98%\")\n", + "axes.text(x=15.5, y=85.5, s=\"85%\")\n", + "axes.get_legend().set_bbox_to_anchor((0.4, -0.1))\n", + "print(axes.get_legend_handles_labels())\n", + "ax2.legend([nSecLine], [\"Number of sections\"], loc=\"upper right\", framealpha=0.3, bbox_to_anchor=(1, -0.1))\n", + "ax2.set_ylabel(\"Count (number of sections)\")\n", + "axes.set_xlabel(\"Users\")\n", + "ax2.set_ylim(bottom=0)\n", + "fig.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 99, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "ax.plot(userResultArray[1], userResultArray[-1], \"o\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let us pick users with really high accuracy. Unfortunately, they also have the least confirmed sections. Let us see whether this is because they are heavy walkers or otherwise." + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(UUID('3537737e-8db4-3706-8c6c-ad4cafd9dc82'),\n", + " UUID('3a307244-ecf1-3e6e-a9a7-3aaf101b40fa'),\n", + " UUID('1cc03940-57f5-3e35-a189-55d067dc6460'))" + ] + }, + "execution_count": 100, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "userIds[5], userIds[6], userIds[2]" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "number of instances of mode 3 = 6\n", + "number of instances of mode 6 = 3\n", + "number of instances of mode 9 = 0\n", + "nClasses = 3\n", + "Number of distinct classes in training set = [ 1. 5. 7.], test set = [ 1. 5. 7.]\n", + "Number of distinct classes in training set = [ 1. 5. 7.], test set = [ 1. 5. 7.]\n", + "Number of distinct classes in training set = [ 1. 5. 7.], test set = [ 1. 5. 7.]\n", + "Number of distinct classes in training set = [ 1. 5. 7.], test set = [ 1. 5. 7.]\n", + "Number of distinct classes in training set = [ 1. 5. 7.], test set = [ 1. 5. 7.]\n", + "[[ 100. 0. 0.]\n", + " [ 3. 83. 13.]\n", + " [ 0. 35. 65.]]\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "number of instances of mode 6 = 1\n", + "number of instances of mode 9 = 1\n", + "nClasses = 4\n", + "Number of distinct classes in training set = [ 1. 3. 5. 7.], test set = [ 1. 3. 5. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 7.], test set = [ 1. 3. 5. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 7.], test set = [ 1. 3. 5. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 7.], test set = [ 1. 3. 5. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 7.], test set = [ 1. 3. 5. 7.]\n", + "[[ 98. 2. 0. 0.]\n", + " [ 15. 76. 0. 9.]\n", + " [ 10. 0. 77. 13.]\n", + " [ 20. 7. 7. 67.]]\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "number of instances of mode 5 = 9\n", + "number of instances of mode 9 = 2\n", + "nClasses = 4\n", + "Number of distinct classes in training set = [ 1. 3. 6. 7.], test set = [ 1. 3. 6. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 6. 7.], test set = [ 1. 3. 6. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 6. 7.], test set = [ 1. 3. 6. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 6. 7.], test set = [ 1. 3. 6. 7.]\n", + "Number of distinct classes in training set = [ 1. 3. 6. 7.], test set = [ 1. 3. 6. 7.]\n", + "[[ 92. 6. 3. 0.]\n", + " [ 5. 94. 0. 1.]\n", + " [ 0. 2. 96. 2.]\n", + " [ 5. 50. 10. 35.]]\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for i in [2,5,6]:\n", + " userId = userIds[i]\n", + " query = {\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, {'user_id': userId}]}\n", + " (userFeatureMatrix, userResultVector) = generateFeatureMatrixAndResultVector(query)\n", + " indicesToStrip = (userResultVector == 2) | (userResultVector == 4) | (userResultVector == 8)\n", + " for mode in [1,3,5,6,7,9]:\n", + " # nFolds = 5\n", + " if np.count_nonzero(userResultVector == mode) <= 10:\n", + " print(\"number of instances of mode %s = %s\" % (mode, np.count_nonzero(userResultVector == mode)))\n", + " indicesToStrip = indicesToStrip | (userResultVector == mode)\n", + " userStrippedIndices = np.logical_not(indicesToStrip)\n", + " strippedUserFeatureMatrix = userFeatureMatrix[userStrippedIndices]\n", + " strippedUserResultVector = userResultVector[userStrippedIndices]\n", + " forestClf = ensemble.RandomForestClassifier()\n", + " printConfusionMatrix(forestClf, strippedUserFeatureMatrix, strippedUserResultVector, \"All features, random forest, user %s\" % i)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "So there's quite a bit of variability in both the overall accuracy, and in the number of trips for a user. The two don't seem to be correlated though. We get some fairly uneven improvement - for some users, the general classification is over 90%. We are also able to classify over 80% of the trips for some users.\n", + "\n", + "But that might just be due to a higher ratio of walk trips, which are classified more accurately. I can explore this only for transport, but first, I'm going to try to build a gesture library and build the associated features. Then maybe Mogeng can continue some of the exploration." + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId 01477d94-e0bb-3903-a428-338551801391 who has 41 unconfirmed sections\n", + "Skipping user with userId 03678a4f-efb9-3100-b0e5-8f296c197eb7 who has 82 unconfirmed sections\n", + "Skipping user with userId 04a9dec3-5a20-38ef-85b7-414dc7a2cf4e who has 0 unconfirmed sections\n", + "Skipping user with userId 1a65368b-888e-3e77-8f7c-1128f16da1df who has 22 unconfirmed sections\n", + "Skipping user with userId 1c97e50a-aa2a-3016-ad31-f9f6b726d4c4 who has 103 unconfirmed sections\n", + "Skipping user with userId 1cc03940-57f5-3e35-a189-55d067dc6460 who has 60 unconfirmed sections\n", + "Skipping user with userId 202a0732-d5c2-307d-aa29-2b39bc5e6660 who has 43 unconfirmed sections\n", + "Skipping user with userId 2491630e-bb62-39c2-8349-df4dad434dee who has 63 unconfirmed sections\n", + "Skipping user with userId 298a1c8e-74c7-3631-b59f-a5ce246c4e6d who has 68 unconfirmed sections\n", + "Skipping user with userId 3537737e-8db4-3706-8c6c-ad4cafd9dc82 who has 35 unconfirmed sections\n", + "Skipping user with userId 399ed209-2e4e-37fc-a6ac-37c25f7ee1f2 who has 101 unconfirmed sections\n", + "Skipping user with userId 3a307244-ecf1-3e6e-a9a7-3aaf101b40fa who has 107 unconfirmed sections\n", + "Found 10 high confidence predictions out of 34\n", + "Found 9 high confidence predictions out of 34\n", + "Found 8 high confidence predictions out of 34\n", + "Found 6 high confidence predictions out of 34\n", + "Found 5 high confidence predictions out of 34\n", + "for prob 0.95, percentage auto classified 0.223529411765\n", + "for prob 0.95, scoring only on high confidence predictions 0.975\n", + "for prob 0.95, scoring on all predictions 0.776470588235\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId 3c1f13e8-b063-3d6c-a1eb-8fd39b874110 who has 20 unconfirmed sections\n", + "Skipping user with userId 527e98f8-710d-3719-93f2-ab140d1439ba who has 107 unconfirmed sections\n", + "Skipping user with userId 5322f635-a82c-3677-a1a4-5c26804a90b7 who has 24 unconfirmed sections\n", + "Skipping user with userId 560a0ea4-fcdf-3c1b-adf0-22d2b79af3ea who has 2 unconfirmed sections\n", + "Skipping user with userId 5c035ff1-e0d5-397f-b989-9cb8faa0a1da who has 112 unconfirmed sections\n", + "Skipping user with userId 5dd35f51-3d1a-30db-9b22-ce0a432c2a59 who has 108 unconfirmed sections\n", + "Skipping user with userId 6a488797-5be1-38aa-9700-5532be978ff9 who has 38 unconfirmed sections\n", + "Skipping user with userId 6dbe9b5a-26a1-31d0-aeb6-7b08ffa49b10 who has 0 unconfirmed sections\n", + "Skipping user with userId 7327a0b3-4959-31f5-86cb-ea0c59fd0c83 who has 8 unconfirmed sections\n", + "Skipping user with userId 7a88d272-3b9e-3d18-9749-57ddb6214440 who has 0 unconfirmed sections\n", + "Skipping user with userId 89e30222-b446-30ad-852c-b305ddafe70d who has 132 unconfirmed sections\n", + "Found 37 high confidence predictions out of 51\n", + "Found 41 high confidence predictions out of 51\n", + "Found 38 high confidence predictions out of 51\n", + "Found 43 high confidence predictions out of 51\n", + "Found 37 high confidence predictions out of 51\n", + "for prob 0.95, percentage auto classified 0.76862745098\n", + "for prob 0.95, scoring only on high confidence predictions 0.964482499038\n", + "for prob 0.95, scoring on all predictions 0.960784313725\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId 8d235d9c-7af6-3132-ba91-626e40181449 who has 5 unconfirmed sections\n", + "Skipping user with userId 8d718272-c46c-3e24-8bae-9696917deeec who has 16 unconfirmed sections\n", + "Skipping user with userId 8e230f78-6e37-3588-bf2c-6888a5b63c82 who has 15 unconfirmed sections\n", + "Skipping user with userId 951779de-a10c-3373-b186-c1c9b14b5e38 who has 1 unconfirmed sections\n", + "Found 3 high confidence predictions out of 37\n", + "Found 7 high confidence predictions out of 37\n", + "Found 8 high confidence predictions out of 37\n", + "Found 9 high confidence predictions out of 37\n", + "Found 3 high confidence predictions out of 37\n", + "for prob 0.95, percentage auto classified 0.162162162162\n", + "for prob 0.95, scoring only on high confidence predictions 0.949206349206\n", + "for prob 0.95, scoring on all predictions 0.745945945946\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId 9cc9d577-3a22-3659-8cd5-9142936f44ec who has 8 unconfirmed sections\n", + "Skipping user with userId a1a10092-0136-37f1-8109-9ebf47ef72b2 who has 1 unconfirmed sections\n", + "Skipping user with userId a47da5c4-3ced-34ac-af25-6c3aa7998827 who has 119 unconfirmed sections\n", + "Skipping user with userId acd105e3-b221-35c5-81ac-fee5ffe9de66 who has 11 unconfirmed sections\n", + "Skipping user with userId adaa57a8-7fb8-3389-acce-db50ddc9e2dd who has 11 unconfirmed sections\n", + "Found 14 high confidence predictions out of 40\n", + "Found 23 high confidence predictions out of 40\n", + "Found 19 high confidence predictions out of 40\n", + "Found 18 high confidence predictions out of 40\n", + "Found 25 high confidence predictions out of 40\n", + "for prob 0.95, percentage auto classified 0.495\n", + "for prob 0.95, scoring only on high confidence predictions 0.975304347826\n", + "for prob 0.95, scoring on all predictions 0.895\n", + "Skipping user with userId b3b9fe85-d510-3e5b-bec2-031ca9da7c83 who has 0 unconfirmed sections\n", + "Skipping user with userId bbd4e1ad-bd2d-3126-a58c-2c2fe1895fba who has 0 unconfirmed sections\n", + "Skipping user with userId bcbefbfc-8021-353f-9f5c-648d539c8cff who has 0 unconfirmed sections\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId bd01c81f-feff-3249-a6de-5cf7f06accc8 who has 98 unconfirmed sections\n", + "Found 15 high confidence predictions out of 43\n", + "Found 13 high confidence predictions out of 43\n", + "Found 10 high confidence predictions out of 43\n", + "Found 15 high confidence predictions out of 43\n", + "Found 12 high confidence predictions out of 42\n", + "for prob 0.95, percentage auto classified 0.30365448505\n", + "for prob 0.95, scoring only on high confidence predictions 0.871282051282\n", + "for prob 0.95, scoring on all predictions 0.808084163898\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 15 high confidence predictions out of 64\n", + "Found 13 high confidence predictions out of 64\n", + "Found 9 high confidence predictions out of 64\n", + "Found 4 high confidence predictions out of 64\n", + "Found 5 high confidence predictions out of 64\n", + "for prob 0.95, percentage auto classified 0.14375\n", + "for prob 0.95, scoring only on high confidence predictions 0.871794871795\n", + "for prob 0.95, scoring on all predictions 0.696875\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId d8a6b737-b6a5-3fc7-a144-76ac2d434252 who has 12 unconfirmed sections\n", + "Skipping user with userId e0509a4e-9842-3c73-8050-875b6383c097 who has 22 unconfirmed sections\n", + "Skipping user with userId e1a99120-9a5a-31ae-9d7a-93b9a3e0c51c who has 23 unconfirmed sections\n", + "Skipping user with userId e211dd91-423f-31ff-a1f8-89e5fdecc164 who has 54 unconfirmed sections\n", + "Skipping user with userId ea3f7719-f4a3-36fd-9477-924114cfe0bd who has 8 unconfirmed sections\n", + "Skipping user with userId ed8ca6a2-9092-37af-adde-46e51a18a310 who has 29 unconfirmed sections\n", + "Found 5 high confidence predictions out of 45\n", + "Found 11 high confidence predictions out of 45\n", + "Found 8 high confidence predictions out of 44\n", + "Found 7 high confidence predictions out of 44\n", + "Found 16 high confidence predictions out of 44\n", + "for prob 0.95, percentage auto classified 0.21202020202\n", + "for prob 0.95, scoring only on high confidence predictions 0.903246753247\n", + "for prob 0.95, scoring on all predictions 0.689191919192\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:49: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + "/Users/shankari/e-mission/e-mission-analysis/featurecalc.py:181: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n", + " if speeds == None:\n", + "/Users/shankari/OSS/anaconda/envs/emission/lib/python3.6/site-packages/ipykernel_launcher.py:57: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Skipping user with userId f8fee20c-0f32-359d-ba75-bce97a7ac83b who has 67 unconfirmed sections\n", + "Skipping user with userId fb457463-9a06-3c84-947d-db1fefb5a199 who has 0 unconfirmed sections\n", + "Skipping user with userId ff860db0-f3fe-387c-a005-c5837f5ba970 who has 0 unconfirmed sections\n", + "(9, 7)\n" + ] + } + ], + "source": [ + "(userIdsTransOnly, userResultArrayTransOnly, labelsTransOnly) = getUserModelComparison(isTransportOnly=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ 0. 