From 0e182cdacb6d7e90b2bd8929691c1fd78d470c97 Mon Sep 17 00:00:00 2001 From: Angelos Chatzimparmpas Date: Wed, 27 Jan 2021 19:43:47 +0100 Subject: [PATCH] new --- __pycache__/run.cpython-38.pyc | Bin 38997 -> 40259 bytes .../metadata.json | 1 + .../output.pkl | Bin 0 -> 116 bytes .../metadata.json | 1 + .../output.pkl | Bin 0 -> 116 bytes .../metadata.json | 1 + .../output.pkl | Bin 0 -> 116 bytes .../metadata.json | 1 + .../output.pkl | Bin 0 -> 116 bytes .../metadata.json | 1 + .../output.pkl | Bin 0 -> 116 bytes .../metadata.json | 1 + .../output.pkl | Bin 0 -> 116 bytes .../metadata.json | 1 + .../output.pkl | Bin 0 -> 116 bytes .../metadata.json | 1 + .../output.pkl | Bin 0 -> 116 bytes .../metadata.json | 1 + .../output.pkl | Bin 0 -> 116 bytes .../metadata.json | 1 + .../output.pkl | Bin 0 -> 116 bytes .../metadata.json | 1 + .../output.pkl | Bin 0 -> 116 bytes .../metadata.json | 1 + .../output.pkl | Bin 0 -> 116 bytes .../metadata.json | 1 + .../output.pkl | Bin 0 -> 116 bytes 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625.669164\n2 2.1 3.0 1210.967074 5.9 2543.030856\n3 1.8 2.9 543.571910 5.6 978.429438\n4 2.2 3.0 664.141633 5.8 1461.111593\n.. ... ... ... ... ...\n145 0.3 3.0 120.510418 1.4 36.153125\n146 0.2 3.8 163.021907 1.6 32.604381\n147 0.2 3.2 98.484316 1.4 19.696863\n148 0.2 3.7 199.336810 1.5 39.867362\n149 0.2 3.3 147.413159 1.4 29.482632\n\n[150 rows x 5 columns]", "clf": "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n colsample_bynode=1, colsample_bytree=0.9223705789444759,\n eta=0.08487346516301046, gamma=0, gpu_id=-1,\n importance_type='gain', interaction_constraints='',\n learning_rate=0.0848734677, max_delta_step=0, max_depth=7,\n min_child_weight=1, missing=nan, monotone_constraints='()',\n n_estimators=76, n_jobs=12, num_parallel_tree=1,\n objective='multi:softprob', probability=True, random_state=42,\n reg_alpha=0, reg_lambda=1, scale_pos_weight=None, silent=True,\n subsample=0.8912139968434072, tree_method='exact',\n use_label_encoder=False, validate_parameters=1, ...)"}} \ No newline at end of file diff --git a/extra_data_sets/vehicle.csv b/extra_data_sets/vehicle.csv index 5c19654..2ce3c03 100644 --- a/extra_data_sets/vehicle.csv +++ b/extra_data_sets/vehicle.csv @@ -1,294 +1,294 @@ COMPACTNESS,CIRCULARITY,DISTANCE_CIRCULARITY,RADIUS_RATIO,PR_AXIS_ASPECT_RATIO,MAX_LENGTH_ASPECT_RATIO,SCATTER_RATIO,ELONGATEDNESS,PR_AXIS_RECTANGULARITY,MAX_LENGTH_RECTANGULARITY,SCALED_VARIANCE_MAJOR,SCALED_VARIANCE_MINOR,SCALED_RADIUS_OF_GYRATION,SKEWNESS_ABOUT_MAJOR,SKEWNESS_ABOUT_MINOR,KURTOSIS_ABOUT_MAJOR,KURTOSIS_ABOUT_MINOR,HOLLOWS_RATIO,Class* 95,48,83,178,72,10,162,42,20,159,176,379,184,70,6,16,187,197,van 91,41,84,141,57,9,149,45,19,143,170,330,158,72,9,14,189,199,van -104,50,106,209,66,10,207,32,23,158,223,635,220,73,14,9,188,196,saab +104,50,106,209,66,10,207,32,23,158,223,635,220,73,14,9,188,196,car 93,41,82,159,63,9,144,46,19,143,160,309,127,63,6,10,199,207,van 85,44,70,205,103,52,149,45,19,144,241,325,188,127,9,11,180,183,bus 107,57,106,172,50,6,255,26,28,169,280,957,264,85,5,9,181,183,bus 97,43,73,173,65,6,153,42,19,143,176,361,172,66,13,1,200,204,bus 90,43,66,157,65,9,137,48,18,146,162,281,164,67,3,3,193,202,van 86,34,62,140,61,7,122,54,17,127,141,223,112,64,2,14,200,208,van -93,44,98,197,62,11,183,36,22,146,202,505,152,64,4,14,195,204,saab +93,44,98,197,62,11,183,36,22,146,202,505,152,64,4,14,195,204,car 86,36,70,143,61,9,133,50,18,130,153,266,127,66,2,10,194,202,van -90,34,66,136,55,6,123,54,17,118,148,224,118,65,5,26,196,202,saab +90,34,66,136,55,6,123,54,17,118,148,224,118,65,5,26,196,202,car 88,46,74,171,68,6,152,43,19,148,180,349,192,71,5,11,189,195,bus 89,42,85,144,58,10,152,44,19,144,173,345,161,72,8,13,187,197,van 94,49,79,203,71,5,174,37,21,154,196,465,206,71,6,2,197,199,bus -96,55,103,201,65,9,204,32,23,166,227,624,246,74,6,2,186,194,opel +96,55,103,201,65,9,204,32,23,166,227,624,246,74,6,2,186,194,car 89,36,51,109,52,6,118,57,17,129,137,206,125,80,2,14,181,185,van 99,41,77,197,69,6,177,36,21,139,202,485,151,72,4,10,198,199,bus -104,54,100,186,61,10,216,31,24,173,225,686,220,74,5,11,185,195,saab -101,56,100,215,69,10,208,32,24,169,227,651,223,74,6,5,186,193,opel +104,54,100,186,61,10,216,31,24,173,225,686,220,74,5,11,185,195,car +101,56,100,215,69,10,208,32,24,169,227,651,223,74,6,5,186,193,car 84,47,75,153,64,6,154,43,19,145,175,354,184,75,0,3,185,192,bus 84,37,53,121,59,5,123,55,17,125,141,221,133,82,7,1,179,183,van 94,43,64,173,69,7,150,43,19,142,169,344,177,68,9,1,199,206,bus 87,39,70,148,61,7,143,46,18,136,164,307,141,69,1,2,192,199,bus -99,53,105,219,66,11,204,32,23,165,221,623,224,68,0,6,191,201,saab +99,53,105,219,66,11,204,32,23,165,221,623,224,68,0,6,191,201,car 85,45,80,154,64,9,147,45,19,148,169,324,174,71,1,4,188,199,van -83,36,54,119,57,6,128,53,18,125,143,238,139,82,6,3,179,183,saab -107,54,98,203,65,11,218,31,25,167,229,696,216,72,1,28,187,199,saab +83,36,54,119,57,6,128,53,18,125,143,238,139,82,6,3,179,183,car +107,54,98,203,65,11,218,31,25,167,229,696,216,72,1,28,187,199,car 102,45,85,193,64,6,192,33,22,146,217,570,163,76,6,7,195,193,bus -80,38,63,129,55,7,146,46,19,130,168,314,158,83,9,20,180,185,saab +80,38,63,129,55,7,146,46,19,130,168,314,158,83,9,20,180,185,car 89,43,85,160,64,11,155,43,19,151,173,356,174,72,5,9,185,196,van -88,42,77,151,58,8,140,47,18,142,165,293,158,64,10,11,198,205,saab -93,35,66,154,59,6,142,46,18,128,162,304,120,64,5,13,197,202,opel -101,48,107,222,68,10,208,32,24,154,232,641,204,70,5,38,190,202,opel -87,38,85,177,61,8,164,40,20,129,186,402,130,63,1,25,198,205,opel +88,42,77,151,58,8,140,47,18,142,165,293,158,64,10,11,198,205,car +93,35,66,154,59,6,142,46,18,128,162,304,120,64,5,13,197,202,car +101,48,107,222,68,10,208,32,24,154,232,641,204,70,5,38,190,202,car +87,38,85,177,61,8,164,40,20,129,186,402,130,63,1,25,198,205,car 100,46,90,172,67,9,157,43,20,150,170,363,184,67,17,7,192,200,van 82,44,72,118,52,7,152,44,19,147,174,340,177,82,2,2,180,185,bus 90,48,86,306,126,49,153,44,19,156,272,346,200,118,0,15,185,194,van -106,53,98,176,54,10,216,31,24,171,235,691,218,74,1,9,187,197,saab +106,53,98,176,54,10,216,31,24,171,235,691,218,74,1,9,187,197,car 81,45,68,169,73,6,151,44,19,146,173,336,186,75,7,0,183,189,bus -95,48,104,214,67,9,205,32,23,151,227,628,202,74,5,9,186,193,opel +95,48,104,214,67,9,205,32,23,151,227,628,202,74,5,9,186,193,car 88,37,51,105,52,5,119,57,17,128,135,207,125,86,8,16,179,183,van 94,49,87,137,54,11,158,43,20,162,178,366,186,75,5,5,183,194,van -93,37,76,183,63,8,164,40,20,134,191,405,139,67,4,7,192,197,saab -119,54,106,220,65,12,213,31,24,167,223,675,232,66,20,1,192,202,saab +93,37,76,183,63,8,164,40,20,134,191,405,139,67,4,7,192,197,car +119,54,106,220,65,12,213,31,24,167,223,675,232,66,20,1,192,202,car 93,46,82,145,58,11,159,43,20,160,180,371,189,77,2,4,183,194,van 91,43,70,133,55,8,130,51,18,146,159,253,156,70,1,8,190,194,van 85,42,66,122,54,6,148,46,19,141,172,317,174,88,6,14,180,182,bus 89,47,81,147,64,11,156,44,20,163,170,352,188,76,6,13,184,193,van -91,45,79,176,59,9,163,40,20,148,184,404,179,62,0,10,199,208,saab -78,38,63,115,51,6,142,47,19,130,162,299,146,77,2,4,181,185,saab -92,38,71,174,66,7,154,43,19,133,181,355,130,70,4,24,189,195,saab -98,55,101,228,70,9,210,31,24,168,236,661,245,72,1,6,188,197,opel +91,45,79,176,59,9,163,40,20,148,184,404,179,62,0,10,199,208,car +78,38,63,115,51,6,142,47,19,130,162,299,146,77,2,4,181,185,car +92,38,71,174,66,7,154,43,19,133,181,355,130,70,4,24,189,195,car +98,55,101,228,70,9,210,31,24,168,236,661,245,72,1,6,188,197,car 101,42,62,175,67,6,149,43,19,139,169,341,165,65,7,11,202,209,bus 101,56,104,185,53,6,257,26,28,168,275,956,230,83,5,26,180,184,bus 94,36,66,151,61,8,133,50,18,135,154,265,119,62,9,3,201,208,van -97,44,96,195,63,9,185,36,22,144,202,512,165,66,4,8,191,199,saab +97,44,96,195,63,9,185,36,22,144,202,512,165,66,4,8,191,199,car 89,47,84,133,55,11,157,44,20,160,169,354,176,74,5,9,182,192,van -107,53,103,221,66,11,209,32,24,163,222,653,212,66,0,1,191,201,opel +107,53,103,221,66,11,209,32,24,163,222,653,212,66,0,1,191,201,car 85,39,68,119,52,5,128,53,18,135,148,241,142,75,8,8,182,187,van -103,50,98,212,63,9,193,34,22,161,214,567,185,64,5,5,198,204,opel -77,38,63,135,59,5,130,52,18,130,145,247,139,79,13,21,183,187,opel +103,50,98,212,63,9,193,34,22,161,214,567,185,64,5,5,198,204,car +77,38,63,135,59,5,130,52,18,130,145,247,139,79,13,21,183,187,car 96,40,70,120,50,8,137,50,18,141,162,269,139,80,10,13,183,183,van 83,42,66,156,67,7,150,45,19,144,174,333,159,78,4,2,182,188,bus 93,45,86,201,69,7,184,35,22,145,203,523,183,72,0,4,194,197,bus -89,41,75,143,56,7,146,46,19,137,170,317,156,76,18,5,184,188,opel +89,41,75,143,56,7,146,46,19,137,170,317,156,76,18,5,184,188,car 81,43,68,125,57,8,149,46,19,146,169,323,172,83,6,18,179,184,bus -98,55,101,219,69,11,225,30,25,178,231,748,216,74,6,14,187,195,opel +98,55,101,219,69,11,225,30,25,178,231,748,216,74,6,14,187,195,car 86,44,78,164,68,9,142,46,18,147,168,305,171,70,1,11,190,201,van 98,49,84,219,74,7,190,34,22,154,208,558,209,74,4,7,195,195,bus -96,55,98,161,54,10,215,31,24,175,226,683,221,76,3,6,185,193,opel -97,59,108,227,70,11,224,30,25,186,225,732,218,70,10,25,186,198,opel -92,39,91,191,62,8,176,37,21,137,196,466,151,67,3,23,192,200,opel -73,37,53,111,54,6,126,55,18,128,135,227,147,82,1,15,176,184,opel +96,55,98,161,54,10,215,31,24,175,226,683,221,76,3,6,185,193,car +97,59,108,227,70,11,224,30,25,186,225,732,218,70,10,25,186,198,car +92,39,91,191,62,8,176,37,21,137,196,466,151,67,3,23,192,200,car +73,37,53,111,54,6,126,55,18,128,135,227,147,82,1,15,176,184,car 89,42,89,147,61,11,151,44,19,145,170,338,163,72,11,23,187,199,van -101,53,103,203,63,9,195,34,22,162,210,571,210,68,5,5,191,198,opel -91,39,83,170,60,8,172,38,21,134,197,445,152,72,0,10,188,194,saab -86,40,62,140,62,7,150,45,19,133,165,330,173,82,2,3,180,185,saab +101,53,103,203,63,9,195,34,22,162,210,571,210,68,5,5,191,198,car +91,39,83,170,60,8,172,38,21,134,197,445,152,72,0,10,188,194,car +86,40,62,140,62,7,150,45,19,133,165,330,173,82,2,3,180,185,car 104,52,94,208,66,5,208,31,24,161,227,666,218,76,11,4,193,191,bus 89,44,68,113,50,7,150,45,19,147,171,328,189,88,6,5,179,182,bus 87,46,71,159,66,6,151,44,19,146,175,343,189,73,2,0,186,190,bus 99,51,92,203,65,5,209,31,24,159,232,671,214,78,5,11,191,189,bus 94,36,68,127,54,7,127,52,18,132,155,242,116,66,1,2,195,196,van -79,40,80,133,55,7,147,47,19,135,172,311,144,76,8,30,181,193,opel +79,40,80,133,55,7,147,47,19,135,172,311,144,76,8,30,181,193,car 89,40,76,188,76,7,150,44,19,136,174,342,148,72,3,8,193,197,bus 110,58,106,180,51,6,261,26,28,171,278,998,257,83,9,13,181,182,bus 89,41,84,141,58,9,149,45,19,145,172,330,162,72,4,18,188,200,van 86,37,60,115,54,5,119,56,17,132,141,209,129,72,2,8,186,190,van 91,42,84,209,75,6,171,38,20,138,189,446,161,69,3,12,196,201,bus -80,37,57,116,55,6,125,54,18,125,142,229,132,81,8,5,178,184,opel -104,55,107,222,68,11,218,31,24,173,232,703,229,71,3,10,188,199,saab -94,38,84,158,55,9,169,39,20,130,196,430,155,69,9,15,190,195,opel -104,52,100,191,59,9,197,33,23,158,218,583,234,70,10,10,191,198,saab +80,37,57,116,55,6,125,54,18,125,142,229,132,81,8,5,178,184,car +104,55,107,222,68,11,218,31,24,173,232,703,229,71,3,10,188,199,car +94,38,84,158,55,9,169,39,20,130,196,430,155,69,9,15,190,195,car +104,52,100,191,59,9,197,33,23,158,218,583,234,70,10,10,191,198,car 94,48,87,162,64,10,157,43,20,161,179,363,186,75,4,15,184,195,van 84,45,66,154,65,6,145,46,19,144,168,312,177,73,2,3,184,188,bus -97,50,108,211,65,10,214,31,24,156,232,683,218,72,7,29,188,197,opel -89,42,80,151,62,6,144,46,19,139,166,308,170,74,17,13,185,189,saab +97,50,108,211,65,10,214,31,24,156,232,683,218,72,7,29,188,197,car +89,42,80,151,62,6,144,46,19,139,166,308,170,74,17,13,185,189,car 86,43,68,152,62,7,150,44,19,142,179,337,164,75,4,9,188,192,bus -95,46,105,219,68,9,201,33,23,148,223,602,201,69,5,38,191,202,opel +95,46,105,219,68,9,201,33,23,148,223,602,201,69,5,38,191,202,car 87,44,65,124,56,6,149,46,19,144,170,321,171,87,4,12,179,182,bus 82,45,66,252,126,52,148,45,19,144,237,326,185,119,1,1,181,185,bus 95,42,85,174,66,9,153,44,19,144,168,347,150,65,11,5,196,204,van 94,42,68,150,64,7,128,52,18,143,154,246,159,69,14,5,192,196,van 92,38,60,130,62,5,114,58,17,132,135,194,137,72,14,5,190,194,van 102,45,83,198,65,5,194,33,22,146,225,576,167,79,0,27,193,191,bus -108,53,103,202,64,10,220,30,25,168,224,711,214,73,11,10,188,199,saab -99,46,105,209,64,11,197,34,23,152,212,575,159,65,0,33,194,205,opel -85,39,77,151,59,8,150,45,19,134,176,331,133,73,0,16,184,193,opel +108,53,103,202,64,10,220,30,25,168,224,711,214,73,11,10,188,199,car +99,46,105,209,64,11,197,34,23,152,212,575,159,65,0,33,194,205,car +85,39,77,151,59,8,150,45,19,134,176,331,133,73,0,16,184,193,car 80,44,68,135,59,8,150,45,19,145,170,329,173,80,7,12,180,185,bus 99,48,79,199,68,6,185,35,22,153,202,524,171,74,5,8,195,195,bus 89,40,77,159,65,9,144,46,19,141,168,314,143,70,0,5,190,200,van 94,48,83,162,64,10,156,43,19,153,177,357,187,74,4,14,185,196,van -77,38,75,144,59,6,147,46,19,132,167,315,136,80,16,20,181,187,opel -88,35,50,121,58,5,114,59,17,122,132,192,138,74,21,4,182,187,opel +77,38,75,144,59,6,147,46,19,132,167,315,136,80,16,20,181,187,car +88,35,50,121,58,5,114,59,17,122,132,192,138,74,21,4,182,187,car 93,43,85,133,54,10,155,44,19,153,174,351,165,75,12,13,184,196,van 95,47,88,162,64,11,159,43,20,157,176,371,185,71,12,13,189,198,van -100,45,100,209,65,8,201,32,23,147,231,611,189,72,5,5,189,195,opel -109,53,109,221,69,12,221,31,25,169,226,712,212,72,13,28,188,201,saab +100,45,100,209,65,8,201,32,23,147,231,611,189,72,5,5,189,195,car +109,53,109,221,69,12,221,31,25,169,226,712,212,72,13,28,188,201,car 85,43,64,128,56,8,150,46,19,144,168,324,173,82,9,14,180,184,bus 93,49,79,180,65,7,173,37,21,158,189,463,194,70,5,10,197,202,bus -89,37,54,119,53,5,134,50,18,127,151,266,146,79,16,14,184,185,saab +89,37,54,119,53,5,134,50,18,127,151,266,146,79,16,14,184,185,car 90,48,78,142,59,11,160,43,20,160,173,370,185,76,10,11,183,192,van 92,40,82,163,63,9,146,45,19,140,165,319,137,64,9,0,199,206,van -90,36,57,130,57,6,121,56,17,127,137,216,132,68,22,23,190,195,saab +90,36,57,130,57,6,121,56,17,127,137,216,132,68,22,23,190,195,car 85,45,71,150,63,8,143,46,19,147,171,307,179,72,2,3,187,196,van 90,46,80,143,62,11,159,43,20,156,169,366,186,74,17,7,185,193,van 89,42,70,148,62,7,147,45,19,143,176,323,153,76,2,6,186,189,bus 85,41,66,155,65,22,149,45,19,139,173,330,155,75,6,16,184,191,bus 97,45,88,173,67,10,157,43,20,157,173,365,157,67,8,12,192,200,van 100,48,95,209,68,7,199,32,23,150,216,605,200,73,7,11,192,194,bus -100,46,104,184,60,9,197,34,23,147,222,578,198,73,13,13,189,197,saab -86,36,77,165,60,7,150,45,19,128,174,331,131,66,0,32,196,203,saab -97,42,101,186,59,9,186,36,22,138,208,511,168,67,7,41,194,206,saab +100,46,104,184,60,9,197,34,23,147,222,578,198,73,13,13,189,197,car +86,36,77,165,60,7,150,45,19,128,174,331,131,66,0,32,196,203,car +97,42,101,186,59,9,186,36,22,138,208,511,168,67,7,41,194,206,car 98,39,68,121,49,7,134,51,18,142,164,261,134,75,4,1,186,186,van -102,54,100,163,53,10,213,31,24,173,219,669,201,76,12,27,187,195,opel +102,54,100,163,53,10,213,31,24,173,219,669,201,76,12,27,187,195,car 89,47,83,322,133,48,158,43,20,163,229,364,176,97,0,14,184,194,van 86,48,75,136,58,10,161,43,20,163,170,371,185,75,3,1,183,192,van 87,42,64,150,64,10,133,50,18,142,157,264,159,67,7,1,193,201,van -88,37,63,130,58,5,125,54,18,130,141,230,145,74,14,20,184,188,saab +88,37,63,130,58,5,125,54,18,130,141,230,145,74,14,20,184,188,car 91,42,80,162,66,8,148,44,19,145,171,331,147,70,3,5,189,199,van -90,37,80,171,58,9,157,42,20,132,172,373,115,60,3,18,201,209,saab +90,37,80,171,58,9,157,42,20,132,172,373,115,60,3,18,201,209,car 81,42,63,125,55,8,149,46,19,145,166,320,172,86,7,7,179,182,bus -106,49,107,194,57,11,214,31,24,161,224,670,172,67,0,39,192,206,opel +106,49,107,194,57,11,214,31,24,161,224,670,172,67,0,39,192,206,car 80,43,68,120,54,8,150,45,19,145,171,329,176,85,4,8,179,183,bus -95,45,80,186,62,7,164,40,20,145,188,406,178,65,11,18,199,204,opel -103,54,107,218,64,12,222,30,25,174,221,728,199,67,0,18,189,200,opel +95,45,80,186,62,7,164,40,20,145,188,406,178,65,11,18,199,204,car +103,54,107,218,64,12,222,30,25,174,221,728,199,67,0,18,189,200,car 100,46,85,164,64,11,163,42,20,163,176,387,170,71,18,0,189,196,van 91,40,76,171,67,7,149,44,19,135,169,332,144,68,4,17,192,200,bus -90,43,72,172,59,8,154,42,19,144,174,360,158,61,15,9,203,209,saab +90,43,72,172,59,8,154,42,19,144,174,360,158,61,15,9,203,209,car 93,36,64,165,69,8,136,49,18,136,161,279,127,67,2,29,193,204,van -104,50,96,211,65,10,187,35,22,156,207,527,195,65,3,7,195,206,saab +104,50,96,211,65,10,187,35,22,156,207,527,195,65,3,7,195,206,car 94,44,84,216,74,6,184,35,22,145,208,525,154,73,4,22,196,197,bus -93,35,72,172,62,7,149,44,19,124,169,334,125,62,5,30,203,210,opel -106,49,106,211,64,9,208,32,24,158,224,645,184,68,1,24,190,202,saab +93,35,72,172,62,7,149,44,19,124,169,334,125,62,5,30,203,210,car +106,49,106,211,64,9,208,32,24,158,224,645,184,68,1,24,190,202,car 89,40,79,154,64,9,144,46,19,139,168,311,149,71,8,7,188,197,van 110,56,103,223,64,5,250,26,27,169,280,928,239,85,4,6,184,183,bus -85,36,78,149,55,7,147,45,19,128,168,321,134,64,10,24,197,203,opel +85,36,78,149,55,7,147,45,19,128,168,321,134,64,10,24,197,203,car 93,42,70,131,56,7,127,53,18,145,156,240,152,74,5,4,189,190,van -87,39,74,152,58,6,151,44,19,136,174,337,140,70,1,33,187,196,saab -91,45,75,154,57,6,150,44,19,146,170,335,180,66,16,2,193,198,opel -82,38,53,125,59,5,133,51,18,128,152,259,146,87,0,0,177,183,opel -107,52,101,218,64,11,202,33,23,164,219,610,192,65,17,2,197,206,opel -98,39,81,191,64,9,166,40,20,138,184,415,131,62,8,19,197,205,saab -85,40,72,139,59,5,132,50,18,135,159,260,150,68,3,9,191,195,saab -98,54,104,186,59,10,213,32,24,172,223,665,217,73,1,26,186,195,opel -103,54,91,179,57,11,220,31,25,170,220,707,198,72,1,32,186,198,opel -92,36,78,165,57,8,153,43,19,128,169,349,124,60,4,19,203,211,saab -110,51,104,191,57,12,213,31,24,162,226,674,190,68,18,2,191,199,saab +87,39,74,152,58,6,151,44,19,136,174,337,140,70,1,33,187,196,car +91,45,75,154,57,6,150,44,19,146,170,335,180,66,16,2,193,198,car +82,38,53,125,59,5,133,51,18,128,152,259,146,87,0,0,177,183,car +107,52,101,218,64,11,202,33,23,164,219,610,192,65,17,2,197,206,car +98,39,81,191,64,9,166,40,20,138,184,415,131,62,8,19,197,205,car +85,40,72,139,59,5,132,50,18,135,159,260,150,68,3,9,191,195,car +98,54,104,186,59,10,213,32,24,172,223,665,217,73,1,26,186,195,car +103,54,91,179,57,11,220,31,25,170,220,707,198,72,1,32,186,198,car +92,36,78,165,57,8,153,43,19,128,169,349,124,60,4,19,203,211,car +110,51,104,191,57,12,213,31,24,162,226,674,190,68,18,2,191,199,car 82,45,68,139,64,6,147,46,19,143,169,320,184,80,0,1,181,184,bus 98,38,70,125,52,8,130,53,18,139,157,243,132,74,0,13,186,185,van -108,51,103,197,60,11,211,31,24,160,222,661,187,67,7,3,190,200,opel +108,51,103,197,60,11,211,31,24,160,222,661,187,67,7,3,190,200,car 106,54,103,161,47,4,247,27,27,166,266,892,242,85,4,11,181,183,bus 94,45,81,166,67,9,145,46,19,147,164,313,179,66,11,14,194,202,van 96,49,98,187,59,6,213,31,24,152,228,680,210,77,8,28,188,189,bus 93,48,84,150,63,11,156,44,20,165,171,354,188,73,8,15,185,195,van 88,40,78,186,73,6,158,41,20,134,185,379,148,73,1,11,193,197,bus -84,39,90,180,60,7,177,37,21,131,209,469,145,71,4,38,190,198,opel +84,39,90,180,60,7,177,37,21,131,209,469,145,71,4,38,190,198,car 89,44,72,160,66,7,144,46,19,147,166,312,169,69,11,1,191,198,bus 93,37,73,174,68,7,151,43,19,131,175,347,135,68,1,22,196,205,bus 89,44,70,137,58,6,136,49,18,146,168,273,166,78,10,3,186,187,van -102,54,106,221,68,11,207,32,24,164,228,638,238,71,0,26,189,200,saab -78,36,60,116,56,6,123,55,17,124,141,221,121,78,3,16,178,185,opel +102,54,106,221,68,11,207,32,24,164,228,638,238,71,0,26,189,200,car +78,36,60,116,56,6,123,55,17,124,141,221,121,78,3,16,178,185,car 91,42,66,169,66,7,145,44,19,140,169,325,159,67,4,0,201,207,bus -84,35,53,122,57,4,116,59,17,123,135,196,128,76,10,27,183,190,saab -103,46,106,209,66,10,203,33,23,149,217,612,210,70,9,10,191,199,saab +84,35,53,122,57,4,116,59,17,123,135,196,128,76,10,27,183,190,car +103,46,106,209,66,10,203,33,23,149,217,612,210,70,9,10,191,199,car 100,41,75,205,71,5,176,36,21,138,204,479,151,72,7,19,197,197,bus 91,42,81,193,69,5,169,38,20,137,184,434,156,68,3,23,198,204,bus -98,45,76,166,60,7,157,42,20,148,184,371,186,69,13,10,190,196,opel -101,51,105,212,68,10,209,32,24,162,222,653,224,73,5,23,186,195,opel -90,36,78,179,64,8,157,42,19,126,182,367,142,66,1,20,192,198,opel -97,48,94,198,63,9,181,36,21,155,200,494,189,64,20,11,199,203,opel +98,45,76,166,60,7,157,42,20,148,184,371,186,69,13,10,190,196,car +101,51,105,212,68,10,209,32,24,162,222,653,224,73,5,23,186,195,car +90,36,78,179,64,8,157,42,19,126,182,367,142,66,1,20,192,198,car +97,48,94,198,63,9,181,36,21,155,200,494,189,64,20,11,199,203,car 87,40,81,162,68,10,146,46,19,139,167,317,157,70,0,13,189,199,van -93,43,76,149,57,7,149,44,19,143,172,335,176,69,14,0,189,194,saab +93,43,76,149,57,7,149,44,19,143,172,335,176,69,14,0,189,194,car 107,55,98,199,59,7,240,27,26,168,258,866,245,80,3,1,186,184,bus -92,37,86,167,60,7,158,42,20,131,181,373,144,68,9,21,190,196,saab +92,37,86,167,60,7,158,42,20,131,181,373,144,68,9,21,190,196,car 86,43,66,130,56,7,152,44,19,142,177,340,173,81,6,14,181,185,bus -107,56,104,231,71,11,219,31,25,172,226,705,217,71,19,11,189,196,saab +107,56,104,231,71,11,219,31,25,172,226,705,217,71,19,11,189,196,car 82,44,72,150,64,7,154,44,19,144,181,350,177,80,0,16,183,187,bus 81,46,71,130,56,7,153,44,19,149,172,342,191,81,3,14,180,186,bus 82,44,72,136,61,7,147,46,19,143,173,317,183,81,6,17,181,185,bus 93,47,85,163,66,11,156,44,20,158,172,355,178,74,7,15,183,195,van -90,36,74,171,60,8,157,42,19,128,177,367,123,61,6,21,197,204,saab -111,54,103,171,50,11,221,30,25,172,227,727,201,69,15,6,190,198,opel -103,55,100,194,62,11,212,31,24,175,217,666,219,73,10,14,187,194,opel +90,36,74,171,60,8,157,42,19,128,177,367,123,61,6,21,197,204,car +111,54,103,171,50,11,221,30,25,172,227,727,201,69,15,6,190,198,car +103,55,100,194,62,11,212,31,24,175,217,666,219,73,10,14,187,194,car 89,40,58,137,58,7,122,54,17,140,146,225,150,63,7,4,199,206,van 87,47,81,149,62,9,147,45,19,152,171,325,181,72,0,6,188,198,van -92,46,79,176,64,8,162,41,20,149,183,396,178,67,2,10,191,198,opel +92,46,79,176,64,8,162,41,20,149,183,396,178,67,2,10,191,198,car 85,42,64,121,55,7,149,46,19,146,167,323,172,85,1,6,179,182,bus 86,46,70,149,65,8,149,45,19,146,170,331,185,77,6,6,183,188,bus -101,56,100,168,55,11,214,31,24,175,219,681,224,74,2,3,185,192,opel -94,39,89,194,62,9,172,38,21,135,191,444,121,63,4,23,201,209,opel +101,56,100,168,55,11,214,31,24,175,219,681,224,74,2,3,185,192,car +94,39,89,194,62,9,172,38,21,135,191,444,121,63,4,23,201,209,car 86,37,69,150,63,8,138,48,18,134,163,284,124,71,1,6,189,195,van 90,41,71,169,68,7,150,44,19,138,175,336,157,71,3,18,192,197,bus 104,49,89,168,54,4,212,31,24,153,238,682,198,78,1,23,190,189,bus -89,36,72,141,56,7,138,48,18,126,163,286,130,72,1,1,187,192,opel -90,39,86,169,62,7,162,41,20,131,194,388,147,74,1,22,185,191,opel -84,44,77,150,59,5,152,44,19,143,175,344,177,77,8,2,183,187,saab -104,57,103,216,69,11,219,30,25,176,228,708,219,73,4,3,186,196,opel +89,36,72,141,56,7,138,48,18,126,163,286,130,72,1,1,187,192,car +90,39,86,169,62,7,162,41,20,131,194,388,147,74,1,22,185,191,car +84,44,77,150,59,5,152,44,19,143,175,344,177,77,8,2,183,187,car +104,57,103,216,69,11,219,30,25,176,228,708,219,73,4,3,186,196,car 83,44,68,144,61,8,147,45,19,143,170,325,180,74,1,1,185,191,bus 85,39,57,126,56,6,114,58,17,135,134,195,145,64,17,7,197,202,van -99,55,101,206,62,13,222,30,25,180,225,722,213,71,2,3,186,196,opel +99,55,101,206,62,13,222,30,25,180,225,722,213,71,2,3,186,196,car 88,44,85,139,56,11,157,43,20,155,176,363,175,76,5,16,184,195,van 100,50,81,197,67,6,186,34,22,158,206,531,198,74,6,1,197,198,bus 81,44,72,139,60,6,153,44,19,146,180,347,178,81,1,15,182,186,bus -86,41,66,133,56,6,136,49,18,136,155,274,162,74,5,14,183,189,saab +86,41,66,133,56,6,136,49,18,136,155,274,162,74,5,14,183,189,car 93,41,79,159,63,8,144,46,19,150,165,309,134,67,4,9,195,203,van -107,54,98,210,66,11,218,31,24,169,221,704,216,71,14,0,188,197,saab +107,54,98,210,66,11,218,31,24,169,221,704,216,71,14,0,188,197,car 94,35,66,147,62,9,131,50,18,127,159,258,115,66,8,7,196,201,van -105,54,106,215,68,10,208,32,24,166,217,640,218,69,14,23,189,199,saab -86,41,64,148,61,5,150,45,19,138,165,333,173,80,5,8,182,185,saab +105,54,106,215,68,10,208,32,24,166,217,640,218,69,14,23,189,199,car +86,41,64,148,61,5,150,45,19,138,165,333,173,80,5,8,182,185,car 85,35,47,110,55,3,117,57,17,122,136,203,139,89,5,9,180,184,van -85,33,40,115,57,3,112,61,17,119,130,184,127,86,12,21,181,183,saab +85,33,40,115,57,3,112,61,17,119,130,184,127,86,12,21,181,183,car 81,44,68,120,53,6,151,45,19,147,170,333,178,86,4,5,179,183,bus -100,52,104,189,59,10,208,32,24,163,220,642,197,70,1,22,187,198,saab +100,52,104,189,59,10,208,32,24,163,220,642,197,70,1,22,187,198,car 93,42,64,158,68,9,134,49,18,142,163,268,170,71,7,13,192,201,van 90,48,78,134,56,11,160,43,20,167,169,366,185,76,1,14,182,192,van 96,37,74,199,74,5,165,39,20,128,188,419,136,72,1,3,196,200,bus 85,45,65,128,56,8,151,45,19,145,170,332,186,81,1,10,179,184,bus -100,55,101,189,57,10,222,30,25,177,225,731,211,71,7,17,188,197,opel +100,55,101,189,57,10,222,30,25,177,225,731,211,71,7,17,188,197,car 79,47,74,141,61,7,153,43,19,149,175,349,199,77,6,10,183,189,bus -89,36,77,172,62,8,157,42,19,125,174,367,126,63,5,22,198,205,opel -93,45,73,164,59,7,159,42,20,146,182,379,188,65,11,15,195,201,opel +89,36,77,172,62,8,157,42,19,125,174,367,126,63,5,22,198,205,car +93,45,73,164,59,7,159,42,20,146,182,379,188,65,11,15,195,201,car 85,42,59,132,58,7,149,46,19,144,166,320,172,83,8,4,179,182,bus -101,55,108,228,69,12,215,31,24,168,229,684,214,71,2,16,188,199,saab +101,55,108,228,69,12,215,31,24,168,229,684,214,71,2,16,188,199,car 85,47,75,121,53,9,157,44,20,165,168,358,176,77,1,7,182,191,van 93,41,75,124,51,7,140,49,18,141,164,284,149,77,5,15,184,185,van 95,36,73,191,73,6,156,41,19,126,184,374,124,71,2,19,199,204,bus -91,39,83,176,59,7,169,39,20,132,190,426,142,67,0,24,192,199,saab -103,55,103,211,65,11,212,31,24,165,229,673,249,72,5,16,188,196,opel -85,34,53,127,58,6,116,58,17,121,137,197,127,70,3,20,185,189,saab +91,39,83,176,59,7,169,39,20,132,190,426,142,67,0,24,192,199,car +103,55,103,211,65,11,212,31,24,165,229,673,249,72,5,16,188,196,car +85,34,53,127,58,6,116,58,17,121,137,197,127,70,3,20,185,189,car 95,38,66,126,52,8,133,52,18,140,158,253,140,78,11,8,184,183,van -104,58,103,230,69,11,219,30,25,176,231,716,246,71,7,4,187,196,opel +104,58,103,230,69,11,219,30,25,176,231,716,246,71,7,4,187,196,car 84,44,80,140,58,11,156,44,20,157,166,349,176,74,5,17,183,193,van 94,43,68,170,67,6,142,46,18,142,164,310,177,65,10,8,198,203,bus 93,47,85,161,65,12,155,43,19,157,179,354,178,76,2,9,184,196,van -112,50,110,186,56,11,214,31,24,159,232,676,203,71,18,27,191,202,saab -91,36,77,157,56,7,155,42,19,126,177,361,123,65,8,15,195,201,saab -92,43,69,158,56,7,149,44,19,143,170,333,168,63,14,18,198,203,opel -99,48,104,196,63,10,201,33,23,152,221,604,199,73,8,4,188,197,saab -98,58,101,208,65,12,226,30,25,182,225,748,216,71,6,1,185,196,opel -83,37,54,118,55,4,129,52,18,127,146,245,140,81,4,13,180,184,saab -91,39,88,189,63,9,175,38,21,132,197,457,156,69,0,23,191,198,saab +112,50,110,186,56,11,214,31,24,159,232,676,203,71,18,27,191,202,car +91,36,77,157,56,7,155,42,19,126,177,361,123,65,8,15,195,201,car +92,43,69,158,56,7,149,44,19,143,170,333,168,63,14,18,198,203,car +99,48,104,196,63,10,201,33,23,152,221,604,199,73,8,4,188,197,car +98,58,101,208,65,12,226,30,25,182,225,748,216,71,6,1,185,196,car +83,37,54,118,55,4,129,52,18,127,146,245,140,81,4,13,180,184,car +91,39,88,189,63,9,175,38,21,132,197,457,156,69,0,23,191,198,car 89,40,60,131,56,6,118,56,17,137,143,209,153,65,10,8,193,199,van 89,35,70,138,58,7,126,53,17,128,147,237,112,64,4,19,199,207,van -103,49,100,194,60,10,185,35,22,160,202,518,178,62,13,8,198,208,saab +103,49,100,194,60,10,185,35,22,160,202,518,178,62,13,8,198,208,car 80,45,71,128,56,7,151,45,19,147,171,337,176,79,3,16,181,187,bus 86,42,65,116,53,6,152,45,19,141,175,335,172,85,5,4,179,183,bus -100,46,81,187,61,9,166,40,20,154,189,415,175,63,13,9,198,207,saab +100,46,81,187,61,9,166,40,20,154,189,415,175,63,13,9,198,207,car 86,39,60,140,60,7,119,55,17,134,140,212,141,61,7,8,200,207,van 83,37,62,113,53,6,122,55,17,129,143,218,135,79,0,7,181,185,van 82,45,68,150,69,5,148,45,19,144,169,322,184,80,5,0,181,184,bus -93,47,88,200,66,7,173,38,21,151,197,452,205,66,0,3,195,202,saab +93,47,88,200,66,7,173,38,21,151,197,452,205,66,0,3,195,202,car 91,43,88,157,61,9,149,45,19,157,165,326,140,64,1,26,197,207,van 96,45,80,162,63,9,146,46,19,148,161,316,161,64,5,10,199,207,van 107,57,106,179,51,8,257,26,28,172,275,954,232,83,2,20,181,184,bus 87,44,70,179,75,6,146,45,19,141,167,326,178,69,6,1,194,201,bus 83,46,73,137,59,6,148,45,19,146,167,327,183,75,8,0,185,191,bus -86,41,66,129,55,7,135,50,18,136,154,266,165,74,3,4,180,187,opel -109,54,109,225,68,11,214,31,24,169,226,675,212,68,11,32,189,202,saab +86,41,66,129,55,7,135,50,18,136,154,266,165,74,3,4,180,187,car +109,54,109,225,68,11,214,31,24,169,226,675,212,68,11,32,189,202,car 94,37,73,186,71,7,154,42,19,127,171,362,132,67,2,8,197,206,bus -100,44,93,193,62,8,186,35,22,147,202,521,151,66,0,2,193,198,opel +100,44,93,193,62,8,186,35,22,147,202,521,151,66,0,2,193,198,car 82,43,73,154,65,7,151,44,19,143,178,341,160,76,5,11,185,189,bus 86,46,73,125,57,6,151,45,19,147,170,334,188,82,9,11,180,184,bus -116,53,110,231,67,12,217,31,24,165,231,692,222,67,16,28,192,206,saab +116,53,110,231,67,12,217,31,24,165,231,692,222,67,16,28,192,206,car 89,46,77,125,52,10,156,44,20,160,171,351,177,78,7,17,183,191,van -89,48,85,189,64,8,169,39,20,153,188,427,190,64,16,5,195,201,saab +89,48,85,189,64,8,169,39,20,153,188,427,190,64,16,5,195,201,car 83,41,70,155,65,7,144,46,19,141,168,309,147,71,4,12,188,195,bus 88,43,84,136,55,11,154,44,19,150,174,350,164,73,6,2,185,196,van -96,47,103,215,69,10,200,33,23,147,220,598,200,73,6,6,187,194,opel -88,37,57,132,62,6,135,50,18,125,151,265,144,83,16,16,180,184,saab +96,47,103,215,69,10,200,33,23,147,220,598,200,73,6,6,187,194,car +88,37,57,132,62,6,135,50,18,125,151,265,144,83,16,16,180,184,car 98,38,66,130,55,7,130,51,18,138,160,251,123,69,3,12,191,194,van 89,45,81,246,102,43,155,44,20,160,200,347,177,90,9,17,183,192,van 87,42,76,159,65,5,155,42,19,138,184,362,157,76,6,12,189,193,bus @@ -296,385 +296,385 @@ COMPACTNESS,CIRCULARITY,DISTANCE_CIRCULARITY,RADIUS_RATIO,PR_AXIS_ASPECT_RATIO,M 109,55,102,169,51,6,241,27,26,165,265,870,247,84,10,11,184,183,bus 90,38,75,164,64,7,151,43,19,131,168,345,139,66,0,0,195,204,bus 98,52,86,207,69,5,192,33,22,161,212,570,221,75,4,6,194,195,bus -82,37,66,126,54,7,132,52,18,127,148,252,142,72,17,7,183,187,saab -91,40,98,192,64,9,177,38,21,135,194,465,165,66,9,35,195,205,saab +82,37,66,126,54,7,132,52,18,127,148,252,142,72,17,7,183,187,car +91,40,98,192,64,9,177,38,21,135,194,465,165,66,9,35,195,205,car 98,40,77,171,61,6,172,37,21,139,197,457,141,72,4,17,199,201,bus -106,53,98,193,60,10,215,31,24,169,224,681,218,73,8,21,188,197,saab -93,43,78,166,59,7,151,44,19,141,182,342,174,68,15,2,193,197,opel +106,53,98,193,60,10,215,31,24,169,224,681,218,73,8,21,188,197,car +93,43,78,166,59,7,151,44,19,141,182,342,174,68,15,2,193,197,car 94,37,72,193,72,6,158,41,19,133,184,385,127,70,0,14,200,204,bus 89,36,68,149,60,8,133,50,18,134,153,265,119,62,6,18,201,209,van 85,45,70,130,58,8,151,45,19,146,171,334,187,79,2,5,181,186,bus 86,45,73,152,63,6,149,44,19,145,170,335,176,71,6,1,189,196,bus -106,48,107,202,61,10,207,32,24,153,227,635,200,70,5,28,190,203,saab -107,52,103,186,57,11,214,31,24,162,217,676,189,66,6,5,189,198,opel -109,51,100,197,59,10,192,34,22,161,210,553,195,64,14,3,196,202,opel -109,48,107,215,62,10,205,32,23,158,222,624,168,65,9,32,195,206,opel -90,50,90,188,61,10,181,36,21,158,211,492,220,69,6,19,191,199,saab +106,48,107,202,61,10,207,32,24,153,227,635,200,70,5,28,190,203,car +107,52,103,186,57,11,214,31,24,162,217,676,189,66,6,5,189,198,car +109,51,100,197,59,10,192,34,22,161,210,553,195,64,14,3,196,202,car +109,48,107,215,62,10,205,32,23,158,222,624,168,65,9,32,195,206,car +90,50,90,188,61,10,181,36,21,158,211,492,220,69,6,19,191,199,car 93,45,83,142,56,10,157,43,20,155,180,364,188,75,1,21,184,197,van 82,41,70,155,64,7,148,45,19,138,172,328,152,72,5,17,187,195,bus -96,52,104,222,67,9,198,33,23,163,217,589,226,67,12,20,192,201,opel +96,52,104,222,67,9,198,33,23,163,217,589,226,67,12,20,192,201,car 90,42,63,126,55,7,152,45,19,142,173,336,173,81,0,15,180,184,bus 93,40,62,117,49,7,131,52,18,145,160,249,156,78,8,6,184,184,van 91,41,66,131,56,9,126,53,18,144,159,237,155,72,3,10,191,194,van -95,45,105,208,64,10,187,36,22,150,202,520,158,64,7,32,198,211,saab +95,45,105,208,64,10,187,36,22,150,202,520,158,64,7,32,198,211,car 89,37,51,111,54,5,120,56,17,127,138,213,147,82,7,4,181,183,van 102,51,92,194,60,6,220,30,25,162,247,731,209,80,7,7,188,186,bus -105,54,100,220,69,10,221,30,25,170,232,718,202,73,0,13,187,199,saab +105,54,100,220,69,10,221,30,25,170,232,718,202,73,0,13,187,199,car 113,57,109,194,56,6,260,26,28,175,288,982,261,85,11,21,182,183,bus 87,43,65,127,56,8,149,46,19,143,169,322,171,85,6,3,180,182,bus -98,51,96,203,66,10,188,35,22,157,207,533,231,68,10,1,191,199,saab -94,38,88,179,60,7,170,39,21,131,188,435,144,66,2,28,195,204,saab +98,51,96,203,66,10,188,35,22,157,207,533,231,68,10,1,191,199,car +94,38,88,179,60,7,170,39,21,131,188,435,144,66,2,28,195,204,car 82,44,63,123,54,7,151,45,19,147,166,329,185,81,3,4,179,182,bus -106,49,96,201,61,10,181,36,21,158,197,494,180,62,19,15,202,209,opel -89,44,82,136,54,6,149,45,19,144,170,332,168,68,10,14,188,193,opel +106,49,96,201,61,10,181,36,21,158,197,494,180,62,19,15,202,209,car +89,44,82,136,54,6,149,45,19,144,170,332,168,68,10,14,188,193,car 93,43,88,170,66,9,150,45,19,147,164,334,143,65,2,17,196,206,van -89,38,80,169,59,7,161,41,20,131,186,389,137,68,5,15,192,197,saab +89,38,80,169,59,7,161,41,20,131,186,389,137,68,5,15,192,197,car 98,44,78,160,63,8,142,47,18,148,160,300,171,63,19,2,201,207,van -104,52,96,188,59,9,188,35,22,161,206,530,205,67,11,8,193,200,opel -99,57,109,220,66,11,221,30,25,176,234,725,236,70,10,25,188,200,opel +104,52,96,188,59,9,188,35,22,161,206,530,205,67,11,8,193,200,car +99,57,109,220,66,11,221,30,25,176,234,725,236,70,10,25,188,200,car 86,42,65,125,54,7,150,45,19,140,171,327,172,85,2,8,180,182,bus 107,57,102,184,55,7,234,28,26,171,243,822,229,77,7,11,187,187,bus -109,54,103,205,63,11,222,30,25,175,229,720,213,71,6,14,187,200,saab +109,54,103,205,63,11,222,30,25,175,229,720,213,71,6,14,187,200,car 89,44,76,125,54,10,156,44,20,151,163,352,176,76,12,12,184,193,van 99,51,88,188,62,5,203,32,23,158,222,625,219,77,8,26,191,190,bus 97,45,91,161,63,10,151,45,19,148,166,334,171,65,18,20,197,205,van 87,41,73,158,64,7,151,44,19,138,175,341,152,73,3,8,190,194,bus 89,40,72,155,63,7,146,45,19,135,175,321,145,72,4,10,192,196,bus -86,40,75,146,62,6,140,48,18,135,158,290,162,72,3,21,183,190,opel -83,37,54,131,61,4,135,50,18,127,152,271,141,85,3,6,180,183,saab -102,54,101,190,58,10,222,30,25,171,224,728,203,71,13,6,189,198,opel -99,55,101,219,68,10,224,30,25,178,228,737,213,74,11,20,187,196,opel +86,40,75,146,62,6,140,48,18,135,158,290,162,72,3,21,183,190,car +83,37,54,131,61,4,135,50,18,127,152,271,141,85,3,6,180,183,car +102,54,101,190,58,10,222,30,25,171,224,728,203,71,13,6,189,198,car +99,55,101,219,68,10,224,30,25,178,228,737,213,74,11,20,187,196,car 101,54,106,188,57,7,236,28,26,164,256,833,253,81,6,14,185,185,bus -117,52,110,228,65,12,212,31,24,163,228,668,220,66,21,25,194,205,saab -88,44,77,167,59,6,151,44,19,145,175,343,177,64,9,12,202,208,opel +117,52,110,228,65,12,212,31,24,163,228,668,220,66,21,25,194,205,car +88,44,77,167,59,6,151,44,19,145,175,343,177,64,9,12,202,208,car 95,44,84,158,62,10,145,46,19,148,163,312,166,64,10,6,199,206,van -89,40,69,147,58,6,132,50,18,137,155,260,151,61,16,6,203,209,opel -97,46,101,210,66,8,192,35,22,151,208,546,169,66,1,32,191,200,opel -88,38,58,137,60,5,148,46,19,131,163,319,157,86,12,0,180,183,saab +89,40,69,147,58,6,132,50,18,137,155,260,151,61,16,6,203,209,car +97,46,101,210,66,8,192,35,22,151,208,546,169,66,1,32,191,200,car +88,38,58,137,60,5,148,46,19,131,163,319,157,86,12,0,180,183,car 91,46,78,148,61,9,147,45,19,152,168,323,199,70,13,11,189,200,van 81,47,69,146,64,6,151,44,19,147,171,340,195,75,5,0,183,188,bus -98,50,90,192,63,9,177,37,21,155,195,472,197,65,10,1,193,201,saab -93,42,88,188,62,10,183,36,21,141,208,504,168,70,3,12,189,197,opel +98,50,90,192,63,9,177,37,21,155,195,472,197,65,10,1,193,201,car +93,42,88,188,62,10,183,36,21,141,208,504,168,70,3,12,189,197,car 91,45,76,171,69,7,150,44,19,144,170,340,179,69,12,1,195,201,bus -109,49,109,193,59,10,207,32,24,156,225,635,213,70,13,31,191,202,saab -87,45,82,164,60,8,156,42,19,144,181,366,174,70,2,2,190,196,opel -100,49,96,206,63,9,186,35,22,156,202,519,176,62,3,5,197,205,opel -108,52,109,182,55,12,216,31,24,171,229,687,214,72,10,28,189,201,saab -101,46,105,195,61,10,198,34,23,150,213,578,195,66,7,38,192,205,saab -95,47,81,176,59,7,168,39,20,152,196,425,185,67,4,4,191,198,saab +109,49,109,193,59,10,207,32,24,156,225,635,213,70,13,31,191,202,car +87,45,82,164,60,8,156,42,19,144,181,366,174,70,2,2,190,196,car +100,49,96,206,63,9,186,35,22,156,202,519,176,62,3,5,197,205,car +108,52,109,182,55,12,216,31,24,171,229,687,214,72,10,28,189,201,car +101,46,105,195,61,10,198,34,23,150,213,578,195,66,7,38,192,205,car +95,47,81,176,59,7,168,39,20,152,196,425,185,67,4,4,191,198,car 89,47,85,147,58,10,153,44,19,151,175,349,186,74,13,7,186,197,van -87,45,77,153,59,7,154,44,19,145,181,350,172,75,15,14,184,189,opel -108,54,105,203,62,11,202,33,23,164,216,608,235,68,12,3,190,200,saab +87,45,77,153,59,7,154,44,19,145,181,350,172,75,15,14,184,189,car +108,54,105,203,62,11,202,33,23,164,216,608,235,68,12,3,190,200,car 90,47,85,149,60,10,155,43,19,155,179,355,186,75,1,5,185,196,van -82,37,59,134,63,7,135,51,18,128,151,264,143,82,11,24,179,185,saab +82,37,59,134,63,7,135,51,18,128,151,264,143,82,11,24,179,185,car 84,45,68,148,64,6,146,46,19,142,168,317,180,75,5,1,183,187,bus -89,47,81,156,57,8,161,41,20,149,187,388,197,72,9,15,187,193,opel +89,47,81,156,57,8,161,41,20,149,187,388,197,72,9,15,187,193,car 96,41,77,177,64,5,177,36,21,134,205,485,148,74,0,4,196,198,bus 97,45,72,187,71,5,161,40,20,144,178,399,186,70,7,7,196,203,bus 97,47,87,164,64,9,156,43,20,149,173,359,182,68,1,13,192,202,van 96,47,77,204,72,6,167,38,20,150,188,429,182,69,6,16,199,203,bus 87,36,53,117,58,4,118,57,17,125,138,205,138,85,9,15,180,183,van 109,52,95,189,58,4,227,29,25,158,262,776,217,82,0,19,187,186,bus -104,51,108,193,59,11,217,31,24,163,232,694,203,72,15,22,190,201,saab -87,37,60,132,57,6,128,52,18,129,154,243,132,71,1,14,186,192,saab -82,36,54,117,53,7,125,54,18,126,146,229,128,78,1,5,180,184,saab -105,56,98,209,64,11,217,31,24,173,225,696,216,72,2,19,188,199,opel -80,39,60,122,56,6,139,49,18,131,151,281,142,80,0,5,179,186,opel +104,51,108,193,59,11,217,31,24,163,232,694,203,72,15,22,190,201,car +87,37,60,132,57,6,128,52,18,129,154,243,132,71,1,14,186,192,car +82,36,54,117,53,7,125,54,18,126,146,229,128,78,1,5,180,184,car +105,56,98,209,64,11,217,31,24,173,225,696,216,72,2,19,188,199,car +80,39,60,122,56,6,139,49,18,131,151,281,142,80,0,5,179,186,car 106,54,100,227,67,4,250,27,27,162,280,923,262,88,5,11,182,182,bus 81,46,71,141,61,7,153,44,19,148,177,347,190,80,1,14,182,187,bus -100,51,109,224,67,9,217,30,24,162,238,704,206,72,6,18,189,199,opel -88,44,71,145,56,8,142,48,19,143,159,296,174,68,7,18,188,197,opel +100,51,109,224,67,9,217,30,24,162,238,704,206,72,6,18,189,199,car +88,44,71,145,56,8,142,48,19,143,159,296,174,68,7,18,188,197,car 94,49,87,159,64,10,157,43,20,158,179,363,203,75,4,0,183,194,van -99,43,89,195,63,8,186,35,22,144,210,521,166,68,6,13,191,199,saab +99,43,89,195,63,8,186,35,22,144,210,521,166,68,6,13,191,199,car 90,47,85,145,58,9,152,44,19,155,175,345,184,73,4,2,186,197,van 94,47,85,333,138,49,155,43,19,155,320,354,187,135,12,9,188,196,van -100,57,107,207,63,11,227,30,25,180,234,756,205,72,6,19,186,198,opel +100,57,107,207,63,11,227,30,25,180,234,756,205,72,6,19,186,198,car 86,42,65,113,50,8,152,45,19,141,169,332,171,85,4,16,179,183,bus 91,38,70,160,66,25,140,47,18,139,162,296,130,67,4,11,192,202,van 93,44,90,166,65,10,153,44,19,156,170,348,143,66,9,17,194,203,van 86,47,75,165,68,6,154,43,19,146,176,356,190,74,7,3,188,194,bus -90,49,83,187,63,7,176,37,21,154,205,467,222,70,1,2,189,195,saab -97,37,76,169,60,8,161,41,20,131,189,391,136,72,0,0,188,192,opel +90,49,83,187,63,7,176,37,21,154,205,467,222,70,1,2,189,195,car +97,37,76,169,60,8,161,41,20,131,189,391,136,72,0,0,188,192,car 108,57,106,177,51,5,256,26,28,170,285,966,261,87,11,2,182,181,bus 89,41,75,162,66,5,153,43,19,136,175,352,154,72,2,0,188,195,bus 98,38,70,186,68,6,164,39,20,136,189,413,129,71,3,17,200,203,bus 87,42,64,150,64,10,133,50,18,141,157,265,159,67,7,0,193,201,van -107,53,108,213,64,12,206,32,23,163,216,627,202,65,21,22,194,205,saab -85,37,80,158,59,8,153,44,19,126,179,348,136,69,6,21,191,197,opel -101,52,105,162,53,10,212,31,24,163,226,669,204,74,12,11,186,194,opel +107,53,108,213,64,12,206,32,23,163,216,627,202,65,21,22,194,205,car +85,37,80,158,59,8,153,44,19,126,179,348,136,69,6,21,191,197,car +101,52,105,162,53,10,212,31,24,163,226,669,204,74,12,11,186,194,car 96,39,77,160,62,8,140,47,18,150,161,294,124,62,15,3,201,208,van -103,48,101,204,62,12,200,33,23,158,215,595,164,66,8,22,192,202,opel +103,48,101,204,62,12,200,33,23,158,215,595,164,66,8,22,192,202,car 88,40,73,173,68,7,150,44,19,137,174,341,151,69,2,20,196,200,bus -80,38,64,130,59,8,134,51,18,126,152,259,135,76,1,23,179,188,opel -91,38,75,136,53,6,144,47,19,131,165,305,149,69,1,7,186,191,saab +80,38,64,130,59,8,134,51,18,126,152,259,135,76,1,23,179,188,car +91,38,75,136,53,6,144,47,19,131,165,305,149,69,1,7,186,191,car 86,45,71,155,66,7,146,45,19,144,167,322,176,72,5,6,189,196,bus -86,38,86,175,60,9,170,39,21,134,191,433,138,68,1,28,191,199,saab -89,45,77,188,64,9,161,41,20,151,190,390,174,66,4,2,194,201,saab -78,36,51,116,56,4,120,57,17,124,135,209,135,84,1,12,177,184,opel +86,38,86,175,60,9,170,39,21,134,191,433,138,68,1,28,191,199,car +89,45,77,188,64,9,161,41,20,151,190,390,174,66,4,2,194,201,car +78,36,51,116,56,4,120,57,17,124,135,209,135,84,1,12,177,184,car 80,43,71,133,60,7,150,45,19,146,170,330,176,81,6,15,180,184,bus -88,36,78,160,62,6,140,48,18,123,161,287,129,66,4,35,194,202,opel +88,36,78,160,62,6,140,48,18,123,161,287,129,66,4,35,194,202,car 85,45,82,133,56,11,159,43,20,156,170,362,173,76,10,21,183,193,van -101,53,108,184,54,12,216,31,24,172,220,685,187,68,4,24,190,201,opel +101,53,108,184,54,12,216,31,24,172,220,685,187,68,4,24,190,201,car 89,44,70,158,64,6,141,47,18,143,164,299,173,66,9,11,193,199,bus 96,36,74,183,70,6,149,43,19,127,178,341,127,69,0,17,201,205,bus 87,43,70,169,72,7,152,44,19,145,177,341,171,76,6,12,184,187,bus -93,34,72,144,56,6,133,50,18,123,158,263,125,63,5,20,200,206,saab +93,34,72,144,56,6,133,50,18,123,158,263,125,63,5,20,200,206,car 96,39,58,117,51,6,133,52,18,139,154,255,150,86,6,0,181,182,van -98,48,101,195,61,11,207,31,23,152,227,650,193,71,5,7,189,196,opel -90,34,66,158,59,7,140,47,18,124,165,298,117,61,1,3,201,207,saab +98,48,101,195,61,11,207,31,23,152,227,650,193,71,5,7,189,196,car 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99,47,91,226,74,5,202,32,23,148,234,629,186,79,4,11,192,191,bus -84,38,83,141,54,7,149,45,19,132,177,327,149,74,6,29,185,191,saab +84,38,83,141,54,7,149,45,19,132,177,327,149,74,6,29,185,191,car 85,42,70,130,56,7,150,45,19,145,177,328,172,82,10,14,181,185,bus -104,51,105,168,54,10,208,32,24,162,220,641,221,72,9,20,187,197,saab +104,51,105,168,54,10,208,32,24,162,220,641,221,72,9,20,187,197,car 85,37,68,145,60,6,130,51,18,130,150,253,121,65,3,14,195,203,van 93,42,64,123,51,7,135,51,18,144,164,262,155,78,16,12,185,185,van -84,40,71,131,55,7,150,45,19,134,167,330,165,80,12,1,180,186,opel -91,49,86,195,63,8,177,37,21,156,203,473,201,67,7,5,192,198,opel -98,47,109,202,59,11,199,34,23,154,207,586,165,61,1,33,194,208,saab -101,51,98,194,60,10,195,34,22,161,219,572,219,67,0,10,192,201,saab +84,40,71,131,55,7,150,45,19,134,167,330,165,80,12,1,180,186,car +91,49,86,195,63,8,177,37,21,156,203,473,201,67,7,5,192,198,car +98,47,109,202,59,11,199,34,23,154,207,586,165,61,1,33,194,208,car +101,51,98,194,60,10,195,34,22,161,219,572,219,67,0,10,192,201,car 90,47,73,136,58,11,161,42,20,153,172,376,185,77,11,8,183,191,van 91,36,60,126,56,6,119,56,17,130,139,211,118,67,6,14,192,198,van -99,50,88,204,64,10,185,35,22,159,209,517,193,66,12,11,194,201,opel +99,50,88,204,64,10,185,35,22,159,209,517,193,66,12,11,194,201,car 102,53,101,238,72,4,238,28,26,163,267,844,242,85,7,22,184,184,bus 89,46,74,135,59,9,157,44,20,158,170,356,177,79,12,3,184,191,van -101,52,101,197,62,9,188,35,22,162,208,527,203,67,14,15,193,202,saab -95,57,104,228,74,10,212,31,24,175,224,670,223,74,0,4,186,193,opel +101,52,101,197,62,9,188,35,22,162,208,527,203,67,14,15,193,202,car +95,57,104,228,74,10,212,31,24,175,224,670,223,74,0,4,186,193,car 101,53,91,194,65,6,204,32,23,161,231,636,214,78,5,14,192,192,bus 91,39,82,164,68,10,143,46,19,137,164,308,158,68,13,9,191,201,van 91,46,75,185,75,7,154,42,19,147,178,362,192,72,8,8,192,199,bus -94,37,74,169,59,7,162,41,20,133,178,394,130,63,6,6,198,204,opel -92,38,74,178,62,9,161,41,20,135,181,388,132,63,7,29,197,206,opel +94,37,74,169,59,7,162,41,20,133,178,394,130,63,6,6,198,204,car +92,38,74,178,62,9,161,41,20,135,181,388,132,63,7,29,197,206,car 95,43,71,159,64,6,145,45,19,141,169,322,171,67,8,4,195,200,bus -106,52,101,213,64,11,201,33,23,158,214,607,204,65,2,4,192,204,saab +106,52,101,213,64,11,201,33,23,158,214,607,204,65,2,4,192,204,car 81,43,68,139,62,7,149,46,19,145,172,323,171,83,1,14,180,184,bus 92,43,70,124,52,6,139,49,18,144,164,282,172,79,4,16,183,185,van 83,45,73,161,68,8,142,46,18,144,169,305,179,71,10,3,191,199,van -103,57,105,221,69,11,218,30,24,173,226,706,250,73,10,2,187,195,opel -98,42,90,192,61,9,178,37,21,144,189,480,138,61,3,8,199,208,saab +103,57,105,221,69,11,218,30,24,173,226,706,250,73,10,2,187,195,car +98,42,90,192,61,9,178,37,21,144,189,480,138,61,3,8,199,208,car 90,41,62,147,60,6,128,52,18,141,149,246,157,61,13,4,201,208,van -106,52,107,211,62,8,200,33,23,161,218,602,200,67,9,17,194,201,opel -97,47,81,183,64,8,168,39,20,150,193,426,182,70,11,2,192,198,opel -85,40,66,121,52,4,152,44,19,133,170,340,163,87,13,3,180,183,opel +106,52,107,211,62,8,200,33,23,161,218,602,200,67,9,17,194,201,car +97,47,81,183,64,8,168,39,20,150,193,426,182,70,11,2,192,198,car +85,40,66,121,52,4,152,44,19,133,170,340,163,87,13,3,180,183,car 100,49,80,206,70,6,183,35,21,156,206,517,198,73,3,13,198,199,bus 82,43,71,154,68,7,150,45,19,143,171,330,173,78,7,11,181,186,bus 78,43,70,147,65,8,147,46,19,145,169,319,168,77,1,12,181,186,bus -96,54,104,175,58,10,215,31,24,175,221,682,222,75,13,23,186,194,opel -105,51,108,201,62,11,220,30,25,163,232,711,202,72,12,16,189,200,saab +96,54,104,175,58,10,215,31,24,175,221,682,222,75,13,23,186,194,car +105,51,108,201,62,11,220,30,25,163,232,711,202,72,12,16,189,200,car 92,40,62,144,59,8,127,52,17,139,149,241,150,62,13,1,204,210,van 91,44,66,151,63,7,137,48,18,146,166,280,167,72,1,9,188,194,van -104,55,109,230,67,12,218,30,24,174,230,706,226,67,8,22,191,202,opel 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88,44,84,135,55,12,155,44,20,158,176,351,164,75,7,11,183,195,van 92,40,66,111,48,7,139,50,19,140,159,277,148,85,12,19,182,183,van 88,44,70,151,61,8,143,46,18,143,163,311,173,68,7,8,196,203,bus 94,39,75,184,72,8,155,42,19,133,175,365,145,70,4,5,192,200,bus -107,51,103,182,56,11,213,31,24,162,226,673,217,72,2,4,188,198,saab +107,51,103,182,56,11,213,31,24,162,226,673,217,72,2,4,188,198,car 86,38,58,119,56,4,118,57,17,129,140,208,152,78,9,2,184,186,van -79,39,72,127,53,9,142,48,19,135,165,295,144,77,7,21,181,189,opel -90,39,89,181,62,8,175,38,21,132,200,458,154,70,11,15,189,195,saab +79,39,72,127,53,9,142,48,19,135,165,295,144,77,7,21,181,189,car +90,39,89,181,62,8,175,38,21,132,200,458,154,70,11,15,189,195,car 86,45,66,126,57,8,148,46,19,145,170,321,186,86,0,7,179,182,bus -113,48,98,208,62,9,203,33,23,151,216,613,183,64,17,29,193,204,saab -87,49,86,190,64,9,177,37,21,153,197,471,209,67,11,7,192,199,opel +113,48,98,208,62,9,203,33,23,151,216,613,183,64,17,29,193,204,car 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98,35,70,182,68,5,155,41,19,124,184,371,117,71,3,22,202,205,bus -101,48,85,191,60,11,175,38,21,153,192,458,187,62,5,22,197,210,saab -108,54,103,212,65,11,208,32,24,162,228,648,240,71,9,0,189,197,saab -91,40,83,166,60,8,160,41,20,133,189,383,155,72,5,7,186,191,saab +101,48,85,191,60,11,175,38,21,153,192,458,187,62,5,22,197,210,car +108,54,103,212,65,11,208,32,24,162,228,648,240,71,9,0,189,197,car +91,40,83,166,60,8,160,41,20,133,189,383,155,72,5,7,186,191,car 86,43,69,123,54,6,150,46,19,144,174,325,177,87,3,7,180,182,bus 97,35,66,151,64,8,128,52,18,129,148,246,112,66,6,2,195,200,van -105,53,108,206,63,12,222,31,25,168,226,712,201,71,15,35,189,203,saab -94,43,69,161,59,7,152,43,19,143,175,349,187,67,12,11,193,198,saab +105,53,108,206,63,12,222,31,25,168,226,712,201,71,15,35,189,203,car +94,43,69,161,59,7,152,43,19,143,175,349,187,67,12,11,193,198,car 96,45,87,169,67,10,154,44,19,149,167,351,174,67,9,8,192,201,van 89,47,80,131,54,11,160,43,20,163,175,369,174,77,1,7,182,193,van 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90,49,85,141,57,11,159,43,20,167,173,365,186,75,1,11,182,192,van -80,34,42,110,57,3,114,59,17,119,131,191,121,87,4,7,179,183,opel +80,34,42,110,57,3,114,59,17,119,131,191,121,87,4,7,179,183,car 92,37,75,191,71,6,161,40,20,128,180,393,135,69,1,14,195,202,bus -85,33,50,104,53,4,115,59,17,118,136,193,127,83,1,30,179,185,saab -88,34,69,152,57,5,138,48,18,122,158,284,120,62,9,29,204,210,opel -92,42,69,153,58,8,140,48,18,138,165,290,151,64,10,21,199,206,opel +85,33,50,104,53,4,115,59,17,118,136,193,127,83,1,30,179,185,car +88,34,69,152,57,5,138,48,18,122,158,284,120,62,9,29,204,210,car +92,42,69,153,58,8,140,48,18,138,165,290,151,64,10,21,199,206,car 83,37,49,112,55,5,122,55,17,128,144,219,146,85,8,16,180,184,van 98,39,68,136,56,8,131,52,18,144,159,251,134,72,4,10,186,187,van -97,55,96,170,54,10,216,31,24,173,219,685,218,75,0,4,184,193,opel -108,56,103,234,73,10,221,30,25,174,232,718,214,73,8,3,187,197,saab +97,55,96,170,54,10,216,31,24,173,219,685,218,75,0,4,184,193,car +108,56,103,234,73,10,221,30,25,174,232,718,214,73,8,3,187,197,car 90,48,81,144,60,9,150,44,19,156,173,333,200,75,2,0,185,195,van -96,40,100,178,58,8,181,37,21,134,205,486,160,68,5,34,192,202,saab -106,52,108,207,64,12,221,31,25,168,229,709,200,73,22,38,190,205,saab -84,36,75,136,55,6,140,48,18,125,166,290,138,71,4,36,189,195,saab -104,53,101,190,63,10,213,32,24,166,218,664,202,74,13,21,188,198,saab +96,40,100,178,58,8,181,37,21,134,205,486,160,68,5,34,192,202,car +106,52,108,207,64,12,221,31,25,168,229,709,200,73,22,38,190,205,car +84,36,75,136,55,6,140,48,18,125,166,290,138,71,4,36,189,195,car +104,53,101,190,63,10,213,32,24,166,218,664,202,74,13,21,188,198,car 83,44,70,166,69,5,143,46,18,143,166,306,170,69,7,6,188,193,bus 88,44,71,165,70,7,144,46,19,141,167,312,172,71,4,4,188,193,bus 98,51,84,207,72,7,184,35,21,161,199,520,198,72,9,11,196,199,bus 90,42,63,144,59,7,131,50,18,142,154,259,162,65,15,3,197,204,van -86,40,63,135,56,5,133,50,18,135,152,262,166,70,9,2,187,191,saab -103,49,107,179,54,12,208,32,24,159,214,644,183,66,1,12,191,200,opel +86,40,63,135,56,5,133,50,18,135,152,262,166,70,9,2,187,191,car +103,49,107,179,54,12,208,32,24,159,214,644,183,66,1,12,191,200,car 86,44,70,140,64,6,148,45,19,145,170,322,185,82,10,1,181,183,bus -102,52,101,213,64,10,203,33,23,157,214,616,186,65,0,19,193,203,opel -81,38,53,123,58,6,134,51,18,128,147,259,148,83,10,6,177,184,opel +102,52,101,213,64,10,203,33,23,157,214,616,186,65,0,19,193,203,car +81,38,53,123,58,6,134,51,18,128,147,259,148,83,10,6,177,184,car 97,41,62,133,56,7,130,52,18,143,158,247,157,78,5,7,184,186,van -96,41,69,153,56,7,141,47,18,141,162,297,169,61,11,8,202,209,saab +96,41,69,153,56,7,141,47,18,141,162,297,169,61,11,8,202,209,car 86,44,65,129,56,6,152,45,19,150,168,331,177,83,4,13,178,183,bus 97,49,76,203,73,7,178,36,21,157,194,487,186,72,0,7,197,200,bus -108,55,105,230,68,11,218,30,24,171,228,709,210,69,14,4,190,197,opel -91,52,98,196,62,9,193,34,22,161,216,562,244,69,3,1,190,199,opel +108,55,105,230,68,11,218,30,24,171,228,709,210,69,14,4,190,197,car +91,52,98,196,62,9,193,34,22,161,216,562,244,69,3,1,190,199,car 84,43,76,180,75,7,155,43,19,143,180,359,173,77,5,12,185,190,bus -95,46,104,208,66,9,191,35,22,148,210,543,169,68,0,28,190,200,saab +95,46,104,208,66,9,191,35,22,148,210,543,169,68,0,28,190,200,car 95,43,83,198,69,6,177,36,21,139,189,484,163,68,6,4,196,198,bus 96,46,88,160,64,9,151,44,19,148,173,339,182,70,15,11,192,199,van -86,44,77,155,60,7,152,44,19,141,174,345,161,72,9,0,187,192,opel +86,44,77,155,60,7,152,44,19,141,174,345,161,72,9,0,187,192,car 90,38,79,185,69,6,160,40,20,130,178,393,133,66,2,14,198,205,bus -85,38,75,132,54,7,147,46,19,131,171,318,145,75,7,25,183,188,saab -105,53,105,184,57,11,211,31,24,168,224,661,218,71,0,15,186,197,saab -89,38,77,161,62,7,149,45,19,129,174,327,153,71,6,21,188,193,saab -98,55,104,213,67,9,206,32,23,167,223,629,220,72,5,19,187,196,saab -85,40,66,136,58,6,142,48,19,137,164,295,164,77,2,22,182,186,saab -97,37,78,181,62,8,161,41,20,131,182,389,117,62,2,28,203,211,opel -97,41,92,197,63,10,179,37,21,140,197,481,136,63,4,3,197,204,opel -100,47,88,190,60,10,171,38,21,155,186,440,169,59,15,18,201,210,saab +85,38,75,132,54,7,147,46,19,131,171,318,145,75,7,25,183,188,car +105,53,105,184,57,11,211,31,24,168,224,661,218,71,0,15,186,197,car +89,38,77,161,62,7,149,45,19,129,174,327,153,71,6,21,188,193,car +98,55,104,213,67,9,206,32,23,167,223,629,220,72,5,19,187,196,car +85,40,66,136,58,6,142,48,19,137,164,295,164,77,2,22,182,186,car +97,37,78,181,62,8,161,41,20,131,182,389,117,62,2,28,203,211,car +97,41,92,197,63,10,179,37,21,140,197,481,136,63,4,3,197,204,car +100,47,88,190,60,10,171,38,21,155,186,440,169,59,15,18,201,210,car 86,35,44,110,54,2,119,57,17,121,139,208,137,90,6,1,180,183,van 84,42,76,156,64,7,151,44,19,143,179,339,157,75,0,20,187,193,bus 89,45,85,149,59,11,158,43,20,158,177,362,173,75,12,16,183,193,van 91,39,77,153,59,8,139,48,18,139,159,289,123,62,8,17,201,209,van -96,50,94,215,67,9,187,35,22,158,214,525,214,67,8,6,193,201,saab +96,50,94,215,67,9,187,35,22,158,214,525,214,67,8,6,193,201,car 88,35,60,143,59,7,128,52,18,129,147,246,109,62,1,6,202,209,van -110,46,100,197,61,9,193,34,22,149,209,561,160,65,11,7,194,203,saab -87,41,66,140,58,6,148,46,19,136,164,318,178,79,19,2,181,185,saab -89,47,83,169,61,8,164,40,20,150,189,402,190,72,7,10,187,193,saab +110,46,100,197,61,9,193,34,22,149,209,561,160,65,11,7,194,203,car +87,41,66,140,58,6,148,46,19,136,164,318,178,79,19,2,181,185,car +89,47,83,169,61,8,164,40,20,150,189,402,190,72,7,10,187,193,car 90,43,72,157,64,8,136,49,18,145,158,279,167,64,4,6,201,209,van 90,47,85,161,64,10,163,42,20,160,177,389,185,73,9,0,185,195,van -102,43,96,197,63,10,185,36,22,142,202,513,139,65,8,12,195,204,opel -110,53,104,223,66,10,211,32,24,164,223,659,210,67,5,16,190,203,saab +102,43,96,197,63,10,185,36,22,142,202,513,139,65,8,12,195,204,car +110,53,104,223,66,10,211,32,24,164,223,659,210,67,5,16,190,203,car 94,46,91,175,70,12,157,43,20,155,172,358,192,69,15,21,190,200,van 85,44,66,125,58,6,148,45,19,145,170,323,185,84,8,1,180,183,bus -95,51,96,196,63,9,190,35,22,161,208,543,235,68,13,0,191,198,opel -103,41,83,194,63,9,175,38,21,142,199,455,138,65,7,30,197,206,opel +95,51,96,196,63,9,190,35,22,161,208,543,235,68,13,0,191,198,car +103,41,83,194,63,9,175,38,21,142,199,455,138,65,7,30,197,206,car 97,47,88,183,60,7,197,33,23,148,214,596,201,74,8,0,192,191,bus -91,35,66,159,59,7,147,45,19,131,169,322,123,64,1,1,197,203,opel -92,37,80,180,67,8,154,43,19,129,180,353,144,69,6,9,190,195,saab -100,58,109,230,70,11,226,30,25,182,234,752,207,72,0,13,187,198,opel +91,35,66,159,59,7,147,45,19,131,169,322,123,64,1,1,197,203,car +92,37,80,180,67,8,154,43,19,129,180,353,144,69,6,9,190,195,car +100,58,109,230,70,11,226,30,25,182,234,752,207,72,0,13,187,198,car 82,43,73,158,68,7,151,44,19,145,181,337,173,80,2,17,183,188,bus 105,51,80,207,71,6,195,33,22,159,214,579,188,75,6,20,194,194,bus 86,45,70,122,56,7,148,45,19,144,170,324,186,84,9,5,180,183,bus @@ -685,163 +685,163 @@ COMPACTNESS,CIRCULARITY,DISTANCE_CIRCULARITY,RADIUS_RATIO,PR_AXIS_ASPECT_RATIO,M 110,56,109,199,57,5,251,27,27,169,272,928,268,82,11,10,183,183,bus 99,38,74,184,66,6,164,39,20,131,193,414,137,71,2,22,200,202,bus 85,42,66,120,53,7,149,46,19,143,169,321,160,85,10,7,180,182,bus -88,40,69,146,59,7,130,51,18,134,147,252,144,64,1,1,193,200,opel +88,40,69,146,59,7,130,51,18,134,147,252,144,64,1,1,193,200,car 106,57,107,235,67,6,262,26,28,171,285,987,260,86,9,31,180,184,bus -89,35,52,121,57,4,122,55,17,125,139,220,128,82,5,13,181,184,saab -105,51,105,197,60,11,191,35,22,162,207,545,194,64,18,4,196,205,saab -94,40,85,186,62,9,169,39,20,139,184,430,133,61,2,9,200,210,saab +89,35,52,121,57,4,122,55,17,125,139,220,128,82,5,13,181,184,car +105,51,105,197,60,11,191,35,22,162,207,545,194,64,18,4,196,205,car +94,40,85,186,62,9,169,39,20,139,184,430,133,61,2,9,200,210,car 86,45,71,170,70,6,146,45,19,146,172,321,189,71,10,8,187,191,bus -108,51,100,206,63,10,196,34,23,159,214,576,201,65,7,16,194,205,saab +108,51,100,206,63,10,196,34,23,159,214,576,201,65,7,16,194,205,car 90,46,75,133,55,11,160,43,20,161,173,369,171,77,0,16,182,192,van -100,43,92,197,62,10,180,36,21,143,200,489,153,64,6,9,195,205,saab +100,43,92,197,62,10,180,36,21,143,200,489,153,64,6,9,195,205,car 92,41,66,125,52,7,139,50,18,143,160,275,161,81,7,19,182,184,van -89,38,82,156,59,8,153,43,19,129,179,351,137,70,1,1,187,192,saab +89,38,82,156,59,8,153,43,19,129,179,351,137,70,1,1,187,192,car 92,37,75,184,70,6,154,42,19,131,184,363,127,71,0,4,198,202,bus 83,42,71,152,64,7,149,45,19,142,172,331,158,74,2,2,184,190,bus -93,47,83,165,60,7,167,40,20,147,197,417,201,73,12,4,187,192,opel -106,53,98,192,58,11,217,31,24,166,228,693,191,71,11,24,188,198,opel -108,49,103,200,62,10,206,32,23,155,227,635,215,72,6,16,189,198,saab -96,48,83,177,59,8,171,39,21,152,195,438,196,67,15,0,195,201,opel +93,47,83,165,60,7,167,40,20,147,197,417,201,73,12,4,187,192,car +106,53,98,192,58,11,217,31,24,166,228,693,191,71,11,24,188,198,car +108,49,103,200,62,10,206,32,23,155,227,635,215,72,6,16,189,198,car +96,48,83,177,59,8,171,39,21,152,195,438,196,67,15,0,195,201,car 93,43,78,162,64,8,137,48,18,145,156,281,159,63,17,12,203,210,van -99,52,104,177,55,10,210,32,24,166,219,657,215,73,3,2,187,194,opel -110,54,102,201,64,11,213,31,24,171,222,669,221,73,17,16,188,198,saab +99,52,104,177,55,10,210,32,24,166,219,657,215,73,3,2,187,194,car +110,54,102,201,64,11,213,31,24,171,222,669,221,73,17,16,188,198,car 82,43,70,250,105,55,139,48,18,145,231,289,172,99,4,9,190,199,van 92,35,58,136,58,6,122,55,17,132,142,222,116,64,6,17,197,203,van 94,49,82,137,56,10,159,43,20,160,176,367,186,76,10,7,183,192,van -95,42,96,197,65,9,178,37,21,141,199,474,149,67,1,29,193,200,opel +95,42,96,197,65,9,178,37,21,141,199,474,149,67,1,29,193,200,car 102,54,98,201,61,6,225,29,25,165,246,766,231,79,9,14,188,187,bus -100,54,102,206,65,10,198,33,23,164,224,587,240,72,4,11,187,196,saab -105,45,100,195,61,10,198,33,23,149,214,586,186,67,8,5,192,200,saab -107,53,108,211,63,11,219,31,25,168,228,704,198,69,10,21,190,203,saab +100,54,102,206,65,10,198,33,23,164,224,587,240,72,4,11,187,196,car +105,45,100,195,61,10,198,33,23,149,214,586,186,67,8,5,192,200,car +107,53,108,211,63,11,219,31,25,168,228,704,198,69,10,21,190,203,car 94,44,70,186,72,8,153,42,19,144,171,361,178,67,7,2,199,206,bus -100,52,109,225,68,10,222,30,25,165,241,731,207,73,7,28,188,199,opel -97,41,88,184,59,9,175,38,21,140,192,459,147,63,1,5,196,205,saab +100,52,109,225,68,10,222,30,25,165,241,731,207,73,7,28,188,199,car +97,41,88,184,59,9,175,38,21,140,192,459,147,63,1,5,196,205,car 96,46,74,202,74,5,163,39,20,149,185,408,191,70,7,8,196,200,bus -104,52,110,172,53,10,219,30,25,166,235,711,218,74,10,28,188,198,opel -104,53,101,199,65,11,213,31,24,168,216,667,221,72,12,12,187,198,saab -91,38,76,172,61,8,167,40,20,134,196,415,145,71,0,28,189,198,opel -105,54,108,234,70,12,215,31,24,168,226,687,228,68,4,22,189,201,saab +104,52,110,172,53,10,219,30,25,166,235,711,218,74,10,28,188,198,car +104,53,101,199,65,11,213,31,24,168,216,667,221,72,12,12,187,198,car +91,38,76,172,61,8,167,40,20,134,196,415,145,71,0,28,189,198,car +105,54,108,234,70,12,215,31,24,168,226,687,228,68,4,22,189,201,car 94,45,85,163,68,10,157,44,20,156,170,357,176,73,17,11,187,195,van -105,46,100,195,61,9,193,34,22,150,207,557,161,65,5,9,194,202,opel +105,46,100,195,61,9,193,34,22,150,207,557,161,65,5,9,194,202,car 94,45,85,160,63,10,158,43,20,157,174,367,162,68,1,6,189,199,van 91,37,76,138,55,8,132,51,18,135,157,256,124,69,0,12,191,192,van -102,48,105,214,64,10,201,33,23,152,214,600,178,64,0,25,192,204,saab +102,48,105,214,64,10,201,33,23,152,214,600,178,64,0,25,192,204,car 96,44,68,190,70,7,155,41,19,145,179,372,166,67,5,7,202,206,bus -85,36,72,127,56,7,127,54,18,125,144,233,123,70,3,30,184,194,opel -103,48,96,232,71,10,205,32,23,153,226,633,197,71,2,15,188,196,opel -101,55,107,200,61,11,225,30,25,178,228,730,204,74,8,35,187,201,opel +85,36,72,127,56,7,127,54,18,125,144,233,123,70,3,30,184,194,car +103,48,96,232,71,10,205,32,23,153,226,633,197,71,2,15,188,196,car +101,55,107,200,61,11,225,30,25,178,228,730,204,74,8,35,187,201,car 103,52,103,170,52,7,236,28,26,160,254,816,250,82,3,23,183,184,bus 85,45,73,167,69,8,143,46,18,148,173,307,176,71,2,0,190,199,van 114,57,102,181,52,6,257,26,28,169,287,968,261,85,2,21,182,184,bus 88,40,55,114,53,7,132,53,18,139,142,249,158,87,0,7,176,183,van -86,37,77,144,54,7,154,43,19,127,179,352,145,71,14,13,186,191,opel -102,51,104,217,67,10,204,32,23,162,220,621,195,68,3,19,188,197,saab +86,37,77,144,54,7,154,43,19,127,179,352,145,71,14,13,186,191,car +102,51,104,217,67,10,204,32,23,162,220,621,195,68,3,19,188,197,car 105,51,93,160,51,7,217,30,24,165,240,703,208,81,9,25,188,188,bus 100,50,98,204,63,6,218,30,24,156,232,719,213,77,8,7,189,189,bus 96,44,85,166,66,10,155,43,19,150,167,355,159,67,3,10,192,202,van -109,52,104,199,60,12,215,31,24,162,220,691,212,67,11,7,189,199,saab +109,52,104,199,60,12,215,31,24,162,220,691,212,67,11,7,189,199,car 87,39,74,165,66,6,145,45,19,134,173,318,139,70,3,21,195,200,bus -90,41,78,145,55,7,138,48,18,138,161,284,158,67,0,1,192,197,opel -98,48,101,203,65,9,197,33,23,152,216,584,174,68,2,5,189,197,saab +90,41,78,145,55,7,138,48,18,138,161,284,158,67,0,1,192,197,car +98,48,101,203,65,9,197,33,23,152,216,584,174,68,2,5,189,197,car 96,46,88,174,68,10,155,43,19,148,173,354,182,69,14,15,194,202,van 85,43,69,141,62,7,152,44,19,145,178,341,179,84,1,4,181,184,bus 91,42,66,142,58,9,134,50,18,142,163,268,164,69,6,5,191,197,van 80,43,68,123,53,7,150,46,19,147,169,327,176,81,7,14,179,184,bus 93,46,85,169,66,9,151,44,19,147,169,339,179,67,0,4,195,204,van -93,51,90,209,69,8,183,36,22,156,211,506,230,70,6,1,189,196,saab -96,40,78,170,58,7,174,38,21,139,197,455,160,68,3,29,191,200,saab 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a/frontend/src/components/FeatureSpaceDetail.vue +++ b/frontend/src/components/FeatureSpaceDetail.vue @@ -802,11 +802,19 @@ export default { // links.push({"source": index, "target": (index*feature.value.length+pushEachFinal.length+indexIns), "value": Math.abs(element.valueIns) * 30, "lin_color": "#e31a1c"}) // } if (element.valueIns > 0) { - links.push({"source": index, "target": (pushEachFinal.length+indexIns), "value": Math.abs(element.valueIns) * 30, "lin_color": "#33a02c"}) + if (Math.abs(element.valueIns) < 0.005) { + links.push({"source": index, "target": (pushEachFinal.length+indexIns), "value": 0.01 * 30, "lin_color": "#33a02c"}) + } else { + links.push({"source": index, "target": (pushEachFinal.length+indexIns), "value": Math.abs(element.valueIns) * 30, "lin_color": "#33a02c"}) + } } else if (element.valueIns == 0) { - links.push({"source": index, "target": (pushEachFinal.length+indexIns), "value": 0.1 * 30, "lin_color": "#D3D3D3"}) + links.push({"source": index, "target": (pushEachFinal.length+indexIns), "value": 0.01 * 30, "lin_color": "#D3D3D3"}) } else { - links.push({"source": index, "target": (pushEachFinal.length+indexIns), "value": Math.abs(element.valueIns) * 30, "lin_color": "#e31a1c"}) + if (Math.abs(element.valueIns) < 0.005) { + links.push({"source": index, "target": (pushEachFinal.length+indexIns), "value": 0.01 * 30, "lin_color": "#e31a1c"}) + } else { + links.push({"source": index, "target": (pushEachFinal.length+indexIns), "value": Math.abs(element.valueIns) * 30, "lin_color": "#e31a1c"}) + } } }) } @@ -827,6 +835,7 @@ export default { var legendCall = this.legendOnlyOnce var listofNodes = this.dataFS[34] + var nodesStable = this.dataFS[33] var corrTarget = JSON.parse(this.dataFS[8+this.quadrantNumber]) var corrGlob = JSON.parse(this.dataFS[13+this.quadrantNumber]) @@ -835,7 +844,7 @@ export default { var MIVar = JSON.parse(this.dataFS[28+this.quadrantNumber]) MIVar = MIVar.concat(this.MIRemaining) //var colorCateg = d3.scaleOrdinal(d3.schemeDark2) - var colorCateg = d3.scaleOrdinal().domain([0, 1, 2, 4]).range(['#808000','#7570b3','#d95f02','#1b9e77']) + var colorCateg = d3.scaleOrdinal().domain([0, 1, 2]).range(['#808000','#7570b3','#469990']) var corrTargetFormatted = [] for (let i = 0; i < Object.keys(corrTarget).length; i++) { @@ -969,8 +978,8 @@ export default { clearSendNode.push(id.name) var name = id.name var splitName = name.split("_") - for (let m = 0; m < listofNodes.length ; m++) { - if (listofNodes[m].includes(splitName[0])) { + for (let m = 0; m < nodesStable.length ; m++) { + if (nodesStable[m].includes(splitName[0])) { var valueToSend = m } } @@ -1088,8 +1097,8 @@ export default { EventBus.$emit('Counter', selectionCounter) var name = id.name var splitName = name.split("_") - for (let m = 0; m < listofNodes.length ; m++) { - if (listofNodes[m].includes(splitName[0])) { + for (let m = 0; m < nodesStable.length ; m++) { + if (nodesStable[m].includes(splitName[0])) { var valueToSend = m } } @@ -1540,7 +1549,12 @@ export default { return 6 }); node.append('title').text(function (d, i) { - return 'Target COR: '+String(corrGlobFormatted[i])+'%'; + if (i >= listofNodes.length) { + var indexNodeTransf = activeNodeLoc*12+i + } else { + var indexNodeTransf = i + } + return 'Target COR: '+String(corrGlobFormatted[indexNodeTransf])+'%'; }); //add zoom capabilities @@ -1598,7 +1612,7 @@ export default { var exemplaryValues = [25, 75] dataLegend.push({value: 25, color: '#D3D3D3'}) - dataLegend.push({value: 50, color: '#9ecae1'}) + dataLegend.push({value: 50, color: '#4292c6'}) for(let k = 0; k < 2; k++) { binaryBarLegend.push({value: exemplaryValues[k], class: k, color: colorCateg(k)}) @@ -1773,7 +1787,7 @@ export default { .attr("orient", "auto-start-reverse") .append("path") .attr('d', d3.line()(arrowPoints)) - .style("fill", "#6baed6"); + .style("fill", "#4292c6"); //line @@ -1820,7 +1834,7 @@ export default { .text("Target COR") textLine.append('line') - .style("stroke", "#6baed6") + .style("stroke", "#4292c6") .style("stroke-width", 3) .attr("x1", 18 + marginBorderX) .attr("y1", 50 - marginBorder) @@ -1831,7 +1845,7 @@ export default { textLine.append("text") .attr("dx", -2 + marginBorderX) .attr("dy", 55 - marginBorder) - .style("fill", "#6baed6") + .style("fill", "#4292c6") .text("MI") } stepper.stop(); diff --git a/frontend/src/components/FeatureSpaceOverview.vue b/frontend/src/components/FeatureSpaceOverview.vue index e8a46dc..a100b93 100644 --- a/frontend/src/components/FeatureSpaceOverview.vue +++ b/frontend/src/components/FeatureSpaceOverview.vue @@ -373,7 +373,7 @@ export default { .attr('transform', 'translate(' + curX + ',' + curY + ')'); d3.select(document) // set up document events - .on('wheel', wheel) // zoom, rotate + //.on('wheel', wheel) // zoom, rotate .on('keydown', keydown) .on('keyup', keyup); d3.select(window).on('resize', resize); @@ -948,24 +948,24 @@ export default { var moveX = 0, moveY = 0, moveZ = 0, moveR = 0; // animations var aniRequest = null; - function wheel() { // mousewheel - var dz, newZ; - var slow = d3.event.altKey ? 0.25 : 1; - if (d3.event.wheelDeltaY !== 0) { // up-down - dz = Math.pow(1.2, d3.event.wheelDeltaY * 0.001 * slow); - newZ = limitZ(curZ * dz); - dz = newZ / curZ; - curZ = newZ; - - curX -= (d3.event.clientX - curX) * (dz - 1); - curY -= (d3.event.clientY - curY) * (dz - 1); - setview(); - } - if (d3.event.wheelDeltaX !== 0) { // left-right - curR = limitR(curR + d3.event.wheelDeltaX * 0.01 * slow); - update(root); - } - } + // function wheel() { // mousewheel + // var dz, newZ; + // var slow = d3.event.altKey ? 0.25 : 1; + // if (d3.event.wheelDeltaY !== 0) { // up-down + // dz = Math.pow(1.2, d3.event.wheelDeltaY * 0.001 * slow); + // newZ = limitZ(curZ * dz); + // dz = newZ / curZ; + // curZ = newZ; + + // curX -= (d3.event.clientX - curX) * (dz - 1); + // curY -= (d3.event.clientY - curY) * (dz - 1); + // setview(); + // } + // if (d3.event.wheelDeltaX !