1. 0. 0. 0. 0. 0.]\n", + "[ 1. 1. 1. 1. 1. 1. 1.]\n", + "[ 1. 1. 1. 1. 1. 1. 1.]\n", + "[ 170. 255. 185. 200. 214. 320. 222.]\n" + ] + }, + { + "data": { + "image/png": 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hmTufq7/sxQ17PO+AHwfOpxrD4RvctK9LWgUF1SKtRIm9hAWbFvD6ptepcFYQ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\nWltQohkr83V3dn8jHQAAAADMinHGKLtvtrL7Zqu8vlyLChf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PamRqZzRKQUCHA5GdO7PgCTl6RQrEFCpMxbfzCdh2dtxu21ebBbHT00WS6Jv8vBYz3rsWR8Ar0b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\n3gy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ADAFCeu+9l8nU8/7+mIGN2SCTZGaeKffnunKdi8yZM/dc6ox8553nzYhc1LCc3q8D\nY4d05kBZBfdMXRQ7R1INONozqrdXPZZXPV4EbEiS5IV3n5AkyW4qr7L+yEHvdxFQBvz2oOeVA78B\nxoQQco6yR5IkSZIkqcH43ey1rNpeRJ8Ozfn4sEN/GV3V8R8XDCI7I8Xv31zPnDU7Y+dIOkbVHqpD\nCBkhhOwQwgDgUWAT8OuqNw8B5h3m3eYDPUMILQ563sokSYoO87xsoP+RxEuSJEmSJDU0B0orePDZ\npQDccP5AsjKO9jrCpq1n+2ZcdVYfAO6cvIB0OolcJOlYHMlXwr8BJcAS4ATg3CRJtlS9rR1wuB9d\n7ah6bFvN57V7vw8eQrg6hDA7hDB769atR5AtSZIkSZJUfzz+ykq27C3h+G6tueC4LrFzGrQvjOxP\nfssc3lq7iz++tT52jqRjcCRD9aeA4VSeMb0HmBFC6F0LTYeVJMljSZIMS5JkWH5+fl19WEmSJEmS\npBqzu6iMH764HICJYwtIpULkooatRU4mN48tBGDS1EXsLyn/gPeQVF9Ve6hOkmRhkiR/S5Lk18B5\nQAvglqo37+R/r5o+WLuD3l6d5+04zNskSZIkSZIahUdmLmdPcTmn92vPmf07xM5pFD56UjeGdm/N\n5j0lPFL1QwBJDc9RHYKUJMkuYBn/e6b0fCrPnz7UYGBNkiT7DnpenxBCs8M8r7TqNSVJkiRJkhqd\nTbuLeXzWSgBuHltICF5NXRNSqcBtEypnqcdeXsHaHYfeGk1SQ3BUQ3UIoRNQCLz7Y6o/A91CCCMO\nek4rYELV2941GcgCPn7Q8zKBTwDTkyQpOZoeSZIkSZKk+u7B55ZSUp5m3HGdGdqjTeycRuWUXm35\nyIldKS1Pc/dfFsbOkXQUMj/oCSGEPwBzgLlUnk09ELgOKAfur3ran4FXgV+EEG6i8oiPrwEBuOfd\n10qS5M0Qwm+BB0IIWcBK4PNAH+DyGvqcJEmSJEmS6pUVW/fxu9lrSQW44fyC2DmN0i3jCpk+fzNT\n3tnEayu2M7xv+9hJko5Ada6ofg24GPgp8AxwPTATODFJkiUASZKkgfHADOBh4A9ABTAySZK1h7ze\nlcDjwLeqXq8HMDZJkjnH/NlIkiRJkiTVQ/dPX0JFOuHSYT3o37FF7JxGqUvrPK4Z0Q+AOyYvoCKd\nRC6SdCRCkjS8/9EOGzYsmT17duwMSZIkSZKkDzR33S4uemgW2ZkpZt50Dl1a58VOarQOlFYw6jsz\nWb/rAHd/9HguO61n7CSpyQshvJEkybAPet5RnVEtSZIkSZKk6rl32mIAPn16b0fqWpaXncEt4woB\nuG/aYvYUl0UuklRdDtWSJEmSJEm1ZNaybby8dBstczP5wjn9Yuc0CeNP6MKpvduyfX8p339uaewc\nSdXkUC1JkiRJklQLkiRh0tRFAFwzoh9tmmVHLmoaQgjcPmEIIcDjs1axYuu+2EmSqsGhWpIkSZIk\nqRZMnbeJuet2k98yhyvP6B07p0k5rltrLj2lB+XphLueWRg7R1I1OFRLkiRJkiTVsPKKNPdOrzyb\n+svnDaBZdmbkoqbnxjEFtMjJ5LlFW5i5ZGvsHEkfwKFakiRJkiSphj35xjpWbN1Pr/bN+OSpPWLn\nNEn5LXP44rn9Afjm0wsoq0hHLpL0zzhUS5IkSZIk1aDisgoeeLbyJn43nF9AVobzSyxXntGbXu2b\nsWzLPn7x2urYOZL+Cb9SSpIkSZIk1aCfvrKKTXuKGdylFeOP7xI7p0nLyczg1gsGAfDAs0vZub80\ncpGk9+NQLUmSJEmSVEN2Hyjj4ReXAzBxbAGpVIhcpNGDO3Fm/w7sPlDGd59dEjtH0vtwqJYkSZIk\nSaohj85czu4DZQzv244RA/Nj5wgIIfCN8YNJBfjFa6tZvGlv7CRJh+FQLUmSJEmSVAO27Cnmv2et\nBGDi2EJC8Grq+qKgc0v+bXgv0gnc+fR8kiSJnSTpEA7VkiRJkiRJNeB7zy+luCzN+YM7cXLPtrFz\ndIjrRg2kdV4Ws5ZtZ8aCzbFzJB3CoVqSJEmSJOkYrdq2n9+8vpZUgJvGFMTO0WG0bZ7NdaMGAHDX\nlIWUlFdELpJ0MIdqSZIkSZKkY3T/jCWUpxMuObk7Azq1jJ2j93H58F7079iC1duLeHzWqtg5kg7i\nUC1JkiRJknQM5q3fzeS3N5CdmeKrowfGztE/kZWR4hvjBwPw0PPL2LK3OHKRpHc5VEuSJEmSJB2D\ne6YtBuCK4b3o1iYvco0+yIiB+ZxX2JF9JeXcV/WfnaT4HKolSZIkSZKO0ivLt/HSkq20yMnkCyP7\nx85RNd164SCyMgJPvLGOd9btjp0jCYdqSZIkSZKko5IkCfdMrbwi9+qz+9KueXbkIlVX3/wWfPr0\n3iQJ3DF5PkmSxE6SmjyHakmSJEmSpKMwbf5m3lq7iw4tsvl/Z/aJnaMj9KXzBtC+eTazV+/k6bkb\nY+dITZ5DtSRJkiRJ0hEqr0hz3/TKq6m/dO4AmudkRi7SkWqVm8WNYwoAuHvKQg6UVkQukpo2h2pJ\nkiRJkqQj9Ps317Nsyz56tMvjstN6xs7RUbp0WA8Gd2nFht3FPPbSitg5UpPmUC1JkiRJknQEissq\neGDGEgBuGF1AdqbzSkOVkQrcPmEwAI/MXMaGXQciF0lNl19JJUmSJEmSjsAvXlvNht3FFHZuyUVD\nu8bO0TH6UN/2XHh8F4rL0kyauih2jtRkOVRLkiRJkiRV057iMn7wwjIAbh5bSCoVIhepJtwyrpDs\nzBR/emsDb6zeETtHapIcqiVJkiRJkqrpRy+tYGdRGaf1bsc5Bfmxc1RDerRrxufO7gvAHZMXkE4n\nkYukpsehWpIkSZIkqRq27i3hxy+vBODmcQWE4NXUjck1I/rRqVUOc9ft5qk562LnSE2OQ7UkSZIk\nSVI1PPT8Ug6UVTBqUCdO6dUudo5qWPOcTG4ZVwjAPdMWs6+kPHKR1LQ4VEuSJEmSJH2ANduL+NXr\nawgBbhpTEDtHteQjQ7txYo82bN1b8t5Z5JLqhkO1JEmSJEnSB/jOjMWUVST8y0ndKOjcMnaOakkq\nFbh9wmAAfvLyStZsL4pcJDUdDtWSJEmSJEn/xIINe/jT2xvIzkhx3aiBsXNUy07q2ZaPntSN0oo0\nd01ZEDtHajIcqiVJkiRJkv6Je6ctIkng8uE96dGuWewc1YGJYwvJy8pg2vzNvLJsW+wcqUlwqJYk\nSZIkSXoff1uxnRcWb6V5dgbXjuwfO0d1pHPrXK4d2Q+AO59eQHlFOnKR1Pg5VEuSJEmSJB1GkiRM\nmroIgM+e3ZcOLXIiF6kuXXVWX7q1yWPRpr385u9rY+dIjZ5DtSRJkiRJ0mE8u3ALc9bsol3zbK46\nq2/sHNWx3KwMbr1wEAD3T1/M7qKyyEVS4+ZQLUmSJEmSdIiKdMK90yqvpv7iyP60yMmMXKQYxh3X\nmdP6tGNnURkPPrc0do7UqDlUS5IkSZIkHeIPb65nyeZ9dGuTx+XDe8bOUSQhBG6fMJgQ4GevrmLZ\nln2xk6RGy6FakiRJkiTpICXlFXx3xhIArh89kJzMjMhFimlI19Z88tQelKcTvvXMgtg5UqPlUC1J\nkiRJknSQX762hvW7DlDQqSUXn9Qtdo7qgRvOL6BlTiYvLt7KC4u2xM6RGiWHakmSJEmSpCp7i8t4\n6IVlANw0poCMVIhcpPqgQ4scvnzeAAC++cwCyirSkYukxsehWpIkSZIkqcqPX17Jjv2lnNKrLecN\n6hg7R/XIv5/emz4dmrNi635+9urq2DlSo+NQLUmSJEmSBGzbV8KPX14BwM1jCwnBq6n1v7IzU3z9\nwkEAPPDsErbvK4lcJDUuDtWSJEmSJEnAQ88vY39pBecWduS0Pu1i56geOrewI2cPzGdvcTnfqbrh\npqSa4VAtSZIkSZKavLU7ivjl31YTQuXZ1NLhhBD4xoWDyEgFfv36GhZu3BM7SWo0HKolSZIkSVKT\n991nl1BWkXDxid0Y1KVV7BzVYwM6teRTw3uRTuDOyQtIkiR2ktQoOFRLkiRJkqQmbdGmPfzhzfVk\nZQSuGzUwdo4agK+OGkCbZlm8umI70+Zvip0jNQoO1ZIkSZIkqUm7b9pikgT+9bSe9GzfLHaOGoA2\nzbK5YXTlDzXumrKQ4rKKyEVSw+dQLUmSJEmSmqzZq3bw7MItNMvO4IvnDoidowbkstN6UtCpJWt3\nHOAnf10ZO0dq8ByqJUmSJElSk5QkCZOmLgLgqjP7kN8yJ3KRGpLMjBS3TRgMwA9eWMbmPcWRi6SG\nzaFakiRJkiQ1SS8s3sLfV+2kbbMsPnt239g5aoDO6N+B0YM7UVRawT1TF8fOkRo0h2pJkiRJktTk\npNPJe8PitSP70zI3K3KRGqpbLxhEdkaKp+as4+21u2LnSA2WQ7UkSZIkSWpy/vT2ehZt2kvX1rn8\n2/BesXPUgPXu0Jwrz+wNwB2T55MkSdwgqYFyqJYkSZIkSU1KaXma+6cvAeCroweSm5URuUgN3RdH\n9qdDixzmrNnFn9/eEDtHapAcqiVJkiRJUpPy69fXsG7nAQZ0bMElJ3ePnaNGoGVuFhPHFABw95RF\nFJWWRy6SGh6HakmSJEmS1GTsLynn+88vBeDGMQVkpELkIjUWHzulO8d1a8WmPcX8cOaK2DlSg+NQ\nLUmSJEmSmoyf/HUl2/aVclLPNpw/uFPsHDUiqVTg9glDAHh05nLW7SyKXCQ1LA7VkiRJkiSpSdi+\nr4THXqq80vXmsYWE4NXUqlmn9m7H+BO6UFKe5tt/WRQ7R2pQHKolSZIkSVKT8PCLy9lXUs6IgfkM\n79s+do4aqa9dMIiczBRPz93I6yt3xM6RGgyHakmSJEmS1Oit33WAn7+6GoCbqm56J9WGbm3y+NyI\nfgDc+fR80ukkcpHUMDhUS5IkSZKkRu+7M5ZQWpHmoqFdOa5b69g5auSuGdGXLq1zmbd+D0++sS52\njtQgOFRLkiRJkqRGbcnmvfx+zjoyU4HrRw+MnaMmoFl2JreMKwTgnmmL2FtcFrlIqv8cqiVJkiRJ\nUqN237TFpBP45Gk96N2heewcNREXDe3KKb3asm1fKQ+9sCx2jlTvOVRLkiRJkqRG643VO5m+YDN5\nWRl8+dwBsXPUhIQQuG38YAD++68rWbVtf+QiqX77wKE6hPCxEMIfQwhrQwgHQgiLQwh3hxBaHvK8\nISGE34cQNoQQ9ocQ5ocQbgwhZB7yvNwQwr0hhI1Vr/dqCOHsmv7EJEmSJElS05YkCZOmLgLgM2f2\npmOr3MhFamqG9mjDx07pTllFwl1TFsbOkeq16lxRfSNQAXwNGAc8AnwemBFCSAGEELoCLwJ9ga8C\nE4A/AvcAdx3yej8BPgvcBowHNgLTQggnHuPnIkmSJEmS9J6ZS7by+sodtM7L4uqz+8XOURM1cUwB\nzbMzmLFgM39dui12jlRvVWeonpAkySVJkvwiSZIXkyR5APgy8CHgnKrnjAc6AJ9IkuR3SZI8nyTJ\nrcDvgCvefaEQwlDgX4HrkiT5UZIkzwGXAmuAO2vss5IkSZIkSU1aOp0waepiAK4d2Y/WeVmRi9RU\ndWyVy7Xn9gfgzqfnU16Rjlwk1U8fOFQnSbL1MH/996rHblWP2VWPuw553q5DPsZFQBnw24Nevxz4\nDTAmhJBTjWZJkiRJkqR/avLcDSzcuIcurXO54sO9Y+eoifvMGX3o0S6PJZv38avX18TOkeqlo72Z\n4oiqx3cP13kC2Ab8IITQJ4TQKoTwL8CngPsPer8hwMokSYoOeb35VI7d/Y+yR5IkSZIkCYDS8jT3\nT18CwFdHDSA3KyNykZq63KwMbr2g8saK35mxhF1FpZGLpPrniIfqEEI3Ko/peDZJktkASZJsBj4M\nDAJWALuBp4BJSZLcc9C7twN2HuZldxz09vf7uFeHEGaHEGZv3Xq4i7wlSZIkSZLgt39fw5odRfTN\nb84lJ3ePnSMBMGZIJz7ctz27isp44NmlsXOkeueIhuoQQgvgT0A5cOVBf58P/B7YD3wMGAl8C/h6\nCOHmmghNkuSxJEmGJUkyLD8/vyZeUpIkSZIkNTJFpeU8+NwyAG46v4DMjKP9ZXKpZoUQuG3CYFIB\nfv7aapZu3hs7SapXqv3VOoSQB0wG+gJjkiRZd9CbJwK9q/7+qaqbLt4G3At8M4TQoep5O4G2h3n5\nd6+k3nGYt0mSJEmSJFXL47NWsW1fCUO7t2bscZ1j50j/YFCXVlx2Wk8q0gl3Pr2AJEliJ0n1RrWG\n6hBCFvAkMAy4IEmSdw55yvHA8iRJDj3W43Ugi/89e3o+0CeE0OyQ5w0GSoFlR9AuSZIkSZL0np37\nS/nhi8sBuHlsISGEyEXS/3X96IG0ys3k5aXbeH7Rltg5Ur3xgUN1CCEF/BI4F7g4SZLXDvO0TUC/\nEMKhV0t/qOpxfdXjZCqH648f9PqZwCeA6UmSlBxZviRJkiRJUqVHZi5nb0k5Zw3owOn9O3zwO0gR\ntG+Rw1dGDQTgW88spLQ8HblIqh+qc0X1D6gclu8H9ocQhh/05907EvwQyAOmhxAuDSGcF0L4JnAj\n8IckSdYCJEnyJvBb4IEQwlUhhPOA3wB9gNtr9lOTJEmSJElNxcbdB/ifV1YBMHFMYdwY6QNc8eFe\n9Mtvzspt+/lp1X9vpaauOkP1uKrHW4FXD/lzFUDVVdZnAVuBB4E/Ax8F7gQuP+T1rgQep/Jmi88A\nPYCxSZLMOZZPRJIkSZIkNV0PzFhKaXmaC0/owvHdW8fOkf6prIwUXx8/GIDvPbeUbfs8ZEDK/KAn\nJEnSuzovVDVWX1CN5x0Arq/6I0mSJEmSdEyWbdnHE2+sJSMVuGH0wNg5UrWMLOjIOQX5vLh4K/dP\nX8zdHz0hdpIUVbVupihJkiRJklRf3T99MekEPnFqD/rmt4idI1Xb1y8cTGYq8Ju/r2Xe+t2xc6So\nHKolSZIkSVKD9dbaXfxl3iZyMlN85bwBsXOkI9K/Ywuu+HBvkgTufHoBSZLETpKicaiWJEmSJEkN\nUpIkTPrLIgCuPKMPnVrlRi6SjtxXzhtAu+bZvL5yB1Pe2RQ7R4rGoVqSJEmSJDVILy/dxqsrttMq\nN5PPj+gXO0c6Kq2bZXF91dnq/zVlIcVlFZEBRM+AAAAgAElEQVSLpDgcqiVJkiRJUoOTTifcM63y\naurPn9Of1s2yIhdJR++y03pS2Lkl63cd4EcvrYidI0XhUC1JkiRJkhqcKfM2Mm/9Hjq1yuHTp/eO\nnSMdk4xU4LYJgwF4+MXlbNpdHLlIqnsO1ZIkSZIkqUEpq0hz37TFAHzlvIHkZWdELpKO3en9OjB2\nSGcOlFUwaeqi2DlSnXOoliRJkiRJDcrvZq9l1fYi+nRozseHdY+dI9WY/7hgENkZKf7w5nrmrNkZ\nO0eqUw7VkiRJkiSpwThQWsGDzy4F4IbzB5KV4bShxqNn+2ZcdVYfAO6cvIB0OolcJNUdv5pLkiRJ\nkqQG4/FXVrJlbwnHd2vNBcd1iZ0j1bgvjOxPfssc3lq7iz++tT52jlRnHKolSZIkSVKDsLuojB++\nuByAiWMLSKVC5CKp5rXIyeTmsYUATJq6iP0l5ZGLpLrhUC1JkiRJkhqER2YuZ09xOWf0b89ZA/Jj\n50i15qMndWNo99Zs3lPCI1U/nJEaO4dqSZIkSZJU723aXczjs1YCMHFMYeQaqXalUoHbJgwB4LGX\nV7B2R1HkIqn2OVRLkiRJkqR678HnllJSnmbccZ0Z2qNN7Byp1p3Sqy0fObErpeVp7v7Lwtg5Uq1z\nqJYkSZIkSfXaiq37+N3stWSkAjeOKYidI9WZW8YVkpeVwZR3NvHaiu2xc6Ra5VAtSZIkSZLqtfun\nL6EinfDxU7rTL79F7BypznRpncc1I/oBcMfkBVSkk8hFUu1xqJYkSZIkSfXW3HW7eOadjeRkpvjK\nqAGxc6Q6d/XZfenWJo+FG/fwu9lrY+dItcahWpIkSZIk1Vv3TlsMwKdP702X1nmRa6S6l5edwS3j\nKm8get+0xewpLotcJNUOh2pJkiRJklQvzVq2jZeXbqNlbiafP6df7BwpmvEndOHU3m3Zvr+U7z+3\nNHaOVCscqiVJkiRJUr2TJAmTpi4C4JoR/WjTLDtykRRPCIHbJwwhBHh81ipWbN0XO0mqcQ7VkiRJ\nkiSp3pk6bxNz1+0mv2UOV57RO3aOFN1x3Vpz6Sk9KE8n3PXMwtg5Uo1zqJYkSZIkSfVKeUWae6dX\nnk395fMG0Cw7M3KRVD/cOKaAFjmZPLdoCzOXbI2dI9Uoh2pJkiRJklSvPPnGOlZs3U+v9s345Kk9\nYudI9UZ+yxy+eG5/AL759ALKKtKRi6Sa41AtSZIkSZLqjeKyCh54tvJmcTecX0BWhtOFdLArz+hN\nr/bNWLZlH794bXXsHKnG+NVekiRJkiTVGz99ZRWb9hQzuEsrxh/fJXaOVO/kZGZw6wWDAPjujCXs\n2F8auUiqGQ7VkiRJkiSpXth9oIyHX1wOwMSxBaRSIXKRVD+NHtyJM/t3YE9xOd+dsSR2jlQjHKol\nSZIkSVK98OjM5ew+UMbwvu0YMTA/do5Ub4UQ+Mb4waQC/PJvq1m0aU/sJOmYOVRLkiRJkqTotuwp\n5r9nrQRg4thCQvBqaumfKejckn8b3ot0UnljxSRJYidJx8ShWpIkSZIkRfe955dSXJbm/MGdOLln\n29g5UoNw3aiBtM7LYtay7cxYsDl2jnRMHKolSZIkSVJUq7bt5zevryUV4KYxBbFzpAajbfNsrhs1\nAIC7piykpLwicpF09ByqJUmSJElSVPfPWEJ5OuGSk7szoFPL2DlSg3L58F7079iC1duLeHzWqtg5\n0lFzqJYkSZIkSdHMW7+byW9vIDszxVdHD4ydIzU4WRkpvjF+MADff24pW/YWRy6Sjo5DtSRJkiRJ\niuaeaYsBuGJ4L7q1yYtcIzVMIwbmc15hR/aXVnBf1f+mpIbGoVqSJEmSJEXxyvJtvLRkKy1zMvnC\nyP6xc6QG7dYLB5GVEXjijXW8s2537BzpiDlUS5IkSZKkOpckCfdMrbzy8+qz+9KueXbkIqlh65vf\ngk+f3pskgTsmzydJkthJ0hFxqJYkSZIkSXVu2vzNvLV2Fx1aZPOZM/vEzpEahS+dN4D2zbOZvXon\nT8/dGDtHOiIO1ZIkSZIkqU6VV6S5b3rl1dRfOncAzXMyIxdJjUOr3CxuHFMAwN1TFnKgtCJykVR9\nDtWSJEmSJKlO/f7N9Szbso8e7fK47LSesXOkRuXSYT0Y3KUVG3YX89hLK2LnSNXmUC1JkiRJkupM\ncVkFD8xYAsANowvIznSakGpSRipw+4TBADwycxkbdh2IXCRVj98NJEmSJElSnfnFa6vZsLuYws4t\nuWho19g5UqP0ob7tufD4LhSXpZk0dVHsHKlaHKolSZIkSVKd2FNcxg9eWAbAzWMLSaVC5CKp8bpl\nXCHZmSn+9NYG3li9I3aO9IEcqiVJkiRJUp340Usr2FlUxmm923FOQX7sHKlR69GuGZ87uy8Ad0xe\nQDqdRC6S/jmHakmSJEmSVOu27i3hxy+vBODmcQWE4NXUUm27ZkQ/OrXKYe663Tw1Z13sHOmfcqiW\nJEmSJEm17qHnl3KgrIJRgzpxSq92sXOkJqF5Tia3jCsE4J5pi9lXUh65SHp/DtWSJEmSJKlWrdle\nxK9eX0MIcNOYgtg5UpPykaHdOLFHG7buLXnvjHipPnKoliRJkiRJteo7MxZTVpHwLyd1o6Bzy9g5\nUpOSSgVunzAYgJ+8vJI124siF0mH51AtSZIkSZJqzYINe/jT2xvIzkhx3aiBsXOkJumknm356End\nKK1Ic9eUBbFzpMNyqJYkSZIkSbXm3mmLSBK4fHhPerRrFjtHarImji0kLyuDafM388qybbFzpP/D\noVqSJEmSJNWKv63YzguLt9I8O4NrR/aPnSM1aZ1b53LtyH4A3Pn0Asor0pGLpH/kUC1JkiRJkmpc\nkiRMmroIgM+e3ZcOLXIiF0m66qy+dGuTx6JNe/nN39fGzpH+gUO1JEmSJEmqcc8u3MKcNbto1zyb\nq87qGztHEpCblcGtFw4C4P7pi9ldVBa5SPpfDtWSJEmSJKlGVaQT7p1WeTX1F0f2p0VOZuQiSe8a\nd1xnTuvTjp1FZTz43NLYOdJ7HKolSZIkSVKN+sOb61myeR/d2uRx+fCesXMkHSSEwO0TBhMC/OzV\nVSzbsi92kgQ4VEuSJEmSpBpUUl7Bd2csAeD60QPJycyIXCTpUEO6tuaTp/agPJ3wrWcWxM6RAIdq\nSZIkSZJUg3752hrW7zpAQaeWXHxSt9g5kt7HDecX0DInkxcXb+WFRVti50gO1ZIkSZIkqWbsLS7j\noReWAXDTmAIyUiFykaT306FFDl8+bwAA33xmAaXl6chFauocqiVJkiRJUo348csr2bG/lGG92nLe\noI6xcyR9gH8/vTd9OjRnxdb9/OzVVbFz1MQ5VEuSJEmSpGO2bV8JP355BQA3jyskBK+mluq77MwU\nX79wEAAPPreU7ftKIhepKXOoliRJkiRJx+yh55exv7SCcws7cmrvdrFzJFXTuYUdOXtgPnuLy/lO\n1Y1QpRgcqiVJkiRJ0jFZu6OIX/5tNSFUnk0tqeEIIfCNCweRkQr8+vU1LNy4J3aSmiiHakmSJEmS\ndEy+++wSyioSLj6xG4O6tIqdI+kIDejUkk8N70U6gTsnLyBJkthJaoIcqiVJkiRJ0lFbtGkPf3hz\nPVkZgetGDYydI+kofXXUANo0y+LVFduZNn9T7Bw1QR84VIcQPhZC+GMIYW0I4UAIYXEI4e4QQsvD\nPHd4CGFqCGFXCGF/COGdEMInD3lObgjh3hDCxqrXezWEcHZNflKSJEmSJKlu3DdtMUkC/3paT3q2\nbxY7R9JRatMsmxtGV/6w6a4pCykuq4hcpKamOldU3whUAF8DxgGPAJ8HZoQQ3nv/EMKFwEvAJuBf\ngY8APwJyD3m9nwCfBW4DxgMbgWkhhBOP6TORJEmSJEl1avaqHTy7cAvNsjP44rkDYudIOkaXndaT\ngk4tWbvjAD/568rYOWpiMqvxnAlJkmw96J9fDCHsAH4KnAM8X3V19ePAw0mSfPWg5z578AuFEIZS\nOWJ/JkmSx6v+biYwH7gTuOhoPxFJkiRJklR3kiRh0tRFAFx1Zh/yW+ZELpJ0rDIzUtw2YTCX//hv\n/OCFZXzslO50anXoNahS7fjAK6oPGanf9feqx25Vjx8H8oH7P+DlLgLKgN8e9PrlwG+AMSEEv6tJ\nkiRJktQAvLB4C39ftZO2zbL47Nl9Y+dIqiFn9O/A6MGdKCqt4J6pi2PnqAk52pspjqh6XFj1eCaw\nAzi+6lzq8qozrW8PIWQc9H5DgJVJkhQd8nrzgWyg/1H2SJIkSZKkOpJOJ+8NWNeO7E/L3KzIRZJq\n0q0XDCI7I8VTc9bx9tpdsXPURBzxUB1C6EblMR3PJkkyu+qvuwLNgF8B/wOMovJokG8A9x307u2A\nnYd52R0Hvf39Pu7VIYTZIYTZW7ce7iJvSZIkSZJUF/709noWbdpL19a5/NvwXrFzJNWw3h2ac+WZ\nvQG4Y/J8kiSJG6Qm4YiG6hBCC+BPQDlw5SGvkwvcmSTJ/UmSvJgkydepvJnitSGE1scamiTJY0mS\nDEuSZFh+fv6xvpwkSZIkSToKpeVp7p++BICvjh5IblbGB7yHpIboiyP706FFDnPW7OLPb2+InaMm\noNpDdQghD5gM9AXGJEmy7qA3b696nHHIu00HsoDBVf+8E2h7mJd/90rqHYd5myRJkiRJqid+/foa\n1u08wICOLbjk5O6xcyTVkpa5WUwcUwDA3VMWUVRaHrlIjV21huoQQhbwJDAMuCBJkncOecr8an68\n+UCfEEKzQ/5+MFAKLKvm60iSJEmSpDq2v6Sc7z+/FIAbxxSQkQqRiyTVpo+d0p3jurVi055ifjhz\nRewcNXIfOFSHEFLAL4FzgYuTJHntME/7Y9XjmEP+fixQDLw7bE+m8grrjx/0+pnAJ4DpSZKUHFG9\nJEmSJEmqMz/560q27SvlpJ5tOH9wp9g5kmpZKhW4fcIQAB6duZx1O4siF6kxy6zGc35A5bB8F7A/\nhDD8oLetS5JkXZIk80II/wPcWTVsz6HyhopXAd9MkmQfQJIkb4YQfgs8UHWV9krg80Af4PKa+qQk\nSZIkSVLN2r6vhMdeqryi8uaxhYTg1dRSU3Bq73aMP6ELT8/dyLf/soiH/vXk2ElqpKpz9Me4qsdb\ngVcP+XPVQc/7HPAd4EvAFOCjwPVJkvznIa93JfA48C3gGaAHMDZJkjlH9ylIkiRJkqTa9vCLy9lX\nUs6IgfkM79s+do6kOvS1CwaRk5ni6bkbeX2lt5hT7fjAoTpJkt5JkoT3+fOfBz2vNEmSrydJ0iNJ\nkuwkSQYmSfLgYV7vQJIk1ydJ0jlJktwkST6UJMmLNftpSZIkSZKkmrJ+1wF+/upqACaOLYhcI6mu\ndWuTx+dG9APgjsnzqUgnkYvUGFXrZoqSJEmSJKnp+u6MJZRWpLloaFeGdG0dO0dSBNeM6EuX1rnM\n37CHJ99YGztHjZBDtSRJkiRJel9LNu/l93PWkZkKXD96YOwcSZE0y87klnGFANw7bTF7i8siF6mx\ncaiWJEmSJEnv675pi0kncNlpPendoXnsHEkRXTS0K6f0asu2faU89Pyy2DlqZByqJUmSJEnSYb2x\neifTF2wmLyuDL53bP3aOpMhCCNw2fjAA/z1rJSu37Y9cpMbEoVqSJEmSJP0fSZIwaeoiAD5zZm86\ntsqNXCSpPhjaow0fO6U7ZRUJdz2zMHaOGhGHakmSJEmS9H/MXLKV11fuoE2zLD43ol/sHEn1yMQx\nBTTPzuDZhZt5eenW2DlqJByqJUmSJEnSP0inEyZNXQzAF87pR6vcrMhFkuqTjq1yubbqOKBvPr2A\n8op05CI1Bg7VkiRJkiTpH0yeu4GFG/fQpXUuV3y4d+wcSfXQZ87oQ492eSzZvI9fvb4mdo4aAYdq\nSZIkSZL0ntLyNPdPXwLAV0cNIDcrI3KRpPooNyuDWy+ovLHid2YsYVdRaeQiNXQO1ZKanC17innq\njXWUlFfETpEkSZLqnd/+fQ1rdhTRN785l5zcPXaOpHpszJBOfLhve3YVlfHAs0tj56iBc6iW1KSU\nlFdw+Y//xg1PvM3XnnqHJEliJ0mSJEn1RlFpOQ8+twyAm84vIDPD2UDS+wshcNuEwaQC/Py11Szd\nvDd2khowv+NIalK+99xSlm7ZB8Dv31zPf89aFTdIkiRJqkcen7WKbftKGNq9NWOP6xw7R1IDMKhL\nKy47rScV6YQ7n17gBWE6ag7VkpqMuet28cOZKwgBrhnRD4D/mrKQWcu2RS6TJEmS4tu5v5Qfvrgc\ngJvHFhJCiFwkqaG4fvRAWuVm8vLSbTy/aEvsHDVQDtWSmoSS8gpuemIuFemE/3dGH24ZV8i1I/tR\nkU649ldzWLujKHaiJEmSFNUjM5ezt6ScswZ04PT+HWLnSGpA2rfI4SujBgLwrWcWUlqejlykhsih\nWlKT8NDzy1i8eS99OjTnhvMLALh+dAHnFnZkV1EZn/3ZbIpKyyNXSpIkSXFs3H2A/3llFQATxxTG\njZHUIF3x4V70y2/Oym37+WnV1xPpSDhUS2r05q3fzcMvLicEuOdjJ5CXnQFARirwwCdPpG+H5iza\ntJebnpjrWVqSJElqkh6YsZTS8jQXntCF47u3jp0jqQHKykjx9fGDgcr7Q23bVxK5SA2NQ7WkRq20\nPM2NT7xNRTrhytP7cGrvdv/w9la5WTx2xTBa5GTyzDsbeWTm8kilkiRJUhzLtuzjiTfWkpEK3DB6\nYOwcSQ3YyIKOjCzIZ29JOfdPXxw7Rw2MQ7WkRu2hF5axaNNeerVvxk1jCg77nP4dW/DAJ04kBLh3\n2mJe8MYPkiRJakLun76YdAKfOLUHffNbxM6R1MB9ffxgMlOB3/x9LfPW746dowbEoVpSozVv/W4e\nfmFZ5QD9saHvHflxOKMGd+L6UQNJEvjyb95kxdZ9dVgqSZIkxfHW2l38Zd4mcjJTfOW8AbFzJDUC\n/fJbcMWHe5MkcOfTCzxiU9XmUC2pUSotT3PTk3MpTyf8+4d7c1qfdh/4PteO7M/YIZ3ZW1zO1T9/\ng73FZXVQKkmSJMWRJAmT/rIIgCvP6EOnVrmRiyQ1Fl85bwDtmmfz+sodTHlnU+wcNRAO1ZIapYdf\nXMbCjXvo2a4ZE8ce/siPQ6VSgfsvHUpBp5Ys27KP6377Num0P/mVJElS4/Ty0m28umI7rXIz+fyI\nfrFzJDUirZtlcX3Vmff/NWUhxWUVkYvUEDhUS2p0FmzYw0PPLwPgno+dQLPszGq/b/OcTB674hRa\n52Xx7MLNPPDc0trKlCRJkqJJpxPumVZ5NfXnz+lP62ZZkYskNTaXndaTws4tWb/rAD96aUXsHDUA\nDtWSGpWyijQ3PvF21ZEfvRjet/0Rv0av9s35/mUnkQrwveeWMnWev6YkSZKkxmXKvI3MW7+HTq1y\n+PTpvWPnSGqEMlKB2yYMBuDhF5ezaXdx5CLVdw7VkhqVR15czoKNe+jRLo+JYwuP+nXOHpjPLeMq\n3/+G373Fks17aypRkiRJiqqsIs190xYD8JXzBv7Tm45L0rE4vV8Hxg7pzIGyCiZNXRQ7R/WcQ7Wk\nRmPhxj18//nKozomXXICzXOqf+TH4Xz2rL5cNLQr+0sr+OzPZrO7yJsrSpIkqeH73ey1rNpeRJ8O\nzfn4sO6xcyQ1cv9xwSCyM1L84c31zFmzM3aO6jGHakmNQllFmpuefJuyioRPDe/F6f06HPNrhhCY\ndMkJDOnaitXbi/jir+dQ4c0VJUmS1IAdKK3gwWcrL+648fwCsjKcBSTVrp7tm3HVWX0AuGPyAtL+\ne7Xeh9+RJDUKj85czrz1e+jeNu+9IztqQl52Bo9+6hTaNc/m5aXb3rvhjCRJktQQPf7KSrbsLeH4\nbq0Zd1zn2DmSmogvjOxPfssc3l67iz++tT52juoph2pJDd7iTXt58LnKq0LuqYEjPw7VvW0zHr78\nZDJSgUdnruBPflOVJElSA7S7qIwfvrgcgIljC0ilQuQiSU1Fi5xMbq66j9S3/7KI/SXlkYtUHzlU\nS2rQyivS3PhE5ZEfl3+oJ6f3P/YjPw5neN/23Da+8m7FNz81l3nrd9fKx5EkSZJqyyMzl7OnuJwz\n+rfnrAH5sXMkNTEfPakbQ7u3ZsveEh6p+qGZdDCHakkN2qMvreCd9bvp1iaPr10wqFY/1hUf7sWl\nw7pTXJbmcz9/g+37Smr140mSJEk1ZdPuYh6ftRKAiWNq7qg8SaquVCpw24QhADz28grW7iiKXKT6\nxqFaUoO1eNNeHnh2CQCTLjmBFjV85MehQgh88+LjOLFHG9bvOsC1v5pDWUW6Vj+mJEmSVBMefG4p\nJeVpxh3XmaE92sTOkdREndKrLR85sSul5Wnu/svC2DmqZxyqJTVI5RVpbnqy8siPy07ryZkDaufI\nj0PlZFbeXDG/ZQ6vrdjBXc/4jVWSJEn124qt+/jd7LVkpAI3jimInSOpibtlXCF5WRlMeWcTr63Y\nHjtH9YhDtaQG6bGXVzB33W66ts7lPy6o219d7NQqlx/+2ylkZ6T4n1dW8bvZa+v040uSJElH4v7p\nS6hIJ3z8lO70y28RO0dSE9eldR7XjOgHwB2TF1CRTiIXqb5wqJbU4CzdvJcHZiwF4NuXnEDL3Kw6\nbzilV1vu/Ejl2Vpf/8M83lyzs84bJEmSpA8yd90unnlnIzmZKb4yakDsHEkC4Oqz+9KtTR4LN+7h\nt3/34i9VcqiW1KCUV6S58cm5lFak+eSpPTh7YLy7lX/ytJ58angvSivSXPOLN9iypzhaiyRJknQ4\n905bDMCnT+9Nl9Z5kWskqVJedga3jKv87ej7py9mT3FZ5CLVBw7VkhqUH/91JW+v3UWX1rn8x4WD\nYudw24TBnNanHZv3lHDNL96gpLwidpIkSZIEwKxl23h56TZa5mby+XP6xc6RpH8w/oQunNq7Ldv3\nl/L955bGzlE94FAtqcFYtmUv35mxBIC7P3o8rSIc+XGorIwUD19+Ml1b5zJnzS7+88/zSRLP15Ik\nSVJcSZIwaeoiAK4Z0Y82zbIjF0nSPwohcPuEIYQAj89axYqt+2InKTKHakkNQkU64cYn5lJanubS\nYd05p6Bj7KT3dGiRw6OfGkZOZopfv76WX/5tTewkSZIkNXFT521i7rrd5LfM4cozesfOkaTDOq5b\nay49pQfl6YS7nlkYO0eROVRLahB+8tcVvLV2F51b5XLrhYNj5/wfx3dvzaRLTgDgP/88n9dX7ohc\nJEmSpKaqvCLNvdMrz6b+8nkDaJadGblIkt7fjWMKaJGTyXOLtjBzydbYOYrIoVpSvbdsyz7um151\n5Mclx9M6L/6RH4dz8Und+OxZfShPJ3zhl2+wYdeB2EmSJElqgp58Yx0rtu6nV/tmfPLUHrFzJOmf\nym+Zw5fO7Q/AN59eQFlFOnKRYnGollSvVaQTJj75NqXlaT5+SndG1qMjPw7n5rGFnNm/A9v2lfK5\nn79BcZk3V5QkSVLdKS6r4IFnK29KdsP5BWRl+K/9kuq/T5/Rm17tm7Fsyz5+8drq2DmKxO9Ykuq1\nx2etZM6aXXRqlcPXx9e/Iz8OlZmR4vuXnUSPdnm8s343X/v9O95cUZIkSXXmp6+sYtOeYoZ0bcX4\n47vEzpGkasnJzODWCwYB8N0ZS9ixvzRykWJwqJZUb63Yuo97p1WerXf3R+vvkR+Hats8mx9dMYy8\nrAz+8OZ6fvLXlbGTJEmS1ATsPlDGwy8uB2Di2EJSqRC5SJKqb/TgTpzZvwN7isv57owlsXMUgUO1\npHqp8siPuZSUp7nk5O6cW9gpdtIRKezcivsvHQrAf01ZyF+XbotcJEmSpMbu0ZnL2X2gjOF923H2\ngA6xcyTpiIQQ+Mb4waQC/PJvq1m0aU/sJNUxh2pJ9dL/vLKK2at30rFlDrc1gCM/DueC47vwxZH9\nSSfwxV/PYc32othJkiRJaqS27Cnmv2dV/ibfxLGFhODV1JIanoLOLfm34b1IJ5U3VvQozabFoVpS\nvbNy237unbYIgP/6l+Np3axhHPlxONePHsi5hR3ZVVTG1T+fTVFpeewkSZIkNULfe34pxWVpxgzp\nxMk928bOkaSjdt2ogbTOy2LWsu3MWLA5do7qkEO1pHolnU6Y+OTbFJel+ehJ3Rg1uGEd+XGoVCrw\nwCdPpG9+cxZt2stNT8z1J8KSJEmqUau27ec3r68lFeDG8wti50jSMWnbPJvrRg0A4K4pCykpr4hc\npLriUC2pXvnpq6v4+6qd5LfM4bYJDfPIj0O1ys3isU8No2VOJs+8s/G9G9xIkiRJNeH+GUsoTydc\ncnJ3BnRqGTtHko7Z5cN70b9jC1ZvL+LxWati56iOOFRLqjdWbdvPpKn/e+RHm2bZkYtqTv+OLXjg\nkycSAtw3fTHPL/LXlyRJknTs5q3fzeS3N5CdmeKrowfGzpGkGpGVkeIbVfer+v5zS9mytzhykeqC\nQ7WkeiGdTpj41FyKy9JcfGJXRjfwIz8O57xBnbh+1ECSBL7y67dYvnVf7CRJkiQ1cPdMWwzAFcN7\n0a1NXuQaSao5Iwbmc15hR/aXVnBf1dc6NW4O1ZLqhZ+/tprXV+6gQ4scbp8wJHZOrfniuf0Zd1xn\n9paUc/XPZrO3uCx2kiRJkhqoV5Zv46UlW2mZk8kXRvaPnSNJNe7WCweRlRF44o11vLNud+wc1TKH\naknRrdlexLf/Unnkx13/chxtmzeeIz8OFULgvo8PpaBTS5Zv3c91v32LdNqbK0qSJOnIJEnCPVMr\nrzC8+uy+tGvE/x9aUtPVN78Fnz69N0kCd0yeT5L478+NmUO1pKgqj/x4mwNlFVw0tCtjhnSOnVTr\nmudk8tgVp9A6L4tnF27hgeeWxk6SJElSAzNt/mbeWruLDi2y+cyZfWLnSFKt+dJ5A2jfPJvZq3cy\nee7G2DmqRQ7VkqL65d9W89qKHXRokVOMLWEAACAASURBVM1/XtR4j/w4VK/2zXnoX08iFeB7zy1l\n6jy/2UqSJKl6yivS3De98mrqL507gOY5mZGLJKn2tMrN4sYxBQB8e8pCDpRWRC5SbXGolhTN2h1F\n3F115Me3Lj6uyf264lkD8vnauEEAXP+7t1m8aW/kIkmSJDUEv39zPcu27KNHuzwuO61n7BxJqnWX\nDuvB4C6t2LC7mEdfWh47R7XEoVpSFOl0wsQn51JUWsH4E7ow9rgusZOiuOqsPlx8YleKSiu4+uez\n2VVUGjtJkiRJ9VhxWQUPzFgCwA2jC8jO9F/rJTV+GanA7RMGA/DDmcvZsOtA5CLVBr+jSYril6+v\n4dUV22nfPJs7mtCRH4cKIfDtS07guG6tWL29iC/9+k0qvLmiJEmS3scvXlvNht3FFHZuyUVDu8bO\nkaQ686G+7bnw+C4Ul6X5dtVvZ6txcaiWVOfW7iji7ikLAfjmxcfRvkVO5KK4crMyePRTw2jfPJuX\nl27jnql+w5UkSdL/tae4jB+8sAyAm8cWkkqFyEWSVLduGVdIdmaKP7+9gdmrdsTOUQ1zqJZUp5Ik\n4eanKo/8uPD4LlxwfNM88uNQ3drk8YPLTyYzFXj0pRX86a31sZMkSZJUz/zopRXsLCrjtN7tOKcg\nP3aOJNW5Hu2a8bmz+wJwx+QFpP2N5EbFoVpSnfrV62t4Zfl22jXP5o6PNN0jPw5neN/23FZ15tbN\nT81l3vrdkYskSZJUX2zdW8KPX14JwM3jCgjBq6klNU3XjOhHp1Y5vLN+N0/NWRc7RzXIoVpSnVm3\ns4j/eqbyyI87PzKEDk38yI/D+dTwXlw6rDvFZWk+9/M32L6vJHaSJEmS6oGHnl/KgbIKRg3qxP9n\n776jo67yPo5/7qT3kEILBBJ6bxEQsBewgNi7+7iPomvZdV3F3rvYdu26++yuZdW1odhQ7KCAdAgk\nlAQCCSGN9J65zx8zsIQFCSX8Mpn365ycQH53Jp85R0nyyf1976gecU7HAQDHRIQE6tZT+kuSHp+d\nqcq6RocT4VChqAZwWFhrdev7K1VV36RTBnfWaYz82CNjjB6YOlgjkmOVW1qja95cooYmt9OxAAAA\n4KCc4mr9a2GOjJFuntjP6TgA4LgzhiVpePdYFVbU7ZzdD9+3z6LaGHOOMWamMWazMabGGJNpjHnE\nGBP1K495yRhjjTFv7OFaqDFmhjFmq/f5fjbGHH2wLwRA2/b2L5s1d32ROoQH6f4zBnOr4q8ICQzQ\nS5eMUseoEC3ILtFD3l3oAAAA8E9PfZWphiars0Z0U7/Oe/1RHAD8hstldI93dObffsxWTnG1w4lw\nKLRkR/VNkpok3SbpFEkvSvqdpK+MMf/1eGPMeEmXSCrfy/P9TdKVku6WdLqkrZJmG2OG73d6AD4h\nt7RmZ9l63xmDlRjFyI996RQdqpcuHaXgAJf+8dNG/XvRZqcjAQAAwAGr88r10fI8BQe4dMOJfZyO\nAwBtxojkDjprRJLqm9x66LPVTsfBIdCSonqytfZsa+0b1trvrLXPSPq9pDGSjt11oTEmSNLLkh6S\ntH33JzLGDJN0kaQ/WmtftdZ+Lek8STmS7j+oVwKgTfKM/FihyrpGTRzUSZOHMvKjpUYmd9ADUz0H\nTt754Sotzfmvf1YBAADQzs2YnSFrpYvHJqt7XLjTcQCgTZk+qb/CgwM0O32bflpf5HQcHKR9FtXW\n2sI9fPgX7/uk3T5+s6QASU/s5emmSGqQ9M4uz98o6W1JE40xbLME2pl/L9qsH9cVKTY8SA9MZeTH\n/jr/iGRddmQP1Te5dfUbi1VQXut0JAAAABwmC7KK9W1moSKCA3Tdcb2djgMAbU7nmFBdc2wvSdL9\nn6xWI2c8+bQDPUzxGO/7nYNTjTG9Jd0p6RprbcNeHjdIUra1dvfBMemSgiXxlRdoR/JKa/TgJ96R\nH1MGqWNUqMOJfNNdpw/U6JQ4bSuv09VvLFZdY5PTkQAAANDKrLV67IsMSdKVR6cqPpJ9XQCwJ1cc\nlaqk2DBl5Ffo7V8Ym+nL9ruoNsYkyTOmY461dtEul16U9IG19ttfeXic9jASRFLJLtf39nmnGWMW\nGWMWFRbuaZM3gLbEWqvbPlipirpGnTSwk6YM6+p0JJ8VFODSCxePVNeYUC3JKdU9H6XLWut0LAAA\nALSiOWsKtCSnVPERwbriqFSn4wBAmxUaFKA7ThsgSXryy0yVVe9t/yzauv0qqo0xkZI+ktQo6fJd\nPn6JpCMk/emQptuFtfYVa22atTYtMTGxtT4NgEPk3cVb9P3aQsWEBekhRn4ctITIEL18aZpCAl16\n+5fNemNBjtORAAAA0Eqa3FYzZnt2U193fG9FhgQ6nAgA2rZTBnfW6JQ4ba9u0J+/Xud0HBygFhfV\nxpgwSbMkpUqaaK3d4v14pKSnJD0mqc4YE2uMifU+d5D370Hep9kuqcMenn7HTuqSPVwD4GO2ltXo\ngU88J+7eO2WgOkYz8uNQGNItRo+dPVSSdN/H6VqQVexwIgAAALSGD5fmau22SiXFhumiMclOxwGA\nNs8Yo3smD5Qx0ms/b9T6gkqnI+EAtKio9hbN70lKk3SqtXblLpcTJCVKelieInrHW3dJ53n/fJp3\nbbqkFGPM7kcVD5RUL2n9gb0MAG2FtVa3f7BSFbWNOnFAR00dvvuZqzgYU0ck6cqjUtTotrrmzSXK\nK61xOhIAAAAOobrGJj391VpJ0o0n9VVIYIDDiQDANwzqGqMLjuiuRrfVg5+udjoODsA+i2pjjEvS\nm5KOlzTVWjt/tyX5ko7bw9s2SXO8f57rXTtLUpCkc3d5/kBJ50v60lpbdzAvBoDz3l+Sq28zCxUd\nGqiHzxzCyI9WcMuk/jqqT4KKq+p11euLVdvA4YoAAADtxZvzc5RbWqN+naI0dQSbPgBgf/zp5H6K\nCgnUd5mF+jajwOk42E8t2VH9vDzF8pOSqowxY3d562atrbXWfrf7m6RaSdu8fy+SJGvtUknvSHrG\nGHOFMeYESW9LSpF0T2u8QACHT35Zre6blS5JunfKIEZ+tJLAAJeevXCEkuPCtTK3TLd9sJLDFQEA\nANqBitoGPfet50bjmyf2U4CLTR8AsD8SIkP0+xP6SJIe+HS16hvdDifC/mhJUX2K9/0dkn7e7e2K\nA/icl0v6u6QHJX0qz4iQSdbaJQfwXADaCGutbv/QM/LjhP4ddSa7P1pVbHiwXrlslMKDA/Th0lz9\nbW6205EAAABwkP76Y7ZKquqV1qODThjQ0ek4AOCTfjOup1ISIpRVWKXXft7odBzsh30W1dbantZa\ns5e3e/fxuEv28PEaa+2N1trO1tpQa+0Y7w5sAD7sw6W5+iajwDPy4yxGfhwO/TtH68lzh0mSHv5s\njeauK3I4EQAAAA5UUWWd/vpjliTpllP68/00AByg4ECX7jxtgCTpz1+vU3Elk4Z9RYsOUwSAX1NQ\nXqt7P/aM/Lh78iB1YuTHYXPKkC66/vjeclvpureWKKe42ulIAAAAOADPfbNeVfVNOr5/Rx3RM87p\nOADg047v31FH901URW2jnvQeUIu2j6IawEHZMfKjvLZRx/VL1NkjGflxuP3xxL46oX9HlVY3aNrr\ni1RV1+h0JAAAAOyHzSXVenPBJhnjmU0NADg4xhjdddoABbiM3l6Yo9V55U5HQgtQVAM4KB8ty9Oc\nNQWKCg3UI2cN5RZFB7hcRk9fMFypiRHKyK/Qze8t53BFAAAAH/L0nLVqaLKaOjxJA7pEOx0HANqF\nPp2idOnYHnJb6f5P0vk52QdQVAM4YAUVtbrHO/LjrtMHqnMMIz+cEh0apFcvS1NUSKA+W5mvF77b\n4HQkAAAAtEBGfrk+XJqroACjP57Y1+k4ANCu3HBiH8WGB2l+Volmp+c7HQf7QFEN4IBYa3XHh6tU\nVtOgY/om6txR3ZyO5Pd6JUbqmQuGyxjpiS8z9U3GNqcjAQAAYB+emJ0pa6WLRicrOT7c6TgA0K7E\nhgfrTyd5fgn44KdrVNvQ5HAi/BqKagAH5OPlefpq9TZFhQTqkbOGMPKjjThhQCf96aS+slb6w1vL\ntKGw0ulIAAAA2ItFG0s0Z02BwoMDdN3xfZyOAwDt0oWjk9WvU5S2bK/R3+ZmOx0Hv4KiGsB+K6yo\n2zny487TB6hrbJjDibCra4/rrVMGd1ZFXaOufG2RymsbnI4EAACA3Vhr9dgXGZKkKyakKDEqxOFE\nANA+BQa4dPfkgZKk579dr23ltQ4nwt5QVAPYL9Za3TlzpUqrG3RUnwSdl9bd6UjYjTFGT5w7TP06\nRSmrsEo3vrNMbjeHRgAAALQl32YW6JeN29UhPEhXHp3qdBwAaNfG907QSQM7qbq+SY9/kel0HOwF\nRTWA/TJrxVbNTt+myJBAPXr2UEZ+tFERIYF65bJRigkL0pw1BXpmzlqnIwEAAMDL7bY7i5Jrj+ut\nqNAghxMBQPt3x6kDFBzg0vtLtmjZ5lKn42APKKoBtFhhRZ3u+WiVJOmO0wYoiZEfbVqP+Ag9d9EI\nuYz0l2/W64tVW52OBAAAAEkfLc9VRn6FusaE6pKxPZyOAwB+oWdChC6f0FOSdP+sdFnLncdtDUU1\ngBax1uqumau0vbpBE3on6IIjGPnhC47qk6jbThkgSbrx38uVmV/hcCIAAAD/Vt/o1pNfeu52++NJ\nfRUaFOBwIgDwH9cd11sJkSFaklOqj5fnOR0Hu6GoBtAin67cqi/S8xURHKBHzx7CyA8fcsVRKZo6\nvKuq65t05WuLVFpd73QkAAAAv/XWwhxt2V6jPh0jddbIbk7HAQC/EhUapOkT+0mSHvksQ9X1jQ4n\nwq4oqgHsU1Flne7+KF2SdPtpA9StQ7jDibA/jDF69OyhGpwUrZySal3/1lI1NrmdjgUAAOB3quoa\n9ew36yRJN03spwAXmz8A4HA7Z1Q3DUmKUX55rV76PsvpONgFRTWAfbrno3SVVNVrXK94XTQ62ek4\nOAChQQF6+dI0xUcE68d1RXp8NqccAwAAHG5/m5utosp6jUiO1ckDOzkdBwD8kstldPfkgZKkl7/f\noC3bqx1OhB0oqgH8qk9XbNWnK7cqPDhAj509lJEfPiwpNkwvXDxSgS6jV37I0kfLcp2OBAAA4DeK\nK+v0yg+enXu3TOrP99UA4KAjesbp9KFdVNfo1qOfZzgdB14U1QD2qriyTnd/tEqSdNupA9Q9jpEf\nvm5Marzu8f7mePp7K7Qqt8zhRAAAAP7hhe82qLKuUcf0TdTY1Hin4wCA37vt1AEKCXTpkxVbtTC7\nxOk4EEU1gF9xz8fpKq6q15Gp8bqYkR/txiVje+j8tO6qa3TrqtcXq6iyzulIAAAA7VpuaY1e/3mT\nJGn6pH4OpwEASJ67jq86ppck6b5Z6WpyW4cTgaIawB59vnKrPlnhGfnx+DlD5eKgl3bDGKP7pw7S\niORY5ZbW6No3l6iBwxUBAABazdNfrVV9k1tThnXVoK4xTscBAHhdfUyqusSEKj2vXO8t3ux0HL9H\nUQ3gv5RU1esu78iPW0/pz8iPdigkMEAvXTJKHaNCtCC7RA9+strpSAAAAO3S2m0V+mDJFgW6jG48\nqa/TcQAAuwgPDtStp/SXJM2YnamK2gaHE/k3imoA/+Xej9NVVFmvMSlxumRMD6fjoJV0ig7VS5eO\nUnCAS//8eZP+/Qu/PQYAADjUnpidKbeVLhydrJ4JEU7HAQDsZsqwrhrVo4OKKuv13DfrnY7j1yiq\nATTzxap8fbw8T2FBjPzwByOTO+jBqYMlSXfOXKUlOdsdTgQAANB+LN60XV+u3qawoABdf3xvp+MA\nAPbAGKO7Tx8oSfq/ednKLqpyOJH/oqgGsNP2qnrdOdMz8uOWSf3UI54dH/7gvCO667Ije6i+ya2r\nX1+sgvJapyMBAAD4PGutHvsiQ5L02wk91TE61OFEAIC9GdY9VueM6qaGJquHPl3jdBy/RVENYKf7\nZqWrqLJOo3vG6bIjezodB4fRXacP1OiUOBVU1OmqNxarrrHJ6UgAAAA+7fu1hVqYXaLY8CBddUwv\np+MAAPZh+sR+iggO0Jw12/TjukKn4/glimoAkqQv0/M1c1meQoNcjPzwQ0EBLr1w8Uh1jQnV0pxS\n3T0zXdZap2MBAAD4JLfb6rEvMiVJ1xzbS9GhQQ4nAgDsS8foUF3rHdP0wCer1djkdjiR/6GoBqDS\n6nrd4R35MX1ifw558VMJkSF65bI0hQS69M6izXpj/ianIwEAAPikWSvytGZrubrEhHKnIgD4kN+O\nT1H3uDCt3Vapfy3McTqO36GoBqD7Z61WYUWdjujZQf8zrqfTceCgwUkxevycoZKk+2at1oKsYocT\nAQAA+Jb6Rree/HKtJOmGE/soNCjA4UQAgJYKDQrQHad6DlZ86qu1Kq2udziRf6GoBvzcnNXb9MHS\nXO/Ij2GM/IDOGJ6kaUenqtFtdc2bS5RbWuN0JAAAAJ/xzi85yimpVmpihM4e2c3pOACA/TRxUCcd\nmRqv0uoGPTNnndNx/ApFNeDHyqobdPuHKyVJN0/srxRGfsBr+sR+OqpPgoqr6nXV64tU28DhigAA\nAPtSXd+oP3+9XpJ088n9FBjAj9wA4GuMMbp78kC5jPT6/E1au63C6Uh+g6+agB+7/5PVKqioU1oP\nRn6gucAAl569cISS48K1Krdct76/gsMVAQAA9uHv8zaqqLJOw7rFaNLgzk7HAQAcoAFdonXh6GQ1\nua0e+GQ1Pw8fJhTVgJ/6JmOb3l+yRSGBLj1+zlAFMPIDu4kND9arl6UpPDhAM5fl6W9zs52OBAAA\n0GZtr6rXS99tkCTdMqm/jOH7awDwZTee1FfRoYH6cV2Rvl5T4HQcv0BRDfihspoG3fbBjpEf/ZSa\nGOlwIrRV/TpH6anzhkmSHv5sjX5cV+hwIgAAgLbpxe83qKKuUUf1SdC43glOxwEAHKT4yBD94cS+\nkqQHP12t+ka3w4naP4pqwA89+MlqbSuv08jkWF0+PsXpOGjjJg3uouuP7y23la7711LlFFc7HQkA\nAKBN2VpWo3/8tFGSNH1if2fDAAAOmcuO7KFeiRHaWFytf/zEXcatjaIa8DPfZhbo3cVbFBzo0oxz\nhzHyAy3yxxP76oT+HVVW06ArX1ukqrpGpyMBAAC0Gc98tU71jW6dNrSLhnSLcToOAOAQCQpw6c7T\nB0qSnv16vQor6hxO1L5RVAN+pLy2Qbe97xn5cdPJfdWLkR9oIZfL6OkLhis1MUKZ2yp007vLOUwC\nAABA0vqCSr27eLMCXEY3ndzP6TgAgEPsuH4ddVy/RFXUNerJLzOdjtOuUVQDfuShT9Yov7xWI5Jj\n9b8TUp2OAx8THRqkVy9LU1RIoD5fla8XvIcFAQAA+LMnv8yU20rnH9FdKQkRTscBALSCO08fqECX\n0TuLNmtVbpnTcdotimrAT3yXWaB3Fm32jPw4ZygjP3BAeiVG6s8XDpcx0hNfZuqbjG1ORwIAAHDM\nss2l+nxVvkKDXPrDCX2cjgMAaCW9EiP1m3E9Za10/yerucO4lVBUA36gvLZBt33gGflx40l91btj\nlMOJ4MuO799JN53cT9ZKf3hrmTYUVjodCQAA4LCz1uqxzzMkSZePT1Gn6FCHEwEAWtPvT+ijuIhg\nLcwu0Wcr852O0y5RVAN+4OFP12hrWa2GdY/VFRNSnI6DduCaY3vp1CGdVVHXqCtfW6Ty2ganIwEA\nABxWP64r0s9ZxYoODdTVR/dyOg4AoJXFhAXpxpP6SpIe/myNahuaHE7U/lBUA+3cD2sL9fYvmxUc\n4NIT5wxVYAD/2+PgGWM045xh6t85SlmFVfrj28vkdnPrEwAA8A9ut9Xjsz27qX93bG/FhAc5nAgA\ncDhcODpZ/TtHKbe0Rq/+kOV0nHaHxgpoxypqG3Tr+yskSTec1Ed9OjHyA4dOREigXrk0TTFhQfo6\no0BPz1nrdCQAAIDD4rNVW7Uqt1ydokP0P+N6Oh0HAHCYBLiM7p48UJL0wncblF9W63Ci9oWiGmjH\nHv4sQ3lltRraLUbTjkp1Og7aoeT4cD1/0Ui5jPTsN+v1+cqtTkcCAABoVQ1Nbj0xO1OS9IcT+ios\nOMDhRACAw2lcrwRNGtRZNQ1NeuyLDKfjtCsU1UA7NXddkd5amKPgAJdmnDOMkR9oNRP6JOj2UwdI\nkv707nJl5Jc7nAgAAKD1/HvRZm0srlZKQoTOTevmdBwAgANuP3WAggNc+nBprpbkbHc6TrtBcwW0\nQ5V1jbrFO/LjDyf2Ub/OjPxA6/rfCSk6c0SSquubNO21xSqtrnc6EgAAwCFXU9+kP89ZJ0m66eR+\nCmIzCAD4peT4cF1xVIok6b5Zqzmz6RDhqyrQDj3y2RrlltZoSFKMrjqakR9ofcYYPXLWEA1OilZO\nSbWuf2upGpvcTscCAAA4pP7+U7YKKuo0JClGpwzu7HQcAICDrjmutxKjQrR8c6lmLst1Ok67QFEN\ntDPz1hfpzQU5CgowmnHuUEZ+4LAJDQrQy5emKT4iWD+uK9Lj3tmNAAAA7UFZdYNe+m6DJGn6pH5y\nuYzDiQAATooMCdQtk/pLkh79PENVdY0OJ/J9NFhAO1JZ16jp73lGfvz++D7q3zna4UTwN0mxYXrh\n4pEKdBm98kOWZi7lt8oAAKB9ePH7DSqvbdT43vE6qk+i03EAAG3AWSOSNKxbjAoq6vSi95eZOHAU\n1UA78tjnGcotrdGgrtG6+theTseBnxqTGq97Jg+UJN3y/gqtyi1zOBEAAMDByS+r1d/nZUuSpk/s\n73AaAEBb4XIZ3T15kCTplR+ztLmk2uFEvo2iGmgnftpQpNfnb1Kgy+iJc4dxsAscdcnYHrrgiO6q\na3Rr2muLVFRZ53QkAACAA/bnr9eprtGtUwZ31rDusU7HAQC0IaN6dNAZw7uqvtGtRz5f43Qcn0aT\nBbQDVXWNuuV9z8iP64/vowFdGPkBZxljdN8ZgzQyOVZ5ZbW65s0lauBwRQAA4IOyCiv170WbFeAy\numliP6fjAADaoFtP6a+woAB9tjJf87OKnY7jsyiqgXbg8S8ytLmkRgO7ROua4xj5gbYhJDBAL10y\nSh2jQrQwu0QPfLLa6UgAAAD77ckv16rJbXXuqG7qlRjpdBwAQBvUJSZMVx/j6WPum7VaTW7rcCLf\nRFEN+Lj5WcX658+ekR8zzh3KyA+0KR2jQ/XypaMUHODSaz9v0ju/5DgdCQAAoMVWbCnVpyu3KiTQ\npT+c2MfpOACANmza0alKig3Tmq3leueXzU7H8Uk0WoAPq65v1PT3PCM/rj2utwZ1jXE4EfDfRiR3\n0INnDpYk3TUzXUtytjucCAAAoGVmzM6UJP3PuJ7qEhPmcBoAQFsWFhygW0/xHLj75JeZKqtpcDiR\n76GoBnzY419kKqekWv07R+na43o7HQfYq/PSuus3R/ZQfZNbV7++WNvKa52OBAAA8KvmrS/Sj+uK\nFBUaqN8dy3g9AMC+nT60i47o2UHFVfV69ut1TsfxORTVgI9akFWsf/y0UQEuoyfOHabgQP53Rtt2\n5+kDNSYlTgUVdbr6jcWqa2xyOhIAAMAeWWv12BcZkqSrj+ml2PBghxMBAHyBMUb3TB4kY6R//LRR\nGwornY7kU2i2AB9UU9+k6e97R34c20uDkxj5gbYvKMClFy4eqaTYMC3NKdXdM9NlLQdMAACAtueL\nVflasaVMiVEhunx8T6fjAAB8yOCkGJ03qrsa3VYPfbrG6Tg+haIa8EEzZmdqU7Fn5Md1x3OoC3xH\nfGSIXr50lEKDXHpn0Wa9MX+T05EAAACaaWxya8aXntnUvz+hj8KDAx1OBADwNTdN7KfIkEB9k1Gg\n7zILnI7jMyiqAR/zy8YS/f2nbAW4jGacw8gP+J7BSTF67OyhkqT7Zq3WgqxihxMBAAD8x3uLtyir\nsEo94sN1wRHdnY4DAPBBiVEhuv54z1liD3yyWg1NbocT+QYaLsCH1NQ3afp7K2St9LtjemlIN0Z+\nwDedMTxJ045OVaPb6po3lyi3tMbpSAAAAKptaNIzczyHX/3p5H4KCuBHZgDAgfmf8T3VIz5cGwqr\nuJu4hfiqC/iQJ7/MVHZRlfp1itL1J/R2Og5wUG6Z1F9H9UlQcVW9rnp9kWrqOVwRAAA4658/bVR+\nea0GdY3W6UO6OB0HAODDQgIDdOdpAyVJT3+1ViVV9Q4navsoqgEfsXhTif42zzvy49yhCgkMcDoS\ncFACXEbPXjhCyXHhWpVbrts+WMHhigAAwDFlNQ164bsNkqTpk/rL5TIOJwIA+LoTB3TUhN4JkqTM\n/AqH07R9FNWAD6htaNLN73pGflx9TKqGdot1OhJwSMSGB+vVy9IUHhygmcvy9Ncfs52OBAAA/NTL\n329QWU2DxqbG6eg+CU7HAQC0A8YYPXr2EH1383E6sle803HavH0W1caYc4wxM40xm40xNcaYTGPM\nI8aYqF3WnGiM+ZcxJtu7ZoMx5kVjTMc9PF+oMWaGMWard+3PxpijD/ULA9qTp75aq6yiKvXpGKnf\nn9DH6TjAIdWvc5SeOm+YJOmRz9fox3WFDicCAAD+pqC8Vv83z/ML8+mT+ssYdlMDAA6Nbh3CFRcR\n7HQMn9CSHdU3SWqSdJukUyS9KOl3kr4yxux4/FWSEiU9JGmSpEckTZE03xgTudvz/U3SlZLulnS6\npK2SZhtjhh/cSwHap8WbtuuvP2bJZaQnzh3GyA+0S5MGd9Hvj+8tt5Wu+9dSbSqucjoSAADwI3/5\nZp1qG9yaOKiTRiZ3cDoOAAB+KbAFayZba3fd3vadMaZE0j8lHSvpG0nX7Lbme2PMWknfSzpP0v9J\nkjFmmKSLJP3WWvt378e+l5Qu6X55ym0AXrUNTbr5veVyW+l3x/bSsO6M/ED7dcOJfbV6a7nmrCnQ\ntNcW64NrxikipCVfpgAAAA7cYcGS2QAAIABJREFUxqIqvb1ws1xGuunkfk7HAQDAb+1zR/VuBfQO\nv3jfJ7V0jdcUSQ2S3tnl+RslvS1pojEmpAWZAb/x9FdrlVVYpd4dI/UHRn6gnXO5jJ4+f7h6JUYo\nc1uFbnp3OYcrAgCAVvfkV2vV6LY6e2Q39ekUte8HAACAVnGghyke432/Zj/XDJKUba2t3m1tuqRg\nSb0PMA/Q7izJ2a5XvSM/ZpwzVKFBjPxA+xcVGqRXLktTVEigPl+Vr+e/Xe90JAAA0I6tyi3TrOV5\nCg506YaT+jodBwAAv7bfRbUxJkmeMR1zrLWL9rImStIz8pTUM3e5FCdp+x4eUrLLdcDv1TY06eZ3\nPSM/rjw6VSOYkwc/0isxUn++cLiM8exw+nrNNqcjAQCAdurx2ZmSpMvG9lBSbJjDaQAA8G/7VVR7\nD0b8SFKjpMv3siZQ0lvyjPy4wDva46AZY6YZYxYZYxYVFu5p0gjQfjwzZ502FFapV2KE/ngiOzvg\nf47v30k3ndxP1ko3vL1M6wsqnY4EAADamZ82FOmHtYWKCgnUNcdxcy8AAE5rcVFtjAmTNEtSqqSJ\n1tote1jjkueQxRMlTbXWrthtyXZJe9oaumMndckerkmSrLWvWGvTrLVpiYmJLY0N+Jxlm0v1yg8b\nPCM/zh3GyA/4rWuO7aVTh3RWRV2jpr2+SOW1DU5HAgAA7YS1Vo9/4dlNPe3oVMVFBDucCAAAtKio\nNsYESXpPUpqkU621K/ey9CVJ58uzk/rrPVxPl5RijAnf7eMDJdVLYhgp/NquIz+uOCpVIxn5AT9m\njNGMc4apf+coZRVW6Ya3l8nt5nBFAABw8Ganb9OyzaVKiAzWbyekOB0HAACoBUW1d5f0m5KOl2eX\n9Py9rHtS0hWSLrfWztzTGnl2ZAdJOneXxwXKU25/aa2t27/4QPvyl6/XaV1BpVITInQjh7kAiggJ\n1CuXpik2PEjfZBToqa/WOh0JAAD4uMYmt5740rOb+vrj+ygiJNDhRAAAQGrZjurn5SmWn5RUZYwZ\nu8tbN0kyxtwi6UZJf5e0brc1vXY8kbV2qaR3JD1jjLnCGHOCpLclpUi659C+NMC3LN9cqpe+3yBj\npBnnDmXkB+CVHB+u5y4cKZeRnvt2vT5budXpSAAAwId9sDRX6wsq1T0uTBeOTnY6DgAA8GpJUX2K\n9/0dkn7e7e2K3db8dg9r7trt+S6Xp9B+UNKnkrpLmmStXXJgLwHwfXWNTbr5Pc/Ij/8dn6JRPeL2\n/SDAj0zok6DbTx0gSbrp3eXKyC93OBEAAPBFtQ1NesZ7h9afTuqn4MAWH9sEAABa2T7vcbLW9mzB\nmmNb+gmttTXy7L6+saWPAdq7Z79er7XbKpWSEKE/ndzP6ThAm/S/E1KUnleuD5fm6srXFmnWdRMU\nG87BRwAAoOXemL9JeWW16t85SlOGdXU6DgAA2AW/PgYctnJLmV70jvx4/JyhCgtm5AewJ8YYPXLW\nEA1JitHmkhpd/9ZSNTa5nY4FAAB8RHltg57/dr0k6ZZJ/eVyGYcTAQCAXVFUAw6qb3TrpneXq8lt\ndfm4FB3Rk5EfwK8JDQrQy5eOUnxEsH5cV6THvshwOhIAAPARr/6Qpe3VDRrdM07H9kt0Og4AANgN\nRTXgoOe+WafMbRXqER+umycy8gNoia6xYXrxklEKdBm9+mO2Zi7NdToSAABo4wor6vTXH7MlSbec\n0k/GsJsaAIC2hqIacMiq3DI9/51n5MeMc4Yx8gPYD6NT4nTPlEGSpFveX6GVW8ocTgQAANqy575Z\np5qGJp04oBMHlwMA0EZRVAMO2HXkx2+O7KnRKXyzDOyvS8Yk64Ijuquu0a2rXl+koso6pyMBAIA2\nKKe4Wv9amCNjxF2MAAC0YRTVgAOe/3a9MvIrlBwXrumT+GYZOBDGGN13xiCNTI5VXlmtrnlziRo4\nXBEAAOzmqa8y1dBkddaIburXOcrpOAAAYC8oqoHDLD2vbOdp44+fM1ThwYEOJwJ8V0hggF66ZJQ6\nRYdoYXaJHvhktdORAABAG7I6r1wfLc9TcIBLN5zYx+k4AADgV1BUA4dRQ5NbN727Qo1uq98c2UNj\nU+OdjgT4vI7RoXrpklEKDnDptZ836Z1fcpyOBAAA2ogZszNkrXTx2GR1jwt3Og4AAPgVFNXAYfTC\ntxu0Zmu5useFafqk/k7HAdqNEckd9OCZgyVJd81M1+JN2x1OBAAAnLYgq1jfZhYqIjhA1x3X2+k4\nAABgHyiqgcNkdV65nv1mnSTpsbOHKiKEkR/AoXReWnf9z7ieqm9y63dvLNa28lqnIwEAAIdYa/XY\nFxmSpCuPTlV8ZIjDiQAAwL5QVAOHQUOTWze/t1yNbqtLx/bQuF4JTkcC2qU7ThugsalxKqio01Wv\nL1ZdY5PTkQAAgAPmrCnQkpxSxUcE64qjUp2OAwAAWoCiGjgMXvpug9LzytWtQ5huPYWRH0BrCQpw\n6fmLRiopNkzLNpfqrpmrZK11OhYAADiMmtxWM2Z7dlNfd3xvRXInIwAAPoGiGmhlGfnl+ot35Mfj\njPwAWl18ZIhevnSUQoNc+veiLXp9/ianIwEAgMPow6W5WrutUkmxYbpoTLLTcQAAQAtRVAOtqKHJ\nrZveXa6GJquLxyRrXG9GfgCHw+CkGD129lBJ0v2zVmt+VrHDiQAAwOFQ19ikp79aK0m68aS+CgkM\ncDgRAABoKYpqoBW98kOWVuWWKyk2TLedOsDpOIBfOWN4kq46OlWNbqtr3lyi3NIapyMBAIBWUFpd\nr9np+bpvVromPztXuaU16tcpSlNHJDkdDQAA7AdmEACtJDO/Qs/M8ezmePycoczGAxwwfVJ/rd5a\nrh/XFWnaa4v03tXjFBbMzioAAHxZSVW9FmYXa35WieZnFSsjv6LZ9YjgAN07ZZACXMahhAAA4EDQ\nnAGtoLHJrZvf84z8uGhMssYz8gNwRIDL6NkLR+iM5+cpPa9ct36wQs+cP1zG8IMrAAC+oqiyTguz\nPaX0gqwSZW5rXkwHB7g0IjlWY1LjNTY1TiOTOyg0iF9MAwDgayiqgVbw8g9ZWrGlzDPy45T+TscB\n/FpseLBeuTRNZ74wTx8ty9OgrtGadnQvp2MBAIC9KKyo04Ls4p3F9LqCymbXQwJdGpncQWNS4zQ2\nNV7Du8dSTAMA0A5QVAOH2NptFfrznHWSpEfPHqKo0CCHEwHo1zlKT503TFe/sUSPfp6h/p2jdXTf\nRKdjAQAASQXltZq/c8d0sTYUVjW7Hhrk0qgeHTQmJV5jU+M1rHsMhyQCANAOUVQDh1Bjk1s3v7tc\n9U1uXTi6u47qQxEGtBWTBnfR74/vrb98s17Xv7VUH183Xj3iI5yOBQCA38kvq222YzqrqHkxHRYU\noLSeHTQmxbNjemi3WAUHuhxKCwAADheKauAQevXHbC3fUqauMaG6/dQBTscBsJsbTuyr1VvLNWdN\ngaa9tlgfXDNOERx0CgBAq8orrfEU0xtKtCC7WBuLq5tdDw8OUFrPuJ3F9JCkGIppAAD8ED+dA4fI\num0VevqrtZKkR84eysgPoA1yuYyePn+4pj4/T5nbKvSnfy/Xi5eM5HBFAAAOoS3bqzU/q0QLsoo1\nP7tYm0tqml2PCA7QESlx3lEecRqcFKOgAIppAAD8HUU1cAg0Nrl103srVN/k1vlp3XUMs2+BNisq\nNEivXpamM56bpy/S8/XcN+t1/Ql9nI4FAIBPstZqy/Yazc8q1vwsz5zp3NLmxXRUSKC3mPbsmB7U\nNVqBFNMAAGA3FNXAIfC3udlavrlUXWJCdcfpjPwA2rrUxEj95cIR+u0/f9FTc9ZqQJdonTiwk9Ox\nAABo86y1yimp3jlfen5WsfLKaputiQ4N1OidO6bjNbBrtAJc3L0EAAB+HUU1cJDWF1TqSe/Ij4fP\nGqJoRn4APuG4/h1108n9NGN2pm54Z5lmXjtevTtGOh0LAIA2xVqrjcU7imnPrun88ubFdExYkEZ7\nd0uPSYnTgC4U0wAAYP9RVAMHocltdfN7y1Xf6Na5o7rpuH4dnY4EYD9cc2wvrc4r16crt2raa4s0\n87rx/LIJAODXrLXKKqpqtmO6oKKu2ZoO4bsW0/Hq3zlKLoppAABwkCiqgYPwf3OztTSnVJ2iQ3Tn\n6QOdjgNgPxljNOPcodpQWKmM/Ard8PYyvXpZGrvAAAB+w1qrDYWV+tl7+OGC7BIV7lZMx0UE75wv\nPSY1Tn07UkwDAIBDj6IaOEAbCiv1xJeZkqRHzhqimDB2YQK+KDw4UK9elqbJz83VNxkFevqrtbpp\nYj+nYwEA0CqstVpXULlzx/SC7GIVVdY3W5MQGeydLx2nManx6tMxUsZQTAMAgNZFUQ0cgCa31fT3\nVqiu0a2zR3bT8f05hA3wZd3jwvX8RSN16d8W6Llv12tg12idOqSL07EAADhobrfV2oIKzd/g2S29\nILtEJVXNi+nEqJCdO6bHpsapVyLFNAAAOPwoqoED8Pd52Vq8abs6RoXobkZ+AO3C+N4Juv3UAXrw\n0zX607+XKyUhQgO6RDsdCwCA/eJ2W63JL985X3rhxhKVVjc0W9MpOmTnfOmxqXFKSYigmAYAAI6j\nqAb2U3ZRlWbM9oz8ePjMIYoJZ+QH0F7874QUrc4r1wdLczXt9UX6+NoJ6hAR7HQsAAD2qslttWZr\nueZnFWt+Vol+2ViisprmxXSXmFBvMe3ZNd0jPpxiGgAAtDkU1cB+aHJb3fzuctU1unXWiCSdOJCR\nH0B7YozRw2cN0frCSq3YUqbr31qqf1x+hAIDXE5HAwBAktTY5Nbqrc13TFfUNjZbkxQbpjGpcRqb\nEq+xqfHqHhdGMQ0AANo8impgP/zzp41atGm7EqNCdPdkRn4A7VFoUIBeumSUpjw3V3PXF+nRzzN0\nJyN+AAAOaWxya1VeuRZkFWt+VrEWbdyuirrmxXS3DmHNdkx3jwt3KC0AAMCBo6gGWmhjUZUen50h\nyTPyIzaccQBAe9U1NkwvXDxKF706X3+dm61BSdE6c0Q3p2MBAPxAQ5NbK3PLdu6YXrSxRFX1Tc3W\nJMeFa2xqnMakxGtMapy6daCYBgAAvo+iGmgBt9tq+nsrVNvg1tThXXUSIz+Adm90SpzumTJId81c\npVvfX6neiVEa0i3G6VgAgHamvtGtlbmlmu8tphdv2q7q3YrpnvHhnh3T3nK6a2yYQ2kBAABaD0U1\n0AKv/bxRCzeWKCEyRPdMHuR0HACHySVjkrU6r0xvLdzsOVzxuglKjApxOhYAwIfVNTZpxZYy7yiP\nEi3etF01Dc2L6dSECI1Jjd+5a7pzTKhDaQEAAA4fimpgHzYVV+mxLzIlSQ+dOVgdIhj5AfgLY4zu\nnTJImfkVWpJTqmvfXKI3rhij4EAOVwQAtExdY5OW5Xh2TC/I9uyYrmt0N1vTu2OkxqTEecrplDh1\njKaYBgAA/oeiGvgVO0Z+1DQ0acqwrpo4qLPTkQAcZiGBnsMVJz83Vws3luiBT1brgamDnY4FAGij\nahuatDSnVPOzirUgu1hLckpVv1sx3bdTpMakxGtsarxGp8Rxtw4AAIAoqoFf9caCTVqQXaKEyGDd\nO4WRH4C/6hgdqpcuGaXzX56v1+dv0qCu0bpgdLLTsQAAbUBNfZOW5mzX/Kxizc8u0bKcUtU3NS+m\n+3eO0piUuJ3FdHwkxTQAAMDuKKqBvcgprtajn2dIkh6cOlhxjPwA/NqI5A568MzBmv7eCt310Sr1\n6RSlUT06OB0LAHCYVdc3asmm/+yYXra5VA1Ndud1Y6QBXaKbFdN8HwkAALBvFNXAHrjdVtPfX67q\n+iadPrSLJg3u4nQkAG3AeWndtTqvXP/4aaOufmOxPrl+gjoxRxQA2rWqukYt3rTdW0yXaPnmUjW6\nmxfTg7pGe0d5xGl0SpxiwymmAQAA9hdFNbAHby7M0fysEsVHBOs+Rn4A2MUdpw1QRn655meV6KrX\nF+vtaWMVGhTgdCwAwCFSWdeoRRtLdh5+uHJLWbNi2mWkIUkxO3dMH9EzTjHhQQ4mBgAAaB8oqoHd\nbC6p1iOfrZEkPTB1MDMEATQTFODS8xeN1JTn5mnZ5lLd/dEqPXb2UBljnI4GADgAFbUNWrTxPzOm\nV+WWqWm3YnpYtxiNTY3XmNQ4pfWMU3QoxTQAAMChRlEN7MLttrrl/RWqrm/SaUO66NQhjPwA8N/i\nI0P08qWjdM5LP+nfi7ZoUNcY/WZcT6djAQBaoKymwbtj2jPKY1VumXbppRXgMhrePfY/xXSPDoqi\nmAYAAGh1FNXALv61MEc/bShWXESw7juDkR8A9m5wUoweO3uo/vD2Mt3/yWr17RSlI3vFOx0LALCb\n0up6Lcwu0YJszyiP9Lxy2V2K6UCX0fDuO3ZMx2tUjw6KDOHHJAAAgMON78AAr2YjP84YrARGfgDY\nhzOGJ2n11nK9/H2Wrv3XEn183Xh16xDudCwA8Gvbq+p3ltLzs0qUkd+8mA4KMBrW7T87pkf16KDw\nYH4sAgAAcBrfkQGSrLW69YMVqqpv0qlDOuu0oYz8ANAy0yf215qtFfphbaGuen2x3rt6nMKCOVwR\nAA6X4sq6nTum52cVKyO/otn14ACXd5RHnMakxmtkcgf+nQYAAGiDKKoBSW8t3Kx564vVITxI958x\n2Ok4AHxIgMvo2QtGaMrzc5WeV65b3l+hP18wnMMVAaCVFFXWaUHWjh3TxVq7rbLZ9eBAl0bsMmN6\nZHIHhQZRTAMAALR1FNXwe1u2V+uhT1dLku5n5AeAAxATHqRXL0vTmc/P08fL8zQ4KVrTju7ldCwA\naBcKKmp3KaZLtL6geTEdEujSyOQOO4vp4d1jKaYBAAB8EEU1/Jq1Vrd9sFJV9U2aNKizTmfkB4AD\n1LdTlJ48b7iufmOxHv08Q/06R+uYvolOxwIAn7OtvFbzs4p3jvLIKqxqdj00yKW0HnEakxKnsb3i\nNbRbjEICKaYBAAB8HUU1/No7v2zWj+uKFBsepAemDuZWfQAHZdLgzvr9CX30l6/X6fp/LdHH101Q\nz4QIp2MBQJu2taym2Y7p7KLmxXRYUIDSenp2TI9NjdOQpFgFB7ocSgsAAIDWQlENv5VbWqMHP10j\nSbpvyiAlRjHyA8DBu+GEPlqdV645a7Zp2uuL9ME14xUZwpdbANght7RGC7KKd+6a3lRc3ex6RHCA\n0nrGaUxqnMamxmtIUoyCAiimAQAA2jt+coZf2jHyo7KuUScP7KQpw7o6HQlAO+FyGT19/jBNfX6e\n1m6r1J/+vUwvXjxKLhd3bADwT5tLqneO8ViQXazNJTXNrkeGBOqInh00JjVeY1PjNbhrtAIppgEA\nAPwORTX80ruLtuiHtYWKCQvSg2cy8gPAoRUV6jlc8Yzn52l2+jY99+16/f6EPk7HAoBWZ63V5pIa\nzc/27pjOKlFuafNiOiokUKNT/rNjemAXimkAAABQVMMPbS2r0QOfrJbkGfnRMSrU4UQA2qPUxEj9\n5YIR+u0/f9FTX63VgC7ROmlgJ6djAcAhZa3VpuLqnfOlF2QVK6+sttma6NBAjU7xzJcemxqvAV2i\nFcBdJgAAANgNRTX8yo6RHxV1jTpxQCedMZyRHwBaz3H9O+qmk/tpxuxM/fGdZZp57Tj17hjldCwA\nOGDWWmUXVf1nlEdWifLLmxfTseFBGt0zzjvKI079O1NMAwAAYN8oquFX3lu8Rd9lFio6NFAPM/ID\nwGFwzbG9tDqvXJ+u3KorX1usmdeOV0xYkNOxAKBFrLXaUFjVbMd0QUVdszUdwoM0xrtjekxqvPp1\nimIuPwAAAPYbRTX8Rn5Zre73jvy4d8ogdYxm5AeA1meM0Yxzh2pDYaUy8it0w9tL9dffHMHuQgBt\nkrVW6wsqNX+XHdNFlc2L6fiI4J3zpcekxKtPx0iKaQAAABw0imr4BWutbv9wpSpqG3VC/446c0SS\n05EA+JHw4EC9elmaJj83V99mFuqprzJ188T+TscCALndVusKKj2ldLanmC6uqm+2JiEyZGcxPTYl\nTr07RnJXGgAAAA45imr4hQ+W5OqbjALPyI+zhvDDFYDDrntcuJ6/aKQu+7+Fev7bDRrYJUanDe3i\ndCwAfsbttsrcVrFzt/SC7GJtr25otqZjVMjO+dJjUuLVKzGC750AAADQ6iiq0e5tK6/VfbPSJUl3\nTx6kToz8AOCQ8b0TdPupA/TAJ6t107vLlZoYoQFdop2OBaAdc7ut1uSX75wvvXBjiUp3K6Y7R4fu\nMsojTikJFNMAAAA4/Ciq0a5Za3X7BytVXtuo4/ol6uyRjPwA4Kzfju+p9NwyfbA0V9NeX6SPr52g\nDhHBTscC0E40ua3WbC3X/CzP4YcLs4tVXtvYbE3XmFBPKe0tp5PjwimmAQAA4Lh9FtXGmHMkXSJp\nlKQESTmSPpD0sLW2Ypd1HSTNkDRVUpiknyX90Vq7crfnC5X0gPc5YyUtk3SLtfaHQ/GCgF3NXJar\nrzMKFBUaqEfOGsoPYQAcZ4zRw2cN0frCSq3YUqbr3lqif14+WoEBLqejAfBBjU1urfYW0wuySrRw\nY4kqdiumk2LDdhbTR6bGq1uHML4nAgAAQJvTkh3VN0nKlXSbpC2Shku6V9Jxxphx1lq38XynO0tS\nT0nXS9ruXf+tMWa4tXbLLs/3N0mnSbpZUpakayXNNsYcaa1ddkheFSCpoLxW9368WpJ01+kD1TmG\nkR8A2obQoAC9dMkoTXluruatL9ajn2foztMHOh0LgA9obHJrVd6OYrpYv2zcrsq65sV097gwjU2J\n1xjvKI/uceEOpQUAAABariVF9WRrbeEuf//OGFMi6Z+SjpX0jaQpksZLOt5a+60kGWN+lpQtabqk\n33s/NkzSRZJ+a639u/dj30tKl3S/93mAg2at1e0frlJZTYOO6Zuoc0d1czoSADTTNTZML14yShe+\nMl9/nZutgV2jddZI/q0C0FxDk1srtpRpQbZnx/SijSWqqm9qtqZHfLi3mI7TmNR4JcWGOZQWAAAA\nOHD7LKp3K6l3+MX7fsfA3ymS8naU1N7HlRljZkk6Q96i2ruuQdI7u6xrNMa8LelWY0yItbZu/18G\n0NzHy/M0Z802RYUE6pGzhnB7K4A26Yiecbp3yiDdOXOVbv1gpXp3jNTQbrFOxwLgoPpGt1ZsKdWC\n7BLNzyrW4k3bVb1bMZ2SEKGxqXEa4y2nu8RQTAMAAMD3Hehhisd436/xvh8kadUe1qVLuswYE2mt\nrfSuy7bWVu9hXbCk3t4/AwesoKJW93zs+c/oztMHqCu7igC0YZeM7aH0vHK9tTBHV72+WB9fN0GJ\nUSFOxwJwmDS5rVbmlmne+iL9vKFYizaVqLbB3WxNamKEZ8Z0iufww07RjDMDAABA+7PfRbUxJkme\nMR1zrLWLvB+Ok7RxD8tLvO87SKr0rtv+K+vifuXzTpM0TZKSk5P3Nzb8hLVWd364SqXVDTqqT4LO\nS+vudCQA2Kf7pgzS2m0VWrxpu655c7HevGKsggM5XBFoj6y1yi6q0rz1RZrrLafLdzv8sHfHyGY7\npjtGUUwDAACg/duvotoYEynpI0mNki5vlUR7Ya19RdIrkpSWlmYP5+eG75i1Yqu+XL1NkSGBevTs\noYz8AOATggNdevGSkZr87Fz9snG77v8kXQ9OHeJ0LACHSGFFnX7aUKS564o0b32R8spqm13vGR+u\ncb0TNK5XvMakxHNXBQAAAPxSi4tqY0yYpFmSUiUdY63dssvl7fLsmt5d3C7Xd7zv8SvrSvZwDWiR\nwoo63fORZwLNHacN4CAhAD6lY1SoXr40Tee99LPemJ+jQV1jdOFo7iACfFFVXaMWZpdo7npPMZ2R\nX9HselxEsMb1itdRfRI0rleCuseFO5QUAAAAaDtaVFQbY4IkvScpTdJJ1tqVuy1Jl3TyHh46UFK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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "displayUserVariation(userIdsTransOnly, userResultArrayTransOnly, labelsTransOnly)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "So looking at transport-only trips, and focusing on users with enough transport history (50+ motorized transport trips), we are able to get an overall accuracy of around 70 - 80% even for the motorized trips. However, there are some clear outliers, like the one who has only 60% accuracy. Also, because our current threshold for high confidence is set so high, the high confidence predictions are > 95% correct as before. We have to decide what to use.\n", + "\n", + "We can autoclassify 20 - 50% of the motorized transport trips. In general, this is related to the number of trips - there is a very clear spike in the data for user 4. But the correlation is not exact. In particular, user 5 has > 50 trips, but only ~ 10% autoclassified trips.\n", + "\n", + "It might be worthwhile to take a closer look at these 6 users, see what their transport trips look like, and get a sense of what the difference between user 4 and user 5 is, for example. This might help us figure out how to build better user models." + ] + }, + { + "cell_type": "code", + "execution_count": 104, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def buildRouteLibrary(userId, threshold):\n", + " '''\n", + " Here we attempt to build a route library for each user.\n", + " Then, the probability of the top match can be a factor in our machine learning.\n", + " Let us just start with the start and end points instead of a full dynamic time warp.\n", + " \n", + " userSections = Sections.find({\"$and\": [{'type': 'move'}, {'confirmed_mode': {'$ne': ''}}, {'user_id': userId}]})\n", + " existingRoutes = RouteLibrary()\n", + " for section in userSections:\n", + " existingRoutes.update(section)\n", + " return existingRoutes\n", + " '''" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## A summary comparision of models" + ] + }, + { + "cell_type": "code", + "execution_count": 105, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "modelCMList = []\n", + "saveDir = \"/tmp/ml_results/\"" + ] + }, + { + "cell_type": "code", + "execution_count": 106, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import os\n", + "os.makedirs(saveDir, exist_ok=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generic model" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 775 high confidence predictions out of 1462\n", + "Found 767 high confidence predictions out of 1462\n", + "Found 795 high confidence predictions out of 1461\n", + "Found 775 high confidence predictions out of 1461\n", + "Found 768 high confidence predictions out of 1461\n", + "for prob 0.9, percentage auto classified 0.530998669464\n", + "for prob 0.9, scoring only on high confidence predictions 0.97479037712\n", + "for prob 0.9, scoring on all predictions 0.852607091258\n", + "Found 752 high confidence predictions out of 1462\n", + "Found 736 high confidence predictions out of 1462\n", + "Found 775 high confidence predictions out of 1461\n", + "Found 750 high confidence predictions out of 1461\n", + "Found 770 high confidence predictions out of 1461\n", + "for prob 0.95, percentage auto classified 0.517725149369\n", + "for prob 0.95, scoring only on high confidence predictions 0.976978396342\n", + "for prob 0.95, scoring on all predictions 0.85206073834\n", + "Found 741 high confidence predictions out of 1462\n", + "Found 750 high confidence predictions out of 1462\n", + "Found 777 high confidence predictions out of 1461\n", + "Found 797 high confidence predictions out of 1461\n", + "Found 753 high confidence predictions out of 1461\n", + "for prob 0.99, percentage auto classified 0.522516107345\n", + "for prob 0.99, scoring only on high confidence predictions 0.976769742835\n", + "for prob 0.99, scoring on all predictions 0.8505535159\n", + "[0.53099866946444296, 0.51772514936923619, 0.52251610734547382]\n", + "[0.80960422904675333, 0.80767398399830892, 0.80237868887669173]\n", + "[0.61957540576256454, 0.57575691097244319, 0.61124031647220811]\n", + "[0.075218091503698695, 0.059239982987050299, 0.05569452045783907]\n", + "[0.089785373889698844, 0.090937946804551778, 0.083042212167778726]\n", + "[0.22653756029902819, 0.20896370175207526, 0.21817741835671317]\n", + "[0.3117867767502906, 0.066666666666666666, 0.21817741835671317]\n", + "[0.97479037711976824, 0.97697839634230077, 0.97676974283542184]\n", + "[0.85260709125825973, 0.8520607383395552, 0.85055351590041484]\n", + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 95. 1. 0. 0. 3. 0.]\n", + " [ 8. 80. 3. 0. 9. 0.]\n", + " [ 8. 10. 19. 3. 60. 0.]\n", + " [ 5. 2. 4. 23. 65. 0.]\n", + " [ 3. 2. 4. 4. 86. 0.]\n", + " [ 35. 3. 0. 7. 10. 45.]]\n" + ] + }, + { + "data": { + "image/png": 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CY0w0uV9z8Ldi2h4EKhlj6hUob3n+96+eDVNERERERESK4km4exVIBlYaY3obY3qRe/fM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\nnDhxgg4dOtz8wVgwGo1WI12Wx9q1a2nbtq0+vXr1agwGgz7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5TMYnvGz+zDMz6d29E75+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\nAEEALE5B2zWMe/SY9/13oXs9vB76nv0BAJ/wtiHqZs/vUe996PdD359fB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XkoVJ2gG4D1gFuKS26n6ez/WESbLrSbL4mCKpf/z+QEnXSJoOTIvnfEXSKEmT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\nBngQdc65Bvx/eQFIUoKA3sgAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices], cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices], cleanedResultVector, \"Generic\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generic + Advanced model" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 741 high confidence predictions out of 1462\n", + "Found 741 high confidence predictions out of 1462\n", + "Found 696 high confidence predictions out of 1461\n", + "Found 709 high confidence predictions out of 1461\n", + "Found 740 high confidence predictions out of 1461\n", + "for prob 0.9, percentage auto classified 0.496370475032\n", + "for prob 0.9, scoring only on high confidence predictions 0.976568239712\n", + "for prob 0.9, scoring on all predictions 0.857396738362\n", + "Found 714 high confidence predictions out of 1462\n", + "Found 742 high confidence predictions out of 1462\n", + "Found 703 high confidence predictions out of 1461\n", + "Found 717 high confidence predictions out of 1461\n", + "Found 721 high confidence predictions out of 1461\n", + "for prob 0.95, percentage auto classified 0.492266133329\n", + "for prob 0.95, scoring only on high confidence predictions 0.975872518129\n", + "for prob 0.95, scoring on all predictions 0.856304032525\n", + "Found 721 high confidence predictions out of 1462\n", + "Found 737 high confidence predictions out of 1462\n", + "Found 741 high confidence predictions out of 1461\n", + "Found 696 high confidence predictions out of 1461\n", + "Found 752 high confidence predictions out of 1461\n", + "for prob 0.99, percentage auto classified 0.499110573029\n", + "for prob 0.99, scoring only on high confidence predictions 0.974967034857\n", + "for prob 0.99, scoring on all predictions 0.856851509048\n", + "[0.49637047503209297, 0.49226613332883895, 0.4991105730291735]\n", + "[0.78496822468232286, 0.788757774216573, 0.77827792143369046]\n", + "[0.47179751747011495, 0.471304979297613, 0.52263458642539962]\n", + "[0.07144092867187754, 0.067695752929590486, 0.057398215366001218]\n", + "[0.087563080254794104, 0.073497091144149956, 0.085269833527643599]\n", + "[0.2220020176033784, 0.20408322774878754, 0.21697164119709855]\n", + "[0.27296196144708129, 0.033333333333333333, 0.21697164119709855]\n", + "[0.97656823971219653, 0.9758725181290806, 0.97496703485721847]\n", + "[0.85739673836202746, 0.85630403252461862, 0.85685150904829721]\n", + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 95. 