== 0) { // left-right + // curR = limitR(curR + d3.event.wheelDeltaX * 0.01 * slow); + // update(root); + // } + // } // keyboard shortcuts function keydown(key, shift) { @@ -1173,10 +1173,10 @@ export default { } var legendRectSize = 14; - var legendSpacing = 3; - var color = d3v5.scaleOrdinal(d3v5.schemeDark2) - var labelsData = JSON.parse(this.overallData[1]) - + var legendSpacing = 3; + var labelsData = JSON.parse(this.overallData[1]) + var color = d3v5.scaleOrdinal().domain(labelsData).range(['#808000','#7570b3','#469990']) + var svgLegend = d3v5.select('#legendTarget').append('svg') .attr('width', 130) .attr('height', 60) @@ -1188,7 +1188,7 @@ export default { .attr('class', 'legend') // NEW .attr('transform', function(d, i) { // NEW var height = legendRectSize + legendSpacing; // NEW - var offset = height * color.domain().length / 2; + var offset = height * 0 / 2; var horz = 25 // NEW var vert = i * height - offset; // NEW return 'translate(' + horz + ',' + vert + ')'; // NEW diff --git a/frontend/src/components/Results.vue b/frontend/src/components/Results.vue index 4a9b7b1..d32a1e7 100644 --- a/frontend/src/components/Results.vue +++ b/frontend/src/components/Results.vue @@ -84,7 +84,9 @@ export default { } var toWhichTrans = this.historyKey + console.log(toWhichTrans) var toWhichPosition = this.whereIsChange + console.log(toWhichPosition) var counterSet = -1 var labelsX = ['Include', 'Exclude', 'Transform', 'Generate'] @@ -179,6 +181,8 @@ export default { if (this.storeBestSoFarAV <= (parseFloat(this.scoresMean[0]) + parseFloat(this.scoresMean[1]) + parseFloat(this.scoresMean[2]) - parseFloat(this.scoresSTD[0]) - parseFloat(this.scoresSTD[1]) - parseFloat(this.scoresSTD[2]))) { this.flag = true this.storeBestSoFarAV = parseFloat(this.scoresMean[0]) + parseFloat(this.scoresMean[1]) + parseFloat(this.scoresMean[2]) - parseFloat(this.scoresSTD[0]) - parseFloat(this.scoresSTD[1]) - parseFloat(this.scoresSTD[2]) + console.log('Better Results:') + console.log(this.storeBestSoFarAV) } var previously = this.previousState @@ -281,6 +285,7 @@ export default { .attr('y', xLabelHeight) .attr('transform', 'translate(0,-6)') .attr('class', 'xLabel') + .style("font-size", "14px") .style('text-anchor', 'middle') .style('fill-opacity', 0) @@ -303,6 +308,7 @@ export default { .text(function (d) { return d.label }) .attr('x', yLabelWidth) .attr('class', 'yLabel') + .style("font-size", "14px") .style('text-anchor', 'end') .style('fill-opacity', 0) @@ -434,6 +440,10 @@ export default { gridcolor: "rgb(230,230,230)", title: 'Validation metric', tickformat: '.0f', + font: { + size: 13, + color: '#000000' + }, showgrid: true, showline: false, showticklabels: true, @@ -444,6 +454,10 @@ export default { yaxis: { gridcolor: "rgb(230,230,230)", title: 'Performance (%)', + font: { + size: 13, + color: '#000000' + }, showgrid: true, showline: false, showticklabels: true, @@ -462,10 +476,18 @@ export default { t: 5, pad: 5 }, + font: { + size: 13, + color: '#000000' + }, legend:{ xanchor:"center", yanchor:"top", - y:-0.3, // play with it + font: { + size: 13, + color: '#000000' + }, + y:-0.35, // play with it x:0.5, // play with it orientation: "h" } @@ -505,10 +527,17 @@ export default { text { font-family: sans-serif; fill: black; - font: 16px sans-serif; cursor: default; } +.xLabel text { + font-size: 14px !important; +} + +.yLabel text { + font-size: 14px !important; +} + svg { display: block; } diff --git a/insertMongo.py b/insertMongo.py index 6b1dac7..92fcce1 100644 --- a/insertMongo.py +++ b/insertMongo.py @@ -10,7 +10,7 @@ def import_content(filepath): mng_client = pymongo.MongoClient('localhost', 27017) mng_db = mng_client['mydb'] #collection_name = 'StanceCTest' - collection_name = 'WineC' + collection_name = 'VehicleC' db_cm = mng_db[collection_name] cdir = os.path.dirname(__file__) file_res = os.path.join(cdir, filepath) @@ -21,5 +21,5 @@ def import_content(filepath): db_cm.insert(data_json) if __name__ == "__main__": - filepath = '/Users/anchaa/Documents/Research/FeatureEnVi_code/extra_data_sets/winequality.csv' + filepath = '/Users/anchaa/Documents/Research/FeatureEnVi_code/extra_data_sets/vehicle.csv' import_content(filepath) \ No newline at end of file diff --git a/run.py b/run.py index 1004c50..f87291c 100644 --- a/run.py +++ b/run.py @@ -8,7 +8,8 @@ import warnings import re import random import math -import pandas as pd +import pandas as pd +pd.set_option('use_inf_as_na', True) import numpy as np import multiprocessing @@ -108,7 +109,7 @@ def reset(): all_classifiers = [] global crossValidation - crossValidation = 5 + crossValidation = 8 global resultsMetrics resultsMetrics = [] @@ -227,7 +228,7 @@ def retrieveFileName(): all_classifiers = [] global crossValidation - crossValidation = 5 + crossValidation = 8 global parametersSelData parametersSelData = [] @@ -288,9 +289,8 @@ def retrieveFileName(): elif data['fileName'] == 'VehicleC': CollectionDB = mongo.db.VehicleC.find() target_names.append('Van') - target_names.append('Saab') + target_names.append('Car') target_names.append('Bus') - target_names.append('Opel') elif data['fileName'] == 'WineC': CollectionDB = mongo.db.WineC.find() target_names.append('Fine') @@ -518,6 +518,11 @@ def dataSetSelection(): def create_global_function(): global estimator + location = './cachedir' + memory = Memory(location, verbose=0) + + # calculating for all algorithms and models the performance and other results + @memory.cache def estimator(n_estimators, eta, max_depth, subsample, colsample_bytree): # initialize model n_estimators = int(n_estimators) @@ -586,7 +591,7 @@ def executeModel(exeCall, flagEx, nodeTransfName): create_global_function() params = {"n_estimators": (5, 200), "eta": (0.05, 0.3), "max_depth": (6,12), "subsample": (0.8,1), "colsample_bytree": (0.8,1)} bayesopt = BayesianOptimization(estimator, params, random_state=RANDOM_SEED) - bayesopt.maximize(init_points=35, n_iter=15, acq='ucb') # 35 and 15 + bayesopt.maximize(init_points=20, n_iter=5, acq='ucb') # 20 and 5 bestParams = bayesopt.max['params'] estimator = XGBClassifier(n_estimators=int(bestParams.get('n_estimators')), eta=bestParams.get('eta'), max_depth=int(bestParams.get('max_depth')), subsample=bestParams.get('subsample'), colsample_bytree=bestParams.get('colsample_bytree'), probability=True, random_state=RANDOM_SEED, silent=True, verbosity = 0, use_label_encoder=False) columnsNewGen = OrignList @@ -615,16 +620,24 @@ def executeModel(exeCall, flagEx, nodeTransfName): elif (flagEx == 4): splittedCol = nodeTransfName.split('_') for col in XDataNoRemoval.columns: - if ((splittedCol[0] in col)): - storeRenamedColumn = col + splitCol = col.split('_') + if ((splittedCol[0] in splitCol[0])): + newSplitted = re.sub("[^0-9]", "", splittedCol[0]) + newCol = re.sub("[^0-9]", "", splitCol[0]) + if (newSplitted == newCol): + storeRenamedColumn = col XData.rename(columns={ storeRenamedColumn: nodeTransfName }, inplace = True) XDataNoRemoval.rename(columns={ storeRenamedColumn: nodeTransfName }, inplace = True) currentColumn = columnsNewGen[exeCall[0]] subString = currentColumn[currentColumn.find("(")+1:currentColumn.find(")")] replacement = currentColumn.replace(subString, nodeTransfName) for ind, column in enumerate(columnsNewGen): - if ((splittedCol[0] in column)): - columnsNewGen[ind] = columnsNewGen[ind].replace(storeRenamedColumn, nodeTransfName) + splitCol = column.split('_') + if ((splittedCol[0] in splitCol[0])): + newSplitted = re.sub("[^0-9]", "", splittedCol[0]) + newCol = re.sub("[^0-9]", "", splitCol[0]) + if (newSplitted == newCol): + columnsNewGen[ind] = columnsNewGen[ind].replace(storeRenamedColumn, nodeTransfName) if (len(splittedCol) == 1): XData[nodeTransfName] = XDataStoredOriginal[nodeTransfName] XDataNoRemoval[nodeTransfName] = XDataStoredOriginal[nodeTransfName] @@ -648,32 +661,32 @@ def executeModel(exeCall, flagEx, nodeTransfName): elif (splittedCol[1] == 'l2'): dfTemp = [] dfTemp = np.log2(XData[nodeTransfName]) - dfTemp = dfTemp.replace(np.nan, 0) - dfTemp = dfTemp.replace(np.inf, 1.7976931348623157e+308) - dfTemp = dfTemp.replace(-np.inf, 1.7976931348623157e-308) + dfTemp = dfTemp.replace([np.inf, -np.inf], np.nan) + dfTemp = dfTemp.fillna(0) XData[nodeTransfName] = dfTemp elif (splittedCol[1] == 'l1p'): - XData[nodeTransfName] = np.log1p(XData[nodeTransfName]) + dfTemp = [] + dfTemp = np.log1p(XData[nodeTransfName]) + dfTemp = dfTemp.replace([np.inf, -np.inf], np.nan) + dfTemp = dfTemp.fillna(0) + XData[nodeTransfName] = dfTemp elif (splittedCol[1] == 'l10'): dfTemp = [] dfTemp = np.log10(XData[nodeTransfName]) - dfTemp = dfTemp.replace(np.nan, 0) - dfTemp = dfTemp.replace(np.inf, 1.7976931348623157e+308) - dfTemp = dfTemp.replace(-np.inf, 1.7976931348623157e-308) + dfTemp = dfTemp.replace([np.inf, -np.inf], np.nan) + dfTemp = dfTemp.fillna(0) XData[nodeTransfName] = dfTemp elif (splittedCol[1] == 'e2'): dfTemp = [] dfTemp = np.exp2(XData[nodeTransfName]) - dfTemp = dfTemp.replace(np.nan, 0) - dfTemp = dfTemp.replace(np.inf, 1.7976931348623157e+308) - dfTemp = dfTemp.replace(-np.inf, 1.7976931348623157e-308) + dfTemp = dfTemp.replace([np.inf, -np.inf], np.nan) + dfTemp = dfTemp.fillna(0) XData[nodeTransfName] = dfTemp elif (splittedCol[1] == 'em1'): dfTemp = [] dfTemp = np.expm1(XData[nodeTransfName]) - dfTemp = dfTemp.replace(np.nan, 0) - dfTemp = dfTemp.replace(np.inf, 1.7976931348623157e+308) - dfTemp = dfTemp.replace(-np.inf, 1.7976931348623157e-308) + dfTemp = dfTemp.replace([np.inf, -np.inf], np.nan) + dfTemp = dfTemp.fillna(0) XData[nodeTransfName] = dfTemp elif (splittedCol[1] == 'p2'): XData[nodeTransfName] = np.power(XData[nodeTransfName], 2) @@ -699,8 +712,6 @@ def executeModel(exeCall, flagEx, nodeTransfName): else: columnsNames.append(splittedCol[0]+'_'+tran) - print(XData) - featureImportanceData = estimatorFeatureSelection(XDataNoRemoval, estimator) tracker = [] @@ -716,7 +727,9 @@ def executeModel(exeCall, flagEx, nodeTransfName): yPredictProb = cross_val_predict(estimator, XData, yData, cv=crossValidation, method='predict_proba') num_cores = multiprocessing.cpu_count() - inputsSc = ['accuracy','precision_macro','recall_macro'] + inputsSc = ['accuracy','precision_weighted','recall_weighted'] + + print(XData) flat_results = Parallel(n_jobs=num_cores)(delayed(solve)(estimator,XData,yData,crossValidation,item,index) for index, item in enumerate(inputsSc)) scoresAct = [item for sublist in flat_results for item in sublist] @@ -774,11 +787,11 @@ def featFun (clfLocalPar,DataLocalPar,yDataLocalPar): return PerFeatureAccuracyLocalPar -# location = './cachedir' -# memory = Memory(location, verbose=0) +location = './cachedir' +memory = Memory(location, verbose=0) -# # calculating for all algorithms and models the performance and other results -# @memory.cache +# calculating for all algorithms and models the performance and other results +@memory.cache def estimatorFeatureSelection(Data, clf): resultsFS = [] @@ -805,7 +818,7 @@ def estimatorFeatureSelection(Data, clf): selector = RFECV(estimator=estim, n_jobs = -1, step=1, cv=crossValidation) selector = selector.fit(Data, yData) RFEImp = selector.ranking_ - print(RFEImp) + for f in range(Data.shape[1]): if (RFEImp[f] == 1): RankingFS.append(0.95) @@ -1028,9 +1041,8 @@ def Transformation(quadrant1, quadrant2, quadrant3, quadrant4, quadrant5): XDataNumericCopy = XDataNumeric.copy() dfTemp = [] dfTemp = np.log2(XDataNumericCopy[i]) - dfTemp = dfTemp.replace(np.nan, 0) - dfTemp = dfTemp.replace(np.inf, 1.7976931348623157e+308) - dfTemp = dfTemp.replace(-np.inf, 1.7976931348623157e-308) + dfTemp = dfTemp.replace([np.inf, -np.inf], np.nan) + dfTemp = dfTemp.fillna(0) XDataNumericCopy[i] = dfTemp for number in range(1,6): quadrantVariable = str('quadrant%s' % number) @@ -1051,7 +1063,11 @@ def Transformation(quadrant1, quadrant2, quadrant3, quadrant4, quadrant5): d={} flagInf = False XDataNumericCopy = XDataNumeric.copy() - XDataNumericCopy[i] = np.log1p(XDataNumericCopy[i]) + dfTemp = [] + dfTemp = np.log1p(XDataNumericCopy[i]) + dfTemp = dfTemp.replace([np.inf, -np.inf], np.nan) + dfTemp = dfTemp.fillna(0) + XDataNumericCopy[i] = dfTemp for number in range(1,6): quadrantVariable = str('quadrant%s' % number) illusion = locals()[quadrantVariable] @@ -1073,9 +1089,8 @@ def Transformation(quadrant1, quadrant2, quadrant3, quadrant4, quadrant5): XDataNumericCopy = XDataNumeric.copy() dfTemp = [] dfTemp = np.log10(XDataNumericCopy[i]) - dfTemp = dfTemp.replace(np.nan, 0) - dfTemp = dfTemp.replace(np.inf, 1.7976931348623157e+308) - dfTemp = dfTemp.replace(-np.inf, 1.7976931348623157e-308) + dfTemp = dfTemp.replace([np.inf, -np.inf], np.nan) + dfTemp = dfTemp.fillna(0) XDataNumericCopy[i] = dfTemp for number in range(1,6): quadrantVariable = str('quadrant%s' % number) @@ -1098,9 +1113,8 @@ def Transformation(quadrant1, quadrant2, quadrant3, quadrant4, quadrant5): XDataNumericCopy = XDataNumeric.copy() dfTemp = [] dfTemp = np.exp2(XDataNumericCopy[i]) - dfTemp = dfTemp.replace(np.nan, 0) - dfTemp = dfTemp.replace(np.inf, 1.7976931348623157e+308) - dfTemp = dfTemp.replace(-np.inf, 1.7976931348623157e-308) + dfTemp = dfTemp.replace([np.inf, -np.inf], np.nan) + dfTemp = dfTemp.fillna(0) XDataNumericCopy[i] = dfTemp if (np.isinf(dfTemp.var())): flagInf = True @@ -1125,9 +1139,8 @@ def Transformation(quadrant1, quadrant2, quadrant3, quadrant4, quadrant5): XDataNumericCopy = XDataNumeric.copy() dfTemp = [] dfTemp = np.expm1(XDataNumericCopy[i]) - dfTemp = dfTemp.replace(np.nan, 0) - dfTemp = dfTemp.replace(np.inf, 1.7976931348623157e+308) - dfTemp = dfTemp.replace(-np.inf, 1.7976931348623157e-308) + dfTemp = dfTemp.replace([np.inf, -np.inf], np.nan) + dfTemp = dfTemp.fillna(0) XDataNumericCopy[i] = dfTemp if (np.isinf(dfTemp.var())): flagInf = True @@ -1251,14 +1264,20 @@ def NewComputationTransf(DataRows1, DataRows2, DataRows3, DataRows4, DataRows5, corrMatrixComb1 = concatDF1.corr() corrMatrixComb1 = corrMatrixComb1.abs() corrMatrixComb1 = corrMatrixComb1.iloc[:,-len(uniqueTarget1):] - X1 = add_constant(DataRows1.dropna()) + DataRows1 = DataRows1.replace([np.inf, -np.inf], np.nan) + DataRows1 = DataRows1.fillna(0) + X1 = add_constant(DataRows1) + X1 = X1.replace([np.inf, -np.inf], np.nan) + X1 = X1.fillna(0) VIF1 = pd.Series([variance_inflation_factor(X1.values, i) for i in range(X1.shape[1])], index=X1.columns) - VIF1 = VIF1.replace(np.nan, 0) - VIF1 = VIF1.replace(-np.inf, 1.7976931348623157e-308) - VIF1 = VIF1.replace(np.inf, 1.7976931348623157e+308) - VIF1 = VIF1.loc[[feature]] + if (flagInf == False): + VIF1 = VIF1.replace([np.inf, -np.inf], np.nan) + VIF1 = VIF1.fillna(0) + VIF1 = VIF1.loc[[feature]] + else: + VIF1 = pd.Series() if ((len(targetRows1Arr) > 2) and (flagInf == False)): MI1 = mutual_info_classif(DataRows1, targetRows1Arr, n_neighbors=3, random_state=RANDOM_SEED) MI1List = MI1.tolist() @@ -1279,14 +1298,20 @@ def NewComputationTransf(DataRows1, DataRows2, DataRows3, DataRows4, DataRows5, corrMatrixComb2 = concatDF2.corr() corrMatrixComb2 = corrMatrixComb2.abs() corrMatrixComb2 = corrMatrixComb2.iloc[:,-len(uniqueTarget2):] - X2 = add_constant(DataRows2.dropna()) + DataRows2 = DataRows2.replace([np.inf, -np.inf], np.nan) + DataRows2 = DataRows2.fillna(0) + X2 = add_constant(DataRows2) + X2 = X2.replace([np.inf, -np.inf], np.nan) + X2 = X2.fillna(0) VIF2 = pd.Series([variance_inflation_factor(X2.values, i) for i in range(X2.shape[1])], index=X2.columns) - VIF2 = VIF2.replace(np.nan, 0) - VIF2 = VIF2.replace(-np.inf, 1.7976931348623157e-308) - VIF2 = VIF2.replace(np.inf, 1.7976931348623157e+308) - VIF2 = VIF2.loc[[feature]] + if (flagInf == False): + VIF2 = VIF2.replace([np.inf, -np.inf], np.nan) + VIF2 = VIF2.fillna(0) + VIF2 = VIF2.loc[[feature]] + else: + VIF2 = pd.Series() if ((len(targetRows2Arr) > 2) and (flagInf == False)): MI2 = mutual_info_classif(DataRows2, targetRows2Arr, n_neighbors=3, random_state=RANDOM_SEED) MI2List = MI2.tolist() @@ -1307,14 +1332,20 @@ def NewComputationTransf(DataRows1, DataRows2, DataRows3, DataRows4, DataRows5, corrMatrixComb3 = concatDF3.corr() corrMatrixComb3 = corrMatrixComb3.abs() corrMatrixComb3 = corrMatrixComb3.iloc[:,-len(uniqueTarget3):] - X3 = add_constant(DataRows3.dropna()) - VIF3 = pd.Series([variance_inflation_factor(X3.values, i) - for i in range(X3.shape[1])], - index=X3.columns) - VIF3 = VIF3.replace(np.nan, 0) - VIF3 = VIF3.replace(-np.inf, 1.7976931348623157e-308) - VIF3 = VIF3.replace(np.inf, 1.7976931348623157e+308) - VIF3 = VIF3.loc[[feature]] + DataRows3 = DataRows3.replace([np.inf, -np.inf], np.nan) + DataRows3 = DataRows3.fillna(0) + X3 = add_constant(DataRows3) + X3 = X3.replace([np.inf, -np.inf], np.nan) + X3 = X3.fillna(0) + if (flagInf == False): + VIF3 = pd.Series([variance_inflation_factor(X3.values, i) + for i in range(X3.shape[1])], + index=X3.columns) + VIF3 = VIF3.replace([np.inf, -np.inf], np.nan) + VIF3 = VIF3.fillna(0) + VIF3 = VIF3.loc[[feature]] + else: + VIF3 = pd.Series() if ((len(targetRows3Arr) > 2) and (flagInf == False)): MI3 = mutual_info_classif(DataRows3, targetRows3Arr, n_neighbors=3, random_state=RANDOM_SEED) MI3List = MI3.tolist() @@ -1335,14 +1366,20 @@ def NewComputationTransf(DataRows1, DataRows2, DataRows3, DataRows4, DataRows5, corrMatrixComb4 = concatDF4.corr() corrMatrixComb4 = corrMatrixComb4.abs() corrMatrixComb4 = corrMatrixComb4.iloc[:,-len(uniqueTarget4):] - X4 = add_constant(DataRows4.dropna()) - VIF4 = pd.Series([variance_inflation_factor(X4.values, i) - for i in range(X4.shape[1])], - index=X4.columns) - VIF4 = VIF4.replace(np.nan, 0) - VIF4 = VIF4.replace(-np.inf, 1.7976931348623157e-308) - VIF4 = VIF4.replace(np.inf, 1.7976931348623157e+308) - VIF4 = VIF4.loc[[feature]] + DataRows4 = DataRows4.replace([np.inf, -np.inf], np.nan) + DataRows4 = DataRows4.fillna(0) + X4 = add_constant(DataRows4) + X4 = X4.replace([np.inf, -np.inf], np.nan) + X4 = X4.fillna(0) + if (flagInf == False): + VIF4 = pd.Series([variance_inflation_factor(X4.values, i) + for i in range(X4.shape[1])], + index=X4.columns) + VIF4 = VIF4.replace([np.inf, -np.inf], np.nan) + VIF4 = VIF4.fillna(0) + VIF4 = VIF4.loc[[feature]] + else: + VIF4 = pd.Series() if ((len(targetRows4Arr) > 2) and (flagInf == False)): MI4 = mutual_info_classif(DataRows4, targetRows4Arr, n_neighbors=3, random_state=RANDOM_SEED) MI4List = MI4.tolist() @@ -1363,14 +1400,20 @@ def NewComputationTransf(DataRows1, DataRows2, DataRows3, DataRows4, DataRows5, corrMatrixComb5 = concatDF5.corr() corrMatrixComb5 = corrMatrixComb5.abs() corrMatrixComb5 = corrMatrixComb5.iloc[:,-len(uniqueTarget5):] - X5 = add_constant(DataRows5.dropna()) - VIF5 = pd.Series([variance_inflation_factor(X5.values, i) - for i in range(X5.shape[1])], - index=X5.columns) - VIF5 = VIF5.replace(np.nan, 0) - VIF5 = VIF5.replace(-np.inf, 1.7976931348623157e-308) - VIF5 = VIF5.replace(np.inf, 1.7976931348623157e+308) - VIF5 = VIF5.loc[[feature]] + DataRows5 = DataRows5.replace([np.inf, -np.inf], np.nan) + DataRows5 = DataRows5.fillna(0) + X5 = add_constant(DataRows5) + X5 = X5.replace([np.inf, -np.inf], np.nan) + X5 = X5.fillna(0) + if (flagInf == False): + VIF5 = pd.Series([variance_inflation_factor(X5.values, i) + for i in range(X5.shape[1])], + index=X5.columns) + VIF5 = VIF5.replace([np.inf, -np.inf], np.nan) + VIF5 = VIF5.fillna(0) + VIF5 = VIF5.loc[[feature]] + else: + VIF5 = pd.Series() if ((len(targetRows5Arr) > 2) and (flagInf == False)): MI5 = mutual_info_classif(DataRows5, targetRows5Arr, n_neighbors=3, random_state=RANDOM_SEED) MI5List = MI5.tolist() @@ -1565,13 +1608,16 @@ def Seperation(): corrMatrixComb1 = concatDF1.corr() corrMatrixComb1 = corrMatrixComb1.abs() corrMatrixComb1 = corrMatrixComb1.iloc[:,-len(uniqueTarget1):] - X1 = add_constant(DataRows1.dropna()) + DataRows1 = DataRows1.replace([np.inf, -np.inf], np.nan) + DataRows1 = DataRows1.fillna(0) + X1 = add_constant(DataRows1) + X1 = X1.replace([np.inf, -np.inf], np.nan) + X1 = X1.fillna(0) VIF1 = pd.Series([variance_inflation_factor(X1.values, i) for i in range(X1.shape[1])], index=X1.columns) - VIF1 = VIF1.replace(np.nan, 0) - VIF1 = VIF1.replace(-np.inf, 1.7976931348623157e-308) - VIF1 = VIF1.replace(np.inf, 1.7976931348623157e+308) + VIF1 = VIF1.replace([np.inf, -np.inf], np.nan) + VIF1 = VIF1.fillna(0) if (len(targetRows1Arr) > 2): MI1 = mutual_info_classif(DataRows1, targetRows1Arr, n_neighbors=3, random_state=RANDOM_SEED) MI1List = MI1.tolist() @@ -1591,13 +1637,16 @@ def Seperation(): corrMatrixComb2 = concatDF2.corr() corrMatrixComb2 = corrMatrixComb2.abs() corrMatrixComb2 = corrMatrixComb2.iloc[:,-len(uniqueTarget2):] - X2 = add_constant(DataRows2.dropna()) + DataRows2 = DataRows2.replace([np.inf, -np.inf], np.nan) + DataRows2 = DataRows2.fillna(0) + X2 = add_constant(DataRows2) + X2 = X2.replace([np.inf, -np.inf], np.nan) + X2 = X2.fillna(0) VIF2 = pd.Series([variance_inflation_factor(X2.values, i) for i in range(X2.shape[1])], index=X2.columns) - VIF2 = VIF2.replace(np.nan, 0) - VIF2 = VIF2.replace(-np.inf, 1.7976931348623157e-308) - VIF2 = VIF2.replace(np.inf, 1.7976931348623157e+308) + VIF2 = VIF2.replace([np.inf, -np.inf], np.nan) + VIF2 = VIF2.fillna(0) if (len(targetRows2Arr) > 2): MI2 = mutual_info_classif(DataRows2, targetRows2Arr, n_neighbors=3, random_state=RANDOM_SEED) MI2List = MI2.tolist() @@ -1617,13 +1666,16 @@ def Seperation(): corrMatrixComb3 = concatDF3.corr() corrMatrixComb3 = corrMatrixComb3.abs() corrMatrixComb3 = corrMatrixComb3.iloc[:,-len(uniqueTarget3):] - X3 = add_constant(DataRows3.dropna()) + DataRows3 = DataRows3.replace([np.inf, -np.inf], np.nan) + DataRows3 = DataRows3.fillna(0) + X3 = add_constant(DataRows3) + X3 = X3.replace([np.inf, -np.inf], np.nan) + X3 = X3.fillna(0) VIF3 = pd.Series([variance_inflation_factor(X3.values, i) for i in range(X3.shape[1])], index=X3.columns) - VIF3 = VIF3.replace(np.nan, 0) - VIF3 = VIF3.replace(-np.inf, 1.7976931348623157e-308) - VIF3 = VIF3.replace(np.inf, 1.7976931348623157e+308) + VIF3 = VIF3.replace([np.inf, -np.inf], np.nan) + VIF3 = VIF3.fillna(0) if (len(targetRows3Arr) > 2): MI3 = mutual_info_classif(DataRows3, targetRows3Arr, n_neighbors=3, random_state=RANDOM_SEED) MI3List = MI3.tolist() @@ -1643,13 +1695,16 @@ def Seperation(): corrMatrixComb4 = concatDF4.corr() corrMatrixComb4 = corrMatrixComb4.abs() corrMatrixComb4 = corrMatrixComb4.iloc[:,-len(uniqueTarget4):] - X4 = add_constant(DataRows4.dropna()) + DataRows4 = DataRows4.replace([np.inf, -np.inf], np.nan) + DataRows4 = DataRows4.fillna(0) + X4 = add_constant(DataRows4) + X4 = X4.replace([np.inf, -np.inf], np.nan) + X4 = X4.fillna(0) VIF4 = pd.Series([variance_inflation_factor(X4.values, i) for i in range(X4.shape[1])], index=X4.columns) - VIF4 = VIF4.replace(np.nan, 0) - VIF4 = VIF4.replace(-np.inf, 1.7976931348623157e-308) - VIF4 = VIF4.replace(np.inf, 1.7976931348623157e+308) + VIF4 = VIF4.replace([np.inf, -np.inf], np.nan) + VIF4 = VIF4.fillna(0) if (len(targetRows4Arr) > 2): MI4 = mutual_info_classif(DataRows4, targetRows4Arr, n_neighbors=3, random_state=RANDOM_SEED) MI4List = MI4.tolist() @@ -1669,13 +1724,16 @@ def Seperation(): corrMatrixComb5 = concatDF5.corr() corrMatrixComb5 = corrMatrixComb5.abs() corrMatrixComb5 = corrMatrixComb5.iloc[:,-len(uniqueTarget5):] - X5 = add_constant(DataRows5.dropna()) + DataRows5 = DataRows5.replace([np.inf, -np.inf], np.nan) + DataRows5 = DataRows5.fillna(0) + X5 = add_constant(DataRows5) + X5 = X5.replace([np.inf, -np.inf], np.nan) + X5 = X5.fillna(0) VIF5 = pd.Series([variance_inflation_factor(X5.values, i) for i in range(X5.shape[1])], index=X5.columns) - VIF5 = VIF5.replace(np.nan, 0) - VIF5 = VIF5.replace(-np.inf, 1.7976931348623157e-308) - VIF5 = VIF5.replace(np.inf, 1.7976931348623157e+308) + VIF5 = VIF5.replace([np.inf, -np.inf], np.nan) + VIF5 = VIF5.fillna(0) if (len(targetRows5Arr) > 2): MI5 = mutual_info_classif(DataRows5, targetRows5Arr, n_neighbors=3, random_state=RANDOM_SEED) MI5List = MI5.tolist()