1. 0. 0. 3. 0.]\n", + " [ 10. 79. 3. 0. 8. 0.]\n", + " [ 7. 9. 18. 2. 64. 0.]\n", + " [ 5. 1. 3. 30. 60. 0.]\n", + " [ 3. 2. 4. 3. 87. 0.]\n", + " [ 25. 3. 0. 3. 17. 51.]]\n" + ] + }, + { + "data": { + "image/png": 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11pE/Q3tFzdLiXRgsy6zqb16GoKoVfVRlpnBXFrWbQ5Ual+AFF2Xcx8W+mLyYsZTx2Eo7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\nbVx7wLdccBg1trW5xk4Wt3Xcdpn+jfYV+jfb4iA5Uf+WbZdvW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p5IjvYWbD8rZbixJdBJiaOZ/DwqNhj1N5kn4zOSCF4JuAj87/GJ/iNEPSBHyq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\nVPHnagpU0oGSJkqaOHfu3EZ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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices], cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices], cleanedResultVector, \"Generic + Advanced\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic_advanced.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generic + Advanced + Location model" + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 741 high confidence predictions out of 1462\n", + "Found 797 high confidence predictions out of 1462\n", + "Found 762 high confidence predictions out of 1461\n", + "Found 721 high confidence predictions out of 1461\n", + "Found 753 high confidence predictions out of 1461\n", + "for prob 0.9, percentage auto classified 0.516488434828\n", + "for prob 0.9, scoring only on high confidence predictions 0.98668175697\n", + "for prob 0.9, scoring on all predictions 0.885315606592\n", + "Found 749 high confidence predictions out of 1462\n", + "Found 770 high confidence predictions out of 1462\n", + "Found 768 high confidence predictions out of 1461\n", + "Found 743 high confidence predictions out of 1461\n", + "Found 738 high confidence predictions out of 1461\n", + "for prob 0.95, percentage auto classified 0.515668858633\n", + "for prob 0.95, scoring only on high confidence predictions 0.982000476172\n", + "for prob 0.95, scoring on all predictions 0.883260252193\n", + "Found 741 high confidence predictions out of 1462\n", + "Found 797 high confidence predictions out of 1462\n", + "Found 756 high confidence predictions out of 1461\n", + "Found 775 high confidence predictions out of 1461\n", + "Found 791 high confidence predictions out of 1461\n", + "for prob 0.99, percentage auto classified 0.528261193212\n", + "for prob 0.99, scoring only on high confidence predictions 0.983775398885\n", + "for prob 0.99, scoring on all predictions 0.887368807415\n", + "[0.5164884348276344, 0.51566885863270384, 0.52826119321230236]\n", + "[0.79493406415311207, 0.781787365548409, 0.79971958476922655]\n", + "[0.46252835129798042, 0.51756213730238887, 0.50455662089152553]\n", + "[0.048523375934322634, 0.055052102745963685, 0.040727557791577801]\n", + "[0.066979539641943725, 0.092112332112332121, 0.11428593947036569]\n", + "[0.28232909756666386, 0.26826699258740244, 0.29058089297013812]\n", + "[0.28560462698789268, 0.125, 0.29058089297013812]\n", + "[0.98668175697025295, 0.98200047617193875, 0.98377539888483623]\n", + "[0.88531560659219044, 0.88326025219313653, 0.88736880741504387]\n", + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 95. 1. 1. 0. 3. 0.]\n", + " [ 9. 82. 2. 0. 7. 0.]\n", + " [ 6. 7. 32. 5. 50. 0.]\n", + " [ 6. 1. 5. 41. 47. 0.]\n", + " [ 5. 3. 4. 3. 85. 0.]\n", + " [ 10. 3. 3. 0. 23. 60.]]\n" + ] + }, + { + "data": { + "image/png": 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PuKswIYQrgC8B1AcwHvdm7hIAFAGYZqmdlHIpgKUA0LVrV/kgx1guPywEck5X7TaFroxA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\nikjCnbgqNKOGuaoNc1Ub3H4h8LkvBL6D5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EREdmBm+DMlKs+VqDx3vL08Xq5Tv7VK4+ZK\nO/TFywUD370Nmvc24HP3soNDcLzSqdCZffXKevsWOSycczTvbXRNHF5ovC/gz0SdMXOX5gjmy0M6\nWxE5zHR3ICKyR/5MRGVmnsqb5tvL4pVW4Ou08sVLtb0fxEHzjQ2ab2yw8fl77cXB8XIW9KY7ga+i\nt3SRg6BVsbd2dYnqtbR1LlkpNpbXmwrbk4aXLs8RHC9jprnmRKSb7gRERIbIn46oPDtP5dlc4Fut\n07i1lo7hy0JfvFgg8AHN+1Wa96tsfOGNzrGPl9MJ17OwF52bUtEEkRFpLtY63SyvLRX+P26VoKub\nZXBqQmFORHakcCci8oj5UxH+MxHlZ461l8VrDRq3usfwxQ+qhY4T36+ycb/Kxh/nAt98mejsZG4M\n3xT+pAKfSFHxSj2tZJlNHN68X+z/r5V8Shdn290swzOTmKcwJyK7o3AnIrIP/MkQ/+ljlJ/uBL5k\nvZGGvVudqRnigjeM8YMqGw+qbHzxfufYc6Wu1r3w3JQq6YnsIF5rUL++RPVqGuiad9cL7c9Cj+jC\nTLuiZXRuGvMV5kSkGIU7EZEDwpsIKfcGvo1mV+BrLKzSfGOj0HHixRrxYo3qS7nAN1vaVLTFn1bg\nk6MrqTapXV9qt8w1Xl+DIlMD+0Z0foby5XTcXPTENBZ4QztfERFQuBMROdC8SkD5qTnKT821lyXV\nLQJfgRvPeKlGvFSj+qVc4JuJegLfNP6MAp+Mp6QeU7+xnM41d22Jxs2VYmHOM6LHpzoVLZ+cwULN\nYykij5bCnYjIIeOVA8qX5yhfzgW+WpPGwlpaqXMhnYC9ea9g4FuuEy8/oPrlB51jT0ddrXvRuSm8\nmUiFHuTQcY2E2qvL7QIo9ddWIC7wH8YgPJsLcxdmNEeliIyc3nVERMaAV0or65UuzbaXJbWYxu1V\n6jc7rXzNu+uFAl+yUqf6lQdUv5ILfFNhV+ALz03jzyrwycHi4oT6ayvtbpa1V5ehWaRpDsLTk+0C\nKKWLM6pOKyL7TuFORGRMeSWf0oVZShdyga8e07i9lk68fmuNxsIKjbvrkOz9OMlqg+pXH1L96sPO\nsSfDzUVb5koKfDIyLnE0FlapXVukenWJ+o0lXL3AhQ4EJyudlrmLsypEJCIHjsKdiMgR4kU+pSdn\nKD05016W1GMar6+1p2RoLKzSuLMOyd5bNZK1BrWvPaT2tVzgmwhyE69PpmP4jinwyXC4xNF4fY3a\ntaxl7voSrhoX2qc/X+6aa86fKQ3pbEVEHg2FOxGRI86LfErnZyid7wQ+10hovJ5NvL6QfX29YOBb\nb1L7+iK1ry92jj0REJ7tqdI5X1bgkx0552je2+iaODxZbxbapz8TZS1z2cThx8pDOlsRkdFQuBMR\nkU0s9IiemCZ6Yrq9zDVbga8z8Xrj9bVCRSiS9Sa1lxepvdwJfFYOiM51T7wezJc1ofMR55wjflCl\ndjWba+7aIslKo9A+vakwHauaBbrguD5YEJHDTeFOREQGYoFH9Pg00eM9ge/OetbClwW+28UCn6s2\ns6IXS51jl/yeoi1TBMcrCnxjrrlY62qZixdrhfZnlaCrm2VwakJhTkTGisKdiIjsmQVeu2hKi4vT\nwNcKe2ngWy1UmdDV4nQs1bXuwBeeTcfutQPfCQW+wyxeqVO7ttiuaNm8Xy20Pyv5lC7Otitahmcm\ndX2IyFhTuBMRkaEy3yM6O0V0dorJb02XuTihcXeDxsJKp2jL7TVcY+/VC10tpn59mfr15c6xo1bg\n67TyBScndEN/QMVrjSy0p61zzbsbhfZnoUd0YSbtZnlplujcNObr315Ejg6FOxEReeTM94jOTBKd\nmWTySrrMxY7mvfXuMXy3VosFvnpM/cYy9Ru5wBd6m4q2BCcndNO/D5Jqs90CW7u6mI7ZLDLVnG9E\n52coX07HzUVPTGOBN7TzFRE5bBTuRERkX5hvhKcnCU9PwtsfA9Jy9n0DX4H5yVwjof7KMvVXegLf\nmcmuidfDUxXMVzAYpiQL27Wri1SvLtJYWC0W5jwjemI6K4IyS+nJGSz0h3a+IiKHncKdiIgcGOYZ\n4WOThI9NwrfkAt8bG7kxfCs0bq3hanufw8w1EuqvrlB/dYW11sIgDXz5idfDxyYU+HbBNRJqry5n\nRVCWqN9cKVRcB4Pw3BSlS3OUL88SXZjFKynMiYhsReFOREQONPOM8NQE4akJJr75FJAFvvsbXROv\n1xdWCwU+mgmN11ZovJYLfL61A197AvbHJtT1L+OaCfWbK+0CKLVXlwsVzgEIT0+mrXKX5yhdnMWr\n6FZFRGRQescUEZFDxzwjPDlBeHKCibd1Al/8oNqp0LmwQn1hDVctMLF17GjcXKVxc7WzLOtO2jU1\nw+nJIxH4XOJoLKxSu7ZI9eoS9RtLhbrMAgQnK+1Jw0sXZ/GnoiGdrYjI0aNwJyIiY8E8IzhRIThR\nYeKtJ4HOxNf51r36wipuo2Dgy/bX5hvhYxNp4ZbHsxa+05NYeLgDn0scjdfX0pa5a4vUri/hqgVa\nRwF/vpzONfdUWtHSnykN6WxFREThTkRExpaZERyvEByvwFtyge9hLRf40gnYk/WCge/WGo1ba6y/\neCdd5nUHvvDcFNGZyQNdAMQ5R/PeRtfE4YV+L4A/G1G6NNdunQuOlYd0tiIi0kvhTkREjhQzI5gv\nE8yX4ZtOAFngW6x1T7y+sEqy1tj7gRJH4/YajdtrrP9RK/CRjh9sTc3w+DThmUm8aH8CX6tls5oV\nQKldWyRZKfCaAW8qzKpZpoEuOF7GTNNOiIiMgsKdiIgceWZGcKxMcKxM5RtzgW+p3tW6V19YJVkt\nEvig8fo6jdfXWf/M3ezgEJyaSMNeq5XvzNQjqwrZXKx1WuauLhEv1QrtzyoB5XaYmyU4NaEwJyKy\nTxTuRERE+jAzgrkSwVyJypuPA2ngS5brXa179YVVkpX63g/koHlnneaddcgHvpOVdOxeewL2SbzS\n7v9sxyv1dhfL6tVF4vvVvZ8rYCWf0sXZdkXL8PQk5inMiYgcBAp3IiIiAzIz/NkSldkSleeOt5fH\ny/Wu1r3GwirxcsHAd3eD5t0N+Gwu8J2opGP3znYqdXrl7j/l8VqD2rWsAMrVxXQfBVjoEV2YoXR5\njvLlOcKzU5ivMCcichAp3ImIiBTkz0RUZo5T+YZc4Fupd7XuNRZWi3WBdNC8t0Hz3gYbn7vXXtwK\nfN5EQP3GMo3ba9vsZAC+UXpyJh0399Qc0ePTR2KaBxGRcaBwJyIi8gj40xGVN81TedN8e1m8Wt80\n8Xq8WGzMW/ONDZpvFGid84zoielOEZQnpw90RU8REdmawp2IiMiI+FMR/rPzlJ/NBb61Rifw3coC\n34Ni4+K2ZRCem6J0aY7y5VmiC7OPrHiLiIiMlsKdiIjIPvInQ/xnjlF+5lh7WbLe6BRtaQW+AoVQ\nwtOT7QIopYuzeBX9+RcRGUd6dxcRETlgvImQ8tPHKD+dC3wbze6J12+tbdkdMzhZaU9NULo4iz8V\njerURURkHynciYiIHAJeJaD81Bzlp+bay5Jqs926l1RjwpMVSpdti9KFAAAVuElEQVTm8GcU5kRE\njiKFOxERkUPKKweUsykKREREFO5ERERERORIcs6RxI5mIyFuJEQVn+AQVwxWuBMRERERkX3nnCNp\nOpqNmGYjoVlPaDZi4kaShq/s+1YQS9eJiZutdRPierZte52YZj3JrdPZX2t95zrn8P0/9lbOP3d8\n65M84BTuRERERESki3MuF6AS4mbcCVCN/PP+ASofwDYFrj4BLK4nNJsJuJ3PbStB6OFHHkHg4Uc+\nQeily0KPqBIwMdP5Pgj9dN3W82zdY6cnh/dL3AcKdyIiIiIiB5hLXBaGslanetL9fb9WrR1DVr51\nrPN93A5zyd5P2GiHpiDKhaksQJWnwq7v01Dm54KXR9D7fS6M+fl9B177q5kN75d+SA0U7szsCeDD\nwJ8FDPi3wAedc68OsO3PA1eAtwPzwA855359rycsIiIiIrJfkjiht1vgpm6CfboFdn3fDmPdIStt\n+coFsHpMs5mQNPfenGWeZWFpc8gKIo+JmWhzyAq8za1aURaocq1jQdTZl58LZJ5vClr7ZMdwZ2YT\nwCeBGvBe0sbSnwM+ZWZvcc6t7bCLHwU+B/xL4K8UO10RERERkU4hjC1DVqur34ABKu7TGtZvzFeS\n7D1oeb51Bah84Aoij9Jk0N1K1V5nh1at3pCV7S8NWt4Qf+ty0A3Scvc+4BLwrHPuZQAz+wLwdeAD\nwC/tsP2scy4xs6dQuBMREREZO/0KYWxqpWru0KqVhaz8tluFrH6FMHYr350vH6BaYak8FXWN2dqq\nW2DX961WrXwYizqtX56n1ix5tAYJd+8CPt0KdgDOuetm9gfAD7BDuHPOFeiwKyIiIiK7kS+Esblb\n4ObwtVOA2rYL4jALYfSMveothNFv7FW6jr+p22H7+8Df1Drmh2mLmCloyRgaJNy9GfjdPstfAv7C\ncE9HREREZHy0CmHsPPZqcyGMTSGr3arVv4thPtDtWd9CGJ0AVZ4Ks5au7gCW7xYYRH67Nax3zFZX\nC1c7gKkQhsiwDBLu5oGHfZY/AI4N93RSZvZ+4P0A58+ffxSHEBERkSOmXyGM/PxY+e93LO+eC1m9\nrVr58Da0QhhBb4DyqExHuQCVG5e1XSGMrcZoqRCGyFg4kFMhOOdeAF4AuHLlSoFGfhERETmI4jhX\nwKI3ZOXKvbdbqXaaH6tPeffe1rGhFMLYorz7xETQHajaLVV7K4Thhx6+CmGIyC4NEu4e0r+FbqsW\nPRERETkkegthbDU/1kDl3ev5roHbVCdsJLgCQcsPvL4BqrcQx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SJuDSehVgSPp9MF3Mj3JWuGokjQJagL7hpDkIuj8N6p3fBXiiIEABzGyypEdx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\nhBANgiCog/8PaRrQmV6+Il4AAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices\n", + " +LocationFeatureIndices], cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices\n", + " +LocationFeatureIndices], cleanedResultVector, \"Generic + Advanced + Location\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic_advanced_location.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generic + BusTrain model" + ] + }, + { + "cell_type": "code", + "execution_count": 110, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 730 high confidence predictions out of 1462\n", + "Found 743 high confidence predictions out of 1462\n", + "Found 749 high confidence predictions out of 1461\n", + "Found 708 high confidence predictions out of 1461\n", + "Found 749 high confidence predictions out of 1461\n", + "for prob 0.9, percentage auto classified 0.503489729782\n", + "for prob 0.9, scoring only on high confidence predictions 0.978069859927\n", + "for prob 0.9, scoring on all predictions 0.853976578454\n", + "Found 755 high confidence predictions out of 1462\n", + "Found 764 high confidence predictions out of 1462\n", + "Found 716 high confidence predictions out of 1461\n", + "Found 734 high confidence predictions out of 1461\n", + "Found 729 high confidence predictions out of 1461\n", + "for prob 0.95, percentage auto classified 0.506086380878\n", + "for prob 0.95, scoring only on high confidence predictions 0.978197794524\n", + "for prob 0.95, scoring on all predictions 0.853563372725\n", + "Found 769 high confidence predictions out of 1462\n", + "Found 723 high confidence predictions out of 1462\n", + "Found 748 high confidence predictions out of 1461\n", + "Found 763 high confidence predictions out of 1461\n", + "Found 788 high confidence predictions out of 1461\n", + "for prob 0.99, percentage auto classified 0.518819915149\n", + "for prob 0.99, scoring only on high confidence predictions 0.976831177517\n", + "for prob 0.99, scoring on all predictions 0.850143868254\n", + "[0.50348972978236706, 0.50608638087774138, 0.51881991514909775]\n", + "[0.79940145198955226, 0.79892349775744254, 0.81079457598188842]\n", + "[0.52497165480819419, 0.54334217442105093, 0.55365195432568803]\n", + "[0.041538268424790817, 0.04614158240492116, 0.038835569315445476]\n", + "[0.10620250120250119, 0.081192235260031859, 0.085035992172989711]\n", + "[0.20124851845243147, 0.20313667748722838, 0.22213964370817418]\n", + "[0.27889373247957833, 0.066666666666666666, 0.22213964370817418]\n", + "[0.97806985992705542, 0.97819779452377842, 0.97683117751738435]\n", + "[0.85397657845431285, 0.85356337272505112, 0.85014386825357136]\n", + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 95. 1. 0. 0. 3. 0.]\n", + " [ 9. 81. 2. 0. 8. 0.]\n", + " [ 7. 10. 16. 2. 65. 0.]\n", + " [ 4. 1. 5. 26. 64. 0.]\n", + " [ 3. 3. 5. 4. 85. 0.]\n", + " [ 25. 3. 0. 3. 20. 49.]]\n" + ] + }, + { + "data": { + "image/png": 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8/fbbrmvuID9whIaGuqY69urVi7lz51K/fv0iI1neaNq0KbGxsSxYsIB77rmn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mkBvp5I07Q6QBJwsry6QgghhBBCCCEqxpeRu0eBOsA9SqlPlVKrgN5ALDCyAueaB7wL7KxwlEII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\njVa9ysxCsnFpDmp3StTulFj6wm1IGdlz+Xh+vSnSp8afOrlIs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NauRWomZ2B+7yFs5nShoCfBX4KPAKcJ2ZzWy6lEEQ9Ei6g7tejYaWfZrZ/3AL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\nSevmLLuspF9Iej0FL3pQ0uf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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+BusTrainFeatureIndices], cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+BusTrainFeatureIndices], cleanedResultVector, \"Generic + BusTrain\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic_bustrain.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generic + Advanced + BusTrain model" + ] + }, + { + "cell_type": "code", + "execution_count": 111, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 729 high confidence predictions out of 1462\n", + "Found 752 high confidence predictions out of 1462\n", + "Found 700 high confidence predictions out of 1461\n", + "Found 729 high confidence predictions out of 1461\n", + "Found 790 high confidence predictions out of 1461\n", + "for prob 0.9, percentage auto classified 0.506363724039\n", + "for prob 0.9, scoring only on high confidence predictions 0.973840213762\n", + "for prob 0.9, scoring on all predictions 0.856575944928\n", + "Found 748 high confidence predictions out of 1462\n", + "Found 718 high confidence predictions out of 1462\n", + "Found 764 high confidence predictions out of 1461\n", + "Found 716 high confidence predictions out of 1461\n", + "Found 760 high confidence predictions out of 1461\n", + "for prob 0.95, percentage auto classified 0.507186483781\n", + "for prob 0.95, scoring only on high confidence predictions 0.977064777779\n", + "for prob 0.95, scoring on all predictions 0.856301691681\n", + "Found 759 high confidence predictions out of 1462\n", + "Found 696 high confidence predictions out of 1462\n", + "Found 714 high confidence predictions out of 1461\n", + "Found 741 high confidence predictions out of 1461\n", + "Found 727 high confidence predictions out of 1461\n", + "for prob 0.99, percentage auto classified 0.497741928537\n", + "for prob 0.99, scoring only on high confidence predictions 0.977424545567\n", + "for prob 0.99, scoring on all predictions 0.85890218176\n", + "[0.50636372403887298, 0.50718648378123032, 0.49774192853685095]\n", + "[0.8016959229122016, 0.79709152759423318, 0.78914885007163416]\n", + "[0.51157304997568454, 0.53105595112713222, 0.49744100519691192]\n", + "[0.081853693075685741, 0.066671574208509971, 0.041572501792357511]\n", + "[0.082803495311167943, 0.086026749580738041, 0.088412055780476839]\n", + "[0.20990625036900495, 0.20945332720504345, 0.21168702317574661]\n", + "[0.28797206860729074, 0.02222222222222222, 0.21168702317574661]\n", + "[0.97384021376187047, 0.9770647777794299, 0.97742454556683001]\n", + "[0.85657594492837497, 0.85630169168092229, 0.85890218175995869]\n", + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 95. 1. 0. 0. 4. 0.]\n", + " [ 8. 81. 3. 0. 7. 0.]\n", + " [ 7. 9. 17. 4. 63. 0.]\n", + " [ 5. 1. 3. 27. 64. 0.]\n", + " [ 3. 2. 4. 3. 87. 0.]\n", + " [ 25. 3. 0. 0. 13. 58.]]\n" + ] + }, + { + "data": { + "image/png": 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o6zhfQp+9bMvtHBRxXEUdn4iUf+ba/L+zxHBnrT1pjOkGvAC8BRjgU2CctTY7X1FD3isI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\nE4mKiiIyM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/Ts2ZO//e1vNG3alBo1avDXv/4Vu90OeH5e8wUFBbm8NhgMBAYGFklz1/+g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\n4rkk2bNNhcT7U5u8pyKy0+IEd58B/lszO+mcuw1gZ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TgBOAQyRNxFXeFYBh6fdO/Ivw01oqUQuSRgFtQP9w0hwE3Z8m9c5vCNxQInwS\nOTq6JS2HL3L3SzN7R8rfKllJXf1JhWMrAjuUCB8ObE0nCtEgCHoWTTLnBwLTSoS/AyyXI/0pwDPA\nRbUWXEmIrl9rZkEQBLWSU4gOStZvgTFmNqYZ5UvaCvg+sKnVIdErrTv/dCMVWwSsL+lMYDN86un5\nwCgzmy9pH3zd+jXTEqlAR1OAmSkT9nNc6x4CfAA8DxxvZtctmtMIgt5LDZ7tp5rZsArHp1Fa4yyn\noWY5D7gAeEXSsimsH9A37c9OPkNKUve6812A64E/ASfizqB/DcynaG35Skj6LnAaMBq4G1gS+Cx+\n4YMgWAQ0yZyfhLeLFrMB1Ydmrp+2Uk2Y04BDgd+WS1yzEJXUH9gEWBlYvFQcM7uq1nzr4HwzOyn9\nv03SMsBhksqebAm2AB4zs9GZsJubVsMgCKrSJCE6FjhV0tDCtHNJQ4AtgSOrpN2mRNhvgb7AwcBz\nJY5/TK0OSPYDjqe8pibcWfOiEKLFZVwB/Bj4TA15TAAOlHQW3rN3X1r6uSzpGuwH0Ldv3xqKCoKg\nmCYuVHc+PiX9BknH4HLoWOBl3FwHQNJgvMludEF5MrPxxZlJehfoV+pYMbnHiUraBfgDPqzpGFxg\n3gy0A7en/euAA/Pm2SBvlNlftYY8LsHn/G+Grw31TpoqNqRcAjMbY2bDzGxYnz61DLMNgqAUzRgn\nmlxxjsB72C/FB8xPBkaY2axMVOEaZtNe3lo00UNxAbqZmc2SdDwwoSDNJX0HuBg4q1mVq8KKwAtF\n++Crja6W/i8wKQD4VHYn9cSdB5yXxol9FW8jvRIXrEEQdDLNckBiZi/hq25UijOFHFPTzWx43nJr\nkcYbAWOLpPrH9qyZ/QXXSNtqyLMRdi/a3wOYBTwOFNZ5+ti0l9QPF5IlMbNpZnYl3kxQS5NAEAQN\n0GsWqktxp2b2Z7PwkILHqDxIv5nsm1zwTcB753+MD3GaLmkC3u5xSoozB29mWKAjTNIYfIXS+3Et\n+9O444LbFtE5BEGvpid4tq9FE30VWCWzPxn4fFGcdXCBtSgYibvdGwt8D1/S+ViANB10JN6ofBFw\nNvAPFp6NcC/wOeCcdPxo4DLcC0wQBIuA7r7ufC2a6P34Cp8FbgR+KemM9H9L3AnATc2r3sKY2Sg6\nxoKWGppQiDcJn4ZazKhMnIvxdtwgCFpEVzfXq1GLEL0MWEPS4LS2/EnAN4CfAz/DG2tfBw5vei2D\nIOixdHUNAJhoAAAXFklEQVRNsxq5haiZ/QM3eQv70yUNA74JrAW8BFxrZtObXssgCHok3cFcr0ZD\n0z7N7ANcQw2CIKiL3mTOB0EQNJ0eq4mWccqcBzOz8CcaBEFVmjjts2XU65S5EkY4ZQ6CICc9VhMl\nnDIHQbAI6LFCtBs4ZQ6CoAfQk835oArz589nzpxFNUFrYaZOnVo9Uify1ltvtazsnXfeuWVlA9Sy\nkFlQnl4/xCkIgqBRQogGQRA0QJjzQRAEDdDdNdFwzR4EQcvI48Epr5CVtLqkayRNlzQjrVKxRo50\ngyXdIOlFSbMlTZV0p6Sv5yk3hGgQBC2lGU6ZJS0FjAPWw11Z7oW75rxD0tJVkn8C95V8DPB14Ee4\nn+G/Sdq1WtlhzgdB0FKaZM7vCwwF1jWz5wAkPQY8C+wPnF6h/Em44PwYSX/DfSb/ALi2UsE1a6KS\nvi7pEkkPSnoiE/5pST+TtHKteQZB0Htpkjm/E/BAQYCmfCfjjtdH1lGnecB0YF61uLk10bTMxqX4\nWkYC5gL9M1Fm4Iu8LYX7Gg2CIKhIE+fOb4gve17MJOBbeTJIMq4PMAhfFv3TuL/kitSiiR4KfAe4\nAFiBIkFpZv8F7gF2rCHPIAh6OU3SRAcC00qEv8PCa8GV42TgQ9y5/C+APczs9mqJahGiPwAmmtl+\nZjYVdzRSzLPAmjXkGQRBLyenEB0kaWJm268TqvJbfN24bwB/By6XVFUprKVjaS18wbdKvEPR2u61\nIGlnYKiZlW0ErjPfi4DhZjakmfkGQdAYNZjzU81sWIXj0yitcZbTUEvV5RXglbR7k6TxwKlUWTeu\nFk30fWBAlTiDyVnhMuwM/L8G0pfjWGCXTsg3CIIGaZI5PwlvFy1mA+DJOqs2EVi7WqRahOgE4Otp\nPNZCSFoBH2N1bw151oWkxavH6sDMnjezhzurPkEQ1E+ThOhYYHNJQwsBkobgqxCPrbVOqZPpS8Dz\n1eLWIkRPB1YGbpb0mWxhkr4A3AwsDZxRW3U/zucifJDsqpIsbVMkDU//d5V0vqS3gDdSmrUlXSpp\ncppp8IKkcyUtV5y3pCmZ/SEpz/0ljZb0uqR3Jd0oabV66h8EQX00Y7A9cD4wBbhB0khJO+G99S8D\n5xUipdlJ8yT9JhM2StKZkr4taWtJ3wZuwZeIb6tWcC2rfd4m6RfA/wGPAh+lQ7NTPgYcZmb1aqLH\nAsvjDbs7pbA5dDQhnIU39u4FLJHCVgFeAw4D3sY7tY7CBfoWOcr8FXAf8EN8xMFp+MJ7w+s8hyAI\naqBZrvDM7D1JI3Al7lJ8GObtwCFmNisTVUBfFlQg/w0cgg/fHAD8F5dxW+WRZzXNWDKz0yTdDhyI\nS+mB+PjQB4GzzeyhWvIryvv5pGXONbMHCuGShqe/D5rZj4vS3AXclYl7L/AccLekTXKY8FPMbM9M\n+uWBUyStYmavlUqQegX3A+jTJ2bNBkGjNMsBiZm9BOxWJc4UXJBmw8ZSh8lfoOZpn2b2CEmILGKu\nKw6QtBhwOPB9vFNriczhdYFqQvTmov3H0+8auIa7EGY2BhgD0K9fv+7tfiYIugDhCm/R8XqJsBOB\ng4HRuFk+E1gNn+u6RIn4xbxTtF9wU58nbRAETaC7u8KrZdrn7nnjmtlV9VWncrYlwvYALjGz4woB\nkj7RCWUHQdAJ9LblQa6gtCDLohSnXiE6B1iyhvhL4dO0svygzrKDIGgBvcmcP6BM+ABgU+Cb+JCC\nWxuoz5PAQEkH4ANdP6gS/xZgb0mP4x1KuwJfbKD8IAgWMb1GEzWz8yodl7Q1LtR+20B9/ghsDpwA\nLAu8COxTIf7BuPZ7fNq/GXeS8mADdQiCYBHSa4RoNczszuTI9HhgqzrzeA8XgsWUXJ82OULZo1p8\nM9unaH9KqTzNbHy5soIgaD5NdIXXMprdO/8CsH2T8wyCoAcTmuiCbEnHMKEgCIKq9BohmubHl8tj\nVXze++bAn5tQryAIegG9zZx/gMpDnIT3qHeGK7sgCHoovUYTxV3nlzrb+bgP0QnAXdbdr0gQBIuU\n7i4yahnidGRnViQIgt5Jdzfnc7shknSfpBM7szJBEPQu8jhk7uqaai2+3D5L9WmfQRAENdEkp8wt\no5Y20SfwxeqChJkxZ07rRnT169daJ1z9+/dvWdljx9bt/rEpnH12tTUbg7x0dU2zGrVooqcCIyVt\n1lmVCYKg99Esc17S6pKukTRd0gxJ10paI0e6z0u6QNKzkt6X9JKkP0vKtfx7LapMH2AccJekK4CH\n8LWOFjrDTnKFFwRBD6NZ40TTAprj8Mk+e+Ny6TjgDkmfTVPKy/FtfKXQM3HH7KsAvwYmStrYzF6u\nVHY9rvCEr3O0FwsL0EZd4QVB0Mtokjm/LzAUWNfMngOQ9BjwLLA/vtBmOU42s8OzAWmpockp39+U\nTJVohiu8IAiCummSEN0JeKAgQFO+k5MwHEkFIWpmb5YIezGt+bZqtYKb5govCIKgVpo47XND3J9x\nMZOAb9WamaT18RWA/1MtbsWOpbSO+89qrUAQBEFemtSxNBCfOVnMO8BytdRHUj/gD8BbwAXV4lfT\nRIfgzpGDIAg6hZxCcpCkiZn9MWnl3c7g9/gKGTuYWSnBvADdabXPIAh6GDWY81PNbFiF49MorXGW\n01BLIukkfEn4vc3stjxpQogGQdBSmtSxNAlvFy1mA3zttqpIOho4AjjYzC7NW3CewfbdezpBEARd\nmia1iY4FNpc0tBAgaQjuKL7q9LbU93MccLSZ/b6W+ufRRA+VVMsyxGZmMT00CIJcNKl3/nzgIOAG\nScfgyt+xwMvAxyOLJA0GngdGm9noFLYHvsDmLcA4SZtn8p1hZhU12TxCdFl6YeeSJAH9zWxuq+sS\nBD2VZnlpMrP3JI0AzgAuxSf+3A4cYmazMlEF9GVBK3z7FL49C68RdycwvFLZecz5UWbWp5YtR55N\nRdJGkq6T9Lak2ZKelvSrdOyrkm6W9HqaF/uEpMMk9S3KY4qkyyT9UNJTwFxgh0V9LkHQ22jW3Hkz\ne8nMdjOzZczsk2a2c1rZNxtnipnJzEZlwvZJYaW24dXK7fYdS2ntp/HAc8ChwCvAOrjrPvCpYOOB\nc4D3gGHAKGB5oNjR9DbAxkA78CYwpROrHgQB3d8pc7cXorh3qbeBzc3s/RQ2rnDQzP5Q+J9M9LuB\nxYDDJR1lZtk7uBzwOTP7b+dXOwgC6P6u8Lq1EE2eW7YETskI0OI4K+Oa5/a4d5bsOa8AZAXmA9UE\nqKT98HFkuEwOgqBeuoPn+mp0ayGKa459cBN+IST1wYc3rIIL0qeA2cDOwNHAEkVJXq9WYJolMQag\nb9++3fvuB0EXoEeb863oJKqRafhqo+U8rayFt4HuZWaXFQIlfaNM/BCKQbCI6e6aaFcXkhVJJvw9\nwPckLVkiylLp98NCgKT+wHcXQfWCIMhBd1+orrub8wCH42O57pd0Gm7aD8V72Q8DXgSOl/QRLkwP\nbVVFgyBYkCa6wmsZ3VoTBTCzCXjn0svAWcDNwC+AV9JA+Z3xzqNLgLOBu4CTWlPbIAiKCU20C2Bm\nDwMl2znN7BHgSyUO/bEo3pDm1ywIgmp0dSFZjR4hRIMg6J70BHM+hGgQBC0lNNEgCIIGCCEaBEHQ\nAGHOB0EQ1El36H2vRgjRIAhaSncXot1+nGgQBN2b+fPnV93yIGl1SddImi5phqRrJa2RM+0Jkm5L\nPolN0j556x9CNAiCltKMwfbJo9s4YD1gb2Av3K/wHZKWzlGNg4ElgZtqrX+Y80EQtIwmtonui0/3\nXtfMngOQ9BjwLLA/cHqV9APMbL6ktYHv11JwCNEGGDBgANttt13Lyr/55ptbVjbAu+++29LyW8nw\n4cNbWv51113XsrIPP/zwpubXpN75nXB/wM8VAsxssqR7gZFUEaJFztlrIsz5IAhaSpPmzm8IPFEi\nfBK+9nynEZpoEAQtpUnm/EDcv3Ax7+DO2zuNEKJBELSMGubOD5I0MbM/Jq0y0XJCiAZB0FJyaqJT\nzWxYhePTKK1xltNQm0YI0SAIWkqTOpYm4e2ixWwAPNmMAsoRHUtBELSMPJ1KOTXVscDmkoYWAiQN\nwR22j+2UyidCiAZB0FKaJETPB6YAN0gaKWkn4AZ8xYvzCpEkDZY0T9JvsoklbS3pm/jS6gDDJH0z\nhVUkzPkgCFpKM8x5M3tP0gjgDOBSQMDtwCFmNisTVUBfFlYg24GtM/s/TVshTVlCiAZB0FKa5YDE\nzF4CdqsSZwolhKKZDa+33F5pzku6SNKUVtcjCHo7TWwTbRm9VRM9FvhdqysRBEE4Ze6WmNnz1eJI\n6g/Ms67+GQyCbk53f8V6lDkvaW1Jl0qaLGm2pBcknStpuaJ4C5jzkoYkH4IHSjpZ0mvAHGDZRXwK\nQdDrCHO+a7EK8BpwGPA2sCZwFHAzsEWO9EcDE4D98B68DzqnmkEQQCyZ3OUws7uAuwr7yQ3Wc8Dd\nkjYxs4erZPEGsEuY8EGw6Ojur1tPM+cXk3SUpKckzQY+BO5Oh9fNkcX11QSopP0kTZQ0cc6cOY1W\nOQh6PWHOdy1OxN38jwbuA2YCqwHXAkvkSP96tQjJc8wYgIEDB3btuxsEXZww57seewCXmNlxhQBJ\nn6ghfQjFIFjEdHVNsxo9TYguhZvwWX7QiooEQZCPEKJdi1uAvSU9jnco7Qp8sbVVCoKgEmHOdy0O\nxufFHp/2bwa+AzzYshoFQVCW7tBxVI0eJUTNbCreLlqMiuLtU7Q/pThOEASLhhCiQRAEDRDmfBAE\nQQOEJhoEQVAnPaFNtEfNWAqCoPsxf/78qlseJK0u6RpJ0yXNkHStpDVypl1C0imSXk/Oi+6X9OU8\naUOIBkHQUpox7VPSUsA4YD1gb2AvYB3gDklL56jGBcC+wG+AHfHZi7dK2rhawjDngyBoKU0y5/cF\nhgLrmtlzAJIeA54F9gdOL5dQ0kbAnsAPzezCFHYnvgzzaGCnSgWHJhoEQcsozJ1vgjm/E/BAQYCm\nvCcD9wIjc6T9ELgyk3YecAXwNUmLV0ocQjQIgpbSJC9OGwJPlAifBGyQI+1kM3u/RNrFgLUrJQ5z\nPgiCltIkc34gMK1E+DvAciXC86YtHC9LCNEGmDZt2tSrrrrqxTqTDwKmNrM+Uf6iK/+RRx5pafm7\n7LJLy8oGBjdSeBG3mtmgHPGWkDQxsz8muaVsOSFEG8DMlq83raSJZjasmfWJ8qP8rl52MWa2fZOy\nmkZpjbOcllmcttSHoaCBvlPi2MdEm2gQBD2BSXjbZjEbAE/mSLtmGiZVnHYu7hGuLCFEgyDoCYwF\nNpc0tBAgaQiwZTpWiRuB/sC3Mmn7Ad8GbjOziusAhRBtHa1uz6m7/MwS0xcVhY+XlLeXoGXnL2k8\n8LmccYencx3VQHml8mja+Ze7HxVo9bPXGZwPTAFukDRS0k7ADcDLwHmFSJIGS5on6TeFsLSA5ZXA\nbyX9WNK2+PCmNYG2agWHEG0ReRrFMy9HdpsjaYqkP0laqzPL70xKlZ/Ob3wLqrPIaeX1b/W97wzM\n7D1gBPAMcCnwZ2AyMMLMZmWiCl8OvVj2/QC4EDgO+BuwOrC9mf27WtnRsdQ9eBa4PP1fBhiO3/Rd\nJG1mZs+0qmJFfB9foiUIFjlm9hKwW5U4UyjhO9jMZgP/L201EUK0e/CMmY0q7EgS/tXcGzg6/bac\n9BAHQa8izPluiPno5HPS7sdDVQptkskjzQmSJkv6UNIhmTgrSTpT0gupaeANSZdJWrNUWZIOlPQf\nSR+kNEfj5lCpuCXbRFN9fiHp35JmJQ87j0g6TlL/Qpthir51UfPFPpl8+kjaV9K/Uj6zJN0nadcy\n9dlY0q0p3rTk4SeXV59qSNpF0pXpmsxO+f9T0leqpBsu6e5Up7clXSpp5TJxN5F0dbpHcyQ9L+lE\n1baCbdDJhCba/SnVkXMd8Bl84b4ZwCsAktYBxgMr4etP/RVv+9kdnyO8uZk9X8hE0mjg18CrwB/w\nj+7PgC3yVi4NG7kd2Bz4D94BYLi3nV8Cp+IdAu14I/6LwEWZLB5J+Qj4S6rrk8DF6fgOwF8lHWJm\nv8uU+1ngbmBJ4OpUxtbAPVQfN5iHE4A5wJ3Af4GVgZ1xzz/fMrNrS6TZAvgVcBNwJv4B/B6wpaTP\nm9nbmfrvgnduzAWuT2VsChwJbCPpy2Y2twnnETRKnnmrsbVmA4bgAuemEsf+lI5dmAkbn8IeApYt\nkeZ+/MX/clH4FrgDhpsyYesA8/DG+YGZ8JWBN1I5FxXlM56kKGfCTk9xzwf6FB1bEeiX2TdgfJlr\nsX86fjbQNxO+NPCvdF6rZMLvSvF3Lcrn4hRupcopUe7wFH9UUfiaJeKuiH+wniuTh+GegrLHjk3h\nZ2XCBuEfvxey55SO/SLFP7zEc3JRnnOKrblbyysQW4Wb0/FyPAOMStvpwMQU/g6wTiZ+QYjuWCKv\nTdOxc8qUdQ3wETAg7f8mxT+oRNyj8ghR3NKZAbwNLJPjfCsJ0ceAd4HFShzbMVtXfPaJARNLxF0D\n/zhYtfqk+CWFaIX4Z6b4Q0rk8RSgovhLp/s4rXAM79wwYPcS+fcB3syeWwjR1m5hzncP1qFjvNqH\nwGu4JnqcubuvYiaWCNss/a5aZszjyvgLuk5Kv1EKv6dE3FJhpVgP+CTwdzObkTPNQqQmgc/gY/6O\ncst+AQrTb9dLv58tV08ze0nSS/gYwLqRtBJumv8v3iSyRFGUlfEmhCz3WpJ6mfq8J+kRYBtc+E+h\n415tKamUB6IP6TjXoMWEEO0e/M3Mdqwh/hslwgrzgHeispPZghfwAen3rZz5l6KQx2s545djOXxY\nyhpUHvycp+7g9a9biEoaCDwIrIYL6r8D04H5uNa5NVDKB+WbFeoDHfUu3Kuf1VvHYNERQrQHUqzt\nJAqa4AFm9occ2UxPv8vjHUtZVsxZlXfT7yo545ejUPd/mdnmOeJn616KvPUvx49w7fNoMzshe0DS\nubgQLcUKVepTqHfhfNc3s6caqWjQ+cQQp97Dg+k3jxACeDT9fqnEsVJhpXgamAlsJmmZHPHnU2L4\nlJnNxNsTN5D0yRz5PFaunmmIU6PDnAozxRaYk51GEFQaubClitoi5Ov/bIx/cApuFWu9V0ELCSHa\nSzCzf+Ev516Sdi4+nsZrZoXOFXhH02HJfC3EWxn4ec4y5+G98gOBUyUt8LxJWkHu6KHAO7iJXIqz\n8PbVP0gqbn9E0oaSVkjlvogPb/pciTGkx1JmnGsNFCYVbFkUfggdbcmlWBefaZblSLy54rKMBXEh\nMAs4UdK6xZlIGiBpk5prHXQKYc73LvYE7gCuk3QP8DDeUz0Y2AoXYusBmNkzkk7Ax4k+JulqXPh8\nG5iAj8/Mw69xYbMvrondimucnwa+hpuyBbN/HLC7pOtT3T4CxprZY8C5wBeB7wJbSRpHx/jM/wE2\nwbXAQrvjwXh75VWp7lNwM3s1XFMtdD7Vw6XAEcDvJQ3HmzuG4Zrj3yh/bW4DzpW0A66lDwO2w4eR\njSpEMrM3JX0Xd4rxuKSb8am/S+NtucPxoVo/aeAcgmbR6uEBsZXfqDBOtEz88VQZugN8CjgRH7A+\nG29/+w++ZOy2JeIfiJvSc/CX/WjcnM01TjSFL4n3ZD+eypyOD6IfDfTPxFsJFxxv4QLUgH2K8vou\n/iGYlur0EnArcACwdFHcTXDB9V6Kfw1uyle9Tpk8hlN6nOgmwD9SvtNTHT6PC0MDhpfKI/2/O9Xp\nHVwgr1Km7A3wiQcv44PupwL/Bk4C1ivxnFyU55xia+5WGJcWBEEQ1EG0iQZBEDRACNEgCIIGCCEa\nBEHQACFEgyAIGiCEaBAEQQOEEA2CIGiAEKJBEAQNEEI0CIKgAUKIBkEQNEAI0SAIggb4//XpovVA\n3X6FAAAAAElFTkSuQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices+BusTrainFeatureIndices], cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices+BusTrainFeatureIndices], cleanedResultVector, \"Generic + Advanced + BusTrain\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic_advanced_bustrain.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generic + Advanced + BusTrain + Location model" + ] + }, + { + "cell_type": "code", + "execution_count": 112, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 706 high confidence predictions out of 1462\n", + "Found 744 high confidence predictions out of 1462\n", + "Found 707 high confidence predictions out of 1461\n", + "Found 764 high confidence predictions out of 1461\n", + "Found 700 high confidence predictions out of 1461\n", + "for prob 0.9, percentage auto classified 0.495552116076\n", + "for prob 0.9, scoring only on high confidence predictions 0.983966908543\n", + "for prob 0.9, scoring on all predictions 0.884358107887\n", + "Found 739 high confidence predictions out of 1462\n", + "Found 729 high confidence predictions out of 1462\n", + "Found 754 high confidence predictions out of 1461\n", + "Found 730 high confidence predictions out of 1461\n", + "Found 803 high confidence predictions out of 1461\n", + "for prob 0.95, percentage auto classified 0.513894030942\n", + "for prob 0.95, scoring only on high confidence predictions 0.983262766583\n", + "for prob 0.95, scoring on all predictions 0.882579253945\n", + "Found 731 high confidence predictions out of 1462\n", + "Found 749 high confidence predictions out of 1462\n", + "Found 750 high confidence predictions out of 1461\n", + "Found 737 high confidence predictions out of 1461\n", + "Found 716 high confidence predictions out of 1461\n", + "for prob 0.99, percentage auto classified 0.504036644504\n", + "for prob 0.99, scoring only on high confidence predictions 0.986429773778\n", + "for prob 0.99, scoring on all predictions 0.887641094354\n", + "[0.49555211607588456, 0.51389403094220842, 0.50403664450355856]\n", + "[0.77195239360720969, 0.78789397635178404, 0.78321509955316593]\n", + "[0.4251570460891827, 0.46869386163978649, 0.42589510859533286]\n", + "[0.049954624363599043, 0.043906693111361264, 0.056616976158780599]\n", + "[0.068965825296708444, 0.097516058820406634, 0.07331698841933057]\n", + "[0.26826550330811239, 0.2782927100351687, 0.27485453333708804]\n", + "[0.26821589877746876, 0.125, 0.27485453333708804]\n", + "[0.98396690854276303, 0.98326276658344547, 0.98642977377768781]\n", + "[0.8843581078866769, 0.8825792539450239, 0.88764109435379124]\n", + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 95. 1. 1. 0. 3. 0.]\n", + " [ 10. 82. 1. 0. 7. 0.]\n", + " [ 9. 6. 26. 4. 54. 0.]\n", + " [ 4. 1. 3. 42. 49. 0.]\n", + " [ 4. 3. 3. 3. 86. 0.]\n", + " [ 7. 3. 0. 3. 33. 53.]]\n" + ] + }, + { + "data": { + "image/png": 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M8fHxNGrUiIyMDJ588kmGDRvG6dOnadu2LU8++STJycnlGlNJvj7nDhw4QFRU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\nA70+V3x9jq5atYqPP/6YN99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du+jcuTMPPPAAVapUYfPmzaSlpZGdne0Mxh9//DFDhw51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63H0vE827dvD4VCIYRWmy+++AImkwlxcXFu25iQkACJRILly5eLwm5Z9Ho9zGazU++uu9lJbW2P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\nwHHOQaOBi6LkFoa4MIRGg+D223f78EaicCciIiIiIkNzzUAUR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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices+BusTrainFeatureIndices\n", + " +LocationFeatureIndices], cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix[:,genericFeatureIndices+AdvancedFeatureIndices+BusTrainFeatureIndices\n", + " +LocationFeatureIndices], cleanedResultVector, \"Gen + Adv + BusTrain + Loc\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic_advanced_bustrain_location.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generic + Advanced + BusTrain + Location + Time model" + ] + }, + { + "cell_type": "code", + "execution_count": 113, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 707 high confidence predictions out of 1462\n", + "Found 736 high confidence predictions out of 1462\n", + "Found 701 high confidence predictions out of 1461\n", + "Found 714 high confidence predictions out of 1461\n", + "Found 728 high confidence predictions out of 1461\n", + "for prob 0.9, percentage auto classified 0.490761532635\n", + "for prob 0.9, scoring only on high confidence predictions 0.983838138873\n", + "for prob 0.9, scoring on all predictions 0.880386913373\n", + "Found 704 high confidence predictions out of 1462\n", + "Found 721 high confidence predictions out of 1462\n", + "Found 750 high confidence predictions out of 1461\n", + "Found 719 high confidence predictions out of 1461\n", + "Found 700 high confidence predictions out of 1461\n", + "for prob 0.95, percentage auto classified 0.491858358357\n", + "for prob 0.95, scoring only on high confidence predictions 0.983652461362\n", + "for prob 0.95, scoring on all predictions 0.884632548402\n", + "Found 681 high confidence predictions out of 1462\n", + "Found 688 high confidence predictions out of 1462\n", + "Found 687 high confidence predictions out of 1461\n", + "Found 709 high confidence predictions out of 1461\n", + "Found 770 high confidence predictions out of 1461\n", + "for prob 0.99, percentage auto classified 0.483786942025\n", + "for prob 0.99, scoring only on high confidence predictions 0.981051280812\n", + "for prob 0.99, scoring on all predictions 0.882031309253\n", + "[0.49076153263463829, 0.49185835835695241, 0.48378694202479233]\n", + "[0.7630528327855115, 0.77114642653348653, 0.77421094719960093]\n", + "[0.42736888918544996, 0.43809871399728878, 0.41140915302105785]\n", + "[0.048841922059239089, 0.045097701971630981, 0.054271336553945247]\n", + "[0.073762225485331651, 0.051996569673520662, 0.079534629292880285]\n", + "[0.2600210796400943, 0.2521147243880118, 0.22838317888915957]\n", + "[0.26217449152593775, 0.0, 0.22838317888915957]\n", + "[0.98383813887335347, 0.98365246136166196, 0.98105128081241855]\n", + "[0.88038691337286556, 0.88463254840162509, 0.88203130925260598]\n", + "nClasses = 6\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "Number of distinct classes in training set = [ 1. 3. 5. 6. 7. 9.], test set = [ 1. 3. 5. 6. 7. 9.]\n", + "[[ 95. 1. 1. 0. 3. 0.]\n", + " [ 9. 82. 2. 0. 7. 0.]\n", + " [ 11. 6. 25. 3. 55. 0.]\n", + " [ 6. 2. 3. 42. 47. 0.]\n", + " [ 4. 3. 4. 3. 86. 0.]\n", + " [ 7. 3. 0. 7. 10. 73.]]\n" + ] + }, + { + "data": { + "image/png": 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GUVFRFBQU0K5dO5/2xVdHjx6latWqBAcHu5THxsY613tz5MgRatWqVabt5ebm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\nc0SfR3+utv/v1n4uncRae+AewN8EAuB807YXid6I/9YGbX+itt+5pm1dw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4strLgVFmNl/SAcBVwNppu1ugxY1gZsqkHY1b5wOB/wIvAz83s1s75jKCoOdS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\nQZAz/x8q4mwuAHSo8QAAAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "forestClf = ensemble.RandomForestClassifier()\n", + "exploreKFoldValidationSpace(forestClf, cleanedFeatureMatrix, cleanedResultVector, 5)\n", + "currCM, fig = printConfusionMatrix(forestClf, cleanedFeatureMatrix, cleanedResultVector, \"Gen + Adv + BusTrain + Loc + Time\")\n", + "modelCMList.append(currCM)\n", + "fig.savefig(saveDir+\"cm_generic_advanced_bustrain_location_time.png\", bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "It seems that with all the features in, we can have the best prediction result." + ] + }, + { + "cell_type": "code", + "execution_count": 114, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "7 (7, 6)\n", + "[[ 94.7508 80.0461 19.0077 23.4044 86.4984 44.6667]\n", + " [ 95.1168 79.1115 18.2484 29.6995 86.7234 51.3333]\n", + " [ 94.9947 82.0052 31.6051 40.8415 84.9798 60. ]\n", + " [ 94.9949 80.7929 16.1871 25.7268 85.1134 48.6667]\n", + " [ 94.5984 81.2562 16.953 26.7049 86.7229 58. ]\n", + " [ 95.1168 81.6323 25.6876 42.4645 86.2308 53.3333]\n", + " [ 94.9641 82.286 24.662 42.1366 85.7413 73.3333]]\n", + "[[ 95. 80. 19. 23. 86. 45.]\n", + " [ 95. 79. 18. 30. 87. 51.]\n", + " [ 95. 82. 32. 41. 85. 60.]\n", + " [ 95. 81. 16. 26. 85. 49.]\n", + " [ 95. 81. 17. 27. 87. 58.]\n", + " [ 95. 82. 26. 42. 86. 53.]\n", + " [ 95. 82. 25. 42. 86. 73.]]\n" + ] + } + ], + "source": [ + "cmDiagList = []\n", + "modelLabels = [\"Generic\", \"G+A\", \"G+A+L\", \"G+B\", \"G+A+B\", \"G+A+B+L\", \"G+A+B+L+T\"]\n", + "for currCM in modelCMList:\n", + " cmDiagList.append(np.diag(currCM) * 100)\n", + "accuracyMatrix = np.vstack(cmDiagList)\n", + "print(len(modelLabels), accuracyMatrix.shape)\n", + "np.set_printoptions(precision=4)\n", + "print(accuracyMatrix)\n", + "np.set_printoptions(precision=0)\n", + "print(accuracyMatrix)" + ] + }, + { + "cell_type": "code", + "execution_count": 115, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "7 (7, 6)\n", + "[['Generic' 95.0 80.0 19.0 23.0 86.0 45.0]\n", + " ['G+A' 95.0 79.0 18.0 30.0 87.0 51.0]\n", + " ['G+A+L' 95.0 82.0 32.0 41.0 85.0 60.0]\n", + " ['G+B' 95.0 81.0 16.0 26.0 85.0 49.0]\n", + " ['G+A+B' 95.0 81.0 17.0 27.0 87.0 58.0]\n", + " ['G+A+B+L' 95.0 82.0 26.0 42.0 86.0 53.0]\n", + " ['G+A+B+L+T' 95.0 82.0 25.0 42.0 86.0 73.0]]\n" + ] + } + ], + "source": [ + "cmDiagList = []\n", + "modelLabels = [\"Generic\", \"G+A\", \"G+A+L\", \"G+B\", \"G+A+B\", \"G+A+B+L\", \"G+A+B+L+T\"]\n", + "for currCM in modelCMList:\n", + " cmDiagList.append(np.diag(currCM) * 100)\n", + "accuracyMatrix = np.vstack(cmDiagList).round(decimals=0).astype(object)\n", + "print(len(modelLabels), accuracyMatrix.shape)\n", + "outputMatrix = np.insert(accuracyMatrix, 0, modelLabels, axis=1)\n", + "print(outputMatrix)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.1" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/percom_moves_collect_2014/modes.json b/percom_moves_collect_2014/modes.json new file mode 100644 index 0000000..85d7a5a --- /dev/null +++ b/percom_moves_collect_2014/modes.json @@ -0,0 +1,11 @@ +[ + { "mode_id": 1,"mode_name":"walking"}, + { "mode_id": 2,"mode_name":"running"}, + { "mode_id": 3,"mode_name":"cycling"}, + { "mode_id": 4,"mode_name":"transport"}, + { "mode_id": 5,"mode_name":"bus"}, + { "mode_id": 6,"mode_name":"train"}, + { "mode_id": 7,"mode_name":"car"}, + { "mode_id": 8,"mode_name":"mixed"}, + { "mode_id": 9,"mode_name":"air"} +] diff --git a/percom_moves_collect_2014/setup.sh b/percom_moves_collect_2014/setup.sh new file mode 100644 index 0000000..918e09b --- /dev/null +++ b/percom_moves_collect_2014/setup.sh @@ -0,0 +1,2 @@ +source activate emission +cp -r $EMISSION_SERVER_HOME/conf . diff --git a/percom_moves_collect_2014/teardown.sh b/percom_moves_collect_2014/teardown.sh new file mode 100644 index 0000000..799c85d --- /dev/null +++ b/percom_moves_collect_2014/teardown.sh @@ -0,0 +1,2 @@ +source deactivate emission +rm -r $EMISSION_SERVER_HOME/conf diff --git a/percom_moves_collect_2014/testFeatureCalcData.json b/percom_moves_collect_2014/testFeatureCalcData.json new file mode 100644 index 0000000..1949105 --- /dev/null +++ b/percom_moves_collect_2014/testFeatureCalcData.json @@ -0,0 +1,397 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